87946 The world by income Low ($1,035 or less) Classified according to Lower middle ($1,036–$4,085) World Bank estimates of 2012 GNI per capita Upper middle ($4,086–$12,615) High ($12,616 or more) No data World Development 2014 Indicators © 2014 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 govern- ments they represent. The World Bank does not guarantee the accuracy of the data included in this work. 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Other photos: Page xviii © Liang Qiang/The World Bank. Used with permission; further permission required for reuse. Page 26 © Arne Hoel/The World Bank. Used with permission; further permission required for reuse. Page 42 © Nahuel Berger/The World Bank. Used with permission; further permission required for reuse. Page 56 © Maria Fleischmann/The World Bank. Used with permission; further permission required for reuse. Page 70 © Roy Witlin/The World Bank. Used with permission; further permission required for reuse. Page 84 © Mai Ky/The World Bank. Used with permission; further permission required for reuse. Preface In 2013 the World Bank Group announced that it trends; and a table of the most relevant and popular would focus on two overarching measurable goals: indicators for that theme, together with a discussion ending extreme poverty by 2030 and promoting of indicator compilation methodology. shared prosperity. The chance to end poverty in a This printed edition, and its companion The Little generation is an unprecedented opportunity—and one Data Book 2014, presents a subset of the data col- that requires data to monitor progress, to understand lected in World Development Indicators; an index to the complexities of development, and to manage the the full list of available indicators is at the end of effective delivery of programs and services. each section. Many additional relevant indicators are World Development Indicators 2014 provides a com- available online, in database and tabular formats, and pilation of relevant, high-quality, and internationally through applications for web and mobile devices, at comparable statistics about global development and http://data.worldbank.org/wdi. Online applications the fight against poverty. It is intended to help users of also provide the indicator description and footnotes in all kinds—policymakers, students, analysts, profes- several languages, including Arabic, Chinese, French, sors, program managers, and citizens—find and use and Spanish. data related to all aspects of development, includ- World Development Indicators is the result of a col- ing those that help monitor and understand progress laborative effort of many partners, including the United toward the two goals. Nations family, the International Monetary Fund, the Six themes are used to organize indicators—world International Telecommunication Union, the Organ- view, people, environment, economy, states and mar- isation for Economic Co-operation and Development, kets, and global links. As in past editions, World view the statistical offices of more than 200 economies, reviews global progress toward the Millennium Devel- and countless others. I am extremely grateful to them opment Goals (MDGs) and provides key indicators all—and especially to government statisticians around related to poverty. A complementary online data analy- the world. Without their hard work, professionalism, sis tool is available this year to allow readers to further and dedication, measuring and monitoring trends in investigate global, regional, and country progress on global development, and advancing toward the new the MDGs: http://data.worldbank.org/mdgs. Each of World Bank goals, would not be possible. the remaining sections includes an introduction; six I welcome your suggestions to improve the useful- stories highlighting specific global, regional, or country ness of World Development Indicators. Haishan Fu Director Development Economics Data Group World Development Indicators 2014 iii Acknowledgments This book was prepared by a team led by William The choice of indicators and text content was Prince under the management of Neil Fantom and shaped through close consultation with and sub- comprising Azita Amjadi, Maja Bresslauer, Liu Cui, stantial contributions from staff in the World Bank’s Federico Escaler, Mahyar Eshragh-Tabary, Juan Feng, four thematic networks—Sustainable Development, Masako Hiraga, Wendy Ven-dee Huang, Bala Bhas- Human Development, Poverty Reduction and Eco- kar Naidu Kalimili, Haruna Kashiwase, Buyant Erdene nomic Management, and Financial and Private Sector Khaltarkhuu, Tariq Khokar, Elysee Kiti, Ibrahim Levent, Development—and staff of the International Finance Hiroko Maeda, Maurice Nsabimana, Leila Rafei, Evis Corporation and the Multilateral Investment Guaran- Rucaj, Umar Serajuddin, Rubena Sukaj, Emi Suzuki, tee Agency. Most important, the team received sub- Jomo Tariku, and Rasiel Victor Vellos, working closely stantial help, guidance, and data from external part- with other teams in the Development Economics Vice ners. For individual acknowledgments of contributions Presidency’s Development Data Group. to the book’s content, see Credits. For a listing of our World Development Indicators electronic products key partners, see Partners. were prepared by a team led by Soong Sup Lee and com- Communications Development Incorporated pro- prising Ying Chi, Jean-Pierre Djomalieu, Ramgopal Era- vided overall design direction, editing, and layout, led belly, Shelley Fu, Omar Hadi, Gytis Kanchas, Siddhesh by Jack Harlow, Bruce Ross-Larson, and Christopher Kaushik, Ugendran Machakkalai, Nacer Megherbi, Shan- Trott. Elaine Wilson created the cover and graphics mugam Natarajan, Parastoo Oloumi, Manish Rathore, and typeset the book. Peter Grundy, of Peter Grundy Ashish Shah, Atsushi Shimo, and Malarvizhi Veerappan. Art & Design, and Diane Broadley, of Broadley Design, All work was carried out under the direction of Hai- designed the report. Staff from The World Bank’s Pub- shan Fu. Valuable advice was provided by Poonam lishing and Knowledge Division oversaw printing and Gupta, Zia M. Qureshi, and David Rosenblatt. dissemination of the book. iv World Development Indicators 2014 Table of contents Preface iii Introduction MDG 1 Eradicate extreme poverty Acknowledgments iv MDG 2 Achieve universal primary education MDG 3 Promote gender equality and Partners vi empower women MDG 4 Reduce child mortality User guide xii MDG 5 Improve maternal health MDG 6 Combat HIV/AIDS, malaria, and other diseases MDG 7 Ensure environmental sustainability MDG 8 Develop a global partnership for 1. World view 1 development Targets and indicators for each goal World view indicators 2. People 27 About the data Online tables and indicators Poverty indicators 3. Environment 43 About the data 4. Economy 57 5. States and markets 71 Introduction Highlights Table of indicators 6. Global links 85 About the data Online tables and indicators Primary data documentation 99 Statistical methods 110 Credits 113 World Development Indicators 2014 v Partners Defining, gathering, and disseminating international and interpretation of statistical indicators. All these statistics is a collective effort of many people and contributors have a strong belief that available, accu- organizations. The indicators presented in World rate data will improve the quality of public and private Development Indicators are the fruit of decades of decisionmaking. work at many levels, from the field workers who The organizations listed here have made World administer censuses and household surveys to the Development Indicators possible by sharing their data committees and working parties of the national and and their expertise with us. More important, their col- international statistical agencies that develop the laboration contributes to the World Bank’s efforts, and nomenclature, classifications, and standards funda- to those of many others, to improve the quality of life mental to an international statistical system. Non- of the world’s people. We acknowledge our debt and governmental organizations and the private sector gratitude to all who have helped to build a base of have also made important contributions, both in gath- comprehensive, quantitative information about the ering primary data and in organizing and publishing world and its people. their results. And academic researchers have played For easy reference, web addresses are included for a crucial role in developing statistical methods and each listed organization. The addresses shown were carrying on a continuing dialogue about the quality active on March 1, 2014. vi World Development Indicators 2014 Front ? User guide World view People Environment International and government agencies Carbon Dioxide Information International Analysis Center Diabetes Federation http://cdiac.ornl.gov www.idf.org Centre for Research on the International Epidemiology of Disasters Energy Agency www.emdat.be www.iea.org Deutsche Gesellschaft für International Internationale Zusammenarbeit Labour Organization www.giz.de www.ilo.org Food and Agriculture International Organization Monetary Fund www.fao.org www.imf.org Internal Displacement International Telecommunication Monitoring Centre Union www.internal-displacement.org www.itu.int International Civil Joint United Nations Aviation Organization Programme on HIV/AIDS www.icao.int www.unaids.org Economy States and markets Global links Back World Development Indicators 2014 vii Partners National Science United Nations Centre for Foundation Human Settlements, Global Urban Observatory www.nsf.gov www.unhabitat.org The Office of U.S. Foreign United Nations Disaster Assistance Children’s Fund www.globalcorps.com/ofda.html www.unicef.org Organisation for Economic United Nations Conference on Co-operation and Trade and Development Development www.oecd.org www.unctad.org Stockholm International United Nations Department of Peace Research Institute Economic and Social Affairs, Population Division www.sipri.org www.un.org/esa/population Understanding United Nations Department of Children’s Work Peacekeeping Operations www.ucw-project.org www.un.org/en/peacekeeping United Nations United Nations Educational, Scientific, and Cultural Organization, Institute for Statistics www.un.org www.uis.unesco.org viii World Development Indicators 2014 Front ? User guide World view People Environment United Nations Upsalla Conflict Environment Programme Data Program www.unep.org www.pcr.uu.se/research/UCDP United Nations Industrial World Bank Development Organization www.unido.org http://data.worldbank.org United Nations World Health Organization International Strategy for Disaster Reduction www.unisdr.org www.who.int United Nations Office on World Intellectual Drugs and Crime Property Organization www.unodc.org www.wipo.int United Nations Office World Tourism of the High Commissioner Organization for Refugees www.unhcr.org www.unwto.org United Nations World Trade Population Fund Organization www.unfpa.org www.wto.org Economy States and markets Global links Back World Development Indicators 2014 ix Partners Private and nongovernmental organizations Center for International Earth International Institute for Science Information Network Strategic Studies www.ciesin.org www.iiss.org Containerisation International International Road Federation www.ci-online.co.uk www.irfnet.ch DHL Netcraft www.dhl.com http://news.netcraft.com x World Development Indicators 2014 Front ? User guide World view People Environment PwC World Economic Forum www.pwc.com www.weforum.org Standard & World Resources Poor’s Institute www.standardandpoors.com www.wri.org World Conservation Monitoring Centre www.unep-wcmc.org Economy States and markets Global links Back World Development Indicators 2014 xi User guide to tables World Development Indicators is the World Bank’s premier compilation of cross-country comparable data on develop- ment. The database contains more than 1,300 time series indicators for 214 economies and more than 30 country 4 Economy groups, with data for many indicators going back more Gross domestic product Gross savings Adjusted net savings Current account Central Central Consumer government government price index Broad money balance cash surplus debt or deficit than 50 years. average annual % growth Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP The 2014 edition of World Development Indicators Afghanistan 2000–12 .. 2012–13 .. 2013–14 .. 2012 .. 2012 .. 2012 .. 2012 –0.6 2012 .. 2012 5.7 2012 35.8 Afghanistan 9.4 3.1 3.5 –14.9 .. –35.5 –0.6 .. 7.2 31.9 offers a condensed presentation of the principal indica- Albania Algeria 5.0 3.7 1.3 2.8 2.1 3.3 14.5 47.5 –1.3 28.3 –10.4 6.0 –3.4 –0.3 56.6 .. 2.0 8.9 82.1 61.0 American Samoa .. .. .. .. .. .. .. .. .. .. tors, arranged in their traditional sections, along with Andorra Angola 5.9 11.8 .. 5.1 .. 8.0 .. 18.0 –25.2 .. .. 12.1 .. .. .. .. .. 10.3 34.9 .. Antigua and Barbuda 2.2 .. .. 24.9 .. –6.9 –1.4 .. 3.4 102.6 regional and topical highlights. Argentina Armenia 5.8a 7.6 5.0 3.2 2.8 5.0 21.9 11.7 10.1 –3.7 0.0 –11.1 .. –1.4 .. .. 10.0a 2.6 33.0 33.7 Aruba –0.1 .. .. .. .. –9.5 .. .. 0.6 68.3 Australia 3.1 .. .. 25.5 12.0 –3.7 –3.7 30.6 1.8 102.8 Austriab 1.7 .. .. 24.6 13.1 1.6 –2.2 75.3 2.5 .. Azerbaijan 14.8 4.9 5.3 41.9 15.9 22.5 6.1 6.4 1.1 31.1 World view People Environment Bahamas, The Bahrain 0.6 5.4 .. .. .. .. 8.4 19.5 .. –0.8 –18.4 9.7 –4.1 –0.5 47.9 35.6 2.0 2.8 76.6 74.1 Bangladesh 6.0 6.0 5.7 39.8 21.3 2.3 –0.9 .. 6.2 69.7 Barbados 1.2 .. .. 8.4 3.6 –4.9 –8.0 96.8 4.5 .. Belarus 7.5 1.0 1.5 31.5 19.7 –2.7 1.7 40.8 59.2 30.5 Belgiumb 1.4 .. .. 20.3 7.9 –2.0 –3.6 91.1 2.8 .. Economy States and markets Global links Belize 3.8 1.8 2.7 15.8 9.3 –1.3 –0.2 74.2 1.3 77.4 Benin 3.8 4.2 4.1 7.1 –5.2 –7.1 –1.4 .. 6.8 37.9 Bermuda 0.9 .. .. .. .. 14.1 .. .. .. .. Bhutan 8.7 7.6 8.1 44.5 23.7 –19.7 .. .. 10.9 61.2 Bolivia 4.2 5.3 4.7 25.7 5.5 7.9 .. .. 4.6 73.8 Bosnia and Herzegovina 3.8 0.8 2.0 14.5 .. –9.3 –1.2 .. 2.0 58.1 Botswana 4.2 4.6 4.9 40.7 33.2 –7.4 –1.9 .. 7.5 44.2 Brazil 3.7 2.2 2.4 14.8 4.3 –2.4 –2.6 52.8 5.4 80.8 Tables Brunei Darussalam Bulgaria 1.2 4.0 .. 0.6 .. 1.7 .. 21.7 .. 10.9 .. –1.4 .. –2.0 .. 15.4 0.5 3.0 65.9 79.6 Burkina Faso 5.9 7.0 7.0 22.9 8.5 –2.0 –3.2 .. 3.8 30.3 The tables include all World Bank member countries (188), Burundi Cabo Verde 3.6 6.7 4.3 2.6 4.5 2.9 17.5 35.0 –13.7 .. –10.3 –11.5 .. –9.0 .. .. 18.0 2.5 23.0 78.7 Cambodia 8.1 7.0 7.0 10.6 –7.5 –8.6 –4.4 .. 2.9 50.1 and all other economies with populations of more than Cameroon 3.3 4.8 5.0 15.8 –1.6 –3.8 .. .. 2.9 21.2 Canada 1.9 .. .. 23.6 13.0 –3.5 –1.3 53.8 1.5 .. 30,000 (214 total). Countries and economies are listed Cayman Islands Central African Republic .. 4.8 –18.0 .. –1.8 .. .. .. .. .. .. .. .. 0.7 .. .. .. 5.8 18.1 .. Chad 9.6 5.0 8.7 .. .. .. .. .. 10.2 11.9 alphabetically (except for Hong Kong SAR, China and Channel Islands Chile 0.5 4.1 .. .. .. .. .. 21.4 .. –0.2 .. –3.5 .. 1.3 .. .. .. 3.0 77.3 .. China 10.6 7.7 7.7 51.2 35.0 2.3 .. .. 2.7 187.6 Macao SAR, China, which appear after China). Hong Kong SAR, China Macao SAR, China 4.4 12.7 .. .. .. .. 28.3 57.4 .. .. 2.3 42.9 3.8 23.8 39.2 .. 4.1 6.1 335.3 107.6 Colombia 4.5 4.0 4.3 18.9 –3.2 –3.3 –1.1 62.6 3.2 42.9 The term country, used interchangeably with economy, Comoros Congo, Dem. Rep. 1.9 5.7 3.3 7.5 3.5 7.5 .. .. .. .. .. .. .. 3.8 .. .. 1.8 85.1 38.3 18.3 does not imply political independence but refers to any terri- 60 World Development Indicators 2014 Front ? User guide World view People Environment tory for which authorities report separate social or economic statistics. When available, aggregate measures for income and regional groups appear at the end of each table. Aggregate measures for income groups Aggregate measures for income groups include the 214 economies listed in the tables, plus Taiwan, China, when- ever data are available. To maintain consistency in the aggregate measures over time and between tables, miss- ing data are imputed where possible. Data presentation conventions • A blank means not applicable or, for an aggregate, not Aggregate measures for regions analytically meaningful. The aggregate measures for regions cover only low- and • A billion is 1,000 million. middle-income economies. • A trillion is 1,000 billion. The country composition of regions is based on the • Figures in blue italics refer to years or periods other World Bank’s analytical regions and may differ from com- than those specified or to growth rates calculated for mon geographic usage. For regional classifications, see less than the full period specified. the map on the inside back cover and the list on the back • Data for years that are more than three years from the cover flap. For further discussion of aggregation methods, range shown are footnoted. see Statistical methods. • The cutoff date for data is February 1, 2014. xii World Development Indicators 2014 Front ? User guide World view People Environment Classification of economies For operational and analytical purposes the World Bank’s main criterion for classifying economies is gross national Economy 4 income (GNI) per capita (calculated using the World Bank Gross domestic product Gross savings Adjusted net savings Current account Central Central Consumer government government price index Broad money Atlas method). Because GNI per capita changes over time, balance cash surplus debt or deficit average annual % growth the country composition of income groups may change Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP Congo, Rep. 2000–12 4.6 2012–13 5.6 2013–14 5.4 2012 .. 2012 .. 2012 .. 2012 .. 2012 .. 2012 3.9 2012 31.5 from one edition of World Development Indicators to the Costa Rica 4.7 3.4 4.3 15.9 15.1 –5.3 –3.5 .. 4.5 49.4 Côte d’Ivoire Croatia 1.2 2.1 8.7 .. 8.2 .. .. 18.9 9.3 .. 2.0 –0.3 –3.1 –4.7 .. .. 1.3 3.4 39.0 80.7 next. Once the classification is fixed for an edition, based Cuba 5.8 .. .. .. .. .. .. .. .. .. Curacao Cyprusb .. 2.6c .. .. .. .. .. 8.8c 3.9c .. .. –6.9 .. –6.3 .. 113.3 2.4 .. .. .. on GNI per capita in the most recent year for which data Czech Republic 3.3 .. .. 21.0 5.1 –2.4 –4.4 38.3 3.3 77.3 Denmark Djibouti 0.6 3.5 .. .. .. .. 23.6 .. 15.7 .. 5.9 .. –2.0 .. 50.6 .. 2.4 3.7 74.6 .. are available (2012 in this edition), all historical data pre- Dominica 3.2 1.1 1.7 10.8 .. –11.5 –11.9 .. 1.4 97.4 Dominican Republic Ecuador 5.6 4.4 2.5 4.0 3.9 4.1 9.2 26.9 6.1 .. –6.8 –0.2 –2.9 .. .. .. 3.7 5.1 34.3 31.6 sented are based on the same country grouping. Egypt, Arab Rep. 4.9 1.8 2.3 13.0 0.0 –2.7 –10.6 .. 7.1 74.1 El Salvador 2.0 1.9 2.3 8.9 6.6 –5.3 –2.2 47.8 1.7 44.6 Low-income economies are those with a GNI per capita Equatorial Guinea 10.9 .. .. .. .. .. .. .. 6.1 18.7 Eritrea Estoniab 0.9 3.7 6.0 .. 3.5 .. .. 25.0 12.5 .. .. –1.8 .. 1.0 .. 6.9 3.9 .. 114.7 59.6 of $1,035 or less in 2012. Middle-income economies are Ethiopia 8.9 7.0 7.2 28.8 6.1 –7.2 –1.4 .. 22.8 .. Faeroe Islands Fiji .. 1.2 .. 2.4 .. 2.1 .. .. .. .. .. –1.4 .. .. .. .. 3.4 .. 68.8 .. those with a GNI per capita of more than $1,035 but less Finlandb 1.7 .. .. 18.1 7.6 –1.5 –0.5 48.0 2.8 .. Franceb French Polynesia 1.1 .. .. .. .. .. 17.5 .. 9.9 .. –2.2 .. –5.1 .. 93.7 .. 2.0 .. .. .. than $12,616. Lower middle-income and upper middle- Gabon 2.4 4.2 4.2 .. .. .. .. .. 2.7 20.8 Gambia, The Georgia 3.4 6.5d 6.5 2.5d 7.5 6.3d 17.1 18.3d 0.9 7.0 d 6.4 –11.7 .. –0.5 .. 32.6 4.3 –0.9 53.6 30.2 income economies are separated at a GNI per capita of Germany b 1.1 .. .. 24.2 15.8 7.0 –0.4 55.3 2.0 .. Ghana Greeceb 6.6 1.1 7.4 .. 7.4 .. 21.5 9.8 2.7 –4.3 –11.7 –2.5 –3.9 –9.8 .. 106.5 9.2 1.5 31.3 .. $4,085. High-income economies are those with a GNI per Greenland 1.7 .. .. .. .. .. .. .. .. .. Grenada Guam 1.9 .. 1.1 .. 1.1 .. –10.2 .. .. .. –28.0 .. –5.8 .. .. .. 2.4 .. 95.4 .. capita of $12,616 or more. The 18 participating member Guatemala 3.5 3.3 3.4 12.0 –2.3 –2.6 –2.3 24.4 3.8 46.2 Guinea 2.6 4.0 4.7 –6.2 –42.8 –18.4 .. .. 15.2 36.4 countries of the euro area are presented as a subgroup Guinea-Bissau 2.3 3.0 2.7 1.5 –22.4 –8.5 .. .. 2.1 38.8 Guyana Haiti 1.7 0.8 4.4 3.4 3.9 4.2 11.1 25.6 –11.8 12.7 –13.9 –4.4 .. .. .. .. 2.4 6.3 67.0 45.8 under high-income economies. Honduras 4.3 2.9 3.4 16.5 11.4 –8.6 –3.2 .. 5.2 51.0 Hungary 1.6 0.7 1.7 23.4 12.4 0.9 3.7 82.4 5.7 60.9 Iceland 2.4 .. .. 9.3 .. –5.5 –5.3 119.1 5.2 89.8 India 7.7 4.8 6.2 30.3 14.8 –4.9 –3.8 49.7 9.3 75.6 Indonesia Iran, Islamic Rep. 5.5 4.8 5.6 –1.5 5.3 1.0 32.0 .. 24.1 .. –2.7 .. –1.1 .. 26.2 .. 4.3 27.3 40.1 19.7 Statistics Iraq 5.1 4.2 6.5 26.7 .. 13.7 .. .. 5.8 30.7 Irelandb Isle of Man 2.2 6.2 .. .. .. .. 16.0 .. 10.9 .. 4.4 .. –13.0 .. 102.0 .. 1.7 .. .. .. Additional information about the data is provided in Pri- mary data documentation, which summarizes national and Economy States and markets Global links Back World Development Indicators 2014 61 international efforts to improve basic data collection and gives country-level information on primary sources, census years, fiscal years, statistical methods and concepts used, and other background information. Statistical methods pro- vides technical information on some of the general calcula- tions and formulas used throughout the book. Symbols Country notes .. means that data are not available or that aggregates • Cabo Verde is the new name for the country previously cannot be calculated because of missing data in the listed as Cape Verde. years shown. • Data for China do not include data for Hong Kong SAR, 0 or means zero or small enough that the number would China; Macao SAR, China; or Taiwan, China. 0.0 round to zero at the displayed number of decimal places. • Data for Serbia do not include data for Kosovo or Montenegro. / in dates, as in 2011/12, means that the period of • Data for Sudan include South Sudan unless otherwise time, usually 12 months, straddles two calendar years noted. and refers to a crop year, a survey year, or a fiscal year. $ means current U.S. dollars unless otherwise noted. < means less than. Economy States and markets Global links Back World Development Indicators 2014 xiii User guide to WDI online tables Statistical tables that were previously available in the use the URL http://wdi.worldbank.org/table/ and the World Development Indicators print edition are available table number (for example, http://wdi.worldbank.org online. Using an automated query process, these refer- /table/1.1 to view the fi rst table in the World view sec- ence tables are consistently updated based on revisions to tion). Each section of this book also lists the indicators the World Development Indicators database. included by table and by code. To view a specifi c indi- cator online, use the URL http://data.worldbank.org How to access WDI online tables /indicator/ and the indicator code (for example, http://data To access the WDI online tables, visit http://wdi.worldbank .worldbank.org/indicator/SP.POP.TOTL to view a page for .org/tables. To access a specific WDI online table directly, total population). xiv World Development Indicators 2014 Front ? User guide World view People Environment Breadcrumbs to show where you’ve been Click on an indicator to view metadata Click on a country to view metadata How to use DataBank Actions DataBank (http://databank.worldbank.org) is a web Click to edit and revise the table in resource that provides simple and quick access to col- DataBank lections of time series data. It has advanced functions Click to download corresponding indicator for selecting and displaying data, performing customized metadata queries, downloading data, and creating charts and maps. Click to export the table to Excel Users can create dynamic custom reports based on their selection of countries, indicators, and years. All these Click to export the table and corresponding reports can be easily edited, saved, shared, and embed- indicator metadata to PDF ded as widgets on websites or blogs. For more information, see http://databank.worldbank.org/help. Click to print the table and corresponding indicator metadata Click to access the WDI Online Tables Help file Click the checkbox to highlight cell level metadata and values from years other than those specified; click the checkbox again to reset to the default display Economy States and markets Global links Back World Development Indicators 2014 xv User guide to DataFinder DataFinder is a free mobile app that accesses the full DataFinder works on mobile devices (smartphone or set of data from the World Development Indicators data- tablet computer) in both offline (no Internet connection) base. Data can be displayed and saved in a table, chart, and online (Wi-Fi or 3G/4G connection to the Internet) or map and shared via email, Facebook, and Twitter. modes. • Select a topic to display all related indicators. • View reports in table, chart, and map formats. • Compare data for multiple countries. • Send the data as a CSV file attachment to an email. • Select predefined queries. • Share comments and screenshots via Facebook, • Create a new query that can be saved and edited later. Twitter, or email. xvi World Development Indicators 2014 Front ? User guide World view People Environment Table view provides time series data tables of key devel- opment indicators by country or topic. A compare option shows the most recent year’s data for the selected country and another country. Chart view illustrates data trends and cross-country com- parisons as line or bar charts. Map view colors selected indicators on world and regional maps. A motion option animates the data changes from year to year. Economy States and markets Global links Back World Development Indicators 2014 xvii User guide to MDG Data Dashboards The World Development Indicators database provides data Development Indicators. Sufficient progress indicates that on trends in Millennium Development Goals (MDGs) indi- the MDG will be attained by 2015 based on an extrapo- cators for developing countries and other country groups. lation of the last observed data point using the growth Each year the World Bank’s Global Monitoring Report uses rate over the last observable fi ve-year period (or seven- these data to assess progress toward achieving the MDGs. year period, in the case of MDG 7). Insuffi cient progress Six online interactive MDG Data Dashboards, available at indicates that the MDG will be met between 2016 and http://data.worldbank.org/mdgs, provide an opportunity to 2020. Moderately off track indicates that the MDG will learn more about the assessments. be met between 2020 and 2030. Seriously off track indi- The MDG progress charts presented in the World cates that the MDG will not be met by 2030. Insuffi cient view section of this book correspond to the Global Moni- data indicates an inadequate number of data points to toring Report assessments (except MDG  6) and cannot estimate progress or that the MDG’s starting value is be compared with those in previous editions of World missing. View progress status for regions, income classifications, and other groups by number or percentage of countries. xviii World Development Indicators 2014 Front ? User guide World view People Environment View details of a country’s progress toward each MDG tar- get, including trends from 1990 to the latest year of avail- able data, and projected trends toward the 2015 target and 2030. Compare trends and targets of each MDG indicator for selected groups and countries. Compare the progress status of all MDG indicators across selected groups. Economy States and markets Global links Back World Development Indicators 2014 xix WORLD VIEW xx World Development Indicators 2014 Front ? User guide World view People Environment 1 World view presents progress toward the eight The target year of 2015 for the MDGs is Millennium Development Goals (MDGs), draw- now just around the corner. One important ing on the charts of progress in online interac- aspect of the MDGs has been their focus on tive visualizations (http://data.worldbank.org measuring and monitoring progress; this has /mdgs). It complements the detailed analysis in presented a clear challenge in improving the the World Bank Group’s Global Monitoring Report, quality, frequency, and availability of relevant and it uses the same methodology to assess statistics. In the last few years much has whether countries are on track or off track to been done by both countries and international meet the targets by 2015. partners to invest in the national statistical The new twin goals of the World Bank Group, systems where most data originate. But weak- announced in October 2013, are to end extreme nesses remain in the coverage and quality poverty and to boost shared prosperity across of many indicators in the poorest countries, the world. Progress will be closely monitored where resources are scarce and careful mea- using two indicators: the proportion of the popu- surement of progress may matter the most. lation living on less than $1.25 a day (in 2005 While the focus will continue to be on achiev- purchasing power parity terms) and the growth in ing the MDGs, especially in areas that have the average real per capita income of the bottom been lagging, the international community has 40 percent of the population in every country. started to discuss what comes next. While poverty rates have fallen across the world, The 2013 report of the 27-member High- progress has been uneven, and meeting the new Level Panel on the Post-2015 Development targets will require a sustained effort. As Jim Agenda, convened by the UN Secretary-Gen- Yong Kim said in the World Bank’s 2013 Annual eral, recognizes the important role of data and Report, “We must halve poverty once, then halve the challenge of improving development data. it again, and then nearly halve it a third time—all It calls for a “data revolution for sustainable in less than one generation.” development, with a new international initia- Two tables in World view present the latest tive to improve the quality of statistics and estimates of poverty rates at the international information available to citizens.” This is timely poverty line. The World Development Indicators and welcome, as is the panel’s call to “take online database and tabular presentations also advantage of new technology, crowd sourcing, present poverty rates at national poverty lines. and improved connectivity to empower people Work is under way to develop a reliable database with information on the progress toward the of growth in the per capita incomes of the bot- targets.” Both governments and development tom 40 percent of the population in most coun- partners should invest in national statistical tries. We expect to publish it later in 2014 as systems, where much of the data will continue part of World Development Indicators online. to originate. Economy States and markets Global links Back World Development Indicators 2014 1 MDG 1 Eradicate extreme poverty Poverty rates 1a The world will not have eradicated extreme poverty in 2015, but continue to fall People living on less than $1.25 a day (% of population) it will have met the Millennium Development Goal target of halv- 60 ing world poverty. The proportion of people in developing countries Sub-Saharan Africa (those classified as low and middle income in 1990) living on less South Asia than $1.25 a day fell from 43.1 percent in 1990 to 20.6 percent 40 in 2010 and reached a new low in five of six developing country regions. Except in South Asia and Sub- Saharan Africa the target East Asia & Pacific 20 was met at the regional level by 2010 (figure 1a). Latin America & Caribbean Further progress is possible—and likely—before the 2015 tar- Middle East & North Africa get date. Developing economies are expected to maintain GDP 0 Europe & Central Asia 1990 1995 2000 2005 2010 2015 target growth of 5.3–5.5 percent over the next two years, with GDP per Source: World Bank PovcalNet (http://iresearch.worldbank.org/PovcalNet). capita growth around 4.2 percent. Growth will be fastest in East Asia and Pacific and in South Asia, which still have more than half Progress in reaching the poverty 1b the world’s poorest people. Growth will be slower in Sub-Saharan target by region Countries making progress toward reducing extreme poverty Africa, the poorest region, but faster than in the preceding years, (% of countries in region) 100 quickening the pace of poverty reduction. According to these fore- casts, the proportion of people living in extreme poverty will fall to 75 16 percent by 2015. 50 Based on current trends, around 40 percent of developing coun- tries have already achieved the first Millennium Development Goal, 25 and only 17 percent are seriously off track, based on the methodol- 0 Developing East Asia Europe Latin Middle East South Sub-Saharan ogy used in the 2013 Global Monitoring Report (World Bank 2013). countries & Pacific & Central America & & North Asia Africa Asia Caribbean Africa However, in Sub-Saharan Africa up to a third of countries are seri- Target met Sufficient progress Insufficient progress Moderately off track Seriously off track Insufficient data ously off track—meaning that they would be unable at current rates Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). of progress to halve extreme poverty rates by 2030 (figure 1b). Progress is also sluggish among countries classified as fragile and Progress by income and 1c conflict situations and small states (figure 1c). lending group Countries making progress toward reducing extreme poverty Data gaps remain and hinder the monitoring of progress. About (% of countries in group) 100 a fifth of developing countries have not conducted a survey since 1990, the minimum requirement for monitoring progress when 75 using national accounts data to interpolate or extrapolate survey 50 data. By number of countries the gaps are greatest in East Asia and Pacific and especially among small states and fragile and con- 25 flict situations (figures 1b and 1c). 0 Low income Lower Upper IDA Blend IBRD Fragile & Small Poverty estimates for 2010 are provisional; revised estimates middle middle conflict states income income situations will be published later in 2014, along with new estimates for 2011. Target met Sufficient progress Insufficient progress Moderately off track Seriously off track Insufficient data Any revisions will affect estimated projections to 2015. Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). 2 World Development Indicators 2014 Front ? User guide World view People Environment MDG 2 Achieve universal primary education Growth in primary The commitment to provide primary education to every child is the 2a completion rate oldest of the Millennium Development Goals, having been set at Primary completion rate (% of relevant age group) the first Education for All conference in Jomtien, Thailand, more 125 Latin America than 20 years ago. East Asia & Pacific Europe & Central Asia & Caribbean 100 Primary completion rates—the proportion of new entrants in the last grade of primary school—reached nearly 90 percent for devel- 75 Middle East & North Africa South Asia oping countries as a whole in 2009 but have since stalled, with Sub-Saharan Africa 50 no appreciable gains in any region. Three regions have attained or are close to attaining universal primary education: East Asia and 25 Pacific, Europe and Central Asia, and Latin America and the Carib- 0 bean. Completion rates in the Middle East and North Africa have 1990 1995 2000 2005 2010 2015 target Source: United Nations Educational, Scientific and Cultural Organization stayed at 90 percent since 2009. South Asia has reached 88 per- Institute for Statistics and World Development Indicators database. cent, but progress has been slow. And Sub- Saharan Africa lags Progress toward universal behind at 70 percent (figure 2a). 2b primary education Progress among the poorest countries has accelerated since Countries making progress toward universal primary education (% of countries in region) 2000, particularly in South Asia and Sub- Saharan Africa, but full 100 enrollment remains elusive. Fifty-three countries have achieved 75 or are on track to achieve the Millennium Development Goal, while 38 countries remain seriously off track (figure 2b). Even if 50 the schools in these countries were to now enroll every eligible 25 child in the first grade, they would not be able to meet the 2015 deadline. 0 Developing East Asia Europe Latin Middle East South Sub-Saharan countries & Pacific & Central America & & North Asia Africa Another challenge is helping more children stay in school. Many Asia Caribbean Africa Target met Sufficient progress Insufficient progress children start school but drop out before completion, discouraged Moderately off track Seriously off track Insufficient data Source: World Bank (2013) and World Bank MDG Data Dashboards by cost, distance, physical danger, and failure to progress. Today, (http://data.worldbank.org/mdgs). 55 million primary school–age children remain out of school in low- Many children drop out and middle-income countries—80 percent of them in Sub-Saharan 2c after enrolling in school and South Asia, where dropout rates are highest (figure 2c). Primary dropout rate, 2010–11 (%) Even as countries approach the Millennium Development Goal 50 target, the education demands of modern economies expand, and 40 primary education will increasingly be of value only as a stepping 30 stone toward secondary and higher education. In that context, demand is growing for measuring and monitoring education qual- 20 ity and learning achievement. The primary completion rate does 10 not always ensure the quality of education, and some children Boys Girls 0 complete basic education without acquiring adequate literacy and East Asia Europe Latin Middle East South Sub-Saharan & Pacific & Central America & & North Asia Africa numeracy skills. Asia Caribbean Africa Source: United Nations Educational, Scientific and Cultural Organization Institute for Statistics and World Bank EdStats database. Economy States and markets Global links Back World Development Indicators 2014 3 MDG 3 Promote gender equality and empower women Narrowing gender gap 3a Women make important contributions to economic and social in access to education Ratio of girls to boys in primary and secondary gross development. Expanding their opportunities in the public and pri- enrollment rate (%) 120 vate sectors is a core development strategy, and education is the East Asia & Pacific Latin America & Caribbean Europe & Central Asia starting point. By enrolling and staying in school, girls gain skills to 100 enter the labor market, care for families, and make decisions for 80 Sub-Saharan Africa South Asia themselves. Middle East & 60 North Africa Girls have made substantial gains in school enrollment. In 1990 40 girls’ primary school enrollment rate in developing countries was 20 only 86 percent of boys’. By 2011 it was 97 percent. Improvements in secondary schooling have also been made, with girls’ enroll- 0 1990 1995 2000 2005 2010 2015 target ments having risen from 77 percent of boys’ in 1990 to 96 per- Source: United Nations Educational, Scientific and Cultural Organization Institute for Statistics and World Development Indicators database. cent in 2011. But the averages mask large differences across and within countries. Low-income countries lag far behind, and only 8 Progress toward gender equality 3b of 36 countries reached or exceeded equal education for girls in in education Countries making progress toward gender equality in education primary and secondary education. Poor households are less likely (% of countries in region) 100 than wealthy households to keep their children in school, and girls from wealthier households are more likely to enroll in school and 75 stay longer. 50 Women work long hours and contribute much to their families’ welfare, but many are in the informal sector or are unpaid for their 25 labor. The highest proportion of women in wage employment in the 0 Developing East Asia Europe Latin Middle East South Sub-Saharan nonagricultural sector (median value) is in Europe and Central Asia countries & Pacific & Central America & & North Asia Africa Asia Caribbean Africa (46 percent). The lowest is in Middle East and North Africa (16 per- Target met Sufficient progress Insufficient progress Moderately off track Seriously off track Insufficient data cent) and South Asia (19 percent), where women’s full economic Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). empowerment remains a distant goal. More women are taking part in public life at the highest levels. Women still lack opportunities 3c The share of parliamentary seats held by women continues to in paid employment Female employees in nonagricultural wage employment, median increase. The largest gains have been in the Middle East and North value, most recent year available, 2004–12 (% of total nonagricultural employment) Africa, where the proportion more than quadrupled between 1990 50 and 2013, though it remains a mere 16 percent. 40 Lack of data hampers the ability to understand women’s roles in 30 the economy. Led by the Inter-agency and Experts Group on Gender 20 Statistics, many new international initiatives—including the World Bank’s gender statistics projects, Evidence and Data for Gender 10 Equality, and Data2X—are tackling the paucity of data by mapping 0 East Asia Europe Latin Middle East South Sub-Saharan & Pacifica & Central America & & North Asia Africaa data gaps, providing technical assistance, and developing methods Asia Caribbean Africa a. Data cover less than two-thirds of regional population. to produce statistics in emerging areas. Source: International Labour Organization Key Indicators of the Labour Market database and World Development Indicators database. 4 World Development Indicators 2014 Front ? User guide World view People Environment MDG 4 Reduce child mortality Under-five mortality rates In 1990, 13 million children died before their fifth birthday. By 1999 4a continue to fall fewer than 10 million did. And in 2012, 7 million did. Over that time Under-five mortality rate (per 1,000 live births) the under-five mortality rate in developing countries fell 46 percent, 200 from an average of 99 per 1,000 live births in 1990 to 53 in 2012. The rates remain much higher in Sub-Saharan Africa and South 150 Sub-Saharan Africa Asia than in the other four developing country regions (figure 4a). All developing regions except for Sub-Saharan Africa have halved their 100 South Asia under-five mortality rate since 1990. Overall, progress has been 50 substantial, but globally the rate of decline is insufficient to achieve East Asia & Pacific Middle East & North Africa Europe & Central Asia Millennium Development Goal  4 to reduce the under-five mortal- Latin America & Caribbean 0 ity rate by two-thirds between 1990 and 2015. However, the aver- 1990 1995 2000 2005 2010 2015 target Source: UN Inter-agency Group for Child Mortality Estimation and World age annual rate of decline in under-five mortality accelerated, from Development Indicators database. 1.2 percent in 1990–95 to 3.9 percent in 2005–12. This recent Progress toward reducing progress is close to the average needed to be on track to achieve 4b child mortality Millennium Development Goal 4 (figure 4b). Countries making progress toward reducing child mortality (% of countries in region) Most children die from causes readily preventable or curable 100 with existing interventions, such as pneumonia (17 percent), diar- 75 rhea (9 percent), and malaria (7 percent). Roughly 70 percent of deaths of children under age 5 occur in the first year of life, and 50 60 percent of those in the first month. Preterm birth complications 25 account for 15 percent of deaths, and complications during birth another 10 percent (UNICEF 2013). Reducing child mortality thus 0 Developing East Asia Europe Latin Middle East South Sub-Saharan countries & Pacific & Central America & & North Asia Africa requires addressing the causes of neonatal and infant deaths: mal- Asia Caribbean Africa Target met Sufficient progress Insufficient progress nutrition, poor sanitation, inadequate care at and after birth, and Moderately off track Seriously off track Insufficient data Source: World Bank (2013) and World Bank MDG Data Dashboards exposure to acute and chronic disease. (http://data.worldbank.org/mdgs). Improving infant and child mortality are the largest contribu- Measles immunization rates tors to higher life expectancy in most countries. Childhood vac- 4c are stagnating cinations are a proven, cost-effective way of reducing childhood Children ages 12–23 months immunized against measles (%) illness and death. But despite years of vaccination campaigns, 100 Latin America & Caribbean many children in low- and lower middle-income economies remain Europe & Central Asia Middle East & North Africa unprotected, as with measles. To succeed, vaccination campaigns 75 East Asia & Pacific South Asia must reach all children and be sustained over time. That is why Sub-Saharan Africa 50 it is worrisome that measles vaccination rates in the two highest mortality regions, South Asia and Sub- Saharan Africa, have stag- 25 nated in the last three years, at less than 80 percent coverage (figure 4c). 0 1990 1995 2000 2005 2010 2012 Source: World Health Organization, United Nations Children’s Fund, and World Development Indicators database. Economy States and markets Global links Back World Development Indicators 2014 5 MDG 5 Improve maternal health Maternal deaths are more likely in 5a An estimated 287,000 maternal deaths occurred worldwide in South Asia and Sub-Saharan Africa Maternal mortality ratio, modeled estimate 2010, a 47  percent decline since 1990. All but 2,400 maternal (per 100,000 live births) 1,000 deaths were in developing countries. In 2010 more than half the maternal deaths were in Sub-Saharan Africa and a quarter in South 750 Asia. While the number of maternal deaths remains high in South Sub-Saharan Africa Asia, the region has made the most progress toward the Millen- 500 nium Development Goal target, reaching a maternal mortality ratio South Asia Middle East & of 220 per 100,000 live births in 2010, down from 620 in 1990, a North Africa 250 Latin America & Caribbean reduction of 65 percent. The Middle East and North Africa and East East Asia & Pacific Europe & Central Asia Asia and Pacific have also reduced their maternal mortality ratios 0 1990 1995 2000 2005 2015 target 2010 more than 60 percent (figure 5a). Source: UN Maternal Mortality Estimation Inter-agency Group and World Development Indicators database. These achievements are impressive, but progress in reducing maternal mortality ratios has been slow, far slower than the 75 per- Progress toward reducing 5b cent reduction between 1990 and 2015 imagined by the Millen- maternal mortality Countries making progress toward reducing maternal mortality nium Development Goals. Few countries and no developing region (% of countries in region) 100 on average will achieve this target. But the average annual rate of decline has accelerated, from 2.1 percent in 1990–95 to 4.3 per- 75 cent in 2005–10. This recent progress is closer to the average rate 50 needed to be on track to achieve Millennium Development Goal 5 (figure 5b). 25 Better maternal health care and lower fertility can reduce 0 Developing East Asia Europe Latin Middle East South Sub-Saharan maternal deaths. Family planning and access to contraception countries & Pacific & Central America & & North Asia Africa Asia Caribbean Africa can help avoid the large number of births that are unwanted or Target met Sufficient progress Insufficient progress Moderately off track Seriously off track Insufficient data mistimed. At least 200 million women want to use safe and effec- Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). tive family planning methods but are unable to do so (figure 5c; UNFPA 2014). A wide range 5c Many health problems among pregnant women are prevent- of needs Unmet need for contraception, most recent year available, 2007–12 able or treatable through visits with trained health workers before (% of married women ages 15–49) 40 childbirth. Good nutrition, vaccinations, and treating infections Regional median can improve outcomes for mother and child. Skilled attendants 30 at delivery and access to hospital treatments are essential for 20 dealing with life-threatening emergencies such as severe bleed- ing and hypertensive disorders. In South Asia and Sub- Saharan 10 Africa many births are not attended by doctors, nurses, or trained midwives. 0 East Asia Europe Latin Middle East South Sub-Saharan & Pacific & Central America & & North Asia Africa (7 countries) Asia Caribbean Africa (4 countries) (26 countries) (4 countries) (8 countries) (2 countries) Source: Household surveys, including Demographic and Health Survey and Multiple Indicator Cluster Surveys, and World Development Indicators database. 6 World Development Indicators 2014 Front ? User guide World view People Environment MDG 6 Combat HIV/AIDS, malaria, and other diseases HIV prevalence in Sub-Saharan Africa Epidemic diseases exact a huge toll in human suffering and lost 6a continues to fall development opportunities. Poverty, armed conflict, and natu- HIV prevalence (% of population ages 15–49) ral disasters contribute to the spread of disease and are made 6 Sub-Saharan Africa worse by it. In Africa the spread of HIV/AIDS has reversed decades of improvement in life expectancy and left millions of children 4 orphaned. Malaria takes a large toll on young children and weak- ens adults at great cost to their productivity. Tuberculosis killed 900,000 people in 2012, most of them ages 15–45, and sickened 2 millions more. World In 2012 35 million people were living with HIV/AIDS, and 2.3 mil- South Asia 0 lion more acquired the disease. Sub- Saharan Africa remains the 1990 1995 2000 2005 2010 2012 Source: Joint United Nations Programme on HIV/AIDS and World center of the epidemic, but the proportion of adults living with AIDS Development Indicators database. has begun to fall even as the survival rate of those with access to Progress toward halting and reversing antiretroviral drugs has increased (figures 6a and 6b). At the end 6b the HIV epidemic of 2012, 9.7 million people in developing countries were receiving Countries making progress toward halting and reversing the HIV epidemic (% of countries in region) antiretroviral drugs. The scale-up has been exponential in recent 100 years (UNAIDS 2013) but still far short of universal access. 75 In 2012 8.6 million people were newly diagnosed with tuber- culosis, but incidence, prevalence, and death rates are falling 50 (figure 6c). If these trends are sustained, the world could achieve 25 the target of halting and reversing the spread of tuberculosis by 2015. People living with HIV/AIDS, which reduces resistance 0 Developing East Asia Europe Latin Middle East South Sub-Saharan countries & Pacific & Central America & & North Asia Africa to tuberculosis, are particularly vulnerable, as are refugees, Asia Caribbean Africa Halted and reversed Halted or reversed Stable low prevalence displaced persons, and prisoners living in close quarters and Not improving Insufficient data unsanitary conditions. Well managed medical intervention using Source: World Bank staff calculations. appropriate drug therapy is crucial to stopping the spread of Fewer people contacting, living with, tuberculosis. 6c and dying from tuberculosis There were an estimated 200 million cases of malaria in 2012, Tuberculosis prevalence, incidence, and deaths in low- and middle-income countries (per 100,000 people) causing 600,000 deaths (WHO 2013). Malaria is a disease of pov- 400 erty, but there has been progress. Although it occurs in all regions, Sub- Saharan Africa is where the most lethal malaria parasite is 300 most abundant. Insecticide-treated nets have proved effective for Prevalence 200 prevention, and their use is growing. Incidence 100 Deaths 0 1990 1995 2000 2005 2010 2012 Source: World Health Organization and World Development Indicators database. Economy States and markets Global links Back World Development Indicators 2014 7 MDG 7 Ensure environmental sustainability Carbon dioxide emissions continue 7a Millennium Development Goal 7 is the most far-reaching, affecting to surge to unprecedented levels Carbon dioxide emissions (billions of metric tons) each person now and in the future. It addresses the condition of 40 the natural and built environments: reversing the loss of natural resources, preserving biodiversity, increasing access to safe water 30 and sanitation, and improving living conditions of people in slums. High income The overall theme is sustainability, improving people’s lives without 20 depleting natural and humanmade capital stocks. Failure to reach a comprehensive agreement on limiting green- 10 Upper middle income house gas emissions leaves billions of people vulnerable to climate Low income Lower middle income change, with the effects expected to hit hardest in developing coun- 0 1990 1995 2000 2005 2010 tries. Higher temperatures, changes in precipitation patterns, ris- Source: Carbon Dioxide Information Analysis Center and World Development Indicators database. ing sea levels, and more frequent weather-related disasters pose risks for agriculture, food, and water supplies. The world released Progress toward halving the proportion 33.6 billion metric tons of carbon dioxide in 2010, up 5 percent of people without sustainable access to 7b safe drinking water over 2009 and a considerable rise of 51 percent since 1990—the Countries making progress toward halving the proportion of baseline for Kyoto Protocol requirements (figure 7a). Global emis- people without sustainable access to safe drinking water (% of countries in region) sions in 2013 are estimated at an unprecedented 36 billion tons, 100 with a growth rate of 2 percent, slightly lower than the historical 75 average of 3 percent since 2000. 50 The Millennium Development Goals call for halving the propor- 25 tion of people without access to an improved water source and 0 Developing East Asia Europe Latin Middle East South Sub-Saharan sanitation facilities by 2015. In 1990 almost 1.3 billion people countries & Pacific & Central America & & North Asia Africa Asia Caribbean Africa worldwide lacked access to drinking water from a convenient, Target met Sufficient progress Insufficient progress Moderately off track Seriously off track Insufficient data protected source. By 2012 that had improved to 752  million Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). people—a 41 percent reduction. In developing countries the pro- portion of people with access to an improved water source rose Progress toward halving the proportion from 70 percent in 1990 to 87 percent in 2012. However, almost of people without sustainable access to 7c basic sanitation 27  percent of countries are seriously off track toward meet- Countries making progress toward halving the proportion of ing the water target (fi gure 7b). In 1990 only 35 percent of the people without sustainable access to basic sanitation (% of countries in region) people living in low- and middle-income economies had access 100 to a flush toilet or other form of improved sanitation. By 2012 75 the access rate had risen to 57 percent. But 2.5 billion people 50 still lack access to improved sanitation. The situation is worse 25 in rural areas, where 43 percent of the population has access to 0 Developing East Asia Europe Latin Middle East South Sub-Saharan improved sanitation, compared with 73 percent in urban areas. countries & Pacific & Central America & & North Asia Africa Asia Caribbean Africa This large disparity, especially in Sub- Saharan Africa and South Target met Sufficient progress Insufficient progress Moderately off track Seriously off track Insufficient data Asia, is the main reason the sanitation target is unlikely to be Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). met on time (figure 7c). 8 World Development Indicators 2014 Front ? User guide World view People Environment MDG 8 Develop a global partnership for development Official development assistance from The financial crisis that began in 2008 and the ensuing fiscal 8a Development Assistance Committee members austerity in many high-income economies have undermined com- Official development assistance (2011 $ billions) mitments to increase official development assistance (ODA) from 200 Multilateral net official development assistance members of the Organisation for Economic Co-operation and Devel- opment’s Development Assistance Committee (DAC). Since 2010, 150 the year of its peak, ODA has fallen 6 percent in real terms, after adjusting prices and exchange rates. Net disbursements of ODA by 100 DAC members totaled $127 billion in 2012, a decrease of 4 per- 50 cent in real terms. This decline has been accompanied by a notice- able shift in aid allocations away from the poorest countries and Bilateral net official development assistance 0 toward middle-income countries. Bilateral ODA from DAC members 1990 1995 2000 2005 2010 2012 to Sub-Saharan Africa, $27.3 billion in 2012, fell 4.3 percent in real Source: Organisation for Economic Co-operation and Development. terms from 2011. As a share of gross national income, it fell to Debt service burdens 0.29 percent in 2012, well below half the UN target of 0.7 percent 8b continue to fall (figure 8a). Total debt service (% of exports of goods, services, and income) Economic growth, improved debt management, debt restructur- 50 Europe & ing, and outright debt relief have enabled developing countries to Latin America & Caribbean Central Asia 40 substantially reduce their debt burdens. This is in part due to 35 of South Asia the 39 countries being eligible for the Heavily Indebted Poor Coun- 30 try (HIPC) Debt Relief Initiative and Multilateral Debt Relief Initiative Middle East & North Africa 20 (MDRI) benefiting from substantial relief. The ratio of debt service to exports in low- and middle-income economies fell to 9.8  per- East Asia & Pacific 10 Sub-Saharan Africa cent in 2012, well below half the 21.1 percent at the start of the 0 decade. Sub-Saharan Africa, home to the majority of the HIPC and 1990 1995 2000 2005 2010 2012 MDRI countries, has one of the lowest ratios of debt service to Source: World Development Indicators database. exports: 4.5 percent in 2012 (figure 8b). The number of internet users Telecommunications is essential for development, and new tech- 8c continues to rise nologies are creating new opportunities everywhere. By the end Internet users (per 100 people) of 2012 there were 6.3  billion mobile phone subscriptions, and 75 High income 2.5 billion people were using the Internet worldwide. As the global mobile-cellular penetration rate approaches market saturation, 50 the growth rates for both developing and developed economies Europe & Central Asia are slowing. Mobile phones are one of several ways of accessing Latin America & Caribbean East Asia & Pacific the Internet. And like telephone use, Internet use is strongly cor- 25 Middle East & North Africa Sub-Saharan Africa related with income. Since 2000 Internet users per 100 people in developing economies has grown 28  percent a year, but the South Asia 0 low-income economies of South Asia and Sub- Saharan Africa lag 2000 2005 2010 2012 Source: International Telecommunications Union and World Development behind (figure 8c). Indicators database. Economy States and markets Global links Back World Development Indicators 2014 9 Millennium Development Goals Goals and targets from the Millennium Declaration Indicators for monitoring progress Goal 1 Eradicate extreme poverty and hunger Target 1.A Halve, between 1990 and 2015, the proportion of 1.1 Proportion of population below $1 purchasing power people whose income is less than $1 a day parity (PPP) a daya 1.2 Poverty gap ratio [incidence × depth of poverty] 1.3 Share of poorest quintile in national consumption Target 1.B Achieve full and productive employment and decent 1.4 Growth rate of GDP per person employed work for all, including women and young people 1.5 Employment to population ratio 1.6 Proportion of employed people living below $1 (PPP) a day 1.7 Proportion of own-account and contributing family workers in total employment Target 1.C Halve, between 1990 and 2015, the proportion of 1.8 Prevalence of underweight children under five years of age people who suffer from hunger 1.9 Proportion of population below minimum level of dietary energy consumption Goal 2 Achieve universal primary education Target 2.A Ensure that by 2015 children everywhere, boys and 2.1 Net enrollment ratio in primary education girls alike, will be able to complete a full course of 2.2 Proportion of pupils starting grade 1 who reach last primary schooling grade of primary education 2.3 Literacy rate of 15- to 24-year-olds, women and men Goal 3 Promote gender equality and empower women Target 3.A Eliminate gender disparity in primary and secondary 3.1 Ratios of girls to boys in primary, secondary, and tertiary education, preferably by 2005, and in all levels of education education no later than 2015 3.2 Share of women in wage employment in the nonagricultural sector 3.3 Proportion of seats held by women in national parliament Goal 4 Reduce child mortality Target 4.A Reduce by two-thirds, between 1990 and 2015, the 4.1 Under-five mortality rate under-five mortality rate 4.2 Infant mortality rate 4.3 Proportion of one-year-old children immunized against measles Goal 5 Improve maternal health Target 5.A Reduce by three-quarters, between 1990 and 2015, 5.1 Maternal mortality ratio the maternal mortality ratio 5.2 Proportion of births attended by skilled health personnel Target 5.B Achieve by 2015 universal access to reproductive 5.3 Contraceptive prevalence rate health 5.4 Adolescent birth rate 5.5 Antenatal care coverage (at least one visit and at least four visits) 5.6 Unmet need for family planning Goal 6 Combat HIV/AIDS, malaria, and other diseases Target 6.A Have halted by 2015 and begun to reverse the 6.1 HIV prevalence among population ages 15–24 years spread of HIV/AIDS 6.2 Condom use at last high-risk sex 6.3 Proportion of population ages 15–24 years with comprehensive, correct knowledge of HIV/AIDS 6.4 Ratio of school attendance of orphans to school attendance of nonorphans ages 10–14 years Target 6.B Achieve by 2010 universal access to treatment for 6.5 Proportion of population with advanced HIV infection with HIV/AIDS for all those who need it access to antiretroviral drugs Target 6.C Have halted by 2015 and begun to reverse the 6.6 Incidence and death rates associated with malaria incidence of malaria and other major diseases 6.7 Proportion of children under age five sleeping under insecticide-treated bednets 6.8 Proportion of children under age five with fever who are treated with appropriate antimalarial drugs 6.9 Incidence, prevalence, and death rates associated with tuberculosis 6.10 Proportion of tuberculosis cases detected and cured under directly observed treatment short course Note: The Millennium Development Goals and targets come from the Millennium Declaration, signed by 189 countries, including 147 heads of state and government, in September 2000 (www.un.org/millennium/declaration/ares552e.htm) as updated by the 60th UN General Assembly in September 2005. The revised Millennium Development Goal (MDG) monitoring framework shown here, including new targets and indicators, was presented to the 62nd General Assembly, with new numbering as recommended by the Inter-agency and Expert Group on MDG Indicators at its 12th meeting on November 14, 2007. The goals and targets are interrelated and should be seen as a whole. They represent a partnership between the developed countries and the developing countries “to create an environment—at the national and global levels alike—which is conducive to development and the elimination of poverty.” All indicators should be disaggregated by sex and urban-rural location as far as possible. 10 World Development Indicators 2014 Front ? User guide World view People Environment Goals and targets from the Millennium Declaration Indicators for monitoring progress Goal 7 Ensure environmental sustainability Target 7.A Integrate the principles of sustainable development 7.1 Proportion of land area covered by forest into country policies and programs and reverse the 7.2 Carbon dioxide emissions, total, per capita and loss of environmental resources per $1 GDP (PPP) 7.3 Consumption of ozone-depleting substances Target 7.B Reduce biodiversity loss, achieving, by 2010, 7.4 Proportion of fish stocks within safe biological limits a significant reduction in the rate of loss 7.5 Proportion of total water resources used 7.6 Proportion of terrestrial and marine areas protected 7.7 Proportion of species threatened with extinction Target 7.C Halve by 2015 the proportion of people without 7.8 Proportion of population using an improved drinking water sustainable access to safe drinking water and basic source sanitation 7.9 Proportion of population using an improved sanitation facility Target 7.D Achieve by 2020 a significant improvement in the 7.10 Proportion of urban population living in slumsb lives of at least 100 million slum dwellers Goal 8 Develop a global partnership for development Target 8.A Develop further an open, rule-based, predictable, Some of the indicators listed below are monitored separately nondiscriminatory trading and financial system for the least developed countries (LDCs), Africa, landlocked developing countries, and small island developing states. (Includes a commitment to good governance, development, and poverty reduction—both Official development assistance (ODA) nationally and internationally.) 8.1 Net ODA, total and to the least developed countries, as percentage of OECD/DAC donors’ gross national income 8.2 Proportion of total bilateral, sector-allocable ODA of OECD/DAC donors to basic social services (basic Target 8.B Address the special needs of the least developed education, primary health care, nutrition, safe water, and countries sanitation) 8.3 Proportion of bilateral official development assistance of (Includes tariff and quota-free access for the least OECD/DAC donors that is untied developed countries’ exports; enhanced program of 8.4 ODA received in landlocked developing countries as a debt relief for heavily indebted poor countries (HIPC) proportion of their gross national incomes and cancellation of official bilateral debt; and more 8.5 ODA received in small island developing states as a generous ODA for countries committed to poverty proportion of their gross national incomes reduction.) Market access Target 8.C Address the special needs of landlocked 8.6 Proportion of total developed country imports (by value developing countries and small island developing and excluding arms) from developing countries and least states (through the Programme of Action for developed countries, admitted free of duty the Sustainable Development of Small Island 8.7 Average tariffs imposed by developed countries on Developing States and the outcome of the 22nd agricultural products and textiles and clothing from special session of the General Assembly) developing countries 8.8 Agricultural support estimate for OECD countries as a percentage of their GDP 8.9 Proportion of ODA provided to help build trade capacity Target 8.D Deal comprehensively with the debt problems of developing countries through national and Debt sustainability international measures in order to make debt 8.10 Total number of countries that have reached their HIPC sustainable in the long term decision points and number that have reached their HIPC completion points (cumulative) 8.11 Debt relief committed under HIPC Initiative and Multilateral Debt Relief Initiative (MDRI) 8.12 Debt service as a percentage of exports of goods and services Target 8.E In cooperation with pharmaceutical companies, 8.13 Proportion of population with access to affordable provide access to affordable essential drugs in essential drugs on a sustainable basis developing countries Target 8.F In cooperation with the private sector, make 8.14 Fixed-line telephones per 100 population available the benefits of new technologies, 8.15 Mobile cellular subscribers per 100 population especially information and communications 8.16 Internet users per 100 population a. Where available, indicators based on national poverty lines should be used for monitoring country poverty trends. b. The proportion of people living in slums is measured by a proxy, represented by the urban population living in households with at least one of these characteristics: lack of access to improved water supply, lack of access to improved sanitation, overcrowding (three or more people per room), and dwellings made of nondurable material. Economy States and markets Global links Back World Development Indicators 2014 11 1 World view Population Surface Population Urban Gross national income Gross domestic area density population product Atlas method Purchasing power parity thousand people % of total Per capita Per capita Per capita millions sq. km per sq. km population $ billions $ $ billions $ % growth % growth 2012 2012 2012 2012 2012 2012 2012 2012 2011–12 2011–12 Afghanistan 29.8 652.2 46 24 20.4 680 46.6a 1,560a 14.4 11.6 Albania 3.2 28.8 115 54 12.7 4,030 b 29.3 9,280 1.6 1.3 Algeria 38.5 2,381.7 16 74 193.2 5,020 321.6a 8,360a 3.3 1.4 American Samoa 0.1 0.2 276 93 .. ..c .. .. .. .. Andorra 0.1 0.5 167 87 .. ..d .. .. .. .. Angola 20.8 1,246.7 17 60 95.4 4,580 112.4 5,400 6.8 3.5 Antigua and Barbuda 0.1 0.4 202 30 1.1 12,480e 1.7a 18,920a 2.8 1.8 Argentina 41.1 2,780.4 15 93 ..f ..c,f ..f ..f 1.9g ..f Armenia 3.0 29.7 104 64 11.0 3,720 20.4 6,860 7.2 7.0 Aruba 0.1 0.2 569 47 .. ..d .. .. .. .. Australia 22.7 7,741.2 3 89 1,346.6 59,260 966.6 42,540 3.4 1.7 Austria 8.4 83.9 102 68 403.4 47,850 369.7 43,850 0.9 0.6 Azerbaijan 9.3 86.6 112 54 57.9 6,220 86.5 9,310 2.2 0.9 Bahamas, The 0.4 13.9 37 84 7.7 20,600 10.8a 29,020a 1.8 0.3 Bahrain 1.3 0.8 1,734 89 25.8 19,560 27.8 22,250 3.4 1.4 Bangladesh 154.7 144.0 1,188 29 129.3 840 314.2 2,030 6.2 5.0 Barbados 0.3 0.4 659 45 4.3 15,080 7.3a 25,670a 0.0 –0.5 Belarus 9.5 207.6 47 75 61.8 6,530 141.6 14,960 1.5 1.6 Belgium 11.1 30.5 368 98 497.6 44,720 452.7 40,680 –0.1 –0.9 Belize 0.3 23.0 14 45 1.4 4,490 2.5a 7,630a 5.3 2.8 Benin 10.1 114.8 89 46 7.5 750 15.6 1,550 5.4 2.6 Bermuda 0.1 0.1 1,296 100 6.8 104,590 .. .. –4.9 –5.2 Bhutan 0.7 38.4 19 36 1.8 2,420 4.6 6,200 9.4 7.6 Bolivia 10.5 1,098.6 10 67 23.3 2,220 51.2 4,880 5.2 3.5 Bosnia and Herzegovina 3.8 51.2 75 49 18.2 4,750 37.0 9,650 –0.7 –0.6 Botswana 2.0 581.7 4 62 15.3 7,650 32.2 16,060 4.2 3.3 Brazil 198.7 8,514.9 23 85 2,311.1 11,630 2,291.0 11,530 0.9 0.0 Brunei Darussalam 0.4 5.8 78 76 .. ..d .. .. 2.2 0.7 Bulgaria 7.3 111.0 67 74 50.0 6,840 112.9 15,450 0.8 1.4 Burkina Faso 16.5 274.2 60 27 11.0 670 24.4 1,480 9.5 6.4 Burundi 9.8 27.8 384 11 2.4 240 5.4 550 4.0 0.8 Cabo Verde 0.5 4.0 123 63 1.9 3,830 2.4 4,930 2.5 1.7 Cambodia 14.9 181.0 84 20 13.0 880 34.6 2,330 7.3 5.4 Cameroon 21.7 475.4 46 53 25.3 1,170 49.3 2,270 4.6 2.0 Canada 34.8 9,984.7 4 81 1,792.3 51,570 1,469.0 42,270 1.7 0.5 Cayman Islands 0.1 0.3 240 100 .. ..d .. .. .. .. Central African Republic 4.5 623.0 7 39 2.3 510 4.9 1,080 6.9 4.8 Chad 12.4 1,284.0 10 22 9.6 770 20.1 1,620 8.9 5.7 Channel Islands 0.2 0.2 849 31 .. ..d .. .. .. .. Chile 17.5 756.1 23 89 249.9 14,310 357.2 20,450 5.6 4.6 China 1,350.7 9,600.0 145 52 7,731.3 5,720 12,205.8 9,040 7.8 7.3 Hong Kong SAR, China 7.2 1.1 6,866 100 261.6 36,560 373.4 52,190 1.5 0.3 Macao SAR, China 0.6 0.0h 19,885 100 30.4 55,720 37.1 68,000 9.9 7.9 Colombia 47.7 1,141.8 43 76 334.8 7,020 476.4 9,990 4.2 2.8 Comoros 0.7 1.9 386 28 0.6 840 0.9 1,210 3.0 0.5 Congo, Dem. Rep. 65.7 2,344.9 29 35 15.4 230 25.5 390 7.2 4.3 Congo, Rep. 4.3 342.0 13 64 11.1 2,550 15.0 3,450 3.8 1.1 12 World Development Indicators 2014 Front ? User guide World view People Environment World view 1 Population Surface Population Urban Gross national income Gross domestic area density population product Atlas method Purchasing power parity thousand people % of total Per capita Per capita Per capita millions sq. km per sq. km population $ billions $ $ billions $ % growth % growth 2012 2012 2012 2012 2012 2012 2012 2012 2011–12 2011–12 Costa Rica 4.8 51.1 94 65 42.4 8,820 60.1a 12,500a 5.1 3.6 Côte d’Ivoire 19.8 322.5 62 52 24.2 1,220 38.2 1,920 9.5 7.0 Croatia 4.3 56.6 76 58 57.6 13,490 86.2 20,200 –2.0 –1.7 Cuba 11.3 109.9 106 75 66.4 5,890 .. .. 2.7 2.8 Curaçao 0.2 0.4 342 .. .. ..d .. .. .. .. Cyprus 1.1 9.3 122 71 22.8i 26,110i 26.1i 29,840i –2.4i –4.9i Czech Republic 10.5 78.9 136 73 190.5 18,130 267.9 25,480 –1.0 –1.2 Denmark 5.6 43.1 132 87 334.8 59,870 246.4 44,070 –0.4 –0.7 Djibouti 0.9 23.2 37 77 .. ..j .. .. .. .. Dominica 0.1 0.8 96 67 0.5 6,440 0.9a 11,980a –1.7 –2.1 Dominican Republic 10.3 48.7 213 70 56.3 5,470 99.3a 9,660a 3.9 2.6 Ecuador 15.5 256.4 62 68 80.1 5,170 147.0 9,490 5.1 3.5 Egypt, Arab Rep. 80.7 1,001.5 81 44 240.3 2,980 520.7 6,450 2.2 0.5 El Salvador 6.3 21.0 304 65 22.6 3,590 42.3a 6,720a 1.9 1.3 Equatorial Guinea 0.7 28.1 26 40 10.0 13,560 13.7 18,570 2.5 –0.3 Eritrea 6.1 117.6 61 22 2.8 450 3.4 a 550a 7.0 3.6 Estonia 1.3 45.2 31 70 21.6 16,270 31.0 23,280 3.9 4.4 Ethiopia 91.7 1,104.3 92 17 34.7 380 101.5 1,110 8.5 5.7 Faeroe Islands 0.0k 1.4 35 41 .. ..d .. .. .. .. Fiji 0.9 18.3 48 53 3.6 4,110 4.1 4,690 2.3 1.5 Finland 5.4 338.4 18 84 251.7 46,490 212.0 39,150 –0.8 –1.3 France 65.7 549.2 120 86 2,742.9 41,750 2,458.1 37,420 0.0 –0.5 French Polynesia 0.3 4.0 75 51 .. ..d .. .. .. .. Gabon 1.6 267.7 6 86 16.4 10,040 23.0 14,090 5.6 3.1 Gambia, The 1.8 11.3 177 58 0.9 510 3.3 1,830 5.3 2.0 Georgia 4.5l 69.7 79l 53 14.8l 3,290l 26.0l 5,790l 6.0l 5.8l Germany 80.4 357.1 231 74 3,624.6 45,070 3,516.2 43,720 0.7 2.4 Ghana 25.4 238.5 111 53 39.4 1,550 48.4 1,910 7.9 5.6 Greece 11.1 132.0 86 62 262.4 23,660 290.3 26,170 –6.4 –6.1 Greenland 0.1 410.5m 0n 85 .. ..d .. .. .. .. Grenada 0.1 0.3 310 39 0.8 7,220 1.1a 10,350a 0.6 0.2 Guam 0.2 0.5 302 93 .. ..d .. .. .. .. Guatemala 15.1 108.9 141 50 47.1 3,120 73.6a 4,880a 3.0 0.4 Guinea 11.5 245.9 47 36 5.0 440 11.1 970 3.9 1.3 Guinea-Bissau 1.7 36.1 59 45 0.9 510 1.8 1,100 –6.7 –8.9 Guyana 0.8 215.0 4 28 2.7 3,410 2.7a 3,340a 4.8 4.2 Haiti 10.2 27.8 369 55 7.7 760 12.4 a 1,220a 2.8 1.4 Honduras 7.9 112.5 71 53 16.8 2,120 30.8a 3,880a 3.9 1.8 Hungary 9.9 93.0 110 70 123.1 12,410 211.8 21,350 –1.7 –1.2 Iceland 0.3 103.0 3 94 12.3 38,270 11.2 34,770 1.4 0.9 India 1,236.7 3,287.3 416 32 1,913.2 1,550 4,730.3 3,820 4.7 3.4 Indonesia 246.9 1,904.6 136 51 844.0 3,420 1,168.7 4,730 6.2 4.9 Iran, Islamic Rep. 76.4 1,745.2 47 69 .. ..c .. .. –1.9 –3.2 Iraq 32.6 435.2 75 66 199.8 6,130 242.9 7,460 9.3 6.5 Ireland 4.6 70.3 67 63 179.0 39,020 164.2 35,790 0.2 –0.1 Isle of Man 0.1 0.6 150 51 .. ..d .. .. .. .. Israel 7.9 22.1 366 92 253.4 32,030 240.2 30,370 3.4 1.5 Economy States and markets Global links Back World Development Indicators 2014 13 1 World view Population Surface Population Urban Gross national income Gross domestic area density population product Atlas method Purchasing power parity thousand people % of total Per capita Per capita Per capita millions sq. km per sq. km population $ billions $ $ billions $ % growth % growth 2012 2012 2012 2012 2012 2012 2012 2012 2011–12 2011–12 Italy 59.5 301.3 202 69 2,062.5 34,640 2,065.9 34,700 –2.5 –0.6 Jamaica 2.7 11.0 250 52 13.9 5,130 .. .. –0.5 –0.7 Japan 127.6 378.0 350 92 6,106.7 47,870 4,687.6 36,750 2.0 2.2 Jordan 6.3 89.3 71 83 29.5 4,670 37.8 5,980 2.7 0.4 Kazakhstan 16.8 2,724.9 6 54 164.3 9,780 197.9 11,790 5.0 3.5 Kenya 43.2 580.4 76 24 37.2 860 74.7 1,730 4.6 1.8 Kiribati 0.1 0.8 124 44 0.3 2,520 0.4a 3,870a 2.8 1.2 Korea, Dem. People’s Rep. 24.8 120.5 206 60 .. ..o .. .. .. .. Korea, Rep. 50.0 99.9 515 83 1,133.8 22,670 1,509.0 30,180 2.0 1.6 Kosovo 1.8 10.9 166 .. 6.5 3,600 .. .. 2.7 1.8 Kuwait 3.3 17.8 182 98 140.2 44,880 149.2 47,750 6.2 2.1 Kyrgyz Republic 5.6 199.9 29 35 5.5 990 12.4 2,220 –0.9 –2.5 Lao PDR 6.6 236.8 29 35 8.4 1,270 17.9 2,690 8.2 6.2 Latvia 2.0 64.5 33 68 28.6 14,060 44.4 21,820 5.0 6.3 Lebanon 4.4 10.5 433 87 40.7 9,190 62.7 14,160 1.4 0.4 Lesotho 2.1 30.4 68 28 2.8 1,380 4.5 2,170 4.0 2.8 Liberia 4.2 111.4 44 49 1.5 370 2.4 580 10.2 7.3 Libya 6.2 1,759.5 3 78 .. ..c .. .. .. .. Liechtenstein 0.0k 0.2 229 14 .. ..d .. .. .. .. Lithuania 3.0 65.3 48 67 41.3 13,820 70.3 23,540 3.7 5.1 Luxembourg 0.5 2.6 205 86 38.0 71,640 32.4 60,950 –0.2 –2.5 Macedonia, FYR 2.1 25.7 83 59 9.7 4,620 24.3 11,540 –0.3 –0.3 Madagascar 22.3 587.0 38 33 9.7 430 20.8 930 3.1 0.3 Malawi 15.9 118.5 169 16 5.0 320 11.6 730 1.9 –1.0 Malaysia 29.2 330.8 89 73 287.0 9,820 475.8 16,270 5.6 3.9 Maldives 0.3 0.3 1,128 42 1.9 5,750 2.6 7,560 3.4 1.4 Mali 14.9 1,240.2 12 36 9.8 660 16.9 1,140 –0.4 –3.3 Malta 0.4 0.3 1,311 95 8.3 19,710 11.3 26,930 1.0 0.2 Marshall Islands 0.1 0.2 292 72 0.2 4,040 b .. .. 1.9 1.8 Mauritania 3.8 1,030.7 4 42 4.2 1,110 9.4 2,480 7.6 4.9 Mauritius 1.3 2.0 636 42 11.1 8,570 19.5 15,060 3.2 2.8 Mexico 120.8 1,964.4 62 78 1,165.1 9,640 1,951.1 16,140 3.8 2.5 Micronesia, Fed. Sts. 0.1 0.7 148 23 0.3 3,230 0.4 a 3,920a 0.4 0.5 Moldova 3.6p 33.9 124p 48 7.4p 2,070p 12.9p 3,630p –0.8p –0.8p Monaco 0.0k 0.0h 18,790 100 .. ..d .. .. .. .. Mongolia 2.8 1,564.1 2 69 8.8 3,160 14.0 5,020 12.3 10.6 Montenegro 0.6 13.8 46 63 4.5 7,220 9.1 14,590 –0.5 –0.6 Morocco 32.5 446.6 73 57 97.9q 2,960q 167.4 q 5,060q 4.2q 2.7q Mozambique 25.2 799.4 32 31 12.8 510 25.3 1,000 7.4 4.7 Myanmar 52.8 676.6 81 33 .. ..o .. .. .. .. Namibia 2.3 824.3 3 39 12.7 5,610 16.4 7,240 5.0 3.1 Nepal 27.5 147.2 192 17 19.2 700 40.4 1,470 4.9 3.6 Netherlands 16.8 41.5 497 84 804.3 48,000 733.0 43,750 –1.2 –1.6 New Caledonia 0.3 18.6 14 62 .. ..d .. .. .. .. New Zealand 4.4 267.7 17 86 163.6 36,900 144.6 32,620 3.2 2.6 Nicaragua 6.0 130.4 50 58 9.9 1,650 23.3a 3,890a 5.2 3.7 Niger 17.2 1,267.0 14 18 6.7 390 13.0 760 10.8 6.7 14 World Development Indicators 2014 Front ? User guide World view People Environment World view 1 Population Surface Population Urban Gross national income Gross domestic area density population product Atlas method Purchasing power parity thousand people % of total Per capita Per capita Per capita millions sq. km per sq. km population $ billions $ $ billions $ % growth % growth 2012 2012 2012 2012 2012 2012 2012 2012 2011–12 2011–12 Nigeria 168.8 923.8 185 50 242.7 1,440 404.8 2,400 6.5 3.6 Northern Mariana Islands 0.1 0.5 116 92 .. ..d .. .. .. .. Norway 5.0 323.8 16 80 495.7 98,780 338.5 67,450 2.9 1.6 Oman 3.3 309.5 11 74 58.8 19,450 71.0 25,330 5.0 –7.1 Pakistan 179.2 796.1 232 37 225.1 1,260 516.5 2,880 4.0 2.3 Palau 0.0k 0.5 45 85 0.2 9,860 0.4 a 16,870a 5.3 4.5 Panama 3.8 75.4 51 76 32.4 8,510 57.6a 15,150a 10.7 8.9 Papua New Guinea 7.2 462.8 16 13 12.8 1,790 19.6a 2,740a 8.0 5.7 Paraguay 6.7 406.8 17 62 22.8 3,400 38.2 5,720 –1.2 –2.9 Peru 30.0 1,285.2 23 78 181.8 6,060 302.7 10,090 6.3 5.0 Philippines 96.7 300.0 324 49 241.7 2,500 423.6 4,380 6.8 5.0 Poland 38.5 312.7 127 61 488.0 12,660 838.6 21,760 1.8 1.8 Portugal 10.5 92.1 115 62 217.0 20,640 266.3 25,330 –3.2 –2.8 Puerto Rico 3.7 8.9 413 99 66.0 18,000 .. .. 0.5 1.3 Qatar 2.1 11.6 177 99 142.6 74,600 168.8 88,350 6.2 –1.0 Romania 20.1 238.4 87 53 171.9 8,560 354.3 17,650 0.4 0.7 Russian Federation 143.5 17,098.2 9 74 1,822.7 12,700 3,272.9 22,800 3.4 3.0 Rwanda 11.5 26.3 464 19 6.9 600 15.1 1,320 8.0 5.0 Samoa 0.2 2.8 67 20 0.6 3,260 0.8a 4,250a 2.9 2.1 San Marino 0.0k 0.1 521 94 .. ..d .. .. .. .. São Tomé and Príncipe 0.2 1.0 196 63 0.2 1,310 0.3 1,810 4.0 1.3 Saudi Arabia 28.3 2,149.7r 13 82 687.8 24,310 837.4 30,160 5.1 3.2 Senegal 13.7 196.7 71 43 14.2 1,030s 25.8 1,880 3.5 0.5 Serbia 7.2 88.4 83 57 38.1 5,280 82.6 11,430 –1.7 –1.2 Seychelles 0.1 0.5 192 54 1.1 12,180 2.3a 25,580a 2.8 1.8 Sierra Leone 6.0 71.7 83 40 3.5 580 8.0 1,340 15.2 13.0 Singapore 5.3 0.7 7,589 100 250.8 47,210 319.3 60,110 1.3 –1.1 Sint Maarten (Dutch part) 0.0k 0.0h 1,150 .. .. ..d .. .. .. .. Slovak Republic 5.4 49.0 112 55 93.0 17,190 137.5 25,430 1.8 1.6 Slovenia 2.1 20.3 102 50 46.9 22,810 58.1 28,240 –2.5 –2.7 Solomon Islands 0.5 28.9 20 21 0.6 1,130 1.2a 2,130a 3.9 1.7 Somalia 10.2 637.7 16 38 .. ..o .. .. .. .. South Africa 52.3 1,219.1 43 62 389.8 7,460 563.3 10,780 2.5 1.2 South Sudan 10.8 644.3 .. 18 8.6 790 .. .. –47.6 –49.8 Spain 46.8 505.6 94 78 1,368.8 29,270 1,485.1 31,760 –1.6 –1.7 Sri Lanka 20.3 65.6 324 15 59.3 2,920 122.5 6,030 6.4 9.2 St. Kitts and Nevis 0.1 0.3 206 32 0.7 13,610 0.9a 17,630a 6.9 5.7 St. Lucia 0.2 0.6 297 17 1.2 6,890 2.0a 11,300a 0.5 –0.4 St. Martin (French part) 0.0k 0.1 569 .. .. ..d .. .. .. .. St. Vincent & the Grenadines 0.1 0.4 280 50 0.7 6,400 1.2a 10,870a 2.3 2.3 Sudan 37.2 t 1,879.4t 20 33t 55.9 t 1,500 t 77.1t 2,070 t –10.1u 0.6u Suriname 0.5 163.8 3 70 4.6 8,680 4.5a 8,380a 3.9 2.9 Swaziland 1.2 17.4 72 21 3.5 2,860 5.9 4,760 –1.5 –3.0 Sweden 9.5 450.3 23 85 534.3 56,120 418.5 43,960 0.9 0.2 Switzerland 8.0 41.3 200 74 647.5 80,970 439.8 55,000 1.0 0.0 Syrian Arab Republic 22.4 185.2 122 56 .. ..j .. .. .. 0.8 Tajikistan 8.0 142.6 57 27 7.1 880 17.4 2,180 7.5 4.9 Economy States and markets Global links Back World Development Indicators 2014 15 1 World view Population Surface Population Urban Gross national income Gross domestic area density population product Atlas method Purchasing power parity thousand people % of total Per capita Per capita Per capita millions sq. km per sq. km population $ billions $ $ billions $ % growth % growth 2012 2012 2012 2012 2012 2012 2012 2012 2011–12 2011–12 Tanzania 47.8 947.3 54 27 26.7v 570 v 72.4v 1,560 v 6.9 v 3.7v Thailand 66.8 513.1 131 34 347.8 5,210 619.5 9,280 6.5 6.2 Timor-Leste 1.2 14.9 81 29 4.4 3,620 7.5a 6,230a 0.6 –2.3 Togo 6.6 56.8 122 39 3.3 500 6.0 900 5.6 2.9 Tonga 0.1 0.8 146 24 0.4 4,220 0.5a 5,020a 0.8 0.5 Trinidad and Tobago 1.3 5.1 261 14 19.7 14,710 30.6a 22,860a 1.5 1.2 Tunisia 10.8 163.6 69 67 44.8 4,150 99.2 9,210 3.6 2.6 Turkey 74.0 783.6 96 72 801.1 10,830 1,360.6 18,390 2.2 0.9 Turkmenistan 5.2 488.1 11 49 28.0 5,410 46.9a 9,070a 11.1 9.7 Turks and Caicos Islands 0.0k 1.0 34 94 .. ..d .. .. .. .. Tuvalu 0.0k 0.0h 329 51 0.1 5,650 .. .. 0.2 0.0 Uganda 36.3 241.6 182 16 17.6 480 47.1 1,300 3.4 0.0 Ukraine 45.6 603.6 79 69 159.6 3,500 327.1 7,180 0.2 0.4 United Arab Emirates 9.2 83.6 110 85 355.5 38,620 381.4 41,430 4.4 1.2 United Kingdom 63.6 243.6 263 80 2,448.8 38,500 2,266.0 35,620 0.3 –0.3 United States 313.9 9,831.5 34 83 16,430.4 52,340 16,514.5 52,610 2.8 2.0 Uruguay 3.4 176.2 19 93 46.1 13,580 52.0 15,310 3.9 3.6 Uzbekistan 29.8 447.4 70 36 51.2 1,720 109.1a 3,670a 8.2 6.6 Vanuatu 0.2 12.2 20 25 0.7 3,000 1.1a 4,300a 2.3 0.0 Venezuela, RB 30.0 912.1 34 94 373.3 12,460 386.9 12,920 5.6 4.0 Vietnam 88.8 331.0 286 32 137.5 1,550 321.4 3,620 5.2 4.1 Virgin Islands (U.S.) 0.1 0.4 301 96 .. ..d .. .. .. .. West Bank and Gaza 4.0 6.0 672 75 .. ..j .. .. .. .. Yemen, Rep. 23.9 528.0 45 33 30.4 1,270 55.1 2,310 0.1 –2.2 Zambia 14.1 752.6 19 40 19.0 1,350 22.4 1,590 7.2 3.9 Zimbabwe 13.7 390.8 35 39 8.9 650 .. .. 4.4 1.6 World 7,043.9 s 134,289.9 s 54 w 53 w 71,692.4 t 10,178 w 85,986.8 t 12,207 w 2.4 w 1.2 w Low income 846.5 16,197.8 56 28 499.4 590 1,171.1 1,383 6.3 4.0 Middle income 4,897.6 64,212.0 77 50 21,404.7 4,370 35,099.0 7,167 4.9 3.7 Lower middle income 2,507.0 20,739.9 122 39 4,745.3 1,893 9,718.6 3,877 4.7 3.2 Upper middle income 2,390.6 43,472.2 56 61 16,661.1 6,969 25,389.9 10,621 5.0 4.2 Low & middle income 5,744.1 80,409.9 73 46 21,916.1 3,815 36,250.5 6,311 4.9 3.6 East Asia & Pacific 1,991.6 16,301.6 126 50 9,727.7 4,884 15,451.5 7,758 7.5 6.7 Europe & Central Asia 270.8 6,478.6 43 60 1,804.4 6,664 3,234.8 11,946 1.8 1.1 Latin America & Carib. 581.4 19,460.9 30 79 5,273.2 9,070 6,852.9 11,787 2.9 1.7 Middle East & N. Africa 339.6 8,775.4 39 60 .. .. .. .. 1.9 0.2 South Asia 1,649.2 5,131.1 346 31 2,370.1 1,437 5,777.6 3,503 4.9 3.5 Sub-Saharan Africa 911.5 24,262.3 39 37 1,230.2 1,350 2,030.0 2,227 4.3 1.5 High income 1,299.8 53,880.1 25 80 49,905.7 38,394 50,055.1 38,509 1.5 1.2 Euro area 331.2 2,693.1 128 76 12,673.5 38,263 12,354.0 37,299 –0.6 0.0 a. Based on regression; others are extrapolated from the 2005 International Comparison Program benchmark estimates. b. Included in the aggregates for upper middle-income economies based on earlier data. c. Estimated to be upper middle income ($4,086–$12,615). d. Estimated to be high income ($12,616 or more). e. Included in the aggregates for high-income economies based on earlier data. f. Data series will be calculated once ongoing revisions to official statistics reported by the National Statistics and Censuses Institute of Argentina have been finalized. g. Data for Argentina are officially reported by the National Statistics and Censuses Institute of Argentina. The International Monetary Fund has, however, issued a declaration of censure and called on Argentina to adopt remedial measures to address the quality of official GDP and consumer price index data. Alternative data sources have shown significantly lower real growth and higher inflation than the official data since 2008. In this context, the World Bank is also using alternative data sources and estimates for the surveillance of macroeconomic developments in Argentina. h. Greater than 0 but less than 50. i. Data are for the area controlled by the government of Cyprus. j. Estimated to be lower middle income ($1,036–$4,085). k. Greater than 0 but less than 50,000. l. Excludes Abkhazia and South Ossetia. m. Refers to area free from ice. n. Greater than 0 but less than 0.5. o. Estimated to be low income ($1,035 or less). p. Excludes Transnistria. q. Includes Former Spanish Sahara. r. Provisional estimate. s. Included in the aggregates for lower middle-income economies based on earlier data. t. Excludes South Sudan. u. Excludes South Sudan after July 9, 2011. v. Covers mainland Tanzania only. 16 World Development Indicators 2014 Front ? User guide World view People Environment World view 1 About the data Population, land area, income (as measured by gross national income, the environmental effects of human activity. Innovations in satellite GNI), and output (as measured by gross domestic product, GDP) are mapping and computer databases have resulted in more precise basic measures of the size of an economy. They also provide a broad measurements of land and water areas. indication of actual and potential resources and are therefore used throughout World Development Indicators to normalize other indicators. Urban population There is no consistent and universally accepted standard for distin- Population guishing urban from rural areas, in part because of the wide variety Population estimates are usually based on national population cen- of situations across countries. Most countries use an urban clas- suses. Estimates for the years before and after the census are sification related to the size or characteristics of settlements. Some interpolations or extrapolations based on demographic models. define urban areas based on the presence of certain infrastructure Errors and undercounting occur even in high-income countries; in and services. And other countries designate urban areas based on developing countries errors may be substantial because of limits administrative arrangements. Because the estimates in the table in the transport, communications, and other resources required to are based on national definitions of what constitutes a city or met- conduct and analyze a full census. ropolitan area, cross-country comparisons should be made with The quality and reliability of official demographic data are also caution. To estimate urban populations, ratios of urban to total affected by public trust in the government, government commit- population obtained from the United Nations were applied to the ment to full and accurate enumeration, confidentiality and protection World Bank’s estimates of total population. against misuse of census data, and census agencies’ independence from political influence. Moreover, comparability of population indi- Size of the economy cators is limited by differences in the concepts, definitions, collec- GNI measures total domestic and foreign value added claimed by tion procedures, and estimation methods used by national statisti- residents. GNI comprises GDP plus net receipts of primary income cal agencies and other organizations that collect the data. (compensation of employees and property income) from nonresident Of the 214 economies in the table, 180 (about 86 percent) con- sources. GDP is the sum of gross value added by all resident pro- ducted a census during the 2000 census round (1995–2004). As ducers in the economy plus any product taxes (less subsidies) not of January 2014, 175 countries (about 82 percent) have completed included in the valuation of output. GNI is calculated without deduct- a census for the 2010 census round (2005–14). The currentness of ing for depreciation of fabricated assets or for depletion and degrada- a census and the availability of complementary data from surveys or tion of natural resources. Value added is the net output of an industry registration systems are important indicators of demographic data after adding up all outputs and subtracting intermediate inputs. The quality. See Primary data documentation for the most recent census industrial origin of value added is determined by the International or survey year and for the completeness of registration. Some Euro- Standard Industrial Classification revision 3 and revision 4. The World pean countries’ registration systems offer complete information on Bank uses GNI per capita in U.S. dollars to classify countries for ana- population in the absence of a census. lytical purposes and to determine borrowing eligibility. For definitions Current population estimates for developing countries that lack of the income groups in World Development Indicators, see User guide. recent census data and pre- and post-census estimates for coun- When calculating GNI in U.S. dollars from GNI reported in national tries with census data are provided by the United Nations Popula- currencies, the World Bank follows the World Bank Atlas conversion tion Division and other agencies. The cohort component method—a method, using a three-year average of exchange rates to smooth standard method for estimating and projecting population—requires the effects of transitory fluctuations in exchange rates. (For further fertility, mortality, and net migration data, often collected from sam- discussion of the World Bank Atlas method, see Statistical methods.) ple surveys, which can be small or limited in coverage. Population Because exchange rates do not always reflect differences in price estimates are from demographic modeling and so are susceptible to levels between countries, the table also converts GNI and GNI per biases and errors from shortcomings in the model and in the data. capita estimates into international dollars using purchasing power Because the fi ve-year age group is the cohort unit and fi ve-year parity (PPP) rates. PPP rates provide a standard measure allowing period data are used, interpolations to obtain annual data or single comparison of real levels of expenditure between countries, just as age structure may not reflect actual events or age composition. conventional price indexes allow comparison of real values over time. PPP rates are calculated by simultaneously comparing the prices Surface area of similar goods and services among a large number of countries. The surface area of an economy includes inland bodies of water In the most recent round of price surveys conducted by the Interna- and some coastal waterways. Surface area thus differs from land tional Comparison Program (ICP) in 2005, 146 countries and territo- area, which excludes bodies of water, and from gross area, which ries participated, including China for the first time, India for the first may include offshore territorial waters. Land area is particularly time since 1985, and almost all African countries. The PPP conver- important for understanding an economy’s agricultural capacity and sion factors presented in the table come from three sources. For Economy States and markets Global links Back World Development Indicators 2014 17 1 World view 47 high- and upper middle-income countries conversion factors are Population and Vital Statistics Report, the U.S. Bureau of the Cen- provided by Eurostat and the Organisation for Economic Co-operation sus’s International Data Base, and the Secretariat of the Pacific and Development (OECD); PPP estimates for these countries incor- Community’s Statistics and Demography Programme. porate new price data collected since 2005. For the remaining 2005 Data on surface and land area are from the Food and Agricul- ICP countries the PPP estimates are extrapolated from the 2005 ICP ture Organization, which gathers these data from national agen- benchmark results, which account for relative price changes between cies through annual questionnaires and by analyzing the results of each economy and the United States. For countries that did not par- national agricultural censuses. ticipate in the 2005 ICP round, the PPP estimates are imputed using Data on urban population shares are from United Nations Popula- a statistical model. More information on the results of the 2005 ICP tion Division (2012). is available at www.worldbank.org/data/icp. GNI, GNI per capita, GDP growth, and GDP per capita growth are Growth rates of GDP and GDP per capita are calculated using the least estimated by World Bank staff based on national accounts data col- squares method and constant price data in local currency. Constant lected by World Bank staff during economic missions or reported by price U.S. dollar series are used to calculate regional and income group national statistical offices to other international organizations such growth rates. The growth rates in the table are annual averages. Meth- as the OECD. PPP conversion factors are estimates by Eurostat/ ods of computing growth rates are described in Statistical methods. OECD and by World Bank staff based on data collected by the ICP. Definitions References • Population is based on the de facto definition of population, which Eurostat (Statistical Office of the European Communities). n.d. Demo- counts all residents regardless of legal status or citizenship—except graphic Statistics. [http://epp.eurostat.ec.europa.eu/portal/page for refugees not permanently settled in the country of asylum, who /portal/eurostat/home/]. Luxembourg. are generally considered part of the population of their country of OECD (Organisation for Economic Co-operation and Development). origin. The values shown are midyear estimates. • Surface area n.d. OECD.StatExtracts database. [http://stats.oecd.org/]. Paris. is a country’s total area, including areas under inland bodies of UNAIDS (Joint United Nations Programme on HIV/AIDS). 2013a. AIDS water and some coastal waterways. • Population density is midyear by Numbers. Geneva. population divided by land area. • Urban population is the midyear ———. 2013b. Global Report: UNAIDS Report on the Global AIDS Epi- population of areas defined as urban in each country and obtained demic 2013. [www.unaids.org/en/resources/publications/2013/]. by the United Nations. • Gross national income, Atlas method, is Geneva. the sum of value added by all resident producers plus any product UNFPA (United Nations Population Fund). 2014. Reproductive Health taxes (less subsidies) not included in the valuation of output plus website. [www.unfpa.org/rh/planning.htm]. net receipts of primary income (compensation of employees and UNICEF (United Nations Children’s Fund). 2013. Committing to Child property income) from abroad. Data are in current U.S. dollars con- Survival: A Promise Renewed—Progress Report 2013. [www.unicef verted using the World Bank Atlas method (see Statistical methods). .org/publications/files/APR_Progress_Report_2013_9_Sept_2013. • Gross national income, purchasing power parity, is GNI converted pdf]. New York. to international dollars using PPP rates. An international dollar has UN Inter-agency Group for Child Mortality Estimation. 2013. Levels the same purchasing power over GNI that a U.S. dollar has in the and Trends in Child Mortality: Report 2013. [www.childinfo.org/files United States. • Gross national income per capita is GNI divided by /Child_Mortality_Report_2013.pdf]. New York. midyear population. • Gross domestic product is the sum of value United Nations. 2013. The Millennium Development Goals Report added by all resident producers plus any product taxes (less subsi- 2013. [www.un.org/millenniumgoals/reports.shtml]. New York. dies) not included in the valuation of output. Growth is calculated United Nations Population Division. 2012. World Urbanization Pros- from constant price GDP data in local currency. • Gross domestic pects: The 2011 Revision. New York: United Nations, Department of product per capita is GDP divided by midyear population. Economic and Social Affairs. ———. 2013. World Population Prospects: The 2012 Revision. New Data sources York: United Nations, Department of Economic and Social Affairs. The World Bank’s population estimates are compiled and produced United Nations Statistics Division. Various years. Population and Vital by its Development Data Group in consultation with its Human Devel- Statistics Report. New York. opment Network, operational staff, and country offices. The United WHO (World Health Organization). 2013. World Malaria Report 2013. Nations Population Division (2013) is a source of the demographic Geneva. data for more than half the countries, most of them developing World Bank. 2011. The Changing Wealth of Nations: Measuring Sustain- countries. Other important sources are census reports and other able Development for the New Millennium. Washington, DC. statistical publications from national statistical offices, Eurostat’s ———. 2013. Global Monitoring Report 2013: Rural-Urban Dynamics Demographic Statistics, the United Nations Statistics Division’s and the Millennium Development Goals. Washington, DC. 18 World Development Indicators 2014 Front ? User guide World view People Environment World view 1 Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/1.1). To view a specific /indicator/SP.POP.TOTL). 1.1 Size of the economy Carbon dioxide emissions per capita EN.ATM.CO2E.PC Population SP.POP.TOTL Nationally protected terrestrial and marine Surface area AG.SRF.TOTL.K2 areas ER.PTD.TOTL.ZS Population density EN.POP.DNST Access to improved sanitation facilities SH.STA.ACSN Gross national income, Atlas method NY.GNP.ATLS.CD Internet users IT.NET.USER.PZ Gross national income per capita, Atlas method NY.GNP.PCAP.CD 1.4 Millennium Development Goals: overcoming obstacles Purchasing power parity gross national This table provides data on net official income NY.GNP.MKTP.PP.CD development assistance by donor, least developed countries’ access to high-income Purchasing power parity gross national markets, and the Debt Initiative for Heavily income, Per capita NY.GNP.PCAP.PP.CD Indebted Poor Countries. ..a Gross domestic product NY.GDP.MKTP.KD.ZG Gross domestic product, Per capita NY.GDP.PCAP.KD.ZG 1.5 Women in development Female population SP.POP.TOTL.FE.ZS 1.2 Millennium Development Goals: eradicating poverty Life expectancy at birth, Male SP.DYN.LE00.MA.IN and saving lives Share of poorest quintile in national Life expectancy at birth, Female SP.DYN.LE00.FE.IN consumption or income SI.DST.FRST.20 Pregnant women receiving prenatal care SH.STA.ANVC.ZS Vulnerable employment SL.EMP.VULN.ZS Teenage mothers SP.MTR.1519.ZS Prevalence of malnutrition, Underweight SH.STA.MALN.ZS Women in wage employment in nonagricultural sector SL.EMP.INSV.FE.ZS Primary completion rate SE.PRM.CMPT.ZS Unpaid family workers, Male SL.FAM.WORK.MA.ZS Ratio of girls to boys enrollments in primary and secondary education SE.ENR.PRSC.FM.ZS Unpaid family workers, Female SL.FAM.WORK.FE.ZS Under-five mortality rate SH.DYN.MORT Female part-time employment SL.TLF.PART.TL.FE.ZS Female legislators, senior officials, and 1.3 Millennium Development Goals: protecting our managers SG.GEN.LSOM.ZS common environment Women in parliaments SG.GEN.PARL.ZS Maternal mortality ratio, Modeled estimate SH.STA.MMRT Female-headed households SP.HOU.FEMA.ZS Contraceptive prevalence rate SP.DYN.CONU.ZS HIV prevalence SH.DYN.AIDS.ZS Data disaggregated by sex are available in Incidence of tuberculosis SH.TBS.INCD the World Development Indicators database. a. Available online only as part of the table, not as an individual indicator. Economy States and markets Global links Back World Development Indicators 2014 19 Poverty rates International poverty Population below international poverty linesa line in local currency Population Poverty gap Population Poverty Population Poverty gap Population Poverty below at $1.25 below gap at below at $1.25 below gap at $1.25 a day $2 a day Survey $1.25 a day a day $2 a day $2 a day Survey $1.25 a day a day $2 a day $2 a day 2005 2005 year b % % % % year b % % % % Albania 75.5 120.8 2005 <2 <0.5 7.9 1.5 2008 <2 <0.5 4.3 0.9 Algeria 48.4 c 77.5c 1988 7.6 1.2 24.6 6.7 1995 6.8 1.4 23.6 6.5 Angola 88.1 141.0 2000 54.3 29.9 70.2 42.4 2009 43.4 16.5 67.4 31.5 Argentina 1.7 2.7 2009d,e 2.0 1.2 3.4 1.7 2010d,e <2 0.7 <2 0.9 Armenia 245.2 392.4 2008 <2 <0.5 12.4 2.3 2010 2.5 <0.5 19.9 4.0 Azerbaijan 2,170.9 3,473.5 2001 6.3 1.1 27.1 6.8 2008 <2 <0.5 2.8 0.6 Bangladesh 31.9 51.0 2005 50.5 14.2 80.3 34.3 2010 43.3 11.2 76.5 30.4 Belarus 949.5 1,519.2 2010 <2 <0.5 <2 <0.5 2011 <2 <0.5 <2 <0.5 Belize 1.8 c 2.9c 1998f 11.3 4.7 26.3 10.0 1999 f 12.2 5.5 22.0 9.9 Benin 344.0 550.4 .. .. .. .. 2003 47.3 15.7 75.3 33.5 Bhutan 23.1 36.9 2007 10.2 1.8 29.8 8.5 2012 1.7 <0.5 12.6 2.6 Bolivia 3.2 5.1 2007e 13.1 6.6 24.7 10.9 2008e 15.6 8.6 24.9 13.1 Bosnia and Herzegovina 1.1 1.7 2004 <2 <0.5 <2 <0.5 2007 <2 <0.5 <2 <0.5 Botswana 4.2 6.8 1986 35.6 13.8 54.7 25.8 1994 31.2 11.0 49.4 22.3 Brazil 2.0 3.1 2008f 6.0 3.4 11.3 5.3 2009 f 6.1 3.6 10.8 5.4 Bulgaria 0.9 1.5 2003 <2 <0.5 <2 <0.5 2007 <2 <0.5 <2 <0.5 Burkina Faso 303.0 484.8 2003 56.5 20.3 81.2 39.3 2009 44.6 14.7 72.6 31.7 Burundi 558.8 894.1 1998 86.4 47.3 95.4 64.1 2006 81.3 36.4 93.5 56.1 Cabo Verde 97.7 156.3 .. .. .. .. 2002 21.0 6.1 40.9 15.2 Cambodia 2,019.1 3,230.6 2008 22.8 4.9 53.3 17.4 2009 18.6 3.6 49.5 15.1 Cameroon 368.1 589.0 2001 10.8 2.3 32.5 9.5 2007 9.6 1.2 30.4 8.2 Central African Republic 384.3 614.9 2003 62.4 28.3 81.9 45.3 2008 62.8 31.3 80.1 46.8 Chad 409.5 655.1 .. .. .. .. 2003 61.9 25.6 83.3 43.9 Chile 484.2 774.7 2006f <2 0.5 3.2 1.1 2009 f <2 0.7 2.7 1.2 China 5.1g 8.2g 2008h 13.1 3.2 29.8 10.1 2009h 11.8 2.8 27.2 9.1 Colombia 1,489.7 2,383.5 2009 f 9.7 4.7 18.5 8.2 2010 f 8.2 3.8 15.8 6.8 Comoros 368.0 588.8 .. .. .. .. 2004 46.1 20.8 65.0 34.2 Congo, Dem. Rep. 395.3 632.5 .. .. .. .. 2006 87.7 52.8 95.2 67.6 Congo, Rep. 469.5 751.1 .. .. .. .. 2005 54.1 22.8 74.4 38.8 Costa Rica 348.7c 557.9c 2008f 2.4 1.5 5.0 2.3 2009 f 3.1 1.8 6.0 2.7 Côte d’Ivoire 5.6 8.9 2004 <2 <0.5 <2 <0.5 2008 <2 <0.5 <2 <0.5 Croatia 19.0 30.4 1993e <2 <0.5 <2 <0.5 1996e <2 <0.5 <2 <0.5 Czech Republic 407.3 651.6 2002 23.3 6.8 46.8 17.6 2008 23.8 7.5 46.3 17.8 Djibouti 134.8 215.6 .. .. .. .. 2002 18.8 5.3 41.2 14.6 Dominican Republic 25.5c 40.8 c 2009 f 3.0 0.7 10.0 2.7 2010 f 2.2 <0.5 9.9 2.4 Ecuador 0.6 1.0 2009 f 6.4 2.9 13.5 5.5 2010 f 4.6 2.1 10.6 4.1 Egypt, Arab Rep. 2.5 4.0 2005 2.0 <0.5 18.5 3.5 2008 <2 <0.5 15.4 2.8 El Salvador 6.0 c 9.6c 2008f 5.4 1.9 14.0 4.8 2009 f 9.0 4.4 16.9 7.6 Estonia 11.0 17.7 2003 <2 <0.5 2.6 <0.5 2004 <2 <0.5 <2 0.5 Ethiopia 3.4 5.5 2005 39.0 9.6 77.6 28.9 2011 30.7 8.2 66.0 23.6 Fiji 1.9 3.1 2003 29.2 11.3 48.7 21.8 2009 5.9 1.1 22.9 6.0 Gabon 554.7 887.5 .. .. .. .. 2005 4.8 0.9 19.6 5.0 Gambia, The 12.9 20.7 1998 65.6 33.8 81.2 49.1 2003 29.8 9.8 55.9 24.4 Georgia 1.0 1.6 2009 15.2 4.2 32.7 11.6 2010 18.0 5.8 35.6 13.7 Ghana 5,594.8 8,951.6 1998 39.1 14.4 63.3 28.5 2006 28.6 9.9 51.8 21.3 Guatemala 5.7c 9.1c 2004f 24.4 13.2 39.2 20.2 2006f 13.5 4.7 26.3 10.5 Guinea 1,849.5 2,959.1 2003 56.3 21.3 80.8 39.7 2007 43.3 15.0 69.6 31.0 20 World Development Indicators 2014 Front ? User guide World view People Environment Poverty rates International poverty Population below international poverty linesa line in local currency Population Poverty gap Population Poverty Population Poverty gap Population Poverty below at $1.25 below gap at below at $1.25 below gap at $1.25 a day $2 a day Survey $1.25 a day a day $2 a day $2 a day Survey $1.25 a day a day $2 a day $2 a day 2005 2005 year b % % % % year b % % % % Guinea-Bissau 355.3 568.6 1993 52.1 20.6 75.7 37.4 2002 48.9 16.6 78.0 34.9 Guyana 131.5c 210.3c 1993e 6.9 1.5 17.1 5.4 1998e 8.7 2.8 18.0 6.7 Haiti 24.2c 38.7c .. .. .. .. 2001 61.7 32.3 77.5 46.7 Honduras 12.1c 19.3c 2008f 21.4 11.8 32.6 17.5 2009 f 17.9 9.4 29.8 14.9 Hungary 171.9 275.0 2004 <2 <0.5 <2 <0.5 2007 <2 <0.5 <2 <0.5 India 19.5i 31.2i 2005h 41.6 10.5 75.6 29.5 2010h 32.7 7.5 68.7 24.5 Indonesia 5,241.0i 8,385.7i 2010h 18.1 3.3 46.1 14.3 2011h 16.2 2.7 43.3 13.0 Iran, Islamic Rep. 3,393.5 5,429.6 1998 <2 <0.5 8.3 1.8 2005 <2 <0.5 8.0 1.8 Iraq 799.8 1,279.7 .. .. .. .. 2007 2.8 <0.5 21.4 4.4 Jamaica 54.2c 86.7c 2002 <2 <0.5 8.5 1.5 2004 <2 <0.5 5.4 0.8 Jordan 0.6 1.0 2008 <2 <0.5 2.1 <0.5 2010 <2 <0.5 <2 <0.5 Kazakhstan 81.2 129.9 2008 <2 <0.5 <2 <0.5 2009 <2 <0.5 <2 <0.5 Kenya 40.9 65.4 1997 19.6 4.6 42.7 14.7 2005 43.4 16.9 67.2 31.8 Kyrgyz Republic 16.2 26.0 2010 6.7 1.5 22.9 6.4 2011 5.0 1.1 21.6 5.4 Lao PDR 4,677.0 7,483.2 2002 44.0 12.1 76.9 31.1 2008 33.9 9.0 66.0 24.8 Latvia 0.4 0.7 2008 <2 <0.5 <2 <0.5 2009 <2 <0.5 <2 <0.5 Lesotho 4.3 6.9 1994 46.2 25.6 59.7 36.1 2003 43.4 20.8 62.3 33.1 Liberia 0.6 1.0 .. .. .. .. 2007 83.8 40.9 94.9 59.6 Lithuania 2.1 3.3 2004 <2 <0.5 <2 0.5 2008 <2 <0.5 <2 <0.5 Macedonia, FYR 29.5 47.2 2009 <2 <0.5 5.9 0.9 2010 <2 <0.5 6.9 1.2 Madagascar 945.5 1,512.8 2005 67.8 26.5 89.6 46.9 2010 81.3 43.3 92.6 60.1 Malawi 71.2 113.8 2004 73.9 32.3 90.5 51.8 2010 61.6 26.2 82.3 44.0 Malaysia 2.6 4.2 2007e <2 <0.5 2.9 <0.5 2009e <2 <0.5 2.3 <0.5 Maldives 358.3 573.5 1998 25.6 13.1 37.0 20.0 2004 <2 <0.5 12.2 2.5 Mali 362.1 579.4 2006 51.4 18.8 77.1 36.5 2010 50.4 16.4 78.7 35.2 Mauritania 157.1 251.3 2004 25.4 7.0 52.6 19.2 2008 23.4 6.8 47.7 17.7 Mexico 9.6 15.3 2008 <2 <0.5 5.2 1.3 2010 <2 <0.5 4.5 1.0 Micronesia, Fed. Sts. 0.8 c 1.3c .. .. .. .. 2000 d 31.2 16.3 44.7 24.5 Moldova 6.0 9.7 2009 <2 <0.5 7.1 1.2 2010 <2 <0.5 4.4 0.7 Montenegro 0.6 1.0 2009 <2 <0.5 <2 <0.5 2010 <2 <0.5 <2 <0.5 Morocco 6.9 11.0 2001 6.3 0.9 24.3 6.3 2007 2.5 0.5 14.0 3.2 Mozambique 14,532.1 23,251.4 2003 74.7 35.4 90.0 53.6 2008 59.6 25.1 81.8 42.9 Namibia 6.3 10.1 1993e 49.1 24.6 62.2 36.5 2004 e 31.9 9.5 51.1 21.8 Nepal 33.1 52.9 2003 53.1 18.4 77.3 36.6 2010 24.8 5.6 57.3 19.0 Nicaragua 9.1c 14.6c 2001e 14.4 3.7 34.4 11.5 2005e 11.9 2.4 31.7 9.6 Niger 334.2 534.7 2005 50.2 18.3 75.3 35.6 2008 43.6 12.4 75.2 30.8 Nigeria 98.2 157.2 2004 63.1 28.7 83.1 45.9 2010 68.0 33.7 84.5 50.2 Pakistan 25.9 41.4 2006 22.6 4.1 61.0 18.8 2008 21.0 3.5 60.2 17.9 Panama 0.8c 1.2c 2009 f 5.9 1.8 14.6 4.9 2010 f 6.6 2.1 13.8 5.1 Papua New Guinea 2.1c 3.4 c .. .. .. .. 1996 35.8 12.3 57.4 25.5 Paraguay 2,659.7 4,255.6 2009 f 7.6 3.2 14.2 6.0 2010 f 7.2 3.0 13.2 5.7 Peru 2.1 3.3 2009 f 5.5 1.6 14.0 4.6 2010 f 4.9 1.3 12.7 4.1 Philippines 30.2 48.4 2006 22.6 5.5 45.0 16.4 2009 18.4 3.7 41.5 13.8 Poland 2.7 4.3 2010 <2 <0.5 <2 <0.5 2011 <2 <0.5 <2 <0.5 Romania 2.1 3.4 2010 <2 <0.5 <2 0.5 2011 <2 <0.5 <2 <0.5 Russian Federation 16.7 26.8 2008 <2 <0.5 <2 <0.5 2009 <2 <0.5 <2 <0.5 Rwanda 295.9 473.5 2006 72.1 34.8 87.4 52.2 2011 63.2 26.6 82.4 44.6 Economy States and markets Global links Back World Development Indicators 2014 21 Poverty rates International poverty Population below international poverty linesa line in local currency Population Poverty gap Population Poverty Population Poverty gap Population Poverty below at $1.25 below gap at below at $1.25 below gap at $1.25 a day $2 a day Survey $1.25 a day a day $2 a day $2 a day Survey $1.25 a day a day $2 a day $2 a day 2005 2005 year b % % % % year b % % % % São Tomé and Príncipe 7,953.9 12,726.3 .. .. .. .. 2001 28.2 7.9 54.2 20.6 Senegal 372.8 596.5 2005 33.5 10.8 60.4 24.7 2011 29.6 9.1 55.2 21.9 Serbia 42.9 68.6 2009 <2 <0.5 <2 <0.5 2010 <2 <0.5 <2 <0.5 Seychelles 5.6c 9.0 c 2000 <2 <0.5 <2 <0.5 2007 <2 <0.5 <2 <0.5 Sierra Leone 1,745.3 2,792.4 2003 53.4 20.3 76.1 37.5 2011 51.7 16.6 79.6 35.8 Slovak Republic 23.5 37.7 2008e <2 <0.5 <2 <0.5 2009e <2 <0.5 <2 <0.5 Slovenia 198.2 317.2 2003 <2 <0.5 <2 <0.5 2004 <2 <0.5 <2 <0.5 South Africa 5.7 9.1 2006 17.4 3.3 35.7 12.3 2009 13.8 2.3 31.3 10.2 Sri Lanka 50.0 80.1 2007 7.0 1.0 29.1 7.4 2010 4.1 0.7 23.9 5.4 St. Lucia 2.4 c 3.8 c .. .. .. .. 1995 20.9 7.2 40.6 15.5 Sudan 154.4 247.0 .. .. .. .. 2009 19.8 5.5 44.1 15.4 Suriname 2.3c 3.7c .. .. .. .. 1999 15.5 5.9 27.2 11.7 Swaziland 4.7 7.5 2001 62.9 29.4 81.0 45.8 2010 40.6 16.0 60.4 29.3 Syrian Arab Republic 30.8 49.3 .. .. .. .. 2004 <2 <0.5 16.9 3.3 Tajikistan 1.2 1.9 2007 14.7 4.4 37.0 12.2 2009 6.6 1.2 27.7 7.0 Tanzania 603.1 964.9 2000 84.6 41.6 95.3 60.3 2007 67.9 28.1 87.9 47.5 Thailand 21.8 34.9 2009j <2 <0.5 4.6 0.8 2010j <2 <0.5 4.1 0.7 Togo 352.8 564.5 2006 38.7 11.4 69.3 27.9 2011 28.2 8.8 52.7 20.9 Trinidad and Tobago 5.8 c 9.2c 1988e <2 <0.5 8.6 1.9 1992e 4.2 1.1 13.5 3.9 Tunisia 0.9 1.4 2005 <2 <0.5 8.1 1.8 2010 <2 <0.5 4.3 1.1 Turkey 1.3 2.0 2009 <2 <0.5 2.7 0.7 2010 <2 <0.5 4.7 1.4 Turkmenistan 5,961.1c 9,537.7c 1993e 63.5 25.8 85.7 44.9 1998e 24.8 7.0 49.7 18.4 Uganda 930.8 1,489.2 2006 51.5 19.1 75.6 36.4 2009 38.0 12.2 64.7 27.4 Ukraine 2.1 3.4 2009 <2 <0.5 <2 <0.5 2010 <2 <0.5 <2 <0.5 Uruguay 19.1 30.6 2009 f <2 <0.5 <2 <0.5 2010 f <2 <0.5 <2 <0.5 Venezuela, RB 1,563.9 2,502.2 2005f 13.4 8.2 21.9 11.6 2006f 6.6 3.7 12.9 5.9 Vietnam 7,399.9 11,839.8 2006 21.4 5.3 48.1 16.3 2008 16.9 3.8 43.4 13.5 West Bank and Gaza 2.7c 4.3c 2007 <2 <0.5 2.5 0.5 2009 <2 <0.5 <2 <0.5 Yemen, Rep. 113.8 182.1 1998 12.9 3.0 36.4 11.1 2005 17.5 4.2 46.6 14.8 Zambia 3,537.9 5,660.7 2006 68.5 37.0 82.6 51.8 2010 74.5 41.9 86.6 56.8 a. Based on nominal per capita consumption averages and distributions estimated parametrically from grouped household survey data, unless otherwise noted. b. Refers to the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected. c. Based on purchasing power parity (PPP) dollars imputed using regression. d. Covers urban areas only. e. Based on per capita income averages and distribution data estimated parametrically from grouped household survey data. f. Estimated nonparametrically from nominal income per capita distributions based on unit-record household survey data. g. PPP conversion factor based on urban prices. h. Population-weighted average of urban and rural estimates. i. Based on benchmark national PPP estimate rescaled to account for cost-of-living differences in urban and rural areas. j. Estimated nonparametrically from nominal consumption per capita distributions based on unit-record household survey data. 22 World Development Indicators 2014 Front ? User guide World view People Environment Poverty rates Trends in poverty indicators by region, 1990–2015 Region 1990 1993 1996 1999 2002 2005 2008 2010 estimate 2015 forecast Trend, 1990–2010 Share of population living on less than 2005 PPP $1.25 a day (%) East Asia & Pacific 56.2 50.7 35.9 35.6 27.6 17.1 14.3 12.5 5.5 Europe & Central Asia 1.9 2.9 3.9 3.8 2.3 1.3 0.5 0.7 0.4 Latin America & Caribbean 12.2 11.4 11.1 11.9 11.9 8.7 6.5 5.5 4.9 Middle East & North Africa 5.8 4.8 4.8 5.0 4.2 3.5 2.7 2.4 2.6 South Asia 53.8 51.7 48.6 45.1 44.3 39.4 36.0 31.0 23.2 Sub- Saharan Africa 56.5 59.4 58.1 57.9 55.7 52.3 49.2 48.5 42.3 Total 43.1 41.0 34.8 34.1 30.8 25.1 22.7 20.6 15.5 People living on less than 2005 PPP $1.25 a day (millions) East Asia & Pacific 926 871 640 656 523 332 284 251 115 Europe & Central Asia 9 14 18 18 11 6 2 3 2 Latin America & Caribbean 53 53 54 60 63 48 37 32 30 Middle East & North Africa 13 12 12 14 12 10 9 8 9 South Asia 617 632 631 619 640 598 571 507 406 Sub- Saharan Africa 290 330 349 376 390 395 399 414 408 Total 1,908 1,910 1,704 1,743 1,639 1,389 1,302 1,215 970 Regional distribution of people living on less than $1.25 a day (% of total population living on less than $1.25 a day) East Asia & Pacific 48.5 45.6 37.6 37.6 31.9 23.9 21.8 20.7 11.8 Europe & Central Asia 0.5 0.7 1.1 1.0 0.6 0.5 0.2 0.3 0.2 Latin America & Caribbean 2.8 2.7 3.1 3.4 3.8 3.4 2.9 2.7 3.1 Middle East & North Africa 0.7 0.6 0.7 0.8 0.7 0.8 0.7 0.7 1.0 South Asia 32.3 33.1 37.0 35.5 39.1 43.1 43.8 41.7 41.9 Sub- Saharan Africa 15.2 17.3 20.5 21.6 23.8 28.4 30.7 34.1 42.1 Average daily consumption or income of people living on less than 2005 PPP $1.25 a day (2005 PPP $) East Asia & Pacific 0.83 0.85 0.89 0.87 0.89 0.95 0.95 0.97 .. Europe & Central Asia 0.90 0.90 0.91 0.92 0.93 0.88 0.88 0.85 .. Latin America & Caribbean 0.71 0.69 0.68 0.67 0.65 0.63 0.62 0.60 .. Middle East & North Africa 1.02 1.02 1.01 1.01 1.01 0.99 0.97 0.96 .. South Asia 0.88 0.89 0.91 0.91 0.92 0.94 0.95 0.96 .. Sub- Saharan Africa 0.69 0.68 0.69 0.69 0.70 0.71 0.71 0.71 .. Total 0.82 0.83 0.85 0.84 0.85 0.87 0.87 0.87 .. Survey coverage (% of total population represented by underlying survey data) East Asia & Pacific 92.4 93.3 93.7 93.4 93.5 93.2 93.6 93.5 .. Europe & Central Asia 81.5 87.3 97.1 93.9 96.3 94.7 89.9 85.3 .. Latin America & Caribbean 94.9 91.8 95.9 97.7 97.5 95.9 94.5 86.9 .. Middle East & North Africa 76.8 65.3 81.7 70.0 21.5 85.7 46.7 30.8 .. South Asia 96.5 98.2 98.1 20.1 98.0 98.0 97.9 94.5 .. Sub- Saharan Africa 46.0 68.8 68.0 53.1 65.7 82.7 81.7 64.1 .. Total 86.4 89.4 91.6 68.2 87.8 93.0 90.2 84.7 .. Source: World Bank PovcalNet. Economy States and markets Global links Back World Development Indicators 2014 23 Poverty rates About the data The World Bank produced its first global poverty estimates for devel- countries. The availability and quality of poverty monitoring data oping countries for World Development Report 1990: Poverty (World remain low in small states, fragile situations, and low-income coun- Bank 1990) using household survey data for 22 countries (Ravallion, tries and even some middle-income countries. Datt, and van de Walle 1991). Since then there has been consid- The low frequency and lack of comparability of the data available erable expansion in the number of countries that field household in some countries create uncertainty over the magnitude of poverty income and expenditure surveys. The World Bank’s Development reduction. The table on trends in poverty indicators reports the Research Group maintains a database that is updated regularly as percentage of the regional and global population represented by new survey data become available (and thus may contain more recent household survey samples collected during the reference year or data or revisions that are not incorporated into the table) and con- during the two preceding or two subsequent years (in other words, ducts a major reassessment of progress against poverty about every within a five-year window centered on the reference year). Data cov- three years. The next comprehensive reassessment is due later this erage in Sub- Saharan Africa and the Middle East and North Africa year, and revised and updated poverty data will be published in the remains low and variable. The need to improve household survey World Development Indicators online tables and database. programs for monitoring poverty is clearly urgent. But institutional, Last year the World Bank published the 2010 extreme poverty esti- political, and financial obstacles continue to limit data collection, mates for developing country regions and the developing world as a analysis, and public access. whole (that is, countries classified as low and middle income in 1990). They are provisional due to low household survey data availability for Data quality recent years (2008–12). Because about 40 new surveys have become Besides the frequency and timeliness of survey data, other data available this year, the provisional 2010 estimates will be revised into quality issues arise in measuring household living standards. The 2011 estimates during the aforementioned comprehensive reassess- surveys ask detailed questions on sources of income and how it ment. The projections to 2015, which will also be revised later this was spent, which must be carefully recorded by trained personnel. year, use the 2010 provisional estimates as a baseline and assume Income is generally more difficult to measure accurately, and con- that average household income or consumption will grow in line with sumption comes closer to the notion of living standards. And income the aggregate economic projections reported in Global Economic Pros- can vary over time even if living standards do not. But consumption pects 2014 (World Bank 2014) but that inequality within countries data are not always available: the latest estimates reported here will remain unchanged. Estimates of the number of people living in use consumption for about two-thirds of countries. extreme poverty are based on population projections in the World However, even similar surveys may not be strictly comparable Bank’s HealthStats database (http://datatopics.worldbank.org/hnp). because of differences in timing, sampling frames, or the quality PovcalNet (http://iresearch.worldbank.org/PovcalNet) is an inter- and training of enumerators. Comparisons of countries at different active computational tool that allows users to replicate these inter- levels of development also pose a potential problem because of dif- nationally comparable $1.25 and $2 a day poverty estimates for ferences in the relative importance of the consumption of nonmarket countries, developing country regions, and the developing world as a goods. The local market value of all consumption in kind (including whole and to compute poverty measures for custom country group- own production, particularly important in underdeveloped rural econ- ings and for different poverty lines. The Poverty and Equity Data portal omies) should be included in total consumption expenditure, but (http://povertydata.worldbank.org/poverty/home) provides access to may not be. Most survey data now include valuations for consump- the database and user-friendly dashboards with graphs and interac- tion or income from own production, but valuation methods vary. tive maps that visualize trends in key poverty and inequality indicators The statistics reported here are based on consumption data or, for different regions and countries. The country dashboards display when unavailable, on income data. Analysis of some 20 countries trends in poverty measures based on the national poverty lines (see for which both consumption and income data were available from the online table 2.7) alongside the internationally comparable estimates same surveys found income to yield a higher mean than consumption in the table, produced from and consistent with PovcalNet. but also higher inequality. When poverty measures based on con- sumption and income were compared, the two effects roughly can- Data availability celled each other out: there was no significant statistical difference. The World Bank’s internationally comparable poverty monitoring Invariably some sampled households do not participate in surveys database now draws on income or detailed consumption data because they refuse to do so or because nobody is at home during the collected from interviews with 1.23 million randomly sampled interview visit. This is referred to as “unit nonresponse” and is distinct households through more than 850 household surveys collected from “item nonresponse,” which occurs when some of the sampled by national statistical offices in nearly 130 countries. Despite prog- respondents participate but refuse to answer certain questions, such ress in the last decade, the challenges of measuring poverty remain. as those pertaining to income or consumption. To the extent that The timeliness, frequency, quality, and comparability of household survey nonresponse is random, there is no concern regarding biases surveys need to increase substantially, particularly in the poorest in survey-based inferences; the sample will still be representative 24 World Development Indicators 2014 Front ? User guide World view People Environment Poverty rates of the population. However, households with different income might Definitions not be equally likely to respond. Richer households may be less likely • International poverty line in local currency is the international to participate because of the high opportunity cost of their time or poverty lines of $1.25 and $2.00 a day in 2005 prices, converted concerns about intrusion in their affairs. It is conceivable that the to local currency using the PPP conversion factors estimated by poorest can likewise be underrepresented; some are homeless or the International Comparison Program. • Survey year is the year in nomadic and hard to reach in standard household survey designs, and which the underlying data were collected or, when the data collection some may be physically or socially isolated and thus less likely to be period bridged two calendar years, the year in which most of the data interviewed. This can bias both poverty and inequality measurement were collected. • Population below $1.25 a day and population if not corrected for (Korinek, Mistiaen, and Ravallion 2007). below $2 a day are the percentages of the population living on less than $1.25 a day and $2 a day at 2005 international prices. As a International poverty lines result of revisions in PPP exchange rates, consumer price indexes, International comparisons of poverty estimates entail both concep- or welfare aggregates, poverty rates for individual countries cannot tual and practical problems. Countries have different definitions of be compared with poverty rates reported in earlier editions. The poverty, and consistent comparisons across countries can be diffi - PovcalNet online database and tool (http://iresearch.worldbank cult. Local poverty lines tend to have higher purchasing power in rich .org/PovcalNet) always contain the most recent full time series of countries, where more generous standards are used, than in poor comparable country data. • Poverty gap is the mean shortfall from countries. Poverty measures based on an international poverty line the poverty line (counting the nonpoor as having zero shortfall), attempt to hold the real value of the poverty line constant across expressed as a percentage of the poverty line. This measure reflects countries, as is done when making comparisons over time. Since the depth of poverty as well as its incidence. World Development Report 1990 the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what Data sources poverty means in the world’s poorest countries. The welfare of people The poverty measures are prepared by the World Bank’s Develop- living in different countries can be measured on a common scale by ment Research Group. The international poverty lines are based on adjusting for differences in the purchasing power of currencies. The nationally representative primary household surveys conducted by commonly used $1 a day standard, measured in 1985 international national statistical offices or by private agencies under the supervi- prices and adjusted to local currency using purchasing power parities sion of government or international agencies and obtained from (PPPs), was chosen for World Development Report 1990 because it government statistical offices and World Bank Group country depart- was typical of the poverty lines in low-income countries at the time. ments. For details on data sources and methods used in deriving Early editions of World Development Indicators used PPPs from the the World Bank’s latest estimates, see http://iresearch.worldbank Penn World Tables to convert values in local currency to equivalent .org/povcalnet. purchasing power measured in U.S dollars. Later editions used 1993 consumption PPP estimates produced by the World Bank. References International poverty lines were recently revised using the new data Chen, Shaohua, and Martin Ravallion. 2011. “The Developing World on PPPs compiled in the 2005 round of the International Comparison Is Poorer Than We Thought, But No Less Successful in the Fight Program, along with data from an expanded set of household income Against Poverty.” Quarterly Journal of Economics 125(4): 1577–625. and expenditure surveys. The new extreme poverty line is set at Korinek, Anton, Johan A. Mistiaen, and Martin Ravallion. 2007. “An $1.25 a day in 2005 PPP terms, which represents the mean of the Econometric Method of Correcting for Unit Nonresponse Bias in poverty lines found in the poorest 15 countries ranked by per capita Surveys.” Journal of Econometrics 136: 213–35. consumption. The new poverty line maintains the same standard for Ravallion, Martin, Guarav Datt, and Dominique van de Walle. 1991. extreme poverty—the poverty line typical of the poorest countries “Quantifying Absolute Poverty in the Developing World.” Review of in the world—but updates it using the latest information on the cost Income and Wealth 37(4): 345–61. of living in developing countries. PPP exchange rates are used to Ravallion, Martin, Shaohua Chen, and Prem Sangraula. 2009. “Dol- estimate global poverty because they take into account the local lar a Day Revisited.” World Bank Economic Review 23(2): 163–84. prices of goods and services not traded internationally. But PPP rates World Bank. 1990. World Development Report 1990: Poverty. Wash- were designed for comparing aggregates from national accounts, not ington, DC. for making international poverty comparisons. As a result, there is ———. 2008. Poverty Data: A Supplement to World Development Indi- no certainty that an international poverty line measures the same cators 2008. Washington, DC. degree of need or deprivation across countries. So-called poverty ———. 2014. Global Economic Prospects: Coping with Policy Normal- PPPs, designed to compare the consumption of the poorest people ization in High-income Countries. Volume 8, January 14. Washington, in the world, might provide a better basis for comparison of poverty DC. across countries. Work on these measures is ongoing. Economy States and markets Global links Back World Development Indicators 2014 25 PEOPLE 26 World Development Indicators 2014 Front ? User guide World view People Environment 2 The People section presents demographic trends and quality. These efforts range from providing and forecasts alongside indicators of education, technical and financial assistance for strength- health, jobs, social protection, poverty, and the ening country statistical systems to fostering distribution of income. Together they provide a international collaboration through participation multidimensional portrait of human development. in the United Nations Inter-agency and Expert This edition includes estimates of extreme Group on the Millennium Development Goal Indi- poverty rates for 2010—measured as the pro- cators and several thematic interagency groups. portion of the population living on less than For example, estimates of child mortality in $1.25 a day. The availability, frequency, and 2000 varied by source, method, and availability, quality of poverty monitoring data remain low, making comparisons across countries and over especially in small states and in countries and time difficult. To address this, a UN interagency territories with fragile situations. While esti- group has improved methods and harmoniza- mates may change marginally as additional coun- tion, shared sources, reported on progress, and try data become available, it is now clear that helped boost countries’ measurement capacity. the first Millennium Development Goal target— This effort has produced consistent estimates of cutting the global extreme poverty rate to half neonatal, infant, and under-five mortality rates its 1990 level—was achieved before the 2015 that span 50 years. Similar interagency efforts target date. In 1990, the benchmark year for the are improving maternal mortality estimates and Millennium Development Goals, the extreme pov- gender statistics. For gender an interagency and erty rate was 43.1 percent. Estimates for 2010 expert group has endorsed a set of indicators show that the extreme poverty rate had fallen to guide national efforts to produce, compile, to 20.6 percent. The World Bank is working to and disseminate comparable gender statistics. create a complementary dataset to measure the As part of this work, the World Bank is provid- goal of promoting shared prosperity, using the ing technical assistance and training to national per capita incomes of the bottom 40 percent of statistical offices, and new partnerships and ini- the population in each country. To be released tiatives, such as Evidence and Data for Gender at the 2014 Annual Meetings of the World Bank, Statistics and Data2X, are facilitating interna- the dataset will be included in future World Devel- tional action and collaboration. opment Indicators. People includes indicators disaggregated by In addition to extreme poverty rates, the location and by socioeconomic and demographic People section includes many other indicators variables, such as sex, age, subnational and to monitor the Millennium Development Goals. regional location, and wealth. These data provide Following the Millennium Declaration by the important perspectives on the disparities within United Nations General Assembly in 2000, vari- countries. New for the 2014 edition is an indi- ous international agencies, including the World cator of severe wasting, disaggregated by sex. Bank, resolved to monitor the Millennium Devel- Other new indicators include national estimates opment Goals using a harmonized set of indica- for labor force participation rates and ratios of tors and to invest in improving data availability employment to population. Economy States and markets Global links Back World Development Indicators 2014 27 Highlights Lower secondary completion rates fell only in the Middle East and North Africa Completion rate, lower secondary education Over the past 20 years lower secondary completion rates have increased (% of relevant age group) 66 percent in low- and middle-income countries. East Asia and Pacific 125 has seen the most progress, with the rate doubling to 99 percent over East Asia & Pacific 1990–2011. Until the mid-1990s the Middle East and North Africa 100 was on par with East Asia and Pacific, but upward trajectories in many of the region’s countries have not been enough to offset Iran’s decline Middle East & North Africa 75 since 2003. In Sub-Saharan Africa only 26 percent of students in the final grade of lower secondary education completed school in 2011, Low & middle income 50 compared with 70 percent of students in the final grade of primary education. Given that these rates are an upper estimate of actual Sub-Saharan Africa 25 completion rates, the real situation is likely to be worse. 0 1990 1995 2000 2005 2011 Source: United Nations Educational, Scientific and Cultural Organization Institute for Statistics. Europe and Central Asia has the lowest gap between net and gross enrollment rates Gross enrollment ratio, primary education, 2011 (%) The gap between net and gross enrollment rates captures the incidence Share of underage or overage students Net enrollment rate of underage or overage students and is a measure of the efficiency of 125 an education system. In Sub-Saharan Africa 42 percent of children enrolled in primary education dropped out in 2011, giving the region 100 the highest dropout rate, repetition rate, and gap between gross and 75 net enrollment. Latin America and Caribbean’s net enrollment rate is almost the same as Europe and Central Asia’s, but the gap is wider in 50 the former. This suggests that the education system is more efficient Europe and Central Asia, which has the lowest repeater rate and drop- 25 out rate. 0 Sub-Saharan South Latin East Asia Middle East Europe Africa Asia America & & Pacific & North & Central Caribbean Africa Asia Source: United Nations Educational, Scientific and Cultural Organization Institute for Statistics. In 2012 child wasting was most serious in South Asia Prevalence of wasting among children ages 0–59 months, 2012 (%) Wasting, defined as weight for height more than two standard devia- 95% lower confidence limit Prevalence estimate 95% upper confidence limit tions below the median for the international reference population ages 20 WHO severity level classification Critical 0–59 months, is a measure for acute malnutrition. World Health Orga- nization (WHO) member countries have endorsed a global nutrition 15 Poor target to reduce the prevalence of child wasting to less than 5 percent by 2025. In 2012 the prevalence was estimated at 8.5 percent for all Public health emergency line 10 Serious developing countries and was below 5 percent in three out of the six World Bank developing regions. In the Middle East and North Africa 5 Acceptable and Sub- Saharan Africa the prevalence was above 5 percent but below the WHO Public Health Emergency Line of 10 percent. South Asia had the highest prevalence, 16 percent, which is considered critical in the 0 Latin Europe East Asia Middle All Sub- South WHO severity level classification. America & & Central & Pacific East & developing Saharan Asia Caribbean Asia North Africa countries Africa Source: UNICEF, WHO, and World Bank 2013. 28 World Development Indicators 2014 Front ? User guide World view People Environment Most maternal deaths are in Sub-Saharan Africa and South Asia In 2010, 85 percent of the world’s maternal deaths occurred in Sub- Share of global maternal deaths (%) Saharan Africa and South Asia. Although the number of maternal High income Europe & Central Asia 100 deaths has been falling in every region—globally from 540,000 to Middle East & North Africa Latin America & Caribbean East Asia & Pacific 290,000 over 1990–2010—the share of maternal deaths is increas- ingly concentrated in these two regions. In 2010 more than half of 75 maternal deaths occurred in Sub- Saharan Africa, and 29  percent South Asia occurred in South Asia. In Sub- Saharan Africa the share of global 50 maternal deaths increased from 35 percent in 1990 to 57 percent in 2010, suggesting a rate of decline that is slower than in other regions. In South Asia the share decreased from 45 percent in 1990 25 to 29 percent in 2010, but it still has the second largest share of global maternal deaths. Sub-Saharan Africa 0 1990 1995 2000 2005 2010 Source: WHO and others 2012. Globally, a large proportion of under-five deaths occur in the first 28 days of life The first 28 days of life (the neonatal period) are the most vulner- Proportion of deaths among children under age 5 that occur during the neonatal period (%) able time for a child’s survival. The proportion of deaths among chil- 60 dren under age 5 that occur in the neonatal period is large and has increased in all regions since 1990, although neonatal mortality rates have been falling in every region. Declines in the neonatal mortality 40 rate are slower than those in the under-fi ve mortality rate: between 1990 and 2012 global neonatal mortality rates fell from 33 deaths per 1,000 births to 21, but the proportion of neonatal deaths in under- fi ve deaths increased from 37 percent to 44 percent. In 2012 the 20 proportion was more than 50 percent in four regions: Middle East 1990 2012 and North Africa, East Asia and Pacific, South Asia, and Latin America and the Caribbean. 0 Middle East East Asia South Latin Europe Sub-Saharan World & North & Pacific Asia America & & Central Africa Africa Caribbean Asia Source: UN Inter-agency Group for Child Mortality Estimation 2013. Over 20 percent of ministers in Latin America and Sub-Saharan Africa are women With over 20  percent of ministers being women, Latin America Women in ministerial positions (% of total) and Caribbean and Sub- Saharan Africa lead developing regions in 25 women’s participation in ministerial positions. Women occupy over Latin America & Caribbean 40 percent of ministerial positions in Cabo Verde, Ecuador, Bolivia, 20 Nicaragua, and South Africa. However, even with these achieve- Sub-Saharan Africa ments, men still dominate leadership and decisionmaking positions 15 in politics, business, and households. There are still 14 countries, South Asia including 5 high-income countries, that have no female representa- Europe & Central Asia East Asia & Pacific 10 tion in ministerial positions. Gender equality in decisionmaking not only benefi ts women and girls, but also matters for society more Middle East & North Africa broadly. Empowering women as economic, political, and social actors 5 can change policy choices and make institutions more representative of a range of voices. 0 2005 2008 2010 2012 Source: Inter Parliamentary Union. Economy States and markets Global links Back World Development Indicators 2014 29 2 People Prevalence Under-five Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female of child mortality mortality fertility of HIV completion literacy participation employment legislators, malnutrition, rate ratio rate rate rate rate Unpaid family senior underweight workers and officials, and Modeled births per Modeled own-account managers estimate 1,000 % of ILO estimate workers % of children per 1,000 per 100,000 women ages population % of relevant % ages % ages 15 % of total % of total under age 5 live births live births 15–19 ages 15–49 age group 15–24 and older employment labor force % of total 2005–12a 2012 2010 2012 2012 2008–12a 2005–12a 2012 2008–12a 2008–12a 2008–12a Afghanistan .. 99 460 87 <0.1 .. .. 48 .. .. .. Albania 6.3 17 27 15 .. .. 99 55 .. 14 .. Algeria 3.7 20 97 10 .. 100 92 44 30 10 .. American Samoa .. .. .. .. .. .. .. .. .. .. .. Andorra .. 3 .. .. .. .. .. .. .. .. .. Angola 15.6 164 450 170 2.3 54 73 70 .. .. .. Antigua and Barbuda .. 10 .. 49 .. 100 .. .. .. .. .. Argentina 2.3 14 77 54 0.4 109 99 61 19 7 .. Armenia 5.3 16 30 27 0.2 100 100 63 30 18 22 Aruba .. .. .. 27 .. 95 99 .. .. .. .. Australia 0.2 5 7 12 .. .. .. 65 9 5 37 Austria .. 4 4 4 .. 97 .. 61 9 4 27 Azerbaijan 8.4 35 43 40 0.2 92 100 66 55 5 7 Bahamas, The .. 17 47 28 3.3 93 .. 74 .. 14 52 Bahrain .. 10 20 14 .. .. 98 71 2 1 .. Bangladesh 36.8 41 240 81 <0.1 75 79 71 .. 5 .. Barbados .. 18 51 48 0.9 104 .. 71 .. 12 47 Belarus 1.3 5 4 21 0.4 103 100 56 2 6 .. Belgium .. 4 8 7 .. 91 .. 53 10 8 30 Belize 6.2 18 53 71 1.4 116 .. 66 .. 8 .. Benin 20.2 90 350 90 1.1 71 42 73 .. .. .. Bermuda .. .. .. .. .. 91 .. .. .. .. .. Bhutan 12.8 45 180 41 0.2 101 74 72 53 2 27 Bolivia 4.5 41 190 72 0.3 92 99 72 55 3 .. Bosnia and Herzegovina 1.5 7 8 15 .. .. 100 45 27 28 .. Botswana 11.2 53 160 44 23.0 95 95 77 .. .. .. Brazil 2.2 14 56 71 .. .. 98 70 25 7 .. Brunei Darussalam .. 8 24 23 .. 102 100 64 .. .. .. Bulgaria .. 12 11 36 .. 104 98 53 8 12 37 Burkina Faso 26.2 102 300 115 1.0 58 39 84 .. .. .. Burundi 29.1 104 800 30 1.3 62 89 83 .. .. .. Cabo Verde .. 22 79 71 0.2 99 98 67 .. .. .. Cambodia 29.0 40 250 44 0.8 98 87 83 64 0 21 Cameroon 15.1 95 690 116 4.5 73 81 70 76 4 .. Canada .. 5 12 14 .. .. .. 66 .. 7 36 Cayman Islands .. .. .. .. .. .. 99 .. .. 4 44 Central African Republic 28.0 129 890 98 .. 45 66 79 .. .. .. Chad .. 150 1,100 152 2.7 35 48 72 .. .. .. Channel Islands .. .. .. 8 .. .. .. .. .. .. .. Chile 0.5 9 25 55 0.4 97 99 62 24 6 .. China 3.4 14 37 9 .. .. 100 71 .. 4 .. Hong Kong SAR, China .. .. .. 3 .. 98 .. 59 7 3 32 Macao SAR, China .. .. .. 4 .. 98 100 71 4 3 31 Colombia 3.4 18 92 69 0.5 105 98 67 49 11 .. Comoros .. 78 280 51 2.1 80 86 58 .. .. .. Congo, Dem. Rep. 24.2 146 540 135 1.1 73 66 72 .. .. .. Congo, Rep. 11.8 96 560 127 2.8 73 .. 71 .. .. .. 30 World Development Indicators 2014 Front ? User guide World view People Environment People 2 Prevalence Under-five Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female of child mortality mortality fertility of HIV completion literacy participation employment legislators, malnutrition, rate ratio rate rate rate rate Unpaid family senior underweight workers and officials, and Modeled births per Modeled own-account managers estimate 1,000 % of ILO estimate workers % of children per 1,000 per 100,000 women ages population % of relevant % ages % ages 15 % of total % of total under age 5 live births live births 15–19 ages 15–49 age group 15–24 and older employment labor force % of total 2005–12a 2012 2010 2012 2012 2008–12a 2005–12a 2012 2008–12a 2008–12a 2008–12a Costa Rica 1.1 10 40 61 0.3 95 98 63 20 8 35 Côte d’Ivoire 29.4 108 400 130 3.2 61 68 67 .. .. .. Croatia .. 5 17 13 .. 94 100 51 17 16 25 Cuba .. 6 73 43 <0.1 96 100 57 .. 3 .. Curaçao .. .. .. 28 .. .. .. .. .. .. .. Cyprus .. 3 10 5 .. 102 100 64 13 12 14 Czech Republic .. 4 5 5 .. 102 .. 59 15 7 26 Denmark .. 4 12 5 .. 99 .. 63 6 8 28 Djibouti 29.8 81 200 19 1.2 52b .. 52 .. .. .. Dominica .. 13 .. .. .. 104 .. .. .. .. .. Dominican Republic 3.4 27 150 100 0.7 90 97 65 37 15 .. Ecuador .. 23 110 77 0.6 111 99 68 51 4 .. Egypt, Arab Rep. 6.8 21 66 43 <0.1 107 89 49 23 13 .. El Salvador 6.6 16 81 76 0.6 101 96 62 38 6 29 Equatorial Guinea .. 100 240 113 6.2 55 98 87 .. .. .. Eritrea .. 52 240 65 0.7 31 90 85 .. .. .. Estonia .. 4 2 17 .. 96 100 62 5 10 36 Ethiopia 29.2 68 350 78 1.3 .. 55 84 .. .. .. Faeroe Islands .. .. .. .. .. .. .. .. .. .. .. Fiji .. 22 26 43 0.2 103 .. 55 39 9 .. Finland .. 3 5 9 .. 97 .. 60 10 8 32 France .. 4 8 6 .. .. .. 56 7 10 39 French Polynesia .. .. .. 38 .. .. .. 56 .. .. .. Gabon 6.5 62 230 103 4.0 .. 98 61 .. .. .. Gambia, The 15.8 73 360 116 1.3 70 68 78 .. .. .. Georgia 1.1 20 67 47 0.3 108 100 65 61 15 .. Germany 1.1 4 7 4 .. 100 .. 60 7 5 30 Ghana 14.3 72 350 58 1.4 98b 86 69 77 4 .. Greece .. 5 3 12 .. 100 99 53 30 24 23 Greenland .. .. .. .. .. .. .. .. .. .. .. Grenada .. 14 24 35 .. 112 .. .. .. .. .. Guam .. .. .. 50 .. .. .. 63 .. 12 .. Guatemala 13.0 32 120 97 0.7 88 87 68 .. 3 .. Guinea 16.3 101 610 131 1.7 61 31 72 .. .. .. Guinea-Bissau 16.6 129 790 99 3.9 64 73 73 .. .. .. Guyana 11.1 35 280 88 1.3 85 93 61 .. .. .. Haiti 18.9 76 350 42 2.1 .. 72 66 .. .. .. Honduras 8.6 23 100 84 0.5 100 96 63 53 4 .. Hungary .. 6 21 12 .. 99 99 52 6 11 40 Iceland .. 2 5 11 .. 99 .. 74 8 6 40 India 43.5 56 200 33 0.3 96 81 56 81 4 14 Indonesia 18.6 31 220 48 0.4 100 99 68 57 7 22 Iran, Islamic Rep. .. 18 21 32 0.2 102 99 45 42 11 13 Iraq 7.1 34 63 69 .. .. 82 42 .. 15 .. Ireland .. 4 6 8 .. .. .. 60 12 15 33 Isle of Man .. .. .. .. .. .. .. .. .. .. .. Israel .. 4 7 8 .. 102 .. 64 7 7 32 Economy States and markets Global links Back World Development Indicators 2014 31 2 People Prevalence Under-five Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female of child mortality mortality fertility of HIV completion literacy participation employment legislators, malnutrition, rate ratio rate rate rate rate Unpaid family senior underweight workers and officials, and Modeled births per Modeled own-account managers estimate 1,000 % of ILO estimate workers % of children per 1,000 per 100,000 women ages population % of relevant % ages % ages 15 % of total % of total under age 5 live births live births 15–19 ages 15–49 age group 15–24 and older employment labor force % of total 2005–12a 2012 2010 2012 2012 2008–12a 2005–12a 2012 2008–12a 2008–12a 2008–12a Italy .. 4 4 4 .. 103 100 49 18 11 25 Jamaica 3.2 17 110 70 1.7 .. 96 63 38 14 .. Japan .. 3 5 5 .. 102 .. 59 11 4 .. Jordan 1.9 19 63 26 .. 93 99 41 10 12 .. Kazakhstan 3.7 19 51 30 .. 102b 100 72 29 5 38 Kenya 16.4 73 360 94 6.1 .. 82 67 .. .. .. Kiribati .. 60 .. 17 .. 115 .. .. .. .. .. Korea, Dem. People’s Rep. 18.8 29 81 1 .. .. 100 78 .. .. .. Korea, Rep. .. 4 16 2 .. 103 .. 61 25 3 10 Kosovo .. .. .. .. .. .. .. .. 17 31 .. Kuwait 2.2 11 14 14 .. .. 99 68 2 4 .. Kyrgyz Republic 2.7 27 71 29 0.3 98 100 67 .. 8 .. Lao PDR 31.6 72 470 65 0.3 95 84 78 .. .. .. Latvia .. 9 34 14 .. 99 100 60 8 15 45 Lebanon .. 9 25 12 .. 86 99 47 .. .. .. Lesotho 13.5 100 620 89 23.1 72 83 66 .. 25 .. Liberia 20.4 75 770 117 0.9 65 49 61 79 4 .. Libya 5.6 15 58 3 .. .. 100 53 .. .. .. Liechtenstein .. .. .. .. .. 101 .. .. .. .. .. Lithuania .. 5 8 11 .. 101 100 61 9 13 38 Luxembourg .. 2 20 8 .. 84 .. 58 6 5 24 Macedonia, FYR 2.1 7 10 18 .. 94 99 55 22 31 28 Madagascar .. 58 240 123 0.5 70 65 89 .. .. .. Malawi 13.8 71 460 145 10.8 74 72 83 .. .. .. Malaysia 12.9 9 29 6 0.4 .. 98 59 21 3 25 Maldives 17.8 11 60 4 <0.1 110 99 67 .. .. .. Mali 27.9 128 540 176 0.9 59 47 66 .. .. .. Malta .. 7 8 18 .. 92 98 52 9 6 23 Marshall Islands .. 38 .. .. .. 100 .. .. .. .. .. Mauritania 19.5 84 510 73 0.4 69 69 54 .. 31 .. Mauritius .. 15 60 31 1.2 99 97 59 17 9 23 Mexico 2.8 16 50 63 0.2 93 98 62 29 5 31 Micronesia, Fed. Sts. .. 39 100 19 .. .. .. .. .. .. .. Moldova 3.2 18 41 29 0.7 90 100 40 29 6 44 Monaco .. 4 .. .. .. .. .. .. .. .. .. Mongolia 5.3 28 63 19 <0.1 130 96 62 55 5 47 Montenegro 2.2 6 8 15 .. 101 99 50 .. 20 30 Morocco 3.1 31 100 36 0.1 99b 82 50 51 9 13 Mozambique 15.6 90 490 138 11.1 52 67 84 .. .. .. Myanmar 22.6 52 200 12 0.6 95 96 79 .. .. .. Namibia 17.5 39 200 55 13.3 85 87 59 33 17 37 Nepal 29.1 42 170 74 0.3 100 b 82 83 .. 3 .. Netherlands .. 4 6 6 .. .. .. 65 12 5 30 New Caledonia .. .. .. 21 .. .. 100 57 .. .. .. New Zealand .. 6 15 25 .. .. .. 68 12 7 40 Nicaragua 5.7 24 95 101 0.3 80 87 63 47 8 .. Niger 39.9 114 590 205 0.5 49 37 65 .. .. .. 32 World Development Indicators 2014 Front ? User guide World view People Environment People 2 Prevalence Under-five Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female of child mortality mortality fertility of HIV completion literacy participation employment legislators, malnutrition, rate ratio rate rate rate rate Unpaid family senior underweight workers and officials, and Modeled births per Modeled own-account managers estimate 1,000 % of ILO estimate workers % of children per 1,000 per 100,000 women ages population % of relevant % ages % ages 15 % of total % of total under age 5 live births live births 15–19 ages 15–49 age group 15–24 and older employment labor force % of total 2005–12a 2012 2010 2012 2012 2008–12a 2005–12a 2012 2008–12a 2008–12a 2008–12a Nigeria 24.4 124 630 120 3.1 76 66 56 .. .. .. Northern Mariana Islands .. .. .. .. .. .. .. .. .. .. .. Norway .. 3 7 8 .. 98 .. 66 5 3 31 Oman 8.6 12 32 11 .. 104 98 64 .. .. .. Pakistan 30.9 86 260 27 <0.1 72 71 54 63 5 3 Palau .. 21 .. .. .. .. .. .. .. .. .. Panama 3.9 19 92 79 0.7 98 98 66 29 4 46 Papua New Guinea 18.1 63 230 62 0.5 .. 71 72 .. .. .. Paraguay 3.4 22 99 67 0.3 86 99 70 43 5 34 Peru 4.5 18 67 51 0.4 91 97 76 46 4 19 Philippines 20.2 30 99 47 <0.1 91 98 65 40 7 55 Poland .. 5 5 12 .. 95 100 57 18 10 38 Portugal .. 4 8 13 .. .. 100 61 17 16 33 Puerto Rico .. .. 20 47 .. .. 87 42 .. 15 43 Qatar .. 7 7 10 .. .. 97 87 .. 1 4 Romania .. 12 27 31 .. 97 97 56 32 7 31 Russian Federation .. 10 34 26 .. 98 100 64 6 6 37 Rwanda 11.7 55 340 34 2.9 58 77 86 .. .. .. Samoa .. 18 100 28 .. 102 100 41 38 6 36 San Marino .. 3 .. .. .. 93 .. .. .. .. 18 São Tomé and Príncipe 14.4 53 70 65 1.0 104b 80 61 .. .. .. Saudi Arabia 5.3 9 24 10 .. 106 98 52 .. 6 5 Senegal 14.4 60 370 94 0.5 60 65 77 .. .. .. Serbia 1.6 7 12 17 .. 93 99 52 26 24 33 Seychelles .. 13 .. 56 .. 105 99 .. .. .. .. Sierra Leone 21.1 182 890 101 1.5 72 61 67 .. .. .. Singapore .. 3 3 6 .. .. 100 68 9 3 34 Sint Maarten .. .. .. .. .. .. .. .. .. .. .. Slovak Republic .. 8 6 16 .. 95 .. 60 12 14 31 Slovenia .. 3 12 1 .. 101 100 58 13 9 38 Solomon Islands 11.5 31 93 65 .. 85 .. 66 .. .. .. Somalia 32.8 147 1,000 110 0.5 .. .. 56 .. .. .. South Africa 8.7 45 300 51 17.9 .. 99 52 10 25 31 South Sudan 32.5 104 .. 75 2.7 .. .. .. .. .. .. Spain .. 5 6 11 .. 102 100 59 12 25 30 Sri Lanka 21.6 10 35 17 <0.1 97 98 55 41 4 24 St. Kitts and Nevis .. 9 .. .. .. 93 .. .. .. .. .. St. Lucia .. 18 35 56 .. 92 .. 69 .. 21 .. St. Martin .. .. .. .. .. .. .. .. .. .. .. St. Vincent & the Grenadines .. 23 48 55 .. 99 .. 67 8 19 .. Sudan 27.0 c 73c 730 84 c .. .. 87 54 .. 15 .. Suriname 5.8 21 130 35 1.1 88 98 55 .. .. .. Swaziland 5.8 80 320 72 26.5 77 94 57 .. .. .. Sweden .. 3 4 7 .. 102 .. 64 7 8 35 Switzerland .. 4 8 2 .. 96 .. 68 9 4 33 Syrian Arab Republic 10.1 15 70 42 .. 107 95 44 33 8 9 Tajikistan 15.0 58 65 43 0.3 98 100 68 47 12 .. Economy States and markets Global links Back World Development Indicators 2014 33 2 People Prevalence Under-five Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female of child mortality mortality fertility of HIV completion literacy participation employment legislators, malnutrition, rate ratio rate rate rate rate Unpaid family senior underweight workers and officials, and Modeled births per Modeled own-account managers estimate 1,000 % of ILO estimate workers % of children per 1,000 per 100,000 women ages population % of relevant % ages % ages 15 % of total % of total under age 5 live births live births 15–19 ages 15–49 age group 15–24 and older employment labor force % of total 2005–12a 2012 2010 2012 2012 2008–12a 2005–12a 2012 2008–12a 2008–12a 2008–12a Tanzania 16.2 54 460 123 5.1 81 75 89 .. 4 .. Thailand 7.0 13 48 41 1.1 .. 98 72 54 1 25 Timor-Leste 45.3 57 300 52 .. 71 80 38 70 4 10 Togo 16.5 96 300 92 2.9 74 80 81 .. .. .. Tonga .. 13 110 18 .. 100 99 64 .. .. .. Trinidad and Tobago .. 21 46 35 1.6 95 100 64 .. 5 .. Tunisia 3.3 16 56 5 <0.1 102 97 48 29 18 .. Turkey .. 14 20 31 .. 103 99 49 32 9 10 Turkmenistan .. 53 67 18 .. .. 100 61 .. .. .. Turks and Caicos Islands .. .. .. .. .. .. .. .. .. .. .. Tuvalu 1.6 30 .. .. .. .. .. .. .. .. .. Uganda 14.1 69 310 127 7.2 53 87 78 .. 4 .. Ukraine .. 11 32 26 0.9 103 100 59 18 8 39 United Arab Emirates .. 8 12 28 .. 111 95 79 1 4 10 United Kingdom .. 5 12 26 .. .. .. 62 12 8 34 United States .. 7 21 31 .. 98 .. 63 .. 8 43 Uruguay 4.5 7 29 58 0.7 104 99 66 22 7 .. Uzbekistan 4.4 40 28 39 0.1 92 100 61 .. .. .. Vanuatu 11.7 18 110 45 .. 84 95 71 70 5 29 Venezuela, RB 2.9 15 92 83 0.6 96 99 65 32 8 .. Vietnam 12.0 23 59 29 0.4 101 97 77 63 2 .. Virgin Islands (U.S.) .. .. .. 51 .. .. .. 63 .. .. .. West Bank and Gaza 2.2 23 .. 46 .. 90 99 41 27 23 10 Yemen, Rep. .. 60 200 47 0.1 70 86 49 30 18 5 Zambia 14.9 89 440 125 12.7 91 64 79 .. .. .. Zimbabwe 10.1 90 570 60 14.7 .. 91 86 .. .. .. World 15.1 w 48 w 210 w 45 w 0.8 w 91 w 89 w 64 w .. w 6w Low income 21.8 82 410 93 2.3 67 73 76 .. .. Middle income 15.7 45 190 40 .. 94 91 63 .. 5 Lower middle income 24.1 61 260 47 0.6 91 84 58 65 5 Upper middle income 2.8 20 64 31 .. .. 98 67 .. 5 Low & middle income 17.0 53 240 49 1.2 89 88 64 .. 5 East Asia & Pacific 5.3 21 83 20 .. .. 99 71 .. 4 Europe & Central Asia 1.8 22 32 31 .. 99 99 57 27 9 Latin America & Carib. 2.9 19 82 69 .. 102 97 67 32 7 Middle East & N. Africa 6.2 26 81 37 .. 91 92 46 34 11 South Asia 32.2 60 220 39 0.3 88 80 57 78 4 Sub-Saharan Africa 20.8 98 500 108 4.7 69 70 70 .. .. High income 1.4 6 16 18 .. 100 .. 61 11 8 Euro area .. 4 6 6 .. 99 100 57 11 11 a. Data are for the most recent year available. b. Data are for 2013. c. Excludes South Sudan. 34 World Development Indicators 2014 Front ? User guide World view People Environment People 2 About the data Though not included in the table due to space limitations, many and research institutes, has developed and adopted a statistical indicators in this section are available disaggregated by sex, place method that uses all available information to reconcile differences. of residence, wealth, and age in the World Development Indicators Trend lines are obtained by fi tting a country-specifi c regression database. model of mortality rates against their reference dates. (For further discussion of childhood mortality estimates, see UN Inter-agency Child malnutrition Group for Child Mortality Estimation [2013]; for detailed background Good nutrition is the cornerstone for survival, health, and devel- data and for a graphic presentation, see www.childmortality.org). opment. Well-nourished children perform better in school, grow into healthy adults, and in turn give their children a better start Maternal mortality in life. Well-nourished women face fewer risks during pregnancy Measurements of maternal mortality are subject to many types and childbirth, and their children set off on firmer developmental of errors. In countries with incomplete vital registration systems, paths, both physically and mentally. Undernourished children have deaths of women of reproductive age or their pregnancy status may lower resistance to infection and are more likely to die from com- not be reported, or the cause of death may not be known. Even in mon childhood ailments such as diarrheal diseases and respiratory high-income countries with reliable vital registration systems, mis- infections. Frequent illness saps the nutritional status of those who classification of maternal deaths has been found to lead to serious survive, locking them into a vicious cycle of recurring sickness and underestimation. Surveys and censuses can be used to measure faltering growth. maternal mortality by asking respondents about survivorship of sis- The proportion of underweight children is the most common child ters. But these estimates are retrospective, referring to a period malnutrition indicator. Being even mildly underweight increases the approximately five years before the survey, and may be affected by risk of death and inhibits cognitive development in children. And recall error. Further, they reflect pregnancy-related deaths (deaths it perpetuates the problem across generations, as malnourished while pregnant or within 42 days of pregnancy termination, irrespec- women are more likely to have low-birthweight babies. Estimates tive of the cause of death) and need to be adjusted to conform to of prevalence of underweight children are from the World Health the strict definition of maternal death. Organization’s (WHO) Global Database on Child Growth and Malnu- Maternal mortality ratios in the table are modeled estimates trition, a standardized compilation of child growth and malnutrition based on work by WHO, UNICEF, United Nations Population Fund data from national nutritional surveys. To better monitor global child (UNFPA), and the World Bank and include country-level time series malnutrition, the United Nations Children’s Fund (UNICEF), WHO, data. For countries without complete registration data but with other and the World Bank have jointly produced estimates for 2012 and types of data and for countries with no data, maternal mortality trends since 1990 for regions, income groups, and the world, using is estimated with a multilevel regression model using available a harmonized database and aggregation method. national maternal mortality data and socioeconomic information, including fertility, birth attendants, and gross domestic product. Under-five mortality The methodology differs from that used for previous estimates, so Mortality rates for children and others are important indicators data presented here should not be compared across editions (WHO of health status. When data on the incidence and prevalence of and others 2012). diseases are unavailable, mortality rates may be used to identify vulnerable populations. And they are among the indicators most Adolescent fertility frequently used to compare socioeconomic development across Reproductive health is a state of physical and mental well-being countries. in relation to the reproductive system and its functions and pro- The main sources of mortality data are vital registration systems cesses. Means of achieving reproductive health include education and direct or indirect estimates based on sample surveys or cen- and services during pregnancy and childbirth, safe and effective suses. A complete vital registration system—covering at least contraception, and prevention and treatment of sexually transmitted 90 percent of vital events in the population—is the best source of diseases. Complications of pregnancy and childbirth are the leading age-specific mortality data. But complete vital registration systems cause of death and disability among women of reproductive age in are fairly uncommon in developing countries. Thus estimates must developing countries. be obtained from sample surveys or derived by applying indirect Adolescent pregnancies are high risk for both mother and child. estimation techniques to registration, census, or survey data (see They are more likely to result in premature delivery, low birthweight, Primary data documentation). Survey data are subject to recall error. delivery complications, and death. Many adolescent pregnancies are To make estimates comparable and to ensure consistency across unintended, but young girls may continue their pregnancies, giving estimates by different agencies, the UN Inter-agency Group for Child up opportunities for education and employment, or seek unsafe Mortality Estimation, which comprises UNICEF, WHO, the United abortions. Estimates of adolescent fertility rates are based on Nations Population Division, the World Bank, and other universities vital registration systems or, in their absence, censuses or sample Economy States and markets Global links Back World Development Indicators 2014 35 2 People surveys and are generally considered reliable measures of fertility primary completion rate may exceed 100 percent. The numerator in the recent past. Where no empirical information on age-specific may include late entrants and overage children who have repeated fertility rates is available, a model is used to estimate the share one or more grades of primary education as well as children who of births to adolescents. For countries without vital registration entered school early, while the denominator is the number of chil- systems fertility rates are generally based on extrapolations from dren at the entrance age for the last grade of primary education. trends observed in censuses or surveys from earlier years. Youth literacy Prevalence of HIV The youth literacy rate for ages 15–24 is a standard measure of HIV prevalence rates reflect the rate of HIV infection in each coun- recent progress in student achievement. It reflects the accumulated try’s population. Low national prevalence rates can be misleading, outcomes of primary education by indicating the proportion of the however. They often disguise epidemics that are initially concen- population that has acquired basic literacy and numeracy skills over trated in certain localities or population groups and threaten to spill the previous 10 years or so. In practice, however, literacy is difficult over into the wider population. In many developing countries most to measure. Estimating literacy rates requires census or survey mea- new infections occur in young adults, with young women especially surements under controlled conditions. Many countries estimate vulnerable. the number of literate people from self-reported data. Some use Data on HIV prevalence are from the Joint United Nations Pro- educational attainment data as a proxy but apply different lengths gramme on HIV/AIDS. Changes in procedures and assumptions for of school attendance or levels of completion. Because definitions estimating the data and better coordination with countries have and methods of data collection differ across countries, data should resulted in improved estimates. The models, which are routinely be used cautiously. Generally, literacy encompasses numeracy, the updated, track the course of HIV epidemics and their impacts, mak- ability to make simple arithmetic calculations. ing full use of information on HIV prevalence trends from surveil- Data on youth literacy are compiled by the United Nations Educa- lance data as well as survey data. The models take into account tional, Scientific and Cultural Organization (UNESCO) Institute for reduced infectivity among people receiving antiretroviral therapy Statistics based on national censuses and household surveys dur- (which is having a larger impact on HIV prevalence and allowing HIV- ing 1985–2012 and, for countries without recent literacy data, using positive people to live longer) and allow for changes in urbanization the Global Age-Specific Literacy Projection Model. over time in generalized epidemics (important because prevalence is higher in urban areas and because many countries have seen rapid Labor force participation urbanization over the past two decades). The estimates include The labor force is the supply of labor available for producing goods plausibility bounds, available at http://data.worldbank.org, which and services in an economy. It includes people who are currently reflect the certainty associated with each of the estimates. employed, people who are unemployed but seeking work, and first- time job-seekers. Not everyone who works is included, however. Primary completion Unpaid workers, family workers, and students are often omitted, Many governments publish statistics that indicate how their educa- and some countries do not count members of the armed forces. tion systems are working and developing—statistics on enrollment Labor force size tends to vary during the year as seasonal workers and efficiency indicators such as repetition rates, pupil–teacher enter and leave. ratios, and cohort progression. The primary completion rate, also Data on the labor force are compiled by the International Labour called the gross intake ratio to last grade of primary education, is Organization (ILO) from labor force surveys, censuses, and estab- a core indicator of an education system’s performance. It reflects lishment censuses and surveys and from administrative records an education system’s coverage and the educational attainment such as employment exchange registers and unemployment insur- of students. It is a key measure of progress toward the Millennium ance schemes. Labor force surveys are the most comprehensive Development Goals and the Education for All initiative. However, a source for internationally comparable labor force data. Labor force high primary completion rate does not necessarily mean high levels data from population censuses are often based on a limited number of student learning. of questions on the economic characteristics of individuals, with The indicator reflects the primary cycle as defined by the Interna- little scope to probe. Establishment censuses and surveys provide tional Standard Classification of Education (ISCED97), ranging from data on the employed population only, not unemployed workers, three or four years of primary education (in a very small number of workers in small establishments, or workers in the informal sector countries) to fi ve or six years (in most countries) and seven (in a (ILO, Key Indicators of the Labour Market 2001–2002). small number of countries). It is a proxy that should be taken as an Besides the data sources, there are other important factors that upper estimate of the actual primary completion rate, since data affect data comparability, such as census or survey reference period, limitations preclude adjusting for students who drop out during the definition of working age, and geographic coverage. For country-level final year of primary education. There are many reasons why the information on source, reference period, or definition, consult the 36 World Development Indicators 2014 Front ? User guide World view People Environment People 2 footnotes in the World Development Indicators database or the ILO’s suitable or desirable jobs. But high and sustained unemployment Key Indicators of the Labour Market, 8th edition, database. indicates serious inefficiencies in resource allocation. The labor force participation rates in the table are modeled esti- The criteria for people considered to be seeking work, and the mates from the ILO’s Key Indicators of the Labour Market, 8th edition, treatment of people temporarily laid off or seeking work for the database. These harmonized estimates use strict data selection crite- first time, vary across countries. In many developing countries it ria and enhanced methods to ensure comparability across countries is especially difficult to measure employment and unemployment and over time to avoid the inconsistencies mentioned above. Esti- in agriculture. The timing of a survey can maximize the effects of mates are based mainly on labor force surveys, with other sources seasonal unemployment in agriculture. And informal sector employ- (population censuses and nationally reported estimates) used only ment is difficult to quantify where informal activities are not tracked. when no survey data are available. National estimates of labor force Data on unemployment are drawn from labor force sample surveys participation rates are available in the World Development Indicators and general household sample surveys, censuses, and official esti- online database. Because other employment data are mostly national mates. Administrative records, such as social insurance statistics estimates, caution should be used when comparing the modeled and employment office statistics, are not included because of their labor force participation rate and other employment data. limitations in coverage. Women tend to be excluded from the unemployment count for vari- Vulnerable employment ous reasons. Women suffer more from discrimination and from struc- The proportion of unpaid family workers and own-account workers in tural, social, and cultural barriers that impede them from seeking work. total employment is derived from information on status in employ- Also, women are often responsible for the care of children and the ment. Each group faces different economic risks, and unpaid fam- elderly and for household affairs. They may not be available for work ily workers and own-account workers are the most vulnerable—and during the short reference period, as they need to make arrangements therefore the most likely to fall into poverty. They are the least likely before starting work. Further, women are considered to be employed to have formal work arrangements, are the least likely to have social when they are working part-time or in temporary jobs, despite the insta- protection and safety nets to guard against economic shocks, and are bility of these jobs or their active search for more secure employment. often incapable of generating enough savings to offset these shocks. A high proportion of unpaid family workers in a country indicates Female legislators, senior officials, and managers weak development, little job growth, and often a large rural economy. Despite much progress in recent decades, gender inequalities remain Data on vulnerable employment are drawn from labor force and pervasive in many dimensions of life. But while gender inequalities general household sample surveys, censuses, and official estimates. exist throughout the world, they are most prevalent in developing Besides the limitation mentioned for calculating labor force participa- countries. Inequalities in the allocation of education, health care, tion rates, there are other reasons to limit comparability. For exam- nutrition, and political voice matter because of their strong associa- ple, information provided by the Organisation for Economic Co-oper- tion with well-being, productivity, and economic growth. These pat- ation and Development relates only to civilian employment, which terns of inequality begin at an early age, with boys usually receiving a can result in an underestimation of “employees” and “workers not larger share of education and health spending than girls, for example. classified by status,” especially in countries with large armed forces. The share of women in high-skilled occupations such as legislators, While the categories of unpaid family workers and own-account work- senior officials, and managers indicates women’s status and role ers would not be affected, their relative shares would be. in the labor force and society at large. Women are vastly under- represented in decisionmaking positions in government, although Unemployment there is some evidence of recent improvement. The ILO defines the unemployed as members of the economically Data on female legislators, senior officials, and managers are active population who are without work but available for and seek- based on the employment by occupation estimates, classifi ed ing work, including people who have lost their jobs or who have according to the International Standard Classification of Occupa- voluntarily left work. Some unemployment is unavoidable. At any tions 1988. Data are drawn mostly from labor force surveys, supple- time some workers are temporarily unemployed—between jobs as mented in limited cases with other household surveys, population employers look for the right workers and workers search for better censuses, and official estimates. Countries could apply different jobs. Such unemployment, often called frictional unemployment, practice whether or where the armed forces are included. Armed results from the normal operation of labor markets. forces constitute a separate major group, but in some countries they Changes in unemployment over time may reflect changes in the are included in the most closely matching civilian occupation or in demand for and supply of labor, but they may also reflect changes nonclassifiable workers. For country-level information on classifica- in reporting practices. In countries without unemployment or welfare tion, source, reference period, or definition, consult the footnotes in benefits people eke out a living in vulnerable employment. In coun- the World Development Indicators database or the ILO’s Key Indica- tries with well-developed safety nets workers can afford to wait for tors of the Labour Market, 8th edition, database. Economy States and markets Global links Back World Development Indicators 2014 37 2 People Definitions Data sources • Prevalence of child malnutrition, underweight, is the percent- Data on child malnutrition prevalence are from WHO’s Global Data- age of children under age 5 whose weight for age is more than two base on Child Growth and Malnutrition (www.who.int/nutgrowthdb). standard deviations below the median for the international reference Data on under-fi ve mortality rates are from the UN Inter- agency population ages 0–59 months. Data are based on the WHO child Group for Child Mortality Estimation (www.childmortality.org) and growth standards released in 2006. • Under-five mortality rate is are based mainly on household surveys, censuses, and vital reg- the probability of a child born in a specific year dying before reaching istration data. Modeled estimates of maternal mortality ratios are age 5, if subject to the age-specific mortality rates of that year. The from the UN Maternal Mortality Estimation Inter- agency Group (www probability is expressed as a rate per 1,000 live births. • Maternal .maternalmortalitydata.org). Data on adolescent fertility rates are mortality ratio, modeled estimate, is the number of women who from United Nations Population Division (2013), with annual data die from pregnancy-related causes while pregnant or within 42 days linearly interpolated by the World Bank’s Development Data Group. of pregnancy termination, per 100,000 live births. • Adolescent Data on HIV prevalence are from UNAIDS (2013). Data on primary fertility rate is the number of births per 1,000 women ages 15–19. completion rates and literacy rates are from the UNESCO Institute • Prevalence of HIV is the percentage of people who are infected for Statistics (www.uis.unesco.org). Data on labor force participation with HIV in the relevant age group. • Primary completion rate is rates, vulnerable employment, unemployment, and female legisla- the number of new entrants (enrollments minus repeaters) in the tors, senior officials, and managers are from the ILO’s Key Indicators last grade of primary education, regardless of age, divided by the of the Labour Market, 8th edition, database. population at the entrance age for the last grade of primary educa- tion. Data limitations preclude adjusting for students who drop out References during the final year of primary education. • Youth literacy rate is ILO (International Labour Organization).Various years. Key Indicators of the percentage of the population ages 15–24 that can, with under- the Labour Market. Geneva: International Labour Office. standing, both read and write a short simple statement about their UNAIDS (Joint United Nations Programme on HIV/AIDS). 2013. Global everyday life. • Labor force participation rate is the proportion of Report: UNAIDS Report on the Global AIDS Epidemic 2013. Geneva. the population ages 15 and older that engages actively in the labor UNICEF (United Nations Children’s Fund), WHO (World Health Orga- market, by either working or looking for work during a reference nization), and the World Bank. 2013. 2012 Joint Child Malnutrition period. Data are modeled ILO estimates. • Vulnerable employment Estimates - Levels and Trends. New York: UNICEF. [www.who.int is unpaid family workers and own-account workers as a percentage /nutgrowthdb/estimates2012/en/]. of total employment. • Unemployment is the share of the labor force UN Inter-agency Group for Child Mortality Estimation. 2013. Levels and without work but available for and seeking employment. Definitions Trends in Child Mortality: Report 2013. New York. of labor force and unemployment may differ by country. • Female United Nations Population Division. 2013. World Population Prospects: legislators, senior officials, and managers are the percentage of The 2012 Revision. New York: United Nations, Department of Eco- legislators, senior officials, and managers (International Standard nomic and Social Affairs. Classification of Occupations–88 category 1) who are female. WHO (World Health Organization), UNICEF (United Nations Children’s Fund), UNFPA (United Nations Population Fund), and World Bank. 2012. Trends in Maternal Mortality: 1990 to 2010. Geneva: WHO. World Bank. 2011. World Development Report 2012: Gender Equality and Development. Washington, DC. ———. n.d. PovcalNet online database. [http://iresearch.worldbank .org/PovcalNet]. Washington, DC. 38 World Development Indicators 2014 Front ? User guide World view People Environment People 2 Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/2.1). To view a specific /indicator/SP.POP.TOTL). 2.1 Population dynamics Unemployment by educational attainment, Population SP.POP.TOTL Secondary SL.UEM.SECO.ZS Population growth SP.POP.GROW Unemployment by educational attainment, Population ages 0–14 SP.POP.0014.TO.ZS Tertiary SL.UEM.TERT.ZS Population ages 15–64 SP.POP.1564.TO.ZS 2.6 Children at work Population ages 65+ SP.POP.65UP.TO.ZS Children in employment, Total SL.TLF.0714.ZS Dependency ratio, Young SP.POP.DPND.YG Children in employment, Male SL.TLF.0714.MA.ZS Dependency ratio, Old SP.POP.DPND.OL Children in employment, Female SL.TLF.0714.FE.ZS Crude death rate SP.DYN.CDRT.IN Work only SL.TLF.0714.WK.ZS Crude birth rate SP.DYN.CBRT.IN Study and work SL.TLF.0714.SW.ZS 2.2 Labor force structure Employment in agriculture SL.AGR.0714.ZS Labor force participation rate, Male SL.TLF.CACT.MA.ZS Employment in manufacturing SL.MNF.0714.ZS Labor force participation rate, Female SL.TLF.CACT.FE.ZS Employment in services SL.SRV.0714.ZS Labor force, Total SL.TLF.TOTL.IN Self-employed SL.SLF.0714.ZS Labor force, Average annual growth ..a,b Wage workers SL.WAG.0714.ZS Labor force, Female SL.TLF.TOTL.FE.ZS Unpaid family workers SL.FAM.0714.ZS 2.3 Employment by sector 2.7 Poverty rates at national poverty lines Agriculture, Male SL.AGR.EMPL.MA.ZS Poverty headcount ratio, Rural SI.POV.RUHC Agriculture, Female SL.AGR.EMPL.FE.ZS Poverty headcount ratio, Urban SI.POV.URHC Industry, Male SL.IND.EMPL.MA.ZS Poverty headcount ratio, National SI.POV.NAHC Industry, Female SL.IND.EMPL.FE.ZS Poverty gap, Rural SI.POV.RUGP Services, Male SL.SRV.EMPL.MA.ZS Poverty gap, Urban SI.POV.URGP Poverty gap, National SI.POV.NAGP Services, Female SL.SRV.EMPL.FE.ZS 2.8 Poverty rates at international poverty lines 2.4 Decent work and productive employment Population living below 2005 PPP $1.25 Employment to population ratio, Total SL.EMP.TOTL.SP.ZS a day SI.POV.DDAY Employment to population ratio, Youth SL.EMP.1524.SP.ZS Poverty gap at 2005 PPP $1.25 a day SI.POV.2DAY Vulnerable employment, Male SL.EMP.VULN.MA.ZS Population living below 2005 PPP $2 a day SI.POV.GAPS Vulnerable employment, Female SL.EMP.VULN.FE.ZS Poverty gap at 2005 PPP $2 a day SI.POV.GAP2 GDP per person employed SL.GDP.PCAP.EM.KD 2.9 Distribution of income or consumption 2.5 Unemployment Gini index SI.POV.GINI Unemployment, Male SL.UEM.TOTL.MA.ZS Share of consumption or income, Lowest Unemployment, Female SL.UEM.TOTL.FE.ZS 10% of population SI.DST.FRST.10 Youth unemployment, Male SL.UEM.1524.MA.ZS Share of consumption or income, Lowest 20% of population SI.DST.FRST.20 Youth unemployment, Female SL.UEM.1524.FE.ZS Share of consumption or income, Second Long-term unemployment, Total SL.UEM.LTRM.ZS 20% of population SI.DST.02ND.20 Long-term unemployment, Male SL.UEM.LTRM.MA.ZS Share of consumption or income, Third 20% Long-term unemployment, Female SL.UEM.LTRM.FE.ZS of population SI.DST.03RD.20 Unemployment by educational attainment, Share of consumption or income, Fourth Primary SL.UEM.PRIM.ZS 20% of population SI.DST.04TH.20 Economy States and markets Global links Back World Development Indicators 2014 39 2 People Share of consumption or income, Highest Primary completion rate, Female SE.PRM.CMPT.FE.ZS 20% of population SI.DST.05TH.20 Youth literacy rate, Male SE.ADT.1524.LT.MA.ZS Share of consumption or income, Highest Youth literacy rate, Female SE.ADT.1524.LT.FE.ZS 10% of population SI.DST.10TH.10 Adult literacy rate, Male SE.ADT.LITR.MA.ZS 2.10 Education inputs Adult literacy rate, Female SE.ADT.LITR.FE.ZS Public expenditure per student, Primary SE.XPD.PRIM.PC.ZS Public expenditure per student, Secondary SE.XPD.SECO.PC.ZS 2.14 Education gaps by income and gender Public expenditure per student, Tertiary SE.XPD.TERT.PC.ZS This table provides education survey data for the poorest and richest quintiles. ..b Public expenditure on education, % of GDP SE.XPD.TOTL.GD.ZS Public expenditure on education, % of total 2.15 Health systems government expenditure SE.XPD.TOTL.GB.ZS Total health expenditure SH.XPD.TOTL.ZS Trained teachers in primary education SE.PRM.TCAQ.ZS Public health expenditure SH.XPD.PUBL Primary school pupil-teacher ratio SE.PRM.ENRL.TC.ZS Out-of-pocket health expenditure SH.XPD.OOPC.TO.ZS External resources for health SH.XPD.EXTR.ZS 2.11 Participation in education Health expenditure per capita, $ SH.XPD.PCAP Gross enrollment ratio, Preprimary SE.PRE.ENRR Health expenditure per capita, PPP $ SH.XPD.PCAP.PP.KD Gross enrollment ratio, Primary SE.PRM.ENRR Physicians SH.MED.PHYS.ZS Gross enrollment ratio, Secondary SE.SEC.ENRR Nurses and midwives SH.MED.NUMW.P3 Gross enrollment ratio, Tertiary SE.TER.ENRR Community health workers SH.MED.CMHW.P3 Net enrollment rate, Primary SE.PRM.NENR Hospital beds SH.MED.BEDS.ZS Net enrollment rate, Secondary SE.SEC.NENR Completeness of birth registration SP.REG.BRTH.ZS Adjusted net enrollment rate, Primary, Male SE.PRM.TENR.MA Adjusted net enrollment rate, Primary, Female SE.PRM.TENR.FE 2.16 Disease prevention coverage and quality Primary school-age children out of school, Access to an improved water source SH.H2O.SAFE.ZS Male SE.PRM.UNER.MA Access to improved sanitation facilities SH.STA.ACSN Primary school-age children out of school, Child immunization rate, Measles SH.IMM.MEAS Female SE.PRM.UNER.FE Child immunization rate, DTP3 SH.IMM.IDPT Children with acute respiratory infection 2.12 Education efficiency taken to health provider SH.STA.ARIC.ZS Gross intake ratio in first grade of primary Children with diarrhea who received oral education, Male SE.PRM.GINT.MA.ZS rehydration and continuous feeding SH.STA.ORCF.ZS Gross intake ratio in first grade of primary Children sleeping under treated bed nets SH.MLR.NETS.ZS education, Female SE.PRM.GINT.FE.ZS Children with fever receiving antimalarial Cohort survival rate, Reaching grade 5, drugs SH.MLR.TRET.ZS Male SE.PRM.PRS5.MA.ZS Tuberculosis treatment success rate SH.TBS.CURE.ZS Cohort survival rate, Reaching grade 5, Female SE.PRM.PRS5.FE.ZS Tuberculosis case detection rate SH.TBS.DTEC.ZS Cohort survival rate, Reaching last grade of primary education, Male SE.PRM.PRSL.MA.ZS 2.17 Reproductive health Cohort survival rate, Reaching last grade of Total fertility rate SP.DYN.TFRT.IN primary education, Female SE.PRM.PRSL.FE.ZS Adolescent fertility rate SP.ADO.TFRT Repeaters in primary education, Male SE.PRM.REPT.MA.ZS Unmet need for contraception SP.UWT.TFRT Repeaters in primary education, Female SE.PRM.REPT.FE.ZS Contraceptive prevalence rate SP.DYN.CONU.ZS Transition rate to secondary education, Male SE.SEC.PROG.MA.ZS Pregnant women receiving prenatal care SH.STA.ANVC.ZS Transition rate to secondary education, Births attended by skilled health staff SH.STA.BRTC.ZS Female SE.SEC.PROG.FE.ZS Maternal mortality ratio, National estimate SH.STA.MMRT.NE Maternal mortality ratio, Modeled estimate SH.STA.MMRT 2.13 Education completion and outcomes Lifetime risk of maternal mortality SH.MMR.RISK Primary completion rate, Total SE.PRM.CMPT.ZS Primary completion rate, Male SE.PRM.CMPT.MA.ZS 40 World Development Indicators 2014 Front ? User guide World view People Environment People 2 2.18 Nutrition and growth Prevalence of HIV, Total SH.DYN.AIDS.ZS Prevalence of undernourishment SN.ITK.DEFC.ZS Women’s share of population ages 15+ Prevalence of underweight, Male SH.STA.MALN.MA.ZS living with HIV SH.DYN.AIDS.FE.ZS Prevalence of underweight, Female SH.STA.MALN.FE.ZS Prevalence of HIV, Youth male SH.HIV.1524.MA.ZS Prevalence of stunting, Male SH.STA.STNT.MA.ZS Prevalence of HIV, Youth female SH.HIV.1524.FE.ZS Prevalence of stunting, Female SH.STA.STNT.FE.ZS Antiretroviral therapy coverage SH.HIV.ARTC.ZS Prevalence of wasting, Male SH.STA.WAST.MA.ZS Death from communicable diseases and maternal, prenatal, and nutrition conditions SH.DTH.COMM.ZS Prevalence of wasting, Female SH.STA.WAST.FE.ZS Death from non-communicable diseases SH.DTH.NCOM.ZS Prevalence of severe wasting, Male SH.SVR.WAST.MA.ZS Death from injuries SH.DTH.INJR.ZS Prevalence of severe wasting, Female SH.SVR.WAST.FE.ZS Prevalence of overweight children, Male SH.STA.OWGH.MA.ZS 2.21 Mortality Prevalence of overweight children, Female SH.STA.OWGH.FE.ZS Life expectancy at birth SP.DYN.LE00.IN Neonatal mortality rate SH.DYN.NMRT 2.19 Nutrition intake and supplements Infant mortality rate SP.DYN.IMRT.IN Low-birthweight babies SH.STA.BRTW.ZS Under-five mortality rate, Total SH.DYN.MORT Exclusive breastfeeding SH.STA.BFED.ZS Under-five mortality rate, Male SH.DYN.MORT.MA Consumption of iodized salt SN.ITK.SALT.ZS Under-five mortality rate, Female SH.DYN.MORT.FE Vitamin A supplementation SN.ITK.VITA.ZS Prevalence of anemia among children Adult mortality rate, Male SP.DYN.AMRT.MA under age 5 SH.ANM.CHLD.ZS Adult mortality rate, Female SP.DYN.AMRT.FE Prevalence of anemia among pregnant women SH.PRG.ANEM 2.22 Health gaps by income This table provides health survey data for 2.20 Health risk factors and future challenges the poorest and richest quintiles. ..b Prevalence of smoking, Male SH.PRV.SMOK.MA Prevalence of smoking, Female SH.PRV.SMOK.FE Data disaggregated by sex are available in the World Development Indicators database. Incidence of tuberculosis SH.TBS.INCD a. Derived from data elsewhere in the World Development Indicators database. Prevalence of diabetes SH.STA.DIAB.ZS b. Available online only as part of the table, not as an individual indicator. Economy States and markets Global links Back World Development Indicators 2014 41 ENVIRONMENT 42 World Development Indicators 2014 Front ? User guide World view People Environment 3 A healthy environment is integral to meeting governments, businesses, and civil societies to the Millennium Development Goals, which call achieve three goals by 2030. First is universal for reversing environmental losses and insert- access to electricity and clean cooking fuels. ing principles of environmental sustainability Second is doubling the share of the world’s into country policies and programs. Whether the energy supply from renewable sources. And third world sustains itself depends largely on properly is doubling the rate of improvement in energy managing natural resources. The indicators in efficiency. Several indicators in the Environment the Environment section measure resource use section cover energy use and efficiency, electric- and the way human activities affect the natural ity use and production, greenhouse gas emis- and built environment. They include measures sions, carbon dioxide emissions by economic of environmental goods (forest, water, cultivable sector, and access to electricity. land) and of degradation (pollution, deforesta- Other indicators describe land use, agri- tion, loss of habitat, and loss of biodiversity). culture and food production, forests and bio- They show that growing populations and expand- diversity, threatened species, water resources, ing economies have placed greater demands climate variability, exposure to impact, resil- on land, water, forest, minerals, and energy ience, urbanization, traffic and congestion, air sources. But better policies, rising productivity, pollution, and natural resources rents. Where and new technologies can ensure that future possible, the indicators come from international development is environmentally and socially sources and have been standardized to facili- sustainable. tate comparisons across countries. But ecosys- Economic growth and greater energy use tems span national boundaries, and access to are positively correlated—access to electricity natural resources may vary within countries. For and the use of energy are essential in raising example, water may be abundant in some parts people’s standard of living. Economic develop- of a country but scarce in others, and countries ment has improved the quality of life for many often share water resources. Land productivity people, yielding gains unparalleled in human and optimal land use may be location-specific, history. But the gains have been uneven, and but widely separated regions can have common economic growth has often had negative environ- characteristics. Greenhouse gas emissions and mental consequences, with a drastic impact on climate change are measured globally, but their poor people. Generating energy from fossil fuels effects are experienced locally, shaping people’s produces emissions of carbon dioxide, the main lives and livelihoods. Measuring environmental greenhouse gas contributing to climate change. phenomena and their effects at the subnational, The World Bank Group has joined the UN national, and supranational levels thus remains Sustainable Energy for All, which calls on a major challenge. Economy States and markets Global links Back World Development Indicators 2014 43 Highlights Agricultural land use increases while industry’s share of GDP declines Land under cereal production (million hectares) The share of agriculture in GDP is declining in all regions and income groups. Between 2000 and 2012 it fell 20 percentage points globally. 200 Even in low-income countries the share fell 6 percentage points, from 34 percent to 28 percent, as most economies gradually shifted to 150 industry and services. Over the last decade, apart from developing countries in Europe and Central Asia, low- and middle-income countries 100 in general are increasing land under cereal production. Both East Asia and Pacific and Sub- Saharan Africa saw land under cereal production increase more than 15 percent. Since most of the land available for 50 current and future food requirements is already in production, further 2000 2012 expansion will likely involve fragile and marginal land—a strategy that 0 cannot be sustained for long. Middle East Latin Europe Sub-Saharan South East Asia High & North America & & Central Africa Asia & Pacific income Africa Caribbean Asia Source: Online table 3.2. Forest shrinking but protected areas increasing Terrestrial and marine protected areas (% of total territorial area) At the beginning of the 20th century the Earth’s forest area was about 5 billion hectares. That has since shrunk to about 4 billion hectares, 25 with the decline concentrated in developing countries. Low- and 20 middle- income countries lost 14.6 million hectares of forest a year between 1990 and 2011. Latin America and the Caribbean—with the 15 largest share of forest areas at about a quarter of the earth’s forest resources—lost some 99 million hectares, about 11 percent of its 10 total forest area. But high-income economies have gained about 17.7 million hectares of forest area since 1990. Many countries des- 5 ignate protected areas to preserve valuable habitat and the plant and animal species that live there. And by 2012 more than 14 percent of 1990 2012 0 the world’s land area and its oceans had been protected. Latin Sub- East Middle East South Europe High World America & Saharan Asia & & North Asia & Central income Caribbean Africa Pacific Africa Asia Source: Table 3 and online table 1.3. High-income countries use more energy, but growth is faster in developing countries Global energy use, 2011 (%) Economic growth and energy use move together, and energy producers tend to be energy users. With only 18 percent of the world’s popula- tion, high-income economies use about half the world’s energy produc- tion each year—more than 4 times more energy per person than United Rest of States middle-income economies and almost 14 times more than low-income the world 17% 23% Japan 4% economies. But low- and middle-income economies more than doubled their energy consumption and production over 1990–2011, as high- Russian income countries increased consumption 16 percent and production Federation 6% Other 21 percent. The average growth in energy use over 1990–2011 was India high-income 6% 23% 2 percent globally—3.6 percent for developing countries and 0.9 per- China cent for high-income economies. 21% Source: Online table 3.6. 44 World Development Indicators 2014 Front ? User guide World view People Environment Per capita carbon dioxide emissions are not highest in countries with the highest total emissions Global per capita carbon dioxide emissions rose 16 percent between Per capita carbon dioxide emissions (metric tons per capita) 1990 and 2010 to a record 4.9 metric tons. The countries with the 40 highest per capita emissions are not among the countries with the highest total emissions. In 2010 the top fi ve per capita emitters were Qatar, Trinidad and Tobago, Kuwait, Brunei Darussalam, and 30 Aruba, all high-income countries, whereas the top fi ve total emitters were China, the United States, India, the Russian Federation, and 20 Japan. Europe and Central Asia had the highest per capita emissions among developing country regions (5.3 metric tons), followed by East 10 Asia and Pacifi c (4.9 metric tons). While high-income countries saw 1990 2010 per capita carbon dioxide emissions fall 2.5 percent between 1990 and 2010, to 11.6 metric tons, they remain the world’s highest per 0 Qatar Trinidad Kuwait Brunei Aruba World capita emitters. and Tobago Darussalam Source: Online table 3.8. Sub-Saharan Africa’s fast-growing urban population Home to more than half the world’s people, urban areas will accom- Urban and rural population, 2012 (% of total population) modate almost all population growth over the next four decades. The 100 pace will be fastest in developing countries, where the urban popula- Rural tion is forecast to rise from 2.7 billion in 2012 to 5.2 billion in 2050. At 4 percent a year between 1990 and 2012, Sub- Saharan Africa 75 had the fastest pace of urban growth rate of all developing regions. Urbanization can yield important social benefits, such as improving 50 people’s access to public services. In Sub- Saharan Africa 83 percent of the urban population has access to an improved water source, com- 25 pared with 51 percent of the rural population. And access to improved Urban sanitation facilities in urban areas is almost twice that in rural areas. But urbanization can also have adverse environmental effects, con- 0 Latin Europe Middle East East Sub- South High World centrating pollution, harming health, and reducing productivity. America & & Central & North Asia & Saharan Asia income Caribbean Asia Africa Pacific Africa Source: Online table 3.12. Developing countries join the WAVES partnership The Wealth Accounting and the Valuation of Ecosystem Services Botswana’s sector shares of water use, formal employment, and GDP, 2011–12 (%) Water consumption Formal employment GDP (WAVES) is a global partnership that promotes sustainable develop- 50 ment by mainstreaming natural resources in development planning 40 and national economic accounts. Water accounts, a subset of natural capital accounts, collect data on water stocks and flows and water 30 rights and use. They provide a conceptual framework for organizing 20 water resources data for use in resource allocation policies at the 10 national and regional levels. Botswana, Colombia, Costa Rica, Mada- gascar, and the Philippines joined WAVES in 2012. Using the System of 0 de n ure e s s ts mm tion g t g en ice es nin n us tio ran i Tra Environmental-Economic Accounting methodology approved by the UN tur ult rnm sin ica c v old Mi tru tau er fac ric bu un ls ve eh ns Ag res nu Go na ,& us Co Statistics Commission, Botswana updated its water accounts from the Ma rso s& Ho ing co pe tel nk & Ho ba l& rt 1990s using natural capital accounting. In addition to water accounts, po e, cia ns nc So Tra ura Botswana’s natural capital accounts will include land and ecosystem Ins accounts, with a focus on tourism, minerals, and energy. Source: Wealth Accounting and the Valuation of Ecosystem Services and Botswana Department of Water Affairs. Economy States and markets Global links Back World Development Indicators 2014 45 3 Environment Deforestationa Nationally Internal Access to Access to Urban Particulate Carbon Energy use Electricity protected renewable improved improved population matter dioxide production areas freshwater water sanitation concentration emissions b Terrestrial and resources source facilities urban-population- marine areas weighted PM10 Per capita billion average % of total Per capita % of total % of total micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2012 2011 2012 2012 2011–12 2011 2010 2011 2011 Afghanistan 0.00 0.4 1,620 64 29 3.7 63 8.2 .. .. Albania –0.10 9.5 8,529 96 91 2.2 43 4.3 689 4.2 Algeria 0.57 7.4 298 84 95 3.0 34 123.5 1,108 51.2 American Samoa 0.19 16.8 .. 100 62 0.0 .. .. .. .. Andorra 0.00 9.8 4,053 100 100 0.0 31 0.5 .. .. Angola 0.21 12.1 7,334 54 60 4.4 21 30.4 673 5.7 Antigua and Barbuda 0.20 1.2 590 98 91 1.0 9 0.5 .. .. Argentina 0.81 6.6 6,777 99 97 1.0 35 180.5 1,967 129.6 Armenia 1.48 8.1 2,314 100 91 0.2 13 4.2 916 7.4 Aruba 0.00 0.0 .. 98 98 0.6 .. 2.3 .. .. Australia 0.37 15.0 22,023 100 100 1.9 14 373.1 5,501 252.6 Austria –0.13 23.6 6,543 100 100 0.6 28 66.9 3,928 62.2 Azerbaijan 0.00 7.4 885 80 82 1.8 20 45.7 1,369 20.3 Bahamas, The 0.00 1.0 55 98 92 1.8 .. 2.5 .. .. Bahrain –3.55 6.8 3 100 99 2.0 24 24.2 7,353 13.8 Bangladesh 0.18 4.2 687 85 57 2.9 121 56.2 205 44.1 Barbados 0.00 0.1 284 100 .. 1.6 11 1.5 .. .. Belarus –0.43 8.3 3,927 100 94 0.4 20 62.2 3,114 32.2 Belgium –0.16 24.5 1,086 100 100 0.8 29 108.9 5,349 89.0 Belize 0.67 26.4 50,588 99 91 2.0 18 0.4 .. .. Benin 1.04 25.5 1,053 76 14 4.2 69 5.2 385 0.2 Bermuda 0.00 5.1 .. .. .. 0.4 .. 0.5 .. .. Bhutan –0.34 28.4 106,933 98 47 3.8 16 0.5 .. .. Bolivia 0.50 20.8 29,396 88 46 2.3 78 15.5 746 7.2 Bosnia and Herzegovina 0.00 1.5 9,246 100 95 1.0 84 31.1 1,848 15.3 Botswana 0.99 37.2 1,208 97 64 1.9 199 5.2 1,115 0.4 Brazil 0.50 26.0 27,512 98 81 1.2 36 419.8 1,371 531.8 Brunei Darussalam 0.44 29.6 20,910 .. .. 1.9 9 9.2 9,427 3.7 Bulgaria –1.53 35.4 2,858 99 100 0.2 41 44.7 2,615 50.0 Burkina Faso 1.01 15.2 781 82 19 6.0 51 1.7 .. .. Burundi 1.40 4.9 1,054 75 47 5.8 30 0.3 .. .. Cabo Verde –0.36 0.2 612 89 65 2.0 .. 0.4 .. .. Cambodia 1.34 23.8 8,257 71 37 2.7 89 4.2 365 1.1 Cameroon 1.05 10.9 12,904 74 45 3.6 26 7.2 318 6.0 Canada 0.00 7.0 82,987 100 100 1.3 14 499.1 7,333 636.9 Cayman Islands 0.00 1.5 .. 96 96 1.7 .. 0.6 .. .. Central African Republic 0.13 18.0 31,784 68 22 2.6 32 0.3 .. .. Chad 0.66 16.6 1,242 51 12 3.4 50 0.5 .. .. Channel Islands .. 0.5 .. .. .. 1.0 .. .. .. .. Chile –0.25 15.0 51,073 99 99 1.1 60 72.3 1,940 65.7 China –1.57 16.1 2,093 92 65 3.0 82 8,286.9 2,029 4,715.7 Hong Kong SAR, China .. 41.9 .. .. .. 1.2 30 36.3 2,106 39.0 Macao SAR, China .. .. .. .. .. 1.9 33 1.0 .. .. Colombia 0.17 20.8 44,861 91 80 1.7 53 75.7 671 61.8 Comoros 9.34 4.0 1,714 95 35 2.8 21 0.1 .. .. Congo, Dem. Rep. 0.20 12.0 14,078 46 31 4.3 46 3.0 383 7.9 Congo, Rep. 0.07 30.4 52,540 75 15 3.3 29 2.0 393 1.3 46 World Development Indicators 2014 Front ? User guide World view People Environment Environment 3 Deforestationa Nationally Internal Access to Access to Urban Particulate Carbon Energy use Electricity protected renewable improved improved population matter dioxide production areas freshwater water sanitation concentration emissions b Terrestrial and resources source facilities urban-population- marine areas weighted PM10 Per capita billion average % of total Per capita % of total % of total micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2012 2011 2012 2012 2011–12 2011 2010 2011 2011 Costa Rica –0.93 22.6 23,725 97 94 2.1 48 7.8 983 9.8 Côte d’Ivoire –0.15 22.2 3,963 80 22 3.7 21 5.8 579 6.1 Croatia –0.19 10.3 8,807 99 98 0.2 30 20.9 1,971 10.7 Cuba –1.66 9.9 3,381 94 93 –0.1 37 38.4 992 17.8 Curaçao .. .. .. .. .. .. .. .. .. .. Cyprus –0.09 17.1 699 100 100 1.4 42 7.7 2,121 4.9 Czech Republic –0.08 22.4 1,253 100 100 0.1 29 111.8 4,138 86.8 Denmark –1.14 23.6 1,077 100 100 0.5 25 46.3 3,231 35.2 Djibouti 0.00 0.2 354 92 61 1.6 40 0.5 .. .. Dominica 0.58 3.7 .. .. .. 0.6 15 0.1 .. .. Dominican Republic 0.00 20.8 2,069 81 82 2.1 31 21.0 727 13.0 Ecuador 1.81 37.0 28,334 86 83 2.4 32 32.6 849 20.3 Egypt, Arab Rep. –1.73 11.3 23 99 96 2.0 120 204.8 978 156.6 El Salvador 1.45 8.7 2,837 90 70 1.4 46 6.2 690 5.8 Equatorial Guinea 0.69 15.1 36,313 .. .. 3.2 21 4.7 .. .. Eritrea 0.28 3.8 472 .. .. 5.4 77 0.5 129 0.3 Estonia 0.12 23.2 9,521 99 95 –0.3 17 18.3 4,197 12.9 Ethiopia 1.08 18.4 1,365 52 24 4.1 86 6.5 381 5.2 Faeroe Islands 0.00 1.0 .. .. .. 0.4 21 0.7 .. .. Fiji –0.34 6.0 32,895 96 87 1.5 27 1.3 .. .. Finland 0.14 15.2 19,858 100 100 0.6 16 61.8 6,449 73.5 France –0.39 28.7 3,059 100 100 1.1 24 361.3 3,868 556.9 French Polynesia –3.97 0.1 .. 100 97 1.1 .. 0.9 .. .. Gabon 0.00 19.1 102,884 92 41 2.7 12 2.6 1,253 1.8 Gambia, The –0.41 4.4 1,729 90 60 4.2 39 0.5 .. .. Georgia 0.09 3.7 12,966 99 93 0.4 35 6.2 790 10.2 Germany 0.00 49.0 1,308 100 100 –1.5 24 745.4 3,811 602.4 Ghana 2.08 14.4 1,221 87 14 3.4 82 9.0 425 11.2 Greece –0.81 21.5 5,214 100 99 0.1 35 86.7 2,402 59.2 Greenland 0.00 40.6 .. 100 100 0.2 .. 0.6 .. .. Grenada 0.00 0.3 .. 97 98 1.3 9 0.3 .. .. Guam 0.00 5.3 .. 100 90 1.2 .. .. .. .. Guatemala 1.40 29.8 7,425 94 80 3.4 75 11.1 691 8.1 Guinea 0.54 26.8 20,248 75 19 3.9 37 1.2 .. .. Guinea-Bissau 0.48 27.1 9,851 74 20 3.9 34 0.2 .. .. Guyana 0.00 5.0 304,723 98 84 0.9 17 1.7 .. .. Haiti 0.76 0.1 1,297 62 24 3.8 56 2.1 320 0.7 Honduras 2.06 16.2 12,336 90 80 3.1 84 8.1 609 7.1 Hungary –0.62 23.1 602 100 100 0.2 32 50.6 2,503 36.0 Iceland –4.99 13.3 532,892 100 100 0.6 18 2.0 17,964 17.2 India –0.46 5.0 1,184 93 36 2.4 100 2,008.8 614 1,052.3 Indonesia 0.51 9.1 8,281 85 59 2.7 47 434.0 857 182.4 Iran, Islamic Rep. 0.00 7.0 1,704 96 89 1.5 115 571.6 2,813 239.7 Iraq –0.09 0.4 1,108 85 85 2.5 36 114.7 1,266 54.2 Ireland –1.53 12.8 10,706 100 99 0.7 18 40.0 2,888 27.7 Isle of Man 0.00 .. .. .. .. 0.7 .. .. .. .. Israel –0.07 14.7 97 100 100 1.9 47 70.7 2,994 59.6 Economy States and markets Global links Back World Development Indicators 2014 47 3 Environment Deforestationa Nationally Internal Access to Access to Urban Particulate Carbon Energy use Electricity protected renewable improved improved population matter dioxide production areas freshwater water sanitation concentration emissions b Terrestrial and resources source facilities urban-population- marine areas weighted PM10 Per capita billion average % of total Per capita % of total % of total micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2012 2011 2012 2012 2011–12 2011 2010 2011 2011 Italy –0.90 21.0 3,005 100 .. –1.7 34 406.3 2,757 300.6 Jamaica 0.11 7.1 3,483 93 80 0.5 41 7.2 1,135 5.1 Japan –0.05 11.0 3,364 100 100 0.4 19 1,170.7 3,610 1,042.7 Jordan 0.00 0.0 110 96 98 2.5 38 20.8 1,143 14.6 Kazakhstan 0.17 3.3 3,887 93 97 1.2 47 248.7 4,717 86.6 Kenya 0.33 11.6 493 62 30 4.4 66 12.4 480 7.8 Kiribati 0.00 20.2 .. 67 40 1.8 .. 0.1 .. .. Korea, Dem. People’s Rep. 2.00 1.7 2,720 98 82 0.8 124 71.6 773 21.6 Korea, Rep. 0.11 5.3 1,303 98 100 0.8 46 567.6 5,232 520.1 Kosovo .. .. .. .. .. .. 48 .. 1,411 5.8 Kuwait –2.57 12.9 – 99 100 4.0 89 93.7 10,408 57.5 Kyrgyz Republic –1.07 6.3 8,873 88 92 1.9 50 6.4 562 15.2 Lao PDR 0.49 16.7 29,197 72 65 5.1 46 1.9 .. .. Latvia –0.34 17.6 8,127 98 .. –1.2 39 7.6 2,122 6.1 Lebanon –0.45 0.5 1,095 100 .. 1.1 43 20.4 1,449 16.4 Lesotho –0.47 0.5 2,577 81 30 3.7 42 0.0 .. .. Liberia 0.67 2.4 49,023 75 17 3.5 25 0.8 .. .. Libya 0.00 0.1 115 .. 97 1.1 74 59.0 2,186 27.6 Liechtenstein 0.00 43.1 .. .. .. 0.5 30 .. .. .. Lithuania –0.68 17.2 5,139 96 94 –1.2 32 13.6 2,406 4.2 Luxembourg 0.00 39.7 1,929 100 100 2.7 17 10.8 8,046 2.6 Macedonia, FYR –0.41 7.3 2,567 99 91 0.3 82 10.9 1,484 6.9 Madagascar 0.45 4.7 15,545 50 14 4.7 48 2.0 .. .. Malawi 0.97 18.3 1,044 85 10 3.8 49 1.2 .. .. Malaysia 0.54 13.9 20,168 100 96 2.6 47 216.8 2,639 130.1 Maldives 0.00 .. 90 99 99 4.6 21 1.1 .. .. Mali 0.61 6.0 4,162 67 22 4.8 55 0.6 .. .. Malta 0.00 2.2 121 100 100 0.9 41 2.6 2,060 2.2 Marshall Islands 0.00 0.7 .. 95 76 0.5 .. 0.1 .. .. Mauritania 2.66 1.2 108 50 27 3.2 46 2.2 .. .. Mauritius 1.00 0.7 2,139 100 91 0.5 11 4.1 .. .. Mexico 0.30 13.7 3,427 95 85 1.6 46 443.7 1,560 295.8 Micronesia, Fed. Sets. –0.04 0.1 .. 89 57 0.4 .. 0.1 .. .. Moldova –1.77 3.8 281 97 87 1.5 44 4.9 936 5.8 Monaco 0.00 98.4 .. 100 100 0.8 18 .. .. .. Mongolia 0.73 13.8 12,635 85 56 2.8 284 11.5 1,310 4.8 Montenegro 0.00 12.8 .. 98 90 0.4 30 2.6 1,900 2.7 Morocco –0.23 19.9 905 84 75 2.1 66 50.6 539 24.9 Mozambique 0.54 16.4 4,080 49 21 3.3 34 2.9 415 16.8 Myanmar 0.93 6.0 19,159 86 77 2.6 67 9.0 268 7.3 Namibia 0.97 42.6 2,778 92 32 3.3 55 3.2 717 1.4 Nepal 0.70 16.4 7,298 88 37 3.1 110 3.8 383 3.3 Netherlands –0.14 31.5 659 100 100 0.8 25 182.1 4,638 113.0 New Caledonia 0.00 30.5 .. 98 100 1.4 29 3.9 .. .. New Zealand –0.01 21.3 74,230 100 .. 0.7 16 31.6 4,124 44.5 Nicaragua 2.01 32.5 32,125 85 52 2.0 49 4.5 515 3.8 Niger 0.98 16.7 212 52 9 5.2 50 1.4 .. .. 48 World Development Indicators 2014 Front ? User guide World view People Environment Environment 3 Deforestationa Nationally Internal Access to Access to Urban Particulate Carbon Energy use Electricity protected renewable improved improved population matter dioxide production areas freshwater water sanitation concentration emissions b Terrestrial and resources source facilities urban-population- marine areas weighted PM10 Per capita billion average % of total Per capita % of total % of total micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2012 2011 2012 2012 2011–12 2011 2010 2011 2011 Nigeria 3.67 13.8 1,346 64 28 4.0 149 78.9 721 27.0 Northern Mariana Islands 0.53 19.9 .. 98 80 0.3 .. .. .. .. Norway –0.80 12.2 77,124 100 100 1.7 24 57.2 5,681 126.9 Oman 0.00 9.3 463 93 97 9.5 32 57.2 8,356 21.9 Pakistan 2.24 10.6 312 91 48 2.6 171 161.4 482 95.3 Palau –0.18 28.2 .. 95 100 1.6 .. 0.2 .. .. Panama 0.36 14.1 39,409 94 73 2.4 49 9.6 1,085 7.9 Papua New Guinea 0.48 1.4 114,217 40 19 2.7 32 3.1 .. .. Paraguay 0.97 6.4 14,301 94 80 2.6 32 5.1 739 57.6 Peru 0.18 18.3 54,567 87 73 1.7 63 57.6 695 39.2 Philippines –0.75 5.1 5,039 92 74 2.2 45 81.6 426 69.2 Poland –0.31 34.8 1,391 .. .. –0.1 34 317.3 2,629 163.1 Portugal –0.11 14.7 3,599 100 100 0.5 28 52.4 2,187 51.9 Puerto Rico –1.76 4.6 1,922 .. 99 –0.6 15 .. .. .. Qatar 0.00 2.4 29 100 100 7.2 28 70.5 17,419 30.7 Romania –0.32 19.2 2,100 .. .. –0.3 35 78.7 1,778 62.0 Russian Federation 0.00 11.3 30,169 97 70 0.6 27 1,740.8 5,113 1,053.0 Rwanda –2.38 10.5 852 71 64 4.4 30 0.6 .. .. Samoa 0.00 2.3 .. 99 92 –0.2 .. 0.2 .. .. San Marino 0.00 .. .. .. .. 0.7 20 .. .. .. São Tomé and Príncipe 0.00 0.0 11,901 97 34 3.7 14 0.1 .. .. Saudi Arabia 0.00 29.9 86 97 100 2.1 108 464.5 6,738 250.1 Senegal 0.49 24.2 1,935 74 52 3.6 147 7.1 264 3.0 Serbia –0.99 6.3 1,158 99 97 0.1 43 46.0 2,230 38.0 Seychelles 0.00 1.3 .. 96 97 1.7 .. 0.7 .. .. Sierra Leone 0.69 10.3 27,278 60 13 2.9 29 0.7 .. .. Singapore 0.00 3.4 116 100 100 2.5 25 13.5 6,452 46.0 Sint Maarten .. .. .. .. .. .. .. .. .. .. Slovak Republic –0.06 36.1 2,334 100 100 0.1 30 36.1 3,214 28.3 Slovenia –0.16 54.9 9,095 100 100 0.2 31 15.3 3,531 15.9 Solomon Islands 0.25 1.1 83,086 81 29 4.3 25 0.2 .. .. Somalia 1.07 0.5 606 31 23 4.1 32 0.6 .. .. South Africa 0.00 6.6 869 95 74 2.0 40 460.1 2,741 259.6 South Sudan .. .. .. 57 9 5.4 .. .. .. .. Spain –0.68 25.3 2,379 100 100 0.2 27 269.7 2,686 289.0 Sri Lanka 1.12 15.4 2,530 94 92 –2.1 62 12.7 499 11.6 St. Kitts and Nevis 0.00 0.8 453 98 .. 1.4 9 0.2 .. .. St. Lucia –0.07 2.5 .. 94 65 –3.0 11 0.4 .. .. St. Martin 0.00 .. .. .. .. .. .. .. .. .. St. Vincent & the Grenadines –0.27 1.2 .. 95 .. 0.8 14 0.2 .. .. Sudan 0.08 7.1 641 55c 24 c 2.5c 62 14.2 355 8.6 Suriname 0.01 15.2 166,113 95 80 1.5 18 2.4 .. .. Swaziland –0.84 3.0 2,178 74 57 1.4 52 1.0 .. .. Sweden –0.30 13.9 18,097 100 100 0.9 20 52.5 5,190 150.3 Switzerland –0.38 26.3 5,106 100 100 1.2 21 38.8 3,207 62.9 Syrian Arab Republic –1.29 0.7 325 90 96 2.7 27 61.9 910 41.1 Tajikistan 0.00 4.8 8,120 72 94 2.7 15 2.9 306 16.2 Economy States and markets Global links Back World Development Indicators 2014 49 3 Environment Deforestationa Nationally Internal Access to Access to Urban Particulate Carbon Energy use Electricity protected renewable improved improved population matter dioxide production areas freshwater water sanitation concentration emissions b Terrestrial and resources source facilities urban-population- marine areas weighted PM10 Per capita billion average % of total Per capita % of total % of total micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2012 2011 2012 2012 2011–12 2011 2010 2011 2011 Tanzania 1.13 31.7 1,812 53 12 4.8 62 6.8 448 5.3 Thailand 0.02 16.4 3,372 96 93 1.4 45 295.3 1,790 156.0 Timor-Leste 1.40 6.2 6,986 70 39 4.2 .. 0.2 .. .. Togo 5.13 24.2 1,777 61 11 3.9 34 1.5 427 0.1 Tonga 0.00 9.5 .. 99 91 0.8 .. 0.2 .. .. Trinidad and Tobago 0.32 10.1 2,881 94 92 2.3 16 50.7 15,691 8.9 Tunisia –1.86 4.8 393 97 90 1.3 79 25.9 890 16.1 Turkey –1.11 2.1 3,107 100 91 2.6 65 298.0 1,539 229.4 Turkmenistan 0.00 3.2 275 71 99 2.0 21 53.1 4,839 17.2 Turks and Caicos Islands 0.00 3.6 .. .. .. 2.6 .. 0.2 .. .. Tuvalu 0.00 0.3 .. 98 83 1.0 .. .. .. .. Uganda 2.56 11.5 1,110 75 34 6.0 29 3.8 .. .. Ukraine –0.21 4.5 1,162 98 94 0.0 47 304.8 2,766 194.9 United Arab Emirates –0.24 15.5 17 100 98 3.4 132 167.6 7,407 99.1 United Kingdom –0.31 23.4 2,292 100 100 0.7 20 493.5 2,973 364.9 United States –0.13 15.1 9,044 99 100 1.0 18 5,433.1 7,032 4,326.6 Uruguay –2.14 2.6 17,438 99 96 0.4 33 6.6 1,309 10.3 Uzbekistan –0.20 3.4 557 87 100 1.6 35 104.4 1,628 52.4 Vanuatu 0.00 0.5 .. 91 58 3.5 23 0.1 .. .. Venezuela, RB 0.60 49.5 24,488 .. .. 1.7 38 201.7 2,380 122.1 Vietnam –1.65 4.7 4,092 95 75 3.1 69 150.2 697 99.2 Virgin Islands (U.S.) 0.80 2.8 .. 100 96 –0.3 .. .. .. .. West Bank and Gaza –0.10 0.6 207 82 94 3.3 .. 2.4 .. .. Yemen, Rep. 0.00 1.1 90 55 53 4.1 78 21.9 312 6.2 Zambia 0.33 37.8 5,882 63 43 4.3 46 2.4 621 11.5 Zimbabwe 1.88 27.2 918 80 40 4.0 104 9.4 697 8.9 World 0.11 w 14.0 w 6,122 s 89 w 64 w 2.0 w 61 w 33,615.4d w 1,890 w 22,158.5 w Low income 0.61 13.5 5,121 69 37 3.7 74 229.3 360 209.7 Middle income 0.13 14.4 4,931 90 60 2.4 75 16,548.5 1,281 9,778.8 Lower middle income 0.31 11.1 3,144 88 48 2.6 90 3,827.0 687 2,211.0 Upper middle income 0.04 15.8 6,791 93 74 2.3 65 12,721.1 1,893 7,566.7 Low & middle income 0.22 14.2 4,958 87 57 2.5 75 16,777.5 1,179 10,005.1 East Asia & Pacific –0.44 13.7 4,438 91 67 2.9 75 9,570.5 1,671 5,410.8 Europe & Central Asia –0.48 5.2 2,744 95 94 1.3 48 1,416.7 2,078 908.6 Latin America & Carib. 0.46 21.2 21,735 94 81 1.5 43 1,553.7 1,292 1,348.0 Middle East & N. Africa –0.15 5.9 679 90 88 2.2 79 1,277.9 1,376 654.4 South Asia –0.29 5.9 1,217 91 40 2.5 110 2,252.6 555 1,215.8 Sub-Saharan Africa 0.48 16.3 4,391 64 30 3.9 77 703.8 681 445.2 High income –0.03 13.8 11,335 99 96 0.7 27 14,901.7 4,872 12,198.4 Euro area –0.31 27.0 2,962 100 100 –0.2 27 2,472.4 3,480 2,292.2 a. Negative values indicate an increase in forest area. b. River flows from other countries are not included because of data unreliability. c. Excludes South Sudan. d. Includes emissions not allocated to specific countries. 50 World Development Indicators 2014 Front ? User guide World view People Environment Environment 3 About the data Environmental resources are needed to promote growth and poverty in total renewable water resources. Data do not distinguish between reduction, but growth can create new stresses on the environment. seasonal and geographic variations in water availability within coun- Deforestation, loss of biologically diverse habitat, depletion of water tries. Data for small countries and countries in arid and semiarid resources, pollution, urbanization, and ever increasing demand for zones are less reliable than data for larger countries and countries energy production are some of the factors that must be considered with greater rainfall. in shaping development strategies. Water and sanitation Loss of forests A reliable supply of safe drinking water and sanitary disposal of Forests provide habitat for many species and act as carbon sinks. If excreta are two of the most important means of improving human properly managed they also provide a livelihood for people who man- health and protecting the environment. Improved sanitation facilities age and use forest resources. FAO (2010) provides information on prevent human, animal, and insect contact with excreta. forest cover in 2010 and adjusted estimates of forest cover in 1990 Data on access to an improved water source measure the percent- and 2000. Data presented here do not distinguish natural forests age of the population with ready access to water for domestic pur- from plantations, a breakdown the FAO provides only for developing poses, based on surveys and estimates of service users provided countries. Thus, data may underestimate the rate at which natural by governments to the Joint Monitoring Programme of the World forest is disappearing in some countries. Health Organization (WHO) and the United Nations Children’s Fund (UNICEF). The coverage rates are based on information from service Habitat protection and biodiversity users on household use rather than on information from service Deforestation is a major cause of loss of biodiversity, and habitat providers, which may include nonfunctioning systems. Access to conservation is vital for stemming this loss. Conservation efforts drinking water from an improved source does not ensure that the have focused on protecting areas of high biodiversity. The World water is safe or adequate, as these characteristics are not tested Conservation Monitoring Centre (WCMC) and the United Nations at the time of survey. While information on access to an improved Environment Programme (UNEP) compile data on protected areas. water source is widely used, it is extremely subjective; terms such as Differences in definitions, reporting practices, and reporting peri- “safe,” “improved,” “adequate,” and “reasonable” may have differ- ods limit cross-country comparability. Nationally protected areas ent meanings in different countries despite official WHO definitions are defined using the six International Union for Conservation of (see Definitions). Even in high-income countries treated water may Nature (IUCN) categories for areas of at least 1,000 hectares— not always be safe to drink. Access to an improved water source is scientific reserves and strict nature reserves with limited public equated with connection to a supply system; it does not account for access, national parks of national or international significance and variations in the quality and cost of the service. not materially affected by human activity, natural monuments and natural landscapes with unique aspects, managed nature reserves Urbanization and wildlife sanctuaries, protected landscapes (which may include There is no consistent and universally accepted standard for distin- cultural landscapes), and areas managed mainly for the sustainable guishing urban from rural areas and, by extension, calculating their use of natural systems to ensure long-term protection and mainte- populations. Most countries use a classification related to the size nance of biological diversity—as well as terrestrial protected areas or characteristics of settlements. Some define areas based on the not assigned to an IUCN category. Designating an area as protected presence of certain infrastructure and services. Others designate does not mean that protection is in force. For small countries with areas based on administrative arrangements. Because data are protected areas smaller than 1,000 hectares, the size limit in the based on national definitions, cross-country comparisons should definition leads to underestimation of protected areas. Due to varia- be made with caution. tions in consistency and methods of collection, data quality is highly variable across countries. Some countries update their information Air pollution more frequently than others, some have more accurate data on Indoor and outdoor air pollution place a major burden on world health. extent of coverage, and many underreport the number or extent of More than half the world’s people rely on dung, wood, crop waste, protected areas. or coal to meet basic energy needs. Cooking and heating with these fuels on open fires or stoves without chimneys lead to indoor air pol- Freshwater resources lution, which is responsible for 1.6 million deaths a year—one every The data on freshwater resources are derived from estimates of 20 seconds. In many urban areas air pollution exposure is the main runoff into rivers and recharge of groundwater. These estimates are environmental threat to health. Long-term exposure to high levels of derived from different sources and refer to different years, so cross- soot and small particles contributes to such health effects as respira- country comparisons should be made with caution. Data are col- tory diseases, lung cancer, and heart disease. Particulate pollution, lected intermittently and may hide substantial year-to-year variations alone or with sulfur dioxide, creates an enormous burden of ill health. Economy States and markets Global links Back World Development Indicators 2014 51 3 Environment Data on particulate matter are estimated average annual concen- urban areas—but also reflects climatic, geographic, and economic trations in residential areas away from air pollution “hotspots,” such factors. Energy use has been growing rapidly in low- and middle- as industrial districts and transport corridors. Data are estimates income economies, but high-income economies still use more than of annual ambient concentrations of particulate matter in cities of four times as much energy per capita. more than 100,000 people by the World Bank’s Agriculture and Total energy use refers to the use of primary energy before trans- Environmental Services Department. formation to other end-use fuels (such as electricity and refined Pollutant concentrations are sensitive to local conditions, and petroleum products). It includes energy from combustible renew- even monitoring sites in the same city may register different levels. ables and waste—solid biomass and animal products, gas and liq- Thus these data should be considered only a general indication of uid from biomass, and industrial and municipal waste. Biomass is air quality, and comparisons should be made with caution. They any plant matter used directly as fuel or converted into fuel, heat, allow for cross-country comparisons of the relative risk of particulate or electricity. Data for combustible renewables and waste are often matter pollution facing urban residents. Major sources of urban based on small surveys or other incomplete information and thus outdoor particulate matter pollution are traffic and industrial emis- give only a broad impression of developments and are not strictly sions, but nonanthropogenic sources such as dust storms may also comparable across countries. The International Energy Agency (IEA) be a substantial contributor for some cities. Country technology and reports include country notes that explain some of these differences pollution controls are important determinants of particulate matter. (see Data sources). All forms of energy—primary energy and primary Current WHO air quality guidelines are annual mean concentrations electricity—are converted into oil equivalents. A notional thermal of 20 micrograms per cubic meter for particulate matter less than efficiency of 33 percent is assumed for converting nuclear electric- 10 microns in diameter. ity into oil equivalents and 100 percent efficiency for converting hydroelectric power. Carbon dioxide emissions Carbon dioxide emissions are the primary source of greenhouse Electricity production gases, which contribute to global warming, threatening human and Use of energy is important in improving people’s standard of living. natural habitats. Fossil fuel combustion and cement manufacturing But electricity generation also can damage the environment. Whether are the primary sources of anthropogenic carbon dioxide emissions, such damage occurs depends largely on how electricity is generated. which the U.S. Department of Energy’s Carbon Dioxide Information For example, burning coal releases twice as much carbon dioxide—a Analysis Center (CDIAC) calculates using data from the United major contributor to global warming—as does burning an equivalent Nations Statistics Division’s World Energy Data Set and the U.S. amount of natural gas. Nuclear energy does not generate carbon Bureau of Mines’s Cement Manufacturing Data Set. Carbon dioxide dioxide emissions, but it produces other dangerous waste products. emissions, often calculated and reported as elemental carbon, were The IEA compiles data and data on energy inputs used to gen- converted to actual carbon dioxide mass by multiplying them by erate electricity. Data for countries that are not members of the 3.667 (the ratio of the mass of carbon to that of carbon dioxide). Organisation for Economic Co-operation and Development (OECD) Although estimates of global carbon dioxide emissions are probably are based on national energy data adjusted to conform to annual accurate within 10 percent (as calculated from global average fuel questionnaires completed by OECD member governments. In addi- chemistry and use), country estimates may have larger error bounds. tion, estimates are sometimes made to complete major aggregates Trends estimated from a consistent time series tend to be more from which key data are missing, and adjustments are made to accurate than individual values. Each year the CDIAC recalculates compensate for differences in definitions. The IEA makes these the entire time series since 1949, incorporating recent findings and estimates in consultation with national statistical offices, oil com- corrections. Estimates exclude fuels supplied to ships and aircraft panies, electric utilities, and national energy experts. It occasionally in international transport because of the difficulty of apportioning revises its time series to reflect political changes. For example, the the fuels among benefiting countries. IEA has constructed historical energy statistics for countries of the former Soviet Union. In addition, energy statistics for other countries Energy use have undergone continuous changes in coverage or methodology in In developing economies growth in energy use is closely related to recent years as more detailed energy accounts have become avail- growth in the modern sectors—industry, motorized transport, and able. Breaks in series are therefore unavoidable. 52 World Development Indicators 2014 Front ? User guide World view People Environment Environment 3 Definitions Data sources • Deforestation is the permanent conversion of natural forest area Data on deforestation are from FAO (2010) and the FAO’s data to other uses, including agriculture, ranching, settlements, and website. Data on protected areas, derived from the UNEP and infrastructure. Deforested areas do not include areas logged but WCMC online databases, are based on data from national authori- intended for regeneration or areas degraded by fuelwood gathering, ties, national legislation, and international agreements. Data on acid precipitation, or forest fires. • Nationally protected areas are freshwater resources are from the FAO’s AQUASTAT database. terrestrial and marine protected areas as a percentage of total ter- Data on access to water and sanitation are from the WHO/UNICEF ritorial area and include all nationally designated protected areas Joint Monitoring Programme for Water Supply and Sanitation (www with known location and extent. All overlaps between different desig- .wssinfo.org). Data on urban population are from the United Nations nations and categories, buffered points, and polygons are removed, Population Division (2011). Data on particulate matter concentra- and all undated protected areas are dated. • Internal renewable tions are World Bank estimates. Data on carbon dioxide emissions freshwater resources are the average annual flows of rivers and are from CDIAC online databases. Data on energy use and electricity groundwater from rainfall in the country. Natural incoming flows origi- production are from IEA online databases and published in IEA’s nating outside a country’s borders and overlapping water resources annual publications, Energy Statistics of Non-OECD Countries, Energy between surface runoff and groundwater recharge are excluded. Balances of Non-OECD Countries, Energy Statistics of OECD Countries, • Access to an improved water source is the percentage of the and Energy Balances of OECD Countries. population with reasonable access to an adequate amount of water from an improved source, such as piped water into a dwelling, plot, References or yard; public tap or standpipe; tubewell or borehole; protected dug Botswana Department of Water Affairs. n.d. Various reports. [www well or spring; and rainwater collection. Unimproved sources include .water.gov.bw]. Gaborone. unprotected dug wells or springs, carts with small tank or drum, CDIAC (Carbon Dioxide Information Analysis Center). n.d. Online data- bottled water, and tanker trucks. • Access to improved sanitation base. [http://cdiac.ornl.gov/home.html]. Oak Ridge National Labo- facilities is the percentage of the population with at least adequate ratory, Environmental Science Division, Oak Ridge, TN. access to excreta disposal facilities (private or shared, but not pub- FAO (Food and Agriculture Organization of the United Nations). 2010. lic) that can effectively prevent human, animal, and insect contact Global Forest Resources Assessment 2010. Rome. with excreta (facilities do not have to include treatment to render ———. n.d. AQUASTAT. Online database. [www.fao.org/nr/water sewage outflows innocuous). Improved facilities range from simple /aquastat/data/query/index.html]. Rome. but protected pit latrines to flush toilets with a sewerage connection. IEA (International Energy Agency). Various years. Energy Balances of To be effective, facilities must be correctly constructed and properly Non-OECD Countries. Paris. maintained. • Urban population is the midyear population of areas ———.Various years. Energy Balances of OECD Countries. Paris. defined as urban in each country and reported to the United Nations ———. Various years. Energy Statistics of Non-OECD Countries. Paris. divided by the World Bank estimate of total population. • Particulate ———.Various years. Energy Statistics of OECD Countries. Paris. matter concentration is fine suspended particulates of less than UNEP (United Nations Environment Programme) and WCMC (World 10 microns in diameter (PM10) that are capable of penetrating deep Conservation Monitoring Centre). 2013. Online databases [www into the respiratory tract and causing severe health damage. Data .unep-wcmc.org/datasets-tools--reports_15.html?&types=Data,We are urban-population-weighted PM10 levels in residential areas of bsite,Tool&ctops=]. Cambridge, UK. cities with more than 100,000 residents. • Carbon dioxide emis- United Nations Population Division. 2012. World Urbanization Pros- sions are emissions from the burning of fossil fuels and the manu- pects: The 2011 Revision. New York: United Nations, Department facture of cement and include carbon dioxide produced during con- of Economic and Social Affairs. [http://esa.un.org/unpd/wup sumption of solid, liquid, and gas fuels and gas flaring. • Energy use /CD-ROM/Urban-Agglomerations.htm]. refers to the use of primary energy before transformation to other WAVES (Wealth Accounting and the Valuation of Ecosystem Services). end use fuels, which equals indigenous production plus imports n.d. Online reports. [www.wavespartnership.org]. Washington, DC. and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport. • Electricity production is measured at the terminals of all alternator sets in a station. In addition to hydropower, coal, oil, gas, and nuclear power generation, it covers generation by geothermal, solar, wind, and tide and wave energy as well as that from combustible renewables and waste. Pro- duction includes the output of electric plants designed to produce electricity only, as well as that of combined heat and power plants. Economy States and markets Global links Back World Development Indicators 2014 53 3 Environment Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/3.1). To view a specific /indicator/SP.RUR.TOTL.ZS). 3.1 Rural environment and land use Annual freshwater withdrawals, % for Rural population SP.RUR.TOTL.ZS agriculture ER.H2O.FWAG.ZS Rural population growth SP.RUR.TOTL.ZG Annual freshwater withdrawals, % for Land area AG.LND.TOTL.K2 industry ER.H2O.FWIN.ZS Forest area AG.LND.FRST.ZS Annual freshwater withdrawals, % of domestic ER.H2O.FWDM.ZS Permanent cropland AG.LND.CROP.ZS Water productivity, GDP/water use ER.GDP.FWTL.M3.KD Arable land, % of land area AG.LND.ARBL.ZS Access to an improved water source, % of Arable land, hectares per person AG.LND.ARBL.HA.PC rural population SH.H2O.SAFE.RU.ZS Access to an improved water source, % of 3.2 Agricultural inputs urban population SH.H2O.SAFE.UR.ZS Agricultural land, % of land area AG.LND.AGRI.ZS Agricultural land, % irrigated AG.LND.IRIG.AG.ZS 3.6 Energy production and use Average annual precipitation AG.LND.PRCP.MM Energy production EG.EGY.PROD.KT.OE Land under cereal production AG.LND.CREL.HA Energy use EG.USE.COMM.KT.OE Fertilizer consumption, % of fertilizer Energy use, Average annual growth ..a,b production AG.CON.FERT.PT.ZS Energy use, Per capita EG.USE.PCAP.KG.OE Fertilizer consumption, kilograms per Fossil fuel EG.USE.COMM.FO.ZS hectare of arable land AG.CON.FERT.ZS Combustible renewable and waste EG.USE.CRNW.ZS Agricultural employment SL.AGR.EMPL.ZS Alternative and nuclear energy production EG.USE.COMM.CL.ZS Tractors AG.LND.TRAC.ZS 3.7 Electricity production, sources, and access 3.3 Agricultural output and productivity Electricity production EG.ELC.PROD.KH Crop production index AG.PRD.CROP.XD Coal sources EG.ELC.COAL.ZS Food production index AG.PRD.FOOD.XD Natural gas sources EG.ELC.NGAS.ZS Livestock production index AG.PRD.LVSK.XD Oil sources EG.ELC.PETR.ZS Cereal yield AG.YLD.CREL.KG Hydropower sources EG.ELC.HYRO.ZS Agriculture value added per worker EA.PRD.AGRI.KD Renewable sources EG.ELC.RNWX.ZS 3.4 Deforestation and biodiversity Nuclear power sources EG.ELC.NUCL.ZS Forest area AG.LND.FRST.K2 Access to electricity EG.ELC.ACCS.ZS Average annual deforestation ..a,b 3.8 Energy dependency, efficiency and carbon dioxide Threatened species, Mammals EN.MAM.THRD.NO emissions Threatened species, Birds EN.BIR.THRD.NO Net energy imports EG.IMP.CONS.ZS Threatened species, Fishes EN.FSH.THRD.NO GDP per unit of energy use EG.GDP.PUSE.KO.PP.KD Threatened species, Higher plants EN.HPT.THRD.NO Carbon dioxide emissions, Total EN.ATM.CO2E.KT Terrestrial protected areas ER.LND.PTLD.ZS Carbon dioxide emissions, Carbon intensity EN.ATM.CO2E.EG.ZS Marine protected areas ER.MRN.PTMR.ZS Carbon dioxide emissions, Per capita EN.ATM.CO2E.PC 3.5 Freshwater Carbon dioxide emissions, kilograms per 2005 PPP $ of GDP EN.ATM.CO2E.PP.GD.KD Internal renewable freshwater resources ER.H2O.INTR.K3 Internal renewable freshwater resources, 3.9 Trends in greenhouse gas emissions Per capita ER.H2O.INTR.PC Carbon dioxide emissions, Total EN.ATM.CO2E.KT Annual freshwater withdrawals, cu. m ER.H2O.FWTL.K3 Carbon dioxide emissions, % change ..a,b Annual freshwater withdrawals, % of internal resources ER.H2O.FWTL.ZS Methane emissions, Total EN.ATM.METH.KT.CE Methane emissions, % change ..a,b 54 World Development Indicators 2014 Front ? User guide World view People Environment Environment 3 Methane emissions, From energy processes EN.ATM.METH.EG.ZS Population in the largest city EN.URB.LCTY.UR.ZS Methane emissions, Agricultural EN.ATM.METH.AG.ZS Access to improved sanitation facilities, Nitrous oxide emissions, Total EN.ATM.NOXE.KT.CE % of urban population SH.STA.ACSN.UR Nitrous oxide emissions, % change ..a,b Access to improved sanitation facilities, % of rural population SH.STA.ACSN.RU Nitrous oxide emissions, Energy and industry EN.ATM.NOXE.EI.ZS Nitrous oxide emissions, Agriculture EN.ATM.NOXE.AG.ZS 3.13 Traffic and congestion Other greenhouse gas emissions, Total EN.ATM.GHGO.KT.CE Motor vehicles, Per 1,000 people IS.VEH.NVEH.P3 Other greenhouse gas emissions, % change ..a,b Motor vehicles, Per kilometer of road IS.VEH.ROAD.K1 Passenger cars IS.VEH.PCAR.P3 3.10 Carbon dioxide emissions by sector Road density IS.ROD.DNST.K2 Electricity and heat production EN.CO2.ETOT.ZS Road sector energy consumption, % of total Manufacturing industries and construction EN.CO2.MANF.ZS consumption IS.ROD.ENGY.ZS Residential buildings and commercial and Road sector energy consumption, Per capita IS.ROD.ENGY.PC public services EN.CO2.BLDG.ZS Diesel fuel consumption IS.ROD.DESL.PC Transport EN.CO2.TRAN.ZS Gasoline fuel consumption IS.ROD.SGAS.PC Other sectors EN.CO2.OTHX.ZS Pump price for super grade gasoline EP.PMP.SGAS.CD 3.11 Climate variability, exposure to impact, and Pump price for diesel EP.PMP.DESL.CD resilience Urban-population-weighted particulate Average daily minimum/maximum temperature ..b matter concentrations (PM10) EN.ATM.PM10.MC.M3 Projected annual temperature ..b 3.14 Air pollution Projected annual cool days/cold nights ..b This table provides air pollution data for Projected annual hot days/warm nights ..b major cities. ..b Projected annual precipitation ..b Land area with an elevation of 5 meters or less AG.LND.EL5M.ZS 3.15 Contribution of natural resources to gross domestic Population living in areas with elevation of product 5 meters or less EN.POP.EL5M.ZS Total natural resources rents NY.GDP.TOTL.RT.ZS Population affected by droughts, floods, Oil rents NY.GDP.PETR.RT.ZS and extreme temperatures EN.CLC.MDAT.ZS Natural gas rents NY.GDP.NGAS.RT.ZS Disaster risk reduction progress score EN.CLC.DRSK.XQ Coal rents NY.GDP.COAL.RT.ZS Mineral rents NY.GDP.MINR.RT.ZS 3.12 Urbanization Forest rents NY.GDP.FRST.RT.ZS Urban population SP.URB.TOTL Urban population, % of total population SP.URB.TOTL.IN.ZS a. Derived from data elsewhere in the World Development Indicators database. Urban population, Average annual growth SP.URB.GROW b. Available online only as part of the table, not as an individual indicator. Population in urban agglomerations of more than 1 million EN.URB.MCTY.TL.ZS Economy States and markets Global links Back World Development Indicators 2014 55 ECONOMY 56 World Development Indicators 2014 Front ? User guide World view People Environment 4 The Economy section provides a picture of the aspects of the economy that have come into global economy and the economic activity of prominence, elaborates on aspects that have more than 200 countries and territories that pro- increasingly become the focus of analytical duce, trade, and consume the world’s output. attention, and clarifies guidance on a wide range It includes measures of macroeconomic perfor- of issues. The changes in the 2008 SNA include mance and stability and broader measures of further specification of assets, capital forma- income and saving adjusted for pollution, depre- tion, and consumption of fixed capital; concepts ciation, and resource depletion. related to statistical units and institutional sec- The world economy grew 2.4  percent in toring; the scope of transactions, including the 2013 to reach $73 trillion in current prices, and production boundary; the scope of transactions growth is projected to accelerate to 3.2 percent by government and the public sector; and the in 2014. The share from low- and middle-income treatment and definition of financial instruments economies increased to 32.2  percent from and assets. The 2008 SNA and the sixth edition 31.0 percent in 2012. Low- and middle-income of the IMF’s Balance of Payments Manual have economies, estimated to have grown 4.9 percent harmonized concepts and classifications. in 2013, are projected to expand 5.3 percent These changes bring the accounts into line in 2014. Growth in high-income economies has with developments in the economic environ- been upgraded from earlier forecasts to 1.3 per- ment, advances in methodological research, cent in 2013 and 2.2 percent in 2014. and the needs of users. As of 2013, Australia; During 2014 many countries are expected to Canada; Hong Kong SAR, China; Mexico; Timor- switch to the System of National Accounts 2008 Leste; and the United States have switched to (2008 SNA)—the latest version of the interna- the 2008 SNA. tionally agreed standard set of recommendations A detailed explanation of the changes on how to compile measures of economic activity, from the 1993 SNA are in annex 3 of the adopted by the United Nations Statistical Com- 2008 SNA manual (http://unstats.un.org mission. The 2008 SNA is an update of the Sys- /unsd/nationalaccount/docs/SNA2008.pdf). tem of National Accounts 1993 and retains the The complete 2008 SNA methodology can be basic theoretical framework of its predecessor. accessed through the United Nations Statistics In line with the commission’s mandate, Division website (http://unstats.un.org/unsd the 2008 SNA introduces treatments for new /nationalaccount/sna2008.asp). Economy States and markets Global links Back World Development Indicators 2014 57 Highlights East Asia & Pacific: Deterioration of current account balances Current account balance (% of GDP) In 2012 Indonesia posted its first current account deficit since the Asian financial crisis. Private savings are under pressure from lower 20 commodity prices, and public savings are suffering from slow revenue growth and high subsidy spending despite recent reductions. Thai- 15 land’s current account balance turned negative in 2012, and savings Malaysia China rates have declined due to rising household leverage and fiscal sup- 10 port, driving private consumption higher. Malaysia’s current account Thailand surplus, in double digits since 2003, dropped to 6 percent of GDP in 5 2012. Public savings are also lower following stimulus packages imple- mented since the global financial crisis. China’s current account bal- 0 ance fell from a high of 10.1 percent of GDP in 2007 to 2.3 percent in Indonesia 2012 (World Bank 2013a). –5 2005 2006 2007 2008 2009 2010 2011 2012 Source: Online table 4.17. South Asia: Growth has slowed but is stabilizing Annual GDP growth (%) South Asian economies managed the financial and economic crisis reason- ably well. But real GDP growth has moderated and remains far below 25 pre-crisis levels. Regional growth slowed from 6.3 percent in 2011 to 4.9  percent in 2012, driven mainly by the slowdown in India, which 20 accounts for about 80 percent of the region’s GDP. India’s real GDP growth Afghanistan for 2012 was 4.7 percent, down from 6.6 percent in 2011. In Bangladesh, 15 with slower export and investment growth, GDP growth was 6.2 percent South Asia in 2012, down from 6.7 percent in 2011. Sri Lanka, facing prudent mac- India 10 roeconomic policies and dampened demand in its main export markets, recorded 6.4 percent growth in 2012, down from 8.2 percent in 2011. In 5 Afghanistan, the regional outlier, real GDP growth for 2012 is estimated Sri Lanka Bangladesh at 14.4 percent, up from 6.1 percent in 2011. Bhutan, Nepal, and Paki- Pakistan 0 stan recorded higher growth rates in 2012 than in 2011, but GDP growth 2005 2006 2007 2008 2009 2010 2011 2012 in the Maldives in 2011 was half that in 2011 (World Bank 2013b). Source: Online table 4.1. Middle East and North Africa: Diverging trends in adjusted net savings Adjusted net savings (% of GNI) Adjusted net savings measure the real difference between national income and consumption—in other words, the change in a country’s 30 real wealth. It takes into account investment in human capital, depre- Algeria ciation of fixed capital, depletion of natural resources, and damage 20 caused by pollution. Savings rates below zero suggest declining wealth Morocco and, as a result, unsustainable development. Higher savings lay the Jordan basis for building wealth and future growth. Recent trends in the Middle 10 Egypt, Arab Rep. East and North Africa show diverging pathways. Adjusted net savings are positive and high for Algeria and Morocco but below zero for Jordan, Lebanon, and Tunisia. The central negative factor affecting saving 0 rates is depletion of energy resources, which reached 25 percent of Lebanon Tunisia gross national income in Middle East and North African countries in –10 2008 before falling back to around 13 percent in 2012. 2005 2006 2007 2008 2009 2010 2011 2012 Source: Online table 4.11. 58 World Development Indicators 2014 Front ? User guide World view People Environment Sub-Saharan Africa: More than 10 years of steady growth Sub- Saharan Africa averaged GDP growth of 5.5  percent a year Annual GDP growth (%) between 1999 and 2010 (6.5 percent excluding South Africa), nearly 15 1 percentage point higher than the rest of the developing world (exclud- China ing China). In 2012, 5 of the world’s 10 fastest growing economies Sub-Saharan Africa (excluding South Africa) were in Sub- Saharan Africa: Sierra Leone, Niger, Liberia, Burkina Faso, and Côte d’Ivoire. But growth varied widely—from a severe contrac- 10 tion in South Sudan and Sudan to over 10 percent growth in Liberia, Niger, and Sierra Leone, thanks largely to new mineral production. Sub-Saharan Africa (all income levels) Many countries have seen high growth for several years, with about 5 a third growing 6  percent or more annually (World Bank 2013c). Rest of the developing world (excluding China) 0 1999 2002 2004 2006 2008 2010 2012 Source: Online table 4.1. Latin America and the Caribbean: Growth present but slowing Latin America and the Caribbean was the third slowest growing Annual GDP growth (%) region in 2012, ahead of Europe and Central Asia and the Middle 10 East Asia & Pacific East and North Africa. Growth decelerated, part of a 3 percentage (developing countries only) point decline from 2010 peaks across all developing countries. In much of the Caribbean growth was constrained by higher debt and South Asia lower tourism activity. Weak external conditions and contractions in 5 domestic demand were largely responsible for causing the region’s GDP growth to fall from 6 percent in 2010 to an estimated 3 per- Sub-Saharan Africa (all income levels) Middle East & North Africa cent in 2012. The drop was pronounced in the region’s largest econo- (developing countries only) 0 mies, Brazil and Argentina, but other countries continued to grow, Latin America & Caribbean (developing countries only) in most cases with robust domestic demand helping offset some of the slowdown in exports (De la Torre, Yeyati, and Pienknagura 2013). Europe & Central Asia (developing countries only) –5 2008 2009 2010 2011 2012 Source: Online table 4.1. Europe and Central Asia: Multispeed recovery Europe and Central Asia saw economic growth fall sharply, from Annual GDP growth (%) 6.3 percent in 2011 to 1.8 percent in 2012 because of poor harvests, 10 higher inflation, weak external demand, and European banks’ shrinking balance sheets. The slowdown was severe in Eastern Europe, where GDP grew less than 1 percent (and declined in Serbia). The adjustment in the Commonwealth of Independent States was less severe, but they 0 grew more slowly in 2012 than in 2011. Many developing countries have yet to recover from the 2008 crisis. The recovery of the 11 EU member states that joined after 2004 stalled in 2012, as domestic demand –10 fell and the external environment weakened, leaving net exports as Latvia Romania the sole driver of growth. That group’s GDP growth of 0.6 percent in Estonia Czech Republic Lithuania Hungary Poland Croatia 2012 was a fifth that of the year before, and Bosnia and Herzegov- Slovak Republic Slovenia Bulgaria ina, the Czech Republic, Hungary, the Kyrgyz Republic, and Moldova –20 2009 2010 2011 2012 joined Croatia and Slovenia in a recession (World Bank 2013d,e,f). Source: Online table 4.1. Economy States and markets Global links Back World Development Indicators 2014 59 4 Economy Gross domestic product Gross Adjusted Current Central Central Consumer Broad savings net savings account government government price index money balance cash surplus debt or deficit average annual % growth Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2000–12 2012–13 2013–14 2012 2012 2012 2012 2012 2012 2012 Afghanistan 9.4 3.1 3.5 –14.9 .. –35.5 –0.6 .. 7.2 31.9 Albania 5.0 1.3 2.1 14.5 –1.3 –10.4 –3.4 56.6 2.0 82.1 Algeria 3.7 2.8 3.3 47.5 28.3 6.0 –0.3 .. 8.9 61.0 American Samoa .. .. .. .. .. .. .. .. .. .. Andorra 5.9 .. .. .. .. .. .. .. .. .. Angola 11.8 5.1 8.0 18.0 –25.2 12.1 .. .. 10.3 34.9 Antigua and Barbuda 2.2 .. .. 24.9 .. –6.9 –1.4 .. 3.4 102.6 Argentina 5.8a 5.0 2.8 21.9 10.1 0.0 .. .. 10.0a 33.0 Armenia 7.6 3.2 5.0 11.7 –3.7 –11.1 –1.4 .. 2.6 33.7 Aruba –0.1 .. .. .. .. –9.5 .. .. 0.6 68.3 Australia 3.1 .. .. 25.5 12.0 –3.7 –3.7 30.6 1.8 102.8 Austriab 1.7 .. .. 24.6 13.1 1.6 –2.2 75.3 2.5 .. Azerbaijan 14.8 4.9 5.3 41.9 15.9 22.5 6.1 6.4 1.1 31.1 Bahamas, The 0.6 .. .. 8.4 .. –18.4 –4.1 47.9 2.0 76.6 Bahrain 5.4 .. .. 19.5 –0.8 9.7 –0.5 35.6 2.8 74.1 Bangladesh 6.0 6.0 5.7 39.8 21.3 2.3 –0.9 .. 6.2 69.7 Barbados 1.2 .. .. 8.4 3.6 –4.9 –8.0 96.8 4.5 .. Belarus 7.5 1.0 1.5 31.5 19.7 –2.7 1.7 40.8 59.2 30.5 Belgiumb 1.4 .. .. 20.3 7.9 –2.0 –3.6 91.1 2.8 .. Belize 3.8 1.8 2.7 15.8 9.3 –1.3 –0.2 74.2 1.3 77.4 Benin 3.8 4.2 4.1 7.1 –5.2 –7.1 –1.4 .. 6.8 37.9 Bermuda 0.9 .. .. .. .. 14.1 .. .. .. .. Bhutan 8.7 7.6 8.1 44.5 23.7 –19.7 .. .. 10.9 61.2 Bolivia 4.2 5.3 4.7 25.7 5.5 7.9 .. .. 4.6 73.8 Bosnia and Herzegovina 3.8 0.8 2.0 14.5 .. –9.3 –1.2 .. 2.0 58.1 Botswana 4.2 4.6 4.9 40.7 33.2 –7.4 –1.9 .. 7.5 44.2 Brazil 3.7 2.2 2.4 14.8 4.3 –2.4 –2.6 52.8 5.4 80.8 Brunei Darussalam 1.2 .. .. .. .. .. .. .. 0.5 65.9 Bulgaria 4.0 0.6 1.7 21.7 10.9 –1.4 –2.0 15.4 3.0 79.6 Burkina Faso 5.9 7.0 7.0 22.9 8.5 –2.0 –3.2 .. 3.8 30.3 Burundi 3.6 4.3 4.5 17.5 –13.7 –10.3 .. .. 18.0 23.0 Cabo Verde 6.7 2.6 2.9 35.0 .. –11.5 –9.0 .. 2.5 78.7 Cambodia 8.1 7.0 7.0 10.6 –7.5 –8.6 –4.4 .. 2.9 50.1 Cameroon 3.3 4.8 5.0 15.8 –1.6 –3.8 .. .. 2.9 21.2 Canada 1.9 .. .. 23.6 13.0 –3.5 –1.3 53.8 1.5 .. Cayman Islands .. .. .. .. .. .. .. .. .. .. Central African Republic 4.8 –18.0 –1.8 .. .. .. 0.7 .. 5.8 18.1 Chad 9.6 5.0 8.7 .. .. .. .. .. 10.2 11.9 Channel Islands 0.5 .. .. .. .. .. .. .. .. .. Chile 4.1 .. .. 21.4 –0.2 –3.5 1.3 .. 3.0 77.3 China 10.6 7.7 7.7 51.2 35.0 2.3 .. .. 2.7 187.6 Hong Kong SAR, China 4.4 .. .. 28.3 .. 2.3 3.8 39.2 4.1 335.3 Macao SAR, China 12.7 .. .. 57.4 .. 42.9 23.8 .. 6.1 107.6 Colombia 4.5 4.0 4.3 18.9 –3.2 –3.3 –1.1 62.6 3.2 42.9 Comoros 1.9 3.3 3.5 .. .. .. .. .. 1.8 38.3 Congo, Dem. Rep. 5.7 7.5 7.5 .. .. .. 3.8 .. 85.1 18.3 Congo, Rep. 4.6 5.6 5.4 .. .. .. .. .. 3.9 31.5 60 World Development Indicators 2014 Front ? User guide World view People Environment Economy 4 Gross domestic product Gross Adjusted Current Central Central Consumer Broad savings net savings account government government price index money balance cash surplus debt or deficit average annual % growth Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2000–12 2012–13 2013–14 2012 2012 2012 2012 2012 2012 2012 Costa Rica 4.7 3.4 4.3 15.9 15.1 –5.3 –3.5 .. 4.5 49.4 Côte d’Ivoire 1.2 8.7 8.2 .. .. 2.0 –3.1 .. 1.3 39.0 Croatia 2.1 .. .. 18.9 9.3 –0.3 –4.7 .. 3.4 80.7 Cuba 5.8 .. .. .. .. .. .. .. .. .. Curaçao .. .. .. .. .. .. .. .. .. .. Cyprusb 2.6c .. .. 8.8c 3.9c –6.9 –6.3 113.3 2.4 .. Czech Republic 3.3 .. .. 21.0 5.1 –2.4 –4.4 38.3 3.3 77.3 Denmark 0.6 .. .. 23.6 15.7 5.9 –2.0 50.6 2.4 74.6 Djibouti 3.5 .. .. .. .. .. .. .. 3.7 .. Dominica 3.2 1.1 1.7 10.8 .. –11.5 –11.9 .. 1.4 97.4 Dominican Republic 5.6 2.5 3.9 9.2 .. –6.8 –2.9 .. 3.7 34.3 Ecuador 4.4 4.0 4.1 26.9 6.1 –0.2 .. .. 5.1 31.6 Egypt, Arab Rep. 4.9 1.8 2.3 13.0 0.0 –2.7 –10.6 .. 7.1 74.1 El Salvador 2.0 1.9 2.3 8.9 6.6 –5.3 –2.2 47.8 1.7 44.6 Equatorial Guinea 10.9 .. .. .. .. .. .. .. 6.1 18.7 Eritrea 0.9 6.0 3.5 .. .. .. .. .. .. 114.7 Estoniab 3.7 .. .. 25.0 12.5 –1.8 1.0 6.9 3.9 59.6 Ethiopia 8.9 7.0 7.2 28.8 6.1 –7.2 –1.4 .. 22.8 .. Faeroe Islands .. .. .. .. .. .. .. .. .. .. Fiji 1.2 2.4 2.1 .. .. –1.4 .. .. 3.4 68.8 Finlandb 1.7 .. .. 18.1 7.6 –1.5 –0.5 48.0 2.8 .. Franceb 1.1 .. .. 17.5 9.9 –2.2 –5.1 93.7 2.0 .. French Polynesia .. .. .. .. .. .. .. .. .. .. Gabon 2.4 4.2 4.2 .. .. .. .. .. 2.7 20.8 Gambia, The 3.4 6.5 7.5 17.1 0.9 6.4 .. .. 4.3 53.6 Georgia 6.5d 2.5d 6.3d 18.3d 7.0 d –11.7 –0.5 32.6 –0.9 30.2 Germany b 1.1 .. .. 24.2 15.8 7.0 –0.4 55.3 2.0 .. Ghana 6.6 7.4 7.4 21.5 2.7 –11.7 –3.9 .. 9.2 31.3 Greeceb 1.1 .. .. 9.8 –4.3 –2.5 –9.8 106.5 1.5 .. Greenland 1.7 .. .. .. .. .. .. .. .. .. Grenada 1.9 1.1 1.1 –10.2 .. –28.0 –5.8 .. 2.4 95.4 Guam .. .. .. .. .. .. .. .. .. .. Guatemala 3.5 3.3 3.4 12.0 –2.3 –2.6 –2.3 24.4 3.8 46.2 Guinea 2.6 4.0 4.7 –6.2 –42.8 –18.4 .. .. 15.2 36.4 Guinea-Bissau 2.3 3.0 2.7 1.5 –22.4 –8.5 .. .. 2.1 38.8 Guyana 1.7 4.4 3.9 11.1 –11.8 –13.9 .. .. 2.4 67.0 Haiti 0.8 3.4 4.2 25.6 12.7 –4.4 .. .. 6.3 45.8 Honduras 4.3 2.9 3.4 16.5 11.4 –8.6 –3.2 .. 5.2 51.0 Hungary 1.6 0.7 1.7 23.4 12.4 0.9 3.7 82.4 5.7 60.9 Iceland 2.4 .. .. 9.3 .. –5.5 –5.3 119.1 5.2 89.8 India 7.7 4.8 6.2 30.3 14.8 –4.9 –3.8 49.7 9.3 75.6 Indonesia 5.5 5.6 5.3 32.0 24.1 –2.7 –1.1 26.2 4.3 40.1 Iran, Islamic Rep. 4.8 –1.5 1.0 .. .. .. .. .. 27.3 19.7 Iraq 5.1 4.2 6.5 26.7 .. 13.7 .. .. 5.8 30.7 Irelandb 2.2 .. .. 16.0 10.9 4.4 –13.0 102.0 1.7 .. Isle of Man 6.2 .. .. .. .. .. .. .. .. .. Israel 3.7 .. .. 14.8 6.0 1.3 –5.4 .. 1.7 .. Economy States and markets Global links Back World Development Indicators 2014 61 4 Economy Gross domestic product Gross Adjusted Current Central Central Consumer Broad savings net savings account government government price index money balance cash surplus debt or deficit average annual % growth Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2000–12 2012–13 2013–14 2012 2012 2012 2012 2012 2012 2012 Italy b 0.2 .. .. 17.4 3.3 –0.4 –3.5 110.8 3.0 .. Jamaica .. .. .. 8.3 3.5 –12.9 –4.2 .. 6.9 47.1 Japan 0.7 .. .. 21.5 1.5 1.0 –8.3 189.8 0.0 241.2 Jordan 6.2 3.0 3.1 8.5 –0.7 –18.4 –8.3 66.8 4.8 118.4 Kazakhstan 7.7 6.0 5.8 26.2 –8.0 3.8 7.7 9.9 5.1 34.7 Kenya 4.4 5.0 5.1 9.4 4.7 –10.4 –4.8 .. 9.4 50.6 Kiribati 1.4 1.8 1.8 .. .. .. –7.2 .. .. .. Korea, Dem. People’s Rep. .. .. .. .. .. .. .. .. .. .. Korea, Rep. 4.0 .. .. 30.9 18.1 3.8 1.8 .. 2.2 144.3 Kosovo 5.2 .. .. 18.3 .. –7.5 .. .. 2.5 40.6 Kuwait 5.1 .. .. 59.5 11.2 43.2 27.9 .. 2.8 57.6 Kyrgyz Republic 4.2 7.8 6.5 29.6 12.1 –22.1 –6.6 .. 2.7 .. Lao PDR 7.4 8.0 7.7 15.7 –11.6 –4.4 –0.8 .. 4.3 35.9 Latvia 3.6 .. .. 25.7 11.0 –2.5 –2.8 42.1 2.3 44.1 Lebanon 5.0 0.7 2.0 13.6 –2.2 –3.9 –8.8 .. 4.0 241.7 Lesotho 4.1 4.6 5.1 18.1 11.5 –24.0 .. .. 6.1 35.6 Liberia 6.6 7.9 7.5 31.4 –6.0 –49.1 –2.6 32.7 6.8 34.9 Libya 5.4 –6.0 23.0 .. .. .. .. .. 6.1 .. Liechtenstein 2.5 .. .. .. .. .. .. .. .. .. Lithuania 4.3 .. .. 17.1 9.1 –0.2 –5.1 43.5 3.1 47.4 Luxembourgb 2.5 .. .. 16.4 8.3 6.5 –0.4 17.2 2.7 .. Macedonia, FYR 3.2 2.5 3.0 25.5 6.0 –3.1 –4.0 .. 3.3 58.3 Madagascar 3.0 4.1 4.8 .. .. .. –1.7 .. 6.4 24.4 Malawi 3.7 4.4 4.8 12.5 –2.7 –18.8 .. .. 21.3 36.4 Malaysia 4.9 4.5 4.8 31.9 16.1 6.1 –4.5 53.3 1.7 141.2 Maldives 7.2 4.3 4.2 .. .. –27.0 –8.8 73.8 13.1 58.6 Mali 5.2 4.0 5.2 8.5 –10.8 –12.6 –2.5 .. 5.4 32.3 Maltab 1.8 .. .. 11.7 .. 2.1 –2.7 84.0 2.4 .. Marshall Islands 1.4 5.0 5.0 .. .. .. .. .. .. .. Mauritania 5.6 5.7 4.6 .. .. .. .. .. 4.9 33.3 Mauritius 3.9 3.7 4.1 15.1 4.5 –11.2 –1.1 36.4 3.9 100.5 Mexico 2.2 1.4 3.4 21.5 5.8 –1.2 .. .. 4.1 32.0 Micronesia, Fed. Sts. 0.0 1.4 1.4 .. .. .. .. .. .. 41.3 Moldova 4.8e 4.2e 3.8e 12.8e 6.2e –6.8 –1.8 23.7 4.7 56.4 Monaco 4.2 .. .. .. .. .. .. .. .. .. Mongolia 7.7 12.5 10.3 33.3 13.8 –32.7 –8.5 .. 15.0 54.6 Montenegro 4.0 1.8 2.5 –0.2 .. –17.6 .. .. 3.2 50.5 Morocco 4.8f 4.5f 3.6f 25.8f 14.7f –10.0 –4.2 56.8 1.3 113.9 Mozambique 7.5 7.0 8.5 12.4 0.4 –44.2 –2.8 .. 2.1 46.0 Myanmar .. .. .. .. .. .. .. .. 1.5 .. Namibia 4.8 4.2 4.3 18.2 12.0 –1.2 .. .. 6.5 57.1 Nepal 4.0 3.6 3.8 40.8 30.0 3.0 –0.6 33.9 9.5 77.5 Netherlandsb 1.3 .. .. 24.8 16.9 9.4 –3.9 66.4 2.4 .. New Caledonia .. .. .. .. .. .. .. .. .. .. New Zealand 2.3 .. .. 14.6 8.0 –4.1 –7.2 62.5 0.9 94.7 Nicaragua 3.4 3.8 4.2 17.3 3.7 –13.0 0.5 .. 7.2 33.6 Niger 4.5 5.6 6.2 20.1 10.0 –19.9 .. .. 0.5 23.1 62 World Development Indicators 2014 Front ? User guide World view People Environment Economy 4 Gross domestic product Gross Adjusted Current Central Central Consumer Broad savings net savings account government government price index money balance cash surplus debt or deficit average annual % growth Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2000–12 2012–13 2013–14 2012 2012 2012 2012 2012 2012 2012 Nigeria 6.8 6.7 6.7 40.6 8.2 7.8 .. .. 12.2 36.5 Northern Mariana Islands .. .. .. .. .. .. .. .. .. .. Norway 1.5 .. .. 39.1 21.7 14.5 14.6 20.9 0.7 .. Oman 5.0 .. .. .. .. 10.6 10.6 5.0 2.9 36.3 Pakistan 4.4 6.1 3.4 20.3 3.7 –0.9 –8.0 .. 9.7 39.9 Palau –0.1 5.8 5.8 .. .. .. .. .. .. .. Panama 7.5 7.9 7.3 26.7 23.3 –9.0 .. .. 5.7 80.6 Papua New Guinea 4.7 4.0 8.5 .. .. –6.7 .. .. 2.2 52.0 Paraguay 3.7 14.1 4.6 12.4 6.1 0.5 1.6 .. 3.7 44.6 Peru 6.3 4.9 5.5 25.4 7.7 –3.4 1.2 19.1 3.7 36.8 Philippines 4.9 6.9 6.5 23.9 9.4 2.8 –1.9 51.5 3.2 58.9 Poland 4.2 .. .. 17.5 7.9 –3.7 –4.3 .. 3.6 57.9 Portugalb 0.4 .. .. 15.9 8.7 –2.1 –4.0 92.5 2.8 .. Puerto Rico –0.4 .. .. .. .. .. .. .. .. .. Qatar 14.0 .. .. 66.2 46.1 32.0 2.9 .. 1.9 54.4 Romania 4.2 2.5 2.5 22.2 7.0 –4.4 –5.1 .. 3.3 37.8 Russian Federation 4.8 .. .. 29.6 15.3 3.6 3.3 9.3 5.1 51.5 Rwanda 7.9 7.0 7.5 11.5 –3.7 –11.6 –0.9 .. 6.3 .. Samoa 2.4 2.1 2.1 .. .. –5.2 0.0 .. 2.0 44.6 San Marino 3.2 .. .. .. .. .. .. .. 2.8 .. São Tomé and Príncipe 4.5 5.5 4.9 .. .. –37.8 –12.6 .. 10.4 36.9 Saudi Arabia 6.1 .. .. 50.5 10.0 23.2 .. .. 2.9 54.1 Senegal 4.0 4.0 4.5 21.8 15.9 –7.9 –6.2 .. 1.4 40.4 Serbia 3.3 2.0 1.0 18.0 .. –10.7 –4.5 .. 7.3 49.8 Seychelles 3.1 3.5 3.9 .. .. –24.7 4.8 73.3 7.1 48.0 Sierra Leone 6.9 17.0 14.1 10.2 –22.7 –29.0 –5.2 .. 12.9 20.5 Singapore 5.9 .. .. 45.6 31.9 18.7 9.0 115.1 4.5 137.6 Sint Maarten .. .. .. .. .. .. .. .. .. .. Slovak Republicb 4.8 .. .. 22.0 6.1 2.2 –4.9 45.6 3.6 .. Sloveniab 2.5 .. .. 21.4 9.5 3.3 –5.9 .. 2.6 .. Solomon Islands 5.1 4.0 3.5 .. .. 0.2 .. .. 7.3 41.3 Somalia .. .. .. .. .. .. .. .. .. .. South Africa 3.6 1.9 2.7 13.2 0.4 –5.2 –4.4 .. 5.4 75.2 South Sudan .. 33.9 17.0 .. .. .. .. .. 47.3 .. Spainb 1.7 .. .. 18.9 5.9 –1.1 –3.6 56.1 2.4 .. Sri Lanka 5.9 7.0 7.4 24.1 19.7 –6.7 –6.1 79.1 7.5 38.6 St. Kitts and Nevis 2.4 .. .. 18.3 .. –9.2 10.7 .. 1.4 140.7 St. Lucia 2.7 0.7 1.5 13.0 4.5 –14.9 –6.8 .. 4.2 95.8 St. Martin .. .. .. .. .. .. .. .. .. .. St. Vincent & the Grenadines 2.8 2.1 2.7 –6.7 .. –30.3 –2.0 .. 2.6 68.6 Sudan 5.2g 2.9h 2.9h 9.9h –6.7h –10.8 .. .. 37.4 27.9h Suriname 4.9 3.9 4.1 .. .. 4.7 –0.7 .. 5.0 49.1 Swaziland 2.2 0.0 0.0 7.7 1.4 4.1 .. .. 8.9 31.4 Sweden 2.2 .. .. 25.4 17.8 6.1 –0.4 36.6 0.9 85.2 Switzerland 1.9 .. .. 32.8 18.9 8.5 0.6 26.7 –0.7 188.0 Syrian Arab Republic 5.0 –22.5 –8.6 16.8 .. .. .. .. 36.7 73.9 Tajikistan 7.8 7.0 6.0 17.9 9.0 –3.2 .. .. 5.8 15.5 Economy States and markets Global links Back World Development Indicators 2014 63 4 Economy Gross domestic product Gross Adjusted Current Central Central Consumer Broad savings net savings account government government price index money balance cash surplus debt or deficit average annual % growth Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2000–12 2012–13 2013–14 2012 2012 2012 2012 2012 2012 2012 Tanzaniai 7.0 7.1 7.4 23.5 8.7 –12.9 –7.2 .. 16.0 32.8 Thailand 4.1 3.2 4.5 30.2 16.7 –0.4 –1.2 30.2 3.0 131.1 Timor-Leste 5.8 .. .. 326.7 .. 211.9 .. .. 11.8 31.5 Togo 2.8 5.0 4.5 0.0 –21.3 –6.3 –6.3 .. 2.6 46.4 Tonga 1.1 1.2 1.2 5.9 .. –20.2 .. .. 1.2 40.5 Trinidad and Tobago 5.1 .. .. .. .. 12.3 –1.6 .. 9.3 62.0 Tunisia 4.2 2.6 2.5 14.5 –3.1 –8.3 –5.0 44.1 5.5 66.7 Turkey 4.6 4.3 3.5 14.5 3.4 –6.1 –1.1 47.2 8.9 55.4 Turkmenistan 9.0 10.1 10.7 .. .. .. .. .. .. .. Turks and Caicos Islands .. .. .. .. .. .. .. .. .. .. Tuvalu 1.3 1.0 1.0 .. .. .. .. .. .. .. Uganda 7.5 6.2 6.7 12.8 –11.2 –11.1 –3.9 42.7 14.0 24.2 Ukraine 3.8 –1.1 2.0 9.3 –3.7 –8.4 –2.3 27.4 0.6 54.9 United Arab Emirates 4.2 .. .. .. .. .. 0.1 .. 0.9 61.2 United Kingdom 1.5 .. .. 10.9 3.0 –3.7 –7.6 99.8 2.8 161.6 United States 1.7 .. .. 16.5 7.3 –2.7 –7.5 93.8 2.1 87.4 Uruguay 4.2 .. .. 15.0 1.6 –5.3 –2.1 44.6 8.1 43.6 Uzbekistan 7.4 7.4 7.0 .. .. .. .. .. .. .. Vanuatu 3.8 1.7 2.2 19.3 .. –6.4 –2.3 .. 1.4 78.1 Venezuela, RB 4.3 0.7 0.5 25.6 6.8 2.9 .. .. 21.1 47.5 Vietnam 6.6 5.3 5.4 31.6 12.7 5.8 .. .. 9.1 106.5 Virgin Islands (U.S.) .. .. .. .. .. .. .. .. .. .. West Bank and Gaza .. .. .. .. .. .. .. .. .. .. Yemen, Rep. 3.1 3.0 3.4 8.1 –10.8 –3.2 .. .. 17.3 34.6 Zambia 5.9 6.0 6.5 24.7 1.8 0.0 5.0 .. 6.6 24.2 Zimbabwe –4.1 2.2 3.3 .. .. .. .. .. .. .. World 2.7 w 2.4 w 3.2 w 21.6 w 11.3 w Low income 5.6 6.2 6.3 23.8 7.1 Middle income 6.3 4.9 5.6 30.9 18.6 Lower middle income 6.2 4.5 5.9 26.9 12.5 Upper middle income 6.3 5.0 5.5 32.2 20.2 Low & middle income 6.3 4.8 5.3 30.9 18.4 East Asia & Pacific 9.2 7.2 7.2 46.0 31.8 Europe & Central Asia 4.7 3.4 3.5 16.9 2.8 Latin America & Carib. 3.6 2.5 2.9 19.2 5.1 Middle East & N. Africa 4.6 –0.1 2.8 .. 5.3 South Asia 7.2 4.6 5.7 29.5 13.9 Sub-Saharan Africa 5.0 4.7 5.3 19.8 –0.4 High income 1.8 1.3 2.2 19.6 8.2 Euro area 1.1 –0.4 1.1 20.1 10.2 a. Data for Argentina are officially reported by the National Statistics and Censuses Institute of Argentina. The International Monetary Fund has, however, issued a declaration of censure and called on Argentina to adopt remedial measures to address the quality of official GDP and consumer price index data. Alternative data sources have shown significantly lower real growth and higher inflation than the official data since 2008. In this context, the World Bank is also using alternative data sources and estimates for the surveillance of macroeconomic developments in Argentina. b. As members of the European Monetary Union, these countries share a single currency, the euro. c. Refers to the area controlled by the government of Cyprus. d. Excludes Abkhazia and South Ossetia. e. Excludes Transnistria. f. Includes Former Spanish Sahara. g. Excludes South Sudan after July 9, 2011. h. Excludes South Sudan. i. Covers mainland Tanzania only. 64 World Development Indicators 2014 Front ? User guide World view People Environment Economy 4 About the data Economic data are organized by several different accounting con- edition are not comparable with those from earlier editions with ventions: the system of national accounts, the balance of pay- different base years. ments, government fi nance statistics, and international fi nance Rescaling may result in a discrepancy between the rescaled GDP statistics. There has been progress in unifying the concepts in the and the sum of the rescaled components. To avoid distortions in the system of national accounts, balance of payments, and government growth rates, the discrepancy is left unallocated. As a result, the fi nance statistics, but there are many national variations in the weighted average of the growth rates of the components generally implementation of these standards. For example, even though the does not equal the GDP growth rate. United Nations recommends using the 2008 System of National Accounts (2008 SNA) methodology in compiling national accounts, Adjusted net savings many are still using earlier versions, some as old as 1968. The Adjusted net savings measure the change in a country’s real wealth International Monetary Fund (IMF) has recently published a new after accounting for the depreciation and depletion of a full range of balance of payments methodology (BPM6), but many countries are assets in the economy. If a country’s adjusted net savings are posi- still using the previous version. Similarly, the standards and defini- tive and the accounting includes a sufficiently broad range of assets, tions for government finance statistics were updated in 2001, but economic theory suggests that the present value of social welfare is several countries still report using the 1986 version. For individual increasing. Conversely, persistently negative adjusted net savings country information about methodology used, refer to Primary data indicate that the present value of social welfare is decreasing, sug- documentation. gesting that an economy is on an unsustainable path. Adjusted net savings are derived from standard national account- Economic growth ing measures of gross savings by making four adjustments. First, An economy’s growth is measured by the change in the volume of its estimates of fi xed capital consumption of produced assets are output or in the real incomes of its residents. The 2008 SNA offers deducted to obtain net savings. Second, current public expendi- three plausible indicators for calculating growth: the volume of gross tures on education are added to net savings (in standard national domestic product (GDP), real gross domestic income, and real gross accounting these expenditures are treated as consumption). Third, national income. Only growth in GDP is reported here. estimates of the depletion of a variety of natural resources are Growth rates of GDP and its components are calculated using the deducted to reflect the decline in asset values associated with their least squares method and constant price data in the local currency extraction and harvest. And fourth, deductions are made for dam- for countries and using constant price U.S. dollar series for regional ages from carbon dioxide emissions and local pollution. By account- and income groups. Local currency series are converted to constant ing for the depletion of natural resources and the degradation of U.S. dollars using an exchange rate in the common reference year. the environment, adjusted net savings go beyond the definition of The growth rates are average annual and compound growth rates. savings or net savings in the SNA. Methods of computing growth are described in Statistical methods. Forecasts of growth rates come from World Bank (2014). Balance of payments The balance of payments records an economy’s transactions with Rebasing national accounts the rest of the world. Balance of payments accounts are divided Rebasing of national accounts can alter the measured growth rate of into two groups: the current account, which records transactions an economy and lead to breaks in series that affect the consistency in goods, services, primary income, and secondary income, and of data over time. When countries rebase their national accounts, the capital and financial account, which records capital transfers, they update the weights assigned to various components to better acquisition or disposal of nonproduced, nonfinancial assets, and reflect current patterns of production or uses of output. The new transactions in financial assets and liabilities. The current account base year should represent normal operation of the economy—it balance is one of the most analytically useful indicators of an exter- should be a year without major shocks or distortions. Some devel- nal imbalance. oping countries have not rebased their national accounts for many A primary purpose of the balance of payments accounts is to years. Using an old base year can be misleading because implicit indicate the need to adjust an external imbalance. Where to draw price and volume weights become progressively less relevant and the line for analytical purposes requires a judgment concerning the useful. imbalance that best indicates the need for adjustment. There are a To obtain comparable series of constant price data for comput- number of definitions in common use for this and related analytical ing aggregates, the World Bank rescales GDP and value added by purposes. The trade balance is the difference between exports and industrial origin to a common reference year. This year’s World Devel- imports of goods. From an analytical view it is arbitrary to distinguish opment Indicators switches the reference year to 2005. Because goods from services. For example, a unit of foreign exchange earned rescaling changes the implicit weights used in forming regional and by a freight company strengthens the balance of payments to the income group aggregates, aggregate growth rates in this year’s same extent as the foreign exchange earned by a goods exporter. Economy States and markets Global links Back World Development Indicators 2014 65 4 Economy Even so, the trade balance is useful because it is often the most encompasses currency held by the public and demand deposits with timely indicator of trends in the current account balance. Customs banks. M2 includes M1 plus time and savings deposits with banks authorities are typically able to provide data on trade in goods long that require prior notice for withdrawal. M3 includes M2 as well as before data on trade in services are available. various money market instruments, such as certificates of deposit Beginning in August 2012, the International Monetary Fund imple- issued by banks, bank deposits denominated in foreign currency, mented the Balance of Payments Manual 6 (BPM6) framework in its and deposits with financial institutions other than banks. However major statistical publications. The World Bank implemented BPM6 defined, money is a liability of the banking system, distinguished in its online databases and publications from April 2013. Balance from other bank liabilities by the special role it plays as a medium of payments data for 2005 onward will be presented in accord with of exchange, a unit of account, and a store of value. the BPM6. The historical BPM5 data series will end with data for A general and continuing increase in an economy’s price level is 2008, which can be accessed through the World Development Indi- called inflation. The increase in the average prices of goods and cators archives. services in the economy should be distinguished from a change The complete balance of payments methodology can be accessed in the relative prices of individual goods and services. Generally through the International Monetary Fund website (www.imf.org accompanying an overall increase in the price level is a change in /external/np/sta/bop/bop.htm). the structure of relative prices, but it is only the average increase, not the relative price changes, that constitutes inflation. A commonly Government finance used measure of inflation is the consumer price index, which mea- Central government cash surplus or deficit, a summary measure of sures the prices of a representative basket of goods and services the ongoing sustainability of government operations, is comparable purchased by a typical household. The consumer price index is usu- to the national accounting concept of savings plus net capital trans- ally calculated on the basis of periodic surveys of consumer prices. fers receivable, or net operating balance in the 2001 update of the Other price indices are derived implicitly from indexes of current and IMF’s Government Finance Statistics Manual. constant price series. The 2001 manual, harmonized with the 1993 SNA, recommends Consumer price indexes are produced more frequently and so an accrual accounting method, focusing on all economic events are more current. They are constructed explicitly, using surveys affecting assets, liabilities, revenues, and expenses, not just those of the cost of a defined basket of consumer goods and services. represented by cash transactions. It accounts for all changes in Nevertheless, consumer price indexes should be interpreted with stocks, so stock data at the end of an accounting period equal stock caution. The definition of a household, the basket of goods, and the data at the beginning of the period plus flows over the period. The geographic (urban or rural) and income group coverage of consumer 1986 manual considered only debt stocks. price surveys can vary widely by country. In addition, weights are For most countries central government finance data have been derived from household expenditure surveys, which, for budgetary consolidated into one account, but for others only budgetary central reasons, tend to be conducted infrequently in developing countries, government accounts are available. Countries reporting budgetary impairing comparability over time. Although useful for measuring data are noted in Primary data documentation. Because budgetary consumer price inflation within a country, consumer price indexes accounts may not include all central government units (such as are of less value in comparing countries. social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incom- Definitions plete view of total public finance. • Gross domestic product (GDP) at purchaser prices is the sum of Data on government revenue and expense are collected by the IMF gross value added by all resident producers in the economy plus any through questionnaires to member countries and by the Organisa- product taxes (less subsidies) not included in the valuation of out- tion for Economic Co-operation and Development (OECD). Despite put. It is calculated without deducting for depreciation of fabricated IMF efforts to standardize data collection, statistics are often incom- capital assets or for depletion and degradation of natural resources. plete, untimely, and not comparable across countries. Value added is the net output of an industry after adding up all out- Government finance statistics are reported in local currency. The puts and subtracting intermediate inputs. • Gross savings are the indicators here are shown as percentages of GDP. Many countries difference between gross national income and public and private report government finance data by fiscal year; see Primary data consumption, plus net current transfers. • Adjusted net savings documentation for information on fiscal year end by country. measure the change in value of a specified set of assets, excluding capital gains. Adjusted net savings are net savings plus education Financial accounts expenditure minus energy depletion, mineral depletion, net forest Money and the financial accounts that record the supply of money depletion, and carbon dioxide and particulate emissions damage. lie at the heart of a country’s financial system. There are several • Current account balance is the sum of net exports of goods and commonly used definitions of the money supply. The narrowest, M1, services, net primary income, and net secondary income. • Central 66 World Development Indicators 2014 Front ? User guide World view People Environment Economy 4 government cash surplus or deficit is revenue (including grants) current account balance are from the IMF’s Balance of Payments minus expense, minus net acquisition of nonfinancial assets. In Statistics Yearbook and International Financial Statistics. Data on editions before 2005 nonfinancial assets were included under rev- central government finances are from the IMF’s Government Finance enue and expenditure in gross terms. This cash surplus or deficit is Statistics database. Data on the consumer price index are from the close to the earlier overall budget balance (still missing is lending IMF’s International Financial Statistics. Data on broad money are minus repayments, which are included as a financing item under net from the IMF’s monthly International Financial Statistics and annual acquisition of financial assets). • Central government debt is the International Financial Statistics Yearbook. entire stock of direct government fixed-term contractual obligations to others outstanding on a particular date. It includes domestic and References foreign liabilities such as currency and money deposits, securities Asian Development Bank. 2012. Asian Development Outlook 2012 other than shares, and loans. It is the gross amount of government Update: Services and Asia’s Future Growth. Manila. liabilities reduced by the amount of equity and financial derivatives De la Torre, Augusto, Eduardo Levy Yeyati, Samuel Pienknagura. 2013. held by the government. Because debt is a stock rather than a flow, Latin America’s Deceleration and the Exchange Rate Buffer. Semian- it is measured as of a given date, usually the last day of the fiscal nual Report, Office of the Chief Economist. Washington, DC: World year. • Consumer price index reflects changes in the cost to the Bank. average consumer of acquiring a basket of goods and services that Fankhauser, Samuel. 1994. “The Social Costs of Greenhouse Gas Emis- may be fixed or may change at specified intervals, such as yearly. sions: An Expected Value Approach.” Energy Journal 15 (2): 157–84. The Laspeyres formula is generally used. • Broad money (IFS line Hamilton, Kirk, and Michael Clemens. 1999. “Genuine Savings 35L..ZK) is the sum of currency outside banks; demand deposits Rates in Developing Countries.” World Bank Economic Review 13 other than those of the central government; the time, savings, and (2): 333–56. foreign currency deposits of resident sectors other than the central IMF (International Monetary Fund). 2001. Government Finance Statis- government; bank and traveler’s checks; and other securities such tics Manual. Washington, DC. as certificates of deposit and commercial paper. International Energy Agency. 2013. IEA CO2 Emissions from Fuel Combustion Statistics database. [http://dx.doi.org/10.1787 Data sources /data-00430-en]. Paris. Data on GDP for most countries are collected from national statisti- Pandey, Kiran D., Katharine Bolt, Uwe Deichmann, Kirk Hamilton, Bart cal organizations and central banks by visiting and resident World Ostro, and David Wheeler. 2006. “The Human Cost of Air Pollution: Bank missions; data for selected high-income economies are from New Estimates for Developing Countries.” World Bank, Development the OECD. Estimates of GDP growth for 2012–13 and projections Research Group and Environment Department, Washington, DC. for 2013–14 are from the World Bank’s Global Economic Prospects United Nations Statistics Division. Various years. National Accounts database. Data on gross savings are from World Bank national Statistics: Main Aggregates and Detailed Tables. Parts 1 and 2. New accounts data files. Data on adjusted net savings are based on York: United Nations. a conceptual underpinning by Hamilton and Clemens (1999) and World Bank. 2011. The Changing Wealth of Nations: Measuring Sustain- calculated using data on consumption of fi xed capital from the able Development for the New Millennium. Washington, DC. United Nations Statistics Division’s National Accounts Statistics: ———. 2013a. East Asia and Pacific Economic Update 2013: Rebuild- Main Aggregates and Detailed Tables, extrapolated to 2010; data ing Policy Buffers, Reinvigorating Growth. Washington, DC. on education expenditure from the United Nations Educational, ———. 2013b. South Asia Economic Focus—Regaining Momentum. Scientific, and Cultural Organization Institute for Statistics online Washington, DC. database, with missing data estimated by World Bank staff; data ———. 2013c. Africa’s Pulse: An Analysis of Issues Shaping Africa’s on forest, energy, and mineral depletion based on sources and Economic Future. Volume 8, October. Washington, DC. methods in World Bank (2011); estimates of damages from carbon ———. 2013d. EU11 Regular Economic Report. Issue 26, January. dioxide emissions following the method of Fankhauser (1994) and Washington, DC. using emissions data published by the International Energy Agency ———. 2013e. EU11 Regular Economic Report. Issue 27, June. (2013); and predicted concentrations of local air pollution following Washington, DC. the method of Pandey and others (2006) and using monitoring data ———. 2013f. Global Economic Prospects, Volume 7, June 13: Assur- for air quality available online in the World Health Organization’s ing Growth over the Medium Term. Washington, DC. Global Health Observatory database, the Clean Air Asia’s Cities- ———. 2014. Global Economic Prospects: Coping with Policy Normaliza- ACT database, the European Environment Agency’s database, and tion in High-income Countries. Volume 8, January 14. Washington, DC. the database of the U.S. Environmental Protection Agency. Data on ———. Various years. World Development Indicators. Washington, DC. Economy States and markets Global links Back World Development Indicators 2014 67 4 Economy Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/4.1). To view a specific /indicator/NY.GDP.MKTP.KD.ZG). 4.1 Growth of output 4.7 Structure of service imports Gross domestic product NY.GDP.MKTP.KD.ZG Commercial service imports TM.VAL.SERV.CD.WT Agriculture NV.AGR.TOTL.KD.ZG Transport TM.VAL.TRAN.ZS.WT Industry NV.IND.TOTL.KD.ZG Travel TM.VAL.TRVL.ZS.WT Manufacturing NV.IND.MANF.KD.ZG Insurance and financial services TM.VAL.INSF.ZS.WT Services NV.SRV.TETC.KD.ZG Computer, information, communications, and other commercial services TM.VAL.OTHR.ZS.WT 4.2 Structure of output Gross domestic product NY.GDP.MKTP.CD 4.8 Structure of demand Agriculture NV.AGR.TOTL.ZS Household final consumption expenditure NE.CON.PETC.ZS Industry NV.IND.TOTL.ZS General government final consumption expenditure NE.CON.GOVT.ZS Manufacturing NV.IND.MANF.ZS Gross capital formation NE.GDI.TOTL.ZS Services NV.SRV.TETC.ZS Exports of goods and services NE.EXP.GNFS.ZS 4.3 Structure of manufacturing Imports of goods and services NE.IMP.GNFS.ZS Manufacturing value added NV.IND.MANF.CD Gross savings NY.GNS.ICTR.ZS Food, beverages and tobacco NV.MNF.FBTO.ZS.UN 4.9 Growth of consumption and investment Textiles and clothing NV.MNF.TXTL.ZS.UN Household final consumption expenditure NE.CON.PRVT.KD.ZG Machinery and transport equipment NV.MNF.MTRN.ZS.UN Household final consumption expenditure, Chemicals NV.MNF.CHEM.ZS.UN Per capita NE.CON.PRVT.PC.KD.ZG Other manufacturing NV.MNF.OTHR.ZS.UN General government final consumption expenditure NE.CON.GOVT.KD.ZG 4.4 Structure of merchandise exports Gross capital formation NE.GDI.TOTL.KD.ZG Merchandise exports TX.VAL.MRCH.CD.WT Exports of goods and services NE.EXP.GNFS.KD.ZG Food TX.VAL.FOOD.ZS.UN Imports of goods and services NE.IMP.GNFS.KD.ZG Agricultural raw materials TX.VAL.AGRI.ZS.UN Fuels TX.VAL.FUEL.ZS.UN 4.10 Toward a broader measure of national income Ores and metals TX.VAL.MMTL.ZS.UN Gross domestic product, $ NY.GDP.MKTP.CD Manufactures TX.VAL.MANF.ZS.UN Gross national income, $ NY.GNP.MKTP.CD Consumption of fixed capital NY.ADJ.DKAP.GN.ZS 4.5 Structure of merchandise imports Natural resource depletion NY.ADJ.DRES.GN.ZS Merchandise imports TM.VAL.MRCH.CD.WT Adjusted net national income NY.ADJ.NNTY.CD Food TM.VAL.FOOD.ZS.UN Gross domestic product, % growth NY.GDP.MKTP.KD.ZG Agricultural raw materials TM.VAL.AGRI.ZS.UN Gross national income, % growth NY.GNP.MKTP.KD.ZG Fuels TM.VAL.FUEL.ZS.UN Adjusted net national income NY.ADJ.NNTY.KD.ZG Ores and metals TM.VAL.MMTL.ZS.UN Manufactures TM.VAL.MANF.ZS.UN 4.11 Toward a broader measure of savings Gross savings NY.ADJ.ICTR.GN.ZS 4.6 Structure of service exports Consumption of fixed capital NY.ADJ.DKAP.GN.ZS Commercial service exports TX.VAL.SERV.CD.WT Education expenditure NY.ADJ.AEDU.GN.ZS Transport TX.VAL.TRAN.ZS.WT Net forest depletion NY.ADJ.DFOR.GN.ZS Travel TX.VAL.TRVL.ZS.WT Energy depletion NY.ADJ.DNGY.GN.ZS Insurance and financial services TX.VAL.INSF.ZS.WT Mineral depletion NY.ADJ.DMIN.GN.ZS Computer, information, communications, Carbon dioxide damage NY.ADJ.DCO2.GN.ZS and other commercial services TX.VAL.OTHR.ZS.WT Local pollution damage NY.ADJ.DPEM.GN.ZS Adjusted net savings NY.ADJ.SVNG.GN.ZS 68 World Development Indicators 2014 Front ? User guide World view People Environment Economy 4 4.12 Central government finances 4.15 Monetary indicators Revenue GC.REV.XGRT.GD.ZS Broad money FM.LBL.BMNY.ZG Expense GC.XPN.TOTL.GD.ZS Claims on domestic economy FM.AST.DOMO.ZG.M3 Cash surplus or deficit GC.BAL.CASH.GD.ZS Claims on central governments FM.AST.CGOV.ZG.M3 Net incurrence of liabilities, Domestic GC.FIN.DOMS.GD.ZS Interest rate, Deposit FR.INR.DPST Net incurrence of liabilities, Foreign GC.FIN.FRGN.GD.ZS Interest rate, Lending FR.INR.LEND Debt and interest payments, Total debt GC.DOD.TOTL.GD.ZS Interest rate, Real FR.INR.RINR Debt and interest payments, Interest GC.XPN.INTP.RV.ZS 4.16 Exchange rates and price 4.13 Central government expenditure Official exchange rate PA.NUS.FCRF Goods and services GC.XPN.GSRV.ZS Purchasing power parity (PPP) conversion Compensation of employees GC.XPN.COMP.ZS factor PA.NUS.PPP Interest payments GC.XPN.INTP.ZS Ratio of PPP conversion factor to market exchange rate PA.NUS.PPPC.RF Subsidies and other transfers GC.XPN.TRFT.ZS Real effective exchange rate PX.REX.REER Other expense GC.XPN.OTHR.ZS GDP implicit deflator NY.GDP.DEFL.KD.ZG 4.14 Central government revenues Consumer price index FP.CPI.TOTL.ZG Taxes on income, profits and capital gains GC.TAX.YPKG.RV.ZS Wholesale price index FP.WPI.TOTL Taxes on goods and services GC.TAX.GSRV.RV.ZS 4.17 Balance of payments current account Taxes on international trade GC.TAX.INTT.RV.ZS Goods and services, Exports BX.GSR.GNFS.CD Other taxes GC.TAX.OTHR.RV.ZS Goods and services, Imports BM.GSR.GNFS.CD Social contributions GC.REV.SOCL.ZS Balance on primary income BN.GSR.FCTY.CD Grants and other revenue GC.REV.GOTR.ZS Balance on secondary income BN.TRF.CURR.CD Current account balance BN.CAB.XOKA.CD Total reserves FI.RES.TOTL.CD Economy States and markets Global links Back World Development Indicators 2014 69 STATES AND MARKETS 70 World Development Indicators 2014 Front ? User guide World view People Environment 5 States and markets includes indicators of private System of National Accounts. In this edition we investment and performance, the role of the pub- have revised the indicator name to make the defi - lic sector in nurturing investment and growth, nition clearer. And more significantly we are add- and the quality and availability of infrastructure ing a new indicator, domestic credit to the private essential for growth and development. These sector by banks, to capture the resources that indicators measure the business environment, domestic banks provide to private firms. the functions of government, financial system The data on domestic credit provided by development, infrastructure, information and financial sector (previously domestic credit pro- communication technology, science and tech- vided by banking sector) are from the financial nology, performance of governments and their corporation survey or, when unavailable, from the policies, and conditions in fragile countries with depository corporations survey. Similarly, data weak institutions. for domestic credit to the private sector cap- Data on the access to finance, availability of ture the claims on the private sector by financial credit, and cost of service improve understand- corporation or, when unavailable, by depository ing of the state of financial development. Credit corporations. The financial corporations survey is an important link in money transmission; it includes all resident corporations or quasi-corpo- finances production, consumption, and capital rations principally engaged in financial interme- formation, which in turn affect economic activity. diation or in related auxiliary financial activities. The availability of credit to households, private It combines the data for depository corporations companies, and public entities shows the depth (central banks and other depository corpora- of banking and financial sector development in tions) and other financial corporations, such as the economy. In 2012 East Asia and Pacific pro- finance and leasing companies, money lenders, vided more credit to the private sector, 122 per- insurance corporations, pension funds, and for- cent of GDP, than did other developing regions. eign exchange companies. The newly reported In previous years we have presented both data generally start only in December 2001 and data for total domestic credit and credit to the in most cases are slightly higher than the values private sector as a percentage of GDP. Data for previously reported in the World Development the numerator come from the International Mon- Indicators database. etary Fund (IMF)’s International Financial Statis- The IMF is planning soon to issue a com- tics database. In 2009 the IMF began publish- bined Monetary and Financial Statistics Manual ing a new presentation of monetary statistics and Monetary and Financial Statistics Compilation for countries that report data in accord with the Guide aligned to the 2008 System of National IMF’s Monetary and Financial Statistics Manual Accounts and the sixth edition of the Balance 2000 and its Monetary and Financial Statistics of Payments and International Investment Posi- Compilation Guide 2008. The new presentation tion Manual. The latest information, manual, aligns the reporting of monetary and financial and guidelines can be viewed at the IMF website statistics with the financial account of the 1993 (http://www.imf.org/external/data.htm#guide). Economy States and markets Global links Back World Development Indicators 2014 71 Highlights Major economies are requiring higher capital to asset ratios in banks Average bank capital to asset ratio (%) The ratio of capital to assets measures bank solvency and resiliency— and the extent to which banks can deal with unexpected losses. With 15 banks under stress in the global financial crisis, the likelihood and cost of bank failures led countries to review their banking regulations. Many major economies have required higher minimum capital ratios to 10 ensure bank capacity to cover liabilities and protect depositors and other lenders. In the United States the average ratio of capital to assets rose to 11.2 percent in 2011, up from 9.3 percent in 2008. Also maintaining higher ratios were euro area countries (6.7 percent) 5 and the United Kingdom (5.1 percent). Japan and Germany, by con- trast, kept rates below 5  percent because of their banking conditions. 2005 2008 2011 0 United States Euro area United Kingdom Canada Japan Germany Source: Online table 5.5. A rising proportion of high-technology exports from developing countries High-technology exports (% of manufactured exports) Exports are an engine of industrial competitiveness and economic growth. And the share of high-technology goods in manufactured 30 exports is a common indicator of the innovation in an economy. In the Developed early 1990s the proportion of high-technology manufactured exports from developed countries was twice the proportion from developing 20 countries. Since then, exports from developing countries have grown rapidly and diversified, moving away from traditional resource- and labor-intensive products toward high-technology manufacturing. In Developing 2004 the gap between developed and developing countries closed, 10 with both around 21 percent. Shares have since fallen slightly, to 18 percent in developing countries and 17 percent in developed coun- tries in 2012. 0 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Source: Online table 5.13. Large differences in fixed-broadband Internet penetration across regions Fixed-broadband Internet subscriptions (% of population) After more than a decade of growth, there were about 640 million fixed broadband subscriptions in the world at the end of 2012—a global 30 penetration rate of 9 percent. More than 340 million of the subscrip- High income tions were in high-income countries—a 26 percent penetration rate. The nearly 300 million subscriptions in low- and middle-income coun- 20 tries indicate very low penetration—about 5 percent. And the differ- ences across regions are large. The lowest rates are in South Asia (1.1 percent) and Sub- Saharan Africa (0.2 percent), and the highest Europe & Central Asia rate in Europe and Central Asia (over 10 percent), followed closely by 10 Latin America & Caribbean East Asia and Pacific (9.7 percent) and Latin America and the Carib- East Asia & Pacific bean (8 percent). The Middle East and North Africa remains farther South Asia Middle East & North Africa Sub-Saharan Africa behind, at 3 percent. 0 2001 2003 2005 2007 2009 2011 2012 Source: International Telecommunication Union’s World Telecommunication/ICT indicators database; online table 5.12. 72 World Development Indicators 2014 Front ? User guide World view People Environment Electricity consumption up dramatically in middle-income countries Between 1991 and 2011 electricity consumption increased 82 percent Electric power consumption (trillions of kilowatt-hours) globally and 69 percent in low-income countries. But the share of 15 global electricity consumed by low-income countries remained fairly constant, despite a 60 percent increase in their population, while the High income share consumed by high-income countries dropped from 76 percent to 56 percent. The share consumed by middle-income countries rose 10 Middle income from 24 percent to 43 percent, with China accounting for more than half of that. Middle-income countries also saw per capita consump- tion increase—by 152 percent, from 721 kilowatt-hours in 1991 to 5 1,816 in 2011. China Low income 0 1991 2001 2011 Source: Online table 5.11. Business tax rates fall in developing countries Taxes fund a range of social and economic programs such as financing Average total corporate tax rate (% of commercial profits) public goods and services and redistributing income to the elderly and 75 unemployed. According to the Doing Business report, high corporate tax rates are negatively associated with corporate investment and Sub-Saharan Africa Europe & Central Asia entrepreneurship. Between 2004 and 2012 countries in East Asia 50 Latin America & Caribbean and Pacific reduced their total tax rates 5 percentage points, leaving South Asia them with the lowest average rate, 36 percent in 2012. The largest reductions were in Europe and Central Asia (18 percentage points) Middle East & North Africa East Asia & Pacific and Sub- Saharan Africa (19 percentage points). The average rate in 25 the Middle East and North Africa fell from 56  percent in 2004 to 43 percent in 2005 but has since dropped only 3 percentage points. South Asia saw an increase in 2009 and 2010, but the average rate fell to 41 percent in 2012. The average rate in Latin America and the 0 2004 2005 2006 2007 2008 2009 2010 2011 2012 Caribbean has changed little. Source: Online table 5.3. Air carriers from East Asia and Pacific countries take flight From 2002 to 2012 global air passenger transport grew 76 percent, Passengers carried by air (millions) to 2.8 billion passengers. While the total number of passengers car- 1,000 ried increased in all regions, the rise for carriers registered in East Asia and the Pacifi c was by far the highest. In 2002 the share of North America global air passenger transport by carriers registered in North America 750 was 38 percent, followed by Europe and Central Asia at 26 percent Europe & Central Asia and East Asia and the Pacific with 23 percent. By 2012 North America 500 and East Asia and Pacifi c each had 28 percent, with Europe and East Asia & Pacific Central Asia remaining steady at 26 percent. The increase in pas- senger traffi c by carriers registered in countries in East Asia and the 250 Latin America & Caribbean Pacifi c has been rapid: from around 425 million in 2002 to 810 mil- Middle East & North Africa Sub-Saharan Africa South Asia lion in 2012. 0 2000 2002 2004 2006 2008 2010 2012 Source: Online table 5.10. Economy States and markets Global links Back World Development Indicators 2014 73 5 States and markets Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta per 1,000 business financial government per capita people sector ages per % of % of manufactured 15–64 days % of GDP % of GDP % of GDP % of GDP kilowatt-hours 100 people population exports 2012 June 2013 2012 2012 2012 2012 2011 2012 2012 2012 Afghanistan 0.15 5 .. –4.0 7.5b 3.6 .. 60 5 .. Albania 0.88 5 .. 66.5 .. 1.5 2,022 111 55 0.4 Algeria 0.53 25 .. –2.1 37.4 4.6 1,091 98 15 0.1 American Samoa .. .. .. .. .. .. .. .. .. .. Andorra .. .. .. .. .. .. .. 82 86 .. Angola .. 66 .. 15.9 19.0 b 3.6 248 47 17 .. Antigua and Barbuda .. 21 .. 98.0 19.7b .. .. 143 59 0.0 Argentina 0.47 25 7.2 37.3 .. 0.9 2,967 152 56 7.7 Armenia 1.55 4 1.3 44.2 18.7b 3.9 1,755 112 39 2.6 Aruba .. .. .. 56.0 .. .. .. 132 74 10.2 Australia 12.16 3 83.9 154.2 21.6 1.7 10,712 106 82 12.7 Austria 0.50 25 26.9 135.0 18.9 0.8 8,374 161 81 12.8 Azerbaijan 0.70 7 .. 24.7 13.0 b 4.6 1,705 109 54 7.3 Bahamas, The .. 24 .. 105.0 15.7b .. .. 81 72 0.0 Bahrain .. 9 52.9 73.1 1.1 3.1 10,018 161 88 0.2 Bangladesh 0.09 11 15.0 69.0 10.0 b 1.3 259 63 6 .. Barbados .. 18 106.4 .. 25.2 .. .. 123 73 12.0 Belarus 1.14 9 .. 32.2 15.2b 1.2 3,628 114 47 2.9 Belgium 2.48 4 62.1 116.7 25.7 1.1 8,021 111 82 11.4 Belize 4.31 44 .. 63.0 22.6b 0.9 .. 53 25 4.8 Benin .. 15 .. 19.7 15.5 1.0 .. 84 4 0.5 Bermuda .. .. 27.2 .. .. .. .. 140 91 7.3 Bhutan 0.20 32 .. 50.4 .. .. .. 76 25 0.0 Bolivia 0.56 49 16.4 48.7 .. 1.5 623 90 34 9.2 Bosnia and Herzegovina 0.70 37 .. 67.9 20.9 1.4 3,189 88 65 2.5 Botswana 12.30 60 31.6 14.9 27.2b 2.3 1,603 154 12 1.2 Brazil 2.17 108 54.6 110.5 15.4b 1.5 2,438 125 50 10.5 Brunei Darussalam .. 101 .. 13.5 .. 2.4 8,507 114 60 12.8 Bulgaria 9.03 18 13.1 71.0 19.6b 1.5 4,864 148 55 7.7 Burkina Faso 0.15 13 .. 19.3 16.3 1.4 .. 61 4 5.9 Burundi .. 5 .. 26.1 .. 2.4 .. 23 1 2.7 Cabo Verde .. 10 .. 79.7 17.1b 0.5 .. 86 35 0.6 Cambodia .. 104 .. 33.9 11.6 1.5 164 129 5 0.1 Cameroon .. 15 .. 15.0 .. 1.4 256 60 6 3.7 Canada 1.07 5 113.3 .. 11.9 1.3 16,473 80 87 12.4 Cayman Islands .. .. .. .. .. .. .. 172 74 .. Central African Republic .. 22 .. 26.3 9.4 2.6 .. 25 3 0.0 Chad .. 62 .. 5.3 .. 2.0 .. 35 2 .. Channel Islands .. .. .. .. .. .. .. .. .. .. Chile 5.69 6 116.1 108.0 18.9 2.0 3,568 138 61 4.6 China .. 33 44.9 155.1 10.6 b 2.0 c 3,298 81 42 26.3 Hong Kong SAR, China 28.12 3 420.9 200.6 14.2 .. 5,949 229 73 16.2 Macao SAR, China .. .. .. –13.0 36.5b .. .. 290 64 0.0 Colombia 2.00 15 70.9 72.9 13.3 3.3 1,123 103 49 5.2 Comoros .. 15 .. 21.6 .. .. .. 40 6 .. Congo, Dem. Rep. 0.02 31 .. 11.1 13.7b 1.8 105 31 2 .. Congo, Rep. .. 101 .. –8.9 .. 1.1 172 99 6 3.7 74 World Development Indicators 2014 Front ? User guide World view People Environment States and markets 5 Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta per 1,000 business financial government per capita people sector ages per % of % of manufactured 15–64 days % of GDP % of GDP % of GDP % of GDP kilowatt-hours 100 people population exports 2012 June 2013 2012 2012 2012 2012 2011 2012 2012 2012 Costa Rica 3.55 24 4.5 53.4 13.7 .. 1,844 112 48 39.6 Côte d’Ivoire .. 8 31.7 27.3 15.6 1.7 212 91 2 15.1 Croatia 2.82 8 36.4 96.3 19.6b 1.7 3,901 115 63 9.9 Cuba .. .. .. .. .. 3.3 1,327 15 26 .. Curaçao .. .. .. .. .. .. .. .. .. .. Cyprus 22.51 8 8.8 347.3 25.5 2.1 4,271 98 61 13.0 Czech Republic 2.96 20 18.9 68.4 14.2b 1.1 6,289 127 75 16.1 Denmark 4.36 6 71.3 206.0 34.1 1.4 6,122 118 93 14.2 Djibouti .. 17 .. .. .. .. .. 25 8 .. Dominica 3.30 12 .. 62.4 23.4b .. .. 152 55 8.8 Dominican Republic 1.05 19 .. 46.5 12.8 0.6 893 87 45 2.7 Ecuador .. 56 7.0 29.2 .. 2.8 1,192 106 35 2.5 Egypt, Arab Rep. .. 8 22.1 77.7 13.2b 1.7 1,743 120 44 0.6 El Salvador 0.48 17 45.0 66.1 14.5 1.0 830 137 26 4.7 Equatorial Guinea .. 135 .. –3.5 .. .. .. 68 14 .. Eritrea .. 84 .. 104.0 .. .. 49 5 1 .. Estonia 7.92 7 10.4 77.2 16.5 1.9 6,279 160 79 10.7 Ethiopia 0.03 15 .. .. 9.4b 0.9 52 22 1 2.4 Faeroe Islands .. .. .. .. .. .. .. 119 85 .. Fiji .. 59 11.6 116.3 .. 1.5 .. 98 34 2.1 Finland 2.32 14 64.1 105.2 20.7 1.5 15,738 172 91 8.5 France 2.88 7 69.8 136.4 22.0 2.3 7,289 97 83 25.4 French Polynesia .. .. .. .. .. .. .. 83 53 2.5 Gabon 4.11 50 .. 13.2 .. 1.4 907 179 9 .. Gambia, The .. 27 .. 44.4 .. .. .. 85 12 3.3 Georgia 4.86 2 6.0 35.0 24.1b 2.9 1,918 108 46 2.4 Germany 1.29 15 43.4 122.5 11.9 1.3 7,081 112 84 15.8 Ghana 0.90 14 8.5 32.3 14.9 b 0.3 344 101 17 7.3 Greece 0.77 14 17.9 135.5 22.5 2.6 5,380 120 56 9.2 Greenland .. .. .. .. .. .. .. 105 65 2.4 Grenada .. 15 .. 95.2 19.5b .. .. 121 42 .. Guam .. .. .. .. .. .. .. .. 62 .. Guatemala 0.52 20 .. 39.2 10.9b 0.4 539 138 16 4.7 Guinea 0.23 16 .. 32.2 .. .. .. 42 1 .. Guinea-Bissau .. 9 .. 20.3 .. 2.0 .. 63 3 .. Guyana .. 20 21.4 50.6 .. 1.1 .. 69 33 0.1 Haiti 0.06 97 .. 19.6 .. .. 32 60 10 .. Honduras .. 14 .. 55.9 14.7 1.1 708 93 18 .. Hungary 4.75 5 16.9 68.7 23.3 0.8 3,895 116 72 18.1 Iceland 8.17 5 20.8 143.9 23.2 0.1 52,374 108 96 14.3 India 0.12 27 68.0 75.9 10.7b 2.4 684 70 13 6.6 Indonesia 0.29 48 45.2 42.6 .. 0.8 680 114 15 7.3 Iran, Islamic Rep. .. 16 25.5 18.0 .. .. 2,649 76 26 4.1 Iraq 0.13 29 .. –1.8 .. 2.8 1,343 82 7 .. Ireland 4.50 10 51.7 201.7 23.2 0.6 5,701 107 79 22.6 Isle of Man 45.27 .. .. .. .. .. .. .. .. .. Israel 2.96 14 56.1 .. 22.1 5.7 6,926 121 73 15.8 Economy States and markets Global links Back World Development Indicators 2014 75 5 States and markets Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta per 1,000 business financial government per capita people sector ages per % of % of manufactured 15–64 days % of GDP % of GDP % of GDP % of GDP kilowatt-hours 100 people population exports 2012 June 2013 2012 2012 2012 2012 2011 2012 2012 2012 Italy 1.91 6 23.8 167.5 23.2 1.7 5,393 160 58 7.1 Jamaica 1.11 6 43.3 51.8 27.1 0.9 1,553 96 47 0.6 Japan 1.15 22 61.8 346.1 10.1 1.0 7,848 111 79 17.4 Jordan 0.98 12 87.0 114.2 15.3 4.7 2,289 128 41 2.5 Kazakhstan 1.71 12 11.5 41.1 .. 1.2 4,893 186 53 30.0 Kenya 0.84 32 36.3 52.3 19.7b 2.0 155 71 32 5.7 Kiribati 0.11 31 .. .. 16.1b .. .. 16 11 38.5 Korea, Dem. People’s Rep. .. .. .. .. .. .. 739 7 0 .. Korea, Rep. 2.03 6 104.5 168.7 15.6 b 2.8 10,162 109 84 26.2 Kosovo 1.22 30 .. 21.0 .. .. 2,947 .. .. .. Kuwait .. 32 53.0 47.9 0.7b 3.3 16,122 157 79 .. Kyrgyz Republic 0.92 8 2.5 .. 18.5b 3.7 1,642 124 22 4.6 Lao PDR 0.10 92 .. 26.5 14.8b 0.2 .. 65 11 .. Latvia 11.63 13 3.9 62.9 13.8b 0.9 3,264 112 74 9.8 Lebanon .. 9 24.0 176.4 15.6 4.0 3,499 81 61 2.0 Lesotho 1.49 29 .. 3.2 .. 1.9 .. 75 5 .. Liberia .. 5 .. 33.9 20.9b 0.8 .. 57 4 .. Libya .. 35 .. .. .. .. 3,926 156 14 .. Liechtenstein 25.11 .. .. .. .. .. .. 97 89 .. Lithuania 4.71 7 9.4 52.0 13.4 1.0 3,530 165 68 10.4 Luxembourg 20.98 19 127.5 173.6 26.1 0.6 15,530 145 92 8.1 Macedonia, FYR 3.60 2 5.8 48.9 16.6b 1.4 3,881 106 63 3.9 Madagascar 0.05 8 .. 12.9 10.1 0.7 .. 39 2 0.4 Malawi 0.08 40 17.7 35.6 .. 0.9 .. 29 4 3.2 Malaysia 2.28 6 156.2 134.0 16.1b 1.5 4,246 141 66 43.7 Maldives 4.39 9 .. 83.9 15.6 b .. .. 166 39 .. Mali .. 11 .. 19.7 14.6 1.4 .. 98 2 1.2 Malta 13.61 40 41.6 154.2 27.5 0.6 4,689 127 70 45.7 Marshall Islands .. 17 .. .. .. .. .. .. 10 .. Mauritania .. 19 .. 36.8 .. .. .. 106 5 .. Mauritius 7.40 6 67.6 113.7 19.0 0.2 .. 120 41 0.9 Mexico 0.88 6 44.6 47.0 .. 0.6 2,092 83 38 16.3 Micronesia, Fed. Sts. .. 16 .. –19.1 .. .. .. 30 26 .. Moldova 1.63 7 .. 42.2 18.7b 0.3 1,470 102 43 4.8 Monaco .. .. .. .. .. .. .. 88 87 .. Mongolia .. 11 12.6 30.8 18.3b 1.1 1,577 121 16 .. Montenegro 10.66 10 87.5 58.7 .. 1.9 5,747 181 57 .. Morocco 1.26 11 54.8 115.4 24.5 3.5 826 120 55 6.4 Mozambique .. 13 .. 29.1 21.8b 0.9 447 36 5 24.7 Myanmar .. 72 .. .. .. .. 110 10 1 0.0 Namibia 0.85 66 10.0 49.5 14.9 b 3.1 1,549 95 13 5.3 Nepal 0.66 17 21.9 67.9 13.8b 1.4 106 60 11 0.3 Netherlands 4.44 4 84.5 216.2 21.1 1.3 7,036 118 93 20.1 New Caledonia .. .. .. .. .. .. .. 91 58 10.6 New Zealand 15.07 1 46.6 154.0 29.3 1.1 9,399 110 90 9.7 Nicaragua .. 36 .. 44.0 15.0 b 0.6 522 86 14 4.8 Niger .. 17 .. 13.2 .. 1.0 .. 31 1 6.0 76 World Development Indicators 2014 Front ? User guide World view People Environment States and markets 5 Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta per 1,000 business financial government per capita people sector ages per % of % of manufactured 15–64 days % of GDP % of GDP % of GDP % of GDP kilowatt-hours 100 people population exports 2012 June 2013 2012 2012 2012 2012 2011 2012 2012 2012 Nigeria 0.91 28 21.5 35.6 2.7b 0.9 149 67 33 1.9 Northern Mariana Islands .. .. .. .. .. .. .. .. .. .. Norway 7.83 7 50.6 .. 27.3 1.4 23,174 117 95 18.8 Oman .. 8 25.7 35.4 2.6b 8.6 6,292 159 60 3.4 Pakistan 0.04 21 19.4 45.8 10.1b 3.1 449 67 10 1.7 Palau .. 28 .. .. .. .. .. 83 .. .. Panama 14.10 6 34.6 89.0 .. .. 1,829 178 45 35.4 Papua New Guinea .. 53 68.4 38.3 .. 0.5 .. 38 2 3.5 Paraguay .. 35 3.8 37.2 12.4b 1.7 1,228 102 27 6.9 Peru 3.83 25 47.5 17.4 15.6b 1.3 1,248 98 38 3.5 Philippines 0.27 35 105.6 50.9 12.9b 1.2 647 107 36 48.9 Poland 0.53 30 36.3 63.8 16.2 1.9 3,832 140 65 7.0 Portugal 3.62 3 30.9 198.9 20.9 1.8 4,848 116 64 4.1 Puerto Rico .. 6 .. .. .. .. .. 83 51 .. Qatar 1.74 9 65.7 77.5 14.7b 1.5 15,755 127 88 0.0 Romania 4.12 9 9.4 54.3 18.8 1.3 2,639 105 50 6.4 Russian Federation 4.30 15 43.4 41.5 15.0 4.5 6,486 183 53 8.4 Rwanda 1.07 2 .. .. 13.3b 1.1 .. 50 8 2.5 Samoa 1.04 9 .. 45.3 0.0 b .. .. .. 13 0.1 San Marino .. 40 .. .. .. .. .. 115 51 .. São Tomé and Príncipe 3.75 5 .. 35.1 14.0 .. .. 65 22 14.3 Saudi Arabia .. 21 52.5 –10.5 .. 8.0 8,161 187 54 0.6 Senegal 0.27 6 .. 31.3 19.2 1.5 187 84 19 0.7 Serbia 1.68 12 19.9 62.3 21.5b 2.2 4,474 118 48 .. Seychelles .. 39 .. 35.5 28.5b 0.8 .. 148 47 .. Sierra Leone 0.32 12 .. 14.0 10.9b 0.7 .. 37 1 .. Singapore 8.04 3 150.8 99.5 14.5b 3.5 8,404 152 74 45.3 Sint Maarten .. .. .. .. .. .. .. .. .. .. Slovak Republic 5.11 19 5.1 .. 12.4 1.1 5,348 112 80 9.3 Slovenia 4.36 6 14.3 93.8 17.9b 1.2 6,806 109 70 6.2 Solomon Islands .. 9 .. 12.0 .. .. .. 55 7 87.4 Somalia .. .. .. .. .. .. .. 23 1 .. South Africa 6.54 19 159.3 187.2 26.4 1.2 4,604 131 41 5.5 South Sudan 0.73 17 .. .. .. 9.4 .. 21 .. .. Spain 2.71 23 75.2 225.9 7.3 0.9 5,530 108 72 7.0 Sri Lanka 0.51 8 28.7 48.4 12.0 b 2.4 490 92 18 0.9 St. Kitts and Nevis 5.69 19 85.6 105.6 19.3b .. .. 157 79 0.1 St. Lucia 3.00 15 .. 129.0 24.2b .. .. 126 49 .. St. Martin .. .. .. .. .. .. .. .. .. .. St. Vincent & the Grenadines 1.37 10 .. 56.8 22.4b .. .. 124 48 0.1 Sudan .. 36 .. 24.6 .. .. 143 74 d 21d 0.7 Suriname 1.63 208 .. 25.4 19.4b .. .. 106 35 6.5 Swaziland .. 38 .. 21.1 .. 3.2 .. 65 21 .. Sweden 6.41 16 107.0 145.3 21.5 1.2 14,030 125 94 13.4 Switzerland 2.53 18 171.0 192.9 10.3 0.8 7,928 130 85 25.8 Syrian Arab Republic 0.04 13 .. 47.7 .. 3.9 1,715 59 24 1.3 Tajikistan 0.26 33 .. 13.1 .. .. 1,714 82 15 .. Economy States and markets Global links Back World Development Indicators 2014 77 5 States and markets Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta per 1,000 business financial government per capita people sector ages per % of % of manufactured 15–64 days % of GDP % of GDP % of GDP % of GDP kilowatt-hours 100 people population exports 2012 June 2013 2012 2012 2012 2012 2011 2012 2012 2012 Tanzania .. 26 6.4 24.7 16.1b 1.1 92 57 4 10.2 Thailand 0.86 28 104.7 169.6 16.5 1.5 2,316 127 27 20.5 Timor-Leste 2.76 94 .. –52.7 .. 2.9 .. 56 1 .. Togo 0.12 19 .. 37.6 16.8 1.6 .. 50 4 0.2 Tonga 1.91 16 .. 27.3 .. .. .. 53 35 6.5 Trinidad and Tobago .. 38 65.0 37.5 28.3b .. 6,332 141 60 0.1 Tunisia 1.52 11 19.5 82.3 20.8b 1.6 1,297 118 41 5.6 Turkey 0.79 6 39.1 71.9 20.4 2.3 2,709 91 45 1.8 Turkmenistan .. .. .. .. .. .. 2,444 76 7 .. Turks and Caicos Islands .. .. .. .. .. .. .. .. .. 1.9 Tuvalu .. .. .. .. .. .. .. 28 35 .. Uganda 1.17 32 36.7 16.3 13.0b 1.4 .. 45 15 20.7 Ukraine 0.92 21 11.7 80.2 18.3b 2.8 3,662 130 34 6.3 United Arab Emirates 1.38 8 17.7 76.5 0.4 5.5 9,389 150 85 .. United Kingdom 11.04 12 122.0 206.7 26.7 2.4 5,472 135 87 21.7 United States .. 5 114.9 229.9 10.2 4.2 13,246 95 81 17.8 Uruguay 2.98 7 0.4 32.0 19.3b 1.9 2,810 147 55 9.3 Uzbekistan 0.64 9 .. .. .. .. 1,626 71 37 .. Vanuatu 2.34 35 .. 69.5 16.1b .. .. 59 11 54.0 Venezuela, RB .. 144 6.6 42.0 .. 1.1 3,313 102 44 2.5 Vietnam .. 34 21.1 104.9 .. 2.2 1,073 148 39 14.5 Virgin Islands (U.S.) .. .. .. .. .. .. .. .. 41 .. West Bank and Gaza .. 45 .. .. .. .. .. 76 41 .. Yemen, Rep. .. 40 .. 26.9 .. 4.0 193 58 17 0.2 Zambia 1.36 7 14.6 18.6 19.7b 1.6 599 75 13 24.8 Zimbabwe .. 90 120.5 .. .. 3.2 757 92 17 5.9 World 3.83 u 25 u 75.3 w 169.0 w 14.5 w 2.9 w 3,044 w 89 w 36 w 17.6 w Low income 0.40 29 .. 39.4 12.8 1.7 233 47 6 .. Middle income 2.25 28 48.9 104.7 13.3 3.3 1,816 88 30 18.2 Lower middle income 1.12 26 50.6 62.0 11.5 8.9 734 83 19 8.4 Upper middle income 3.01 30 48.4 116.8 14.0 1.8 2,932 92 42 20.8 Low & middle income 1.86 28 48.6 103.6 13.3 3.3 1,646 82 26 18.1 East Asia & Pacific 1.34 40e 51.5 141.5 11.2 1.9 2,582 89 36 26.5 Europe & Central Asia 2.19 12e 25.6 62.6 19.7 2.0 2,951 108 43 8.2 Latin America & Carib. 2.38 41e 43.3 73.6 .. 1.3 1,985 108 43 11.7 Middle East & N. Africa 0.55 21e 28.9 37.4 .. .. 1,696 95 31 2.2 South Asia 0.25 16e 59.1 71.1 10.6 2.4 605 69 12 6.2 Sub-Saharan Africa 2.09 27e 83.8 77.8 17.3 1.5 535 59 15 4.0 High income 7.47 17 86.8 197.8 14.4 2.7 8,896 123 75 17.3 Euro area 6.75 13 51.6 153.3 17.7 1.5 6,599 120 76 15.2 a. Data are from the International Telecommunication Union’s (ITU) World Telecommunication/ICT Indicators database. Please cite ITU for third party use of these data. b. Data were reported on a cash basis and have been adjusted to the accrual framework of the International Monetary Fund’s Government Finance Statistics Manual 2001. c. Differs from the official value published by the government of China (1.3 percent; see National Bureau of Statistics of China, www.stats.gov.cn). d. Excludes South Sudan. e. Differs from data reported on the Doing Business website because the regional aggregates on the Doing Business website include developed economies. 78 World Development Indicators 2014 Front ? User guide World view People Environment States and markets 5 About the data Entrepreneurial activity different estimates, the Doing Business time indicators represent The rate new businesses are added to an economy is a measure of the median values of several responses given under the assumptions its dynamism and entrepreneurial activity. Data on business entry of the standardized case. Fifth, the methodology assumes that a density are from the World Bank’s 2013 Entrepreneurship Database, business has full information on what is required and does not waste which includes indicators for more than 150 countries for 2004–12. time when completing procedures. In constructing the indicators, it is Survey data are used to analyze firm creation, its relationship to assumed that entrepreneurs know about all regulations and comply economic growth and poverty reduction, and the impact of regula- with them. In practice, entrepreneurs may not be aware of all required tory and institutional reforms. Data on total registered businesses procedures or may avoid legally required procedures altogether. were collected from national registrars of companies. For cross- country comparability, only limited liability corporations that oper- Financial systems ate in the formal sector are included. For additional information on Stock markets and banking systems both enhance growth, the main sources, methodology, calculation of entrepreneurship rates, and factor in poverty reduction. At low levels of economic development com- data limitations see www.doingbusiness.org/data/exploretopics mercial banks tend to dominate the financial system, while at higher /entrepreneurship. levels domestic stock markets become more active and efficient. Data on time required to start a business are from the Doing Busi- Open economies with sound macroeconomic policies, good legal ness database, whose indicators measure business regulation, gauge systems, and shareholder protection attract capital and thus have regulatory outcomes, and measure the extent of legal protection of larger financial markets. The table includes market capitalization property, the flexibility of employment regulation, and the tax burden as a share of gross domestic product (GDP) as a measure of stock on businesses. The fundamental premise is that economic activity market size. Market size can be measured in other ways that may requires good rules and regulations that are efficient, accessible, produce a different ranking of countries. Recent research on stock and easy to implement. Some indicators give a higher score for more market development shows that modern communications tech- regulation, such as stricter disclosure requirements in related-party nology and increased financial integration have resulted in more transactions, and others give a higher score for simplified regulations, cross-border capital flows, a stronger presence of financial firms such as a one-stop shop for completing business startup formalities. around the world, and the migration of trading activities to interna- There are 11 sets of indicators covering starting a business, register- tional exchanges. Many firms in emerging markets now cross-list ing property, dealing with construction permits, getting electricity, on international exchanges, which provides them with lower cost enforcing contracts, getting credit, protecting investors, paying taxes, capital and more liquidity-traded shares. However, this also means trading across borders, resolving insolvency, and employing workers. that exchanges in emerging markets may not have enough financial The indicators are available at www.doingbusiness.org. activity to sustain them. Comparability across countries may be lim- Doing Business data are collected with a standardized survey that ited by conceptual and statistical weaknesses, such as inaccurate uses a simple business case to ensure comparability across econo- reporting and differences in accounting standards. mies and over time—with assumptions about the legal form of the Standard & Poor’s (S&P) Indices provides regular updates on 21 business, its size, its location, and nature of its operation. Surveys emerging stock markets and 36 frontier markets. The S&P Global in 189 countries are administered through more than 10,200 local Equity Indices, S&P Indices’s leading emerging markets index, is experts, including lawyers, business consultants, accountants, designed to be sufficiently investable to support index tracking portfo- freight forwarders, government officials, and other professionals who lios in emerging market stocks that are legally and practically open to routinely administer or advise on legal and regulatory requirements. foreign portfolio investment. The S&P Frontier Broad Market Index mea- The Doing Business methodology has limitations that should be sures the performance of 36 smaller and less liquid markets. These considered when interpreting the data. First, the data collected refer indexes are widely used benchmarks for international portfolio manage- to businesses in the economy’s largest city and may not represent ment. See www.spindices.com for further information on the indexes. regulations in other locations of the economy. To address this limita- Because markets included in S&P’s emerging markets category tion, subnational indicators are being collected for selected econo- vary widely in level of development, it is best to look at the entire mies; they point to significant differences in the speed of reform category to identify the most significant market trends. And it is and the ease of doing business across cities in the same economy. useful to remember that stock market trends may be distorted by Second, the data often focus on a specific business form—generally currency conversions, especially when a currency has registered a limited liability company of a specified size—and may not represent a significant devaluation (Demirgüç-Kunt and Levine 1996; Beck regulation for other types of businesses such as sole proprietor- and Levine 2001; and Claessens, Klingebiel, and Schmukler 2002). ships. Third, transactions described in a standardized business case Domestic credit provided by the financial sector as a share of GDP refer to a specific set of issues and may not represent all the issues measures banking sector depth and financial sector development in a business encounters. Fourth, the time measures involve an ele- terms of size. Data are taken from the financial corporation survey ment of judgment by the expert respondents. When sources indicate of the International Monetary Fund’s (IMF) International Financial Economy States and markets Global links Back World Development Indicators 2014 79 5 States and markets Statistics or, when unavailable, from its deposit corporation survey. definitions and the difficulty of verifying the accuracy and complete- The financial corporation survey includes monetary authorities (the ness of data, data are not always comparable across countries. central bank), deposit money banks, and other banking institutions, However, SIPRI puts a high priority on ensuring that the data series such as finance companies, development banks, and savings and for each country is comparable over time. More information on loan institutions. In a few countries governments may hold inter- SIPRI’s military expenditure project can be found at www.sipri.org national reserves as deposits in the banking system rather than /contents/milap/. in the central bank. Claims on the central government are a net item (claims on the central government minus central government Infrastructure deposits) and thus may be negative, resulting in a negative value The quality of an economy’s infrastructure, including power and for domestic credit provided by the financial sector. communications, is an important element in investment decisions and economic development. The International Energy Agency (IEA) Tax revenues collects data on electric power consumption from national energy Taxes are the main source of revenue for most governments. Tax agencies and adjusts the values to meet international definitions. revenue as a share of GDP provides a quick overview of the fiscal Consumption by auxiliary stations, losses in transformers that are obligations and incentives facing the private sector across coun- considered integral parts of those stations, and electricity produced tries. The table shows only central government data, which may by pumping installations are included. Where data are available, significantly understate the total tax burden, particularly in countries electricity generated by primary sources of energy—coal, oil, gas, where provincial and municipal governments are large or have con- nuclear, hydro, geothermal, wind, tide and wave, and combustible siderable tax authority. renewables—are included. Consumption data do not capture the Low ratios of tax revenue to GDP may reflect weak administration reliability of supplies, including breakdowns, load factors, and fre- and large-scale tax avoidance or evasion. Low ratios may also reflect quency of outages. a sizable parallel economy with unrecorded and undisclosed incomes. The International Telecommunication Union (ITU) estimates that Tax revenue ratios tend to rise with income, with higher income coun- there were 6.3 billion mobile subscriptions globally in 2012. No tries relying on taxes to finance a much broader range of social ser- technology has ever spread faster around the world. Mobile com- vices and social security than lower income countries are able to. munications have a particularly important impact in rural areas. The mobility, ease of use, flexible deployment, and relatively low Military expenditures and declining rollout costs of wireless technologies enable them to Although national defense is an important function of government, reach rural populations with low levels of income and literacy. The high expenditures for defense or civil conflicts burden the economy next billion mobile subscribers will consist mainly of the rural poor. and may impede growth. Military expenditures as a share of GDP Operating companies have traditionally been the main source of are a rough indicator of the portion of national resources used for telecommunications data, so information on subscriptions has been military activities. As an “input” measure, military expenditures are widely available for most countries. This gives a general idea of not directly related to the “output” of military activities, capabilities, access, but a more precise measure is the penetration rate—the or security. Comparisons across countries should take into account share of households with access to telecommunications. During the many factors, including historical and cultural traditions, the length past few years more information on information and communication of borders that need defending, the quality of relations with neigh- technology use has become available from household and business bors, and the role of the armed forces in the body politic. surveys. Also important are data on actual use of telecommunica- Data are from the Stockholm International Peace Research Institute tions services. The quality of data varies among reporting countries (SIPRI), whose primary source of military expenditure data is offi - as a result of differences in regulations covering data provision and cial data provided by national governments. These data are derived availability. from budget documents, defense white papers, and other public documents from official government agencies, including govern- High-technology exports ment responses to questionnaires sent by SIPRI, the United Nations The method for determining high-technology exports was developed Office for Disarmament Affairs, or the Organization for Security and by the Organisation for Economic Co-operation and Development in Co-operation in Europe. Secondary sources include international sta- collaboration with Eurostat. It takes a “product approach” (rather tistics, such as those of the North Atlantic Treaty Organization (NATO) than a “sectoral approach”) based on research and development and the IMF’s Government Finance Statistics Yearbook. Other second- intensity (expenditure divided by total sales) for groups of prod- ary sources include country reports of the Economist Intelligence Unit, ucts from Germany, Italy, Japan, the Netherlands, Sweden, and the country reports by IMF staff, and specialist journals and newspapers. United States. Because industrial sectors specializing in a few high- In the many cases where SIPRI cannot make independent esti- technology products may also produce low-technology products, the mates, it uses country-provided data. Because of differences in product approach is more appropriate for international trade. The 80 World Development Indicators 2014 Front ? User guide World view People Environment States and markets 5 method takes only research and development intensity into account, technology. Postpaid subscriptions and active prepaid accounts (that but other characteristics of high technology are also important, such is, accounts that have been used during the last three months) are as knowhow, scientific personnel, and technology embodied in pat- included. The indicator applies to all mobile cellular subscriptions ents. Considering these characteristics would yield a different list that offer voice communications and excludes subscriptions for data (see Hatzichronoglou 1997). cards or USB modems, subscriptions to public mobile data services, private-trunked mobile radio, telepoint, radio paging, and telemetry Definitions services. • Individuals using the Internet are the percentage of • Business entry density is the number of newly registered limited individuals who have used the Internet (from any location) in the last liability corporations per 1,000 people ages 15–64. • Time required 12 months. Internet can be used via a computer, mobile phone, per- to start a business is the number of calendar days to complete the sonal digital assistant, games machine, digital television, or similar procedures for legally operating a business using the fastest pro- device. • High-technology exports are products with high research cedure, independent of cost. • Stock market capitalization (also and development intensity, such as in aerospace, computers, phar- known as market value) is the share price times the number of shares maceuticals, scientific instruments, and electrical machinery. outstanding. • Domestic credit provided by financial sector is all credit to various sectors on a gross basis, except to the central Data sources government, which is net. The financial sector includes monetary Data on business entry density are from the World Bank’s Entre- authorities, deposit money banks, and other banking institutions preneurship Database (www.doingbusiness.org/data/exploretopics for which data are available. • Tax revenue collected by central /entrepreneurship). Data on time required to start a business are government is compulsory transfers to the central government for from the World Bank’s Doing Business project (www.doingbusiness public purposes. Certain compulsory transfers such as fines, penal- .org). Data on stock market capitalization are from Standard & ties, and most social security contributions are excluded. Refunds Poor’s (2012). Data on domestic credit are from the IMF’s Inter- and corrections of erroneously collected tax revenue are treated as national Financial Statistics. Data on central government tax rev- negative revenue. The analytic framework of the IMF’s Government enue are from the IMF’s Government Finance Statistics. Data on Finance Statistics Manual 2001 (GFSM 2001) is based on accrual military expenditures are from SIPRI’s Military Expenditure Database accounting and balance sheets. For countries still reporting govern- (www.sipri.org/databases/milex). Data on electricity consumption ment finance data on a cash basis, the IMF adjusts reported data are from the IEA’s Energy Statistics of Non-OECD Countries, Energy to the GFSM 2001 accrual framework. These countries are foot- Balances of Non-OECD Countries, and Energy Statistics of OECD noted in the table. • Military expenditures are SIPRI data derived Countries and from the United Nations Statistics Division’s Energy from NATO’s former definition (in use until 2002), which includes Statistics Yearbook. Data on mobile cellular phone subscriptions and all current and capital expenditures on the armed forces, including individuals using the Internet are from the ITU’s World Telecommu- peacekeeping forces; defense ministries and other government agen- nication/ICT Indicators database. Data on high-technology exports cies engaged in defense projects; paramilitary forces, if judged to are from the United Nations Statistics Division’s Commodity Trade be trained and equipped for military operations; and military space (Comtrade) database. activities. Such expenditures include military and civil personnel, including retirement pensions and social services for military per- References sonnel; operation and maintenance; procurement; military research Beck, Thorsten, and Ross Levine. 2001. “Stock Markets, Banks, and and development; and military aid (in the military expenditures of the Growth: Correlation or Causality?” Policy Research Working Paper donor country). Excluded are civil defense and current expenditures 2670, World Bank, Washington, DC. for previous military activities, such as for veterans benefits, demo- Claessens, Stijn, Daniela Klingebiel, and Sergio L. Schmukler. 2002. bilization, and weapons conversion and destruction. This definition “Explaining the Migration of Stocks from Exchanges in Emerging cannot be applied for all countries, however, since that would require Economies to International Centers.” Policy Research Working Paper more detailed information than is available about military budgets 2816, World Bank, Washington, DC. and off-budget military expenditures (for example, whether military Demirgüç-Kunt, Asli, and Ross Levine. 1996. “Stock Market Devel- budgets cover civil defense, reserves and auxiliary forces, police opment and Financial Intermediaries: Stylized Facts.” World Bank and paramilitary forces, and military pensions). • Electric power Economic Review 10 (2): 291–321. consumption per capita is the production of power plants and com- Hatzichronoglou, Thomas. 1997. “Revision of the High-Technology bined heat and power plants less transmission, distribution, and Sector and Product Classification.” STI Working Paper 1997/2. transformation losses and own use by heat and power plants, divided Organisation for Economic Co-operation and Development, Direc- by midyear population. • Mobile cellular subscriptions are the num- torate for Science, Technology, and Industry, Paris. ber of subscriptions to a public mobile telephone service that pro- Standard & Poors. 2012. Global Stock Markets Factbook 2012. New vides access to the public switched telephone network using cellular York. Economy States and markets Global links Back World Development Indicators 2014 81 5 States and markets To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/5.1). To view a specific /indicator/IE.PPI.TELE.CD). 5.1 Private sector in the economy Telecommunications investment IE.PPI.TELE.CD 5.5 Financial access, stability, and efficiency Energy investment IE.PPI.ENGY.CD Strength of legal rights index IC.LGL.CRED.XQ Transport investment IE.PPI.TRAN.CD Depth of credit information index IC.CRD.INFO.XQ Water and sanitation investment IE.PPI.WATR.CD Depositors with commercial banks FB.CBK.DPTR.P3 Domestic credit to private sector FS.AST.PRVT.GD.ZS Borrowers from commercial banks FB.CBK.BRWR.P3 Businesses registered, New IC.BUS.NREG Commercial bank branches FB.CBK.BRCH.P5 Businesses registered, Entry density IC.BUS.NDNS.ZS Automated teller machines FB.ATM.TOTL.P5 Bank capital to assets ratio FB.BNK.CAPA.ZS 5.2 Business environment: enterprise surveys Ratio of bank non-performing loans to total Time dealing with officials IC.GOV.DURS.ZS gross loans FB.AST.NPER.ZS Number of visits or meetings with tax officials IC.TAX.METG Domestic credit to private sector by banks Time required to obtain operating license IC.FRM.DURS (% of GDP) FD.AST.PRVT.GD.ZS Informal payments to public officials IC.FRM.CORR.ZS Interest rate spread FR.INR.LNDP Losses due to theft, robbery, vandalism, Risk premium on lending FR.INR.RISK and arson IC.FRM.CRIM.ZS Firms competing against unregistered firms IC.FRM.CMPU.ZS 5.6 Tax policies Firms with female top manager IC.FRM.FEMM.ZS Tax revenue collected by central government GC.TAX.TOTL.GD.ZS Firms using banks to finance investment IC.FRM.BNKS.ZS Number of tax payments by businesses IC.TAX.PAYM Value lost due to electrical outages IC.FRM.OUTG.ZS Time for businesses to prepare, file and pay taxes IC.TAX.DURS Internationally recognized quality certification IC.FRM.ISOC.ZS Business profit tax IC.TAX.PRFT.CP.ZS Average time to clear exports through customs IC.CUS.DURS.EX Business labor tax and contributions IC.TAX.LABR.CP.ZS Firms offering formal training IC.FRM.TRNG.ZS Other business taxes IC.TAX.OTHR.CP.ZS Total business tax rate IC.TAX.TOTL.CP.ZS 5.3 Business environment: Doing Business indicators Number of procedures to start a business IC.REG.PROC 5.7 Military expenditures and arms transfers Time required to start a business IC.REG.DURS Military expenditure, % of GDP MS.MIL.XPND.GD.ZS Cost to start a business IC.REG.COST.PC.ZS Military expenditure, % of central government expenditure MS.MIL.XPND.ZS Number of procedures to register property IC.PRP.PROC Arm forces personnel MS.MIL.TOTL.P1 Time required to register property IC.PRP.DURS Arm forces personnel, % of total labor force MS.MIL.TOTL.TF.ZS Number of procedures to build a warehouse IC.WRH.PROC Arms transfers, Exports MS.MIL.XPRT.KD Time required to build a warehouse IC.WRH.DURS Arms transfers, Imports MS.MIL.MPRT.KD Time required to get electricity IC.ELC.TIME Number of procedures to enforce a contract IC.LGL.PROC 5.8 Fragile situations Time required to enforce a contract IC.LGL.DURS International Development Association Business disclosure index IC.BUS.DISC.XQ Resource Allocation Index IQ.CPA.IRAI.XQ Time required to resolve insolvency IC.ISV.DURS Peacekeeping troops, police, and military observers VC.PKP.TOTL.UN 5.4 Stock markets Battle related deaths VC.BTL.DETH Market capitalization, $ CM.MKT.LCAP.CD Intentional homicides VC.IHR.PSRC.P5 Market capitalization, % of GDP CM.MKT.LCAP.GD.ZS Military expenditures MS.MIL.XPND.GD.ZS Value of shares traded CM.MKT.TRAD.GD.ZS Losses due to theft, robbery, vandalism, Turnover ratio CM.MKT.TRNR and arson IC.FRM.CRIM.ZS Listed domestic companies CM.MKT.LDOM.NO Firms formally registered when operations started IC.FRM.FREG.ZS S&P/Global Equity Indices CM.MKT.INDX.ZG 82 World Development Indicators 2014 Front ? User guide World view People Environment States and markets 5 Children in employment SL.TLF.0714.ZS Air freight IS.AIR.GOOD.MT.K1 Refugees, By country of origin SM.POP.REFG.OR 5.11 Power and communications Refugees, By country of asylum SM.POP.REFG Electric power consumption per capita EG.USE.ELEC.KH.PC Internally displaced persons VC.IDP.TOTL.HE Electric power transmission and Access to an improved water source SH.H2O.SAFE.ZS distribution losses EG.ELC.LOSS.ZS Access to improved sanitation facilities SH.STA.ACSN Fixed telephone subscriptions IT.MLT.MAIN.P2 Maternal mortality ratio, National estimate SH.STA.MMRT.NE Mobile cellular subscriptions IT.CEL.SETS.P2 Maternal mortality ratio, Modeled estimate SH.STA.MMRT Fixed telephone international voice traffic ..a Under-five mortality rate SH.DYN.MORT Mobile cellular network international voice traffic ..a Depth of food deficit SN.ITK.DFCT Population covered by mobile cellular network ..a Primary gross enrollment ratio SE.PRM.ENRR Fixed telephone sub-basket ..a Mobile cellular sub-basket ..a 5.9 Public policies and institutions Telecommunications revenue ..a International Development Association Resource Allocation Index IQ.CPA.IRAI.XQ Mobile cellular and fixed-line subscribers per employee ..a Macroeconomic management IQ.CPA.MACR.XQ Fiscal policy IQ.CPA.FISP.XQ 5.12 The information age Debt policy IQ.CPA.DEBT.XQ Households with television ..a Economic management, Average IQ.CPA.ECON.XQ Households with a computer ..a Trade IQ.CPA.TRAD.XQ Individuals using the Internet ..a Financial sector IQ.CPA.FINS.XQ Fixed (wired) broadband Internet Business regulatory environment IQ.CPA.BREG.XQ subscriptions IT.NET.BBND.P2 Structural policies, Average IQ.CPA.STRC.XQ International Internet bandwidth ..a Gender equality IQ.CPA.GNDR.XQ Fixed broadband sub-basket ..a Equity of public resource use IQ.CPA.PRES.XQ Secure Internet servers IT.NET.SECR.P6 Building human resources IQ.CPA.HRES.XQ Information and communications Social protection and labor IQ.CPA.PROT.XQ technology goods, Exports TX.VAL.ICTG.ZS.UN Policies and institutions for environmental Information and communications sustainability IQ.CPA.ENVR.XQ technology goods, Imports TM.VAL.ICTG.ZS.UN Policies for social inclusion and equity, Average IQ.CPA.SOCI.XQ Information and communications technology services, Exports BX.GSR.CCIS.ZS Property rights and rule-based governance IQ.CPA.PROP.XQ Quality of budgetary and financial management IQ.CPA.FINQ.XQ 5.13 Science and technology Efficiency of revenue mobilization IQ.CPA.REVN.XQ Research and development (R&D), Researchers SP.POP.SCIE.RD.P6 Quality of public administration IQ.CPA.PADM.XQ Research and development (R&D), Technicians SP.POP.TECH.RD.P6 Transparency, accountability, and Scientific and technical journal articles IP.JRN.ARTC.SC corruption in the public sector IQ.CPA.TRAN.XQ Expenditures for R&D GB.XPD.RSDV.GD.ZS Public sector management and institutions, Average IQ.CPA.PUBS.XQ High-technology exports, $ TX.VAL.TECH.CD High-technology exports, % of manufactured 5.10 Transport services exports TX.VAL.TECH.MF.ZS Total road network IS.ROD.TOTL.KM Charges for the use of intellectual property, Receipts BX.GSR.ROYL.CD Paved roads IS.ROD.PAVE.ZS Charges for the use of intellectual property, Road passengers carried IS.ROD.PSGR.K6 Payments BM.GSR.ROYL.CD Road goods hauled IS.ROD.GOOD.MT.K6 Patent applications filed, Residents IP.PAT.RESD Rail lines IS.RRS.TOTL.KM Patent applications filed, Nonresidents IP.PAT.NRES Railway passengers carried IS.RRS.PASG.KM Trademark applications filed, Total IP.TMK.TOTL Railway goods hauled IS.RRS.GOOD.MT.K6 Port container traffic IS.SHP.GOOD.TU Data disaggregated by sex are available in the World Development Indicators database. Registered air carrier departures worldwide IS.AIR.DPRT a. Available online only as part of the table, not as an individual indicator. Air passengers carried IS.AIR.PSGR Economy States and markets Global links Back World Development Indicators 2014 83 GLOBAL 84 World Development Indicators 2014 Front ? User guide LINKS World view People Environment 6 The world economy is bound together by trade net flows to private nonguaranteed borrowers, in goods and services, financial flows, and and a sharp 41 percent contraction in short-term movements of people. As national economies debt flows. develop, their links expand and grow more com- Unlike debt and direct investment, global plex. The indicators in Global links measure the portfolio equity investment grew in 2012 at a size and direction of these flows and document faster pace than had been expected, resulting the effects of policy interventions, such as in equity inflows that were three times higher tariffs, trade facilitation, and aid flows, on the than in 2011. Inflows to high-income economies development of the world economy. in 2012 were well above their 2011 level, attrib- Volatility in international financial markets utable mainly to investors’ switching from debt was still prevalent in 2012. Concerns about the securities to equity. Flows of portfolio equity to sustainability of public finances, inherited from low- and middle-income economies also rose the financial crisis in the euro area, appear to considerably, as growth prospects remained have affected direct investment. Global foreign good, with high expected returns. direct investment (FDI) inflows dropped 16 per- The sovereign debt crisis in the euro area cent from 2011. FDI flows to high-income econo- continued to restrain international trade. The mies dropped 22 percent, with the euro area slowdown of demand for goods from high- accounting for almost half the fall. But FDI flows income economies, especially euro area to low- and middle-income economies showed economies, slowed the growth in merchandise a more moderate decline of only 6 percent. FDI imports from an annual 19.4 percent in 2011 to flows to low- and middle-income economies were 0.4 percent in 2012. The growth of merchandise around $617 billion in 2012, accounting for an exports also dropped, by nearly 20 percentage increase in the share of world inflows of 17 per- points. But merchandise exports to low- and centage points over the previous five years. middle-income countries rose 4.4 percent from Although more of these economies receive FDI, the previous year, while those to high-income the flows remain highly concentrated among the countries fell 0.8 percent. Brazil, China, India, 10 largest recipients, with Brazil, China, and and the Russian Federation are among the India accounting for more than half. top traders, with China accounting for almost Net debt flows to developing countries fell 70 percent of the total merchandise trade in 9 percent in 2012, to $412 billion, and were East Asia and Pacific. characterized by important shifts in borrowing Official development assistance—a stable patterns and financing sources. Viewed from the source of development financing and buffer borrower, net flows of public and publicly guaran- against the impact of several financial crises— teed debt drove the overall increase in long-term was $133 billion in 2012, or 0.59 percent of debt flows in 2012. They jumped 67 percent to developing countries’ combined gross national $155 billion, in contrast to a 17 percent fall in income, down from 0.66 percent in 2011. Economy States and markets Global links Back World Development Indicators 2014 85 Highlights Bond issuance rises Bond issuance by developing country borrowers ($ billions) Bond issuance from public and private borrowers in developing econo- 150 mies rose to a record $226 billion in 2012, up from $175 billion in All developing, private nonguaranteed All developing, public and publicly guaranteed 2011. The increase was driven mainly by new bond issuances from the Latin America & Caribbean, private nonguaranteed 125 Latin America & Caribbean, public and publicly guaranteed public sector, which rose 30 percent in 2012 as emerging economies Europe & Central Asia, private nonguaranteed Europe & Central Asia, public and publicly guaranteed continued to diversify risk away from banks and pursue different 100 sources of financing after the 2008 crisis. Influenced by purchases of Mexico’s domestically issued sovereign bonds by nonresidents, Latin 75 America and the Caribbean held the largest share, 39 percent, while Europe and Central Asia accounted for the second largest share, 50 25 percent. Private borrowers also saw an increase in bond issuances, but at a more moderate rate of 11 percent in 2012, to $88.1 billion. 25 Private borrowers in Latin America and the Caribbean also claimed the 0 largest share, with Mexico and Brazil dominant bond issuers. 2005 2006 2007 2008 2009 2010 2011 2012 Source: Online table 6.9. Europe and Central Asia: remittances are more resilient than foreign direct investment Inflows of remittances and foreign direct investment, Europe and Inflows of personal remittances yet again proved resilient to economic Central Asia (% of GDP) downturns in Europe and Central Asia, especially when compared with 12 infl ows of foreign direct investment (FDI). Personal remittances 10 received as a percentage of GDP continued a slow but steady path of Foreign direct investment growth, up 1.5 percent in 2012. Despite signs of recovery in 2011, 8 FDI inflows as a percentage of GDP fell 15 percent in 2012, showing that the region had not fully recovered from the financial crisis. The 6 high volatility of FDI inflows is not evident in remittances, where flows have proven more resilient to economic shocks. The greater persis- 4 tence in remittances has proven beneficial for countries in the region 2 that rely heavily on inflows of remittances for economic stability, such Personal remittances as the Kyrgyz Republic, Moldova, and Tajikistan. 0 2007 2008 2009 2010 2011 2012 Source: Online tables 6.9 and 6.13. Capital equity investment in India turns around in 2012 Equity investment flows to India ($ billions) The Indian economy saw net capital equity inflows in 2012 rise 44 per- cent, or 2.7 percent of GDP (up from 1.7 percent in 2011). Direct invest- 50 Foreign direct investment ment inflows in 2012 reflected the country’s slow economic growth and high inflation rate, which shook investor confidence. Even though foreign direct investment flows fell by a third in 2012 to $24 billion, the lowest 25 since 2005, India remained the third most important developing country destination for investment flows, after China and Brazil. The downturn was partly offset by a considerable turnaround in portfolio equity flows. In January 2012 India began allowing qualified foreign investors to invest 0 directly in the Indian stock market. Portfolio equity investment inflows Portfolio equity shot up to a remarkable $23 billion from a depletion of $40 billion in 2011, thanks mainly to qualified foreign investor purchases of equities –25 in the Indian stock market. 2005 2006 2007 2008 2009 2010 2011 2012 Source: Online table 6.9. 86 World Development Indicators 2014 Front ? User guide World view People Environment Debt indicators improve in Europe and Central Asia Europe and Central Asia, the most indebted region, recorded the Debt ratios for Europe and Central Asia (%) highest external debt outstanding ratio to gross national income 200 (GNI), 68.3 percent, in 2012—three times the comparable ratio for all developing countries combined. Similarly, external debt stock as a percentage of exports at the end of 2012, 144.7 percent, was 150 twice the developing country average. But despite a mild deteriora- External debt stock to exports tion in 2012, the ratio of external debt stock to GNI has declined 100 12 percentage points since 2009 while the ratio of external debt stock to exports declined 23 percentage points. The main drivers External debt stock to GNI of growth and higher export earnings are the oil exporters, notably 50 Kazakhstan and Turkey, followed by Hungary and Ukraine. Investment in Kazakhstan’s hydrocarbon sector in 2012 tremendously increased Debt service to exports production and exports. 0 2007 2008 2009 2010 2011 2012 Source: Online table 6.8. The Syrian refugee population continues to rise The refugee population by country of origin has remained fairly steady Refugee population by origin, top five (millions) since 2004 among developing countries. For over a decade five coun- 3 tries accounted for more than 50 percent of refugees from develop- ing countries: Afghanistan, Somalia, Iraq, Sudan, and the Democratic Republic of Congo. But conflict in Middle East and North Africa has changed that. In 2011 the Syrian Arab Republic was ranked 32nd, with 2 fewer than 20,000 refugees, but by 2012 the number of refugees flee- ing the country had grown 35 times to almost 730,000, fourth highest among developing countries. And the increase is expected to continue. 1 According to the Office of the UN High Commissioner for Refugees (2013), an estimated 1.3 million people from Syria sought refuge in 2011 2012 surrounding countries in the first half of 2013. 0 Sudan Syrian Arab Republic Iraq Somalia Afghanistan Source: Online table 6.13. Commodity prices fall in 2013 Except for energy, commodity price indexes continued to fall in 2013. Change in commodity price indices (%) In real terms (2005) the biggest declines were in fertilizers (16 percent) 50 Fertilizers and precious metals (16 percent), followed by agriculture (6 percent) Precious metals and metals and minerals (4 percent). Even though fertilizer prices have Agriculture Metals and minerals more than doubled from a decade ago, the price index has declined Energy 46 percent from its peak in 2008 (from 197 to 107). Energy and fertil- 25 izer prices typically move together because natural gas is a key input for fertilizer. But the correlation has reversed with U.S. natural gas trading at 80 percent below crude oil. Precious metals saw their first 0 price decline in 11 years in 2013. The gold market, driven mainly by China and India, has fallen due to India’s restrictions on gold imports. China, despite overtaking India as the world’s largest gold consumer, is not expected to offset the weak physical demand from India (World –25 2010 2011 2012 2013 Bank 2014). Source: Online table 6.5. Economy States and markets Global links Back World Development Indicators 2014 87 6 Global links Merchandise Net barter Inbound Net official Net Personal Foreign Portfolio Total Total debt trade terms of tourism development migration remittances, direct equity external service trade index expenditure assistance received investment debt stock % of exports of goods, services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions income 2012 2012 2012 2012 2010–15 2012 2012 2012 2012 2012 Afghanistan 32.0 139.1 3.2 32.8 –400 385 94 2 2,709 0.3 Albania 54.2 96.2 45.9 2.7 –50 1,027 1,265 13 6,934 7.1 Algeria 58.7 217.3 0.4 0.1 –50 213 1,602 .. 5,643 1.1 American Samoa .. 129.0 .. .. .. .. .. .. .. .. Andorra .. .. .. .. .. .. .. .. .. .. Angola 85.0 257.6 1.0 0.2 66 0 –6,898 .. 22,171 5.9 Antigua and Barbuda 51.6 64.2 .. 0.2 0 21 71 .. .. .. Argentina 31.5 130.3 5.9 0.0 –100 573 12,128 876 121,013 13.2 Armenia 57.2 117.6 20.1 2.6 –50 2,123 489 2 7,608 30.9 Aruba .. 122.0 44.9 .. 1 5 –140 0 .. .. Australia 33.8 184.8 11.0 .. 750 1,827 56,595 15,174 .. .. Austria 87.3 86.9 9.9 .. 150 2,754 4,144 936 .. .. Azerbaijan 63.5 199.9 7.2 0.6 0 1,990 5,293 0 9,712 5.1 Bahamas, The 54.6 88.5 65.7 .. 10 .. 360 .. .. .. Bahrain 116.6 129.0 7.6 .. 22 .. 891 1,383 .. .. Bangladesh 50.9 59.2 0.4 1.7 –2,041 14,085 1,178 91 26,130 5.4 Barbados 55.4 107.6 .. .. 2 .. 356 .. .. .. Belarus 146.0 100.7 1.9 0.2 –10 1,053 1,464 –4 34,173 9.5 Belgium 182.3 94.2 3.1 .. 150 10,123 –1,917 4,570 .. .. Belize .. 93.8 28.7 .. 8 76 194 .. 1,241 11.3 Benin 47.6 117.9 .. 6.8 –10 .. 159 .. 2,055 .. Bermuda 16.8 62.1 32.6 .. .. 1,191 133 –10 .. .. Bhutan 90.5 134.3 13.5 9.6 10 18 10 .. 1,459 17.8 Bolivia 70.3 179.1 4.8 2.6 –125 1,111 1,060 .. 6,909 5.3 Bosnia and Herzegovina 86.9 98.8 12.8 3.2 –5 1,849 350 .. 10,577 18.4 Botswana 96.5 85.0 0.5 0.5 20 18 293 –9 2,488 0.8 Brazil 21.1 128.9 2.4 0.1 –190 2,583 76,111 5,600 440,478 15.5 Brunei Darussalam 100.0 226.5 .. .. 2 .. 850 .. .. .. Bulgaria 116.6 107.4 12.4 .. –50 1,449 2,095 5 50,750 13.0 Burkina Faso 51.3 126.9 .. 10.8 –125 .. 40 .. 2,506 .. Burundi 36.8 149.1 1.2 21.2 –20 46 1 .. 663 8.5 Cabo Verde 44.8 108.9 60.6 13.3 –17 167 74 .. 1,261 4.6 Cambodia 136.8 75.2 23.4 6.1 –175 256 1,557 .. 5,716 1.5 Cameroon 45.8 156.6 5.1 2.4 –50 210 526 0 3,672 3.1 Canada 52.2 118.5 3.8 .. 1,100 1,206 43,085 949 .. .. Cayman Islands .. 82.9 .. .. .. .. 4,234 .. .. .. Central African Republic 24.3 68.8 .. 10.4 10 .. 71 .. 552 .. Chad 50.4 220.6 .. 4.9 –120 .. 323 .. 1,831 .. Channel Islands .. .. .. .. 4 .. .. .. .. .. Chile 58.6 182.4 3.5 0.0 30 .. 30,323 5,222 .. .. China 47.0 71.8 2.5 0.0 –1,500 39,221 253,475 29,903 754,009 3.3 Hong Kong SAR, China 397.9 96.0 6.7 .. 150 368 74,584 25,006 .. .. Macao SAR, China 23.2 92.9 94.2 .. 35 46 4,261 .. .. .. Colombia 32.3 151.1 4.9 0.2 –120 4,019 15,649 3,778 79,051 22.0 Comoros 54.5 80.3 .. 11.5 –10 .. 17 .. 251 .. Congo, Dem. Rep. 72.1 143.1 .. 17.8 –75 12 2,892 .. 5,651 3.2 Congo, Rep. 118.4 221.0 .. 1.3 –45 .. 2,758 .. 2,829 .. 88 World Development Indicators 2014 Front ? User guide World view People Environment Global links 6 Merchandise Net barter Inbound Net official Net Personal Foreign Portfolio Total Total debt trade terms of tourism development migration remittances, direct equity external service trade index expenditure assistance received investment debt stock % of exports of goods, services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions income 2012 2012 2012 2012 2010–15 2012 2012 2012 2012 2012 Costa Rica 64.2 77.7 20.0 0.1 64 562 2,636 .. 14,458 17.6 Côte d’Ivoire 89.7 144.3 .. 11.1 50 .. 478 .. 9,871 .. Croatia 55.9 98.1 36.2 .. –20 1,437 1,395 –174 .. .. Cuba .. 144.6 .. .. –140 .. .. .. .. .. Curaçao .. .. .. .. 14 30 57 .. .. .. Cyprus 39.8 94.2 27.8 .. 35 112 1,247 742 .. .. Czech Republic 151.3 101.0 5.2 .. 200 2,026 10,581 –148 .. .. Denmark 63.2 99.8 3.6 .. 75 1,257 1,269 4,784 .. .. Djibouti .. 82.0 4.6 .. –16 33 110 .. 808 8.8 Dominica 49.0 103.1 57.2 5.5 .. 23 20 .. 284 10.0 Dominican Republic 45.0 91.5 39.3 0.5 –140 3,615 3,857 .. 16,851 14.0 Ecuador 58.5 134.7 3.9 0.2 –30 2,456 591 5 16,931 9.8 Egypt, Arab Rep. 37.7 156.2 22.3 0.7 –216 19,236 2,798 –983 40,000 6.6 El Salvador 65.4 90.2 14.7 1.0 –225 3,927 467 .. 13,279 18.7 Equatorial Guinea 121.5 244.8 .. 0.1 20 .. 2,115 .. .. .. Eritrea 45.9 98.5 .. 4.4 55 .. 74 .. 994 .. Estonia 150.9 93.9 7.9 .. 0 401 1,648 –151 .. .. Ethiopia 36.1 130.6 33.0 7.9 –60 624 279 .. 10,462 7.2 Faeroe Islands .. 104.0 .. .. .. .. .. .. .. .. Fiji 86.8 108.1 40.5 2.9 –29 191 267 .. 732 .. Finland 60.1 87.1 5.3 .. 50 866 4,332 3,097 .. .. France 47.6 88.8 8.3 .. 650 21,676 28,122 36,077 .. .. French Polynesia .. 78.7 .. .. –1 .. 87 .. .. .. Gabon 86.5 226.0 .. 0.4 5 .. 702 .. 2,870 .. Gambia, The 52.9 92.1 29.6 15.9 –13 141 34 .. 513 7.1 Georgia 64.9 134.2 26.0 4.2 –125 1,770 831 74 13,426 23.3 Germany 75.1 95.3 3.0 .. 550 13,964 27,221 –3,746 .. .. Ghana 73.7 172.2 6.9 4.7 –100 138 3,295 .. 12,436 4.2 Greece 37.9 87.2 21.0 .. 50 681 1,663 –66 .. .. Greenland .. 79.0 .. .. .. .. .. .. .. .. Grenada 48.3 91.1 56.8 1.1 –4 29 30 .. 591 7.7 Guam .. 81.1 .. .. 0 .. .. .. .. .. Guatemala 54.0 87.7 11.3 0.6 –75 5,035 1,150 .. 14,975 10.9 Guinea 65.7 103.7 0.1 6.5 –10 66 605 .. 1,097 7.0 Guinea-Bissau 46.2 81.6 .. 9.6 –10 .. 16 .. 279 .. Guyana 112.3 128.3 3.8 4.0 –33 469 276 .. 1,974 8.7 Haiti 46.2 67.9 16.3 16.1 –175 1,612 179 .. 1,154 0.3 Honduras 103.6 84.3 10.0 3.3 –50 2,909 1,068 .. 4,987 13.8 Hungary 159.8 92.6 5.3 .. 75 2,144 9,356 1,137 203,757 84.6 Iceland 72.4 87.3 10.7 .. 5 19 1,086 –3 .. .. India 42.1 127.4 4.1 0.1 –2,294 68,821 23,996 22,809 379,099 6.8 Indonesia 43.1 129.2 4.5 0.0 –700 7,212 19,618 1,698 254,899 17.1 Iran, Islamic Rep. 27.5 194.5 .. .. –300 .. 4,870 .. 11,477 .. Iraq 70.1 227.1 1.7 0.6 450 271 3,400 7 .. .. Ireland 85.1 92.7 4.0 .. 50 700 40,962 105,422 .. .. Isle of Man .. .. .. .. .. .. .. .. .. .. Israel .. 97.6 6.7 .. –76 685 9,481 290 .. .. Economy States and markets Global links Back World Development Indicators 2014 89 6 Global links Merchandise Net barter Inbound Net official Net Personal Foreign Portfolio Total Total debt trade terms of tourism development migration remittances, direct equity external service trade index expenditure assistance received investment debt stock % of exports of goods, services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions income 2012 2012 2012 2012 2010–15 2012 2012 2012 2012 2012 Italy 48.9 94.8 7.4 .. 900 7,326 6,686 20,835 .. .. Jamaica 56.3 87.1 46.8 0.1 –80 2,145 229 –1 14,333 38.2 Japan 28.3 60.5 1.8 .. 350 2,540 2,525 34,941 .. .. Jordan 92.1 83.7 33.0 4.6 400 3,574 1,497 53 18,632 6.9 Kazakhstan 67.2 231.3 1.6 0.1 0 171 15,117 –418 137,014 23.5 Kenya 55.1 89.9 18.2 6.5 –50 1,214 259 26 11,569 5.1 Kiribati 62.9 96.6 .. 25.0 –1 .. –2 .. .. .. Korea, Dem. People’s Rep. .. 85.9 .. .. 0 .. 79 .. .. .. Korea, Rep. 94.5 61.8 3.0 .. 300 8,474 4,999 16,925 .. .. Kosovo .. .. .. 8.9 .. 1,059 293 1 2,002 8.8 Kuwait 80.2 227.8 0.6 .. 300 8 1,851 –41 .. .. Kyrgyz Republic 112.2 108.2 23.8 7.8 –175 2,031 372 0 6,026 10.9 Lao PDR 54.2 109.4 16.2 4.6 –75 59 294 6 6,372 8.2 Latvia 109.2 102.9 6.3 .. –10 730 1,076 4 .. .. Lebanon 64.2 97.9 22.6 1.7 500 6,918 3,678 –239 28,950 14.2 Lesotho 151.2 77.7 4.4 10.3 –20 554 198 .. 860 2.3 Liberia 88.0 138.6 .. 36.1 –20 .. 1,354 .. 487 .. Libya .. 201.4 .. .. –239 .. .. .. .. .. Liechtenstein .. .. .. .. .. .. .. .. .. .. Lithuania 145.6 93.2 4.0 .. –28 1,508 574 –51 .. .. Luxembourg 84.7 75.8 5.2 .. 26 1,681 27,878 161,691 .. .. Macedonia, FYR 109.4 88.7 5.5 1.6 –5 394 283 –6 6,678 15.1 Madagascar 45.6 80.2 .. 3.9 –5 .. 895 .. 2,896 .. Malawi 85.6 95.9 2.7 28.4 0 28 129 1 1,314 2.0 Malaysia 139.0 101.3 7.6 0.0 450 1,320 9,734 .. 103,950 3.5 Maldives 84.1 102.0 79.9 3.1 0 3 284 0 1,027 3.8 Mali 49.1 172.1 .. 10.2 –302 .. 310 .. 3,073 .. Malta 115.9 125.9 15.9 .. 5 33 599 3 .. .. Marshall Islands 95.9 106.4 .. 34.7 .. .. 38 .. .. .. Mauritania 126.2 153.1 .. 10.0 –20 .. 1,204 .. 3,348 4.9 Mauritius 74.9 70.9 29.2 1.7 0 1 361 6,840 4,459 2.4 Mexico 63.8 109.1 3.4 0.0 –1,200 23,366 15,453 10,038 354,897 17.7 Micronesia, Fed. Sts. 75.1 98.3 .. 33.5 –8 .. 1 .. .. .. Moldova 101.7 101.5 10.6 6.1 –103 1,786 185 14 6,135 15.1 Monaco .. .. .. .. .. .. .. .. .. .. Mongolia 108.3 206.0 9.0 4.7 –15 320 4,452 15 5,080 4.5 Montenegro 64.2 .. 50.3 2.3 –3 333 618 0 2,833 13.6 Morocco 68.3 145.4 26.3 1.6 –450 6,508 2,842 –108 33,816 11.2 Mozambique 76.5 100.2 5.8 14.8 –25 220 5,238 .. 4,788 1.6 Myanmar .. 112.8 .. .. –100 .. 2,243 .. 2,563 .. Namibia 83.0 122.9 .. 2.1 –3 .. 357 .. .. .. Nepal 39.3 77.7 19.6 4.0 –401 4,793 92 .. 3,818 10.3 Netherlands 161.8 93.1 3.2 .. 50 1,617 6,684 3,674 .. .. New Caledonia .. 195.9 .. .. 6 .. 1,588 .. .. .. New Zealand 44.1 129.4 10.7 .. 75 .. 2,209 442 .. .. Nicaragua 81.2 82.4 8.5 5.2 –120 1,016 805 0 8,858 12.3 Niger 65.0 169.0 .. 13.5 –28 .. 793 .. 2,340 .. 90 World Development Indicators 2014 Front ? User guide World view People Environment Global links 6 Merchandise Net barter Inbound Net official Net Personal Foreign Portfolio Total Total debt trade terms of tourism development migration remittances, direct equity external service trade index expenditure assistance received investment debt stock % of exports of goods, services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions income 2012 2012 2012 2012 2010–15 2012 2012 2012 2012 2012 Nigeria 62.8 221.8 0.7 0.8 –300 20,633 7,101 10,003 10,077 0.3 Northern Mariana Islands .. 84.8 .. .. .. .. 5 .. .. .. Norway 49.4 161.6 2.6 .. 150 767 22,951 965 .. .. Oman 103.7 244.2 3.2 .. 1,030 39 1,514 1,373 .. .. Pakistan 30.5 53.9 3.2 0.9 –1,634 14,007 854 178 61,867 14.9 Palau 64.4 105.3 .. 7.3 .. .. 5 .. .. .. Panama 108.7 86.2 13.6 0.2 29 402 3,383 .. 12,294 8.7 Papua New Guinea 76.7 193.1 .. 4.4 0 .. 29 .. 23,128 .. Paraguay 73.5 110.5 2.1 0.4 –40 634 363 .. 6,331 6.3 Peru 43.3 163.7 6.5 0.2 –300 2,788 12,244 –32 54,148 12.5 Philippines 46.9 65.6 7.6 0.0 –700 24,641 2,797 1,728 61,390 8.0 Poland 77.5 97.1 5.2 .. –38 6,935 6,701 3,888 .. .. Portugal 61.4 91.3 17.6 .. 100 3,904 13,377 –8,518 .. .. Puerto Rico .. .. .. .. –104 .. .. .. .. .. Qatar 85.5 217.8 5.1 .. 500 803 327 –925 .. .. Romania 75.5 110.7 3.0 .. –45 3,674 2,024 403 131,889 34.2 Russian Federation 42.9 248.9 3.0 .. 1,100 5,788 50,661 1,162 .. .. Rwanda 34.8 214.9 33.2 12.5 –45 182 160 7 1,269 2.2 Samoa 61.7 81.1 61.1 18.6 –13 159 24 .. 423 5.3 San Marino .. .. .. .. .. .. .. .. .. .. São Tomé and Príncipe 57.3 106.8 50.4 18.7 –2 6 22 .. 202 6.9 Saudi Arabia 74.6 215.5 2.1 .. 300 246 12,182 .. .. .. Senegal 63.7 109.1 .. 7.8 –100 .. 338 .. 4,900 .. Serbia 81.0 104.2 7.0 3.0 –100 2,763 355 –24 34,438 36.7 Seychelles 114.9 78.1 2.8 3.3 –2 1 12 .. 2,024 64.3 Sierra Leone 63.2 58.1 3.1 11.7 –21 61 548 7 1,121 1.5 Singapore 286.9 80.6 3.5 .. 400 .. 56,651 2,851 .. .. Sint Maarten .. .. .. .. .. 13 14 .. .. .. Slovak Republic 174.7 92.3 2.7 .. 15 1,928 1,527 0 .. .. Slovenia 141.3 94.2 8.3 .. 22 644 –227 149 .. .. Solomon Islands 96.2 89.7 10.5 43.6 –12 17 68 .. 228 4.5 Somalia .. 107.8 .. .. –150 .. 107 .. 3,055 .. South Africa 54.6 145.5 9.8 0.3 –100 1,085 4,644 –679 137,501 7.9 South Sudan .. .. .. 17.0 865 .. .. .. .. .. Spain 47.2 88.5 14.8 .. 600 9,633 36,161 9,819 .. .. Sri Lanka 48.1 75.0 12.9 0.8 –317 6,000 898 305 25,382 13.3 St. Kitts and Nevis 35.9 71.4 37.5 3.0 .. 45 100 .. .. .. St. Lucia 71.9 91.4 56.9 2.2 0 30 109 .. 473 6.9 St. Martin .. .. .. .. .. .. .. .. .. .. St. Vincent & the Grenadines 55.3 107.4 48.5 1.2 –5 30 125 .. 267 16.6 Sudan 20.8 .. 19.4 1.7a –800a 401 2,488 2 21,840 8.9 Suriname 83.8 134.8 2.9 0.8 –5 8 66 .. .. .. Swaziland 102.8 110.2 .. 2.6 –6 31 90 .. 460 2.2 Sweden 63.9 92.3 5.0 .. 200 812 4,039 3,968 .. .. Switzerland 67.1 80.3 4.8 .. 320 3,039 2,748 14,554 .. .. Syrian Arab Republic .. 146.8 .. .. –1,500 .. .. .. 4,736 .. Tajikistan 67.3 99.3 3.7 5.2 –100 3,626 198 .. 3,648 25.5 Economy States and markets Global links Back World Development Indicators 2014 91 6 Global links Merchandise Net barter Inbound Net official Net Personal Foreign Portfolio Total Total debt trade terms of tourism development migration remittances, direct equity external service trade index expenditure assistance received investment debt stock % of exports of goods, services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions income 2012 2012 2012 2012 2010–15 2012 2012 2012 2012 2012 Tanzania 58.8 145.2 18.8 10.1 –150 67 1,707 4 11,581 1.9 Thailand 130.4 93.2 13.7 0.0 100 4,713 10,689 2,663 134,223 4.1 Timor-Leste 29.5 .. 20.5 5.8 –75 114 19 .. .. .. Togo 73.4 28.7 .. 7.2 –10 .. 166 .. 754 .. Tonga 47.9 81.9 .. 16.1 –8 60 8 .. 197 7.8 Trinidad and Tobago 96.5 156.9 .. .. –15 .. 2,527 .. .. .. Tunisia 90.8 97.1 13.2 2.3 –33 2,266 1,554 –15 25,475 11.5 Turkey 49.3 87.2 15.6 0.4 350 1,015 12,519 6,274 337,492 26.1 Turkmenistan 73.1 238.5 .. 0.1 –25 .. 3,159 .. 492 .. Turks and Caicos Islands .. 68.4 .. .. .. .. .. .. .. .. Tuvalu 63.4 .. .. 42.3 .. .. .. .. .. .. Uganda 41.6 110.0 23.4 8.5 –150 733 1,721 5 3,769 1.4 Ukraine 86.9 118.1 6.9 0.4 –40 8,449 7,833 516 135,067 31.5 United Arab Emirates 135.5 186.1 .. .. 514 .. 9,602 .. .. .. United Kingdom 46.4 99.4 6.0 .. 900 1,776 56,136 –27,555 .. .. United States 23.9 94.7 9.0 .. 5,000 6,285 203,790 232,063 .. .. Uruguay 40.8 104.2 16.7 0.0 –30 97 2,907 .. .. .. Uzbekistan 43.2 172.1 .. 0.5 –200 .. 1,094 .. 8,853 .. Vanuatu 44.5 88.0 76.5 13.6 0 22 38 .. 369 2.1 Venezuela, RB 41.3 262.1 0.9 0.0 40 118 2,199 –50 72,097 5.6 Vietnam 146.6 100.5 5.5 2.8 –200 .. 8,368 1,887 59,133 4.4 Virgin Islands (U.S.) .. .. .. .. –4 .. .. .. .. .. West Bank and Gaza .. .. .. .. –44 .. .. .. .. .. Yemen, Rep. 57.5 167.7 .. 2.1 –135 .. 349 .. 7,555 .. Zambia 80.4 183.6 1.6 4.9 –40 73 1,066 26 5,385 2.2 Zimbabwe 83.7 105.0 .. 10.6 400 .. 400 .. 7,713 .. World 50.8 .. 5.8b 0.2c 0 478,461 1,509,565 776,000 .. .. Low income 55.1 .. 12.4 8.0 –3,647 30,184 24,291 142 134,345 4.8 Middle income 50.5 .. 5.3 0.2 –13,345 320,209 592,608 104,290 4,695,263 9.9 Lower middle income 51.1 .. 6.3 0.8 –11,030 199,670 103,112 38,172 1,273,289 9.7 Upper middle income 50.4 .. 5.1 0.1 –2,314 120,539 489,495 66,118 3,421,974 10.0 Low & middle income 50.6 .. 5.4 0.6 –16,991 350,393 616,899 104,432 4,829,608 9.8 East Asia & Pacific 54.2 .. 4.4 0.1 –3,061 78,304 313,801 37,899 1,412,411 4.5 Europe & Central Asia 72.6 .. 8.6 0.6 –661 38,706 65,194 7,988 1,149,505 32.9 Latin America & Carib. 38.2 .. 4.7 0.2 –3,017 59,537 150,393 20,214 1,257,876 15.0 Middle East & N. Africa 47.5 .. 11.0 .. –1,632 39,019 22,699 –1,286 177,092 3.9 South Asia 41.5 .. 4.5 0.6 –7,076 108,112 27,405 23,386 501,491 7.3 Sub-Saharan Africa 61.6 .. 6.6 3.8 –1,545 26,715 37,406 16,232 331,234 4.5 High income 50.9 .. 5.9 0.0 16,941 128,067 892,666 671,568 .. .. Euro area 72.1 .. 6.1 0.0 3,402 78,775 201,185 334,538 .. .. a. Excludes South Sudan. b. Calculated using the World Bank’s weighted aggregation methodology (see Statistical methods) and thus may differ from data reported by the World Tourism Organization. c. Based on the World Bank classification of economies and thus may differ from data reported by the Organisation for Economic Co-operation and Development. 92 World Development Indicators 2014 Front ? User guide World view People Environment Global links 6 About the data Starting with World Development Indicators 2013, the World Bank Official development assistance changed its presentation of balance of payments data to conform Data on official development assistance received refer to aid to to the International Monetary Fund’s (IMF) Balance of Payments eligible countries from members of the Organisation of Economic Manual, 6th edition (BPM6). The historical data series based on Co-operation and Development’s (OECD) Development Assistance BPM5 ends with data for 2005. Balance of payments data from Committee (DAC), multilateral organizations, and non-DAC donors. 2005 forward have been presented in accord with the BPM6 meth- Data do not reflect aid given by recipient countries to other develop- odology, which can be accessed at www.imf.org/external/np/sta ing countries or distinguish among types of aid (program, project, /bop/bop.htm. or food aid; emergency assistance; or postconflict peacekeeping assistance), which may have different effects on the economy. Trade in goods Ratios of aid to gross national income (GNI), gross capital for- Data on merchandise trade are from customs reports of goods mation, imports, and government spending measure a country’s moving into or out of an economy or from reports of fi nancial dependency on aid. Care must be taken in drawing policy conclu- transactions related to merchandise trade recorded in the balance sions. For foreign policy reasons some countries have traditionally of payments. Because of differences in timing and defi nitions, received large amounts of aid. Thus aid dependency ratios may trade fl ow estimates from customs reports and balance of pay- reveal as much about a donor’s interests as about a recipient’s ments may differ. Several international agencies process trade needs. Increases in aid dependency ratios can reflect events affect- data, each correcting unreported or misreported data, leading to ing both the numerator (aid) and the denominator (GNI). other differences. The most detailed source of data on interna- Data are based on information from donors and may not be con- tional trade in goods is the United Nations Statistics Division’s sistent with information recorded by recipients in the balance of Commodity Trade Statistics (Comtrade) database. The IMF and payments, which often excludes all or some technical assistance— the World Trade Organization also collect customs-based data particularly payments to expatriates made directly by the donor. on trade in goods. Similarly, grant commodity aid may not always be recorded in trade The “terms of trade” index measures the relative prices of a coun- data or in the balance of payments. DAC statistics exclude aid for try’s exports and imports. The most common way to calculate terms military and antiterrorism purposes. The aggregates refer to World of trade is the net barter (or commodity) terms of trade index, or Bank classifications of economies and therefore may differ from the ratio of the export price index to the import price index. When a those reported by the OECD. country’s net barter terms of trade index increases, its exports have become more expensive or its imports cheaper. Migration and personal remittances The movement of people, most often through migration, is a signifi - Tourism cant part of global integration. Migrants contribute to the economies Tourism is defined as the activity of people traveling to and staying of both their host country and their country of origin. Yet reliable sta- in places outside their usual environment for no more than one year tistics on migration are difficult to collect and are often incomplete, for leisure, business, and other purposes not related to an activity making international comparisons a challenge. remunerated from within the place visited. Data on inbound and Since data on emigrant stock is difficult for countries to collect, outbound tourists refer to the number of arrivals and departures, the United Nations Population Division provides data on net migra- not to the number of unique individuals. Thus a person who makes tion, taking into account the past migration history of a country or several trips to a country during a given period is counted each area, the migration policy of a country, and the influx of refugees time as a new arrival. Data on inbound tourism show the arrivals of in recent periods to derive estimates of net migration. The data to nonresident tourists (overnight visitors) at national borders. When calculate these estimates come from various sources, including data on international tourists are unavailable or incomplete, the border statistics, administrative records, surveys, and censuses. table shows the arrivals of international visitors, which include tour- When there are insufficient data, net migration is derived through ists, same-day visitors, cruise passengers, and crew members. The the difference between the growth rate of a country’s population aggregates are calculated using the World Bank’s weighted aggrega- over a certain period and the rate of natural increase of that popu- tion methodology (see Statistical methods) and differ from the World lation (itself being the difference between the birth rate and the Tourism Organization’s aggregates. death rate). For tourism expenditure, the World Tourism Organization uses bal- Migrants often send funds back to their home countries, which are ance of payments data from the IMF supplemented by data from recorded as personal transfers in the balance of payments. Personal individual countries. These data, shown in the table, include travel transfers thus include all current transfers between resident and and passenger transport items as defined by the BPM6. When the nonresident individuals, independent of the source of income of the IMF does not report data on passenger transport items, expenditure sender (irrespective of whether the sender receives income from data for travel items are shown. labor, entrepreneurial or property income, social benefi ts, or any Economy States and markets Global links Back World Development Indicators 2014 93 6 Global links other types of transfers or disposes of assets) and the relationship by different parties during their lives. Negotiability allows investors between the households (irrespective of whether they are related to diversify their portfolios and to withdraw their investment read- or unrelated individuals). ily. Included in portfolio investment are investment fund shares or Compensation of employees refers to the income of border, units (that is, those issued by investment funds) that are evidenced seasonal, and other short-term workers who are employed in an by securities and that are not reserve assets or direct investment. economy where they are not resident and of residents employed by Although they are negotiable instruments, exchange-traded financial nonresident entities. Compensation of employees has three main derivatives are not included in portfolio investment because they components: wages and salaries in cash, wages and salaries in are in their own category. kind, and employers’ social contributions. Personal remittances are the sum of personal transfers and compensation of employees. External debt External indebtedness affects a country’s creditworthiness and Equity flows investor perceptions. Data on external debt are gathered through the Equity flows comprise foreign direct investment (FDI) and portfolio World Bank’s Debtor Reporting System (DRS). Indebtedness is cal- equity. The internationally accepted definition of FDI (from BPM6) culated using loan-by-loan reports submitted by countries on long- includes the following components: equity investment, including term public and publicly guaranteed borrowing and using information investment associated with equity that gives rise to control or influ- on short-term debt collected by the countries, from creditors through ence; investment in indirectly influenced or controlled enterprises; the reporting systems of the Bank for International Settlements, or investment in fellow enterprises; debt (except selected debt); and based on national data from the World Bank’s Quarterly External reverse investment. The Framework for Direct Investment Relation- Debt Statistics. These data are supplemented by information from ships provides criteria for determining whether cross-border owner- major multilateral banks and official lending agencies in major credi- ship results in a direct investment relationship, based on control tor countries. Currently, 124 developing countries report to the DRS. and influence. Debt data are reported in the currency of repayment and compiled Direct investments may take the form of greenfield investment, and published in U.S. dollars. End-of-period exchange rates are used where the investor starts a new venture in a foreign country by con- for the compilation of stock figures (amount of debt outstanding), structing new operational facilities; joint venture, where the inves- and projected debt service and annual average exchange rates are tor enters into a partnership agreement with a company abroad to used for the flows. Exchange rates are taken from the IMF’s Inter- establish a new enterprise; or merger and acquisition, where the national Financial Statistics. Debt repayable in multiple currencies, investor acquires an existing enterprise abroad. The IMF suggests goods, or services and debt with a provision for maintenance of the that investments should account for at least 10 percent of voting value of the currency of repayment are shown at book value. stock to be counted as FDI. In practice many countries set a higher While data related to public and publicly guaranteed debt are threshold. Many countries fail to report reinvested earnings, and the reported to the DRS on a loan-by-loan basis, data on long-term definition of long-term loans differs among countries. private nonguaranteed debt are reported annually in aggregate by Portfolio equity investment is defined as cross-border transac- the country or estimated by World Bank staff for countries. Private tions and positions involving equity securities, other than those nonguaranteed debt is estimated based on national data from the included in direct investment or reserve assets. Equity securities are World Bank’s Quarterly External Debt Statistics. equity instruments that are negotiable and designed to be traded, Total debt service as a share of exports of goods, services, and usually on organized exchanges or “over the counter.” The negotia- primary income provides a measure of a country’s ability to service bility of securities facilitates trading, allowing securities to be held its debt out of export earnings. 94 World Development Indicators 2014 Front ? User guide World view People Environment Global links 6 Definitions Data sources •  Merchandise trade includes all trade in goods and excludes Data on merchandise trade are from the World Trade Organization. trade in services. • Net barter terms of trade index is the percent- Data on trade indexes are from the United Nations Conference on age ratio of the export unit value indexes to the import unit value Trade and Development’s (UNCTAD) annual Handbook of Statistics. indexes, measured relative to the base year 2000. • Inbound tour- Data on tourism expenditure are from the World Tourism Organiza- ism expenditure is expenditures by international inbound visitors, tion’s Yearbook of Tourism Statistics and World Tourism Organization including payments to national carriers for international transport (2013) and updated from its electronic files. Data on net official and any other prepayment made for goods or services received in development assistance are compiled by the OECD (http://stats the destination country. They may include receipts from same-day .oecd.org). Data on net migration are from United Nations Population visitors, except when these are important enough to justify sepa- Division (2013). Data on personal remittances are from the IMF’s rate classifi cation. Data include travel and passenger transport Balance of Payments Statistics Yearbook supplemented by World Bank items as defined by BPM6. When passenger transport items are staff estimates. Data on FDI are World Bank staff estimates based not reported, expenditure data for travel items are shown. Exports on IMF balance of payments statistics and UNCTAD data (http:// refer to all transactions between residents of a country and the rest unctadstat.unctad.org/ReportFolders/reportFolders.aspx). Data on of the world involving a change of ownership from residents to non- portfolio equity are from the IMF’s Balance of Payments Statistics residents of general merchandise, goods sent for processing and Yearbook. Data on external debt are mainly from reports to the World repairs, nonmonetary gold, and services. • Net official development Bank through its DRS from member countries that have received assistance is flows (net of repayment of principal) that meet the DAC International Bank for Reconstruction and Development loans or definition of official development assistance and are made to coun- International Development Assistance credits, with additional infor- tries and territories on the DAC list of aid recipients, divided by World mation from the files of the World Bank, the IMF, the African Develop- Bank estimates of GNI. • Net migration is the net total of migrants ment Bank and African Development Fund, the Asian Development (immigrants less emigrants, including both citizens and noncitizens) Bank and Asian Development Fund, and the Inter-American Devel- during the period. Data are five-year estimates. • Personal remit- opment Bank. Summary tables of the external debt of developing tances, received, are the sum of personal transfers (current trans- countries are published annually in the World Bank’s International fers in cash or in kind made or received by resident households to Debt Statistics and International Debt Statistics database. or from nonresident households) and compensation of employees (remuneration for the labor input to the production process contrib- References uted by an individual in an employer-employee relationship with the IMF (International Monetary Fund). Various issues. International Finan- enterprise). • Foreign direct investment is cross-border investment cial Statistics. Washington, DC. associated with a resident in one economy having control or a signifi - ———. Various years. Balance of Payments Statistics Yearbook. Parts cant degree of influence on the management of an enterprise that is 1 and 2. Washington, DC. resident in another economy. • Portfolio equity is net inflows from UNCTAD (United Nations Conference on Trade and Development). Vari- equity securities other than those recorded as direct investment or ous years. Handbook of Statistics. New York and Geneva. reserve assets, including shares, stocks, depository receipts, and UNHCR (Office of the UN High Commissioner for Refugees). 2013. direct purchases of shares in local stock markets by foreign inves- UNHCR Mid-Year Trends 2013. Geneva. tors • Total external debt stock is debt owed to nonresident credi- United Nations Population Division. 2013. World Population Prospects: tors and repayable in foreign currency, goods, or services by public The 2012 Revision. New York: United Nations, Department of Eco- and private entities in the country. It is the sum of long-term external nomic and Social Affairs. debt, short-term debt, and use of IMF credit. • Total debt service is World Bank. 2014. Global Economic Prospects: Commodity Market the sum of principal repayments and interest actually paid in foreign Outlook. January 2014. Washington, DC. currency, goods, or services on long-term debt; interest paid on ———. Various years. International Debt Statistics. Washington, DC. short-term debt; and repayments (repurchases and charges) to the World Tourism Organization. 2013. Compendium of Tourism Statistics IMF. Exports of goods and services and primary income are the total 2013. Madrid. value of exports of goods and services, receipts of compensation of ———. Various years. Yearbook of Tourism Statistics. Vols. 1 and 2. nonresident workers, and primary investment income from abroad. Madrid. Economy States and markets Global links Back World Development Indicators 2014 95 6 Global links Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/6.1). To view a specific /indicator/TX.QTY.MRCH.XD.WD). 6.1 Growth of merchandise trade Lead time to export LP.EXP.DURS.MD Export volume TX.QTY.MRCH.XD.WD Lead time to import LP.IMP.DURS.MD Import volume TM.QTY.MRCH.XD.WD Documents to export IC.EXP.DOCS Export value TX.VAL.MRCH.XD.WD Documents to import IC.IMP.DOCS Import value TM.VAL.MRCH.XD.WD Liner shipping connectivity index IS.SHP.GCNW.XQ Net barter terms of trade index TT.PRI.MRCH.XD.WD Quality of port infrastructure IQ.WEF.PORT.XQ 6.2 Direction and growth of merchandise trade 6.8 External debt This table provides estimates of the flow of Total external debt, $ DT.DOD.DECT.CD trade in goods between groups of economies. ..a Total external debt, % of GNI DT.DOD.DECT.GN.ZS 6.3 High-income economy trade with low- and Long-term debt, Public and publicly guaranteed DT.DOD.DPPG.CD middle-income economies Long-term debt, Private nonguaranteed DT.DOD.DPNG.CD This table illustrates the importance of developing economies in the global trading Short-term debt, $ DT.DOD.DSTC.CD system. ..a Short-term debt, % of total debt DT.DOD.DSTC.ZS Short-term debt, % of total reserves DT.DOD.DSTC.IR.ZS 6.4 Direction of trade of developing economies Total debt service DT.TDS.DECT.EX.ZS Exports to developing economies within region TX.VAL.MRCH.WR.ZS Present value of debt, % of GNI DT.DOD.PVLX.GN.ZS Exports to developing economies outside region TX.VAL.MRCH.OR.ZS Present value of debt, % of exports of Exports to high-income economies TX.VAL.MRCH.HI.ZS goods, services and primary income DT.DOD.PVLX.EX.ZS Imports from developing economies within region TM.VAL.MRCH.WR.ZS 6.9 Global private financial flows Imports from developing economies outside Foreign direct investment net inflows, $ BX.KLT.DINV.CD.WD region TM.VAL.MRCH.OR.ZS Foreign direct investment net inflows, % Imports from high-income economies TM.VAL.MRCH.HI.ZS of GDP BX.KLT.DINV.WD.GD.ZS Portfolio equity BX.PEF.TOTL.CD.WD 6.5 Primary commodity prices Bonds DT.NFL.BOND.CD This table provides historical commodity Commercial banks and other lendings DT.NFL.PCBO.CD price data. ..a 6.10 Net official financial flows 6.6 Tariff barriers Net financial flows from bilateral sources DT.NFL.BLAT.CD All products, Binding coverage TM.TAX.MRCH.BC.ZS Net financial flows from multilateral Simple mean bound rate TM.TAX.MRCH.BR.ZS sources DT.NFL.MLAT.CD Simple mean tariff TM.TAX.MRCH.SM.AR.ZS World Bank, IDA DT.NFL.MIDA.CD Weighted mean tariff TM.TAX.MRCH.WM.AR.ZS World Bank, IBRD DT.NFL.MIBR.CD Share of tariff lines with international peaks TM.TAX.MRCH.IP.ZS IMF, Concessional DT.NFL.IMFC.CD Share of tariff lines with specific rates TM.TAX.MRCH.SR.ZS IMF, Non concessional DT.NFL.IMFN.CD Primary products, Simple mean tariff TM.TAX.TCOM.SM.AR.ZS Regional development banks, Concessional DT.NFL.RDBC.CD Primary products, Weighted mean tariff TM.TAX.TCOM.WM.AR.ZS Regional development banks, Manufactured products, Simple mean tariff TM.TAX.MANF.SM.AR.ZS Nonconcessional DT.NFL.RDBN.CD Manufactured products, Weighted mean Regional development banks, Other tariff TM.TAX.MANF.WM.AR.ZS institutions DT.NFL.MOTH.CD 6.7 Trade facilitation 6.11 Aid dependency Logistics performance index LP.LPI.OVRL.XQ Net official development assistance (ODA) DT.ODA.ODAT.CD Burden of customs procedures IQ.WEF.CUST.XQ Net ODA per capita DT.ODA.ODAT.PC.ZS 96 World Development Indicators 2014 Front ? User guide World view People Environment Global links 6 Grants, excluding technical cooperation BX.GRT.EXTA.CD.WD 6.13 Movement of people Net migration SM.POP.NETM Technical cooperation grants BX.GRT.TECH.CD.WD International migrant stock SM.POP.TOTL Net ODA, % of GNI DT.ODA.ODAT.GN.ZS Emigration rate of tertiary educated to Net ODA, % of gross capital formation DT.ODA.ODAT.GI.ZS OECD countries SM.EMI.TERT.ZS Net ODA, % of imports of goods and Refugees by country of origin SM.POP.REFG.OR services and income DT.ODA.ODAT.MP.ZS Refugees by country of asylum SM.POP.REFG Net ODA, % of central government expenditure DT.ODA.ODAT.XP.ZS Personal remittances, Received BX.TRF.PWKR.CD.DT Personal remittances, Paid BM.TRF.PWKR.CD.DT 6.12 Distribution of net aid by Development Assistance Committee members 6.14 Travel and tourism Net bilateral aid flows from DAC donors DC.DAC.TOTL.CD International inbound tourists ST.INT.ARVL United States DC.DAC.USAL.CD International outbound tourists ST.INT.DPRT EU institutions DC.DAC.CECL.CD Inbound tourism expenditure, $ ST.INT.RCPT.CD Germany DC.DAC.DEUL.CD Inbound tourism expenditure, % of exports ST.INT.RCPT.XP.ZS France DC.DAC.FRAL.CD Outbound tourism expenditure, $ ST.INT.XPND.CD United Kingdom DC.DAC.GBRL.CD Outbound tourism expenditure, % of Japan DC.DAC.JPNL.CD imports ST.INT.XPND.MP.ZS Netherlands DC.DAC.NLDL.CD Australia DC.DAC.AUSL.CD a. Available online only as part of the table, not as an individual indicator. b. Derived from data elsewhere in the World Development Indicators database. Canada DC.DAC.CANL.CD Sweden DC.DAC.SWEL.CD Other DAC donors ..a,b Economy States and markets Global links Back World Development Indicators 2014 97 98 World Development Indicators 2014 Front ? User guide World view People Environment Primary data documentation As a major user of development data, the World national level may not be suitable for standard- Bank recognizes the importance of data docu- ized international use due to methodological con- mentation to inform users of the methods and cerns or the lack of clear documentation. Delays conventions used by primary data collectors— in reporting data and the use of old surveys as usually national statistical agencies, central the base for current estimates may further com- banks, and customs services—and by interna- promise the quality of data reported. tional organizations, which compile the statistics To meet these challenges and improve the that appear in the World Development Indicators quality of data disseminated, the World Bank database. works closely with other international agencies, This section provides information on sources, regional development banks, donors, and other methods, and reporting standards of the princi- partners to pal demographic, economic, and environmen- • Develop appropriate frameworks, guidance, tal indicators in World Development Indicators. and standards of good practice for statistics. Additional documentation is available online in • Build consensus and define internationally the World Development Indicators database and agreed indicators, such as those for the Mil- from the World Bank’s Bulletin Board on Statisti- lennium Development Goals and the post- cal Capacity at http://data.worldbank.org. 2015 development agenda. The demand for good-quality statistical data • Establish data exchange processes and is ever increasing. Statistics provide the evi- methods. dence needed to improve decisionmaking, docu- • Help countries improve their statistical ment results, and heighten public accountability. capacity. However, differences among data collectors may More information on these activities and give rise to large discrepancies over time, both other data programs is available at http://data within and across countries. Data relevant at the worldbank.org. Economy States and markets Global links Back World Development Indicators 2014 99 Primary data documentation Currency National Balance of payments Government IMF data accounts and trade finance dissem- ination standard Balance of System of SNA Alternative PPP Payments Base Reference National price conversion survey Manual External System Accounting year year Accounts valuation factor year in use debt of trade concept Afghanistan Afghan afghani 2002/03 1993 B A G C G a Albania Albanian lek 1996 1993 B Rolling 6 A G B G Algeria Algerian dinar 1980 1968 B 6 A S B G American Samoa U.S. dollar 1968 S Andorra Euro 1990 1968 S Angola Angolan kwanza 2002 1993 P 1991–96 2005 6 A S B G Antigua and Barbuda East Caribbean dollar 2006 1968 B 6 G B G Argentina Argentine peso 1993 1993 B 1971–84 2005 6 A S C S a Armenia Armenian dram 1996 1993 B 1990–95 2005 6 A S C S Aruba Aruban florin 2000 1993 B 6 S a Australia Australian dollar 2011 2008 B 2011 6 G C S Austria Euro 2005 1993 B Rolling 6 S C S Azerbaijan New Azeri manat 2000 1993 B 1992–95 2005 6 A G C G Bahamas, The Bahamian dollar 2006 1993 B 6 G B G Bahrain Bahraini dinar 1985 1968 P 2005 6 G B G Bangladesh Bangladeshi taka 1995/96 1993 B 2005 6 A G C G Barbados Barbados dollar 1974 1968 B 6 G B G a Belarus Belarusian rubel 2000 1993 B 1990–95 2005 6 A G C S Belgium Euro 2005 1993 B Rolling 6 S C S Belize Belize dollar 2000 1993 B 6 A G B G Benin CFA franc 1985 1968 P 1992 2005 6 A S B G Bermuda Bermuda dollar 2006 1993 B 6 G Bhutan Bhutanese ngultrum 2000 1993 B 2005 6 A G C G Bolivia Bolivian Boliviano 1990 1968 B 1960–85 2005 6 A G C G a Bosnia and Herzegovina Bosnia and Herzegovina 1996 1993 B Rolling 6 A S C G convertible mark Botswana Botswana pula 2006 1993 B 2005 6 A G B G Brazil Brazilian real 2000 1993 B 2005 6 A G C S Brunei Darussalam Brunei dollar 2000 1993 P 2005 S G a Bulgaria Bulgarian lev 2002 1993 B 1978–89, Rolling 6 A S C S 1991–92 Burkina Faso CFA franc 1999 1993 B 1992–93 2005 6 A G B G Burundi Burundi franc 2005 1993 B 2005 6 A S C G Cabo Verde Cabo Verde escudo 2007 1993 P 2005 6 A G B G Cambodia Cambodian riel 2000 1993 B 2005 6 A S B G Cameroon CFA franc 2000 1993 B 2005 6 A S B G Canada Canadian dollar 2005 2008 B 2011 6 G C S Cayman Islands Cayman Islands dollar 2007 1993 G Central African Republic CFA franc 2000 1968 B 2005 6 A S B G Chad CFA franc 2005 1993 B 2005 6 P S G Channel Islands Pound sterling 2003 2007 1968 B Chile Chilean peso 2008 1993 B 2011 6 S C S China Chinese yuan 2000 1993 P 1978–93 2005 6 P S C G a Hong Kong SAR, China Hong Kong dollar 2011 2008 B 2005 6 G C S Macao SAR, China Macao pataca 2011 1993 B 2005 6 G C G Colombia Colombian peso 2005 1993 B 1992–94 2005 6 A G C S Comoros Comorian franc 1990 1968 P 2005 A S G Congo, Dem. Rep. Congolese franc 2000 1968 B 1999–2001 2005 6 A S C G Congo, Rep. CFA franc 1990 1968 P 1993 2005 6 P S C G Costa Rica Costa Rican colon 1991 1993 B 6 A S C S Côte d'Ivoire CFA franc 1996 1968 P 2005 6 E S B G a Croatia Croatian kuna 2005 1993 B Rolling 6 G C S Cuba Cuban peso 2005 1993 B S Curaçao Netherlands Antilles 1993 guilder a Cyprus Euro 2000 1993 B Rolling 6 G C S Czech Republic Czech koruna 2005 1993 B Rolling 6 S C S 100 World Development Indicators 2014 Front ? User guide World view People Environment Latest Latest demographic, Source of most Vital Latest Latest Latest Latest population education, or health recent income registration agricultural industrial trade water census household survey and expenditure data complete census data data withdrawal data Afghanistan 1979 MICS, 2010/11 IHS, 2008 2013/14 2012 2000 Albania 2011 DHS, 2008/09 LSMS, 2012 Yes 2012 2010 2012 2006 Algeria 2008 MICS, 2012 IHS, 1995 2012 2001 American Samoa 2010 Yes 2007 Andorra 2011b Yes 2006 Angola 1970 MIS, 2011 IHS, 2008 2015 2005 Antigua and Barbuda 2011 Yes 2007 2012 2005 Argentina 2010 MICS, 2011/12 IHS, 2012 Yes 2013 2002 2012 2000 Armenia 2011 DHS, 2010 IHS, 2012 Yes 2013/14 2012 2007 Aruba 2010 Yes 2012 Australia 2011 ES/BS, 1994 Yes 2011 2010 2012 2000 Austria 2011b IS, 2000 Yes 2010 2009 2012 2002 Azerbaijan 2009 DHS, 2006 ES/BS, 2012 Yes 2015 2010 2012 2005 Bahamas, The 2010 2012 Bahrain 2010 Yes 2011 2003 Bangladesh 2011 DHS, 2011 IHS, 2010 2008 2007 2008 Barbados 2010 MICS, 2012 Yes 2010 c 2012 2005 Belarus 2009 MICS, 2012 ES/BS, 2012 Yes 2009 2012 2000 Belgium 2011 IHS, 2000 Yes 2010 2009 2012 2007 Belize 2010 MICS, 2011 ES/BS, 2011 2012 2000 Benin 2013 DHS, 2011/12 CWIQ, 2011 2011/12 2010 2001 Bermuda 2010 Yes 2012 Bhutan 2005 MICS, 2010 IHS, 2012 2009 2011 2008 Bolivia 2012 DHS, 2008 IHS, 2009 2013 2001 2012 2000 Bosnia and Herzegovina 2013 MICS, 2011/12 LSMS, 2007 Yes 2012 2009 Botswana 2011 DHS, 1988 ES/BS, 2009/10 2011c 2010 2012 2000 Brazil 2010 WHS, 2003 IHS, 2012 2006 2010 2012 2006 Brunei Darussalam 2011 Yes 2012 1994 Bulgaria 2011 LSMS, 2007 ES/BS, 2007 Yes 2010 2010 2012 2009 Burkina Faso 2006 DHS, 2010 CWIQ, 2009 2010 2011 2001 Burundi 2008 MIS, 2012 CWIQ, 2006 2012 2000 Cabo Verde 2010 DHS, 2005 ES/BS, 2007 Yes 2014 2012 2001 Cambodia 2008 DHS, 2010 IHS, 2011 2013 2000 2012 2006 Cameroon 2005 DHS, 2011 PS, 2007 2002 2012 2000 Canada 2011 LFS, 2000 Yes 2011 2010 2012 1986 Cayman Islands 2010 Yes Central African Republic 2003 MICS, 2010 PS, 2008 2011 2005 Chad 2009 MICS, 2010 PS, 2002/03 2010/11 1995 2005 Channel Islands 2009/11d Yese Chile 2012 IHS, 2011 Yes 2007 2008 2012 2007 China 2010 NSS, 2007 IHS, 2008 2007 2007 2012 2005 Hong Kong SAR, China 2011f Yes 2010 2012 Macao SAR, China 2011 Yes 2010 2012 Colombia 2006 DHS, 2010 IHS, 2012 2013 2010 2012 2000 Comoros 2003 DHS, 2012 IHS, 2004 2009 1999 Congo, Dem. Rep. 1984 DHS, 2013 1-2-3, 2004/05 2005 Congo, Rep. 2007 DHS, 2011/12 CWIQ/PS, 2011 2013 2009 2010 2002 Costa Rica 2011 MICS, 2011 IHS, 2012 Yes 2014 2010 2012 1997 Côte d’Ivoire 1998 DHS, 2011/12 IHS, 2008 2014 2012 2005 Croatia 2011 WHS, 2003 ES/BS, 2008 Yes 2010 2012 2010 Cuba 2012 MICS, 2010/11 Yes 2006 2007 Curaçao Cyprus 2011 Yes 2010 2010 2012 2009 Czech Republic 2011 WHS, 2003 IS, 1996 Yes 2010 2007 2012 2007 Economy States and markets Global links Back World Development Indicators 2014 101 Primary data documentation Currency National Balance of payments Government IMF data accounts and trade finance dissem- ination standard Balance of System of SNA Alternative PPP Payments Base Reference National price conversion survey Manual External System Accounting year year Accounts valuation factor year in use debt of trade concept Denmark Danish krone 2005 1993 B Rolling 6 S C S Djibouti Djibouti franc 1990 1968 B 2005 6 A G G Dominica East Caribbean dollar 2006 1993 B 6 A S B G Dominican Republic Dominican peso 1991 1993 B 6 A G C G Ecuador U.S. dollar 2007 2008 B 2005 6 A G B S Egypt, Arab Rep. Egyptian pound 1991/92 1993 B 2005 6 A G C S El Salvador U.S. dollar 1990 1968 B 6 A S C S Equatorial Guinea CFA franc 2000 1968 B 1965–84 2005 G B Eritrea Eritrean nakfa 2000 1968 B 6 E Estonia Euro 2005 1993 B 1987–95 Rolling 6 S C S Ethiopia Ethiopian birr 2011 1993 B 2005 6 A G B G Faeroe Islands Danish krone 1993 B 6 G Fiji Fijian dollar 2005 1993 B 2005 6 A G B G Finland Euro 2005 1993 B Rolling 6 G C S a France Euro 2005 1993 B Rolling 6 S C S French Polynesia CFP franc 1990/91 1993 S Gabon CFA franc 1991 1993 P 19932005 6 A S G Gambia, The Gambian dalasi 2004 1993 P 2005 6 A G B G a Georgia Georgian lari 1996 1993 B 1990–95 2005 6 A G C S Germany Euro 2005 1993 B Rolling 6 S C S Ghana New Ghanaian cedi 2006 1993 B 1973–87 2005 6 P G B G a Greece Euro 2005 1993 B Rolling 6 S C S Greenland Danish krone 1990 1993 G Grenada East Caribbean dollar 2006 1968 B 6 A S B G Guam U.S. dollar 1993 G Guatemala Guatemalan quetzal 2001 1993 B 6 E S B G Guinea Guinean franc 2003 1993 B 2005 6 E S B G Guinea-Bissau CFA franc 2005 1993 B 2005 6 E G G Guyana Guyana dollar 2006 1993 B 6 A S G Haiti Haitian gourde 1986/87 1968 B 1991 6 A G G Honduras Honduran lempira 2000 1993 B 1988–89 6 A S C G a Hungary Hungarian forint 2005 1993 B Rolling 6 A S C S Iceland Iceland krona 2005 1993 B Rolling 6 G C S India Indian rupee 2004/05 1993 B 2005 6 A G C S Indonesia Indonesian rupiah 2000 1993 P 2005 6 A S B S Iran, Islamic Rep. Iranian rial 1997/98 1993 B 1980–2002 2005 6 A S C G Iraq Iraqi dinar 1988 1968 P 1997, 2004 2005 6 G Ireland Euro 2005 1993 B Rolling 6 G C S Isle of Man Pound sterling 2003 1968 Israel Israeli new shekel 2005 1993 P 2011 6 S C S Italy Euro 2005 1993 B Rolling 6 S C S Jamaica Jamaican dollar 2007 1993 B 6 A G C G Japan Japanese yen 2005 1993 B 2011 6 G C S Jordan Jordanian dinar 1994 1968 B 2005 6 A G S a Kazakhstan Kazakh tenge 2000 1993 B 1987–95 2005 6 A G C S Kenya Kenyan shilling 2001 1993 B 2005 6 A G B G Kiribati Australian dollar 2006 1993 B 6 G B G Korea, Dem. People’s Democratic People's 1968 6 Rep. Republic of Korean won Korea, Rep. Korean won 2005 1993 B 2011 6 G C S Kosovo Euro 2008 1993 B A G Kuwait Kuwaiti dinar 1995 1968 P 2005 6 S B G a Kyrgyz Republic Kyrgyz som 1995 1993 B 1990–95 2005 6 A S B S Lao PDR Lao kip 2002 1993 B 2005 6 P S B Latvia Latvian lats 2000 1993 B 1987–95 Rolling 6 S C S Lebanon Lebanese pound 1997 1993 B 2005 6 A G B G Lesotho Lesotho loti 2004 1993 B 2005 6 A G C G 102 World Development Indicators 2014 Front ? User guide World view People Environment Latest Latest demographic, Source of most Vital Latest Latest Latest Latest population education, or health recent income registration agricultural industrial trade water census household survey and expenditure data complete census data data withdrawal data Denmark 2011 ITR, 1997 Yes 2010 2009 2012 2009 Djibouti 2009 MICS, 2006 PS, 2002 2009 2000 Dominica 2011 Yes 2012 2004 Dominican Republic 2010 DHS, 2013 IHS, 2012 2012/13 2012 2005 Ecuador 2010 RHS, 2004 IHS, 2012 2013/15 2008 2012 2005 Egypt, Arab Rep. 2006 DHS, 2008 ES/BS, 2011 Yes 2009/10 2010 2012 2000 El Salvador 2007 RHS, 2008 IHS, 2012 Yes 2007/08 2012 2007 Equatorial Guinea 2002 DHS, 2011 PS, 2006 2000 Eritrea 1984 DHS, 2002 PS, 1993 2010 2003 2004 Estonia 2012 WHS, 2003 ES/BS, 2004 Yes 2010 2010 2012 2007 Ethiopia 2007 DHS, 2011 ES/BS, 2010/11 2009 2012 2002 Faeroe Islands 2011 Yes 2009 Fiji 2007 ES/BS, 2009 Yes 2009 2009 2012 2000 Finland 2010 IS, 2000 Yes 2010 2009 2012 2005 France 2006g ES/BS, 1994/95 Yes 2010 2009 2012 2007 French Polynesia 2007 Yes 2012 Gabon 2013 DHS, 2012 CWIQ/IHS, 2005 2009 2005 Gambia, The 2013 DHS, 2013 IHS, 2010 2004 2011 2000 Georgia 2002 MICS, 2005; RHS, 2005 IHS, 2011 Yes 2010 2012 2005 Germany 2011 IHS, 2000 Yes 2010 2009 2012 2007 Ghana 2010 MICS, 2011 LSMS, 2005/06 2013/14 2003 2012 2000 Greece 2011 IHS, 2000 Yes 2009 2007 2012 2007 Greenland 2010 Yes 2012 Grenada 2011 RHS, 1985 Yes 2012 2009 2005 Guam 2010 Yes 2007 Guatemala 2002 RHS, 2008/09 LSMS, 2011 Yes 2013 2012 2006 Guinea 1996 DHS, 2012 CWIQ, 2012 2008 2001 Guinea-Bissau 2009 MICS, 2010 CWIQ, 2010 2005 2000 Guyana 2012 DHS, 2009 IHS, 1998 2012 2000 Haiti 2003 HIV/MCH SPA, 2013 IHS, 2001 2008/09 1997 2000 Honduras 2013 DHS, 2011/12 IHS, 2010 2013 2012 2006 Hungary 2011 WHS, 2003 ES/BS, 2007 Yes 2010 2009 2012 2007 Iceland 2011 Yes 2010 2005 2012 2005 India 2011 DHS, 2005/06 IHS, 2012 2011 2009 2012 2010 Indonesia 2010 DHS, 2012 IHS, 2013 2013 2009 2012 2000 Iran, Islamic Rep. 2011 DHS, 2000 ES/BS, 2005 Yes 2013 2009 2011 2004 Iraq 1997 MICS, 2011 IHS, 2007 2011/12 2000 Ireland 2011 IHS, 2000 Yes 2010 2009 2012 1979 Isle of Man 2011 Yes Israel 2009 ES/BS, 2001 Yes 2009 2012 2004 Italy 2012 ES/BS, 2000 Yes 2010 2009 2012 2000 Jamaica 2011 MICS, 2011 LSMS, 2010 2007 2012 1993 Japan 2010 IS, 1993 Yes 2010 2010 2012 2001 Jordan 2004 DHS, 2012 ES/BS, 2010 2007 2010 2012 2005 Kazakhstan 2009 MICS, 2010/11 ES/BS, 2012 Yes 2012 2010 Kenya 2009 MIS, 2010; IHS, 2005/06 2009c 2010 2010 2003 HIV/MCH SPA, 2010 Kiribati 2010 2012 Korea, Dem. People’s 2008 MICS, 2009 2005 Rep. Korea, Rep. 2010 ES/BS, 1998 Yes 2010 2008 2012 2002 Kosovo 2011 IHS, 2011 Kuwait 2011 FHS, 1996 Yes 2010 2009 2002 Kyrgyz Republic 2009 DHS, 2012 ES/BS, 2012 Yes 2014 2010 2012 2006 Lao PDR 2005 MICS, 2011/12 ES/BS, 2008 2010/11 2005 Latvia 2011 WHS, 2003 IHS, 2008 Yes 2010 2010 2012 2002 Lebanon 1970 MICS, 2000 Yes 2011 2007 2012 2005 Lesotho 2006 DHS, 2009 ES/BS, 2002/03 2010 2009 2000 Economy States and markets Global links Back World Development Indicators 2014 103 Primary data documentation Currency National Balance of payments Government IMF data accounts and trade finance dissem- ination standard Balance of System of SNA Alternative PPP Payments Base Reference National price conversion survey Manual External System Accounting year year Accounts valuation factor year in use debt of trade concept Liberia Liberian dollar 2000 1968 P 2005 6 A S B G Libya Libyan dinar 1999 1993 B 1986 6 G G Liechtenstein Swiss franc 1990 1993 B S Lithuania Lithuanian litas 2000 1993 B 1990–95 Rolling 6 G C S a Luxembourg Euro 2005 1993 B Rolling 6 S C S Macedonia, FYR Macedonian denar 1995 1993 B Rolling 6 A S C S Madagascar Malagasy ariary 1984 1968 B 2005 6 A S C G Malawi Malawi kwacha 2009 1993 B 2005 6 A G G Malaysia Malaysian ringgit 2005 1993 P 2005 6 E G B S Maldives Maldivian rufiyaa 2003 1993 B 2005 6 A G C G Mali CFA franc 1987 1968 B 2005 6 A S B G Malta Euro 2005 1993 B Rolling 6 G C S Marshall Islands U.S. dollar 2004 1968 B G Mauritania Mauritanian ouguiya 2004 1993 B 2005 6 A S G Mauritius Mauritian rupee 2006 1993 B 2005 6 A G S Mexico Mexican peso 2008 2008 B 2011 6 A G C S Micronesia, Fed. Sts. U.S. dollar 2004 1993 B a Moldova Moldovan leu 1996 1993 B 1990–95 2005 6 A G C S Monaco Euro 1990 1993 S Mongolia Mongolian tugrik 2005 1993 B 2005 6 A G C G Montenegro Euro 2000 1993 B Rolling 6 A S G Morocco Moroccan dirham 1998 1993 B 2005 6 A S C S Mozambique New Mozambican metical 2003 1993 B 1992–95 2005 6 A S B G Myanmar Myanmar kyat 2005/06 1968 P 6 E G C G Namibia Namibian dollar 2004/05 1993 B 2005 6 G B G Nepal Nepalese rupee 2000/01 1993 B 2005 6 A G B G a Netherlands Euro 2005 1993 B Rolling 6 S C S New Caledonia CFP franc 1990 1993 S New Zealand New Zealand dollar 2005/06 1993 B 2011 6 G C Nicaragua Nicaraguan gold cordoba 2006 1993 B 1965–95 6 A G B G Niger CFA franc 2006 1993 P 1993 2005 6 A S B G Nigeria Nigerian naira 1990 1993 B 1971–98 2005 6 A G B G Northern Mariana Islands U.S. dollar 1968 a Norway Norwegian krone 2005 1993 B Rolling 6 G C S Oman Rial Omani 1988 1993 P 2005 6 G B G Pakistan Pakistani rupee 2005/06 1993 B 2005 6 A G B G Palau U.S. dollar 2005 1993 B S G Panama Panamanian balboa 1996 1993 B 6 A S C G Papua New Guinea Papua New Guinea kina 1998 1993 B 1989 6 A G B G Paraguay Paraguayan guarani 1994 1993 B 2005 6 A S C G Peru Peruvian new sol 1994 1993 B 1985–90 2005 6 A S C S Philippines Philippine peso 2000 1993 P 2005 6 A G B S a Poland Polish zloty 2005 1993 B Rolling 6 S C S Portugal Euro 2005 1993 B Rolling 6 S C S Puerto Rico U.S. dollar 1954 1968 P G Qatar Qatari riyal 2001 1993 P 2005 S B G Romania New Romanian leu 2000 1993 B 1987–89, Rolling 6 A S C S 1992 Russian Federation Russian ruble 2000 1993 B 1987–95 2011 6 G C S Rwanda Rwandan franc 2006 1993 P 1994 2005 6 A G B G Samoa Samoan tala 2002 1993 B 6 A S B G San Marino Euro 1995 2000 1993 B C G São Tomé and Príncipe São Tomé and Principe 2001 1993 P 2005 6 A S B G dobra Saudi Arabia Saudi Arabian riyal 1999 1993 P 2005 6 S G Senegal CFA franc 1999 1987 1993 B 2005 6 A G B G a Serbia New Serbian dinar 2002 1993 B Rolling 6 A S C G 104 World Development Indicators 2014 Front ? User guide World view People Environment Latest Latest demographic, Source of most Vital Latest Latest Latest Latest population education, or health recent income registration agricultural industrial trade water census household survey and expenditure data complete census data data withdrawal data Liberia 2008 DHS, 2013 CWIQ, 2007 2008 c 2000 Libya 2006 2013/14 2010 2000 Liechtenstein 2010 Yes Lithuania 2011 ES/BS, 2008 Yes 2010 2010 2012 2007 Luxembourg 2011 Yes 2010 2009 2012 1999 Macedonia, FYR 2002 MICS, 2011 ES/BS, 2009 Yes 2007 2010 2012 2007 Madagascar 1993 MIS, 2013 PS, 2010 2006 2012 2000 Malawi 2008 HIV/MCH SPA, 2013 IHS, 2010/11 2006/07 2009 2011 2005 Malaysia 2010 WHS, 2003 ES/BS, 2012 Yes 2015 2010 2012 2005 Maldives 2006 DHS, 2009 IHS, 2010 Yes 2012 2008 Mali 2009 DHS, 2012/13 IHS, 2009/10 2012 2000 Malta 2011 Yes 2010 2008 2012 2002 Marshall Islands 2011 2011c Mauritania 2013 MICS, 2011 IHS, 2008 2012 2005 Mauritius 2011 RHS, 1991 Yes 2013/14 2010 2012 2003 Mexico 2010 ENADID, 2009 IHS, 2012 2007 2010 2012 2009 Micronesia, Fed. Sts. 2010 IHS, 2000 Moldova 2004 MICS, 2012 ES/BS, 2012 Yes 2011 2010 2012 2007 Monaco 2008 Yes 2009 Mongolia 2010 MICS, 2010 LSMS, 2012 Yes 2012 2008 2007 2009 Montenegro 2011 MICS, 2005/06 ES/BS, 2011 Yes 2010 2012 2010 Morocco 2004 MICS/PAPFAM, 2006 ES/BS, 2007 2012 2010 2012 2000 Mozambique 2007 DHS, 2011 ES/BS, 2008/09 2009/10 2012 2001 Myanmar 1983 MICS, 2009/10 2010 2003 2010 2000 Namibia 2011 DHS, 2013 ES/BS, 2009/10 2014 2012 2002 Nepal 2011 DHS, 2011 LSMS, 2011 2011/12 2008 2011 2006 Netherlands 2011 IHS, 1999 Yes 2010 2008 2012 2008 New Caledonia 2009 Yes 2012 New Zealand 2013 IS, 1997 Yes 2012 2009 2012 2002 Nicaragua 2005 RHS, 2006/2007 LSMS, 2009 2011 2012 2001 Niger 2012 DHS, 2012 CWIQ/PS, 2007 2004-08 2002 2012 2005 Nigeria 2006 DHS, 2013 IHS, 2010 2013 2012 2005 Northern Mariana Islands 2010 2007 Norway 2011 IS, 2000 Yes 2010 2008 2012 2006 Oman 2010 MICS, 2012 2012/13 2010 2012 2003 Pakistan 1998 DHS, 2012/13 IHS, 2008 2010 2006 2012 2008 Palau 2010 Yes 2012 Panama 2010 LSMS, 2008 IHS, 2011 2011 2001 2011 2000 Papua New Guinea 2011 LSMS, 1996 IHS, 2009/10 2012 2005 Paraguay 2012 RHS, 2008 IHS, 2011 2008 2002 2012 2000 Peru 2007 Continuous DHS, 2013 IHS, 2012 2012 2010 2012 2000 Philippines 2010 DHS, 2013 ES/BS, 2012 Yes 2012 2008 2012 2009 Poland 2011 ES/BS, 2010 Yes 2010 2009 2012 2009 Portugal 2011 IS, 1997 Yes 2009 2009 2012 2002 Puerto Rico 2010 RHS, 1995/96 Yes 2007 2006 2005 Qatar 2010 MICS, 2012 Yes 2010 2012 2005 Romania 2011 RHS, 1999 LFS, 2010 Yes 2010 2010 2012 2009 Russian Federation 2010 WHS, 2003 IHS, 2012 Yes 2014 2010 2012 2001 Rwanda 2012 MIS, 2013 IHS, 2011 2008 2012 2000 Samoa 2011 DHS, 2009 2009 2012 San Marino 2010 Yes São Tomé and Príncipe 2012 DHS, 2008/09 PS, 2009/10 2011/12 2012 1993 Saudi Arabia 2010 Demographic survey, 2007 2010 2006 2011 2006 Senegal 2013 Continuous DHS, 2013/14; PS, 2010/11 2013 2010 2012 2002 HIV/MCH SPA, 2013/14 Serbia 2011 MICS, 2010 IHS, 2010 Yes 2012 2010 2009 Economy States and markets Global links Back World Development Indicators 2014 105 Primary data documentation Currency National Balance of payments Government IMF data accounts and trade finance dissem- ination standard Balance of System of SNA Alternative PPP Payments Base Reference National price conversion survey Manual External System Accounting year year Accounts valuation factor year in use debt of trade concept Seychelles Seychelles rupee 2006 1993 P 6 A G C G Sierra Leone Sierra Leonean leone 2006 1993 B 2005 6 A S B G Singapore Singapore dollar 2005 2008 B 2005 6 G C S Sint Maarten Netherlands Antilles 1993 guilder Slovak Republic Euro 2005 1993 B Rolling 6 S C S a Slovenia Euro 2005 1993 B Rolling 6 S C S Solomon Islands Solomon Islands dollar 2004 1993 B 6 A S G Somalia Somali shilling 1985 1968 B 1977–90 E South Africa South African rand 2005 1993 B 2005 6 P G C S South Sudan South Sudanese pound 2009 1993 Spain Euro 2005 1993 B Rolling 6 S C S Sri Lanka Sri Lankan rupee 2002 1993 P 2005 6 A G B G St. Kitts and Nevis East Caribbean dollar 2006 1993 B 6 S B G St. Lucia East Caribbean dollar 2006 1968 B 6 A S B G St. Martin Euro 1993 St. Vincent and the East Caribbean dollar 2006 1993 B 6 A S B G Grenadines Sudan Sudanese pound 1981/82h 1996 1968 B 2005 6 A G B G Suriname Suriname dollar 2007 1993 B 6 G B G Swaziland Swaziland lilangeni 2000 1993 B 2005 6 A G C G a Sweden Swedish krona 2005 1993 B Rolling 6 G C S Switzerland Swiss franc 2005 1993 B Rolling 6 S C S Syrian Arab Republic Syrian pound 2000 1968 B 1970–2010 2005 6 E S B G a Tajikistan Tajik somoni 2000 1993 B 1990–95 2005 6 A G C G a Tanzania Tanzanian shilling 2001 1993 B 2005 6 A G B G Thailand Thai baht 1988 1993 P 2005 6 A S C S Timor-Leste U.S. dollar 2010 2008 B S G Togo CFA franc 2000 1968 P 2005 6 A S B G Tonga Tongan pa'anga 2010/11 1993 B 6 A G G Trinidad and Tobago Trinidad and Tobago 2000 1993 B 6 S C G dollar Tunisia Tunisian dinar 1990 1993 B 2005 6 A G C S Turkey New Turkish lira 1998 1993 B Rolling 6 A S C S Turkmenistan New Turkmen manat 2005 1993 B 1987–95, 6 E G 1997–2007 Turks and Caicos Islands U.S. dollar 1993 G Tuvalu Australian dollar 2005 1968 B G G Uganda Ugandan shilling 2001/02 1968 B 2005 6 A G B G a Ukraine Ukrainian hryvnia 2003 1993 B 1987–95 2005 6 A G C S United Arab Emirates U.A.E. dirham 2007 1993 P 6 G C G United Kingdom Pound sterling 2005 1993 B Rolling 6 G C S a United States U.S. dollar 2005 2008 B 2011 6 G C S Uruguay Uruguayan peso 2005 1993 B 2005 6 G C S a Uzbekistan Uzbek sum 1997 1993 B 1990–95 6 A G Vanuatu Vanuatu vatu 2006 1993 B 6 E G B G Venezuela, RB Venezuelan bolivar fuerte 1997 1993 B 2005 6 A G C G Vietnam Vietnamese dong 2010 1993 P 1991 2005 6 A G G Virgin Islands (U.S.) U.S. dollar 1982 1968 G West Bank and Gaza Israeli new shekel 1997 1968 B 6 S B S Yemen, Rep. Yemeni rial 1990 1993 P 1990–96 2005 6 A S B G Zambia New Zambian kwacha 1994 1968 B 1990–92 2005 6 A S B G Zimbabwe U.S. dollar 2009 1993 B 1991, 1998 2005 6 A G C G 106 World Development Indicators 2014 Front ? User guide World view People Environment Latest Latest demographic, Source of most Vital Latest Latest Latest Latest population education, or health recent income registration agricultural industrial trade water census household survey and expenditure data complete census data data withdrawal data Seychelles 2010 BS, 2006/07 Yes 2011 2008 2005 Sierra Leone 2004 DHS, 2013; MIS, 2013 IHS, 2011 2002 2005 Singapore 2010 NHS, 2010 Yes 2010 2012 1975 Sint Maarten 2011 Yes Slovak Republic 2011 WHS, 2003 IS, 2009 Yes 2010 2009 2012 2007 Slovenia 2011b WHS, 2003 ES/BS, 2004 Yes 2010 2010 2012 2009 Solomon Islands 2009 IHS, 2005/06 2012/13 2012 Somalia 1987 MICS, 2006 2003 South Africa 2011 DHS, 2003; WHS, 2003 ES/BS, 2010 2007 2010 2012 2000 South Sudan 2008 ES/BS, 2009 Spain 2011 IHS, 2000 Yes 2010 2009 2012 2008 Sri Lanka 2012 DHS, 2006/07 ES/BS, 2010 Yes 2013/14 2010 2012 2005 St. Kitts and Nevis 2011 Yes 2011 St. Lucia 2010 MICS, 2012 IHS, 1995 Yes 2007 2008 2005 St. Martin St. Vincent and the 2011 Yes 2012 1995 Grenadines Sudan 2008 SHHS, 2010 ES/BS, 2009 2013/14 2001 2011 2005i Suriname 2012 MICS, 2010 ES/BS, 1999 Yes 2008 2011 2000 Swaziland 2007 MICS, 2010 ES/BS, 2009/10 2007c 2007 2000 Sweden 2011 IS, 2000 Yes 2010 2009 2012 2007 Switzerland 2010 ES/BS, 2000 Yes 2008 2007 2012 2000 Syrian Arab Republic 2004 MICS, 2006 ES/BS, 2004 2014 2010 2005 Tajikistan 2010 DHS, 2012 LSMS, 2009 2013 2000 2006 Tanzania 2012 HIV/MCH SPA, 2013/14 ES/BS, 2011/12 2007/08 2007 2012 2002 Thailand 2010 MICS, 2012 IHS, 2011 2013 2006 2012 2007 Timor-Leste 2010 DHS, 2009/10 LSMS, 2007 2010 c 2005 2004 Togo 2010 DHS, 2013 CWIQ, 2011 2011/12 2012 2002 Tonga 2006 2012 Trinidad and Tobago 2011 MICS, 2011 IHS, 1992 Yes 2006 2010 2000 Tunisia 2004 MICS, 2011/12 IHS, 2010 2014/15 2006 2011 2001 Turkey 2011 DHS, 2003; WHS, 2003 LFS, 2009 2009 2012 2003 Turkmenistan 2012 MICS, 2011 LSMS, 1998 Yes 2000 2004 Turks and Caicos Islands 2012 Yes 2012 Tuvalu 2012 2008 Uganda 2002 AIS, 2011; DHS, 2011 PS, 2009/10 2008/09 2000 2012 2002 Ukraine 2001 MICS, 2012 ES/BS, 2009 Yes 2012/13 2012 2005 United Arab Emirates 2010 2012 2011 2005 United Kingdom 2011 IS, 1999 Yes 2010 2009 2012 2007 United States 2010 LFS, 2000 Yes 2012 2008 2012 2005 Uruguay 2011 MICS, 2012 IHS, 2012 Yes 2011 2008 2012 2000 Uzbekistan 1989 MICS, 2006 ES/BS, 2011 Yes 2005 Vanuatu 2009 MICS, 2007 2007 2011 Venezuela, RB 2011 MICS, 2000 IHS, 2012 Yes 2007 2011 2000 Vietnam 2009 MICS, 2010/11 IHS, 2010 Yes 2011/12 2010 2011 2005 Virgin Islands (U.S.) 2010 Yes 2007 West Bank and Gaza 2007 MICS, 2010 IHS, 2009 2010 2005 Yemen, Rep. 2004 DHS, 2013 ES/BS, 2005 2006 2012 2005 Zambia 2010 DHS, 2013 IHS, 2010 2010 c 2011 2002 Zimbabwe 2012 DHS, 2010/11 IHS, 2011/12 2012 2002 Note: For explanation of the abbreviations used in the table, see notes following the table. a. Original chained constant price data are rescaled. b. Population data compiled from administrative registers. c. Population and Housing Census. d. Latest population census: Guernsey, 2009; Jersey, 2011 e. Vital registration for Guernsey and Jersey. f. The population censuses for 1986 and 1996 were based on a one-in-seven sample of the population, while that for 2006 was based on a one-in-ten sample of the population. g. Rolling census based on continuous sample survey. h. Reporting period switch from fiscal year to calendar year from 1996. Pre-1996 data converted to calendar year. i. Includes South Sudan. Economy States and markets Global links Back World Development Indicators 2014 107 Primary data documentation notes • Base year is the base or pricing period used for con- general system comprise outward-moving goods: (a) HIV/AIDS Indicator Survey, DHS is Demographic and stant price calculations in the country’s national national goods wholly or partly produced in the country; Health Survey, ENADID is National Survey of Demo- accounts. Price indexes derived from national accounts (b) foreign goods, neither transformed nor declared for graphic Dynamics, FHS is Family Health Survey, HIV/ aggregates, such as the implicit deflator for gross domestic consumption in the country, that move out- MCH is HIV/Maternal and Child Health, LSMS is Living domestic product (GDP), express the price level relative ward from customs storage; and (c) nationalized goods Standards Measurement Study Survey, MICS is Multiple to base year prices. • Reference year is the year in that have been declared for domestic consumption and Indicator Cluster Survey, MIS is Malaria Indicator Survey, which the local currency constant price series of a coun- move outward without being transformed. Under the NHS is National Health Survey, NSS is National Sample try is valued. The reference year is usually the same as special system of trade, exports are categories a and c. Survey on Population Change, PAPFAM is Pan Arab Proj- the base year used to report the constant price series. In some compilations categories b and c are classified ect for Family Health, RHS is Reproductive Health Sur- However, when the constant price data are chain linked, as re-exports. Direct transit trade—goods entering or vey, SHHS is Sudan Household Health Survey, SPA is the base year is changed annually, so the data are res- leaving for transport only—is excluded from both import Service Provision Assessments, and WHS is World caled to a specific reference year to provide a consistent and export statistics. • Government finance accounting Health Survey. Detailed information for AIS, DHS, MIS, time series. When the country has not rescaled following concept is the accounting basis for reporting central and SPA are available at www.measuredhs.com; for a change in base year, World Bank staff rescale the data government financial data. For most countries govern- MICS at www.childinfo.org; for RHS at www.cdc.gov to maintain a longer historical series. To allow for cross- ment finance data have been consolidated (C) into one /reproductivehealth; and for WHS at www.who.int country comparison and data aggregation, constant set of accounts capturing all central government fiscal /healthinfo/survey/en. • Source of most recent income price data reported in World Development Indicators are activities. Budgetary central government accounts (B) and expenditure data shows household surveys that rescaled to a common reference year (2000) and cur- exclude some central government units. • IMF data dis- collect income and expenditure data. Names and rency (U.S. dollars). • System of National Accounts semination standard shows the countries that sub- detailed information on household surveys can be found identifies whether a country uses the 1968, 1993, or scribe to the IMF’s Special Data Dissemination Stan- on the website of the International Household Survey 2008 System of National Accounts (SNA). • SNA price dard (SDDS) or General Data Dissemination System Network (www.surveynetwork.org). Core Welfare Indica- valuation shows whether value added in the national (GDDS). S refers to countries that subscribe to the SDDS tor Questionnaire Surveys (CWIQ), developed by the accounts is reported at basic prices (B) or producer and have posted data on the Dissemination Standards World Bank, measure changes in key social indicators prices (P). Producer prices include taxes paid by produc- Bulletin Board at http://dsbb.imf.org. G refers to coun- for different population groups—specifically indicators ers and thus tend to overstate the actual value added in tries that subscribe to the GDDS. The SDDS was estab- of access, utilization, and satisfaction with core social production. However, value added can be higher at basic lished for member countries that have or might seek and economic services. Expenditure survey/budget prices than at producer prices in countries with high access to international capital markets to guide them in surveys (ES/BS) collect detailed information on house- agricultural subsidies. • Alternative conversion factor providing their economic and financial data to the public. hold consumption as well as on general demographic, identifies the countries and years for which a World The GDDS helps countries disseminate comprehensive, social, and economic characteristics. Integrated house- Bank–estimated conversion factor has been used in timely, accessible, and reliable economic, financial, and hold surveys (IHS) collect detailed information on a wide place of the official exchange rate (line rf in the Interna- sociodemographic statistics. IMF member countries variety of topics, including health, education, economic tional Monetary Fund’s [IMF] International Financial Sta- elect to participate in either the SDDS or the GDDS. Both activities, housing, and utilities. Income surveys (IS) col- tistics). See Statistical methods for further discussion of standards enhance the availability of timely and com- lect information on the income and wealth of house- alternative conversion factors. • Purchasing power prehensive data and therefore contribute to the pursuit holds as well as various social and economic character- parity (PPP) survey year is the latest available survey of sound macroeconomic policies. The SDDS is also istics. Income tax registers (ITR) provide information on year for the International Comparison Program’s esti- expected to improve the functioning of financial mar- a population’s income and allowance, such as gross mates of PPPs. • Balance of Payments Manual in use kets. •  Latest population census shows the most income, taxable income, and taxes by socioeconomic refers to the classification system used to compile and recent year in which a census was conducted and in group. Labor force surveys (LFS) collect information on report data on balance of payments. 6 refers to the 6th which at least preliminary results have been released. employment, unemployment, hours of work, income, edition of the IMF’s Balance of Payments Manual (2009). The preliminary results from the very recent censuses and wages. Living Standards Measurement Study Sur- • External debt shows debt reporting status for 2012 could be reflected in timely revisions if basic data are veys (LSMS), developed by the World Bank, provide a data. A indicates that data are as reported, P that data available, such as population by age and sex, as well as comprehensive picture of household welfare and the are based on reported or collected information but the detailed definition of counting, coverage, and com- factors that affect it; they typically incorporate data col- include an element of staff estimation, and E that data pleteness. Countries that hold register-based censuses lection at the individual, household, and community are World Bank staff estimates. • System of trade produce similar census tables every 5 or 10 years. Ger- levels. Priority surveys (PS) are a light monitoring survey, refers to the United Nations general trade system (G) or many’s 2001 census is a register-based test census designed by the World Bank, that collect data from a special trade system (S). Under the general trade sys- using a sample of 1.2 percent of the population. A rare large number of households cost-effectively and quickly. tem goods entering directly for domestic consumption case, France conducts a rolling census every year; the 1-2-3 (1-2-3) surveys are implemented in three phases and goods entered into customs storage are recorded 1999 general population census was the last to cover and collect sociodemographic and employment data, as imports at arrival. Under the special trade system the entire population simultaneously. • Latest demo- data on the informal sector, and information on living goods are recorded as imports when declared for graphic, education, or health household survey indi- conditions and household consumption. • Vital registra- domestic consumption whether at time of entry or on cates the household surveys used to compile the demo- tion complete identifies countries that report at least withdrawal from customs storage. Exports under the graphic, education, and health data in section 2. AIS is 90 percent complete registries of vital (birth and death) 108 World Development Indicators 2014 Front ? User guide World view People Environment Primary data documentation notes statistics to the United Nations Statistics Division and accounts data have been revised from 2006 onward; year is 2011. • Fiji. Based on data from the Bureau of are reported in its Population and Vital Statistics Reports. the new base year is 2006. Data before 2006 were Statistics, national accounts data on the expenditure Countries with complete vital statistics registries may reported on a fiscal year basis. • Cabo Verde. Based side have been revised from 2005 onward; the new have more accurate and more timely demographic indi- on official government statistics and IMF data, national base year is 2005. • Hong Kong SAR, China. Hong Kong cators than other countries. • Latest agricultural cen- accounts data have been revised from 1990 onward; SAR, China, reports using SNA 2008. • Iraq. Based on sus shows the most recent year in which an agricultural the new base year is 2007. • Chad. Based on IMF data, official government data, national accounts have been census was conducted or planned to be conducted, as national accounts data have been revised from 2005 revised from 2000 onward; the new base year is 1988. reported to the Food and Agriculture Organization of the onward; the new base year is 2005. • Canada. Canada • Kiribati. Based on IMF, Asian Development Bank, and United Nations. • Latest industrial data show the most reports using SNA 2008. • China. Based on data from World Bank data, national accounts data have been recent year for which manufacturing value added data the National Bureau of Statistics, the methodology used revised from 2000 onward. • Malawi. Based on IMF at the three-digit level of the International Standard to calculate exports and imports of goods and services data, national accounts data have been revised from Industrial Classification (revision 2 or 3) are available in in constant prices has been revised from 2000 onward. 2000 onward; the new base year is 2009. • Malaysia. the United Nations Industrial Development Organization • Ecuador. Based on official government data, national Based on official government statistics, value added database. • Latest trade data show the most recent accounts have been revised from 1965 onward; the new services in constant and current prices have been year for which structure of merchandise trade data from base year is 2007. Ecuador reports using SNA 2008. revised from 1990 onward. National accounts data in the United Nations Statistics Division’s Commodity • Ethiopia. Based on IMF data, national accounts data constant prices have been linked back to 1960; the Trade (Comtrade) database are available. •  Latest have been revised from 2000 onward; the new base new base year is 2005. • Mexico. The base year has water withdrawal data show the most recent year for changed to 2008; Mexico reports using SNA 2008. Economies with exceptional reporting periods which data on freshwater withdrawals have been com- • Micronesia, Fed. Sts. Based on the Pacific and Virgin Reporting period piled from a variety of sources. Fiscal for national Islands Training Initiative, national accounts data have Economy year end accounts data been revised from 2009 onward. • Niger. Based on Afghanistan Mar. 20 FY Exceptional reporting periods official government statistics, national accounts data Australia Jun. 30 FY In most economies the fiscal year is concurrent with Bangladesh Jun. 30 FY have been revised from 2006 onward; the new base the calendar year. Exceptions are shown in the table Botswana Mar. 31 CY year is 2006. • Nigeria. Based on official government at right. The ending date reported here is for the fiscal Canada Mar. 31 CY statistics, national accounts data have been revised year of the central government. Fiscal years for other Egypt, Arab Rep. Jun. 30 FY from 1981 onward while preserving historical growth levels of government and reporting years for statisti- Ethiopia Jul. 7 FY rates for constant GDP at market prices through 2006. Gambia, The Jun. 30 CY cal surveys may differ. • Paraguay. National accounts data have been revised Haiti Sep. 30 FY The reporting period for national accounts data is from 1960 onward. The output of two hydroelectric India Mar. 31 FY designated as either calendar year basis (CY) or fiscal Indonesia Mar. 31 CY plants (shared with neighboring countries) were added, year basis (FY). Most economies report their national Iran, Islamic Rep. Mar. 20 FY raising GDP from previous estimates • Romania. Based accounts and balance of payments data using calen- Japan Mar. 31 CY on data from the National Statistical Institute, national dar years, but some use fiscal years. In World Devel- Kenya Jun. 30 CY accounts data have been revised; the new base year is Kuwait Jun. 30 CY opment Indicators fiscal year data are assigned to 2000. • Singapore. Singapore reports using a blend Lesotho Mar. 31 CY the calendar year that contains the larger share of of SNA 1993 and SNA 2008. • Timor-Leste. Based on Malawi Mar. 31 CY the fiscal year. If a country’s fiscal year ends before Marshall Islands Sep. 30 FY official government statistics, national accounts data June 30, data are shown in the first year of the fiscal Micronesia, Fed. Sts. Sep. 30 FY have been revised, and value added is measured at period; if the fiscal year ends on or after June 30, data Myanmar Mar. 31 FY basic prices; the new base year is 2010. Timor-Leste are shown in the second year of the period. Balance Namibia Mar. 31 CY reports using SNA 2008. • Tuvalu. Based on data from of payments data are reported in World Development Nepal Jul. 14 FY the IMF, World Bank, and official government statistics, New Zealand Mar. 31 FY Indicators by calendar year. national accounts data have been revised from 2006 Pakistan Jun. 30 FY onward. Value added is measured at producer prices Palau Sep. 30 FY Revisions to national accounts data Puerto Rico Jun. 30 FY through 1999 and at basic prices from 2000 onward. National accounts data are revised by national statisti- Samoa Jun. 30 FY • United States. The United States reports using SNA cal offices when methodologies change or data sources Sierra Leone Jun. 30 CY 2008. • Vanuatu. Based on official government sta- improve. National accounts data in World Development Singapore Mar. 31 CY tistics, value added is measured at producer prices South Africa Mar. 31 CY Indicators are also revised when data sources change. through 1997 and at basic prices from 1998 onward. Swaziland Mar. 31 CY The following notes, while not comprehensive, provide • Vietnam. Based on data from the Vietnam Statistics Sweden Jun. 30 CY information on revisions from previous data. • Austra- Thailand Sep. 30 CY Office, national accounts data have been revised from lia. Value added current series updated by the Australian Tonga Jun. 30 FY 2000 onward; the new base year is 2010. • Zambia. Bureau of Statistics; data have been revised from 1990 Uganda Jun. 30 FY National accounts data have rebased to reflect the Janu- onward; Australia reports using SNA 2008. • Botswana. United States Sep. 30 CY ary 1, 2013, introduction of the new Zambian kwacha at Based on official government statistics, national Zimbabwe Jun. 30 CY a rate of 1,000 old kwacha = 1 new kwacha. Economy States and markets Global links Back World Development Indicators 2014 109 Statistical methods This section describes some of the statistical proce- the year of the previous estimate. The imputation dures used in preparing World Development Indica- process works forward and backward from 2005. tors. It covers the methods employed for calculating Missing values in 2005 are imputed using one of regional and income group aggregates and for calcu- several proxy variables for which complete data are lating growth rates, and it describes the World Bank available in that year. The imputed value is calcu- Atlas method for deriving the conversion factor used lated so that it (or its proxy) bears the same relation- to estimate gross national income (GNI) and GNI per ship to the total of available data. Imputed values capita in U.S. dollars. Other statistical procedures are usually not calculated if missing data account and calculations are described in the About the data for more than a third of the total in the benchmark sections following each table. year. The variables used as proxies are GNI in U.S. dollars; total population; exports and imports of Aggregation rules goods and services in U.S. dollars; and value added Aggregates based on the World Bank’s regional and in agriculture, industry, manufacturing, and services income classifications of economies appear at the in U.S. dollars. end of the tables, including most of those available • Aggregates marked by an s are sums of available online. The 214 economies included in these classifi - data. Missing values are not imputed. Sums are not cations are shown on the flaps on the front and back computed if more than a third of the observations covers of the book. Aggregates also contain data for in the series or a proxy for the series are missing Taiwan, China. Most tables also include the aggregate in a given year. for the euro area, which includes the member states • Aggregates of ratios are denoted by a w when cal- of the Economic and Monetary Union (EMU) of the culated as weighted averages of the ratios (using European Union that have adopted the euro as their the value of the denominator or, in some cases, currency: Austria, Belgium, Cyprus, Estonia, Finland, another indicator as a weight) and denoted by a u France, Germany, Greece, Ireland, Italy, Latvia, Luxem- when calculated as unweighted averages. The bourg, Malta, Netherlands, Portugal, Slovak Republic, aggregate ratios are based on available data. Miss- Slovenia, and Spain. Other classifications, such as the ing values are assumed to have the same average European Union, are documented in About the data for value as the available data. No aggregate is calcu- the online tables in which they appear. lated if missing data account for more than a third Because of missing data, aggregates for groups of the value of weights in the benchmark year. In of economies should be treated as approximations a few cases the aggregate ratio may be computed of unknown totals or average values. The aggregation as the ratio of group totals after imputing values rules are intended to yield estimates for a consistent for missing data according to the above rules for set of economies from one period to the next and for computing totals. all indicators. Small differences between sums of sub- • Aggregate growth rates are denoted by a w when group aggregates and overall totals and averages may calculated as a weighted average of growth rates. occur because of the approximations used. In addi- In a few cases growth rates may be computed from tion, compilation errors and data reporting practices time series of group totals. Growth rates are not may cause discrepancies in theoretically identical calculated if more than half the observations in a aggregates such as world exports and world imports. period are missing. For further discussion of meth- Five methods of aggregation are used in World ods of computing growth rates see below. Development Indicators: • Aggregates denoted by an m are medians of the • For group and world totals denoted in the tables by values shown in the table. No value is shown if a t, missing data are imputed based on the rela- more than half the observations for countries with tionship of the sum of available data to the total in a population of more than 1 million are missing. 110 World Development Indicators 2014 Front ? User guide World view People Environment Exceptions to the rules may occur. Depending on notably labor force and population, is calculated from the judgment of World Bank analysts, the aggregates the equation may be based on as little as 50 percent of the avail- able data. In other cases, where missing or excluded r = ln(pn/p0)/n values are judged to be small or irrelevant, aggregates are based only on the data shown in the tables. where pn and p0 are the last and first observations in the period, n is the number of years in the period, Growth rates and ln is the natural logarithm operator. This growth Growth rates are calculated as annual averages and rate is based on a model of continuous, exponential represented as percentages. Except where noted, growth between two points in time. It does not take growth rates of values are computed from constant into account the intermediate values of the series. price series. Three principal methods are used to cal- Nor does it correspond to the annual rate of change culate growth rates: least squares, exponential end- measured at a one-year interval, which is given by point, and geometric endpoint. Rates of change from (pn – pn–1)/pn–1. one period to the next are calculated as proportional changes from the earlier period. Geometric growth rate. The geometric growth rate is applicable to compound growth over discrete Least squares growth rate. Least squares growth periods, such as the payment and reinvestment of rates are used wherever there is a sufficiently long interest or dividends. Although continuous growth, as time series to permit a reliable calculation. No growth modeled by the exponential growth rate, may be more rate is calculated if more than half the observations in realistic, most economic phenomena are measured a period are missing. The least squares growth rate, r, only at intervals, in which case the compound growth is estimated by fitting a linear regression trend line to model is appropriate. The average growth rate over n the logarithmic annual values of the variable in the rel- periods is calculated as evant period. The regression equation takes the form r = exp[ln(pn/p0)/n] – 1. ln Xt = a + bt which is the logarithmic transformation of the com- World Bank Atlas method pound growth equation, In calculating GNI and GNI per capita in U.S. dollars Xt = Xo (1 + r )t. for certain operational and analytical purposes, the World Bank uses the Atlas conversion factor instead In this equation X is the variable, t is time, and a = ln Xo of simple exchange rates. The purpose of the Atlas and b = ln (1 + r) are parameters to be estimated. If conversion factor is to reduce the impact of exchange b* is the least squares estimate of b, then the aver- rate fluctuations in the cross-country comparison of age annual growth rate, r, is obtained as [exp(b*) – 1] national incomes. and is multiplied by 100 for expression as a percent- The Atlas conversion factor for any year is the aver- age. The calculated growth rate is an average rate that age of a country’s exchange rate (or alternative conver- is representative of the available observations over sion factor) for that year and its exchange rates for the entire period. It does not necessarily match the the two preceding years, adjusted for the difference actual growth rate between any two periods. between the rate of inflation in the country and the rate of international inflation. Exponential growth rate. The growth rate between The objective of the adjustment is to reduce any two points in time for certain demographic indicators, changes to the exchange rate caused by inflation. Economy States and markets Global links Back World Development Indicators 2014 111 Statistical methods A country’s inflation rate between year t and year t–n GNI in U.S. dollars (Atlas method) for year t (Y tatlas$) (r t–n) is measured by the change in its GDP deflator (pt): is calculated by applying the Atlas conversion factor pt to a country’s GNI in current prices (local currency) r t–n = p (Yt) as follows: t–n Y tatlas$ = Yt /e tatlas International inflation between year t and year t–n SDR$ (r t–n ) is measured using the change in a deflator The resulting Atlas GNI in U.S. dollars can then be based on the International Monetary Fund’s unit of divided by a country’s midyear population to yield its account, special drawing rights (or SDRs). Known as GNI per capita (Atlas method). the “SDR deflator,” it is a weighted average of the GDP deflators (in SDR terms) of Japan, the United Kingdom, Alternative conversion factors the United States, and the euro area, converted to The World Bank systematically assesses the appro- U.S. dollar terms; weights are the amount of each priateness of official exchange rates as conversion currency in one SDR unit. factors. An alternative conversion factor is used p tSDR$ when the offi cial exchange rate is deemed to be SDR$ = r t–n unreliable or unrepresentative of the rate effectively SDR$ p t–n applied to domestic transactions of foreign curren- The Atlas conversion factor (local currency to the cies and traded products. This applies to only a U.S. dollar) for year t (e tatlas) is given by: small number of countries, as shown in Primary data documentation. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conver- where et is the average annual exchange rate (local sion factors. currency to the U.S. dollar) for year t. 112 World Development Indicators 2014 Front ? User guide World view People Environment Credits 1. World view Hossain (water and sanitation), Luz Maria de Regil Section 1 was prepared by a team led by Neil Fantom. (anemia), Hazim Timimi (tuberculosis), Colin Mathers Neil Fantom wrote the introduction, and the Millen- and Wahyu Mahanani (cause of death), and Lori Marie nium Development Goal spreads were produced by Newman (syphilis), all of the World Health Organiza- Mahyar Eshragh-Tabary, Juan Feng, Masako Hiraga, tion; Leonor Guariguata of the International Diabetes Wendy Huang, Buyant Erdene Khaltarkhuu, Hiroko Federation (diabetes); Mary Mahy of the Joint United Maeda, Johan Mistiaen, Malvina Pollock, and Emi Nations Programme on HIV/AIDS (HIV/AIDS); and Col- Suzuki. Tables were produced by Mahyar Eshragh- leen Murray (health) and Rolf Luyendijk (water and Tabary, Juan Feng, Masako Hiraga, Wendy Huang, sanitation) of the United Nations Children’s Fund. Bala Bhaskar Naidu Kalimili, Haruna Kashiwase, Buyant Erdene Khaltarkhuu, Hiroko Maeda, and Emi 3. Environment Suzuki. Signe Zeikate of the World Bank’s Economic Section 3 was prepared by Mahyar Eshragh-Tabary in Policy and Debt Department provided the estimates partnership with the Agriculture and Environmental of debt relief for the Heavily Indebted Poor Countries Services Department of the Sustainable Develop- Debt Initiative and Multilateral Debt Relief Initiative. ment Network Vice Presidency of the World Bank. Mahyar Eshragh-Tabary wrote the introduction and 2. People the highlights stories with invaluable comments and Section 2 was prepared by Juan Feng, Masako Hiraga, editorial help from Tariq Khokhar. Sonu Jain helped Haruna Kashiwase, Hiroko Maeda, and Emi Suzuki in prepare the highlight story on wealth accounting. partnership with the World Bank’s Human Develop- Esther G. Naikal and Chris Sall prepared the data ment Network and the Development Research Group on particulate matter concentration and natural in the Development Economics Vice Presidency. Emi resources rents. Ramgopal Erabelly provided techni- Suzuki prepared the demographic estimates and pro- cal assistance in calculating the population data for jections. The poverty estimates at national poverty largest city and urban agglomerations. Neil Fantom lines were compiled by the Global Poverty Working and William Prince provided instrumental comments, Group, a team of poverty experts from the Poverty suggestions, and support at all stages of production. Reduction and Equality Network, the Development Other contributors include Sharon Burghgraeve and Research Group, and the Development Data Group. Karen Tréanto of the International Energy Agency, Shaohua Chen and Prem Sangraula of the World Gerhard Metchies and Armin Wagner of German Inter- Bank’s Development Research Group prepared the national Cooperation, Craig Hilton-Taylor and Caroline poverty estimates at international poverty lines. Pollock of the International Union for Conservation Lorenzo Guarcello and Furio Rosati of the Under- of Nature, and Cristian Gonzalez of the International standing Children’s Work project prepared the data Road Federation. The team is grateful to the United on children at work. Other contributions were provided Nations Food and Agriculture Organization, the by Samuel Mills (health); Salwa Haidar, Maddalena United Nations Environment Programme and World Honorati, Theodoor Sparreboom, and Alan Wittrup of Conservation Monitoring Centre, the International the International Labour Organization (labor force); Union for Conservation of Nature, the U.S. Depart- Amélie Gagnon, Friedrich Huebler, and Weixin Lu of ment of Energy’s Carbon Dioxide Information Analy- the United Nations Educational, Scientific and Cultural sis Center, the International Energy Agency, and the Organization Institute for Statistics (education and U.S. Agency for International Development’s Office literacy); Chandika Indikadahena (health expenditure), of Foreign Disaster Assistance for access to their Monika Bloessner, Elaine Borghi, and Mercedes de online databases. The World Bank’s Agriculture and Onis (malnutrition and overweight), Teena Kunjumen Environmental Services Department devoted gener- (health workers), Jessica Ho (hospital beds), Rifat ous staff resources. Economy States and markets Global links Back World Development Indicators 2014 113 Credits 4. Economy Strategic Studies (military personnel); Sam Perlo-Free- Section 4 was prepared by Bala Bhaskar Naidu man of the Stockholm International Peace Research Kalimili in close collaboration with the Sustainable Institute (military expenditures and arms transfers); Development and Economic Data Team of the World Therese Petterson (battle-related deaths); Cristian Bank’s Development Data Group and with sugges- Gonzalez of the International Road Federation, Narjess tions from Liu Cui and William Prince. Bala Bhaskar Teyssier of the International Civil Aviation Organization, Naidu Kalimili wrote the introduction with suggestions and Marc Juhel and Hélène Stephan (transport); Vin- from Tariq Khokhar. The highlights section was pre- cent Valentine of the United Nations Conference on pared by Bala Bhaskar Naidu Kalimili and Maurice Trade and Development (ports); Azita Amjadi (high-tech Nsabimana. The national accounts data for low- and exports); Vanessa Grey, Esperanza Magpantay, Susan middle-income economies were gathered by the World Teltscher, and Ivan Vallejo Vall of the International Bank’s regional staff through the annual Unified Telecommunication Union and Torbjörn Fredriksson, Survey. Maja Bresslauer, Liu Cui, Federico Escaler, Scarlett Fondeur Gil, and Diana Korka of the United Mahyar Eshragh-Tabary, Bala Bhaskar Naidu Kalimili, Nations Conference on Trade and Development (infor- Buyant Erdene Khaltarkhuu, and Maurice Nsabimana mation and communication technology goods trade); updated, estimated, and validated the databases for Martin Schaaper of the United Nations Educational, national accounts. Esther G. Naikal and Chris Sall Scientific and Cultural Organization Institute for Sta- prepared the data on adjusted savings and adjusted tistics (research and development, researchers, and income. Azita Amjadi contributed data on trade from technicians); and Ryan Lamb of the World Intellectual the World Integrated Trade Solution. The team is grate- Property Organization (patents and trademarks). ful to Eurostat, the International Monetary Fund, the Organisation for Economic Co-operation and Devel- 6. Global links opment, the United Nations Industrial Development Section 6 was prepared by Wendy Huang with sub- Organization, and the World Trade Organization for stantial input from Evis Rucaj and Rubena Sukaj and access to their databases. in partnership with the Financial Data Team of the World Bank’s Development Data Group, Development 5. States and markets Research Group (trade), Development Prospects Section 5 was prepared by Federico Escaler and Buy- Group (commodity prices and remittances), Inter- ant Erdene Khaltarkhuu in partnership with the World national Trade Department (trade facilitation), and Bank’s Financial and Private Sector Development Net- external partners. Evis Rucaj wrote the introduction. work, Poverty Reduction and Economic Management Azita Amjadi (trade and tariffs) and Rubena Sukaj Network, and Sustainable Development Network; the (external debt and financial data) provided input on International Finance Corporation; and external part- the data and tables. Other contributors include Fré- ners. Buyant Erdene Khaltarkhuu wrote the introduction déric Docquier (emigration rates); Flavine Creppy and with input from Neil Fantom, Tariq Khokhar, and William Yumiko Mochizuki of the United Nations Conference on Prince. Other contributors include Alexander Nicholas Trade and Development and Mondher Mimouni of the Jett (privatization and infrastructure projects); Leora International Trade Centre (trade); Cristina Savescu Klapper and Frederic Meunier (business registration); (commodity prices); Jeff Reynolds and Joseph Siegel Jorge Luis Rodriguez Meza, Valeria Perotti, and Joshua of DHL (freight costs); Yasmin Ahmad and Elena Ber- Wimpey (Enterprise Surveys); Frederic Meunier and naldo of the Organisation for Economic Co-operation Rita Ramalho (Doing Business); Alka Banerjee, Trisha and Development (aid); Ibrahim Levent and Maryna Malinky, and Michael Orzano (Standard & Poor’s global Taran (external debt); Tarek Abou Chabake of the stock market indexes); Kenneth Anye (fragile situa- Office of the UN High Commissioner for Refugees tions); James Hackett of the International Institute for (refugees); and Teresa Ciller of the World Tourism 114 World Development Indicators 2014 Front ? User guide World view People Environment Organization (tourism). Ramgopal Erabelly, Shelley Bergeron, Stephen McGroarty, Nora Ridolfi, Paola Fu, and William Prince provided technical assistance. Scalabrin, and Janice Tuten coordinated printing, marketing, and distribution. Merrell Tuck-Primdahl of Other parts of the book the Development Economics Vice President’s Office Jeff Lecksell of the World Bank’s Map Design Unit managed the communications strategy. coordinated preparation of the maps on the inside cov- ers. William Prince prepared User guide and the lists World Development Indicators of online tables and indicators for each section and mobile applications wrote Statistical methods, with input from Neil Fantom. Software preparation and testing were managed by Liu Cui and Federico Escaler prepared Primary data Shelley Fu with assistance from Prashant Chaudhari, documentation. Leila Rafei prepared Partners. Neil Fantom, Mohammed Omar Hadi, Soong Sup Lee, Parastoo Oloumi, William Prince, Virginia Romand, Database management Jomo Tariku, and Malarvizhi Veerappan. Systems William Prince coordinated management of the World development was undertaken in the Data and Infor- Development Indicators database, with assistance mation Systems Team led by Soong Sup Lee. Liu Cui from Liu Cui and Shelley Fu in the Data Administration and William Prince provided data quality assurance. and Quality Team. Operation of the database man- agement system was made possible by Ramgopal Online access Erabelly in the Data and Information Systems Team Coordination of the presentation of the WDI online, under the leadership of Soong Sup Lee. through the Open Data website, the DataBank appli- cation, the table browser application, and the Appli- Design, production, and editing cation Programming Interface, was provided by Neil Azita Amjadi and Leila Rafei coordinated all stages Fantom and Soong Sup Lee. Development and main- of production with Communications Development tenance of the website were managed by a team led Incorporated, which provided overall design direc- by Azita Amjadi and comprising George Gongadze, tion, editing, and layout, led by Jack Harlow, Bruce Timothy Herzog, Meri Jebirashvili, Jeffrey McCoy, Leila Ross-Larson, and Christopher Trott. Elaine Wilson cre- Rafei, and Jomo Tariku. Systems development was ated the cover and graphics and typeset the book. managed by a team led by Soong Sup Lee, with proj- Peter Grundy, of Peter Grundy Art & Design, and Diane ect management provided by Malarvizhi Veerappan. Broadley, of Broadley Design, designed the report. Design, programming, and testing were carried out by Ying Chi, Shelley Fu, Siddhesh Kaushik, Ugendran Administrative assistance, office technology, Machakkalai, Nacer Megherbi, Shanmugam Nata- and systems development support rajan, Parastoo Oloumi, Manish Rathore, Ashish B. Elysee Kiti provided administrative assistance. Jean- Shah, Atsushi Shimo, Maryna Taran, and Jomo Tariku. Pierre Djomalieu, Gytis Kanchas, and Nacer Megherbi Liu Cui and William Prince coordinated production and provided information technology support. Ugendran provided data quality assurance. Multilingual transla- Machakkalai, Shanmugam Natarajan, Atsushi Shimo, tions of online content were provided by a team in the and Malarvizhi Veerappan provided software support General Services Department. on the DataBank application. Client feedback Publishing and dissemination The team is grateful to the many people who have The World Bank’s Publishing and Knowledge Division, taken the time to provide feedback and suggestions, under the direction of Carlos Rossel, provided assis- which have helped improve this year’s edition. Please tance throughout the production process. Denise contact us at data@worldbank.org. Economy States and markets Global links Back World Development Indicators 2014 115 ECO -AUDIT Environmental Benefits Statement The World Bank is committed to preserving Saved: endangered forests and natural resources. • 12 trees World Development Indicators 2014 is printed • 5 million British on recycled paper with 30  percent post- thermal units of total energy consumer fi ber in accordance with the rec- • 1,072 pounds of net ommended standards for paper usage set greenhouse gases by the Green Press Initiative, a nonprofi t • 5,816 gallons of program supporting publishers in using waste water fi ber that is not sourced from endangered • 389 pounds of solid forests. For more information, visit www waste .greenpressinitiative.org. The world by region Classified according to Low- and middle-income economies World Bank analytical East Asia and Pacific Middle East and North Africa High-income economies grouping Europe and Central Asia South Asia OECD Latin America and the Caribbean Sub-Saharan Africa Other No data