World development indicators 2014

87946 The world by income Low ($1,035 or less) Lower middle ($1,036–$4,085) Upper middle ($4,086–$12,615) High ($12,616 or more) No data Classified according to World Bank estimates of 2012 GNI per capita 2014 World Development Indicators © 2014 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved 1 2 3 4 17 16 15 14 This work is a product of the staff of The World Bank with external contributions. The indings, interpretations, and conclusions expressed in this work do not necessarily relect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. 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Other photos: Page xviii © Liang Qiang/The World Bank. Used with permission; further permission required for reuse. Page 26 © Arne Hoel/The World Bank. Used with permission; further permission required for reuse. Page 42 © Nahuel Berger/The World Bank. Used with permission; further permission required for reuse. Page 56 © Maria Fleischmann/The World Bank. Used with permission; further permission required for reuse. Page 70 © Roy Witlin/The World Bank. Used with permission; further permission required for reuse. Page 84 © Mai Ky/The World Bank. Used with permission; further permission required for reuse. Preface In 2013 the World Bank Group announced that it would focus on two overarching measurable goals: ending extreme poverty by 2030 and promoting shared prosperity. The chance to end poverty in a generation is an unprecedented opportunity—and one that requires data to monitor progress, to understand the complexities of development, and to manage the effective delivery of programs and services. World Development Indicators 2014 provides a compilation of relevant, high-quality, and internationally comparable statistics about global development and the ight against poverty. It is intended to help users of all kinds—policymakers, students, analysts, professors, program managers, and citizens—ind and use data related to all aspects of development, including those that help monitor and understand progress toward the two goals. Six themes are used to organize indicators—world view, people, environment, economy, states and markets, and global links. As in past editions, World view reviews global progress toward the Millennium Development Goals (MDGs) and provides key indicators related to poverty. A complementary online data analysis tool is available this year to allow readers to further investigate global, regional, and country progress on the MDGs: http://data.worldbank.org/mdgs. Each of the remaining sections includes an introduction; six stories highlighting speciic global, regional, or country trends; and a table of the most relevant and popular indicators for that theme, together with a discussion of indicator compilation methodology. This printed edition, and its companion The Little Data Book 2014, presents a subset of the data collected in World Development Indicators; an index to the full list of available indicators is at the end of each section. Many additional relevant indicators are available online, in database and tabular formats, and through applications for web and mobile devices, at http://data.worldbank.org/wdi. Online applications also provide the indicator description and footnotes in several languages, including Arabic, Chinese, French, and Spanish. World Development Indicators is the result of a collaborative effort of many partners, including the United Nations family, the International Monetary Fund, the International Telecommunication Union, the Organisation for Economic Co-operation and Development, the statistical ofices of more than 200 economies, and countless others. I am extremely grateful to them all—and especially to government statisticians around the world. Without their hard work, professionalism, and dedication, measuring and monitoring trends in global development, and advancing toward the new World Bank goals, would not be possible. I welcome your suggestions to improve the usefulness of World Development Indicators. Haishan Fu Director Development Economics Data Group World Development Indicators 2014 iii Acknowledgments This book was prepared by a team led by William Prince under the management of Neil Fantom and comprising Azita Amjadi, Maja Bresslauer, Liu Cui, Federico Escaler, Mahyar Eshragh-Tabary, Juan Feng, Masako Hiraga, Wendy Ven-dee Huang, Bala Bhaskar Naidu Kalimili, Haruna Kashiwase, Buyant Erdene Khaltarkhuu, Tariq Khokar, Elysee Kiti, Ibrahim Levent, Hiroko Maeda, Maurice Nsabimana, Leila Rafei, Evis Rucaj, Umar Serajuddin, Rubena Sukaj, Emi Suzuki, Jomo Tariku, and Rasiel Victor Vellos, working closely with other teams in the Development Economics Vice Presidency’s Development Data Group. World Development Indicators electronic products were prepared by a team led by Soong Sup Lee and comprising Ying Chi, Jean-Pierre Djomalieu, Ramgopal Erabelly, Shelley Fu, Omar Hadi, Gytis Kanchas, Siddhesh Kaushik, Ugendran Machakkalai, Nacer Megherbi, Shanmugam Natarajan, Parastoo Oloumi, Manish Rathore, Ashish Shah, Atsushi Shimo, and Malarvizhi Veerappan. All work was carried out under the direction of Haishan Fu. Valuable advice was provided by Poonam Gupta, Zia M. Qureshi, and David Rosenblatt. iv World Development Indicators 2014 The choice of indicators and text content was shaped through close consultation with and substantial contributions from staff in the World Bank’s four thematic networks—Sustainable Development, Human Development, Poverty Reduction and Economic Management, and Financial and Private Sector Development—and staff of the International Finance Corporation and the Multilateral Investment Guarantee Agency. Most important, the team received substantial help, guidance, and data from external partners. For individual acknowledgments of contributions to the book’s content, see Credits. For a listing of our key partners, see Partners. Communications Development Incorporated provided overall design direction, editing, and layout, led by Jack Harlow, Bruce Ross-Larson, and Christopher Trott. Elaine Wilson created the cover and graphics and typeset the book. Peter Grundy, of Peter Grundy Art & Design, and Diane Broadley, of Broadley Design, designed the report. Staff from The World Bank’s Publishing and Knowledge Division oversaw printing and dissemination of the book. Table of contents Preface iii Acknowledgments iv Partners vi User guide xii 1. World view 2. People 27 3. Environment 43 4. Economy 57 5. States and markets 71 6. Global links 85 Primary data documentation 1 Introduction MDG 1 Eradicate extreme poverty MDG 2 Achieve universal primary education MDG 3 Promote gender equality and empower women MDG 4 Reduce child mortality MDG 5 Improve maternal health MDG 6 Combat HIV/AIDS, malaria, and other diseases MDG 7 Ensure environmental sustainability MDG 8 Develop a global partnership for development Targets and indicators for each goal World view indicators About the data Online tables and indicators Poverty indicators About the data Introduction Highlights Table of indicators About the data Online tables and indicators 99 Statistical methods 110 Credits 113 World Development Indicators 2014 v Partners Deining, gathering, and disseminating international statistics is a collective effort of many people and organizations. The indicators presented in World Development Indicators are the fruit of decades of work at many levels, from the ield workers who administer censuses and household surveys to the committees and working parties of the national and international statistical agencies that develop the nomenclature, classiications, and standards fundamental to an international statistical system. Nongovernmental organizations and the private sector have also made important contributions, both in gathering primary data and in organizing and publishing their results. And academic researchers have played a crucial role in developing statistical methods and carrying on a continuing dialogue about the quality vi World Development Indicators 2014 Front ? User guide and interpretation of statistical indicators. All these contributors have a strong belief that available, accurate data will improve the quality of public and private decisionmaking. The organizations listed here have made World Development Indicators possible by sharing their data and their expertise with us. More important, their collaboration contributes to the World Bank’s efforts, and to those of many others, to improve the quality of life of the world’s people. We acknowledge our debt and gratitude to all who have helped to build a base of comprehensive, quantitative information about the world and its people. For easy reference, web addresses are included for each listed organization. The addresses shown were active on March 1, 2014. World view People Environment International and government agencies Carbon Dioxide Information Analysis Center International Diabetes Federation http://cdiac.ornl.gov www.idf.org Centre for Research on the Epidemiology of Disasters International Energy Agency www.emdat.be www.iea.org Deutsche Gesellschaft für Internationale Zusammenarbeit International Labour Organization www.giz.de www.ilo.org Food and Agriculture Organization International Monetary Fund www.fao.org www.imf.org Internal Displacement Monitoring Centre International Telecommunication Union www.internal-displacement.org www.itu.int International Civil Aviation Organization Joint United Nations Programme on HIV/AIDS www.icao.int www.unaids.org Economy States and markets Global links Back World Development Indicators 2014 vii Partners viii National Science Foundation United Nations Centre for Human Settlements, Global Urban Observatory www.nsf.gov www.unhabitat.org The Ofice of U.S. Foreign Disaster Assistance United Nations Children’s Fund www.globalcorps.com/ofda.html www.unicef.org Organisation for Economic Co-operation and Development United Nations Conference on Trade and Development www.oecd.org www.unctad.org Stockholm International Peace Research Institute United Nations Department of Economic and Social Affairs, Population Division www.sipri.org www.un.org/esa/population Understanding Children’s Work United Nations Department of Peacekeeping Operations www.ucw-project.org www.un.org/en/peacekeeping United Nations United Nations Educational, Scientiic, and Cultural Organization, Institute for Statistics www.un.org www.uis.unesco.org World Development Indicators 2014 Front ? User guide World view People Environment United Nations Environment Programme Upsalla Conlict Data Program www.unep.org www.pcr.uu.se/research/UCDP United Nations Industrial Development Organization World Bank www.unido.org http://data.worldbank.org United Nations International Strategy for Disaster Reduction World Health Organization www.unisdr.org www.who.int United Nations Ofice on Drugs and Crime World Intellectual Property Organization www.unodc.org www.wipo.int United Nations Ofice of the High Commissioner for Refugees World Tourism Organization www.unhcr.org www.unwto.org United Nations Population Fund World Trade Organization www.unfpa.org www.wto.org Economy States and markets Global links Back World Development Indicators 2014 ix Partners Private and nongovernmental organizations x Center for International Earth Science Information Network International Institute for Strategic Studies www.ciesin.org www.iiss.org Containerisation International International Road Federation www.ci-online.co.uk www.irfnet.ch DHL Netcraft www.dhl.com http://news.netcraft.com World Development Indicators 2014 Front ? User guide World view People Environment PwC World Economic Forum www.pwc.com www.weforum.org Standard & Poor’s World Resources Institute www.standardandpoors.com www.wri.org World Conservation Monitoring Centre www.unep-wcmc.org Economy States and markets Global links Back World Development Indicators 2014 xi User guide to tables World Development Indicators is the World Bank’s premier compilation of cross-country comparable data on development. The database contains more than 1,300 time series 4 Economy indicators for 214 economies and more than 30 country groups, with data for many indicators going back more than 50 years. The 2014 edition of World Development Indicators offers a condensed presentation of the principal indicators, arranged in their traditional sections, along with regional and topical highlights. Gross domestic product % of GDP % of GDP % of GDP % growth % of GDP 2012 2012 2012 2012 2012 2012 2012 .. .. .. .. .. –0.6 .. 5.7 9.4 3.1 3.5 –14.9 .. –35.5 –0.6 .. 7.2 31.9 Albania 5.0 1.3 2.1 14.5 –1.3 –10.4 –3.4 56.6 2.0 82.1 Algeria 3.7 2.8 3.3 47.5 28.3 6.0 –0.3 .. 8.9 .. .. .. .. .. .. .. .. .. Andorra .. .. .. .. .. .. .. 18.0 –25.2 12.1 .. .. 10.3 34.9 Antigua and Barbuda 2.2 .. .. 24.9 .. –6.9 –1.4 .. 3.4 102.6 Argentina 5.8a 5.0 2.8 21.9 10.1 0.0 .. .. 10.0a 33.0 –3.7 –11.1 –1.4 11.7 xii 5.0 .. .. .. .. –9.5 .. .. 0.6 68.3 .. .. 25.5 12.0 –3.7 –3.7 30.6 1.8 102.8 .. 1.7 .. .. 24.6 13.1 1.6 –2.2 75.3 2.5 .. 14.8 4.9 5.3 41.9 15.9 22.5 6.1 6.4 1.1 31.1 Bahamas, The 0.6 .. .. 8.4 .. –18.4 –4.1 47.9 2.0 76.6 Bahrain 5.4 .. .. 19.5 –0.8 9.7 –0.5 35.6 2.8 74.1 39.8 21.3 2.3 –0.9 .. –4.9 Bangladesh 6.0 Barbados 1.2 .. .. 8.4 3.6 –8.0 96.8 4.5 .. 7.5 1.0 1.5 31.5 19.7 –2.7 1.7 40.8 59.2 30.5 1.4 .. .. 20.3 7.9 –2.0 –3.6 91.1 2.8 .. 3.8 1.8 2.7 15.8 9.3 –1.3 –0.2 74.2 1.3 77.4 Benin 3.8 4.2 4.1 7.1 –5.2 –7.1 –1.4 .. 6.8 37.9 Bermuda 0.9 .. .. .. .. 14.1 .. .. .. .. 8.1 23.7 –19.7 10.9 Belarus Belgiumb Belize 6.0 5.7 8.7 7.6 .. .. 4.2 5.3 4.7 25.7 5.5 7.9 .. .. 4.6 3.8 0.8 2.0 14.5 .. –9.3 –1.2 .. 2.0 58.1 Botswana 4.2 4.6 4.9 40.7 33.2 –7.4 –1.9 .. 7.5 44.2 Brazil 3.7 2.2 2.4 14.8 4.3 –2.4 –2.6 52.8 5.4 80.8 Brunei Darussalam 1.2 .. 44.5 65.9 .. .. .. 1.7 21.7 –1.4 –2.0 15.4 3.0 79.6 7.0 7.0 22.9 8.5 –2.0 –3.2 .. 3.8 30.3 3.6 4.3 4.5 17.5 –13.7 –10.3 .. .. 18.0 23.0 Cabo Verde 6.7 2.6 2.9 35.0 .. –11.5 –9.0 .. 2.5 –4.4 78.7 Cambodia 8.1 7.0 7.0 10.6 –7.5 –8.6 2.9 50.1 Cameroon 3.3 4.8 5.0 15.8 –1.6 –3.8 .. .. 2.9 21.2 Canada 1.9 .. .. 23.6 13.0 –3.5 –1.3 53.8 1.5 Cayman Islands .. .. .. .. .. .. .. .. 4.8 –18.0 –1.8 .. .. .. 0.7 .. 5.8 18.1 Chad 9.6 5.0 8.7 .. .. .. .. .. 10.2 11.9 .. .. .. Chile 4.1 .. .. 21.4 –0.2 –3.5 1.3 10.6 7.7 7.7 51.2 35.0 2.3 .. .. 2.7 187.6 4.4 .. .. 28.3 .. 2.3 3.8 39.2 4.1 335.3 107.6 Macao SAR, China 12.7 .. .. .. .. .. .. 3.0 .. China Hong Kong SAR, China 0.5 .. .. .. Central African Republic Channel Islands .. 77.3 .. .. 57.4 .. 42.9 23.8 .. 6.1 Colombia 4.5 4.0 4.3 18.9 –3.2 –3.3 –1.1 62.6 3.2 42.9 Comoros 1.9 3.3 3.5 .. .. .. .. .. 1.8 38.3 Congo, Dem. Rep. 5.7 7.5 7.5 .. .. .. 3.8 .. 85.1 18.3 Front World Development Indicators 2014 ? User guide World view People Data presentation conventions World view 0.5 .. 4.0 5.9 Burundi 10.9 .. 73.8 Burkina Faso 0.6 .. 61.2 Bulgaria • Data for years that are more than three years from the range shown are footnoted. • The cutoff date for data is February 1, 2014. User guide 69.7 Bosnia and Herzegovina the map on the inside back cover and the list on the back cover lap. For further discussion of aggregation methods, see Statistical methods. ? 6.2 Bolivia The aggregate measures for regions cover only low- and middle-income economies. The country composition of regions is based on the World Bank’s analytical regions and may differ from common geographic usage. For regional classiications, see Front 33.7 3.2 3.1 • A blank means not applicable or, for an aggregate, not analytically meaningful. • A billion is 1,000 million. • A trillion is 1,000 billion. • Figures in blue italics refer to years or periods other than those speciied or to growth rates calculated for less than the full period speciied. World Development Indicators 2014 2.6 7.6 –0.1 Aggregate measures for income groups include the 214 economies listed in the tables, plus Taiwan, China, whenever data are available. To maintain consistency in the Aggregate measures for regions .. .. 8.0 Aggregate measures for income groups aggregate measures over time and between tables, missing data are imputed where possible. 61.0 .. Bhutan 60 35.8 5.1 Azerbaijan The tables include all World Bank member countries (188), and all other economies with populations of more than 30,000 (214 total). Countries and economies are listed alphabetically (except for Hong Kong SAR, China and Macao SAR, China, which appear after China). The term country, used interchangeably with economy, Forecast 2013–14 5.9 Armenia Tables Estimate 2012–13 11.8 Angola Global links does not imply political independence but refers to any territory 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. % of GNI Broad money Afghanistan American Samoa Environment States and markets % of GDP Central Central Consumer government government price index cash surplus debt or deficit average annual % growth Austriab Economy Current account balance .. 2000–12 Aruba People Adjusted net savings Afghanistan Australia World view Gross savings People Environment Environment Classification of economies For operational and analytical purposes the World Bank’s main criterion for classifying economies is gross national Economy 4 Gross domestic product Gross savings Adjusted net savings Current account balance % of GNI % of GDP 2012 2012 Central Central Consumer government government price index cash surplus debt or deficit income (GNI) per capita (calculated using the World Bank Atlas method). Because GNI per capita changes over time, the country composition of income groups may change from one edition of World Development Indicators to the next. Once the classiication is ixed for an edition, based on GNI per capita in the most recent year for which data are available (2012 in this edition), all historical data presented are based on the same country grouping. Low-income economies are those with a GNI per capita of $1,035 or less in 2012. Middle-income economies are Broad money average annual % growth 2000–12 Estimate Forecast % of GDP 2012–13 2013–14 2012 % of GDP % of GDP % growth % of GDP 2012 2012 2012 2012 .. 3.9 31.5 .. 4.5 49.4 .. 1.3 39.0 –4.7 .. 3.4 80.7 .. .. .. .. .. .. .. .. 3.9c –6.9 –6.3 113.3 2.4 .. –2.4 –4.4 38.3 3.3 77.3 –2.0 50.6 2.4 74.6 Congo, Rep. 4.6 5.6 5.4 .. .. .. .. Costa Rica 4.7 3.4 4.3 15.9 15.1 –5.3 –3.5 Côte d’Ivoire 1.2 8.7 8.2 .. .. 2.0 –3.1 Croatia 2.1 .. .. 18.9 9.3 –0.3 Cuba 5.8 .. .. .. .. .. .. .. .. .. Curacao Cyprusb 2.6c .. .. Czech Republic 3.3 .. .. 21.0 5.1 .. Denmark 0.6 23.6 15.7 Djibouti 3.5 .. .. .. .. .. .. .. 3.7 3.2 1.1 1.7 10.8 .. –11.5 –11.9 .. 1.4 97.4 Dominican Republic 5.6 2.5 3.9 9.2 .. –6.8 –2.9 .. 3.7 34.3 6.1 Ecuador Egypt, Arab Rep. Equatorial Guinea Eritrea Estoniab 5.9 .. .. Dominica El Salvador .. 8.8c .. 4.4 4.0 4.1 26.9 –0.2 .. 4.9 1.8 2.3 13.0 0.0 –2.7 –10.6 .. 7.1 74.1 2.0 1.9 2.3 8.9 6.6 –5.3 –2.2 47.8 1.7 44.6 10.9 .. .. .. .. .. .. .. 6.1 18.7 6.0 3.5 .. .. .. .. .. .. 114.7 –1.8 0.9 3.7 5.1 31.6 .. 25.0 12.5 1.0 6.9 3.9 7.2 28.8 6.1 –7.2 –1.4 .. 22.8 .. .. .. .. .. .. .. .. .. .. Fiji 1.2 2.4 2.1 .. .. –1.4 .. .. 3.4 68.8 Finlandb 1.7 .. .. 18.1 7.6 –1.5 –0.5 48.0 2.8 Franceb 1.1 .. .. 17.5 9.9 –2.2 –5.1 93.7 2.0 .. .. .. .. .. .. .. .. .. .. .. Ethiopia 8.9 Faeroe Islands French Polynesia Gabon 2.4 .. .. 7.0 4.2 4.2 .. Gambia, The 3.4 6.5 7.5 17.1 Georgia 6.5d 2.5d 6.3d 18.3d Germany b 1.1 .. .. 24.2 Ghana 6.6 7.4 7.4 Greeceb 1.1 .. .. .. 0.9 .. .. .. 2.7 59.6 .. 20.8 6.4 .. .. 4.3 53.6 –11.7 –0.5 32.6 –0.9 30.2 15.8 7.0 –0.4 55.3 2.0 .. 21.5 2.7 –11.7 –3.9 .. 9.2 31.3 9.8 –4.3 –2.5 –9.8 106.5 1.5 7.0 d .. Greenland 1.7 .. .. .. .. .. .. .. .. .. Grenada 1.9 1.1 1.1 –10.2 .. –28.0 –5.8 .. 2.4 95.4 .. .. .. .. .. .. .. .. .. .. 3.5 3.3 3.4 12.0 –2.3 –2.6 –2.3 –42.8 Guam Guatemala 24.4 3.8 Guinea 2.6 –18.4 .. .. 15.2 36.4 Guinea-Bissau 2.3 3.0 2.7 1.5 –22.4 –8.5 .. .. 2.1 38.8 Guyana 1.7 4.4 3.9 11.1 –11.8 –13.9 .. .. 2.4 67.0 Haiti 0.8 3.4 4.2 25.6 12.7 –4.4 .. .. 6.3 45.8 Honduras 4.3 2.9 3.4 16.5 11.4 –8.6 –3.2 .. 5.2 51.0 Hungary 1.6 0.7 1.7 23.4 12.4 0.9 3.7 82.4 5.7 60.9 119.1 5.2 89.8 Iceland 2.4 4.0 4.7 –6.2 46.2 .. .. 9.3 .. –5.5 –5.3 4.8 6.2 30.3 14.8 –4.9 –3.8 49.7 9.3 75.6 Indonesia 5.5 5.6 5.3 32.0 24.1 –2.7 –1.1 26.2 4.3 40.1 Iran, Islamic Rep. 4.8 –1.5 1.0 .. .. .. .. .. 27.3 19.7 Iraq 5.1 4.2 6.5 26.7 .. 13.7 .. .. 5.8 30.7 Irelandb 2.2 .. .. 16.0 10.9 4.4 –13.0 102.0 1.7 .. Isle of Man 6.2 .. .. .. .. .. .. .. .. .. India 7.7 Economy States and markets Global links Back those with a GNI per capita of more than $1,035 but less than $12,616. Lower middle-income and upper middleincome economies are separated at a GNI per capita of $4,085. High-income economies are those with a GNI per capita of $12,616 or more. The 18 participating member countries of the euro area are presented as a subgroup under high-income economies. .. World Development Indicators 2014 Statistics Additional information about the data is provided in Pri61 mary data documentation, which summarizes national and international efforts to improve basic data collection and gives country-level information on primary sources, census years, iscal years, statistical methods and concepts used, and other background information. Statistical methods provides technical information on some of the general calculations and formulas used throughout the book. Symbols Country notes .. • Cabo Verde is the new name for the country previously listed as Cape Verde. • Data for China do not include data for Hong Kong SAR, China; Macao SAR, China; or Taiwan, China. • Data for Serbia do not include data for Kosovo or Montenegro. • Data for Sudan include South Sudan unless otherwise noted. means that data are not available or that aggregates cannot be calculated because of missing data in the years shown. 0 or means zero or small enough that the number would 0.0 round to zero at the displayed number of decimal places. / in dates, as in 2011/12, means that the period of time, usually 12 months, straddles two calendar years and refers to a crop year, a survey year, or a iscal year. $ means current U.S. dollars unless otherwise noted. < means less than. Economy States and markets Global links Back World Development Indicators 2014 xiii User guide to WDI online tables Statistical tables that were previously available in the use the URL http://wdi.worldbank.org/table/ and the World Development Indicators print edition are available online. Using an automated query process, these refer- table number (for example, http://wdi.worldbank.org /table/1.1 to view the i rst table in the World view sec- ence tables are consistently updated based on revisions to tion). Each section of this book also lists the indicators the World Development Indicators database. included by table and by code. To view a specii c indicator online, use the URL http://data.worldbank.org /indicator/ and the indicator code (for example, http://data .worldbank.org/indicator/SP.POP.TOTL to view a page for total population). How to access WDI online tables To access the WDI online tables, visit http://wdi.worldbank .org/tables. To access a speciic WDI online table directly, xiv World Development Indicators 2014 Front ? User guide World view People Environment Breadcrumbs to show where you’ve been Click on an indicator to view metadata Click on a country to view metadata How to use DataBank Actions DataBank (http://databank.worldbank.org) is a web resource that provides simple and quick access to collections of time series data. It has advanced functions Click to edit and revise the table in DataBank Click to download corresponding indicator metadata for selecting and displaying data, performing customized queries, downloading data, and creating charts and maps. Users can create dynamic custom reports based on their selection of countries, indicators, and years. All these reports can be easily edited, saved, shared, and embedded as widgets on websites or blogs. For more information, see http://databank.worldbank.org/help. Click to export the table to Excel Click to export the table and corresponding indicator metadata to PDF Click to print the table and corresponding indicator metadata Click to access the WDI Online Tables Help ile Click the checkbox to highlight cell level metadata and values from years other than those speciied; click the checkbox again to reset to the default display Economy States and markets Global links Back World Development Indicators 2014 xv User guide to DataFinder xvi 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 database. Data can be displayed and saved in a table, chart, tablet computer) in both ofline (no Internet connection) and online (Wi-Fi or 3G/4G connection to the Internet) or map and shared via email, Facebook, and Twitter. modes. • • • • • View reports in table, chart, and map formats. • Send the data as a CSV ile attachment to an email. • Share comments and screenshots via Facebook, Twitter, or email. Select a topic to display all related indicators. Compare data for multiple countries. Select predeined queries. Create a new query that can be saved and edited later. World Development Indicators 2014 Front ? User guide World view People Environment Table view provides time series data tables of key development 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 comparisons as line or bar charts. Map view colors selected indicators on world and regional maps. A motion option animates the data changes from year to year. Economy States and markets Global links Back World Development Indicators 2014 xvii User guide to MDG Data Dashboards The World Development Indicators database provides data Development Indicators. Suficient progress indicates that on trends in Millennium Development Goals (MDGs) indicators for developing countries and other country groups. the MDG will be attained by 2015 based on an extrapolation of the last observed data point using the growth Each year the World Bank’s Global Monitoring Report uses rate over the last observable i ve-year period (or seven- these data to assess progress toward achieving the MDGs. Six online interactive MDG Data Dashboards, available at http://data.worldbank.org/mdgs, provide an opportunity to learn more about the assessments. The MDG progress charts presented in the World view section of this book correspond to the Global Monitoring Report assessments (except MDG 6) and cannot be compared with those in previous editions of World year period, in the case of MDG 7). Insufi cient progress indicates that the MDG will be met between 2016 and 2020. Moderately off track indicates that the MDG will be met between 2020 and 2030. Seriously off track indicates that the MDG will not be met by 2030. Insufi cient data indicates an inadequate number of data points to estimate progress or that the MDG’s starting value is missing. View progress status for regions, income classiications, and other groups by number or percentage of countries. xviii World Development Indicators 2014 Front ? User guide World view People Environment View details of a country’s progress toward each MDG target, including trends from 1990 to the latest year of available data, and projected trends toward the 2015 target and 2030. Compare trends and targets of each MDG indicator for selected groups and countries. Compare the progress status of all MDG indicators across selected groups. Economy States and markets Global links Back World Development Indicators 2014 xix WORLD VIEW xx World Development Indicators 2014 Front ? User guide World view People Environment World view presents progress toward the eight Millennium Development Goals (MDGs), drawing on the charts of progress in online interactive visualizations (http://data.worldbank.org /mdgs). It complements the detailed analysis in the World Bank Group’s Global Monitoring Report, and it uses the same methodology to assess whether countries are on track or off track to meet the targets by 2015. The new twin goals of the World Bank Group, announced in October 2013, are to end extreme poverty and to boost shared prosperity across the world. Progress will be closely monitored using two indicators: the proportion of the population living on less than $1.25 a day (in 2005 purchasing power parity terms) and the growth in the average real per capita income of the bottom 40 percent of the population in every country. While poverty rates have fallen across the world, progress has been uneven, and meeting the new targets will require a sustained effort. As Jim Yong Kim said in the World Bank’s 2013 Annual Report, “We must halve poverty once, then halve it again, and then nearly halve it a third time—all in less than one generation.” Two tables in World view present the latest estimates of poverty rates at the international poverty line. The World Development Indicators online database and tabular presentations also present poverty rates at national poverty lines. Work is under way to develop a reliable database of growth in the per capita incomes of the bottom 40 percent of the population in most countries. We expect to publish it later in 2014 as part of World Development Indicators online. Economy States and markets The target year of 2015 for the MDGs is now just around the corner. One important aspect of the MDGs has been their focus on measuring and monitoring progress; this has presented a clear challenge in improving the quality, frequency, and availability of relevant statistics. In the last few years much has been done by both countries and international partners to invest in the national statistical systems where most data originate. But weaknesses remain in the coverage and quality of many indicators in the poorest countries, where resources are scarce and careful measurement of progress may matter the most. While the focus will continue to be on achieving the MDGs, especially in areas that have been lagging, the international community has started to discuss what comes next. The 2013 report of the 27-member HighLevel Panel on the Post-2015 Development Agenda, convened by the UN Secretary-General, recognizes the important role of data and the challenge of improving development data. It calls for a “data revolution for sustainable development, with a new international initiative to improve the quality of statistics and information available to citizens.” This is timely and welcome, as is the panel’s call to “take advantage of new technology, crowd sourcing, and improved connectivity to empower people with information on the progress toward the targets.” Both governments and development partners should invest in national statistical systems, where much of the data will continue to originate. Global links Back 1 World Development Indicators 2014 1 MDG 1 Eradicate extreme poverty Poverty rates continue to fall 1a The world will not have eradicated extreme poverty in 2015, but it will have met the Millennium Development Goal target of halv- People living on less than $1.25 a day (% of population) ing world poverty. The proportion of people in developing countries 60 Sub-Saharan Africa (those classiied as low and middle income in 1990) living on less than $1.25 a day fell from 43.1 percent in 1990 to 20.6 percent South Asia 40 in 2010 and reached a new low in ive of six developing country regions. Except in South Asia and Sub- Saharan Africa the target East Asia & Pacific was met at the regional level by 2010 (igure 1a). 20 Latin America & Caribbean Further progress is possible—and likely—before the 2015 tar- Middle East & North Africa 0 1990 Europe & Central Asia 1995 2000 get date. Developing economies are expected to maintain GDP 2005 2010 2015 target Source: World Bank PovcalNet (http://iresearch.worldbank.org/PovcalNet). growth of 5.3–5.5 percent over the next two years, with GDP per capita growth around 4.2 percent. Growth will be fastest in East Asia and Paciic and in South Asia, which still have more than half Progress in reaching the poverty target by region 1b the world’s poorest people. Growth will be slower in Sub-Saharan Africa, the poorest region, but faster than in the preceding years, Countries making progress toward reducing extreme poverty (% of countries in region) quickening the pace of poverty reduction. According to these fore- 100 casts, the proportion of people living in extreme poverty will fall to 75 16 percent by 2015. Based on current trends, around 40 percent of developing coun- 50 tries have already achieved the irst Millennium Development Goal, 25 and only 17 percent are seriously off track, based on the methodol0 Developing East Asia countries & Pacific Target met Moderately off track Europe Latin Middle East & Central America & & North Asia Caribbean Africa Sufficient progress Seriously off track South Sub-Saharan Asia Africa Insufficient progress Insufficient data ogy used in the 2013 Global Monitoring Report (World Bank 2013). However, in Sub-Saharan Africa up to a third of countries are seriously off track—meaning that they would be unable at current rates Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). of progress to halve extreme poverty rates by 2030 (igure 1b). Progress is also sluggish among countries classiied as fragile and Progress by income and lending group 1c Countries making progress toward reducing extreme poverty (% of countries in group) 100 conlict situations and small states (igure 1c). Data gaps remain and hinder the monitoring of progress. About a ifth of developing countries have not conducted a survey since 1990, the minimum requirement for monitoring progress when 75 using national accounts data to interpolate or extrapolate survey data. By number of countries the gaps are greatest in East Asia 50 and Paciic and especially among small states and fragile and con25 lict situations (igures 1b and 1c). 0 Low income Lower middle income Target met Moderately off track Upper middle income IDA Sufficient progress Seriously off track Blend IBRD Fragile & Small conlict states situations Insufficient progress Insufficient data Poverty estimates for 2010 are provisional; revised estimates will be published later in 2014, along with new estimates for 2011. Any revisions will affect estimated projections to 2015. Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). 2 World Development Indicators 2014 Front ? User guide World view People Environment MDG 2 Achieve universal primary education The commitment to provide primary education to every child is the oldest of the Millennium Development Goals, having been set at the irst Education for All conference in Jomtien, Thailand, more Growth in primary completion rate 2a Primary completion rate (% of relevant age group) 125 than 20 years ago. Latin America & Caribbean East Asia & Pacific Europe & Central Asia Primary completion rates—the proportion of new entrants in the last grade of primary school—reached nearly 90 percent for devel- 100 75 South Asia Middle East & North Africa oping countries as a whole in 2009 but have since stalled, with no appreciable gains in any region. Three regions have attained or are close to attaining universal primary education: East Asia and Sub-Saharan Africa 50 25 Paciic, Europe and Central Asia, and Latin America and the Caribbean. Completion rates in the Middle East and North Africa have stayed at 90 percent since 2009. South Asia has reached 88 per- 0 1990 1995 2000 2005 2010 2015 target Source: United Nations Educational, Scientiic and Cultural Organization Institute for Statistics and World Development Indicators database. cent, but progress has been slow. And Sub- Saharan Africa lags Progress toward universal primary education behind at 70 percent (igure 2a). Progress among the poorest countries has accelerated since 2000, particularly in South Asia and Sub- Saharan Africa, but full 2b Countries making progress toward universal primary education (% of countries in region) 100 enrollment remains elusive. Fifty-three countries have achieved or are on track to achieve the Millennium Development Goal, while 38 countries remain seriously off track (igure 2b). Even if 75 50 the schools in these countries were to now enroll every eligible 25 child in the irst grade, they would not be able to meet the 2015 deadline. 0 Developing East Asia countries & Pacific Another challenge is helping more children stay in school. Many children start school but drop out before completion, discouraged by cost, distance, physical danger, and failure to progress. Today, Target met Moderately off track Europe Latin Middle East & Central America & & North Asia Caribbean Africa Sufficient progress Seriously off track South Sub-Saharan Asia Africa Insufficient progress Insufficient data Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). 55 million primary school–age children remain out of school in lowand middle-income countries—80 percent of them in Sub-Saharan and South Asia, where dropout rates are highest (igure 2c). Even as countries approach the Millennium Development Goal Many children drop out after enrolling in school 2c Primary dropout rate, 2010–11 (%) 50 target, the education demands of modern economies expand, and 40 primary education will increasingly be of value only as a stepping stone toward secondary and higher education. In that context, 30 demand is growing for measuring and monitoring education qual- 20 ity and learning achievement. The primary completion rate does numeracy skills. 0 Girls complete basic education without acquiring adequate literacy and 10 Boys not always ensure the quality of education, and some children East Asia & Pacific Europe & Central Asia Latin America & Caribbean Middle East & North Africa South Asia Sub-Saharan Africa Source: United Nations Educational, Scientiic and Cultural Organization Institute for Statistics and World Bank EdStats database. Economy States and markets Global links Back World Development Indicators 2014 3 MDG 3 Promote gender equality and empower women Narrowing gender gap in access to education 3a development. Expanding their opportunities in the public and pri- Ratio of girls to boys in primary and secondary gross enrollment rate (%) 120 Latin America & Caribbean Women make important contributions to economic and social vate sectors is a core development strategy, and education is the East Asia & Pacific Europe & Central Asia starting point. By enrolling and staying in school, girls gain skills to 100 enter the labor market, care for families, and make decisions for Sub-Saharan Africa 80 themselves. South Asia Middle East & North Africa 60 Girls have made substantial gains in school enrollment. In 1990 girls’ primary school enrollment rate in developing countries was 40 only 86 percent of boys’. By 2011 it was 97 percent. Improvements 20 in secondary schooling have also been made, with girls’ enroll0 1990 1995 2000 2005 2010 2015 target Source: United Nations Educational, Scientiic and Cultural Organization Institute for Statistics and World Development Indicators database. ments having risen from 77 percent of boys’ in 1990 to 96 percent in 2011. But the averages mask large differences across and within countries. Low-income countries lag far behind, and only 8 Progress toward gender equality in education 3b Countries making progress toward gender equality in education (% of countries in region) 100 of 36 countries reached or exceeded equal education for girls in primary and secondary education. Poor households are less likely than wealthy households to keep their children in school, and girls from wealthier households are more likely to enroll in school and 75 stay longer. Women work long hours and contribute much to their families’ 50 welfare, but many are in the informal sector or are unpaid for their 25 labor. The highest proportion of women in wage employment in the 0 Developing East Asia countries & Pacific Target met Moderately off track Europe Latin Middle East & Central America & & North Asia Caribbean Africa Sufficient progress Seriously off track South Sub-Saharan Asia Africa Insufficient progress Insufficient data nonagricultural sector (median value) is in Europe and Central Asia (46 percent). The lowest is in Middle East and North Africa (16 percent) and South Asia (19 percent), where women’s full economic Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). empowerment remains a distant goal. More women are taking part in public life at the highest levels. Women still lack opportunities in paid employment 3c Female employees in nonagricultural wage employment, median value, most recent year available, 2004–12 (% of total nonagricultural employment) 50 The share of parliamentary seats held by women continues to increase. The largest gains have been in the Middle East and North Africa, where the proportion more than quadrupled between 1990 and 2013, though it remains a mere 16 percent. 40 Lack of data hampers the ability to understand women’s roles in 30 the economy. Led by the Inter-agency and Experts Group on Gender 20 Statistics, many new international initiatives—including the World Bank’s gender statistics projects, Evidence and Data for Gender 10 Equality, and Data2X—are tackling the paucity of data by mapping 0 Sub-Saharan Middle East South Latin Europe Africaa & North Asia & Central America & Africa Caribbean Asia a. Data cover less than two-thirds of regional population. Source: International Labour Organization Key Indicators of the Labour Market database and World Development Indicators database. 4 East Asia & Pacifica World Development Indicators 2014 Front data gaps, providing technical assistance, and developing methods to produce statistics in emerging areas. ? User guide World view People Environment MDG 4 Reduce child mortality In 1990, 13 million children died before their ifth birthday. By 1999 fewer than 10 million did. And in 2012, 7 million did. Over that time the under-ive mortality rate in developing countries fell 46 percent, Under-five mortality rates continue to fall 4a Under-ive mortality rate (per 1,000 live births) 200 from an average of 99 per 1,000 live births in 1990 to 53 in 2012. The rates remain much higher in Sub-Saharan Africa and South 150 Sub-Saharan Africa Asia than in the other four developing country regions (igure 4a). All developing regions except for Sub-Saharan Africa have halved their 100 South Asia under-ive mortality rate since 1990. Overall, progress has been substantial, but globally the rate of decline is insuficient to achieve 50 Millennium Development Goal 4 to reduce the under-ive mortality rate by two-thirds between 1990 and 2015. However, the average annual rate of decline in under-ive mortality accelerated, from 0 Middle East & North Africa East Asia & Pacific Europe & Central Asia Latin America & Caribbean 1990 1995 2000 2005 2010 2015 target Source: UN Inter-agency Group for Child Mortality Estimation and World Development Indicators database. 1.2 percent in 1990–95 to 3.9 percent in 2005–12. This recent progress is close to the average needed to be on track to achieve Millennium Development Goal 4 (igure 4b). Most children die from causes readily preventable or curable Progress toward reducing child mortality 4b Countries making progress toward reducing child mortality (% of countries in region) 100 with existing interventions, such as pneumonia (17 percent), diarrhea (9 percent), and malaria (7 percent). Roughly 70 percent of deaths of children under age 5 occur in the irst year of life, and 75 50 60 percent of those in the irst month. Preterm birth complications 25 account for 15 percent of deaths, and complications during birth another 10 percent (UNICEF 2013). Reducing child mortality thus 0 requires addressing the causes of neonatal and infant deaths: malnutrition, poor sanitation, inadequate care at and after birth, and Developing East Asia countries & Pacific Target met Moderately off track Europe Latin Middle East & Central America & & North Asia Caribbean Africa Sufficient progress Seriously off track South Sub-Saharan Asia Africa Insufficient progress Insufficient data Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). exposure to acute and chronic disease. Improving infant and child mortality are the largest contributors to higher life expectancy in most countries. Childhood vaccinations are a proven, cost-effective way of reducing childhood illness and death. But despite years of vaccination campaigns, Measles immunization rates are stagnating 4c Children ages 12–23 months immunized against measles (%) 100 Latin America & Caribbean many children in low- and lower middle-income economies remain unprotected, as with measles. To succeed, vaccination campaigns Europe & Central Asia 75 Middle East & North Africa East Asia & Pacific South Asia must reach all children and be sustained over time. That is why it is worrisome that measles vaccination rates in the two highest Sub-Saharan Africa 50 mortality regions, South Asia and Sub- Saharan Africa, have stagnated in the last three years, at less than 80 percent coverage 25 (igure 4c). 0 1990 1995 2000 2005 2010 2012 Source: World Health Organization, United Nations Children’s Fund, and World Development Indicators database. Economy States and markets Global links Back World Development Indicators 2014 5 MDG 5 Improve maternal health Maternal deaths are more likely in South Asia and Sub-Saharan Africa 5a An estimated 287,000 maternal deaths occurred worldwide in 2010, a 47 percent decline since 1990. All but 2,400 maternal Maternal mortality ratio, modeled estimate (per 100,000 live births) deaths were in developing countries. In 2010 more than half the 1,000 maternal deaths were in Sub-Saharan Africa and a quarter in South Asia. While the number of maternal deaths remains high in South 750 Sub-Saharan Africa Asia, the region has made the most progress toward the Millennium Development Goal target, reaching a maternal mortality ratio 500 250 of 220 per 100,000 live births in 2010, down from 620 in 1990, a South Asia Middle East & North Africa Latin America & Caribbean reduction of 65 percent. The Middle East and North Africa and East East Asia & Pacific 0 Asia and Paciic have also reduced their maternal mortality ratios Europe & Central Asia 1990 1995 2000 2005 2010 2015 target Source: UN Maternal Mortality Estimation Inter-agency Group and World Development Indicators database. more than 60 percent (igure 5a). These achievements are impressive, but progress in reducing maternal mortality ratios has been slow, far slower than the 75 per- Progress toward reducing maternal mortality 5b Countries making progress toward reducing maternal mortality (% of countries in region) 100 cent reduction between 1990 and 2015 imagined by the Millennium Development Goals. Few countries and no developing region on average will achieve this target. But the average annual rate of decline has accelerated, from 2.1 percent in 1990–95 to 4.3 per- 75 cent in 2005–10. This recent progress is closer to the average rate needed to be on track to achieve Millennium Development Goal 5 50 (igure 5b). 25 Better maternal health care and lower fertility can reduce 0 Developing East Asia countries & Pacific Target met Moderately off track Europe Latin Middle East & Central America & & North Asia Caribbean Africa Sufficient progress Seriously off track South Sub-Saharan Asia Africa Insufficient progress Insufficient data maternal deaths. Family planning and access to contraception can help avoid the large number of births that are unwanted or mistimed. At least 200 million women want to use safe and effec- Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). tive family planning methods but are unable to do so (igure 5c; UNFPA 2014). A wide range of needs Unmet need for contraception, most recent year available, 2007–12 (% of married women ages 15–49) 40 Many health problems among pregnant women are prevent- 5c Regional median able or treatable through visits with trained health workers before childbirth. Good nutrition, vaccinations, and treating infections can improve outcomes for mother and child. Skilled attendants 30 at delivery and access to hospital treatments are essential for dealing with life-threatening emergencies such as severe bleed- 20 ing and hypertensive disorders. In South Asia and Sub- Saharan Africa many births are not attended by doctors, nurses, or trained 10 0 midwives. East Asia & Pacific (7 countries) Europe & Central Asia Latin America & Caribbean Middle East & North Africa (4 countries) (8 countries) (2 countries) South Asia Sub-Saharan Africa (4 countries) (26 countries) Source: Household surveys, including Demographic and Health Survey and Multiple Indicator Cluster Surveys, and World Development Indicators database. 6 World Development Indicators 2014 Front ? User guide World view People Environment MDG 6 Combat HIV/AIDS, malaria, and other diseases Epidemic diseases exact a huge toll in human suffering and lost development opportunities. Poverty, armed conlict, and natural disasters contribute to the spread of disease and are made HIV prevalence in Sub-Saharan Africa continues to fall 6a HIV prevalence (% of population ages 15–49) 6 Sub-Saharan Africa worse by it. In Africa the spread of HIV/AIDS has reversed decades of improvement in life expectancy and left millions of children orphaned. Malaria takes a large toll on young children and weak- 4 ens adults at great cost to their productivity. Tuberculosis killed 900,000 people in 2012, most of them ages 15–45, and sickened 2 millions more. World In 2012 35 million people were living with HIV/AIDS, and 2.3 million more acquired the disease. Sub- Saharan Africa remains the center of the epidemic, but the proportion of adults living with AIDS South Asia 0 1990 1995 2000 2005 2010 2012 Source: Joint United Nations Programme on HIV/AIDS and World Development Indicators database. has begun to fall even as the survival rate of those with access to antiretroviral drugs has increased (igures 6a and 6b). At the end of 2012, 9.7 million people in developing countries were receiving antiretroviral drugs. The scale-up has been exponential in recent Progress toward halting and reversing the HIV epidemic 6b Countries making progress toward halting and reversing the HIV epidemic (% of countries in region) 100 years (UNAIDS 2013) but still far short of universal access. In 2012 8.6 million people were newly diagnosed with tuberculosis, but incidence, prevalence, and death rates are falling 75 50 (igure 6c). If these trends are sustained, the world could achieve 25 the target of halting and reversing the spread of tuberculosis by 2015. People living with HIV/AIDS, which reduces resistance 0 to tuberculosis, are particularly vulnerable, as are refugees, displaced persons, and prisoners living in close quarters and unsanitary conditions. Well managed medical intervention using Developing East Asia countries & Pacific Halted and reversed Not improving Europe Latin Middle East & Central America & & North Asia Caribbean Africa Halted or reversed Insufficient data South Sub-Saharan Asia Africa Stable low prevalence Source: World Bank staff calculations. appropriate drug therapy is crucial to stopping the spread of Fewer people contacting, living with, and dying from tuberculosis tuberculosis. There were an estimated 200 million cases of malaria in 2012, causing 600,000 deaths (WHO 2013). Malaria is a disease of pov- 6c Tuberculosis prevalence, incidence, and deaths in low- and middle-income countries (per 100,000 people) 400 erty, but there has been progress. Although it occurs in all regions, Sub- Saharan Africa is where the most lethal malaria parasite is 300 most abundant. Insecticide-treated nets have proved effective for prevention, and their use is growing. Prevalence 200 Incidence 100 Deaths 0 1990 1995 2000 2005 2010 2012 Source: World Health Organization and World Development Indicators database. Economy States and markets Global links Back World Development Indicators 2014 7 MDG 7 Ensure environmental sustainability Carbon dioxide emissions continue to surge to unprecedented levels 7a Millennium Development Goal 7 is the most far-reaching, affecting each person now and in the future. It addresses the condition of Carbon dioxide emissions (billions of metric tons) the natural and built environments: reversing the loss of natural 40 resources, preserving biodiversity, increasing access to safe water and sanitation, and improving living conditions of people in slums. 30 High income The overall theme is sustainability, improving people’s lives without depleting natural and humanmade capital stocks. 20 Failure to reach a comprehensive agreement on limiting greenUpper middle income 10 Low income 0 1990 1995 2000 Lower middle income 2005 2010 Source: Carbon Dioxide Information Analysis Center and World Development Indicators database. house gas emissions leaves billions of people vulnerable to climate change, with the effects expected to hit hardest in developing countries. Higher temperatures, changes in precipitation patterns, rising sea levels, and more frequent weather-related disasters pose risks for agriculture, food, and water supplies. The world released Progress toward halving the proportion of people without sustainable access to safe drinking water 7b 33.6 billion metric tons of carbon dioxide in 2010, up 5 percent over 2009 and a considerable rise of 51 percent since 1990—the baseline for Kyoto Protocol requirements (igure 7a). Global emis- Countries making progress toward halving the proportion of people without sustainable access to safe drinking water (% of countries in region) sions in 2013 are estimated at an unprecedented 36 billion tons, 100 with a growth rate of 2 percent, slightly lower than the historical 75 average of 3 percent since 2000. 50 The Millennium Development Goals call for halving the propor- 25 0 tion of people without access to an improved water source and Developing East Asia countries & Pacific Target met Moderately off track Latin Middle East South Sub-Saharan Europe Asia Africa & Central America & & North Africa Caribbean Asia Sufficient progress Insufficient progress Seriously off track Insufficient data Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). sanitation facilities by 2015. In 1990 almost 1.3 billion people worldwide lacked access to drinking water from a convenient, protected source. By 2012 that had improved to 752 million people—a 41 percent reduction. In developing countries the proportion of people with access to an improved water source rose Progress toward halving the proportion of people without sustainable access to basic sanitation 7c from 70 percent in 1990 to 87 percent in 2012. However, almost 27 percent of countries are seriously off track toward meet- Countries making progress toward halving the proportion of people without sustainable access to basic sanitation (% of countries in region) 100 ing the water target (i gure 7b). In 1990 only 35 percent of the people living in low- and middle-income economies had access to a lush toilet or other form of improved sanitation. By 2012 75 the access rate had risen to 57 percent. But 2.5 billion people 50 still lack access to improved sanitation. The situation is worse 25 in rural areas, where 43 percent of the population has access to 0 Developing East Asia countries & Pacific Target met Moderately off track Latin Middle East South Sub-Saharan Europe Asia Africa & Central America & & North Africa Caribbean Asia Sufficient progress Insufficient progress Seriously off track Insufficient data Source: World Bank (2013) and World Bank MDG Data Dashboards (http://data.worldbank.org/mdgs). 8 World Development Indicators 2014 Front improved sanitation, compared with 73 percent in urban areas. This large disparity, especially in Sub- Saharan Africa and South Asia, is the main reason the sanitation target is unlikely to be met on time (igure 7c). ? User guide World view People Environment MDG 8 Develop a global partnership for development The inancial crisis that began in 2008 and the ensuing iscal austerity in many high-income economies have undermined commitments to increase oficial development assistance (ODA) from Official development assistance from 8a Development Assistance Committee members Oficial development assistance (2011 $ billions) 200 members of the Organisation for Economic Co-operation and Development’s Development Assistance Committee (DAC). Since 2010, Multilateral net official development assistance 150 the year of its peak, ODA has fallen 6 percent in real terms, after adjusting prices and exchange rates. Net disbursements of ODA by 100 DAC members totaled $127 billion in 2012, a decrease of 4 percent in real terms. This decline has been accompanied by a notice- 50 able shift in aid allocations away from the poorest countries and toward middle-income countries. Bilateral ODA from DAC members to Sub-Saharan Africa, $27.3 billion in 2012, fell 4.3 percent in real Bilateral net official development assistance 0 1990 1995 2000 2005 2010 2012 Source: Organisation for Economic Co-operation and Development. terms from 2011. As a share of gross national income, it fell to 0.29 percent in 2012, well below half the UN target of 0.7 percent (igure 8a). Debt service burdens continue to fall 8b Total debt service (% of exports of goods, services, and income) Economic growth, improved debt management, debt restructur- 50 ing, and outright debt relief have enabled developing countries to substantially reduce their debt burdens. This is in part due to 35 of the 39 countries being eligible for the Heavily Indebted Poor Country (HIPC) Debt Relief Initiative and Multilateral Debt Relief Initiative (MDRI) beneiting from substantial relief. The ratio of debt service to exports in low- and middle-income economies fell to 9.8 per- South Asia 30 Middle East & North Africa 20 East Asia & Pacific 10 Sub-Saharan Africa cent in 2012, well below half the 21.1 percent at the start of the decade. Sub-Saharan Africa, home to the majority of the HIPC and MDRI countries, has one of the lowest ratios of debt service to Europe & Central Asia Latin America & Caribbean 40 0 1990 1995 2000 2005 2010 2012 Source: World Development Indicators database. exports: 4.5 percent in 2012 (igure 8b). Telecommunications is essential for development, and new technologies are creating new opportunities everywhere. By the end of 2012 there were 6.3 billion mobile phone subscriptions, and The number of internet users continues to rise 8c Internet users (per 100 people) 75 High income 2.5 billion people were using the Internet worldwide. As the global mobile-cellular penetration rate approaches market saturation, the growth rates for both developing and developed economies 50 Europe & Central Asia are slowing. Mobile phones are one of several ways of accessing the Internet. And like telephone use, Internet use is strongly cor- Latin America & Caribbean East Asia & Pacific 25 Middle East & North Africa related with income. Since 2000 Internet users per 100 people in developing economies has grown 28 percent a year, but the low-income economies of South Asia and Sub- Saharan Africa lag South Asia 0 2000 2005 2010 2012 Source: International Telecommunications Union and World Development Indicators database. behind (igure 8c). Economy Sub-Saharan Africa States and markets Global links Back World Development Indicators 2014 9 Millennium Development Goals Goals and targets from the Millennium Declaration Indicators for monitoring progress Goal 1 Eradicate extreme poverty and hunger Target 1.A Halve, between 1990 and 2015, the proportion of people whose income is less than $1 a day 1.1 Target 1.B Achieve full and productive employment and decent work for all, including women and young people 1.2 1.3 1.4 1.5 1.6 1.7 Target 1.C Halve, between 1990 and 2015, the proportion of people who suffer from hunger 1.8 1.9 Goal 2 Achieve universal primary education Target 2.A Ensure that by 2015 children everywhere, boys and girls alike, will be able to complete a full course of primary schooling 2.1 2.2 2.3 Goal 3 Promote gender equality and empower women Target 3.A Eliminate gender disparity in primary and secondary education, preferably by 2005, and in all levels of education no later than 2015 3.1 3.2 3.3 Goal 4 Reduce child mortality Target 4.A Reduce by two-thirds, between 1990 and 2015, the under-five mortality rate Goal 5 Improve maternal health Target 5.A Reduce by three-quarters, between 1990 and 2015, the maternal mortality ratio Target 5.B Achieve by 2015 universal access to reproductive health Target 6.B Achieve by 2010 universal access to treatment for HIV/AIDS for all those who need it Target 6.C Have halted by 2015 and begun to reverse the incidence of malaria and other major diseases Net enrollment ratio in primary education Proportion of pupils starting grade 1 who reach last grade of primary education Literacy rate of 15- to 24-year-olds, women and men Ratios of girls to boys in primary, secondary, and tertiary education Share of women in wage employment in the nonagricultural sector Proportion of seats held by women in national parliament 4.1 4.2 4.3 Under-five mortality rate Infant mortality rate Proportion of one-year-old children immunized against measles 5.1 5.2 5.3 5.4 5.5 Maternal mortality ratio Proportion of births attended by skilled health personnel Contraceptive prevalence rate Adolescent birth rate Antenatal care coverage (at least one visit and at least four visits) Unmet need for family planning 5.6 Goal 6 Combat HIV/AIDS, malaria, and other diseases Target 6.A Have halted by 2015 and begun to reverse the spread of HIV/AIDS Proportion of population below $1 purchasing power parity (PPP) a daya Poverty gap ratio [incidence × depth of poverty] Share of poorest quintile in national consumption Growth rate of GDP per person employed Employment to population ratio Proportion of employed people living below $1 (PPP) a day Proportion of own-account and contributing family workers in total employment Prevalence of underweight children under five years of age Proportion of population below minimum level of dietary energy consumption 6.1 6.2 6.3 HIV prevalence among population ages 15–24 years Condom use at last high-risk sex 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 6.5 Proportion of population with advanced HIV infection with access to antiretroviral drugs 6.6 Incidence and death rates associated with malaria 6.7 Proportion of children under age five sleeping under insecticide-treated bednets 6.8 Proportion of children under age five with fever who are treated with appropriate antimalarial drugs 6.9 Incidence, prevalence, and death rates associated with tuberculosis 6.10 Proportion of tuberculosis cases detected and cured under directly observed treatment short course Note: The Millennium Development Goals and targets come from the Millennium Declaration, signed by 189 countries, including 147 heads of state and government, in September 2000 (www.un.org/millennium/declaration/ares552e.htm) as updated by the 60th UN General Assembly in September 2005. The revised Millennium Development Goal (MDG) monitoring framework shown here, including new targets and indicators, was presented to the 62nd General Assembly, with new numbering as recommended by the Inter-agency and Expert Group on MDG Indicators at its 12th meeting on November 14, 2007. The goals and targets are interrelated and should be seen as a whole. They represent a partnership between the developed countries and the developing countries “to create an environment—at the national and global levels alike—which is conducive to development and the elimination of poverty.” All indicators should be disaggregated by sex and urban-rural location as far as possible. 10 World Development Indicators 2014 Front ? User guide World view People Environment Goals and targets from the Millennium Declaration Indicators for monitoring progress Goal 7 Ensure environmental sustainability Target 7.A Integrate the principles of sustainable development into country policies and programs and reverse the loss of environmental resources Target 7.B Reduce biodiversity loss, achieving, by 2010, a significant reduction in the rate of loss Target 7.C Halve by 2015 the proportion of people without sustainable access to safe drinking water and basic sanitation Target 7.D Achieve by 2020 a significant improvement in the 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, nondiscriminatory trading and financial system 7.1 7.2 Proportion of land area covered by forest Carbon dioxide emissions, total, per capita and per $1 GDP (PPP) 7.3 Consumption of ozone-depleting substances 7.4 Proportion of fish stocks within safe biological limits 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 7.8 Proportion of population using an improved drinking water source 7.9 Proportion of population using an improved sanitation facility 7.10 Proportion of urban population living in slumsb Some of the indicators listed below are monitored separately 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 nationally and internationally.) Target 8.B Target 8.C Target 8.D Target 8.E Target 8.F Official development assistance (ODA) 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 education, primary health care, nutrition, safe water, and Address the special needs of the least developed sanitation) countries 8.3 Proportion of bilateral official development assistance of OECD/DAC donors that is untied (Includes tariff and quota-free access for the least developed countries’ exports; enhanced program of 8.4 ODA received in landlocked developing countries as a proportion of their gross national incomes debt relief for heavily indebted poor countries (HIPC) 8.5 ODA received in small island developing states as a and cancellation of official bilateral debt; and more proportion of their gross national incomes generous ODA for countries committed to poverty reduction.) Market access 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 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 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 In cooperation with the private sector, make 8.14 Fixed-line telephones per 100 population available the benefits of new technologies, 8.15 Mobile cellular subscribers per 100 population especially information and communications 8.16 Internet users per 100 population a. Where available, indicators based on national poverty lines should be used for monitoring country poverty trends. b. The proportion of people living in slums is measured by a proxy, represented by the urban population living in households with at least one of these characteristics: lack of access to improved water supply, lack of access to improved sanitation, overcrowding (three or more people per room), and dwellings made of nondurable material. Economy States and markets Global links Back World Development Indicators 2014 11 1 World view Population Population density Urban population Gross national income millions thousand sq. km people per sq. km % of total population $ billions Per capita $ $ billions 2012 2012 2012 2012 2012 Atlas method Purchasing power parity Gross domestic product Per capita $ % growth Per capita % growth 2012 2012 2012 2011–12 2011–12 29.8 652.2 46 24 20.4 680 46.6a 1,560a 14.4 11.6 Albania 3.2 28.8 115 54 12.7 4,030 b 29.3 9,280 1.6 1.3 Algeria 38.5 2,381.7 16 74 193.2 5,020 321.6a 8,360a 3.3 1.4 American Samoa 0.1 0.2 276 93 .. ..c .. .. .. .. Andorra 0.1 0.5 167 87 .. ..d .. .. .. .. 20.8 1,246.7 17 60 95.4 0.1 0.4 202 30 1.1 Afghanistan Angola Antigua and Barbuda 4,580 112.4 12,480e 1.7a 6.8 3.5 2.8 1.8 Argentina 41.1 2,780.4 15 93 ..f 3.0 29.7 104 64 11.0 Aruba 0.1 0.2 569 47 .. .. .. .. .. 22.7 7,741.2 3 89 1,346.6 59,260 966.6 42,540 3.4 1.7 Austria 8.4 83.9 102 68 403.4 47,850 369.7 43,850 0.9 0.6 Azerbaijan 9.3 86.6 112 54 57.9 6,220 86.5 9,310 2.2 0.9 Bahamas, The 0.4 13.9 37 84 7.7 20,600 10.8a 29,020a 1.8 0.3 Bahrain 1.3 0.8 1,734 89 25.8 19,560 27.8 22,250 3.4 1.4 154.7 144.0 1,188 29 129.3 840 314.2 2,030 6.2 5.0 0.3 0.4 659 45 4.3 15,080 25,670a 0.0 –0.5 Belarus 9.5 207.6 47 75 61.8 6,530 141.6 14,960 1.5 1.6 Belgium 11.1 30.5 368 98 497.6 44,720 452.7 40,680 –0.1 –0.9 2.8 Bangladesh Barbados ..c,f 5,400 18,920a Armenia Australia 3,720 ..d ..f ..f 20.4 6,860 7.3a 2.5a 1.9g 7.2 ..f 7.0 Belize 0.3 23.0 14 45 1.4 4,490 7,630a 5.3 Benin 10.1 114.8 89 46 7.5 750 15.6 1,550 5.4 2.6 0.1 0.1 1,296 100 6.8 104,590 .. .. –4.9 –5.2 Bermuda Bhutan 0.7 38.4 19 36 1.8 2,420 4.6 6,200 9.4 7.6 Bolivia 10.5 1,098.6 10 67 23.3 2,220 51.2 4,880 5.2 3.5 Bosnia and Herzegovina 3.8 51.2 75 49 18.2 4,750 37.0 9,650 –0.7 –0.6 Botswana 2.0 581.7 4 62 15.3 7,650 32.2 16,060 4.2 3.3 198.7 8,514.9 23 85 2,311.1 11,630 2,291.0 11,530 0.9 0.0 Brunei Darussalam 0.4 5.8 78 76 .. .. .. 2.2 0.7 Bulgaria 7.3 111.0 67 74 50.0 6,840 112.9 15,450 0.8 1.4 16.5 274.2 60 27 11.0 670 24.4 1,480 9.5 6.4 9.8 27.8 384 11 2.4 240 5.4 550 4.0 0.8 0.5 4.0 123 63 1.9 3,830 2.4 4,930 2.5 1.7 14.9 181.0 84 20 13.0 880 34.6 2,330 7.3 5.4 Brazil Burkina Faso Burundi Cabo Verde Cambodia ..d Cameroon 21.7 475.4 46 53 25.3 1,170 49.3 2,270 4.6 2.0 Canada 34.8 9,984.7 4 81 1,792.3 51,570 1,469.0 42,270 1.7 0.5 Cayman Islands 0.1 0.3 240 100 .. .. .. .. .. Central African Republic 4.5 623.0 7 39 2.3 510 4.9 1,080 6.9 4.8 12.4 1,284.0 10 22 9.6 770 20.1 1,620 8.9 5.7 0.2 0.2 849 31 .. .. .. .. .. 17.5 756.1 23 89 249.9 14,310 357.2 20,450 5.6 4.6 Chad Channel Islands Chile China ..d ..d 1,350.7 9,600.0 145 52 7,731.3 5,720 12,205.8 9,040 7.8 7.3 Hong Kong SAR, China 7.2 1.1 6,866 100 261.6 36,560 373.4 52,190 1.5 0.3 Macao SAR, China 0.6 0.0h Colombia Comoros Congo, Dem. Rep. Congo, Rep. 12 Surface area World Development Indicators 2014 47.7 19,885 100 30.4 55,720 37.1 68,000 9.9 7.9 1,141.8 43 76 334.8 7,020 476.4 9,990 4.2 2.8 0.7 1.9 386 28 0.6 840 0.9 1,210 3.0 0.5 65.7 2,344.9 29 35 15.4 230 25.5 390 7.2 4.3 4.3 342.0 13 64 11.1 2,550 15.0 3,450 3.8 1.1 Front ? User guide World view People Environment World view 1 Population Costa Rica Côte d’Ivoire Croatia Cuba Surface area Population density Urban population Gross national income millions thousand sq. km people per sq. km % of total population $ billions Per capita $ $ billions 2012 2012 2012 2012 2012 2012 2012 Atlas method Purchasing power parity Gross domestic product Per capita $ % growth Per capita % growth 2012 2011–12 2011–12 4.8 51.1 94 65 42.4 8,820 60.1a 12,500a 5.1 3.6 19.8 322.5 62 52 24.2 1,220 38.2 1,920 9.5 7.0 4.3 56.6 76 58 57.6 13,490 86.2 20,200 –2.0 –1.7 5,890 2.8 11.3 109.9 106 75 66.4 .. .. 2.7 Curaçao 0.2 0.4 342 .. .. ..d .. .. .. .. Cyprus 1.1 9.3 122 71 22.8i 26,110i 26.1i 29,840i –2.4i –4.9i Czech Republic 10.5 78.9 136 73 190.5 18,130 267.9 25,480 –1.0 –1.2 Denmark 5.6 43.1 132 87 334.8 59,870 246.4 44,070 –0.4 –0.7 Djibouti 0.9 23.2 37 77 .. ..j .. .. .. .. Dominica 0.1 0.8 96 67 0.5 6,440 0.9a 11,980a –1.7 –2.1 Dominican Republic 10.3 48.7 213 70 56.3 5,470 99.3a 9,660a 3.9 2.6 Ecuador 15.5 256.4 62 68 80.1 5,170 147.0 9,490 5.1 3.5 Egypt, Arab Rep. 80.7 1,001.5 81 44 240.3 2,980 520.7 6,450 2.2 0.5 6.3 21.0 304 65 22.6 3,590 6,720a 1.9 1.3 2.5 –0.3 7.0 3.6 El Salvador 42.3a Equatorial Guinea 0.7 28.1 26 40 10.0 13,560 Eritrea 6.1 117.6 61 22 2.8 450 Estonia 1.3 45.2 31 70 21.6 16,270 31.0 23,280 3.9 4.4 Ethiopia 91.7 1,104.3 92 17 34.7 380 101.5 1,110 8.5 5.7 1.4 35 41 .. .. .. .. .. 48 53 3.6 4,110 4.1 4,690 2.3 1.5 3.4 a 18,570 550a Faeroe Islands 0.0k Fiji 0.9 18.3 Finland 5.4 338.4 18 84 251.7 46,490 212.0 39,150 –0.8 –1.3 France 65.7 549.2 120 86 2,742.9 41,750 2,458.1 37,420 0.0 –0.5 French Polynesia 0.3 4.0 75 51 .. Gabon 1.6 267.7 6 86 16.4 Gambia, The 1.8 11.3 177 58 0.9 Georgia 4.5l 69.7 79l 53 14.8l ..d 13.7 ..d .. .. .. .. 23.0 14,090 5.6 3.1 510 3.3 1,830 5.3 2.0 3,290l 26.0l 5,790l 6.0l 5.8l 2.4 10,040 Germany 80.4 357.1 231 74 3,624.6 45,070 3,516.2 43,720 0.7 Ghana 25.4 238.5 111 53 39.4 1,550 48.4 1,910 7.9 5.6 Greece 11.1 132.0 86 62 262.4 23,660 290.3 26,170 –6.4 –6.1 Greenland 0.1 Grenada 0.1 Guam 410.5m 0n 0.3 310 85 .. 39 0.8 ..d 7,220 ..d .. 1.1a .. 0.2 0.2 0.5 302 93 .. 15.1 108.9 141 50 47.1 3,120 Guinea 11.5 245.9 47 36 5.0 440 11.1 970 3.9 1.3 1.7 36.1 59 45 0.9 510 1.8 1,100 –6.7 –8.9 4.2 Guyana Haiti Honduras 73.6a .. .. 0.6 Guatemala Guinea-Bissau .. .. 10,350a 4,880a .. .. 3.0 0.4 0.8 215.0 4 28 2.7 3,410 2.7a 3,340a 4.8 10.2 27.8 369 55 7.7 760 12.4 a 1,220a 2.8 1.4 7.9 112.5 71 53 16.8 2,120 30.8a 3,880a 3.9 1.8 –1.2 Hungary 9.9 93.0 110 70 123.1 12,410 211.8 21,350 –1.7 Iceland 0.3 103.0 3 94 12.3 38,270 11.2 34,770 1.4 0.9 1,236.7 3,287.3 416 32 1,913.2 1,550 4,730.3 3,820 4.7 3.4 India Indonesia 246.9 1,904.6 136 51 844.0 3,420 1,168.7 4,730 6.2 4.9 Iran, Islamic Rep. 76.4 1,745.2 47 69 .. ..c .. .. –1.9 –3.2 Iraq 32.6 435.2 75 66 199.8 6,130 242.9 7,460 9.3 6.5 Ireland 4.6 70.3 67 63 179.0 39,020 164.2 35,790 0.2 –0.1 Isle of Man 0.1 0.6 150 51 .. Israel 7.9 22.1 366 92 253.4 Economy States and markets Global links ..d 32,030 Back .. .. .. .. 240.2 30,370 3.4 1.5 World Development Indicators 2014 13 1 World view Population Population density Urban population millions thousand sq. km people per sq. km % of total population 2012 Gross national income Atlas method $ billions Purchasing power parity Per capita $ $ billions Gross domestic product Per capita $ % growth Per capita % growth 2012 2012 2012 2012 2012 2012 2012 2011–12 2011–12 59.5 301.3 202 69 2,062.5 34,640 2,065.9 34,700 –2.5 –0.6 2.7 11.0 250 52 13.9 5,130 .. .. –0.5 –0.7 127.6 378.0 350 92 6,106.7 47,870 4,687.6 36,750 2.0 2.2 6.3 89.3 71 83 29.5 4,670 37.8 5,980 2.7 0.4 Kazakhstan 16.8 2,724.9 6 54 164.3 9,780 197.9 11,790 5.0 3.5 Kenya 43.2 580.4 76 24 37.2 860 74.7 0.1 0.8 124 44 0.3 2,520 Korea, Dem. People’s Rep. 24.8 120.5 206 60 .. Korea, Rep. 50.0 99.9 515 83 1,133.8 Kosovo 1.8 10.9 166 .. 6.5 3,600 .. Kuwait 3.3 17.8 182 98 140.2 44,880 149.2 Kyrgyz Republic 5.6 199.9 29 35 5.5 990 12.4 Lao PDR 6.6 236.8 29 35 8.4 1,270 Latvia 2.0 64.5 33 68 28.6 14,060 Lebanon 4.4 10.5 433 87 40.7 9,190 Lesotho 2.1 30.4 68 28 2.8 Italy Jamaica Japan Jordan Kiribati 0.4a ..o 1,730 4.6 1.8 3,870a 2.8 1.2 .. .. .. .. 1,509.0 30,180 2.0 1.6 .. 2.7 1.8 47,750 6.2 2.1 2,220 –0.9 –2.5 17.9 2,690 8.2 6.2 44.4 21,820 5.0 6.3 62.7 14,160 1.4 0.4 1,380 4.5 2,170 4.0 2.8 370 22,670 Liberia 4.2 111.4 44 49 1.5 2.4 580 10.2 7.3 Libya 6.2 1,759.5 3 78 .. ..c .. .. .. .. Liechtenstein 0.0k 0.2 229 14 .. ..d .. .. .. .. Lithuania 3.0 65.3 48 67 41.3 13,820 70.3 23,540 3.7 5.1 Luxembourg 0.5 2.6 205 86 38.0 71,640 32.4 60,950 –0.2 –2.5 Macedonia, FYR 2.1 25.7 83 59 9.7 4,620 24.3 11,540 –0.3 –0.3 Madagascar 22.3 587.0 38 33 9.7 430 20.8 930 3.1 0.3 Malawi 15.9 118.5 169 16 5.0 320 11.6 730 1.9 –1.0 Malaysia 29.2 330.8 89 73 287.0 9,820 475.8 16,270 5.6 3.9 Maldives 0.3 0.3 1,128 42 1.9 5,750 2.6 7,560 3.4 1.4 14.9 1,240.2 12 36 9.8 660 16.9 1,140 –0.4 –3.3 19,710 11.3 26,930 1.0 0.2 .. .. 1.9 1.8 Mali Malta 0.4 0.3 1,311 95 8.3 Marshall Islands 0.1 0.2 292 72 0.2 4,040 b Mauritania 3.8 1,030.7 4 42 4.2 1,110 9.4 2,480 7.6 4.9 Mauritius 1.3 2.0 636 42 11.1 8,570 19.5 15,060 3.2 2.8 1,951.1 16,140 3.8 2.5 Mexico 120.8 1,964.4 62 78 1,165.1 9,640 Micronesia, Fed. Sts. 0.1 0.7 148 23 0.3 3,230 Moldova 3.6p 124p 48 7.4p 2,070p Monaco 0.0k Mongolia 2.8 Montenegro 33.9 0.0h 18,790 100 .. 1,564.1 2 69 8.8 ..d 3,160 0.4 a 3,920a 0.4 0.5 12.9p 3,630p –0.8p –0.8p .. .. .. .. 14.0 5,020 12.3 10.6 9.1 14,590 –0.5 –0.6 0.6 13.8 46 63 4.5 7,220 Morocco 32.5 446.6 73 57 97.9q 2,960q Mozambique 25.2 799.4 32 31 12.8 Myanmar 52.8 676.6 81 33 .. 2.3 824.3 3 39 12.7 Nepal 27.5 147.2 192 17 19.2 700 40.4 1,470 4.9 3.6 Netherlands 16.8 41.5 497 84 804.3 48,000 733.0 43,750 –1.2 –1.6 Namibia 510 ..o 5,610 ..d New Caledonia 0.3 18.6 14 62 .. New Zealand 4.4 267.7 17 86 163.6 36,900 6.0 130.4 50 58 9.9 1,650 17.2 1,267.0 14 18 6.7 390 Nicaragua Niger 14 Surface area World Development Indicators 2014 Front ? User guide World view 167.4 q 5,060q 4.2q 2.7q 25.3 1,000 7.4 4.7 .. .. .. .. 16.4 7,240 5.0 3.1 .. .. .. .. 144.6 32,620 3.2 2.6 5.2 3.7 10.8 6.7 23.3a 13.0 3,890a 760 People Environment World view 1 Population Surface area Population density Urban population Gross national income millions thousand sq. km people per sq. km % of total population $ billions 2012 2012 2012 2012 Atlas method Purchasing power parity Per capita $ Gross domestic product $ billions Per capita $ % growth Per capita % growth 2012 2012 2012 2012 2011–12 2011–12 168.8 923.8 185 50 242.7 1,440 404.8 2,400 6.5 3.6 Northern Mariana Islands 0.1 0.5 116 92 .. .. .. .. .. Norway 5.0 323.8 16 80 495.7 98,780 338.5 67,450 2.9 1.6 Nigeria Oman Pakistan Palau Panama ..d 3.3 309.5 11 74 58.8 19,450 71.0 25,330 5.0 –7.1 179.2 796.1 232 37 225.1 1,260 516.5 2,880 4.0 2.3 0.0k 0.5 45 85 0.2 9,860 0.4 a 16,870a 5.3 4.5 3.8 75.4 51 76 32.4 8,510 57.6a 15,150a 10.7 8.9 Papua New Guinea 7.2 462.8 16 13 12.8 1,790 19.6a 2,740a 8.0 5.7 Paraguay 6.7 406.8 17 62 22.8 3,400 38.2 5,720 –1.2 –2.9 Peru 30.0 1,285.2 23 78 181.8 6,060 302.7 10,090 6.3 5.0 Philippines 96.7 300.0 324 49 241.7 2,500 423.6 4,380 6.8 5.0 Poland 38.5 312.7 127 61 488.0 12,660 838.6 21,760 1.8 1.8 Portugal –2.8 10.5 92.1 115 62 217.0 20,640 266.3 25,330 –3.2 Puerto Rico 3.7 8.9 413 99 66.0 18,000 .. .. 0.5 1.3 Qatar 2.1 11.6 177 99 142.6 74,600 168.8 88,350 6.2 –1.0 Romania Russian Federation Rwanda Samoa 20.1 238.4 87 53 171.9 8,560 354.3 17,650 0.4 0.7 143.5 17,098.2 9 74 1,822.7 12,700 3,272.9 22,800 3.4 3.0 11.5 26.3 464 19 6.9 600 15.1 0.2 2.8 67 20 0.6 3,260 ..d 0.8a 1,320 8.0 5.0 4,250a 2.9 2.1 San Marino 0.0k 0.1 521 94 .. .. .. .. .. São Tomé and Príncipe 0.2 1.0 196 63 0.2 1,310 0.3 1,810 4.0 1.3 Saudi Arabia 28.3 2,149.7r 13 82 687.8 24,310 837.4 30,160 5.1 3.2 Senegal 13.7 196.7 71 43 14.2 1,030s 25.8 1,880 3.5 0.5 Serbia 7.2 88.4 83 57 38.1 5,280 82.6 11,430 –1.7 –1.2 Seychelles 0.1 0.5 192 54 1.1 12,180 Sierra Leone 6.0 71.7 83 40 3.5 Singapore 5.3 0.7 7,589 100 250.8 Sint Maarten (Dutch part) 0.0k 0.0h 1,150 .. .. Slovak Republic 5.4 49.0 112 55 93.0 2.3a 25,580a 2.8 1.8 580 8.0 1,340 15.2 13.0 47,210 319.3 60,110 1.3 –1.1 .. .. .. .. 17,190 137.5 25,430 1.8 1.6 58.1 28,240 –2.5 –2.7 3.9 1.7 ..d Slovenia 2.1 20.3 102 50 46.9 22,810 Solomon Islands 0.5 28.9 20 21 0.6 1,130 Somalia 10.2 637.7 16 38 .. ..o .. .. .. .. South Africa 52.3 1,219.1 43 62 389.8 7,460 563.3 10,780 2.5 1.2 South Sudan 10.8 644.3 .. 18 8.6 790 .. .. –47.6 –49.8 Spain 46.8 505.6 94 78 1,368.8 29,270 1,485.1 31,760 –1.6 –1.7 Sri Lanka 20.3 65.6 324 15 59.3 2,920 122.5 6,030 6.4 9.2 St. Kitts and Nevis 0.1 0.3 206 32 0.7 13,610 0.9a 17,630a 6.9 5.7 St. Lucia 0.2 0.6 297 17 1.2 6,890 2.0a 11,300a 0.5 –0.4 St. Martin (French part) 0.0k 0.1 569 .. .. St. Vincent & the Grenadines 0.1 0.4 280 50 0.7 6,400 1.2a 10,870a 37.2 t 1,879.4t 20 33t 55.9 t 1,500 t 77.1t 2,070 t a a Sudan ..d 1.2a .. 2,130a .. Suriname 0.5 163.8 3 70 4.6 8,680 4.5 Swaziland 1.2 17.4 72 21 3.5 2,860 5.9 4,760 Sweden 9.5 450.3 23 85 534.3 56,120 418.5 Switzerland 8.0 41.3 200 74 647.5 80,970 439.8 22.4 185.2 122 56 .. ..j 8.0 142.6 57 27 7.1 880 Syrian Arab Republic Tajikistan Economy States and markets Global links Back 8,380 .. .. 2.3 2.3 –10.1u 0.6u 3.9 2.9 –1.5 –3.0 43,960 0.9 0.2 55,000 1.0 0.0 .. .. .. 0.8 17.4 2,180 7.5 4.9 World Development Indicators 2014 15 1 World view Population Surface area Population density Urban population Gross national income millions thousand sq. km people per sq. km % of total population $ billions Per capita $ $ billions 2012 2012 2012 2012 2012 Atlas method 2012 2012 Tanzania 47.8 947.3 54 27 26.7v Thailand Purchasing power parity 570 v 72.4v 619.5 Gross domestic product Per capita $ % growth Per capita % growth 2012 2011–12 2011–12 1,560 v 6.9 v 3.7v 9,280 6.5 6.2 6,230a 0.6 –2.3 2.9 66.8 513.1 131 34 347.8 5,210 Timor-Leste 1.2 14.9 81 29 4.4 3,620 Togo 6.6 56.8 122 39 3.3 500 6.0 900 5.6 Tonga 0.1 0.8 146 24 0.4 4,220 0.5a 5,020a 0.8 0.5 Trinidad and Tobago 1.3 5.1 261 14 19.7 14,710 30.6a 22,860a 1.5 1.2 7.5a Tunisia 10.8 163.6 69 67 44.8 4,150 99.2 9,210 3.6 2.6 Turkey 74.0 783.6 96 72 801.1 10,830 1,360.6 18,390 2.2 0.9 Turkmenistan 5.2 488.1 11 49 28.0 5,410 11.1 9.7 Turks and Caicos Islands 0.0k 1.0 34 94 .. Tuvalu 0.0k 0.0h 329 51 0.1 46.9a ..d 5,650 9,070a .. .. .. .. .. .. 0.2 0.0 Uganda 36.3 241.6 182 16 17.6 480 47.1 1,300 3.4 0.0 Ukraine 45.6 603.6 79 69 159.6 3,500 327.1 7,180 0.2 0.4 United Arab Emirates 9.2 83.6 110 85 355.5 38,620 381.4 41,430 4.4 1.2 63.6 243.6 263 80 2,448.8 38,500 2,266.0 35,620 0.3 –0.3 313.9 9,831.5 34 83 16,430.4 52,340 16,514.5 52,610 2.8 2.0 3.4 176.2 19 93 46.1 13,580 52.0 15,310 3.9 3.6 29.8 447.4 70 36 51.2 1,720 109.1a 3,670a 8.2 6.6 0.2 12.2 20 25 0.7 3,000 1.1a 4,300a 2.3 0.0 Venezuela, RB 30.0 912.1 34 94 373.3 12,460 386.9 12,920 5.6 4.0 Vietnam 1,550 4.1 United Kingdom United States Uruguay Uzbekistan Vanuatu 88.8 331.0 286 32 137.5 321.4 3,620 5.2 Virgin Islands (U.S.) 0.1 0.4 301 96 .. ..d .. .. .. .. West Bank and Gaza 4.0 6.0 672 75 .. ..j .. .. .. .. Yemen, Rep. 23.9 528.0 45 33 30.4 1,270 55.1 2,310 0.1 –2.2 Zambia 14.1 752.6 19 40 19.0 1,350 22.4 1,590 7.2 3.9 Zimbabwe 13.7 390.8 35 39 8.9 650 .. .. 4.4 1.6 54 w 53 w 2.4 w 1.2 w 4.0 World 7,043.9 s 134,289.9 s 71,692.4 t 10,178 w 85,986.8 t 12,207 w 846.5 16,197.8 56 28 499.4 590 1,171.1 1,383 6.3 4,897.6 64,212.0 77 50 21,404.7 4,370 35,099.0 7,167 4.9 3.7 Lower middle income 2,507.0 20,739.9 122 39 4,745.3 1,893 9,718.6 3,877 4.7 3.2 Low income Middle income Upper middle income 2,390.6 43,472.2 56 61 16,661.1 6,969 25,389.9 10,621 5.0 4.2 Low & middle income 5,744.1 80,409.9 73 46 21,916.1 3,815 36,250.5 6,311 4.9 3.6 East Asia & Paciic 1,991.6 16,301.6 126 50 9,727.7 4,884 15,451.5 7,758 7.5 6.7 Europe & Central Asia 270.8 6,478.6 43 60 1,804.4 6,664 3,234.8 11,946 1.8 1.1 Latin America & Carib. 581.4 19,460.9 30 79 5,273.2 9,070 6,852.9 11,787 2.9 1.7 Middle East & N. Africa 339.6 8,775.4 39 60 .. .. .. .. 1.9 0.2 1,649.2 5,131.1 346 31 2,370.1 1,437 5,777.6 3,503 4.9 3.5 911.5 24,262.3 39 37 1,230.2 1,350 2,030.0 2,227 4.3 1.5 1,299.8 53,880.1 25 80 49,905.7 38,394 50,055.1 38,509 1.5 1.2 331.2 2,693.1 128 76 12,673.5 38,263 12,354.0 37,299 –0.6 0.0 South Asia Sub-Saharan Africa High income Euro area a. Based on regression; others are extrapolated from the 2005 International Comparison Program benchmark estimates. b. Included in the aggregates for upper middle-income economies based on earlier data. c. Estimated to be upper middle income ($4,086–$12,615). d. Estimated to be high income ($12,616 or more). e. Included in the aggregates for high-income economies based on earlier data. f. Data series will be calculated once ongoing revisions to oficial statistics reported by the National Statistics and Censuses Institute of Argentina have been inalized. g. Data for Argentina are oficially reported by the National Statistics and Censuses Institute of Argentina. The International Monetary Fund has, however, issued a declaration of censure and called on Argentina to adopt remedial measures to address the quality of oficial GDP and consumer price index data. Alternative data sources have shown signiicantly lower real growth and higher inlation than the oficial data since 2008. In this context, the World Bank is also using alternative data sources and estimates for the surveillance of macroeconomic developments in Argentina. h. Greater than 0 but less than 50. i. Data are for the area controlled by the government of Cyprus. j. Estimated to be lower middle income ($1,036–$4,085). k. Greater than 0 but less than 50,000. l. Excludes Abkhazia and South Ossetia. m. Refers to area free from ice. n. Greater than 0 but less than 0.5. o. Estimated to be low income ($1,035 or less). p. Excludes Transnistria. q. Includes Former Spanish Sahara. r. Provisional estimate. s. Included in the aggregates for lower middle-income economies based on earlier data. t. Excludes South Sudan. u. Excludes South Sudan after July 9, 2011. v. Covers mainland Tanzania only. 16 World Development Indicators 2014 Front ? User guide World view People Environment World view 1 About the data Population, land area, income (as measured by gross national income, the environmental effects of human activity. Innovations in satellite GNI), and output (as measured by gross domestic product, GDP) are mapping and computer databases have resulted in more precise basic measures of the size of an economy. They also provide a broad measurements of land and water areas. indication of actual and potential resources and are therefore used throughout World Development Indicators to normalize other indicators. Urban population There is no consistent and universally accepted standard for distin- Population guishing urban from rural areas, in part because of the wide variety Population estimates are usually based on national population cen- of situations across countries. Most countries use an urban clas- suses. Estimates for the years before and after the census are siication related to the size or characteristics of settlements. Some interpolations or extrapolations based on demographic models. deine urban areas based on the presence of certain infrastructure Errors and undercounting occur even in high-income countries; in and services. And other countries designate urban areas based on developing countries errors may be substantial because of limits administrative arrangements. Because the estimates in the table in the transport, communications, and other resources required to are based on national deinitions of what constitutes a city or met- conduct and analyze a full census. ropolitan area, cross-country comparisons should be made with The quality and reliability of oficial demographic data are also caution. To estimate urban populations, ratios of urban to total affected by public trust in the government, government commit- population obtained from the United Nations were applied to the ment to full and accurate enumeration, conidentiality and protection World Bank’s estimates of total population. against misuse of census data, and census agencies’ independence from political inluence. Moreover, comparability of population indi- Size of the economy cators is limited by differences in the concepts, deinitions, collec- GNI measures total domestic and foreign value added claimed by tion procedures, and estimation methods used by national statisti- residents. GNI comprises GDP plus net receipts of primary income cal agencies and other organizations that collect the data. (compensation of employees and property income) from nonresident Of the 214 economies in the table, 180 (about 86 percent) con- sources. GDP is the sum of gross value added by all resident pro- ducted a census during the 2000 census round (1995–2004). As ducers in the economy plus any product taxes (less subsidies) not of January 2014, 175 countries (about 82 percent) have completed included in the valuation of output. GNI is calculated without deduct- a census for the 2010 census round (2005–14). The currentness of ing for depreciation of fabricated assets or for depletion and degrada- a census and the availability of complementary data from surveys or tion of natural resources. Value added is the net output of an industry registration systems are important indicators of demographic data after adding up all outputs and subtracting intermediate inputs. The quality. See Primary data documentation for the most recent census industrial origin of value added is determined by the International or survey year and for the completeness of registration. Some Euro- Standard Industrial Classiication revision 3 and revision 4. The World pean countries’ registration systems offer complete information on Bank uses GNI per capita in U.S. dollars to classify countries for ana- population in the absence of a census. lytical purposes and to determine borrowing eligibility. For deinitions Current population estimates for developing countries that lack of the income groups in World Development Indicators, see User guide. recent census data and pre- and post-census estimates for coun- When calculating GNI in U.S. dollars from GNI reported in national tries with census data are provided by the United Nations Popula- currencies, the World Bank follows the World Bank Atlas conversion tion Division and other agencies. The cohort component method—a method, using a three-year average of exchange rates to smooth standard method for estimating and projecting population—requires the effects of transitory luctuations in exchange rates. (For further fertility, mortality, and net migration data, often collected from sam- discussion of the World Bank Atlas method, see Statistical methods.) ple surveys, which can be small or limited in coverage. Population Because exchange rates do not always relect differences in price estimates are from demographic modeling and so are susceptible to levels between countries, the table also converts GNI and GNI per biases and errors from shortcomings in the model and in the data. capita estimates into international dollars using purchasing power Because the i ve-year age group is the cohort unit and i ve-year parity (PPP) rates. PPP rates provide a standard measure allowing period data are used, interpolations to obtain annual data or single comparison of real levels of expenditure between countries, just as age structure may not relect actual events or age composition. conventional price indexes allow comparison of real values over time. Surface area of similar goods and services among a large number of countries. The surface area of an economy includes inland bodies of water In the most recent round of price surveys conducted by the Interna- and some coastal waterways. Surface area thus differs from land tional Comparison Program (ICP) in 2005, 146 countries and territo- area, which excludes bodies of water, and from gross area, which ries participated, including China for the irst time, India for the irst may include offshore territorial waters. Land area is particularly time since 1985, and almost all African countries. The PPP conver- important for understanding an economy’s agricultural capacity and sion factors presented in the table come from three sources. For PPP rates are calculated by simultaneously comparing the prices Economy States and markets Global links Back World Development Indicators 2014 17 1 World view 47 high- and upper middle-income countries conversion factors are Population and Vital Statistics Report, the U.S. Bureau of the Cen- provided by Eurostat and the Organisation for Economic Co-operation sus’s International Data Base, and the Secretariat of the Paciic and Development (OECD); PPP estimates for these countries incor- Community’s Statistics and Demography Programme. porate new price data collected since 2005. For the remaining 2005 Data on surface and land area are from the Food and Agricul- ICP countries the PPP estimates are extrapolated from the 2005 ICP ture Organization, which gathers these data from national agen- benchmark results, which account for relative price changes between cies through annual questionnaires and by analyzing the results of each economy and the United States. For countries that did not par- national agricultural censuses. ticipate in the 2005 ICP round, the PPP estimates are imputed using a statistical model. More information on the results of the 2005 ICP is available at www.worldbank.org/data/icp. Data on urban population shares are from United Nations Population Division (2012). GNI, GNI per capita, GDP growth, and GDP per capita growth are Growth rates of GDP and GDP per capita are calculated using the least estimated by World Bank staff based on national accounts data col- squares method and constant price data in local currency. Constant lected by World Bank staff during economic missions or reported by price U.S. dollar series are used to calculate regional and income group national statistical ofices to other international organizations such growth rates. The growth rates in the table are annual averages. Meth- as the OECD. PPP conversion factors are estimates by Eurostat/ ods of computing growth rates are described in Statistical methods. OECD and by World Bank staff based on data collected by the ICP. Definitions References • Population is based on the de facto deinition of population, which Eurostat (Statistical Ofice of the European Communities). n.d. Demo- counts all residents regardless of legal status or citizenship—except graphic Statistics. [http://epp.eurostat.ec.europa.eu/portal/page for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of /portal/eurostat/home/]. Luxembourg. OECD (Organisation for Economic Co-operation and Development). origin. The values shown are midyear estimates. • Surface area n.d. OECD.StatExtracts database. [http://stats.oecd.org/]. Paris. is a country’s total area, including areas under inland bodies of UNAIDS (Joint United Nations Programme on HIV/AIDS). 2013a. AIDS water and some coastal waterways. • Population density is midyear by Numbers. Geneva. population divided by land area. • Urban population is the midyear ———. 2013b. Global Report: UNAIDS Report on the Global AIDS Epi- population of areas deined as urban in each country and obtained demic 2013. [www.unaids.org/en/resources/publications/2013/]. by the United Nations. • Gross national income, Atlas method, is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus Geneva. UNFPA (United Nations Population Fund). 2014. Reproductive Health website. [www.unfpa.org/rh/planning.htm]. net receipts of primary income (compensation of employees and UNICEF (United Nations Children’s Fund). 2013. Committing to Child property income) from abroad. Data are in current U.S. dollars con- Survival: A Promise Renewed—Progress Report 2013. [www.unicef verted using the World Bank Atlas method (see Statistical methods). .org/publications/iles/APR_Progress_Report_2013_9_Sept_2013. • Gross national income, purchasing power parity, is GNI converted pdf]. New York. to international dollars using PPP rates. An international dollar has UN Inter-agency Group for Child Mortality Estimation. 2013. Levels the same purchasing power over GNI that a U.S. dollar has in the and Trends in Child Mortality: Report 2013. [www.childinfo.org/iles United States. • Gross national income per capita is GNI divided by midyear population. • Gross domestic product is the sum of value added by all resident producers plus any product taxes (less subsi- /Child_Mortality_Report_2013.pdf]. New York. United Nations. 2013. The Millennium Development Goals Report 2013. [www.un.org/millenniumgoals/reports.shtml]. New York. dies) not included in the valuation of output. Growth is calculated United Nations Population Division. 2012. World Urbanization Pros- from constant price GDP data in local currency. • Gross domestic pects: The 2011 Revision. New York: United Nations, Department of product per capita is GDP divided by midyear population. Economic and Social Affairs. ———. 2013. World Population Prospects: The 2012 Revision. New Data sources York: United Nations, Department of Economic and Social Affairs. The World Bank’s population estimates are compiled and produced by its Development Data Group in consultation with its Human Development Network, operational staff, and country ofices. The United Nations Population Division (2013) is a source of the demographic data for more than half the countries, most of them developing countries. Other important sources are census reports and other statistical publications from national statistical ofices, Eurostat’s Demographic Statistics, the United Nations Statistics Division’s 18 World Development Indicators 2014 Front ? User guide United Nations Statistics Division. Various years. Population and Vital Statistics Report. New York. WHO (World Health Organization). 2013. World Malaria Report 2013. Geneva. World Bank. 2011. The Changing Wealth of Nations: Measuring Sustainable Development for the New Millennium. Washington, DC. ———. 2013. Global Monitoring Report 2013: Rural-Urban Dynamics and the Millennium Development Goals. Washington, DC. World view People Environment World view 1 Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/1.1). To view a speciic /indicator/SP.POP.TOTL). 1.1 Size of the economy Carbon dioxide emissions per capita Population SP.POP.TOTL Surface area AG.SRF.TOTL.K2 Population density EN.POP.DNST Nationally protected terrestrial and marine areas Access to improved sanitation facilities EN.ATM.CO2E.PC ER.PTD.TOTL.ZS SH.STA.ACSN Gross national income, Atlas method NY.GNP.ATLS.CD Internet users Gross national income per capita, Atlas method NY.GNP.PCAP.CD 1.4 Millennium Development Goals: overcoming obstacles Purchasing power parity gross national income NY.GNP.MKTP.PP.CD Purchasing power parity gross national income, Per capita NY.GNP.PCAP.PP.CD Gross domestic product NY.GDP.MKTP.KD.ZG Gross domestic product, Per capita NY.GDP.PCAP.KD.ZG 1.2 Millennium Development Goals: eradicating poverty IT.NET.USER.PZ This table provides data on net oficial development assistance by donor, least developed countries’ access to high-income markets, and the Debt Initiative for Heavily Indebted Poor Countries. 1.5 Women in development Female population SP.POP.TOTL.FE.ZS SP.DYN.LE00.MA.IN Life expectancy at birth, Male and saving lives Life expectancy at birth, Female Share of poorest quintile in national consumption or income SI.DST.FRST.20 SH.STA.ANVC.ZS SP.MTR.1519.ZS Vulnerable employment SL.EMP.VULN.ZS Prevalence of malnutrition, Underweight SH.STA.MALN.ZS Primary completion rate SE.PRM.CMPT.ZS Women in wage employment in nonagricultural sector Under-ive mortality rate SP.DYN.LE00.FE.IN Pregnant women receiving prenatal care Teenage mothers Ratio of girls to boys enrollments in primary and secondary education ..a Unpaid family workers, Male SL.EMP.INSV.FE.ZS SL.FAM.WORK.MA.ZS SE.ENR.PRSC.FM.ZS Unpaid family workers, Female SL.FAM.WORK.FE.ZS SH.DYN.MORT Female part-time employment SL.TLF.PART.TL.FE.ZS 1.3 Millennium Development Goals: protecting our Female legislators, senior oficials, and managers common environment Women in parliaments SG.GEN.PARL.ZS Female-headed households SP.HOU.FEMA.ZS Maternal mortality ratio, Modeled estimate SH.STA.MMRT Contraceptive prevalence rate SP.DYN.CONU.ZS HIV prevalence SH.DYN.AIDS.ZS Incidence of tuberculosis Economy SH.TBS.INCD States and markets SG.GEN.LSOM.ZS Data disaggregated by sex are available in the World Development Indicators database. a. Available online only as part of the table, not as an individual indicator. Global links Back World Development Indicators 2014 19 Poverty rates Population below international poverty linesa International poverty line in local currency Poverty gap at $2 a day % Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % % Poverty gap at $2 a day % $2 a day 2005 2005 Survey year b 120.8 2005 <2 <0.5 7.9 1.5 2008 <2 <0.5 4.3 0.9 1988 7.6 1.2 24.6 6.7 1995 6.8 1.4 23.6 6.5 2000 2009 Albania 75.5 Algeria 48.4 c Angola 88.1 141.0 1.7 2.7 245.2 Argentina Armenia Azerbaijan Bangladesh Belarus Belize Benin 77.5c Survey year b 54.3 29.9 70.2 42.4 43.4 16.5 67.4 31.5 2009d,e 2.0 1.2 3.4 1.7 2010d,e <2 0.7 <2 0.9 392.4 2008 <2 <0.5 12.4 2.3 2010 2.5 <0.5 19.9 4.0 2,170.9 3,473.5 2001 6.3 1.1 27.1 6.8 2008 <2 <0.5 2.8 0.6 31.9 51.0 2005 50.5 14.2 80.3 34.3 2010 43.3 11.2 76.5 30.4 949.5 1,519.2 2010 <2 <0.5 <2 <0.5 2011 <2 <0.5 <2 <0.5 1998f 11.3 4.7 26.3 10.0 1999 f 12.2 5.5 22.0 9.9 .. .. .. .. 2003 47.3 15.7 75.3 33.5 1.8 c 2.9c 344.0 550.4 Bhutan 23.1 36.9 2007 10.2 1.8 29.8 8.5 2012 Bolivia 3.2 5.1 2007e 13.1 6.6 24.7 10.9 2008e 1.7 <0.5 12.6 2.6 15.6 8.6 24.9 13.1 Bosnia and Herzegovina 1.1 1.7 2004 <2 <0.5 <2 <0.5 2007 <2 <0.5 <2 <0.5 Botswana 4.2 6.8 1986 35.6 13.8 54.7 25.8 1994 31.2 11.0 49.4 22.3 Brazil 2.0 3.1 2008f 6.0 3.4 11.3 5.3 2009 f 6.1 3.6 10.8 5.4 Bulgaria 0.9 1.5 2003 <2 <0.5 <2 <0.5 2007 <2 <0.5 <2 <0.5 Burkina Faso 303.0 484.8 2003 56.5 20.3 81.2 39.3 2009 44.6 14.7 72.6 31.7 Burundi 558.8 894.1 1998 86.4 47.3 95.4 64.1 2006 81.3 36.4 93.5 56.1 Cabo Verde 97.7 156.3 .. .. .. .. 2002 21.0 6.1 40.9 15.2 Cambodia 2,019.1 3,230.6 2008 22.8 4.9 53.3 17.4 2009 18.6 3.6 49.5 15.1 Cameroon 368.1 589.0 2001 10.8 2.3 32.5 9.5 2007 9.6 1.2 30.4 8.2 Central African Republic 384.3 614.9 2003 62.4 28.3 81.9 45.3 2008 62.8 31.3 80.1 46.8 Chad 409.5 655.1 .. .. .. .. 2003 61.9 25.6 83.3 43.9 Chile 484.2 774.7 2006f <2 0.5 3.2 1.1 2009 f <2 0.7 2.7 1.2 2008h 13.1 3.2 29.8 10.1 2009h 11.8 2.8 27.2 9.1 2009 f 9.7 4.7 18.5 8.2 2010 f 8.2 3.8 15.8 6.8 34.2 China 5.1g 8.2g Colombia 1,489.7 2,383.5 Comoros 368.0 588.8 .. .. .. .. 2004 46.1 20.8 65.0 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 8.9 2004 <2 <0.5 <2 <0.5 2008 <2 <0.5 <2 <0.5 1993e <0.5 Côte d’Ivoire Croatia 5.6 19.0 30.4 Czech Republic 407.3 651.6 Djibouti 134.8 215.6 2002 <2 <0.5 <2 <0.5 1996e <2 <0.5 <2 23.3 6.8 46.8 17.6 2008 23.8 7.5 46.3 17.8 .. .. .. .. 2002 18.8 5.3 41.2 14.6 2.4 25.5c 40.8 c 2009 f 3.0 0.7 10.0 2.7 2010 f 2.2 <0.5 9.9 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 <2 <0.5 2.6 <0.5 2004 <2 <0.5 <2 0.5 23.6 Dominican Republic Estonia 11.0 17.7 2003 Ethiopia 3.4 5.5 2005 39.0 9.6 77.6 28.9 2011 30.7 8.2 66.0 Fiji 1.9 3.1 2003 29.2 11.3 48.7 21.8 2009 5.9 1.1 22.9 6.0 554.7 887.5 .. .. .. .. 2005 4.8 0.9 19.6 5.0 12.9 20.7 1998 65.6 33.8 81.2 49.1 2003 29.8 9.8 55.9 24.4 1.0 1.6 2009 15.2 4.2 32.7 11.6 2010 18.0 5.8 35.6 13.7 5,594.8 8,951.6 1998 39.1 14.4 63.3 28.5 2006 28.6 9.9 51.8 21.3 2004f 24.4 13.2 39.2 20.2 2006f 13.5 4.7 26.3 10.5 2003 56.3 21.3 80.8 39.7 2007 43.3 15.0 69.6 31.0 Gabon Gambia, The Georgia Ghana Guatemala Guinea 20 Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % % $1.25 a day World Development Indicators 2014 5.7c 1,849.5 9.1c 2,959.1 Front ? User guide World view People Environment Poverty rates Population below international poverty linesa International poverty line in local currency Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % % Poverty gap at $2 a day % Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % % Poverty gap at $2 a day % $1.25 a day $2 a day 2005 2005 Guinea-Bissau 355.3 568.6 1993 52.1 20.6 75.7 37.4 2002 48.9 16.6 78.0 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 2004 <2 <0.5 <2 <0.5 2007 <2 <0.5 <2 <0.5 Hungary 171.9 275.0 Survey year b Survey year b 34.9 19.5i 31.2i 2005h 41.6 10.5 75.6 29.5 2010h 32.7 7.5 68.7 24.5 Indonesia 5,241.0i 8,385.7i 2010h 18.1 3.3 46.1 14.3 2011h 16.2 2.7 43.3 13.0 Iran, Islamic Rep. 3,393.5 5,429.6 1998 <2 <0.5 8.3 1.8 2005 <2 <0.5 8.0 1.8 799.8 1,279.7 .. .. .. .. 2007 2.8 <0.5 21.4 4.4 <2 <0.5 8.5 1.5 2004 <2 <0.5 5.4 0.8 India Iraq Jamaica Jordan 54.2c 86.7c 2002 0.6 1.0 2008 <2 <0.5 2.1 <0.5 2010 <2 <0.5 <2 <0.5 Kazakhstan 81.2 129.9 2008 <2 <0.5 <2 <0.5 2009 <2 <0.5 <2 <0.5 Kenya 40.9 65.4 1997 19.6 4.6 42.7 14.7 2005 43.4 16.9 67.2 31.8 Kyrgyz Republic 16.2 26.0 2010 6.7 1.5 22.9 6.4 2011 5.0 1.1 21.6 5.4 4,677.0 7,483.2 2002 44.0 12.1 76.9 31.1 2008 33.9 9.0 66.0 24.8 Lao PDR 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 .. .. .. .. 2007 83.8 40.9 94.9 59.6 2004 <2 <0.5 <2 0.5 2008 <2 <0.5 <2 <0.5 Liberia 0.6 1.0 Lithuania 2.1 3.3 Macedonia, FYR Madagascar Malawi 29.5 47.2 2009 <2 <0.5 5.9 0.9 2010 <2 <0.5 6.9 1.2 945.5 1,512.8 2005 67.8 26.5 89.6 46.9 2010 81.3 43.3 92.6 60.1 2004 73.9 32.3 90.5 51.8 2010 61.6 26.2 82.3 44.0 <2 <0.5 2.9 <0.5 2009e <2 <0.5 2.3 <0.5 71.2 113.8 Malaysia 2.6 4.2 Maldives 358.3 573.5 1998 25.6 13.1 37.0 20.0 2004 <2 <0.5 12.2 2.5 Mali 362.1 579.4 2006 51.4 18.8 77.1 36.5 2010 50.4 16.4 78.7 35.2 Mauritania 17.7 2007e 157.1 251.3 2004 25.4 7.0 52.6 19.2 2008 23.4 6.8 47.7 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 .. .. .. .. 31.2 16.3 44.7 24.5 Moldova 6.0 9.7 2009 <2 <0.5 7.1 1.2 2010 <2 <0.5 4.4 0.7 Montenegro 0.6 1.0 2009 <2 <0.5 <2 <0.5 2010 <2 <0.5 <2 <0.5 6.9 11.0 2001 6.3 0.9 24.3 6.3 2007 2.5 0.5 14.0 3.2 14,532.1 23,251.4 2003 74.7 35.4 90.0 53.6 2008 59.6 25.1 81.8 42.9 Morocco Mozambique Namibia Nepal Nicaragua Niger 1.3c 2000 d 6.3 10.1 1993e 49.1 24.6 62.2 36.5 2004 e 31.9 9.5 51.1 21.8 33.1 52.9 2003 53.1 18.4 77.3 36.6 2010 24.8 5.6 57.3 19.0 14.6c 2001e 14.4 3.7 34.4 11.5 2005e 11.9 2.4 31.7 9.6 2005 50.2 18.3 75.3 35.6 2008 43.6 12.4 75.2 30.8 9.1c 334.2 534.7 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 2009 f 5.9 1.8 14.6 4.9 2010 f 6.6 2.1 13.8 5.1 .. .. .. .. 1996 35.8 12.3 57.4 25.5 Panama 0.8c 1.2c Papua New Guinea 2.1c 3.4 c Paraguay Peru Philippines 4,255.6 2009 f 7.6 3.2 14.2 6.0 2010 f 7.2 3.0 13.2 5.7 2.1 3.3 2009 f 5.5 1.6 14.0 4.6 2010 f 4.9 1.3 12.7 4.1 2,659.7 30.2 48.4 2006 22.6 5.5 45.0 16.4 2009 18.4 3.7 41.5 13.8 Poland 2.7 4.3 2010 <2 <0.5 <2 <0.5 2011 <2 <0.5 <2 <0.5 Romania 2.1 3.4 2010 <2 <0.5 <2 0.5 2011 <2 <0.5 <2 <0.5 16.7 26.8 2008 <2 <0.5 <2 <0.5 2009 <2 <0.5 <2 <0.5 295.9 473.5 2006 72.1 34.8 87.4 52.2 2011 63.2 26.6 82.4 44.6 Russian Federation Rwanda Economy States and markets Global links Back World Development Indicators 2014 21 Poverty rates Population below international poverty linesa International poverty line in local currency $1.25 a day $2 a day 2005 2005 São Tomé and Príncipe Senegal Serbia Seychelles Sierra Leone Slovak Republic Slovenia South Africa Sri Lanka St. Lucia Sudan Survey year b 7,953.9 12,726.3 372.8 596.5 42.9 68.6 5.6c 9.0 c 1,745.3 2,792.4 23.5 37.7 198.2 2005 Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % % Poverty gap at $2 a day % Survey year b Population Poverty gap Population below at $1.25 below $1.25 a day a day $2 a day % % % Poverty gap at $2 a day % .. .. .. .. 2001 28.2 7.9 54.2 20.6 33.5 10.8 60.4 24.7 2011 29.6 9.1 55.2 21.9 2009 <2 <0.5 <2 <0.5 2010 <2 <0.5 <2 <0.5 2000 <2 <0.5 <2 <0.5 2007 <2 <0.5 <2 <0.5 2003 53.4 20.3 76.1 37.5 2011 51.7 16.6 79.6 35.8 2008e <2 <0.5 <2 <0.5 2009e <2 <0.5 <2 <0.5 317.2 2003 <2 <0.5 <2 <0.5 2004 <2 <0.5 <2 <0.5 5.7 9.1 2006 17.4 3.3 35.7 12.3 2009 13.8 2.3 31.3 10.2 50.0 80.1 2007 7.0 1.0 29.1 7.4 2010 4.1 0.7 23.9 5.4 .. .. .. .. 1995 20.9 7.2 40.6 15.5 .. .. .. .. 2009 19.8 5.5 44.1 15.4 .. .. .. .. 1999 15.5 5.9 27.2 11.7 2001 62.9 29.4 81.0 45.8 2010 40.6 16.0 60.4 29.3 3.3 2.4 c 154.4 3.8 c 247.0 Suriname 2.3c 3.7c Swaziland 4.7 7.5 30.8 49.3 .. .. .. .. 2004 <2 <0.5 16.9 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 0.7 352.8 564.5 2006 38.7 11.4 69.3 27.9 2011 28.2 8.8 52.7 20.9 3.9 Syrian Arab Republic Tajikistan Togo Trinidad and Tobago 5.8 c 9.2c 1988e <2 <0.5 8.6 1.9 1992e 4.2 1.1 13.5 Tunisia 0.9 1.4 2005 <2 <0.5 8.1 1.8 2010 <2 <0.5 4.3 1.1 Turkey 1.3 2.0 2009 <2 <0.5 2.7 0.7 2010 <2 <0.5 4.7 1.4 18.4 5,961.1c 9,537.7c 1993e 63.5 25.8 85.7 44.9 1998e 24.8 7.0 49.7 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 13.4 8.2 21.9 11.6 2006f 6.6 3.7 12.9 5.9 21.4 5.3 48.1 16.3 2008 16.9 3.8 43.4 13.5 Turkmenistan Venezuela, RB 1,563.9 2,502.2 2005f Vietnam 7,399.9 11,839.8 2006 West Bank and Gaza Yemen, Rep. Zambia 2.7c 4.3c 2007 <2 <0.5 2.5 0.5 2009 <2 <0.5 <2 <0.5 113.8 182.1 1998 12.9 3.0 36.4 11.1 2005 17.5 4.2 46.6 14.8 3,537.9 5,660.7 2006 68.5 37.0 82.6 51.8 2010 74.5 41.9 86.6 56.8 a. Based on nominal per capita consumption averages and distributions estimated parametrically from grouped household survey data, unless otherwise noted. b. Refers to the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected. c. Based on purchasing power parity (PPP) dollars imputed using regression. d. Covers urban areas only. e. Based on per capita income averages and distribution data estimated parametrically from grouped household survey data. f. Estimated nonparametrically from nominal income per capita distributions based on unit-record household survey data. g. PPP conversion factor based on urban prices. h. Population-weighted average of urban and rural estimates. i. Based on benchmark national PPP estimate rescaled to account for cost-of-living differences in urban and rural areas. j. Estimated nonparametrically from nominal consumption per capita distributions based on unit-record household survey data. 22 World Development Indicators 2014 Front ? User guide World view People Environment Poverty rates Trends in poverty indicators by region, 1990–2015 Region 1990 1993 1996 1999 2002 2005 2008 2010 estimate 2015 forecast Trend, 1990–2010 Share of population living on less than 2005 PPP $1.25 a day (%) East Asia & Paciic 56.2 50.7 35.9 35.6 27.6 17.1 14.3 12.5 5.5 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 Europe & Central Asia 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 & Paciic 926 871 640 656 523 332 284 251 115 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 1,908 1,910 1,704 1,743 1,639 1,389 1,302 1,215 970 Europe & Central Asia Total Regional distribution of people living on less than $1.25 a day (% of total population living on less than $1.25 a day) 48.5 45.6 37.6 37.6 31.9 23.9 21.8 20.7 11.8 Europe & Central Asia East Asia & Paciic 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 & Paciic 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 & Paciic 92.4 93.3 93.7 93.4 93.5 93.2 93.6 93.5 .. Europe & Central Asia 81.5 87.3 97.1 93.9 96.3 94.7 89.9 85.3 .. Latin America & Caribbean 94.9 91.8 95.9 97.7 97.5 95.9 94.5 86.9 .. Middle East & North Africa 76.8 65.3 81.7 70.0 21.5 85.7 46.7 30.8 .. South Asia 96.5 98.2 98.1 20.1 98.0 98.0 97.9 94.5 .. Sub- Saharan Africa 46.0 68.8 68.0 53.1 65.7 82.7 81.7 64.1 .. Total 86.4 89.4 91.6 68.2 87.8 93.0 90.2 84.7 .. Source: World Bank PovcalNet. Economy States and markets Global links Back World Development Indicators 2014 23 Poverty rates About the data The World Bank produced its irst global poverty estimates for devel- countries. The availability and quality of poverty monitoring data oping countries for World Development Report 1990: Poverty (World remain low in small states, fragile situations, and low-income coun- Bank 1990) using household survey data for 22 countries (Ravallion, tries and even some middle-income countries. Datt, and van de Walle 1991). Since then there has been consid- The low frequency and lack of comparability of the data available erable expansion in the number of countries that ield household in some countries create uncertainty over the magnitude of poverty income and expenditure surveys. The World Bank’s Development reduction. The table on trends in poverty indicators reports the Research Group maintains a database that is updated regularly as percentage of the regional and global population represented by new survey data become available (and thus may contain more recent household survey samples collected during the reference year or data or revisions that are not incorporated into the table) and con- during the two preceding or two subsequent years (in other words, ducts a major reassessment of progress against poverty about every within a ive-year window centered on the reference year). Data cov- three years. The next comprehensive reassessment is due later this erage in Sub- Saharan Africa and the Middle East and North Africa year, and revised and updated poverty data will be published in the remains low and variable. The need to improve household survey World Development Indicators online tables and database. programs for monitoring poverty is clearly urgent. But institutional, Last year the World Bank published the 2010 extreme poverty estimates for developing country regions and the developing world as a political, and inancial obstacles continue to limit data collection, analysis, and public access. whole (that is, countries classiied as low and middle income in 1990). They are provisional due to low household survey data availability for Data quality recent years (2008–12). Because about 40 new surveys have become Besides the frequency and timeliness of survey data, other data available this year, the provisional 2010 estimates will be revised into quality issues arise in measuring household living standards. The 2011 estimates during the aforementioned comprehensive reassess- surveys ask detailed questions on sources of income and how it ment. The projections to 2015, which will also be revised later this was spent, which must be carefully recorded by trained personnel. year, use the 2010 provisional estimates as a baseline and assume Income is generally more dificult to measure accurately, and con- that average household income or consumption will grow in line with sumption comes closer to the notion of living standards. And income the aggregate economic projections reported in Global Economic Pros- can vary over time even if living standards do not. But consumption pects 2014 (World Bank 2014) but that inequality within countries data are not always available: the latest estimates reported here will remain unchanged. Estimates of the number of people living in use consumption for about two-thirds of countries. extreme poverty are based on population projections in the World However, even similar surveys may not be strictly comparable Bank’s HealthStats database (http://datatopics.worldbank.org/hnp). because of differences in timing, sampling frames, or the quality PovcalNet (http://iresearch.worldbank.org/PovcalNet) is an inter- and training of enumerators. Comparisons of countries at different active computational tool that allows users to replicate these inter- levels of development also pose a potential problem because of dif- nationally comparable $1.25 and $2 a day poverty estimates for ferences in the relative importance of the consumption of nonmarket countries, developing country regions, and the developing world as a goods. The local market value of all consumption in kind (including whole and to compute poverty measures for custom country group- own production, particularly important in underdeveloped rural econ- ings and for different poverty lines. The Poverty and Equity Data portal omies) should be included in total consumption expenditure, but (http://povertydata.worldbank.org/poverty/home) provides access to may not be. Most survey data now include valuations for consump- the database and user-friendly dashboards with graphs and interac- tion or income from own production, but valuation methods vary. tive maps that visualize trends in key poverty and inequality indicators The statistics reported here are based on consumption data or, for different regions and countries. The country dashboards display when unavailable, on income data. Analysis of some 20 countries trends in poverty measures based on the national poverty lines (see for which both consumption and income data were available from the online table 2.7) alongside the internationally comparable estimates same surveys found income to yield a higher mean than consumption in the table, produced from and consistent with PovcalNet. but also higher inequality. When poverty measures based on consumption and income were compared, the two effects roughly can- Data availability 24 celled each other out: there was no signiicant statistical difference. The World Bank’s internationally comparable poverty monitoring Invariably some sampled households do not participate in surveys database now draws on income or detailed consumption data because they refuse to do so or because nobody is at home during the collected from interviews with 1.23 million randomly sampled interview visit. This is referred to as “unit nonresponse” and is distinct households through more than 850 household surveys collected from “item nonresponse,” which occurs when some of the sampled by national statistical ofices in nearly 130 countries. Despite prog- respondents participate but refuse to answer certain questions, such ress in the last decade, the challenges of measuring poverty remain. as those pertaining to income or consumption. To the extent that The timeliness, frequency, quality, and comparability of household survey nonresponse is random, there is no concern regarding biases surveys need to increase substantially, particularly in the poorest in survey-based inferences; the sample will still be representative World Development Indicators 2014 Front ? User guide World view People Environment Poverty rates of the population. However, households with different income might Definitions not be equally likely to respond. Richer households may be less likely • International poverty line in local currency is the international to participate because of the high opportunity cost of their time or poverty lines of $1.25 and $2.00 a day in 2005 prices, converted concerns about intrusion in their affairs. It is conceivable that the to local currency using the PPP conversion factors estimated by poorest can likewise be underrepresented; some are homeless or the International Comparison Program. • Survey year is the year in nomadic and hard to reach in standard household survey designs, and which the underlying data were collected or, when the data collection some may be physically or socially isolated and thus less likely to be period bridged two calendar years, the year in which most of the data interviewed. This can bias both poverty and inequality measurement were collected. • Population below $1.25 a day and population if not corrected for (Korinek, Mistiaen, and Ravallion 2007). below $2 a day are the percentages of the population living on less than $1.25 a day and $2 a day at 2005 international prices. As a International poverty lines result of revisions in PPP exchange rates, consumer price indexes, International comparisons of poverty estimates entail both concep- or welfare aggregates, poverty rates for individual countries cannot tual and practical problems. Countries have different deinitions of be compared with poverty rates reported in earlier editions. The poverty, and consistent comparisons across countries can be difi - PovcalNet online database and tool (http://iresearch.worldbank cult. Local poverty lines tend to have higher purchasing power in rich .org/PovcalNet) always contain the most recent full time series of countries, where more generous standards are used, than in poor comparable country data. • Poverty gap is the mean shortfall from countries. Poverty measures based on an international poverty line the poverty line (counting the nonpoor as having zero shortfall), attempt to hold the real value of the poverty line constant across expressed as a percentage of the poverty line. This measure relects countries, as is done when making comparisons over time. Since the depth of poverty as well as its incidence. World Development Report 1990 the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what Data sources poverty means in the world’s poorest countries. The welfare of people The poverty measures are prepared by the World Bank’s Develop- living in different countries can be measured on a common scale by ment Research Group. The international poverty lines are based on adjusting for differences in the purchasing power of currencies. The nationally representative primary household surveys conducted by commonly used $1 a day standard, measured in 1985 international national statistical ofices 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 ofices and World Bank Group country depart- was typical of the poverty lines in low-income countries at the time. ments. For details on data sources and methods used in deriving Early editions of World Development Indicators used PPPs from the the World Bank’s latest estimates, see http://iresearch.worldbank Penn World Tables to convert values in local currency to equivalent .org/povcalnet. purchasing power measured in U.S dollars. Later editions used 1993 consumption PPP estimates produced by the World Bank. References International poverty lines were recently revised using the new data Chen, Shaohua, and Martin Ravallion. 2011. “The Developing World on PPPs compiled in the 2005 round of the International Comparison Is Poorer Than We Thought, But No Less Successful in the Fight Program, along with data from an expanded set of household income Against Poverty.” Quarterly Journal of Economics 125(4): 1577–625. and expenditure surveys. The new extreme poverty line is set at Korinek, Anton, Johan A. Mistiaen, and Martin Ravallion. 2007. “An $1.25 a day in 2005 PPP terms, which represents the mean of the Econometric Method of Correcting for Unit Nonresponse Bias in poverty lines found in the poorest 15 countries ranked by per capita Surveys.” Journal of Econometrics 136: 213–35. consumption. The new poverty line maintains the same standard for Ravallion, Martin, Guarav Datt, and Dominique van de Walle. 1991. extreme poverty—the poverty line typical of the poorest countries “Quantifying Absolute Poverty in the Developing World.” Review of in the world—but updates it using the latest information on the cost of living in developing countries. PPP exchange rates are used to Income and Wealth 37(4): 345–61. Ravallion, Martin, Shaohua Chen, and Prem Sangraula. 2009. “Dol- estimate global poverty because they take into account the local lar a Day Revisited.” World Bank Economic Review 23(2): 163–84. prices of goods and services not traded internationally. But PPP rates World Bank. 1990. World Development Report 1990: Poverty. Wash- were designed for comparing aggregates from national accounts, not for making international poverty comparisons. As a result, there is no certainty that an international poverty line measures the same ington, DC. ———. 2008. Poverty Data: A Supplement to World Development Indicators 2008. Washington, DC. degree of need or deprivation across countries. So-called poverty ———. 2014. Global Economic Prospects: Coping with Policy Normal- PPPs, designed to compare the consumption of the poorest people ization in High-income Countries. Volume 8, January 14. Washington, in the world, might provide a better basis for comparison of poverty DC. across countries. Work on these measures is ongoing. Economy States and markets Global links Back World Development Indicators 2014 25 PEOPLE 26 World Development Indicators 2014 Front ? User guide World view People Environment The People section presents demographic trends and forecasts alongside indicators of education, health, jobs, social protection, poverty, and the distribution of income. Together they provide a multidimensional portrait of human development. This edition includes estimates of extreme poverty rates for 2010—measured as the proportion of the population living on less than $1.25 a day. The availability, frequency, and quality of poverty monitoring data remain low, especially in small states and in countries and territories with fragile situations. While estimates may change marginally as additional country data become available, it is now clear that the irst Millennium Development Goal target— cutting the global extreme poverty rate to half its 1990 level—was achieved before the 2015 target date. In 1990, the benchmark year for the Millennium Development Goals, the extreme poverty rate was 43.1 percent. Estimates for 2010 show that the extreme poverty rate had fallen to 20.6 percent. The World Bank is working to create a complementary dataset to measure the goal of promoting shared prosperity, using the per capita incomes of the bottom 40 percent of the population in each country. To be released at the 2014 Annual Meetings of the World Bank, the dataset will be included in future World Development Indicators. In addition to extreme poverty rates, the People section includes many other indicators to monitor the Millennium Development Goals. Following the Millennium Declaration by the United Nations General Assembly in 2000, various international agencies, including the World Bank, resolved to monitor the Millennium Development Goals using a harmonized set of indicators and to invest in improving data availability Economy States and markets and quality. These efforts range from providing technical and inancial assistance for strengthening country statistical systems to fostering international collaboration through participation in the United Nations Inter-agency and Expert Group on the Millennium Development Goal Indicators and several thematic interagency groups. For example, estimates of child mortality in 2000 varied by source, method, and availability, making comparisons across countries and over time dificult. To address this, a UN interagency group has improved methods and harmonization, shared sources, reported on progress, and helped boost countries’ measurement capacity. This effort has produced consistent estimates of neonatal, infant, and under-ive mortality rates that span 50 years. Similar interagency efforts are improving maternal mortality estimates and gender statistics. For gender an interagency and expert group has endorsed a set of indicators to guide national efforts to produce, compile, and disseminate comparable gender statistics. As part of this work, the World Bank is providing technical assistance and training to national statistical ofices, and new partnerships and initiatives, such as Evidence and Data for Gender Statistics and Data2X, are facilitating international action and collaboration. People includes indicators disaggregated by location and by socioeconomic and demographic variables, such as sex, age, subnational and regional location, and wealth. These data provide important perspectives on the disparities within countries. New for the 2014 edition is an indicator of severe wasting, disaggregated by sex. Other new indicators include national estimates for labor force participation rates and ratios of employment to population. Global links Back 2 World Development Indicators 2014 27 Highlights Lower secondary completion rates fell only in the Middle East and North Africa Over the past 20 years lower secondary completion rates have increased Completion rate, lower secondary education (% of relevant age group) 66 percent in low- and middle-income countries. East Asia and Paciic 125 has seen the most progress, with the rate doubling to 99 percent over East Asia & Pacific 100 1990–2011. Until the mid-1990s the Middle East and North Africa was on par with East Asia and Paciic, but upward trajectories in many Middle East & North Africa 75 of the region’s countries have not been enough to offset Iran’s decline since 2003. In Sub-Saharan Africa only 26 percent of students in the inal grade of lower secondary education completed school in 2011, Low & middle income 50 compared with 70 percent of students in the inal grade of primary Sub-Saharan Africa education. Given that these rates are an upper estimate of actual completion rates, the real situation is likely to be worse. 25 0 1990 1995 2000 2005 2011 Source: United Nations Educational, Scientiic and Cultural Organization Institute for Statistics. Europe and Central Asia has the lowest gap between net and gross enrollment rates The gap between net and gross enrollment rates captures the incidence Gross enrollment ratio, primary education, 2011 (%) Share of underage or overage students 125 Net enrollment rate of underage or overage students and is a measure of the eficiency of an education system. In Sub-Saharan Africa 42 percent of children enrolled in primary education dropped out in 2011, giving the region 100 the highest dropout rate, repetition rate, and gap between gross and net enrollment. Latin America and Caribbean’s net enrollment rate is 75 almost the same as Europe and Central Asia’s, but the gap is wider in the former. This suggests that the education system is more eficient 50 Europe and Central Asia, which has the lowest repeater rate and dropout rate. 25 0 Sub-Saharan Africa Latin America & Caribbean South Asia East Asia & Pacific Middle East & North Africa Europe & Central Asia Source: United Nations Educational, Scientiic and Cultural Organization Institute for Statistics. In 2012 child wasting was most serious in South Asia Prevalence of wasting among children ages 0–59 months, 2012 (%) 95% lower confidence limit 20 Prevalence estimate 95% upper confidence limit WHO severity level classification Critical Wasting, deined as weight for height more than two standard deviations below the median for the international reference population ages 0–59 months, is a measure for acute malnutrition. World Health Organization (WHO) member countries have endorsed a global nutrition 15 Poor target to reduce the prevalence of child wasting to less than 5 percent by 2025. In 2012 the prevalence was estimated at 8.5 percent for all Public health emergency line 10 Serious developing countries and was below 5 percent in three out of the six World Bank developing regions. In the Middle East and North Africa and Sub- Saharan Africa the prevalence was above 5 percent but below 5 Acceptable the WHO Public Health Emergency Line of 10 percent. South Asia had 0 the highest prevalence, 16 percent, which is considered critical in the Latin Europe America & & Central Caribbean Asia East Asia & Pacific Middle All SubEast & developing Saharan North Africa countries Africa South Asia WHO severity level classiication. Source: UNICEF, WHO, and World Bank 2013. 28 World Development Indicators 2014 Front ? User guide World view People Environment Most maternal deaths are in Sub-Saharan Africa and South Asia In 2010, 85 percent of the world’s maternal deaths occurred in SubSaharan Africa and South Asia. Although the number of maternal Share of global maternal deaths (%) High income 100 deaths has been falling in every region—globally from 540,000 to Middle East & North Africa Europe & Central Asia Latin America & Caribbean East Asia & Pacific 290,000 over 1990–2010—the share of maternal deaths is increasingly concentrated in these two regions. In 2010 more than half of 75 maternal deaths occurred in Sub- Saharan Africa, and 29 percent South Asia occurred in South Asia. In Sub- Saharan Africa the share of global maternal deaths increased from 35 percent in 1990 to 57 percent 50 in 2010, suggesting a rate of decline that is slower than in other regions. In South Asia the share decreased from 45 percent in 1990 to 29 percent in 2010, but it still has the second largest share of 25 global maternal deaths. Sub-Saharan Africa 0 1990 1995 2000 2005 2010 Source: WHO and others 2012. Globally, a large proportion of under-ive deaths occur in the irst 28 days of life The irst 28 days of life (the neonatal period) are the most vulnerable time for a child’s survival. The proportion of deaths among chil- Proportion of deaths among children under age 5 that occur during the neonatal period (%) 60 dren under age 5 that occur in the neonatal period is large and has increased in all regions since 1990, although neonatal mortality rates have been falling in every region. Declines in the neonatal mortality rate are slower than those in the under-i ve mortality rate: between 40 1990 and 2012 global neonatal mortality rates fell from 33 deaths per 1,000 births to 21, but the proportion of neonatal deaths in underi ve deaths increased from 37 percent to 44 percent. In 2012 the 20 and North Africa, East Asia and Paciic, South Asia, and Latin America and the Caribbean. 0 2012 1990 proportion was more than 50 percent in four regions: Middle East Middle East East Asia & North & Pacific Africa South Asia Latin Europe Sub-Saharan World America & & Central Africa Caribbean Asia Source: UN Inter-agency Group for Child Mortality Estimation 2013. Over 20 percent of ministers in Latin America and Sub-Saharan Africa are women With over 20 percent of ministers being women, Latin America and Caribbean and Sub- Saharan Africa lead developing regions in Women in ministerial positions (% of total) 25 Latin America & Caribbean women’s participation in ministerial positions. Women occupy over 40 percent of ministerial positions in Cabo Verde, Ecuador, Bolivia, Nicaragua, and South Africa. However, even with these achieve- 20 Sub-Saharan Africa ments, men still dominate leadership and decisionmaking positions in politics, business, and households. There are still 14 countries, 15 South Asia including 5 high-income countries, that have no female representation in ministerial positions. Gender equality in decisionmaking not Europe & Central Asia East Asia & Pacific 10 only benei ts women and girls, but also matters for society more broadly. Empowering women as economic, political, and social actors Middle East & North Africa 5 can change policy choices and make institutions more representative of a range of voices. 0 2005 2008 2010 2012 Source: Inter Parliamentary Union. Economy States and markets Global links Back World Development Indicators 2014 29 2 People Prevalence Under-five of child mortality malnutrition, rate underweight estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group % of children under age 5 per 1,000 live births 2005–12a 2012 2010 Afghanistan 2012 2012 2008–12a % ages 15–24 ILO estimate % ages 15 and older workers % of total employment % of total labor force % of total 2005–12a 2012 2008–12a 2008–12a 2008–12a .. 99 460 87 <0.1 .. .. 48 .. .. Albania 6.3 17 27 15 .. .. 99 55 .. 14 .. Algeria 3.7 20 97 10 .. 100 92 44 30 10 .. .. .. American Samoa .. .. .. .. .. .. .. .. .. .. Andorra .. 3 .. .. .. .. .. .. .. .. .. 15.6 164 450 170 2.3 54 73 70 .. .. .. .. Angola Antigua and Barbuda .. 10 .. 49 .. 100 .. .. .. .. Argentina 2.3 14 77 54 0.4 109 99 61 19 7 .. Armenia 5.3 16 30 27 0.2 100 100 63 30 18 22 Aruba Australia Austria Azerbaijan Bahamas, The Bahrain .. .. .. 27 .. 95 99 .. .. .. .. 0.2 5 7 12 .. .. .. 65 9 5 37 27 .. 4 4 4 .. 97 .. 61 9 4 8.4 35 43 40 0.2 92 100 66 55 5 7 .. 17 47 28 3.3 93 .. 74 .. 14 52 .. .. 10 20 14 .. .. 98 71 2 1 36.8 41 240 81 <0.1 75 79 71 .. 5 .. .. 18 51 48 0.9 104 .. 71 .. 12 47 Belarus 1.3 5 4 21 0.4 103 100 56 2 6 .. Belgium .. 4 8 7 .. 91 .. 53 10 8 30 Bangladesh Barbados Belize 6.2 18 53 71 1.4 116 .. 66 .. 8 .. Benin 20.2 90 350 90 1.1 71 42 73 .. .. .. Bermuda .. .. .. .. .. 91 .. .. .. .. .. 12.8 45 180 41 0.2 101 74 72 53 2 27 Bolivia 4.5 41 190 72 0.3 92 99 72 55 3 .. Bosnia and Herzegovina 1.5 7 8 15 .. .. 100 45 27 28 .. 11.2 53 160 44 23.0 95 95 77 .. .. .. 2.2 14 56 71 .. .. 98 70 25 7 .. .. 8 24 23 .. 102 100 64 .. .. .. Bhutan Botswana Brazil Brunei Darussalam Bulgaria .. 12 11 36 .. 104 98 53 8 12 37 Burkina Faso 26.2 102 300 115 1.0 58 39 84 .. .. .. Burundi 29.1 104 800 30 1.3 62 89 83 .. .. .. .. 22 79 71 0.2 99 98 67 .. .. .. Cambodia 29.0 40 250 44 0.8 98 87 83 64 0 21 Cameroon 15.1 95 690 116 4.5 73 81 70 76 4 .. .. 5 12 14 .. .. .. 66 .. 7 36 Cabo Verde Canada Cayman Islands .. .. .. .. .. .. 99 .. .. 4 44 28.0 129 890 98 .. 45 66 79 .. .. .. Chad .. 150 1,100 152 2.7 35 48 72 .. .. .. Channel Islands .. .. .. 8 .. .. .. .. .. .. .. Central African Republic 30 Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per Modeled own-account Chile 0.5 9 25 55 0.4 97 99 62 24 6 .. China 3.4 14 37 9 .. .. 100 71 .. 4 .. Hong Kong SAR, China .. .. .. 3 .. 98 .. 59 7 3 32 Macao SAR, China .. .. .. 4 .. 98 100 71 4 3 31 Colombia 3.4 18 92 69 0.5 105 98 67 49 11 .. Comoros .. 78 280 51 2.1 80 86 58 .. .. .. Congo, Dem. Rep. 24.2 146 540 135 1.1 73 66 72 .. .. .. Congo, Rep. 11.8 96 560 127 2.8 73 .. 71 .. .. .. Front ? World Development Indicators 2014 User guide World view People Environment People 2 Prevalence Under-five of child mortality malnutrition, rate underweight Costa Rica % of children under age 5 per 1,000 live births 2005–12a 2012 Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per Modeled own-account estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group 2010 2012 2012 2008–12a % ages 15–24 ILO estimate % ages 15 and older workers % of total employment % of total labor force % of total 2005–12a 2012 2008–12a 2008–12a 2008–12a 1.1 10 40 61 0.3 95 98 63 20 8 29.4 108 400 130 3.2 61 68 67 .. .. .. Croatia .. 5 17 13 .. 94 100 51 17 16 25 Cuba .. 6 73 43 <0.1 96 100 57 .. 3 .. Curaçao .. .. .. 28 .. .. .. .. .. .. .. Cyprus .. 3 10 5 .. 102 100 64 13 12 14 Czech Republic .. 4 5 5 .. 102 .. 59 15 7 26 99 .. 63 6 8 28 52b .. 52 .. .. .. Côte d’Ivoire Denmark Djibouti Dominica Dominican Republic Ecuador 35 .. 4 12 5 .. 29.8 81 200 19 1.2 .. 13 .. .. .. 104 .. .. .. .. .. 3.4 27 150 100 0.7 90 97 65 37 15 .. .. 23 110 77 0.6 111 99 68 51 4 .. Egypt, Arab Rep. 6.8 21 66 43 <0.1 107 89 49 23 13 .. El Salvador 29 6.6 16 81 76 0.6 101 96 62 38 6 Equatorial Guinea .. 100 240 113 6.2 55 98 87 .. .. .. Eritrea .. 52 240 65 0.7 31 90 85 .. .. .. Estonia .. 4 2 17 .. 96 100 62 5 10 36 Ethiopia 29.2 68 350 78 1.3 .. 55 84 .. .. .. Faeroe Islands .. .. .. .. .. .. .. .. .. .. .. Fiji .. 22 26 43 0.2 103 .. 55 39 9 .. Finland .. 3 5 9 .. 97 .. 60 10 8 32 France .. 4 8 6 .. .. .. 56 7 10 39 French Polynesia Gabon Gambia, The .. .. .. 38 .. .. .. 56 .. .. .. 6.5 62 230 103 4.0 .. 98 61 .. .. .. .. 15.8 73 360 116 1.3 70 68 78 .. .. Georgia 1.1 20 67 47 0.3 108 100 65 61 15 .. Germany 1.1 4 7 4 .. 100 .. 60 7 5 30 Ghana 14.3 72 350 58 1.4 Greece .. 5 3 12 .. 98b 100 86 69 77 4 .. 99 53 30 24 23 .. Greenland .. .. .. .. .. .. .. .. .. .. Grenada .. 14 24 35 .. 112 .. .. .. .. .. Guam .. .. .. 50 .. .. .. 63 .. 12 .. Guatemala 13.0 32 120 97 0.7 88 87 68 .. 3 .. Guinea 16.3 101 610 131 1.7 61 31 72 .. .. .. Guinea-Bissau 16.6 129 790 99 3.9 64 73 73 .. .. .. Guyana 11.1 35 280 88 1.3 85 93 61 .. .. .. Haiti 18.9 76 350 42 2.1 .. 72 66 .. .. .. 8.6 23 100 84 0.5 100 96 63 53 4 .. .. 6 21 12 .. 99 99 52 6 11 40 40 Honduras Hungary Iceland .. 2 5 11 .. 99 .. 74 8 6 India 43.5 56 200 33 0.3 96 81 56 81 4 14 Indonesia 18.6 31 220 48 0.4 100 99 68 57 7 22 13 Iran, Islamic Rep. Iraq Ireland .. 18 21 32 0.2 102 99 45 42 11 7.1 34 63 69 .. .. 82 42 .. 15 .. .. 4 6 8 .. .. .. 60 12 15 33 Isle of Man .. .. .. .. .. .. .. .. .. .. .. Israel .. 4 7 8 .. 102 .. 64 7 7 32 Economy States and markets Global links Back World Development Indicators 2014 31 2 People Prevalence Under-five of child mortality malnutrition, rate underweight % of children under age 5 per 1,000 live births 2005–12a 2012 Italy estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group 2010 2012 2012 % ages 15–24 ILO estimate % ages 15 and older workers % of total employment % of total labor force % of total 2008–12a 2005–12a 2012 2008–12a 2008–12a 2008–12a .. 4 4 4 .. 103 100 49 18 11 3.2 17 110 70 1.7 .. 96 63 38 14 .. .. 3 5 5 .. 102 .. 59 11 4 .. Jordan 1.9 19 63 26 .. 93 99 41 10 12 .. Kazakhstan 3.7 19 51 30 .. 102b 100 72 29 5 38 16.4 73 360 94 6.1 .. 82 67 .. .. .. .. 60 .. 17 .. 115 .. .. .. .. .. 18.8 29 81 1 .. .. 100 78 .. .. .. .. 4 16 2 .. 103 .. 61 25 3 10 Jamaica Japan Kenya Kiribati Korea, Dem. People’s Rep. Korea, Rep. 25 Kosovo .. .. .. .. .. .. .. .. 17 31 .. Kuwait 2.2 11 14 14 .. .. 99 68 2 4 .. .. Kyrgyz Republic Lao PDR Latvia 2.7 27 71 29 0.3 98 100 67 .. 8 31.6 72 470 65 0.3 95 84 78 .. .. .. .. 9 34 14 .. 99 100 60 8 15 45 Lebanon .. 9 25 12 .. 86 99 47 .. .. .. Lesotho 13.5 100 620 89 23.1 72 83 66 .. 25 .. Liberia 20.4 75 770 117 0.9 65 49 61 79 4 .. 5.6 15 58 3 .. .. 100 53 .. .. .. Liechtenstein .. .. .. .. .. 101 .. .. .. .. .. Lithuania .. 5 8 11 .. 101 100 61 9 13 38 Libya Luxembourg Macedonia, FYR Madagascar .. 2 20 8 .. 84 .. 58 6 5 24 2.1 7 10 18 .. 94 99 55 22 31 28 .. .. 58 240 123 0.5 70 65 89 .. .. Malawi 13.8 71 460 145 10.8 74 72 83 .. .. .. Malaysia 12.9 9 29 6 0.4 .. 98 59 21 3 25 Maldives 17.8 11 60 4 <0.1 110 99 67 .. .. .. Mali 27.9 128 540 176 0.9 59 47 66 .. .. .. 23 Malta .. 7 8 18 .. 92 98 52 9 6 Marshall Islands .. 38 .. .. .. 100 .. .. .. .. .. 19.5 84 510 73 0.4 69 69 54 .. 31 .. Mauritania Mauritius Mexico Micronesia, Fed. Sts. Moldova Monaco .. 15 60 31 1.2 99 97 59 17 9 23 2.8 16 50 63 0.2 93 98 62 29 5 31 .. 39 100 19 .. .. .. .. .. .. .. 3.2 18 41 29 0.7 90 100 40 29 6 44 .. 4 .. .. .. .. .. .. .. .. .. Mongolia 5.3 28 63 19 <0.1 130 96 62 55 5 47 Montenegro 2.2 6 8 15 .. 101 Morocco 3.1 31 100 36 0.1 Mozambique 15.6 90 490 138 Myanmar 22.6 52 200 Namibia 17.5 39 Nepal 29.1 Netherlands .. New Caledonia .. New Zealand .. Nicaragua Niger 32 Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per Modeled own-account World Development Indicators 2014 99 50 .. 20 30 99b 82 50 51 9 13 11.1 52 67 84 .. .. .. 12 0.6 95 96 79 .. .. .. 200 55 13.3 85 87 59 33 17 37 42 170 74 0.3 100 b 4 6 6 .. .. .. 21 6 15 25 82 83 .. 3 .. .. .. 65 12 5 30 .. .. 100 57 .. .. .. .. .. .. 68 12 7 40 5.7 24 95 101 0.3 80 87 63 47 8 .. 39.9 114 590 205 0.5 49 37 65 .. .. .. Front ? User guide World view People Environment People 2 Prevalence Under-five of child mortality malnutrition, rate underweight Nigeria Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per Modeled own-account estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group % of children under age 5 per 1,000 live births 2005–12a 2012 2010 2012 2012 2008–12a % ages 15–24 ILO estimate % ages 15 and older workers % of total employment % of total labor force % of total 2005–12a 2012 2008–12a 2008–12a 2008–12a 24.4 124 630 120 3.1 76 66 56 .. .. Northern Mariana Islands .. .. .. .. .. .. .. .. .. .. .. Norway .. 3 7 8 .. 98 .. 66 5 3 31 Oman Pakistan Palau Panama Papua New Guinea Paraguay Peru Philippines .. 8.6 12 32 11 .. 104 98 64 .. .. .. 30.9 86 260 27 <0.1 72 71 54 63 5 3 .. 21 .. .. .. .. .. .. .. .. .. 3.9 19 92 79 0.7 98 98 66 29 4 46 18.1 63 230 62 0.5 .. 71 72 .. .. .. 3.4 22 99 67 0.3 86 99 70 43 5 34 4.5 18 67 51 0.4 91 97 76 46 4 19 20.2 30 99 47 <0.1 91 98 65 40 7 55 Poland .. 5 5 12 .. 95 100 57 18 10 38 Portugal .. 4 8 13 .. .. 100 61 17 16 33 Puerto Rico .. .. 20 47 .. .. 87 42 .. 15 43 Qatar .. 7 7 10 .. .. 97 87 .. 1 4 Romania .. 12 27 31 .. 97 97 56 32 7 31 37 Russian Federation Rwanda Samoa San Marino São Tomé and Príncipe Saudi Arabia Senegal Serbia Seychelles Sierra Leone Singapore .. 10 34 26 .. 98 100 64 6 6 11.7 55 340 34 2.9 58 77 86 .. .. .. .. 18 100 28 .. 102 100 41 38 6 36 18 .. 3 .. .. .. 14.4 53 70 65 1.0 .. .. .. .. 104b 5.3 9 24 10 14.4 60 370 1.6 7 12 93 80 61 .. .. .. .. 106 98 52 .. 6 5 94 0.5 60 65 77 .. .. .. 17 .. 93 99 52 26 24 33 .. .. 13 .. 56 .. 105 99 .. .. .. 21.1 182 890 101 1.5 72 61 67 .. .. .. .. 3 3 6 .. .. 100 68 9 3 34 Sint Maarten .. .. .. .. .. .. .. .. .. .. .. Slovak Republic .. 8 6 16 .. 95 .. 60 12 14 31 38 Slovenia .. 3 12 1 .. 101 100 58 13 9 Solomon Islands 11.5 31 93 65 .. 85 .. 66 .. .. .. Somalia 32.8 147 1,000 110 0.5 .. .. 56 .. .. .. 31 South Africa South Sudan Spain Sri Lanka 8.7 45 300 51 17.9 .. 99 52 10 25 32.5 104 .. 75 2.7 .. .. .. .. .. .. .. 5 6 11 .. 102 100 59 12 25 30 21.6 10 35 17 <0.1 97 98 55 41 4 24 St. Kitts and Nevis .. 9 .. .. .. 93 .. .. .. .. .. St. Lucia .. 18 35 56 .. 92 .. 69 .. 21 .. St. Martin .. .. .. .. .. .. .. .. .. .. .. St. Vincent & the Grenadines .. 27.0 c Sudan 23 48 55 .. 99 .. 67 8 19 .. 73c 730 84 c .. .. 87 54 .. 15 .. Suriname 5.8 21 130 35 1.1 88 98 55 .. .. .. Swaziland 5.8 80 320 72 26.5 77 94 57 .. .. .. Sweden .. 3 4 7 .. 102 .. 64 7 8 35 Switzerland .. 4 8 2 .. 96 .. 68 9 4 33 Syrian Arab Republic 10.1 15 70 42 .. 107 95 44 33 8 9 Tajikistan 15.0 58 65 43 0.3 98 100 68 47 12 .. Economy States and markets Global links Back World Development Indicators 2014 33 2 People Prevalence Under-five of child mortality malnutrition, rate underweight Maternal Adolescent Prevalence Primary Youth Labor force Vulnerable Unemployment Female mortality fertility of HIV completion literacy participation employment legislators, ratio rate rate rate rate senior Unpaid family officials, and workers and managers Modeled births per Modeled own-account estimate 1,000 % of per 100,000 women ages population % of relevant live births 15–19 ages 15–49 age group % ages 15–24 ILO estimate % ages 15 and older workers % of total employment % of total labor force % of total 2005–12a 2012 2008–12a 2008–12a 2008–12a % of children under age 5 per 1,000 live births 2005–12a 2012 2010 2012 Tanzania 16.2 54 460 123 5.1 81 75 89 .. 4 .. Thailand 7.0 13 48 41 1.1 .. 98 72 54 1 25 2012 2008–12a Timor-Leste 45.3 57 300 52 .. 71 80 38 70 4 10 Togo 16.5 96 300 92 2.9 74 80 81 .. .. .. Tonga .. 13 110 18 .. 100 99 64 .. .. .. Trinidad and Tobago .. 21 46 35 1.6 95 100 64 .. 5 .. 3.3 16 56 5 <0.1 102 97 48 29 18 .. Turkey .. 14 20 31 .. 103 99 49 32 9 10 Turkmenistan .. 53 67 18 .. .. 100 61 .. .. .. Turks and Caicos Islands .. .. .. .. .. .. .. .. .. .. .. Tunisia Tuvalu 1.6 30 .. .. .. .. .. .. .. .. .. Uganda 14.1 69 310 127 7.2 53 87 78 .. 4 .. Ukraine .. 11 32 26 0.9 103 100 59 18 8 39 United Arab Emirates .. 8 12 28 .. 111 95 79 1 4 10 United Kingdom .. 5 12 26 .. .. .. 62 12 8 34 43 United States .. 7 21 31 .. 98 .. 63 .. 8 Uruguay 4.5 7 29 58 0.7 104 99 66 22 7 .. Uzbekistan 4.4 40 28 39 0.1 92 100 61 .. .. .. 11.7 18 110 45 .. 84 95 71 70 5 29 2.9 15 92 83 0.6 96 99 65 32 8 .. 12.0 23 59 29 0.4 101 97 77 63 2 .. Vanuatu Venezuela, RB Vietnam Virgin Islands (U.S.) West Bank and Gaza Yemen, Rep. .. .. .. 51 .. .. .. 63 .. .. .. 2.2 23 .. 46 .. 90 99 41 27 23 10 .. 60 200 47 0.1 70 86 49 30 18 5 Zambia 14.9 89 440 125 12.7 91 64 79 .. .. .. Zimbabwe 10.1 90 570 60 14.7 .. 91 86 .. .. .. 15.1 w 48 w 210 w 45 w 0.8 w 89 w 64 w .. w 6w World 91 w Low income 21.8 82 410 93 2.3 67 73 76 .. .. Middle income 15.7 45 190 40 .. 94 91 63 .. 5 Lower middle income 24.1 61 260 47 0.6 91 84 58 65 5 Upper middle income 2.8 20 64 31 .. .. 98 67 .. 5 Low & middle income 17.0 53 240 49 1.2 89 88 64 .. 5 East Asia & Paciic 5.3 21 83 20 .. .. 99 71 .. 4 Europe & Central Asia 1.8 22 32 31 .. 99 99 57 27 9 Latin America & Carib. 2.9 19 82 69 .. 102 97 67 32 7 Middle East & N. Africa 6.2 26 81 37 .. 91 92 46 34 11 South Asia 32.2 60 220 39 0.3 88 80 57 78 4 Sub-Saharan Africa 20.8 98 500 108 4.7 69 70 70 .. .. 1.4 6 16 18 .. 100 .. 61 11 8 .. 4 6 6 .. 99 100 57 11 11 High income Euro area a. Data are for the most recent year available. b. Data are for 2013. c. Excludes South Sudan. 34 World Development Indicators 2014 Front ? User guide World view People Environment People 2 About the data Though not included in the table due to space limitations, many and research institutes, has developed and adopted a statistical indicators in this section are available disaggregated by sex, place method that uses all available information to reconcile differences. of residence, wealth, and age in the World Development Indicators Trend lines are obtained by i tting a country-specii c regression database. model of mortality rates against their reference dates. (For further discussion of childhood mortality estimates, see UN Inter-agency Child malnutrition Group for Child Mortality Estimation [2013]; for detailed background Good nutrition is the cornerstone for survival, health, and devel- data and for a graphic presentation, see www.childmortality.org). opment. Well-nourished children perform better in school, grow into healthy adults, and in turn give their children a better start Maternal mortality in life. Well-nourished women face fewer risks during pregnancy Measurements of maternal mortality are subject to many types and childbirth, and their children set off on irmer developmental of errors. In countries with incomplete vital registration systems, paths, both physically and mentally. Undernourished children have deaths of women of reproductive age or their pregnancy status may lower resistance to infection and are more likely to die from com- not be reported, or the cause of death may not be known. Even in mon childhood ailments such as diarrheal diseases and respiratory high-income countries with reliable vital registration systems, mis- infections. Frequent illness saps the nutritional status of those who classiication of maternal deaths has been found to lead to serious survive, locking them into a vicious cycle of recurring sickness and underestimation. Surveys and censuses can be used to measure faltering growth. maternal mortality by asking respondents about survivorship of sis- The proportion of underweight children is the most common child ters. But these estimates are retrospective, referring to a period malnutrition indicator. Being even mildly underweight increases the approximately ive years before the survey, and may be affected by risk of death and inhibits cognitive development in children. And recall error. Further, they relect pregnancy-related deaths (deaths it perpetuates the problem across generations, as malnourished while pregnant or within 42 days of pregnancy termination, irrespec- women are more likely to have low-birthweight babies. Estimates tive of the cause of death) and need to be adjusted to conform to of prevalence of underweight children are from the World Health the strict deinition of maternal death. Organization’s (WHO) Global Database on Child Growth and Malnu- Maternal mortality ratios in the table are modeled estimates trition, a standardized compilation of child growth and malnutrition based on work by WHO, UNICEF, United Nations Population Fund data from national nutritional surveys. To better monitor global child (UNFPA), and the World Bank and include country-level time series malnutrition, the United Nations Children’s Fund (UNICEF), WHO, data. For countries without complete registration data but with other and the World Bank have jointly produced estimates for 2012 and types of data and for countries with no data, maternal mortality trends since 1990 for regions, income groups, and the world, using is estimated with a multilevel regression model using available a harmonized database and aggregation method. national maternal mortality data and socioeconomic information, including fertility, birth attendants, and gross domestic product. Under-five mortality The methodology differs from that used for previous estimates, so Mortality rates for children and others are important indicators data presented here should not be compared across editions (WHO of health status. When data on the incidence and prevalence of and others 2012). diseases are unavailable, mortality rates may be used to identify vulnerable populations. And they are among the indicators most Adolescent fertility frequently used to compare socioeconomic development across Reproductive health is a state of physical and mental well-being countries. in relation to the reproductive system and its functions and pro- The main sources of mortality data are vital registration systems cesses. Means of achieving reproductive health include education and direct or indirect estimates based on sample surveys or cen- and services during pregnancy and childbirth, safe and effective suses. A complete vital registration system—covering at least contraception, and prevention and treatment of sexually transmitted 90 percent of vital events in the population—is the best source of diseases. Complications of pregnancy and childbirth are the leading age-speciic mortality data. But complete vital registration systems cause of death and disability among women of reproductive age in are fairly uncommon in developing countries. Thus estimates must developing countries. be obtained from sample surveys or derived by applying indirect Adolescent pregnancies are high risk for both mother and child. estimation techniques to registration, census, or survey data (see They are more likely to result in premature delivery, low birthweight, Primary data documentation). Survey data are subject to recall error. delivery complications, and death. Many adolescent pregnancies are To make estimates comparable and to ensure consistency across unintended, but young girls may continue their pregnancies, giving estimates by different agencies, the UN Inter-agency Group for Child up opportunities for education and employment, or seek unsafe Mortality Estimation, which comprises UNICEF, WHO, the United abortions. Estimates of adolescent fertility rates are based on Nations Population Division, the World Bank, and other universities vital registration systems or, in their absence, censuses or sample Economy States and markets Global links Back World Development Indicators 2014 35 2 People surveys and are generally considered reliable measures of fertility primary completion rate may exceed 100 percent. The numerator in the recent past. Where no empirical information on age-speciic may include late entrants and overage children who have repeated fertility rates is available, a model is used to estimate the share one or more grades of primary education as well as children who of births to adolescents. For countries without vital registration entered school early, while the denominator is the number of chil- systems fertility rates are generally based on extrapolations from dren at the entrance age for the last grade of primary education. trends observed in censuses or surveys from earlier years. Youth literacy Prevalence of HIV The youth literacy rate for ages 15–24 is a standard measure of HIV prevalence rates relect the rate of HIV infection in each coun- recent progress in student achievement. It relects 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 dificult 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 deinitions estimating the data and better coordination with countries have and methods of data collection differ across countries, data should resulted in improved estimates. The models, which are routinely be used cautiously. Generally, literacy encompasses numeracy, the updated, track the course of HIV epidemics and their impacts, mak- ability to make simple arithmetic calculations. ing full use of information on HIV prevalence trends from surveil- Data on youth literacy are compiled by the United Nations Educa- lance data as well as survey data. The models take into account tional, Scientiic and Cultural Organization (UNESCO) Institute for reduced infectivity among people receiving antiretroviral therapy Statistics based on national censuses and household surveys dur- (which is having a larger impact on HIV prevalence and allowing HIV- ing 1985–2012 and, for countries without recent literacy data, using positive people to live longer) and allow for changes in urbanization the Global Age-Speciic Literacy Projection Model. over time in generalized epidemics (important because prevalence is higher in urban areas and because many countries have seen rapid Labor force participation urbanization over the past two decades). The estimates include The labor force is the supply of labor available for producing goods plausibility bounds, available at http://data.worldbank.org, which and services in an economy. It includes people who are currently relect the certainty associated with each of the estimates. employed, people who are unemployed but seeking work, and irsttime job-seekers. Not everyone who works is included, however. 36 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 eficiency 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 relects 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 relects the primary cycle as deined by the Interna- little scope to probe. Establishment censuses and surveys provide tional Standard Classiication 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 i ve or six years (in most countries) and seven (in a (ILO, Key Indicators of the Labour Market 2001–2002). small number of countries). It is a proxy that should be taken as an Besides the data sources, there are other important factors that upper estimate of the actual primary completion rate, since data affect data comparability, such as census or survey reference period, limitations preclude adjusting for students who drop out during the deinition of working age, and geographic coverage. For country-level inal year of primary education. There are many reasons why the information on source, reference period, or deinition, consult the World Development Indicators 2014 Front ? User guide World view People Environment People 2 footnotes in the World Development Indicators database or the ILO’s suitable or desirable jobs. But high and sustained unemployment Key Indicators of the Labour Market, 8th edition, database. indicates serious ineficiencies in resource allocation. The labor force participation rates in the table are modeled esti- The criteria for people considered to be seeking work, and the mates from the ILO’s Key Indicators of the Labour Market, 8th edition, treatment of people temporarily laid off or seeking work for the database. These harmonized estimates use strict data selection crite- irst time, vary across countries. In many developing countries it ria and enhanced methods to ensure comparability across countries is especially dificult to measure employment and unemployment and over time to avoid the inconsistencies mentioned above. Esti- in agriculture. The timing of a survey can maximize the effects of mates are based mainly on labor force surveys, with other sources seasonal unemployment in agriculture. And informal sector employ- (population censuses and nationally reported estimates) used only ment is dificult to quantify where informal activities are not tracked. when no survey data are available. National estimates of labor force Data on unemployment are drawn from labor force sample surveys participation rates are available in the World Development Indicators and general household sample surveys, censuses, and oficial esti- online database. Because other employment data are mostly national mates. Administrative records, such as social insurance statistics estimates, caution should be used when comparing the modeled and employment ofice statistics, are not included because of their labor force participation rate and other employment data. limitations in coverage. Vulnerable employment ous reasons. Women suffer more from discrimination and from struc- The proportion of unpaid family workers and own-account workers in tural, social, and cultural barriers that impede them from seeking work. total employment is derived from information on status in employ- Also, women are often responsible for the care of children and the ment. Each group faces different economic risks, and unpaid fam- elderly and for household affairs. They may not be available for work ily workers and own-account workers are the most vulnerable—and during the short reference period, as they need to make arrangements therefore the most likely to fall into poverty. They are the least likely before starting work. Further, women are considered to be employed to have formal work arrangements, are the least likely to have social when they are working part-time or in temporary jobs, despite the insta- protection and safety nets to guard against economic shocks, and are bility of these jobs or their active search for more secure employment. Women tend to be excluded from the unemployment count for vari- often incapable of generating enough savings to offset these shocks. A high proportion of unpaid family workers in a country indicates Female legislators, senior officials, and managers weak development, little job growth, and often a large rural economy. Despite much progress in recent decades, gender inequalities remain Data on vulnerable employment are drawn from labor force and pervasive in many dimensions of life. But while gender inequalities general household sample surveys, censuses, and oficial estimates. exist throughout the world, they are most prevalent in developing Besides the limitation mentioned for calculating labor force participa- countries. Inequalities in the allocation of education, health care, tion rates, there are other reasons to limit comparability. For exam- nutrition, and political voice matter because of their strong associa- ple, information provided by the Organisation for Economic Co-oper- tion with well-being, productivity, and economic growth. These pat- ation and Development relates only to civilian employment, which terns of inequality begin at an early age, with boys usually receiving a can result in an underestimation of “employees” and “workers not larger share of education and health spending than girls, for example. classiied by status,” especially in countries with large armed forces. The share of women in high-skilled occupations such as legislators, While the categories of unpaid family workers and own-account work- senior oficials, and managers indicates women’s status and role ers would not be affected, their relative shares would be. in the labor force and society at large. Women are vastly underrepresented in decisionmaking positions in government, although Unemployment there is some evidence of recent improvement. The ILO deines the unemployed as members of the economically Data on female legislators, senior oficials, and managers are active population who are without work but available for and seek- based on the employment by occupation estimates, classii ed ing work, including people who have lost their jobs or who have according to the International Standard Classiication of Occupa- voluntarily left work. Some unemployment is unavoidable. At any tions 1988. Data are drawn mostly from labor force surveys, supple- time some workers are temporarily unemployed—between jobs as mented in limited cases with other household surveys, population employers look for the right workers and workers search for better censuses, and oficial estimates. Countries could apply different jobs. Such unemployment, often called frictional unemployment, practice whether or where the armed forces are included. Armed results from the normal operation of labor markets. forces constitute a separate major group, but in some countries they Changes in unemployment over time may relect changes in the are included in the most closely matching civilian occupation or in demand for and supply of labor, but they may also relect changes nonclassiiable workers. For country-level information on classiica- in reporting practices. In countries without unemployment or welfare tion, source, reference period, or deinition, consult the footnotes in beneits people eke out a living in vulnerable employment. In coun- the World Development Indicators database or the ILO’s Key Indica- tries with well-developed safety nets workers can afford to wait for tors of the Labour Market, 8th edition, database. Economy States and markets Global links Back World Development Indicators 2014 37 2 People Definitions Data sources • Prevalence of child malnutrition, underweight, is the percent- Data on child malnutrition prevalence are from WHO’s Global Data- age of children under age 5 whose weight for age is more than two base on Child Growth and Malnutrition (www.who.int/nutgrowthdb). standard deviations below the median for the international reference Data on under-i ve mortality rates are from the UN Inter- agency population ages 0–59 months. Data are based on the WHO child Group for Child Mortality Estimation (www.childmortality.org) and growth standards released in 2006. • Under-five mortality rate is are based mainly on household surveys, censuses, and vital reg- the probability of a child born in a speciic year dying before reaching istration data. Modeled estimates of maternal mortality ratios are age 5, if subject to the age-speciic mortality rates of that year. The from the UN Maternal Mortality Estimation Inter- agency Group (www probability is expressed as a rate per 1,000 live births. • Maternal .maternalmortalitydata.org). Data on adolescent fertility rates are mortality ratio, modeled estimate, is the number of women who from United Nations Population Division (2013), with annual data die from pregnancy-related causes while pregnant or within 42 days linearly interpolated by the World Bank’s Development Data Group. of pregnancy termination, per 100,000 live births. • Adolescent Data on HIV prevalence are from UNAIDS (2013). Data on primary fertility rate is the number of births per 1,000 women ages 15–19. completion rates and literacy rates are from the UNESCO Institute • Prevalence of HIV is the percentage of people who are infected for Statistics (www.uis.unesco.org). Data on labor force participation with HIV in the relevant age group. • Primary completion rate is rates, vulnerable employment, unemployment, and female legisla- the number of new entrants (enrollments minus repeaters) in the tors, senior oficials, and managers are from the ILO’s Key Indicators last grade of primary education, regardless of age, divided by the of the Labour Market, 8th edition, database. population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out References during the inal year of primary education. • Youth literacy rate is ILO (International Labour Organization).Various years. Key Indicators of the percentage of the population ages 15–24 that can, with understanding, both read and write a short simple statement about their the Labour Market. Geneva: International Labour Ofice. UNAIDS (Joint United Nations Programme on HIV/AIDS). 2013. Global everyday life. • Labor force participation rate is the proportion of Report: UNAIDS Report on the Global AIDS Epidemic 2013. Geneva. the population ages 15 and older that engages actively in the labor UNICEF (United Nations Children’s Fund), WHO (World Health Orga- market, by either working or looking for work during a reference nization), and the World Bank. 2013. 2012 Joint Child Malnutrition period. Data are modeled ILO estimates. • Vulnerable employment Estimates - Levels and Trends. New York: UNICEF. [www.who.int is unpaid family workers and own-account workers as a percentage of total employment. • Unemployment is the share of the labor force without work but available for and seeking employment. Deinitions /nutgrowthdb/estimates2012/en/]. UN Inter-agency Group for Child Mortality Estimation. 2013. Levels and Trends in Child Mortality: Report 2013. New York. of labor force and unemployment may differ by country. • Female United Nations Population Division. 2013. World Population Prospects: legislators, senior officials, and managers are the percentage of The 2012 Revision. New York: United Nations, Department of Eco- legislators, senior oficials, and managers (International Standard Classiication of Occupations–88 category 1) who are female. 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. 2011. World Development Report 2012: Gender Equality and Development. Washington, DC. ———. n.d. PovcalNet online database. [http://iresearch.worldbank .org/PovcalNet]. Washington, DC. 38 World Development Indicators 2014 Front ? User guide World view People Environment People 2 Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/2.1). To view a speciic /indicator/SP.POP.TOTL). 2.1 Population dynamics Population SP.POP.TOTL Population growth SP.POP.GROW Population ages 0–14 SP.POP.0014.TO.ZS Population ages 15–64 SP.POP.1564.TO.ZS Population ages 65+ SP.POP.65UP.TO.ZS Dependency ratio, Young SP.POP.DPND.YG Dependency ratio, Old SP.POP.DPND.OL Crude death rate SP.DYN.CDRT.IN Crude birth rate SP.DYN.CBRT.IN Unemployment by educational attainment, Secondary SL.UEM.SECO.ZS Unemployment by educational attainment, Tertiary SL.UEM.TERT.ZS 2.6 Children at work Children in employment, Total SL.TLF.0714.ZS Children in employment, Male SL.TLF.0714.MA.ZS Children in employment, Female SL.TLF.0714.FE.ZS Work only SL.TLF.0714.WK.ZS 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 Employment in manufacturing SL.MNF.0714.ZS Employment in services SL.SRV.0714.ZS SL.TLF.CACT.MA.ZS Labor force participation rate, Female Labor force, Total SL.TLF.CACT.FE.ZS SL.TLF.TOTL.IN Self-employed SL.SLF.0714.ZS ..a,b Wage workers SL.WAG.0714.ZS Unpaid family workers SL.FAM.0714.ZS Labor force, Average annual growth Labor force, Female SL.TLF.TOTL.FE.ZS 2.3 Employment by sector 2.7 Poverty rates at national poverty lines Agriculture, Male Agriculture, Female Industry, Male Industry, Female Services, Male SL.AGR.EMPL.MA.ZS Poverty headcount ratio, Rural SI.POV.RUHC SL.AGR.EMPL.FE.ZS Poverty headcount ratio, Urban SI.POV.URHC SL.IND.EMPL.MA.ZS Poverty headcount ratio, National SI.POV.NAHC SL.IND.EMPL.FE.ZS Poverty gap, Rural SI.POV.RUGP SL.SRV.EMPL.MA.ZS Poverty gap, Urban SI.POV.URGP Poverty gap, National SI.POV.NAGP SL.SRV.EMPL.FE.ZS Services, Female 2.4 Decent work and productive employment Employment to population ratio, Total SL.EMP.TOTL.SP.ZS Employment to population ratio, Youth SL.EMP.1524.SP.ZS SL.EMP.VULN.MA.ZS Vulnerable employment, Male Vulnerable employment, Female SL.EMP.VULN.FE.ZS GDP per person employed SL.GDP.PCAP.EM.KD 2.8 Poverty rates at international poverty lines Population living below 2005 PPP $1.25 a day SI.POV.DDAY Poverty gap at 2005 PPP $1.25 a day SI.POV.2DAY Population living below 2005 PPP $2 a day SI.POV.GAPS Poverty gap at 2005 PPP $2 a day SI.POV.GAP2 2.9 Distribution of income or consumption 2.5 Unemployment Gini index Unemployment, Male SL.UEM.TOTL.MA.ZS SL.UEM.TOTL.FE.ZS Unemployment, Female SL.UEM.1524.MA.ZS Youth unemployment, Male SL.UEM.1524.FE.ZS Youth unemployment, Female Long-term unemployment, Total SL.UEM.LTRM.ZS Long-term unemployment, Male SL.UEM.LTRM.MA.ZS SL.UEM.LTRM.FE.ZS Long-term unemployment, Female Unemployment by educational attainment, Primary Economy SL.UEM.PRIM.ZS States and markets SI.POV.GINI Share of consumption or income, Lowest 10% of population SI.DST.FRST.10 Share of consumption or income, Lowest 20% of population SI.DST.FRST.20 Share of consumption or income, Second 20% of population SI.DST.02ND.20 Share of consumption or income, Third 20% of population SI.DST.03RD.20 Share of consumption or income, Fourth 20% of population SI.DST.04TH.20 Global links Back World Development Indicators 2014 39 2 People Share of consumption or income, Highest 20% of population SI.DST.05TH.20 Share of consumption or income, Highest 10% of population SI.DST.10TH.10 Primary completion rate, Female SE.ADT.1524.LT.MA.ZS Youth literacy rate, Female SE.ADT.1524.LT.FE.ZS SE.ADT.LITR.MA.ZS Adult literacy rate, Male 2.10 Education inputs SE.XPD.PRIM.PC.ZS Public expenditure per student, Secondary SE.XPD.SECO.PC.ZS Public expenditure per student, Tertiary SE.XPD.TERT.PC.ZS Public expenditure on education, % of GDP SE.XPD.TOTL.GD.ZS Public expenditure on education, % of total government expenditure SE.XPD.TOTL.GB.ZS Primary school pupil-teacher ratio 2.14 Education gaps by income and gender This table provides education survey data for the poorest and richest quintiles. SE.PRM.TCAQ.ZS SE.PRM.ENRL.TC.ZS Total health expenditure SH.XPD.TOTL.ZS Public health expenditure SH.XPD.PUBL Out-of-pocket health expenditure External resources for health 2.11 Participation in education Gross enrollment ratio, Preprimary SE.PRE.ENRR Gross enrollment ratio, Primary SE.PRM.ENRR Gross enrollment ratio, Secondary SE.SEC.ENRR SE.TER.ENRR Gross enrollment ratio, Tertiary Net enrollment rate, Primary SE.PRM.NENR Net enrollment rate, Secondary SE.SEC.NENR Adjusted net enrollment rate, Primary, Male SE.PRM.TENR.MA Adjusted net enrollment rate, Primary, Female SE.PRM.TENR.FE SE.PRM.UNER.MA Primary school-age children out of school, Female Health expenditure per capita, PPP $ Physicians SH.MED.PHYS.ZS SH.MED.NUMW.P3 Community health workers SH.MED.CMHW.P3 Hospital beds SH.MED.BEDS.ZS Completeness of birth registration SE.PRM.GINT.MA.ZS Gross intake ratio in irst grade of primary education, Female Cohort survival rate, Reaching grade 5, Male Cohort survival rate, Reaching grade 5, Female SE.PRM.GINT.FE.ZS SE.PRM.PRS5.MA.ZS SE.PRM.PRS5.FE.ZS Cohort survival rate, Reaching last grade of SE.PRM.PRSL.MA.ZS primary education, Male SP.REG.BRTH.ZS 2.16 Disease prevention coverage and quality Access to improved sanitation facilities Child immunization rate, DTP3 Children with acute respiratory infection taken to health provider 2.12 Education efficiency SH.XPD.PCAP SH.XPD.PCAP.PP.KD Nurses and midwives Child immunization rate, Measles SE.PRM.UNER.FE SH.XPD.OOPC.TO.ZS SH.XPD.EXTR.ZS Health expenditure per capita, $ Access to an improved water source Primary school-age children out of school, Male Gross intake ratio in irst grade of primary education, Male ..b 2.15 Health systems Trained teachers in primary education SH.H2O.SAFE.ZS SH.STA.ACSN SH.IMM.MEAS SH.IMM.IDPT SH.STA.ARIC.ZS Children with diarrhea who received oral rehydration and continuous feeding SH.STA.ORCF.ZS Children sleeping under treated bed nets SH.MLR.NETS.ZS Children with fever receiving antimalarial drugs SH.MLR.TRET.ZS Tuberculosis treatment success rate SH.TBS.CURE.ZS Tuberculosis case detection rate SH.TBS.DTEC.ZS 2.17 Reproductive health Total fertility rate SP.DYN.TFRT.IN Cohort survival rate, Reaching last grade of primary education, Female SE.PRM.PRSL.FE.ZS Adolescent fertility rate SP.ADO.TFRT Repeaters in primary education, Male SE.PRM.REPT.MA.ZS Unmet need for contraception SP.UWT.TFRT Repeaters in primary education, Female SE.PRM.REPT.FE.ZS Contraceptive prevalence rate SP.DYN.CONU.ZS Transition rate to secondary education, Male SE.SEC.PROG.MA.ZS Pregnant women receiving prenatal care SH.STA.ANVC.ZS Births attended by skilled health staff Transition rate to secondary education, Female SE.SEC.PROG.FE.ZS 2.13 Education completion and outcomes 40 SE.ADT.LITR.FE.ZS Adult literacy rate, Female Public expenditure per student, Primary SE.PRM.CMPT.FE.ZS Youth literacy rate, Male Primary completion rate, Total SE.PRM.CMPT.ZS Primary completion rate, Male SE.PRM.CMPT.MA.ZS World Development Indicators 2014 Front ? User guide SH.STA.BRTC.ZS Maternal mortality ratio, National estimate SH.STA.MMRT.NE Maternal mortality ratio, Modeled estimate SH.STA.MMRT Lifetime risk of maternal mortality SH.MMR.RISK World view People Environment People 2 2.18 Nutrition and growth Prevalence of HIV, Total Prevalence of undernourishment SN.ITK.DEFC.ZS Prevalence of underweight, Male SH.STA.MALN.MA.ZS SH.DYN.AIDS.ZS Women’s share of population ages 15+ living with HIV SH.DYN.AIDS.FE.ZS SH.HIV.1524.MA.ZS Prevalence of underweight, Female SH.STA.MALN.FE.ZS Prevalence of HIV, Youth male Prevalence of stunting, Male SH.STA.STNT.MA.ZS Prevalence of HIV, Youth female SH.STA.STNT.FE.ZS Antiretroviral therapy coverage Prevalence of stunting, Female SH.STA.WAST.MA.ZS Prevalence of wasting, Male SH.STA.WAST.FE.ZS Prevalence of wasting, Female SH.SVR.WAST.MA.ZS Prevalence of severe wasting, Male SH.SVR.WAST.FE.ZS Prevalence of severe wasting, Female Prevalence of overweight children, Male SH.STA.OWGH.MA.ZS Prevalence of overweight children, Female SH.STA.OWGH.FE.ZS 2.19 Nutrition intake and supplements Low-birthweight babies SH.STA.BRTW.ZS Exclusive breastfeeding SH.STA.BFED.ZS Consumption of iodized salt SN.ITK.SALT.ZS Vitamin A supplementation SN.ITK.VITA.ZS Prevalence of anemia among children under age 5 Prevalence of anemia among pregnant women SH.ANM.CHLD.ZS SH.PRG.ANEM 2.20 Health risk factors and future challenges Prevalence of smoking, Male Prevalence of smoking, Female Incidence of tuberculosis Prevalence of diabetes Economy SH.HIV.1524.FE.ZS SH.HIV.ARTC.ZS Death from communicable diseases and maternal, prenatal, and nutrition conditions SH.DTH.COMM.ZS Death from non-communicable diseases SH.DTH.NCOM.ZS Death from injuries SH.DTH.INJR.ZS 2.21 Mortality Life expectancy at birth SP.DYN.LE00.IN Neonatal mortality rate SH.DYN.NMRT Infant mortality rate SP.DYN.IMRT.IN Under-ive mortality rate, Total SH.DYN.MORT Under-ive mortality rate, Male SH.DYN.MORT.MA Under-ive mortality rate, Female SH.DYN.MORT.FE Adult mortality rate, Male SP.DYN.AMRT.MA SP.DYN.AMRT.FE Adult mortality rate, Female 2.22 Health gaps by income This table provides health survey data for the poorest and richest quintiles. ..b SH.PRV.SMOK.MA SH.PRV.SMOK.FE SH.TBS.INCD SH.STA.DIAB.ZS States and markets Data disaggregated by sex are available in the World Development Indicators database. 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. Global links Back World Development Indicators 2014 41 ENVIRONMENT 42 World Development Indicators 2014 Front ? User guide World view People Environment A healthy environment is integral to meeting the Millennium Development Goals, which call for reversing environmental losses and inserting principles of environmental sustainability into country policies and programs. Whether the world sustains itself depends largely on properly managing natural resources. The indicators in the Environment section measure resource use and the way human activities affect the natural and built environment. They include measures of environmental goods (forest, water, cultivable land) and of degradation (pollution, deforestation, loss of habitat, and loss of biodiversity). They show that growing populations and expanding economies have placed greater demands on land, water, forest, minerals, and energy sources. But better policies, rising productivity, and new technologies can ensure that future development is environmentally and socially sustainable. Economic growth and greater energy use are positively correlated—access to electricity and the use of energy are essential in raising people’s standard of living. Economic development has improved the quality of life for many people, yielding gains unparalleled in human history. But the gains have been uneven, and economic growth has often had negative environmental consequences, with a drastic impact on poor people. Generating energy from fossil fuels produces emissions of carbon dioxide, the main greenhouse gas contributing to climate change. The World Bank Group has joined the UN Sustainable Energy for All, which calls on Economy States and markets governments, businesses, and civil societies to achieve three goals by 2030. First is universal access to electricity and clean cooking fuels. Second is doubling the share of the world’s energy supply from renewable sources. And third is doubling the rate of improvement in energy eficiency. Several indicators in the Environment section cover energy use and eficiency, electricity use and production, greenhouse gas emissions, carbon dioxide emissions by economic sector, and access to electricity. Other indicators describe land use, agriculture and food production, forests and biodiversity, threatened species, water resources, climate variability, exposure to impact, resilience, urbanization, trafic and congestion, air pollution, and natural resources rents. Where possible, the indicators come from international sources and have been standardized to facilitate comparisons across countries. But ecosystems span national boundaries, and access to natural resources may vary within countries. For example, water may be abundant in some parts of a country but scarce in others, and countries often share water resources. Land productivity and optimal land use may be location-speciic, but widely separated regions can have common characteristics. Greenhouse gas emissions and climate change are measured globally, but their effects are experienced locally, shaping people’s lives and livelihoods. Measuring environmental phenomena and their effects at the subnational, national, and supranational levels thus remains a major challenge. Global links Back 3 World Development Indicators 2014 43 Highlights Agricultural land use increases while industry’s share of GDP declines The share of agriculture in GDP is declining in all regions and income Land under cereal production (million hectares) groups. Between 2000 and 2012 it fell 20 percentage points globally. 200 Even in low-income countries the share fell 6 percentage points, from 34 percent to 28 percent, as most economies gradually shifted to 150 industry and services. Over the last decade, apart from developing countries in Europe and Central Asia, low- and middle-income countries in general are increasing land under cereal production. Both East Asia 100 and Paciic and Sub- Saharan Africa saw land under cereal production increase more than 15 percent. Since most of the land available for 50 2000 2012 current and future food requirements is already in production, further 0 Europe Sub-Saharan South Middle East Latin Africa Asia & North America & & Central Asia Africa Caribbean East Asia & Pacific expansion will likely involve fragile and marginal land—a strategy that cannot be sustained for long. High income Source: Online table 3.2. Forest shrinking but protected areas increasing Terrestrial and marine protected areas (% of total territorial area) At the beginning of the 20th century the Earth’s forest area was about 5 billion hectares. That has since shrunk to about 4 billion hectares, 25 with the decline concentrated in developing countries. Low- and middle- income countries lost 14.6 million hectares of forest a year 20 between 1990 and 2011. Latin America and the Caribbean—with the largest share of forest areas at about a quarter of the earth’s forest 15 resources—lost some 99 million hectares, about 11 percent of its total forest area. But high-income economies have gained about 10 17.7 million hectares of forest area since 1990. Many countries designate protected areas to preserve valuable habitat and the plant and 1990 2012 5 0 East Middle East South Asia Asia & & North Africa Pacific SubLatin America & Saharan Caribbean Africa Europe High & Central income Asia animal species that live there. And by 2012 more than 14 percent of the world’s land area and its oceans had been protected. World Source: Table 3 and online table 1.3. High-income countries use more energy, but growth is faster in developing countries Economic growth and energy use move together, and energy producers Global energy use, 2011 (%) tend to be energy users. With only 18 percent of the world’s population, high-income economies use about half the world’s energy production each year—more than 4 times more energy per person than United States 17% Rest of the world 23% middle-income economies and almost 14 times more than low-income Japan 4% economies. But low- and middle-income economies more than doubled their energy consumption and production over 1990–2011, as high- Russian Federation 6% income countries increased consumption 16 percent and production Other high-income 23% India 6% 21 percent. The average growth in energy use over 1990–2011 was 2 percent globally—3.6 percent for developing countries and 0.9 percent for high-income economies. China 21% Source: Online table 3.6. 44 World Development Indicators 2014 Front ? User guide World view People Environment Per capita carbon dioxide emissions are not highest in countries with the highest total emissions Global per capita carbon dioxide emissions rose 16 percent between Per capita carbon dioxide emissions (metric tons per capita) 1990 and 2010 to a record 4.9 metric tons. The countries with the 40 highest per capita emissions are not among the countries with the highest total emissions. In 2010 the top i ve per capita emitters 30 were Qatar, Trinidad and Tobago, Kuwait, Brunei Darussalam, and Aruba, all high-income countries, whereas the top i ve total emitters were China, the United States, India, the Russian Federation, and 20 Japan. Europe and Central Asia had the highest per capita emissions among developing country regions (5.3 metric tons), followed by East 1990 per capita carbon dioxide emissions fall 2.5 percent between 1990 and 2010, to 11.6 metric tons, they remain the world’s highest per 2010 10 Asia and Pacii c (4.9 metric tons). While high-income countries saw 0 Qatar capita emitters. Trinidad and Tobago Kuwait Brunei Darussalam Aruba World Source: Online table 3.8. Sub-Saharan Africa’s fast-growing urban population Home to more than half the world’s people, urban areas will accom- Urban and rural population, 2012 (% of total population) modate almost all population growth over the next four decades. The 100 Rural pace will be fastest in developing countries, where the urban population is forecast to rise from 2.7 billion in 2012 to 5.2 billion in 2050. 75 At 4 percent a year between 1990 and 2012, Sub- Saharan Africa had the fastest pace of urban growth rate of all developing regions. Urbanization can yield important social beneits, such as improving 50 people’s access to public services. In Sub- Saharan Africa 83 percent of the urban population has access to an improved water source, com25 Urban pared with 51 percent of the rural population. And access to improved sanitation facilities in urban areas is almost twice that in rural areas. But urbanization can also have adverse environmental effects, con- 0 Europe Middle East East Latin America & & Central & North Asia & Pacific Africa Caribbean Asia centrating pollution, harming health, and reducing productivity. SubSaharan Africa South Asia High income World Source: Online table 3.12. Developing countries join the WAVES partnership The Wealth Accounting and the Valuation of Ecosystem Services (WAVES) is a global partnership that promotes sustainable develop- Botswana’s sector shares of water use, formal employment, and GDP, 2011–12 (%) Water consumption Formal employment GDP 50 ment by mainstreaming natural resources in development planning and national economic accounts. Water accounts, a subset of natural capital accounts, collect data on water stocks and lows and water rights and use. They provide a conceptual framework for organizing 40 30 20 water resources data for use in resource allocation policies at the gascar, and the Philippines joined WAVES in 2012. Using the System of Environmental-Economic Accounting methodology approved by the UN Statistics Commission, Botswana updated its water accounts from the 1990s using natural capital accounting. In addition to water accounts, Botswana’s natural capital accounts will include land and ecosystem accounts, with a focus on tourism, minerals, and energy. 10 0 Ag ric ult Ho ure us eh old us e Mi nin So cia g Go l& ve rnm pe rso en t na ls Ins er ura v ice Ma nc s e, nu ba fac nk tur ing i n g ,& bu sin es s Ho tel Tra s& de res tau Tra ran ns ts Co po ns rt tru & c co mm tion un ica tio n national and regional levels. Botswana, Colombia, Costa Rica, Mada- Source: Wealth Accounting and the Valuation of Ecosystem Services and Botswana Department of Water Affairs. Economy States and markets Global links Back World Development Indicators 2014 45 3 Environment Deforestationa Nationally protected areas Albania marine areas % of total Per capita territorial area cubic meters % of total population % of total population Access to Urban Particulate Carbon improved population matter dioxide sanitation concentration emissions facilities urban-population- Energy use Electricity production million metric tons Per capita kilograms of oil equivalent billion kilowatt hours % growth 2000–10 2012 2011 2012 2012 2011–12 2011 0.00 0.4 1,620 64 29 3.7 63 2010 8.2 2011 .. 2011 .. –0.10 9.5 8,529 96 91 2.2 43 4.3 689 4.2 51.2 Algeria 0.57 7.4 298 84 95 3.0 34 123.5 1,108 American Samoa 0.19 16.8 .. 100 62 0.0 .. .. .. .. Andorra 0.00 9.8 4,053 100 100 0.0 31 0.5 .. .. Angola 0.21 12.1 7,334 54 60 4.4 21 30.4 673 5.7 Antigua and Barbuda 0.20 1.2 590 98 91 1.0 9 0.5 .. .. Argentina 0.81 6.6 6,777 99 97 1.0 35 180.5 1,967 129.6 Armenia 1.48 8.1 2,314 100 91 0.2 13 4.2 916 7.4 Aruba 0.00 0.0 .. 98 98 0.6 .. 2.3 .. .. Australia 0.37 15.0 22,023 100 100 1.9 14 373.1 5,501 252.6 Austria –0.13 23.6 6,543 100 100 0.6 28 66.9 3,928 62.2 Azerbaijan 0.00 7.4 885 80 82 1.8 20 45.7 1,369 20.3 Bahamas, The 0.00 1.0 55 98 92 1.8 .. 2.5 .. .. –3.55 6.8 3 100 99 2.0 24 24.2 7,353 13.8 Bangladesh 0.18 4.2 687 85 57 2.9 121 56.2 205 44.1 Barbados 0.00 0.1 284 100 .. 1.6 11 1.5 .. .. Belarus –0.43 8.3 3,927 100 94 0.4 20 62.2 3,114 32.2 Belgium 89.0 Bahrain –0.16 24.5 1,086 100 100 0.8 29 108.9 5,349 Belize 0.67 26.4 50,588 99 91 2.0 18 0.4 .. .. Benin 1.04 25.5 1,053 76 14 4.2 69 5.2 385 0.2 .. Bermuda 0.00 5.1 .. .. .. 0.4 .. 0.5 .. Bhutan –0.34 28.4 106,933 98 47 3.8 16 0.5 .. .. Bolivia 0.50 20.8 29,396 88 46 2.3 78 15.5 746 7.2 Bosnia and Herzegovina 0.00 1.5 9,246 100 95 1.0 84 31.1 1,848 15.3 Botswana 0.99 37.2 1,208 97 64 1.9 199 5.2 1,115 0.4 Brazil 0.50 26.0 27,512 98 81 1.2 36 419.8 1,371 531.8 Brunei Darussalam 0.44 29.6 20,910 .. .. 1.9 9 9.2 9,427 3.7 –1.53 35.4 2,858 99 100 0.2 41 44.7 2,615 50.0 Burkina Faso 1.01 15.2 781 82 19 6.0 51 1.7 .. .. Burundi 1.40 4.9 1,054 75 47 5.8 30 0.3 .. .. –0.36 0.2 612 89 65 2.0 .. 0.4 .. .. Cambodia 1.34 23.8 8,257 71 37 2.7 89 4.2 365 1.1 Cameroon 1.05 10.9 12,904 74 45 3.6 26 7.2 318 6.0 Canada 0.00 7.0 82,987 100 100 1.3 14 499.1 7,333 636.9 Cayman Islands 0.00 1.5 .. 96 96 1.7 .. 0.6 .. .. Central African Republic 0.13 18.0 31,784 68 22 2.6 32 0.3 .. .. Chad 0.66 16.6 1,242 51 12 3.4 50 0.5 .. .. .. 0.5 .. .. .. 1.0 .. .. .. .. Chile –0.25 15.0 51,073 99 99 1.1 60 72.3 1,940 65.7 China Bulgaria Cabo Verde Channel Islands –1.57 16.1 2,093 92 65 3.0 82 8,286.9 2,029 4,715.7 Hong Kong SAR, China .. 41.9 .. .. .. 1.2 30 36.3 2,106 39.0 Macao SAR, China .. .. .. .. .. 1.9 33 1.0 .. .. 0.17 20.8 44,861 91 80 1.7 53 75.7 671 61.8 Colombia 46 Access to improved water source weighted PM10 micrograms per cubic meter average annual % Afghanistan Internal renewable freshwater b Terrestrial and resources Comoros 9.34 4.0 1,714 95 35 2.8 21 0.1 .. .. Congo, Dem. Rep. 0.20 12.0 14,078 46 31 4.3 46 3.0 383 7.9 Congo, Rep. 0.07 30.4 52,540 75 15 3.3 29 2.0 393 1.3 World Development Indicators 2014 Front ? User guide World view People Environment Environment 3 Deforestationa Nationally protected areas average annual % Internal renewable freshwater b Terrestrial and resources Access to improved water source marine areas % of total Per capita territorial area cubic meters % of total population % of total population 2012 2012 Energy use Electricity production % growth weighted PM10 micrograms per cubic meter million metric tons Per capita kilograms of oil equivalent billion kilowatt hours 2011–12 2011 2010 2011 2011 2000–10 2012 Costa Rica –0.93 22.6 23,725 97 94 2.1 48 7.8 983 Côte d’Ivoire –0.15 22.2 3,963 80 22 3.7 21 5.8 579 6.1 Croatia –0.19 10.3 8,807 99 98 0.2 30 20.9 1,971 10.7 Cuba –1.66 9.9 3,381 94 93 –0.1 37 38.4 992 17.8 .. .. .. .. .. .. .. .. .. .. Cyprus –0.09 17.1 699 100 100 1.4 42 7.7 2,121 4.9 Czech Republic –0.08 22.4 1,253 100 100 0.1 29 111.8 4,138 86.8 Denmark –1.14 23.6 1,077 100 100 0.5 25 46.3 3,231 35.2 Djibouti 0.00 0.2 354 92 61 1.6 40 0.5 .. .. Dominica 0.58 3.7 .. .. .. 0.6 15 0.1 .. .. Dominican Republic 0.00 20.8 2,069 81 82 2.1 31 21.0 727 13.0 Ecuador 1.81 37.0 28,334 86 83 2.4 32 32.6 849 20.3 Curaçao Egypt, Arab Rep. 2011 Access to Urban Particulate Carbon improved population matter dioxide sanitation concentration emissions facilities urban-population- 9.8 –1.73 11.3 23 99 96 2.0 120 204.8 978 156.6 El Salvador 1.45 8.7 2,837 90 70 1.4 46 6.2 690 5.8 Equatorial Guinea 0.69 15.1 36,313 .. .. 3.2 21 4.7 .. .. Eritrea 0.28 3.8 472 .. .. 5.4 77 0.5 129 0.3 Estonia 0.12 23.2 9,521 99 95 –0.3 17 18.3 4,197 12.9 Ethiopia 1.08 18.4 1,365 52 24 4.1 86 6.5 381 5.2 Faeroe Islands 0.00 1.0 .. .. .. 0.4 21 0.7 .. .. –0.34 6.0 32,895 96 87 1.5 27 1.3 .. .. Finland 0.14 15.2 19,858 100 100 0.6 16 61.8 6,449 73.5 France –0.39 28.7 3,059 100 100 1.1 24 361.3 3,868 556.9 French Polynesia –3.97 0.1 .. 100 97 1.1 .. 0.9 .. .. 0.00 19.1 102,884 92 41 2.7 12 2.6 1,253 1.8 –0.41 4.4 1,729 90 60 4.2 39 0.5 .. .. 0.09 3.7 12,966 99 93 0.4 35 6.2 790 10.2 Germany 0.00 49.0 1,308 100 100 –1.5 24 745.4 3,811 602.4 Ghana 2.08 14.4 1,221 87 14 3.4 82 9.0 425 11.2 Greece –0.81 21.5 5,214 100 99 0.1 35 86.7 2,402 59.2 Greenland 0.00 40.6 .. 100 100 0.2 .. 0.6 .. .. Grenada 0.00 0.3 .. 97 98 1.3 9 0.3 .. .. Guam 0.00 5.3 .. 100 90 1.2 .. .. .. .. Guatemala 1.40 29.8 7,425 94 80 3.4 75 11.1 691 8.1 Guinea 0.54 26.8 20,248 75 19 3.9 37 1.2 .. .. Guinea-Bissau 0.48 27.1 9,851 74 20 3.9 34 0.2 .. .. Guyana 0.00 5.0 304,723 98 84 0.9 17 1.7 .. .. Haiti 0.76 0.1 1,297 62 24 3.8 56 2.1 320 0.7 Fiji Gabon Gambia, The Georgia Honduras 2.06 16.2 12,336 90 80 3.1 84 8.1 609 7.1 Hungary –0.62 23.1 602 100 100 0.2 32 50.6 2,503 36.0 Iceland –4.99 13.3 532,892 100 100 0.6 18 2.0 17,964 17.2 India –0.46 5.0 1,184 93 36 2.4 100 2,008.8 614 1,052.3 Indonesia 0.51 9.1 8,281 85 59 2.7 47 434.0 857 182.4 Iran, Islamic Rep. 0.00 7.0 1,704 96 89 1.5 115 571.6 2,813 239.7 Iraq –0.09 0.4 1,108 85 85 2.5 36 114.7 1,266 54.2 Ireland –1.53 12.8 10,706 100 99 0.7 18 40.0 2,888 27.7 0.00 .. .. .. .. 0.7 .. .. .. .. –0.07 14.7 97 100 100 1.9 47 70.7 2,994 59.6 Isle of Man Israel Economy States and markets Global links Back World Development Indicators 2014 47 3 Environment Deforestationa Nationally protected areas average annual % Italy Jamaica Access to improved water source marine areas % of total Per capita territorial area cubic meters % of total population % of total population % growth weighted PM10 micrograms per cubic meter 2011–12 2011 2010 2011 2011 34 406.3 2,757 300.6 Access to Urban Particulate Carbon improved population matter dioxide sanitation concentration emissions facilities urban-population- 2000–10 2012 2011 2012 2012 –0.90 21.0 3,005 100 .. –1.7 million metric tons Energy use Electricity production Per capita kilograms of oil equivalent billion kilowatt hours 0.11 7.1 3,483 93 80 0.5 41 7.2 1,135 5.1 Japan –0.05 11.0 3,364 100 100 0.4 19 1,170.7 3,610 1,042.7 Jordan 0.00 0.0 110 96 98 2.5 38 20.8 1,143 14.6 Kazakhstan 0.17 3.3 3,887 93 97 1.2 47 248.7 4,717 86.6 Kenya 0.33 11.6 493 62 30 4.4 66 12.4 480 7.8 Kiribati 0.00 20.2 .. 67 40 1.8 .. 0.1 .. .. Korea, Dem. People’s Rep. 2.00 1.7 2,720 98 82 0.8 124 71.6 773 21.6 Korea, Rep. 520.1 0.11 5.3 1,303 98 100 0.8 46 567.6 5,232 Kosovo .. .. .. .. .. .. 48 .. 1,411 5.8 Kuwait –2.57 12.9 – 99 100 4.0 89 93.7 10,408 57.5 Kyrgyz Republic –1.07 6.3 8,873 88 92 1.9 50 6.4 562 15.2 0.49 16.7 29,197 72 65 5.1 46 1.9 .. .. Latvia –0.34 17.6 8,127 98 .. –1.2 39 7.6 2,122 6.1 Lebanon –0.45 0.5 1,095 100 .. 1.1 43 20.4 1,449 16.4 Lesotho –0.47 0.5 2,577 81 30 3.7 42 0.0 .. .. Liberia 0.67 2.4 49,023 75 17 3.5 25 0.8 .. .. Libya 0.00 0.1 115 .. 97 1.1 74 59.0 2,186 27.6 Liechtenstein 0.00 43.1 .. .. .. 0.5 30 .. .. .. –0.68 17.2 5,139 96 94 –1.2 32 13.6 2,406 4.2 0.00 39.7 1,929 100 100 2.7 17 10.8 8,046 2.6 –0.41 7.3 2,567 99 91 0.3 82 10.9 1,484 6.9 Lao PDR Lithuania Luxembourg Macedonia, FYR Madagascar 0.45 4.7 15,545 50 14 4.7 48 2.0 .. .. Malawi 0.97 18.3 1,044 85 10 3.8 49 1.2 .. .. Malaysia 0.54 13.9 20,168 100 96 2.6 47 216.8 2,639 130.1 Maldives 0.00 .. 90 99 99 4.6 21 1.1 .. .. Mali 0.61 6.0 4,162 67 22 4.8 55 0.6 .. .. Malta 0.00 2.2 121 100 100 0.9 41 2.6 2,060 2.2 Marshall Islands 0.00 0.7 .. 95 76 0.5 .. 0.1 .. .. Mauritania 2.66 1.2 108 50 27 3.2 46 2.2 .. .. Mauritius 1.00 0.7 2,139 100 91 0.5 11 4.1 .. .. Mexico 0.30 13.7 3,427 95 85 1.6 46 443.7 1,560 295.8 Micronesia, Fed. Sets. –0.04 0.1 .. 89 57 0.4 .. 0.1 .. .. Moldova –1.77 3.8 281 97 87 1.5 44 4.9 936 5.8 Monaco 0.00 98.4 .. 100 100 0.8 18 .. .. .. Mongolia 0.73 13.8 12,635 85 56 2.8 284 11.5 1,310 4.8 Montenegro 0.00 12.8 .. 98 90 0.4 30 2.6 1,900 2.7 –0.23 19.9 905 84 75 2.1 66 50.6 539 24.9 Mozambique 0.54 16.4 4,080 49 21 3.3 34 2.9 415 16.8 Myanmar 0.93 6.0 19,159 86 77 2.6 67 9.0 268 7.3 Namibia 0.97 42.6 2,778 92 32 3.3 55 3.2 717 1.4 0.70 16.4 7,298 88 37 3.1 110 3.8 383 3.3 –0.14 31.5 659 100 100 0.8 25 182.1 4,638 113.0 Morocco Nepal Netherlands New Caledonia 0.00 30.5 .. 98 100 1.4 29 3.9 .. .. –0.01 21.3 74,230 100 .. 0.7 16 31.6 4,124 44.5 Nicaragua 2.01 32.5 32,125 85 52 2.0 49 4.5 515 3.8 Niger 0.98 16.7 212 52 9 5.2 50 1.4 .. .. New Zealand 48 Internal renewable freshwater b Terrestrial and resources World Development Indicators 2014 Front ? User guide World view People Environment Environment 3 Deforestationa Nationally protected areas Internal renewable freshwater b Terrestrial and resources Access to improved water source marine areas % of total Per capita territorial area cubic meters % of total population % of total population Access to Urban Particulate Carbon improved population matter dioxide sanitation concentration emissions facilities urban-population- Energy use Electricity production % growth weighted PM10 micrograms per cubic meter 2000–10 2012 2011 2012 2012 2011–12 2011 Nigeria 3.67 13.8 1,346 64 28 4.0 149 78.9 721 Northern Mariana Islands 0.53 19.9 .. 98 80 0.3 .. .. .. .. –0.80 12.2 77,124 100 100 1.7 24 57.2 5,681 126.9 average annual % Norway million metric tons Per capita kilograms of oil equivalent billion kilowatt hours 2010 2011 2011 27.0 Oman 0.00 9.3 463 93 97 9.5 32 57.2 8,356 21.9 Pakistan 2.24 10.6 312 91 48 2.6 171 161.4 482 95.3 Palau –0.18 28.2 .. 95 100 1.6 .. 0.2 .. .. Panama 0.36 14.1 39,409 94 73 2.4 49 9.6 1,085 7.9 Papua New Guinea 0.48 1.4 114,217 40 19 2.7 32 3.1 .. .. Paraguay 0.97 6.4 14,301 94 80 2.6 32 5.1 739 57.6 Peru 0.18 18.3 54,567 87 73 1.7 63 57.6 695 39.2 –0.75 5.1 5,039 92 74 2.2 45 81.6 426 69.2 Poland –0.31 34.8 1,391 .. .. –0.1 34 317.3 2,629 163.1 Portugal –0.11 14.7 3,599 100 100 0.5 28 52.4 2,187 51.9 Puerto Rico –1.76 4.6 1,922 .. 99 –0.6 15 .. .. .. 0.00 2.4 29 100 100 7.2 28 70.5 17,419 30.7 Philippines Qatar Romania –0.32 19.2 2,100 .. .. –0.3 35 78.7 1,778 62.0 0.00 11.3 30,169 97 70 0.6 27 1,740.8 5,113 1,053.0 Rwanda –2.38 10.5 852 71 64 4.4 30 0.6 .. .. Samoa 0.00 2.3 .. 99 92 –0.2 .. 0.2 .. .. San Marino 0.00 .. .. .. .. 0.7 20 .. .. .. São Tomé and Príncipe 0.00 0.0 11,901 97 34 3.7 14 0.1 .. .. Saudi Arabia 0.00 29.9 86 97 100 2.1 108 464.5 6,738 250.1 Senegal 0.49 24.2 1,935 74 52 3.6 147 7.1 264 3.0 –0.99 6.3 1,158 99 97 0.1 43 46.0 2,230 38.0 .. Russian Federation Serbia Seychelles 0.00 1.3 .. 96 97 1.7 .. 0.7 .. Sierra Leone 0.69 10.3 27,278 60 13 2.9 29 0.7 .. .. Singapore 0.00 3.4 116 100 100 2.5 25 13.5 6,452 46.0 .. .. .. .. .. .. .. .. .. .. Slovak Republic Sint Maarten –0.06 36.1 2,334 100 100 0.1 30 36.1 3,214 28.3 Slovenia 15.9 –0.16 54.9 9,095 100 100 0.2 31 15.3 3,531 Solomon Islands 0.25 1.1 83,086 81 29 4.3 25 0.2 .. .. Somalia 1.07 0.5 606 31 23 4.1 32 0.6 .. .. South Africa 0.00 6.6 869 95 74 2.0 40 460.1 2,741 259.6 .. .. .. 57 9 5.4 .. .. .. .. –0.68 25.3 2,379 100 100 0.2 27 269.7 2,686 289.0 Sri Lanka 1.12 15.4 2,530 94 92 –2.1 62 12.7 499 11.6 St. Kitts and Nevis 0.00 0.8 453 98 .. 1.4 9 0.2 .. .. St. Lucia –0.07 2.5 .. 94 65 –3.0 11 0.4 .. .. St. Martin 0.00 .. .. .. .. .. .. .. .. .. –0.27 1.2 .. 95 .. 0.8 14 0.2 .. .. Sudan 0.08 7.1 641 55c 24 c 2.5c 62 14.2 355 8.6 Suriname 0.01 15.2 166,113 95 80 1.5 18 2.4 .. .. Swaziland –0.84 3.0 2,178 74 57 1.4 52 1.0 .. .. Sweden –0.30 13.9 18,097 100 100 0.9 20 52.5 5,190 150.3 Switzerland –0.38 26.3 5,106 100 100 1.2 21 38.8 3,207 62.9 Syrian Arab Republic –1.29 0.7 325 90 96 2.7 27 61.9 910 41.1 0.00 4.8 8,120 72 94 2.7 15 2.9 306 16.2 South Sudan Spain St. Vincent & the Grenadines Tajikistan Economy States and markets Global links Back World Development Indicators 2014 49 3 Environment Deforestationa Nationally protected areas Internal renewable freshwater b Terrestrial and resources Access to improved water source marine areas % of total Per capita territorial area cubic meters % of total population % of total population Access to Urban Particulate Carbon improved population matter dioxide sanitation concentration emissions facilities urban-population- Energy use Electricity production % growth weighted PM10 micrograms per cubic meter 2000–10 2012 2011 2012 2012 2011–12 2011 Tanzania 1.13 31.7 1,812 53 12 4.8 62 6.8 448 5.3 Thailand 0.02 16.4 3,372 96 93 1.4 45 295.3 1,790 156.0 Timor-Leste 1.40 6.2 6,986 70 39 4.2 .. 0.2 .. .. Togo 5.13 24.2 1,777 61 11 3.9 34 1.5 427 0.1 average annual % million metric tons Per capita kilograms of oil equivalent billion kilowatt hours 2010 2011 2011 Tonga 0.00 9.5 .. 99 91 0.8 .. 0.2 .. .. Trinidad and Tobago 0.32 10.1 2,881 94 92 2.3 16 50.7 15,691 8.9 Tunisia –1.86 4.8 393 97 90 1.3 79 25.9 890 16.1 Turkey –1.11 2.1 3,107 100 91 2.6 65 298.0 1,539 229.4 Turkmenistan 0.00 3.2 275 71 99 2.0 21 53.1 4,839 17.2 Turks and Caicos Islands 0.00 3.6 .. .. .. 2.6 .. 0.2 .. .. Tuvalu 0.00 0.3 .. 98 83 1.0 .. .. .. .. Uganda 2.56 11.5 1,110 75 34 6.0 29 3.8 .. .. Ukraine –0.21 4.5 1,162 98 94 0.0 47 304.8 2,766 194.9 United Arab Emirates –0.24 15.5 17 100 98 3.4 132 167.6 7,407 99.1 United Kingdom –0.31 23.4 2,292 100 100 0.7 20 493.5 2,973 364.9 United States –0.13 15.1 9,044 99 100 1.0 18 5,433.1 7,032 4,326.6 Uruguay –2.14 2.6 17,438 99 96 0.4 33 6.6 1,309 10.3 Uzbekistan –0.20 3.4 557 87 100 1.6 35 104.4 1,628 52.4 Vanuatu 0.00 0.5 .. 91 58 3.5 23 0.1 .. .. Venezuela, RB 0.60 49.5 24,488 .. .. 1.7 38 201.7 2,380 122.1 99.2 Vietnam –1.65 4.7 4,092 95 75 3.1 69 150.2 697 Virgin Islands (U.S.) 0.80 2.8 .. 100 96 –0.3 .. .. .. .. West Bank and Gaza –0.10 0.6 207 82 94 3.3 .. 2.4 .. .. Yemen, Rep. 0.00 1.1 90 55 53 4.1 78 21.9 312 6.2 Zambia 0.33 37.8 5,882 63 43 4.3 46 2.4 621 11.5 918 80 40 4.0 104 697 8.9 89 w 64 w 2.0 w Zimbabwe 1.88 27.2 0.11 w 14.0 w 6,122 s Low income 0.61 13.5 5,121 69 37 3.7 74 229.3 360 209.7 Middle income 0.13 14.4 4,931 90 60 2.4 75 16,548.5 1,281 9,778.8 2,211.0 World 61 w 9.4 33,615.4d w 1,890 w 22,158.5 w Lower middle income 0.31 11.1 3,144 88 48 2.6 90 3,827.0 687 Upper middle income 0.04 15.8 6,791 93 74 2.3 65 12,721.1 1,893 7,566.7 Low & middle income 0.22 14.2 4,958 87 57 2.5 75 16,777.5 1,179 10,005.1 East Asia & Paciic –0.44 13.7 4,438 91 67 2.9 75 9,570.5 1,671 5,410.8 Europe & Central Asia –0.48 5.2 2,744 95 94 1.3 48 1,416.7 2,078 908.6 Latin America & Carib. 0.46 21.2 21,735 94 81 1.5 43 1,553.7 1,292 1,348.0 Middle East & N. Africa –0.15 5.9 679 90 88 2.2 79 1,277.9 1,376 654.4 South Asia –0.29 5.9 1,217 91 40 2.5 110 2,252.6 555 1,215.8 0.48 16.3 4,391 64 30 3.9 77 703.8 681 445.2 High income Sub-Saharan Africa –0.03 13.8 11,335 99 96 0.7 27 14,901.7 4,872 12,198.4 Euro area –0.31 27.0 2,962 100 100 –0.2 27 2,472.4 3,480 2,292.2 a. Negative values indicate an increase in forest area. b. River lows from other countries are not included because of data unreliability. c. Excludes South Sudan. d. Includes emissions not allocated to speciic countries. 50 World Development Indicators 2014 Front ? User guide World view People Environment Environment 3 About the data Environmental resources are needed to promote growth and poverty in total renewable water resources. Data do not distinguish between reduction, but growth can create new stresses on the environment. seasonal and geographic variations in water availability within coun- Deforestation, loss of biologically diverse habitat, depletion of water tries. Data for small countries and countries in arid and semiarid resources, pollution, urbanization, and ever increasing demand for zones are less reliable than data for larger countries and countries energy production are some of the factors that must be considered with greater rainfall. in shaping development strategies. Water and sanitation Loss of forests A reliable supply of safe drinking water and sanitary disposal of Forests provide habitat for many species and act as carbon sinks. If excreta are two of the most important means of improving human properly managed they also provide a livelihood for people who man- health and protecting the environment. Improved sanitation facilities age and use forest resources. FAO (2010) provides information on prevent human, animal, and insect contact with excreta. forest cover in 2010 and adjusted estimates of forest cover in 1990 Data on access to an improved water source measure the percent- and 2000. Data presented here do not distinguish natural forests age of the population with ready access to water for domestic pur- from plantations, a breakdown the FAO provides only for developing poses, based on surveys and estimates of service users provided countries. Thus, data may underestimate the rate at which natural by governments to the Joint Monitoring Programme of the World forest is disappearing in some countries. Health Organization (WHO) and the United Nations Children’s Fund (UNICEF). The coverage rates are based on information from service Habitat protection and biodiversity users on household use rather than on information from service Deforestation is a major cause of loss of biodiversity, and habitat providers, which may include nonfunctioning systems. Access to conservation is vital for stemming this loss. Conservation efforts drinking water from an improved source does not ensure that the have focused on protecting areas of high biodiversity. The World water is safe or adequate, as these characteristics are not tested Conservation Monitoring Centre (WCMC) and the United Nations at the time of survey. While information on access to an improved Environment Programme (UNEP) compile data on protected areas. water source is widely used, it is extremely subjective; terms such as Differences in deinitions, 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 oficial WHO deinitions are deined 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 scientiic 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 signiicance 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 classiication related to the size nance of biological diversity—as well as terrestrial protected areas or characteristics of settlements. Some deine 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 deinitions, cross-country comparisons should deinition leads to underestimation of protected areas. Due to varia- be made with caution. tions in consistency and methods of collection, data quality is highly variable across countries. Some countries update their information Air pollution more frequently than others, some have more accurate data on Indoor and outdoor air pollution place a major burden on world health. extent of coverage, and many underreport the number or extent of More than half the world’s people rely on dung, wood, crop waste, protected areas. or coal to meet basic energy needs. Cooking and heating with these fuels on open ires or stoves without chimneys lead to indoor air pol- Freshwater resources lution, which is responsible for 1.6 million deaths a year—one every The data on freshwater resources are derived from estimates of 20 seconds. In many urban areas air pollution exposure is the main runoff into rivers and recharge of groundwater. These estimates are environmental threat to health. Long-term exposure to high levels of derived from different sources and refer to different years, so cross- soot and small particles contributes to such health effects as respira- country comparisons should be made with caution. Data are col- tory diseases, lung cancer, and heart disease. Particulate pollution, lected intermittently and may hide substantial year-to-year variations alone or with sulfur dioxide, creates an enormous burden of ill health. Economy States and markets Global links Back World Development Indicators 2014 51 3 Environment Data on particulate matter are estimated average annual concen- urban areas—but also relects climatic, geographic, and economic trations in residential areas away from air pollution “hotspots,” such factors. Energy use has been growing rapidly in low- and middle- as industrial districts and transport corridors. Data are estimates income economies, but high-income economies still use more than of annual ambient concentrations of particulate matter in cities of four times as much energy per capita. more than 100,000 people by the World Bank’s Agriculture and Environmental Services Department. Total energy use refers to the use of primary energy before transformation to other end-use fuels (such as electricity and reined Pollutant concentrations are sensitive to local conditions, and petroleum products). It includes energy from combustible renew- even monitoring sites in the same city may register different levels. ables and waste—solid biomass and animal products, gas and liq- Thus these data should be considered only a general indication of uid from biomass, and industrial and municipal waste. Biomass is air quality, and comparisons should be made with caution. They any plant matter used directly as fuel or converted into fuel, heat, allow for cross-country comparisons of the relative risk of particulate or electricity. Data for combustible renewables and waste are often matter pollution facing urban residents. Major sources of urban based on small surveys or other incomplete information and thus outdoor particulate matter pollution are trafic and industrial emis- give only a broad impression of developments and are not strictly sions, but nonanthropogenic sources such as dust storms may also comparable across countries. The International Energy Agency (IEA) be a substantial contributor for some cities. Country technology and reports include country notes that explain some of these differences pollution controls are important determinants of particulate matter. (see Data sources). All forms of energy—primary energy and primary Current WHO air quality guidelines are annual mean concentrations electricity—are converted into oil equivalents. A notional thermal of 20 micrograms per cubic meter for particulate matter less than eficiency of 33 percent is assumed for converting nuclear electric- 10 microns in diameter. ity into oil equivalents and 100 percent eficiency for converting hydroelectric power. Carbon dioxide emissions Carbon dioxide emissions are the primary source of greenhouse Electricity production gases, which contribute to global warming, threatening human and Use of energy is important in improving people’s standard of living. natural habitats. Fossil fuel combustion and cement manufacturing But electricity generation also can damage the environment. Whether are the primary sources of anthropogenic carbon dioxide emissions, such damage occurs depends largely on how electricity is generated. which the U.S. Department of Energy’s Carbon Dioxide Information For example, burning coal releases twice as much carbon dioxide—a Analysis Center (CDIAC) calculates using data from the United major contributor to global warming—as does burning an equivalent Nations Statistics Division’s World Energy Data Set and the U.S. amount of natural gas. Nuclear energy does not generate carbon Bureau of Mines’s Cement Manufacturing Data Set. Carbon dioxide dioxide emissions, but it produces other dangerous waste products. emissions, often calculated and reported as elemental carbon, were The IEA compiles data and data on energy inputs used to gen- converted to actual carbon dioxide mass by multiplying them by erate electricity. Data for countries that are not members of the 3.667 (the ratio of the mass of carbon to that of carbon dioxide). Organisation for Economic Co-operation and Development (OECD) Although estimates of global carbon dioxide emissions are probably are based on national energy data adjusted to conform to annual accurate within 10 percent (as calculated from global average fuel questionnaires completed by OECD member governments. In addi- chemistry and use), country estimates may have larger error bounds. tion, estimates are sometimes made to complete major aggregates Trends estimated from a consistent time series tend to be more from which key data are missing, and adjustments are made to accurate than individual values. Each year the CDIAC recalculates compensate for differences in deinitions. The IEA makes these the entire time series since 1949, incorporating recent indings and estimates in consultation with national statistical ofices, oil com- corrections. Estimates exclude fuels supplied to ships and aircraft panies, electric utilities, and national energy experts. It occasionally in international transport because of the dificulty of apportioning revises its time series to relect political changes. For example, the the fuels among beneiting countries. IEA has constructed historical energy statistics for countries of the former Soviet Union. In addition, energy statistics for other countries 52 Energy use have undergone continuous changes in coverage or methodology in In developing economies growth in energy use is closely related to recent years as more detailed energy accounts have become avail- growth in the modern sectors—industry, motorized transport, and able. Breaks in series are therefore unavoidable. World Development Indicators 2014 Front ? User guide World view People Environment Environment 3 Definitions Data sources • Deforestation is the permanent conversion of natural forest area Data on deforestation are from FAO (2010) and the FAO’s data to other uses, including agriculture, ranching, settlements, and website. Data on protected areas, derived from the UNEP and infrastructure. Deforested areas do not include areas logged but WCMC online databases, are based on data from national authori- intended for regeneration or areas degraded by fuelwood gathering, ties, national legislation, and international agreements. Data on acid precipitation, or forest ires. • Nationally protected areas are freshwater resources are from the FAO’s AQUASTAT database. terrestrial and marine protected areas as a percentage of total ter- Data on access to water and sanitation are from the WHO/UNICEF ritorial area and include all nationally designated protected areas Joint Monitoring Programme for Water Supply and Sanitation (www with known location and extent. All overlaps between different desig- .wssinfo.org). Data on urban population are from the United Nations nations and categories, buffered points, and polygons are removed, Population Division (2011). Data on particulate matter concentra- and all undated protected areas are dated. • Internal renewable tions are World Bank estimates. Data on carbon dioxide emissions freshwater resources are the average annual lows of rivers and are from CDIAC online databases. Data on energy use and electricity groundwater from rainfall in the country. Natural incoming lows origi- production are from IEA online databases and published in IEA’s nating outside a country’s borders and overlapping water resources annual publications, Energy Statistics of Non-OECD Countries, Energy between surface runoff and groundwater recharge are excluded. Balances of Non-OECD Countries, Energy Statistics of OECD Countries, • Access to an improved water source is the percentage of the and Energy Balances of OECD Countries. population with reasonable access to an adequate amount of water from an improved source, such as piped water into a dwelling, plot, References or yard; public tap or standpipe; tubewell or borehole; protected dug Botswana Department of Water Affairs. n.d. Various reports. [www well or spring; and rainwater collection. Unimproved sources include .water.gov.bw]. Gaborone. unprotected dug wells or springs, carts with small tank or drum, CDIAC (Carbon Dioxide Information Analysis Center). n.d. Online data- bottled water, and tanker trucks. • Access to improved sanitation base. [http://cdiac.ornl.gov/home.html]. Oak Ridge National Labo- facilities is the percentage of the population with at least adequate access to excreta disposal facilities (private or shared, but not public) that can effectively prevent human, animal, and insect contact with excreta (facilities do not have to include treatment to render sewage outlows innocuous). Improved facilities range from simple but protected pit latrines to lush toilets with a sewerage connection. To be effective, facilities must be correctly constructed and properly ratory, Environmental Science Division, Oak Ridge, TN. FAO (Food and Agriculture Organization of the United Nations). 2010. Global Forest Resources Assessment 2010. Rome. ———. n.d. AQUASTAT. Online database. [www.fao.org/nr/water /aquastat/data/query/index.html]. Rome. IEA (International Energy Agency). Various years. Energy Balances of Non-OECD Countries. Paris. maintained. • Urban population is the midyear population of areas ———.Various years. Energy Balances of OECD Countries. Paris. deined as urban in each country and reported to the United Nations ———. Various years. Energy Statistics of Non-OECD Countries. Paris. divided by the World Bank estimate of total population. • Particulate ———.Various years. Energy Statistics of OECD Countries. Paris. matter concentration is ine suspended particulates of less than UNEP (United Nations Environment Programme) and WCMC (World 10 microns in diameter (PM10) that are capable of penetrating deep Conservation Monitoring Centre). 2013. Online databases [www into the respiratory tract and causing severe health damage. Data .unep-wcmc.org/datasets-tools--reports_15.html?&types=Data,We are urban-population-weighted PM10 levels in residential areas of bsite,Tool&ctops=]. Cambridge, UK. cities with more than 100,000 residents. • Carbon dioxide emis- United Nations Population Division. 2012. World Urbanization Pros- sions are emissions from the burning of fossil fuels and the manu- pects: The 2011 Revision. New York: United Nations, Department facture of cement and include carbon dioxide produced during con- of Economic and Social Affairs. [http://esa.un.org/unpd/wup sumption of solid, liquid, and gas fuels and gas laring. • Energy use /CD-ROM/Urban-Agglomerations.htm]. refers to the use of primary energy before transformation to other WAVES (Wealth Accounting and the Valuation of Ecosystem Services). end use fuels, which equals indigenous production plus imports n.d. Online reports. [www.wavespartnership.org]. Washington, DC. and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport. • Electricity production is measured at the terminals of all alternator sets in a station. In addition to hydropower, coal, oil, gas, and nuclear power generation, it covers generation by geothermal, solar, wind, and tide and wave energy as well as that from combustible renewables and waste. Production includes the output of electric plants designed to produce electricity only, as well as that of combined heat and power plants. Economy States and markets Global links Back World Development Indicators 2014 53 3 Environment Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/3.1). To view a speciic /indicator/SP.RUR.TOTL.ZS). 3.1 Rural environment and land use Rural population SP.RUR.TOTL.ZS Rural population growth SP.RUR.TOTL.ZG Land area AG.LND.TOTL.K2 Forest area AG.LND.FRST.ZS Permanent cropland AG.LND.CROP.ZS Arable land, % of land area AG.LND.ARBL.ZS Arable land, hectares per person AG.LND.ARBL.HA.PC 3.2 Agricultural inputs Agricultural land, % of land area AG.LND.AGRI.ZS Agricultural land, % irrigated AG.LND.IRIG.AG.ZS Average annual precipitation AG.LND.PRCP.MM Land under cereal production AG.LND.CREL.HA Fertilizer consumption, % of fertilizer production Annual freshwater withdrawals, % for agriculture ER.H2O.FWAG.ZS Annual freshwater withdrawals, % for industry ER.H2O.FWIN.ZS Annual freshwater withdrawals, % of domestic ER.GDP.FWTL.M3.KD Access to an improved water source, % of rural population SH.H2O.SAFE.RU.ZS Access to an improved water source, % of urban population SH.H2O.SAFE.UR.ZS 3.6 Energy production and use Energy production EG.EGY.PROD.KT.OE Energy use EG.USE.COMM.KT.OE ..a,b Energy use, Average annual growth AG.CON.FERT.PT.ZS Fertilizer consumption, kilograms per hectare of arable land AG.CON.FERT.ZS Agricultural employment SL.AGR.EMPL.ZS Tractors AG.LND.TRAC.ZS Crop production index AG.PRD.CROP.XD Food production index Energy use, Per capita EG.USE.PCAP.KG.OE Fossil fuel EG.USE.COMM.FO.ZS Combustible renewable and waste Alternative and nuclear energy production EG.USE.CRNW.ZS EG.USE.COMM.CL.ZS 3.7 Electricity production, sources, and access 3.3 Agricultural output and productivity AG.PRD.FOOD.XD Livestock production index AG.PRD.LVSK.XD Cereal yield AG.YLD.CREL.KG Electricity production EG.ELC.PROD.KH Coal sources EG.ELC.COAL.ZS Natural gas sources EG.ELC.NGAS.ZS Oil sources EG.ELC.PETR.ZS Hydropower sources EG.ELC.HYRO.ZS Renewable sources EG.ELC.RNWX.ZS 3.4 Deforestation and biodiversity Nuclear power sources EG.ELC.NUCL.ZS Forest area Access to electricity EG.ELC.ACCS.ZS Agriculture value added per worker EA.PRD.AGRI.KD AG.LND.FRST.K2 ..a,b Average annual deforestation Threatened species, Mammals EN.MAM.THRD.NO Threatened species, Birds EN.BIR.THRD.NO Threatened species, Fishes EN.FSH.THRD.NO Threatened species, Higher plants EN.HPT.THRD.NO Terrestrial protected areas ER.LND.PTLD.ZS Marine protected areas ER.MRN.PTMR.ZS 3.5 Freshwater Internal renewable freshwater resources ER.H2O.INTR.K3 Internal renewable freshwater resources, Per capita ER.H2O.INTR.PC Annual freshwater withdrawals, cu. m ER.H2O.FWTL.K3 Annual freshwater withdrawals, % of internal resources ER.H2O.FWTL.ZS 3.8 Energy dependency, efficiency and carbon dioxide emissions Net energy imports EG.IMP.CONS.ZS GDP per unit of energy use EG.GDP.PUSE.KO.PP.KD Carbon dioxide emissions, Total Carbon dioxide emissions, Carbon intensity World Development Indicators 2014 Front ? User guide EN.ATM.CO2E.KT EN.ATM.CO2E.EG.ZS Carbon dioxide emissions, Per capita Carbon dioxide emissions, kilograms per 2005 PPP $ of GDP EN.ATM.CO2E.PC EN.ATM.CO2E.PP.GD.KD 3.9 Trends in greenhouse gas emissions Carbon dioxide emissions, Total Carbon dioxide emissions, % change Methane emissions, Total World view EN.ATM.CO2E.KT ..a,b EN.ATM.METH.KT.CE Methane emissions, % change 54 ER.H2O.FWDM.ZS Water productivity, GDP/water use People ..a,b Environment Environment 3 Methane emissions, From energy processes EN.ATM.METH.EG.ZS Population in the largest city Methane emissions, Agricultural EN.ATM.METH.AG.ZS Access to improved sanitation facilities, % of urban population SH.STA.ACSN.UR Access to improved sanitation facilities, % of rural population SH.STA.ACSN.RU Nitrous oxide emissions, Total EN.ATM.NOXE.KT.CE ..a,b Nitrous oxide emissions, % change Nitrous oxide emissions, Energy and industry EN.ATM.NOXE.EI.ZS EN.URB.LCTY.UR.ZS Nitrous oxide emissions, Agriculture EN.ATM.NOXE.AG.ZS 3.13 Traffic and congestion Other greenhouse gas emissions, Total EN.ATM.GHGO.KT.CE Motor vehicles, Per 1,000 people IS.VEH.NVEH.P3 Motor vehicles, Per kilometer of road IS.VEH.ROAD.K1 ..a,b Other greenhouse gas emissions, % change 3.10 Carbon dioxide emissions by sector Electricity and heat production EN.CO2.ETOT.ZS Manufacturing industries and construction EN.CO2.MANF.ZS Residential buildings and commercial and public services EN.CO2.BLDG.ZS Transport EN.CO2.TRAN.ZS Other sectors EN.CO2.OTHX.ZS Passenger cars IS.VEH.PCAR.P3 Road density IS.ROD.DNST.K2 Road sector energy consumption, % of total consumption IS.ROD.ENGY.ZS Road sector energy consumption, Per capita IS.ROD.ENGY.PC Diesel fuel consumption IS.ROD.DESL.PC 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 Pump price for diesel EP.PMP.DESL.CD resilience Urban-population-weighted particulate matter concentrations (PM10) ..b Average daily minimum/maximum temperature Projected annual temperature ..b Projected annual cool days/cold nights ..b Projected annual hot days/warm nights ..b Projected annual precipitation ..b EN.ATM.PM10.MC.M3 3.14 Air pollution This table provides air pollution data for major cities. ..b 3.15 Contribution of natural resources to gross domestic Land area with an elevation of 5 meters or less AG.LND.EL5M.ZS Population living in areas with elevation of 5 meters or less EN.POP.EL5M.ZS Population affected by droughts, loods, and extreme temperatures Oil rents NY.GDP.PETR.RT.ZS EN.CLC.MDAT.ZS Natural gas rents NY.GDP.NGAS.RT.ZS Disaster risk reduction progress score EN.CLC.DRSK.XQ Coal rents NY.GDP.COAL.RT.ZS Mineral rents NY.GDP.MINR.RT.ZS Forest rents NY.GDP.FRST.RT.ZS product 3.12 Urbanization Urban population SP.URB.TOTL Urban population, % of total population Urban population, Average annual growth Population in urban agglomerations of more than 1 million Economy Total natural resources rents NY.GDP.TOTL.RT.ZS SP.URB.TOTL.IN.ZS 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. EN.URB.MCTY.TL.ZS States and markets Global links Back World Development Indicators 2014 55 ECONOMY 56 World Development Indicators 2014 Front ? User guide World view People Environment The Economy section provides a picture of the global economy and the economic activity of more than 200 countries and territories that produce, trade, and consume the world’s output. It includes measures of macroeconomic performance and stability and broader measures of income and saving adjusted for pollution, depreciation, and resource depletion. The world economy grew 2.4 percent in 2013 to reach $73 trillion in current prices, and growth is projected to accelerate to 3.2 percent in 2014. The share from low- and middle-income economies increased to 32.2 percent from 31.0 percent in 2012. Low- and middle-income economies, estimated to have grown 4.9 percent in 2013, are projected to expand 5.3 percent in 2014. Growth in high-income economies has been upgraded from earlier forecasts to 1.3 percent in 2013 and 2.2 percent in 2014. During 2014 many countries are expected to switch to the System of National Accounts 2008 (2008 SNA)—the latest version of the internationally agreed standard set of recommendations on how to compile measures of economic activity, adopted by the United Nations Statistical Commission. The 2008 SNA is an update of the System of National Accounts 1993 and retains the basic theoretical framework of its predecessor. In line with the commission’s mandate, the 2008 SNA introduces treatments for new Economy States and markets aspects of the economy that have come into prominence, elaborates on aspects that have increasingly become the focus of analytical attention, and clariies guidance on a wide range of issues. The changes in the 2008 SNA include further speciication of assets, capital formation, and consumption of ixed capital; concepts related to statistical units and institutional sectoring; the scope of transactions, including the production boundary; the scope of transactions by government and the public sector; and the treatment and deinition of inancial instruments and assets. The 2008 SNA and the sixth edition of the IMF’s Balance of Payments Manual have harmonized concepts and classiications. These changes bring the accounts into line with developments in the economic environment, advances in methodological research, and the needs of users. As of 2013, Australia; Canada; Hong Kong SAR, China; Mexico; TimorLeste; and the United States have switched to the 2008 SNA. A detailed explanation of the changes from the 1993 SNA are in annex 3 of the 2008 SNA manual (http://unstats.un.org /unsd/nationalaccount/docs/SNA2008.pdf). The complete 2008 SNA methodology can be accessed through the United Nations Statistics Division website (http://unstats.un.org/unsd /nationalaccount/sna2008.asp). Global links Back 4 World Development Indicators 2014 57 Highlights East Asia & Paciic: Deterioration of current account balances In 2012 Indonesia posted its irst current account deicit since the Current account balance (% of GDP) Asian inancial crisis. Private savings are under pressure from lower 20 commodity prices, and public savings are suffering from slow revenue growth and high subsidy spending despite recent reductions. Thai15 land’s current account balance turned negative in 2012, and savings Malaysia rates have declined due to rising household leverage and iscal sup- China 10 port, driving private consumption higher. Malaysia’s current account Thailand surplus, in double digits since 2003, dropped to 6 percent of GDP in 5 2012. Public savings are also lower following stimulus packages implemented since the global inancial crisis. China’s current account balance fell from a high of 10.1 percent of GDP in 2007 to 2.3 percent in 0 Indonesia 2012 (World Bank 2013a). –5 2005 2006 2007 2008 2009 2010 2011 2012 Source: Online table 4.17. South Asia: Growth has slowed but is stabilizing South Asian economies managed the inancial and economic crisis reason- Annual GDP growth (%) ably well. But real GDP growth has moderated and remains far below 25 pre-crisis levels. Regional growth slowed from 6.3 percent in 2011 to 4.9 percent in 2012, driven mainly by the slowdown in India, which 20 accounts for about 80 percent of the region’s GDP. India’s real GDP growth Afghanistan for 2012 was 4.7 percent, down from 6.6 percent in 2011. In Bangladesh, 15 with slower export and investment growth, GDP growth was 6.2 percent India 10 in 2012, down from 6.7 percent in 2011. Sri Lanka, facing prudent mac- South Asia roeconomic policies and dampened demand in its main export markets, recorded 6.4 percent growth in 2012, down from 8.2 percent in 2011. In 5 Afghanistan, the regional outlier, real GDP growth for 2012 is estimated Sri Lanka Bangladesh at 14.4 percent, up from 6.1 percent in 2011. Bhutan, Nepal, and PakiPakistan stan recorded higher growth rates in 2012 than in 2011, but GDP growth 0 2005 2006 2007 2008 2009 2010 2011 2012 in the Maldives in 2011 was half that in 2011 (World Bank 2013b). Source: Online table 4.1. Middle East and North Africa: Diverging trends in adjusted net savings Adjusted net savings measure the real difference between national Adjusted net savings (% of GNI) income and consumption—in other words, the change in a country’s 30 Algeria real wealth. It takes into account investment in human capital, depreciation of ixed capital, depletion of natural resources, and damage caused by pollution. Savings rates below zero suggest declining wealth 20 Morocco Jordan and, as a result, unsustainable development. Higher savings lay the basis for building wealth and future growth. Recent trends in the Middle 10 East and North Africa show diverging pathways. Adjusted net savings Egypt, Arab Rep. are positive and high for Algeria and Morocco but below zero for Jordan, Lebanon, and Tunisia. The central negative factor affecting saving 0 rates is depletion of energy resources, which reached 25 percent of Tunisia Lebanon gross national income in Middle East and North African countries in 2008 before falling back to around 13 percent in 2012. –10 2005 2006 2007 2008 2009 2010 2011 2012 Source: Online table 4.11. 58 World Development Indicators 2014 Front ? User guide World view People Environment Sub-Saharan Africa: More than 10 years of steady growth Sub- Saharan Africa averaged GDP growth of 5.5 percent a year between 1999 and 2010 (6.5 percent excluding South Africa), nearly Annual GDP growth (%) 15 1 percentage point higher than the rest of the developing world (exclud- China ing China). In 2012, 5 of the world’s 10 fastest growing economies Sub-Saharan Africa (excluding South Africa) were in Sub- Saharan Africa: Sierra Leone, Niger, Liberia, Burkina Faso, and Côte d’Ivoire. But growth varied widely—from a severe contrac- 10 tion in South Sudan and Sudan to over 10 percent growth in Liberia, Sub-Saharan Africa (all income levels) Niger, and Sierra Leone, thanks largely to new mineral production. Many countries have seen high growth for several years, with about 5 a third growing 6 percent or more annually (World Bank 2013c). Rest of the developing world (excluding China) 0 1999 2002 2004 2006 2008 2010 2012 Source: Online table 4.1. Latin America and the Caribbean: Growth present but slowing Latin America and the Caribbean was the third slowest growing region in 2012, ahead of Europe and Central Asia and the Middle Annual GDP growth (%) 10 East Asia & Pacific (developing countries only) East and North Africa. Growth decelerated, part of a 3 percentage point decline from 2010 peaks across all developing countries. In much of the Caribbean growth was constrained by higher debt and lower tourism activity. Weak external conditions and contractions in South Asia 5 domestic demand were largely responsible for causing the region’s GDP growth to fall from 6 percent in 2010 to an estimated 3 per- Sub-Saharan Africa (all income levels) cent in 2012. The drop was pronounced in the region’s largest economies, Brazil and Argentina, but other countries continued to grow, 0 Middle East & North Africa (developing countries only) Latin America & Caribbean (developing countries only) in most cases with robust domestic demand helping offset some of Europe & Central Asia (developing countries only) the slowdown in exports (De la Torre, Yeyati, and Pienknagura 2013). –5 2008 2009 2010 2011 2012 Source: Online table 4.1. Europe and Central Asia: Multispeed recovery Europe and Central Asia saw economic growth fall sharply, from 6.3 percent in 2011 to 1.8 percent in 2012 because of poor harvests, Annual GDP growth (%) 10 higher inlation, weak external demand, and European banks’ shrinking balance sheets. The slowdown was severe in Eastern Europe, where GDP grew less than 1 percent (and declined in Serbia). The adjustment in the Commonwealth of Independent States was less severe, but they 0 grew more slowly in 2012 than in 2011. Many developing countries have yet to recover from the 2008 crisis. The recovery of the 11 EU member states that joined after 2004 stalled in 2012, as domestic demand fell and the external environment weakened, leaving net exports as –10 Latvia Estonia Lithuania Poland Slovak Republic Bulgaria the sole driver of growth. That group’s GDP growth of 0.6 percent in 2012 was a ifth that of the year before, and Bosnia and Herzegovina, the Czech Republic, Hungary, the Kyrgyz Republic, and Moldova joined Croatia and Slovenia in a recession (World Bank 2013d,e,f). Romania Czech Republic Hungary Croatia Slovenia –20 2009 2010 2011 2012 Source: Online table 4.1. Economy States and markets Global links Back World Development Indicators 2014 59 4 Economy Gross domestic product Gross savings Adjusted net savings Current account balance Central Central Consumer government government price index cash surplus debt or deficit Broad money average annual % growth Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2000–12 2012–13 2013–14 2012 2012 2012 2012 2012 2012 2012 Afghanistan 9.4 3.1 3.5 –14.9 .. –35.5 –0.6 .. 7.2 31.9 Albania 5.0 1.3 2.1 14.5 –1.3 –10.4 –3.4 56.6 2.0 82.1 Algeria 3.7 2.8 3.3 47.5 28.3 6.0 –0.3 .. 8.9 61.0 .. .. .. .. .. .. .. .. .. .. 5.9 .. .. .. .. .. .. .. .. .. 11.8 5.1 8.0 18.0 –25.2 12.1 .. .. 10.3 34.9 American Samoa Andorra Angola Antigua and Barbuda 2.2 .. .. 24.9 .. –6.9 –1.4 .. 3.4 102.6 Argentina 5.8a 5.0 2.8 21.9 10.1 0.0 .. .. 10.0a 33.0 Armenia 7.6 3.2 5.0 11.7 –3.7 –11.1 –1.4 .. 2.6 33.7 –0.1 .. .. .. .. –9.5 .. .. 0.6 68.3 3.1 .. .. 25.5 12.0 –3.7 –3.7 30.6 1.8 102.8 Aruba Australia Austriab 1.7 .. .. 24.6 13.1 1.6 –2.2 75.3 2.5 .. 14.8 4.9 5.3 41.9 15.9 22.5 6.1 6.4 1.1 31.1 Bahamas, The 0.6 .. .. 8.4 .. –18.4 –4.1 47.9 2.0 76.6 Bahrain 5.4 .. .. 19.5 –0.8 9.7 –0.5 35.6 2.8 74.1 Bangladesh 6.0 6.0 5.7 39.8 21.3 2.3 –0.9 .. 6.2 69.7 Barbados 1.2 .. .. 8.4 3.6 –4.9 –8.0 96.8 4.5 .. Belarus 7.5 1.0 1.5 31.5 19.7 –2.7 1.7 40.8 59.2 30.5 Azerbaijan Belgiumb 1.4 .. .. 20.3 7.9 –2.0 –3.6 91.1 2.8 .. Belize 3.8 1.8 2.7 15.8 9.3 –1.3 –0.2 74.2 1.3 77.4 37.9 Benin 3.8 4.2 4.1 7.1 –5.2 –7.1 –1.4 .. 6.8 Bermuda 0.9 .. .. .. .. 14.1 .. .. .. .. Bhutan 8.7 7.6 8.1 44.5 23.7 –19.7 .. .. 10.9 61.2 Bolivia 4.2 5.3 4.7 25.7 5.5 7.9 .. .. 4.6 73.8 Bosnia and Herzegovina 3.8 0.8 2.0 14.5 .. –9.3 –1.2 .. 2.0 58.1 Botswana 4.2 4.6 4.9 40.7 33.2 –7.4 –1.9 .. 7.5 44.2 Brazil 3.7 2.2 2.4 14.8 4.3 –2.4 –2.6 52.8 5.4 80.8 Brunei Darussalam 1.2 .. .. .. .. .. .. .. 0.5 65.9 Bulgaria 4.0 0.6 1.7 21.7 10.9 –1.4 –2.0 15.4 3.0 79.6 Burkina Faso 5.9 7.0 7.0 22.9 8.5 –2.0 –3.2 .. 3.8 30.3 Burundi 3.6 4.3 4.5 17.5 –13.7 –10.3 .. .. 18.0 23.0 Cabo Verde 6.7 2.6 2.9 35.0 .. –11.5 –9.0 .. 2.5 78.7 Cambodia 8.1 7.0 7.0 10.6 –7.5 –8.6 –4.4 .. 2.9 50.1 Cameroon 3.3 4.8 5.0 15.8 –1.6 –3.8 .. .. 2.9 21.2 Canada 1.9 .. .. 23.6 13.0 –3.5 –1.3 53.8 1.5 .. .. .. .. .. .. .. .. .. .. .. Central African Republic 4.8 –18.0 –1.8 .. .. .. 0.7 .. 5.8 18.1 Chad 9.6 5.0 8.7 .. .. .. .. .. 10.2 11.9 Channel Islands 0.5 .. .. .. .. .. .. .. .. .. Chile 4.1 .. .. 21.4 –0.2 –3.5 1.3 .. 3.0 77.3 China 10.6 7.7 7.7 51.2 35.0 2.3 .. .. 2.7 187.6 4.4 .. .. 28.3 .. 2.3 3.8 39.2 4.1 335.3 107.6 Cayman Islands Hong Kong SAR, China Macao SAR, China 60 12.7 .. .. 57.4 .. 42.9 23.8 .. 6.1 Colombia 4.5 4.0 4.3 18.9 –3.2 –3.3 –1.1 62.6 3.2 42.9 Comoros 1.9 3.3 3.5 .. .. .. .. .. 1.8 38.3 Congo, Dem. Rep. 5.7 7.5 7.5 .. .. .. 3.8 .. 85.1 18.3 Congo, Rep. 4.6 5.6 5.4 .. .. .. .. .. 3.9 31.5 World Development Indicators 2014 Front ? User guide World view People Environment Economy 4 Gross domestic product Gross savings Adjusted net savings Current account balance Central Central Consumer government government price index cash surplus debt or deficit Broad money average annual % growth Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2000–12 2012–13 2013–14 2012 2012 2012 2012 2012 2012 2012 Costa Rica 4.7 3.4 4.3 15.9 15.1 –5.3 –3.5 .. 4.5 49.4 Côte d’Ivoire 1.2 8.7 8.2 .. .. 2.0 –3.1 .. 1.3 39.0 Croatia 2.1 .. .. 18.9 9.3 –0.3 –4.7 .. 3.4 80.7 Cuba 5.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Curaçao Cyprusb 2.6c .. .. 3.9c –6.9 –6.3 113.3 2.4 .. Czech Republic 3.3 .. .. 21.0 5.1 –2.4 –4.4 38.3 3.3 77.3 Denmark 0.6 .. .. 23.6 15.7 5.9 –2.0 50.6 2.4 74.6 Djibouti 3.5 .. .. .. .. .. .. .. 3.7 .. Dominica 3.2 1.1 1.7 10.8 .. –11.5 –11.9 .. 1.4 97.4 8.8c Dominican Republic 5.6 2.5 3.9 9.2 .. –6.8 –2.9 .. 3.7 34.3 Ecuador 4.4 4.0 4.1 26.9 6.1 –0.2 .. .. 5.1 31.6 Egypt, Arab Rep. 4.9 1.8 2.3 13.0 0.0 –2.7 –10.6 .. 7.1 74.1 El Salvador 2.0 1.9 2.3 8.9 6.6 –5.3 –2.2 47.8 1.7 44.6 Equatorial Guinea Eritrea 10.9 .. .. .. .. .. .. .. 6.1 18.7 0.9 6.0 3.5 .. .. .. .. .. .. 114.7 Estoniab 3.7 .. .. 25.0 12.5 –1.8 1.0 6.9 3.9 59.6 Ethiopia 8.9 7.0 7.2 28.8 6.1 –7.2 –1.4 .. 22.8 .. .. .. .. .. .. .. .. .. .. .. 1.2 2.4 2.1 .. .. –1.4 .. .. 3.4 68.8 Faeroe Islands Fiji Finlandb 1.7 .. .. 18.1 7.6 –1.5 –0.5 48.0 2.8 .. Franceb 1.1 .. .. 17.5 9.9 –2.2 –5.1 93.7 2.0 .. .. .. .. .. .. .. .. .. .. .. 2.4 4.2 4.2 .. .. .. .. .. 2.7 20.8 French Polynesia Gabon Gambia, The 3.4 6.5 7.5 17.1 0.9 Georgia 6.5d 2.5d 6.3d 18.3d 7.0 d Germany b 1.1 .. .. 24.2 Ghana 6.6 7.4 7.4 21.5 Greeceb 1.1 .. .. Greenland 1.7 .. .. Grenada 1.9 1.1 1.1 Guam Guatemala 6.4 .. .. 4.3 53.6 –11.7 –0.5 32.6 –0.9 30.2 15.8 7.0 –0.4 55.3 2.0 .. 2.7 –11.7 –3.9 .. 9.2 31.3 9.8 –4.3 –2.5 –9.8 106.5 1.5 .. .. .. .. .. .. .. .. –10.2 .. –28.0 –5.8 .. 2.4 95.4 .. .. .. .. .. .. .. .. .. .. 3.5 3.3 3.4 12.0 –2.3 –2.6 –2.3 24.4 3.8 46.2 Guinea 2.6 4.0 4.7 –6.2 –42.8 –18.4 .. .. 15.2 36.4 Guinea-Bissau 2.3 3.0 2.7 1.5 –22.4 –8.5 .. .. 2.1 38.8 Guyana 1.7 4.4 3.9 11.1 –11.8 –13.9 .. .. 2.4 67.0 Haiti 0.8 3.4 4.2 25.6 12.7 –4.4 .. .. 6.3 45.8 Honduras 4.3 2.9 3.4 16.5 11.4 –8.6 –3.2 .. 5.2 51.0 Hungary 1.6 0.7 1.7 23.4 12.4 0.9 3.7 82.4 5.7 60.9 Iceland 2.4 .. .. 9.3 .. –5.5 –5.3 119.1 5.2 89.8 India 7.7 4.8 6.2 30.3 14.8 –4.9 –3.8 49.7 9.3 75.6 Indonesia 5.5 5.6 5.3 32.0 24.1 –2.7 –1.1 26.2 4.3 40.1 Iran, Islamic Rep. 4.8 –1.5 1.0 .. .. .. .. .. 27.3 19.7 Iraq 5.1 4.2 6.5 26.7 .. 13.7 .. .. 5.8 30.7 Irelandb 2.2 .. .. 16.0 10.9 4.4 –13.0 102.0 1.7 .. Isle of Man 6.2 .. .. .. .. .. .. .. .. .. Israel 3.7 .. .. 14.8 6.0 1.3 –5.4 .. 1.7 .. Economy States and markets Global links Back World Development Indicators 2014 61 4 Economy Gross domestic product Gross savings Adjusted net savings Current account balance Central Central Consumer government government price index cash surplus debt or deficit Broad money average annual % growth 2000–12 Italy b Jamaica Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2013–14 2012 2012 2012 2012 2012 2012 2012 0.2 .. .. 17.4 3.3 –0.4 –3.5 110.8 3.0 .. .. .. .. 8.3 3.5 –12.9 –4.2 .. 6.9 47.1 Japan 0.7 .. .. 21.5 1.5 1.0 –8.3 189.8 0.0 241.2 Jordan 6.2 3.0 3.1 8.5 –0.7 –18.4 –8.3 66.8 4.8 118.4 Kazakhstan 7.7 6.0 5.8 26.2 –8.0 3.8 7.7 9.9 5.1 34.7 Kenya 4.4 5.0 5.1 9.4 4.7 –10.4 –4.8 .. 9.4 50.6 Kiribati 1.4 1.8 1.8 .. .. .. –7.2 .. .. .. .. .. .. .. .. .. .. .. .. .. Korea, Rep. 4.0 .. .. 30.9 18.1 3.8 1.8 .. 2.2 144.3 Kosovo 5.2 .. .. 18.3 .. –7.5 .. .. 2.5 40.6 Kuwait 5.1 .. .. 59.5 11.2 43.2 27.9 .. 2.8 57.6 Kyrgyz Republic 4.2 7.8 6.5 29.6 12.1 –22.1 –6.6 .. 2.7 .. Lao PDR 7.4 8.0 7.7 15.7 –11.6 –4.4 –0.8 .. 4.3 35.9 Latvia 3.6 .. .. 25.7 11.0 –2.5 –2.8 42.1 2.3 44.1 Lebanon 5.0 0.7 2.0 13.6 –2.2 –3.9 –8.8 .. 4.0 241.7 Lesotho 4.1 4.6 5.1 18.1 11.5 –24.0 .. .. 6.1 35.6 Liberia 6.6 7.9 7.5 31.4 –6.0 –49.1 –2.6 32.7 6.8 34.9 Libya 5.4 –6.0 23.0 .. .. .. .. .. 6.1 .. Liechtenstein 2.5 .. .. .. .. .. .. .. .. .. 47.4 Korea, Dem. People’s Rep. Lithuania 4.3 .. .. 17.1 9.1 –0.2 –5.1 43.5 3.1 Luxembourgb 2.5 .. .. 16.4 8.3 6.5 –0.4 17.2 2.7 .. Macedonia, FYR 3.2 2.5 3.0 25.5 6.0 –3.1 –4.0 .. 3.3 58.3 Madagascar 3.0 4.1 4.8 .. .. .. –1.7 .. 6.4 24.4 Malawi 3.7 4.4 4.8 12.5 –2.7 –18.8 .. .. 21.3 36.4 Malaysia 4.9 4.5 4.8 31.9 16.1 6.1 –4.5 53.3 1.7 141.2 Maldives 7.2 4.3 4.2 .. .. –27.0 –8.8 73.8 13.1 58.6 Mali 5.2 4.0 5.2 8.5 –10.8 –12.6 –2.5 .. 5.4 32.3 Maltab 1.8 .. .. 11.7 .. 2.1 –2.7 84.0 2.4 .. Marshall Islands 1.4 5.0 5.0 .. .. .. .. .. .. .. Mauritania 5.6 5.7 4.6 .. .. .. .. .. 4.9 33.3 Mauritius 3.9 3.7 4.1 15.1 4.5 –11.2 –1.1 36.4 3.9 100.5 Mexico 2.2 1.4 3.4 21.5 5.8 –1.2 .. .. 4.1 32.0 Micronesia, Fed. Sts. 0.0 1.4 1.4 .. .. .. .. .. .. 41.3 Moldova 4.8e 4.2e 3.8e –6.8 –1.8 23.7 4.7 56.4 Monaco 4.2 .. .. .. .. .. .. .. .. .. Mongolia 7.7 12.5 10.3 33.3 13.8 –32.7 –8.5 .. 15.0 54.6 12.8e 6.2e Montenegro 4.0 1.8 2.5 –0.2 .. –17.6 .. .. 3.2 50.5 Morocco 4.8f 4.5f 3.6f 25.8f 14.7f –10.0 –4.2 56.8 1.3 113.9 Mozambique 7.5 7.0 8.5 12.4 0.4 –44.2 –2.8 .. 2.1 46.0 .. .. .. .. .. .. .. .. 1.5 .. 4.8 4.2 4.3 18.2 12.0 –1.2 .. .. 6.5 57.1 Nepal 4.0 3.6 3.8 40.8 30.0 3.0 –0.6 33.9 9.5 77.5 Netherlandsb 1.3 .. .. 24.8 16.9 9.4 –3.9 66.4 2.4 .. .. .. .. .. .. .. .. .. .. .. Myanmar Namibia New Caledonia 62 Estimate 2012–13 New Zealand 2.3 .. .. 14.6 8.0 –4.1 –7.2 62.5 0.9 94.7 Nicaragua 3.4 3.8 4.2 17.3 3.7 –13.0 0.5 .. 7.2 33.6 Niger 4.5 5.6 6.2 20.1 10.0 –19.9 .. .. 0.5 23.1 World Development Indicators 2014 Front ? User guide World view People Environment Economy 4 Gross domestic product Gross savings Adjusted net savings Current account balance Central Central Consumer government government price index cash surplus debt or deficit Broad money average annual % growth Nigeria Northern Mariana Islands Norway Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2000–12 2012–13 2013–14 2012 2012 2012 2012 2012 2012 2012 6.8 6.7 6.7 40.6 8.2 7.8 .. .. 12.2 .. .. .. .. .. .. .. .. .. .. 1.5 .. .. 39.1 21.7 14.5 14.6 20.9 0.7 .. 36.5 Oman 5.0 .. .. .. .. 10.6 10.6 5.0 2.9 36.3 Pakistan 4.4 6.1 3.4 20.3 3.7 –0.9 –8.0 .. 9.7 39.9 –0.1 5.8 5.8 .. .. .. .. .. .. .. 7.5 7.9 7.3 26.7 23.3 –9.0 .. .. 5.7 80.6 Palau Panama Papua New Guinea 4.7 4.0 8.5 .. .. –6.7 .. .. 2.2 52.0 Paraguay 3.7 14.1 4.6 12.4 6.1 0.5 1.6 .. 3.7 44.6 Peru 6.3 4.9 5.5 25.4 7.7 –3.4 1.2 19.1 3.7 36.8 Philippines 4.9 6.9 6.5 23.9 9.4 2.8 –1.9 51.5 3.2 58.9 Poland 4.2 .. .. 17.5 7.9 –3.7 –4.3 .. 3.6 57.9 Portugalb 0.4 .. .. 15.9 8.7 –2.1 –4.0 92.5 2.8 .. Puerto Rico –0.4 .. .. .. .. .. .. .. .. .. Qatar 14.0 .. .. 66.2 46.1 32.0 2.9 .. 1.9 54.4 Romania 4.2 2.5 2.5 22.2 7.0 –4.4 –5.1 .. 3.3 37.8 Russian Federation 4.8 .. .. 29.6 15.3 3.6 3.3 9.3 5.1 51.5 Rwanda 7.9 7.0 7.5 11.5 –3.7 –11.6 –0.9 .. 6.3 .. Samoa 2.4 2.1 2.1 .. .. –5.2 0.0 .. 2.0 44.6 San Marino 3.2 .. .. .. .. .. .. .. 2.8 .. São Tomé and Príncipe 4.5 5.5 4.9 .. .. –37.8 –12.6 .. 10.4 36.9 Saudi Arabia 6.1 .. .. 50.5 10.0 23.2 .. .. 2.9 54.1 Senegal 4.0 4.0 4.5 21.8 15.9 –7.9 –6.2 .. 1.4 40.4 Serbia 3.3 2.0 1.0 18.0 .. –10.7 –4.5 .. 7.3 49.8 Seychelles 3.1 3.5 3.9 .. .. –24.7 4.8 73.3 7.1 48.0 Sierra Leone 6.9 17.0 14.1 10.2 –22.7 –29.0 –5.2 .. 12.9 20.5 Singapore 5.9 .. .. 45.6 31.9 18.7 9.0 115.1 4.5 137.6 .. .. .. .. .. .. .. .. .. .. Slovak Republicb Sint Maarten 4.8 .. .. 22.0 6.1 2.2 –4.9 45.6 3.6 .. Sloveniab 2.5 .. .. 21.4 9.5 3.3 –5.9 .. 2.6 .. Solomon Islands 5.1 4.0 3.5 .. .. 0.2 .. .. 7.3 41.3 Somalia South Africa South Sudan .. .. .. .. .. .. .. .. .. .. 3.6 1.9 2.7 13.2 0.4 –5.2 –4.4 .. 5.4 75.2 .. .. 33.9 17.0 .. .. .. .. .. 47.3 Spainb 1.7 .. .. 18.9 5.9 –1.1 –3.6 56.1 2.4 .. Sri Lanka 5.9 7.0 7.4 24.1 19.7 –6.7 –6.1 79.1 7.5 38.6 St. Kitts and Nevis 2.4 .. .. 18.3 .. –9.2 10.7 .. 1.4 140.7 St. Lucia 2.7 0.7 1.5 13.0 4.5 –14.9 –6.8 .. 4.2 95.8 .. .. .. .. .. .. .. .. .. .. St. Vincent & the Grenadines 2.8 2.1 2.7 –6.7 .. –30.3 –2.0 .. 2.6 68.6 Sudan 5.2g 2.9h 2.9h –10.8 .. .. 37.4 27.9h Suriname 4.9 3.9 4.1 .. .. 4.7 –0.7 .. 5.0 49.1 Swaziland 2.2 0.0 0.0 7.7 1.4 4.1 .. .. 8.9 31.4 Sweden 2.2 .. .. 25.4 17.8 6.1 –0.4 36.6 0.9 85.2 Switzerland 1.9 .. .. 32.8 18.9 8.5 0.6 26.7 –0.7 188.0 Syrian Arab Republic 5.0 –22.5 –8.6 16.8 .. .. .. .. 36.7 73.9 Tajikistan 7.8 7.0 6.0 17.9 9.0 –3.2 .. .. 5.8 15.5 St. Martin Economy States and markets 9.9h –6.7h Global links Back World Development Indicators 2014 63 4 Economy Gross domestic product Gross savings Adjusted net savings Current account balance Central Central Consumer government government price index cash surplus debt or deficit Broad money average annual % growth Estimate Forecast % of GDP % of GNI % of GDP % of GDP % of GDP % growth % of GDP 2000–12 2012–13 2013–14 2012 2012 2012 2012 2012 2012 2012 Tanzaniai 7.0 7.1 7.4 23.5 8.7 –12.9 –7.2 .. 16.0 32.8 Thailand 4.1 3.2 4.5 30.2 16.7 –0.4 –1.2 30.2 3.0 131.1 Timor-Leste 5.8 .. .. 326.7 .. 211.9 .. .. 11.8 31.5 Togo 2.8 5.0 4.5 0.0 –21.3 –6.3 –6.3 .. 2.6 46.4 Tonga 1.1 1.2 1.2 5.9 .. –20.2 .. .. 1.2 40.5 Trinidad and Tobago 5.1 .. .. .. .. 12.3 –1.6 .. 9.3 62.0 Tunisia 4.2 2.6 2.5 14.5 –3.1 –8.3 –5.0 44.1 5.5 66.7 Turkey 4.6 4.3 3.5 14.5 3.4 –6.1 –1.1 47.2 8.9 55.4 Turkmenistan 9.0 10.1 10.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Tuvalu 1.3 1.0 1.0 .. .. .. .. .. .. .. Uganda 7.5 6.2 6.7 12.8 –11.2 –11.1 –3.9 42.7 14.0 24.2 Ukraine 3.8 –1.1 2.0 9.3 –3.7 –8.4 –2.3 27.4 0.6 54.9 United Arab Emirates 4.2 .. .. .. .. .. 0.1 .. 0.9 61.2 United Kingdom 1.5 .. .. 10.9 3.0 –3.7 –7.6 99.8 2.8 161.6 Turks and Caicos Islands United States 1.7 .. .. 16.5 7.3 –2.7 –7.5 93.8 2.1 87.4 Uruguay 4.2 .. .. 15.0 1.6 –5.3 –2.1 44.6 8.1 43.6 Uzbekistan 7.4 7.4 7.0 .. .. .. .. .. .. .. Vanuatu 3.8 1.7 2.2 19.3 .. –6.4 –2.3 .. 1.4 78.1 Venezuela, RB 4.3 0.7 0.5 25.6 6.8 2.9 .. .. 21.1 47.5 Vietnam 6.6 5.3 5.4 31.6 12.7 5.8 .. .. 9.1 106.5 .. Virgin Islands (U.S.) .. .. .. .. .. .. .. .. .. West Bank and Gaza .. .. .. .. .. .. .. .. .. .. 3.1 3.0 3.4 8.1 –10.8 –3.2 .. .. 17.3 34.6 Yemen, Rep. 5.9 6.0 6.5 24.7 1.8 0.0 5.0 .. 6.6 24.2 –4.1 2.2 3.3 .. .. .. .. .. .. .. 2.7 w 2.4 w 3.2 w 21.6 w 11.3 w Low income 5.6 6.2 6.3 23.8 7.1 Middle income 6.3 4.9 5.6 30.9 18.6 Lower middle income 6.2 4.5 5.9 26.9 12.5 Upper middle income 6.3 5.0 5.5 32.2 20.2 Low & middle income 6.3 4.8 5.3 30.9 18.4 East Asia & Paciic 9.2 7.2 7.2 46.0 31.8 Europe & Central Asia 4.7 3.4 3.5 16.9 2.8 Latin America & Carib. 3.6 2.5 2.9 19.2 5.1 Middle East & N. Africa 4.6 –0.1 2.8 .. 5.3 South Asia 7.2 4.6 5.7 29.5 13.9 Sub-Saharan Africa 5.0 4.7 5.3 19.8 –0.4 High income 1.8 1.3 2.2 19.6 8.2 Euro area 1.1 –0.4 1.1 20.1 10.2 Zambia Zimbabwe World a. Data for Argentina are oficially reported by the National Statistics and Censuses Institute of Argentina. The International Monetary Fund has, however, issued a declaration of censure and called on Argentina to adopt remedial measures to address the quality of oficial GDP and consumer price index data. Alternative data sources have shown signiicantly lower real growth and higher inlation than the oficial data since 2008. In this context, the World Bank is also using alternative data sources and estimates for the surveillance of macroeconomic developments in Argentina. b. As members of the European Monetary Union, these countries share a single currency, the euro. c. Refers to the area controlled by the government of Cyprus. d. Excludes Abkhazia and South Ossetia. e. Excludes Transnistria. f. Includes Former Spanish Sahara. g. Excludes South Sudan after July 9, 2011. h. Excludes South Sudan. i. Covers mainland Tanzania only. 64 World Development Indicators 2014 Front ? User guide World view People Environment Economy 4 About the data Economic data are organized by several different accounting con- edition are not comparable with those from earlier editions with ventions: the system of national accounts, the balance of pay- different base years. ments, government i nance statistics, and international i nance Rescaling may result in a discrepancy between the rescaled GDP statistics. There has been progress in unifying the concepts in the and the sum of the rescaled components. To avoid distortions in the system of national accounts, balance of payments, and government growth rates, the discrepancy is left unallocated. As a result, the i nance statistics, but there are many national variations in the weighted average of the growth rates of the components generally implementation of these standards. For example, even though the does not equal the GDP growth rate. United Nations recommends using the 2008 System of National Accounts (2008 SNA) methodology in compiling national accounts, Adjusted net savings many are still using earlier versions, some as old as 1968. The Adjusted net savings measure the change in a country’s real wealth International Monetary Fund (IMF) has recently published a new after accounting for the depreciation and depletion of a full range of balance of payments methodology (BPM6), but many countries are assets in the economy. If a country’s adjusted net savings are posi- still using the previous version. Similarly, the standards and deini- tive and the accounting includes a suficiently broad range of assets, tions for government inance statistics were updated in 2001, but economic theory suggests that the present value of social welfare is several countries still report using the 1986 version. For individual increasing. Conversely, persistently negative adjusted net savings country information about methodology used, refer to Primary data indicate that the present value of social welfare is decreasing, sug- documentation. gesting that an economy is on an unsustainable path. Economic growth ing measures of gross savings by making four adjustments. First, An economy’s growth is measured by the change in the volume of its estimates of i xed capital consumption of produced assets are output or in the real incomes of its residents. The 2008 SNA offers deducted to obtain net savings. Second, current public expendi- three plausible indicators for calculating growth: the volume of gross tures on education are added to net savings (in standard national domestic product (GDP), real gross domestic income, and real gross accounting these expenditures are treated as consumption). Third, national income. Only growth in GDP is reported here. estimates of the depletion of a variety of natural resources are Adjusted net savings are derived from standard national account- Growth rates of GDP and its components are calculated using the deducted to relect the decline in asset values associated with their least squares method and constant price data in the local currency extraction and harvest. And fourth, deductions are made for dam- for countries and using constant price U.S. dollar series for regional ages from carbon dioxide emissions and local pollution. By account- and income groups. Local currency series are converted to constant ing for the depletion of natural resources and the degradation of U.S. dollars using an exchange rate in the common reference year. the environment, adjusted net savings go beyond the deinition of The growth rates are average annual and compound growth rates. savings or net savings in the SNA. Methods of computing growth are described in Statistical methods. Forecasts of growth rates come from World Bank (2014). Balance of payments The balance of payments records an economy’s transactions with Rebasing national accounts the rest of the world. Balance of payments accounts are divided Rebasing of national accounts can alter the measured growth rate of into two groups: the current account, which records transactions an economy and lead to breaks in series that affect the consistency in goods, services, primary income, and secondary income, and of data over time. When countries rebase their national accounts, the capital and inancial account, which records capital transfers, they update the weights assigned to various components to better acquisition or disposal of nonproduced, noninancial assets, and relect current patterns of production or uses of output. The new transactions in inancial assets and liabilities. The current account base year should represent normal operation of the economy—it balance is one of the most analytically useful indicators of an exter- should be a year without major shocks or distortions. Some devel- nal imbalance. oping countries have not rebased their national accounts for many A primary purpose of the balance of payments accounts is to years. Using an old base year can be misleading because implicit indicate the need to adjust an external imbalance. Where to draw price and volume weights become progressively less relevant and the line for analytical purposes requires a judgment concerning the useful. imbalance that best indicates the need for adjustment. There are a To obtain comparable series of constant price data for comput- number of deinitions in common use for this and related analytical ing aggregates, the World Bank rescales GDP and value added by purposes. The trade balance is the difference between exports and industrial origin to a common reference year. This year’s World Devel- imports of goods. From an analytical view it is arbitrary to distinguish opment Indicators switches the reference year to 2005. Because goods from services. For example, a unit of foreign exchange earned rescaling changes the implicit weights used in forming regional and by a freight company strengthens the balance of payments to the income group aggregates, aggregate growth rates in this year’s same extent as the foreign exchange earned by a goods exporter. Economy States and markets Global links Back World Development Indicators 2014 65 4 Economy Even so, the trade balance is useful because it is often the most encompasses currency held by the public and demand deposits with timely indicator of trends in the current account balance. Customs banks. M2 includes M1 plus time and savings deposits with banks authorities are typically able to provide data on trade in goods long that require prior notice for withdrawal. M3 includes M2 as well as before data on trade in services are available. various money market instruments, such as certiicates of deposit Beginning in August 2012, the International Monetary Fund imple- issued by banks, bank deposits denominated in foreign currency, mented the Balance of Payments Manual 6 (BPM6) framework in its and deposits with inancial institutions other than banks. However major statistical publications. The World Bank implemented BPM6 deined, money is a liability of the banking system, distinguished in its online databases and publications from April 2013. Balance from other bank liabilities by the special role it plays as a medium of payments data for 2005 onward will be presented in accord with of exchange, a unit of account, and a store of value. the BPM6. The historical BPM5 data series will end with data for A general and continuing increase in an economy’s price level is 2008, which can be accessed through the World Development Indi- called inlation. The increase in the average prices of goods and cators archives. services in the economy should be distinguished from a change The complete balance of payments methodology can be accessed in the relative prices of individual goods and services. Generally through the International Monetary Fund website (www.imf.org accompanying an overall increase in the price level is a change in /external/np/sta/bop/bop.htm). the structure of relative prices, but it is only the average increase, not the relative price changes, that constitutes inlation. A commonly Government finance used measure of inlation is the consumer price index, which mea- Central government cash surplus or deicit, a summary measure of sures the prices of a representative basket of goods and services the ongoing sustainability of government operations, is comparable purchased by a typical household. The consumer price index is usu- to the national accounting concept of savings plus net capital trans- ally calculated on the basis of periodic surveys of consumer prices. fers receivable, or net operating balance in the 2001 update of the Other price indices are derived implicitly from indexes of current and IMF’s Government Finance Statistics Manual. constant price series. The 2001 manual, harmonized with the 1993 SNA, recommends Consumer price indexes are produced more frequently and so an accrual accounting method, focusing on all economic events are more current. They are constructed explicitly, using surveys affecting assets, liabilities, revenues, and expenses, not just those of the cost of a deined basket of consumer goods and services. represented by cash transactions. It accounts for all changes in Nevertheless, consumer price indexes should be interpreted with stocks, so stock data at the end of an accounting period equal stock caution. The deinition of a household, the basket of goods, and the data at the beginning of the period plus lows over the period. The geographic (urban or rural) and income group coverage of consumer 1986 manual considered only debt stocks. price surveys can vary widely by country. In addition, weights are For most countries central government inance data have been derived from household expenditure surveys, which, for budgetary consolidated into one account, but for others only budgetary central reasons, tend to be conducted infrequently in developing countries, government accounts are available. Countries reporting budgetary impairing comparability over time. Although useful for measuring data are noted in Primary data documentation. Because budgetary consumer price inlation within a country, consumer price indexes accounts may not include all central government units (such as are of less value in comparing countries. social security funds), they usually provide an incomplete picture. In federal states the central government accounts provide an incom- Definitions plete view of total public inance. • Gross domestic product (GDP) at purchaser prices is the sum of Data on government revenue and expense are collected by the IMF gross value added by all resident producers in the economy plus any through questionnaires to member countries and by the Organisa- product taxes (less subsidies) not included in the valuation of out- tion for Economic Co-operation and Development (OECD). Despite put. It is calculated without deducting for depreciation of fabricated IMF efforts to standardize data collection, statistics are often incom- capital assets or for depletion and degradation of natural resources. plete, untimely, and not comparable across countries. Value added is the net output of an industry after adding up all out- Government inance statistics are reported in local currency. The puts and subtracting intermediate inputs. • Gross savings are the indicators here are shown as percentages of GDP. Many countries difference between gross national income and public and private report government inance data by iscal year; see Primary data consumption, plus net current transfers. • Adjusted net savings documentation for information on iscal year end by country. measure the change in value of a speciied set of assets, excluding capital gains. Adjusted net savings are net savings plus education 66 Financial accounts expenditure minus energy depletion, mineral depletion, net forest Money and the inancial accounts that record the supply of money depletion, and carbon dioxide and particulate emissions damage. lie at the heart of a country’s inancial system. There are several • Current account balance is the sum of net exports of goods and commonly used deinitions of the money supply. The narrowest, M1, services, net primary income, and net secondary income. • Central World Development Indicators 2014 Front ? User guide World view People Environment Economy 4 government cash surplus or deficit is revenue (including grants) current account balance are from the IMF’s Balance of Payments minus expense, minus net acquisition of noninancial assets. In Statistics Yearbook and International Financial Statistics. Data on editions before 2005 noninancial assets were included under rev- central government inances are from the IMF’s Government Finance enue and expenditure in gross terms. This cash surplus or deicit is Statistics database. Data on the consumer price index are from the close to the earlier overall budget balance (still missing is lending IMF’s International Financial Statistics. Data on broad money are minus repayments, which are included as a inancing item under net from the IMF’s monthly International Financial Statistics and annual acquisition of inancial assets). • Central government debt is the International Financial Statistics Yearbook. entire stock of direct government ixed-term contractual obligations to others outstanding on a particular date. It includes domestic and References foreign liabilities such as currency and money deposits, securities Asian Development Bank. 2012. Asian Development Outlook 2012 other than shares, and loans. It is the gross amount of government Update: Services and Asia’s Future Growth. Manila. liabilities reduced by the amount of equity and inancial derivatives De la Torre, Augusto, Eduardo Levy Yeyati, Samuel Pienknagura. 2013. held by the government. Because debt is a stock rather than a low, Latin America’s Deceleration and the Exchange Rate Buffer. Semian- it is measured as of a given date, usually the last day of the iscal nual Report, Ofice of the Chief Economist. Washington, DC: World year. • Consumer price index relects changes in the cost to the average consumer of acquiring a basket of goods and services that Bank. Fankhauser, Samuel. 1994. “The Social Costs of Greenhouse Gas Emis- may be ixed or may change at speciied intervals, such as yearly. sions: An Expected Value Approach.” Energy Journal 15 (2): 157–84. The Laspeyres formula is generally used. • Broad money (IFS line Hamilton, Kirk, and Michael Clemens. 1999. “Genuine Savings 35L..ZK) is the sum of currency outside banks; demand deposits Rates in Developing Countries.” World Bank Economic Review 13 other than those of the central government; the time, savings, and foreign currency deposits of resident sectors other than the central government; bank and traveler’s checks; and other securities such as certiicates of deposit and commercial paper. (2): 333–56. IMF (International Monetary Fund). 2001. Government Finance Statistics Manual. Washington, DC. International Energy Agency. 2013. IEA CO2 Emissions from Fuel Combustion Statistics database. [http://dx.doi.org/10.1787 Data sources /data-00430-en]. Paris. Data on GDP for most countries are collected from national statisti- Pandey, Kiran D., Katharine Bolt, Uwe Deichmann, Kirk Hamilton, Bart cal organizations and central banks by visiting and resident World Ostro, and David Wheeler. 2006. “The Human Cost of Air Pollution: Bank missions; data for selected high-income economies are from New Estimates for Developing Countries.” World Bank, Development the OECD. Estimates of GDP growth for 2012–13 and projections Research Group and Environment Department, Washington, DC. for 2013–14 are from the World Bank’s Global Economic Prospects United Nations Statistics Division. Various years. National Accounts database. Data on gross savings are from World Bank national Statistics: Main Aggregates and Detailed Tables. Parts 1 and 2. New accounts data iles. Data on adjusted net savings are based on a conceptual underpinning by Hamilton and Clemens (1999) and calculated using data on consumption of i xed capital from the United Nations Statistics Division’s National Accounts Statistics: Main Aggregates and Detailed Tables, extrapolated to 2010; data on education expenditure from the United Nations Educational, Scientiic, and Cultural Organization Institute for Statistics online database, with missing data estimated by World Bank staff; data on forest, energy, and mineral depletion based on sources and methods in World Bank (2011); estimates of damages from carbon dioxide emissions following the method of Fankhauser (1994) and using emissions data published by the International Energy Agency (2013); and predicted concentrations of local air pollution following the method of Pandey and others (2006) and using monitoring data for air quality available online in the World Health Organization’s Global Health Observatory database, the Clean Air Asia’s Cities- York: United Nations. World Bank. 2011. The Changing Wealth of Nations: Measuring Sustainable Development for the New Millennium. Washington, DC. ———. 2013a. East Asia and Pacific Economic Update 2013: Rebuilding Policy Buffers, Reinvigorating Growth. Washington, DC. ———. 2013b. South Asia Economic Focus—Regaining Momentum. Washington, DC. ———. 2013c. Africa’s Pulse: An Analysis of Issues Shaping Africa’s Economic Future. Volume 8, October. Washington, DC. ———. 2013d. EU11 Regular Economic Report. Issue 26, January. Washington, DC. ———. 2013e. EU11 Regular Economic Report. Issue 27, June. Washington, DC. ———. 2013f. Global Economic Prospects, Volume 7, June 13: Assuring Growth over the Medium Term. Washington, DC. ———. 2014. Global Economic Prospects: Coping with Policy Normaliza- ACT database, the European Environment Agency’s database, and tion in High-income Countries. Volume 8, January 14. Washington, DC. the database of the U.S. Environmental Protection Agency. Data on ———. Various years. World Development Indicators. Washington, DC. Economy States and markets Global links Back World Development Indicators 2014 67 4 Economy Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/4.1). To view a speciic /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 Travel TM.VAL.TRVL.ZS.WT TM.VAL.INSF.ZS.WT Industry NV.IND.TOTL.KD.ZG Manufacturing NV.IND.MANF.KD.ZG Insurance and inancial services 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 Agriculture NV.AGR.TOTL.ZS Industry NV.IND.TOTL.ZS Manufacturing NV.IND.MANF.ZS Services NV.SRV.TETC.ZS 4.3 Structure of manufacturing Manufacturing value added NV.IND.MANF.CD Food, beverages and tobacco NV.MNF.FBTO.ZS.UN Textiles and clothing NV.MNF.TXTL.ZS.UN Machinery and transport equipment NV.MNF.MTRN.ZS.UN Chemicals NV.MNF.CHEM.ZS.UN Other manufacturing NV.MNF.OTHR.ZS.UN 4.4 Structure of merchandise exports 4.8 Structure of demand Household inal consumption expenditure NE.CON.PETC.ZS General government inal consumption expenditure NE.CON.GOVT.ZS Gross capital formation NE.GDI.TOTL.ZS Exports of goods and services NE.EXP.GNFS.ZS Imports of goods and services NE.IMP.GNFS.ZS Gross savings NY.GNS.ICTR.ZS 4.9 Growth of consumption and investment Household inal consumption expenditure General government inal consumption expenditure Gross capital formation Merchandise exports TX.VAL.MRCH.CD.WT Food TX.VAL.FOOD.ZS.UN Agricultural raw materials NE.CON.GOVT.KD.ZG NE.GDI.TOTL.KD.ZG Exports of goods and services NE.EXP.GNFS.KD.ZG Imports of goods and services NE.IMP.GNFS.KD.ZG 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 4.5 Structure of merchandise imports Merchandise imports TM.VAL.MRCH.CD.WT Food TM.VAL.FOOD.ZS.UN Agricultural raw materials TM.VAL.AGRI.ZS.UN Fuels TM.VAL.FUEL.ZS.UN Ores and metals TM.VAL.MMTL.ZS.UN Manufactures TM.VAL.MANF.ZS.UN Consumption of ixed capital NY.ADJ.DKAP.GN.ZS Natural resource depletion NY.ADJ.DRES.GN.ZS Adjusted net national income NY.ADJ.NNTY.CD Gross domestic product, % growth NY.GDP.MKTP.KD.ZG Gross national income, % growth NY.GNP.MKTP.KD.ZG Adjusted net national income NY.ADJ.NNTY.KD.ZG 4.11 Toward a broader measure of savings Gross savings 4.6 Structure of service exports Commercial service exports TX.VAL.SERV.CD.WT Transport TX.VAL.TRAN.ZS.WT Travel TX.VAL.TRVL.ZS.WT Insurance and inancial services TX.VAL.INSF.ZS.WT World Development Indicators 2014 Front NY.ADJ.ICTR.GN.ZS Consumption of ixed capital Computer, information, communications, and other commercial services 68 NE.CON.PRVT.KD.ZG Household inal consumption expenditure, Per capita NE.CON.PRVT.PC.KD.ZG TX.VAL.OTHR.ZS.WT ? User guide NY.ADJ.DKAP.GN.ZS Education expenditure NY.ADJ.AEDU.GN.ZS Net forest depletion NY.ADJ.DFOR.GN.ZS Energy depletion NY.ADJ.DNGY.GN.ZS Mineral depletion NY.ADJ.DMIN.GN.ZS Carbon dioxide damage NY.ADJ.DCO2.GN.ZS Local pollution damage NY.ADJ.DPEM.GN.ZS Adjusted net savings NY.ADJ.SVNG.GN.ZS World view People Environment Economy 4 4.12 Central government finances 4.15 Monetary indicators Revenue GC.REV.XGRT.GD.ZS Broad money Expense GC.XPN.TOTL.GD.ZS Claims on domestic economy FM.LBL.BMNY.ZG Cash surplus or deicit GC.BAL.CASH.GD.ZS Claims on central governments Net incurrence of liabilities, Domestic FM.AST.DOMO.ZG.M3 FM.AST.CGOV.ZG.M3 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 Oficial exchange rate Goods and services GC.XPN.GSRV.ZS Compensation of employees GC.XPN.COMP.ZS Interest payments GC.XPN.INTP.ZS Subsidies and other transfers GC.XPN.TRFT.ZS Other expense GC.XPN.OTHR.ZS PA.NUS.FCRF Purchasing power parity (PPP) conversion factor Taxes on income, proits and capital gains GC.TAX.YPKG.RV.ZS Taxes on goods and services GC.TAX.GSRV.RV.ZS Taxes on international trade GC.TAX.INTT.RV.ZS Other taxes Social contributions Grants and other revenue GC.TAX.OTHR.RV.ZS GC.REV.SOCL.ZS GC.REV.GOTR.ZS PX.REX.REER NY.GDP.DEFL.KD.ZG Consumer price index FP.CPI.TOTL.ZG Wholesale price index FP.WPI.TOTL 4.17 Balance of payments current account Goods and services, Exports BX.GSR.GNFS.CD Goods and services, Imports BM.GSR.GNFS.CD Balance on primary income BN.GSR.FCTY.CD Balance on secondary income BN.TRF.CURR.CD Current account balance BN.CAB.XOKA.CD Total reserves Economy States and markets PA.NUS.PPPC.RF Real effective exchange rate GDP implicit delator 4.14 Central government revenues PA.NUS.PPP Ratio of PPP conversion factor to market exchange rate Global links FI.RES.TOTL.CD Back World Development Indicators 2014 69 STATES AND MARKETS 70 World Development Indicators 2014 Front ? User guide World view People Environment States and markets includes indicators of private investment and performance, the role of the public sector in nurturing investment and growth, and the quality and availability of infrastructure essential for growth and development. These indicators measure the business environment, the functions of government, inancial system development, infrastructure, information and communication technology, science and technology, performance of governments and their policies, and conditions in fragile countries with weak institutions. Data on the access to inance, availability of credit, and cost of service improve understanding of the state of inancial development. Credit is an important link in money transmission; it inances production, consumption, and capital formation, which in turn affect economic activity. The availability of credit to households, private companies, and public entities shows the depth of banking and inancial sector development in the economy. In 2012 East Asia and Paciic provided more credit to the private sector, 122 percent of GDP, than did other developing regions. In previous years we have presented both data for total domestic credit and credit to the private sector as a percentage of GDP. Data for the numerator come from the International Monetary Fund (IMF)’s International Financial Statistics database. In 2009 the IMF began publishing a new presentation of monetary statistics for countries that report data in accord with the IMF’s Monetary and Financial Statistics Manual 2000 and its Monetary and Financial Statistics Compilation Guide 2008. The new presentation aligns the reporting of monetary and inancial statistics with the inancial account of the 1993 Economy States and markets System of National Accounts. In this edition we have revised the indicator name to make the dei nition clearer. And more signiicantly we are adding a new indicator, domestic credit to the private sector by banks, to capture the resources that domestic banks provide to private irms. The data on domestic credit provided by inancial sector (previously domestic credit provided by banking sector) are from the inancial corporation survey or, when unavailable, from the depository corporations survey. Similarly, data for domestic credit to the private sector capture the claims on the private sector by inancial corporation or, when unavailable, by depository corporations. The inancial corporations survey includes all resident corporations or quasi-corporations principally engaged in inancial intermediation or in related auxiliary inancial activities. It combines the data for depository corporations (central banks and other depository corporations) and other inancial corporations, such as inance and leasing companies, money lenders, insurance corporations, pension funds, and foreign exchange companies. The newly reported data generally start only in December 2001 and in most cases are slightly higher than the values previously reported in the World Development Indicators database. The IMF is planning soon to issue a combined Monetary and Financial Statistics Manual and Monetary and Financial Statistics Compilation Guide aligned to the 2008 System of National Accounts and the sixth edition of the Balance of Payments and International Investment Position Manual. The latest information, manual, and guidelines can be viewed at the IMF website (http://www.imf.org/external/data.htm#guide). Global links Back 5 World Development Indicators 2014 71 Highlights Major economies are requiring higher capital to asset ratios in banks The ratio of capital to assets measures bank solvency and resiliency— Average bank capital to asset ratio (%) and the extent to which banks can deal with unexpected losses. With 15 banks under stress in the global inancial crisis, the likelihood and cost of bank failures led countries to review their banking regulations. Many major economies have required higher minimum capital ratios to ensure bank capacity to cover liabilities and protect depositors and 10 other lenders. In the United States the average ratio of capital to assets rose to 11.2 percent in 2011, up from 9.3 percent in 2008. Also maintaining higher ratios were euro area countries (6.7 percent) 5 and the United Kingdom (5.1 percent). Japan and Germany, by contrast, kept rates below 5 percent because of their banking 2005 2008 2011 conditions. 0 United States Euro area United Kingdom Canada Japan Germany Source: Online table 5.5. A rising proportion of high-technology exports from developing countries Exports are an engine of industrial competitiveness and economic High-technology exports (% of manufactured exports) growth. And the share of high-technology goods in manufactured 30 exports is a common indicator of the innovation in an economy. In the early 1990s the proportion of high-technology manufactured exports Developed from developed countries was twice the proportion from developing countries. Since then, exports from developing countries have grown 20 rapidly and diversiied, moving away from traditional resource- and labor-intensive products toward high-technology manufacturing. In Developing 2004 the gap between developed and developing countries closed, 10 with both around 21 percent. Shares have since fallen slightly, to 18 percent in developing countries and 17 percent in developed countries in 2012. 0 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 Source: Online table 5.13. Large differences in ixed-broadband Internet penetration across regions Fixed-broadband Internet subscriptions (% of population) After more than a decade of growth, there were about 640 million ixed broadband subscriptions in the world at the end of 2012—a global 30 High income penetration rate of 9 percent. More than 340 million of the subscriptions were in high-income countries—a 26 percent penetration rate. The nearly 300 million subscriptions in low- and middle-income countries indicate very low penetration—about 5 percent. And the differ- 20 ences across regions are large. The lowest rates are in South Asia (1.1 percent) and Sub- Saharan Africa (0.2 percent), and the highest Europe & Central Asia 10 Latin America & Caribbean East Asia & Pacific East Asia and Paciic (9.7 percent) and Latin America and the Caribbean (8 percent). The Middle East and North Africa remains farther Middle East & North Africa Sub-Saharan Africa South Asia rate in Europe and Central Asia (over 10 percent), followed closely by behind, at 3 percent. 0 2001 2003 2005 2007 2009 2011 2012 Source: International Telecommunication Union’s World Telecommunication/ICT indicators database; online table 5.12. 72 World Development Indicators 2014 Front ? User guide World view People Environment Electricity consumption up dramatically in middle-income countries Between 1991 and 2011 electricity consumption increased 82 percent globally and 69 percent in low-income countries. But the share of Electric power consumption (trillions of kilowatt-hours) 15 global electricity consumed by low-income countries remained fairly constant, despite a 60 percent increase in their population, while the High income share consumed by high-income countries dropped from 76 percent to 56 percent. The share consumed by middle-income countries rose 10 Middle income from 24 percent to 43 percent, with China accounting for more than half of that. Middle-income countries also saw per capita consumption increase—by 152 percent, from 721 kilowatt-hours in 1991 to 5 1,816 in 2011. China Low income 0 1991 2001 2011 Source: Online table 5.11. Business tax rates fall in developing countries Taxes fund a range of social and economic programs such as inancing public goods and services and redistributing income to the elderly and Average total corporate tax rate (% of commercial proits) 75 unemployed. According to the Doing Business report, high corporate tax rates are negatively associated with corporate investment and Sub-Saharan Africa Europe & Central Asia entrepreneurship. Between 2004 and 2012 countries in East Asia and Paciic reduced their total tax rates 5 percentage points, leaving Latin America & Caribbean 50 South Asia them with the lowest average rate, 36 percent in 2012. The largest reductions were in Europe and Central Asia (18 percentage points) Middle East & North Africa East Asia & Pacific and Sub- Saharan Africa (19 percentage points). The average rate in the Middle East and North Africa fell from 56 percent in 2004 to 25 43 percent in 2005 but has since dropped only 3 percentage points. South Asia saw an increase in 2009 and 2010, but the average rate fell to 41 percent in 2012. The average rate in Latin America and the 0 2004 Caribbean has changed little. 2005 2006 2007 2008 2009 2010 2011 2012 Source: Online table 5.3. Air carriers from East Asia and Paciic countries take light From 2002 to 2012 global air passenger transport grew 76 percent, to 2.8 billion passengers. While the total number of passengers car- Passengers carried by air (millions) 1,000 ried increased in all regions, the rise for carriers registered in East Asia and the Pacii c was by far the highest. In 2002 the share of global air passenger transport by carriers registered in North America North America 750 was 38 percent, followed by Europe and Central Asia at 26 percent Europe & Central Asia and East Asia and the Paciic with 23 percent. By 2012 North America and East Asia and Pacii c each had 28 percent, with Europe and 500 East Asia & Pacific Central Asia remaining steady at 26 percent. The increase in passenger trafi c by carriers registered in countries in East Asia and the 250 Pacii c has been rapid: from around 425 million in 2002 to 810 milSub-Saharan Africa lion in 2012. South Asia Latin America & Caribbean Middle East & North Africa 0 2000 2002 2004 2006 2008 2010 2012 Source: Online table 5.10. Economy States and markets Global links Back World Development Indicators 2014 73 5 States and markets Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta financial government per capita per 1,000 business sector people days % of GDP 2012 June 2013 % of GDP % of GDP % of GDP kilowatt-hours per 100 people 2012 2012 2011 2012 % of % of manufactured population exports 2012 2012 Afghanistan 0.15 5 .. –4.0 7.5b 3.6 .. 60 5 .. Albania 0.88 5 .. 66.5 .. 1.5 2,022 111 55 0.4 Algeria 2012 2012 0.1 0.53 25 .. –2.1 37.4 4.6 1,091 98 15 American Samoa .. .. .. .. .. .. .. .. .. .. Andorra .. .. .. .. .. .. .. 82 86 .. Angola .. 66 .. 15.9 19.0 b 3.6 248 47 17 .. Antigua and Barbuda .. 21 .. 98.0 19.7b .. .. 143 59 0.0 Argentina 0.47 25 7.2 37.3 0.9 2,967 152 56 7.7 Armenia 1.55 4 1.3 44.2 3.9 1,755 112 39 2.6 10.2 Aruba .. 18.7b .. .. .. 56.0 .. .. .. 132 74 12.16 3 83.9 154.2 21.6 1.7 10,712 106 82 12.7 Austria 0.50 25 26.9 135.0 18.9 0.8 8,374 161 81 12.8 Azerbaijan 0.70 7 .. 24.7 13.0 b 4.6 1,705 109 54 7.3 .. 24 .. 105.0 15.7b .. .. 81 72 0.0 0.2 Australia Bahamas, The Bahrain Bangladesh Barbados .. 9 52.9 73.1 1.1 3.1 10,018 161 88 0.09 11 15.0 69.0 10.0 b 1.3 259 63 6 .. .. 18 106.4 .. .. .. 123 73 12.0 25.2 Belarus 1.14 9 .. 32.2 15.2b 1.2 3,628 114 47 2.9 Belgium 2.48 4 62.1 116.7 25.7 1.1 8,021 111 82 11.4 Belize 4.31 44 .. 63.0 22.6b 0.9 .. 53 25 4.8 Benin .. 15 .. 19.7 15.5 1.0 .. 84 4 0.5 Bermuda .. .. 27.2 .. .. .. .. 140 91 7.3 Bhutan 0.20 32 .. 50.4 .. .. .. 76 25 0.0 Bolivia 0.56 49 16.4 48.7 .. 1.5 623 90 34 9.2 Bosnia and Herzegovina 0.70 37 .. 67.9 20.9 1.4 3,189 88 65 2.5 12.30 60 31.6 14.9 27.2b 2.3 1,603 154 12 1.2 2.17 108 54.6 110.5 15.4b 1.5 2,438 125 50 10.5 12.8 Botswana Brazil Brunei Darussalam .. 101 .. 13.5 2.4 8,507 114 60 Bulgaria 9.03 18 13.1 71.0 19.6b 1.5 4,864 148 55 7.7 Burkina Faso 0.15 13 .. 19.3 16.3 1.4 .. 61 4 5.9 .. .. 2.7 Burundi .. 5 .. 26.1 2.4 .. 23 1 Cabo Verde .. 10 .. 79.7 17.1b 0.5 .. 86 35 0.6 Cambodia .. 104 .. 33.9 11.6 1.5 164 129 5 0.1 .. 15 .. 15.0 .. 1.4 256 60 6 3.7 1.07 5 113.3 .. 11.9 1.3 16,473 80 87 12.4 Cameroon Canada Cayman Islands .. .. .. .. .. .. .. 172 74 .. Central African Republic .. 22 .. 26.3 9.4 2.6 .. 25 3 0.0 Chad .. 62 .. 5.3 .. 2.0 .. 35 2 .. Channel Islands .. .. .. .. .. .. .. .. .. .. 5.69 6 116.1 108.0 18.9 2.0 3,568 138 61 4.6 .. 33 44.9 155.1 10.6 b 2.0 c 3,298 81 42 26.3 28.12 3 420.9 200.6 14.2 .. 5,949 229 73 16.2 .. .. .. –13.0 36.5b .. .. 290 64 0.0 2.00 15 70.9 72.9 13.3 3.3 1,123 103 49 5.2 .. Chile China Hong Kong SAR, China Macao SAR, China Colombia Comoros Congo, Dem. Rep. Congo, Rep. 74 ages 15–64 World Development Indicators 2014 .. 15 .. 21.6 0.02 31 .. 11.1 .. 101 .. –8.9 Front ? .. 13.7b .. User guide .. .. 40 6 1.8 105 31 2 .. 1.1 172 99 6 3.7 World view People Environment States and markets 5 Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta financial government per capita per 1,000 business sector people Costa Rica Côte d’Ivoire ages 15–64 days % of GDP 2012 4.5 2012 June 2013 3.55 24 % of GDP % of GDP % of GDP 2012 2012 2012 53.4 13.7 .. kilowatt-hours per 100 people % of % of manufactured population exports 2011 2012 2012 2012 1,844 112 48 39.6 .. 8 31.7 27.3 15.6 1.7 212 91 2 15.1 2.82 8 36.4 96.3 19.6b 1.7 3,901 115 63 9.9 Cuba .. .. .. .. .. 3.3 1,327 15 26 .. Curaçao .. .. .. .. .. .. .. .. .. .. 13.0 Croatia Cyprus 22.51 8 8.8 347.3 25.5 2.1 4,271 98 61 Czech Republic 2.96 20 18.9 68.4 14.2b 1.1 6,289 127 75 16.1 Denmark 4.36 6 71.3 206.0 34.1 1.4 6,122 118 93 14.2 Djibouti .. 17 .. .. Dominica 3.30 12 .. 62.4 23.4b .. Dominican Republic .. .. 25 8 .. .. .. 152 55 8.8 1.05 19 .. 46.5 12.8 0.6 893 87 45 2.7 Ecuador .. 56 7.0 29.2 .. 2.8 1,192 106 35 2.5 Egypt, Arab Rep. .. 8 22.1 77.7 13.2b 1.7 1,743 120 44 0.6 0.48 17 45.0 66.1 14.5 1.0 830 137 26 4.7 Equatorial Guinea .. 135 .. –3.5 .. .. .. 68 14 .. Eritrea .. 84 .. 104.0 .. .. 49 5 1 .. Estonia 7.92 7 10.4 77.2 16.5 1.9 6,279 160 79 10.7 Ethiopia 2.4 El Salvador 0.03 15 .. .. 9.4b 0.9 52 22 1 Faeroe Islands .. .. .. .. .. .. .. 119 85 .. Fiji .. 59 11.6 116.3 .. 1.5 .. 98 34 2.1 Finland 2.32 14 64.1 105.2 20.7 1.5 15,738 172 91 8.5 France 2.88 7 69.8 136.4 22.0 2.3 7,289 97 83 25.4 2.5 French Polynesia .. .. .. .. .. .. .. 83 53 4.11 50 .. 13.2 .. 1.4 907 179 9 .. .. 27 .. 44.4 .. .. .. 85 12 3.3 Georgia 4.86 2 6.0 35.0 24.1b 2.9 1,918 108 46 2.4 Germany 1.29 15 43.4 122.5 11.9 1.3 7,081 112 84 15.8 Ghana 0.90 14 8.5 32.3 14.9 b 0.3 344 101 17 7.3 Greece 0.77 14 17.9 135.5 22.5 2.6 5,380 120 56 9.2 Gabon Gambia, The Greenland .. .. .. .. Grenada .. 15 .. 95.2 Guam .. .. .. .. Guatemala 0.52 20 .. 39.2 Guinea .. 19.5b .. 10.9b .. .. 105 65 2.4 .. .. 121 42 .. .. .. .. 62 .. 0.4 539 138 16 4.7 .. 0.23 16 .. 32.2 .. .. .. 42 1 Guinea-Bissau .. 9 .. 20.3 .. 2.0 .. 63 3 .. Guyana .. 20 21.4 50.6 .. 1.1 .. 69 33 0.1 0.06 97 .. 19.6 .. .. 32 60 10 .. .. 14 .. 55.9 14.7 1.1 708 93 18 .. 4.75 5 16.9 68.7 23.3 0.8 3,895 116 72 18.1 23.2 0.1 52,374 108 96 14.3 10.7b 2.4 684 70 13 6.6 Haiti Honduras Hungary Iceland 8.17 5 20.8 143.9 India 0.12 27 68.0 75.9 Indonesia 0.29 48 45.2 42.6 .. 0.8 680 114 15 7.3 .. 16 25.5 18.0 .. .. 2,649 76 26 4.1 Iraq 0.13 29 .. –1.8 .. 2.8 1,343 82 7 .. Ireland 4.50 10 51.7 201.7 23.2 0.6 5,701 107 79 22.6 Iran, Islamic Rep. Isle of Man Israel Economy 45.27 .. .. .. .. .. .. .. .. .. 2.96 14 56.1 .. 22.1 5.7 6,926 121 73 15.8 States and markets Global links Back World Development Indicators 2014 75 5 States and markets Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta financial government per capita per 1,000 business sector people days % of GDP 2012 June 2013 % of GDP % of GDP % of GDP kilowatt-hours per 100 people % of % of manufactured population exports 2012 2012 2012 2012 2011 2012 2012 Italy 1.91 6 23.8 167.5 23.2 1.7 5,393 160 58 7.1 Jamaica 1.11 6 43.3 51.8 27.1 0.9 1,553 96 47 0.6 2012 17.4 Japan 1.15 22 61.8 346.1 10.1 1.0 7,848 111 79 Jordan 0.98 12 87.0 114.2 15.3 4.7 2,289 128 41 2.5 Kazakhstan 1.71 12 11.5 41.1 .. 1.2 4,893 186 53 30.0 Kenya 0.84 32 36.3 52.3 19.7b 2.0 155 71 32 5.7 Kiribati 0.11 31 .. .. 16.1b .. .. 16 11 38.5 Korea, Dem. People’s Rep. .. .. .. .. Korea, Rep. 2.03 6 104.5 168.7 Kosovo 1.22 30 .. 21.0 .. .. 2,947 Kuwait .. 32 53.0 47.9 0.7b 3.3 16,122 Kyrgyz Republic 0.92 8 2.5 .. 18.5b 3.7 1,642 Lao PDR 0.10 92 .. 26.5 14.8b 0.2 11.63 13 3.9 62.9 13.8b 0.9 Latvia .. 15.6 b .. 739 7 0 .. 2.8 10,162 109 84 26.2 .. .. .. 157 79 .. 124 22 4.6 .. 65 11 .. 3,264 112 74 9.8 Lebanon .. 9 24.0 176.4 15.6 4.0 3,499 81 61 2.0 Lesotho 1.49 29 .. 3.2 .. 1.9 .. 75 5 .. Liberia .. 5 .. 33.9 0.8 .. 57 4 .. Libya .. 35 .. .. .. 3,926 156 14 .. 25.11 .. .. .. .. .. .. 97 89 .. 4.71 7 9.4 52.0 13.4 1.0 3,530 165 68 10.4 Liechtenstein Lithuania Luxembourg 20.9b .. 20.98 19 127.5 173.6 26.1 0.6 15,530 145 92 8.1 Macedonia, FYR 3.60 2 5.8 48.9 16.6b 1.4 3,881 106 63 3.9 Madagascar 0.05 8 .. 12.9 10.1 0.7 .. 39 2 0.4 Malawi 0.08 40 17.7 35.6 .. 0.9 .. 29 4 3.2 Malaysia 2.28 6 156.2 134.0 16.1b 1.5 4,246 141 66 43.7 Maldives 4.39 9 .. 83.9 15.6 b .. .. 166 39 .. .. 11 .. 19.7 14.6 1.4 .. 98 2 1.2 45.7 Mali Malta 13.61 40 41.6 154.2 27.5 0.6 4,689 127 70 Marshall Islands .. 17 .. .. .. .. .. .. 10 .. Mauritania .. 19 .. 36.8 .. .. .. 106 5 .. Mauritius 7.40 6 67.6 113.7 19.0 0.2 .. 120 41 0.9 Mexico 0.88 6 44.6 47.0 .. 0.6 2,092 83 38 16.3 .. 16 .. –19.1 1.63 7 .. 42.2 Micronesia, Fed. Sts. Moldova Monaco .. .. .. .. Mongolia .. 11 12.6 30.8 10.66 10 87.5 58.7 1.26 11 54.8 115.4 .. 13 .. 29.1 Montenegro Morocco Mozambique Myanmar .. 18.7b .. .. .. 30 26 .. 0.3 1,470 102 43 4.8 .. .. .. 88 87 1.1 1,577 121 16 .. .. 1.9 5,747 181 57 .. 24.5 3.5 826 120 55 6.4 21.8b 0.9 447 36 5 24.7 18.3b .. 72 .. .. Namibia 0.85 66 10.0 49.5 14.9 b Nepal 0.66 17 21.9 67.9 13.8b 1.4 106 60 11 0.3 Netherlands 4.44 4 84.5 216.2 21.1 1.3 7,036 118 93 20.1 10.6 New Caledonia .. .. 110 10 1 0.0 3.1 1,549 95 13 5.3 .. .. .. .. .. .. .. 91 58 15.07 1 46.6 154.0 29.3 1.1 9,399 110 90 9.7 Nicaragua .. 36 .. 44.0 15.0 b 0.6 522 86 14 4.8 Niger .. 17 .. 13.2 1.0 .. 31 1 6.0 Front ? New Zealand 76 ages 15–64 World Development Indicators 2014 .. User guide World view People Environment States and markets 5 Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta financial government per capita per 1,000 business sector people Nigeria Northern Mariana Islands Norway ages 15–64 days % of GDP % of GDP % of GDP % of GDP kilowatt-hours per 100 people 2012 2012 2011 2012 2012 June 2013 2012 2012 0.91 28 21.5 35.6 .. .. .. .. 7.83 7 50.6 .. % of % of manufactured population exports 2012 2012 0.9 149 67 33 1.9 .. .. .. .. .. .. 27.3 1.4 23,174 117 95 18.8 2.7b .. 8 25.7 35.4 2.6b 8.6 6,292 159 60 3.4 0.04 21 19.4 45.8 10.1b 3.1 449 67 10 1.7 .. 28 .. .. .. .. .. 83 .. .. 14.10 6 34.6 89.0 .. .. 1,829 178 45 35.4 Papua New Guinea .. 53 68.4 38.3 .. 0.5 .. 38 2 3.5 Paraguay .. 35 3.8 37.2 12.4b 1.7 1,228 102 27 6.9 Peru 3.83 25 47.5 17.4 15.6b 1.3 1,248 98 38 3.5 Philippines 0.27 35 105.6 50.9 12.9b 1.2 647 107 36 48.9 Poland 0.53 30 36.3 63.8 16.2 1.9 3,832 140 65 7.0 Portugal 3.62 3 30.9 198.9 20.9 1.8 4,848 116 64 4.1 Oman Pakistan Palau Panama Puerto Rico Qatar .. 6 .. .. .. .. 83 51 .. 1.74 9 65.7 77.5 14.7b .. 1.5 15,755 127 88 0.0 Romania 4.12 9 9.4 54.3 18.8 1.3 2,639 105 50 6.4 Russian Federation 4.30 15 43.4 41.5 15.0 4.5 6,486 183 53 8.4 Rwanda 1.07 2 .. .. 13.3b 1.1 .. 50 8 2.5 Samoa 1.04 9 .. 45.3 0.0 b .. .. .. 13 0.1 .. 40 .. .. .. .. .. 115 51 .. 3.75 5 .. 35.1 14.0 .. .. 65 22 14.3 San Marino São Tomé and Príncipe Saudi Arabia .. 21 52.5 –10.5 .. 8.0 8,161 187 54 0.6 Senegal 0.27 6 .. 31.3 19.2 1.5 187 84 19 0.7 Serbia 1.68 12 19.9 62.3 21.5b 2.2 4,474 118 48 .. .. 39 .. 35.5 28.5b 0.8 .. 148 47 .. Sierra Leone 0.32 12 .. 14.0 10.9b 0.7 .. 37 1 .. Singapore 8.04 3 150.8 99.5 14.5b 3.5 8,404 152 74 45.3 Seychelles .. .. .. .. .. .. .. .. .. .. Slovak Republic Sint Maarten 5.11 19 5.1 .. 12.4 1.1 5,348 112 80 9.3 Slovenia 4.36 6 14.3 93.8 17.9b 1.2 6,806 109 70 6.2 .. 9 .. 12.0 .. .. 55 7 87.4 Solomon Islands Somalia .. .. .. .. .. .. .. .. 23 1 .. South Africa 6.54 19 159.3 187.2 26.4 1.2 4,604 131 41 5.5 South Sudan 0.73 17 .. .. .. 9.4 .. 21 .. .. Spain 2.71 23 75.2 225.9 7.3 0.9 5,530 108 72 7.0 Sri Lanka 0.51 8 28.7 48.4 12.0 b 2.4 490 92 18 0.9 St. Kitts and Nevis 5.69 19 85.6 105.6 19.3b .. .. 157 79 0.1 St. Lucia 3.00 15 .. 129.0 24.2b .. .. 126 49 .. .. .. .. .. .. .. .. .. .. 1.37 10 .. 56.8 124 48 0.1 .. 36 .. 24.6 1.63 208 .. 25.4 St. Martin St. Vincent & the Grenadines Sudan Suriname Swaziland .. 22.4b .. 19.4b .. .. .. 143 .. .. 74 d 106 21d 0.7 35 6.5 .. 38 .. 21.1 .. 3.2 .. 65 21 .. Sweden 6.41 16 107.0 145.3 21.5 1.2 14,030 125 94 13.4 Switzerland 2.53 18 171.0 192.9 10.3 0.8 7,928 130 85 25.8 Syrian Arab Republic 0.04 13 .. 47.7 .. 3.9 1,715 59 24 1.3 Tajikistan 0.26 33 .. 13.1 .. .. 1,714 82 15 .. Economy States and markets Global links Back World Development Indicators 2014 77 5 States and markets Business Time Stock market Domestic Tax revenue Military Electric Mobile Individuals High-technology entry required capitalization credit collected expenditures power cellular using the exports density to start a provided by by central consumption subscriptionsa Interneta financial government per capita per 1,000 business sector people ages 15–64 days % of GDP 2012 June 2013 % of GDP % of GDP % of GDP kilowatt-hours per 100 people 2011 2012 % of % of manufactured population exports 2012 2012 2012 2012 26 6.4 24.7 16.1b 1.1 92 57 4 10.2 0.86 28 104.7 169.6 16.5 1.5 2,316 127 27 20.5 2.76 94 .. –52.7 .. 2.9 .. 56 1 .. Togo 0.12 19 .. 37.6 16.8 1.6 .. 50 4 0.2 Tonga 1.91 16 .. 27.3 .. .. 53 35 6.5 .. 38 65.0 37.5 28.3b .. 6,332 141 60 0.1 Tunisia 1.52 11 19.5 82.3 20.8b 1.6 1,297 118 41 5.6 Turkey 1.8 Tanzania .. Thailand Timor-Leste Trinidad and Tobago .. 2012 2012 0.79 6 39.1 71.9 20.4 2.3 2,709 91 45 Turkmenistan .. .. .. .. .. .. 2,444 76 7 .. Turks and Caicos Islands .. .. .. .. .. .. .. .. .. 1.9 Tuvalu .. .. .. .. .. .. 28 35 .. Uganda 1.17 32 36.7 16.3 13.0b 1.4 .. 45 15 20.7 Ukraine 0.92 21 11.7 80.2 18.3b 2.8 3,662 130 34 6.3 United Arab Emirates 1.38 8 17.7 76.5 0.4 5.5 9,389 150 85 .. 11.04 12 122.0 206.7 26.7 2.4 5,472 135 87 21.7 10.2 4.2 13,246 95 81 17.8 19.3b 1.9 2,810 147 55 9.3 .. 1,626 71 37 .. .. .. 59 11 54.0 United Kingdom United States .. .. 5 114.9 229.9 Uruguay 2.98 7 0.4 32.0 Uzbekistan 0.64 9 .. .. Vanuatu 2.34 35 .. 69.5 Venezuela, RB .. 144 6.6 42.0 .. 1.1 3,313 102 44 2.5 Vietnam .. 34 21.1 104.9 .. 2.2 1,073 148 39 14.5 .. 16.1b Virgin Islands (U.S.) .. .. .. .. .. .. .. .. 41 .. West Bank and Gaza .. 45 .. .. .. .. .. 76 41 .. 4.0 193 58 17 0.2 1.6 599 75 13 24.8 757 92 17 89 w 36 w Yemen, Rep. Zambia Zimbabwe World .. 40 .. 26.9 1.36 7 14.6 18.6 .. 90 120.5 75.3 w .. 19.7b .. .. 169.0 w 14.5 w 3.2 2.9 w 3,044 w 5.9 3.83 u 25 u 17.6 w Low income 0.40 29 .. 39.4 12.8 1.7 233 47 6 .. Middle income 2.25 28 48.9 104.7 13.3 3.3 1,816 88 30 18.2 Lower middle income 1.12 26 50.6 62.0 11.5 8.9 734 83 19 8.4 Upper middle income 3.01 30 48.4 116.8 14.0 1.8 2,932 92 42 20.8 Low & middle income 1.86 28 48.6 103.6 13.3 3.3 1,646 82 26 18.1 East Asia & Paciic 1.34 40e 51.5 141.5 11.2 1.9 2,582 89 36 26.5 Europe & Central Asia 2.19 12e 25.6 62.6 19.7 2.0 2,951 108 43 8.2 Latin America & Carib. 2.38 41e 43.3 73.6 .. 1.3 1,985 108 43 11.7 Middle East & N. Africa 0.55 21e 28.9 37.4 .. .. 1,696 95 31 2.2 South Asia 0.25 16e 59.1 71.1 10.6 2.4 605 69 12 6.2 Sub-Saharan Africa 2.09 27e 83.8 77.8 17.3 1.5 535 59 15 4.0 High income 7.47 17 86.8 197.8 14.4 2.7 8,896 123 75 17.3 Euro area 6.75 13 51.6 153.3 17.7 1.5 6,599 120 76 15.2 a. Data are from the International Telecommunication Union’s (ITU) World Telecommunication/ICT Indicators database. Please cite ITU for third party use of these data. b. Data were reported on a cash basis and have been adjusted to the accrual framework of the International Monetary Fund’s Government Finance Statistics Manual 2001. c. Differs from the oficial value published by the government of China (1.3 percent; see National Bureau of Statistics of China, www.stats.gov.cn). d. Excludes South Sudan. e. Differs from data reported on the Doing Business website because the regional aggregates on the Doing Business website include developed economies. 78 World Development Indicators 2014 Front ? User guide World view People Environment States and markets 5 About the data Entrepreneurial activity different estimates, the Doing Business time indicators represent The rate new businesses are added to an economy is a measure of the median values of several responses given under the assumptions its dynamism and entrepreneurial activity. Data on business entry of the standardized case. Fifth, the methodology assumes that a density are from the World Bank’s 2013 Entrepreneurship Database, business has full information on what is required and does not waste which includes indicators for more than 150 countries for 2004–12. time when completing procedures. In constructing the indicators, it is Survey data are used to analyze irm creation, its relationship to assumed that entrepreneurs know about all regulations and comply economic growth and poverty reduction, and the impact of regula- with them. In practice, entrepreneurs may not be aware of all required tory and institutional reforms. Data on total registered businesses procedures or may avoid legally required procedures altogether. were collected from national registrars of companies. For crosscountry comparability, only limited liability corporations that oper- Financial systems ate in the formal sector are included. For additional information on Stock markets and banking systems both enhance growth, the main sources, methodology, calculation of entrepreneurship rates, and factor in poverty reduction. At low levels of economic development com- data limitations see www.doingbusiness.org/data/exploretopics mercial banks tend to dominate the inancial system, while at higher /entrepreneurship. levels domestic stock markets become more active and eficient. 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 inancial markets. The table includes market capitalization property, the lexibility 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 eficient, 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 inancial integration have resulted in more transactions, and others give a higher score for simpliied regulations, cross-border capital lows, a stronger presence of inancial irms 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 irms 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 inancial The indicators are available at www.doingbusiness.org. activity to sustain them. Comparability across countries may be lim- Doing Business data are collected with a standardized survey that uses a simple business case to ensure comparability across econo- ited by conceptual and statistical weaknesses, such as inaccurate reporting and differences in accounting standards. mies and over time—with assumptions about the legal form of the Standard & Poor’s (S&P) Indices provides regular updates on 21 business, its size, its location, and nature of its operation. Surveys emerging stock markets and 36 frontier markets. The S&P Global in 189 countries are administered through more than 10,200 local Equity Indices, S&P Indices’s leading emerging markets index, is experts, including lawyers, business consultants, accountants, designed to be suficiently investable to support index tracking portfo- freight forwarders, government oficials, 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 signiicant differences in the speed of reform category to identify the most signiicant 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 speciic business form—generally currency conversions, especially when a currency has registered a limited liability company of a speciied size—and may not represent a signiicant devaluation (Demirgüç-Kunt and Levine 1996; Beck regulation for other types of businesses such as sole proprietor- and Levine 2001; and Claessens, Klingebiel, and Schmukler 2002). ships. Third, transactions described in a standardized business case Domestic credit provided by the inancial sector as a share of GDP refer to a speciic set of issues and may not represent all the issues measures banking sector depth and inancial sector development in a business encounters. Fourth, the time measures involve an ele- terms of size. Data are taken from the inancial corporation survey ment of judgment by the expert respondents. When sources indicate of the International Monetary Fund’s (IMF) International Financial Economy States and markets Global links Back World Development Indicators 2014 79 5 States and markets Statistics or, when unavailable, from its deposit corporation survey. deinitions and the dificulty of verifying the accuracy and complete- The inancial corporation survey includes monetary authorities (the ness of data, data are not always comparable across countries. central bank), deposit money banks, and other banking institutions, However, SIPRI puts a high priority on ensuring that the data series such as inance companies, development banks, and savings and for each country is comparable over time. More information on loan institutions. In a few countries governments may hold inter- SIPRI’s military expenditure project can be found at www.sipri.org national reserves as deposits in the banking system rather than /contents/milap/. in the central bank. Claims on the central government are a net item (claims on the central government minus central government Infrastructure deposits) and thus may be negative, resulting in a negative value The quality of an economy’s infrastructure, including power and for domestic credit provided by the inancial sector. communications, is an important element in investment decisions and economic development. The International Energy Agency (IEA) Tax revenues collects data on electric power consumption from national energy Taxes are the main source of revenue for most governments. Tax agencies and adjusts the values to meet international deinitions. revenue as a share of GDP provides a quick overview of the iscal Consumption by auxiliary stations, losses in transformers that are obligations and incentives facing the private sector across coun- considered integral parts of those stations, and electricity produced tries. The table shows only central government data, which may by pumping installations are included. Where data are available, signiicantly understate the total tax burden, particularly in countries electricity generated by primary sources of energy—coal, oil, gas, where provincial and municipal governments are large or have con- nuclear, hydro, geothermal, wind, tide and wave, and combustible siderable tax authority. renewables—are included. Consumption data do not capture the Low ratios of tax revenue to GDP may relect weak administration and large-scale tax avoidance or evasion. Low ratios may also relect reliability of supplies, including breakdowns, load factors, and frequency of outages. a sizable parallel economy with unrecorded and undisclosed incomes. The International Telecommunication Union (ITU) estimates that Tax revenue ratios tend to rise with income, with higher income coun- there were 6.3 billion mobile subscriptions globally in 2012. No tries relying on taxes to inance a much broader range of social ser- technology has ever spread faster around the world. Mobile com- vices and social security than lower income countries are able to. munications have a particularly important impact in rural areas. The mobility, ease of use, lexible deployment, and relatively low Military expenditures and declining rollout costs of wireless technologies enable them to Although national defense is an important function of government, reach rural populations with low levels of income and literacy. The high expenditures for defense or civil conlicts burden the economy next billion mobile subscribers will consist mainly of the rural poor. and may impede growth. Military expenditures as a share of GDP Operating companies have traditionally been the main source of are a rough indicator of the portion of national resources used for telecommunications data, so information on subscriptions has been military activities. As an “input” measure, military expenditures are widely available for most countries. This gives a general idea of not directly related to the “output” of military activities, capabilities, access, but a more precise measure is the penetration rate—the or security. Comparisons across countries should take into account share of households with access to telecommunications. During the many factors, including historical and cultural traditions, the length past few years more information on information and communication of borders that need defending, the quality of relations with neigh- technology use has become available from household and business bors, and the role of the armed forces in the body politic. surveys. Also important are data on actual use of telecommunica- Data are from the Stockholm International Peace Research Institute tions services. The quality of data varies among reporting countries (SIPRI), whose primary source of military expenditure data is ofi - as a result of differences in regulations covering data provision and cial data provided by national governments. These data are derived availability. from budget documents, defense white papers, and other public 80 documents from oficial government agencies, including govern- High-technology exports ment responses to questionnaires sent by SIPRI, the United Nations The method for determining high-technology exports was developed Ofice for Disarmament Affairs, or the Organization for Security and by the Organisation for Economic Co-operation and Development in Co-operation in Europe. Secondary sources include international sta- collaboration with Eurostat. It takes a “product approach” (rather tistics, such as those of the North Atlantic Treaty Organization (NATO) than a “sectoral approach”) based on research and development and the IMF’s Government Finance Statistics Yearbook. Other second- intensity (expenditure divided by total sales) for groups of prod- ary sources include country reports of the Economist Intelligence Unit, ucts from Germany, Italy, Japan, the Netherlands, Sweden, and the country reports by IMF staff, and specialist journals and newspapers. United States. Because industrial sectors specializing in a few high- In the many cases where SIPRI cannot make independent esti- technology products may also produce low-technology products, the mates, it uses country-provided data. Because of differences in product approach is more appropriate for international trade. The World Development Indicators 2014 Front ? User guide World view People Environment States and markets 5 method takes only research and development intensity into account, technology. Postpaid subscriptions and active prepaid accounts (that but other characteristics of high technology are also important, such is, accounts that have been used during the last three months) are as knowhow, scientiic personnel, and technology embodied in pat- included. The indicator applies to all mobile cellular subscriptions ents. Considering these characteristics would yield a different list that offer voice communications and excludes subscriptions for data (see Hatzichronoglou 1997). cards or USB modems, subscriptions to public mobile data services, private-trunked mobile radio, telepoint, radio paging, and telemetry Definitions services. • Individuals using the Internet are the percentage of • Business entry density is the number of newly registered limited individuals who have used the Internet (from any location) in the last liability corporations per 1,000 people ages 15–64. • Time required 12 months. Internet can be used via a computer, mobile phone, per- to start a business is the number of calendar days to complete the sonal digital assistant, games machine, digital television, or similar procedures for legally operating a business using the fastest pro- device. • High-technology exports are products with high research cedure, independent of cost. • Stock market capitalization (also and development intensity, such as in aerospace, computers, phar- known as market value) is the share price times the number of shares maceuticals, scientiic instruments, and electrical machinery. outstanding. • Domestic credit provided by financial sector is all credit to various sectors on a gross basis, except to the central Data sources government, which is net. The inancial sector includes monetary Data on business entry density are from the World Bank’s Entre- authorities, deposit money banks, and other banking institutions preneurship Database (www.doingbusiness.org/data/exploretopics for which data are available. • Tax revenue collected by central /entrepreneurship). Data on time required to start a business are government is compulsory transfers to the central government for from the World Bank’s Doing Business project (www.doingbusiness public purposes. Certain compulsory transfers such as ines, penal- .org). Data on stock market capitalization are from Standard & ties, and most social security contributions are excluded. Refunds Poor’s (2012). Data on domestic credit are from the IMF’s Inter- and corrections of erroneously collected tax revenue are treated as national Financial Statistics. Data on central government tax rev- negative revenue. The analytic framework of the IMF’s Government enue are from the IMF’s Government Finance Statistics. Data on Finance Statistics Manual 2001 (GFSM 2001) is based on accrual military expenditures are from SIPRI’s Military Expenditure Database accounting and balance sheets. For countries still reporting govern- (www.sipri.org/databases/milex). Data on electricity consumption ment inance data on a cash basis, the IMF adjusts reported data are from the IEA’s Energy Statistics of Non-OECD Countries, Energy to the GFSM 2001 accrual framework. These countries are foot- Balances of Non-OECD Countries, and Energy Statistics of OECD noted in the table. • Military expenditures are SIPRI data derived Countries and from the United Nations Statistics Division’s Energy from NATO’s former deinition (in use until 2002), which includes Statistics Yearbook. Data on mobile cellular phone subscriptions and all current and capital expenditures on the armed forces, including individuals using the Internet are from the ITU’s World Telecommu- peacekeeping forces; defense ministries and other government agen- nication/ICT Indicators database. Data on high-technology exports cies engaged in defense projects; paramilitary forces, if judged to are from the United Nations Statistics Division’s Commodity Trade be trained and equipped for military operations; and military space (Comtrade) database. activities. Such expenditures include military and civil personnel, including retirement pensions and social services for military per- References sonnel; operation and maintenance; procurement; military research Beck, Thorsten, and Ross Levine. 2001. “Stock Markets, Banks, and and development; and military aid (in the military expenditures of the Growth: Correlation or Causality?” Policy Research Working Paper donor country). Excluded are civil defense and current expenditures 2670, World Bank, Washington, DC. for previous military activities, such as for veterans beneits, demo- Claessens, Stijn, Daniela Klingebiel, and Sergio L. Schmukler. 2002. bilization, and weapons conversion and destruction. This deinition “Explaining the Migration of Stocks from Exchanges in Emerging cannot be applied for all countries, however, since that would require Economies to International Centers.” Policy Research Working Paper more detailed information than is available about military budgets 2816, World Bank, Washington, DC. and off-budget military expenditures (for example, whether military Demirgüç-Kunt, Asli, and Ross Levine. 1996. “Stock Market Devel- budgets cover civil defense, reserves and auxiliary forces, police opment and Financial Intermediaries: Stylized Facts.” World Bank and paramilitary forces, and military pensions). • Electric power Economic Review 10 (2): 291–321. consumption per capita is the production of power plants and com- Hatzichronoglou, Thomas. 1997. “Revision of the High-Technology bined heat and power plants less transmission, distribution, and Sector and Product Classiication.” STI Working Paper 1997/2. transformation losses and own use by heat and power plants, divided Organisation for Economic Co-operation and Development, Direc- by midyear population. • Mobile cellular subscriptions are the number of subscriptions to a public mobile telephone service that provides access to the public switched telephone network using cellular Economy States and markets torate for Science, Technology, and Industry, Paris. Standard & Poors. 2012. Global Stock Markets Factbook 2012. New York. Global links Back World Development Indicators 2014 81 5 States and markets To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/5.1). To view a speciic /indicator/IE.PPI.TELE.CD). 5.1 Private sector in the economy Telecommunications investment IE.PPI.TELE.CD 5.5 Financial access, stability, and efficiency Energy investment IE.PPI.ENGY.CD Strength of legal rights index IC.LGL.CRED.XQ Transport investment IE.PPI.TRAN.CD Depth of credit information index IC.CRD.INFO.XQ Water and sanitation investment IE.PPI.WATR.CD Depositors with commercial banks FB.CBK.DPTR.P3 Domestic credit to private sector FS.AST.PRVT.GD.ZS Borrowers from commercial banks FB.CBK.BRWR.P3 IC.BUS.NREG Commercial bank branches FB.CBK.BRCH.P5 IC.BUS.NDNS.ZS Automated teller machines FB.ATM.TOTL.P5 Bank capital to assets ratio FB.BNK.CAPA.ZS Ratio of bank non-performing loans to total gross loans FB.AST.NPER.ZS Businesses registered, New Businesses registered, Entry density 5.2 Business environment: enterprise surveys Time dealing with oficials IC.GOV.DURS.ZS Number of visits or meetings with tax oficials IC.TAX.METG Time required to obtain operating license IC.FRM.DURS Informal payments to public oficials IC.FRM.CORR.ZS Losses due to theft, robbery, vandalism, and arson IC.FRM.CRIM.ZS Domestic credit to private sector by banks (% of GDP) FR.INR.LNDP Risk premium on lending FR.INR.RISK Firms competing against unregistered irms IC.FRM.CMPU.ZS 5.6 Tax policies Firms with female top manager IC.FRM.FEMM.ZS Tax revenue collected by central government IC.FRM.BNKS.ZS Number of tax payments by businesses Firms using banks to inance investment FD.AST.PRVT.GD.ZS Interest rate spread GC.TAX.TOTL.GD.ZS IC.TAX.PAYM IC.FRM.OUTG.ZS Internationally recognized quality certiication Time for businesses to prepare, ile and pay taxes IC.FRM.ISOC.ZS Business proit tax Average time to clear exports through customs IC.CUS.DURS.EX Business labor tax and contributions IC.TAX.LABR.CP.ZS IC.FRM.TRNG.ZS Other business taxes IC.TAX.OTHR.CP.ZS Value lost due to electrical outages Firms offering formal training IC.TAX.DURS IC.TAX.PRFT.CP.ZS Total business tax rate IC.TAX.TOTL.CP.ZS 5.3 Business environment: Doing Business indicators Number of procedures to start a business IC.REG.PROC 5.7 Military expenditures and arms transfers Time required to start a business IC.REG.DURS Military expenditure, % of GDP Cost to start a business IC.REG.COST.PC.ZS Number of procedures to register property IC.PRP.PROC Time required to register property IC.PRP.DURS Number of procedures to build a warehouse IC.WRH.PROC Time required to build a warehouse IC.WRH.DURS Time required to get electricity IC.ELC.TIME Arm forces personnel MS.MIL.XPRT.KD MS.MIL.MPRT.KD 5.8 Fragile situations IC.LGL.DURS International Development Association Resource Allocation Index IC.ISV.DURS 5.4 Stock markets MS.MIL.TOTL.TF.ZS Arms transfers, Imports Time required to enforce a contract Time required to resolve insolvency MS.MIL.XPND.ZS Arms transfers, Exports IC.LGL.PROC IC.BUS.DISC.XQ MS.MIL.XPND.GD.ZS MS.MIL.TOTL.P1 Arm forces personnel, % of total labor force Number of procedures to enforce a contract Business disclosure index Peacekeeping troops, police, and military observers IQ.CPA.IRAI.XQ VC.PKP.TOTL.UN Battle related deaths VC.BTL.DETH CM.MKT.LCAP.CD Intentional homicides VC.IHR.PSRC.P5 Market capitalization, % of GDP CM.MKT.LCAP.GD.ZS Military expenditures MS.MIL.XPND.GD.ZS Value of shares traded CM.MKT.TRAD.GD.ZS Losses due to theft, robbery, vandalism, and arson IC.FRM.CRIM.ZS Firms formally registered when operations started IC.FRM.FREG.ZS Market capitalization, $ Turnover ratio CM.MKT.TRNR Listed domestic companies CM.MKT.LDOM.NO S&P/Global Equity Indices 82 Military expenditure, % of central government expenditure World Development Indicators 2014 CM.MKT.INDX.ZG Front ? User guide World view People Environment States and markets 5 Children in employment SL.TLF.0714.ZS Refugees, By country of origin Air freight IS.AIR.GOOD.MT.K1 SM.POP.REFG.OR Refugees, By country of asylum SM.POP.REFG Internally displaced persons VC.IDP.TOTL.HE Access to an improved water source SH.H2O.SAFE.ZS Access to improved sanitation facilities SH.STA.ACSN Maternal mortality ratio, National estimate SH.STA.MMRT.NE Maternal mortality ratio, Modeled estimate SH.STA.MMRT Under-ive mortality rate SH.DYN.MORT Depth of food deicit SN.ITK.DFCT SE.PRM.ENRR Primary gross enrollment ratio 5.9 Public policies and institutions International Development Association Resource Allocation Index Macroeconomic management IQ.CPA.IRAI.XQ IQ.CPA.MACR.XQ Fiscal policy IQ.CPA.FISP.XQ Debt policy IQ.CPA.DEBT.XQ Economic management, Average IQ.CPA.ECON.XQ Trade IQ.CPA.TRAD.XQ Financial sector IQ.CPA.FINS.XQ 5.11 Power and communications Electric power consumption per capita Electric power transmission and distribution losses EG.USE.ELEC.KH.PC EG.ELC.LOSS.ZS Fixed telephone subscriptions IT.MLT.MAIN.P2 Mobile cellular subscriptions IT.CEL.SETS.P2 Fixed telephone international voice trafic ..a Mobile cellular network international voice trafic ..a Population covered by mobile cellular network ..a Fixed telephone sub-basket ..a Mobile cellular sub-basket ..a Telecommunications revenue ..a Mobile cellular and ixed-line subscribers per employee ..a 5.12 The information age Households with television ..a Households with a computer ..a Individuals using the Internet ..a Business regulatory environment IQ.CPA.BREG.XQ Fixed (wired) broadband Internet subscriptions IT.NET.BBND.P2 Structural policies, Average IQ.CPA.STRC.XQ International Internet bandwidth ..a Gender equality IQ.CPA.GNDR.XQ Fixed broadband sub-basket ..a Equity of public resource use IQ.CPA.PRES.XQ Secure Internet servers Building human resources IQ.CPA.HRES.XQ 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 Information and communications technology services, Exports BX.GSR.CCIS.ZS Policies for social inclusion and equity, Average IQ.CPA.SOCI.XQ Property rights and rule-based governance IQ.CPA.PROP.XQ Quality of budgetary and inancial management IQ.CPA.FINQ.XQ Eficiency of revenue mobilization IQ.CPA.REVN.XQ Quality of public administration IQ.CPA.PADM.XQ Transparency, accountability, and corruption in the public sector IQ.CPA.TRAN.XQ Public sector management and institutions, Average IQ.CPA.PUBS.XQ Total road network IS.ROD.TOTL.KM Paved roads IS.ROD.PAVE.ZS IS.ROD.PSGR.K6 Road goods hauled IS.ROD.GOOD.MT.K6 Rail lines IS.RRS.TOTL.KM Railway passengers carried IS.RRS.PASG.KM Railway goods hauled Research and development (R&D), Researchers SP.POP.SCIE.RD.P6 Research and development (R&D), Technicians SP.POP.TECH.RD.P6 Scientiic and technical journal articles IP.JRN.ARTC.SC GB.XPD.RSDV.GD.ZS High-technology exports, $ TX.VAL.TECH.CD High-technology exports, % of manufactured exports TX.VAL.TECH.MF.ZS Charges for the use of intellectual property, Receipts BX.GSR.ROYL.CD Charges for the use of intellectual property, Payments BM.GSR.ROYL.CD Patent applications iled, Residents IP.PAT.RESD Patent applications iled, Nonresidents IP.PAT.NRES Trademark applications iled, Total IP.TMK.TOTL IS.RRS.GOOD.MT.K6 Port container trafic IS.SHP.GOOD.TU Registered air carrier departures worldwide IS.AIR.DPRT Air passengers carried IS.AIR.PSGR Economy 5.13 Science and technology Expenditures for R&D 5.10 Transport services Road passengers carried IT.NET.SECR.P6 States and markets Data disaggregated by sex are available in the World Development Indicators database. a. Available online only as part of the table, not as an individual indicator. Global links Back World Development Indicators 2014 83 GLOBAL LINKS 84 World Development Indicators 2014 Front ? User guide World view People Environment The world economy is bound together by trade in goods and services, inancial lows, and movements of people. As national economies develop, their links expand and grow more complex. The indicators in Global links measure the size and direction of these lows and document the effects of policy interventions, such as tariffs, trade facilitation, and aid lows, on the development of the world economy. Volatility in international inancial markets was still prevalent in 2012. Concerns about the sustainability of public inances, inherited from the inancial crisis in the euro area, appear to have affected direct investment. Global foreign direct investment (FDI) inlows dropped 16 percent from 2011. FDI lows to high-income economies dropped 22 percent, with the euro area accounting for almost half the fall. But FDI lows to low- and middle-income economies showed a more moderate decline of only 6 percent. FDI lows to low- and middle-income economies were around $617 billion in 2012, accounting for an increase in the share of world inlows of 17 percentage points over the previous ive years. Although more of these economies receive FDI, the lows remain highly concentrated among the 10 largest recipients, with Brazil, China, and India accounting for more than half. Net debt lows to developing countries fell 9 percent in 2012, to $412 billion, and were characterized by important shifts in borrowing patterns and inancing sources. Viewed from the borrower, net lows of public and publicly guaranteed debt drove the overall increase in long-term debt lows in 2012. They jumped 67 percent to $155 billion, in contrast to a 17 percent fall in Economy States and markets net lows to private nonguaranteed borrowers, and a sharp 41 percent contraction in short-term debt lows. Unlike debt and direct investment, global portfolio equity investment grew in 2012 at a faster pace than had been expected, resulting in equity inlows that were three times higher than in 2011. Inlows to high-income economies in 2012 were well above their 2011 level, attributable mainly to investors’ switching from debt securities to equity. Flows of portfolio equity to low- and middle-income economies also rose considerably, as growth prospects remained good, with high expected returns. The sovereign debt crisis in the euro area continued to restrain international trade. The slowdown of demand for goods from highincome economies, especially euro area economies, slowed the growth in merchandise imports from an annual 19.4 percent in 2011 to 0.4 percent in 2012. The growth of merchandise exports also dropped, by nearly 20 percentage points. But merchandise exports to low- and middle-income countries rose 4.4 percent from the previous year, while those to high-income countries fell 0.8 percent. Brazil, China, India, and the Russian Federation are among the top traders, with China accounting for almost 70 percent of the total merchandise trade in East Asia and Paciic. Oficial development assistance—a stable source of development inancing and buffer against the impact of several inancial crises— was $133 billion in 2012, or 0.59 percent of developing countries’ combined gross national income, down from 0.66 percent in 2011. Global links Back 6 World Development Indicators 2014 85 Highlights Bond issuance rises Bond issuance from public and private borrowers in developing econo- Bond issuance by developing country borrowers ($ billions) 150 125 mies rose to a record $226 billion in 2012, up from $175 billion in All developing, private nonguaranteed All developing, public and publicly guaranteed Latin America & Caribbean, private nonguaranteed Latin America & Caribbean, public and publicly guaranteed Europe & Central Asia, private nonguaranteed Europe & Central Asia, public and publicly guaranteed 2011. The increase was driven mainly by new bond issuances from the public sector, which rose 30 percent in 2012 as emerging economies continued to diversify risk away from banks and pursue different sources of inancing after the 2008 crisis. Inluenced by purchases of 100 Mexico’s domestically issued sovereign bonds by nonresidents, Latin 75 America and the Caribbean held the largest share, 39 percent, while Europe and Central Asia accounted for the second largest share, 50 25 percent. Private borrowers also saw an increase in bond issuances, but at a more moderate rate of 11 percent in 2012, to $88.1 billion. 25 Private borrowers in Latin America and the Caribbean also claimed the largest share, with Mexico and Brazil dominant bond issuers. 0 2005 2006 2007 2008 2009 2010 2011 2012 Source: Online table 6.9. Europe and Central Asia: remittances are more resilient than foreign direct investment Inlows of remittances and foreign direct investment, Europe and Central Asia (% of GDP) 12 Inlows of personal remittances yet again proved resilient to economic downturns in Europe and Central Asia, especially when compared with inl ows of foreign direct investment (FDI). Personal remittances received as a percentage of GDP continued a slow but steady path of 10 growth, up 1.5 percent in 2012. Despite signs of recovery in 2011, Foreign direct investment FDI inlows as a percentage of GDP fell 15 percent in 2012, showing 8 that the region had not fully recovered from the inancial crisis. The 6 high volatility of FDI inlows is not evident in remittances, where lows have proven more resilient to economic shocks. The greater persis- 4 tence in remittances has proven beneicial for countries in the region that rely heavily on inlows of remittances for economic stability, such 2 Personal remittances as the Kyrgyz Republic, Moldova, and Tajikistan. 0 2007 2008 2009 2010 2011 2012 Source: Online tables 6.9 and 6.13. Capital equity investment in India turns around in 2012 The Indian economy saw net capital equity inlows in 2012 rise 44 per- Equity investment lows to India ($ billions) cent, or 2.7 percent of GDP (up from 1.7 percent in 2011). Direct invest- 50 ment inlows in 2012 relected the country’s slow economic growth and Foreign direct investment high inlation rate, which shook investor conidence. Even though foreign direct investment lows fell by a third in 2012 to $24 billion, the lowest since 2005, India remained the third most important developing country 25 destination for investment lows, after China and Brazil. The downturn was partly offset by a considerable turnaround in portfolio equity lows. In January 2012 India began allowing qualiied foreign investors to invest 0 directly in the Indian stock market. Portfolio equity investment inlows shot up to a remarkable $23 billion from a depletion of $40 billion in Portfolio equity 2011, thanks mainly to qualiied foreign investor purchases of equities in the Indian stock market. –25 2005 2006 2007 2008 2009 2010 2011 2012 Source: Online table 6.9. 86 World Development Indicators 2014 Front ? User guide World view People Environment Debt indicators improve in Europe and Central Asia Europe and Central Asia, the most indebted region, recorded the highest external debt outstanding ratio to gross national income Debt ratios for Europe and Central Asia (%) 200 (GNI), 68.3 percent, in 2012—three times the comparable ratio for all developing countries combined. Similarly, external debt stock as a percentage of exports at the end of 2012, 144.7 percent, was 150 twice the developing country average. But despite a mild deteriora- External debt stock to exports tion in 2012, the ratio of external debt stock to GNI has declined 12 percentage points since 2009 while the ratio of external debt 100 stock to exports declined 23 percentage points. The main drivers of growth and higher export earnings are the oil exporters, notably External debt stock to GNI 50 Kazakhstan and Turkey, followed by Hungary and Ukraine. Investment Debt service to exports in Kazakhstan’s hydrocarbon sector in 2012 tremendously increased production and exports. 0 2007 2008 2009 2010 2011 2012 Source: Online table 6.8. The Syrian refugee population continues to rise The refugee population by country of origin has remained fairly steady since 2004 among developing countries. For over a decade ive coun- Refugee population by origin, top ive (millions) 3 tries accounted for more than 50 percent of refugees from developing countries: Afghanistan, Somalia, Iraq, Sudan, and the Democratic Republic of Congo. But conlict in Middle East and North Africa has changed that. In 2011 the Syrian Arab Republic was ranked 32nd, with 2 fewer than 20,000 refugees, but by 2012 the number of refugees leeing the country had grown 35 times to almost 730,000, fourth highest among developing countries. And the increase is expected to continue. According to the Ofice of the UN High Commissioner for Refugees 1 0 2012 surrounding countries in the irst half of 2013. 2011 (2013), an estimated 1.3 million people from Syria sought refuge in Sudan Syrian Arab Republic Iraq Somalia Afghanistan Source: Online table 6.13. Commodity prices fall in 2013 Except for energy, commodity price indexes continued to fall in 2013. In real terms (2005) the biggest declines were in fertilizers (16 percent) Change in commodity price indices (%) 50 Fertilizers Precious metals Agriculture Metals and minerals Energy and precious metals (16 percent), followed by agriculture (6 percent) and metals and minerals (4 percent). Even though fertilizer prices have more than doubled from a decade ago, the price index has declined 46 percent from its peak in 2008 (from 197 to 107). Energy and fertil- 25 izer prices typically move together because natural gas is a key input for fertilizer. But the correlation has reversed with U.S. natural gas trading at 80 percent below crude oil. Precious metals saw their irst 0 price decline in 11 years in 2013. The gold market, driven mainly by China and India, has fallen due to India’s restrictions on gold imports. China, despite overtaking India as the world’s largest gold consumer, is not expected to offset the weak physical demand from India (World –25 2010 Bank 2014). 2011 2012 2013 Source: Online table 6.5. Economy States and markets Global links Back World Development Indicators 2014 87 6 Global links Merchandise Net barter Inbound Net official Net Personal trade terms of tourism development migration remittances, trade index expenditure assistance received Portfolio equity Total external debt stock Total debt service % of GDP 2000 = 100 % of exports % of GNI thousands $ millions Net inlow $ millions Net inlow $ millions $ millions % of exports of goods, services, and primary income 2012 2012 2012 2012 2010–15 2012 2012 2012 2012 2012 Afghanistan 32.0 139.1 3.2 32.8 –400 385 94 2 2,709 Albania 54.2 96.2 45.9 2.7 –50 1,027 1,265 13 6,934 7.1 Algeria 58.7 217.3 0.4 0.1 –50 213 1,602 .. 5,643 1.1 American Samoa .. 129.0 .. .. .. .. .. .. .. .. Andorra .. .. .. .. .. .. .. .. .. .. Angola 85.0 257.6 1.0 0.2 66 0 –6,898 .. 22,171 5.9 Antigua and Barbuda 51.6 64.2 .. 0.2 0 21 71 .. .. .. Argentina 31.5 130.3 5.9 0.0 –100 573 12,128 876 121,013 13.2 Armenia 57.2 117.6 20.1 2.6 –50 2,123 489 2 7,608 30.9 .. 122.0 44.9 .. 1 5 –140 0 .. .. 33.8 184.8 11.0 .. 750 1,827 56,595 15,174 .. .. Aruba Australia 0.3 Austria 87.3 86.9 9.9 .. 150 2,754 4,144 936 .. .. Azerbaijan 63.5 199.9 7.2 0.6 0 1,990 5,293 0 9,712 5.1 54.6 88.5 65.7 .. 10 .. 360 .. .. .. 116.6 129.0 7.6 .. 22 .. 891 1,383 .. .. 5.4 Bahamas, The Bahrain Bangladesh 50.9 59.2 0.4 1.7 –2,041 14,085 1,178 91 26,130 Barbados 55.4 107.6 .. .. 2 .. 356 .. .. .. Belarus 146.0 100.7 1.9 0.2 –10 1,053 1,464 –4 34,173 9.5 Belgium 182.3 94.2 3.1 .. 150 10,123 –1,917 4,570 .. .. .. 93.8 28.7 .. 8 76 194 .. 1,241 11.3 Benin 47.6 117.9 .. 6.8 –10 .. 159 .. 2,055 .. Bermuda 16.8 62.1 32.6 .. .. 1,191 133 –10 .. .. Bhutan 90.5 134.3 13.5 9.6 10 18 10 .. 1,459 17.8 Bolivia 70.3 179.1 4.8 2.6 –125 1,111 1,060 .. 6,909 5.3 Bosnia and Herzegovina 86.9 98.8 12.8 3.2 –5 1,849 350 .. 10,577 18.4 Botswana 96.5 85.0 0.5 0.5 20 18 293 –9 2,488 0.8 Brazil 21.1 128.9 2.4 0.1 –190 2,583 76,111 5,600 440,478 15.5 Brunei Darussalam 100.0 226.5 .. .. 2 .. 850 .. .. .. Bulgaria 116.6 107.4 12.4 .. –50 1,449 2,095 5 50,750 13.0 Burkina Faso 51.3 126.9 .. 10.8 –125 .. 40 .. 2,506 .. Burundi 36.8 149.1 1.2 21.2 –20 46 1 .. 663 8.5 Belize Cabo Verde 44.8 108.9 60.6 13.3 –17 167 74 .. 1,261 4.6 Cambodia 136.8 75.2 23.4 6.1 –175 256 1,557 .. 5,716 1.5 Cameroon 45.8 156.6 5.1 2.4 –50 210 526 0 3,672 3.1 Canada 52.2 118.5 3.8 .. 1,100 1,206 43,085 949 .. .. .. 82.9 .. .. .. .. 4,234 .. .. .. Central African Republic 24.3 68.8 .. 10.4 10 .. 71 .. 552 .. Chad 50.4 220.6 .. 4.9 –120 .. 323 .. 1,831 .. .. .. .. .. 4 .. .. .. .. .. Chile 58.6 182.4 3.5 0.0 30 .. 30,323 5,222 .. .. China 47.0 71.8 2.5 0.0 –1,500 39,221 253,475 29,903 754,009 3.3 .. Cayman Islands Channel Islands Hong Kong SAR, China 397.9 96.0 6.7 .. 150 368 74,584 25,006 .. 23.2 92.9 94.2 .. 35 46 4,261 .. .. .. Colombia 32.3 151.1 4.9 0.2 –120 4,019 15,649 3,778 79,051 22.0 Comoros 54.5 80.3 .. 11.5 –10 .. 17 .. 251 .. Congo, Dem. Rep. 72.1 143.1 .. 17.8 –75 12 2,892 .. 5,651 3.2 118.4 221.0 .. 1.3 –45 .. 2,758 .. 2,829 .. Macao SAR, China Congo, Rep. 88 Foreign direct investment World Development Indicators 2014 Front ? User guide World view People Environment Global links 6 Merchandise Net barter Inbound Net official Net Personal trade terms of tourism development migration remittances, trade index expenditure assistance received Foreign direct investment Portfolio equity Total external debt stock Total debt service $ millions % of exports of goods, services, and primary income 2012 2012 14,458 17.6 % of GDP 2000 = 100 % of exports % of GNI thousands $ millions Net inlow $ millions Net inlow $ millions 2012 2012 2012 2012 2010–15 2012 2012 2012 Costa Rica 64.2 77.7 20.0 0.1 64 562 2,636 .. Côte d’Ivoire 89.7 144.3 .. 11.1 50 .. 478 .. 9,871 .. Croatia 55.9 98.1 36.2 .. –20 1,437 1,395 –174 .. .. Cuba .. 144.6 .. .. –140 .. .. .. .. .. Curaçao .. .. .. .. 14 30 57 .. .. .. Cyprus 39.8 94.2 27.8 .. 35 112 1,247 742 .. .. 151.3 101.0 5.2 .. 200 2,026 10,581 –148 .. .. 63.2 99.8 3.6 .. 75 1,257 1,269 4,784 .. .. .. 82.0 4.6 .. –16 33 110 .. 808 8.8 Dominica 49.0 103.1 57.2 5.5 .. 23 20 .. 284 10.0 Dominican Republic 45.0 91.5 39.3 0.5 –140 3,615 3,857 .. 16,851 14.0 Ecuador 58.5 134.7 3.9 0.2 –30 2,456 591 5 16,931 9.8 Egypt, Arab Rep. 37.7 156.2 22.3 0.7 –216 19,236 2,798 –983 40,000 6.6 El Salvador 65.4 90.2 14.7 1.0 –225 3,927 467 .. 13,279 18.7 121.5 244.8 .. 0.1 20 .. 2,115 .. .. .. 45.9 98.5 .. 4.4 55 .. 74 .. 994 .. Czech Republic Denmark Djibouti Equatorial Guinea Eritrea Estonia 150.9 93.9 7.9 .. 0 401 1,648 –151 .. .. Ethiopia 36.1 130.6 33.0 7.9 –60 624 279 .. 10,462 7.2 Faeroe Islands .. 104.0 .. .. .. .. .. .. .. .. Fiji 86.8 108.1 40.5 2.9 –29 191 267 .. 732 .. Finland 60.1 87.1 5.3 .. 50 866 4,332 3,097 .. .. France 47.6 88.8 8.3 .. 650 21,676 28,122 36,077 .. .. .. .. 78.7 .. .. –1 .. 87 .. .. Gabon French Polynesia 86.5 226.0 .. 0.4 5 .. 702 .. 2,870 .. Gambia, The 52.9 92.1 29.6 15.9 –13 141 34 .. 513 7.1 Georgia 64.9 134.2 26.0 4.2 –125 1,770 831 74 13,426 23.3 Germany 75.1 95.3 3.0 .. 550 13,964 27,221 –3,746 .. .. Ghana 73.7 172.2 6.9 4.7 –100 138 3,295 .. 12,436 4.2 Greece 37.9 87.2 21.0 .. 50 681 1,663 –66 .. .. .. 79.0 .. .. .. .. .. .. .. .. 48.3 91.1 56.8 1.1 –4 29 30 .. 591 7.7 .. 81.1 .. .. 0 .. .. .. .. .. 54.0 87.7 11.3 0.6 –75 5,035 1,150 .. 14,975 10.9 Guinea 65.7 103.7 0.1 6.5 –10 66 605 .. 1,097 7.0 Guinea-Bissau 46.2 81.6 .. 9.6 –10 .. 16 .. 279 .. 112.3 128.3 3.8 4.0 –33 469 276 .. 1,974 8.7 Greenland Grenada Guam Guatemala Guyana Haiti 46.2 67.9 16.3 16.1 –175 1,612 179 .. 1,154 0.3 Honduras 103.6 84.3 10.0 3.3 –50 2,909 1,068 .. 4,987 13.8 Hungary 84.6 159.8 92.6 5.3 .. 75 2,144 9,356 1,137 203,757 Iceland 72.4 87.3 10.7 .. 5 19 1,086 –3 .. .. India 42.1 127.4 4.1 0.1 –2,294 68,821 23,996 22,809 379,099 6.8 Indonesia 43.1 129.2 4.5 0.0 –700 7,212 19,618 1,698 254,899 17.1 Iran, Islamic Rep. 27.5 194.5 .. .. –300 .. 4,870 .. 11,477 .. Iraq 70.1 227.1 1.7 0.6 450 271 3,400 7 .. .. Ireland 85.1 92.7 4.0 .. 50 700 40,962 105,422 .. .. Isle of Man .. .. .. .. .. .. .. .. .. .. Israel .. 97.6 6.7 .. –76 685 9,481 290 .. .. Economy States and markets Global links Back World Development Indicators 2014 89 6 Global links Merchandise Net barter Inbound Net official Net Personal trade terms of tourism development migration remittances, trade index expenditure assistance received Portfolio equity Total external debt stock Total debt service % of GDP 2000 = 100 % of exports % of GNI thousands $ millions Net inlow $ millions Net inlow $ millions $ millions % of exports of goods, services, and primary income 2012 2012 2012 2012 2010–15 2012 2012 2012 2012 2012 Italy 48.9 94.8 7.4 .. 900 7,326 6,686 20,835 .. .. Jamaica 56.3 87.1 46.8 0.1 –80 2,145 229 –1 14,333 38.2 Japan 28.3 60.5 1.8 .. 350 2,540 2,525 34,941 .. .. Jordan 92.1 83.7 33.0 4.6 400 3,574 1,497 53 18,632 6.9 Kazakhstan 67.2 231.3 1.6 0.1 0 171 15,117 –418 137,014 23.5 Kenya 55.1 89.9 18.2 6.5 –50 1,214 259 26 11,569 5.1 Kiribati 62.9 96.6 .. 25.0 –1 .. –2 .. .. .. .. 85.9 .. .. 0 .. 79 .. .. .. 94.5 61.8 3.0 .. 300 8,474 4,999 16,925 .. .. 8.8 Korea, Dem. People’s Rep. Korea, Rep. Kosovo .. .. .. 8.9 .. 1,059 293 1 2,002 Kuwait 80.2 227.8 0.6 .. 300 8 1,851 –41 .. .. 112.2 108.2 23.8 7.8 –175 2,031 372 0 6,026 10.9 8.2 Kyrgyz Republic Lao PDR 54.2 109.4 16.2 4.6 –75 59 294 6 6,372 109.2 102.9 6.3 .. –10 730 1,076 4 .. .. Lebanon 64.2 97.9 22.6 1.7 500 6,918 3,678 –239 28,950 14.2 Lesotho 151.2 77.7 4.4 10.3 –20 554 198 .. 860 2.3 Liberia 88.0 138.6 .. 36.1 –20 .. 1,354 .. 487 .. Libya .. 201.4 .. .. –239 .. .. .. .. .. Liechtenstein .. .. .. .. .. .. .. .. .. .. 145.6 93.2 4.0 .. –28 1,508 574 –51 .. .. 84.7 75.8 5.2 .. 26 1,681 27,878 161,691 .. .. 15.1 Latvia Lithuania Luxembourg Macedonia, FYR 109.4 88.7 5.5 1.6 –5 394 283 –6 6,678 Madagascar 45.6 80.2 .. 3.9 –5 .. 895 .. 2,896 .. Malawi 85.6 95.9 2.7 28.4 0 28 129 1 1,314 2.0 Malaysia 139.0 101.3 7.6 0.0 450 1,320 9,734 .. 103,950 3.5 Maldives 84.1 102.0 79.9 3.1 0 3 284 0 1,027 3.8 Mali Malta Marshall Islands Mauritania 49.1 172.1 .. 10.2 –302 .. 310 .. 3,073 .. 115.9 125.9 15.9 .. 5 33 599 3 .. .. 95.9 106.4 .. 34.7 .. .. 38 .. .. .. 126.2 153.1 .. 10.0 –20 .. 1,204 .. 3,348 4.9 Mauritius 74.9 70.9 29.2 1.7 0 1 361 6,840 4,459 2.4 Mexico 63.8 109.1 3.4 0.0 –1,200 23,366 15,453 10,038 354,897 17.7 Micronesia, Fed. Sts. Moldova Monaco Mongolia 75.1 98.3 .. 33.5 –8 .. 1 .. .. .. 101.7 101.5 10.6 6.1 –103 1,786 185 14 6,135 15.1 .. .. .. .. .. .. .. .. .. .. 108.3 206.0 9.0 4.7 –15 320 4,452 15 5,080 4.5 Montenegro 64.2 .. 50.3 2.3 –3 333 618 0 2,833 13.6 Morocco 68.3 145.4 26.3 1.6 –450 6,508 2,842 –108 33,816 11.2 Mozambique 76.5 100.2 5.8 14.8 –25 220 5,238 .. 4,788 1.6 .. 112.8 .. .. –100 .. 2,243 .. 2,563 .. Namibia 83.0 122.9 .. 2.1 –3 .. 357 .. .. .. Nepal 39.3 77.7 19.6 4.0 –401 4,793 92 .. 3,818 10.3 161.8 93.1 3.2 .. 50 1,617 6,684 3,674 .. .. .. 195.9 .. .. 6 .. 1,588 .. .. .. New Zealand 44.1 129.4 10.7 .. 75 .. 2,209 442 .. .. Nicaragua 81.2 82.4 8.5 5.2 –120 1,016 805 0 8,858 12.3 Niger 65.0 169.0 .. 13.5 –28 .. 793 .. 2,340 .. Myanmar Netherlands New Caledonia 90 Foreign direct investment World Development Indicators 2014 Front ? User guide World view People Environment Global links 6 Merchandise Net barter Inbound Net official Net Personal trade terms of tourism development migration remittances, trade index expenditure assistance received Nigeria Northern Mariana Islands Norway Oman Foreign direct investment Portfolio equity Total external debt stock Total debt service % of GDP 2000 = 100 % of exports % of GNI thousands $ millions Net inlow $ millions Net inlow $ millions $ millions % of exports of goods, services, and primary income 2012 2012 2012 2012 2010–15 2012 2012 2012 2012 2012 62.8 221.8 0.7 0.8 –300 20,633 7,101 10,003 10,077 0.3 .. 84.8 .. .. .. .. 5 .. .. .. 49.4 161.6 2.6 .. 150 767 22,951 965 .. .. 103.7 244.2 3.2 .. 1,030 39 1,514 1,373 .. .. 14.9 Pakistan 30.5 53.9 3.2 0.9 –1,634 14,007 854 178 61,867 Palau 64.4 105.3 .. 7.3 .. .. 5 .. .. .. 108.7 86.2 13.6 0.2 29 402 3,383 .. 12,294 8.7 Papua New Guinea 76.7 193.1 .. 4.4 0 .. 29 .. 23,128 .. Paraguay 73.5 110.5 2.1 0.4 –40 634 363 .. 6,331 6.3 Peru 43.3 163.7 6.5 0.2 –300 2,788 12,244 –32 54,148 12.5 Philippines 46.9 65.6 7.6 0.0 –700 24,641 2,797 1,728 61,390 8.0 Poland 77.5 97.1 5.2 .. –38 6,935 6,701 3,888 .. .. Portugal 61.4 91.3 17.6 .. 100 3,904 13,377 –8,518 .. .. .. .. .. .. –104 .. .. .. .. .. 85.5 217.8 5.1 .. 500 803 327 –925 .. .. 34.2 Panama Puerto Rico Qatar Romania 75.5 110.7 3.0 .. –45 3,674 2,024 403 131,889 Russian Federation 42.9 248.9 3.0 .. 1,100 5,788 50,661 1,162 .. .. Rwanda 34.8 214.9 33.2 12.5 –45 182 160 7 1,269 2.2 Samoa 61.7 81.1 61.1 18.6 –13 159 24 .. 423 5.3 .. .. .. .. .. .. .. .. .. .. 57.3 106.8 50.4 18.7 –2 6 22 .. 202 6.9 Saudi Arabia 74.6 215.5 2.1 .. 300 246 12,182 .. .. .. Senegal 63.7 109.1 .. 7.8 –100 .. 338 .. 4,900 .. Serbia 81.0 104.2 7.0 3.0 –100 2,763 355 –24 34,438 36.7 114.9 78.1 2.8 3.3 –2 1 12 .. 2,024 64.3 63.2 58.1 3.1 11.7 –21 61 548 7 1,121 1.5 286.9 80.6 3.5 .. 400 .. 56,651 2,851 .. .. .. .. .. .. .. 13 14 .. .. .. .. San Marino São Tomé and Príncipe Seychelles Sierra Leone Singapore Sint Maarten Slovak Republic 174.7 92.3 2.7 .. 15 1,928 1,527 0 .. Slovenia 141.3 94.2 8.3 .. 22 644 –227 149 .. .. 96.2 89.7 10.5 43.6 –12 17 68 .. 228 4.5 Solomon Islands Somalia South Africa South Sudan .. 107.8 .. .. –150 .. 107 .. 3,055 .. 54.6 145.5 9.8 0.3 –100 1,085 4,644 –679 137,501 7.9 .. .. .. 17.0 865 .. .. .. .. .. Spain 47.2 88.5 14.8 .. 600 9,633 36,161 9,819 .. .. Sri Lanka 48.1 75.0 12.9 0.8 –317 6,000 898 305 25,382 13.3 St. Kitts and Nevis 35.9 71.4 37.5 3.0 .. 45 100 .. .. .. St. Lucia 71.9 91.4 56.9 2.2 0 30 109 .. 473 6.9 St. Martin .. .. .. .. .. .. .. .. .. .. St. Vincent & the Grenadines 55.3 107.4 48.5 1.2 –5 30 125 .. 267 16.6 Sudan 20.8 .. 19.4 1.7a 401 2,488 2 21,840 8.9 Suriname 83.8 134.8 2.9 0.8 –5 8 66 .. .. .. Swaziland 102.8 110.2 .. 2.6 –6 31 90 .. 460 2.2 –800a Sweden 63.9 92.3 5.0 .. 200 812 4,039 3,968 .. .. Switzerland 67.1 80.3 4.8 .. 320 3,039 2,748 14,554 .. .. .. 146.8 .. .. –1,500 .. .. .. 4,736 .. 67.3 99.3 3.7 5.2 –100 3,626 198 .. 3,648 25.5 Syrian Arab Republic Tajikistan Economy States and markets Global links Back World Development Indicators 2014 91 6 Global links Merchandise Net barter Inbound Net official Net Personal trade terms of tourism development migration remittances, trade index expenditure assistance received Foreign direct investment Portfolio equity Total external debt stock Total debt service $ millions % of exports of goods, services, and primary income 2012 2012 % of GDP 2000 = 100 % of exports % of GNI thousands $ millions Net inlow $ millions Net inlow $ millions 2012 2012 2012 2012 2010–15 2012 2012 2012 Tanzania 58.8 145.2 18.8 10.1 –150 67 1,707 4 11,581 1.9 Thailand 130.4 93.2 13.7 0.0 100 4,713 10,689 2,663 134,223 4.1 Timor-Leste 29.5 .. 20.5 5.8 –75 114 19 .. .. .. Togo 73.4 28.7 .. 7.2 –10 .. 166 .. 754 .. 7.8 Tonga 47.9 81.9 .. 16.1 –8 60 8 .. 197 Trinidad and Tobago 96.5 156.9 .. .. –15 .. 2,527 .. .. .. Tunisia 90.8 97.1 13.2 2.3 –33 2,266 1,554 –15 25,475 11.5 Turkey 49.3 87.2 15.6 0.4 350 1,015 12,519 6,274 337,492 26.1 Turkmenistan 73.1 238.5 .. 0.1 –25 .. 3,159 .. 492 .. .. 68.4 .. .. .. .. .. .. .. .. Turks and Caicos Islands Tuvalu 63.4 .. .. 42.3 .. .. .. .. .. .. Uganda 41.6 110.0 23.4 8.5 –150 733 1,721 5 3,769 1.4 31.5 Ukraine United Arab Emirates United Kingdom 86.9 118.1 6.9 0.4 –40 8,449 7,833 516 135,067 135.5 186.1 .. .. 514 .. 9,602 .. .. .. 46.4 99.4 6.0 .. 900 1,776 56,136 –27,555 .. .. United States 23.9 94.7 9.0 .. 5,000 6,285 203,790 232,063 .. .. Uruguay 40.8 104.2 16.7 0.0 –30 97 2,907 .. .. .. Uzbekistan 43.2 172.1 .. 0.5 –200 .. 1,094 .. 8,853 .. Vanuatu 44.5 88.0 76.5 13.6 0 22 38 .. 369 2.1 Venezuela, RB 41.3 262.1 0.9 0.0 40 118 2,199 –50 72,097 5.6 146.6 100.5 5.5 2.8 –200 .. 8,368 1,887 59,133 4.4 Virgin Islands (U.S.) .. .. .. .. –4 .. .. .. .. .. West Bank and Gaza .. .. .. .. –44 .. .. .. .. .. Yemen, Rep. 57.5 167.7 .. 2.1 –135 .. 349 .. 7,555 .. Zambia 80.4 183.6 1.6 4.9 –40 73 1,066 26 5,385 2.2 Zimbabwe 83.7 105.0 .. 10.6 400 .. 400 .. 7,713 .. 50.8 .. 0 478,461 1,509,565 776,000 .. .. Vietnam World 5.8b 0.2c Low income 55.1 .. 12.4 8.0 –3,647 30,184 24,291 142 134,345 4.8 Middle income 50.5 .. 5.3 0.2 –13,345 320,209 592,608 104,290 4,695,263 9.9 Lower middle income 51.1 .. 6.3 0.8 –11,030 199,670 103,112 38,172 1,273,289 9.7 Upper middle income 50.4 .. 5.1 0.1 –2,314 120,539 489,495 66,118 3,421,974 10.0 Low & middle income 50.6 .. 5.4 0.6 –16,991 350,393 616,899 104,432 4,829,608 9.8 East Asia & Paciic 54.2 .. 4.4 0.1 –3,061 78,304 313,801 37,899 1,412,411 4.5 Europe & Central Asia 72.6 .. 8.6 0.6 –661 38,706 65,194 7,988 1,149,505 32.9 Latin America & Carib. 38.2 .. 4.7 0.2 –3,017 59,537 150,393 20,214 1,257,876 15.0 Middle East & N. Africa 47.5 .. 11.0 .. –1,632 39,019 22,699 –1,286 177,092 3.9 South Asia 41.5 .. 4.5 0.6 –7,076 108,112 27,405 23,386 501,491 7.3 Sub-Saharan Africa 61.6 .. 6.6 3.8 –1,545 26,715 37,406 16,232 331,234 4.5 High income 50.9 .. 5.9 0.0 16,941 128,067 892,666 671,568 .. .. Euro area 72.1 .. 6.1 0.0 3,402 78,775 201,185 334,538 .. .. a. Excludes South Sudan. b. Calculated using the World Bank’s weighted aggregation methodology (see Statistical methods) and thus may differ from data reported by the World Tourism Organization. c. Based on the World Bank classiication of economies and thus may differ from data reported by the Organisation for Economic Co-operation and Development. 92 World Development Indicators 2014 Front ? User guide World view People Environment Global links 6 About the data Starting with World Development Indicators 2013, the World Bank Official development assistance changed its presentation of balance of payments data to conform Data on oficial 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 relect 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 postconlict 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 i nancial dependency on aid. Care must be taken in drawing policy conclu- transactions related to merchandise trade recorded in the balance sions. For foreign policy reasons some countries have traditionally of payments. Because of differences in timing and dei nitions, received large amounts of aid. Thus aid dependency ratios may trade l ow estimates from customs reports and balance of pay- reveal as much about a donor’s interests as about a recipient’s ments may differ. Several international agencies process trade needs. Increases in aid dependency ratios can relect 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 classiications of economies and therefore may differ from the ratio of the export price index to the import price index. When a those reported by the OECD. country’s net barter terms of trade index increases, its exports have become more expensive or its imports cheaper. Migration and personal remittances The movement of people, most often through migration, is a signii - Tourism cant part of global integration. Migrants contribute to the economies Tourism is deined as the activity of people traveling to and staying of both their host country and their country of origin. Yet reliable sta- in places outside their usual environment for no more than one year tistics on migration are dificult to collect and are often incomplete, for leisure, business, and other purposes not related to an activity making international comparisons a challenge. remunerated from within the place visited. Data on inbound and Since data on emigrant stock is dificult for countries to collect, outbound tourists refer to the number of arrivals and departures, the United Nations Population Division provides data on net migra- not to the number of unique individuals. Thus a person who makes tion, taking into account the past migration history of a country or several trips to a country during a given period is counted each area, the migration policy of a country, and the inlux of refugees time as a new arrival. Data on inbound tourism show the arrivals of in recent periods to derive estimates of net migration. The data to nonresident tourists (overnight visitors) at national borders. When calculate these estimates come from various sources, including data on international tourists are unavailable or incomplete, the border statistics, administrative records, surveys, and censuses. table shows the arrivals of international visitors, which include tour- When there are insuficient data, net migration is derived through ists, same-day visitors, cruise passengers, and crew members. The the difference between the growth rate of a country’s population aggregates are calculated using the World Bank’s weighted aggrega- over a certain period and the rate of natural increase of that popu- tion methodology (see Statistical methods) and differ from the World lation (itself being the difference between the birth rate and the Tourism Organization’s aggregates. death rate). For tourism expenditure, the World Tourism Organization uses bal- Migrants often send funds back to their home countries, which are ance of payments data from the IMF supplemented by data from recorded as personal transfers in the balance of payments. Personal individual countries. These data, shown in the table, include travel transfers thus include all current transfers between resident and and passenger transport items as deined by the BPM6. When the nonresident individuals, independent of the source of income of the IMF does not report data on passenger transport items, expenditure sender (irrespective of whether the sender receives income from data for travel items are shown. labor, entrepreneurial or property income, social benei ts, or any Economy States and markets Global links Back World Development Indicators 2014 93 6 Global links other types of transfers or disposes of assets) and the relationship by different parties during their lives. Negotiability allows investors between the households (irrespective of whether they are related to diversify their portfolios and to withdraw their investment read- or unrelated individuals). ily. Included in portfolio investment are investment fund shares or Compensation of employees refers to the income of border, units (that is, those issued by investment funds) that are evidenced seasonal, and other short-term workers who are employed in an by securities and that are not reserve assets or direct investment. economy where they are not resident and of residents employed by Although they are negotiable instruments, exchange-traded inancial nonresident entities. Compensation of employees has three main derivatives are not included in portfolio investment because they components: wages and salaries in cash, wages and salaries in are in their own category. kind, and employers’ social contributions. Personal remittances are the sum of personal transfers and compensation of employees. External debt External indebtedness affects a country’s creditworthiness and 94 Equity flows investor perceptions. Data on external debt are gathered through the Equity lows comprise foreign direct investment (FDI) and portfolio World Bank’s Debtor Reporting System (DRS). Indebtedness is cal- equity. The internationally accepted deinition 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 inlu- on short-term debt collected by the countries, from creditors through ence; investment in indirectly inluenced 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 oficial lending agencies in major credi- ship results in a direct investment relationship, based on control tor countries. Currently, 124 developing countries report to the DRS. and inluence. Debt data are reported in the currency of repayment and compiled Direct investments may take the form of greenield 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 igures (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 lows. 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 deinition of long-term loans differs among countries. private nonguaranteed debt are reported annually in aggregate by Portfolio equity investment is deined 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. World Development Indicators 2014 Front ? User guide World view People Environment Global links 6 Definitions Data sources • Merchandise trade includes all trade in goods and excludes Data on merchandise trade are from the World Trade Organization. trade in services. • Net barter terms of trade index is the percent- Data on trade indexes are from the United Nations Conference on age ratio of the export unit value indexes to the import unit value Trade and Development’s (UNCTAD) annual Handbook of Statistics. indexes, measured relative to the base year 2000. • Inbound tour- Data on tourism expenditure are from the World Tourism Organiza- ism expenditure is expenditures by international inbound visitors, tion’s Yearbook of Tourism Statistics and World Tourism Organization including payments to national carriers for international transport (2013) and updated from its electronic iles. Data on net oficial and any other prepayment made for goods or services received in development assistance are compiled by the OECD (http://stats the destination country. They may include receipts from same-day .oecd.org). Data on net migration are from United Nations Population visitors, except when these are important enough to justify sepa- Division (2013). Data on personal remittances are from the IMF’s rate classii cation. Data include travel and passenger transport Balance of Payments Statistics Yearbook supplemented by World Bank items as deined by BPM6. When passenger transport items are staff estimates. Data on FDI are World Bank staff estimates based not reported, expenditure data for travel items are shown. Exports on IMF balance of payments statistics and UNCTAD data (http:// refer to all transactions between residents of a country and the rest unctadstat.unctad.org/ReportFolders/reportFolders.aspx). Data on of the world involving a change of ownership from residents to non- portfolio equity are from the IMF’s Balance of Payments Statistics residents of general merchandise, goods sent for processing and Yearbook. Data on external debt are mainly from reports to the World repairs, nonmonetary gold, and services. • Net official development Bank through its DRS from member countries that have received assistance is lows (net of repayment of principal) that meet the DAC International Bank for Reconstruction and Development loans or deinition of oficial development assistance and are made to coun- International Development Assistance credits, with additional infor- tries and territories on the DAC list of aid recipients, divided by World mation from the iles of the World Bank, the IMF, the African Develop- Bank estimates of GNI. • Net migration is the net total of migrants ment Bank and African Development Fund, the Asian Development (immigrants less emigrants, including both citizens and noncitizens) Bank and Asian Development Fund, and the Inter-American Devel- during the period. Data are ive-year estimates. • Personal remit- opment Bank. Summary tables of the external debt of developing tances, received, are the sum of personal transfers (current trans- countries are published annually in the World Bank’s International fers in cash or in kind made or received by resident households to Debt Statistics and International Debt Statistics database. or from nonresident households) and compensation of employees (remuneration for the labor input to the production process contrib- References uted by an individual in an employer-employee relationship with the IMF (International Monetary Fund). Various issues. International Finan- enterprise). • Foreign direct investment is cross-border investment associated with a resident in one economy having control or a signii cant degree of inluence on the management of an enterprise that is resident in another economy. • Portfolio equity is net inlows from equity securities other than those recorded as direct investment or reserve assets, including shares, stocks, depository receipts, and direct purchases of shares in local stock markets by foreign inves- cial Statistics. Washington, DC. ———. Various years. Balance of Payments Statistics Yearbook. Parts 1 and 2. Washington, DC. UNCTAD (United Nations Conference on Trade and Development). Various years. Handbook of Statistics. New York and Geneva. UNHCR (Ofice of the UN High Commissioner for Refugees). 2013. UNHCR Mid-Year Trends 2013. Geneva. tors • Total external debt stock is debt owed to nonresident credi- United Nations Population Division. 2013. World Population Prospects: tors and repayable in foreign currency, goods, or services by public The 2012 Revision. New York: United Nations, Department of Eco- and private entities in the country. It is the sum of long-term external debt, short-term debt, and use of IMF credit. • Total debt service is the sum of principal repayments and interest actually paid in foreign nomic and Social Affairs. World Bank. 2014. Global Economic Prospects: Commodity Market Outlook. January 2014. Washington, DC. currency, goods, or services on long-term debt; interest paid on ———. Various years. International Debt Statistics. Washington, DC. short-term debt; and repayments (repurchases and charges) to the World Tourism Organization. 2013. Compendium of Tourism Statistics IMF. Exports of goods and services and primary income are the total value of exports of goods and services, receipts of compensation of nonresident workers, and primary investment income from abroad. Economy States and markets 2013. Madrid. ———. Various years. Yearbook of Tourism Statistics. Vols. 1 and 2. Madrid. Global links Back World Development Indicators 2014 95 6 Global links Online tables and indicators To access the World Development Indicators online tables, use indicator online, use the URL http://data.worldbank.org/indicator/ the URL http://wdi.worldbank.org/table/ and the table number (for and the indicator code (for example, http://data.worldbank.org example, http://wdi.worldbank.org/table/6.1). To view a speciic /indicator/TX.QTY.MRCH.XD.WD). 6.1 Growth of merchandise trade Export volume TX.QTY.MRCH.XD.WD Import volume TM.QTY.MRCH.XD.WD Export value TX.VAL.MRCH.XD.WD Import value TM.VAL.MRCH.XD.WD Net barter terms of trade index TT.PRI.MRCH.XD.WD 6.2 Direction and growth of merchandise trade This table provides estimates of the low of trade in goods between groups of economies. 6.3 High-income economy trade with low- and middle-income economies ..a 6.4 Direction of trade of developing economies Exports to developing economies within region TX.VAL.MRCH.WR.ZS Exports to developing economies outside region TX.VAL.MRCH.OR.ZS Exports to high-income economies TX.VAL.MRCH.HI.ZS Imports from developing economies within region TM.VAL.MRCH.WR.ZS Imports from developing economies outside region TM.VAL.MRCH.OR.ZS Imports from high-income economies LP.EXP.DURS.MD Lead time to import LP.IMP.DURS.MD Documents to export IC.EXP.DOCS Documents to import IC.IMP.DOCS Liner shipping connectivity index Quality of port infrastructure TM.VAL.MRCH.HI.ZS IQ.WEF.PORT.XQ Total external debt, $ DT.DOD.DECT.CD Total external debt, % of GNI DT.DOD.DECT.GN.ZS Long-term debt, Public and publicly guaranteed DT.DOD.DPPG.CD Long-term debt, Private nonguaranteed DT.DOD.DPNG.CD Short-term debt, $ DT.DOD.DSTC.CD Short-term debt, % of total debt 6.5 Primary commodity prices ..a DT.DOD.DSTC.IR.ZS Total debt service DT.TDS.DECT.EX.ZS Present value of debt, % of GNI DT.DOD.PVLX.GN.ZS Present value of debt, % of exports of goods, services and primary income DT.DOD.PVLX.EX.ZS 6.9 Global private financial flows Foreign direct investment net inlows, $ BX.KLT.DINV.CD.WD Foreign direct investment net inlows, % of GDP BX.KLT.DINV.WD.GD.ZS BX.PEF.TOTL.CD.WD Bonds DT.NFL.BOND.CD Commercial banks and other lendings DT.NFL.PCBO.CD 6.10 Net official financial flows 6.6 Tariff barriers All products, Binding coverage TM.TAX.MRCH.BC.ZS Simple mean bound rate TM.TAX.MRCH.BR.ZS Simple mean tariff TM.TAX.MRCH.SM.AR.ZS Weighted mean tariff TM.TAX.MRCH.WM.AR.ZS Share of tariff lines with international peaks TM.TAX.MRCH.IP.ZS Net inancial lows from bilateral sources DT.NFL.BLAT.CD Net inancial lows from multilateral sources DT.NFL.MLAT.CD World Bank, IDA DT.NFL.MIDA.CD World Bank, IBRD DT.NFL.MIBR.CD IMF, Concessional DT.NFL.IMFC.CD IMF, Non concessional DT.NFL.IMFN.CD Regional development banks, Concessional DT.NFL.RDBC.CD Manufactured products, Simple mean tariff TM.TAX.MANF.SM.AR.ZS Regional development banks, Nonconcessional DT.NFL.RDBN.CD Manufactured products, Weighted mean tariff Regional development banks, Other institutions DT.NFL.MOTH.CD Share of tariff lines with speciic rates TM.TAX.MRCH.SR.ZS Primary products, Simple mean tariff TM.TAX.TCOM.SM.AR.ZS Primary products, Weighted mean tariff TM.TAX.TCOM.WM.AR.ZS TM.TAX.MANF.WM.AR.ZS 6.7 Trade facilitation 6.11 Aid dependency Logistics performance index LP.LPI.OVRL.XQ Burden of customs procedures 96 DT.DOD.DSTC.ZS Short-term debt, % of total reserves Portfolio equity This table provides historical commodity price data. IS.SHP.GCNW.XQ 6.8 External debt ..a This table illustrates the importance of developing economies in the global trading system. Lead time to export World Development Indicators 2014 IQ.WEF.CUST.XQ Front ? User guide Net oficial development assistance (ODA) Net ODA per capita World view DT.ODA.ODAT.CD DT.ODA.ODAT.PC.ZS People Environment Global links 6 Grants, excluding technical cooperation BX.GRT.EXTA.CD.WD Technical cooperation grants BX.GRT.TECH.CD.WD Net ODA, % of GNI DT.ODA.ODAT.GN.ZS Net ODA, % of gross capital formation Net ODA, % of imports of goods and services and income DT.ODA.ODAT.GI.ZS DT.ODA.ODAT.MP.ZS 6.13 Movement of people Net migration SM.POP.NETM International migrant stock SM.POP.TOTL Emigration rate of tertiary educated to OECD countries Refugees by country of origin SM.POP.REFG.OR Refugees by country of asylum Net ODA, % of central government expenditure DT.ODA.ODAT.XP.ZS SM.EMI.TERT.ZS SM.POP.REFG Personal remittances, Received BX.TRF.PWKR.CD.DT Personal remittances, Paid BM.TRF.PWKR.CD.DT 6.12 Distribution of net aid by Development Assistance Committee members 6.14 Travel and tourism Net bilateral aid lows from DAC donors DC.DAC.TOTL.CD International inbound tourists United States DC.DAC.USAL.CD International outbound tourists ST.INT.DPRT EU institutions DC.DAC.CECL.CD Inbound tourism expenditure, $ ST.INT.RCPT.CD Germany DC.DAC.DEUL.CD Inbound tourism expenditure, % of exports France DC.DAC.FRAL.CD Outbound tourism expenditure, $ United Kingdom DC.DAC.GBRL.CD Outbound tourism expenditure, % of imports Japan DC.DAC.JPNL.CD Netherlands DC.DAC.NLDL.CD Australia DC.DAC.AUSL.CD Canada DC.DAC.CANL.CD Sweden DC.DAC.SWEL.CD ST.INT.RCPT.XP.ZS ST.INT.XPND.CD ST.INT.XPND.MP.ZS a. Available online only as part of the table, not as an individual indicator. b. Derived from data elsewhere in the World Development Indicators database. ..a,b Other DAC donors Economy ST.INT.ARVL States and markets Global links Back World Development Indicators 2014 97 98 World Development Indicators 2014 Front ? User guide World view People Environment Primary data documentation As a major user of development data, the World Bank recognizes the importance of data documentation to inform users of the methods and conventions used by primary data collectors— usually national statistical agencies, central banks, and customs services—and by international organizations, which compile the statistics that appear in the World Development Indicators database. This section provides information on sources, methods, and reporting standards of the principal demographic, economic, and environmental indicators in World Development Indicators. Additional documentation is available online in the World Development Indicators database and from the World Bank’s Bulletin Board on Statistical Capacity at http://data.worldbank.org. The demand for good-quality statistical data is ever increasing. Statistics provide the evidence needed to improve decisionmaking, document results, and heighten public accountability. However, differences among data collectors may give rise to large discrepancies over time, both within and across countries. Data relevant at the Economy States and markets national level may not be suitable for standardized international use due to methodological concerns or the lack of clear documentation. Delays in reporting data and the use of old surveys as the base for current estimates may further compromise the quality of data reported. To meet these challenges and improve the quality of data disseminated, the World Bank works closely with other international agencies, regional development banks, donors, and other partners to • Develop appropriate frameworks, guidance, and standards of good practice for statistics. • Build consensus and deine internationally agreed indicators, such as those for the Millennium Development Goals and the post2015 development agenda. • Establish data exchange processes and methods. • Help countries improve their statistical capacity. More information on these activities and other data programs is available at http://data worldbank.org. Global links Back World Development Indicators 2014 99 Primary data documentation Currency National accounts System of SNA Reference National price year Accounts valuation Base year Afghanistan Albania Algeria American Samoa Andorra Angola Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas, The Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina Botswana Brazil Brunei Darussalam Bulgaria Burkina Faso Burundi Cabo Verde Cambodia Cameroon Canada Cayman Islands Central African Republic Chad Channel Islands Chile China Hong Kong SAR, China Macao SAR, China Colombia Comoros Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d'Ivoire Croatia Cuba Curaçao Cyprus Czech Republic 100 Afghan afghani 2002/03 a Albanian lek Algerian dinar 1980 U.S. dollar Euro 1990 Angolan kwanza 2002 East Caribbean dollar 2006 Argentine peso 1993 a Armenian dram Aruban lorin 2000 a Australian dollar Euro 2005 New Azeri manat 2000 Bahamian dollar 2006 Bahraini dinar 1985 Bangladeshi taka 1995/96 Barbados dollar 1974 a Belarusian rubel Euro 2005 Belize dollar 2000 CFA franc 1985 Bermuda dollar 2006 Bhutanese ngultrum 2000 Bolivian Boliviano 1990 a Bosnia and Herzegovina convertible mark Botswana pula 2006 Brazilian real 2000 Brunei dollar 2000 a Bulgarian lev CFA franc Burundi franc Cabo Verde escudo Cambodian riel CFA franc Canadian dollar Cayman Islands dollar CFA franc CFA franc Pound sterling Chilean peso Chinese yuan Hong Kong dollar Macao pataca Colombian peso Comorian franc Congolese franc CFA franc Costa Rican colon CFA franc Croatian kuna Cuban peso Netherlands Antilles guilder Euro Czech koruna World Development Indicators 2014 1999 2005 2007 2000 2000 2005 2007 2000 2005 2003 2008 2000 a 1996 1993 1993 1968 1968 1968 1993 1968 1993 1993 1993 2008 1993 1993 1993 1968 1993 1968 1993 1993 1993 1968 1993 1993 1968 1993 P B B B B B B B B P B B B B B P B B B B 2002 1993 1993 1993 1993 B B P B 1993 1993 1993 1993 1993 2008 1993 1968 1993 1968 1993 1993 2008 1993 1993 1968 1968 1968 1993 1968 1993 1993 1993 B B P B B B 1996 1996 2011 2000 2007 2011 2011 2005 1990 2000 1990 1991 1996 a 2005 2005 a 2000 2005 Front 1993 1993 ? Balance of payments and trade Balance of Payments Manual in use External debt System of trade Accounting concept Rolling 6 6 A A A C B B G G G 1991–96 2005 1971–84 1990–95 2005 2005 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 B B C C G G S S C C C B B C B C C B B S S G G G G G S S G G A A A G G S S S S G S S S G S G G G G G G S G S G G G S C C C G G G 6 6 A A G G S S B C C G S G S G S G S S G G S S B C B B B C G G G G G S B G G S S G G G S S S S S G S C C C C C C C C B C S G S G S G G G S G S C C S S Alternative conversion factor B B B B B B B P B B B P B P B P B B B B User guide Government IMF data inance dissemination standard PPP survey year 2011 Rolling 1992–95 2005 2005 2005 1990–95 2005 Rolling 1992 2005 1960–85 2005 2005 Rolling A A A A A A A A 2005 2005 2005 1978–89, Rolling 1991–92 1992–93 2005 2005 2005 2005 2005 2011 6 A 6 6 6 6 6 6 A A A A A 2005 2005 6 6 A P 2011 2005 2005 2005 2005 2005 2005 2005 6 6 6 6 6 1978–93 1992–94 1999–2001 1993 2005 Rolling 6 6 6 6 6 Rolling Rolling 6 6 World view P A A A P A E G S People Environment Latest population census Afghanistan Albania Algeria American Samoa Andorra Angola Antigua and Barbuda Argentina Armenia Aruba Australia Austria Azerbaijan Bahamas, The Bahrain Bangladesh Barbados Belarus Belgium Belize Benin Bermuda Bhutan Bolivia Bosnia and Herzegovina 1979 2011 2008 2010 2011b 1970 2011 2010 2011 2010 2011 2011b 2009 2010 2010 2011 2010 2009 2011 2010 2013 2010 2005 2012 2013 Botswana Brazil Brunei Darussalam Bulgaria 2011 2010 2011 2011 Burkina Faso Burundi Cabo Verde Cambodia Cameroon Canada Cayman Islands Central African Republic Chad Channel Islands Chile China Hong Kong SAR, China Macao SAR, China Colombia Comoros Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Curaçao Cyprus Czech Republic Economy 2006 2008 2010 2008 2005 2011 2010 2003 2009 2009/11d 2012 2010 2011f 2011 2006 2003 1984 2007 2011 1998 2011 2012 2011 2011 Latest demographic, education, or health household survey MICS, 2010/11 DHS, 2008/09 MICS, 2012 Source of most recent income and expenditure data Vital Latest Latest registration agricultural industrial complete census data IHS, 2008 LSMS, 2012 IHS, 1995 Yes Yes Yes MIS, 2011 IHS, 2008 MICS, 2011/12 DHS, 2010 IHS, 2012 IHS, 2012 DHS, 2006 ES/BS, 1994 IS, 2000 ES/BS, 2012 Yes Yes Yes Yes Yes Yes Yes 2013/14 2012 2010 MICS, 2011 DHS, 2011/12 IHS, 2010 Yes Yes Yes ES/BS, 2012 IHS, 2000 ES/BS, 2011 CWIQ, 2011 IHS, 2012 IHS, 2009 LSMS, 2007 DHS, 1988 WHS, 2003 ES/BS, 2009/10 IHS, 2012 LSMS, 2007 ES/BS, 2007 2011 2010 2015 2002 2010 2009 2010 2008 2010 c 2010 2009 2009 2011/12 DHS, 2010 MIS, 2012 DHS, 2005 DHS, 2010 DHS, 2011 CWIQ, 2009 CWIQ, 2006 ES/BS, 2007 IHS, 2011 PS, 2007 LFS, 2000 MICS, 2010 MICS, 2010 PS, 2008 PS, 2002/03 NSS, 2007 IHS, 2011 IHS, 2008 2009 2013 2001 2011c 2006 2010 2010 2010 Yes Yes Yes Yes Yes IHS, 2012 IHS, 2004 1-2-3, 2004/05 CWIQ/PS, 2011 IHS, 2012 IHS, 2008 ES/BS, 2008 WHS, 2003 IS, 1996 States and markets Global links Yes Yes Yes Yes Back 2000 2002 2005 2003 2008 2005 2000 2007 2000 2001 2008 2000 2009 2000 2002 2010 2011 2012 2012 2012 2012 2012 2001 2000 2001 2006 2000 1986 2011 1995 2005 2005 2008 2007 2010 2010 2010 2012 2012 2012 2012 2012 2009 2007 2005 2013 2014 2014 2010 2009 2010 2010 2012 2012 2012 2006 2000 1999 2005 2002 1997 2005 2010 2007 2010 2010 2010 2007 2012 2012 2009 2007 2014 2013 2011 2007 2007 2013 Yes 2005 2005 2000 2007 2010 Yes Yes DHS, 2010 DHS, 2012 DHS, 2013 DHS, 2011/12 MICS, 2011 DHS, 2011/12 WHS, 2003 MICS, 2010/11 2012 2012 2012 2012 2012 2012 2012 2012 2011 2007 2012 2012 2012 2012 2010 2012 2011 2012 2012 2000 2006 1994 2009 2010/11 Yese Yes 2000 2006 2001 2012 2012 2012 2012 2010 Yes 2012 2012 2012 2006 2015 2007 2013 2013/14 Yes MICS, 2010 DHS, 2008 MICS, 2011/12 Latest water withdrawal data 2007 Yes DHS, 2011 MICS, 2012 MICS, 2012 Latest trade data World Development Indicators 2014 101 Primary data documentation Currency National accounts System of SNA Reference National price year Accounts valuation Base year Denmark Djibouti Dominica Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Faeroe Islands Fiji Finland France French Polynesia Gabon Gambia, The Georgia Germany Ghana Greece Greenland Grenada Guam Guatemala Guinea Guinea-Bissau Guyana Haiti Honduras Hungary Iceland India Indonesia Iran, Islamic Rep. Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Danish krone Djibouti franc East Caribbean dollar Dominican peso U.S. dollar Egyptian pound U.S. dollar CFA franc Eritrean nakfa Euro Ethiopian birr Danish krone Fijian dollar Euro Euro CFP franc CFA franc Gambian dalasi Georgian lari Euro New Ghanaian cedi Euro Danish krone East Caribbean dollar U.S. dollar Guatemalan quetzal Guinean franc CFA franc Guyana dollar Haitian gourde Honduran lempira Hungarian forint Iceland krona Indian rupee Indonesian rupiah Iranian rial Iraqi dinar Euro Pound sterling Israeli new shekel Euro Jamaican dollar Japanese yen Jordanian dinar Kazakh tenge Kenyan shilling Kiribati Korea, Dem. People’s Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Australian dollar Democratic People's Republic of Korean won Korean won Euro Kuwaiti dinar Kyrgyz som Lao kip Latvian lats Lebanese pound Lesotho loti 102 World Development Indicators 2014 2005 1990 2006 1991 2007 1991/92 1990 2000 2000 2005 2011 2005 2005 a 2005 1990/91 1991 2004 a 1996 2005 2006 a 2005 1990 2006 2001 2003 2005 2006 1986/87 2000 a 2005 2005 2004/05 2000 1997/98 1988 2005 2003 2005 2005 2007 2005 1994 a 2000 2001 1993 1968 1993 1993 2008 1993 1968 1968 1968 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1968 1993 1993 1993 1993 1993 1968 1993 1993 1993 1993 1993 1993 1968 1993 1968 1993 1993 1993 1993 1968 1993 1993 B B B B B B B B B B B B B B B P P B B B B B B B B B B B B B P B P B P B B B B B B 1993 1968 B 2005 2008 1995 1993 1993 1968 1993 1993 1993 1993 1993 B B P B B B B B 1995 2002 2000 1997 2004 Front ? Alternative conversion factor PPP survey year External debt System of trade Accounting concept 6 6 6 6 6 6 6 S G S G G G S G C A A A A A A Rolling 2005 2005 2005 1965–84 2005 2005 Rolling Rolling 6 6 6 6 6 6 6 2005 2005 1990–95 2005 Rolling 1973–87 2005 Rolling 6 6 6 6 6 6 A A A 6 A 6 6 6 6 6 6 6 6 6 6 6 6 6 E E E A A A A 1987–95 Rolling 2005 1993 User guide 2005 2005 1991 1988–89 Rolling Rolling 2005 2005 1980–2002 2005 1997, 2004 2005 Rolling 2011 Rolling 1987–95 Government IMF data inance dissemination standard Balance of Payments Manual in use B 2006 a Balance of payments and trade 2011 2005 2005 2005 6 6 6 6 6 6 6 E A A P A A A A A A A 6 6 2011 B C B C C B 6 S G G G G S S S G G S G S G S G S S G S G S S G G S S C B S G B C C G S S B C C B C G G S S G S B G B B G G G G G G S S S S G G S C C C C B C G C S S G G G G G C C C C C B S S G S S S G G B G G C S S S S G G B B B C B C S G G S A 2005 2005 2005 1987–95 Rolling 2005 2005 1990–95 World view 6 6 6 6 6 6 S G G G S S S A P A A People S G G Environment Latest population census Denmark Djibouti Dominica Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Equatorial Guinea Eritrea Estonia Ethiopia Faeroe Islands Fiji Finland France French Polynesia Gabon Gambia, The Georgia Germany Ghana Greece Greenland Grenada Guam Guatemala Guinea Guinea-Bissau Guyana Haiti Honduras Hungary Iceland India Indonesia Iran, Islamic Rep. Iraq Ireland Isle of Man Israel Italy Jamaica Japan Jordan Kazakhstan Kenya 2011 2009 2011 2010 2010 2006 2007 2002 1984 2012 2007 2011 2007 2010 2006g 2007 2013 2013 2002 2011 2010 2011 2010 2011 2010 2002 1996 2009 2012 2003 2013 2011 2011 2011 2010 2011 1997 2011 2011 2009 2012 2011 2010 2004 2009 2009 Kiribati Korea, Dem. People’s Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho 2010 2008 Economy 2010 2011 2011 2009 2005 2011 1970 2006 Latest demographic, education, or health household survey Source of most recent income and expenditure data MICS, 2006 ITR, 1997 PS, 2002 DHS, 2013 RHS, 2004 DHS, 2008 RHS, 2008 DHS, 2011 DHS, 2002 WHS, 2003 DHS, 2011 IHS, 2012 IHS, 2012 ES/BS, 2011 IHS, 2012 PS, 2006 PS, 1993 ES/BS, 2004 ES/BS, 2010/11 Vital Latest Latest registration agricultural industrial complete census data Yes 2010 2009 Yes Yes 2012/13 2013/15 2009/10 2007/08 2008 2010 Yes 2010 2010 2010 2009 Yes Yes Yes Yes Yes 2009 2010 2010 2009 2009 2009 2010 2013/14 2009 2004 2010 2009 2003 2007 Yes ES/BS, 2009 IS, 2000 ES/BS, 1994/95 DHS, 2012 DHS, 2013 MICS, 2005; RHS, 2005 MICS, 2011 CWIQ/IHS, 2005 IHS, 2010 IHS, 2011 IHS, 2000 LSMS, 2005/06 IHS, 2000 Yes Yes Yes Yes Yes Yes Yes RHS, 1985 RHS, 2008/09 DHS, 2012 MICS, 2010 DHS, 2009 HIV/MCH SPA, 2013 DHS, 2011/12 WHS, 2003 LSMS, 2011 CWIQ, 2012 CWIQ, 2010 IHS, 1998 IHS, 2001 IHS, 2010 ES/BS, 2007 DHS, 2005/06 DHS, 2012 DHS, 2000 MICS, 2011 IHS, 2012 IHS, 2013 ES/BS, 2005 IHS, 2007 IHS, 2000 MICS, 2011 DHS, 2012 MICS, 2010/11 MIS, 2010; HIV/MCH SPA, 2010 Yes Yes Yes Yes Yes Yes Yes ES/BS, 2001 ES/BS, 2000 LSMS, 2010 IS, 1993 ES/BS, 2010 ES/BS, 2012 IHS, 2005/06 Yes 2012 2007 2013 2008/09 2013 2010 2010 2011 2013 2013 2011/12 2010 2010 2007 2010 2007 Latest water withdrawal data 2012 2009 2012 2012 2012 2012 2012 2009 2000 2004 2005 2005 2000 2007 2000 2004 2007 2002 2003 2012 2012 2009 2012 2012 2012 2012 2009 2011 2012 2012 2012 2012 2012 2009 2000 2005 2007 2005 2000 2005 2007 2000 2007 2005 2009 2005 2009 2009 2009 2012 2008 2005 2012 1997 2012 2012 2012 2012 2012 2011 2009 2012 2006 2001 2000 2000 2000 2006 2007 2005 2010 2000 2004 2000 1979 2009 2009 2012 2012 2012 2012 2012 2012 2010 2004 2000 1993 2001 2005 2010 2003 2010 2010 Yes 2009c Latest trade data 2010 2012 MICS, 2009 2005 ES/BS, 1998 IHS, 2011 FHS, 1996 DHS, 2012 MICS, 2011/12 WHS, 2003 MICS, 2000 DHS, 2009 States and markets Yes Yes Yes ES/BS, 2012 ES/BS, 2008 IHS, 2008 Yes Yes ES/BS, 2002/03 Global links Back 2010 2014 2010/11 2010 2011 2010 2008 2012 2002 2010 2010 2009 2012 2010 2007 2012 2012 2009 2002 2006 2005 2002 2005 2000 World Development Indicators 2014 103 Primary data documentation Currency National accounts System of SNA Reference National price year Accounts valuation Base year Liberia Libya Liechtenstein Lithuania Luxembourg Macedonia, FYR Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Mauritania Mauritius Mexico Micronesia, Fed. Sts. Moldova Monaco Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Northern Mariana Islands Norway Oman Pakistan Palau Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania Liberian dollar 2000 Libyan dinar 1999 Swiss franc 1990 Lithuanian litas 2000 a Euro Macedonian denar 1995 Malagasy ariary 1984 Malawi kwacha 2009 Malaysian ringgit 2005 Maldivian ruiyaa 2003 CFA franc 1987 Euro 2005 U.S. dollar 2004 Mauritanian ouguiya 2004 Mauritian rupee 2006 Mexican peso 2008 U.S. dollar 2004 a Moldovan leu Euro 1990 Mongolian tugrik 2005 Euro 2000 Moroccan dirham 1998 New Mozambican metical 2003 Myanmar kyat 2005/06 Namibian dollar 2004/05 Nepalese rupee 2000/01 a Euro CFP franc 1990 New Zealand dollar 2005/06 Nicaraguan gold cordoba 2006 CFA franc 2006 Nigerian naira 1990 U.S. dollar a Norwegian krone Rial Omani 1988 Pakistani rupee 2005/06 U.S. dollar 2005 Panamanian balboa 1996 Papua New Guinea kina 1998 Paraguayan guarani 1994 Peruvian new sol 1994 Philippine peso 2000 a Polish zloty Euro 2005 U.S. dollar 1954 Qatari riyal 2001 New Romanian leu 2000 Russian Federation Rwanda Samoa San Marino São Tomé and Príncipe Saudi Arabia Senegal Russian ruble Rwandan franc Samoan tala Euro São Tomé and Principe dobra Saudi Arabian riyal CFA franc Serbia New Serbian dinar 104 World Development Indicators 2014 2000 2006 2002 1995 2001 1999 1999 a 2005 1996 2005 2005 2005 1968 1993 1993 1993 1993 1993 1968 1993 1993 1993 1968 1993 1968 1993 1993 2008 1993 1993 1993 1993 1993 1993 1993 1968 1993 1993 1993 1993 1993 1993 1993 1993 1968 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 1968 1993 1993 P B B B B B B B P B B B B B B B B B B B B B P B B B B B P B B P B B B B B B P B B P P B Balance of payments and trade Alternative conversion factor PPP survey year Balance of Payments Manual in use External debt System of trade Accounting concept A S G S G S S S G G G S G G S G G B G G C C C C B C B C S S S G G S G G S C G S S C S C C B C B B C G G S G G G G S C B B B G G G 2005 6 6 1990–95 Rolling Rolling Rolling 2005 2005 2005 2005 2005 Rolling 6 6 6 6 6 6 6 6 6 2005 2005 2011 6 6 6 A A A 2005 6 A 2005 Rolling 2005 1992–95 2005 6 6 6 6 6 6 6 6 A A A A E 1986 1990–95 2005 2005 Rolling 2011 1965–95 1993 1971–98 1985–90 A A A E A A G S G S S S G G G S S G G S G A 2005 2005 6 6 6 6 Rolling 2005 2005 6 6 6 2005 2005 2005 Rolling Rolling 6 6 6 6 6 6 6 A A A A A 6 A G G G S S G S S G S S G S S 6 6 6 A A G G S 2005 6 A 1989 2005 1987–89, Rolling 1992 1987–95 2011 1994 2005 Government IMF data inance dissemination standard A A A A C B B C B C C B C C S G G G G G G S S S S B C G S S C B B C B S G G G G 1993 1993 1993 1993 1993 B P B B P 1987 1993 1993 P B 2005 2005 6 6 A S G B G G 2002 1993 B Rolling 6 A S C G 2000 Front ? User guide World view People Environment Latest population census Latest demographic, education, or health household survey Vital Latest Latest registration agricultural industrial complete census data 2008 c 2013/14 Liberia Libya Liechtenstein Lithuania Luxembourg Macedonia, FYR Madagascar Malawi Malaysia Maldives Mali Malta Marshall Islands Mauritania Mauritius Mexico Micronesia, Fed. Sts. Moldova Monaco Mongolia Montenegro Morocco Mozambique Myanmar Namibia Nepal Netherlands New Caledonia New Zealand Nicaragua Niger Nigeria Northern Mariana Islands Norway Oman Pakistan Palau Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar Romania 2008 2006 2010 2011 2011 2002 1993 2008 2010 2006 2009 2011 2011 2013 2011 2010 2010 2004 2008 2010 2011 2004 2007 1983 2011 2011 2011 2009 2013 2005 2012 2006 2010 2011 2010 1998 2010 2010 2011 2012 2007 2010 2011 2011 2010 2010 2011 Russian Federation Rwanda Samoa San Marino São Tomé and Príncipe 2010 2012 2011 2010 2012 WHS, 2003 MIS, 2013 DHS, 2009 IHS, 2012 IHS, 2011 DHS, 2008/09 PS, 2009/10 2011/12 Saudi Arabia Senegal 2010 2013 PS, 2010/11 2010 2013 2006 2010 Serbia 2011 Demographic survey, 2007 Continuous DHS, 2013/14; HIV/MCH SPA, 2013/14 MICS, 2010 2012 2010 Economy DHS, 2013 Source of most recent income and expenditure data CWIQ, 2007 Yes Yes Yes Yes ES/BS, 2008 MICS, 2011 MIS, 2013 HIV/MCH SPA, 2013 WHS, 2003 DHS, 2009 DHS, 2012/13 ES/BS, 2009 PS, 2010 IHS, 2010/11 ES/BS, 2012 IHS, 2010 IHS, 2009/10 Yes Yes Yes MICS, 2011 RHS, 1991 ENADID, 2009 MICS, 2012 MICS, 2010 MICS, 2005/06 MICS/PAPFAM, 2006 DHS, 2011 MICS, 2009/10 DHS, 2013 DHS, 2011 RHS, 2006/2007 DHS, 2012 DHS, 2013 2006/07 2015 2010 2011c IHS, 2012 IHS, 2000 ES/BS, 2012 LSMS, 2012 ES/BS, 2011 ES/BS, 2007 ES/BS, 2008/09 ES/BS, 2009/10 LSMS, 2011 IHS, 1999 2000 2000 2008 2012 2012 2012 2012 2011 2012 2012 2012 2012 2007 1999 2007 2000 2005 2005 2008 2000 2002 2010 2009 2010 2006 2009 2010 Yes 2013/14 2007 2010 2010 2012 2012 2012 2005 2003 2009 Yes Yes Yes Yes 2011 2010 2012 2012 2010 2012 2009/10 2010 2014 2011/12 2010 2008 2007 2012 2012 2012 2010 2012 2011 2012 2012 2012 2012 2012 2012 2007 2009 2009 2010 2000 2001 2000 2002 2006 2008 Yes Yes Yes IS, 1997 LSMS, 2009 CWIQ/PS, 2007 IHS, 2010 Yes IHS, 2008 2010 2003 2008 2008 2012 2011 2004-08 2013 2007 2010 2012/13 2010 2009 2008 2010 2006 2011 2001 2008 2012 2012 2010 2009 2007 2002 2010 2008 2009 2009 2006 2010 2010 2002 Yes LSMS, 2008 LSMS, 1996 RHS, 2008 Continuous DHS, 2013 DHS, 2013 RHS, 1995/96 MICS, 2012 RHS, 1999 IHS, 2011 IHS, 2009/10 IHS, 2011 IHS, 2012 ES/BS, 2012 ES/BS, 2010 IS, 1997 Yes Yes Yes Yes Yes Yes LFS, 2010 Latest water withdrawal data 2010 IHS, 2008 IS, 2000 MICS, 2012 DHS, 2012/13 2010 2010 2007 Latest trade data Yes 2010 2014 2008 2009 2010 2012 2012 2012 2012 2011 2012 2012 2012 2012 2012 2012 2012 2012 2002 2001 2005 2005 2006 2003 2008 2000 2005 2000 2000 2009 2009 2002 2005 2005 2009 2012 2012 2012 2001 2000 2012 1993 2011 2012 2006 2002 Yes States and markets IHS, 2010 Global links Yes Back 2009 World Development Indicators 2014 105 Primary data documentation Currency National accounts System of SNA Reference National price year Accounts valuation Base year Seychelles Sierra Leone Singapore Sint Maarten Slovak Republic Slovenia Solomon Islands Somalia South Africa South Sudan Spain Sri Lanka St. Kitts and Nevis St. Lucia St. Martin St. Vincent and the Grenadines Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Tonga Trinidad and Tobago Seychelles rupee Sierra Leonean leone Singapore dollar Netherlands Antilles guilder Euro Euro Solomon Islands dollar Somali shilling South African rand South Sudanese pound Euro Sri Lankan rupee East Caribbean dollar East Caribbean dollar Euro East Caribbean dollar 2006 2006 2005 1993 1993 2008 1993 P B B 1993 1993 1993 1968 1993 1993 1993 1993 1993 1968 1993 1993 B B B B B 1988 2010 2000 2010/11 2000 1968 1993 1993 1993 1993 1968 1993 1993 1993 2008 1968 1993 1993 B B B B B B B B P B P B B 1990 1998 2005 1993 1993 1993 B B B 2005 a 2004 1985 2005 2009 2005 2002 2006 2006 2006 1981/82h 2007 2000 1996 a 2005 Tunisia Turkey Turkmenistan Sudanese pound Suriname dollar Swaziland lilangeni Swedish krona Swiss franc Syrian pound Tajik somoni Tanzanian shilling Thai baht U.S. dollar CFA franc Tongan pa'anga Trinidad and Tobago dollar Tunisian dinar New Turkish lira New Turkmen manat Turks and Caicos Islands Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Vanuatu Venezuela, RB Vietnam Virgin Islands (U.S.) West Bank and Gaza Yemen, Rep. Zambia Zimbabwe U.S. dollar Australian dollar 2005 Ugandan shilling 2001/02 a Ukrainian hryvnia U.A.E. dirham 2007 Pound sterling 2005 a U.S. dollar Uruguayan peso 2005 a Uzbek sum Vanuatu vatu 2006 Venezuelan bolivar fuerte 1997 Vietnamese dong 2010 U.S. dollar 1982 Israeli new shekel 1997 Yemeni rial 1990 New Zambian kwacha 1994 U.S. dollar 2009 106 World Development Indicators 2014 2005 2005 2000 a a 2000 2001 2003 2005 1997 Front 1993 1968 1968 1993 1993 1993 2008 1993 1993 1993 1993 1993 1968 1968 1993 1968 1993 ? Balance of payments and trade Alternative conversion factor PPP survey year Balance of Payments Manual in use 2005 2005 6 6 6 Rolling Rolling 1977–90 B P B B B P B B User guide External debt System of trade Accounting concept A A G S G C B C G G S S S S C C S S G G C S C B B B S G G G A E P 2005 6 Rolling 2005 6 6 6 6 A S G S S 6 A S B G 6 6 6 6 6 6 6 6 6 A G G G G S S G G S S S G S B B C C C B C B C C G G G S S G G G S G G G G G S G C C S S B C C C C C G G S G S S S B B B B P B B B B B B P 6 6 6 2005 2005 Rolling Rolling 1970–2010 2005 1990–95 2005 2005 2005 2005 2005 Rolling 1987–95, 1997–2007 2005 2005 A A E A A A 6 6 6 A A 6 6 6 A A E 1991 2005 2005 6 6 6 6 6 6 6 6 6 6 A E A A 1990–96 1990–92 1991, 1998 2005 2005 2005 6 6 6 6 A A A 1987–95 Government IMF data inance dissemination standard Rolling 2011 2005 1990–95 World view G G G G G G G G G G G G G S S S G A A People B B C G G G B B B C S G G G Environment Latest population census Latest demographic, education, or health household survey Seychelles Sierra Leone Singapore Sint Maarten 2010 2004 2010 2011 Slovak Republic Slovenia Solomon Islands Somalia South Africa South Sudan Spain Sri Lanka St. Kitts and Nevis St. Lucia St. Martin St. Vincent and the Grenadines Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Tonga Trinidad and Tobago 2011 2011b 2009 1987 2011 2008 2011 2012 2011 2010 2008 2012 2007 2011 2010 2004 2010 2012 2010 2010 2010 2006 2011 SHHS, 2010 MICS, 2010 MICS, 2010 Tunisia Turkey Turkmenistan 2004 2011 2012 Turks and Caicos Islands Tuvalu Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Vanuatu Venezuela, RB Vietnam Virgin Islands (U.S.) West Bank and Gaza Yemen, Rep. Zambia Zimbabwe 2012 2012 2002 2001 2010 2011 2010 2011 1989 2009 2011 2009 2010 2007 2004 2010 2012 DHS, 2013; MIS, 2013 NHS, 2010 WHS, 2003 WHS, 2003 MICS, 2006 DHS, 2003; WHS, 2003 Source of most recent income and expenditure data Vital Latest Latest registration agricultural industrial complete census data BS, 2006/07 IHS, 2011 Yes 2011 Yes Yes IS, 2009 ES/BS, 2004 IHS, 2005/06 DHS, 2006/07 ES/BS, 2010 ES/BS, 2009 IHS, 2000 ES/BS, 2010 MICS, 2012 IHS, 1995 Yes Yes Yes Yes Yes Yes 2011 2010 MICS, 2006 DHS, 2012 HIV/MCH SPA, 2013/14 MICS, 2012 DHS, 2009/10 DHS, 2013 MICS, 2011 IHS, 1992 MICS, 2011/12 DHS, 2003; WHS, 2003 MICS, 2011 IHS, 2010 LFS, 2009 LSMS, 1998 Yes Yes Yes 2010 2012 2010 2013/14 2009 2010 2012 2012 2011 2008 2008 2005 2012 1995 2011 2011 2007 2012 2012 2010 2000 2012 2012 2005 2012 2012 2010 2005i 2000 2000 2007 2000 2005 2006 2002 2007 2004 2002 2000 2011 2012 2000 2001 2003 2004 2007 2013/14 2008 2007c 2010 2008 2014 2013 2007/08 2013 2010 c 2011/12 2001 2009 2007 2007 2006 2006 2006 2009 Yes MICS, 2012 MICS, 2006 MICS, 2007 MICS, 2000 MICS, 2010/11 IS, 1999 LFS, 2000 IHS, 2012 ES/BS, 2011 Yes Yes Yes Yes IHS, 2012 IHS, 2010 Yes Yes Yes MICS, 2010 DHS, 2013 DHS, 2013 DHS, 2010/11 IHS, 2009 ES/BS, 2005 IHS, 2010 IHS, 2011/12 2007 2009 2007 2014/15 Yes 2005 2005 1975 2012 2012 2012 Yes PS, 2009/10 ES/BS, 2009 2008 2002 2012 2009 2010 Yes AIS, 2011; DHS, 2011 MICS, 2012 Latest water withdrawal data 2010 2010 2012/13 Yes ES/BS, 2009 ES/BS, 1999 ES/BS, 2009/10 IS, 2000 ES/BS, 2000 ES/BS, 2004 LSMS, 2009 ES/BS, 2011/12 IHS, 2011 LSMS, 2007 CWIQ, 2011 Latest trade data 2008/09 2012/13 2012 2010 2012 2011 2007 2007 2011/12 2007 2005 2009 2008 2008 2012 2008 2012 2012 2011 2012 2012 2012 2010 2011 2011 2011 2000 2005 2012 2011 2012 2005 2005 2002 2002 2000 2010 2006 2010 c 2003 2000 2002 2005 2005 2007 2005 2000 2005 Note: For explanation of the abbreviations used in the table, see notes following the table. a. Original chained constant price data are rescaled. b. Population data compiled from administrative registers. c. Population and Housing Census. d. Latest population census: Guernsey, 2009; Jersey, 2011 e. Vital registration for Guernsey and Jersey. f. The population censuses for 1986 and 1996 were based on a one-in-seven sample of the population, while that for 2006 was based on a one-in-ten sample of the population. g. Rolling census based on continuous sample survey. h. Reporting period switch from iscal year to calendar year from 1996. Pre-1996 data converted to calendar year. i. Includes South Sudan. Economy States and markets Global links Back World Development Indicators 2014 107 Primary data documentation notes 108 • Base year is the base or pricing period used for con- general system comprise outward-moving goods: (a) HIV/AIDS Indicator Survey, DHS is Demographic and stant price calculations in the country’s national national goods wholly or partly produced in the country; Health Survey, ENADID is National Survey of Demo- accounts. Price indexes derived from national accounts (b) foreign goods, neither transformed nor declared for graphic Dynamics, FHS is Family Health Survey, HIV/ aggregates, such as the implicit delator for gross domestic consumption in the country, that move out- MCH is HIV/Maternal and Child Health, LSMS is Living domestic product (GDP), express the price level relative ward from customs storage; and (c) nationalized goods Standards Measurement Study Survey, MICS is Multiple to base year prices. • Reference year is the year in that have been declared for domestic consumption and Indicator Cluster Survey, MIS is Malaria Indicator Survey, which the local currency constant price series of a coun- move outward without being transformed. Under the NHS is National Health Survey, NSS is National Sample try is valued. The reference year is usually the same as special system of trade, exports are categories a and c. Survey on Population Change, PAPFAM is Pan Arab Proj- the base year used to report the constant price series. In some compilations categories b and c are classiied ect for Family Health, RHS is Reproductive Health Sur- However, when the constant price data are chain linked, as re-exports. Direct transit trade—goods entering or vey, SHHS is Sudan Household Health Survey, SPA is the base year is changed annually, so the data are res- leaving for transport only—is excluded from both import Service Provision Assessments, and WHS is World caled to a speciic reference year to provide a consistent and export statistics. • Government finance accounting Health Survey. Detailed information for AIS, DHS, MIS, time series. When the country has not rescaled following concept is the accounting basis for reporting central and SPA are available at www.measuredhs.com; for a change in base year, World Bank staff rescale the data government inancial data. For most countries govern- MICS at www.childinfo.org; for RHS at www.cdc.gov to maintain a longer historical series. To allow for cross- ment inance data have been consolidated (C) into one /reproductivehealth; and for WHS at www.who.int country comparison and data aggregation, constant set of accounts capturing all central government iscal /healthinfo/survey/en. • Source of most recent income price data reported in World Development Indicators are activities. Budgetary central government accounts (B) and expenditure data shows household surveys that rescaled to a common reference year (2000) and cur- exclude some central government units. • IMF data dis- collect income and expenditure data. Names and rency (U.S. dollars). • System of National Accounts semination standard shows the countries that sub- detailed information on household surveys can be found identiies whether a country uses the 1968, 1993, or scribe to the IMF’s Special Data Dissemination Stan- on the website of the International Household Survey 2008 System of National Accounts (SNA). • SNA price dard (SDDS) or General Data Dissemination System Network (www.surveynetwork.org). Core Welfare Indica- valuation shows whether value added in the national (GDDS). S refers to countries that subscribe to the SDDS tor Questionnaire Surveys (CWIQ), developed by the accounts is reported at basic prices (B) or producer and have posted data on the Dissemination Standards World Bank, measure changes in key social indicators prices (P). Producer prices include taxes paid by produc- Bulletin Board at http://dsbb.imf.org. G refers to coun- for different population groups—speciically indicators ers and thus tend to overstate the actual value added in tries that subscribe to the GDDS. The SDDS was estab- of access, utilization, and satisfaction with core social production. However, value added can be higher at basic lished for member countries that have or might seek and economic services. Expenditure survey/budget prices than at producer prices in countries with high access to international capital markets to guide them in surveys (ES/BS) collect detailed information on house- agricultural subsidies. • Alternative conversion factor providing their economic and inancial data to the public. hold consumption as well as on general demographic, identiies the countries and years for which a World The GDDS helps countries disseminate comprehensive, social, and economic characteristics. Integrated house- Bank–estimated conversion factor has been used in timely, accessible, and reliable economic, inancial, and hold surveys (IHS) collect detailed information on a wide place of the oficial exchange rate (line rf in the Interna- sociodemographic statistics. IMF member countries variety of topics, including health, education, economic tional Monetary Fund’s [IMF] International Financial Sta- elect to participate in either the SDDS or the GDDS. Both activities, housing, and utilities. Income surveys (IS) col- tistics). See Statistical methods for further discussion of standards enhance the availability of timely and com- lect information on the income and wealth of house- alternative conversion factors. • Purchasing power prehensive data and therefore contribute to the pursuit holds as well as various social and economic character- parity (PPP) survey year is the latest available survey of sound macroeconomic policies. The SDDS is also istics. Income tax registers (ITR) provide information on year for the International Comparison Program’s esti- expected to improve the functioning of inancial mar- a population’s income and allowance, such as gross mates of PPPs. • Balance of Payments Manual in use kets. • Latest population census shows the most income, taxable income, and taxes by socioeconomic refers to the classiication system used to compile and recent year in which a census was conducted and in group. Labor force surveys (LFS) collect information on report data on balance of payments. 6 refers to the 6th which at least preliminary results have been released. employment, unemployment, hours of work, income, edition of the IMF’s Balance of Payments Manual (2009). The preliminary results from the very recent censuses and wages. Living Standards Measurement Study Sur- • External debt shows debt reporting status for 2012 could be relected in timely revisions if basic data are veys (LSMS), developed by the World Bank, provide a data. A indicates that data are as reported, P that data available, such as population by age and sex, as well as comprehensive picture of household welfare and the are based on reported or collected information but the detailed deinition of counting, coverage, and com- factors that affect it; they typically incorporate data col- include an element of staff estimation, and E that data pleteness. Countries that hold register-based censuses lection at the individual, household, and community are World Bank staff estimates. • System of trade produce similar census tables every 5 or 10 years. Ger- levels. Priority surveys (PS) are a light monitoring survey, refers to the United Nations general trade system (G) or many’s 2001 census is a register-based test census designed by the World Bank, that collect data from a special trade system (S). Under the general trade sys- using a sample of 1.2 percent of the population. A rare large number of households cost-effectively and quickly. tem goods entering directly for domestic consumption case, France conducts a rolling census every year; the 1-2-3 (1-2-3) surveys are implemented in three phases and goods entered into customs storage are recorded 1999 general population census was the last to cover and collect sociodemographic and employment data, as imports at arrival. Under the special trade system the entire population simultaneously. • Latest demo- data on the informal sector, and information on living goods are recorded as imports when declared for graphic, education, or health household survey indi- conditions and household consumption. • Vital registra- domestic consumption whether at time of entry or on cates the household surveys used to compile the demo- tion complete identiies countries that report at least withdrawal from customs storage. Exports under the graphic, education, and health data in section 2. AIS is 90 percent complete registries of vital (birth and death) World Development Indicators 2014 Front ? User guide World view People Environment Primary data documentation notes statistics to the United Nations Statistics Division and accounts data have been revised from 2006 onward; year is 2011. • Fiji. Based on data from the Bureau of are reported in its Population and Vital Statistics Reports. the new base year is 2006. Data before 2006 were Statistics, national accounts data on the expenditure Countries with complete vital statistics registries may reported on a iscal year basis. • Cabo Verde. Based side have been revised from 2005 onward; the new have more accurate and more timely demographic indi- on oficial government statistics and IMF data, national base year is 2005. • Hong Kong SAR, China. Hong Kong cators than other countries. • Latest agricultural cen- accounts data have been revised from 1990 onward; SAR, China, reports using SNA 2008. • Iraq. Based on sus shows the most recent year in which an agricultural the new base year is 2007. • Chad. Based on IMF data, oficial government data, national accounts have been census was conducted or planned to be conducted, as national accounts data have been revised from 2005 revised from 2000 onward; the new base year is 1988. reported to the Food and Agriculture Organization of the onward; the new base year is 2005. • Canada. Canada • Kiribati. Based on IMF, Asian Development Bank, and United Nations. • Latest industrial data show the most reports using SNA 2008. • China. Based on data from World Bank data, national accounts data have been recent year for which manufacturing value added data the National Bureau of Statistics, the methodology used revised from 2000 onward. • Malawi. Based on IMF at the three-digit level of the International Standard to calculate exports and imports of goods and services data, national accounts data have been revised from Industrial Classiication (revision 2 or 3) are available in in constant prices has been revised from 2000 onward. 2000 onward; the new base year is 2009. • Malaysia. the United Nations Industrial Development Organization • Ecuador. Based on oficial government data, national Based on oficial government statistics, value added database. • Latest trade data show the most recent accounts have been revised from 1965 onward; the new services in constant and current prices have been year for which structure of merchandise trade data from base year is 2007. Ecuador reports using SNA 2008. revised from 1990 onward. National accounts data in the United Nations Statistics Division’s Commodity • Ethiopia. Based on IMF data, national accounts data constant prices have been linked back to 1960; the Trade (Comtrade) database are available. • Latest have been revised from 2000 onward; the new base new base year is 2005. • Mexico. The base year has water withdrawal data show the most recent year for which data on freshwater withdrawals have been com- Economies with exceptional reporting periods Economy Fiscal year end Reporting period for national accounts data Afghanistan Australia Bangladesh Botswana Canada Egypt, Arab Rep. Ethiopia Gambia, The Haiti India Indonesia Iran, Islamic Rep. Japan Kenya Kuwait Lesotho Malawi Marshall Islands Micronesia, Fed. Sts. Myanmar Namibia Nepal New Zealand Pakistan Palau Puerto Rico Samoa Sierra Leone Singapore South Africa Swaziland Sweden Thailand Tonga Uganda United States Zimbabwe Mar. 20 Jun. 30 Jun. 30 Mar. 31 Mar. 31 Jun. 30 Jul. 7 Jun. 30 Sep. 30 Mar. 31 Mar. 31 Mar. 20 Mar. 31 Jun. 30 Jun. 30 Mar. 31 Mar. 31 Sep. 30 Sep. 30 Mar. 31 Mar. 31 Jul. 14 Mar. 31 Jun. 30 Sep. 30 Jun. 30 Jun. 30 Jun. 30 Mar. 31 Mar. 31 Mar. 31 Jun. 30 Sep. 30 Jun. 30 Jun. 30 Sep. 30 Jun. 30 FY FY FY CY CY FY FY CY FY FY CY FY CY CY CY CY CY FY FY FY CY FY FY FY FY FY FY CY CY CY CY CY CY FY FY CY CY piled from a variety of sources. Exceptional reporting periods In most economies the iscal year is concurrent with the calendar year. Exceptions are shown in the table at right. The ending date reported here is for the iscal year of the central government. Fiscal years for other levels of government and reporting years for statistical surveys may differ. The reporting period for national accounts data is designated as either calendar year basis (CY) or iscal year basis (FY). Most economies report their national accounts and balance of payments data using calendar years, but some use iscal years. In World Development Indicators iscal year data are assigned to the calendar year that contains the larger share of the iscal year. If a country’s iscal year ends before June 30, data are shown in the irst year of the iscal period; if the iscal year ends on or after June 30, data are shown in the second year of the period. Balance of payments data are reported in World Development Indicators by calendar year. Revisions to national accounts data National accounts data are revised by national statistical ofices when methodologies change or data sources improve. National accounts data in World Development Indicators are also revised when data sources change. The following notes, while not comprehensive, provide information on revisions from previous data. • Australia. Value added current series updated by the Australian Bureau of Statistics; data have been revised from 1990 onward; Australia reports using SNA 2008. • Botswana. Based on oficial government statistics, national Economy States and markets Global links changed to 2008; Mexico reports using SNA 2008. • Micronesia, Fed. Sts. Based on the Paciic and Virgin Islands Training Initiative, national accounts data have been revised from 2009 onward. • Niger. Based on oficial government statistics, national accounts data have been revised from 2006 onward; the new base year is 2006. • Nigeria. Based on oficial government statistics, national accounts data have been revised from 1981 onward while preserving historical growth rates for constant GDP at market prices through 2006. • Paraguay. National accounts data have been revised from 1960 onward. The output of two hydroelectric plants (shared with neighboring countries) were added, raising GDP from previous estimates • Romania. Based on data from the National Statistical Institute, national accounts data have been revised; the new base year is 2000. • Singapore. Singapore reports using a blend of SNA 1993 and SNA 2008. • Timor-Leste. Based on oficial government statistics, national accounts data have been revised, and value added is measured at basic prices; the new base year is 2010. Timor-Leste reports using SNA 2008. • Tuvalu. Based on data from the IMF, World Bank, and oficial government statistics, national accounts data have been revised from 2006 onward. Value added is measured at producer prices through 1999 and at basic prices from 2000 onward. • United States. The United States reports using SNA 2008. • Vanuatu. Based on oficial government statistics, value added is measured at producer prices through 1997 and at basic prices from 1998 onward. • Vietnam. Based on data from the Vietnam Statistics Ofice, national accounts data have been revised from 2000 onward; the new base year is 2010. • Zambia. National accounts data have rebased to relect the January 1, 2013, introduction of the new Zambian kwacha at a rate of 1,000 old kwacha = 1 new kwacha. Back World Development Indicators 2014 109 Statistical methods This section describes some of the statistical procedures used in preparing World Development Indicators. It covers the methods employed for calculating regional and income group aggregates and for calculating growth rates, and it describes the World Bank Atlas method for deriving the conversion factor used to estimate gross national income (GNI) and GNI per capita in U.S. dollars. Other statistical procedures and calculations are described in the About the data sections following each table. Aggregation rules Aggregates based on the World Bank’s regional and income classiications of economies appear at the end of the tables, including most of those available online. The 214 economies included in these classii cations are shown on the laps on the front and back covers of the book. Aggregates also contain data for Taiwan, China. Most tables also include the aggregate for the euro area, which includes the member states of the Economic and Monetary Union (EMU) of the European Union that have adopted the euro as their currency: Austria, Belgium, Cyprus, Estonia, Finland, France, Germany, Greece, Ireland, Italy, Latvia, Luxembourg, Malta, Netherlands, Portugal, Slovak Republic, Slovenia, and Spain. Other classiications, such as the European Union, are documented in About the data for the online tables in which they appear. Because of missing data, aggregates for groups of economies should be treated as approximations of unknown totals or average values. The aggregation rules are intended to yield estimates for a consistent set of economies from one period to the next and for all indicators. Small differences between sums of subgroup aggregates and overall totals and averages may occur because of the approximations used. In addition, compilation errors and data reporting practices may cause discrepancies in theoretically identical aggregates such as world exports and world imports. Five methods of aggregation are used in World Development Indicators: • For group and world totals denoted in the tables by a t, missing data are imputed based on the relationship of the sum of available data to the total in 110 World Development Indicators 2014 Front ? User guide • • • • the year of the previous estimate. The imputation process works forward and backward from 2005. Missing values in 2005 are imputed using one of several proxy variables for which complete data are available in that year. The imputed value is calculated so that it (or its proxy) bears the same relationship to the total of available data. Imputed values are usually not calculated if missing data account for more than a third of the total in the benchmark year. The variables used as proxies are GNI in U.S. dollars; total population; exports and imports of goods and services in U.S. dollars; and value added in agriculture, industry, manufacturing, and services in U.S. dollars. Aggregates marked by an s are sums of available data. Missing values are not imputed. Sums are not computed if more than a third of the observations in the series or a proxy for the series are missing in a given year. Aggregates of ratios are denoted by a w when calculated as weighted averages of the ratios (using the value of the denominator or, in some cases, another indicator as a weight) and denoted by a u when calculated as unweighted averages. The aggregate ratios are based on available data. Missing values are assumed to have the same average value as the available data. No aggregate is calculated if missing data account for more than a third of the value of weights in the benchmark year. In a few cases the aggregate ratio may be computed as the ratio of group totals after imputing values for missing data according to the above rules for computing totals. Aggregate growth rates are denoted by a w when calculated as a weighted average of growth rates. In a few cases growth rates may be computed from time series of group totals. Growth rates are not calculated if more than half the observations in a period are missing. For further discussion of methods of computing growth rates see below. Aggregates denoted by an m are medians of the values shown in the table. No value is shown if more than half the observations for countries with a population of more than 1 million are missing. World view People Environment Exceptions to the rules may occur. Depending on the judgment of World Bank analysts, the aggregates may be based on as little as 50 percent of the available data. In other cases, where missing or excluded values are judged to be small or irrelevant, aggregates are based only on the data shown in the tables. Growth rates Growth rates are calculated as annual averages and represented as percentages. Except where noted, growth rates of values are computed from constant price series. Three principal methods are used to calculate growth rates: least squares, exponential endpoint, and geometric endpoint. Rates of change from one period to the next are calculated as proportional changes from the earlier period. Least squares growth rate. Least squares growth rates are used wherever there is a suficiently long time series to permit a reliable calculation. No growth rate is calculated if more than half the observations in a period are missing. The least squares growth rate, r, is estimated by itting a linear regression trend line to the logarithmic annual values of the variable in the relevant period. The regression equation takes the form notably labor force and population, is calculated from the equation r = ln(pn/p0)/n where pn and p0 are the last and irst observations in the period, n is the number of years in the period, and ln is the natural logarithm operator. This growth rate is based on a model of continuous, exponential growth between two points in time. It does not take into account the intermediate values of the series. Nor does it correspond to the annual rate of change measured at a one-year interval, which is given by (pn – pn–1)/pn–1. Geometric growth rate. The geometric growth rate is applicable to compound growth over discrete periods, such as the payment and reinvestment of interest or dividends. Although continuous growth, as modeled by the exponential growth rate, may be more realistic, most economic phenomena are measured only at intervals, in which case the compound growth model is appropriate. The average growth rate over n periods is calculated as r = exp[ln(pn/p0)/n] – 1. ln Xt = a + bt which is the logarithmic transformation of the compound growth equation, Xt = Xo (1 + r )t. In this equation X is the variable, t is time, and a = ln Xo and b = ln (1 + r) are parameters to be estimated. If b* is the least squares estimate of b, then the average annual growth rate, r, is obtained as [exp(b*) – 1] and is multiplied by 100 for expression as a percentage. The calculated growth rate is an average rate that is representative of the available observations over the entire period. It does not necessarily match the actual growth rate between any two periods. Exponential growth rate. The growth rate between two points in time for certain demographic indicators, Economy States and markets World Bank Atlas method In calculating GNI and GNI per capita in U.S. dollars for certain operational and analytical purposes, the World Bank uses the Atlas conversion factor instead of simple exchange rates. The purpose of the Atlas conversion factor is to reduce the impact of exchange rate luctuations in the cross-country comparison of national incomes. The Atlas conversion factor for any year is the average of a country’s exchange rate (or alternative conversion factor) for that year and its exchange rates for the two preceding years, adjusted for the difference between the rate of inlation in the country and the rate of international inlation. The objective of the adjustment is to reduce any changes to the exchange rate caused by inlation. Global links Back World Development Indicators 2014 111 Statistical methods A country’s inlation rate between year t and year t–n (r t–n) is measured by the change in its GDP delator (pt): pt r t–n = p t–n International inlation between year t and year t–n SDR$) is measured using the change in a delator (r t–n based on the International Monetary Fund’s unit of account, special drawing rights (or SDRs). Known as the “SDR delator,” it is a weighted average of the GDP delators (in SDR terms) of Japan, the United Kingdom, the United States, and the euro area, converted to U.S. dollar terms; weights are the amount of each currency in one SDR unit. SDR$ r t–n = p tSDR$ SDR$ p t–n The Atlas conversion factor (local currency to the U.S. dollar) for year t (e tatlas) is given by: where et is the average annual exchange rate (local currency to the U.S. dollar) for year t. 112 World Development Indicators 2014 Front ? User guide GNI in U.S. dollars (Atlas method) for year t (Y tatlas$) is calculated by applying the Atlas conversion factor to a country’s GNI in current prices (local currency) (Yt) as follows: Y tatlas$ = Yt /e tatlas The resulting Atlas GNI in U.S. dollars can then be divided by a country’s midyear population to yield its GNI per capita (Atlas method). Alternative conversion factors The World Bank systematically assesses the appropriateness of oficial exchange rates as conversion factors. An alternative conversion factor is used when the ofi cial exchange rate is deemed to be unreliable or unrepresentative of the rate effectively applied to domestic transactions of foreign currencies and traded products. This applies to only a small number of countries, as shown in Primary data documentation. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors. World view People Environment Credits 1. World view Section 1 was prepared by a team led by Neil Fantom. Neil Fantom wrote the introduction, and the Millennium Development Goal spreads were produced by Mahyar Eshragh-Tabary, Juan Feng, Masako Hiraga, Wendy Huang, Buyant Erdene Khaltarkhuu, Hiroko Maeda, Johan Mistiaen, Malvina Pollock, and Emi Suzuki. Tables were produced by Mahyar EshraghTabary, Juan Feng, Masako Hiraga, Wendy Huang, Bala Bhaskar Naidu Kalimili, Haruna Kashiwase, Buyant Erdene Khaltarkhuu, Hiroko Maeda, and Emi Suzuki. Signe Zeikate of the World Bank’s Economic Policy and Debt Department provided the estimates of debt relief for the Heavily Indebted Poor Countries Debt Initiative and Multilateral Debt Relief Initiative. 2. People Section 2 was prepared by Juan Feng, Masako Hiraga, Haruna Kashiwase, Hiroko Maeda, and Emi Suzuki in partnership with the World Bank’s Human Development Network and the Development Research Group in the Development Economics Vice Presidency. Emi Suzuki prepared the demographic estimates and projections. The poverty estimates at national poverty lines were compiled by the Global Poverty Working Group, a team of poverty experts from the Poverty Reduction and Equality Network, the Development Research Group, and the Development Data Group. Shaohua Chen and Prem Sangraula of the World Bank’s Development Research Group prepared the poverty estimates at international poverty lines. Lorenzo Guarcello and Furio Rosati of the Understanding Children’s Work project prepared the data on children at work. Other contributions were provided by Samuel Mills (health); Salwa Haidar, Maddalena Honorati, Theodoor Sparreboom, and Alan Wittrup of the International Labour Organization (labor force); Amélie Gagnon, Friedrich Huebler, and Weixin Lu of the United Nations Educational, Scientiic and Cultural Organization Institute for Statistics (education and literacy); Chandika Indikadahena (health expenditure), Monika Bloessner, Elaine Borghi, and Mercedes de Onis (malnutrition and overweight), Teena Kunjumen (health workers), Jessica Ho (hospital beds), Rifat Economy States and markets Hossain (water and sanitation), Luz Maria de Regil (anemia), Hazim Timimi (tuberculosis), Colin Mathers and Wahyu Mahanani (cause of death), and Lori Marie Newman (syphilis), all of the World Health Organization; Leonor Guariguata of the International Diabetes Federation (diabetes); Mary Mahy of the Joint United Nations Programme on HIV/AIDS (HIV/AIDS); and Colleen Murray (health) and Rolf Luyendijk (water and sanitation) of the United Nations Children’s Fund. 3. Environment Section 3 was prepared by Mahyar Eshragh-Tabary in partnership with the Agriculture and Environmental Services Department of the Sustainable Development Network Vice Presidency of the World Bank. Mahyar Eshragh-Tabary wrote the introduction and the highlights stories with invaluable comments and editorial help from Tariq Khokhar. Sonu Jain helped prepare the highlight story on wealth accounting. Esther G. Naikal and Chris Sall prepared the data on particulate matter concentration and natural resources rents. Ramgopal Erabelly provided technical assistance in calculating the population data for largest city and urban agglomerations. Neil Fantom and William Prince provided instrumental comments, suggestions, and support at all stages of production. Other contributors include Sharon Burghgraeve and Karen Tréanto of the International Energy Agency, Gerhard Metchies and Armin Wagner of German International Cooperation, Craig Hilton-Taylor and Caroline Pollock of the International Union for Conservation of Nature, and Cristian Gonzalez of the International Road Federation. The team is grateful to the United Nations Food and Agriculture Organization, the United Nations Environment Programme and World Conservation Monitoring Centre, the International Union for Conservation of Nature, the U.S. Department of Energy’s Carbon Dioxide Information Analysis Center, the International Energy Agency, and the U.S. Agency for International Development’s Ofice of Foreign Disaster Assistance for access to their online databases. The World Bank’s Agriculture and Environmental Services Department devoted generous staff resources. Global links Back World Development Indicators 2014 113 Credits 4. Economy Section 4 was prepared by Bala Bhaskar Naidu Kalimili in close collaboration with the Sustainable Development and Economic Data Team of the World Bank’s Development Data Group and with suggestions from Liu Cui and William Prince. Bala Bhaskar Naidu Kalimili wrote the introduction with suggestions from Tariq Khokhar. The highlights section was prepared by Bala Bhaskar Naidu Kalimili and Maurice Nsabimana. The national accounts data for low- and middle-income economies were gathered by the World Bank’s regional staff through the annual Uniied Survey. Maja Bresslauer, Liu Cui, Federico Escaler, Mahyar Eshragh-Tabary, Bala Bhaskar Naidu Kalimili, Buyant Erdene Khaltarkhuu, and Maurice Nsabimana updated, estimated, and validated the databases for national accounts. Esther G. Naikal and Chris Sall prepared the data on adjusted savings and adjusted income. Azita Amjadi contributed data on trade from the World Integrated Trade Solution. The team is grateful to Eurostat, the International Monetary Fund, the Organisation for Economic Co-operation and Development, the United Nations Industrial Development Organization, and the World Trade Organization for access to their databases. 5. States and markets Section 5 was prepared by Federico Escaler and Buyant Erdene Khaltarkhuu in partnership with the World Bank’s Financial and Private Sector Development Network, Poverty Reduction and Economic Management Network, and Sustainable Development Network; the International Finance Corporation; and external partners. Buyant Erdene Khaltarkhuu wrote the introduction with input from Neil Fantom, Tariq Khokhar, and William Prince. Other contributors include Alexander Nicholas Jett (privatization and infrastructure projects); Leora Klapper and Frederic Meunier (business registration); Jorge Luis Rodriguez Meza, Valeria Perotti, and Joshua Wimpey (Enterprise Surveys); Frederic Meunier and Rita Ramalho (Doing Business); Alka Banerjee, Trisha Malinky, and Michael Orzano (Standard & Poor’s global stock market indexes); Kenneth Anye (fragile situations); James Hackett of the International Institute for 114 World Development Indicators 2014 Front ? User guide Strategic Studies (military personnel); Sam Perlo-Freeman of the Stockholm International Peace Research Institute (military expenditures and arms transfers); Therese Petterson (battle-related deaths); Cristian Gonzalez of the International Road Federation, Narjess Teyssier of the International Civil Aviation Organization, and Marc Juhel and Hélène Stephan (transport); Vincent Valentine of the United Nations Conference on Trade and Development (ports); Azita Amjadi (high-tech exports); Vanessa Grey, Esperanza Magpantay, Susan Teltscher, and Ivan Vallejo Vall of the International Telecommunication Union and Torbjörn Fredriksson, Scarlett Fondeur Gil, and Diana Korka of the United Nations Conference on Trade and Development (information and communication technology goods trade); Martin Schaaper of the United Nations Educational, Scientiic and Cultural Organization Institute for Statistics (research and development, researchers, and technicians); and Ryan Lamb of the World Intellectual Property Organization (patents and trademarks). 6. Global links Section 6 was prepared by Wendy Huang with substantial input from Evis Rucaj and Rubena Sukaj and in partnership with the Financial Data Team of the World Bank’s Development Data Group, Development Research Group (trade), Development Prospects Group (commodity prices and remittances), International Trade Department (trade facilitation), and external partners. Evis Rucaj wrote the introduction. Azita Amjadi (trade and tariffs) and Rubena Sukaj (external debt and inancial data) provided input on the data and tables. Other contributors include Frédéric Docquier (emigration rates); Flavine Creppy and Yumiko Mochizuki of the United Nations Conference on Trade and Development and Mondher Mimouni of the International Trade Centre (trade); Cristina Savescu (commodity prices); Jeff Reynolds and Joseph Siegel of DHL (freight costs); Yasmin Ahmad and Elena Bernaldo of the Organisation for Economic Co-operation and Development (aid); Ibrahim Levent and Maryna Taran (external debt); Tarek Abou Chabake of the Ofice of the UN High Commissioner for Refugees (refugees); and Teresa Ciller of the World Tourism World view People Environment Organization (tourism). Ramgopal Erabelly, Shelley Fu, and William Prince provided technical assistance. Other parts of the book Jeff Lecksell of the World Bank’s Map Design Unit coordinated preparation of the maps on the inside covers. William Prince prepared User guide and the lists of online tables and indicators for each section and wrote Statistical methods, with input from Neil Fantom. Liu Cui and Federico Escaler prepared Primary data documentation. Leila Rafei prepared Partners. Database management William Prince coordinated management of the World Development Indicators database, with assistance from Liu Cui and Shelley Fu in the Data Administration and Quality Team. Operation of the database management system was made possible by Ramgopal Erabelly in the Data and Information Systems Team under the leadership of Soong Sup Lee. Design, production, and editing Azita Amjadi and Leila Rafei coordinated all stages of production with Communications Development Incorporated, which provided overall design direction, editing, and layout, led by Jack Harlow, Bruce Ross-Larson, and Christopher Trott. Elaine Wilson created the cover and graphics and typeset the book. Peter Grundy, of Peter Grundy Art & Design, and Diane Broadley, of Broadley Design, designed the report. Administrative assistance, office technology, and systems development support Elysee Kiti provided administrative assistance. JeanPierre Djomalieu, Gytis Kanchas, and Nacer Megherbi provided information technology support. Ugendran Machakkalai, Shanmugam Natarajan, Atsushi Shimo, and Malarvizhi Veerappan provided software support on the DataBank application. Publishing and dissemination The World Bank’s Publishing and Knowledge Division, under the direction of Carlos Rossel, provided assistance throughout the production process. Denise Economy States and markets Bergeron, Stephen McGroarty, Nora Ridoli, Paola Scalabrin, and Janice Tuten coordinated printing, marketing, and distribution. Merrell Tuck-Primdahl of the Development Economics Vice President’s Ofice managed the communications strategy. World Development Indicators mobile applications Software preparation and testing were managed by Shelley Fu with assistance from Prashant Chaudhari, Neil Fantom, Mohammed Omar Hadi, Soong Sup Lee, Parastoo Oloumi, William Prince, Virginia Romand, Jomo Tariku, and Malarvizhi Veerappan. Systems development was undertaken in the Data and Information Systems Team led by Soong Sup Lee. Liu Cui and William Prince provided data quality assurance. Online access Coordination of the presentation of the WDI online, through the Open Data website, the DataBank application, the table browser application, and the Application Programming Interface, was provided by Neil Fantom and Soong Sup Lee. Development and maintenance of the website were managed by a team led by Azita Amjadi and comprising George Gongadze, Timothy Herzog, Meri Jebirashvili, Jeffrey McCoy, Leila Rafei, and Jomo Tariku. Systems development was managed by a team led by Soong Sup Lee, with project management provided by Malarvizhi Veerappan. Design, programming, and testing were carried out by Ying Chi, Shelley Fu, Siddhesh Kaushik, Ugendran Machakkalai, Nacer Megherbi, Shanmugam Natarajan, Parastoo Oloumi, Manish Rathore, Ashish B. Shah, Atsushi Shimo, Maryna Taran, and Jomo Tariku. Liu Cui and William Prince coordinated production and provided data quality assurance. Multilingual translations of online content were provided by a team in the General Services Department. Client feedback The team is grateful to the many people who have taken the time to provide feedback and suggestions, which have helped improve this year’s edition. Please contact us at [email protected]. Global links Back World Development Indicators 2014 115 ECO -AUDIT Environmental Benefits Statement The World Bank is committed to preserving endangered forests and natural resources. World Development Indicators 2014 is printed on recycled paper with 30 percent postconsumer i ber in accordance with the recommended standards for paper usage set by the Green Press Initiative, a nonproi t program supporting publishers in using i ber that is not sourced from endangered forests. For more information, visit www .greenpressinitiative.org. Saved: • 12 trees • 5 million British thermal units of total energy • 1,072 pounds of net greenhouse gases • 5,816 gallons of waste water • 389 pounds of solid waste The world by region Classified according to World Bank analytical grouping Low- and middle-income economies East Asia and Paciic Middle East and North Africa High-income economies Europe and Central Asia South Asia OECD Latin America and the Caribbean Sub-Saharan Africa Other No data