92494 Purchasing Power Parities and the Real Size of World Economies Purchasing Power Parities and the Real Size of World Economies A COMPREHENSIVE REPORT OF THE 2011 INTERNATIONAL COMPARISON PROGRAM © 2015 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved 1 2 3 4 17 16 15 14 This work is a product of the staff of The World Bank with external contributions. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved. Rights and Permissions This work is available under the Creative Commons Attribution 3.0 IGO license (CC BY 3.0 IGO) http://creativecommons.org/licenses/by/3.0/igo. Under the Creative Commons Attribution license, you are free to copy, distribute, transmit, and adapt this work, including for commercial purposes, under the following conditions: Attribution—Please cite the work as follows: World Bank. 2015. Purchasing Power Parities and the Real Size of World Economies: A Comprehensive Report of the 2011 International Comparison Program. Washington, DC: World Bank. doi:10.1596/978-1-4648-0329-1. License: Creative Commons Attribution CC BY 3.0 IGO Translations—If you create a translation of this work, please add the following disclaimer along with the attribution: This translation was not created by The World Bank and should not be considered an official World Bank translation. The World Bank shall not be liable for any content or error in this translation. Adaptations—If you create an adaptation of this work, please add the following disclaimer along with the attribution: This is an adaptation of an original work by The World Bank. Views and opinions expressed in the adaptation are the sole responsibility of the author or authors and are not endorsed by The World Bank. Third-party content—The World Bank does not necessarily own each component of the content contained within the work. The World Bank therefore does not warrant that the use of any third-party-owned individual component or part contained in the work will not infringe on the rights of those third parties. The risk of claims resulting from such infringement rests solely with you. If you wish to re-use a component of the work, it is your responsibility to determine whether permission is needed for that re-use and to obtain permission from the copyright owner. Examples of components can include, but are not limited to, tables, figures, or images. All queries on rights and licenses should be addressed to the Publishing and Knowledge Division, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@worldbank.org. ISBN (paper): 978-1-4648-0329-1 ISBN (electronic): 978-1-4648-0330-7 DOI: 10.1596/978-1-4648-0329-1 Cover design: Jomo Tariku/World Bank Group. Library of Congress Cataloging-in-Publication Data has been requested. Contents Foreword................................................................................................................................................... xi Acknowledgments ........................................................................................................................... xiii Abbreviations ..................................................................................................................................... xvii Overview.....................................................................................1 Governance of ICP 2011 ......................................................................................................................... 2 Regional and Country Coverage ............................................................................................................ 2 Methodology and Innovations ................................................................................................................ 3 ICP 2011 versus ICP 2005 ....................................................................................................................... 5 The ICP 2011 Results: An Overview....................................................................................................... 5 Organization of This Report .................................................................................................................... 6 Chapter 1 Background ................................................................................9 Organization of ICP 2011 ...................................................................................................................... 10 The ICP Approach to GDP Comparisons............................................................................................... 11 Exchange Rates..................................................................................................................................... 12 Purchasing Power Parities .................................................................................................................... 13 Price Level Indexes ............................................................................................................................... 13 Real Expenditures ................................................................................................................................. 14 Actual Individual Consumption............................................................................................................. 14 Uses of PPPs and Real Expenditures ................................................................................................... 15 Chapter 2 Presentation and Analysis of Results ..................................17 Presentation of Results ........................................................................................................................ 17 Analysis of Results ............................................................................................................................. 152 Reliability and Limitations of PPPs and Real Expenditures............................................................... 167 Differences between the 2005 and 2011 Comparisons .................................................................... 170 Comparing 2011 PPPs Extrapolated from ICP 2005 and ICP 2011 Benchmark PPPs ........................ 172 Chapter 3 Data Requirements ...............................................................175 Conceptual Framework ....................................................................................................................... 175 Surveys and Data Collection .............................................................................................................. 182 Data Validation ................................................................................................................................... 193 v Chapter 4 Methodologies Used to Calculate Regional and Global PPPs ............................................................................203 Household Consumption..................................................................................................................... 204 Comparison-Resistant Components ................................................................................................... 206 Reference PPPs ................................................................................................................................... 210 Aggregating Linked Basic Heading PPPs to GDP............................................................................... 211 Special Situations ............................................................................................................................... 211 Imputing PPPs for Nonparticipating Economies ................................................................................ 212 Appendix A History of the International Comparison Program (ICP)..... 215 Appendix B Governance of ICP 2011 .......................................................219 Appendix C Eurostat-OECD PPP Programme ........................................223 Eurostat-OECD Comparisons .............................................................................................................. 223 Organization of the 2011 Comparison ............................................................................................... 224 Data Collection for the 2011 Comparison.......................................................................................... 225 Calculation and Aggregation of PPPS................................................................................................. 227 Additional Information ........................................................................................................................ 227 Appendix D ICP Expenditure Classification ...........................................229 Deriving Actual Individual Consumption ............................................................................................ 229 Facilitating the Input Price Approach ................................................................................................ 230 Adjusting the Household Expenditure to the National Concept ....................................................... 231 Appendix E National Accounts: Estimation, Compliance, and Exhaustiveness.......................................................................241 Estimation ........................................................................................................................................... 241 Compliance and Exhaustiveness ........................................................................................................ 244 Appendix F Changes in Methodology between the 2005 and 2011 ICP Rounds .............................................................................251 Household Consumption: Product Selection and Important Products .............................................. 252 Housing Rents ..................................................................................................................................... 253 Government Compensation ................................................................................................................ 254 Construction ........................................................................................................................................ 254 Estimating Within-Region PPPS.......................................................................................................... 256 Linking the Regions ............................................................................................................................ 257 Summary ............................................................................................................................................. 258 Appendix G Reference PPPs Used in ICP 2011 .......................................259 Appendix H Updated ICP 2005 Results ....................................................263 Appendix I Comparison of ICP 2011 Results with 2011 Results Extrapolated from ICP 2005 ..................................275 Appendix J ICP 2011 Data Access and Archiving Policy .....................283 Context ............................................................................................................................................... 283 Data Access Objectives ...................................................................................................................... 283 Guiding Principles ............................................................................................................................... 284 Procedures for Data Archiving ........................................................................................................... 285 Procedures for Data Access ............................................................................................................... 285 vi Contents Appendix K ICP Revision Policy ...............................................................287 Triggers for Revising ICP Indicators ................................................................................................... 288 Guidelines for Revising ICP Indicators ............................................................................................... 288 Timing and Communication of Revisions ........................................................................................... 289 Glossary ........................................................................................................ 291 References .................................................................................................... 305 Boxes 1.1 Using Exchange Rates and PPPs to Convert to a Common Currency ................ 12 2.1 Analytical Categories: Tables 2.2–2.11 and Supplementary Tables 2.12 and 2.13............................................................................................. 19 3.1 Standardized Price Ratios ................................................................................... 197 E.1 MORES Worksheets, ICP 2011 .......................................................................... 242 E.2 ICP National Accounts Quality Assurance Questionnaire, ICP 2011 ................ 245 E.3 Types of Nonexhaustiveness Identified in GDP Exhaustiveness Questionnaire, ICP 2011 .................................................................................... 247 Figures 2.1 Percentage of PPP-Based and Exchange Rate–Based GDP and Population by Income Group, ICP 2011 and ICP 2005 ...................................................... 153 2.2 PPP-Based and Exchange Rate–Based GDP Regional Shares (World = 100), ICP 2011 .................................................................................... 153 2.3 Index of Regional Average Real Expenditures Per Capita (World = 100) on Major Aggregates (PPP-Based), ICP 2011 .............................156 2.4 Real GDP Per Capita and Shares of Global Population, ICP 2011 .................... 158 2.5 GDP Price Level Index versus GDP Per Capita (and Size of GDP Expenditures), ICP 2011 ........................................................................... 160 2.6 GDP Price Level Index versus Expenditure Per Capita with Trend Lines, Eurostat-OECD and Non–Eurostat-OECD Economies, ICP 2011 ..................... 161 2.7 Regional Average Price Level Indexes by GDP and Major Aggregates, ICP 2011 ......................................................................................... 162 2.8 Regional Average Price Level Indexes (World = 100) for GDP and 15 Aggregates, ICP 2011 ......................................................................................... 164 2.9 Coefficients of Variation (CVs): GDP Per Capita Index and Price Level Indexes (PLIs) for GDP and Major Aggregates by Region, ICP 2011 ................ 165 2.10 Lorenz Curve for ICP 2011 and ICP 2005 GDP Per Capita Distribution ........... 167 Tables O.1 Number of Participating Economies, by ICP Region, ICP 2011 ............................ 3 2.1 Summary Results and Reference Data, ICP 2011................................................ 24 Contents vii 2.2 Nominal Expenditures in National Currency Units, ICP 2011............................ 30 2.3 Shares of Nominal Expenditures (GDP = 100), ICP 2011 ................................... 42 2.4 Purchasing Power Parities (U.S. Dollar = 1.00), ICP 2011 .................................. 54 2.5 Real Expenditures in U.S. Dollars, ICP 2011 ....................................................... 66 2.6 Shares of World Real Expenditures (World = 100), ICP 2011 ............................ 78 2.7 Real Expenditures Per Capita in U.S. Dollars, ICP 2011 ..................................... 90 2.8 Indexes of Real Expenditures Per Capita (World = 100), ICP 2011.................. 102 2.9 Price Level Indexes (World = 100), ICP 2011 ................................................... 114 2.10 Nominal Expenditures in U.S. Dollars, ICP 2011 .............................................. 126 2.11 Nominal Expenditures Per Capita in U.S. Dollars, ICP 2011 ............................ 138 2.12 Main Results and Reference Data, Pacific Islands, ICP 2011 ............................ 150 2.13 Estimated Results and Reference Data, Nonbenchmark Economies, ICP 2011......................................................................................................... 151 2.14 Twelve Largest Economies by Share of World GDP, ICP 2011 .......................... 154 2.15 Percentage of GDP to U.S. GDP (PPP-Based) for 12 Largest Economies, ICP 2011 and ICP 2005 ...................................................................................... 154 2.16 Regional Shares of World GDP and Major Aggregates, ICP 2011 ..................... 155 2.17 Shares of World Expenditure on Construction and Machinery and Equipment of Economies with Largest Construction Shares, ICP 2011 ........... 155 2.18 PPP-Based Shares of World GDP and Per Capita Measures: High-, Middle-, and Low-Income Economies, ICP 2011 .................................. 156 2.19 PPP-Based and Exchange Rate–Based GDP Per Capita Expenditures for the 10 Economies with the Largest and Smallest Values and Ratios Relative to the United States, ICP 2011............................................................. 157 2.20 PPP-Based and Exchange Rate–Based Actual Individual Consumption (AIC) Per Capita and Ratios Relative to the United States, ICP 2011 ............................ 159 2.21 Economies with Highest and Lowest Price Level Indexes (PLIs), ICP 2011 .......161 2.22 Population-Weighted Gini Coefficient for ICP Economies, ICP 2011 and ICP 2005 ...................................................................................................... 166 3.1 Number of Priced Global Core Products per Region and Survey, ICP 2011 ..... 183 3.2 Machinery and Equipment Core Product List, ICP 2011 .................................. 191 D.1 Structure of the ICP Expenditure Classification, ICP 2011 ............................... 230 D.2 Expenditure Classification, ICP 2011 ................................................................. 231 E.1 Economic Activities, Expenditure Categories, and Income Transactions Identified in Exhaustiveness Questionnaire, ICP 2011 ..................................... 248 G.1 Reference PPPs, ICP 2011 .................................................................................. 260 viii Contents H.1 Revised ICP 2005 Summary Results: GDP......................................................... 264 H.2 Analytical ICP 2005 Summary Results Using the Country Aggregation with Redistribution (CAR) Method: GDP ..................................... 269 I.1 Comparison of ICP 2011 Global Results with Data in World Development Indicators (Extrapolation from ICP 2005) ......................................................... 276 Contents ix Foreword The International Comparison Program (ICP) is under the overall auspices of the United Nations a worldwide statistical initiative—the largest in Statistical Commission, the program would not geographical scope, in implementation time have been such a success without the invaluable frame, and in institutional partnership. It esti- theoretical, conceptual, and methodological mates purchasing power parities (PPPs) for use advice of the ICP Technical Advisory Group of as currency converters to compare the size and renowned experts. price levels of economies around the world. The Thanks to the relentless efforts of all those par- previous round of the program, for reference ticipating in this federated governance structure, year 2005, covered 146 economies. The 2011 the work of ICP 2011 was carried out according to ICP round covered 199 economies from eight a schedule that, by and large, has remained regions, seven of them geographical: Africa, Asia unchanged since the inception of the round in the and the Pacific, Commonwealth of Independent fourth quarter of 2009—an achievement in itself States, Latin America, the Caribbean, Western in view of the complexity of such an undertaking. Asia, and the Pacific Islands. The eighth region All this testifies to the effectiveness of the system comprised the economies participating in the that was rolled out to manage the program and regular PPP program managed by the Statistical implement related statistical operations. Indeed, Office of the European Communities (Eurostat) an economy cannot by itself produce a PPP with and the Organisation for Economic Co-operation other economies. Likewise, a region cannot by and Development (OECD). itself generate interregional PPPs with other On behalf of the ICP Executive Board and the regions. Therefore, there is no other statistical pro- World Bank, we would like to thank all those who gram that requires as much cooperation and trust contributed to the success of the 2011 ICP program: across economies and between regions as the ICP. the national coordinating agencies that collected Methodological improvements covering four the necessary data in each economy; the regional major areas were introduced in the 2011 round coordinating agencies that supported country of the ICP, leveraging the very strong base pro- activities, compiled the results, and produced vided by ICP 2005. First, the survey frame- regional estimates—the African Development works were further aligned with the ICP Bank, Asian Development Bank, Interstate conceptual framework to ensure that related Statistical Committee of the Commonwealth of data collection would yield the most reliable Independent States, United Nations Economic average prices possible, and instruments for Commission for Latin America and the Caribbean, price surveys were enhanced accordingly. United Nations Economic and Social Commission Second, an ICP national accounts framework for Western Asia, Australian Bureau of Statistics, was developed to ensure that expenditure val- OECD, and Eurostat; and the ICP Global Office, ues were compiled in compliance with the which coordinated and managed the work at the System of National Accounts, while also ensur- global level. The office is hosted by the Development ing consistency with the prices collected and Data Group at the World Bank Group. generating the relevant metadata documenta- Although the responsibility for oversight tion. Third, the Ring approach used in 2005 to rested with the ICP Executive Board established link the regions and the Eurostat-OECD PPPs to xi the global results was changed to a global core and they are explicitly described in this report. list approach in which all participating econo- Because of the many important changes in eco- mies were asked to include a common set of nomic and price structures since 2005 and a items in the regional list of products they sur- number of methodological improvements, users veyed. Fourth, more broadly, a research agenda of the data are urged to be cautious when com- was established and then implemented by the paring the ICP 2011 results with those for Technical Advisory Group and other experts to ICP 2005. advise the Global Office on the price survey, We believe the ICP 2011 results represent the expenditure compilation, data validation, and most comprehensive price data and gross domes- computation processes to be applied at the tic product (GDP) expenditure values, using the country, regional, and global levels. best methods that have ever been developed. In other developments, all major knowledge We are also very pleased to see that ICP-related items related to the most recent ICP rounds activities have played a fruitful role in the were consolidated in a book entitled Measuring regions, serving as capacity-building platforms the Real Size of the World Economy: The Framework, in the areas of prices and national accounts Methodology, and Results of the International statistics. Comparison Program (ICP) (World Bank 2013). We trust that users of the ICP 2011 results The items are also available on the ICP website will find this report useful and that those results (http://icp.worldbank.org), which was will form a crucial information base for research revamped to better serve as a repository of ICP in comparative analysis and policy making. We knowledge resources and data. Meanwhile, a hope that in the future, more regular data col- comprehensive ICP quality assurance frame- lection and compilation will support a more work was developed to ensure that major ICP frequent PPP exercise at the global level. principles were being met at the country, Once again, we wish to express our sincere regional, and global levels. The aim of the thanks to all those involved in this very gratify- framework was to introduce rigor, structure, ing undertaking. and common criteria for assessment of the quality of the input data and the results pro- Martine Durand duced. As part of the quality and transparency OECD Chief Statistician objective, at the global level parallel and inde- Chair, ICP Executive Board pendent processes were established for the vali- dation of input data, computation of PPPs, and Haishan Fu review of the final results. Finally, the limita- Director tions of the data and methods were identified, Development Data Group, World Bank xii Foreword Acknowledgments The International Comparison Program (ICP) is whose directors during this ICP round were the largest worldwide statistical operation. The Shaida Badiee and then Haishan Fu and whose 2011 round of the ICP was a complex exercise, managers were Misha Belkindas and then Grant conceptually and organizationally, and the James Cameron. The World Bank equipped the Global Office is pleased that, thanks to the strong Global Office with all the necessary workplace engagement of the 199 participating economies resources and provided support for various in the entire process, we succeeded in bringing it organs of the program’s governance structure. to fruition. As the decision-making and strategic body of The 2011 ICP round saw changes on several ICP governance, the ICP 2011 Executive Board fronts by leveraging the successful implementa- provided leadership and ensured strict adher- tion of the 2005 round: the scope of the exercise ence to the program’s objectives and strategic was broadened; quality assessment processes lines. Its successive chairs are hereby thanked were streamlined; and statistical capacity- for their leadership: Oystein Olsen, Enrico building activities were carried out with a spe- Giovannini, and Martine Durand. Thanks are cific focus on price statistics and implementation also extended to the institutions represented of the System of National Accounts. In addition, on the board: African Development Bank, several improvements were introduced: prepa- Asian Development Bank, Australian Bureau ration and implementation of an ICP data qual- of Statistics, Brazilian Institute of Geography ity assurance framework; development of a and Statistics, China’s National Bureau of national accounts framework for the ICP that Statistics, Interstate Statistical Committee of the was implemented using specifically defined Commonwealth of Independent States, Eurostat, guidelines for activities; development of a global Statistics Department of the IMF, India’s Ministry core list of goods and services that were priced of Statistics and Programme Implementation, by all the participating economies in addition to France’s National Institute for Statistics and their regional lists; introduction of a new method Economic Studies, Italy’s National Institute for for construction and civil engineering; and Statistics, Mexico’s National Institute for Statistics improvements in the approach to computing and Geography, Organisation for Economic global purchasing power parities (PPPs). Co-operation and Development (OECD), Russian All these achievements were made possible by Federation Federal State Statistics Service, Saudi the financial support of donors who contributed Arabia Central Department of Statistics and to specifically established trust funds. Special Information, Senegal National Agency for thanks go to the United Kingdom’s Department Statistics and Demography, Statistics Canada, for International Development (DFID), Australian Statistics Norway, Statistics South Africa, Uganda Agency for International Development (Aus- Bureau of Statistics, United Nations Economic AID), International Monetary Fund (IMF), Commission for Latin America and the Caribbean, Islamic Development Bank, Norway’s Ministry of United Nations Economic and Social Commission Foreign Affairs, and the World Bank. for Western Asia, United Nations Statistics The ICP Global Office is hosted by the World Division, U.S. Office of Management and Budget, Bank’s Development Data Group (DECDG), and the World Bank’s Development Data Group. xiii The Technical Advisory Group deserves special the ICP, the cornerstone of the program is the acknowledgment. Under the chairmanship of national coordinating agencies, which are Erwin Diewert and then the co-chairmanship of responsible for the bulk of ICP activities, from Paul McCarthy and Frederic Vogel, technical price data collection to the compilation of the issues linked to the conceptual integrity and national accounts expenditure data. The 2011 methodological adequacy of the program were participating economies demonstrated com- addressed by the group’s experts: Luigi Biggeri, plete commitment and dedication to the ICP. Angus Deaton, Yuri Dikhanov, Qiu Dong, Louis We truly owe them utmost respect and appre- Marc Ducharme, Alan Heston, Robert Hill, Youri ciation for the amazing job they did in carrying Ivanov, Francette Koechlin, Paulus Konijn, Vasily out the rigorous ICP activities over the last few Kouznetsov, Tom Andersen Langer, Julian May, years. Prasada Rao, Sergey Sergeev, Mick Silver, Jim The Global Office also recognizes the technical Thomas, Marcel Timmer, and Kim Zieschang. The advice provided by various experts, including the Technical Advisory Group was assisted by various Academy for Educational Development, Roger experts on some topics, including Derek Blades, Akers, Eric Peter Bruggeman, Richard Dibley, Richard Dibley, Jim Meikle, and David Roberts. Gylliane Gervais, Simon Humphries, Robert The results of ICP 2011 were calculated by the Inklaar, Albert Keidel, Troy Michael Martin, group of experts forming the PPP Computation Joseph McCormack, Jim Meikle, William Vigil Task Force: Bettina Aten, Yuri Dikhanov, Alan Oliver, Ehraz Refayet, Gary Reid, Michael Scholz, Heston, Robert Hill, Francette Koechlin, Paulus Ruben Suarez, Michael Thomas, and Dennis Konijn, and Sergey Sergeev. The results under- Trewin. Nicole El-Hajj, Rouba Romanos, and went the quality review of the experts forming Rachel Wilkins provided the ICP with valuable the Results Review Group: Angus Deaton, Erwin translation services. The consulting firms TATA Diewert, Alan Heston, Paul McCarthy, Prasada and Prognoz helped to develop the software tools Rao, and Frederic Vogel. that supported implementation of the program. Our achievement was made possible by the This report was drafted by the Global Office relentless work of the regional coordinators: and David Roberts with input from Paul Oliver Chinganya (Africa), Chellam Palanyandy McCarthy, Prasada Rao, and Frederic Vogel. It (Asia and the Pacific), Andrey Kosarev was edited by Sabra Bissette Ledent. The cover (Commonwealth of Independent States), David was designed by Jomo Tariku. Roberts and Derek Blades (Georgia-Armenia The Global Office team responsible for the bilateral), Giovanni Savio (Latin America and day-to-day work was Morgan Brannon, Yuri the Caribbean), Athol Maritz (Pacific Islands), Dikhanov, Biokou Mathieu Djayeola, Federico and Majed Skaini (Western Asia), as well as the Escaler, Christelle Signo Kouame, Marko Olavi great cooperation of Francette Koechlin and Rissanen, Virginia Romand, and Mizuki Paulus Konijn, who were leading the Eurostat- Yamanaka. Recognition for their efforts is also OECD PPP program. This testifies to the effective given to former Global Office members Miglena partnership between the Global Office and the Abels, Olga Akcadag, Claude Djekadom regional agencies that assumed coordination of Walendom, Imededdine Jerbi, Min Ji Lee, the ICP in their various regions: African Kyung Sam Min, Inyoung Song, Seong Heon Development Bank, Asian Development Bank, Song, and Estela Zamora. Several colleagues Australian Bureau of Statistics, Interstate from other DECDG units provided valuable sup- Statistical Committee of the Commonwealth of port to the Global Office: Awatif H. Abuzeid, Independent States, United Nations Economic Azita Amjadi, Colleen Burke, Lisa Burke, Ying Commission for Latin America and the Chi, Shelley Fu, Omar Hadi, Hulda Hunter, Caribbean, and United Nations Economic and Elysee Kiti, Vilas Mandlekar, Maurice Nsabimana, Social Commission for Western Asia, as well as Parastoo Oloumi, Beatriz Prieto-Oramas, Eurostat and OECD. William Prince, and Premi Rathan Raj. I was Although the Global Office and the regional privileged to lead the Global Office with the out- coordinators play a crucial role in implementing standing collaboration of Nada Hamadeh, the xiv Acknowledgments current ICP team leader, who acted as de facto played by the national implementing agencies deputy global manager. in all the 199 participating economies. We all As a team, we are grateful to all the dedi- share the credit for the production of this cated experts and international and regional unique public good. institutions that contributed their knowledge, expertise, time, and resources to this daunting Michel Mouyelo-Katoula effort. We particularly recognize the major role ICP 2011 Global Manager Acknowledgments xv Abbreviations AIC actual individual consumption CAR country aggregation with redistribution (procedure) CEP consumption expenditure of the population CIS Commonwealth of Independent States COFOG Classification of the Function of Government COICOP Classification of Individual Consumption according to Purpose COMECON Council for Mutual Economic Assistance CPD country product dummy (method) CPD-W country product dummy-weighted (method) CPRD country product representative dummy (method) Eurostat Statistical Office of the European Union FISIM financial intermediation services indirectly measured f.o.b. free on board GDP gross domestic product GEKS Gini-Èltetö-Köves-Szulc (method) GNI gross national income ICP International Comparison Program (Project prior to 1989) ILO International Labour Organization IMF International Monetary Fund MORES Model Report on Expenditure Statistics NBS National Bureau of Statistics (China) NCA national coordinating agency n.e.c. not elsewhere classified NPISH nonprofit institution serving households OECD Organisation for Economic Co-operation and Development PISA Programme for International Student Assessment PLI price level index PPP purchasing power parity RCA regional coordinating agency SAR special administrative region SNA System of National Accounts SPD structured product description TAG Technical Advisory Group (ICP) TFP total factor productivity UN United Nations UNESCO United Nations Educational, Scientific, and Cultural Organization xvii UNSC United Nations Statistical Commission UNSD United Nations Statistics Division UNSO United Nations Statistics Office VAT value added tax XR exchange rate All dollar amounts are U.S. dollars unless otherwise indicated. xviii Abbreviations Overview The International Comparison Program (ICP) regional and global inequality in incomes and is a large and highly complex worldwide statis- consumption; and estimates of the incidence of tical program conducted under the charter of absolute poverty using World Bank–developed the United Nations Statistical Commission yardsticks such as the US$1 a day and $2 a day (UNSC). The ICP is designed to provide glob- poverty lines.1 ally comparable economic aggregates in ICP 2011, the latest round of the ICP, is the national accounts that can be used by individ- eighth phase of the program. The first phase in ual researchers, analysts, and policy makers at 1970 saw very limited program coverage, only the national and international levels and by 10 economies. By contrast, the 2011 round has international organizations such as the achieved, for the first time, truly global cover- European Union, International Monetary age by including 199 economies from all regions Fund, Organisation for Economic Co-operation of the world. The seven geographic regions cov- and Development (OECD), United Nations, ered by ICP 2011 were Africa, Asia and the and World Bank. Over its lifetime, the ICP has Pacific, Commonwealth of Independent States become the principal source of data on the (CIS), Latin America, the Caribbean, Western purchasing power parities (PPPs) of currencies, Asia, and the Pacific Islands. The eighth region measures of real per capita income, and mea- comprised the economies that were participat- sures of real gross domestic product (GDP) and ing in the PPP program run by Eurostat, the its main components from the expenditure statistical arm of the European Union, and the side, including private consumption, govern- OECD. This comprehensive report on ICP 2011 ment expenditures, and gross fixed capital provides readers with details of the conceptual formation. Indeed, since its inception in 1970, framework and the methodology employed by successive rounds of the ICP have produced the ICP, along with detailed results of the 2011 valuable data for international economic anal- round and a brief analysis of those results. This yses of economic growth and the catch-up and overview highlights the distinguishing features convergence of incomes among nations; pro- of ICP 2011 that make it a significant improve- ductivity levels and trends; analyses of system- ment over ICP 2005. atic patterns in national price levels and trends; construction of the Human Development 1 All dollar amounts in this report are U.S. dollars unless otherwise Index by the United Nations; measures of indicated. 1 GOVERNANCE OF ICP 2011 hosted by the World Bank. The Global Office was responsible for implementing the work pro- The governance structure of ICP 2011 was gram of the ICP. The preparation of regular designed to ensure the delivery of accurate, reports for the Executive Board and the UNSC reliable, and timely estimates of the PPPs of was also entrusted to the Global Office. It was currencies and real GDP and its components. responsible for compiling the global core list of At the apex of the structure was the UNSC, products for household consumption, housing, which provided overall supervision, ensuring government compensation, machinery and that the ICP strictly adhered to accepted guid- equipment, and construction. The Global Office ing principles for the production of official sta- was also responsible for linking regional com- tistics and international standards for national parisons in order to provide global comparisons accounts data. At the next level, the Executive of PPPs and real incomes, preparing and dis- Board, composed of internationally renowned seminating the global results, and publishing the chief statisticians, provided the ICP with lead- ICP 2011 reports. ership and played an important role in setting The Global Office was assisted by the Technical the strategic direction and ensuring progress in Advisory Group, PPP Computation Task Force, and attainment of the various milestones set Validation Expert Group, and Results Review Group. for the program. Significantly, a major innovation of ICP 2011 The governance and implementation of ICP was introduction of the PPP Computation Task 2011 were characterized by a strong bottom-up Force. The main purpose of the task force was to approach in which the participating economies ensure the accuracy of the ICP results and to were encouraged to actively participate in the guarantee their reproducibility. The task force program and assume ownership of the data and was composed of four computational experts, the final results. At the country level, the each of whom calculated the global results, national coordinating agencies and the national using his or her preferred software, to ensure coordinators assumed responsibility for the convergence of the results in full accordance collection and validation of the information with the recommendations of the Technical requested for analysis and the transmittal of Advisory Group. that information to the respective regional coordi- nating agencies. The activities of the economies in any given region were coordinated by the regional coordinating agencies, and the regional REGIONAL AND COUNTRY COVERAGE coordinators were responsible for the development ICP 2011 achieved the first truly global coverage of product lists, coordination of data collection, in the history of the ICP. Building on the impres- and validation within the region. The regional sive participation of 146 economies in ICP 2005, coordinating agencies were responsible for com- the 2011 round covered 199 economies, repre- piling and disseminating the PPPs and real senting more than 90 percent of the world’s expenditures for the respective regions. Those economies. The 199 economies account for agencies for the seven ICP 2011 regions were the roughly 97 percent of the world’s population African Development Bank, Asian Development and some 99 percent of the world nominal GDP Bank, Interstate Statistical Committee of the (in U.S. dollars using exchange rates). Table O.1 Commonwealth of Independent States, United shows the distribution of the economies cov- Nations Economic Commission for Latin ered, by region. America and the Caribbean, United Nations In addition to this impressive coverage, a Economic and Social Commission for Western number of features distinguish this ICP round Asia, and Australian Bureau of Statistics, which from the previous rounds: assumed responsibility for the Pacific Islands economies. The activities of the eighth region • For the first time in the history of the ICP, were organized by Eurostat and the OECD. China fully participated in ICP 2011, follow- The overall coordination of ICP 2011 at the ing all the prescribed procedures and methods. global level was entrusted to the Global Office, In ICP 2005, China provided price data 2 Purchasing Power Parities and the Real Size of World Economies Table O.1 Number of Participating Economies, by Because of the global coverage of ICP 2011, ICP Region, ICP 2011 there was little need for the extrapolation of PPPs and real incomes for nonparticipating Africa 50 economies, as undertaken in the earlier ICP Asia and the Pacific 23 rounds. However, the extrapolated results for Commonwealth of Independent States 9 the few nonparticipating economies are pre- Eurostat-OECD 47 sented in this report. Latin America 17 Caribbean 22 Western Asia 12 METHODOLOGY AND INNOVATIONS Pacific Islands 21 Singletonsa 2 The ICP is a complex international statistical project, and its methodology has evolved over Total (less four dual participantsb) 199 several decades. Challenging measurement and Source: ICP, http://icp.worldbank.org/. a. Georgia and the Islamic Republic of Iran. index number problems have been encoun- b. The Arab Republic of Egypt, Fiji, the Russian Federation, and Sudan. tered in implementation of the ICP. The ICP 2005 methodological approach represented a major step forward from the less satisfactory collected only from 11 cities or provinces. round in 1993. Along with improved gover- By contrast, for ICP 2011 China conducted nance, considerable progress was made in nationwide surveys covering both rural and establishing procedures for price surveys; data urban outlets in all provinces of the country. editing and validation; and methods for dealing • India and Indonesia, the two other populous with comparison-resistant sectors such as hous- economies in the Asia and the Pacific region, ing, the government expenditure on health and also achieved coverage of both rural and education, machinery and equipment, and urban areas in their collection of prices for construction. In ICP 2005, the statistical meth- consumption goods and services. odology for linking was based on data collected for a set of Ring countries and on the estimation • The Latin America region consisted of of linking factors to link regional comparisons 17 economies in ICP 2011 in contrast to only in order to yield global comparisons. 10 economies in ICP 2005. Learning from the invaluable experience • The Caribbean region with its participation gained through implementation of ICP 2005, the of 22 economies is a special feature of ICP Technical Advisory Group recommended 2011. improved procedures in a number of areas for ICP 2011. As a result of these improvements and • Another achievement of ICP 2011 is its inclu- methodological innovations, ICP 2011 was sig- sion of 21 Pacific Island economies, even nificantly better than its 2005 predecessor. A few though their participation was limited to of these methodological innovations follow: individual household consumption. The par- ticipation of these island economies was • Coverage of rural and urban outlets. Because facilitated by the coordination and support of the importance of achieving national of the Australian Bureau of Statistics. coverage for price surveys, particular care Participation in the ICP has helped these was taken by the large economies to ensure island economies improve the coverage and adequate coverage of rural and urban reliability of their price statistics and national outlets when collecting the prices of indi- accounts. Although this aspect of statistical vidual household consumption items. capacity building is amply demonstrated by Efforts were made to reduce urban bias, the benefits received by the Pacific Island thereby leading to reliable national annual economies, their limited participation in ICP average prices for use in the computation of 2011 ruled out the inclusion of their results PPPs both at the basic heading level and for in the main tables in this report. higher-level aggregates. Overview 3 • National accounts data. Recognizing the impor- wages and salaries received for specific occu- tance of obtaining reliable national accounts pational categories across economies in a data, the regional coordinating agencies con- given region, and across regions, ICP 2011 ducted special workshops focusing on implemented productivity adjustments for all national accounts statistics and their valida- of the participating economies in linking the tion. The Global Office provided the partici- regions (in ICP 2005 only three regions— pating economies with manuals for the Africa, Asia and the Pacific, and Western collection and validation of national accounts Asia—implemented productivity adjustments). data. As a result, the weights used in aggre- The resulting parities for government com- gating price data in ICP 2011 were more reli- pensation were thus more reliable than those able than in the earlier rounds. used in ICP 2005. • Use of importance indicators. In view of the • Procedures for global linking. The ex post assess- competing requirements of comparability and ment of ICP 2005 revealed several weak- representativity in the prices of goods and ser- nesses in the linking procedures. The reliance vices in the participating economies, the on a set of 18 Ring countries for linking Technical Advisory Group recommended use meant that the quality of the linking factors of an importance indicator and 3:1 weights and global results critically depended on the for products considered important in the esti- quality of the price data supplied by these mation of PPPs at the basic heading level. Ring countries. In addition, the product list used in the 2005 ICP Ring comparisons was • Data editing and validation. In addition to the found to contain numerous items that were standard methods of validation based on the not representative in a number of regions, Quaranta and Dikhanov tables, a new method including Africa and Asia and the Pacific. of validation was developed and implemented. Finally, the methodology for linking at the This method compares observed price move- higher levels of aggregation was found to be ments in the participating economies, mea- deficient in that it was not invariant to the sured by domestic consumer price indexes choice of the reference or numéraire country. and deflators, with a measure of price change Consequently, major innovations were intro- over the period 2005 to 2011 implicit in the duced to the linking procedures for ICP 2011: ICP price data provided by the participating economies over these two benchmarks. This – The practice of using a small set of selected method was used in the Asia and the Pacific Ring countries was discontinued and region in identifying sources of major errors replaced by the new approach in which and deviations. the price data from all the economies of all • Construction. The basket of construction the regions were used in the linking proce- components (BOCC) method used in ICP dure. This approach resulted in robust 2005 was replaced by a simple approach estimates of linking factors that were based on the prices of basic construction minimally affected by deficient data from materials, different types of labor, and the some of the participating economies. hire of machinery and equipment. The new – The linking was based on price data col- approach eliminated the requirement to lected for a global core list (GCL) of prod- provide the various types of weights needed ucts. The Global Office developed a GCL in implementation of the BOCC. Instead, for household consumption, housing, the new method relied on the cost shares of government compensation, machinery the materials, labor, and equipment that are and equipment, and construction. The needed for different types of construction GCL for household consumption included and that were readily available from the 618 products representative of consump- participating economies. tion in all ICP regions. The participating • Productivity adjustment for government compensa- economies integrated the GCL products tion. Because of the significant disparities in into their regional product lists—for 4 Purchasing Power Parities and the Real Size of World Economies example, 610 GCL items were added to the software used in the computations. In view the regional list in Africa, 412 in Asia and of these methodological improvements and the Pacific, 394 in Eurostat-OECD, 489 in innovations, the ICP 2011 results can be consid- Latin America and the Caribbean, and ered more reliable than those for ICP 2005, 606 in Western Asia. The extent of this especially when taking into account the incon- integration resulted in more reliable sistencies between the ICP 2011 benchmark linking factors. results and extrapolations from ICP 2005. Thus it is recommended that greater reliance be – The weighted country product dummy placed on the ICP 2011 results. method was used on prices collected for all global core list items weighted by their importance to provide linking factors at the basic heading level. THE ICP 2011 RESULTS: AN OVERVIEW – The aggregation at the GDP level and other This report presents results from ICP 2011 for aggregates such as household consump- the 199 participating economies (the Pacific tion, government expenditure, and gross Islands economies, however, covered only fixed capital formation were based on the individual household consumption). The country aggregation with redistribution results presented include estimates of the pur- (CAR)–volume procedure. chasing power parities of currencies, real expenditures derived using PPPs, nominal – As for 2005 ICP, fixity of the regional-level expenditures based on exchange rates, and relativities was ensured by the new meth- price levels expressed relative to the world odology implemented for linking regions. average. These results are available for GDP and its 25 subaggregates. Selected highlights from these results follow. ICP 2011 VERSUS ICP 2005 Size of the world economy. In 2011 the size of The methodology for ICP 2011 and its imple- the world economy, as measured by world GDP, mentation by regions and the Global Office covered by the 177 participating economies,2 marked a significant improvement over ICP was $90,647 billion in PPP terms. Measured by 2005. Some of the deficiencies in the methodol- exchange rates, the size was $70,295 billion. In ogy used in ICP 2005, including the Ring the ICP 2005 final report, world GDP was country approach for linking, were addressed by reported to be $54,976 billion in PPP terms and incorporating new methods designed to provide $44,309 billion in exchange rate terms. more reliable and robust estimates of PPPs and Distribution of world GDP. In 2011, shares real GDP and its components. Some of the of world GDP in PPP terms accruing to the major innovations, just listed and discussed in high-income economies were 50.3 percent more detail, were (1) the use of a global core list (67.3 percent in exchange rate terms); middle- of products for linking at the basic heading level; income economies, 48.2 percent (32.0 percent); (2) the use of the CAR-volume method for link- and low-income economies, 1.5 percent ing above the basic heading level; (3) increased (0.7 percent). The poorest 83.2 percent of the attention to the validation of national accounts population received 49.7 percent of world real data; (4) new procedures for data validation and GDP. According to the results from ICP 2005, the editing; (5) improved coverage of price surveys poorest 83.6 percent of the global population in large economies, including China, India, and received only 39.4 percent of world GDP in real Indonesia; (6) implementation of productivity terms. The regional shares of world GDP were adjustments for all the participating economies 53.2 percent, Eurostat-OECD; 30 percent, Asia instead of a subset of economies, as was the and the Pacific; 5.5 percent, Latin America; case in 2005; (7) a simplified approach to con- struction; and (8) the establishment of a PPP Computation Task Force to ensure the accuracy 2 Because of comparability issues, world total GDP does not include two and replicability of the ICP results irrespective of participating economies—Cuba and Bonaire—or the Pacific Islands. Overview 5 4.8 percent, CIS; 4.5 percent, Africa and Western respectively. The Democratic Republic of Congo, Asia; and 0.1 percent, the Caribbean. Liberia, and the Comoros were the lowest- Ranking of economies by size. ICP 2011 resulted ranked economies, according to real actual indi- in some significant changes in the rankings of vidual consumption. economies determined by their share of world Price level index. The price level index (PLI) is GDP. The United States retained top ranking the ratio of the PPP of a currency in a given with 17.1 percent of world GDP, followed by economy and the corresponding exchange rates. China with 14.9 percent and India with 6.4 per- The PLI is usually expressed relative to the cent. Of particular note was the performance of world average price level set at 100. According China with its GDP in 2011 of 86.9 percent of to ICP 2011, economies with the highest price U.S. GDP compared with only 43.1 percent in level index for GDP were Switzerland, Norway, 2005. The ranking of India rose from fifth in Bermuda, Australia, and Denmark, with indexes 2005 to third in 2011, and Indonesia became ranging from 210 to 185. The United States was one of the top 10 world economies. In 2011 the ranked 25th in the world, according to PLI. top 12 economies accounted for two-thirds of Low-income economies usually had PLIs below world GDP in real terms. 100. Twenty-three economies had PLIs of 50 or Ranking of economies by real per capita GDP. For below, and the Arab Republic of Egypt, Pakistan, the purpose of assessing standards of living, it is Myanmar, Ethiopia and the Lao People’s more appropriate to rank economies by real per Democratic Republic were identified as the least capita GDP. In 2011 Qatar and Macao SAR, expensive economies. China, were the highest-ranked economies, Intereconomy inequality in incomes. It is possible with $146,521 and $115,441 in real per capita to obtain a measure of intereconomy inequality GDP, respectively. They were followed by using real per capita GDP estimates from ICP Luxembourg, Kuwait, Brunei Darussalam, 2011. The population-weighted Gini measure Singapore, the United Arab Emirates, Bermuda, of intereconomy inequality in real per capita and Switzerland. The United States ranked 12th. income in PPP terms was 0.49, which indicated China, Indonesia, and India ranked 99th, 107th, a sharp fall from the level of 0.57 for ICP 2005. and 127th, respectively. The poorest economy A similar sharp decline from 0.71 to 0.64 in the was Liberia with $535, followed by the Comoros Gini measure of inequality was observed when with $610 and the Democratic Republic of exchange rate–converted or nominal per capita Congo with $655. Burundi, Niger, the Central incomes were used. Such a sharp fall in inequal- African Republic, Mozambique, Malawi, ity would have significant implications for the Ethiopia, and Guinea were in the bottom 10 estimates of poverty incidence in the world. ranked economies. Similar trends in intereconomy inequality Ranking of economies by actual individual were also evident when per capita household consumption (AIC). In assessing the welfare of consumption or per capita actual individual people in different economies, a more informa- consumption was used. tive measure is real per capita actual individ- ual consumption, which is the sum of individual consumption by households and individual ORGANIZATION OF THIS REPORT consumption by government. A slightly differ- ent picture emerges when real per capita AIC is This final report on ICP 2011 contains a used in ranking economies. In 2011, Bermuda, wealth of information on the compilation of the United States, and the Cayman Islands were PPPs, and it presents detailed results for major the top-ranked economies with real per capita economic aggregates of GDP, including indi- AIC of $37,924, $37,390, and $34,020, respec- vidual consumption, government expendi- tively. Qatar, which was top-ranked according ture, and investment. The report is divided to real per capita GDP, was now ranked 35th into four chapters. Chapter 1 provides a gen- according to real per capita AIC. Indonesia, eral background of the ICP, including the with a ranking of 118th, was placed above China concept and uses of PPPs. Chapter 2 is the and India, which ranked 121st and 134th, core of the report, presenting and analyzing 6 Purchasing Power Parities and the Real Size of World Economies the 2011 results on PPPs, real expenditures, the history and governance of the ICP and price levels for GDP and its subaggre- (appendixes A and B); the Eurostat–OECD gates. The salient features of the results of the comparison (appendix C); the expenditure 2011 round are discussed, and the PPPs from classification used in the ICP (appendix D); 2011 are compared and contrasted with the the estimation and compilation of national PPP extrapolations from ICP 2005. Chapters 3 accounts (appendix E); the changes in and 4 focus on the methodology that under- methodology between ICP 2005 and ICP 2011 pinned ICP 2011. Chapter 3 describes the (appendix F); reference PPPs (appendix G); conceptual framework and the survey and the updated set of 2005 results incorporating data editing methods used. Chapter 4 pro- all the data revisions that have taken vides details on the special approaches devel- place since publication of the ICP 2005 oped for household consumption as well as report in 2008 (appendix H); comparison of for the comparison-resistant aggregates: the ICP 2011 results with the 2011 results housing, government compensation, machin- extrapolated from ICP 2005 (appendix I); ery and equipment, and construction. The the ICP data access and archiving policy methodology used in linking regional com- (appendix J); and the ICP revision policy parisons in 2011 ICP is also described. The (appendix K). The appendixes are followed by appendixes provide additional information on an extensive glossary. Overview 7 Chapter 1 Background The International Comparison Program (ICP) ICP 2011 in which 199 economies participated. was established in the late 1960s on the rec- The results of the 2011 comparison are presented ommendation of the United Nations Statistical in this report. A history of the ICP appears in Commission (UNSC). It began as a research appendix A and a description of the governance project carried out jointly by the United Nations structure of ICP 2011 in appendix B. Statistical Office (UNSO) and the University Since its beginning, the purpose of the ICP of Pennsylvania. Comparisons were carried has been to compare the gross domestic prod- out in 1970 for 10 economies, in 1973 for ucts (GDPs) of economies with a view toward 16 economies, and in 1975 for 34 economies. determining their relative size, productivity, After the 1975 comparison, the ICP shifted and material well-being. More specifically, the from being a research project to being a regular ICP’s objective is to compile on a timely and operational part of the UNSO work program. It regular basis internationally comparable price was also regionalized; comparisons were orga- and volume measures with which to compare nized by region and then combined to obtain the price and real expenditure levels of GDP and a global comparison. Comparisons were car- its component expenditures across participat- ried out in 1980 for 60 economies, in 1985 for ing economies. The GDPs and their component 64 economies, and in 1993 for 83 economies. expenditures of the economies are valued at The 1993 regional comparisons could not be national price levels and expressed in national combined to produce a global comparison. In currencies. But to be compared, they must be response, the UNSC commissioned a thorough valued at a common price level and expressed review of the ICP before further comparisons in a common currency. The ICP uses purchas- were attempted. Subsequently, the UNSC asked ing power parities (PPPs) to effect this double the World Bank to draw up an action plan that conversion. PPPs are price indexes that serve would address the issues raised by the review. as spatial price deflators. They make it possible This request resulted in the establishment of to compare the GDPs and component expendi- the ICP Global Office within the Bank to coor- tures of economies in real terms by removing dinate and combine the regional comparisons the price level differences between them. This and the formation of a multi-tiered governance approach closely parallels that for GDP compari- structure headed by the UNSC to oversee and sons over time for a single economy where it is assist the Global Office. The first global compari- necessary to remove the price changes between son made under the new arrangements was ICP the periods being compared in order to assess 2005 involving 146 economies. The second was the change in underlying volumes. 9 To calculate PPPs for its comparisons, the ICP African Development Bank, Asian Development holds worldwide surveys at regular intervals— Bank, Interstate Statistical Committee of the currently every six years—to collect comparable Commonwealth of Independent States, United price and expenditure data for the whole range Nations Economic Commission for Latin America of final goods and services that make up the and the Caribbean, United Nations Economic final expenditure on GDP: consumer goods and and Social Commission for Western Asia, and services, government services, and capital goods. Australian Bureau of Statistics. The responsibil- The surveys are organized by region and are ity was shared with the national agencies coor- coordinated by an agency located in the region. dinating the comparison. The national agencies The intention is to produce regional comparisons carried out data collection and data validation that can be combined in a single global compari- within their respective economies. The regional son for a given reference year. The main reasons agencies provided the national agencies with for conducting the surveys on a regional basis methodological and operational guidance, and are that the products to be priced tend to be they coordinated and supervised data collection more homogeneous within regions, expenditure and data validation within the region in line patterns are likely to be similar, and language with the global timetable. They also computed differences are reduced. In addition, there are and finalized the regional comparisons and operational advantages in having the ICP carried published the results. The ICP Global Office was out by agencies that are in relatively close prox- responsible for ensuring that the seven regional imity to the economies they are coordinating. comparisons and the Eurostat-OECD compari- son could be combined in the global comparison and then actually combining them. The compi- ORGANIZATION OF ICP 2011 lation, validation, and publication of the global results were also responsibilities of the Global ICP 2011 covered eight regions. Seven of the Office. eight were ICP regions (geographical) over- The global results presented in chapter 2 of seen by the Global Office: Africa, Asia and the this volume include two singleton economies— Pacific, Commonwealth of Independent States Georgia and the Islamic Republic of Iran— (CIS), Latin America, the Caribbean, Western that did not participate in any of the regional Asia, and the Pacific Islands. The eighth region comparisons. They were each linked to the was neither an ICP region nor a geographi- global comparison through a bilateral compari- cal entity. It comprised the economies that son with an economy participating in a regional were participating in the PPP program run by comparison. The bilateral comparison provided Eurostat, the statistical arm of the European a bridge to the regional comparison, and the Union, and the Organisation for Economic regional comparison provided a bridge to the Co-operation and Development (OECD). The other regions in the global comparison. Georgia economies were mainly European, but they was linked to the CIS comparison through a included some from regions outside Europe as bilateral comparison with Armenia, and the well. Even so, the economies were treated as Islamic Republic of Iran was linked to the though they were an autonomous region for Eurostat-OECD comparison through a bilateral the purpose of incorporating them in the global comparison with Turkey. The bilateral com- comparison. The agenda and timetable of the parisons were organized and coordinated by the Eurostat-OECD PPP Programme differ from Global Office. those of the ICP, but it employs a similar meth- The global results also cover four economies odology, as described in appendix C. Eurostat that participated in two regional comparisons. and the OECD worked closely with the Global The dual participants were the Arab Republic Office to ensure that their economies could be of Egypt and Sudan, which participated in included with the economies of the seven ICP the Africa and Western Asia comparisons; the regions in the 2011 global comparison. Russian Federation, which participated in the The regional agencies responsible for the com- CIS and Eurostat-OECD comparisons; and Fiji, parisons within the seven ICP regions were the which participated in the Asia and the Pacific 10 Purchasing Power Parities and the Real Size of World Economies and the Pacific Islands comparisons. In the GDP is a measure of production, and it is presentation of the global results, these dual commonly estimated as the sum of the value of participants appear under both regions, but they the outputs from production less the cost of the are included only once in the world totals. Dual goods and services used in their production (the participation required additional coordination so-called production approach). It also can be between the regional agencies responsible for estimated as the sum of the final expenditures the regional comparisons affected because each on goods and services plus exports less imports of the economies had to price products specified of goods and services, which is known as the in each region’s product lists. And they had to expenditure side of national accounts and is the ensure that the price, expenditure, population, approach used by the ICP. Yet another alterna- and other data common to both comparisons tive is to estimate GDP as the sum of the incomes were the same. arising from production (wages, profits, etc.), Throughout all stages of the 2011 compari- which is referred to as the income approach. son, the activities of the Global Office were In theory, the three approaches yield the same overseen by the ICP Executive Board, which result. However, whereas values estimated from reported in turn to the UNSC. The board pro- the production side and the expenditure side can vided strategic leadership, set priorities and be split into meaningful price and volume com- standards, and determined the Global Office’s ponents, values estimated from the income side overall work program. The objective was to cannot. In other words, price and volume com- ensure that the global comparison was com- parisons of GDP can be made from the produc- pleted on time and within budget and that it tion side and from the expenditure side, but not produced price and real expenditure measures from the income side. ICP comparisons are made of high quality. To this end, the board appointed from the expenditure side. This approach allows a Technical Advisory Group of international comparison of the levels of the principal elements experts to assist the Global Office with the con- of final demand—consumption and investment. ceptual, methodological, and technical ques- It also avoids the difficulties encountered in tions that would arise during the comparison. organizing comparisons from the production In addition, three task forces were formed: the side, which requires data for both intermedi- Validation Expert Group to oversee validation of ate consumption and gross output in order to the data provided for the global comparison; the effect double deflation. The disadvantage of the PPP Computation Task Force (a group of com- expenditure approach is that, unlike the produc- putation experts) to calculate the global results tion approach, it does not identify individual independently from each other and ensure their industries, and so productivity comparisons can convergence; and the Results Review Group to be made only at the level of the whole economy. review the global results in terms of their plausi- On the other hand, a major advantage is that the bility and adherence to agreed-on methodologies estimates of final demand can be used in many and procedures. Details on the various tiers of different types of economic analysis, including governance for ICP 2011 appear in appendix B. forecasting and poverty analysis. Economies estimate their expenditures on GDP at national price levels and in national cur- THE ICP APPROACH TO GDP rencies. But before the estimates can be used to COMPARISONS compare the volumes of goods and services pro- duced by economies, differences in national price ICP comparisons of GDP are based on the value levels have to be eliminated and national curren- of an individual product equaling the product cies have to be converted to a common currency. of its price and quantity (that is, the identity of Differences in price levels between economies value = price × quantity). Once more than one can be removed either by observing the volumes product is involved, the identity can no longer directly as the sum of their underlying quantities be expressed in terms of price × quantity. or by deriving them indirectly using a measure Therefore, in ICP terms it becomes value = of relative prices to place the expenditures of price × volume. all economies on the same price level. Prices Background 11 are easier to observe than quantities, and direct goods and services would have to be traded measures of relative prices usually have a smaller internationally, and the supply and demand for variability than direct measures of relative quan- currencies would have to be driven predomi- tities. In ICP comparisons, volumes (referred to as nantly, if not solely, by the currency require- real expenditures) are mostly estimated indirectly ments of international trade. But this is not the using direct measures of relative prices—PPPs— case. Many goods and services such as buildings, to deflate nominal expenditures. In addition to government services, and most household mar- being spatial price deflators, PPPs are currency ket services are not traded internationally, and converters. Thus PPP-deflated expenditures are the supply and demand for currencies are expressed in a common currency unit and are influenced primarily by factors such as currency also valued at the same price level. speculation, interest rates, government inter- vention, and capital flows between economies. Consequently, as equation (1.2) in box 1.1 indi- EXCHANGE RATES cates, GDPs converted to a common currency using exchange rates remain valued at national Before PPPs became widely available, exchange price levels. The differences between the levels rates were used to make international com- of GDP in two or more economies reflect both parisons of GDP. Exchange rates, however, only differences in the volumes of goods and services convert GDPs to a common currency. They do produced by the economies and differences in not provide GDPs valued at a common price the price levels of the economies. On the other level because exchange rates do not reflect hand, as equation (1.4) in box 1.1 shows, GDPs the relative purchasing power of currencies in converted with PPPs reflect only differences in their national markets. For them to do so, all the volumes produced by the economies. BOX 1.1 Using Exchange Rates and PPPs to Convert to a Common Currency 1. The ratio of the gross domestic products (GDPs) of two economies when both GDPs are valued at national price levels and expressed in national currencies has three component ratios: GDP ratio = price level ratio × volume ratio × currency ratio. (1.1) 2. When converting the GDP ratio in (1.1) to a common currency using the exchange rate, the resulting GDPXR ratio has two component ratios: GDPXR ratio = price level ratio × volume ratio. (1.2) The GDP ratio in (1.2) is expressed in a common currency, but it reflects both the price level differences and the volume differences between the two economies. 3. A purchasing power parity (PPP) is defined as a spatial price deflator and currency con- verter. It is composed of two component ratios: PPP = price level ratio × currency ratio. (1.3) 4. When a PPP is used, the GDP ratio in (1.1) is divided by (1.3), and the resulting GDPPPP ratio has only one component ratio: GDPPPP ratio = volume ratio. (1.4) The GDP ratio in (1.4) is expressed in a common currency, is valued at a common price level, and reflects only volume differences between the two economies. 12 Purchasing Power Parities and the Real Size of World Economies Exchange rate–converted GDPs can be highly (4.80/4.00). In other words, for every euro spent misleading on the relative sizes of economies on hamburgers in France, $0.83 would have and levels of material well-being. Price levels to be spent in the United States to obtain the are normally higher in high-income economies same quantity and quality—that is, the same than they are in low-income economies, and, as volume—of hamburgers. Conversely, for every a result, differences in price levels between high- dollar spent on hamburgers in the United States, income economies and low-income economies a1.20 would have to be spent in France to obtain are greater for nontraded products than they the same volume of hamburgers. To compare are for traded products. Before the addition the volumes of hamburgers purchased in the of tariffs, subsidies, and trade costs, the prices two economies, either the expenditure on ham- of traded products are basically determined burgers in France can be expressed in dollars by globally by the law of one price, whereas the dividing by 1.20 or the expenditure on ham- prices of nontraded products are determined by burgers in the United States can be expressed in local circumstances, in particular by wages and euros by dividing by 0.83. salaries, which are generally higher in high- PPPs are calculated in stages: first for indi- income economies. If the larger price level dif- vidual goods and services, then for groups of ferences for nontraded products are not taken products, and finally for each of the various into account when converting GDPs to a com- levels of aggregation up to GDP. PPPs continue mon currency, the size of high-income econo- to be price relatives whether they refer to a mies with high price levels will be overstated product group, to an aggregation level, or to and the size of low-income economies with low GDP. As one moves up the aggregation hier- price levels will be understated. This is known as archy, the price relatives refer to increasingly the Penn effect. No distinction is made between complex assortments of goods and services. traded products and nontraded products when Therefore, if the PPP for GDP between France exchange rates are used to convert GDPs to a and the United States is a0.95 to the dollar, it common currency—the rate is the same for all can be inferred that for every dollar spent on products. PPP-converted GDPs do not have this GDP in the United States, a0.95 would have to bias because, as explained shortly, PPPs are cal- be spent in France to purchase the same volume culated first for individual products. They thus of goods and services. Purchasing the same vol- take into account the different price levels for ume of goods and services does not mean that traded products and nontraded products. the baskets of goods and services purchased in ICP PPPs are designed specifically for inter- both economies will be identical. The composi- national comparisons of GDP. They are not tion of the baskets will vary between economies designed to compare monetary flows or trade and reflect differences in taste, culture, climate, flows. International comparisons of flows—such price structure, product availability, and income as development aid, foreign direct investment, level, but both baskets will, in principle, provide migrants’ remittances, or imports and exports equivalent satisfaction or utility. of goods and services—should be made with exchange rates, not with PPPs. PRICE LEVEL INDEXES PPPs are spatial price indexes. They show—with PURCHASING POWER PARITIES reference to a base economy (or region)—the PPPs are price relatives that show the ratio of the price of a given basket of goods and services prices in national currencies of the same good or in each of the economies being compared. service in different economies. For example, if This index is similar to a temporal price index, the price of a hamburger is a4.80 in France and which shows with reference to a base period $4.00 in the United States, the PPP for hamburg- the price of a given basket of goods and services ers between the two economies is $0.83 to the at different points in time. However, unlike the euro from the French perspective (4.00/4.80) temporal price index in which the indexes at and a1.20 to the dollar from the U.S. perspective the different points in time are expressed in the Background 13 same currency unit so that price changes over should not be used to compare the size of time are readily identifiable, the PPP index for economies. Fluctuations in exchange rates can each economy is expressed in the economy’s make economies appear suddenly larger or national currency. It is thus not possible to say smaller even though there has been little or no whether one economy is more expensive or change in the relative volume of goods and ser- less expensive than another. For this type of vices produced. comparison, one would have to standardize the indexes by expressing them in a common unit of currency. The common currency used for the REAL EXPENDITURES global comparison is the U.S. dollar, and so each economy’s PPP has been standardized by divid- Economies report nominal expenditures on ing it by that economy’s dollar exchange rate. GDP and its constituent aggregates and product The standardized indexes so obtained are called groups. Nominal expenditures are expenditures price level indexes (PLIs). that are valued at national price levels. They can Economies with PLIs greater than 100 have be expressed in national currencies or, when price levels that are higher than that of the base converted with exchange rates, in a common economy. Economies with PLIs less than 100 currency. In the latter, the converted expen- have price levels that are lower than that of the ditures remain nominal because, as explained base economy. So, returning to the hamburger earlier, exchange rates do not correct for differ- example, if the exchange rate is $1.00 to a0.79, ences in price levels between economies, and the PLI for a hamburger with the United States so the expenditures are still valued at national as the base economy is 152 (1.20/0.79 × 100). price levels. For the ICP, economies report their From this, it can be inferred that, given the rela- nominal expenditures in national currencies. tive purchasing power of the dollar and the euro, PPPs are used to convert these nominal expen- hamburgers cost 52 percent more in France than ditures to real expenditures. Real expenditures they do in the United States. In addition to prod- are expenditures that are valued at a common ucts, PLIs can be calculated for product groups, price level. They reflect real or actual differences aggregates, and GDP. At the level of GDP, PLIs in the volumes purchased in economies and pro- provide a measure of the differences in the gen- vide the measures required for international vol- eral price levels of economies. Thus, if the PPP ume comparisons: indexes of real expenditure for GDP between France and the United States is and indexes of real expenditure per capita. At a0.95 to the dollar, the PLI for GDP based on the the level of GDP, indexes of real expenditure are United States is 120 (0.95/0.79 × 100), indicat- widely used to compare the size of economies, ing that the general price level of France is 20 and indexes of real expenditure per capita are percent higher than that of the United States. frequently used to compare the material well- The PLIs of economies can be compared directly. being of their resident populations. Although the For example, if the PLI of one economy is 120 indexes of real expenditure and real expenditure while that of another economy is 80 (both with per capita for GDP are the most well known, the United States as base), then it is valid to infer indexes of real expenditure and real expenditure that the price level in the former is 50 percent per capita for aggregates and product groups are (that is, 120/80) higher than in the latter. also important, allowing an in-depth analysis of It is worth remembering that PPPs evolve comparison results. slowly, whereas exchange rates can change quickly. Sudden changes in PLIs are usually the result of fluctuations in exchange rates. When ACTUAL INDIVIDUAL CONSUMPTION exchange rates change rapidly, a PLI for an economy could change rapidly as well, reflect- One aggregate below the level of GDP that has ing the fact that an economy that was relatively particular significance in ICP comparisons is cheap has now become relatively expensive actual individual consumption (AIC). On a per compared with the base economy. The volatil- capita basis, it is a better measure of material ity of exchange rates is another reason they well-being than either GDP or the household 14 Purchasing Power Parities and the Real Size of World Economies final consumption expenditure when material USES OF PPPs AND REAL EXPENDITURES well-being is defined in terms of the goods and services consumed by households to satisfy their PPPs and the PLIs and indexes of real expenditure individual needs. Such goods and services are to which they give rise are used for research referred to as individual goods and services, and and analysis, for statistical compilation, and for the expenditure on individual goods and ser- administrative purposes. The principal users are vices is referred to as the individual consump- international bodies such as the World Bank, tion expenditure. the International Monetary Fund (IMF), the GDP covers the individual goods and services United Nations and its affiliates, the OECD, and consumed by resident households. But it also the European Commission. Improvements in includes collective services—such as defense, the timeliness, frequency, and coverage of ICP police, and environment protection—that gen- comparisons, however, have sparked a growing eral government produces to meet the collective demand for PPP-based measures from a variety needs of the community, as well as gross fixed of national users—in particular, government capital formation and net exports, which do not agencies, universities, and research institutes. constitute final consumption. The household At the same time, there has been a switch in final consumption expenditure, on the other user focus. The ICP was established to compare hand, covers only the individual goods and the GDPs of economies in real terms, and PPPs services that households purchase. It does not were seen primarily as a means of convert- take into account the individual services—such ing nominal expenditures to real expenditures. as health, education, and social protection— Comparisons of real expenditure are still the that general government and nonprofit institu- ICP’s primary purpose. But now international tions serving households (NPISHs) provide to users and national users are showing a growing households individually. The provision of such interest in PPPs as measures of the relative prices services, particularly health and education, can between economies at all levels of aggregation vary considerably from economy to economy. and in the national annual average prices under- If only the household expenditure is compared, lying them. As a result of this interest, the Global economies in which households purchase health Office has had to establish a set of rules govern- and education services themselves will appear to ing access to unpublished results and basic data. consume more than economies in which these Researchers and policy makers at both the services are provided to households by general international and national levels use PPPs as government or NPISHs. inputs into economic research and policy analysis Actual individual consumption comprises that involve comparisons of economies. In this only the goods and services that households context, PPPs are employed either to generate consume to meet their individual needs. It cov- measures of real expenditure with which to ers all such goods and services whether they compare the size of economies and their levels of are purchased by households or are provided by material well-being, consumption, investment, general government and NPISHs. AIC is defined government expenditure, and overall productiv- as the sum of the individual consumption expen- ity, or to generate price measures with which to ditures of households, general government, and compare price levels, price structures, price con- NPISHs. The concept of actual individual con- vergence, and competitiveness. PPP-converted sumption dates back to the earliest years of the GDP is used to standardize other economic vari- ICP, when it was called the consumption expen- ables such as carbon emissions per unit of GDP, diture of the population. Initially, the individ- energy use per unit of GDP, GDP per employee, ual consumption expenditure by NPISHs was or GDP per hour worked. Multinational corpora- not included. Later, however, the concept was tions, for example, use PPPs to evaluate the cost expanded to include the consumption expendi- of investment in different economies. ture of NPISHs, and it was adopted by national One major use of PPPs is poverty assess- accountants in the System of National Accounts ment using the World Bank’s international 1993 or SNA93 (Commission of the European poverty threshold of $1.25 per day per person. Communities et al. 1993). National poverty assessments differ because Background 15 the purchasing power of national curren- a group to obtain totals for the group. The shares cies differs from one economy to another. of economies in these totals are used as weights Therefore, establishing an international pov- when economic indicators, such as price indexes erty line requires equalizing purchasing power or growth rates, are combined to obtain aver- over economies. The international poverty ages for the group. Both the IMF and the OECD line of $1.25 per day is converted to national use PPP-based GDP and GDP aggregates to price levels by using the PPPs for the individ- provide estimates of regional and world out- ual consumption expenditures by households. put and growth in their respective publications Data from household income and expenditure World Economic Outlook and Economic Outlook. surveys are then used to determine the num- Finally, PPPs are employed for administrative ber of people whose consumption per capita purposes by the European Commission and the is below this poverty line. The international IMF. The European Commission uses the PPPs poverty line itself has typically been calculated of its member states when allocating the struc- as the average of the national poverty lines tural funds intended to reduce economic dis- of the world’s poorest economies, converted parities between and within member states. The to international dollars using consumption principal indicator influencing the allocation PPPs. The PPPs thus enter the calculation at is PPP-deflated intra-economy regional GDP two stages—first, in establishing the poverty per capita. The IMF uses PPP-based GDP from line and, second, in calculating the number of the World Economic Outlook in its current quota people below it in each economy. formula. In the past, that measure often helped Eradication of hunger and poverty is the first guide increases in members’ quotas. Quota United Nations Millennium Development Goal. subscriptions determine the maximum financial Other goals are in the areas of health care, partic- resources that member economies are obliged ularly that of mothers and children, and primary to provide the IMF, the amount of financing education. The World Health Organization uses that members can obtain from the IMF, their PPPs when comparing expenditures per capita share in a general allocation of special drawing on health care across economies. Similarly, rights, and their voting power in IMF decisions. the United Nations Educational, Scientific and PPP-based GDP has a weight of 20 percent in the Cultural Organization (UNESCO) uses PPPs current quota formula. when assessing the expenditures per capita of The uses of PPPs and related data are different economies on education. A related continuing to expand as the limitations of the use is the estimation of the United Nations main alternative method of adjusting values to Human Development Index. PPP-converted a common currency—using exchange rates— gross national income per capita is one of the become more widely recognized and as the three variables that constitute the index. number of economies included in the ICP con- PPPs are also used for statistical compilation. tinues to increase. The main issue that needs International organizations use PPPs to obtain to be addressed now is the availability of more totals and averages for a group of economies timely PPP data sets. The World Bank is inves- such as an ICP region. Real GDP and its com- tigating ways in which PPPs can be estimated ponents are aggregated across the economies in more frequently. 16 Purchasing Power Parities and the Real Size of World Economies Chapter 2 Presentation and Analysis of Results The results presented here are based exclu- PRESENTATION OF RESULTS sively on the price and national accounts data provided by all economies participating Eleven tables of ICP 2011 results and two sup- in the global comparison undertaken in the plementary tables appear at the end of this sec- 2011 round of the International Comparison tion, preceded by a detailed description of their Program (ICP). Purchasing power parities various components. The tables are as follows: (PPPs) and real expenditures were compiled in • Table 2.1 Summary Results and Reference accordance with established ICP principles and Data procedures recommended by the Technical Advisory Group for ICP 2011. Users of ICP • Table 2.2 Nominal Expenditures in National results are reminded to recognize that the ICP Currency Units is a complex major statistical exercise whose • Table 2.3 Shares of Nominal Expenditures methodology is constantly being refined and (GDP = 100) improved. The National Bureau of Statistics (NBS) of • Table 2.4 Purchasing Power Parities China expressed reservations about some aspects (U.S. Dollar = 1.00) of the methodology employed in ICP 2011 and • Table 2.5 Real Expenditures in U.S. Dollars did not agree to publish the headline results for China. Those results were estimated by the 2011 • Table 2.6 Shares of World Real Expenditures ICP Regional Office in the Asian Development (World = 100) Bank and the 2011 ICP Global Office hosted • Table 2.7 Real Expenditures Per Capita in by the World Bank. However, the NBS of U.S. Dollars China does not endorse these results as official statistics. • Table 2.8 Indexes of Real Expenditures Per In addition to providing the ICP 2011 Capita (World = 100) results and analysis, this chapter addresses the • Table 2.9 Price Level Indexes (World = 100) reliability and limitations of PPPs and real • Table 2.10 Nominal Expenditures in expenditures, the differences between the 2005 U.S. Dollars and 2011 comparisons, and the differences between 2011 PPPs extrapolated from ICP 2005 • Table 2.11 Nominal Expenditures Per Capita and ICP 2011 benchmark PPPs. in U.S. Dollars 17 • Supplementary Table 2.12 Main Results and global or regional relativity between economies. Reference Data, Pacific Islands The two economies are listed at the end of each table as singletons and are included in world • Supplementary Table 2.13 Estimated Results totals and averages. and Reference Data, Nonbenchmark Four economies—the Arab Republic of Egypt, Economies Sudan, the Russian Federation, and Fiji— In all tables, results are presented by economy participated in two regional comparisons, but and by region and include regional totals and only the dual participation of Egypt, Sudan, and averages as well as world totals and averages. The Russia is of concern here because the dual partici- world is defined as all economies covered by the pation of Fiji involved the Pacific Islands compari- tables with the exception of Cuba and Bonaire, son covered in supplementary table 2.12. Egypt which do not have a full set of results and are not and Sudan participated in the Africa comparison included in either the regional or world totals. and the Western Asia comparison, and Russia Afghanistan, Argentina, Lebanon, Libya, South participated in the CIS comparison and the Sudan, and the Syrian Arab Republic are the Eurostat-OECD comparison. In the tables, they only large economies that did not take part in ICP appear under both regions and are included in 2011, and so they are not included in the world the totals and averages of both regions. They are totals. They are included in supplementary included only once in the world totals and averages. table 2.13, which shows the estimated real gross domestic product (GDP) per capita for economies Summary results: table 2.1 and supplementary that did not participate in ICP 2011. tables 2.12 and 2.13 Eight regions participated in ICP 2011: Africa, Asia and the Pacific, Commonwealth of Table 2.1 provides the summary results for ICP Independent States (CIS), Eurostat–Organisation 2011 broken down into the following indicators: for Economic Co-operation and Development • Column (01): GDP based on PPPs in U.S. (OECD), Latin America, the Caribbean, Western dollars Asia, and the Pacific Islands. All are geographi- cal regions except the Eurostat-OECD group • Column (02): GDP based on exchange rates of economies, which, though predominantly in U.S. dollars European, include a worldwide spread of non- • Column (03): GDP per capita based on PPPs European economies as well. Thus the regional in U.S. dollars classification used to present the results differs from the regional classifications used by other • Column (04): GDP per capita based on international statistical programs. Of the eight exchange rates in U.S. dollars regions listed, only the first seven are covered • Column (05): Price level index for GDP with in the tables. The comparison for the eighth the world equal to 100 region—the Pacific Islands—was limited to household consumption, and so its results are • Column (06): GDP per capita index based shown in supplementary table 2.12 and not in on PPPs with the world equal to 100 the tables that cover all GDP. • Column (07): GDP per capita index based on Two economies, Georgia and the Islamic exchange rates with the world equal to 100 Republic of Iran, did not participate in a regional • Column (08): GDP per capita index based comparison. Instead, they were linked to on PPPs with the United States equal to 100 the global comparison through a bilateral com- parison with an economy participating in a • Column (09): GDP per capita index based regional comparison: Armenia and the CIS com- on exchange rates with the United States parison in the case of Georgia; Turkey and the equal to 100 Eurostat-OECD comparison in the case of the • Column (10): Share of PPP-based world GDP Islamic Republic of Iran. The linking took place after the global comparison was calculated, and • Column (11): Share of exchange rate–based so their inclusion does not influence either the world GDP 18 Purchasing Power Parities and the Real Size of World Economies • Column (12): Share of world population Column (02) shows the nominal expenditures of economies and regions on GDP in U.S. dollars. • Column (13): PPP for GDP with the The expenditures reflect both price differences U.S. dollar equal to 1.000 and volume differences between economies and • Column (14): Exchange rate with the regions (see box 2.1). They were derived by divid- U.S. dollar equal to 1.000 ing the nominal expenditures on GDP in col- umn (16) by the exchange rates in column (14). • Column (15): Resident population The GDP per capita in column (04), the GDP per capita indexes in columns (07) and (09), and the • Column (16): Nominal GDP in national shares of world GDP in column (11) are all based currency unit on the nominal expenditures in column (02). Users are reminded that, as explained in chap- Supplementary tables 2.12 and 2.13 provide ter 1, exchange rate–converted GDPs are not the same information but for a limited set of reliable measures of either the size of economies indicators. or the material well-being of their populations. Column (01) shows the real expenditures of They are included in the summary table and in economies and regions on GDP in U.S. dollars. the supplementary tables for reference only. The expenditures reflect only volume differ- ences between economies and regions. They Detailed results: tables 2.2–2.11 were obtained by dividing the nominal expendi- tures on GDP in column (16) by the PPPs for Tables 2.2–2.11 present the results for ICP 2011 GDP in column (13). The GDP per capita in broken down into 26 analytical categories. column (03), the GDP per capita indexes in col- These categories, which cover GDP and a selec- umns (06) and (08), and the shares of world tion of component final expenditures, are listed GDP in column (10) are all based on the real and defined in box 2.1. Their codes in the ICP expenditures in column (01). expenditure classification in appendix D are also BOX 2.1 Analytical Categories: Tables 2.2–2.11 and Supplementary Tables 2.12 and 2.13 Column (01) Gross domestic product: Actual individual consumption at purchasers’ prices plus collective consumption expenditure by government at purchasers’ prices plus gross capital formation at purchasers’ prices plus the f.o.b. (free on board) value of exports of goods and services less the f.o.b. value of imports of goods and services. Code in ICP expenditure classification, appendix D: 100000 Column (02) Actual individual consumption: The total value of the individual consumption expenditures of households, nonprofit institutions serving households (NPISHs), and general government at purchasers’ prices. Code in ICP expenditure classifica- tion, appendix D: not identified in classification; sum of 110000 + 120000 + 130000 Column (03) Food and nonalcoholic beverages: Household expenditure on food products and nonalcoholic beverages purchased for consumption at home (excludes food products and nonalcoholic beverages sold for immediate consumption away from home by hotels, restaurants, cafés, bars, kiosks, street vendors, automatic vending machines, etc.; cooked dishes prepared by restaurants for consumption off their premises; cooked dishes prepared by catering contractors whether collected by the customer or delivered to the customer’s home; and products sold specifically as pet foods). Code in ICP expenditure classification, appendix D: 110100 (continued) Presentation and Analysis of Results 19 BOX 2.1 (Continued) Column (04) Alcoholic beverages, tobacco, and narcotics: Household expenditure on alcoholic beverages purchased for consumption at home (includes low or nonalcoholic bev- erages that are generally alcoholic such as nonalcoholic beer, and excludes alcoholic bever- ages sold for immediate consumption away from the home by hotels, restaurants, cafés, bars, kiosks, street vendors, automatic vending machines, etc.) and household expenditure on tobacco (covers all purchases of tobacco, including purchases of tobacco in cafés, bars, restaurants, and service stations). Code in ICP expenditure classification, appendix D: 110200 Column (05) Clothing and footwear: Household expenditure on clothing materials; gar- ments for men, women, children, and infants; other articles of clothing and clothing acces- sories; cleaning, repair, and hire of clothing; all footwear for men, women, children, and infants; and repair and hire of footwear. Code in ICP expenditure classification, appendix D: 110300 Column (06) Housing, water, electricity, gas, and other fuels: Household expenditure on actual and imputed rentals for housing; maintenance and repair of the dwelling; water supply and services related to the dwelling; and electricity, gas, and other fuels plus expendi- ture by NPISHs on housing plus general government expenditure on housing services pro- vided to individuals. Codes in ICP expenditure classification, appendix D: 110400 + (120000) + 130100 Column (07) Furnishings, household equipment, and maintenance: Household expenditure on furniture and furnishings; carpets and other floor coverings; household textiles; household appliances; glassware, tableware, and household utensils; tools and equipment for house and garden; and goods and services for routine household main- tenance. Code in ICP expenditure classification, appendix D: 110500 Column (08) Health: Household expenditure on pharmaceuticals; medical products, appliances, and equipment; outpatient services; and hospital services plus expenditure of NPISHs on health plus general government expenditure on health benefits and reimburse- ments, and the production of health services. Codes in ICP expenditure classification, appendix D: 110600 + (120000) + 130200 Column (09) Transport: Household expenditure on purchase of vehicles, operation of personal transport equipment, and transport services. Code in ICP expenditure classification, appendix D: 110700 Column (10) Communication: Household expenditure on postal services, telephone and telefax equipment, and telephone and telefax services. Code in ICP expenditure classifica- tion, appendix D: 110800 Column (11) Recreation and culture: Household expenditure on audiovisual, photo- graphic, and information processing equipment; other major durables for recreation and culture; other recreational items and equipment; gardens and pets; recreational and cul- tural services; newspapers, books, and stationery; and package holidays plus expenditure by NPISHs on recreation and culture plus general government expenditure on recreation and culture. Codes in ICP expenditure classification, appendix D: 110900 + (120000) + 130300 Column (12) Education: Household expenditure on pre-primary, primary, secondary, postsecondary, and tertiary education plus expenditure of NPISHs on education plus general government expenditure on education benefits and reimbursements and the production of education services. Codes in ICP expenditure classification, appendix D: 111000 + (120000) + 130400 Column (13) Restaurants and hotels: Household expenditure on food products and beverages sold for immediate consumption away from the home by hotels, restaurants, cafés, bars, kiosks, street vendors, automatic vending machines, etc. (includes cooked dishes prepared by restaurants for consumption off their premises and cooked dishes pre- pared by catering contractors, whether collected by the customer or delivered to the cus- tomer’s home) and household expenditure on accommodation services provided by hotels and similar establishments. Code in ICP expenditure classification, appendix D: 111100 20 Purchasing Power Parities and the Real Size of World Economies BOX 2.1 (Continued) Column (14) Miscellaneous goods and service: Household expenditure on personal care, personal effects, social protection, insurance, and financial and other services plus expenditure by NPISHs on social protection and other services plus general government expenditure on social protection. Codes in ICP expenditure classification, appendix D: 111200 + (120000) + 130500 Column (15) Net purchases abroad: Purchases by resident households outside the economic territory of the economy less purchases by nonresident households in the economic territory of the economy. Code in ICP expenditure classification, appendix D: 111300 Column (16) Individual consumption expenditure by households: The total value of actual and imputed final consumption expenditures incurred by households on individual goods and services. It also includes expenditures on individual goods and services sold at prices that are not economically significant. Code in ICP expenditure clas- sification, appendix D: 110000 Column (17) Individual consumption expenditure by government: The total value of actual and imputed final consumption expenditures incurred by general government on individual goods and services. Code in ICP expenditure classification, appendix D: 130000 Column (18) Collective consumption expenditure by government: The final con- sumption expenditure of general government on collective services. Code in ICP expenditure classification, appendix D: 140000 Column (19) Gross fixed capital formation: The total value of acquisitions less dispos- als of fixed assets by resident institutional units during the accounting period plus the additions to the value of nonproduced assets realized by the productive activity of resident institutional units. Code in ICP expenditure classification, appendix D: 150000 Column (20) Machinery and equipment: Capital expenditure on fabricated metal products, general-purpose machinery, special-purpose machinery, electrical and optical equipment, transport equipment, and other manufactured goods. Code in ICP expenditure classification, appendix D: 150100 Column (21) Construction: Capital expenditure on the construction of new structures and renovation of existing structures. Structures include residential buildings, nonresiden- tial buildings, and civil engineering works. Code in ICP expenditure classification, appendix D: 150200 Column (22) Other products: Capital expenditure on plantation, orchard, and vineyard development; change in stocks of breeding stock, draft animals, dairy cattle, animals raised for wool clippings, etc.; computer software that a producer expects to use in production for more than one year; land improvement, including dams and dikes that are part of flood control and irrigation projects; mineral exploration; acquisition of entertainment, literary, or artistic originals; and other intangible fixed assets. Code in ICP expenditure classification, appendix D: 150300 Column (23) Changes in inventories and valuables: The acquisition less disposals of stocks of raw materials, semi-finished goods, and finished goods that are held by producer units prior to being further processed or sold or otherwise used; and the acquisition less disposals of valu- ables (produced assets that are not used primarily for production or consumption but pur- chased and held as stores of value). Code in ICP expenditure classification, appendix D: 160000 Column (24) Balance of exports and imports: The f.o.b. value of exports of goods and services less the f.o.b. value of imports of goods and services. Code in ICP expenditure classi- fication, appendix D: 170000 (continued) Presentation and Analysis of Results 21 BOX 2.1 (Continued) Column (25) Domestic absorption: Actual individual consumption at purchasers’ prices plus collective consumption expenditure by government at purchasers’ prices plus gross capital formation at purchasers’ prices. Code in ICP expenditure classification, appendix D: not identified in the classification; sum of 110000 + 120000 + 130000 + 140000 + 150000 + 160000 Column (26) Individual consumption expenditure by households, excluding housing: Individual consumption expenditure by households in column (16) without the actual and imputed rentals included in column (06). Codes in ICP expenditure classifica- tion, appendix D: 110000−110410 given to show the correspondence between the memorandum items. The individual consump- tables and the classification. tion expenditure by households includes the In the classification, consumption expendi- individual consumption expenditure by NPISHs. tures are structured by who pays: households, Two other memorandum items that appear in nonprofit institutions serving households the tables are domestic absorption, column (25), (NPISHs), or general government. But in and individual consumption expenditure, tables 2.2–2.9 and the supplementary tables, con- excluding housing, column (26). sumption expenditures are structured by who Table 2.2 shows the nominal expenditures in consumes: households, under actual individual the analytical categories reported by the econo- consumption in column (02), or general govern- mies. The expenditures are valued at national ment, under collective consumption expenditure price levels and expressed in national currency by government in column (18). The analytical units. They are converted to real expenditures categories affected by the change in structure— in table 2.5 by deflating them by the PPPs in which entails adding the expenditures on indi- table 2.4. The nominal expenditures at the more vidual services by NPISHs and general government detailed basic heading level (not shown) are the to the expenditure on individual services by weights used to calculate PPPs for the analytical households—are those covering individual categories. The nominal expenditures are addi- household consumption in column (02), housing tive, and tables 2.2, 2.3, 2.10, and 2.11 contain in column (6), health in column (08), recreation four additional analytical categories for com- and culture in column (11), education in col- pleteness: net purchases abroad, column (15); umn (12), and social protection in column (14). other products, column (22); changes in inven- These categories are shaded in blue in box 2.1. tories and valuables, column (23); and balance In the tables, actual individual consumption of exports and imports, column (24). in column (02) is broken down by the analytical Table 2.3 contains each economy’s nominal categories covering the expenditure on con- expenditures in the analytical categories in sumer goods and services in columns (03) to table 2.2 as a percentage of its GDP. (15). The expenditure includes the individual Table 2.4 presents the PPPs for the analytical consumption expenditures of NPISHs and gen- categories. The final PPPs were calculated by eral government as well as the individual con- the Global Office. The Gini-Èltetö-Köves-Szulc sumption expenditure of households. Because (GEKS) method and country aggregation with actual individual consumption is defined as the redistribution (CAR) procedure described in sum of the individual consumption expendi- chapter 4 were used to provide PPPs and real tures of households, NPISHs, and general gov- expenditures with the following properties: ernment, the tables also show the individual consumption expenditure by households in • They are commensurate, meaning they do not column (16) and the individual consumption change when the units of quantity to which expenditure by government in column (17) as their prices refer are changed—for example, 22 Purchasing Power Parities and the Real Size of World Economies when the price of petrol is quoted per gallon are in U.S. dollars, they are free of the rather than per liter. Gerschenkron effect, and they respect fixity, but they are not additive. They reflect only volume • They are transitive, meaning that every differences between economies. indirect multilateral PPP between a pair Table 2.6 shows for economies and regions of economies calculated via a third their real expenditures in each analytical cate- economy equals the direct multilat- gory as a percentage share of the world real eral PPP between the economies. expenditure in the analytical category. The per- • They are base economy–invariant, meaning that centage shares are based on the real expenditures the relativities between economies are the in table 2.5. At the level of GDP, they measure same whichever economy or region is taken the relative size of the economies covered in as base. the table. Table 2.7 presents the real expenditures per • They provide real expenditures that are free capita in the analytical categories. The expendi- of the Gerschenkron effect, which is the bias tures are in U.S. dollars. They were obtained by resulting when high-income economies dividing the real expenditures in table 2.5 by receive more weight in the estimation pro- the population totals in column (15) of table 2.1. cess, resulting in overestimates of the real size Table 2.8 provides the indexes of real expen- of low-income economies. ditures per capita in the analytical categories • Their real expenditures are not additive, with the world equal to 100. They are based on meaning that the real expenditures at higher the real expenditures per capita in table 2.7. The levels of aggregation are not equal to the indexes are base economy–invariant and can be sum of the real expenditures of their compo- rebased on an economy or on a region. At the nents. (Many users consider additivity to be level of actual individual consumption, they an important feature of real expenditures. measure the relative material well-being of the However, in practice it is not possible to resident populations of the economies included maintain the additivity of the component in the table. aggregates within real GDP without having Table 2.9 gives the price level indexes (PLIs) real expenditures for GDP that are signifi- for the analytical categories relative to the cantly biased between low- and high-income world average. A value above 100 indicates economies (that is, the Gerschenkron effect). that the economy’s price level for the analyti- cal category in question is higher than the • Moreover, the PPPs and real expenditures world average; a value below 100 indicates respect fixity, meaning that the relativities that the economy’s price level for the analyti- established between economies in a regional cal category is lower than the world average. comparison remain the same when the The PLIs are base country–invariant and can economies are included in the global be rebased on an economy or on a region. For comparison. example, the PLIs in the table were first calcu- For the PPPs in table 2.4, the United States lated with the United States as base by dividing serves as the base and the U.S. dollar as numéraire. the PPPs in table 2.4 by the exchange rates in But, being base economy–invariant, they can be table 2.1. They were subsequently rebased on rebased on another economy or on a region by the world. dividing them by the PPP for the economy or Table 2.10 presents the nominal expenditures region selected as the new base. For example, in table 2.3 in U.S. dollars. The expenditures they can be rebased on the United Kingdom with were converted using the exchange rates in col- the pound sterling as numéraire by dividing them umn (14) of table 2.1. by the PPP for the United Kingdom. Table 2.11 gives the nominal expenditures Table 2.5 gives the real expenditures in the per capita on the analytical categories in U.S. dol- analytical categories. They were derived by lars. They were derived by dividing the nominal dividing the nominal expenditures in table 2.2 expenditures in table 2.10 by the population by the PPPs in table 2.4. The real expenditures totals in column (15) of table 2.1. Presentation and Analysis of Results 23 Table 2.1 Summary Results and Reference Data, ICP 2011 Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expendi- (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion ture in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) AFRICA Algeria 474.8 198.5 13,195 5,518 53.9 98.0 52.9 26.5 11.1 0.5 0.3 0.5 30.502 72.938 35.98 14,481.0 Angola 143.0 104.2 7,288 5,311 94.0 54.1 50.9 14.6 10.7 0.2 0.1 0.3 68.315 93.741 19.62 9,767.6 Benin 16.1 7.3 1,766 801 58.5 13.1 7.7 3.5 1.6 0.0 0.0 0.1 214.035 471.866 9.10 3,439.8 Botswana 27.2 15.0 13,409 7,381 71.0 99.6 70.7 26.9 14.8 0.0 0.0 0.0 3.764 6.838 2.03 102.5 Burkina Faso 22.8 10.3 1,343 608 58.4 10.0 5.8 2.7 1.2 0.0 0.0 0.3 213.659 471.866 16.97 4,868.5 Burundi 6.1 2.1 712 240 43.5 5.3 2.3 1.4 0.5 0.0 0.0 0.1 425.768 1,261.074 8.58 2,599.9 Cameroon 55.2 26.6 2,757 1,327 62.1 20.5 12.7 5.5 2.7 0.1 0.0 0.3 227.212 471.866 20.03 12,545.7 Cape Verde 3.1 1.9 6,126 3,773 79.4 45.5 36.1 12.3 7.6 0.0 0.0 0.0 48.592 78.886 0.50 149.0 Central African Republic 4.0 2.2 897 486 69.9 6.7 4.7 1.8 1.0 0.0 0.0 0.1 255.862 471.866 4.49 1,029.7 Chad 22.9 12.1 1,984 1,053 68.4 14.7 10.1 4.0 2.1 0.0 0.0 0.2 250.443 471.866 11.53 5,725.3 Comoros 0.5 0.3 610 358 75.6 4.5 3.4 1.2 0.7 0.0 0.0 0.0 207.584 353.900 0.75 95.4 Congo, Rep. 24.1 14.8 5,830 3,575 79.1 43.3 34.2 11.7 7.2 0.0 0.0 0.1 289.299 471.866 4.14 6,982.5 Congo, Dem. Rep. 44.4 25.2 655 372 73.2 4.9 3.6 1.3 0.7 0.0 0.0 1.0 521.870 919.491 67.76 23,146.1 Côte d’Ivoire 53.8 26.0 2,669 1,291 62.4 19.8 12.4 5.4 2.6 0.1 0.0 0.3 228.228 471.866 20.15 12,275.5 Djibouti 2.2 1.2 2,412 1,276 68.2 17.9 12.2 4.8 2.6 0.0 0.0 0.0 94.003 177.721 0.91 205.3 c Egypt, Arab Rep. 843.8 229.9 10,599 2,888 35.1 78.7 27.7 21.3 5.8 0.9 0.3 1.2 1.625 5.964 79.62 1,371.1 Equatorial Guinea 28.4 17.7 39,440 24,621 80.5 293.0 235.9 79.2 49.5 0.0 0.0 0.0 294.572 471.866 0.72 8,367.3 Ethiopia 102.9 29.9 1,214 353 37.5 9.0 3.4 2.4 0.7 0.1 0.0 1.3 4.919 16.899 84.73 506.1 Gabon 25.3 17.1 16,483 11,114 86.9 122.5 106.5 33.1 22.3 0.0 0.0 0.0 318.156 471.866 1.53 8,046.1 Gambia, The 2.7 0.9 1,507 508 43.5 11.2 4.9 3.0 1.0 0.0 0.0 0.0 9.939 29.462 1.78 26.6 Ghana 85.5 39.6 3,426 1,585 59.7 25.5 15.2 6.9 3.2 0.1 0.1 0.4 0.699 1.512 24.97 59.8 Guinea 13.2 5.0 1,287 490 49.0 9.6 4.7 2.6 1.0 0.0 0.0 0.2 2,518.386 6,620.841 10.22 33,128.3 Guinea-Bissau 2.1 1.0 1,365 637 60.1 10.1 6.1 2.7 1.3 0.0 0.0 0.0 220.085 471.866 1.55 464.7 Kenya 88.9 34.3 2,136 825 49.8 15.9 7.9 4.3 1.7 0.1 0.0 0.6 34.298 88.811 41.61 3,048.9 Lesotho 4.7 2.5 2,130 1,151 69.7 15.8 11.0 4.3 2.3 0.0 0.0 0.0 3.923 7.261 2.19 18.3 Liberia 2.2 1.1 537 278 66.7 4.0 2.7 1.1 0.6 0.0 0.0 0.1 0.517 1.000 4.13 1.1 Madagascar 30.1 10.0 1,412 470 42.9 10.5 4.5 2.8 0.9 0.0 0.0 0.3 673.730 2,025.118 21.32 20,276.4 Malawi 15.0 7.3 973 476 63.1 7.2 4.6 2.0 1.0 0.0 0.0 0.2 76.259 155.776 15.38 1,140.8 Mali 23.9 10.6 1,509 672 57.4 11.2 6.4 3.0 1.4 0.0 0.0 0.2 210.193 471.866 15.84 5,024.5 Mauritania 11.3 4.6 3,191 1,295 52.3 23.7 12.4 6.4 2.6 0.0 0.0 0.1 115.855 285.470 3.54 1,309.4 Mauritius 20.3 11.3 15,506 8,611 71.6 115.2 82.5 31.1 17.3 0.0 0.0 0.0 15.941 28.706 1.31 323.0 Morocco 218.3 99.2 6,764 3,074 58.6 50.2 29.5 13.6 6.2 0.2 0.1 0.5 3.677 8.090 32.27 802.6 Mozambique 22.8 12.5 951 524 71.1 7.1 5.0 1.9 1.1 0.0 0.0 0.4 16.030 29.068 23.93 364.7 Namibia 19.4 12.5 8,360 5,369 82.8 62.1 51.4 16.8 10.8 0.0 0.0 0.0 4.663 7.261 2.32 90.6 Niger 13.7 6.4 852 399 60.4 6.3 3.8 1.7 0.8 0.0 0.0 0.2 221.087 471.866 16.07 3,025.5 Nigeria 511.1 247.0 3,146 1,520 62.3 23.4 14.6 6.3 3.1 0.6 0.4 2.4 74.378 153.903 162.47 38,017.0 Rwanda 14.6 6.3 1,337 579 55.9 9.9 5.5 2.7 1.2 0.0 0.0 0.2 260.751 601.833 10.94 3,814.4 24 Purchasing Power Parities and the Real Size of World Economies Table 2.1 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expendi- (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion ture in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) São Tomé and Príncipe 0.5 0.2 3,045 1,473 62.4 22.6 14.1 6.1 3.0 0.0 0.0 0.0 8,527.157 17,622.933 0.17 4,375.5 Senegal 28.6 14.3 2,243 1,123 64.6 16.7 10.8 4.5 2.3 0.0 0.0 0.2 236.287 471.866 12.77 6,766.8 Seychelles 2.0 1.1 22,569 12,196 69.7 167.7 116.8 45.3 24.5 0.0 0.0 0.0 6.690 12.381 0.09 13.1 Sierra Leone 8.2 2.9 1,369 490 46.2 10.2 4.7 2.8 1.0 0.0 0.0 0.1 1,553.139 4,336.129 6.00 12,754.9 South Africa 611.1 401.8 12,111 7,963 84.8 90.0 76.3 24.3 16.0 0.7 0.6 0.7 4.774 7.261 50.46 2,917.5 Sudand 152.4 70.0 3,608 1,656 59.2 26.8 15.9 7.2 3.3 0.2 0.1 0.6 1.224 2.667 42.25 186.6 Swaziland 7.6 4.1 6,328 3,399 69.3 47.0 32.6 12.7 6.8 0.0 0.0 0.0 3.900 7.261 1.20 29.7 Tanzania 71.8 23.9 1,554 517 42.9 11.5 4.9 3.1 1.0 0.1 0.0 0.7 522.483 1,572.115 46.22 37,533.0 Togo 8.1 3.7 1,314 599 58.8 9.8 5.7 2.6 1.2 0.0 0.0 0.1 215.060 471.866 6.15 1,739.2 Tunisia 109.3 46.0 10,319 4,340 54.2 76.7 41.6 20.7 8.7 0.1 0.1 0.2 0.592 1.408 10.59 64.7 Uganda 55.1 18.2 1,597 528 42.6 11.9 5.1 3.2 1.1 0.1 0.0 0.5 833.540 2,522.747 34.51 45,944.1 Zambia 42.5 20.8 3,155 1,544 63.1 23.4 14.8 6.3 3.1 0.0 0.0 0.2 2,378.380 4,860.667 13.47 101,104.8 Zimbabwe 17.6 8.9 1,378 695 65.0 10.2 6.7 2.8 1.4 0.0 0.0 0.2 0.504 1.000 12.75 8.9 Total (50) 4,115.1 1,870.4 4,044 1,838 58.6 30.0 17.6 8.1 3.7 4.5 2.7 15.1 n.a. n.a. 1,017.60 n.a. ASIA AND THE PACIFIC Bangladesh 419.2 130.9 2,800 874 40.3 20.8 8.4 5.6 1.8 0.5 0.2 2.2 23.145 74.152 149.70 9,702.9 Bhutan 5.1 1.8 7,199 2,600 46.6 53.5 24.9 14.5 5.2 0.0 0.0 0.0 16.856 46.670 0.71 85.9 Brunei Darussalam 29.3 16.7 74,397 42,432 73.5 552.7 406.5 149.4 85.2 0.0 0.0 0.0 0.717 1.258 0.39 21.0 Cambodia 38.7 12.8 2,717 902 42.8 20.2 8.6 5.5 1.8 0.0 0.0 0.2 1,347.115 4,058.500 14.23 52,068.7 Chinae 13,495.9 7,321.9 10,057 5,456 70.0 74.7 52.3 20.2 11.0 14.9 10.4 19.9 3.506 6.461 1,341.98 47,310.4 Fiji 6.5 3.8 7,558 4,393 75.0 56.1 42.1 15.2 8.8 0.0 0.0 0.0 1.042 1.793 0.85 6.7 Hong Kong SAR, China 354.5 248.7 50,129 35,173 90.5 372.4 337.0 100.7 70.7 0.4 0.4 0.1 5.462 7.784 7.07 1,936.1 India 5,757.5 1,864.0 4,735 1,533 41.7 35.2 14.7 9.5 3.1 6.4 2.7 18.1 15.109 46.670 1,215.96 86,993.1 Indonesia 2,058.1 846.3 8,539 3,511 53.0 63.4 33.6 17.2 7.1 2.3 1.2 3.6 3,606.566 8,770.433 241.04 7,422,781.2 Lao PDR 26.2 8.1 4,108 1,262 39.6 30.5 12.1 8.3 2.5 0.0 0.0 0.1 2,467.753 8,030.055 6.39 64,727.1 Macao SAR, China 64.3 36.8 115,441 66,063 73.8 857.6 632.9 231.9 132.7 0.1 0.1 0.0 4.589 8.018 0.56 295.0 Malaysia 606.1 289.0 20,926 9,979 61.5 155.5 95.6 42.0 20.0 0.7 0.4 0.4 1.459 3.060 28.96 884.5 Maldives 3.7 2.2 11,392 6,653 75.3 84.6 63.7 22.9 13.4 0.0 0.0 0.0 8.527 14.602 0.33 31.6 Mongolia 23.4 9.9 8,719 3,701 54.7 64.8 35.5 17.5 7.4 0.0 0.0 0.0 537.127 1,265.516 2.68 12,546.8 Myanmar 192.1 55.2 3,181 914 37.0 23.6 8.8 6.4 1.8 0.2 0.1 0.9 234.974 817.917 60.38 45,128.0 Nepal 58.9 19.6 2,221 739 42.9 16.5 7.1 4.5 1.5 0.1 0.0 0.4 24.628 74.020 26.49 1,449.5 Pakistan 788.1 222.2 4,450 1,255 36.4 33.1 12.0 8.9 2.5 0.9 0.3 2.6 24.346 86.343 177.11 19,187.9 Philippines 543.7 224.1 5,772 2,379 53.2 42.9 22.8 11.6 4.8 0.6 0.3 1.4 17.854 43.313 94.19 9,706.3 Singapore 374.8 265.6 72,296 51,242 91.4 537.1 490.9 145.2 102.9 0.4 0.4 0.1 0.891 1.258 5.18 334.1 Sri Lanka 169.3 59.2 8,111 2,836 45.1 60.3 27.2 16.3 5.7 0.2 0.1 0.3 38.654 110.565 20.87 6,542.7 Taiwan, China 907.1 465.2 39,059 20,030 66.1 290.2 191.9 78.5 40.2 1.0 0.7 0.3 15.112 29.469 23.22 13,709.1 Thailand 899.0 364.7 13,299 5,395 52.3 98.8 51.7 26.7 10.8 1.0 0.5 1.0 12.370 30.492 67.60 11,120.5 Vietnam 414.3 135.5 4,717 1,543 42.2 35.0 14.8 9.5 3.1 0.5 0.2 1.3 6,709.192 20,509.750 87.84 2,779,880.2 Total (23) 27,235.6 12,604.3 7,621 3,527 59.7 56.6 33.8 15.3 7.1 30.0 17.9 53.1 n.a. n.a. 3,573.72 n.a. Presentation and Analysis of Results 25 Table 2.1 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expendi- (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion ture in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) COMMONWEALTH OF INDEPENDENT STATES Armenia 20.2 10.1 6,696 3,363 64.8 49.7 32.2 13.5 6.8 0.0 0.0 0.0 187.095 372.501 3.02 3,777.9 Azerbaijan 144.5 66.0 15,963 7,285 58.8 118.6 69.8 32.1 14.6 0.2 0.1 0.1 0.360 0.790 9.05 52.1 Belarus 157.3 53.0 16,603 5,596 43.5 123.3 53.6 33.4 11.2 0.2 0.1 0.1 1,889.308 5,605.840 9.47 297,157.7 Kazakhstan 343.9 188.0 20,772 11,358 70.5 154.3 108.8 41.7 22.8 0.4 0.3 0.2 80.171 146.620 16.56 27,571.9 Kyrgyz Republic 16.1 6.2 3,062 1,178 49.6 22.7 11.3 6.2 2.4 0.0 0.0 0.1 17.757 46.144 5.26 286.0 Moldova 14.9 7.0 4,179 1,971 60.8 31.0 18.9 8.4 4.0 0.0 0.0 0.1 5.535 11.739 3.56 82.3 f Russian Federation 3,216.9 1,901.0 22,502 13,298 76.2 167.2 127.4 45.2 26.7 3.5 2.7 2.1 17.346 29.352 142.96 55,799.6 Tajikistan 17.3 6.5 2,243 846 48.7 16.7 8.1 4.5 1.7 0.0 0.0 0.1 1.740 4.610 7.71 30.1 Ukraine 379.1 163.4 8,295 3,575 55.6 61.6 34.3 16.7 7.2 0.4 0.2 0.7 3.434 7.968 45.71 1,302.1 Total (9) 4,310.3 2,401.3 17,716 9,870 71.8 131.6 94.6 35.6 19.8 4.8 3.4 3.6 n.a. n.a. 243.29 n.a. EUROSTAT-OECD Albania 28.2 12.6 9,963 4,467 57.8 74.0 42.8 20.0 9.0 0.0 0.0 0.0 45.452 101.372 2.83 1,282.3 Australia 956.0 1,490.0 42,000 65,464 201.0 312.0 627.2 84.4 131.5 1.1 2.1 0.3 1.511 0.969 22.76 1,444.5 Austria 360.5 416.0 42,978 49,590 148.8 319.3 475.1 86.3 99.6 0.4 0.6 0.1 0.830 0.719 8.39 299.2 Belgium 440.1 513.3 40,093 46,759 150.4 297.9 448.0 80.5 93.9 0.5 0.7 0.2 0.839 0.719 10.98 369.3 Bosnia and Herzegovina 37.0 19.0 9,629 4,957 66.4 71.5 47.5 19.3 10.0 0.0 0.0 0.1 0.724 1.407 3.84 26.8 Bulgaria 114.1 53.5 15,522 7,284 60.5 115.3 69.8 31.2 14.6 0.1 0.1 0.1 0.660 1.407 7.35 75.3 Canada 1,416.2 1,778.3 41,069 51,572 161.9 305.1 494.1 82.5 103.6 1.6 2.5 0.5 1.243 0.990 34.48 1,759.7 Chile 349.1 251.2 20,216 14,546 92.8 150.2 139.4 40.6 29.2 0.4 0.4 0.3 348.017 483.668 17.27 121,492.7 Croatia 86.8 61.7 20,308 14,429 91.6 150.9 138.2 40.8 29.0 0.1 0.1 0.1 3.802 5.351 4.28 330.2 Cyprus 26.6 24.9 31,229 29,208 120.6 232.0 279.8 62.7 58.7 0.0 0.0 0.0 0.673 0.719 0.85 17.9 Czech Republic 283.9 216.1 27,045 20,592 98.2 200.9 197.3 54.3 41.4 0.3 0.3 0.2 13.468 17.689 10.50 3,823.4 Denmark 233.0 334.3 41,843 60,030 185.0 310.9 575.1 84.1 120.6 0.3 0.5 0.1 7.689 5.360 5.57 1,791.8 Estonia 30.9 22.5 23,088 16,821 93.9 171.5 161.1 46.4 33.8 0.0 0.0 0.0 0.524 0.719 1.34 16.2 Finland 208.0 262.3 38,611 48,686 162.6 286.8 466.4 77.6 97.8 0.2 0.4 0.1 0.907 0.719 5.39 188.7 France 2,369.6 2,782.2 36,391 42,728 151.4 270.4 409.3 73.1 85.8 2.6 4.0 1.0 0.845 0.719 65.11 2,001.4 Germany 3,352.1 3,628.1 40,990 44,365 139.6 304.5 425.0 82.3 89.1 3.7 5.2 1.2 0.779 0.719 81.78 2,609.9 Greece 300.8 289.9 26,622 25,654 124.3 197.8 245.8 53.5 51.5 0.3 0.4 0.2 0.693 0.719 11.30 208.5 Hungary 223.5 137.5 22,413 13,790 79.3 166.5 132.1 45.0 27.7 0.2 0.2 0.1 123.650 200.966 9.97 27,635.4 Iceland 12.2 14.0 38,226 43,969 148.3 284.0 421.2 76.8 88.3 0.0 0.0 0.0 133.563 116.118 0.32 1,628.7 Ireland 196.6 226.0 42,942 49,383 148.3 319.0 473.1 86.3 99.2 0.2 0.3 0.1 0.827 0.719 4.58 162.6 Israel 234.2 258.2 30,168 33,259 142.2 224.1 318.6 60.6 66.8 0.3 0.4 0.1 3.945 3.578 7.76 923.9 Italy 2,056.7 2,197.0 33,870 36,180 137.7 251.6 346.6 68.0 72.7 2.3 3.1 0.9 0.768 0.719 60.72 1,580.4 Japan 4,379.8 5,897.0 34,262 46,131 173.6 254.5 441.9 68.8 92.7 4.8 8.4 1.9 107.454 79.807 127.83 470,623.2 Korea, Rep. 1,445.3 1,114.5 29,035 22,388 99.4 215.7 214.5 58.3 45.0 1.6 1.6 0.7 854.586 1,108.290 49.78 1,235,160.5 Latvia 41.1 28.1 19,994 13,658 88.1 148.5 130.8 40.2 27.4 0.0 0.0 0.0 0.347 0.508 2.06 14.3 Lithuania 68.2 43.0 22,521 14,212 81.4 167.3 136.2 45.2 28.5 0.1 0.1 0.0 1.567 2.484 3.03 106.9 Luxembourg 46.1 58.0 88,670 111,689 162.4 658.8 1070.0 178.1 224.4 0.1 0.1 0.0 0.906 0.719 0.52 41.7 26 Purchasing Power Parities and the Real Size of World Economies Table 2.1 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expendi- (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion ture in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) Macedonia, FYR 24.6 10.4 11,957 5,050 54.5 88.8 48.4 24.0 10.1 0.0 0.0 0.0 18.680 44.226 2.06 459.8 Malta 11.9 9.2 28,608 22,201 100.1 212.5 212.7 57.5 44.6 0.0 0.0 0.0 0.558 0.719 0.41 6.6 Mexico 1,894.6 1,170.1 16,377 10,115 79.6 121.7 96.9 32.9 20.3 2.1 1.7 1.7 7.673 12.423 115.68 14,536.9 Montenegro 8.8 4.5 14,128 7,244 66.1 105.0 69.4 28.4 14.6 0.0 0.0 0.0 0.369 0.719 0.62 3.2 Netherlands 720.3 832.8 43,150 49,888 149.1 320.6 477.9 86.7 100.2 0.8 1.2 0.2 0.832 0.719 16.69 599.0 New Zealand 137.6 161.5 31,172 36,591 151.4 231.6 350.5 62.6 73.5 0.2 0.2 0.1 1.486 1.266 4.41 204.5 Norway 306.5 490.5 61,879 99,035 206.4 459.7 948.8 124.3 198.9 0.3 0.7 0.1 8.973 5.606 4.95 2,750.0 Poland 838.0 515.5 21,753 13,382 79.3 161.6 128.2 43.7 26.9 0.9 0.7 0.6 1.823 2.964 38.53 1,528.1 Portugal 272.7 237.9 25,672 22,396 112.5 190.7 214.6 51.6 45.0 0.3 0.3 0.2 0.628 0.719 10.62 171.1 Romania 344.8 182.6 16,146 8,549 68.3 119.9 81.9 32.4 17.2 0.4 0.3 0.3 1.615 3.049 21.35 556.7 Russian Federationf 3,216.9 1,901.0 22,502 13,298 76.2 167.2 127.4 45.2 26.7 3.5 2.7 2.1 17.346 29.352 142.96 55,799.6 Serbia 86.1 43.8 11,854 6,027 65.6 88.1 57.7 23.8 12.1 0.1 0.1 0.1 37.288 73.338 7.26 3,208.6 Slovak Republic 135.7 95.9 25,130 17,762 91.1 186.7 170.2 50.5 35.7 0.1 0.1 0.1 0.508 0.719 5.40 69.0 Slovenia 57.8 50.3 28,156 24,480 112.1 209.2 234.5 56.6 49.2 0.1 0.1 0.0 0.625 0.719 2.05 36.1 Spain 1,483.2 1,454.5 32,156 31,534 126.5 238.9 302.1 64.6 63.3 1.6 2.1 0.7 0.705 0.719 46.13 1,046.3 Sweden 394.6 535.8 41,761 56,704 175.1 310.3 543.2 83.9 113.9 0.4 0.8 0.1 8.820 6.496 9.45 3,480.5 Switzerland 405.9 659.9 51,582 83,854 209.6 383.2 803.3 103.6 168.4 0.4 0.9 0.1 1.441 0.887 7.87 585.1 Turkey 1,314.9 771.7 17,781 10,435 75.7 132.1 100.0 35.7 21.0 1.5 1.1 1.1 0.987 1.682 73.95 1,297.7 United Kingdom 2,201.4 2,461.8 35,091 39,241 144.2 260.7 375.9 70.5 78.8 2.4 3.5 0.9 0.698 0.624 62.74 1,536.9 United States 15,533.8 15,533.8 49,782 49,782 129.0 369.8 476.9 100.0 100.0 17.1 22.1 4.6 1.000 1.000 312.04 15,533.8 Total (47) 48,686.6 49,253.0 33,675 34,067 130.5 250.2 326.4 67.6 68.4 53.7 70.1 21.5 n.a. n.a. 1,445.76 n.a. LATIN AMERICA Bolivia 56.4 23.9 5,557 2,360 54.8 41.3 22.6 11.2 4.7 0.1 0.0 0.2 2.946 6.937 10.15 166.1 Brazil 2,816.3 2,476.6 14,639 12,874 113.4 108.8 123.3 29.4 25.9 3.1 3.5 2.9 1.471 1.673 192.38 4,143.0 Colombia 535.0 336.3 11,360 7,142 81.1 84.4 68.4 22.8 14.3 0.6 0.5 0.7 1,161.910 1,848.139 47.09 621,615.0 Costa Rica 59.8 41.0 13,030 8,935 88.4 96.8 85.6 26.2 17.9 0.1 0.1 0.1 346.738 505.664 4.59 20,748.0 Cubag … … … … 41.5 … … … … … … … 0.322 1.000 11.17 … Dominican Republic 109.0 55.6 10,858 5,541 65.8 80.7 53.1 21.8 11.1 0.1 0.1 0.1 19.449 38.109 10.04 2,119.3 Ecuador 151.6 79.8 9,932 5,226 67.9 73.8 50.1 20.0 10.5 0.2 0.1 0.2 0.526 1.000 15.27 79.8 El Salvador 46.0 23.1 7,357 3,701 64.9 54.7 35.5 14.8 7.4 0.1 0.0 0.1 0.503 1.000 6.25 23.1 Guatemala 102.4 47.7 6,971 3,247 60.1 51.8 31.1 14.0 6.5 0.1 0.1 0.2 3.626 7.785 14.69 371.3 Haiti 15.6 7.3 1,557 734 60.8 11.6 7.0 3.1 1.5 0.0 0.0 0.1 19.108 40.523 10.01 297.7 Honduras 33.8 17.7 4,349 2,282 67.7 32.3 21.9 8.7 4.6 0.0 0.0 0.1 9.915 18.895 7.77 335.0 Nicaragua 24.2 9.6 4,111 1,635 51.3 30.5 15.7 8.3 3.3 0.0 0.0 0.1 8.919 22.424 5.89 216.1 Panama 57.2 31.3 15,369 8,411 70.6 114.2 80.6 30.9 16.9 0.1 0.0 0.1 0.547 1.000 3.72 31.3 Paraguay 47.2 25.2 7,193 3,836 68.8 53.4 36.8 14.4 7.7 0.1 0.0 0.1 2,227.340 4,176.066 6.57 105,203.2 Peru 327.2 180.7 10,981 6,066 71.2 81.6 58.1 22.1 12.2 0.4 0.3 0.4 1.521 2.754 29.80 497.8 Uruguay 58.7 46.4 17,343 13,722 102.0 128.8 131.5 34.8 27.6 0.1 0.1 0.1 15.282 19.314 3.38 896.8 Presentation and Analysis of Results 27 Table 2.1 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expendi- (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion ture in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) Venezuela, RB 500.3 316.5 16,965 10,731 81.6 126.0 102.8 34.1 21.6 0.6 0.5 0.4 2.713 4.289 29.49 1,357.5 Total (17) 4,940.8 3,719.1 12,443 9,366 97.1 92.4 89.7 25.0 18.8 5.5 5.3 5.9 n.a. n.a. 397.09 n.a. CARIBBEAN Anguilla 0.4 0.3 27,274 20,982 99.2 202.6 201.0 54.8 42.1 0.0 0.0 0.0 2.077 2.700 0.01 0.8 Antigua and Barbuda 1.8 1.1 20,540 13,172 82.7 152.6 126.2 41.3 26.5 0.0 0.0 0.0 1.731 2.700 0.09 3.0 Aruba 3.7 2.6 36,017 25,355 90.8 267.6 242.9 72.3 50.9 0.0 0.0 0.0 1.260 1.790 0.10 4.6 Bahamas, The 8.3 7.9 22,639 21,490 122.4 168.2 205.9 45.5 43.2 0.0 0.0 0.0 0.949 1.000 0.37 7.9 Barbados 4.3 4.4 15,354 15,483 130.0 114.1 148.3 30.8 31.1 0.0 0.0 0.0 2.017 2.000 0.28 8.7 Belize 2.6 1.5 8,212 4,721 74.1 61.0 45.2 16.5 9.5 0.0 0.0 0.0 1.150 2.000 0.32 3.0 Bermuda 3.6 5.6 54,899 85,839 201.6 407.9 822.4 110.3 172.4 0.0 0.0 0.0 1.564 1.000 0.06 5.6 Bonaireh … … … … … … … … … … … … … 1.000 0.02 … Cayman Islands 2.8 3.2 49,686 56,883 147.6 369.1 544.9 99.8 114.3 0.0 0.0 0.0 0.959 0.838 0.06 2.7 Curaçao 4.2 3.0 27,781 20,055 93.1 206.4 192.1 55.8 40.3 0.0 0.0 0.0 1.292 1.790 0.15 5.4 Dominica 0.7 0.5 9,983 6,881 88.9 74.2 65.9 20.1 13.8 0.0 0.0 0.0 1.861 2.700 0.07 1.3 Grenada 1.2 0.8 11,221 7,410 85.2 83.4 71.0 22.5 14.9 0.0 0.0 0.0 1.783 2.700 0.11 2.1 Jamaica 22.9 14.5 8,329 5,248 81.3 61.9 50.3 16.7 10.5 0.0 0.0 0.0 54.122 85.892 2.75 1,241.8 Montserrat 0.1 0.1 15,762 11,343 92.8 117.1 108.7 31.7 22.8 0.0 0.0 0.0 1.943 2.700 0.01 0.2 St. Kitts and Nevis 1.1 0.7 20,582 13,744 86.1 152.9 131.7 41.3 27.6 0.0 0.0 0.0 1.803 2.700 0.05 2.0 St. Lucia 1.8 1.2 9,893 6,755 88.1 73.5 64.7 19.9 13.6 0.0 0.0 0.0 1.844 2.700 0.18 3.3 St. Vincent and the Grenadines 1.1 0.7 9,883 6,191 80.8 73.4 59.3 19.9 12.4 0.0 0.0 0.0 1.691 2.700 0.11 1.8 Sint Maarten 1.2 1.0 32,972 25,402 99.3 245.0 243.4 66.2 51.0 0.0 0.0 0.0 1.379 1.790 0.04 1.7 Suriname 7.8 4.4 14,463 8,082 72.1 107.4 77.4 29.1 16.2 0.0 0.0 0.0 1.826 3.268 0.54 14.3 Trinidad and Tobago 38.3 23.5 28,743 17,660 79.2 213.5 169.2 57.7 35.5 0.0 0.0 0.0 3.938 6.409 1.33 150.9 Turks and Caicos Islands 0.7 0.7 20,878 22,971 141.9 155.1 220.1 41.9 46.1 0.0 0.0 0.0 1.100 1.000 0.03 0.7 Virgin Islands, British 0.9 0.9 30,290 32,580 138.7 225.0 312.1 60.8 65.4 0.0 0.0 0.0 1.076 1.000 0.03 0.9 Total (22) 109.3 78.4 16,351 11,732 92.5 121.5 112.4 32.8 23.6 0.1 0.1 0.1 n.a. n.a. 6.69 n.a. WESTERN ASIA Bahrain 51.8 28.9 43,360 24,200 72.0 322.1 231.8 87.1 48.6 0.1 0.0 0.0 0.211 0.378 1.20 10.9 c Egypt, Arab Rep. 843.8 229.9 10,599 2,888 35.1 78.7 27.7 21.3 5.8 0.9 0.3 1.2 1.625 5.964 79.62 1,371.1 Iraq 371.0 159.8 11,130 4,794 55.5 82.7 45.9 22.4 9.6 0.4 0.2 0.5 516.521 1,199.200 33.34 191,652.9 Jordan 69.8 28.8 11,169 4,615 53.3 83.0 44.2 22.4 9.3 0.1 0.0 0.1 0.293 0.710 6.25 20.5 Kuwait 257.7 160.6 84,058 52,379 80.4 624.5 501.8 168.9 105.2 0.3 0.2 0.0 0.172 0.276 3.07 44.3 Oman 140.4 70.0 42,619 21,234 64.2 316.6 203.4 85.6 42.7 0.2 0.1 0.0 0.192 0.385 3.30 26.9 Qatar 258.1 171.0 146,521 97,091 85.4 1,088.5 930.1 294.3 195.0 0.3 0.2 0.0 2.419 3.650 1.76 624.2 Saudi Arabia 1,366.7 669.5 48,163 23,594 63.2 357.8 226.0 96.7 47.4 1.5 1.0 0.4 1.837 3.750 28.38 2,510.6 Sudand 152.4 70.0 3,608 1,656 59.2 26.8 15.9 7.2 3.3 0.2 0.1 0.6 1.224 2.667 42.25 186.6 United Arab Emirates 503.2 348.6 60,886 42,182 89.3 452.3 404.1 122.3 84.7 0.6 0.5 0.1 2.544 3.673 8.26 1,280.2 28 Purchasing Power Parities and the Real Size of World Economies Table 2.1 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expendi- (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion ture in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) West Bank and Gaza 16.0 9.8 3,833 2,345 78.9 28.5 22.5 7.7 4.7 0.0 0.0 0.1 2.189 3.578 4.17 35.0 Yemen, Rep. 88.6 31.4 3,716 1,318 45.7 27.6 12.6 7.5 2.6 0.1 0.0 0.4 75.818 213.800 23.83 6,714.9 Total (12) 4,119.5 1,978.3 17,499 8,403 61.9 130.0 80.5 35.2 16.9 4.5 2.8 3.5 n.a. n.a. 235.41 n.a. SINGLETONS Georgia 28.3 14.4 6,343 3,231 65.7 47.1 31.0 12.7 6.5 0.0 0.0 0.1 0.859 1.686 4.47 24.3 Iran, Islamic Rep. 1,314.2 576.3 17,488 7,669 56.5 129.9 73.5 35.1 15.4 1.4 0.8 1.1 4,657.463 10,621.000 75.15 6,121,004.0 Total (2) 1,342.6 590.7 16,863 7,420 56.7 125.3 71.1 33.9 14.9 1.5 0.8 1.2 n.a. n.a. 79.62 n.a. i WORLD (179) 90,646.6 70,294.6 13,460 10,438 100.0 100.0 100.0 27.0 21.0 100.0 100.0 100.0 n.a. n.a. 6,734.36 n.a. Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; PPP = purchasing power parity; XR = exchange rate; ... = data suppressed because of incompleteness. a. All shares are rounded to one decimal place. More precision can be found in the Excel version of the table, which can be downloaded from the ICP website. b. All exchange rates and PPPs are rounded to three decimal places. More precision can be found in the Excel version of the table, which can be downloaded from the ICP website. c. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. d. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. e. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China were estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. f. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. g. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. h. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. i. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. Presentation and Analysis of Results 29 Table 2.2 Nominal Expenditures in National Currency Units, ICP 2011 Furnishings, Alcoholic Housing, household EXPENDITURES Actual beverages, water, equipment (national currency Gross individual Food and tobacco, Clothing electricity, and Recreation units, billions) domestic consump- nonalcoholic and and gas, and mainte- Communi- and Economy product tion beverages narcotics footwear other fuels nance Health Transport cation culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) AFRICA Algeria 14,481.0 6,515.4 1,955.5 111.9 190.1 318.1 161.5 460.8 787.3 369.0 165.7 623.0 Angola 9,767.6 5,929.1 2,433.6 257.3 299.5 622.3 330.8 311.4 318.2 61.1 126.8 289.8 Benin 3,439.8 2,779.0 1,339.9 80.4 117.9 283.0 75.1 94.7 202.0 84.1 41.8 142.6 Botswana 102.5 56.0 10.0 4.2 3.4 6.2 3.3 2.9 9.0 1.4 1.5 7.1 Burkina Faso 4,868.5 3,294.3 1,686.5 211.1 68.9 364.0 143.5 122.9 212.9 108.7 76.9 97.5 Burundi 2,599.9 2,424.1 1,058.2 334.0 23.5 374.3 21.6 67.9 158.9 27.4 25.2 134.1 Cameroon 12,545.7 9,829.0 4,521.7 259.2 811.5 897.1 903.8 149.7 798.9 149.1 151.4 224.0 Cape Verde 149.0 105.3 36.6 5.0 2.9 20.8 7.5 5.7 7.3 3.6 1.0 8.6 Central African Republic 1,029.7 951.6 545.3 86.6 68.4 46.7 49.1 14.5 34.2 8.2 16.1 28.1 Chad 5,725.3 3,931.6 1,890.1 182.3 88.4 369.8 263.3 276.1 367.7 148.2 90.6 55.7 Comoros 95.4 94.2 48.4 0.3 2.9 29.3 3.6 0.8 1.9 0.5 1.0 2.3 Congo, Rep. 6,982.5 1,729.3 634.4 71.1 46.3 227.2 59.6 135.7 141.0 89.9 47.2 129.4 Congo, Dem. Rep. 23,146.1 14,896.2 8,177.3 429.9 696.0 1,778.8 517.8 666.2 386.1 169.1 193.8 635.2 Côte d’Ivoire 12,275.5 8,766.0 3,727.4 276.3 304.3 857.7 724.1 372.1 957.3 251.7 304.4 375.2 Djibouti 205.3 146.7 44.2 11.5 4.3 45.9 8.2 4.7 9.1 0.4 1.7 9.5 Egypt, Arab Rep.a 1,371.1 1,090.5 457.0 35.4 65.9 142.3 52.7 99.5 64.4 27.8 32.4 72.2 Equatorial Guinea 8,367.3 1,076.8 408.2 24.5 32.5 152.4 40.9 101.0 86.3 40.4 19.9 52.6 Ethiopia 506.1 409.2 151.9 10.0 21.0 66.9 39.2 33.5 6.7 1.6 1.9 14.0 Gabon 8,046.1 3,066.5 921.4 173.3 155.1 439.6 139.5 210.5 257.1 136.4 69.8 160.4 Gambia, The 26.6 21.2 9.0 0.6 1.5 1.5 0.5 3.2 0.6 0.5 0.7 1.8 Ghana 59.8 40.0 14.9 0.6 5.7 4.0 2.8 1.4 2.6 0.6 0.4 5.5 Guinea 33,128.3 18,673.4 10,798.4 273.7 1,286.3 1,491.0 724.8 1,360.6 1,024.3 30.3 152.1 594.4 Guinea-Bissau 464.7 318.1 162.3 5.3 25.6 43.7 22.5 7.8 22.6 1.7 13.8 6.0 Kenya 3,048.9 2,669.6 913.5 129.9 65.9 208.1 120.5 193.7 271.0 81.5 90.9 385.2 Lesotho 18.3 20.2 5.2 0.5 2.5 2.1 1.8 0.9 0.7 0.6 0.7 1.9 Liberia 1.1 1.3 0.3 0.0 0.2 0.3 0.1 0.0 0.0 0.0 0.0 0.2 Madagascar 20,276.4 18,408.8 8,046.8 559.3 1,188.1 1,133.5 2,458.7 324.7 2,376.6 160.2 773.7 649.6 Malawi 1,140.8 1,125.8 549.7 54.4 29.3 122.9 114.3 44.5 87.5 18.9 26.3 56.7 Mali 5,024.5 3,352.6 1,559.4 47.3 193.2 326.5 199.5 132.8 444.4 74.7 133.3 146.6 Mauritania 1,309.4 766.3 461.7 7.3 25.7 72.9 21.6 30.6 33.2 29.6 7.4 57.1 Mauritius 323.0 255.2 73.8 21.3 14.9 39.4 20.4 12.6 34.4 7.8 16.6 20.4 Morocco 802.6 536.6 182.9 17.1 21.8 74.3 24.7 33.2 47.8 32.8 23.6 61.3 Mozambique 364.7 313.2 161.5 13.6 15.1 22.8 8.8 8.9 26.3 3.8 8.2 21.6 Namibia 90.6 64.8 13.0 2.6 3.1 12.4 4.6 7.2 2.6 0.5 2.6 9.1 Niger 3,025.5 2,427.9 1,013.4 54.2 187.3 245.0 117.2 98.6 184.0 56.5 133.1 79.4 Nigeria 38,017.0 24,474.5 9,243.1 345.1 3,537.5 2,504.4 1,727.1 777.3 1,628.3 381.1 262.9 3,122.0 Rwanda 3,814.4 3,313.2 1,586.9 111.0 109.7 546.5 107.1 86.5 213.4 40.1 55.0 173.3 30 Purchasing Power Parities and the Real Size of World Economies Individual Miscella- Individual Individual Collective consumption neous consumption consumption consumption Gross Changes in Balance expenditure Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports by households and and purchases by by by capital and Construc- Other and and Domestic without hotels services abroad households government government formation equipment tion products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 153.6 1,218.9 0.0 4,552.7 1,962.7 1,337.8 4,617.7 1,952.7 2,403.6 261.5 494.2 1,515.9 12,965.1 4,430.2 174.3 704.1 0.0 4,957.5 971.5 2,560.1 1,669.2 519.1 1,073.7 76.4 27.0 −417.8 10,185.4 4,815.0 258.9 85.4 −26.9 2,631.4 147.6 252.4 712.9 244.9 460.0 8.0 29.5 −334.1 3,773.8 2,453.1 2.2 4.7 0.0 48.6 7.4 12.0 33.6 13.9 19.4 0.4 6.9 −6.0 108.5 45.4 109.6 93.2 −1.3 3,169.0 125.4 741.4 802.6 329.6 407.8 65.2 375.8 −345.7 5,214.2 2,986.8 100.2 57.4 41.4 2,244.6 179.5 333.2 492.3 215.5 249.5 27.3 18.3 −667.9 3,267.9 1,906.9 658.6 223.3 80.9 9,519.1 309.8 1,147.4 2,582.6 1,202.8 1,319.5 60.4 1.0 −1,014.3 13,560.0 8,963.4 12.9 6.6 −13.1 93.0 12.3 15.1 69.8 25.2 41.8 2.8 1.4 −42.6 191.6 81.2 18.4 36.0 0.0 925.6 26.1 46.7 157.7 45.2 85.4 27.1 0.0 −126.4 1,156.1 917.7 29.5 86.2 83.8 3,811.5 120.2 249.1 1,637.9 661.2 788.0 188.7 68.2 −161.5 5,886.9 3,535.2 0.0 3.0 0.3 93.6 0.6 21.9 12.8 5.7 6.4 0.6 3.6 −37.1 132.6 70.4 129.9 51.4 −33.8 1,552.7 176.6 335.4 2,406.5 390.8 1,993.4 22.3 0.0 2,511.4 4,471.1 1,445.3 898.9 347.2 0.0 14,337.3 558.8 2,675.7 5,460.5 2,002.8 3,258.6 199.0 21.2 92.6 23,053.5 13,418.0 125.7 395.8 94.1 8,294.8 471.3 966.1 1,373.7 487.4 820.0 66.3 −804.8 1,974.4 10,301.1 7,735.9 1.4 3.4 2.3 136.2 10.5 40.7 54.1 17.9 36.0 0.3 9.1 −45.3 250.6 110.4 34.3 77.2 −70.7 1,036.1 54.4 102.6 229.1 106.5 116.4 6.2 5.4 −56.5 1,427.6 940.1 36.9 59.0 22.2 1,004.4 72.3 152.2 2,765.0 1,416.0 902.8 446.2 0.0 4,373.3 3,994.0 922.7 19.3 43.2 0.0 397.6 11.6 32.0 131.0 48.6 59.3 23.0 10.4 −76.5 582.6 363.7 141.2 99.1 163.1 2,813.0 253.5 762.2 1,528.4 447.1 450.5 630.8 3.1 2,686.0 5,360.1 2,527.0 0.2 1.0 0.0 20.2 1.0 1.9 7.1 4.5 2.2 0.4 0.0 −3.6 30.2 19.7 0.0 1.5 0.0 36.8 3.3 6.7 15.3 8.7 5.7 0.9 1.1 −3.3 63.2 36.2 264.3 466.8 206.4 18,424.7 248.7 1,518.1 7,899.0 5,023.5 2,604.4 271.1 641.7 4,396.2 28,732.2 17,419.2 1.5 5.3 0.0 311.0 7.1 81.9 59.7 26.4 31.0 2.3 5.0 0.0 464.7 299.8 165.7 185.9 −142.2 2,304.9 364.7 256.2 610.8 335.3 273.7 1.8 16.2 −503.9 3,552.8 2,195.8 0.3 1.2 1.9 17.8 2.4 3.9 4.9 1.3 3.4 0.2 0.2 −10.8 29.2 16.3 0.0 0.1 0.0 1.3 0.0 0.1 0.1 0.1 0.0 0.0 0.1 −0.5 1.7 1.1 603.0 289.2 −154.6 17,830.7 578.0 1,463.3 3,527.8 1,567.2 1,791.9 168.7 0.0 −3,123.5 23,399.8 17,644.3 28.1 26.0 −32.8 1,062.3 63.5 78.4 189.6 140.2 37.7 11.7 −37.4 −215.6 1,356.4 985.0 61.1 85.3 −51.6 3,180.8 171.8 604.3 1,114.2 479.6 583.7 51.0 43.8 −90.5 5,115.0 2,959.0 5.2 13.9 0.1 678.7 87.6 199.3 752.1 370.1 315.6 66.4 −313.4 −94.8 1,404.2 634.2 8.8 16.0 −31.1 237.2 18.0 25.7 77.6 23.3 50.7 3.6 6.3 −41.8 364.7 219.8 31.0 35.1 −48.8 472.9 63.7 82.6 246.4 105.7 127.2 13.4 42.2 −105.2 907.8 427.7 2.9 15.8 3.8 290.6 22.6 26.3 64.9 21.9 42.8 0.2 7.7 −47.5 412.2 276.4 3.9 5.7 −2.5 55.9 8.9 14.0 19.3 7.1 11.6 0.7 −1.1 −6.4 97.0 47.8 119.8 143.0 −3.6 2,342.3 85.6 301.9 1,120.9 493.0 601.7 26.3 2.0 −827.3 3,852.8 2,223.2 10.9 924.8 9.9 22,840.8 1,633.7 3,346.2 3,908.3 2,215.4 1,454.7 238.2 2.3 6,285.6 31,731.3 22,468.3 102.9 118.8 61.8 3,181.4 131.8 346.0 817.9 178.6 601.8 37.5 0.0 −662.7 4,477.1 2,828.1 (continued) Presentation and Analysis of Results 31 Table 2.2 (Continued) Furnishings, Alcoholic Housing, household EXPENDITURES Actual beverages, water, equipment (national currency Gross individual Food and tobacco, Clothing electricity, and Recreation units, billions) domestic consump- nonalcoholic and and gas, and mainte- Communi- and Economy product tion beverages narcotics footwear other fuels nance Health Transport cation culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) São Tomé and Príncipe 4,375.5 5,117.2 2,793.7 230.9 201.0 483.0 172.9 202.0 500.8 65.0 74.4 198.1 Senegal 6,766.8 5,601.0 2,744.5 72.6 194.7 1,075.5 316.1 162.9 275.1 274.1 72.2 297.2 Seychelles 13.1 8.0 3.2 0.2 0.3 1.4 0.3 0.5 0.5 0.2 0.2 0.8 Sierra Leone 12,754.9 11,448.2 4,530.5 353.6 915.9 858.6 324.4 1,826.7 351.7 324.5 396.4 871.9 South Africa 2,917.5 1,992.4 353.1 87.6 86.0 271.4 122.0 220.7 257.5 51.3 81.3 213.0 Sudanb 186.6 130.9 67.7 0.9 5.8 19.2 8.5 1.7 10.7 2.1 3.0 4.3 Swaziland 29.7 26.8 12.2 0.2 1.5 3.6 2.8 1.7 2.1 0.3 1.1 2.2 Tanzania 37,533.0 25,647.6 16,914.0 171.1 1,708.1 1,822.3 1,115.7 899.9 989.0 17.9 274.6 1,230.2 Togo 1,739.2 1,539.4 667.2 36.1 76.5 119.8 69.3 100.2 86.0 36.1 19.8 103.2 Tunisia 64.7 48.2 10.6 1.5 3.3 6.8 2.9 3.4 6.9 1.7 1.6 3.8 Uganda 45,944.1 41,649.9 13,863.6 2,427.8 1,204.2 7,473.0 2,346.3 1,150.3 2,480.8 766.8 2,506.2 4,477.0 Zambia 101,104.8 55,896.0 32,622.8 449.3 3,508.4 6,652.1 851.2 2,876.9 760.9 1,443.9 387.2 3,471.5 Zimbabwe 8.9 8.5 4.7 0.3 0.5 0.5 0.2 0.2 0.6 0.0 0.2 0.6 Total (50) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. ASIA AND THE PACIFIC Bangladesh 9,702.9 7,299.2 3,715.3 151.8 437.2 1,255.4 236.1 266.7 305.6 35.0 52.9 394.6 Bhutan 85.9 44.4 13.0 1.1 3.3 7.8 0.8 5.0 4.2 1.1 2.7 3.9 Brunei Darussalam 21.0 5.0 0.9 0.0 0.2 0.6 0.2 0.3 0.7 0.3 0.4 0.8 Cambodia 52,068.7 43,880.6 20,093.0 1,664.1 837.5 6,511.2 797.6 3,096.9 3,281.9 108.9 1,218.0 2,967.4 Chinac 47,310.4 20,301.3 3,814.9 437.2 1,403.2 2,813.9 990.3 3,045.5 1,186.4 689.1 1,103.2 2,042.4 Fiji 6.7 5.2 1.5 0.2 0.1 1.3 0.5 0.3 0.4 0.0 0.2 0.3 Hong Kong SAR, China 1,936.1 1,289.9 139.8 13.7 56.3 244.9 71.4 108.3 90.2 27.8 144.4 45.4 India 86,993.1 51,479.1 14,485.2 1,541.0 3,621.4 6,619.7 1,920.3 2,395.6 7,737.4 533.9 773.7 2,306.2 Indonesia 7,422,781.2 4,321,509.5 1,635,156.2 74,477.8 161,475.9 879,768.0 116,939.2 144,792.2 295,717.5 83,173.0 83,913.8 319,157.1 Lao PDR 64,727.1 37,958.6 19,378.0 1,935.0 592.6 4,857.2 1,002.5 857.5 4,010.0 466.0 1,003.5 1,582.0 Macao SAR, China 295.0 69.0 6.6 0.5 4.2 10.5 1.4 4.9 6.0 1.9 7.1 5.0 Malaysia 884.5 474.5 80.7 7.0 8.7 70.1 20.8 27.9 62.5 28.5 18.7 49.8 Maldives 31.6 12.0 2.3 0.5 0.2 4.7 0.5 0.7 0.5 0.2 0.2 1.6 Mongolia 12,546.8 7,613.9 2,176.4 543.7 381.3 1,092.5 112.5 357.3 1,196.3 222.8 217.1 767.8 Myanmar 45,128.0 31,485.5 16,452.6 643.0 971.6 4,169.9 427.8 1,948.8 1,033.0 482.4 360.6 2,619.1 Nepal 1,449.5 1,164.0 652.5 38.2 30.4 150.7 21.3 48.9 36.7 16.4 29.3 66.0 Pakistan 19,187.9 16,296.8 7,200.2 154.4 757.4 3,159.5 534.4 1,014.2 1,044.8 271.1 181.1 775.2 Philippines 9,706.3 7,468.0 3,053.3 91.8 100.9 885.0 291.9 236.2 770.4 225.4 129.6 532.2 Singapore 334.1 143.2 8.9 2.6 3.8 26.1 7.2 12.1 17.9 2.7 15.5 13.3 Sri Lanka 6,542.7 5,025.1 2,126.6 374.1 149.6 682.7 122.6 259.9 390.0 95.2 69.9 276.8 Taiwan, China 13,709.1 8,835.7 1,040.6 175.7 375.4 1,461.2 391.6 842.5 918.4 314.1 842.1 768.9 Thailand 11,120.5 6,890.0 1,765.5 242.9 231.9 625.9 280.5 522.7 964.3 143.0 320.6 604.6 Vietnam 2,779,880.2 1,762,838.5 455,802.1 49,429.5 72,689.9 402,769.2 101,638.7 128,338.8 176,330.7 13,025.9 69,843.1 151,555.0 Total (23) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 32 Purchasing Power Parities and the Real Size of World Economies Individual Miscella- Individual Individual Collective consumption neous consumption consumption consumption Gross Changes in Balance expenditure Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports by households and and purchases by by by capital and Construc- Other and and Domestic without hotels services abroad households government government formation equipment tion products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 65.1 96.0 34.4 4,919.9 197.2 336.7 861.5 647.0 153.6 61.0 6.7 −1,946.6 6,322.1 4,650.4 50.6 215.2 −149.7 5,312.1 288.9 670.8 1,611.4 615.0 981.5 14.9 98.0 −1,214.5 7,981.3 4,740.3 0.1 0.2 0.0 6.9 1.0 2.7 4.5 1.8 2.4 0.2 0.8 −2.7 15.8 6.0 140.9 553.0 0.0 11,163.1 285.1 1,004.1 5,315.9 3,776.8 1,477.3 61.8 50.0 −5,063.2 17,818.1 10,839.6 41.4 226.9 −19.8 1,731.7 260.7 374.3 553.3 263.0 265.0 25.3 15.6 −18.0 2,935.6 1,545.7 2.9 3.4 0.7 129.9 1.0 11.7 41.6 21.7 19.9 0.0 4.9 −2.5 189.1 117.2 0.2 0.4 −1.7 25.1 1.7 2.8 2.8 1.1 1.3 0.4 0.0 −2.6 32.3 22.3 3.5 501.4 0.0 24,815.7 832.0 5,313.7 13,534.1 5,821.4 7,409.9 302.8 228.0 −7,190.4 44,723.4 24,741.9 125.6 164.3 −64.7 1,474.2 65.2 141.0 307.7 93.6 200.0 14.1 30.8 −279.7 2,018.9 1,417.7 4.6 3.0 −2.0 42.5 5.7 6.2 14.0 4.6 8.9 0.5 1.1 −4.8 69.5 37.2 1,187.7 1,766.1 0.0 37,758.9 3,891.0 756.4 11,341.5 3,281.1 7,541.0 519.4 144.4 −7,948.2 53,892.2 34,447.2 149.7 2,722.2 0.0 52,484.7 3,411.2 15,796.5 21,902.2 6,629.6 14,269.7 1,003.0 1,435.9 6,074.3 95,030.6 49,188.8 0.1 0.4 0.1 7.8 0.7 0.8 1.0 0.3 0.7 0.0 0.4 −1.8 10.6 7.5 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 165.8 282.8 0.0 7,154.3 144.9 359.8 2,748.6 652.8 2,059.8 36.0 53.1 −757.8 10,460.7 6,502.4 0.5 1.0 0.0 37.6 6.8 10.2 57.2 23.6 33.5 0.0 −0.3 −25.5 111.5 32.2 0.3 0.3 0.0 4.1 0.9 2.6 2.7 0.8 1.7 0.2 −0.1 10.7 10.3 3.6 2,101.9 1,202.0 0.0 41,431.0 2,449.5 1,931.4 6,035.3 2,966.8 3,002.6 65.9 277.9 −56.5 52,125.2 37,025.0 1,033.6 1,741.7 0.0 16,254.7 4,046.7 2,958.3 21,568.2 6,185.3 13,609.8 1,773.1 1,266.2 1,216.3 46,094.1 14,654.0 0.1 0.2 0.0 4.8 0.4 0.4 1.3 0.6 0.5 0.2 0.2 −0.3 7.1 3.8 129.6 218.1 0.0 1,224.8 65.0 103.5 455.0 200.6 214.0 40.5 11.7 76.0 1,860.1 1,017.4 1,283.5 8,261.0 0.0 48,648.2 2,830.9 7,196.2 26,908.2 10,274.4 15,618.4 1,015.4 6,344.1 −4,934.5 91,927.6 44,142.9 309,883.2 217,055.6 0.0 4,053,363.6 268,146.0 400,436.9 2,372,765.8 391,059.2 1,923,723.7 57,982.9 223,318.3 104,750.6 7,318,030.6 3,526,617.3 1,131.5 1,142.6 0.0 36,750.1 1,208.5 5,049.9 23,103.7 6,902.8 11,301.1 4,899.8 961.0 −2,346.2 67,073.2 34,671.0 13.1 7.8 0.0 60.5 8.5 12.4 36.6 8.5 27.8 0.3 4.2 172.8 122.2 52.2 39.1 60.7 0.0 418.3 56.3 58.8 197.2 71.3 98.3 27.6 8.7 145.3 739.2 379.2 0.2 0.3 0.0 10.2 1.8 5.6 15.9 6.1 9.8 0.0 0.0 −1.9 33.5 6.5 131.7 414.4 0.0 6,885.5 728.4 895.2 5,910.4 3,519.1 2,181.9 209.5 1,510.4 −3,383.2 15,930.0 5,949.8 1,417.3 959.3 0.0 28,760.0 2,725.5 1,895.4 12,061.2 5,872.0 5,231.0 958.1 5.7 −319.8 45,447.8 26,511.1 24.1 49.4 0.0 1,114.6 49.5 97.0 299.5 65.2 166.6 67.7 231.6 −342.6 1,792.1 993.5 166.3 1,038.1 0.0 15,712.2 584.6 1,356.4 2,481.8 796.6 1,186.4 498.8 307.0 −1,254.1 20,441.9 14,436.1 263.7 887.5 0.0 7,132.6 335.4 606.4 1,817.2 698.7 904.5 213.9 168.7 −354.0 10,060.3 6,521.9 14.8 18.2 0.0 130.2 13.0 21.6 79.4 29.6 46.7 3.1 −4.0 93.9 240.2 107.8 191.8 286.1 0.0 4,568.4 456.8 511.0 1,772.5 542.1 1,118.6 111.8 186.3 −952.3 7,494.9 4,143.2 473.4 1,231.8 0.0 8,235.4 600.3 1,096.3 2,866.0 1,334.2 1,297.3 234.5 −6.9 918.0 12,791.0 7,019.7 538.7 649.6 0.0 6,076.1 813.9 1,004.7 2,973.5 1,992.8 935.1 45.6 62.1 190.2 10,930.3 5,645.2 76,959.6 64,456.3 0.0 1,638,345.5 124,493.0 164,322.9 827,032.2 214,706.0 564,516.5 47,809.7 140,574.1 −114,887.5 2,894,767.7 1,388,272.7 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. (continued) Presentation and Analysis of Results 33 Table 2.2 (Continued) Furnishings, Alcoholic Housing, household EXPENDITURES Actual beverages, water, equipment (national currency Gross individual Food and tobacco, Clothing electricity, and Recreation units, billions) domestic consump- nonalcoholic and and gas, and mainte- Communi- and Economy product tion beverages narcotics footwear other fuels nance Health Transport cation culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) COMMONWEALTH OF INDEPENDENT STATES Armenia 3,777.9 3,356.4 1,830.7 151.9 116.7 270.7 46.1 205.4 173.2 178.6 76.7 149.6 Azerbaijan 52.1 21.4 7.9 0.5 2.0 1.7 1.1 0.9 2.2 1.2 0.7 1.6 Belarus 297,157.7 168,548.8 53,321.4 10,240.9 10,656.8 13,051.3 7,630.1 15,115.5 14,014.2 7,235.4 8,995.9 14,331.7 Kazakhstan 27,571.9 13,329.9 2,717.1 296.8 785.6 2,887.3 526.1 1,044.9 1,429.0 521.7 655.3 1,118.6 Kyrgyz Republic 286.0 267.8 101.3 12.2 19.2 19.8 9.4 13.7 28.1 17.3 11.3 21.6 Moldova 82.3 92.6 26.0 5.4 5.3 11.9 6.6 3.3 9.3 3.4 3.0 7.7 d Russian Federation 55,799.6 32,186.9 8,155.0 2,211.3 2,437.8 3,135.3 1,322.0 2,553.4 3,322.8 1,238.2 1,756.8 1,790.3 Tajikistan 30.1 34.6 15.3 0.1 3.0 2.1 1.2 1.6 2.7 2.1 0.7 1.4 Ukraine 1,302.1 1,030.6 337.7 59.6 54.8 110.8 37.7 90.5 106.9 21.3 42.3 91.5 Total (9) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. EUROSTAT-OECD Albania 1,282.3 1,094.3 413.5 29.1 41.8 133.6 72.5 62.4 55.6 21.9 25.8 36.0 Australia 1,444.5 928.0 80.4 28.5 26.1 182.4 35.7 117.7 81.2 19.3 93.1 76.5 Austria 299.2 197.3 16.6 5.7 9.9 35.3 10.8 20.8 22.0 3.3 19.1 15.8 Belgium 369.3 252.4 25.2 6.5 9.4 44.7 10.7 36.7 23.1 4.0 18.7 23.3 Bosnia and Herzegovina 26.8 25.0 7.2 1.6 1.0 3.2 1.3 2.1 2.1 0.7 1.2 1.4 Bulgaria 75.3 52.9 9.9 3.5 1.5 8.4 3.7 5.1 8.2 2.9 4.3 2.7 Canada 1,759.7 1,202.8 89.2 33.1 39.7 231.7 53.0 152.9 142.0 23.6 96.2 94.3 Chile 121,492.7 83,595.3 12,027.6 2,269.6 4,147.8 12,147.6 5,304.3 7,976.6 9,472.7 2,942.5 5,741.0 7,064.1 Croatia 330.2 233.4 44.4 14.9 10.1 41.1 12.3 27.6 22.5 7.6 23.6 18.6 Cyprus 17.9 13.7 1.7 0.6 0.8 2.4 0.6 1.2 1.5 0.4 1.1 1.3 Czech Republic 3,823.4 2,347.3 294.3 184.1 61.1 534.9 105.6 277.4 186.0 60.5 215.6 163.6 Denmark 1,791.8 1,236.6 97.6 30.4 39.7 249.4 42.9 160.9 105.1 14.6 107.2 113.7 Estonia 16.2 9.9 1.6 0.7 0.5 1.8 0.3 0.9 1.1 0.3 0.8 0.8 Finland 188.7 136.2 12.4 5.0 5.0 26.9 5.4 16.4 11.4 2.1 13.1 11.1 France 2,001.4 1,475.7 150.9 35.8 47.8 296.0 65.2 185.1 160.1 31.0 117.9 107.8 Germany 2,609.9 1,818.0 162.9 45.8 69.1 343.3 89.0 230.3 197.7 37.3 142.3 106.5 Greece 208.5 170.3 26.0 7.0 6.0 38.1 6.4 16.9 18.9 4.7 9.2 11.3 Hungary 27,635.4 17,717.0 2,582.8 1,120.6 431.1 3,294.8 652.2 2,012.8 1,952.3 563.5 1,356.4 1,219.7 Iceland 1,628.7 1,117.2 118.5 34.5 34.0 183.8 56.4 139.5 120.8 18.7 111.4 113.7 Ireland 162.6 99.2 7.6 4.1 3.1 18.5 3.2 14.6 9.7 2.2 5.9 7.7 Israel 923.9 642.2 84.5 13.3 15.5 128.3 32.1 55.1 82.7 20.6 40.6 66.3 Italy 1,580.4 1,156.1 139.4 26.5 73.2 216.2 69.5 138.4 123.0 23.3 78.3 68.6 Japan 470,623.2 340,953.4 38,436.2 7,607.6 8,858.4 70,934.6 14,061.2 36,104.6 30,162.8 9,624.9 25,592.3 17,222.5 Korea, Rep. 1,235,160.5 739,451.4 82,192.5 14,325.5 32,153.0 103,510.6 21,124.2 81,457.7 74,796.7 27,242.4 51,734.8 81,382.4 Latvia 14.3 10.0 1.7 0.7 0.4 2.0 0.3 0.7 1.3 0.3 0.8 0.7 Lithuania 106.9 78.7 16.4 5.2 4.1 11.0 4.0 7.8 10.2 1.6 5.1 5.2 Luxembourg 41.7 17.5 1.3 1.4 0.7 3.9 1.0 1.9 3.1 0.3 1.4 1.8 34 Purchasing Power Parities and the Real Size of World Economies Individual Miscella- Individual Individual Collective consumption neous consumption consumption consumption Gross Changes in Balance expenditure Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports by households and and purchases by by by capital and Construc- Other and and Domestic without hotels services abroad households government government formation equipment tion products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 39.7 105.2 11.8 3,161.0 195.4 293.0 982.7 163.5 793.3 25.9 37.3 −891.5 4,669.4 3,051.1 0.7 0.9 0.0 19.4 2.0 3.3 10.5 5.4 4.6 0.5 0.0 16.8 35.2 18.8 4,891.8 6,935.0 2,128.9 141,646.8 26,902.0 14,485.3 112,308.9 48,972.0 62,402.2 934.8 5,020.9 −3,206.2 300,363.9 136,878.2 459.5 885.8 2.1 11,791.9 1,538.0 1,403.9 5,771.6 1,662.2 3,757.3 352.1 1,176.7 5,889.8 21,682.1 9,779.0 10.4 11.2 −7.6 238.5 29.3 22.9 67.8 30.2 35.4 2.1 5.1 −77.5 363.5 234.0 1.4 8.0 1.3 79.5 13.0 3.5 19.2 6.1 11.6 1.5 0.7 −33.6 116.0 75.2 898.9 2,747.3 617.7 27,398.6 4,788.3 5,252.5 11,595.2 4,163.3 6,489.2 942.7 1,988.6 4,776.5 51,023.0 26,024.0 0.4 1.7 2.3 32.1 2.5 1.6 9.7 4.3 4.4 1.0 1.1 −17.0 47.0 31.6 22.7 55.9 −1.0 875.6 155.1 82.4 241.8 92.7 143.6 5.4 28.2 −80.9 1,383.0 821.4 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 27.6 61.3 113.0 1,029.6 64.7 70.6 423.8 89.2 325.1 9.6 −10.9 −295.7 1,578.0 947.0 54.2 136.3 −3.3 774.5 153.6 101.4 389.3 94.2 223.8 71.3 7.0 18.8 1,425.7 633.2 19.8 24.6 −6.3 163.9 33.5 23.3 63.5 24.3 33.0 6.3 6.1 9.0 290.3 141.7 11.5 35.7 2.9 194.7 57.7 32.6 76.5 28.6 41.0 6.9 4.7 3.1 366.2 164.5 1.6 2.3 −0.7 22.2 2.8 3.1 4.8 2.0 2.6 0.2 0.1 −6.3 33.0 20.7 3.2 3.3 −3.7 47.0 5.9 5.9 16.2 7.0 8.6 0.6 0.3 0.0 75.3 42.0 64.5 166.0 16.7 980.1 222.7 159.1 412.0 82.0 273.8 56.3 7.7 −21.9 1,781.6 789.9 3,510.0 11,215.6 −224.1 74,405.2 9,190.1 5,385.9 27,248.3 10,690.3 14,472.6 2,085.4 1,280.7 3,982.5 117,510.2 67,304.3 35.1 20.3 −44.6 197.8 35.5 29.8 63.3 20.5 37.9 4.9 4.0 −0.2 330.4 174.9 2.0 1.2 −1.1 12.1 1.6 2.0 3.0 0.9 2.0 0.1 0.0 −0.8 18.7 10.5 154.1 200.4 −90.2 1,935.2 412.2 380.4 922.6 409.5 462.0 51.1 14.5 158.6 3,664.8 1,613.8 44.7 228.4 2.0 872.4 364.2 144.0 310.9 108.9 157.3 44.7 6.3 93.9 1,697.8 700.3 0.6 0.9 −0.4 8.2 1.7 1.4 3.8 1.8 1.9 0.1 0.5 0.6 15.6 7.0 6.4 21.3 −0.3 105.2 31.0 15.2 36.6 8.8 24.6 3.2 2.0 −1.4 190.0 86.5 79.1 206.5 −7.5 1,155.3 320.5 169.5 400.0 108.2 248.8 42.9 15.5 −59.3 2,060.7 951.2 82.6 275.4 35.7 1,498.4 319.6 179.9 473.2 181.2 263.3 28.6 3.2 135.7 2,474.3 1,262.5 18.8 15.3 −8.2 155.6 14.7 21.5 31.6 12.8 16.6 2.2 2.0 −16.9 225.4 130.0 1,001.3 2,270.6 −741.1 14,725.9 2,991.1 2,824.3 4,950.0 2,073.6 2,579.8 296.6 359.3 1,784.8 25,850.6 12,890.9 69.6 117.6 −1.3 844.8 272.4 141.0 229.5 87.3 124.7 17.5 4.6 136.3 1,492.4 699.3 9.5 11.2 1.9 78.2 21.0 8.9 17.3 6.5 9.3 1.5 2.1 35.1 127.5 64.9 35.5 75.3 −7.6 529.2 113.0 99.8 188.8 60.5 91.3 37.0 −2.3 −4.6 928.5 428.7 97.8 116.5 −14.4 967.9 188.2 133.8 301.3 120.6 143.6 37.1 11.2 −22.1 1,602.5 818.5 18,231.3 61,586.4 2,530.5 284,784.3 56,169.1 40,034.2 96,872.1 37,812.0 45,646.5 13,413.6 −2,953.1 −4,283.4 474,906.7 225,972.2 51,650.2 107,940.1 9,941.3 655,386.6 84,064.8 105,486.9 340,101.0 120,249.7 192,753.0 27,098.3 25,181.4 24,939.8 1,210,220.7 583,407.8 0.4 0.7 0.0 8.9 1.1 1.4 3.0 1.3 1.7 0.1 0.5 −0.7 15.0 7.7 1.9 6.9 −0.6 67.1 11.6 8.4 19.3 6.3 11.3 1.6 3.4 −2.9 109.8 62.7 1.1 3.1 −3.3 13.3 4.3 2.7 7.7 2.9 4.4 0.5 1.1 12.7 29.1 10.3 (continued) Presentation and Analysis of Results 35 Table 2.2 (Continued) Furnishings, Alcoholic Housing, household EXPENDITURES Actual beverages, water, equipment (national currency Gross individual Food and tobacco, Clothing electricity, and Recreation units, billions) domestic consump- nonalcoholic and and gas, and mainte- Communi- and Economy product tion beverages narcotics footwear other fuels nance Health Transport cation culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) Macedonia, FYR 459.8 380.6 116.9 11.5 17.0 66.6 14.1 24.0 34.2 20.2 12.0 20.2 Malta 6.6 4.7 0.7 0.1 0.2 0.6 0.3 0.6 0.6 0.2 0.5 0.3 Mexico 14,536.9 10,539.2 2,246.1 253.0 287.9 1,985.4 547.3 661.7 1,801.4 358.2 443.5 547.2 Montenegro 3.2 3.0 1.0 0.1 0.1 0.4 0.3 0.2 0.4 0.2 0.1 0.1 Netherlands 599.0 374.0 31.5 8.3 14.3 66.2 15.8 46.8 34.1 11.1 30.8 30.3 New Zealand 204.5 146.7 17.6 6.4 5.5 28.5 6.0 18.0 14.5 3.9 13.5 11.8 Norway 2,750.0 1,519.8 137.6 44.3 55.3 224.8 59.2 202.8 155.7 27.2 152.5 116.1 Poland 1,528.1 1,092.1 174.2 59.5 40.7 226.2 41.7 105.1 92.9 27.2 83.2 81.6 Portugal 171.1 131.5 19.4 3.9 6.4 18.7 6.4 16.0 15.3 3.4 9.6 10.2 Romania 556.7 402.1 94.8 17.3 13.1 76.5 17.0 44.6 38.0 17.1 24.7 19.2 Russian Federationd 55,799.6 32,186.9 8,155.0 2,211.3 2,437.8 3,103.8 1,322.0 2,538.5 3,322.8 1,238.2 1,721.6 1,780.9 Serbia 3,208.6 2,879.5 681.7 137.3 93.3 567.0 95.4 300.2 334.2 111.9 147.1 149.9 Slovak Republic 69.0 45.7 7.0 1.8 1.6 10.2 2.4 4.3 3.1 1.5 4.2 2.9 Slovenia 36.1 25.2 3.3 1.2 1.2 4.3 1.3 2.9 3.3 0.7 2.2 2.2 Spain 1,046.3 741.8 88.7 18.6 33.6 132.5 30.2 85.7 72.9 17.6 61.4 54.2 Sweden 3,480.5 2,337.4 198.7 59.0 78.8 442.0 82.2 281.4 216.9 54.1 213.4 229.0 Switzerland 585.1 371.6 29.5 11.8 11.1 79.4 13.7 50.0 29.9 7.9 29.9 29.5 Turkey 1,297.7 1,022.7 222.9 32.6 52.0 186.3 75.9 78.4 159.9 27.9 42.9 50.8 United Kingdom 1,536.9 1,205.1 86.6 33.8 55.2 239.8 47.2 133.8 128.1 20.4 134.4 95.6 United States 15,533.8 11,667.0 698.4 207.6 366.0 1,962.8 429.5 2,300.0 1,079.1 246.7 996.1 930.9 Total (47) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. LATIN AMERICA Bolivia 166.1 104.0 35.1 1.6 2.2 11.1 7.4 9.0 17.8 1.1 1.1 6.3 Brazil 4,143.0 2,833.3 408.8 51.0 118.9 379.7 190.4 316.7 383.8 91.0 132.4 242.4 Colombia 621,615.0 422,979.0 70,269.0 11,791.0 24,695.0 60,636.0 16,114.0 31,460.5 46,840.0 16,804.0 19,893.0 36,552.5 Costa Rica 20,748.0 16,078.7 3,223.3 145.7 701.5 1,008.7 935.6 1,961.6 2,863.4 375.6 1,563.8 1,638.3 Cubae … … … … … … … … … … … … Dominican Republic 2,119.3 1,883.9 457.0 111.5 61.2 279.2 67.4 117.5 243.3 79.7 40.8 83.4 Ecuador 79.8 53.5 10.8 1.3 2.2 7.3 3.8 4.4 6.0 2.9 2.7 5.5 El Salvador 23.1 22.8 5.8 0.4 1.2 3.8 2.2 1.8 2.0 0.8 1.0 1.1 Guatemala 371.3 334.1 129.4 5.4 17.5 42.0 18.4 22.5 23.9 24.2 10.2 13.9 Haiti 297.7 337.5 197.1 7.8 23.2 38.0 11.3 11.3 17.4 1.4 8.0 14.4 Honduras 335.0 287.9 85.2 9.1 12.6 35.5 11.6 28.1 27.4 9.1 10.8 25.0 Nicaragua 216.1 181.4 47.3 5.1 5.2 24.2 10.0 19.5 22.2 6.2 6.9 12.9 Panama 31.3 20.7 3.5 0.1 1.3 4.1 1.5 1.5 2.7 0.7 1.1 1.2 Paraguay 105,203.2 80,072.8 22,129.6 1,013.0 4,162.6 7,226.3 6,471.4 6,500.1 6,862.1 2,949.0 5,181.8 7,436.4 Peru 497.8 311.2 70.5 6.9 19.4 32.9 15.4 20.1 33.2 12.2 18.5 26.2 Uruguay 896.8 677.3 125.1 15.9 30.5 129.3 37.5 81.7 49.9 26.7 22.8 44.1 36 Purchasing Power Parities and the Real Size of World Economies Individual Miscella- Individual Individual Collective consumption neous consumption consumption consumption Gross Changes in Balance expenditure Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports by households and and purchases by by by capital and Construc- Other and and Domestic without hotels services abroad households government government formation equipment tion products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 13.0 26.9 4.0 345.3 35.4 48.8 94.7 31.8 59.0 3.9 25.8 −90.2 550.0 305.1 0.8 0.6 −0.7 4.0 0.7 0.6 1.0 0.4 0.5 0.1 0.0 0.3 6.4 3.7 393.1 1,063.5 −48.9 9,640.8 898.4 794.4 3,165.0 974.6 2,125.7 64.8 221.2 −182.9 14,719.9 8,040.4 0.4 0.2 −0.6 2.7 0.3 0.4 0.6 0.2 0.4 0.0 0.0 −0.7 4.0 2.4 13.4 72.9 −1.5 271.8 102.2 65.1 106.9 33.0 60.4 13.4 1.7 51.4 547.6 228.6 8.6 15.4 −3.0 122.2 24.5 16.9 37.1 12.7 21.3 3.1 0.9 2.9 201.6 98.1 62.7 239.7 41.8 1,131.7 388.1 202.7 536.8 173.0 255.3 108.5 125.9 364.8 2,385.1 965.0 26.4 139.9 −6.5 933.9 158.2 116.5 308.7 116.0 173.5 19.2 28.4 −17.6 1,545.7 868.6 12.9 14.7 −5.3 113.0 18.5 15.5 30.8 9.2 18.9 2.7 0.8 −7.5 178.6 101.1 11.5 27.0 1.2 353.5 48.7 35.2 145.2 47.1 91.3 6.8 3.8 −29.6 586.3 305.6 898.9 2,838.3 617.7 27,398.6 4,788.3 5,252.5 11,595.2 4,163.3 6,489.2 942.7 1,988.6 4,776.5 51,023.0 26,055.5 57.2 241.8 −37.5 2,469.4 410.2 209.3 592.8 252.0 304.2 36.6 53.5 −526.5 3,735.1 2,134.7 2.0 4.8 0.0 39.7 6.0 6.4 16.0 5.3 7.2 3.5 0.5 0.4 68.6 36.1 1.5 2.5 −1.4 20.8 4.5 3.1 6.7 2.9 3.3 0.5 0.6 0.6 35.6 18.4 108.5 70.8 −33.0 612.8 128.9 93.8 216.7 63.0 111.0 42.7 5.1 −11.0 1,057.3 523.4 91.8 403.6 −13.6 1,671.2 666.2 257.9 650.8 241.2 316.9 92.7 40.4 194.0 3,286.5 1,348.9 22.3 56.6 0.0 335.4 36.2 28.3 120.3 52.7 54.5 13.0 4.2 60.7 524.4 268.9 60.0 75.0 −41.9 923.8 98.9 81.8 283.2 164.2 118.0 1.0 22.5 −112.5 1,410.2 786.4 79.4 144.4 6.3 992.3 212.8 124.4 220.7 44.9 126.3 49.5 10.0 −23.3 1,560.2 792.9 670.7 1,803.2 −23.8 10,711.8 955.2 1,570.9 2,828.2 1,014.6 1,295.0 518.6 36.4 −568.7 16,102.5 9,105.2 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 8.1 3.1 0.1 101.3 2.7 20.2 31.5 17.7 11.8 2.0 1.0 9.4 156.7 95.6 159.9 358.1 0.0 2,499.5 333.8 522.9 798.7 418.1 330.8 49.8 18.5 −30.4 4,173.4 2,240.1 44,222.0 43,621.0 81.0 381,323.0 41,656.0 56,385.0 146,522.0 50,778.0 90,288.0 5,456.0 1,094.0 −5,365.0 626,980.0 342,707.8 748.3 753.0 159.9 13,555.4 2,523.3 1,203.6 4,104.9 1,767.8 2,214.8 122.2 377.0 −1,016.3 21,764.2 13,120.1 … … … … … … … … … … … … … … 153.4 199.8 −10.4 1,833.7 50.1 105.8 345.4 98.0 241.9 5.5 2.9 −218.7 2,338.0 1,648.0 2.2 4.9 −0.3 48.7 4.8 5.3 20.8 6.7 5.9 8.1 2.4 −2.2 82.0 43.3 1.5 1.3 −0.1 21.6 1.2 1.4 2.9 1.5 1.4 0.0 0.4 −4.3 27.5 19.3 19.4 13.7 −6.3 316.6 17.6 20.8 54.6 28.6 25.9 0.1 1.6 −39.8 411.1 284.2 0.7 7.0 0.0 334.0 3.5 0.3 86.3 2.2 84.0 0.0 0.0 −126.4 424.1 320.1 15.7 17.8 0.0 260.1 27.8 26.0 81.9 45.5 32.1 4.3 5.2 −66.0 401.0 241.4 10.9 13.7 −2.7 168.1 13.3 18.5 48.7 18.8 26.0 3.9 1.8 −34.2 250.3 152.6 1.1 1.9 0.0 18.9 1.8 2.0 8.2 3.7 4.5 0.0 0.3 0.1 31.2 15.9 3,829.4 6,311.0 0.0 73,739.5 6,333.3 4,822.9 17,231.6 7,333.3 8,529.5 1,368.9 401.1 2,674.8 102,528.4 71,754.5 27.6 28.3 0.0 296.0 15.2 30.6 129.3 46.5 78.7 4.1 5.3 21.4 476.4 273.6 46.9 53.7 13.1 609.2 68.1 50.1 170.4 54.2 105.5 10.7 3.4 −4.4 901.2 511.0 (continued) Presentation and Analysis of Results 37 Table 2.2 (Continued) Furnishings, Alcoholic Housing, household EXPENDITURES Actual beverages, water, equipment (national currency Gross individual Food and tobacco, Clothing electricity, and Recreation units, billions) domestic consump- nonalcoholic and and gas, and mainte- Communi- and Economy product tion beverages narcotics footwear other fuels nance Health Transport cation culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) Venezuela, RB 1,357.5 823.8 177.4 24.3 37.7 40.3 47.2 74.3 109.3 46.1 52.3 69.7 Total (17) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. CARIBBEAN Anguilla 0.8 0.7 0.1 0.0 0.0 0.1 0.0 0.0 0.1 0.1 0.0 0.0 Antigua and Barbuda 3.0 2.1 0.3 0.0 0.0 0.6 0.1 0.2 0.2 0.1 0.1 0.1 Aruba 4.6 3.6 0.3 0.0 0.1 1.2 0.1 0.4 0.4 0.1 0.2 0.2 Bahamas, The 7.9 6.0 0.6 0.1 0.2 1.9 0.3 0.5 0.5 0.2 0.3 0.4 Barbados 8.7 7.8 1.1 0.1 0.1 4.1 0.2 0.4 0.5 0.3 0.3 0.4 Belize 3.0 2.3 0.4 0.0 0.2 0.6 0.1 0.2 0.3 0.1 0.1 0.1 Bermuda 5.6 4.3 0.4 0.1 0.1 1.2 0.2 0.4 0.3 0.1 0.2 0.3 Bonairef … … 0.0 0.0 0.0 … 0.0 … 0.0 0.0 … … Cayman Islands 2.7 2.0 0.1 0.0 0.1 0.7 0.1 0.1 0.2 0.1 0.1 0.1 Curaçao 5.4 4.2 0.4 0.1 0.3 1.3 0.1 0.3 0.4 0.2 0.2 0.2 Dominica 1.3 1.2 0.2 0.0 0.1 0.3 0.1 0.1 0.2 0.0 0.0 0.1 Grenada 2.1 2.0 0.4 0.0 0.1 0.4 0.1 0.1 0.4 0.2 0.1 0.1 Jamaica 1,241.8 1,155.4 324.2 15.5 20.9 156.7 64.3 69.8 164.5 31.2 102.3 85.5 Montserrat 0.2 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 St. Kitts and Nevis 2.0 1.5 0.2 0.0 0.1 0.4 0.1 0.1 0.1 0.1 0.1 0.1 St. Lucia 3.3 2.6 0.5 0.0 0.2 0.6 0.1 0.1 0.2 0.1 0.1 0.2 St. Vincent and the Grenadines 1.8 1.7 0.3 0.1 0.0 0.5 0.1 0.1 0.3 0.1 0.1 0.1 Sint Maarten 1.7 1.1 0.1 0.0 0.1 0.5 0.0 0.0 0.1 0.1 0.0 0.0 Suriname 14.3 5.5 2.0 0.1 0.2 0.9 0.3 0.3 0.4 0.2 0.2 0.1 Trinidad and Tobago 150.9 87.7 18.5 0.9 1.2 10.7 3.7 6.8 9.4 1.8 5.7 9.3 Turks and Caicos Islands 0.7 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 Virgin Islands, British 0.9 0.4 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Total (22) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. WESTERN ASIA Bahrain 10.9 4.8 0.6 0.0 0.3 1.0 0.3 0.3 0.5 0.2 0.3 0.5 a Egypt, Arab Rep. 1,371.1 1,090.5 457.0 35.4 65.9 142.3 52.7 99.5 64.4 27.8 32.4 72.2 Iraq 191,652.9 90,152.8 27,607.4 510.1 5,363.9 23,449.2 4,234.5 6,461.7 6,537.8 1,278.2 1,048.7 9,982.6 Jordan 20.5 16.3 4.6 0.5 0.7 3.3 0.7 1.1 1.7 0.6 0.3 2.0 Kuwait 44.3 12.3 1.9 0.0 1.0 2.9 1.5 1.0 0.9 0.4 0.4 1.2 Oman 26.9 9.7 1.9 0.0 0.5 1.8 0.4 0.6 1.5 0.5 0.3 1.1 Qatar 624.2 103.3 11.0 0.3 3.6 23.2 4.2 7.5 8.9 2.2 7.6 15.8 Saudi Arabia 2,510.6 922.3 146.2 3.2 44.3 191.4 60.7 76.3 62.5 38.5 28.1 158.4 b Sudan 186.6 130.9 67.7 0.9 5.8 19.2 8.5 1.7 10.7 2.1 3.0 4.3 United Arab Emirates 1,280.2 675.8 79.2 1.2 83.4 224.0 23.9 10.4 108.7 39.5 18.4 31.5 38 Purchasing Power Parities and the Real Size of World Economies Individual Miscella- Individual Individual Collective consumption neous consumption consumption consumption Gross Changes in Balance expenditure Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports by households and and purchases by by by capital and Construc- Other and and Domestic without hotels services abroad households government government formation equipment tion products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 99.3 42.4 3.5 748.8 75.0 81.3 240.7 109.1 122.9 8.6 72.5 139.1 1,218.4 719.6 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 0.0 0.1 0.0 0.7 0.0 0.1 0.1 0.0 0.1 0.0 0.0 −0.1 0.9 0.6 0.1 0.3 0.0 1.8 0.2 0.3 0.6 0.1 0.5 0.0 0.0 0.0 3.0 1.5 0.1 0.3 0.0 2.9 0.7 0.4 1.2 0.3 0.9 0.0 0.1 −0.7 5.4 2.1 0.3 0.9 0.0 5.6 0.5 0.7 2.1 1.0 1.1 0.0 0.1 −1.1 9.0 4.3 1.4 0.6 −1.8 7.1 0.7 0.9 1.4 0.7 0.7 0.0 −0.1 −1.3 10.0 3.6 0.0 0.1 0.0 2.1 0.1 0.3 0.5 0.2 0.3 0.0 0.0 −0.1 3.1 1.6 0.5 0.6 0.0 3.7 0.6 0.5 1.1 0.6 0.5 0.0 0.1 −0.4 6.0 2.6 0.0 … 0.0 0.2 … … … … … … … … … 0.1 0.1 0.4 0.0 1.9 0.1 0.2 0.6 0.3 0.3 0.0 0.0 −0.2 2.9 1.4 0.1 0.9 −0.3 3.8 0.4 0.4 2.2 1.2 0.6 0.4 0.1 −1.4 6.8 3.0 0.0 0.1 0.0 1.1 0.1 0.2 0.3 0.1 0.2 0.0 −0.1 −0.2 1.5 0.9 0.0 0.1 0.0 1.9 0.2 0.2 0.4 0.2 0.3 0.0 0.0 −0.5 2.6 1.7 141.8 136.2 −157.5 1,063.5 91.9 106.6 258.0 124.6 128.6 4.8 6.0 −284.2 1,526.0 969.0 0.0 0.0 0.0 0.1 0.0 0.1 0.0 0.0 0.0 0.0 0.0 −0.1 0.2 0.1 0.1 0.1 0.0 1.3 0.1 0.2 0.6 0.2 0.4 0.0 0.0 −0.3 2.3 1.1 0.0 0.3 0.0 2.4 0.2 0.3 1.0 0.3 0.7 0.0 0.0 −0.7 3.9 2.1 0.1 0.1 −0.2 1.5 0.2 0.2 0.4 0.1 0.3 0.0 0.0 −0.5 2.3 1.2 0.0 0.1 0.0 1.0 0.1 0.2 0.3 0.2 0.1 0.0 0.0 0.1 1.6 0.7 0.1 0.7 0.0 5.3 0.1 1.6 5.3 4.3 0.8 0.1 1.0 0.9 13.4 5.0 8.1 11.9 0.0 69.1 18.6 2.5 22.6 11.2 11.0 0.5 0.0 38.0 112.9 62.5 0.0 0.0 0.0 0.3 0.0 0.1 0.1 0.0 0.1 0.0 0.0 0.2 0.5 0.2 0.0 0.0 0.0 0.3 0.0 0.0 0.2 0.1 0.1 0.0 0.0 0.3 0.6 0.3 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 0.2 0.3 0.1 4.2 0.5 1.0 1.7 0.5 1.2 0.0 0.1 3.4 7.5 3.4 34.3 77.2 −70.7 1,036.1 54.4 102.6 229.1 106.5 116.4 6.2 5.4 −56.5 1,427.6 940.1 862.2 2,816.5 0.0 76,260.3 13,892.5 28,862.4 37,255.3 14,402.2 22,694.1 159.0 −832.3 36,214.8 155,438.1 59,573.4 0.3 0.5 0.1 14.6 1.7 2.3 4.4 1.1 3.0 0.3 0.3 −2.8 23.3 12.5 0.4 0.8 0.0 10.3 2.0 4.6 7.0 2.8 3.5 0.7 0.3 20.1 24.2 7.8 0.3 0.7 0.1 8.1 1.6 3.0 7.1 2.8 3.5 0.7 −0.8 8.0 19.0 6.7 2.0 14.6 2.3 79.7 23.6 54.4 182.9 89.5 28.6 64.8 0.0 283.6 340.6 58.4 34.8 44.9 33.0 681.8 240.5 247.5 568.8 219.5 282.2 67.2 103.6 668.4 1,842.2 547.6 2.9 3.4 0.7 129.9 1.0 11.7 41.6 21.7 19.9 0.0 4.9 −2.5 189.1 117.2 25.0 30.5 0.0 661.8 14.0 79.6 281.7 111.9 140.6 29.1 12.2 230.9 1,049.3 469.1 (continued) Presentation and Analysis of Results 39 Table 2.2 (Continued) Furnishings, Alcoholic Housing, household EXPENDITURES Actual beverages, water, equipment (national currency Gross individual Food and tobacco, Clothing electricity, and Recreation units, billions) domestic consump- nonalcoholic and and gas, and mainte- Communi- and Economy product tion beverages narcotics footwear other fuels nance Health Transport cation culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) West Bank and Gaza 35.0 37.8 12.0 1.5 2.2 4.1 2.0 2.8 3.6 1.1 0.9 3.2 Yemen, Rep. 6,714.9 4,904.7 2,216.2 236.3 214.9 700.1 146.2 471.0 281.1 52.7 18.8 344.4 Total (12) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. SINGLETONS Georgia 24.3 19.1 6.0 1.0 0.5 2.2 0.7 2.0 1.7 0.6 1.3 1.3 Iran, Islamic Rep. 6,121,004.0 2,717,581.9 659,037.8 12,538.2 116,321.1 782,477.8 100,873.7 221,043.0 199,053.5 84,484.1 65,577.4 86,156.1 Total (2) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. g WORLD (179) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; ... = data suppressed because of incompleteness. a. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. b. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. c. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. d. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. e. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. f. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. g. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 40 Purchasing Power Parities and the Real Size of World Economies Individual Miscella- Individual Individual Collective consumption neous consumption consumption consumption Gross Changes in Balance expenditure Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports by households and and purchases by by by capital and Construc- Other and and Domestic without hotels services abroad households government government formation equipment tion products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 0.9 3.1 0.5 33.7 4.1 6.3 7.2 1.3 5.2 0.8 −1.2 −15.3 50.2 32.3 1.6 221.4 0.0 4,573.2 331.6 614.0 886.4 83.5 686.9 116.1 379.0 −69.2 6,784.1 4,203.0 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 0.6 1.1 0.0 18.0 1.1 3.4 5.5 2.0 2.6 0.8 0.9 −4.5 28.9 17.0 31,387.9 289,176.1 69,455.2 2,557,440.1 160,141.8 513,541.4 1,570,527.5 710,604.0 812,701.0 47,222.5 666,188.3 653,165.0 5,467,839.0 1,924,614.9 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. Presentation and Analysis of Results 41 Table 2.3 Shares of Nominal Expenditures (GDP = 100), ICP 2011 NOMINAL Alcoholic Housing, Furnishings, EXPENDITURE SHARES beverages, water, household (GDP = 100)a Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) AFRICA Algeria 100.0 45.0 13.5 0.8 1.3 2.2 1.1 3.2 5.4 2.5 1.1 4.3 Angola 100.0 60.7 24.9 2.6 3.1 6.4 3.4 3.2 3.3 0.6 1.3 3.0 Benin 100.0 80.8 39.0 2.3 3.4 8.2 2.2 2.8 5.9 2.4 1.2 4.1 Botswana 100.0 54.6 9.7 4.1 3.4 6.1 3.2 2.8 8.8 1.3 1.5 6.9 Burkina Faso 100.0 67.7 34.6 4.3 1.4 7.5 2.9 2.5 4.4 2.2 1.6 2.0 Burundi 100.0 93.2 40.7 12.8 0.9 14.4 0.8 2.6 6.1 1.1 1.0 5.2 Cameroon 100.0 78.3 36.0 2.1 6.5 7.2 7.2 1.2 6.4 1.2 1.2 1.8 Cape Verde 100.0 70.7 24.5 3.3 1.9 14.0 5.0 3.9 4.9 2.4 0.7 5.8 Central African Republic 100.0 92.4 53.0 8.4 6.6 4.5 4.8 1.4 3.3 0.8 1.6 2.7 Chad 100.0 68.7 33.0 3.2 1.5 6.5 4.6 4.8 6.4 2.6 1.6 1.0 Comoros 100.0 98.7 50.7 0.3 3.0 30.7 3.8 0.8 2.0 0.6 1.0 2.4 Congo, Rep. 100.0 24.8 9.1 1.0 0.7 3.3 0.9 1.9 2.0 1.3 0.7 1.9 Congo, Dem. Rep. 100.0 64.4 35.3 1.9 3.0 7.7 2.2 2.9 1.7 0.7 0.8 2.7 Côte d’Ivoire 100.0 71.4 30.4 2.3 2.5 7.0 5.9 3.0 7.8 2.1 2.5 3.1 Djibouti 100.0 71.5 21.5 5.6 2.1 22.3 4.0 2.3 4.4 0.2 0.8 4.6 b Egypt, Arab Rep. 100.0 79.5 33.3 2.6 4.8 10.4 3.8 7.3 4.7 2.0 2.4 5.3 Equatorial Guinea 100.0 12.9 4.9 0.3 0.4 1.8 0.5 1.2 1.0 0.5 0.2 0.6 Ethiopia 100.0 80.9 30.0 2.0 4.2 13.2 7.7 6.6 1.3 0.3 0.4 2.8 Gabon 100.0 38.1 11.5 2.2 1.9 5.5 1.7 2.6 3.2 1.7 0.9 2.0 Gambia, The 100.0 79.6 33.9 2.2 5.8 5.5 2.0 12.0 2.1 2.1 2.5 6.9 Ghana 100.0 66.9 24.9 0.9 9.5 6.7 4.6 2.3 4.4 1.0 0.7 9.2 Guinea 100.0 56.4 32.6 0.8 3.9 4.5 2.2 4.1 3.1 0.1 0.5 1.8 Guinea-Bissau 100.0 68.5 34.9 1.2 5.5 9.4 4.9 1.7 4.9 0.4 3.0 1.3 Kenya 100.0 87.6 30.0 4.3 2.2 6.8 4.0 6.4 8.9 2.7 3.0 12.6 Lesotho 100.0 110.3 28.2 2.9 13.7 11.5 9.6 4.8 3.7 3.1 3.8 10.4 Liberia 100.0 113.2 30.4 3.8 14.5 25.4 6.1 2.1 2.8 4.2 2.0 13.2 Madagascar 100.0 90.8 39.7 2.8 5.9 5.6 12.1 1.6 11.7 0.8 3.8 3.2 Malawi 100.0 98.7 48.2 4.8 2.6 10.8 10.0 3.9 7.7 1.7 2.3 5.0 Mali 100.0 66.7 31.0 0.9 3.8 6.5 4.0 2.6 8.8 1.5 2.7 2.9 Mauritania 100.0 58.5 35.3 0.6 2.0 5.6 1.6 2.3 2.5 2.3 0.6 4.4 Mauritius 100.0 79.0 22.9 6.6 4.6 12.2 6.3 3.9 10.6 2.4 5.1 6.3 Morocco 100.0 66.9 22.8 2.1 2.7 9.3 3.1 4.1 6.0 4.1 2.9 7.6 Mozambique 100.0 85.9 44.3 3.7 4.2 6.2 2.4 2.5 7.2 1.1 2.3 5.9 Namibia 100.0 71.5 14.3 2.9 3.4 13.7 5.1 7.9 2.9 0.6 2.8 10.0 Niger 100.0 80.2 33.5 1.8 6.2 8.1 3.9 3.3 6.1 1.9 4.4 2.6 Nigeria 100.0 64.4 24.3 0.9 9.3 6.6 4.5 2.0 4.3 1.0 0.7 8.2 Rwanda 100.0 86.9 41.6 2.9 2.9 14.3 2.8 2.3 5.6 1.1 1.4 4.5 São Tomé and Príncipe 100.0 116.9 63.8 5.3 4.6 11.0 4.0 4.6 11.4 1.5 1.7 4.5 42 Purchasing Power Parities and the Real Size of World Economies Miscel- Individual Individual Collective Individual laneous consumption consumption consumption Gross Changes in Balance consumption Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and and purchases by by by capital and Other and and Domestic households hotels services abroad households government government formation equipment Construction products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 1.1 8.4 0.0 31.4 13.6 9.2 31.9 13.5 16.6 1.8 3.4 10.5 89.5 30.6 1.8 7.2 0.0 50.8 9.9 26.2 17.1 5.3 11.0 0.8 0.3 −4.3 104.3 49.3 7.5 2.5 −0.8 76.5 4.3 7.3 20.7 7.1 13.4 0.2 0.9 −9.7 109.7 71.3 2.2 4.6 0.0 47.4 7.2 11.7 32.8 13.5 18.9 0.4 6.7 −5.9 105.9 44.3 2.3 1.9 0.0 65.1 2.6 15.2 16.5 6.8 8.4 1.3 7.7 −7.1 107.1 61.3 3.9 2.2 1.6 86.3 6.9 12.8 18.9 8.3 9.6 1.0 0.7 −25.7 125.7 73.3 5.2 1.8 0.6 75.9 2.5 9.1 20.6 9.6 10.5 0.5 0.0 −8.1 108.1 71.4 8.7 4.4 −8.8 62.4 8.3 10.1 46.8 16.9 28.1 1.9 0.9 −28.6 128.6 54.5 1.8 3.5 0.0 89.9 2.5 4.5 15.3 4.4 8.3 2.6 0.0 −12.3 112.3 89.1 0.5 1.5 1.5 66.6 2.1 4.4 28.6 11.5 13.8 3.3 1.2 −2.8 102.8 61.7 0.0 3.1 0.3 98.1 0.6 23.0 13.4 6.0 6.7 0.7 3.8 −38.9 138.9 73.8 1.9 0.7 −0.5 22.2 2.5 4.8 34.5 5.6 28.5 0.3 0.0 36.0 64.0 20.7 3.9 1.5 0.0 61.9 2.4 11.6 23.6 8.7 14.1 0.9 0.1 0.4 99.6 58.0 1.0 3.2 0.8 67.6 3.8 7.9 11.2 4.0 6.7 0.5 −6.6 16.1 83.9 63.0 0.7 1.7 1.1 66.3 5.1 19.8 26.4 8.7 17.5 0.1 4.4 −22.0 122.0 53.8 2.5 5.6 −5.2 75.6 4.0 7.5 16.7 7.8 8.5 0.5 0.4 −4.1 104.1 68.6 0.4 0.7 0.3 12.0 0.9 1.8 33.0 16.9 10.8 5.3 0.0 52.3 47.7 11.0 3.8 8.5 0.0 78.6 2.3 6.3 25.9 9.6 11.7 4.5 2.1 −15.1 115.1 71.9 1.8 1.2 2.0 35.0 3.2 9.5 19.0 5.6 5.6 7.8 0.0 33.4 66.6 31.4 0.9 3.6 0.0 76.0 3.6 7.0 26.9 17.1 8.4 1.3 0.0 −13.5 113.5 73.9 0.0 2.5 0.0 61.4 5.5 11.2 25.6 14.5 9.5 1.6 1.9 −5.6 105.6 60.4 0.8 1.4 0.6 55.6 0.8 4.6 23.8 15.2 7.9 0.8 1.9 13.3 86.7 52.6 0.3 1.1 0.0 66.9 1.5 17.6 12.8 5.7 6.7 0.5 1.1 0.0 100.0 64.5 5.4 6.1 −4.7 75.6 12.0 8.4 20.0 11.0 9.0 0.1 0.5 −16.5 116.5 72.0 1.5 6.6 10.5 97.0 13.3 21.0 26.5 6.9 18.4 1.2 1.2 −59.1 159.1 89.0 0.8 7.9 0.0 112.6 0.6 12.3 12.8 11.3 1.5 0.0 6.5 −44.7 144.7 96.4 3.0 1.4 −0.8 87.9 2.9 7.2 17.4 7.7 8.8 0.8 0.0 −15.4 115.4 87.0 2.5 2.3 −2.9 93.1 5.6 6.9 16.6 12.3 3.3 1.0 −3.3 −18.9 118.9 86.3 1.2 1.7 −1.0 63.3 3.4 12.0 22.2 9.5 11.6 1.0 0.9 −1.8 101.8 58.9 0.4 1.1 0.0 51.8 6.7 15.2 57.4 28.3 24.1 5.1 −23.9 −7.2 107.2 48.4 2.7 5.0 −9.6 73.4 5.6 7.9 24.0 7.2 15.7 1.1 1.9 −12.9 112.9 68.1 3.9 4.4 −6.1 58.9 7.9 10.3 30.7 13.2 15.9 1.7 5.3 −13.1 113.1 53.3 0.8 4.3 1.0 79.7 6.2 7.2 17.8 6.0 11.7 0.0 2.1 −13.0 113.0 75.8 4.3 6.2 −2.7 61.7 9.8 15.5 21.3 7.8 12.8 0.7 −1.2 −7.1 107.1 52.8 4.0 4.7 −0.1 77.4 2.8 10.0 37.0 16.3 19.9 0.9 0.1 −27.3 127.3 73.5 0.0 2.4 0.0 60.1 4.3 8.8 10.3 5.8 3.8 0.6 0.0 16.5 83.5 59.1 2.7 3.1 1.6 83.4 3.5 9.1 21.4 4.7 15.8 1.0 0.0 −17.4 117.4 74.1 1.5 2.2 0.8 112.4 4.5 7.7 19.7 14.8 3.5 1.4 0.2 −44.5 144.5 106.3 (continued) Presentation and Analysis of Results 43 Table 2.3 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURE SHARES beverages, water, household (GDP = 100)a Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) Senegal 100.0 82.8 40.6 1.1 2.9 15.9 4.7 2.4 4.1 4.1 1.1 4.4 Seychelles 100.0 60.7 24.1 1.7 2.6 10.8 2.6 4.0 3.7 1.1 1.5 6.4 Sierra Leone 100.0 89.8 35.5 2.8 7.2 6.7 2.5 14.3 2.8 2.5 3.1 6.8 South Africa 100.0 68.3 12.1 3.0 2.9 9.3 4.2 7.6 8.8 1.8 2.8 7.3 Sudanc 100.0 70.2 36.3 0.5 3.1 10.3 4.5 0.9 5.7 1.1 1.6 2.3 Swaziland 100.0 90.1 41.1 0.8 5.0 12.1 9.6 5.7 7.0 1.2 3.8 7.6 Tanzania 100.0 68.3 45.1 0.5 4.6 4.9 3.0 2.4 2.6 0.0 0.7 3.3 Togo 100.0 88.5 38.4 2.1 4.4 6.9 4.0 5.8 4.9 2.1 1.1 5.9 Tunisia 100.0 74.4 16.4 2.4 5.1 10.5 4.5 5.3 10.6 2.6 2.4 5.9 Uganda 100.0 90.7 30.2 5.3 2.6 16.3 5.1 2.5 5.4 1.7 5.5 9.7 Zambia 100.0 55.3 32.3 0.4 3.5 6.6 0.8 2.8 0.8 1.4 0.4 3.4 Zimbabwe 100.0 95.3 53.3 3.1 5.2 6.1 2.8 2.6 7.2 0.1 2.0 6.8 Total (50) 100.0 66.9 23.3 2.1 4.1 7.9 3.8 4.5 5.9 1.7 1.9 5.8 ASIA AND THE PACIFIC Bangladesh 100.0 75.2 38.3 1.6 4.5 12.9 2.4 2.7 3.1 0.4 0.5 4.1 Bhutan 100.0 51.6 15.1 1.3 3.8 9.1 0.9 5.8 4.9 1.3 3.2 4.6 Brunei Darussalam 100.0 23.9 4.3 0.1 1.0 2.9 1.0 1.3 3.6 1.3 1.8 3.9 Cambodia 100.0 84.3 38.6 3.2 1.6 12.5 1.5 5.9 6.3 0.2 2.3 5.7 d China 100.0 42.9 8.1 0.9 3.0 5.9 2.1 6.4 2.5 1.5 2.3 4.3 Fiji 100.0 76.7 22.6 2.6 1.9 18.9 6.7 3.9 5.9 0.3 3.7 4.5 Hong Kong SAR, China 100.0 66.6 7.2 0.7 2.9 12.6 3.7 5.6 4.7 1.4 7.5 2.3 India 100.0 59.2 16.7 1.8 4.2 7.6 2.2 2.8 8.9 0.6 0.9 2.7 Indonesia 100.0 58.2 22.0 1.0 2.2 11.9 1.6 2.0 4.0 1.1 1.1 4.3 Lao PDR 100.0 58.6 29.9 3.0 0.9 7.5 1.5 1.3 6.2 0.7 1.6 2.4 Macao SAR, China 100.0 23.4 2.2 0.2 1.4 3.6 0.5 1.7 2.0 0.7 2.4 1.7 Malaysia 100.0 53.7 9.1 0.8 1.0 7.9 2.4 3.2 7.1 3.2 2.1 5.6 Maldives 100.0 37.9 7.3 1.7 0.8 14.7 1.5 2.2 1.5 0.8 0.7 5.0 Mongolia 100.0 60.7 17.3 4.3 3.0 8.7 0.9 2.8 9.5 1.8 1.7 6.1 Myanmar 100.0 69.8 36.5 1.4 2.2 9.2 0.9 4.3 2.3 1.1 0.8 5.8 Nepal 100.0 80.3 45.0 2.6 2.1 10.4 1.5 3.4 2.5 1.1 2.0 4.6 Pakistan 100.0 84.9 37.5 0.8 3.9 16.5 2.8 5.3 5.4 1.4 0.9 4.0 Philippines 100.0 76.9 31.5 0.9 1.0 9.1 3.0 2.4 7.9 2.3 1.3 5.5 Singapore 100.0 42.9 2.7 0.8 1.1 7.8 2.2 3.6 5.4 0.8 4.6 4.0 Sri Lanka 100.0 76.8 32.5 5.7 2.3 10.4 1.9 4.0 6.0 1.5 1.1 4.2 Taiwan, China 100.0 64.5 7.6 1.3 2.7 10.7 2.9 6.1 6.7 2.3 6.1 5.6 Thailand 100.0 62.0 15.9 2.2 2.1 5.6 2.5 4.7 8.7 1.3 2.9 5.4 Vietnam 100.0 63.4 16.4 1.8 2.6 14.5 3.7 4.6 6.3 0.5 2.5 5.5 Total (23) 100.0 50.6 12.0 1.1 2.9 7.4 2.2 5.2 4.3 1.3 2.3 4.2 44 Purchasing Power Parities and the Real Size of World Economies Miscel- Individual Individual Collective Individual laneous consumption consumption consumption Gross Changes in Balance consumption Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and and purchases by by by capital and Other and and Domestic households hotels services abroad households government government formation equipment Construction products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 0.7 3.2 −2.2 78.5 4.3 9.9 23.8 9.1 14.5 0.2 1.4 −17.9 117.9 70.1 0.4 1.9 0.0 52.8 7.9 20.3 33.9 14.0 18.5 1.4 5.8 −20.8 120.8 46.0 1.1 4.3 0.0 87.5 2.2 7.9 41.7 29.6 11.6 0.5 0.4 −39.7 139.7 85.0 1.4 7.8 −0.7 59.4 8.9 12.8 19.0 9.0 9.1 0.9 0.5 −0.6 100.6 53.0 1.6 1.8 0.4 69.6 0.5 6.3 22.3 11.7 10.6 0.0 2.6 −1.4 101.4 62.8 0.6 1.4 −5.8 84.5 5.6 9.3 9.3 3.6 4.3 1.4 0.0 −8.7 108.7 75.0 0.0 1.3 0.0 66.1 2.2 14.2 36.1 15.5 19.7 0.8 0.6 −19.2 119.2 65.9 7.2 9.4 −3.7 84.8 3.7 8.1 17.7 5.4 11.5 0.8 1.8 −16.1 116.1 81.5 7.1 4.7 −3.1 65.6 8.8 9.6 21.7 7.1 13.8 0.8 1.7 −7.4 107.4 57.5 2.6 3.8 0.0 82.2 8.5 1.6 24.7 7.1 16.4 1.1 0.3 −17.3 117.3 75.0 0.1 2.7 0.0 51.9 3.4 15.6 21.7 6.6 14.1 1.0 1.4 6.0 94.0 48.7 0.6 4.7 0.8 87.4 7.9 8.8 11.1 3.8 7.3 0.0 4.6 −19.9 119.9 84.0 1.8 5.2 −1.3 60.1 6.8 10.7 20.9 9.2 10.6 1.1 1.1 0.5 99.5 55.8 1.7 2.9 0.0 73.7 1.5 3.7 28.3 6.7 21.2 0.4 0.5 −7.8 107.8 67.0 0.6 1.1 0.0 43.7 7.9 11.9 66.5 27.5 39.0 0.0 −0.4 −29.7 129.7 37.5 1.2 1.3 0.0 19.5 4.4 12.6 13.1 3.9 8.3 0.9 −0.7 51.1 48.9 17.3 4.0 2.3 0.0 79.6 4.7 3.7 11.6 5.7 5.8 0.1 0.5 −0.1 100.1 71.1 2.2 3.7 0.0 34.4 8.6 6.3 45.6 13.1 28.8 3.7 2.7 2.6 97.4 31.0 2.0 3.6 0.0 71.2 5.5 6.0 19.4 9.3 7.3 2.8 3.0 −5.1 105.1 56.2 6.7 11.3 0.0 63.3 3.4 5.3 23.5 10.4 11.1 2.1 0.6 3.9 96.1 52.6 1.5 9.5 0.0 55.9 3.3 8.3 30.9 11.8 18.0 1.2 7.3 −5.7 105.7 50.7 4.2 2.9 0.0 54.6 3.6 5.4 32.0 5.3 25.9 0.8 3.0 1.4 98.6 47.5 1.7 1.8 0.0 56.8 1.9 7.8 35.7 10.7 17.5 7.6 1.5 −3.6 103.6 53.6 4.4 2.6 0.0 20.5 2.9 4.2 12.4 2.9 9.4 0.1 1.4 58.6 41.4 17.7 4.4 6.9 0.0 47.3 6.4 6.6 22.3 8.1 11.1 3.1 1.0 16.4 83.6 42.9 0.7 1.0 0.0 32.2 5.6 17.9 50.4 19.4 30.9 0.0 0.0 −6.1 106.1 20.4 1.0 3.3 0.0 54.9 5.8 7.1 47.1 28.0 17.4 1.7 12.0 −27.0 127.0 47.4 3.1 2.1 0.0 63.7 6.0 4.2 26.7 13.0 11.6 2.1 0.0 −0.7 100.7 58.7 1.7 3.4 0.0 76.9 3.4 6.7 20.7 4.5 11.5 4.7 16.0 −23.6 123.6 68.5 0.9 5.4 0.0 81.9 3.0 7.1 12.9 4.2 6.2 2.6 1.6 −6.5 106.5 75.2 2.7 9.1 0.0 73.5 3.5 6.2 18.7 7.2 9.3 2.2 1.7 −3.6 103.6 67.2 4.4 5.5 0.0 39.0 3.9 6.5 23.8 8.9 14.0 0.9 −1.2 28.1 71.9 32.3 2.9 4.4 0.0 69.8 7.0 7.8 27.1 8.3 17.1 1.7 2.8 −14.6 114.6 63.3 3.5 9.0 0.0 60.1 4.4 8.0 20.9 9.7 9.5 1.7 −0.1 6.7 93.3 51.2 4.8 5.8 0.0 54.6 7.3 9.0 26.7 17.9 8.4 0.4 0.6 1.7 98.3 50.8 2.8 2.3 0.0 58.9 4.5 5.9 29.8 7.7 20.3 1.7 5.1 −4.1 104.1 49.9 2.5 5.1 0.0 44.0 6.6 6.6 37.8 11.7 23.4 2.8 3.0 1.9 98.1 39.4 (continued) Presentation and Analysis of Results 45 Table 2.3 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURE SHARES beverages, water, household (GDP = 100)a Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) COMMONWEALTH OF INDEPENDENT STATES Armenia 100.0 88.8 48.5 4.0 3.1 7.2 1.2 5.4 4.6 4.7 2.0 4.0 Azerbaijan 100.0 41.0 15.1 1.0 3.8 3.3 2.1 1.8 4.3 2.3 1.4 3.0 Belarus 100.0 56.7 17.9 3.4 3.6 4.4 2.6 5.1 4.7 2.4 3.0 4.8 Kazakhstan 100.0 48.3 9.9 1.1 2.8 10.5 1.9 3.8 5.2 1.9 2.4 4.1 Kyrgyz Republic 100.0 93.6 35.4 4.3 6.7 6.9 3.3 4.8 9.8 6.0 3.9 7.5 Moldova 100.0 112.4 31.6 6.5 6.5 14.5 8.0 4.0 11.3 4.1 3.6 9.4 Russian Federatione 100.0 57.7 14.6 4.0 4.4 5.6 2.4 4.6 6.0 2.2 3.1 3.2 Tajikistan 100.0 115.1 50.9 0.4 9.9 7.0 3.9 5.3 8.9 7.0 2.4 4.8 Ukraine 100.0 79.2 25.9 4.6 4.2 8.5 2.9 6.9 8.2 1.6 3.2 7.0 Total (9) 100.0 58.5 15.4 3.7 4.2 6.1 2.4 4.6 6.0 2.2 3.0 3.6 EUROSTAT−OECD Albania 100.0 85.3 32.3 2.3 3.3 10.4 5.7 4.9 4.3 1.7 2.0 2.8 Australia 100.0 64.2 5.6 2.0 1.8 12.6 2.5 8.1 5.6 1.3 6.4 5.3 Austria 100.0 65.9 5.5 1.9 3.3 11.8 3.6 6.9 7.4 1.1 6.4 5.3 Belgium 100.0 68.3 6.8 1.8 2.5 12.1 2.9 9.9 6.3 1.1 5.1 6.3 Bosnia and Herzegovina 100.0 93.4 27.0 6.0 3.7 11.8 4.9 8.0 7.9 2.6 4.6 5.3 Bulgaria 100.0 70.3 13.2 4.6 1.9 11.2 4.9 6.8 10.9 3.8 5.7 3.5 Canada 100.0 68.4 5.1 1.9 2.3 13.2 3.0 8.7 8.1 1.3 5.5 5.4 Chile 100.0 68.8 9.9 1.9 3.4 10.0 4.4 6.6 7.8 2.4 4.7 5.8 Croatia 100.0 70.7 13.4 4.5 3.0 12.5 3.7 8.4 6.8 2.3 7.2 5.6 Cyprus 100.0 76.5 9.3 3.2 4.3 13.4 3.6 6.6 8.2 2.4 6.2 7.5 Czech Republic 100.0 61.4 7.7 4.8 1.6 14.0 2.8 7.3 4.9 1.6 5.6 4.3 Denmark 100.0 69.0 5.4 1.7 2.2 13.9 2.4 9.0 5.9 0.8 6.0 6.3 Estonia 100.0 61.3 10.1 4.6 3.3 11.0 1.9 5.5 6.5 1.9 4.7 4.8 Finland 100.0 72.2 6.6 2.6 2.6 14.3 2.8 8.7 6.1 1.1 6.9 5.9 France 100.0 73.7 7.5 1.8 2.4 14.8 3.3 9.2 8.0 1.5 5.9 5.4 Germany 100.0 69.7 6.2 1.8 2.6 13.2 3.4 8.8 7.6 1.4 5.5 4.1 Greece 100.0 81.7 12.5 3.3 2.9 18.3 3.1 8.1 9.1 2.2 4.4 5.4 Hungary 100.0 64.1 9.3 4.1 1.6 11.9 2.4 7.3 7.1 2.0 4.9 4.4 Iceland 100.0 68.6 7.3 2.1 2.1 11.3 3.5 8.6 7.4 1.1 6.8 7.0 Ireland 100.0 61.0 4.6 2.5 1.9 11.4 2.0 9.0 6.0 1.4 3.6 4.8 Israel 100.0 69.5 9.1 1.4 1.7 13.9 3.5 6.0 8.9 2.2 4.4 7.2 Italy 100.0 73.2 8.8 1.7 4.6 13.7 4.4 8.8 7.8 1.5 5.0 4.3 Japan 100.0 72.4 8.2 1.6 1.9 15.1 3.0 7.7 6.4 2.0 5.4 3.7 Korea, Rep. 100.0 59.9 6.7 1.2 2.6 8.4 1.7 6.6 6.1 2.2 4.2 6.6 Latvia 100.0 70.1 12.0 4.6 3.0 14.4 2.4 5.0 8.9 1.9 5.6 4.7 Lithuania 100.0 73.7 15.3 4.8 3.8 10.3 3.8 7.3 9.5 1.5 4.7 4.9 Luxembourg 100.0 42.0 3.2 3.3 1.8 9.4 2.4 4.5 7.3 0.6 3.3 4.4 46 Purchasing Power Parities and the Real Size of World Economies Miscel- Individual Individual Collective Individual laneous consumption consumption consumption Gross Changes in Balance consumption Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and and purchases by by by capital and Other and and Domestic households hotels services abroad households government government formation equipment Construction products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 1.1 2.8 0.3 83.7 5.2 7.8 26.0 4.3 21.0 0.7 1.0 −23.6 123.6 80.8 1.3 1.7 0.0 37.3 3.8 6.4 20.2 10.5 8.8 0.9 0.1 32.3 67.7 36.2 1.6 2.3 0.7 47.7 9.1 4.9 37.8 16.5 21.0 0.3 1.7 −1.1 101.1 46.1 1.7 3.2 0.0 42.8 5.6 5.1 20.9 6.0 13.6 1.3 4.3 21.4 78.6 35.5 3.6 3.9 −2.7 83.4 10.2 8.0 23.7 10.6 12.4 0.7 1.8 −27.1 127.1 81.8 1.7 9.7 1.6 96.5 15.8 4.3 23.3 7.4 14.1 1.9 0.9 −40.9 140.9 91.4 1.6 4.9 1.1 49.1 8.6 9.4 20.8 7.5 11.6 1.7 3.6 8.6 91.4 46.6 1.3 5.7 7.5 106.9 8.2 5.2 32.4 14.3 14.7 3.4 3.7 −56.4 156.4 105.2 1.7 4.3 −0.1 67.2 11.9 6.3 18.6 7.1 11.0 0.4 2.2 −6.2 106.2 63.1 1.6 4.6 0.9 50.0 8.5 8.6 21.1 7.6 11.9 1.5 3.4 8.4 91.6 47.1 2.2 4.8 8.8 80.3 5.0 5.5 33.1 7.0 25.4 0.7 −0.8 −23.1 123.1 73.9 3.7 9.4 −0.2 53.6 10.6 7.0 26.9 6.5 15.5 4.9 0.5 1.3 98.7 43.8 6.6 8.2 −2.1 54.8 11.2 7.8 21.2 8.1 11.0 2.1 2.1 3.0 97.0 47.4 3.1 9.7 0.8 52.7 15.6 8.8 20.7 7.7 11.1 1.9 1.3 0.8 99.2 44.6 5.9 8.4 −2.5 82.9 10.6 11.8 17.9 7.6 9.7 0.6 0.2 −23.3 123.3 77.4 4.3 4.3 −4.9 62.4 7.9 7.8 21.5 9.3 11.5 0.8 0.4 0.0 100.0 55.7 3.7 9.4 0.9 55.7 12.7 9.0 23.4 4.7 15.6 3.2 0.4 −1.2 101.2 44.9 2.9 9.2 −0.2 61.2 7.6 4.4 22.4 8.8 11.9 1.7 1.1 3.3 96.7 55.4 10.6 6.1 −13.5 59.9 10.8 9.0 19.2 6.2 11.5 1.5 1.2 −0.1 100.1 53.0 11.0 6.5 −6.0 67.7 8.8 11.3 16.6 4.8 11.1 0.8 −0.1 −4.4 104.4 59.0 4.0 5.2 −2.4 50.6 10.8 9.9 24.1 10.7 12.1 1.3 0.4 4.1 95.9 42.2 2.5 12.7 0.1 48.7 20.3 8.0 17.4 6.1 8.8 2.5 0.4 5.2 94.8 39.1 3.9 5.6 −2.6 50.6 10.7 8.5 23.6 10.9 11.9 0.8 2.9 3.7 96.3 43.2 3.4 11.3 −0.2 55.7 16.4 8.0 19.4 4.7 13.1 1.7 1.1 −0.7 100.7 45.8 4.0 10.3 −0.4 57.7 16.0 8.5 20.0 5.4 12.4 2.1 0.8 −3.0 103.0 47.5 3.2 10.6 1.4 57.4 12.2 6.9 18.1 6.9 10.1 1.1 0.1 5.2 94.8 48.4 9.0 7.4 −4.0 74.6 7.1 10.3 15.1 6.1 8.0 1.1 1.0 −8.1 108.1 62.3 3.6 8.2 −2.7 53.3 10.8 10.2 17.9 7.5 9.3 1.1 1.3 6.5 93.5 46.6 4.3 7.2 −0.1 51.9 16.7 8.7 14.1 5.4 7.7 1.1 0.3 8.4 91.6 42.9 5.8 6.9 1.1 48.1 12.9 5.5 10.6 4.0 5.7 0.9 1.3 21.6 78.4 39.9 3.8 8.1 −0.8 57.3 12.2 10.8 20.4 6.5 9.9 4.0 −0.2 −0.5 100.5 46.4 6.2 7.4 −0.9 61.2 11.9 8.5 19.1 7.6 9.1 2.3 0.7 −1.4 101.4 51.8 3.9 13.1 0.5 60.5 11.9 8.5 20.6 8.0 9.7 2.9 −0.6 −0.9 100.9 48.0 4.2 8.7 0.8 53.1 6.8 8.5 27.5 9.7 15.6 2.2 2.0 2.0 98.0 47.2 2.9 4.6 0.0 62.2 7.9 9.8 21.3 8.8 11.8 0.6 3.6 −4.8 104.8 53.8 1.8 6.4 −0.6 62.8 10.8 7.8 18.0 5.9 10.6 1.5 3.2 −2.7 102.7 58.7 2.5 7.3 −7.9 31.8 10.3 6.5 18.5 6.9 10.5 1.1 2.6 30.4 69.6 24.7 (continued) Presentation and Analysis of Results 47 Table 2.3 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURE SHARES beverages, water, household (GDP = 100)a Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) Macedonia, FYR 100.0 82.8 25.4 2.5 3.7 14.5 3.1 5.2 7.4 4.4 2.6 4.4 Malta 100.0 71.6 10.7 2.1 2.9 8.5 4.8 8.5 8.9 2.6 7.6 5.1 Mexico 100.0 72.5 15.5 1.7 2.0 13.7 3.8 4.6 12.4 2.5 3.1 3.8 Montenegro 100.0 91.9 30.7 4.4 3.0 12.8 9.3 6.3 11.2 5.1 3.7 4.0 Netherlands 100.0 62.4 5.3 1.4 2.4 11.0 2.6 7.8 5.7 1.9 5.1 5.1 New Zealand 100.0 71.7 8.6 3.1 2.7 13.9 2.9 8.8 7.1 1.9 6.6 5.8 Norway 100.0 55.3 5.0 1.6 2.0 8.2 2.2 7.4 5.7 1.0 5.5 4.2 Poland 100.0 71.5 11.4 3.9 2.7 14.8 2.7 6.9 6.1 1.8 5.4 5.3 Portugal 100.0 76.9 11.3 2.3 3.7 10.9 3.7 9.4 8.9 2.0 5.6 5.9 Romania 100.0 72.2 17.0 3.1 2.4 13.7 3.1 8.0 6.8 3.1 4.4 3.5 e Russian Federation 100.0 57.7 14.6 4.0 4.4 5.6 2.4 4.5 6.0 2.2 3.1 3.2 Serbia 100.0 89.7 21.2 4.3 2.9 17.7 3.0 9.4 10.4 3.5 4.6 4.7 Slovak Republic 100.0 66.3 10.2 2.7 2.4 14.8 3.4 6.2 4.5 2.1 6.1 4.1 Slovenia 100.0 69.8 9.0 3.3 3.3 11.9 3.7 8.0 9.2 2.0 6.1 6.1 Spain 100.0 70.9 8.5 1.8 3.2 12.7 2.9 8.2 7.0 1.7 5.9 5.2 Sweden 100.0 67.2 5.7 1.7 2.3 12.7 2.4 8.1 6.2 1.6 6.1 6.6 Switzerland 100.0 63.5 5.0 2.0 1.9 13.6 2.3 8.5 5.1 1.4 5.1 5.0 Turkey 100.0 78.8 17.2 2.5 4.0 14.4 5.9 6.0 12.3 2.1 3.3 3.9 United Kingdom 100.0 78.4 5.6 2.2 3.6 15.6 3.1 8.7 8.3 1.3 8.7 6.2 United States 100.0 75.1 4.5 1.3 2.4 12.6 2.8 14.8 6.9 1.6 6.4 6.0 Total (47) 100.0 71.5 7.0 1.8 2.6 13.0 3.0 10.1 7.2 1.7 5.7 5.1 LATIN AMERICA Bolivia 100.0 62.6 21.1 1.0 1.3 6.7 4.5 5.4 10.7 0.7 0.6 3.8 Brazil 100.0 68.4 9.9 1.2 2.9 9.2 4.6 7.6 9.3 2.2 3.2 5.9 Colombia 100.0 68.0 11.3 1.9 4.0 9.8 2.6 5.1 7.5 2.7 3.2 5.9 Costa Rica 100.0 77.5 15.5 0.7 3.4 4.9 4.5 9.5 13.8 1.8 7.5 7.9 f Cuba … … … … … … … … … … … … Dominican Republic 100.0 88.9 21.6 5.3 2.9 13.2 3.2 5.5 11.5 3.8 1.9 3.9 Ecuador 100.0 67.1 13.6 1.7 2.7 9.1 4.7 5.5 7.5 3.6 3.4 6.9 El Salvador 100.0 98.5 25.1 1.9 5.2 16.5 9.3 7.9 8.6 3.4 4.5 4.5 Guatemala 100.0 90.0 34.9 1.4 4.7 11.3 5.0 6.1 6.4 6.5 2.8 3.7 Haiti 100.0 113.4 66.2 2.6 7.8 12.8 3.8 3.8 5.9 0.5 2.7 4.8 Honduras 100.0 85.9 25.4 2.7 3.8 10.6 3.5 8.4 8.2 2.7 3.2 7.5 Nicaragua 100.0 83.9 21.9 2.3 2.4 11.2 4.6 9.0 10.3 2.9 3.2 6.0 Panama 100.0 66.0 11.2 0.4 4.1 13.0 4.8 4.7 8.6 2.3 3.5 3.8 Paraguay 100.0 76.1 21.0 1.0 4.0 6.9 6.2 6.2 6.5 2.8 4.9 7.1 Peru 100.0 62.5 14.2 1.4 3.9 6.6 3.1 4.0 6.7 2.4 3.7 5.3 Uruguay 100.0 75.5 14.0 1.8 3.4 14.4 4.2 9.1 5.6 3.0 2.5 4.9 Venezuela, RB 100.0 60.7 13.1 1.8 2.8 3.0 3.5 5.5 8.1 3.4 3.9 5.1 Total (17) 100.0 68.6 11.6 1.4 3.1 8.7 4.3 6.9 8.8 2.5 3.3 5.7 48 Purchasing Power Parities and the Real Size of World Economies Miscel- Individual Individual Collective Individual laneous consumption consumption consumption Gross Changes in Balance consumption Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and and purchases by by by capital and Other and and Domestic households hotels services abroad households government government formation equipment Construction products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 2.8 5.8 0.9 75.1 7.7 10.6 20.6 6.9 12.8 0.8 5.6 −19.6 119.6 66.4 11.6 9.2 −10.8 60.8 10.8 9.6 15.1 5.5 7.7 1.9 −0.2 3.9 96.1 55.2 2.7 7.3 −0.3 66.3 6.2 5.5 21.8 6.7 14.6 0.4 1.5 −1.3 101.3 55.3 13.6 6.2 −18.3 82.5 9.4 12.1 18.4 5.7 12.3 0.4 −0.3 −22.2 122.2 75.1 2.2 12.2 −0.3 45.4 17.1 10.9 17.8 5.5 10.1 2.2 0.3 8.6 91.4 38.2 4.2 7.5 −1.5 59.8 12.0 8.2 18.2 6.2 10.4 1.5 0.5 1.4 98.6 48.0 2.3 8.7 1.5 41.2 14.1 7.4 19.5 6.3 9.3 3.9 4.6 13.3 86.7 35.1 1.7 9.2 −0.4 61.1 10.4 7.6 20.2 7.6 11.4 1.3 1.9 −1.2 101.2 56.8 7.5 8.6 −3.1 66.0 10.8 9.1 18.0 5.4 11.0 1.6 0.4 −4.4 104.4 59.1 2.1 4.9 0.2 63.5 8.7 6.3 26.1 8.5 16.4 1.2 0.7 −5.3 105.3 54.9 1.6 5.1 1.1 49.1 8.6 9.4 20.8 7.5 11.6 1.7 3.6 8.6 91.4 46.7 1.8 7.5 −1.2 77.0 12.8 6.5 18.5 7.9 9.5 1.1 1.7 −16.4 116.4 66.5 2.9 6.9 0.0 57.6 8.7 9.3 23.1 7.7 10.4 5.0 0.7 0.5 99.5 52.3 4.1 7.0 −3.9 57.5 12.4 8.5 18.6 8.0 9.2 1.4 1.6 1.5 98.5 51.0 10.4 6.8 −3.2 58.6 12.3 9.0 20.7 6.0 10.6 4.1 0.5 −1.1 101.1 50.0 2.6 11.6 −0.4 48.0 19.1 7.4 18.7 6.9 9.1 2.7 1.2 5.6 94.4 38.8 3.8 9.7 0.0 57.3 6.2 4.8 20.6 9.0 9.3 2.2 0.7 10.4 89.6 46.0 4.6 5.8 −3.2 71.2 7.6 6.3 21.8 12.7 9.1 0.1 1.7 −8.7 108.7 60.6 5.2 9.4 0.4 64.6 13.8 8.1 14.4 2.9 8.2 3.2 0.6 −1.5 101.5 51.6 4.3 11.6 −0.2 69.0 6.1 10.1 18.2 6.5 8.3 3.3 0.2 −3.7 103.7 58.6 4.2 10.2 −0.1 61.4 10.1 8.7 19.6 6.7 10.2 2.7 0.6 −0.4 100.4 51.6 4.9 1.9 0.0 61.0 1.6 12.1 19.0 10.6 7.1 1.2 0.6 5.7 94.3 57.6 3.9 8.6 0.0 60.3 8.1 12.6 19.3 10.1 8.0 1.2 0.4 −0.7 100.7 54.1 7.1 7.0 0.0 61.3 6.7 9.1 23.6 8.2 14.5 0.9 0.2 −0.9 100.9 55.1 3.6 3.6 0.8 65.3 12.2 5.8 19.8 8.5 10.7 0.6 1.8 −4.9 104.9 63.2 … … … … … … … … … … … … … … 7.2 9.4 −0.5 86.5 2.4 5.0 16.3 4.6 11.4 0.3 0.1 −10.3 110.3 77.8 2.7 6.1 −0.4 61.1 6.0 6.7 26.0 8.4 7.4 10.2 3.0 −2.8 102.8 54.2 6.6 5.5 −0.6 93.3 5.2 5.9 12.5 6.3 6.2 0.1 1.8 −18.7 118.7 83.3 5.2 3.7 −1.7 85.3 4.7 5.6 14.7 7.7 7.0 0.0 0.4 −10.7 110.7 76.5 0.2 2.4 0.0 112.2 1.2 0.1 29.0 0.7 28.2 0.0 0.0 −42.5 142.5 107.5 4.7 5.3 0.0 77.6 8.3 7.8 24.4 13.6 9.6 1.3 1.6 −19.7 119.7 72.0 5.0 6.3 −1.3 77.8 6.2 8.5 22.5 8.7 12.0 1.8 0.8 −15.8 115.8 70.6 3.4 6.2 0.0 60.2 5.8 6.5 26.1 11.8 14.3 0.0 1.1 0.2 99.8 50.6 3.6 6.0 0.0 70.1 6.0 4.6 16.4 7.0 8.1 1.3 0.4 2.5 97.5 68.2 5.6 5.7 0.0 59.5 3.1 6.2 26.0 9.3 15.8 0.8 1.1 4.3 95.7 55.0 5.2 6.0 1.5 67.9 7.6 5.6 19.0 6.0 11.8 1.2 0.4 −0.5 100.5 57.0 7.3 3.1 0.3 55.2 5.5 6.0 17.7 8.0 9.1 0.6 5.3 10.2 89.8 53.0 4.6 7.6 0.0 61.3 7.2 10.7 20.0 9.5 9.2 1.2 1.0 −0.2 100.2 55.4 (continued) Presentation and Analysis of Results 49 Table 2.3 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURE SHARES beverages, water, household (GDP = 100)a Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) CARIBBEAN Anguilla 100.0 87.6 10.9 2.0 2.6 17.9 3.4 2.1 15.9 6.8 3.7 3.6 Antigua and Barbuda 100.0 68.1 10.5 1.1 1.6 18.7 2.9 6.1 7.1 3.5 2.2 3.8 Aruba 100.0 78.2 5.8 0.5 2.5 26.0 3.2 9.3 9.3 2.8 5.4 4.8 Bahamas, The 100.0 76.8 7.3 0.9 2.5 23.5 3.3 6.5 5.9 3.1 3.2 5.0 Barbados 100.0 89.1 12.3 1.4 1.6 46.5 2.4 4.1 6.2 3.7 3.3 4.4 Belize 100.0 76.0 13.8 1.2 6.0 19.0 5.0 5.6 9.8 2.4 5.0 4.0 Bermuda 100.0 78.2 6.8 1.3 1.6 21.7 3.7 6.4 4.8 2.1 4.5 5.7 Bonaireg … … … … … … … … … … … … Cayman Islands 100.0 74.8 4.6 0.9 2.2 25.8 3.5 3.4 7.0 3.2 3.6 3.7 Curaçao 100.0 76.7 8.1 0.9 5.8 24.5 2.3 5.8 7.2 2.9 3.4 3.2 Dominica 100.0 89.7 15.4 0.7 4.3 20.3 4.5 5.8 17.1 3.4 3.4 5.7 Grenada 100.0 97.2 19.2 1.7 4.3 18.8 4.0 3.9 17.6 9.4 2.6 6.0 Jamaica 100.0 93.0 26.1 1.2 1.7 12.6 5.2 5.6 13.2 2.5 8.2 6.9 Montserrat 100.0 95.3 15.0 2.0 1.2 17.9 4.0 9.6 25.4 6.1 2.8 5.6 St. Kitts and Nevis 100.0 74.9 12.3 2.1 3.2 19.6 4.7 4.4 6.8 3.9 2.6 4.0 St. Lucia 100.0 80.5 16.1 1.4 4.8 18.4 4.5 4.3 7.5 4.4 1.5 6.7 St. Vincent and the Grenadines 100.0 92.6 18.3 5.2 1.9 24.8 3.9 5.8 16.1 6.2 5.7 5.5 Sint Maarten 100.0 64.3 5.4 0.2 3.2 26.7 2.8 2.1 7.4 3.2 2.5 2.0 Suriname 100.0 38.3 14.3 1.0 1.3 6.5 1.8 1.9 2.9 1.4 1.4 0.5 Trinidad and Tobago 100.0 58.1 12.2 0.6 0.8 7.1 2.4 4.5 6.2 1.2 3.8 6.1 Turks and Caicos Islands 100.0 39.4 5.6 0.7 1.4 4.2 1.5 3.7 9.1 0.7 2.0 4.5 Virgin Islands, British 100.0 38.4 6.5 0.8 3.6 8.0 4.8 2.1 3.6 1.2 1.5 2.1 Total (22) 100.0 72.2 13.3 1.0 1.9 16.3 3.3 5.0 7.8 2.4 4.4 5.3 WESTERN ASIA Bahrain 100.0 43.7 5.9 0.2 2.5 8.9 3.1 3.2 4.6 2.0 2.8 4.9 Egypt, Arab Rep.b 100.0 79.5 33.3 2.6 4.8 10.4 3.8 7.3 4.7 2.0 2.4 5.3 Iraq 100.0 47.0 14.4 0.3 2.8 12.2 2.2 3.4 3.4 0.7 0.5 5.2 Jordan 100.0 79.8 22.3 2.5 3.5 16.0 3.4 5.6 8.1 3.1 1.3 9.8 Kuwait 100.0 27.8 4.3 0.1 2.2 6.5 3.4 2.2 2.0 0.9 1.0 2.7 Oman 100.0 36.0 7.0 0.1 2.0 6.6 1.4 2.1 5.7 1.7 1.2 4.0 Qatar 100.0 16.6 1.8 0.0 0.6 3.7 0.7 1.2 1.4 0.4 1.2 2.5 Saudi Arabia 100.0 36.7 5.8 0.1 1.8 7.6 2.4 3.0 2.5 1.5 1.1 6.3 c Sudan 100.0 70.2 36.3 0.5 3.1 10.3 4.5 0.9 5.7 1.1 1.6 2.3 United Arab Emirates 100.0 52.8 6.2 0.1 6.5 17.5 1.9 0.8 8.5 3.1 1.4 2.5 West Bank and Gaza 100.0 108.2 34.2 4.3 6.3 11.8 5.6 7.9 10.2 3.3 2.6 9.1 Yemen, Rep. 100.0 73.0 33.0 3.5 3.2 10.4 2.2 7.0 4.2 0.8 0.3 5.1 Total (12) 100.0 45.7 11.2 0.5 3.1 9.9 2.5 3.0 4.2 1.7 1.3 4.6 50 Purchasing Power Parities and the Real Size of World Economies Miscel- Individual Individual Collective Individual laneous consumption consumption consumption Gross Changes in Balance consumption Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and and purchases by by by capital and Other and and Domestic households hotels services abroad households government government formation equipment Construction products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 3.4 15.3 0.0 84.2 3.4 12.5 17.5 4.6 12.6 0.3 −1.6 −16.1 116.1 73.6 2.2 8.4 0.0 60.0 8.1 10.3 20.9 4.4 16.2 0.4 0.6 0.0 100.0 48.6 1.8 6.6 0.0 62.1 16.1 9.5 26.4 6.5 19.9 0.0 1.6 −15.7 115.7 44.5 4.1 11.4 0.0 71.0 5.8 9.0 26.4 12.9 13.4 0.1 1.7 −13.9 113.9 54.4 16.4 7.3 −20.6 81.5 7.6 10.6 15.6 7.6 7.9 0.0 −0.9 −14.4 114.4 40.9 0.5 3.7 0.0 71.6 4.4 11.3 15.1 6.4 8.4 0.3 1.4 −3.8 103.8 54.3 9.1 10.5 0.0 67.2 11.1 8.2 20.2 10.5 9.7 0.0 1.1 −7.8 107.8 47.6 … … … … … … … … … … … … … … 3.6 13.4 0.0 70.3 4.5 8.9 22.4 11.1 11.3 0.1 0.0 −6.1 106.1 50.6 2.4 15.9 −5.8 69.1 7.6 7.3 39.8 21.6 11.3 6.9 1.5 −25.3 125.3 55.1 2.5 6.8 0.0 81.8 7.9 13.6 23.0 11.1 11.5 0.4 −11.2 −15.2 115.2 68.4 1.7 7.0 1.0 89.9 7.3 8.4 20.4 8.0 12.1 0.4 −0.1 −25.9 125.9 79.4 11.4 11.0 −12.7 85.6 7.4 8.6 20.8 10.0 10.4 0.4 0.5 −22.9 122.9 78.0 0.3 10.2 −4.9 80.8 14.5 33.0 28.7 8.4 19.8 0.5 0.0 −57.0 157.0 71.3 4.3 7.0 0.0 68.5 6.4 10.7 30.9 7.7 22.7 0.6 0.0 −16.5 116.5 54.7 1.4 9.5 0.0 73.9 6.6 10.0 30.0 9.2 20.2 0.6 0.0 −20.5 120.5 62.9 2.9 7.8 −11.6 82.1 10.5 10.3 23.9 7.3 16.1 0.4 1.5 −28.2 128.2 67.6 1.1 7.7 0.0 60.4 3.8 12.7 16.8 9.1 4.8 2.9 0.0 6.2 93.8 40.3 0.5 4.7 0.0 37.4 0.9 11.4 37.0 30.4 5.9 0.7 6.9 6.3 93.7 35.2 5.3 7.9 0.0 45.8 12.3 1.7 15.0 7.4 7.3 0.3 0.0 25.2 74.8 41.4 1.5 4.6 0.0 35.8 3.6 19.0 14.5 5.1 9.4 0.0 0.1 27.0 73.0 33.5 2.1 2.3 0.0 35.1 3.3 5.2 23.9 10.6 12.6 0.7 −1.9 34.4 65.6 29.8 6.2 9.1 −3.8 63.6 8.6 7.1 21.3 10.6 10.1 0.6 0.7 −1.3 101.3 52.0 1.9 2.7 1.1 38.7 5.0 8.7 15.6 4.8 10.8 0.1 0.7 31.2 68.8 31.4 2.5 5.6 −5.2 75.6 4.0 7.5 16.7 7.8 8.5 0.5 0.4 −4.1 104.1 68.6 0.4 1.5 0.0 39.8 7.2 15.1 19.4 7.5 11.8 0.1 −0.4 18.9 81.1 31.1 1.6 2.3 0.3 71.4 8.3 11.1 21.4 5.6 14.5 1.3 1.6 −13.8 113.8 60.8 0.8 1.8 0.0 23.3 4.5 10.5 15.8 6.3 7.9 1.6 0.6 45.4 54.6 17.5 1.0 2.8 0.3 30.0 6.0 11.2 26.3 10.5 13.1 2.7 −3.1 29.6 70.4 25.0 0.3 2.3 0.4 12.8 3.8 8.7 29.3 14.3 4.6 10.4 0.0 45.4 54.6 9.4 1.4 1.8 1.3 27.2 9.6 9.9 22.7 8.7 11.2 2.7 4.1 26.6 73.4 21.8 1.6 1.8 0.4 69.6 0.5 6.3 22.3 11.7 10.6 0.0 2.6 −1.4 101.4 62.8 1.9 2.4 0.0 51.7 1.1 6.2 22.0 8.7 11.0 2.3 1.0 18.0 82.0 36.6 2.6 9.0 1.4 96.5 11.7 18.2 20.7 3.6 14.8 2.2 −3.4 −43.6 143.6 92.4 0.0 3.3 0.0 68.1 4.9 9.1 13.2 1.2 10.2 1.7 5.6 −1.0 101.0 62.6 1.4 2.5 −0.1 40.0 5.7 9.3 21.4 8.7 10.2 2.6 1.7 21.9 78.1 32.5 (continued) Presentation and Analysis of Results 51 Table 2.3 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURE SHARES beverages, water, household (GDP = 100)a Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) SINGLETONS Georgia 100.0 78.3 24.6 4.1 2.0 8.9 2.9 8.2 7.2 2.3 5.5 5.4 Iran, Islamic Rep. 100.0 44.4 10.8 0.2 1.9 12.8 1.6 3.6 3.3 1.4 1.1 1.4 Total (2) 100.0 45.2 11.1 0.3 1.9 12.7 1.7 3.7 3.3 1.4 1.2 1.5 WORLDh (179) 100.0 66.5 8.7 1.6 2.7 11.5 2.9 8.6 6.6 1.7 4.7 5.0 Source: ICP, http://icp.worldbank.org/. Note: ... = data suppressed because of incompleteness. a. All shares are rounded to one decimal place. More precision can be found in the Excel version of the table, which can be downloaded from the ICP website. b. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. c. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. d. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. e. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. f. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. g. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. h. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 52 Purchasing Power Parities and the Real Size of World Economies Miscel- Individual Individual Collective Individual laneous consumption consumption consumption Gross Changes in Balance consumption Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and and purchases by by by capital and Other and and Domestic households hotels services abroad households government government formation equipment Construction products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 2.6 4.6 0.0 74.0 4.3 13.9 22.5 8.4 10.8 3.2 3.8 −18.5 118.5 69.7 0.5 4.7 1.1 41.8 2.6 8.4 25.7 11.6 13.3 0.8 10.9 10.7 89.3 31.4 0.6 4.7 1.1 42.6 2.7 8.5 25.6 11.5 13.2 0.8 10.7 10.0 90.0 32.4 3.7 8.7 −0.1 57.4 9.1 8.5 23.0 7.9 12.6 2.5 1.2 0.8 99.2 48.9 Presentation and Analysis of Results 53 Table 2.4 Purchasing Power Parities (U.S. Dollar = 1.00), ICP 2011 PPPs Alcoholic Housing, Furnishings, (US$ = 1.00)a beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) AFRICA Algeria 30.502 28.880 50.736 45.390 41.983 24.135 40.767 13.000 33.258 35.940 Angola 68.315 69.973 118.137 45.559 84.022 54.741 106.349 48.788 85.333 87.875 Benin 214.035 207.312 370.582 195.942 204.200 183.014 306.313 121.413 261.628 244.766 Botswana 3.764 4.068 6.493 5.494 3.612 4.464 6.733 2.265 4.975 3.263 Burkina Faso 213.659 203.814 384.850 213.069 184.918 150.487 294.974 118.447 319.797 251.165 Burundi 425.768 436.019 811.292 734.215 411.072 245.866 719.055 172.356 1,009.766 809.509 Cameroon 227.212 213.640 352.218 238.073 270.966 152.184 372.608 156.911 327.774 373.135 Cape Verde 48.592 44.321 73.270 50.568 55.775 42.236 57.249 25.849 70.940 37.054 Central African Republic 255.862 243.981 490.055 270.572 221.472 126.380 398.509 125.804 367.859 408.955 Chad 250.443 231.089 405.506 273.297 223.693 206.605 366.992 122.505 344.546 362.389 Comoros 207.584 201.132 355.581 316.673 219.065 149.348 395.660 105.986 297.720 353.045 Congo, Rep. 289.299 276.070 544.905 268.940 299.812 161.770 396.022 144.276 436.562 418.054 Congo, Dem. Rep. 521.870 492.254 995.879 619.168 501.385 276.923 643.047 241.443 759.322 659.755 Côte d’Ivoire 228.228 219.769 384.924 239.408 266.556 157.061 300.325 108.338 340.632 341.438 Djibouti 94.003 94.223 152.682 102.279 99.873 75.699 127.879 65.130 139.712 86.983 Egypt, Arab Rep.b 1.625 1.606 3.436 2.808 2.059 0.711 3.145 0.830 2.298 1.909 Equatorial Guinea 294.572 304.097 589.322 232.061 298.294 220.223 512.584 165.533 420.726 307.635 Ethiopia 4.919 4.934 8.869 6.164 5.821 4.581 7.853 2.385 7.979 5.305 Gabon 318.156 334.429 655.855 224.212 349.681 272.532 418.056 200.389 366.084 491.042 Gambia, The 9.939 9.766 19.680 10.536 6.736 7.793 13.390 4.379 13.590 8.031 Ghana 0.699 0.715 1.570 0.845 0.685 0.463 0.985 0.284 0.763 0.723 Guinea 2,518.386 2,316.675 5,352.043 2,579.447 2,128.158 783.311 3,128.116 1,181.841 3,516.903 3,411.063 Guinea-Bissau 220.085 221.672 400.082 252.336 258.633 175.909 364.520 99.848 354.574 276.273 Kenya 34.298 33.121 57.162 45.543 29.655 21.796 46.101 17.176 64.245 26.523 Lesotho 3.923 3.652 5.909 4.687 3.692 2.630 5.867 2.029 5.537 4.292 Liberia 0.517 0.519 0.974 0.627 0.446 0.585 0.600 0.221 0.721 0.668 Madagascar 673.730 648.609 1168.502 780.876 527.001 611.475 878.136 294.532 1,282.158 1,130.163 Malawi 76.259 72.760 139.599 80.997 61.783 32.754 116.176 29.785 170.095 86.546 Mali 210.193 202.208 337.779 198.514 211.992 183.738 323.588 92.883 374.476 264.925 Mauritania 115.855 103.576 187.179 118.403 85.477 79.922 146.549 56.410 149.556 142.122 Mauritius 15.941 16.535 26.573 26.403 14.211 11.609 24.149 8.425 32.685 14.309 Morocco 3.677 3.859 6.745 7.936 4.290 2.058 5.494 2.953 5.624 5.306 Mozambique 16.030 14.714 25.956 15.548 14.057 9.035 24.847 9.500 21.892 18.716 Namibia 4.663 4.787 8.100 4.866 3.702 5.223 5.367 3.069 6.475 4.015 Niger 221.087 210.030 404.077 249.451 155.168 172.083 238.900 124.830 315.442 359.186 Nigeria 74.378 72.612 147.012 69.312 63.131 58.511 76.549 31.751 92.809 88.164 Rwanda 260.751 234.141 395.081 321.317 281.734 156.671 273.610 118.960 488.544 278.187 54 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 30.056 7.265 35.529 31.437 31.772 12.652 16.887 42.024 92.827 22.862 30.305 32.518 105.365 27.003 127.387 70.663 73.833 44.125 56.269 56.979 127.789 30.395 66.927 80.752 280.396 80.370 296.896 152.285 224.917 117.370 145.384 300.059 596.385 174.495 216.125 245.853 4.914 1.433 6.456 3.869 4.438 2.017 3.206 3.280 8.340 1.576 3.736 4.661 309.305 56.244 231.348 185.561 222.242 107.352 178.693 282.177 632.359 151.518 215.759 247.388 672.530 97.107 621.541 412.487 487.327 168.112 267.615 694.095 1,537.329 376.842 451.102 566.859 312.047 81.898 318.543 184.641 230.375 147.671 191.977 313.991 576.878 204.738 228.238 254.190 57.595 17.731 48.689 40.568 47.565 25.998 39.411 58.738 106.972 37.180 47.065 51.239 332.745 53.939 319.759 230.136 267.869 108.142 222.564 326.106 644.138 195.366 254.555 301.388 263.169 58.233 366.836 189.836 251.296 138.720 194.455 352.971 646.425 233.637 250.393 273.669 307.250 59.084 266.392 221.546 220.572 99.914 161.339 235.828 483.486 138.494 203.046 249.360 375.075 100.640 355.001 198.525 296.500 166.999 249.543 389.529 645.298 237.979 304.566 328.144 563.809 118.748 819.140 492.233 537.732 263.255 433.663 670.561 1,262.883 411.468 520.880 624.732 349.107 97.615 262.761 187.185 235.688 142.951 201.782 280.418 637.984 147.727 227.432 259.002 138.358 36.887 143.404 97.928 101.481 56.525 79.427 95.412 221.793 49.438 93.384 111.787 1.981 0.507 2.410 1.585 1.803 0.566 0.822 2.689 6.656 1.391 1.646 2.096 471.311 92.634 396.115 288.349 321.354 208.318 424.930 276.018 651.258 139.287 296.396 347.065 5.573 1.042 4.918 3.936 5.439 2.109 3.563 7.257 22.179 2.796 5.206 5.685 346.142 151.414 449.083 294.853 359.219 200.687 270.502 341.082 641.631 238.831 329.296 382.640 11.260 3.338 18.363 8.225 10.826 3.865 6.318 15.386 40.512 6.639 10.361 11.878 0.917 0.217 1.214 0.580 0.788 0.328 0.566 0.728 2.192 0.273 0.703 0.870 3,007.694 491.235 3,939.802 2,193.499 2,572.343 757.024 1,452.971 3,918.304 8,810.390 2,112.444 2,519.622 3,078.433 349.481 36.493 357.777 200.254 248.236 64.014 141.517 284.615 648.499 150.102 220.501 269.672 43.897 16.344 43.244 27.262 35.430 20.076 34.539 45.103 107.244 22.760 35.328 40.572 4.124 1.831 6.030 3.182 3.864 2.405 3.803 4.480 9.989 2.388 3.847 4.338 0.571 0.128 0.621 0.423 0.568 0.261 0.407 0.567 1.368 0.265 0.516 0.591 734.663 185.694 537.343 534.671 704.913 371.423 623.767 1,057.595 2,641.207 510.621 705.252 764.790 117.541 31.032 126.817 61.150 78.017 45.753 89.255 94.347 215.156 49.599 76.604 90.743 252.679 67.442 337.254 169.240 221.868 96.115 158.062 280.664 609.570 154.951 211.692 238.355 133.247 37.018 179.295 98.129 112.807 52.798 87.516 172.135 395.510 90.122 118.151 124.699 18.718 6.358 30.157 16.094 18.285 6.849 10.190 16.322 34.607 9.035 15.794 19.559 4.754 1.642 5.484 3.819 4.193 2.040 3.245 3.535 9.616 1.581 3.711 4.897 17.793 8.538 16.117 11.285 15.527 11.507 20.501 19.633 37.092 11.817 15.913 17.391 5.455 1.554 7.415 3.630 5.131 2.773 4.006 4.108 9.814 2.084 4.582 5.224 293.685 47.662 292.256 185.423 228.753 113.222 199.902 284.825 520.917 183.047 223.884 248.570 85.736 28.683 98.119 52.658 79.531 35.768 56.511 92.040 210.505 48.496 74.143 85.360 338.584 119.571 311.579 223.509 246.834 193.765 361.760 373.046 754.637 210.292 265.992 279.765 (continued) Presentation and Analysis of Results 55 Table 2.4 (Continued) PPPs Alcoholic Housing, Furnishings, (US$ = 1.00)a beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) São Tomé and Príncipe 8,527.157 9,091.140 17,061.052 10,212.969 9,837.834 7,455.455 14,014.117 3,994.580 13,685.972 10,968.728 Senegal 236.287 228.085 404.663 266.125 208.121 177.926 282.251 126.884 371.307 295.559 Seychelles 6.690 6.987 11.970 16.058 8.474 4.449 10.917 3.122 12.145 7.362 Sierra Leone 1,553.139 1,599.223 3,310.580 1,580.447 1,178.052 905.604 2,156.711 706.823 2,833.988 2,697.819 South Africa 4.774 4.769 6.637 4.994 5.357 4.155 7.736 3.543 6.995 4.181 c Sudan 1.224 1.342 2.405 2.278 0.899 1.125 1.783 0.537 2.283 1.594 Swaziland 3.900 3.820 5.971 4.686 4.258 3.294 5.440 1.949 5.791 3.756 Tanzania 522.483 539.161 948.924 764.066 483.312 527.251 743.475 206.764 829.729 530.828 Togo 215.060 209.618 402.353 220.192 197.023 148.357 303.684 108.131 410.501 396.666 Tunisia 0.592 0.624 1.068 0.984 1.024 0.461 0.930 0.382 0.877 0.445 Uganda 833.540 868.234 1,419.160 1,165.303 948.693 793.013 1,309.352 455.930 1,617.989 1,011.713 Zambia 2,378.380 2,332.796 3,914.496 3,169.257 2,363.291 1,703.604 3,697.202 1,125.337 4,781.428 5,040.040 Zimbabwe 0.504 0.491 0.825 0.435 0.572 0.391 0.941 0.265 0.885 0.649 Total (50) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. ASIA AND THE PACIFIC Bangladesh 23.145 22.805 39.209 19.099 25.936 16.181 31.291 10.646 48.795 7.472 Bhutan 16.856 15.675 24.439 29.060 14.995 13.340 26.101 8.943 24.846 10.654 Brunei Darussalam 0.717 0.812 1.070 2.071 0.986 0.646 1.838 0.546 0.870 1.268 Cambodia 1,347.115 1,354.578 2,331.001 1,429.182 1,184.241 1,406.818 1,884.477 515.098 2,543.614 1,419.612 Chinad 3.506 3.493 5.155 5.564 4.351 2.651 5.827 2.026 4.619 2.392 Fiji 1.042 1.119 1.504 1.367 0.950 1.397 1.560 0.631 1.643 1.321 Hong Kong SAR, China 5.462 5.580 7.468 7.232 4.228 6.020 7.233 5.110 8.125 2.693 India 15.109 14.006 20.873 22.195 12.156 10.160 24.448 5.227 28.738 10.855 Indonesia 3,606.566 3,730.983 6,157.657 6,622.350 4,903.733 3,042.564 4,933.488 2,483.411 5,679.080 3,875.469 Lao PDR 2,467.753 2,539.736 5,270.823 3,453.660 2,361.992 1,346.045 4,076.574 1,032.080 5,810.923 1,858.096 Macao SAR, China 4.589 5.236 7.697 4.822 5.646 4.933 8.539 3.958 7.174 3.209 Malaysia 1.459 1.478 2.275 2.670 1.809 1.013 2.515 0.923 2.293 1.803 Maldives 8.527 9.479 11.468 6.454 7.155 18.378 11.559 3.560 12.006 4.804 Mongolia 537.127 516.566 902.689 537.792 702.971 493.523 1,099.131 167.374 765.573 709.616 Myanmar 234.974 229.428 460.487 392.505 236.055 177.945 383.760 80.253 588.254 282.002 Nepal 24.628 23.781 38.433 34.457 21.491 19.036 33.316 8.878 67.859 24.708 Pakistan 24.346 23.438 41.794 27.343 26.862 14.690 42.664 8.637 46.456 20.388 Philippines 17.854 17.658 27.590 16.870 22.757 14.333 23.305 12.516 26.851 28.026 Singapore 0.891 1.117 1.364 2.558 0.909 1.345 1.446 0.818 1.662 0.889 Sri Lanka 38.654 37.663 68.447 43.560 35.854 26.225 67.631 15.615 73.151 29.822 Taiwan, China 15.112 15.140 24.167 19.640 13.367 14.974 25.063 7.608 21.955 8.605 Thailand 12.370 12.024 19.962 19.982 11.307 7.399 20.897 7.141 20.666 10.809 Vietnam 6,709.192 6,709.833 11,848.213 6,325.120 6,165.746 7,010.913 9,838.586 2,192.803 16,568.476 7,836.986 Total (23) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 56 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 13,376.353 2,149.474 12,688.537 6,993.394 10,194.790 2,819.715 4,126.597 9,241.418 24,171.930 3,747.563 8,579.655 11,177.667 278.748 88.128 337.755 200.000 246.107 139.583 194.217 292.180 613.280 164.140 236.736 272.043 8.671 2.223 21.400 7.254 7.895 2.524 3.370 8.787 16.854 5.415 6.674 8.864 1,922.111 599.129 2,161.433 1,376.626 1,767.190 638.725 1,096.515 2,116.595 5,503.057 920.123 1,650.738 2,019.469 5.761 2.411 6.942 4.700 5.068 3.064 4.499 4.596 9.138 2.782 4.730 5.548 1.659 0.436 1.306 1.348 1.486 0.424 0.600 1.258 3.317 0.597 1.223 1.584 4.796 2.278 5.118 3.914 4.049 2.677 4.116 3.651 9.939 1.603 3.879 4.374 706.846 216.587 649.250 441.795 585.520 286.040 531.374 589.644 1,952.579 223.196 547.716 629.659 352.321 48.523 306.679 156.687 232.215 84.953 160.620 289.650 675.887 149.704 217.596 258.365 0.872 0.179 0.864 0.590 0.697 0.259 0.404 0.611 1.913 0.253 0.598 0.765 1,133.831 269.971 1,129.419 745.005 946.890 441.279 787.670 991.598 3,438.705 381.763 872.463 1,017.697 3,000.717 1,261.497 2,770.402 1,697.794 2,505.341 1,491.393 2,269.101 2,502.117 6,248.330 1,231.789 2,377.336 2,761.234 0.632 0.180 0.761 0.387 0.536 0.255 0.386 0.661 1.363 0.374 0.505 0.584 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 32.074 7.271 25.561 32.419 24.849 11.428 19.139 27.331 74.844 13.711 23.409 27.241 19.221 5.932 15.131 18.018 16.963 8.356 11.145 22.242 59.395 10.943 17.103 17.590 0.980 0.397 1.031 0.939 0.853 0.519 0.545 0.845 1.444 0.547 0.787 0.915 1,659.132 295.104 1,435.989 1,782.481 1,527.558 455.657 903.485 1,546.795 4,210.961 731.735 1,346.019 1,647.472 3.179 1.761 3.453 4.425 3.696 2.115 3.407 3.769 7.771 2.184 3.538 4.024 1.317 0.395 1.283 1.239 1.217 0.594 0.766 0.964 2.035 0.567 1.042 1.165 4.406 3.586 5.661 5.623 5.753 4.823 6.577 5.582 9.148 4.013 5.587 5.798 19.151 5.442 20.778 20.227 14.975 8.824 14.580 18.887 48.134 9.598 15.241 16.394 3,972.661 1,130.723 4,075.512 3,973.200 4,091.939 1,745.408 2,946.737 3,644.949 9,087.622 1,920.377 3,619.225 4,303.985 3,870.335 323.801 3,453.192 3,603.112 2,914.847 608.252 1,257.088 2,903.759 8,303.871 1,365.707 2,494.284 3,311.374 5.107 2.187 5.577 6.179 5.462 3.601 5.561 4.972 8.000 3.210 5.157 5.699 1.641 0.632 1.380 1.857 1.586 0.863 1.236 1.589 3.307 0.929 1.477 1.736 9.295 3.062 6.705 8.582 10.676 3.994 5.157 8.725 16.291 5.474 8.527 8.367 704.127 120.073 626.364 754.770 590.330 171.697 321.823 673.132 1,513.112 374.028 543.470 617.312 300.591 30.875 244.550 384.713 275.828 57.672 117.871 309.744 899.997 137.510 234.780 306.294 29.046 6.722 26.447 31.820 25.759 13.065 24.727 31.785 76.442 16.875 25.265 27.710 29.495 7.940 33.426 34.012 25.414 12.828 18.950 33.691 93.382 16.141 24.637 28.125 21.404 5.933 18.506 21.844 18.873 11.541 19.032 19.201 47.289 9.959 17.945 20.811 0.839 0.642 0.921 1.159 1.171 0.820 0.835 0.809 1.379 0.540 0.984 1.176 43.336 9.979 60.263 52.204 42.219 14.294 25.064 51.363 130.729 26.378 39.263 46.186 16.055 7.844 13.900 16.885 15.995 10.415 14.252 16.316 30.511 10.555 15.225 16.501 14.539 4.823 10.778 15.871 12.844 7.264 12.386 13.503 33.118 6.793 12.441 14.398 7,493.130 1,377.315 7,199.463 8,406.631 7,624.973 2,144.721 3,507.570 8,252.133 20,999.077 4,261.080 6,717.197 7,815.116 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. (continued) Presentation and Analysis of Results 57 Table 2.4 (Continued) PPPs Alcoholic Housing, Furnishings, (US$ = 1.00)a beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) COMMONWEALTH OF INDEPENDENT STATES Armenia 187.095 152.389 307.022 132.876 308.634 45.532 278.122 80.450 290.455 217.902 Azerbaijan 0.360 0.282 0.497 0.257 0.569 0.087 0.517 0.169 0.566 0.401 Belarus 1,889.308 1,536.970 2,787.022 1,364.111 3,467.556 434.660 3,374.569 849.825 3,506.415 1,346.222 Kazakhstan 80.171 70.553 105.203 49.216 110.002 56.286 108.395 36.826 116.329 72.795 Kyrgyz Republic 17.757 14.522 31.037 11.766 32.355 3.431 27.833 7.695 31.229 14.494 Moldova 5.535 4.599 7.769 3.431 9.327 2.425 8.296 2.495 9.834 5.055 e Russian Federation 17.346 14.837 25.517 12.136 24.282 6.688 22.300 10.901 28.071 13.292 Tajikistan 1.740 1.484 3.136 1.545 3.815 0.346 3.449 0.611 3.987 1.120 Ukraine 3.434 2.852 5.011 2.470 6.081 0.982 4.685 1.601 5.842 3.104 Total (9) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. EUROSTAT-OECD Albania 45.452 47.617 78.529 40.445 81.406 39.923 87.079 25.013 108.431 89.749 Australia 1.511 1.505 1.632 1.786 1.482 1.822 1.414 1.550 1.526 1.080 Austria 0.830 0.850 0.980 0.621 0.809 0.766 0.940 0.748 1.180 0.676 Belgium 0.839 0.876 0.898 0.655 0.907 0.918 0.910 0.734 1.138 0.873 Bosnia and Herzegovina 0.724 0.770 1.217 0.632 1.702 0.443 1.090 0.594 1.583 1.139 Bulgaria 0.660 0.657 1.095 0.839 1.295 0.442 1.068 0.330 1.434 1.048 Canada 1.243 1.271 1.546 1.491 1.212 1.223 1.427 1.192 1.450 1.223 Chile 348.017 353.270 512.602 362.499 478.358 327.442 489.811 277.773 486.429 434.318 Croatia 3.802 3.972 5.673 3.982 6.245 2.914 5.270 2.600 6.832 4.244 Cyprus 0.673 0.700 0.915 0.644 0.798 0.558 0.805 0.559 0.953 0.427 Czech Republic 13.468 13.447 16.631 13.897 20.094 14.214 17.901 8.458 21.523 20.396 Denmark 7.689 8.447 8.668 6.177 7.748 9.315 7.773 6.947 11.447 5.222 Estonia 0.524 0.537 0.709 0.537 0.818 0.539 0.726 0.312 0.913 0.534 Finland 0.907 0.951 0.953 0.898 0.985 1.049 0.971 0.727 1.293 0.579 France 0.845 0.856 0.893 0.718 0.843 0.948 0.956 0.677 1.157 0.841 Germany 0.779 0.781 0.865 0.628 0.830 0.868 0.845 0.565 1.170 0.584 Greece 0.693 0.709 0.864 0.653 0.764 0.675 0.850 0.469 1.055 0.914 Hungary 123.650 121.164 187.217 113.616 184.804 103.710 168.273 65.679 260.871 217.219 Iceland 133.563 135.543 149.608 178.242 178.096 100.261 167.395 109.906 207.367 95.485 Ireland 0.827 0.941 0.991 1.212 0.843 0.935 0.905 0.930 1.174 0.845 Israel 3.945 4.038 5.053 3.904 4.223 3.863 4.211 3.205 5.480 4.638 Italy 0.768 0.797 0.917 0.672 0.865 0.801 0.918 0.666 1.060 0.745 Japan 107.454 109.100 165.984 85.476 107.457 116.322 125.188 79.655 132.992 99.387 Korea, Rep. 854.586 849.741 1,559.073 744.912 1,411.931 552.128 1,076.292 501.343 1,181.480 625.231 Latvia 0.347 0.354 0.504 0.411 0.614 0.303 0.479 0.183 0.623 0.408 Lithuania 1.567 1.572 2.214 1.726 2.876 1.203 2.289 0.875 3.048 1.437 Luxembourg 0.906 1.056 0.953 0.590 0.821 1.351 0.951 1.005 1.054 0.644 58 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 216.106 28.693 266.080 161.591 183.780 45.272 107.557 387.109 472.609 314.908 183.741 232.422 0.423 0.077 0.526 0.283 0.329 0.112 0.241 0.788 0.967 0.646 0.353 0.398 2,319.743 354.870 3,100.710 2,113.921 1,832.435 516.563 1,310.124 4,012.222 5,556.187 3,003.890 1,899.071 2,210.871 94.378 16.355 104.543 57.224 83.612 24.275 48.057 137.116 177.032 108.372 78.948 80.998 24.871 2.744 31.997 13.756 17.538 4.473 9.700 44.935 59.957 34.392 18.139 21.786 6.778 1.094 6.781 4.635 5.451 1.628 2.605 11.531 13.655 9.581 5.475 6.588 22.012 4.762 26.264 15.844 16.769 6.824 14.905 27.911 33.765 22.944 17.071 19.430 1.796 0.205 2.797 1.631 1.883 0.297 0.729 4.409 5.247 3.693 1.826 2.298 4.582 0.830 5.961 3.087 3.311 1.128 2.250 6.877 8.760 5.474 3.416 3.967 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 63.108 3.801 50.314 50.444 58.168 11.211 27.455 57.947 117.937 35.018 47.680 63.141 1.444 1.070 1.462 1.468 1.527 1.220 1.299 1.706 1.450 1.734 1.526 1.473 0.960 0.761 0.903 0.873 0.848 0.699 0.894 0.792 0.851 0.732 0.838 0.892 0.895 0.688 0.968 0.917 0.879 0.674 0.957 0.710 0.862 0.589 0.844 0.887 0.978 0.194 1.034 0.857 0.867 0.353 0.561 0.810 1.633 0.448 0.753 1.002 0.851 0.174 0.758 0.729 0.765 0.243 0.363 0.879 1.515 0.538 0.656 0.891 1.341 0.998 1.487 1.268 1.285 1.036 1.166 1.197 1.150 1.098 1.244 1.296 473.689 113.723 432.197 366.239 391.644 172.765 248.533 373.660 552.221 267.717 346.942 417.614 4.830 1.878 5.691 4.100 4.359 2.134 2.777 3.778 6.065 2.542 3.800 4.835 0.837 0.617 0.856 0.716 0.712 0.568 0.629 0.608 0.855 0.451 0.674 0.768 15.268 6.014 12.567 13.841 14.901 7.002 10.363 14.931 20.398 11.082 13.422 15.450 8.822 6.255 9.797 8.959 8.524 6.166 7.720 6.247 6.910 5.817 7.871 8.565 0.689 0.210 0.633 0.552 0.609 0.256 0.361 0.555 0.823 0.385 0.522 0.634 1.077 0.637 1.111 1.019 0.980 0.656 0.842 0.822 0.927 0.700 0.912 0.972 0.926 0.571 0.885 0.892 0.880 0.600 0.867 0.812 0.848 0.735 0.846 0.873 0.910 0.502 0.873 0.789 0.818 0.514 0.792 0.819 0.832 0.769 0.786 0.832 0.862 0.418 0.846 0.723 0.758 0.427 0.566 0.719 0.971 0.546 0.693 0.772 146.268 47.007 122.914 124.296 137.883 55.982 91.196 144.767 209.985 102.368 121.888 152.506 176.255 95.506 162.761 141.116 138.895 95.632 112.211 155.029 162.494 143.619 136.054 150.779 0.983 0.524 1.080 1.012 0.952 0.705 0.774 0.615 0.870 0.455 0.858 0.965 4.804 2.304 5.145 4.046 4.270 2.626 3.315 4.027 5.984 3.057 3.954 4.369 0.930 0.479 0.919 0.820 0.825 0.560 0.815 0.666 0.855 0.520 0.771 0.843 113.130 64.286 111.304 110.687 116.103 68.523 95.251 110.171 114.375 105.534 107.629 117.140 977.072 568.013 1,273.910 858.964 912.021 514.561 780.601 895.660 1,178.551 693.771 853.226 1,010.707 0.435 0.126 0.484 0.373 0.403 0.151 0.230 0.400 0.575 0.285 0.348 0.440 2.003 0.592 1.888 1.692 1.786 0.714 1.035 1.883 2.743 1.321 1.569 2.007 0.941 1.370 0.922 1.005 0.989 1.005 1.029 0.729 0.848 0.615 0.962 0.901 (continued) Presentation and Analysis of Results 59 Table 2.4 (Continued) PPPs Alcoholic Housing, Furnishings, (US$ = 1.00)a beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Macedonia, FYR 18.680 19.500 29.821 16.318 35.648 15.257 32.456 9.712 43.517 32.391 Malta 0.558 0.581 0.783 0.656 0.804 0.441 0.830 0.401 1.008 0.666 Mexico 7.673 7.692 9.640 7.834 8.380 10.247 9.821 6.304 11.754 10.184 Montenegro 0.369 0.389 0.614 0.341 0.796 0.288 0.595 0.238 0.772 0.527 Netherlands 0.832 0.862 0.798 0.699 0.885 0.943 0.880 0.766 1.212 0.874 New Zealand 1.486 1.477 1.804 1.972 1.399 1.726 1.609 1.069 1.840 1.728 Norway 8.973 9.894 11.661 13.756 9.758 8.612 8.905 9.188 13.170 5.389 Poland 1.823 1.738 2.095 2.060 3.329 1.395 2.323 0.995 3.206 2.027 Portugal 0.628 0.666 0.737 0.580 0.859 0.646 0.789 0.566 1.038 0.802 Romania 1.615 1.684 2.492 2.170 3.115 1.771 2.485 0.768 3.311 2.083 Russian Federatione 17.346 14.837 25.517 12.136 24.282 6.688 22.300 10.901 28.071 13.292 Serbia 37.288 39.247 62.369 33.470 85.242 30.511 67.090 23.635 81.372 40.554 Slovak Republic 0.508 0.502 0.704 0.543 0.770 0.427 0.715 0.263 0.845 0.885 Slovenia 0.625 0.651 0.786 0.535 0.807 0.588 0.801 0.480 0.944 0.636 Spain 0.705 0.749 0.770 0.580 0.731 0.811 0.850 0.634 1.050 1.070 Sweden 8.820 9.236 8.993 8.394 9.433 8.875 9.387 7.838 12.268 5.113 Switzerland 1.441 1.603 1.587 1.043 1.367 2.128 1.364 1.488 1.645 1.062 Turkey 0.987 1.007 1.592 1.444 1.239 0.772 1.363 0.684 1.964 1.364 United Kingdom 0.698 0.735 0.688 0.901 0.577 0.927 0.776 0.570 0.993 0.598 United States 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 Total (47) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. LATIN AMERICA Bolivia 2.946 2.801 4.404 3.461 4.226 1.284 4.254 2.785 3.654 4.967 Brazil 1.471 1.487 1.661 1.180 3.242 1.444 1.935 0.882 2.429 2.914 Colombia 1,161.910 1,146.218 1,615.194 1,193.256 1,778.228 643.113 1,986.418 863.861 1,841.147 1,921.748 Costa Rica 346.738 341.808 514.970 353.478 526.617 185.558 498.447 408.384 453.671 258.014 f Cuba 0.322 0.295 0.474 0.507 0.395 0.105 0.594 0.204 0.503 0.562 Dominican Republic 19.449 19.309 28.007 26.262 27.477 14.506 31.610 14.872 34.231 22.016 Ecuador 0.526 0.519 0.789 0.557 0.847 0.331 0.885 0.385 0.580 0.746 El Salvador 0.503 0.500 0.795 0.669 0.892 0.297 0.847 0.414 0.578 0.526 Guatemala 3.626 3.656 5.839 5.430 5.478 2.487 4.207 3.162 5.087 5.464 Haiti 19.108 19.976 31.450 16.429 44.005 11.714 23.191 15.105 24.596 25.732 Honduras 9.915 9.887 14.240 9.866 18.779 6.220 14.585 9.080 14.162 17.783 Nicaragua 8.919 8.581 14.935 10.936 12.256 3.927 11.988 7.119 14.294 16.145 Panama 0.547 0.523 0.808 0.582 0.889 0.334 0.795 0.458 0.701 0.419 Paraguay 2,227.340 2,180.826 3,315.801 2,114.347 4,855.416 1,164.644 3,160.069 1,868.982 3,453.794 2,077.333 Peru 1.521 1.461 2.121 1.591 2.434 1.035 2.539 1.023 2.058 2.137 Uruguay 15.282 15.517 22.144 18.197 28.689 11.479 24.106 12.366 21.420 14.176 Venezuela, RB 2.713 2.722 5.856 4.876 8.807 0.904 7.627 2.078 2.270 2.818 Total (17) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 60 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 25.840 4.257 21.757 20.816 22.936 6.633 11.650 24.827 48.894 14.528 19.497 25.546 0.683 0.320 0.666 0.574 0.629 0.335 0.402 0.573 0.893 0.387 0.557 0.692 9.837 1.347 8.934 8.024 8.940 2.757 4.878 9.264 14.729 6.448 7.688 8.670 0.570 0.079 0.548 0.394 0.449 0.147 0.233 0.496 0.812 0.328 0.383 0.494 0.895 0.581 0.904 0.901 0.869 0.640 0.829 0.802 0.920 0.690 0.847 0.871 1.638 0.746 1.486 1.511 1.589 0.879 1.308 1.687 1.825 1.662 1.494 1.577 10.921 7.436 12.558 11.174 9.797 7.792 9.484 8.602 8.710 8.155 9.529 10.270 2.112 0.795 2.690 1.887 1.936 0.864 1.418 2.416 3.285 1.804 1.821 2.152 0.836 0.335 0.676 0.678 0.704 0.427 0.538 0.551 0.906 0.366 0.629 0.738 1.901 0.379 1.824 1.698 2.001 0.593 0.927 1.811 3.491 1.073 1.625 2.055 22.012 4.762 26.264 15.844 16.769 6.824 14.905 27.911 33.765 22.944 17.071 19.430 52.662 9.736 49.547 38.602 45.370 15.892 22.028 45.487 84.416 26.168 38.394 49.595 0.633 0.198 0.609 0.538 0.567 0.230 0.342 0.633 0.901 0.450 0.508 0.629 0.806 0.450 0.753 0.666 0.681 0.439 0.495 0.615 0.793 0.482 0.626 0.719 0.858 0.462 0.809 0.728 0.777 0.519 0.622 0.623 0.845 0.472 0.707 0.783 9.973 8.352 11.374 9.742 9.105 7.273 7.921 8.946 8.415 9.255 9.008 9.386 1.543 1.475 1.658 1.556 1.613 1.432 1.526 1.282 1.332 1.304 1.513 1.503 1.329 0.182 1.414 1.140 1.164 0.379 0.733 1.116 1.858 0.689 0.999 1.300 0.770 0.554 0.785 0.699 0.756 0.521 0.615 0.628 0.668 0.546 0.701 0.717 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 4.471 1.402 3.660 2.777 2.906 2.700 3.100 3.624 7.274 2.203 2.978 3.300 2.083 0.647 1.866 1.502 1.659 0.683 1.650 1.306 2.823 0.722 1.469 1.761 1,318.597 537.119 1,585.522 1,090.827 1,196.955 896.440 907.599 1,395.264 2,528.150 883.720 1,169.408 1,351.984 430.513 187.950 423.759 283.873 343.786 349.561 289.663 395.883 798.305 233.246 346.902 385.230 0.286 0.176 0.343 0.354 0.292 0.218 0.263 0.543 1.110 0.315 0.319 0.321 25.063 5.659 19.915 17.560 20.741 9.795 13.201 25.431 51.125 14.840 19.791 22.491 0.711 0.244 0.724 0.542 0.547 0.365 0.482 0.611 1.458 0.309 0.532 0.591 0.626 0.167 0.916 0.501 0.531 0.331 0.425 0.635 1.258 0.381 0.515 0.595 4.656 1.341 4.116 3.095 3.873 2.450 2.995 4.302 8.768 2.494 3.714 4.324 23.340 8.546 32.674 17.038 20.706 15.782 24.118 21.163 49.656 11.493 20.133 23.762 11.649 4.409 11.451 8.463 10.080 9.996 10.177 11.288 22.845 6.678 10.117 11.309 13.808 2.499 11.844 8.026 9.160 5.288 6.764 14.345 28.246 8.511 9.305 10.928 0.666 0.205 0.758 0.546 0.553 0.359 0.428 0.732 1.376 0.459 0.553 0.607 3,473.908 862.251 2,924.159 1,937.258 2,309.430 1,473.418 2,173.686 2,663.075 6,091.921 1,425.662 2,251.650 2,624.223 1.824 0.624 2.084 1.262 1.569 0.800 1.261 1.956 3.978 1.135 1.535 1.733 20.879 7.504 18.290 14.448 16.424 10.667 12.534 15.732 27.773 10.074 15.299 17.925 5.402 0.843 4.471 3.588 2.915 1.571 1.915 2.846 7.388 1.351 2.712 3.303 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. (continued) Presentation and Analysis of Results 61 Table 2.4 (Continued) PPPs Alcoholic Housing, Furnishings, (US$ = 1.00)a beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) CARIBBEAN Anguilla 2.077 2.350 3.943 2.453 2.506 1.924 3.191 1.628 2.719 2.319 Antigua and Barbuda 1.731 1.931 3.377 2.046 2.291 1.435 3.018 1.039 3.600 2.383 Aruba 1.260 1.478 2.066 2.090 1.717 1.174 2.702 0.813 2.022 1.746 Bahamas, The 0.949 1.060 1.360 0.951 1.285 0.883 1.880 0.759 1.331 1.196 Barbados 2.017 2.238 2.685 2.551 1.885 1.942 2.722 1.366 2.452 2.363 Belize 1.150 1.105 1.934 2.456 1.519 0.556 1.762 0.846 2.224 1.241 Bermuda 1.564 1.771 1.836 1.118 1.484 2.600 2.111 1.236 1.491 1.120 Bonaireg … … 1.328 0.941 0.661 … 1.307 … 1.264 1.201 Cayman Islands 0.959 1.048 1.332 1.244 1.047 0.963 1.597 0.906 1.192 1.031 Curaçao 1.292 1.330 1.872 1.582 2.070 0.963 2.201 0.862 1.851 1.930 Dominica 1.861 1.924 3.231 2.321 1.534 1.393 3.662 1.252 2.843 1.914 Grenada 1.783 1.905 3.333 2.413 2.763 1.286 3.441 1.220 3.039 2.070 Jamaica 54.122 57.926 102.779 83.799 60.249 39.431 85.601 39.970 91.181 46.085 Montserrat 1.943 2.144 3.960 2.767 2.462 1.289 4.318 1.535 3.603 1.789 St. Kitts and Nevis 1.803 1.923 3.772 2.379 2.102 1.264 4.773 0.952 3.514 2.903 St. Lucia 1.844 1.952 3.041 2.566 2.295 1.204 4.828 1.289 2.838 2.420 St. Vincent and the Grenadines 1.691 1.852 3.141 2.167 2.067 1.344 3.393 1.039 2.562 2.516 Sint Maarten 1.379 1.514 2.107 1.013 1.399 1.326 2.295 0.809 1.856 2.243 Suriname 1.826 1.712 3.317 2.372 1.858 0.873 3.314 0.955 3.429 2.149 Trinidad and Tobago 3.938 4.193 6.703 6.444 5.260 3.131 7.911 2.770 5.920 4.094 Turks and Caicos Islands 1.100 1.193 1.417 1.275 0.880 1.350 1.459 0.795 1.523 0.748 Virgin Islands, British 1.076 1.164 1.543 0.644 1.078 1.223 1.731 0.777 1.171 0.950 Total (22) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. WESTERN ASIA Bahrain 0.211 0.214 0.301 0.228 0.267 0.187 0.311 0.216 0.172 0.182 b Egypt, Arab Rep. 1.625 1.606 3.436 2.808 2.059 0.711 3.145 0.830 2.298 1.909 Iraq 516.521 502.565 938.605 803.639 820.477 319.578 838.134 306.231 667.454 467.485 Jordan 0.293 0.295 0.566 0.367 0.302 0.170 0.435 0.171 0.439 0.345 Kuwait 0.172 0.183 0.234 0.192 0.235 0.119 0.273 0.196 0.142 0.240 Oman 0.192 0.194 0.307 0.210 0.221 0.164 0.253 0.141 0.186 0.231 Qatar 2.419 2.854 3.231 2.266 2.974 2.730 3.551 2.749 2.013 2.664 Saudi Arabia 1.837 1.826 2.984 2.065 2.089 1.081 2.532 1.575 1.753 2.240 c Sudan 1.224 1.342 2.405 2.278 0.899 1.125 1.783 0.537 2.283 1.594 United Arab Emirates 2.544 2.776 3.504 2.689 2.804 2.646 2.672 2.857 2.592 2.254 West Bank and Gaza 2.189 2.230 3.382 5.117 2.119 2.207 2.778 1.111 3.840 2.366 Yemen, Rep. 75.818 74.499 166.661 71.501 70.023 38.681 128.799 39.244 98.140 96.748 Total (12) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 62 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 3.640 0.756 3.231 2.774 2.591 1.142 1.392 1.574 3.113 0.996 2.081 2.729 2.932 0.551 2.180 2.052 2.200 0.724 1.002 1.581 3.457 0.969 1.745 2.572 2.059 0.650 2.568 1.504 1.653 0.693 0.780 0.959 1.656 0.664 1.272 1.878 1.136 0.553 1.148 1.121 1.151 0.601 0.499 0.798 1.330 0.570 0.930 1.234 2.386 1.013 3.084 2.152 2.413 1.361 1.086 1.512 2.578 1.039 1.952 2.412 1.820 0.456 1.725 1.349 1.183 0.796 0.814 1.844 2.695 1.456 1.167 1.572 1.794 0.718 2.082 1.664 1.900 1.078 1.145 0.966 1.141 1.025 1.490 1.636 … … 0.986 … 0.919 … … … … … … 1.027 1.238 0.418 1.112 1.106 1.136 0.615 0.716 0.795 1.237 0.596 0.955 1.150 1.846 0.620 2.031 1.378 1.429 0.830 0.802 1.469 2.290 1.112 1.307 1.705 2.656 0.726 2.374 2.201 2.069 1.230 1.416 2.034 3.500 1.391 1.885 2.375 2.933 0.494 2.562 1.907 2.092 0.969 1.089 2.006 3.444 1.368 1.828 2.476 81.680 20.280 81.394 63.874 63.354 30.555 37.720 58.977 113.403 36.789 55.667 74.167 2.799 0.686 2.481 2.325 2.336 1.152 1.328 1.739 3.544 1.080 1.978 2.821 2.924 0.354 2.299 2.068 2.221 0.610 0.795 2.196 3.650 1.518 1.835 2.687 2.785 0.635 3.882 2.230 2.139 1.019 1.188 1.984 3.640 1.331 1.875 2.535 2.623 0.589 3.481 2.058 2.039 0.916 1.097 1.768 3.704 1.077 1.749 2.345 1.661 0.568 2.140 1.745 1.678 0.686 0.848 1.210 1.764 1.003 1.374 1.813 2.235 0.857 2.159 1.794 1.885 0.872 1.197 2.178 4.093 1.224 1.842 2.072 4.943 1.353 6.277 3.922 4.619 2.054 2.073 3.610 6.488 2.390 3.832 4.703 1.301 0.621 1.499 1.199 1.282 0.775 0.692 1.177 1.310 1.113 1.140 1.270 1.347 0.647 1.545 1.219 1.250 0.775 0.702 1.151 1.345 1.109 1.123 1.206 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. 0.220 0.130 0.231 0.208 0.215 0.199 0.223 0.188 0.400 0.112 0.211 0.195 1.981 0.507 2.410 1.585 1.803 0.566 0.822 2.689 6.656 1.391 1.646 2.096 706.104 167.996 752.625 783.801 573.418 226.398 317.367 695.065 1134.199 492.284 502.704 655.873 0.371 0.124 0.463 0.330 0.319 0.159 0.196 0.373 0.710 0.238 0.294 0.371 0.229 0.135 0.296 0.259 0.180 0.185 0.217 0.153 0.290 0.102 0.181 0.174 0.236 0.107 0.266 0.194 0.200 0.147 0.179 0.172 0.385 0.093 0.187 0.194 3.190 2.303 3.709 2.979 2.640 3.218 3.547 1.737 3.527 0.922 2.546 2.373 2.274 1.212 2.327 1.936 1.785 1.674 1.914 1.538 3.279 0.876 1.781 1.855 1.659 0.436 1.306 1.348 1.486 0.424 0.600 1.258 3.317 0.597 1.223 1.584 3.306 1.908 3.694 2.939 2.718 3.257 3.627 1.811 3.276 1.187 2.622 2.580 2.528 0.793 3.527 2.530 2.523 1.011 1.421 2.458 4.098 1.665 2.122 2.720 89.965 27.016 70.912 83.048 82.094 33.258 42.454 103.215 198.265 72.003 74.395 92.814 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. (continued) Presentation and Analysis of Results 63 Table 2.4 (Continued) PPPs Alcoholic Housing, Furnishings, (US$ = 1.00)a beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) SINGLETONS Georgia 0.859 0.705 1.392 0.734 1.430 0.237 1.252 0.402 1.351 0.637 Iran, Islamic Rep. 4,657.463 4,216.441 7,960.468 3,154.675 8,110.943 3,527.879 7,674.926 1,943.926 6,321.803 2,749.561 Total (2) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. WORLDh (179) n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; PPP = purchasing power parity; ... = data suppressed because of incompleteness. a. PPPs are rounded to three decimal places. More precision can be found in the Excel version of the table, which can be downloaded from the ICP website. b. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. c. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. d. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. e. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. f. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. g. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. h. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 64 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.927 0.157 1.214 0.671 0.842 0.243 0.539 1.651 1.789 1.365 0.841 1.047 5,177.313 474.430 7,247.766 5,662.554 5,001.363 1,161.991 2,461.785 7,137.243 14,891.530 3,470.697 4,677.234 5,062.124 n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a. Presentation and Analysis of Results 65 Table 2.5 Real Expenditures in U.S. Dollars, ICP 2011 REAL EXPENDITURES Alcoholic Housing, Furnishings, (US$, billions) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) AFRICA Algeria 474.8 225.6 38.5 2.5 4.5 13.2 4.0 35.4 23.7 10.3 Angola 143.0 84.7 20.6 5.6 3.6 11.4 3.1 6.4 3.7 0.7 Benin 16.1 13.4 3.6 0.4 0.6 1.5 0.2 0.8 0.8 0.3 Botswana 27.2 13.8 1.5 0.8 1.0 1.4 0.5 1.3 1.8 0.4 Burkina Faso 22.8 16.2 4.4 1.0 0.4 2.4 0.5 1.0 0.7 0.4 Burundi 6.1 5.6 1.3 0.5 0.1 1.5 0.0 0.4 0.2 0.0 Cameroon 55.2 46.0 12.8 1.1 3.0 5.9 2.4 1.0 2.4 0.4 Cape Verde 3.1 2.4 0.5 0.1 0.1 0.5 0.1 0.2 0.1 0.1 Central African Republic 4.0 3.9 1.1 0.3 0.3 0.4 0.1 0.1 0.1 0.0 Chad 22.9 17.0 4.7 0.7 0.4 1.8 0.7 2.3 1.1 0.4 Comoros 0.5 0.5 0.1 0.0 0.0 0.2 0.0 0.0 0.0 0.0 Congo, Rep. 24.1 6.3 1.2 0.3 0.2 1.4 0.2 0.9 0.3 0.2 Congo, Dem. Rep. 44.4 30.3 8.2 0.7 1.4 6.4 0.8 2.8 0.5 0.3 Côte d’Ivoire 53.8 39.9 9.7 1.2 1.1 5.5 2.4 3.4 2.8 0.7 Djibouti 2.2 1.6 0.3 0.1 0.0 0.6 0.1 0.1 0.1 0.0 Egypt, Arab Rep.a 843.8 679.1 133.0 12.6 32.0 200.1 16.8 119.8 28.0 14.6 Equatorial Guinea 28.4 3.5 0.7 0.1 0.1 0.7 0.1 0.6 0.2 0.1 Ethiopia 102.9 82.9 17.1 1.6 3.6 14.6 5.0 14.0 0.8 0.3 Gabon 25.3 9.2 1.4 0.8 0.4 1.6 0.3 1.1 0.7 0.3 Gambia, The 2.7 2.2 0.5 0.1 0.2 0.2 0.0 0.7 0.0 0.1 Ghana 85.5 56.0 9.5 0.7 8.3 8.7 2.8 4.8 3.4 0.8 Guinea 13.2 8.1 2.0 0.1 0.6 1.9 0.2 1.2 0.3 0.0 Guinea-Bissau 2.1 1.4 0.4 0.0 0.1 0.2 0.1 0.1 0.1 0.0 Kenya 88.9 80.6 16.0 2.9 2.2 9.5 2.6 11.3 4.2 3.1 Lesotho 4.7 5.5 0.9 0.1 0.7 0.8 0.3 0.4 0.1 0.1 Liberia 2.2 2.5 0.4 0.1 0.4 0.5 0.1 0.1 0.0 0.1 Madagascar 30.1 28.4 6.9 0.7 2.3 1.9 2.8 1.1 1.9 0.1 Malawi 15.0 15.5 3.9 0.7 0.5 3.8 1.0 1.5 0.5 0.2 Mali 23.9 16.6 4.6 0.2 0.9 1.8 0.6 1.4 1.2 0.3 Mauritania 11.3 7.4 2.5 0.1 0.3 0.9 0.1 0.5 0.2 0.2 Mauritius 20.3 15.4 2.8 0.8 1.0 3.4 0.8 1.5 1.1 0.5 Morocco 218.3 139.1 27.1 2.2 5.1 36.1 4.5 11.2 8.5 6.2 Mozambique 22.8 21.3 6.2 0.9 1.1 2.5 0.4 0.9 1.2 0.2 Namibia 19.4 13.5 1.6 0.5 0.8 2.4 0.9 2.3 0.4 0.1 Niger 13.7 11.6 2.5 0.2 1.2 1.4 0.5 0.8 0.6 0.2 Nigeria 511.1 337.1 62.9 5.0 56.0 42.8 22.6 24.5 17.5 4.3 Rwanda 14.6 14.2 4.0 0.3 0.4 3.5 0.4 0.7 0.4 0.1 São Tomé and Príncipe 0.5 0.6 0.2 0.0 0.0 0.1 0.0 0.1 0.0 0.0 66 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 5.5 85.8 4.3 38.8 143.3 155.1 79.2 109.9 21.0 105.1 427.8 136.2 1.2 10.7 1.4 10.0 67.1 22.0 45.5 29.3 4.1 35.3 152.2 59.6 0.1 1.8 0.9 0.6 11.7 1.3 1.7 2.4 0.4 2.6 17.5 10.0 0.3 5.0 0.3 1.2 11.0 3.7 3.8 10.3 1.7 12.3 29.1 9.7 0.2 1.7 0.5 0.5 14.3 1.2 4.1 2.8 0.5 2.7 24.2 12.1 0.0 1.4 0.2 0.1 4.6 1.1 1.2 0.7 0.1 0.7 7.2 3.4 0.5 2.7 2.1 1.2 41.3 2.1 6.0 8.2 2.1 6.4 59.4 35.3 0.0 0.5 0.3 0.2 2.0 0.5 0.4 1.2 0.2 1.1 4.1 1.6 0.0 0.5 0.1 0.2 3.5 0.2 0.2 0.5 0.1 0.4 4.5 3.0 0.3 1.0 0.1 0.5 15.2 0.9 1.3 4.6 1.0 3.4 23.5 12.9 0.0 0.0 0.0 0.0 0.4 0.0 0.1 0.1 0.0 0.0 0.7 0.3 0.1 1.3 0.4 0.3 5.2 1.1 1.3 6.2 0.6 8.4 14.7 4.4 0.3 5.3 1.1 0.7 26.7 2.1 6.2 8.1 1.6 7.9 44.3 21.5 0.9 3.8 0.5 2.1 35.2 3.3 4.8 4.9 0.8 5.6 45.3 29.9 0.0 0.3 0.0 0.0 1.3 0.2 0.5 0.6 0.1 0.7 2.7 1.0 16.3 142.5 14.2 48.7 574.7 96.0 124.8 85.2 16.0 83.7 867.2 448.5 0.0 0.6 0.1 0.2 3.1 0.3 0.4 10.0 2.2 6.5 13.5 2.7 0.3 13.5 3.9 11.0 73.1 5.5 9.0 18.0 2.2 21.2 111.9 64.0 0.2 1.1 0.3 0.3 7.8 1.3 2.8 4.5 0.7 1.9 16.3 6.6 0.1 0.6 0.0 0.1 1.9 0.2 0.3 0.5 0.1 0.3 2.9 1.7 0.5 25.4 0.0 2.6 46.6 9.9 11.8 21.0 4.0 20.9 89.9 41.6 0.1 1.2 0.1 0.2 7.2 0.3 1.0 2.0 0.6 1.2 11.4 5.7 0.0 0.2 0.0 0.0 1.3 0.1 0.6 0.2 0.0 0.2 2.1 1.1 2.1 23.6 3.8 6.8 65.1 18.2 7.4 13.5 3.1 12.0 100.6 54.1 0.2 1.0 0.0 0.4 4.6 1.0 1.0 1.1 0.1 1.4 7.6 3.8 0.0 1.2 0.0 0.2 2.3 0.0 0.3 0.3 0.1 0.1 3.2 1.9 1.1 3.5 1.1 0.5 25.3 1.6 2.3 3.3 0.6 3.5 33.2 23.1 0.2 1.8 0.2 0.4 13.6 1.4 0.9 2.0 0.7 0.8 17.7 10.9 0.5 2.2 0.2 0.5 14.3 1.8 3.8 4.0 0.8 3.8 24.2 12.4 0.1 1.5 0.0 0.1 6.0 1.7 2.3 4.4 0.9 3.5 11.9 5.1 0.9 3.2 0.3 1.0 13.0 2.6 2.5 4.8 0.7 5.6 23.1 11.2 5.0 37.3 5.6 9.2 112.8 31.2 25.5 69.7 11.0 80.5 244.6 87.3 0.5 2.5 0.2 1.4 18.7 2.0 1.3 3.3 0.6 3.6 25.9 15.9 0.5 5.9 0.5 1.6 10.9 3.2 3.5 4.7 0.7 5.5 21.2 9.2 0.5 1.7 0.4 0.8 10.2 0.8 1.5 3.9 0.9 3.3 17.2 8.9 3.1 108.8 0.1 17.6 287.2 45.7 59.2 42.5 10.5 30.0 428.0 263.2 0.2 1.4 0.3 0.5 12.9 0.7 1.0 2.2 0.2 2.9 16.8 10.1 0.0 0.1 0.0 0.0 0.5 0.1 0.1 0.1 0.0 0.0 0.7 0.4 (continued) Presentation and Analysis of Results 67 Table 2.5 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, (US$, billions) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Senegal 28.6 24.6 6.8 0.3 0.9 6.0 1.1 1.3 0.7 0.9 Seychelles 2.0 1.1 0.3 0.0 0.0 0.3 0.0 0.2 0.0 0.0 Sierra Leone 8.2 7.2 1.4 0.2 0.8 0.9 0.2 2.6 0.1 0.1 South Africa 611.1 417.8 53.2 17.5 16.0 65.3 15.8 62.3 36.8 12.3 Sudanb 152.4 97.5 28.1 0.4 6.5 17.0 4.8 3.1 4.7 1.3 Swaziland 7.6 7.0 2.0 0.0 0.4 1.1 0.5 0.9 0.4 0.1 Tanzania 71.8 47.6 17.8 0.2 3.5 3.5 1.5 4.4 1.2 0.0 Togo 8.1 7.3 1.7 0.2 0.4 0.8 0.2 0.9 0.2 0.1 Tunisia 109.3 77.2 9.9 1.6 3.2 14.8 3.2 8.9 7.9 3.8 Uganda 55.1 48.0 9.8 2.1 1.3 9.4 1.8 2.5 1.5 0.8 Zambia 42.5 24.0 8.3 0.1 1.5 3.9 0.2 2.6 0.2 0.3 Zimbabwe 17.6 17.2 5.7 0.6 0.8 1.4 0.3 0.9 0.7 0.0 Total (50) 4,115.1 2,834.9 560.6 69.1 170.3 517.9 107.6 347.3 164.2 66.1 ASIA AND THE PACIFIC Bangladesh 419.2 320.1 94.8 7.9 16.9 77.6 7.5 25.1 6.3 4.7 Bhutan 5.1 2.8 0.5 0.0 0.2 0.6 0.0 0.6 0.2 0.1 Brunei Darussalam 29.3 6.2 0.8 0.0 0.2 0.9 0.1 0.5 0.9 0.2 Cambodia 38.7 32.4 8.6 1.2 0.7 4.6 0.4 6.0 1.3 0.1 Chinac 13,495.9 5,811.5 740.1 78.6 322.5 1,061.3 170.0 1,503.0 256.8 288.1 Fiji 6.5 4.6 1.0 0.1 0.1 0.9 0.3 0.4 0.2 0.0 Hong Kong SAR, China 354.5 231.2 18.7 1.9 13.3 40.7 9.9 21.2 11.1 10.3 India 5,757.5 3,675.4 694.0 69.4 297.9 651.5 78.5 458.3 269.2 49.2 Indonesia 2,058.1 1,158.3 265.5 11.2 32.9 289.2 23.7 58.3 52.1 21.5 Lao PDR 26.2 14.9 3.7 0.6 0.3 3.6 0.2 0.8 0.7 0.3 Macao SAR, China 64.3 13.2 0.9 0.1 0.8 2.1 0.2 1.2 0.8 0.6 Malaysia 606.1 321.0 35.5 2.6 4.8 69.2 8.3 30.2 27.2 15.8 Maldives 3.7 1.3 0.2 0.1 0.0 0.3 0.0 0.2 0.0 0.0 Mongolia 23.4 14.7 2.4 1.0 0.5 2.2 0.1 2.1 1.6 0.3 Myanmar 192.1 137.2 35.7 1.6 4.1 23.4 1.1 24.3 1.8 1.7 Nepal 58.9 48.9 17.0 1.1 1.4 7.9 0.6 5.5 0.5 0.7 Pakistan 788.1 695.3 172.3 5.6 28.2 215.1 12.5 117.4 22.5 13.3 Philippines 543.7 422.9 110.7 5.4 4.4 61.8 12.5 18.9 28.7 8.0 Singapore 374.8 128.2 6.5 1.0 4.2 19.4 5.0 14.8 10.8 3.0 Sri Lanka 169.3 133.4 31.1 8.6 4.2 26.0 1.8 16.6 5.3 3.2 Taiwan, China 907.1 583.6 43.1 8.9 28.1 97.6 15.6 110.7 41.8 36.5 Thailand 899.0 573.0 88.4 12.2 20.5 84.6 13.4 73.2 46.7 13.2 Vietnam 414.3 262.7 38.5 7.8 11.8 57.4 10.3 58.5 10.6 1.7 Total (23) 27,235.6 14,593.0 2,410.0 227.2 798.1 2,797.9 372.3 2,547.9 797.2 472.5 68 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.3 3.4 0.1 1.1 21.6 2.1 3.5 5.5 1.0 6.0 33.7 17.4 0.0 0.4 0.0 0.0 0.9 0.4 0.8 0.5 0.1 0.4 2.4 0.7 0.2 1.5 0.1 0.4 6.3 0.4 0.9 2.5 0.7 1.6 10.8 5.4 14.1 88.4 6.0 48.3 341.7 85.1 83.2 120.4 28.8 95.3 620.6 278.6 1.8 9.8 2.2 2.5 87.4 2.4 19.5 33.1 6.6 33.3 154.6 74.0 0.2 1.0 0.0 0.1 6.2 0.6 0.7 0.8 0.1 0.8 8.3 5.1 0.4 5.7 0.0 1.1 42.4 2.9 10.0 23.0 3.0 33.2 81.7 39.3 0.1 2.1 0.4 1.0 6.3 0.8 0.9 1.1 0.1 1.3 9.3 5.5 1.8 21.3 5.3 5.1 61.0 22.0 15.4 22.9 2.4 35.2 116.2 48.7 2.2 16.6 1.1 2.4 39.9 8.8 1.0 11.4 1.0 19.8 61.8 33.8 0.1 2.8 0.1 1.6 20.9 2.3 7.0 8.8 1.1 11.6 40.0 17.8 0.3 3.4 0.1 1.1 14.5 2.7 2.0 1.5 0.2 1.7 21.0 12.8 63.4 658.7 58.9 225.2 2,344.9 550.8 564.5 722.3 136.1 725.3 4,108.5 1,969.1 1.6 54.3 6.5 8.7 287.9 12.7 18.8 100.6 8.7 150.2 446.9 238.7 0.1 0.7 0.0 0.1 2.2 0.8 0.9 2.6 0.4 3.1 6.5 1.8 0.4 2.1 0.2 0.3 4.8 1.8 4.9 3.3 0.6 3.2 13.0 4.0 0.7 10.1 1.5 0.7 27.1 5.4 2.1 3.9 0.7 4.1 38.7 22.5 347.1 1,159.9 299.3 393.6 4,397.8 1,913.6 868.3 5,723.1 795.9 6,230.3 13,029.2 3,641.6 0.2 0.8 0.1 0.2 3.9 0.6 0.5 1.4 0.3 0.9 6.8 3.2 32.8 12.6 22.9 38.8 212.9 13.5 15.7 81.5 21.9 53.3 332.9 175.5 40.4 423.8 61.8 408.4 3,248.6 320.8 493.6 1,424.7 213.5 1,627.2 6,031.6 2,692.7 21.1 282.3 76.0 54.6 990.6 153.6 135.9 651.0 43.0 1,001.7 2,022.0 819.4 0.3 4.9 0.3 0.3 12.6 2.0 4.0 8.0 0.8 8.3 26.9 10.5 1.4 2.3 2.3 1.3 11.1 2.4 2.2 7.4 1.1 8.7 23.7 9.2 11.4 78.8 28.4 32.7 263.7 65.2 47.6 124.1 21.6 105.9 500.4 218.4 0.0 0.5 0.0 0.0 1.0 0.4 1.1 1.8 0.4 1.8 3.9 0.8 0.3 6.4 0.2 0.5 11.7 4.2 2.8 8.8 2.3 5.8 29.3 9.6 1.2 84.8 5.8 2.5 104.3 47.3 16.1 38.9 6.5 38.0 193.6 86.6 1.0 9.8 0.9 1.6 43.3 3.8 3.9 9.4 0.9 9.9 70.9 35.9 6.1 97.6 5.0 30.5 618.2 45.6 71.6 73.7 8.5 73.5 829.7 513.3 6.1 89.7 14.3 40.6 377.9 29.1 31.9 94.6 14.8 90.8 560.6 313.4 18.5 20.7 16.1 15.7 111.2 15.9 25.8 98.2 21.4 86.5 244.1 91.7 1.6 27.7 3.2 5.5 108.2 32.0 20.4 34.5 4.1 42.4 190.9 89.7 52.5 98.0 34.1 73.0 514.9 57.6 76.9 175.7 43.7 122.9 840.2 425.4 22.1 125.4 50.0 40.9 473.1 112.0 81.1 220.2 60.2 137.6 878.6 392.1 9.3 110.0 10.7 7.7 214.9 58.0 46.8 100.2 10.2 132.5 430.9 177.6 576.2 2,703.1 639.5 1,158.2 12,041.7 2,898.2 1,973.0 8,987.4 1,281.6 9,938.7 26,751.5 9,973.3 (continued) Presentation and Analysis of Results 69 Table 2.5 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, (US$, billions) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) COMMONWEALTH OF INDEPENDENT STATES Armenia 20.2 22.0 6.0 1.1 0.4 5.9 0.2 2.6 0.6 0.8 Azerbaijan 144.5 75.7 15.9 2.0 3.5 19.6 2.1 5.4 3.9 3.0 Belarus 157.3 109.7 19.1 7.5 3.1 30.0 2.3 17.8 4.0 5.4 Kazakhstan 343.9 188.9 25.8 6.0 7.1 51.3 4.9 28.4 12.3 7.2 Kyrgyz Republic 16.1 18.4 3.3 1.0 0.6 5.8 0.3 1.8 0.9 1.2 Moldova 14.9 20.1 3.3 1.6 0.6 4.9 0.8 1.3 0.9 0.7 Russian Federationd 3,216.9 2,169.4 319.6 182.2 100.4 468.8 59.3 234.2 118.4 93.2 Tajikistan 17.3 23.3 4.9 0.1 0.8 6.1 0.3 2.6 0.7 1.9 Ukraine 379.1 361.4 67.4 24.1 9.0 112.8 8.1 56.5 18.3 6.9 Total (9) 4,310.3 2,989.1 465.3 225.7 125.4 705.3 78.1 350.6 160.0 120.1 EUROSTAT-OECD Albania 28.2 23.0 5.3 0.7 0.5 3.3 0.8 2.5 0.5 0.2 Australia 956.0 616.6 49.3 16.0 17.6 100.1 25.3 75.9 53.2 17.9 Austria 360.5 232.2 16.9 9.1 12.2 46.2 11.4 27.8 18.7 4.8 Belgium 440.1 288.2 28.0 10.0 10.3 48.7 11.7 50.0 20.3 4.6 Bosnia and Herzegovina 37.0 32.5 5.9 2.5 0.6 7.2 1.2 3.6 1.3 0.6 Bulgaria 114.1 80.6 9.1 4.2 1.1 19.1 3.4 15.6 5.7 2.7 Canada 1,416.2 946.0 57.7 22.2 32.7 189.4 37.2 128.3 97.9 19.3 Chile 349.1 236.6 23.5 6.3 8.7 37.1 10.8 28.7 19.5 6.8 Croatia 86.8 58.8 7.8 3.7 1.6 14.1 2.3 10.6 3.3 1.8 Cyprus 26.6 19.5 1.8 0.9 1.0 4.3 0.8 2.1 1.5 1.0 Czech Republic 283.9 174.6 17.7 13.2 3.0 37.6 5.9 32.8 8.6 3.0 Denmark 233.0 146.4 11.3 4.9 5.1 26.8 5.5 23.2 9.2 2.8 Estonia 30.9 18.5 2.3 1.4 0.6 3.3 0.4 2.9 1.2 0.6 Finland 208.0 143.2 13.1 5.5 5.0 25.6 5.5 22.6 8.8 3.7 France 2,369.6 1,724.6 168.9 49.9 56.7 312.1 68.3 273.4 138.4 36.8 Germany 3,352.1 2,328.9 188.3 73.0 83.3 395.5 105.3 407.6 168.9 63.9 Greece 300.8 240.2 30.1 10.7 7.8 56.4 7.5 36.1 17.9 5.1 Hungary 223.5 146.2 13.8 9.9 2.3 31.8 3.9 30.6 7.5 2.6 Iceland 12.2 8.2 0.8 0.2 0.2 1.8 0.3 1.3 0.6 0.2 Ireland 196.6 105.5 7.6 3.4 3.7 19.7 3.6 15.7 8.3 2.6 Israel 234.2 159.0 16.7 3.4 3.7 33.2 7.6 17.2 15.1 4.4 Italy 2,056.7 1,449.8 152.1 39.4 84.6 269.8 75.7 207.8 116.0 31.3 Japan 4,379.8 3,125.1 231.6 89.0 82.4 609.8 112.3 453.3 226.8 96.8 Korea, Rep. 1,445.3 870.2 52.7 19.2 22.8 187.5 19.6 162.5 63.3 43.6 Latvia 41.1 28.3 3.4 1.6 0.7 6.8 0.7 3.9 2.0 0.7 Lithuania 68.2 50.1 7.4 3.0 1.4 9.2 1.8 8.9 3.3 1.1 70 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.4 5.2 0.1 0.7 17.2 4.3 2.7 2.5 0.3 2.5 25.4 13.1 1.7 20.5 1.3 3.1 58.9 17.5 13.7 13.3 5.6 7.1 99.8 47.3 3.9 40.4 1.6 3.3 77.3 52.1 11.1 28.0 8.8 20.8 158.2 61.9 6.9 68.4 4.4 15.5 141.0 63.4 29.2 42.1 9.4 34.7 274.6 120.7 0.5 7.9 0.3 0.8 13.6 6.5 2.4 1.5 0.5 1.0 20.0 10.7 0.4 7.0 0.2 1.7 14.6 8.0 1.4 1.7 0.4 1.2 21.2 11.4 79.8 375.9 34.2 173.4 1,633.9 701.7 352.4 415.4 123.3 282.8 2,988.9 1,339.3 0.4 7.0 0.1 1.1 17.1 8.3 2.2 2.2 0.8 1.2 25.7 13.8 9.2 110.3 3.8 18.1 264.4 137.5 36.6 35.2 10.6 26.2 404.9 207.1 103.3 642.7 46.1 217.7 2,238.0 999.2 451.6 541.9 159.8 377.6 4,018.8 1,825.4 0.4 9.5 0.5 1.2 17.7 5.8 2.6 7.3 0.8 9.3 33.1 15.0 64.4 71.5 37.1 92.8 507.3 125.8 78.1 228.2 65.0 129.0 934.2 429.8 19.9 20.7 21.9 28.2 193.3 47.9 26.1 80.1 28.5 45.0 346.5 158.9 20.9 33.8 11.9 38.9 221.5 85.6 34.0 107.7 33.2 69.6 433.7 185.6 1.2 7.3 1.5 2.6 25.6 8.0 5.6 5.9 1.2 5.8 43.8 20.7 5.1 15.3 4.3 4.5 61.4 24.5 16.2 18.5 4.6 16.0 114.9 47.1 71.7 94.5 43.4 130.8 763.0 214.9 136.4 344.3 71.3 249.4 1,432.3 609.7 12.1 62.1 8.1 30.6 190.0 53.2 21.7 72.9 19.4 54.1 338.7 161.2 4.9 9.9 6.2 4.9 45.4 16.6 10.7 16.8 3.4 14.9 86.9 36.2 1.3 2.2 2.3 1.6 17.0 2.8 3.2 4.9 1.0 4.4 27.7 13.7 14.1 27.2 12.3 14.5 129.9 58.9 36.7 61.8 20.1 41.7 273.0 104.5 12.2 18.2 4.6 25.5 102.4 59.1 18.7 49.8 15.8 27.0 215.7 81.8 1.1 3.7 1.0 1.7 13.5 6.8 3.8 6.9 2.1 5.0 29.9 11.0 12.1 17.4 5.8 20.9 107.3 47.3 18.0 44.6 9.5 35.2 208.5 89.0 127.3 188.7 89.3 231.5 1,313.2 534.1 195.5 492.4 127.6 338.4 2,437.1 1,089.5 156.4 212.3 94.6 348.9 1,831.7 621.9 227.2 577.8 217.9 342.6 3,147.4 1,517.6 10.7 27.0 22.2 21.2 205.2 34.5 38.1 44.0 13.1 30.5 325.2 168.4 9.3 25.9 8.1 18.3 106.8 53.4 31.0 34.2 9.9 25.2 212.1 84.5 0.6 1.2 0.4 0.8 6.1 2.8 1.3 1.5 0.5 0.9 11.0 4.6 6.0 14.8 8.8 11.1 82.2 29.8 11.5 28.1 7.5 20.4 148.5 67.2 8.5 28.8 6.9 18.6 123.9 43.0 30.1 46.9 10.1 29.9 234.8 98.1 84.1 143.4 106.3 142.0 1,172.7 336.0 164.1 452.4 141.1 276.4 2,078.7 970.7 226.2 267.9 163.8 556.4 2,452.9 819.7 420.3 879.3 330.6 432.5 4,412.4 1,929.1 52.9 143.3 40.5 125.7 718.6 163.4 135.1 379.7 102.0 277.8 1,418.4 577.2 1.8 5.4 0.9 1.8 22.0 7.5 6.1 7.6 2.2 5.9 42.9 17.5 2.5 8.8 1.0 4.1 37.6 16.2 8.1 10.2 2.3 8.6 70.0 31.3 (continued) Presentation and Analysis of Results 71 Table 2.5 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, (US$, billions) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Luxembourg 46.1 16.6 1.4 2.3 0.9 2.9 1.1 1.9 2.9 0.4 Macedonia, FYR 24.6 19.5 3.9 0.7 0.5 4.4 0.4 2.5 0.8 0.6 Malta 11.9 8.2 0.9 0.2 0.2 1.3 0.4 1.4 0.6 0.3 Mexico 1,894.6 1,370.1 233.0 32.3 34.4 193.8 55.7 105.0 153.3 35.2 Montenegro 8.8 7.6 1.6 0.4 0.1 1.4 0.5 0.8 0.5 0.3 Netherlands 720.3 433.7 39.4 11.8 16.2 70.2 18.0 61.1 28.2 12.7 New Zealand 137.6 99.3 9.7 3.2 3.9 16.5 3.7 16.8 7.9 2.2 Norway 306.5 153.6 11.8 3.2 5.7 26.1 6.6 22.1 11.8 5.0 Poland 838.0 628.3 83.2 28.9 12.2 162.1 17.9 105.6 29.0 13.4 Portugal 272.7 197.4 26.3 6.7 7.5 28.9 8.1 28.4 14.7 4.2 Romania 344.8 238.8 38.0 8.0 4.2 43.2 6.8 58.1 11.5 8.2 Russian Federationd 3,216.9 2,169.4 319.6 182.2 100.4 464.1 59.3 232.9 118.4 93.2 Serbia 86.1 73.4 10.9 4.1 1.1 18.6 1.4 12.7 4.1 2.8 Slovak Republic 135.7 91.1 10.0 3.4 2.1 23.9 3.3 16.3 3.7 1.6 Slovenia 57.8 38.8 4.2 2.2 1.5 7.3 1.7 6.1 3.5 1.1 Spain 1,483.2 991.0 115.2 32.1 46.0 163.4 35.6 135.3 69.4 16.4 Sweden 394.6 253.1 22.1 7.0 8.4 49.8 8.8 35.9 17.7 10.6 Switzerland 405.9 231.9 18.6 11.4 8.1 37.3 10.1 33.6 18.2 7.5 Turkey 1,314.9 1,015.5 140.0 22.6 42.0 241.3 55.7 114.5 81.4 20.4 United Kingdom 2,201.4 1,640.3 125.9 37.5 95.6 258.6 60.9 234.9 129.0 34.2 United States 15,533.8 11,667.0 698.4 207.6 366.0 1,962.8 429.5 2,300.0 1,079.1 246.7 Total (47) 48,686.6 34,597.3 3,037.0 1,011.3 1,206.8 6,274.2 1,314.4 5,570.6 2,803.6 876.1 LATIN AMERICA Bolivia 56.4 37.1 8.0 0.5 0.5 8.6 1.7 3.2 4.9 0.2 Brazil 2,816.3 1,905.7 246.1 43.2 36.7 263.0 98.4 359.0 158.0 31.2 Colombia 535.0 369.0 43.5 9.9 13.9 94.3 8.1 36.4 25.4 8.7 Costa Rica 59.8 47.0 6.3 0.4 1.3 5.4 1.9 4.8 6.3 1.5 Cubae … … … … … … … … … … Dominican Republic 109.0 97.6 16.3 4.2 2.2 19.2 2.1 7.9 7.1 3.6 Ecuador 151.6 103.2 13.7 2.4 2.5 21.9 4.3 11.3 10.3 3.8 El Salvador 46.0 45.5 7.3 0.7 1.3 12.8 2.5 4.4 3.4 1.5 Guatemala 102.4 91.4 22.2 1.0 3.2 16.9 4.4 7.1 4.7 4.4 Haiti 15.6 16.9 6.3 0.5 0.5 3.2 0.5 0.7 0.7 0.1 Honduras 33.8 29.1 6.0 0.9 0.7 5.7 0.8 3.1 1.9 0.5 Nicaragua 24.2 21.1 3.2 0.5 0.4 6.2 0.8 2.7 1.6 0.4 Panama 57.2 39.5 4.3 0.2 1.4 12.2 1.9 3.2 3.8 1.7 Paraguay 47.2 36.7 6.7 0.5 0.9 6.2 2.0 3.5 2.0 1.4 Peru 327.2 213.0 33.2 4.3 8.0 31.7 6.1 19.6 16.1 5.7 72 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 1.4 1.3 1.2 3.0 13.4 4.3 2.6 10.6 3.4 7.1 30.2 11.4 0.5 4.8 0.6 1.3 15.1 5.3 4.2 3.8 0.7 4.1 28.2 11.9 0.7 1.1 1.2 1.1 6.4 2.1 1.6 1.7 0.4 1.3 11.4 5.3 45.1 406.2 44.0 132.5 1,078.4 325.8 162.9 341.6 66.2 329.7 1,914.6 927.3 0.2 1.6 0.8 0.5 5.9 2.1 1.7 1.2 0.2 1.2 10.3 4.9 34.4 52.1 14.9 80.9 312.7 159.8 78.5 133.2 35.8 87.6 646.7 262.5 8.2 15.8 5.8 10.2 76.9 27.8 12.9 22.0 7.0 12.8 134.9 62.2 14.0 15.6 5.0 21.4 115.5 49.8 21.4 62.4 19.9 31.3 250.3 94.0 39.4 102.7 9.8 74.2 482.3 183.1 82.2 127.8 35.3 96.2 848.9 403.6 11.5 30.4 19.0 21.7 160.5 43.4 28.9 55.9 10.1 51.6 283.9 137.1 13.0 50.8 6.3 15.9 176.7 82.0 38.0 80.2 13.5 85.1 360.8 148.7 78.2 374.0 34.2 179.1 1,633.9 701.7 352.4 415.4 123.3 282.8 2,988.9 1,341.0 2.8 15.4 1.2 6.3 54.4 25.8 9.5 13.0 3.0 11.6 97.3 43.0 6.6 14.4 3.2 8.9 70.1 26.1 18.8 25.2 5.9 16.0 135.1 57.4 2.7 4.9 1.9 3.8 30.5 10.2 6.2 10.9 3.6 6.9 56.8 25.6 71.6 117.5 134.0 97.2 788.8 248.5 150.9 347.8 74.5 235.1 1,494.6 668.8 21.4 27.4 8.1 41.4 183.6 91.6 32.6 72.7 28.7 34.2 364.8 143.7 19.4 20.0 13.5 36.3 207.9 25.3 18.5 93.9 39.6 41.8 346.6 179.0 32.3 279.3 42.5 65.7 793.4 260.6 111.7 253.8 88.4 171.3 1,411.3 604.7 174.4 172.6 101.1 206.6 1,311.9 408.7 202.1 351.5 67.1 231.4 2,227.0 1,105.6 996.1 930.9 670.7 1,803.2 10,711.8 955.2 1,570.9 2,828.2 1,014.6 1,295.0 16,102.5 9,105.2 2,501.7 4,099.4 1,822.7 4,690.5 28,697.9 7,058.7 4,588.4 9,256.7 2,881.8 5,530.0 48,802.6 23,862.9 0.2 4.5 2.2 1.1 34.9 1.0 6.5 8.7 2.4 5.4 52.6 29.0 63.6 374.8 85.7 238.4 1,506.8 488.8 316.9 611.4 148.1 458.2 2,840.5 1,272.4 15.1 68.1 27.9 40.0 318.6 46.5 62.1 105.0 20.1 102.2 536.2 253.5 3.6 8.7 1.8 2.7 39.4 7.2 4.2 10.4 2.2 9.5 62.7 34.1 … … … … … … … … … … … … 1.6 14.7 7.7 11.4 88.4 5.1 8.0 13.6 1.9 16.3 118.1 73.3 3.8 22.5 3.0 9.0 89.0 13.1 11.0 34.0 4.6 19.1 154.0 73.2 1.6 6.3 1.7 2.5 40.7 3.6 3.2 4.6 1.2 3.7 53.4 32.4 2.2 10.3 4.7 4.4 81.7 7.2 6.9 12.7 3.3 10.4 110.7 65.7 0.3 1.7 0.0 0.4 16.1 0.2 0.0 4.1 0.0 7.3 21.1 13.5 0.9 5.7 1.4 2.1 25.8 2.8 2.6 7.3 2.0 4.8 39.6 21.3 0.5 5.1 0.9 1.7 18.3 2.5 2.7 3.4 0.7 3.1 26.9 14.0 1.7 5.8 1.4 3.5 34.1 5.1 4.8 11.2 2.7 9.7 56.5 26.1 1.5 8.6 1.3 3.3 31.9 4.3 2.2 6.5 1.2 6.0 45.5 27.3 10.1 42.0 13.3 22.4 188.7 19.0 24.3 66.1 11.7 69.3 310.3 157.8 (continued) Presentation and Analysis of Results 73 Table 2.5 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, (US$, billions) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Uruguay 58.7 43.6 5.7 0.9 1.1 11.3 1.6 6.6 2.3 1.9 Venezuela, RB 500.3 302.7 30.3 5.0 4.3 44.6 6.2 35.7 48.2 16.4 Total (17) 4,940.8 3,399.3 459.0 75.0 79.0 563.3 143.3 509.4 296.8 83.1 CARIBBEAN Anguilla 0.4 0.3 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 Antigua and Barbuda 1.8 1.1 0.1 0.0 0.0 0.4 0.0 0.2 0.1 0.0 Aruba 3.7 2.4 0.1 0.0 0.1 1.0 0.1 0.5 0.2 0.1 Bahamas, The 8.3 5.7 0.4 0.1 0.2 2.1 0.1 0.7 0.4 0.2 Barbados 4.3 3.5 0.4 0.0 0.1 2.1 0.1 0.3 0.2 0.1 Belize 2.6 2.1 0.2 0.0 0.1 1.0 0.1 0.2 0.1 0.1 Bermuda 3.6 2.5 0.2 0.1 0.1 0.5 0.1 0.3 0.2 0.1 f Bonaire … … 0.0 0.0 0.0 … 0.0 … 0.0 0.0 Cayman Islands 2.8 1.9 0.1 0.0 0.1 0.7 0.1 0.1 0.2 0.1 Curaçao 4.2 3.1 0.2 0.0 0.2 1.4 0.1 0.4 0.2 0.1 Dominica 0.7 0.6 0.1 0.0 0.0 0.2 0.0 0.1 0.1 0.0 Grenada 1.2 1.1 0.1 0.0 0.0 0.3 0.0 0.1 0.1 0.1 Jamaica 22.9 19.9 3.2 0.2 0.3 4.0 0.8 1.7 1.8 0.7 Montserrat 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 St. Kitts and Nevis 1.1 0.8 0.1 0.0 0.0 0.3 0.0 0.1 0.0 0.0 St. Lucia 1.8 1.3 0.2 0.0 0.1 0.5 0.0 0.1 0.1 0.1 St. Vincent and the Grenadines 1.1 0.9 0.1 0.0 0.0 0.3 0.0 0.1 0.1 0.0 Sint Maarten 1.2 0.7 0.0 0.0 0.0 0.3 0.0 0.0 0.1 0.0 Suriname 7.8 3.2 0.6 0.1 0.1 1.1 0.1 0.3 0.1 0.1 Trinidad and Tobago 38.3 20.9 2.8 0.1 0.2 3.4 0.5 2.4 1.6 0.4 Turks and Caicos Islands 0.7 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Virgin Islands, British 0.9 0.3 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 Total (22) 109.3 72.7 9.0 0.8 1.7 19.8 2.1 7.6 5.7 2.3 WESTERN ASIA Bahrain 51.8 22.3 2.1 0.1 1.0 5.2 1.1 1.6 2.9 1.2 Egypt, Arab Rep.a 843.8 679.1 133.0 12.6 32.0 200.1 16.8 119.8 28.0 14.6 Iraq 371.0 179.4 29.4 0.6 6.5 73.4 5.1 21.1 9.8 2.7 Jordan 69.8 55.4 8.0 1.4 2.4 19.2 1.6 6.7 3.8 1.9 Kuwait 257.7 67.1 8.1 0.1 4.1 24.2 5.5 4.9 6.3 1.7 Oman 140.4 50.0 6.1 0.1 2.5 10.8 1.5 4.0 8.3 2.0 Qatar 258.1 36.2 3.4 0.1 1.2 8.5 1.2 2.7 4.4 0.8 Saudi Arabia 1,366.7 505.0 49.0 1.5 21.2 177.0 24.0 48.4 35.6 17.2 Sudanb 152.4 97.5 28.1 0.4 6.5 17.0 4.8 3.1 4.7 1.3 United Arab Emirates 503.2 243.5 22.6 0.5 29.8 84.7 9.0 3.7 41.9 17.5 74 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 1.1 5.9 2.6 3.7 37.1 6.4 4.0 10.8 2.0 10.5 58.9 28.5 9.7 82.6 22.2 11.8 256.9 47.8 42.5 84.6 14.8 91.0 449.3 217.9 117.7 667.3 177.7 358.6 2,808.5 660.6 501.9 994.2 218.8 826.4 4,936.4 2,339.9 0.0 0.0 0.0 0.0 0.3 0.0 0.1 0.1 0.0 0.1 0.4 0.2 0.0 0.2 0.0 0.1 0.8 0.3 0.3 0.4 0.0 0.5 1.7 0.6 0.1 0.3 0.0 0.2 1.7 1.1 0.6 1.3 0.2 1.4 4.2 1.1 0.2 0.7 0.3 0.8 4.9 0.8 1.4 2.6 0.8 1.9 9.6 3.5 0.1 0.4 0.5 0.3 2.9 0.5 0.9 0.9 0.3 0.7 5.1 1.5 0.1 0.3 0.0 0.1 1.8 0.2 0.4 0.2 0.1 0.2 2.7 1.0 0.1 0.4 0.2 0.3 2.0 0.6 0.4 1.2 0.5 0.5 4.0 1.6 … … 0.0 … 0.2 … … … … … … 0.1 0.1 0.2 0.1 0.3 1.7 0.2 0.3 0.8 0.2 0.5 3.0 1.2 0.1 0.3 0.1 0.6 2.6 0.5 0.5 1.5 0.5 0.6 5.2 1.8 0.0 0.1 0.0 0.0 0.5 0.1 0.1 0.2 0.0 0.1 0.8 0.4 0.0 0.3 0.0 0.1 0.9 0.2 0.2 0.2 0.0 0.2 1.4 0.7 1.3 4.2 1.7 2.1 16.8 3.0 2.8 4.4 1.1 3.5 27.4 13.1 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.2 0.0 0.1 0.6 0.2 0.3 0.3 0.0 0.3 1.2 0.4 0.0 0.3 0.0 0.1 1.1 0.2 0.3 0.5 0.1 0.5 2.1 0.8 0.0 0.2 0.0 0.1 0.7 0.2 0.2 0.2 0.0 0.3 1.3 0.5 0.0 0.1 0.0 0.1 0.6 0.1 0.3 0.2 0.1 0.1 1.2 0.4 0.1 0.1 0.0 0.4 2.8 0.2 1.4 2.4 1.1 0.7 7.3 2.4 1.1 6.8 1.3 3.0 15.0 9.1 1.2 6.3 1.7 4.6 29.5 13.3 0.0 0.1 0.0 0.0 0.2 0.0 0.2 0.1 0.0 0.1 0.5 0.2 0.0 0.0 0.0 0.0 0.3 0.0 0.1 0.2 0.1 0.1 0.5 0.2 3.5 15.3 4.4 8.9 58.3 17.4 11.8 23.9 6.9 16.7 109.4 44.8 1.4 4.1 0.9 1.4 19.6 2.7 4.3 9.1 1.3 10.5 35.6 17.6 16.3 142.5 14.2 48.7 574.7 96.0 124.8 85.2 16.0 83.7 867.2 448.5 1.5 59.4 1.1 3.6 133.0 61.4 90.9 53.6 12.7 46.1 309.2 90.8 0.7 16.2 0.7 1.4 45.8 10.8 11.5 11.8 1.6 12.4 79.2 33.6 1.9 8.8 1.2 3.1 57.2 10.8 21.4 45.7 9.6 34.2 133.6 44.7 1.4 10.1 1.0 3.9 40.4 10.9 16.8 41.3 7.3 37.9 101.2 34.6 2.4 6.9 0.6 4.9 30.2 7.3 15.3 105.3 25.4 31.0 133.8 24.6 12.4 130.7 15.0 23.2 381.9 143.7 129.3 369.7 66.9 322.0 1,034.1 295.3 1.8 9.8 2.2 2.5 87.4 2.4 19.5 33.1 6.6 33.3 154.6 74.0 5.6 16.5 6.8 10.4 243.5 4.3 22.0 155.6 34.2 118.5 400.2 181.8 (continued) Presentation and Analysis of Results 75 Table 2.5 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, (US$, billions) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) West Bank and Gaza 16.0 17.0 3.5 0.3 1.0 1.9 0.7 2.5 0.9 0.5 Yemen, Rep. 88.6 65.8 13.3 3.3 3.1 18.1 1.1 12.0 2.9 0.5 Total (12) 4,119.5 2,018.3 306.8 21.1 111.3 640.1 72.2 230.6 149.6 62.0 SINGLETONS Georgia 28.3 27.1 4.3 1.4 0.3 9.1 0.6 5.0 1.3 0.9 Iran, Islamic Rep. 1,314.2 644.5 82.8 4.0 14.3 221.8 13.1 113.7 31.5 30.7 Total (2) 1,342.6 671.6 87.1 5.3 14.7 230.9 13.7 118.7 32.8 31.6 WORLDg (179) 90,646.6 58,230.1 6,854.0 1,440.2 2,368.2 11,063.6 2,023.0 9,325.5 4,258.7 1,604.8 Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; ... = data suppressed because of incompleteness. a. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. b. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. c. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. d. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. e. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. f. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. g. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 76 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.4 4.0 0.3 1.2 13.4 4.1 4.5 2.9 0.3 3.1 23.7 11.9 0.2 12.7 0.0 2.7 55.7 10.0 14.5 8.6 0.4 9.5 91.2 45.3 45.9 421.7 44.0 107.0 1,682.6 364.4 474.8 921.8 182.3 742.3 3,363.6 1,302.6 1.4 8.4 0.5 1.7 21.4 4.3 6.3 3.3 1.1 1.9 34.3 16.2 12.7 181.6 4.3 51.1 511.3 137.8 208.6 220.0 47.7 234.2 1,169.0 380.2 14.1 190.0 4.8 52.7 532.7 142.2 214.9 223.4 48.9 236.1 1,203.3 396.4 3,327.8 8,870.0 2,747.5 6,594.3 48,108.7 11,891.4 8,284.1 21,137.9 4,770.3 17,993.4 89,283.4 39,852.6 Presentation and Analysis of Results 77 Table 2.6 Shares of World Real Expenditures (World = 100), ICP 2011 Alcoholic Housing, Furnishings, REAL EXPENDITURES: beverages, water, household COUNTRY AND REGIONAL Gross Actual Food and tobacco, Clothing electricity, equipment SHARES (world = 100)a domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) AFRICA Algeria 0.50 0.40 0.60 0.20 0.20 0.10 0.20 0.40 0.60 0.60 Angola 0.20 0.10 0.30 0.40 0.20 0.10 0.20 0.10 0.10 0.00 Benin 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Botswana 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 Burkina Faso 0.00 0.00 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 Burundi 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Cameroon 0.10 0.10 0.20 0.10 0.10 0.10 0.10 0.00 0.10 0.00 Cape Verde 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Central African Republic 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Chad 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Comoros 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Congo, Rep. 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Congo, Dem. Rep. 0.00 0.10 0.10 0.00 0.10 0.10 0.00 0.00 0.00 0.00 Côte d’Ivoire 0.10 0.10 0.10 0.10 0.00 0.00 0.10 0.00 0.10 0.00 Djibouti 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Egypt, Arab Rep.b 0.90 1.20 1.90 0.90 1.40 1.80 0.80 1.30 0.70 0.90 Equatorial Guinea 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Ethiopia 0.10 0.10 0.20 0.10 0.20 0.10 0.20 0.20 0.00 0.00 Gabon 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 Gambia, The 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Ghana 0.10 0.10 0.10 0.00 0.40 0.10 0.10 0.10 0.10 0.10 Guinea 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Guinea-Bissau 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Kenya 0.10 0.10 0.20 0.20 0.10 0.10 0.10 0.10 0.10 0.20 Lesotho 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Liberia 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Madagascar 0.00 0.00 0.10 0.00 0.10 0.00 0.10 0.00 0.00 0.00 Malawi 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Mali 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Mauritania 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Mauritius 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 Morocco 0.20 0.20 0.40 0.10 0.20 0.30 0.20 0.10 0.20 0.40 Mozambique 0.00 0.00 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 Namibia 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Niger 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 Nigeria 0.60 0.60 0.90 0.30 2.40 0.40 1.10 0.30 0.40 0.30 Rwanda 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 São Tomé and Príncipe 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 78 Purchasing Power Parities and the Real Size of World Economies Individual Individual Individual Collective consumption Miscella- consumption consumption consumption Gross expenditure Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery by households and and goods and by by by capital and Domestic without culture Education hotels services households government government formation equipment Construction absorption housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.20 1.00 0.20 0.60 0.30 1.30 1.00 0.50 0.40 0.60 0.50 0.30 0.00 0.10 0.00 0.20 0.10 0.20 0.50 0.10 0.10 0.20 0.20 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.10 0.00 0.10 0.00 0.00 0.00 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.10 0.00 0.10 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.10 0.00 0.10 0.00 0.00 0.00 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.50 1.60 0.50 0.70 1.20 0.80 1.50 0.40 0.30 0.50 1.00 1.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.20 0.10 0.20 0.20 0.00 0.10 0.10 0.00 0.10 0.10 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.30 0.00 0.00 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.30 0.10 0.10 0.10 0.20 0.10 0.10 0.10 0.10 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.40 0.20 0.10 0.20 0.30 0.30 0.30 0.20 0.40 0.30 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 1.20 0.00 0.30 0.60 0.40 0.70 0.20 0.20 0.20 0.50 0.70 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 (continued) Presentation and Analysis of Results 79 Table 2.6 (Continued) Alcoholic Housing, Furnishings, REAL EXPENDITURES: beverages, water, household COUNTRY AND REGIONAL Gross Actual Food and tobacco, Clothing electricity, equipment SHARES (world = 100)a domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Senegal 0.00 0.00 0.10 0.00 0.00 0.10 0.10 0.00 0.00 0.10 Seychelles 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Sierra Leone 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 South Africa 0.70 0.70 0.80 1.20 0.70 0.60 0.80 0.70 0.90 0.80 Sudanc 0.20 0.20 0.40 0.00 0.30 0.20 0.20 0.00 0.10 0.10 Swaziland 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Tanzania 0.10 0.10 0.30 0.00 0.10 0.00 0.10 0.00 0.00 0.00 Togo 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Tunisia 0.10 0.10 0.10 0.10 0.10 0.10 0.20 0.10 0.20 0.20 Uganda 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.00 0.00 0.00 Zambia 0.00 0.00 0.10 0.00 0.10 0.00 0.00 0.00 0.00 0.00 Zimbabwe 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Total (50) 4.50 4.90 8.20 4.80 7.20 4.70 5.30 3.70 3.90 4.10 ASIA AND THE PACIFIC Bangladesh 0.50 0.50 1.40 0.60 0.70 0.70 0.40 0.30 0.10 0.30 Bhutan 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Brunei Darussalam 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Cambodia 0.00 0.10 0.10 0.10 0.00 0.00 0.00 0.10 0.00 0.00 Chinad 14.90 10.00 10.80 5.50 13.60 9.60 8.40 16.10 6.00 18.00 Fiji 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Hong Kong SAR, China 0.40 0.40 0.30 0.10 0.60 0.40 0.50 0.20 0.30 0.60 India 6.40 6.30 10.10 4.80 12.60 5.90 3.90 4.90 6.30 3.10 Indonesia 2.30 2.00 3.90 0.80 1.40 2.60 1.20 0.60 1.20 1.30 Lao PDR 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Macao SAR, China 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Malaysia 0.70 0.60 0.50 0.20 0.20 0.60 0.40 0.30 0.60 1.00 Maldives 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Mongolia 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 Myanmar 0.20 0.20 0.50 0.10 0.20 0.20 0.10 0.30 0.00 0.10 Nepal 0.10 0.10 0.20 0.10 0.10 0.10 0.00 0.10 0.00 0.00 Pakistan 0.90 1.20 2.50 0.40 1.20 1.90 0.60 1.30 0.50 0.80 Philippines 0.60 0.70 1.60 0.40 0.20 0.60 0.60 0.20 0.70 0.50 Singapore 0.40 0.20 0.10 0.10 0.20 0.20 0.20 0.20 0.30 0.20 Sri Lanka 0.20 0.20 0.50 0.60 0.20 0.20 0.10 0.20 0.10 0.20 Taiwan, China 1.00 1.00 0.60 0.60 1.20 0.90 0.80 1.20 1.00 2.30 Thailand 1.00 1.00 1.30 0.80 0.90 0.80 0.70 0.80 1.10 0.80 Vietnam 0.50 0.50 0.60 0.50 0.50 0.50 0.50 0.60 0.20 0.10 Total (23) 30.00 25.10 35.20 15.80 33.70 25.30 18.40 27.30 18.70 29.40 80 Purchasing Power Parities and the Real Size of World Economies Individual Individual Individual Collective consumption Miscella- consumption consumption consumption Gross expenditure Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery by households and and goods and by by by capital and Domestic without culture Education hotels services households government government formation equipment Construction absorption housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.40 1.00 0.20 0.70 0.70 0.70 1.00 0.60 0.60 0.50 0.70 0.70 0.10 0.10 0.10 0.00 0.20 0.00 0.20 0.20 0.10 0.20 0.20 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.10 0.00 0.10 0.10 0.10 0.20 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.20 0.20 0.10 0.10 0.20 0.20 0.10 0.10 0.20 0.10 0.10 0.10 0.20 0.00 0.00 0.10 0.10 0.00 0.10 0.00 0.10 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.90 7.40 2.10 3.40 4.90 4.60 6.80 3.40 2.90 4.00 4.60 4.90 0.00 0.60 0.20 0.10 0.60 0.10 0.20 0.50 0.20 0.80 0.50 0.60 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.10 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.10 10.40 13.10 10.90 6.00 9.10 16.10 10.50 27.10 16.70 34.60 14.60 9.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 0.10 0.80 0.60 0.40 0.10 0.20 0.40 0.50 0.30 0.40 0.40 1.20 4.80 2.20 6.20 6.80 2.70 6.00 6.70 4.50 9.00 6.80 6.80 0.60 3.20 2.80 0.80 2.10 1.30 1.60 3.10 0.90 5.60 2.30 2.10 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.30 0.90 1.00 0.50 0.50 0.50 0.60 0.60 0.50 0.60 0.60 0.50 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 0.20 0.00 0.20 0.40 0.20 0.20 0.10 0.20 0.20 0.20 0.00 0.10 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.10 0.10 0.10 0.20 1.10 0.20 0.50 1.30 0.40 0.90 0.30 0.20 0.40 0.90 1.30 0.20 1.00 0.50 0.60 0.80 0.20 0.40 0.40 0.30 0.50 0.60 0.80 0.60 0.20 0.60 0.20 0.20 0.10 0.30 0.50 0.40 0.50 0.30 0.20 0.00 0.30 0.10 0.10 0.20 0.30 0.20 0.20 0.10 0.20 0.20 0.20 1.60 1.10 1.20 1.10 1.10 0.50 0.90 0.80 0.90 0.70 0.90 1.10 0.70 1.40 1.80 0.60 1.00 0.90 1.00 1.00 1.30 0.80 1.00 1.00 0.30 1.20 0.40 0.10 0.40 0.50 0.60 0.50 0.20 0.70 0.50 0.40 17.30 30.50 23.30 17.60 25.00 24.40 23.80 42.50 26.90 55.20 30.00 25.00 (continued) Presentation and Analysis of Results 81 Table 2.6 (Continued) Alcoholic Housing, Furnishings, REAL EXPENDITURES: beverages, water, household COUNTRY AND REGIONAL Gross Actual Food and tobacco, Clothing electricity, equipment SHARES (world = 100)a domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) COMMONWEALTH OF INDEPENDENT STATES Armenia 0.00 0.00 0.10 0.10 0.00 0.10 0.00 0.00 0.00 0.10 Azerbaijan 0.20 0.10 0.20 0.10 0.10 0.20 0.10 0.10 0.10 0.20 Belarus 0.20 0.20 0.30 0.50 0.10 0.30 0.10 0.20 0.10 0.30 Kazakhstan 0.40 0.30 0.40 0.40 0.30 0.50 0.20 0.30 0.30 0.40 Kyrgyz Republic 0.00 0.00 0.00 0.10 0.00 0.10 0.00 0.00 0.00 0.10 Moldova 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 Russian Federatione 3.50 3.70 4.70 12.70 4.20 4.20 2.90 2.50 2.80 5.80 Tajikistan 0.00 0.00 0.10 0.00 0.00 0.10 0.00 0.00 0.00 0.10 Ukraine 0.40 0.60 1.00 1.70 0.40 1.00 0.40 0.60 0.40 0.40 Total (9) 4.80 5.10 6.80 15.70 5.30 6.40 3.90 3.80 3.80 7.50 EUROSTAT-OECD Albania 0.00 0.00 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 Australia 1.10 1.10 0.70 1.10 0.70 0.90 1.20 0.80 1.20 1.10 Austria 0.40 0.40 0.20 0.60 0.50 0.40 0.60 0.30 0.40 0.30 Belgium 0.50 0.50 0.40 0.70 0.40 0.40 0.60 0.50 0.50 0.30 Bosnia and Herzegovina 0.00 0.10 0.10 0.20 0.00 0.10 0.10 0.00 0.00 0.00 Bulgaria 0.10 0.10 0.10 0.30 0.00 0.20 0.20 0.20 0.10 0.20 Canada 1.60 1.60 0.80 1.50 1.40 1.70 1.80 1.40 2.30 1.20 Chile 0.40 0.40 0.30 0.40 0.40 0.30 0.50 0.30 0.50 0.40 Croatia 0.10 0.10 0.10 0.30 0.10 0.10 0.10 0.10 0.10 0.10 Cyprus 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.10 Czech Republic 0.30 0.30 0.30 0.90 0.10 0.30 0.30 0.40 0.20 0.20 Denmark 0.30 0.30 0.20 0.30 0.20 0.20 0.30 0.20 0.20 0.20 Estonia 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 Finland 0.20 0.20 0.20 0.40 0.20 0.20 0.30 0.20 0.20 0.20 France 2.60 3.00 2.50 3.50 2.40 2.80 3.40 2.90 3.30 2.30 Germany 3.70 4.00 2.70 5.10 3.50 3.60 5.20 4.40 4.00 4.00 Greece 0.30 0.40 0.40 0.70 0.30 0.50 0.40 0.40 0.40 0.30 Hungary 0.20 0.30 0.20 0.70 0.10 0.30 0.20 0.30 0.20 0.20 Iceland 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Ireland 0.20 0.20 0.10 0.20 0.20 0.20 0.20 0.20 0.20 0.20 Israel 0.30 0.30 0.20 0.20 0.20 0.30 0.40 0.20 0.40 0.30 Italy 2.30 2.50 2.20 2.70 3.60 2.40 3.70 2.20 2.70 2.00 Japan 4.80 5.40 3.40 6.20 3.50 5.50 5.60 4.90 5.30 6.00 Korea, Rep. 1.60 1.50 0.80 1.30 1.00 1.70 1.00 1.70 1.50 2.70 Latvia 0.00 0.00 0.00 0.10 0.00 0.10 0.00 0.00 0.00 0.00 Lithuania 0.10 0.10 0.10 0.20 0.10 0.10 0.10 0.10 0.10 0.10 82 Purchasing Power Parities and the Real Size of World Economies Individual Individual Individual Collective consumption Miscella- consumption consumption consumption Gross expenditure Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery by households and and goods and by by by capital and Domestic without culture Education hotels services households government government formation equipment Construction absorption housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.20 0.00 0.00 0.10 0.10 0.20 0.10 0.10 0.00 0.10 0.10 0.10 0.50 0.10 0.00 0.20 0.40 0.10 0.10 0.20 0.10 0.20 0.20 0.20 0.80 0.20 0.20 0.30 0.50 0.40 0.20 0.20 0.20 0.30 0.30 0.00 0.10 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 2.40 4.20 1.20 2.60 3.40 5.90 4.30 2.00 2.60 1.60 3.30 3.40 0.00 0.10 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.30 1.20 0.10 0.30 0.50 1.20 0.40 0.20 0.20 0.10 0.50 0.50 3.10 7.20 1.70 3.30 4.70 8.40 5.50 2.60 3.40 2.10 4.50 4.60 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 1.90 0.80 1.30 1.40 1.10 1.10 0.90 1.10 1.40 0.70 1.00 1.10 0.60 0.20 0.80 0.40 0.40 0.40 0.30 0.40 0.60 0.30 0.40 0.40 0.60 0.40 0.40 0.60 0.50 0.70 0.40 0.50 0.70 0.40 0.50 0.50 0.00 0.10 0.10 0.00 0.10 0.10 0.10 0.00 0.00 0.00 0.00 0.10 0.20 0.20 0.20 0.10 0.10 0.20 0.20 0.10 0.10 0.10 0.10 0.10 2.20 1.10 1.60 2.00 1.60 1.80 1.60 1.60 1.50 1.40 1.60 1.50 0.40 0.70 0.30 0.50 0.40 0.40 0.30 0.30 0.40 0.30 0.40 0.40 0.10 0.10 0.20 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.40 0.30 0.40 0.20 0.30 0.50 0.40 0.30 0.40 0.20 0.30 0.30 0.40 0.20 0.20 0.40 0.20 0.50 0.20 0.20 0.30 0.20 0.20 0.20 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.40 0.20 0.20 0.30 0.20 0.40 0.20 0.20 0.20 0.20 0.20 0.20 3.80 2.10 3.30 3.50 2.70 4.50 2.40 2.30 2.70 1.90 2.70 2.70 4.70 2.40 3.40 5.30 3.80 5.20 2.70 2.70 4.60 1.90 3.50 3.80 0.30 0.30 0.80 0.30 0.40 0.30 0.50 0.20 0.30 0.20 0.40 0.40 0.30 0.30 0.30 0.30 0.20 0.40 0.40 0.20 0.20 0.10 0.20 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.20 0.20 0.30 0.20 0.20 0.30 0.10 0.10 0.20 0.10 0.20 0.20 0.30 0.30 0.30 0.30 0.30 0.40 0.40 0.20 0.20 0.20 0.30 0.20 2.50 1.60 3.90 2.20 2.40 2.80 2.00 2.10 3.00 1.50 2.30 2.40 6.80 3.00 6.00 8.40 5.10 6.90 5.10 4.20 6.90 2.40 4.90 4.80 1.60 1.60 1.50 1.90 1.50 1.40 1.60 1.80 2.10 1.50 1.60 1.40 0.10 0.10 0.00 0.00 0.00 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.10 0.10 0.00 0.10 0.10 0.10 0.10 0.00 0.00 0.00 0.10 0.10 (continued) Presentation and Analysis of Results 83 Table 2.6 (Continued) Alcoholic Housing, Furnishings, REAL EXPENDITURES: beverages, water, household COUNTRY AND REGIONAL Gross Actual Food and tobacco, Clothing electricity, equipment SHARES (world = 100)a domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Luxembourg 0.10 0.00 0.00 0.20 0.00 0.00 0.10 0.00 0.10 0.00 Macedonia, FYR 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Malta 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Mexico 2.10 2.40 3.40 2.20 1.50 1.80 2.80 1.10 3.60 2.20 Montenegro 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Netherlands 0.80 0.70 0.60 0.80 0.70 0.60 0.90 0.70 0.70 0.80 New Zealand 0.20 0.20 0.10 0.20 0.20 0.10 0.20 0.20 0.20 0.10 Norway 0.30 0.30 0.20 0.20 0.20 0.20 0.30 0.20 0.30 0.30 Poland 0.90 1.10 1.20 2.00 0.50 1.50 0.90 1.10 0.70 0.80 Portugal 0.30 0.30 0.40 0.50 0.30 0.30 0.40 0.30 0.30 0.30 Romania 0.40 0.40 0.60 0.60 0.20 0.40 0.30 0.60 0.30 0.50 e Russian Federation 3.50 3.70 4.70 12.70 4.20 4.20 2.90 2.50 2.80 5.80 Serbia 0.10 0.10 0.20 0.30 0.00 0.20 0.10 0.10 0.10 0.20 Slovak Republic 0.10 0.20 0.10 0.20 0.10 0.20 0.20 0.20 0.10 0.10 Slovenia 0.10 0.10 0.10 0.20 0.10 0.10 0.10 0.10 0.10 0.10 Spain 1.60 1.70 1.70 2.20 1.90 1.50 1.80 1.50 1.60 1.00 Sweden 0.40 0.40 0.30 0.50 0.40 0.50 0.40 0.40 0.40 0.70 Switzerland 0.40 0.40 0.30 0.80 0.30 0.30 0.50 0.40 0.40 0.50 Turkey 1.50 1.70 2.00 1.60 1.80 2.20 2.80 1.20 1.90 1.30 United Kingdom 2.40 2.80 1.80 2.60 4.00 2.30 3.00 2.50 3.00 2.10 United States 17.10 20.00 10.20 14.40 15.50 17.70 21.20 24.70 25.30 15.40 Total (47) 53.70 59.40 44.30 70.20 51.00 56.70 65.00 59.70 65.80 54.60 LATIN AMERICA Bolivia 0.10 0.10 0.10 0.00 0.00 0.10 0.10 0.00 0.10 0.00 Brazil 3.10 3.30 3.60 3.00 1.50 2.40 4.90 3.80 3.70 1.90 Colombia 0.60 0.60 0.60 0.70 0.60 0.90 0.40 0.40 0.60 0.50 Costa Rica 0.10 0.10 0.10 0.00 0.10 0.00 0.10 0.10 0.10 0.10 f Cuba … … … … … … … … … … Dominican Republic 0.10 0.20 0.20 0.30 0.10 0.20 0.10 0.10 0.20 0.20 Ecuador 0.20 0.20 0.20 0.20 0.10 0.20 0.20 0.10 0.20 0.20 El Salvador 0.10 0.10 0.10 0.00 0.10 0.10 0.10 0.00 0.10 0.10 Guatemala 0.10 0.20 0.30 0.10 0.10 0.20 0.20 0.10 0.10 0.30 Haiti 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Honduras 0.00 0.10 0.10 0.10 0.00 0.10 0.00 0.00 0.00 0.00 Nicaragua 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 Panama 0.10 0.10 0.10 0.00 0.10 0.10 0.10 0.00 0.10 0.10 Paraguay 0.10 0.10 0.10 0.00 0.00 0.10 0.10 0.00 0.00 0.10 Peru 0.40 0.40 0.50 0.30 0.30 0.30 0.30 0.20 0.40 0.40 84 Purchasing Power Parities and the Real Size of World Economies Individual Individual Individual Collective consumption Miscella- consumption consumption consumption Gross expenditure Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery by households and and goods and by by by capital and Domestic without culture Education hotels services households government government formation equipment Construction absorption housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.10 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.40 4.60 1.60 2.00 2.20 2.70 2.00 1.60 1.40 1.80 2.10 2.30 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 0.60 0.50 1.20 0.60 1.30 0.90 0.60 0.80 0.50 0.70 0.70 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.10 0.10 0.10 0.20 0.20 0.40 0.20 0.20 0.30 0.20 0.40 0.30 0.30 0.40 0.20 0.30 0.20 1.20 1.20 0.40 1.10 1.00 1.50 1.00 0.60 0.70 0.50 1.00 1.00 0.30 0.30 0.70 0.30 0.30 0.40 0.30 0.30 0.20 0.30 0.30 0.30 0.40 0.60 0.20 0.20 0.40 0.70 0.50 0.40 0.30 0.50 0.40 0.40 2.40 4.20 1.20 2.70 3.40 5.90 4.30 2.00 2.60 1.60 3.30 3.40 0.10 0.20 0.00 0.10 0.10 0.20 0.10 0.10 0.10 0.10 0.10 0.10 0.20 0.20 0.10 0.10 0.10 0.20 0.20 0.10 0.10 0.10 0.20 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.00 0.10 0.10 2.20 1.30 4.90 1.50 1.60 2.10 1.80 1.60 1.60 1.30 1.70 1.70 0.60 0.30 0.30 0.60 0.40 0.80 0.40 0.30 0.60 0.20 0.40 0.40 0.60 0.20 0.50 0.60 0.40 0.20 0.20 0.40 0.80 0.20 0.40 0.40 1.00 3.10 1.50 1.00 1.60 2.20 1.30 1.20 1.90 1.00 1.60 1.50 5.20 1.90 3.70 3.10 2.70 3.40 2.40 1.70 1.40 1.30 2.50 2.80 29.90 10.50 24.40 27.30 22.30 8.00 19.00 13.40 21.30 7.20 18.00 22.80 75.20 46.20 66.30 71.10 59.70 59.40 55.40 43.80 60.40 30.70 54.70 59.90 0.00 0.10 0.10 0.00 0.10 0.00 0.10 0.00 0.10 0.00 0.10 0.10 1.90 4.20 3.10 3.60 3.10 4.10 3.80 2.90 3.10 2.50 3.20 3.20 0.50 0.80 1.00 0.60 0.70 0.40 0.70 0.50 0.40 0.60 0.60 0.60 0.10 0.10 0.10 0.00 0.10 0.10 0.10 0.00 0.00 0.10 0.10 0.10 … … … … … … … … … … … … 0.00 0.20 0.30 0.20 0.20 0.00 0.10 0.10 0.00 0.10 0.10 0.20 0.10 0.30 0.10 0.10 0.20 0.10 0.10 0.20 0.10 0.10 0.20 0.20 0.00 0.10 0.10 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.10 0.10 0.10 0.10 0.20 0.10 0.20 0.10 0.10 0.10 0.10 0.10 0.10 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.10 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.10 0.10 0.10 0.00 0.10 0.10 0.10 0.10 0.10 0.10 0.00 0.10 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.10 0.10 0.30 0.50 0.50 0.30 0.40 0.20 0.30 0.30 0.20 0.40 0.30 0.40 (continued) Presentation and Analysis of Results 85 Table 2.6 (Continued) Alcoholic Housing, Furnishings, REAL EXPENDITURES: beverages, water, household COUNTRY AND REGIONAL Gross Actual Food and tobacco, Clothing electricity, equipment SHARES (world = 100)a domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Uruguay 0.10 0.10 0.10 0.10 0.00 0.10 0.10 0.10 0.10 0.10 Venezuela, RB 0.60 0.50 0.40 0.30 0.20 0.40 0.30 0.40 1.10 1.00 Total (17) 5.50 5.80 6.70 5.20 3.30 5.10 7.10 5.50 7.00 5.20 CARIBBEAN Anguilla 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Antigua and Barbuda 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Aruba 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Bahamas, The 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Barbados 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Belize 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Bermuda 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 g Bonaire … … … … … … … … … … Cayman Islands 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Curaçao 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Dominica 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Grenada 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Jamaica 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Montserrat 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 St. Kitts and Nevis 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 St. Lucia 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 St. Vincent and the Grenadines 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Sint Maarten 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Suriname 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Trinidad and Tobago 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Turks and Caicos Islands 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Virgin Islands, British 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Total (22) 0.10 0.10 0.10 0.10 0.10 0.20 0.10 0.10 0.10 0.10 WESTERN ASIA Bahrain 0.10 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.10 0.10 b Egypt, Arab Rep. 0.90 1.20 1.90 0.90 1.40 1.80 0.80 1.30 0.70 0.90 Iraq 0.40 0.30 0.40 0.00 0.30 0.70 0.20 0.20 0.20 0.20 Jordan 0.10 0.10 0.10 0.10 0.10 0.20 0.10 0.10 0.10 0.10 Kuwait 0.30 0.10 0.10 0.00 0.20 0.20 0.30 0.10 0.10 0.10 Oman 0.20 0.10 0.10 0.00 0.10 0.10 0.10 0.00 0.20 0.10 Qatar 0.30 0.10 0.00 0.00 0.10 0.10 0.10 0.00 0.10 0.10 Saudi Arabia 1.50 0.90 0.70 0.10 0.90 1.60 1.20 0.50 0.80 1.10 c Sudan 0.20 0.20 0.40 0.00 0.30 0.20 0.20 0.00 0.10 0.10 United Arab Emirates 0.60 0.40 0.30 0.00 1.30 0.80 0.40 0.00 1.00 1.10 West Bank and Gaza 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 86 Purchasing Power Parities and the Real Size of World Economies Individual Individual Individual Collective consumption Miscella- consumption consumption consumption Gross expenditure Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery by households and and goods and by by by capital and Domestic without culture Education hotels services households government government formation equipment Construction absorption housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.00 0.10 0.10 0.10 0.10 0.10 0.00 0.10 0.00 0.10 0.10 0.10 0.30 0.90 0.80 0.20 0.50 0.40 0.50 0.40 0.30 0.50 0.50 0.50 3.50 7.50 6.50 5.40 5.80 5.60 6.10 4.70 4.60 4.60 5.50 5.90 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 … … … … … … … … … … … … 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.20 0.20 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.10 0.00 0.00 0.50 1.60 0.50 0.70 1.20 0.80 1.50 0.40 0.30 0.50 1.00 1.10 0.00 0.70 0.00 0.10 0.30 0.50 1.10 0.30 0.30 0.30 0.30 0.20 0.00 0.20 0.00 0.00 0.10 0.10 0.10 0.10 0.00 0.10 0.10 0.10 0.10 0.10 0.00 0.00 0.10 0.10 0.30 0.20 0.20 0.20 0.10 0.10 0.00 0.10 0.00 0.10 0.10 0.10 0.20 0.20 0.20 0.20 0.10 0.10 0.10 0.10 0.00 0.10 0.10 0.10 0.20 0.50 0.50 0.20 0.10 0.10 0.40 1.50 0.50 0.40 0.80 1.20 1.60 1.70 1.40 1.80 1.20 0.70 0.10 0.10 0.10 0.00 0.20 0.00 0.20 0.20 0.10 0.20 0.20 0.20 0.20 0.20 0.20 0.20 0.50 0.00 0.30 0.70 0.70 0.70 0.40 0.50 0.00 0.00 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 (continued) Presentation and Analysis of Results 87 Table 2.6 (Continued) Alcoholic Housing, Furnishings, REAL EXPENDITURES: beverages, water, household COUNTRY AND REGIONAL Gross Actual Food and tobacco, Clothing electricity, equipment SHARES (world = 100)a domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Yemen, Rep. 0.10 0.10 0.20 0.20 0.10 0.20 0.10 0.10 0.10 0.00 Total (12) 4.50 3.50 4.50 1.50 4.70 5.80 3.60 2.50 3.50 3.90 SINGLETONS Georgia 0.00 0.00 0.10 0.10 0.00 0.10 0.00 0.10 0.00 0.10 Iran, Islamic Rep. 1.40 1.10 1.20 0.30 0.60 2.00 0.60 1.20 0.70 1.90 Total (2) 1.50 1.20 1.30 0.40 0.60 2.10 0.70 1.30 0.80 2.00 WORLDh (179) 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; ... = data suppressed because of incompleteness. a. All shares are rounded to one decimal place. More precision can be found in the Excel version of the table, which can be downloaded from the ICP website. b. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. c. Sudan participated in both the Africa and Western Asia regions.The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. d. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. e. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. f. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. g. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. h. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 88 Purchasing Power Parities and the Real Size of World Economies Individual Individual Individual Collective consumption Miscella- consumption consumption consumption Gross expenditure Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery by households and and goods and by by by capital and Domestic without culture Education hotels services households government government formation equipment Construction absorption housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 0.00 0.10 0.00 0.00 0.10 0.10 0.20 0.00 0.00 0.10 0.10 0.10 1.40 4.80 1.60 1.60 3.50 3.10 5.70 4.40 3.80 4.10 3.80 3.30 0.00 0.10 0.00 0.00 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.40 2.00 0.20 0.80 1.10 1.20 2.50 1.00 1.00 1.30 1.30 1.00 0.40 2.10 0.20 0.80 1.10 1.20 2.60 1.10 1.00 1.30 1.30 1.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 100.00 Presentation and Analysis of Results 89 Table 2.7 Real Expenditures Per Capita in U.S. Dollars, ICP 2011 REAL EXPENDITURES Alcoholic Housing, Furnishings, PER CAPITA (US$) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) AFRICA Algeria 13,195 6,270 1,071 69 126 366 110 985 658 285 Angola 7,288 4,319 1,050 288 182 579 159 325 190 35 Benin 1,766 1,473 397 45 63 170 27 86 85 38 Botswana 13,409 6,780 758 379 469 688 243 626 889 208 Burkina Faso 1,343 953 258 58 22 143 29 61 39 26 Burundi 712 648 152 53 7 178 4 46 18 4 Cameroon 2,757 2,297 641 54 150 294 121 48 122 20 Cape Verde 6,126 4,747 997 196 104 983 262 444 206 194 Central African Republic 897 869 248 71 69 82 27 26 21 4 Chad 1,984 1,476 404 58 34 155 62 196 93 35 Comoros 610 621 180 1 17 260 12 10 8 2 Congo, Rep. 5,830 1,513 281 64 37 339 36 227 78 52 Congo, Dem. Rep. 655 447 121 10 20 95 12 41 8 4 Côte d’Ivoire 2,669 1,979 480 57 57 271 120 170 139 37 Djibouti 2,412 1,719 319 124 48 669 71 80 72 6 a Egypt, Arab Rep. 10,599 8,529 1,670 159 402 2,514 210 1,505 352 183 Equatorial Guinea 39,440 4,916 962 147 151 961 111 847 285 182 Ethiopia 1,214 979 202 19 43 172 59 166 10 4 Gabon 16,483 5,976 916 504 289 1,051 217 685 458 181 Gambia, The 1,507 1,221 258 32 129 105 23 412 24 38 Ghana 3,426 2,242 380 26 333 349 113 192 138 34 Guinea 1,287 789 197 10 59 186 23 113 28 1 Guinea-Bissau 1,365 928 262 14 64 161 40 50 41 4 Kenya 2,136 1,937 384 69 53 229 63 271 101 74 Lesotho 2,130 2,524 399 52 310 366 136 197 55 60 Liberia 537 606 87 17 90 121 28 26 11 17 Madagascar 1,412 1,332 323 34 106 87 131 52 87 7 Malawi 973 1,006 256 44 31 244 64 97 33 14 Mali 1,509 1,047 291 15 58 112 39 90 75 18 Mauritania 3,191 2,089 697 17 85 258 42 153 63 59 Mauritius 15,506 11,812 2,127 616 802 2,597 646 1,148 805 416 Morocco 6,764 4,309 840 67 157 1,118 139 348 263 192 Mozambique 951 890 260 37 45 105 15 39 50 9 Namibia 8,360 5,827 690 231 362 1,021 372 1,004 175 56 Niger 852 719 156 14 75 89 31 49 36 10 Nigeria 3,146 2,075 387 31 345 263 139 151 108 27 Rwanda 1,337 1,293 367 32 36 319 36 66 40 13 São Tomé and Príncipe 3,045 3,340 972 134 121 384 73 300 217 35 90 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 153 2,383 120 1,078 3,983 4,311 2,202 3,054 585 2,922 11,890 3,787 61 547 70 508 3,423 1,122 2,319 1,493 207 1,800 7,757 3,039 16 195 96 62 1,286 138 191 261 45 290 1,919 1,096 152 2,447 170 596 5,396 1,801 1,848 5,051 819 6,049 14,305 4,794 15 102 28 30 840 69 245 168 31 159 1,424 712 4 161 19 16 537 125 145 83 16 77 845 392 24 137 103 60 2,063 105 298 411 104 322 2,966 1,760 35 967 529 324 3,907 945 766 2,374 471 2,246 8,133 3,164 11 116 13 35 770 54 47 108 16 97 1,012 679 30 83 7 39 1,316 75 111 403 89 293 2,040 1,121 4 52 0 18 563 8 180 72 16 62 866 375 30 311 88 63 1,265 256 325 1,492 146 2,023 3,546 1,064 5 79 16 10 393 31 91 120 23 117 653 317 43 191 24 105 1,746 164 238 243 38 275 2,247 1,482 14 284 11 39 1,482 206 566 626 89 804 2,963 1,091 205 1,789 179 612 7,218 1,206 1,568 1,070 201 1,051 10,892 5,633 59 788 129 284 4,340 482 497 13,909 3,019 9,000 18,710 3,692 4 159 46 129 863 65 106 213 26 250 1,321 755 131 691 205 219 5,104 823 1,836 2,921 454 1,229 10,609 4,304 33 311 7 66 1,051 141 167 261 63 190 1,640 932 18 1,017 1 104 1,868 398 474 843 159 837 3,601 1,665 5 118 7 21 701 32 102 197 56 121 1,116 554 25 106 3 17 810 72 374 136 26 133 1,362 719 50 566 92 164 1,563 437 178 325 75 289 2,417 1,301 77 476 20 173 2,098 462 462 495 57 645 3,456 1,714 10 287 3 52 551 6 84 63 23 16 779 453 49 164 53 25 1,187 73 110 156 28 165 1,557 1,082 15 119 14 28 885 90 57 131 42 49 1,151 706 33 137 11 32 905 113 241 251 50 238 1,525 784 16 435 8 40 1,699 469 643 1,234 264 989 3,356 1,436 679 2,453 223 762 9,927 2,015 1,928 3,637 515 4,298 17,674 8,603 154 1,157 175 285 3,495 967 789 2,160 341 2,493 7,580 2,706 19 106 8 58 782 82 54 138 25 151 1,082 664 202 2,519 227 670 4,689 1,382 1,506 2,021 310 2,387 9,109 3,939 28 104 25 48 637 47 94 245 59 205 1,071 557 19 670 1 108 1,768 281 364 261 65 185 2,634 1,620 15 132 30 49 1,178 62 87 200 22 262 1,538 924 33 547 30 81 2,864 415 484 553 159 243 4,372 2,469 (continued) Presentation and Analysis of Results 91 Table 2.7 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, PER CAPITA (US$) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Senegal 2,243 1,923 531 21 73 473 88 101 58 73 Seychelles 22,569 13,113 3,040 158 462 3,668 358 1,936 455 235 Sierra Leone 1,369 1,194 228 37 130 158 25 431 21 20 South Africa 12,111 8,280 1,054 347 318 1,295 313 1,235 729 243 Sudanb 3,608 2,309 666 9 154 403 112 74 111 32 Swaziland 6,328 5,822 1,701 41 291 908 434 728 299 77 Tanzania 1,554 1,029 386 5 76 75 32 94 26 1 Togo 1,314 1,193 269 27 63 131 37 151 34 15 Tunisia 10,319 7,290 937 147 307 1,394 298 842 742 361 Uganda 1,597 1,390 283 60 37 273 52 73 44 22 Zambia 3,155 1,778 618 11 110 290 17 190 12 21 Zimbabwe 1,378 1,349 449 50 63 108 21 68 57 2 Total (50) 4,044 2,786 551 68 167 509 106 341 161 65 ASIA AND THE PACIFIC Bangladesh 2,800 2,138 633 53 113 518 50 167 42 31 Bhutan 7,199 3,998 751 55 307 826 43 785 240 142 Brunei Darussalam 74,397 15,683 2,160 32 564 2,374 300 1,288 2,187 544 Cambodia 2,717 2,277 606 82 50 325 30 423 91 5 c China 10,057 4,331 551 59 240 791 127 1,120 191 215 Fiji 7,558 5,397 1,186 148 154 1,063 339 491 285 20 Hong Kong SAR, China 50,129 32,690 2,648 267 1,884 5,752 1,396 2,996 1,570 1,458 India 4,735 3,023 571 57 245 536 65 377 221 40 Indonesia 8,539 4,805 1,102 47 137 1,200 98 242 216 89 Lao PDR 4,108 2,341 576 88 39 565 39 130 108 39 Macao SAR, China 115,441 23,649 1,538 176 1,351 3,831 291 2,230 1,496 1,082 Malaysia 20,926 11,082 1,225 91 165 2,388 286 1,044 940 546 Maldives 11,392 3,883 619 256 104 780 128 599 118 152 Mongolia 8,719 5,501 900 377 202 826 38 797 583 117 Myanmar 3,181 2,273 592 27 68 388 18 402 29 28 Nepal 2,221 1,848 641 42 53 299 24 208 20 25 Pakistan 4,450 3,926 973 32 159 1,214 71 663 127 75 Philippines 5,772 4,490 1,175 58 47 656 133 200 305 85 Singapore 72,296 24,725 1,263 197 805 3,748 964 2,846 2,079 582 Sri Lanka 8,111 6,393 1,489 412 200 1,247 87 797 255 153 Taiwan, China 39,059 25,129 1,854 385 1,209 4,202 673 4,768 1,801 1,572 Thailand 13,299 8,477 1,308 180 303 1,251 199 1,083 690 196 Vietnam 4,717 2,991 438 89 134 654 118 666 121 19 Total (23) 7,621 4,083 674 64 223 783 104 713 223 132 92 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 20 264 12 84 1,691 162 271 432 79 468 2,641 1,365 258 4,315 30 385 10,102 4,702 9,108 5,830 1,251 5,169 27,324 7,830 34 243 11 67 1,053 74 153 419 114 268 1,800 895 280 1,751 118 957 6,772 1,686 1,649 2,386 570 1,888 12,299 5,521 44 232 53 59 2,069 57 462 783 155 787 3,660 1,752 197 819 27 90 5,152 514 557 628 89 668 6,915 4,230 8 123 0 25 917 63 216 497 65 718 1,767 850 9 346 67 170 1,031 125 143 173 23 217 1,507 892 171 2,010 499 482 5,758 2,078 1,451 2,166 226 3,326 10,970 4,595 64 481 30 69 1,156 256 28 331 28 572 1,790 981 10 204 4 119 1,555 170 517 650 79 860 2,967 1,322 22 263 5 85 1,134 216 159 117 19 137 1,650 1,001 62 647 58 221 2,304 541 555 710 134 713 4,037 1,935 11 363 43 58 1,923 85 126 672 58 1,004 2,985 1,595 201 931 47 76 3,127 1,152 1,296 3,629 561 4,325 9,202 2,585 990 5,279 620 764 12,190 4,512 12,332 8,273 1,452 8,057 33,145 10,092 52 707 103 47 1,907 378 150 274 50 288 2,722 1,580 259 864 223 293 3,277 1,426 647 4,265 593 4,643 9,709 2,714 221 897 124 231 4,611 727 622 1,581 361 1,009 7,949 3,801 4,636 1,788 3,238 5,484 30,104 1,906 2,225 11,527 3,101 7,540 47,081 24,815 33 349 51 336 2,672 264 406 1,172 176 1,338 4,960 2,214 88 1,171 315 227 4,110 637 564 2,701 179 4,156 8,389 3,399 41 765 51 50 1,975 311 629 1,246 130 1,296 4,212 1,640 2,497 4,105 4,203 2,256 19,887 4,223 4,007 13,222 1,905 15,545 42,562 16,442 393 2,720 979 1,129 9,105 2,251 1,642 4,284 744 3,656 17,278 7,539 78 1,580 98 116 2,934 1,373 3,369 5,607 1,159 5,488 12,091 2,374 115 2,387 78 205 4,354 1,583 1,038 3,277 868 2,177 10,941 3,597 20 1,405 96 41 1,727 783 266 645 108 630 3,206 1,433 38 371 34 59 1,633 143 148 356 32 373 2,677 1,353 35 551 28 172 3,491 257 404 416 48 415 4,685 2,898 64 952 151 431 4,013 309 338 1,005 157 964 5,952 3,327 3,564 3,994 3,104 3,030 21,444 3,061 4,984 18,936 4,137 16,692 47,087 17,683 77 1,329 153 263 5,185 1,531 977 1,654 199 2,032 9,147 4,299 2,258 4,221 1,466 3,141 22,169 2,482 3,312 7,563 1,883 5,292 36,175 18,317 326 1,854 739 605 6,998 1,658 1,200 3,258 890 2,036 12,997 5,800 106 1,253 122 87 2,446 661 533 1,141 116 1,508 4,906 2,022 161 756 179 324 3,370 811 552 2,515 359 2,781 7,486 2,791 (continued) Presentation and Analysis of Results 93 Table 2.7 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, PER CAPITA (US$) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) COMMONWEALTH OF INDEPENDENT STATES Armenia 6,696 7,304 1,977 379 125 1,972 55 847 198 272 Azerbaijan 15,963 8,366 1,755 216 384 2,169 228 598 435 331 Belarus 16,603 11,576 2,020 792 324 3,170 239 1,878 422 567 Kazakhstan 20,772 11,411 1,560 364 431 3,098 293 1,714 742 433 Kyrgyz Republic 3,062 3,506 621 197 113 1,096 65 339 171 227 Moldova 4,179 5,653 940 441 161 1,381 222 369 265 188 Russian Federationd 22,502 15,175 2,236 1,275 702 3,279 415 1,638 828 652 Tajikistan 2,243 3,025 634 10 101 790 44 336 88 243 Ukraine 8,295 7,907 1,475 528 197 2,468 176 1,236 400 150 Total (9) 17,716 12,286 1,913 928 515 2,899 321 1,441 658 494 EUROSTAT-OECD Albania 9,963 8,116 1,860 254 181 1,182 294 880 181 86 Australia 42,000 27,089 2,164 702 773 4,398 1,110 3,336 2,338 786 Austria 42,978 27,677 2,017 1,091 1,454 5,504 1,363 3,308 2,225 577 Belgium 40,093 26,250 2,552 909 941 4,434 1,069 4,557 1,852 418 Bosnia and Herzegovina 9,629 8,468 1,546 657 151 1,864 312 936 348 160 Bulgaria 15,522 10,970 1,233 566 154 2,595 467 2,124 778 370 Canada 41,069 27,434 1,674 643 949 5,493 1,078 3,720 2,839 561 Chile 20,216 13,703 1,359 363 502 2,148 627 1,663 1,128 392 Croatia 20,308 13,740 1,830 873 377 3,300 545 2,481 771 419 Cyprus 31,229 22,957 2,141 1,057 1,140 5,061 947 2,473 1,813 1,194 Czech Republic 27,045 16,631 1,686 1,262 290 3,585 562 3,124 823 282 Denmark 41,843 26,288 2,021 882 920 4,807 992 4,160 1,648 504 Estonia 23,088 13,795 1,716 1,041 484 2,476 318 2,151 863 427 Finland 38,611 26,582 2,423 1,027 934 4,760 1,024 4,198 1,641 686 France 36,391 26,486 2,593 766 871 4,793 1,048 4,198 2,126 565 Germany 40,990 28,478 2,303 892 1,018 4,836 1,287 4,984 2,066 781 Greece 26,622 21,254 2,660 944 693 4,994 664 3,193 1,587 454 Hungary 22,413 14,664 1,383 989 234 3,186 389 3,073 751 260 Iceland 38,226 25,839 2,484 607 598 5,747 1,057 3,979 1,826 614 Ireland 42,942 23,043 1,666 745 805 4,313 781 3,439 1,811 570 Israel 30,168 20,483 2,153 440 471 4,278 983 2,213 1,943 572 Italy 33,870 23,875 2,504 649 1,394 4,442 1,246 3,421 1,910 516 Japan 34,262 24,447 1,811 696 645 4,770 879 3,546 1,774 758 Korea, Rep. 29,035 17,481 1,059 386 457 3,766 394 3,264 1,272 875 Latvia 19,994 13,734 1,653 784 340 3,282 350 1,898 987 328 Lithuania 22,521 16,537 2,440 991 472 3,022 578 2,951 1,101 377 Luxembourg 88,670 32,000 2,667 4,432 1,735 5,563 2,060 3,633 5,580 802 94 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 118 1,729 49 216 5,704 1,431 903 842 115 835 8,427 4,353 193 2,262 143 348 6,507 1,933 1,514 1,473 622 787 11,028 5,223 409 4,263 167 346 8,160 5,498 1,167 2,955 930 2,193 16,696 6,535 419 4,131 265 935 8,518 3,827 1,764 2,542 567 2,094 16,588 7,292 86 1,495 62 155 2,586 1,243 448 287 96 196 3,810 2,042 123 1,978 60 486 4,097 2,250 382 467 125 340 5,951 3,208 558 2,630 239 1,213 11,429 4,908 2,465 2,906 863 1,978 20,907 9,369 52 913 18 137 2,215 1,075 280 287 106 155 3,340 1,786 202 2,414 83 396 5,785 3,008 801 769 232 574 8,859 4,530 424 2,642 190 895 9,199 4,107 1,856 2,228 657 1,552 16,518 7,503 144 3,346 194 429 6,251 2,039 909 2,583 267 3,279 11,687 5,297 2,831 3,140 1,628 4,079 22,288 5,529 3,430 10,026 2,854 5,669 41,042 18,885 2,375 2,467 2,616 3,364 23,049 5,708 3,107 9,553 3,401 5,367 41,311 18,943 1,902 3,080 1,083 3,546 20,173 7,796 3,098 9,814 3,020 6,338 39,504 16,906 325 1,898 395 686 6,667 2,084 1,463 1,543 323 1,517 11,417 5,386 689 2,083 581 610 8,358 3,328 2,202 2,512 627 2,180 15,631 6,406 2,079 2,740 1,257 3,794 22,127 6,232 3,956 9,984 2,068 7,234 41,537 17,680 702 3,597 470 1,773 11,002 3,080 1,255 4,223 1,121 3,131 19,614 9,333 1,144 2,312 1,442 1,157 10,616 3,894 2,507 3,918 790 3,487 20,333 8,459 1,551 2,564 2,711 1,913 19,999 3,251 3,763 5,749 1,188 5,144 32,532 16,149 1,345 2,592 1,168 1,379 12,372 5,608 3,497 5,887 1,913 3,972 26,012 9,951 2,182 3,264 819 4,579 18,379 10,605 3,350 8,937 2,831 4,855 38,734 14,682 828 2,788 741 1,237 10,051 5,065 2,849 5,142 1,603 3,748 22,337 8,245 2,249 3,229 1,071 3,880 19,917 8,771 3,343 8,274 1,760 6,541 38,695 16,526 1,954 2,898 1,372 3,555 20,167 8,202 3,002 7,562 1,959 5,198 37,427 16,732 1,912 2,596 1,157 4,267 22,398 7,605 2,779 7,066 2,664 4,189 38,487 18,557 946 2,388 1,962 1,878 18,156 3,050 3,368 3,890 1,162 2,695 28,780 14,903 930 2,602 817 1,832 10,710 5,358 3,106 3,429 990 2,527 21,269 8,477 1,981 3,733 1,340 2,611 19,066 8,931 3,940 4,640 1,684 2,722 34,386 14,539 1,302 3,223 1,918 2,416 17,949 6,513 2,504 6,147 1,638 4,455 32,443 14,691 1,089 3,709 889 2,395 15,963 5,541 3,879 6,038 1,302 3,847 30,243 12,640 1,386 2,361 1,751 2,338 19,311 5,533 2,703 7,449 2,323 4,552 34,232 15,985 1,770 2,096 1,281 4,353 19,188 6,412 3,288 6,878 2,586 3,384 34,518 15,091 1,064 2,878 814 2,524 14,436 3,282 2,715 7,628 2,050 5,581 28,494 11,596 894 2,612 417 855 10,700 3,634 2,965 3,701 1,069 2,890 20,868 8,499 835 2,907 337 1,343 12,416 5,357 2,665 3,379 763 2,831 23,111 10,322 2,780 2,571 2,215 5,851 25,804 8,213 5,042 20,440 6,512 13,753 58,182 22,004 (continued) Presentation and Analysis of Results 95 Table 2.7 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, PER CAPITA (US$) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Macedonia, FYR 11,957 9,482 1,905 343 232 2,120 211 1,202 382 303 Malta 28,608 19,701 2,173 509 566 3,079 921 3,394 1,406 633 Mexico 16,377 11,844 2,014 279 297 1,675 482 907 1,325 304 Montenegro 14,128 12,315 2,606 666 198 2,313 816 1,368 755 501 Netherlands 43,150 25,983 2,361 708 969 4,205 1,079 3,662 1,688 763 New Zealand 31,172 22,502 2,204 734 886 3,744 849 3,809 1,790 506 Norway 61,879 31,014 2,383 650 1,144 5,270 1,343 4,457 2,387 1,018 Poland 21,753 16,307 2,159 750 317 4,207 465 2,741 752 348 Portugal 25,672 18,584 2,477 632 703 2,719 760 2,670 1,388 399 Romania 16,146 11,184 1,781 373 197 2,023 320 2,721 538 385 Russian Federationd 22,502 15,175 2,236 1,275 702 3,246 415 1,629 828 652 Serbia 11,854 10,107 1,506 565 151 2,560 196 1,750 566 380 Slovak Republic 25,130 16,880 1,852 629 393 4,426 609 3,017 685 304 Slovenia 28,156 18,880 2,026 1,093 729 3,553 819 2,953 1,722 546 Spain 32,156 21,484 2,497 696 997 3,544 771 2,933 1,505 356 Sweden 41,761 26,781 2,338 744 885 5,271 927 3,800 1,871 1,120 Switzerland 51,582 29,465 2,364 1,443 1,030 4,740 1,281 4,266 2,308 948 Turkey 17,781 13,732 1,893 305 568 3,264 753 1,549 1,101 276 United Kingdom 35,091 26,146 2,006 599 1,525 4,122 970 3,745 2,057 545 United States 49,782 37,390 2,238 665 1,173 6,290 1,376 7,371 3,458 790 Total (47) 33,675 23,930 2,101 699 835 4,340 909 3,853 1,939 606 LATIN AMERICA Bolivia 5,557 3,661 786 46 52 851 172 319 481 22 Brazil 14,639 9,906 1,279 225 191 1,367 511 1,866 821 162 Colombia 11,360 7,836 924 210 295 2,002 172 773 540 186 Costa Rica 13,030 10,244 1,363 90 290 1,184 409 1,046 1,374 317 e Cuba … … … … … … … … … … Dominican Republic 10,858 9,722 1,626 423 222 1,918 212 787 708 361 Ecuador 9,932 6,759 901 155 167 1,435 280 740 675 252 El Salvador 7,357 7,285 1,170 108 215 2,053 407 703 549 238 Guatemala 6,971 6,222 1,509 67 217 1,149 299 484 319 302 Haiti 1,557 1,688 626 47 53 324 49 74 71 5 Honduras 4,349 3,748 770 118 87 734 102 399 249 66 Nicaragua 4,111 3,587 538 79 72 1,045 141 464 263 66 Panama 15,369 10,618 1,166 54 385 3,267 510 871 1,033 467 Paraguay 7,193 5,591 1,016 73 131 945 312 530 303 216 Peru 10,981 7,148 1,115 146 267 1,066 204 659 542 191 Uruguay 17,343 12,899 1,670 258 314 3,328 460 1,951 689 557 Venezuela, RB 16,965 10,263 1,027 169 145 1,513 210 1,212 1,633 555 Total (17) 12,443 8,561 1,156 189 199 1,419 361 1,283 747 209 96 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 225 2,310 290 627 7,313 2,590 2,036 1,853 316 1,973 13,704 5,802 1,775 2,553 2,786 2,555 15,455 5,145 3,821 4,209 990 3,163 27,562 12,740 390 3,511 380 1,146 9,322 2,817 1,408 2,953 572 2,850 16,550 8,016 335 2,614 1,291 825 9,565 3,332 2,709 1,939 364 1,955 16,618 7,932 2,060 3,120 891 4,844 18,732 9,570 4,705 7,981 2,146 5,249 38,743 15,727 1,866 3,581 1,316 2,310 17,425 6,302 2,921 4,985 1,581 2,907 30,559 14,085 2,819 3,153 1,008 4,331 23,322 10,055 4,315 12,598 4,009 6,322 50,535 18,971 1,023 2,666 254 1,925 12,519 4,754 2,134 3,317 917 2,497 22,034 10,476 1,081 2,861 1,793 2,043 15,112 4,090 2,721 5,261 952 4,857 26,725 12,905 609 2,380 295 745 8,274 3,841 1,779 3,754 632 3,986 16,894 6,964 547 2,616 239 1,253 11,429 4,908 2,465 2,906 863 1,978 20,907 9,380 385 2,121 159 863 7,498 3,556 1,309 1,795 411 1,601 13,402 5,930 1,222 2,675 602 1,650 12,981 4,840 3,478 4,670 1,087 2,968 25,026 10,637 1,326 2,393 949 1,843 14,856 4,961 3,018 5,326 1,772 3,375 27,684 12,489 1,552 2,547 2,906 2,107 17,101 5,388 3,271 7,541 1,616 5,098 32,404 14,499 2,265 2,901 854 4,384 19,424 9,693 3,446 7,698 3,034 3,623 38,610 15,209 2,460 2,544 1,710 4,618 26,418 3,212 2,353 11,927 5,030 5,316 44,050 22,744 437 3,776 574 889 10,729 3,524 1,510 3,431 1,195 2,316 19,084 8,177 2,780 2,751 1,612 3,293 20,912 6,515 3,222 5,603 1,070 3,689 35,499 17,624 3,192 2,983 2,150 5,779 34,329 3,061 5,034 9,064 3,252 4,150 51,605 29,180 1,730 2,835 1,261 3,244 19,850 4,882 3,174 6,403 1,993 3,825 33,756 16,505 23 444 218 110 3,436 100 641 857 239 530 5,187 2,856 330 1,948 446 1,239 7,833 2,541 1,647 3,178 770 2,382 14,765 6,614 320 1,445 592 849 6,765 987 1,319 2,230 427 2,170 11,385 5,383 791 1,898 385 578 8,586 1,572 905 2,258 482 2,068 13,662 7,417 … … … … … … … … … … … … 162 1,468 768 1,134 8,810 510 799 1,353 191 1,624 11,771 7,301 251 1,474 195 591 5,832 858 721 2,225 303 1,250 10,089 4,793 264 1,004 268 407 6,503 582 510 732 186 600 8,535 5,179 150 703 320 302 5,565 488 472 865 222 708 7,536 4,474 34 169 2 41 1,612 22 1 407 4 730 2,105 1,346 119 730 177 271 3,321 358 329 934 257 618 5,102 2,747 85 873 156 290 3,113 428 463 576 113 519 4,564 2,369 447 1,547 382 952 9,154 1,358 1,283 3,000 724 2,613 15,183 7,018 227 1,313 199 496 4,862 655 338 985 183 911 6,934 4,164 341 1,409 445 753 6,332 638 815 2,219 393 2,326 10,412 5,297 323 1,737 758 1,099 10,962 1,886 1,182 3,201 577 3,095 17,408 8,424 328 2,802 753 401 8,710 1,619 1,440 2,868 501 3,084 15,234 7,388 296 1,681 448 903 7,073 1,664 1,264 2,504 551 2,081 12,432 5,893 (continued) Presentation and Analysis of Results 97 Table 2.7 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, PER CAPITA (US$) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) CARIBBEAN Anguilla 27,274 21,119 1,560 458 587 5,268 607 743 3,319 1,662 Antigua and Barbuda 20,540 12,549 1,108 192 242 4,634 345 2,084 704 522 Aruba 36,017 24,000 1,284 100 659 10,061 541 5,212 2,094 737 Bahamas, The 22,639 15,565 1,150 197 419 5,731 378 1,854 960 556 Barbados 15,354 12,326 1,422 166 268 7,405 277 934 780 489 Belize 8,212 6,492 672 46 370 3,233 267 628 414 183 Bermuda 54,899 37,924 3,168 1,034 898 7,160 1,507 4,468 2,756 1,624 Bonairef … … 920 71 790 … 504 … 1,531 486 Cayman Islands 49,686 34,020 1,628 330 1,006 12,748 1,046 1,784 2,793 1,482 Curaçao 27,781 20,690 1,553 211 1,008 9,120 376 2,435 1,400 546 Dominica 9,983 8,664 885 53 524 2,709 226 856 1,119 327 Grenada 11,221 10,211 1,150 143 308 2,926 231 642 1,160 912 Jamaica 8,329 7,241 1,145 67 126 1,442 273 634 655 246 Montserrat 15,762 13,609 1,159 217 146 4,243 280 1,922 2,163 1,051 St. Kitts and Nevis 20,582 14,444 1,213 322 564 5,770 368 1,702 713 495 St. Lucia 9,893 7,520 964 97 386 2,783 170 612 481 333 St. Vincent and the Grenadines 9,883 8,356 973 402 154 3,086 193 935 1,053 410 Sint Maarten 32,972 19,298 1,171 86 1,036 9,144 550 1,176 1,816 642 Suriname 14,463 5,913 1,138 114 191 1,978 147 522 226 170 Trinidad and Tobago 28,743 15,691 2,066 103 170 2,555 347 1,831 1,187 325 Turks and Caicos Islands 20,878 7,593 902 125 357 716 240 1,082 1,365 206 Virgin Islands, British 30,290 10,753 1,367 380 1,074 2,119 895 898 1,012 395 Total (22) 16,351 10,867 1,343 117 247 2,962 309 1,142 848 346 WESTERN ASIA Bahrain 43,360 18,626 1,780 64 853 4,366 912 1,342 2,422 1,022 Egypt, Arab Rep.a 10,599 8,529 1,670 159 402 2,514 210 1,505 352 183 Iraq 11,130 5,381 882 19 196 2,201 152 633 294 82 Jordan 11,169 8,868 1,288 227 380 3,078 256 1,066 603 296 Kuwait 84,058 21,888 2,637 48 1,324 7,878 1,798 1,613 2,070 556 Oman 42,619 15,182 1,866 34 751 3,273 449 1,217 2,518 602 Qatar 146,521 20,552 1,927 73 689 4,830 675 1,552 2,497 479 Saudi Arabia 48,163 17,797 1,726 54 748 6,238 845 1,707 1,256 606 b Sudan 3,608 2,309 666 9 154 403 112 74 111 32 United Arab Emirates 60,886 29,463 2,735 56 3,600 10,245 1,084 442 5,073 2,119 West Bank and Gaza 3,833 4,070 849 71 248 447 169 596 222 116 Yemen, Rep. 3,716 2,762 558 139 129 759 48 504 120 23 Total (12) 17,499 8,574 1,303 90 473 2,719 307 979 635 263 98 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 571 2,721 601 3,116 18,416 1,672 5,101 6,306 830 7,185 31,600 15,282 268 2,475 357 1,453 9,708 3,976 3,663 4,708 451 5,934 20,385 6,716 1,181 3,375 316 2,001 17,040 10,539 5,540 12,498 1,786 13,584 41,264 10,759 606 1,943 761 2,185 13,249 2,077 3,887 7,109 2,086 5,056 26,314 9,477 426 1,339 1,648 1,053 10,453 1,733 3,034 3,187 917 2,357 18,143 5,247 259 838 28 262 5,718 517 1,315 774 224 548 8,401 3,265 2,146 6,872 3,753 5,405 30,343 8,804 6,184 17,994 7,875 8,146 62,109 24,960 … … 800 … 12,119 … … … … … … 9,142 1,395 4,253 1,545 5,755 29,497 3,474 5,921 13,439 4,262 9,036 52,931 20,953 662 1,830 418 4,140 17,354 3,282 3,257 9,733 3,383 3,658 34,418 11,601 237 1,446 192 575 7,347 1,193 1,784 2,102 590 1,531 11,351 5,346 176 2,437 133 736 8,603 1,503 1,542 2,036 462 1,767 13,786 6,419 455 1,530 632 774 6,094 1,091 1,026 1,588 399 1,269 9,951 4,743 311 2,518 37 1,344 10,589 3,858 7,609 5,059 723 5,621 24,308 7,745 336 4,240 687 1,249 11,441 3,896 5,015 5,225 780 5,544 23,565 7,556 100 1,920 65 776 6,299 1,180 1,537 2,757 462 2,769 11,720 4,525 363 1,560 140 637 6,727 1,917 1,563 2,258 330 2,504 12,255 4,818 692 1,608 225 2,017 16,375 2,553 6,819 6,307 2,344 2,165 31,031 10,118 163 154 59 697 5,239 285 2,513 4,487 1,961 1,277 13,430 4,484 862 5,137 965 2,282 11,225 6,791 917 4,703 1,290 3,450 22,097 9,973 362 1,652 223 888 6,421 1,058 6,320 2,830 888 1,947 14,711 6,058 371 1,075 438 604 9,147 1,394 2,395 6,768 2,561 3,701 19,018 8,055 530 2,290 657 1,335 8,719 2,600 1,771 3,575 1,033 2,497 16,359 6,706 1,165 3,402 762 1,201 16,419 2,300 3,584 7,584 1,097 8,791 29,822 14,704 205 1,789 179 612 7,218 1,206 1,568 1,070 201 1,051 10,892 5,633 45 1,782 34 108 3,989 1,841 2,728 1,608 381 1,383 9,275 2,724 114 2,585 115 229 7,328 1,724 1,844 1,882 259 1,991 12,671 5,371 608 2,881 390 1,013 18,653 3,507 6,971 14,911 3,129 11,158 43,562 14,587 428 3,069 314 1,171 12,252 3,319 5,100 12,529 2,217 11,495 30,713 10,485 1,344 3,906 313 2,785 17,140 4,163 8,707 59,793 14,413 17,614 75,947 13,981 435 4,605 527 818 13,457 5,064 4,556 13,029 2,359 11,349 36,443 10,405 44 232 53 59 2,069 57 462 783 155 787 3,660 1,752 675 2,000 818 1,254 29,459 522 2,656 18,824 4,134 14,341 48,431 22,000 86 964 63 298 3,209 973 1,072 706 75 747 5,678 2,851 9 535 1 112 2,337 418 607 360 18 400 3,826 1,900 195 1,791 187 455 7,148 1,548 2,017 3,916 774 3,153 14,288 5,533 (continued) Presentation and Analysis of Results 99 Table 2.7 (Continued) REAL EXPENDITURES Alcoholic Housing, Furnishings, PER CAPITA (US$) beverages, water, household Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) SINGLETONS Georgia 6,343 6,054 963 306 76 2,043 128 1,115 289 198 Iran, Islamic Rep. 17,488 8,576 1,102 53 191 2,951 175 1,513 419 409 Total (2) 16,863 8,435 1,094 67 184 2,900 172 1,491 412 397 WORLDg (179) 13,460 8,647 1,018 214 352 1,643 300 1,385 632 238 Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; ... = data suppressed because of incompleteness. a. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. b. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. c. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. d. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. e. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. f. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. g. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 100 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 322 1,884 116 374 4,789 973 1,402 742 256 433 7,675 3,624 169 2,417 58 680 6,804 1,834 2,776 2,928 635 3,116 15,556 5,059 177 2,387 61 662 6,691 1,786 2,699 2,805 614 2,965 15,114 4,979 494 1,317 408 979 7,144 1,766 1,230 3,139 708 2,672 13,258 5,918 Presentation and Analysis of Results 101 Table 2.8 Indexes of Real Expenditures Per Capita (World = 100), ICP 2011 Alcoholic Housing, Furnishings, INDEX OF REAL beverages, water, household EXPENDITURES PER Gross Actual Food and tobacco, Clothing electricity, equipment CAPITA (world = 100) domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) AFRICA Algeria 98.0 72.5 105.3 32.1 35.8 22.3 36.6 71.1 104.0 119.7 Angola 54.1 50.0 103.2 134.6 51.7 35.3 52.8 23.5 30.1 14.9 Benin 13.1 17.0 39.0 21.1 18.0 10.3 9.0 6.2 13.4 15.8 Botswana 99.6 78.4 74.4 177.3 133.4 41.9 80.8 45.2 140.6 87.3 Burkina Faso 10.0 11.0 25.4 27.3 6.2 8.7 9.5 4.4 6.2 10.7 Burundi 5.3 7.5 14.9 24.8 1.9 10.8 1.2 3.3 2.9 1.7 Cameroon 20.5 26.6 63.0 25.4 42.5 17.9 40.3 3.4 19.2 8.4 Cape Verde 45.5 54.9 98.0 91.7 29.5 59.9 87.1 32.1 32.6 81.3 Central African Republic 6.7 10.1 24.4 33.4 19.6 5.0 9.1 1.9 3.3 1.9 Chad 14.7 17.1 39.7 27.1 9.8 9.5 20.7 14.1 14.6 14.9 Comoros 4.5 7.2 17.7 0.5 4.9 15.8 4.0 0.7 1.3 0.9 Congo, Rep. 43.3 17.5 27.6 29.9 10.6 20.6 12.1 16.4 12.3 21.8 Congo, Dem. Rep. 4.9 5.2 11.9 4.8 5.8 5.8 4.0 2.9 1.2 1.6 Côte d’Ivoire 19.8 22.9 47.2 26.8 16.1 16.5 39.8 12.3 22.1 15.3 Djibouti 17.9 19.9 31.4 58.1 13.7 40.7 23.6 5.8 11.4 2.4 a Egypt, Arab Rep. 78.7 98.6 164.1 74.1 114.4 153.0 70.0 108.7 55.7 76.7 Equatorial Guinea 293.0 56.9 94.5 68.6 43.0 58.5 36.9 61.2 45.0 76.5 Ethiopia 9.0 11.3 19.9 8.9 12.1 10.5 19.6 12.0 1.6 1.5 Gabon 122.5 69.1 90.0 235.6 82.2 64.0 72.4 49.4 72.4 76.0 Gambia, The 11.2 14.1 25.4 14.9 36.6 6.4 7.6 29.7 3.7 16.0 Ghana 25.5 25.9 37.3 12.3 94.7 21.2 37.6 13.9 21.8 14.3 Guinea 9.6 9.1 19.4 4.9 16.8 11.3 7.5 8.1 4.5 0.4 Guinea-Bissau 10.1 10.7 25.8 6.4 18.2 9.8 13.3 3.6 6.5 1.6 Kenya 15.9 22.4 37.7 32.1 15.2 14.0 20.9 19.6 16.0 31.0 Lesotho 15.8 29.2 39.2 24.3 88.3 22.3 45.4 14.2 8.7 25.3 Liberia 4.0 7.0 8.5 8.0 25.6 7.4 9.4 1.9 1.7 7.3 Madagascar 10.5 15.4 31.7 15.7 30.1 5.3 43.7 3.7 13.8 2.8 Malawi 7.2 11.6 25.2 20.4 8.8 14.9 21.3 7.0 5.3 6.0 Mali 11.2 12.1 28.6 7.0 16.4 6.8 13.0 6.5 11.8 7.5 Mauritania 23.7 24.2 68.4 8.1 24.2 15.7 13.8 11.0 9.9 24.7 Mauritius 115.2 136.6 208.9 288.1 228.0 158.1 215.2 82.9 127.3 174.7 Morocco 50.2 49.8 82.6 31.2 44.7 68.1 46.3 25.2 41.6 80.4 Mozambique 7.1 10.3 25.5 17.1 12.8 6.4 4.9 2.8 7.9 3.6 Namibia 62.1 67.4 67.8 108.2 102.9 62.2 123.7 72.5 27.7 23.3 Niger 6.3 8.3 15.3 6.3 21.4 5.4 10.2 3.5 5.7 4.1 Nigeria 23.4 24.0 38.0 14.3 98.1 16.0 46.2 10.9 17.1 11.2 Rwanda 9.9 15.0 36.1 14.8 10.1 19.4 11.9 4.8 6.3 5.5 São Tomé and Príncipe 22.6 38.6 95.5 62.7 34.5 23.4 24.4 21.7 34.3 14.8 102 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 31.0 180.9 29.5 110.0 55.7 244.2 179.0 97.3 82.5 109.4 89.7 64.0 12.4 41.5 17.1 51.9 47.9 63.6 188.5 47.6 29.2 67.4 58.5 51.4 3.3 14.8 23.5 6.3 18.0 7.8 15.5 8.3 6.4 10.8 14.5 18.5 30.8 185.7 41.6 60.9 75.5 102.0 150.2 160.9 115.6 226.4 107.9 81.0 3.0 7.8 6.8 3.0 11.8 3.9 19.9 5.3 4.3 5.9 10.7 12.0 0.9 12.2 4.6 1.7 7.5 7.1 11.8 2.6 2.3 2.9 6.4 6.6 4.9 10.4 25.3 6.2 28.9 5.9 24.3 13.1 14.7 12.0 22.4 29.7 7.0 73.5 129.7 33.1 54.7 53.5 62.2 75.6 66.5 84.1 61.3 53.5 2.2 8.8 3.1 3.6 10.8 3.0 3.8 3.4 2.2 3.6 7.6 11.5 6.0 6.3 1.7 4.0 18.4 4.3 9.0 12.8 12.5 11.0 15.4 18.9 0.8 4.0 0.0 1.8 7.9 0.5 14.6 2.3 2.2 2.3 6.5 6.3 6.1 23.6 21.7 6.4 17.7 14.5 26.4 47.5 20.7 75.7 26.7 18.0 1.0 6.0 4.0 1.1 5.5 1.8 7.4 3.8 3.3 4.4 4.9 5.4 8.8 14.5 5.8 10.7 24.4 9.3 19.3 7.7 5.4 10.3 17.0 25.0 2.7 21.6 2.7 3.9 20.7 11.7 46.0 20.0 12.6 30.1 22.4 18.4 41.6 135.9 43.8 62.5 101.0 68.3 127.4 34.1 28.4 39.3 82.2 95.2 11.9 59.8 31.7 29.0 60.8 27.3 40.4 443.1 426.2 336.8 141.1 62.4 0.8 12.1 11.4 13.2 12.1 3.7 8.6 6.8 3.7 9.4 10.0 12.8 26.6 52.4 50.2 22.4 71.4 46.6 149.3 93.0 64.1 46.0 80.0 72.7 6.7 23.6 1.8 6.7 14.7 8.0 13.6 8.3 8.9 7.1 12.4 15.7 3.7 77.2 0.1 10.7 26.2 22.6 38.5 26.9 22.4 31.3 27.2 28.1 1.0 9.0 1.6 2.1 9.8 1.8 8.3 6.3 7.9 4.5 8.4 9.4 5.2 8.1 0.7 1.7 11.3 4.1 30.4 4.3 3.7 5.0 10.3 12.1 10.1 43.0 22.6 16.7 21.9 24.7 14.5 10.4 10.6 10.8 18.2 22.0 15.6 36.1 5.0 17.7 29.4 26.1 37.6 15.8 8.1 24.1 26.1 29.0 1.9 21.8 0.8 5.3 7.7 0.3 6.8 2.0 3.2 0.6 5.9 7.7 10.0 12.5 12.9 2.6 16.6 4.1 8.9 5.0 3.9 6.2 11.7 18.3 2.9 9.0 3.5 2.8 12.4 5.1 4.6 4.2 6.0 1.8 8.7 11.9 6.7 10.4 2.8 3.2 12.7 6.4 19.6 8.0 7.0 8.9 11.5 13.2 3.2 33.1 2.0 4.1 23.8 26.5 52.3 39.3 37.3 37.0 25.3 24.3 137.4 186.2 54.6 77.8 139.0 114.1 156.8 115.9 72.7 160.8 133.3 145.4 31.1 87.9 42.9 29.1 48.9 54.8 64.1 68.8 48.1 93.3 57.2 45.7 3.9 8.0 1.9 6.0 10.9 4.6 4.4 4.4 3.5 5.7 8.2 11.2 40.8 191.2 55.7 68.4 65.6 78.3 122.4 64.4 43.7 89.4 68.7 66.6 5.7 7.9 6.3 4.9 8.9 2.7 7.6 7.8 8.3 7.7 8.1 9.4 3.8 50.9 0.2 11.0 24.7 15.9 29.6 8.3 9.1 6.9 19.9 27.4 3.0 10.1 7.4 5.0 16.5 3.5 7.1 6.4 3.1 9.8 11.6 15.6 6.7 41.5 7.5 8.3 40.1 23.5 39.4 17.6 22.4 9.1 33.0 41.7 (continued) Presentation and Analysis of Results 103 Table 2.8 (Continued) Alcoholic Housing, Furnishings, INDEX OF REAL beverages, water, household EXPENDITURES PER Gross Actual Food and tobacco, Clothing electricity, equipment CAPITA (world = 100) domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Senegal 16.7 22.2 52.2 10.0 20.8 28.8 29.2 7.3 9.2 30.5 Seychelles 167.7 151.6 298.7 73.7 131.4 223.3 119.1 139.8 72.0 98.8 Sierra Leone 10.2 13.8 22.4 17.4 36.9 9.6 8.3 31.1 3.3 8.4 South Africa 90.0 95.8 103.6 162.5 90.4 78.8 104.1 89.2 115.3 102.0 Sudanb 26.8 26.7 65.5 4.3 43.7 24.5 37.4 5.3 17.6 13.3 Swaziland 47.0 67.3 167.1 19.3 82.8 55.2 144.3 52.6 47.3 32.3 Tanzania 11.5 11.9 37.9 2.3 21.7 4.6 10.8 6.8 4.1 0.3 Togo 9.8 13.8 26.5 12.5 17.9 8.0 12.3 10.9 5.4 6.2 Tunisia 76.7 84.3 92.1 68.8 87.2 84.8 99.3 60.8 117.4 151.3 Uganda 11.9 16.1 27.8 28.2 10.5 16.6 17.3 5.3 7.0 9.2 Zambia 23.4 20.6 60.8 4.9 31.3 17.6 5.7 13.7 1.9 8.9 Zimbabwe 10.2 15.6 44.1 23.5 18.0 6.6 6.8 4.9 9.0 0.6 Total (50) 30.0 32.2 54.1 31.7 47.6 31.0 35.2 24.6 25.5 27.3 ASIA AND THE PACIFIC Bangladesh 20.8 24.7 62.2 24.8 32.0 31.5 16.8 12.1 6.6 13.1 Bhutan 53.5 46.2 73.8 25.9 87.2 50.3 14.3 56.7 37.9 59.8 Brunei Darussalam 552.7 181.4 212.3 14.9 160.3 144.5 99.8 93.0 345.8 228.2 Cambodia 20.2 26.3 59.5 38.3 14.1 19.8 9.9 30.5 14.3 2.3 c China 74.7 50.1 54.2 27.4 68.3 48.1 42.2 80.9 30.3 90.1 Fiji 56.1 62.4 116.5 69.0 43.8 64.7 112.8 35.5 45.1 8.2 Hong Kong SAR, China 372.4 378.1 260.2 125.1 535.9 350.1 464.7 216.4 248.2 611.9 India 35.2 35.0 56.1 26.7 69.7 32.6 21.5 27.2 35.0 17.0 Indonesia 63.4 55.6 108.2 21.8 38.8 73.0 32.7 17.5 34.2 37.4 Lao PDR 30.5 27.1 56.6 41.0 11.2 34.4 12.8 9.4 17.1 16.5 Macao SAR, China 857.6 273.5 151.1 82.4 384.1 233.2 97.0 161.0 236.6 454.0 Malaysia 155.5 128.2 120.4 42.3 47.1 145.3 95.3 75.4 148.7 229.3 Maldives 84.6 44.9 60.9 119.8 29.6 47.5 42.7 43.3 18.6 63.7 Mongolia 64.8 63.6 88.4 176.4 57.6 50.3 12.7 57.5 92.2 49.2 Myanmar 23.6 26.3 58.1 12.7 19.4 23.6 6.1 29.0 4.6 11.9 Nepal 16.5 21.4 63.0 19.6 15.2 18.2 8.0 15.0 3.2 10.5 Pakistan 33.1 45.4 95.6 14.9 45.3 73.9 23.5 47.9 20.1 31.5 Philippines 42.9 51.9 115.5 27.0 13.4 39.9 44.3 14.5 48.2 35.8 Singapore 537.1 285.9 124.1 92.3 229.0 228.1 321.0 205.5 328.8 244.2 Sri Lanka 60.3 73.9 146.3 192.4 56.8 75.9 28.9 57.6 40.4 64.2 Taiwan, China 290.2 290.6 182.2 180.1 343.9 255.7 224.0 344.3 284.8 659.6 Thailand 98.8 98.0 128.6 84.1 86.3 76.2 66.1 78.2 109.2 82.1 Vietnam 35.0 34.6 43.0 41.6 38.2 39.8 39.2 48.1 19.2 7.9 Total (23) 56.6 47.2 66.3 29.7 63.5 47.7 34.7 51.5 35.3 55.5 104 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 4.1 20.1 2.9 8.6 23.7 9.2 22.0 13.8 11.1 17.5 19.9 23.1 52.2 327.6 7.3 39.4 141.4 266.3 740.4 185.7 176.5 193.5 206.1 132.3 7.0 18.4 2.7 6.8 14.7 4.2 12.4 13.3 16.2 10.0 13.6 15.1 56.6 132.9 28.9 97.7 94.8 95.5 134.0 76.0 80.5 70.7 92.8 93.3 8.8 17.6 12.9 6.1 29.0 3.2 37.6 24.9 21.9 29.5 27.6 29.6 39.9 62.2 6.7 9.2 72.1 29.1 45.3 20.0 12.6 25.0 52.2 71.5 1.7 9.3 0.0 2.5 12.8 3.6 17.6 15.8 9.1 26.9 13.3 14.4 1.8 26.2 16.3 17.4 14.4 7.1 11.6 5.5 3.2 8.1 11.4 15.1 34.7 152.6 122.4 49.3 80.6 117.7 118.0 69.0 31.9 124.5 82.7 77.6 13.0 36.5 7.5 7.0 16.2 14.5 2.3 10.6 3.9 21.4 13.5 16.6 1.9 15.5 1.0 12.2 21.8 9.6 42.0 20.7 11.1 32.2 22.4 22.3 4.5 20.0 1.3 8.7 15.9 12.2 12.9 3.7 2.7 5.1 12.4 16.9 12.6 49.1 14.2 22.6 32.3 30.7 45.1 22.6 18.9 26.7 30.5 32.7 2.2 27.5 10.6 6.0 26.9 4.8 10.2 21.4 8.2 37.6 22.5 26.9 40.8 70.7 11.6 7.8 43.8 65.3 105.3 115.6 79.3 161.9 69.4 43.7 200.3 400.8 151.9 78.0 170.6 255.5 1002.5 263.6 205.0 301.5 250.0 170.5 10.4 53.7 25.2 4.8 26.7 21.4 12.2 8.7 7.0 10.8 20.5 26.7 52.3 65.6 54.7 30.0 45.9 80.8 52.6 135.9 83.7 173.8 73.2 45.9 44.8 68.1 30.5 23.6 64.5 41.2 50.5 50.4 51.0 37.8 60.0 64.2 938.2 135.8 793.7 560.1 421.4 108.0 180.8 367.3 437.8 282.2 355.1 419.3 6.7 26.5 12.5 34.3 37.4 14.9 33.0 37.3 24.8 50.1 37.4 37.4 17.7 88.9 77.3 23.1 57.5 36.1 45.8 86.0 25.2 155.5 63.3 57.4 8.2 58.1 12.6 5.1 27.6 17.6 51.1 39.7 18.4 48.5 31.8 27.7 505.2 311.7 1030.1 230.4 278.4 239.1 325.8 421.2 268.9 581.8 321.0 277.8 79.6 206.5 240.0 115.3 127.4 127.5 133.5 136.5 105.1 136.8 130.3 127.4 15.8 119.9 24.1 11.9 41.1 77.8 273.8 178.6 163.6 205.4 91.2 40.1 23.3 181.2 19.2 20.9 60.9 89.7 84.4 104.4 122.5 81.5 82.5 60.8 4.0 106.7 23.5 4.2 24.2 44.3 21.6 20.5 15.3 23.6 24.2 24.2 7.7 28.2 8.4 6.0 22.9 8.1 12.0 11.3 4.5 13.9 20.2 22.9 7.0 41.9 6.9 17.6 48.9 14.6 32.9 13.3 6.8 15.5 35.3 49.0 13.0 72.3 37.1 44.1 56.2 17.5 27.5 32.0 22.1 36.1 44.9 56.2 721.3 303.2 760.7 309.5 300.2 173.3 405.2 603.3 584.0 624.7 355.2 298.8 15.6 100.9 37.4 26.8 72.6 86.7 79.4 52.7 28.1 76.1 69.0 72.6 457.0 320.4 359.4 320.8 310.3 140.5 269.2 241.0 265.8 198.1 272.9 309.5 66.0 140.8 181.2 61.8 98.0 93.9 97.5 103.8 125.7 76.2 98.0 98.0 21.5 95.1 29.8 8.9 34.2 37.4 43.4 36.3 16.4 56.4 37.0 34.2 32.6 57.4 43.9 33.1 47.2 45.9 44.9 80.1 50.6 104.1 56.5 47.2 (continued) Presentation and Analysis of Results 105 Table 2.8 (Continued) Alcoholic Housing, Furnishings, INDEX OF REAL beverages, water, household EXPENDITURES PER Gross Actual Food and tobacco, Clothing electricity, equipment CAPITA (world = 100) domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) COMMONWEALTH OF INDEPENDENT STATES Armenia 49.7 84.5 194.3 177.2 35.7 120.0 18.3 61.1 31.3 114.1 Azerbaijan 118.6 96.8 172.4 101.2 109.2 132.0 75.9 43.2 68.8 139.0 Belarus 123.3 133.9 198.4 370.6 92.3 192.9 79.5 135.6 66.7 238.1 Kazakhstan 154.3 132.0 153.3 170.3 122.7 188.6 97.6 123.8 117.3 181.6 Kyrgyz Republic 22.7 40.5 61.0 92.0 32.1 66.7 21.5 24.5 27.0 95.2 Moldova 31.0 65.4 92.4 206.3 45.7 84.1 74.0 26.6 41.9 78.8 Russian Federationd 167.2 175.5 219.7 596.0 199.7 199.6 138.0 118.3 130.9 273.4 Tajikistan 16.7 35.0 62.3 4.7 28.7 48.1 14.6 24.2 13.8 102.2 Ukraine 61.6 91.4 144.9 247.1 56.0 150.2 58.7 89.3 63.3 63.0 Total (9) 131.6 142.1 187.9 433.8 146.6 176.5 106.9 104.1 104.0 207.2 EUROSTAT-OECD Albania 74.0 93.9 182.7 119.0 51.6 72.0 97.9 63.6 28.7 36.2 Australia 312.0 313.3 212.6 328.3 219.8 267.7 369.4 240.9 369.7 330.0 Austria 319.3 320.1 198.2 510.0 413.4 335.0 453.6 238.9 351.9 242.1 Belgium 297.9 303.6 250.8 424.9 267.7 269.9 355.7 329.1 292.8 175.5 Bosnia and Herzegovina 71.5 97.9 151.9 307.1 43.0 113.5 103.9 67.6 55.1 67.1 Bulgaria 115.3 126.9 121.2 264.7 43.8 158.0 155.5 153.4 123.1 155.3 Canada 305.1 317.3 164.5 300.8 269.9 334.4 358.8 268.7 448.9 235.3 Chile 150.2 158.5 133.5 169.5 142.8 130.8 208.8 120.1 178.3 164.6 Croatia 150.9 158.9 179.8 408.4 107.2 200.9 181.3 179.2 122.0 176.0 Cyprus 232.0 265.5 210.4 494.4 324.1 308.1 315.4 178.6 286.7 501.1 Czech Republic 200.9 192.3 165.6 590.2 82.4 218.2 187.0 225.6 130.2 118.5 Denmark 310.9 304.0 198.6 412.6 261.7 292.6 330.1 300.4 260.6 211.3 Estonia 171.5 159.5 168.6 486.8 137.6 150.7 105.9 155.3 136.5 179.4 Finland 286.8 307.4 238.1 480.3 265.6 289.7 340.8 303.1 259.5 288.0 France 270.4 306.3 254.8 358.0 247.8 291.7 348.9 303.2 336.2 237.2 Germany 304.5 329.4 226.3 417.2 289.5 294.4 428.6 359.9 326.7 327.8 Greece 197.8 245.8 261.3 441.6 197.1 304.0 221.0 230.6 251.0 190.3 Hungary 166.5 169.6 135.9 462.5 66.5 193.9 129.4 221.9 118.7 109.2 Iceland 284.0 298.8 244.1 283.7 170.0 349.8 351.9 287.3 288.8 257.5 Ireland 319.0 266.5 163.6 348.6 228.9 262.5 260.0 248.3 286.3 239.4 Israel 224.1 236.9 211.6 205.7 134.1 260.4 327.3 159.8 307.3 240.1 Italy 251.6 276.1 246.0 303.3 396.4 270.4 414.8 247.1 302.1 216.4 Japan 254.5 282.7 178.0 325.6 183.4 290.4 292.5 256.1 280.6 317.9 Korea, Rep. 215.7 202.2 104.1 180.7 130.1 229.2 131.3 235.7 201.1 367.3 Latvia 148.5 158.8 162.4 366.5 96.6 199.8 116.6 137.0 156.1 137.8 Lithuania 167.3 191.3 239.8 463.3 134.3 183.9 192.6 213.1 174.1 158.0 Luxembourg 658.8 370.1 262.1 2072.6 493.5 338.6 685.9 262.4 882.4 336.7 106 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 23.8 131.3 12.1 22.0 79.8 81.1 73.4 26.8 16.2 31.3 63.6 73.6 39.0 171.7 35.0 35.5 91.1 109.5 123.1 46.9 87.8 29.4 83.2 88.3 82.8 323.7 40.8 35.4 114.2 311.3 94.9 94.1 131.3 82.1 125.9 110.4 84.9 313.6 65.1 95.5 119.2 216.7 143.4 81.0 80.1 78.4 125.1 123.2 17.4 113.5 15.2 15.8 36.2 70.4 36.4 9.1 13.5 7.3 28.7 34.5 24.9 150.1 14.6 49.6 57.3 127.4 31.0 14.9 17.6 12.7 44.9 54.2 113.0 199.6 58.7 123.9 160.0 278.0 200.4 92.6 121.8 74.0 157.7 158.3 10.6 69.3 4.4 14.0 31.0 60.9 22.8 9.1 15.0 5.8 25.2 30.2 40.9 183.3 20.4 40.4 81.0 170.3 65.1 24.5 32.7 21.5 66.8 76.6 85.9 200.6 46.5 91.4 128.8 232.6 150.9 71.0 92.7 58.1 124.6 126.8 29.2 254.1 47.5 43.8 87.5 115.5 73.9 82.3 37.7 122.7 88.2 89.5 572.9 238.4 399.1 416.5 312.0 313.1 278.8 319.4 402.9 212.2 309.6 319.1 480.6 187.3 641.2 343.5 322.6 323.2 252.6 304.3 480.1 200.9 311.6 320.1 385.0 233.8 265.6 362.1 282.4 441.5 251.9 312.7 426.4 237.2 298.0 285.7 65.8 144.1 96.9 70.1 93.3 118.0 119.0 49.2 45.7 56.8 86.1 91.0 139.4 158.1 142.4 62.3 117.0 188.4 179.0 80.0 88.5 81.6 117.9 108.2 420.8 208.1 308.2 387.5 309.7 353.0 321.6 318.1 292.0 270.7 313.3 298.8 142.0 273.1 115.3 181.1 154.0 174.5 102.0 134.5 158.3 117.2 147.9 157.7 231.5 175.5 353.4 118.2 148.6 220.5 203.8 124.8 111.6 130.5 153.4 142.9 313.8 194.7 664.4 195.4 279.9 184.1 305.9 183.1 167.8 192.5 245.4 272.9 272.2 196.8 286.3 140.8 173.2 317.6 284.3 187.5 270.0 148.6 196.2 168.2 441.6 247.8 200.8 467.6 257.3 600.6 272.3 284.7 399.6 181.7 292.2 248.1 167.6 211.7 181.7 126.3 140.7 286.9 231.6 163.8 226.3 140.3 168.5 139.3 455.1 245.1 262.4 396.3 278.8 496.7 271.8 263.6 248.5 244.8 291.9 279.3 395.5 220.0 336.2 363.1 282.3 464.5 244.0 240.9 276.6 194.5 282.3 282.7 387.0 197.1 283.5 435.7 313.5 430.7 225.9 225.1 376.2 156.8 290.3 313.6 191.3 181.3 480.9 191.8 254.1 172.8 273.8 123.9 164.0 100.9 217.1 251.8 188.2 197.6 200.2 187.1 149.9 303.4 252.5 109.2 139.8 94.6 160.4 143.2 400.9 283.4 328.3 266.7 266.9 505.8 320.3 147.8 237.7 101.9 259.4 245.7 263.5 244.7 470.2 246.7 251.2 368.9 203.5 195.8 231.2 166.7 244.7 248.2 220.3 281.6 218.0 244.6 223.5 313.8 315.3 192.4 183.8 144.0 228.1 213.6 280.4 179.2 429.2 238.8 270.3 313.4 219.7 237.3 327.9 170.4 258.2 270.1 358.1 159.1 314.1 444.5 268.6 363.2 267.3 219.1 365.1 126.6 260.4 255.0 215.3 218.5 199.6 257.8 202.1 185.9 220.7 243.0 289.4 208.9 214.9 195.9 181.0 198.3 102.2 87.4 149.8 205.8 241.0 117.9 150.9 108.1 157.4 143.6 169.1 220.7 82.7 137.2 173.8 303.4 216.7 107.7 107.8 106.0 174.3 174.4 562.6 195.2 542.9 597.5 361.2 465.1 409.9 651.2 919.2 514.7 438.8 371.8 (continued) Presentation and Analysis of Results 107 Table 2.8 (Continued) Alcoholic Housing, Furnishings, INDEX OF REAL beverages, water, household EXPENDITURES PER Gross Actual Food and tobacco, Clothing electricity, equipment CAPITA (world = 100) domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Macedonia, FYR 88.8 109.7 187.1 160.5 65.8 129.0 70.3 86.8 60.4 127.1 Malta 212.5 227.8 213.5 238.1 160.9 187.4 306.6 245.1 222.4 265.8 Mexico 121.7 137.0 197.9 130.5 84.4 102.0 160.4 65.5 209.5 127.6 Montenegro 105.0 142.4 256.0 311.4 56.4 140.8 271.5 98.8 119.4 210.4 Netherlands 320.6 300.5 232.0 331.3 275.6 256.0 359.3 264.4 266.9 320.3 New Zealand 231.6 260.2 216.5 343.2 251.8 227.9 282.6 275.1 283.0 212.4 Norway 459.7 358.7 234.1 304.0 325.3 320.8 446.9 321.9 377.4 427.3 Poland 161.6 188.6 212.1 350.7 90.2 256.1 154.9 198.0 118.9 146.1 Portugal 190.7 214.9 243.4 295.5 200.0 165.5 253.0 192.8 219.5 167.5 Romania 119.9 129.3 175.0 174.7 56.0 123.2 106.5 196.5 85.0 161.4 d Russian Federation 167.2 175.5 219.7 596.0 199.7 197.6 138.0 117.6 130.9 273.4 Serbia 88.1 116.9 148.0 264.2 42.9 155.8 65.2 126.4 89.5 159.5 Slovak Republic 186.7 195.2 182.0 294.0 111.9 269.4 202.8 217.9 108.3 127.6 Slovenia 209.2 218.3 199.0 511.2 207.3 216.3 272.7 213.2 272.4 229.0 Spain 238.9 248.5 245.4 325.3 283.5 215.7 256.7 211.8 238.0 149.4 Sweden 310.3 309.7 229.7 347.9 251.5 320.8 308.5 274.4 295.9 469.9 Switzerland 383.2 340.8 232.3 674.6 292.9 288.5 426.4 308.0 365.0 397.7 Turkey 132.1 158.8 186.0 142.8 161.5 198.7 250.8 111.9 174.1 116.0 United Kingdom 260.7 302.4 197.1 279.9 433.6 250.9 323.0 270.4 325.3 228.5 United States 369.8 432.4 219.9 311.1 333.5 382.9 458.2 532.3 546.8 331.7 Total (47) 250.2 276.8 206.4 327.1 237.4 264.2 302.6 278.2 306.6 254.3 LATIN AMERICA Bolivia 41.3 42.3 77.2 21.4 14.8 51.8 57.2 23.0 76.0 9.1 Brazil 108.8 114.6 125.7 105.0 54.2 83.2 170.3 134.8 129.9 68.1 Colombia 84.4 90.6 90.8 98.1 83.9 121.9 57.3 55.8 85.4 77.9 Costa Rica 96.8 118.5 133.9 42.0 82.5 72.1 136.1 75.5 217.3 133.0 Cubae … … … … … … … … … … Dominican Republic 80.7 112.4 159.8 197.8 63.1 116.8 70.7 56.8 112.0 151.4 Ecuador 73.8 78.2 88.5 72.7 47.4 87.3 93.1 53.4 106.7 105.7 El Salvador 54.7 84.3 115.0 50.3 61.3 124.9 135.6 50.8 86.7 100.0 Guatemala 51.8 72.0 148.3 31.5 61.8 69.9 99.4 34.9 50.5 126.6 Haiti 11.6 19.5 61.5 22.1 15.0 19.7 16.2 5.4 11.2 2.2 Honduras 32.3 43.4 75.6 55.4 24.7 44.7 34.0 28.8 39.4 27.6 Nicaragua 30.5 41.5 52.8 36.8 20.6 63.6 47.0 33.5 41.6 27.5 Panama 114.2 122.8 114.5 25.1 109.3 198.9 169.7 62.9 163.3 195.8 Paraguay 53.4 64.7 99.9 34.1 37.1 57.5 103.8 38.2 47.8 90.7 Peru 81.6 82.7 109.5 68.2 76.0 64.9 67.9 47.6 85.6 80.2 Uruguay 128.8 149.2 164.1 120.6 89.3 202.6 153.0 140.9 108.9 233.9 Venezuela, RB 126.0 118.7 100.9 78.9 41.3 92.1 69.9 87.5 258.3 232.8 Total (17) 92.4 99.0 113.6 88.3 56.6 86.4 120.2 92.6 118.2 87.8 108 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 45.6 175.4 71.1 64.0 102.4 146.7 165.5 59.0 44.6 73.9 103.4 98.0 359.3 193.9 682.9 260.9 216.3 291.4 310.6 134.1 139.8 118.4 207.9 215.3 78.9 266.6 93.2 117.0 130.5 159.5 114.4 94.1 80.7 106.7 124.8 135.5 67.7 198.5 316.3 84.3 133.9 188.7 220.2 61.8 51.4 73.2 125.3 134.0 416.8 236.9 218.4 494.7 262.2 542.0 382.5 254.3 303.0 196.5 292.2 265.8 377.5 271.9 322.6 235.9 243.9 356.9 237.5 158.8 223.1 108.8 230.5 238.0 570.5 239.4 247.1 442.3 326.5 569.4 350.8 401.4 566.0 236.6 381.2 320.6 206.9 202.4 62.4 196.6 175.2 269.2 173.4 105.7 129.4 93.5 166.2 177.0 218.7 217.2 439.4 208.6 211.5 231.6 221.2 167.6 134.4 181.8 201.6 218.1 123.2 180.7 72.3 76.1 115.8 217.5 144.7 119.6 89.2 149.2 127.4 117.7 110.7 198.6 58.7 128.0 160.0 278.0 200.4 92.6 121.8 74.0 157.7 158.5 77.8 161.1 39.0 88.1 105.0 201.4 106.4 57.2 58.1 59.9 101.1 100.2 247.3 203.1 147.4 168.5 181.7 274.1 282.7 148.8 153.5 111.1 188.8 179.8 268.3 181.7 232.7 188.3 208.0 280.9 245.4 169.7 250.1 126.3 208.8 211.0 314.1 193.4 712.3 215.2 239.4 305.1 265.9 240.2 228.1 190.8 244.4 245.0 458.3 220.3 209.3 447.7 271.9 549.0 280.1 245.3 428.3 135.6 291.2 257.0 497.7 193.2 419.2 471.7 369.8 181.9 191.3 380.0 710.2 199.0 332.3 384.3 88.4 286.7 140.7 90.8 150.2 199.6 122.8 109.3 168.8 86.7 143.9 138.2 562.7 208.9 395.2 336.3 292.7 369.0 261.9 178.5 151.1 138.1 267.8 297.8 646.0 226.5 526.9 590.1 480.5 173.4 409.3 288.8 459.0 155.3 389.2 493.1 350.2 215.3 309.0 331.3 277.9 276.5 258.0 204.0 281.4 143.2 254.6 278.9 4.7 33.7 53.6 11.3 48.1 5.6 52.1 27.3 33.8 19.8 39.1 48.3 66.9 147.9 109.2 126.6 109.6 143.9 133.9 101.3 108.7 89.1 111.4 111.8 64.8 109.7 145.2 86.7 94.7 55.9 107.2 71.0 60.2 81.2 85.9 91.0 160.1 144.1 94.3 59.0 120.2 89.0 73.6 71.9 68.1 77.4 103.0 125.3 … … … … … … … … … … … … 32.8 111.5 188.2 115.8 123.3 28.9 64.9 43.1 27.0 60.8 88.8 123.4 50.8 111.9 47.7 60.4 81.6 48.6 58.6 70.9 42.7 46.8 76.1 81.0 53.4 76.3 65.8 41.6 91.0 33.0 41.4 23.3 26.3 22.4 64.4 87.5 30.3 53.4 78.5 30.9 77.9 27.6 38.4 27.6 31.3 26.5 56.8 75.6 6.9 12.8 0.5 4.2 22.6 1.3 0.1 13.0 0.6 27.3 15.9 22.7 24.1 55.4 43.4 27.7 46.5 20.3 26.7 29.7 36.2 23.1 38.5 46.4 17.3 66.3 38.3 29.6 43.6 24.2 37.7 18.4 15.9 19.4 34.4 40.0 90.4 117.4 93.6 97.2 128.1 76.9 104.3 95.6 102.2 97.8 114.5 118.6 46.0 99.7 48.9 50.7 68.1 37.1 27.5 31.4 25.9 34.1 52.3 70.4 68.9 107.0 109.0 76.9 88.6 36.1 66.3 70.7 55.4 87.0 78.5 89.5 65.3 131.9 185.9 112.2 153.4 106.8 96.1 102.0 81.4 115.8 131.3 142.3 66.5 212.7 184.5 40.9 121.9 91.7 117.0 91.4 70.7 115.4 114.9 124.8 60.0 127.6 109.7 92.2 99.0 94.2 102.7 79.8 77.8 77.9 93.8 99.6 (continued) Presentation and Analysis of Results 109 Table 2.8 (Continued) Alcoholic Housing, Furnishings, INDEX OF REAL beverages, water, household EXPENDITURES PER Gross Actual Food and tobacco, Clothing electricity, equipment CAPITA (world = 100) domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) CARIBBEAN Anguilla 202.6 244.2 153.3 214.1 167.0 320.7 202.1 53.6 524.8 697.4 Antigua and Barbuda 152.6 145.1 108.9 90.0 68.7 282.1 114.8 150.5 111.3 219.0 Aruba 267.6 277.6 126.2 46.6 187.4 612.4 180.2 376.3 331.2 309.4 Bahamas, The 168.2 180.0 113.0 91.9 119.2 348.9 125.7 133.9 151.8 233.1 Barbados 114.1 142.6 139.7 77.6 76.1 450.7 92.2 67.5 123.3 205.2 Belize 61.0 75.1 66.0 21.5 105.3 196.8 88.8 45.3 65.5 76.8 Bermuda 407.9 438.6 311.3 483.7 255.4 435.8 501.6 322.7 435.9 681.4 Bonairef … … 90.4 33.2 224.6 … 167.7 … 242.1 204.0 Cayman Islands 369.1 393.4 160.0 154.1 286.1 776.0 348.2 128.8 441.7 621.7 Curaçao 206.4 239.3 152.6 98.8 286.7 555.1 125.3 175.9 221.4 229.2 Dominica 74.2 100.2 87.0 24.6 148.9 164.9 75.2 61.8 177.0 137.1 Grenada 83.4 118.1 113.0 66.7 87.5 178.1 77.0 46.4 183.4 382.8 Jamaica 61.9 83.7 112.5 31.4 35.8 87.8 90.8 45.8 103.6 103.1 Montserrat 117.1 157.4 113.8 101.6 41.5 258.3 93.3 138.8 342.0 441.0 St. Kitts and Nevis 152.9 167.0 119.2 150.4 160.4 351.2 122.4 122.9 112.8 207.7 St. Lucia 73.5 87.0 94.7 45.6 109.6 169.4 56.5 44.2 76.0 139.9 St. Vincent and the Grenadines 73.4 96.6 95.6 187.8 43.7 187.8 64.1 67.5 166.5 172.2 Sint Maarten 245.0 223.2 115.0 40.1 294.6 556.6 183.2 84.9 287.2 269.6 Suriname 107.4 68.4 111.8 53.4 54.4 120.4 48.8 37.7 35.7 71.3 Trinidad and Tobago 213.5 181.5 203.0 48.1 48.2 155.5 115.6 132.3 187.7 136.5 Turks and Caicos Islands 155.1 87.8 88.6 58.2 101.6 43.6 79.8 78.2 215.9 86.3 Virgin Islands, British 225.0 124.4 134.3 177.5 305.5 129.0 298.0 64.8 160.0 165.8 Total (22) 121.5 125.7 132.0 54.8 70.3 180.3 102.9 82.5 134.1 145.2 WESTERN ASIA Bahrain 322.1 215.4 174.9 30.1 242.4 265.8 303.6 96.9 383.0 429.0 a Egypt, Arab Rep. 78.7 98.6 164.1 74.1 114.4 153.0 70.0 108.7 55.7 76.7 Iraq 82.7 62.2 86.7 8.9 55.8 134.0 50.4 45.7 46.5 34.4 Jordan 83.0 102.6 126.5 106.0 107.9 187.4 85.1 77.0 95.4 124.3 Kuwait 624.5 253.1 259.1 22.3 376.4 479.5 598.6 116.5 327.3 233.2 Oman 316.6 175.6 183.3 16.1 213.4 199.3 149.3 87.9 398.2 252.8 Qatar 1088.5 237.7 189.4 34.0 195.8 294.0 224.8 112.0 394.9 200.9 Saudi Arabia 357.8 205.8 169.6 25.2 212.7 379.7 281.3 123.3 198.5 254.1 Sudanb 26.8 26.7 65.5 4.3 43.7 24.5 37.4 5.3 17.6 13.3 United Arab Emirates 452.3 340.7 268.7 26.1 1023.8 623.6 360.8 31.9 802.2 889.2 West Bank and Gaza 28.5 47.1 83.4 33.1 70.6 27.2 56.3 43.0 35.1 48.7 Yemen, Rep. 27.6 31.9 54.8 64.8 36.6 46.2 15.9 36.4 19.0 9.6 Total (12) 130.0 99.2 128.0 42.0 134.4 165.5 102.1 70.7 100.5 110.4 110 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 115.5 206.6 147.2 318.3 257.8 94.7 414.7 200.9 117.1 268.9 238.4 258.2 54.2 187.9 87.5 148.4 135.9 225.2 297.8 150.0 63.6 222.1 153.8 113.5 238.9 256.2 77.5 204.3 238.5 596.9 450.4 398.2 252.2 508.4 311.2 181.8 122.7 147.5 186.6 223.1 185.5 117.6 316.0 226.5 294.5 189.2 198.5 160.1 86.2 101.7 403.8 107.5 146.3 98.1 246.7 101.5 129.5 88.2 136.8 88.7 52.3 63.6 6.8 26.7 80.0 29.3 106.9 24.7 31.6 20.5 63.4 55.2 434.3 521.8 919.8 552.0 424.7 498.6 502.7 573.3 1111.7 304.9 468.5 421.8 … … 196.1 … 169.6 … … … … … … 154.5 282.3 322.9 378.6 587.7 412.9 196.7 481.3 428.2 601.7 338.2 399.2 354.1 133.9 138.9 102.4 422.8 242.9 185.9 264.8 310.1 477.6 136.9 259.6 196.0 48.0 109.8 47.1 58.7 102.8 67.6 145.0 67.0 83.3 57.3 85.6 90.3 35.7 185.0 32.6 75.2 120.4 85.1 125.4 64.9 65.3 66.1 104.0 108.5 92.0 116.2 155.0 79.1 85.3 61.8 83.4 50.6 56.3 47.5 75.1 80.1 63.0 191.1 8.9 137.2 148.2 218.5 618.6 161.2 102.0 210.4 183.3 130.9 67.9 321.9 168.4 127.6 160.2 220.6 407.6 166.5 110.2 207.5 177.7 127.7 20.3 145.8 15.9 79.2 88.2 66.9 124.9 87.8 65.3 103.6 88.4 76.5 73.5 118.5 34.3 65.1 94.2 108.6 127.1 71.9 46.6 93.7 92.4 81.4 140.1 122.0 55.1 206.0 229.2 144.6 554.3 200.9 331.0 81.0 234.1 171.0 32.9 11.7 14.4 71.2 73.3 16.2 204.3 143.0 276.9 47.8 101.3 75.8 174.4 390.0 236.4 233.1 157.1 384.6 74.6 149.8 182.1 129.1 166.7 168.5 73.2 125.4 54.6 90.7 89.9 59.9 513.7 90.1 125.4 72.9 111.0 102.4 75.1 81.6 107.3 61.7 128.0 79.0 194.7 215.6 361.5 138.5 143.4 136.1 107.2 173.8 161.1 136.3 122.0 147.2 144.0 113.9 145.9 93.4 123.4 113.3 235.7 258.3 186.7 122.7 229.8 130.2 291.4 241.6 154.9 329.0 224.9 248.5 41.6 135.9 43.8 62.5 101.0 68.3 127.4 34.1 28.4 39.3 82.2 95.2 9.0 135.3 8.4 11.0 55.8 104.2 221.8 51.2 53.8 51.8 70.0 46.0 23.1 196.3 28.2 23.4 102.6 97.6 149.9 59.9 36.6 74.5 95.6 90.8 123.0 218.7 95.6 103.5 261.1 198.6 566.7 475.1 441.7 417.6 328.6 246.5 86.6 233.0 77.1 119.5 171.5 188.0 414.6 399.2 313.0 430.2 231.7 177.2 272.1 296.6 76.8 284.5 239.9 235.7 707.8 1904.9 2034.7 659.2 572.8 236.2 88.1 349.6 129.2 83.5 188.4 286.8 370.4 415.1 333.0 424.8 274.9 175.8 8.8 17.6 12.9 6.1 29.0 3.2 37.6 24.9 21.9 29.5 27.6 29.6 136.6 151.8 200.4 128.1 412.4 29.6 215.9 599.7 583.6 536.7 365.3 371.8 17.4 73.2 15.3 30.5 44.9 55.1 87.1 22.5 10.5 27.9 42.8 48.2 1.8 40.6 0.2 11.4 32.7 23.7 49.3 11.5 2.5 15.0 28.9 32.1 39.5 136.0 45.8 46.4 100.1 87.7 164.0 124.8 109.3 118.0 107.8 93.5 (continued) Presentation and Analysis of Results 111 Table 2.8 (Continued) Alcoholic Housing, Furnishings, INDEX OF REAL beverages, water, household EXPENDITURES PER Gross Actual Food and tobacco, Clothing electricity, equipment CAPITA (world = 100) domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) SINGLETONS Georgia 47.1 70.0 94.6 143.0 21.6 124.3 42.5 80.5 45.7 83.0 Iran, Islamic Rep. 129.9 99.2 108.2 24.7 54.3 179.7 58.2 109.3 66.3 171.6 Total (2) 125.3 97.6 107.5 31.4 52.4 176.5 57.3 107.7 65.1 166.6 WORLDg (179) 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; ... = data suppressed because of incompleteness. a. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. b. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. c. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. d. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. e. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. f. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. g. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 112 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross consumption Recreation Restaurants neous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 65.2 143.0 28.4 38.2 67.0 55.1 114.0 23.6 36.1 16.2 57.9 61.2 34.1 183.5 14.1 69.4 95.2 103.9 225.7 93.3 89.6 116.6 117.3 85.5 35.9 181.2 14.9 67.6 93.7 101.1 219.4 89.4 86.6 111.0 114.0 84.1 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Presentation and Analysis of Results 113 Table 2.9 Price Level Indexes (World = 100), ICP 2011 Alcoholic Housing, Furnishings, PRICE LEVEL INDEX beverages, water, household (world = 100) Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) AFRICA Algeria 53.9 49.4 77.7 78.0 70.8 45.2 55.2 27.5 41.8 67.8 Angola 94.0 93.0 140.7 61.0 110.2 79.8 112.1 80.4 83.4 129.0 Benin 58.5 54.8 87.7 52.1 53.2 53.0 64.2 39.7 50.8 71.4 Botswana 71.0 74.1 106.0 100.8 65.0 89.2 97.3 51.2 66.7 65.6 Burkina Faso 58.4 53.8 91.1 56.6 48.2 43.6 61.8 38.8 62.1 73.2 Burundi 43.5 43.1 71.8 73.0 40.1 26.7 56.4 21.1 73.4 88.3 Cameroon 62.1 56.4 83.3 63.3 70.6 44.1 78.1 51.4 63.6 108.8 Cape Verde 79.4 70.0 103.7 80.4 86.9 73.2 71.7 50.6 82.4 64.6 Central African Republic 69.9 64.5 116.0 71.9 57.7 36.6 83.5 41.2 71.4 119.2 Chad 68.4 61.0 95.9 72.6 58.3 59.9 76.9 40.1 66.9 105.7 Comoros 75.6 70.8 112.2 112.2 76.1 57.7 110.5 46.3 77.1 137.2 Congo, Rep. 79.1 72.9 128.9 71.5 78.1 46.9 83.0 47.2 84.8 121.9 Congo, Dem. Rep. 73.2 66.7 120.9 84.5 67.0 41.2 69.1 40.6 75.7 98.7 Côte d’Ivoire 62.4 58.1 91.1 63.6 69.5 45.5 62.9 35.5 66.1 99.5 Djibouti 68.2 66.1 95.9 72.2 69.1 58.2 71.1 56.6 72.0 67.3 Egypt, Arab Rep.a 35.1 33.6 64.3 59.1 42.4 16.3 52.1 21.5 35.3 44.0 Equatorial Guinea 80.5 80.3 139.4 61.7 77.7 63.8 107.4 54.2 81.7 89.7 Ethiopia 37.5 36.4 58.6 45.7 42.3 37.1 45.9 21.8 43.3 43.2 Gabon 86.9 88.3 155.2 59.6 91.1 79.0 87.6 65.6 71.1 143.2 Gambia, The 43.5 41.3 74.6 44.8 28.1 36.2 44.9 23.0 42.3 37.5 Ghana 59.7 59.0 116.0 70.1 55.7 41.9 64.4 29.1 46.2 65.8 Guinea 49.0 43.6 90.3 48.9 39.5 16.2 46.7 27.6 48.7 70.9 Guinea-Bissau 60.1 58.6 94.7 67.1 67.4 51.0 76.4 32.7 68.8 80.5 Kenya 49.8 46.5 71.9 64.3 41.1 33.5 51.3 29.9 66.3 41.1 Lesotho 69.7 62.7 90.9 80.9 62.5 49.5 79.9 43.2 69.9 81.3 Liberia 66.7 64.7 108.8 78.6 54.8 80.0 59.3 34.2 66.1 92.0 Madagascar 42.9 39.9 64.4 48.4 32.0 41.3 42.9 22.5 58.0 76.8 Malawi 63.1 58.2 100.1 65.2 48.8 28.7 73.7 29.5 100.0 76.4 Mali 57.4 53.4 79.9 52.8 55.2 53.2 67.8 30.4 72.7 77.2 Mauritania 52.3 45.2 73.2 52.0 36.8 38.3 50.7 30.5 48.0 68.5 Mauritius 71.6 71.8 103.4 115.4 60.9 55.3 83.2 45.3 104.3 68.6 Morocco 58.6 59.5 93.1 123.0 65.2 34.8 67.1 56.4 63.7 90.2 Mozambique 71.1 63.1 99.7 67.1 59.5 42.5 84.5 50.5 69.0 88.6 Namibia 82.8 82.2 124.6 84.0 62.7 98.3 73.1 65.3 81.7 76.1 Niger 60.4 55.5 95.6 66.3 40.4 49.9 50.0 40.9 61.2 104.7 Nigeria 62.3 58.8 106.7 56.5 50.4 52.0 49.2 31.9 55.2 78.8 Rwanda 55.9 48.5 73.3 67.0 57.6 35.6 44.9 30.5 74.4 63.6 São Tomé and Príncipe 62.4 64.3 108.1 72.7 68.6 57.8 78.6 35.0 71.2 85.6 114 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual consumption consumption consumption Gross consumption Recreation Restaurants Miscellaneous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 41.4 25.3 50.9 46.4 52.0 32.3 32.1 75.2 108.8 63.9 53.2 51.7 112.9 73.1 142.1 81.1 94.0 87.7 83.2 79.3 116.6 66.1 91.4 99.8 59.7 43.2 65.8 34.7 56.9 46.3 42.7 83.0 108.1 75.4 58.7 60.4 72.1 53.2 98.7 60.9 77.4 54.9 65.0 62.6 104.3 47.0 70.0 79.0 65.8 30.3 51.3 42.3 56.2 42.4 52.5 78.1 114.6 65.5 58.6 60.8 53.5 19.5 51.5 35.2 46.1 24.8 29.4 71.8 104.2 60.9 45.8 52.1 66.4 44.1 70.6 42.1 58.2 58.3 56.4 86.9 104.5 88.5 61.9 62.4 73.3 57.1 64.5 55.3 71.9 61.4 69.2 97.2 115.9 96.1 76.4 75.3 70.8 29.0 70.9 52.5 67.7 42.7 65.4 90.2 116.7 84.4 69.1 74.0 56.0 31.3 81.3 43.3 63.5 54.8 57.1 97.6 117.1 100.9 68.0 67.2 87.2 42.4 78.7 67.3 74.3 52.6 63.2 87.0 116.8 79.8 73.5 81.7 79.8 54.1 78.7 45.2 75.0 65.9 73.3 107.8 116.9 102.8 82.7 80.6 61.6 32.8 93.2 57.6 69.8 53.3 65.4 95.2 117.4 91.2 72.5 78.7 74.3 52.5 58.2 42.7 59.6 56.4 59.3 77.6 115.6 63.8 61.7 63.6 78.2 52.7 84.4 59.3 68.1 59.2 61.9 70.1 106.7 56.7 67.3 72.9 33.4 21.6 42.3 28.6 36.1 17.7 19.1 58.9 95.4 47.6 35.3 40.7 100.3 49.8 87.8 65.7 81.2 82.2 124.8 76.4 118.0 60.2 80.4 85.3 33.1 15.6 30.4 25.0 38.4 23.2 29.2 56.1 112.2 33.7 39.5 39.0 73.6 81.5 99.5 67.2 90.8 79.2 79.4 94.4 116.3 103.2 89.4 94.0 38.4 28.8 65.2 30.0 43.8 24.4 29.7 68.2 117.6 45.9 45.0 46.7 60.9 36.5 84.0 41.3 62.2 40.5 51.8 62.8 124.0 36.8 59.5 66.7 45.6 18.8 62.2 35.6 46.3 21.3 30.4 77.3 113.8 65.0 48.7 53.9 74.4 19.6 79.3 45.6 62.8 25.3 41.6 78.7 117.5 64.9 59.8 66.2 49.6 46.7 50.9 33.0 47.6 42.1 53.9 66.3 103.2 52.2 50.9 53.0 57.0 64.0 86.9 47.1 63.5 61.7 72.6 80.5 117.6 67.1 67.9 69.2 57.3 32.5 65.0 45.5 67.7 48.7 56.5 74.0 116.9 54.0 66.1 68.5 36.4 23.3 27.7 28.4 41.5 34.2 42.7 68.2 111.5 51.4 44.6 43.8 75.8 50.6 85.1 42.2 59.7 54.7 79.4 79.1 118.1 64.9 63.0 67.5 53.8 36.3 74.7 38.6 56.1 37.9 46.4 77.6 110.4 66.9 57.5 58.5 46.9 32.9 65.7 37.0 47.1 34.5 42.5 78.7 118.5 64.4 53.0 50.6 65.5 56.2 109.9 60.3 76.0 44.4 49.2 74.2 103.1 64.2 70.5 79.0 59.0 51.5 70.9 50.8 61.8 47.0 55.6 57.0 101.6 39.9 58.7 70.2 61.5 74.6 58.0 41.8 63.7 73.7 97.7 88.2 109.1 82.9 70.1 69.3 75.4 54.3 106.8 53.8 84.3 71.1 76.4 73.9 115.6 58.5 80.8 83.4 62.5 25.6 64.8 42.3 57.8 44.7 58.7 78.8 94.4 79.1 60.8 61.1 55.9 47.3 66.7 36.8 61.6 43.3 50.9 78.1 116.9 64.2 61.7 64.3 56.5 50.4 54.1 39.9 48.9 60.0 83.3 80.9 107.2 71.2 56.6 53.9 76.2 31.0 75.3 42.7 69.0 29.8 32.4 68.5 117.3 43.4 62.3 73.5 (continued) Presentation and Analysis of Results 115 Table 2.9 (Continued) Alcoholic Housing, Furnishings, PRICE LEVEL INDEX beverages, water, household (world = 100) Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Senegal 64.6 60.3 95.7 70.7 54.2 51.5 59.1 41.5 72.1 86.2 Seychelles 69.7 70.3 107.9 162.7 84.2 49.1 87.2 38.9 89.9 81.8 Sierra Leone 46.2 46.0 85.2 45.7 33.4 28.6 49.2 25.2 59.9 85.6 South Africa 84.8 81.9 102.0 86.3 90.7 78.2 105.3 75.4 88.3 79.2 Sudanb 59.2 62.7 100.7 107.1 41.4 57.7 66.1 31.1 78.4 82.2 Swaziland 69.3 65.6 91.8 80.9 72.1 62.0 74.1 41.5 73.1 71.2 Tanzania 42.9 42.7 67.4 61.0 37.8 45.8 46.7 20.3 48.4 46.5 Togo 58.8 55.4 95.2 58.5 51.3 43.0 63.6 35.4 79.7 115.6 Tunisia 54.2 55.2 84.7 87.7 89.4 44.7 65.3 41.9 57.0 43.4 Uganda 42.6 42.9 62.8 57.9 46.2 43.0 51.3 27.9 58.8 55.2 Zambia 63.1 59.8 89.9 81.8 59.8 47.9 75.2 35.8 90.1 142.7 Zimbabwe 65.0 61.2 92.1 54.6 70.3 53.5 93.0 40.9 81.1 89.3 Total (50) 58.6 55.0 86.9 71.7 56.0 39.1 65.4 37.8 61.1 68.0 ASIA AND THE PACIFIC Bangladesh 40.3 38.3 59.0 32.3 43.0 29.8 41.7 22.2 60.3 13.9 Bhutan 46.6 41.9 58.5 78.1 39.5 39.1 55.3 29.6 48.8 31.4 Brunei Darussalam 73.5 80.5 95.0 206.5 96.4 70.2 144.5 67.0 63.3 138.7 Cambodia 42.8 41.6 64.1 44.2 35.9 47.4 45.9 19.6 57.4 48.1 c China 70.0 67.4 89.1 108.0 82.8 56.1 89.1 48.4 65.5 50.9 Fiji 75.0 77.8 93.7 95.6 65.1 106.5 86.0 54.4 83.9 101.4 Hong Kong SAR, China 90.5 89.4 107.1 116.5 66.8 105.7 91.9 101.4 95.6 47.6 India 41.7 37.4 49.9 59.6 32.0 29.8 51.8 17.3 56.4 32.0 Indonesia 53.0 53.0 78.4 94.7 68.7 47.4 55.6 43.7 59.3 60.8 Lao PDR 39.6 39.4 73.3 53.9 36.2 22.9 50.2 19.9 66.3 31.8 Macao SAR, China 73.8 81.4 107.2 75.4 86.6 84.1 105.3 76.2 82.0 55.1 Malaysia 61.5 60.2 83.0 109.4 72.7 45.3 81.2 46.6 68.7 81.1 Maldives 75.3 80.9 87.7 55.4 60.2 172.1 78.2 37.7 75.3 45.3 Mongolia 54.7 50.9 79.6 53.3 68.3 53.3 85.9 20.4 55.4 77.1 Myanmar 37.0 35.0 62.9 60.2 35.5 29.7 46.4 15.2 65.9 47.4 Nepal 42.9 40.0 58.0 58.4 35.7 35.2 44.5 18.5 84.0 45.9 Pakistan 36.4 33.8 54.0 39.7 38.3 23.3 48.8 15.5 49.3 32.5 Philippines 53.2 50.8 71.1 48.8 64.6 45.2 53.2 44.6 56.8 89.0 Singapore 91.4 110.7 121.1 255.0 88.9 146.1 113.6 100.5 121.1 97.3 Sri Lanka 45.1 42.5 69.1 49.4 39.9 32.4 60.5 21.8 60.6 37.1 Taiwan, China 66.1 64.0 91.6 83.6 55.8 69.5 84.1 39.9 68.3 40.2 Thailand 52.3 49.2 73.1 82.2 45.6 33.2 67.7 36.2 62.1 48.8 Vietnam 42.2 40.8 64.5 38.7 37.0 46.7 47.4 16.5 74.0 52.6 Total (23) 59.7 54.5 70.3 79.3 57.2 45.7 73.3 39.5 62.5 49.4 116 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual consumption consumption consumption Gross consumption Recreation Restaurants Miscellaneous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 59.3 47.4 74.9 45.6 62.2 55.1 57.0 80.8 111.1 70.9 64.2 66.8 70.3 45.6 180.8 63.0 76.1 38.0 37.7 92.6 116.4 89.2 69.0 83.0 44.5 35.1 52.1 34.1 48.6 27.4 35.0 63.7 108.5 43.3 48.8 54.0 79.7 84.3 100.0 69.6 83.2 78.6 85.9 82.6 107.6 78.1 83.4 88.6 62.5 41.5 51.2 54.4 66.5 29.6 31.2 61.6 106.3 45.7 58.7 68.8 66.3 79.6 73.7 58.0 66.5 68.7 78.5 65.6 117.0 45.0 68.4 69.8 45.1 35.0 43.2 30.2 44.4 33.9 46.8 49.0 106.2 28.9 44.6 46.4 75.0 26.1 68.0 35.7 58.7 33.5 47.2 80.1 122.5 64.7 59.1 63.5 62.2 32.3 64.2 45.1 59.0 34.2 39.8 56.6 116.2 36.6 54.4 63.0 45.1 27.2 46.8 31.8 44.8 32.6 43.3 51.3 116.5 30.9 44.3 46.8 62.0 65.9 59.6 37.6 61.5 57.2 64.7 67.2 109.9 51.7 62.6 65.8 63.4 45.8 79.6 41.6 63.9 47.5 53.5 86.3 116.6 76.2 64.7 67.6 55.9 42.0 61.3 46.7 57.2 43.0 48.9 70.5 108.1 55.8 58.0 61.4 43.4 24.9 36.0 47.0 40.0 28.7 35.8 48.1 86.3 37.7 40.4 42.6 41.3 32.3 33.9 41.5 43.4 33.4 33.1 62.2 108.8 47.8 46.9 43.7 78.2 80.2 85.8 80.3 80.9 76.8 60.1 87.7 98.2 88.6 80.1 84.3 41.0 18.5 37.0 47.2 44.9 20.9 30.8 49.7 88.7 36.8 42.5 47.0 49.4 69.2 55.9 73.6 68.2 61.0 73.1 76.1 102.8 68.9 70.1 72.2 73.7 55.9 74.8 74.3 80.9 61.7 59.2 70.2 97.0 64.5 74.4 75.3 56.8 117.0 76.1 77.7 88.2 115.4 117.1 93.6 100.5 105.1 91.9 86.3 41.2 29.6 46.6 46.6 38.3 35.2 43.3 52.8 88.2 41.9 41.8 40.7 45.5 32.7 48.6 48.7 55.7 37.1 46.6 54.2 88.6 44.6 52.8 56.9 48.4 10.2 45.0 48.3 43.3 14.1 21.7 47.2 88.4 34.7 39.8 47.8 64.0 69.2 72.7 82.9 81.3 83.7 96.1 80.9 85.3 81.6 82.4 82.4 53.9 52.4 47.2 65.3 61.8 52.5 56.0 67.8 92.4 61.9 61.8 65.8 63.9 53.2 48.0 63.2 87.2 50.9 48.9 78.0 95.4 76.4 74.8 66.4 55.9 24.1 51.8 64.1 55.6 25.3 35.2 69.4 102.2 60.3 55.0 56.5 36.9 9.6 31.3 50.6 40.2 13.1 20.0 49.4 94.1 34.3 36.8 43.4 39.4 23.1 37.4 46.2 41.5 32.9 46.3 56.1 88.3 46.5 43.7 43.4 34.3 23.3 40.5 42.4 35.1 27.7 30.4 50.9 92.5 38.1 36.5 37.8 49.6 34.8 44.7 54.2 52.0 49.6 60.9 57.9 93.3 46.9 53.1 55.7 66.9 129.6 76.6 99.1 111.1 121.5 92.0 84.0 93.7 87.5 100.2 108.4 39.4 22.9 57.0 50.8 45.5 24.1 31.4 60.6 101.1 48.6 45.5 48.4 54.7 67.6 49.3 61.6 64.7 65.8 67.0 72.3 88.5 73.0 66.2 64.9 47.9 40.2 37.0 56.0 50.2 44.4 56.3 57.8 92.9 45.4 52.3 54.7 36.7 17.0 36.7 44.1 44.3 19.5 23.7 52.5 87.5 42.4 41.9 44.2 49.8 49.2 52.0 59.7 54.9 53.7 58.6 69.2 98.1 60.5 59.2 57.7 (continued) Presentation and Analysis of Results 117 Table 2.9 (Continued) Alcoholic Housing, Furnishings, PRICE LEVEL INDEX beverages, water, household (world = 100) Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) COMMONWEALTH OF INDEPENDENT STATES Armenia 64.8 51.0 92.0 44.7 101.9 16.7 73.8 33.4 71.4 80.5 Azerbaijan 58.8 44.5 70.2 40.7 88.5 15.0 64.8 33.1 65.6 69.9 Belarus 43.5 34.2 55.5 30.5 76.1 10.6 59.5 23.4 57.3 33.0 Kazakhstan 70.5 60.0 80.1 42.1 92.2 52.5 73.1 38.8 72.7 68.3 Kyrgyz Republic 49.6 39.2 75.1 32.0 86.2 10.2 59.6 25.8 62.0 43.2 Moldova 60.8 48.8 73.9 36.7 97.7 28.2 69.9 32.8 76.8 59.2 Russian Federationd 76.2 63.0 97.1 51.9 101.7 31.1 75.1 57.4 87.6 62.3 Tajikistan 48.7 40.1 75.9 42.0 101.8 10.3 74.0 20.5 79.2 33.4 Ukraine 55.6 44.6 70.2 38.9 93.8 16.8 58.1 31.0 67.2 53.6 Total (9) 71.8 58.6 89.0 49.2 99.5 28.6 72.4 48.8 82.5 60.5 EUROSTAT-OECD Albania 57.8 58.6 86.5 50.0 98.7 53.8 84.9 38.1 98.0 121.8 Australia 201.0 193.5 188.0 231.0 187.9 257.0 144.2 247.0 144.2 153.3 Austria 148.8 147.3 152.1 108.3 138.2 145.5 129.2 160.6 150.3 129.2 Belgium 150.4 151.8 139.3 114.2 155.1 174.5 125.0 157.6 144.9 166.9 Bosnia and Herzegovina 66.4 68.2 96.6 56.4 148.7 43.0 76.6 65.2 103.1 111.4 Bulgaria 60.5 58.2 86.9 74.7 113.2 42.9 75.0 36.2 93.4 102.5 Canada 161.9 160.2 174.4 188.9 150.7 169.0 142.6 186.0 134.3 170.0 Chile 92.8 91.0 118.3 94.0 121.6 92.5 100.1 88.7 92.1 123.5 Croatia 91.6 92.5 118.4 93.3 143.5 74.4 97.4 75.1 117.0 109.1 Cyprus 120.6 121.4 142.1 112.2 136.4 106.1 110.6 120.1 121.4 81.6 Czech Republic 98.2 94.8 105.0 98.5 139.7 109.8 100.0 73.9 111.5 158.6 Denmark 185.0 196.4 180.6 144.5 177.8 237.6 143.4 200.2 195.7 134.0 Estonia 93.9 93.1 110.1 93.6 139.8 102.4 99.8 66.9 116.3 102.2 Finland 162.6 164.8 147.9 156.6 168.4 199.3 133.4 156.2 164.6 110.7 France 151.4 148.3 138.7 125.2 144.1 180.2 131.3 145.4 147.3 160.9 Germany 139.6 135.3 134.3 109.4 141.9 165.0 116.1 121.3 149.0 111.6 Greece 124.3 122.9 134.2 113.9 130.5 128.3 116.7 100.7 134.4 174.8 Hungary 79.3 75.2 104.0 70.9 113.1 70.5 82.8 50.5 118.9 148.7 Iceland 148.3 145.5 143.9 192.5 188.6 118.0 142.5 146.2 163.6 113.1 Ireland 148.3 163.0 153.9 211.2 144.1 177.8 124.3 199.6 149.6 161.7 Israel 142.2 140.7 157.7 136.8 145.1 147.6 116.3 138.3 140.3 178.3 Italy 137.7 138.2 142.3 117.2 147.8 152.3 126.2 143.0 135.0 142.5 Japan 173.6 170.4 232.2 134.3 165.6 199.2 155.1 154.2 152.7 171.3 Korea, Rep. 99.4 95.6 157.1 84.3 156.6 68.1 96.0 69.9 97.7 77.6 Latvia 88.1 86.9 110.8 101.5 148.5 81.6 93.1 55.7 112.4 110.4 Lithuania 81.4 78.9 99.5 87.1 142.4 66.2 91.1 54.4 112.4 79.6 Luxembourg 162.4 182.9 147.9 102.8 140.3 256.7 130.6 215.7 134.2 123.1 Macedonia, FYR 54.5 55.0 75.3 46.3 99.1 47.2 72.5 33.9 90.1 100.8 118 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual consumption consumption consumption Gross consumption Recreation Restaurants Miscellaneous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 58.2 19.6 74.7 46.7 58.9 22.6 40.0 135.7 108.5 172.3 63.2 72.3 53.8 24.7 69.6 38.5 49.8 26.5 42.4 130.3 104.6 166.8 57.2 58.5 41.5 16.1 57.8 40.6 39.0 17.2 32.4 93.4 84.7 109.2 43.4 45.7 64.6 28.3 74.6 42.0 68.0 30.8 45.4 122.1 103.2 150.7 69.0 64.0 54.1 15.1 72.5 32.1 45.3 18.1 29.1 127.1 111.1 151.9 50.3 54.7 58.0 23.7 60.4 42.5 55.4 25.8 30.7 128.2 99.4 166.4 59.7 65.0 75.3 41.2 93.6 58.1 68.1 43.3 70.4 124.1 98.4 159.4 74.5 76.7 39.1 11.3 63.5 38.1 48.7 12.0 21.9 124.9 97.3 163.3 50.7 57.8 57.7 26.4 78.2 41.7 49.6 26.4 39.1 112.7 94.0 140.1 54.9 57.7 71.0 34.2 88.2 54.6 64.0 37.9 63.7 121.9 97.9 154.7 70.1 71.8 62.5 9.5 51.9 53.5 68.4 20.6 37.5 74.6 99.5 70.4 60.2 72.2 149.5 280.2 157.7 162.8 187.8 234.5 185.7 229.7 127.9 364.7 201.6 176.1 134.0 268.7 131.3 130.5 140.5 181.0 172.3 143.8 101.1 207.5 149.1 143.7 124.9 242.9 140.8 137.0 145.8 174.6 184.4 128.8 102.5 167.0 150.3 142.8 69.8 35.0 76.9 65.5 73.5 46.8 55.2 75.2 99.2 64.9 68.6 82.5 60.7 31.4 56.3 55.7 64.9 32.2 35.8 81.6 92.1 78.0 59.7 73.4 136.1 256.1 157.1 137.9 154.9 195.0 163.3 157.9 99.3 226.1 161.0 151.8 98.3 59.7 93.5 81.4 96.6 66.5 71.2 100.8 97.6 112.8 91.9 100.1 90.6 89.1 111.2 82.4 97.2 74.3 71.9 92.1 96.9 96.8 90.9 104.7 116.8 217.7 124.5 107.0 118.0 147.1 121.2 110.3 101.6 127.9 120.0 123.7 86.7 86.3 74.3 84.2 100.5 73.7 81.2 110.2 98.6 127.7 97.2 101.2 165.3 296.2 191.2 179.8 189.7 214.3 199.6 152.1 110.2 221.3 188.1 185.2 96.2 74.1 92.0 82.6 100.9 66.3 69.6 100.7 97.8 109.0 92.9 102.2 150.4 224.8 161.6 152.4 162.5 170.0 162.2 149.1 110.1 198.2 162.3 156.5 129.3 201.7 128.7 133.4 145.9 155.4 167.1 147.4 100.8 208.4 150.5 140.7 127.0 177.1 127.0 118.0 135.6 133.1 152.5 148.6 98.8 217.9 139.9 134.0 120.4 147.5 123.0 108.1 125.7 110.5 109.0 130.4 115.5 154.8 123.4 124.4 73.1 59.4 64.0 66.5 81.8 51.9 62.9 94.0 89.3 103.8 77.7 88.0 152.4 208.8 146.6 130.7 142.7 153.4 133.9 174.3 119.6 252.1 150.0 150.5 137.2 185.1 157.1 151.3 157.8 182.6 149.1 111.5 103.5 128.9 152.8 155.5 134.8 163.5 150.4 121.6 142.4 136.7 128.4 146.9 143.0 174.2 141.5 141.5 129.9 169.0 133.7 122.6 136.9 145.1 157.1 120.9 101.6 147.2 137.2 135.9 142.3 204.5 145.9 149.2 173.5 159.9 165.4 180.2 122.5 269.6 172.7 170.1 88.5 130.1 120.2 83.4 98.2 86.5 97.6 105.5 90.9 127.6 98.6 105.7 85.9 63.0 99.6 79.0 94.7 55.4 62.8 102.7 96.7 114.2 87.8 100.3 81.0 60.5 79.5 73.3 85.8 53.6 57.7 99.0 94.4 108.4 80.9 93.7 131.4 483.6 134.1 150.2 164.1 260.2 198.3 132.3 100.8 174.3 171.2 145.1 58.7 24.4 51.4 50.6 61.9 27.9 36.5 73.3 94.5 67.0 56.5 66.9 (continued) Presentation and Analysis of Results 119 Table 2.9 (Continued) Alcoholic Housing, Furnishings, PRICE LEVEL INDEX beverages, water, household (world = 100) Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) Malta 100.1 100.6 121.6 114.4 137.5 83.8 114.1 86.0 128.4 127.3 Mexico 79.6 77.2 86.6 79.1 82.9 112.8 78.1 78.4 86.7 112.8 Montenegro 66.1 67.4 95.3 59.5 136.1 54.8 81.7 51.1 98.4 100.8 Netherlands 149.1 149.4 123.9 121.9 151.3 179.1 120.9 164.4 154.3 167.2 New Zealand 151.4 145.4 159.1 195.4 135.9 186.4 125.6 130.5 133.2 187.8 Norway 206.4 220.0 232.2 307.7 214.0 210.0 157.0 253.1 215.2 132.2 Poland 79.3 73.1 78.9 87.1 138.1 64.4 77.5 51.8 99.1 94.1 Portugal 112.5 115.5 114.3 101.2 146.8 122.8 108.4 121.5 132.2 153.3 Romania 68.3 68.8 91.2 89.2 125.6 79.4 80.6 38.9 99.5 94.0 d Russian Federation 76.2 63.0 97.1 51.9 101.7 31.1 75.1 57.4 87.6 62.3 Serbia 65.6 66.7 95.0 57.2 142.9 56.9 90.4 49.8 101.7 76.1 Slovak Republic 91.1 87.0 109.2 94.7 131.7 81.2 98.3 56.4 107.6 169.3 Slovenia 112.1 112.9 122.0 93.2 138.0 111.8 110.0 103.1 120.3 121.7 Spain 126.5 129.7 119.5 101.1 124.9 154.1 116.8 136.1 133.7 204.7 Sweden 175.1 177.2 154.6 162.1 178.5 186.8 142.8 186.4 173.0 108.3 Switzerland 209.6 225.3 199.8 147.5 189.5 328.1 152.1 259.2 170.0 164.7 Turkey 75.7 74.6 105.7 107.7 90.6 62.7 80.1 62.9 107.0 111.6 United Kingdom 144.2 146.7 123.1 180.9 113.7 203.0 122.8 140.9 145.7 131.7 United States 129.0 124.7 111.7 125.4 123.0 136.7 98.8 154.5 91.6 137.6 Total (47) 130.5 126.9 127.3 110.7 130.7 139.3 111.3 137.3 115.8 129.3 LATIN AMERICA Bolivia 54.8 50.3 70.9 62.6 74.9 25.3 60.6 62.0 48.3 98.5 Brazil 113.4 110.8 110.9 88.5 238.3 118.0 114.3 81.5 133.0 239.7 Colombia 81.1 77.3 97.6 81.0 118.3 47.6 106.2 72.2 91.3 143.1 Costa Rica 88.4 84.3 113.7 87.7 128.0 50.2 97.4 124.7 82.2 70.2 Cubae 41.5 36.7 52.9 63.6 48.5 14.4 58.7 31.6 46.1 77.3 Dominican Republic 65.8 63.2 82.1 86.4 88.6 52.0 82.0 60.3 82.3 79.5 Ecuador 67.9 64.6 88.1 69.9 104.1 45.3 87.5 59.5 53.1 102.6 El Salvador 64.9 62.4 88.7 83.9 109.7 40.7 83.7 63.9 52.9 72.4 Guatemala 60.1 58.5 83.7 87.5 86.5 43.7 53.4 62.7 59.9 96.6 Haiti 60.8 61.4 86.7 50.8 133.5 39.5 56.6 57.6 55.6 87.4 Honduras 67.7 65.2 84.1 65.5 122.2 45.0 76.3 74.2 68.7 129.5 Nicaragua 51.3 47.7 74.4 61.2 67.2 23.9 52.8 49.0 58.4 99.1 Panama 70.6 65.2 90.2 73.0 109.3 45.7 78.6 70.7 64.2 57.6 Paraguay 68.8 65.1 88.7 63.5 143.0 38.1 74.8 69.1 75.8 68.4 Peru 71.2 66.1 86.0 72.5 108.7 51.4 91.1 57.4 68.5 106.8 Uruguay 102.0 100.1 128.0 118.2 182.6 81.2 123.4 98.9 101.6 101.0 Venezuela, RB 81.6 79.1 152.4 142.6 252.4 28.8 175.8 74.8 48.5 90.4 Total (17) 97.1 93.5 105.3 88.7 178.3 78.8 109.3 78.3 101.2 152.4 120 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual consumption consumption consumption Gross consumption Recreation Restaurants Miscellaneous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 95.3 112.8 96.8 85.8 104.2 86.8 77.5 104.1 106.1 109.7 99.2 111.5 79.5 27.5 75.2 69.5 85.8 41.3 54.4 97.3 101.4 105.8 79.3 80.9 79.6 27.8 79.7 59.0 74.5 38.1 44.8 89.9 96.5 93.1 68.2 79.6 125.0 205.0 131.4 134.7 144.1 165.6 159.8 145.6 109.4 195.5 150.7 140.3 129.9 149.6 122.8 128.4 149.8 129.4 143.2 173.9 123.3 267.6 151.2 144.4 195.6 336.7 234.3 214.4 208.5 258.9 234.4 200.3 132.8 296.5 217.7 212.3 71.5 68.1 94.9 68.5 77.9 54.3 66.3 106.4 94.8 124.0 78.7 84.2 116.6 118.1 98.2 101.4 116.7 110.5 103.6 99.9 107.7 103.8 112.0 118.9 62.6 31.5 62.6 59.9 78.3 36.2 42.1 77.5 97.9 71.7 68.3 78.1 75.3 41.2 93.6 58.1 68.1 43.3 70.4 124.1 98.4 159.4 74.5 76.7 72.1 33.7 70.7 56.6 73.8 40.4 41.6 81.0 98.4 72.7 67.0 78.4 88.3 69.8 88.5 80.4 94.0 59.6 65.8 114.9 107.1 127.4 90.4 101.3 112.6 158.7 109.5 99.6 113.0 113.6 95.3 111.5 94.3 136.6 111.5 115.8 119.7 162.9 117.6 108.8 128.8 134.3 119.8 113.1 100.4 133.8 125.9 126.1 154.1 326.4 183.1 161.3 167.2 208.6 169.0 179.8 110.8 290.5 177.6 167.5 174.8 422.3 195.6 188.8 217.1 300.8 238.5 188.7 128.5 299.7 218.5 196.4 79.3 27.5 87.9 72.9 82.6 42.0 60.4 86.6 94.5 83.5 76.1 89.6 123.9 225.3 131.6 120.4 144.5 155.3 136.6 131.3 91.5 178.2 143.7 133.1 100.4 253.9 104.6 107.5 119.3 186.3 138.6 130.5 85.5 203.9 128.1 115.9 113.5 156.8 118.5 115.2 125.7 131.6 129.9 136.0 98.5 184.6 129.8 123.4 64.7 51.3 55.2 43.1 50.0 72.5 61.9 68.2 89.7 64.7 55.0 55.1 125.0 98.1 116.7 96.6 118.3 76.0 136.7 101.9 144.3 88.0 112.5 122.0 71.6 73.8 89.7 63.5 77.3 90.4 68.0 98.5 117.0 97.5 81.0 84.8 85.5 94.4 87.6 60.4 81.1 128.8 79.4 102.2 135.0 94.0 87.9 88.3 28.7 44.6 35.9 38.1 34.8 40.6 36.4 70.9 94.9 64.1 40.9 37.2 66.0 37.7 54.7 49.6 64.9 47.9 48.0 87.1 114.7 79.4 66.5 68.4 71.4 62.0 75.7 58.3 65.3 68.1 66.8 79.8 124.6 63.0 68.2 68.5 62.9 42.5 95.8 53.8 63.3 61.6 58.9 82.8 107.5 77.6 65.9 69.0 60.0 43.7 55.3 42.8 59.3 58.6 53.3 72.1 96.3 65.3 61.1 64.4 57.8 53.5 84.3 45.2 61.0 72.5 82.5 68.2 104.8 57.8 63.6 68.0 61.9 59.2 63.4 48.2 63.6 98.5 74.6 78.0 103.4 72.1 68.6 69.4 61.8 28.3 55.2 38.5 48.7 43.9 41.8 83.5 107.7 77.4 53.1 56.5 66.9 52.0 79.3 58.7 66.0 66.9 59.3 95.6 117.7 93.6 70.8 70.3 83.5 52.4 73.2 49.9 66.0 65.7 72.1 83.2 124.7 69.6 69.0 72.8 66.5 57.5 79.1 49.3 67.9 54.1 63.4 92.7 123.5 84.0 71.4 72.9 108.5 98.6 99.0 80.5 101.4 102.9 89.9 106.3 122.9 106.3 101.4 107.6 126.4 49.9 109.0 90.0 81.1 68.2 61.9 86.6 147.3 64.2 81.0 89.2 104.8 80.9 100.8 84.2 96.9 75.9 110.0 97.4 137.5 84.8 96.7 102.1 (continued) Presentation and Analysis of Results 121 Table 2.9 (Continued) Alcoholic Housing, Furnishings, PRICE LEVEL INDEX beverages, water, household (world = 100) Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) CARIBBEAN Anguilla 99.2 108.5 163.0 113.9 114.1 97.4 116.8 93.2 92.3 118.2 Antigua and Barbuda 82.7 89.2 139.6 95.1 104.3 72.6 110.5 59.4 122.2 121.4 Aruba 90.8 102.9 128.9 146.4 117.9 89.7 149.2 70.1 103.5 134.2 Bahamas, The 122.4 132.1 151.9 119.3 158.0 120.7 185.8 117.2 122.0 164.5 Barbados 130.0 139.5 149.9 160.0 115.9 132.8 134.5 105.5 112.3 162.5 Belize 74.1 68.9 107.9 154.0 93.4 38.0 87.1 65.3 101.9 85.4 Bermuda 201.6 220.7 205.0 140.2 182.5 355.4 208.7 191.0 136.6 154.1 Bonairef … … 148.3 118.0 81.2 … 129.2 … 115.8 165.2 Cayman Islands 147.6 155.9 177.6 186.2 153.8 157.2 188.5 167.1 130.5 169.4 Curaçao 93.1 92.7 116.8 110.8 142.2 73.5 121.5 74.4 94.7 148.3 Dominica 88.9 88.8 133.6 107.8 69.9 70.5 134.1 71.6 96.5 97.5 Grenada 85.2 87.9 137.8 112.1 125.8 65.1 126.0 69.8 103.1 105.5 Jamaica 81.3 84.1 133.6 122.4 86.2 62.8 98.5 71.9 97.3 73.8 Montserrat 92.8 99.0 163.8 128.5 112.1 65.3 158.1 87.8 122.3 91.2 St. Kitts and Nevis 86.1 88.8 156.0 110.5 95.7 64.0 174.8 54.5 119.2 147.9 St. Lucia 88.1 90.1 125.7 119.2 104.5 61.0 176.7 73.7 96.3 123.3 St. Vincent and the Grenadines 80.8 85.5 129.9 100.7 94.1 68.0 124.2 59.4 86.9 128.2 Sint Maarten 99.3 105.4 131.4 71.0 96.1 101.3 126.7 69.8 95.0 172.4 Suriname 72.1 65.3 113.3 91.0 69.9 36.5 100.2 45.1 96.1 90.5 Trinidad and Tobago 79.2 81.5 116.8 126.1 100.9 66.8 122.0 66.8 84.6 87.9 Turks and Caicos Islands 141.9 148.7 158.2 160.0 108.2 184.5 144.2 122.7 139.5 102.9 Virgin Islands, British 138.7 145.1 172.3 80.8 132.5 167.1 171.1 120.1 107.3 130.6 Total (22) 92.5 97.2 130.0 123.0 111.0 88.3 124.7 79.8 98.9 109.9 WESTERN ASIA Bahrain 72.0 70.8 89.1 75.7 86.9 67.6 81.4 88.4 41.7 66.2 a Egypt, Arab Rep. 35.1 33.6 64.3 59.1 42.4 16.3 52.1 21.5 35.3 44.0 Iraq 55.5 52.2 87.4 84.0 84.1 36.4 69.1 39.4 51.0 53.6 Jordan 53.3 51.7 89.1 64.9 52.3 32.8 60.5 37.3 56.6 66.8 Kuwait 80.4 82.8 94.7 87.3 104.6 58.9 97.6 109.7 47.3 119.8 Oman 64.2 62.8 89.2 68.6 70.6 58.2 64.9 56.5 44.4 82.6 Qatar 85.4 97.5 98.8 77.9 100.2 102.2 96.2 116.3 50.5 100.4 Saudi Arabia 63.2 60.7 88.8 69.1 68.5 39.4 66.7 64.9 42.8 82.2 Sudanb 59.2 62.7 100.7 107.1 41.4 57.7 66.1 31.1 78.4 82.2 United Arab Emirates 89.3 94.2 106.5 91.8 93.9 98.5 71.9 120.2 64.7 84.4 West Bank and Gaza 78.9 77.7 105.5 179.4 72.8 84.3 76.8 47.9 98.3 91.0 Yemen, Rep. 45.7 43.4 87.0 41.9 40.3 24.7 59.5 28.4 42.1 62.3 Total (12) 61.9 55.9 80.9 62.0 67.9 41.8 67.0 39.1 50.3 73.0 122 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual consumption consumption consumption Gross consumption Recreation Restaurants Miscellaneous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 135.4 71.1 125.1 110.5 114.5 78.8 71.4 76.1 98.6 75.2 98.7 117.2 109.0 51.8 84.4 81.7 97.2 49.9 51.4 76.5 109.5 73.1 82.8 110.4 115.5 92.2 150.0 90.4 110.1 72.2 60.4 69.9 79.1 75.6 91.0 121.6 114.0 140.5 120.0 120.6 137.3 111.9 69.2 104.1 113.7 116.1 119.1 143.0 119.8 128.6 161.2 115.7 143.9 126.7 75.2 98.7 110.2 106.0 125.0 139.8 91.4 57.9 90.2 72.5 70.5 74.1 56.4 120.3 115.2 148.4 74.7 91.1 180.1 182.3 217.7 179.0 226.7 200.8 158.6 126.1 97.6 209.0 190.8 189.6 … … 103.1 … 109.7 … … … … … … 119.0 148.5 126.6 138.9 142.0 161.8 136.8 118.4 123.9 126.3 145.1 146.1 159.1 103.5 88.0 118.6 82.8 95.2 86.4 62.1 107.1 109.4 126.7 93.5 110.4 98.8 68.3 91.9 87.7 91.4 84.9 72.7 98.3 110.8 105.1 89.4 102.0 109.1 46.4 99.2 76.0 92.4 66.8 55.9 97.0 109.1 103.3 86.7 106.3 95.5 59.9 99.1 80.0 88.0 66.3 60.9 89.6 112.9 87.3 83.0 100.1 104.1 64.5 96.1 92.6 103.2 79.5 68.1 84.1 112.2 81.6 93.8 121.1 108.7 33.3 89.0 82.4 98.1 42.1 40.8 106.2 115.6 114.6 87.0 115.4 103.6 59.7 150.3 88.8 94.5 70.3 61.0 95.9 115.3 100.5 88.9 108.8 97.5 55.4 134.8 82.0 90.1 63.2 56.3 85.5 117.3 81.3 83.0 100.7 93.2 80.6 125.0 104.8 111.8 71.4 65.7 88.3 84.3 114.2 98.3 117.4 68.7 66.6 69.1 59.0 68.8 49.7 50.8 87.0 107.1 76.3 72.2 73.5 77.4 53.6 102.4 65.8 86.0 59.7 44.8 73.5 86.6 76.0 76.6 85.1 130.6 157.5 156.8 129.0 153.0 144.3 95.9 153.6 112.0 226.8 146.0 147.2 135.3 164.1 161.5 131.1 149.1 144.4 97.3 150.2 115.0 226.1 143.8 139.8 96.9 68.3 116.2 86.4 102.1 72.5 65.2 91.1 103.3 96.3 93.0 105.5 58.6 87.6 63.9 59.3 68.0 98.3 81.7 65.1 90.6 60.4 71.5 59.9 33.4 21.6 42.3 28.6 36.1 17.7 19.1 58.9 95.4 47.6 35.3 40.7 59.1 35.6 65.6 70.3 57.0 35.2 36.7 75.7 80.9 83.7 53.7 63.4 52.4 44.4 68.2 49.9 53.7 41.6 38.3 68.6 85.5 68.4 53.1 60.6 83.5 123.9 112.2 100.7 78.0 124.6 109.0 72.4 89.8 75.4 84.1 72.9 61.5 70.4 72.3 54.2 62.1 71.4 64.6 58.2 85.6 49.5 62.4 58.6 87.7 160.2 106.3 87.8 86.3 164.2 134.7 62.1 82.6 51.5 89.3 75.3 60.9 82.1 64.9 55.5 56.8 83.2 70.7 53.6 74.8 47.6 60.8 57.3 62.5 41.5 51.2 54.4 66.5 29.6 31.2 61.6 106.3 45.7 58.7 68.8 90.4 131.9 105.2 86.1 88.3 165.2 136.8 64.4 76.3 65.9 91.4 81.4 70.9 56.3 103.1 76.1 84.1 52.6 55.0 89.7 97.9 94.8 76.0 88.1 42.2 32.1 34.7 41.8 45.8 29.0 27.5 63.0 79.3 68.7 44.6 50.3 56.8 54.8 65.3 49.3 56.1 58.0 53.5 60.1 81.0 55.2 58.8 57.1 (continued) Presentation and Analysis of Results 123 Table 2.9 (Continued) Alcoholic Housing, Furnishings, PRICE LEVEL INDEX beverages, water, household (world = 100) Gross Actual Food and tobacco, Clothing electricity, equipment domestic individual nonalcoholic and and gas, and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) SINGLETONS Georgia 65.7 52.1 92.2 54.6 104.3 19.2 73.4 36.8 73.4 52.0 Iran, Islamic Rep. 56.5 49.5 83.7 37.3 93.9 45.4 71.4 28.3 54.5 35.6 Total (2) 56.7 49.6 84.1 41.7 94.1 44.4 71.5 28.6 55.3 36.1 WORLDg (179) 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; ... = data suppressed because of incompleteness. a. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. b. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. c. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. d. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. e. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. f. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. g. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 124 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual consumption consumption consumption Gross consumption Recreation Restaurants Miscellaneous expenditure expenditure expenditure fixed Machinery expenditure by and and goods and by by by capital and Domestic households culture Education hotels services households government government formation equipment Construction absorption without housing (11) (12) (13) (14) (16) (17) (18) (19) (20) (21) (25) (26) 55.2 23.6 75.3 42.8 59.6 26.8 44.3 127.8 90.7 165.0 63.9 72.0 48.9 11.3 71.4 57.3 56.2 20.4 32.1 87.7 119.9 66.6 56.4 55.2 49.6 11.9 71.8 56.9 56.3 20.6 32.5 88.3 119.2 67.4 56.6 55.9 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Presentation and Analysis of Results 125 Table 2.10 Nominal Expenditures in U.S. Dollars, ICP 2011 NOMINAL Alcoholic Housing, Furnishings, EXPENDITURES beverages, water, household (US$, billions) Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and Commu- and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport nication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) AFRICA Algeria 198.5 89.3 26.8 1.5 2.6 4.4 2.2 6.3 10.8 5.1 2.3 8.5 Angola 104.2 63.3 26.0 2.7 3.2 6.6 3.5 3.3 3.4 0.7 1.4 3.1 Benin 7.3 5.9 2.8 0.2 0.2 0.6 0.2 0.2 0.4 0.2 0.1 0.3 Botswana 15.0 8.2 1.5 0.6 0.5 0.9 0.5 0.4 1.3 0.2 0.2 1.0 Burkina Faso 10.3 7.0 3.6 0.4 0.1 0.8 0.3 0.3 0.5 0.2 0.2 0.2 Burundi 2.1 1.9 0.8 0.3 0.0 0.3 0.0 0.1 0.1 0.0 0.0 0.1 Cameroon 26.6 20.8 9.6 0.5 1.7 1.9 1.9 0.3 1.7 0.3 0.3 0.5 Cape Verde 1.9 1.3 0.5 0.1 0.0 0.3 0.1 0.1 0.1 0.0 0.0 0.1 Central African Republic 2.2 2.0 1.2 0.2 0.1 0.1 0.1 0.0 0.1 0.0 0.0 0.1 Chad 12.1 8.3 4.0 0.4 0.2 0.8 0.6 0.6 0.8 0.3 0.2 0.1 Comoros 0.3 0.3 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Congo, Rep. 14.8 3.7 1.3 0.2 0.1 0.5 0.1 0.3 0.3 0.2 0.1 0.3 Congo, Dem. Rep. 25.2 16.2 8.9 0.5 0.8 1.9 0.6 0.7 0.4 0.2 0.2 0.7 Côte d’Ivoire 26.0 18.6 7.9 0.6 0.6 1.8 1.5 0.8 2.0 0.5 0.6 0.8 Djibouti 1.2 0.8 0.2 0.1 0.0 0.3 0.0 0.0 0.1 0.0 0.0 0.1 Egypt, Arab Rep.a 229.9 182.8 76.6 5.9 11.1 23.9 8.8 16.7 10.8 4.7 5.4 12.1 Equatorial Guinea 17.7 2.3 0.9 0.1 0.1 0.3 0.1 0.2 0.2 0.1 0.0 0.1 Ethiopia 29.9 24.2 9.0 0.6 1.2 4.0 2.3 2.0 0.4 0.1 0.1 0.8 Gabon 17.1 6.5 2.0 0.4 0.3 0.9 0.3 0.4 0.5 0.3 0.1 0.3 Gambia, The 0.9 0.7 0.3 0.0 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.1 Ghana 39.6 26.5 9.8 0.4 3.8 2.7 1.8 0.9 1.7 0.4 0.3 3.7 Guinea 5.0 2.8 1.6 0.0 0.2 0.2 0.1 0.2 0.2 0.0 0.0 0.1 Guinea-Bissau 1.0 0.7 0.3 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Kenya 34.3 30.1 10.3 1.5 0.7 2.3 1.4 2.2 3.1 0.9 1.0 4.3 Lesotho 2.5 2.8 0.7 0.1 0.3 0.3 0.2 0.1 0.1 0.1 0.1 0.3 Liberia 1.1 1.3 0.3 0.0 0.2 0.3 0.1 0.0 0.0 0.0 0.0 0.2 Madagascar 10.0 9.1 4.0 0.3 0.6 0.6 1.2 0.2 1.2 0.1 0.4 0.3 Malawi 7.3 7.2 3.5 0.3 0.2 0.8 0.7 0.3 0.6 0.1 0.2 0.4 Mali 10.6 7.1 3.3 0.1 0.4 0.7 0.4 0.3 0.9 0.2 0.3 0.3 Mauritania 4.6 2.7 1.6 0.0 0.1 0.3 0.1 0.1 0.1 0.1 0.0 0.2 Mauritius 11.3 8.9 2.6 0.7 0.5 1.4 0.7 0.4 1.2 0.3 0.6 0.7 Morocco 99.2 66.3 22.6 2.1 2.7 9.2 3.0 4.1 5.9 4.1 2.9 7.6 Mozambique 12.5 10.8 5.6 0.5 0.5 0.8 0.3 0.3 0.9 0.1 0.3 0.7 Namibia 12.5 8.9 1.8 0.4 0.4 1.7 0.6 1.0 0.4 0.1 0.4 1.3 Niger 6.4 5.1 2.1 0.1 0.4 0.5 0.2 0.2 0.4 0.1 0.3 0.2 Nigeria 247.0 159.0 60.1 2.2 23.0 16.3 11.2 5.1 10.6 2.5 1.7 20.3 Rwanda 6.3 5.5 2.6 0.2 0.2 0.9 0.2 0.1 0.4 0.1 0.1 0.3 São Tomé and Príncipe 0.2 0.3 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 126 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross Changes in Balance consumption Restaurants neous Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and goods and purchases by by by capital and Construc- Other and and Domestic households hotels services abroad households government government formation equipment tion products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 2.1 16.7 0.0 62.4 26.9 18.3 63.3 26.8 33.0 3.6 6.8 20.8 177.8 60.7 1.9 7.5 0.0 52.9 10.4 27.3 17.8 5.5 11.5 0.8 0.3 −4.5 108.7 51.4 0.5 0.2 −0.1 5.6 0.3 0.5 1.5 0.5 1.0 0.0 0.1 −0.7 8.0 5.2 0.3 0.7 0.0 7.1 1.1 1.8 4.9 2.0 2.8 0.1 1.0 −0.9 15.9 6.6 0.2 0.2 0.0 6.7 0.3 1.6 1.7 0.7 0.9 0.1 0.8 −0.7 11.1 6.3 0.1 0.0 0.0 1.8 0.1 0.3 0.4 0.2 0.2 0.0 0.0 −0.5 2.6 1.5 1.4 0.5 0.2 20.2 0.7 2.4 5.5 2.5 2.8 0.1 0.0 −2.1 28.7 19.0 0.2 0.1 −0.2 1.2 0.2 0.2 0.9 0.3 0.5 0.0 0.0 −0.5 2.4 1.0 0.0 0.1 0.0 2.0 0.1 0.1 0.3 0.1 0.2 0.1 0.0 −0.3 2.5 1.9 0.1 0.2 0.2 8.1 0.3 0.5 3.5 1.4 1.7 0.4 0.1 −0.3 12.5 7.5 0.0 0.0 0.0 0.3 0.0 0.1 0.0 0.0 0.0 0.0 0.0 −0.1 0.4 0.2 0.3 0.1 −0.1 3.3 0.4 0.7 5.1 0.8 4.2 0.0 0.0 5.3 9.5 3.1 1.0 0.4 0.0 15.6 0.6 2.9 5.9 2.2 3.5 0.2 0.0 0.1 25.1 14.6 0.3 0.8 0.2 17.6 1.0 2.0 2.9 1.0 1.7 0.1 −1.7 4.2 21.8 16.4 0.0 0.0 0.0 0.8 0.1 0.2 0.3 0.1 0.2 0.0 0.1 −0.3 1.4 0.6 5.8 13.0 −11.9 173.7 9.1 17.2 38.4 17.9 19.5 1.0 0.9 −9.5 239.4 157.6 0.1 0.1 0.0 2.1 0.2 0.3 5.9 3.0 1.9 0.9 0.0 9.3 8.5 2.0 1.1 2.6 0.0 23.5 0.7 1.9 7.8 2.9 3.5 1.4 0.6 −4.5 34.5 21.5 0.3 0.2 0.3 6.0 0.5 1.6 3.2 0.9 1.0 1.3 0.0 5.7 11.4 5.4 0.0 0.0 0.0 0.7 0.0 0.1 0.2 0.2 0.1 0.0 0.0 −0.1 1.0 0.7 0.0 1.0 0.0 24.3 2.2 4.4 10.1 5.7 3.8 0.6 0.7 −2.2 41.8 23.9 0.0 0.1 0.0 2.8 0.0 0.2 1.2 0.8 0.4 0.0 0.1 0.7 4.3 2.6 0.0 0.0 0.0 0.7 0.0 0.2 0.1 0.1 0.1 0.0 0.0 0.0 1.0 0.6 1.9 2.1 −1.6 26.0 4.1 2.9 6.9 3.8 3.1 0.0 0.2 −5.7 40.0 24.7 0.0 0.2 0.3 2.4 0.3 0.5 0.7 0.2 0.5 0.0 0.0 −1.5 4.0 2.2 0.0 0.1 0.0 1.3 0.0 0.1 0.1 0.1 0.0 0.0 0.1 −0.5 1.7 1.1 0.3 0.1 −0.1 8.8 0.3 0.7 1.7 0.8 0.9 0.1 0.0 −1.5 11.6 8.7 0.2 0.2 −0.2 6.8 0.4 0.5 1.2 0.9 0.2 0.1 −0.2 −1.4 8.7 6.3 0.1 0.2 −0.1 6.7 0.4 1.3 2.4 1.0 1.2 0.1 0.1 −0.2 10.8 6.3 0.0 0.0 0.0 2.4 0.3 0.7 2.6 1.3 1.1 0.2 −1.1 −0.3 4.9 2.2 0.3 0.6 −1.1 8.3 0.6 0.9 2.7 0.8 1.8 0.1 0.2 −1.5 12.7 7.7 3.8 4.3 −6.0 58.5 7.9 10.2 30.5 13.1 15.7 1.7 5.2 −13.0 112.2 52.9 0.1 0.5 0.1 10.0 0.8 0.9 2.2 0.8 1.5 0.0 0.3 −1.6 14.2 9.5 0.5 0.8 −0.3 7.7 1.2 1.9 2.7 1.0 1.6 0.1 −0.2 −0.9 13.4 6.6 0.3 0.3 0.0 5.0 0.2 0.6 2.4 1.0 1.3 0.1 0.0 −1.8 8.2 4.7 0.1 6.0 0.1 148.4 10.6 21.7 25.4 14.4 9.5 1.5 0.0 40.8 206.2 146.0 0.2 0.2 0.1 5.3 0.2 0.6 1.4 0.3 1.0 0.1 0.0 −1.1 7.4 4.7 0.0 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 −0.1 0.4 0.3 (continued) Presentation and Analysis of Results 127 Table 2.10 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURES beverages, water, household (US$, billions) Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and Commu- and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport nication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) Senegal 14.3 11.9 5.8 0.2 0.4 2.3 0.7 0.3 0.6 0.6 0.2 0.6 Seychelles 1.1 0.6 0.3 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.1 Sierra Leone 2.9 2.6 1.0 0.1 0.2 0.2 0.1 0.4 0.1 0.1 0.1 0.2 South Africa 401.8 274.4 48.6 12.1 11.8 37.4 16.8 30.4 35.5 7.1 11.2 29.3 Sudanb 70.0 49.1 25.4 0.3 2.2 7.2 3.2 0.6 4.0 0.8 1.1 1.6 Swaziland 4.1 3.7 1.7 0.0 0.2 0.5 0.4 0.2 0.3 0.0 0.2 0.3 Tanzania 23.9 16.3 10.8 0.1 1.1 1.2 0.7 0.6 0.6 0.0 0.2 0.8 Togo 3.7 3.3 1.4 0.1 0.2 0.3 0.1 0.2 0.2 0.1 0.0 0.2 Tunisia 46.0 34.2 7.5 1.1 2.4 4.8 2.1 2.4 4.9 1.2 1.1 2.7 Uganda 18.2 16.5 5.5 1.0 0.5 3.0 0.9 0.5 1.0 0.3 1.0 1.8 Zambia 20.8 11.5 6.7 0.1 0.7 1.4 0.2 0.6 0.2 0.3 0.1 0.7 Zimbabwe 8.9 8.5 4.7 0.3 0.5 0.5 0.2 0.2 0.6 0.0 0.2 0.6 Total (50) 1,870.4 1,251.8 436.5 39.5 77.5 148.1 71.1 84.9 109.5 32.7 35.3 109.0 ASIA AND THE PACIFIC Bangladesh 130.9 98.4 50.1 2.0 5.9 16.9 3.2 3.6 4.1 0.5 0.7 5.3 Bhutan 1.8 1.0 0.3 0.0 0.1 0.2 0.0 0.1 0.1 0.0 0.1 0.1 Brunei Darussalam 16.7 4.0 0.7 0.0 0.2 0.5 0.2 0.2 0.6 0.2 0.3 0.7 Cambodia 12.8 10.8 5.0 0.4 0.2 1.6 0.2 0.8 0.8 0.0 0.3 0.7 c China 7,321.9 3,141.9 590.4 67.7 217.2 435.5 153.3 471.3 183.6 106.7 170.7 316.1 Fiji 3.8 2.9 0.9 0.1 0.1 0.7 0.3 0.1 0.2 0.0 0.1 0.2 Hong Kong SAR, China 248.7 165.7 18.0 1.8 7.2 31.5 9.2 13.9 11.6 3.6 18.6 5.8 India 1,864.0 1,103.0 310.4 33.0 77.6 141.8 41.1 51.3 165.8 11.4 16.6 49.4 Indonesia 846.3 492.7 186.4 8.5 18.4 100.3 13.3 16.5 33.7 9.5 9.6 36.4 Lao PDR 8.1 4.7 2.4 0.2 0.1 0.6 0.1 0.1 0.5 0.1 0.1 0.2 Macao SAR, China 36.8 8.6 0.8 0.1 0.5 1.3 0.2 0.6 0.7 0.2 0.9 0.6 Malaysia 289.0 155.1 26.4 2.3 2.8 22.9 6.8 9.1 20.4 9.3 6.1 16.3 Maldives 2.2 0.8 0.2 0.0 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.1 Mongolia 9.9 6.0 1.7 0.4 0.3 0.9 0.1 0.3 0.9 0.2 0.2 0.6 Myanmar 55.2 38.5 20.1 0.8 1.2 5.1 0.5 2.4 1.3 0.6 0.4 3.2 Nepal 19.6 15.7 8.8 0.5 0.4 2.0 0.3 0.7 0.5 0.2 0.4 0.9 Pakistan 222.2 188.7 83.4 1.8 8.8 36.6 6.2 11.7 12.1 3.1 2.1 9.0 Philippines 224.1 172.4 70.5 2.1 2.3 20.4 6.7 5.5 17.8 5.2 3.0 12.3 Singapore 265.6 113.8 7.1 2.1 3.0 20.8 5.7 9.6 14.2 2.1 12.3 10.6 Sri Lanka 59.2 45.4 19.2 3.4 1.4 6.2 1.1 2.4 3.5 0.9 0.6 2.5 Taiwan, China 465.2 299.8 35.3 6.0 12.7 49.6 13.3 28.6 31.2 10.7 28.6 26.1 Thailand 364.7 226.0 57.9 8.0 7.6 20.5 9.2 17.1 31.6 4.7 10.5 19.8 Vietnam 135.5 86.0 22.2 2.4 3.5 19.6 5.0 6.3 8.6 0.6 3.4 7.4 Total (23) 12,604.3 6,382.1 1,518.2 143.6 371.5 935.8 276.0 652.3 544.0 169.8 285.6 524.2 128 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross Changes in Balance consumption Restaurants neous Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and goods and purchases by by by capital and Construc- Other and and Domestic households hotels services abroad households government government formation equipment tion products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 0.1 0.5 −0.3 11.3 0.6 1.4 3.4 1.3 2.1 0.0 0.2 −2.6 16.9 10.0 0.0 0.0 0.0 0.6 0.1 0.2 0.4 0.1 0.2 0.0 0.1 −0.2 1.3 0.5 0.0 0.1 0.0 2.6 0.1 0.2 1.2 0.9 0.3 0.0 0.0 −1.2 4.1 2.5 5.7 31.2 −2.7 238.5 35.9 51.6 76.2 36.2 36.5 3.5 2.1 −2.5 404.3 212.9 1.1 1.3 0.3 48.7 0.4 4.4 15.6 8.2 7.4 0.0 1.8 −0.9 70.9 43.9 0.0 0.1 −0.2 3.5 0.2 0.4 0.4 0.1 0.2 0.1 0.0 −0.4 4.4 3.1 0.0 0.3 0.0 15.8 0.5 3.4 8.6 3.7 4.7 0.2 0.1 −4.6 28.4 15.7 0.3 0.3 −0.1 3.1 0.1 0.3 0.7 0.2 0.4 0.0 0.1 −0.6 4.3 3.0 3.2 2.1 −1.4 30.2 4.0 4.4 10.0 3.3 6.3 0.4 0.8 −3.4 49.4 26.5 0.5 0.7 0.0 15.0 1.5 0.3 4.5 1.3 3.0 0.2 0.1 −3.2 21.4 13.7 0.0 0.6 0.0 10.8 0.7 3.2 4.5 1.4 2.9 0.2 0.3 1.2 19.6 10.1 0.1 0.4 0.1 7.8 0.7 0.8 1.0 0.3 0.7 0.0 0.4 −1.8 10.6 7.5 34.5 97.7 −24.6 1,124.6 127.3 199.2 390.3 172.1 198.5 19.7 20.5 8.5 1,861.9 1,043.7 2.2 3.8 0.0 96.5 2.0 4.9 37.1 8.8 27.8 0.5 0.7 −10.2 141.1 87.7 0.0 0.0 0.0 0.8 0.1 0.2 1.2 0.5 0.7 0.0 0.0 −0.5 2.4 0.7 0.2 0.2 0.0 3.3 0.7 2.1 2.2 0.7 1.4 0.2 −0.1 8.5 8.2 2.9 0.5 0.3 0.0 10.2 0.6 0.5 1.5 0.7 0.7 0.0 0.1 0.0 12.8 9.1 160.0 269.5 0.0 2,515.6 626.3 457.8 3,338.0 957.3 2,106.3 274.4 196.0 188.2 7,133.7 2,267.9 0.1 0.1 0.0 2.7 0.2 0.2 0.7 0.4 0.3 0.1 0.1 −0.2 3.9 2.1 16.7 28.0 0.0 157.4 8.4 13.3 58.5 25.8 27.5 5.2 1.5 9.8 239.0 130.7 27.5 177.0 0.0 1,042.4 60.7 154.2 576.6 220.1 334.7 21.8 135.9 −105.7 1,969.7 945.8 35.3 24.7 0.0 462.2 30.6 45.7 270.5 44.6 219.3 6.6 25.5 11.9 834.4 402.1 0.1 0.1 0.0 4.6 0.2 0.6 2.9 0.9 1.4 0.6 0.1 −0.3 8.4 4.3 1.6 1.0 0.0 7.5 1.1 1.5 4.6 1.1 3.5 0.0 0.5 21.6 15.2 6.5 12.8 19.8 0.0 136.7 18.4 19.2 64.4 23.3 32.1 9.0 2.8 47.5 241.6 123.9 0.0 0.0 0.0 0.7 0.1 0.4 1.1 0.4 0.7 0.0 0.0 −0.1 2.3 0.4 0.1 0.3 0.0 5.4 0.6 0.7 4.7 2.8 1.7 0.2 1.2 −2.7 12.6 4.7 1.7 1.2 0.0 35.2 3.3 2.3 14.7 7.2 6.4 1.2 0.0 −0.4 55.6 32.4 0.3 0.7 0.0 15.1 0.7 1.3 4.0 0.9 2.3 0.9 3.1 −4.6 24.2 13.4 1.9 12.0 0.0 182.0 6.8 15.7 28.7 9.2 13.7 5.8 3.6 −14.5 236.8 167.2 6.1 20.5 0.0 164.7 7.7 14.0 42.0 16.1 20.9 4.9 3.9 −8.2 232.3 150.6 11.8 14.5 0.0 103.5 10.3 17.2 63.1 23.5 37.2 2.5 −3.2 74.6 191.0 85.7 1.7 2.6 0.0 41.3 4.1 4.6 16.0 4.9 10.1 1.0 1.7 −8.6 67.8 37.5 16.1 41.8 0.0 279.5 20.4 37.2 97.3 45.3 44.0 8.0 −0.2 31.2 434.1 238.2 17.7 21.3 0.0 199.3 26.7 32.9 97.5 65.4 30.7 1.5 2.0 6.2 358.5 185.1 3.8 3.1 0.0 79.9 6.1 8.0 40.3 10.5 27.5 2.3 6.9 −5.6 141.1 67.7 318.2 642.8 0.0 5,546.2 835.9 834.6 4,767.6 1,470.2 2,950.8 346.6 382.1 237.8 12,366.4 4,966.7 (continued) Presentation and Analysis of Results 129 Table 2.10 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURES beverages, water, household (US$, billions) Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and Commu- and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport nication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) COMMONWEALTH OF INDEPENDENT STATES Armenia 10.1 9.0 4.9 0.4 0.3 0.7 0.1 0.6 0.5 0.5 0.2 0.4 Azerbaijan 66.0 27.1 10.0 0.6 2.5 2.2 1.4 1.2 2.8 1.5 0.9 2.0 Belarus 53.0 30.1 9.5 1.8 1.9 2.3 1.4 2.7 2.5 1.3 1.6 2.6 Kazakhstan 188.0 90.9 18.5 2.0 5.4 19.7 3.6 7.1 9.7 3.6 4.5 7.6 Kyrgyz Republic 6.2 5.8 2.2 0.3 0.4 0.4 0.2 0.3 0.6 0.4 0.2 0.5 Moldova 7.0 7.9 2.2 0.5 0.5 1.0 0.6 0.3 0.8 0.3 0.3 0.7 Russian Federationd 1,901.0 1,096.6 277.8 75.3 83.1 106.8 45.0 87.0 113.2 42.2 59.9 61.0 Tajikistan 6.5 7.5 3.3 0.0 0.6 0.5 0.3 0.3 0.6 0.5 0.2 0.3 Ukraine 163.4 129.4 42.4 7.5 6.9 13.9 4.7 11.4 13.4 2.7 5.3 11.5 Total (9) 2,401.3 1,404.2 370.9 88.5 101.5 147.5 57.2 110.8 144.1 52.8 73.0 86.5 EUROSTAT-OECD Albania 12.6 10.8 4.1 0.3 0.4 1.3 0.7 0.6 0.5 0.2 0.3 0.4 Australia 1,490.0 957.3 82.9 29.4 26.9 188.2 36.8 121.4 83.7 19.9 96.0 78.9 Austria 416.0 274.3 23.0 7.9 13.7 49.1 14.9 28.9 30.6 4.5 26.6 21.9 Belgium 513.3 350.8 35.0 9.1 13.0 62.1 14.8 51.0 32.2 5.6 26.0 32.4 Bosnia and Herzegovina 19.0 17.8 5.1 1.1 0.7 2.3 0.9 1.5 1.5 0.5 0.9 1.0 Bulgaria 53.5 37.6 7.1 2.5 1.0 6.0 2.6 3.7 5.8 2.0 3.1 1.9 Canada 1,778.3 1,215.5 90.2 33.4 40.1 234.1 53.6 154.5 143.5 23.9 97.2 95.3 Chile 251.2 172.8 24.9 4.7 8.6 25.1 11.0 16.5 19.6 6.1 11.9 14.6 Croatia 61.7 43.6 8.3 2.8 1.9 7.7 2.3 5.2 4.2 1.4 4.4 3.5 Cyprus 24.9 19.0 2.3 0.8 1.1 3.3 0.9 1.6 2.0 0.6 1.5 1.9 Czech Republic 216.1 132.7 16.6 10.4 3.5 30.2 6.0 15.7 10.5 3.4 12.2 9.3 Denmark 334.3 230.7 18.2 5.7 7.4 46.5 8.0 30.0 19.6 2.7 20.0 21.2 Estonia 22.5 13.8 2.3 1.0 0.7 2.5 0.4 1.2 1.5 0.4 1.1 1.1 Finland 262.3 189.3 17.3 6.9 6.9 37.4 7.4 22.9 15.9 3.0 18.1 15.4 France 2,782.2 2,051.5 209.7 49.8 66.5 411.4 90.7 257.3 222.6 43.1 163.9 149.9 Germany 3,628.1 2,527.3 226.5 63.7 96.1 477.3 123.7 320.2 274.8 51.8 197.8 148.1 Greece 289.9 236.7 36.1 9.7 8.3 53.0 8.9 23.5 26.3 6.5 12.8 15.7 Hungary 137.5 88.2 12.9 5.6 2.1 16.4 3.2 10.0 9.7 2.8 6.7 6.1 Iceland 14.0 9.6 1.0 0.3 0.3 1.6 0.5 1.2 1.0 0.2 1.0 1.0 Ireland 226.0 137.9 10.5 5.7 4.3 25.7 4.5 20.3 13.5 3.1 8.1 10.8 Israel 258.2 179.5 23.6 3.7 4.3 35.8 9.0 15.4 23.1 5.8 11.3 18.5 Italy 2,197.0 1,607.2 193.8 36.8 101.8 300.5 96.6 192.4 170.9 32.4 108.8 95.4 Japan 5,897.0 4,272.2 481.6 95.3 111.0 888.8 176.2 452.4 377.9 120.6 320.7 215.8 Korea, Rep. 1,114.5 667.2 74.2 12.9 29.0 93.4 19.1 73.5 67.5 24.6 46.7 73.4 Latvia 28.1 19.7 3.4 1.3 0.8 4.0 0.7 1.4 2.5 0.5 1.6 1.3 Lithuania 43.0 31.7 6.6 2.1 1.7 4.4 1.6 3.1 4.1 0.7 2.0 2.1 Luxembourg 58.0 24.4 1.8 1.9 1.0 5.4 1.4 2.6 4.2 0.4 1.9 2.5 130 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross Changes in Balance consumption Restaurants neous Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and goods and purchases by by by capital and Construc- Other and and Domestic households hotels services abroad households government government formation equipment tion products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 0.1 0.3 0.0 8.5 0.5 0.8 2.6 0.4 2.1 0.1 0.1 −2.4 12.5 8.2 0.9 1.1 0.0 24.6 2.5 4.2 13.3 6.9 5.8 0.6 0.1 21.3 44.6 23.9 0.9 1.2 0.4 25.3 4.8 2.6 20.0 8.7 11.1 0.2 0.9 −0.6 53.6 24.4 3.1 6.0 0.0 80.4 10.5 9.6 39.4 11.3 25.6 2.4 8.0 40.2 147.9 66.7 0.2 0.2 −0.2 5.2 0.6 0.5 1.5 0.7 0.8 0.0 0.1 −1.7 7.9 5.1 0.1 0.7 0.1 6.8 1.1 0.3 1.6 0.5 1.0 0.1 0.1 −2.9 9.9 6.4 30.6 93.6 21.0 933.4 163.1 178.9 395.0 141.8 221.1 32.1 67.7 162.7 1,738.3 886.6 0.1 0.4 0.5 7.0 0.5 0.3 2.1 0.9 1.0 0.2 0.2 −3.7 10.2 6.9 2.8 7.0 −0.1 109.9 19.5 10.3 30.3 11.6 18.0 0.7 3.5 −10.2 173.6 103.1 38.9 110.6 21.8 1,201.0 203.2 207.6 505.9 183.0 286.5 36.4 80.8 202.9 2,198.5 1,131.2 0.3 0.6 1.1 10.2 0.6 0.7 4.2 0.9 3.2 0.1 −0.1 −2.9 15.6 9.3 55.9 140.6 −3.4 798.9 158.4 104.6 401.5 97.2 230.8 73.6 7.2 19.4 1,470.6 653.2 27.5 34.2 −8.7 227.8 46.5 32.4 88.3 33.7 45.8 8.7 8.5 12.4 403.5 197.0 16.0 49.6 4.1 270.6 80.2 45.3 106.3 39.7 57.0 9.6 6.6 4.3 509.1 228.7 1.1 1.6 −0.5 15.8 2.0 2.2 3.4 1.4 1.9 0.1 0.0 −4.4 23.5 14.7 2.3 2.3 −2.6 33.4 4.2 4.2 11.5 5.0 6.1 0.4 0.2 0.0 53.5 29.8 65.1 167.7 16.9 990.5 225.0 160.8 416.4 82.8 276.7 56.9 7.7 −22.1 1,800.4 798.2 7.3 23.2 −0.5 153.8 19.0 11.1 56.3 22.1 29.9 4.3 2.6 8.2 243.0 139.2 6.6 3.8 −8.3 37.0 6.6 5.6 11.8 3.8 7.1 0.9 0.7 0.0 61.7 32.7 2.7 1.6 −1.5 16.8 2.2 2.8 4.1 1.2 2.7 0.2 0.0 −1.1 25.9 14.7 8.7 11.3 −5.1 109.4 23.3 21.5 52.2 23.2 26.1 2.9 0.8 9.0 207.2 91.2 8.3 42.6 0.4 162.8 67.9 26.9 58.0 20.3 29.3 8.3 1.2 17.5 316.8 130.7 0.9 1.3 −0.6 11.4 2.4 1.9 5.3 2.5 2.7 0.2 0.7 0.8 21.7 9.7 8.9 29.6 −0.4 146.2 43.1 21.1 50.9 12.2 34.3 4.4 2.8 −1.9 264.2 120.3 109.9 287.1 −10.4 1,606.0 445.5 235.6 556.0 150.4 345.9 59.7 21.6 −82.4 2,864.7 1,322.2 114.9 382.9 49.6 2,082.9 444.3 250.1 657.8 251.9 366.1 39.8 4.4 188.6 3,439.5 1,755.0 26.1 21.3 −11.5 216.3 20.5 29.9 43.9 17.7 23.1 3.1 2.8 −23.5 313.3 180.7 5.0 11.3 −3.7 73.3 14.9 14.1 24.6 10.3 12.8 1.5 1.8 8.9 128.6 64.1 0.6 1.0 0.0 7.3 2.3 1.2 2.0 0.8 1.1 0.2 0.0 1.2 12.9 6.0 13.2 15.6 2.6 108.7 29.2 12.3 24.0 9.1 12.9 2.1 2.9 48.8 177.2 90.2 9.9 21.0 −2.1 147.9 31.6 27.9 52.8 16.9 25.5 10.3 −0.6 −1.3 259.5 119.8 135.9 161.9 −20.0 1,345.5 261.7 186.0 418.9 167.7 199.6 51.6 15.6 −30.7 2,227.7 1,137.9 228.4 771.7 31.7 3,568.4 703.8 501.6 1,213.8 473.8 572.0 168.1 −37.0 −53.7 5,950.7 2,831.5 46.6 97.4 9.0 591.3 75.9 95.2 306.9 108.5 173.9 24.5 22.7 22.5 1,092.0 526.4 0.8 1.3 0.0 17.5 2.2 2.8 6.0 2.5 3.3 0.2 1.0 −1.3 29.4 15.1 0.8 2.8 −0.3 27.0 4.7 3.4 7.8 2.6 4.6 0.6 1.4 −1.2 44.2 25.3 1.5 4.2 −4.6 18.4 6.0 3.7 10.8 4.0 6.1 0.7 1.5 17.6 40.4 14.3 (continued) Presentation and Analysis of Results 131 Table 2.10 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURES beverages, water, household (US$, billions) Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and Commu- and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport nication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) Macedonia, FYR 10.4 8.6 2.6 0.3 0.4 1.5 0.3 0.5 0.8 0.5 0.3 0.5 Malta 9.2 6.6 1.0 0.2 0.3 0.8 0.4 0.8 0.8 0.2 0.7 0.5 Mexico 1,170.1 848.3 180.8 20.4 23.2 159.8 44.1 53.3 145.0 28.8 35.7 44.0 Montenegro 4.5 4.1 1.4 0.2 0.1 0.6 0.4 0.3 0.5 0.2 0.2 0.2 Netherlands 832.8 519.8 43.7 11.5 19.9 92.0 22.0 65.1 47.5 15.5 42.8 42.1 New Zealand 161.5 115.9 13.9 5.0 4.3 22.5 4.8 14.2 11.5 3.1 10.7 9.3 Norway 490.5 271.1 24.5 7.9 9.9 40.1 10.6 36.2 27.8 4.8 27.2 20.7 Poland 515.5 368.4 58.8 20.1 13.7 76.3 14.1 35.5 31.3 9.2 28.1 27.5 Portugal 237.9 182.8 26.9 5.4 8.9 25.9 8.9 22.3 21.3 4.7 13.3 14.1 Romania 182.6 131.9 31.1 5.7 4.3 25.1 5.6 14.6 12.5 5.6 8.1 6.3 Russian Federationd 1,901.0 1,096.6 277.8 75.3 83.1 105.7 45.0 86.5 113.2 42.2 58.7 60.7 Serbia 43.8 39.3 9.3 1.9 1.3 7.7 1.3 4.1 4.6 1.5 2.0 2.0 Slovak Republic 95.9 63.6 9.8 2.6 2.3 14.2 3.3 6.0 4.3 2.0 5.8 4.0 Slovenia 50.3 35.1 4.5 1.7 1.7 6.0 1.9 4.0 4.6 1.0 3.1 3.1 Spain 1,454.5 1,031.1 123.3 25.9 46.7 184.3 42.0 119.2 101.3 24.4 85.4 75.4 Sweden 535.8 359.8 30.6 9.1 12.1 68.1 12.7 43.3 33.4 8.3 32.9 35.3 Switzerland 659.9 419.1 33.3 13.4 12.5 89.5 15.5 56.3 33.7 8.9 33.7 33.3 Turkey 771.7 608.1 132.6 19.4 30.9 110.8 45.2 46.6 95.1 16.6 25.5 30.2 United Kingdom 2,461.8 1,930.3 138.7 54.2 88.4 384.1 75.6 214.3 205.3 32.7 215.2 153.2 United States 15,533.8 11,667.0 698.4 207.6 366.0 1,962.8 429.5 2,300.0 1,079.1 246.7 996.1 930.9 Total (47) 49,253.0 35,226.8 3,462.0 892.4 1,283.1 6,391.4 1,479.4 4,951.2 3,543.0 823.7 2,827.8 2,532.5 LATIN AMERICA Bolivia 23.9 15.0 5.1 0.2 0.3 1.6 1.1 1.3 2.6 0.2 0.2 0.9 Brazil 2,476.6 1,693.7 244.4 30.5 71.1 227.0 113.8 189.3 229.4 54.4 79.1 144.9 Colombia 336.3 228.9 38.0 6.4 13.4 32.8 8.7 17.0 25.3 9.1 10.8 19.8 Costa Rica 41.0 31.8 6.4 0.3 1.4 2.0 1.9 3.9 5.7 0.7 3.1 3.2 Cubae … … … … … … … … … … … … Dominican Republic 55.6 49.4 12.0 2.9 1.6 7.3 1.8 3.1 6.4 2.1 1.1 2.2 Ecuador 79.8 53.5 10.8 1.3 2.2 7.3 3.8 4.4 6.0 2.9 2.7 5.5 El Salvador 23.1 22.8 5.8 0.4 1.2 3.8 2.2 1.8 2.0 0.8 1.0 1.1 Guatemala 47.7 42.9 16.6 0.7 2.2 5.4 2.4 2.9 3.1 3.1 1.3 1.8 Haiti 7.3 8.3 4.9 0.2 0.6 0.9 0.3 0.3 0.4 0.0 0.2 0.4 Honduras 17.7 15.2 4.5 0.5 0.7 1.9 0.6 1.5 1.5 0.5 0.6 1.3 Nicaragua 9.6 8.1 2.1 0.2 0.2 1.1 0.4 0.9 1.0 0.3 0.3 0.6 Panama 31.3 20.7 3.5 0.1 1.3 4.1 1.5 1.5 2.7 0.7 1.1 1.2 Paraguay 25.2 19.2 5.3 0.2 1.0 1.7 1.5 1.6 1.6 0.7 1.2 1.8 Peru 180.7 113.0 25.6 2.5 7.0 11.9 5.6 7.3 12.1 4.4 6.7 9.5 Uruguay 46.4 35.1 6.5 0.8 1.6 6.7 1.9 4.2 2.6 1.4 1.2 2.3 Venezuela, RB 316.5 192.1 41.4 5.7 8.8 9.4 11.0 17.3 25.5 10.7 12.2 16.2 Total (17) 3,719.1 2,549.6 432.8 53.0 114.5 324.9 158.5 258.2 327.7 92.0 122.8 212.6 132 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross Changes in Balance consumption Restaurants neous Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and goods and purchases by by by capital and Construc- Other and and Domestic households hotels services abroad households government government formation equipment tion products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 0.3 0.6 0.1 7.8 0.8 1.1 2.1 0.7 1.3 0.1 0.6 −2.0 12.4 6.9 1.1 0.8 −1.0 5.6 1.0 0.9 1.4 0.5 0.7 0.2 0.0 0.4 8.9 5.1 31.6 85.6 −3.9 776.0 72.3 63.9 254.8 78.4 171.1 5.2 17.8 −14.7 1,184.9 647.2 0.6 0.3 −0.8 3.7 0.4 0.5 0.8 0.3 0.6 0.0 0.0 −1.0 5.5 3.4 18.7 101.3 −2.1 377.8 142.1 90.6 148.6 45.8 84.0 18.7 2.3 71.5 761.3 317.7 6.8 12.2 −2.4 96.6 19.3 13.3 29.3 10.1 16.8 2.4 0.7 2.3 159.3 77.5 11.2 42.8 7.5 201.9 69.2 36.2 95.7 30.9 45.5 19.3 22.5 65.1 425.4 172.1 8.9 47.2 −2.2 315.1 53.4 39.3 104.1 39.1 58.5 6.5 9.6 −5.9 521.5 293.0 17.9 20.4 −7.3 157.1 25.8 21.6 42.8 12.7 26.3 3.8 1.1 −10.4 248.3 140.6 3.8 8.9 0.4 115.9 16.0 11.6 47.6 15.4 29.9 2.2 1.2 −9.7 192.3 100.2 30.6 96.7 21.0 933.4 163.1 178.9 395.0 141.8 221.1 32.1 67.7 162.7 1,738.3 887.7 0.8 3.3 −0.5 33.7 5.6 2.9 8.1 3.4 4.1 0.5 0.7 −7.2 50.9 29.1 2.7 6.7 0.0 55.2 8.4 8.9 22.2 7.4 10.0 4.8 0.7 0.5 95.4 50.2 2.0 3.5 −2.0 28.9 6.2 4.3 9.3 4.0 4.6 0.7 0.8 0.8 49.5 25.6 150.8 98.4 −45.8 851.9 179.2 130.4 301.2 87.5 154.3 59.4 7.1 −15.3 1,469.8 727.6 14.1 62.1 −2.1 257.3 102.6 39.7 100.2 37.1 48.8 14.3 6.2 29.9 506.0 207.7 25.2 63.8 0.0 378.3 40.8 31.9 135.7 59.5 61.5 14.7 4.7 68.5 591.4 303.3 35.7 44.6 −24.9 549.3 58.8 48.7 168.4 97.7 70.1 0.6 13.4 −66.9 838.6 467.6 127.3 231.3 10.0 1,589.5 340.8 199.2 353.5 71.9 202.3 79.4 16.0 −37.3 2,499.1 1,270.1 670.7 1,803.2 −23.8 10,711.8 955.2 1,570.9 2,828.2 1,014.6 1,295.0 518.6 36.4 −568.7 16,102.5 9,105.2 2,066.0 5,023.2 −48.7 30,241.8 4,985.0 4,299.8 9,644.7 3,321.1 5,007.5 1,316.1 286.6 −204.9 49,457.9 25,395.7 1.2 0.4 0.0 14.6 0.4 2.9 4.5 2.5 1.7 0.3 0.1 1.4 22.6 13.8 95.6 214.1 0.0 1,494.2 199.5 312.6 477.5 249.9 197.7 29.8 11.1 −18.2 2,494.8 1,339.1 23.9 23.6 0.0 206.3 22.5 30.5 79.3 27.5 48.9 3.0 0.6 −2.9 339.2 185.4 1.5 1.5 0.3 26.8 5.0 2.4 8.1 3.5 4.4 0.2 0.7 −2.0 43.0 25.9 … … … … … … … … … … … … … … 4.0 5.2 −0.3 48.1 1.3 2.8 9.1 2.6 6.3 0.1 0.1 −5.7 61.3 43.2 2.2 4.9 −0.3 48.7 4.8 5.3 20.8 6.7 5.9 8.1 2.4 −2.2 82.0 43.3 1.5 1.3 −0.1 21.6 1.2 1.4 2.9 1.5 1.4 0.0 0.4 −4.3 27.5 19.3 2.5 1.8 −0.8 40.7 2.3 2.7 7.0 3.7 3.3 0.0 0.2 −5.1 52.8 36.5 0.0 0.2 0.0 8.2 0.1 0.0 2.1 0.1 2.1 0.0 0.0 −3.1 10.5 7.9 0.8 0.9 0.0 13.8 1.5 1.4 4.3 2.4 1.7 0.2 0.3 −3.5 21.2 12.8 0.5 0.6 −0.1 7.5 0.6 0.8 2.2 0.8 1.2 0.2 0.1 −1.5 11.2 6.8 1.1 1.9 0.0 18.9 1.8 2.0 8.2 3.7 4.5 0.0 0.3 0.1 31.2 15.9 0.9 1.5 0.0 17.7 1.5 1.2 4.1 1.8 2.0 0.3 0.1 0.6 24.6 17.2 10.0 10.3 0.0 107.5 5.5 11.1 47.0 16.9 28.6 1.5 1.9 7.8 173.0 99.3 2.4 2.8 0.7 31.5 3.5 2.6 8.8 2.8 5.5 0.6 0.2 −0.2 46.7 26.5 23.1 9.9 0.8 174.6 17.5 19.0 56.1 25.4 28.7 2.0 16.9 32.4 284.0 167.8 171.3 280.9 0.2 2,280.6 269.0 398.5 742.0 351.8 343.8 46.4 35.4 −6.5 3,725.6 2,060.6 (continued) Presentation and Analysis of Results 133 Table 2.10 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURES beverages, water, household (US$, billions) Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and Commu- and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport nication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) CARIBBEAN Anguilla 0.3 0.3 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Antigua and Barbuda 1.1 0.8 0.1 0.0 0.0 0.2 0.0 0.1 0.1 0.0 0.0 0.0 Aruba 2.6 2.0 0.2 0.0 0.1 0.7 0.1 0.2 0.2 0.1 0.1 0.1 Bahamas, The 7.9 6.0 0.6 0.1 0.2 1.9 0.3 0.5 0.5 0.2 0.3 0.4 Barbados 4.4 3.9 0.5 0.1 0.1 2.0 0.1 0.2 0.3 0.2 0.1 0.2 Belize 1.5 1.1 0.2 0.0 0.1 0.3 0.1 0.1 0.1 0.0 0.1 0.1 Bermuda 5.6 4.3 0.4 0.1 0.1 1.2 0.2 0.4 0.3 0.1 0.2 0.3 Bonairef … … 0.0 0.0 0.0 … 0.0 … 0.0 0.0 … … Cayman Islands 3.2 2.4 0.1 0.0 0.1 0.8 0.1 0.1 0.2 0.1 0.1 0.1 Curaçao 3.0 2.3 0.2 0.0 0.2 0.7 0.1 0.2 0.2 0.1 0.1 0.1 Dominica 0.5 0.4 0.1 0.0 0.0 0.1 0.0 0.0 0.1 0.0 0.0 0.0 Grenada 0.8 0.8 0.1 0.0 0.0 0.1 0.0 0.0 0.1 0.1 0.0 0.0 Jamaica 14.5 13.5 3.8 0.2 0.2 1.8 0.7 0.8 1.9 0.4 1.2 1.0 Montserrat 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 St. Kitts and Nevis 0.7 0.5 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 St. Lucia 1.2 1.0 0.2 0.0 0.1 0.2 0.1 0.1 0.1 0.1 0.0 0.1 St. Vincent and the Grenadines 0.7 0.6 0.1 0.0 0.0 0.2 0.0 0.0 0.1 0.0 0.0 0.0 Sint Maarten 1.0 0.6 0.1 0.0 0.0 0.3 0.0 0.0 0.1 0.0 0.0 0.0 Suriname 4.4 1.7 0.6 0.0 0.1 0.3 0.1 0.1 0.1 0.1 0.1 0.0 Trinidad and Tobago 23.5 13.7 2.9 0.1 0.2 1.7 0.6 1.1 1.5 0.3 0.9 1.4 Turks and Caicos Islands 0.7 0.3 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.0 Virgin Islands, British 0.9 0.4 0.1 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 Total (22) 78.4 56.7 10.5 0.8 1.5 12.8 2.6 3.9 6.1 1.8 3.4 4.1 WESTERN ASIA Bahrain 28.9 12.6 1.7 0.0 0.7 2.6 0.9 0.9 1.3 0.6 0.8 1.4 a Egypt, Arab Rep. 229.9 182.8 76.6 5.9 11.1 23.9 8.8 16.7 10.8 4.7 5.4 12.1 Iraq 159.8 75.2 23.0 0.4 4.5 19.6 3.5 5.4 5.5 1.1 0.9 8.3 Jordan 28.8 23.0 6.4 0.7 1.0 4.6 1.0 1.6 2.3 0.9 0.4 2.8 Kuwait 160.6 44.6 6.9 0.1 3.5 10.4 5.4 3.5 3.3 1.5 1.5 4.3 Oman 70.0 25.2 4.9 0.1 1.4 4.6 1.0 1.5 4.0 1.2 0.9 2.8 Qatar 171.0 28.3 3.0 0.1 1.0 6.4 1.2 2.1 2.4 0.6 2.1 4.3 Saudi Arabia 669.5 245.9 39.0 0.8 11.8 51.0 16.2 20.3 16.7 10.3 7.5 42.2 Sudanb 70.0 49.1 25.4 0.3 2.2 7.2 3.2 0.6 4.0 0.8 1.1 1.6 United Arab Emirates 348.6 184.0 21.6 0.3 22.7 61.0 6.5 2.8 29.6 10.7 5.0 8.6 West Bank and Gaza 9.8 10.6 3.3 0.4 0.6 1.1 0.5 0.8 1.0 0.3 0.3 0.9 Yemen, Rep. 31.4 22.9 10.4 1.1 1.0 3.3 0.7 2.2 1.3 0.2 0.1 1.6 Total (12) 1,978.3 904.3 222.2 10.4 61.5 195.6 48.9 58.4 82.2 32.9 26.0 91.1 134 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross Changes in Balance consumption Restaurants neous Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and goods and purchases by by by capital and Construc- Other and and Domestic households hotels services abroad households government government formation equipment tion products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 0.0 0.0 0.0 0.2 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.3 0.2 0.0 0.1 0.0 0.7 0.1 0.1 0.2 0.0 0.2 0.0 0.0 0.0 1.1 0.5 0.0 0.2 0.0 1.6 0.4 0.2 0.7 0.2 0.5 0.0 0.0 −0.4 3.0 1.2 0.3 0.9 0.0 5.6 0.5 0.7 2.1 1.0 1.1 0.0 0.1 −1.1 9.0 4.3 0.7 0.3 −0.9 3.6 0.3 0.5 0.7 0.3 0.3 0.0 0.0 −0.6 5.0 1.8 0.0 0.1 0.0 1.1 0.1 0.2 0.2 0.1 0.1 0.0 0.0 −0.1 1.5 0.8 0.5 0.6 0.0 3.7 0.6 0.5 1.1 0.6 0.5 0.0 0.1 −0.4 6.0 2.6 0.0 … 0.0 0.2 … … … … … … … … … 0.1 0.1 0.4 0.0 2.3 0.1 0.3 0.7 0.4 0.4 0.0 0.0 −0.2 3.4 1.6 0.1 0.5 −0.2 2.1 0.2 0.2 1.2 0.7 0.3 0.2 0.0 −0.8 3.8 1.7 0.0 0.0 0.0 0.4 0.0 0.1 0.1 0.1 0.1 0.0 −0.1 −0.1 0.6 0.3 0.0 0.1 0.0 0.7 0.1 0.1 0.2 0.1 0.1 0.0 0.0 −0.2 1.0 0.6 1.7 1.6 −1.8 12.4 1.1 1.2 3.0 1.5 1.5 0.1 0.1 −3.3 17.8 11.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.1 0.0 0.5 0.0 0.1 0.2 0.1 0.2 0.0 0.0 −0.1 0.8 0.4 0.0 0.1 0.0 0.9 0.1 0.1 0.4 0.1 0.2 0.0 0.0 −0.2 1.5 0.8 0.0 0.1 −0.1 0.6 0.1 0.1 0.2 0.0 0.1 0.0 0.0 −0.2 0.9 0.5 0.0 0.1 0.0 0.6 0.0 0.1 0.2 0.1 0.0 0.0 0.0 0.1 0.9 0.4 0.0 0.2 0.0 1.6 0.0 0.5 1.6 1.3 0.3 0.0 0.3 0.3 4.1 1.5 1.3 1.9 0.0 10.8 2.9 0.4 3.5 1.7 1.7 0.1 0.0 5.9 17.6 9.8 0.0 0.0 0.0 0.3 0.0 0.1 0.1 0.0 0.1 0.0 0.0 0.2 0.5 0.2 0.0 0.0 0.0 0.3 0.0 0.0 0.2 0.1 0.1 0.0 0.0 0.3 0.6 0.3 4.9 7.2 −3.0 49.9 6.8 5.6 16.7 8.3 7.9 0.4 0.6 −1.0 79.5 40.8 0.6 0.8 0.3 11.2 1.5 2.5 4.5 1.4 3.1 0.0 0.2 9.0 19.9 9.1 5.8 13.0 −11.9 173.7 9.1 17.2 38.4 17.9 19.5 1.0 0.9 −9.5 239.4 157.6 0.7 2.3 0.0 63.6 11.6 24.1 31.1 12.0 18.9 0.1 −0.7 30.2 129.6 49.7 0.5 0.7 0.1 20.6 2.4 3.2 6.2 1.6 4.2 0.4 0.5 −4.0 32.8 17.5 1.3 2.9 0.0 37.4 7.2 16.8 25.4 10.1 12.7 2.6 0.9 72.9 87.7 28.1 0.7 1.9 0.2 21.0 4.2 7.8 18.4 7.3 9.2 1.9 −2.2 20.7 49.3 17.5 0.6 4.0 0.6 21.8 6.5 14.9 50.1 24.5 7.8 17.7 0.0 77.7 93.3 16.0 9.3 12.0 8.8 181.8 64.1 66.0 151.7 58.5 75.2 17.9 27.6 178.2 491.3 146.0 1.1 1.3 0.3 48.7 0.4 4.4 15.6 8.2 7.4 0.0 1.8 −0.9 70.9 43.9 6.8 8.3 0.0 180.2 3.8 21.7 76.7 30.5 38.3 7.9 3.3 62.9 285.7 127.7 0.3 0.9 0.1 9.4 1.1 1.8 2.0 0.4 1.4 0.2 −0.3 −4.3 14.0 9.0 0.0 1.0 0.0 21.4 1.6 2.9 4.1 0.4 3.2 0.5 1.8 −0.3 31.7 19.7 27.5 49.1 −1.4 790.9 113.5 183.3 424.2 172.7 201.1 50.5 33.9 432.6 1,545.7 642.0 (continued) Presentation and Analysis of Results 135 Table 2.10 (Continued) NOMINAL Alcoholic Housing, Furnishings, EXPENDITURES beverages, water, household (US$, billions) Gross Actual Food and tobacco, Clothing electricity, equipment Recreation domestic individual nonalcoholic and and gas, and and Commu- and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport nication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) SINGLETONS Georgia 14.4 11.3 3.6 0.6 0.3 1.3 0.4 1.2 1.0 0.3 0.8 0.8 Iran, Islamic Rep. 576.3 255.9 62.1 1.2 11.0 73.7 9.5 20.8 18.7 8.0 6.2 8.1 Total (2) 590.7 267.2 65.6 1.8 11.2 75.0 9.9 22.0 19.8 8.3 7.0 8.9 WORLDg (179) 70,294.6 46,714.2 6,138.8 1,148.3 1,926.1 8,093.2 2,046.6 6,037.4 4,648.4 1,166.5 3,314.5 3,494.2 Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; ... = data suppressed because of incompleteness. a. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. b. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. c. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. d. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. e. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. f. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. g. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 136 Purchasing Power Parities and the Real Size of World Economies Individual Individual Collective Individual Miscella- consumption consumption consumption Gross Changes in Balance consumption Restaurants neous Net expenditure expenditure expenditure fixed Machinery inventories of exports expenditure by and goods and purchases by by by capital and Construc- Other and and Domestic households hotels services abroad households government government formation equipment tion products valuables imports absorption without housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 0.4 0.7 0.0 10.7 0.6 2.0 3.2 1.2 1.6 0.5 0.6 −2.7 17.1 10.1 3.0 27.2 6.5 240.8 15.1 48.4 147.9 66.9 76.5 4.4 62.7 61.5 514.8 181.2 3.3 27.9 6.5 251.5 15.7 50.4 151.1 68.1 78.1 4.9 63.3 58.8 531.9 191.3 2,627.2 6,131.5 −58.5 40,330.5 6,383.7 5,978.4 16,193.5 5,579.5 8,826.1 1,787.9 832.6 575.9 69,718.8 34,383.8 Presentation and Analysis of Results 137 Table 2.11 Nominal Expenditures Per Capita in U.S. Dollars, ICP 2011 Alcoholic Housing, Furnishings, beverages, water, household NOMINAL EXPENDITURES Gross Actual Food and tobacco, Clothing electricity, equipment Recreation PER CAPITA (US$) domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) AFRICA Algeria 5,518 2,483 745 43 72 121 62 176 300 141 63 237 Angola 5,311 3,224 1,323 140 163 338 180 169 173 33 69 158 Benin 801 647 312 19 27 66 17 22 47 20 10 33 Botswana 7,381 4,033 719 305 248 449 239 207 647 99 109 513 Burkina Faso 608 411 211 26 9 45 18 15 27 14 10 12 Burundi 240 224 98 31 2 35 2 6 15 3 2 12 Cameroon 1,327 1,040 478 27 86 95 96 16 85 16 16 24 Cape Verde 3,773 2,667 926 126 73 526 190 145 185 91 25 217 Central African Republic 486 449 258 41 32 22 23 7 16 4 8 13 Chad 1,053 723 348 34 16 68 48 51 68 27 17 10 Comoros 358 353 181 1 11 110 14 3 7 2 4 9 Congo, Rep. 3,575 885 325 36 24 116 31 69 72 46 24 66 Congo, Dem. Rep. 372 239 131 7 11 29 8 11 6 3 3 10 Côte d’Ivoire 1,291 922 392 29 32 90 76 39 101 26 32 39 Djibouti 1,276 912 274 71 27 285 51 29 57 3 11 59 a Egypt, Arab Rep. 2,888 2,297 962 75 139 300 111 210 136 59 68 152 Equatorial Guinea 24,621 3,168 1,201 72 96 448 120 297 254 119 59 155 Ethiopia 353 286 106 7 15 47 27 23 5 1 1 10 Gabon 11,114 4,236 1,273 239 214 607 193 291 355 188 96 222 Gambia, The 508 405 172 11 29 28 10 61 11 10 13 35 Ghana 1,585 1,060 394 15 151 107 74 36 69 16 11 146 Guinea 490 276 160 4 19 22 11 20 15 0 2 9 Guinea-Bissau 637 436 222 7 35 60 31 11 31 2 19 8 Kenya 825 722 247 35 18 56 33 52 73 22 25 104 Lesotho 1,151 1,270 325 34 158 133 110 55 42 36 44 120 Liberia 278 314 84 11 40 71 17 6 8 12 5 37 Madagascar 470 426 186 13 28 26 57 8 55 4 18 15 Malawi 476 470 229 23 12 51 48 19 37 8 11 24 Mali 672 449 209 6 26 44 27 18 59 10 18 20 Mauritania 1,295 758 457 7 25 72 21 30 33 29 7 56 Mauritius 8,611 6,804 1,969 567 397 1,050 544 337 916 207 443 543 Morocco 3,074 2,055 701 65 83 284 94 127 183 126 90 235 Mozambique 524 450 232 20 22 33 13 13 38 6 12 31 Namibia 5,369 3,841 769 155 184 734 275 424 156 31 152 539 Niger 399 320 134 7 25 32 15 13 24 7 18 10 Nigeria 1,520 979 370 14 141 100 69 31 65 15 11 125 Rwanda 579 503 241 17 17 83 16 13 32 6 8 26 138 Purchasing Power Parities and the Real Size of World Economies Individual Miscel- Individual Individual Collective consumption laneous consumption consumption consumption Gross Changes in Balance expenditure by Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports households and and purchases by by by capital and Other and and Domestic without hotels services abroad households government government formation equipment Construction products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 59 464 0 1,735 748 510 1,760 744 916 100 188 578 4,940 1,688 95 383 0 2,696 528 1,392 908 282 584 42 15 −227 5,538 2,618 60 20 −6 613 34 59 166 57 107 2 7 −78 879 571 160 337 0 3,502 531 866 2,423 999 1,394 29 494 −435 7,816 3,268 14 12 0 396 16 93 100 41 51 8 47 −43 651 373 9 5 4 208 17 31 46 20 23 3 2 −62 302 176 70 24 9 1,007 33 121 273 127 140 6 0 −107 1,435 948 327 167 −333 2,356 311 383 1,768 639 1,059 70 35 −1,079 4,853 2,055 9 17 0 437 12 22 75 21 40 13 0 −60 546 433 5 16 15 701 22 46 301 122 145 35 13 −30 1,082 650 0 11 1 351 2 82 48 21 24 2 13 −139 497 264 66 26 −17 795 90 172 1,232 200 1,020 11 0 1,286 2,289 740 14 6 0 230 9 43 88 32 52 3 0 1 370 215 13 42 10 872 50 102 144 51 86 7 −85 208 1,083 813 9 21 14 846 66 253 336 111 224 2 56 −281 1,557 686 72 163 −149 2,182 114 216 482 224 245 13 11 −119 3,006 1,980 108 173 65 2,956 213 448 8,136 4,167 2,657 1,313 0 12,869 11,752 2,715 13 30 0 278 8 22 91 34 41 16 7 −53 407 254 195 137 225 3,886 350 1,053 2,111 618 622 871 4 3,710 7,404 3,490 5 18 0 386 18 36 136 87 43 7 0 −69 577 376 0 40 0 974 87 177 406 230 151 25 30 −88 1,673 958 4 7 3 272 4 22 117 74 38 4 9 65 425 257 2 7 0 426 10 112 82 36 42 3 7 0 637 411 45 50 −38 624 99 69 165 91 74 0 4 −136 961 594 17 76 121 1,117 153 242 305 79 212 14 14 −680 1,831 1,024 2 22 0 313 2 34 36 31 4 0 18 −124 402 268 14 7 −4 413 13 34 82 36 42 4 0 −72 542 409 12 11 −14 443 27 33 79 59 16 5 −16 −90 566 411 8 11 −7 426 23 81 149 64 78 7 6 −12 684 396 5 14 0 671 87 197 744 366 312 66 −310 −94 1,389 627 234 427 −830 6,323 481 685 2,068 621 1,353 95 168 −1,113 9,724 5,861 119 134 −187 1,811 244 316 944 405 487 51 162 −403 3,477 1,638 4 23 5 418 32 38 93 32 62 0 11 −68 593 397 232 335 −146 3,313 528 831 1,143 419 685 39 −67 −379 5,748 2,834 16 19 0 309 11 40 148 65 79 3 0 −109 508 293 0 37 0 913 65 134 156 89 58 10 0 251 1,269 899 16 18 9 483 20 53 124 27 91 6 0 −101 680 429 (continued) Presentation and Analysis of Results 139 Table 2.11 (Continued) Alcoholic Housing, Furnishings, beverages, water, household NOMINAL EXPENDITURES Gross Actual Food and tobacco, Clothing electricity, equipment Recreation PER CAPITA (US$) domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) São Tomé and Príncipe 1,473 1,723 941 78 68 163 58 68 169 22 25 67 Senegal 1,123 930 456 12 32 179 52 27 46 45 12 49 Seychelles 12,196 7,400 2,939 204 316 1,318 315 488 447 140 181 775 Sierra Leone 490 440 174 14 35 33 12 70 14 12 15 34 South Africa 7,963 5,438 964 239 235 741 333 602 703 140 222 581 Sudanb 1,656 1,162 601 8 52 170 75 15 95 19 27 38 Swaziland 3,399 3,063 1,399 27 171 412 325 195 238 40 130 257 Tanzania 517 353 233 2 24 25 15 12 14 0 4 17 Togo 599 530 230 12 26 41 24 34 30 12 7 36 Tunisia 4,340 3,231 711 103 223 456 197 228 462 114 106 256 Uganda 528 478 159 28 14 86 27 13 28 9 29 51 Zambia 1,544 853 498 7 54 102 13 44 12 22 6 53 Zimbabwe 695 663 370 22 36 42 19 18 50 1 14 47 Total (50) 1,838 1,230 429 39 76 146 70 83 108 32 35 107 ASIA AND THE PACIFIC Bangladesh 874 658 335 14 39 113 21 24 28 3 5 36 Bhutan 2,600 1,343 393 34 99 236 24 150 128 33 83 118 Brunei Darussalam 42,432 10,124 1,838 53 442 1,219 438 559 1,512 548 771 1,668 Cambodia 902 760 348 29 15 113 14 54 57 2 21 51 c China 5,456 2,341 440 50 162 325 114 351 137 79 127 236 Fiji 4,393 3,369 995 112 82 828 295 173 261 14 162 197 Hong Kong SAR, China 35,173 23,433 2,540 248 1,024 4,448 1,297 1,967 1,638 504 2,624 824 India 1,533 907 255 27 64 117 34 42 136 9 14 41 Indonesia 3,511 2,044 773 35 76 416 55 68 140 39 40 151 Lao PDR 1,262 740 378 38 12 95 20 17 78 9 20 31 Macao SAR, China 66,063 15,444 1,476 106 951 2,357 310 1,101 1,338 433 1,590 1,120 Malaysia 9,979 5,354 911 79 98 790 235 315 705 322 211 562 Maldives 6,653 2,521 487 113 51 981 102 146 97 50 50 331 Mongolia 3,701 2,246 642 160 112 322 33 105 353 66 64 226 Myanmar 914 638 333 13 20 84 9 39 21 10 7 53 Nepal 739 594 333 19 15 77 11 25 19 8 15 34 Pakistan 1,255 1,066 471 10 50 207 35 66 68 18 12 51 Philippines 2,379 1,831 748 22 25 217 72 58 189 55 32 130 Singapore 51,242 21,960 1,369 401 582 4,007 1,108 1,852 2,748 411 2,377 2,039 Sri Lanka 2,836 2,178 922 162 65 296 53 113 169 41 30 120 Taiwan, China 20,030 12,910 1,520 257 549 2,135 572 1,231 1,342 459 1,230 1,123 Thailand 5,395 3,343 857 118 113 304 136 254 468 69 156 293 140 Purchasing Power Parities and the Real Size of World Economies Individual Miscel- Individual Individual Collective consumption laneous consumption consumption consumption Gross Changes in Balance expenditure by Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports households and and purchases by by by capital and Other and and Domestic without hotels services abroad households government government formation equipment Construction products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 22 32 12 1,657 66 113 290 218 52 21 2 −655 2,129 1,566 8 36 −25 882 48 111 267 102 163 2 16 −202 1,325 787 52 226 0 6,442 959 2,479 4,138 1,702 2,261 175 711 −2,532 14,728 5,606 5 21 0 429 11 39 204 145 57 2 2 −195 685 417 113 619 −54 4,726 712 1,022 1,510 718 723 69 42 −49 8,012 4,219 26 30 6 1,153 9 104 369 193 176 0 43 −22 1,678 1,040 19 49 −198 2,873 190 316 316 122 147 46 0 −295 3,694 2,548 0 7 0 342 11 73 186 80 102 4 3 −99 616 341 43 57 −22 508 22 49 106 32 69 5 11 −96 695 488 307 202 −134 2,849 382 417 940 307 597 35 76 −323 4,663 2,498 14 20 0 434 45 9 130 38 87 6 2 −91 619 396 2 42 0 801 52 241 334 101 218 15 22 93 1,451 751 4 33 5 608 55 61 77 26 51 0 32 −138 834 584 34 96 −24 1,105 125 196 384 169 195 19 20 8 1,830 1,026 15 25 0 644 13 32 248 59 186 3 5 −68 942 586 15 29 0 1,136 206 309 1,730 715 1,014 1 −10 −772 3,372 974 508 570 0 8,263 1,861 5,347 5,557 1,667 3,501 389 −284 21,688 20,744 7,342 36 21 0 718 42 33 105 51 52 1 5 −1 903 641 119 201 0 1,875 467 341 2,487 713 1,570 204 146 140 5,316 1,690 89 160 0 3,128 241 266 850 410 319 121 132 −224 4,617 2,470 2,355 3,962 0 22,251 1,181 1,879 8,267 3,644 3,887 735 213 1,380 33,792 18,483 23 146 0 857 50 127 474 181 275 18 112 −87 1,620 778 147 103 0 1,917 127 189 1,122 185 910 27 106 50 3,462 1,668 22 22 0 717 24 98 451 135 220 96 19 −46 1,308 676 2,923 1,739 0 13,547 1,897 2,779 8,198 1,900 6,222 75 951 38,690 27,372 11,687 442 685 0 4,719 635 663 2,225 804 1,110 311 98 1,639 8,340 4,278 45 68 0 2,145 376 1,190 3,350 1,293 2,057 0 0 −408 7,061 1,360 39 122 0 2,031 215 264 1,743 1,038 644 62 445 −998 4,698 1,755 29 19 0 582 55 38 244 119 106 19 0 −6 920 537 12 25 0 568 25 49 153 33 85 35 118 −175 914 507 11 68 0 1,027 38 89 162 52 78 33 20 −82 1,337 944 65 218 0 1,748 82 149 445 171 222 52 41 −87 2,466 1,599 2,272 2,793 0 19,964 1,996 3,310 12,178 4,535 7,167 477 −608 14,401 36,841 16,531 83 124 0 1,980 198 221 768 235 485 48 81 −413 3,248 1,796 692 1,800 0 12,033 877 1,602 4,187 1,949 1,896 343 −10 1,341 18,689 10,256 261 315 0 2,948 395 487 1,443 967 454 22 30 92 5,303 2,739 (continued) Presentation and Analysis of Results 141 Table 2.11 (Continued) Alcoholic Housing, Furnishings, beverages, water, household NOMINAL EXPENDITURES Gross Actual Food and tobacco, Clothing electricity, equipment Recreation PER CAPITA (US$) domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) Vietnam 1,543 978 253 27 40 224 56 71 98 7 39 84 Total (23) 3,527 1,786 425 40 104 262 77 183 152 48 80 147 COMMONWEALTH OF INDEPENDENT STATES Armenia 3,363 2,988 1,630 135 104 241 41 183 154 159 68 133 Azerbaijan 7,285 2,989 1,103 70 277 239 149 128 312 168 103 220 Belarus 5,596 3,174 1,004 193 201 246 144 285 264 136 169 270 Kazakhstan 11,358 5,491 1,119 122 324 1,189 217 430 589 215 270 461 Kyrgyz Republic 1,178 1,103 417 50 79 81 39 57 116 71 46 89 Moldova 1,971 2,215 622 129 128 285 157 78 222 81 71 184 Russian Federationd 13,298 7,670 1,943 527 581 747 315 609 792 295 419 427 Tajikistan 846 974 431 3 83 59 33 44 76 59 20 41 Ukraine 3,575 2,830 927 164 150 304 104 248 294 58 116 251 Total (9) 9,870 5,772 1,525 364 417 606 235 455 592 217 300 356 EUROSTAT-OECD Albania 4,467 3,812 1,441 102 146 466 253 217 194 76 90 125 Australia 65,464 42,056 3,643 1,293 1,181 8,267 1,619 5,333 3,679 876 4,217 3,466 Austria 49,590 32,703 2,748 942 1,635 5,858 1,781 3,441 3,650 542 3,169 2,611 Belgium 46,759 31,959 3,185 828 1,187 5,661 1,352 4,649 2,930 507 2,366 2,947 Bosnia and Herzegovina 4,957 4,631 1,337 295 183 586 242 395 392 129 226 262 Bulgaria 7,284 5,120 960 337 142 815 354 498 793 276 417 258 Canada 51,572 35,250 2,615 969 1,163 6,790 1,555 4,480 4,160 693 2,818 2,765 Chile 14,546 10,009 1,440 272 497 1,454 635 955 1,134 352 687 846 Croatia 14,429 10,199 1,940 650 440 1,797 536 1,206 985 333 1,032 811 Cyprus 29,208 22,349 2,725 946 1,264 3,927 1,060 1,923 2,402 708 1,804 2,199 Czech Republic 20,592 12,642 1,585 992 329 2,881 568 1,494 1,002 326 1,161 881 Denmark 60,030 41,430 3,269 1,017 1,331 8,354 1,438 5,392 3,520 491 3,592 3,809 Estonia 16,821 10,305 1,692 777 550 1,855 321 932 1,096 318 794 814 Finland 48,686 35,144 3,209 1,282 1,280 6,940 1,382 4,244 2,949 552 3,368 2,859 France 42,728 31,505 3,221 764 1,021 6,318 1,392 3,951 3,419 661 2,517 2,302 Germany 44,365 30,903 2,769 779 1,175 5,836 1,512 3,915 3,360 634 2,419 1,811 Greece 25,654 20,948 3,196 858 736 4,687 784 2,081 2,329 576 1,133 1,387 Hungary 13,790 8,841 1,289 559 215 1,644 325 1,004 974 281 677 609 Iceland 43,969 30,161 3,200 931 917 4,962 1,524 3,766 3,262 505 3,007 3,070 Ireland 49,383 30,131 2,295 1,256 943 5,608 982 4,444 2,956 671 1,780 2,349 Israel 33,259 23,118 3,041 480 556 4,618 1,157 1,982 2,976 742 1,461 2,388 Italy 36,180 26,467 3,191 606 1,676 4,949 1,590 3,168 2,815 534 1,792 1,571 Japan 46,131 33,421 3,768 746 868 6,953 1,378 3,539 2,957 943 2,509 1,688 Korea, Rep. 22,388 13,403 1,490 260 583 1,876 383 1,476 1,356 494 938 1,475 142 Purchasing Power Parities and the Real Size of World Economies Individual Miscel- Individual Individual Collective consumption laneous consumption consumption consumption Gross Changes in Balance expenditure by Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports households and and purchases by by by capital and Other and and Domestic without hotels services abroad households government government formation equipment Construction products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 43 36 0 909 69 91 459 119 313 27 78 −64 1,607 771 89 180 0 1,552 234 234 1,334 411 826 97 107 67 3,460 1,390 35 94 11 2,814 174 261 875 146 706 23 33 −794 4,157 2,716 95 125 0 2,714 275 463 1,470 761 644 65 7 2,356 4,929 2,635 92 131 40 2,667 507 273 2,115 922 1,175 18 95 −60 5,656 2,577 189 365 1 4,858 634 578 2,378 685 1,548 145 485 2,426 8,932 4,028 43 46 −31 983 121 94 279 125 146 9 21 −319 1,498 964 34 192 31 1,903 312 85 459 145 277 37 17 −805 2,776 1,800 214 655 147 6,529 1,141 1,252 2,763 992 1,546 225 474 1,138 12,159 6,202 11 49 64 905 69 44 274 121 125 29 31 −477 1,323 890 62 153 −3 2,404 426 226 664 255 394 15 78 −222 3,798 2,256 160 455 90 4,936 835 853 2,080 752 1,178 150 332 834 9,036 4,650 96 214 394 3,587 226 246 1,477 311 1,133 33 −38 −1,030 5,497 3,299 2,455 6,176 −149 35,097 6,959 4,597 17,642 4,269 10,140 3,232 317 852 64,612 28,697 3,283 4,082 −1,036 27,158 5,546 3,863 10,521 4,023 5,463 1,036 1,019 1,484 48,106 23,482 1,459 4,519 371 24,651 7,309 4,123 9,687 3,620 5,193 874 601 388 46,371 20,835 291 418 −126 4,108 523 583 889 375 483 30 11 −1,157 6,114 3,835 313 316 −358 4,545 575 569 1,569 675 834 61 27 −2 7,285 4,059 1,889 4,864 490 28,724 6,525 4,663 12,075 2,402 8,024 1,649 224 −641 52,213 23,149 420 1,343 −27 8,909 1,100 645 3,262 1,280 1,733 250 153 477 14,070 8,058 1,533 886 −1,950 8,646 1,553 1,301 2,766 896 1,656 214 173 −10 14,439 7,644 3,226 1,904 −1,739 19,782 2,568 3,290 4,860 1,412 3,228 220 −20 −1,272 30,479 17,233 830 1,079 −486 10,422 2,220 2,049 4,969 2,206 2,488 275 78 854 19,738 8,692 1,497 7,653 67 29,229 12,201 4,825 10,417 3,650 5,270 1,497 213 3,147 56,884 23,461 652 950 −444 8,503 1,802 1,432 3,968 1,834 2,004 130 496 620 16,201 7,272 1,654 5,499 −75 27,141 8,003 3,914 9,452 2,267 6,360 825 527 −350 49,036 22,321 1,688 4,409 −160 24,664 6,841 3,619 8,539 2,310 5,313 916 331 −1,266 43,994 20,306 1,405 4,682 607 25,470 5,433 3,059 8,043 3,080 4,476 487 54 2,306 42,059 21,460 2,307 1,887 −1,013 19,138 1,810 2,649 3,887 1,569 2,046 272 246 −2,076 27,729 15,990 500 1,133 −370 7,348 1,493 1,409 2,470 1,035 1,287 148 179 891 12,900 6,433 1,878 3,174 −35 22,806 7,355 3,808 6,195 2,356 3,367 473 125 3,680 40,289 18,878 2,881 3,400 565 23,746 6,384 2,694 5,251 1,982 2,817 452 639 10,668 38,715 19,706 1,279 2,709 −272 19,051 4,067 3,594 6,796 2,177 3,287 1,331 −83 −165 33,424 15,434 2,238 2,666 −330 22,158 4,309 3,064 6,898 2,761 3,288 849 257 −506 36,686 18,739 1,787 6,037 248 27,915 5,506 3,924 9,496 3,706 4,474 1,315 −289 −420 46,551 22,150 936 1,956 180 11,879 1,524 1,912 6,165 2,180 3,494 491 456 452 21,936 10,575 (continued) Presentation and Analysis of Results 143 Table 2.11 (Continued) Alcoholic Housing, Furnishings, beverages, water, household NOMINAL EXPENDITURES Gross Actual Food and tobacco, Clothing electricity, equipment Recreation PER CAPITA (US$) domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) Latvia 13,658 9,571 1,641 634 410 1,960 330 684 1,211 263 765 649 Lithuania 14,212 10,468 2,175 688 547 1,464 533 1,039 1,351 218 674 693 Luxembourg 111,689 46,959 3,533 3,634 1,981 10,446 2,723 5,075 8,175 718 3,639 4,897 Macedonia, FYR 5,050 4,181 1,284 127 187 731 155 264 376 222 132 222 Malta 22,201 15,901 2,367 465 633 1,888 1,063 1,890 1,971 586 1,685 1,135 Mexico 10,115 7,333 1,563 176 200 1,381 381 460 1,253 249 309 381 Montenegro 7,244 6,656 2,224 316 219 927 674 453 811 367 265 287 Netherlands 49,888 31,142 2,620 689 1,192 5,509 1,320 3,898 2,844 928 2,563 2,520 New Zealand 36,591 26,252 3,141 1,144 979 5,103 1,079 3,217 2,601 691 2,415 2,111 Norway 99,035 54,733 4,956 1,595 1,991 8,096 2,133 7,305 5,607 979 5,492 4,183 Poland 13,382 9,563 1,526 521 356 1,981 365 920 813 238 729 715 Portugal 22,396 17,213 2,536 510 840 2,442 833 2,100 2,003 445 1,255 1,331 Romania 8,549 6,175 1,456 266 201 1,175 261 686 584 263 380 295 Russian Federationd 13,298 7,670 1,943 527 581 740 315 605 792 295 410 424 Serbia 6,027 5,409 1,281 258 175 1,065 179 564 628 210 276 282 Slovak Republic 17,762 11,781 1,812 475 421 2,628 606 1,103 804 374 1,075 735 Slovenia 24,480 17,095 2,214 813 818 2,905 912 1,971 2,261 483 1,486 1,496 Spain 31,534 22,355 2,674 561 1,012 3,995 911 2,584 2,197 530 1,851 1,634 Sweden 56,704 38,081 3,237 962 1,284 7,202 1,339 4,585 3,534 881 3,477 3,730 Switzerland 83,854 53,258 4,231 1,697 1,588 11,376 1,970 7,159 4,283 1,135 4,281 4,232 Turkey 10,435 8,224 1,793 262 418 1,498 611 630 1,286 224 345 408 United Kingdom 39,241 30,769 2,211 863 1,410 6,122 1,205 3,417 3,272 521 3,431 2,442 United States 49,782 37,390 2,238 665 1,173 6,290 1,376 7,371 3,458 790 3,192 2,983 Total (47) 34,067 24,366 2,395 617 887 4,421 1,023 3,425 2,451 570 1,956 1,752 LATIN AMERICA Bolivia 2,360 1,478 499 23 32 157 105 128 253 16 15 90 Brazil 12,874 8,804 1,270 159 370 1,180 592 984 1,193 283 411 753 Colombia 7,142 4,860 807 135 284 697 185 361 538 193 229 420 Costa Rica 8,935 6,924 1,388 63 302 434 403 845 1,233 162 673 706 e Cuba … … … … … … … … … … … … Dominican Republic 5,541 4,926 1,195 292 160 730 176 307 636 208 107 218 Ecuador 5,226 3,505 711 87 141 475 247 285 391 188 179 360 El Salvador 3,701 3,644 930 72 192 611 345 291 317 125 165 168 Guatemala 3,247 2,922 1,132 47 153 367 161 196 209 212 89 121 Haiti 734 832 486 19 57 94 28 28 43 3 20 36 Honduras 2,282 1,961 580 62 86 242 79 192 187 62 73 170 Nicaragua 1,635 1,372 358 38 40 183 76 147 168 47 53 97 Panama 8,411 5,554 942 31 342 1,092 405 399 724 195 298 317 144 Purchasing Power Parities and the Real Size of World Economies Individual Miscel- Individual Individual Collective consumption laneous consumption consumption consumption Gross Changes in Balance expenditure by Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports households and and purchases by by by capital and Other and and Domestic without hotels services abroad households government government formation equipment Construction products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 397 629 −2 8,491 1,081 1,343 2,913 1,208 1,618 86 486 −655 14,313 7,353 257 915 −86 8,927 1,540 1,111 2,562 843 1,506 213 459 −387 14,599 8,341 2,840 8,174 −8,875 35,487 11,472 7,216 20,710 7,674 11,757 1,280 2,884 33,920 77,769 27,555 143 295 44 3,792 388 536 1,040 349 648 43 284 −991 6,041 3,351 2,579 2,038 −2,397 13,505 2,396 2,138 3,356 1,228 1,702 425 −51 857 21,344 12,255 274 740 −34 6,708 625 553 2,202 678 1,479 45 154 −127 10,242 5,595 983 452 −1,324 5,975 681 876 1,336 411 892 32 −18 −1,606 8,850 5,444 1,119 6,067 −127 22,632 8,510 5,425 8,900 2,746 5,034 1,120 139 4,283 45,605 19,035 1,545 2,758 −533 21,876 4,376 3,018 6,641 2,279 3,817 546 165 514 36,076 17,547 2,258 8,631 1,507 40,757 13,976 7,300 19,330 6,229 9,195 3,906 4,533 13,138 85,897 34,754 231 1,226 −57 8,178 1,386 1,020 2,703 1,016 1,519 168 249 −154 13,536 7,606 1,684 1,925 −691 14,786 2,426 2,034 4,028 1,199 2,474 355 100 −979 23,375 13,237 177 415 19 5,428 747 541 2,230 723 1,402 104 58 −455 9,004 4,692 214 676 147 6,529 1,141 1,252 2,763 992 1,546 225 474 1,138 12,159 6,209 107 454 −70 4,639 770 393 1,114 473 571 69 100 −989 7,016 4,010 509 1,233 6 10,233 1,548 1,652 4,109 1,362 1,855 892 123 97 17,665 9,297 994 1,706 −964 14,070 3,025 2,077 4,550 1,953 2,262 335 381 379 24,102 12,479 3,269 2,132 −994 18,470 3,886 2,827 6,531 1,898 3,346 1,287 153 −331 31,866 15,773 1,495 6,575 −221 27,228 10,854 4,202 10,602 3,930 5,162 1,510 658 3,161 53,543 21,976 3,199 8,107 0 48,070 5,188 4,050 17,244 7,560 7,816 1,868 600 8,704 75,150 38,542 483 603 −337 7,429 795 658 2,277 1,321 949 8 181 −905 11,340 6,323 2,028 3,687 160 25,337 5,433 3,176 5,636 1,146 3,225 1,265 254 −594 39,835 20,245 2,150 5,779 −76 34,329 3,061 5,034 9,064 3,252 4,150 1,662 117 −1,823 51,605 29,180 1,429 3,474 −34 20,918 3,448 2,974 6,671 2,297 3,464 910 198 −142 34,209 17,566 115 44 1 1,439 39 287 448 251 168 29 14 134 2,226 1,359 497 1,113 0 7,767 1,037 1,625 2,482 1,299 1,028 155 58 −94 12,968 6,961 508 501 1 4,381 479 648 1,684 583 1,037 63 13 −62 7,204 3,938 322 324 69 5,838 1,087 518 1,768 761 954 53 162 −438 9,373 5,650 … … … … … … … … … … … … … … 401 522 −27 4,795 131 277 903 256 633 14 7 −572 6,113 4,309 141 320 −20 3,192 313 348 1,360 441 386 533 157 −144 5,370 2,834 246 204 −21 3,452 192 217 464 234 228 2 67 −691 4,392 3,083 169 120 −55 2,769 154 181 478 250 227 1 14 −348 3,595 2,485 2 17 0 823 9 1 213 5 207 0 0 −312 1,046 789 107 121 0 1,772 190 177 558 310 218 29 36 −450 2,732 1,644 83 104 −21 1,272 101 140 369 142 197 30 13 −259 1,894 1,154 289 520 0 5,066 488 549 2,197 996 1,200 1 91 21 8,390 4,259 (continued) Presentation and Analysis of Results 145 Table 2.11 (Continued) Alcoholic Housing, Furnishings, beverages, water, household NOMINAL EXPENDITURES Gross Actual Food and tobacco, Clothing electricity, equipment Recreation PER CAPITA (US$) domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) Paraguay 3,836 2,920 807 37 152 264 236 237 250 108 189 271 Peru 6,066 3,792 858 84 236 400 188 245 405 148 226 319 Uruguay 13,722 10,363 1,915 243 466 1,978 574 1,249 764 409 349 675 Venezuela, RB 10,731 6,513 1,402 192 298 319 373 587 864 365 414 551 Total (17) 9,366 6,421 1,090 134 288 818 399 650 825 232 309 535 CARIBBEAN Anguilla 20,982 18,380 2,278 416 545 3,754 718 448 3,342 1,427 770 762 Antigua and Barbuda 13,172 8,975 1,386 146 205 2,462 386 802 939 461 291 505 Aruba 25,355 19,816 1,482 116 632 6,599 817 2,366 2,366 719 1,358 1,226 Bahamas, The 21,490 16,496 1,564 187 539 5,060 710 1,407 1,278 664 689 1,075 Barbados 15,483 13,790 1,908 212 252 7,192 377 638 956 578 508 679 Belize 4,721 3,587 650 56 281 898 235 265 461 114 235 191 Bermuda 85,839 67,145 5,816 1,156 1,333 18,618 3,181 5,524 4,109 1,819 3,849 4,935 Bonairef … … 1,222 67 522 … 658 … 1,935 584 … … Cayman Islands 56,883 42,553 2,590 489 1,258 14,655 1,994 1,930 3,977 1,824 2,063 2,121 Curaçao 20,055 15,378 1,624 187 1,166 4,905 463 1,173 1,448 589 682 634 Dominica 6,881 6,174 1,060 45 298 1,398 306 397 1,179 232 233 389 Grenada 7,410 7,204 1,419 127 315 1,394 295 290 1,306 699 192 446 Jamaica 5,248 4,883 1,370 66 88 662 272 295 695 132 433 361 Montserrat 11,343 10,808 1,700 223 133 2,025 448 1,093 2,886 696 322 640 St. Kitts and Nevis 13,744 10,290 1,695 283 439 2,700 650 600 929 532 363 556 St. Lucia 6,755 5,436 1,086 93 328 1,241 304 292 505 299 103 452 St. Vincent and the Grenadines 6,191 5,731 1,131 322 118 1,536 242 360 999 383 353 341 Sint Maarten 25,402 16,324 1,378 49 810 6,776 705 531 1,883 805 643 510 Suriname 8,082 3,098 1,155 83 109 528 149 152 237 112 111 40 Trinidad and Tobago 17,660 10,265 2,160 103 139 1,248 428 792 1,096 208 665 1,084 Turks and Caicos Islands 22,971 9,055 1,278 159 315 966 350 860 2,079 154 471 1,025 Virgin Islands, British 32,580 12,517 2,109 244 1,158 2,590 1,550 698 1,185 375 500 695 Total (22) 11,732 8,472 1,564 115 223 1,914 390 590 916 276 511 616 WESTERN ASIA Bahrain 24,200 10,580 1,421 39 603 2,158 751 768 1,103 492 679 1,174 Egypt, Arab Rep.a 2,888 2,297 962 75 139 300 111 210 136 59 68 152 Iraq 4,794 2,255 691 13 134 587 106 162 164 32 26 250 Jordan 4,615 3,681 1,027 117 161 738 157 257 372 144 60 452 Kuwait 52,379 14,541 2,236 33 1,126 3,393 1,776 1,145 1,068 484 506 1,407 Oman 21,234 7,647 1,490 19 431 1,394 295 446 1,220 362 262 852 Qatar 97,091 16,069 1,706 45 561 3,612 657 1,168 1,378 349 1,175 2,465 Saudi Arabia 23,594 8,667 1,374 30 417 1,798 571 717 587 362 264 1,489 146 Purchasing Power Parities and the Real Size of World Economies Individual Miscel- Individual Individual Collective consumption laneous consumption consumption consumption Gross Changes in Balance expenditure by Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports households and and purchases by by by capital and Other and and Domestic without hotels services abroad households government government formation equipment Construction products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 140 230 0 2,689 231 176 628 267 311 50 15 98 3,739 2,617 337 345 0 3,606 185 373 1,576 567 959 50 64 261 5,805 3,334 718 822 201 9,321 1,042 767 2,607 830 1,614 163 52 −67 13,789 7,818 785 335 27 5,919 593 643 1,903 863 972 68 573 1,100 9,631 5,689 431 707 1 5,743 678 1,004 1,869 886 866 117 89 −16 9,382 5,189 719 3,202 0 17,674 707 2,629 3,677 957 2,651 69 −328 −3,376 24,358 15,447 288 1,105 0 7,910 1,066 1,360 2,757 577 2,129 52 81 −1 13,173 6,398 454 1,681 0 15,734 4,082 2,415 6,692 1,653 5,040 0 403 −3,972 29,327 11,287 874 2,450 0 15,248 1,248 1,941 5,671 2,776 2,880 16 360 −2,978 24,468 11,692 2,540 1,133 −3,183 12,611 1,179 1,647 2,409 1,183 1,225 1 −138 −2,225 17,708 6,327 24 176 0 3,381 206 535 714 302 399 13 65 −179 4,901 2,566 7,811 8,994 0 57,654 9,491 7,079 17,377 8,989 8,351 37 959 −6,721 92,560 40,832 789 … 0 11,141 … … … … … … … … … 9,389 2,051 7,599 0 40,002 2,551 5,061 12,756 6,294 6,431 31 0 −3,487 60,369 28,763 474 3,188 −1,153 13,856 1,522 1,459 7,987 4,328 2,273 1,386 302 −5,071 25,126 11,050 169 469 0 5,630 543 936 1,584 765 789 30 −769 −1,043 7,924 4,704 126 520 75 6,665 539 622 1,513 590 895 28 −7 −1,922 9,332 5,887 599 576 −666 4,495 388 450 1,090 527 543 20 25 −1,201 6,450 4,095 34 1,157 −550 9,161 1,647 3,742 3,258 948 2,249 61 0 −6,465 17,807 8,092 585 957 0 9,409 880 1,476 4,250 1,055 3,116 79 2 −2,274 16,018 7,520 93 641 0 4,990 446 676 2,026 623 1,365 38 0 −1,384 8,139 4,249 180 486 −718 5,081 650 635 1,479 452 999 28 93 −1,747 7,938 4,184 269 1,966 0 15,346 978 3,232 4,264 2,311 1,213 740 0 1,582 23,820 10,249 39 383 0 3,022 76 921 2,990 2,456 478 56 562 512 7,570 2,844 945 1,396 0 8,090 2,176 297 2,649 1,306 1,287 56 0 4,449 13,211 7,319 334 1,065 0 8,235 820 4,375 3,329 1,163 2,166 0 17 6,195 16,776 7,692 676 737 0 11,436 1,081 1,682 7,790 3,445 4,105 239 −628 11,219 21,361 9,715 730 1,073 −445 7,460 1,012 833 2,495 1,248 1,180 67 86 −154 11,886 6,105 465 662 264 9,366 1,214 2,112 3,781 1,163 2,606 13 177 7,550 16,650 7,605 72 163 −149 2,182 114 216 482 224 245 13 11 −119 3,006 1,980 22 70 0 1,907 347 722 932 360 568 4 −21 906 3,888 1,490 75 107 13 3,296 385 510 989 259 669 61 73 −637 5,252 2,806 418 949 0 12,194 2,346 5,485 8,272 3,286 4,129 856 309 23,772 28,607 9,171 217 590 70 6,374 1,273 2,379 5,590 2,221 2,790 578 −657 6,275 14,959 5,302 318 2,273 361 12,399 3,670 8,462 28,453 13,926 4,450 10,077 0 44,107 52,983 9,088 327 422 311 6,407 2,260 2,326 5,345 2,062 2,652 631 974 6,282 17,312 5,146 (continued) Presentation and Analysis of Results 147 Table 2.11 (Continued) Alcoholic Housing, Furnishings, beverages, water, household NOMINAL EXPENDITURES Gross Actual Food and tobacco, Clothing electricity, equipment Recreation PER CAPITA (US$) domestic individual nonalcoholic and and gas, and and and Economy product consumption beverages narcotics footwear other fuels maintenance Health Transport Communication culture Education (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10) (11) (12) b Sudan 1,656 1,162 601 8 52 170 75 15 95 19 27 38 United Arab Emirates 42,182 22,267 2,610 41 2,749 7,381 788 344 3,581 1,301 608 1,039 West Bank and Gaza 2,345 2,537 802 101 147 276 131 185 238 77 61 214 Yemen, Rep. 1,318 963 435 46 42 137 29 92 55 10 4 68 Total (12) 8,403 3,841 944 44 261 831 208 248 349 140 110 387 SINGLETONS Georgia 3,231 2,531 795 133 64 287 95 265 232 75 177 175 Iran, Islamic Rep. 7,669 3,405 826 16 146 980 126 277 249 106 82 108 Total (2) 7,420 3,356 824 22 141 941 125 276 248 104 87 112 WORLDg (179) 10,438 6,937 912 171 286 1,202 304 897 690 173 492 519 Source: http://icp.worldbank.org/. Note: n.a. = not applicable; ... = data suppressed because of incompleteness. a. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The regional results for Egypt were averaged by taking the geometric mean of the regional PPPs, allowing Egypt to have the same global results in each region. b. Sudan participated in both the Africa and Western Asia regions. The regional results for Sudan were averaged by taking the geometric mean of the regional PPPs, allowing Sudan to have the same global results in each region. c. The results presented in the tables are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. d. The Russian Federation participated in both the CIS and Eurostat-OECD comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. e. The official GDP of Cuba for reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the tables because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. f. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean or the world total. g. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. 148 Purchasing Power Parities and the Real Size of World Economies Individual Miscel- Individual Individual Collective consumption laneous consumption consumption consumption Gross Changes in Balance expenditure by Restaurants goods Net expenditure expenditure expenditure fixed Machinery inventories of exports households and and purchases by by by capital and Other and and Domestic without hotels services abroad households government government formation equipment Construction products valuables imports absorption housing (13) (14) (15) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) (26) 26 30 6 1,153 9 104 369 193 176 0 43 −22 1,678 1,040 822 1,004 0 21,805 463 2,623 9,281 3,688 4,633 960 402 7,608 34,574 15,458 62 211 33 2,262 275 426 485 85 347 52 −80 −1,023 3,368 2,168 0 43 0 897 65 120 174 16 135 23 74 −14 1,331 825 117 208 −6 3,359 482 778 1,802 734 854 214 144 1,838 6,566 2,727 83 149 0 2,391 140 448 726 271 350 105 124 −599 3,829 2,250 39 362 87 3,204 201 643 1,968 890 1,018 59 835 818 6,851 2,411 42 350 82 3,159 197 632 1,898 856 981 62 795 739 6,681 2,402 390 910 −9 5,989 948 888 2,405 829 1,311 265 124 86 10,353 5,106 Presentation and Analysis of Results 149 Supplementary Table 2.12 Main Results and Reference Data, Pacific Islands, ICP 2011 INDIVIDUAL CONSUMPTION Expenditure Expenditure Price PPP Reference data EXPENDITURE BY per capita level HOUSEHOLD index (US$, millions) (US$) Exchange Population Expenditure rate in national Based on Based on Based on Based on (world = (US$ (US$ currency unit Economy PPPs XRs PPPs XRs 100.0) = 1.000) = 1.000) (thousands) (millions) (00) (01) (02) (03) (04) (05) (13)a (14)a (15) (16)b c PACIFIC ISLANDS American Samoad 469.0 432.0 7,032 6,478 109.9 0.921 1.000 66.69 432.0 Cook Islands 93.3 116.0 6,228 7,747 148.4 1.564 1.257 14.97 145.8 French Polynesia 3,351.8 4,272.1 12,330 15,716 152.0 119.593 93.830 271.83 400,850.5 d Guam 2,697.2 2,926.0 16,900 18,333 129.4 1.085 1.000 159.60 2,926.0 Kiribati 158.3 173.7 1,541 1,692 130.9 1.066 0.971 102.70 168.7 Marshall Islands 156.1 169.1 2,937 3,182 129.2 1.083 1.000 53.16 169.1 Micronesia, Fed. States 229.8 229.4 2,245 2,241 119.1 0.998 1.000 102.36 229.4 Nauru 69.2 86.1 6,860 8,540 148.5 1.209 0.971 10.08 83.6 New Caledonia 3,976.2 5,514.8 15,758 21,855 165.4 130.139 93.830 252.33 517,453.9 Niuee … … … … 164.2 1.730 1.257 1.61 … d Northern Mariana Islands 503.5 527.0 9,345 9,781 124.9 1.047 1.000 53.88 527.0 Palau 121.1 108.7 5,864 5,268 107.2 0.898 1.000 20.64 108.7 Papua New Guinea 7,284.5 7,325.3 1,032 1,038 120.0 2.138 2.126 7,059.65 15,573.5 Samoa 758.3 591.6 4,038 3,150 93.1 1.900 2.436 187.82 1,441.0 Solomon Islands 338.5 313.8 612 567 110.6 7.131 7.692 553.25 2,413.9 e Tokelau … … … … 115.6 1.218 1.257 1.21 … Tonga 436.3 407.8 4,225 3,950 111.5 1.639 1.753 103.25 714.9 Tuvalu 7.2 8.8 686 829 144.1 1.173 0.971 10.56 8.5 Vanuatu 367.7 462.2 1,460 1,836 149.9 115.827 92.150 251.78 42,591.0 e Wallis and Futuna … … … … 180.5 141.986 93.830 13.19 … Total (20) n.a. n.a. n.a. n.a. n.a. n.a. n.a. 9,332.71 n.a. ECONOMIES FOR REFERENCEf Australia 507.3 798.9 22,288 35,097 187.8 1.527 0.969 22.76 774.5 Fiji 3.9 2.7 4,611 3,128 80.9 1.217 1.793 0.85 4.8 New Zealand 76.9 96.6 17,425 21,876 149.8 1.589 1.266 4.41 122.2 Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; PPP = purchasing power parity; XR = exchange rate; ... = data suppressed because of incompleteness. a. All exchange rates (XRs) and PPPs are rounded to three decimal places. b. Data source: World Development Indicators (World Bank) or National Accounts Main Aggregates (United Nations). c. Results for the Pacific Islands are provided only for the individual consumption expenditure by households. d. Therefore, to ensure consistency across the tables, the Pacific Islands are not included in the world totals in the main results tables. e. Data source, expenditure: Bureau of Economic Analysis, U.S.Department of Commerce. No expenditure estimate is available for the economy. f. Data for the three economies involved in the linking of the Pacific Islands are shown for reference purposes only. Figures shown are from the main results tables for the respective economies. 150 Purchasing Power Parities and the Real Size of World Economies Supplementary Table 2.13 Estimated Results and Reference Data, Nonbenchmark Economies, ICP 2011 GROSS DOMESTIC Expenditure Expenditure Price PPP Reference data PRODUCT per capita level index (US$, billions) (US$) Exchange Population Expenditure rate in national Based on Based on Based on Based on (world = (US$ = (US$ currency unit Economy PPPs XRs PPPs XRs 100.0) 1.000) = 1.000) (thousands) (millions) (00) (01) (02) (03) (04) (05) (13)a (14)a (15)b (16)b c NONBENCHMARK ECONOMIES Afghanistan 49.3 17.9 1,695 614 46.7 17.356 47.919 29.11 856.3 Argentina 691.2 446.0 16,972 10,952 83.2 2.665 4.130 40.73 1,842.0 Eritrea 6.8 2.6 1,139 440 49.8 5.932 15.375 5.93 40.1 Guyana 4.6 2.6 5,808 3,258 72.3 114.435 204.007 0.79 525.7 Kosovo 14.6 6.6 8,146 3,706 58.7 0.327 0.719 1.79 4.8 Lebanon 72.0 40.1 16,437 9,148 71.8 838.986 1,507.500 4.38 60,442.2 d Libya 69.3 34.7 11,358 5,687 64.6 0.613 1.224 6.10 42.5 Puerto Rico 123.8 98.8 33,512 26,734 102.9 0.798 1.000 3.69 98.8 e San Marino 2.1 2.0 66,240 65,462 127.4 0.710 0.719 0.03 1.5 f Somalia 3.0 … 301 … … 11,427.680 … 9.91 34,047.0 South Sudan 37.0 19.1 3,563 1,844 66.7 1.465 2.830 10.38 54.2 Syrian Arab Republicf 142.9 … 6,505 … … 21.325 … 21.96 3,046.3 Timor-Leste 2.2 1.1 1,857 960 66.6 0.517 1.000 1.18 1.1 Turkmenistan 58.0 29.2 11,361 5,725 65.0 1.436 2.850 5.11 83.3 Uzbekistan 129.5 45.3 4,412 1,545 45.1 600.579 1,715.428 29.34 77,750.6 Total (15) n.a. n.a. n.a. n.a. n.a. n.a. n.a. 170.43 n.a. Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; PPP = purchasing power parity; XR = exchange rate; ... = data suppressed because of incompleteness. a. All exchange rates (XRs) and PPPs are rounded to three decimal places. b. Data source: World Development Indicators (World Bank). c. The results for the nonbenchmark economies are estimated only for reference purposes. Therefore, to ensure consistency across the tables, nonbenchmark economies are not included in the world totals in the main results tables. d. Data sources, exchange rate and expenditure: World Economic Outlook (International Monetary Fund). e. Data sources, exchange rate: World Economic Outlook (International Monetary Fund); expenditure: National Accounts Main Aggregates (United Nations). f. Data source, expenditure: National Accounts Main Aggregates (United Nations). No exchange rate information is available for the economy. Presentation and Analysis of Results 151 ANALYSIS OF RESULTS Size of economies The tables described and presented in the previ- In 2011 the PPP-based world GDP as repre- ous section provide PPP-based estimates of sented by the 177 economies was $90,647 billion expenditures and relative price levels for GDP compared with $70,295 billion measured by and 25 major aggregates. In this section, these exchange rates (XRs). Figure 2.1 shows that estimates are used to present analyses of the this 29 percent increase was produced by size of economies, measures of material well- the middle-income3 economies, whose share being, price level indexes, and measures of of world GDP went from 32 percent using equality for the 177 economies included in the exchange rates to 48 percent using PPPs. In tables. (All GDP expenditures unless otherwise low-income economies, PPP world shares were noted—such as exchange rate–based or in a more than twice as large as exchange rate local currency unit—are PPP-based estimates.) shares in 2011, and yet accounted for only By way of explanation, of the 199 economies 1.5 percent of the global economy with nearly that participated in ICP 2011, it was only pos- 11 percent of the world’s population. High- sible to provide the full set of results for 177 income economies accounted for about half of economies.1 Partial results are provided for the world GDP. The figure also shows, for refer- remaining economies. The Pacific Islands com- ence, the share of GDP by income group as it parison, for example, covered only household stood in 2005.4 consumption, and those results are given in Although high-income economies account supplementary table 2.12. for 50 percent of world GDP, they are home to The analyses make only limited reference to only about 17 percent of the world’s popula- ICP 2005.2 The addition of 53 economies (ICP tion. In 2005, 35 percent of the world’s popula- 2011 covered 199 economies compared with tion was in low-income economies. This figure 146 by ICP 2005), the shifting of economies from dropped to 11 percent in 2011 because the one region to another, and improvements in the percentage of the world’s population in middle- methodology limit the comparisons that can be income economies rose from 48 percent to made between the two benchmarks. Moreover, 72 percent. the world has changed since 2005, with some Figure 2.2 shows the distribution of global economies enjoying remarkable GDP growth GDP by ICP region, comparing PPP-based shares rates even though they were buffeted by the with exchange rate–based shares. According to global financial crisis at the midpoint of the the PPP-based distribution, the Asia and the 2005–11 period. However, a major outcome of ICP 2011 is the 3 The categorization of economies is based on the Atlas conversion factor, finding that the world is more equal because which is the average of an economy’s exchange rate (or alternative consumption and GDP values in most poor conversion factor) for that year and its exchange rates for the two preceding years, adjusted for the difference between the rate of inflation economies are larger relative to those of the in the economy and international inflation. International inflation is United States than previously thought. The fol- determined by inflation in a subset of economies. Since 2001, the subset lowing sections present the major outcomes by has included the Euro Area, Japan, the United Kingdom, and the United States. The income categories for 2011 are as follows: low-income reviewing results for the size of economies, economies, gross national income (GNI) per capita of less than $1,025; material well-being, price levels, and measures middle-income economies, $1,026–$12,475; high-income economies, more of inequality. than $12,475. Three Caribbean islands—Anguilla, Montserrat, and the British Virgin Islands—are not classified by income group. Thus they are not included in the analyses and tables related to income groups. For detailed information on the classification, visit http://data.worldbank.org/about/country-classifications. 1 4 The main tables cover 179 economies, but two of the economies—Cuba For 2005, 142 economies for which both benchmark ICP data and 2005 and Bonaire—do not have a full set of results and are not included in income classification were available are included in figure 2.1. The either the regional or world totals. Nor are they included in the analyses income categories for 2005 are as follows: low-income economies, GNI in this chapter. per capita of less than $875; middle-income economies, $876 –$10,725; 2 The 2005 data used in this section are based on the ICP 2005 global high-income economies, more than $10,725. The comparison between report (World Bank 2008). They differ from the revised 2005 data in the two benchmarks is limited by the fact that 40 economies moved up appendix H of this report. in income classification between 2005 and 2011. 152 Purchasing Power Parities and the Real Size of World Economies Figure 2.1 Percentage of PPP-Based and Exchange Rate–Based GDP and Population by Income Group, ICP 2011 and ICP 2005 2011 2005 80 80 78.0 72.1 67.3 60.5 60 60 50.3 48.2 48.2 Percent Percent 40 40 35.4 32.0 32.4 20 20 16.4 18.9 16.8 11.1 7.1 1.5 0.7 3.1 0 0 High-income Middle-income Low-income High-income Middle-income Low-income (56 economies) (86 economies) (32 economies) (56 economies) (86 economies) (32 economies) PPP-based Exchange rate–based Population Source: ICP, http://icp.worldbank.org/. Note: Figure based on unrevised 2005 data. Income categories for 2011: low-income economies, gross national income (GNI) per capita of less than $1,025; middle-income economies, $1,026–$12,475; high-income economies, more than $12,475. Income categories for 2005: low-income economies, GNI per capita of less than $875; middle- income economies, $876–$10,725; high-income economies, more than $10,725. GDP= gross domestic product; PPP = purchasing power parity. Pacific region accounted for over 30 percent of Figure 2.2 PPP-Based and Exchange Rate–Based GDP Regional world GDP in 2011. The Eurostat-OECD region Shares (World = 100), ICP 2011 becomes significantly smaller when PPP-based 100 2.8 4.5 0.1 GDPs are used. The following sections will shed 0.1 5.3 5.5 more light on these distributions. Chile and Mexico are not included in the Latin America 80 and Caribbean regions; rather, they are in the Eurostat-OECD region, along with Japan and Percentage of world GDP the Republic of Korea. 53.7 Table 2.14 shows the share of world GDP of 60 70.1 the 12 largest economies. In 2011 six of the 12 largest economies (identified in the table by boldface) were in the middle-income category, 40 but together with the other six economies they 4.8 accounted for two-thirds of the world’s econ- omy and 59 percent of the world’s population. Except for Brazil, the shares of world GDP of the 20 3.4 30.0 middle-income economies increased when using 17.9 PPPs instead of exchange rates to measure GDP. The United States remained the world’s largest 4.5 2.7 0 economy, but it was closely followed by China Share of GDP (PPP-based) Share of GDP (exchange rate–based) when measured using PPPs. India was now the Western Asia Commonwealth of Independent States world’s third largest economy, moving ahead of Caribbean Asia and the Pacific Japan. Latin America Africa The largest economies were not the richest, Eurostat-OECD as shown in the ranking of GDP per capita in table 2.14. The middle-income economies with Source: ICP, http://icp.worldbank.org/. Note: Singleton economies account for 1.5 percent in PPP terms and 0.8 percent in exchange rate terms. The large GDPs also had large populations, setting percentage shares add up to more than 100 because of dual participating economies that are counted in two the stage for continued growth. regions. Presentation and Analysis of Results 153 Table 2.14 Twelve Largest Economies by Share of World GDP, Table 2.15 Percentage of GDP to U.S. GDP ICP 2011 (PPP-Based) for 12 Largest Economies, ICP 2011 and ICP 2005 Share of Ranking Ranking Share of world GDP by GDP Economy 2011 2005 by GDP world GDP (exchange per capita United States 100.0 100.0 (PPP- (PPP-based, rate–based, (PPP- based) Economy world = 100) world = 100) based) China 86.9 43.1 1 United States 17.1 22.1 12 India 37.1 18.9 2 China 14.9 10.4 99 Japan 28.2 31.3 3 India 6.4 2.7 127 Germany 21.6 20.3 Russian Federation 20.7 13.7 4 Japan 4.8 8.4 33 Brazil 18.1 12.8 5 Germany 3.7 5.2 24 France 15.3 15.0 6 Russian Federation 3.5 2.7 55 United Kingdom 14.2 15.4 7 Brazil 3.1 3.5 80 Indonesia 13.2 5.7 8 France 2.6 4.0 30 Italy 13.2 13.1 9 United Kingdom 2.4 3.5 32 Mexico 12.2 9.5 10 Indonesia 2.3 1.2 107 Source: ICP, http://icp.worldbank.org/. 11 Italy 2.3 3.1 34 12 Mexico 2.1 1.7 72 Source: ICP, http://icp.worldbank.org/. region. In Africa, shares range from 3.7 percent Note: The six of the 12 largest economies that are in the middle-income category are in of the world expenditures for health care to boldface. 8.2 percent for food and nonalcoholic beverages. The food and nonalcoholic beverage expenditure It is difficult to compare the results of the share exceeds those of the other aggregates 2005 and 2011 rounds of the ICP because the shown for Africa, but it is the smallest shown for number of economies compared was very differ- the Eurostat-OECD region, except for construc- ent, as noted. Table 2.15 shows the relative size tion. The regional shares for construction in the of the largest economies compared with the Asia and the Pacific region far exceed the shares United States. India went from the 10th largest of the other aggregates shown. economy in 2005 to the third largest in 2011. The construction aggregate is examined in Relative to the United States, Japan and the more detail in table 2.17, which shows shares United Kingdom became smaller, while Germany of construction expenditures as a percentage of increased slightly and France and Italy remained the total for the six economies with the largest the same. The relative shares of the three Asian values. China accounts for nearly 35 percent economies—China, India, and Indonesia—to of the world’s expenditures on construction. the United States doubled, while Brazil, Mexico, Together, these economies account for over and Russia increased by one-third or more. As 61 percent of the world’s expenditure on con- discussed elsewhere in this report, some of the struction and over 53 percent of the world’s large differences in the Asian economies and expenditure on machinery and equipment. developing economies in general can be attrib- Table 2.6 shows the world shares for GDP and uted to the changes in the methodology used for 25 major aggregates and provides more detail on the two benchmark comparisons. the relative sizes of economies and how they are Table 2.16 provides an example of how the distributed by region. GDP shares relate to world shares of major aggregates for the ICP regions. The regional GDP Material well-being shares are the same as those shown in figure 2.2. The remaining columns of the table show the An economy’s GDP divided by its population regional shares for selected aggregates. Note the provides a measure of its relative material well- variability in the aggregate shares for each being compared with that of other economies. 154 Purchasing Power Parities and the Real Size of World Economies Table 2.16 Regional Shares of World GDP and Major Aggregates, ICP 2011 percent Region GDP Food Housing Health Education Construction Africa 4.5 8.2 4.7 3.7 7.4 4.0 Asia and the Pacific 30.0 35.2 25.3 27.3 30.5 55.2 Commonwealth of Independent States 4.8 6.8 6.4 3.8 7.2 2.1 Eurostat-OECD 53.7 44.3 56.7 59.7 46.2 30.7 Latin America 5.5 6.7 5.1 5.5 7.5 4.6 Caribbean 0.1 0.1 0.2 0.1 0.2 0.1 Western Asia 4.5 4.5 5.8 2.5 4.8 4.1 Source: ICP, http://icp.worldbank.org/. Note: The percentage shares add up to more than 100 because of dual participating economies that are counted in two regions. Table 2.17 Shares of World Expenditure on that are below that average. The approximate Construction and Machinery and Equipment of median expenditure per capita of $10,057 means Economies with Largest Construction Shares, that half of the world’s population is experienc- ICP 2011 ing expenditures per capita above that amount percent and half are experiencing those below. Although comparisons with the 2005 ICP results should be Machinery and Economy Construction equipment carried out with caution, 25 percent of the popu- lation lived in economies above the world aver- China 34.6 16.7 age in 2005 compared with 28 percent in 2011. India 9.0 4.5 These differences are within the range of statisti- United States 7.2 21.3 cal variability. Indonesia 5.6 0.9 As a group, the middle-income economy Brazil 2.5 3.1 shares of world GDP are nearly as large as the Japan 2.4 6.9 high-income economy shares, and the middle- Total 61.3 53.4 income economies have the largest shares of Source: ICP, http://icp.worldbank.org/. gross fixed capital formation (GFCF). However, the expenditures per capita of the middle- income economies are significantly lower than The GDP per capita comparison between econo- those of the high-income economies. Recall that mies is best carried out using PPPs. Table 2.18 72 percent of the world population is in middle- shows the PPP-based world shares and expendi- income economies, led by China and India. tures per capita for GDP, with the economies The world shares and expenditures per capita grouped into the high-, middle-, and low- for the major aggregates are consistent with income categories used in figure 2.1. Huge dif- the measures for GDP. One exception is gross ferences in the per capita levels are evident fixed capital formation for the middle-income between income categories. economies, where the world share for GFCF The PPP-based expenditures per capita aver- at 55.4 percent greatly exceeds that for other age $40,282 over the 56 high-income economies. aggregates. This is consistent with the expendi- However, the 24 economies with GDP expendi- ture shares shown in table 2.17 for construction tures per capita above this average account for and machinery and equipment for China, India, over 40 percent of world GDP. Further analysis and Indonesia. shows that the distribution of expenditures per Figure 2.3 is a view of the regional per capita capita is highly skewed. Twenty-eight percent of values as a ratio of the world average for GDP, the world’s population lives in economies with actual individual consumption (AIC), collective GDP expenditures per capita above the $13,460 government, and GFCF. AIC per capita provides world average, and 72 percent live in economies a general measure of the material well-being of Presentation and Analysis of Results 155 Table 2.18 PPP-Based Shares of World GDP and Per Capita Measures: High-, Middle-, and Low-Income Economies, ICP 2011 High-income Middle-income Low-income World economies (56) economies (86) economies (32) (174) EXPENDITURE SHARE (PPP-BASED, WORLD = 100) Gross domestic product 50.3 48.2 1.5 100.0 Actual individual consumption 53.6 44.5 1.9 100.0 Individual household consumption 54.5 43.5 2.0 100.0 Individual government consumption 49.0 49.8 1.2 100.0 Collective government consumption 50.6 48.1 1.3 100.0 Gross fixed capital formation 43.3 55.4 1.3 100.0 Domestic absorption 50.1 48.2 1.7 100.0 AVERAGE EXPENDITURES PER CAPITA (PPP-BASED, US$) Gross domestic product 40,282 9,004 1,839 13,460 Actual individual consumption 27,570 5,345 1,473 8,647 Individual household consumption 23,207 4,309 1,263 7,144 Individual government consumption 5,149 1,221 188 1,766 Collective government consumption 3,703 822 143 1,230 Gross fixed capital formation 8,083 2,414 370 3,139 Domestic absorption 39,535 8,872 2,004 13,258 Source: ICP, http://icp.worldbank.org/. Note: See note to figure 2.1 for ICP 2011 income categories. Figure 2.3 Index of Regional Average Real Expenditures Per Capita (World = 100) on Major Aggregates (PPP-Based), ICP 2011 300 Expenditure per capita index (world = 100) 250 200 150 100 World average = 100 50 0 AFR ASI CIS EUO LAT CAR WAS GDP 30.0 56.6 131.6 250.2 92.4 121.5 130.0 Actual final consumption 32.2 47.2 142.1 276.8 99.0 125.7 99.2 Collective consumption 45.1 44.9 150.9 258.0 102.7 144.0 164.0 expenditure by government Gross fixed capital formation 22.6 80.1 71.0 204.0 79.8 113.9 124.8 Source: ICP, http://icp.worldbank.org/. Note: AFR = Africa; ASI = Asia and the Pacific; CAR = Caribbean; CIS = Commonwealth of Independent States; EUO = Eurostat-OECD; LAT = Latin America; WAS = Western Asia. 156 Purchasing Power Parities and the Real Size of World Economies each economy’s population. AIC makes up the $50,000. By contrast, eight economies have a greatest share of GDP in the Eurostat-OECD GDP per capita of less than $1,000. The econo- region, but it is exceeded by collective govern- mies with the largest per capita values are small ment expenditures in every other region except in terms of their GDP. Even though Ethiopia has Asia and the Pacific, where the two measures one of the lowest per capita values in the world, are about the same. GFCF shares exceed those its GDP is larger than the GDP of four of the of all other aggregates in the Asia-Pacific region, economies with the largest per capita values. The which is consistent with the large values last two columns of table 2.19 show the per observed when reviewing the relative sizes of capita values as a percentage of the U.S. values economies in previous tables. for 2011 and 2005. The non–Eurostat-OECD Table 2.19 shows the ranking by GDP per economies with the highest per capita values in capita for the economies with the highest and 2011 exhibit the greatest increases from 2005 to lowest values. It reveals the extreme variability 2011. The economies with the lowest per capita of relative well-being across the world. In two values also showed gains relative to 2005. economies, GDP per capita is more than PPP-based per capita values exceed exchange $100,000, and in 11 economies it is more than rate values for all economies except Luxembourg, Table 2.19 PPP-Based and Exchange Rate–Based GDP Per Capita Expenditures for the 10 Economies with the Largest and Smallest Values and Ratios Relative to the United States, ICP 2011 GDP per capita (US$) Ranking, GDP Ratio of GDP per capita relative to United States (%) Ranking, GDP per capita Exchange (PPP-based) Economy PPP-based rate–based (PPP-based) 2011 2005 1 Qatar 146,521 97,091 52 294 165 2 Macao SAR, China 115,441 66,063 83 232 89 3 Luxembourg 88,670 111,689 95 178 168 4 Kuwait 84,058 52,379 53 169 108 5 Brunei Darussalam 74,397 42,432 106 149 114 6 Singapore 72,296 51,242 40 145 100 7 Norway 61,879 99,035 48 124 114 8 United Arab Emirates 60,886 42,182 31 122 — 9 Bermuda 54,899 85,839 156 110 — 10 Switzerland 51,582 83,854 37 104 85 168 Guinea 1,287 490 137 2.6 2.3 169 Ethiopia 1,214 353 73 2.4 1.4 170 Malawi 973 476 133 2.0 1.7 171 Mozambique 951 524 123 1.9 1.8 172 Central African Republic 897 486 153 1.8 1.6 173 Niger 852 399 136 1.7 1.5 174 Burundi 712 240 148 1.4 n.a. 175 Congo, Dem. Rep. 655 372 97 1.3 0.6 176 Comoros 610 358 175 1.2 2.6 177 Liberia 537 278 161 1.1 0.9 Source: ICP, http://icp.worldbank.org/. Note: — = economy did not participate in ICP 2005; n.a. = not available. Presentation and Analysis of Results 157 Norway, Bermuda, and Switzerland. The analy- with the rectangles shows the disparity in GDP sis that follows shows that these economies per capita across the world. have high price levels. Table 2.20 shows the actual individual con- Figure 2.4 shows the distribution of global sumption per capita first for the 10 economies GDP; economies are arranged in order of GDP with the largest values and then for the 10 econo- per capita along the horizontal axis and presented mies with the smallest values. Except for the as rectangles. The horizontal scale corresponds to United States and Germany, the economies with each economy’s share of the world’s population. the largest per capita values are small. At the GDP per capita is shown on the vertical axis. other end of the distribution are the 10 econo- Each economy’s size in terms of GDP is thus rep- mies with per capita values below $1,000, and all resented by the area of its rectangle, which is the are in the Africa region. The last two columns of product of GDP per capita and population. The table 2.20 show the ratio of AIC per capita relative United States, with the 12th largest GDP per to the United States in 2011 and 2005. It is impor- capita, is placed at the right. The remaining 11 tant to note that the relative AIC ratios of the economies with the highest GDP per capita are economies with the smallest values were in most not visible in this figure because together they cases greater in 2011 than they were in 2005. account for less than 0.6 percent of the world’s In the economies with the largest per capita population. The intersection of the average line values, only Hong Kong SAR, China, has Figure 2.4 Real GDP Per Capita and Shares of Global Population, ICP 2011 70,000 60,000 United States 50,000 Germany Real GDP per capita (US$) Japan 40,000 Russian Fed. 30,000 Brazil Mexico India China South Africa 20,000 Bangladesh Egypt, Arab. Rep. World average = 13,460 10,000 Ethiopia Nigeria 0 0 20 40 60 80 100 Cumulative share of global population (%) Source: ICP, http://icp.worldbank.org/. Note: Economies are arranged in the order of increasing real GDP per capita. Each rectangle describes an economy: (1) width corresponds to its population share; (2) height corresponds to its real GDP per capita; and (3) area corresponds to its share of world total real GDP—(3) = (1) × (2). 158 Purchasing Power Parities and the Real Size of World Economies Table 2.20 PPP-Based and Exchange Rate–Based Actual Individual Consumption (AIC) Per Capita and Ratios Relative to the United States, ICP 2011 AIC per capita Ratio of AIC per capita relative to United States (%) Ranking, AIC per capita Exchange Ranking, AIC (PPP-based) Economy PPP-based rate–based (PPP-based) 2011 2005 1 Bermuda 37,924 67,145 155 101 — 2 United States 37,390 37,390 1 100 100 3 Cayman Islands 34,020 42,553 160 91 — 4 Hong Kong SAR, China 32,690 23,433 43 87 61 5 Luxembourg 32,000 46,959 120 86 105 6 Norway 31,014 54,733 51 83 77 7 Switzerland 29,465 53,258 42 79 72 8 United Arab Emirates 29,463 22,267 37 79 — 9 Germany 28,478 30,903 5 76 68 10 Austria 27,677 32,703 41 74 73 169 Guinea-Bissau 928 436 162 2.5 1.4 170 Mozambique 890 450 107 2.4 1.9 171 Central African Republic 869 449 148 2.3 2.0 172 Guinea 789 276 136 2.1 2.1 173 Niger 719 320 132 1.9 1.5 174 Burundi 648 224 145 1.7 n.a. 175 Comoros 621 353 173 1.7 2.8 176 Liberia 606 314 154 1.6 0.8 177 Congo, Dem. Rep. 447 239 96 1.2 0.5 Source: ICP, http://icp.worldbank.org/. Note: — = economy did not participate in ICP 2005; n.a. = not available. PPP-based values greater than the exchange rate price level index with the world equal to 100. In numbers. The PPP-based per capita values this figure, each economy is represented by a exceed those from exchange rates for all of the circle with an area proportional to its size. The economies with the smallest per capita values. economies are color-coded by region. As a gen- These economies have low price levels com- eral observation, PLIs at the GDP level tend to be pared with those with high per capita values. generally lower in economies with lower GDP The section that follows examines price level per capita. This observation is consistent with indexes and their relationship to the per the fact that as an economy develops, consumers capita measures. move from consuming basic goods that are also tradable to consuming more services that are not tradable. As wage rates increase, so do the costs Price level indexes of services. After a certain level of expenditure The price level index (PLI), the ratio of a PPP to per capita is reached, there is a rapid rise in price a corresponding exchange rate, is used to com- levels rather than continued increases in the pare the price levels of economies. Figure 2.5 expenditure per capita. As the figure shows, for presents a multidimensional comparison of the economies in the Eurostat-OECD comparison, GDP per capita of each economy relative to its the price levels increase very sharply with Presentation and Analysis of Results 159 Figure 2.5 GDP Price Level Index versus GDP Per Capita (and Size of GDP Expenditures), ICP 2011 220 Switzerland Norway 200 Australia Eurostat-OECD Denmark high-income economies 180 Japan Canada 160 Luxembourg France Price level index (world average = 100) United Kingdom 140 Germany Italy Small high-income 120 Middle-income Bahamas economies economies Portugal United States Brazil 100 African low-income Angola Chile Singapore economies South Africa 80 United Arab Emirates Qatar Comoros Fiji Honduras Russian Fed. Mozambique Macao SAR, China 60 Nigeria Liberia China Malaysia Kenya Sudan Iran, Saudi Arabia Indonesia Islamic Rep. 40 Burundi India Real expenditures 0 EthiopiaBangladesh Pakistan Egypt, Arab. Rep. 20 5,000 10,000 15,534 0 0 500 1,000 2,000 5,000 10,000 20,000 50,000 100,000 200,000 GDP per capita (PPP-based, US$) Africa Caribbean Eurostat-OECD Western Asia Asia and the Pacific Commonwealth of Latin America Singletons Independent States Source: ICP, http://icp.worldbank.org/. relatively small changes in the expenditure per Eurostat-OECD region at 0.84 and falls to 0.44 capita, whereas other regions follow somewhat and 0.60, respectively, for collective government different patterns. and GFCF. However, the R2 value for non– It is useful to look at the Eurostat-OECD and Eurostat-OECD economies is relatively weak. non–Eurostat-OECD economies separately The GDP and AIC per capita measures for the because Eurostat-OECD mainly represents high- Eurostat-OECD economies are much less vari- income economies. Figure 2.6 shows the same able than shown for the rest of the world, whose distribution as figure 2.5, but the Eurostat-OECD economies cover the full range of per capita economies are represented by dark grey squares measures, but in a more narrow price band. and the rest of the world by blue squares for GDP Table 2.21 shows the PLIs (world = 100) for and the three major aggregates (actual individual the 10 most expensive and 10 least expensive consumption, collective government, and gross economies in the world. With the exception of fixed capital formation). The R2 value between Bermuda, the most expensive economies are in the PLI and per capita measures is the highest for the Eurostat-OECD region. The economies with GDP and actual individual consumption in the the lowest prices are either in Africa or the Asia 160 Purchasing Power Parities and the Real Size of World Economies Figure 2.6 GDP Price Level Index versus Expenditure Per Capita with Trend Lines, Eurostat-OECD and Non–Eurostat-OECD Economies, ICP 2011 GDP price level index (world average = 100) AIC price level index (world average = 100) 250 y = 0.0775x0.7117 250 R² = 0.837 y = 0.0135x0.9165 200 200 R² = 0.8391 150 150 100 100 50 y = 29.458x0.0842 50 y = 22.939x0.112 R² = 0.1867 R² = 0.1711 0 0 500 5,000 50,000 500 5,000 50,000 GDP per capita (PPP-based) AIC per capita (PPP-based) GFCF price level index (world average = 100) 250 CG price level index (world average = 100) 250 y = 0.7642x0.4931 200 R² = 0.6851 200 y = 0.0018x1.067 R² = 0.8588 150 150 100 100 50 50 y = 17.485x0.1262 y = 66.183x0.0163 R² = 0.1372 R² = 0.007 0 0 500 5,000 500 5,000 50,000 CG per capita (PPP-based) GFCF per capita (PPP-based) Non–Eurostat-OECD economies Eurostat-OECD economies Source: ICP, http://icp.worldbank.org/. Note: AIC = actual individual consumption; CG = collective government; GDP = gross domestic product; GFCF = gross fixed capital formation. Table 2.21 Economies with Highest and Lowest Price Level Indexes (PLIs), ICP 2011 Ranking by GDP (PPP- Ranking by GDP PLI Economy GDP PLI (world = 100) GDP PLI (US = 100) based, per capita) 1 Switzerland 209.6 162.6 10 2 Norway 206.4 160.0 7 3 Bermuda 201.6 156.4 9 4 Australia 201.0 155.9 20 5 Denmark 185.0 143.5 21 6 Sweden 175.1 135.8 22 7 Japan 173.6 134.6 33 8 Finland 162.6 126.1 28 9 Luxembourg 162.4 126.0 3 10 Canada 161.9 125.6 23 (continued) Presentation and Analysis of Results 161 Table 2.21 (Continued) Ranking by GDP (PPP- Ranking by GDP PLI Economy GDP PLI (world = 100) GDP PLI (US = 100) based, per capita) 168 Cambodia 42.8 33.2 146 169 Uganda 42.6 33.0 156 170 Vietnam 42.2 32.7 128 171 India 41.7 32.4 127 172 Bangladesh 40.3 31.2 144 173 Lao PDR 39.6 30.7 133 174 Ethiopia 37.5 29.1 169 175 Myanmar 37.0 28.7 139 176 Pakistan 36.4 28.2 129 177 Egypt, Arab Rep. 35.1 27.2 97 Source: ICP, http://icp.worldbank.org/. Figure 2.7 Regional Average Price Level Indexes by GDP and Major Aggregates, ICP 2011 160 140 120 World average = 100 100 Price level index 80 60 40 20 0 Africa Asia and the Commonwealth Eurostat-OECD Latin America Caribbean Western Asia Pacific of Independent States GDP Actual final consumption Collective consumption expenditure by government Gross fixed capital formation Source: ICP, http://icp.worldbank.org/. and the Pacific region and include India, which more than double the exchange rate–based has the third-largest economy. Economies with nominal expenditures. the lowest prices still have GDP per capita val- Price level indexes can be computed for each ues among the smallest in the world even aggregation level of GDP and by region. Figure 2.7 though the PPP-based real expenditures are is a view of the regional price levels of three 162 Purchasing Power Parities and the Real Size of World Economies major aggregates of GDP. Actual individual con- compared with 178 in Latin America. Similar sumption includes all household consumption differences are shown for communication and expenditure, as well as general government and machinery and equipment. NPISH expenditures on individual goods and The CIS in general has lower than average services such as health and education. Collective prices, except for construction where the prices consumption expenditures by general govern- are significantly higher than the world average. ment include expenditures on services such as At the same time, the prices for most services defense, justice, general administration, and pro- such as housing, health, and education are tection of the environment. Gross fixed capital among the lowest in the world. formation measures investment expenditures, which mostly are on purchases of machinery Variations in GDP per capita and PLI and equipment and construction services. All three aggregates in the Eurostat-OECD The world economy is very complex, with region have price levels above the world aver- extreme differences in the overall size of econo- age. Only gross fixed capital formation in the mies as measured by GDP and how it is distrib- CIS region and collective government in Latin uted across the major aggregates. Per capita America are at price levels above the world measures provide another view, as do the price average for the remaining regions. The high level indexes. This section reviews the inherent price levels of gross fixed capital formation in variability across economies for the per capita the CIS region translate to the real expenditures and price level indexes. per capita in figure 2.3 that are below those of Across the 177 economies analyzed here, GDP all other regions except Africa. per capita ranges from $146,521 in Qatar to Figure 2.8 presents the regional average $655 in the Democratic Republic of Congo—a PLIs for GDP and 15 aggregates with the world range of 223 based on the ratio of the maximum average equal to 100. The Eurostat-OECD area to minimum values. The price level index shows higher than average price levels across all across the 177 economies varies from 209.6 in categories, except for machinery and equipment, Switzerland to 35.1 in the Arab Republic of where the price index is near the world average. Egypt—a range of 6.0—suggesting there is The Eurostat-OECD economies lead the world in much less variation in price levels than in per price levels for construction, followed by various capita measures. The coefficient of variation services: education, housing, and health. (CV) provides a measure of the average variabil- At the same time, the Western Asia, Africa, ity. Figure 2.9 shows the coefficients of variation and Asia and the Pacific regions all show signifi- by major aggregates for the world and region for cantly lower than average price levels in virtu- the GDP per capita and price level indexes. ally all categories except machinery and The coefficient of variation for the GDP per equipment, again with service PLIs the lowest. capita index appears on the left-hand side of each For example, health services, at 40, are signifi- graph and for the PLI on the right-hand side. cantly below the world average in all these With few exceptions, the variation in the GDP regions, and the housing and education price per capita measures is much greater than the levels are quite low as well. variation in price levels. One exception is the Price levels in Latin America are about variability in the education price levels, which is average at the GDP level, but they exhibit driven by the CV of 72 percent for the Eurostat- significant variation at the component level. OECD, the largest of any aggregate at the regional For example, clothing and footwear and level. The Eurostat-OECD used a different meth- machinery and equipment price levels exceed odology to estimate PPPs for education than was those of all other regions. used in the rest of the world (see appendix C). The Caribbean region, which is not much dif- Figure 2.9 also displays the homogeneity of ferent from Latin America at the GDP level, is economies within each region. The Asia and the quite different from Latin America at the com- Pacific region contains some of the world’s ponent level. For example, the clothing and largest economies, but with smaller per capita footwear price level in the Caribbean is 111 measures. The Africa region, with its 50 economies, Presentation and Analysis of Results 163 Figure 2.8 Regional Average Price Level Indexes (World = 100) for GDP and 15 Aggregates, ICP 2011 Africa Asia and the Pacific 58.6 Gross domestic product 59.7 86.9 Food and nonalcoholic beverages 70.3 71.7 Alcoholic beverages, tobacco, and narcotics 79.3 56.0 Clothing and footwear 57.2 39.1 Housing, water, electricity, gas, and other fuels 45.7 65.4 Furnishings, household equipment and maintenance 73.3 37.8 Health 39.5 61.1 Transport 62.5 68.0 Communication 49.4 55.9 Recreation and culture 49.8 42.0 Education 49.2 61.3 Restaurants and hotels 52.0 46.7 Miscellaneous goods and service 59.7 48.9 Collective consumption expenditure by government 58.6 108.1 Machinery and equipment 98.1 55.8 Construction 60.5 0 50 100 150 200 0 50 100 150 200 Commonwealth of Independent States Eurostat-OECD 71.8 Gross domestic product 130.5 89.0 Food and nonalcoholic beverages 127.3 49.2 Alcoholic beverages, tobacco, and narcotics 110.7 99.5 Clothing and footwear 130.7 28.6 Housing, water, electricity, gas, and other fuels 139.3 72.4 Furnishings, household equipment and maintenance 111.3 48.8 Health 137.3 82.5 Transport 115.8 60.5 Communication 129.3 71.0 Recreation and culture 113.5 34.2 Education 156.8 88.2 Restaurants and hotels 118.5 54.6 Miscellaneous goods and service 115.2 63.7 Collective consumption expenditure by government 129.9 97.9 Machinery and equipment 98.5 154.7 Construction 184.6 0 50 100 150 200 0 50 100 150 200 Latin America Caribbean 97.1 Gross domestic product 92.5 105.3 Food and nonalcoholic beverages 130.0 88.7 Alcoholic beverages, tobacco, and narcotics 123.0 178.3 Clothing and footwear 111.0 78.8 Housing, water, electricity, gas, and other fuels 88.3 109.3 Furnishings, household equipment and maintenance 124.7 78.3 Health 79.8 101.2 Transport 98.9 152.4 Communication 109.9 104.8 Recreation and culture 96.9 80.9 Education 68.3 100.8 Restaurants and hotels 116.2 84.2 Miscellaneous goods and service 86.4 110.0 Collective consumption expenditure by government 65.2 137.5 Machinery and equipment 103.3 84.8 Construction 96.3 0 50 100 150 200 0 50 100 150 200 Western Asia Gross domestic product 61.9 Food and nonalcoholic beverages 80.9 Alcoholic beverages, tobacco, and narcotics 62.0 Clothing and footwear 67.9 Housing, water, electricity, gas, and other fuels 41.8 Furnishings, household equipment and maintenance 67.0 Health 39.1 Transport 50.3 Communication 73.0 Recreation and culture 56.8 Education 54.8 Restaurants and hotels 65.3 Miscellaneous goods and service 49.3 Collective consumption expenditure by government 53.5 Machinery and equipment 81.0 Construction 55.2 0 50 100 150 200 Source: ICP, http://icp.worldbank.org/. 164 Purchasing Power Parities and the Real Size of World Economies contains a large number of the world’s poorest explained by its highly tradable character. economies. However, the variability of the per capita The lowest price level CVs are observed in the index for machinery and equipment has the CIS data, even though real expenditures per highest value at the world level and also in capita vary significantly more. several regions. The aggregate machinery and equipment Services such as health and education, as well exhibits the lowest price variation (10 percent) as collective government consumption, show in at both the regional and global levels, which is general the largest price level variations across Figure 2.9 Coefficients of Variation (CVs): GDP Per Capita Index and Price Level Indexes (PLIs) for GDP and Major Aggregates by Region, ICP 2011 World Africa 111 45 Gross domestic product 135 21 58 31 Food and nonalcoholic beverages 90 21 138 48 Alcoholic beverages, tobacco, and narcotics 134 30 109 46 Clothing and footwear 101 29 93 75 Housing, water, electricity, gas, and other fuels 129 34 101 37 Furnishings, household equipment and maintenance 110 26 98 71 Health 123 34 107 38 Transport 130 22 105 41 Communication 134 31 134 41 Recreation and culture 156 25 71 96 Education 128 40 138 44 Restaurants and hotels 151 35 122 50 Miscellaneous goods and service 131 27 99 59 Collective consumption expenditure by government 185 36 153 12 Machinery and equipment 6 108 60 Construction 150 30 200 150 100 50 0 50 100 200 150 100 50 0 50 100 Asia and the Pacific Commonwealth of Independent States 138 29 Gross domestic product 67 17 52 24 Food and nonalcoholic beverages 39 15 85 63 Alcoholic beverages, tobacco, and narcotics 76 15 128 35 Clothing and footwear 67 9 94 64 Housing, water, electricity, gas, and other fuels 41 62 138 37 Furnishings, household equipment and maintenance 60 10 105 63 Health 60 31 116 23 Transport 60 12 143 49 Communication 48 28 178 24 Recreation and culture 70 19 79 69 Education 44 37 166 30 Restaurants and hotels 69 14 161 26 Miscellaneous goods and service 74 16 146 48 Collective consumption expenditure by government 63 33 127 6 Machinery and equipment 79 7 111 35 Construction 78 12 200 150 100 50 0 50 100 200 150 100 50 0 50 100 Eurostat-OECD Latin America 47 35 Gross domestic product 47 22 19 28 Food and nonalcoholic beverages 30 21 73 43 Alcoholic beverages, tobacco, and narcotics 68 27 57 18 Clothing and footwear 50 40 31 51 Housing, water, electricity, gas, and other fuels 54 45 47 22 Furnishings, household equipment and maintenance 51 34 40 53 Health 62 25 59 23 Transport 63 31 44 25 Communication 68 40 56 30 Recreation and culture 69 28 16 72 Education 48 34 63 34 Restaurants and hotels 60 24 59 37 Miscellaneous goods and service 61 29 32 49 Collective consumption expenditure by government 56 30 71 12 Machinery and equipment 61 13 49 45 Construction 58 18 200 150 100 50 0 50 100 200 150 100 50 0 50 100 (continued) Presentation and Analysis of Results 165 Figure 2.9 (Continued) Caribbean Western Asia 56 29 Gross domestic product 105 24 39 16 Food and nonalcoholic beverages 44 12 93 20 Alcoholic beverages, tobacco, and narcotics 77 39 64 24 Clothing and footwear 116 31 63 68 Housing, water, electricity, gas, and other fuels 76 48 74 22 Furnishings, household equipment and maintenance 90 19 77 38 Health 51 54 62 14 Transport 99 32 71 23 Communication 111 26 84 21 Recreation and culture 100 26 64 48 Education 56 58 131 29 Restaurants and hotels 90 34 85 28 Miscellaneous goods and service 92 31 57 35 Collective consumption expenditure by government 75 58 106 11 Machinery and equipment 163 10 74 41 Construction 89 24 200 150 100 50 0 50 100 200 150 100 50 0 50 100 Index of GDP per capita (PPP-based) variation (CV) PLI variation (CV) Source: ICP, http://icp.worldbank.org/. all regions. Housing, too, has high PLI variances. Table 2.22 Population-Weighted Gini Coefficient These aggregates are also the most difficult for ICP Economies, ICP 2011 and ICP 2005 to measure. 2011 2005 GDP, PPP-based 0.49 0.57 Inequality in incomes among economies GDP, exchange rate–based 0.64 0.71 The Gini index measures the distribution of con- Actual individual consumption, PPP-based 0.51 0.60 sumption expenditures across economies and Household consumption, PPP-based 0.52 0.62 the extent to which an economy deviates from Source: ICP, http://icp.worldbank.org/. the hypothetical l distribution if all economies had the same share of world GDP. A Lorenz curve plots the cumulative percentages of rate–based expenditures exhibit the same trend expenditures against the cumulative population between the two benchmark years. starting with the poorest economy. The 45° line Figure 2.10, shows, using the Lorenz curve, represents the plot of equality. The Gini index the distribution of 2005 GDP per capita (dotted reflects the area between the Lorenz curve and line) and 2011 GDP per capita. The area between the line of equality. A Gini index of zero repre- the line of equality and the line showing the per sents perfect equality, and an index of 100 rep- capita distribution represents the inequality, resents perfect inequality. which became smaller between 2005 and 2011. According to table 2.22, ICP 2011 revealed a population-weighted Gini measure of inequality Summary among economies in real expenditures per capita in PPP terms of 0.49, which indicates a sharp This section has described the interaction drop from 0.57 in ICP 2005. Even though the between the real sizes of GDP for 177 economies economies participating in ICP 2005 and ICP with the relative price levels for major aggre- 2011 were different, the general trend is a sharp gates and expenditures per capita based on their fall in inequality, which would have significant population sizes. The results indicate that only a implications for estimates of poverty incidence small number of economies have the greatest worldwide. Similar trends in inequality among shares of world GDP. However, the shares of economies are also evident when per capita large economies such as China and India more household consumption or per capita actual than doubled relative to that of the United individual consumption is used. Exchange States between 2005 and 2011. The results also 166 Purchasing Power Parities and the Real Size of World Economies Figure 2.10 Lorenz Curve for ICP 2011 and ICP 2005 weights and price data reported by the partici- GDP Per Capita Distribution pating economies as well as the extent to which 100 the goods and services priced reflect the con- sumption patterns and price levels of each par- ticipating economy. The margins of error around Cumulative percentage of expenditures 80 PPPs are the result of sampling and nonsampling errors plus the inherent variability in price and economic structures between economies. 60 Sampling errors emerge from several of the steps taken to collect prices and calculate basic 40 heading PPPs. First, a sample of products is selected for pricing rather than pricing the universe of products. Second, a sample of out- 20 lets is selected rather than including every out- let in the economy in the price surveys. Third, 0 prices from the sample of outlets are generally 0 20 40 60 80 100 observed monthly, quarterly, or annually, Cumulative percentage of population depending on the seasonal variability in the prices. Although selection of the sample of 2011 GDP per capita (PPP-based) products and outlets is a subjective process 2005 GDP per capita (PPP-based) involving expert judgment, sampling theory can Source: ICP, http://icp.worldbank.org/. be used to determine the number of products to be priced, the number of outlets to be selected for the price surveys, and the number of times reveal that PPP-based consumption and GDP prices are observed for each selected product. expenditures in most poor economies are larger Chapter 7 of Measuring the Real Size of the than previously thought, based on analysis of World Economy: The Framework, Methodology, and the ICP 2005 results. Results of the International Comparison Program Meanwhile, the spread of actual individual (ICP) (World Bank 2013) provides measures of consumption per capita as a percentage of that the sources of sampling error. Table 7.3 shows of the United States has been greatly reduced, that only 10–15 rice products need to be priced suggesting that the world has become more compared with 70–100 garments and 50+ phar- equal regarding the distribution of income. maceutical products to obtain about the same However, this reduction in the spread must be level of precision of the estimated basic heading interpreted with caution because changes in the PPPs. Products such as rice, milk, and eggs are ICP methodology and economy coverage make very homogeneous, whereas the garment basic it difficult to make direct comparisons with pre- heading, which includes clothing for men, vious benchmark results. The sections on meth- women, and children, is very heterogeneous. odology in this report should be carefully The desired degree of precision also depends on considered when using the ICP 2011 results. the relative expenditure shares of each basic heading. PPPs for basic headings with large shares of GDP must be measured with greater RELIABILITY AND LIMITATIONS OF PPPs precision than those with small shares. In gen- AND REAL EXPENDITURES eral, the sampling errors of the basic heading PPPs are mostly kept below 10 percent by Reliability of PPPs and real expenditures increasing the number of products and prices PPPs are statistical constructs rather than precise where there is greater variability. measures—that is, they are point estimates that A nonsampling error is one that cannot be fall within some margin of error of the unknown reduced by increasing the number of products true values. The error margins surrounding PPPs surveyed or the number of prices observed. depend on the reliability of the expenditure It also can be considered a source of bias. Presentation and Analysis of Results 167 The weights used to aggregate basic heading ratio or spread. Analysis by Deaton (2012) has PPPs to GDP depend on the coverage and com- shown that these standard errors for econo- pleteness of the national accounts. The per cap- mies similar to the United States—Canada, for ita measures are dependent on the reliability of example—are about 2.5 percent. For less similar the population numbers, and the PLIs are economies, such as China and India, they are dependent on the accuracy of the exchange about 7 percent, and over 10 percent for several rates as well as of the PPPs. The need for CIS economies. national average prices can be difficult to fulfill The Fisher indexes are not transitive or base in large economies with large rural areas and economy–invariant. Therefore, the GEKS populations. Product specifications can be vague, method is used for the final calculation. The which means that economies may not price aggregated PPP between France and Germany is the same products. These nonsampling errors the direct PPP between France and Germany and sources of bias are minimized by the times the geometric mean of the indirect PPPs exhaustive data validation process described in through the n – 2 other economies in the com- chapter 9 of Measuring the Real Size of the World parison. Because of the transitivity requirement, Economy (World Bank 2013) and in the chapters the price level of the direct comparison between on data validation in Operational Guidelines and France and Germany must also be the same as Procedures for Measuring the Real Size of the World the PPP for the entire chain of economies—that Economy: 2011 International Comparison Program is, from the United States to India to Tajikistan (World Bank forthcoming). and so forth, through all economies in the com- The reliability of the aggregated PPPs is parison. Although the GEKS method produces affected not only by sampling and nonsampling multilateral results satisfying transitivity and base errors, but also by the underlying variability economy invariance, the relative standard errors inherent in each economy’s price and economic are increased for comparisons of similar econo- structure. The relative price of rice as shown by mies such as the United States with its major the basic heading PPP for rice may be very cheap trading partners. The relative standard error of in an economy in which the relative prices for the India and China to U.S. PPPs just described other basic headings are relatively expensive. could increase to 15 percent from the multilat- The basic heading PPPs of an economy to the eral comparison, although in practice this is base will differ by factors of 20 for most basic likely to be somewhat lower because of fixity. headings and much more for those difficult to measure. This source of variability does not Limitations in the use of 2011 PPPs mean there are errors. Rather, it is an example of the variability of PPPs across economies with Anyone comparing economies by the size of wide differences in economic and price struc- their real GDP or their real GDP per capita tures. The variability of basic heading PPPs is less should do so with caution. Such comparisons when comparing economies of similar price and require that all the economies employ the same economic structures, which is the main reason definition of GDP and that their measurement PPPs are first computed at the regional level. of GDP be equally exhaustive. Although the first Another source of variability in aggregated requirement is broadly met because the GDP PPPs arises from the variation in the basic head- estimates of most ICP participants are compiled ing expenditures. The PPPs between any pair of more or less in line with the System of National economies are aggregated to GDP first using Accounts 1993 (Commission of the European economy A’s expenditures as weights (Laspeyres Communities et al. 1993), the measurement of index) and then using economy B’s weights GDP is not sufficiently uniform over all partici- (Paasche index). The Laspeyres and Paasche pants to satisfy the second requirement. In indexes will result in different estimates of the particular, the GDPs of participants with large PPPs and real expenditures of each economy. nonobserved economies could be underesti- The geometric mean is then taken, which is the mated. Bearing in mind that there may be Fisher index. The variability around the Fisher errors in the population data in addition to index is approximated by the Paasche-Laspeyres those in the price and expenditure data, one 168 Purchasing Power Parities and the Real Size of World Economies should not consider small differences between rates are assumed to converge in the long term). real GDP and real GDP per capita significant. But ICP PPPs should not be interpreted as equi- ICP 2011 includes economies ranging from librium exchange rates. They have been calcu- city-states and small islands, such as Hong Kong lated specifically to enable international SAR, China and Qatar, to large and diverse econ- comparisons of prices and real expenditures for omies, such as Brazil, China, India, Russia, South GDP. They refer to the entire range of goods and Africa, and the United States. Because of the wide services that make up GDP and include many differences in the price and economic structures items that are not traded internationally. of economies and the inherent statistical variabil- Moreover, except for exports and imports, they ity in the methods used to calculate PPPs, the are valued at domestic market prices, and PPPs following guidelines are recommended for those for GDP are calculated using expenditure using the 2011 PPPs and real expenditures: weights that reflect domestic demand. For the same reason, ICP PPPs do not indicate whether • Comparisons between economies that are a currency is undervalued or overvalued and similar are more precise than comparisons should not be used for this purpose. between economies that are dissimilar. ICP comparisons are designed to compare the For example, the PPP between Nigeria and volumes of goods and services that enter GDP at South Africa is more precise than the PPP of specific points in time. They are not designed to either to Liberia or Zimbabwe. Comparisons measure the relative rates of growth in GDP between economies in the same region will between these points. Each ICP comparison pro- be more precise than between economies in duces indexes of real GDP that show the relative other regions. For example, the China-India volume levels of GDP among participating econ- comparison will be more precise than the omies for the reference year. When the indexes comparison of either to the United States. for consecutive reference years are placed side • PPPs based on the prices of goods are more by side, they appear to provide points in a time precise than PPPs for services. Areas such as series of relative GDP volume levels over the housing and health will have wider measures intervening years. This apparent time series of of error than those for food products. volume measures is actually a time series of value indexes because the volume indexes for • PPPs provide the overall price level of an each reference year are calculated using the economy, but do not capture price differences prices and expenditures for that year. Changes within an economy. in the volume indexes between reference years Because of the sampling errors and statistical are thus due to changes in the relative price errors arising from the calculation methods, dif- levels as well as changes in the relative volume ferences in real GDP of less than 5 percent levels. As a result, the rates of relative growth should not be considered significant. This mar- derived from the indexes are not consistent with gin of error can rise to plus or minus 15 percent those obtained from times series of GDP vol- for economies that differ widely in their price umes estimated by the economies themselves. and economic structures. This should be kept in The rates of growth estimated by the economies mind when using, for example, the PPPs of the should be used to determine relative rates of United States, China, India, and Brazil to com- growth in GDP. pare the economies not only with each other The PLIs for the household final consump- but also with more disparate economies such as tion expenditure provide a measure of the most of those in the Africa region. differences in the cost of living between economies—that is, they indicate whether the overall price level for consumer goods and ser- Correct usage of 2011 PPPs vices faced by the average household in one Linked to reliability is correct usage. PPPs appear economy is higher or lower than that faced by in international trade theory in the context of the average household in another economy. equilibrium exchange rates (the underlying Even so, people considering moving from one rates of exchange to which actual exchange economy to another should not use these PLIs Presentation and Analysis of Results 169 to infer how the change of economy will affect economies so that, if the prices are the same in their cost of living. For one thing, PLIs reflect the aggregate and “poor” comparisons, the PPPs the expenditure pattern of the average house- are not much affected. There are some excep- hold, which in all likelihood is different from tions, however, such as in economies that have that of the person contemplating the move. For extensive food subsidies so that the poor pay another, PLIs are national averages and do not lower prices. There would be more exceptions if reflect differences in the cost of living between the prices paid by the poor were systematically specific locations. different from the average prices in a way that differed from one economy to another. Some Reliability of PPPs for poverty analysis attempts have been made to measure such price differences, but there is no general agreement Global poverty numbers require a large and var- on how to do so, or on whether such differences ied set of data collected from different places, are important. Thus additional research will be time periods, and sources. Five unique data needed before international poverty rates can be sources are required for the World Bank’s calcu- estimated using ICP PPPs. lation of global poverty numbers and global poverty lines: household surveys, population censuses, national accounts, consumer price DIFFERENCES BETWEEN THE 2005 AND indexes, and PPPs from the ICP. Each new 2011 COMPARISONS round of the ICP brings revisions of the PPPs, and these revisions, like revisions of the other The ICP is designed to compare levels of eco- data sources, can have large effects on global, nomic activity across economies, expressed in a regional, and national poverty counts. The common currency, in a particular benchmark global poverty line itself is calculated as an aver- year. The ICP should not be used to compare age of the PPP equivalents of the poverty lines changes in an economy’s GDP volume over time: of the world’s poorest economies. In general, the national accounts volume estimates of each therefore, the global line will also change with individual economy are the best data source for new PPPs, even if the underlying national pov- this purpose. The 2005 and 2011 global compari- erty lines remain unchanged. sons are the first two that include comparable The PPPs for individual consumption expen- real expenditures for such a large number of ditures by households generated by ICP 2011 economies. With the release of ICP 2011 results, are designed to match the national accounts it is inevitable that many analysts will attempt to estimates of consumption, and the weights used compare the positions of economies in 2011 to construct them are the shares of each good or with those in 2005 by simultaneously studying service in the aggregate individual consumption changes over time and across economies. expenditures by households. The use of those However, many of the comparisons will be prob- PPPs for poverty measurement has sometimes lematical because they will be based on two dif- been criticized on the grounds that people who ferent price levels, and so real expenditures and live at or below the global poverty line have dif- PLIs will not be directly comparable between ferent patterns of consumption than the aggre- 2005 and 2011. In addition, some of the econo- gates in the national accounts. In particular, mies participating in one comparison were not in they spend a much larger share of their budgets the other comparison, a small number of econo- on food, and they spend very little on housing mies moved from one region to another, and, and essentially nothing at all on air travel or on most important, some significant changes in financial services indirectly measured, just to methodology were implemented in ICP 2011. take one example. Both the changes in the composition of regions PPPs offer comparisons across economies, not between 2005 and 2011 and the methodological across the rich and poor within economies. As a changes introduced in 2011 will affect any com- consequence, in comparisons of any two econo- parisons between ICP 2005 and ICP 2011. mies the shift from aggregate to “poor” weights ICP 2005 estimated the real expenditure should have roughly the same effect in both on GDP for 146 economies, ICP 2011 for 170 Purchasing Power Parities and the Real Size of World Economies 199 economies. The greater part of this increase • Calculating basic heading PPPs. In 2005 basic can be explained by the inclusion of 22 Caribbean heading PPPs were calculated using the coun- islands and 21 Pacific islands in ICP 2011. Other try dummy product (CPD) method without newcomers to ICP 2011 were Algeria and the assigning any weight at the product level. In Seychelles in Africa; Myanmar in the Asia and 2011 it was decided that products would be the Pacific region; Costa Rica, Cuba, Dominican classified as important or less important and Republic, El Salvador, Guatemala, Haiti, that weights of 3:1 would be used in comput- Honduras, Nicaragua, and Panama in the Latin ing basic heading PPPs at the intraregion level America region; and the United Arab Emirates and also in estimating linking factors. Thus and West Bank and Gaza in the Western Asia basic heading PPPs were calculated using the region. Economies that participated in ICP 2005 weighted country product dummy (CPD-W) but not in ICP 2011 included Argentina in the method. The classification and weighting of Latin America region and Lebanon and the products by their relative importance affected Syrian Arab Republic in the Western Asia region. the 2011 PPPs. Other changes in the composition of regions • Dwellings. In ICP 2005, Africa and the CIS were the result of Chile leaving the Latin used the dwelling stock approach, Latin America region to join the OECD and the America the rental approach, and Asia and Islamic Republic of Iran leaving the Asia and the the Pacific the reference volume approach, Pacific region and Georgia leaving the CIS to whereas Eurostat-OECD and Western Asia become singletons. used a combination of rental and dwelling The major methodological changes in ICP stock data. The regional results were linked 2011 were as follows: using dwelling stock data. In ICP 2011, Africa, Latin America, the Caribbean, and • Global linking and aggregation. The 2011 link- Western Asia calculated PPPs using rental ing procedures differ from those used in 2005 data collected for the global list of dwelling in two important respects: types; Asia and the Pacific used the reference – At the basic heading level. In 2005 only 18 volume approach; the CIS used dwelling economies participated in the Ring, a spe- stock data; and the Eurostat-OECD used a cial group of representative economies combination of rental and dwelling stock from ICP regions that priced a common list data. Linking was carried out in stages. The of products (the Ring list) to be used in Africa, Latin America, Caribbean, and linking regions, whereas in 2011 almost all Western Asia regions were linked using the participating economies contributed to the same rental data that went into the estima- interregional linking by pricing products in tion of their intraregion PPPs. For Asia and the global core list, the worldwide list of the Pacific, the CIS, and Eurostat-OECD, products designed to provide links between dwelling stock data were used to link them to regions. each other and then to the rest of the world. – At the aggregate levels above the basic heading. In 2011 a new procedure, the country • Government. In 2005 government consump- aggregation with redistribution (CAR), tion estimates were adjusted for productivity replaced the 2005 super-region method in differences between economies in three of which linking factors were computed for the six regions—Africa, Asia and the Pacific, regional aggregates. and Western Asia—but the regional linking The change in methods was based on the factors were computed without any produc- outcomes of an analysis of the 2005 results tivity adjustments. In 2011 the Africa, Asia that showed that the linking factors were and the Pacific, Latin America, and Caribbean overly sensitive to pricing problems in the regions used productivity adjustments when Ring economies. The 2011 methodology is computing their regional results, but no pro- considered a significant improvement over ductivity adjustments were applied within the 2005 linking method at both the basic the Eurostat-OECD, CIS, and Western Asia heading level and above. regions. The linking factors for all regions Presentation and Analysis of Results 171 were computed with productivity adjust- consistent across economies. The methods used ments to produce the global results. to produce the national accounts estimates that • Construction. The method used to estimate provide the basis for extrapolating PPPs can construction PPPs changed completely in ICP differ significantly from one economy to another, 2011 and is not comparable with that used in thereby affecting the reliability of extrapola- 2005. In ICP 2005, construction PPPs were tions. For example, economies differ in the ways estimated using a hybrid approach that com- in which they treat productivity changes over bined prices for some construction outputs time, in how they update their national accounts with those for some inputs. Because of the to take into consideration revised data or the difficulties encountered in implementing this introduction of new methodology, and in the approach, a simplified input method based methods they use to adjust price deflators for on the prices of basic materials, labor, and quality change. machinery was adopted for ICP 2011. The most common method used to interpo- late PPPs and real expenditures between ICP Aside from the methodological changes, benchmarks and to extrapolate from the most directly comparing the ICP estimates of real recent one the latest set of benchmark PPPs for expenditures for 2011 with those for 2005 is not each economy is a time series of price deflators a valid exercise. Not only did price levels change at a broad level (typically GDP but sometimes a between 2005 and 2011, but they also changed handful of major components of GDP). The pro- to a different extent across economies. Even cess involves comparing changes in national comparing the relative positions of economies accounts deflators for an economy with those in can be misleading when world or regional aver- a base economy and using these comparative ages are used as the basis for comparison. For movements to extrapolate from the latest ICP example, in the Asia and the Pacific region, benchmark. Some very restrictive assumptions whose economic activity is dominated by China, underlie this method, the most important of the relationship between the real expenditure which is that the economies have similar eco- for one of the high-income economies such as nomic structures and are evolving in a similar Hong Kong SAR, China, and the regional aver- way. Clearly, this is not the case when develop- age will decline between 2005 and 2011, even ing economies are compared with the United though the real GDP of that economy rose States, which is regularly used as the base appreciably between these two years. The rea- economy. Changes in an economy’s terms of son is that the regional average real expenditure trade also can have a significant effect on the on GDP increased even more than the real consistency of extrapolated PPPs and real GDP of Hong Kong SAR, China, because of the expenditures. In addition, the global financial dominance in the region of the rapidly growing crisis of 2008–09 affected economies very Chinese economy. differently, with some economies, mainly high- income ones, falling into recession for a year or more, while others continued to grow despite the financial crisis. COMPARING 2011 PPPs EXTRAPOLATED FROM ICP 2005 AND ICP 2011 Several assumptions relate to the consis- BENCHMARK PPPs tency of the methods used to estimate an economy’s national accounts with those used Purchasing power parities can be extrapolated at by the ICP. For example, the products priced any level, ranging from the most detailed, the by the ICP are carefully defined to ensure basic heading level, up to total GDP. Extrapolating comparability between economies, but the at the more detailed levels is likely to produce products priced in the time series used in better results when compared with successive estimating the volumes in an economy’s benchmarks, but it is more likely that an national accounts are selected to ensure that approach based on extrapolating at fairly broad they are the most representative products levels will generally be used in practice because available in the economy. In addition, the of a lack of detailed price deflators that are weighting patterns used in an economy’s price 172 Purchasing Power Parities and the Real Size of World Economies indexes are specific to that economy, whereas fixed-base methods to estimate their GDP vol- those underlying the ICP results are an umes. In practice, fixed-base volumes tend to amalgam of those for the economies partici- be biased upward for the most recent years, pating in the ICP. Finally, the prices in an which means that any deflators derived from economy’s price indexes, such as the con- them are biased downward. sumer price index, are adjusted for quality Experience has shown that sizable discrepan- changes over time, and economies do not use cies can arise between extrapolated estimates common methods to adjust for these changes. and a new benchmark, even when they are only For example, hedonic methods are used to a a couple of years apart. The gap between the lat- different extent in different economies, or not est ICP rounds was six years, which resulted in at all in many economies, with the result that some very large differences for many economies the quality-adjusted time series are not consis- between the extrapolated real expenditures for tent across economies. 2011 and the benchmark real expenditures that Many economies use chain-linked volumes have become available from ICP 2011. It is not in their time series because of the distortions possible to quantify separately the various fac- introduced by using a fixed base year for vol- tors underlying these differences. ume estimates for a lengthy period of time. As A detailed explanation of the issues underly- a result, the GDP deflators derived from chain- ing extrapolation is available in chapter 18 of linked volumes behave differently from those Measuring the Real Size of the World Economy for economies that use the more traditional (World Bank 2013). Presentation and Analysis of Results 173 Chapter 3 Data Requirements The International Comparison Program (ICP) The price approach is usually applied in ICP compares the gross domestic products (GDPs) of comparisons because prices are generally easier participating economies in real terms by remov- to observe directly than quantities, which are ing the differences in GDPs that are attributable required to directly estimate real expenditures. to differences in price levels and expressing the In addition, direct measures of relative prices GDPs in a common currency. The conceptual normally have a smaller variability than direct framework of an ICP comparison is determined measures of relative quantities. Even so, the by the definition of GDP, which for the 2005 and price approach is not applied in every instance. 2011 rounds of the ICP was the internationally Of the exceptions, the most notable are the real agreed-on definition of GDP in the System of expenditures for housing services, which are National Accounts 1993 or SNA93 (Commission measured directly via the quantity approach in of the European Communities et al. 1993). many economies. In such cases, PPPs are derived indirectly by dividing the real expenditures into the nominal values for the relevant aggregate(s). CONCEPTUAL FRAMEWORK The direct measurement of real expenditures and the indirect measurement of PPPs are General approach known as the quantity approach. ICP comparisons of price and real expenditure Each ICP comparison has a reference year, levels of GDP are based on the expenditure and the most recent one is 2011. The basic data aggregates of the national accounts using spatial that an economy participating in the comparison price deflators or purchasing power parities provides for the reference year are as follows: a (PPPs) as the measure of the price component. set of prices for a selection of products chosen In these cases, the prices of products constitut- from a common basket of precisely defined ing final demand are collected and compared goods and services, a detailed breakdown of the across economies to produce the price relatives, national expenditure according to a common PPPs, with which the GDPs and component classification, the economy’s exchange rates, expenditures being compared are deflated to and its resident population. The prices and obtain the real expenditure relatives. In other expenditures are used to calculate PPPs and real words, the price measures are derived directly expenditures (or volumes); the exchange rates and the real expenditure measures indirectly. and PPPs are used to calculate price level indexes; This is called the price approach. and the population totals and real expenditures 175 are used to calculate real expenditures per Expenditure approach capita. Prices and expenditures are reported in SNA93 defines GDP from the expenditure side national currencies. Both cover the whole range as the sum of the expenditures on final con- of final goods and services comprising GDP as sumption, gross capital formation, and net defined in the ICP expenditure classification in exports. Final consumption is the total expendi- appendix D of this volume. ture on the goods and services consumed by The ICP expenditure classification adheres to individual households or the community to the concepts, definitions, classifications, and satisfy their individual or collective needs. Gross accounting rules of SNA93. It gives the capital formation is the total expenditure on comparison structure. Economies are expected gross fixed capital formation, changes in inven- to estimate their national expenditure for the tories, and acquisitions less disposals of valuables. reference year broadly in line with SNA93 and Net exports are the difference between the to break down their GDP estimate into the value of goods and services exported and the component expenditures identified in the value of goods and services imported. ICP com- classification. The component expenditures parisons are based largely on PPPs calculated comprise different levels of aggregation. At the using prices collected for the component expen- lowest level of aggregation, they are called basic ditures of final consumption and gross fixed headings. The classification breaks down the capital formation. Prices are not collected for expenditure on final goods and services into 155 changes in inventories, the acquisition and basic headings that comply with the functional disposal of valuables, and net exports; they are and product classifications of SNA93. deflated with reference PPPs. Reference PPPs Basic headings are the building blocks of the are described in appendix G. comparison. They are the level at which expen- Expenditures on final consumption are ditures are defined and estimated, products are incurred by three of the five institutional selected for pricing, prices are collected and vali- sectors recognized by SNA93—households, dated, and PPPs are first calculated and averaged. nonprofit institutions serving households In theory, basic headings should be homoge- (NPISHs), and general government—but not neous, each covering a group of similar well- by financial corporations or nonfinancial defined goods or services, but in practice they corporations. Expenditures on gross fixed often are not. Basic headings are determined by capital formation are incurred by resident pro- the lowest level of final expenditure for which ducers of goods and services irrespective of economies in the comparison can be expected to institutional sector and include households estimate explicit expenditures. As a result, basic when engaged in own-account production headings can cover a broader range of products (e.g., subsistence production by a farmer). In than is theoretically desirable, and they can the ICP classification, expenditures on final include both goods and services. consumption are classified by the institutional For each basic heading, economies report sector making the purchase, with the final prices for a subset of products covered by the consumption expenditures of households, basic heading and their expenditure on the basic NPISHs, and general government identified heading. The prices are used to calculate PPPs and treated separately. No such distinction is for the basic heading, and the PPPs are used to made for expenditures on gross fixed deflate the expenditures on the basic heading, capital formation. which are at national price levels, to real expen- ditures at a uniform price level. The basic head- ing PPPs are subsequently aggregated, using the Actual Individual Consumption expenditures on the basic headings as weights, SNA93 classifies the expenditure on final con- to provide PPPs for each level of aggregation up sumption as either an individual consumption to the level of GDP. Real expenditures for an expenditure or a collective consumption expen- aggregation level are obtained by deflating the diture. The individual consumption expenditure expenditures on the aggregation level with the comprises the expenditures made by households, PPPs for the aggregation level. NPISHs, and general government on individual 176 Purchasing Power Parities and the Real Size of World Economies goods and services—that is, they benefit house- or general government, and thus misleading holds individually. The collective consumption conclusions about the relative material well- expenditure comprises the expenditures made being of economies can result. Comparing the by general government on collective services— actual individual consumption of economies, that is, they benefit households collectively. which covers the individual goods and services Health, education, and social protection are that households receive from NPISHs and examples of individual services. Defense, public general government as well as their own pur- order and safety, and environmental protection chases of individual goods and services, avoids are examples of collective services. such conclusions. In the ICP classification, the expenditure on final consumption is broken down into four Derivation of Actual Individual aggregates: (1) individual consumption expen- Consumption diture by households, (2) individual consump- The ICP classification is primarily an expendi- tion expenditure by NPISHs, (3) individual ture classification in which the final consump- consumption expenditure by government, and tion expenditure is structured by who pays. (4) collective consumption expenditure by However, because one of the principal aims of government. Each aggregate clearly indicates ICP comparisons is to compare actual individual who benefits from the expenditure—households consumption at various levels of aggregation, either individually or collectively—and who the results of comparisons are presented by who makes the expenditure—households, NPISHs, consumes. The classification is designed to allow or general government. SNA93 uses the the final consumption expenditures of house- distinction between who consumes and who holds, NPISHs, and general government to be pays to derive an additional aggregate: actual reclassified and combined according to whether individual consumption. they benefit households individually or collec- Actual individual consumption is the sum of tively. This is achieved by applying two classifi- the individual consumption expenditures of cations from SNA93: the Classification of households, NPISHs, and general government. It Individual Consumption According to Purpose is a measure of the individual goods and services (COICOP) and the Classification of the Functions consumed by households. It is particularly perti- of Government (COFOG)—see United Nations nent to comparisons of material well-being Statistics Division (1999a, 1999b). when well-being is measured in terms of the COICOP classifies the individual consump- individual goods and services that households tion expenditures of households, NPISHs, and consume. The alternative, the consumption general government by purpose. It ensures that expenditure by households on goods and the treatment of the three expenditures is con- services, is a measure of the expenditure incurred sistent and harmonized. In principle, the three by households rather than a measure of their expenditures should be broken down so that total consumption. It covers only the individual they can be compared and summed at the low- goods and services that households themselves est level of aggregation, the basic heading purchase and does not take into account the level. In practice, this is feasible only for the individual services that NPISHs and general individual consumption expenditures of house- government supply households as social trans- holds and general government because most fers in kind (e.g., subsidized medical services). economies cannot provide the required level of The financing and provision of individual ser- detail for the individual consumption vices, especially health and education, can vary expenditure of NPISHs. (In recognition of this considerably from economy to economy. If only constraint, the ICP classification requires econ- the individual consumption expenditure by omies to report a single figure for the NPISH households is compared, economies in which consumption expenditure. Prior to the calcula- households themselves purchase health care tion of PPPs for actual individual consumption, and education will appear to consume more the NPISH consumption expenditures than households in economies in which these reported by economies are distributed across services are provided (or subsidized) by NPISHs the relevant basic headings in the same Data Requirements 177 proportions in which their household con- and the PPPs calculated with the average of the sumption expenditures are distributed.) two prices. If the basic prices are not taken into COFOG classifies the outlays of general account, the PPPs will be overestimated and the government by function. As for the outlays on real expenditures underestimated. final consumption, it distinguishes between the The imputed rents of owner-occupiers are individual consumption expenditure and collec- also important, but many economies have tive consumption expenditure, defining the difficulty estimating them to international stan- former in line with COICOP. dards. This problem usually arises because they do not have a large representative rental market Imputed Expenditures that would allow them to use actual rents for Expenditures on final consumption and gross rented houses and apartments to estimate fixed capital formation include the actual expen- imputed rents for equivalent owner-occupied ditures covering monetary transactions and the houses and apartments as recommended by imputed expenditures covering nonmonetary SNA93. For such economies, volumes are esti- transactions. Expenditures on monetary trans- mated directly using a quality-adjusted quantity actions can be measured directly because a price approach based on housing stock numbers is stated in monetary units for each transaction. broken down by size of dwelling and the Expenditures on nonmonetary transactions percentage of dwellings having facilities such as cannot be measured directly because there is electricity, running water, a private toilet, a either no price or, in the case of barter, there is private kitchen, and central heating or no price stated in monetary units. Expenditures air-conditioning. on nonmonetary transactions are obtained by imputing a value to them. The values to be Nonmarket Services imputed are defined by the national accounting SNA93 distinguishes between market services conventions adopted by SNA93. The general and nonmarket services. Market services are rule is that the goods and services in a nonmon- sold at economically significant prices; nonmar- etary transaction should be valued at the basic ket services are supplied free or at prices that are prices at which they would be sold if offered for not economically significant. The individual sale on the market or, in the absence of basic services that general government purchases for prices, as the sum of their costs of production. households from market producers are bought The imputations of particular relevance to ICP at economically significant prices and are mar- comparisons are those made for goods that house- ket services. The individual services and the col- holds produce and consume themselves; gross lective services that general government itself fixed capital formation carried out by producers produces for households and that it provides on their own account, such as the construction of free or at noneconomically significant prices are dwellings by households; housing services that nonmarket services. owner-occupiers are said to purchase from them- Economically significant prices are prices that selves; financial intermediation services indirectly have a significant influence on the amounts pro- measured (FISIM); unfunded social insurance ducers are willing to supply and on the amounts schemes operated by general government for its purchasers wish to buy, and so they influence employees; and consumption of fixed capital by the amounts producers supply and purchasers NPISHs and general government. buy. By multiplying the quantities sold by the The consumption of own-account production prices at which they are sold, one could deter- of agricultural produce, preserved foodstuffs, mine the expenditure on market services, and wine and spirits is significant in many econ- although the values for most market services in omies. For ICP purposes, not only must the the national accounts are based on directly imputed expenditure be included in the estimate collecting the values (e.g., from a household of GDP so it will not be underestimated, but the survey). These are the same prices required to basic prices used to impute the expenditure must calculate the PPPs for market services. Because be weighted and averaged with the purchasers’ nonmarket services have no economically sig- prices collected from outlets for the same goods nificant prices, their expenditures and their PPPs 178 Purchasing Power Parities and the Real Size of World Economies cannot be derived in the same way that they are productivity differences can even have a signifi- for market services. Instead, following the con- cant effect on the real expenditures for GDP. In vention adopted by national accountants, ICP 2011, adjustments for differences in produc- expenditures on nonmarket services are esti- tivity were made to the real expenditure esti- mated by summing the costs to produce them, mates for government-produced nonmarket and their PPPs are calculated using the prices of services in the regional comparisons for Africa, inputs. This is known as the input price approach. Asia and the Pacific, Latin America, and the To implement the input price approach, one Caribbean. Productivity adjustments were not must break down the expenditures on nonmar- made in the regional comparisons for the ket services by cost components. The cost Commonwealth of Independent States (CIS) components identified in the ICP classification and Western Asia, nor were they made in the for government-produced health, education, comparison conducted by Eurostat and the and collective services are compensation of Organisation for Economic Co-operation and employees, intermediate consumption, gross Development (OECD). The reason was that dif- operating surplus, net taxes on production, and ferences in labor productivity between econo- receipts from sales (which are deducted from mies in each of these regions were considered to the value of output to derive the final be relatively small. Productivity adjustments consumption expenditure). Of these cost com- were made to all regions when they were com- ponents, compensation of employees is by far bined in the global comparison. the largest and most important. It is the only cost component for which the ICP collects Price approach prices. Reference PPPs are used for the other cost components. The real expenditures of economies participat- ing in an ICP comparison are generally obtained Productivity adjustments by deflating their national expenditures for the The disadvantage of the input price approach is reference year with PPPs for the reference year. that differences in productivity between econo- To ensure that the deflation of national expen- mies are not reflected in the real expenditures. ditures produces unbiased real expenditures, It is assumed that producers of nonmarket ser- the PPPs used as deflators have to be based on vices are equally efficient and that the same prices that meet three conditions. First, they level of input will yield the same volume of should be consistent with the prices underlying output regardless of the economy in which the the national expenditure estimates of the econ- producer is operating. However, this assumption omies. Second, they should be for products that is difficult to defend because of the degree to are comparable across the economies. And, which levels of economic development vary third, the products priced should be important among the economies participating in ICP com- items of expenditure within the economies. parisons. If productivity differences are not Deflating with PPPs based on prices that do not taken into account when calculating the real satisfy these three requirements can result in expenditures, they will be disguised as price dif- PPPs that are either too high or too low and a ferences. In economies in which input costs are corresponding underestimation or overestima- relatively low, the real expenditures on non- tion of real expenditures. market output would be overestimated, and in Comparability and importance are not neces- economies in which input costs are relatively sarily complementary. Consumption patterns high, the real expenditures on nonmarket out- can vary from economy to economy because of put would be underestimated. differences in taste, culture, climate, price struc- Failure to take into account productivity dif- tures, product availability, and income levels. ferences between the producers of nonmarket Products that are important in one economy are services in different economies affects not only not necessarily important in other economies, the PPPs and real expenditures for nonmarket and products that are strictly comparable across services, but also the PPPs and real expenditures economies are unlikely to have equal impor- for GDP. In some cases, not adjusting for tance in all of them. At times, a choice has to be Data Requirements 179 made between pricing a comparable but less transaction prices. Rather, they have to collect important product and pricing an important the prices that purchasers would have to pay if product that is not comparable. When such a they were to purchase the goods and services choice has to be made, comparability has prior- specified at the time of the price collection. In ity over importance. If products are not compa- other words, in practice the prices at which rable, there can be no valid comparison because goods and services are offered, and not actual like is not being compared with like. If products transaction prices, should be observed. However, are comparable but not equally important, a before recording an offer price as the purchaser’s comparison can be made, although the result price, the price collector must first establish may be biased. whether the price includes nondeductible value added taxes, discounts, and, if relevant, delivery Consistency and installation costs, invoiced service charges, ICP comparisons are based on an identity: value = and voluntary gratuities. If not, the price collec- price × volume. If volumes are to be derived tor must adjust the offer price accordingly. correctly, then the prices that economies provide for the comparison should be consistent with Total Price the valuation methods used to estimate their For most products, collecting the purchaser’s national expenditures. In principle, the national price is relatively straightforward because a pur- expenditures reported for the reference year are chase normally involves a transaction between a compiled according to SNA93, which calls for seller and a single buyer. But this is not always expenditures to be estimated using the purchas- the case. Certain products purchased from mar- ers’ prices for actual transactions. To be consis- ket producers can entail a transaction involving tent with SNA93, economies have to collect the a seller and two independent buyers. Such prices that purchasers actually pay sellers to transactions are particularly prevalent in health acquire a particular good or service. Transaction services where the provider of the service can be prices paid by purchasers include the supplier’s paid in part by households and in part by a sec- retail and wholesale margins, transport and ond party (government, NPISH, or private insurance charges, and any nondeductible value health insurer). When there are two purchasers, added tax on products. They should also be net there are two prices and two expenditures. prices that include all discounts, surcharges, What is consistent in these circumstances? rebates, and, for certain services, invoiced ser- Should PPPs be calculated separately for each vice charges and voluntary gratuities. Moreover, buyer based on the prices each pays and their because the national expenditures cover the expenditures deflated accordingly? Or should whole economic territory of an economy, the the PPPs used to deflate the expenditures be prices should be national averages that take into based on the total price—that is, the sum of the account regional variations in prices within the price paid by the household and the price paid economic territory. They should also be annual by the second party? With the first option, the averages that take into account seasonal varia- PPPs used to deflate the two expenditures will tions in prices, general inflation, and changes in be based on prices that are consistent with the price structures during the reference year. prices underlying the expenditures, but the real Ideally, economies would collect national expenditure on health services will be twice annual purchasers’ prices for actual transactions what it should be. With the second option, the from purchasers, but, because it is neither prac- PPPs used to deflate the two expenditures will tical nor cost-effective to do so, the prices are not be based on prices that are consistent with collected from sellers instead. Most sellers dis- the prices underlying the expenditures, but the play the prices at which they are prepared to sell real expenditure on health services will be their products, but the prices at which products correct, which is the primary objective of consis- are offered for sale are not necessarily the prices tency. For ICP comparisons, PPPs for the expen- at which they are actually sold. Unless price col- diture on health services are calculated using lectors have access to data on actual transactions the total price, which is consistent with the such as scanner data, they cannot collect actual expenditures when combined. 180 Purchasing Power Parities and the Real Size of World Economies Comparability descriptions (SPDs) introduced during ICP 2005. The national annual purchasers’ prices that They standardize the product specifications for economies supply for the comparison should be different types of products so that all specifica- for products that are comparable between them. tions for a specific product type are uniformly Products are said to be comparable if they have defined and list the same technical and transac- identical or equivalent physical and economic tional characteristics that price collectors have to characteristics. Equivalent means the products match. The purpose of SPDs is to improve the meet the same needs with equal efficiency so precision of the specifications and to simplify that purchasers are indifferent between them price collection. The more precise a specification and are not prepared to pay more for one prod- the easier it is for price collectors to determine uct than for the other. The pricing of comparable whether the product in an outlet matches the products ensures that the differences in prices product specified. SPDs identify those character- between economies for a product reflect actual istics that are price-determining because only price differences and are not influenced by differ- characteristics that have an impact on the price ences in quality. If differences in quality are not of the product should be included in the product avoided or corrected, they can be mistaken for specification. Characteristics that do not have an apparent price differences, leading to the under- effect on price do not need to be specified. They estimation or overestimation of price levels. do not affect comparability, and their inclusion Comparability is obtained in ICP comparisons only increases the number of characteristics to by economies using product specifications in be matched. This can make it more difficult for their pricing that fully define the products in a price collector to find the product in an outlet, terms of the principal characteristics that influ- and fewer prices will be collected as a result. By ence their transaction prices. Product specifica- focusing on the characteristics that influence tions can be brand- and model-specific (that is, a price, SPDs strike a balance between the need particular brand and model are stipulated), or for precision and the need for a sufficient num- they can be generic (that is, only the relevant ber of price observations. technical parameters and other price-determining characteristics are specified, and no brand is Importance designated). Ideally, all product specifications In addition to being comparable across econo- would be brand- and model-specific so that mies, the products that economies price for the economies would price products of identical comparison should be products that reflect, or quality. In practice, however, this is not possible are characteristic of, their final expenditures. In in many cases because the brand or the model is other words, the products should be important not generally available or, if available, is not an items of expenditure. Usually, such products are important item of expenditure, and so generic volume sellers. Products that are important gen- specifications have to be employed. Generic erally have a lower price level than products specifications are typically looser than brand and that are less important, and this factor has to be model specifications, and some variability in taken into account when choosing products for quality between the products priced by econo- the product list and when calculating the PPPs mies can occur. Differences in quality can arise for a basic heading; otherwise, the PPPs can be because economies price products that do not biased. Either they will be either too high and match exactly the product specifications, or yield real expenditures that are too low, or they because the products priced appear to match the will be too low and yield real expenditures that product specifications exactly but the product are too high. To avoid such a situation, econo- specifications are too loose or too open-ended to mies are expected to (1) ensure that a sufficient ensure that economies price products of the number of their important products are included same quality. Differences in quality are usually in the regional product list when drawing up the identified and corrected when the price data product list prior to price collection (at least one are validated. important product per basic heading); (2) price Product specifications for ICP comparisons the important products of other economies as are defined using the structured product well as their own important products during Data Requirements 181 price collection (otherwise, the number of over- ICP comparisons ensure that any imbalance laps between economies will be insufficient and between economies in the number of impor- no comparison can be made); and (3) indicate tant and less important products priced does which of the products they priced are important not produce biased PPPs. The methods give and which are less important when reporting greater weight to important products. prices after price collection so that the product’s importance can be taken into account during the validation of prices and the calculation of SURVEYS AND DATA COLLECTION basic heading PPPs. Coverage of surveys The importance of a product is determined by its share of expenditure in its basic heading. The Economies participating in ICP 2011 collected decision about whether a product is important is prices for a selection of the goods and services made in the context of its basic heading and is that make up the final consumption expendi- independent of the relative importance of the ture and gross fixed capital formation. The basic heading with respect to other basic head- four principal price surveys that economies ings. Whether its basic heading has a high or low conducted covered (1) consumer goods and share of GDP expenditure is not a consideration services (also known as the main price sur- when deciding a product’s importance. Defining vey), (2) compensation of employees paid by importance by reference to expenditure shares is general government to employees producing problematic because usually there are no explicit individual and collective services, (3) machin- expenditure details below the basic heading ery and equipment, and (4) construction and level. The relative importance of the various civil engineering (all described in the separate products within a basic heading has to be deter- sections that follow). Because the household mined by other means, using alternative sources consumption expenditure accounts for over of information. Examples of such sources for 60 percent of GDP in the majority of econo- consumer products are the consumer price index, mies, the most important of the four price retail price index, household budget surveys, and surveys was the survey of consumer goods retail trade surveys. More generally, information and services. It included a wide assortment of can be obtained by consulting marketing experts, products, ranging from food, beverages, producers, importers, distributors, sales manag- clothing, footwear, electricity, furniture, and ers, shop buyers, and the Internet. household appliances to motor vehicles, Ideally, the product list would be balanced. transport services, audiovisual and informa- For each basic heading, the number of impor- tion processing equipment, restaurants, hotels, tant products to be priced and the number of and hairdressers. less important products to be priced would be Pricing of most of these consumer products the same for each economy. The number was relatively straightforward. Price collectors would not be the same for all basic headings; it visited a sample of outlets, identifying products would vary with the importance and homoge- in the outlets that matched the product specifi- neity of the basic heading. A comparison based cations on the product list and recording their on a list of products that is not balanced may prices. But some consumer goods and services result in biased price relatives. There is a risk required a different or more focused treatment, that price levels for economies pricing a smaller and these were surveyed separately from other number of important products will be overesti- consumer products. Separate surveys were orga- mated and that price levels for economies nized for housing services, private health pricing a larger number of important products services, private education, water supply, and will be underestimated. In practice, though, fast-evolving technology products. These five the product list will not be balanced. Each surveys and the price surveys for compensation economy will not have the same number of of employees, machinery and equipment, important and less important products for and construction and civil engineering men- each basic heading. However, the methods tioned earlier were referred to collectively as the used to calculate PPPs for a basic heading in special price surveys, thereby emphasizing their 182 Purchasing Power Parities and the Real Size of World Economies specificity as well as distinguishing them from Particular care was taken with the global core the main price survey covering consumer goods product list for the main price survey. and services. Consultation was an iterative process, with the list evolving in line with the comments and pro- posals of those consulted. Considerable effort Global core products was made to ensure that the list was not The 2011 global comparison combined seven dominated by the products of any one region regional comparisons—six ICP regional compari- and that the products were global so that they sons (Africa, Asia and the Pacific, CIS, Latin could be priced across most if not all regions. America, the Caribbean, and Western Asia) and The final version of the list specified 618 core the Eurostat-OECD comparison—in a single consumer products. comparison. The Pacific Islands priced a separate For the main price survey, regions developed product list that did not include the global core their own regional product list by revising their products. Linking the seven regions into a global regional product list from ICP 2005. Products no comparison was achieved by using global core longer available or problematic were dropped; products—that is, products that had been selected products still available were retained and their for the specific purpose of providing links or specifications updated; and new products, fully overlaps between the regional comparisons in specified, were added to replace deleted products which they were priced. For the main price sur- and to stay abreast of market trends. The global vey and for each of the special price surveys, the core products were combined with those on the Global Office compiled a list of global core prod- revised regional lists, and care was taken to ucts in consultation with regional and national avoid duplication. Regional products that coordinators and, in the case of the special price matched a global core product exactly or were surveys, with subject matter experts. SPDs were comparable to a global core product were used to define the price-determining characteris- removed from the regional list and replaced by tics of the products. Table 3.1 presents the num- the global core product. ber of priced global core products per region and The economies in a region were asked to survey and the total number of global core prod- review the global and regional products on the ucts for each survey. regional list and indicate the availability and Table 3.1 Number of Priced Global Core Products per Region and Survey, ICP 2011 Household Housing Private Government Machinery and consumptiona rentals education compensationb equipment Construction Africa 610 64 7 209 176 137 Asia and the Pacific 412 64 6 41 160 124 c Commonwealth of Independent States 560 n.a. 3 25 132 114 c d d Eurostat-OECD 394 n.a. n.a. 19 131 135 Latin America 489 51 7 31 175 144 Caribbean 446 8 5 42 75 157 Western Asia 606 64 7 210 174 156 Total number of global products 618 64 7 210 177 165 Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable. An item is counted as priced if at least one country within a region priced it. In addition to the priced global core products, economies also priced regional products for regional comparisons. a. Excluding housing and private education, which are counted separately in this table. b. Two regions—Africa and Western Asia—provided remunerations for all four levels of experience, in addition to average remunerations, and the remaining regions provided average remunerations only. See the section on compensation of government employees later in this chapter for more information on government remunerations. c. The quantity data for housing were used for linking the CIS and Eurostat-OECD. d. The Eurostat-OECD implements a different approach for education, and thus it does not provide data on private education or on the compensation for education-related occupations. Data Requirements 183 importance of each product specified. Inclusion diverging price levels. Underrepresentation of in the final regional list depended on a product’s rural areas, for example, could result in overes- availability within the region (the number of timation of the national price level for those economies in the region that could price it) and items such as food products whose price levels on its importance within the region (the num- are generally lower in rural areas than in urban ber of economies in the region that could price areas. However, not all types of products are it and for which it was important). When final- available in rural areas, and when this occurs izing its lists, a region endeavored to ensure the urban price level is also the national that, as a minimum, each economy in the price level. region could price at least one global core prod- Prior to selecting outlets, economies were uct and three regional products for a basic head- required to classify the outlets in each geograph- ing. Global core products selected for the final ical stratum by type. For ICP purposes, nine regional list were treated as regional products categories of outlets were identified: supermar- meeting the same validation criteria and kets and department stores; kiosks, neighbor- included in the calculation of regional PPPs. hood shops, grocery stores, and the like; open With the exception of the CIS and Eurostat- and closed markets; mobile shops and street OECD, the regions did not draw up their own vendors; wholesale stores and discount shops; product lists for the special price surveys. Instead, specialized shops; private service providers; as in ICP 2005, the global core product lists for public service providers; and Internet shopping the special price surveys doubled as the regional sites. Later, when selecting outlets, the national product lists for the surveys. The CIS and coordinators were expected to ensure that each Eurostat-OECD identified products on their lists outlet type was adequately represented in order that matched those on the global lists. to accommodate the different distribution pro- files of different product types during price col- lection. In other words, the mix of outlet types Survey frameworks selected would allow for the possibility that the The objective of the main price survey and the mix of outlet types visited to price foodstuffs special price surveys was to collect prices that would not necessarily be the same as the mix were consistent with the prices underlying the visited to price clothing or the mix visited to national expenditures that economies had esti- price household appliances. In making the selec- mated for 2011. Because their estimates covered tion, the national coordinators had to take into the whole of their economic territory through- account the sales volumes of both individual out 2011, the prices collected had to be the outlets and outlet types, the variability in prices national annual averages for 2011. Moreover, both within and between outlet types, the loca- because economies compiled their estimates tion and distribution of outlets, and the number broadly in line with SNA93, the prices had to be of outlets per outlet type. those that purchasers actually paid to sellers, A similar approach was adopted for the although, for practical reasons, they had to be special price surveys, although the selection of collected from sellers rather than purchasers. outlets was more focused: real estate agents The fact that the average prices had to be (plus newspapers and the Internet) for the national averages and the averages had to be rental part of the housing survey; pharmacies derived from the prices observed at sales outlets and private providers of health services for the had implications for the survey framework, par- private health survey; private schools and col- ticularly that for the main price survey. leges engaged in primary, secondary, or tertiary When drawing up the survey framework for education for the private education survey; the main price survey, economies were required shops and specialist stores selling audiovisual, to ensure that their economic territories were photographic, and information processing stratified so that all parts of the territory were equipment for the survey of fast-evolving tech- represented. Balanced coverage of both urban nology products; central, state, and local and rural areas is important because the two government units for the survey of the compen- frequently exhibit different pricing patterns and sation of general government employees; 184 Purchasing Power Parities and the Real Size of World Economies producers, importers, and distributors of equip- their economy) or less important (it would ment goods for the survey of machinery and account for a relatively small share). Economies equipment; and construction contractors for the were expected to price important products construction and civil engineering survey. and a selection of less important products in The selection of products to be priced was order to provide the links with prices collected made by basic heading. Economies based their by other economies. When reporting prices, selection on the availability of the product in the economies were required to indicate which of economic territory and the importance of the the products priced were important and which product relative to other products in the basic were less important. Important products were heading. For the main price survey, economies given a bigger weight than less important prod- were required to select at least one global core ucts when calculating an economy’s PPP for product and three regional products from the a basic heading. combined global-regional product list for each basic heading. The heterogeneity and impor- Housing Services tance of the basic heading were deciding factors The household expenditure on housing ser- in the number of products that were selected for vices constitutes a single basic heading in the the product list for the basic heading. They were ICP classification and covers actual rents and also factors influencing the number of products imputed rents. Actual rents are the rents that that economies selected to price for the tenants pay to the owner of the dwelling they basic heading. are leasing. Imputed rents are estimates of the rents that owner-occupiers would have to pay for their dwelling if they rented it instead of Consumer goods and services (main survey) owning it. SNA93 recommends that imputed As noted, the main survey covered all con- rents be estimated using the actual rents paid sumer goods and services except housing ser- for equivalent dwellings. An equivalent dwell- vices, private health, private education, and ing is one that is the same type and size, has fast-evolving technology products; special sur- the same facilities, and is in the same location veys were organized for these areas (these sur- with the same neighborhood amenities. For veys are described in the sections that follow). economies applying the rental equivalence Prices for the main survey were collected from method, the price approach can be used to a sample of outlets in rural and urban areas. compute the PPPs directly for both actual and Most economies collected prices quarterly imputed rents. throughout 2011. The main exceptions were Implementation of the rental equivalence the Eurostat-OECD economies, which surveyed method requires a well-organized and represen- prices over three years: 2010, 2011, and 2012, tative rent market. Economies in which such and adjusted the prices to averages for 2011 a market does not exist cannot use rental using detailed times series price indexes. In equivalents to estimate imputed rents, and so addition, the majority of Eurostat-OECD econo- another method has to be employed. SNA93 mies collected prices only in their capital cities. recommends summing the costs of production (How these prices were converted to national of the housing service, but in ICP 2011 this was average prices for 2011 is explained in not the alternative followed by the majority of appendix C.) Some African economies began by economies not using the rental equivalence collecting prices monthly, but later changed to method. Instead, a variety of approaches that quarterly price collection. did not conform to international standards were When selecting products to price from the used—such as not making an imputation, mak- regional product list, economies were asked to ing an imputation only for urban areas, or take into account the importance of the prod- asking owner-occupiers what rent they would ucts listed by classifying those products that pay if they rented their dwelling—and the were available in their economic territory as expenditure estimates that resulted were of either important (it would account for a signifi- poor quality. In economies that did not apply cant share of the basic heading expenditure in the rental equivalence method, the PPPs for Data Requirements 185 housing services were obtained indirectly using by location—large urban areas, small urban the quantity approach. areas, and rural areas. The special survey for housing services was For each section, economies were expected designed to collect data for both the price to report the number of dwellings, the number approach and the quantity approach. For the of rooms, the usable surface area, the number price approach, the global core product list of occupants, and the land area occupied by the specified 54 dwellings of which 12 were tradi- dwellings—these were the indicators for the tional dwellings and 42 were modern dwell- quantity measure. Economies were also ings. Traditional dwellings were specified by expected to report the number of dwellings their size, facilities, and age. The facilities iden- with electricity, inside water, private toilet, cen- tified were electricity, inside water, private toi- tral heating, and air-conditioning—these were let, and private kitchen. Some of the traditional the indicators for the quality measure—as well dwellings had all the facilities, some had none, as the percentage of dwellings rented and the and the others had various combinations. percentage owner-occupied. All economies, Modern dwellings were broken down by type— including those pricing the rental specifications individual single-family house or villa, detached for the price approach, were required to com- or row house, studio apartment, one-bedroom plete the reporting form for the quantity apartment, and two-bedroom apartment—and approach. The data supplied by economies then by size and age. All modern dwellings were to refer either to 2011 or to a year close were specified as having electricity, inside to 2011. water, private toilet, and private kitchen, and The Eurostat-OECD comparison employed about half were specified as also having either the same dual approach as the ICP regions— central heating or air-conditioning. For both that is, PPPs and real expenditures were based traditional and modern dwellings, age was on a mix of rental data and housing stock data. defined as less than five years or more than five The rental specifications used for the compari- years (although regions could change this son differed from the global core specifications, parameter if they wished). but the quantity and quality data collected Regions were expected to select from the were similar. global core product list those specifications that were relevant to the region. When pricing the Private Health specifications selected, economies were required For ICP 2011, the health expenditure was bro- to collect annual rents for 2011 in both urban ken down into the expenditure by households and rural areas and to report national annual and the expenditure by general government. average rents. The PPPs for actual and imputed Subsequently, the household expenditure was rents were calculated using the national annual broken down into the expenditure on medical average rents that economies reported. products (which included pharmaceuticals), Estimating the volume of housing services outpatient services, and hospital services, and directly by the quantity approach involves first the government expenditure was broken down calculating a measure of relative quantity and a into the expenditure on health benefits and measure of relative quality between economies. reimbursements and the expenditure on the Subsequently, the quality measure is used to production of health services. Prices were convert the quantity measure into a real expen- collected from market producers for medical diture (volume) measure. Therefore, for the products and outpatient services, but not for quantity approach the special survey on housing hospital services (except in the Eurostat-OECD services collected data on the quantity and qual- comparison, as explained in appendix C). The ity of the housing stock. The reporting form had PPPs calculated using prices collected from mar- three sections: the first covered all dwellings ket producers for medical products and outpa- irrespective of type and location; the second tient services were used to deflate both the covered dwellings by type of construction— household expenditure and the government modern houses, modern apartments, and tradi- expenditure (under health benefits and reim- tional dwellings; and the third covered dwellings bursements) on these goods and services. The 186 Purchasing Power Parities and the Real Size of World Economies PPP for outpatient services was also used as the available as brand-name products or as generic reference PPP for the household expenditure on products. Brand-name products are medicines hospital services. produced and sold by their innovative pharma- PPPs for government-produced hospital ceutical companies. A generic product is services, which are supplied free or at prices identical (bioequivalent) to an existing brand- that are not economically significant, were name medicine in dosage form, safety, strength, obtained using the input price approach. route of administration, quality, performance, For this approach, the compensation that and intended use. Although chemically government paid to employees in a selection of identical to its branded counterpart, a generic occupations supplying medical, technical, medicine is typically sold at a lower price than administrative, and support services in govern- the branded product because the drug has ment hospitals was collected as described already been tested and approved. In general, shortly. The PPPs were used to deflate the the only differences between the brand-name expenditure on government-produced hospital product and the generic product are the price services as well as the government expenditure and the trade name. To compare the prices of on hospital services under health benefits the two directly would lead to biased PPPs. and reimbursements. This bias was avoided by comparing the prices The special survey for health collected prices of brand-name products with brand-name for pharmaceutical products; other medical products and the prices of generic products products; therapeutic appliances and equip- with generic products. Finally, drugs may be ment; and medical, dental, and paramedical sold in different quantities in different econo- outpatient services. Prices were collected from mies. This problem was overcome by convert- market producers, generally quarterly. The ing the price for the quantity observed and prices collected were total prices—that is, the reported by the price collector to a price for the total amount paid for the good or service to its quantity specified. When the product was provider—which is not necessarily straightfor- available in a range of quantities other than ward in the case of medical products. Although the specified quantity, the price collector was the sale of most consumer products involves a required to collect prices for the range. These transaction between a seller and a single prices were subsequently rebased to the speci- buyer, the sale of medical products can entail fied quantity and averaged. a transaction involving a seller and two Other medical products are sold not only independent buyers. The seller is paid in part over the Internet and in pharmacies, but also in by a household and in part by a second party supermarkets, petrol stations, and low-cost (such as government, NPISH, or private health optician chains, whereas therapeutic appliances insurer). For such transactions, price collectors and equipment are sold by the suppliers of were required to establish the total price by medical equipment. Economies were required consulting either the seller or the second party to include such outlets in their sample of out- because both would be aware of what the lets in proportion to their share of total sales household pays. when pricing other medical products and Pricing pharmaceutical products posed therapeutic appliances and equipment. As with additional problems. First, the same product pharmaceutical products, the total price had to can be sold under different names in different be collected. economies. For this reason, the identification Total prices were to be collected for outpatient of pharmaceutical products has to be based on health services as well, but this was not always the active substance or active ingredient and its possible, and the prices had to be estimated. In strength. This requires specialist knowledge, some economies, households do not pay any- which is usually not available in statistical thing to the private service provider for the offices. Thus price collection forms had to be outpatient service received because the private completed either by the pharmacist or by the service provider is reimbursed by the social price collector in consultation with the phar- security system under a general agreement macist. Second, pharmaceuticals may be between the government and private health Data Requirements 187 service providers. In other words, no actual (textbooks and stationery) and on educational price may exist for a particular service—the support services (health transport, catering, and government simply pays the private service accommodation) were not to be included. provider a lump sum payment. This sum may Schools and colleges often reported fees that be based on the total number of visits to a given covered the cost of educational materials and clinic, the size of the population living in a support services as well as the cost of tuition. given area, the number of persons registered When this happened, economies were required with the private service provider, and so forth. to estimate the cost of the materials and support If the second party is a NPISH or a private services and subtract it from the total reported health insurer, the situation might be similar— to obtain the cost of education. that is, it may not be possible to obtain directly The tuition fees supplied by economies were the prices related to a certain individual service. the annual averages for 2011. However, the Economies were required to consult with academic and school years do not necessarily health service experts to identify the best way coincide with the calendar year, and economies of establishing reliable estimates of the total were expected to adjust fees to a calendar year prices paid for the outpatient health basis if the academic or school year extended services specified. over two years. For example, if the academic or school year ran from the beginning of September Private Education to the end of June, economies were required to The ICP expenditure classification distinguishes add six-tenths of the fees for the school year between the expenditure on education by that began in September 2010 to four-tenths of households and the expenditure on education the fees for the school year that began in by general government. The expenditure on September 2011. education by NPISHs is not identified separately, The tuition fees and hourly fees that econo- although it is included in the total individual mies reported were supposed to be national consumption expenditure reported for NPISHs. averages as well as annual averages. Fees were PPPs for government expenditure on education collected directly from a selection of private were obtained using the input price approach. schools and colleges. The selection reflected the For this, the compensation that government distribution of all types of private schools and paid to employees in a selection of occupations colleges operating in the capital city, in urban supplying educational, administrative, and sup- areas other than the capital city, and in rural areas. port services in government schools and colleges Economies in the Eurostat-OECD comparison was collected as described shortly. PPPs for did not follow the price approach just described. household expenditure were calculated using They did not collect tuitions from private the tuitions collected by the special survey for schools and colleges, nor did they collect the private education. compensation of employees from government The special survey collected tuitions from schools and colleges. Instead, the quantity private schools and colleges for seven global approach was applied, with a quality adjustment core products: primary education; lower based on country scores from the Programme for secondary education; upper secondary educa- International Student Assessment (PISA). tion; tertiary education: a degree in computer Real expenditures were estimated directly, and science; tertiary education: a degree in the PPPs were estimated indirectly, as explained humanities or social sciences; a foreign language in appendix C. course; and a private lesson in mathematics outside school hours. For primary, secondary, Fast-Evolving Technology Products and tertiary education, economies collected Products based on fast-evolving technology tend annual tuition fees. For the language course to have short life cycles, making it difficult for and the private lesson, economies collected economies to price the same product through- hourly fees. Both the tuition fees and the out the reference year. A further complication is hourly fees were to cover only the cost of edu- that new models are not necessarily introduced cation. Expenditures on educational materials in all economies at the same time, or they are 188 Purchasing Power Parities and the Real Size of World Economies introduced with minor variations between nonmarket services. They are not sold at economies. To deal with this problem, the economically significant prices, and, in the following approach was adopted. It involved absence of such prices, their outputs are valued pricing two sets of products: one in the first half by summing the costs of their production, and of the year and the other in the second half of their PPPs are calculated using the prices of the year. The approach was limited to audiovi- inputs. In practice, prices are collected only for sual equipment, photographic equipment, and the most important input, compensation of information processing equipment for which employees. Reference PPPs are used for the the problem is especially acute. Together, the other inputs. three types of equipment constitute a single ICP comparisons used the input price basic heading. approach to compute PPPs for collective services Prior to price collection, a set of products was and for the two most important individual selected for the basic heading and included in services produced by government: health and the global core product list. The selection focused education. Reference PPPs were used for the on products that were widely available and had other individual services produced by a small number of alternative models and that government—housing, recreation and culture, had a relatively long life span with clearly iden- and social protection. tified replacement models. Particular care was The special survey of the compensation of taken to ensure that all the key price-determining government employees for ICP 2011 covered parameters of the selected products were a selection of occupations in collective services, included in their specification. Rather than public health services, and public education specifying a brand and a specific model, the services. This selection was made so that they product list specified a brand and a series. Price represent the various education and skill levels collectors were expected to price the cheapest that are commonly found among employees model available in the series specified. If models working in these three government services. in the series were not available, price collectors Thirty-seven occupations were included in had to price a model from another series whose the selection. The civilian occupations were parameters were the closest to those specified defined using job descriptions taken from the and note the model number and differences in International Standard Classification of parameters. Economies priced this set of prod- Occupations 2008 (International Labor Office). ucts during the first and second quarters of These descriptions specified the occupations in 2011. Meanwhile, a second set of products was terms of the kind of work done. selected and specified for the global core product Of the 37 occupations, 23 were for collective list. Economies priced this second set in the services, 10 for public health services, and 9 for third and fourth quarters of 2011. PPPs were public education services. Thirty-four of the calculated using products from both sets. occupations were specific to only one service, one was common for two services, and two were common to all three services. Because Compensation of government employees work such as cleaning and catering were out- Government provides households with both sourced to private companies on contract to the collective and individual services. Collective ser- government, some occupations were no longer vices are produced by government, whereas relevant in some economies and could not be individual services can be produced by govern- priced by them. ment, or they can be purchased by government The national coordinators were expected to from market producers. The individual services provide the compensation of employees for as that government purchases from market many of the selected occupations as possible. producers are called market services. Their Compensation of employees as defined in outputs can be valued and their PPPs calculated SNA93 comprised the basic salary or wage, using the economically significant prices at allowances and cash payments over and above which they are sold. The collective and individ- the basic salary or wage, income in kind, and ual services that government produces itself are the employer’s social security contribution. Data Requirements 189 When the government did not place social within the same level of government—that is, security payments in a separate fund for its between different ministries and departments of employees, economies were required to report central government or between different the imputed contribution calculated in the same regional governments, state governments, or way as in their national accounts. For each local governments. The national coordinators occupation, economies were expected to supply were advised to calculate weighted averages compensation data for an employee at four based on the number of employees. stages of his or her career: starting level, after 5 For each occupation and career stage, the years, after 10 years, and after 20 years. national coordinators also had to supply infor- The national coordinators were required to mation on the official and actual hours worked use official government pay scales to determine per week, the number of workdays per week, the compensation of employees in the selected the number of days of paid annual leave, and occupations. The basic salaries and wages laid the number of public holidays falling on work- down in government pay scales were the basis ing days during the reference year. These data for the compensation of employees by govern- were needed to compute compensation per ment. Once the basic salary or wage was estab- hour. PPPs were calculated using the compensa- lished for an occupation, computing the tion per hour for the 37 occupations, each with compensation of employees was relatively four career stages, and also for the average straightforward because the other components remuneration for each occupation. of compensation of employees are normally Economies in the Eurostat-OECD compari- related to the salary scale by being defined as son reported the compensation paid to govern- percentage additions to the basic salary or wage. ment employees working in selected occupations Pay scales are typically made up of grades. in collective services and public health services. Each grade has a number of levels, and each For the ICP 2011 global comparison, they also level has a number of steps. Grades usually reported the compensation paid to government reflect education and skill requirements; levels, employees working in selected occupations in experience and responsibility; and steps, years public education services. There was a good of service. Each step is generally 12 months, overlap between occupations selected for the although steps of 18 or 24 months are not global list and those selected for the Eurostat- uncommon. To derive the compensation of OECD list. However, the compensation of employees for the selected occupations and employees reported for an occupation was the career stages, the national coordinators had to average compensation paid for the occupation first locate the grade, level, and step for each for a standardized number of working hours and selected occupation and career stage in the did not take into account career stages. Moreover, government pay scale. This provided the basic it was extracted from the government payroll salary or wage for the selected occupation and and not from government pay scales. career stage, which could then be augmented as appropriate to arrive at the compensation of Machinery and equipment employees for the occupation and career stage. The compensation of employees reported for To determine the availability of the products each selected occupation and career stage had to initially selected as core products for the special be annual. When there were revisions of the sal- survey of machinery and equipment prices, the ary or wage scales during the reference year, a Global Office carried out a pilot study in nine weighted average was calculated based on the economies. The list of core products priced number of months the original scale and the during the special survey was based on the find- revised scale were operational. The compensa- ings of the pilot study. In line with the ICP tion of employees also had to be the national expenditure classification, the list covered eight average, taking into account the discrepancies in basic headings as shown in table 3.2. For each compensation that may arise between the sev- basic heading, a number of products were cho- eral levels of government—that is, between cen- sen, and for each product a number of items tral, regional, state, and local governments—and were specified. Item specifications were either 190 Purchasing Power Parities and the Real Size of World Economies Table 3.2 Machinery and Equipment Core Product List, ICP 2011 Basic heading Item Code Title Product Brand-specific Generic (no brand) Total 150111.1 Fabricated metal products except machinery and equipment 5 3 6 9 150112.1 General-purpose machinery 9 14 6 20 150113.1 Special-purpose machinery 24 33 17 50 150114.1 Electrical and optical equipment 25 41 15 56 150115.1 Other manufactured goods not elsewhere classified (n.e.c.) 4 5 3 8 150121.1 Motor vehicles, trailers, and semitrailers 5 13 4 17 150121.2 Other road transport 1 2 1 3 150311.1 Other products 4 14 0 14 Total 77 125 52 177 Source: ICP, http://icp.worldbank.org/. brand-specific, with the SPD specifying a brand Economies collected prices only for new and model as well as the item’s technical products, even though in some economies a parameters, or generic, with the SPD specifying significant proportion of the capital formation in the item’s technical parameters only; no brand machinery and equipment consists of imported and model was specified. Seventy percent of second-hand products. So far it has proven the item specifications on the list were impossible to collect prices for comparable brand-specific. second-hand machines and equipment. When pricing items, economies were expected Experimental pricing of such goods has revealed to match the brand, model, and technical param- that there is considerable variation in the quality eters of the brand-specific specifications and the of the second-hand items priced by different technical parameters of the generic specifica- economies and that substantial quality adjust- tions, but this was not always possible. With ments would be needed to make the prices brand-specific specifications, the brand may comparable. Such quality adjustments are not have been available in the economy’s market feasible in practice. The PPPs calculated for new but not the model; with generic specifications, products would be appropriate only for deflating the technical parameters of the items in the the expenditures on machinery and equipment economy’s market may not have matched recorded in the national accounts (which include exactly the technical parameters of the specified expenditures on both new and second-hand item. In such circumstances, economies were products) if the relative prices of new products expected to price items that were comparable— are similar to the relative prices of second-hand that is, items in the economy’s market with products. This is probably a reasonable assump- technical parameters that came closest to the tion, but because of the lack of comparability technical parameters of the brand and model between second-hand equipment goods, it is specification or the generic specification. To help difficult to establish empirically. economies identify comparable items, item spec- In ICP 2011, economies were expected to ifications listed up to 12 key parameters in report national average prices. In some small approximate order of importance. Matching was economies, it was sufficient to collect prices in not just a question of counting the number of only a single location, such as the capital city or parameters that did or did not match, but also the largest industrial or commercial urban area, one of taking into account the degree to which but in larger economies prices had to be collected the parameters differed. Items with near misses in several urban areas. In economies in which a on most parameters could still be an acceptable single dealer had exclusive rights to sell the type substitute for the item specified. of equipment specified, a single price observation Data Requirements 191 was sufficient, but in economies in which there similar manner. In practice, however, the com- were several distributors of the specified equip- plexity and the country specificity of the prod- ment, several price observations were needed to ucts of the construction industry mean that the establish the national average price. The national products are basically unique. For example, no average prices reported were also to be the aver- two economies build exactly the same kind of age prices for the reference year—that is, the house or power station. It is therefore difficult to average of prices collected at regular intervals price construction products that are comparable throughout the year. However, experience sug- between economies. gests that if all economies price equipment goods One way of getting around this difficulty is during the same period, there is no need to col- for economies to price a common set of standard lect prices throughout the year. Economies were construction projects covering different types of asked to collect midyear prices for 2011. buildings and civil engineering works. The proj- Economies obtained prices for the specified ects are fictitious in that they are not actually items of machinery and equipment either built, but they are based on actual structures directly from producers, importers, and distribu- and on the materials and methods commonly tors, or from their catalogues and websites. used in their construction. For each project, the Some economies were able to use prices from components required for its construction are their producer price index or their import price itemized and defined in a product specification index. Economies had to ensure that the prices called a bill of quantities. A quantity is specific collected were purchasers’ prices and included for each component. Multiplying the quantity import duties and other product taxes actually by the unit price of a component yields a total paid by the purchaser, the costs of transporting price for the component. Summing the total the good to the place it would be used, any prices of all components itemized in the bill charges for installing the good so that it was yields the overall price for the project. Because ready for production, and the discounts gener- all economies pricing a specific project price the ally available to most purchasers for most of the same bill of quantities, their overall prices for year. Economies adjusted the prices when they the project are the prices of a comparable prod- did not meet these requirements. uct. PPPs for construction are calculated using Experience from previous rounds of the ICP the overall prices of the projects. has shown that national statistics institutes The bill of quantities approach was used in generally lack the specialized knowledge the Eurostat-OECD comparison. Of the 11 stan- required to collect prices for most types of dard construction projects specified, economies machinery and equipment. Economies were were expected to price seven of them. The unit encouraged to hire outside experts to carry out prices used to price the projects were based on the special survey. the prices of successful tenders submitted during the reference year. Strictly speaking, tender prices are price forecasts for construction activity Construction that will take place after the reference year. Gross fixed capital formation in construction is However, the overall price derived using tender broken down into three basic headings in the prices is considered an acceptable proxy for the ICP expenditure classification. Each basic head- purchaser’s price of a project in the reference ing covers a specific type of structure: residential year because it includes the contractor’s markups buildings, nonresidential buildings, and civil for general site costs, head office overheads, and engineering works. PPPs are calculated for each profit, as well as the percentage addition for the of these basic headings separately, and they are professional fees of architects and engineers. then aggregated to provide the PPPs for con- A modified version of the bill of quantities struction as a whole. The usual procedure in ICP approach was applied in the CIS comparison. comparisons is to calculate PPPs directly using CIS economies were required to provide unit the prices of products that are comparable across prices for 66 inputs covering materials and labor. the participating economies. In principle, the The unit prices were used by the regional coor- PPPs for construction should be obtained in a dinating agency to price a variety of model 192 Purchasing Power Parities and the Real Size of World Economies structures. The PPPs for construction were heading that were spent on materials, equipment calculated using the overall prices for the model hire, and labor. The percentage shares were structures. The bills of quantities for the models used to derive expenditure weights for three were simpler and less complete than those in subheadings—materials, equipment hire, and the Eurostat-OECD comparison, but the range labor—within the basic heading. PPPs were cal- of structures specified was more extensive. culated separately for each subheading using The other ICP regions did not use the bill of the unit prices of the relevant inputs. PPPs quantities approach in their comparisons, chiefly for the basic heading were obtained by aggregat- because of the cost of hiring construction experts ing the PPPs of its subheadings with subheading to price the bills of quantities for the economies. expenditure weights. Instead, they followed the approach developed No adjustments were made for differences by the Global Office for ICP 2011. Rather than in productivity across the participating econo- trying to collect prices for comparable products, mies because the weights supplied for each economies were required to collect unit prices economy to combine labor, materials, and for a common set of inputs. The unit prices were equipment hire would differ according to the to be those paid by construction contractors to productivity level in each economy. In effect, their suppliers—that is, the purchasers’ prices the underlying assumption was that total fac- complete with nondeductible taxes and dis- tor productivity was identical across participat- counts. The inputs did not include the contrac- ing economies. tors’ markups or professional fees, and so these were assumed to be proportional to the overall costs. The unit prices had to be national aver- DATA VALIDATION ages, and they had to be collected in a number Prices of different locations in line with the size of the economy’s economic territory and the price Before the PPPs for the basic headings were cal- variation within it. They also had to be annual culated, the prices on which they were to be averages or midyear prices. based were checked and corrected for any non- More specifically, economies were expected sampling error. The process of checking and to report unit prices for 38 kinds of basic build- correcting the prices is called validation, and a ing materials, the hourly cost of hiring five types nonsampling error is the error that occurs of building equipment with and without an during the collection and processing of price operator, and the hourly rate of compensation data. The objective of the validation process was paid to construction workers in seven occupa- to minimize the incidence of nonsampling error tions. The 55 inputs constituted the global core through editing and verification. Editing is the product list for the special survey of construc- process of checking the prices for possible errors. tion prices. The same 55 inputs were listed for Verification is the process of either confirming each of the three basic headings. In addition to prices or correcting those prices identified as providing unit prices for the inputs that were possibly wrong. available, the national coordinators had to indi- In ICP 2011, validation had three distinct cate the types of structures for which each of the stages. The first was the intra-economy or inputs was commonly used: residential buildings, national validation stage during which the prices nonresidential buildings, or civil engineering collected by a single economy were edited and works. In other words, the national coordina- verified. The second was the intereconomy or tors had to identify the basic headings for which regional validation stage during which the prices inputs were available and important and the collected by all economies participating in a basic headings for which they were relevant regional comparison were edited and verified. (e.g., roofing tiles in civil engineering projects). And the third was the interregional or global In addition to unit prices, economies were validation stage during which the prices col- required to provide information on the average lected for global core products—prices that had resource mix for each basic heading—that is, the already been edited and verified within regions percentages of total expenditure on the basic during the intereconomy validation—were Data Requirements 193 edited and verified across all economies and all considered marginal and not worth pursuing. regions. The Global Office supplied custom-built Time was also a consideration. The longer the software for each stage of validation. delay between price collection and verification Intra-economy validation was directed at an the more difficult it became to correct prices economy’s individual price observations and the that were wrong. average prices to which they gave rise. The Intra-economy validation generally consisted objective was to verify that price collectors of two rounds of editing and verification and within an economy had priced comparable took from two to two and a half months to com- products and had priced them correctly. It was plete. By contrast, intereconomy validation carried out by the economy’s national coordi- required an average of four rounds of editing nating agency (NCA). Intereconomy validation and verification and three to four months to and interregional global validation were directed complete. This validation took longer because of at the average prices reported by participating the interactions that arose during validation economies and the price ratios that the average between the data sets of different economies. prices generated between the economies. The Revisions introduced by one economy could objective was to verify that price collectors in alter the outcome of the edits made on the different economies had priced products that prices of other economies. The interactions were were comparable across the economies and had compounded because not all economies partici- priced them correctly. Intereconomy validation, pating in the comparison were covered in the which was conducted after intra-economy vali- early rounds of intereconomy validation and dation, was carried out jointly by the regional were introduced in later rounds as their average coordinating agency (RCA) and the NCAs. prices become available. Interregional validation Interregional validation followed intereconomy required about the same length of time as inter- validation and involved the NCAs, RCAs, and economy validation. Global Office. It was overseen by the ICP’s Validation focused on two types of nonsam- Validation Expert Group. pling error: price error and product error. Price Validation was an iterative process requiring error occurs when price collectors price products a number of rounds of editing and verification. that match the product specification but they Possible errors were found by identifying prices record the price incorrectly, or they record the that diverged significantly from the other prices price correctly and an error is introduced in the series. They were detected by having afterward in the process of reporting and a measure of divergence that was greater transmitting the price. Associated with each than a given critical value or a value that fell price are two quantities: the specified quantity outside a given range of acceptable values. The (the quantity to be priced) and the reference divergence measures were generally defined by quantity (the quantity to which the price col- the parameters of the series being edited— lected is to be adjusted). A price error can also parameters such as the average and the stan- arise when, even though the price is correctly dard deviation. Thus if some of the possible recorded, the quantity priced is recorded incor- errors identified in the initial edit were found rectly (or it is recorded correctly and an error is to be actual errors and were corrected, the introduced later during processing). Thus the parameters of the price series changed and the adjusted price for the reference quantity (the divergence measures of each price remaining in price that is validated) will be wrong as well. the series also changed. A second edit would Product error occurs when price collectors then uncover new possible errors that needed price products that do not match the product to be verified. When those that were actual specification and they neglect to report having errors were corrected, the parameters of the done so. They may not be aware of the mis- price series would change again, which could match, such as when the product specification is lead to more possible errors being detected if a too loose, or they may price a substitute product third edit was conducted. Usually, the number as required by the pricing guidelines but do not of new possible errors fell as validation pro- mention this on the price reporting form. ICP gressed, until the return on further rounds was price collectors were instructed to collect the 194 Purchasing Power Parities and the Real Size of World Economies price of a substitute product if they were unable and the t-value test. The ratio-to-average price to find the product specified. They were further test is the ratio of the reference quantity price instructed to flag the substitution and to note for a price observation to the average reference the differences between the substitute product quantity price for the product. To pass the test, and the specified product. Flagging would bring the price observation’s ratio had to be within the the substitution to the attention of the NCA, 0.5–1.5 range. In other words, an individual which, together with the RCA, would then price was expected to be no less than half the decide what to do with the price collected. It average price or no more than double the aver- might be possible to adjust the price for quality age price. Price observations with ratios that fell differences between the product priced and the outside the range failed the test and were product specified. Or, if other economies flagged as outliers. The t-value test is the ratio of reported prices for the same substitute product, the deviation of the reference quantity price for price comparisons could be made for the substi- a price observation from the average reference tute product as well as for the product originally quantity price for the product to the standard specified. If neither of these options was feasible, deviation of the product. To pass the test, the the price would have to be discarded. price observation’s ratio had to be 2.0 or less. Editing for price and product errors involved (A value greater than 2.0 was suspect because it identifying extreme price observations or generally fell outside the 95 percent confidence outliers—that is, prices found to be either too limit.) Price observations with ratios greater high or too low vis-à-vis the average according than 2.0 failed the test and were flagged to given criteria. The prices identified as outliers as outliers. were not necessarily wrong, but the fact that Outliers among average prices were also they were considered extreme suggested that identified by two tests: the max-min ratio test they could be wrong—that is, they were possi- and the coefficient of variation test. The max- ble errors. As possible errors, they needed to be min ratio is the ratio of the maximum reference investigated to ascertain whether they were quantity price observed for a product to the accurate observations. Once this was deter- minimum reference quantity price observed for mined, it could be decided how to deal with a product. Average prices with ratios greater them. Outliers found to be wrong were either than 2.0 failed the test and were flagged as outli- corrected or dropped, whereas outliers shown to ers. (A ratio of 2.0 implied a coefficient of varia- be valid observations were retained, at least in tion of between 20 and 30 percent at the 95 principle. In practice, it was not unusual for percent confidence limit.) The coefficient of valid outliers to be replaced by an imputed value variation is the standard deviation for the prod- or discarded during intereconomy validation in uct expressed as a percentage of the average order to remove the noise they introduced in price of the product. For an average price to pass the data set. the test, its coefficient of variation had to fall below 40 percent. Average prices with coeffi- Intra-economy Validation cients of variation of 40 or above failed the test To establish that price collectors within the same and were flagged as outliers. economy had priced products that matched the The intra-economy validation software devel- product specifications and that they had reported oped by the Global Office screened the price prices correctly, intra-economy editing searched observations and average prices for outliers and for outliers first among the individual prices that generated two diagnostic tables: one for price an economy had collected for each product it observations and one for average prices. The had chosen to survey and then among the aver- tables revealed which of the price observations age prices of these products. Outliers were and which of the average prices were outliers to defined as price observations or average prices be verified. Verification determined the reliability that scored a value for a given test that fell out- of the flagged price observations and the flagged side a critical value. average prices or, more precisely, the reliability of Outliers among price observations were iden- the flagged price observations and the price obser- tified by two tests: the ratio-to-average price test vations underlying the flagged average prices. Data Requirements 195 This entailed revisiting the outlets where the highlighting the anomalies among them that prices were collected to ascertain whether the needed further explanation. The average prices products priced matched the product specifica- were returned to the RCA after the NCA tions and whether the prices reported were answered the questions posed by the RCA and correct. If the product matched the product corrected the prices as required. specification and the correct price had been reported, verification was complete. The outlier Intereconomy Validation was found to be an accurate observation. If the Intereconomy validation involved editing the product priced did not match the product speci- average prices reported by the economies for fication or if the price had been incorrectly possible errors by assessing the reliability of the reported, it was necessary to rectify the situation PPPs they provided. The objective was to verify by finding a product in the outlet that did match that the average prices were for comparable the product specification and pricing it or estab- products and that the products had been cor- lishing the correct price for the product originally rectly priced—that is, to ascertain that the priced if it was still available. economies had interpreted the product specifi- After verification, the price observations that cations in the same way and that they had also were flagged as outliers and found to be incor- priced the products accurately. This was done by rect were either replaced by the correct observa- comparing the prices for the same product in tion or suppressed. Price observations that were different economies and by analyzing the dis- flagged as failing the ratio-to-average price test— persion of the price ratios that the average prices but not the t-value test—and that were found to generated between economies. In short, inter- be correct were retained, providing that they economy editing entailed detecting outliers were part of the population as defined by the rest among the average prices through their price of the price observations for the product. This ratios. It was during this process that the final was established by recalculating the average selection of products to be included in the final price and the standard deviation without includ- computation of regional PPPs was made. ing the outlier and using them to derive a t-value Because economies reported their average for the outlier. If the t-value was greater than prices in national currencies, the prices could be 2.0, the outlier, although accurate, was consid- compared only if they were expressed in a ered invalid and discarded. If the t-value still did common currency. Once converted to a common not fall outside the critical value, it was consid- currency, the average prices of different econo- ered a valid observation and retained, at least mies for the same product could be compared initially. (Later, during intereconomy validation, and outliers identified according to predeter- it was decided whether to keep the observation, mined criteria. But prices, even when expressed to replace it by an imputation, or to suppress it.) in the same currency, could not be compared Price observations that were flagged as failing the across products directly. Even so, the price ratios t-value test and found to be correct were removed of economies pricing a product could be because they clearly were not part of the same compared with the equivalent price ratios for population as the other price observations even other products, providing that they had first when included in the calculation of the average been standardized. Standardized price ratios for price and standard deviation. a product are the ratios between the individual Once intra-economy validation was com- average prices of the economies pricing the pleted, the economy’s NCA provided the RCA product and the geometric mean of the average with validated average prices for the products prices of all the economies pricing the product the economy had priced, plus the coefficient of when the average prices are expressed in a variation, the max-min ratio, and the number of common currency (see box 3.1). price observations for each of the average prices Both exchange rates and PPPs were employed reported. These were reviewed by the RCA to convert the average prices to a common cur- before starting intereconomy validation. In rency; both the exchange rate–converted aver- some instances, the review prompted the RCA age prices and the PPP-converted average prices to send the average prices back to the NCA after were used to derive standardized price ratios; 196 Purchasing Power Parities and the Real Size of World Economies BOX 3.1 Standardized Price Ratios A standardized price ratio equals (CC-price1A/[CC-price1A × CC-price1B × . . . CC-price1N]1/N) 100, where CC-price1A is the average price for product 1 in economy A in the common currency. CC-price1A is itself equal to NC-price1A/CC1A, where NC-price1A is the average price for prod- uct 1 in economy A in national currency and CC1A is the currency conversion rate between the national currency of economy A and the common currency. The currency conversion rate is either the exchange rate or the PPP: CC1A = XR1A or PPP1A. and both sets of standardized price ratios were The PPPs used to obtain the PPP-ratios can be edited and verified. The reason for this approach calculated using the average prices of products was that the PPPs used to convert the average covered by a basic heading or the average prices prices to a common currency were calculated of products covered by an aggregate. from the average prices that were being vali- Intereconomy editing is carried out first at the dated. This meant that editing began with PPPs basic heading level and subsequently at the calculated from prices that still had to be veri- various aggregation levels of the ICP expendi- fied. These opening PPPs were likely to be unre- ture classification. Validation at the aggregate liable, and the flagging of outliers among the level places the editing and verification of standardized price ratios based on PPP-converted average prices in a broader context. Are the prices (PPP-ratios) was likely to be unreliable as average prices consistent, not just within the well. Exchange rates, however, are not deter- basic heading but also within a larger set of mined by the average prices and remain unaf- products? Editing at the aggregate level enables fected by them. It is for this reason that inconsistencies to be identified that would not standardized price ratios based on exchange be found by editing solely at the basic heading rate–converted prices (XR-ratios) were used in level. For example, if for the basic heading for the initial stages of editing and verification. alcoholic beverages an economy had priced all Experience has shown that XR-ratios provide a its beverages in quarts instead of liters as better feel for the reliability of the average prices specified, its price ratios would be consistent reported at the beginning of the validation pro- within the basic heading, but they would not be cess. Experience has also shown that many of consistent with the economy’s price ratios in the ratios initially identified as outliers among other basic headings. Such errors are identified the XR-ratios are found to be incorrect. by editing across basic headings. In this respect, Intereconomy validation involved several iter- it is useful to validate at different levels of ations or rounds. After each round, as incorrect aggregation progressively—for example, check- prices were corrected or removed, the PPPs ing the basic headings for food products using became more reliable and so too did the flagging first the PPPs for the basic heading, then the of outliers among the PPP-ratios. As validation PPPs for food and nonalcoholic beverages, and progressed, the focus on outliers shifted from finally the PPPs for the household final con- those among the XR-ratios to those among the sumption expenditure. PPP-ratios—the purpose of the exercise was to In addition to flagging outliers among the PPP- remove, or at least reduce, the outliers among the ratios, intereconomy validation involved analyz- PPP-ratios. Thus in later rounds, as the PPP-ratios ing their dispersion. For this purpose, three became more reliable, the outliers remaining coefficients of variation were calculated during among the XR-ratios could be ignored. XR-ratios the validation process: the product coefficient of and PPP-ratios that fell outside the 80–125 range variation, the economy coefficient of variation, were flagged as outliers requiring verification. and the overall coefficient of variation. Data Requirements 197 The product coefficient of variation measures among the PPP-ratios and provided similar dispersion among PPP-ratios for a product. It is measures of price variation for products and an indicator of comparability and accuracy and economies employing either basic heading PPPs addresses the question of whether the econo- for editing basic headings individually or PPPs mies pricing the product priced the same prod- for an aggregate for editing across the products uct (or an equivalent product) and whether and basic headings constituting the aggregate.1 they priced it correctly. The higher the product’s During intereconomy validation, Quaranta value the less likely it is that economies priced a tables were employed to edit average prices comparable product or, if they did, that they all within a basic heading and Dikhanov tables priced it accurately. The economy coefficient of were used to edit average prices within variation measures dispersion among the PPP- an aggregate. ratios for an economy either at the basic head- The Quaranta table was originally designed ing level or at the level of an aggregate. It is an to edit prices within a basic heading. It provides indicator of the reliability of the economy’s PPPs a large amount of information about product for the basic heading or the aggregate. The prices, but its presentation becomes unwieldy higher the coefficient’s value the less uniform when applied to a large number of products are the economy’s price levels and the less reli- such as those priced for an aggregate. A able are the economy’s PPPs. Finally, the overall Dikhanov table contains much of the same coefficient of variation measures dispersion information, but it is programmed to hide among all the PPP-ratios for a basic heading or certain items (which can be called up as an aggregate. It is an indicator of the homogene- required) so that only key series are displayed. ity of the price structures of the economies The more compact format of the Dikhanov covered by the basic heading or aggregate. The table makes it better suited to editing prices higher the value of the coefficient the less across the basic headings and products compris- homogeneous are the price structures and the ing an aggregate. Moreover, to assist in the less reliable are the PPPs for the basic heading identification of outliers, the Dikhanov table or aggregate. uses different colors to indicate different ranges In ICP 2011, the critical value for all three of extreme values. The coding helps to identify coefficients of variation was 39 percent. Products, those products having average prices that need economies, and basic headings with coefficients verification. But, more important, it makes of variation of 40 percent and above were identification of possible problem economies considered to be outliers that warranted investi- easier because such economies will have col- gation. During verification, priority was given to umns with a significant amount of coloring. basic headings with a coefficient of variation Editing a basic heading with a Quaranta table over the critical value and with a large expendi- or an aggregate with a Dikhanov table entailed ture weight because they would have a greater identifying average prices that were outliers or, influence on the overall PPPs than basic head- more precisely, the PPP-ratios that were outliers. ings with a small expenditure weight. The average prices underlying the PPP-ratios In addition to their role as editing tools, the flagged as outliers were only possible errors. coefficients provided the means to monitor They were not errors by definition and could progress during validation and, at its conclusion, not be removed automatically; they had to be to assess how effective the whole process of referred back to the economy reporting them for editing and verification had been in reducing verification. NCAs were required to investigate the incidence of nonsampling error among the the average prices returned to them as possible price data. Coefficients should be significantly smaller at the end of validation than they were 1 The layout of the tables, their differences, and how to read them are at the beginning. described in chapter 9 of Measuring the Real Size of the World Economy: The intereconomy validation software The Framework, Methodology, and Results of the International developed by the Global Office generated two Comparison Program (ICP) (World Bank 2013) and in the chapter on validation tables in Operational Guidelines and Procedures for Measuring diagnostic tables: the Quaranta table and the the Real Size of the World Economy: 2011 International Comparison Dikhanov table. Both tables flagged outliers Program (World Bank forthcoming) and so are not repeated here. 198 Purchasing Power Parities and the Real Size of World Economies errors and to confirm whether they were correct economies participating in the comparison had or incorrect. When prices were found to be been included in the database, there was incorrect, NCAs were expected to correct them; convergence, and the return on further rounds otherwise, they were suppressed. But if they of verification was deemed marginal by the were found to be correct, a decision had to be NCAs and the RCA and not worth pursuing. made on whether to keep them, to replace them Intereconomy validation was considered to with an imputed value, or to drop them—not be complete. necessarily an easy decision. Some of the devia- tions, even large ones, were legitimate. For Interregional Validation example, the prices of economies with particular Intereconomy validation was followed by inter- pricing policies, such as low fuel prices in some regional validation. The process consisted of of the oil-producing economies, were likely to be three steps. The first step was to assess how well flagged as outliers, but they were not incorrect; the price level indexes (PLIs) and PPPs of the they were a reality. It would have been wrong to global core products priced in the region reflected remove them, and, despite the noise they intro- regional PLIs and PPPs. This was carried out by duced into the data set, they were retained. comparing the PLIs and PPPs calculated for the If, however, there were no extenuating complete set of regional products (which circumstances, the disturbance created by an included global core products) with the PLIs and outlier could affect not only the PPP of the PPPs calculated only for global core products and economy reporting the outlier but also the PPPs with the PLIs and PPPs calculated for regional of other economies in the regional comparison. products other than global core products. In such cases, replacing the outlier with an The second step was to validate the prices of imputed value or suppressing it were options to global core products across regions in order to be considered. If, within the context of a basic establish whether the global core products priced heading, the outlying average price referred to a by the regions were comparable. The large num- product that was important to the reporting ber of economies made it difficult to apply the economy, removing it might not be justified, conventional bottom-up approach of the although imputing a value might be. But if the Quaranta and Dikhanov tables. Instead, a average price referred to a less important top-down approach was followed. Validation product, removing it was probably warranted. began at the class level (the aggregation level Whatever the action taken, it was decided above the basic heading level) and the basic jointly by the economy’s NCA and the RCA on heading level, only descending to the product a case-by-case basis. level when problem cases were encountered. It The mechanics of the intereconomy valida- consisted of the following tasks: (1) calculating tion process were straightforward. Validation PPPs and PLIs for all economies based on global usually started before all economies participat- core products; (2) compiling two matrixes show- ing in the regional comparison had supplied ing, respectively, the PLIs and the economy their average prices. The RCA prepared Quaranta coefficients of variation for all aggregation levels and Dikhanov tables for the economies whose (basic headings and above); (3) flagging basic average prices were available and sent them to heading PLIs in the PLI matrix that had a large the NCAs for verification. After each round of discrepancy vis-à-vis the PLI for its class; verification, the RCA changed the regional price (4) flagging basic headings in the coefficient of database in line with the findings reported by variation matrix that had a coefficient of varia- the economies covered in the round, added the tion of 40 percent or more; and (5) analyzing prices of economies joining the validation pro- the flagged outliers using economy diagnostic cess to the database, and produced new Quaranta reports (a summary report containing all infor- and Dikhanov tables. These tables identified mation related to a single economy that is new outliers as a result of the changes intro- provided by a Quaranta table). duced by the RCA, and these had to be investi- Outliers identified in the first and second steps gated by the NCAs. Gradually, after a number of were reviewed by the RCAs and NCAs con- rounds of verification and after the prices of all cerned. Outliers that could not be verified were Data Requirements 199 removed from the global calculation by the expenditure classification in appendix D. The Global Office after consultation with the RCAs. classification adheres to the concepts, definitions, The third step was validating the global PPPs. classifications, and accounting rules of SNA93. Validation took place at each level of aggrega- The same expenditure classification was tion, starting at the basic heading level. It employed in ICP 2005, and many of the econo- entailed looking first at the spread between the mies participating experienced difficulties break- Paasche-type indexes and Laspeyres-type ing down their GDP expenditures into the 155 indexes generated by the Gini-Éltetö-Köves- basic headings. To help economies overcome Szulc (GEKS) aggregation method between each these difficulties in ICP 2011, the Global Office pair of economies and then at the variability of drew up the Model Report on Expenditure the indirect PPPs that the GEKS generated to Statistics, or MORES (described in appendix E). make the bilateral Fisher-type PPPs multilateral It was designed so that economies could estimate and transitive. Paasche-Laspeyres spreads (the the expenditure on each basic heading and, at ratio of the Paasche indexes to the Laspeyres the same time, document how the expendi- indexes) with small values indicated that two ture was estimated. The detailed metadata economies had similar price and expenditure provided by MORES were referred to through- structures; large values indicated that they did out the validation of national accounts data. not. When pairs of economies had a value In addition to MORES, the Global Office pre- greater than 2, their distributions of basic head- pared the National Accounts Quality Assurance ing PPPs and expenditure shares were reviewed Questionnaire and GDP Exhaustiveness in case one or both were outliers requiring addi- Questionnaire (both described in appendix E). tional investigation. Variability between the indi- The former focused on the extent to which an rect PPPs for each economy was measured by the economy’s GDP estimate complied with SNA93 relative standard deviation of the indirect PPPs. and the latter on the degree of exhaustiveness of When economies had large deviations, their an economy’s GDP estimates. Both were con- PPPs were reappraised to determine whether sulted during the validation process. they should be excluded from the global GEKS As for the process itself, it had the same three (any such economies were still included in the stages as price validation: intra-economy vali- final results, but they did not contribute to the dation carried out by the NCAs individually, linking of their region to other regions). intereconomy validation carried out by the RCAs in consultation with their NCAs, and interregional validation carried out by the National accounts Global Office in consultation with the RCAs and The national expenditures that economies sup- the NCAs. Intra-economy validation and inter- ply for an ICP comparison are essential to the economy validation were facilitated by the comparison, first, because they are the expendi- national accounts workshops that each RCA tures that are to be deflated and expressed as real organized for its region. The workshops gave expenditures, and, second, because they are the ICP staff in the region an opportunity to weights used to aggregate basic heading PPPs exchange information on how their basic head- through the various levels of aggregation up to ing expenditures were estimated and to com- GDP. Neither the real expenditures nor the pare the distribution of the expenditures. This aggregated PPPs will be reliable unless the promoted comparability. Economies could national expenditures provided by economies adopt what they considered to be the better are comparable—that is, they are compiled using practices of others, and economies having dif- the same definitions of GDP and its component ficulty in breaking down expenditure on a spe- expenditures and are equally exhaustive in their cific aggregate by basic heading could borrow measurement of economic activity. For ICP the breakdowns of other economies. 2011, the common national accounts framework was that of SNA93. Economies were required to Intra-economy Validation report their national expenditures broken down Before sending its national accounts data to into 155 basic headings, as defined in the ICP the RCA, the NCA was expected to carry out a 200 Purchasing Power Parities and the Real Size of World Economies number of basic checks on the data. These region. This review was carried out by grouping included verifying that there was a non-zero the economies in the region into clusters of value recorded for every basic heading; that similar economies using indicators such as GDP negative values were clearly marked as nega- per capita and comparing their basic heading tive; that the value of each aggregate was the shares of GDP. The comparison was repeated sum of its constituent subaggregates; that FISIM using first basic heading shares based on was allocated across institutional sectors; and notional real expenditures and then basic head- that the values at the level of GDP and main ing notional real expenditures per capita. aggregates corresponded to the latest official Finally, the RCA checked for consistency estimates disseminated by the economy. Basic between an economy’s national accounts data headings with zero values had to be flagged and and price data by looking at the economy’s justified. For example, an economy that based comparison of basic heading notional real its estimate of the household final consumption expenditures per capita for 2005 and 2011 and expenditure on a household budget survey analyzing the differences to see from which of would not provide a value for net purchases the two data sets—prices or expenditures— abroad because the estimate was already on a they arose. Basic headings identified as prob- national basis, but this had to be explained lematic during these checks were flagged. The and reported. RCA then returned to each NCA its national In addition to the basic checks, an NCA was accounts data with the problem basic headings expected to check the basic heading expenditure flagged, requesting either justification or cor- shares for 2011 against the basic heading expen- rection. After justifying or correcting the prob- diture shares for ICP 2005 to ensure that they lem basic headings, the NCA returned the were coherent over time. Large differences had verified national accounts data to the RCA, to be flagged and justified. For the same reason, which repeated all the checks. This process con- an economy was also required to calculate and tinued until the data were considered final and compare basic heading notional real expendi- included in the regional database. tures per capita for 2005 and 2011. Large varia- tions had to be flagged and justified. (The Interregional Validation notional real expenditure for a basic heading is Upon completion of the intereconomy valida- the estimated expenditure on the basic heading tion, the economy’s edited and verified national divided by the geometric average of the prices accounts data were sent to the Global Office. collected for the basic heading. Variations over There, they were given a final review before time can be explained by changes in expendi- being combined with the national accounts data ture, changes in prices, or both.) Having of other economies in the global database that completed these various checks, the NCA covered all regions. The review carried out by submitted the edited data and relevant metadata the Global Office simply repeated the checks to the RCA. already undertaken by the economy’s RCA. The difference was that the review took place Intereconomy Validation in the context of all economies and all regions. Upon receipt of an economy’s national accounts The Global Office was then able to compare the data, the RCA repeated the basic checks just results of each regional review with the results described. In addition to checking that the val- of the other regional reviews. Problem basic ues at the level of GDP and main aggregates headings identified in this global overview were corresponded to the latest official estimates dis- sent back to the RCA and the NCA concerned seminated by the economy, the RCA verified for justification or correction. After justifying or that they were the same as those in the UNSD correcting the problem basic headings, the database. The RCA also compared the basic verified national accounts data were returned heading expenditure shares reported for 2011 to the Global Office, which repeated the checks. with those reported for 2005. The process was repeated until the data were After the basic checks, the RCA reviewed the considered final and ready for inclusion in the plausibility of the economy’s data within the global database. Data Requirements 201 Chapter 4 Methodologies Used to Calculate Regional and Global PPPs The International Comparison Program (ICP) pricing purposes. Basic headings fall into three has three major components. The first compo- categories. The first consists of the products con- nent is the conceptual framework, which is sumers purchase in various markets. Prices are determined by the final expenditures making up obtained by means of market surveys. This cat- the gross domestic product (GDP). The second egory is the basis for nearly all basic headings component is the basket of goods and services under the aggregate household final consump- from which products are selected for pricing: the tion expenditure. The second category is hous- products are comparable across economies and ing rents, health, education, government are an important part of each economy’s final services, machinery and equipment, and con- purchases. The national annual average prices struction. These goods and services are difficult or quantity data collected for these goods and to compare and require data beyond what can services must be consistent with the underlying be collected in market surveys. The third cate- values in the national accounts. The third com- gory is those basic headings for which price or ponent is the methodology used to compute value data are either not available, such as nar- purchasing power parities (PPPs), first within cotics, or too difficult or too expensive to obtain. regions for the regional comparisons and then PPPs are first computed at the individual across regions for the global comparison. product level within each basic heading for each The PPPs provided by the ICP are based on a pair of economies being compared. Suppose large body of statistical and economic theory three economies—A, B, and C—price three fully documented in Measuring the Real Size of the kinds of rice for the basic heading rice. For each World Economy: The Framework, Methodology, and kind of rice, there are three PPPs: PB/PA, PC/PA, Results of the International Comparison Program and PC/PB. The basic heading PPP for each pair of (ICP) (World Bank 2013). This volume describes economies can be computed directly by taking the many methods available for ICP 2005, the the geometric mean of the PPPs between them choices made, and the lessons learned that were for the three kinds of rice. This is a bilateral com- applied to ICP 2011. parison. The PPP between economies B and A As described in earlier chapters, the estima- can be computed indirectly: PPPC/A × PPPB/C = tion of PPPs begins by breaking down GDP into PPPB/A. The use of both direct and indirect PPPs 155 basic headings. Basic headings, the lowest is a multilateral comparison. This means that the level at which expenditure estimates are PPPs between any two economies are affected by required, are the product groups into which their respective PPPs with each other economy. individual goods or services are placed for A change in the mix of economies included 203 in the comparison will also change the PPPs that the relative volume—the ratio of real between any two economies. expenditures—between any pair of economies Different methods can be used to compute in a region remains the same after the region has multilateral PPPs. The choice of method is based been combined with economies in other regions. on two basic properties: transitivity and base The following sections are an overview of the country invariance. PPPs are transitive when methodologies used to obtain regional and the PPP between any two economies is the same global PPPs for household consumption, hous- whether it is computed directly or indirectly ing, government compensation, machinery and through a third economy. PPPs are base country– equipment, and construction. invariant if the PPP between any two economies is the same regardless of the choice of base country. These properties apply for every com- HOUSEHOLD CONSUMPTION putational step: computing basic heading PPPs between economies, aggregating basic heading Statistical theory suggests that a master frame PPPs to the within-region GDP, linking basic should list every possible product purchased by heading PPPs across regions, and then comput- consumers and the annual expenditures associ- ing global PPPs. ated with each product for every economy. Another property underlying the computa- A random sample of products would be selected tional steps to obtain PPPs for ICP 2011 (and ICP for which national annual average prices would 2005) is that economies are treated equally be determined. The expenditure on each product regardless of the size of their GDP. Weights based would be used to weight product PPPs to basic on basic heading expenditures are used in the heading PPPs. The reality, however, is that there methodology to weight a group of basic headings is no such list. Although statistical theory can be to an aggregate level. Therefore, PPPs are first used to determine the number of products to be weighted using economy A’s weights (Laspeyres priced, it is left to the regional and national coor- index), and then weighted again using economy dinators using their expert judgment to select the B’s weights (Paasche index). Each index pro- actual products out of the thousands of possibili- vides a weighted average of the PPP between ties. Measuring the Real Size of the World Economy economy A and economy B. To maintain sym- (World Bank 2013) provides guidelines on the metry, the geometric mean is taken of the two number of products to be priced. For example, it aggregated PPPs for every pair of economies in recommends that 10–15 products be priced for the comparison. The result is a Fisher index. For the rice basic heading compared with 70–100 for each pair of economies, the multilateral PPP is the garment basic heading. Rice is a relatively the geometric mean of the direct and indirect homogeneous product, although it is necessary Fisher indexes. to specify the different varieties to be priced. This method, however, does not satisfy the Garments are much more heterogeneous. additivity requirement. Additivity occurs when Comparability of the products being priced is the sum of the real expenditures of the basic an essential principle underlying the estimation headings constituting an aggregate equals the real of PPPs. A dilemma facing the ICP is that, expenditures based on the PPPs for the aggregate. although a product may be available in several Additive methods have the disadvantage of giv- economies, it may be a significant part of con- ing more weight to the relative prices of the sumption in only a few. Because no data are larger, more developed economies. As a result, available on expenditures for individual products, the real expenditures of poor economies become the relative prices or product PPPs would have to artificially larger and move closer to the real be averaged with equal weights to obtain the expenditures of rich economies. This is known as basic heading PPP. To overcome this problem, the the Gerschenkron effect. For uses of ICP PPPs Eurostat–Organisation for Economic Co-operation such as poverty analysis, nonadditive methods and Development (OECD) and Commonwealth that avoid the Gerschenkron bias are preferred. of Independent States (CIS) regions adopted the Fixity is yet another concept that determines concept of representativity to induce a form of the methods used. The fixity concept means weighting. A representative product is one that is 204 Purchasing Power Parities and the Real Size of World Economies purchased frequently by households and has a product prices. Product PPPs were averaged to price level consistent with the majority of prod- the basic heading using the weighted country ucts in the basic heading. Because representative product dummy (CPD-W) method, with products are those most frequently purchased, it weights of 3:1 for important versus less impor- is likely that they have lower price levels in tant products. The Jevons–Gini-Èltetö-Köves- economies where they are representative com- Szulc* (Jevons-GEKS*) method was used in pared with the price levels in economies where the Eurostat-OECD and CIS regions to com- the product is available but not representative. pute basic heading PPPs. This method used the This factor can lead to bias if not taken into representative classification by giving a weight account when computing basic heading PPPs. of 1 to the prices of representative products A simpler method was used in the remaining and a weight of 0 to unrepresentative products. regions. Economies other than those in the • All regions used the GEKS method to aggre- Eurostat-OECD and CIS regions were asked to gate the basic headings to higher level aggre- classify all goods and services for household gates. These multilateral PPPs are transitive consumption as either important or less impor- and base country–invariant. tant. Importance is defined by reference to the notional expenditure share of a product within At this stage, within-region PPPs are aggre- its basic heading. The importance classification is gated to the level of household consumption. a subjective process, as is the assignment of rep- Chapter 6 in Measuring the Real Size of the World resentativeness, but it is easier to apply. If the Economy (World Bank 2013) reviews the proper- expenditure share is thought to be large, the ties of the various methods to link the within- product is classified as important; if the expendi- region PPPs. The steps used in ICP 2011 to link ture share is thought to be small, the product is basic heading PPPs for household consumption classified as less important. across regions were the following: The steps taken to arrive at PPPs for house- • Global core product prices provided by all hold consumption within regions took into economies were deflated to a regional cur- account the methods used to calibrate within- rency using within-region basic heading PPPs. region PPPs to global PPPs: The result was five sets of regional prices • The Global Office developed a list of global treated as “super economies.” core products that would be priced by all • The CPD-W over these five sets of regional economies. These prices would be used to prices provided between-region basic heading compute between-region PPPs for each basic PPPs linking each region to a base region. heading. • Multiplying the within-region basic heading • Each region developed its own list of products PPPs by the between-region basic heading for its comparison and incorporated as many PPPs converted them to a global currency. of the global core list products as possible. Multiplying the same regional scalar by each • Each economy within a region classified the economy’s within-region PPP converted it to products they priced from the regional prod- a global PPP. This method preserved within- uct list and the global core product list as region fixity, which means the relative rank- important or less important. ings between economies in the same region remained the same after linking. Chapters 4 and 5 of Measuring the Real Size of the World Economy (World Bank 2013) describe The steps just described were applied only to the different properties of the various indexes the Africa, Asia and the Pacific, Eurostat-OECD, that can be used to compute basic heading PPPs Latin America, and Western Asia regions. The and aggregate them to GDP. The basic method- CIS region was linked to the Eurostat-OECD ology used in 2011 was as follows: region through the Russian Federation and through the Eurostat-OECD region to the other • Within-region basic heading PPPs were based regions, and the Caribbean region was linked on regional product prices and global core through Latin America. These methods are Methodologies Used to Calculate Regional and Global PPPs 205 described later in this chapter in the section on used for the rest of household consumption special situations. but without importance indicators. The concepts and methodology just described were essentially the same for the remaining • The Asia and the Pacific region, after in-depth aggregates, which are described in the rest of analysis of the available data, resorted to this chapter. using a reference volume approach. This implies that the relative volumes of housing services between economies are equal to the relative volumes of household expenditure, COMPARISON-RESISTANT COMPONENTS excluding rents. Some components of expenditure on GDP have • The Eurostat-OECD region used a mix of a long history of being difficult to estimate—in rents and dwelling stock data. Generally, for ICP parlance, they are known as “comparison- economies that have a well-developed rental resistant” goods and services. They are found market, PPPs were determined on the basis of mainly in the basic headings for housing, health, the rental data, whereas for other economies education, collective government, and invest- dwelling stock data were used to obtain esti- ment in equipment and construction. mates of PPPs indirectly. Indirect PPPs are In ICP 2011, different approaches were used based on the relationship price × quantity = to obtain prices and PPPs for these activities. The expenditure. An indirect PPP can be derived Global Office consulted closely with experts in by dividing the expenditure on rents from an the relevant organizations or employed experts economy’s national accounts by the real on investment in equipment and construction expenditure on rents estimated using dwell- to assist in setting up special pricing lists for ing stock data adjusted for quality. This is the products involved. The requirements for the known as the quantity method of estimating prices recorded were similar to those for the real expenditures and the indirect method of household final consumption products—that is, estimating PPPs. they had to be national annual average prices consistent with the expenditures recorded in an • The quantity method was used in the CIS economy’s national accounts. region, which was then linked to other regions using Russia as the bridge country. Housing The rental data used to link the Africa, Latin All economies participating in the ICP were America, Caribbean, and Western Asia regions asked to collect average annual rents for a global were the same as those that entered the calcula- list of dwelling types and dwelling stock data: tion of their regional PPPs. The linking factors number of dwellings, usable surface area in for these four regions were calculated by means square meters, and information on three quality of the same CPD method used to link the rest of indicators. In addition, national accounts household expenditures. For the Asia and the expenditure data on actual and imputed rentals Pacific and Eurostat-OECD regions, the method were collected. chosen was to link them to each other and to Not all economies were able to report rents the rest of the world through use of the dwelling and dwelling stock data, and some were only stock data. able to provide rents for a subset of dwelling The dwelling stock data provided by the types or limited dwelling stock data. Each regional economies were carefully analyzed. The pre- coordinator then decided on the best way to use ferred measure of housing quantity—usable the collected data for his or her region: surface area in square meters—could not be • The Africa, Latin America, Caribbean, and utilized because too few economies had reliable Western Asia regions calculated their regional data. Thus the basic quantity information used PPPs on the basis of the rents collected for the was number of dwellings, for which a sufficient global list of dwelling types, relying on the number of economies within each region pro- same country product dummy (CPD) method vided an estimate. It was not possible to make 206 Purchasing Power Parities and the Real Size of World Economies further distinctions within total dwellings, Government-produced services are consid- which would have enriched the estimations. ered to be nonmarket services because they are The plausibility of each economy’s estimate of provided free or sold at prices that are not eco- number of dwellings was evaluated by calculat- nomically significant and therefore have no ing the ratio of the number of dwellings to the observable value of output. The System of total population. Economies with very high or National Accounts 1993 or SNA93 (Commission very low ratios were not included in the linking of the European Communities et al. 1993) rec- process. For each economy with a plausible ommends that nonmarket services be mea- estimate of number of dwellings, the data on sured using the input cost approach. In other housing quality were reviewed. Three quality words, the value of their output is recorded as indicators were available: share of dwellings the sum of the costs of production—that is, the with electricity, share of dwellings with sum of compensation of employees, intermedi- inside water, and share of dwellings with a ate consumption, and consumption of fixed private toilet. Only economies for which a plau- capital. In ICP 2011, basic headings were sible estimate for all three indicators was avail- specified for each of these inputs in the ICP able or could be imputed were included in the expenditure classification, but prices were col- linking process. lected only for the compensation of a range of employees engaged in producing government health, education, and collective services. The Government compensation compensation collected covered a number of The main components of the government final carefully selected and well-defined occupations consumption expenditure are health, education, that are typical of government expenditures and collective services such as general adminis- around the world.1 tration, defense, police, fire fighting, and envi- Measuring the compensation of government ronmental protection. The health and education employees is a difficult area for the ICP because services provided by government are classified labor productivity in government varies mark- as individual services because they are offered edly between economies. Detailed specifications to individuals rather than collectively to an were provided for each occupation, including economy’s residents. The individual services required level of skill and experience. Because provided by government are combined with factors such as workers’ levels of skill and expe- similar services purchased by residents (and rience and the availability of equipment such as nonprofit institutions serving households, computers are key elements of such differences NPISHs) as part of the household final con- in productivity, it was essential to adjust for sumption expenditure to form actual final productivity differences between economies. In consumption. Actual final consumption covers some regions, not adjusting for them would all expenditures on individual services. It is an have significantly distorted the estimates of real important aggregate because it enables com- expenditures for government. In some cases, parisons of economies that have markedly the distortions would have been so large that different institutional arrangements for provid- they would have affected comparisons of real ing services such as health and education. For expenditures on GDP. For example, in the Asia example, in some economies these types of and the Pacific region average compensation services are supplied (sold) largely by the private (based on exchange rates) in the government sector, while in others government agencies sector of Hong Kong SAR, China, was about provide virtually all of these services. Most 100 times higher than in the poorest economies economies fall somewhere between these two in the region. If no productivity adjustments extremes, and estimating real expenditures for actual final consumption provides a means of 1 For education, the Eurostat-OECD region used an output approach for comparing economies that are not affected by the first time. PPPs were based on numbers of students and average the extent to which these services are provided student scores from the Programme for International Student Assessment (PISA). These within-region PPPs were linked to the rest of the world (or financed) by either the government or the using five Latin American economies that have data for both the input private sector. approach used by ICP regions and the Eurostat-OECD output approach. Methodologies Used to Calculate Regional and Global PPPs 207 were made, economies in which government output elasticity of capital. The standard salaries were very low would have had very approach to this problem is to define a hypo- high real consumption of government services thetical “average” country, with variables compared with the high-income economies in denoted by an upper bar, and compare each the region in which government salaries were country to this average. This procedure is akin relatively much higher. to the GEKS index number approach, but is based on the Törnqvist index instead of the Productivity Adjustment for Government Fisher index. Relative labor productivity Compensation between country i and the average country is Productivity adjustments were calculated using then equal to capital-labor estimates for each economy.2 It was not possible to estimate productivity y  A  1 k  ln  i  = ln  i  + (a i + a )ln  i  . (4.3) adjustments directly for the government sector,  y  A 2 k and so they were based on comparisons of economy-wide capital-labor estimates. Following the earlier work on this approach, Productivity estimates were imputed for it is assumed that efficiency in the use of inputs economies that had insufficient data to calcu- is the same across countries. Once the necessary late such estimates. They were based on the data are available, adjustment factors for the productivity estimates for similar types of relative wages (F) can be computed. These are economies in their region. based on capital input (relative to the average The capital/worker adjustment is straightfor- country) for country i compared with capital ward conceptually because it answers the ques- input for base country b in each region: tion of how much higher labor productivity would be if workers in the economy of concern Fi ,b = =1/e (Pi − Pb ) (4.4) had the same level of capital as the base country.  ki  where Pi = 1 2 (a + a )ln  and similarly for k The production function framework that was  used in ICP 2005 was applied, assuming that base country b. output is produced by means of two inputs: The adjustment factors, as defined in equa- labor and capital (World Bank 2008; Heston tion (4.4), are used to adjust the PPP for wages 2013). It is assumed that output of government in country i relative to base country b for pro- services Y is produced using capital K and labor ductivity differences: L with efficiency level A: w ,b × Fi ,b . PPP i ,b = PPPiw (4.5) Y = f(K, L, A). (4.1) Because this model implies that a govern- Assuming the production function has con- ment worker is less productive in a country stant returns to scale and exhibits Hicks-neutral with less capital per worker, that worker’s efficiency, (4.1) can be rewritten as productivity-adjusted wage should be higher, which leads to higher input PPPs and thus lower a Y  K relative output volumes. Another element that = A   ⇔ y = Aka (4.2) L  L would normally lead to cross-country differ- ences in labor productivity, and thus wages, are where a is the output elasticity of capital. differences in levels of schooling. Because the The aim is to compare labor productivity y ICP wages are collected for precisely specified between any given pair of countries i and j categories of workers, also distinguished by their (multilateral comparisons). Each country educational qualifications, it is assumed that no could be at a different point on the production further adjustments are required. The produc- function and thus could have a different tivity adjustment would be applied across all 2 categories of workers. This section is based an unpublished working paper, “Productivity Adjustment for Government Services PPPs: Alternatives and Proposal for The key input in implementing a capital- ICP 2011,” by Inklaar and Timmer (2013). based productivity adjustment is an estimate of 208 Purchasing Power Parities and the Real Size of World Economies capital stocks at current national prices. Capital taken from the Conference Board’s Total stocks are estimated using the perpetual inven- Economy Database, supplemented by data from tory method (PIM) and data on investment by the International Labour Organization (ILO) and asset. In contrast to the approach followed in the World Bank’s World Development Indicators. the 2005 ICP round, in the 2011 round capital- For economies for which these sources did not labor ratios were calculated based on country- provide enough information—in particular in the specific data on capital stocks and capital Caribbean region—the average employment- elasticities. For some economies time series of to-population ratio of the region was used. investment by assets were readily available from Adjustments for productivity differences were national accounts sources. For economies in made to the real expenditure estimates for gov- which this was not the case, the starting point ernment in the Africa, Asia and the Pacific, Latin was the ICP investment by asset data. For econ- America, and Caribbean regions. No productivity omies that participated in an ICP comparison adjustments were applied within the Eurostat- before 2011, the benchmark investment shares OECD, CIS, and Western Asia regions because were used in combination with the commodity differences in labor productivity within each of flow method (CFM) to estimate the share of those regions were considered to be relatively each asset in total investment over time. The small. However, productivity adjustments were CFM uses changes in the total supply (imports + made to all regions when the interregional link- production – exports) of a commodity to approx- ing factors were estimated to maintain consis- imate the change in investment. For economies tency in the global comparison. that were newcomers in ICP 2011, it was assumed that their 2011 asset investment pat- Machinery and equipment tern was constant over time. The investment PPPs from ICP 2011 were In the ICP 2011 expenditure classification, the available at a more detailed level than was category machinery and equipment was broken required for the productivity adjustment. As a down into two groups, metal products and first step, they were aggregated to six assets equipment and transport equipment, which were using a within-region GEKS procedure and further disaggregated into eight basic headings. investment shares as weights. As long as the Economies collected the prices of several speci- depreciation rates within each of the six assets fied items within most of these basic headings. are approximately the same, this simplification The prices included import duties, other product does not lead to a bias in the final PPP. In the taxes actually paid by the purchaser, the costs of second step, the six asset PPPs were combined transporting the asset to the place where it would into an overall capital stock PPP using a within- be used, and any charges for installing the asset region GEKS procedure and the capital stocks at so that it was ready for use in production. Any current national prices as weights. discount generally available to most producers The second type of national data needed for a was deducted from the price. Only new equip- capital-based productivity adjustment is the ment goods were priced in all economies in one marginal productivity of capital as reflected in or two quarters, depending on the region. the output elasticity of capital. This is not The procedures followed for collecting prices directly observable, but a common approach is for machinery and equipment were similar to to assume perfect competition in the labor and those followed for household consumption. product markets so that the revenue share of Detailed product specifications were prepared capital can be used instead. In ICP 2011, no for a global list that was generally used by all ICP information about the revenue share of capital regions for their regional comparisons and again for government services was available, and so by the Global Office to link the regions. For con- the capital share in overall GDP was used sistency with SNA93, pricing rules were defined instead. It also allowed consistency with the for transport and installation costs, nondeduct- capital stock measures. ible taxes, and discounts. Basic heading PPPs Implementing equation (4.4) also requires were computed using the CPD method—the data on employment. Employment data were importance classification was not applied. Methodologies Used to Calculate Regional and Global PPPs 209 Construction economies because it was assumed that the dif- ferent weights used took into account differ- Construction is a comparison-resistant compo- ences in the combined labor and capital nent of the ICP because it is not possible to com- productivity—that is, total factor productivity— pare actual construction projects from one between economies. In other words, the under- economy to another. Historically, the ICP used lying assumption was that total factor an output method to price construction. It productivity was constant across economies. involved specifying models in bills of quantities The construction PPPs were estimated in for various construction projects such as a dwell- four separate but consecutive steps: (1) input ing, a factory, or a bridge. For its 2005 round, prices collected for materials, labor, and equip- the ICP changed its approach and introduced ment were allocated to the three construction the basket of construction components (BOCC) category basic headings (residential buildings, method, mainly because of the greater number nonresidential buildings, and civil engineering of participating economies and the high cost of works) using product relevance information; collecting price data in all those economies for (2) PPPs for the input groups (materials, labor, the various models specified in previous rounds. and equipment), or subheadings under the However, problems were encountered in data three basic headings, were calculated using collection and validation, and so yet another the CPD, resulting in nine sets of subheading approach was adopted for ICP 2011. Meanwhile, PPPs; (3) the subheading PPPs were aggre- the Eurostat-OECD PPP Programme continues gated using resource mixes as weights, result- to use the bills of quantities approach, and the ing in three sets of basic heading PPPs; and CIS economies use a hybrid method that embod- (4) PPPs for the three basic headings were ies some characteristics of both the input aggregated using national accounts expendi- approach and the output approach. ture data as weights, resulting in PPPs for the The 2011 ICP construction and civil engi- construction category. neering survey was based on an input approach Construction PPPs for the CIS economies in which economies priced 50 basic and com- were linked to the Eurostat-OECD economies mon resources for construction work that were using Russia as a bridge (Russia priced construc- selected to correspond with the main inputs to tion using both the bills of quantities approach national construction output. In addition, infor- and the CIS hybrid approach). Several econo- mation was collected on product relevance, mies involved in the Eurostat-OECD compari- resource mixes (the weights needed to combine son also priced the inputs specified for the other prices for labor, materials, and equipment hire), regions, which provided a link for construction typical markups (overheads, profits, etc.), and between the Eurostat-OECD economies and the professional fees. rest of the world. The initial proposal included adjustments to the input prices for markups and professional fees, but the data collected on these elements REFERENCE PPPs turned out to be patchy and incomplete. Many economies did not provide these estimates, and For basic headings for which no price or other the data that were supplied proved to be so data were collected, PPPs were imputed in three inconsistent that they could not be used. different ways. In the first approach, most miss- Therefore, the 2011 construction PPPs for each ing PPPs were imputed using price-based refer- of the regions coordinated by the Global ence PPPs. This simply means that the PPPs from Office were based on input prices for the three a similar basic heading or headings became the categories weighted together. More than PPP for the missing value. The second approach 80 percent of economies reported details of the was the reference volume method used for resource mixes, and weights were imputed for housing and described earlier. Finally, exchange the remaining economies, based mainly on rates were used for the two basic headings those of similar economies. The PPPs were not exports of goods and services and imports of adjusted for productivity differences across goods and services and the two basic headings 210 Purchasing Power Parities and the Real Size of World Economies expenditures of residents abroad and expendi- the CIS and Eurostat-OECD comparisons. tures of nonresidents on the economic territory. Because Russia was included in the Eurostat- Appendix G provides a complete listing of the OECD comparison, its basic heading PPPs reference PPPs and the basic headings for which were linked to the rest of the world and they were used. aggregated to world GDP using the CAR pro- cedure. Global PPPs for the CIS economies were their PPPs from the CIS comparison (Russia = 1), multiplied by Russia’s global PPP AGGREGATING LINKED BASIC HEADING PPPs TO GDP in the global comparison. At this stage, there was a matrix of 148 econo- • The Caribbean was linked to the global com- mies3 (Africa, 50; Asia and the Pacific, 23; parison via the Latin America economies. As Eurostat-OECD, 47; Latin America, 16; and an initial step, the 22 Caribbean economies Western Asia, 12) times 155 basic heading PPPs. were linked to the 16 Latin America econo- Another matrix of the same size contained 155 mies, first at the basic heading level and then basic heading expenditures. A final computa- at aggregated levels. Linking at the basic tional step was to link regions at higher-level heading level was carried out by calculating aggregates and GDP. The country aggregation separate sets of CPD-W PPPs for Latin with redistribution (CAR) procedure was used America and the Caribbean, by subsequently for the global aggregation, and it included the calculating a combined set of respective following steps: PPPs, and finally by re-indexing the com- bined set of PPPs in accordance with the • A global aggregation that included all 148 intraregional results in order to maintain fix- economies and 155 basic headings in a GEKS ity of both the Latin America and Caribbean computation provided PPPs calibrated to a basic heading PPPs. Linking at the aggre- global currency. gated level was carried out using the CAR • To preserve within-region fixity, real expendi- procedure. The GEKS aggregation was car- tures expressed in the global currency were ried out first for Latin America and the summed to regional totals, which were then Caribbean separately and then for the com- distributed within each region according to the bined set of data. Finally, subregional totals distribution from the within-region of real expenditures were redistributed in computations. These results were base accordance with the economy’s real expen- country–invariant and transitive, and they diture shares from separate Latin America preserved fixity. and Caribbean aggregations in order to maintain fixity of both the Latin America and Caribbean results at all aggregated lev- els. As in the case of the standard ICP SPECIAL SITUATIONS regions, the aggregated PPPs were calculated The methods just described were used in the indirectly by dividing the nominal expendi- main ICP regions: Africa, Asia and the Pacific, tures by the real expenditures. This approach Eurostat-OECD, and Western Asia. This section enabled regional linking of the Caribbean is an overview of the special actions taken to economies, using the Latin America econo- increase the number of economies included in mies as a base, while maintaining base the global comparison. Those actions included economy invariance and fixity of results for the following: both subregions. As a second step, the Caribbean results were linked to the global • The CIS region was linked to the global com- comparison using Latin America’s global parison via Russia, which participated in both results as a bridge. 3 The CIS region, Cuba, the Caribbean region, and the singleton economies • Cuba was linked to the Latin America com- were linked in a second stage after the 148 economies were linked. parison via Peru for household consumption, Methodologies Used to Calculate Regional and Global PPPs 211 government compensation, machinery and economies did not participate in the comparison equipment, and construction. For housing, for a variety of reasons, including civil unrest, Cuba was linked via República Bolivariana lack of resources, or no national interest. de Venezuela, which had a typical housing Although these nonparticipating economies volume index per capita for the Latin America account for a small share of the world economy comparison as well as the dwelling stock and world population, it is still important that quantity and quality data needed for the they be included in any comprehensive mea- bilateral comparison. The price and expendi- surement of the world’s economic size or of ture data used for Cuba in the calculations world poverty. Thus to provide a more complete were expressed in convertible pesos. set of PPPs for the world economy, the ICP imputed PPPs for 15 of the economies that did • The global results contain two singleton econ- not participate in ICP 2011. omies that were not part of a regional com- For its 2005 round, the ICP imputed PPPs for parison. Georgia was linked to the CIS 42 nonparticipating economies. The drop in the comparison through a bilateral comparison number of nonparticipants in ICP 2011 was the with Armenia, and the Islamic Republic of result of the improved coverage in the Latin Iran was linked to the Eurostat-OECD com- America region and the introduction of two parison through a bilateral comparison with new regions, the Caribbean region and the Turkey. The global PPP for Georgia is a bilat- Pacific Islands region. Four of the nonpartici- eral PPP (Armenia = 1), multiplied by pants in ICP 2011 participated in ICP 2005: Armenia’s global PPP in the global compari- Argentina, Lebanon, South Sudan (as part of son. Similarly, the global PPP for Iran is a Sudan), and the Syrian Arab Republic. Eight of bilateral PPP (Turkey = 1), multiplied by the nonparticipants in ICP 2011 were also non- Turkey’s global PPP in the global comparison. participants in ICP 2005: Afghanistan, Eritrea, • The Pacific Islands comparison covered only Guyana, Libya, San Marino, Timor-Leste, the individual consumption expenditures by Turkmenistan, and Uzbekistan. households. The islands were linked to the rest of the world through economies in other ICP 2005 regional comparisons: Fiji from the Asia and the Pacific comparison and Australia and New The regression model used for ICP 2011 was Zealand from the Eurostat-OECD comparison. not the same as that used for ICP 2005. The 2005 model is described in the report Global The PPPs for the CIS, the Caribbean, Cuba, Purchasing Power Parities and Real Expenditures: the Pacific Islands, and the singletons were not 2005 International Comparison Program (World directly included in the global aggregations as Bank 2008) as described in previous sections. Instead, they were linked to the global aggregation in a way ln(GDP per capita) that had no impact on the comparisons of the = a + b × ln(GNI per capita) + c × ln(SGER) other economies. The results for the CIS, the Caribbean, Cuba, where GDP per capita is the ICP estimate based and the singletons are included in the main on 2005 PPPs; GNI per capita is gross national tables. The results for the Pacific Islands appear income per capita in U.S. dollars estimated by in supplementary table 2.12. the World Bank Atlas method; and SGER is the secondary (school) gross enrollment rate. The model was originally used to impute GDP per capita for economies missing from the 1993–96 IMPUTING PPPs FOR NONPARTICIPATING ECONOMIES ICP round. The 2008 World Bank report pointed out The 2011 round of the ICP attracted the partici- that the fit of the model could probably be pation of 199 economies. Even so, coverage of improved by including additional independent the world economy was not exhaustive. Some variables, but that a full exploration of various 212 Purchasing Power Parities and the Real Size of World Economies model specifications would have to wait until PLIusa = a + b × Xusa. (4.7) after the report’s publication. Subsequently, the search for a better regression model was carried If (4.7) is substituted into (4.6), the equation out, and the alternative model found yielded becomes better estimates. PLIi – PLIusa = b × (Xi – Xusa) + ec. (4.8) ICP 2011 Both the dependent variable and explanatory The improved method was used to impute PPPs variables are normalized by the corresponding for nonbenchmark economies for ICP 2011. The values of the United States. In the regression, all regression model uses the price level index (PLI) continuous variables are in natural log. In fact, for participating economies as the dependent there are two regressions, one for the PLI at the variable (the PLI is the ratio of a PPP to a cor- level of GDP, the other for the PLI at the level of responding market exchange rate). The PLI with private consumption. The two regressions are the United States equal to 100 is modeled as run together using Zellner’s Seemingly Unrelated Regression method. PLIi = a + b × Xi + ei . (4.6) Supplemental table 2.13 in chapter 2 presents the regression results for the 15 The explanatory variables, Xi, are GDP per economies that did not participate in ICP 2011 capita at market prices in U.S. dollars (based on for which estimates were imputed using this exchange rates), imports as a share of GDP, approach. It shows the regression PLI rebased exports as a share of GDP, and the age depen- on the world (world = 100); the PPP based on dency ratio. Dummy variables are included for the United States (US$ = 1.000)—obtained each of the groups—Sub-Saharan Africa econo- by dividing the economy’s regression PLI mies, OECD economies, island economies, and based on the United States by its exchange landlocked developing economies— and finally rate; the real GDP (and real GDP per capita) the interaction terms of GDP per capita and the in U.S. dollars—obtained by dividing the dummy variables. economy’s expenditure in national currency Because the United States is the base economy by its PPP (and its population); and the in the global multilateral comparison, its PPPs are nominal GDP (and nominal GDP per capita) always 1 and its PLIs are always 100. This in U.S. dollars—obtained by dividing the requires a constraint on equation (4.6) to force economy’s expenditure in national currency those values. The constraint can be written as by its exchange rate (and its population). Methodologies Used to Calculate Regional and Global PPPs 213 Appendix A History of the International Comparison Program (ICP) Statisticians have long recognized that using second and third editions of his study, Clark exchange rates to compare economies’ levels of increased the number of economies covered and economic activity can lead to misleading results. refined the methodology applied. In particular, the differences in the size of high- Clark’s pioneering stimulated further research. income economies with high price levels and In the 1950s, the Organisation for European low-income economies with low price levels Economic Cooperation used purchasing power will appear larger than they actually are. This equivalents to compare the national products of distortion can be avoided by using purchasing France, Germany, Italy, the United Kingdom, power parities (PPPs) instead of exchange rates and the United States. The comparison was to undertake such comparisons. subsequently enlarged to include Belgium, In his study, The Conditions of Economic Progress, Denmark, the Netherlands, and Norway. All British economist Colin Clark was the first to final expenditures, including government and use PPPs to estimate levels of real income. The capital expenditures, were covered in the com- first edition of his study was published in 1940, parison. In the 1960s, the Economic Commission followed by second and third editions in 1951 for Latin America carried out PPP-based com- and 1957 (all published by Macmillan, London). parisons of real product in 19 Latin American The first edition covered the United States and economies; the Council for Mutual Economic 52 other economies. Other economies were Assistance (COMECON) conducted PPP-based linked through a series of bilateral comparisons comparisons of national income between several with the United States. The results were then central and eastern European centrally planned used to quantify the intereconomy spread in economies; and the Conference of European real income per capita and to provide an esti- Statisticians approved a project to undertake mate of world income. Income was defined as PPP-based comparisons of consumption levels consumer expenditure and did not include gov- among a small group of market economies and ernment expenditure or capital expenditure. centrally planned economies. For income per capita, total persons employed In 1965 the United Nations Statistical rather than total population was the denomina- Commission (UNSC) discussed the problems tor. The PPPs were calculated using Fisher’s ideal inherent in exchange rate–based comparisons index formula. Referred to as international and agreed that the United Nations Statistical units, they measured the purchasing power of Office (UNSO)1 should develop a more suitable national currencies over the period 1925–34 based on average prices for the period. In the 1 Now called the United Nations Statistics Division (UNSD). 215 methodology for making international com- regarding the extent to which the government parisons of gross domestic product (GDP). In and private sectors provided health and 1968 the UNSC considered a report that out- education services in different economies. In lined a research project to be run from 1968 to this respect, the ICP was more than two decades 1971 aimed at developing PPP-based compari- ahead of the System of National Accounts sons. The report proposed using a small group 1993 (SNA93), which set out the concept of of economies representative of different income actual individual consumption (defined almost levels, social systems, and geographical areas to identically to the CEP) as an official national test and assess methodology. The UNSC agreed accounts measure (Commission of the European that the project should proceed, and, because Communities et al. 1993). the UNSO had only limited resources, asked Until 1993, the ICP was conducted in phases; other international organizations and UN mem- after 1993 it was organized by rounds. Phase I ber economies to assist in the project. At this had two stages. The first stage was a pilot study stage, the research endorsed by the UNSC was based on data collected for 1967 for six econo- to cover GDP measured from both the expendi- mies (Hungary, India, Japan, Kenya, the United ture and production sides of the national Kingdom, and the United States). The second accounts. Even so, it was understood that the stage was run for 1970 and included four addi- initial efforts would concentrate on the expen- tional economies (Colombia, France, Germany, diture side—it was less difficult to implement in and Italy) that had not been able to report the practice because a single set of expenditures necessary data for 1967. The outcome consisted was involved rather than both outputs and of different sets of estimates, including multilat- inputs, which gave rise to the added complexity eral comparisons between all 10 economies for of double deflation. GDP and a range of expenditure components for The International Comparison Project was 1970. The results of Phase I were published in launched in 1968 as a joint undertaking between 1975 in A System of International Comparisons of the UNSO and the University of Pennsylvania, Gross Product and Purchasing Power (Kravis et al. which established a special unit funded by a 1975). The details presented in this publication grant from the Ford Foundation. The World include the overall results of the multilateral Bank became involved, providing financial comparison for 1970, a variety of bilateral assistance directly and also through a grant from comparisons for both 1967 and 1970, and the the Scandinavian economies that was chan- outcomes of various experiments on important neled through the Bank. The U.S. Agency for issues such as rents, motor vehicle prices, and the International Development and the U.S. Social consistency of different quantity comparisons. Science Research Council assisted with mone- Phase II included six more economies tary contributions. The United Kingdom offered (Belgium, the Islamic Republic of Iran, the in-kind statistical support for the participating Republic of Korea, Malaysia, the Netherlands, economies. The director of UNSO was responsible and the Philippines), initially to enable a broader for supervising the project. The advisory board comparison for 1970, but mainly to update the set up to provide technical advice considered PPPs and associated price and volume measures detailed proposals for the project at a meeting to 1973. Results for the 16 economies were pub- held in October 1969. lished in 1978 in International Comparisons of Real One of the proposals discussed by the advisory Product and Purchasing Power (Kravis, Heston, and board resulted in the ICP adopting a concept of Summers 1978). consumption that summed the individual con- Thirty-four economies participated in Phase sumption expenditures of households and III for reference year 1975. In the earlier phases, government to obtain an aggregate of total the detailed characteristics of products in the individual consumption called the consumption U.S. consumer price index were used as the expenditure of the population (CEP). The starting point for developing the ICP product objective in measuring the CEP was to minimize lists. Later, they were modified in consultation the effect on the volume comparisons of differ- with some of the participating economies, ences in institutional arrangements, particularly including India and the COMECON group, to 216 Purchasing Power Parities and the Real Size of World Economies make the ICP product specifications more approach in which selected economies priced a generally applicable—for example, by removing range of product specifications from another characteristics such as brand name that were region to provide a bridge or link between their specific to the United States. The greater diver- region and the other region. The reference year sity of economies in Phase III meant that the for Phase IV was 1980. range of products to be priced had to be further The reference year for Phase V was 1985. It expanded so that all participating economies saw only a small increase in the number of par- could price a sufficient number of products ticipating economies, from 60 to 64, with some representative of their expenditures. At this new economies replacing some that had been point, the ICP considered the pros and cons of in Phase IV but then dropped out of Phase V. continuing with a single global comparison or Once again, a regional approach was adopted. moving to regional comparisons that would be The regions were Africa, Asia, the Caribbean, linked to produce worldwide results. The trade- and Eurostat-OECD. In addition, three central off involved in regionalizing the project was and eastern European economies were added to improved comparisons between economies the Eurostat-OECD region using Austria as a within a region but at the expense of the bridge. The bridge economy approach was comparisons between economies in different again used to link the regions, but some of the regions because of the difficulties inherent in links were problematic because of the difficul- linking results between regions. In the end, ties several bridge economies encountered in however, Phase III went ahead as a single global collecting prices for a sufficiently broad range of comparison, although some regional results products from the other region. were presented as having been calculated for Phase VI, conducted with 1993 as the ref- the relevant economies from the globally based erence year, was the most ambitious phase results. The results of this phase were published yet, seeking to produce PPP-based compari- in 1982 in World Product and Income: International sons for 118 economies. In the end, however, Comparisons of Real Gross Product (Kravis, Heston, only 83 were covered. From the outset, this and Summers 1982). phase was beset by difficulties. Lack of fund- Phase IV saw some major developments in ing was the major problem, although the the program. The first was that the number of lack of overall coordination also led to some participating economies almost doubled, from major deficiencies in the final outcome. 34 to 60. The second was that the ICP shifted Regional comparisons were undertaken for from being a research project to being a regular Africa, Asia, Eurostat-OECD, and Western operational part of the UNSO work program. Asia, but not for Latin America. Moreover, With this development, the University of there was no global comparison because it Pennsylvania’s participation in the day-to-day proved virtually impossible to link the regions. running of the project ended, although it con- In response to these problems, in 1997 the tinued to advise on methodological issues. The UNSC commissioned a major review of the third significant change was the regionalization ICP before further phases were attempted. of the ICP. The principal reason for regionaliza- The report on the review was presented to tion was the large number of economies now the UNSC in 1999. It concluded that PPPs and involved worldwide, making it no longer feasible PPP-related statistics were needed, but that the to organize comparisons centrally. Another fac- ICP was not producing these data on a timely tor was the decision by the Organisation for and regular basis for a sufficient number of Economic Co-operation and Development economies as required by potential users. Poor (OECD) to set up a PPP program for its member management and insufficient resources at all economies in conjunction with the PPP program levels—central, regional, and national—were being run by Eurostat for economies in what is identified as the principal reasons for now the European Union. In addition to the the difficulties. Other important contributory Eurostat-OECD region, Africa, Asia, and Latin factors were inadequate documentation, heavy America participated in Phase IV as regions. The data requirements that did not take into regions were linked using the bridge economy account the circumstances of individual History of the International Comparison Program (ICP) 217 economies, lack of uniformity in the execution (assisted by the Australian Bureau of Statistics), of activities across regions, lack of confidence the Interstate Statistical Committee of the among economies that others were following Commonwealth of Independent States (CIS) guidelines and standards consistently, and fail- with the State Statistical Service of the Russian ure to involve economies in the editing and Federation, the United Nations Economic calculation stages of the exercise. The report Commission for Latin America and the Caribbean recommended that the UNSC not sanction a with Statistics Canada, and the United Nations new round until at least the management and Economic and Social Commission for Western resource issues had been resolved. Asia—and by Eurostat and the OECD. The ICP The UNSC’s response was to ask the World Global Office was established at the World Bank Bank to consult with other interested parties to provide overall coordination and to ensure and propose a strategy to address the deficien- technical and procedural uniformity across the cies identified by the review and to draw up an regions. The Global Office was also responsible implementation plan for a new round of the ICP. for organizing the Ring comparison that, by com- The plan involved mobilizing funds from a vari- paring a small number of economies from each ety of sources and establishing a governance region across regions, provided the means to link infrastructure to provide effective management the regional comparisons in one global or world- and coordination between the center and the wide comparison. The final results of the regional regions and between the regions and the par- and global comparisons were published at the ticipating economies. It also involved providing end of 2007 and the beginning of 2008. complete and clearly written documentation on ICP 2005 was generally considered to be a the ICP’s technical and procedural guidelines success. It covered 146 economies, including the and standards. Such guidelines would allow major emerging ones such as Brazil, China, economies to participate in a full comparison India, Indonesia, the Russian Federation, and covering GDP or in a partial comparison cover- South Africa, and its results were published on a ing actual final consumption, using, as far as timely basis in 2008 in Global Purchasing Power possible, regular national statistical programs to Parities and Real Expenditures: 2005 International obtain price and national accounts data for the Comparison Program (World Bank 2008). An ICP and linking participation in the ICP to important contributory factor was the gover- national statistical capacity building. nance structure that the World Bank had put in The UNSC considered the implementation plan place prior to the start of the exercise to ensure in 2000 and again in 2001. It was reluctant to start that the ICP regional coordinating agencies another round of the ICP before adequate funding would deliver within a common time frame had been secured. However, after the World Bank regional results that would be consistent across embarked on a successful major fund-raising exer- regions and that could be combined in a global cise, the UNSC agreed to a new round in 2002. comparison. The governance structure was The new round was launched in 2003 and retained after ICP 2005 to commence prepara- ended in 2008. The reference year was 2005. tions for the next round of the ICP proposed for Regional comparisons were organized by the 2011. The proposal was approved by the UNSC ICP regional coordinating agencies—the African in 2009. Appendix B describes the governance Development Bank, the Asian Development Bank structure of the ICP. 218 Purchasing Power Parities and the Real Size of World Economies Appendix B Governance of ICP 2011 As described in appendix A, the regional forces; the regional coordinating agencies and comparisons of the 1993 round of the regional coordinators; and the national coordi- International Comparison Program (ICP) could nating agencies and national coordinators. It not be combined in a global comparison. In contributed significantly to the successful con- response to this problem, in 1997 the United clusion of ICP 2005 and the timely publication Nations Statistical Commission (UNSC) called of the results of the global comparison covering for a major review of the ICP before it would 146 economies. The governance structure was agree to another round of comparisons. The retained for ICP 2011. findings of the review were reported to the The UNSC was the governing body at the top UNSC in 1999. Among the principal shortcom- of the structure. Because it included the nation- ings identified were the lack of a formally al statistics institutes of UN members, the major- defined governance structure and the conse- ity of which were participating in ICP 2011, as quent poor coordination between regions. well as the World Bank and other international Methods, processes, and timetables were not organizations, it was well placed to provide uniform across regions; results were not consis- overall supervision of ICP 2011 and to review tent between regions; and there was no blue- and act on issues raised by the Executive Board print for linking the regional comparisons. in its annual progress reports. One major result of the review was that in The Executive Board was made up of eminent 2002 the World Bank put in place a governance economists and statisticians and experienced structure to ensure that each region produced statistical managers. Many were heads of nation- results consistent with the results of other al statistics institutes or the statistics depart- regions and that each region’s results could be ments in international organizations. Others combined with the results of other regions in a were managers of economic statistics divisions global comparison. This goal was to be achieved and so were well versed in national accounts by coordinating the work globally, establishing a and price statistics. The board provided strategic single set of standards, providing centralized leadership and made decisions about ICP priori- technical and practical guidance, and ruling on ties, standards, the overall work program, and issues that had the potential to be interpreted in the budget. It had a key role in providing over- different ways in the regions. The structure had sight of the activities of the Global Office and several tiers: the UNSC; the ICP Executive ensuring that the ICP was completed on time Board; the Global Office and global manager; and within budget and that it produced and dis- the Technical Advisory Group and affiliate task seminated high-quality purchasing power 219 parities (PPPs) and real expenditures. The board ing expenditures, the reporting of metadata, and met twice a year. Usually the first meeting of the the establishment of a quality assurance frame- year was held back to back with the annual work. The Global Office also imputed the real meeting of the UNSC. Between meetings, the GDP per capita of economies that did not par- board was kept informed about program imple- ticipate in ICP 2011. mentation by means of a midyear progress Helping the Global Office to resolve concep- report prepared by the Global Office. In 2013, tual, methodological, and technical issues was the final year of ICP 2011, the Global Office pro- the Technical Advisory Group (TAG). Its members, vided the board with a status report every two who were international experts in the fields of months in addition to the midyear report. index numbers, prices, or national accounts, The Global Office was situated in the head- were appointed by the Executive Board. TAG quarters of the World Bank in Washington, DC. met twice a year, usually in tandem with the It was subject to the World Bank’s administra- spring and fall meetings of the regional coordi- tive and fiduciary rules and regulations, and on nating agencies organized by the Global Office. routine matters it reported to the director of the Working with TAG and the Global Office were World Bank’s Development Data Group. The three task forces: the Validation Expert Group, the Global Office carried out the day-to-day work PPP Computation Task Force, and the Results Review required to implement ICP 2011 worldwide. Group. The Validation Expert Group was con- The global manager was responsible for the oper- cerned primarily with the interregional valida- ations of the Global Office, supported by a team tion of the price, expenditure, and other data of professional statisticians and administrative that regions provided for the global comparison, staff. The Global Office reported regularly to the ensuring that it was carried out correctly follow- Executive Board and, through the board, to the ing the agreed-on approach and processes. The UNSC. Its annual work program and budget PPP Computation Task Force focused on calcu- required the approval of the board. lating the results for the global comparison. It The principal activities carried out by the consisted of a group of computation experts Global Office during ICP 2011 included develop- who calculated the global results independently ing ICP methodologies and standards; preparing of each other to ensure that they converged and Measuring the Real Size of the World Economy: were computed in full accordance with TAG The Framework, Methodology, and Results of the recommendations. Finally, the Results Review International Comparison Program (ICP) (World Group reviewed the plausibility of the global Bank 2013) and the Operational Guidelines and results and their compliance with approved Procedures for Measuring the Real Size of the World methods and procedures. Economy: 2011 International Comparison Program The regional coordinating agencies, working (World Bank forthcoming); updating and main- with the regional coordinators, oversaw the taining the ICP website; drawing up the product regional comparisons for ICP 2011. They were specifications for the global core product lists for responsible for developing the regional product consumer goods and services, dwelling services, lists and selecting the global core products to be government services, and capital goods; coordi- included in them; coordinating price data col- nating data collection and data validation across lection, expenditure data validation, and data regions; integrating economies not participating validation within their region; and compiling in a regional comparison in the global compari- and disseminating the regional PPPs and real son; producing software for data validation and expenditures. The regional coordinators met for the calculation of PPPs and related price and regularly at meetings convened by the Global real expenditure measures; providing the regions Office to discuss methodology, implementation, with technical assistance as required; calculating timetable, and progress. and publishing the global PPPs and real expendi- In ICP 2011, there were eight regions, tures; and, with the Executive Board, formulat- of which seven (all geographical) were overseen ing policies such as those on data access and by the Global Office: Africa, Asia and the revisions. Particular attention was paid to Pacific, Commonwealth of Independent States improving the estimation of GDP and basic head- (CIS), Latin America, the Caribbean, Western 220 Purchasing Power Parities and the Real Size of World Economies Asia, and the Pacific Islands. The eighth region government; actual and imputed rents; quanti- comprised the group of economies participating tative and qualitative data on the dwelling stock; in the 2011 comparison under way within the population; and exchange rates) and transmit- PPP program being run by Eurostat, the statisti- ting them to the regional coordinating agency. cal arm of the European Union, and the This responsibility entailed ensuring that the Organisation for Economic Co-operation and economy’s data were correctly estimated and Development (OECD)—see appendix C. The complied with ICP requirements; that statistical group consisted mainly of European economies, staff, particularly price collectors, were trained but also included economies from regions in the concepts underlying the ICP and the outside Europe. The economies were treated as practical implications for collecting prices; that an autonomous region for the purposes of data were edited and entered into the ICP data- incorporating them in the global comparison. base; and that editing queries from the regional The regional coordinating agencies for the seven coordinator were handled promptly. The nation- ICP regions were the African Development al coordinators also attended the data validation Bank, Asian Development Bank, Interstate workshops held in each of the regions to check Statistical Committee of the Commonwealth the consistency of the data supplied within of Independent States, United Nations Economic each region. Commission for Latin America and the Not all economies participated in the frame- Caribbean, United Nations Economic and Social work of the governance structure. Georgia and Commission for Western Asia, and Australian the Islamic Republic of Iran did not participate in Bureau of Statistics. Comparisons in the eighth any of the regional comparisons. Their link to the region were organized by Eurostat and the global comparison was established through a OECD. The methodology employed was, with bilateral comparison with an economy participat- some exceptions, basically the same as that used ing in a regional comparison. Georgia was linked in the seven ICP regions. The Global Office, to the CIS comparison through a bilateral com- Eurostat, and the OECD worked closely together parison with Armenia, and the Islamic Republic during all phases of ICP 2011 to ensure that the of Iran was linked to the Eurostat-OECD com- economies in the eighth region could be includ- parison through a bilateral comparison with ed in the global comparison. Turkey. The bilateral comparisons were organized In most economies, different units within and coordinated by the Global Office. By con- their statistical offices and sometimes different trast, the Arab Republic of Egypt, Fiji, the Russian agencies were involved in providing the various Federation, and Sudan participated in two data sets required for ICP 2011. In such cases, regional comparisons. Egypt and Sudan partici- one unit or agency was nominated as the pated in the Africa comparison and the Western national coordinating agency and within that unit Asia comparison; Russia participated in the CIS or agency a national coordinator was appointed. comparison and the Eurostat-OECD comparison; The national coordinator was responsible for and Fiji participated in the Asia and the Pacific assembling the economy’s ICP data (national comparison and the Pacific Islands comparison. final expenditures; prices for consumer products, The dual participation was coordinated by the equipment goods, and construction; compensa- regional agencies responsible for the regional tion of employees for selected occupations in comparisons involved and the Global Office. Governance of ICP 2011 221 Appendix C Eurostat-OECD PPP Programme The output of the purchasing power parity expenditure each year. Annual comparisons of (PPP) program jointly managed by Eurostat (the the household expenditure are made with statistical arm of the European Union) and the the prices of products priced in the reference Organisation for Economic Co-operation and year and with the extrapolated or retropo- Development (OECD) is PPP-based comparisons lated prices of products priced in adjacent of the gross domestic product (GDP) and its years. Annual comparisons of other compo- component expenditures of economies that are nents of GDP—government expenditure and members, or candidates for membership, or capital formation—are made with the prices associates of either the European Union or the collected each year for government services OECD. The program was established in the early and capital goods. 1980s, but its origins can be traced back to 1975 The OECD also adopted the rolling survey when, as part of Phase II of the International approach and the collection of consumer prices Comparison Program (ICP), Eurostat conducted over three years, but it did not adopt the yearly the first official comparison for the European pricing of government services and capital goods Community (see appendix A). The comparison that annual comparisons of GDP require. covered the nine economies that were members Instead, because of the cost involved in pricing of the European Community at the time: capital goods and the resource constraints of the Belgium, Denmark, France, Germany, Ireland, economies participating in OECD comparisons, Italy, Luxembourg, the Netherlands, and the it was decided to price government services and United Kingdom. capital goods every third year. Thus since 1990, In the beginning, Eurostat-OECD compari- Eurostat-OECD comparisons have been carried sons were conducted every five years: 1980, out every three years; the comparison for 2011 1985, and 1990. After the 1990 comparison, is the latest. The next joint comparison will be Eurostat adopted the rolling survey approach conducted in 2014, with preliminary results and began making annual comparisons—see becoming available toward the end of 2015. chapter 18 of Measuring the Real Size of the World Economy: The Framework, Methodology, and Results of the International Comparison Program EUROSTAT-OECD COMPARISONS (ICP) (World Bank 2013). This approach entails collecting prices for consumer goods and ser- Eurostat-OECD comparisons, like ICP compari- vices over three years and pricing roughly sons, are made from the expenditure side. Each one-third of the product list for the household economy participating in the comparison 223 supplies a set of national annual purchasers’ still used for collective services. As for capital prices for a selection of goods and services cho- goods, Eurostat economies price construction sen from a common list of precisely defined every year and machinery and equipment every products and a detailed breakdown of the two years. OECD economies price capital goods national expenditure according to a common every three years. classification. Prices and expenditures refer to Both the Eurostat and OECD economies pro- the year of the comparison and cover the entire vide a breakdown of their national expenditure range of final goods and services comprising for the reference year t in t + 1, t + 2, and, in the GDP: consumer goods and services, government case of Eurostat economies, t + 3. OECD com- services, capital goods, inventories, valuables, parisons are considered final two years after the imports, and exports. In practice, economies reference year, whereas Eurostat comparisons report detailed expenditure data for the com- are considered final three years after the refer- plete range of final goods and services, but they ence year. The global results for the Eurostat report only prices for consumer goods and ser- and OECD economies included in this report are vices, government services, and capital goods based on the breakdowns of national expendi- because they are not required to price invento- ture that they reported in 2013 for 2011. ries, valuables, imports, and exports. For the most part, the price approach is followed. PPPs are calculated directly, with the prices provided ORGANIZATION OF THE 2011 COMPARISON by the participating economies, and volumes are obtained indirectly by deflating the national Forty-seven economies participated in the 2011 expenditures with the PPPs. The two exceptions Eurostat-OECD comparison: 37 European to this are housing and education, for which economies and 10 non-European economies volumes are calculated directly. (Australia, Canada, Chile, Israel, Japan, the Consumer goods and services are priced over Republic of Korea, Mexico, New Zealand, the three years in line with the rolling survey Russian Federation, and the United States). approach. Not all household expenditures are Eurostat was responsible for the European covered by the surveys that make up the economies and the OECD for the non-Euro- approach. Housing, hospital services, and edu- pean economies. The large number of econo- cation have their own surveys. Housing is sur- mies made it difficult for Eurostat and the veyed separately because the data sources are OECD to manage centrally the six price surveys different from those for other consumer ser- that constitute the three-year survey cycle of vices. The economies have to supply quantity the rolling survey approach. The organization and quality data on the housing stock in addi- of the effort was therefore decentralized for tion to prices. Hospital services and education operational reasons. are surveyed separately because of the overlap The 37 European economies were divided between consumer services and government into four groups; the 10 non-European econo- services. Both are purchased by households and mies were treated as one group. Each group are provided as well by government. Moreover, was headed by a group leader. The group an output-based approach, and not the input- leader’s principal responsibilities were coordi- price approach used previously, is employed for nating the establishment of a product list for both of them. The approach requires economi- the group for each survey and overseeing vali- cally significant quasi prices for hospital outputs dation of the prices collected by the group dur- and quantity and quality data for education ing each survey. Comparisons between groups outputs. The three surveys are conducted every were made by means of overlap products—that year by Eurostat economies and every three is, products included in two or more group years by OECD economies. product lists. When drawing up the product Government services, or more precisely lists, group leaders were required to ensure that collective services, are priced annually by there was a sufficient number of overlap prod- Eurostat economies and every three years by ucts to combine all five groups in a single com- OECD economies. The input-price approach is parison. Eurostat and the OECD supervised the 224 Purchasing Power Parities and the Real Size of World Economies coordination of group leaders and ensured a the end of each year. They covered all basic harmonized approach to the surveys. headings comprising the household expendi- Economies were divided into groups solely to ture because they were also used to extrapolate facilitate implementation of the rolling survey and retropolate prices from years adjacent to approach. All other surveys, such as those cover- the reference year. ing housing, hospital services, education, collec- For the services of cafés, restaurants, and tive services, capital goods, and GDP expenditures, hairdressers, economies reported the prices that were organized and coordinated centrally by purchasers paid for the service specified before Eurostat and the OECD. allowing for tips. They also provided the global tipping rates that their national accountants use to estimate the total expenditures on these ser- vices. The rates were used to adjust the PPPs DATA COLLECTION FOR THE 2011 COMPARISON calculated using the prices originally reported for these services. (Formerly, economies were The prices for consumer goods and services were also required to report a global rate for discounts collected over three years: 2010, 2011, and on motor vehicles and a global rate for tips to 2012. Economies reported purchasers’ prices for taxi drivers. However, this practice was discon- all items except motor vehicles, for which they tinued. Economies found it difficult to supply reported list prices because of the difficulty in global rates for discounts on motor vehicles, establishing discounts for individual transac- and, because PPPs are not calculated specifically tions. The majority of economies collected for taxis but for passenger transport by road in prices from a variety of outlets—convenience general, an adjustment could not be made.) stores, corner and neighborhood shops, depart- The data that an economy provided for ment stores, discount stores, kiosks, markets, housing depended on its rental market and how supermarkets, specialist shops and shop chains, it estimated imputed rents in its national service establishments, etc.—located in the cap- accounts. Economies with a large, representa- ital city. Some economies did not limit their tive, well-organized rental market typically price collections to capital cities and collected estimated imputed rents by the stratification prices in other cities as well. When averaged, method, whereby the housing stock was broken these prices were considered to be national down by type, size, quality, and location into prices. In most cases, however, the prices were strata and combined with information on actual not national because they referred to the capital rents paid in each stratum. Economies with city. In all cases, the prices were not annual small, unrepresentative, informally organized because they referred to the month in which rental markets tended to estimate imputed rents they were collected (usually May or November by the user cost method, which entails summing of the survey year). all the costs that owner-occupiers incur in own- Economies that collected prices in their capi- ing their dwellings. Economies employing the tal city provided spatial adjustment factors with stratification method reported actual rents and which to convert their capital city prices to imputed rents for a selection of apartments and national prices. All economies provided monthly houses. The rents reported were the national temporal adjustment factors with which to con- annual averages for 2011. Economies employ- vert their survey prices to annual prices. Spatial ing the user cost method provided details on adjustment factors and temporal adjustment their housing stock. The data on the quantity factors were supplied for basic headings. Spatial and quality of the housing stock were used to adjustment factors that were relevant to the estimate volumes for housing directly. The link basic headings covered by a particular price between the two groups of economies was pro- survey were reported one month after report- vided by a small subset of economies supplying ing the prices for the survey. The temporal both sets of data. adjustment factors, which were monthly and For hospital services, economies reported eco- which economies extracted from their con- nomically significant quasi prices for a com- sumer price index database, were reported at mon set of tightly defined treatments or case Eurostat-OECD PPP Programme 225 types typically offered in general and specialist section of occupations in collective services in hospitals. The quasi prices were economically 2011. The compensation of employees collected significant in that they reflected the direct, for an occupation was the average compensa- capital, and overhead costs of the case types tion paid for the occupation for a standardized and influenced decisions on the allocation of number of working hours. It was extracted from hospital resources. They were extracted from the government payroll. databases that health administrations and For capital goods in Eurostat-OECD compari- national insurance funds maintain for the pur- sons, Eurostat economies collect national pur- poses of health financing and reimbursement. chasers’ prices without the value added tax Case types referred to groups of treatments (VAT). Later, after the prices have been col- that were similar from a clinical perspective lected, economies report the global rate of the and in terms of their consumption of resources. VAT actually paid on capital goods during the Two kinds of case types were specified: medi- year to which the prices refer. The global rate is cal, which referred only to inpatients, and taken from their national accounts. The rates surgical, which were divided between those are used to adjust the PPPs calculated using the that applied only to inpatients and those that national purchasers’ prices originally reported were performed on both inpatients and outpa- for individual capital items. OECD economies tients (day patients). The specification for each also collect national purchasers’ prices but with case type included the relevant codes from the nondeductible taxes. No global rate is subse- International Classification of Diseases, 10th quently reported. There are two price surveys Revision (World Health Organization 2008) to for capital goods: one for equipment goods, the help economies locate the case type within other for construction. national classification and coding systems. For the 2011 comparison, economies col- Economies did not collect prices for education lected prices for equipment goods between April because volumes are estimated directly in and July of 2011. The prices were obtained from Eurostat-OECD comparisons. In the volumes for producers, importers, distributors, or actual pur- 2011, student numbers were measured in full- chasers. The prices collected were either pur- time equivalents that Eurostat and the OECD chasers’ prices for actual market transactions extracted from the Eurostat-OECD-UNESCO or purchasers’ prices for hypothetical market education database for each of the following six transactions—that is, what purchasers would levels of education: pre-primary, primary, lower pay if they made a purchase. secondary, upper secondary, postsecondary For construction in Eurostat-OECD compari- nontertiary, and tertiary. Results from the sons, economies price eight standard construc- OECD’s Programme for International Student tion projects covering different types of buildings Assessment (PISA) were used to make quality and structures. Each project is defined by a bill adjustments at the primary and lower secondary of quantities, and each bill of quantities has two levels. No quality adjustments were made at versions: a complete version specifying all the other levels. components making up the project and a The collective services produced by government reduced version specifying only the key compo- are nonmarket services that have no economi- nents. Each year, four projects are priced using cally significant market price. Because there are the complete version of their bill of quantities, no market prices with which to value output, and four projects are priced using the reduced nonmarket services are valued in the national version of their bill of quantities. There is a two- accounts at cost. To preserve consistency with year pricing cycle, and the version priced for a the prices underlying the estimates, the current project alternates from year to year. Prices for practice in Eurostat-OECD comparisons is to the projects have to be at the level of the pre- calculate PPPs for nonmarket services using vailing tender prices—that is, the prices of ten- input prices. Not all inputs are priced, only the ders that have been accepted by purchasers. most important, labor. Thus for the 2011 For the 2011 comparison, the four com- comparison, economies reported the annual plete bills of quantities and the four reduced compensation that government paid to a cross bills of quantities were priced by construction 226 Purchasing Power Parities and the Real Size of World Economies experts in the economies between May and and equipment goods were calculated using July of 2011. quasi expenditure weights that take the repre- In addition to the prices, quantities, and sentativity (importance) of the products priced adjustment factors just enumerated, participat- into account: a weight of 1 if the product is ing economies reported detailed basic heading representative (important) for an economy and expenditures for the 2011 comparison, first in a weight of 0 if it is not. PPPs for the basic 2012 and then again in 2013. The GDP expen- headings for housing, hospital services, educa- diture was broken down into 206 basic headings tion, and collective services were calculated in line with the definitions, concepts, classifica- using the expenditure shares of products tions, and accounting rules of the System of within the basic heading as weights. Basic National Accounts 1993 (Commission of the heading PPPs for construction were calculated European Communities et al. 1993) and the without weights. European System of Accounts 1995 (Eurostat 1996). PPPs for aggregates were obtained by The 206 basic headings summed exactly to the weighting and summing the PPPs of their com- 155 basic headings of the ICP expenditure clas- ponent basic headings. GDP expenditures on sification (see appendix D). the basic headings were used as weights. The Also required for the 2011 comparison were results of the joint comparison for 2011 respect each economy’s annual average exchange rates fixity—that is, the relativities established and annual average resident population. These between economies in the Eurostat compari- data were extracted by Eurostat or the OECD son remain unchanged when the economies from in-house databases. The exchange rates are included in the comparison with OECD were the annual averages of daily market or economies. This ensures that there is only one central rates compiled by the European Central set of results for the European Union, an Bank or the International Monetary Fund. important consideration because of the admin- Average annual resident population referred to istrative uses to which PPPs are put by the the economic territories covered by the GDPs of European Commission. participating economies. ADDITIONAL INFORMATION CALCULATION AND AGGREGATION OF PPPS Further details about the Eurostat-OECD PPP Programme can be found in the 2012 edition of In the Eurostat-OECD comparisons, the Gini- the Eurostat-OECD Methodological Manual on Éltetö-Köves-Szulc (GEKS) method is used to Purchasing Power Parities (OECD and Eurostat compute the multilateral PPPs that are transitive 2012). The manual explains the theory and and base country–invariant at both the basic practice underlying the program and describes heading and aggregate levels. the methods, organization, and information For the 2011 comparison, PPPs for basic technology tools employed by Eurostat and the headings covering consumer goods and services OECD in making their comparisons. Eurostat-OECD PPP Programme 227 Appendix D ICP Expenditure Classification The classification of gross domestic product (GDP) a four-digit code, groups by a five-digit code, expenditures used by the International and classes by a six-digit code. Basic headings Comparison Program (ICP) adheres to the inter- have a seven-digit code. Thus nationally agreed-on concepts, definitions, classifi- 110000 INDIVIDUAL CONSUMPTION cations, and accounting rules of the System of EXPENDITURE BY HOUSEHOLDS National Accounts 1993 (Commission of the (main aggregate) European Communities et al. 1993). It is struc- 110100 FOOD AND NONALCOHOLIC tured first by type of final expenditure—individual BEVERAGES (category) consumption expenditure, collective consumption 110110 Food (group) expenditure, or capital expenditure—and then, in 110111 Bread and cereals (class) the case of individual consumption expenditure, 110111.1 Rice (basic heading). by purchaser—households, nonprofit institu- tions serving households (NPISHs), and general Of these aggregation levels, the basic heading government. The individual consumption expen- level is particularly important. It is at this level diture and collective consumption expenditure that expenditures are defined and estimated, are classified by purpose or function following products are selected for pricing, prices are col- the Classification of Individual Consumption lected and validated, and purchasing power According to Purpose (COICOP) and the parities (PPPs) are first calculated and averaged. Classification of the Functions of Government In principle, a basic heading consists of a group (COFOG)—see United Nations Statistics Division of similar well-defined goods or services. In (1999a, 1999b). Capital expenditure is classified practice, a basic heading is defined by the lowest by type of product broadly in line with the Central level of final expenditure for which explicit Product Classification (CPC)—see United Nations expenditures can be estimated by the participat- Statistics Division (1998). ing economies. Consequently, basic headings GDP comprises seven main aggregates, and in can cover a broader range of goods or services the classification these are broken down into 26 than is theoretically desirable. expenditure categories, 61 expenditure groups, 126 expenditure classes, and 155 basic headings, DERIVING ACTUAL INDIVIDUAL as shown in table D.1. CONSUMPTION In the outline of the expenditure classifica- tion that appears in table D.2, main aggregates ICP comparisons of material well-being compare are identified by a two-digit code, categories by the actual individual consumption of households 229 Table D.1 Structure of the ICP Expenditure Classification, ICP 2011 Main aggregates with code description Categories Groups Classes Basic headings 11. Individual consumption expenditure by households 13 43 90 110 12. Individual consumption expenditure by nonprofit institutions serving households (NPISHs) 1 1 1 1 13. Individual consumption expenditure by government 5 7 16 21 14. Collective consumption expenditure by government 1 1 5 5 15. Gross fixed capital formation 3 6 11 12 16. Changes in inventories and valuables 2 2 2 4 17. Balance of exports and imports 1 1 1 2 Gross domestic product 26 61 126 155 Source: ICP, http://icp.worldbank.org/. and not the individual consumption expenditure the outline shows that basic heading 110631.1, of households. Actual individual consumption is hospital services, is combined with basic heading obtained by summing the individual consump- 130212.4, hospital services, under (government) tion expenditures of households, NPISHs, and health benefits and reimbursements, and with general government. The individual consumption group 130220 (government), production of health expenditures of NPISHs and general government services, which is assumed to be predominantly cover their expenditures on the services they pro- the provision of hospital services. vide individual households as social transfers in The individual consumption expenditures of kind—that is, services related to housing, health, NPISHs should also be broken down, but they are recreation and culture, education, and social not because most economies are unable to pro- protection. Combining these expenditures is vide the required level of detail. Instead, the necessary because of the various ways in which expenditures of NPISHs are reported in total. individual services are financed in different econ- Subsequently, this total is distributed over the 13 omies. If the expenditures are not combined and basic headings covering individual services under only the individual consumption expenditures of the household expenditure in the same propor- households are compared, households in econo- tions that the household expenditure on indi- mies in which NPISHs or general government vidual services is distributed across the 13 basic provide individual services will appear to con- headings. Thus if households spend a total of sume a smaller volume of goods and services than $100,000 on the 13 basic headings, of which households in economies in which households $10,000 is spent on the basic heading 110411.1, themselves pay directly for these services. actual and imputed rentals, and if the total indi- In order to combine the individual consump- vidual consumption expenditure by NPISHs is tion expenditures of households and general $50,000, then $5,000 of the NPISH expenditure government, the classification breaks down the will be allocated to the basic heading for actual individual consumption expenditures of govern- and imputed rents. ment so that they can be added to their counterpart expenditures under the household expenditure. The breakdowns are structured so that the sum- FACILITATING THE INPUT PRICE mation is at the lowest level of aggregation feasi- APPROACH ble, which is generally at the level of the basic heading. In the outline of the classification shown The collective and individual services produced in table D.2, the combinations are indicated in by general government are nonmarket services italics. For example, under household expenditure because they are either provided free or sold at 230 Purchasing Power Parities and the Real Size of World Economies prices that are not economically significant. In the government expenditure on government- the absence of economically significant prices, produced services. national accountants obtain the expenditure on nonmarket services by summing the costs of the inputs required to produce them. To main- ADJUSTING THE HOUSEHOLD tain consistency with the prices underlying the EXPENDITURE TO THE NATIONAL estimated expenditure on nonmarket services CONCEPT in the national accounts, the PPPs for nonmar- ket services are based on input prices. To enable Expenditures on the basic headings constituting application of the input price approach, the the individual consumption expenditure by classification breaks down the final consump- households are defined according to the national tion expenditure by government on the pro- concept—that is, they cover only expenditures duction of collective services and the principal by resident households, including their expendi- individual services—education and health— tures abroad, and exclude the expenditures of into the following components: compensation nonresident households within the economic of employees, intermediate consumption, gross territory. Many economies, however, estimate operating surplus, and net taxes on production the expenditures on these basic headings (the sum of these four components is a mea- according to the domestic concept—that is, irre- sure of government output). Receipts from spective of whether the household making the sales (such as those from statistical publica- purchase is resident or not. For these econo- tions) are deducted from output to provide the mies, the classification contains a global adjust- estimate of the government final consumption ment to rectify this difference. The adjustment is expenditure. defined as the balance of the expenditures of A distinction is made between the govern- residents abroad less the expenditures of non- ment expenditure on the health and education residents within the economic territory or as net services that a government produces and a gov- purchases abroad. It is important to note that ernment’s expenditure on the health and educa- many economies base their estimates of the tion services that it purchases from market household final consumption expenditure on producers in the private sector under benefits household budget surveys, and so the estimates and reimbursements. This approach ensures are automatically on a national basis. For these that the input price approach is applied only to economies, the global adjustment is not required. Table D.2 Expenditure Classification, ICP 2011 Code Description 100000 GROSS DOMESTIC PRODUCT 110000 INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS 110100 FOOD AND NONALCOHOLIC BEVERAGES 110110 Food 110111 Bread and cereals 110111.1 Rice 110111.2 Other cereals, flour, and other cereal products 110111.3 Bread 110111.4 Other bakery products 110111.5 Pasta products 110112 Meat 110112.1 Beef and veal 110112.2 Pork (continued) ICP Expenditure Classification 231 Table D.2 (Continued) Code Description 110112.3 Lamb, mutton, and goat 110112.4 Poultry 110112.5 Other meats and meat preparations 110113 Fish 110113.1 Fresh, chilled, or frozen fish and seafood 110113.2 Preserved or processed fish and seafood 110114 Milk, cheese, and eggs 110114.1 Fresh milk 110114.2 Preserved milk and other milk products 110114.3 Cheese 110114.4 Eggs and egg-based products 110115 Oils and fats 110115.1 Butter and margarine 110115.3 Other edible oils and fats 110116 Fruit 110116.1 Fresh or chilled fruit 110116.2 Frozen, preserved, or processed fruit and fruit-based products 110117 Vegetables 110117.1 Fresh or chilled vegetables other than potatoes 110117.2 Fresh or chilled potatoes 110117.3 Frozen, preserved, or processed vegetables and vegetable-based products 110118 Sugar, jam, honey, chocolate, and confectionery 110118.1 Sugar 110118.2 Jams, marmalades, and honey 110118.3 Confectionery, chocolate, and ice cream 110119 Food products n.e.c. 110119.1 Food products n.e.c. 110120 Nonalcoholic beverages 110121 Coffee, tea, and cocoa 110121.1 Coffee, tea, and cocoa 110122 Mineral waters, soft drinks, fruit and vegetable juices 110122.1 Mineral waters, soft drinks, fruit and vegetable juices 110200 ALCOHOLIC BEVERAGES, TOBACCO, AND NARCOTICS 110210 Alcoholic beverages 110211 Spirits 110211.1 Spirits 110212 Wine 110212.1 Wine 110213 Beer 110213.1 Beer 110220 Tobacco 110221 Tobacco 110221.1 Tobacco 232 Purchasing Power Parities and the Real Size of World Economies Table D.2 (Continued) Code Description 110230 Narcotics 110231 Narcotics 110231.1 Narcotics 110300 CLOTHING AND FOOTWEAR 110310 Clothing 110311 Clothing materials, other articles of clothing, and clothing accessories 110311.1 Clothing materials, other articles of clothing, and clothing accessories 110312 Garments 110312.1 Garments 110314 Cleaning, repair, and hire of clothing 110314.1 Cleaning, repair, and hire of clothing 110320 Footwear 110321 Shoes and other footwear 110321.1 Shoes and other footwear 110322 Repair and hire of footwear 110322.1 Repair and hire of footwear 110400 HOUSING, WATER, ELECTRICITY, GAS, AND OTHER FUELS 110410 Actual and imputed rentals for housing 110411 Actual and imputed rentals for housing 110411.1 Actual and imputed rentals for housing (combines with 130111.1) 110430 Maintenance and repair of the dwelling 110431 Maintenance and repair of the dwelling 110431.1 Maintenance and repair of the dwelling 110440 Water supply and miscellaneous services relating to the dwelling 110441 Water supply 110441.1 Water supply 110442 Miscellaneous services relating to the dwelling 110442.1 Miscellaneous services relating to the dwelling 110450 Electricity, gas, and other fuels 110451 Electricity 110451.1 Electricity 110452 Gas 110452.1 Gas 110453 Other fuels 110453.1 Other fuels 110500 FURNISHINGS, HOUSEHOLD EQUIPMENT, AND ROUTINE MAINTENANCE OF THE HOUSE 110510 Furniture and furnishings, carpets, and other floor coverings 110511 Furniture and furnishings 110511.1 Furniture and furnishings 110512 Carpets and other floor coverings 110512.1 Carpets and other floor coverings (continued) ICP Expenditure Classification 233 Table D.2 (Continued) Code Description 110513 Repair of furniture, furnishings, and floor coverings 110513.1 Repair of furniture, furnishings, and floor coverings 110520 Household textiles 110521 Household textiles 110521.1 Household textiles 110530 Household appliances 110531 Major household appliances whether electric or not 110531.1 Major household appliances whether electric or not 110532 Small electric household appliances 110532.1 Small electric household appliances 110533 Repair of household appliances 110533.1 Repair of household appliances 110540 Glassware, tableware, and household utensils 110541 Glassware, tableware, and household utensils 110541.1 Glassware, tableware, and household utensils 110550 Tools and equipment for house and garden 110551 Major tools and equipment 110551.1 Major tools and equipment 110552 Small tools and miscellaneous accessories 110552.1 Small tools and miscellaneous accessories 110560 Goods and services for routine household maintenance 110561 Nondurable household goods 110561.1 Nondurable household goods 110562 Domestic services and household services 110562.1 Domestic services 110562.2 Household services 110600 HEALTH 110610 Medical products, appliances, and equipment 110611 Pharmaceutical products 110611.1 Pharmaceutical products (combines with 130211.1) 110612 Other medical products 110612.1 Other medical products (combines with 130211.2) 110613 Therapeutic appliances and equipment 110613.1 Therapeutic appliances and equipment (combines with 130211.3) 110620 Outpatient services 110621 Medical Services 110621.1 Medical services (combines with 130212.1) 110622 Dental services 110622.1 Services of dentists (combines with 130212.2) 110623 Paramedical services 110623.1 Paramedical services (combines with 130212.3) 110630 Hospital services 234 Purchasing Power Parities and the Real Size of World Economies Table D.2 (Continued) Code Description 110631 Hospital services 110631.1 Hospital services (combines with 130212.4 and 130220) 110700 TRANSPORT 110710 Purchase of vehicles 110711 Motor cars 110711.1 Motor cars 110712 Motorcycles 110712.1 Motorcycles 110713 Bicycles 110713.1 Bicycles 110714 Animal-drawn vehicles 110714.1 Animal-drawn vehicles 110720 Operation of personal transport equipment 110722 Fuels and lubricants for personal transport equipment 110722.1 Fuels and lubricants for personal transport equipment 110723 Maintenance and repair of personal transport equipment 110723.1 Maintenance and repair of personal transport equipment 110724 Other services in respect of personal transport equipment 110724.1 Other services in respect of personal transport equipment 110730 Transport services 110731 Passenger transport by railway 110731.1 Passenger transport by railway 110732 Passenger transport by road 110732.1 Passenger transport by road 110733 Passenger transport by air 110733.1 Passenger transport by air 110734 Passenger transport by sea and inland waterway 110734.1 Passenger transport by sea and inland waterway 110735 Combined passenger transport 110735.1 Combined passenger transport 110736 Other purchased transport services 110736.1 Other purchased transport services 110800 COMMUNICATION 110810 Postal services 110811 Postal services 110811.1 Postal services 110820 Telephone and telefax equipment 110821 Telephone and telefax equipment 110821.1 Telephone and telefax equipment 110830 Telephone and telefax services 110831 Telephone and telefax services 110831.1 Telephone and telefax services (continued) ICP Expenditure Classification 235 Table D.2 (Continued) Code Description 110900 RECREATION AND CULTURE 110910 Audiovisual, photographic, and information processing equipment 110911 Audiovisual, photographic, and information processing equipment 110911.1 Audiovisual, photographic, and information processing equipment 110914 Recording media 110914.1 Recording media 110915 Repair of audiovisual, photographic, and information processing equipment 110915.1 Repair of audiovisual, photographic, and information processing equipment 110920 Other major durables for recreation and culture 110921 Major durables for outdoor and indoor recreation 110921.1 Major durables for outdoor and indoor recreation 110923 Maintenance and repair of other major durables for recreation and culture 110923.1 Maintenance and repair of other major durables for recreation and culture 110930 Other recreational items and equipment, gardens and pets 110931 Other recreational items and equipment 110931.1 Other recreational items and equipment 110933 Gardens and pets 110933.1 Gardens and pets 110935 Veterinary and other services for pets 110935.1 Veterinary and other services for pets 110940 Recreational and cultural services (combines with 130311.1) 110941 Recreational and sporting services 110941.1 Recreational and sporting services 110942 Cultural services 110942.1 Cultural services 110943 Games of chance 110943.1 Games of chance 110950 Newspapers, books, and stationery 110951 Newspapers, books, and stationery 110951.1 Newspapers, books, and stationery 110960 Package holidays 110961 Package holidays 110961.1 Package holidays 111000 EDUCATION 111010 Education 111011 Education 111011.1 Education (combines with 130400) 111100 RESTAURANTS AND HOTELS 111110 Catering services 111111 Catering services 111111.1 Catering services 236 Purchasing Power Parities and the Real Size of World Economies Table D.2 (Continued) Code Description 111120 Accommodation services 111121 Accommodation services 111121.1 Accommodation services 111200 MISCELLANEOUS GOODS AND SERVICES 111210 Personal care 111211 Hairdressing salons and personal grooming establishments 111211.1 Hairdressing salons and personal grooming establishments 111212 Appliances, articles, and products for personal care 111212.1 Appliances, articles, and products for personal care 111220 Prostitution 111221 Prostitution 111221.1 Prostitution 111230 Personal effects n.e.c. 111231 Jewelry, clocks, and watches 111231.1 Jewelry, clocks, and watches 111232 Other personal effects 111232.1 Other personal effects 111240 Social protection 111241 Social protection 111241.1 Social protection (combines with 130511.1) 111250 Insurance 111251 Insurance 111251.1 Insurance 111260 Financial services n.e.c. 111261 Financial intermediation services indirectly measured (FISIM) 111261.1 Financial intermediation services indirectly measured (FISIM) 111262 Other financial services n.e.c 111262.1 Other financial services n.e.c. 111270 Other services n.e.c. 111271 Other services n.e.c. 111271.1 Other services n.e.c. 111300 BALANCE OF EXPENDITURES OF RESIDENTS ABROAD AND EXPENDITURES OF NONRESIDENTS ON THE ECONOMIC TERRITORY 111310 Balance of expenditures of residents abroad and expenditures of nonresidents on the economic territory 111311 Balance of expenditures of residents abroad and expenditures of nonresidents on the economic territory 111311.1 Individual consumption expenditure by resident households in the rest of the world 111311.2 Individual consumption expenditure by nonresident households on the economic territory 120000 INDIVIDUAL CONSUMPTION EXPENDITURE BY NPISHs 120100 INDIVIDUAL CONSUMPTION EXPENDITURE BY NPISHs 120110 Individual consumption expenditure by NPISHs 120111 Individual consumption expenditure by NPISHs (continued) ICP Expenditure Classification 237 Table D.2 (Continued) Code Description 120111.1 Individual consumption expenditure by NPISHs (distributed over 110411.1, 110611.1 to 110631.1, 110941.1 to 110943.1, 111011.1, and 111241.1 in line with the distribution of household expen- diture on these basic headings) 130000 INDIVIDUAL CONSUMPTION EXPENDITURE BY GOVERNMENT 130100 HOUSING 130110 Housing 130111 Housing 130111.1 Housing (combines with 110411.1) 130200 HEALTH 130210 Health benefits and reimbursements 130211 Medical products, appliances, and equipment 130211.1 Pharmaceutical products (combines with 110611.1) 130211.2 Other medical products (combines with 110612.1) 130211.3 Therapeutic appliances and equipment (combines with 110613.1) 130212 Health services 130212.1 Outpatient medical services (combines with 110621.1) 130212.2 Outpatient dental services (combines with 110622.1) 130212.3 Outpatient paramedical services (combines with 110623.1) 130212.4 Hospital services (combines with 110631.1) 130220 Production of health services (combines with 110631.1) 130221 Compensation of employees 130221.1 Compensation of employees 130222 Intermediate consumption 130222.1 Intermediate consumption 130223 Gross operating surplus 130223.1 Gross operating surplus 130224 Net taxes on production 130224.1 Net taxes on production 130225 Receipts from sales 130225.1 Receipts from sales 130300 RECREATION AND CULTURE 130310 Recreation and culture 130311 Recreation and culture 130311.1 Recreation and culture (combines with 110940) 130400 EDUCATION (combines with 111011.1) 130410 Education benefits and reimbursements 130411 Education benefits and reimbursements 130411.1 Education benefits and reimbursements 130420 Production of education services 130421 Compensation of employees 130421.1 Compensation of employees 130422 Intermediate consumption 130422.1 Intermediate consumption 238 Purchasing Power Parities and the Real Size of World Economies Table D.2 (Continued) Code Description 130423 Gross operating surplus 130423.1 Gross operating surplus 130424 Net taxes on production 130424.1 Net taxes on production 130425 Receipts from sales 130425.1 Receipts from sales 130500 SOCIAL PROTECTION 130510 Social protection 130511 Social protection 130511.1 Social protection (combines with 111241.1) 140000 COLLECTIVE CONSUMPTION EXPENDITURE BY GOVERNMENT 140100 COLLECTIVE SERVICES 140110 Collective services 140111 Compensation of employees 140111.1 Compensation of employees 140112 Intermediate consumption 140112.1 Intermediate consumption 140113 Gross operating surplus 140113.1 Gross operating surplus 140114 Net taxes on production 140114.1 Net taxes on production 140115 Receipts from sales 140115.1 Receipts from sales 150000 EXPENDITURE ON GROSS FIXED CAPITAL FORMATION 150100 MACHINERY AND EQUIPMENT 150110 Metal products and equipment 150111 Fabricated metal products, except machinery and equipment 150111.1 Fabricated metal products, except machinery and equipment 150112 General-purpose machinery 150112.1 General-purpose machinery 150113 Special-purpose machinery 150113.1 Special-purpose machinery 150114 Electrical and optical equipment 150114.1 Electrical and optical equipment 150115 Other manufactured goods n.e.c. 150115.1 Other manufactured goods n.e.c. 150120 Transport equipment 150121 Road transport equipment 150121.1 Motor vehicles, trailers, and semitrailers 150121.2 Other road transport 150122 Other transport equipment 150122.1 Other transport equipment (continued) ICP Expenditure Classification 239 Table D.2 (Continued) Code Description 150200 CONSTRUCTION 150210 Residential buildings 150211 Residential buildings 150211.1 Residential buildings 150220 Nonresidential buildings 150221 Nonresidential buildings 150221.1 Nonresidential buildings 150230 Civil engineering works 150231 Civil engineering works 150231.1 Civil engineering works 150300 OTHER PRODUCTS 150310 Other products 150311 Other products 150311.1 Other products 160000 CHANGES IN INVENTORIES AND VALUABLES 160100 CHANGES IN INVENTORIES 160110 Changes in inventories 160111 Changes in inventories 160111.1 Opening value of inventories 160111.2 Closing value of inventories 160200 CHANGE IN VALUABLES 160210 Change in valuables 160211 Change in valuables 160211.1 Acquisitions of valuables 160211.2 Disposals of valuables 170000 BALANCE OF EXPORTS AND IMPORTS 170100 BALANCE OF EXPORTS AND IMPORTS 170110 Balance of exports and imports 170111 Balance of exports and imports 170111.1 Exports of goods and services 170111.2 Imports of goods and services Source: ICP, http://icp.worldbank.org/. Note: n.e.c. = not elsewhere classified. 240 Purchasing Power Parities and the Real Size of World Economies Appendix E National Accounts: Estimation, Compliance, and Exhaustiveness Economies participating in the International expenditure on each basic heading and, at the Comparison Program (ICP) are required to pro- same time, document how the expenditure was vide a detailed breakdown of their national estimated. The documentation aspect of MORES expenditure for the reference year according to was important because it allowed the estimation a common classification. The breakdown is used to be repeated if data were revised or if basic first in the regional comparison in which the heading expenditures had to be estimated for reporting economy is engaged and then in the another reference year. It was also in keeping global comparison. An outline of the classifica- with the emphasis placed on metadata and qual- tion used for ICP 2011 appears in appendix D; it ity assessment during ICP 2011. consists of 155 basic headings. Expenditures on the basic headings are used as weights when MORES worksheets basic heading purchasing power parities (PPPs) are weighted together to obtain PPPs for aggre- The MORES reporting form covered two years: gation levels above the basic heading level. The a recent year prior to 2011 and 2011. It was to PPPs so obtained are used to convert the nomi- be completed in two stages: first for the recent nal expenditures (in an economy’s national cur- year before national accounts data for 2011 rency) for each of the aggregation levels, became available and then for 2011 when data including the gross domestic product (GDP) for 2011 became available. The two-stage itself, to real expenditures. It is therefore essen- approach was adopted because it would allow tial that each participating economy supply a national accountants to address problems well complete set of basic heading expenditures. beforehand. Moreover, in the absence of data for a basic heading in 2011, the estimate for the recent year could be extrapolated to 2011. ESTIMATION There were three worksheets for each year (see the examples in box E.1). On worksheet 1, Many economies experience difficulties in economies recorded the initial expenditure val- breaking down their expenditure on GDP to the ues that were available for the year in question. basic heading level. To help economies over- These initial values could be just for GDP and the come these difficulties during ICP 2011, the main aggregates, or the values for the main Global Office developed the Model Report on aggregates could be broken down further by cat- Expenditure Statistics, or MORES. It was egory or even by group and class. If broken designed so that economies could estimate the down further, not all main aggregates would 241 necessarily be broken down with the same domestic production, imports, population degree of detail. The initial expenditure values growth, and consumer price inflation. provided the control totals. Values estimated for The Global Office also identified five the basic headings on worksheet 2 and recorded approaches to estimating basic heading expendi- under estimated expenditure values on work- tures. These approaches were not linked to spe- sheet 1 had to sum to these totals. Discrepancies cific basic headings because the choice of between initial values and estimated values had approach depended on the availability of data. to be resolved before the estimated values The five approaches were as follows: could be considered final and recorded on worksheet 3. 1. Estimating expenditure on the basic heading using data for the year for which the esti- mate was being made. Data sources, extrapolators, and estimation 2. Extrapolating the expenditure on the basic methods heading in a recent year or the previous To support MORES, the Global Office compiled comparison (ICP 2005). for each basic heading a list of potential data 3. Borrowing from another economy in the sources and a list of possible indicators with region a per capita quantity or volume which to extrapolate or adjust data. For exam- related to the basic heading. ple, for the basic heading rice, the list of sources 4. Borrowing from another economy in the included household expenditure surveys, retail region the structure of the class, group, or trade surveys, agricultural surveys, Food and category that includes the basic heading. Agriculture Organization (FAO) food balances, 5. Breaking down the quantity or volume of a sales tax data, and the consumer price index. class, group, or category into its constituent The list of indicators covered measures of basic headings in line with expert opinion. BOX E.1 MORES Worksheets, ICP 2011 Worksheet 1 Initial Estimated Expenditure Expenditure ICP Code Heading Value Values Discrepancies 100000 GROSS DOMESTIC PRODUCT 168,527.54 168,527.54 0 INDIVIDUAL CONSUMPTION EXPENDITURE BY 110000 HOUSEHOLDS 117,081.29 117,081.29 0 110100 FOOD AND NON-ALCOHOLIC BEVERAGES 59,812.66 59,812.66 0 110110 FOOD 0.00 51,634.63 110111 Bread and cereals 0.00 19,335.26 110111.1 Rice 6,370.77 110111.2 Other cereals, flour and other products 3,874.10 110111.3 Bread 3,435.03 110111.4 Other bakery products 1,907.83 110111.5 Pasta products 3,747.53 242 Purchasing Power Parities and the Real Size of World Economies BOX E.1 (Continued) MORES Worksheets, ICP 2011 Worksheet 2 Code Name # Indicator name Source name Year Value Unit 1101111 Rice 1 Sales of Rice Retail Census 2007 5,364 Population increase from Population Splitting Approach 2 2007 to 2011 Census 2011 5.30% Please indicate all the approach- 3 CPI price increase CPI 2011 12.1% es used in calculation of expendi- Adjusted expenditure for ture for this basic heading 4 rice [5364 × 1.053 × 1.121] 2011 6,331.74 Summation of adjusted basic heading values 2 Extrapolation 5 under “bread and cereals” 2011 19,216.79 Household Expenditure for “bread Expenditure 6 and cereals” subgroup Survey 2009 17,965.00 Population increase from Population 7 2009 to 2011 Census 2011 2.60% CPI increase for this sub- 8 group CPI 2011 4.90% Adjusted expenditure for “bread and cereals” 9 [17965 × 1.026 × 1.049] 2011 19,335.26 10 Estimated 2011 expenditure for 1101111 Rice [6331.74/19216,79] × 19335.26 6,370.77 Worksheet 3 Expenditure ICP Code Heading Value 100000 GROSS DOMESTIC PRODUCT 168,527.54 110000 INDIVIDUAL CONSUMPTION EXPENDITURE BY HOUSEHOLDS 117,081.29 110100 FOOD AND NON-ALCOHOLIC BEVERAGES 59,812.66 110110 FOOD 51,634.63 110111 Bread and cereals 19,335.26 110111.1 Rice 6,370.77 110111.2 Other cereals, flour and other products 3,874.10 110111.3 Bread 3,435.03 110111.4 Other bakery products 1,907.83 110111.5 Pasta products 3,747.53 National Accounts: Estimation, Compliance, and Exhaustiveness 243 Of these approaches, the first, in which the FISIM is only one of the imputations required expenditure on the basic heading is estimated by SNA93 that economies have problems imple- directly with data for the reference year, was the menting. Many economies have difficulty esti- recommended method. Because the four other mating the imputed rents of owner-occupiers by approaches estimate expenditure indirectly the stratification approach or by the user cost using data other than that for the reference approach as advocated by SNA93. They either year, they were considered second-best meth- use an alternative approach, such as asking ods. Even so, they were better than allocating owner-occupiers how much rent their dwelling expenditure on a class evenly across all basic would warrant, or limit the imputation to urban headings in the class. Of the four, extrapolation areas, or make no imputation at all. When prop- was the preferred method. The third and fourth erly measured, total rents for dwellings (that is, approaches, which involved borrowing from both actual and imputed rents together) account another economy in the region, required the for at least 5 percent of GDP in low-income advice and assistance of the regional coordina- economies, and that percentage is nearly twice tor. Exchanges between economies were facili- as much in high-income economies. Thus the tated by the national accounts workshops that GDP of economies that do not follow the SNA regional coordinators organized for the econo- rules on estimation of imputed rents are likely mies in their region. to be underestimated when compared with the GDP of economies that do. Even when economies adhere strictly to the COMPLIANCE AND EXHAUSTIVENESS definitions and accounting rules of SNA93, their measurement of GDP and its component Volume comparisons of GDP and its component expenditures will not necessarily be exhaus- expenditures require that all economies in a tive. If they have a large nonobserved econ- comparison employ the same definitions of GDP omy, their GDPs could be underestimated. and its component expenditures and that their Nonobserved refers to economic activities that measurement of GDP and its component expen- are hidden because they are illegal, or are legal ditures be exhaustive. but carried out clandestinely, or are under- ICP participants compile, or attempt to taken by households for their own use. The compile, their national accounts estimates in term also refers to activities that are missed line with the System of National Accounts because of deficiencies in the statistical system. 1993 or SNA93 (Commission of the European Such deficiencies include out-of-date survey Communities et al. 1993), but compliance is registers, surveys that have reporting thresh- not necessarily complete. For example, many olds that are too high or that have high rates of economies do not follow the SNA93 recom- nonresponse, poor survey editing procedures, mendation that imputed bank services and no surveys of informal activities such as charges—otherwise known as financial inter- street trading. Adjustments for the nonob- mediation services indirectly measured served economy can be significant. For example, (FISIM) in SNA93—be allocated to house- the 10 eastern and central European countries holds, general government, and the rest of the that joined the European Union in 2004 world, where they would be shown as final adjusted their GDP at that time by an average consumption, which increases GDP. Instead, of 12 percent. the economies retain the SNA68 practice of To ascertain the degree to which the GDPs allocating all the imputed bank service charges of economies participating in ICP 2011 were to producers, where they are treated as inter- comparable, the Global Office prepared two mediate consumption, which offsets the value questionnaires for the economies to com- of the charges and so they have no impact on plete: the National Accounts Quality GDP. Thus the levels of GDP of economies that Assurance Questionnaire, which focused on allocate FISIM and the levels of GDPs of econ- compliance with SNA93 and ICP require- omies that do not allocate FISIM are not ments, and the GDP Exhaustiveness strictly comparable. Questionnaire, which focused on quantifying 244 Purchasing Power Parities and the Real Size of World Economies the adjustments to be made to an economy’s GDP exhaustiveness questionnaire estimates of GDP to compensate for various Exhaustiveness is the extent to which an types of nonexhaustiveness. economy’s national accounts cover all the eco- nomic activities that are supposed to be included in GDP according to SNA93. The questionnaire National accounts quality assurance drawn up by the Global Office to determine the questionnaire exhaustiveness of the national accounts of par- This questionnaire was made up of 30 questions ticipants in ICP 2011 was based on the tabular that required a yes or no answer. There were approach to exhaustiveness developed by also boxes for comments if respondents wished Eurostat in the 1990s. The Eurostat approach to elaborate on their answers. The questions are focused primarily on the exhaustiveness of esti- listed in box E.2. mates from the production side. It took the form BOX E.2 ICP National Accounts Quality Assurance Questionnaire, ICP 2011 01. Do you implement SNA93? 02. Does your estimate of GDP cover the full range of economic activities and transactions that are included in the production boundary of SNA93? 03. Do your estimates of final expenditures on GDP cover all basic headings as defined in the ICP classification of expenditure and in line with SNA93? 04. Does the price survey framework provide national annual average prices for the basic headings defined in the ICP classification of expenditure that are consistent with the prices underlying the expenditures on the basic headings? 05. Do you classify institutional sectors in line with SNA93? 06. In general, are transactions valued at the actual prices agreed by the transactors—that is, at purchasers’ prices? 07. Are imputed rentals valued in accordance with the guidelines given in the ICP oper- ational material? 08. Are goods produced on own account for consumption by the household valued at basic prices? 09. Is income in kind valued at purchasers’ prices if the employer has purchased the goods or services and at producers’ prices if the goods or services have been produced by the enterprise itself? 10. Is the individual consumption expenditure of nonprofit institutions serving house- holds valued as the sum of the costs of production, including the consumption of fixed capital? 11. Is the production of individual services by government valued as the sum of the costs of production, including the consumption of fixed capital? 12. Are the purchases of goods and services by government that are passed on to house- holds without any further processing by government valued at purchasers’ prices? 13. Is the collective consumption expenditure by government valued as the sum of the costs of production, including the consumption of fixed capital? 14. Is gross fixed capital formation valued at purchasers’ prices? 15. Is own-account production of fixed capital assets valued at basic prices? (continued) National Accounts: Estimation, Compliance, and Exhaustiveness 245 BOX E.2 (Continued) ICP National Accounts Quality Assurance Questionnaire, ICP 2011 16. Is change in inventories valued as the change in the physical quantities at the begin- ning and end of the year using either the average of prices over the year or the prices prevailing at the middle of the year? 17. Are total imports and exports valued on an f.o.b. (free-on-board) basis? 18. Are transactions in foreign currency converted using the midpoint exchange rate prevailing in the market at the moment they take place? 19. Are the prices used in your national accounts national annual average prices, or, if they are not, are they adjusted to national annual average prices by accepted proce- dures? 20. Are transactions and flows recorded on an accrual basis? 21. Is work in progress recorded in the period it is produced? 22. Are government-related transactions recorded on an accrual basis, in particular taxes and subsidies on products and expenditures? 23. Does gross fixed capital formation consist of net acquisitions (acquisitions less dispos- als) of fixed assets? 24. Are valuables measured as acquisitions less disposals? 25. Are transaction prices measured net of discounts or rebates? 26. Do statistical procedures used by your office to adjust country final expenditure data to meet ICP requirements follow a detailed, case-by-case approach using specific sources that are most closely related to the estimated variables and pertinent to the reference period? 27. Do you maintain and disseminate detailed methodological notes about your national accounts compilation process? 28. Has your country compiled supply and use tables (SUTs)? 29. If yes, please indicate the reference year of the latest SUT, as well as the number of products (rows) in the SUT. 30. Please indicate the reference year of the most recent household expenditure survey. of a matrix in which types of nonexhaustive- The Global Office extended the Eurostat ness were columns and economic activities approach to include estimates made from the were rows. Definitions of the types of nonex- expenditure side and from the income side. The haustiveness, together with the compilation expenditure categories and the income transac- methods that could be employed to measure tions considered are listed in the second and them, are given in box E.3. Of the seven types third columns of table E.1. The types of nonex- of nonexhaustiveness identified, all but the haustiveness remained unchanged. The ques- last, N7, are defined in terms of producers. tionnaire consisted of five matrixes: three for The economic activities covered are listed in the production account covering gross output, the first column of table E.1. Economies were intermediate consumption, and gross value expected to complete the matrix by indicating added; one for the expenditure account; and in the relevant cells the adjustments needed one for the income account. In addition, the for the various types of nonexhaustiveness to Global Office prepared two simplified versions render the initial estimate for an economic of the questionnaire. The first was limited to activity exhaustive. gross value added by economic activity and 246 Purchasing Power Parities and the Real Size of World Economies BOX E.3 Types of Nonexhaustiveness Identified in GDP Exhaustiveness Questionnaire, ICP 2011 N1—Producer deliberately does not register (underground activity) in order to avoid tax and social security obligations or to avoid losing some social benefits. Typically, this cat- egory includes small producers with income above the threshold set for registration. Producers who do not register because they are engaged in illegal activities should be classi- fied as N2, while producers who deliberately misreport their activities should be classified as N6. The methods that can be used to estimate the adjustments required include labor inputs (from household-based labor force surveys), commodity flow, and supply and use tables. N2—Producer deliberately does not register (illegal activity) because the producer is involved in illegal activities such as prostitution, sale of stolen goods, drug dealing, smuggling, or illegal gambling. This category excludes any illegal production not reported by registered producers, which should be classified as N6, and illegal production by units not required to register, which should be classified as N3. The methods that can be used to estimate the adjustments are the quantity price method, unit per input or use, and expert judgment. N3—Producer not required to register because the producer does not have any market output or the producer’s market output is below a set threshold. Activities include produc- tion for own final consumption or own fixed capital formation, including construction of own dwellings and repairs to dwellings. Also includes market output of households that is below the level at which the producer is obliged to register as a business: paid domestic services, etc. No adjustment is necessary if the estimation method for a particular activity (or survey) implicitly takes into account the nonregistered activity. The methods that can be used to estimate adjustments are household expenditure surveys, building permits, commodity flow, administrative data, and time use surveys. N4—Legal producer not surveyed because, although registered, the producer is excluded from statistical surveys. For example, the producer may be newly registered and not yet record- ed in the business register because the register updating procedures are slow or inadequate. On the other hand, a producer may be recorded in the business register but excluded from survey frames because the classification data used in developing the survey frames (such as activity code, size of business, geographic location) may be wrong, or there may be a size cutoff that precludes the producer from being selected to participate in a particular survey. The methods that can be used to estimate adjustments are surveying the quality of the business register, reviewing the lags involved in update procedures and whether they change over time, or cross- checking the business register against other administrative sources covering businesses. N5—Registered entrepreneurs not surveyed. Registered entrepreneurs such as consul- tants, private writers, and freelance journalists may not be recorded in the business register, either deliberately or because the register updating sources do not include the details on such persons. Even if their details are recorded in the business register, they may be exclud- ed from statistical surveys either because of errors in the details recorded or because of the small size of their individual activities. The methods that can be used to estimate adjustments are conducting surveys of the quality of the register, cross-checking against other adminis- trative sources (such as income tax statements), or carrying out specialized surveys. (continued) National Accounts: Estimation, Compliance, and Exhaustiveness 247 BOX E.3 (Continued) Types of Nonexhaustiveness Identified in GDP Exhaustiveness Questionnaire, ICP 2011 N6—Misreporting by producers. Misreporting involves underreporting gross output (and therefore revenues) or overreporting intermediate consumption (and therefore the costs of production) in order to avoid paying income tax, other taxes such as value added tax, or social security contributions. The methods that can be used to estimate adjustments are consulting the data from tax audits, comparing average salaries and profits with similar businesses, comparing input-output ratios with those of similar businesses, conducting spe- cial surveys, or relying on expert judgment on the accounting relationships expected to be observed in such businesses. N7—Other statistical deficiencies. This category can be divided into two parts: data that are incomplete or cannot be directly collected from surveys and data that are incorrectly compiled during survey processing. The items that should be considered in determining the adjustments to be made include how nonresponse was taken into account, the extent to which wages and salaries were paid in kind, production for own final use by market producers, tips, valuation techniques, and adjustments for accruals. Table E.1 Economic Activities, Expenditure Categories, and Income Transactions Identified in Exhaustiveness Questionnaire, ICP 2011 Production approach Expenditure approach Income approach Gross value added (basic prices): Household final consumption: Compensation of employees A. Agriculture, hunting, and forestry 01. Food and nonalcoholic beverages Gross operating surplus and mixed B. Fishing 02. Alcoholic beverages, tobacco, and narcotics income C. Mining and quarrying 03. Clothing and footwear Taxes on production and imports D. Manufacturing 04. Housing, water, electricity, gas, and other Subsidies E. Electricity, gas, and water supply fuels Statistical discrepancy F. Construction 05. Furnishings, household equipment, and Gross domestic product routine household maintenance G. Wholesale and retail trade; repair of motor vehicles, motorcycles, and personal and 06. Health household goods 07. Transport H. Hotels and restaurants 08. Communication I. Transport, storage, and communications 09. Recreation and culture J. Financial intermediation 10. Education K. Real estate, renting, and business activities 11. Restaurants and hotels L. Public administration and defense; 12. Miscellaneous goods and services compulsory social security M. Education N. Health and social work O. Other community, social, and personal ser- vice activities P. Private households with employed persons Q. Extraterritorial organizations and bodies 248 Purchasing Power Parities and the Real Size of World Economies Table E.1 (Continued) Production approach Expenditure approach Income approach Taxes on products NPISH final consumption Compensation of employees Value added type taxes Government final consumption received from rest of world Other taxes on products Gross capital formation Compensation of employees paid to rest of world Subsidies on products Gross fixed capital formation Property income received from rest Statistical discrepancy Change in inventories of world Acquisition less disposals of valuables Property income paid to rest of Exports of goods and services world Goods Taxes on production and imports Services subsidies Imports of goods and services Goods Services Statistical discrepancy Gross domestic product Gross domestic product Gross national income Source: ICP, http://icp.worldbank.org/. expenditures by category and the second to of nonexhaustiveness as another. What was expenditures by category. important was that all omissions from the For each account, economies were asked to accounts be identified and included under one report the adjustments required to make the of the seven types of nonexhaustiveness and initial estimates for the economic activities, the that there be no double counting. Not all econo- expenditure categories, and the income transac- mies could quantify the adjustments to improve tions exhaustive. The adjustments were to be exhaustiveness. Economies that could not pro- given as a percentage of the initial estimate. vide an actual adjustment were asked to indi- Economies were advised that the distinction cate in the matrixes the estimates that were not between the seven types of nonexhaustiveness exhaustive (or considered to be not exhaustive) was not hard and fast because some adjustments and the reason they were not exhaustive (the could just as easily be classified under one type type of nonexhaustiveness). National Accounts: Estimation, Compliance, and Exhaustiveness 249 Appendix F Changes in Methodology between the 2005 and 2011 ICP Rounds Measuring the Real Size of the World Economy: The needed to link every economy in every region to Framework, Methodology, and Results of the a common numéraire currency. International Comparison Program (ICP) (World The choices do not make much difference Bank 2013) is a comprehensive review of the when the economies being compared have statistical and economic theory underlying the similar expenditure patterns and relative estimation of purchasing power parities (PPPs). prices. However, when computing PPPs across Even though the PPPs provided by the ICP rest economies such as Tajikistan and the United on a large body of statistical and economic States or Chad and the United States, the theory, many decisions based on expert judg- choices affect the results to a greater degree. ment have to be made.1 In fact, because the And, finally, some aggregates of GDP are diffi- decisions to be made require expertise ranging cult to compare, such as housing rents, gov- from survey design to price and index number ernment expenditures, and construction, theory, the system of national accounts, and thereby adding another dimension of decisions methods of aggregating PPPs to the gross domes- to be made. tic product (GDP), the ICP formed a Technical Lessons learned from previous ICP compari- Advisory Group (TAG) composed of interna- sons led to the development of several signifi- tionally known experts in each of these areas as cantly new and improved methods for ICP 2005. well as those who use the ICP results for Subsequent analysis of the 2005 data set the research, especially on poverty. stage for making additional improvements in Indeed, the outcome of each ICP comparison ICP 2011. is a function of the choices made, starting by The dilemma facing the ICP is that the con- determining what products to price and how to tinual improvement of methods is limiting the price them, choosing the index number formula comparison of PPPs over time. Although each to turn prices into basic heading PPPs, and then benchmark may be based on the best methods determining the multilateral formula needed to available at the time, their comparability may be aggregate the PPPs to GDP. Decisions about limited. The purpose of this appendix is to these different methods are made first at the describe the new methods implemented in ICP regional level, and then again on the process 2011, explain why they were chosen, and pro- vide a subjective assessment of the potential impact of the changes. The following sections go 1 This appendix is based on the paper “Understanding Changes in into more detail about the choices made for ICP Methodology between the 2005 and 2011 International Comparison Programs” by Paul McCarthy and Frederic A. Vogel, co-chairs of the ICP 2011 and how they affect comparability with Technical Advisory Group (see McCarthy and Vogel 2014). ICP 2005. 251 HOUSEHOLD CONSUMPTION: PRODUCT available but not representative. Economies in SELECTION AND IMPORTANT PRODUCTS the ICP regions attempted to use the representa- tive classification in 2005 but were unable to Statistical theory suggests that a master frame apply the notion of a representative price level should list every possible product purchased by consistently. As a result, the concept was not consumers and the annual expenditures associ- used in 2005 in the ICP regions or for estimating ated with each product for every economy. interregional linking factors. A random sample of products would then be TAG proposed a simpler method for ICP selected and the national annual average prices 2011. Economies other than those in the for them would be determined. The expenditure Eurostat-OECD and CIS regions were asked to on each product would be used to weight prod- classify all goods and services for household uct PPPs to basic heading PPPs. The reality, how- consumption as either important or less impor- ever, is that there is no such list. Although tant. Importance was defined by reference to statistical theory can be used to determine the the notional expenditure share of the product number of products to be priced, it is left to within a basic heading. The importance classifi- the regional and national coordinators using cation was a subjective process, as was the their expert judgment to select the actual assignment of representative status, but simpler. products out of the thousands of possibilities. If it was thought that the expenditure share The ICP’s Measuring the Real Size of the World would probably be large, the product was classi- Economy (World Bank 2013) provides guidelines fied as important; if small, it was classified as on the number of products to be priced. For less important. example, it recommends that six products be The procedure to determine the products to priced for the rice basic heading but about be priced for household consumption in 2005 70–100 for the garment basic heading. The rea- differed from that for 2011: son is that rice is a relatively homogeneous product (although it is necessary to specify dif- • In 2005 each regional coordinator, in collabo- ferent varieties to be priced), whereas garments ration with the national coordinators, used are much more heterogeneous. structured product descriptions (SPDs) fur- The comparability of the products being priced nished by the Global Office to create product is an essential principle underlying the estima- specifications. Each region did so indepen- tion of PPPs. A dilemma facing the ICP is that, dently of other regions. although a product may be available in several • After data collection and several iterations of economies, it may be a significant part of con- data validation were completed, all regions sumption in only a few of them. Because there submitted their final set of priced products. are no data on expenditures for individual products, the relative prices or product PPPs are • The Global Office harmonized definitions and averaged with equal weights to obtain the basic collapsed the combined lists from the regions heading PPP. To overcome this problem, two into a list of about 1,000 products called the regions—the Eurostat–Organisation for Economic Ring list. This list was the basis for a separate Co-operation and Development (OECD) region data collection by a subset of economies in and Commonwealth of Independent States each region—the Ring economies—that was (CIS) region—have adopted the concept of rep- then used to link PPPs across regions. resentativity to induce a form of weighting. A • The resulting price levels from the Ring data representative product is one that is purchased collection were not consistent with those frequently by households and has a price level for the corresponding economies within each consistent with all products in the basic heading. of the regions. For example, some Ring econ- Because representative products are those omies priced products that were not repre- most frequently purchased, it is likely that they sentative of their consumption patterns, but have lower price levels in economies in which those products received equal weight in the they are representative compared with the price computation of linking factors. To the degree levels in the economies in which they are this took place, it points to an overestimate of 252 Purchasing Power Parities and the Real Size of World Economies price levels and an underestimate of real would be difficult to quantify because one expenditures in the Africa and the Asia would assume that the regional and national and the Pacific regions compared with the coordinators, because of their previous experi- other regions. ence, would be able to better validate prices for the 2011 comparison. Subsequent analysis of the Ring list, prices, PPPs, and linking factors produced several les- sons learned. First, the selected Ring economies did not always turn out to be representative of HOUSING RENTS the other economies in the region. Analysis Housing rents have proven to be one of the most showed that between-economy variability was problematic components of each ICP compari- greater than the variability in relative prices son, in part because the values are estimated so within basic headings. Based on this analysis, poorly in many economies’ national accounts TAG recommended the following steps: and in part because the prices provided for the • Develop a set of global core products that ICP are often not consistent with the national would be priced by all economies for linking accounts values. It is difficult to estimate PPPs purposes. The final 2005 Ring list became the for housing rents because of the varying mix of starting point for determining the set of rental versus owner-occupied housing. PPPs for global core products for 2011. dwellings were computed in three different ways in 2005. Rental rates were used where • Include the global core products in the there was a large rental market. Where the regional lists as well. The starting point in rental market was not large enough, PPPs were each region to develop the list for 2011 was computed indirectly using the quantity approach. the 2005 regional product list and the set of Because the rental markets in the Africa and the global core products. Asia and the Pacific regions were not large • Classify products as important or less impor- enough to use market rents to estimate PPPs, tant. Although economies were expected to the regions attempted to use the quantity be able to price a large number of global core method. However, this approach produced products, not all would have the same price implausible results, and so PPPs were imputed levels or relative expenditures. Products com- for those regions using the reference volume mon in some economies may be more diffi- method. Even though there were insufficient cult to find in other economies, with the data to use the quantity method within those likelihood of higher prices. Therefore, the regions, there was enough to compute between- importance classification is needed to prevent region linking factors. an upward bias in the price levels used to In view of the importance of housing PPPs, estimate the between-region PPPs. it was agreed by TAG and the regions to place greater emphasis on obtaining rental data. • Aggregate product PPPs to the basic heading TAG recommended that all economies provide level using the weighted country product two sets of data. First, all economies were to dummy (CPD-W) method, with a weight of 3 redouble efforts to provide rental prices. for important products and a weight of 1 for Second, all economies were to provide data less important products. on quantities (ideally, square meters of dwell- Because the representative classification ings but at least numbers of dwellings, classi- was used only in the Eurostat-OECD and CIS fied by type) and quality (indoor plumbing, regions in ICP 2005, the likely result was an etc.) of the entire housing stock even where upward bias in PPPs (that is, smaller real expen- there was a large rental market. Global speci- ditures) in the remaining ICP regions. If the fications were prepared to collect data on use of the importance classification were suc- rents and quantities, which meant that the cessful in 2011, the result would be lower rela- within-region PPPs were based on the same tive prices and larger real expenditures in the data used to compute the between-region remaining regions. These price level differences PPPs or linking factors. Changes in Methodology between the 2005 and 2011 ICP Rounds 253 The dilemma was that economies without CIS, and Western Asia regions because differ- rental markets also had difficulty providing con- ences in labor productivity within each of those sistent and comparable quantity and quality regions were considered to be relatively small. data. For that reason, the Asia and the Pacific However, productivity adjustments were made region imputed PPPs for dwellings in the same to all regions when the interregional linking way it did in 2005, relying on the reference vol- factors were estimated, thereby improving ume method. Rental data were used to estimate the quality of the resulting PPPs and real dwelling PPPs in the Africa, Latin America, expenditures. Caribbean, and Western Asia regions; quantity data in the CIS region; and a combination of both in the Eurostat-OECD region. Regions CONSTRUCTION were linked using a combination of rental and quantity data for the subset of economies able to Prior to ICP 2005, PPPs for construction were provide them. based on an output (model-based) approach. Although the PPPs for dwellings are not The pricing methods for construction were optimal, the results between 2005 and 2011 are changed in ICP 2005, in part for cost reasons mostly comparable. (pricing models required specialists such as quantity surveyors) and in part for method- ological reasons (it had proven to be virtually GOVERNMENT COMPENSATION impossible to specify a small number of mod- els that were relevant to all economies in a For ICP 2005, the Global Office prepared a region). The method adopted in ICP 2005 was global list of over 40 government occupations known as the basket of construction compo- for which economies provided annual salaries. nents (BOCC) approach. Government salaries were adjusted for produc- The BOCC approach involved collecting tivity in the Africa, Asia and the Pacific, and prices for a range of major construction compo- Western Asia regions because of the huge differ- nents and basic inputs that were common ences in the salaries paid in the economies in across economies. The term construction compo- those regions. (Not adjusting for productivity nents was used to describe specific physical differences would have resulted in some implau- outputs that were produced as intermediate sibly large estimates of the government final steps in construction projects. A key element consumption expenditure in lower-income in this process was that the overall price esti- economies.) The annual salaries from the same mated for each composite component related list of occupations were used to compute to an installed component, including the costs between-region linking factors. However, they of materials, labor, and equipment—that is, the were not adjusted for productivity. price was more related to an output price than For ICP 2011, the list of global occupations to an input price. remained about the same as those used in 2005. The objective of the BOCC approach was to A major change was that the Eurostat-OECD provide simple and affordable price comparisons region was now using output indicators to for construction. An important goal was to estimate real expenditures on education, develop a technique that would enable con- whereas the other regions were continuing to struction to be priced in major locations within use input indicators (salaries). Therefore, it was each economy. Such a technique would result necessary to develop some special procedures to in comparable prices for similar components link the Eurostat-OECD region to the other across economies that had different labor- regions for the education PPPs. to-equipment mixes because of their different Productivity adjustments were made to the levels of economic development. real expenditure estimates for government in In practice, the BOCC method did not prove the Africa, Asia and the Pacific, Latin America, to be satisfactory. The main problems were the and Caribbean regions. No productivity adjust- difficulty in pricing the composite components ments were applied within the Eurostat-OECD, (they required construction specialists) and 254 Purchasing Power Parities and the Real Size of World Economies overlaps between the composite and the basic • Information on markups (profits, value materials that also had to be priced to ensure added tax, project overheads, etc.) would be adequate coverage of products. collected from construction experts, thereby The approach initially proposed for ICP 2011 enabling the PPPs for each basic heading was based on pricing inputs (basic materials and to be adjusted to account for markups. equipment hire) and using them to approximate Ideally, markups would be specific to each an output price on the basis of the relationships economy, but it might be necessary in some between the outputs and inputs for each econ- cases to estimate markups for a group of omy, as estimated in each economy’s input- similar economies. output tables. However, investigations showed Later, in October 2011, TAG discussed that up-to-date input-output tables were not whether labor productivity adjustments should available in enough economies for the approach be applied. It concluded that there was no need to be viable. to adjust for labor productivity differences In April 2011, TAG endorsed the proposal to between economies because each economy had use an input-price approach and recommended to provide weights for materials, labor, and the following: equipment hire for each basic heading. However, • Basic heading PPPs for construction would be an assumption underlying not making this based on a simple combination of three adjustment was that total factor productivity groups of inputs (materials, labor, and equip- (TFP) was equal across economies. ment) rather than allocating each input to In May 2013, TAG examined the construc- model projects, or weighting each input in tion data collected. It found that the data qual- any other way. ity was poor in a number of areas, particularly that related to the relevance indicators (the • An unweighted country product dummy types of materials being used in different (CPD) regression would be used to estimate types of construction) and the overheads for PPPs within each of the three product markups and professional fees. In many cases, groups for each basic heading: residential economies did not provide any estimates of buildings, nonresidential buildings, and civil these markups. As a result, TAG recommended engineering works. Each basic heading the following: would then have three PPPs—one for mate- rials, one for labor, and one for equipment. • A single set of relevance indicators should be These would be combined using their respec- used within each region rather than those tive weights. provided by individual economies. Each region would use a construction expert to • Basic headings PPPs would be computed as provide advice on the relevance of the vari- weighted averages of the PPPs for materials, ous components to the different types of con- labor, and equipment. The weights would be struction activity. centrally determined for five clusters of econ- omies in each region (although economies • Resource weights provided by the Global could provide their own specific weights, if Office should be used to average PPPs for available, rather than having a cluster-based materials, labor, and equipment for econo- weight applied). This was later changed to mies not able to provide the data. three clusters (high, middle, and low income). • Construction prices should not be adjusted • Prices would be collected for 38 material for markups and professional fees because inputs and seven categories of labor, and hire of the poor quality of the data collected on rates would be collected for five types of these aspects. equipment. • The prices for equipment hire should be split • Economies would be asked to confirm which into those including an operator and those resources were relevant to each basic excluding an operator and treated as separate heading. product specifications. Changes in Methodology between the 2005 and 2011 ICP Rounds 255 Finally, in September 2013 TAG reconsidered The basic methodology used in ICP 2005 was as its earlier recommendation that no productivity follows: adjustment be applied to construction labor, • The CPD method was used in the ICP which implied that the TFP in construction regions coordinated by the Global Office and would be identical across economies. TAG con- the Jevons-GEKS* (Gini-Éltetö-Köves-Szulc) sidered the possibilities for specific adjustments method in the Eurostat-OECD and CIS regions for labor productivity or for TFP, and the even- to compute basic heading PPPs. The Jevons- tual consensus was that no adjustment should GEKS* method used the representative clas- be applied for labor productivity but that an sification; the CPD method did not. adjustment for TFP should be considered. Thus a set of TFP adjustment factors was produced, • The GEKS method was used in the final but it became clear that they added noise to the stage of estimation to ensure that the PPPs construction price estimates rather than were transitive and base country–invariant. improving them. As a result, TAG reaffirmed its In 2005 Africa used the Iklé method, earlier decision that no adjustments should which produces additive results but also is be applied to construction prices for either subject to the Gerschenkron effect. Both labor productivity or TFP differences across approaches provide results that are transi- economies. tive and base country–invariant. The base Fully implementing TAG’s recommendations country–invariant property ensures that the regarding adjustments to prices for construction PPPs between any two economies are the markups proved problematic because of the poor same no matter which economy is the base. quality (or nonprovision) of data by the partici- The transitive property simply means that pating economies. Data were available for some the price level—for example, of the United economies, but they had not been properly vali- Kingdom relative to the United States—is dated because of the regional coordinators’ views the same whether it is calculated directly or that an insufficient number of economies had through any possible chain of economies provided data on markups, and there was a large such as the United States to Nepal to degree of variability in the data that were avail- Nigeria, etc. If one imposes the transitive able. At this late stage, it was not possible to ask property, the PPPs between any two econo- economies to collect new markup data for 2011. mies can change if the mix of the remaining Because of problems in 2005 pricing the com- economies changes. When a region is homo- posite components, the construction PPPs were geneous, the direct and indirect PPPs remain essentially based on the basic components, which similar. However, the process induces more meant that the resulting PPPs mostly reflected an variability when indirect PPPs enter from input approach. The basic components priced in economies with widely different price and 2011 were about the same as those priced in expenditure structures. This effect has 2005. The net result was that neither the 2005 implications for the linking methods dis- PPPs nor the 2011 PPPs were based on output cussed in the next section. prices. Although this was not the desired method, • Housing rent PPPs in the Africa and the Asia the construction results for 2005 and 2011 were and the Pacific regions were imputed, with considered to be broadly comparable. the other regions using either rental prices or quantities adjusted for quality. Government salaries were adjusted for productivity in the ESTIMATING WITHIN-REGION PPPS Africa, Asia and the Pacific, and Western Asia regions. Although these steps improved the Chapters 4 and 5 of Measuring the Real Size of the results within the Africa and Asia and the World Economy (World Bank 2013) describe the Pacific regions, they affected their compara- different properties of the various indexes that can bility with economies in other regions. This be used to compute basic heading PPPs and especially applied to government compensa- aggregate them to GDP. These chapters are also tion because the between-region PPPs were the basis for the choices made for ICP 2011. not adjusted for productivity. 256 Purchasing Power Parities and the Real Size of World Economies • Prices for each product were to represent provided prices for a set of global core products national annual average prices. Where this instead of 18 economies providing prices for a was not possible, economies were to use the separate Ring list. However, a significant change consumer price index and other information was made in how the linking took place for to calibrate the prices to national annual higher aggregates up to GDP. The linking method averages. There was much debate about at the basic heading level was as follows: China, which submitted prices that mostly • Core product prices provided by all econo- represented urban areas and so were poten- mies (18 Ring economies in 2005) were tially overstating national average prices. deflated to a regional currency using within- Experts such as Deaton and Heston (2008) region basic heading PPPs. estimated that adjustments based on the dis- tribution of consumption between urban and • The result was five sets of regional prices rural areas would raise the estimates of the treated as super economies. The CPD-W real expenditure on Chinese GDP by about (CPD in 2005) regression over these five sets 10 percent in 2005. of regional prices provided between-region basic heading PPPs. These between-region The methodology for ICP 2011, adhering to PPPs, when multiplied by within-region basic the TAG recommendations, was the following: heading PPPs, were converted to a global cur- • The CPD-W for household consumption was rency. The same regional scalar, say for rice, used in ICP regions, with weights of 3:1 for times each economy’s within-region PPP con- important versus less important products. verted it to a global PPP. The Jevons-GEKS* method used in the • This method preserved within-region fixity, Eurostat-OECD and CIS regions in 2005 which means the relative rankings between remained in effect. economies in the same region remained the • The GEKS method was used in the final stage same after linking. of estimation to ensure that the PPPs were • In 2005 this computation step included only transitive and base country–invariant. the 18 Ring economies and the Ring prices, The issue now is whether the relative rank- whereas in 2011 the between-region PPPs ings within each region are comparable between were based on core prices provided by every 2011 and 2005. The within-region 2011 results economy. Because these core prices were also will not be exactly comparable with those for included in the estimation of within-region 2005 if the methods used to estimate housing PPPs, the between-region results were more rents and the application of productivity adjust- consistent with the within-region results. ments differ between the two periods. The set of • The CIS region in both 2005 and 2011 was economies changed between some regions—for linked to the Eurostat-OECD region using the example, Chile became part of the OECD, major Russian Federation as a bridge economy. Two economies such as Argentina did not take part, new 2011 regions, the Caribbean and Pacific and others such as the Islamic Republic of Iran Islands, were linked similarly using the bridge were treated separately. In other words, changes approach. The Caribbean economies were in the relative rankings of economies within linked through Latin America, and the Pacific regions can be the result of changes in method- Islands were linked through Australia, Fiji, ology or because of the different composition of and New Zealand as bridge economies. economies within a region. Between-region linking factors for 2011 were based on all economies instead of a subset of subjectively selected economies. Thus the fac- LINKING THE REGIONS tors were more statistically robust. The final The methodology to link the regions remained computational step was to link regions at the about the same between 2005 and 2011 at the higher-level aggregates and GDP. In 2005 the basic heading level except that all economies between-region PPPs (linking factors) were Changes in Methodology between the 2005 and 2011 ICP Rounds 257 aggregated to GDP using the GEKS method. In a SUMMARY separate computation, within-region PPPs were aggregated to GDP as described in the previous The ICP includes economies ranging from city- section. Again, the aggregated between-region states and small islands to large and diverse PPPs times the aggregated within-region PPPs economies such as Brazil, China, India, and calibrated the results to the global currency.2 Russia. Like all statistical endeavors, PPPs are After considering several alternatives, TAG statistical estimates that fall within some margin proposed that a procedure called the country of error of the unknown true values. The ICP aggregation with redistribution (CAR) be used: 2005 final report suggested using caution when comparing economies by the size of their GDP • A global aggregation that includes all or expenditures per capita because there could 177 economies and 155 basic headings in a be errors in the calculation of GDP and popula- GEKS aggregation would provide PPPs cali- tion sizes in addition to the statistical variability brated to a global currency. To preserve inherent in the PPPs (World Bank 2008). The within-region fixity, real expenditures would report indicated that differences in GDP of less be summed to regional totals, which would than 5 percent lie within the margin of error of then be distributed within each region accord- the PPP estimation. Deaton (2013) has sug- ing to the distribution from the within-region gested a method to measure statistical variability computations. These results would be base in the estimation of PPPs that stems from the country–invariant and transitive, and they choice of products, the range of PPP product would preserve fixity. prices, and differences in basic heading expendi- • The global PPP between any two economies tures. He shows that standard errors of PPPs would be the geometric mean of the direct become larger for economies with different comparison and the n – 2 indirect compari- price and expenditure structures. Approximations sons with every other economy. The range of revealed that the standard errors of Indian or the direct and indirect comparisons would be Chinese prices to U.S. 2005 prices were between small for economies with similar price and 10 and 15 percent. expenditure structures, but could become The range suggested by the standard errors large where economies differed significantly. reflects the variability resulting from the choice of methods. This analysis has pointed out that a • Simulations show that real expenditures possible adjustment for urban/rural prices in were increased in Asia and the Pacific by China would have raised its real expenditures 9 percent and 6 percent, respectively, for by about 10 percent in 2005. The CAR proce- 2005 and 2011. This simulation did not dure would have raised real expenditures for all include the impact of using global core prices Asia and the Pacific economies in 2005 by about from all economies versus Ring prices from 9 percent compared with the other regions. 18 economies. Therefore, adopting the CAR approach for 2011 rather than the Ring approach would have raised the real expenditures of all Asia and the Pacific economies in 2011 compared with those 2 of the Eurostat-OECD economies. Table H.2 in Chapter 6 in Measuring the Real Size of the World Economy (World Bank 2013) reviews the properties of this method, which reveals that the appendix H presents the analytical 2005 results computations are dependent on the choice of base economy. calculated using the CAR procedure. 258 Purchasing Power Parities and the Real Size of World Economies Appendix G Reference PPPs Used in ICP 2011 The gross domestic product (GDP) expenditures of the PPP for transport services and the PPP for used for the 2011 round of the International restaurants and hotels where the weights are Comparison Program (ICP) were classified the expenditures on the constituent basic head- into 155 basic headings. However, prices for 42 ings. Neutral price-based reference PPPs are basic headings were not collected. For some of based on the PPPs of a large group of basic head- these basic headings it was too difficult to spec- ings. For example, one could use the PPP for the ify comparable products that could be priced individual consumption expenditure by house- across economies; for others it was too expen- holds as the reference PPP for FISIM and inter- sive and time-consuming to collect prices. The mediate consumption. The objective is to ensure basic headings for which prices were not col- that the use of a reference PPP does not change lected are listed in table G.1. Some obvious the PPP of the larger group to which the basic examples are narcotics, prostitution, financial heading with missing PPPs belongs. intermediation services indirectly measured The reference PPPs used for ICP 2011 and the (FISIM), gross operating surplus, inventories, basic headings to which they apply are detailed exports, and imports. in table G.1. They were either price-based Without prices for those basic headings, reference PPPs or exchange rate–based refer- aggregation at higher aggregate levels is clearly ence PPPs. A volume-based reference PPP was not possible because it is necessary to have a employed in the Asia and the Pacific comparison complete matrix of basic heading PPPs. For that for the basic heading actual and imputed rentals. reason, reference PPPs were used in ICP 2011 as Exchange rate–based reference PPPs were used proxies for the basic headings for which no for four basic headings: purchases by resident prices were collected. This is standard practice in households in the rest of the world, purchases all ICP comparisons. by nonresident households in the economic ter- Reference PPPs fall into three categories: ritory, exports of goods and services, and imports price-based, volume-based, and exchange rate– of goods and services. based. Two types of price-based reference PPPs In calculating reference PPPs, with the can be distinguished: those that are specific and exception of narcotics, weighted Gini-Éltetö- those that are neutral. Specific price-based refer- Köves-Szulc (GEKS) indexes were used. The ence PPPs are based on the PPPs of basic head- weights were the expenditures on the basic ings considered similar to the basic headings for headings whose PPPs were being averaged. which no prices were collected. An example of Basic headings with reference PPPs were not a specific price-based reference PPP is that for used to generate reference PPPs for other basic package holidays, which is the weighted average headings for which no prices were collected. 259 Table G.1 Reference PPPs, ICP 2011 Basic heading Reference PPP Individual consumption expenditure by households and nonprofit institutions serving households (NPISHs) 110231.1 Narcotics Unweighted geometric average of the PPP for tobacco (110221.1) and the PPP for pharmaceutical products (110611.1) 110442.1 Miscellaneous dwelling services Weighted Gini-Éltetö-Köves-Szulc (GEKS) of the PPP for maintenance and repair of the dwelling (110431.1) and the PPP for water supply (110441.1) 110631.1 Hospital services PPP for outpatient health services (110620) 110714.1 Animal-drawn vehicles PPP for bicycles (110713.1) 110734.1 Passenger transport by sea PPP for transport services (110730), excluding basic headings (BHs) with reference PPPs 110735.1 Combined passenger transport Weighted GEKS of the PPP for passenger transport by railway (110731.1) and the PPP for passenger transport by road (110732.1) 110736.1 Other transport services Weighted GEKS of the PPP for passenger transport by railway (110731.1) and the PPP for passenger transport by road (110732.1) 110923.1 Maintenance of other major durables Weighted GEKS of the PPP for maintenance and repair of personal transport equipment (110723.1) and the PPP for repair of audiovisual, photographic, and information processing equipment (110915.1) 110943.1 Games of chance PPP for recreational and sporting services (110941.1) 110961.1 Package holidays Weighted GEKS of the PPP for transport services (110730) and the PPP for restaurants and hotels (111100), excluding BHs with reference PPPs 111221.1 Prostitution PPP for individual consumption expenditure by households (110000), excluding health and education BHs and BHs with reference PPPs 111241.1 Social protection PPP for collective consumption expenditure by government (140000), excluding BHs with reference PPPs 111251.1 Insurance PPP for individual consumption expenditure by households (110000), excluding health and education BHs and BHs with reference PPPs 111261.1 Financial intermediation services PPP for individual consumption expenditure by households (110000), excluding indirectly measured (FISIM) health and education BHs and BHs with reference PPPs 111311.1 Purchases by resident households in Exchange rate the rest of the world 111311.2 Purchases by nonresident households Exchange rate in the economic territory 120111.1 NPISHs PPP for individual consumption expenditure by government (130000), excluding BHs with reference PPPs Individual and collective consumption expenditure by government 130111.1 Housing PPP for actual and imputed rentals (110411.1) 130212.4 Hospital services PPP for production of health services by government (130220), excluding BHs with reference PPPs 130222.1 Intermediate consumption (health) PPP for individual consumption expenditure by households (110000), excluding health and education BHs and BHs with reference PPPs 130223.1 Gross operating surplus (health) PPP for gross fixed capital formation (150000), excluding BHs with reference PPPs 130224.1 Net taxes on production (health) PPP for production of health services by government (130220), excluding BHs with reference PPPs 130225.1 Receipts from sales (health) PPP for production of health services by government (130220), excluding BHs with reference PPPs 130311.1 Recreation and culture Weighted GEKS of the PPP for recreational and sporting services (110941.1) and the PPP for cultural services (110942.1) 260 Purchasing Power Parities and the Real Size of World Economies Table G.1 (Continued) Basic heading Reference PPP 130411.1 Education benefits and PPP for production of education services by government (130420), excluding BHs reimbursements with reference PPPs 130422.1 Intermediate consumption (education) PPP for individual consumption expenditures by households (110000), excluding health and education BHs and BHs with reference PPPs 130423.1 Gross operating surplus (education) PPP for gross fixed capital formation (150000), excluding BHs with reference PPPs 130424.1 Net taxes on production (education) PPP for production of education services by government (130420), excluding BHs with reference PPPs 130425.1 Receipt from sales (education) PPP for production of education services by government (130420), excluding BHs with reference PPPs 130511.1 Social protection PPP for collective consumption expenditure by government (140000), excluding BHs with reference PPPs 140112.1 Intermediate consumption (collective PPP for individual consumption expenditures by households (110000), excluding services) health and education BHs and BHs with reference PPPs 140113.1 Gross operating surplus (collective PPP for gross fixed capital formation (150000), excluding BHs with reference PPPs services) 140114.1 Net taxes on production (collective PPP for collective consumption expenditure by government (140000), excluding services) BHs with reference PPPs 140115.1 Receipts from sales (collective PPP for collective consumption expenditure by government (140000), excluding services) BHs with reference PPPs Gross fixed capital formation 150121.2 Other road transport PPP for motor vehicles, trailers, and semitrailers (150121.1) 150122.1 Other transport equipment PPP for machinery and equipment (150100), excluding BHs with reference PPPs Other expenditures 160111.1 Opening value of inventories Weighted GEKS of the PPPs of BHs classified as containing predominantly goods, excluding BHs with reference PPPs 160111.2 Closing value of inventories Weighted GEKS of the PPPs of BHs classified as containing predominantly goods, excluding BHs with reference PPPs 160211.1 Acquisitions of valuables Exchange rate 160211.2 Disposals of valuables Exchange rate 170111.1 Exports of goods and services Exchange rate 170111.2 Imports of goods and services Exchange rate Source: ICP, http://icp.worldbank.org/. Reference PPPs Used in ICP 2011 261 Appendix H Updated ICP 2005 Results This appendix provides updated results for the • Column (08): GDP per capita index based on 2005 International Comparison Program (ICP). PPPs with the United States equal to 100 Table H.1 presents revised ICP 2005 results • Column (09): GDP per capita index based on using updated 2005 expenditure, population, exchange rates with the United States equal and exchange rate data. Subsequently, all related to 100 indicators were revised. In addition, purchasing • Column (10): Share of PPP-based world GDP power parities (PPPs) for the Eurostat— • Column (11): Share of exchange rate–based Organisation for Economic Co-operation and world GDP Development (OECD) comparison were updated • Column (12): Share of world population as per their published revised 2005 results. Table • Column (13): PPP for GDP with the U.S. dol- H.2 presents the revised ICP 2005 results, lar equal to 1.000 calculated using the ICP 2011 aggregation • Column (14): Exchange rate with the procedure, the country aggregation with redis- U.S. dollar equal to 1.000 tribution (CAR). • Column (15): Resident population In tables H.1 and H.2, the updated ICP 2005 • Column (16): Nominal GDP in national cur- summary results are broken down into the fol- rency unit lowing indicators: Column (01) shows the real expenditures of • Column (01): Gross domestic product (GDP) economies and regions on GDP in U.S. dollars. based on PPPs in U.S. dollars The expenditures reflect only volume differ- • Column (02): GDP based on exchange rates ences between economies and regions. They in U.S. dollars were obtained by dividing the nominal expendi- • Column (03): GDP per capita based on PPPs tures for GDP in column (16) by the PPPs for in U.S. dollars GDP in column (13). The GDP per capita in • Column (04): GDP per capita based on column (03), the GDP per capita indexes in col- exchange rates in U.S. dollars umns (06) and (08), and the shares of world • Column (05): Price level index for GDP with GDP in column (10) are all based on the real the world equal to 100 expenditures in column (01). • Column (06): GDP per capita index based on Column (02) shows the nominal expenditures PPPs with the world equal to 100 of economies and regions on GDP in U.S. dollars. • Column (07): GDP per capita index based The expenditures reflect both price differences on exchange rates with the world equal and volume differences between economies and to 100 regions (see box 2.1 in chapter 2). They were 263 derived by dividing the nominal expenditures on Users are reminded that, as explained in GDP in column (16) by the exchange rates in chapter 1, exchange rate–converted GDPs are column (14). The GDP per capita in column (04), not reliable measures of either the size of the GDP per capita indexes in columns (07) and economies or the material well-being of their (09), and the shares of world GDP in column (11) populations. They are included in the sum- are all based on the nominal expenditures in mary table and in the supplementary tables for column (02). reference only. Table H.1 Revised ICP 2005 Summary Results: GDP Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) AFRICA Angola 60.0 30.6 3,627 1,851 63.6 39.3 25.0 8.2 4.2 0.1 0.1 0.3 44.488 87.159 16.54 2,669.6 Benin 10.5 4.4 1,279 533 51.9 13.9 7.2 2.9 1.2 0.0 0.0 0.1 219.585 527.468 8.18 2,298.7 Botswana 20.5 9.7 10,927 5,176 59.0 118.4 69.8 24.7 11.7 0.0 0.0 0.0 2.421 5.110 1.88 49.6 Burkina Faso 14.4 5.5 1,072 407 47.3 11.6 5.5 2.4 0.9 0.0 0.0 0.2 200.227 527.468 13.42 2,881.4 Burundic … … … … 39.5 … … … … … … 0.1 342.964 1,081.577 7.77 … Cameroon 35.0 16.6 1,929 918 59.3 20.9 12.4 4.4 2.1 0.1 0.0 0.3 251.015 527.468 18.14 8,781.0 Cape Verde 1.4 1.1 2,912 2,278 97.4 31.5 30.7 6.6 5.1 0.0 0.0 0.0 69.360 88.670 0.48 96.7 Central African Republic 2.7 1.4 682 341 62.3 7.4 4.6 1.5 0.8 0.0 0.0 0.1 263.740 527.468 3.96 712.1 Chad 16.8 6.6 1,680 662 49.1 18.2 8.9 3.8 1.5 0.0 0.0 0.2 208.000 527.468 10.01 3,499.3 Comoros 0.6 0.4 1,076 615 71.2 11.7 8.3 2.4 1.4 0.0 0.0 0.0 226.195 395.601 0.60 146.2 Congo, Dem. Rep. 22.9 10.3 424 191 56.3 4.6 2.6 1.0 0.4 0.0 0.0 0.9 214.267 473.908 54.03 4,903.0 Congo, Rep. 12.0 6.1 3,395 1,730 63.5 36.8 23.3 7.7 3.9 0.0 0.0 0.1 268.760 527.468 3.54 3,232.7 Côte d’Ivoire 31.3 17.1 1,802 982 67.9 19.5 13.3 4.1 2.2 0.1 0.0 0.3 287.485 527.468 17.39 9,011.8 Djibouti 1.5 0.7 1,916 913 59.3 20.7 12.3 4.3 2.1 0.0 0.0 0.0 84.685 177.721 0.78 126.0 d Egypt, Arab Rep. 351.6 98.2 5,023 1,402 34.8 54.4 18.9 11.4 3.2 0.6 0.2 1.1 1.616 5.789 70.00 568.2 Equatorial Guinea 13.2 7.2 21,904 11,936 67.9 237.3 161.0 49.5 27.0 0.0 0.0 0.0 287.423 527.468 0.60 3,800.5 Ethiopia 42.5 11.1 559 145 32.4 6.1 2.0 1.3 0.3 0.1 0.0 1.2 2.254 8.666 76.17 95.9 Gabon 19.5 9.5 14,116 6,857 60.5 152.9 92.5 31.9 15.5 0.0 0.0 0.0 256.230 527.468 1.38 4,989.3 Gambia, The 2.4 0.6 1,642 434 33.0 17.8 5.9 3.7 1.0 0.0 0.0 0.0 7.560 28.575 1.44 17.8 e Ghana 41.9 17.2 1,961 805 51.1 21.2 10.9 4.4 1.8 0.1 0.0 0.3 0.372 0.906 21.38 15.6 Guinea 8.8 2.9 917 307 41.7 9.9 4.1 2.1 0.7 0.0 0.0 0.2 1,219.348 3,644.333 9.58 10,703.7 Guinea-Bissau 1.9 0.8 1,344 554 51.3 14.6 7.5 3.0 1.3 0.0 0.0 0.0 217.300 527.468 1.42 415.3 Kenya 48.0 18.7 1,340 524 48.7 14.5 7.1 3.0 1.2 0.1 0.0 0.6 29.524 75.554 35.79 1,415.8 Lesotho 2.5 1.4 1,295 711 68.4 14.0 9.6 2.9 1.6 0.0 0.0 0.0 3.490 6.359 1.93 8.7 Liberia 1.2 0.6 378 186 61.3 4.1 2.5 0.9 0.4 0.0 0.0 0.1 0.493 1.000 3.27 0.6 Madagascar 15.7 5.1 857 278 40.4 9.3 3.8 1.9 0.6 0.0 0.0 0.3 649.568 2,003.026 18.29 10,186.7 Malawi 10.1 3.4 779 259 41.5 8.4 3.5 1.8 0.6 0.0 0.0 0.2 39.457 118.420 12.92 397.1 Mali 20.9 9.5 1,752 798 56.7 19.0 10.8 4.0 1.8 0.0 0.0 0.2 240.092 527.468 11.94 5,024.2 Mauritania 5.9 2.2 1,865 694 46.4 20.2 9.4 4.2 1.6 0.0 0.0 0.1 98.840 265.528 3.15 580.0 264 Purchasing Power Parities and the Real Size of World Economies Table H.1 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) Mauritius 12.5 6.2 10,014 4,983 62.0 108.5 67.2 22.6 11.3 0.0 0.0 0.0 14.677 29.496 1.24 182.7 Morocco 107.1 59.0 3,556 1,957 68.5 38.5 26.4 8.0 4.4 0.2 0.1 0.5 4.878 8.865 30.13 522.6 Mozambiquee 13.9 6.6 662 313 58.9 7.2 4.2 1.5 0.7 0.0 0.0 0.3 10.909 23.061 21.01 151.7 Namibia 10.8 7.3 5,341 3,582 83.5 57.9 48.3 12.1 8.1 0.0 0.0 0.0 4.265 6.359 2.03 46.2 Niger 7.8 3.4 595 256 53.5 6.4 3.4 1.3 0.6 0.0 0.0 0.2 226.661 527.468 13.18 1,777.0 Nigeria 247.3 113.5 1,772 813 57.1 19.2 11.0 4.0 1.8 0.4 0.2 2.3 60.232 131.274 139.59 14,894.5 Rwanda 7.7 2.6 820 274 41.6 8.9 3.7 1.9 0.6 0.0 0.0 0.2 186.182 557.823 9.43 1,439.8 São Tomé and Príncipe 0.2 0.1 1,514 797 65.6 16.4 10.8 3.4 1.8 0.0 0.0 0.0 5,558.089 10,557.970 0.15 1,301.3 Senegal 18.3 8.7 1,619 773 59.4 17.5 10.4 3.7 1.7 0.0 0.0 0.2 251.668 527.468 11.27 4,593.1 Sierra Leone 4.4 1.7 867 322 46.3 9.4 4.3 2.0 0.7 0.0 0.0 0.1 1,074.122 2,889.588 5.12 4,769.8 South Africa 405.8 247.1 8,517 5,186 75.8 92.3 70.0 19.3 11.7 0.7 0.5 0.8 3.872 6.359 47.64 1,571.1 e Sudan 79.6 35.3 2,199 974 55.2 23.8 13.1 5.0 2.2 0.1 0.1 0.6 1.077 2.430 36.20 85.7 Swaziland 5.0 2.6 4,517 2,339 64.5 48.9 31.6 10.2 5.3 0.0 0.0 0.0 3.293 6.359 1.10 16.4 Tanzania 35.9 12.6 926 324 43.6 10.0 4.4 2.1 0.7 0.1 0.0 0.6 395.627 1,128.934 38.82 14,219.1 Togo 4.6 2.1 836 381 56.8 9.1 5.1 1.9 0.9 0.0 0.0 0.1 240.381 527.468 5.54 1,113.1 Tunisia 72.0 32.3 7,182 3,218 55.8 77.8 43.4 16.2 7.3 0.1 0.1 0.2 0.581 1.297 10.03 41.9 Uganda 28.9 10.0 1,004 350 43.3 10.9 4.7 2.3 0.8 0.1 0.0 0.5 619.640 1,780.666 28.72 17,877.9 Zambiae 13.9 7.5 1,214 657 67.4 13.2 8.9 2.7 1.5 0.0 0.0 0.2 2.415 4.464 11.47 33.6 Zimbabwef 3.6 … 287 … 184.2 3.1 … 0.6 1.0 0.0 … 0.2 1.479 … 12.71 5.4 Total (48) 1,898.7 863.7 2,230 1,014 56.7 24.2 13.7 5.0 2.3 3.3 1.9 13.8 n.a. n.a. 851.4 n.a. ASIA AND THE PACIFIC Bangladesh 191.3 67.3 1,381 486 43.8 15.0 6.6 3.1 1.1 0.3 0.1 2.3 22.642 64.327 138.60 4,332.3 Bhutan 2.3 0.8 3,639 1,299 44.5 39.4 17.5 8.2 2.9 0.0 0.0 0.0 15.739 44.100 0.63 36.4 Brunei Darussalam 17.6 9.5 49,001 26,587 67.6 530.7 358.7 110.8 60.1 0.0 0.0 0.0 0.903 1.664 0.36 15.9 Cambodia 20.1 6.3 1,558 487 38.9 16.9 6.6 3.5 1.1 0.0 0.0 0.2 1,278.552 4,092.500 12.93 25,754.3 Chinag 5,364.3 2,256.9 4,123 1,735 52.4 44.7 23.4 9.3 3.9 9.4 4.9 21.1 3.448 8.194 1,301.16 18,493.7 Hong Kong SAR, China 248.3 181.6 36,440 26,650 91.1 394.7 359.5 82.4 60.2 0.4 0.4 0.1 5.688 7.777 6.81 1,412.1 Macao SAR, China 17.9 11.8 37,041 24,365 81.9 401.2 328.7 83.7 55.1 0.0 0.0 0.0 5.270 8.011 0.48 94.5 Taiwan, China 607.0 365.0 26,659 16,029 74.9 288.7 216.2 60.3 36.2 1.1 0.8 0.4 19.341 32.167 22.77 11,740.3 Fiji 3.6 3.0 4,300 3,636 105.3 46.6 49.0 9.7 8.2 0.0 0.0 0.0 1.430 1.691 0.83 5.1 India 2,425.5 806.8 2,202 733 41.4 23.9 9.9 5.0 1.7 4.3 1.8 17.9 14.669 44.100 1,101.32 35,579.1 Indonesia 705.2 285.9 3,192 1,294 50.5 34.6 17.5 7.2 2.9 1.2 0.6 3.6 3,934.264 9,704.742 220.93 27,74,281.1 Iran, Islamic Rep. 725.7 216.6 10,345 3,087 37.2 112.1 41.6 23.4 7.0 1.3 0.5 1.1 2,674.755 8,963.959 70.15 19,41,187.6 Lao PDR 9.7 2.7 1,723 483 34.9 18.7 6.5 3.9 1.1 0.0 0.0 0.1 2,988.385 10,655.167 5.62 28,947.8 Malaysia 313.5 143.5 12,036 5,511 57.0 130.4 74.3 27.2 12.5 0.6 0.3 0.4 1.734 3.787 26.05 543.6 Maldives 1.7 1.1 5,070 3,222 79.1 54.9 43.5 11.5 7.3 0.0 0.0 0.0 8.134 12.800 0.34 14.0 Mongolia 7.3 2.5 2,845 985 43.1 30.8 13.3 6.4 2.2 0.0 0.0 0.0 417.222 1,205.247 2.56 3,041.4 Nepal 27.3 8.7 1,119 355 39.5 12.1 4.8 2.5 0.8 0.0 0.0 0.4 22.651 71.368 24.44 619.4 Pakistan 398.4 127.9 2,588 831 40.0 28.0 11.2 5.8 1.9 0.7 0.3 2.5 19.102 59.514 153.96 7,610.8 (continued) Updated ICP 2005 Results 265 Table H.1 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) Philippines 261.0 103.1 3,061 1,209 49.2 33.2 16.3 6.9 2.7 0.5 0.2 1.4 21.755 55.085 85.26 5,677.7 Singapore 193.6 125.4 45,374 29,403 80.7 491.5 396.7 102.6 66.5 0.3 0.3 0.1 1.079 1.664 4.27 208.8 Sri Lanka 69.7 24.4 3,546 1,241 43.6 38.4 16.7 8.0 2.8 0.1 0.1 0.3 35.170 100.498 19.67 2,452.8 Thailand 476.2 188.6 7,314 2,897 49.3 79.2 39.1 16.5 6.5 0.8 0.4 1.1 15.932 40.220 65.10 7,586.3 Vietnam 193.9 57.6 2,368 704 37.0 25.6 9.5 5.4 1.6 0.3 0.1 1.3 4,712.688 15,858.917 81.91 9,14,000.8 Total (23) 12,281.2 4,997.0 3,670 1,493 50.7 39.8 20.1 8.3 3.4 21.6 11.0 54.4 n.a. n.a. 3,346.1 n.a. COMMONWEALTH OF INDEPENDENT STATES Armenia 12.6 4.9 4,008 1,564 48.6 43.4 21.1 9.1 3.5 0.0 0.0 0.1 178.580 457.688 3.13 2,242.9 Azerbaijane 38.4 13.2 4,579 1,580 43.0 49.6 21.3 10.4 3.6 0.1 0.0 0.1 0.326 0.946 8.38 12.5 Belarus 83.5 30.2 8,639 3,126 45.1 93.6 42.2 19.5 7.1 0.1 0.1 0.2 779.330 2,153.800 9.66 65,067.1 Georgia 15.3 6.2 3,505 1,427 50.7 38.0 19.3 7.9 3.2 0.0 0.0 0.1 0.738 1.813 4.36 11.3 Kazakhstan 131.8 57.1 8,699 3,771 54.0 94.2 50.9 19.7 8.5 0.2 0.1 0.2 57.610 132.880 15.15 7,590.6 Kyrgyz Republic 8.9 2.5 1,776 491 34.5 19.2 6.6 4.0 1.1 0.0 0.0 0.1 11.350 41.012 5.01 100.9 Moldova 8.5 3.0 2,364 831 43.8 25.6 11.2 5.3 1.9 0.0 0.0 0.1 4.430 12.600 3.60 37.7 h Russian Federation 1,696.7 764.1 11,822 5,324 56.1 128.1 71.8 26.7 12.0 3.0 1.7 2.3 12.736 28.280 143.52 21,609.8 Tajikistan 9.7 2.3 1,436 341 29.6 15.6 4.6 3.2 0.8 0.0 0.0 0.1 0.740 3.118 6.78 7.2 Ukraine 262.8 86.1 5,578 1,829 40.8 60.4 24.7 12.6 4.1 0.5 0.2 0.8 1.680 5.125 47.11 441.5 Total (10) 2,268.1 969.7 9,194 3,931 53.3 99.6 53.0 20.8 8.9 4.0 2.1 4.0 n.a. n.a. 246.7 n.a. EUROSTAT-OECD Albania 18.7 8.1 5,942 2,574 54.0 64.4 34.7 13.4 5.8 0.0 0.0 0.1 43.640 100.739 3.14 814.8 Australia 693.4 735.2 33,755 35,789 132.1 365.6 482.8 76.3 80.9 1.2 1.6 0.3 1.388 1.309 20.54 962.7 Austria 276.7 305.1 33,638 37,095 137.4 364.3 500.4 76.0 83.8 0.5 0.7 0.1 0.886 0.804 8.23 245.2 Belgium 337.3 377.5 32,204 36,042 139.4 348.8 486.2 72.8 81.5 0.6 0.8 0.2 0.900 0.804 10.47 303.4 Bosnia and Herzegovina 25.4 11.6 6,608 3,019 56.9 71.6 40.7 14.9 6.8 0.0 0.0 0.1 0.718 1.572 3.84 18.2 Bulgaria 75.9 28.9 9,835 3,748 47.5 106.5 50.6 22.2 8.5 0.1 0.1 0.1 0.599 1.572 7.72 45.5 Canada 1,132.0 1,133.8 35,106 35,161 124.7 380.2 474.3 79.3 79.5 2.0 2.5 0.5 1.214 1.212 32.25 1,373.8 Croatia 68.1 44.8 15,329 10,089 82.0 166.0 136.1 34.6 22.8 0.1 0.1 0.1 3.915 5.949 4.44 266.7 Cyprus 18.4 16.9 24,917 22,893 114.4 269.9 308.8 56.3 51.7 0.0 0.0 0.0 0.426 0.464 0.74 7.8 Czech Republic 217.7 130.2 21,268 12,719 74.5 230.4 171.6 48.1 28.7 0.4 0.3 0.2 14.316 23.939 10.23 3,116.1 Denmark 179.9 258.0 33,196 47,608 178.6 359.6 642.3 75.0 107.6 0.3 0.6 0.1 8.590 5.990 5.42 1,545.3 Estonia 22.3 13.9 16,525 10,320 77.8 179.0 139.2 37.4 23.3 0.0 0.0 0.0 7.854 12.577 1.35 175.0 Finland 161.1 195.9 30,709 37,335 151.4 332.6 503.7 69.4 84.4 0.3 0.4 0.1 0.977 0.804 5.25 157.4 France 1,860.7 2,137.4 29,555 33,950 143.1 320.1 458.0 66.8 76.7 3.3 4.7 1.0 0.923 0.804 62.96 1,718.0 Germany 2,566.0 2,767.4 31,117 33,559 134.3 337.0 452.7 70.3 75.9 4.5 6.1 1.3 0.867 0.804 82.46 2,224.4 Greece 270.4 240.2 24,348 21,629 110.6 263.7 291.8 55.0 48.9 0.5 0.5 0.2 0.714 0.804 11.10 193.0 Hungary 171.2 110.4 16,975 10,948 80.3 183.9 147.7 38.4 24.7 0.3 0.2 0.2 128.593 199.381 10.09 22,018.3 Iceland 10.4 16.3 34,976 55,110 196.2 378.8 743.5 79.1 124.6 0.0 0.0 0.0 99.078 62.881 0.30 1,025.7 Ireland 161.4 202.8 38,795 48,758 156.5 420.2 657.8 87.7 110.2 0.3 0.4 0.1 1.010 0.804 4.16 163.0 Israel 161.4 133.7 23,210 19,223 103.2 251.4 259.3 52.5 43.5 0.3 0.3 0.1 3.717 4.488 6.96 600.0 266 Purchasing Power Parities and the Real Size of World Economies Table H.1 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) Italy 1,657.4 1,787.0 28,280 30,491 134.3 306.3 411.3 63.9 68.9 2.9 3.9 1.0 0.867 0.804 58.61 1,436.4 Japan 3,889.6 4,571.9 30,446 35,786 146.4 329.8 482.8 68.8 80.9 6.8 10.0 2.1 129.552 110.218 127.76 5,03,903.0 Korea, Rep. 1,096.7 844.9 22,783 17,551 95.9 246.8 236.8 51.5 39.7 1.9 1.9 0.8 788.920 1,024.120 48.14 8,65,240.9 Latvia 29.8 16.1 13,312 7,183 67.2 144.2 96.9 30.1 16.2 0.1 0.0 0.0 0.302 0.560 2.24 9.0 Lithuania 48.7 26.1 14,657 7,851 66.7 158.8 105.9 33.1 17.7 0.1 0.1 0.1 1.487 2.775 3.32 72.4 Luxembourg 31.8 37.7 68,167 80,812 147.7 738.3 1090.2 154.1 182.7 0.1 0.1 0.0 0.953 0.804 0.47 30.3 Macedonia, FYR 16.0 6.0 7,877 2,939 46.5 85.3 39.7 17.8 6.6 0.0 0.0 0.0 18.389 49.280 2.04 295.1 Malta 8.7 6.1 21,590 15,222 87.8 233.8 205.4 48.8 34.4 0.0 0.0 0.0 0.244 0.346 0.40 2.1 Mexico 1,293.8 846.1 12,461 8,149 81.5 135.0 109.9 28.2 18.4 2.3 1.9 1.7 7.127 10.898 103.83 9,220.7 Montenegro 5.2 2.3 8,288 3,624 54.5 89.8 48.9 18.7 8.2 0.0 0.0 0.0 0.352 0.804 0.62 1.8 Netherlands 572.9 638.7 35,111 39,145 138.9 380.3 528.1 79.4 88.5 1.0 1.4 0.3 0.896 0.804 16.32 513.4 New Zealand 103.9 112.3 25,046 27,069 134.6 271.3 365.2 56.6 61.2 0.2 0.2 0.1 1.535 1.420 4.15 159.5 Norway 220.2 304.3 47,640 65,834 172.1 516.0 888.1 107.7 148.8 0.4 0.7 0.1 8.896 6.438 4.62 1,958.9 Poland 526.1 304.1 13,786 7,968 72.0 149.3 107.5 31.2 18.0 0.9 0.7 0.6 1.869 3.234 38.16 983.3 Portugal 225.4 191.9 21,370 18,194 106.0 231.5 245.4 48.3 41.1 0.4 0.4 0.2 0.684 0.804 10.55 154.3 Romania 203.1 99.3 9,390 4,591 60.9 101.7 61.9 21.2 10.4 0.4 0.2 0.4 1.423 2.910 21.62 289.0 Russian Federationh 1,696.7 764.1 11,822 5,324 56.1 128.1 71.8 26.7 12.0 3.0 1.7 2.3 12.736 28.280 143.52 21,609.8 Serbia 63.4 25.2 8,515 3,391 49.6 92.2 45.7 19.2 7.7 0.1 0.1 0.1 26.564 66.707 7.44 1,683.2 Slovak Republic 87.1 47.9 16,175 8,889 68.4 175.2 119.9 36.6 20.1 0.2 0.1 0.1 17.050 31.026 5.39 1,485.6 Slovenia 47.0 35.7 23,470 17,863 94.8 254.2 241.0 53.0 40.4 0.1 0.1 0.0 146.564 192.563 2.00 6,883.0 Spain 1,188.8 1,131.3 27,392 26,067 118.5 296.7 351.7 61.9 58.9 2.1 2.5 0.7 0.765 0.804 43.40 909.3 Sweden 295.3 371.2 32,702 41,105 156.6 354.2 554.5 73.9 92.9 0.5 0.8 0.1 9.378 7.461 9.03 2,769.4 Switzerland 274.9 385.0 36,649 51,321 174.4 397.0 692.3 82.8 116.0 0.5 0.8 0.1 1.743 1.245 7.50 479.1 Turkey 781.2 481.4 11,394 7,021 76.7 123.4 94.7 25.8 15.9 1.4 1.1 1.1 0.831 1.348 68.57 648.9 United Kingdom 1,984.9 2,297.4 32,952 38,140 144.2 356.9 514.5 74.5 86.2 3.5 5.0 1.0 0.636 0.550 60.24 1,262.7 United States 13,095.5 13,095.5 44,243 44,243 124.6 479.2 596.9 100.0 100.0 23.0 28.7 4.8 1.000 1.000 295.99 13,095.5 Total (46) 37,872.3 37,297.3 27,492 27,075 122.7 297.8 365.3 62.1 61.2 66.7 81.8 22.4 n.a. n.a. 1,377.6 n.a. LATIN AMERICA Argentina 419.0 183.2 10,843 4,740 54.5 117.4 63.9 24.5 10.7 0.7 0.4 0.6 1.269 2.904 38.65 531.9 Bolivia 34.5 9.5 3,747 1,037 34.5 40.6 14.0 8.5 2.3 0.1 0.0 0.1 2.232 8.066 9.21 77.0 Brazil 1,582.6 882.0 8,502 4,738 69.4 92.1 63.9 19.2 10.7 2.8 1.9 3.0 1.357 2.434 186.15 2,147.2 Chile 206.4 123.1 12,690 7,565 74.2 137.4 102.1 28.7 17.1 0.4 0.3 0.3 333.690 559.768 16.27 68,882.8 Colombia 314.4 146.6 7,280 3,394 58.1 78.9 45.8 16.5 7.7 0.6 0.3 0.7 1,081.948 2,320.830 43.19 3,40,156.0 Ecuador 98.2 41.5 7,116 3,007 52.6 77.1 40.6 16.1 6.8 0.2 0.1 0.2 0.423 1.000 13.80 41.5 Paraguay 26.9 8.7 4,554 1,479 40.5 49.3 20.0 10.3 3.3 0.0 0.0 0.1 2,006.827 6,177.960 5.90 53,962.3 Peru 176.0 79.4 6,348 2,863 56.2 68.8 38.6 14.3 6.5 0.3 0.2 0.5 1.487 3.296 27.73 261.7 Uruguay 32.0 17.4 9,626 5,221 67.6 104.3 70.4 21.8 11.8 0.1 0.0 0.1 13.278 24.479 3.33 425.0 e Venezuela, RB 263.8 145.5 9,869 5,445 68.7 106.9 73.5 22.3 12.3 0.5 0.3 0.4 1.153 2.090 26.73 304.1 Total (10) 3,153.9 1,636.9 8,502 4,413 64.6 92.1 59.5 19.2 10.0 5.6 3.6 6.0 n.a. n.a. 370.9 n.a. (continued) Updated ICP 2005 Results 267 Table H.1 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) WESTERN ASIA Bahrain 24.2 15.9 27,173 17,901 82.1 294.3 241.5 61.4 40.5 0.0 0.0 0.0 0.249 0.378 0.89 6.0 Egypt, Arab Rep.d 351.6 98.2 5,023 1,402 34.8 54.4 18.9 11.4 3.2 0.6 0.2 1.1 1.616 5.789 70.00 568.2 Iraq 95.6 36.2 3,417 1,296 47.2 37.0 17.5 7.7 2.9 0.2 0.1 0.5 558.701 1,473.000 27.96 53,386.4 Jordan 23.5 12.6 4,485 2,406 66.8 48.6 32.5 10.1 5.4 0.0 0.0 0.1 0.381 0.709 5.23 8.9 Kuwait 110.4 80.8 49,899 36,504 91.1 540.5 492.5 112.8 82.5 0.2 0.2 0.0 0.214 0.292 2.21 23.6 Lebanon 38.9 21.9 9,750 5,481 70.0 105.6 73.9 22.0 12.4 0.1 0.0 0.1 847.518 1,507.500 3.99 32,944.0 Oman 51.1 30.9 20,381 12,318 75.3 220.7 166.2 46.1 27.8 0.1 0.1 0.0 0.232 0.385 2.51 11.9 Qatar 59.0 44.4 69,612 52,357 93.7 754.0 706.3 157.3 118.3 0.1 0.1 0.0 2.745 3.650 0.85 162.1 Saudi Arabia 510.6 328.2 21,886 14,068 80.1 237.1 189.8 49.5 31.8 0.9 0.7 0.4 2.410 3.750 23.33 1,230.8 Syrian Arab Rep. 76.4 28.9 4,206 1,590 47.1 45.6 21.5 9.5 3.6 0.1 0.1 0.3 19.717 52.140 18.17 1,506.4 Yemen, Rep. 52.5 19.1 2,626 953 45.2 28.4 12.9 5.9 2.2 0.1 0.0 0.3 69.490 191.400 19.98 3,646.6 Total (11) 1,393.7 717.0 7,959 4,094 64.1 86.2 55.2 18.0 9.3 2.5 1.6 2.8 n.a. n.a. 175.1 n.a. WORLDi (146) 56,819.6 45,619.4 9,232 7,413 100.0 100.0 100.0 20.9 16.8 100.0 100.0 100.0 n.a. n.a. 6,154.30 n.a. Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; XR = exchange rate; ... = data suppressed because of incompleteness. a. All shares are rounded to one decimal place. More precision can be found in the Excel version of the table, which can be downloaded from the ICP website. b. All exchange rates (XRs) and PPPs are rounded to three decimal places. More precision can be found in the Excel version of the table, which can be downloaded from the ICP website. c. Burundi submitted prices, but it did not provide official national accounts data. d. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The results for Egypt from each region were averaged by taking the geometric mean of the PPPs, allowing Egypt to be shown in each region with the same ranking in the world comparison. e. Currency adjusted to reflect 2011 currency. f. Zimbabwe’s exchange rate–related data were suppressed because of extreme volatility in the official exchange rate. PPP adjusted to reflect 2011 currency. g. Results for China were based on the national average prices extrapolated by the World Bank and Asian Development Bank using price data for 11 cities submitted by the National Bureau of Statistics of China. The data for China do not include Hong Kong SAR, China; Macao SAR, China; and Taiwan, China. h. The Russian Federation participated in both the Commonwealth of Independent States (CIS) and Eurostat-Organisation for Economic Co-operation and Development (OECD) comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. i. Does not double count the dual participation economies: the Arab Republic of Egypt and the Russian Federation. 268 Purchasing Power Parities and the Real Size of World Economies Table H.2 Analytical ICP 2005 Summary Results Using the Country Aggregation with Redistribution (CAR) Method: GDP Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) AFRICA Angola 59.2 30.6 3,577 1,851 65.8 38.0 25.0 8.1 4.2 0.1 0.1 0.3 45.117 87.159 16.54 2,669.6 Benin 10.3 4.4 1,262 533 53.7 13.4 7.2 2.9 1.2 0.0 0.0 0.1 222.691 527.468 8.18 2,298.7 Botswana 20.2 9.7 10,775 5,176 61.1 114.3 69.8 24.4 11.7 0.0 0.0 0.0 2.455 5.110 1.88 49.6 Burkina Faso 14.2 5.5 1,057 407 48.9 11.2 5.5 2.4 0.9 0.0 0.0 0.2 203.059 527.468 13.42 2,881.4 Burundic … … … … 40.9 ... … … … … … 0.1 347.817 1,081.577 7.77 ... Cameroon 34.5 16.6 1,902 918 61.4 20.2 12.4 4.3 2.1 0.1 0.0 0.3 254.567 527.468 18.14 8,781.0 Cape Verde 1.4 1.1 2,872 2,278 100.9 30.5 30.7 6.5 5.1 0.0 0.0 0.0 70.342 88.670 0.48 96.7 Central African Republic 2.7 1.4 672 341 64.5 7.1 4.6 1.5 0.8 0.0 0.0 0.1 267.472 527.468 3.96 712.1 Chad 16.6 6.6 1,657 662 50.8 17.6 8.9 3.7 1.5 0.0 0.0 0.2 210.943 527.468 10.01 3,499.3 Comoros 0.6 0.4 1,061 615 73.7 11.3 8.3 2.4 1.4 0.0 0.0 0.0 229.395 395.601 0.60 146.2 Congo, Dem. Rep. 22.6 10.3 418 191 58.3 4.4 2.6 0.9 0.4 0.0 0.0 0.9 217.298 473.908 54.03 4,903.0 Congo, Rep. 11.9 6.1 3,348 1,730 65.7 35.5 23.3 7.6 3.9 0.0 0.0 0.1 272.563 527.468 3.54 3,232.7 Côte d’Ivoire 30.9 17.1 1,777 982 70.3 18.9 13.3 4.0 2.2 0.1 0.0 0.3 291.553 527.468 17.39 9,011.8 Djibouti 1.5 0.7 1,889 913 61.4 20.0 12.3 4.3 2.1 0.0 0.0 0.0 85.883 177.721 0.78 126.0 d Egypt, Arab Rep. 346.7 98.2 4,953 1,402 36.0 52.6 18.9 11.2 3.2 0.6 0.2 1.1 1.639 5.789 70.00 568.2 Equatorial Guinea 13.0 7.2 21,599 11,936 70.3 229.2 161.0 48.8 27.0 0.0 0.0 0.0 291.489 527.468 0.60 3,800.5 Ethiopia 42.0 11.1 551 145 33.5 5.8 2.0 1.2 0.3 0.1 0.0 1.2 2.286 8.666 76.17 95.9 Gabon 19.2 9.5 13,919 6,857 62.6 147.7 92.5 31.5 15.5 0.0 0.0 0.0 259.855 527.468 1.38 4,989.3 Gambia, The 2.3 0.6 1,619 434 34.1 17.2 5.9 3.7 1.0 0.0 0.0 0.0 7.667 28.575 1.44 17.8 e Ghana 41.3 17.2 1,934 805 52.9 20.5 10.9 4.4 1.8 0.1 0.0 0.3 0.377 0.906 21.38 15.6 Guinea 8.7 2.9 904 307 43.1 9.6 4.1 2.0 0.7 0.0 0.0 0.2 1,236.599 3,644.333 9.58 10,703.7 Guinea-Bissau 1.9 0.8 1,326 554 53.1 14.1 7.5 3.0 1.3 0.0 0.0 0.0 220.375 527.468 1.42 415.3 Kenya 47.3 18.7 1,321 524 50.4 14.0 7.1 3.0 1.2 0.1 0.0 0.6 29.942 75.554 35.79 1,415.8 Lesotho 2.5 1.4 1,277 711 70.8 13.5 9.6 2.9 1.6 0.0 0.0 0.0 3.539 6.359 1.93 8.7 Liberia 1.2 0.6 372 186 63.5 4.0 2.5 0.8 0.4 0.0 0.0 0.1 0.500 1.000 3.27 0.6 Madagascar 15.5 5.1 845 278 41.8 9.0 3.8 1.9 0.6 0.0 0.0 0.3 658.758 2,003.026 18.29 10,186.7 Malawi 9.9 3.4 768 259 43.0 8.1 3.5 1.7 0.6 0.0 0.0 0.2 40.015 118.420 12.92 397.1 Mali 20.6 9.5 1,728 798 58.7 18.3 10.8 3.9 1.8 0.0 0.0 0.2 243.489 527.468 11.94 5,024.2 Mauritania 5.8 2.2 1,839 694 48.0 19.5 9.4 4.2 1.6 0.0 0.0 0.1 100.238 265.528 3.15 580.0 Mauritius 12.3 6.2 9,875 4,983 64.2 104.8 67.2 22.3 11.3 0.0 0.0 0.0 14.885 29.496 1.24 182.7 Morocco 105.6 59.0 3,507 1,957 70.9 37.2 26.4 7.9 4.4 0.2 0.1 0.5 4.947 8.865 30.13 522.6 Mozambiquee 13.7 6.6 653 313 61.0 6.9 4.2 1.5 0.7 0.0 0.0 0.3 11.064 23.061 21.01 151.7 Namibia 10.7 7.3 5,267 3,582 86.5 55.9 48.3 11.9 8.1 0.0 0.0 0.0 4.325 6.359 2.03 46.2 Niger 7.7 3.4 586 256 55.4 6.2 3.4 1.3 0.6 0.0 0.0 0.2 229.868 527.468 13.18 1,777.0 Nigeria 243.8 113.5 1,747 813 59.2 18.5 11.0 3.9 1.8 0.4 0.2 2.3 61.084 131.274 139.59 14,894.5 Rwanda 7.6 2.6 809 274 43.0 8.6 3.7 1.8 0.6 0.0 0.0 0.2 188.816 557.823 9.43 1,439.8 São Tomé and Príncipe 0.2 0.1 1,493 797 67.9 15.8 10.8 3.4 1.8 0.0 0.0 0.0 5,636.722 10,557.970 0.15 1,301.3 (continued) Updated ICP 2005 Results 269 Table H.2 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) Senegal 18.0 8.7 1,597 773 61.5 16.9 10.4 3.6 1.7 0.0 0.0 0.2 255.228 527.468 11.27 4,593.1 Sierra Leone 4.4 1.7 855 322 47.9 9.1 4.3 1.9 0.7 0.0 0.0 0.1 1,089.318 2,889.588 5.12 4,769.8 South Africa 400.1 247.1 8,398 5,186 78.5 89.1 70.0 19.0 11.7 0.7 0.5 0.8 3.927 6.359 47.64 1,571.1 Sudane 78.5 35.3 2,168 974 57.1 23.0 13.1 4.9 2.2 0.1 0.1 0.6 1.092 2.430 36.20 85.7 Swaziland 4.9 2.6 4,454 2,339 66.8 47.3 31.6 10.1 5.3 0.0 0.0 0.0 3.340 6.359 1.10 16.4 Tanzania 35.4 12.6 913 324 45.2 9.7 4.4 2.1 0.7 0.1 0.0 0.6 401.224 1,128.934 38.82 14,219.1 Togo 4.6 2.1 824 381 58.8 8.7 5.1 1.9 0.9 0.0 0.0 0.1 243.782 527.468 5.54 1,113.1 Tunisia 71.0 32.3 7,082 3,218 57.8 75.2 43.4 16.0 7.3 0.1 0.1 0.2 0.590 1.297 10.03 41.9 Uganda 28.4 10.0 990 350 44.9 10.5 4.7 2.2 0.8 0.0 0.0 0.5 628.407 1,780.666 28.72 17,877.9 Zambiae 13.7 7.5 1,198 657 69.8 12.7 8.9 2.7 1.5 0.0 0.0 0.2 2.449 4.464 11.47 33.6 Zimbabwef 3.6 … 283 … 190.6 3.0 … 0.6 … 0.0 … 0.2 1.500 … 12.71 5.4 Total (48) 1,872.2 863.7 2,199 1,014 58.6 23.3 13.7 5.0 2.3 3.2 1.9 13.8 n.a. n.a. 851.4 n.a. ASIA AND THE PACIFIC Bangladesh 209.7 67.3 1,513 486 40.8 16.1 6.6 3.4 1.1 0.4 0.1 2.3 20.658 64.327 138.60 4,332.3 Bhutan 2.5 0.8 3,988 1,299 41.4 42.3 17.5 9.0 2.9 0.0 0.0 0.0 14.360 44.100 0.63 36.4 Brunei Darussalam 19.3 9.5 53,706 26,587 62.9 569.9 358.7 121.4 60.1 0.0 0.0 0.0 0.824 1.664 0.36 15.9 Cambodia 22.1 6.3 1,708 487 36.2 18.1 6.6 3.9 1.1 0.0 0.0 0.2 1,166.549 4,092.500 12.93 25,754.3 Chinag 5,879.3 2,256.9 4,519 1,735 48.8 47.9 23.4 10.2 3.9 10.1 4.9 21.1 3.146 8.194 1,301.16 18,493.7 Hong Kong SAR, China 272.1 181.6 39,939 26,650 84.8 423.8 359.5 90.3 60.2 0.5 0.4 0.1 5.190 7.777 6.81 1,412.1 Macao SAR, China 19.6 11.8 40,597 24,365 76.3 430.8 328.7 91.8 55.1 0.0 0.0 0.0 4.808 8.011 0.48 94.5 Taiwan, China 665.3 365.0 29,218 16,029 69.7 310.1 216.2 66.0 36.2 1.1 0.8 0.4 17.646 32.167 22.77 11,740.3 Fiji 3.9 3.0 4,713 3,636 98.1 50.0 49.0 10.7 8.2 0.0 0.0 0.0 1.304 1.691 0.83 5.1 India 2,658.4 806.8 2,414 733 38.6 25.6 9.9 5.5 1.7 4.6 1.8 17.9 13.384 44.100 1,101.32 35,579.1 Indonesia 772.9 285.9 3,498 1,294 47.0 37.1 17.5 7.9 2.9 1.3 0.6 3.6 3,589.617 9,704.742 220.93 27,74,281.1 Iran, Islamic Rep. 795.4 216.6 11,339 3,087 34.6 120.3 41.6 25.6 7.0 1.4 0.5 1.1 2,440.443 8,963.959 70.15 19,41,187.6 Lao PDR 10.6 2.7 1,888 483 32.5 20.0 6.5 4.3 1.1 0.0 0.0 0.1 2,726.598 10,655.167 5.62 28,947.8 Malaysia 343.6 143.5 13,192 5,511 53.1 140.0 74.3 29.8 12.5 0.6 0.3 0.4 1.582 3.787 26.05 543.6 Maldives 1.9 1.1 5,556 3,222 73.7 59.0 43.5 12.6 7.3 0.0 0.0 0.0 7.421 12.800 0.34 14.0 Mongolia 8.0 2.5 3,118 985 40.2 33.1 13.3 7.0 2.2 0.0 0.0 0.0 380.672 1,205.247 2.56 3,041.4 Nepal 30.0 8.7 1,226 355 36.8 13.0 4.8 2.8 0.8 0.1 0.0 0.4 20.666 71.368 24.44 619.4 Pakistan 436.7 127.9 2,836 831 37.2 30.1 11.2 6.4 1.9 0.8 0.3 2.5 17.429 59.514 153.96 7,610.8 Philippines 286.0 103.1 3,355 1,209 45.8 35.6 16.3 7.6 2.7 0.5 0.2 1.4 19.849 55.085 85.26 5,677.7 Singapore 212.1 125.4 49,731 29,403 75.2 527.7 396.7 112.4 66.5 0.4 0.3 0.1 0.984 1.664 4.27 208.8 Sri Lanka 76.4 24.4 3,886 1,241 40.6 41.2 16.7 8.8 2.8 0.1 0.1 0.3 32.089 100.498 19.67 2,452.8 Thailand 521.9 188.6 8,017 2,897 45.9 85.1 39.1 18.1 6.5 0.9 0.4 1.1 14.536 40.220 65.10 7,586.3 Vietnam 212.6 57.6 2,595 704 34.5 27.5 9.5 5.9 1.6 0.4 0.1 1.3 4,299.850 15,858.917 81.91 9,14,000.8 Total (23) 13,460.3 4,997.0 4,023 1,493 47.2 42.7 20.1 9.1 3.4 23.2 11.0 54.4 n.a. n.a. 3,346.1 n.a. 270 Purchasing Power Parities and the Real Size of World Economies Table H.2 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) COMMONWEALTH OF INDEPENDENT STATES Armenia 12.6 4.9 4,008 1,564 49.6 42.5 21.1 9.1 3.5 0.0 0.0 0.1 178.580 457.688 3.13 2,242.9 Azerbaijane 38.4 13.2 4,579 1,580 43.9 48.6 21.3 10.4 3.6 0.1 0.0 0.1 0.326 0.946 8.38 12.5 Belarus 83.5 30.2 8,639 3,126 46.0 91.7 42.2 19.5 7.1 0.1 0.1 0.2 779.330 2,153.800 9.66 65,067.1 Georgia 15.3 6.2 3,505 1,427 51.8 37.2 19.3 7.9 3.2 0.0 0.0 0.1 0.738 1.813 4.36 11.3 Kazakhstan 131.8 57.1 8,699 3,771 55.1 92.3 50.9 19.7 8.5 0.2 0.1 0.2 57.610 132.880 15.15 7,590.6 Kyrgyz Republic 8.9 2.5 1,776 491 35.2 18.8 6.6 4.0 1.1 0.0 0.0 0.1 11.350 41.012 5.01 100.9 Moldova 8.5 3.0 2,364 831 44.7 25.1 11.2 5.3 1.9 0.0 0.0 0.1 4.430 12.600 3.60 37.7 Russian Federationh 1,696.7 764.1 11,822 5,324 57.3 125.5 71.8 26.7 12.0 2.9 1.7 2.3 12.736 28.280 143.52 21,609.8 Tajikistan 9.7 2.3 1,436 341 30.2 15.2 4.6 3.2 0.8 0.0 0.0 0.1 0.740 3.118 6.78 7.2 Ukraine 262.8 86.1 5,578 1,829 41.7 59.2 24.7 12.6 4.1 0.5 0.2 0.8 1.680 5.125 47.11 441.5 Total (10) 2,268.1 969.7 9,194 3,931 54.4 97.6 53.0 20.8 8.9 3.9 2.1 4.0 n.a. n.a. 246.7 n.a. EUROSTAT-OECD Albania 18.7 8.1 5,942 2,574 55.1 63.1 34.7 13.4 5.8 0.0 0.0 0.1 43.640 100.739 3.14 814.8 Australia 693.4 735.2 33,755 35,789 134.8 358.2 482.8 76.3 80.9 1.2 1.6 0.3 1.388 1.309 20.54 962.7 Austria 276.7 305.1 33,638 37,095 140.2 357.0 500.4 76.0 83.8 0.5 0.7 0.1 0.886 0.804 8.23 245.2 Belgium 337.3 377.5 32,204 36,042 142.3 341.7 486.2 72.8 81.5 0.6 0.8 0.2 0.900 0.804 10.47 303.4 Bosnia and Herzegovina 25.4 11.6 6,608 3,019 58.1 70.1 40.7 14.9 6.8 0.0 0.0 0.1 0.718 1.572 3.84 18.2 Bulgaria 75.9 28.9 9,835 3,748 48.4 104.4 50.6 22.2 8.5 0.1 0.1 0.1 0.599 1.572 7.72 45.5 Canada 1,132.0 1,133.8 35,106 35,161 127.3 372.5 474.3 79.3 79.5 2.0 2.5 0.5 1.214 1.212 32.25 1,373.8 Croatia 68.1 44.8 15,329 10,089 83.7 162.7 136.1 34.6 22.8 0.1 0.1 0.1 3.915 5.949 4.44 266.7 Cyprus 18.4 16.9 24,917 22,893 116.8 264.4 308.8 56.3 51.7 0.0 0.0 0.0 0.426 0.464 0.74 7.8 Czech Republic 217.7 130.2 21,268 12,719 76.0 225.7 171.6 48.1 28.7 0.4 0.3 0.2 14.316 23.939 10.23 3,116.1 Denmark 179.9 258.0 33,196 47,608 182.3 352.3 642.3 75.0 107.6 0.3 0.6 0.1 8.590 5.990 5.42 1,545.3 Estonia 22.3 13.9 16,525 10,320 79.4 175.4 139.2 37.4 23.3 0.0 0.0 0.0 7.854 12.577 1.35 175.0 Finland 161.1 195.9 30,709 37,335 154.6 325.9 503.7 69.4 84.4 0.3 0.4 0.1 0.977 0.804 5.25 157.4 France 1,860.7 2,137.4 29,555 33,950 146.0 313.6 458.0 66.8 76.7 3.2 4.7 1.0 0.923 0.804 62.96 1,718.0 Germany 2,566.0 2,767.4 31,117 33,559 137.1 330.2 452.7 70.3 75.9 4.4 6.1 1.3 0.867 0.804 82.46 2,224.4 Greece 270.4 240.2 24,348 21,629 112.9 258.4 291.8 55.0 48.9 0.5 0.5 0.2 0.714 0.804 11.10 193.0 Hungary 171.2 110.4 16,975 10,948 82.0 180.1 147.7 38.4 24.7 0.3 0.2 0.2 128.593 199.381 10.09 22,018.3 Iceland 10.4 16.3 34,976 55,110 200.3 371.2 743.5 79.1 124.6 0.0 0.0 0.0 99.078 62.881 0.30 1,025.7 Ireland 161.4 202.8 38,795 48,758 159.8 411.7 657.8 87.7 110.2 0.3 0.4 0.1 1.010 0.804 4.16 163.0 Israel 161.4 133.7 23,210 19,223 105.3 246.3 259.3 52.5 43.5 0.3 0.3 0.1 3.717 4.488 6.96 600.0 Italy 1,657.4 1,787.0 28,280 30,491 137.1 300.1 411.3 63.9 68.9 2.9 3.9 1.0 0.867 0.804 58.61 1,436.4 Japan 3,889.6 4,571.9 30,446 35,786 149.4 323.1 482.8 68.8 80.9 6.7 10.0 2.1 129.552 110.218 127.76 5,03,903.0 Korea, Rep. 1,096.7 844.9 22,783 17,551 97.9 241.8 236.8 51.5 39.7 1.9 1.9 0.8 788.920 1,024.120 48.14 8,65,240.9 Latvia 29.8 16.1 13,312 7,183 68.6 141.3 96.9 30.1 16.2 0.1 0.0 0.0 0.302 0.560 2.24 9.0 (continued) Updated ICP 2005 Results 271 Table H.2 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) Lithuania 48.7 26.1 14,657 7,851 68.1 155.5 105.9 33.1 17.7 0.1 0.1 0.1 1.487 2.775 3.32 72.4 Luxembourg 31.8 37.7 68,167 80,812 150.7 723.4 1090.2 154.1 182.7 0.1 0.1 0.0 0.953 0.804 0.47 30.3 Macedonia, FYR 16.0 6.0 7,877 2,939 47.4 83.6 39.7 17.8 6.6 0.0 0.0 0.0 18.389 49.280 2.04 295.1 Malta 8.7 6.1 21,590 15,222 89.6 229.1 205.4 48.8 34.4 0.0 0.0 0.0 0.244 0.346 0.40 2.1 Mexico 1,293.8 846.1 12,461 8,149 83.1 132.2 109.9 28.2 18.4 2.2 1.9 1.7 7.127 10.898 103.83 9,220.7 Montenegro 5.2 2.3 8,288 3,624 55.6 87.9 48.9 18.7 8.2 0.0 0.0 0.0 0.352 0.804 0.62 1.8 Netherlands 572.9 638.7 35,111 39,145 141.7 372.6 528.1 79.4 88.5 1.0 1.4 0.3 0.896 0.804 16.32 513.4 New Zealand 103.9 112.3 25,046 27,069 137.4 265.8 365.2 56.6 61.2 0.2 0.2 0.1 1.535 1.420 4.15 159.5 Norway 220.2 304.3 47,640 65,834 175.7 505.5 888.1 107.7 148.8 0.4 0.7 0.1 8.896 6.438 4.62 1,958.9 Poland 526.1 304.1 13,786 7,968 73.5 146.3 107.5 31.2 18.0 0.9 0.7 0.6 1.869 3.234 38.16 983.3 Portugal 225.4 191.9 21,370 18,194 108.2 226.8 245.4 48.3 41.1 0.4 0.4 0.2 0.684 0.804 10.55 154.3 Romania 203.1 99.3 9,390 4,591 62.2 99.6 61.9 21.2 10.4 0.4 0.2 0.4 1.423 2.910 21.62 289.0 Russian Federationh 1,696.7 764.1 11,822 5,324 57.3 125.5 71.8 26.7 12.0 2.9 1.7 2.3 12.736 28.280 143.52 21,609.8 Serbia 63.4 25.2 8,515 3,391 50.6 90.4 45.7 19.2 7.7 0.1 0.1 0.1 26.564 66.707 7.44 1,683.2 Slovak Republic 87.1 47.9 16,175 8,889 69.9 171.6 119.9 36.6 20.1 0.2 0.1 0.1 17.050 31.026 5.39 1,485.6 Slovenia 47.0 35.7 23,470 17,863 96.8 249.1 241.0 53.0 40.4 0.1 0.1 0.0 146.564 192.563 2.00 6,883.0 Spain 1,188.8 1,131.3 27,392 26,067 121.0 290.7 351.7 61.9 58.9 2.0 2.5 0.7 0.765 0.804 43.40 909.3 Sweden 295.3 371.2 32,702 41,105 159.8 347.0 554.5 73.9 92.9 0.5 0.8 0.1 9.378 7.461 9.03 2,769.4 Switzerland 274.9 385.0 36,649 51,321 178.0 388.9 692.3 82.8 116.0 0.5 0.8 0.1 1.743 1.245 7.50 479.1 Turkey 781.2 481.4 11,394 7,021 78.3 120.9 94.7 25.8 15.9 1.3 1.1 1.1 0.831 1.348 68.57 648.9 United Kingdom 1,984.9 2,297.4 32,952 38,140 147.1 349.7 514.5 74.5 86.2 3.4 5.0 1.0 0.636 0.550 60.24 1,262.7 United States 13,095.5 13,095.5 44,243 44,243 127.1 469.5 596.9 100.0 100.0 22.6 28.7 4.8 1.000 1.000 295.99 13,095.5 Total (46) 37,872.3 37,297.3 27,492 27,075 125.2 291.7 365.3 62.1 61.2 65.3 81.8 22.4 n.a. n.a. 1,377.6 n.a. LATIN AMERICA Argentina 413.5 183.2 10,698 4,740 56.3 113.5 63.9 24.2 10.7 0.7 0.4 0.6 1.287 2.904 38.65 531.9 Bolivia 34.0 9.5 3,697 1,037 35.7 39.2 14.0 8.4 2.3 0.1 0.0 0.1 2.263 8.066 9.21 77.0 Brazil 1,561.6 882.0 8,389 4,738 71.8 89.0 63.9 19.0 10.7 2.7 1.9 3.0 1.375 2.434 186.15 2,147.2 Chile 203.7 123.1 12,521 7,565 76.8 132.9 102.1 28.3 17.1 0.4 0.3 0.3 338.197 559.768 16.27 68,882.8 Colombia 310.2 146.6 7,183 3,394 60.1 76.2 45.8 16.2 7.7 0.5 0.3 0.7 1,096.560 2,320.830 43.19 3,40,156.0 Ecuador 96.9 41.5 7,021 3,007 54.5 74.5 40.6 15.9 6.8 0.2 0.1 0.2 0.428 1.000 13.80 41.5 Paraguay 26.5 8.7 4,494 1,479 41.9 47.7 20.0 10.2 3.3 0.0 0.0 0.1 2,033.929 6,177.960 5.90 53,962.3 Peru 173.7 79.4 6,263 2,863 58.1 66.5 38.6 14.2 6.5 0.3 0.2 0.5 1.507 3.296 27.73 261.7 Uruguay 31.6 17.4 9,497 5,221 69.9 100.8 70.4 21.5 11.8 0.1 0.0 0.1 13.458 24.479 3.33 425.0 Venezuela, RBe 260.2 145.5 9,738 5,445 71.1 103.3 73.5 22.0 12.3 0.4 0.3 0.4 1.168 2.090 26.73 304.1 Total (10) 3,111.9 1,636.9 8,389 4,413 66.9 89.0 59.5 19.0 10.0 5.4 3.6 6.0 n.a. n.a. 370.9 n.a. WESTERN ASIA Bahrain 25.7 15.9 28,874 17,901 78.8 306.4 241.5 65.3 40.5 0.0 0.0 0.0 0.234 0.378 0.89 6.0 d Egypt, Arab Rep. 373.6 98.2 5,337 1,402 33.4 56.6 18.9 12.1 3.2 0.6 0.2 1.1 1.521 5.789 70.00 568.2 Iraq 101.5 36.2 3,631 1,296 45.4 38.5 17.5 8.2 2.9 0.2 0.1 0.5 525.779 1,473.000 27.96 53,386.4 272 Purchasing Power Parities and the Real Size of World Economies Table H.2 (Continued) Expenditure Expenditure Price level Expenditure per capita index Share (world = 100.0) PPP Reference data GROSS DOMESTIC per capita index PRODUCT Popula- Exchange Popula- Expenditure (US$, billions) (US$) World = 100.0 US = 100.0 Expenditure tion rate tion in national currency Based Based Based Based (world Based Based Based Based Based Based (US$ unit Economy on PPPs on XRs on PPPs on XRs = 100.0) on PPPs on XRs on PPPs on XRs on PPPs on XRs = 1.000) (US$ = 1.000) (millions) (billions) (00) (01) (02) (03) (04) (05) (06) (07) (08) (09) (10)a (11)a (12)a (13)b (14)b (15) (16) Jordan 24.9 12.6 4,766 2,406 64.2 50.6 32.5 10.8 5.4 0.0 0.0 0.1 0.358 0.709 5.23 8.9 Kuwait 117.4 80.8 53,023 36,504 87.5 562.7 492.5 119.8 82.5 0.2 0.2 0.0 0.201 0.292 2.21 23.6 Lebanon 41.3 21.9 10,360 5,481 67.3 109.9 73.9 23.4 12.4 0.1 0.0 0.1 797.578 1,507.500 3.99 32,944.0 Oman 54.3 30.9 21,657 12,318 72.3 229.8 166.2 48.9 27.8 0.1 0.1 0.0 0.219 0.385 2.51 11.9 Qatar 62.7 44.4 73,971 52,357 90.0 785.0 706.3 167.2 118.3 0.1 0.1 0.0 2.583 3.650 0.85 162.1 Saudi Arabia 542.6 328.2 23,257 14,068 76.9 246.8 189.8 52.6 31.8 0.9 0.7 0.4 2.268 3.750 23.33 1,230.8 Syria, Arab Rep. 81.2 28.9 4,469 1,590 45.2 47.4 21.5 10.1 3.6 0.1 0.1 0.3 18.555 52.140 18.17 1,506.4 Yemen, Rep. 55.8 19.1 2,790 953 43.4 29.6 12.9 6.3 2.2 0.1 0.0 0.3 65.395 191.400 19.98 3,646.6 Total (11) 1,481.0 717.0 8,457 4,094 61.5 89.7 55.2 19.1 9.3 2.6 1.6 2.8 n.a. n.a. 175.1 n.a. i WORLD (146) 57,995.4 45,619.4 9,424 7,413 100.0 100.0 100.0 21.3 16.8 100.0 100.0 100.0 n.a. n.a. 6,154.30 n.a. Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; XR = exchange rate; ... = data suppressed because of incompleteness. a. All shares are rounded to one decimal place. More precision can be found in the Excel version of the table, which can be downloaded from the ICP website. b. All exchange rates (XRs) and PPPs are rounded to three decimal places. More precision can be found in the Excel version of the table, which can be downloaded from the ICP website. c. Burundi submitted prices, but it did not provide official national accounts data. d. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The results for Egypt from each region were averaged by taking the geometric mean of the PPPs, allowing Egypt to be shown in each region with the same ranking in the world comparison. e. Currency adjusted to reflect 2011 currency. f. Zimbabwe’s exchange rate-related data were suppressed because of extreme volatility in the official exchange rate. PPP adjusted to reflect 2011 currency. g. Results for China were based on the national average prices extrapolated by the World Bank and Asian Development Bank using price data for 11 cities submitted by the National Bureau of Statistics of China. The data for China do not include Hong Kong SAR, China; Macao SAR, China; and Taiwan, China. h. The Russian Federation participated in both the Commonwealth of Independent States (CIS) and Eurostat-Organisation for Economic Co-operation and Development (OECD) comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. i. Does not double count the dual participation economies: the Arab Republic of Egypt and the Russian Federation. Updated ICP 2005 Results 273 Appendix I Comparison of ICP 2011 Results with 2011 Results Extrapolated from ICP 2005 This appendix presents the difference between • Column (06): Percentage difference between the new benchmark results of the 2011 round columns (04) and (05) of the International Comparison Program (ICP) • Column (07): Status of participation in ICP and the previous estimates for the year 2011 2005 benchmark survey based on extrapolations from the 2005 bench- Column (01) shows the GDP PPPs for 2011 mark data. The extrapolations were published from ICP 2011, and column (02) shows the GDP in the World Bank’s World Development PPPs for 2011 from WDI, which is based on Indicators (WDI) database released in April extrapolations from the 2005 benchmark data. 2014, before the 2005-based purchasing power Column (03) shows the percentage difference parities (PPPs) were replaced with the figures between the two sets of GDP PPPs for 2011 by based on the 2011 results. subtracting the ICP 2011 GDP PPP in column Table I.1 compares the PPPs arising from the (01) from the WDI GDP in column (02) and then ICP 2011 benchmark data and from the ICP dividing it by the WDI GDP PPP in column (02). 2005 results extrapolated to 2011, as well as the Column (04) shows the GDP expenditure from gross domestic product (GDP) expenditures in ICP 2011, and column (05) shows the GDP expen- current local currency units between ICP 2011 diture from the WDI data published in April 2014. and WDI for the year 2011. The table provides Column (06) shows the percentage difference the following indicators: between the two sets of GDP PPPs for 2011 by • Column (01): GDP PPPs with the U.S. dollar subtracting the ICP 2011 GDP PPP in column equal to 1.00 based on ICP 2011 (04) from the WDI GDP in column (05) and then • Column (02): GDP PPPs with the U.S. dollar dividing it by the WDI GDP PPP in column (05). equal to 1.00 based on World Bank’s WDI Column (07) indicates whether the economy 2011 PPPs, extrapolated from ICP 2005 participated in the benchmark survey in ICP benchmark PPPs 2005. If an economy did participate in the • Column (03): Percentage difference between benchmark survey, its PPPs were calculated columns (01) and (02) from the benchmark 2005 data and then extrap- • Column (04): GDP expenditure in national olated to 2011. If an economy is labeled non- currency units based on ICP 2011 benchmark, its PPPs were estimated using the • Column (05): GDP expenditure in national regression model described in chapter 4 and currency units based on WDI then extrapolated to 2011. 275 Table I.1 Comparison of ICP 2011 Global Results with Data in World Development Indicators (Extrapolation from ICP 2005) PPP (US$ = 1.000) Expenditure in national currency unit (billions) ICP 2005 Percentage Percentage benchmark or Economy ICP 2011 WDI difference ICP 2011 WDI difference nonbenchmark a (00) (01) (02) (03) (04) (05)a (06) (07) AFRICA Algeria 30.502 46.952 −35 14,481.0 14,519.8 0 Nonbenchmark Angola 68.315 85.009 −20 9,767.6 9,780.1 0 Benchmark Benin 214.035 235.872 −9 3,439.8 3,442.2 0 Benchmark Botswana 3.764 3.435 10 102.5 104.6 −2 Benchmark Burkina Faso 213.659 224.166 −5 4,868.5 4,905.4 −1 Benchmark Burundi 425.768 579.047 −26 2,599.9 2,970.7 −12 Benchmark Cameroon 227.212 255.110 −11 12,545.7 12,026.4 4 Benchmark Cape Verde 48.592 64.393 −25 149.0 147.9 1 Benchmark Central African Republic 255.862 233.100 10 1,029.7 1,044.1 −1 Benchmark Chad 250.443 239.124 5 5,725.3 5,736.2 0 Benchmark Comoros 207.584 260.700 −20 95.4 216.0 −56 Benchmark Congo, Dem. Rep. 521.870 576.744 −10 23,146.1 14,436.4 60 Benchmark Congo, Rep. 289.299 380.687 −24 6,982.5 6,807.0 3 Benchmark Côte d’Ivoire 228.228 317.985 −28 12,275.5 11,359.6 8 Benchmark Djibouti 94.003 ... ... 205.3 ... ... Benchmark Egypt, Arab Rep.b 1.625 2.671 −39 1,371.1 1,371.1 0 Benchmark Equatorial Guinea 294.572 377.683 −22 8,367.3 7,930.6 6 Benchmark Ethiopia 4.919 5.491 −10 506.1 506.1 0 Benchmark Gabon 318.156 369.552 −14 8,046.1 8,852.0 −9 Benchmark Gambia, The 9.939 8.315 20 26.6 26.5 0 Benchmark Ghana 0.699 1.286 −46 59.8 59.8 0 Benchmark Guinea 2,518.386 2,963.644 −15 33,128.3 33,738.6 −2 Benchmark Guinea−Bissau 220.085 236.595 −7 464.7 456.7 2 Benchmark Kenya 34.298 42.373 −19 3,048.9 2,985.9 2 Benchmark Lesotho 3.923 4.894 −20 18.3 18.3 0 Benchmark c Liberia 0.517 0.644 −20 1.1 1.5 −25 Benchmark Madagascar 673.730 981.330 −31 20,276.4 20,072.5 1 Benchmark Malawi 76.259 76.107 0 1,140.8 879.8 30 Benchmark Mali 210.193 285.393 −26 5,024.5 5,037.6 0 Benchmark Mauritania 115.855 135.243 −14 1,309.4 1,201.3 9 Benchmark Mauritius 15.941 17.625 −10 323.0 323.0 0 Benchmark Morocco 3.677 4.930 −25 802.6 802.6 0 Benchmark Mozambique 16.030 15.727 2 364.7 365.3 0 Benchmark Namibia 4.663 5.824 −20 90.6 91.7 −1 Benchmark Niger 221.087 258.520 −14 3,025.5 3,025.5 0 Benchmark Nigeria 74.378 93.161 −20 38,017.0 38,017.0 0 Benchmark Rwanda 260.751 274.541 −5 3,814.4 3,814.4 0 Benchmark São Tomé and Príncipe 8,527.157 13,508.864 −37 4,375.5 4,375.5 0 Benchmark 276 Purchasing Power Parities and the Real Size of World Economies Table I.1 (Continued) PPP (US$ = 1.000) Expenditure in national currency unit (billions) ICP 2005 Percentage Percentage benchmark or Economy ICP 2011 WDI difference ICP 2011 WDI difference nonbenchmark a (00) (01) (02) (03) (04) (05)a (06) (07) Senegal 236.287 273.913 −14 6,766.8 6,814.1 −1 Benchmark Seychelles 6.690 5.931 13 13.1 13.3 −1 Nonbenchmark Sierra Leone 1,553.139 1,874.545 −17 12,754.9 12,781.1 0 Benchmark South Africa 4.774 5.284 −10 2,917.5 2,917.5 0 Benchmark Sudand 1.224 1.941 −37 186.6 170.7 9 Benchmark Swaziland 3.900 4.546 −14 29.7 28.8 3 Benchmark Tanzania 522.483 558.527 −6 37,533.0 37,533.0 0 Benchmark Togo 215.060 272.137 −21 1,739.2 1,739.2 0 Benchmark Tunisia 0.592 0.664 −11 64.7 65.4 −1 Benchmark Uganda 833.540 851.008 −2 45,944.1 39,085.7 18 Benchmark c Zambia 2,378.380 4,299.701 −45 101,104.8 93,344.4 8 Benchmark Zimbabwe 0.504 ... ... 8.9 8.9 0 Benchmark Total (50) n.a. n.a. n.a. n.a. n.a. n.a. n.a. ASIA AND THE PACIFIC Bangladesh 23.145 30.074 −23 9,702.9 7,967.0 22 Benchmark Bhutan 16.856 19.492 −14 85.9 85.6 0 Benchmark Brunei Darussalam 0.717 0.989 −27 21.0 20.6 2 Benchmark Cambodia 1,347.115 1,557.872 −14 52,068.7 52,068.7 0 Benchmark e China 3.506 4.230 −17 47,310.4 47,310.4 0 Benchmark Fiji 1.042 1.642 −37 6.7 6.7 0 Benchmark Hong Kong SAR, China 5.462 5.469 0 1,936.1 1,936.1 0 Benchmark India 15.109 20.063 −25 86,993.1 90,097.2 −3 Benchmark Indonesia 3,606.566 6,665.474 −46 7,422,781.2 7,422,781.2 0 Benchmark Lao PDR 2,467.753 3,827.025 −36 64,727.1 66,514.7 −3 Benchmark Macao SAR, China 4.589 6.866 −33 295.0 295.0 0 Benchmark Malaysia 1.459 1.922 −24 884.5 884.5 0 Benchmark Maldives 8.527 10.956 −22 31.6 31.4 0 Benchmark Mongolia 537.127 842.962 −36 12,546.8 11,087.7 13 Benchmark Myanmar 234.974 ... ... 45,128.0 ... ... Nonbenchmark Nepal 24.628 36.648 −33 1,449.5 1,375.0 5 Benchmark Pakistan 24.346 39.401 −38 19,187.9 18,284.9 5 Benchmark Philippines 17.854 25.142 −29 9,706.3 9,706.3 0 Benchmark Singapore 0.891 1.066 −16 334.1 334.1 0 Benchmark Sri Lanka 38.654 56.712 −32 6,542.7 6,544.0 0 Benchmark Taiwan, China 15.112 ... ... 13,709.1 ... ... Benchmark Thailand 12.370 17.701 −30 11,120.5 10,540.1 6 Benchmark Vietnam 6,709.192 8,854.016 −24 2,779,880.2 2,779,881.0 0 Benchmark (continued) Comparison of ICP 2011 Results with 2011 Results Extrapolated from ICP 2005 277 Table I.1 (Continued) PPP (US$ = 1.000) Expenditure in national currency unit (billions) ICP 2005 Percentage Percentage benchmark or Economy ICP 2011 WDI difference ICP 2011 WDI difference nonbenchmark a (00) (01) (02) (03) (04) (05)a (06) (07) Total (23) n.a. n.a. n.a. n.a. n.a. n.a. n.a. COMMONWEALTH OF INDEPENDENT STATES Armenia 187.095 212.057 −12 3,777.9 3,777.9 0 Benchmark Azerbaijan 0.360 0.575 −37 52.1 52.1 0 Benchmark Belarus 1,889.308 2,115.740 −11 297,157.7 297,157.7 0 Benchmark Kazakhstan 80.171 128.313 −38 27,571.9 27,571.9 0 Benchmark Kyrgyz Republic 17.757 21.794 −19 286.0 286.0 0 Benchmark Moldova 5.535 6.933 −20 82.3 82.3 0 Benchmark f Russian Federation 17.346 17.346 0 55,799.6 55,799.6 0 Benchmark Tajikistan 1.740 1.874 −7 30.1 30.1 0 Benchmark Ukraine 3.434 3.990 −14 1,302.1 1,302.1 0 Benchmark Total (9) n.a. n.a. n.a. n.a. n.a. n.a. n.a. g EUROSTAT−OECD Albania 45.452 45.452 0 1,282.3 1,307.6 −2 Benchmark Australia 1.511 1.511 0 1,444.5 1,403.9 3 Benchmark Austria 0.830 0.830 0 299.2 299.2 0 Benchmark Belgium 0.839 0.839 0 369.3 369.3 0 Benchmark Bosnia and Herzegovina 0.724 0.724 0 26.8 25.7 4 Benchmark Bulgaria 0.660 0.660 0 75.3 75.3 0 Benchmark Canada 1.243 1.240 0 1,759.7 1,719.6 2 Benchmark Chile 348.017 348.017 0 121,492.7 121,492.7 0 Benchmark Croatia 3.802 3.802 0 330.2 330.2 0 Benchmark Cyprus 0.673 0.673 0 17.9 17.9 0 Benchmark Czech Republic 13.468 13.468 0 3,823.4 3,823.4 0 Benchmark Denmark 7.689 7.689 0 1,791.8 1,791.8 0 Benchmark Estonia 0.524 0.524 0 16.2 16.2 0 Benchmark Finland 0.907 0.907 0 188.7 188.7 0 Benchmark France 0.845 0.845 0 2,001.4 2,001.4 0 Benchmark Germany 0.779 0.779 0 2,609.9 2,609.9 0 Benchmark Greece 0.693 0.693 0 208.5 208.5 0 Benchmark Hungary 123.650 123.650 0 27,635.4 27,635.4 0 Benchmark Iceland 133.563 133.563 0 1,628.7 1,628.7 0 Benchmark Ireland 0.827 0.827 0 162.6 162.6 0 Benchmark Israel 3.945 3.945 0 923.9 923.9 0 Benchmark Italy 0.768 0.768 0 1,580.4 1,580.4 0 Benchmark Japan 107.454 107.454 0 470,623.2 470,623.2 0 Benchmark Korea, Rep. 854.586 854.586 0 1,235,160.5 1,235,160.5 0 Benchmark Latvia 0.347 0.347 0 14.3 14.3 0 Benchmark Lithuania 1.567 1.567 0 106.9 106.4 0 Benchmark 278 Purchasing Power Parities and the Real Size of World Economies Table I.1 (Continued) PPP (US$ = 1.000) Expenditure in national currency unit (billions) ICP 2005 Percentage Percentage benchmark or Economy ICP 2011 WDI difference ICP 2011 WDI difference nonbenchmark a (00) (01) (02) (03) (04) (05)a (06) (07) Luxembourg 0.906 0.906 0 41.7 41.7 0 Benchmark Macedonia, FYR 18.680 18.680 0 459.8 461.7 0 Benchmark Malta 0.558 0.558 0 6.6 6.6 1 Benchmark Mexico 7.673 7.673 0 14,536.9 14,423.7 1 Benchmark Montenegro 0.369 0.369 0 3.2 3.2 0 Benchmark Netherlands 0.832 0.832 0 599.0 599.0 0 Benchmark New Zealand 1.486 1.486 0 204.5 206.5 −1 Benchmark Norway 8.973 8.973 0 2,750.0 2,750.8 0 Benchmark Poland 1.823 1.823 0 1,528.1 1,528.1 0 Benchmark Portugal 0.628 0.628 0 171.1 171.1 0 Benchmark Romania 1.615 1.615 0 556.7 556.7 0 Benchmark f Russian Federation 17.346 17.346 0 55,799.6 55,799.6 0 Benchmark Serbia 37.288 37.288 0 3,208.6 3,175.0 1 Benchmark Slovak Republic 0.508 0.508 0 69.0 69.0 0 Benchmark Slovenia 0.625 0.625 0 36.1 36.2 0 Benchmark Spain 0.705 0.705 0 1,046.3 1,046.3 0 Benchmark Sweden 8.820 8.820 0 3,480.5 3,480.5 0 Benchmark Switzerland 1.441 1.441 0 585.1 585.1 0 Benchmark Turkey 0.987 0.987 0 1,297.7 1,297.7 0 Benchmark United Kingdom 0.698 0.698 0 1,536.9 1,536.9 0 Benchmark United States 1.000 1.000 0 15,533.8 15,533.8 0 Benchmark Total (47) n.a. n.a. n.a. n.a. n.a. n.a. n.a. LATIN AMERICA Bolivia 2.946 3.260 −10 166.1 166.1 0 Benchmark Brazil 1.471 1.827 −19 4,143.0 4,143.0 0 Benchmark Colombia 1,161.910 1,323.970 −12 621,615.0 621,615.0 0 Benchmark Costa Rica 346.738 362.710 −4 20,748.0 20,748.0 0 Nonbenchmark h Cuba 0.322 ... ... ... 68.2 ... Nonbenchmark Dominican Republic 19.449 21.716 −10 2,119.3 2,119.3 0 Nonbenchmark Ecuador 0.526 0.550 −4 79.8 76.8 4 Benchmark El Salvador 0.503 0.545 −8 23.1 23.1 0 Nonbenchmark Guatemala 3.626 5.138 −29 371.3 371.3 0 Nonbenchmark Haiti 19.108 25.340 −25 297.7 297.7 0 Nonbenchmark Honduras 9.915 10.688 −7 335.0 335.0 0 Nonbenchmark Nicaragua 8.919 9.637 −7 216.1 216.1 0 Nonbenchmark Panama 0.547 0.567 −4 31.3 31.3 0 Nonbenchmark Paraguay 2,227.340 2,708.237 −18 105,203.2 108,794.6 −3 Benchmark Peru 1.521 1.668 −9 497.8 497.8 0 Benchmark (continued) Comparison of ICP 2011 Results with 2011 Results Extrapolated from ICP 2005 279 Table I.1 (Continued) PPP (US$ = 1.000) Expenditure in national currency unit (billions) ICP 2005 Percentage Percentage benchmark or Economy ICP 2011 WDI difference ICP 2011 WDI difference nonbenchmark a (00) (01) (02) (03) (04) (05)a (06) (07) Uruguay 15.282 17.706 −14 896.8 896.8 0 Benchmark Venezuela, RB 2.713 3.671 −26 1,357.5 1,357.5 0 Benchmark Total (17) n.a. n.a. n.a. n.a. n.a. n.a. n.a. CARIBBEAN Anguilla 2.077 ... ... 0.8 ... ... Nonbenchmark Antigua and Barbuda 1.731 1.768 −2 3.0 3.0 3 Nonbenchmark Aruba 1.260 ... ... 4.6 4.6 0 Nonbenchmark Bahamas, The 0.949 0.705 35 7.9 7.9 0 Nonbenchmark Barbados 2.017 1.185 70 8.7 8.7 0 Nonbenchmark Belize 1.150 1.244 −8 3.0 3.0 0 Nonbenchmark Bermuda 1.564 ... ... 5.6 5.6 0 Nonbenchmark i Bonaire ... ... ... 0.2 ... ... Nonbenchmark Cayman Islands 0.959 ... ... 2.7 ... ... Nonbenchmark Curaçao 1.292 ... ... 5.4 ... ... Nonbenchmark Dominica 1.861 1.467 27 1.3 1.3 1 Nonbenchmark Grenada 1.783 1.957 −9 2.1 2.2 −5 Nonbenchmark Jamaica 54.122 ... ... 1,241.8 1,239.8 0 Nonbenchmark Montserrat 1.943 ... ... 0.2 ... ... Nonbenchmark St. Kitts and Nevis 1.803 2.085 −14 2.0 1.9 4 Nonbenchmark St. Lucia 1.844 1.681 10 3.3 3.4 −4 Nonbenchmark St. Vincent and the Grenadines 1.691 1.600 6 1.8 1.9 −2 Nonbenchmark Sint Maarten 1.379 ... ... 1.7 ... ... Nonbenchmark Suriname 1.826 3.233 −44 14.3 14.3 0 Nonbenchmark Trinidad and Tobago 3.938 4.389 −10 150.9 150.9 0 Nonbenchmark Turks and Caicos Islands 1.100 ... ... 0.7 ... ... Nonbenchmark Virgin Islands, British 1.076 ... ... 0.9 ... ... Nonbenchmark Total (22) n.a. n.a. n.a. n.a. n.a. n.a. n.a. WESTERN ASIA Bahrain 0.211 0.301 −30 10.9 10.9 0 Benchmark c Egypt, Arab Rep. 1.625 2.671 −39 1,371.1 1,371.1 0 Benchmark Iraq 516.521 1,026.903 −50 191,652.9 223,677.0 −14 Benchmark Jordan 0.293 0.561 −48 20.5 20.5 0 Benchmark Kuwait 0.172 0.318 −46 44.3 44.3 0 Benchmark Oman 0.192 0.331 −42 26.9 26.9 0 Benchmark Qatar 2.419 3.650 −34 624.2 624.2 0 Benchmark Saudi Arabia 1.837 3.041 −40 2,510.6 2,510.7 0 Benchmark d Sudan 1.224 1.941 −37 186.6 170.7 9 Benchmark 280 Purchasing Power Parities and the Real Size of World Economies Table I.1 (Continued) PPP (US$ = 1.000) Expenditure in national currency unit (billions) ICP 2005 Percentage Percentage benchmark or Economy ICP 2011 WDI difference ICP 2011 WDI difference nonbenchmark a (00) (01) (02) (03) (04) (05)a (06) (07) United Arab Emirates 2.544 3.567 −29 1,280.2 1,280.2 0 Nonbenchmark West Bank and Gaza 2.189 ... ... 35.0 ... ... Nonbenchmark Yemen, Rep. 75.818 125.914 −40 6,714.9 7,217.4 −7 Benchmark Total (12) n.a. n.a. n.a. n.a. n.a. n.a. n.a. SINGLETONS Georgia 0.859 1.002 −14 24.3 24.3 0 Benchmark Iran, Islamic Rep. 4,657.463 5,968.997 −22 6,121,004.0 5,609,930.0 9 Benchmark Total (2) n.a. n.a. n.a. n.a. n.a. n.a. n.a. WORLDj (179) n.a. n.a. n.a. n.a. n.a. n.a. n.a. Source: ICP, http://icp.worldbank.org/. Note: n.a. = not applicable; ... data suppressed because of incompleteness. a. Data source: World Development Indicators (WDI), World Bank; data as of April 2014. b. The Arab Republic of Egypt participated in both the Africa and Western Asia regions. The results for Egypt from each region were averaged by taking the geometric mean of the PPPs, allowing Egypt to be shown in each region with the same ranking in the world comparison. c. WDI data were released in a different currency unit, and they were converted to the same currency as ICP 2011 for comparison purposes. d. Sudan participated in both the Africa and Western Asia regions. The results for Sudan from each region were averaged by taking the geometric mean of the PPPs, allowing Sudan to be shown in each region with the same ranking in the world comparison. e. The results presented in the table are based on data supplied by all the participating economies and compiled in accordance with ICP principles and the procedures recommended by the 2011 ICP Technical Advisory Group. The results for China are estimated by the 2011 ICP Asia and the Pacific Regional Office and the Global Office. The National Bureau of Statistics of China does not recognize these results as official statistics. f. The Russian Federation participated in both the Commonwealth of Independent States (CIS) and Eurostat-Organisation for Economic Co-operation and Development (OECD) comparisons. The PPPs for Russia are based on the Eurostat-OECD comparison. They were the basis for linking the CIS comparison to the ICP. g. Eurostat-OECD provides data directly to WDI from their PPP program. Thus the figures for Eurostat-OECD economies are not based on the WDI extrapolation method. h. The official GDP of Cuba for the reference year 2011 is 68,990.15 million in national currency. However, this number and its breakdown into main aggregates are not shown in the table because of methodological comparability issues. Therefore, Cuba’s results are provided only for the PPP and price level index. In addition, Cuba’s figures are not included in the Latin America and world totals. i. Bonaire’s results are provided only for the individual consumption expenditure by households. Therefore, to ensure consistency across the tables, Bonaire is not included in the Caribbean total or the world total. j. This table does not include the Pacific Islands and does not double count the dual participation economies: the Arab Republic of Egypt, Sudan, and the Russian Federation. Comparison of ICP 2011 Results with 2011 Results Extrapolated from ICP 2005 281 Appendix J ICP 2011 Data Access and Archiving Policy This appendix outlines the elements of the data community would press for greater access to access and archiving policy of the 2011 more detailed data in subsequent ICP rounds. International Comparison Program (ICP), as In the face of the mounting demands for approved by the 2011 ICP Executive Board. more detailed data, the ICP Executive Board These elements include the objectives, guiding agreed that ICP 2011 should provide access to principles, and procedures for data access and such data while respecting confidentiality con- archiving. straints and data quality limitations. To increase the quality and utility of the data collected, the 2011 ICP round should also focus on collecting, CONTEXT archiving, and providing access to metadata. The ICP compiles the large amounts of price data and detailed national accounts expenditure DATA ACCESS OBJECTIVES data submitted by its participating economies. The resulting ICP databases are put to various The overall objective of ICP’s data access policy statistical and analytical uses by policy makers is that data derived from the ICP be utilized to the and researchers at international, regional, and maximum extent possible for statistical and analytical national agencies and ministries, as well as at purposes. Specifically, the objective is to provide universities and research centers. This rich data users with access to detailed data beyond what set is an important contributor to the value of was accessible through ICP 2005 as follows: the ICP. In the 2005 ICP round, the data access and 1. Purchasing power parities (PPPs), price level archiving policy strongly limited access to indexes (PLIs), and expenditure data for all detailed ICP data (that is, data below the basic economies are being published at the ana- heading level for each economy). For example, lytical level, with the supporting metadata. to access price data at the product level, users For ICP 2011 data, the analytical level is the could only gain access in regions where memo- level of detail (that is, aggregates, categories, randa of understanding between regional coor- groups, and classes) that the Global Office, dinating agencies and economies preventing Organisation for Economic Co-operation and data sharing had not been drafted. By the end of Development (OECD), Eurostat, and regional the 2005 round, it was clear that the user coordinating agencies agree to publish. 283 2. PPPs, PLIs, and expenditure data for all 4. Transparency. The principles and procedures economies at various levels of detail below for access to detailed ICP data, as well as the the published level (that is, categories, uses of these data, should be transparent groups, and classes not included above as and publicly available. well as basic headings) are available to data 5. Consistency. The principles and procedures users, with the supporting metadata. for data access should strive to be consistent 3. National average price data for all economies across all regions and economies, with a at the product level for items on the global view toward promoting equality in the core list, with the supporting metadata and treatment of all economies. measures of quality, are available to data 6. Reciprocity. Reciprocity between participat- users, except when the confidentiality of ing economies should be established to respondents is jeopardized. the maximum extent possible. All partici- 4. National average price data for all economies pating economies are automatically con- at the product level for regional items not on sidered to be approved users of ICP data. the global core list, with the supporting Nonparticipating economies are not consid- metadata and measures of quality, are avail- ered to be approved users of ICP data, but able to data users, except when the confiden- they may apply for access to these data fol- tiality of respondents is jeopardized. lowing the procedures highlighted shortly. 5. Subnational data and individual price obser- 7. Reliability. Releases of ICP data should be vations, with the supporting metadata, are accompanied by the appropriate metadata, available where permitted by the laws of including metadata that describe the qual- individual economies, as long as the confi- ity limitations of the data. dentiality of respondents is protected. 8. Quality limitations. Users of ICP data should The availability of individual economy data be informed of the quality limitations, and must respect legislation and policies that protect they should agree that the data are still use- respondent confidentiality. Such protections ful for their purposes. may place restrictions on public access to data, 9. Serviceability. ICP data should be archived to especially at the finer levels of detail. ensure that they can be used to service future approved requests for access to data, that they are available for possible use in GUIDING PRINCIPLES future ICP rounds, and that they are avail- The following guiding principles support the able as backup in case these data are lost objective of greater data access: through a disaster or other reasons by a region or an economy. 1. Appropriate use. Data should be made avail- able for analytical, research, and statistical 10. Disclosure limitations. Users accessing detailed purposes. Users should not misuse data by ICP data should publish the detailed data attempting to deduce the underlying confi- only when the data are accompanied by a dential data. statement of the data’s quality. 2. Equality of access. ICP data are a public good 11. Promotion of uses. To promote the use of ICP and thus should be made available on an data, users are encouraged to share their equal basis to anyone who wants to use feedback and research findings with all them, in the same way that most national stakeholders, consistent with the disclosure statistical offices make data available to users. limitations in this policy. 3. Preservation of microdata confidentiality. 12. Limitations on users’ findings. Indicators com- Provision of data should be consistent with puted by users based on ICP data are not legal and other arrangements that ensure the considered part of the official publications confidentiality of respondents. program of the ICP. 284 Purchasing Power Parities and the Real Size of World Economies 13. Ease of access. Data access procedures should The data to be archived by DECDG will be ensure a simple and expedited process for treated with confidentiality. The data will be access to ICP data. archived in a secure database with limited access rights and administered by a designated data custodian. Access to the data (or any portions of PROCEDURES FOR DATA ARCHIVING the data) will be subject to the procedures high- lighted in the next section. The procedures for archiving data for the ICP 2011–related variables are as follows: 1. PPPs, PLIs, and expenditure data for all econ- PROCEDURES FOR DATA ACCESS omies are published at the analytical level The procedures for accessing data for the ICP (that is, aggregates, categories, groups, and 2011–related variables are as follows: classes), with the supporting metadata. They are archived by the World Bank Development 1. PPPs, PLIs, and expenditure data for all Economics Data Group (DECDG) and also by economies at the analytical level, with the the regional coordinating agencies. supporting metadata, will be published in ICP reports electronically and in paper for- 2. PPPs, PLIs, and expenditure data at various mat. They will also be available for down- levels of detail below the published level (that loading from an online database. is, categories, groups, and classes not included in procedure 1, as well as basic headings) for 2. PPPs, PLIs, and expenditure data at various all economies, with the supporting metadata, levels of detail below the published level for are archived by DECDG and also by the rel- all economies, with the supporting metadata, evant regional coordinating agencies. can be accessed by users through an applica- tion process administered by DECDG. 3. National average price data at the product level for items on the global core list for all 3. National average price data at the product economies, with the supporting metadata level for items on the global core list for all and measures of quality, are archived by economies, with the supporting metadata DECDG and also by the relevant regional and measures of quality, can be accessed by coordinating agencies. users through an application process administered by DECDG, consistent with the 4. National average price data at the product participating economy’s confidentiality laws level for regional items not on the global and processes. An economy should inform core list for all economies, with the support- the relevant regional coordinator which ing metadata and measures of quality, are average prices are considered confidential archived by DECDG and also by the rele- and thus cannot be released. The regional vant regional coordinating agencies. coordinator will in turn inform the Global Office. Product names and descriptions will 5. Participating economies are responsible for be rendered anonymous before sharing them archiving their subnational data and indi- with users—that is, brand names will vidual price observations, with the support- be suppressed. ing metadata. However, some economies may ask DECDG or the relevant regional 4. National average price data at the product coordinating agency to archive these data level for regional items not on the global core and observations because they do not have list for all economies, with the supporting their own facilities for archiving them. If an metadata and measures of quality, can be economy asks DECDG or the relevant accessed by users through an application regional coordinating agency to archive process administered by DECDG, consistent these data, the data should be encrypted and with the participating economy’s confidenti- the economy in question should hold the ality laws and processes. An economy should encryption key. inform the relevant regional coordinator ICP 2011 Data Access and Archiving Policy 285 which average prices are considered confi- An outline of the information required by this dential and thus cannot be released. The application is available on the ICP website.1 regional coordinator will in turn inform the The director of DECDG decides whether to Global Office. Product names and descrip- approve requests, in line with the access policy tions will be rendered anonymous before agreed on by the ICP Executive Board. The sharing them with users—that is, brand director may also seek other expert advice names will be suppressed. before making a final decision on applications. Alternatively, users may approach the regional 5. Access to subnational data and individual coordinating agencies for access to the regional price observations, with the supporting meta- data (regional PPPs, expenditure data, and aver- data, is restricted in general. However, users age prices). In this case, the regional coordinat- may address applications of access to these ing agencies follow the access policy agreed on data directly to the economies in question. by the Executive Board. The release of regional Applying for access to the ICP 2011–related data does not require clearance from DECDG. variables listed in procedures 2, 3, and 4 is initiated by the user with a written and signed application addressed to the director of the 1 http://siteresources.worldbank.org/ICPINT/Resources/270056- Development Data Group at the World Bank. 1255977254560/121120_ICPDataAccessPrinciples&Procedures.pdf. 286 Purchasing Power Parities and the Real Size of World Economies Appendix K ICP Revision Policy The motivation for developing a revision policy rounds. And, third, for each benchmark round for the International Comparison Program some economies are added and others may (ICP) is user interest in comparing the latest drop out or shift from one region to another. ICP results with those from subsequent bench- Such changes affect comparisons between mark rounds. economies because the multilateral results will For its benchmark rounds, the ICP pub- differ, depending on the economies included lishes indicators for all participating econo- and their ICP grouping. In addition, the mies that include: (1) real expenditures and national accounts in virtually all economies real expenditures per capita; (2) purchasing are revised over time as additional data become power parities (PPPs) and price level indexes available. For example, the 2005 estimates of (PLIs); and (3) nominal expenditures and the expenditures related to the GDP and its nominal expenditures per capita. Indicators major components have been revised in most are published at the analytical level—that is, economies since the ICP 2005 results were the level of detail (gross domestic product released in December 2007. Indeed, in 22 [GDP] and major components and categories) economies these revisions were in excess of at which the Global Office, Organisation for 10 percent. Analogous problems arise with Economic Co-operation and Development revisions to population estimates. (OECD), Eurostat, and regional coordinating The ICP benchmarks produce a onetime agencies agree to publish data from the ICP snapshot of ICP indicators, whereas the World benchmark rounds. Results at various levels of Bank’s World Development Indicators data- detail below the published level—down to the base produces a time series of ICP indicators basic heading level—for all economies are on an annual basis for nonbenchmark years, available to researchers through the data beginning with 1980. These interim esti- access process stipulated in the ICP data access mates are computed on the basis of an extrap- and archiving policy (see appendix J). olation method. Comparing results from ICP benchmarks is This appendix summarizes the ICP policy that complicated by three significant factors. First, defines how ICP indicators are revised. It ICP benchmark rounds are designed to provide describes the triggers and guidelines for revising a onetime “snapshot” of ICP indicators. Second, ICP indicators, as well as the timing of revisions the collection and estimation methodologies and the steps to be taken to communicate these for some components are improved between revisions to users. 287 TRIGGERS FOR REVISING ICP INDICATORS GUIDELINES FOR REVISING ICP INDICATORS Revisions in input data Historical revisions • Revisions in aggregate GDP estimates trigger a • The World Bank assumes that historical esti- revision of real expenditures and real expen- mates of country prices and exchange rates ditures per capita and nominal expenditures used in the ICP benchmarks will remain and nominal expenditures per capita. unchanged. • Revisions in major components of GDP trigger a • Revisions triggered by changes in an econo- revision of real expenditures and real my’s national accounts estimates may require expenditures per capita and nominal expen- a revision of the time series of ICP indicators— ditures and nominal expenditures per cap- including benchmark data—going back his- ita. It may also trigger a revision of PPPs torically as far as necessary to incorporate the and PLIs. changes in the economy’s national accounts time series. For example, revisions in a coun- • Revisions in population figures trigger a revision try’s GDP from 2004 to 2011 would trigger a of real expenditures per capita and nominal revision in the real expenditures and real expenditures per capita. expenditures per capita of the ICP 2005 • Changes in economies’ currency units trigger a benchmark. However, if the revisions spanned revision of real expenditures and real expen- 2006 through 2011, the ICP 2005 benchmark ditures per capita, PPPs, PLIs, and nominal data would not be revised. expenditures and nominal expenditures • Revisions triggered by a new benchmark ICP per capita. methodology should not go beyond the last • Release of new results from regional nonbench- benchmark. For example, ICP 2011 uses an mark exercises may trigger a revision of global- improved global linking method, so revisions level results related to real expenditures and could be carried out for the last benchmark real expenditures per capita, PPPs, and PLIs indicators (2005) but not for the previous for nonbenchmark years. benchmark indicators (1993–96). • Correction of errors in source data or results may trigger a revision of real expenditures and Geographical scope real expenditures per capita, PPPs, PLIs, and • It is desirable to introduce revisions first to nominal expenditures and nominal expendi- regional benchmark indicators and then to tures per capita. global benchmark indicators in order to pre- serve the consistency between the regional and global data sets. Revised within-region New methodology PPPs will be the input to estimation of the • Materially improved PPP computation and aggre- between-region linking factors needed to gation methods trigger a revision of real expen- determine global-level PPPs. ditures and real expenditures per capita, PPPs, and PLIs. • The World Bank is responsible for revis- ing benchmark indicators at the global • Materially improved global linking approach trig- level (that is, denominated in the global gers a revision of real expenditures and real numéraire currency). expenditures per capita, PPPs, and PLIs. • If a particular region does not revise its • Materially improved extrapolation method trig- regional benchmark indicators, the World gers a revision of real expenditures and real Bank will revise and publish global bench- expenditures per capita, PPPs, and PLIs for mark indicators to take into account any revi- nonbenchmark years. sion in other regions. 288 Purchasing Power Parities and the Real Size of World Economies • Results of regional interim exercises may Quality review be incorporated in the time series of ICP • Revised ICP indicators should go through an indicators if the results are deemed of suf- expert review before they are published to ficient quality by the World Development ensure data quality. Indicators team. • The World Bank will maintain a database containing the various vintages of data for Fixity quality purposes. • Revised global benchmark results should respect, to the extent possible, regional Publication of revised results price fixity—the convention whereby the price relativities established between econo- • Revised ICP indicators should be published mies in a regional comparison are retained once they have been compiled and have when the economies are included in the undergone the quality review process. global comparison. • Revised ICP indicators should be released at the analytical level of the benchmark results, as established in the ICP data access and Classification level archiving policy (see appendix J). • PPPs could be revised at various classification levels (GDP, major components, categories, Consistency between published and unpublished groups, or classes), depending on the level of data sets detail of the national accounts expenditure revisions. For example, revised expenditures • The World Bank provides researchers with a at the class level would result in revisions to detailed data set from benchmark ICP exer- higher-level PPP aggregates (GDP, major cises, as stipulated in the ICP data access and components, categories, and groups) through archiving policy. This data set includes real the aggregation process. expenditures and real expenditures per capita, PPPs, PLIs, and nominal expenditures and nominal expenditures per capita at all levels, Categories of indicators down to the basic heading level. When revis- ing ICP indicators, the ICP may need to revise • Real expenditures and real expenditures per this unpublished detailed data set in order capita will be revised when the national to maintain the consistency between the accounts expenditure data or population data published and the unpublished data sets. For are revised. example, if a revision of nominal expendi- • PPPs and PLIs may be revised, depending on tures and nominal expenditures per capita is the level of detail of the national accounts triggered, it may be desirable to reflect it at all expenditure revisions. When economies levels—down to that of the basic heading— revise their expenditure data for major depending on the World Bank’s assessment of components, categories, groups, classes, or the need to do so. basic headings, then PPPs (and the result- ing PLIs) may be revised at levels above the lowest level for which expenditures TIMING AND COMMUNICATION OF were revised. REVISIONS • Nominal expenditures and nominal expenditures • The time series of ICP indicators will be per capita will be revised when the national revised by the World Bank on an annual basis accounts expenditure data or population as part of the World Development Indicators data are revised. April update. ICP Revision Policy 289 • The schedule of revisions will be announced • Results will be made publicly available on to stakeholders and users well in advance. the Internet, ICP portal, and all other rele- vant sites. • When a methodology is improved, the new method will be communicated to users well in advance. 290 Purchasing Power Parities and the Real Size of World Economies Glossary accounting period. The period to which esti- and expenditure classes for which the results mates of GDP refer, usually a calendar year or of a comparison are published. a quarter. For ICP comparisons of GDP, the average test for volumes. A test that requires accounting period is a calendar year. the volume index for an aggregate to lie actual individual consumption. The total between the smallest and the largest of its value of the individual consumption expen- component volume indexes. ditures of households, nonprofit institutions base country invariance. The property serving households, and general government. whereby the relativities between the PPPs, It is a measure of the individual goods and price level indexes, and volume indexes of services that households actually consume as economies are not affected by either the opposed to what they actually purchase. choice of national currency as numéraire or additive. An aggregation method is additive if, the choice of reference economy. for each economy being compared, it pro- basic heading. The lowest aggregation level in vides real expenditures for aggregates that are the ICP expenditure classification. In theory, a equal to the sum of the real expenditures of basic heading is defined as a group of similar their constituent basic headings. An additive well-defined goods or services. In practice, it aggregation method provides real expendi- is defined by the lowest level of final expen- tures that satisfy the average test for volumes diture for which explicit expenditure weights but are subject to the Gerschenkron effect. can be estimated. Thus an actual basic head- aggregate. A set of transactions related to a ing can cover a broader range of products specified flow of goods and services in a given than is theoretically desirable and include accounting period, such as the total pur- both goods and services. It is at the level of chases of consumer goods and services by the basic heading that expenditures are resident households or the total expenditure defined and estimated, products are selected on collective services by government or the for pricing, prices are collected and validated, total value of gross fixed capital formation. and PPPs are first calculated and averaged. aggregation. The process of weighting and basic price. The amount received by the pro- averaging basic heading PPPs to obtain PPPs ducer from the purchaser for a unit of good for each level of aggregation up to GDP. or service produced as output. It includes analytical categories. GDP, main aggregates, subsidies on products and other taxes on pro- expenditure categories, expenditure groups, duction. It excludes taxes on products, other 291 subsidies on production, the supplier’s retail that are expected to appreciate or at least and wholesale margins, and separately not decline in real value, that do not dete- invoiced transport and insurance charges. riorate over time in normal conditions, and Basic prices are the prices most relevant for that are acquired and held primarily as decision making by suppliers (producers). stores of value. bias. A systematic error in a PPP or volume characteristics. The technical parameters and index. Bias can arise for a number of rea- price-determining properties of a product sons, including failure to respect importance, listed in a product specification. comparability, or consistency; the price Classification of the Functions of collection and measurement procedures Government (COFOG). Classification of followed; and the calculation and aggrega- transactions by general government, includ- tion formula employed. ing outlays on the final consumption expen- bilateral or binary comparison. A price or diture, intermediate consumption, gross fixed volume comparison between two econo- capital formation, and capital and current mies that draws on data only for those transfers, by function or purpose. A major two economies. use of COFOG is to identify which final con- bilateral or binary PPP. A PPP between two sumption expenditures of general govern- economies calculated using only the prices ment benefit households individually and and weights for those two economies. which benefit households collectively. bridge economy. An economy that provides Classification of Individual Consumption the link or bridge between two or more sepa- According to Purpose (COICOP). rate comparisons involving different groups of Classification of the individual consumption economies. The bridge economy participates expenditures of three institutional sectors— in all comparisons and by doing so enables the households, nonprofit institutions serving economies in one comparison to be compared households (NPISHs), and general with the economies in the other comparisons. government—by the ends that they wish to An alternative to linking groups of economies achieve through these expenditures. Individual through bridge economies is to combine them consumption expenditures are those that are using core products. made for the benefit of individual households. All final consumption expenditures by house- change in inventories. The acquisition less holds and NPISHs are defined as individual, disposals of stocks of raw materials, semifin- but only the final consumption expenditures ished goods, and finished goods that are held by general government on individual services by producer units prior to being further pro- are treated as individual. cessed or sold or otherwise used. Semifinished goods cover work in progress (partially com- collective consumption expenditure by pleted products whose production process government. The final consumption expen- will be continued by the same producer in a diture of general government on collective subsequent accounting period), including the services. It is a measure of the services that natural growth of agricultural crops prior to general government provides to the com- harvest and the natural growth in livestock munity as a whole and that households raised for slaughter. Inventories also cover all consume collectively. Also called actual col- raw materials and goods stored by govern- lective consumption. ment as strategic reserves. collective services. Services provided by change in valuables. The acquisition less dis- general government that benefit the com- posals of valuables. Valuables are defined as munity as a whole: general public services, produced assets such as nonmonetary gold, defense, public order and safety, economic precious stones, antiques, paintings, sculp- affairs, environmental protection, and hous- tures, and other art objects that are not used ing and community amenities. They also primarily for production or consumption, include the overall policy-making, planning, 292 Purchasing Power Parities and the Real Size of World Economies budgetary, and coordinating responsibilities component. A subset of goods or services or of government ministries overseeing indi- both that make up some defined aggregate. vidual services and government research consistency. The requirement that the prices and development for individual services. collected by economies be consistent with These activities cannot be identified with the prices underlying their estimates of specific individual households and are con- GDP and its component expenditures. In sidered to benefit households collectively. most cases, this means that they should be comparability. The requirement that econo- national annual purchasers’ prices for mies price products that are identical or, if actual market transactions. The basis of a not identical, equivalent. Products are said to comparison is an identity, expenditure = be comparable if they have identical or price × volume, and volumes are obtained equivalent technical parameters and price- by dividing expenditures by prices. Using determining properties. Equivalent means prices that do not correspond to those that they meet the same needs with equal used to derive the expenditures would efficiency so that purchasers are indifferent result in volumes that are either underesti- between them and are not prepared to pay mated or overestimated. more for one than for the other. The pricing consumption of fixed capital. The reduction of comparable products ensures that the dif- in the value of the fixed assets used in pro- ferences in prices between economies for a duction during the accounting period result- product reflect actual price differences and ing from physical deterioration, normal are not affected by differences in quality. If obsolescence, or normal accidental damage. differences in quality are not avoided or cor- rected, they can be mistaken for apparent core product. A product that appears on the price differences leading to an underestima- product lists of two or more separate groups tion or overestimation of price levels and of economies for the purpose of combining an overestimation or underestimation of the groups in a single multilateral compari- volume levels. son. The use of core products is an alterna- comparison-resistant. A term first used to tive to linking groups of economies through describe nonmarket services that are difficult bridge economies. to compare across economies because they country aggregation with redistribution have no economically significant prices with (CAR) procedure. A means of obtaining for which to value outputs, their units of output a specified aggregate global volumes and PPPs cannot be otherwise defined and measured, for economies within each region that retain the institutional arrangements for their provi- the relativities established between the econ- sion and the conditions of payment differ omies in the regional comparison. In other from economy to economy, and their quality words, each region’s results for the aggregate varies between economies but the differences remain fixed when linked with the results of cannot be identified and quantified. other regions. The procedure is as follows. Increasingly, the term is being used to describe The global basic heading PPPs for all econo- construction and market services such as tele- mies in the comparison are aggregated to the communications, whose complexity, varia- level of the aggregate. The global PPPs for the tion, and economy specificity make it difficult aggregate are used to calculate global real to price them comparably across economies. expenditures for each economy, with which compensation of employees. All payments in the total global real expenditure on the cash and in kind made by employers to aggregate for each region can be determined. employees in return for work carried out dur- The total global real expenditure of each ing the accounting period. These payments region is redistributed across the economies comprise gross wages and salaries in cash and in the region in line with the distribution of in kind, employers’ actual social contribu- the real expenditures in the regional com- tions, and imputed social contributions. parison. Global PPPs for economies are Glossary 293 calculated indirectly with the redistributed or not the product is important. The assump- global real expenditure. tion is that the ratio of price levels for impor- country product dummy (CPD) method. tant and less important products is the same The multilateral method used to obtain tran- for all products within a basic heading. In sitive PPPs at the basic heading level through theory, the ratio should be less than 1 because regression analysis. It treats the calculation of less important products are expected to be PPPs as a matter of statistical inference— more expensive than important products. that is, an estimation problem rather than an deflation. The division of the current value of index number problem. The underlying an aggregate by a price index—the deflator— hypothesis is that, apart from random distur- in order to value its volumes at the prices of bance, the PPPs for individual products within the price reference period. a basic heading are all constant between any Dikhanov editing procedure. The iterative given pair of economies. In other words, it is intereconomy validation procedure devel- assumed that the pattern of the relative prices oped by Yuri Dikhanov to edit the average of the different products within a given basic survey prices reported by economies. It can be heading is the same in all economies. It is also viewed as an alternative or as a complement assumed that each economy has its own to the Quaranta editing procedure. Both pro- overall price level for the basic heading, and cedures provide similar measures of price that this overall price level fixes the levels of variation for products and economies employ- absolute prices of the products in the basic ing either basic heading PPPs for editing basic heading for the economy. By treating the headings individually or PPPs for an aggregate prices observed in the economies for the basic for editing across the basic headings constitut- heading as random samples, the PPPs between ing the aggregate. In practice, the Quaranta each pair of economies and the common pat- procedure is employed to edit prices within tern of relative prices can be estimated using basic headings, and the Dikhanov procedure classical least square methods. The method is used to edit prices within aggregates. The allows the estimation of sampling errors for Dikhanov procedure is specific to the country the PPPs. product dummy (CPD)–based methods of cal- country product dummy-weighted (CPD-W) culating PPPs, whereas the Quaranta table method. A variant of the country product has a broader application that includes Gini- dummy method in which important prod- Èltetö-Köves-Szulc (GEKS)–based methods as ucts receive a higher weight in the calcula- well as CPD-based methods. tion than less important products. For Dikhanov table. The intereconomy valida- example, important products could have a tion table generated by the Dikhanov editing weight of 2 or 3 and less important products procedure. a weight of 1. The choice of weights is arbi- trary as it is in the Gini-Éltetö-Köves-Szulc* economically significant price. A price that (GEKS*) method. However, the weight of 1 has a significant influence on the amounts for an important product and 0 for a less producers are willing to supply and on the important product used in the GEKS* amounts purchasers wish to buy. This is the method cannot be used in a weighted CPD basic price for producers and the purchasers’ because the assignment of 0 to prices of less price for purchasers. important products will remove them from economic territory. The geographical territory the calculation. In ICP 2011, important of an economy plus any territorial enclaves in products were given a weight of 3 and less the rest of the world. By convention, it important products a weight of 1. includes embassies, military bases, and ships country product representativity dummy and aircraft abroad. The economic territory (CPRD) method. A variant of the country does not include extraterritorial enclaves— product dummy (CPD) method that has an that is, the parts of the economy’s own geo- additional dummy variable to denote whether graphical territory used by government 294 Purchasing Power Parities and the Real Size of World Economies agencies of other economies or by interna- Fisher-type PPP. The PPP for a basic heading tional organizations under international trea- or an aggregate between two economies that ties or agreements between states. is defined as the geometric mean of the editing. The first step of validation, which Laspeyres-type PPP and the Paasche-type PPP entails scrutinizing data for errors. It is the for the basic heading or the aggregate. See process of checking survey prices for non- Laspeyres-type PPP and Paasche-type PPP sampling errors by identifying those prices (their formulation depends on whether they that have extreme values—that is, prices are being used to calculate basic heading PPPs whose value is determined to be either too or to aggregate basic heading PPPs). high or too low vis-à-vis the average accord- fixity. The convention whereby the relativities ing to certain criteria. The price may score a between a group of economies that were value for a given test that exceeds a prede- established in a comparison covering just that termined critical value, or its value may fall group of economies remain unchanged, or outside some prespecified range of accept- fixed, when the economies of the group are able values. Both are standard ways of included in comparisons with a wider group detecting errors in survey data, and both are of economies. For example, the price and employed by the ICP. Prices with extreme volume relativities of the ICP regions and values are not necessarily wrong. But the Eurostat-OECD remain unchanged in the fact that their values are considered extreme global comparison. If fixity were not observed, suggests that they could be wrong. They are there would be two sets of relativities for the possible errors, and as such they need to be participating economies that would not nec- investigated to establish whether they are essarily be in agreement because the relativi- actual errors. ties and ranking of economies can change as employers’ actual social contributions. the composition of the group of economies Payments actually made by employers to being compared changes. Fixity ensures that social security funds, insurance enterprises, participating economies have only one set of or autonomous pension funds for the benefit results to explain to users. of their employees. free on board (f.o.b.) value. The price of a error. The difference between the observed good delivered at the customs frontier of the value of a PPP or volume index and its correct exporting economy. It includes the freight value. Errors may be random or systematic. and insurance charges incurred to that point Random errors are generally called errors; and any export duties or other taxes on systematic errors are called biases. exports levied by the exporting economy. exhaustiveness. The extent to which an econ- Geary-Khamis (GK) method. An average omy’s estimate of GDP covers all economic price aggregation method for computing PPPs activity in its economic territory. and real expenditures above the basic head- ing level. It entails valuing a matrix of quanti- expenditure weight. The share of the expen- ties using a vector of international prices. The diture on a basic heading in nominal GDP. vector is obtained by averaging national prices final consumption expenditure. The expen- across participating economies after they have diture on goods and services consumed been converted to a common currency with by individual households or the community PPPs and weighted by economy quantity to satisfy their individual or collective needs shares. The economy PPPs are obtained by or wants. averaging the ratios of national and interna- financial intermediation services indi- tional prices weighted by economy expendi- rectly measured (FISIM). An indirect ture shares. The international prices and the measure of the value of the financial inter- PPPs are defined by a system of interrelated mediation services that financial institutions linear equations that must be solved simulta- provide clients but for which they do not neously. The GK method produces PPPs that charge explicitly. are transitive and real expenditures that are Glossary 295 additive. One of its disadvantages is that a numbers are made transitive and multilateral change in the composition of the group can while respecting characteristicity (the prop- alter significantly the international prices as erty in which the resulting multilateral well as the relationships between economies. indexes differ as little as possible from the Another is that the real expenditures are sub- original binary indexes). The procedure is ject to the Gerschenkron effect, which can be independent of the method used to calculate large. GK results are considered better suited the intransitive binary indexes. But as used in to the analysis of price and volume structures the current literature, GEKS covers both the across economies. way in which the intransitive binary PPPs are general government. The institutional sector calculated and the procedure used to make that consists of federal, central, regional, them transitive and multilateral. state, and local government units together The intransitive binary PPPs for a basic with the social security funds imposed and heading or an aggregate are obtained by cal- controlled by those units. It includes non- culating first a matrix of Laspeyres-type PPPs profit institutions engaged in nonmarket pro- and then a matrix of Paasche-type PPPs, and duction that are controlled and mainly finally by taking the geometric mean of the financed by government units or social secu- two, a matrix of Fisher-type PPPs. The Fisher- rity funds. type PPPs are made transitive and multilat- Gerschenkron effect. An effect applicable eral by applying the GEKS procedure, which only to aggregation methods that use either a involves replacing the Fisher-type PPP reference price structure, whereby each between each pair of economies with the economy’s quantities are valued by a uniform geometric mean of itself squared and all the set of prices to obtain volumes, or a reference corresponding indirect Fisher-type PPPs volume structure, whereby each economy’s between the pair obtained using the other prices are used to value a uniform set of economies as bridges. The resulting GEKS quantities to obtain PPPs. For methods PPPs provide real expenditures that are not employing a reference price structure, an subject to the Gerschenkron effect and that economy’s share of total GDP—that is, the are not additive. GEKS results are considered total for the group of economies being better suited to comparisons across econo- compared—will rise as the reference price mies of the price and volume levels of indi- structure becomes less characteristic of its vidual basic headings or aggregates. See own price structure. For methods employing Laspeyres-type PPP and Paasche-type PPP a reference volume structure, an economy’s (their formulation depends on whether they share of total GDP will fall as the reference are being used to calculate basic heading PPPs volume structure becomes less characteristic or to aggregate basic heading PPPs). of its own volume structure. The Gerschenkron global core product. A product priced for the effect arises because of the negative correla- specific purpose of providing a link or overlap tion between prices and volumes. between regional comparisons at the basic Gini-Èltetö-Köves-Szulc (GEKS) method. A heading level in order to combine them in a method to calculate PPPs for basic headings single world comparison. For ICP 2011, lists or to aggregate basic heading PPPs to obtain of global core products were compiled for PPPs for each level of aggregation up to GDP. consumer goods and services, government There are two versions of the GEKS at the services, and capital goods by the Global basic heading level: one that takes account of Office in consultation with the regions, par- the importance of the products priced and ticipating economies, and subject matter one that does not. The version that takes the experts. Regions selected products from the importance of products into consideration is global core product lists and added them to referred to as GEKS* in the literature. their regional product lists in line with prod- Strictly speaking, the GEKS is a procedure uct availability and importance in their whereby any set of intransitive binary index region. The global core products priced by the 296 Purchasing Power Parities and the Real Size of World Economies regions were included in the regional com- employees before the deduction of taxes and parisons as well as the world comparison. social contributions payable by employees. goods. Physical objects for which a demand household. A small group of persons who share exists, over which ownership rights can be the same living accommodation, who pool established, and whose ownership can be some or all of their income and wealth, and transferred from one institutional unit to who consume certain types of goods and ser- another by engaging in transactions on the vices collectively, mainly food and housing. A market. They are in demand because they household can consist of only one person. may be used to satisfy the needs or wants of Iklé method. An average price aggregation households or the community or used to pro- method similar to the Geary-Khamis (GK) duce other goods or services. method. It was used in the 2005 ICP regional government final consumption expendi- comparison for Africa. Like the GK method, it ture. The actual and imputed final consump- derives a vector of international prices by tion expenditure incurred by general averaging national prices across participating government on individual goods and services economies after the prices have been con- and collective services. It is the total value of verted to a common currency with PPPs and the individual consumption expenditure and weighted. The GK method uses quantity collective consumption expenditure by gen- shares as weights, whereas the Iklé method eral government. uses expenditure shares as weights. In addi- tion, GK international prices are arithmetic gross capital formation. The total value of means, while Iklé international prices are har- gross fixed capital formation, changes in monic means. The Iklé method is designed to inventories, and acquisitions less disposals prevent prices in economies with large expen- of valuables. ditures from dominating the average prices. gross domestic product (GDP). When esti- Because the sum of expenditure shares in each mated from the expenditure side, GDP is economy is equal to one, the Iklé method can defined as the total value of the final con- be regarded as equi-representative of all econ- sumption expenditures of households, non- omies. The Iklé method produces PPPs that are profit institutions serving households, and transitive and real expenditures that are addi- general government plus gross capital forma- tive. Compared with the GK method, the Iklé tion plus the balance of exports and imports. method minimizes the Gerschenkron effect. gross fixed capital formation. The total value importance. A concept that is defined in terms of acquisitions less disposals of fixed assets of a specific economy within a basic heading. by resident institutional units during the A product is either important or less impor- accounting period, plus the additions to tant in the economy for the given basic head- the value of nonproduced assets realized by ing. An important product is one that accounts the productive activity of resident institu- for a significant share of the expenditure on tional units. the basic heading in the economy in ques- gross operating surplus. The surplus or defi- tion. Formerly, important products were cit accruing from production before taking called representative products. into account (1) consumption of fixed capi- imputed expenditure. Some transactions that tal by the enterprise; (2) any interest, rent, are desirable to include in GDP do not take or similar charges payable on financial or place in money terms and so cannot be mea- tangible nonproduced assets borrowed or sured directly. Expenditures on these non- rented by the enterprise; or (3) any interest, monetary transactions are obtained by rent, or similar charges receivable on finan- imputing a value to them. The values to be cial or tangible nonproduced assets owned imputed are defined by national accounting by the enterprise. conventions. These vary from case to case gross wages and salaries. The wages and sala- and are described in the System of National ries in cash and in kind paid by enterprises to Accounts (SNA). Glossary 297 imputed rent. Owner-occupiers use the Because most final consumption expendi- dwelling they own and occupy to produce tures of NPISHs are individual, all final con- housing services for themselves. Thus they sumption expenditures of NPISHs are treated are in effect renting the dwelling to them- by convention as individual. selves and the value of the rent has to be individual good or service. A consumption imputed. The imputed rent should be valued good or service acquired by a household and at the estimated rent a tenant pays for a used to satisfy the needs and wants of mem- dwelling of the same size and quality in a bers of that household. comparable location with similar neighbor- hood amenities. When markets for rented individual services. A term used to describe accommodation are virtually nonexistent or the services (and goods) provided to individ- unrepresentative, the value of the imputed ual households by nonprofit institutions rent has to be derived by some other objec- serving households and by general govern- tive procedure such as the user cost method. ment. Such services include housing, health, recreation and culture, education, and imputed social contributions. The imputa- social protection. They do not include the tions that have to be made when employers overall policy-making, planning, budgetary, provide social benefits directly to their and coordinating responsibilities of the gov- employees, former employees, or dependents ernment ministries overseeing individual out of their own resources without involving services. Nor do they include government an insurance enterprise or autonomous pen- research and development for individual ser- sion fund and without creating a special fund vices. These activities are considered to ben- or segregated reserve for the purpose. efit households collectively and are therefore indirect binary comparison. A price or vol- classified under collective services. ume comparison between two economies input price approach. The approach used to made through a third economy. For example, obtain PPPs for nonmarket services. Because for economies A, B, and C, the PPP between there are no economically significant prices A and C is obtained by dividing the PPP with which to value the outputs of these between A and B by the PPP between C and services, national accountants follow the con- B so that PPPA/C = PPPA/B/PPPC/B. vention of estimating the expenditures on individual consumption expenditure by nonmarket services by summing the costs of government. The actual and imputed the inputs required to produce them. PPPs for final consumption expenditure incurred by nonmarket services are calculated using input general government on individual goods prices because these are the prices that are and services. consistent with the prices underlying the esti- individual consumption expenditure by mated expenditures. In practice, prices are households. The actual and imputed final only collected for labor, which is by far the consumption expenditure incurred by resi- largest and most important input. dent households on individual goods and institutional sector. The System of National services. Includes expenditures on individual Accounts identifies five institutional sectors: goods and services sold at prices that are not nonfinancial corporations, financial corpora- economically significant. By definition, all tions, general government, households, and final consumption expenditures of house- nonprofit institutions serving households. holds are for the benefit of individual house- intereconomy validation. The validation that holds and are individual. takes place after participating economies individual consumption expenditure by have completed their intra-economy valida- nonprofit institutions serving house- tion and submitted their survey prices to the holds (NPISHs). The actual and imputed regional coordinator. It is an iterative process final consumption expenditure incurred by consisting of several rounds of questions and NPISHs on individual goods and services. answers between the regional coordinator and 298 Purchasing Power Parities and the Real Size of World Economies participating economies. It involves editing reference economy is economy A and the and verifying the average survey prices weights are those of economy A. At the basic reported by participating economies for a basic heading level, the PPP is defined as a quasi- heading and assessing the reliability of the weighted geometric average of the price rela- PPPs they produce for the basic heading. The tives between economy B and economy A objective is to establish that the average sur- for the important products of economy A. At vey prices are for comparable products, that the aggregate level, the PPP is defined as the the products have been accurately priced, and weighted arithmetic average of the PPPs that the allocation of importance indicators is between economy B and economy A for correct. In other words, it seeks to ascertain the basic headings covered by the aggregate. whether economies have interpreted the The expenditure shares of economy A are product specifications in the same way and used as weights. whether their price collectors have priced market price. The amount of money a willing them without error. The Quaranta and buyer pays to acquire a good or service from Dikhanov editing procedures are employed a willing seller—that is, the actual price for a for this purpose. Both procedures entail transaction agreed to by the transactors. It is detecting outliers among the average survey the net price inclusive of all discounts, sur- prices by identifying outliers among the cor- charges, and rebates applied to the transac- responding price ratios. Economies verify the tion. Also called the transaction price. outliers found in order to ascertain whether material well-being. The volume of goods and they are valid observations. If they are not, the services that households consume to satisfy economy either corrects or suppresses them. their individual needs. intermediate consumption. The value of the Model Report on Expenditure Statistics goods and services, other than fixed assets, (MORES). A set of worksheets designed to that are used or consumed as inputs by a pro- help economies participating in a compari- cess of production. son break down their expenditure on GDP intra-economy validation. The validation for the reference year to the basic head- that precedes intereconomy validation. It is ing level and, at the same time, docu- undertaken by participating economies prior ment how each basic heading expenditure to submitting their survey prices to the was estimated. regional coordinator. Each economy edits multilateral comparison. A price or volume and verifies its own prices without reference comparison of more than two economies to the price data of other economies. simultaneously that is made with price and Validation is carried out at the product level. expenditure data from all economies covered The objective is to establish that price collec- and that produces consistent relations among tors within the economy have priced items all pairs of participating economies—that is, that match the product specifications and one that satisfies the transitivity requirement, that the prices they have reported are accu- among other requirements. rate. This entails an economy searching for outliers first among the individual prices that national annual price. A price that has been have been collected for each product it has averaged both over all localities of an econ- chosen to survey and then among the aver- omy in order to take into account the regional age prices for these products. Subsequently, variations in prices and over the whole of the the economy verifies the outliers found in reference year in order to allow for seasonal order to ascertain whether they are valid variations in prices as well as general inflation observations. If they are not, the economy and changes in price structures. either corrects or suppresses them. net taxes on production. Taxes less subsidies Laspeyres-type PPP. A PPP for a basic head- on production. ing or an aggregate between two economies, nominal expenditure. An expenditure that economy B and economy A, where the is valued at national price levels. It can be Glossary 299 expressed in national currencies or in a com- Paasche-type PPP. A PPP for a basic heading or mon currency to which it has been converted an aggregate between two economies, econ- with exchange rates. It reflects both volume omy B and economy A, where the reference and price differences between economies. economy is economy A and the weights are nonmarket service. A service that is provided those of economy B. At the basic heading level, to households free or at a price that is not the PPP is defined as a quasi-weighted geomet- economically significant by nonprofit institu- ric average of the price relatives between tions serving households or by general economy B and economy A for the important government. products of economy B. At the aggregate level, the PPP is defined as the weighted harmonic nonobserved economy. Activities that are hid- average of the PPPs between economy B and den because they are illegal or because they economy A for the basic headings covered by are legal but carried out clandestinely or the aggregate. The expenditure shares of econ- because they are undertaken by households omy B are used as weights. for their own use. These activities also include those that are missed because of deficiencies in Penn effect. The overstatement of the eco- the statistical system. Such deficiencies include nomic size of high-income economies with out-of-date survey registers, surveys whose high price levels and the understatement of reporting thresholds are too high or that have the economic size of low-income economies high rates of nonresponse, poor survey editing with low price levels that result when procedures, and lack of surveys of informal exchange rate–converted GDPs are used to activities such as street trading. establish the relative sizes of economies. It arises because exchange rates do not take nonprofit institution serving households into account price level differences between (NPISH). A nonprofit institution that is not economies when used to convert their GDPs predominantly financed and controlled by to a common currency. government, that provides goods or ser- vices to households free or at prices that are price approach. The approach whereby the not economically significant, and whose price comparison between two or more main resources are voluntary contributions economies is made by comparing the prices by households. for a representative sample of comparable products. PPPs are generally derived using numéraire currency. The currency unit the price approach. selected to be the common currency in which PPPs and real and nominal expendi- price error. An error that arises when price tures are expressed. collectors price products that match the product specification, but record the price observation. An individual price, or one of a incorrectly or record the price correctly and number of individual prices, collected for an error is introduced afterward in the process item at an outlet. of reporting and transmitting the price. A outlet. A shop, market, service establishment, price error can also arise because the quan- internet site, mail order service, or other tity priced is recorded incorrectly (or error is place from where goods or services can be introduced later during processing). Thus purchased and from where the purchasers’ when the price collected is standardized and or list prices of the products sold can adjusted to a reference quantity, it will not be obtained. be correct. outlier. A term generally used to describe any price level index (PLI). PLIs are the ratios of extreme value in a set of survey data. Can PPPs to exchange rates. They provide a mea- also mean an extreme value that has been sure of the differences in price levels between verified as being correct. economies by indicating for a given aggrega- Paasche-Laspeyres spread. The ratio of the tion level the number of units of the common Paasche-type index to the Laspeyres-type currency needed to buy the same volume index in a binary comparison. of the aggregation level in each economy. 300 Purchasing Power Parities and the Real Size of World Economies At the level of GDP, they provide a measure brand and model is stipulated—or generic— of the differences in the general price levels that is, a specification in which only the of economies. relevant price-determining and techni- price measure. Price measures are the PPPs and cal characteristics are given and no brand the price level indexes to which they give rise. is designated. price relative. The ratio of the price of an indi- purchaser’s price. The amount paid by the vidual product in one economy to the price of purchaser in order to take delivery of a unit the same product in some other economy. It of a good or service at the time and place shows how many units of currency A must required by the purchaser. It excludes any be spent in economy A to obtain the same value added tax (or similar deductible tax on quantity and quality—that is, the same products) that purchasers can deduct from volume—of the product that X units of cur- their own VAT liability with respect to the rency B purchase in economy B. VAT invoiced to their customers. It includes suppliers’ retail and wholesale margins, sepa- product. A good or service that is the result of rately invoiced transport and insurance production. Products are exchanged and used charges, and any VAT (or similar deductible for various purposes—as inputs in the pro- tax on products) that purchasers cannot duction of other goods and services, for final deduct from their own VAT liability. For consumption, or for investment. equipment goods, it would also include the product error. An error that occurs when price installation costs if applicable. The purchas- collectors price products that do not match er’s price is the price most relevant for deci- the product specification and neglect to report sion making by buyers. having done so. They may not have been purchasing power parity (PPP). Spatial aware of the mismatch, such as when the deflator and currency converter that elimi- product specification is too loose, or they may nates the effects of the differences in price have priced a substitute product as required levels between economies, thereby allowing by the pricing guidelines but failed to men- volume comparisons of GDP and GDP com- tion that they had done so on the price ponent expenditures. reporting form. PPPs are calculated in three stages: (1) for productivity adjustment. An adjustment individual products, (2) for groups of products made to the prices paid by nonmarket pro- or basic headings, and (3) for groups of basic ducers for labor, capital, and intermediate headings or aggregates. The PPPs for individ- inputs so that they correspond to a common ual products are the ratios of national prices level of multifactor productivity. In practice, in national currencies for the same good or it is an adjustment made to the prices (com- service. The PPPs for basic headings are the pensation of employees) paid by nonmarket unweighted averages of the PPPs for individ- producers for labor so that they represent the ual products. And the PPPs for aggregates are same level of labor productivity. the weighted averages of the PPPs for basic product list. The common list of well-defined headings. The weights used are the expendi- goods and services from which economies tures on the basic headings. participating in a comparison make a selec- At all stages, PPPs are price relatives. They tion of products to price for the purpose of show how many units of currency A need to compiling PPPs. be spent in economy A to obtain the same product specification. A list of the physical volume of a product or a basic heading or an and economic characteristics that can be aggregate that X units of currency B pur- used to identify a product selected for pric- chases in economy B. In the case of a single ing, thereby ensuring that economies price product, the same volume means an identi- comparable items. A product specification cal volume. But in the case of the complex can be either brand- and model-specific— assortment of goods and services that make that is, a specification in which a particular up an aggregate such as GDP, the same Glossary 301 volume does not mean an identical basket of Quaranta table. The intereconomy validation goods and services. The composition of the table generated by the Quaranta editing basket will vary among economies according procedure. to their economic, social, and cultural differ- real expenditure. An expenditure that has ences, but each basket will provide equiva- been converted to a common currency lent satisfaction or utility. and valued at a uniform price level with quality adjustment. An adjustment to the PPPs. It reflects only volume differences prices of a product whose characteristics are between economies. broadly similar but not the same in all econo- reference economy. The economy, or group mies pricing it. The aim of the adjustment of economies, for which the value of the is to remove from the price differences PPP is set at 1.00 and the value of the price observed between economies that part of the level index and of the volume index is set difference due to the difference in the charac- at 100. teristics of the product priced. The adjustment is made so that the price differences between reference PPP. The PPP used for a basic head- economies reflect only pure price differences. ing for which no prices are collected and no PPP is calculated. It is based on prices col- quantity approach. The approach whereby a lected for other basic headings and serves as a volume comparison between two or more proxy for the missing PPP. economies is made by comparing the vol- umes of a representative sample of compara- reference quantity. The quantity to which the ble products. Volume comparisons are not prices collected for a product must be rebased usually made directly, but indirectly by divid- to ensure that they refer to the same quantity ing the expenditure ratios between econo- when being compared. mies by their corresponding price ratios. reference year. The calendar year to which the Quaranta editing procedure. The iterative results of the comparison refer. intereconomy validation procedure proposed resident population. The average number of by Vincenzo Quaranta that is used to edit the people present in the economic territory of average survey prices reported by economies an economy during the reference year. for a basic heading. For each basic heading covered by a price survey, the procedure seasonal product. A product for which both screens the average survey prices for possible prices and the quantities sold vary signifi- errors and evaluates the reliability of the cantly throughout the year. Typically, the pat- price ratios they provide. It does this by com- tern of variation is repeated from one year to paring the average survey prices for the same the next. Seasonal products vary from econ- product across economies (the average sur- omy to economy. vey prices are expressed in the same currency services. Outputs produced to order and that unit for this purpose) and by analyzing the cannot be traded separately from their pro- dispersion of the price ratios across econo- duction. Ownership rights cannot be estab- mies and across products (the price ratios are lished over services, and by the time their standardized for this purpose). It is thus both production is completed they must have been an editing tool and an analytical tool. As an provided to the consumers. An exception to editing tool, it identifies among the average this rule is a group of industries, generally survey prices outliers that have to be returned classified as service industries, some of whose to the participating economies for verifica- outputs have the characteristics of goods. tion. As an analytical tool, it provides a range These industries are those concerned with of variation coefficients—at the product, the provision, storage, communication, and economy, and basic heading levels—that can dissemination of information, advice, and be used to assess the reliability of completed entertainment in the broadest sense of those price surveys and assist the planning of future terms. The products of these industries, where price surveys. ownership rights can be established, may be 302 Purchasing Power Parities and the Real Size of World Economies classified as either goods or services, depend- services (that is, taxes payable per unit of ing on the medium by which these outputs good or service produced, such as excise are supplied. duties and a nondeductible value added social transfers in kind. Individual goods and tax) as well as taxes that resident enter- services provided as transfers in kind to indi- prises may pay as a consequence of engag- vidual households by government units ing in production (such as, payroll taxes (including social security funds) and nonprofit and taxes on motor vehicles). The former institutions serving households (NPISHs). The are called taxes on products; the latter are goods and services can be purchased on the called other taxes on production. market or produced as nonmarket output by transitivity. The property whereby the direct government units or NPISHs. PPP between any two economies yields the structured product description (SPD). A same result as an indirect comparison via any tool designed to standardize the product other economy. For example, for economies specifications for different types of products A, B, and C, the ratio of the PPP between A so that all product specifications for a particu- and B and the PPP between C and B is equal lar type of product are defined in the same to the PPP between A and C so that PPPA/C = way and specify the same parameters. PPPA/B/PPPC/B. Standardizing product specifications helps to user cost method. The method of estimating improve their precision, making it easier for the value of imputed rentals for owner- price collectors to determine whether a prod- occupiers by summing the relevant cost uct in an outlet matches the product speci- items: intermediate consumption (current fied. Also, by identifying the parameters that maintenance and repairs, insurance), con- need to be specified for different products, sumption of fixed capital, other taxes on pro- SPDs provide a framework within which duction, and net operating surplus (nominal economies can present their proposals for rate of return on the capital invested in the new products. dwelling and land). subsidies on production. Subsidies on goods value added tax (VAT). A tax on products col- and services produced as outputs by resident lected in stages by enterprises. This wide- enterprises that become payable as a result of ranging tax is usually designed to cover most the production of these goods or services or all goods and services. Producers are (that is, subsidies payable per unit of good or obliged to pay the government only the dif- service produced) as well as subsidies that ference between the VAT on their sales and resident enterprises may receive as a conse- the VAT on their purchases for intermediate quence of engaging in production (e.g., sub- consumption or capital formation. The VAT is sidies to reduce pollution or to increase not usually levied on exports. employment). The former are called subsidies on products; the latter are called other subsi- verification. The second step of validation, dies on production. which entails investigating the possible errors detected during the editing of survey symmetric index. An index that treats the two prices to establish whether they are actual economies being compared symmetrically by errors and, if they are actual errors, correct- giving equal importance to the price and ing or suppressing them. In many cases, expenditure data of both economies. The verification will require revisiting the out- price and expenditure data for both econo- lets where the prices were collected to mies enter into the index number formula in determine whether what was priced matches a balanced or symmetric way. the product description and whether the taxes on production. Taxes on the goods correct price and quantity were recorded. and services produced as outputs by resi- Price observations found to be incorrect dent enterprises that become payable as a should be either eliminated or replaced by result of the production of these goods or the correct observation. Glossary 303 volume index. A weighted average of the rela- importance as measured by their values in tive levels in the quantities of a specified set of one or both economies. goods and services between two economies. volume measure. Volume measures are the The quantities have to be homogeneous, and real expenditures, the real expenditures per the relative levels for the different goods and capita, and the volume indexes to which they services must be weighted by their economic give rise. 304 Purchasing Power Parities and the Real Size of World Economies References Commission of the European Communities, International Comparisons of Gross Product and Purchasing Power. Monetary Fund, Organisation for Economic Washington, DC: World Bank. Co-operation and Development, United Nations, and McCarthy, Paul, and Fred Vogel. 2014. “Understanding World Bank. 1993. System of National Accounts 1993. Changes in Methodology between the 2005 and 2011 https://unstats.un.org/unsd/nationalaccount International Comparison Programs.” Paper pre- /sna1993.asp. sented at 10th meeting of the ICP Executive Board, Deaton, Angus. 2013. “Calibrating Measurement Washington, DC, January 24. Uncertainty in Purchasing Power Exchange Rates.” OECD (Organisation for Economic Co-operation and Paper presented at seventh meeting of the ICP Development) and Eurostat. 2012. Eurostat-OECD Technical Advisory Group, Washington, DC, Methodological Manual on Purchasing Power Parities. September 17–18. Luxembourg: Publications Office of the European Deaton, A., and A. H. Heston. 2008. “Understanding Union. PPPs and PPP-based National Accounts.” NBER United Nations Statistics Division. 1998. Central Working Paper No. 14499, National Bureau of Product Classification, Version 1.0. New York: United Economic Research, Cambridge, MA. Nations. Eurostat. 1996. European System of Accounts 1995. ———. 1999a. “Classification of Individual Consumption Luxembourg: Publications Office of the European According to Purpose (COICOP).” Classification of Union. Expenditure According to Purpose. New York: United Heston, Alan. 2013. “Government Services: Productivity Nations. Adjustments.” In Measuring the Real Size of the World ———. 1999b. “Classification of the Functions of Economy: The Framework, Methodology, and Results of the Government (COFOG).” Classification of Expenditure International Comparison Program (ICP). Washington, According to Purpose. New York: United Nations. DC: World Bank. World Bank. 2008. Global Purchasing Power Parities and Inklaar, Robert, and Marcel P. Timmer. 2013. Real Expenditures: 2005 International Comparison “Productivity Adjustment for Government Services Program. http://siteresources.worldbank.org/ICPINT PPPs: Alternatives and Proposal for ICP 2011.” /Resources/icp-final.pdf. Groningen Growth and Development Centre, ———. 2013. Measuring the Real Size of the World Economy: University of Groningen, September. The Framework, Methodology, and Results of the Kravis, Irving B., Alan Heston, and Robert Summers. International Comparison Program (ICP). Washington, 1978. International Comparisons of Real Product and DC: World Bank. Purchasing Power. Baltimore: Johns Hopkins University ———. Forthcoming. Operational Guidelines and Procedures Press. for Measuring the Real Size of the World Economy: 2011 ———. 1982. World Product and Income: International International Comparison Program. Washington, DC: Comparisons of Real Gross Product. Baltimore: Johns World Bank. Hopkins University Press. World Health Organization. 2008. International Kravis, Irving B., Zoltan Kenessey, Alan Heston, and Classification of Diseases, 10th Revision. http://www.who Robert Summers. 1975. A System of International .int/classifications/icd/en/. 305 ECO-AUDIT Environmental Benefits Statement The World Bank is committed to pre- Saved: serving endangered forests and natu- • 19 trees ral resources. The Publishing and • 9 million British Knowledge Unit has chosen to print thermal units of Purchasing Power Parities and the Real total energy Size of World Economies on recycled • 1,655 pounds of net paper with 100 percent postconsumer greenhouse gases fiber in accordance with the recom- • 8,975 gallons of mended standards for paper usage set waste water by the Green Press Initiative, a nonprofit • 937 pounds of solid program supporting publishers in using waste fiber that is not sourced from endan- gered forests. For more information, visit www.greenpressinitiative.org.