76824 The world by income Low ($1,025 or less) Classified according to Lower middle ($1,026–$4,035) World Bank estimates of 2011 GNI per capita Upper middle ($4,036–$12,475) High ($12,476 or more) No data Greenland (Den) Iceland Faeroe Norway Islands (Den) Sweden Finland Russian Federation The Netherlands Estonia Isle of Man (UK) Canada Denmark Russian Latvia Fed. Lithuania United Ireland Kingdom Germany Poland Belarus Channel Islands (UK) Belgium Ukraine Luxembourg Moldova Kazakhstan Mongolia Liechtenstein France Italy Romania Switzerland Bulgaria Georgia Uzbekistan Kyrgyz Andorra Armenia Azer- Rep. Dem.People’s United States Spain baijan Turkmenistan Rep.of Korea Portugal Turkey Tajikistan Monaco Greece Japan Cyprus Syrian Rep.of Gibraltar (UK) Arab Islamic Rep. Korea Bermuda Malta Lebanon China Tunisia Rep. of Iran Afghanistan (UK) Israel Iraq Morocco Kuwait West Bank and Gaza Jordan Algeria Bahrain Pakistan Bhutan Libya Arab Rep. Qatar Nepal The Bahamas Western of Egypt Saudi Sahara Arabia Bangladesh Cayman Is.(UK) United Arab Turks and Caicos Is. (UK) Emirates India Mexico Cuba Myanmar Mauritania Oman Lao Haiti Cape Verde P.D.R. Belize Jamaica Mali Niger N. Mariana Islands (US) Chad Eritrea Rep. of Yemen Thailand Guatemala Honduras Senegal Sudan The Gambia Vietnam Guam (US) El Salvador Nicaragua Burkina Cambodia Guinea-Bissau Faso Djibouti Philippines Guinea Federated States of Micronesia Costa Rica Benin Marshall Islands Panama Nigeria Central Ethiopia Sri R.B. de Guyana Sierra Leone Côte Ghana Lanka Venezuela d’Ivoire African South Suriname Republic Sudan Brunei Darussalam Liberia Palau French Guiana (Fr) Cameroon Malaysia Colombia Togo Somalia Equatorial Guinea Maldives Uganda São Tomé and Príncipe Kenya Nauru Kiribati Congo Singapore Ecuador Gabon Rwanda Kiribati Dem.Rep.of Burundi Seychelles Congo Solomon Tanzania Papua New Guinea Islands Comoros Indonesia Tuvalu Peru Brazil Timor-Leste Samoa French Polynesia (Fr) Angola Malawi Zambia Mayotte American (Fr) Vanuatu Fiji Samoa (US) Bolivia Mozambique Fiji Zimbabwe Madagascar Tonga Mauritius Namibia Botswana New Paraguay Réunion (Fr) Caledonia Australia (Fr) Swaziland Dominican St. Martin (Fr) Germany South Republic Puerto Poland Lesotho Rico (US) St. Maarten (Neth) Africa Czech Republic Ukraine Uruguay Slovak Republic Antigua and Barbuda Chile U.S. Virgin Argentina Islands (US) Guadeloupe (Fr) Austria St. Kitts Hungary New and Nevis Zealand Dominica Slovenia Romania Croatia Martinique (Fr) Bosnia and St. Lucia Herzegovina Serbia Aruba (Neth) St. Vincent and San Curaçao (Neth) the Grenadines Barbados Marino Kosovo Bulgaria Grenada Italy Montenegro FYR Macedonia Trinidad Vatican Albania and Tobago City Greece R.B. de Venezuela Antarctica IBRD 39817 MARCH 2013 Designed, edited, and produced by Communications Development Incorporated, Washington, D.C., with Peter Grundy Art & Design, London 2013 World Development Indicators © 2013 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 16 15 14 13 This work is a product of the staff of The World Bank with external contributions. 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The World Bank shall not be liable for any content or error in this translation. All queries on rights and licenses should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2625; e-mail: pubrights@ worldbank.org. ISBN (paper): 978-0-8213-9824-1 ISBN (electronic): 978-0-8213-9825-8 DOI: 10.1596/978-0-8213-9824-1 Cover photo: Arne Hoel/World Bank; Cover design: Communications Development Incorporated. Other photos: page xviii, Arne Hoel/World Bank; page 34, Kim Eun Yeul/World Bank; page 50, Curt Carnemark/World Bank; page 64, Gerardo Pesantez/ World Bank; page 78, Maria Fleischmann/ World Bank; page 92, Curt Carnemark/World Bank. Preface Welcome to World Development Indicators 2013, the additions and revisions to the data. They will be avail- World Bank’s premier compilation of relevant, high- able to a far greater audience. And they will be free quality, and internationally comparable statistics for everyone. about global development. World Development Indicators 2013 is organized The first edition of World Development Indicators around six themes—world view, people, environment, in 1997 included this forecast: “The global economy economy, states and markets, and global links. Each is undergoing an information revolution that will be section includes an introduction, a set of six stories as significant in effect as the industrial revolution of highlighting regional trends, a table of the most rel- the nineteenth century.� At that time the number of evant and popular indicators, and an index to the full mobile phones worldwide was estimated to be less set of tables and indicators available online. World than 2  per 100  people, with eight times as many view also reviews progress toward the Millennium telephone mainlines. World Development Indicators Development Goals. has tracked the revolution: this edition reports that Other companion products include The Little Data mobile phone subscriptions in 2011 grew to 85 per Book 2013, which provides an at-a-glance view of indi- 100 people—a more than fortyfold increase. cators for each economy, and a new version of the This is just one example of how people were com- DataFinder mobile application, available in Chinese, municating and acquiring knowledge and how infor- English, French, and Spanish and designed to reflect mation was changing. But in addition to measuring the structure and tables of World Development Indica- the change, World Development Indicators has felt it tors 2013, for both tablet and handheld devices and directly. Use of the online database and the tools for all major mobile platforms (http://data.worldbank that access it—particularly the Open Data website .org/apps). (http://data.worldbank.org), the web-based DataBank World Development Indicators is the result of a query application (http://databank.worldbank.org), collaborative effort of many partners: the United and applications for mobile devices—has increased Nations family, the International Monetary Fund, the dramatically. International Telecommunication Union, the Organ- And so we have refined and improved the pre- isation for Economic Co-operation and Development, sentation of this 17th edition. Our aim is to find the the statistical offices of more than 200 economies, best way to put data in the hands of policymakers, and countless others. I extend my gratitude to them development specialists, students, and the public, all—and especially to government statisticians around so that they may use the data to reduce poverty and the world. Without their hard work, professionalism, solve the world’s most pressing development chal- and dedication, measuring and monitoring trends in lenges. The biggest change is that the data tables global development would not be possible. previously published in the book are now available We hope you will find the new World Development online (http://wdi.worldbank.org/tables). This has Indicators a useful resource, and we welcome any sug- many advantages: The tables will reflect the latest gestions to improve it at data@worldbank.org. Shaida Badiee Director Development Economics Data Group Economy States and markets Global links Back World Development Indicators 2013 iii Acknowledgments This book was prepared by a team led by Soong Sup Tito Cordella, Doerte Doemeland, Zia M. Qureshi, and Lee under the management of Neil Fantom and com- David Rosenblatt. prising Azita Amjadi, Liu Cui, Federico Escaler, Mahyar The choice of indicators and text content was shaped Eshragh-Tabary, Juan Feng, Masako Hiraga, Wendy through close consultation with and substantial contri- Ven-dee Huang, Bala Bhaskar Naidu Kalimili, Buyant butions from staff in the World Bank’s four thematic Khaltarkhuu, Elysee Kiti, Alison Kwong, Ibrahim Lev- networks—Sustainable Development, Human Develop- ent, Hiroko Maeda, Johan Mistiaen, Vanessa Moreira ment, Poverty Reduction and Economic Management, da Silva, Maurice Nsabimana, Beatriz Prieto-Oramas, and Financial and Private Sector Development—and William Prince, Evis Rucaj, Rubena Sukaj, Emi Suzuki, staff of the International Finance Corporation and the Eric Swanson, Jomo Tariku, Rasiel Victor Vellos, and Multilateral Investment Guarantee Agency. Most impor- Olga Victorovna Vybornaia, working closely with other tant, the team received substantial help, guidance, and teams in the Development Economics Vice Presiden- data from external partners. For individual acknowl- cy’s Development Data Group. edgments of contributions to the book’s content, see World Development Indicators electronic products Credits. For a listing of our key partners, see Partners. were prepared by a team led by Reza Farivari and com- Communications Development Incorporated pro- prising Ying Chi, Jean‑Pierre Djomalieu, Ramgopal Era- vided overall design direction, editing, and layout, belly, Shelley Fu, Gytis Kanchas, Siddhesh Kaushik, led by Meta de Coquereaumont, Jack Harlow, Bruce Ugendran Machakkalai, Nacer Megherbi, Shanmugam Ross-Larson, and Christopher Trott. Elaine Wilson cre- Natarajan, Parastoo Oloumi, Manish Rathore, Ash- ated the cover and graphics and typeset the book. ish Shah, Atsushi Shimo, Malarvizhi Veerappan, and Peter Grundy, of Peter Grundy Art & Design, and Diane Vera Wen. Broadley, of Broadley Design, designed the report. All work was carried out under the direction of Staff from The World Bank’s Office of the Publisher Shaida Badiee. Valuable advice was provided by oversaw printing and dissemination of the book. iv  World Development Indicators 2013 Front ? User guide World view People Environment Table of contents Prefaceiii Introduction Goal 1 Eradicate extreme poverty Acknowledgmentsiv Goal 2 Achieve universal primary education Goal 3 Promote gender equality and Partnersvi empower women Goal 4 Reduce child mortality User guide xii Goal 5 Improve maternal health Goal 6 Combat HIV/AIDS, malaria, and other diseases Goal 7 Ensure environmental sustainability Goal 8 Develop a global partnership for 1. World view1 development Targets and indicators for each goal World view indicators 2. People35 About the data Online tables and indicators Poverty indicators NEW! 3. Environment51 About the data 4. Economy65 5. States and markets79 Introduction Highlights Table of indicators 6. Global links93 About the data Online tables and indicators Primary data documentation 107 Statistical methods 118 Credits121 Economy States and markets Global links Back World Development Indicators 2013 v Partners Defining, gathering, and disseminating international tion of statistical indicators. All these contributors statistics is a collective effort of many people and have a strong belief that available, accurate data will organizations. The indicators presented in World Devel- improve the quality of public and private decisionmak- opment Indicators are the fruit of decades of work at ing. many levels, from the field workers who administer The organizations listed here have made World censuses and household surveys to the committees Development Indicators possible by sharing their data and working parties of the national and international and their expertise with us. More important, their col- statistical agencies that develop the nomenclature, laboration contributes to the World Bank’s efforts, and classifications, and standards fundamental to an to those of many others, to improve the quality of life international statistical system. Nongovernmental of the world’s people. We acknowledge our debt and organizations and the private sector have also made gratitude to all who have helped to build a base of important contributions, both in gathering primary comprehensive, quantitative information about the data and in organizing and publishing their results. world and its people. And academic researchers have played a crucial role For easy reference, web addresses are included for in developing statistical methods and carrying on a each listed organization. The addresses shown were continuing dialogue about the quality and interpreta- active on March 1, 2013. vi  World Development Indicators 2013 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 Programme Aviation Organization on HIV/AIDS www.icao.int www.unaids.org Economy States and markets Global links Back World Development Indicators 2013 vii Partners National Science United Nations Centre for Human Foundation 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 Development Trade and 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 2013 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 2013 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.org DHL Netcraft www.dhl.com http://news.netcraft.com x  World Development Indicators 2013 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 2013 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 1,200 time series indicators for 214 economies and more than 30 country 3 Environment groups, with data for many indicators going back more Deforestation Nationally protected areas Internal renewable freshwater Access to improved water Access to Urban improved population sanitation Particulate matter Carbon dioxide concentration emissions Energy use Electricity production than 50 years. b Terrestrial and resources source facilities urban-population- marine areas average weighted PM10 Per capita billion average % of total Per capita % of total % of total annual micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours The 2013 edition of World Development Indicators has Afghanistan 2000–10 0.00 2011 0.4 2011 1,335 2010 50 2010 37 1990–2011 4.0 2010 30 2009 6.3 2010 .. 2010 .. Albania –0.10 8.4 8,364 95 94 2.4 38 3.0 648 7.6 been reconfigured to offer a more condensed presentation Algeria American Samoa 0.57 0.19 6.2 16.7 313 .. 83 .. 95 .. 2.6 1.9 69 .. 121.3 .. 1,138 .. 45.6 .. Andorra 0.00 6.1 3,663 100 100 0.9 18 0.5 .. .. of the principal indicators, arranged in their traditional sec- Angola Antigua and Barbuda 0.21 0.20 12.1 1.0 7,544 580 51 .. 58 .. 4.1 1.0 58 13 26.7 0.5 716 .. 5.3 .. Argentina 0.81 5.3 6,771 .. .. 1.0 57 174.7 1,847 125.3 tions, along with regional and topical highlights. Armenia Aruba 1.48 0.00 8.0 0.0 2,212 .. 98 100 90 .. 0.3 0.8 45 .. 4.5 2.3 791 .. 6.5 .. Australia 0.37 12.5 22,039 100 100 1.3 13 400.2 5,653 241.5 Austria –0.13 22.9 6,529 100 100 0.7 27 62.3 4,034 67.9 Azerbaijan 0.00 7.1 885 80 82 1.8 27 49.1 1,307 18.7 Bahamas, The 0.00 1.0 58 .. 100 1.5 .. 2.6 .. ..   World view  People  Environment Bahrain Bangladesh –3.55 0.18 0.7 1.6 698 3 81 .. 56 .. 4.9 3.0 44 115 24.2 51.0 7,754 209 13.2 42.3 Barbados 0.00 0.1 292 100 100 1.4 35 1.6 .. .. Belarus –0.43 7.2 3,927 100 93 0.4 6 60.3 2,922 34.9 Belgium –0.16 13.2 1,089 100 100 1.2 21 103.6 5,586 93.8  Economy   States and markets   Global links Belize Benin 0.67 1.04 20.6 23.3 44,868 1,132 98 75 90 13 3.0 4.2 12 48 0.4 4.9 413 .. 0.2 .. Bermuda 0.00 5.1 .. .. .. 0.7 .. 0.5 .. .. Bhutan –0.34 28.3 105,653 96 44 3.9 20 0.4 .. .. Bolivia 0.50 18.5 30,085 88 27 2.2 57 14.5 737 6.9 Bosnia and Herzegovina 0.00 0.6 9,461 99 95 0.9 21 30.1 1,703 17.1 Botswana 0.99 30.9 1,182 96 62 2.2 64 4.4 1,128 0.5 Brazil 0.50 26.0 27,551 98 79 1.2 18 367.1 1,363 515.7 Tables Brunei Darussalam 0.44 29.6 20,939 .. .. 2.2 44 9.3 8,308 3.9 Bulgaria –1.53 8.9 2,858 100 100 –1.7 40 42.8 2,370 46.0 Burkina Faso 1.01 14.2 737 79 17 6.2 65 1.7 .. .. The tables include all World Bank member countries (188), Burundi 1.40 4.8 1,173 72 46 4.9 24 0.2 .. .. Cambodia 1.34 23.4 8,431 64 31 2.1 42 4.6 355 1.0 Cameroon 1.05 9.0 13,629 77 49 3.3 59 6.7 363 5.9 and all other economies with populations of more than Canada Cape Verde 0.00 –0.36 6.2 0.2 82,647 599 100 88 100 61 1.2 2.1 15 .. 513.9 0.3 7,380 .. 607.8 .. Cayman Islands 0.00 1.5 .. 96 96 0.9 .. 0.5 .. .. 30,000 (214 total). Countries and economies are listed Central African Republic Chad 0.13 0.66 17.7 9.4 31,425 1,301 67 51 34 13 2.6 3.0 35 83 0.2 0.4 .. .. .. .. Channel Islands .. 0.5 .. .. .. 0.8 .. .. .. .. alphabetically (except for Hong Kong SAR, China, and Chile China –0.25 –1.57 13.3 16.0 51,188 2,093 96 91 96 64 1.1 3.0 46 59 66.7 7,687.1 1,807 1,807 60.4 4,208.3 Hong Kong SAR, China .. 41.8 .. .. .. 0.1 .. 37.0 1,951 38.3 Macao SAR, China, which appear after China). Macao SAR, China Colombia .. 0.17 20.5 .. 45,006 .. 92 .. 77 .. 2.2 1.7 .. 19 1.5 71.2 696 .. 56.8 .. Comoros 9.34 .. 1,592 95 36 2.9 30 0.1 .. .. The term country, used interchangeably with economy, Congo, Dem. Rep. Congo, Rep. 0.20 0.07 10.0 9.7 13,283 53,626 45 71 24 18 4.3 3.0 35 57 2.7 1.9 360 363 7.9 0.6 does not imply political independence but refers to any terri- 46 World Development Indicators 2013 Front Users 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 orange 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, 2013. xii  World Development Indicators 2013 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 Environment 3 income (GNI) per capita (calculated using the World Bank Deforestation Nationally protected areas Internal renewable freshwater Access to improved water Access to improved population sanitation Urban Particulate matter Carbon dioxide concentration emissions Energy use Electricity production Atlas method). Because GNI per capita changes over time, the country composition of income groups may change b Terrestrial and resources source facilities urban-population- marine areas average weighted PM10 Per capita billion average % of total Per capita % of total % of total annual micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours Costa Rica 2000–10 –0.93 2011 17.6 2011 23,780 2010 97 2010 95 1990–2011 2.2 2010 27 2009 8.3 2010 998 2010 9.6 from one edition of World Development Indicators to the Côte d’Ivoire –0.15 21.8 3,813 80 24 3.5 30 6.6 485 6.0 Croatia Cuba –0.19 –1.66 9.5 5.3 8,562 3,387 99 94 99 91 0.2 –0.1 22 15 21.5 31.6 1,932 975 14.0 17.4 next. Once the classification is fixed for an edition, based Curacao .. .. .. .. .. .. .. .. .. .. Cyprus Czech Republic –0.09 –0.08 4.5 15.1 699 1,253 100 100 100 98 1.4 –0.3 27 16 8.2 108.1 2,215 4,193 5.4 85.3 on GNI per capita in the most recent year for which data Denmark –1.14 4.1 1,077 100 100 0.6 15 45.7 3,470 38.8 Djibouti Dominica 0.00 0.58 0.0 3.7 331 .. 88 .. 50 .. 2.0 0.1 28 20 0.5 0.1 .. .. .. .. are available (2011 in this edition), all historical data pre- Dominican Republic 0.00 24.1 2,088 86 83 2.1 14 20.3 840 15.9 Ecuador Egypt, Arab Rep. 1.81 –1.73 38.0 6.1 29,456 22 94 99 92 95 2.2 2.1 19 78 30.1 216.1 836 903 17.7 146.8 sented are based on the same country grouping. Low-income economies are those with a GNI per capita El Salvador 1.45 1.4 2,850 88 87 1.3 28 6.3 677 6.0 Equatorial Guinea 0.69 14.0 36,100 .. .. 3.2 6 4.8 .. .. Eritrea 0.28 3.8 517 61 14 5.2 61 0.5 142 0.3 Estonia Ethiopia 0.12 1.08 22.6 18.4 9,486 1,440 98 44 95 21 0.1 3.7 9 47 16.0 7.9 4,155 400 13.0 5.0 of $1,025 or less in 2011. Middle-income economies are Faeroe Islands 0.00 .. .. .. .. 0.8 11 0.7 .. .. Fiji Finland –0.34 0.14 0.2 8.5 32,876 19,858 98 100 100 83 1.7 0.6 20 15 0.8 53.6 6,787 .. 80.7 .. those with a GNI per capita of more than $1,025 but less France –0.39 17.1 3,057 100 100 1.2 12 363.4 4,031 564.3 French Polynesia Gabon –3.97 0.00 0.1 14.6 106,892 .. 100 87 98 33 1.1 2.3 .. 7 0.9 1.6 1,418 .. 1.8 .. than $12,475. Lower middle-income and upper middle- Gambia, The –0.41 1.3 1,689 89 68 3.7 60 0.4 .. .. Georgia Germany 0.09 0.00 3.4 42.3 12,958 1,308 98 100 100 95 1.0 0.2 49 16 5.8 734.6 700 4,003 10.1 622.1 income economies are separated at a GNI per capita of Ghana 2.08 14.0 1,214 86 14 3.6 22 7.4 382 8.4 Greece Greenland –0.81 0.00 9.9 40.1 5,133 .. 100 100 100 98 0.3 0.2 27 .. 94.9 0.6 2,440 .. 57.4 .. $4,036. High-income economies are those with a GNI per capita of $12,476 or more. The 17 participating member Grenada 0.00 0.1 .. .. 97 1.3 19 0.2 .. .. Guam 0.00 3.6 .. 100 99 1.3 .. .. .. .. Guatemala 1.40 29.5 7,400 92 78 3.4 51 15.2 713 8.8 Guinea Guinea-Bissau 0.54 0.48 6.4 26.9 22,110 10,342 74 64 18 20 3.8 3.6 55 48 1.2 0.3 .. .. .. .. countries of the euro area are presented as a subgroup Guyana 0.00 4.8 318,766 94 84 0.5 20 1.6 .. .. Haiti Honduras 0.76 2.06 0.1 13.9 1,285 12,371 69 87 17 77 3.8 3.1 35 34 2.3 7.7 229 601 0.6 6.7 under high income economies. Hungary –0.62 5.1 602 100 100 0.4 15 48.7 2,567 37.4 Iceland –4.99 13.2 532,892 100 100 0.4 18 2.0 16,882 17.1 India –0.46 4.8 1,165 92 34 2.5 52 1,979.4 566 959.9 Indonesia 0.51 6.4 8,332 82 54 2.5 60 451.8 867 169.8 Iran, Islamic Rep. Iraq 0.00 –0.09 6.9 0.1 1,718 1,068 96 79 100 73 1.3 2.8 56 88 602.1 109.0 2,817 1,180 233.0 50.2 Statistics Ireland –1.53 1.2 10,707 100 99 2.7 13 41.6 3,218 28.4 Isle of Man Israel 0.00 –0.07 15.1 .. 97 .. 100 .. 100 .. 0.5 1.9 .. 21 .. 67.2 3,005 .. 58.6 .. 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 2013 47 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 • Data for China do not include data for Hong Kong SAR, cannot be calculated because of missing data in the China; Macao SAR, China; or Taiwan, China. years shown. • Data for Indonesia include Timor-Leste through 1999. 0 or means zero or small enough that the number would • Data for Mayotte, to which a reference appeared in pre- 0.0 round to zero at the displayed number of decimal places. vious editions, are included in data for France. • Data for Serbia do not include data for Kosovo or / in dates, as in 2010/11, means that the period of Monte­negro. time, usually 12 months, straddles two calendar years • Data for Sudan include South Sudan unless otherwise and refers to a crop year, a survey year, or a fiscal year. noted. $ means current U.S. dollars unless otherwise noted. < means less than. Economy States and markets Global links Back World Development Indicators 2013 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 now avail- table number (for example, http://wdi.worldbank.org/ able online. Using an automated query process, these ref- table/1.1 to view the first table in the World view sec- erence tables will be consistently updated based on the tion). Each section of this book also lists the indicators revisions to the World Development Indicators database. included by table and by code. To view a specific 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 2013 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 an online Click to edit and revise the table in web resource that provides simple and quick access to DataBank collections of time series data. It has advanced functions Click to print the table and corresponding for selecting and displaying data, performing customized indicator 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, shared, and embedded as indicator metadata to PDF widgets on websites or blogs. For more information, see http://databank.worldbank.org/help. 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 2013 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 2013 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 2013 xvii WORLD VIEW xviii  World Development Indicators 2013 Front ? User guide World view People Environment 1 The Millennium Declaration adopted by all the measure progress. The Millennium Development members of the United Nations General Assem- Goals have contributed to the development of bly in 2000 represents a commitment to a more a statistical infrastructure that is increasingly effective, results-oriented development partner- capable of producing reliable statistics on vari- ship in the 21st century. Progress documented ous topics. The post-2015 agenda and a well- here and in the annual reports of the United designed monitoring framework will build on that Nations Secretary-­ General has been encourag- infrastructure. ing: poverty rates have fallen, more children— The international database for monitoring especially girls—are enrolled in and completing the Millennium Development Goals is a valu- school, and they are—on average—living longer able resource for analyzing many development and healthier lives. Fewer mothers die in child issues. The effort of building and maintaining birth, and more women have access to reproduc- such a database should not be underestimated, tive health services. and it will take several years to implement a The indicators used to monitor the Millen- new framework of goals and targets. To serve nium Development Goals have traced the path of as an analytical resource, the database will need the HIV epidemic, the resurgence and retreat of to include additional indicators, beyond those tuberculosis, and the step-by-step efforts to “roll directly associated with the targets and the core back malaria.� More people now have access data for conducting these indicators. New tech- to reliable water supplies and basic sanitation nologies and methods for reporting data should facilities. But forests continue to disappear and improve the quality and timeliness of the result- with them the habitat for many species of plants ing database. The quality of data will ultimately and animals, and greenhouse gases continue to depend on the capacity of national statistical accumulate in the atmosphere. systems, where most data originate. From the start monitoring the Millennium When the Millennium Development Goals Development Goals posed three challenges: were adopted, few developing countries had selecting appropriate targets and indicators, the capacity or resources to produce statistics constructing an international database for global of the requisite quality or frequency. Despite monitoring, and significantly improving the qual- much progress, the statistical capacity-building ity, frequency, and availability of the relevant sta- programs initiated over the last decade should tistics. When they were adopted, the target year continue, and other statistical domains need of 2015 seemed comfortably far away, and the attention. Planning for post-2015 goals must baseline year of 1990 for measuring progress include concomitant plans for investments in seemed a reasonable starting point with well- statistics—by governments and development established data. As we near the end of that partners alike. 25-year span, we have a better appreciation of The effort to achieve the Millennium Develop- how great those challenges were. ment Goals has been enormous. The next set of Already there is discussion of the post- goals will require an even larger effort. Without 2015 development agenda and the monitoring good statistics, we will never know if we have framework needed to record commitments and succeeded. Economy States and markets Global links Back World Development Indicators 2013 1 Goal 1 Eradicate extreme poverty Poverty rates The world will not have eradicated extreme pov- 1a continue to fall erty in 2015, but the Millennium Development People living on less than 2005 PPP $1.25 a day (%) Goal target of halving world poverty will have 75 Forecast been met. The proportion of people living on less 2010–15 than $1.25 a day fell from 43.1 percent in 1990 Sub-Saharan Africa to 22.7 percent in 2008, reaching new lows in 50 South Asia all six developing country regions. While the food, fuel, and financial crises over the past five 25 years worsened the situation of vulnerable popu- Latin America Europe & Central Asia lations and slowed poverty reduction in some & Caribbean Middle East & North Africa countries, global poverty rates continued to fall 0 in most regions. Preliminary estimates for 2010 1990 1995 2000 2005 2010 2015 estimate forecast confirm that the extreme poverty rate fell fur- Source: World Bank PovcalNet. ther, to 20.6 percent, reaching the global target five years early. Except in South Asia and Sub-­ Progress in reaching the 1b Saharan Africa the target has also been met at poverty target, 1990–2010 Share of countries making progress toward reducing poverty (%) the regional level (figure 1a). 100 Fur ther progress is possible and likely before the 2015 target date of the Millen- nium Development Goals. Developing econo- 50 mies are expected to maintain GDP growth of 6.6–6.8 percent over the next three years, with 0 growth of GDP per capita around 5.5 percent. Growth will be fastest in East Asia and Pacific 50 and South Asia, which still contain more than Reached target On track Off track Seriously off track half the world’s poorest people. Growth will 100 Europe East Asia Latin & Central America & Middle East & North South Asia Sub-Saharan Africa be slower in Sub-­ S aharan Africa, the poorest Asia Caribbean Source: World Bank staff calculations. Africa region in the world, but faster than in the pre- ceding years, quickening the pace of poverty Fewer people are living reduction. According to these forecasts, the 1c in extreme poverty proportion of people living in extreme poverty People living on less than 2005 PPP $1.25 a day (billions) will fall to 16 percent by 2015. Based on cur- 2.0 Forecast rent trends, 59 of 112 economies with ade- Europe & Central Asia 2010–15 Latin America quate data are likely to achieve the first Millen- & Caribbean 1.5 Middle East & North Africa nium Development Goal (figure 1b). The number of people living in extreme poverty will continue 1.0 to fall to less than a billion in 2015 (figure 1c). Of these, 40 percent will live in South Asia and 0.5 40 percent in Sub-­ S aharan Africa. South Asia How fast poverty reduction will proceed 0.0 Sub-Saharan Africa depends not just on the growth of GDP but 1990 1995 2000 2005 2010 estimate 2015 forecast also on its distribution. Income distribution has Source: World Bank PovcalNet. improved in some countries, such as Brazil, while 2  World Development Indicators 2013 Front ? User guide World view People Environment worsening in others, such as China. To speed Poorer 1d progress toward eliminating extreme poverty, than poor Average daily income of people living on less than 2005 PPP development strategies should attempt to $1.25 a day, 2008 (2005 PPP $) 1.25 increase not just the mean rate of growth but also the share of income going to the poor- 1.00 est part of the population. Sub-­ Saharan Africa, where average income is low and average income 0.75 of those below the poverty line is even lower, will 0.50 face great difficulties in bringing the poorest peo- ple to an adequate standard of living (figure 1d). 0.25 Latin America and the Caribbean, where average income is higher, must overcome extremely ineq- 0.00 East Asia Europe Latin Middle East South Sub-Saharan & Paci c & Central America & & North Asia Africa uitable income distributions. Asia Caribbean Africa Two Millennium Development Goal indicators Source: World Bank PovcalNet. address hunger and malnutrition. Child malnu- Fewer malnourished trition, measured by comparing a child’s weight 1e children with that of other children of similar age, reflects Malnutrition prevalence, weight for age (% of children under age 5) a shortfall in food energy, poor feeding prac- 60 tices by mothers, and lack of essential nutri- South Asia ents in the diet. Malnutrition in children often begins at birth, when poorly nourished mothers 40 give birth to underweight babies. Malnourished Sub-Saharan Africa children develop more slowly, enter school later, East Asia & Paci c and perform less well. Malnutrition rates have 20 Middle East & North Africa dropped substantially since 1990, from 28 per- Europe & Central Asia cent of children under age 5 in developing coun- Latin America & Caribbean 0 tries to 17 percent in 2011. Every developing 1990 1995 2000 2005 2011 region except Sub-­ S aharan Africa is on track Source: World Development Indicators database. to cut child malnutrition rates in half by 2015 (figure 1e). However, collecting data on malnutri- And fewer people lacking 1f tion through surveys with direct measurement of sufficient food energy children’s weight and height is costly, and many Undernourishment prevalence (% of population) countries lack the information to calculate time 40 trends. Undernourishment, a shortage of food energy 30 Sub-Saharan Africa to sustain normal daily activities, is affected by South Asia changes in the average amount of food available 20 Latin America and its distribution. After steady declines in most & Caribbean East Asia & Paci c regions from 1991 to 2005, further improve- 10 Middle East & North Africa ments in undernourishment have stalled, leav- Europe & Central Asia ing 13 percent of the world’s population, almost 0 900 million people, without adequate daily food 1991 1996 2001 2006 2011 Source: Food and Agriculture Organization and World Development intake (figure 1f). Indicators database. Economy States and markets Global links Back World Development Indicators 2013 3 Goal 2 Achieve universal primary education Growth in complete The commitment to provide primary education to 2a primary education has slowed every child is the oldest of the Millennium Devel- Primary school completion rate (% of relevant age group) opment Goals, having been set at the first Educa- 125 East Asia & Paci c Latin America tion for All conference in Jomtien, Thailand, more Europe & Central Asia & Caribbean 100 than 20 years ago. Middle East & Progress among the poorest countries has North Africa 75 South Asia accelerated since 2000, particularly in South Sub-Saharan Africa Asia and Sub-­ Saharan Africa, but full enrollment 50 remains elusive. Many children start school but 25 drop out before completion, discouraged by cost, distance, physical danger, and failure to progress. 0 1990 1995 2000 2005 2010 2015 Even as countries approach the target, the educa- Note: Dotted lines indicate progress needed to reach target. Source: United Nations Educational, Scientific and Cultural Organization tion demands of modern economies expand, and Institute of Statistics and World Development Indicators database. primary education will increasingly be of value only as a stepping stone toward secondary and Progress toward universal  2b higher education. primary education, 1990–2010 Share of countries making progress toward universal primary In most developing country regions school education (%) 100 enrollment picked up after the Millennium Development Goals were promulgated in 2000, 50 when the completion rate was 80 percent. Sub-­ Saharan Africa and South Asia, which started out farthest behind, made substantial prog- 0 ress. By 2009 nearly 90 percent of children in developing countries completed primary school, 50 but completion rates have stalled since, with Reached target On track Off track Seriously off track Insuf cient data no appreciable gains in any region (figure  2a). 100 East Asia Europe & Paci c Latin & Central America & Middle East & North South Asia Sub-Saharan Africa Three regions have attained or are close to Asia Caribbean Africa Source: World Bank staff calculations. attaining complete primary education: East Asia and Pacific, Europe and Central Asia, and Latin More girls than boys remain America and the Caribbean (figure 2b). Comple- 2c out of school in most regions tion rates in the Middle East and North Africa Children not attending primary school, 2010 (% of relevant age group) have stayed at 90 percent since 2008. South 30 Asia has reached 88 percent, but progress 25 has been slow. And Sub-­ S aharan Africa lags behind at 70 percent. Even if the schools in 20 these regions were to now enroll every eligible 15 child in the first grade, they would not be able 10 to achieve a full course of primary education by 5 2015. But it would help. Many children enroll in primary school but Boys Girls 0 East AsiaEurope Latin Middle East South Sub-Saharan attend intermittently or drop out entirely. This & Paci c& Central America & & North Asia Africa Asia Caribbean Africa is particularly true for girls—almost all school Source: United Nations Educational, Scientific and Cultural Organization Institute of Statistics and World Development Indicators database. 4  World Development Indicators 2013 Front ? User guide World view People Environment systems with low enrollment rates show under­ Rural students 2d enrollment of girls in primary school, since at a disadvantage Share of people ages 10–19 completing each grade of schooling, their work is needed at home (figure 2c). Other by location, 2010–11 (%) 100 obstacles discourage parents from sending their Urban Cambodia children to school, including the need for boys Urban Senegal Urban Ethiopia and girls during planting and harvest, lack of 75 Rural Ethiopia suitable school facilities, absence of teachers, Rural Cambodia and school fees. The problem is worst in South 50 Rural Senegal Asia and Sub-­ Saharan Africa, where more than 46 million children of primary school age are not 25 in school. Not all children have the same opportunities 0 Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 to enroll in school or remain in school. Across Source: Demographic and Health Surveys and World Bank EdStats the world, children in rural areas are less likely database. to enter school, and when they do, they are likely Parents’ education makes to drop out sooner. In Ethiopia nearly all urban 2e a difference in Nepal children complete first grade, but fewer than Share of people ages 10–19 completing each grade of schooling, by parents’ education level, 2011 (%) 80  percent of rural children do (figure  2d). In 100 Some higher Senegal, where slightly more than 80 percent of Primary urban children complete first grade, barely half Incomplete primary 75 of rural children begin the first grade and only Incomplete secondary No education 40  percent remain after nine years. Cambodia 50 follows a similar pattern. Parents’ education makes a big difference 25 in how far children go in school. In Nepal, for example, less than 90 percent of children whose 0 parents lack any education complete first grade Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 and barely 70 percent remain through the ninth Source: Demographic and Health Surveys and World Bank EdStats database. (figure  2e). But 95  percent of children from households with some higher education stay Poverty is a barrier to 2f through nine grades, and many of those go onto education in Senegal complete secondary school and enter tertiary Share of people ages 10–19 completing each grade of schooling, by wealth quintile, 2010 (%) education. 100 Income inequality and educational quality are Wealthiest quintile closely linked. Take Senegal (figure 2f). Children 75 Fourth quintile from wealthier households (as measured by a Third quintile household’s ownership of certain assets) are 50 more likely to enroll and stay in school than chil- Second quintile dren from poorer households. Thus children from 25 Poorest quintile poor households are least likely to acquire the one asset—human capital—that could most help 0 Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 them to escape poverty. Source: Demographic and Health Surveys and World Bank EdStats database. Economy States and markets Global links Back World Development Indicators 2013 5 Goal 3 Promote gender equality and empower women A ragged kind of parity Women make important contributions to eco- 3a in school enrollments nomic and social development. Expanding oppor- Ratio of girls’ to boys’ gross enrollment, 2011 (%) tunities for them in the public and private sectors is a core development strategy, and education East Asia Primary is the starting point. By enrolling and staying in Secondary & Paci c school, girls gains skills needed to enter the labor Tertiary market, care for families, and make decisions for themselves. Achieving gender equality in educa- Europe & tion is an important demonstration that young Central Asia women are full, contributing members of society. Girls have made substantial gains in school enrollment. In 1990 girls’ primary school enroll- Latin America ment rate in developing countries was only & Caribbean 86 percent of boys’. By 2011 it was 97 percent (figure 3a). Similar improvements have been made in secondary schooling, where girls’ enroll- Middle East & North Africa ments have risen from 78 percent of boys’ to 96 percent over the same period. But the aver- ages mask large differences across countries. At the end of 2011, 31 upper middle-income coun- South Asia tries had reached or exceeded equal enrollment of girls in primary and secondary education, as had 23  lower middle-income countries but only 9 low-income countries. South Asia and Sub-­ Sub-Saharan Africa Saharan Africa are lagging behind (figure 3b). Patterns of school attendance at the national 0 25 50 75 100 125 level mirror those at the regional level: poor house- Source: United Nations Educational, Scientific and Cultural Organization Institute of Statistics and World Development Indicators database. holds are less likely than wealthy households to keep their children in school, and girls from wealth- Progress toward gender equality ier households are more likely to enroll in school 3b in education, 1990–2010 and stay longer. Ethiopia is just one example of the Share of countries making progress toward gender equality in primary and secondary education (%) prevailing pattern documented by household sur- 100 veys from many developing countries (figure 3c). More women are participating in public life at 50 the highest levels. The proportion of parliamen- tary seats held by women continues to increase. 0 In Latin America and the Caribbean women now hold 25 percent of all parliamentary seats (figure 50 3d). The most impressive gains have been made Reached target On track Off track Seriously off track in the Middle East and North Africa, where the pro- Insuf cient data 100 portion of seats held by women more than tripled Europe East Asia Latin Middle East South Sub-Saharan & Paci c & Central America & Asia Caribbean & North Africa Asia Africa between 1990 and 2012. Algeria leads the way Source: World Bank staff calculations. with 32 percent. In Nepal a third of parliamentary 6  World Development Indicators 2013 Front ? User guide World view People Environment seats were held by women in 2012. Rwanda con- Girls are disadvantaged at 3c tinues to lead the world. Since 2008, 56 percent every income level in Ethiopia Share of people ages 10–19 completing each grade of schooling, of parliamentary seats have been held by women. by sex and wealth quintile, 2011 (%) 100 Women work long hours and make important Wealthiest quintile, boys Wealthiest quintile, contributions to their families’ welfare, but many girls Third quintile, boys in the informal sector are unpaid for their labor. 75 Third quintile, girls The largest proportion of women working in the formal sector is in Europe and Central Asia, 50 Poorest quintile, boys Poorest quintile, girls where the median proportion of women in wage employment outside the agricultural sector was 25 46  percent (figure  3e). Latin America and the Caribbean is not far behind, with 42 percent of 0 Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 Grade 6 Grade 7 Grade 8 Grade 9 women in nonagricultural employment. Women’s Source: Demographic and Health Surveys and World Bank EdStats share in paid employment in the nonagricultural database. sector has risen marginally but remains less More women than 20 percent in most countries in the Middle 3d in parliaments East and North Africa and South Asia and less Share of seats held by women in national parliaments (%) than 35 percent in Sub-­ Saharan Africa. In these 25 regions full economic empowerment of women remains a distant goal. 20 East Asia & Paci c Lack of data hampers the ability to understand 15 Latin America women’s roles in the economy. The Evidence and & Caribbean Europe & Central Asia Data for Gender Equality (EDGE) Initiative is a Sub-Saharan Africa 10 new partnership, jointly managed by UN Women South Asia and the United Nations Statistics Division, in col- 5 laboration with member states, the World Bank, Middle East & North Africa 0 the Organisation for Economic Co-operation and 1990 1995 2000 2005 2012 Development, and others, that seeks to acceler- Source: Inter-Parliamentary Union and World Development Indicators database. ate the work of gathering indicators on women’s education, employment, entrepreneurship, and Women still lack opportunities 3e asset ownership. During its initial phase EDGE in the labor market will lay the ground work for a database of basic Share of women employed in the nonagricultural sector, median value, most recent year available, 2004–10 (% of total education and employment indicators, develop- nonagricultural employment) 50 ing standards and guidelines for entrepreneur- 40 ship and assets indicators, and pilot data in sev- eral countries. Relevant indicators could include 30 the percentage distribution of the employed 20 population, by sector and sex; the proportion of employed who are employer, by sex; the length of 10 maternity leave; the percentage of firms owned 0 East Asia Europe Latin Middle East South Sub-Saharan by women; the proportion of the population with & Paci ca& Central America & & North Asia Africaa Asia Caribbean Africa access to credit, by sex; and the proportion of the a. Data cover less than two-thirds of regional population. Source: International Labour Organization and World Development population who own land, by sex. Indicators database. Economy States and markets Global links Back World Development Indicators 2013 7 Goal 4 Reduce child mortality Under-five mortality rates In 1990, 12 million children died before their fifth 4a continue to fall birthday. By 1999 fewer than 10 million did. And Under- ve mortality rate (per 1,000 live births) in 2012 7 million did. In developing countries the 200 under-five mortality rate fell from an average of 95 per 1,000 live births in 1990 to 56 in 2011, but 150 Sub-Saharan Africa rates in Sub-­Saharan Africa and South Asia remain much higher (figure 4a). Currently, 41 countries 100 are poised to reach the Millennium Development East Asia & Paci c South Asia Goal target of a two-thirds reduction in under-five 50 Middle East & mortality rates by 2015 (figure 4b). Faster improve- North Africa Europe & Central Asia Latin America ments over the last decade suggest that many & Caribbean 0 countries are accelerating progress and another 1990 1995 2000 2005 2011 Source: Inter-agency Group for Child Mortality Estimation and World 25 could reach the target as soon as 2020. Look- Development Indicators database. ing past 2015, still faster progress is possible if high mortality countries give priority to addressing Progress toward reducing 4b the causes of child mortality. Concomitant reduc- child mortality, 1990–2010 Share of countries making progress toward reducing child mortality tions in fertility rates, particularly among adoles- (%) 100 cents, will also help. Most children die from causes that are read- 50 ily preventable or curable with existing interven- tions, such as pneumonia (18 percent), diarrhea (11 percent), and malaria (7 percent). Almost 70 0 percent of deaths of children under age 5 occur in the first year of life, and 60 percent of those 50 in the first month (figure 4c). Preterm birth com- Reached target On track Off track Seriously off track Insuf cient data plications account for 14 percent of deaths, and 100 East Asia Europe & Paci c Latin & Central America & Middle East & North South Asia Sub-Saharan Africa complications during birth another 9 percent (UN Asia Caribbean Africa Source: World Bank staff calculations. Inter-Agency Group for Child Mortality Estimation 2012). Therefore reducing child mortality requires As mortality rates fall, a larger proportion addressing the causes of neonatal and infant 4c of deaths occur in the first month deaths: inadequate care at birth and afterward, Deaths of children under age 5, 2011 (millions) malnutrition, poor sanitation, and exposure to 4 Children (ages 1–4) acute and chronic disease. Lower infant and child Infants (ages 1–11 months) Neonatals (ages 0–1 month) mortality rates are, in turn, the largest contribu- 3 tors to higher life expectancy in most countries. Childhood vaccinations are a proven, cost-­ 2 effective way of reducing childhood illness and death. But despite years of vaccination campaigns, 1 many children in low- and lower middle-income economies remain unprotected. To be success- 0 East Asia Europe Latin Middle East South Sub-Saharan ful, vaccination campaigns must reach all children & Central America & & Paci c & North Asia Africa Asia Caribbean Africa and be sustained over time. Thus it is worrisome Source: Inter-agency Group for Child Mortality Estimation and World Development Indicators database. that measles vaccination rates in the two highest 8  World Development Indicators 2013 Front ? User guide World view People Environment mortality regions, South Asia and Sub-­ Saharan Measles immunization 4d Africa, have stagnated in the last three years, at rates are stagnating Children ages 12–23 months immunized against measles (%) less than 80 percent coverage (figure 4d). 100 Twenty countries in the developing world East Asia Europe & Central Asia & Paci c accounted for 4.5 million deaths among children Middle East & North Africa under age 5 in 2011, or 65 percent of all such 75 Latin America & Caribbean deaths worldwide (figure 4e). These countries are South Asia Sub-Saharan Africa mostly large, often with high birth rates, but many 50 have substantially reduced mortality rates over the past two decades. Of the 20, 11 have reached 25 or are likely to achieve a two-thirds reduction in their under-five mortality rate by 2015: Bangla- 0 1990 1995 2000 2005 2011 desh, Brazil, China, the Arab Republic of Egypt, Source: World Health Organization, United Nations Children’s Fund, and Ethiopia, Indonesia, Madagascar, Malawi, Mexico, World Development Indicators database. Niger, and Turkey. Had the mortality rates of 1990 Five million deaths prevailed in 2011, these 11 countries would have 4e averted in 20 countries experienced 2 million more deaths. The remaining Deaths of children under age 5, 2011 (millions) nine, where progress has been slower, have nev- At 2011 mortality rate Averted based on 1990 mortality rate ertheless averted 3 million deaths. If India were India on track to reach the target, another 440,000 Nigeria deaths would have been averted. China The data used to monitor child mortality are pro- Pakistan duced by the Inter-agency Group for Child Mortal- Ethiopia ity Estimation (IGME), which evaluates data from Bangladesh existing sources and then fits a statistical model Indonesia to data points that are judged to be reliable. The model produces a trend line for under-five mortality Tanzania rates in each country. Infant mortality and neona- Afghanistan tal mortality rates are derived from under-five mor- Uganda tality estimates. The data come from household Niger surveys and, where available, vital registration sys- Mozambique tems. But surveys are slow and costly. While they Angola remain important tools for investigating certain Brazil complex, micro-level problems, vital registration systems are usually better sources of timely statis- Egypt, Arab Rep. tics. Recent IGME estimates of under-five mortality Malawi include new data from vital registration systems Philippines for about 70 countries. But many countries lack Madagascar complete reporting of vital events, and even those Mexico that do often misreport cause of death. Vital reg- Turkey istration supplemented by surveys and censuses 0 1 2 3 4 offers the best approach for improving knowledge of morbidity and mortality in all age groups. Source: World Bank staff calculations. Economy States and markets Global links Back World Development Indicators 2013 9 Goal 5 Improve maternal health Maternal deaths are more likely in An estimated 287,000 maternal deaths occurred 5a Saharan Africa South Asia and Sub-­ worldwide in 2010, all but 1,700 of them in Maternal mortality ratio, modeled estimate (per 100,000 live births) developing countries. More than half of mater- 1,000 nal deaths occur in Sub-­ S aharan Africa and a Sub-Saharan Africa quarter in South Asia. And while the number of 750 maternal deaths remains high, South Asia has South Asia made great progress in reducing them, reaching 500 a maternal mortality ratio of 220 per 100,000 Latin America live births in 2010, down from 620 in 1990, a & Caribbean 250 Middle East & North Africa drop of 65 percent. The Middle East and North East Asia & Paci c Africa and East Asia and Pacific have also 0 Europe & Central Asia reduced their maternal morality ratios more than 1990 1995 2000 2005 2010 Source: Maternal Mortality Estimation Inter-Agency Group and World 60 percent (figure 5a). Development Indicators database. These are impressive achievements, but prog- ress in reducing maternal mortality has been Progress toward reducing 5b slow, far slower than targeted by the Millennium maternal mortality, 1990–2010 Share of countries making progress toward reducing maternal Development Goals, which call for reducing the mortality (%) 100 maternal mortality ratio by 75 percent between 1990 and 2015. But few countries and no devel- 50 oping region on average will achieve this target. Based on progress through 2010, 8 countries have achieved a 75 percent reduction, and 10 0 more are on track to reach the 2015 target (fig- ure 5b). This is an improvement over the 2008 50 assessment, suggesting that progress is accel- Reached target On track Off track Seriously off track Insuf cient data erating. Because of the reductions in Cambodia, 100 East Asia & Paci c Europe Latin & Central America & Middle East & North South Asia Sub-Saharan Africa China, Lao People’s Democratic Republic, and Asia Caribbean Africa Source: World Bank staff calculations. Vietnam, 74 percent of people in East Asia and Pacific live in a country that has reached the tar- Reducing the get (Vietnam) or is on track to do so by 2015. 5c risk to mothers On average a third of people in low- and middle- Lifetime risk of maternal death (%) income countries live in countries that have 6 reached the target or are on track to do so. The maternal mortality ratio gives the risk of a maternal death at each birth, a risk compounded 4 with each pregnancy. And because women in poor countries have more children under riskier 2 conditions, their lifetime risk of maternal death may be 100 times greater than for women in high- 1990 2010 income countries. Improved health care and lower 0 East Asia Europe Latin Middle East South Sub-Saharan fertility rates have reduced the lifetime risk in all & Paci c & Central America & & North Asia Africa Asia Caribbean Africa regions, but women ages 15–49 in Sub-­ Saharan Source: Maternal Mortality Estimation Inter-Agency Group and World Development Indicators database. Africa still face a 2.5 percent chance of dying 10  World Development Indicators 2013 Front ? User guide World view People Environment in childbirth, down from more than 5 percent in A wide range 5d 1990 (figure 5c). In Chad and Somalia, both frag- of needs Unmet need for contraception, most recent year available, ile states, lifetime risk is still more than 6  per- 2006–10 (% of women married or in union ages 15–49) 50 cent, meaning more than 1 woman in 16 will die Regional median in childbirth. 40 Reducing maternal mortality requires a com- 30 prehensive approach to women’s reproductive health, starting with family planning and access 20 to contraception. In countries with data half of women who are married or in union use some 10 method of birth control. Household surveys of 0 East Asia Europe Latin Middle East South Sub-Saharan women show that some 200 million women & Paci c & Central America & & North Asia Africa (7 countries) Asia Caribbean Africa (5 countries) (31 countries) want to delay or cease childbearing, and a sub- (10 countries) (9 countries) (6 countries) Source: Demographic and Household Surveys, Multiple Indicator Cluster stantial proportion say that their last birth was Surveys, and World Development Indicators database. unwanted or mistimed (United Nations 2012). Fewer young women Figure 5d shows the share of women of child- 5e giving birth bearing age who say they need but are not using Adolescent fertility rate (births per 1,000 women ages 15–19) contraception. There are large differences within 150 each region. More surveys have been carried out Sub-Saharan Africa in Sub-­Saharan Africa than in any other region, South Asia and many show a large unmet need for family 100 planning. Latin America & Caribbean Women who give birth at an early age are likely Middle East & North Africa to bear more children and are at greater risk of 50 death or serious complications from pregnancy. Europe & Central Asia The adolescent birth rate is highest in Sub-­ East Asia & Paci c Saharan Africa and is declining slowly. A rapid 0 1997 1999 2001 2003 2005 2007 2009 2011 decrease in South Asia has been led by Maldives, Source: United Nations Population Division and World Development Indicators database. Afghanistan, and Pakistan (figure 5e). Many health problems among pregnant women Every mother 5f are preventable or treatable through visits with needs care trained health workers before childbirth. Skilled Births attended by skilled health staff, average of most recent year available for 2007–11 (% of total) attendants at delivery and access to hospital 100 treatments are essential for dealing with life- threatening emergencies such as severe bleed- 75 ing and hypertensive disorders. In South Asia and 50 Sub-­ Saharan Africa fewer than half of births are attended by doctors, nurses, or trained midwives 25 (figure 5f). Having skilled health workers present for deliveries is key to reducing maternal mortal- 0 ity. In many places women have only untrained East Asia & Paci c Europe Latin & Central America & Middle East & North South Asia Sub-Saharan Africa Asia Caribbeana Africaa caregivers or family members to attend them dur- a. Data are for 1998–2002. Source: United Nations Children’s Fund and World Development ing childbirth. Indicators database. Economy States and markets Global links Back World Development Indicators 2013 11 Goal 6 Combat HIV/AIDS, malaria, and other diseases HIV prevalence in Sub-­ Saharan Epidemic diseases exact a huge toll in human 6a Africa continues to fall suffering and lost opportunities for development. HIV prevalence (% of population ages 15–49) Poverty, armed conflict, and natural disasters 6 Sub-Saharan Africa contribute to the spread of disease and are made 5 worse by it. In Africa the spread of HIV/AIDS has reversed decades of improvement in life expec- 4 tancy and left millions of children orphaned. 3 Malaria takes a large toll on young children and 2 weakens adults at great cost to their productiv- Latin America & Caribbean High income ity. Tuberculosis killed 1.4 million people in 2010, 1 Other developing regions most of them ages 15–45, and sickened millions 0 more. 1990 1995 2000 2005 2011 Source: Joint United Nations Programme on HIV/AIDS and World There were 34 million people living with HIV/ Development Indicators database. AIDS in 2011, and 2.5 million more people acquired the disease. Sub-­ Saharan Africa remains Progress toward halting and reversing 6b the center of the HIV/AIDS epidemic, but the pro- the HIV epidemic, 1990–2010 Share of countries making progress against HIV/AIDS (%) portion of adults living with AIDS has begun to 100 fall even as the survival rate of those with access to antiretroviral drugs has increased (figures 6a and 6b). By the end of 2010, 6.5 million people 50 worldwide were receiving antiretroviral drugs. This represented the largest one-year increase in cov- 0 erage but still fell far short of universal access (United Nations 2012). 50 Altering the course of the HIV epidemic requires Halted and reversed Halted or reversed Stable low prevalence Not improving Insuf cient data changes in behaviors by those already infected by 100 East Asia Europe & Paci c Latin & Central America & Middle East & North South Asia Sub-Saharan Africa the virus and those at risk of becoming infected. Asia Caribbean Source: World Bank staff calculations. Africa Knowledge of the cause of the disease, its trans- mission, and what can be done to avoid it is the Knowledge to starting point. The ability to reject false informa- 6c control HIV/AIDS tion is another important kind of knowledge. But People with comprehensive and correct knowledge about HIV, most recent year available (% of adults ages 15–49) significant gaps in knowledge remain. In 26 of 75 31 countries with a generalized epidemic and in which nationally representative surveys were car- 50 ried out recently, less than half of young women have comprehensive and correct knowledge about 25 HIV (UNAIDS 2012). And less than half of men in 21 of 25 countries had correct knowledge. In only Women Men 0 nia d o e bia ia ue i da a law bw ny th n mb biq ila an za mi so Ke Ma ba az Za Ug n Le Na am Ta Zim Sw z Mo Note: Comprehensive and correct knowledge about HIV entails knowledge of two ways to prevent HIV and rejecting three misconceptions. Source: Joint United Nations Programme on HIV/AIDS and World Development Indicators database. 12  World Development Indicators 2013 Front ? User guide World view People Environment 3 of the 10 countries with the highest HIV preva- Fewer people contracting, living with, 6d lence rates in 2011 did more than half the men and dying from tuberculosis Tuberculosis prevalence, incidence, and deaths in low- and and women tested demonstrate knowledge of two middle-income countries (per 100,000 people) 400 ways to prevent HIV and reject three misconcep- tions (figure 6c). In Kenya men scored better than Prevalence 50  percent, but women fell short. Clearly more 300 work is to be done. In 2011 there were 8.8  million people newly 200 diagnosed with tuberculosis, but incidence, prev- Incidence alence, and death rates from tuberculosis are 100 falling (figure 6d). If these trends are sustained, Deaths the world could achieve the target of halting and 0 1990 1995 2000 2005 2011 reversing the spread of this disease by 2015. Source: World Health Organization and World Development Indicators People living with HIV/AIDS, which reduces resis- database. tance to tuberculosis, are particularly vulnerable, Use of insecticide-treated nets as are refugees, displaced persons, and prison- 6e increasing in Sub- ­Saharan Africa ers living in close quarters and unsanitary con- Use of insecticide-treated nets (% of population under age 5) ditions. Well-managed medical intervention using First observation (2000 or earlier) Most recent observation (2006 or later) Swaziland appropriate drug therapy is crucial to stopping the Côte d’Ivoire Guinea spread of tuberculosis. Comoros There are 300–500 million cases of malaria Zimbabwe Chad each year, causing more than 1 million deaths. Somalia Mozambique Malaria is a disease of poverty. But there has Benin Cameroon been progress against it. In 2011 Armenia was Sudan added to the list of countries certified free of the Angola Nigeria disease. Although malaria occurs in all regions, Sierra Leone Ethiopia Sub-­ Saharan Africa is where the most lethal form Gambia, The Namibia of the malaria parasite is most abundant. Insec- Senegal ticide-treated nets have proved to be an effec- Guinea-Bissau Central African Rep. tive preventative, and their use in the region is Liberia Congo, Dem. Rep. growing: from 2 percent of the population under Ghana Malawi age 5 in 2000 to 39 percent in 2010 (figure 6e). Uganda Better testing and the use of combination thera- Burundi Madagascar pies with artemisinin-based drugs are improving Kenya Burkina Faso the treatment of at-risk populations. But malaria Eritrea Zambia is difficult to control. There is evidence of emerg- Gabon ing resistance to artemisinins and to pyrethroid São Tomé and Príncipe Togo insecticides used to treat mosquito nets. Tanzania Niger Rwanda Mali Congo, Rep. (2005) Mauritania (2004) 0 20 40 60 80 Source: United Nations Children’s Fund and World Development Indicators database. Economy States and markets Global links Back World Development Indicators 2013 13 Goal 7 Ensure environmental sustainability Carbon dioxide emissions The seventh goal of the Millennium Development 7a dropped slightly in 2009 Goals is the most far-reaching, affecting each Carbon dioxide emissions (millions of metric tons) person now and in the future. It addresses the 40 condition of the natural and built environments: reversing the loss of natural resources, pre- 30 serving biodiversity, increasing access to safe water and sanitation, and improving living con- 20 High income ditions of people in slums. The overall theme is sustainability, an equilibrium in which people’s 10 lives can improve without depleting natural and Upper middle income manmade capital stocks. Low income 0 Lower middle income The failure to reach a comprehensive agree- 1990 1995 2000 2005 2009 Source: Carbon Dioxide Information Analysis Center and World ment on limiting greenhouse gas emissions leaves Development Indicators database. billions of people vulnerable to climate change. Although the global financial crisis caused a slight Forest losses 7b decrease in carbon dioxide emissions, such emis- and gains Average annual change in forest area (thousands of square sions are expected to rise as economic activity kilometers) 250 resumes in large industrial economies (figure 7a). The loss of forests threatens the livelihood of poor people, destroys the habitat that harbors bio- 0 diversity, and eliminates an important carbon sink 1990–2000 2000–10 that helps moderate the climate. Net losses since 1990 have been substantial, especially in Latin –250 American and the Caribbean and Sub-­ Saharan Africa, and only partly compensated by net gains –500 elsewhere. The rate of deforestation slowed in the East AsiaEurope Latin Middle East South Sub-Saharan High & Paci c& Central America & & North Asia Caribbean Africa Asia Africa income past decade, but on current trends zero net losses Source: Food and Agriculture Organization and World Development Indicators database. will not be reached for another 20 years (figure 7b). Protecting forests and other terrestrial and Better access to marine areas helps protect plant and animal 7c improved water sources habitats and preserve the diversity of species. By Share of population with access to improved water sources (%) 2010, 13  percent of the world’s land area had 100 been protected, but only 1.6 percent of oceans had similar protection. Such measures have 75 slowed the rate of species extinction, but sub- stantial losses continue (United Nations 2012). 50 The Millennium Development Goals call for halving the proportion of the population without 25 access to improved sanitation facilities and water 1990 2010 0 sources by 2015. In 1990 more than 1 billion East Asia Europe Latin Middle East South Sub-Saharan & Paci c & Central America & & North Asia Africa people lacked access to drinking water from a Asia Caribbean Africa Source: Joint Monitoring Programme of the World Health Organization convenient, protected source. In developing coun- and United Nations Children’s Fund and World Development Indicators database. tries the proportion of people with access to an 14  World Development Indicators 2013 Front ? User guide World view People Environment improved water source rose from 71 percent in Rural areas lack 7d 1990 to 86 in 2010 (figure 7c). sanitation facilities Share of population with access to improved sanitation facilities, In 1990 only 37 percent of the people living in 2010 (%) 100 low- and middle-income economies had access to a flush toilet or other form of improved sanitation. 75 By 2010 the access rate had risen to 56  per- cent. But 2.7 billion people still lack access to 50 improved sanitation, and more than 1 billion prac- tice open defecation, posing enormous health 25 risks. The situation is worse in rural areas, where Urban Rural 43 percent of the population have access to 0 East Asia Europe Latin Middle East South Sub-Saharan improved sanitation; in urban areas the access & Paci c & Central America & & North Asia Africa Asia Caribbean Africa rate is 30 percentage points higher (figure 7d). Source: Joint Monitoring Programme of the World Health Organization and United Nations Children’s Fund and World Development Indicators This large disparity, especially in South Asia and database. Sub-­ Saharan Africa, is the principal reason the Resource rents are a large share of sanitation target of the Millennium Development 7e GDP in Africa and the Middle East Goals will not be met. Resource rents (% of GDP) Achieving sustainable development also 50 requires managing natural resources carefully, since high economic growth can deplete natural 40 Middle East & North Africa capital, such as forests and minerals. Countries 30 that rely heavily on extractive industries have Europe & Central Asia seen large increases in natural resource rents, 20 but their growth will not be sustainable unless Sub-Saharan Africa they invest in productive assets, including human 10 capital (figure 7e). Latin America & Caribbean East Asia & Paci c South Asia The World Bank has constructed a global data- 0 1990 1995 2000 2005 2010 base to monitor the sustainability of economic Source: World Bank staff calculations and World Development Indicators database. progress using wealth accounts, including indi- cators of adjusted net savings and adjusted net A nonsustainable path 7f national income. Wealth is defined comprehen- in Sub‑Saharan Africa sively to include stocks of manufactured capital, Share of gross national income, 2008 (%) natural capital, human capital, and social capital. 20 Development is conceived as building wealth and Depreciation of xed Education managing a portfolio of assets. The challenge of capital expenditures 10 development is to manage not just the total vol- Depletion of natural resources ume of assets but also the composition of the asset portfolio—that is, how much to invest in 0 different types of capital. Adjusted net savings is a sustainability indicator that measures whether a Pollution damages country is building its wealth sustainably (positive –10 Gross Net Net savings Depletion Adjusted values) or running it down on an unsustainable savings savings plus education expeditures adjusted savings net savings development path (negative values; figure 7f). Source: World Bank 2011. Economy States and markets Global links Back World Development Indicators 2013 15 Goal 8 Develop a global partnership for development Aid flows The eighth and final goal distinguishes the Mil- 8a decline lennium Development Goals from previous reso- Of cial development assistance from Development Assistance Committee members (2010 $ billions) lutions and targeted programs. It recognizes the 200 multidimensional nature of development and the Humanitarian assistance need for wealthy countries and developing coun- 150 tries to work together to create an environment in Net debt relief which rapid, sustainable development is possible. 100 Along with increased aid flows and debt relief for the poorest, highly indebted countries, goal 8 rec- 50 Bilateral net of cial development assistance, excluding debt relief and humanitarian assistance ognizes the need to reduce barriers to trade and to share the benefits of new medical and commu- Multilateral net of cial development assistance, 0 excluding debt relief and humanitarian assistance nication technologies. It is also a reminder that 1990 1995 2000 2005 2011 Source: Organisation for Economic Co-operation and Development development challenges differ for large and small StatExtracts. countries and for those that are landlocked or iso- lated by large expanses of ocean. Building and Domestic subsidies to 8b sustaining a partnership is an ongoing process agriculture exceed aid flows Agricultural support ($ billions) that does not stop at a specific date or when a 150 target is reached. After falling through much of the 1990s, offi- European Union cial development assistance (ODA) from mem- 100 bers of the Organisation for Economic Co-oper- ation and Development’s (OECD) Development Japan Assistance Committee (DAC) rose sharply after 50 2002, but a large part of the increase was in the United States Korea, Rep. form of debt relief and humanitarian assistance Turkey (figure 8a). The financial crisis that began in 2008 0 1990 1995 2000 2005 2011 and fiscal austerity in many high-income econo- Source: Organisation for Economic Co-operation and Development StatExtracts. mies have begun to undermine commitments to increase ODA. Net disbursements of ODA by More opportunities for exporters members of the DAC rose to $134 billion in 2011, 8c in developing countries but, after accounting for price and exchange Goods (excluding arms) admitted free of tariffs from developing countries (% total merchandise imports, excluding arms) rate adjustments, fell 2.3 percent in real terms 100 from 2010. Aid from multilateral organizations Norway United States remained essentially unchanged at $34.7 billion, 75 a decrease of 6.6 percent in real terms. ODA from Australia DAC members has fallen back to 0.31 percent of 50 Japan their combined gross national income, less than European Union half the UN target of 0.7 percent. 25 OECD members, mostly high-income econo- mies but also some upper middle-income econo- 0 1996 1998 2000 2002 2004 2006 2008 2010 mies such as Chile, Mexico, and Turkey, continue Source: World Trade Organization, International Trade Center, United to spend more on support to domestic agricul- Nations Conference on Trade and Development, and World Development Indicators database. tural producers than on ODA. In 2011 the OECD 16  World Development Indicators 2013 Front ? User guide World view People Environment estimate of agricultural subsidies was $252 bil- Debt service burdens 8d lion, 41  percent of which was to EU producers continue to fall Total debt service (% of exports of goods, services, and income) (figure 8b). 50 Many rich countries have pledged to open their markets to exports from developing countries, and Latin America & Caribbean 40 the share of goods (excluding arms) admitted duty South Asia free by OECD economies has been rising. However, 30 Europe & Central Asia arcane rules of origin and phytosanitary standards keep many countries from qualifying for duty-free 20 access. And uncertainty over market access may East Asia & Paci c inhibit development of export industries (figure 8c). 10 Sub-Saharan Africa Growing economies, better debt management, Middle East & North Africa 0 and debt relief for the poorest countries have 1990 1995 2000 2005 2011 allowed developing countries to substantially Source: World Development Indicators database. reduce their debt burdens. Despite the financial Telecommunications crisis and a 2.3 percent contraction in the global 8e on the move economy in 2009, the debt service to exports ratio Mobile phone subscriptions (per 100 people) in low- and middle-income economies reached a 125 new low of 8.8 percent in 2011. In Europe and High income Central Asia, where the debt service to exports 100 ratio rose to 26 percent in 2009, higher export Upper middle income 75 earnings have helped return the average to its 2007 level of 17.8 percent (figure 8d). 50 Telecommunications is an essential tool for Lower middle income development, and new technologies are creating 25 new opportunities everywhere. The growth of fixed- Low income line phone systems has peaked in high-income 0 1990 1995 2000 2005 2011 economies and will never reach the same level Source: International Telecommunications Union and World Development Indicators database. of use in developing countries. In high-income economies mobile phone subscriptions have now More people connecting 8f passed 1 per person, and upper middle-income to the Internet economies are not far behind (figure 8e). Internet users (per 100 people) Mobile phones are one of several ways of 80 High income accessing the Internet. In 2000 Internet use was spreading rapidly in high-income economies but 60 was barely under way in developing country regions. Europe & Central Asia Now developing countries are beginning to catch 40 up. Since 2000 Internet use per person in develop- Latin America & Caribbean East Asia & Paci c ing economies has grown 28 percent a year. Like 20 Middle East & North Africa Sub-Saharan telephones, Internet use is strongly correlated with Africa income. The low-income economies of South Asia South Asia 0 and Sub-­ Saharan Africa lag behind, but even there 2000 2002 2004 2006 2008 2011 Source: International Telecommunications Union and World Development Internet access is spreading rapidly (figure 8f). Indicators database. Economy States and markets Global links Back World Development Indicators 2013 17 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. 18  World Development Indicators 2013 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.  he 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 b. T 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 2013 19 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 2011 2011 2011 2011 2011 2011 2011 2011 2010–11 2010–11 Afghanistan 35.3 652.2 54 24 16.6 470 40.3a 1,140a 5.7 2.9 Albania 3.2 28.8 117 53 12.8 3,980 28.4 8,820 3.0 2.6 Algeria 36.0 2,381.7 15 73 160.8 4,470 299.0a 8,310a 2.5 1.0 American Samoa 0.1 0.2 348 93 .. ..b .. .. .. .. Andorra 0.1 0.5 183 87 .. ..c .. .. .. .. Angola 19.6 1,246.7 16 59 75.2 3,830 d 102.7 5,230 3.9 1.1 Antigua and Barbuda 0.1 0.4 204 30 1.1 11,940 1.6a 17,900a –5.0 –6.0 Argentina 40.8 2,780.4 15 93 .. .. .. .. .. .. Armenia 3.1 29.7 109 64 10.4 3,360 18.9 6,100 4.6 4.3 Aruba 0.1 0.2 601 47 .. ..c .. .. .. .. Australia 22.3 7,741.2 3 89 1,111.4 49,790 862.0 38,610 1.9 0.7 Austria 8.4 83.9 102 68 405.7 48,170 354.0 42,030 2.7 2.3 Azerbaijan 9.2 86.6 111 54 48.5 5,290 82.1 8,950 1.0 –0.3 Bahamas, The 0.3 13.9 35 84 7.5 21,970 10.2a 29,790a 1.6 0.4 Bahrain 1.3 0.8 1,742 89 20.1 15,920 26.8 21,200 3.0 –3.1 Bangladesh 150.5 144.0 1,156 28 117.8 780 291.7 1,940 6.7 5.4 Barbados 0.3 0.4 637 44 3.5 12,660 5.2a 18,900a 1.2 –5.5 Belarus 9.5 207.6 47 75 55.2 5,830 137.0 14,460 5.3 5.5 Belgium 11.0 30.5 364 98 506.2 45,930 431.4 39,150 1.8 0.6 Belize 0.4 23.0 16 45 1.3 3,710 2.2a 6,090a 1.9 –1.5 Benin 9.1 112.6 82 45 7.1 780 14.6 1,610 3.5 0.7 Bermuda 0.1 0.1 1,294 100 .. ..c .. .. –1.9 –1.7 Bhutan 0.7 38.4 19 36 1.6 2,130 4.1 5,570 5.6 3.8 Bolivia 10.1 1,098.6 9 67 20.4 2,020 49.3 4,890 5.2 3.5 Bosnia and Herzegovina 3.8 51.2 74 48 18.0 4,780 34.5 9,190 1.7 1.9 Botswana 2.0 581.7 4 62 15.2 7,470 29.5 14,550 5.7 4.5 Brazil 196.7 8,514.9 23 85 2,107.7 10,720 2,245.8 11,420 2.7 1.8 Brunei Darussalam 0.4 5.8 77 76 12.5 31,800 19.6 49,910 2.2 0.4 Bulgaria 7.3 111.0 68 73 48.8 6,640 105.8 14,400 1.7 4.3 Burkina Faso 17.0 274.2 62 27 9.9 580 22.5 1,330 4.2 1.1 Burundi 8.6 27.8 334 11 2.2 250 5.2 610 4.2 1.9 Cambodia 14.3 181.0 81 20 11.7 820 31.8 2,230 7.1 5.8 Cameroon 20.0 475.4 42 52 24.1 1,210 46.7 2,330 4.2 2.0 Canada 34.5 9,984.7 4 81 1,570.9 45,550 1,367.6 39,660 2.5 1.4 Cape Verde 0.5 4.0 124 63 1.8 3,540 2.0 3,980 5.0 4.1 Cayman Islands 0.1 0.3 236 100 .. ..c .. .. .. .. Central African Republic 4.5 623.0 7 39 2.1 480 3.6 810 3.3 1.3 Chad 11.5 1,284.0 9 22 8.3 720 17.7 1,540 1.6 –1.0 Channel Islands 0.2 0.2 810 31 .. ..c .. .. .. .. Chile 17.3 756.1 23 89 212.0 12,280 282.1 16,330 6.0 5.0 China 1,344.1 9,600.0 144 51 6,643.2 4,940 11,270.8 8,390 9.3 8.8 Hong Kong SAR, China 7.1 1.1 6,787 100 254.6 36,010 370.2 52,350 4.9 4.8 Macao SAR, China 0.6 0.0e 19,848 100 24.7 45,460 31.0 56,950 20.7 18.1 Colombia 46.9 1,141.8 42 75 284.9 6,070 448.6 9,560 5.9 4.5 Comoros 0.8 1.9 405 28 0.6 770 0.8 1,110 2.2 –0.4 Congo, Dem. Rep. 67.8 2,344.9 30 34 13.1 190 23.2 340 6.9 4.1 Congo, Rep. 4.1 342.0 12 64 9.3 2,250 13.4 3,240 3.4 1.0 20  World Development Indicators 2013 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 2011 2011 2011 2011 2011 2011 2011 2011 2010–11 2010–11 Costa Rica 4.7 51.1 93 65 36.1 7,640 56.1a 11,860a 4.2 2.7 Côte d’Ivoire 20.2 322.5 63 51 22.1 1,090 34.5 1,710 –4.7 –6.7 Croatia 4.4 56.6 79 58 59.6 13,540 82.7 18,780 0.0 0.3 Cuba 11.3 109.9 106 75 .. ..b .. .. 2.1 2.1 Curaçao 0.1 0.4 328 .. .. ..c .. .. .. .. Cyprus 1.1 9.3 121 71 23.7f 29,450 f 24.9 f 30,970 f 0.5f 0.3f Czech Republic 10.5 78.9 136 73 196.3 18,700 257.0 24,490 1.9 2.1 Denmark 5.6 43.1 131 87 335.1 60,160 233.5 41,920 1.1 0.7 Djibouti 0.9 23.2 39 77 1.1 1,270 2.1 2,450 5.0 3.0 Dominica 0.1 0.8 90 67 0.5 7,030 0.9a 13,000a –0.3 –0.2 Dominican Republic 10.1 48.7 208 70 52.6 5,240 94.7a 9,420a 4.5 3.1 Ecuador 14.7 256.4 59 67 61.7 4,200 124.7 8,510 7.8 6.3 Egypt, Arab Rep. 82.5 1,001.5 83 44 214.7 2,600 504.8 6,120 1.8 0.1 El Salvador 6.2 21.0 301 65 21.7 3,480 41.4 a 6,640a 1.5 0.9 Equatorial Guinea 0.7 28.1 26 40 11.3 15,670 18.4 25,620 7.8 4.8 Eritrea 5.4 117.6 54 21 2.3 430 3.1a 580a 8.7 5.5 Estonia 1.3 45.2 32 70 20.4 15,260 27.9 20,850 8.3 8.3 Ethiopia 84.7 1,104.3 85 17 31.0 370 93.8 1,110 7.3 5.0 Faeroe Islands 0.0 g 1.4 35 41 .. ..c .. .. .. .. Fiji 0.9 18.3 48 52 3.2 3,720 4.0 4,610 2.0 1.1 Finland 5.4 338.4 18 84 257.3 47,760 202.9 37,660 2.7 2.3 France 65.4 549.2 120 86 2,775.7 42,420 2,349.8 35,910 1.7 1.1 French Polynesia 0.3 4.0 75 51 .. ..c .. .. .. .. Gabon 1.5 267.7 6 86 12.4 8,080 21.1 13,740 4.8 2.8 Gambia, The 1.8 11.3 178 57 0.9 500 3.1 1,750 –4.3 –6.9 Georgia 4.5h 69.7 79 h 53h 12.8h 2,860h 24.0h 5,350h 7.0h 6.2h Germany 81.8 357.1 235 74 3,617.7 44,230 3,287.6 40,190 3.0 3.0 Ghana 25.0 238.5 110 52 35.1 1,410 45.2 1,810 14.4 11.8 Greece 11.3 132.0 88 62 276.7 24,490 283.7 25,110 –7.1 –7.0 Greenland 0.1 410.5i 0j 85 1.5 26,020 .. .. –5.4 –5.4 Grenada 0.1 0.3 309 39 0.8 7,350 1.1a 10,350a 1.0 0.6 Guam 0.2 0.5 337 93 .. ..c .. .. .. .. Guatemala 14.8 108.9 138 50 42.4 2,870 70.3a 4,760a 3.9 1.3 Guinea 10.2 245.9 42 36 4.4 430 10.5 1,020 3.9 1.5 Guinea-Bissau 1.5 36.1 55 44 0.9 600 1.9 1,230 5.7 3.5 Guyana 0.8 215.0 4 28 2.2 2,900 2.6 a 3,460a 4.2 4.2 Haiti 10.1 27.8 367 53 7.1 700 11.9a 1,180a 5.6 4.2 Honduras 7.8 112.5 69 52 15.4 1,980 29.7a 3,820a 3.6 1.6 Hungary 10.0 93.0 110 69 126.9 12,730 202.5 20,310 1.7 2.0 Iceland 0.3 103.0 3 94 11.1 34,820 9.9 31,020 2.6 2.2 India 1,241.5 3,287.3 418 31 1,766.2 1,420 4,524.6 3,640 6.3 4.9 Indonesia 242.3 1,904.6 134 51 712.7 2,940 1,091.4 4,500 6.5 5.4 Iran, Islamic Rep. 74.8 1,745.2 46 69 330.4 4,520 835.5 11,420 .. .. Iraq 33.0 435.2 76 67 87.0 2,640 123.5 3,750 9.9 6.8 Ireland 4.6 70.3 66 62 179.2 39,150 153.4 33,520 0.7 –1.5 Isle of Man 0.1 0.6 146 51 .. ..c .. .. .. .. Israel 7.8 22.1 359 92 224.7 28,930 210.5 27,110 4.7 2.8 Economy States and markets Global links Back World Development Indicators 2013 21 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 2011 2011 2011 2011 2011 2011 2011 2011 2010–11 2010–11 Italy 60.7 301.3 206 68 2,144.7 35,320 1,968.9 32,420 0.4 0.0 Jamaica 2.7 11.0 250 52 .. ..b .. .. –0.3 .. Japan 127.8 377.9 351 91 5,739.5 44,900 4,516.3 35,330 –0.7 –1.0 Jordan 6.2 89.3 70 83 27.1 4,380 36.6 5,930 2.6 0.4 Kazakhstan 16.6 2,724.9 6 54 136.7 8,260 186.4 11,250 7.5 6.0 Kenya 41.6 580.4 73 24 34.1 820 71.1 1,710 4.4 1.6 Kiribati 0.1 0.8 125 44 0.2 2,030 0.3a 3,300a 1.8 0.2 Korea, Dem. Rep. 24.5 120.5 203 60 .. ..k .. .. .. .. Korea, Rep. 49.8 99.9 513 83 1,039.0 20,870 1,511.7 30,370 3.6 2.9 Kosovo 1.8 10.9 166 .. 6.3 3,510 .. .. 5.0 3.4 Kuwait 2.8 17.8 158 98 133.8 48,900 147.0 53,720 8.2 5.1 Kyrgyz Republic 5.5 199.9 29 35 5.0 900 12.7 2,290 6.0 4.7 Lao PDR 6.3 236.8 27 34 7.1 1,130 16.2 2,580 8.0 6.5 Latvia 2.1 64.6 33 68 27.4 13,320 d 39.3 19,090 5.5 14.7 Lebanon 4.3 10.5 416 87 38.9 9,140 61.6 14,470 3.0 2.2 Lesotho 2.2 30.4 72 28 2.7 1,210 4.5 2,050 4.2 3.1 Liberia 4.1 111.4 43 48 1.4 330 2.2 540 9.4 5.9 Libya 6.4 1,759.5 4 78 77.1 12,320 105.2a 16,800a 2.1 0.3 Liechtenstein 0.0 g 0.2 227 14 4.9 137,070 .. .. –1.2 –1.9 Lithuania 3.0 65.3 48 67 39.3 12,980 d 62.9 20,760 5.9 14.8 Luxembourg 0.5 2.6 200 85 40.1 77,390 33.2 64,110 1.7 –0.6 Macedonia, FYR 2.1 25.7 82 59 9.9 4,810 23.5 11,370 2.8 2.7 Madagascar 21.3 587.0 37 33 9.1 430 20.2 950 1.0 –1.9 Malawi 15.4 118.5 163 16 5.6 360 13.4 870 4.3 1.1 Malaysia 28.9 330.8 88 73 253.0 8,770 451.7 15,650 5.1 3.4 Maldives 0.3 0.3 1,067 41 1.8 5,720 2.4 7,430 7.5 6.1 Mali 15.8 1,240.2 13 35 9.7 610 16.8 1,060 2.7 –0.3 Malta 0.4 0.3 1,299 95 7.7 18,620 10.2 24,480 2.1 2.2 Marshall Islands 0.1 0.2 305 72 0.2 3,910 .. .. 5.0 3.5 Mauritania 3.5 1,030.7 3 42 3.6 1,030l 8.9 2,530 4.0 1.6 Mauritius 1.3 2.0 634 42 10.3 8,040 18.4 14,330 4.1 3.7 Mexico 114.8 1,964.4 59 78 1,081.8 9,420 1,766.4 15,390 3.9 2.7 Micronesia, Fed. Sts. 0.1 0.7 159 23 0.3 2,860 0.4 a 3,580a 2.1 1.6 Moldova 3.6m 33.9 124m 48m 7.1m 1,980m 13.0m 3,640m 6.4m 6.5m Monaco 0.0 g 0.0e 17,714 100 6.5 183,150 .. .. –2.6 –2.7 Mongolia 2.8 1,564.1 2 69 6.5 2,310 12.0 4,290 17.5 15.7 Montenegro 0.6 13.8 47 63 4.5 7,140 8.7 13,700 3.2 3.1 Morocco 32.3 446.6 72 57 97.6n 2,970n 160.1n 4,880n 4.5n 3.5n Mozambique 23.9 799.4 30 31 11.1 460 22.9 960 7.1 4.7 Myanmar 48.3 676.6 74 33 .. ..k .. .. .. .. Namibia 2.3 824.3 3 38 10.9 4,700 15.4 6,610 4.8 3.0 Nepal 30.5 147.2 213 17 16.6 540 38.4 1,260 3.9 2.1 Netherlands 16.7 41.5 495 83 829.0 49,660 720.3 43,150 1.0 0.5 New Caledonia 0.3 18.6 14 62 .. ..c .. .. .. .. New Zealand 4.4 267.7 17 86 127.3 29,140 126.3 28,930 1.0 0.1 Nicaragua 5.9 130.4 49 58 8.9 1,510 21.9a 3,730a 5.1 3.6 Niger 16.1 1,267.0 13 18 5.8 360 11.6 720 2.3 –1.2 22  World Development Indicators 2013 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 2011 2011 2011 2011 2011 2011 2011 2011 2010–11 2010–11 Nigeria 162.5 923.8 178 50 207.3 1,280 372.8 2,290 7.4 4.7 Northern Mariana Islands 0.1 0.5 133 92 .. ..c .. .. .. .. Norway 5.0 323.8 16 79 440.2 88,870 304.4 61,450 1.4 0.1 Oman 2.8 309.5 9 73 53.6 19,260 71.6 25,720 5.5 3.1 Pakistan 176.7 796.1 229 36 198.0 1,120 507.2 2,870 3.0 1.1 Palau 0.0 g 0.5 45 84 0.1 6,510 0.2a 11,080a 5.8 5.1 Panama 3.6 75.4 48 75 26.7 7,470 51.8a 14,510a 10.6 8.9 Papua New Guinea 7.0 462.8 16 13 10.4 1,480 18.0a 2,570a 9.0 6.6 Paraguay 6.6 406.8 17 62 19.8 3,020 35.4 5,390 6.9 5.0 Peru 29.4 1,285.2 23 77 151.4 5,150 277.6 9,440 6.8 5.6 Philippines 94.9 300.0 318 49 209.7 2,210 393.0 4,140 3.9 2.2 Poland 38.5 312.7 127 61 477.0 12,380o 780.8 20,260 4.3 3.4 Portugal 10.6 92.1 115 61 225.6 21,370 259.9 24,620 –1.7 –0.9 Puerto Rico 3.7 8.9 418 99 61.6 16,560 .. .. –2.1 –1.6 Qatar 1.9 11.6 161 99 150.4 80,440 161.6 86,440 18.8 11.7 Romania 21.4 238.4 93 53 174.0 8,140 337.4 15,780 2.5 2.7 Russian Federation 143.0 17,098.2 9 74 1,522.3 10,650 2,917.7 20,410 4.3 3.9 Rwanda 10.9 26.3 444 19 6.2 570 13.9 1,270 8.3 5.1 Samoa 0.2 2.8 65 20 0.6 3,160 0.8a 4,270a 2.0 1.6 San Marino 0.0 g 0.1 529 94 .. ..c .. .. .. .. São Tomé and Príncipe 0.2 1.0 176 63 0.2 1,350 0.4 2,080 4.9 3.0 Saudi Arabia 28.1 2,149.7p 13 82 500.5 17,820 693.7 24,700 6.8 4.4 Senegal 12.8 196.7 66 43 13.7 1,070 24.8 1,940 2.6 –0.1 Serbia 7.3 88.4 83 56 41.3 5,690 83.8 11,550 2.0 2.5 Seychelles 0.1 0.5 187 54 1.0 11,270 2.3a 26,280a 5.0 5.6 Sierra Leone 6.0 71.7 84 39 2.8 460 6.8 1,140 6.0 3.7 Singapore 5.2 0.7 7,405 100 222.6 42,930 307.8 59,380 4.9 2.7 Sint Maarten 0.0 g 0.0e 1,077 .. .. ..c .. .. .. .. Slovak Republic 5.4 49.0 112 55 87.4 16,190 120.4 22,300 3.3 4.0 Slovenia 2.1 20.3 102 50 48.5 23,600 54.4 26,500 –0.2 –0.4 Solomon Islands 0.6 28.9 20 21 0.6 1,110 1.3a 2,350a 9.0 6.2 Somalia 9.6 637.7 15 38 .. ..k .. .. .. .. South Africa 50.6 1,219.1 42 62 352.0 6,960 542.0 10,710 3.1 1.9 South Sudan 10.3p 644.3 .. 18 .. ..q .. .. 1.9 –1.7 Spain 46.2 505.4 93 77 1,428.3 30,930 1,451.7 31,440 0.4 0.2 Sri Lanka 20.9 65.6 333 15 53.8 2,580 115.2 5,520 8.3 7.1 St. Kitts and Nevis 0.1 0.3 204 32 0.7 12,610 0.9a 16,470a 2.1 0.9 St. Lucia 0.2 0.6 289 18 1.2 6,820 2.0a 11,220a 1.3 0.1 g c St. Martin 0.0 0.1 563 .. .. .. .. .. .. .. St. Vincent and Grenadines 0.1 0.4 280 49 0.7 6,070 1.1a 10,440a 0.1 0.1 Sudan 34.3p,r 1,861.5r 18 33 58.3u 1,310u 94.7u 2,120u 4.7u 2.2u a a Suriname 0.5 163.8 3 70 4.1 7,840 4.1 7,730 4.7 3.7 Swaziland 1.1 17.4 62 21 3.7 3,470 6.5 6,110 1.3 0.1 Sweden 9.4 450.3 23 85 502.5 53,170 398.9 42,210 3.9 3.1 Switzerland 7.9 41.3 198 74 604.1 76,350 415.6 52,530 1.9 0.8 Syrian Arab Republic 20.8 185.2 113 56 67.9 2,750 104.0 5,080 .. .. Tajikistan 7.0 142.6 50 27 6.1 870 16.0 2,300 7.4 5.9 Economy States and markets Global links Back World Development Indicators 2013 23 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 2011 2011 2011 2011 2011 2011 2011 2011 2010–11 2010–11 Tanzania 46.2 947.3 52 27 24.2 v 540 v 67.1v 1,500 v 6.4v 3.3v Thailand 69.5 513.1 136 34 308.3 4,440 581.4 8,360 0.1 –0.5 Timor-Leste 1.2 14.9 79 28 3.1 2,730 5.9a 5,200a 10.6 7.5 Togo 6.2 56.8 113 38 3.5 570 6.4 1,040 4.9 2.7 Tonga 0.1 0.8 145 24 0.4 3,820 0.5a 5,000a 4.9 4.5 Trinidad and Tobago 1.3 5.1 262 14 21.3 15,840 32.7a 24,350a –4.1 –4.4 Tunisia 10.7 163.6 69 66 42.9 4,020 d 96.0 8,990 –2.0 –3.1 Turkey 73.6 783.6 96 71 766.6 10,410 1,247.3 16,940 8.5 7.2 Turkmenistan 5.1 488.1 11 49 24.5 4,800 44.3a 8,690a 14.7 13.3 Turks and Caicos Islands 0.0 g 1.0 41 94 .. ..c .. .. .. .. Tuvalu 0.0 g 0.0e 328 51 0.0 4,950 .. .. 1.2 1.0 Uganda 34.5 241.6 173 16 17.5 510 45.3 1,310 6.7 3.3 Ukraine 45.7 603.6 79 69 142.9 3,130 321.9 7,040 5.2 5.6 United Arab Emirates 7.9 83.6 94 84 321.7 40,760 377.9 47,890 4.9 –0.1 United Kingdom 62.7 243.6 259 80 2,370.4 37,780 2,255.9 35,950 0.8 0.0 United States 311.6 9,831.5 34 82 15,148.2 48,620 15,211.3 48,820 1.7 1.0 Uruguay 3.4 176.2 19 93 40.0 11,860 49.3 14,640 5.7 5.3 Uzbekistan 29.3 447.4 69 36 44.2 1,510 100.3a 3,420a 8.3 5.4 Vanuatu 0.2 12.2 20 25 0.7 2,730 1.1a 4,330a 1.4 –1.0 Venezuela, RB 29.3 912.1 33 94 346.1 11,820 363.9 12,430 4.2 2.6 Vietnam 87.8 331.1 283 31 111.1 1,270 285.5 3,250 5.9 4.8 Virgin Islands (U.S.) 0.1 0.4 313 95 .. ..c .. .. .. .. West Bank and Gaza 3.9 6.0 652 74 .. ..q .. .. .. .. Yemen, Rep. 24.8 528.0 47 32 26.4 1,070 53.7 2,170 –10.5 –13.2 Zambia 13.5 752.6 18 39 15.7 1,160 20.1 1,490 6.5 2.1 Zimbabwe 12.8 390.8 33 39 8.4 660 .. .. 9.4 7.8 World 6,974.2 s 134,269.2 s 54 w 52 w 66,354.3 t 9,514 w 80,624.2 t 11,560 w 2.7 w 1.6 w Low income 816.8 16,582.1 51 28 466.0 571 1,125.4 1,378 6.0 3.7 Middle income 5,022.4 81,875.7 63 50 20,835.4 4,149 36,311.9 7,230 6.3 5.2 Lower middle income 2,532.7 20,841.9 126 39 4,488.5 1,772 9,719.0 3,837 5.5 3.9 Upper middle income 2,489.7 61,033.8 42 61 16,340.5 6,563 26,646.2 10,703 6.6 5.9 Low & middle income 5,839.2 98,457.7 61 47 21,324.4 3,652 37,436.4 6,411 6.3 5.0 East Asia & Pacific 1,974.2 16,301.7 125 49 8,387.3 4,248 14,344.6 7,266 8.3 7.6 Europe & Central Asia 408.1 23,613.7 18 65 3,156.6 7,734 5,845.7 14,323 5.9 5.4 Latin America & Carib. 589.0 20,393.6 29 79 5,050.3 8,574 6,822.0 11,582 4.7 3.6 Middle East & N. Africa 336.5 8,775.4 39 59 1,279.5 3,866 2,619.2 8,052 0.2 2.4 South Asia 1,656.5 5,131.1 347 31 2,174.5 1,313 5,523.5 3,335 6.1 4.6 Sub-­Saharan Africa 874.8 24,242.3 37 37 1,100.8 1,258 1,946.2 2,225 4.7 2.1 High income 1,135.0 35,811.5 33 81 45,242.5 39,861 43,724.5 38,523 1.5 0.9 Euro area 332.9 2,628.4 131 76 12,871.5 38,661 11,735.7 35,250 1.5 1.2 a. Based on regression; others are extrapolated from the 2005 International Comparison Program benchmark estimates. b. Estimated to be upper middle income ($4,036–$12,475). c. Estimated to be high income ($12,476 or more). d. Included in the aggregates for upper middle-income economies based on earlier data. e. Greater than 0 but less than 50. f. Data are for the area controlled by the government of Cyprus. g. Greater than 0 but less than 50,000. h. Excludes Abkhazia and South Ossetia. i. Refers to area free from ice. j. Greater than 0 but less than 0.5. k. Estimated to be low income ($1,025 or less). l. Included in the aggregates for low-income economies based on earlier data. m. Excludes Transnistria. n. Includes Former Spanish Sahara. o. Included in the aggregates for high-income economies based on earlier data. p. Provisional estimate. q. Estimated to be lower middle income ($1,026–$4,035). r. Excludes South Sudan. s. Sum of available data (see Statistical methods). t. Missing data are imputed (see Statistical methods). u. Excludes South Sudan after July 9, 2011. v. Covers mainland Tanzania only. w. Weighted average (see Statistical methods). 24  World Development Indicators 2013 Front ? User guide World view People Environment World view  1 About the data Population, land area, income (as measured by gross national area, which excludes bodies of water, and from gross area, which income, GNI), and output (as measured by gross domestic product, may include offshore territorial waters. Land area is particularly GDP) are basic measures of the size of an economy. They also pro- important for understanding an economy’s agricultural capacity and vide a broad indication of actual and potential resources and are the environmental effects of human activity. Innovations in satellite therefore used throughout World Development Indicators to normal- mapping and computer databases have resulted in more precise ize other indicators. measurements of land and water areas. Population Urban population Population estimates are usually based on national population cen- There is no consistent and universally accepted standard for suses. Estimates for the years before and after the census are distinguishing urban from rural areas, in part because of the interpolations or extrapolations based on demographic models. wide variety of situations across countries. Most countries use Errors and undercounting occur even in high-income countries; in an urban classification related to the size or characteristics developing countries errors may be substantial because of limits of settlements. Some define urban areas based on the pres- in the transport, communications, and other resources required to ence of certain infrastructure and services. And other countries conduct and analyze a full census. designate urban areas based on administrative arrangements. The quality and reliability of official demographic data are also Because the estimates in the table are based on national defi- affected by public trust in the government, government commit- nitions of what constitutes a city or metropolitan area, cross- ment to full and accurate enumeration, confidentiality and pro- country comparisons should be made with caution. To estimate tection against misuse of census data, and census agencies’ urban populations, ratios of urban to total population obtained independence from political influence. Moreover, comparability of from the United Nations were applied to the World Bank’s esti- population indicators is limited by differences in the concepts, mates of total population. definitions, collection procedures, and estimation methods used by national statistical agencies and other organizations that col- Size of the economy lect the data. GNI measures total domestic and foreign value added claimed by Of the 214 economies in the table, 180 (about 86 percent) con- residents. GNI comprises GDP plus net receipts of primary income ducted a census during the 2000 census round (1995–2004). As (compensation of employees and property income) from nonresi- of January 2012, 141 countries have completed a census for the dent sources. GDP is the sum of gross value added by all resident 2010 census round (2005–14). The currentness of a census and producers in the economy plus any product taxes (less subsidies) the availability of complementary data from surveys or registration not included in the valuation of output. GNI is calculated without systems are important indicators of demographic data quality. See deducting for depreciation of fabricated assets or for depletion and Primary data documentation for the most recent census or survey degradation of natural resources. Value added is the net output of year and for the completeness of registration. Some European coun- an industry after adding up all outputs and subtracting intermedi- tries’ registration systems offer complete information on population ate inputs. The industrial origin of value added is determined by in the absence of a census. the International Standard Industrial Classification revision 3. The Current population estimates for developing countries that World Bank uses GNI per capita in U.S. dollars to classify countries lack recent census data and pre- and post-census estimates for for analytical purposes and to determine borrowing eligibility. For countries with census data are provided by the United Nations definitions of the income groups in World Development Indicators, Population Division and other agencies. The cohort compo- see User guide. nent method—a standard method for estimating and projecting When calculating GNI in U.S. dollars from GNI reported in national p opulation—requires fertility, mortality, and net migration data, ­ currencies, the World Bank follows the World Bank Atlas conversion often collected from sample surveys, which can be small or limited method, using a three-year average of exchange rates to smooth in coverage. Population estimates are from demographic modeling the effects of transitory fluctuations in exchange rates. (For fur- and so are susceptible to biases and errors from shortcomings in ther discussion of the World Bank Atlas method, see Statistical the model and in the data. Because the five-year age group is the methods.) cohort unit and five-year period data are used, interpolations to Because exchange rates do not always reflect differences in price obtain annual data or single age structure may not reflect actual levels between countries, the table also converts GNI and GNI per events or age composition. capita estimates into international dollars using purchasing power parity (PPP) rates. PPP rates provide a standard measure allowing Surface area comparison of real levels of expenditure between countries, just The surface area of an economy includes inland bodies of water as conventional price indexes allow comparison of real values over and some coastal waterways. Surface area thus differs from land time. Economy States and markets Global links Back World Development Indicators 2013 25 1  World view PPP rates are calculated by simultaneously comparing the prices Data sources of similar goods and services among a large number of countries. The World Bank’s population estimates are compiled and produced In the most recent round of price surveys conducted by the Interna- by its Development Data Group in consultation with its Human Devel- tional Comparison Program (ICP) in 2005, 146 countries and ter- opment Network, operational staff, and country offices. The United ritories participated, including China for the first time, India for the Nations Population Division (2011) is a source of the demographic first time since 1985, and almost all African countries. The PPP data for more than half the countries, most of them developing conversion factors presented in the table come from three sources. countries. Other important sources are census reports and other For 47 high- and upper middle-income countries conversion fac- statistical publications from national statistical offices; household tors are provided by Eurostat and the Organisation for Economic surveys by national agencies, ICF International (for MEASURE DHS), Co-operation and Development (OECD); PPP estimates for these and the U.S. Centers for Disease Control and Prevention; Eurostat’s countries incorporate new price data collected since 2005. For the Demographic Statistics; the Secretariat of the Pacific Community’s remaining 2005 ICP countries the PPP estimates are extrapolated Statistics and Demography Programme; and the U.S. Bureau of the from the 2005 ICP benchmark results, which account for relative Census’s International Data Base. price changes between each economy and the United States. For Data on surface and land area are from the Food and Agricul- countries that did not participate in the 2005 ICP round, the PPP ture Organization, which gathers these data from national agen- estimates are imputed using a statistical model. More information cies through annual questionnaires and by analyzing the results of on the results of the 2005 ICP is available at www.worldbank.org/ national agricultural censuses. data/icp. Data on urban population shares are from United Nations Popula- Growth rates of GDP and GDP per capita are calculated using the tion Division (2010). least squares method and constant price data in local currency. GNI, GNI per capita, GDP growth, and GDP per capita growth are Constant price U.S. dollar series are used to calculate regional and estimated by World Bank staff based on national accounts data col- income group growth rates. The growth rates in the table are annual lected by World Bank staff during economic missions or reported by averages. Methods of computing growth rates are described in Sta- national statistical offices to other international organizations such tistical methods. as the OECD. PPP conversion factors are estimates by Eurostat/ OECD and by World Bank staff based on data collected by the ICP. Definitions • Population is based on the de facto definition of population, which References citizenship— counts all residents regardless of legal status or ­ Eurostat (Statistical Office of the European Communities). n.d. Demo- except for refugees not permanently settled in the country of asy- graphic Statistics. http://epp.eurostat.ec.europa.eu/portal/page/ lum, who are generally considered part of the population of their portal/eurostat/home/. Luxembourg. country of origin. The values shown are midyear estimates. • Sur - ICF International. Various years. Demographic and Health Surveys. face area is a country’s total area, including areas under inland http://www.measuredhs.com. Calverton, MD. bodies of water and some coastal waterways. • Population density OECD (Organisation for Economic Co-operation and Development). n.d. is midyear population divided by land area. • Urban population is OECD.StatExtracts database. http://stats.oecd.org/. Paris. the midyear population of areas defined as urban in each country UNAIDS (Joint United Nations Programme on HIV/AIDS). 2012. Global and reported to the United Nations. • Gross national income, Atlas Report: UNAIDS Report on the Global AIDS Epidemic 2012. www method, is the sum of value added by all resident producers plus .unaids.org/en/resources/publications/2012/. Geneva. any product taxes (less subsidies) not included in the valuation United Nations Inter-Agency Group for Child Mortality Estimation. of output plus net receipts of primary income (compensation of 2012. Levels and Trends in Child Mortality: Report 2012. www employees and property income) from abroad. Data are in current .childinfo.org/files/Child_Mortality_Report_2012.pdf. New York. U.S. dollars converted using the World Bank Atlas method (see United Nations. 2012. The Millennium Development Goals Report Statistical methods). • Gross national income, purchasing power 2012. New York. parity, is GNI converted to international dollars using PPP rates. An United Nations Population Division. 2010. World Urbanization Pros- international dollar has the same purchasing power over GNI that pects: The 2009 Revision. New York: United Nations, Department of a U.S. dollar has in the United States. • Gross national income Economic and Social Affairs. per capita is GNI divided by midyear population. • Gross domestic ———. 2011. World Population Prospects: The 2010 Revision. New product is the sum of value added by all resident producers plus York: United Nations, Department of Economic and Social Affairs. any product taxes (less subsidies) not included in the valuation of World Bank. 2011. The Changing Wealth of Nations: Measuring Sustain- output. Growth is calculated from constant price GDP data in local able Development for the New Millennium. Washington, DC. currency. • Gross domestic product per capita is GDP divided by ———. n.d. PovcalNet online database. http://iresearch.worldbank midyear population. .org/PovcalNet/index.htm 26  World Development Indicators 2013 Front ? User guide World view People Environment World view  1 About the Online data 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 Individuals using the Internet ..a 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 2013 27 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 Argentina 1.7 2.7 2009d,e 2.0 1.2 3.4 1.7 2010 d,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 2008 <2 <0.5 <2 <0.5 2010 <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 2003 26.2 7.0 49.5 18.8 2007 10.2 1.8 29.8 8.5 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 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 Cape Verde 97.7 156.3 .. .. .. .. 2002 21.0 6.1 40.9 15.2 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 407.3 651.6 2002 23.3 6.8 46.8 17.6 2008 23.8 7.5 46.3 17.8 Croatia 5.6 8.9 2004 <2 <0.5 <2 <0.5 2008 <2 <0.5 <2 <0.5 Czech Republic 19.0 30.4 1993e <2 <0.5 <2 <0.5 1996e <2 <0.5 <2 <0.5 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 2008 15.3 4.6 32.2 11.7 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 28  World Development Indicators 2013 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 2009h 20.4 4.1 52.7 16.5 2010h 18.1 3.3 46.1 14.3 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 2009 6.2 1.4 21.7 6.0 2010 6.7 1.5 22.9 6.4 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 1998 83.1 46.0 93.5 62.3 2004 73.9 32.3 90.5 51.8 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 .. .. .. .. 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 2008 <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 0.8 c 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 2009 <2 <0.5 <2 <0.5 2010 <2 <0.5 <2 <0.5 Romania 2.1 3.4 2009 <2 <0.5 <2 0.5 2010 <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 2013 29 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 1990 62.8 44.8 75.0 54.0 2003 53.4 20.3 76.1 37.5 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 2008 <2 <0.5 4.2 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 2004 64.3 32.8 81.5 48.3 2006 68.5 37.0 82.6 51.8 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. 30  World Development Indicators 2013 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 provisional 2015 projection 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 2013 31 Poverty rates About the data The World Bank produced its first global poverty estimates for The low frequency and lack of comparability of the data available developing countries for World Development Report 1990: Poverty in some countries create uncertainty over the magnitude of poverty (World Bank 1990) using household survey data for 22 coun- reduction. The table on trends in poverty indicators reports the tries (Ravallion, Datt, and van de Walle 1991). Since then there percentage of the regional and global population represented by has been considerable expansion in the number of countries household survey samples collected during the reference year or that field household income and expenditure surveys. The World during the two preceding or two subsequent years (in other words, Bank’s Development Research Group maintains a database that within a five-year window centered on the reference year). Data cov- is updated regularly as new survey data become available (and Saharan Africa and the Middle East and North Africa erage in Sub-­ thus may contain more recent data or revisions that are not incor- remains low and variable. The need to improve household survey porated into the table) and conducts a major reassessment of programs for monitoring poverty is clearly urgent. But institutional, progress against poverty about every three years. political, and financial obstacles continue to limit data collection, This year the database has been updated with global and regional analysis, and public access. extreme poverty estimates for 2010, which are provisional due to low coverage in household survey data availability for recent years Data quality (2008–12). The projections to 2015 of poverty rates use the 2010 Besides the frequency and timeliness of survey data, other data provisional estimates as a baseline and assume that average house- quality issues arise in measuring household living standards. The hold income or consumption will grow in line with the aggregate eco- surveys ask detailed questions on sources of income and how it nomic projections reported in this year’s Global Monitoring Report was spent, which must be carefully recorded by trained personnel. (World Bank 2013) but that inequality within countries will remain Income is generally more difficult to measure accurately, and con- unchanged. This methodology was first used and described in the sumption comes closer to the notion of living standards. And income Global Economic Prospects report (World Bank 2000). Estimates of can vary over time even if living standards do not. But consumption the number of people living in extreme poverty are based on popula- data are not always available: the latest estimates reported here tion projections in the World Bank’s HealthStats database (http:// use consumption for about two-thirds of countries. datatopics.worldbank.org/hnp). However, even similar surveys may not be strictly comparable PovcalNet (http://iresearch.worldbank.org/PovcalNet) is an because of differences in timing, sampling frames, or the quality interactive computational tool that allows users to replicate these and training of enumerators. Comparisons of countries at different internationally comparable $1.25 and $2 a day global, regional and levels of development also pose a potential problem because of dif- country-level poverty estimates and to compute poverty measures ferences in the relative importance of the consumption of nonmarket for custom country groupings and for different poverty lines. The goods. The local market value of all consumption in kind (includ- Poverty and Equity Data portal (http://povertydata.worldbank.org/ ing own production, particularly important in underdeveloped rural poverty/home) provides access to the database and user-friendly economies) should be included in total consumption expenditure, but dashboards with graphs and interactive maps that visualize trends in may not be. Most survey data now include valuations for consump- key poverty and inequality indicators for different regions and coun- tion or income from own production, but valuation methods vary. tries. The country dashboards display trends in poverty measures The statistics reported here are based on consumption data or, based on the national poverty lines (see online table 2.7) alongside when unavailable, on income data. Analysis of some 20 countries the internationally comparable estimates in the table, produced for which both were available from the same surveys found income from and consistent with PovcalNet. to yield a higher mean than consumption but also higher inequality. When poverty measures based on consumption and income were Data availability compared, the two effects roughly cancelled each other out: there The World Bank’s internationally comparable poverty monitoring was no significant statistical difference. database now draws on income or detailed consumption data Invariably some sampled households do not participate in collected from interviews with 1.23 million randomly sampled surveys because they refuse to do so or because nobody is households through more than 850 household surveys collected at home during the interview visit. This is referred to as “unit by national statistical offices in nearly 130 countries. Despite prog- nonresponse� and is distinct from “item nonresponse,� which ress in the last decade, the challenges of measuring poverty remain. occurs when some of the sampled respondents participate but The timeliness, frequency, quality, and comparability of household refuse to answer certain questions, such as those pertaining to surveys need to increase substantially, particularly in the poorest income or consumption. To the extent that survey nonresponse countries. The availability and quality of poverty monitoring data is random, there is no concern regarding biases in survey-based remain low in small states, fragile situations, and low-income coun- inferences; the sample will still be representative of the popula- tries and even some middle-income countries. tion. However, households with different income might not be equally likely to respond. Richer households may be less likely 32  World Development Indicators 2013 Front ? User guide World view People Environment Poverty rates to participate because of the high opportunity cost of their time Definitions or concerns about intrusion in their affairs. It is conceivable that • International poverty line in local currency is the international the poorest can likewise be underrepresented; some are home- poverty lines of $1.25 and $2.00 a day in 2005 prices, converted less or nomadic and hard to reach in standard household survey to local currency using the PPP conversion factors estimated by designs, and some may be physically or socially isolated and the International Comparison Program. • Survey year is the year in thus less likely to be interviewed. This can bias both poverty and which the underlying data were collected or, when the data collection inequality measurement if not corrected for (Korinek, Mistiaen, period bridged two calendar years, the year in which most of the data and Ravallion 2007). were collected. • Population below $1.25 a day and population below $2 a day are the percentages of the population living on less International poverty lines than $1.25 a day and $2 a day at 2005 international prices. As a International comparisons of poverty estimates entail both concep- result of revisions in PPP exchange rates, consumer price indexes, tual and practical problems. Countries have different definitions of or welfare aggregates, poverty rates for individual countries cannot poverty, and consistent comparisons across countries can be diffi- be compared with poverty rates reported in earlier editions. The cult. Local poverty lines tend to have higher purchasing power in rich PovcalNet online database and tool always contain the most recent countries, where more generous standards are used, than in poor full time series of comparable country data. • Poverty gap is the countries. Poverty measures based on an international poverty line mean shortfall from the poverty line (counting the nonpoor as hav- attempt to hold the real value of the poverty line constant across ing zero shortfall), expressed as a percentage of the poverty line. countries, as is done when making comparisons over time. Since This measure reflects 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/index.htm. 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 Chen, Shaohua, and Martin Ravallion. 2011. “The Developing World Is data on PPPs compiled in the 2005 round of the International Com- Poorer Than We Thought, But No Less Successful in the Fight Against parison Program, along with data from an expanded set of house- Poverty.� Quarterly Journal of Economics 125(4): 1577–1625. hold income and expenditure surveys. The new extreme poverty Korinek, Anton, Johan A. Mistiaen, and Martin Ravallion. 2007. “An line is set at $1.25 a day in 2005 PPP terms, which represents the Econometric Method of Correcting for Unit Nonresponse Bias in mean of the poverty lines found in the poorest 15 countries ranked Surveys.� Journal of Econometrics 136: 213–35. by per capita consumption. The new poverty line maintains the same Ravallion, Martin, Guarav Datt, and Dominique van de Walle. 1991. standard for extreme poverty—the poverty line typical of the poorest “Quantifying Absolute Poverty in the Developing World.� Review of countries in the world—but updates it using the latest information Income and Wealth 37(4): 345–61. on the cost of living in developing countries. PPP exchange rates are Ravallion, Martin, Shaohua Chen, and Prem Sangraula. 2009. “Dol- used to estimate global poverty because they take into account the lar a Day Revisited.� World Bank Economic Review 23(2): 163–84. local prices of goods and services not traded internationally. But World Bank. 1990. World Development Report 1990: Poverty. Wash- PPP rates were designed for comparing aggregates from national ington, DC. accounts, not for making international poverty comparisons. As a ———. 2000. Global Economic Prospects and the Developing Coun- result, there is no certainty that an international poverty line mea- tries. Washington, DC. sures the same degree of need or deprivation across countries. ———. 2008. Poverty Data: A Supplement to World Development Indi- So-called poverty PPPs, designed to compare the consumption of cators 2008. Washington, DC. the poorest people in the world, might provide a better basis for ———. 2013. Global Monitoring Report: Rural-Urban Dynamics and comparison of poverty across countries. Work on these measures the Millennium Development Goals. Washington, DC. is ongoing. Economy States and markets Global links Back World Development Indicators 2013 33 PEOPLE 34  World Development Indicators 2013 Front ? User guide World view People Environment 2 The indicators in the People section present inter-agency groups. These forums bring together demographic trends and forecasts alongside agency subject matter specialists with leading indicators of education, health, jobs, social pro- academic and local experts. Successful the- tection, poverty, and the distribution of income. matic inter-agency efforts have improved esti- Together they provide a multidimensional portrait mates on child mortality, child malnutrition, as of human development. well as maternal mortality, one of the most chal- Data updates in this edition include provi- lenging indicators to measure. sional estimates of global and regional extreme For 2013 the People section includes im- poverty rates for 2010—measured as the propor- proved child malnutrition indicators produced by tion of the population living on less than $1.25 the United Nations Children’s Fund, the World a day. The availability, frequency, and quality of Health Organization, and the World Bank using poverty monitoring data remain low, especially in a harmonized dataset and the same statistical small states and in countries and territories with methodology to estimate global, regional, and fragile situations. While estimates may change income group aggregates. marginally as additional country data become Another result is the improvement in monitor- available, it is now clear that the first Millennium ing HIV prevalence. Initial efforts relied solely on Development Goal target—cutting the global country surveillance systems that collected data extreme poverty rate to half its 1990 level—was from pregnant women who attended sentinel achieved before the 2015 target date. In 1990, antenatal clinics. Now the methodology measur- the benchmark year for the Millennium Devel- information— ing this indicator uses all available ­ opment Goals, the extreme poverty rate was including blood test data collected through 43.1 percent. Estimates for 2010 show that the nationally representative sample s ­ urveys—and extreme poverty rate had fallen to 20.6 percent. the models account for the effects of anti­ retro­ In addition to extreme poverty rates, the Peo- viral therapy and urbanization (see About the ple section includes many other indicators used data for online table 2.20). to monitor the Millennium Development Goals. In addition to providing insights into differ- Following the adoption of the Millennium Declara- ences between countries and between groups of tion by the United Nations General Assembly in countries, the People section includes indicators 2000, various international agencies including disaggregated by location and by socioeconomic the World Bank resolved to invest in using high- and demographic strata within countries, such quality harmonized data to monitor the Millen- as gender, age, and wealth quintile. These data nium Development Goals. These efforts range provide a deeper perspective on the disparities from providing technical and financial assis- within countries. New indicators for 2013 include tance to strengthen country statistical systems sex-disaggregated data on the under-five mortal- to fostering international collaboration through ity rate, sex-disaggregated youth labor force par- participation in the United Nations Inter-Agency ticipation rates, and numerous indicators from and Expert Group on the Millennium Develop- the World Bank’s Atlas of Social Protection Indica- ment Goal Indicators and several thematic tors of Resilience and Equity database. Economy States and markets Global links Back World Development Indicators 2013 35 Highlights East Asia & Pacific: Narrowing gaps in access to improved sanitation facilities and water sources Share of population with access (%) During the past 20 years the share of the developing world’s population  To improved sanitation facilities To improved water sources with access to improved sanitation facilities and water sources has 100 risen substantially. East Asia and Pacific has made above-average 90 90 86 progress on improving both and narrowing the gap between them, 75 driven by a rapid expansion in access to improved sanitation from 71 71 68 66 61 30 percent in 1990 to 66 percent in 2010. In South Asia progress on 56 50 access to an improved water source was almost on par with East Asia 48 and Pacific, but access to improved sanitation facilities remains very 37 38 30 31 Saharan low. Indeed, the region fares only marginally better than Sub-­ 25 26 22 Africa, which progressed substantially slower over the past two decades. But both regions made progress on expanding the share of 0 the population with access to an improved water source. 1990 2010 1990 2010 1990 2010 1990 2010 Developing East Asia South Sub-Saharan countries & Paci c Asia Africa Source: Online table 2.16. Europe & Central Asia: Variation in prevalence of underweight children Prevalence of child malnutrition, underweight, Malnourishment in children has been linked to poverty, low levels of most recent year, 2005–11 (% of children under age 5) education, and poor access to health services. It increases the risk of 25 death, inhibits cognitive development, and can adversely affect health 20 status during adulthood. Adequate nutrition is a cornerstone for devel- opment, health, and the survival of current and future generations. 15 Europe and Central Asia has the lowest prevalence (1.5 percent) of underweight children among developing regions, but there is substan- 10 tial variation across countries. At 3.2 percent, prevalence in Moldova is more like that in Latin America and the Caribbean countries; at 5 5.3 percent, prevalence in Armenia is more like that in East Asia and 0 Pacific countries; and at 6.3 percent, prevalence in Albania is more Middle East & North Africa Georgia Bulgaria Moldova Armenia Albania Tajikistan Europe & Central Asia Latin America & Caribbean East Asia & Paci c Sub-Saharan Africa like that in Middle East and North African countries. Tajikistan, a low- income country, at 15 percent has the highest proportion of under- weight children in the region. Source: Online table 2.18. Latin America & Caribbean: Income inequality falling but remains among the world’s highest Gini coef cient, most recent value, 2000–11 T he Gini coefficient, a common indicator of income inequality, mea-  sures how much the per capita income distribution within a country 65 Latin America & Caribbean countries deviates from perfect equality. (A Gini coefficient of 0 represents Inequality Other upper middle income countries increased Other countries perfect equality, and a value of 100 perfect inequality.) Trends in 55 developing countries over the past two decades suggest that many Inequality unchanged countries have become less unequal, but trends differ by region and by income. Inequality in Latin America and the Caribbean fell notably 45 Inequality in almost all upper middle-income countries but remains among the decreased ­ orldwide. The Gini coefficient is higher than the Latin highest w 35 America and the Caribbean average in only two other upper middle- i ncome income countries and in only a few low- and lower middle-­ countries. 25 25 35 45 55 65 Gini coef cient (most recent value, 1990–99) Source: Online table 2.9 and World Bank PovcalNet. 36  World Development Indicators 2013 Front ? User guide World view People Environment Middle East & North Africa: Many educated women are not participating in the labor force More than 70 percent of girls in the Middle East and North Africa Gross secondary enrollment ratio for girls (% of relevant age group) Labor force participation rate for women (% of women ages 15 attend secondary school (higher than most developing countries), but and older) labor force participation rates have stagnated at around 20 percent 100 since 1990 (lower than most developing countries). Eight of the ten countries with the largest gap between their labor force participation 75 rate and secondary enrollment ratio are in the Middle East and North Africa. (Costa Rica and Sri Lanka are the only countries in the top 10 50 not from the region.) Morocco and the Republic of Yemen have the smallest gap, but they also have the lowest secondary enrollment ratio. 25 In addition to whether women participate in economic activities, where and in what condition women work are also important. The region also 0 Yemen, Rep., Tunisia, Jordan, Algeria, Lebanon, Morocco, North Africa, countries, 2011 2009 2010 2009 2011 Iran, Islamic Rep., 2011 Egypt, Arab Rep., 2010 2007 Middle East & 2011 Developing 2011 has the largest gender gap in the share of vulnerable employment (see online table 2.4). Source: Online tables 2.2 and 2.11. South Asia: In India more girls than boys die before their fifth birthday The ratio of girls’ to boys’ under-five mortality rate varies across Ratio of girls’ to boys’ under- ve mortality rate, 2011 Lowest in region Highest in region developing countries, but on average it is 0.96. East Asia and Pacific has the largest variation among developing regions. At one extreme East Asia Palau 0.59 1.06 Solomon Islands & Paci c is Palau, where mortality rates for boys are two-thirds higher than Europe & that for girls. Biologically, boys are more vulnerable than girls, so Belarus 0.73 0.92 Azerbaijan Central Asia under-five mortality rates are usually higher for boys than girls. This Latin America biological advantage can be reversed, however, by socioeconomic Jamaica 0.75 0.93 Grenada & Caribbean factors such as gender inequalities in nutrition and medical care or Middle East & Tunisia 0.85 0.96 Iran, Islamic Rep. discrimination against girls. India and the Solomon Islands are the North Africa only developing countries where more girls than boys die before their South Sri Lanka 0.81 1.09 India Asia fifth birthday. In India under-five mortality rates for girls and boys have improved, but the ratio of girls’ to boys’ under-five deaths has stayed Sub-Saharan Eritrea 0.83 0.98 South Sudan Africa at around 1.1 since 1990. 0.50 0.75 1.00 1.25 (parity) Source: Online table 2.21. Saharan Africa: Different demographic transition paths at varying speeds Sub-­ S aharan Africa dies before Today, one of every nine children in Sub-­ Under- ve mortality rate (per 1,000 live births) their fifth birthday, and fertility rates there remain higher than any- 400 S aharan countries pro- where else in the developing world. Sub-­ Côte d’Ivoire Gabon 1970 Mali Niger gressed over the past four decades, but they are moving along dif- Sub-Saharan Africa 1970 1990 ferent paths at varying speeds. Gabon, ahead of the curve, had the 300 under-five mortality and total fertility rates in 1980 that the region 1970 1970 has today. Niger made little progress between 1970 and 1990 but 200 2010 has since seen rapid improvements in its under-five mortality rate 1980 and a marginal decline in its fertility rate. In 1970 Côte d’Ivoire had 2010 1980 2010 2010 an average mortality rate but a high fertility rate. Its mortality rate 100 declined quickly until 1980, thereafter its fertility rate declined rap- 2010 idly and overtook the region by 2010. Mali, which had the highest 0 under-five mortality rate in 1970, took until 2010 to reach the rate 3 4 5 6 7 8 9 Total fertility rate (births per woman) the region passed in 1990. Source: Online table 2.21. Economy States and markets Global links Back World Development Indicators 2013 37 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 own-account managers estimate 1,000 % of 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 2005–11 a 2011 2010 2011 2011 2011 2005–11a 2011 2007–11 a 2007–11 a 2007–11 a Afghanistan .. 101 460 103 <0.1 .. .. 49 .. .. .. Albania 6.3 14 27 16 .. .. 99 60 .. 13.8 .. Algeria 3.7 30 97 6 .. 94 92 44 .. 10.0 .. American Samoa .. .. .. .. .. .. .. .. .. .. .. Andorra .. 3 .. .. .. 63 .. .. .. .. .. Angola 15.6 158 450 153 2.1 .. 73 70 .. .. .. Antigua and Barbuda .. 8 .. .. .. 98 .. .. .. .. .. Argentina 2.3 14 77 55 0.4 .. 99 61 19 7.2 .. Armenia 5.3 18 30 34 0.2 83 100 59 38 28.6 22 Aruba .. .. .. 28 .. .. 99 .. 4 5.7 40 Australia .. 5 7 13 0.2 .. .. 66 9 5.1 37 Austria .. 4 4 10 0.4 .. .. 61 9 4.1 27 Azerbaijan 8.4 45 43 32 <0.1 93 100 65 55 5.4 7 Bahamas, The .. 16 47 29 2.8 .. .. 74 .. 13.7 52 Bahrain .. 10 20 15 .. .. 100 71 2 .. .. Bangladesh 41.3 46 240 70 <0.1 .. 77 71 .. 5.0 .. Barbados .. 20 51 41 0.9 111 .. 70 .. 11.2 47 Belarus 1.3 6 4 21 0.4 104 100 56 .. .. .. Belgium .. 4 8 12 0.3 .. .. 54 10 7.1 30 Belize 4.9 17 53 72 2.3 110 .. 65 .. 8.2 .. Benin 20.2 106 350 100 1.2 75 55 73 .. .. .. Bermuda .. .. .. .. .. .. .. .. .. .. .. Bhutan 12.7 54 180 46 0.3 103b 74 72 71 3.1 27 Bolivia 4.5 51 190 75 0.3 .. 99 72 55 3.4 29 Bosnia and Herzegovina 1.6 8 8 14 .. 76 100 46 25 27.6 .. Botswana 11.2 26 160 45 23.4 .. 95 77 .. .. .. Brazil 2.2 16 56 76 0.3 .. 98 70 25 8.3 36 Brunei Darussalam .. 7 24 23 .. 120 100 66 .. .. .. Bulgaria .. 12 11 38 <0.1 .. 98 54 9 11.2 37 Burkina Faso 26.0 146 300 119 1.1 .. 39 84 .. 3.3 .. Burundi 35.2 139 800 20 1.3 62 78 83 .. .. .. Cambodia 29.0 43 250 35 0.6 90 87 83 69 0.2 21 Cameroon 16.6 127 690 118 4.6 78 83 71 76 3.8 .. Canada .. 6 12 12 0.3 .. .. 67 .. 7.4 36 Cape Verde .. 21 79 72 1.0 95 98 67 .. .. .. Cayman Islands .. .. .. .. .. .. 99 .. .. 4.0 44 Central African Republic 28.0 164 890 100 4.6 43 65 79 .. .. .. Chad .. 169 1,100 143 3.1 38 47 72 .. .. .. Channel Islands .. .. .. 9 .. .. .. .. .. .. .. Chile 0.5 9 25 56 0.5 .. 99 60 24 7.1 .. China 3.4 15 37 9 <0.1 .. 99 74 .. 4.1 .. Hong Kong SAR, China .. .. .. 4 .. 91 .. 59 7 3.4 32 Macao SAR, China .. .. .. 4 .. .. 100 72 4 2.6 31 Colombia 3.4 18 92 69 0.5 112 98 67 49 11.6 .. Comoros .. 79 280 52 <0.1 .. 86 58 .. .. .. Congo, Dem. Rep. 28.2 168 540 177 .. .. 65 71 .. .. .. Congo, Rep. 11.8 99 560 114 3.3 .. 80 71 .. .. .. 38  World Development Indicators 2013 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 own-account managers estimate 1,000 % of 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 2005–11 a 2011 2010 2011 2011 2011 2005–11a 2011 2007–11 a 2007–11 a 2007–11 a Costa Rica 1.1 10 40 63 0.3 99 98 63 20 7.7 35 Côte d’Ivoire 29.4 115 400 110 3.0 59 67 67 .. .. .. Croatia .. 5 17 13 <0.1 .. 100 53 18 13.4 25 Cuba 1.3 6 73 44 0.2 99 100 57 .. 2.5 .. Curaçao .. .. .. .. .. .. .. .. .. .. .. Cyprus .. 3 10 6 .. .. 100 65 14 7.7 14 Czech Republic .. 4 5 10 <0.1 .. .. 59 14 6.7 26 Denmark .. 4 12 5 0.2 .. .. 64 6 7.6 28 Djibouti 29.6 90 200 20 1.4 57b .. 52 .. .. .. Dominica .. 12 .. .. .. 94 .. .. .. .. .. Dominican Republic 3.4 25 150 105 0.7 92 97 65 37 12.4 31 Ecuador .. 23 110 81 0.4 112 99 68 42 4.2 .. Egypt, Arab Rep. 6.8 21 66 42 <0.1 .. 88 49 27 9.0 11 El Salvador 6.6 15 81 77 0.6 101 96 62 38 7.0 29 Equatorial Guinea .. 118 240 116 4.7 52 98 87 .. .. .. Eritrea .. 68 240 56 0.6 .. 89 85 .. .. .. Estonia .. 4 2 18 1.3 .. 100 62 5 12.5 36 Ethiopia 29.2 77 350 53 1.4 58 55 84 .. .. .. Faeroe Islands .. .. .. .. .. .. .. .. .. .. .. Fiji .. 16 26 43 <0.1 103 .. 60 .. 8.6 .. Finland .. 3 5 9 <0.1 .. .. 60 9 7.7 32 France .. 4 8 6 0.4 .. .. 56 7 9.3 39 French Polynesia .. .. .. 49 .. .. .. 58 .. 11.7 .. Gabon .. 66 230 83 5.0 .. 98 61 .. .. .. Gambia, The 15.8 101 360 69 1.5 66 67 78 .. .. .. Georgia 1.1 21 67 41 0.2 .. 100 64 63 15.1 34 Germany 1.1 4 7 7 0.2 .. .. 60 7 5.9 30 Ghana 14.3 78 350 64 1.5 99 b 81 69 .. .. .. Greece 1.1 4 3 10 0.2 .. 99 55 29 17.7 23 Greenland .. .. .. .. .. .. .. .. .. .. .. Grenada .. 13 24 37 .. .. .. .. .. .. .. Guam .. .. .. 50 .. .. .. 61 .. .. .. Guatemala 13.0 30 120 103 0.8 .. 87 68 .. 4.1 .. Guinea 20.8 126 610 138 1.4 .. 63 72 .. .. .. Guinea-Bissau 17.2 161 790 99 2.5 .. 72 73 .. .. .. Guyana 11.1 36 280 57 1.1 85 .. 60 .. 21.0 .. Haiti 18.9 70 350 42 1.8 .. 72 65 .. .. .. Honduras 8.6 21 100 87 .. 101 95 62 53 4.8 .. Hungary .. 6 21 14 <0.1 .. 99 51 7 10.9 40 Iceland .. 3 5 12 0.3 .. .. 75 8 7.1 40 India 43.5 61 200 77 .. .. 81 56 81 3.5 14 Indonesia 18.6 32 220 43 0.3 .. 99 68 57 6.6 22 Iran, Islamic Rep. .. 25 21 26 0.2 106 99 45 42 10.5 13 Iraq 7.1 38 63 88 .. .. 83 42 .. .. .. Ireland .. 4 6 11 0.3 .. .. 61 12 14.4 33 Isle of Man .. .. .. .. .. .. .. .. .. .. .. Israel .. 4 7 14 0.2 .. .. 57 7 5.6 32 Economy States and markets Global links Back World Development Indicators 2013 39 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 own-account managers estimate 1,000 % of 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 2005–11 a 2011 2010 2011 2011 2011 2005–11a 2011 2007–11 a 2007–11 a 2007–11 a Italy .. 4 4 5 0.4 .. 100 48 18 8.4 25 Jamaica 1.9 18 110 71 1.8 .. 95 64 37 12.7 .. Japan .. 3 5 6 <0.1 .. .. 60 11 4.5 .. Jordan 1.9 21 63 24 .. .. 99 42 9 12.9 .. Kazakhstan 4.9 28 51 26 0.2 108b 100 72 30 5.4 38 Kenya 16.4 73 360 99 6.2 .. 93 67 .. .. .. Kiribati .. 47 .. .. .. .. .. .. .. .. .. Korea, Dem. Rep. 18.8 33 81 1 .. .. 100 78 .. .. .. Korea, Rep. .. 5 16 5 <0.1 .. .. 60 25 3.4 10 Kosovo .. .. .. .. .. .. .. .. .. 45.4 .. Kuwait 1.7 11 14 14 .. .. 99 68 .. .. .. Kyrgyz Republic 2.7 31 71 33 0.4 96 100 67 .. 8.2 .. Lao PDR 31.6 42 470 32 0.3 93 84 78 .. .. .. Latvia .. 8 34 14 0.7 93 100 61 8 15.4 45 Lebanon 5.2 9 25 16 <0.1 87 99 46 28 9.0 8 Lesotho 13.5 86 620 63 23.3 68 92 66 .. 25.3 .. Liberia 20.4 78 770 127 1.0 66 77 61 79 3.7 .. Libya 5.6 16 58 3 .. .. 100 53 .. .. .. Liechtenstein .. 2 .. .. .. 101 .. .. .. .. .. Lithuania .. 6 8 17 <0.1 95 100 59 8 15.4 38 Luxembourg .. 3 20 9 0.3 .. .. 57 6 4.9 24 Macedonia, FYR 1.8 10 10 19 .. .. 99 56 23 31.4 28 Madagascar .. 62 240 125 0.3 73 65 86 .. .. .. Malawi 13.8 83 460 108 10.0 71 87 83 .. .. .. Malaysia 12.9 7 29 11 0.4 .. 98 60 22 3.4 25 Maldives 17.8 11 60 11 <0.1 107 99 66 .. .. .. Mali 27.9 176 540 172 1.1 55 44 53 83 .. .. Malta .. 6 8 13 <0.1 .. 98 51 9 6.4 23 Marshall Islands .. 26 .. .. .. 97 .. .. .. .. .. Mauritania 15.9 112 510 73 1.1 .. 68 54 .. 31.2 .. Mauritius .. 15 60 33 1.0 .. 97 60 15 7.9 23 Mexico 3.4 16 50 67 0.3 104 98 62 29 5.3 31 Micronesia, Fed. Sts. .. 42 100 20 .. .. .. .. .. .. .. Moldova 3.2 16 41 30 0.5 91 99 42 29 6.7 38 Monaco .. 4 .. .. .. .. .. .. .. .. .. Mongolia 5.3 31 63 19 <0.1 115 96 60 58 .. 47 Montenegro 2.2 7 8 15 .. 99 b 99 .. .. 19.7 31 Morocco 3.1 33 100 12 0.2 99 b 79 50 52 8.9 13 Mozambique 18.3 103 490 129 11.3 56 72 85 .. .. .. Myanmar 22.6 62 200 13 0.6 .. 96 79 .. .. .. Namibia 17.5 42 200 58 13.4 .. 93 64 14 37.6 .. Nepal 29.1 48 170 90 0.3 .. 83 84 .. 2.7 .. Netherlands .. 4 6 4 0.2 .. .. 65 11 4.4 30 New Caledonia .. .. .. 20 .. .. 100 58 .. .. .. New Zealand .. 6 15 21 <0.1 .. .. 68 12 6.5 40 Nicaragua 5.7 26 95 106 0.2 .. 87 63 47 8.0 .. Niger 39.9 125 590 196 0.8 46 37 65 .. .. .. 40  World Development Indicators 2013 Front ? User guide view People Environment 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 own-account managers estimate 1,000 % of 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 2005–11 a 2011 2010 2011 2011 2011 2005–11a 2011 2007–11 a 2007–11 a 2007–11 a Nigeria 26.7 124 630 113 3.7 .. 72 56 .. .. .. Northern Mariana Islands .. .. .. .. .. .. .. .. .. .. .. Norway .. 3 7 8 0.2 .. .. 66 5 3.3 31 Oman 8.6 9 32 9 .. 107 98 61 .. .. .. Pakistan 30.9 72 260 29 <0.1 67 71 53 63 5.0 3 Palau .. 19 .. .. .. .. .. .. .. .. .. Panama 3.9 20 92 77 0.8 101 98 66 29 4.5 46 Papua New Guinea 18.1 58 230 63 0.7 .. 68 72 .. 4.0 .. Paraguay 3.4 22 99 68 0.3 .. 99 72 42 5.6 34 Peru 4.5 18 67 50 0.4 97 97 76 40 7.8 19 Philippines 20.7 25 99 48 <0.1 .. 98 64 41 7.0 55 Poland .. 6 5 13 <0.1 .. 100 56 18 9.6 38 Portugal .. 3 8 13 0.7 .. 100 62 16 12.7 33 Puerto Rico .. .. 20 51 .. .. 87 45 .. 15.7 43 Qatar .. 8 7 16 .. 96 97 86 0 0.6 10 Romania .. 13 27 29 <0.1 .. 97 56 32 7.4 31 Russian Federation .. 12 34 25 .. .. 100 63 6 6.6 37 Rwanda 11.7 54 340 36 2.9 .. 77 86 .. 2.4 .. Samoa .. 19 100 26 .. 98 99 61 .. .. .. San Marino .. 2 .. .. .. 93 .. .. .. 2.6 18 São Tomé and Príncipe 14.4 89 70 58 1.0 115 95 60 .. .. .. Saudi Arabia 5.3 9 24 20 .. 106 98 50 .. 5.4 8 Senegal 19.2 65 370 93 0.7 63 65 77 .. .. .. Serbia 1.8 7 12 20 <0.1 99 99 .. 27 19.2 33 Seychelles .. 14 .. .. .. 125 99 .. .. .. .. Sierra Leone 21.3 185 890 112 1.6 74 59 68 .. .. .. Singapore .. 3 3 6 <0.1 .. 100 67 10 2.9 34 Sint Maarten .. .. .. .. .. .. .. .. .. .. .. Slovak Republic .. 8 6 17 <0.1 .. .. 59 12 13.5 31 Slovenia .. 3 12 5 <0.1 .. 100 59 13 8.2 38 Solomon Islands 11.5 22 93 66 .. .. .. 67 .. .. .. Somalia 32.8 180 1,000 68 0.7 .. .. 57 .. .. .. South Africa 8.7 47 300 52 17.3 .. 98 52 10 24.7 31 South Sudan .. 121 .. .. 3.1 .. .. .. .. .. .. Spain .. 4 6 11 0.4 .. 100 59 11 21.6 30 Sri Lanka 21.6 12 35 22 <0.1 .. 98 55 42 4.9 24 St. Kitts and Nevis .. 7 .. .. .. 93 .. .. .. .. .. St. Lucia .. 16 35 57 .. 93 .. 71 .. 14.0 .. St. Martin .. .. .. .. .. .. .. .. .. .. .. St. Vincent and Grenadines .. 21 48 55 .. .. .. 67 .. .. .. Sudan 31.7 86d 730 55 0.4 d .. 87 54 .. .. .. Suriname 7.5 30 130 36 1.0 88 98 55 .. .. .. Swaziland 7.3 104 320 71 26.0 77 94 57 .. .. .. Sweden .. 3 4 6 0.2 .. .. 64 7 7.5 35 Switzerland .. 4 8 4 0.4 .. .. 68 9 4.1 33 Syrian Arab Republic 10.1 15 70 38 .. 106 95 43 33 8.4 9 Tajikistan 15.0 63 65 26 0.3 104 100 66 .. .. .. Economy States and markets Global links Back World Development Indicators 2013 41 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 own-account managers estimate 1,000 % of 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 2005–11 a 2011 2010 2011 2011 2011 2005–11a 2011 2007–11 a 2007–11 a 2007–11 a Tanzania 16.2 68 460 129 5.8 81b 77 89 .. .. .. Thailand 7.0 12 48 38 1.2 .. 98 72 54 0.7 25 Timor-Leste 45.3 54 300 55 .. 72 80 57 70 3.6 .. Togo 20.5 110 300 57 3.4 77 82 81 .. .. .. Tonga .. 15 110 19 .. .. 99 64 .. .. .. Trinidad and Tobago .. 28 46 32 1.5 .. 100 66 .. 4.6 .. Tunisia 3.3 16 56 5 <0.1 .. 97 48 .. 13.0 .. Turkey .. 15 20 32 <0.1 .. 98 50 33 9.8 10 Turkmenistan .. 53 67 17 .. .. 100 61 .. .. .. Turks and Caicos Islands .. .. .. .. .. .. .. .. .. 5.4 .. Tuvalu 1.6 30 .. .. .. .. .. .. .. .. .. Uganda 16.4 90 310 131 7.2 55 87 78 .. 4.2 .. Ukraine .. 10 32 27 0.8 97 100 59 .. 7.9 39 United Arab Emirates .. 7 12 24 .. .. 95 79 1 4.0 10 United Kingdom .. 5 12 30 0.3 .. .. 62 12 7.8 34 United States .. 8 21 30 0.7 .. .. 64 .. 8.9 43 Uruguay .. 10 29 59 0.6 .. 99 66 22 6.0 40 Uzbekistan 4.4 49 28 13 .. 93 100 61 .. .. .. Vanuatu 11.7 13 110 51 .. .. 94 71 70 4.6 29 Venezuela, RB 3.7 15 92 88 0.6 95 99 66 33 8.3 .. Vietnam 20.2 22 59 24 0.5 104 97 77 63 2.0 .. Virgin Islands (U.S.) .. .. .. 23 .. .. .. 62 .. .. .. West Bank and Gaza 2.2 22 .. 49 .. 91 99 41 26 23.7 10 Yemen, Rep. .. 77 200 69 0.2 63 85 49 .. 14.6 .. Zambia 14.9 83 440 140 12.5 .. 74 79 .. .. .. Zimbabwe 10.1 67 570 56 14.9 .. 99 86 .. .. .. World 15.7 w 51 w 210 w 53 w 0.8 w 90 w 90 w 64 w .. w 5.9 w Low income 22.6c 95 410 92 2.4 68 74 75 .. .. Middle income 16.0 c 46 190 50 .. .. 91 64 .. 5.2 Lower middle income 24.3c 62 260 66 .. .. 84 58 71 4.9 Upper middle income 2.9c 20 62 30 0.6 .. 99 69 .. 5.0 Low & middle income 17.4 c 56 230 57 1.0 89 88 65 .. 5.2 East Asia & Pacific 5.5c 21 83 19 0.2 .. 99 73 .. 4.2 Europe & Central Asia 1.5c 21 32 26 .. 98 99 59 18 8.0 Latin America & Carib. 3.1c 19 81 71 0.4 102 97 66 31 7.7 Middle East & N. Africa 6.3c 32 81 37 .. 90 91 46 .. 10.6 South Asia 33.2c 62 220 71 .. .. 79 57 78 3.5 Sub-­Saharan Africa 21.4 c 109 500 106 4.9 70 72 70 .. .. High income 1.7c 6 14 17 0.4 100 100 60 .. 8.1 Euro area .. 4 6 8 0.3 99 100 57 11 10.1 a. Data are for the most recent year available. b. Data are for 2012. c. Calculated by World Bank staff using the United Nations Children’s Fund, World Health Organization, and World Bank harmonized database and aggregation method. d. Excludes South Sudan. 42  World Development Indicators 2013 Front ? User guide World view People Environment People 2 About the data Though not included in the table due to space limitations, many WHO, the United Nations Population Division, the World Bank, indicators in this section are available disaggregated by sex, place and other universities and research institutes, has developed and of residence, wealth, and age in the World Development Indicators adopted a statistical method that uses all available information to database. reconcile differences. Trend lines are obtained by fitting a country- specific regression model of mortality rates against their reference Child malnutrition dates. (For further discussion of childhood mortality estimates, Good nutrition is the cornerstone for survival, health, and devel- see UN Inter-agency Group for Child Mortality Estimation 2012; for opment. Well-nourished children perform better in school, grow detailed background data and for a graphic presentation, see www into healthy adults, and in turn give their children a better start .childmortality.org). in life. Well-nourished women face fewer risks during pregnancy and childbirth, and their children set off on firmer developmental Maternal mortality paths, both physically and mentally. Undernourished children have Measurements of maternal mortality are subject to many types lower resistance to infection and are more likely to die from com- of errors. In countries with incomplete vital registration systems, mon childhood ailments such as diarrheal diseases and respiratory deaths of women of reproductive age or their pregnancy status may infections. Frequent illness saps the nutritional status of those who not be reported, or the cause of death may not be known. Even in survive, locking them into a vicious cycle of recurring sickness and high-income countries with reliable vital registration systems, mis- faltering growth. classification of maternal deaths has been found to lead to serious The proportion of underweight children is the most common child underestimation. Surveys and censuses can be used to measure malnutrition indicator. Being even mildly underweight increases the maternal mortality by asking respondents about survivorship of sis- risk of death and inhibits cognitive development in children. And ters. But these estimates are retrospective, referring to a period it perpetuates the problem across generations, as malnourished approximately five years before the survey, and may be affected by women are more likely to have low-birthweight babies. Estimates recall error. Further, they reflect pregnancy-related deaths (deaths of prevalence of underweight children are from the World Health while pregnant or within 42 days of pregnancy termination, irrespec- Organization’s (WHO) Global Database on Child Growth and Malnu- tive of the cause of death) and need to be adjusted to conform to trition, a standardized compilation of child growth and malnutrition the strict definition of maternal death. data from national nutritional surveys. To better monitor global child Maternal mortality ratios in the table are modeled estimates malnutrition, the United Nations Children’s Fund (UNICEF), the WHO, based on work by the WHO, UNICEF, United Nations Population Fund and the World Bank have jointly produced estimates for 2011 and (UNFPA), and World Bank and include country-level time series data. trends since 1990 for regions, income groups, and the world, using For countries without complete registration data but with other types a harmonized database and aggregation method. of data and for countries with no data, maternal mortality is esti- mated with a multilevel regression model using available national Under-five mortality maternal mortality data and socioeconomic information, including Mortality rates for children and others are important indicators fertility, birth attendants, and gross domestic product. The meth- of health status. When data on the incidence and prevalence of odology differs from that used for previous estimates, so data pre- diseases are unavailable, mortality rates may be used to identify sented here should not be compared across editions. vulnerable populations. And they are among the indicators most frequently used to compare socioeconomic development across Adolescent fertility countries. Reproductive health is a state of physical and mental well-being The main sources of mortality data are vital registration sys- in relation to the reproductive system and its functions and pro- tems and direct or indirect estimates based on sample surveys cesses. Means of achieving reproductive health include education ­ ystem—covering at or censuses. A complete vital registration s and services during pregnancy and childbirth, safe and effective least 90 percent of vital events in the population—is the best contraception, and prevention and treatment of sexually transmitted source of age-specific mortality data. But complete vital registra- diseases. Complications of pregnancy and childbirth are the leading tion systems are fairly uncommon in developing countries. Thus cause of death and disability among women of reproductive age in estimates must be obtained from sample surveys or derived by developing countries. applying indirect estimation techniques to registration, census, Adolescent pregnancies are high risk for both mother and child. or survey data (see Primary data documentation). Survey data are They are more likely to result in premature delivery, low birthweight, 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 United Nations Inter-agency up opportunities for education and employment, or seek unsafe Group for Child Mortality Estimation, which comprises UNICEF, abortions. Estimates of adolescent fertility rates are based on vital Economy States and markets Global links Back World Development Indicators 2013 43 2 People registration systems or, in their absence, censuses or sample sur- final year of primary education. There are many reasons why the pri- veys and are generally considered reliable measures of fertility in the mary completion rate may exceed 100 percent. The numerator may recent past. Where no empirical information on age-specific fertility include late entrants and overage children who have repeated one rates is available, a model is used to estimate the share of births to or more grades of primary education as well as children who entered adolescents. For countries without vital registration systems fertility school early, while the denominator is the number of children at the rates are generally based on extrapolations from trends observed entrance age for the last grade of primary education. 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. New models track the course of be used cautiously. Generally, literacy encompasses numeracy, the HIV epidemics and their impacts, making full use of information ability to make simple arithmetic calculations. on HIV prevalence trends from surveillance data as well as survey Data on youth literacy are compiled by the United Nations Educa- data. The models include the effect of antiretroviral therapy, take tional, Scientific and Cultural Organization (UNESCO) Institute for into account reduced infectivity among people receiving antiretrovi- Statistics based on national censuses and household surveys dur- ral therapy (which is having a larger impact on HIV prevalence and ing 1985–2011 and, for countries without recent literacy data, using allowing HIV-positive people to live longer), and allow for changes in the Global Age-Specific Literacy Projection Model. urbanization over time (important because prevalence is higher in urban areas and because many countries have seen rapid urbaniza- Labor force participation tion over the past two decades). The estimates include plausible The labor force is the supply of labor available for producing goods bounds, available at http://data.worldbank.org, which reflect the and services in an economy. It includes people who are currently 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 five 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 upper estimate of the actual primary completion rate, since data that affect data comparability, such as census or survey reference limitations preclude adjusting for students who drop out during the period, definition of working age, and geographic coverage. For 44  World Development Indicators 2013 Front ? User guide World view People Environment People 2 country-level information on source, reference period, or definition, jobs. Such unemployment, often called frictional unemployment, consult the footnotes in the World Development Indicators data- results from the normal operation of labor markets. base or the ILO’s Key Indicators of the Labour Market, 7th edition, Changes in unemployment over time may reflect changes in the database. demand for and supply of labor, but they may also reflect changes The labor force participation rates in the table are estimates in reporting practices. In countries without unemployment or welfare from the ILO’s Key Indicators of the Labour Market, 7th edition, benefits people eke out a living in vulnerable employment. In coun- database. These harmonized estimates use strict data selection tries with well-developed safety nets workers can afford to wait for criteria and enhanced methods to ensure comparability across suitable or desirable jobs. But high and sustained unemployment countries and over time to avoid the inconsistencies mentioned indicates serious inefficiencies in resource allocation. above. Estimates are based mainly on labor force surveys, with The criteria for people considered to be seeking work, and the other sources (population censuses and nationally reported esti- treatment of people temporarily laid off or seeking work for the mates) used only when no survey data are available. Because other first time, vary across countries. In many developing countries it employment data are mostly national estimates, caution should is especially difficult to measure employment and unemployment be used when comparing labor force participation rate and other in agriculture. The timing of a survey can maximize the effects of employment data. seasonal unemployment in agriculture. And informal sector employ- ment is difficult to quantify where informal activities are not tracked. Vulnerable employment Data on unemployment are drawn from labor force sample surveys The proportion of unpaid family workers and own-account workers in and general household sample surveys, censuses, and official esti- total employment is derived from information on status in employ- mates. Administrative records, such as social insurance statistics ment. Each group faces different economic risks, and unpaid family and employment office statistics, are not included because of their workers and own-account workers are the most vulnerable—and limitations in coverage. therefore the most likely to fall into poverty. They are the least likely Women tend to be excluded from the unemployment count for to have formal work arrangements, are the least likely to have social various reasons. Women suffer more from discrimination and from protection and safety nets to guard against economic shocks, and structural, social, and cultural barriers that impede them from seek- are often incapable of generating enough savings to offset these ing work. Also, women are often responsible for the care of children shocks. A high proportion of unpaid family workers in a country and the elderly and for household affairs. They may not be available indicates weak development, little job growth, and often a large for work during the short reference period, as they need to make rural economy. arrangements before starting work. Further, women are considered Data on vulnerable employment are drawn from labor force and to be employed when they are working part-time or in temporary general household sample surveys, censuses, and official esti- jobs, despite the instability of these jobs or their active search for mates. Besides the limitation mentioned for calculating labor force more secure employment. participation rates, there are other reasons to limit comparability. For example, information provided by the Organisation for Economic Female legislators, senior officials, and managers Co-operation and Development relates only to civilian employment, Despite much progress in recent decades, gender inequalities which can result in an underestimation of “employees� and “work- remain pervasive in many dimensions of life. But while gender ers not classified by status,� especially in countries with large inequalities exist throughout the world, they are most prevalent in armed forces. While the categories of unpaid family workers and developing countries. Inequalities in the allocation of education, own-account workers would not be affected, their relative shares health care, nutrition, and political voice matter because of their would be. strong association with well-being, productivity, and economic growth. These patterns of inequality begin at an early age, with boys Unemployment routinely receiving a larger share of education and health spending The ILO defines the unemployed as members of the economically than girls, for example. The share of women in high-skilled occu- active population who are without work but available for and seek- pations such as legislators, senior officials, and managers indi- ing work, including people who have lost their jobs or who have cates women’s status and role in the labor force and society at voluntarily left work. Some unemployment is unavoidable. At any large. Women are vastly underrepresented in decisionmaking posi- time some workers are temporarily unemployed—between jobs as tions in government, although there is some evidence of recent employers look for the right workers and workers search for better improvement. Economy States and markets Global links Back World Development Indicators 2013 45 2 People Definitions Data sources • Prevalence of child malnutrition, underweight, is the percent- Data on child malnutrition prevalence are from the WHO’s Global age of children under age 5 whose weight for age is more than two Database on Child Growth and Malnutrition (www.who.int/ standard deviations below the median for the international refer- nutgrowthdb/en/). Data on under-five mortality rates are from UN ence population ages 0–59 months. Data are based on the WHO Inter-agency Group for Child Mortality Estimation (2012) and are child growth standards released in 2006. • Under-five mortality based mainly on household surveys, censuses, and vital registra- rate is the probability of a child born in a specific year dying before tion data. Modeled estimates of maternal mortality ratios are from reaching age 5, if subject to the age-specific mortality rates of that WHO and others (2012). Data on adolescent fertility rates are from year. The probability is derived from life tables and is expressed as United Nations Population Division (2011), with annual data linearly a rate per 1,000 live births. • Maternal mortality ratio, modeled interpolated by the World Bank’s Development Data Group. Data on estimate, is the number of women who die from pregnancy-related HIV prevalence are from UNAIDS (2012). Data on primary completion causes while pregnant or within 42 days of pregnancy termination, rates and literacy rates are from the UNESCO Institute for Statistics per 100,000 live births. • Adolescent fertility rate is the number (www.uis.unesco.org). Data on labor force participation rates, vul- of births per 1,000 women ages 15–19. • Prevalence of HIV is the nerable employment, unemployment, and female legislators, senior percentage of people who are infected with HIV in the relevant age officials, and managers are from the ILO’s Key Indicators of the group. • Primary completion rate is the number of new entrants Labour Market, 7th edition, database. (enrollments minus repeaters) in the last grade of primary educa- tion, regardless of age, divided by the population at the entrance age References for the last grade of primary education. Data limitations preclude De Onis, Mercedes, Monika Blössner, Elaine Borghi, Richard Mor- adjusting for students who drop out during the final year of primary ris, and Edward A. Frongillo. 2004. “Methodology for Estimating education. • Youth literacy rate is the percentage of the popula- Regional and Global Trends of Child Malnutrition.� International Jour- tion ages 15–24 that can, with understanding, both read and write nal of Epidemiology 33: 1260–70. a short simple statement about their everyday life. • Labor force ILO (International Labour Organization).Various years. Key Indicators of participation rate is the proportion of the population ages 15 and the Labour Market. Geneva: International Labour Office. older that engages actively in the labor market, by either working or UNAIDS (Joint United Nations Programme on HIV/AIDS). 2012. Global looking for work during a reference period. • Vulnerable employment Report: UNAIDS Report on the Global AIDS Epidemic 2012. Geneva. is unpaid family workers and own-account workers as a percentage UNICEF (United Nations Children’s Fund), WHO (World Health Organi- of total employment. • Unemployment is the share of the labor force zation), and World Bank. 2012. Joint Child Malnutrition Estimates—­ without work but available for and seeking employment. Definitions Levels and Trends. www.who.int/nutgrowthdb/jme_unicef_who_ of labor force and unemployment may differ by country. • Female wb.pdf. New York: UNICEF. legislators, senior officials, and managers are the percentage of UN Inter-agency Group for Child Mortality Estimation. 2012. Levels and legislators, senior officials, and managers (International Standard Trends in Child Mortality: Report 2012. New York. Classification of Occupations–88 category 1) who are female. United Nations Population Division. 2011. World Population Prospects: The 2010 Revision. New York: United Nations, Department of Eco- nomic and Social Affairs. 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. n.d. PovcalNet online database. http://iresearch .worldbank.org/PovcalNet. Washington, DC. 46  World Development Indicators 2013 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.WAG0714.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 2013 47 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.ZS External resources for health SH.XPD.EXTR.ZS 2.11 Participation in education Health expenditure per capita, $ SH.XPD.PCAP Preprimary gross enrollment ratio SE.PRE.ENRR Health expenditure per capita, PPP $ SH.XPD.PCAP.PP.KD Primary gross enrollment ratio SE.PRM.ENRR Physicians SH.MED.PHYS.ZS Secondary gross enrollment ratio SE.SEC.ENRR Nurses and midwives SH.MED.NUMW.P3 Tertiary gross enrollment ratio SE.TER.ENRR Community health workers SH.MED.CMHW.P3 Primary net enrollment rate SE.PRM.NENR Hospital beds SH.MED.BEDS.ZS Secondary net enrollment rate SE.SEC.NENR Completeness of birth registration SP.REG.BRTH.ZS Primary adjusted net enrollment rate, Male SE.PRM.TENR.MA Primary adjusted net enrollment rate, 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 Reaching grade 5, Male SE.PRM.PRS5.MA.ZS drugs SH.MLR.TRET.ZS Reaching grade 5, Female SE.PRM.PRS5.FE.ZS Tuberculosis treatment success rate SH.TBS.CURE.ZS Reaching last grade of primary education, Tuberculosis case detection rate SH.TBS.DTEC.ZS Male SE.PRM.PRSL.MA.ZS Reaching last grade of primary education, 2.17 Reproductive health Female SE.PRM.PRSL.FE.ZS Total fertility rate SP.DYN.TFRT.IN Repeaters in primary education, Male SE.PRM.REPT.MA.ZS Adolescent fertility rate SP.ADO.TFRT Repeaters in primary education, Female SE.PRM.REPT.FE.ZS Unmet need for contraception SP.UWT.TFRT Transition rate to secondary education, Male SE.SEC.PROG.MA.ZS Contraceptive prevalence rate SP.DYN.CONU.ZS Transition rate to secondary education, Pregnant women receiving prenatal care SH.STA.ANVC.ZS Female SE.SEC.PROG.FE.ZS Births attended by skilled health staff SH.STA.BRTC.ZS 2.13 Education completion and outcomes Maternal mortality ratio, National estimate SH.STA.MMRT.NE Primary completion rate, Total SE.PRM.CMPT.ZS Maternal mortality ratio, Modeled estimate SH.STA.MMRT Primary completion rate, Male SE.PRM.CMPT.MA.ZS Lifetime risk of maternal mortality SH.MMR.RISK 48  World Development Indicators 2013 Front ? User guide World view People Environment People 2 2.18 Nutrition and growth Women’s share of population ages 15+ Prevalence of undernourishment SN.ITK.DEFC.ZS living with HIV SH.DYN.AIDS.FE.ZS Prevalence of underweight, Male SH.STA.MALN.MA.ZS Prevalence of HIV, Youth male SH.HIV.1524.MA.ZS Prevalence of underweight, Female SH.STA.MALN.FE.ZS Prevalence of HIV, Youth female SH.HIV.1524.FE.ZS Prevalence of stunting, Male SH.STA.STNT.MA.ZS Antiretroviral therapy coverage SH.HIV.ARTC.ZS Prevalence of stunting, Female SH.STA.STNT.FE.ZS Death from communicable diseases and maternal, prenatal, and nutrition conditions SH.DTH.COMM.ZS Prevalence of wasting, Male SH.STA.WAST.MA.ZS Death from non-communicable diseases SH.DTH.NCOM.ZS Prevalence of wasting, Female SH.STA.WAST.FE.ZS Death from injuries SH.DTH.INJR.ZS Prevalence of overweight children, Male SH.STA.OWGH.MA.ZS Prevalence of overweight children, Female SH.STA.OWGH.FE.ZS 2.21 Mortality Life expectancy at birth SP.DYN.LE00.IN 2.19 Nutrition intake and supplements Neonatal mortality rate SH.DYN.NMRT Low-birthweight babies SH.STA.BRTW.ZS Infant mortality rate SP.DYN.IMRT.IN Exclusive breastfeeding SH.STA.BFED.ZS Under-five mortality rate, Total SH.DYN.MORT Consumption of iodized salt SN.ITK.SALT.ZS Under-five mortality rate, Male SH.DYN.MORT.MA Vitamin A supplementation SN.ITK.VITA.ZS Prevalence of anemia among children Under-five mortality rate, Female SH.DYN.MORT.FE under age 5 SH.ANM.CHLD.ZS Adult mortality rate, Male SP.DYN.AMRT.MA Prevalence of anemia among pregnant Adult mortality rate, Female SP.DYN.AMRT.FE women SH.PRG.ANEM 2.22 Health gaps by income 2.20 Health risk factors and future challenges This table provides health survey data for Prevalence of smoking, Male SH.PRV.SMOK.MA the poorest and richest quintiles. ..b Prevalence of smoking, Female SH.PRV.SMOK.FE Incidence of tuberculosis SH.TBS.INCD Data disaggregated by sex are available in Prevalence of diabetes SH.STA.DIAB.ZS the World Development Indicators database. a. Derived from data elsewhere in the World Development Indicators database. Prevalence of HIV, Total SH.DYN.AIDS.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 2013 49 ENVIRONMENT 50  World Development Indicators 2013 Front ? User guide World view People Environment 3 The Millennium Development Goals call for inte- change. The first presents data on carbon diox- grating principles of environmental sustainability ide emissions by economic sector from the into country policies and programs and reversing International Energy Agency’s annual time series environmental losses. Whether the world contin- statistics. And the second contains country indi- ues to sustain itself depends largely on properly cators on climate variability, exposure to impact, managing its natural resources. The indicators in and resilience. the Environment section measure resource use Other indicators in this section describe and the way human activities affect the natural land use, agriculture and food production, for- and built environment. They include measures of ests and biodiversity, threatened species, water environmental goods (forest, water, cultivatable resources, energy use and efficiency, electricity land) and of degradation (pollution, deforesta- production and use, greenhouse gas emissions, tion, loss of habitat, and loss of biodiversity). urbanization, traffic and congestion, air pollution, These indicators show that growing populations government commitments, and natural resource and expanding economies have placed greater rents. demands on land, water, forests, minerals, and Where possible, the indicators come from energy sources. But new technologies, increas- international sources and are standardized to ing productivity, and better policies can ensure facilitate comparison across countries. But eco- that future development is environmentally and systems span national boundaries, and access socially sustainable. to natural resources may vary within countries. Nowhere are these risks and opportunities For example, water may be abundant in some more intertwined than in the global effort to miti- parts of a country but scarce in others, and gate the effects of climate change. A continuing countries often share water resources. Land pro- rise in temperature, accompanied by changes ductivity and optimal land use may be location in precipitation patterns, is projected for this specific, but widely separated regions can have century, as are more frequent, severe, and pro- common characteristics. Greenhouse gas emis- longed climate-related events such as floods sions and climate change are measured globally, and droughts—posing risks for agriculture, food but their effects are experienced locally, shaping production, and water supplies. Poor countries people’s lives and opportunities. Measuring envi- and the poorest people in all countries are most ronmental phenomena and their effects at the vulnerable to the changing climate. subnational, national, and supranational levels The 2012 edition of World Development remains a major challenge for achieving long- Indicators included two new tables on climate term, sustainable development. Economy States and markets Global links Back World Development Indicators 2013 51 Highlights East Asia & Pacific: More access to improved sanitation facilities Share of population with access to improved sanitation facilities (%) East Asia and Pacific has more than doubled the proportion of people Samoa with access to improved sanitation facilities. This is an impressive 100 achievement, bringing access to basic sanitation facilities to more Tonga than 700 million additional people, mostly in China. Because of its 80 size, China dominates the regional average of East Asia and Pacific. Palau East Asia & Paci c But some countries progressed even faster than China, such as 60 China Palau, with 100 percent access in 2010. At the other end of the Papua New Guinea spectrum is Cambodia, where only 31 percent of the population has 40 access. Timor-Leste 20 Cambodia 0 1990 1995 2000 2005 2010 Source: Table 3. Europe & Central Asia: Emissions fall but per capita carbon dioxide emissions remain high Carbon dioxide emissions (metric tons per capita) Carbon dioxide emissions, largely a byproduct of energy production  and use, account for the largest portion of greenhouse gases released 30 each year. Greenhouse gases—including carbon dioxide, methane, nitrous oxide, and other industrial gases (hydrofluorocarbons, perfluo- 20 rocarbons, and sulfur hexafluoride)—are associated with global warm- ing and environmental damage. In 2009 the world released an esti- mated 32 billion metric tons of carbon dioxide, up 44 percent from 10 1990. In Europe and Central Asia carbon dioxide emissions fell 25 per- cent over the same period, but emissions per capita remain the highest 1990 2009 0 among developing regions. Emissions of other greenhouse gases have ia a s n ia n ic s nd d ay rg nd nd sta tio lan l ton ou e & Norw also risen over the last two decades. In 2010 global emissions were ub As nla sla rla a kh Fin mb ep Es r al ee de the eI za ntr hR xe Gr Fe Ka ero Ne Ce Lu estimated at 7.5 billion metric tons of carbon dioxide equivalent for ec ian Fa Cz ss Ru rop methane, 2.9 billion for nitrous dioxide, and 1.0 billion for other indus- Eu a. Includes countries at all income levels. trial gases. Source: Online table 3.8. Latin America & Caribbean: The leader in clean and efficient energy Energy use, 2010 (%) Latin America and the Caribbean remains one of the world’s most efficient  energy-using regions, measured by the ratio of gross domestic product 100 to energy use. Latin American countries averaged $7.70 of output per kilogram of oil-equivalent energy used in 2010 (in 2005 purchasing 75 power parity dollars), up 12 percent from 1990. Peru, Colombia, Pan- ama, Costa Rica, and Uruguay were the region’s most efficient energy 50 users. Clean energy from noncarbon energy sources, which consists of alternative energy (geothermal, solar, and hydropower) and nuclear energy, is also on the rise, accounting for 9.2 percent of world energy 25 use in 2010, but 10.4 percent in Latin America and the Caribbean, high- Alternative and nuclear energy Combustible renewables and waste est among developing regions. The increase in carbon dioxide emissions Fossil fuel 0 slowed, but the region’s emissions still rose more than 57 percent Latin Europe East Asia South Sub-Saharan Middle East America & & Central & Paci c Asia Africa & North between 1990 and 2009. Mexico, Brazil, República Bolivariana de Vene- Caribbean Asia Africa zuela, Argentina, and Colombia were the largest emitters. Source: Online tables 3.6 and 3.8. 52  World Development Indicators 2013 Front ? User guide World view People Environment Middle East & North Africa: The most water-stressed region The world has about 42 trillion cubic meters of available freshwater, Renewable internal freshwater resources, 2011 (%) but distribution is drastically uneven. The Middle East and North South Asia 5% Middle East & North Africa 0.5% Africa is the most water-stressed region, with less than 1 percent of global renewable freshwater resources. At 226 billion cubic meters, Sub- the region has only 673 cubic meters of water per person, the lowest Saharan Africa among developing regions. By contrast, Latin America and the Carib- 9% Latin America bean, with 32 percent of world resources, has 22,810 cubic meters per Europe & & Caribbean Central Asia 32% person; Europe and Central Asia, with 12 percent, has 12,516 cubic 12% meters per person; and East Asia and Pacific, with 21 percent, has 4,446 cubic meters per person. East Asia & Paci c 21% High income 21% Source: Online table 3.5. South Asia: Some of the world’s most polluted cities South Asia has some of the most polluted air in the world, as Particulates of less than 10 microns in diameter, 2010 measured by the concentration of fine suspended particulates of (micrograms per cubic meter) Nyala, Sudan fewer than 10 microns in diameter (PM10), capable of penetrating Maroua, Cameroon deep into the respiratory tract and causing severe health damage. Dhaka, Bangladesh The PM10 estimates measure the annual exposure of the average Muzaffarpur, India urban resident to outdoor particulate matter. Globally, air pollution Hyderabad, Pakistan Saint-Louis, Senegal has fallen from 78 micrograms per cubic meter to 41 over the last Ségou, Mali two decades. Among developing regions the highest concentrations Xi’an, China are in South Asia (62) and the Middle East and North Africa (59). Montevideo, Uruguay Bamako, Mali City-level PM10 concentration data, however, indicate that Sub-­ Niamey, Niger Saharan Africa has the most cities with high levels of pollution Osh, Kyrgyz Republic among developing regions. Even so, the PM10 concentration has Shubra-El-Khema, Egypt N’djamena, Chad S aharan Africa, falling 65 percent over dropped significantly in Sub-­ 0 50 100 150 200 1990–2010. Source: Online tables 3.13 and 3.14. Saharan Africa: Use of biomass energy for cooking and heating increases health risks Sub-­ Combustible renewables and waste, 2010 (% of energy use) Many poor people depend on biomass energy from plant materials or 100 animal waste for cooking and heating. Millions of deaths are caused by indoor air pollution each year, due largely to indoor particulate pol- 75 lution. Many are children, who die of acute respiratory infections from burning fuel wood, crop residues, or animal dung (WHO 2004). These sources of energy account for 66 percent of total energy used by more 50 Saharan than 800 million low-income inhabitants of the world. In Sub-­ Africa use of combustible renewables and waste, which account for 25 more than half of total energy use, has risen almost 3 percent over the last two decades. For this region, where an estimated 67 percent 0 of the population lacks access to any form of electrical services, use p. ia Mo Togo ia ria e ia Cô trea ire ya a rld iqu ric an Re iop mb en vo ge Wo Af Eri nz mb K d’I Ni Eth m. Za ran Ta of biomass and coal—the primary cooking and heating fuel—is still De za te ha o, Sa ng b- on the rise. Co Su Source: Online tables 1.1 and 3.6. Economy States and markets Global links Back World Development Indicators 2013 53 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 average weighted PM10 Per capita billion average % of total Per capita % of total % of total annual micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2010 2011 2010 2010 1990–2011 2010 2009 2010 2010 Afghanistan 0.00 0.4 1,335 50 37 4.0 30 6.3 .. .. Albania –0.10 8.4 8,364 95 94 2.4 38 3.0 648 7.6 Algeria 0.57 6.2 313 83 95 2.6 69 121.3 1,138 45.6 American Samoa 0.19 16.7 .. .. .. 1.9 .. .. .. .. Andorra 0.00 6.1 3,663 100 100 0.9 18 0.5 .. .. Angola 0.21 12.1 7,544 51 58 4.1 58 26.7 716 5.3 Antigua and Barbuda 0.20 1.0 580 .. .. 1.0 13 0.5 .. .. Argentina 0.81 5.3 6,771 .. .. 1.0 57 174.7 1,847 125.3 Armenia 1.48 8.0 2,212 98 90 0.3 45 4.5 791 6.5 Aruba 0.00 0.0 .. 100 .. 0.8 .. 2.3 .. .. Australia 0.37 12.5 22,039 100 100 1.3 13 400.2 5,653 241.5 Austria –0.13 22.9 6,529 100 100 0.7 27 62.3 4,034 67.9 Azerbaijan 0.00 7.1 885 80 82 1.8 27 49.1 1,307 18.7 Bahamas, The 0.00 1.0 58 .. 100 1.5 .. 2.6 .. .. Bahrain –3.55 0.7 3 .. .. 4.9 44 24.2 7,754 13.2 Bangladesh 0.18 1.6 698 81 56 3.0 115 51.0 209 42.3 Barbados 0.00 0.1 292 100 100 1.4 35 1.6 .. .. Belarus –0.43 7.2 3,927 100 93 0.4 6 60.3 2,922 34.9 Belgium –0.16 13.2 1,089 100 100 1.2 21 103.6 5,586 93.8 Belize 0.67 20.6 44,868 98 90 3.0 12 0.4 .. .. Benin 1.04 23.3 1,132 75 13 4.2 48 4.9 413 0.2 Bermuda 0.00 5.1 .. .. .. 0.7 .. 0.5 .. .. Bhutan –0.34 28.3 105,653 96 44 3.9 20 0.4 .. .. Bolivia 0.50 18.5 30,085 88 27 2.2 57 14.5 737 6.9 Bosnia and Herzegovina 0.00 0.6 9,461 99 95 0.9 21 30.1 1,703 17.1 Botswana 0.99 30.9 1,182 96 62 2.2 64 4.4 1,128 0.5 Brazil 0.50 26.0 27,551 98 79 1.2 18 367.1 1,363 515.7 Brunei Darussalam 0.44 29.6 20,939 .. .. 2.2 44 9.3 8,308 3.9 Bulgaria –1.53 8.9 2,858 100 100 –1.7 40 42.8 2,370 46.0 Burkina Faso 1.01 14.2 737 79 17 6.2 65 1.7 .. .. Burundi 1.40 4.8 1,173 72 46 4.9 24 0.2 .. .. Cambodia 1.34 23.4 8,431 64 31 2.1 42 4.6 355 1.0 Cameroon 1.05 9.0 13,629 77 49 3.3 59 6.7 363 5.9 Canada 0.00 6.2 82,647 100 100 1.2 15 513.9 7,380 607.8 Cape Verde –0.36 0.2 599 88 61 2.1 .. 0.3 .. .. Cayman Islands 0.00 1.5 .. 96 96 0.9 .. 0.5 .. .. Central African Republic 0.13 17.7 31,425 67 34 2.6 35 0.2 .. .. Chad 0.66 9.4 1,301 51 13 3.0 83 0.4 .. .. Channel Islands .. 0.5 .. .. .. 0.8 .. .. .. .. Chile –0.25 13.3 51,188 96 96 1.1 46 66.7 1,807 60.4 China –1.57 16.0 2,093 91 64 3.0 59 7,687.1 1,807 4,208.3 Hong Kong SAR, China .. 41.8 .. .. .. 0.1 .. 37.0 1,951 38.3 Macao SAR, China .. .. .. .. .. 2.2 .. 1.5 .. .. Colombia 0.17 20.5 45,006 92 77 1.7 19 71.2 696 56.8 Comoros 9.34 .. 1,592 95 36 2.9 30 0.1 .. .. Congo, Dem. Rep. 0.20 10.0 13,283 45 24 4.3 35 2.7 360 7.9 Congo, Rep. 0.07 9.7 53,626 71 18 3.0 57 1.9 363 0.6 54  World Development Indicators 2013 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 average weighted PM10 Per capita billion average % of total Per capita % of total % of total annual micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2010 2011 2010 2010 1990–2011 2010 2009 2010 2010 Costa Rica –0.93 17.6 23,780 97 95 2.2 27 8.3 998 9.6 Côte d’Ivoire –0.15 21.8 3,813 80 24 3.5 30 6.6 485 6.0 Croatia –0.19 9.5 8,562 99 99 0.2 22 21.5 1,932 14.0 Cuba –1.66 5.3 3,387 94 91 –0.1 15 31.6 975 17.4 Curaçao .. .. .. .. .. .. .. .. .. .. Cyprus –0.09 4.5 699 100 100 1.4 27 8.2 2,215 5.4 Czech Republic –0.08 15.1 1,253 100 98 –0.3 16 108.1 4,193 85.3 Denmark –1.14 4.1 1,077 100 100 0.6 15 45.7 3,470 38.8 Djibouti 0.00 0.0 331 88 50 2.0 28 0.5 .. .. Dominica 0.58 3.7 .. .. .. 0.1 20 0.1 .. .. Dominican Republic 0.00 24.1 2,088 86 83 2.1 14 20.3 840 15.9 Ecuador 1.81 38.0 29,456 94 92 2.2 19 30.1 836 17.7 Egypt, Arab Rep. –1.73 6.1 22 99 95 2.1 78 216.1 903 146.8 El Salvador 1.45 1.4 2,850 88 87 1.3 28 6.3 677 6.0 Equatorial Guinea 0.69 14.0 36,100 .. .. 3.2 6 4.8 .. .. Eritrea 0.28 3.8 517 61 14 5.2 61 0.5 142 0.3 Estonia 0.12 22.6 9,486 98 95 0.1 9 16.0 4,155 13.0 Ethiopia 1.08 18.4 1,440 44 21 3.7 47 7.9 400 5.0 Faeroe Islands 0.00 .. .. .. .. 0.8 11 0.7 .. .. Fiji –0.34 0.2 32,876 98 83 1.7 20 0.8 .. .. Finland 0.14 8.5 19,858 100 100 0.6 15 53.6 6,787 80.7 France –0.39 17.1 3,057 100 100 1.2 12 363.4 4,031 564.3 French Polynesia –3.97 0.1 .. 100 98 1.1 .. 0.9 .. .. Gabon 0.00 14.6 106,892 87 33 2.3 7 1.6 1,418 1.8 Gambia, The –0.41 1.3 1,689 89 68 3.7 60 0.4 .. .. Georgia 0.09 3.4 12,958 98 95 1.0 49 5.8 700 10.1 Germany 0.00 42.3 1,308 100 100 0.2 16 734.6 4,003 622.1 Ghana 2.08 14.0 1,214 86 14 3.6 22 7.4 382 8.4 Greece –0.81 9.9 5,133 100 98 0.3 27 94.9 2,440 57.4 Greenland 0.00 40.1 .. 100 100 0.2 .. 0.6 .. .. Grenada 0.00 0.1 .. .. 97 1.3 19 0.2 .. .. Guam 0.00 3.6 .. 100 99 1.3 .. .. .. .. Guatemala 1.40 29.5 7,400 92 78 3.4 51 15.2 713 8.8 Guinea 0.54 6.4 22,110 74 18 3.8 55 1.2 .. .. Guinea-Bissau 0.48 26.9 10,342 64 20 3.6 48 0.3 .. .. Guyana 0.00 4.8 318,766 94 84 0.5 20 1.6 .. .. Haiti 0.76 0.1 1,285 69 17 3.8 35 2.3 229 0.6 Honduras 2.06 13.9 12,371 87 77 3.1 34 7.7 601 6.7 Hungary –0.62 5.1 602 100 100 0.4 15 48.7 2,567 37.4 Iceland –4.99 13.2 532,892 100 100 0.4 18 2.0 16,882 17.1 India –0.46 4.8 1,165 92 34 2.5 52 1,979.4 566 959.9 Indonesia 0.51 6.4 8,332 82 54 2.5 60 451.8 867 169.8 Iran, Islamic Rep. 0.00 6.9 1,718 96 100 1.3 56 602.1 2,817 233.0 Iraq –0.09 0.1 1,068 79 73 2.8 88 109.0 1,180 50.2 Ireland –1.53 1.2 10,707 100 99 2.7 13 41.6 3,218 28.4 Isle of Man 0.00 .. .. .. .. 0.5 .. .. .. .. Israel –0.07 15.1 97 100 100 1.9 21 67.2 3,005 58.6 Economy States and markets Global links Back World Development Indicators 2013 55 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 average weighted PM10 Per capita billion average % of total Per capita % of total % of total annual micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2010 2011 2010 2010 1990–2011 2010 2009 2010 2010 Italy –0.90 15.9 3,005 100 .. 0.7 21 400.8 2,815 298.8 Jamaica 0.11 7.3 3,475 93 80 0.4 27 8.6 1,131 4.2 Japan –0.05 10.9 3,364 100 100 0.9 24 1,101.1 3,898 1,110.8 Jordan 0.00 1.9 110 97 98 2.5 30 22.5 1,191 14.8 Kazakhstan 0.17 2.5 3,886 95 97 1.3 18 225.8 4,595 82.6 Kenya 0.33 11.7 497 59 32 4.4 30 12.4 483 7.5 Kiribati 0.00 22.6 .. .. .. 1.8 .. 0.1 .. .. Korea, Dem. Rep. 2.00 3.9 2,740 98 80 0.6 52 75.1 761 21.7 Korea, Rep. 0.11 3.0 1,303 98 100 1.1 30 509.4 5,060 496.7 Kosovo .. .. .. .. .. .. .. .. 1,372 5.2 Kuwait –2.57 1.1 0 99 100 2.9 91 80.2 12,204 57.0 Kyrgyz Republic –1.07 6.9 8,873 90 93 1.5 35 6.7 536 11.4 Lao PDR 0.49 16.6 30,280 67 63 4.7 45 1.8 .. .. Latvia –0.34 16.4 8,133 99 78 –8.4 12 6.7 1,971 6.6 Lebanon –0.45 0.4 1,127 100 .. 0.9 25 21.0 1,526 15.7 Lesotho –0.47 0.5 2,384 78 26 3.7 38 .. .. .. Liberia 0.67 1.6 48,443 73 18 4.1 31 0.5 .. .. Libya 0.00 0.1 109 .. 97 1.3 65 62.9 3,013 31.6 Liechtenstein 0.00 42.4 .. .. .. 0.5 24 .. .. .. Lithuania –0.68 14.4 5,135 92 86 –8.0 16 12.8 2,107 5.0 Luxembourg 0.00 20.0 1,930 100 100 2.5 12 10.1 8,343 3.2 Macedonia, FYR –0.41 4.9 2,616 100 88 0.4 17 11.3 1,402 7.3 Madagascar 0.45 2.5 15,810 46 15 4.8 28 1.8 .. .. Malawi 0.97 15.0 1,049 83 51 4.1 29 1.1 .. .. Malaysia 0.54 13.7 20,098 100 96 2.5 18 198.3 2,558 125.3 Maldives 0.00 .. 94 98 97 4.1 28 1.0 .. .. Mali 0.61 2.4 3,788 64 22 4.9 111 0.6 .. .. Malta 0.00 1.7 121 100 100 0.1 .. 2.5 2,013 2.1 Marshall Islands 0.00 0.6 .. 94 75 1.9 .. 0.1 .. .. Mauritania 2.66 1.1 113 50 26 3.0 68 2.1 .. .. Mauritius 1.00 0.7 2,139 99 89 0.4 16 3.8 .. .. Mexico 0.30 11.9 3,563 96 85 1.6 30 446.2 1,570 271.0 Micronesia, Fed. Sts. –0.04 0.1 .. .. .. 0.9 .. 0.1 .. .. Moldova –1.77 1.4 281 96 85 1.4 36 4.5 731 3.6 Monaco 0.00 98.1 .. 100 100 0.1 .. .. .. .. Mongolia 0.73 13.4 12,428 82 51 2.9 96 14.5 1,189 4.5 Montenegro 0.00 11.5 .. 98 90 0.4 .. 3.1 1,303 4.2 Morocco –0.23 1.5 899 83 70 1.6 23 48.8 517 22.3 Mozambique 0.54 14.8 4,191 47 18 3.1 22 2.6 436 16.7 Myanmar 0.93 5.2 20,750 83 76 2.5 40 11.1 292 7.5 Namibia 0.97 14.7 2,651 93 32 3.3 42 3.6 702 1.5 Nepal 0.70 17.0 6,501 89 31 3.8 27 3.5 341 3.2 Netherlands –0.14 15.2 659 100 100 0.9 30 169.7 5,021 118.1 New Caledonia 0.00 23.9 .. .. .. 1.4 48 3.0 .. .. New Zealand –0.01 20.0 74,230 100 .. 0.9 11 32.1 4,166 44.8 Nicaragua 2.01 36.8 32,318 85 52 1.9 21 4.5 542 3.7 Niger 0.98 7.1 218 49 9 5.0 96 1.2 .. .. 56  World Development Indicators 2013 Front ? User guide view People 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 average weighted PM10 Per capita billion average % of total Per capita % of total % of total annual micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2010 2011 2010 2010 1990–2011 2010 2009 2010 2010 Nigeria 3.67 12.6 1,360 58 31 3.8 38 70.2 714 26.1 Northern Mariana Islands 0.53 28.4 .. 98 .. 0.5 .. .. .. .. Norway –0.80 10.9 77,124 100 100 1.6 16 47.1 6,637 124.1 Oman 0.00 9.3 492 89 99 2.6 95 41.1 7,188 19.8 Pakistan 2.24 9.8 311 92 48 2.7 91 161.2 487 94.5 Palau –0.18 4.8 .. 85 100 1.6 .. 0.2 .. .. Panama 0.36 11.5 41,275 93 69 2.3 45 7.8 1,073 7.5 Papua New Guinea 0.48 1.4 114,203 40 45 2.8 16 3.5 .. .. Paraguay 0.97 5.4 14,311 86 71 2.6 64 4.5 742 54.1 Peru 0.18 13.1 54,966 85 71 1.5 42 47.4 667 35.9 Philippines –0.75 5.0 5,050 92 74 2.2 17 68.6 434 67.7 Poland –0.31 21.8 1,391 .. 90 0.8 33 298.9 2,657 157.1 Portugal –0.11 6.1 3,600 99 100 0.1 18 57.4 2,213 53.7 Puerto Rico –1.76 4.4 1,915 .. .. –0.3 15 .. .. .. Qatar 0.00 1.4 30 100 100 6.3 20 70.3 12,799 28.1 Romania –0.32 7.8 1,978 89 73 –0.2 11 79.5 1,632 60.3 Russian Federation 0.00 9.2 30,169 97 70 0.6 15 1,574.4 4,927 1,036.1 Rwanda –2.38 10.0 868 65 55 4.6 21 0.7 .. .. Samoa 0.00 1.2 .. 96 98 –0.5 .. 0.2 .. .. San Marino 0.00 .. .. .. .. 0.7 8 .. .. .. São Tomé and Príncipe 0.00 .. 12,936 89 26 2.9 28 0.1 .. .. Saudi Arabia 0.00 29.9 85 .. .. 2.5 96 432.8 6,168 240.1 Senegal 0.49 23.5 2,021 72 52 3.4 77 4.6 272 3.0 Serbia –0.99 6.0 1,158 99 92 0.2 .. 46.3 2,141 37.4 Seychelles 0.00 0.9 .. .. .. 0.1 .. 0.7 .. .. Sierra Leone 0.69 4.3 26,678 55 13 3.2 39 1.4 .. .. Singapore 0.00 3.4 116 100 100 2.1 23 31.9 6,456 45.4 Sint Maarten .. .. .. .. .. .. .. .. .. .. Slovak Republic –0.06 23.2 2,334 100 100 –0.7 13 33.9 3,280 27.5 Slovenia –0.16 13.1 9,095 99 100 0.1 26 15.3 3,520 16.2 Solomon Islands 0.25 0.1 80,939 .. .. 4.8 31 0.2 .. .. Somalia 1.07 0.5 628 29 23 3.6 26 0.6 .. .. South Africa 0.00 6.9 886 91 79 1.9 18 499.0 2,738 256.6 South Sudan .. .. .. .. .. 4.7 .. .. .. .. Spain –0.68 7.6 2,408 100 100 0.4 24 288.2 2,773 299.9 Sri Lanka 1.12 15.0 2,530 91 92 1.6 65 12.7 478 10.8 St. Kitts and Nevis 0.00 0.8 452 99 96 1.5 15 0.3 .. .. St. Lucia –0.07 2.0 .. 96 65 –2.6 31 0.4 .. .. St. Martin 0.00 .. .. .. .. .. .. .. .. .. St. Vincent and Grenadines –0.27 1.2 .. .. .. 0.8 22 0.2 .. .. Sudan 0.08 4.2 672 58 26 2.6c 137 14.3 371 7.8 Suriname 0.01 12.2 166,220 92 83 1.5 20 2.5 .. .. Swaziland –0.84 3.0 2,472 71 57 1.0 30 1.0 .. .. Sweden –0.30 10.0 18,097 100 100 0.9 10 43.7 5,468 148.5 Switzerland –0.38 24.9 5,106 100 100 1.2 20 41.6 3,349 66.1 Syrian Arab Republic –1.29 0.6 343 90 95 2.5 54 65.3 1,063 46.4 Tajikistan 0.00 4.1 9,096 64 94 1.6 29 2.8 336 16.4 Economy States and markets Global links Back World Development Indicators 2013 57 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 average weighted PM10 Per capita billion average % of total Per capita % of total % of total annual micrograms per million kilograms of kilowatt annual % territorial area cubic meters population population % growth cubic meter metric tons oil equivalent hours 2000–10 2010 2011 2010 2010 1990–2011 2010 2009 2010 2010 Tanzania 1.13 26.9 1,817 53 10 4.8 19 7.0 448 4.4 Thailand 0.02 17.3 3,229 96 96 1.7 53 271.7 1,699 159.5 Timor-Leste 1.40 6.4 6,986 69 47 4.2 .. 0.2 .. .. Togo 5.13 11.0 1,868 61 13 3.4 27 1.5 446 0.1 Tonga 0.00 9.4 .. 100 96 0.9 .. 0.2 .. .. Trinidad and Tobago 0.32 9.6 2,852 94 92 2.3 97 47.8 15,913 8.5 Tunisia –1.86 1.3 393 94 85 1.5 23 25.2 913 16.1 Turkey –1.11 1.9 3,083 100 90 2.5 35 277.8 1,445 211.2 Turkmenistan 0.00 3.0 275 .. 98 1.9 36 48.2 4,226 16.7 Turks and Caicos Islands 0.00 3.5 .. 100 .. 2.6 .. 0.2 .. .. Tuvalu 0.00 0.2 .. 98 85 1.0 .. .. .. .. Uganda 2.56 10.3 1,130 72 34 5.9 10 3.5 .. .. Ukraine –0.21 3.6 1,162 98 94 –0.1 15 272.2 2,845 188.6 United Arab Emirates –0.24 4.7 19 100 98 5.3 89 156.8 8,271 97.7 United Kingdom –0.31 18.1 2,311 100 100 0.9 13 474.6 3,252 378.0 United States –0.13 13.7 9,044 99 100 1.0 18 5,299.6 7,164 4,354.4 Uruguay –2.14 0.3 17,515 100 100 0.5 112 7.9 1,241 10.8 Uzbekistan –0.20 2.3 557 87 100 2.8 31 116.5 1,533 51.7 Vanuatu 0.00 0.5 .. 90 57 3.7 14 0.1 .. .. Venezuela, RB 0.60 50.2 24,674 .. .. 1.7 10 184.8 2,669 118.3 Vietnam –1.65 4.6 4,092 95 76 3.1 54 142.3 681 94.9 Virgin Islands (U.S.) 0.80 1.5 .. .. .. 0.1 .. .. .. .. West Bank and Gaza –0.10 0.6 207 85 92 3.3 .. 2.2 .. .. Yemen, Rep. 0.00 0.7 85 55 53 4.9 34 24.0 298 7.8 Zambia 0.33 36.0 5,952 61 48 5.3 27 2.0 628 11.3 Zimbabwe 1.88 28.0 961 80 40 2.7 34 8.9 764 8.1 World 0.11 w 11.9 w 6,115 s 88 w 63 w 2.1 w 41 w 32,042.2d w 1,851 w 21,448.9 w Low income 0.61 10.0 5,125 65 37 3.6 54 229.8 363 197.4 Middle income 0.08 12.0 5,819 90 59 2.3 46 17,344.8 1,310 10,122.1 Lower middle income 0.31 8.8 3,121 87 47 2.6 53 3,884.9 667 2,138.2 Upper middle income 0.02 13.1 8,550 93 73 2.1 42 13,460.8 1,948 7,981.7 Low & middle income 0.15 11.6 5,722 86 56 2.4 47 17,574.2 1,210 10,344.7 East Asia & Pacific –0.44 13.3 4,446 90 66 2.9 55 8,936.9 1,520 4,888.8 Europe & Central Asia –0.04 7.7 12,498 96 84 0.9 21 2,863.0 3,015 1,884.3 Latin America & Carib. 0.45 19.8 22,810 94 79 1.5 28 1,533.7 1,312 1,356.4 Middle East & N. Africa –0.15 4.0 673 89 88 2.1 59 1,320.9 1,372 638.4 South Asia –0.29 5.6 1,197 90 38 2.7 62 2,215.6 519 1,120.1 Sub-­Saharan Africa 0.48 11.6 4,455 61 31 3.8 41 724.0 683 441.4 High income –0.04 12.7 8,195 100 100 1.0 22 12,727.0 5,000 11,163.7 Euro area –0.31 16.5 2,933 100 100 0.6 18 2,456.1 3,633 2,352.4 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. 58  World Development Indicators 2013 Front ? User guide view People World view People Environment Environment 3 About the data Environmental resources are needed to promote growth and poverty collected intermittently and may hide substantial year-to-year varia- reduction, but growth can create new stresses on the environment. tions in total renewable water resources. Data do not distinguish Deforestation, loss of biologically diverse habitat, depletion of water between seasonal and geographic variations in water availability resources, pollution, urbanization, and ever increasing demand for within countries. Data for small countries and countries in arid and energy production are some of the factors that must be considered semiarid zones are less reliable than data for larger countries and in shaping development strategies. countries with greater rainfall. Loss of forests Water and sanitation Forests provide habitat for many species and act as carbon sinks. A reliable supply of safe drinking water and sanitary disposal of If properly managed they also provide a livelihood for people who excreta are two of the most important means of improving human manage and use forest resources. FAO (2010) uses a uniform defi- health and protecting the environment. Improved sanitation facilities nition of forest to provide information on forest cover in 2010 and prevent human, animal, and insect contact with excreta. adjusted estimates of forest cover in 1990 and 2000. Data pre- Data on access to an improved water source measure the percent- sented here do not distinguish natural forests from plantations, a age of the population with ready access to water for domestic pur- breakdown the FAO provides only for developing countries. Thus, poses, based on surveys and estimates of service users provided data may underestimate the rate at which natural forest is disap- by governments to the Joint Monitoring Programme of the World pearing 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 extent of coverage, and many underreport the number or extent of health. More than half the world’s people rely on dung, wood, crop protected areas. waste, or coal to meet basic energy needs. Cooking and heating with these fuels on open fires or stoves without chimneys lead to indoor Freshwater resources air pollution, which is responsible for 1.6 million deaths a year—one The data on freshwater resources are derived from estimates of every 20 seconds. In many urban areas air pollution exposure is the runoff into rivers and recharge of groundwater. These estimates main environmental threat to health. Long-term exposure to high are derived from different sources and refer to different years, so levels of soot and small particles contributes to such health effects cross-country comparisons should be made with caution. Data are as respiratory diseases, lung cancer, and heart disease. Particulate Economy States and markets Global links Back World Development Indicators 2013 59 3 Environment pollution, alone or with sulfur dioxide, creates an enormous burden urban areas—but also reflects climatic, geographic, and economic of ill health. factors. Energy use has been growing rapidly in low- and middle- Data on particulate matter are estimated average annual concen- income economies, but high-income economies still use almost five trations in residential areas away from air pollution “hotspots,� such times as much energy per capita. as industrial districts and transport corridors. Data are estimates Total energy use refers to the use of primary energy before trans- of annual ambient concentrations of particulate matter in cities of formation to other end-use fuels (such as electricity and refined more than 100,000 people by the World Bank’s Agriculture and petroleum products). It includes energy from combustible renew- Environmental Services Department. ables and waste—solid biomass and animal products, gas and Pollutant concentrations are sensitive to local conditions, and liquid from biomass, and industrial and municipal waste. Biomass even monitoring sites in the same city may register different levels. is any plant matter used directly as fuel or converted into fuel, Thus these data should be considered only a general indication of heat, or electricity. Data for combustible renewables and waste air quality, and comparisons should be made with caution. They are often based on small surveys or other incomplete informa- allow for cross-country comparisons of the relative risk of particulate tion and thus give only a broad impression of developments and matter pollution facing urban residents. Major sources of urban are not strictly comparable across countries. The IEA reports outdoor particulate matter pollution are traffic and industrial emis- include country notes that explain some of these differences (see sions, but nonanthropogenic sources such as dust storms may also Data sources). All forms of energy—primary energy and primary be a substantial contributor for some cities. Country technology and electricity—are converted into oil equivalents. A notional thermal ­ pollution controls are important determinants of particulate matter. efficiency of 33 percent is assumed for converting nuclear electric- Current WHO air quality guidelines are annual mean concentrations ity into oil equivalents and 100 percent efficiency for converting of 20 micrograms per cubic meter for particulate matter less than hydroelectric power. 10 microns in diameter. Electricity production Carbon dioxide emissions Use of energy is important in improving people’s standard of liv- Carbon dioxide emissions are the primary source of greenhouse ing. But electricity generation also can damage the environment. gases, which contribute to global warming, threatening human and Whether such damage occurs depends largely on how electricity natural habitats. Fossil fuel combustion and cement manufacturing is generated. For example, burning coal releases twice as much are the primary sources of anthropogenic carbon dioxide emissions, carbon dioxide—a major contributor to global warming—as does which the U.S. Department of Energy’s Carbon Dioxide Information burning an equivalent amount of natural gas. Nuclear energy does Analysis Center (CDIAC) calculates using data from the United not generate carbon dioxide emissions, but it produces other dan- Nations Statistics Division’s World Energy Data Set and the U.S. gerous waste products. Bureau of Mines’s Cement Manufacturing Data Set. Carbon dioxide The International Energy Agency (IEA) compiles data and data emissions, often calculated and reported as elemental carbon, were on energy inputs used to generate electricity. Data for countries converted to actual carbon dioxide mass by multiplying them by that are not members of the Organisation for Economic Co-opera- 3.667 (the ratio of the mass of carbon to that of carbon dioxide). tion and Development (OECD) are based on national energy data Although estimates of global carbon dioxide emissions are probably adjusted to conform to annual questionnaires completed by OECD accurate within 10 percent (as calculated from global average fuel member governments. In addition, estimates are sometimes made chemistry and use), country estimates may have larger error bounds. to complete major aggregates from which key data are missing, Trends estimated from a consistent time series tend to be more and adjustments are made to compensate for differences in defini- accurate than individual values. Each year the CDIAC recalculates tions. The IEA makes these estimates in consultation with national the entire time series since 1949, incorporating recent findings and statistical offices, oil companies, electric utilities, and national corrections. Estimates exclude fuels supplied to ships and aircraft energy experts. It occasionally revises its time series to reflect in international transport because of the difficulty of apportioning political changes. For example, the IEA has constructed historical the fuels among benefiting countries. energy statistics for countries of the former Soviet Union. In addi- tion, energy statistics for other countries have undergone continu- Energy use ous changes in coverage or methodology in recent years as more In developing economies growth in energy use is closely related to detailed energy accounts have become available. Breaks in series growth in the modern sectors—industry, motorized transport, and are therefore unavoidable. 60  World Development Indicators 2013 Front ? User guide view People World view People Environment Environment 3 Definitions addition to hydropower, coal, oil, gas, and nuclear power generation, • Deforestation is the permanent conversion of natural forest area it covers generation by geothermal, solar, wind, and tide and wave to other uses, including agriculture, ranching, settlements, and energy as well as that from combustible renewables and waste. Pro- infrastructure. Deforested areas do not include areas logged but duction includes the output of electric plants designed to produce intended for regeneration or areas degraded by fuelwood gathering, electricity only, as well as that of combined heat and power plants. acid precipitation, or forest fires. • Nationally protected areas are terrestrial and marine protected areas as a percentage of total ter- Data sources ritorial area and include all nationally designated protected areas Data on deforestation are from FAO (2010) and the FAO’s data with known location and extent. All overlaps between different desig- website. Data on protected areas, derived from the UNEP and nations and categories, buffered points, and polygons are removed, WCMC online databases, are based on data from national authori- and all undated protected areas are dated. • Internal renewable ties, national legislation, and international agreements. Data on freshwater resources are the average annual flows of rivers and freshwater resources are from the FAO’s AQUASTAT database. Data groundwater from rainfall in the country. Natural incoming flows origi- on access to water and sanitation are from WHO and UNICEF (2012). nating outside a country’s borders and overlapping water resources Data on urban population are from the United Nations Population between surface runoff and groundwater recharge are excluded. Division (2011). Data on particulate matter concentrations are World • Access to an improved water source is the percentage of the Bank estimates. Data on carbon dioxide emissions are from the population with reasonable access to an adequate amount of water CDIAC. Data on energy use and electricity production are from IEA from an improved source, such as piped water into a dwelling, plot, electronic files and published in IEA’s annual publications, Energy or yard; public tap or standpipe; tubewell or borehole; protected dug Statistics of Non-OECD Countries, Energy Balances of Non-OECD well or spring; and rainwater collection. Unimproved sources include Countries, Energy Statistics of OECD Countries, and Energy Balances unprotected dug wells or springs, carts with small tank or drum, of OECD Countries. bottled water, and tanker trucks. Reasonable access is defined as the availability of at least 20 liters a person a day from a source References within 1 kilometer of the dwelling • Access to improved sanitation CDIAC (Carbon Dioxide Information Analysis Center). n.d. Online data- facilities is the percentage of the population with at least adequate base. http://cdiac.ornl.gov/home.html. Oak Ridge National Labora- access to excreta disposal facilities (private or shared, but not pub- tory, Environmental Science Division, Oak Ridge, TN. lic) that can effectively prevent human, animal, and insect contact FAO (Food and Agriculture Organization of the United Nations). 2010. with excreta (facilities do not have to include treatment to render Global Forest Resources Assessment 2010. Rome. sewage outflows innocuous). Improved facilities range from simple ———. n.d. AQUASTAT. Online database. www.fao.org/nr/water/ but protected pit latrines to flush toilets with a sewerage connection. aquastat/data/query/index.html. Rome. To be effective, facilities must be correctly constructed and properly IEA (International Energy Agency). Various years. Energy Balances of maintained. • Urban population is the midyear population of areas Non-OECD Countries. Paris. defined as urban in each country and reported to the United Nations ———.Various years. Energy Balances of OECD Countries. Paris. divided by the World Bank estimate of total population. • Particulate ———. Various years. Energy Statistics of Non-OECD Countries. Paris. matter concentration is fine suspended particulates of less than ———.Various years. Energy Statistics of OECD Countries. Paris. 10 microns in diameter (PM10) that are capable of penetrating deep UNEP (United Nations Environment Programme) and WCMC (World into the respiratory tract and causing severe health damage. Data Conservation Monitoring Centre). 2012. Online databases www are urban-population-weighted PM10 levels in residential areas of .unep-wcmc-apps.org/species/dbases/about.cfm. Nairobi. cities with more than 100,000 residents. • Carbon dioxide emis - United Nations Population Division. 2011. World Urbanization Pros- sions are emissions from the burning of fossil fuels and the manu- pects: The 2011 Revision. New York: United Nations, Department of facture of cement and include carbon dioxide produced during con- Economic and Social Affairs. sumption of solid, liquid, and gas fuels and gas flaring. • Energy use WHO (World Health Organization). 2004. Inheriting the World: The refers to the use of primary energy before transformation to other Atlas of Children’s Health and the Environment. www.who.int/ceh/ end use fuels, which equals indigenous production plus imports publications/atlas/en/index.html. Geneva. and stock changes, minus exports and fuels supplied to ships and WHO (World Health Organization) and UNICEF (United Nations Chil- aircraft engaged in international transport. • Electricity production dren’s Fund). 2012. Progress on Sanitation and Drinking Water. is measured at the terminals of all alternator sets in a station. In Geneva: WHO. Economy States and markets Global links Back World Development Indicators 2013 61 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, Average annual Annual freshwater withdrawals, cu. m ER.H2O.FWTL.K3 growth ..a,b Annual freshwater withdrawals, % of Carbon dioxide emissions, % change ..a,b internal resources ER.H2O.FWTL.ZS Methane emissions, Total EN.ATM.METH.KT.CE 62  World Development Indicators 2013 Front ? User guide view People World view People Environment Environment 3 Methane emissions, % change ..a,b Population in urban agglomerations of Methane emissions, From energy processes EN.ATM.METH.EG.ZS more than 1 million EN.URB.MCTY.TL.ZS Methane emissions, Agricultural EN.ATM.METH.AG.ZS Population in the largest city EN.URB.LCTY.UR.ZS Nitrous oxide emissions, Total EN.ATM.NOXE.KT.CE Access to improved sanitation facilities, % of urban population SH.STA.ACSN.UR Nitrous oxide emissions, % change ..a,b Access to improved sanitation facilities, Nitrous oxide emissions, Energy and industry EN.ATM.NOXE.EI.ZS % of rural population SH.STA.ACSN.RU Nitrous oxide emissions, Agriculture EN.ATM.NOXE.AG.ZS Other greenhouse gas emissions, Total EN.ATM.GHGO.KT.CE 3.13 Traffic and congestion Other greenhouse gas emissions, % change ..a,b Motor vehicles, Per 1,000 people IS.VEH.NVEH.P3 Motor vehicles, Per kilometer of road IS.VEH.ROAD.K1 3.10 Carbon dioxide emissions by sector Passenger cars IS.VEH.PCAR.P3 Electricity and heat production EN.CO2.ETOT.ZS Road density IS.ROD.DNST.K2 Manufacturing industries and construction EN.CO2.MANF.ZS Road sector energy consumption, % of total Residential buildings and commercial and consumption IS.ROD.ENGY.ZS public services EN.CO2.BLDG.ZS Road sector energy consumption, Per capita IS.ROD.ENGY.PC Transport EN.CO2.TRAN.ZS Diesel fuel consumption IS.ROD.DESL.PC Other sectors EN.CO2.OTHX.ZS Gasoline fuel consumption IS.ROD.SGAS.PC Pump price for super grade gasoline EP.PMP.SGAS.CD 3.11 Climate variability, exposure to impact, and resilience Pump price for diesel EP.PMP.DESL.CD Average daily minimum/maximum temperature ..b Urban-population-weighted particulate matter concentrations (PM10) EN.ATM.PM10.MC.M3 Projected annual temperature ..b Projected annual cool days/cold nights ..b 3.14 Air pollution Projected annual hot days/warm nights ..b This table provides air pollution data for Projected annual precipitation ..b major cities. ..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 5 meters or less EN.POP.EL5M.ZS product Population affected by droughts, floods, Total natural resources rents NY.GDP.TOTL.RT.ZS and extreme temperatures EN.CLC.MDAT.ZS Oil rents NY.GDP.PETR.RT.ZS Disaster risk reduction progress score EN.CLC.DRSK.XQ Natural gas rents NY.GDP.NGAS.RT.ZS Coal rents NY.GDP.COAL.RT.ZS 3.12 Urbanization Mineral rents NY.GDP.MINR.RT.ZS Urban population SP.URB.TOTL Forest rents NY.GDP.FRST.RT.ZS Urban population, % of total population SP.URB.TOTL.IN.ZS Urban population, Average annual growth SP.URB.GROW a. Derived from data elsewhere in the World Development Indicators database. b. Available online only as part of the table, not as an individual indicator. Economy States and markets Global links Back World Development Indicators 2013 63 ECONOMY 64  World Development Indicators 2013 Front ? User guide World view People Environment 4 The data in the Economy section provide a pic- the goods being present in the economy—has ture of the global economy and the economic been reclassified from services to goods, while activity of more than 200 countries and ter- manufacturing services performed on physical ritories that produce, trade, and consume inputs owned by others along with maintenance the world’s output. They include measures of and repair services were reclassified from goods macroeconomic performance and stability to services. In the capital account, reverse and broader measures of income and savings investment in direct investment has been adjusted for pollution, depreciation, and deple- reclassified to present assets and liabilities on tion of resources. a gross basis in the balance of payments and The world economy grew 2.3 percent in 2012, international investment position. No changes to reach $71 trillion, and the share from develop- were made to the balances on current account, ing economies grew to 34.3 percent. Growth is capital account, or financial account. Levels of expected to remain around 2.4 percent in 2013. reserves were not adjusted, nor were net errors Low- and middle-income economies, estimated and omissions. to have grown 5.1 percent in 2012, are projected For many economies changes to major aggre- to expand 5.5 percent in 2013. Growth in high- gates and balancing items will be limited. The income economies has been downgraded from change in the methodology for “goods for pro- earlier forecasts to 1.3  percent in 2012 and cessing� results in increases in imports and 2013. exports of services (equivalent to the amounts Beginning in August 2012, the International received or paid for manufacturing services) and Monetary Fund implemented the Balance of larger reductions in gross imports and exports of Payments Manual 6 (BPM6) framework in its goods (due to the elimination of imputed trans- major statistical publications. The World Bank actions in goods that do not change ownership), will implement BPM6 in its online databases though net goods and services trade may not be and publications in April 2013. Balance of pay- affected. The change in the recording of reverse ments data for 2005 onward will be presented investment in foreign direct investment will result in accord with the BPM6. The historical BPM5 in substantial increases in both international data series will end with data for 2008, which investment position assets and liabilities for can be accessed through the World Development many economies under BPM6, though net inter- Indicators archives. national investment position is not affected by The change to the BPM6 framework will affect this change. some components of the balance of payments. The complete balance of payments methodol- In the current account, “merchanting�—the pur- ogy can be accessed through the International chase of goods from a nonresident and the sub- Monetary Fund website (www.imf.org/external/ sequent resale to another nonresident without np/sta/bop/bop.htm). Economy States and markets Global links Back World Development Indicators 2013 65 Highlights East Asia & Pacific: Service sector has potential for more growth Value added in services as a share of GDP, 2010 (%) The service sector contributed substantially to gross domestic product  (GDP) growth in many East Asia and Pacific economies in recent years, 100 constituting nearly half of GDP and contributing 3.7 percentage points to an overall growth rate of 8.5 percent. Reflecting strong domestic 75 Larger than Fiji demand, continuing growth of services is consistent with long-term expected Kiribati Samoa trends of rising incomes in other regions. But despite recent growth, Tonga Philippines the service sector in many East Asia and Pacific economies is smaller 50 Mongolia Malaysia China Vietnam Smaller than expected based on average income. This reflects the relative Cambodia Thailand than Lao PDR Indonesia expected success of manufacturing among the countries in the region. It may 25 also be the result of limited adoption of high-value, modern services Papua New Guinea (information and communications technology, finance and professional business services). Few East Asia and Pacific countries besides the 0 500 5,000 50,000 Philippines have developed robust industries focused on exporting GDP per capita, 2010 (2005 PPP $, log scale) modern services (World Bank 2012a; Asian Development Bank 2012). Source: World Development Indicators database. Europe & Central Asia: Volatile food and energy prices pose a challenge Net energy exports or imports, 2010 (% of energy use) Europe and Central Asia is in general a net exporter of energy, but many  economies in the region depend heavily on energy imports and are Azerbaijan Turkmenistan thus vulnerable to sudden price changes. Azerbaijan, Kazakhstan, the Kazakhstan Net energy Russian Federation exporters Russian Federation, Turkmenistan, and Uzbekistan, the main export- Uzbekistan Montenegro Net energy ers, stand to benefit from rising world energy prices. But net energy Romania Albania importers imports account for 96 percent of energy use in Moldova, 84 percent Kosovo Bosnia & Herzegovina in Belarus, 69 percent in Turkey, 64 percent in Armenia, and 59 per- Serbia Poland cent in the Kyrgyz Republic. Most energy imports are oil, but Belarus, Tajikistan Bulgaria Ukraine Croatia, Poland, and Serbia are also large importers of electricity. Macedonia, FYR Croatia Some of these economies may face an acute deterioration of their Georgia Kyrgyz Rep. balance of payments positions if oil prices rise. And some are also Armenia Turkey vulnerable to rising food prices, triggered by the substitution of crop- Belarus Moldova based fuels for petroleum-based fuels. –500 –250 0 250 Source: Online table 3.9. Latin America & Caribbean: Tracking global uncertainties GDP growth (%)  GDP growth in Latin America and the Caribbean fell 1.7 percentage points from 2011 to 3.0 percent in 2012, the second largest drop 10 among developing country regions after Europe and Central Asia, where growth fell 2.8 percentage points. The region’s GDP growth decelerated Chile 5 due to slowing domestic demand and a weak external environment. The slowdown was particularly severe in Brazil, the region’s largest econ- Latin America omy, where global uncertainties and earlier fiscal, monetary, and credit & Caribbean Brazil 0 policy tightening to contain inflation risks had a large impact, especially on private investment. In Chile growth remained buoyant and continued Mexico to expand briskly, if slightly slower than in 2011. Growth in Central –5 America and the Caribbean slowed modestly, while growth in Mexico (the second largest economy in the region) rose slightly in 2012, to 4 –10 percent, benefiting from the fairly strong recovery in U.S. manufacturing 2007 2008 2009 2010 2011 2012 (De la Torre, Didier, and Pienknagura 2012; World Bank 2013). Source: Online table 4.1. 66  World Development Indicators 2013 Front ? User guide World view People Environment Middle East & North Africa: Recovery has been slow Macroeconomic fundamentals weakened in most Middle East and GDP growth (%) North Africa countries in 2011 and 2012, as growth slowed and 10 Lebanon governments responded to social pressures with expansionary fis- cal policies. High oil prices heightened current account and fiscal 5 Morocco deficits in oil importers, especially in places where governments subsidize energy use. Domestic pressures coupled with a challeng- Egypt, Arab Rep. 0 ing global environment and spillovers from regional events also Algeria Jordan weighed heavily on the economies of some oil importers such as Tunisia Jordan, Lebanon, and Morocco. Postrevolutionary economies such –5 as the Arab Republic of Egypt, Tunisia, and the Republic of Yemen Yemen, Rep. are recovering after the Arab Spring turmoil. However, recovery has –10 taken place in a weak global environment. The transition in these countries is far from complete, and uncertainty around the reform pro- –15 2007 2008 2009 2010 2011 2012 cess continues to constrain private investment (World Bank 2012b). Source: Online table 4.1. South Asia: Revenues are low and stagnating South Asian countries collect exceptionally low levels of tax revenue. Tax revenue (% of GDP) Revenue collection by central governments in the region averages 20 10–15 percent of GDP, compared with 20 percent in similar develop- ing economies and higher rates in more developed economies. In most South Asian countries the major source of revenue is the value added Sri Lanka 15 Nepal tax. Some are changing their tax structures—India is adopting a goods India Maldives and services tax, for example—but the main problem remains low Pakistan 10 collection rates for the value added tax and income tax. Most South Asian countries have outdated tax laws and inadequate institutional Bangladesh Bhutan arrangements unsuitable to the growing complexity of their economies. 5 South Asian countries all need to upgrade their infrastructure and improve social services such as education and health care, which will Afghanistan require a substantial increase in fiscal spending and better sources 0 2000 2002 2004 2006 2008 2010 2011 of revenue (World Bank 2012c). Source: Online table 5.6. Saharan Africa: Resilient growth in an uncertain global economic environment Sub-­ Despite a sluggish global economy, economic conditions in Sub-­ GDP growth (%) Saharan Africa held up well in 2011–12. Robust domestic demand, 25 high commodity prices, rising export volumes (due to new capacity in Angola the natural resources sector), and steady remittance flows supported 20 Saharan Africa expanded at an average of growth in 2012. GDP in Sub-­ 4.9 percent a year over 2000–11 and rose an estimated 4.6 percent 15 in 2012, the third most among developing regions. Excluding South Africa, the region’s largest economy, GDP output rose 5.8 percent 10 Nigeria in 2012, with a third of countries growing at least 6 percent. Growth 5 varied across the region, with steady expansion in most low-income countries but slow growth in middle-income countries, such as South Sub-Saharan Africa 0 Africa, that are more tightly integrated with the global economy and South Africa Mali in some countries affected by political instability, such as Mali (IMF –5 2007 2008 2009 2010 2011 2012 2012; World Bank 2013). Source: Online table 4.1. Economy States and markets Global links Back World Development Indicators 2013 67 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 2000–11 2011–12 2012–13 2011 2011 2011 2011 2011 2011 2011 Afghanistan .. .. .. .. .. .. –0.6 .. 5.7 35.8 Albania 5.2 0.8 1.6 12.7 0.9 –12.1 .. .. 3.5 81.8 Algeria 3.7 3.0 3.4 48.4 25.3 10.4 –0.3 .. 4.5 64.6 American Samoa .. .. .. .. .. .. .. .. .. .. Andorra 5.9 .. .. .. .. .. .. .. .. .. Angola 12.2 8.1 7.2 20.2 –21.4 12.5 .. .. 13.5 35.9 Antigua and Barbuda 2.7 1.7 2.4 26.8 .. –10.7 .. .. 3.5 101.4 Argentina .. .. .. 22.3 11.3 0.0 .. .. .. 28.8 Armenia 8.2 6.8 4.3 19.3 8.7 –10.8 –2.7 .. 7.7 29.5 Aruba .. .. .. .. .. .. .. .. 4.4 .. Australia 3.1 .. .. 22.9 6.8 –2.8 –3.7 30.7 3.4 105.8 Austriaa 1.8 .. .. 25.5 16.4 0.5 –2.2 75.0 3.3 .. Azerbaijan 16.0 2.0 4.2 45.9 7.5 27.0 1.4 6.4 7.9 27.8 Bahamas, The 0.5 .. .. 11.5 .. –14.0 –3.5 .. 3.2 80.5 Bahrain 6.3 .. .. 30.1 9.6 3.4 .. .. –0.4 91.2 Bangladesh 6.0 6.1 6.0 36.5 25.0 0.2 –0.9 .. 10.7 68.7 Barbados 0.9 .. .. 16.9 .. –5.3 –8.6 104.4 9.4 152.3 Belarus 7.8 2.8 4.0 26.3 17.6 –10.5 1.9 44.2 53.2 40.5 Belgiuma 1.5 .. .. 22.3 14.1 –1.4 –3.6 91.0 3.5 .. Belize 3.7 4.0 2.8 .. .. –2.2 –1.6 .. –2.5 76.0 Benin 3.8 3.5 3.8 13.1 7.7 –8.1 –1.4 .. 2.7 40.0 Bermuda 1.9 .. .. .. .. .. .. .. .. .. Bhutan 8.5 .. .. .. .. .. 0.5 56.8 8.8 67.1 Bolivia 4.2 4.7 4.4 26.1 6.9 2.2 .. .. 9.8 68.7 Bosnia and Herzegovina 4.2 .. .. 13.1 .. –8.8 –1.2 .. 3.7 56.7 Botswana 4.0 5.8 5.1 27.7 20.4 0.3 –1.7 .. 8.9 37.8 Brazil 3.8 0.9 3.4 17.2 6.8 –2.1 –2.6 52.8 6.6 74.4 Brunei Darussalam 1.2 .. .. 50.9 10.1 37.1 .. .. 2.0 67.2 Bulgaria 4.3 0.8 1.8 23.6 13.7 0.4 –2.0 15.5 4.2 75.6 Burkina Faso 5.8 6.4 6.7 15.6 5.5 –4.6 –2.4 .. 2.8 29.0 Burundi 3.5 4.1 4.3 1.7 –6.1 –12.2 .. .. 9.7 24.2 Cambodia 8.4 6.6 6.7 10.6 3.4 –5.5 –4.2 .. 5.5 39.1 Cameroon 3.2 4.6 4.8 12.2 0.8 –3.8 .. .. 2.9 23.1 Canada 1.9 .. .. 19.6 6.7 –2.8 –1.3 53.8 2.9 .. Cape Verde 6.2 4.8 4.9 22.2 16.7 –16.0 –3.7 .. 4.5 77.0 Cayman Islands .. .. .. .. .. .. .. .. .. .. Central African Republic 1.3 3.8 4.0 .. .. .. .. .. 1.3 19.2 Chad 8.7 .. .. .. .. .. .. .. –4.9 13.8 Channel Islands 0.5 .. .. .. .. .. .. .. .. .. Chile 4.1 5.8 5.1 24.9 5.4 1.8 1.3 .. 3.3 76.1 China 10.8 7.9 8.4 52.7 36.4 2.8 .. .. 5.4 180.1 Hong Kong SAR, China 4.6 .. .. 29.4 18.1 5.2 4.1 35.5 5.3 328.2 Macao SAR, China 12.5 .. .. 55.9 .. 42.7 25.0 .. 5.8 101.9 Colombia 4.5 3.5 3.8 19.1 1.3 –3.0 0.3 53.2 3.4 39.9 Comoros 1.9 2.5 3.5 .. .. .. .. .. 0.9 34.9 Congo, Dem. Rep. 5.6 6.6 8.2 .. .. .. 3.8 .. .. 16.8 Congo, Rep. 4.5 4.7 5.6 .. .. .. .. .. 1.3 27.0 68  World Development Indicators 2013 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 2000–11 2011–12 2012–13 2011 2011 2011 2011 2011 2011 2011 Costa Rica 4.8 4.6 4.0 14.7 9.0 –5.3 –3.5 .. 4.9 49.8 Côte d’Ivoire 1.0 8.2 7.0 12.7 4.1 2.0 .. .. 4.9 40.5 Croatia 2.6 .. .. 19.9 10.7 –0.7 –4.6 .. 2.3 72.9 Cuba 6.1 .. .. .. .. .. .. .. .. .. Curaçao .. .. .. .. .. .. .. .. .. .. Cyprusa 2.9b .. .. 8.8b 4.6 b –4.7 –6.3 114.0 3.3 .. Czech Republic 3.7 .. .. 21.7 12.6 –2.9 –4.4 38.1 1.9 73.9 Denmark 0.8 .. .. 23.5 15.0 5.7 –2.0 50.6 2.8 74.0 Djibouti 4.0 .. .. .. .. –6.8 .. .. 4.4 89.7 Dominica 3.5 0.4 1.2 5.0 –3.7 –17.5 .. .. 2.4 86.7 Dominican Republic 5.7 3.0 4.3 8.4 –1.7 –8.1 –2.9 .. 8.5 33.4 Ecuador 4.8 4.5 3.9 22.8 –3.2 –0.4 .. .. 4.5 35.6 Egypt, Arab Rep. 5.0 2.4 3.2 16.9 1.4 –2.4 –10.1 .. 10.1 76.1 El Salvador 2.0 1.8 2.3 8.9 0.7 –4.6 –2.2 48.0 5.1 45.7 Equatorial Guinea 14.4 .. .. .. .. .. .. .. 6.9 11.5 Eritrea 0.9 7.5 6.0 .. .. .. .. .. .. 114.7 Estoniaa 3.9 .. .. 25.1 16.3 2.2 1.0 7.1 5.0 59.8 Ethiopia 8.9 7.8 7.5 27.3 17.6 –2.6 –1.4 .. 33.2 .. Faeroe Islands .. .. .. .. .. –0.7 .. .. .. .. Fiji 1.2 .. .. .. .. –13.0 .. .. 8.7 66.3 Finlanda 1.9 .. .. 19.7 11.5 –1.2 –0.5 47.8 3.4 .. Francea 1.2 .. .. 17.9 9.0 –2.0 –5.2 93.9 2.1 .. French Polynesia .. .. .. .. .. .. .. .. .. .. Gabon 2.4 4.7 3.5 .. .. .. .. .. 1.3 22.1 Gambia, The 3.4 3.9 10.7 12.1 6.6 7.5 .. .. 4.8 54.9 Georgia 6.6c 4.9c 5.1c 13.9c 4.9c –11.8 –1.2 32.6 49.4 29.3 Germanya 1.1 .. .. 23.9 13.8 5.6 –0.4 55.6 2.1 .. Ghana 6.3 7.5 7.8 8.8 –6.6 –8.9 –4.0 .. 8.7 30.8 Greecea 1.8 .. .. 5.4 –5.5 –9.9 –9.8 106.5 3.3 .. Greenland 1.7 .. .. .. .. .. .. .. .. .. Grenada 2.2 .. .. –5.7 .. –26.6 –3.0 .. 3.0 94.3 Guam .. .. .. .. .. .. .. .. .. .. Guatemala 3.6 3.1 3.2 10.7 0.9 –3.1 –2.8 24.6 6.2 45.5 Guinea 2.6 4.8 5.0 –6.5 –27.7 –22.8 .. .. 21.4 36.4 Guinea-Bissau 2.5 –2.8 3.0 .. .. –8.5 .. .. 5.0 40.5 Guyana 2.5 .. .. 14.5 –1.3 –7.1 .. .. 5.0 65.8 Haiti 0.7 2.2 6.0 24.6 17.0 –4.6 .. .. 8.4 47.2 Honduras 4.4 3.3 3.7 17.9 11.0 –8.6 –2.6 .. 6.8 52.2 Hungary 1.9 .. .. 20.6 13.0 0.9 3.6 80.9 4.0 63.7 Iceland 2.7 .. .. 7.3 0.9 –6.9 –5.3 119.3 4.0 96.3 India 7.8 5.5 5.9 34.6 22.5 –3.0 –3.7 48.5 8.9 76.7 Indonesia 5.4 6.1 6.3 31.8 17.1 0.2 –1.1 26.2 5.4 38.8 Iran, Islamic Rep. 5.4 .. .. .. .. .. 0.5 .. 20.6 45.0 Iraq 1.1 .. .. .. .. 22.7 .. .. 2.9 54.9 Irelanda 2.4 .. .. 14.0 5.5 1.2 –13.5 106.0 2.6 .. Isle of Man 6.2 .. .. .. .. .. .. .. .. .. Israel 3.6 .. .. 14.7 6.3 0.1 –4.4 .. 3.5 104.5 Economy States and markets Global links Back World Development Indicators 2013 69 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 2000–11 2011–12 2012–13 2011 2011 2011 2011 2011 2011 2011 Italya 0.4 .. .. 16.4 6.8 –3.1 –3.5 110.8 2.7 .. Jamaica .. .. .. 8.4 1.3 –14.3 –5.1 .. 7.5 50.8 Japan 0.7 .. .. 21.7 10.4 2.0 –8.3 175.0 –0.3 239.2 Jordan 6.5 3.0 3.3 13.4 5.8 –12.0 –6.8 61.9 4.4 129.6 Kazakhstan 8.0 5.0 5.5 29.7 –4.3 7.5 7.7 9.9 8.3 35.4 Kenya 4.4 4.3 4.9 13.5 11.3 –9.9 –4.6 .. 14.0 51.0 Kiribati 0.4 .. .. .. .. .. .. .. .. .. Korea, Dem. Rep. .. .. .. .. .. .. .. .. .. .. Korea, Rep. 4.0 .. .. 31.5 22.2 2.4 1.8 .. 4.0 78.1 Kosovo 5.2 .. .. .. .. .. .. .. 7.3 41.0 Kuwait 6.0 .. .. 48.7 12.2 29.6 25.0 .. 4.7 56.9 Kyrgyz Republic 4.4 1.0 8.5 18.2 5.6 –6.1 –4.8 .. 16.5 .. Lao PDR 7.3 8.2 7.5 16.3 –1.7 –2.5 –0.9 .. 7.6 35.9 Latvia 4.1 5.3 3.0 26.1 18.5 –2.2 –2.9 42.5 4.4 47.0 Lebanon 5.0 1.7 2.8 11.5 0.8 –12.1 –5.9 .. 4.0 242.0 Lesotho 3.8 4.3 5.2 15.1 .. –21.4 .. .. 5.0 37.9 Liberia 6.0 .. .. 30.4 23.0 –48.9 0.0 .. 8.5 38.2 Libya 5.4 .. .. .. .. 15.0 .. .. 2.5 58.0 Liechtenstein 2.5 .. .. .. .. .. .. .. .. .. Lithuania 4.7 3.3 2.5 17.5 9.6 –1.4 –5.2 43.7 4.1 47.6 Luxembourga 2.9 .. .. 22.0 12.4 7.1 –0.4 16.8 3.4 .. Macedonia, FYR 3.3 0.0 1.0 25.6 14.9 –3.0 .. .. 3.9 55.7 Madagascar 3.2 2.2 4.5 .. .. .. .. .. 9.5 24.9 Malawi 5.1 4.1 5.4 13.5 9.8 –13.6 .. .. 7.6 35.7 Malaysia 4.9 5.1 5.0 34.6 20.6 11.0 –4.8 51.8 3.2 138.5 Maldives 7.2 .. .. .. .. –23.9 –16.7 68.4 12.8 63.7 Mali 5.1 –1.5 3.5 8.5 –5.2 –12.6 –2.5 .. 2.9 29.1 Maltaa 1.8 .. .. 9.5 .. –0.2 –2.8 86.5 2.7 .. Marshall Islands 1.5 .. .. .. .. .. .. .. .. .. Mauritania 5.6 4.8 5.2 .. .. .. .. .. 5.7 32.8 Mauritius 3.9 3.3 3.6 13.8 4.8 –12.6 –1.1 36.3 6.5 103.3 Mexico 2.1 4.0 3.3 26.6 12.4 –1.0 .. .. 3.4 31.4 Micronesia, Fed. Sts. 0.0 .. .. .. .. .. .. .. .. 38.2 Moldova 5.1d 1.0 d 3.0 d 13.0 d 10.2d –11.3 –1.8 23.8 7.7 49.9 Monaco 4.3 .. .. .. .. .. .. .. .. .. Mongolia 7.4 11.8 16.2 31.1 –5.5 –31.5 –3.1 46.9 9.5 57.8 Montenegro 4.2 .. .. .. .. .. .. .. 3.2 47.4 Morocco 4.8e 3.0e 4.4 e 28.1e 20.2e –8.0 –4.1 56.3 0.9 112.4 Mozambique 7.5 7.5 8.0 12.4 5.6 –19.1 .. .. 10.4 38.8 Myanmar .. .. .. .. .. .. .. .. 5.0 .. Namibia 4.9 4.2 4.3 18.6 14.6 –1.2 .. .. 5.0 66.6 Nepal 3.9 4.2 4.0 34.2 27.9 1.5 –1.0 33.8 9.5 75.7 Netherlandsa 1.5 .. .. 26.1 15.1 9.7 –3.9 66.0 2.4 .. New Caledonia .. .. .. .. .. .. .. .. .. .. New Zealand 2.0 .. .. 18.8 11.2 –4.2 –7.3 63.6 4.4 95.8 Nicaragua 3.2 4.0 4.2 19.0 11.2 –14.0 0.5 .. 8.1 34.5 Niger 4.2 12.0 6.8 .. .. –25.1 .. .. 2.9 21.4 70  World Development Indicators 2013 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 2000–11 2011–12 2012–13 2011 2011 2011 2011 2011 2011 2011 Nigeria 6.8 6.5 6.6 .. .. 3.6 .. .. 10.8 33.6 Northern Mariana Islands .. .. .. .. .. .. .. .. .. .. Norway 1.6 .. .. 37.7 19.2 14.5 14.7 20.4 1.3 .. Oman 4.9 .. .. .. .. 14.3 –0.8 5.1 4.1 35.7 Pakistan 4.9 3.8 3.9 20.4 9.3 –1.1 –6.5 .. 11.9 38.0 Palau 0.3 .. .. .. .. .. .. .. .. .. Panama 7.2 10.0 7.5 17.7 9.4 –14.5 .. .. 5.9 98.1 Papua New Guinea 4.3 8.0 4.0 20.3 .. –6.7 .. .. 8.4 49.9 Paraguay 4.1 –1.0 8.5 10.6 3.6 –1.1 1.1 .. 8.3 45.0 Peru 6.2 6.3 5.8 23.4 5.4 –1.9 1.3 19.5 3.4 35.8 Philippines 4.9 6.0 6.2 25.1 14.6 3.1 –1.8 .. 4.6 59.8 Poland 4.3 .. .. 16.9 9.2 –4.9 –4.3 .. 4.2 58.0 Portugala 0.5 .. .. 11.7 –1.6 –6.5 –4.0 92.6 3.7 .. Puerto Rico 0.0 .. .. .. .. .. .. .. .. .. Qatar 13.6 .. .. .. .. .. 2.9 .. 1.9 49.2 Romania 4.4 0.6 1.6 24.8 14.4 –4.4 –4.9 .. 5.8 37.3 Russian Federation 5.1 3.5 3.6 30.3 7.2 5.3 3.4 9.5 8.4 52.7 Rwanda 7.9 7.7 7.5 11.3 4.5 –7.5 .. .. 5.7 .. Samoa 2.6 .. .. .. .. –11.9 .. .. 5.2 47.2 San Marino 3.2 .. .. .. .. .. .. .. 2.6 .. São Tomé and Príncipe .. .. .. .. .. –43.5 .. .. 11.9 35.8 Saudi Arabia 3.7 .. .. 46.8 3.8 27.5 .. .. 5.0 57.2 Senegal 4.1 3.7 4.8 21.8 17.3 –4.7 .. .. 3.4 40.2 Serbia 3.7 .. .. 16.4 .. –8.4 –4.2 .. 11.1 44.7 Seychelles 2.9 3.3 4.2 .. .. –21.4 5.6 75.3 2.6 57.9 Sierra Leone 6.6 25.0 11.1 9.8 –6.0 –37.9 –4.6 .. 16.2 21.6 Singapore 6.0 .. .. 46.6 35.7 23.3 9.8 112.7 5.3 135.7 Sint Maarten .. .. .. .. .. .. .. .. .. .. Slovak Republica 5.1 .. .. 16.5 7.2 0.0 –4.9 45.6 3.9 .. Sloveniaa 2.9 .. .. 21.4 13.2 0.0 –6.0 .. 1.8 .. Solomon Islands 4.9 5.3 4.0 .. .. –30.1 .. .. 7.3 40.8 Somalia .. .. .. .. .. .. .. .. .. .. South Africa 3.7 2.4 2.7 16.4 1.5 –3.4 –4.4 .. 5.0 76.1 South Sudan .. –2.0 11.0 .. .. .. .. .. .. .. Spaina 2.1 .. .. 18.2 9.1 –3.5 –3.5 55.2 3.2 .. Sri Lanka 5.8 6.1 6.8 22.1 13.4 –7.8 –6.4 .. 6.7 38.1 St. Kitts and Nevis 2.5 .. .. 23.4 .. –8.6 2.6 .. 5.9 138.3 St. Lucia 2.9 0.7 1.2 11.8 .. –22.5 .. .. 2.8 91.3 St. Martin .. .. .. .. .. .. .. .. .. .. St. Vincent and Grenadines 3.1 1.2 1.5 –4.8 –12.2 –30.2 –3.7 .. 4.0 67.8 Sudan 7.1f 3.0 f 3.2f 20.9 f 0.1f 0.2 .. .. 13.0 24.5 Suriname 4.9 4.0 4.5 .. .. 5.8 .. .. 17.7 47.5 Swaziland 2.4 –2.0 1.0 –0.5 –5.1 –10.0 .. .. 6.1 29.6 Sweden 2.3 .. .. 26.2 18.7 6.5 0.5 38.2 3.0 86.6 Switzerland 1.9 .. .. 32.1 22.0 7.5 .. .. 0.2 167.8 Syrian Arab Republic 5.0 .. .. 16.8 –5.7 –0.6 .. .. 4.8 73.9 Tajikistan 8.0 .. .. 23.2 16.4 –12.1 .. .. 12.4 .. Economy States and markets Global links Back World Development Indicators 2013 71 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 2000–11 2011–12 2012–13 2011 2011 2011 2011 2011 2011 2011 Tanzaniag 7.0 6.5 6.8 20.3 10.5 –16.6 .. .. 12.7 34.7 Thailand 4.2 4.7 5.0 31.0 20.8 4.1 –1.2 30.2 3.8 128.2 Timor-Leste 5.6 .. .. .. .. .. .. .. 13.5 30.6 Togo 2.6 4.0 4.4 12.2 5.3 –6.3 –1.1 .. 3.6 48.5 Tonga 1.0 .. .. 3.9 .. –17.0 .. .. 6.3 39.0 Trinidad and Tobago 5.6 .. .. .. .. 19.9 –4.8 21.3 5.1 65.1 Tunisia 4.4 2.4 3.2 15.9 5.8 –7.3 –3.7 44.0 3.6 67.6 Turkey 4.7 2.9 4.0 14.1 4.0 –10.0 –1.3 45.9 6.5 54.7 Turkmenistan 8.7 .. .. .. .. .. .. .. .. .. Turks and Caicos Islands .. .. .. .. .. .. .. .. .. .. Tuvalu 1.1 .. .. .. .. .. .. .. .. .. Uganda 7.7 3.4 6.2 20.8 11.2 –13.5 –3.9 42.7 18.7 26.5 Ukraine 4.3 0.5 2.2 16.0 6.2 –5.5 –2.3 27.1 8.0 52.1 United Arab Emirates 4.8 .. .. .. .. .. .. .. 0.9 62.4 United Kingdom 1.7 .. .. 12.9 2.7 –1.9 –7.7 101.2 4.5 165.7 United States 1.6 .. .. 11.7 0.9 –3.2 –9.3 81.8 3.2 89.8 Uruguay 4.0 4.0 4.0 16.5 5.9 –3.1 –0.6 46.6 8.1 44.6 Uzbekistan 7.3 8.0 6.5 .. .. .. .. .. .. .. Vanuatu 3.9 2.0 2.5 .. .. –15.2 .. .. 0.9 84.2 Venezuela, RB 4.4 5.2 1.8 30.7 1.4 8.6 .. .. 26.1 36.6 Vietnam 7.3 5.2 5.5 33.1 17.4 0.2 .. .. 18.7 109.3 Virgin Islands (U.S.) .. .. .. .. .. .. .. .. .. .. West Bank and Gaza .. .. .. .. .. .. .. .. 2.8 .. Yemen, Rep. 3.6 0.1 4.0 8.3 –10.0 –3.0 .. .. 16.4 30.1 Zambia 5.7 6.7 7.1 27.8 4.0 1.1 –1.5 .. 6.4 23.4 Zimbabwe –5.1 5.0 6.0 .. .. .. .. .. .. .. World 2.7 w 2.3 w 2.4 w 19.4 w 6.7 w Low income 5.5 5.6 6.1 26.5 15.6 Middle income 6.4 4.9 5.5 30.0 15.1 Lower middle income 6.2 4.8 5.5 28.1 13.4 Upper middle income 6.5 5.0 5.5 31.0 15.6 Low & middle income 6.4 4.9 5.5 29.9 15.1 East Asia & Pacific 9.4 7.5 7.9 47.7 30.3 Europe & Central Asia 5.2 3.0 3.6 22.9 6.2 Latin America & Carib. 3.9 3.0 3.6 21.5 8.6 Middle East & N. Africa 4.7 0.2 2.4 .. .. South Asia 7.3 5.4 5.7 33.3 21.2 Sub-­Saharan Africa 4.9 4.6 4.9 16.8 –2.4 High income 1.6 1.3 1.3 17.6 5.7 Euro area 1.2 –0.4 –0.1 20.1 8.6 a. As members of the European Monetary Union, these countries share a single currency, the euro. b. Refers to the area controlled by the government of the Republic of Cyprus. c. Excludes Abkhazia and South Ossetia. d. Excludes Transnistria. e. Includes Former Spanish Sahara. f. Excludes South Sudan after July 9, 2011. g. Covers mainland Tanzania only. 72  World Development Indicators 2013 Front ? User guide World view People Environment Economy 4 About the data Economic data are organized by several different accounting con- this year’s edition are not comparable with those from earlier edi- ventions: the system of national accounts, the balance of pay- tions with different base years. ments, government finance statistics, and international finance 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 finance 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 balance of payments methodology (BPM6), but many countries are of assets in the economy. If a country’s adjusted net savings are still using the previous version. Similarly, the standards and defini- positive and the accounting includes a sufficiently broad range of tions for government finance statistics were updated in 2001, but assets, economic theory suggests that the present value of social several countries still report using the 1986 version. For individual welfare is increasing. Conversely, persistently negative adjusted country information about methodology used, refer to Primary data net savings indicate that the present value of social welfare is documentation. decreasing, suggesting that an economy is on an unsustainable path. Economic growth Adjusted net savings are derived from standard national account- An economy’s growth is measured by the change in the volume of its ing measures of gross savings by making four adjustments. First, output or in the real incomes of its residents. The 2008 SNA offers estimates of fixed capital consumption of produced assets are three plausible indicators for calculating growth: the volume of gross deducted to obtain net savings. Second, current public expendi- domestic product (GDP), real gross domestic income, and real gross tures on education are added to net savings (in standard national national income. Only growth in GDP is reported here. accounting these expenditures are treated as consumption). Third, Growth rates of GDP and its components are calculated using the estimates of the depletion of a variety of natural resources are least squares method and constant price data in the local currency deducted to reflect the decline in asset values associated with their for countries and using constant price U.S. dollar series for regional extraction and harvest. And fourth, deductions are made for dam- and income groups. Local currency series are converted to constant ages from carbon dioxide emissions and local pollution. By account- U.S. dollars using an exchange rate in the common reference year. ing for the depletion of natural resources and the degradation of The growth rates are average annual and compound growth rates. the environment, adjusted net savings goes beyond the definition Methods of computing growth are described in Statistical methods. of savings or net savings in the SNA. Forecasts of growth rates come from World Bank (2013). Balance of payments Rebasing national accounts The balance of payments records an economy’s transactions with Rebasing of national accounts can alter the measured growth rate of the rest of the world. Balance of payments accounts are divided an economy and lead to breaks in series that affect the consistency into two groups: the current account, which records transactions of data over time. When countries rebase their national accounts, in goods, services, primary income, and secondary income, and they update the weights assigned to various components to better the capital and financial account, which records capital transfers, reflect current patterns of production or uses of output. The new acquisition or disposal of nonproduced, nonfinancial assets, and economy—it base year should represent normal operation of the ­ transactions in financial assets and liabilities. The current account should be a year without major shocks or distortions. Some devel- balance is one of the most analytically useful indicators of an exter- oping countries have not rebased their national accounts for many nal imbalance. years. Using an old base year can be misleading because implicit A primary purpose of the balance of payments accounts is to price and volume weights become progressively less relevant and indicate the need to adjust an external imbalance. Where to draw useful. the line for analytical purposes requires a judgment concerning the To obtain comparable series of constant price data for comput- imbalance that best indicates the need for adjustment. There are a ing aggregates, the World Bank rescales GDP and value added by number of definitions in common use for this and related analytical industrial origin to a common reference year. This year’s World Devel- purposes. The trade balance is the difference between exports and opment Indicators continues to use 2000 as the reference year. imports of goods. From an analytical view it is arbitrary to distinguish Because rescaling changes the implicit weights used in forming goods from services. For example, a unit of foreign exchange earned regional and income group aggregates, aggregate growth rates in by a freight company strengthens the balance of payments to the Economy States and markets Global links Back World Development Indicators 2013 73 4 Economy same extent as the foreign exchange earned by a goods exporter. Government finance statistics are reported in local currency. The Even so, the trade balance is useful because it is often the most indicators here are shown as percentages of GDP. Many countries timely indicator of trends in the current account balance. Customs report government finance data by fiscal year; see Primary data authorities are typically able to provide data on trade in goods long documentation for information on fiscal year end by country. before data on trade in services are available. Beginning in August 2012, the International Monetary Fund imple- Financial accounts mented the Balance of Payments Manual 6 (BPM6) framework in Money and the financial accounts that record the supply of money its major statistical publications. The World Bank will implement lie at the heart of a country’s financial system. There are several BPM6 in its online databases and publications in April 2013. Bal- commonly used definitions of the money supply. The narrowest, M1, ance of payments data for 2005 onward will be presented in accord encompasses currency held by the public and demand deposits with with the BPM6. The historical BPM5 data series will end with data banks. M2 includes M1 plus time and savings deposits with banks for 2008, which can be accessed through the World Development that require prior notice for withdrawal. M3 includes M2 as well as Indicators archives. various money market instruments, such as certificates of deposit The complete balance of payments methodology can be accessed issued by banks, bank deposits denominated in foreign currency, through the International Monetary Fund website (www.imf.org/ and deposits with financial institutions other than banks. However external/np/sta/bop/bop.htm). defined, money is a liability of the banking system, distinguished from other bank liabilities by the special role it plays as a medium Government finance of exchange, a unit of account, and a store of value. Central government cash surplus or deficit, a summary measure of A general and continuing increase in an economy’s price level is the ongoing sustainability of government operations, is comparable called inflation. The increase in the average prices of goods and to the national accounting concept of savings plus net capital trans- services in the economy should be distinguished from a change fers receivable, or net operating balance in the 2001 update of the in the relative prices of individual goods and services. Generally IMF’s Government Finance Statistics Manual. accompanying an overall increase in the price level is a change in The 2001 manual, harmonized with the 1993 SNA, recommends the structure of relative prices, but it is only the average increase, an accrual accounting method, focusing on all economic events not the relative price changes, that constitutes inflation. A commonly affecting assets, liabilities, revenues, and expenses, not just those used measure of inflation is the consumer price index, which mea- represented by cash transactions. It accounts for all changes in sures the prices of a representative basket of goods and services stocks, so stock data at the end of an accounting period equal stock purchased by a typical household. The consumer price index is usu- data at the beginning of the period plus flows over the period. The ally calculated on the basis of periodic surveys of consumer prices. 1986 manual considered only debt stocks. Other price indices are derived implicitly from indexes of current and For most countries central government finance data have been constant price series. consolidated into one account, but for others only budgetary central Consumer price indexes are produced more frequently and so government accounts are available. Countries reporting budgetary are more current. They are constructed explicitly, using surveys data are noted in Primary data documentation. Because budgetary of the cost of a defined basket of consumer goods and services. accounts may not include all central government units (such as Nevertheless, consumer price indexes should be interpreted with social security funds), they usually provide an incomplete picture. caution. The definition of a household, the basket of goods, and the In federal states the central government accounts provide an incom- geographic (urban or rural) and income group coverage of consumer plete view of total public finance. price surveys can vary widely by country. In addition, weights are Data on government revenue and expense are collected by the IMF derived from household expenditure surveys, which, for budgetary through questionnaires to member countries and by the Organisa- reasons, tend to be conducted infrequently in developing countries, tion for Economic Co-operation and Development (OECD). Despite impairing comparability over time. Although useful for measuring IMF efforts to standardize data collection, statistics are often incom- consumer price inflation within a country, consumer price indexes plete, untimely, and not comparable across countries. are of less value in comparing countries. 74  World Development Indicators 2013 Front ? User guide World view People Environment Economy 4 Definitions on education expenditure from the United Nations Educational, • Gross domestic product (GDP) at purchaser prices is the sum of Scientific, and Cultural Organization Institute for Statistics online gross value added by all resident producers in the economy plus any database, with missing data estimated by World Bank staff; data on product taxes (less subsidies) not included in the valuation of output. forest, energy, and mineral depletion based on sources and meth- It is calculated without deducting for depreciation of fabricated capital ods in World Bank (2011); data on carbon dioxide damage from assets or for depletion and degradation of natural resources. Value Fankhauser (1994); data on local pollution damage from Pandey and added is the net output of an industry after adding up all outputs and others (2006). Data on current account balance are from the IMF’s subtracting intermediate inputs. • Gross savings are the difference Balance of Payments Statistics Yearbook and International Financial between gross national income and public and private consump- Statistics. Data on central government finances are from the IMF’s tion, plus net current transfers. • Adjusted net savings measure Government Finance Statistics database. Data on the consumer the change in value of a specified set of assets, excluding capital price index are from the IMF’s International Financial Statistics. Data gains. Adjusted net savings are net savings plus education expendi- on broad money are from the IMF’s monthly International Financial ture minus energy depletion, mineral depletion, net forest depletion, Statistics and annual International Financial Statistics Yearbook. and carbon dioxide and particulate emissions damage. • Current account balance is the sum of net exports of goods and services, net References primary income, and net secondary income. • Central government Asian Development Bank. 2012. Asian Development Outlook 2012 cash surplus or deficit is revenue (including grants) minus expense, Update: Services and Asia’s Future Growth. Manila. minus net acquisition of nonfinancial assets. In editions before 2005 De la Torre, Augusto, Tatiana Didier, and Samuel Pienknagura. 2012. nonfinancial assets were included under revenue and expenditure in Latin America Copes with Volatility, the Dark Side of Globalization. gross terms. This cash surplus or deficit is close to the earlier overall Washington, DC: World Bank. budget balance (still missing is lending minus repayments, which are Fankhauser, Samuel. 1994. “The Social Costs of Greenhouse Gas Emis- included as a financing item under net acquisition of financial assets). sions: An Expected Value Approach.� Energy Journal 15 (2): 157–84. • Central government debt is the entire stock of direct government Hamilton, Kirk, and Michael Clemens. 1999. “Genuine Savings Rates in fixed-term contractual obligations to others outstanding on a particu- Developing Countries.� World Bank Economic Review 13 (2): 333–56. lar date. It includes domestic and foreign liabilities such as currency IMF (International Monetary Fund). 2001. Government Finance Statis- and money deposits, securities other than shares, and loans. It is tics Manual. Washington, DC. the gross amount of government liabilities reduced by the amount ———. 2012. Regional Economic Outlook: Sub-­ Saharan Africa—Main- of equity and financial derivatives held by the government. Because taining Growth in an Uncertain World, October 2012. Washington, DC. debt is a stock rather than a flow, it is measured as of a given date, www.imf.org/external/pubs/ft/reo/2012/afr/eng/sreo1012.htm. usually the last day of the �scal year. • Consumer price index reflects Pandey, Kiran D., Katharine Bolt, Uwe Deichmann, Kirk Hamilton, Bart changes in the cost to the average consumer of acquiring a basket Ostro, and David Wheeler. 2006. “The Human Cost of Air Pollution: of goods and services that may be fixed or may change at specified New Estimates for Developing Countries.� World Bank, Development intervals, such as yearly. The Laspeyres formula is generally used. Research Group and Environment Department, Washington, DC. • Broad money (IFS line 35L..ZK) is the sum of currency outside United Nations Statistics Division. Various years. National Accounts banks; demand deposits other than those of the central government; Statistics: Main Aggregates and Detailed Tables. Parts 1 and 2. New the time, savings, and foreign currency deposits of resident sectors York: United Nations. other than the central government; bank and traveler’s checks; and World Bank. 2011. The Changing Wealth of Nations: Measuring Sustain- other securities such as certificates of deposit and commercial paper. able Development for the New Millennium. Washington, DC. ———. 2012a. East Asia and Pacific Economic Update 2012, Volume 2: Data sources Remaining Resilient. Washington, DC. Data on GDP for most countries are collected from national statisti- ———. 2012b. Middle East and North Africa Region Economic Devel- cal organizations and central banks by visiting and resident World opments and Prospects, October 2012: Looking Ahead After a Year Bank missions; data for selected high-income economies are from in Transition. Washington, DC. the OECD. Data on gross savings are from World Bank national ———. 2012c. South Asia Economic Focus—A Review of Economic accounts data files. Data on adjusted net savings are based on Developments in South Asian Countries: Creating Fiscal Space a conceptual underpinning by Hamilton and Clemens (1999) and through Revenue Mobilization. Washington, DC. calculated using data on consumption of fixed capital from the ———. 2013. Global Economic Prospects, Volume 6, January 13: United Nations Statistics Division’s National Accounts Statistics: Assuring Growth over the Medium Term. Washington, DC. Main Aggregates and Detailed Tables, extrapolated to 2010; data ———. Various years. World Development Indicators. Washington, DC. Economy States and markets Global links Back World Development Indicators 2013 75 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 76  World Development Indicators 2013 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 2013 77 STATES AND MARKETS 78  World Development Indicators 2013 Front ? User guide World view People Environment 5 States and markets includes indicators of pri- evaluating investment options, governments vate sector investment and performance, the interested in improving business conditions, role of the public sector in nurturing investment and economists seeking to explain economic and growth, and the quality and availability of performance have all grappled with defining and infrastructure essential for growth and develop- measuring the business environment and how ment. These indicators measure the business constraints affect productivity and job creation. environment, the functions of government, finan- The World Development Indicators database cial system development, infrastructure, informa- includes results from enterprise surveys and tion and communication technology, science and expert assessments of the business environ- technology, performance of governments and ment from the Doing Business project. their policies, and conditions in fragile countries States and markets also includes data on the with weak institutions. size of the transportation and power sectors, as Measures of investment in infrastructure well as the spread of new information technol- projects with private participation show the ogy. To become competitive suppliers to the rest private sector’s contributions to providing pub- of the world, many developing countries need to lic services and easing fiscal constraints. For improve their road, rail, port, and air transport example, private investment in the dynamic tele- facilities. Expanding electricity supply to meet communications sector has increased more than the growing demand of increasingly urban and 50 percent since 2006, reaching $158.5 billion industrialized economies without unacceptable in 2011. social, economic, and environmental costs is Data on access to finance, availability of one of the greatest challenges facing developed credit, cost of service, and stock markets help and developing countries. Data on electric power improve understanding of the state of finan- consumption per capita show that consumption cial development. In 2011 people had greater in developing countries has doubled since 1995, access to finance in Europe and Central Asia, to 1,660 kilowatt-hours in 2010. with 19 commercial bank branches and 47 auto- With rapid growth of mobile telephony and mated teller machines per 100,000 people, the global expansion of the Internet, informa- than in other developing regions. Stock market tion and communication technologies are measures show the effects of the global finan- increasingly recognized as essential for devel- cial crises: the market capitalization of listed opment. World Development Indicators includes companies dropped from $64.6 trillion in 2007 data showing the rapid changes in this sec- to $34.9  trillion in 2008, recovering to only tor. For instance, mobile cellular subscriptions $46.8 trillion in 2011. increased from 16 percent of the global popula- Economic health is measured not only in tion in 2001 to 85 percent in 2011, and Internet macroeconomic terms but also by laws, regu- users from 8 percent to 33 percent over the lations, and institutional arrangements. Firms same period. Economy States and markets Global links Back World Development Indicators 2013 79 Highlights East Asia & Pacific: Patent applications are rising, especially in China Patent applications, 2011 (thousands) W hile the global economy continued to underperform, intellectual  600 property filings worldwide grew strongly in 2011. Demand for patents rose from 800,000 applications in the early 1980s to 2.14 million in 2011, topping 2 million for the first time. After dropping 4 percent in 400 2009, patent applications rebounded strongly in 2010 and 2011, aver- aging 7 percent growth a year. In 2011 China’s patent office became the world’s largest, measured by patent applications received, accord- 200 ing to World Intellectual Property Organization (2012). China received 526,412 applications, compared with 503,582 for the United States and 342,610 for Japan. Of the 20 busiest patent offices, 7 were in 0 East Asia and Pacific, accounting for 58 percent of total applications Ge ep. rea an dS a es de ia Ca ion ite us a ing lia ng M ce R, co ga a re uth aly a Ne ala l Ze a Ind land ia y M rae m an ite hin Un A nad Sin hin ric w ysi Fe Ind es po filed worldwide in 2011. tat n d K tra SA exi Ko Jap do So It ,R rat rm Fra Af Is on Un C C a ian Ko ss Ru ng Ho Source: Online table 5.13. Europe & Central Asia: Container traffic picks up Container port traf c (millions of twenty-foot equivalent units) M easures of port container traffic, much of it commodity shipments  of medium to high value added, give some indication of a country’s 8 economic status, though much of the economic benefit from trans- shipments goes to the terminal operator and ancillary services for 6 ships and containers rather than to the country more broadly. After the 2008 fiscal crisis, worldwide container shipments fell to 472 million in 2009, an almost 9 percent drop from 2008, affecting 4 all ports, operators, and countries. But shipments rebounded in 2010, growing 15 percent and reaching precrisis levels. Most of the 2 growth came from intercontinental shipments by developing coun- tries. In 2011 the Russian Federation (3.8  million) and Turkey 2009 2011 (6.1 million) led the market in container shipments in Europe and 0 Lithuania Romania Russian Turkey Ukraine Central Asia. Federation Source: Online table 5.10. Latin America & Caribbean: Homicide rates mount Intentional homicides, 2011 or latest available (per 100,000 people) Homicide rates are very high in Latin America and the Caribbean and Saharan Africa, where they add to the death toll caused by armed Sub-­ 100 conflicts. According to the Geneva Declaration on Armed Violence and Development (2011), a quarter of all violent deaths occur in just 14 75 countries, averaging more than 30 violent deaths per 100,000 people a year, half of them in Latin America and the Caribbean. In many of 50 these countries, homicides, not armed conflicts, account for the majority of violent deaths. The links between violent death rates and 25 socioeconomic development show that homicide rates are higher where income disparity, extreme poverty, and hunger are high. Coun- 0 tries that have strengthened their rule of law have seen a decline in Gu aica uth o El uras e B Ja e itts ala vis ia da i o a r law homicide rates. Cô vado So bag r liz ad oth ric ,R mb i Ve ’Ivo an Ne m Be Af Ma ela m nd nid Les To St ate Za Ug l d & Sa Ho zu & te ne .K Tri Source: Online table 5.8. 80  World Development Indicators 2013 Front ? User guide World view People Environment Middle East & North Africa: Military spending share continues to rise Demanding open government and good governance from their head Military spending (% of GDP) of states, citizens of countries in the Middle East and North Africa 4 brought about the Arab Spring in late 2010 and 2011. Although it is still too soon to estimate the effects of the turbulent years, there 3 are signs of higher military spending and arms imports. From 2010 to 2011 all regions except the Middle East and North Africa reduced Algeria military spending as a share of gross domestic product (GDP). ­ 2 increased military spending from 3.5 percent of GDP in 2010 to 4.6 percent in 2011, and Tunisia from 1.2 percent of GDP in 2010 1 to 1.3 percent in 2011. Saudi Arabia (8.4 percent of GDP) and Israel (6.8 percent), both high-income economies, spend the most on the 2010 2011 military, followed by Iraq (5.1 percent), Jordan (4.7 percent), and Leba- 0 East Asia Europe Latin Middle East South Sub-Saharan non (4.4 percent). & Paci c & Central America & & North Asia Africa Asia Caribbean Africa Source: Online table 5.7. South Asia: Mobile phone access growing rapidly Mobile phone subscriptions have roughly doubled every two years Mobile phone subscriptions (per 100 people) since 2002 and now exceed the number of fixed-line subscriptions 150 in 2002. By the end of 2011 there were 5.9 billion mobile phone Europe & Central Asia subscriptions worldwide, almost one for every person if distributed equally. Developing economies have lagged behind, but they are catch- Latin America & Caribbean S aharan Africa, where 53 per 100 people have mobile ing up. Sub-­ 100 Middle East & North Africa phone subscriptions, started far behind but has reached the same High income subscription rate as high-income economies did 11 years ago. South Asia is only eight years behind. In recent years South Asia has had East Asia & Paci c 50 the largest growth in mobile subscription coverage among developing Sub-Saharan regions, with 69 mobile phone subscriptions per 100 people in 2011, Africa up from 8 in 2005. South Asia 0 2000 2002 2004 2006 2008 2010 2011 Source: Online table 5.11. Saharan Africa: Growth with good policies Sub-­ The World Bank’s Country Policy and Institutional Assessment (CPIA) Average GDP growth, 2006–11 (%) score reflects country performance in promoting economic growth 15 Saharan countries show a positive and reducing poverty. Data for Sub-­ association between average CPIA score and average GDP growth over 2006–11. In 2011 the region’s average CPIA score for International 10 Development Association countries was 3.2 on a scale of 1 (low) to 6 (high). The regional average masks the wide variation across coun- tries, from 2.2 in Eritrea and Zimbabwe to 4.0 in Cape Verde. For several countries the policy environment is the best in recent years. 5 Thirteen countries saw an improvement in the 2011 score by at least 0.1, 20 countries saw no change, and 5 saw a decline of 0.1 or more (World Bank 2012). 0 2.0 2.5 3.0 3.5 4.0 Average CPIA score, 2006–11 (1, low, to 6, high) Source: Online table 5.9. Economy States and markets Global links Back World Development Indicators 2013 81 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 central consumption subscriptionsa Interneta per 1,000 business by banking 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 2011 June 2012 2011 2011 2011 2011 2010 2011 2011 2011 Afghanistan 0.12 7 .. –2.9 8.7 4.7 .. 54 5 .. Albania 0.96 4 .. 69.1 .. 1.5 1,770 96 49 0.5 Algeria 0.19 25 .. –4.7 39.4b 4.6 1,026 99 14 0.2 American Samoa .. .. .. .. .. .. .. .. .. .. Andorra .. .. .. .. .. .. .. 75 81 .. Angola .. 68 .. 17.9 .. 3.5 248 48 15 .. Antigua and Barbuda .. 21 .. 101.4 .. .. .. 196 82 0.0 Argentina 0.46 26 9.8 31.3 .. 0.7 2,904 135 48 8.0 Armenia 1.12 8 0.4 36.0 17.0 4.0 1,606 104 32 2.6 Aruba .. .. .. .. .. .. .. 123 57 4.6 Australia 6.17 2 86.9 145.1 20.6b 1.9 10,286 108 79 13.0 Austria 0.56 25 19.7 135.3 18.4b 0.9 8,356 155 80 11.9 Azerbaijan 0.63 8 .. 20.0 12.7 4.9 1,603 109 50 1.3 Bahamas, The .. 31 .. 108.1 16.8 .. .. 86 65 0.0 Bahrain .. 9 89.0 75.2 .. 3.4 9,814 128 77 0.2 Bangladesh 0.10 19 21.0 70.4 10.0 1.3 279 56 5 .. Barbados .. 18 124.1 136.3 27.2 .. .. 127 72 13.7 Belarus 0.91 5 .. 34.4 16.3 1.1 3,564 112 40 2.6 Belgium 3.00 4 44.8 116.9 24.6b 1.1 8,388 117 78 10.0 Belize 4.54 44 .. 66.9 22.3 1.1 .. 70 14 0.4 Benin .. 26 .. 21.7 15.7b 1.0 90 85 4 0.5 Bermuda .. .. 26.6 .. .. .. .. 136 88 .. Bhutan 0.06 36 .. 49.2 9.2 .. .. 66 21 0.1 Bolivia 0.48 50 17.2 48.6 .. 1.5 616 83 30 13.7 Bosnia and Herzegovina 0.71 37 .. 57.7 20.9b 1.4 3,110 85 60 3.0 Botswana 9.44 61 23.7 7.1 20.8 2.1 1,586 143 7 0.9 Brazil 2.38 119 49.6 98.3 15.7 1.4 2,384 124 45 9.7 Brunei Darussalam .. 101 .. 8.1 .. 2.5 8,759 109 56 .. Bulgaria 7.20 18 15.4 71.4 19.1 1.5 4,476 141 51 7.5 Burkina Faso 0.11 13 .. 17.6 14.2b 1.3 .. 45 3 5.9 Burundi .. 8 .. 28.3 .. 2.7 .. 22 1 8.5 Cambodia 0.22 85 .. 24.2 10.0 b 1.5 146 96 3 0.1 Cameroon .. 15 .. 14.0 .. 1.4 271 52 5 4.9 Canada 7.56 5 109.8 177.6 11.9b 1.4 15,137 80 83 13.4 Cape Verde .. 11 .. 80.6 19.8 0.5 .. 79 32 0.6 Cayman Islands .. .. .. .. .. .. .. 168 69 .. Central African Republic .. 22 .. 25.4 .. 2.6 .. 41 2 0.0 Chad .. 62 .. 7.0 .. 2.3 .. 32 2 .. Channel Islands .. .. .. .. .. .. .. .. .. .. Chile 4.13 8 108.7 71.2 19.1b 3.2 3,297 130 54 4.6 China .. 33 46.3 145.5 10.5 2.0 c 2,944 73 38 25.8 b Hong Kong SAR, China 27.67 3 357.8 207.1 13.5 .. 5,923 215 75 13.7 Macao SAR, China .. .. .. –28.1 37.9b .. .. 243 58 0.0 Colombia 1.80 13 60.4 65.6 13.9b 3.3 1,012 98 40 4.3 Comoros .. 20 .. 21.2 .. .. .. 29 6 .. Congo, Dem. Rep. .. 58 .. 3.3 13.7 1.5 95 23 1 .. Congo, Rep. .. 161 .. –16.1 .. 1.1 145 94 6 3.7 82  World Development Indicators 2013 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 central consumption subscriptionsa Interneta per 1,000 business by banking 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 2011 June 2012 2011 2011 2011 2011 2010 2011 2011 2011 Costa Rica 17.64 60 3.5 53.3 13.8b .. 1,855 92 42 40.8 Côte d’Ivoire .. 32 26.1 25.3 ..b 1.5 210 86 2 15.1 Croatia 2.39 9 34.9 90.3 18.4 1.7 3,813 116 71 7.6 Cuba .. .. .. .. .. 3.3 1,299 12 23 .. Curaçao .. .. .. .. .. .. .. .. .. .. Cyprus 24.73 8 11.6 330.1 26.1b 2.2 4,675 98 58 27.3 Czech Republic 2.84 20 17.7 67.4 13.7 1.1 6,321 123 73 16.0 Denmark 4.55 6 53.8 205.4 33.8b 1.5 6,327 128 90 13.9 Djibouti .. 37 .. 32.3 .. 3.7 .. 21 7 0.1 Dominica 3.30 13 .. 57.9 .. .. .. 164 51 0.0 Dominican Republic 0.96 19 .. 43.8 12.7b 0.6 1,442 87 36 2.2 Ecuador .. 56 8.8 28.3 .. 3.5 1,055 105 31 3.2 Egypt, Arab Rep. 0.13 7 21.2 74.9 14.1 1.9 1,608 101 39 0.7 El Salvador 0.46 17 23.7 66.5 13.5b 1.0 855 134 18 5.8 Equatorial Guinea .. 135 .. –3.0 .. .. .. 59 6 .. Eritrea .. 84 .. 104.0 .. .. 52 4 6 .. Estonia 8.10 7 7.3 85.8 16.0 b 1.7 6,464 139 77 13.4 Ethiopia 0.03 15 .. 37.1 9.3 1.1 54 17 1 2.0 Faeroe Islands .. .. .. .. .. .. .. 122 81 0.6 Fiji .. 58 35.9 114.3 .. 1.6 .. 84 28 4.5 Finland 3.60 14 54.4 101.6 20.6b 1.5 16,483 166 89 9.3 France 3.13 7 56.6 133.5 21.3b 2.2 7,729 95 80 23.7 French Polynesia .. .. .. .. .. .. .. 81 49 15.8 Gabon 4.27 58 .. 12.2 .. 0.9 1,004 117 8 3.0 Gambia, The .. 27 .. 43.8 .. .. .. 79 11 3.3 Georgia 4.49 2 5.5 34.3 23.9 3.0 1,743 102 37 1.8 Germany 1.35 15 32.9 124.8 11.8b 1.3 7,215 132 83 15.0 Ghana 1.09 12 7.9 27.7 15.0 0.3 298 85 14 1.4 Greece 0.85 11 11.6 153.2 21.3b 2.8 5,242 106 53 9.7 Greenland .. .. .. .. .. .. .. 103 64 .. Grenada .. 15 .. 91.3 18.3 .. .. 117 33 11.1 Guam .. .. .. .. .. .. .. .. 51 .. Guatemala 0.64 40 .. 39.2 11.0 0.4 567 140 12 4.4 Guinea .. 35 .. 32.3 .. .. .. 44 1 0.1 Guinea-Bissau .. 9 .. 13.6 .. .. .. 56 3 .. Guyana .. 20 17.1 51.0 .. 1.2 .. 70 32 0.1 Haiti .. 105 .. 17.4 .. .. 24 41 8 .. Honduras .. 14 .. 53.3 15.0 b 1.1 671 104 16 1.3 Hungary 7.63 5 13.4 75.7 21.0 b 1.0 3,876 117 59 22.7 Iceland 7.94 5 14.4 148.2 22.3 0.1 51,440 106 95 20.9 India 0.09 27 54.2 74.1 10.4 2.5 616 72 10 6.9 Indonesia 0.27 47 46.1 38.5 11.8 0.7 641 103 18 8.3 Iran, Islamic Rep. .. 13 19.1 37.4 9.3 1.9 2,652 75 21 4.5 Iraq 0.11 74 .. –0.8 .. 5.1 1,183 78 5 .. Ireland 4.78 10 16.3 225.7 23.1b 0.6 6,025 108 77 21.2 Isle of Man 11.65 .. .. .. .. .. .. .. .. .. Israel 4.46 21 59.7 85.9 24.5b 6.8 6,856 122 70 14.0 Economy States and markets Global links Back World Development Indicators 2013 83 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 central consumption subscriptionsa Interneta per 1,000 business by banking 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 2011 June 2012 2011 2011 2011 2011 2010 2011 2011 2011 Italy 1.63 6 19.7 157.0 22.5b 1.6 5,384 158 57 7.4 Jamaica 1.10 7 50.0 49.6 25.6b 0.8 1,223 108 32 0.6 Japan 1.10 23 60.3 341.7 9.8b 1.0 8,394 105 80 17.5 Jordan 0.83 12 94.3 106.7 15.0 4.7 2,226 118 35 2.5 Kazakhstan 1.64 19 23.0 40.3 22.5 1.0 4,728 156 45 29.9 Kenya 0.85 32 30.3 52.0 19.9 1.5 156 67 28 5.7 Kiribati 0.11 31 .. .. .. .. .. 14 10 42.7 Korea, Dem. Rep. .. .. .. .. .. .. 749 4 0 .. Korea, Rep. 1.83 7 89.1 102.7 15.6 2.8 9,744 109 84 25.7 Kosovo 0.92 52 .. 20.8 .. .. 2,650 .. .. .. Kuwait .. 32 57.1 50.0 0.7 3.2 18,320 175 74 0.5 Kyrgyz Republic 0.95 10 2.7 .. 16.1 4.2 1,375 116 20 3.0 Lao PDR 0.10 92 .. 26.5 13.6 0.2 .. 87 9 .. Latvia 11.18 16 3.8 79.3 13.3 1.0 3,026 103 72 8.2 Lebanon .. 9 25.3 173.7 17.0 b 4.4 3,569 79 52 2.4 Lesotho 1.22 24 .. 0.7 58.9 2.4 .. 56 4 0.3 Liberia .. 6 .. 30.9 0.2 0.7 .. 49 3 .. Libya .. .. .. –65.9 .. 1.2 4,270 156 17 .. Liechtenstein 25.11 .. .. .. .. .. .. 102 85 .. Lithuania 2.18 20 9.5 57.5 13.4b 1.0 3,271 151 65 10.3 Luxembourg 7.31 19 114.2 172.4 24.3 .. 16,834 148 91 9.7 Macedonia, FYR 4.12 2 24.0 45.5 19.1 1.3 3,591 107 57 3.9 Madagascar 0.08 8 .. 11.7 13.0 b 0.7 .. 41 2 8.4 Malawi 0.08 39 24.6 38.0 .. .. .. 26 3 3.2 Malaysia 2.42 6 137.2 128.7 15.3 1.6 4,117 127 61 43.4 Maldives 3.09 9 .. 82.5 11.0 .. .. 166 34 .. Mali .. 8 .. 16.6 14.6 b 1.8 .. 68 2 2.4 Malta 9.52 40 38.5 159.2 27.7 0.7 4,151 125 69 47.2 Marshall Islands .. 17 .. .. .. .. .. .. 4 .. Mauritania .. 19 .. 42.4 .. 3.8 .. 94 5 .. Mauritius 7.88 6 58.1 110.0 18.4 0.1 .. 99 35 0.8 Mexico 0.87 9 35.4 45.5 .. 0.5 1,990 82 36 16.5 Micronesia, Fed. Sts. .. 16 .. –18.3 .. .. .. 25 20 .. Moldova 1.32 9 .. 39.5 18.3 0.3 1,049 105 38 6.3 Monaco .. .. .. .. .. .. .. 90 75 .. Mongolia .. 12 18.0 40.3 21.9 0.9 1,530 105 20 .. Montenegro 10.44 10 73.9 61.8 .. 2.0 5,547 185 40 .. Morocco 1.28 12 60.0 110.9 23.6b 3.3 781 113 51 7.7 Mozambique .. 13 .. 25.0 .. 0.9 444 33 4 26.5 Myanmar .. .. .. .. .. .. 131 3 1 0.0 Namibia .. 66 9.2 50.9 .. 3.4 1,479 96 12 1.6 Nepal .. 29 24.0 66.6 13.2 1.4 93 44 9 0.3 Netherlands 3.20 5 71.1 211.4 21.7b 1.4 7,010 115 92 19.8 New Caledonia .. .. .. .. .. .. .. 89 50 15.4 New Zealand 14.53 1 44.9 155.8 27.5b 1.1 9,566 109 86 9.3 Nicaragua .. 39 .. 46.1 15.2 0.6 473 82 11 5.3 Niger 0.00 17 .. 14.7 .. 0.9 .. 30 1 4.5 84  World Development Indicators 2013 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 central consumption subscriptionsa Interneta per 1,000 business by banking 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 2011 June 2012 2011 2011 2011 2011 2010 2011 2011 2011 Nigeria 0.83 34 16.1 37.5 0.3 1.0 136 59 28 1.1 Northern Mariana Islands .. .. .. .. .. .. .. .. .. .. Norway 4.94 7 45.1 .. 28.4b 1.6 25,175 116 94 18.5 Oman 1.67 8 27.5 32.3 2.2 6.0 5,933 169 68 2.6 Pakistan 0.03 21 15.6 43.3 9.3 3.0 457 62 9 1.8 Palau .. 28 .. .. .. .. .. 75 .. .. Panama 0.08 7 39.9 104.9 .. .. 1,832 189 43 35.4 Papua New Guinea .. 51 69.6 27.8 .. 0.5 .. 34 2 .. Paraguay .. 35 4.0 34.7 13.2 1.1 1,134 99 24 7.3 Peru 2.54 26 44.8 18.7 15.9 1.2 1,106 110 37 6.2 Philippines 0.19 36 73.6 51.8 12.3 1.1 643 99 29 46.4 Poland 0.52 32 26.9 66.2 17.0 b 1.9 3,783 131 65 5.9 Portugal 3.92 5 26.0 204.1 21.5b 2.0 4,929 115 55 3.5 Puerto Rico .. 6 .. .. .. .. .. 83 48 .. Qatar .. 9 72.5 70.2 14.4 2.2 14,997 123 86 0.0 Romania 4.41 10 11.2 52.1 17.2b 1.1 2,392 109 44 10.2 Russian Federation 0.83 18 42.9 39.5 15.4b 3.9 6,431 179 49 8.0 Rwanda 0.78 3 .. .. .. 1.2 .. 41 7 3.4 Samoa 1.37 9 .. 47.3 .. .. .. 91 7 0.2 San Marino .. .. .. .. 22.3 .. .. 112 50 .. São Tomé and Príncipe 2.56 7 .. 39.5 .. .. .. 68 20 14.0 Saudi Arabia .. 21 58.7 –4.8 .. 8.4 7,967 191 48 0.7 Senegal 0.19 5 .. 31.5 .. 1.6 195 73 18 0.6 Serbia 1.66 12 18.3 54.1 20.5 2.1 4,359 125 42 .. Seychelles .. 39 .. 45.8 31.7 0.9 .. 146 43 3.4 Sierra Leone 0.38 12 .. 12.9 11.1 0.9 .. 36 0 .. Singapore 8.45 3 128.6 93.6 14.1 3.6 8,307 150 71 45.2 Sint Maarten .. .. .. .. .. .. .. .. .. .. Slovak Republic 4.81 16 4.9 54.1 12.7b 1.1 5,164 109 74 7.1 Slovenia 4.04 6 12.8 94.7 17.9 1.4 6,521 107 72 5.9 Solomon Islands .. 9 .. 15.0 .. .. .. 50 6 .. Somalia .. .. .. .. .. .. .. 7 1 .. South Africa 0.77 19 209.6 175.0 25.7b 1.3 4,803 127 21 5.1 South Sudan 0.31 .. .. .. .. 2.9 .. .. .. .. Spain 2.59 28 69.8 230.9 9.5b 1.0 6,155 113 68 6.4 Sri Lanka 0.58 7 32.8 46.2 12.4 2.6 449 87 15 1.0 St. Kitts and Nevis 5.69 19 85.8 123.3 19.7 .. .. 153 76 0.1 St. Lucia 3.00 15 .. 114.6 .. .. .. 123 42 16.9 St. Martin .. .. .. .. .. .. .. .. .. .. St. Vincent and Grenadines .. 10 .. 56.6 22.2 .. .. 121 43 0.0 Sudan .. 36 .. 23.0 .. .. 141 56 19 29.4 Suriname 1.02 694 .. 24.1 .. .. .. 179 32 6.5 Swaziland .. 56 .. 25.8 .. 3.0 .. 64 18 .. Sweden 7.17 16 87.1 142.3 21.9b 1.3 14,939 119 91 13.3 Switzerland 2.52 18 141.4 185.1 10.4 0.8 8,175 131 85 24.4 Syrian Arab Republic 0.05 13 .. 47.7 .. 3.9 1,905 63 23 1.3 Tajikistan 0.29 24 .. .. .. .. 2,004 91 13 .. Economy States and markets Global links Back World Development Indicators 2013 85 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 central consumption subscriptionsa Interneta per 1,000 business by banking 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 2011 June 2012 2011 2011 2011 2011 2010 2011 2011 2011 Tanzania .. 26 6.4 24.2 .. 1.1 78 56 12 5.4 Thailand 0.59 29 77.7 159.0 17.6b 1.6 2,243 112 24 20.7 Timor-Leste .. 94 .. –26.5 .. 2.6 .. 53 1 .. Togo 0.11 38 .. 35.4 17.1b 1.6 107 50 4 0.2 Tonga 1.96 16 .. 29.0 .. .. .. 53 25 0.0 Trinidad and Tobago .. 41 65.5 32.3 26.2 .. 5,894 136 55 0.1 Tunisia 0.63 11 20.8 82.1 20.9 1.3 1,350 117 39 5.6 Turkey 0.96 6 26.0 69.3 20.1b 2.3 2,477 89 42 1.8 Turkmenistan .. .. .. .. .. .. 2,403 69 5 .. Turks and Caicos Islands .. .. .. .. .. .. .. .. .. 2.1 Tuvalu .. .. .. .. .. .. .. 22 30 .. Uganda 0.72 33 46.0 18.7 16.1 1.6 .. 48 13 21.9 Ukraine 0.60 22 15.5 73.4 18.3 2.5 3,550 123 31 4.4 United Arab Emirates 1.37 8 26.0 81.4 .. 5.4 11,044 149 70 3.2 United Kingdom 10.41 13 118.7 212.6 27.4b 2.6 5,733 131 82 21.3 United States .. 6 104.3 234.9 10.1b 4.7 13,394 93 78 18.1 Uruguay 3.36 7 0.4 29.9 19.6 1.9 2,763 141 51 5.8 Uzbekistan 0.82 12 .. .. .. .. 1,648 92 30 .. Vanuatu 2.18 35 .. 70.5 .. .. .. 56 8 .. Venezuela, RB .. 144 1.6 29.3 .. 0.8 3,287 98 40 2.5 Vietnam .. 34 14.8 120.7 .. 2.2 1,035 143 35 8.6 Virgin Islands (U.S.) .. .. .. .. .. .. .. .. 27 .. West Bank and Gaza .. 48 .. .. .. .. .. 46 41 .. Yemen, Rep. .. 40 .. 22.7 .. 4.4 249 47 15 0.3 Zambia 1.26 17 20.9 18.0 16.6 1.6 623 61 12 24.8 Zimbabwe .. 90 112.9 .. .. 1.6 1,022 72 16 1.0 World 3.42 u 30 u 68.7 w 164.9 w 14.8 w 2.5 w 2,975 w 85 w 33 w 17.6 w Low income 0.32 30 .. 40.4 11.6 1.6 242 42 6 .. Middle income 2.30 35 47.7 92.4 13.2 2.0 1,823 86 27 17.1 Lower middle income 1.01 31 43.2 58.9 11.9 2.0 698 80 16 9.3 Upper middle income 3.50 40 48.8 101.3 13.6 2.0 2,942 92 38 18.6 Low & middle income 2.01 34 47.4 91.6 13.2 2.0 1,661 80 24 17.0 East Asia & Pacific 1.04 37d 50.6 132.5 10.9 1.8 2,337 81 34 26.0 Europe & Central Asia 2.82 15d 32.9 49.2 17.1 3.0 4,059 132 42 6.3 Latin America & Carib. 2.84 58d 42.0 68.5 .. 1.3 1,973 107 39 10.9 Middle East & N. Africa 0.36 25d .. 53.6 23.8 3.5 1,658 89 27 2.9 South Asia 0.16 19d 48.2 69.7 10.3 2.5 555 69 9 6.4 Sub-­Saharan Africa 1.99 32d .. 74.7 .. 1.5 553 53 13 2.8 High income 6.38 18 78.6 203.2 14.6 2.8 9,415 114 76 17.9 Euro area 5.10 13 41.9 153.5 17.6 1.5 6,847 125 73 14.9 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. Differs from data reported on the Doing Business website because the regional aggregates on the Doing Business website include developed economies. 86  World Development Indicators 2013 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 2012 Entrepreneurship Data- business has full information on what is required and does not waste base, which includes indicators for more than 150 countries for time when completing procedures. In constructing the indicators, it is 2004–11. Survey data are used to analyze firm creation, its relation- assumed that entrepreneurs know about all regulations and comply ship to economic growth and poverty reduction, and the impact of with them. In practice, entrepreneurs may not be aware of all required regulatory and institutional reforms. Data on total registered busi- procedures or may avoid legally required procedures altogether. nesses were collected from national registrars of companies. For cross-country comparability, only limited liability corporations that Financial systems operate in the formal sector are included. For additional information Stock markets and banking systems both enhance growth, the main on sources, methodology, calculation of entrepreneurship rates, factor in poverty reduction. At low levels of economic development com- and data limitations see http://www.doingbusiness.org/data/ mercial banks tend to dominate the financial system, while at higher exploretopics/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 ited by conceptual and statistical weaknesses, such as inaccurate that uses a simple business case to ensure comparability across reporting and differences in accounting standards. economies and over time—with assumptions about the legal form Standard & Poor’s (S&P) Indices provides regular updates on 21 of the business, its size, its location, and nature of its operation. emerging stock markets and 36 frontier markets. The S&P Global Surveys in 185 countries are administered through more than 9,000 Equity Indices, S&P Indices’s leading emerging markets index, is local 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 2006; 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 banking 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 banking survey of the Interna- ment of judgment by the expert respondents. When sources indicate tional Monetary Fund’s (IMF) International Financial Statistics or, when Economy States and markets Global links Back World Development Indicators 2013 87 5  States and markets unavailable, from its monetary survey. The monetary survey includes data are not always comparable across countries. However, SIPRI puts monetary authorities (the central bank), deposit money banks, and a high priority on ensuring that the data series for each country is com- other banking institutions, such as finance companies, development parable over time. More information on SIPRI’s military expenditure banks, and savings and loan institutions. In a few countries govern- project can be found at www.sipri.org/research/armaments/milex. ments may hold international reserves as deposits in the banking system rather than in the central bank. Claims on the central gov- Infrastructure ernment are a net item (claims on the central government minus The quality of an economy’s infrastructure, including power and com- central government deposits) and thus may be negative, resulting in munications, is an important element in investment decisions and a negative value for domestic credit provided by the banking sector. economic development. The International Energy Agency (IEA) collects data on electric power consumption from national energy agencies Tax revenues and adjusts the values to meet international definitions. Consump- Taxes are the main source of revenue for most governments. Tax tion by auxiliary stations, losses in transformers that are considered revenue as a share of GDP provides a quick overview of the fiscal integral parts of those stations, and electricity produced by pumping obligations and incentives facing the private sector across coun- installations are included. Where data are available, electricity gen- tries. The table shows only central government data, which may erated by primary sources of energy—coal, oil, gas, nuclear, hydro, significantly understate the total tax burden, particularly in countries geothermal, wind, tide and wave, and combustible renewables—are where provincial and municipal governments are large or have con- included. Consumption data do not capture the reliability of supplies, siderable tax authority. including breakdowns, load factors, and frequency of outages. Low ratios of tax revenue to GDP may reflect weak administration and The International Telecommunication Union (ITU) estimates that large-scale tax avoidance or evasion. Low ratios may also reflect a there were 5.9 billion mobile subscriptions globally in 2011. No sizable parallel economy with unrecorded and undisclosed incomes. technology has ever spread faster around the world. Mobile com- Tax revenue ratios tend to rise with income, with higher income coun- munications have a particularly important impact in rural areas. tries relying on taxes to finance a much broader range of social The mobility, ease of use, flexible deployment, and relatively low services and social security than lower income countries are able to.
 and declining rollout costs of wireless technologies enable them to reach rural populations with low levels of income and literacy. The Military expenditures next billion mobile subscribers will consist mainly of the rural poor. Although national defense is an important function of government, Operating companies have traditionally been the main source of high expenditures for defense or civil conflicts burden the economy telecommunications data, so information on subscriptions has been and may impede growth. Military expenditures as a share of GDP widely available for most countries. This gives a general idea of access, are a rough indicator of the portion of national resources used for but a more precise measure is the penetration rate—the share of military activities. As an “input� measure, military expenditures are households with access to telecommunications. During the past few not directly related to the “output� of military activities, capabilities, years more information on information and communication technology or security. Comparisons across countries should take into account use has become available from household and business surveys. Also many factors, including historical and cultural traditions, the length important are data on actual use of telecommunications services. The of borders that need defending, the quality of relations with neigh- quality of data varies among reporting countries as a result of differ- bors, and the role of the armed forces in the body politic. ences in regulations covering data provision and availability. Data are from the Stockholm International Peace Research Institute (SIPRI), whose primary source of military expenditure data is offi- High-technology exports cial data provided by national governments. These data are derived The method for determining high-technology exports was developed from budget documents, defense white papers, and other public by the Organisation for Economic Co-operation and Development in documents from official government agencies, including govern- collaboration with Eurostat. It takes a “product approach� (rather than ment responses to questionnaires sent by SIPRI, the United Nations a “sectoral approach�) based on research and development intensity Office for Disarmament Affairs, or the Organization for Security and (expenditure divided by total sales) for groups of products from Ger- ­ Co-operation in Europe. Secondary sources include international sta- many, Italy, Japan, the Netherlands, Sweden, and the United States. tistics, such as those of the North Atlantic Treaty Organization (NATO) Because industrial sectors specializing in a few high-technology prod- and the IMF’s Government Finance Statistics Yearbook. Other second- ucts may also produce low-technology products, the product approach ary sources include country reports of the Economist Intelligence Unit, is more appropriate for international trade. The method takes only country reports by IMF staff, and specialist journals and newspapers. research and development intensity into account, but other characteris- In the many cases where SIPRI cannot make independent estimates, tics of high technology are also important, such as knowhow, scientific it uses country-provided data. Because of differences in definitions personnel, and technology embodied in patents. Considering these and the difficulty of verifying the accuracy and completeness of data, characteristics would yield a different list (see Hatzichronoglou 1997). 88  World Development Indicators 2013 Front ? User guide view People World view People Environment States and markets  5 Definitions telepoint, radio paging, and telemetry services. • Individuals using • Business entry density is the number of newly registered lim- the Internet are the percentage of individuals who have used the ited liability corporations per 1,000 people ages 15–64. • Time Internet (from any location) in the last 12 months. Internet can required to start a business is the number of calendar days to com- be used via a computer, mobile phone, personal digital assistant, plete the procedures for legally operating a business using the fast- games machine, digital television, or similar device. • High-tech - est procedure, independent of cost. • Stock market capitalization nology exports are products with high research and development (also known as market value) is the share price times the number of intensity, such as in aerospace, computers, pharmaceuticals, sci- shares outstanding. • Domestic credit provided by banking sector entific instruments, and electrical machinery. is all credit to various sectors on a gross basis, except to the central government, which is net. The banking sector includes monetary Data sources authorities, deposit money banks, and other banking institutions Data on business entry density are from the World Bank’s Entrepre- for which data are available. • Tax revenue collected by central neurship Database (www.doingbusiness.org/data/exploretopics/ government is compulsory transfers to the central government for entrepreneurship). Data on time required to start a business are public purposes. Certain compulsory transfers such as fines, penal- from the World Bank’s Doing Business project (www.doingbusiness ties, and most social security contributions are excluded. Refunds .org). Data on stock market capitalization are from Standard & and corrections of erroneously collected tax revenue are treated as Poor’s (2012). Data on domestic credit are from the IMF’s Inter- negative revenue. The analytic framework of the IMF’s Government national Financial Statistics. Data on central government tax rev- Finance Statistics Manual 2001 (GFSM 2001) is based on accrual enue are from the IMF’s Government Finance Statistics. Data on accounting and balance sheets. For countries still reporting govern- military expenditures are from SIPRI’s Military Expenditure Database ment finance data on a cash basis, the IMF adjusts reported data to (www.sipri.org/databases/milex). Data on electricity consumption the GFSM 2001 accrual framework. These countries are footnoted are from the IEA’s Energy Statistics of Non-OECD Countries, Energy in the table. • Military expenditures are SIPRI data derived from Balances of Non-OECD Countries, and Energy Statistics of OECD NATO’s former definition (in use until 2002), which includes all cur- Countries and from the United Nations Statistics Division’s Energy rent and capital expenditures on the armed forces, including peace- Statistics Yearbook. Data on mobile cellular phone subscriptions keeping forces; defense ministries and other government agencies and individuals using the Internet are from the ITU’s World Tele- engaged in defense projects; paramilitary forces, if judged to be communication/ICT Indicators database and TeleGeography. Data trained and equipped for military operations; and military space on high-technology exports are from the United Nations Statistics activities. Such expenditures include military and civil personnel, Division’s Commodity Trade (Comtrade) database. including retirement pensions and social services for military per- sonnel; operation and maintenance; procurement; military research References and development; and military aid (in the military expenditures of Beck, Thorsten, and Ross Levine. 2001. “Stock Markets, Banks, and the donor country). Excluded are civil defense and current expendi- Growth: Correlation or Causality?� Policy Research Working Paper tures for previous military activities, such as for veterans bene�ts, 2670, World Bank, Washington, DC. demobilization, and weapons conversion and destruction. This defi- Claessens, Stijn, Daniela Klingebiel, and Sergio L. Schmukler. 2002. nition cannot be applied for all countries, however, since that would “Explaining the Migration of Stocks from Exchanges in Emerging require more detailed information than is available about military Economies to International Centers.� Policy Research Working Paper budgets and off-budget military expenditures (for example, whether 2816, World Bank, Washington, DC. military budgets cover civil defense, reserves and auxiliary forces, Demirgüç-Kunt, Asli, and Ross Levine. 1996. “Stock Market Devel- police and paramilitary forces, and military pensions). • Electric opment and Financial Intermediaries: Stylized Facts.� World Bank power consumption per capita is the production of power plants Economic Review 10 (2): 291–321. and combined heat and power plants less transmission, distribu- Geneva Declaration on Armed Violence and Development. 2011. tion, and transformation losses and own use by heat and power Global Burden of Armed Violence. Geneva. plants, divided by midyear population. • Mobile cellular subscrip - Hatzichronoglou, Thomas. 1997. “Revision of the High-Technology tions are the number of subscriptions to a public mobile telephone Sector and Product Classification.� STI Working Paper 1997/2. service that provides access to the public switched telephone net- Organisation for Economic Co-operation and Development, Direc- work using cellular technology. Postpaid subscriptions and active torate for Science, Technology, and Industry, Paris. prepaid accounts (that is, accounts that have been used during Standard & Poors. 2012. Global Stock Markets Factbook 2012. New York. the last three months) are included. The indicator applies to all WIPO (World Intellectual Property Organization). 2012. World Intel- mobile cellular subscriptions that offer voice communications and lectual Property Indicators 2012. Geneva. excludes subscriptions for data cards or USB modems, subscrip- World Bank. 2012. CPIA Africa: Accessing Africa’s Policies and Institu- tions to public mobile data services, private-trunked mobile radio, tions. Washington, DC. Economy States and markets Global links Back World Development Indicators 2013 89 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 S&P/Global Equity Indices CM.MKT.INDX.ZG Telecommunications investment IE.PPI.TELE.CD Energy investment IE.PPI.ENGY.CD 5.5 Financial access, stability, and efficiency Transport investment IE.PPI.TRAN.CD Strength of legal rights index IC.LGL.CRED.XQ Water and sanitation investment IE.PPI.WATR.CD Depth of credit information index IC.CRD.INFO.XQ Domestic credit to private sector FS.AST.PRVT.GD.ZS Depositors with commercial banks FB.CBK.DPTR.P3 Businesses registered, New IC.BUS.NREG Borrowers from commercial banks FB.CBK.BRWR.P3 Businesses registered, Entry density IC.BUS.NDNS.ZS Commercial bank branches FB.CBK.BRCH.P5 Automated teller machines FB.ATM.TOTL.P5 5.2 Business environment: enterprise surveys Bank capital to assets ratio FB.BNK.CAPA.ZS Time dealing with officials IC.GOV.DURS.ZS Ratio of bank non-performing loans to total Average number of times meeting with tax gross loans FB.AST.NPER.ZS officials IC.TAX.METG Domestic credit provided by banking sector FS.AST.DOMS.GD.ZS Time required to obtain operating license IC.FRM.DURS Interest rate spread FR.INR.LNDP Informal payments to public officials IC.FRM.CORR.ZS Risk premium on lending FR.INR.RISK Losses due to theft, robbery, vandalism, and arson IC.FRM.CRIM.ZS 5.6 Tax policies Firms competing against unregistered firms IC.FRM.CMPU.ZS Tax revenue collected by central government GC.TAX.TOTL.GD.ZS Firms with female top manager IC.FRM.FEMM.ZS Number of tax payments by businesses IC.TAX.PAYM Firms using banks to finance investment IC.FRM.BNKS.ZS Time for businesses to prepare, file and Value lost due to electrical outages IC.FRM.OUTG.ZS pay taxes IC.TAX.DURS Internationally recognized quality Business profit tax IC.TAX.PRFT.CP.ZS certification ownership IC.FRM.ISOC.ZS Business labor tax and contributions IC.TAX.LABR.CP.ZS Average time to clear exports through customs IC.CUS.DURS.EX Other business taxes IC.TAX.OTHR.CP.ZS Firms offering formal training IC.FRM.TRNG.ZS Total business tax rate IC.TAX.TOTL.CP.ZS 5.3 Business environment: Doing Business indicators 5.7 Military expenditures and arms transfers Number of procedures to start a business IC.REG.PROC Military expenditure, % of GDP MS.MIL.XPND.GD.ZS Time required to start a business IC.REG.DURS Military expenditure, % of central Cost to start a business IC.REG.COST.PC.ZS 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 5.8 Fragile situations Number of procedures to enforce a contract IC.LGL.PROC International Development Association Time required to enforce a contract IC.LGL.DURS Resource Allocation Index IQ.CPA.IRAI.XQ Business disclosure index IC.BUS.DISC.XQ Peacekeeping troops, police, and military Time required to resolve insolvency IC.ISV.DURS observers VC.PKP.TOTL.UN Battle related deaths VC.BTL.DETH 5.4 Stock markets Intentional homicides VC.IHR.PSRC.P5 Market capitalization, $ CM.MKT.LCAP.CD Military expenditures MS.MIL.XPND.GD.ZS Market capitalization, % of GDP CM.MKT.LCAP.GD.ZS Losses due to theft, robbery, vandalism, Value of shares traded CM.MKT.TRAD.GD.ZS and arson IC.FRM.CRIM.ZS Turnover ratio CM.MKT.TRNR Firms formally registered when operations Listed domestic companies CM.MKT.LDOM.NO started IC.FRM.FREG.ZS 90  World Development Indicators 2013 Front ? User guide view People 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 Depth of food deficit SN.ITK.DFCT traffic ..a Primary gross enrollment ratio SE.PRM.ENRR Population covered by mobile cellular network ..a Fixed telephone sub-basket ..a 5.9 Public policies and institutions Mobile cellular sub-basket ..a International Development Association Telecommunications revenue ..a Resource Allocation Index IQ.CPA.IRAI.XQ Mobile cellular and fixed-line subscribers Macroeconomic management IQ.CPA.MACR.XQ per employee ..a Fiscal policy IQ.CPA.FISP.XQ Debt policy IQ.CPA.DEBT.XQ 5.12 The information age Economic management, Average IQ.CPA.ECON.XQ Households with television ..a Trade IQ.CPA.TRAD.XQ Households with a computer ..a Financial sector IQ.CPA.FINS.XQ Individuals using the Internet ..a Business regulatory environment IQ.CPA.BREG.XQ Fixed (wired) broadband Internet Structural policies, Average IQ.CPA.STRC.XQ subscriptions IT.NET.BBND.P2 Gender equality IQ.CPA.GNDR.XQ International Internet bandwidth ..a Equity of public resource use IQ.CPA.PRES.XQ Fixed broadband sub-basket ..a Building human resources IQ.CPA.HRES.XQ Secure Internet servers IT.NET.SECR.P6 Social protection and labor IQ.CPA.PROT.XQ Information and communications technology goods, Exports TX.VAL.ICTG.ZS.UN Policies and institutions for environmental sustainability IQ.CPA.ENVR.XQ Information and communications technology goods, Imports TM.VAL.ICTG.ZS.UN Policies for social inclusion and equity, Average IQ.CPA.SOCI.XQ Information and communications Property rights and rule-based governance IQ.CPA.PROP.XQ technology services, Exports BX.GSR.CCIS.ZS Quality of budgetary and financial management IQ.CPA.FINQ.XQ Efficiency of revenue mobilization IQ.CPA.REVN.XQ 5.13 Science and technology Quality of public administration IQ.CPA.PADM.XQ Research and development (R&D), Researchers SP.POP.SCIE.RD.P6 Transparency, accountability, and Research and development (R&D), Technicians SP.POP.TECH.RD.P6 corruption in the public sector IQ.CPA.TRAN.XQ Scientific and technical journal articles IP.JRN.ARTC.SC Public sector management and institutions, Expenditures for R&D GB.XPD.RSDV.GD.ZS Average IQ.CPA.PUBS.XQ High-technology exports, $ TX.VAL.TECH.CD 5.10 Transport services High-technology exports, % of manufactured exports TX.VAL.TECH.MF.ZS Total road network IS.ROD.TOTL.KM Charges for the use of intellectual property, Paved roads IS.ROD.PAVE.ZS Receipts BX.GSR.ROYL.CD Road passengers carried IS.ROD.PSGR.K6 Charges for the use of intellectual property, Road goods hauled IS.ROD.GOOD.MT.K6 Payments BM.GSR.ROYL.CD Rail lines IS.RRS.TOTL.KM Patent applications filed, Residents IP.PAT.RESD Railway passengers carried IS.RRS.PASG.KM Patent applications filed, Nonresidents IP.PAT.NRES Railway goods hauled IS.RRS.GOOD.MT.K6 Trademark applications filed, Total IP.TMK.TOTL Port container traffic IS.SHP.GOOD.TU Registered air carrier departures worldwide IS.AIR.DPRT Data disaggregated by sex are available in the World Development Indicators database. Air passengers carried IS.AIR.PSGR a. Available online only as part of the table, not as an individual indicator. Economy States and markets Global links Back World Development Indicators 2013 91 GLOBAL LINKS 92  World Development Indicators 2013 Front ? User guide World view People Environment 6 The world economy is bound together by trade Global foreign direct investment (FDI) rose in goods and services, financial flows, and the 22.7 percent in 2011, to its pre-crisis level. movement of people. As national economies Some 40 percent of those investments were develop, their links expand and grow more com- directed to developing economies. In 2011 plex. The indicators in this section measure the many developing countries continued to imple- size and direction of these flows and document ment policy changes to further liberalize and the effects of policy interventions and aid flows facilitate FDI entry and operations and to regu- on the world economy. late FDI. The largest recipients of FDI inflows The optimistic economic momentum at the were Brazil, China, India, and the Russian beginning of 2011 slowed over the course of the Federation, accounting for more than half of year. The adverse effects of the tsunami in Japan inflows to developing economies. China was coupled with intensification of the sovereign debt the largest recipient, with net FDI inflows of crisis in the euro area shook confidence at the $220 billion, a decline of 10 percent compared global level. The slowdown became more pro- with 2010. nounced in high-income economies, reducing the In 2011 world merchandise exports to devel- growth in capital inflows to developing countries. oping countries increased 27 percent from 2010, Net debt and equity inflows to developing econ- while exports to high-income countries increased omies in 2011 were $1.1 trillion—or 8 percent 20 percent. Brazil, China, India, and the Rus- lower than in 2010 and below the level reached sian Federation were among the top traders, with before the global financial crisis. The downturn China accounting for 70 percent of East Asia and was driven by the collapse of portfolio equity, Pacific’s merchandise trade. again the most volatile of capital flows. Equity Official development assistance, a stable flows to emerging markets with good growth pros- source of development financing and buffer pects, such as China, Brazil, and India, dropped against the impact of several financial crises, substantially. Low- and middle-income economies was $134 billion in 2011, or 0.58 percent of recorded net inflows of only $8.3 billion in 2011, developing countries’ combined gross national compared with $130 billion in 2010. income, down from 0.65 percent in 2010. Debt net inflows to developing countries in Worldwide tourism continues to grow and 2011 were $437 billion—down 9 percent from has become one of the largest and fastest 2010. The slowdown was led by a drop in lending growing economic sectors in the world. The by official creditors from $77 billion in 2010 to number of international tourist arrivals in 2011 $30 billion in 2011. However, commercial bank reached a record high of over 1 billion, and financing tripled to $110 billion, and the pri- inbound tourism expenditures increased 12 per- vate sector created more liquidity through bond cent to $1.3 trillion from 2010. The only devel- issuances, reaching their highest stock level oping region that saw a drop in tourist arrivals of $1.5 trillion. Net inflows of short-term debt in 2011 was the Middle East and North Africa, shrank 27 percent in 2011 after being the fast- due to political instability and armed conflict in est growing debt component the previous year. the region. Economy States and markets links Back Global links Back World Development Indicators 2013 93 Highlights East Asia & Pacific: Equity investment drops Equity in ows to East Asia and Paci c ($ billions) After recovering from a 2009 low by 2010, equity investment in East  Asia and Pacific fell again in 2011. Turmoil in the euro area and the 300 Foreign direct investment natural disaster in Japan caused a large withdrawal of foreign equity. 250 Foreign direct investment (FDI) net inflows combined with portfolio equity inflows in 2011 were 17 percent lower than in 2010. Net FDI 200 flows declined 5 percent, while portfolio equity inflows fell to a fifth 150 their 2010 level. China, the largest recipient of capital flows into the region (with 80 percent), recorded a 10 percent decline of FDI inflows 100 compared with 2010 and portfolio equity inflows a sixth of their 2010 50 level. Investments in the service sector in China maintained their growth rate. 0 Portfolio equity –50 2000 2002 2004 2006 2008 2010 2011 Source: Online table 6.10. Europe & Central Asia: Remittance flows diverge Remittance in ows ($ billions) High unemployment in the developed countries of the European Union impaired employment prospects of existing migrants and limited their 30 ability to send money home. Remittance flows to developing countries 25 in Eastern Europe dropped sharply in 2009 and have yet to recover. Commonwealth of Independent States Romania, one of the largest recipients of remittances in the European 20 Union, experienced an annual average decrease of 30 percent over the last three years. In contrast, remittances to almost all the member 15 countries of the Commonwealth of Independent States rebounded Eastern Europe strongly. Rising employment and higher real wages in the Russian 10 Federation gave migrants the opportunity to increase their remit- tances. Tajikistan, with the most emigrants to the Russian Federation, 5 depends on remittances as a major source of external finance. In 0 2011 it received $3.2 billion in remittances, equivalent to 46 percent 2002 2004 2006 2008 2010 2011 of GDP. Source: Online table 6.14. Latin America & Caribbean: More trade with developing countries Share of total merchandise exports (%) Trade between developing countries continues to grow. Between 2000  and 2010 merchandise exports between developing countries grew 80 Developing countries to more than 600 percent, while developing country exports to high-income high-income countries countries grew half that amount. By 2011 a third of developing country Brazil to high-income countries 60 trade went to other developing countries, while the share of merchan- dise exports from developing countries to high-income countries fell from 77 percent in 2000 to about 63 percent. In Latin America and the Brazil to developing countries 40 Caribbean, Brazil is a leading example. Since 2009 Brazil’s merchandise exports to developing countries have exceeded those to high-income Developing countries to developing countries countries—largely due to Brazil’s increased natural resource exports to 20 Asia, particularly to China. In addition, intraregional trade has increased since 2009, especially between Common Market of the South members 0 (Argentina, Brazil, Paraguay, Uruguay, and Venezuela), surpassing the 2000 2002 2004 2006 2008 2010 2011 level reached before the global financial crisis. Source: Online table 6.4. 94  World Development Indicators 2013 Front ? User guide World view People Environment Middle East & North Africa: Tourist arrivals fall due to instability Despite increased worldwide tourism, tourist arrivals fell in the International tourist arrivals (millions) Middle East and North Africa in 2011 due to political instability and 80 armed conflict in the region (World Tourism Organization 2012b). “The Arab Spring,� as it has come to be known, began in Tuni- sia with mass demonstrations and riots at the end of 2010. As a 60 result, international tourist arrivals to Tunisia fell 31 percent, from 6.9 million in 2010 to 4.8 million in 2011, the lowest level since 40 1998, and tourist expenditures fell from $3.5 billion to $2.5 bil- lion. In February 2011 Egypt’s government was overthrown. Egypt experienced a 32 percent drop in tourist arrivals in 2011 after an 20 18 percent increase in 2010. Heavily dependent on tourism, it saw tourist expenditures fall from $51.2 billion in 2010 to $43.1 billion 2009 2010 2011 in 2011. 0 Middle East & North Africa Egypt Tunisia Source: Online table 6.15. South Asia: Encouraging investment in China and India China and India, the two largest and fastest growing economies in Net in ows of foreign direct investment (% of GDP) the developing world, have altered their regulatory systems to attract 5 and keep inflows of foreign direct investment (FDI). China started first. It began opening its economy in 1979 and continued through to China 4 its membership in the World Trade Organization in 2001, reassuring investors of its increasing reliability. While FDI in China was driven by 3 export-oriented policies, India pursued an import substitution policy, promoting domestic firms and limiting the rights of foreign investors. It was not until the 1990s that India started significantly liberalizing 2 FDI, and it only recently liberalized the FDI policies of its retail sector. India Before the financial crisis net FDI inflows as a share of GDP to India 1 began to catch up with those to China. After bottoming out in 2010, they began to recover, while net FDI inflows as a share of GDP to China 0 2000 2002 2004 2006 2008 2010 2011 dropped again. Source: Online table 6.10. Saharan Africa: Less official development assistance in 2011 Sub-­ Saharan Africa as a share of Official development assistance to Sub-­ Net of cial development assistance from all donors (% of GNI) the region’s gross national income fell in 2011. But aid to three of the 150 five largest recipients, the Democratic Republic of Congo, São Tomé and Príncipe, and Rwanda, rose. The Democratic Republic of Congo was second among all countries receiving aid from Development Assistance Committee (DAC) members (after Afghanistan). But this distinction is 100 likely to be short lived. Like Liberia in 2010, the Democratic Republic of Congo benefited from debt forgiveness after reaching the completion point under the enhanced Heavily Indebted Poor Countries initiative in 50 July 2010 and the subsequent Paris Club rescheduling agreement at the end of 2010. As its two major Paris Club creditors, the United States 2009 2010 2011 and France were also the top DAC donors to the Democratic Republic of 0 Congo, increasing their aid to the country from $278 million to $1.3 bil- Rwanda Burundi São Tomé Congo, Liberia and Príncipe Dem. Rep. lion and from $135 million to $1.1 billion respectively from 2010. Source: Online table 6.12. Economy States and markets links Back Global links Back World Development Indicators 2013 95 6  Global links Merchandise Net barter Inbound Net official Net Personal Foreign Portfolio Total Total debt trade terms of tourism development migration transfers and direct equity external service trade index expenditure assistance compensation investment debt stock % of exports of employees, of goods, received services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions incomea 2011 2011 2011 2011 2005–10 2011 2011 2011 2011 2011 Afghanistan 33.1 146.3 .. 35.0 –381 .. 83 .. 2,623 .. Albania 56.6 94.1 41.7 2.4 –48 1,162 1,370 2 5,938 9.3 Algeria 63.5 199.1 0.4 0.1 –140 203 2,721 0 6,072 0.8 American Samoa .. 129.0 .. .. .. .. .. .. .. .. Andorra .. .. .. .. .. .. .. .. .. .. Angola 82.9 244.7 1.0 0.2 82 0 –3,024 0 21,115 4.3 Antigua and Barbuda 47.0 75.1 58.1 1.4 .. 20 58 .. .. .. Argentina 35.5 135.2 6.2 0.0 –200 686 8,671 –174 114,704 15.3 Armenia 53.5 128.5 20.2 3.5 –75 1,994 663 0 7,383 25.4 Aruba .. 118.5 19.8 .. 4 5 544 0 .. .. Australia 37.3 200.7 .. .. 1,125 1,871 67,638 –3,308 .. .. Austria 88.8 89.0 9.6 .. 160 2,674 15,734 483 .. .. Azerbaijan 71.3 187.6 4.0 0.5 53 1,893 4,485 0 8,427 4.9 Bahamas, The 46.4 108.6 66.0 .. 6 .. 595 .. .. .. Bahrain .. 128.5 7.7 .. 448 .. 781 982 .. .. Bangladesh 54.2 54.8 0.4 1.2 –2,908 12,068 798 –10 27,043 5.5 Barbados 62.7 111.0 .. .. 0 82 334 .. .. .. Belarus 156.3 103.8 1.9 0.2 –50 814 4,002 0 29,120 4.5 Belgium 182.4 100.1 3.0 .. 200 10,912 102,000 –4,200 .. .. Belize 86.4 104.4 26.7 2.3 –1 76 95 .. 1,278 13.9 Benin 61.7 125.1 .. 9.3 50 185 118 .. 1,423 .. Bermuda .. 72.4 .. .. .. 1,253 111 –3 .. .. Bhutan 90.6 151.5 .. 8.7 17 10 16 0 1,035 11.1 Bolivia 66.8 175.4 5.5 3.3 –165 1,043 859 0 6,474 4.9 Bosnia and Herzegovina 93.4 101.5 9.8 2.3 –10 1,958 380 .. 10,729 10.9 Botswana 74.7 82.4 .. 0.7 19 63 587 .. 2,396 .. Brazil 19.9 135.8 2.3 0.0 –500 2,798 71,539 7,174 404,317 19.4 Brunei Darussalam 94.7 200.6 .. .. 4 .. 1,208 .. .. .. Bulgaria 112.3 110.7 12.7 .. –50 1,483 2,588 –42 39,930 12.2 Burkina Faso 42.3 141.2 .. 9.5 –125 111 7 .. 2,420 .. Burundi 36.1 172.6 1.6 24.8 370 45 3 .. 628 3.4 Cambodia 126.7 70.6 24.1 6.5 –255 160 902 0 4,336 1.0 Cameroon 44.0 149.6 .. 2.5 –19 115 360 .. 3,074 .. Canada 52.7 122.5 3.7 .. 1,098 .. 39,510 21,313 .. .. Cape Verde 53.7 106.0 55.5 13.3 –17 177 105 .. 1,025 5.0 Cayman Islands .. 77.6 .. .. .. .. 7,408 .. .. .. Central African Republic 24.6 82.4 .. 12.4 5 .. 109 .. 573 .. Chad 64.3 208.8 .. 4.9 –75 .. 1,855 .. 1,821 .. Channel Islands .. .. .. .. 5 .. .. .. .. .. Chile 62.3 213.3 .. 0.0 30 4 17,299 4,477 96,245 15.2 China 49.8 72.8 2.6 0.0 –1,884 40,483 220,143 5,308 685,418 3.6 Hong Kong SAR, China 388.9 95.9 6.0 .. 176 357 95,352 9,814 .. .. Macao SAR, China 24.2 87.1 .. .. 51 48 2,116 0 .. .. Colombia 33.5 142.4 4.9 0.4 –120 4,205 13,605 1,969 76,918 15.6 Comoros 49.5 76.1 .. 8.5 –10 .. 7 .. 278 .. Congo, Dem. Rep. 77.3 146.7 .. 38.4 –24 115 1,596 .. 5,448 2.4 Congo, Rep. 110.2 214.5 .. 2.4 50 .. 2,931 .. 2,523 .. 96  World Development Indicators 2013 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 transfers and direct equity external service trade index expenditure assistance compensation investment debt stock % of exports of employees, of goods, received services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions incomea 2011 2011 2011 2011 2005–10 2011 2011 2011 2011 2011 Costa Rica 65.2 78.1 15.4 0.1 76 520 2,157 0 10,292 13.5 Côte d’Ivoire 74.0 159.0 .. 6.2 –360 373 344 .. 12,012 .. Croatia 57.7 99.0 36.6 0.0 10 1,378 1,265 17 .. .. Cuba .. 165.6 .. .. –190 .. 110 .. .. .. Curaçao .. 99.9 .. .. .. 34 70 0 .. .. Cyprus 42.1 103.1 25.5 .. 44 127 1,080 429 .. .. Czech Republic 144.6 104.0 5.2 .. 240 1,815 5,380 –2 .. .. Denmark 63.3 106.2 3.4 .. 90 1,273 13,106 –2,250 .. .. Djibouti .. 77.8 4.6 .. 0 32 79 0 767 .. Dominica 54.1 104.3 58.9 5.2 .. 23 34 .. 284 9.8 Dominican Republic 47.1 92.4 31.4 0.4 –140 3,650 2,295 0 15,395 10.4 Ecuador 70.7 130.4 3.4 0.3 –120 2,681 568 2 16,497 9.7 Egypt, Arab Rep. 39.0 159.4 19.8 0.2 –347 14,324 –483 –711 35,001 7.4 El Salvador 66.9 90.5 11.3 1.3 –292 3,665 247 0 11,995 21.7 Equatorial Guinea 98.5 226.4 .. 0.2 20 .. 737 .. .. .. Eritrea 49.8 81.9 .. 6.3 55 .. 19 .. 1,055 .. Estonia 155.0 141.9 7.6 .. 0 407 436 –112 .. .. Ethiopia 38.1 136.5 34.4 11.8 –300 513 627 .. 8,597 6.1 Faeroe Islands .. 103.1 .. .. .. 146 .. .. .. .. Fiji 82.8 107.8 .. 2.0 –29 158 204 .. 861 .. Finland 61.8 74.8 5.3 .. 73 751 –5,758 –5 .. .. France 47.3 95.6 8.0 .. 500 19,307 45,209 3,608 .. .. French Polynesia .. 83.1 .. .. 0 700 40 .. .. .. Gabon 95.6 218.6 .. 0.5 5 .. 728 .. 2,879 .. Gambia, The 48.8 91.7 32.4 15.6 –14 91 36 .. 466 7.5 Georgia 64.4 133.8 20.2 3.9 –150 1,537 1,154 –7 11,124 26.9 Germany 75.8 99.5 3.0 .. 550 13,160 39,067 7,778 .. .. Ghana 71.4 185.3 5.4 4.8 –51 152 3,222 1 11,289 2.4 Greece 30.9 93.9 22.0 .. 154 1,186 1,092 –354 .. .. Greenland .. 72.4 .. .. .. .. .. .. .. .. Grenada 42.4 101.9 57.0 1.6 –5 29 41 .. 567 13.3 Guam .. 85.0 .. .. 0 .. .. .. .. .. Guatemala 57.7 90.9 10.5 0.9 –200 4,508 1,081 0 16,286 15.6 Guinea 73.7 109.9 0.1 4.5 –300 65 896 .. 3,139 11.2 Guinea-Bissau 54.8 80.6 .. 12.3 –10 46 19 .. 284 .. Guyana 114.5 130.0 .. 6.2 –40 373 165 .. 1,846 .. Haiti 49.8 64.5 15.9 23.2 –240 1,551 181 0 783 0.5 Honduras 97.2 89.8 8.5 3.8 –100 2,811 1,043 0 4,642 16.0 Hungary 152.9 94.1 5.5 .. 75 2,441 9,629 –203 .. .. Iceland 72.5 90.3 9.0 .. 10 21 1,107 –11 .. .. India 40.5 135.9 .. 0.2 –3,000 63,818 32,190 –4,137 334,331 6.5 Indonesia 44.6 134.1 4.1 0.1 –1,293 6,924 18,160 –326 213,541 14.5 Iran, Islamic Rep. .. 180.9 .. .. –186 1,330 4,150 .. 19,113 1.4 Iraq 119.0 211.8 1.9 1.7 –150 386 1,396 94 .. .. Ireland 88.9 86.2 4.2 .. 100 755 11,506 86,184 .. .. Isle of Man .. .. .. .. .. .. .. .. .. .. Israel 58.7 95.0 6.2 .. 274 595 11,374 –821 .. .. Economy States and markets Global links Back World Development Indicators 2013 97 6  Global links Merchandise Net barter Inbound Net official Net Personal Foreign Portfolio Total Total debt trade terms of tourism development migration transfers and direct equity external service trade index expenditure assistance compensation investment debt stock % of exports of employees, of goods, received services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions incomea 2011 2011 2011 2011 2005–10 2011 2011 2011 2011 2011 Italy 49.2 95.6 7.2 .. 1,999 7,025 28,003 5,978 .. .. Jamaica 55.4 68.6 48.1 0.4 –100 2,106 173 0 14,350 36.5 Japan 28.6 60.1 1.3 .. 270 2,132 79 5,645 .. .. Jordan 91.1 76.5 29.4 3.4 203 3,453 1,469 109 17,634 6.7 Kazakhstan 67.1 219.9 1.6 0.1 7 180 13,227 39 124,437 34.6 Kenya 61.1 90.7 18.6 7.4 –189 934 335 20 10,258 4.2 Kiribati 78.0 90.1 .. 27.2 .. .. 4 .. .. .. Korea, Dem. Rep. .. 79.6 .. .. 0 .. 55 .. .. .. Korea, Rep. 96.7 63.1 2.7 .. –30 8,494 4,661 –7,479 .. .. Kosovo .. .. .. 9.9 .. 1,122 546 0 1,531 8.9 Kuwait 69.9 219.2 .. .. 278 .. 400 1,099 .. .. Kyrgyz Republic 105.1 109.4 20.3 9.7 –132 1,709 694 5 5,486 11.8 Lao PDR 60.9 125.0 17.2 5.2 –75 110 301 11 6,158 .. Latvia 103.0 110.4 6.7 .. –10 695 1,502 38 38,255 47.0 Lebanon 65.9 98.1 27.5 1.1 –13 7,322 3,476 240 24,767 19.9 Lesotho 152.5 73.7 2.1 9.0 –20 649 132 0 792 .. Liberia 90.7 162.0 18.6 53.6 300 360 1,313 .. 448 .. Libya .. 185.4 .. .. –20 .. 200 0 .. .. Liechtenstein .. .. .. .. .. .. .. .. .. .. Lithuania 139.5 102.3 4.3 .. –36 1,956 1,443 9 29,988 20.1 Luxembourg 85.6 98.5 5.3 .. 42 1,740 18,366 32,486 .. .. Macedonia, FYR 112.8 86.7 4.5 1.6 2 434 495 –8 6,286 18.9 Madagascar 45.3 74.7 .. 4.2 –5 .. 907 .. 2,769 2.1 Malawi 62.8 98.2 2.7 14.5 –20 17 92 –1 1,202 1.3 Malaysia 144.0 100.7 7.4 0.0 84 1,198 12,001 .. 94,468 3.9 Maldives 88.3 100.1 80.3 2.7 0 3 282 0 983 .. Mali 52.7 177.3 .. 12.3 –101 473 178 .. 2,931 .. Malta 120.2 53.6 16.1 .. 5 37 467 –7 .. .. Marshall Islands 100.8 107.2 .. 38.2 .. .. 7 .. .. .. Mauritania 125.1 131.5 .. 9.2 10 .. 45 .. 2,709 3.6 Mauritius 69.3 71.5 30.5 1.7 0 1 273 9,387 1,435 1.4 Mexico 61.6 107.9 3.4 0.1 –1,805 23,588 20,823 –6,244 287,037 11.2 Micronesia, Fed. Sts. 62.8 97.3 .. 41.2 –9 .. 8 .. .. .. Moldova 105.9 105.9 8.3 6.0 –172 1,600 294 5 5,452 12.8 Monaco .. .. .. .. .. .. .. .. .. .. Mongolia 129.1 226.8 4.7 4.3 –15 279 4,715 9 2,564 2.1 Montenegro 70.6 .. .. 1.6 –3 343 558 –15 2,093 10.2 Morocco 65.1 140.6 25.7 1.3 –675 7,256 2,521 166 29,049 9.9 Mozambique 77.6 106.8 7.0 16.3 –20 157 2,079 0 4,097 1.6 Myanmar .. 104.5 3.3 .. –500 127 1,001 .. 7,765 .. Namibia 85.5 116.7 12.1 2.4 –1 15 969 4 .. .. Nepal 35.5 77.9 22.3 4.7 –100 4,217 94 .. 3,956 9.5 Netherlands 150.7 .. .. .. 8 .. .. .. .. .. New Caledonia .. 230.2 .. .. 6 519 1,745 0 .. .. New Zealand 46.8 132.6 11.3 .. 65 875 4,285 1,594 .. .. Nicaragua 80.4 82.8 8.0 7.6 –200 914 968 0 7,121 14.8 Niger 60.7 163.9 .. 10.9 –29 102 1,014 .. 1,408 .. 98  World Development Indicators 2013 Front ? User guide view People 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 transfers and direct equity external service trade index expenditure assistance compensation investment debt stock % of exports of employees, of goods, received services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions incomea 2011 2011 2011 2011 2005–10 2011 2011 2011 2011 2011 Nigeria 71.3 211.4 0.7 0.8 –300 20,619 8,842 2,571 13,108 0.4 Northern Mariana Islands .. 86.2 .. .. .. .. 0 .. .. .. Norway 51.4 156.6 3.2 .. 171 765 7,281 1,708 .. .. Oman 98.6 230.9 3.3 .. 153 39 788 –447 .. .. Pakistan 33.2 52.4 3.6 1.6 –2,000 12,263 1,309 –37 60,182 9.2 Palau 76.1 104.2 .. 20.7 .. .. 2 .. .. .. Panama 133.3 86.4 12.2 0.4 11 388 3,223 0 12,583 3.6 Papua New Guinea 92.4 166.0 .. 4.9 0 11 –309 .. 12,582 15.8 Paraguay 74.8 107.5 2.3 0.4 –40 893 412 0 6,011 3.6 Peru 47.6 159.0 5.8 0.4 –725 2,697 8,233 147 44,872 6.5 Philippines 49.9 64.7 6.0 –0.1 –1,233 22,973 1,869 1,038 76,043 17.6 Poland 76.8 99.7 5.0 .. 56 7,641 15,296 3,052 .. .. Portugal 58.6 86.8 17.3 .. 150 3,778 13,074 –10,557 .. .. Puerto Rico .. .. .. .. –145 .. .. .. .. .. Qatar 83.4 213.3 .. .. 857 574 –87 –903 .. .. Romania 77.2 98.3 2.9 .. –100 3,889 2,557 –37 129,822 27.5 Russian Federation 45.5 234.2 3.0 .. 1,136 4,951 52,878 –9,707 542,977 10.5 Rwanda 33.1 225.7 .. 20.2 15 103 106 .. 1,103 .. Samoa 62.7 77.5 67.9 16.6 –16 139 15 .. 368 5.8 San Marino .. .. .. .. .. .. .. .. .. .. São Tomé and Príncipe 57.6 120.3 54.2 30.2 –7 7 35 0 231 5.4 Saudi Arabia 82.6 215.8 2.5 .. 1,056 244 16,308 .. .. .. Senegal 59.1 105.4 .. 7.5 –133 1,478 286 .. 4,320 .. Serbia 69.7 .. 7.2 1.3 0 3,271 2,700 69 31,569 31.5 Seychelles 115.1 75.0 34.6 2.1 .. 26 139 0 1,780 3.2 Sierra Leone 68.6 61.7 8.1 14.7 60 59 715 .. 1,049 3.8 Singapore 323.4 81.2 .. .. 722 .. 64,003 –3,754 .. .. Sint Maarten .. .. .. .. .. 11 –48 .. .. .. Slovak Republic 163.0 87.4 3.0 .. 37 1,753 3,658 39 .. .. Slovenia 141.6 86.1 8.0 .. 22 433 818 222 .. .. Solomon Islands 104.3 87.9 .. 49.6 0 2 146 .. 256 2.0 Somalia .. 100.3 .. .. –300 .. 102 .. 3,050 .. South Africa 53.5 154.1 9.1 0.3 700 1,158 5,889 –3,769 113,512 5.3 South Sudan .. .. .. .. .. .. .. .. .. .. Spain 44.7 99.0 14.9 .. 2,250 9,907 31,419 2,978 .. .. Sri Lanka 51.0 72.1 10.4 1.0 –250 5,153 956 –623 23,984 9.3 St. Kitts and Nevis 42.1 66.8 40.8 2.5 .. 48 114 .. .. .. St. Lucia 69.9 94.8 56.7 3.0 –1 29 81 .. 448 7.8 St. Martin .. .. .. .. .. .. .. .. .. .. St. Vincent and Grenadines 53.8 107.2 48.3 2.8 –5 29 110 .. 283 15.2 Sudan 28.3 229.4 .. 2.0 135 1,420 1,936 .. 21,169 .. Suriname 96.3 141.8 2.6 .. –5 4 145 0 .. .. Swaziland 97.8 105.3 .. 3.2 –6 55 95 .. 605 1.9 Sweden 67.1 87.2 6.2 .. 266 776 3,054 2,146 .. .. Switzerland 67.1 79.8 5.0 .. 183 3,307 10,077 7,543 .. .. Syrian Arab Republic .. 143.7 .. .. –56 2,079 1,060 .. 4,968 .. Tajikistan 68.1 102.4 3.4 5.5 –296 3,060 11 0 3,323 .. Economy States and markets Global links Back World Development Indicators 2013 99 6  Global links Merchandise Net barter Inbound Net official Net Personal Foreign Portfolio Total Total debt trade terms of tourism development migration transfers and direct equity external service trade index expenditure assistance compensation investment debt stock % of exports of employees, of goods, received services, Net inflow Net inflow and primary % of GDP 2000 = 100 % of exports % of GNI thousands $ millions $ millions $ millions $ millions incomea 2011 2011 2011 2011 2005–10 2011 2011 2011 2011 2011 Tanzania 66.3 151.4 19.9 10.4 –300 76 1,095 3 10,044 2.0 Thailand 132.3 93.9 .. –0.1 492 4,554 7,780 875 80,039 3.8 Timor-Leste 30.4 .. .. .. –50 131 47 .. .. .. Togo 77.3 30.4 .. 15.5 –5 337 54 .. 643 .. Tonga 44.7 81.2 .. 21.1 –8 72 10 .. 191 8.8 Trinidad and Tobago 103.2 152.6 .. .. –20 91 574 .. .. .. Tunisia 91.2 95.0 11.2 1.5 –20 2,005 433 –44 22,335 10.7 Turkey 48.5 88.6 15.4 0.1 –50 1,087 16,049 –986 307,007 30.2 Turkmenistan 72.7 221.2 .. 0.2 –55 .. 3,186 .. 445 .. Turks and Caicos Islands .. 73.4 .. .. .. .. 97 .. .. .. Tuvalu 70.7 .. .. 76.9 .. .. 2 .. .. .. Uganda 45.0 119.7 24.2 9.6 –135 949 797 106 3,858 1.7 Ukraine 91.4 124.0 6.1 0.5 –40 7,822 7,207 519 134,481 30.8 United Arab Emirates 136.0 178.3 .. .. 3,077 .. 7,679 .. .. .. United Kingdom 45.4 101.4 5.9 .. 1,020 1,796 36,244 –16,894 .. .. United States 25.0 94.6 8.8 .. 4,955 5,810 257,528 27,350 .. .. Uruguay 40.1 100.9 18.7 0.0 –50 102 2,177 .. 14,350 11.1 Uzbekistan 51.2 178.0 .. 0.5 –518 .. 1,403 .. 8,382 .. Vanuatu 47.4 91.9 71.2 12.4 0 22 58 0 202 1.6 Venezuela, RB 44.3 258.7 0.9 0.0 40 138 5,226 .. 67,908 6.4 Vietnam 164.8 99.9 5.3 3.0 –431 8,600 7,430 1,064 57,841 3.2 Virgin Islands (U.S.) .. .. .. .. –4 .. .. .. .. .. West Bank and Gaza .. .. .. .. –90 1,545 .. .. .. .. Yemen, Rep. 59.0 157.5 9.2 1.5 –135 1,404 –713 0 6,418 2.8 Zambia 83.3 192.8 1.6 6.1 –85 46 1,982 11 4,360 2.1 Zimbabwe 81.8 110.5 .. 7.4 –900 .. 387 .. 6,275 .. World 51.8 .. 5.4b 0.2c .. 479,246 1,654,419 183,598 .. .. Low income 58.1 .. 12.0 b 8.8 c –6,808 27,628 18,331 124 133,292 4.6 Middle income 51.4 .. 4.7 b 0.2c –16,352 330,766 629,613 8,474 4,742,871 8.9 Lower middle income 53.2 .. 6.5b 0.8 c –12,699 202,300 108,774 –349 1,170,790 9.5 Upper middle income 50.9 .. 4.3b 0.1c –3,653 128,466 520,838 8,822 3,572,081 8.8 Low & middle income 51.5 .. 4.8b 0.6c –23,160 358,394 647,943 8,598 4,876,163 8.8 b East Asia & Pacific 57.2 .. 3.4 0.1c –5,221 85,943 274,550 7,980 1,242,633 4.7 Europe & Central Asia 57.0 .. 5.7b 0.2c –595 42,960 119,394 –10,115 1,484,186 17.8 Latin America & Carib. 38.2 .. 4.7b 0.2c –5,088 59,532 161,618 7,351 1,233,484 13.4 Middle East & N. Africa 67.3 .. 11.1b .. –1,628 41,339 16,309 –145 166,124 5.1 South Asia 40.7 .. 6.5b 0.7c –8,622 97,532 35,728 –4,807 454,138 6.7 Sub-­Saharan Africa 62.7 .. 6.5b 3.9c –2,006 31,088 40,345 8,334 295,598 3.4 High income 51.9 .. 5.7b 0.0 c 22,906 120,853 1,006,476 175,000 .. .. Euro area 70.8 .. 6.1b 0.0 c 6,336 75,712 320,055 128,811 .. .. a. The numerator refers to 2011, whereas the denominator is a three-year average of 2009–11 data. 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. 100  World Development Indicators 2013 Front ? User guide World view People Environment Global links  6 About the data Starting with World Development Indicators 2013, the World Bank is Official development assistance changing 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 financial 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 definitions, received large amounts of aid. Thus aid dependency ratios may trade flow 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, personal transfers, and compensation of employees Tourism The movement of people, most often through migration, is a signifi- Tourism is defined as the activity of people traveling to and staying cant part of global integration. Migrants contribute to the economies in places outside their usual environment for no more than one year of both their host country and their country of origin. Yet reliable sta- for leisure, business, and other purposes not related to an activity tistics on migration are difficult to collect and are often incomplete, remunerated from within the place visited. Data on inbound and making international comparisons a challenge. outbound tourists refer to the number of arrivals and departures, Since data on emigrant stock is difficult for countries to collect, not to the number of unique individuals. Thus a person who makes the United Nations Population Division provides data on net migra- several trips to a country during a given period is counted each tion, taking into account the past migration history of a country or time as a new arrival. Data on inbound tourism show the arrivals of area, the migration policy of a country, and the influx of refugees nonresident tourists (overnight visitors) at national borders. When in recent periods to derive estimates of net migration. The data to data on international tourists are unavailable or incomplete, the calculate these estimates come from various sources, including table shows the arrivals of international visitors, which include tour- border statistics, administrative records, surveys, and censuses. ists, same-day visitors, cruise passengers, and crew members. The When there are insufficient data, net migration is derived through aggregates are calculated using the World Bank’s weighted aggrega- the difference between the growth rate of a country’s population tion methodology (see Statistical methods) and differ from the World over a certain period and the rate of natural increase of that popu- Tourism Organization’s aggregates. lation (itself being the difference between the birth rate and the For tourism expenditure, the World Tourism Organization uses bal- death rate). ance of payments data from the IMF supplemented by data from Migrants often send funds back to their home countries, which are individual countries. These data, shown in the table, include travel recorded as personal transfers in the balance of payments. Personal and passenger transport items as defined by the Balance of Pay- transfers thus include all current transfers between resident and ments. When the IMF does not report data on passenger transport nonresident individuals, independent of the source of income of the items, expenditure data for travel items are shown. sender (irrespective of whether the sender receives income from Economy States and markets links Back Global links Back World Development Indicators 2013 101 6  Global links labor, entrepreneurial or property income, social benefits, or any by different parties during their lives. Negotiability allows investors other types of transfers or disposes of assets) and the relationship to diversify their portfolios and to withdraw their investment read- between the households (irrespective of whether they are related ily. Included in portfolio investment are investment fund shares or or unrelated individuals). units (that is, those issued by investment funds) that are evidenced Compensation of employees refers to the income of border, by securities and that are not reserve assets or direct investment. seasonal, and other short-term workers who are employed in an Although they are negotiable instruments, exchange-traded financial economy where they are not resident and of residents employed by derivatives are not included in portfolio investment because they nonresident entities. Compensation of employees has three main are in their own category. components: wages and salaries in cash, wages and salaries in kind, and employers’ social contributions. 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, 128 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. 102  World Development Indicators 2013 Front ? User guide World view People Environment Global links  6 Definitions Data sources • Merchandise trade includes all trade in goods and excludes trade Data on merchandise trade are from the World Trade Organization. in services. • Net barter terms of trade index is the percentage ratio Data on trade indexes are from the United Nations Conference of the export unit value indexes to the import unit value indexes, mea- on Trade and Development’s (UNCTAD) annual Handbook of Sta- sured relative to the base year 2000. • Inbound tourism expenditure tistics. Data on tourism expenditure are from the World Tourism is expenditures by international inbound visitors, including payments Organization’s Yearbook of Tourism Statistics and World Tourism to national carriers for international transport and any other prepay- Organization (2012a) and updated from its electronic files. Data ment made for goods or services received in the destination country. on net official development assistance are compiled by the OECD They may include receipts from same-day visitors, except when these (http://stats.oecd.org). Data on net migration are from United are important enough to justify separate classification. Data include Nations Population Division (2011). Data on personal transfers travel and passenger transport items as defined by Balance of Pay- and compensation of employees are from the IMF’s Balance of ments. When passenger transport items are not reported, expendi- Payments Statistics Yearbook supplemented by World Bank staff ture data for travel items are shown. Exports refer to all transactions estimates. Data on FDI are World Bank staff estimates based between residents of a country and the rest of the world involving on IMF balance of payments statistics and UNCTAD data (http:// a change of ownership from residents to nonresidents of general unctadstat.unctad.org/ReportFolders/reportFolders.aspx). Data merchandise, goods sent for processing and repairs, nonmonetary on portfolio equity are from the IMF’s Balance of Payments Sta- gold, and services. • Net official development assistance is flows tistics Yearbook. Data on external debt are mainly from reports (net of repayment of principal) that meet the DAC definition of official to the World Bank through its DRS from member countries that development assistance and are made to countries and territories have received International Bank for Reconstruction and Develop- on the DAC list of aid recipients, divided by World Bank estimates ment loans or International Development Assistance credits, with of GNI. • Net migration is the net total of migrants (immigrants additional information from the files of the World Bank, the IMF, less emigrants, including both citizens and noncitizens) during the the African Development Bank and African Development Fund, period. Data are five-year estimates. • Personal transfers and com - the Asian Development Bank and Asian Development Fund, and pensation of employees, received, are the sum of personal transfers the Inter-American Development Bank. Summary tables of the (current transfers in cash or in kind made or received by resident external debt of developing countries are published annually in households to or from nonresident households) and compensation the World Bank’s International Debt Statistics and International of employees (remuneration for the labor input to the production Debt Statistics database. process contributed by an individual in an employer-employee rela- tionship with the enterprise). • Foreign direct investment is cross- References border investment associated with a resident in one economy having IMF (International Monetary Fund). Various issues. International Finan- control or a significant degree of influence on the management of an cial Statistics. Washington, DC. enterprise that is resident in another economy. • Portfolio equity is ———. Various years. Balance of Payments Statistics Yearbook. Parts net inflows from equity securities other than those recorded as direct 1 and 2. Washington, DC. investment or reserve assets, including shares, stocks, depository UNCTAD (United Nations Conference on Trade and Development). Vari- receipts, and direct purchases of shares in local stock markets ous years. Handbook of Statistics. New York and Geneva. by foreign investors • Total external debt stock is debt owed to United Nations Population Division. 2011. World Population Prospects: nonresident creditors and repayable in foreign currency, goods, or The 2010 Revision. New York: United Nations, Department of Eco- services by public and private entities in the country. It is the sum nomic and Social Affairs. of long-term external debt, short-term debt, and use of IMF credit. World Bank. Various years. International Debt Statistics. Washington, • Total debt service is the sum of principal repayments and interest DC. actually paid in foreign currency, goods, or services on long-term World Tourism Organization. 2012a. Compendium of Tourism Statistics debt; interest paid on short-term debt; and repayments (repurchases 2012. Madrid. and charges) to the IMF. Exports of goods and services and primary ———. 2012b Tourism Highlights: 2012 Edition. Madrid. income are the total value of exports of goods and services, receipts ———. Various years. Yearbook of Tourism Statistics. Vols. 1 and 2. of compensation of nonresident workers, and primary investment Madrid. income from abroad. Economy States and markets links Back Global links Back World Development Indicators 2013 103 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 104  World Development Indicators 2013 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 transfers and compensation of employees, Received BX.TRF.PWKR.CD.DT 6.12 Distribution of net aid by Development Assistance Personal transfers and compensation of Committee members employees, Paid BM.TRF.PWKR.CD.DT Net bilateral aid flows from DAC donors DC.DAC.TOTL.CD 6.14 Travel and tourism United States DC.DAC.USAL.CD International inbound tourists ST.INT.ARVL EU institutions DC.DAC.CECL.CD International outbound tourists ST.INT.DPRT Germany DC.DAC.DEUL.CD Inbound tourism expenditure, $ ST.INT.RCPT.CD France DC.DAC.FRAL.CD Inbound tourism expenditure, % of exports ST.INT.RCPT.XP.ZS United Kingdom DC.DAC.GBRL.CD Outbound tourism expenditure, $ ST.INT.XPND.CD Japan DC.DAC.JPNL.CD Outbound tourism expenditure, % of Netherlands DC.DAC.NLDL.CD imports ST.INT.XPND.MP.ZS Australia DC.DAC.AUSL.CD Canada DC.DAC.CANL.CD a. Available online only as part of the table, not as an individual indicator. Norway DC.DAC.NORL.CD b. Derived from data elsewhere in the World Development Indicators database. Other DAC donors ..a,b Economy States and markets links Back Global links Back World Development Indicators 2013 105 106  World Development Indicators 2013 Front ? User guide World view People Environment Primary data documentation As a major user of socioeconomic data, the World document results, and heighten public account- Bank recognizes the importance of data docu- ability. The need for improved statistics to moni- mentation to inform users of differences in the tor the Millennium Development Goals and the methods and conventions used by primary data parallel effort to support a culture of results- collectors—usually national statistical agencies, based management has stimulated a decade- central banks, and customs services—and by long effort to improve statistics. The results have international organizations, which compile the been impressive, but more needs to done. statistics that appear in the World Development The “Statistics for Transparency, Account- Indicators database. These differences may ability, and Results: A Busan Action Plan for give rise to significant discrepancies over time, Statistics� was endorsed by the Busan Partner- both within countries and across them. Delays in ship for Effective Development Cooperation at reporting data and the use of old surveys as the the Fourth High-level Forum for Aid Effective- base for current estimates may further compro- ness held November 29–December 1, 2011, in mise the quality of data reported here. Busan, Republic of Korea. This plan builds on This section provides information on sources, the progress made under the first global plan to methods, and reporting standards of the princi- improve national and international statistics, the pal demographic, economic, and environmental 2004 Marrakech Action Plan for Statistics, but indicators in World Development Indicators. Addi- goes beyond it in many ways. The main objec- tional documentation is available from the World tives of the plan are to integrate statistics into Bank’s Bulletin Board on Statistical Capacity at decisionmaking, promote open access to statis- http://data.worldbank.org. tics within government and for all other uses, and The demand for good-quality statistical increase resources for statistical systems, both data is ever increasing. Statistics provide the for investment in new capacity and for maintain- evidence needed to improve decisionmaking, ing current operations. Economy States and markets Global links Back World Development Indicators 2013 107 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 C 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 G Antigua and Barbuda East Caribbean dollar 2006 1968 B 6 G G Argentina Argentine peso 1993 1993 B 1971–84 2005 6 A S C S Armenia Armenian dram a 1996 1993 B 1990–95 2005 6 A S C S Aruba Aruban florin 1995 1993 6 S a Australia Australian dollar 2009 2008 B 2008 6 G C S Austria Euro 2005 1993 B Rolling 6 S C S a Azerbaijan New Azeri manat 2003 1993 B 1992–95 2005 6 A G B 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 Belarus Belarusian rubel a 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 convertible mark Botswana Botswana pula 1993/94 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 Bulgaria Bulgarian lev a 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 2008 1993 B 2005 6 A S C G Cambodia Cambodian riel 2000 1993 B 2005 6 A S C G Cameroon CFA franc 2000 1993 B 2005 6 A S B G Canada Canadian dollar 2005 1993 B 2008 6 G C S Cape Verde Cape Verde escudo 1980 1968 P 2005 6 A G C G Cayman Islands Cayman Islands dollar 1993 G Central African Republic CFA franc 2000 1968 B 2005 6 P S B G Chad CFA franc 1995 1993 B 2005 6 E S G Channel Islands Pound sterling 2003 2007 1968 B Chile Chilean peso 2003 1993 B 2008 6 A S C S China Chinese yuan 2000 1993 P 1978–93 2005 6 P S B G Hong Kong SAR, China Hong Kong dollar 2009 1993 B 2005 6 G C S Macao SAR, China Macao pataca 2009 1993 B 2005 6 G C G Colombia Colombian peso 2005 1993 B 1992–94 2005 6 A G B S Comoros Comorian franc 1990 1968 P 2005 A S 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 A S C 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 108  World Development Indicators 2013 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 2011 2000 Albania 2011 DHS, 2009 LSMS, 2008 Yes 2009 2011 2006 Algeria 2008 MICS, 2012 IHS, 1995 2011 2001 American Samoa 2010 Yes 2007 Andorra 2011b Yes 2006 Angola 1970 MIS, 2011; IBEP, 2008/09 IHS, 2000 1964/65 1991 2005 Antigua and Barbuda 2011 Yes 2007 2011 2005 Argentina 2010 MICS, 2011 IHS, 2011 Yes 2013 2002 2011 2000 Armenia 2011 DHS, 2010 IHS, 2010 Yes 2013/14 2011 2007 Aruba 2010 Yes 2011 Australia 2011 ES/BS, 1994 Yes 2011 2006 2011 2000 Austria 2011b IS, 2000 Yes 2010 2009 2011 2002 Azerbaijan 2009 DHS, 2006 ES/BS, 2008 Yes 2009 2011 2005 Bahamas, The 2010 2011 Bahrain 2010 Yes 2011 2003 Bangladesh 2011 DHS, 2011 IHS, 2010 2008 2007 2008 Barbados 2010 MICS, 2012 Yes 2011 2005 Belarus 2009 MICS, 2012 ES/BS, 2009 Yes 2009 2011 2000 Belgium 2011 IHS, 2000 Yes 2010 2009 2011 2007 Belize 2010 MICS, 2011 ES/BS, 2011 2011 2000 Benin 2002 DHS, 2011/12 CWIQ, 2007 2011/12 2010 2001 Bermuda 2010 Yes 2011 Bhutan 2005 MICS, 2010 IHS, 2010 2009 2011 2008 Bolivia 2012 DHS, 2008 IHS, 2009 2013 2001 2011 2000 Bosnia and Herzegovina 1991 MICS, 2011/12 LSMS, 2007 Yes 2011 2009 Botswana 2011 DHS, 1988 ES/BS, 2008 2009 2011 2000 Brazil 2010 LSMS, 1996/97 LFS, 2009 2006 2007 2011 2006 Brunei Darussalam 2011 Yes 2006 1994 Bulgaria 2011 LSMS, 2007 ES/BS, 2007 Yes 2010 2009 2011 2009 Burkina Faso 2006 DHS, 2011 CWIQ, 2009 2010 2011 2001 Burundi 2008 DHS, 2010 CWIQ, 2006 2010 2000 Cambodia 2008 DHS, 2010 IHS, 2008 2013 2000 2011 2006 Cameroon 2005 DHS, 2011 PS, 2007 1984 2002 2011 2000 Canada 2011 LFS, 2000 Yes 2011 2008 2011 1986 Cape Verde 2010 DHS, 2005 ES/BS, 2007 Yes 2011 2001 Cayman Islands 2010 Yes Central African Republic 2003 MICS, 2010 PS, 2008 2011 2005 Chad 2009 MICS, 2010 PS, 2002/03 2011 1995 2005 Channel Islands 2009, 2011c Chile 2012 IHS, 2009 Yes 2007 2008 2011 2007 China 2010 NSS, 2007 IHS, 2008 2007 2007 2011 2005 Hong Kong SAR, China 2011d Yes 2009 2011 Macao SAR, China 2011 Yes 2009 2007 Colombia 2006 DHS, 2010 IHS, 2011 2013 2005 2011 2000 Comoros 2003 DHS, 2012 IHS, 2004 2007 1999 Congo, Dem. Rep. 1984 MICS, 2010 1-2-3, 2004/05 1990 1987 2005 Congo, Rep. 2007 DHS, 2011/12 CWIQ/PS, 2011 1985/86 2009 2010 2002 Costa Rica 2011 MICS, 2011 LFS, 2011 Yes 1973 2009 2011 1997 Côte d’Ivoire 1998 DHS, 2012 IHS, 2008 2001 2011 2005 Croatia 2011 ES/BS, 2008 Yes 2010 2011 2010 Cuba 2012 MICS, 2010/11 Yes 2006 2007 Curaçao Cyprus 2011 Yes 2010 2009 2011 2009 Czech Republic 2011 RHS, 1993 IS, 1996 Yes 2010 2007 2011 2007 Economy States and markets Global links Back World Development Indicators 2013 109 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 G Dominican Republic Dominican peso 1991 1993 B 6 A G C G Ecuador U.S. dollar 2000 1993 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 Eritrea Eritrean nakfa 2000 1968 B 6 E Estonia Euro 2005 1993 B 1987–95 Rolling 6 S C S Ethiopia Ethiopian birr 1999/2000 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 France Euro a 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 C 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 A 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 A S B G Guinea Guinean franc 2003 1993 B 2005 6 P 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 Hungary Hungarian forint a 2005 1993 B Rolling 6 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 1997 1968 B 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 2008 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 2008 6 G C S Jordan Jordanian dinar 1994 1968 B 2005 6 A G B S Kazakhstan Kazakh tenge a 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 G Korea, Dem. Rep. Democratic People’s 1968 6 Republic of Korean won Korea, Rep. Korean won 2005 1993 B 2008 6 G C S Kosovo Euro 2008 1993 A G Kuwait Kuwaiti dinar 1995 1968 P 2005 6 S B G Kyrgyz Republic Kyrgyz som a 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 A S C S Lebanon Lebanese pound 1997 1993 B 2005 6 A G B G Lesotho Lesotho loti 1995 1993 B 2005 6 A G C G 110  World Development Indicators 2013 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 2008 2011 2009 Djibouti 2009 MICS, 2006 PS, 2002 2009 2000 Dominica 2011 Yes 2010 2004 Dominican Republic 2010 DHS, 2007 IHS, 2011 2012/13 2011 2005 Ecuador 2010 RHS, 2004 LFS, 2011 2013/15 2008 2011 2005 Egypt, Arab Rep. 2006 DHS, 2008 ES/BS, 2008 Yes 2010 2006 2011 2000 El Salvador 2007 RHS, 2008 IHS, 2010 Yes 2008 2011 2007 Equatorial Guinea 2002 2000 Eritrea 1984 DHS, 2002 2009 2003 2004 Estonia 2012 ES/BS, 2004 Yes 2010 2009 2011 2007 Ethiopia 2007 DHS, 2011 ES/BS, 2010/11 2009 2011 2002 Faeroe Islands 2011 Yes 2009 Fiji 2007 ES/BS, 2009 Yes 2009 2008 2010 2000 Finland 2010 IS, 2000 Yes 2010 2009 2011 2005 France 2006e ES/BS, 1994/95 Yes 2010 2009 2011 2007 French Polynesia 2007 Yes 2011 Gabon 2003 DHS, 2012 CWIQ/IHS, 2005 2009 2005 Gambia, The 2003 MICS, 2010 IHS, 2010 2001/02 2004 2011 2000 Georgia 2002 MICS, 2005 IHS, 2009 Yes 2009 2010 2005 Germany 2011e IHS, 2000 Yes 2010 2009 2011 2007 Ghana 2010 MICS, 2011 LSMS, 2005/06 2013/14 2003 2011 2000 Greece 2011 IHS, 2000 Yes 2009 2007 2011 2007 Greenland 2010 Yes 2011 Grenada 2011 RHS, 1985 Yes 2012 2009 2005 Guam 2010 Yes Guatemala 2012 RHS, 2008/09 LSMS, 2011 Yes 2013 2011 2006 Guinea 1996 DHS, 2005 CWIQ, 2012 2008 2001 Guinea-Bissau 2009 MICS, 2010 CWIQ, 2010 2005 2000 Guyana 2012 DHS, 2009 IHS, 1998 2011 2000 Haiti 2003 DHS, 2012 IHS, 2001 2008 1997 2000 Honduras 2001 DHS, 2011/12 IHS, 2010 2013 2009 2006 Hungary 2011 ES/BS, 2007 Yes 2010 2009 2011 2007 Iceland 2011 Yes 2010 2005 2011 2005 India 2011 DHS, 2006 IHS, 2010 2011 2008 2011 2010 Indonesia 2010 DHS, 2012 IHS, 2012 2013 2008 2011 2000 Iran, Islamic Rep. 2011 DHS, 2000 ES/BS, 2005 2003 2008 2011 2004 Iraq 1997 MICS, 2011 IHS, 2007 2012 2009 2000 Ireland 2011 IHS, 2000 Yes 2010 2009 2011 1979 Isle of Man 2011 Yes Israel 2009 ES/BS, 2001 Yes 2008 2011 2004 Italy 2012 ES/BS, 2000 Yes 2010 2009 2011 2000 Jamaica 2011 MICS, 2011 LSMS, 2010 2007 2010 1993 Japan 2010 IS, 1993 Yes 2010 2007 2011 2001 Jordan 2004 DHS, 2012 ES/BS, 2010 2007 2009 2011 2005 Kazakhstan 2009 MICS, 2010/11 ES/BS, 2011 Yes 2011 2010 Kenya 2009 MIS, 2010; IHS, 2005/06 2007 2010 2003 HIV/MCH SPA, 2010 Kiribati 2010 2011 Korea, Dem. Rep. 2008 MICS, 2009 2005 Korea, Rep. 2010 ES/BS, 1998 Yes 2000 2008 2011 2002 Kosovo 2011 IHS, 2009 Kuwait 2010 FHS, 1996 Yes 2009 2009 2002 Kyrgyz Republic 2009 DHS, 2012 ES/BS, 2010 Yes 2002 2009 2011 2006 Lao PDR 2005 MICS, 2011/12 ES/BS, 2008 2010/11 1974 2005 Latvia 2011 IHS, 2008 Yes 2010 2009 2011 2002 Lebanon 1970 MICS, 2000 Yes 2011 2007 2011 2005 Lesotho 2006 DHS, 2009 ES/BS, 2002/03 2010 2009 2000 Economy States and markets Global links Back World Development Indicators 2013 111 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 A 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 S Madagascar Malagasy ariary 1984 1968 B 2005 6 A S C G Malawi Malawi kwacha 2007 1993 B 2005 6 A G G Malaysia Malaysian ringgit 2000 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 C S Mexico Mexican peso 2003 1993 B 2008 6 A G C S Micronesia, Fed. Sts. U.S. dollar 2004 1993 B Moldova Moldovan leu a 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 G Myanmar Myanmar kyat 2005/06 1968 P 6 E G C Namibia Namibian dollar 2004/05 1993 B 2005 6 G B G Nepal Nepalese rupee 2000/01 1993 B 2005 6 A G C 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 2008 6 G C Nicaragua Nicaraguan gold cordoba 2006 1993 B 1965–95 6 A G B G Niger CFA franc 1987 1993 P 1993 2005 6 A S B G Nigeria Nigerian naira 2002 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 1999/ 1993 B 2005 6 A G B G 2000 Palau U.S. dollar 1995 1993 B S 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 P 2005 6 A S B 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 a 2005 1993 B 1987–89, Rolling 6 A S C S 1992 Russian Federation Russian ruble 2000 1993 B 1987–95 2008 6 P G C S Rwanda Rwandan franc 2006 1993 P 1994 2005 6 A G C G Samoa Samoan tala 2002 1993 B 6 A S G San Marino Euro 1995 2000 1993 B C G São Tomé and Príncipe São Tomé and Príncipe 2001 1993 P 2005 6 A S 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 112  World Development Indicators 2013 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 MIS, 2011 CWIQ, 2007 1984 2000 Libya 2006 2010 2000 Liechtenstein 2010 Yes Lithuania 2011 ES/BS, 2008 Yes 2010 2009 2011 2007 Luxembourg 2011 Yes 2010 2009 2011 1999 Macedonia, FYR 2011 MICS, 2011 ES/BS, 2009 Yes 2007 2009 2011 2007 Madagascar 1993 MIS, 2011 PS, 2010 2006 2011 2000 Malawi 2008 MIS, 2012; LSMS, 2010/11 IHS, 2010/11 2007 2009 2011 2005 Malaysia 2010 ES/BS, 2009 Yes 2012 2008 2011 2005 Maldives 2006 DHS, 2009 IHS, 2010 Yes 2011 2008 Mali 2009 DHS, 2012 IHS, 2009/10 2010 2000 Malta 2011 Yes 2010 2008 2011 2002 Marshall Islands 2011 Mauritania 2000 MICS, 2011 IHS, 2008 2011 2005 Mauritius 2011 RHS, 1991 Yes 2007 2011 2003 Mexico 2010 ENPF, 1995 LFS, 2010 2007 2007 2011 2009 Micronesia, Fed. Sts. 2010 IHS, 2000 Moldova 2004 MICS, 2012 ES/BS, 2010 Yes 2011 2009 2011 2007 Monaco 2008 Yes 2009 Mongolia 2010 MICS, 2010 LSMS, 2011 Yes 2012 2008 2007 2009 Montenegro 2011 MICS, 2005/06 ES/BS, 2011 Yes 2010 2011 2010 Morocco 2004 MICS/PAPFAM, 2006 ES/BS, 2007 2012 2009 2010 2000 Mozambique 2007 DHS, 2011 ES/BS, 2008/09 2010 2011 2001 Myanmar 1983 MICS, 2009/10 2011/12 2003 2010 2000 Namibia 2011 HIV/MCH, 2009 ES/BS, 2009 2011 2002 Nepal 2011 DHS, 2011 LSMS, 2011 2012 2008 2011 2006 Netherlands 2011 IHS, 1999 Yes 2010 2008 2011 2008 New Caledonia 2009 Yes 2011 New Zealand 2006 IS, 1997 Yes 2012 2008 2011 2002 Nicaragua 2005 RHS, 2006/07 LSMS, 2009 2011 2011 2001 Niger 2012 DHS, 2012 CWIQ/PS, 2008 2008 2002 2011 2005 Nigeria 2006 MICS, 2011 IHS, 2010 2007 2011 2005 Northern Mariana Islands 2010 Norway 2011 IS, 2000 Yes 2010 2008 2011 2006 Oman 2010 MICS, 2012 2007 2011 2003 Pakistan 1998 DHS, 2012 IHS, 2008 2010 2006 2011 2008 Palau 2010 Yes Panama 2010 LSMS, 2008 LFS, 2010 2011 2001 2011 2000 Papua New Guinea 2011 LSMS, 1996 IHS, 1996 2004 2005 Paraguay 2012 RHS, 2008 IHS, 2011 2008 2002 2011 2000 Peru 2007 Continuous DHS, 2012 IHS, 2011 2012 2007 2011 2000 Philippines 2010 DHS, 2008 ES/BS, 2009 Yes 2012 2006 2011 2009 Poland 2011 ES/BS, 2010 Yes 2010 2009 2011 2009 Portugal 2011 IS, 1997 Yes 2009 2009 2011 2002 Puerto Rico 2010 RHS, 1995/96 Yes 2007 2006 2005 Qatar 2010 MICS, 2012 Yes 2006 2010 2005 Romania 2011 RHS, 1999 LFS, 2010 Yes 2010 2009 2011 2009 Russian Federation 2010 LSMS, 1992 IHS, 2010 Yes 2006 2009 2011 2001 Rwanda 2012 Special DHS, 2011 IHS, 2011 2008 2011 2000 Samoa 2011 DHS, 2009 2009 2011 San Marino 2010 Yes São Tomé and Príncipe 2012 DHS, 2008/09 PS, 2009/10 2011/12 2010 1993 Saudi Arabia 2010 Demographic survey, 2007 2010 2006 2011 2006 Senegal 2002 Continuous DHS, 2012 PS, 2010/11 2011/12 2009 2011 2002 Serbia 2011 MICS, 2010 IHS, 2010 Yes 2012 2009 2011 2009 Economy States and markets Global links Back World Development Indicators 2013 113 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 1993 B 2005 6 G C S Sint Maarten Netherlands Antilles 1993 guilder Slovak Republic Euro 2005 1993 B Rolling 6 S C S Slovenia Euro a 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 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 C G St. Lucia East Caribbean dollar 2006 1968 B 6 A S G St. Martin Euro 1993 St. Vincent and Grenadines East Caribbean dollar 2006 1993 B 6 A S B G Sudan Sudanese pound 1981/82f 1996 1968 B 2005 6 A G B G Suriname Suriname dollar 1990 1993 B 6 G G Swaziland Swaziland lilangeni 2000 1993 B 2005 6 E G B 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 C 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 G Thailand Thai baht 1988 1993 P 2005 6 A S C S Timor-Leste U.S. dollar 2000 2008 P G 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 B S a Turkmenistan New Turkmen manat 2007 1993 B 1987–95, 6 E G 1997–2007 Turks and Caicos Islands U.S. dollar 1993 G Tuvalu Australian dollar 2005 1968 P 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 B G United Kingdom Pound sterling 2005 1993 B Rolling 6 G C S a United States U.S. dollar 2005 1993 B 2008 6 G C S Uruguay Uruguayan peso 2005 1993 B 2005 6 A G C S a Uzbekistan Uzbek sum 1997 1993 B 1990–95 6 A G Vanuatu Vanuatu vatu 2006 1993 P 6 E G C G Venezuela, R.B. Venezuelan bolivar fuerte 1997 1993 B 2005 6 A G C G Vietnam Vietnamese dong 1994 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 Zambian kwacha 1994 1968 B 1990–92 2005 6 P S B G Zimbabwe U.S. dollar 2009 1993 B 1991, 1998 2005 6 A G C G 114  World Development Indicators 2013 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 IHS, 2007 Yes 2011 2008 2005 Sierra Leone 2004 MICS, 2010 IHS, 2011 2002 2005 Singapore 2010 General household, 2005 Yes 2009 2011 1975 Sint Maarten 2001 Population Census, 2011 Slovak Republic 2011 IS, 2009 Yes 2001 2009 2011 2007 Slovenia 2011b ES/BS, 2004 Yes 2010 2009 2011 2009 Solomon Islands 2009 IHS, 2005/06 2012/13 2011 Somalia 1987 MICS, 2006 1983 2003 South Africa 2011 DHS, 2003 ES/BS, 2010 2012 2009 2011 2000 South Sudan 2008 ES/BS, 2009 Spain 2011 IHS, 2000 Yes 2010 2009 2011 2008 Sri Lanka 2012 DHS, 2006/07 ES/BS, 2010 Yes 2013 2008 2011 2005 St. Kitts and Nevis 2011 Yes 2011 St. Lucia 2010 MICS, 2012 IHS, 1995 Yes 2008 2005 St. Martin St. Vincent and Grenadines 2011 Yes 2011 1995 Sudan 2008 SHHS, 2010 ES/BS, 2009 2001 2009 2005g Suriname 2012 MICS, 2010 ES/BS, 1999 Yes 2008 2004 2011 2000 Swaziland 2007 MICS, 2010 ES/BS, 2009/10 2007 2000 Sweden 2011 IS, 2000 Yes 2010 2009 2011 2007 Switzerland 2010 ES/BS, 2000 Yes 2008 2007 2011 2000 Syrian Arab Republic 2004 MICS, 2006 ES/BS, 2004 1981 2009 2010 2005 Tajikistan 2010 LSMS, 2009 LSMS, 2009 2013 2000 2006 Tanzania 2012 AIS, 2011/12; ES/BS, 2011 2007/08 2007 2011 2002 LSMS, 2010/11 Thailand 2010 MICS, 2012 IHS, 2010 2013 2006 2011 2007 Timor-Leste 2010 DHS, 2009/10 LSMS, 2007 2012 2005 2004 Togo 2010 MICS, 2010 CWIQ, 2011 2011/12 2011 2002 Tonga 2006 2011 Trinidad and Tobago 2011 MICS, 2011 IHS, 1992 Yes 2006 2010 2000 Tunisia 2004 MICS, 2011 IHS, 2010 2004 2006 2011 2001 Turkey 2011 DHS, 2003 LFS, 2009 2008 2011 2003 Turkmenistan 2012 MICS, 2011 LSMS, 1998 Yes 2000 2004 Turks and Caicos Islands 2012 Yes 2011 Tuvalu 2012 2008 Uganda 2002 DHS, 2011 PS, 2009/10 2008 2000 2011 2002 Ukraine 2001 MICS, 2012 ES/BS, 2009 Yes 2012/13 2004 2011 2005 United Arab Emirates 2010 2012 2008 2005 United Kingdom 2001 IS, 1999 Yes 2010 2009 2011 2007 United States 2010 LFS, 2000 Yes 2007 2008 2011 2005 Uruguay 2011 MICS, 2012 IHS, 2011 Yes 2011 2008 2009 2000 Uzbekistan 1989 MICS, 2006 ES/BS, 2003 Yes 2005 Vanuatu 2009 MICS, 2007 2007 2011 Venezuela, R.B. 2011 MICS, 2000 IHS, 2011 Yes 2007 2011 2000 Vietnam 2009 MICS, 2010/11 IHS, 2010 Yes 2011 2000 2010 2005 Virgin Islands (U.S.) 2010 Yes 2007 West Bank and Gaza 2007 MICS, 2010 IHS, 2009 1971 2009 2011 2005 Yemen, Rep. 2004 MICS, 2006 ES/BS, 2005 2006 2011 2005 Zambia 2010 DHS, 2007 IHS, 2010 2011 2002 Zimbabwe 2012 DHS, 2010/11 IHS, 2003/04 2011 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. Latest population census: Guernsey, 2009; Jersey, 2011. d. 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. e. Rolling census based on continuous sample survey. f. Reporting period switch from fiscal year to calendar year from 1996. Pre-1996 data converted to calendar year. g. Includes South Sudan. Economy States and markets Global links Back World Development Indicators 2013 115 Primary data documentation notes • Base year is the base or pricing period used for con- on withdrawal from customs storage. Exports under demographic, education, or health household survey stant price calculations in the country’s national the general system comprise outward-moving goods: indicates the household surveys used to compile the accounts. Price indexes derived from national accounts (a) national goods wholly or partly produced in the coun- demographic, education, and health data in section 2. aggregates, such as the implicit deflator for gross try; (b) foreign goods, neither transformed nor declared AIS is HIV/AIDS Indicator Survey, DHS is Demographic domestic product (GDP), express the price level rela- for domestic consumption in the country, that move and Health Survey, ENPF is National Family Planning tive to base year prices. • Reference year is the year outward from customs storage; and (c) nationalized Survey, FHS is Family Health Survey, HIV/MCH is in which the local currency constant price series of a goods that have been declared for domestic consump- HIV/Maternal and Child Health, IBEP is Integrated Sur- country is valued. The reference year is usually the tion and move outward without being transformed. vey on Population Welfare, LSMS is Living Standards same as the base year used to report the constant Under the special system of trade, exports are catego- Measurement Study Survey, MICS is Multiple Indicator price series. However, when the constant price data ries a and c. In some compilations categories b and c Cluster Survey, MIS is Malaria Indicator Survey, NSS are chain linked, the base year is changed annually, so are classified as re-exports. Direct transit trade— is National Sample Survey on Population Change, the data are rescaled to a specific reference year to goods entering or leaving for transport only—is PAPFAM is Pan Arab Project for Family Health, RHS is provide a consistent time series. When the country has excluded from both import and export statistics. • Gov- Reproductive Health Survey, SHHS is Sudan House- not rescaled following a change in base year, World ernment finance accounting concept is the account- hold Health Survey, and SPA is Service Provision Bank staff rescale the data to maintain a longer histori- ing basis for reporting central government financial Assessments. Detailed information for AIS, DHS, MIS, cal series. To allow for cross-country comparison and data. For most countries government finance data have and SPA are available at www.measuredhs.com; for data aggregation, constant price data reported in been consolidated (C) into one set of accounts captur- MICS at www.childinfo.org; and for RHS at www.cdc World Development Indicators are rescaled to a com- ing all central government fiscal activities. Budgetary .gov/reproductivehealth. •  Source of most recent mon reference year (2000) and currency (U.S. dollars). central government accounts (B) exclude some central income and expenditure data shows household sur- • System of National Accounts identifies whether a government units. • IMF data dissemination standard veys that collect income and expenditure data. Names country uses the 1968, 1993, or 2008 System of shows the countries that subscribe to the IMF’s Spe- and detailed information on household surveys can be National Accounts (SNA). • SNA price valuation shows cial Data Dissemination Standard (SDDS) or General found on the website of the International Household whether value added in the national accounts is Data Dissemination System (GDDS). S refers to coun- Survey Network (www.surveynetwork.org). Core Wel- reported at basic prices (B) or producer prices (P). Pro- tries that subscribe to the SDDS and have posted data fare Indicator Questionnaire Surveys (CWIQ), devel- ducer prices include taxes paid by producers and thus on the Dissemination Standards Bulletin Board at oped by the World Bank, measure changes in key social tend to overstate the actual value added in production. http://dsbb.imf.org. G refers to countries that sub- indicators for different population groups—specifically However, value added can be higher at basic prices scribe to the GDDS. The SDDS was established for indicators of access, utilization, and satisfaction with than at producer prices in countries with high agricul- member countries that have or might seek access to core social and economic services. Expenditure tural subsidies. • Alternative conversion factor identi- international capital markets to guide them in providing budget surveys (ES/BS) collect detailed infor- survey/­ fies the countries and years for which a World Bank– their economic and financial data to the public. The mation on household consumption as well as on gen- estimated conversion factor has been used in place of GDDS helps countries disseminate comprehensive, eral demographic, social, and economic characteris- the official exchange rate (line rf in the International timely, accessible, and reliable economic, financial, tics. Integrated household surveys (IHS) collect Monetary Fund’s [IMF] International Financial Statis- and sociodemographic statistics. IMF member coun- detailed information on a wide variety of topics, includ- tics). See Statistical methods for further discussion of tries elect to participate in either the SDDS or the ing health, education, economic activities, housing, alternative conversion factors. • Purchasing power GDDS. Both standards enhance the availability of and utilities. Income surveys (IS) collect information parity (PPP) survey year is the latest available survey timely and comprehensive data and therefore contrib- on the income and wealth of households as well as year for the International Comparison Program’s esti- ute to the pursuit of sound macroeconomic policies. various social and economic characteristics. Income mates of PPPs. • Balance of Payments Manual in use The SDDS is also expected to improve the functioning tax registers (ITR) provide information on a population’s refers to the classification system used to compile and of financial markets. •  Latest population census income and allowance, such as gross income, taxable report data on balance of payments. 6 refers to the 6th shows the most recent year in which a census was income, and taxes by socioeconomic group. Labor edition of the IMF’s Balance of Payments Manual conducted and in which at least preliminary results force surveys (LFS) collect information on employment, (2009). • External debt shows debt reporting status have been released. The preliminary results from the unemployment, hours of work, income, and wages. for 2011 data. A indicates that data are as reported, very recent censuses could be reflected in timely revi- Living Standards Measurement Study Surveys (LSMS), P that data are based on reported or collected informa- sions if basic data are available, such as population developed by the World Bank, provide a comprehensive tion but include an element of staff estimation, and E by age and sex, as well as the detailed definition of picture of household welfare and the factors that affect that data are World Bank staff estimates. • System of counting, coverage, and completeness. Countries that it; they typically incorporate data collection at the indi- trade refers to the United Nations general trade system hold register-based censuses produce similar census vidual, household, and community levels. Priority sur- (G) or special trade system (S). Under the general trade tables every 5 or 10 years. Germany’s 2001 census is veys (PS) are a light monitoring survey, designed by the system goods entering directly for domestic consump- a register-based test census using a sample of 1.2 World Bank, that collect data from a large number of tion and goods entered into customs storage are percent of the population. A rare case, France has been households cost-effectively and quickly. 1-2-3 (1-2-3) recorded as imports at arrival. Under the special trade conducting a rolling census every year since 2004; the surveys are implemented in three phases and collect system goods are recorded as imports when declared 1999 general population census was the last to cover demographic and employment data, data on the socio­ for domestic consumption whether at time of entry or the entire population simultaneously. •  Latest informal sector, and information on living conditions 116  World Development Indicators 2013 Front ? User guide view People World view People Environment Primary data documentation notes and household consumption. • Vital registration com - sourced from the IMF and differ from the Central Sta- have been revised for 1990 onward; the new base year plete identifies countries that report at least 90 per- tistics Organization numbers due to exclusion of the is 1990. • Croatia. Based on official government sta- cent complete registries of vital (birth and death) sta- opium economy. • Angola. Based on IMF data, national tistics, the new base year for constant price series is tistics to the United Nations Statistics Division and are accounts data have been revised for 2000 onward; 2005. • Eritrea. Based on IMF data, national accounts reported in its Population and Vital Statistics Reports. the new base year is 2002. • Australia. Value added data have been revised for 2000 onward; the new base Countries with complete vital statistics registries may series data are taken from the United Nations National year is 2000. • The Gambia. Based on official gov- have more accurate and more timely demographic Accounts Main Aggregates, and gross national income ernment statistics, national accounts data have been indicators than other countries. • Latest agricultural is computed using Australian Bureau of Statistics revised for 2004 onward; the new base year is 2004. census shows the most recent year in which an agri- data. • Bhutan. Data were updated recently using the • Guinea. Based on IMF data, national accounts data cultural census was conducted and reported to the government of Bhutan macroeconomic framework. have been revised for 2000 onward; the new base Food and Agriculture Organization of the United • China. National accounts historical data for expendi- year is 2003. • Hong Kong SAR, China. Agriculture Nations. • Latest industrial data show the most recent ture series in constant prices have been revised based value added includes mining and quarrying. • India. year for which manufacturing value added data at the on National Statistics Bureau data not previously avail- The India Central Statistical Office revised historical three-digit level of the International Standard Industrial able. • Democratic Republic of Congo. Based on IMF data series both current and constant going back to Classification (revision  2 or 3) are available in the data, national accounts data have been revised for 1960 with 2004–05 as the base. • Jamaica. Based United Nations Industrial Development Organization 2000 onward; the new base year is 2000. • Republic on official government statistics, national accounts database. • Latest trade data show the most recent of Congo. Based on IMF data, national accounts data data have been revised for 2002 onward; the new year for which structure of merchandise trade data base year is 2007. • Kiribati. Based on data from the from the United Nations Statistics Division’s Commod- Economies with exceptional reporting periods Asian Development Bank, national accounts data have ity Trade (Comtrade) database are available. • Latest Reporting period been revised for 2005 onward. • Liberia. Based on IMF Fiscal for national water withdrawal data show the most recent year for Economy year end accounts data data, national accounts data have been revised for which data on freshwater withdrawals have been com- Afghanistan Mar. 20 FY 2000 onward; the new base year is 2000. • Malawi. piled from a variety of sources. Australia Jun. 30 FY Based on IMF data, national accounts data have been Bangladesh Jun. 30 FY revised for 2003 onward; the new base year is 2007. Exceptional reporting periods Botswana Jun. 30 FY • Malaysia. Based on data from the National Statistics In most economies the fiscal year is concurrent with Canada Mar. 31 CY Office, national accounts data in current prices have the calendar year. Exceptions are shown in the table Egypt, Arab Rep. Jun. 30 FY been revised for 2005 onward. • Nicaragua. Based on at right. The ending date reported here is for the fis- Ethiopia Jul. 7 FY official government statistics, national accounts data cal year of the central government. Fiscal years for Gambia, The Jun. 30 CY have been revised for 1994 onward; the new base other levels of government and reporting years for Haiti Sep. 30 FY year is 2006. • Palau. Based on IMF data, national statistical surveys may differ. India Mar. 31 FY accounts data have been revised for 2007 onward. The reporting period for national accounts data is Indonesia Mar. 31 CY • Rwanda. Based on official government statistics, designated as either calendar year basis (CY) or fiscal Iran, Islamic Rep. Mar. 20 FY national accounts data have been revised for 1999 year basis (FY). Most economies report their national Japan Mar. 31 CY onward; the new base year is 2006. • Samoa. Based accounts and balance of payments data using calen- Kenya Jun. 30 CY on IMF data, national accounts data have been revised dar years, but some use fiscal years. In World Devel- Kuwait Jun. 30 CY for 2007 onward. • Seychelles. Based on official gov- opment Indicators fiscal year data are assigned to Lesotho Mar. 31 CY ernment statistics, national accounts data have been the calendar year that contains the larger share of Malawi Mar. 31 CY revised for 1976 onward; the new base year is 2006. the fiscal year. If a country’s fiscal year ends before Myanmar Mar. 31 FY • Sierra Leone. Based on official government statis- June 30, data are shown in the first year of the fiscal Namibia Mar. 31 CY tics, national accounts data have been revised for period; if the fiscal year ends on or after June 30, data Nepal Jul. 14 FY 1990 onward; the new base year is 2006. • Syrian are shown in the second year of the period. Balance New Zealand Mar. 31 FY Arab Republic. Based on data from the Central Bureau of payments data are reported in World Development Pakistan Jun. 30 FY of Statistics, national accounts data have been revised Indicators by calendar year. Puerto Rico Jun. 30 FY for 2003 onward. • Togo. Based on IMF data, national Sierra Leone Jun. 30 CY accounts data have been revised for 2000; the new Revisions to national accounts data Singapore Mar. 31 CY base year is 2000. • Tonga. Based on data from the National accounts data are revised by national sta- South Africa Mar. 31 CY National Bureau of Statistics, national accounts data tistical offices when methodologies change or data Swaziland Mar. 31 CY have been revised; the new base year is 2010/11. sources improve. National accounts data in World Sweden Jun. 30 CY • Tuvalu. Based on IMF data, national accounts data Thailand Sep. 30 CY Development Indicators are also revised when data for 2000 onward have been revised. • United Arab Uganda Jun. 30 FY sources change. The following notes, while not com- Emirates. Based on data from the National Bureau of United States Sep. 30 CY prehensive, provide information on revisions from pre- Statistics, national accounts data have been revised Zimbabwe Jun. 30 CY vious data. • Afghanistan. National accounts data are for 2001 onward; the new base year is 2007. Economy States and markets Global links Back World Development Indicators 2013 117 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 2000. tors. It covers the methods employed for calculating Missing values in 2000 are imputed using one of regional and income group aggregates and for calcu- several proxy variables for which complete data lating growth rates, and it describes the World Bank are available in that year. The imputed value is Atlas method for deriving the conversion factor used calculated so that it (or its proxy) bears the same to estimate gross national income (GNI) and GNI per relationship to the total of available data. Imputed capita in U.S. dollars. Other statistical procedures values are usually not calculated if missing data and calculations are described in the About the data account for more than a third of the total in the sections following each table. benchmark year. The variables used as proxies are GNI in U.S. dollars; total population; exports and Aggregation rules imports of goods and services in U.S. dollars; and Aggregates based on the World Bank’s regional and value added in agriculture, industry, manufactur- income classifications of economies appear at the ing, and services in U.S. dollars. end of the tables, including most of those available • Aggregates marked by an sare sums of available online. The 214 economies included in these classifi- data. Missing values are not imputed. Sums are cations are shown on the flaps on the front and back not computed if more than a third of the observa- covers of the book. Aggregates also contain data for tions in the series or a proxy for the series are Taiwan, China. Most tables also include the aggregate missing in a given year. for the euro area, which includes the member states • Aggregates of ratios are denoted by a wwhen 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 France, Germany, Greece, Ireland, Italy, Luxembourg, u when calculated as unweighted averages. The Malta, Netherlands, Portugal, Slovak Republic, Slo- aggregate ratios are based on available data. Miss- venia, and Spain. Other classifications, such as the ing values are assumed to have the same average European Union, are documented in About the data value as the available data. No aggregate is calcu- for 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 wwhen 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. 118  World Development Indicators 2013 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 into growth rates of values are computed from constant account the intermediate values of the series. Nor does price series. Three principal methods are used to cal- it correspond to the annual rate of change measured culate growth rates: least squares, exponential end- at a one-year interval, which is given by (pn – pn–1)/pn–1. point, and geometric endpoint. Rates of change from one period to the next are calculated as proportional Geometric growth rate. The geometric growth changes from the earlier period. rate is applicable to compound growth over discrete periods, such as the payment and reinvestment of Least squares growth rate. Least squares growth interest or dividends. Although continuous growth, as rates are used wherever there is a sufficiently long modeled by the exponential growth rate, may be more time series to permit a reliable calculation. No growth realistic, most economic phenomena are measured rate is calculated if more than half the observations in only at intervals, in which case the compound growth a period are missing. The least squares growth rate, r, model is appropriate. The average growth rate over n is estimated by fitting a linear regression trend line to periods is calculated as the logarithmic annual values of the variable in the rel- evant period. The regression equation takes the form r = exp[ln(pn/p0)/n] – 1. ln Xt = a + bt World Bank Atlas method which is the logarithmic transformation of the com- In calculating GNI and GNI per capita in U.S. dollars pound growth equation, for certain operational purposes, the World Bank uses Xt = Xo (1 + r )t. the Atlas conversion factor. The purpose of the Atlas conversion factor is to reduce the impact of exchange In this equation X is the variable, t is time, and a = ln Xo rate fluctuations in the cross-country comparison of and b = ln (1 + r) are parameters to be estimated. If national incomes. b* is the least squares estimate of b, then the aver- The Atlas conversion factor for any year is the aver- age annual growth rate, r, is obtained as [exp(b*) – 1] age of a country’s exchange rate (or alternative conver- and is multiplied by 100 for expression as a percent- sion factor) for that year and its exchange rates for age. The calculated growth rate is an average rate that the two preceding years, adjusted for the difference is representative of the available observations over between the rate of inflation in the country and that the entire period. It does not necessarily match the in Japan, the United Kingdom, the United States, and actual growth rate between any two periods. the euro area. A country’s inflation rate is measured by the change in its GDP deflator. Exponential growth rate. The growth rate between The inflation rate for Japan, the United Kingdom, two points in time for certain demographic indicators, the United States, and the euro area, representing Economy States and markets Global links Back World Development Indicators 2013 119 Statistical methods international inflation, is measured by the change in and the calculation of GNI per capita in U.S. dollars the “SDR deflator.� (Special drawing rights, or SDRs, for year t: are the International Monetary Fund’s unit of account.) The SDR deflator is calculated as a weighted average Yt$ = (Yt/Nt)/et* of these countries’ GDP deflators in SDR terms, the weights being the amount of each country’s currency where et* is the Atlas conversion factor (national cur- in one SDR unit. Weights vary over time because both rency to the U.S. dollar) for year t, et is the average the composition of the SDR and the relative exchange annual exchange rate (national currency to the U.S. rates for each currency change. The SDR deflator is dollar) for year t, pt is the GDP deflator for year t, ptS$ calculated in SDR terms first and then converted to is the SDR deflator in U.S. dollar terms for year t, Yt$ U.S. dollars using the SDR to dollar Atlas conversion is the Atlas GNI per capita in U.S. dollars in year t, Yt factor. The Atlas conversion factor is then applied to is current GNI (local currency) for year t, and Nt is the a country’s GNI. The resulting GNI in U.S. dollars is midyear population for year t. divided by the midyear population to derive GNI per capita. Alternative conversion factors When official exchange rates are deemed to The World Bank systematically assesses the appro- be unreliable or unrepresentative of the effective priateness of official exchange rates as conversion exchange rate during a period, an alternative esti- factors. An alternative conversion factor is used when mate of the exchange rate is used in the Atlas formula the official exchange rate is judged to diverge by an (see below). exceptionally large margin from the rate effectively The following formulas describe the calculation of applied to domestic transactions of foreign curren- the Atlas conversion factor for year t: cies and traded products. This applies to only a small number of countries, as shown in Primary data docu- mentation. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Devel- opment Indicators as single-year conversion factors. 120  World Development Indicators 2013 Front ? User guide World view People Environment Credits 1. World view Statistics (education and literacy); the World Health Section 1 was prepared by a team led by Eric Swan- Organization Chandika Indikadahena (health expendi- son. Eric Swanson wrote the introduction with input ture), Monika Bloessner and Mercedes de Onis (mal- from Neil Fantom, Juan Feng, Masako Hiraga, Wendy nutrition and overweight), Teena Kunjumen (health Huang, Hiroko Maeda, Johan Mistiaen, Vanessa workers), Jessica Ho (hospital beds), Rifat Hossain Moreira, Esther Naikal, William Prince, Evis Rucaj, (water and sanitation), Luz Maria de Regil (anemia), Rubena Sakaj, and Emi Suzuki. Bala Bhaskar Naidu Hazim Timimi (tuberculosis), and Lori Marie Newman Kalimili coordinated tables 1.1 and 1.6. Masako (syphilis); Leonor Guariguata of the International Dia- Hiraga, Hiroko Maeda, Johan Mistiaen, Vanessa betes Federation (diabetes); Mary Mahy of the Joint Moreira, and Emi Suzuki prepared tables 1.2 and United Nations Programme on HIV/AIDS (HIV/AIDS); 1.5. Mahyar Eshragh-Tabary, Masako Hiraga, Buyant and Colleen Murray of the United Nations Children’s Erdene Khaltarkhuu, Hiroko Maeda, Vanessa Moreira, Fund (health). Eric Swanson provided comments and and Emi Suzuki prepared table 1.3. Wendy Huang suggestions on the introduction and at all stages of prepared table 1.4 with input from Azita Amjadi. Signe production. Zeikate of the World Bank’s Economic Policy and Debt Department provided the estimates of debt relief for 3. Environment the Heavily Indebted Poor Countries Debt Initiative Section 3 was prepared by Mahyar Eshragh-Tabary and Multilateral Debt Relief Initiative. in partnership with the Agriculture and Environmen- tal Services Department of the Sustainable Devel- 2. People opment Network Vice Presidency of the World Bank. Section 2 was prepared by Juan Feng, Masako Hiraga, Mahyar Eshragh-Tabary wrote the introduction with Hiroko Maeda, Johan Mistiaen, Vanessa Moreira, Emi suggestions from Eric Swanson. Other contributors Suzuki, and Eric Swanson in partnership with the include Esther G. Naikal and Karen Treanton of the World Bank’s Human Development Network and the International Energy Agency, Gerhard Metchies and Development Research Group in the Development Armin Wagner of German International Cooperation, Economics Vice Presidency. Emi Suzuki prepared the Craig Hilton-Taylor and Caroline Pollock of the Interna- demographic estimates and projections. The poverty tional Union for Conservation of Nature, and Cristian estimates at national poverty lines were compiled Gonzalez of the International Road Federation. The by the Global Poverty Working Group, a team of pov- World Bank’s Agriculture and Environmental Services erty experts from the Poverty Reduction and Equality Department devoted generous staff resources. Network, the Development Research Group, and the Development Data Group. Shaohua Chen and Prem 4. Economy Sangraula of the World Bank’s Development Research Section 4 was prepared by Bala Bhaskar Naidu Kali- Group prepared the poverty estimates at international mili in close collaboration with the Sustainable Devel- poverty lines. Lorenzo Guarcello and Furio Rosati of opment and Economic Data Team of the World Bank’s the Understanding Children’s Work project prepared Development Data Group and with suggestions from the data on children at work. Other contributions Liu Cui and William Prince. Bala Bhaskar Naidu Kali- were provided by Samuel Mills (health); Maddalena mili wrote the introduction with suggestions from Eric Honorati, Montserrat Pallares-Miralles, and Claudia Swanson. The highlights section was prepared by Bala Rodríguez (vulnerability and security); Theodoor Spar- Bhaskar Naidu Kalimili, Maurice Nsabimana, and Olga reboom and Alan Wittrup of the International Labour Victorovna Vybornaia. The national accounts data for Organization (labor force); Amélie Gagnon, Said Ould low- and middle-income economies were gathered by Voffal, and Weixin Lu of the United Nations Educa- the World Bank’s regional staff through the annual tional, Scientific and Cultural Organization Institute for Unified Survey. Federico M. Escaler, Mahyar Eshragh- Economy States and markets Global links Back World Development Indicators 2013 121 Credits Tabary, Bala Bhaskar Naidu Kalimili, Buyant Erdene Trade and Development (information and communi- Khaltarkhuu, Maurice Nsabimana, and Olga Victoro- cation technology goods trade); Martin Schaaper of vna Vybornaia updated, estimated, and validated the the United Nations Educational, Scientific and Cul- databases for national accounts. Esther G. Naikal tural Organization Institute for Statistics (research prepared adjusted savings and adjusted income data. and development, researchers, and technicians); and Azita Amjadi contributed trade data from the World Ryan Lamb of the World Intellectual Property Organi- Integrated Trade Solution. The team is grateful to zation (patents and trademarks). Eurostat, the International Monetary Fund, the Organ- isation for Economic Co-operation and Development, 6. Global links the United Nations Industrial Development Organiza- Section 6 was prepared by Wendy Huang with input tion, and the World Trade Organization for access to from Evis Rucaj and Rubena Sukaj and in partner- their databases. ship with the Financial Data Team of the World Bank’s Development Data Group, Development Research 5. States and markets Group (trade), Development Prospects Group (com- Section 5 was prepared by Federico Escaler and modity prices and remittances), International Trade Buyant Erdene Khaltarkhuu in partnership with the Department (trade facilitation), and external part- World Bank’s Financial and Private Sector Develop- ners. Wendy Huang and Evis Rucaj wrote the intro- ment Network, Poverty Reduction and Economic duction, with substantial input from Eric Swanson. Management Network, and Sustainable Development Azita Amjadi (trade and tariffs) and Rubena Sukaj Network; the International Finance Corporation; and (external debt and financial data) provided substan- external partners. Buyant Erdene Khaltarkhuu wrote tial input on the data and tables. Other contributors the introduction with input from Eric Swanson. Other include Frédéric Docquier (emigration rates); Flavine contributors include Alexander Nicholas Jett (priva- Creppy and Yumiko Mochizuki of the United Nations tization and infrastructure projects); Leora Klapper Conference on Trade and Development and Mondher (business registration); Federica Saliola and Joshua Mimouni of the International Trade Centre (trade); Cris- Wimpey (Enterprise Surveys); Carolin Geginat and tina Savescu (commodity prices); Jeff Reynolds and Frederic Meunier (Doing Business); Alka Banerjee, Joseph Siegel of DHL (freight costs); Yasmin Ahmad Trisha Malinky, and Michael Orzano (Standard & and Elena Bernaldo of the Organisation for Economic Poor’s global stock market indexes); Gary Milante Co-operation and Development (aid); Ibrahim Levent and Kenneth Anya (fragile situations); Satish Man- and Maryna Taran (external debt); Gemechu Ayana nan (public policies and institutions); James Hackett Aga and Ani Rudra Silwal (remittances); and Teresa of the International Institute for Strategic Studies Ciller of the World Tourism Organization (tourism). (military personnel); Sam Perlo-Freeman of the Stock- Ramgopal Erabelly, Shelley Fu, and William Prince holm International Peace Research Institute (military provided technical assistance. expenditures and arms transfers); Christian Gonzalez of the International Road Federation, Zubair Anwar Other parts of the book and Narjess Teyssier of the International Civil Aviation Jeff Lecksell of the World Bank’s Map Design Unit Organization, and Marc Juhel and Hélène Stephan coordinated preparation of the maps on the inside cov- (transport); Vincent Valentine of the United Nations ers. Alison Kwong and William Prince prepared User Conference on Trade and Development (ports); Azita guide and the lists of online tables and indicators for Amjadi (high-tech exports); Vanessa Grey, Esperanza each section. Eric Swanson wrote Statistical methods, Magpantay, and Susan Teltscher of the International with input from William Prince. Federico Escaler and Telecommunication Union; Torbjörn Fredriksson and Leila Rafei prepared Primary data documentation. Part- Diana Korka of the United Nations Conference on ners was prepared by Alison Kwong. 122  World Development Indicators 2013 Front ? User guide World view People Environment Database management World Development Indicators mobile applications William Prince coordinated management of the World Software preparation and testing were managed by Development Indicators database, with assistance Shelley Fu with assistance from Prashant Chaudhari, from Liu Cui and Shelley Fu in the Data Administration Ying Chi, Liu Cui, Ghislaine Delaine, Neil Fantom, and Quality Team. Operation of the database man- Ramgopal Erabelly, Federico Escaler, Buyant Erdene agement system was made possible by Ramgopal Khaltarkhuu, Sup Lee, Maurice Nsabimana, Parastoo Erabelly in the Data and Information Systems Team Oloumi, Beatriz Prieto Oramas, William Prince, Virginia under the leadership of Reza Farivari. Romand, Jomo Tariku, Malarvizhi Veerappan, and Vera Wen. Systems development was undertaken in the Design, production, and editing Data and Information Systems Team led by Reza Fari- Azita Amjadi and Alison Kwong coordinated all stages vari. William Prince provided data quality assurance. of production with Communications Development Incorporated, which provided overall design direction, Online access editing, and layout, led by Meta de Coquereaumont, Coordination of the presentation of the WDI online, Jack Harlow, Bruce Ross-Larson, and Christopher through the Open Data website, the World Databank Trott. Elaine Wilson created the cover and graphics application, the new table browser application, and and typeset the book. Peter Grundy, of Peter Grundy the Application Programming Interface, was provided Art & Design, and Diane Broadley, of Broadley Design, by Neil Fantom and Soong Sup Lee. Development and designed the report. maintenance of the website were managed by a team led by Azita Amjadi and including Alison Kwong, George Administrative assistance, office technology, Gongadze, Timothy Herzog, Jeffrey McCoy, and Jomo and systems development support Tariku. Systems development was managed by a team Elysee Kiti provided administrative assistance. led by Reza Farivari, with project management provided Jean-Pierre Djomalieu, Gytis Kanchas, and Nacer by Malarvizhi Veerappan. Design, programming, and Megherbi provided information technology support. testing were carried out by Ying Chi, Shelley Fu, Sid- Ugendran Machakkalai, Shanmugam Natarajan, dhesh Kaushik, Ugendran Machakkalai, Nacer Meghe- Atsushi Shimo, and Malarvizhi Veerappan provided rbi, Shanmugam Natarajan, Parastoo Oloumi, Man- software support on the Development Data Platform ish Rathore, Ashish B. Shah, Atsushi Shimo, Maryna application. Taran, and Jomo Tariku. Liu Cui and William Prince coordinated production and provided data quality Publishing and dissemination assurance. Multilingual translations of online applica- The Office of the Publisher, under the direction of tions were provided by a team led by Jim Rosenberg in Carlos Rossel, provided assistance throughout the the World Bank’s External Affairs department. production process. Denise Bergeron, Stephen McGroarty, Nora Ridolfi, and Janice Tuten coordinated Client feedback printing, marketing, and distribution. Merrell Tuck- The team is grateful to the many people who have Primdahl of the Development Economics Vice Presi- taken the time to provide feedback and suggestions, dent’s Office managed the communications strategy. which have helped improve this year’s edition. Please contact us at data@worldbank.org. Economy States and markets Global links Back World Development Indicators 2013 123 ECO-AUDIT Environmental Benefits Statement The World Bank is committed to pre- Saved: serving endangered forests and natural • 25 trees resources. The Office of the Publisher 11 million British •  has chosen to print World Development Thermal Units of Indicators 2013 on recycled paper with total energy 50 percent postconsumer fiber in accord- 2,172 pounds of net •  ance with the recommended standards for greenhouse gases paper usage set by the Green Press Initi- 11,779 gallons of •  ative, a nonprofit program supporting pub- waste water lishers in using fiber that is not sourced 789 pounds of solid •  from endangered forests. For more inform- waste ation, visit www.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 Greenland (Den) Iceland Faeroe Norway Islands (Den) Sweden Finland Russian Federation The Netherlands Estonia Isle of Man (UK) Canada Denmark Russian Latvia Fed. Lithuania United Ireland Kingdom Germany Poland Belarus Channel Islands (UK) Belgium Ukraine Luxembourg Moldova Kazakhstan Mongolia Liechtenstein France Italy Romania Switzerland Bulgaria Georgia Uzbekistan Kyrgyz Andorra Armenia Azer- Rep. Dem.People’s United States Spain baijan Turkmenistan Rep.of Korea Portugal Turkey Tajikistan Monaco Greece Japan Cyprus Syrian Rep.of Gibraltar (UK) Arab Islamic Rep. Korea Bermuda Malta Lebanon China Tunisia Rep. of Iran Afghanistan (UK) Israel Iraq Morocco Kuwait West Bank and Gaza Jordan Algeria Bahrain Pakistan Bhutan Libya Arab Rep. Qatar Nepal The Bahamas Western of Egypt Saudi Sahara Arabia Bangladesh Cayman Is.(UK) United Arab Turks and Caicos Is. (UK) Emirates India Mexico Cuba Myanmar Mauritania Oman Lao Haiti Cape Verde P.D.R. Belize Jamaica Mali Niger N. Mariana Islands (US) Chad Eritrea Rep. of Yemen Thailand Guatemala Honduras Senegal Sudan The Gambia Vietnam Guam (US) El Salvador Nicaragua Burkina Cambodia Guinea-Bissau Faso Djibouti Philippines Guinea Federated States of Micronesia Costa Rica Benin Marshall Islands Panama Nigeria Central Ethiopia Sri R.B. de Guyana Sierra Leone Côte Ghana Lanka Venezuela d’Ivoire African South Suriname Republic Sudan Brunei Darussalam Liberia Palau French Guiana (Fr) Cameroon Malaysia Colombia Togo Somalia Equatorial Guinea Maldives Uganda São Tomé and Príncipe Kenya Nauru Kiribati Congo Singapore Ecuador Gabon Rwanda Kiribati Dem.Rep.of Burundi Seychelles Congo Solomon Tanzania Papua New Guinea Islands Comoros Indonesia Tuvalu Peru Brazil Timor-Leste Samoa French Polynesia (Fr) Angola Malawi Zambia Mayotte American (Fr) Vanuatu Fiji Samoa (US) Bolivia Mozambique Fiji Zimbabwe Madagascar Tonga Mauritius Namibia Botswana New Paraguay Réunion (Fr) Caledonia Australia (Fr) Swaziland Dominican St. Martin (Fr) Germany South Republic Puerto Poland Lesotho Rico (US) St. Maarten (Neth) Africa Czech Republic Ukraine Uruguay Slovak Republic Antigua and Barbuda Chile U.S. Virgin Argentina Islands (US) Guadeloupe (Fr) Austria St. Kitts Hungary New and Nevis Zealand Dominica Slovenia Romania Croatia Martinique (Fr) Bosnia and St. Lucia Herzegovina Serbia Aruba (Neth) St. Vincent and San Curaçao (Neth) the Grenadines Barbados Marino Kosovo Bulgaria Grenada Italy Montenegro FYR Macedonia Trinidad Vatican Albania and Tobago City Greece R.B. de Venezuela Antarctica IBRD 39818 MARCH 2013