64936 2 0 1 1 2 0 1 1 Copyright © 2011 by the International Bank for Reconstruction and Development/The World Bank 1818 H Street, N.W. Washington, D.C. 20433, U.S.A. All rights reserved Manufactured in the United States of America First printing 2011 This volume is a product of the staff of the International Bank for Reconstruction and Development/The World Bank. The �ndings, interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgement on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Rights and Permissions The material in this publication is copyrighted. 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Cover design: Communications Development Incorporated. Photo credits: front cover, Arne Hoel/World Bank; back cover, Arne Hoel/World Bank and Jonathan Ernst/World Bank. The map of Africa is provided by the Map Design Unit/World Bank. To order Africa Development Indicators 2011, The Little Data Book on Africa 2011 (available online only), or Africa Development In- dicators 2011–Multiple User CD-ROM, please visit www.worldbank.org/publications. To subscribe to Africa Development Indica- tors Online please visit http://publications.worldbank.org/ADI. For more information about Africa Development Indicators and its companion products, please visit www.worldbank.org/africa or email ADI@worldbank.org. Contents Foreword vii Acknowledgments ix Indicator tables 1 Users guide 3 Part I. Basic indicators and national and �scal accounts 1. Basic indicators 1.1 Basic indicators 7 2. National and �scal accounts 2.1 Gross domestic product, nominal 8 2.2 Gross domestic product, real 9 2.3 Gross domestic product growth 10 2.4 Gross domestic product per capita, real 11 2.5 Gross domestic product per capita growth 12 2.6 Gross national income, nominal 13 2.7 Gross national income, World Bank Atlas method 14 2.8 Gross national income per capita, World Bank Atlas method 15 2.9 Gross domestic product deflator (local currency series) 16 2.10 Gross domestic product deflator (U.S. dollar series) 17 2.11 Consumer price index 18 2.12 Price indexes 19 2.13 Gross domestic savings 20 2.14 Gross national savings 21 2.15 General government �nal consumption expenditure 22 2.16 Household �nal consumption expenditure 23 2.17 Final consumption expenditure plus discrepancy 24 2.18 Final consumption expenditure plus discrepancy per capita 25 2.19 Gross �xed capital formation 26 2.20 Gross general government �xed capital formation 27 2.21 Private sector �xed capital formation 28 2.22 External trade balance (exports minus imports) 29 2.23 Exports of goods and services, nominal 30 2.24 Imports of goods and services, nominal 31 2.25 Exports of goods and services as a share of GDP 32 2.26 Imports of goods and services as a share of GDP 33 2.27 Balance of payments and current account 34 2.28 Exchange rates and purchasing power parity 36 2.29 Agriculture value added 38 2.30 Industry value added 39 2.31 Services plus discrepancy value added 40 2.32 Central government �nances, expense, and revenue 41 Contents iii 2.33 Structure of demand 45 Part II. Millennium Development Goals 3. Millennium Development Goals 3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger 46 3.2 Millennium Development Goal 2: achieve universal primary education 49 3.3 Millennium Development Goal 3: promote gender equality and empower women 50 3.4 Millennium Development Goal 4: reduce child mortality 51 3.5 Millennium Development Goal 5: improve maternal health 52 3.6 Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases 53 3.7 Millennium Development Goal 7: ensure environmental sustainability 55 3.8 Millennium Development Goal 8: develop a global partnership for development 57 Part III. Development outcomes Drivers of growth 4. Private sector development 4.1 Doing Business indicators 59 4.2 Investment climate 62 4.3 Financial sector infrastructure 64 5. Trade and regional integration 5.1 International trade and tariff barriers 66 5.2 Top three exports and share in total exports, 2009 70 5.3 Regional integration, trade blocs 72 6. Infrastructure 6.1 Water and sanitation 74 6.2 Transportation 75 6.3 Information and communication technology 77 6.4 Energy 80 Participating in growth 7. Human development 7.1 Education 82 7.2 Health 84 8. Agriculture, rural development, and environment 8.1 Rural development 88 8.2 Agriculture 90 8.3 Producer food prices 92 8.4 Environment 94 8.5 Fossil fuel emissions 96 9. Labor, migration, and population 9.1 Labor force participation 98 9.2 Labor force composition 100 9.3 Unemployment 102 9.4 Migration and population 104 10. HIV/AIDS 10.1 HIV/AIDS 106 iv Africa Development Indicators 2011 11. Malaria 11.1 Malaria 110 12. Capable states and partnership 12.1 Aid and debt relief 111 12.2 Status of Paris Declaration indicators 114 12.3 Capable states 116 12.4 Governance and anticorruption indicators 118 12.5 Country Policy and Institutional Assessment ratings 120 12.6 Polity indicators 124 Technical notes 125 Technical notes references 181 Map of Africa 182 Users guide: Africa Development Indicators 2011–Multiple User CD-ROM 183 Contents v Foreword This year’s Africa Development Indicators, civil society, development partners, and which covers some 1,700 macroeconomic, citizens to monitor, study, and document sectoral, and human development indica- Africa’s economic and social development. It tors dating to the 1960s, comes at a critical also shows where we need to improve. Just time for Sub-Saharan Africa’s 48 countries 18 of 48 countries have poverty data for and 841 million people. After a decade of 2007‒10. And in the 2000s Africa averaged economic growth at nearly 5 percent a year, 1.5 poverty �gures per country, less than Africa—along with the rest of the world— half the world’s average of 3.8. One reason was hit hard by the global economic crisis, for the shortcomings is lack of statistical ca- but it rebounded within a year. In 2011 the pacity—as of 2010 only six countries have continent’s growth is expected to return to statistical capacity building indicators of precrisis levels. The poverty rate has been 70‒84 percent. But here too there has been declining at about 1 percentage point a year, progress: all but four countries now have an and progress on the Millennium Develop- official national statistics website, compared ment Goals, while insufficient to reach the with 50 percent a few years ago. More than 2015 targets in many countries, has been 20 countries have made their household sur- substantial. vey datasets available on their national data Yet, Africa faces some of the most formi- archive website, and more than 75 percent dable development challenges in the world. of Africa’s people are covered by a popula- First, growth has been uneven, with about tion census less than 10 years old. 20 fragile and confl ict-affected states seem- Since 2005 countries have developed ingly trapped in persistent poverty. Second, their national statistical systems by de- economic growth has not translated to pro- signing and implementing a National Strat- ductive jobs and more earning opportunities egy for the Development of Statistics, which for Africa’s labor force—most of which is links data with poverty reduction strategies. engaged in agriculture and informal enter- The World Bank, in collaboration with other prises—and especially for the 7‒10 million partners, is providing �nancial support and young people entering the labor force each technical advice through lending operations year. And third, Africa’s growth could be such as STATCAP, through trust funds (in faster and more widespread (and abject pov- particular the Trust Fund for Statistical Ca- erty eliminated) if it could address its most pacity Building and the Statistics for Results fundamental challenges—improving gover- Catalytic Fund), and through international nance and increasing public sector capacity. initiatives. Moving forward, the Bank will Just as the World Bank’s Africa strategy, scale up its statistical capacity development Africa’s Future and World Bank Support to It, activities, not least because it is only with seeks to harness the continent’s recent dy- credible statistics that progress on the Af- namic growth to address these development rica strategy can be monitored. In addition, challenges, so too do statistics in general, technology is being used to accelerate data and Africa Development Indicators in particu- collection, especially in underserved areas. lar, reflect both the progress and the poten- For instance, in Africa’s newest country, the tial of the continent. Africa Development Indi- Republic of South Sudan, the Bank is col- cators permits policymakers, private actors, laborating with the local statistics office to Foreword vii collect information on people’s economic To that end, since April 2010 the World situation, security, and outlook using cell Bank has made all its data freely available, phones distributed to 1,000 households in resulting in continually growing use of its 10 state capitals. online resources. Th is volume is part of the Africa Development Indicators has another, Africa Development Indicators suite of prod- more fundamental role in Africa’s develop- ucts, which also includes The Little Data Book ment. Statistics—and the information con- on Africa 2011 (available online only), the Af- tained in them—can empower citizens to rica Development Indicators 2011–Multiple hold their governments accountable. From User CD-ROM, and a data query and chart- the �rst public expenditure tracking survey ing application for mobile services. of education in Uganda to the Ushahidi plat- A tool for learning, capacity strengthen- form for tracking political violence and nat- ing, and accountability, Africa Development ural disasters, Africans have demonstrated Indicators 2011 will continue to play a critical how systematic data can mobilize citizens to role in Africa’s economic transformation. spur their governments to action. Inasmuch as governance was identi�ed as the funda- Obiageli K. Ezekwesili mental constraint to African development, Vice President Africa Development Indicators is a major in- The World Bank Group strument in relaxing that constraint. Africa Region viii Africa Development Indicators 2011 Acknowledgments Africa Development Indicators is a product of • Stuti Khemani (The political economy of the Africa Region of the World Bank. public policies and government failures). Th is report has been prepared by a core Azita Amjadi, Abdolreza Farivari, team led by Rose Mungai comprising Fran- Shelley Lai Fu, Ugendran Machakkalai, coise Genouille and Jane Njuguna in the pro- Shanmugam Natarajan, Lakshmikanthan duction of this book and its companions— Subramanian, and Malarvizhi Veerappan Africa Development Indicators Online 2011, collaborated in the online data production. Africa Development Indicators 2011—Mul- Maja Bresslauer, Mahyar Eshragh-Tabary, tiple User CD-ROM, and The Little Data Masako Hiraga, and Soong Sup Lee col- Book on Africa 2011 (online only). Yohannes laborated in the update of the live data- Kebede coordinated the Africa Development base. Software preparation and testing for Indicators Online apps platform while Mapi the CD-ROM and mobile applications was Buitano coordinated the dissemination managed by Vilas Mandelkar, with the as- of the book and its companions, and Jane sistance of Ramgopal Erabelly, Parastoo Njuguna coordinated production. The over- Oloumi, William Prince, and Jomo Tariku. all work was carried out under the guidance William Prince also collaborated in the of Shantayanan Devarajan, Chief Economist production of The Little Data Book on Africa of the Africa Region. 2011. The technical box contributors were: Jeff rey Lecksell and Bruno Bonansea of • Ghislaine Delaine and Antoine Simon- the World Bank’s Map Design Unit coordi- pietri (African statistical systems). nated preparation of the maps. • Shantayanan Devarajan (Africa’s future Ann Karasanyi and Kenneth Omondi and the World Bank’s support to it). provided administrative and logistical sup- • Quy-Toan Do (Multidimensional indices port. The core team would like to thank the of poverty). many people who provided useful com- • Punam Chuhan-Pole and Manka S. An- ments on the publication. Their feedback gwafo (Transformation of Rwanda’s cof- and suggestions helped improve this year’s fee sector: an African success story). edition. • Sailesh Tiwari and Hassan Zaman (Food Staff from External Affairs oversaw prices in Africa). printing and dissemination of the book and • Dilip Ratha, Sanket Mohapatra, Caglar its companions. Ozden, Sonia Plaza, and Abebe Shimeles Several institutions provided data to (Migration and remittances in Africa). Africa Development Indicators. Their contribu- • Bernard Harborne, Noro Aina Andri- tion is very much appreciated. amihaja, and Viola Erdmannsdoerfer Communications Development Incorpo- (Confl ict-affected and fragile states in rated provided design direction, editing, and Africa). layout. Acknowledgments ix Indicator tables Part I. Basic indicators and national and �scal accounts 1. Basic indicators 1.1 Basic indicators 7 2. National and �scal accounts 2.1 Gross domestic product, nominal 8 2.2 Gross domestic product, real 9 2.3 Gross domestic product growth 10 2.4 Gross domestic product per capita, real 11 2.5 Gross domestic product per capita growth 12 2.6 Gross national income, nominal 13 2.7 Gross national income, World Bank Atlas method 14 2.8 Gross national income per capita, World Bank Atlas method 15 2.9 Gross domestic product deflator (local currency series) 16 2.10 Gross domestic product deflator (U.S. dollar series) 17 2.11 Consumer price index 18 2.12 Price indexes 19 2.13 Gross domestic savings 20 2.14 Gross national savings 21 2.15 General government �nal consumption expenditure 22 2.16 Household �nal consumption expenditure 23 2.17 Final consumption expenditure plus discrepancy 24 2.18 Final consumption expenditure plus discrepancy per capita 25 2.19 Gross �xed capital formation 26 2.20 Gross general government �xed capital formation 27 2.21 Private sector �xed capital formation 28 2.22 External trade balance (exports minus imports) 29 2.23 Exports of goods and services, nominal 30 2.24 Imports of goods and services, nominal 31 2.25 Exports of goods and services as a share of GDP 32 2.26 Imports of goods and services as a share of GDP 33 2.27 Balance of payments and current account 34 2.28 Exchange rates and purchasing power parity 36 2.29 Agriculture value added 38 2.30 Industry value added 39 2.31 Services plus discrepancy value added 40 2.32 Central government �nances, expense, and revenue 41 2.33 Structure of demand 45 Part II. Millennium Development Goals 3. Millennium Development Goals 3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger 46 3.2 Millennium Development Goal 2: achieve universal primary education 49 3.3 Millennium Development Goal 3: promote gender equality and empower women 50 3.4 Millennium Development Goal 4: reduce child mortality 51 3.5 Millennium Development Goal 5: improve maternal health 52 Indicator tables 1 3.6 Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases 53 3.7 Millennium Development Goal 7: ensure environmental sustainability 55 3.8 Millennium Development Goal 8: develop a global partnership for development 57 Part III. Development outcomes Drivers of growth 4. Private sector development 4.1 Doing Business indicators 59 4.2 Investment climate 62 4.3 Financial sector infrastructure 64 5. Trade and regional integration 5.1 International trade and tariff barriers 66 5.2 Top three exports and share in total exports, 2009 70 5.3 Regional integration, trade blocs 72 6. Infrastructure 6.1 Water and sanitation 74 6.2 Transportation 75 6.3 Information and communication technology 77 6.4 Energy 80 Participating in growth 7. Human development 7.1 Education 82 7.2 Health 84 8. Agriculture, rural development, and environment 8.1 Rural development 88 8.2 Agriculture 90 8.3 Producer food prices 92 8.4 Environment 94 8.5 Fossil fuel emissions 96 9. Labor, migration, and population 9.1 Labor force participation 98 9.2 Labor force composition 100 9.3 Unemployment 102 9.4 Migration and population 104 10. HIV/AIDS 10.1 HIV/AIDS 106 11. Malaria 11.1 Malaria 110 12. Capable states and partnership 12.1 Aid and debt relief 111 12.2 Status of Paris Declaration indicators 114 12.3 Capable states 116 12.4 Governance and anticorruption indicators 118 12.5 Country Policy and Institutional Assessment ratings 120 12.6 Polity indicators 124 2 Africa Development Indicators 2011 Users guide Tables anticorruption indicators, and Country Pol- The tables are numbered by section. Coun- icy and Institutional Assessment ratings are tries are listed alphabetically by subregion provided for 2010. (Sub-Saharan Africa and North Africa). In- dicators are shown for the most recent year Data consistency, reliability, or period for which data are available and, in and comparability most tables, for an earlier year or period (usu- Considerable effort has been made to harmo- ally 1980, 1990, or 1995). Time-series data nize the data, but full comparability cannot be are available on the Africa Development In- assured, and care must be taken in interpreting dicators—Multiple User CD-ROM and Africa indicators. Many factors affect data availabili- Development Indicators Online. The term ty, comparability, and reliability. Data coverage country, used interchangeably with economy, may be incomplete because of circumstances does not imply political independence but affecting the collection and reporting of data, refers to any territory for which authorities such as conflicts. Although drawn from sourc- report separate social or economic statistics. es thought to be the most authoritative, data Known deviations from standard de�nitions should be construed as indicating trends and or breaks in comparability over time or across characterizing differences across economies. countries are noted in the tables. When avail- Discrepancies in data presented in earlier edi- able data are deemed too weak to provide tions of Africa Development Indicators reflect reliable measures of levels and trends or do updates from countries as well as revisions to not adequately adhere to international stan- historical series and changes in methodology. dards, the data are not shown. Readers are therefore advised not to compare data series between editions or across World Aggregate measure for region Bank publications. and subclassi�cations The aggregates are based on the World Bank’s Classi�cation of economies regional classi�cation for Sub-Saharan Af- For operational and analytical purposes the rica and North Africa, which may differ from World Bank’s main criterion for classifying common geographic usage. Former Spanish economies is gross national income (GNI) Sahara is not included in any aggregates. per capita (calculated by the World Bank Atlas method; box 1). Every economy is classi�ed Statistics as low income, middle income (subdivided Data are shown for economies as they were into lower middle and upper middle), or high constituted in 2008, and historical data are income (table 1). Low- and middle-income revised to reflect current political arrange- economies are sometimes referred to as de- ments. Exceptions are noted in the tables. veloping economies. The term is used for Consistent time-series data for 1961–2009 convenience; it is not intended to imply that are available on the Africa Development all economies in the group are experiencing Indicators—Multiple User CD-ROM and Af- similar development or that other economies rica Development Indicators Online. Data for have reached a preferred or �nal stage of de- some indicators, including macroeconomic velopment. Classi�cation by income does not statistics, Doing Business indicators, invest- necessarily reflect development status. Be- ment climate indicators, governance and cause GNI per capita changes over time, the Indicator tables 3 Box 1 The World Bank Atlas method for converting gross national income to a common denominator In calculating GNI and GNI per capita in average of these countries’ GDP deflators U.S. dollars for certain operational pur- in SDR terms, the weights being the amount poses, the World Bank Atlas conversion of each country’s currency in one SDR unit. factor is used to reduce the impact of ex- Weights vary over time because both the change rate fluctuations in cross-country composition of the SDR and the relative ex- and for calculating per capita GNI in U.S. comparison of national incomes. The World change rates for each currency change. The dollars for year t: Bank Atlas conversion factor for any year is SDR deflator is calculated in SDR terms first the average of the official exchange rate or and then converted to U.S. dollars using the alternative conversion factor for that year SDR-to-dollar World Bank Atlas conversion and the two preceding, adjusted for the dif- factor. The conversion factor is then applied ference between the rate of inflation in the to a country’s GNI. The resulting GNI in U.S. where et* is the World Bank Atlas conver- country and that in Japan, the United King- dollars is divided by the midyear population sion factor (national currency to the U.S. dom, the United States, and the euro area. for the latest of the three years to derive GNI dollar) for year t, et is the average annual A country’s inflation rate is measured by the per capita. exchange rate (national currency to the U.S. change in its GDP deflator. When official exchange rates are deemed dollar) for year t, pt is the GDP deflator for The inflation rate for Japan, the United unreliable or unrepresentative of the effec- year t, ptS$ is the SDR deflator in U.S. dollar Kingdom, the United States, and the euro tive exchange rate during a period, an alter- terms for year t, Yt$ is current GNI per capita area, representing international inflation, native estimate of the exchange rate is used in U.S. dollars in year t, Yt is current GNI is measured by the change in the “special in the World Bank Atlas formula below. (local currency) for year t, and Nt is midyear drawing rights (SDR) deflator.� The SDR is The following formulas describe the pro- population for year t. the International Monetary Fund’s unit of cedures for computing the conversion fac- account and is calculated as a weighted tor for year t: country composition of income groups may and elsewhere in Africa Development Indica- change from one edition of Africa Development tors as single-year conversion factors. Indicators to the next. Once the classi�cation is �xed for an edition, based on GNI per capita in Symbols the most recent year for which data are avail- .. means that data are not available able (2008 in this edition), all historical data or that aggregates cannot be cal- are based on the same country grouping. Low- culated because of missing data in income economies are those with a GNI per the years shown. capita of $995 or less in 2008. Middle-income $ means current U.S. dollars unless economies are those with a GNI per capita of otherwise noted. more than $995 but less than $12,126. Lower < means less than middle-income and upper middle-income > means greater than economies are separated at a GNI per capita 0 or 0.0 means zero or small enough that of $3,945. High-income economies are those the number would round to zero with a GNI per capita of $12,126 or more. at the displayed number of decimal places. Alternative conversion factors The World Bank systematically assesses the Data presentation conventions appropriateness of official exchange rates as A blank means not applicable or, for an ag- conversion factors. An alternative conversion gregate, not analytically meaningful. factor is used when the official exchange rate A billion is 1,000 million. is judged to diverge by an exceptionally large Growth rates are in real terms, unless margin from the rate effectively applied to do- other wise speci�ed. mestic transactions of foreign currencies and traded products. This applies to only a small The cutoff date for data is May 2011. number of countries. Alternative conversion However, the database may have more factors are used in the Atlas methodology recent data by the time of publication. 4 Africa Development Indicators 2011 Table 1 World Bank classi�cation of economies, 2009 (GNI per capita) Low income Lower middle income Upper middle income High income $995 or less $996–$3,945 $3,946–$12,195 $12,196 or more Benin Algeria Botswana Equatorial Guinea Burkina Faso Angola Gabon Burundi Cameroon Libya Central African Republic Cape Verde Mauritius Chad Congo, Rep. Seychelles Comoros Djibouti South Africa Congo, Dem. Rep. Egypt, Arab Rep. Côte d’Ivoire Lesotho Eritrea Morocco Ethiopia Namibia Gambia, The Sudan Ghana Swaziland Guinea Tunisia Guinea-Bissau Kenya Liberia Madagascar Malawi Mali Mauritania Mozambique Niger Nigeria Rwanda São Tomé and Príncipe Senegal Sierra Leone Somalia Tanzania Togo Uganda Zambia Zimbabwe Source: World Bank. Indicator tables 5 Participating in growth 1.1 Table Basic indicators GNI GDP per capita Adult Net official Population Population per capita, Constant 2000 prices Life Under-five literacy rate development Land area density World Bank Average expectancy mortality (% ages 15 assistance Total Growth (thousands (people Atlas method annual at birth rate Gini and older) per capita (millions) (annual %) of sq km) per sq km) (current $) $ growth (%) (years) (per 1,000) index Male Female (current $) 2009 2009 2009 2009 2009 2009 a 2000–09 2009 2009 2000–09 b 2009 2009 2009 SUB–SAHARAN AFRICA 841.0 2.5 23,636 35.6 1,130 618 2.6 52.5 130 74.8 56.3 53.2 Excluding South Africa 791.6 2.6 22,422 35.3 844 428 3.1 52.6 132 74.8 56.3 55.1 Excl. S. Africa & Nigeria 636.9 2.6 21,511 29.6 757 408 2.8 53.6 131 .. .. 65.9 Angola 18.5 2.6 1,247 14.8 3,750 1,313 9.9 47.6 161 58.6 82.9 57.6 12.9 Benin 8.9 3.1 111 80.8 750 363 0.6 61.8 118 38.6 54.2 29.1 76.4 Botswana 1.9 1.5 567 3.4 6,260 4,082 3.0 55.0 57 .. 83.8 84.4 143.4 Burkina Faso 15.8 3.4 274 57.6 510 264 1.9 53.3 166 39.6 .. .. 68.8 Burundi 8.3 2.8 26 323.3 150 112 0.2 50.9 166 33.3 72.6 60.9 66.1 Cameroon 19.5 2.2 473 41.3 1,190 694 1.0 51.4 154 44.6 .. .. 33.3 Cape Verde 0.5 1.4 4 125.5 3,010 1,763 4.8 71.3 28 50.4 90.1 80.2 387.5 Central African Republic 4.4 1.9 623 7.1 450 233 –1.0 47.3 171 43.6 69.1 42.1 53.6 Chad 11.2 2.6 1,259 8.9 600 265 6.7 48.9 209 39.8 44.5 23.1 50.1 Comoros 0.7 2.4 2 354.2 810 367 –0.3 65.8 104 64.3 79.7 68.7 76.8 Congo, Dem. Rep. 66.0 2.7 2,267 29.1 160 97 2.1 47.8 199 44.4 79.5 54.9 35.6 Congo, Rep. 3.7 1.9 342 10.8 2,080 1,267 1.8 53.7 128 47.3 .. .. 76.8 Côte d’Ivoire 21.1 2.3 318 66.3 1,070 536 –1.3 58.0 119 41.5 64.7 45.3 112.3 Djibouti 0.9 1.7 23 37.3 1,280 904 2.1 55.7 94 39.9 .. .. 187.7 Equatorial Guinea 0.7 2.6 28 24.1 12,420 8,011 13.6 50.6 145 .. 97.0 89.8 46.7 Eritrea 5.1 2.9 101 50.2 320 133 –3.4 59.9 55 .. 77.9 56.0 28.5 Ethiopia 82.8 2.6 1,000 82.8 330 201 5.7 55.7 104 29.8 .. .. 46.1 Gabon 1.5 1.8 258 5.7 7,370 4,054 0.1 60.9 69 41.5 91.4 84.1 52.6 Gambia, The 1.7 2.7 10 170.5 440 382 2.1 56.2 103 47.3 57.6 35.8 75.1 Ghana 23.8 2.1 228 104.8 1,190 343 3.5 56.8 69 42.8 72.8 60.4 66.4 Guinea 10.1 2.4 246 41.0 370 400 1.0 58.3 142 39.4 50.8 28.1 21.3 Guinea-Bissau 1.6 2.2 28 57.3 510 143 –1.4 48.2 193 35.5 66.9 38.0 90.3 Kenya 39.8 2.6 569 69.9 760 452 1.7 54.9 84 47.7 90.5 83.5 44.7 Lesotho 2.1 0.8 30 68.1 980 471 2.1 45.4 84 52.5 82.9 95.3 59.5 Liberia 4.0 4.2 96 41.1 160 148 –3.5 58.7 112 38.2 63.7 54.5 127.7 Madagascar 19.6 2.7 582 33.7 430 255 0.8 60.8 58 47.2 .. .. 22.7 Malawi 15.3 2.8 94 162.2 290 168 1.9 53.8 110 39.0 80.6 67.0 50.6 Mali 13.0 2.4 1,220 10.7 680 304 2.8 48.8 191 39.0 .. .. 75.7 Mauritania 3.3 2.3 1,031 3.2 990 462 2.0 57.0 117 39.0 64.5 50.3 87.1 Mauritius 1.3 0.5 2 628.2 7,250 4,917 2.9 72.6 17 .. 90.6 85.3 122.0 Mozambique 22.9 2.3 786 29.1 440 371 5.2 48.1 142 45.6 70.1 41.5 87.9 Namibia 2.2 1.9 823 2.6 4,270 2,673 3.3 61.6 48 .. 88.9 88.1 150.2 Niger 15.3 3.9 1,267 12.1 340 173 0.5 52.0 160 34.0 .. .. 30.7 Nigeria 154.7 2.3 911 169.9 1,190 506 4.0 48.1 138 42.9 72.0 49.8 10.7 Rwanda 10.0 2.8 25 405.3 490 334 5.1 50.6 111 53.1 75.0 66.8 93.5 São Tomé and Príncipe 0.2 1.6 1 169.5 1,130 .. .. 65.8 78 50.6 93.7 84.0 188.7 Senegal 12.5 2.6 193 65.1 1,040 534 1.6 55.9 93 39.2 61.8 38.7 81.2 Seychelles 0.1 1.2 0 191.2 8,480 7,389 0.9 73.7 12 65.8 .. .. 263.7 Sierra Leone 5.7 2.4 72 79.5 340 265 5.8 47.9 192 42.5 52.7 30.1 76.8 Somalia 9.1 2.3 627 14.6 .. .. .. 50.1 180 .. .. .. 72.4 South Africa 49.3 1.1 1,214 40.6 5,760 3,689 2.8 51.6 62 57.8 .. .. 21.8 Sudan 42.3 2.2 2,376 17.8 1,220 537 5.0 58.5 108 .. 79.6 60.8 54.1 Swaziland 1.2 1.5 17 68.9 2,470 1,553 1.6 46.3 73 50.7 87.8 86.2 48.9 Tanzania 43.7 2.9 886 49.4 490 426 4.2 56.3 108 37.6 79.0 66.9 67.1 Togo 6.6 2.4 54 121.7 440 247 –0.1 62.9 98 34.4 .. .. 75.4 Uganda 32.7 3.3 197 166.0 460 366 4.3 53.4 128 44.3 .. .. 54.6 Zambia 12.9 2.5 743 17.4 960 401 3.0 46.3 141 50.7 80.6 61.3 98.1 Zimbabwe 12.5 0.5 387 32.4 360 288 –7.4 45.4 90 .. 94.7 89.4 58.8 NORTH AFRICA 166.7 1.6 5,738 29.1 3,280 2,191 3.1 71.5 26 .. .. 17.2 Algeria 34.9 1.5 2,382 14.7 4,420 2,190 2.5 72.6 32 .. .. .. 9.1 Egypt, Arab Rep. 83.0 1.8 995 83.4 2,070 1,836 3.0 70.3 21 32.1 .. .. 11.1 Libya 6.4 2.0 1,760 3.6 12,020 7,692 3.3 74.5 19 .. 95.2 82.0 6.1 Morocco 32.0 1.2 446 71.7 2,810 1,809 3.8 71.6 38 40.9 68.9 43.9 28.5 Tunisia 10.4 1.0 155 67.2 3,720 2,805 3.9 74.5 21 40.8 .. .. 45.4 ALL AFRICA 1,007.7 2.3 29,375 34.3 1,487 879 2.6 55.6 119 .. .. 47.2 a. Provisional. b. Data are for the most recent year available during the period speci�ed. Basic indicators Part I. Basic indicators and national and fiscal accounts 7 2.1 Table Gross domestic product, nominal Current prices ($ millions) Annual average growth (%) 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 272,131 300,900 448,082 559,094 653,676 763,395 879,541 1,009,865 954,357 1.0 1.5 15.2 Excluding South Africa 193,303 189,013 279,985 340,092 406,780 502,768 593,774 734,377 669,740 –0.7 1.2 16.7 Excl. S. Africa & Nigeria 124,769 160,605 212,189 252,030 294,213 355,441 427,372 526,649 496,310 3.0 0.8 15.7 Angola .. 10,260 13,956 19,775 30,632 45,163 59,263 84,179 75,493 .. –3.8 32.9 Benin 1,405 1,845 3,558 4,047 4,287 4,735 5,546 6,683 6,656 2.3 3.5 13.8 Botswana 1,061 3,792 8,087 10,049 10,255 11,255 12,386 13,545 11,823 12.6 4.6 10.8 Burkina Faso 1,929 3,101 4,270 5,109 5,427 5,771 6,767 8,046 8,141 4.8 0.0 14.4 Burundi 920 1,132 595 664 796 919 980 1,169 1,325 2.2 –3.3 8.4 Cameroon 6,741 11,152 13,622 15,775 16,588 17,957 20,686 23,736 22,186 7.3 –2.5 11.2 Cape Verde .. 339 797 925 999 1,108 1,331 1,531 1,549 .. 6.4 14.1 Central African Republic 797 1,488 1,139 1,270 1,350 1,477 1,712 1,988 2,006 8.1 –4.3 9.5 Chad 1,033 1,739 2,737 4,415 5,302 6,099 7,016 8,357 6,839 5.7 –1.3 23.2 Comoros 124 250 324 362 387 403 465 530 535 8.0 –2.0 12.0 Congo, Dem. Rep. 14,395 9,350 5,673 6,570 7,104 8,543 9,977 11,588 10,575 –6.2 –7.1 12.0 Congo, Rep. 1,706 2,799 3,496 4,649 6,087 7,731 8,344 11,789 9,580 2.3 –2.4 18.2 Côte d’Ivoire 10,175 10,796 13,737 15,481 16,363 17,367 19,796 23,414 23,304 2.0 2.2 10.4 Djibouti .. 452 622 666 709 769 848 983 1,049 .. 1.7 7.6 Equatorial Guinea .. 132 2,952 5,241 8,217 9,603 12,576 18,525 10,413 .. 22.5 34.1 Eritrea .. .. 771 939 1,171 1,281 1,374 1,654 1,873 .. 7.2 13.7 Ethiopia .. 12,083 8,539 10,034 12,286 15,134 19,182 25,899 28,526 5.9 –5.7 16.9 Gabon 4,279 5,952 6,055 7,178 8,666 9,546 11,571 14,535 11,062 –0.5 –1.7 13.4 Gambia, The 241 317 367 401 461 508 651 822 733 1.7 3.6 8.6 Ghana 4,445 5,886 7,624 8,872 10,720 20,388 24,632 28,527 26,169 3.2 2.6 25.0 Guinea .. 2,667 3,446 3,666 2,937 2,821 4,209 3,778 4,103 .. 3.0 3.2 Guinea-Bissau 111 244 475 535 590 597 692 847 837 3.7 –0.6 19.4 Kenya 7,265 8,591 14,904 16,096 18,738 22,502 27,166 30,031 29,376 2.6 7.7 11.8 Lesotho 431 541 947 1,206 1,315 1,417 1,577 1,594 1,579 –0.8 4.1 11.8 Liberia 954 384 410 460 530 612 735 843 876 –0.5 1.8 6.1 Madagascar 4,042 3,081 5,474 4,364 5,039 5,515 7,343 9,424 8,590 –5.2 3.4 9.5 Malawi 1,238 1,881 2,425 2,625 2,755 3,117 3,458 4,074 4,727 1.8 0.2 10.9 Mali 1,787 2,421 4,362 4,874 5,305 5,866 7,146 8,722 8,996 3.4 0.4 16.3 Mauritania 709 1,020 1,285 1,548 1,858 2,699 2,838 3,589 3,024 3.5 1.4 15.9 Mauritius 1,137 2,653 5,610 6,386 6,284 6,507 7,521 9,310 8,589 8.8 5.8 8.5 Mozambique 3,526 2,463 4,666 5,698 6,579 7,096 8,030 9,867 9,790 –4.7 8.3 11.8 Namibia 2,169 2,350 4,934 6,606 7,262 7,981 8,806 8,970 9,265 0.1 4.6 13.3 Niger 2,509 2,481 2,731 3,053 3,405 3,645 4,246 5,357 5,383 –0.2 –1.8 13.8 Nigeria 64,202 28,472 67,656 87,845 112,249 146,867 165,921 207,118 173,004 –12.0 3.2 19.9 Rwanda 1,163 2,584 1,846 2,089 2,581 3,111 3,741 4,691 5,216 8.6 –2.0 15.0 São Tomé and Príncipe .. .. 98 107 114 125 145 174 191 .. .. 11.5 Senegal 3,503 5,717 6,871 8,041 8,703 9,378 11,334 13,175 12,822 6.2 –1.8 13.4 Seychelles 147 369 706 700 884 968 1,026 926 764 9.3 6.0 4.9 Sierra Leone 1,101 650 991 1,096 1,239 1,422 1,664 1,955 1,942 –4.3 0.6 13.1 Somalia 604 917 .. .. .. .. .. .. .. 6.4 .. .. South Africa 80,710 112,014 168,219 219,093 247,064 261,007 286,302 276,451 285,366 4.1 2.1 12.2 Sudan 7,617 12,409 17,780 21,684 27,386 36,401 46,531 58,032 54,681 10.1 0.8 21.2 Swaziland 543 1,115 1,796 2,282 2,524 2,670 2,950 2,840 3,001 1.9 4.4 11.3 Tanzania .. 4,259 11,659 12,826 14,142 14,331 16,826 20,715 21,368 .. 10.1 9.1 Togo 1,136 1,628 1,759 2,061 2,108 2,218 2,499 2,899 2,855 4.5 –0.1 10.0 Uganda 1,245 4,304 6,337 8,469 9,000 9,922 11,892 14,441 16,043 20.7 8.8 12.6 Zambia 3,884 3,288 4,374 5,423 7,157 10,675 11,410 14,382 12,805 –3.1 0.2 20.3 Zimbabwe 6,679 8,784 5,658 5,671 5,583 5,203 5,018 4,247 5,625 –0.1 –1.5 –3.6 NORTH AFRICA 111,546 172,192 249,820 282,321 324,517 377,737 448,926 556,721 522,285 4.8 4.2 11.2 Algeria 42,345 62,045 68,019 85,014 102,339 117,169 135,804 170,989 140,577 4.5 –1.2 14.6 Egypt, Arab Rep. 22,912 43,130 82,924 78,845 89,686 107,484 130,473 162,836 188,413 6.8 10.8 7.7 Libya .. 28,905 24,063 33,385 44,000 56,484 71,803 93,168 62,360 .. –0.9 15.0 Morocco 18,821 25,821 49,823 56,948 59,524 65,637 75,226 88,883 91,375 3.7 5.1 11.6 Tunisia 8,743 12,291 24,992 28,129 28,968 30,962 35,620 40,845 39,561 2.3 6.0 9.3 ALL AFRICA 386,556 472,997 697,735 841,140 977,859 1,140,739 1,328,046 1,566,195 1,476,265 2.2 2.5 13.7 a. Provisional. 8 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.2 Table Gross domestic product, real Constant prices (2000 $ millions) Annual average growth (%) 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 227,433 273,288 383,153 407,008 430,323 457,294 486,811 511,548 520,086 1.8 2.4 5.1 Excluding South Africa 132,121 162,355 237,556 254,798 270,086 288,086 308,333 326,524 338,402 2.1 2.7 5.8 Excl. S. Africa & Nigeria 99,187 127,336 184,367 195,958 208,072 222,229 238,231 252,216 259,922 2.6 2.8 5.5 Angola .. 8,464 11,137 12,383 14,935 17,707 21,298 24,136 24,295 .. 1.0 13.1 Benin 1,084 1,412 2,571 2,650 2,727 2,839 2,970 3,121 3,240 2.7 4.7 4.0 Botswana 1,209 3,395 6,751 7,154 7,271 7,643 8,010 8,260 7,959 10.9 4.8 4.4 Burkina Faso 1,101 1,556 3,150 3,296 3,505 3,698 3,831 4,023 4,164 4.0 5.5 5.4 Burundi 559 865 747 783 790 830 860 899 930 4.5 –3.2 3.0 Cameroon 6,339 8,793 11,393 11,815 12,087 12,476 12,913 13,287 13,553 4.5 1.3 3.3 Cape Verde .. 303 613 608 681 750 815 867 891 6.3 5.9 6.4 Central African Republic 735 815 884 892 914 949 984 1,005 1,029 1.6 1.8 0.8 Chad 665 1,106 1,925 2,572 3,018 3,024 3,030 3,018 2,970 6.7 2.3 10.2 Comoros 136 181 223 222 232 234 236 238 242 2.9 1.2 1.9 Congo, Dem. Rep. 7,016 7,659 4,614 4,921 5,239 5,505 5,849 6,212 6,379 2.1 –5.0 5.2 Congo, Rep. 1,746 2,796 3,524 3,647 3,932 4,173 4,107 4,335 4,665 3.8 0.8 4.0 Côte d’Ivoire 7,727 8,298 10,106 10,287 10,417 10,488 10,668 10,904 11,296 0.7 3.5 0.8 Djibouti .. 660 596 619 638 669 703 744 781 .. –2.3 4.0 Equatorial Guinea .. 207 2,764 3,815 4,187 4,239 5,148 5,730 5,418 .. 20.7 16.8 Eritrea .. .. 692 702 720 713 722 652 675 .. 7.9 0.2 Ethiopia .. 6,234 8,798 9,993 11,174 12,384 13,803 15,291 16,623 2.1 3.7 8.5 Gabon 3,594 4,298 5,290 5,361 5,523 5,588 5,899 6,035 5,978 0.5 2.9 2.1 Gambia, The 213 305 460 493 518 552 587 623 651 3.5 2.7 5.2 Ghana 2,640 3,267 5,691 6,010 6,364 6,771 7,209 7,817 8,181 2.6 4.3 5.8 Guinea .. 2,088 3,503 3,585 3,692 3,784 3,851 4,041 4,030 .. 4.4 3.0 Guinea-Bissau 115 186 195 201 211 215 216 224 230 3.8 1.4 1.0 Kenya 7,078 10,544 13,631 14,327 15,173 16,132 17,263 17,531 17,985 4.1 2.2 4.4 Lesotho 380 504 819 838 847 902 924 965 973 2.3 4.0 3.1 Liberia 1,391 433 411 422 444 479 524 561 587 –3.3 0.2 0.0 Madagascar 3,099 3,266 3,941 4,148 4,339 4,557 4,842 5,187 4,997 0.8 1.7 3.6 Malawi 1,000 1,243 1,778 1,875 1,924 2,072 2,192 2,381 2,562 2.4 3.8 4.8 Mali 1,536 1,630 3,039 3,105 3,294 3,469 3,618 3,795 3,958 0.5 3.9 5.3 Mauritania 693 816 1,188 1,249 1,317 1,573 1,483 1,537 1,521 1.9 2.9 4.7 Mauritius 1,519 2,726 4,975 5,261 5,327 5,537 5,842 6,140 6,271 6.1 5.0 3.7 Mozambique 2,462 2,499 5,485 5,918 6,414 6,971 7,478 7,982 8,488 –0.9 6.0 7.9 Namibia 2,292 2,591 4,320 4,850 4,972 5,324 5,610 5,851 5,804 1.1 4.0 5.3 Niger 1,523 1,507 2,089 2,091 2,185 2,312 2,388 2,615 2,641 –0.4 2.4 4.3 Nigeria 31,452 34,978 53,102 58,731 61,903 65,740 69,981 74,179 78,333 0.8 2.4 6.6 Rwanda 1,368 1,673 2,135 2,293 2,507 2,737 2,888 3,211 3,343 2.5 –1.6 7.6 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 2,683 3,463 5,268 5,579 5,893 6,042 6,335 6,546 6,691 2.7 2.8 4.3 Seychelles 292 395 572 556 598 647 710 704 650 3.1 4.5 1.7 Sierra Leone 929 1,014 1,047 1,125 1,206 1,294 1,377 1,454 1,512 0.5 –5.3 9.5 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 95,503 110,945 145,693 152,329 160,367 169,354 178,644 185,216 181,923 1.4 2.0 4.1 Sudan 5,525 7,062 14,821 15,579 16,564 18,434 20,308 21,697 22,678 2.4 5.4 7.3 Swaziland 470 1,033 1,592 1,632 1,668 1,715 1,776 1,818 1,840 7.4 3.1 2.6 Tanzania .. 7,547 12,367 13,335 14,318 15,282 16,375 17,593 18,652 .. 2.8 7.1 Togo 964 1,071 1,419 1,461 1,479 1,537 1,566 1,594 1,634 1.5 3.6 2.5 Uganda .. 3,215 7,542 8,055 8,565 9,489 10,287 11,183 11,973 2.3 7.4 7.8 Zambia 2,730 3,028 3,687 3,886 4,089 4,342 4,611 4,880 5,192 1.0 0.2 5.4 Zimbabwe 3,699 5,691 5,069 4,720 4,431 4,284 4,127 3,415 3,609 3.3 2.7 –7.5 NORTH AFRICA 118,981 178,165 273,922 286,676 301,162 318,159 334,909 352,333 365,307 4.2 3.2 4.8 Algeria 35,291 46,367 62,918 66,190 69,565 70,956 73,085 74,839 76,411 2.9 1.7 4.0 Egypt, Arab Rep. 38,506 65,579 109,198 113,666 118,749 126,876 135,869 145,592 152,360 5.5 4.3 4.9 Libya .. .. 36,180 37,771 41,511 43,960 46,598 48,368 49,384 .. .. 5.4 Morocco 20,086 29,312 43,735 45,835 47,201 50,863 52,240 55,158 57,888 4.2 2.4 5.0 Tunisia 8,622 12,237 21,891 23,213 24,136 25,503 27,118 28,376 29,265 3.2 4.6 4.9 ALL AFRICA 348,882 452,854 657,068 693,666 731,462 775,424 821,680 863,841 885,368 2.6 2.7 5.0 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 9 Table 2.3 Gross domestic product growth Annual growth (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 4.0 1.1 4.2 6.2 5.7 6.3 6.5 5.1 1.7 2.2 2.1 4.6 Excluding South Africa 1.7 2.1 5.0 7.3 6.0 6.7 7.0 5.9 3.6 2.1 2.5 5.2 Excl. S. Africa & Nigeria 0.7 0.6 3.5 6.3 6.2 6.8 7.2 5.9 3.1 2.5 2.4 5.0 Angola .. –0.3 3.3 11.2 20.6 18.6 20.3 13.3 0.7 4.2 1.0 10.9 Benin 6.8 3.2 3.9 3.1 2.9 4.1 4.6 5.1 3.8 3.1 4.5 4.3 Botswana 12.0 6.8 6.3 6.0 1.6 5.1 4.8 3.1 –3.7 11.5 5.3 4.2 Burkina Faso 0.8 –0.6 8.0 4.6 6.4 5.5 3.6 5.0 3.5 3.7 5.1 5.0 Burundi 1.0 3.5 –1.2 4.8 0.9 5.1 3.6 4.5 3.5 4.3 –1.4 2.7 Cameroon –2.0 –6.1 4.0 3.7 2.3 3.2 3.5 2.9 2.0 4.0 0.4 3.4 Cape Verde .. 0.7 6.2 –0.7 11.9 10.1 8.6 6.5 2.8 6.4 5.2 6.0 Central African Republic –4.5 –2.1 –7.6 1.0 2.4 3.8 3.7 2.2 2.4 0.9 1.3 1.0 Chad –6.0 –4.2 14.7 33.6 17.3 0.2 0.2 –0.4 –1.6 5.4 2.2 8.3 Comoros .. 5.1 2.5 –0.2 4.2 1.2 0.5 1.0 1.8 2.7 1.6 2.0 Congo, Dem. Rep. 2.2 –6.6 5.8 6.6 6.5 5.1 6.3 6.2 2.7 1.8 –5.5 3.4 Congo, Rep. 17.6 1.0 0.8 3.5 7.8 6.1 –1.6 5.6 7.6 6.8 0.8 4.6 Côte d’Ivoire –11.0 –1.1 –1.6 1.8 1.3 0.7 1.7 2.2 3.6 –0.2 2.6 0.5 Djibouti .. .. 3.2 3.8 3.2 4.8 5.1 5.8 5.0 .. –2.0 3.6 Equatorial Guinea .. 3.3 14.0 38.0 9.7 1.3 21.4 11.3 –5.4 0.9 20.2 18.5 Eritrea .. .. –2.7 1.5 2.6 –1.0 1.3 –9.8 3.6 .. 8.1 –0.6 Ethiopia .. 2.7 –2.2 13.6 11.8 10.8 11.5 10.8 8.7 2.4 2.7 8.1 Gabon 2.6 5.2 2.5 1.3 3.0 1.2 5.6 2.3 –1.0 1.9 2.5 1.5 Gambia, The 6.3 3.6 6.9 7.1 5.1 6.6 6.3 6.1 4.6 3.9 3.1 5.1 Ghana 0.5 3.3 5.2 5.6 5.9 6.4 6.5 8.4 4.7 2.0 4.3 5.5 Guinea .. 4.3 5.4 2.3 3.0 2.5 1.8 4.9 –0.3 4.5 4.3 2.8 Guinea-Bissau –16.0 6.1 –2.9 3.1 5.0 2.2 0.3 3.5 3.0 2.9 2.0 1.5 Kenya 5.6 4.2 2.9 5.1 5.9 6.3 7.0 1.6 2.6 4.2 2.2 3.6 Lesotho –2.7 6.5 4.3 2.3 1.1 6.5 2.4 4.5 0.9 2.1 4.1 3.3 Liberia –4.1 –51.0 –31.3 2.6 5.3 7.8 9.4 7.1 4.6 –4.5 1.2 3.8 Madagascar 0.8 3.1 9.8 5.3 4.6 5.0 6.2 7.1 –3.7 0.4 1.6 3.2 Malawi 0.4 5.7 5.5 5.5 2.6 7.7 5.8 8.6 7.6 1.7 4.1 4.2 Mali –4.3 –1.9 7.4 2.2 6.1 5.3 4.3 4.9 4.3 0.6 3.6 5.4 Mauritania 3.4 –1.8 5.6 5.2 5.4 19.4 –5.7 3.7 –1.1 2.2 2.6 3.8 Mauritius –10.1 7.2 3.7 5.7 1.2 3.9 5.5 5.1 2.1 4.3 5.2 4.1 Mozambique .. 1.0 6.0 7.9 8.4 8.7 7.3 6.7 6.3 0.4 5.5 7.3 Namibia .. 2.5 4.2 12.3 2.5 7.1 5.4 4.3 –0.8 1.1 4.1 4.4 Niger –2.2 –1.3 5.3 0.1 4.5 5.8 3.3 9.5 1.0 0.0 1.9 3.8 Nigeria 4.2 8.2 10.3 10.6 5.4 6.2 6.4 6.0 5.6 0.9 3.1 6.1 Rwanda 9.0 –2.4 2.2 7.4 9.3 9.2 5.5 11.2 4.1 3.2 2.1 7.7 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal –3.3 –0.7 6.7 5.9 5.6 2.5 4.9 3.3 2.2 2.4 2.7 4.0 Seychelles –4.2 7.0 –5.9 –2.9 7.5 8.3 9.7 –0.9 –7.6 2.1 4.9 1.1 Sierra Leone 4.8 3.4 9.3 7.5 7.2 7.3 6.4 5.5 4.0 1.1 –4.3 9.7 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 6.6 –0.3 2.9 4.6 5.3 5.6 5.5 3.7 –1.8 2.2 1.4 3.6 Sudan 1.5 –5.5 7.1 5.1 6.3 11.3 10.2 6.8 4.5 3.4 4.4 7.1 Swaziland 12.4 9.8 3.9 2.5 2.2 2.9 3.5 2.4 1.2 8.6 3.7 3.1 Tanzania .. 7.0 6.9 7.8 7.4 6.7 7.1 7.4 6.0 3.8 3.3 6.8 Togo 14.6 –0.2 2.7 3.0 1.2 3.9 1.9 1.8 2.5 2.6 2.6 2.0 Uganda .. 6.5 6.5 6.8 6.3 10.8 8.4 8.7 7.1 3.0 7.1 7.2 Zambia 3.0 –0.5 5.1 5.4 5.2 6.2 6.2 5.8 6.4 1.4 0.4 5.2 Zimbabwe 14.4 7.0 –17.2 –6.9 –6.1 –3.3 –3.7 –17.3 5.7 5.2 2.6 –5.9 NORTH AFRICA 5.2 4.0 5.9 4.7 5.1 5.6 5.3 5.2 3.7 4.3 3.3 4.5 Algeria 0.8 0.8 6.9 5.2 5.1 2.0 3.0 2.4 2.1 2.8 1.6 3.6 Egypt, Arab Rep. 10.0 5.7 3.2 4.1 4.5 6.8 7.1 7.2 4.6 5.9 4.3 4.9 Libya .. .. 13.0 4.4 9.9 5.9 6.0 3.8 2.1 .. .. 4.3 Morocco 3.6 4.0 6.3 4.8 3.0 7.8 2.7 5.6 4.9 3.9 2.8 4.8 Tunisia 7.4 7.9 5.6 6.0 4.0 5.7 6.3 4.6 3.1 3.6 5.1 4.7 ALL AFRICA 4.4 2.2 4.9 5.6 5.4 6.0 6.0 5.1 2.5 2.9 2.5 4.6 a. Provisional. 10 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.4 Table Gross domestic product per capita, real Constant prices (2000 $) Annual average growth (%) 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 587 530 528 547 564 585 608 623 618 –0.9 –0.6 2.6 Excluding South Africa 367 338 350 365 378 393 410 423 428 –0.8 –0.2 3.1 Excl. S. Africa & Nigeria 347 332 338 350 362 377 394 406 408 –0.2 –0.3 2.8 Angola .. 794 712 767 899 1,036 1,213 1,339 1,313 .. –2.4 9.9 Benin 305 294 349 348 347 349 354 360 363 –0.4 1.3 0.6 Botswana 1,227 2,512 3,764 3,941 3,954 4,099 4,233 4,300 4,082 7.6 2.5 3.0 Burkina Faso 160 177 245 248 255 260 260 264 264 1.4 2.8 1.9 Burundi 135 152 107 109 107 109 110 111 112 1.2 –3.4 0.2 Cameroon 698 719 670 678 678 684 692 696 694 1.4 –1.6 1.0 Cape Verde .. 854 1,325 1,294 1,426 1,547 1,657 1,739 1,763 .. 3.4 4.8 Central African Republic 324 278 223 222 223 227 231 232 233 –1.2 –0.9 –1.0 Chad 144 181 206 265 301 293 285 277 265 3.4 –0.6 6.7 Comoros 405 416 387 378 386 382 375 370 367 0.0 –1.1 –0.3 Congo, Dem. Rep. 258 207 83 86 89 91 94 97 97 –1.3 –8.8 2.1 Congo, Rep. 962 1,143 1,081 1,092 1,151 1,197 1,157 1,199 1,267 2.1 –1.4 1.8 Côte d’Ivoire 918 658 548 546 541 533 530 530 536 –3.2 –0.3 –1.3 Djibouti .. 1,178 767 782 793 816 843 876 904 .. –4.7 2.1 Equatorial Guinea .. 547 4,796 6,439 6,877 6,779 8,017 8,692 8,011 .. 15.2 13.6 Eritrea .. .. 167 163 161 154 151 132 133 .. .. –3.4 Ethiopia .. 129 124 137 150 162 176 189 201 .. –0.7 5.7 Gabon 5,274 4,640 4,020 3,993 4,034 4,004 4,148 4,168 4,054 –1.6 –0.9 0.1 Gambia, The 346 340 321 333 340 351 363 375 382 –0.2 –0.8 2.1 Ghana 239 218 272 280 290 302 315 335 343 –1.1 1.6 3.5 Guinea .. 340 395 397 400 402 401 411 400 .. 1.0 1.0 Guinea-Bissau 137 182 139 140 143 143 140 142 143 2.8 –1.6 –1.4 Kenya 435 450 401 411 424 439 457 452 452 0.3 –1.0 1.7 Lesotho 293 315 419 424 424 448 455 471 471 0.3 2.1 2.1 Liberia 728 200 131 131 133 138 144 148 148 –6.7 –1.9 –3.5 Madagascar 360 290 237 242 246 252 260 271 255 –2.4 –1.7 0.8 Malawi 161 132 138 141 141 148 152 160 168 –2.4 1.4 1.9 Mali 214 188 270 269 278 286 292 299 304 –1.0 2.1 2.8 Mauritania 454 410 420 430 441 514 472 478 462 –0.6 0.2 2.0 Mauritius 1,573 2,579 4,069 4,266 4,284 4,419 4,634 4,839 4,917 4.8 3.6 2.9 Mozambique 203 185 277 291 308 326 342 357 371 –1.0 2.8 5.2 Namibia 2,262 1,828 2,233 2,460 2,475 2,599 2,686 2,747 2,673 –2.2 1.6 3.3 Niger 257 191 171 166 167 170 169 178 173 –2.8 –1.2 0.5 Nigeria 422 359 396 427 439 456 474 491 506 –2.4 0.0 4.0 Rwanda 263 234 246 260 279 297 306 330 334 –1.1 –0.9 5.1 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 476 460 492 508 522 522 533 536 534 0.0 0.3 1.6 Seychelles 4,532 5,645 6,913 6,740 7,209 7,651 8,350 8,092 7,389 1.8 2.9 0.9 Sierra Leone 285 248 221 229 236 246 254 261 265 –1.7 –5.7 5.8 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 3,463 3,152 3,159 3,264 3,398 3,548 3,702 3,796 3,689 –0.8 –0.7 2.8 Sudan 269 261 399 411 428 466 502 525 537 0.5 2.8 5.0 Swaziland 780 1,196 1,437 1,463 1,483 1,509 1,542 1,557 1,553 4.1 0.7 1.6 Tanzania .. 297 335 351 367 381 397 414 426 .. –0.2 4.2 Togo 346 273 249 250 247 250 249 247 247 –2.3 –0.4 –0.1 Uganda .. 181 281 290 298 320 336 353 366 .. 3.7 4.3 Zambia 473 383 329 339 348 361 375 387 401 –2.0 –2.5 3.0 Zimbabwe 508 544 405 378 355 344 332 274 288 0.3 0.1 –7.4 NORTH AFRICA 1,290 1,480 1,808 1,862 1,925 2,001 2,073 2,147 2,191 1.3 1.3 3.1 Algeria 1,876 1,834 1,973 2,045 2,117 2,128 2,159 2,177 2,190 –0.1 –0.3 2.5 Egypt, Arab Rep. 867 1,135 1,470 1,501 1,539 1,614 1,697 1,786 1,836 2.6 2.1 3.0 Libya .. .. 6,364 6,509 7,009 7,272 7,554 7,685 7,692 .. .. 3.3 Morocco 1,027 1,182 1,467 1,520 1,548 1,649 1,673 1,745 1,809 1.3 0.9 3.8 Tunisia 1,351 1,501 2,225 2,337 2,407 2,518 2,652 2,748 2,805 0.6 3.0 3.9 ALL AFRICA 727 712 749 773 796 825 854 877 879 –0.2 0.0 2.6 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 11 Table 2.5 Gross domestic product per capita growth Annual growth (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 1.0 –1.6 1.6 3.6 3.2 3.7 3.9 2.5 –0.8 –0.7 –0.6 2.1 Excluding South Africa –1.3 –0.7 2.3 4.6 3.3 4.0 4.3 3.3 1.1 –0.9 –0.2 2.6 Excl. S. Africa & Nigeria –2.3 –2.3 0.9 3.6 3.5 4.1 4.5 3.2 0.4 –0.4 –0.4 2.3 Angola .. –3.1 0.1 7.8 17.1 15.3 17.1 10.4 –1.9 1.5 –1.9 7.7 Benin 3.8 –0.1 0.4 –0.3 –0.5 0.8 1.3 1.8 0.6 0.2 1.1 0.9 Botswana 8.0 3.7 5.0 4.7 0.3 3.7 3.3 1.6 –5.1 7.9 3.2 2.7 Burkina Faso –1.4 –3.3 4.6 1.2 2.8 2.0 0.1 1.5 0.1 1.2 2.2 1.6 Burundi –1.9 0.9 –3.9 1.8 –2.1 2.0 0.5 1.4 0.6 1.0 –2.8 0.0 Cameroon –4.8 –8.9 1.6 1.3 0.0 0.9 1.2 0.6 –0.3 1.0 –2.2 1.1 Cape Verde .. –1.5 4.4 –2.3 10.2 8.5 7.1 5.0 1.4 4.2 3.0 4.4 Central African Republic –7.0 –4.4 –9.2 –0.8 0.6 1.9 1.8 0.3 0.5 –1.6 –1.2 –0.9 Chad –8.0 –7.2 10.6 29.1 13.6 –2.8 –2.6 –3.1 –4.2 2.6 –1.0 4.9 Comoros .. 2.4 0.3 –2.3 2.1 –0.9 –1.9 –1.4 –0.6 0.1 –0.7 –0.2 Congo, Dem. Rep. –0.7 –9.9 2.5 3.4 3.3 2.1 3.3 3.3 0.0 –1.2 –8.5 0.4 Congo, Rep. 14.0 –1.8 –1.7 1.0 5.4 4.0 –3.4 3.7 5.6 3.6 –1.4 2.4 Côte d’Ivoire –15.0 –4.6 –3.6 –0.3 –0.9 –1.5 –0.6 –0.1 1.2 –4.3 –0.7 –1.8 Djibouti .. .. 1.3 2.0 1.4 2.9 3.2 3.9 3.2 .. –4.5 1.6 Equatorial Guinea .. –0.1 10.8 34.2 6.8 –1.4 18.3 8.4 –7.8 –2.9 16.3 15.3 Eritrea .. .. –6.7 –2.6 –1.2 –4.3 –1.9 –12.5 0.6 .. 6.5 –4.1 Ethiopia .. –0.6 –4.7 10.7 9.0 8.0 8.6 7.9 5.9 –0.8 –0.5 5.3 Gabon –0.3 1.9 0.4 –0.7 1.0 –0.7 3.6 0.5 –2.7 –1.2 –0.5 –0.5 Gambia, The 2.7 –0.5 3.5 3.8 2.0 3.5 3.4 3.2 1.8 0.2 –0.7 1.9 Ghana –1.9 0.5 2.8 3.2 3.6 4.1 4.2 6.2 2.5 –1.0 1.5 3.2 Guinea .. 0.6 3.5 0.4 1.0 0.4 –0.4 2.6 –2.6 1.4 1.0 0.8 Guinea-Bissau –18.5 3.6 –5.3 0.6 2.6 –0.1 –1.9 1.2 0.7 0.8 –0.5 –0.9 Kenya 1.7 0.7 0.3 2.4 3.2 3.6 4.2 –1.1 –0.1 0.4 –0.8 1.0 Lesotho –5.2 4.9 3.3 1.3 0.1 5.5 1.5 3.6 0.0 –0.1 2.4 2.2 Liberia –7.3 –50.0 –33.1 –0.2 1.8 3.6 4.7 2.4 0.3 –6.2 –2.3 –0.4 Madagascar –1.8 0.1 6.7 2.3 1.7 2.2 3.4 4.3 –6.2 –2.3 –1.4 0.4 Malawi –2.6 1.8 2.6 2.6 –0.2 4.7 2.9 5.6 4.7 –2.4 1.8 1.2 Mali –6.0 –3.8 4.9 –0.2 3.6 2.8 1.9 2.4 1.9 –1.3 1.6 3.0 Mauritania 0.5 –4.3 2.7 2.4 2.7 16.4 –8.0 1.2 –3.3 –0.5 –0.1 1.1 Mauritius –11.4 6.4 2.6 4.8 0.4 3.1 4.9 4.4 1.6 3.3 4.0 3.3 Mozambique .. –0.3 3.2 5.1 5.7 6.0 4.8 4.3 4.0 –0.6 2.6 4.6 Namibia .. –1.3 2.3 10.2 0.6 5.0 3.3 2.3 –2.7 –2.2 1.4 2.4 Niger –5.1 –4.3 1.8 –3.3 0.8 1.9 –0.6 5.3 –2.9 –2.8 –1.4 0.1 Nigeria 1.2 5.4 7.7 8.0 2.9 3.7 4.0 3.6 3.2 –1.8 0.5 3.6 Rwanda 5.4 –2.0 0.5 5.8 7.2 6.6 2.8 8.2 1.2 –0.4 1.3 4.5 São Tomé and Príncipe .. .. 3.6 4.8 3.9 5.0 4.3 4.1 2.4 .. .. 4.7 Senegal –6.0 –3.5 3.9 3.2 2.9 –0.1 2.1 0.6 –0.4 –0.5 –0.1 1.3 Seychelles –5.4 6.1 –4.9 –2.5 7.0 6.1 9.1 –3.1 –8.7 1.2 3.3 0.2 Sierra Leone 2.6 2.1 4.8 3.3 3.4 3.9 3.5 2.9 1.5 –1.2 –4.5 6.2 Somalia –9.0 –1.9 .. .. .. .. .. .. .. 0.9 –1.9 .. South Africa 4.2 –2.3 1.6 3.3 4.1 4.4 4.3 2.5 –2.8 –0.3 –0.8 2.2 Sudan –1.7 –7.7 5.0 3.0 4.1 8.9 7.7 4.5 2.2 0.5 1.8 4.9 Swaziland 9.1 6.0 3.3 1.9 1.4 1.8 2.2 1.0 –0.3 4.8 1.2 2.0 Tanzania .. 3.7 4.1 4.9 4.4 3.8 4.1 4.4 3.0 0.6 0.2 3.9 Togo 11.1 –3.0 0.1 0.4 –1.3 1.3 –0.6 –0.7 0.0 –0.9 –0.3 –0.6 Uganda .. 2.7 3.1 3.4 2.9 7.2 4.9 5.2 3.6 –0.5 4.1 3.8 Zambia –0.3 –3.4 2.8 3.1 2.8 3.7 3.7 3.3 3.8 –1.7 –2.4 2.7 Zimbabwe 10.4 3.9 –17.1 –6.7 –6.0 –3.2 –3.6 –17.3 5.2 1.4 0.6 –6.0 NORTH AFRICA 2.4 1.6 4.3 3.0 3.4 4.0 3.6 3.5 2.1 1.5 1.3 2.8 Algeria –2.5 –1.7 5.3 3.6 3.5 0.5 1.5 0.9 0.6 –0.3 –0.4 2.1 Egypt, Arab Rep. 7.4 3.2 1.2 2.1 2.5 4.9 5.1 5.2 2.8 3.2 2.3 2.9 Libya .. .. 10.7 2.3 7.7 3.8 3.9 1.7 0.1 .. .. 2.2 Morocco 1.0 2.1 5.2 3.7 1.8 6.5 1.5 4.3 3.7 1.4 1.2 3.5 Tunisia 4.6 5.4 4.9 5.1 3.0 4.6 5.3 3.6 2.1 1.0 3.3 3.6 ALL AFRICA 1.4 –0.6 2.5 3.1 3.0 3.6 3.5 2.7 0.2 0.0 –0.1 2.2 a. Provisional. 12 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.6 Table Gross national income, nominal Current prices ($ millions) Annual average growth (%) 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 261,499 284,576 425,226 529,902 616,553 728,169 827,908 947,512 909,888 0.9 1.8 15.1 Excluding South Africa 186,001 176,977 261,709 315,160 374,531 472,616 551,831 680,851 631,533 –1.0 1.5 16.7 Excl. S. Africa & Nigeria 120,669 151,469 201,604 236,870 275,384 330,873 397,306 485,559 468,215 2.8 1.1 15.4 Angola .. 8,214 12,230 17,295 26,601 39,679 50,485 69,675 67,478 .. –2.4 33.5 Benin 1,402 1,806 3,515 4,006 4,259 4,623 5,428 6,672 6,646 2.1 3.7 13.8 Botswana 1,028 3,686 7,368 9,089 9,420 10,482 11,647 12,843 11,341 10.8 4.2 11.0 Burkina Faso 1,924 3,094 4,269 5,102 5,411 5,756 6,752 7,932 8,019 4.8 0.0 14.2 Burundi 922 1,117 577 646 776 910 974 1,165 1,331 1.9 –3.3 8.5 Cameroon 5,618 10,674 13,097 15,374 16,126 17,706 20,608 23,407 22,059 9.0 –2.4 12.0 Cape Verde .. 340 781 907 966 1,063 1,305 1,484 1,499 .. 6.2 13.8 Central African Republic 800 1,465 1,137 1,268 1,348 1,473 1,702 1,966 1,983 7.8 –4.3 9.5 Chad 1,038 1,721 2,279 3,720 4,277 4,888 5,817 6,687 6,124 5.5 –1.2 20.7 Comoros 124 249 322 360 386 404 467 530 535 7.9 –2.0 12.0 Congo, Dem. Rep. 14,102 8,579 5,485 6,276 6,760 8,143 9,621 10,266 9,831 –6.8 –7.0 12.0 Congo, Rep. 1,544 2,324 2,580 3,159 4,039 5,105 5,747 8,728 6,869 1.9 –5.2 18.1 Côte d’Ivoire 9,680 9,209 13,018 14,763 15,643 16,589 18,911 22,438 22,406 1.3 3.3 10.7 Djibouti .. .. 673 731 776 854 936 1,073 1,120 .. 1.3 8.4 Equatorial Guinea .. 124 1,392 2,312 4,173 5,163 6,674 11,868 6,715 .. 16.9 35.3 Eritrea .. .. 761 923 1,162 1,272 1,365 1,642 1,856 .. 7.3 13.7 Ethiopia .. 12,016 8,473 9,971 12,250 15,095 19,196 25,931 28,489 5.8 –5.8 17.0 Gabon 3,856 5,336 5,342 5,987 7,708 7,902 10,044 12,364 9,549 –0.1 –1.9 13.2 Gambia, The 237 291 336 366 418 460 597 776 690 1.6 3.7 8.5 Ghana 4,426 5,774 7,459 8,674 10,590 20,261 24,494 28,268 25,871 2.9 2.6 25.3 Guinea .. 2,518 3,201 3,391 2,658 2,496 3,819 3,321 3,692 .. 3.3 1.9 Guinea-Bissau 105 233 463 524 579 588 681 834 826 3.4 –0.7 20.2 Kenya 7,043 8,224 14,738 15,955 18,732 22,540 27,208 30,134 29,311 2.6 8.3 12.0 Lesotho 695 902 1,202 1,515 1,619 1,797 1,995 2,014 1,934 –0.2 1.5 11.5 Liberia 930 .. 350 373 417 444 560 673 645 –3.2 .. 6.3 Madagascar 4,024 2,958 5,394 4,285 4,960 5,435 7,288 9,372 8,498 –6.0 3.8 9.6 Malawi 1,138 1,837 2,385 2,582 2,714 3,078 3,437 4,051 4,656 2.2 0.2 11.1 Mali 1,768 2,405 4,203 4,679 5,099 5,524 7,146 8,722 8,996 2.8 0.1 17.0 Mauritania 672 1,076 1,343 1,613 1,922 2,334 2,828 3,619 3,041 4.8 1.8 15.3 Mauritius 1,113 2,631 5,580 6,371 6,276 6,559 7,746 9,482 8,874 9.1 5.7 8.9 Mozambique 3,550 2,320 4,469 5,398 6,219 6,472 7,445 9,239 9,696 –5.6 8.6 11.9 Namibia 1,818 2,388 5,163 6,689 7,149 7,928 8,629 8,752 9,174 0.2 4.5 12.8 Niger 2,476 2,423 2,718 3,039 3,397 3,645 4,246 5,338 5,281 0.1 –1.7 13.8 Nigeria 61,079 25,585 59,996 78,110 98,881 141,275 154,068 194,690 162,901 –12.5 3.7 20.8 Rwanda 1,165 2,572 1,816 2,055 2,554 3,083 3,724 4,656 5,179 8.5 –2.0 15.1 São Tomé and Príncipe .. .. .. .. 111 127 151 178 194 .. .. .. Senegal 3,403 5,520 6,766 7,949 8,546 9,290 11,238 13,127 12,778 6.1 –1.6 13.6 Seychelles 142 355 663 666 844 924 954 823 655 8.9 5.9 4.0 Sierra Leone 1,071 580 958 1,034 1,176 1,364 1,629 1,916 1,901 –4.8 1.5 13.3 Somalia 603 835 .. .. .. .. .. .. .. 5.5 .. .. South Africa 77,378 107,746 163,610 214,782 242,122 255,872 276,534 267,509 279,023 4.2 2.2 12.2 Sudan 7,570 11,409 16,428 19,990 25,397 33,503 41,985 52,236 49,255 9.7 1.9 20.9 Swaziland .. 1,174 1,754 2,284 2,702 2,684 2,991 2,833 2,874 .. 4.5 10.7 Tanzania .. 4,072 11,601 12,775 14,114 14,331 16,839 20,731 21,385 .. 10.6 9.3 Togo 1,096 1,598 1,736 2,033 2,073 2,180 2,478 2,892 2,850 4.6 –0.1 10.2 Uganda 1,237 4,227 6,219 8,338 8,771 9,679 11,664 14,161 15,711 20.7 9.1 12.5 Zambia 3,594 3,008 4,231 5,026 6,761 9,506 10,026 12,982 11,444 –4.1 0.7 19.2 Zimbabwe 6,530 8,512 5,439 5,388 5,308 4,890 4,654 3,879 5,213 –0.2 –1.7 –4.0 NORTH AFRICA 103,183 159,989 257,561 289,635 332,058 390,836 469,628 580,537 542,401 4.9 5.4 11.8 Algeria 41,147 59,955 65,319 81,414 97,259 112,669 134,004 169,689 139,577 4.5 –1.3 15.1 Egypt, Arab Rep. 21,453 42,025 82,816 78,638 89,432 108,015 131,650 164,196 188,575 7.5 11.2 7.6 Libya .. .. 24,603 33,139 43,719 57,559 74,070 93,533 61,985 .. .. 22.8 Morocco 18,402 24,835 48,783 55,961 58,760 64,703 74,246 87,411 89,489 3.3 5.3 11.7 Tunisia 8,450 11,882 23,957 26,895 27,309 29,553 33,625 38,471 37,328 2.0 6.0 9.1 ALL AFRICA 369,585 448,242 684,475 822,420 952,088 1,123,145 1,301,612 1,531,638 1,456,113 2.1 3.0 13.9 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 13 Table 2.7 Gross national income, World Bank Atlas method Current prices ($ millions) Annual average growth (%) 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 248,179 296,836 372,146 464,775 582,430 688,914 784,038 902,495 950,647 0.8 1.6 15.0 Excluding South Africa 183,411 177,652 240,847 296,269 354,076 428,060 506,838 617,236 667,916 –1.2 1.1 16.5 Excl. S. Africa & Nigeria 122,461 152,211 184,869 222,371 265,832 307,548 363,836 439,072 482,054 2.1 0.8 14.6 Angola .. 7,700 10,678 14,638 21,938 32,662 45,510 60,022 69,373 .. –2.3 34.9 Benin 1,433 1,723 2,985 3,708 4,316 4,606 5,091 6,062 6,715 1.1 3.2 13.3 Botswana 860 3,311 6,616 7,991 9,506 10,640 11,477 12,592 12,211 9.4 5.1 11.3 Burkina Faso 2,016 2,923 3,684 4,634 5,527 5,990 6,399 7,242 8,036 3.4 –1.1 13.6 Burundi 897 1,187 623 666 723 843 956 1,093 1,232 3.6 –4.1 6.0 Cameroon 4,613 10,553 11,393 14,184 16,293 17,783 19,489 21,731 23,189 8.7 –1.5 11.6 Cape Verde .. 334 678 807 1,001 1,119 1,257 1,411 1,520 .. 6.3 13.4 Central African Republic 785 1,384 1,003 1,187 1,358 1,470 1,602 1,799 1,975 6.9 –4.1 8.8 Chad 929 1,504 1,999 3,254 4,218 4,625 5,213 5,845 6,692 4.5 –0.6 20.4 Comoros .. 234 270 326 390 411 435 483 531 10.5 –1.7 11.7 Congo, Dem. Rep. 14,859 7,912 5,455 6,365 6,950 7,741 8,899 9,702 10,609 –8.4 –5.7 12.2 Congo, Rep. 1,471 2,185 2,365 2,687 3,456 4,414 5,238 7,158 7,671 2.2 –5.8 18.8 Côte d’Ivoire 9,319 9,253 11,191 13,655 15,689 16,521 17,770 20,252 22,545 0.8 2.9 9.9 Djibouti .. .. 675 754 803 864 925 1,029 1,106 .. 0.6 8.5 Equatorial Guinea .. 124 1,232 1,928 3,170 4,296 6,236 9,874 8,398 .. 15.5 37.4 Eritrea .. .. 707 818 1,019 1,163 1,312 1,368 1,620 .. 4.2 11.9 Ethiopia .. 11,542 8,162 9,942 12,172 14,272 17,525 22,441 27,149 6.4 –4.9 14.9 Gabon 3,337 4,577 4,727 5,357 7,009 7,398 9,175 10,606 10,869 0.3 –1.4 13.8 Gambia, The 243 292 369 392 417 456 537 668 743 0.7 3.5 6.8 Ghana 4,643 5,847 6,549 8,144 10,018 13,302 18,374 26,845 28,383 4.0 1.9 21.7 Guinea .. 2,588 3,096 3,424 3,272 2,921 3,090 3,328 3,771 .. 4.1 0.8 Guinea-Bissau 115 219 235 358 580 609 641 732 826 3.4 –1.1 20.4 Kenya 7,446 8,848 14,032 16,078 18,607 21,046 24,831 28,305 30,269 2.4 5.7 11.2 Lesotho 502 879 987 1,211 1,523 1,819 1,941 2,075 2,036 2.5 2.4 11.1 Liberia 849 .. 342 365 407 431 531 645 651 –3.2 .. 5.8 Madagascar 4,018 2,785 4,858 5,184 5,377 5,353 6,359 7,911 8,533 –4.3 4.1 9.1 Malawi 1,169 1,723 2,290 2,813 2,828 3,094 3,382 3,913 4,433 2.0 0.7 11.7 Mali 1,752 2,270 3,477 4,366 5,194 5,546 6,534 7,723 8,862 1.2 0.6 16.2 Mauritania 719 1,102 1,310 1,532 1,797 2,043 2,532 3,153 3,250 4.8 3.1 13.7 Mauritius 1,203 2,579 5,164 6,158 6,658 6,935 7,535 8,523 9,243 7.6 6.3 8.7 Mozambique .. 2,338 4,491 5,186 6,107 6,663 7,437 8,552 9,964 –2.2 6.6 10.7 Namibia .. 2,300 4,292 5,537 6,863 7,966 8,567 9,071 9,264 0.2 5.4 13.5 Niger 2,442 2,368 2,382 2,812 3,347 3,703 4,029 4,821 5,199 –0.3 –2.4 13.1 Nigeria 55,754 25,520 55,622 73,423 87,677 119,729 142,074 177,005 184,656 –10.9 2.7 22.8 Rwanda 1,298 2,546 1,806 2,037 2,469 2,896 3,403 4,252 4,896 8.2 –3.5 11.9 São Tomé and Príncipe .. .. .. .. 117 130 145 164 185 .. .. .. Senegal 2,977 5,046 5,878 7,378 8,684 9,327 10,368 11,960 13,062 5.0 –1.0 12.3 Seychelles 134 351 620 680 803 909 1,004 915 746 9.5 5.9 5.6 Sierra Leone 1,074 768 1,026 1,086 1,200 1,341 1,543 1,788 1,938 –6.6 0.6 12.5 Somalia 656 959 .. .. .. .. .. .. .. 5.9 .. .. South Africa 69,282 119,309 131,765 169,056 228,919 261,586 278,167 286,605 284,270 4.5 2.3 12.2 Sudan 7,909 12,988 15,277 18,512 22,943 29,254 36,800 46,260 51,524 10.0 0.4 20.5 Swaziland .. 940 1,418 1,804 2,542 2,685 2,930 2,991 2,932 .. 7.3 10.0 Tanzania .. 4,836 11,853 13,314 14,699 15,366 16,636 18,992 21,411 .. 7.2 8.8 Togo 1,137 1,516 1,561 1,877 2,104 2,253 2,382 2,652 2,883 3.2 –0.3 9.4 Uganda .. 5,396 6,548 7,692 8,678 10,153 11,280 13,163 15,200 21.2 6.3 11.1 Zambia 3,610 3,491 4,007 4,593 5,847 7,222 9,117 11,929 12,473 –6.1 –0.2 18.7 Zimbabwe 6,692 9,014 5,186 5,289 5,357 5,157 4,858 3,958 4,564 0.1 –2.3 –4.0 NORTH AFRICA 101,468 161,543 255,081 279,856 316,979 362,189 420,732 502,217 546,929 5.8 4.2 10.6 Algeria 38,814 61,138 62,070 73,991 89,341 104,132 122,798 146,510 154,202 6.3 –2.5 15.2 Egypt, Arab Rep. 21,726 42,481 92,987 90,595 92,761 101,678 120,059 146,909 172,048 8.6 9.5 5.7 Libya .. .. 26,540 28,216 37,258 49,554 63,057 77,898 77,185 .. .. 20.7 Morocco 18,734 24,777 44,364 53,199 60,341 66,321 70,682 80,878 89,933 1.9 4.7 11.0 Tunisia 8,689 11,649 22,258 26,325 28,750 30,761 32,816 36,510 38,845 2.0 6.2 8.8 ALL AFRICA 353,620 462,592 627,017 744,930 900,271 1,052,308 1,206,017 1,405,886 1,498,551 2.4 2.5 13.3 a. Provisional. 14 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.8 Table Gross national income per capita, World Bank Atlas method Current prices ($) Annual average growth (%) 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 640 576 513 625 764 882 979 1,100 1,130 –2.0 –1.1 12.2 Excluding South Africa 509 370 354 425 495 583 673 800 844 –4.0 –1.6 13.6 Excl. S. Africa & Nigeria 429 397 339 397 463 522 602 707 757 –0.8 –1.9 11.7 Angola .. 720 680 910 1,320 1,910 2,590 3,330 3,750 .. –5.0 31.1 Benin 400 360 410 490 550 570 610 700 750 –1.9 –0.2 9.7 Botswana 870 2,450 3,690 4,400 5,170 5,710 6,060 6,550 6,260 6.0 2.5 9.8 Burkina Faso 290 330 290 350 400 420 430 480 510 1.0 –3.9 9.8 Burundi 220 210 90 90 100 110 120 140 150 0.3 –5.3 3.3 Cameroon 510 860 670 810 910 980 1,040 1,140 1,190 5.4 –4.1 9.1 Cape Verde .. 940 1,470 1,720 2,100 2,310 2,560 2,830 3,010 .. 4.0 11.6 Central African Republic 350 470 250 290 330 350 380 410 450 4.2 –6.4 6.9 Chad 200 250 210 340 420 450 490 540 600 1.7 –3.6 16.6 Comoros .. 540 470 550 650 670 690 750 810 7.4 –3.9 9.3 Congo, Dem. Rep. 550 210 100 110 120 130 140 150 160 –11.1 –8.5 9.1 Congo, Rep. 810 890 730 800 1,010 1,270 1,470 1,980 2,080 –0.8 –7.8 16.2 Côte d’Ivoire 1,110 730 610 720 820 840 880 980 1,070 –3.3 –0.3 7.6 Djibouti .. .. 870 950 1,000 1,050 1,110 1,210 1,280 .. –2.1 6.5 Equatorial Guinea .. 330 2,140 3,250 5,210 6,870 9,710 14,980 12,420 .. 11.5 33.7 Eritrea .. .. 170 190 230 250 270 280 320 .. 1.7 7.8 Ethiopia .. 240 120 140 160 190 220 280 330 3.3 –7.6 11.7 Gabon 4,900 4,940 3,590 3,990 5,120 5,300 6,450 7,320 7,370 –2.7 –4.2 11.5 Gambia, The 390 330 260 260 270 290 330 400 440 –3.1 –0.4 3.5 Ghana 420 390 310 380 460 590 800 1,150 1,190 0.9 –0.9 19.0 Guinea .. 420 350 380 350 310 320 340 370 .. 0.8 –1.2 Guinea-Bissau 140 210 170 250 390 400 420 460 510 1.3 –3.3 17.2 Kenya 460 380 410 460 520 570 660 730 760 –1.3 2.5 8.4 Lesotho 390 550 500 610 760 900 960 1,010 980 0.3 0.7 10.1 Liberia 440 .. 110 110 120 120 150 170 160 –4.8 .. 1.8 Madagascar 470 250 290 300 310 300 340 410 430 –6.8 1.0 6.0 Malawi 190 180 180 210 210 220 230 260 290 –2.5 –1.3 8.2 Mali 240 260 310 380 440 460 530 610 680 –0.6 –1.4 13.3 Mauritania 470 550 460 530 600 670 810 980 990 2.1 0.4 10.9 Mauritius 1,250 2,440 4,220 4,990 5,350 5,540 5,980 6,720 7,250 6.7 5.0 7.9 Mozambique .. 170 230 260 290 310 340 380 440 –2.7 3.5 7.9 Namibia .. 1,620 2,220 2,810 3,420 3,890 4,100 4,260 4,270 –3.5 2.8 11.3 Niger 410 300 200 220 260 270 280 330 340 –3.0 –5.5 9.1 Nigeria 750 260 410 530 620 830 960 1,170 1,190 –13.2 0.1 19.9 Rwanda 250 360 210 230 270 310 360 440 490 4.3 –3.6 9.3 São Tomé and Príncipe .. .. .. .. 760 840 920 1,020 1,130 .. .. .. Senegal 530 670 550 670 770 810 870 980 1,040 1.9 –3.6 9.4 Seychelles 2,080 5,020 7,490 8,240 9,680 10,740 11,800 10,530 8,480 8.6 4.3 4.7 Sierra Leone 330 190 220 220 240 250 280 320 340 –8.8 0.8 8.8 Somalia 100 150 .. .. .. .. .. .. .. 6.0 .. .. South Africa 2,510 3,390 2,860 3,620 4,850 5,480 5,760 5,870 5,760 1.9 0.0 10.9 Sudan 390 480 410 490 590 740 910 1,120 1,220 6.8 –2.2 18.0 Swaziland .. 1,090 1,280 1,620 2,260 2,360 2,540 2,560 2,470 .. 4.9 8.9 Tanzania .. 190 320 350 380 380 400 450 490 .. 4.1 5.9 Togo 410 390 270 320 350 370 380 410 440 –0.5 –3.0 6.7 Uganda .. 300 240 280 300 340 370 420 460 17.0 3.1 7.5 Zambia 630 440 360 400 500 600 740 950 960 –9.0 –3.0 15.8 Zimbabwe 920 860 410 420 430 410 390 320 360 –3.6 –4.1 –4.0 NORTH AFRICA 1,100 1,342 1,683 1,818 2,026 2,278 2,605 3,060 3,280 3.0 2.3 8.8 Algeria 2,060 2,420 1,950 2,290 2,720 3,120 3,630 4,260 4,420 3.2 –4.4 13.5 Egypt, Arab Rep. 490 740 1,250 1,200 1,200 1,290 1,500 1,800 2,070 5.7 7.4 3.7 Libya .. .. 4,670 4,860 6,290 8,200 10,220 12,380 12,020 .. .. 18.2 Morocco 960 1,000 1,490 1,760 1,980 2,150 2,260 2,560 2,810 –0.6 3.1 9.7 Tunisia 1,360 1,430 2,260 2,650 2,870 3,040 3,210 3,540 3,720 –0.5 4.5 7.7 ALL AFRICA 737 727 715 830 980 1,119 1,253 1,428 1,487 –0.5 –0.1 10.7 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 15 Table 2.9 Gross domestic product deflator (local currency series) Index (2000 = 100) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 20 40 118 127 140 149 164 189 195 26 67 140 Excluding South Africa 20 41 117 127 139 148 164 192 196 27 68 140 Excl. S. Africa & Nigeria 20 42 117 127 139 147 162 189 195 27 69 139 Angola .. 0 931 1,329 1,780 2,041 2,126 2,606 2,455 0 3 1,404 Benin 38 50 113 113 116 122 126 135 136 47 73 118 Botswana 14 43 116 129 141 168 186 217 205 23 66 150 Burkina Faso 52 76 111 115 115 115 119 126 130 67 84 114 Burundi 21 31 120 130 151 158 171 214 243 24 51 150 Cameroon 34 58 106 107 110 115 117 122 118 50 79 110 Cape Verde .. 66 106 113 109 109 110 111 115 60 81 108 Central African Republic 32 70 105 106 109 114 117 124 129 54 83 112 Chad 46 60 116 127 130 148 156 174 153 55 78 133 Comoros 36 70 119 121 124 126 133 140 147 54 82 123 Congo, Dem. Rep. 0 0 722 766 931 1,053 1,276 1,523 1,983 0 2 948 Congo, Rep. 29 38 81 95 115 136 137 171 136 39 50 114 Côte d’Ivoire 39 50 111 112 116 122 125 135 137 50 75 117 Djibouti .. 69 104 108 111 115 121 132 134 .. 85 113 Equatorial Guinea .. 24 87 102 145 166 164 203 135 26 41 128 Eritrea .. .. 161 192 260 287 304 406 443 .. 66 241 Ethiopia .. 49 102 106 117 130 153 200 248 42 79 134 Gabon 35 53 93 99 116 125 132 151 123 44 63 113 Gambia, The 15 64 170 191 199 202 216 229 234 31 82 179 Ghana 0 11 213 244 280 506 589 708 826 3 37 377 Guinea .. 48 112 130 166 228 258 294 310 31 77 180 Guinea-Bissau 0 6 199 198 208 203 215 238 241 1 47 180 Kenya 10 24 109 117 122 132 139 155 166 16 57 124 Lesotho 13 40 126 134 142 153 174 197 204 22 68 146 Liberia 2 2 145 146 166 181 210 232 249 2 22 168 Madagascar 4 21 127 145 172 192 210 229 248 10 54 165 Malawi 2 7 223 256 285 344 371 404 437 3 29 275 Mali 35 57 117 116 119 124 133 145 151 50 79 122 Mauritania 20 42 119 133 157 193 207 233 218 29 75 158 Mauritius 22 55 120 127 133 142 154 164 167 34 76 133 Mozambique 0 6 131 141 153 167 180 194 201 1 45 151 Namibia 11 34 124 127 134 146 159 182 194 19 55 140 Niger 49 63 107 108 115 116 120 129 135 63 78 114 Nigeria 2 7 162 195 234 280 293 325 323 3 41 217 Rwanda 20 33 119 135 147 161 182 205 228 25 70 147 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 39 63 107 107 110 114 121 128 127 55 81 112 Seychelles 56 87 117 121 142 144 170 218 280 70 92 151 Sierra Leone 0 5 106 126 142 156 172 192 204 1 41 140 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 9 38 126 134 141 150 163 178 191 18 65 141 Sudan 0 1 122 140 157 167 180 217 216 0 35 151 Swaziland 13 40 123 130 139 152 169 186 196 19 69 142 Tanzania .. 14 122 131 139 147 160 176 189 10 46 138 Togo 35 58 101 105 106 106 107 114 116 49 78 106 Uganda .. 29 109 126 124 127 136 145 169 4 70 124 Zambia 0 1 180 214 251 285 318 355 400 0 32 238 Zimbabwe 181 154 112 120 126 121 122 124 156 161 122 118 NORTH AFRICA 21 54 111 123 133 143 161 181 178 33 77 134 Algeria 6 16 111 123 143 159 171 196 178 9 50 138 Egypt, Arab Rep. 13 43 112 125 133 143 161 181 200 20 73 136 Libya .. .. 166 224 279 321 367 460 309 .. 84 248 Morocco 35 68 103 104 105 107 111 118 120 50 84 107 Tunisia 30 64 107 110 114 118 123 129 133 46 82 114 ALL AFRICA 20 42 117 127 139 148 163 186 194 26 69 139 a. Provisional. 16 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.10 Table Gross domestic product deflator (U.S. dollar series) Index (2000 = 100) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 120 110 117 137 152 167 181 197 184 106 109 142 Excluding South Africa 146 116 118 133 151 175 193 225 198 119 105 150 Excl. S. Africa & Nigeria 126 126 115 129 141 160 179 209 191 116 113 142 Angola .. 121 125 160 205 255 278 349 311 95 91 198 Benin 130 131 138 153 157 167 187 214 205 103 116 154 Botswana 88 112 120 140 141 147 155 164 149 77 110 132 Burkina Faso 175 199 136 155 155 156 177 200 196 147 135 149 Burundi 164 131 80 85 101 111 114 130 142 153 123 104 Cameroon 106 127 120 134 137 144 160 179 164 102 125 133 Cape Verde .. 112 130 152 147 148 163 177 174 95 117 140 Central African Republic 108 183 129 142 148 156 174 198 195 117 143 145 Chad 155 157 142 172 176 202 232 277 230 121 129 176 Comoros 91 138 146 163 167 172 197 223 221 89 125 161 Congo, Dem. Rep. 205 122 123 134 136 155 171 187 166 133 126 141 Congo, Rep. 98 100 99 127 155 185 203 272 205 84 81 152 Côte d’Ivoire 132 130 136 150 157 166 186 215 206 108 123 153 Djibouti .. 69 104 108 111 115 121 132 134 .. 85 113 Equatorial Guinea .. 64 107 137 196 227 244 323 192 54 65 170 Eritrea .. .. 111 134 163 180 190 254 278 .. 99 160 Ethiopia .. 194 97 100 110 122 139 169 172 167 151 119 Gabon 119 138 114 134 157 171 196 241 185 96 104 148 Gambia, The 113 104 80 81 89 92 111 132 113 91 109 98 Ghana 168 180 134 148 168 301 342 365 320 177 166 209 Guinea .. 128 98 102 80 75 109 93 102 117 136 94 Guinea-Bissau 97 131 244 267 280 277 320 379 363 105 116 242 Kenya 103 81 109 112 123 139 157 171 163 86 86 127 Lesotho 114 107 116 144 155 157 171 165 162 95 120 134 Liberia 69 89 100 109 119 128 140 150 149 76 101 118 Madagascar 130 94 139 105 116 121 152 182 172 108 101 132 Malawi 124 151 136 140 143 150 158 171 185 118 132 145 Mali 116 149 144 157 161 169 198 230 227 108 132 160 Mauritania 102 125 108 124 141 172 191 233 199 108 140 147 Mauritius 75 97 113 121 118 118 129 152 137 72 106 118 Mozambique 143 99 85 96 103 102 107 124 115 157 93 100 Namibia 95 91 114 136 146 150 157 153 160 79 97 129 Niger 165 165 131 146 156 158 178 205 204 137 127 149 Nigeria 204 81 127 150 181 223 237 279 221 127 76 174 Rwanda 85 154 86 91 103 114 130 146 156 112 123 109 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 131 165 130 144 148 155 179 201 192 120 136 146 Seychelles 50 93 123 126 148 150 145 132 118 65 103 126 Sierra Leone 119 64 95 97 103 110 121 134 128 98 99 109 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 85 101 115 144 154 154 160 149 157 88 115 130 Sudan 138 176 120 139 165 197 229 267 241 196 122 167 Swaziland 115 108 113 140 151 156 166 156 163 87 123 131 Tanzania .. 56 94 96 99 94 103 118 115 69 72 101 Togo 118 152 124 141 143 144 160 182 175 106 131 137 Uganda .. 134 84 105 105 105 116 129 134 157 109 105 Zambia 142 109 119 140 175 246 247 295 247 111 111 178 Zimbabwe 181 154 112 120 126 121 122 124 156 161 122 118 NORTH AFRICA 94 97 91 98 108 119 134 158 143 91 93 113 Algeria 120 134 108 128 147 165 186 228 184 128 101 144 Egypt, Arab Rep. 60 66 76 69 76 85 96 112 124 62 76 91 Libya .. .. 67 88 106 128 154 193 126 .. 93 111 Morocco 94 88 114 124 126 129 144 161 158 72 99 125 Tunisia 101 100 114 121 120 121 131 144 135 89 111 119 ALL AFRICA 111 104 106 121 134 147 162 181 167 100 102 130 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 17 Table 2.11 Consumer price index Annual growth (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA .. .. .. .. .. .. .. .. .. .. .. .. Angola .. .. 98.2 43.5 23.0 13.3 12.2 12.5 13.7 .. 1,122.5 80.3 Benin .. .. 1.5 0.9 5.4 3.8 1.3 7.9 2.2 .. 9.7 3.4 Botswana 13.6 11.4 9.2 6.9 8.6 11.6 7.1 12.7 8.0 10.8 10.8 8.7 Burkina Faso 12.2 –0.5 2.0 –0.4 6.4 2.3 –0.2 10.7 2.6 5.0 4.5 3.0 Burundi 2.5 7.0 10.8 7.9 13.5 2.8 8.3 24.1 11.0 7.2 13.5 11.1 Cameroon 9.6 1.1 0.6 0.2 2.0 5.1 0.9 5.3 3.0 9.1 5.6 2.6 Cape Verde .. 10.7 1.2 –1.9 0.4 5.4 4.4 6.8 1.0 6.7 6.4 2.0 Central African Republic .. 0.0 4.1 –2.1 2.9 6.7 0.9 9.3 3.5 3.6 3.9 3.5 Chad .. –0.7 –1.8 –5.4 7.9 8.0 –9.0 10.3 10.0 3.0 5.5 4.2 Comoros .. .. .. .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 46.6 81.3 12.9 4.0 21.3 13.1 16.9 17.3 .. 57.0 3,367.2 110.1 Congo, Rep. .. 2.9 –0.6 2.4 3.1 6.5 2.7 7.3 5.0 1.0 –3.5 3.0 Côte d’Ivoire 14.7 –0.8 3.3 1.4 3.9 2.5 1.9 6.3 1.0 6.7 6.0 3.0 Djibouti 12.1 .. 2.0 3.1 3.1 3.5 5.0 12.0 1.7 5.3 .. 3.6 Equatorial Guinea .. 0.9 7.3 4.2 5.6 4.4 2.8 6.6 .. –5.5 6.6 5.8 Eritrea .. .. .. .. .. .. .. .. .. .. .. .. Ethiopia 4.5 5.2 17.8 3.3 11.6 12.3 17.2 44.4 8.5 4.6 8.0 10.9 Gabon 12.3 7.7 2.2 0.4 3.7 –1.4 5.0 5.3 1.9 6.5 3.7 2.0 Gambia, The 6.8 12.2 17.0 14.2 4.8 2.1 5.4 4.5 4.6 17.5 5.4 6.6 Ghana 50.1 37.3 26.7 12.6 15.1 10.9 10.7 16.5 19.3 48.3 27.6 18.5 Guinea .. .. .. .. .. .. .. 18.4 4.7 .. .. 11.5 Guinea-Bissau .. 33.0 –3.5 0.9 3.3 2.0 4.6 10.5 –1.7 70.5 37.5 3.1 Kenya 13.9 17.8 9.8 11.6 10.3 14.5 9.8 26.2 9.2 11.8 17.4 10.9 Lesotho 16.3 11.6 6.7 5.0 3.4 6.0 8.0 10.7 7.2 13.9 –1.7 7.7 Liberia 14.7 .. .. .. .. .. .. .. .. 5.6 .. .. Madagascar 18.2 11.8 –1.2 13.8 18.5 10.8 10.3 9.2 9.0 18.6 17.3 10.5 Malawi .. 11.8 9.6 11.4 15.4 14.0 8.0 8.7 8.4 16.8 31.0 14.3 Mali .. 0.6 –1.3 –3.1 6.4 1.5 1.4 9.2 2.2 –0.1 4.2 2.6 Mauritania .. 6.6 5.2 10.4 12.1 6.2 7.3 7.3 2.2 7.5 6.4 6.3 Mauritius 42.0 13.5 3.9 4.7 4.9 8.9 8.8 9.7 2.5 11.2 7.6 6.0 Mozambique .. 47.0 13.4 12.7 7.2 13.2 8.2 10.3 3.3 –3.2 34.5 10.7 Namibia .. .. 7.2 4.1 2.3 5.1 6.7 10.4 8.8 .. .. 6.4 Niger 10.3 –0.8 –1.6 0.3 7.8 0.0 0.1 11.3 4.3 3.6 4.3 3.2 Nigeria 10.0 7.4 14.0 15.0 17.9 8.2 5.4 11.6 11.5 20.9 30.6 12.2 Rwanda 7.2 4.2 7.4 12.3 9.0 8.9 9.1 15.4 10.4 4.7 –3.4 8.2 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 8.7 0.3 0.0 0.5 1.7 2.1 5.9 5.8 –1.1 6.9 4.5 2.1 Seychelles 13.6 3.9 3.3 3.9 0.9 –0.4 5.3 37.0 31.8 4.0 2.0 9.4 Sierra Leone .. .. .. .. .. .. 11.6 14.8 9.3 .. .. 11.9 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 13.7 14.3 5.9 1.4 3.4 4.6 7.1 11.5 7.1 14.6 9.9 6.1 Sudan 25.4 65.2 7.7 8.4 8.5 7.2 8.0 14.3 11.2 36.2 80.4 8.7 Swaziland 18.7 13.1 7.3 3.4 4.8 5.3 9.5 13.4 7.3 15.0 9.5 8.1 Tanzania 30.2 35.8 5.3 4.7 5.0 7.3 7.0 10.3 12.1 30.1 23.1 6.8 Togo 12.3 1.0 –1.0 0.4 6.8 2.2 1.0 8.7 2.0 5.0 7.1 2.9 Uganda .. 33.1 8.7 3.7 8.4 7.3 6.1 11.6 13.4 111.2 13.0 6.4 Zambia .. 107.0 21.4 18.0 18.3 9.0 10.7 12.4 13.4 69.3 76.2 17.3 Zimbabwe 5.4 17.4 431.7 282.4 302.1 1,096.7 24,411.0 .. .. 12.8 28.6 3,349.6 NORTH AFRICA .. .. .. .. .. .. .. .. .. .. .. .. Algeria 9.5 16.7 2.6 3.6 1.6 2.5 3.5 4.4 5.7 9.0 18.6 3.0 Egypt, Arab Rep. 20.8 16.8 4.5 11.3 4.9 7.6 9.3 18.3 11.8 17.4 10.5 7.5 Libya 9.7 8.5 –2.2 –2.2 2.7 1.5 6.3 10.4 2.5 7.9 6.7 –0.3 Morocco 9.4 6.8 1.2 1.5 1.0 3.3 2.0 3.7 1.0 7.6 4.4 1.9 Tunisia .. 6.5 2.7 3.6 2.0 4.5 3.1 4.9 3.8 7.6 4.9 3.2 ALL AFRICA .. .. .. .. .. .. .. .. .. .. .. .. a. Provisional. 18 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.12 Table Price indexes Exports of goods and Imports of goods and Inflation, GDP deflator Consumer price index services price index services price index (annual %) (2000 = 100) (2000 = 100) (2000 = 100) 2008 2009a 2008 2009a 2008 2009a 2008 2009a SUB–SAHARAN AFRICA 10.6 4.3 126.6 134.2 .. .. 173.0 153.9 Excluding South Africa 10.8 4.1 126.7 134.6 .. .. .. .. Excl. S. Africa & Nigeria 10.6 4.3 126.6 134.0 .. .. 178.1 .. Angola 22.6 –5.8 143.0 162.7 .. .. .. .. Benin 7.1 1.2 113.5 115.9 .. .. .. .. Botswana 17.0 –5.7 134.6 145.4 138.8 135.2 159.8 163.5 Burkina Faso 5.8 3.1 113.0 115.9 .. .. .. .. Burundi 25.1 13.6 138.2 153.4 .. .. .. .. Cameroon 4.2 –3.4 111.7 115.2 338.8 271.8 296.7 254.4 Cape Verde 1.0 3.8 117.5 118.6 74.2 70.4 126.5 120.0 Central African Republic 6.2 3.9 117.7 121.8 .. .. .. .. Chad 11.9 –12.4 108.5 119.3 .. .. .. .. Comoros 5.5 4.6 .. .. .. .. .. .. Congo, Dem. Rep. 19.4 30.2 155.1 .. 179.4 64.1 127.8 74.6 Congo, Rep. 25.1 –20.4 117.4 123.3 .. .. .. .. Côte d’Ivoire 8.1 1.3 111.0 112.1 194.2 158.6 211.5 165.0 Djibouti 9.5 1.7 121.6 123.6 .. .. .. .. Equatorial Guinea 23.7 –33.5 114.4 .. .. .. .. .. Eritrea 33.4 9.3 .. .. .. .. .. .. Ethiopia 30.5 24.4 190.1 206.2 145.0 138.4 135.4 120.1 Gabon 14.7 –19.0 109.0 111.1 330.3 207.2 204.3 166.6 Gambia, The 6.2 2.4 112.3 117.4 121.3 108.5 170.5 152.1 Ghana 20.2 16.7 143.1 170.7 .. .. .. .. Guinea 14.1 5.2 118.4 123.9 139.1 179.2 165.7 181.3 Guinea-Bissau 10.6 1.1 117.8 115.9 .. .. .. .. Kenya 11.9 6.7 158.6 173.2 174.8 168.1 163.6 146.8 Lesotho 13.4 3.4 126.8 135.9 130.4 136.0 87.1 86.5 Liberia 10.4 7.4 .. .. .. .. .. .. Madagascar 9.2 8.3 133.5 145.4 151.0 135.3 164.0 153.3 Malawi 8.9 8.4 133.8 145.0 .. .. .. .. Mali 8.7 4.3 112.4 114.9 .. .. .. .. Mauritania 12.4 –6.2 122.3 125.0 .. .. .. .. Mauritius 7.0 1.5 130.1 133.4 142.7 126.6 185.1 156.4 Mozambique 8.2 3.3 135.1 139.5 113.8 85.5 211.2 173.3 Namibia 14.3 6.5 123.7 134.6 175.5 184.1 136.1 133.2 Niger 7.7 4.9 111.4 116.2 .. .. .. .. Nigeria 11.0 –0.6 127.3 142.0 .. .. .. .. Rwanda 12.7 11.0 137.1 151.3 .. .. .. .. São Tomé and Príncipe 23.1 15.6 1,171.2 .. .. .. .. .. Senegal 5.9 –0.5 114.3 113.1 183.3 178.1 198.8 193.8 Seychelles 28.5 28.6 143.8 189.4 96.9 73.1 96.9 73.1 Sierra Leone 11.2 6.3 128.2 140.1 .. .. .. .. Somalia .. .. .. .. .. .. .. .. South Africa 9.2 7.3 125.0 133.9 196.5 194.1 168.0 153.7 Sudan 21.0 –0.8 132.3 147.2 255.0 .. 254.3 .. Swaziland 10.1 5.5 130.7 140.3 97.2 103.4 97.2 103.4 Tanzania 10.1 7.4 126.6 142.0 137.4 125.9 129.7 105.5 Togo 6.5 1.3 112.2 114.4 .. .. .. .. Uganda 6.5 16.5 127.2 144.3 108.0 99.5 153.9 148.0 Zambia 11.5 12.7 135.7 153.8 .. .. .. .. Zimbabwe 2.3 25.3 .. .. 187.3 201.5 217.9 196.2 NORTH AFRICA 12.2 1.8 113.1 117.4 .. .. 160.1 152.8 Algeria 14.6 –9.4 110.9 117.2 292.8 216.7 188.8 209.7 Egypt, Arab Rep. 12.2 10.8 139.2 155.6 92.2 94.6 90.9 105.6 Libya 25.4 –32.8 119.0 121.9 .. .. .. .. Morocco 5.9 1.8 109.3 110.4 176.3 159.2 188.5 160.0 Tunisia 5.4 2.9 113.1 117.4 198.7 168.9 204.5 159.4 ALL AFRICA 10.8 3.8 124.4 133.4 .. .. 167.6 153.4 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 19 Table 2.13 Gross domestic savings Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 25.3 17.1 16.0 15.9 15.7 15.9 16.7 16.1 15.5 20.1 15.4 16.0 Excluding South Africa .. 11.7 13.4 14.2 14.2 14.6 15.2 13.3 12.5 11.9 11.7 13.7 Excl. S. Africa & Nigeria 11.7 11.7 13.4 14.2 14.2 14.6 15.2 13.3 12.5 11.8 11.7 13.7 Angola .. 29.7 19.2 25.1 37.9 49.1 45.0 41.1 20.8 24.0 22.0 31.9 Benin –6.3 2.2 6.0 5.5 6.9 6.9 6.1 7.1 10.7 –2.4 3.8 6.5 Botswana 26.7 42.6 41.0 40.5 43.1 40.4 37.8 32.3 13.0 35.3 38.8 36.5 Burkina Faso –7.2 5.4 4.5 1.8 4.8 2.8 .. .. .. –1.6 9.0 2.6 Burundi –0.6 –5.4 –8.7 –11.0 –23.1 –19.9 .. .. .. 3.1 –5.2 –12.3 Cameroon 21.7 20.7 17.8 18.5 18.1 18.9 18.5 .. .. 24.2 18.5 18.8 Cape Verde .. –8.1 –15.8 –1.5 4.4 5.0 5.8 9.2 12.0 –2.2 –5.6 –2.6 Central African Republic –8.9 –0.6 1.6 0.0 0.1 1.4 1.5 –1.0 2.7 –1.1 3.7 2.0 Chad .. –7.7 18.0 24.5 35.1 36.4 20.5 27.4 5.9 –8.1 –0.5 13.8 Comoros –10.1 –3.2 –3.4 –8.5 –12.3 –14.8 –15.4 –20.1 –21.1 –4.5 –4.9 –11.1 Congo, Dem. Rep. 10.1 9.3 5.0 4.0 5.9 –0.6 8.8 8.6 17.7 10.9 8.8 6.1 Congo, Rep. 35.7 23.8 30.9 52.2 52.0 43.3 49.6 48.4 45.5 31.9 28.8 48.3 Côte d’Ivoire 20.4 11.3 21.0 20.0 17.2 19.6 14.6 17.9 19.2 19.6 17.8 19.4 Djibouti .. –10.4 5.3 4.3 8.6 12.1 17.4 .. .. .. –6.4 5.7 Equatorial Guinea .. –20.1 80.1 78.9 83.7 86.1 86.9 72.8 72.2 .. 13.7 79.5 Eritrea .. .. –40.9 –41.5 –27.2 –17.2 –17.7 .. .. .. –29.7 –29.2 Ethiopia .. 9.6 7.7 8.8 2.6 1.5 4.2 0.4 4.1 10.5 9.7 5.7 Gabon 60.6 36.9 48.2 54.6 58.3 56.0 55.3 58.9 47.3 44.3 43.6 53.2 Gambia, The 5.8 10.7 11.1 8.9 4.0 11.2 6.6 6.1 6.3 6.5 7.4 8.8 Ghana 4.9 5.5 7.0 7.3 3.7 6.1 3.8 2.0 8.7 4.8 7.5 5.9 Guinea .. 22.2 21.5 18.4 18.3 13.9 9.7 10.3 16.9 16.6 18.3 15.1 Guinea-Bissau –1.0 2.8 .. .. .. .. .. .. .. –0.9 1.5 –13.2 Kenya 18.1 18.5 10.5 10.8 9.5 8.1 8.0 6.1 7.8 18.3 14.6 8.7 Lesotho –52.0 –49.1 –25.9 –25.7 –27.9 –23.6 –27.1 –25.3 –29.1 –69.5 –37.6 –26.4 Liberia 14.8 .. –3.2 –0.7 2.4 –34.6 –142.5 –121.5 .. 2.2 .. –38.4 Madagascar –1.4 5.5 8.9 8.5 4.9 9.3 10.6 9.9 8.9 2.9 4.2 9.2 Malawi 10.8 13.4 3.2 0.0 –5.5 1.2 18.9 8.9 17.2 12.7 3.4 5.4 Mali 1.1 6.4 13.3 8.6 11.0 14.8 13.0 .. .. –0.4 7.6 12.2 Mauritania –3.5 4.9 –5.0 –3.1 –15.0 18.6 8.0 5.6 7.4 3.1 2.4 0.9 Mauritius 10.4 23.0 24.9 22.0 16.5 15.3 16.6 12.5 10.8 20.3 24.1 19.6 Mozambique –8.9 –5.8 3.5 7.7 6.5 8.8 6.3 1.6 2.2 –6.2 –2.9 6.0 Namibia 38.4 18.2 10.3 16.8 19.8 20.6 22.4 21.4 13.9 10.8 12.7 17.1 Niger 14.6 1.2 5.0 3.9 13.4 .. .. .. .. 7.3 2.7 5.9 Nigeriab .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 4.2 6.2 0.4 1.4 2.0 1.8 3.5 7.0 4.2 5.0 –5.5 2.4 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 2.1 2.4 8.8 7.9 14.1 10.7 8.6 3.6 8.0 4.3 5.4 8.9 Seychelles 27.1 20.3 21.5 14.7 3.1 8.1 –1.7 6.0 15.9 24.1 21.7 13.3 Sierra Leone 0.9 8.7 –3.7 –0.4 4.1 7.6 6.1 1.7 2.3 9.1 2.8 –1.6 Somalia –12.9 –12.5 .. .. .. .. .. .. .. –6.3 –12.5 .. South Africa 37.9 23.2 19.0 17.8 17.5 17.2 18.3 18.9 18.6 28.5 19.4 18.5 Sudan 2.1 8.2 15.7 18.7 19.0 18.6 26.7 26.8 19.4 4.2 9.6 18.4 Swaziland 1.2 5.3 18.1 13.5 11.2 11.5 12.7 –0.2 0.2 3.7 2.0 9.4 Tanzania .. 1.3 16.1 15.2 14.0 11.0 12.6 10.3 17.9 .. 2.9 13.7 Togo 23.2 14.7 5.3 4.5 1.5 .. .. .. .. 12.3 6.7 1.8 Uganda –0.4 0.6 7.2 10.1 11.7 8.1 8.8 15.3 12.5 2.3 4.3 9.5 Zambia 19.3 16.6 13.0 19.9 21.8 31.5 30.5 25.1 25.6 14.0 9.0 18.1 Zimbabwe 13.8 17.5 2.3 –2.8 –7.6 –9.8 –1.6 –22.6 –26.9 16.5 17.1 –3.9 NORTH AFRICA 22.8 20.8 27.2 27.7 29.9 33.5 32.8 33.7 23.8 20.3 19.2 27.9 Algeria 43.1 27.1 44.9 47.7 54.9 56.6 57.5 56.7 45.5 31.5 30.1 49.1 Egypt, Arab Rep. 15.2 16.1 14.3 15.6 15.7 17.1 16.3 16.8 12.4 15.5 14.2 14.8 Libya .. 27.2 46.8 42.7 48.1 66.8 63.6 67.8 .. .. 17.6 46.6 Morocco 14.9 19.9 24.5 24.2 23.2 24.0 23.4 24.7 25.1 16.7 17.8 23.7 Tunisia 24.0 20.0 21.2 21.2 21.4 21.5 22.0 22.4 23.5 22.7 22.3 22.2 ALL AFRICA 24.2 18.8 21.0 21.2 22.1 23.8 24.0 24.3 19.1 20.2 17.1 21.4 a. Provisional. b. For 1994–2000 Nigeria’s values were distorted because the of�cial exchange rate used by the government for oil exports and oil value added was signi�cantly overvalued. 20 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.14 Table Gross national savings Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 23.4 15.8 16.0 16.4 16.4 16.1 15.9 15.5 15.4 18.6 15.2 15.8 Excluding South Africa .. 12.8 16.3 17.8 18.3 .. .. .. .. 13.0 13.9 16.3 Excl. S. Africa & Nigeria 10.9 12.8 16.3 17.8 18.3 18.0 18.0 16.2 .. 12.4 13.9 16.7 Angola .. 9.0 7.6 12.6 24.8 36.5 29.9 23.6 9.7 13.8 1.6 17.7 Benin 4.2 5.3 6.7 6.8 10.1 10.0 8.8 10.6 .. 4.6 7.8 9.3 Botswana 28.7 41.6 35.7 36.2 41.5 41.2 40.8 34.8 16.4 33.8 40.5 35.4 Burkina Faso 9.3 15.9 9.4 5.4 8.8 7.0 .. .. .. 14.6 21.5 6.8 Burundi .. 8.7 9.1 9.5 4.5 4.1 .. .. .. 11.2 6.2 5.8 Cameroon 5.2 16.2 14.9 17.0 16.7 19.2 20.3 .. .. 18.8 13.4 16.5 Cape Verde .. 17.8 9.3 22.0 29.1 27.1 26.5 26.7 31.3 24.3 21.8 19.8 Central African Republic 1.6 6.2 .. .. .. .. .. .. .. 6.1 8.1 .. Chad .. 2.3 .. .. .. .. .. .. .. 6.2 4.6 .. Comoros –0.4 14.4 .. .. .. .. .. .. .. 15.0 15.4 .. Congo, Dem. Rep. .. .. .. .. .. .. .. .. .. .. .. .. Congo, Rep. 26.1 6.9 4.2 19.7 18.9 9.0 18.0 .. .. 25.5 5.3 18.0 Côte d’Ivoire 8.6 –5.1 12.3 12.4 10.0 12.1 8.4 12.3 14.8 6.8 6.0 11.7 Djibouti .. .. 24.6 24.4 28.3 33.4 37.1 .. .. .. 11.4 22.3 Equatorial Guinea .. 2.1 .. .. .. .. .. .. .. .. 14.7 .. Eritrea .. .. .. .. .. .. .. .. .. .. 32.8 4.4 Ethiopia .. 12.8 21.4 22.1 13.7 9.7 21.9 17.1 16.1 13.4 15.5 17.8 Gabon 47.8 24.3 33.4 35.4 44.2 .. .. .. .. 33.7 29.3 37.1 Gambia, The 16.4 21.9 17.1 16.7 10.2 18.9 17.3 10.4 18.8 16.9 16.9 15.6 Ghana 6.3 10.5 21.1 22.9 19.2 16.5 11.5 8.8 15.5 7.3 13.5 17.4 Guinea .. 19.2 18.3 11.4 .. .. –1.6 1.4 7.7 12.4 18.7 9.9 Guinea-Bissau .. 14.5 .. .. .. .. .. .. .. 1.8 9.0 –7.3 Kenya 17.2 18.5 15.2 16.2 16.1 16.2 16.0 14.2 15.4 18.0 21.8 15.1 Lesotho 49.6 70.5 18.9 20.6 18.0 30.7 39.0 33.5 28.1 42.0 49.5 24.9 Liberia 13.1 .. .. 142.2 128.1 134.1 –11.4 –2.1 .. –3.5 .. 78.2 Madagascar –0.7 9.1 13.0 14.1 8.0 .. .. .. .. 3.0 5.1 11.8 Malawi 7.8 16.4 .. .. .. .. .. .. .. 12.5 8.1 8.9 Mali 8.4 15.0 14.4 8.6 11.4 14.5 18.6 .. .. 6.1 14.7 13.1 Mauritania 3.9 18.8 .. .. .. .. .. .. .. 12.2 10.5 .. Mauritius 10.4 25.8 25.3 22.6 17.4 17.1 21.3 16.7 16.7 20.2 26.5 21.9 Mozambique –6.6 6.6 4.1 8.0 7.1 7.1 6.6 3.8 9.1 –2.2 6.0 7.8 Namibia .. 34.8 24.3 28.2 27.5 31.7 31.8 31.6 26.5 .. 27.5 27.8 Niger 17.1 –0.6 7.2 6.9 18.5 .. .. .. .. 8.8 3.6 8.6 Nigeriab .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 14.0 11.3 11.0 14.8 15.1 10.4 14.1 17.3 15.1 12.0 14.2 13.4 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 2.7 1.6 15.0 14.6 21.0 18.7 19.1 16.1 .. 4.2 6.3 16.0 Seychelles 32.4 21.7 17.2 12.4 2.1 8.2 –3.9 1.6 9.2 27.3 21.5 10.0 Sierra Leone 2.9 –1.0 9.1 4.8 10.0 9.0 10.3 5.3 7.8 7.7 0.8 5.7 Somalia 20.1 .. .. .. .. .. .. .. .. 19.2 .. .. South Africa 33.9 19.1 15.7 15.0 14.5 14.4 14.1 14.9 15.4 24.4 16.6 15.2 Sudan 4.5 1.2 12.2 16.0 17.0 13.9 17.8 17.4 12.2 3.7 4.0 13.0 Swaziland .. 19.7 24.1 18.3 22.1 17.0 20.6 6.9 2.4 .. 16.2 17.1 Tanzania .. 10.1 20.0 19.4 17.3 15.2 16.6 13.3 21.2 .. 8.7 16.9 Togo 27.2 21.0 11.3 11.4 8.7 .. .. .. .. 16.8 10.8 7.0 Uganda 1.9 5.6 17.6 20.4 20.7 16.9 16.2 21.9 17.5 5.5 14.4 17.6 Zambia 7.8 19.6 10.8 13.1 17.7 23.9 23.1 19.2 19.0 3.2 7.1 13.0 Zimbabwe 12.0 15.6 .. .. .. .. .. .. .. 14.6 15.7 .. NORTH AFRICA 25.9 27.6 25.2 25.3 27.4 32.5 32.2 32.5 .. 23.6 28.3 28.1 Algeria 41.0 24.3 .. .. .. .. .. .. .. 29.4 28.6 .. Egypt, Arab Rep. 21.0 31.1 18.5 21.1 21.8 23.0 23.6 23.6 16.7 21.8 24.7 20.3 Libya .. .. 42.2 34.4 46.0 69.8 66.5 67.1 .. .. .. 49.7 Morocco 18.6 25.1 30.7 31.0 30.9 32.2 32.3 32.9 31.2 20.5 21.6 30.6 Tunisia 25.3 23.4 21.8 21.7 20.2 21.7 21.0 21.3 22.8 23.7 22.2 21.9 ALL AFRICA 24.5 20.8 19.7 20.0 20.9 23.0 22.7 22.8 17.6 20.8 18.4 20.0 a. Provisional. b. For 1994–2000 Nigeria’s values were distorted because the of�cial exchange rate used by the government for oil exports and oil value added was signi�cantly overvalued. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 21 Table 2.15 General government �nal consumption expenditure Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 15.1 17.5 16.4 16.6 16.7 16.4 16.0 16.3 17.6 16.5 16.8 16.3 Excluding South Africa .. 15.6 13.8 14.1 14.2 13.4 13.1 .. .. 15.6 14.4 13.5 Excl. S. Africa & Nigeria 16.1 15.6 13.8 14.1 14.2 13.4 13.1 13.2 13.9 15.6 14.4 13.5 Angola .. 34.5 .. .. .. .. .. .. .. 31.5 40.7 .. Benin 8.6 11.0 13.3 13.6 15.0 .. .. .. .. 12.7 10.5 12.9 Botswana 21.3 24.1 22.3 21.1 22.4 19.0 19.4 19.8 24.2 24.3 26.7 21.4 Burkina Faso 9.2 21.1 22.2 21.6 22.3 22.0 .. .. .. 15.6 22.5 22.3 Burundi 9.2 10.8 22.7 26.1 26.5 28.8 .. .. .. 9.3 17.0 22.9 Cameroon 9.7 12.8 10.0 10.2 10.0 9.6 9.2 .. .. 10.0 10.6 9.9 Cape Verde .. 14.7 14.7 20.6 20.4 22.1 22.4 20.7 20.8 13.1 17.0 18.6 Central African Republic 15.1 14.9 11.0 10.5 13.3 11.1 2.7 6.6 4.5 15.6 13.9 9.8 Chad .. 10.0 7.6 4.9 5.1 4.9 10.3 12.4 15.6 11.3 8.1 8.4 Comoros 30.9 24.5 14.7 14.3 13.5 14.2 14.3 15.3 15.3 28.6 20.3 14.7 Congo, Dem. Rep. 8.4 11.5 6.3 8.2 8.3 7.8 10.4 11.0 7.9 9.0 9.9 7.9 Congo, Rep. 17.6 13.8 17.4 15.0 13.0 13.9 17.1 12.0 12.2 17.7 18.1 14.5 Côte d’Ivoire 16.9 16.8 8.2 8.3 8.3 8.3 8.7 8.6 8.6 16.5 11.9 8.1 Djibouti .. 31.5 29.5 29.7 27.1 28.0 25.1 .. .. .. 31.8 28.0 Equatorial Guinea .. 39.7 3.8 2.9 2.7 2.6 2.3 2.6 3.4 27.4 25.1 3.3 Eritrea .. .. 50.3 52.9 37.2 35.9 31.4 .. .. .. 39.7 45.4 Ethiopia .. 13.2 13.4 13.1 12.3 12.1 10.4 9.7 8.2 11.2 9.8 12.6 Gabon 13.2 13.4 10.1 9.3 8.3 8.4 8.9 8.2 11.6 18.3 13.2 9.7 Gambia, The 31.2 13.7 11.0 16.9 18.4 18.1 16.0 15.6 15.9 29.1 13.8 15.3 Ghana 11.2 9.3 11.5 12.2 15.3 11.3 11.6 11.2 9.6 9.0 11.7 11.2 Guinea .. 11.0 8.2 6.9 7.0 8.1 6.8 9.3 8.0 11.6 8.2 7.6 Guinea-Bissau 27.6 10.3 .. .. .. .. .. .. .. 18.9 8.4 13.1 Kenya 19.8 18.6 18.1 17.9 17.4 17.5 17.9 16.7 16.3 18.3 15.8 17.0 Lesotho 21.8 25.8 37.4 37.4 39.2 40.4 38.7 44.0 50.4 23.3 33.6 40.2 Liberia 19.1 .. 8.5 10.4 11.1 11.5 14.6 19.3 .. 22.0 .. 12.9 Madagascar 12.1 8.0 9.2 6.9 9.0 8.7 12.3 11.2 11.5 9.8 7.9 9.5 Malawi 19.3 15.1 12.4 12.5 14.3 14.6 14.1 17.3 20.9 17.5 16.6 15.0 Mali 11.6 13.8 8.4 10.0 9.9 9.9 10.3 .. .. 12.3 12.7 9.4 Mauritania 45.3 25.9 30.1 21.9 22.7 17.5 21.6 18.8 20.6 30.6 14.5 22.5 Mauritius 14.0 13.6 14.2 14.3 14.8 14.2 13.1 13.2 14.6 12.6 14.0 14.0 Mozambique 12.2 13.5 10.2 10.8 10.4 10.7 11.8 12.1 13.4 13.8 9.7 10.7 Namibia 17.4 30.6 22.2 20.4 19.3 19.5 20.7 20.5 24.2 27.9 31.0 21.5 Niger 10.4 15.0 11.3 12.5 11.5 .. .. .. .. 11.9 14.6 12.2 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 12.5 10.1 13.8 18.4 18.2 18.1 16.5 14.7 14.6 13.0 11.5 15.0 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 24.8 18.4 13.3 13.7 9.6 9.7 10.0 9.7 8.7 19.3 15.0 11.3 Seychelles 28.7 27.7 25.5 28.3 21.3 19.8 16.0 13.3 12.2 33.1 29.0 20.8 Sierra Leone 8.4 7.8 15.6 13.3 13.8 13.8 11.8 12.5 13.8 7.7 10.6 14.3 Somalia 15.6 .. .. .. .. .. .. .. .. 17.6 .. .. South Africa 14.3 19.7 19.2 19.4 19.5 19.7 19.0 19.1 21.0 17.4 19.4 19.2 Sudan 16.0 5.8 10.8 11.8 18.2 17.3 15.5 15.8 13.9 11.1 6.1 13.0 Swaziland 27.0 14.3 15.3 16.0 15.6 15.3 14.6 23.6 27.0 21.5 17.2 18.1 Tanzania .. 17.8 15.4 16.9 17.6 17.5 19.3 20.0 19.8 .. 14.8 16.3 Togo 22.4 14.2 9.8 9.7 11.5 11.3 9.3 .. .. 16.9 12.8 10.0 Uganda .. 7.5 15.7 13.9 14.5 14.1 12.9 11.2 11.4 9.9 11.1 14.1 Zambia 25.5 19.0 14.4 18.1 9.7 10.2 10.4 9.0 13.1 23.0 17.7 11.6 Zimbabwe 18.5 19.4 17.9 21.0 15.7 6.2 3.4 2.1 13.8 20.1 17.6 14.0 NORTH AFRICA 15.9 15.1 14.3 14.1 13.6 13.0 12.6 12.3 13.3 16.6 15.2 13.8 Algeria 15.2 16.1 14.8 13.8 11.5 11.2 11.3 12.9 13.9 17.2 16.6 13.3 Egypt, Arab Rep. 15.7 11.3 12.7 12.8 12.7 12.3 11.3 10.9 11.4 16.2 10.9 11.9 Libya .. 24.4 13.6 13.1 11.8 10.7 11.6 9.3 .. .. 24.3 14.4 Morocco 18.3 15.5 18.1 18.7 19.4 18.5 18.2 17.1 18.0 16.6 17.0 18.3 Tunisia 14.5 16.4 15.7 15.4 15.4 14.7 14.1 14.4 13.1 16.5 16.0 15.0 ALL AFRICA 15.5 16.4 15.5 15.5 15.3 14.9 14.4 14.4 15.7 16.5 16.1 15.1 a. Provisional. 22 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.16 Table Household �nal consumption expenditure Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 58.9 65.3 67.7 67.7 68.0 68.3 67.8 68.1 66.9 63.3 68.0 68.0 Excluding South Africa .. 72.5 73.0 72.1 72.6 73.3 72.8 .. .. 72.5 74.1 73.2 Excl. S. Africa & Nigeria 71.6 72.5 73.0 72.1 72.6 73.3 72.8 74.7 74.0 72.4 74.1 73.4 Angola .. 35.8 .. .. .. .. .. .. .. 44.5 42.6 .. Benin 97.7 86.8 80.7 80.9 78.1 .. .. .. .. 89.7 85.7 81.3 Botswana 52.0 33.2 36.7 38.4 34.5 40.7 42.8 47.9 62.8 40.4 34.5 42.1 Burkina Faso 98.0 73.5 73.3 76.6 72.8 75.2 .. .. .. 86.0 68.5 75.2 Burundi 91.4 94.5 85.9 84.9 96.6 91.1 .. .. .. 87.5 88.3 89.4 Cameroon 68.6 66.6 72.2 71.4 72.0 71.5 72.2 .. .. 65.8 70.9 71.4 Cape Verde .. 93.4 101.1 80.9 75.2 72.9 71.8 70.0 67.2 89.1 88.6 84.0 Central African Republic 93.7 85.7 87.4 89.5 86.6 87.5 95.9 94.4 92.9 85.5 82.4 88.2 Chad .. 97.6 74.4 70.6 59.8 58.7 69.2 60.2 78.5 96.8 92.5 77.9 Comoros 79.2 78.7 88.7 94.2 98.8 100.6 101.2 104.8 105.8 75.9 84.6 96.4 Congo, Dem. Rep. 81.5 79.1 88.7 87.8 85.8 92.8 80.9 80.4 74.4 80.0 81.3 86.0 Congo, Rep. 46.8 62.4 51.8 32.8 35.0 42.8 33.3 39.6 42.2 50.3 53.1 37.3 Côte d’Ivoire 62.8 71.9 70.8 71.7 74.5 72.0 76.8 73.6 72.2 63.9 70.3 72.5 Djibouti .. 78.9 65.2 66.0 64.2 59.9 57.5 .. .. .. 73.8 66.3 Equatorial Guinea .. 80.3 16.1 18.2 13.6 11.3 10.8 24.5 24.3 .. 61.2 17.1 Eritrea .. .. 90.6 88.6 90.0 81.3 86.2 .. .. .. 90.0 83.8 Ethiopia .. 77.2 78.8 78.2 85.1 86.4 85.5 89.9 87.7 78.4 80.5 81.6 Gabon 26.1 49.7 41.7 36.2 33.3 35.6 35.9 32.9 41.1 37.4 43.2 37.1 Gambia, The 63.0 75.6 78.0 74.2 77.6 70.7 77.4 78.4 77.8 64.4 78.8 76.0 Ghana 83.9 85.2 81.5 80.5 81.0 82.6 84.6 86.8 81.7 86.2 80.8 82.9 Guinea .. 66.9 70.3 74.6 74.8 78.0 83.6 80.5 75.2 71.8 73.5 77.3 Guinea-Bissau 73.3 86.9 .. .. .. .. .. .. .. 82.0 90.1 100.1 Kenya 62.1 62.8 71.3 71.3 73.2 74.5 74.0 77.2 75.9 63.3 69.6 74.4 Lesotho 130.2 123.3 88.6 88.3 88.7 83.2 88.4 81.3 78.8 146.2 104.0 86.1 Liberia 66.1 .. 94.7 90.3 86.4 123.1 228.0 202.3 .. 75.8 .. 125.4 Madagascar 89.3 86.4 81.9 84.5 86.2 82.0 77.1 78.8 79.7 87.2 87.9 81.3 Malawi 69.9 71.5 84.4 87.5 91.1 84.2 67.0 73.8 61.9 69.8 80.0 79.5 Mali 87.4 79.8 78.3 81.4 79.1 75.3 76.8 .. .. 88.1 79.7 78.4 Mauritania 58.2 69.2 74.9 81.2 92.3 63.9 70.4 75.6 72.1 66.3 83.0 76.6 Mauritius 75.6 63.4 60.9 63.7 68.7 70.5 70.3 74.3 74.6 67.1 61.9 66.4 Mozambique 96.7 92.3 86.3 81.4 83.2 80.5 81.9 86.3 84.4 92.3 93.2 83.3 Namibia 44.2 51.2 67.5 62.8 60.9 60.0 56.9 58.1 61.9 61.3 56.3 61.5 Niger 75.1 83.8 83.7 83.6 75.1 .. .. .. .. 80.8 82.7 81.9 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 83.3 83.7 85.8 80.3 79.8 80.1 80.0 78.3 81.1 82.0 94.0 82.6 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 73.1 79.2 77.9 78.4 76.3 79.6 81.4 86.7 83.3 76.4 79.6 79.8 Seychelles 44.2 52.0 52.9 57.0 75.6 72.1 85.7 80.7 71.9 42.7 49.3 65.9 Sierra Leone 90.7 83.5 88.1 87.2 82.2 78.6 82.0 85.8 84.0 83.2 86.6 87.4 Somalia 97.3 .. .. .. .. .. .. .. .. 100.6 .. .. South Africa 47.8 57.1 61.8 62.9 63.1 63.1 62.7 61.9 60.4 54.2 61.2 62.3 Sudan 81.9 86.1 73.5 69.5 62.8 64.1 57.8 57.4 66.7 84.8 84.3 68.7 Swaziland 71.8 80.4 66.6 70.5 73.2 73.2 72.7 76.6 72.8 74.7 80.8 72.6 Tanzania .. 80.9 68.6 67.9 68.4 71.4 68.1 69.7 62.3 .. 82.3 70.0 Togo 54.5 71.1 84.8 85.8 87.0 .. .. .. .. 70.8 80.5 88.3 Uganda .. 91.9 77.1 76.0 73.7 77.8 78.3 73.5 76.1 87.2 84.6 76.4 Zambia 55.2 64.4 72.6 62.0 68.5 58.3 59.0 65.9 61.3 62.9 73.3 70.3 Zimbabwe 67.7 63.1 79.8 81.8 92.0 103.6 98.2 120.5 113.1 63.4 65.2 89.9 NORTH AFRICA 61.3 64.1 58.5 58.1 56.5 53.5 54.5 54.0 62.9 63.1 65.6 58.3 Algeria 41.7 56.8 40.4 38.5 33.6 32.2 31.2 30.4 40.6 51.3 53.3 37.5 Egypt, Arab Rep. 69.2 72.6 73.0 71.7 71.6 70.6 72.4 72.3 76.2 68.3 75.0 73.3 Libya .. 48.4 39.5 44.2 40.2 22.5 24.8 22.9 .. .. 58.1 39.0 Morocco 66.8 64.6 57.3 57.1 57.5 57.5 58.4 58.1 57.0 66.7 65.3 58.0 Tunisia 61.5 63.6 63.1 63.4 63.3 63.7 63.8 63.2 63.4 60.8 61.7 62.8 ALL AFRICA 60.0 64.7 63.5 63.4 62.8 61.5 61.7 61.4 65.2 63.2 66.9 63.5 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 23 Table 2.17 Final consumption expenditure plus discrepancy Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 74.7 82.9 84.0 84.1 84.3 84.1 83.3 83.9 84.5 79.9 84.6 84.0 Excluding South Africa .. 88.3 86.6 85.8 85.8 85.4 84.8 86.7 87.5 88.1 88.3 86.3 Excl. S. Africa & Nigeria 88.3 88.3 86.6 85.8 85.8 85.4 84.8 86.7 87.5 88.2 88.3 86.3 Angola .. 70.3 80.8 74.9 62.1 50.9 55.0 58.9 79.2 76.0 78.0 68.1 Benin 106.3 97.8 94.0 94.5 93.1 93.1 93.9 92.9 89.3 102.4 96.2 93.5 Botswana 73.3 57.4 59.0 59.5 56.9 59.6 62.2 67.7 87.0 64.7 61.2 63.5 Burkina Faso 107.2 94.6 95.5 98.2 95.2 97.2 .. .. .. 101.6 91.0 97.4 Burundi 100.6 105.4 108.7 111.0 123.1 119.9 .. .. .. 96.9 105.2 112.3 Cameroon 78.3 79.3 82.2 81.5 81.9 81.1 81.5 .. .. 75.8 81.5 81.2 Cape Verde .. 108.1 115.8 101.5 95.6 95.0 94.2 90.8 88.0 102.2 105.6 102.6 Central African Republic 108.9 100.6 98.4 100.0 99.9 98.6 98.5 101.0 97.3 101.1 96.3 98.0 Chad .. 107.7 82.0 75.5 64.9 63.6 79.5 72.6 94.1 108.1 100.5 86.2 Comoros 110.1 103.2 103.4 108.5 112.3 114.8 115.4 120.1 121.1 104.5 104.9 111.1 Congo, Dem. Rep. 89.9 90.7 95.0 96.0 94.1 100.6 91.2 91.4 82.3 89.1 91.2 93.9 Congo, Rep. 64.3 76.2 69.1 47.8 48.0 56.7 50.4 51.6 54.5 68.1 71.2 51.7 Côte d’Ivoire 79.6 88.7 79.0 80.0 82.8 80.4 85.4 82.1 80.8 80.4 82.2 80.6 Djibouti .. 110.4 94.7 95.7 91.4 87.9 82.6 .. .. .. 106.4 94.3 Equatorial Guinea .. 120.1 19.9 21.1 16.3 13.9 13.1 27.2 27.8 .. 86.3 20.5 Eritrea .. .. 140.9 141.5 127.2 117.2 117.7 .. .. .. 129.7 129.2 Ethiopia .. 90.4 92.3 91.2 97.4 98.5 95.8 99.6 95.9 89.5 90.3 94.3 Gabon 39.4 63.1 51.8 45.4 41.7 44.0 44.7 41.1 52.7 55.7 56.4 46.8 Gambia, The 94.2 89.3 88.9 91.1 96.0 88.8 93.4 93.9 93.7 93.5 92.6 91.2 Ghana 95.1 94.5 93.0 92.7 96.3 93.9 96.2 98.0 91.3 95.2 92.5 94.1 Guinea .. 77.8 78.5 81.6 81.7 86.1 90.3 89.7 83.1 83.4 81.7 84.9 Guinea-Bissau 101.0 97.2 .. .. .. .. .. .. .. 100.9 98.5 113.2 Kenya 81.9 81.5 89.5 89.2 90.5 91.9 92.0 93.9 92.2 81.7 85.4 91.3 Lesotho 152.0 149.1 125.9 125.7 127.9 123.6 127.1 125.3 129.1 169.5 137.6 126.4 Liberia 85.2 .. 103.2 100.7 97.6 134.6 242.5 221.5 .. 97.8 .. 138.4 Madagascar 101.4 94.5 91.1 91.5 95.1 90.7 89.4 90.1 91.1 97.1 95.8 90.8 Malawi 89.2 86.6 96.8 100.0 105.5 98.8 81.1 91.1 82.8 87.3 96.6 94.6 Mali 98.9 93.6 86.7 91.4 89.0 85.2 87.0 .. .. 100.4 92.4 87.8 Mauritania 103.5 95.1 105.0 103.1 115.0 81.4 92.0 94.4 92.6 96.9 97.6 99.1 Mauritius 89.6 77.0 75.1 78.0 83.5 84.7 83.4 87.5 89.2 79.7 75.9 80.4 Mozambique 108.9 105.8 96.5 92.3 93.5 91.2 93.7 98.4 97.8 106.2 102.9 94.0 Namibia 61.6 81.8 89.7 83.2 80.2 79.4 77.6 78.6 86.1 89.2 87.3 82.9 Niger 85.4 98.8 95.0 96.1 86.6 .. .. .. .. 92.7 97.3 94.1 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 95.8 93.8 99.6 98.6 98.0 98.2 96.5 93.0 95.8 95.0 105.5 97.6 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 97.9 97.6 91.2 92.1 85.9 89.3 91.4 96.4 92.0 95.7 94.6 91.1 Seychelles 72.9 79.7 78.5 85.3 96.9 91.9 101.7 94.0 84.1 75.9 78.3 86.7 Sierra Leone 99.1 91.3 103.7 100.4 95.9 92.4 93.9 98.3 97.7 90.9 97.2 101.6 Somalia 112.9 112.5 .. .. .. .. .. .. .. 106.3 112.5 .. South Africa 62.1 76.8 81.0 82.2 82.5 82.8 81.7 81.1 81.4 71.5 80.6 81.5 Sudan 97.9 91.8 84.3 81.3 81.0 81.4 73.3 73.2 80.6 95.8 90.4 81.6 Swaziland 98.8 94.7 81.9 86.5 88.8 88.5 87.3 100.2 99.8 96.3 98.0 90.6 Tanzania .. 98.7 83.9 84.8 86.0 89.0 87.4 89.7 82.1 .. 97.1 86.3 Togo 76.8 85.3 94.7 95.5 98.5 .. .. .. .. 87.7 93.3 98.2 Uganda 100.4 99.4 92.8 89.9 88.3 91.9 91.2 84.7 87.5 97.7 95.7 90.5 Zambia 80.7 83.4 87.0 80.1 78.2 68.5 69.5 74.9 74.4 86.0 91.0 81.9 Zimbabwe 86.2 82.5 97.7 102.8 107.6 109.8 101.6 122.6 126.9 83.5 82.9 103.9 NORTH AFRICA 77.2 79.2 72.8 72.3 70.1 66.5 67.2 66.3 76.2 79.7 80.8 72.1 Algeria 56.9 72.9 55.1 52.3 45.1 43.4 42.5 43.3 54.5 68.5 69.9 50.9 Egypt, Arab Rep. 84.8 83.9 85.7 84.4 84.3 82.9 83.7 83.2 87.6 84.5 85.8 85.2 Libya .. 72.8 53.2 57.3 51.9 33.2 36.4 32.2 .. .. 82.4 53.4 Morocco 85.1 80.1 75.5 75.8 76.8 76.0 76.6 75.3 74.9 83.3 82.2 76.3 Tunisia 76.0 80.0 78.8 78.8 78.6 78.5 78.0 77.6 76.5 77.3 77.7 77.8 ALL AFRICA 75.8 81.2 79.0 78.8 77.9 76.2 76.0 75.7 80.9 79.8 82.9 78.6 a. Provisional. 24 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.18 Table Final consumption expenditure plus discrepancy per capita Current prices ($) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 450 490 487 584 646 709 792 867 864 449 469 612 Excluding South Africa 362 355 323 364 404 466 543 663 654 335 306 424 Excl. S. Africa & Nigeria 375 365 330 372 412 475 554 676 666 345 314 432 Angola .. 677 721 918 1,144 1,346 1,855 2,753 3,232 581 469 1,343 Benin 420 376 455 503 507 543 621 717 666 332 343 503 Botswana 790 1,609 2,661 3,294 3,174 3,599 4,068 4,774 5,273 830 1,844 3,306 Burkina Faso 301 333 317 378 376 394 .. .. .. 260 238 311 Burundi 224 210 93 103 133 145 .. .. .. 215 170 114 Cameroon 581 723 658 738 763 799 903 .. .. 663 631 672 Cape Verde .. 1,034 1,997 1,996 2,001 2,171 2,550 2,788 2,696 809 1,201 2,057 Central African Republic 382 511 283 315 329 349 396 463 441 360 352 332 Chad .. 307 240 344 343 376 525 556 574 221 232 361 Comoros 406 593 583 669 724 754 854 989 984 394 508 684 Congo, Dem. Rep. 476 229 97 110 113 141 146 165 132 296 155 117 Congo, Rep. 605 872 741 665 855 1,258 1,184 1,683 1,417 681 620 915 Côte d’Ivoire 962 760 588 657 704 710 841 934 894 681 630 677 Djibouti .. 892 758 806 805 825 839 .. .. .. 834 793 Equatorial Guinea .. 418 1,019 1,869 2,204 2,129 2,569 7,637 4,274 .. 410 2,371 Eritrea .. .. 263 308 333 324 338 .. .. .. 240 281 Ethiopia .. 226 111 126 160 195 234 320 330 200 160 180 Gabon 2,472 4,057 2,383 2,429 2,636 3,010 3,640 4,121 3,954 2,570 2,723 2,785 Gambia, The 368 316 227 247 290 287 376 465 403 290 324 310 Ghana 383 372 338 384 471 855 1,036 1,197 1,002 350 358 605 Guinea .. 338 305 331 260 258 395 345 339 323 382 315 Guinea-Bissau 134 232 .. .. .. .. .. .. .. 171 208 175 Kenya 366 299 392 411 474 563 662 727 680 299 313 501 Lesotho 506 503 609 767 843 870 987 974 986 458 581 740 Liberia 425 .. 135 144 155 237 491 492 .. 437 .. 254 Madagascar 477 258 299 233 272 276 353 444 399 320 245 301 Malawi 178 172 182 198 213 219 194 250 256 150 179 200 Mali 246 262 335 386 399 413 501 .. .. 205 244 340 Mauritania 481 488 477 549 716 718 832 1,054 852 450 560 648 Mauritius 1,054 1,933 3,446 4,036 4,219 4,401 4,973 6,422 6,009 1,103 2,486 4,210 Mozambique 316 193 228 259 295 303 344 434 418 275 187 290 Namibia 1,319 1,357 2,288 2,788 2,898 3,095 3,271 3,309 3,675 1,435 1,691 2,626 Niger 362 310 213 232 225 .. .. .. .. 274 216 194 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 214 339 212 234 281 332 382 449 500 270 283 299 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 608 741 586 674 663 723 871 1,040 941 550 580 683 Seychelles 1,667 4,196 6,688 7,234 10,330 10,510 12,276 10,010 7,305 2,170 5,142 8,277 Sierra Leone 335 145 217 224 233 249 288 346 333 248 188 249 Somalia 106 156 .. .. .. .. .. .. .. 138 156 .. South Africa 1,818 2,444 2,955 3,860 4,319 4,526 4,845 4,593 4,711 2,094 2,782 3,635 Sudan 364 421 404 465 573 750 843 1,028 1,043 496 325 610 Swaziland 889 1,222 1,328 1,770 1,994 2,078 2,238 2,436 2,527 753 1,469 1,770 Tanzania .. 165 265 287 312 318 356 437 401 .. 197 315 Togo 314 354 292 337 347 .. .. .. .. 271 308 290 Uganda 99 241 219 274 277 308 354 387 429 231 220 292 Zambia 543 347 339 379 477 609 644 854 737 418 340 498 Zimbabwe 791 693 442 467 482 458 409 418 570 704 543 466 NORTH AFRICA 853 1,104 1,179 1,270 1,362 1,465 1,724 2,060 2,240 957 1,132 1,497 Algeria 1,281 1,789 1,176 1,374 1,405 1,525 1,703 2,152 2,197 1,697 1,217 1,463 Egypt, Arab Rep. 438 626 957 879 980 1,133 1,365 1,662 1,988 529 809 1,242 Libya .. 4,823 2,250 3,298 3,859 3,099 4,236 4,764 .. .. 5,111 3,590 Morocco 819 834 1,261 1,432 1,499 1,618 1,846 2,117 2,140 641 986 1,497 Tunisia 1,041 1,206 2,001 2,231 2,271 2,398 2,716 3,070 2,902 961 1,467 2,242 ALL AFRICA 522 601 600 692 757 824 936 1,055 1,082 541 586 756 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 25 Table 2.19 Gross �xed capital formation Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 22.6 18.2 17.1 17.4 18.2 18.9 20.3 21.7 22.3 20.1 17.1 18.5 Excluding South Africa .. 17.4 18.5 18.6 19.4 19.3 20.4 21.0 22.0 16.6 17.8 19.3 Excl. S. Africa & Nigeria 18.8 17.4 18.5 18.6 19.4 19.3 20.4 21.0 22.0 17.1 17.8 19.3 Angola .. 11.1 12.7 9.1 8.1 11.3 14.0 16.0 14.8 14.2 23.2 12.7 Benin .. 13.4 18.1 17.5 18.9 18.2 21.4 20.7 25.0 14.8 15.7 19.6 Botswana 34.5 32.4 26.0 24.8 24.5 21.6 23.9 23.3 28.2 29.0 27.2 24.6 Burkina Faso 14.1 17.7 17.5 19.3 19.4 20.8 .. .. .. 17.4 21.2 18.2 Burundi 13.9 15.2 10.6 13.0 10.5 16.4 .. .. .. 16.1 9.0 9.9 Cameroon 20.0 17.3 18.1 18.3 17.7 16.7 17.1 .. .. 21.1 14.5 18.0 Cape Verde .. 22.9 18.7 37.4 37.3 40.6 43.8 48.4 53.8 26.9 29.6 33.9 Central African Republic 6.9 11.4 6.1 6.2 8.9 9.2 8.9 11.6 10.6 10.2 11.2 8.8 Chad .. 4.8 48.6 22.7 16.7 13.2 17.0 23.9 32.7 4.4 11.0 29.2 Comoros 28.5 11.9 10.3 9.4 9.3 9.6 11.2 14.3 12.4 24.3 14.6 10.8 Congo, Dem. Rep. 8.8 12.8 12.2 12.8 14.2 13.0 19.5 23.9 29.8 11.4 8.0 14.3 Congo, Rep. 35.8 17.2 25.5 21.9 21.9 24.4 26.0 21.8 24.3 32.5 24.9 23.5 Côte d’Ivoire 24.4 8.5 9.7 9.8 9.7 9.3 8.7 10.1 11.2 15.8 11.4 10.1 Djibouti .. 14.1 14.4 21.5 19.0 29.6 37.5 .. .. .. 11.1 18.6 Equatorial Guinea .. 17.4 41.6 40.5 37.6 31.4 33.3 28.2 36.6 .. 59.5 41.5 Eritrea .. .. 28.1 22.3 18.5 12.6 10.6 .. .. .. 26.1 22.8 Ethiopia .. 12.9 21.8 25.5 23.0 24.2 23.5 19.8 22.4 15.7 16.5 22.6 Gabon 26.7 21.4 24.0 24.4 21.3 25.9 25.9 24.4 28.4 33.8 25.4 24.6 Gambia, The .. 22.3 19.2 24.8 .. .. .. .. .. 18.9 20.1 20.0 Ghana 6.1 14.4 22.9 28.4 29.0 21.6 20.1 21.5 19.6 7.9 19.7 23.2 Guinea .. 22.9 19.8 19.7 18.6 16.6 13.9 15.6 21.6 16.4 20.0 17.4 Guinea-Bissau 28.2 29.9 .. .. .. .. .. .. .. 32.0 25.9 12.0 Kenya 18.3 20.6 15.8 16.3 18.7 19.1 19.4 19.7 20.1 18.8 17.6 18.1 Lesotho 35.6 57.0 34.0 27.2 25.7 24.8 25.8 28.8 31.5 40.3 64.4 31.2 Liberia .. .. 9.4 13.2 16.4 .. .. .. .. .. .. 9.7 Madagascar 14.4 14.8 17.9 23.4 22.2 25.3 32.4 40.3 32.6 10.8 12.4 24.2 Malawi 22.2 20.1 14.1 16.2 20.2 22.7 24.0 23.3 21.8 15.8 15.2 18.7 Mali 15.5 23.0 24.2 21.0 22.6 22.9 22.4 .. .. 17.2 22.5 23.4 Mauritania .. 20.0 25.9 46.4 44.8 29.5 22.4 27.8 25.2 26.6 13.6 28.4 Mauritius 23.2 30.6 22.7 21.6 21.4 24.3 25.1 24.6 26.2 21.2 26.9 23.3 Mozambique 7.6 22.1 22.3 18.6 18.7 17.7 16.1 15.7 21.0 12.2 20.7 21.1 Namibia 27.2 21.2 19.1 18.6 18.6 21.6 23.7 25.7 24.7 18.6 21.0 20.9 Niger 25.5 11.4 14.0 15.8 18.5 .. .. .. .. 14.2 9.0 14.2 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 12.2 14.6 17.9 15.0 15.8 16.0 18.0 22.8 21.8 14.4 14.5 18.2 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 14.6 18.0 21.2 22.7 29.7 28.2 30.9 30.2 27.9 17.4 19.9 26.1 Seychelles 36.5 23.0 10.4 12.7 24.7 26.1 29.5 25.4 24.2 25.6 29.2 24.5 Sierra Leone 14.9 9.6 13.9 10.5 17.0 15.2 13.2 14.7 15.1 11.4 7.2 12.3 Somalia 43.1 14.9 .. .. .. .. .. .. .. 26.9 14.9 .. South Africa 25.9 19.1 15.5 16.0 16.8 18.3 20.2 22.5 22.6 23.1 16.3 17.7 Sudan 10.8 10.4 14.1 17.2 24.0 25.1 26.5 22.7 21.8 12.4 10.6 18.8 Swaziland 35.0 14.5 19.1 16.2 15.4 14.1 14.0 15.3 16.9 25.4 16.7 17.1 Tanzania .. 25.8 20.0 21.2 22.5 23.8 25.0 26.3 29.3 .. 21.5 22.0 Togo 28.2 25.3 20.9 21.2 22.3 .. .. .. .. 19.0 15.6 20.4 Uganda .. 12.7 20.7 20.0 22.2 21.0 21.9 22.7 23.5 9.3 15.9 21.0 Zambia 18.2 13.5 24.1 23.1 22.5 22.6 24.1 22.6 22.1 12.4 12.4 21.5 Zimbabwe 14.1 18.2 13.8 5.1 2.1 2.3 5.4 3.8 2.5 16.0 19.0 6.9 NORTH AFRICA 26.8 24.5 19.0 19.7 20.4 21.7 24.2 25.7 25.1 27.9 21.3 21.6 Algeria 33.8 27.0 24.0 24.1 22.3 22.9 26.0 26.3 33.0 31.9 26.2 24.6 Egypt, Arab Rep. 24.6 26.9 16.3 16.4 17.9 18.7 20.9 22.3 19.0 27.8 20.4 18.6 Libya .. 13.9 9.8 13.9 15.8 20.7 25.0 27.9 .. .. 12.7 16.9 Morocco 22.2 24.0 25.1 26.3 27.5 28.1 31.2 33.0 30.7 23.1 22.2 27.8 Tunisia 28.3 24.4 23.4 22.6 22.2 23.5 23.2 25.0 25.9 27.5 25.3 24.3 ALL AFRICA 24.5 21.1 17.9 18.4 19.2 20.1 22.1 23.6 23.5 23.5 19.0 19.9 a. Provisional. 26 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.20 Table Gross general government �xed capital formation Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 6.6 5.6 5.2 5.4 5.4 5.8 6.5 7.6 8.7 6.1 4.8 5.8 Excluding South Africa .. 7.2 6.0 6.5 6.3 6.6 6.8 7.3 8.3 6.6 6.5 6.5 Excl. S. Africa & Nigeria .. 7.2 6.0 6.5 6.3 6.6 6.8 7.3 8.3 6.3 6.5 6.5 Angola .. .. 7.6 4.9 5.0 8.9 11.7 14.1 12.4 .. 7.8 8.4 Benin .. 7.4 6.1 5.4 6.7 4.6 7.5 5.8 9.6 9.1 7.5 6.8 Botswana 0.0 8.6 10.6 8.5 7.3 6.1 7.8 12.5 15.1 9.7 11.7 10.0 Burkina Faso .. 9.7 6.3 7.2 7.4 8.0 .. .. .. 10.4 10.5 7.0 Burundi 12.8 12.5 8.3 10.7 8.8 .. .. .. .. 13.8 9.3 6.9 Cameroon 4.4 5.5 2.3 2.6 2.5 2.4 2.4 .. .. 6.9 2.9 2.3 Cape Verde .. 10.3 9.8 7.7 9.0 9.3 10.9 10.4 11.0 19.3 20.3 10.4 Central African Republic 3.7 4.7 2.2 2.0 4.0 3.7 2.7 4.5 3.7 5.5 6.2 3.6 Chad .. .. 12.5 7.8 7.8 8.1 7.3 7.9 10.9 3.8 7.4 9.2 Comoros 23.2 5.2 5.4 4.4 4.5 5.0 6.1 9.3 4.7 18.7 7.0 5.3 Congo, Dem. Rep. 5.1 4.0 2.7 2.8 3.7 3.1 8.8 12.6 23.8 4.4 1.7 5.9 Congo, Rep. .. 5.6 6.7 6.5 6.2 9.5 10.4 8.9 10.7 11.1 6.4 8.5 Côte d’Ivoire 11.4 3.6 2.7 2.8 2.7 3.1 2.6 3.0 3.0 7.1 5.6 2.8 Djibouti .. 9.1 6.7 7.7 9.3 7.5 12.2 .. .. .. 6.1 6.6 Equatorial Guinea .. 10.5 9.9 13.1 10.3 15.1 16.9 16.8 20.6 .. 6.9 12.4 Eritrea .. .. 20.4 17.0 16.8 11.5 9.4 .. .. .. 17.6 17.5 Ethiopia .. 4.0 12.8 15.7 14.7 16.7 16.8 14.0 16.5 4.9 6.6 14.7 Gabon 5.3 3.9 3.7 4.2 4.2 4.8 4.5 4.6 5.2 6.7 6.5 4.3 Gambia, The .. 7.4 5.7 10.9 9.0 7.9 3.7 .. .. 10.4 7.8 7.6 Ghana .. 7.5 8.9 12.4 12.0 8.8 8.5 9.4 8.0 6.3 11.1 9.8 Guinea .. 9.7 3.9 3.7 2.8 2.6 2.3 3.5 4.6 7.5 6.1 3.8 Guinea-Bissau .. 27.4 .. .. .. .. .. 6.5 9.6 33.3 20.2 9.8 Kenya 0.0 9.7 4.2 4.3 3.8 4.9 3.9 4.4 5.6 0.8 7.0 4.4 Lesotho 9.9 26.2 9.6 8.1 8.1 7.6 10.4 11.0 14.2 17.2 18.7 10.1 Liberia .. .. 0.0 0.0 0.0 .. .. .. .. .. .. 0.0 Madagascar .. 7.9 7.8 10.0 8.7 10.5 7.0 7.1 3.1 6.9 6.9 7.3 Malawi 17.5 7.7 .. .. .. .. .. .. .. 9.5 9.2 10.2 Mali .. 10.5 6.9 7.5 7.7 8.6 8.4 .. .. 10.2 10.1 7.7 Mauritania .. 6.2 12.0 9.1 8.1 .. .. .. .. 7.6 5.0 9.1 Mauritius 8.4 11.4 8.9 6.6 6.3 7.7 5.5 4.2 6.7 7.4 9.2 6.6 Mozambique 7.6 12.0 10.5 10.7 8.6 11.8 11.7 11.6 13.1 9.5 12.1 11.3 Namibia 15.7 8.2 6.4 6.3 6.4 6.8 2.9 3.4 5.3 10.7 8.2 5.6 Niger 20.4 7.4 8.3 5.1 6.3 .. .. .. .. 11.2 5.6 7.0 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 12.2 5.9 5.1 8.9 8.7 7.5 8.7 11.0 11.1 12.1 7.2 7.9 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 4.7 4.1 6.2 6.7 10.0 9.7 11.2 10.0 10.1 3.7 4.5 7.9 Seychelles .. 8.2 1.7 3.1 4.6 8.1 4.5 3.3 3.3 12.0 9.9 7.2 Sierra Leone 5.3 3.9 4.8 4.5 5.7 5.1 3.5 6.2 7.7 4.0 3.8 5.1 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 6.4 3.9 4.3 4.3 4.3 5.0 6.1 7.9 9.2 5.7 2.8 5.0 Sudan 6.9 .. 2.9 5.0 5.8 6.7 9.5 6.5 5.5 4.3 0.7 5.0 Swaziland 11.9 4.5 13.0 10.7 9.8 8.7 8.0 9.8 10.6 8.0 5.4 9.9 Tanzania .. 10.5 5.1 7.1 8.1 7.5 7.5 8.0 8.8 .. 6.0 6.3 Togo 20.2 7.3 3.7 5.3 2.8 3.6 2.0 .. .. 11.2 3.7 3.0 Uganda .. 6.2 5.1 4.9 5.0 4.6 4.9 4.4 6.1 4.4 5.6 5.3 Zambia .. 6.2 11.4 8.7 7.0 4.1 4.1 5.2 4.3 .. 6.8 7.8 Zimbabwe 1.8 3.4 2.1 5.1 2.1 2.3 1.4 0.3 0.8 2.9 3.0 1.9 NORTH AFRICA .. 10.8 8.1 8.9 9.5 9.5 10.9 11.3 5.5 13.0 10.6 8.9 Algeria 11.0 8.2 10.8 10.5 10.8 12.0 16.5 16.1 0.0 13.8 7.2 10.3 Egypt, Arab Rep. .. 14.7 8.3 8.7 9.3 8.0 7.8 7.9 8.0 16.9 14.5 8.6 Libya .. .. 7.9 12.3 14.1 16.7 19.8 22.0 .. .. .. 14.9 Morocco .. 4.8 3.8 3.8 3.7 3.6 3.6 4.6 5.9 7.1 4.2 4.3 Tunisia 15.0 8.7 .. .. 9.8 .. .. .. .. 14.1 11.5 11.1 ALL AFRICA .. 7.8 6.4 6.9 7.2 7.4 8.4 9.2 7.4 8.9 7.2 7.2 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 27 Table 2.21 Private sector �xed capital formation Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 16.4 12.9 11.8 11.8 12.5 13.5 13.7 14.2 13.4 14.4 12.4 12.6 Excluding South Africa .. 10.7 12.4 11.9 12.5 13.6 13.3 13.7 13.3 9.8 11.5 12.6 Excl. S. Africa & Nigeria .. 10.7 12.4 11.9 12.5 13.6 13.3 13.7 13.3 9.8 11.5 12.6 Angola .. 1.7 5.1 4.2 3.0 2.4 2.3 1.9 2.4 9.2 16.5 4.3 Benin .. 6.0 12.0 12.1 12.2 13.6 13.9 14.9 15.4 4.5 8.3 12.8 Botswana 34.5 23.8 15.4 16.3 17.3 15.5 16.1 21.3 8.9 19.4 15.5 15.3 Burkina Faso .. 8.0 11.1 .. .. .. .. .. .. 8.8 10.8 10.4 Burundi 1.1 2.7 2.3 2.3 1.7 .. .. .. .. 2.3 –0.3 1.9 Cameroon 15.6 11.9 15.8 15.7 15.2 14.3 14.7 12.5 12.4 14.2 11.7 15.0 Cape Verde .. 12.6 8.9 29.7 28.4 31.3 32.9 38.0 42.7 7.6 9.3 23.5 Central African Republic 3.2 6.7 3.9 4.1 4.9 5.6 6.2 7.1 6.9 4.7 5.0 5.3 Chad .. .. 36.1 14.9 8.9 5.1 9.7 16.0 21.8 0.6 4.3 20.0 Comoros 5.3 6.7 4.9 5.0 4.8 4.7 5.0 5.0 7.7 5.5 7.7 5.4 Congo, Dem. Rep. 3.7 8.9 9.5 10.0 10.5 9.9 10.7 11.3 6.1 7.1 6.3 8.4 Congo, Rep. .. 11.6 18.8 15.4 15.7 14.9 15.6 12.9 13.5 11.4 18.5 15.1 Côte d’Ivoire 13.0 4.9 7.0 7.1 7.0 6.3 6.1 7.1 8.3 8.7 6.2 7.3 Djibouti .. 5.1 7.7 13.8 9.7 22.0 25.2 .. .. .. 5.8 11.9 Equatorial Guinea .. 6.9 31.7 27.4 27.4 16.2 16.4 11.4 16.1 .. 52.6 29.1 Eritrea .. .. 7.7 5.3 1.8 1.1 1.2 .. .. .. 8.6 5.3 Ethiopia .. 8.9 9.0 9.7 8.3 7.6 6.7 5.9 5.9 12.8 9.9 7.9 Gabon 21.4 17.6 20.2 20.2 17.1 21.1 21.5 19.8 23.2 27.2 18.9 20.4 Gambia, The .. 14.9 13.5 13.9 .. .. .. .. .. 8.6 12.3 11.9 Ghana .. 6.9 14.0 16.0 17.0 12.8 11.6 12.1 11.6 3.8 8.6 13.4 Guinea .. 8.8 15.9 16.1 15.8 14.0 11.5 12.1 17.0 8.9 11.7 13.6 Guinea-Bissau .. 8.4 .. .. .. .. .. .. .. 10.0 7.7 1.1 Kenya 8.2 10.9 7.8 7.5 6.7 25.4 15.5 15.3 14.5 10.7 9.8 11.5 Lesotho 25.7 30.8 24.4 19.2 17.5 17.3 15.5 17.8 17.3 23.1 46.8 21.1 Liberia .. .. 4.8 4.2 4.3 .. .. .. .. .. .. 3.5 Madagascar .. 6.9 10.1 13.4 13.5 14.7 25.4 33.2 29.4 3.6 5.5 16.9 Malawi 4.7 12.4 7.4 7.1 13.0 15.0 9.2 13.9 14.9 6.3 6.0 9.6 Mali .. 12.4 17.3 13.5 15.0 14.3 14.0 .. .. 9.9 12.4 15.7 Mauritania .. 13.7 13.9 37.3 36.7 .. .. .. .. 19.0 13.9 22.9 Mauritius 14.9 19.2 13.9 15.0 15.1 16.6 19.6 20.4 19.5 13.8 17.7 16.7 Mozambique 0.0 10.1 11.8 8.0 10.1 5.8 4.4 4.1 7.9 2.7 8.6 9.8 Namibia 11.4 13.0 20.1 15.7 16.2 18.4 16.1 14.7 15.6 7.8 12.8 15.4 Niger 5.1 4.0 5.7 10.7 12.2 .. .. .. .. 3.0 3.4 7.2 Nigeria .. .. .. .. .. .. .. .. .. .. .. .. Rwanda .. 8.7 12.8 6.2 7.0 8.5 9.3 11.8 10.6 7.8 7.2 10.3 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 9.9 13.9 15.0 16.0 19.7 18.5 19.7 20.2 17.8 13.7 15.4 18.2 Seychelles .. 14.8 8.7 9.7 20.1 18.1 25.0 22.2 20.9 10.1 19.3 17.2 Sierra Leone 9.5 5.7 9.0 5.9 11.3 10.1 9.7 8.6 7.4 7.3 3.3 7.2 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 19.5 15.3 11.2 11.7 12.5 13.4 14.1 14.6 13.4 17.4 13.5 12.7 Sudan 3.8 .. 11.2 12.2 18.2 18.4 17.0 16.2 16.3 8.9 9.9 13.8 Swaziland 23.1 10.1 6.0 5.5 5.6 6.7 6.0 5.6 3.0 17.3 11.3 7.0 Tanzania .. 15.3 14.9 14.2 14.4 16.3 17.5 18.3 20.5 .. 15.6 15.7 Togo 8.0 18.0 17.2 15.9 19.5 .. .. .. .. 7.8 11.8 17.3 Uganda .. 6.5 15.6 15.1 17.3 16.4 16.9 18.3 17.5 5.4 10.3 15.8 Zambia .. 7.2 12.7 14.3 15.5 18.5 20.0 17.4 17.8 4.9 5.7 13.7 Zimbabwe 12.3 14.8 11.7 0.0 0.0 0.0 4.0 3.5 1.7 13.1 16.0 5.0 NORTH AFRICA .. 15.4 10.5 10.5 10.9 12.1 13.5 14.5 19.9 12.8 12.0 12.8 Algeria 22.8 18.8 13.2 13.6 11.5 11.0 9.5 10.2 33.0 18.1 19.0 14.4 Egypt, Arab Rep. .. 12.3 8.1 7.7 8.6 10.7 13.1 14.4 10.9 9.3 5.9 10.0 Libya .. .. 1.9 1.6 1.7 4.0 5.2 5.9 .. .. .. 3.2 Morocco 16.7 19.2 21.3 22.4 23.8 24.5 27.6 28.4 24.8 16.1 18.0 23.5 Tunisia 13.3 15.6 .. .. 12.3 .. .. .. 23.2 13.5 13.8 16.4 ALL AFRICA .. 14.0 11.3 11.3 11.8 12.9 13.6 14.3 16.1 13.3 12.2 12.7 a. Provisional. 28 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.22 Table External trade balance (exports minus imports) Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 1.2 0.8 –1.5 –1.3 –1.3 –1.9 –2.4 –3.8 –3.7 –0.4 –1.5 –1.5 Excluding South Africa –4.6 –2.5 –4.3 –2.0 –1.9 –1.6 –2.0 –4.4 –5.9 –4.7 –4.6 –2.9 Excl. S. Africa & Nigeria –8.6 –6.3 –5.7 –5.3 –5.8 –5.3 –5.9 –8.4 –9.4 –6.1 –6.6 –6.1 Angola .. 18.0 6.6 16.0 29.8 37.8 31.1 25.1 6.0 9.1 2.2 19.2 Benin –21.5 –12.0 –12.8 –12.7 –12.6 –11.3 –15.3 –13.6 –14.3 –17.5 –12.5 –13.2 Botswana –13.4 5.3 11.0 7.3 16.8 16.4 12.0 –0.1 –11.0 5.3 9.8 8.4 Burkina Faso –22.3 –13.5 –12.9 –13.5 –15.6 –15.3 .. .. .. –19.6 –13.5 –14.2 Burundi –14.5 –19.9 –19.3 –24.3 –33.9 –36.2 .. .. .. –13.5 –14.4 –22.3 Cameroon 0.8 2.9 0.3 –0.4 –1.0 2.1 0.8 –3.0 –4.3 0.4 3.7 –0.4 Cape Verde .. –31.0 –34.5 –38.9 –32.9 –35.6 –38.0 –39.2 –41.8 –29.0 –35.2 –36.5 Central African Republic –15.9 –12.9 –4.5 –6.2 –8.8 –7.9 –7.4 –12.6 –7.9 –12.1 –7.7 –6.9 Chad –11.9 –14.4 –34.1 0.2 17.2 22.0 2.5 2.6 –28.0 –13.5 –13.6 –17.1 Comoros –43.2 –22.9 –13.7 –17.9 –21.6 –24.4 –26.6 –34.4 –33.5 –33.3 –23.0 –21.8 Congo, Dem. Rep. 0.1 0.3 –7.2 –8.8 –8.2 –13.7 –10.8 –15.2 –12.1 –0.8 1.2 –8.2 Congo, Rep. –0.1 7.9 4.8 29.7 29.7 18.5 23.2 26.3 21.0 –0.5 2.9 24.2 Côte d’Ivoire –6.2 4.6 10.9 9.2 7.5 10.3 5.9 7.7 8.0 3.2 6.5 9.2 Djibouti .. –24.6 –9.2 –17.2 –10.3 –17.4 –20.1 .. .. .. –17.5 –12.9 Equatorial Guinea .. –37.4 20.4 35.1 43.8 53.7 51.6 46.1 32.5 –28.6 –45.8 35.3 Eritrea .. .. –69.0 –63.8 –45.7 –29.7 –28.2 –18.1 –15.8 .. –55.8 –44.9 Ethiopia .. –3.3 –14.1 –16.7 –20.4 –22.7 –19.3 –19.4 –18.3 –5.3 –6.8 –16.9 Gabon 33.1 15.2 24.3 30.2 37.0 30.1 29.4 34.6 18.9 9.7 17.7 28.6 Gambia, The –20.9 –11.7 –9.2 –21.1 –22.8 –17.2 –16.3 –18.6 –19.7 –13.2 –12.6 –14.8 Ghana –0.7 –9.0 –15.9 –21.1 –25.3 –15.5 –16.3 –19.5 –10.8 –3.1 –12.4 –17.5 Guinea .. –2.4 –0.1 –2.3 –1.3 –3.3 –4.6 –5.3 –4.7 0.3 –3.0 –3.0 Guinea-Bissau –29.2 –27.1 .. .. .. .. .. .. .. –32.9 –24.5 –25.2 Kenya –6.4 –5.6 –6.0 –6.3 –7.5 –9.9 –11.0 –14.2 –13.1 –4.9 –3.7 –9.3 Lesotho –89.1 –105.1 –58.3 –52.2 –53.8 –49.6 –52.8 –54.0 –60.5 –110.0 –101.9 –57.5 Liberia –0.1 .. –12.6 –13.9 –14.0 –54.6 –162.5 –141.5 .. 2.9 –39.6 –46.7 Madagascar –16.4 –11.4 –9.0 –14.8 –17.3 –16.0 –21.7 –30.3 –23.7 –7.7 –8.2 –15.0 Malawi –14.0 –9.6 –13.9 –18.2 –28.1 –24.5 –8.1 –17.4 –7.7 –6.7 –14.3 –15.2 Mali –14.4 –16.6 –10.9 –12.4 –11.7 –8.1 –9.4 .. .. –17.6 –14.9 –11.2 Mauritania –29.8 –15.1 –30.9 –49.4 –59.8 –11.0 –14.3 –22.2 –17.8 –24.4 –11.2 –27.5 Mauritius –10.2 –7.2 1.3 –2.4 –6.0 –11.3 –10.3 –14.7 –10.6 –3.3 –4.1 –4.6 Mozambique –16.5 –27.9 –18.7 –10.9 –12.2 –8.9 –9.8 –14.1 –18.7 –18.4 –23.6 –15.0 Namibia 7.8 –15.5 –9.1 –2.3 0.1 –1.7 –1.3 –6.7 –13.3 –7.6 –10.0 –4.6 Niger –13.5 –6.9 –9.2 –10.0 –9.2 .. .. .. .. –8.0 –6.2 –8.8 Nigeriab 10.2 14.6 2.3 12.9 15.5 15.1 15.1 12.3 8.7 1.1 4.1 11.4 Rwanda –11.9 –8.5 –17.6 –13.6 –13.8 –14.2 –14.6 –15.8 –17.5 –10.3 –19.9 –15.8 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal –14.5 –6.8 –12.1 –12.9 –15.6 –17.5 –22.3 –26.6 –19.9 –12.1 –7.1 –15.6 Seychelles –11.2 –4.3 11.2 2.0 –21.6 –18.0 –31.2 –19.4 –8.3 –2.3 –8.6 –11.1 Sierra Leone –15.4 –1.3 –17.6 –10.9 –12.9 –7.6 –7.0 –13.0 –12.8 –3.1 –4.5 –14.0 Somalia –55.3 –28.0 .. .. .. .. .. .. .. –35.1 –28.0 .. South Africa 8.0 5.5 2.3 –0.3 –0.5 –2.4 –2.9 –3.0 –0.9 5.1 2.8 0.3 Sudan –12.6 –3.0 –4.2 –3.8 –9.9 –10.9 –3.8 0.8 –5.8 –8.3 –6.7 –5.4 Swaziland –39.4 –9.9 –1.0 –2.7 –4.2 –2.6 –1.3 –15.5 –16.7 –23.5 –15.2 –7.7 Tanzania .. –24.8 –4.2 –6.4 –8.9 –13.1 –12.8 –16.4 –11.9 .. –19.0 –8.7 Togo –5.3 –11.9 –13.6 –13.5 –16.9 –19.5 –20.5 .. .. –7.2 –9.6 –17.7 Uganda –6.6 –12.1 –13.8 –10.1 –10.7 –13.1 –13.3 –7.7 –11.2 –6.2 –11.7 –11.8 Zambia –4.0 –0.7 –12.4 –4.4 –2.1 8.4 6.4 2.5 3.4 –2.1 –5.6 –4.3 Zimbabwe –3.2 0.1 –5.7 –7.3 –9.2 –11.4 –9.1 –28.3 –29.1 –0.8 –2.3 –9.9 NORTH AFRICA –7.2 –5.9 4.6 5.6 8.2 10.1 6.5 5.5 –4.5 –8.9 –3.1 4.2 Algeria 4.0 –1.5 14.4 14.4 23.4 27.1 23.3 23.4 4.3 –2.5 1.6 17.4 Egypt, Arab Rep. –12.4 –12.7 –2.6 –1.4 –2.3 –1.6 –4.6 –5.6 –6.8 –13.2 –6.7 –4.1 Libya .. 8.6 25.7 31.1 38.1 45.8 38.2 39.9 .. .. 3.6 29.1 Morocco –9.4 –5.4 –2.8 –5.0 –5.6 –5.5 –9.1 –13.4 –10.9 –7.4 –4.9 –6.2 Tunisia –5.4 –7.0 –3.9 –2.9 –0.4 –2.3 –2.4 –4.2 –3.4 –6.1 –4.3 –3.2 ALL AFRICA –2.2 –2.0 1.1 1.6 2.7 3.1 1.4 0.2 –4.0 –3.8 –2.2 0.9 a. Provisional. b. For 1994–2000 Nigeria’s values were distorted because the of�cial exchange rate used by the government for oil exports and oil value added was signi�cantly overvalued. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 29 Table 2.23 Exports of goods and services, nominal Current prices ($ millions) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 82,540 79,795 145,376 185,542 234,188 278,709 323,596 396,735 298,039 65,089 87,615 220,178 Excluding South Africa 54,029 52,368 98,474 127,656 166,562 200,430 234,106 299,097 220,322 38,654 55,868 157,694 Excl. S. Africa & Nigeria 33,788 40,438 69,589 89,049 114,319 137,465 166,118 212,813 158,411 31,094 43,640 111,379 Angola .. 3,992 9,716 13,780 24,286 33,343 44,707 64,243 39,432 2,613 4,265 25,294 Benin 222 264 487 539 577 538 900 1,019 922 214 327 606 Botswana 563 2,087 3,668 4,444 5,256 5,292 5,877 5,660 3,971 999 2,378 4,268 Burkina Faso 173 340 376 549 542 665 .. .. .. 189 286 417 Burundi 81 89 50 64 91 99 .. .. .. 111 89 63 Cameroon 1,880 2,251 2,757 3,061 3,393 4,131 4,563 7,718 5,896 2,240 2,198 3,813 Cape Verde .. 43 253 138 171 229 285 345 366 41 79 229 Central African Republic 201 220 154 168 170 207 254 215 290 181 185 197 Chad 175 234 674 2,252 3,234 3,852 3,845 4,413 2,879 153 254 2,189 Comoros 11 36 57 55 55 57 68 74 79 22 40 55 Congo, Dem. Rep. 2,372 2,759 1,483 1,994 2,450 2,621 2,711 2,701 1,017 2,016 1,595 1,799 Congo, Rep. 1,024 1,502 2,825 3,744 5,123 6,507 6,402 8,642 6,884 1,092 1,393 4,734 Côte d’Ivoire 3,561 3,421 6,297 7,517 8,354 9,144 9,465 10,890 9,722 3,142 4,129 7,576 Djibouti .. 244 248 246 288 307 484 .. .. .. 210 276 Equatorial Guinea .. 42 2,859 4,724 7,183 8,332 10,299 14,498 7,713 32 160 6,074 Eritrea .. .. 56 64 68 84 86 61 84 .. 132 77 Ethiopia .. 672 1,137 1,495 1,855 2,101 2,442 2,950 3,011 608 715 1,794 Gabon 2,770 2,740 3,350 4,465 5,610 5,912 7,203 9,675 5,773 1,964 2,728 5,091 Gambia, The 103 190 158 184 185 203 214 244 223 108 195 192 Ghana 376 993 3,101 3,487 3,907 5,136 6,041 7,140 7,982 554 1,684 4,425 Guinea .. 829 865 862 994 1,108 1,267 1,259 1,671 660 798 1,036 Guinea-Bissau 14 24 .. .. .. .. .. .. .. 15 32 62 Kenya 2,144 2,207 3,590 4,283 5,342 5,945 7,062 8,291 7,413 1,805 2,594 5,092 Lesotho 91 98 520 721 703 759 880 936 809 67 187 629 Liberia 613 .. 133 171 201 175 208 262 .. 519 43 168 Madagascar 539 512 1,264 1,424 1,422 1,640 2,227 2,498 2,447 414 673 1,613 Malawi 307 447 647 655 663 705 936 1,203 1,420 295 465 771 Mali 263 415 1,153 1,237 1,359 1,884 1,871 .. .. 255 514 1,262 Mauritania 261 465 356 473 667 1,366 1,548 1,952 1,504 387 465 913 Mauritius 579 1,724 3,180 3,450 3,761 4,009 4,422 4,926 4,161 807 2,257 3,677 Mozambique 383 201 1,348 1,759 2,087 2,722 2,839 3,192 2,454 215 373 1,920 Namibia 1,712 1,220 2,141 2,630 2,937 3,180 4,468 4,787 4,319 1,139 1,543 2,907 Niger 617 372 438 491 512 .. .. .. .. 420 325 403 Nigeria 18,859 12,366 28,891 38,609 52,238 62,959 68,061 86,396 62,054 7,725 12,563 46,350 Rwanda 168 145 139 232 295 344 410 680 610 173 107 315 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 837 1,453 1,830 2,126 2,344 2,401 2,875 3,477 3,082 989 1,347 2,237 Seychelles 100 230 671 684 717 860 993 1,091 912 123 298 750 Sierra Leone 252 146 230 247 292 355 346 319 305 187 155 250 Somalia 200 90 .. .. .. .. .. .. .. 119 90 .. South Africa 28,555 27,149 46,900 57,890 67,647 78,318 89,549 98,005 77,883 26,088 31,523 62,550 Sudan 806 499 2,613 3,822 4,992 6,015 9,287 12,974 8,230 841 579 5,353 Swaziland 405 658 1,872 2,056 2,250 2,259 2,311 1,795 1,794 394 886 1,779 Tanzania .. 538 2,164 2,520 2,945 3,233 4,093 4,689 4,963 .. 949 2,963 Togo 580 545 595 691 850 938 1,048 .. .. 464 441 681 Uganda 242 312 722 1,077 1,278 1,519 1,991 3,506 3,753 371 500 1,587 Zambia 1,608 1,180 1,256 2,079 2,482 4,120 4,802 5,267 4,560 1,060 1,099 2,749 Zimbabwe 1,561 2,009 1,856 2,001 1,931 1,957 2,000 1,802 2,040 1,530 2,467 2,053 NORTH AFRICA 37,505 46,844 84,346 107,367 138,842 167,469 197,126 253,603 200,244 34,399 48,912 135,256 Algeria 14,541 14,546 26,028 34,067 48,761 56,953 63,297 79,123 56,798 12,221 12,420 42,760 Egypt, Arab Rep. 6,992 8,647 18,074 22,258 27,214 32,191 39,469 53,800 47,185 6,654 12,435 28,952 Libya .. 11,468 15,011 21,117 29,230 40,275 48,510 62,780 .. .. 8,527 27,469 Morocco 3,273 6,830 14,282 16,726 19,234 22,449 26,892 33,312 26,121 3,790 8,363 19,266 Tunisia 3,518 5,353 10,950 13,199 14,402 15,600 18,958 24,588 20,568 3,312 7,168 14,598 ALL AFRICA 121,315 126,751 229,724 292,911 373,037 446,193 520,752 650,506 496,886 100,090 136,561 355,318 a. Provisional. 30 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.24 Table Imports of goods and services, nominal Current prices ($ millions) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 75,861 74,537 149,688 181,775 220,807 259,550 306,358 384,534 317,933 66,471 90,422 215,193 Excluding South Africa 53,970 53,674 106,770 123,252 152,038 174,847 208,464 279,044 238,718 44,946 62,531 151,820 Excl. S. Africa & Nigeria 40,777 45,400 79,350 95,931 117,132 134,048 165,502 217,932 191,987 37,295 51,235 118,742 Angola .. 2,147 8,801 10,621 15,144 16,287 26,304 43,121 34,901 1,895 4,032 17,472 Benin 524 486 944 1,055 1,119 1,075 1,750 1,928 1,875 447 579 1,181 Botswana 705 1,888 2,780 3,707 3,534 3,451 4,386 5,679 5,273 842 1,916 3,542 Burkina Faso 603 758 928 1,240 1,390 1,547 .. .. .. 567 640 1,016 Burundi 214 314 165 225 360 432 .. .. .. 254 234 229 Cameroon 1,829 1,931 2,712 3,128 3,562 3,763 4,395 8,435 6,856 2,219 1,816 3,931 Cape Verde .. 148 529 497 500 624 791 945 1,013 118 237 600 Central African Republic 327 411 205 246 289 324 381 464 449 292 282 300 Chad 298 485 1,608 2,241 2,324 2,509 3,670 4,195 4,794 305 469 2,493 Comoros 64 93 101 120 138 156 192 256 258 67 93 143 Congo, Dem. Rep. 2,354 2,731 1,892 2,573 3,036 3,789 3,785 4,468 2,298 2,107 1,537 2,518 Congo, Rep. 1,026 1,282 2,659 2,363 3,318 5,073 4,464 5,541 4,876 1,093 1,309 3,282 Côte d’Ivoire 4,190 2,927 4,796 6,093 7,132 7,356 8,302 9,085 7,866 2,906 3,406 6,147 Djibouti .. 355 305 361 361 441 654 .. .. .. 295 365 Equatorial Guinea .. 92 2,256 2,882 3,583 3,179 3,809 5,953 4,328 61 270 2,978 Eritrea .. .. 588 663 603 465 474 361 379 .. 482 498 Ethiopia .. 1,069 2,341 3,169 4,359 5,537 6,143 7,976 8,229 1,093 1,330 4,373 Gabon 1,354 1,837 1,882 2,299 2,400 3,037 3,805 4,652 3,685 1,586 1,823 2,667 Gambia, The 153 227 192 269 290 290 320 397 368 137 242 273 Ghana 407 1,522 4,316 5,356 6,617 8,304 10,057 12,690 10,820 709 2,509 6,833 Guinea .. 892 868 947 1,031 1,202 1,460 1,460 1,865 658 905 1,140 Guinea-Bissau 46 90 .. .. .. .. .. .. .. 67 91 114 Kenya 2,608 2,691 4,478 5,290 6,740 8,171 10,059 12,563 11,253 2,154 3,071 7,085 Lesotho 475 666 1,072 1,350 1,411 1,462 1,713 1,796 1,764 496 926 1,287 Liberia 614 .. 184 235 275 509 1,403 1,454 .. 491 180 504 Madagascar 1,202 864 1,756 2,072 2,296 2,525 3,823 5,357 4,484 668 942 2,624 Malawi 480 629 984 1,134 1,438 1,468 1,215 1,911 1,783 384 716 1,213 Mali 520 817 1,630 1,841 1,979 2,360 2,542 .. .. 536 882 1,742 Mauritania 473 619 753 1,239 1,778 1,662 1,955 2,747 2,043 576 607 1,422 Mauritius 695 1,915 3,107 3,601 4,138 4,744 5,193 6,295 5,074 853 2,400 4,063 Mozambique 965 888 2,222 2,381 2,891 3,351 3,626 4,585 4,287 773 1,001 2,853 Namibia 1,542 1,584 2,589 2,780 2,927 3,317 4,583 5,387 5,548 1,284 1,844 3,218 Niger 957 545 688 795 825 .. .. .. .. 583 448 629 Nigeria 12,324 8,203 27,360 27,282 34,849 40,726 43,039 61,006 46,999 7,362 11,214 33,073 Rwanda 307 364 464 517 651 787 955 1,423 1,524 354 405 762 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 1,344 1,840 2,662 3,166 3,700 4,037 5,407 6,976 5,637 1,408 1,719 3,725 Seychelles 117 246 593 671 908 1,034 1,313 1,271 975 123 344 850 Sierra Leone 421 154 404 367 452 463 462 575 554 225 191 414 Somalia 534 346 .. .. .. .. .. .. .. 403 346 .. South Africa 22,073 21,016 42,967 58,544 68,809 84,706 97,946 106,345 80,328 21,441 27,961 63,596 Sudan 1,763 877 3,367 4,650 7,701 9,995 11,041 12,537 11,391 1,744 1,289 6,856 Swaziland 619 768 1,889 2,117 2,357 2,329 2,350 2,234 2,295 515 1,109 1,948 Tanzania .. 1,595 2,660 3,343 4,205 5,116 6,250 8,090 7,511 .. 1,986 4,358 Togo 640 738 833 969 1,206 1,371 1,561 .. .. 542 586 1,007 Uganda 324 834 1,597 1,932 2,237 2,820 3,577 4,618 5,557 619 1,039 2,664 Zambia 1,764 1,203 1,796 2,319 2,631 3,221 4,068 4,909 4,118 1,148 1,283 2,757 Zimbabwe 1,771 2,002 2,180 2,413 2,446 2,551 2,455 3,005 3,678 1,598 2,644 2,558 NORTH AFRICA 38,163 53,024 72,890 89,433 103,625 115,892 151,699 199,201 193,682 40,285 53,422 111,461 Algeria 12,847 15,472 16,239 21,808 24,838 25,211 31,633 39,171 50,772 13,875 11,636 24,778 Egypt, Arab Rep. 9,822 14,109 20,219 23,330 29,246 33,931 45,443 62,909 60,048 10,787 16,572 33,962 Libya .. 8,996 8,823 10,723 12,452 14,383 21,074 25,589 .. .. 7,464 12,328 Morocco 5,033 8,227 15,691 19,547 22,569 26,044 33,750 45,214 36,088 4,955 9,907 23,634 Tunisia 3,987 6,220 11,918 14,026 14,521 16,322 19,799 26,317 21,894 3,834 7,842 15,503 ALL AFRICA 115,055 127,845 222,549 271,175 324,379 375,349 458,104 583,978 509,907 107,382 143,939 326,492 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 31 Table 2.25 Exports of goods and services as a share of GDP Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 31.9 26.4 31.0 31.2 32.6 33.3 33.8 36.0 29.8 26.9 27.2 32.4 Excluding South Africa 29.1 28.0 33.2 34.6 36.4 35.8 35.8 36.3 31.7 25.4 29.9 34.4 Excl. S. Africa & Nigeria 29.0 24.6 31.1 32.6 34.1 34.2 34.5 35.1 30.7 26.4 27.3 32.6 Angola .. 38.9 69.6 69.7 79.3 73.8 75.4 76.3 52.2 34.8 63.4 73.6 Benin 15.8 14.3 13.7 13.3 13.5 11.4 16.2 15.2 13.8 16.6 16.4 14.1 Botswana 53.1 55.1 45.4 44.2 51.2 47.0 47.5 41.8 33.6 62.0 51.5 45.5 Burkina Faso 9.0 11.0 8.8 10.7 10.0 11.5 .. .. .. 9.5 11.1 9.7 Burundi 8.8 7.9 8.4 9.6 11.4 10.7 .. .. .. 10.4 9.0 8.7 Cameroon 27.9 20.2 20.2 19.4 20.5 23.0 22.1 32.5 26.6 25.7 20.9 22.9 Cape Verde .. 12.7 31.7 14.9 17.1 20.7 21.4 22.5 23.6 15.5 16.9 24.1 Central African Republic 25.2 14.8 13.5 13.2 12.6 14.0 14.8 10.8 14.5 20.5 16.2 14.5 Chad 16.9 13.5 24.6 51.0 61.0 63.2 54.8 52.8 42.1 14.3 16.1 39.4 Comoros 8.7 14.3 17.5 15.1 14.1 14.2 14.7 13.9 14.7 14.7 17.3 15.2 Congo, Dem. Rep. 16.5 29.5 26.1 30.4 34.5 30.7 27.2 23.3 9.6 21.4 23.1 24.4 Congo, Rep. 60.0 53.7 80.8 80.5 84.2 84.2 76.7 73.3 71.9 52.0 60.2 79.1 Côte d’Ivoire 35.0 31.7 45.8 48.6 51.1 52.7 47.8 46.5 41.7 37.1 36.8 46.6 Djibouti .. 53.8 39.9 37.0 40.6 39.9 57.1 .. .. .. 43.2 40.7 Equatorial Guinea .. 32.2 96.8 90.1 87.4 86.8 81.9 78.3 74.1 35.9 52.9 89.5 Eritrea .. .. 7.3 6.8 5.8 6.5 6.3 3.7 4.5 .. 22.0 8.1 Ethiopia .. 5.6 13.3 14.9 15.1 13.9 12.7 11.4 10.6 6.6 8.1 12.9 Gabon 64.7 46.0 55.3 62.2 64.7 61.9 62.2 66.6 52.2 53.3 54.0 60.7 Gambia, The 42.7 59.9 43.1 46.0 40.0 39.8 32.9 29.6 30.4 47.8 52.6 38.8 Ghana 8.5 16.9 40.7 39.3 36.4 25.2 24.5 25.0 30.5 11.2 25.2 35.8 Guinea .. 31.1 25.1 23.5 33.8 39.3 30.1 33.3 40.7 30.2 23.8 30.3 Guinea-Bissau 12.7 9.9 .. .. .. .. .. .. .. 9.9 13.3 30.1 Kenya 29.5 25.7 24.1 26.6 28.5 26.4 26.0 27.6 25.2 25.7 27.6 25.4 Lesotho 21.0 18.1 54.9 59.8 53.4 53.6 55.8 58.7 51.2 16.9 25.0 52.9 Liberia 64.3 .. 32.4 37.3 37.9 28.6 28.3 31.1 .. 55.3 11.4 28.9 Madagascar 13.3 16.6 23.1 32.6 28.2 29.7 30.3 26.5 28.5 13.6 20.1 27.5 Malawi 24.8 23.8 26.7 25.0 24.0 22.6 27.1 29.5 30.0 23.7 25.1 25.9 Mali 14.7 17.1 26.4 25.4 25.6 32.1 26.2 .. .. 15.8 20.8 28.5 Mauritania 36.8 45.6 27.7 30.6 35.9 50.6 54.5 54.4 49.7 47.9 36.7 41.7 Mauritius 51.0 65.0 56.7 54.0 59.9 61.6 58.8 52.9 48.4 54.4 61.5 58.4 Mozambique 10.9 8.2 28.9 30.9 31.7 38.4 35.4 32.3 25.1 6.8 12.8 29.0 Namibia 78.9 51.9 43.4 39.8 40.5 39.9 50.7 53.4 46.6 61.2 49.7 44.2 Niger 24.6 15.0 16.0 16.1 15.0 .. .. .. .. 21.0 16.2 16.2 Nigeria 29.4 43.4 42.7 44.0 46.5 42.9 41.0 41.7 35.9 21.4 42.0 42.3 Rwanda 14.4 5.6 7.6 11.1 11.4 11.1 11.0 14.5 11.7 10.4 6.0 10.4 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 23.9 25.4 26.6 26.4 26.9 25.6 25.4 26.4 24.0 27.4 26.4 26.7 Seychelles 68.0 62.5 95.1 97.8 81.1 88.8 96.7 117.8 119.3 62.1 59.9 94.0 Sierra Leone 22.9 22.4 23.2 22.5 23.6 24.9 20.8 16.3 15.7 19.5 19.8 19.9 Somalia 33.2 9.8 .. .. .. .. .. .. .. 15.5 9.8 .. South Africa 35.4 24.2 27.9 26.4 27.4 30.0 31.3 35.5 27.3 28.8 23.5 29.7 Sudan 10.6 4.0 14.7 17.6 18.2 16.5 20.0 22.4 15.1 7.4 5.4 16.6 Swaziland 74.6 59.0 104.2 90.1 89.1 84.6 78.3 63.2 59.8 70.2 61.1 83.5 Tanzania .. 12.6 18.6 19.7 20.8 22.6 24.3 22.6 23.2 .. 15.9 20.0 Togo 51.1 33.5 33.8 33.5 40.3 42.3 41.9 .. .. 46.1 30.2 36.0 Uganda 19.4 7.2 11.4 12.7 14.2 15.3 16.7 24.3 23.4 11.6 9.8 15.1 Zambia 41.4 35.9 28.7 38.3 34.7 38.6 42.1 36.6 35.6 34.4 32.8 33.8 Zimbabwe 23.4 22.9 32.8 35.3 34.6 37.6 39.8 42.4 36.3 21.4 33.3 36.5 NORTH AFRICA 30.2 26.4 33.6 37.2 40.8 41.8 41.5 43.4 32.1 24.1 26.0 35.6 Algeria 34.3 23.4 38.3 40.1 47.6 48.6 46.6 46.3 40.4 23.8 25.8 42.0 Egypt, Arab Rep. 30.5 20.0 21.8 28.2 30.3 29.9 30.3 33.0 25.0 22.2 21.8 25.1 Libya .. 39.7 62.4 63.3 66.4 71.3 67.6 67.4 .. .. 28.7 56.9 Morocco 17.4 26.5 28.7 29.4 32.3 34.2 35.7 37.5 28.6 22.2 25.9 31.4 Tunisia 40.2 43.6 43.8 46.9 49.7 50.4 53.2 60.2 52.0 36.9 42.5 49.4 ALL AFRICA 31.2 26.4 32.1 33.7 36.1 36.9 37.1 39.2 30.7 25.8 26.7 33.8 a. Provisional. 32 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.26 Table Imports of goods and services as a share of GDP Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 30.8 25.6 32.5 32.5 33.9 35.3 36.2 39.8 33.5 27.3 28.8 33.9 Excluding South Africa 33.6 30.5 37.4 36.6 38.3 37.4 37.7 40.7 37.6 30.1 34.6 37.3 Excl. S. Africa & Nigeria 37.5 30.8 36.8 37.8 39.9 39.5 40.5 43.4 40.1 32.5 33.8 38.7 Angola .. 20.9 63.1 53.7 49.4 36.1 44.4 51.2 46.2 25.6 61.3 54.4 Benin 37.3 26.3 26.5 26.1 26.1 22.7 31.6 28.8 28.2 34.1 28.9 27.3 Botswana 66.4 49.8 34.4 36.9 34.5 30.7 35.4 41.9 44.6 56.7 41.7 37.0 Burkina Faso 31.3 24.5 21.7 24.3 25.6 26.8 .. .. .. 29.2 24.6 24.0 Burundi 23.3 27.8 27.7 33.9 45.3 47.0 .. .. .. 23.8 23.4 31.0 Cameroon 27.1 17.3 19.9 19.8 21.5 21.0 21.2 35.5 30.9 25.3 17.2 23.3 Cape Verde .. 43.7 66.3 53.8 50.1 56.3 59.4 61.7 65.4 44.6 52.1 60.6 Central African Republic 41.1 27.6 18.0 19.4 21.4 21.9 22.3 23.4 22.4 32.5 24.0 21.4 Chad 28.9 27.9 58.7 50.8 43.8 41.1 52.3 50.2 70.1 27.7 29.7 56.5 Comoros 51.9 37.1 31.2 33.0 35.8 38.6 41.3 48.3 48.2 47.9 40.2 37.0 Congo, Dem. Rep. 16.4 29.2 33.3 39.2 42.7 44.4 37.9 38.6 21.7 22.2 21.9 32.6 Congo, Rep. 60.1 45.8 76.0 50.8 54.5 65.6 53.5 47.0 50.9 52.6 57.3 54.9 Côte d’Ivoire 41.2 27.1 34.9 39.4 43.6 42.4 41.9 38.8 33.8 33.9 30.3 37.5 Djibouti .. 78.4 49.1 54.2 50.9 57.3 77.1 .. .. .. 60.7 53.6 Equatorial Guinea .. 69.6 76.4 55.0 43.6 33.1 30.3 32.1 41.6 64.5 98.6 54.2 Eritrea .. .. 76.3 70.7 51.5 36.3 34.5 21.8 20.3 .. 77.8 53.0 Ethiopia .. 8.8 27.4 31.6 35.5 36.6 32.0 30.8 28.8 11.9 14.9 29.7 Gabon 31.6 30.9 31.1 32.0 27.7 31.8 32.9 32.0 33.3 43.6 36.3 32.1 Gambia, The 63.6 71.6 52.3 67.1 62.8 57.0 49.2 48.3 50.1 61.0 65.3 53.6 Ghana 9.2 25.9 56.6 60.4 61.7 40.7 40.8 44.5 41.3 14.3 37.6 53.3 Guinea .. 33.4 25.2 25.8 35.1 42.6 34.7 38.6 45.4 29.9 26.9 33.3 Guinea-Bissau 41.8 37.0 .. .. .. .. .. .. .. 42.8 37.7 55.3 Kenya 35.9 31.3 30.0 32.9 36.0 36.3 37.0 41.8 38.3 30.6 31.3 34.7 Lesotho 110.1 123.2 113.2 112.0 107.3 103.2 108.6 112.7 111.7 126.9 126.9 110.4 Liberia 64.4 .. 44.9 51.2 51.9 83.2 190.9 172.6 .. 52.4 51.0 75.6 Madagascar 29.7 28.0 32.1 47.5 45.6 45.8 52.1 56.8 52.2 21.3 28.3 42.5 Malawi 38.8 33.4 40.6 43.2 52.2 47.1 35.1 46.9 37.7 30.4 39.4 41.1 Mali 29.1 33.7 37.4 37.8 37.3 40.2 35.6 .. .. 33.4 35.7 39.6 Mauritania 66.7 60.7 58.6 80.0 95.7 61.6 68.9 76.6 67.6 72.2 47.9 69.2 Mauritius 61.2 72.2 55.4 56.4 65.9 72.9 69.0 67.6 59.1 57.6 65.6 63.0 Mozambique 27.4 36.1 47.6 41.8 43.9 47.2 45.2 46.5 43.8 25.1 36.4 44.0 Namibia 71.1 67.4 52.5 42.1 40.3 41.6 52.0 60.1 59.9 68.7 59.7 48.9 Niger 38.1 22.0 25.2 26.0 24.2 .. .. .. .. 29.0 22.4 25.0 Nigeria 19.2 28.8 40.4 31.1 31.0 27.7 25.9 29.5 27.2 20.3 37.8 31.0 Rwanda 26.4 14.1 25.1 24.8 25.2 25.3 25.5 30.3 29.2 20.7 26.0 26.3 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. Senegal 38.4 32.2 38.7 39.4 42.5 43.0 47.7 53.0 44.0 39.6 33.5 42.2 Seychelles 79.1 66.7 84.0 95.8 102.7 106.9 127.9 137.2 127.6 64.4 68.4 105.2 Sierra Leone 38.2 23.8 40.8 33.5 36.5 32.5 27.8 29.4 28.5 22.5 24.2 33.8 Somalia 88.5 37.7 .. .. .. .. .. .. .. 50.6 37.7 .. South Africa 27.3 18.8 25.5 26.7 27.9 32.5 34.2 38.5 28.1 23.8 20.7 29.3 Sudan 23.1 7.1 18.9 21.4 28.1 27.5 23.7 21.6 20.8 15.7 12.1 22.0 Swaziland 114.0 68.9 105.2 92.8 93.4 87.2 79.7 78.7 76.5 93.7 76.3 91.2 Tanzania .. 37.5 22.8 26.1 29.7 35.7 37.1 39.1 35.2 .. 34.9 28.7 Togo 56.4 45.3 47.4 47.0 57.2 61.8 62.5 .. .. 53.3 39.8 53.7 Uganda 26.0 19.4 25.2 22.8 24.9 28.4 30.1 32.0 34.6 17.8 21.5 26.9 Zambia 45.4 36.6 41.1 42.8 36.8 30.2 35.6 34.1 32.2 36.5 38.4 38.0 Zimbabwe 26.5 22.8 38.5 42.6 43.8 49.0 48.9 70.8 65.4 22.2 35.6 46.4 NORTH AFRICA 37.3 32.3 29.0 31.6 32.6 31.7 35.0 37.9 36.6 33.0 29.1 31.4 Algeria 30.3 24.9 23.9 25.7 24.3 21.5 23.3 22.9 36.1 26.3 24.2 24.6 Egypt, Arab Rep. 42.9 32.7 24.4 29.6 32.6 31.6 34.8 38.6 31.9 35.4 28.5 29.1 Libya .. 31.1 36.7 32.1 28.3 25.5 29.4 27.5 .. .. 25.1 27.8 Morocco 26.7 31.9 31.5 34.3 37.9 39.7 44.9 50.9 39.5 29.6 30.9 37.6 Tunisia 45.6 50.6 47.7 49.9 50.1 52.7 55.6 64.4 55.3 43.0 46.8 52.6 ALL AFRICA 33.4 28.4 31.0 32.1 33.4 33.8 35.7 39.0 34.7 29.6 28.9 32.9 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 33 Table 2.27 Balance of payments and current account Exports of goods and services Imports of goods and services Total trade (exports and imports) Current prices Share of GDP Current prices Share of GDP Current prices Share of GDP ($ millions) (%) ($ millions) (%) ($ millions) (%) 2009 a 2009a 2009 a 2009a 2009 a 2009a SUB–SAHARAN AFRICA 298,039 29.8 317,933 33.5 615,972 63.3 Excluding South Africa 220,322 31.7 238,718 37.6 459,041 69.3 Excl. S. Africa & Nigeria 158,411 30.7 191,987 40.1 350,398 70.8 Angola 39,432 52.2 34,901 46.2 74,333 98.5 Benin 922 13.8 1,875 28.2 2,797 42.0 Botswana 3,971 33.6 5,273 44.6 9,245 78.2 Burkina Faso .. .. .. .. .. .. Burundi .. .. .. .. .. .. Cameroon 5,896 26.6 6,856 30.9 12,752 57.5 Cape Verde 366 23.6 1,013 65.4 1,379 89.0 Central African Republic 290 14.5 449 22.4 739 36.9 Chad 2,879 42.1 4,794 70.1 7,673 112.2 Comoros 79 14.7 258 48.2 336 62.8 Congo, Dem. Rep. 1,017 9.6 2,298 21.7 3,315 31.3 Congo, Rep. 6,884 71.9 4,876 50.9 11,760 122.8 Côte d’Ivoire 9,722 41.7 7,866 33.8 17,589 75.5 Djibouti .. .. .. .. .. .. Equatorial Guinea 7,713 74.1 4,328 41.6 12,040 115.6 Eritrea 84 4.5 379 20.3 464 24.7 Ethiopia 3,011 10.6 8,229 28.8 11,240 39.4 Gabon 5,773 52.2 3,685 33.3 9,458 85.5 Gambia, The 223 30.4 368 50.1 591 80.6 Ghana 7,982 30.5 10,820 41.3 18,802 71.8 Guinea 1,671 40.7 1,865 45.4 3,535 86.2 Guinea-Bissau .. .. .. .. .. .. Kenya 7,413 25.2 11,253 38.3 18,666 63.5 Lesotho 809 51.2 1,764 111.7 2,572 163.0 Liberia .. .. .. .. .. .. Madagascar 2,447 28.5 4,484 52.2 6,930 80.7 Malawi 1,420 30.0 1,783 37.7 3,203 67.8 Mali .. .. .. .. .. .. Mauritania 1,504 49.7 2,043 67.6 3,547 117.3 Mauritius 4,161 48.4 5,074 59.1 9,235 107.5 Mozambique 2,454 25.1 4,287 43.8 6,741 68.9 Namibia 4,319 46.6 5,548 59.9 9,868 106.5 Niger .. .. .. .. .. .. Nigeria 62,054 35.9 46,999 27.2 109,052 63.0 Rwanda 610 11.7 1,524 29.2 2,135 40.9 São Tomé and Príncipe .. .. .. .. .. .. Senegal 3,082 24.0 5,637 44.0 8,720 68.0 Seychelles 912 119.3 975 127.6 1,887 246.9 Sierra Leone 305 15.7 554 28.5 859 44.2 Somalia .. .. .. .. .. .. South Africa 77,883 27.3 80,328 28.1 158,210 55.4 Sudan 8,230 15.1 11,391 20.8 19,622 35.9 Swaziland 1,794 59.8 2,295 76.5 4,089 136.3 Tanzania 4,963 23.2 7,511 35.2 12,475 58.4 Togo .. .. .. .. .. .. Uganda 3,753 23.4 5,557 34.6 9,309 58.0 Zambia 4,560 35.6 4,118 32.2 8,678 67.8 Zimbabwe 2,040 36.3 3,678 65.4 5,718 101.7 NORTH AFRICA 200,244 32.1 193,682 36.6 393,926 68.7 Algeria 56,798 40.4 50,772 36.1 107,570 76.5 Egypt, Arab Rep. 47,185 25.0 60,048 31.9 107,233 56.9 Libya .. .. .. .. .. .. Morocco 26,121 28.6 36,088 39.5 62,209 68.1 Tunisia 20,568 52.0 21,894 55.3 42,463 107.3 ALL AFRICA 496,886 30.7 509,907 34.7 1,006,794 65.4 a. Provisional. 34 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts Net income Net current transfers Current account balance Total reserves including gold Current prices Share of GDP Current prices Share of GDP Current prices Share of GDP Current prices Share of GDP ($ millions) (%) ($ millions) (%) ($ millions) (%) ($ millions) (%) 2009 a 2009a 2009 a 2009a 2009 a 2009a 2009 a 2009a .. .. .. .. –12,976 –1.6 160,688 16.8 .. .. .. .. –1,649 –0.3 121,086 18.1 .. .. .. .. –23,308 –6.3 75,576 15.2 –6,823 –9.0 –370 –0.5 –7,572 –10.0 13,664 18.1 .. .. .. .. .. .. 1,230 18.5 –452 –3.8 878 7.4 –526 –4.4 8,704 73.6 .. .. .. .. .. .. 1,296 15.9 –17 –1.3 257 19.4 –164 –12.3 323 24.4 –303 –1.4 393 1.8 –1,137 –5.1 3,676 16.6 –54 –3.5 349 22.5 –154 –9.9 366 23.6 .. .. .. .. .. .. 211 10.5 .. .. .. .. .. .. 617 9.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1,615 15.3 .. .. .. .. .. .. 3,806 39.7 –890 –3.8 –115 –0.5 1,670 7.2 3,267 14.0 22 2.1 86 8.2 –71 –6.8 242 23.1 .. .. .. .. .. .. 3,252 31.2 .. .. .. .. .. .. .. .. –37 –0.1 3,459 12.1 –2,191 –7.7 1,781 6.2 .. .. .. .. .. .. 1,993 18.0 –8 –1.1 135 18.4 63 8.6 224 30.6 –296 –1.1 2,078 7.9 –1,198 –4.6 .. .. –168 –4.1 34 0.8 –403 –9.8 .. .. .. .. .. .. .. .. 169 20.1 –58 –0.2 2,297 7.8 –1,661 –5.7 3,850 13.1 424 26.8 547 34.7 –32 –2.0 .. .. –128 –14.6 1,101 125.6 –277 –31.6 372 42.5 .. .. .. .. .. .. 1,135 13.2 .. .. .. .. .. .. 163 3.5 .. .. .. .. .. .. 1,604 17.8 .. .. .. .. .. .. 238 7.9 27 0.3 224 2.6 –675 –7.9 2,316 27.0 –95 –1.0 764 7.8 –1,171 –12.0 2,181 22.3 –70 –0.8 1,261 13.6 120 1.3 2,051 22.1 .. .. .. .. .. .. 656 12.2 –10,020 –5.8 17,977 10.4 21,659 12.5 45,510 26.3 –37 –0.7 604 11.6 –379 –7.3 743 14.2 0 –0.1 5 2.4 –79 –41.3 .. .. .. .. .. .. .. .. 2,123 16.6 –111 –14.5 58 7.5 –284 –37.2 191 24.9 –36 –1.8 148 7.6 –193 –9.9 405 20.9 .. .. .. .. .. .. .. .. –6,389 –2.2 –2,684 –0.9 –11,327 –4.0 39,603 13.9 –2,402 –4.4 1,480 2.7 –3,908 –7.1 1,094 2.0 –123 –4.1 192 6.4 –414 –13.8 959 32.0 –175 –0.8 683 3.2 –1,816 –8.5 3,470 16.2 .. .. .. .. .. .. 703 24.6 –329 –2.0 1,133 7.1 –451 –2.8 2,994 18.7 –1,363 –10.6 516 4.0 –406 –3.2 1,892 14.8 .. .. .. .. .. .. .. .. .. .. .. .. –174 0.0 328,625 62.9 .. .. .. .. .. .. 155,112 110.3 –2,076 –1.1 7,960 4.2 –3,349 –1.8 34,897 18.5 578 0.9 –1,572 –2.5 9,381 15.0 103,754 166.4 –1,495 –1.6 7,451 8.2 –4,971 –5.4 23,568 25.8 –2,011 –5.1 1,951 4.9 –1,234 –3.1 11,294 28.5 .. .. .. .. –13,150 –1.1 489,313 33.1 National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 35 Table 2.28 Exchange rates and purchasing power parity Purchasing power parity (PPP) Official exchange rate conversion factor Ratio of PPP conversion factor (local currency units to $) (local currency units to international $) to market exchange rate 2007 2008 2009 2007 2008 2009 2007 2008 2009 SUB–SAHARAN AFRICA Excluding South Africa Excl. S. Africa & Nigeria Angola 49.7 59.7 55.7 76.7 75.0 79.3 0.6 0.8 0.7 Benin 222.0 232.7 233.3 479.3 447.8 472.2 0.5 0.5 0.5 Botswana 3.0 3.4 3.2 6.1 6.8 7.2 0.5 0.5 0.5 Burkina Faso 194.3 201.2 205.5 479.3 447.8 472.2 0.4 0.4 0.4 Burundi 363.1 444.6 500.6 1,081.9 1,185.7 1,230.2 0.3 0.4 0.4 Cameroon 249.3 254.2 243.3 479.3 447.8 472.2 0.5 0.6 0.5 Cape Verde 65.7 64.9 66.8 80.6 75.3 79.4 0.8 0.9 0.8 Central African Republic 264.4 274.7 282.8 479.3 447.8 472.2 0.6 0.6 0.6 Chad 232.9 255.2 221.6 479.3 447.8 472.2 0.5 0.6 0.5 Comoros 227.2 234.6 243.2 359.5 335.9 354.1 0.6 0.7 0.7 Congo, Dem. Rep. 274.8 321.0 414.3 516.7 559.3 809.8 0.5 0.6 0.5 Congo, Rep. 300.1 367.3 289.8 479.3 447.8 472.2 0.6 0.8 0.6 Côte d’Ivoire 288.9 305.7 306.9 479.3 447.8 472.2 0.6 0.7 0.6 Djibouti 86.1 92.3 93.0 177.7 177.7 177.7 0.5 0.5 0.5 Equatorial Guinea 304.3 368.3 242.6 479.3 447.8 472.2 0.6 0.8 0.5 Eritrea 6.9 9.0 9.8 15.4 15.4 15.4 0.4 0.6 0.6 Ethiopia 2.8 3.5 4.3 9.0 9.6 11.8 0.3 0.4 0.4 Gabon 272.6 306.0 245.7 479.3 447.8 472.2 0.6 0.7 0.5 Gambia, The 7.7 8.0 8.1 24.9 22.2 26.6 0.3 0.4 0.3 Ghana 0.7 0.9 1.0 0.9 1.1 1.4 0.8 0.8 0.7 Guinea 1,775.0 1,981.9 2,066.8 4,122.8 5,500.0 .. 0.4 0.4 0.4 Guinea-Bissau 211.2 228.5 229.0 479.3 447.8 472.2 0.4 0.5 0.5 Kenya 31.4 34.4 36.3 67.3 69.2 77.4 0.5 0.5 0.5 Lesotho 4.0 4.4 4.5 7.0 8.3 8.5 0.6 0.5 0.5 Liberia 33.2 35.9 38.2 61.3 63.2 68.3 0.5 0.6 0.6 Madagascar 743.2 794.4 852.8 1,873.9 1,708.4 1,956.2 0.4 0.5 0.4 Malawi 48.1 51.3 55.0 140.0 140.5 141.2 0.3 0.4 0.4 Mali 250.5 266.6 275.4 479.3 447.8 472.2 0.5 0.6 0.6 Mauritania 122.3 134.5 125.0 258.6 238.2 262.4 0.5 0.6 0.5 Mauritius 15.9 16.7 16.8 31.3 28.5 32.0 0.5 0.6 0.5 Mozambique 12.0 12.7 13.0 25.8 24.3 27.5 0.5 0.5 0.5 Namibia 4.8 5.3 5.6 7.0 8.3 8.5 0.7 0.6 0.7 Niger 220.0 231.8 241.0 479.3 447.8 472.2 0.5 0.5 0.5 Nigeria 70.7 76.7 75.6 125.8 118.5 148.9 0.6 0.6 0.5 Rwanda 215.1 237.3 261.0 547.0 546.8 568.3 0.4 0.4 0.5 São Tomé and Príncipe 7,514.7 9,049.2 10,364.2 13,536.8 14,695.2 16,208.5 0.6 0.6 0.6 Senegal 259.5 268.9 265.2 479.3 447.8 472.2 0.5 0.6 0.6 Seychelles 3.8 4.7 6.0 6.7 9.5 13.6 0.6 0.5 0.4 Sierra Leone 1,221.5 1,329.2 1,399.7 2,985.2 2,981.5 3,385.7 0.4 0.4 0.4 Somalia .. .. .. .. .. .. .. .. .. South Africa 4.2 4.5 4.7 7.0 8.3 8.5 0.6 0.5 0.6 Sudan 1.2 1.4 1.3 2.0 2.1 2.3 0.6 0.7 0.6 Swaziland 3.7 4.0 4.2 7.0 8.3 8.5 0.5 0.5 0.5 Tanzania 425.0 458.0 487.3 1,245.0 1,196.3 1,320.3 0.3 0.4 0.4 Togo 229.0 238.6 239.5 479.3 447.8 472.2 0.5 0.5 0.5 Uganda 638.1 664.8 767.5 1,723.5 1,720.4 2,030.3 0.4 0.4 0.4 Zambia 2,866.3 3,126.6 3,492.7 4,002.5 3,745.7 5,046.1 0.7 0.8 0.7 Zimbabwe .. .. .. 9,675.8 6,715,424,238.8 .. .. .. .. NORTH AFRICA Algeria 35.6 39.9 35.8 69.3 64.6 72.6 0.5 0.6 0.5 Egypt, Arab Rep. 1.8 2.0 2.2 5.6 5.4 5.5 0.3 0.4 0.4 Libya 0.9 1.1 0.7 1.3 1.2 1.3 0.7 0.9 0.6 Morocco 4.8 5.0 5.0 8.2 7.8 8.1 0.6 0.6 0.6 Tunisia 0.6 0.6 0.6 1.3 1.2 1.4 0.5 0.5 0.5 ALL AFRICA 36 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts Gross domestic product Real effective exchange rate Per capita (index: 2000 = 100) PPP $ billions PPP $ 2007 2008 2009 2007 2008 2009 2007 2008 2009 101.5 104.5 105.7 1,630.7 1,759.6 1,812.9 2,036.1 2,144.0 2,155.8 102.0 105.0 106.6 1,155.6 1,256.7 1,315.6 1,535.4 1,628.1 1,661.8 101.5 104.5 105.7 856.1 932.4 969.7 1,415.3 1,502.2 1,522.6 .. .. .. 91.4 105.8 107.5 5,206.4 5,873.0 5,812.0 .. .. .. 12.0 12.9 13.5 1,426.9 1,484.8 1,507.9 .. .. .. 25.5 26.8 26.1 13,459.8 13,971.3 13,384.5 .. .. .. 16.7 17.9 18.7 1,133.6 1,175.4 1,186.9 96.7 99.3 109.4 2.9 3.1 3.3 372.4 386.1 392.1 102.5 105.6 108.0 39.8 41.8 43.0 2,131.2 2,190.6 2,204.9 .. .. .. 1.6 1.8 1.8 3,320.3 3,561.3 3,643.6 105.3 113.4 115.8 3.1 3.2 3.3 729.0 747.0 757.4 .. .. .. 14.4 14.7 14.6 1,357.0 1,344.4 1,300.1 .. .. .. 0.7 0.8 0.8 1,170.3 1,179.1 1,182.9 106.7 106.3 597.2 18.7 20.3 21.1 299.6 316.4 319.1 .. .. .. 13.3 14.4 15.6 3,752.4 3,976.3 4,238.0 101.0 105.8 105.7 32.8 34.3 35.9 1,631.7 1,665.5 1,701.2 .. .. .. 1.7 1.9 2.0 2,097.3 2,227.5 2,319.5 106.4 115.5 118.1 19.8 22.5 21.5 30,836.7 34,166.0 31,779.1 .. .. .. 3.1 2.8 2.9 639.2 571.8 580.5 .. .. .. 62.3 70.5 77.4 792.3 874.0 934.4 101.0 104.5 105.3 20.3 21.3 21.3 14,309.1 14,689.5 14,419.2 108.3 114.8 104.4 2.1 2.3 2.4 1,304.7 1,376.5 1,414.6 104.6 99.5 91.8 31.6 35.0 37.0 1,382.6 1,500.5 1,552.4 .. .. .. 9.8 10.5 10.5 1,016.9 1,066.2 1,047.8 .. .. .. 1.6 1.7 1.7 1,018.6 1,053.7 1,071.2 .. .. .. 58.3 60.5 62.6 1,543.1 1,559.6 1,572.6 96.5 87.7 93.2 2.8 3.0 3.0 1,374.2 1,454.2 1,467.6 .. .. .. 1.4 1.5 1.6 373.7 391.1 396.0 .. .. .. 18.5 20.3 19.7 995.1 1,060.5 1,004.0 95.0 97.8 107.5 10.1 11.2 12.1 696.8 752.1 794.3 .. .. .. 13.7 14.7 15.4 1,101.7 1,153.3 1,185.5 .. .. .. 6.0 6.4 6.3 1,911.7 1,977.2 1,928.7 .. .. .. 14.8 15.9 16.4 11,733.3 12,518.9 12,838.4 .. .. .. 17.3 18.9 20.3 791.7 843.8 885.2 .. .. .. 13.0 13.9 13.9 6,245.8 6,527.5 6,410.1 .. .. .. 9.2 10.3 10.5 654.1 703.8 689.8 104.9 116.5 109.4 295.3 319.9 340.9 1,999.4 2,115.7 2,203.3 .. .. .. 9.5 10.8 11.4 1,006.3 1,112.2 1,136.0 .. .. .. 0.3 0.3 0.3 1,656.1 1,762.0 1,820.0 .. .. .. 20.9 22.1 22.8 1,757.7 1,807.6 1,816.6 .. .. .. 1.8 1.8 1.7 21,463.1 21,255.3 19,587.0 96.2 102.8 104.5 4.1 4.4 4.6 750.1 788.6 808.0 .. .. .. .. .. .. .. .. .. 90.4 80.4 87.8 482.7 511.4 506.9 10,002.5 10,480.9 10,277.8 .. .. .. 81.1 88.6 93.4 2,006.2 2,141.8 2,209.7 .. .. .. 5.5 5.8 5.9 4,813.6 4,966.0 4,998.4 .. .. .. 49.3 54.1 57.9 1,194.1 1,273.6 1,323.6 98.9 104.3 104.8 5.2 5.4 5.6 830.2 842.4 850.3 101.5 103.6 103.1 33.2 36.8 39.8 1,082.7 1,164.0 1,217.2 120.5 138.8 119.5 15.9 17.2 18.5 1,293.9 1,365.2 1,430.2 .. .. .. .. .. .. .. .. .. 98.5 100.1 102.1 974.0 1,046.3 1,094.3 6,029.5 6,374.8 6,563.2 98.5 103.7 102.1 264.5 276.8 285.2 7,812.4 8,052.2 8,172.5 .. .. .. 407.1 445.8 470.8 5,085.5 5,468.4 5,672.6 .. .. .. 96.9 102.8 105.9 15,713.7 16,335.9 16,502.0 99.7 100.1 102.4 127.8 137.9 146.1 4,094.6 4,364.5 4,566.5 96.1 82.2 94.2 77.5 82.9 86.3 7,584.0 8,028.9 8,272.5 101.0 104.0 105.0 2,602.1 2,803.0 2,904.5 2,703.7 2,846.2 2,882.3 National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 37 Table 2.29 Agriculture value added Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 18.5 18.9 18.6 17.1 16.5 15.9 15.5 12.7 13.1 18.4 18.3 16.2 Excluding South Africa 31.6 31.3 29.6 27.3 26.6 25.6 24.7 22.4 23.5 31.1 30.7 26.6 Excl. S. Africa & Nigeria 31.6 31.3 26.7 25.7 25.2 24.1 22.8 22.4 23.5 31.1 30.7 25.2 Angola .. 17.9 8.3 8.6 7.7 8.9 8.0 6.6 10.2 15.2 11.3 8.0 Benin 35.4 36.1 32.1 32.1 32.2 .. .. .. .. 33.8 36.1 33.7 Botswana 14.7 4.9 2.5 2.0 1.8 1.8 2.1 1.9 3.1 8.7 4.2 2.2 Burkina Faso 29.4 28.8 35.6 32.9 34.1 33.3 .. .. .. 29.8 33.8 33.8 Burundi 62.2 55.9 40.1 40.1 34.8 .. .. .. .. 58.1 50.8 39.2 Cameroon 31.3 24.6 21.7 20.5 19.5 19.9 19.5 .. .. 25.7 24.3 20.9 Cape Verde .. 14.4 6.8 9.7 9.2 9.4 9.2 9.1 9.2 16.6 12.9 9.0 Central African Republic 40.0 47.6 59.7 55.3 54.4 55.0 53.9 52.9 55.5 44.3 48.4 54.9 Chad 45.1 29.3 33.6 23.5 12.3 11.7 12.5 13.6 .. 36.9 36.7 25.6 Comoros 34.0 41.4 50.5 50.9 51.0 45.2 45.3 45.8 46.3 36.3 40.2 48.4 Congo, Dem. Rep. 26.8 31.0 51.0 47.3 45.5 45.7 42.5 40.2 42.9 30.4 47.0 47.6 Congo, Rep. 11.7 12.9 6.3 5.5 4.5 4.0 4.4 3.7 4.5 10.0 10.5 5.0 Côte d’Ivoire 25.9 32.5 25.6 23.2 22.8 22.9 23.9 25.0 24.4 27.1 27.2 24.2 Djibouti .. 3.1 3.6 3.6 3.5 3.5 3.9 .. .. 3.3 3.4 3.6 Equatorial Guinea .. 61.5 5.5 4.1 2.6 2.8 2.7 2.0 3.5 65.8 41.5 4.6 Eritrea .. .. 14.7 13.9 22.6 24.6 24.3 14.4 14.4 .. 22.9 17.8 Ethiopia .. 54.3 41.9 44.2 46.7 47.9 46.2 43.8 50.7 56.5 58.4 46.2 Gabon 6.8 7.3 6.1 5.6 4.9 4.9 4.8 4.1 5.1 7.7 7.7 5.4 Gambia, The 30.8 29.0 31.1 33.7 32.1 30.3 28.7 28.5 27.5 34.0 28.7 31.1 Ghana 60.1 45.1 40.2 41.5 40.9 30.4 29.0 31.0 31.7 52.5 42.6 36.3 Guinea .. 23.8 22.3 25.1 24.2 23.8 25.3 24.9 17.2 24.0 20.1 22.8 Guinea-Bissau 44.3 60.8 .. .. .. .. .. .. .. 48.6 56.3 55.0 Kenya 32.6 29.5 29.0 28.0 27.2 26.7 20.1 21.0 22.6 32.4 30.8 26.8 Lesotho 24.6 24.9 10.2 10.1 8.6 9.8 8.2 7.8 8.4 24.7 19.3 9.9 Liberia 35.9 54.4 71.6 68.2 65.8 56.9 55.0 61.3 .. 35.8 67.2 66.6 Madagascar 30.1 28.6 29.2 28.8 28.3 27.5 25.7 24.8 29.1 34.3 28.6 28.2 Malawi 43.7 45.0 35.7 34.6 32.6 31.2 30.3 30.1 30.5 44.2 37.3 34.0 Mali 48.3 45.5 38.8 36.4 36.6 36.9 36.5 .. .. 44.4 46.7 37.4 Mauritania 30.4 29.6 27.5 25.6 23.7 14.6 18.8 18.9 20.6 30.4 33.9 23.0 Mauritius 13.1 12.9 6.3 6.4 6.0 5.6 4.9 4.4 4.3 14.9 10.2 5.8 Mozambique 37.1 37.1 28.0 27.4 27.0 27.9 27.7 30.5 31.5 39.7 34.7 27.4 Namibia 11.2 11.7 10.9 9.7 11.3 10.5 9.4 9.3 9.4 11.2 11.3 10.4 Niger 43.1 35.3 39.6 .. .. .. .. .. .. 38.6 39.4 39.3 Nigeria .. .. 42.7 34.2 32.8 32.0 32.7 .. .. .. .. 37.2 Rwanda 45.8 32.5 37.0 38.6 38.4 38.4 35.6 32.5 34.2 40.2 40.6 36.5 São Tomé and Príncipe .. .. 21.1 22.6 16.8 .. .. .. .. .. .. 20.0 Senegal 20.1 19.9 17.6 15.9 16.7 14.8 13.4 15.5 16.6 22.0 19.7 16.4 Seychelles 6.8 4.8 3.0 3.0 2.5 2.4 2.1 2.1 2.0 6.1 3.9 2.6 Sierra Leone 33.0 46.9 46.7 44.9 51.6 51.1 49.9 50.2 51.4 40.0 47.9 49.9 Somalia 68.4 65.5 .. .. .. .. .. .. .. 66.5 65.5 .. South Africa 6.2 4.6 3.4 3.1 2.7 2.9 3.4 3.2 3.0 5.5 4.1 3.3 Sudan 32.9 40.6 38.8 35.2 32.0 30.1 28.1 26.2 29.7 35.4 42.1 34.7 Swaziland 22.7 10.4 9.6 8.9 8.5 7.5 7.3 7.3 7.3 19.5 12.1 9.1 Tanzania .. 46.0 32.5 33.3 31.8 30.4 30.0 29.7 28.8 .. 44.5 31.5 Togo 27.5 33.8 40.8 41.2 43.7 .. .. .. .. 31.8 37.4 39.3 Uganda 72.0 56.6 26.1 22.9 26.7 25.6 23.6 22.7 24.7 57.6 47.9 25.6 Zambia 15.1 20.6 22.6 23.0 23.3 22.4 21.8 18.9 21.6 15.9 21.1 22.0 Zimbabwe 15.7 16.5 16.8 20.1 19.2 21.3 22.8 20.2 17.9 16.2 17.0 18.8 NORTH AFRICA 15.5 16.9 13.3 12.5 11.4 11.3 10.8 10.3 13.1 16.2 15.5 12.4 Algeria 8.5 11.4 10.5 10.2 8.2 8.0 8.0 6.9 11.7 9.9 11.2 9.3 Egypt, Arab Rep. 18.3 19.4 16.3 15.2 14.9 14.1 14.1 13.2 13.7 19.8 17.2 15.1 Libya .. .. 4.3 3.0 2.3 2.0 2.1 1.9 .. .. .. 3.0 Morocco 18.5 18.3 17.3 16.3 14.7 16.9 13.7 14.6 16.4 16.4 17.8 15.8 Tunisia 14.1 15.7 12.1 12.7 11.2 10.8 10.2 9.8 7.8 13.8 14.0 10.9 ALL AFRICA 17.2 18.0 16.4 15.1 14.4 13.9 13.5 11.6 13.1 17.4 17.1 14.6 a. Provisional. 38 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.30 Table Industry value added Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 36.9 32.1 29.9 30.9 31.7 32.0 31.9 31.7 29.6 34.2 29.6 30.6 Excluding South Africa 24.6 25.1 28.7 30.7 32.1 32.6 32.4 31.0 28.0 24.7 24.9 29.7 Excl. S. Africa & Nigeria 24.6 25.1 26.9 28.2 29.5 30.4 30.4 31.0 28.0 24.7 24.9 28.6 Angola .. 40.8 67.4 66.1 72.6 69.7 67.9 67.5 59.0 39.4 56.9 67.5 Benin 12.3 13.2 13.7 13.3 13.4 .. .. .. .. 14.0 13.7 13.7 Botswana 50.7 61.0 49.5 51.0 50.6 54.3 53.1 52.9 39.6 57.5 54.8 51.5 Burkina Faso 20.5 21.0 21.6 23.2 22.7 22.4 .. .. .. 21.0 21.1 22.1 Burundi 12.6 19.0 18.9 18.9 20.0 .. .. .. .. 15.1 18.7 19.0 Cameroon 25.6 29.5 30.7 30.7 30.4 31.4 30.6 .. .. 31.8 30.3 31.8 Cape Verde .. 21.4 19.7 15.2 16.8 17.4 17.8 18.8 20.1 19.0 19.7 17.5 Central African Republic 20.1 19.7 15.7 14.0 14.1 14.2 14.2 14.2 14.6 16.2 20.2 14.8 Chad 8.9 17.7 24.4 47.1 60.4 60.6 54.3 48.8 .. 13.5 13.7 37.3 Comoros 13.2 8.3 12.7 12.2 11.0 11.8 11.9 12.0 12.1 12.5 11.4 11.8 Congo, Dem. Rep. 35.0 29.0 21.5 24.5 26.9 27.7 28.4 28.0 24.0 30.1 20.6 24.3 Congo, Rep. 46.6 40.6 61.2 65.9 71.9 75.5 73.1 77.3 71.1 45.1 45.4 69.7 Côte d’Ivoire 19.7 23.2 21.6 23.1 25.9 25.9 25.3 26.1 25.2 20.8 22.2 24.5 Djibouti .. 22.0 16.2 16.6 16.6 16.4 16.9 .. .. 20.6 16.6 16.2 Equatorial Guinea .. 10.6 89.2 92.1 94.4 94.4 94.6 95.7 91.9 8.9 38.5 91.5 Eritrea .. .. 24.5 25.6 20.5 18.2 19.2 22.3 22.2 .. 18.4 22.0 Ethiopia .. 11.1 14.1 14.1 13.0 12.7 13.3 13.0 10.7 11.6 10.2 13.0 Gabon 60.4 43.0 52.0 55.3 61.4 61.2 60.3 64.3 53.8 53.7 48.2 56.7 Gambia, The 14.9 13.1 14.0 13.2 13.3 14.3 14.8 15.1 15.5 13.7 13.7 14.1 Ghana 12.3 16.9 27.8 27.1 27.5 20.8 20.7 20.4 18.9 13.8 24.5 24.8 Guinea .. 33.3 31.5 33.7 38.9 43.4 43.4 46.7 53.0 33.6 30.0 39.1 Guinea-Bissau 19.7 18.6 .. .. .. .. .. .. .. 15.7 12.5 13.0 Kenya 20.8 19.0 17.6 18.2 19.1 18.5 14.9 15.1 15.3 19.4 17.8 17.0 Lesotho 26.5 34.4 33.9 33.9 35.1 36.7 39.0 37.9 34.1 27.7 42.3 35.0 Liberia 28.1 16.8 10.6 13.4 15.7 17.1 18.9 16.8 .. 27.8 11.0 13.5 Madagascar 16.1 12.8 15.4 15.9 15.8 16.1 16.3 16.2 16.0 13.8 12.1 15.5 Malawi 22.5 28.9 19.4 17.4 17.0 17.0 16.3 16.1 16.1 22.7 22.7 17.2 Mali 13.2 15.9 23.6 23.9 24.2 24.0 24.2 .. .. 14.8 17.0 24.3 Mauritania 26.0 28.8 23.6 28.1 29.3 56.3 38.3 40.6 34.7 27.0 26.6 33.4 Mauritius 26.2 32.8 30.3 29.1 27.6 27.6 28.0 29.2 29.1 28.9 32.1 29.4 Mozambique 34.4 18.4 26.1 27.4 25.3 26.4 25.9 23.7 23.6 24.8 17.1 25.2 Namibia 55.8 38.0 28.3 29.4 29.2 34.6 35.6 37.8 32.7 44.2 30.6 31.9 Niger 22.9 16.2 17.1 .. .. .. .. .. .. 19.8 17.4 17.2 Nigeria .. .. 36.8 42.1 43.5 41.9 40.7 .. .. .. .. 39.2 Rwanda 21.5 24.6 12.3 13.9 14.1 13.8 13.9 14.9 14.5 21.0 19.5 13.9 São Tomé and Príncipe .. .. 17.8 21.0 20.5 .. .. .. .. .. .. 18.7 Senegal 20.1 22.2 24.3 24.9 23.8 23.0 23.6 21.7 21.7 20.7 23.5 23.6 Seychelles 15.6 16.3 27.4 28.2 21.9 20.5 20.2 20.2 19.7 16.5 21.5 24.5 Sierra Leone 21.9 19.2 24.7 24.2 23.6 23.2 24.3 23.5 22.1 15.9 32.4 24.4 Somalia 8.0 .. .. .. .. .. .. .. .. 8.0 .. .. South Africa 48.4 40.1 31.7 31.3 31.2 31.2 31.2 32.5 31.1 43.8 35.0 31.7 Sudan 14.1 15.3 22.0 25.8 28.3 29.2 31.2 34.0 26.0 15.2 13.5 25.8 Swaziland 30.2 43.2 47.9 46.7 45.6 48.5 49.4 49.4 49.4 32.3 43.5 47.6 Tanzania .. 17.7 22.5 22.3 22.7 22.9 23.3 23.1 24.3 .. 16.4 22.1 Togo 24.8 22.5 22.2 22.8 24.0 .. .. .. .. 22.0 21.0 20.4 Uganda 4.5 11.1 24.2 22.1 25.0 24.2 26.6 27.4 25.8 9.4 14.9 24.5 Zambia 42.1 51.3 26.5 27.8 31.6 35.3 38.5 41.4 34.1 45.5 39.2 31.2 Zimbabwe 29.0 33.1 21.6 27.1 29.6 33.9 34.9 32.4 29.0 30.2 30.6 27.7 NORTH AFRICA 40.3 34.3 43.0 43.0 44.8 46.3 45.0 46.6 39.3 36.3 35.9 42.4 Algeria 57.7 48.2 54.8 56.4 61.3 62.3 61.3 62.1 54.5 52.1 49.7 57.8 Egypt, Arab Rep. 36.8 28.7 35.2 36.5 35.9 38.4 36.3 37.5 37.3 30.6 31.8 35.8 Libya .. .. 75.1 68.6 75.5 78.5 76.4 78.2 .. .. .. 74.1 Morocco 31.0 33.4 27.9 28.5 28.2 27.2 27.3 30.3 28.5 33.2 32.0 28.2 Tunisia 31.1 29.8 28.3 28.2 28.9 29.2 29.1 32.1 30.0 31.5 28.8 29.3 ALL AFRICA 38.4 33.0 35.4 36.0 37.2 38.1 37.5 38.7 33.8 35.1 32.2 35.7 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 39 Table 2.31 Services plus discrepancy value added Share of GDP (%) Annual average 1980 1990 2003 2004 2005 2006 2007 2008 2009a 1980–89 1990–99 2000–09 SUB–SAHARAN AFRICA 44.6 49.2 51.4 52.0 51.8 52.1 52.8 55.6 57.3 47.5 52.1 53.2 Excluding South Africa 43.8 43.9 41.8 42.0 41.3 41.8 43.0 46.6 48.5 44.3 44.4 43.7 Excl. S. Africa & Nigeria 43.8 43.9 46.5 46.2 45.2 45.5 47.0 46.6 48.5 44.3 44.4 46.2 Angola .. 41.2 24.3 25.3 19.8 21.4 24.1 25.9 30.8 45.4 31.8 24.5 Benin 52.3 50.7 54.2 54.6 54.4 .. .. .. .. 52.2 50.2 52.6 Botswana 34.6 34.1 48.0 47.0 47.6 43.9 44.8 45.2 57.3 33.8 40.9 46.3 Burkina Faso 50.1 50.2 42.8 44.0 43.2 44.4 .. .. .. 49.2 45.1 44.1 Burundi 25.1 25.2 41.0 41.0 45.1 .. .. .. .. 26.8 30.5 41.7 Cameroon 43.1 46.0 47.6 48.9 50.1 48.8 49.9 .. .. 42.5 45.4 47.3 Cape Verde .. 64.3 73.4 75.1 74.0 73.2 73.0 72.1 70.7 64.4 67.4 73.6 Central African Republic 39.9 32.7 24.6 30.7 31.4 30.7 31.9 32.9 29.9 39.5 31.4 30.4 Chad 46.0 53.0 42.0 29.4 27.3 27.8 33.2 37.5 .. 49.6 49.6 37.1 Comoros 52.8 50.3 36.7 36.9 38.0 .. .. .. .. 51.2 48.4 38.0 Congo, Dem. Rep. 38.2 40.0 27.5 28.3 27.5 26.6 29.1 31.8 33.0 39.6 32.4 28.1 Congo, Rep. 41.7 46.5 32.6 28.6 23.6 20.5 22.6 19.0 24.4 44.9 44.1 25.3 Côte d’Ivoire 54.4 44.3 52.8 53.7 51.3 51.2 50.9 48.9 50.4 52.0 50.6 51.3 Djibouti .. 74.9 80.2 79.8 79.9 80.1 79.3 .. .. 76.1 80.0 80.2 Equatorial Guinea .. 27.8 5.3 3.8 3.0 2.9 2.8 2.3 4.7 25.2 20.0 3.8 Eritrea .. .. 60.8 60.5 56.9 57.2 56.5 63.3 63.4 .. 58.7 60.1 Ethiopia .. 34.5 44.0 41.8 40.3 39.4 40.5 43.2 38.6 31.9 31.4 40.8 Gabon 32.8 49.7 41.9 39.1 33.8 33.9 34.9 31.7 41.2 38.6 44.0 37.8 Gambia, The 54.3 57.9 54.9 53.1 54.6 55.5 56.5 56.4 57.1 52.3 57.6 54.8 Ghana 27.6 38.1 32.0 31.4 31.6 48.8 50.2 48.6 49.5 33.6 32.9 38.9 Guinea .. 42.9 46.3 41.3 36.9 32.8 31.3 28.4 29.8 42.3 49.9 38.1 Guinea-Bissau 36.1 20.6 .. .. .. .. .. .. .. 35.7 31.1 32.0 Kenya 46.6 51.4 53.4 53.7 53.7 54.8 65.0 63.9 62.1 48.2 51.5 56.2 Lesotho 48.9 40.7 55.9 56.0 56.3 53.5 52.8 54.3 57.5 47.6 38.4 55.1 Liberia 36.0 28.8 17.7 18.4 18.4 26.0 26.1 21.9 .. 36.4 21.8 19.8 Madagascar 53.9 58.6 55.4 55.3 55.9 56.4 58.1 59.0 54.9 51.9 59.3 56.3 Malawi 33.7 26.1 44.9 47.9 50.3 51.9 53.4 53.8 53.4 33.1 40.1 48.8 Mali 38.5 38.6 37.6 39.8 39.3 39.1 .. .. .. 40.8 36.4 38.1 Mauritania 43.6 41.6 48.9 46.3 47.0 29.1 42.9 40.6 44.8 42.6 39.4 43.6 Mauritius 60.7 54.4 63.4 64.4 66.4 66.9 67.1 66.4 66.6 56.2 57.7 64.8 Mozambique 28.5 44.5 45.9 45.2 47.7 45.7 46.4 45.9 44.9 35.6 48.2 47.4 Namibia 33.0 50.2 60.7 60.8 59.5 54.9 55.0 52.8 58.0 44.6 58.1 57.7 Niger 34.0 48.6 43.2 .. .. .. .. .. .. 41.6 43.2 43.5 Nigeria .. .. 20.5 23.7 23.7 26.1 26.6 .. .. .. .. 23.6 Rwanda 32.6 42.8 50.7 47.6 47.5 47.8 50.4 52.6 51.3 38.8 39.9 49.6 São Tomé and Príncipe .. .. 61.2 56.4 62.7 .. .. .. .. .. .. 61.3 Senegal 59.9 57.9 58.2 59.2 59.5 62.2 63.0 62.8 61.7 57.3 56.8 60.0 Seychelles 77.5 78.9 69.6 68.8 75.6 77.1 77.7 77.7 78.3 77.4 74.6 72.8 Sierra Leone 45.0 33.9 28.6 30.9 24.8 25.7 25.9 26.3 26.6 44.2 19.7 25.7 Somalia 23.6 .. .. .. .. .. .. .. .. 25.1 .. .. South Africa 45.4 55.3 64.9 65.6 66.2 66.0 65.5 64.3 65.8 50.8 60.9 65.1 Sudan 53.0 44.2 39.3 38.9 39.7 40.8 40.7 39.7 44.3 49.5 44.5 39.6 Swaziland 47.1 46.5 42.5 44.4 45.8 43.9 43.3 43.3 43.3 48.2 44.4 43.3 Tanzania .. 36.4 45.0 44.3 45.5 46.7 46.7 47.2 46.9 .. 39.1 46.4 Togo 47.7 43.7 37.1 36.0 32.4 .. .. .. .. 46.2 41.7 40.3 Uganda 23.5 32.4 49.7 55.0 48.3 50.2 49.8 49.9 49.5 33.0 37.2 49.8 Zambia 42.8 28.1 50.9 49.1 45.1 42.3 39.8 39.7 44.3 38.6 39.7 46.8 Zimbabwe 55.3 50.4 61.6 52.7 51.2 44.8 42.3 47.5 53.0 53.6 52.4 53.5 NORTH AFRICA 44.2 48.8 43.7 44.5 43.8 42.4 44.2 43.1 47.7 47.5 48.6 45.2 Algeria 33.8 40.5 34.7 33.5 30.5 29.7 30.7 31.0 33.7 38.0 39.1 32.9 Egypt, Arab Rep. 45.0 52.0 48.4 48.3 49.2 47.5 49.6 49.2 49.0 49.7 51.0 49.1 Libya .. .. 20.6 28.4 22.2 19.5 21.5 19.9 .. .. .. 23.0 Morocco 50.5 48.3 54.8 55.2 57.1 56.0 59.0 55.0 55.1 50.4 50.2 56.0 Tunisia 54.8 54.5 59.7 59.1 59.9 60.1 60.7 58.1 62.3 54.8 57.3 59.9 ALL AFRICA 44.4 49.1 48.2 48.8 48.4 48.0 49.1 49.8 53.1 47.5 50.7 49.8 a. Provisional. 40 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.32 Table Central government �nances, expense, and revenue Finances Share of GDP (%) Revenue, excluding grants Expense Cash surplus or deficit 1990 2000 2009 1990 2000 2009 1990 2000 2009 SUB–SAHARAN AFRICA .. .. .. .. .. .. .. .. .. Excluding South Africa .. .. .. .. .. .. .. .. .. Excl. S. Africa & Nigeria .. .. .. .. .. .. .. .. .. Angola .. .. .. .. .. .. .. .. .. Benina .. .. 17.6 .. .. 15.0 .. .. –4.5 Botswanaa 50.8 .. .. 26.7 .. .. 19.1 .. .. Burkina Faso .. .. 14.0 .. .. 13.0 .. .. –4.8 Burundia .. .. .. .. .. .. .. .. .. Cameroona 14.3 .. .. 14.6 .. .. –5.6 .. .. Cape Verde .. .. 28.7 .. .. 28.2 .. .. –3.8 Central African Republic .. .. .. .. .. .. .. .. .. Chad .. .. .. .. .. .. .. .. .. Comoros .. .. .. .. .. .. .. .. .. Congo, Dem. Rep.a 10.1 3.7 .. 16.7 8.6 .. –6.5 –4.0 .. Congo, Rep. .. 28.6 .. .. 19.9 .. .. 1.9 .. Côte d’Ivoirea .. .. 18.7 .. .. 17.6 .. .. 0.9 Djibouti .. .. .. .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. .. .. .. Ethiopia a 12.4 .. .. 16.2 .. .. –6.6 .. .. Gabon .. .. .. .. .. .. .. .. .. Gambia, Thea 19.4 .. .. 17.2 .. .. 2.1 .. .. Ghanaa 12.5 .. 15.3 .. .. 17.9 .. .. –5.6 Guineaa .. .. .. .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. .. .. .. Kenya .. 19.7 20.5 .. 16.8 21.7 .. 2.0 –5.5 Lesotho 44.9 50.7 .. 33.6 .. .. –0.6 .. .. Liberia .. .. .. .. .. .. .. .. .. Madagascar .. 11.7 .. .. 10.6 .. .. –2.0 .. Malawi .. .. .. .. .. .. .. .. .. Mali .. 13.4 17.1 .. 11.6 14.6 .. –3.4 –2.1 Mauritania .. .. .. .. .. .. .. .. .. Mauritius .. .. 23.5 .. .. 21.6 .. .. 0.6 Mozambique .. .. .. .. .. .. .. .. .. Namibia 31.3 30.1 .. .. 28.5 .. .. –1.6 .. Niger .. .. .. .. .. .. .. .. .. Nigeria .. .. .. .. .. .. .. .. .. Rwanda a 10.8 .. .. 12.7 .. .. –5.4 .. .. São Tomé and Príncipe .. .. .. .. .. .. .. .. .. Senegal .. 16.9 .. .. 12.8 .. .. –0.9 .. Seychelles .. 38.7 36.6 .. 43.1 32.7 .. –13.9 4.3 Sierra Leonea 5.6 11.4 11.6 .. 28.7 22.5 .. –9.3 –3.1 Somalia .. .. .. .. .. .. .. .. .. South Africa .. 26.3 28.2 .. 27.9 33.0 .. –2.0 –4.9 Sudana .. .. .. .. .. .. .. .. .. Swazilanda .. 26.2 .. .. 22.6 .. .. –0.8 .. Tanzania .. .. .. .. .. .. .. .. .. Togoa .. .. 18.8 .. .. 17.4 .. .. –0.6 Ugandaa .. 10.8 12.4 .. 15.5 13.7 .. –1.9 –0.9 Zambiaa 20.4 .. .. .. .. .. .. .. .. Zimbabwea 24.1 .. .. 24.5 .. .. –2.6 .. .. NORTH AFRICA Algeriaa .. .. 36.6 .. .. 25.0 .. .. –4.4 Egypt, Arab Rep.a 23.0 .. 27.0 24.0 .. 30.2 –2.0 .. –6.6 Libya .. .. .. .. .. .. .. .. .. Morocco .. .. 33.1 .. .. 27.9 .. .. 1.0 Tunisiaa 30.7 29.2 31.4 30.4 27.6 29.9 –3.2 –2.7 –1.7 ALL AFRICA (continued) National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 41 Table 2.32 Central government �nances, expense, and revenue (continued) Finances Share of GDP (%) Net incurrance of liabilities Domestic Foreign Total debt 1990 2000 2009 1990 2000 2009 1990 2000 2009 SUB–SAHARAN AFRICA .. .. .. .. .. .. .. .. .. Excluding South Africa .. .. .. .. .. .. 5.8 4.6 1.5 Excl. S. Africa & Nigeria .. .. .. .. .. .. 4.7 4.8 2.0 Angola .. .. .. .. .. .. 3.2 18.7 4.6 Benina .. .. 2.2 .. .. 2.1 2.0 3.3 0.6 Botswanaa –0.8 .. .. 0.0 .. .. 2.8 1.2 0.4 Burkina Faso .. .. 4.5 .. .. 2.9 1.1 1.8 0.5 Burundia .. .. .. .. .. .. 3.7 3.1 1.5 Cameroona .. .. .. 5.2 .. .. 4.6 5.5 1.8 Cape Verde .. .. 4.2 .. .. 5.1 1.7 3.0 2.1 Central African Republic .. .. .. .. .. .. 2.0 1.5 1.6 Chad .. .. .. .. .. .. 0.7 1.8 1.1 Comoros .. .. .. .. .. .. 0.4 1.6 2.2 Congo, Dem. Rep.a 6.5 .. .. .. .. .. 3.7 0.6 6.6 Congo, Rep. .. .. .. .. .. .. 18.6 1.4 1.7 Côte d’Ivoirea .. .. .. .. .. .. 11.7 9.8 4.7 Djibouti .. .. .. .. .. .. 2.4 2.4 2.8 Equatorial Guinea .. .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. .. 0.5 1.2 Ethiopiaa 5.1 .. .. 2.0 .. .. 2.0 1.7 0.4 Gabon .. .. .. .. .. .. 3.0 6.9 4.2 Gambia, Thea .. .. .. .. .. .. 11.9 5.1 3.5 Ghanaa .. .. 2.8 .. .. 2.6 6.2 7.8 0.9 Guineaa .. .. .. .. .. .. 6.3 5.0 3.1 Guinea-Bissau .. .. .. .. .. .. 3.5 2.4 1.2 Kenya .. .. 3.0 .. .. .. 9.2 4.7 1.3 Lesotho –7.9 .. .. 9.1 .. .. 4.3 8.2 2.4 Liberia .. .. .. .. .. .. 0.8 0.1 7.3 Madagascar .. 1.3 .. .. 1.7 .. 7.2 3.0 0.5 Malawi .. .. .. .. .. .. 7.1 3.6 0.8 Mali .. –1.0 –4.4 .. 3.0 2.6 2.8 3.8 0.9 Mauritania .. .. .. .. .. .. 14.3 7.7 2.6 Mauritius .. .. 3.1 .. .. 1.3 5.7 9.9 1.5 Mozambique .. .. .. .. .. .. 3.2 2.3 0.4 Namibia .. 1.0 .. .. 0.7 .. .. .. .. Niger .. .. .. .. .. .. 4.0 1.4 0.8 Nigeria .. .. .. .. .. .. 11.7 4.0 0.3 Rwanda a 3.3 .. .. .. .. .. 0.8 2.1 0.5 São Tomé and Príncipe .. .. .. .. .. .. .. .. 1.8 Senegal .. 0.3 .. .. 0.5 .. 5.7 4.8 1.6 Seychelles .. 0.7 –6.0 .. 13.1 –2.7 5.8 3.4 8.2 Sierra Leonea .. .. .. .. .. .. 3.3 7.3 0.4 Somalia .. .. .. .. .. .. 1.2 .. .. South Africa .. 1.6 7.0 .. 0.3 1.0 .. 2.9 2.7 Sudana .. .. .. .. .. .. 0.4 2.0 0.9 Swazilanda .. .. .. .. .. .. 4.0 2.1 1.5 Tanzania .. .. .. .. .. .. 4.2 1.6 0.8 Togoa .. .. 2.7 .. .. –0.5 5.3 2.2 1.9 Ugandaa .. 0.6 1.5 .. 2.0 1.8 3.4 1.2 0.4 Zambiaa 6.8 .. .. 1.0 .. .. 6.1 5.7 1.3 Zimbabwea .. .. .. .. .. .. 5.4 6.4 1.8 NORTH AFRICA Algeriaa .. .. 5.9 .. .. 0.0 14.2 8.2 0.7 Egypt, Arab Rep.a .. .. 9.9 .. .. –0.2 7.1 1.8 1.6 Libya .. .. .. .. .. .. .. .. .. Morocco .. .. 0.1 .. .. 1.7 6.9 7.3 3.7 Tunisia a 3.6 0.6 0.3 1.8 –0.2 0.0 11.6 9.8 5.3 ALL AFRICA 42 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts Expense Share of expense (%) Goods and services Compensation of employees Interest payments Subsidies and other transfers Other expenses 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 17.7 .. .. 47.2 .. .. 3.3 .. .. 29.7 .. .. 2.1 35.2 .. .. 29.1 .. .. 2.8 .. .. 31.8 .. .. 1.1 .. .. .. .. 19.1 .. .. 45.8 .. .. 3.4 .. .. 11.1 .. .. 20.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 16.7 .. .. 55.6 .. .. 7.8 .. .. 13.3 .. .. .. .. .. .. .. 16.3 .. .. 43.3 .. .. 5.3 .. .. 30.1 .. .. 4.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 56.3 59.4 .. 25.4 27.4 .. 7.4 .. .. .. 13.2 .. .. .. .. .. 25.6 .. .. 27.8 .. .. 35.2 .. .. 10.9 .. .. 0.5 .. .. .. 29.5 .. .. 38.4 .. .. 8.7 .. .. 16.3 .. .. 7.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 43.1 .. .. 48.1 .. .. 5.6 .. .. 11.2 .. .. 0.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 28.3 .. .. 28.7 .. .. 21.4 .. .. 12.2 .. .. 9.4 .. .. .. .. 16.5 .. .. 39.9 .. .. 15.6 .. .. 27.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 21.3 20.2 .. 55.2 37.3 .. 17.8 10.3 .. 3.4 31.3 .. 2.2 0.9 30.8 .. .. 38.6 .. .. 18.7 .. .. 8.9 .. .. 2.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 17.7 .. .. 40.7 .. .. 13.4 .. .. 9.7 .. .. 18.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 37.6 30.6 .. 36.5 34.4 .. 8.0 2.5 .. 0.4 15.0 .. 17.5 17.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 11.7 .. .. 33.7 .. .. 13.6 .. .. 31.0 .. .. 10.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 20.8 .. .. 51.2 .. .. 6.6 .. .. 10.4 .. .. 11.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 35.3 .. .. 43.5 .. .. 7.9 .. .. 15.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 26.0 .. .. 41.4 .. .. 10.7 .. .. 18.7 .. .. .. .. .. 24.6 37.2 .. 36.3 26.8 .. 17.3 20.1 .. 21.6 15.8 .. .. 0.1 .. 14.9 24.3 .. 23.4 27.6 .. 21.9 7.1 .. 5.5 22.6 .. 34.3 18.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 11.3 12.9 .. 15.6 13.4 .. 18.1 7.2 .. 52.9 62.9 .. 2.2 4.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 26.1 .. .. 44.6 .. .. 2.3 .. .. 27.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 24.1 .. .. 40.3 .. .. 5.5 .. .. 17.6 .. .. 12.5 .. 55.1 31.2 .. 12.3 14.2 .. 5.2 8.6 .. 27.4 44.7 .. .. 1.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 21.7 .. .. 40.9 .. .. 17.8 .. .. .. .. .. .. .. .. .. .. 11.3 .. .. 33.7 .. .. 1.4 .. .. 45.4 .. .. 8.3 22.4 .. 8.0 26.6 .. 24.6 16.3 .. 14.0 .. .. 44.7 .. .. 8.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 8.9 .. .. 47.8 .. .. 3.7 .. .. 26.6 .. .. 12.9 7.0 8.6 6.6 31.4 39.8 35.8 10.9 12.1 7.4 44.9 .. 37.7 5.8 .. 12.5 (continued) National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 43 Table 2.32 Central government �nances, expense, and revenue (continued) Revenue Share of revenue (%) Taxes on income, Interest profits, and Taxes on goods Taxes on Other Social Grants and payments capital gains and services international trade taxes contributions other revenue 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 SUB–SAHARAN AFRICA .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Excluding South Africa .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Excl. S. Africa & Nigeria .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Angola .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Benin .. .. 18.4 .. .. 17.0 .. .. 38.8 .. .. 18.4 .. .. 5.9 .. .. 2.4 .. .. 17.5 Botswana 12.9 .. .. 37.6 .. .. 1.8 .. .. 12.9 .. .. 0.1 .. .. .. .. .. 47.6 .. .. Burkina Faso .. .. 11.6 .. .. 13.8 .. .. 36.7 .. .. 11.6 .. .. 2.0 .. .. .. .. .. 35.9 Burundi .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Cameroon 15.5 .. .. 18.9 .. .. 22.2 .. .. 15.5 .. .. 4.6 .. .. 1.8 .. .. 27.5 .. .. Cape Verde .. .. 12.0 .. .. 18.2 .. .. 27.6 .. .. 12.0 .. .. 0.1 .. .. 10.1 .. .. 32.0 Central African Republic .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Chad .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Comoros .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 37.8 16.4 .. 21.9 8.4 .. 15.1 15.8 .. 37.8 16.4 .. 1.1 25.7 .. 1.0 .. .. 23.1 33.7 .. Congo, Rep. .. 5.0 .. .. .. .. .. 15.5 .. .. 5.0 .. .. 0.0 .. .. 3.1 .. .. 76.4 .. Côte d’Ivoire .. .. 32.5 .. .. 15.3 .. .. 20.3 .. .. 32.5 .. .. 7.9 .. .. 6.4 .. .. 17.6 Djibouti .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Ethiopia 14.3 .. .. 28.2 .. .. 24.3 .. .. 14.3 .. .. 2.2 .. .. 1.9 .. .. 29.1 .. .. Gabon .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Gambia, The 32.4 .. .. 9.7 .. .. 28.3 .. .. 32.4 .. .. 0.4 .. .. 0.2 .. .. 28.9 .. .. Ghana 34.7 .. 15.9 20.6 .. 22.6 26.8 .. 29.3 34.7 .. 15.9 .. .. .. .. .. .. 10.4 .. 32.1 Guinea .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Kenya .. 15.0 10.1 .. 28.5 40.0 .. 41.4 40.6 .. 15.0 10.1 .. 0.5 1.0 .. 0.0 .. .. 14.7 8.2 Lesotho 43.6 41.4 .. 8.7 17.2 .. 16.0 12.5 .. 43.6 41.4 .. 0.1 .. .. .. .. .. 31.6 28.9 .. Liberia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Madagascar .. 39.6 .. .. 11.6 .. .. 21.5 .. .. 39.6 .. .. 1.2 .. .. .. .. .. 26.0 .. Malawi .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Mali .. 11.3 9.9 .. 12.5 19.5 .. 41.6 29.2 .. 11.3 9.9 .. 5.0 10.0 .. .. .. .. 29.5 31.4 Mauritania .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Mauritius .. .. 2.2 .. .. 22.8 .. .. 46.3 .. .. 2.2 .. .. 7.1 .. .. 4.1 .. .. 17.4 Mozambique .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Namibia 25.3 35.1 .. 32.6 31.8 .. 23.9 22.7 .. 25.3 35.1 .. 0.9 1.4 .. .. 0.5 .. 17.2 8.5 .. Niger .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Nigeria .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Rwanda 20.5 .. .. 14.0 .. .. 27.1 .. .. 20.5 .. .. 3.1 .. .. 5.4 .. .. 30.0 .. .. São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Senegal .. 29.5 .. .. 21.3 .. .. 33.7 .. .. 29.5 .. .. 3.3 .. .. .. .. .. 12.2 .. Seychelles .. 41.0 10.8 .. 17.3 19.2 .. 5.1 39.7 .. 41.0 10.8 .. 1.6 .. .. 13.8 9.0 .. 21.3 21.3 Sierra Leone 38.1 29.4 14.4 29.7 15.4 16.9 22.1 7.6 24.6 38.1 29.4 14.4 0.2 .. .. .. .. .. 9.9 47.7 44.1 Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa .. 3.0 2.7 .. 51.7 52.6 .. 33.1 31.8 .. 3.0 2.7 .. 2.8 2.4 .. 2.1 2.2 .. 7.4 8.2 Sudan .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Swaziland .. 49.9 .. .. 24.1 .. .. 13.2 .. .. 49.9 .. .. 4.1 .. .. .. .. .. 8.7 .. Tanzania .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Togo .. .. 18.3 .. .. 16.7 .. .. 34.3 .. .. 18.3 .. .. 2.8 .. .. .. .. .. 28.0 Uganda .. 21.8 9.6 .. 9.9 22.0 .. 29.4 46.8 .. 21.8 9.6 .. 0.1 .. .. .. .. .. 38.7 21.6 Zambia 17.2 .. .. 39.5 .. .. 37.4 .. .. 17.2 .. .. 0.2 .. .. 0.0 .. .. 5.8 .. .. Zimbabwe 17.1 .. .. 43.7 .. .. 25.6 .. .. 17.1 .. .. 1.1 .. .. 3.3 .. .. 9.2 .. .. NORTH AFRICA Algeria .. .. 4.5 .. .. 59.7 .. .. 28.0 .. .. 4.5 .. .. 1.5 .. .. .. .. .. 6.3 Egypt, Arab Rep. 12.9 .. 4.9 18.1 .. 27.8 12.8 .. 21.7 12.9 .. 4.9 10.2 .. 2.2 14.5 .. .. 31.5 .. 43.4 Libya .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco .. .. 6.0 .. .. 28.4 .. .. 31.4 .. .. 6.0 .. .. 5.4 .. .. 12.1 .. .. 16.7 Tunisia 27.5 10.7 5.8 12.3 20.4 27.4 19.1 37.1 31.3 27.5 10.7 5.8 4.8 4.4 4.4 13.0 17.0 19.1 23.4 10.5 11.9 ALL AFRICA a. Data were reported on a cash basis and have been adjusted to the accrual framework. 44 Part I. Basic indicators and national and fiscal accounts National and fiscal accounts 2.33 Table Structure of demand Share of GDP (%) Household final General government consumption final consumption Gross fixed capital Exports of goods Imports of goods Gross national expenditure expenditure formation and services and services savings 1990 2000 2009a 1990 2000 2009a 1990 2000 2009a 1990 2000 2009a 1990 2000 2009a 1990 2000 2009a SUB–SAHARAN AFRICA 65.3 68.5 66.9 17.5 15.7 17.6 18.2 16.3 22.3 26.4 32.4 29.8 25.6 30.8 33.5 15.8 15.5 15.4 Excluding South Africa 72.5 73.5 .. 15.6 13.4 .. 17.4 17.4 22.0 28.0 35.7 31.7 30.5 35.1 37.6 12.8 15.2 .. Excl. S. Africa & Nigeria 72.5 73.5 74.0 15.6 13.4 13.9 17.4 17.4 22.0 24.6 31.7 30.7 30.8 35.8 40.1 12.8 15.2 .. Angola 35.8 .. .. 34.5 .. .. 11.1 15.1 14.8 38.9 89.6 52.2 20.9 62.8 46.2 9.0 23.8 9.7 Benin 86.8 82.4 .. 11.0 11.6 .. 13.4 18.9 25.0 14.3 15.2 13.8 26.3 28.1 28.2 5.3 10.4 .. Botswana 33.2 30.8 62.8 24.1 25.4 24.2 32.4 25.8 28.2 55.1 53.3 33.6 49.8 41.2 44.6 41.6 41.4 16.4 Burkina Faso 73.5 78.5 .. 21.1 20.8 .. 17.7 18.7 .. 11.0 9.1 .. 24.5 25.2 .. 15.9 5.1 .. Burundi 94.5 88.5 .. 10.8 17.5 .. 15.2 6.1 .. 7.9 7.8 .. 27.8 19.9 .. 8.7 4.4 .. Cameroon 66.6 70.2 .. 12.8 9.5 .. 17.3 16.0 .. 20.2 23.3 26.6 17.3 19.7 30.9 16.2 15.3 .. Cape Verde 93.4 92.9 67.2 14.7 21.3 20.8 22.9 19.7 53.8 12.7 27.5 23.6 43.7 61.4 65.4 17.8 9.0 31.3 Central African Republic 85.7 80.8 92.9 14.9 14.0 4.5 11.4 9.5 10.6 14.8 19.8 14.5 27.6 24.1 22.4 6.2 .. .. Chad 97.6 86.8 78.5 10.0 7.7 15.6 4.8 20.9 32.7 13.5 16.9 42.1 27.9 34.7 70.1 2.3 .. .. Comoros 78.7 94.0 105.8 24.5 11.7 15.3 11.9 10.1 12.4 14.3 16.7 14.7 37.1 32.5 48.2 14.4 .. .. Congo, Dem. Rep. 79.1 88.0 74.4 11.5 7.5 7.9 12.8 3.5 29.8 29.5 22.4 9.6 29.2 21.4 21.7 .. .. .. Congo, Rep. 62.4 29.1 42.2 13.8 11.6 12.2 17.2 20.9 24.3 53.7 80.3 71.9 45.8 43.6 50.9 6.9 30.6 .. Côte d’Ivoire 71.9 74.9 72.2 16.8 7.2 8.6 8.5 11.2 11.2 31.7 40.4 41.7 27.1 33.3 33.8 –5.1 8.0 14.8 Djibouti 78.9 76.8 .. 31.5 29.7 .. 14.1 8.8 .. 53.8 35.1 .. 78.4 50.4 .. .. 5.4 .. Equatorial Guinea 80.3 20.9 24.3 39.7 4.6 3.4 17.4 61.3 36.6 32.2 98.6 74.1 69.6 85.4 41.6 2.1 .. .. Eritrea .. 79.1 .. .. 63.8 .. .. 23.8 .. .. 15.1 4.5 .. 81.8 20.3 .. 4.4 .. Ethiopia 77.2 73.8 87.7 13.2 17.9 8.2 12.9 20.3 22.4 5.6 12.0 10.6 8.8 24.0 28.8 12.8 15.9 16.1 Gabon 49.7 32.2 41.1 13.4 9.6 11.6 21.4 21.9 28.4 46.0 69.0 52.2 30.9 32.7 33.3 24.3 41.7 .. Gambia, The 75.6 77.8 77.8 13.7 13.7 15.9 22.3 17.4 .. 59.9 48.0 30.4 71.6 56.8 50.1 21.9 .. 18.8 Ghana 85.2 84.3 81.7 9.3 10.2 9.6 14.4 23.1 19.6 16.9 48.8 30.5 25.9 67.2 41.3 10.5 15.3 15.5 Guinea 66.9 77.7 75.2 11.0 6.8 8.0 22.9 18.9 21.6 31.1 23.6 40.7 33.4 27.9 45.4 19.2 15.4 7.7 Guinea-Bissau 86.9 94.6 .. 10.3 14.0 .. 29.9 11.3 .. 9.9 31.8 .. 37.0 51.6 .. 14.5 .. .. Kenya 62.8 77.7 75.9 18.6 15.1 16.3 20.6 16.7 20.1 25.7 21.6 25.2 31.3 31.7 38.3 18.5 13.5 15.4 Lesotho 123.3 83.3 78.8 25.8 41.7 50.4 57.0 42.5 31.5 18.1 34.2 51.2 123.2 103.4 111.7 70.5 24.1 28.1 Liberia .. .. .. .. .. .. .. .. .. .. 21.5 .. .. 26.0 .. .. .. .. Madagascar 86.4 83.2 79.7 8.0 9.0 11.5 14.8 15.0 32.6 16.6 30.7 28.5 28.0 38.0 52.2 9.1 8.8 .. Malawi 71.5 81.6 61.9 15.1 14.6 20.9 20.1 12.3 21.8 23.8 25.6 30.0 33.4 35.3 37.7 16.4 9.5 .. Mali 79.8 79.4 .. 13.8 8.6 .. 23.0 24.6 .. 17.1 26.8 .. 33.7 39.4 .. 15.0 15.9 .. Mauritania 69.2 82.8 72.1 25.9 25.8 20.6 20.0 19.4 25.2 45.6 46.2 49.7 60.7 74.2 67.6 18.8 .. .. Mauritius 63.4 60.3 74.6 13.6 14.1 14.6 30.6 22.9 26.2 65.0 61.4 48.4 72.2 61.9 59.1 25.8 26.3 16.7 Mozambique 92.3 80.6 84.4 13.5 9.0 13.4 22.1 31.0 21.0 8.2 16.5 25.1 36.1 37.0 43.8 6.6 10.4 9.1 Namibia 51.2 63.1 61.9 30.6 23.5 24.2 21.2 16.6 24.7 51.9 40.9 46.6 67.4 44.5 59.9 34.8 25.4 26.5 Niger 83.8 83.4 .. 15.0 13.0 .. 11.4 11.2 .. 15.0 17.8 .. 22.0 25.7 .. –0.6 5.3 .. Nigeria .. .. .. .. .. .. .. .. .. 43.4 54.0 35.9 28.8 32.0 27.2 .. .. .. Rwanda 83.7 87.7 81.1 10.1 11.0 14.6 14.6 18.3 21.8 5.6 8.7 11.7 14.1 25.7 29.2 11.3 12.9 15.1 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Senegal 79.2 76.0 83.3 18.4 12.8 8.7 18.0 22.4 27.9 25.4 27.9 24.0 32.2 37.2 44.0 1.6 13.8 .. Seychelles 52.0 53.9 71.9 27.7 24.2 12.2 23.0 25.2 24.2 62.5 78.2 119.3 66.7 81.4 127.6 21.7 18.5 9.2 Sierra Leone 83.5 100.0 84.0 7.8 14.3 13.8 9.6 6.9 15.1 22.4 18.1 15.7 23.8 39.3 28.5 –1.0 –3.7 7.8 Somalia .. .. .. .. .. .. 14.9 .. .. 9.8 .. .. 37.7 .. .. .. .. .. South Africa 57.1 63.0 60.4 19.7 18.1 21.0 19.1 15.1 22.6 24.2 27.9 27.3 18.8 24.9 28.1 19.1 15.8 15.4 Sudan 86.1 76.5 66.7 5.8 7.6 13.9 10.4 12.1 21.8 4.0 15.3 15.1 7.1 17.7 20.8 1.2 9.3 12.2 Swaziland 80.4 78.0 72.8 14.3 18.7 27.0 14.5 17.4 16.9 59.0 76.1 59.8 68.9 90.1 76.5 19.7 12.4 2.4 Tanzania 80.9 78.3 62.3 17.8 11.7 19.8 25.8 16.4 29.3 12.6 13.4 23.2 37.5 20.1 35.2 10.1 12.7 21.2 Togo 71.1 92.0 .. 14.2 10.2 .. 25.3 17.8 .. 33.5 30.7 .. 45.3 50.7 .. 21.0 0.8 .. Uganda 91.9 77.5 76.1 7.5 14.5 11.4 12.7 19.2 23.5 7.2 10.7 23.4 19.4 22.1 34.6 5.6 14.4 17.5 Zambia 64.4 87.4 61.3 19.0 9.5 13.1 13.5 16.0 22.1 35.9 27.1 35.6 36.6 41.5 32.2 19.6 –1.4 19.0 Zimbabwe 63.1 59.9 113.1 19.4 24.3 13.8 18.2 11.8 2.5 22.9 38.6 36.3 22.8 36.4 65.4 15.6 .. .. NORTH AFRICA 64.1 61.1 62.9 15.1 14.4 13.3 24.5 20.2 25.1 26.4 28.3 32.1 32.3 25.3 36.6 27.6 .. .. Algeria 56.8 41.6 40.6 16.1 13.6 13.9 27.0 20.7 33.0 23.4 41.2 40.4 24.9 21.4 36.1 24.3 .. .. Egypt, Arab Rep. 72.6 75.9 76.2 11.3 11.2 11.4 26.9 18.9 19.0 20.0 16.2 25.0 32.7 22.8 31.9 31.1 18.0 16.7 Libya 48.4 45.7 .. 24.4 20.8 .. 13.9 13.1 .. 39.7 35.6 .. 31.1 15.5 .. .. .. .. Morocco 64.6 61.4 57.0 15.5 18.4 18.0 24.0 26.0 30.7 26.5 28.0 28.6 31.9 33.4 39.5 25.1 24.3 31.2 Tunisia 63.6 60.7 63.4 16.4 15.6 13.1 24.4 26.0 25.9 43.6 44.5 52.0 50.6 48.2 55.3 23.4 23.2 22.8 ALL AFRICA 64.7 65.1 65.2 16.4 15.1 15.7 21.1 18.1 23.5 26.4 30.7 30.7 28.4 28.5 34.7 20.8 17.2 17.6 a. Provisional. National and fiscal accounts Part I. Basic indicators and national and fiscal accounts 45 Table 3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger International poverty linea Share of population Poverty gap ratio Share of population Poverty gap ratio below PPP $1.25 a day at PPP $1.25 a day below PPP $2 a day at PPP $2 a day Surveys Surveys Surveys Surveys Surveys Surveys Surveys Surveys 1990–99c 2000–09c 1990–99c 2000–09c 1990–99c 2000–09c 1990–99c 2000–09c Year Percent Year Percent Year Percent Year Percent Year Percent Year Percent Year Percent Year Percent SUB–SAHARAN AFRICA Angola .. .. 2000 54.3 .. .. 2000 29.9 .. .. 2000 70.2 .. .. 2000 42.4 Benin .. .. 2003 47.3 .. .. 2003 15.7 .. .. 2003 75.3 .. .. 2003 33.5 Botswana 1994 31.2 .. .. 1994 11.0 .. .. 1994 49.4 .. .. 1994 22.3 .. .. Burkina Faso 1998 70.0 2003 56.5 1998 30.2 2003 20.3 1998 87.6 2003 81.2 1998 49.1 2003 39.3 Burundi 1998 86.4 2006 81.3 1998 47.3 2006 36.4 1998 95.4 2006 93.5 1998 64.1 2006 56.1 Cameroon 1996 51.5 2007 9.6 1996 18.9 2007 1.2 1996 74.5 2007 30.4 1996 36.0 2007 8.2 Cape Verde .. .. 2002 21.0 .. .. 2002 6.1 .. .. 2002 40.9 .. .. 2002 15.2 Central African Republic 1992 83.2 2008 62.8 1992 57.4 2008 31.3 1992 91.0 2008 80.1 1992 68.8 2008 46.8 Chad .. .. 2003 61.9 .. .. 2003 25.6 .. .. 2003 83.3 .. .. 2003 43.9 Comoros .. .. 2004 46.1 .. .. 2004 20.8 .. .. 2004 65.0 .. .. 2004 34.2 Congo, Dem. Rep. .. .. 2006 59.2 .. .. 2006 25.3 .. .. 2006 79.6 .. .. 2006 42.4 Congo, Rep. .. .. 2005 54.1 .. .. 2005 22.8 .. .. 2005 74.4 .. .. 2005 38.8 Côte d’Ivoire 1998 24.1 2008 23.8 1998 6.7 2008 7.5 1998 49.2 2008 46.3 1998 18.2 2008 17.8 Djibouti 1996 4.8 2002 18.8 1996 1.6 2002 5.3 1996 15.1 2002 41.2 1996 4.5 2002 14.6 Equatorial Guinea .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Ethiopia 1995 60.5 2005 39.0 1995 21.2 2005 9.6 1995 84.6 2005 77.6 1995 41.2 2005 28.9 Gabon .. .. 2005 4.8 .. .. 2005 0.9 .. .. 2005 19.6 .. .. 2005 5.0 Gambia, The 1998 66.7 2003 34.3 1998 34.7 2003 12.1 1998 82.0 2003 56.7 1998 50.0 2003 24.9 Ghana 1998 39.1 2006 30.0 1998 14.4 2006 10.5 1998 63.3 2006 53.6 1998 28.5 2006 22.3 Guinea 1994 36.8 2007 43.3 1994 11.5 2007 15.0 1994 63.8 2007 69.6 1994 26.5 2007 31.0 Guinea-Bissau 1993 52.1 2002 48.8 1993 20.6 2002 16.5 1993 75.7 2002 77.9 1993 37.4 2002 34.8 Kenya 1997 19.6 2005 19.7 1997 4.6 2005 6.1 1997 42.7 2005 39.9 1997 14.7 2005 15.1 Lesotho 1994 46.2 2003 43.4 1994 25.6 2003 20.8 1994 59.7 2003 62.3 1994 36.1 2003 33.1 Liberia .. .. 2007 83.7 .. .. 2007 40.8 .. .. 2007 94.8 .. .. 2007 59.5 Madagascar 1999 82.3 2005 67.8 1999 44.3 2005 26.5 1999 93.1 2005 89.6 1999 61.0 2005 46.9 Malawi 1998 83.1 2004 73.9 1998 46.0 2004 32.3 1998 93.5 2004 90.5 1998 62.3 2004 51.8 Mali 1994 86.1 2006 51.4 1994 53.1 2006 18.8 1994 93.9 2006 77.1 1994 67.2 2006 36.5 Mauritania 1996 23.4 2000 21.2 1996 7.1 2000 5.7 1996 48.3 2000 44.1 1996 17.8 2000 15.9 Mauritius .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Mozambique 1997 81.3 2008 60.0 1997 42.0 2008 25.2 1997 92.9 2008 81.6 1997 59.4 2008 42.9 Namibia 1993 49.1 .. .. 1993 24.6 .. .. 1993 62.2 .. .. 1993 36.5 .. .. Niger 1994 78.2 2007 43.1 1994 38.6 2007 11.9 1994 91.6 2007 75.9 1994 56.5 2007 30.6 Nigeria 1996 68.5 2004 64.4 1996 32.1 2004 29.6 1996 86.4 2004 83.9 1996 49.7 2004 46.9 Rwanda .. .. 2005 76.8 .. .. 2005 40.9 .. .. 2005 89.6 .. .. 2005 57.2 São Tomé and Príncipe .. .. 2001 28.6 .. .. 2001 8.2 .. .. 2001 57.3 .. .. 2001 21.6 Senegal 1995 54.1 2005 33.5 1995 19.5 2005 10.8 1995 79.4 2005 60.4 1995 37.9 2005 24.7 Seychelles .. .. 2007 0.3 .. .. 2007 0.1 .. .. 2007 1.8 .. .. 2007 0.4 Sierra Leone 1990 62.8 2003 53.4 1990 44.8 2003 20.3 1990 75.0 2003 76.1 1990 54.0 2003 37.5 Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa 1995 21.4 2006 17.4 1995 5.2 2006 3.3 1995 39.9 2006 35.7 1995 15.0 2006 12.3 Sudan .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Swaziland 1995 78.6 2001 62.9 1995 47.7 2001 29.4 1995 89.3 2001 81.0 1995 61.7 2001 45.8 Tanzania 1992 72.6 2007 67.9 1992 29.7 2007 28.1 1992 91.3 2007 87.9 1992 50.1 2007 47.5 Togo .. .. 2006 38.7 .. .. 2006 11.4 .. .. 2006 69.3 .. .. 2006 27.9 Uganda 1996 64.4 2009 28.7 1996 24.8 2009 8.3 1996 86.0 2009 55.3 1996 44.5 2009 21.3 Zambia 1998 55.4 2004 64.3 1998 26.9 2004 32.8 1998 74.8 2004 81.5 1998 41.7 2004 48.3 Zimbabwe .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. NORTH AFRICA Algeria 1995 6.8 .. .. 1995 1.4 .. .. 1995 23.6 .. .. 1995 6.5 .. .. Egypt, Arab Rep. 1996 2.5 2005 <2 1996 0.3 2005 0.4 1996 26.3 2005 18.5 1996 5.0 2005 3.5 Libya .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco 1999 6.8 2007 2.5 1999 1.2 2007 0.5 1999 24.4 2007 14.0 1999 6.5 2007 3.2 Tunisia 1995 6.5 2000 2.6 1995 1.3 2000 0.5 1995 20.4 2000 12.8 1995 5.8 2000 3.0 46 Part II. Millennium Development Goals Millennium Development Goals Share of population below Share of urban population below Share of rural population below national poverty linea national poverty linea national poverty linea (poverty headcount ratio) (poverty headcount ratio) (poverty headcount ratio) Surveys 1990–99c Surveys 2000–09c Surveys 1990–99c Surveys 2000–09c Surveys 1990–99c Surveys 2000–09c Year Percent Year Percent Year Percent Year Percent Year Percent Year Percent .. .. .. .. .. .. 2000e 62.3 .. .. .. .. .. .. 2003e 39.0 .. .. 2003e 29.0 .. .. 2003e 46.0 1993 47.0 2003 30.6 1993 29.0 2003 19.4 1993 55.0 2003 44.8 .. .. 2003e 46.4 .. .. 2003e 19.2 .. .. 2003e 52.4 .. .. 2006e 66.9 .. .. 2006e 34.0 .. .. 2006e 68.9 .. .. 2007e 39.9 .. .. 2007e 12.2 .. .. 2007e 55.0 .. .. 2007e 26.6 .. .. 2007e 13.2 .. .. 2007e 44.3 .. .. 2008e 62.0 .. .. 2008e 49.6 .. .. 2008e 69.4 .. .. 2003e 55.0 .. .. 2003e 24.6 .. .. 2003e 58.6 .. .. 2004e 44.8 .. .. 2004e 34.5 .. .. 2004e 48.7 .. .. 2005 71.3 .. .. 2005 61.5 .. .. 2005 75.7 .. .. 2005 50.1 .. .. .. .. .. .. 2005 57.7 1998 36.4f 2008 42.7f 1998 28.6f 2008 29.4f 1998 41.5f 2008 54.2f .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1993 69.0 .. .. 1993 62.0 .. .. .. .. .. .. 1999 44.2 2004 38.9 1999 36.9 2004 35.1 1999 45.4 2004 39.3 .. .. 2005 32.7 .. .. 2005 29.8 .. .. 2005 44.6 .. .. 2003e 58.0f .. .. 2003e 39.6f .. .. 2003e 67.8f 1998 39.5 2006 28.5 1998 19.4 2006 10.8 1998 49.6 2006 39.2 .. .. 2007e 53.0 .. .. 2007e 30.5 .. .. 2007e 63.0 .. .. 2002e 64.7 .. .. 2002e 51.6 .. .. 2002e 69.1 .. .. 2005e 45.9 .. .. 2005e 33.7 .. .. 2005e 49.1 1994 66.6f 2003 56.6f 1994 36.7f 2003 41.5f 1994 68.9f 2003 60.5f .. .. 2007 63.8f .. .. 2007 55.1f .. .. 2007 67.7f 1999 71.3 2005 68.7 1999 52.1 2005 52.0 1999 76.7 2005 73.5 1998 65.3 2004 52.4 1998 54.9 2004 25.4 1998 66.5 2004 55.9 .. .. 2006e 47.4 .. .. 2006e 25.5 .. .. 2006e 57.6 .. .. 2000e 46.3 .. .. 2000e 25.4 .. .. 2000e 61.2 .. .. .. .. .. .. .. .. .. .. .. .. 1996 69.4 2008 54.7 1996 62.0 2008 49.6 1996 71.3 2008 56.9 .. .. 2003e 38.0 .. .. 2003e 17.0 .. .. 2003e 49.0 .. .. 2007e 59.5 .. .. 2007e 36.7 .. .. 2007e 63.9 .. .. 2004e 54.7 .. .. 2004e 43.1 .. .. 2004e 63.8 .. .. 2006e 58.5 .. .. 2006e 23.2 .. .. 2006e 64.2 .. .. 2001 53.8 .. .. 2001 45.0 .. .. 2001 64.9 .. .. 2005e 50.8f .. .. 2005e 35.1f .. .. 2005e 61.9f .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2003e 66.4 .. .. 2003e 47.0 .. .. 2003e 78.5 .. .. .. .. .. .. .. .. .. .. .. .. 1995 31.0 2005 23.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2001e 69.2 .. .. 2001e 49.0 .. .. 2001e 75.0 .. .. 2007e 33.4 .. .. .. .. .. .. 2007e 37.4 .. .. 2006 61.7 .. .. 2006 36.8 .. .. 2006 74.3 1997 44.4 2009 24.5 1997 16.7 2009 9.1 1997 48.7 2009 27.2 1998 66.8 2006 59.3 1998 39.5 2006 26.7 1998 83.0 2006 76.8 .. .. 2003e 72.0 .. .. .. .. .. .. .. .. 1995 22.6 .. .. 1995 14.7 .. .. 1995 30.3 .. .. 1996 19.4 2008 22.0 .. .. 2008 10.6 .. .. 2008 30.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2007 9.0 .. .. 2007 4.8 .. .. 2007 14.5 1995 6.2 2005 3.8 .. .. .. .. .. .. .. .. (continued) Millennium Development Goals Part II. Millennium Development Goals 47 Table 3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger (continued) Population below Share of poorest quintile in national Prevalence of child malnutrition, underweight minimum dietary consumption or incomeb (% of children under age 5) energy consumption Surveys 1990–99c Surveys 2000–09c Surveys 1990–99c Surveys 2000–09c Share (%) Total (millions) Year Percent Year Percent Year Percent Year Percent 2005–07d 2005–07d SUB–SAHARAN AFRICA Angola .. .. 2000 2 1996 37 2001 27.5 41 7.1 Benin .. .. 2003 6.9 1996 26.8 2006 20.2 12 1.0 Botswana 1994 3.1 .. .. 1996 15.1 2000 10.7 25 0.5 Burkina Faso 1998 5.9 2003 7.0 1999 33.7 2009 26.0 9 1.2 Burundi 1998 5.1 2006 9.0 .. .. 2000 38.9 62 4.7 Cameroon 1996 5.7 2001 5.6 1998 17.8 2006 16.6 21 3.9 Cape Verde .. .. 2001 4.5 1994 11.8 .. .. 10 0.0 Central African Republic 1993 2.0 2003 5.2 1995 23.3 2000 21.8 40 1.7 Chad .. .. 2003 6.3 1997 34.3 2004 33.9 37 3.8 Comoros .. .. 2004 2.6 1996 22.3 2000 25.0 46 0.4 Congo, Dem. Rep. .. .. 2006 5.5 1995 30.7 2007 28.2 69 41.9 Congo, Rep. .. .. 2005 5.0 .. .. 2005 11.8 15 0.5 Côte d’Ivoire 1998 5.8 2008 5.6 1999 18.2 2006 16.7 14 2.8 Djibouti 1996 6.4 2002 6.0 1996 16.0 2006 29.6 28 0.2 Equatorial Guinea .. .. .. .. 1997 13.8 2004 10.6 .. .. Eritrea .. .. .. .. 1996 38.3 2002 34.5 64 3.0 Ethiopia 1995 7.2 2005 9.3 .. .. 2005 34.6 41 31.6 Gabon .. .. 2005 6.1 .. .. 2001 8.8 <5 .. Gambia, The 1998 4.0 2003 4.8 1996 23.2 2006 15.8 19 0.3 Ghana 1998 5.6 2006 5.2 1999 20.3 2008 14.3 5 1.2 Guinea 1994 6.4 2007 6.4 1999 21.2 2008 20.8 17 1.6 Guinea-Bissau 1993 5.2 2002 7.2 .. .. 2006 17.4 22 0.3 Kenya 1997 6.0 2005 4.7 1998 17.6 2009 16.4 31 11.2 Lesotho 1995 1.5 2003 3.0 1992 13.8 2005 16.6 14 0.3 Liberia .. .. 2007 6.4 .. .. 2007 20.4 33 1.2 Madagascar 1999 5.9 2005 6.2 1997 35.5 2004 36.8 25 4.5 Malawi 1998 4.8 2004 7.0 1998 26.3 2006 15.5 28 3.9 Mali 1994 4.6 2006 6.5 1996 38.2 2006 27.9 12 1.5 Mauritania 1996 6.3 2000 6.2 1996 20.3 2008 16.7 7 0.2 Mauritius .. .. .. .. 1995 13.0 .. .. 5 0.1 Mozambique 1997 5.7 2008 5.2 1997 28.1 2003 21.2 38 8.1 Namibia 1993 1.5 .. .. 1992 21.5 2007 17.5 19 0.4 Niger 1994 6.0 2007 8.3 1998 45.0 2006 39.9 20 2.7 Nigeria 1996 5.0 2004 5.1 1999 27.3 2008 26.7 6 9.2 Rwanda .. .. 2006 4.2 1996 24.2 2005 18.0 34 3.1 São Tomé and Príncipe .. .. 2001 5.2 .. .. 2009 13.1 <5 0.0 Senegal 1995 6.5 2005 6.2 1996 19.6 2005 14.5 17 2.0 Seychelles .. .. 2007 10.8 .. .. .. .. 7 0.0 Sierra Leone 1990 1.1 2003 6.1 1990 25.4 2008 21.3 35 1.8 Somalia .. .. .. .. .. .. 2006 32.8 .. .. South Africa 1995 3.6 2000 3.1 1999 10.1 .. .. <5 .. Sudan .. .. .. .. 1993 31.8 2006 31.7 22 8.8 Swaziland 1995 2.7 2001 4.5 .. .. 2007 6.1 18 0.2 Tanzania 1992 7.4 2007 6.8 1999 25.3 2005 16.7 34 13.7 Togo .. .. 2006 5.4 1998 23.2 2006 22.3 30 1.8 Uganda 1999 5.9 2009 5.8 1995 21.5 2006 16.4 21 6.1 Zambia 1998 3.3 2004 3.6 1999 19.6 2007 14.9 43 5.2 Zimbabwe 1995 4.6 .. .. 1999 11.5 2006 14.0 30 3.7 NORTH AFRICA Algeria 1995 6.9 .. .. 1995 11.3 2005 3.7 <5 1.4 Egypt, Arab Rep. 1996 9.5 2005 9.0 1998 10.2 2008 6.8 <5 .. Libya .. .. .. .. 1995 4.2 2007 5.6 <5 .. Morocco 1999 6.4 2007 6.5 1997 7.7 2004 9.9 <5 1.6 Tunisia 1995 5.6 2000 5.9 1997 3.3 2006 3.3 <5 .. a. Based on nominal per capita consumption average and distributions estimated from household surveys. b. Expenditure shares by percentiles of population, ranked by per capita expenditure. c. Survey year refers to the year in which the underlying household survey data were collected; in cases for which the data collection period bridged two calendar years, the year in which most of the data were collected is reported as the reference year. Data are for the most recent year available during the period speci�ed. d. Data for a three-year period are used for the estimation of the prevalence of undernourishment. e. Poverty estimates based on survey data from earlier years are available but not comparable with the most recent year reported here. f. World Bank estimates. 48 Part II. Millennium Development Goals Millennium Development Goals 3.2 Table Millennium Development Goal 2: achieve universal primary education Net primary enrollment ratio Primary completion rate Share of cohort reaching grade 5 Youth literacy rate (% of relevant age group) (% of relevant age group) (% of grade 1 students) (% ages 15–24) 1990 2000 2009 1990 2000 2009 1990 2000 2007–08a 1991 2000 2009 SUB–SAHARAN AFRICA Angola .. .. .. .. .. .. .. .. .. .. .. 73.1 Benin 41.2 .. 94.7 19.5 39.3 62.0 27.3 84.2 .. .. .. 54.3 Botswana 86.9 82.5 .. 89.8 91.0 .. 75.7 89.0 .. .. .. 95.2 Burkina Faso .. 36.0 63.3 19.3 25.1 43.0 55.6 69.1 75.1 .. .. .. Burundi .. 43.2 98.9 40.9 24.6 52.4 57.2 58.8 72.6 53.6 73.3 76.6 Cameroon 71.1 .. 91.6 54.2 49.9 73.4 66.6 .. 77.7 .. 83.1 .. Cape Verde 92.7 98.9 82.6 53.6 103.2 86.6 53.0 89.1 .. 88.2 .. 98.2 Central African Republic 57.9 .. 66.7 30.4 .. 38.0 42.7 .. 53.6 .. 58.5 64.7 Chad .. 53.5 .. 16.3 22.4 33.5 35.6 54.9 .. .. 37.6 46.3 Comoros .. 72.9 .. .. .. .. .. .. .. .. 80.2 85.3 Congo, Dem. Rep. .. .. .. .. .. 55.9 .. .. .. .. .. 67.7 Congo, Rep. .. .. .. 58.8 .. 74.1 70.6 .. .. .. .. .. Côte d’Ivoire .. 54.7 57.2 40.1 41.8 46.5 60.8 88.0 66.1 .. 60.7 66.6 Djibouti 29.3 26.9 44.4 32.0 28.0 35.4 73.9 .. 64.3 .. .. .. Equatorial Guinea .. 68.8 53.5 .. .. 46.5 .. .. 60.9 .. 94.9 97.9 Eritrea .. 37.9 35.7 .. 36.4 47.8 .. 60.5 73.1 .. .. 88.7 Ethiopia .. 40.5 82.7 .. 23.0 55.2 .. 64.6 45.9 .. .. .. Gabon .. .. .. .. .. .. .. .. .. .. .. 97.6 Gambia, The 51.4 72.1 .. .. 74.1 .. .. 73.0 .. .. 52.6 65.5 Ghana .. 62.9 75.9 .. 69.5 82.7 .. 66.2 79.0 .. 70.7 80.1 Guinea 24.9 46.6 72.9 18.8 32.1 61.7 50.6 .. 68.6 .. .. 61.1 Guinea-Bissau .. 52.1 .. .. 30.7 .. .. .. .. .. 59.5 70.9 Kenya .. 64.9 82.6 .. .. .. .. .. .. .. 80.3 92.7 Lesotho 70.7 77.5 73.1 58.4 60.1 70.3 66.3 67.2 .. .. 90.9 92.0 Liberia .. 75.2 .. .. .. .. .. .. .. .. .. 75.6 Madagascar 70.3 67.6 .. 37.0 37.6 78.8 34.0 36.1 49.4 .. 70.2 .. Malawi .. .. 90.8 28.1 65.4 59.2 32.3 .. 50.7 .. .. 86.5 Mali .. .. 72.9 .. 30.8 59.4 .. .. 86.9 .. .. .. Mauritania .. 62.6 76.3 29.1 .. .. 63.8 .. .. .. 61.3 67.7 Mauritius 97.2 92.9 94.0 113.7 102.8 89.4 .. 98.4 97.2 91.2 94.5 96.5 Mozambique 44.0 56.0 90.6 26.4 16.1 56.6 33.8 52.5 53.7 .. .. 70.9 Namibia 79.1 88.8 89.1 .. 91.6 87.1 .. 90.9 91.5 .. .. 93.0 Niger 22.8 26.7 54.0 15.8 17.9 40.3 57.0 74.0 64.3 .. .. .. Nigeria .. 63.0 .. .. .. .. .. .. .. .. .. 71.8 Rwanda .. .. .. 49.2 22.3 .. 51.5 41.7 48.5 .. 77.6 77.2 São Tomé and Príncipe 96.0 .. 97.5 77.9 .. 83.2 .. .. .. .. .. 95.3 Senegal 45.1 57.5 73.1 41.9 39.1 56.9 72.8 72.3 69.8 .. .. 65.0 Seychelles .. .. 94.4 .. 107.2 105.1 .. 91.0 94.9 .. .. .. Sierra Leone .. .. .. .. .. .. .. .. .. .. .. 57.6 Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa .. 89.8 84.7 .. 86.6 93.2 .. .. .. .. .. .. Sudan .. 39.2 .. .. 35.8 57.2 .. .. 86.0 .. 77.2 85.9 Swaziland 74.3 71.1 .. 62.7 60.3 .. 60.0 74.0 .. .. 88.4 93.4 Tanzania 51.4 52.9 96.4 .. .. 102.3 .. 81.4 80.9 .. .. 77.4 Togo 62.3 80.2 93.5 35.0 63.2 61.4 44.5 74.7 .. .. 74.4 .. Uganda .. .. 92.2 .. .. 72.5 .. 56.7 57.7 .. .. .. Zambia .. 68.5 90.7 .. 61.4 87.1 .. .. 71.0 66.4 .. 74.6 Zimbabwe .. 83.9 .. 93.6 .. .. 68.7 .. .. .. .. 98.9 NORTH AFRICA Algeria 87.5 91.6 93.8 80.8 82.6 90.5 83.8 97.1 94.5 .. .. .. Egypt, Arab Rep. .. 86.0 .. .. 87.7 .. .. 99.0 .. .. .. .. Libya .. .. .. .. .. .. .. .. .. .. .. 99.9 Morocco 56.2 75.8 89.7 51.4 56.7 80.4 68.9 80.1 84.2 .. .. 79.5 Tunisia 92.6 95.8 .. 80.3 88.5 .. 80.0 93.1 .. .. .. .. a. Data are for the most recent year available during the period speci�ed. Millennium Development Goals Part II. Millennium Development Goals 49 Table 3.3 Millennium Development Goal 3: promote gender equity and empower women Ratio of girls to boys in primary Ratio of literate young Women in Share of women employed in and secondary school women to men national parliament the nonagricultural sector (%) (% ages 15–24) (% of total seats) (%) 1991 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2000–09 a SUB–SAHARAN AFRICA Angola .. .. .. .. .. 81.1 15.0 16.0 37.3 .. .. .. Benin .. 64.2 .. .. .. 66.9 3.0 6.0 10.8 .. .. 24.3 Botswana 108.0 101.6 .. 107.4 .. 103.2 5.0 .. 11.1 33.5 42.9 43.4 Burkina Faso .. 70.1 85.6 52.9 .. .. .. 8.0 15.3 12.5 .. .. Burundi 79.0 .. 92.7 .. 91.6 99.2 .. 6.0 30.5 14.3 .. .. Cameroon 82.3 .. 85.6 .. 88.2 .. 14.0 6.0 13.9 .. .. 22.2 Cape Verde 94.0 .. 103.4 .. .. 101.7 12.0 11.0 18.1 .. 38.9 38.9 Central African Republic 59.1 .. 68.7 .. 66.6 79.4 4.0 7.0 10.5 .. .. 46.8 Chad 40.9 55.8 63.6 .. 41.7 72.8 .. 2.0 5.2 3.8 .. .. Comoros .. 84.1 .. .. 92.4 98.7 0.0 .. 3.0 .. .. .. Congo, Dem. Rep. .. .. 76.8 .. .. 84.7 5.0 .. 8.4 25.9 .. .. Congo, Rep. 88.5 85.7 .. .. .. .. 14.0 12.0 7.3 26.1 .. .. Côte d’Ivoire .. 69.3 .. .. 73.6 84.6 6.0 .. 8.9 .. .. .. Djibouti 72.2 71.0 82.0 .. .. .. 0.0 0.0 13.8 .. .. 26.7 Equatorial Guinea .. 81.1 .. .. 100.2 100.5 13.0 5.0 10.0 10.5 .. .. Eritrea .. 77.4 77.3 .. .. 93.6 .. 15.0 22.0 .. .. .. Ethiopia .. 65.1 87.9 .. .. .. .. 2.0 21.9 .. .. 47.3 Gabon .. 95.9 .. .. .. 98.0 13.0 8.0 16.7 .. .. .. Gambia, The .. 81.6 .. .. 64.3 84.5 8.0 2.0 9.4 20.9 .. .. Ghana 78.0 89.7 95.4 .. 86.2 97.3 .. 9.0 8.3 .. 31.7 31.7 Guinea 44.0 61.5 77.2 .. .. 79.1 .. 9.0 .. .. .. .. Guinea-Bissau .. 65.5 .. .. 61.4 81.3 20.0 .. 10.0 10.8 .. .. Kenya .. 97.6 95.4 .. 101.1 101.8 1.0 4.0 9.8 21.4 .. .. Lesotho 123.8 107.2 107.1 .. 114.9 114.4 .. 4.0 25.0 .. .. .. Liberia .. 71.9 .. .. .. 114.9 .. .. 12.5 .. .. 11.4 Madagascar 95.6 .. 96.9 .. 93.9 .. 7.0 8.0 .. .. .. 37.7 Malawi 80.9 92.6 100.0 .. .. 99.0 10.0 8.0 20.8 10.5 .. .. Mali 57.6 69.5 78.4 .. .. .. .. 12.0 10.2 .. .. 34.6 Mauritania 68.9 95.3 .. .. 81.9 90.8 .. 4.0 22.1 .. 35.8 35.8 Mauritius 100.4 98.6 101.3 .. 101.7 102.1 7.0 8.0 17.1 37.4 38.6 37.1 Mozambique 72.7 74.9 88.3 .. .. 81.6 16.0 .. 34.8 11.4 .. .. Namibia 110.8 103.2 .. 105.5 .. 104.2 7.0 22.0 26.9 .. 42.8 41.4 Niger 53.0 65.0 75.3 .. .. .. 5.0 1.0 12.4 .. .. 36.1 Nigeria 76.5 80.2 .. 76.8 .. 83.6 .. .. 7.0 .. 18.6 21.1 Rwanda 94.8 96.0 100.3 100.0 97.9 100.5 17.0 17.0 56.3 .. 33.0 33.0 São Tomé and Príncipe .. .. 103.1 95.9 .. 101.0 12.0 9.0 7.3 .. .. .. Senegal 67.4 81.9 .. .. .. 75.7 13.0 12.0 22.0 .. .. 10.6 Seychelles .. 103.7 103.5 .. .. .. 16.0 24.0 23.5 .. .. .. Sierra Leone 61.8 .. .. .. .. 71.1 .. 9.0 13.2 .. .. 23.2 Somalia .. .. .. .. .. .. 4.0 .. 6.1 21.7 .. .. South Africa 103.5 100.3 99.4 .. .. .. 3.0 30.0 44.5 .. 41.1 44.0 Sudan .. .. 89.4 .. 84.4 92.8 .. .. 18.1 22.2 .. .. Swaziland .. 95.5 .. .. 103.2 103.2 4.0 3.0 13.6 .. .. .. Tanzania 97.1 97.5 96.1 .. .. 97.3 .. 16.0 30.4 .. .. 30.5 Togo 58.1 69.1 .. .. 76.0 .. 5.0 .. 11.1 41.0 .. .. Uganda 77.9 92.8 98.7 81.7 .. .. 12.0 18.0 30.7 .. .. 39.0 Zambia .. 91.4 95.8 .. .. 82.3 7.0 10.0 15.2 16.6 22.0 22.0 Zimbabwe 96.4 94.4 .. .. .. 101.1 11.0 14.0 15.2 15.4 20.4 21.9 NORTH AFRICA Algeria 81.6 .. .. .. .. .. 2.0 3.0 7.7 .. .. 13.1 Egypt, Arab Rep. 80.5 92.5 .. .. .. .. 4.0 2.0 1.8 20.5 19.0 19.0 Libya .. .. .. .. .. 99.9 .. .. 7.7 .. .. 15.8 Morocco 68.8 82.4 .. .. .. 83.2 0.0 1.0 10.5 .. .. 20.8 Tunisia 84.6 99.5 .. .. .. .. 4.0 12.0 22.8 .. 24.3 25.0 a. Data are for the most recent year available during the period speci�ed. 50 Part II. Millennium Development Goals Millennium Development Goals 3.4 Table Millennium Development Goal 4: reduce child mortality Under-five mortality rate Infant mortality rate Child immunization rate, measles (per 1,000) (per 1,000 live births) (% of children ages 12–23 months) 1990 2000 2008 2009 1990 2000 2008 2009 1990 2000 2008 2009 SUB–SAHARAN AFRICA Angola 258 212 166 161 153 126 101 98 38 41 79 77 Benin 184 144 121 118 111 89 76 75 79 70 66 72 Botswana 60 99 59 57 46 66 44 43 87 91 94 94 Burkina Faso 201 188 169 166 110 102 92 91 79 51 75 75 Burundi 189 178 168 166 114 107 102 101 74 76 84 91 Cameroon 148 156 155 154 91 96 95 95 56 49 80 74 Cape Verde 63 41 29 28 49 33 24 23 79 86 96 96 Central African Republic 175 184 172 171 115 119 113 112 82 36 62 62 Chad 201 205 209 209 120 122 124 124 32 28 23 23 Comoros 128 114 105 104 90 81 76 75 87 70 76 79 Congo, Dem. Rep. 199 199 199 199 126 126 126 126 38 46 67 76 Congo, Rep. 104 116 127 128 67 74 80 81 75 34 79 76 Côte d’Ivoire 152 142 121 119 105 97 85 83 56 71 63 67 Djibouti 123 106 95 94 95 84 76 75 85 50 73 73 Equatorial Guinea 198 168 148 145 120 102 90 88 88 51 51 51 Eritrea 150 89 58 55 92 58 41 39 .. 86 95 95 Ethiopia 210 148 109 104 124 91 69 67 38 52 74 75 Gabon 93 83 71 69 68 61 53 52 76 55 55 55 Gambia, The 153 131 106 103 104 93 80 78 86 92 91 96 Ghana 120 106 72 69 76 68 49 47 61 90 86 93 Guinea 231 185 146 142 137 111 90 88 35 42 51 51 Guinea-Bissau 240 218 195 193 142 129 117 115 53 71 76 76 Kenya 99 105 86 84 64 66 56 55 78 78 76 74 Lesotho 93 124 91 84 74 86 66 61 80 74 85 85 Liberia 247 198 119 112 165 134 85 80 .. 63 64 64 Madagascar 167 100 61 58 102 65 43 41 47 55 70 64 Malawi 218 164 115 110 129 99 71 69 81 73 88 92 Mali 250 217 194 191 139 120 103 101 43 55 71 71 Mauritania 129 122 118 117 81 77 75 74 38 62 65 59 Mauritius 24 19 17 17 21 17 15 15 76 84 98 99 Mozambique 232 183 147 142 155 123 99 96 59 71 77 77 Namibia 73 76 50 48 49 50 35 34 .. 69 73 76 Niger 305 227 167 160 144 107 79 76 25 37 66 73 Nigeria 212 190 143 138 126 114 89 86 54 33 41 41 Rwanda 171 180 117 111 103 108 74 70 83 74 92 92 São Tomé and Príncipe 95 86 79 78 62 56 52 52 71 69 93 90 Senegal 151 120 95 93 73 61 52 51 51 48 77 79 Seychelles 15 14 13 12 13 12 11 11 86 97 99 97 Sierra Leone 285 250 198 192 166 150 126 123 .. 37 66 71 Somalia 180 180 180 180 109 109 109 109 30 35 24 24 South Africa 62 77 65 62 48 54 45 43 79 72 62 62 Sudan 124 115 109 108 78 73 70 69 57 58 79 82 Swaziland 92 105 77 73 67 71 53 52 85 92 95 95 Tanzania 162 139 111 108 99 86 70 68 80 78 88 91 Togo 150 124 100 98 89 78 66 64 73 58 77 84 Uganda 184 154 130 128 111 94 81 79 52 57 68 68 Zambia 179 166 145 141 108 99 88 86 90 85 85 85 Zimbabwe 81 116 93 90 54 69 58 56 87 75 70 76 NORTH AFRICA Algeria 61 46 34 32 51 40 30 29 83 80 88 88 Egypt, Arab Rep. 90 47 23 21 66 38 20 18 86 98 92 95 Libya 36 25 19 19 32 23 17 17 89 93 98 98 Morocco 89 55 39 38 69 46 35 33 79 93 96 98 Tunisia 50 27 21 21 40 23 18 18 93 95 98 98 Millennium Development Goals Part II. Millennium Development Goals 51 Table 3.5 Millennium Development Goal 5: improve maternal health Maternal mortality ratio Births attended by skilled health staff (per 100,000 live births) (% of total) Modeled estimate National estimate Surveys 1990–99a Surveys 2000–09a 1990 2008 1990–99a 2000–09a Year Percent Year Percent SUB–SAHARAN AFRICA Angola 1,000 610 .. .. 1996 22.5 2007 47.3 Benin 790 410 .. 397 1996 59.8 2006 74.0 Botswana 83 190 498 198 1996 87 2007 94.6 Burkina Faso 770 560 326 307 1999 31 2006 53.5 Burundi 1,200 970 484 615 .. .. 2005 33.6 Cameroon 680 600 .. 669 1998 55 2006 63.0 Cape Verde 230 94 .. 16 1998 88.5 2005 77.5 Central African Republic 880 850 .. 543 1995 45.9 2009 43.7 Chad 1,300 1,200 1,100 1,099 1997 15 2004 14.4 Comoros 530 340 830 380 1996 51.6 2000 61.8 Congo, Dem. Rep. 900 670 .. 549 .. .. 2007 74.0 Congo, Rep. 460 580 .. 781 .. .. 2005 83.4 Côte d’Ivoire 690 470 .. 543 1999 47.1 2006 56.8 Djibouti 370 300 600 546 .. .. 2006 92.9 Equatorial Guinea 1,000 280 74 .. 1994 5 2000 64.6 Eritrea 930 280 .. .. 1995 20.6 2002 28.3 Ethiopia 990 470 998 673 .. .. 2005 5.7 Gabon 260 260 .. 519 .. .. 2000 85.5 Gambia, The 750 400 .. 730 1990 44.1 2006 56.8 Ghana 630 350 .. 451 1998 44.3 2008 57.1 Guinea 1,200 680 .. 980 1999 34.8 2007 46.1 Guinea-Bissau 1,200 1,000 530 405 1995 25 2006 38.8 Kenya 380 530 910 488 1998 44.3 2009 43.8 Lesotho 370 530 .. 762 1993 49.6 2009 61.5 Liberia 1,100 990 .. 994 .. .. 2007 46.3 Madagascar 710 440 .. 498 1997 47.3 2009 43.9 Malawi 910 510 .. 807 1992 54.8 2006 53.6 Mali 1,200 830 .. 464 1996 40 2006 49.0 Mauritania 780 550 .. 686 1991 40 2007 60.9 Mauritius 72 36 .. 22 1999 98.5 2005 99.2 Mozambique 1,000 550 .. 408 1997 44.2 2008 55.3 Namibia 180 180 .. 449 1992 68.2 2007 81.4 Niger 1,400 820 .. 648 1998 17.6 2006 32.9 Nigeria 1,100 840 590 545 1999 41.6 2008 38.9 Rwanda 1,100 540 .. 750 1992 25.8 2008 52.1 São Tomé and Príncipe .. .. .. 148 .. .. 2009 81.7 Senegal 750 410 .. 401 1999 48.3 2005 51.9 Seychelles .. .. 560 57 .. .. .. .. Sierra Leone 1,300 970 .. 857 .. .. 2008 42.4 Somalia 1,100 1,200 .. 1,044 1999 32.2 2006 33.0 South Africa 230 410 1,000 166 1998 84.4 2003 91.2 Sudan 830 750 150 1,107 1999 56.9 2006 49.2 Swaziland 260 420 .. 589 1994 56 2007 69.0 Tanzania 880 790 229 578 1999 43.8 2005 43.4 Togo 650 350 .. .. 1998 50.5 2006 62.0 Uganda 670 430 478 435 1995 37.8 2006 41.9 Zambia 390 470 .. 591 1999 47.1 2007 46.5 Zimbabwe 390 790 .. 555 1999 72.5 2009 60.2 NORTH AFRICA Algeria 250 120 .. .. 1992 77 2006 95.2 Egypt, Arab Rep. 220 82 117 55 1998 55.2 2008 78.9 Libya 100 64 .. .. 1999 99 .. .. Morocco 270 110 77 132 1995 39.6 2004 62.6 Tunisia 130 60 332 .. 1995 80.5 2006 94.6 a. Data are for the most recent year available during the period speci�ed. 52 Part II. Millennium Development Goals Millennium Development Goals 3.6 Table Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases Children sleeping under Contraceptive use, any method insecticide-treated nets Prevalence of HIV (% of married women ages 15–49) (% of children under age 5) (% ages 15–49) Surveys 1990–99a Surveys 2000–09a Surveys 2000–09a 1990 2009 Year Percent Year Percent Year Percent SUB–SAHARAN AFRICA Angola 0.5 2.0 1996 8.1 2001 6.2 2007 18 Benin 0.2 1.2 1996 16.4 2006 17.0 2006 20 Botswana 3.5 24.8 .. .. 2007 52.8 .. .. Burkina Faso 3.9 1.2 1999 11.9 2006 17.4 2006 10 Burundi 3.9 3.3 .. .. 2005 9.1 2005 8 Cameroon 0.6 5.3 1998 19.3 2006 29.2 2006 13 Cape Verde .. .. 1998 52.9 2005 61.3 .. .. Central African Republic 3.1 4.7 1995 14.8 2006 19.0 2006 15 Chad 1.1 3.4 1997 4.2 2004 2.8 2000 1 Comoros <0.1 0.1 1996 21.0 2000 25.7 2000 9 Congo, Dem. Rep. .. .. 1991 7.7 2007 20.6 2007 6 Congo, Rep. 5.2 3.4 .. .. 2005 44.3 2005 6 Côte d’Ivoire 2.4 3.4 1999 15.0 2006 12.9 2006 3 Djibouti 0.9 2.5 .. .. 2008 22.5 2009 20 Equatorial Guinea 0.1 5.0 .. .. .. .. 2000 1 Eritrea 0.3 0.8 1995 8.0 2002 8.0 2002 4 Ethiopia .. .. 1990 4.3 2005 14.7 2007 33 Gabon 0.9 5.2 .. .. 2000 32.7 .. .. Gambia, The 0.1 2.0 1990 11.8 2001 17.5 2006 49 Ghana 0.3 1.8 1999 22.0 2008 23.5 2008 28 Guinea 1.1 1.3 1999 6.2 2005 9.1 2008 5 Guinea-Bissau 0.3 2.5 .. .. 2006 10.3 2006 39 Kenya 3.9 6.3 1998 39.0 2009 45.5 2009 46 Lesotho 0.8 23.6 1992 23.2 2009 47.0 .. .. Liberia 0.3 1.5 .. .. 2007 11.4 2009 26 Madagascar 0.2 0.2 1997 19.3 2009 39.9 2009 46 Malawi 7.2 11.0 1996 21.9 2006 41.0 2006 25 Mali 0.4 1.0 1996 6.7 2006 8.2 2006 27 Mauritania 0.2 0.7 1991 3.3 2007 9.3 2004 2 Mauritius <0.1 1.0 1999 26.0 2002 75.9 .. .. Mozambique 1.2 11.5 1997 5.6 2008 16.2 2008 23 Namibia 1.6 13.1 1992 28.9 2007 55.1 2006 11 Niger 0.1 0.8 1998 8.2 2006 11.2 2009 43 Nigeria 1.3 3.6 1999 15.3 2008 14.6 2008 6 Rwanda 5.2 2.9 1996 13.7 2008 36.4 2008 56 São Tomé and Príncipe .. .. .. .. 2009 38.4 2009 56 Senegal 0.2 0.9 1999 10.5 2005 11.8 2009 29 Seychelles .. .. .. .. .. .. .. .. Sierra Leone <0.1 1.6 .. .. 2008 8.2 2008 26 Somalia 0.1 0.7 1999 7.9 2006 14.6 2006 11 South Africa 0.7 17.8 1998 56.3 2003 59.9 .. .. Sudan 0.1 1.1 1993 9.9 2006 7.6 2006 28 Swaziland 2.3 25.9 .. .. 2007 50.6 2007 1 Tanzania 4.8 5.6 1999 25.4 2005 26.4 2008 26 Togo 0.6 3.2 1999 23.5 2006 16.8 2006 38 Uganda 10.2 6.5 1995 14.8 2006 23.7 2006 10 Zambia 12.7 13.5 1999 22.0 2007 40.8 2008 41 Zimbabwe 10.1 14.3 1999 53.5 2009 64.9 2009 17 NORTH AFRICA Algeria <0.1 0.1 1995 52.0 2006 61.4 .. .. Egypt, Arab Rep. <0.1 <0.1 1998 51.7 2008 60.3 .. .. Libya .. .. 1995 45.2 .. .. .. .. Morocco <0.1 0.1 1997 58.8 2004 63.0 .. .. Tunisia <0.1 <0.1 1995 60.0 2006 60.2 .. .. (continued) Millennium Development Goals Part II. Millennium Development Goals 53 Table 3.6 Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases (continued) Tuberculosis treatment success rate Incidence of tuberculosis (% of registered cases) (per 100,000 people) Surveys 1990–99a Surveys 2000–08a 1990 1999 2009 Year Percent Year Percent SUB-SAHARAN AFRICA Angola 205 245 298 1998 68.0 2008 70.0 Benin 77 84 93 1999 77.0 2008 89.0 Botswana 307 588 694 1999 71.0 2008 65.0 Burkina Faso 95 182 215 1999 61.0 2008 76.0 Burundi 154 295 348 1998 74.0 2008 90.0 Cameroon 81 154 182 1999 75.0 2007 76.0 Cape Verde 175 162 148 .. .. 2008 74.0 Central African Republic 145 277 327 1995 37.0 2008 71.0 Chad 125 240 283 1998 64.0 2006 54.0 Comoros 85 59 39 1999 93.0 2008 90.0 Congo, Dem. Rep. 165 315 372 1999 69.0 2008 87.0 Congo, Rep. 169 324 382 1999 61.0 2008 76.0 Côte d’Ivoire 177 338 399 1999 63.0 2008 76.0 Djibouti 619 619 620 1999 72.0 2008 84.0 Equatorial Guinea 86 97 117 1997 82.0 2008 56.0 Eritrea 72 84 99 1999 44.0 2008 76.0 Ethiopia 159 304 359 1999 74.0 2008 84.0 Gabon 153 210 501 1998 50.0 2008 53.0 Gambia, The 185 221 269 1997 70.0 2008 84.0 Ghana 223 212 201 1999 51.0 2008 86.0 Guinea 119 190 318 1999 74.0 2008 78.0 Guinea-Bissau 158 188 229 1999 35.0 2008 70.0 Kenya 112 382 305 1999 79.0 2008 85.0 Lesotho 184 519 634 1999 69.0 2008 73.0 Liberia 199 237 288 1999 74.0 2008 79.0 Madagascar 177 213 261 1997 64.0 2008 81.0 Malawi 258 417 304 1999 71.0 2008 87.0 Mali 275 297 324 1999 69.0 2008 82.0 Mauritania 228 272 330 .. .. 2008 68.0 Mauritius 28 25 22 1999 87.0 2008 87.0 Mozambique 181 347 409 1999 71.0 2008 84.0 Namibia 322 616 727 1999 51.0 2008 82.0 Niger 125 149 181 1999 60.0 2008 81.0 Nigeria 131 250 295 1999 75.0 2008 78.0 Rwanda 167 319 376 1999 67.0 2008 87.0 São Tomé and Príncipe 135 116 98 1999 81.0 2008 94.0 Senegal 195 232 282 1999 58.0 2008 84.0 Seychelles 43 37 31 1999 91.0 2008 100.0 Sierra Leone 207 355 644 1999 75.0 2008 86.0 Somalia 285 285 285 1999 88.0 2008 81.0 South Africa 301 479 971 1999 57.0 2008 76.0 Sudan 119 119 119 1999 80.0 2008 81.0 Swaziland 267 691 1257 .. .. 2008 68.0 Tanzania 226 232 183 1999 78.0 2008 88.0 Togo 308 367 446 1999 76.0 2008 79.0 Uganda 163 324 293 1999 61.0 2008 70.0 Zambia 297 603 433 1999 69.0 2008 88.0 Zimbabwe 329 628 742 1999 73.0 2008 74.0 NORTH AFRICA Algeria 38 47 59 1999 87.0 2008 90.0 Egypt, Arab Rep. 34 27 19 1999 85.0 2008 89.0 Libya 40 40 40 1999 67.0 2008 69.0 Morocco 147 123 92 1999 88.0 2008 85.0 Tunisia 29 26 24 1999 91.0 2008 86.0 a. Data are for the most recent year available during the period speci�ed. 54 Part II. Millennium Development Goals Millennium Development Goals 3.7 Table Millennium Development Goal 7: ensure environmental sustainability Forest area Terrestrial protected areas GDP per unit of energy use (% of total land area) (% of total land area) (2005 PPP $ per kg of oil equivalent) 1990 2000 2010 1990 2000 2009 1990 2000 2008 SUB–SAHARAN AFRICA Angola 48.9 47.9 46.9 12.4 12.4 12.4 5.8 4.9 8.8 Benin 52.1 45.8 41.2 23.8 23.8 23.8 3.2 4.3 3.9 Botswana 24.2 22.1 20.0 30.3 30.9 30.9 7.6 9.1 11.6 Burkina Faso 25.0 22.8 20.6 13.3 13.5 13.9 .. .. .. Burundi 11.3 7.7 6.7 3.8 4.8 4.8 .. .. .. Cameroon 51.4 46.8 42.1 7.0 8.7 9.2 5.1 4.6 5.4 Cape Verde 14.3 20.4 21.1 2.5 2.5 2.5 .. .. .. Central African Republic 37.2 36.8 36.3 14.4 14.7 14.7 .. .. .. Chad 10.4 9.8 9.2 9.4 9.4 9.4 .. .. .. Comoros 6.4 4.3 1.6 0.0 0.0 0.0 .. .. .. Congo, Dem. Rep. 70.7 69.4 68.0 10.0 10.0 10.0 1.9 0.8 0.8 Congo, Rep. 66.5 66.1 65.6 5.4 7.8 9.4 10.7 11.5 9.6 Côte d’Ivoire 32.1 32.5 32.7 22.6 22.6 22.6 5.5 4.5 3.1 Djibouti 0.2 0.2 0.3 0.0 0.0 0.0 .. .. .. Equatorial Guinea 66.3 62.1 58.0 7.3 19.2 19.2 .. .. .. Eritrea .. 15.6 15.2 4.9 4.9 5.0 .. 3.5 3.8 Ethiopia 15.2 13.7 12.3 17.7 17.7 18.4 1.8 1.9 2.0 Gabon 85.4 85.4 85.4 4.2 5.2 14.9 11.8 11.2 9.4 Gambia, The 44.2 46.1 48.0 1.5 1.5 1.5 .. .. .. Ghana 32.7 26.8 21.7 13.9 14.0 14.0 2.5 2.6 3.4 Guinea 29.6 28.1 26.6 6.8 6.8 6.8 .. .. .. Guinea-Bissau 78.8 75.4 71.9 7.6 16.1 16.1 .. .. .. Kenya 6.5 6.3 6.1 11.5 11.6 11.6 3.0 2.9 3.1 Lesotho 1.3 1.4 1.4 0.5 0.5 0.5 .. .. .. Liberia 51.2 48.1 44.9 18.1 18.1 18.1 .. .. .. Madagascar 23.5 22.6 21.6 2.1 2.9 2.9 .. .. .. Malawi 41.4 37.9 34.4 15.0 15.0 15.0 .. .. .. Mali 11.5 10.9 10.2 2.3 2.3 2.4 .. .. .. Mauritania 0.4 0.3 0.2 0.5 0.5 0.5 .. .. .. Mauritius 19.1 19.1 17.2 1.7 4.5 4.5 .. .. .. Mozambique 55.2 52.4 49.6 14.8 14.8 15.8 0.9 1.3 1.9 Namibia 10.6 9.8 8.9 14.4 14.5 14.5 .. 8.4 7.3 Niger 1.5 1.0 1.0 6.8 6.8 6.8 .. .. .. Nigeria 18.9 14.4 9.9 11.6 12.8 12.8 2.0 2.0 2.6 Rwanda 12.9 13.9 17.6 9.9 9.9 10.0 .. .. .. São Tomé and Príncipe 28.1 28.1 28.1 .. .. .. .. .. .. Senegal 48.6 46.2 44.0 24.1 24.1 24.1 6.3 6.0 7.1 Seychelles 88.5 88.5 89.1 42.0 42.0 42.0 .. .. .. Sierra Leone 43.5 40.8 38.1 5.0 5.0 5.0 .. .. .. Somalia 13.2 12.0 10.8 0.6 0.6 0.6 .. .. .. South Africa 7.6 7.6 4.7 6.5 6.9 6.9 3.1 3.0 3.5 Sudan 32.1 29.7 29.4 4.7 4.9 4.9 2.5 3.4 5.3 Swaziland 27.4 30.1 32.7 3.0 3.0 3.0 .. .. .. Tanzania 46.8 42.3 37.7 26.5 26.9 27.7 2.2 2.1 2.6 Togo 12.6 8.9 5.3 11.3 11.3 11.3 2.7 2.0 1.9 Uganda 24.1 19.6 15.2 7.3 7.9 9.7 .. .. .. Zambia 71.0 68.8 66.5 36.0 36.0 36.0 1.8 1.7 2.1 Zimbabwe 57.3 48.8 40.4 18.0 18.0 28.0 .. .. .. NORTH AFRICA Algeria 0.7 0.7 0.6 6.3 6.3 6.3 7.1 6.9 6.8 Egypt, Arab Rep. 0.0 0.1 0.1 1.9 4.3 5.9 5.8 6.2 5.8 Libya 0.1 0.1 0.1 0.1 0.1 0.1 .. 4.0 5.2 Morocco 11.3 11.2 11.5 1.2 1.5 1.5 9.7 8.3 8.4 Tunisia 4.1 5.4 6.5 1.3 1.3 1.3 6.6 7.1 8.3 (continued) Millennium Development Goals Part II. Millennium Development Goals 55 Table 3.7 Millennium Development Goal 7: ensure environmental sustainability (continued) Carbon dioxide emissions Population with sustainable access Population with sustainable access per capita to an improved water source to improved sanitation (metric tons) (%) (%) 1990 2000 2007 1990 2000 2008 1990 2000 2008 SUB–SAHARAN AFRICA Angola 0.4 0.7 1.4 36.0 41.0 50.0 25.0 40.0 57.0 Benin 0.1 0.2 0.5 56.0 66.0 75.0 5.0 9.0 12.0 Botswana 1.6 2.5 2.6 93.0 94.0 95.0 36.0 50.0 60.0 Burkina Faso 0.1 0.1 0.1 41.0 60.0 76.0 6.0 8.0 11.0 Burundi 0.1 0.0 0.0 70.0 72.0 72.0 44.0 45.0 46.0 Cameroon 0.1 0.2 0.3 50.0 64.0 74.0 47.0 47.0 47.0 Cape Verde 0.2 0.4 0.6 .. 83.0 84.0 .. 45.0 54.0 Central African Republic 0.1 0.1 0.1 58.0 63.0 67.0 11.0 22.0 34.0 Chad 0.0 0.0 0.0 38.0 45.0 50.0 6.0 7.0 9.0 Comoros 0.2 0.2 0.2 87.0 92.0 95.0 17.0 28.0 36.0 Congo, Dem. Rep. 0.1 0.0 0.0 45.0 44.0 46.0 9.0 16.0 23.0 Congo, Rep. 0.5 0.3 0.4 .. 70.0 71.0 .. 30.0 30.0 Côte d’Ivoire 0.5 0.4 0.3 76.0 78.0 80.0 20.0 22.0 23.0 Djibouti 0.7 0.6 0.6 77.0 84.0 92.0 66.0 63.0 56.0 Equatorial Guinea 0.3 0.9 7.5 .. 43.0 .. .. 51.0 .. Eritrea .. 0.2 0.1 43.0 54.0 61.0 9.0 11.0 14.0 Ethiopia 0.1 0.1 0.1 17.0 28.0 38.0 4.0 8.0 12.0 Gabon 6.6 1.0 1.4 .. 85.0 87.0 .. 36.0 33.0 Gambia, The 0.2 0.2 0.2 74.0 84.0 92.0 .. 63.0 67.0 Ghana 0.3 0.3 0.4 54.0 71.0 82.0 7.0 9.0 13.0 Guinea 0.2 0.2 0.1 52.0 62.0 71.0 9.0 15.0 19.0 Guinea-Bissau 0.2 0.2 0.2 .. 55.0 61.0 .. 18.0 21.0 Kenya 0.2 0.3 0.3 43.0 52.0 59.0 26.0 29.0 31.0 Lesotho .. .. .. 61.0 74.0 85.0 32.0 29.0 29.0 Liberia 0.2 0.2 0.2 58.0 65.0 68.0 11.0 14.0 17.0 Madagascar 0.1 0.2 0.1 31.0 37.0 41.0 8.0 10.0 11.0 Malawi 0.1 0.1 0.1 40.0 63.0 80.0 42.0 50.0 56.0 Mali 0.0 0.1 0.0 29.0 44.0 56.0 26.0 32.0 36.0 Mauritania 1.3 0.5 0.6 30.0 40.0 49.0 16.0 21.0 26.0 Mauritius 1.4 2.3 3.1 99.0 99.0 99.0 91.0 91.0 91.0 Mozambique 0.1 0.1 0.1 36.0 42.0 47.0 11.0 14.0 17.0 Namibia 0.0 1.0 1.5 64.0 81.0 92.0 25.0 29.0 33.0 Niger 0.1 0.1 0.1 35.0 42.0 48.0 5.0 7.0 9.0 Nigeria 0.5 0.6 0.6 47.0 53.0 58.0 37.0 34.0 32.0 Rwanda 0.1 0.1 0.1 68.0 67.0 65.0 23.0 40.0 54.0 São Tomé and Príncipe 0.6 0.6 0.8 .. 79.0 89.0 .. 21.0 26.0 Senegal 0.4 0.4 0.5 61.0 65.0 69.0 38.0 45.0 51.0 Seychelles 1.6 7.0 7.3 .. .. .. .. .. .. Sierra Leone 0.1 0.1 0.2 .. 55.0 49.0 .. 11.0 13.0 Somalia 0.0 0.1 0.1 .. 23.0 30.0 .. 22.0 23.0 South Africa 9.5 8.4 9.0 83.0 86.0 91.0 69.0 73.0 77.0 Sudan 0.2 0.2 0.3 65.0 61.0 57.0 34.0 34.0 34.0 Swaziland 0.5 1.1 0.9 .. 55.0 69.0 .. 49.0 55.0 Tanzania 0.1 0.1 0.1 55.0 54.0 54.0 24.0 24.0 24.0 Togo 0.2 0.3 0.2 49.0 55.0 60.0 13.0 12.0 12.0 Uganda 0.0 0.1 0.1 43.0 57.0 67.0 39.0 44.0 48.0 Zambia 0.3 0.2 0.2 49.0 54.0 60.0 46.0 47.0 49.0 Zimbabwe 1.5 1.1 0.8 78.0 80.0 82.0 43.0 44.0 44.0 NORTH AFRICA Algeria 3.1 3.8 4.1 94.0 89.0 83.0 88.0 92.0 95.0 Egypt, Arab Rep. 1.3 2.0 2.3 90.0 96.0 99.0 72.0 86.0 94.0 Libya 9.2 9.3 9.3 54.0 54.0 .. 97.0 97.0 97.0 Morocco 0.9 1.2 1.5 74.0 78.0 81.0 53.0 64.0 69.0 Tunisia 1.6 2.1 2.3 81.0 90.0 94.0 74.0 81.0 85.0 56 Part II. Millennium Development Goals Millennium Development Goals 3.8 Table Millennium Development Goal 8: develop a global partnership for development Debt sustainability Heavily Indebted Poor Countries Debt service relief Public and publicly guaranteed debt service (HIPC) Debt Initiative committed (% of exports, excluding worker remittances) Decision pointa Completion pointa ($ millions)a 1990 2000 2009 SUB–SAHARAN AFRICA Angola .. .. .. 7.1 20.4 8.4 Benin Jul. 2000 Mar. 2003 460 8.4 10.7 .. Botswana .. .. .. 4.3 2.0 1.0 Burkina Faso Jul. 2000 Apr. 2002 930 7.7 15.1 .. Burundi Aug. 2005 Jan. 2009 1,366 40.7 25.1 10.1 Cameroon Oct. 2000 Apr. 2006 4,917 12.5 14.0 2.5 Cape Verde .. .. .. 8.9 10.5 5.1 Central African Republic Sep. 2007 Jun. 2009 804 7.5 .. .. Chad May 2001 .. 260 2.3 .. .. Comoros Jun. 2010 .. 136 2.5 .. .. Congo, Dem. Rep. Jul. 2003 Jul. 2010 15,222 .. .. .. Congo, Rep. Mar. 2006 Jan. 2010 1,738 30.9 0.5 .. Côte d’Ivoire Mar. 2009 .. 3,415 14.7 14.9 6.6 Djibouti .. .. .. .. 4.8 5.7 Equatorial Guinea .. .. .. .. .. .. Eritrea .. .. .. .. 2.8 .. Ethiopia Nov. 2001 Apr. 2004 3,275 33.2 12.2 3.0 Gabon .. .. .. 3.8 8.8 .. Gambia, The Dec. 2000 Dec. 2007 112 17.3 .. 8.7 Ghana Feb. 2002 Jul. 2004 3,500 19.9 12.0 2.5 Guinea Dec. 2000 .. 800 17.7 17.6 10.1 Guinea-Bissau Dec. 2000 .. 790 22.0 .. .. Kenya .. .. .. 22.7 15.7 4.5 Lesotho .. .. .. 4.1 10.3 2.5 Liberia Mar. 2008 Jun. 2010 4,600 .. .. 11.2 Madagascar Dec. 2000 Oct. 2004 1,900 31.9 8.4 .. Malawi Dec. 2000 Aug. 2006 1,628 22.4 10.8 .. Mali Sep. 2000 Mar. 2003 895 9.7 10.2 .. Mauritania Feb. 2000 Jun. 2002 1,100 24.8 .. .. Mauritius .. .. .. 4.5 16.4 1.9 Mozambique Apr. 2000 Sep. 2001 4,300 17.2 7.0 1.4 Namibia .. .. .. .. .. .. Niger Dec. 2000 Apr. 2004 1,190 3.2 6.0 .. Nigeria .. .. .. 22.3 8.2 0.7 Rwanda Dec. 2000 Apr. 2005 1,316 9.4 15.3 4.7 São Tomé and Príncipe Dec. 2000 Mar. 2007 263 28.6 20.3 16.2 Senegal Jun. 2000 Apr. 2004 850 13.7 13.2 .. Seychelles .. .. .. 7.6 3.3 6.2 Sierra Leone Mar. 2002 Dec. 2006 994 7.8 29.6 2.1 Somalia .. .. .. .. .. .. South Africa .. .. .. .. 5.5 2.4 Sudan .. .. .. 4.5 10.1 5.6 Swaziland .. .. .. 5.3 2.1 2.1 Tanzania Apr. 2000 Nov. 2001 3,000 25.1 10.3 1.0 Togo Nov. 2008 .. 360 8.6 3.2 .. Uganda Feb. 2000 May 2000 1,950 47.1 6.5 1.7 Zambia Dec. 2000 Apr. 2005 3,900 12.6 17.2 1.6 Zimbabwe .. .. .. 18.2 .. .. NORTH AFRICA Algeria .. .. .. 63.3 .. .. Egypt, Arab Rep. .. .. .. 23.2 8.5 6.2 Libya .. .. .. .. .. .. Morocco .. .. .. 23.1 23.0 6.4 Tunisia .. .. .. 23.0 20.0 9.0 (continued) Millennium Development Goals Part II. Millennium Development Goals 57 Table 3.8 Millennium Development Goal 8: develop a global partnership for development (continued) Youth unemployment rate (ages 15–24) Information and communication Total Male Female Fixed-line and mobile (share of total (share of male (share of female telephone subscribers Personal computers Internet users labor force) labor force) labor force) (per 100 people) (per 100 people) (per 100 people) Year Percent Year Percent Year Percent 1990 2000 2009 1990 2000 2005–09b 1995 2000 2009 SUB–SAHARAN AFRICA Angola .. .. .. .. .. .. 0.7 0.6 45.5 .. 0.1 0.7 .. 0.1 3.3 Benin 2002 0.82 2002 1.07 2002 0.61 0.3 1.6 57.8 .. 0.2 0.7 .. 0.2 2.2 Botswana 2000 13.6 2000 13.23 2000 14.01 2.0 20.8 103.5 .. 3.5 6.3 0.1 2.9 6.2 Burkina Faso .. .. .. .. .. .. 0.2 0.7 22.0 0.0 0.1 0.6 .. 0.1 1.1 Burundi .. .. .. .. .. .. 0.1 0.6 10.5 .. 0.1 0.9 0.0 0.1 0.8 Cameroon .. .. .. .. .. .. 0.3 1.3 39.6 .. 0.3 1.1 .. 0.3 3.8 Cape Verde .. .. .. .. .. .. 2.3 16.9 91.8 .. 5.7 14.0 .. 1.8 29.7 Central African Republic .. .. .. .. .. .. 0.2 0.4 4.1 .. 0.2 0.3 .. 0.1 0.5 Chad .. .. .. .. .. .. 0.1 0.2 24.1 .. 0.1 0.2 .. 0.0 1.7 Comoros .. .. .. .. .. .. 0.8 1.3 19.0 0.0 0.6 0.9 .. 0.3 3.7 Congo, Dem. Rep. .. .. .. .. .. .. 0.1 0.1 15.5 .. .. 0.0 .. 0.0 0.6 Congo, Rep. .. .. .. .. .. .. 0.7 3.0 59.6 .. 0.4 0.6 .. 0.0 6.7 Côte d’Ivoire .. .. .. .. .. .. 0.6 4.3 64.7 .. 0.5 1.7 0.0 0.2 4.6 Djibouti .. .. .. .. .. .. 1.0 1.4 16.9 0.2 0.9 4.3 0.0 0.2 3.0 Equatorial Guinea .. .. .. .. .. .. 0.3 2.1 67.3 .. 0.4 1.5 .. 0.1 2.1 Eritrea .. .. .. .. .. .. .. 0.8 3.7 .. 0.2 1.0 0.0 0.1 4.9 Ethiopia 2006 24.89 2006 19.51 2006 29.42 0.3 0.4 6.0 .. 0.1 0.7 0.0 0.0 0.5 Gabon .. .. .. .. .. .. 2.2 12.9 94.9 .. 1.0 3.4 .. 1.2 6.7 Gambia, The .. .. .. .. .. .. 0.7 3.0 86.9 .. 1.2 3.5 0.0 0.9 7.6 Ghana 2000 16.55 2000 16.42 2000 16.68 0.3 1.8 64.5 0.0 0.3 1.1 0.0 0.2 5.4 Guinea .. .. .. .. .. .. 0.2 0.8 55.9 .. 0.4 0.5 0.0 0.1 0.9 Guinea-Bissau .. .. .. .. .. .. 0.6 0.9 35.1 .. .. 0.2 .. 0.2 2.3 Kenya .. .. .. .. .. .. 0.8 1.3 50.3 0.0 0.5 1.4 0.0 0.3 10.0 Lesotho .. .. .. .. .. .. 0.8 2.3 33.9 .. .. 0.3 .. 0.2 3.7 Liberia 2007 4.73 2007 5.73 2007 3.73 0.4 0.3 21.3 .. .. .. .. 0.0 0.5 Madagascar 2005 2.27 2005 1.74 2005 2.77 0.3 0.8 31.5 .. 0.2 0.6 .. 0.2 1.6 Malawi .. .. .. .. .. .. 0.3 0.8 16.9 .. 0.1 0.2 .. 0.1 4.7 Mali .. .. .. .. .. .. 0.1 0.5 29.4 .. 0.1 0.8 .. 0.1 1.9 Mauritania .. .. .. .. .. .. 0.3 1.3 68.6 .. 1.0 4.5 .. 0.2 2.3 Mauritius 2009 21.36 2009 18.08 2009 26.25 5.5 38.8 114.9 0.4 10.1 17.6 .. 7.3 22.7 Mozambique .. .. .. .. .. .. 0.4 0.8 26.4 .. 0.3 1.4 .. 0.1 2.7 Namibia 2004 41.7 2004 36.68 2004 47.05 3.7 10.5 62.6 .. 4.1 23.9 0.0 1.6 5.9 Niger 2001 3.16 2001 3.95 2001 1.67 0.1 0.2 17.4 .. 0.1 0.1 .. 0.0 0.8 Nigeria .. .. .. .. .. .. 0.3 0.5 48.2 .. 0.6 0.9 .. 0.1 28.4 Rwanda .. .. .. .. .. .. 0.2 0.7 24.6 .. .. 0.3 .. 0.1 4.5 São Tomé and Príncipe .. .. .. .. .. .. 1.9 3.3 44.1 .. .. 3.9 .. 4.6 16.4 Senegal 2006 14.8 2006 11.92 2006 20.11 0.6 4.6 57.3 0.2 1.6 2.2 0.0 0.4 7.4 Seychelles 2002 20.33 .. .. .. .. 12.4 57.4 130.0 .. 13.6 21.2 .. 7.4 38.7 Sierra Leone 2004 5.15 2004 7.27 2004 3.5 0.3 0.7 20.9 .. .. .. 0.0 0.1 0.3 Somalia .. .. .. .. .. .. 0.2 1.4 8.1 .. .. 0.9 0.0 0.2 1.2 South Africa 2009 48.15 2009 44.59 2009 52.51 9.4 30.2 102.9 0.7 6.6 8.4 0.7 5.5 9.0 Sudan .. .. .. .. .. .. 0.2 1.2 37.2 .. 0.3 10.7 0.0 0.0 9.9 Swaziland .. .. .. .. .. .. 1.6 6.0 59.1 .. 1.1 3.7 0.0 0.9 7.6 Tanzania 2006 8.84 2006 7.39 2006 10.11 0.3 0.8 40.3 .. 0.3 0.9 .. 0.1 1.6 Togo .. .. .. .. .. .. 0.3 1.8 35.8 .. 1.9 3.1 0.0 1.9 5.4 Uganda .. .. .. .. .. .. 0.2 0.8 29.4 .. 0.3 1.7 0.0 0.2 9.8 Zambia 2000 21.36 2000 23.11 2000 19.48 0.8 1.7 34.8 .. 0.7 1.1 0.0 0.2 6.3 Zimbabwe 2002 24.88 2002 28.18 2002 21.4 1.2 4.1 27.0 0.0 1.6 7.6 0.0 0.4 11.4 NORTH AFRICA Algeria 2006 24.3 2004 42.85 2004 46.27 3.2 6.1 101.2 0.1 0.7 1.1 0.0 0.5 13.5 Egypt, Arab Rep. 2007 24.8 2007 17.16 2007 47.89 2.8 9.8 79.1 .. 1.1 3.9 0.0 0.6 20.0 Libya .. .. .. .. .. .. 5.0 12.1 95.1 .. .. 2.2 .. 0.2 5.5 Morocco 2009 21.88 2009 22.77 2009 19.37 1.6 13.1 90.1 .. 1.2 5.7 0.0 0.7 32.2 Tunisia 2005 30.68 2005 31.35 2005 29.32 3.7 11.2 105.8 0.3 2.2 9.7 0.0 2.7 33.6 Note: 0.0 indicates less than 1 but more than 0. a. As of 2010. b. Data are for the most recent year available during the period speci�ed. 58 Part II. Millennium Development Goals Millennium Development Goals Drivers of growth 4.1 Table Doing Business indicators Starting a business Registering property Time required for each Cost Minimum capital Cost Number of procedure (% of GNI (% of GNI Number of Time required (% of property Overall ranking procedures (days) per capita) per capita) procedures (days) value) 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 SUB–SAHARAN AFRICA 9 9 47 45 106.8 97.0 149.0 151.9 7 7 72 67 10.0 9.6 Angola 164 163 8 8 68 68 151.1 163.0 29.0 28.7 7 7 184 184 11.4 11.5 Benin 172 170 7 7 31 31 155.5 152.6 290.8 285.3 4 4 120 120 11.8 11.8 Botswana 50 52 10 10 61 61 2.1 2.2 0.0 0.0 5 5 16 16 5.0 5.0 Burkina Faso 154 151 4 4 14 14 50.3 49.8 428.2 416.2 4 4 59 59 13.2 13.1 Burundi 181 181 11 11 32 32 151.6 129.3 0.0 0.0 5 5 94 94 6.3 5.8 Cameroon 173 168 10 6 35 19 115.0 51.2 182.9 191.8 5 5 93 93 19.2 19.3 Cape Verde 142 132 9 8 24 11 17.0 18.5 38.9 42.4 6 6 73 73 7.6 3.9 Central African Republic 182 182 8 8 22 22 244.9 228.4 507.1 468.6 5 5 75 75 18.6 18.5 Chad 183 183 13 13 75 75 246.4 226.9 369.3 386.7 6 6 44 44 18.7 18.2 Comoros 159 159 11 11 24 24 182.1 176.5 261.8 245.5 5 5 24 24 20.8 20.8 Congo, Dem. Rep. 179 175 14 10 127 84 847.6 735.1 0.0 0.0 6 6 54 54 9.8 7.0 Congo, Rep. 177 177 10 10 160 160 86.5 111.4 96.5 129.8 6 6 55 55 10.3 10.7 Côte d’Ivoire 168 169 10 10 40 40 133.3 133.0 204.9 202.9 6 6 62 62 13.9 13.9 Djibouti 157 158 11 11 37 37 195.1 169.9 500.5 434.1 7 7 40 40 13.2 13.0 Equatorial Guinea 161 164 20 20 136 136 100.4 104.3 12.4 21.3 6 6 23 23 6.2 6.3 Eritrea 180 180 13 13 84 84 76.5 69.2 297.0 268.4 11 11 78 78 9.1 9.1 Ethiopia 103 104 5 5 9 9 18.9 14.1 492.4 367.7 10 10 41 41 2.2 2.1 Gabon 158 156 9 9 58 58 17.8 21.9 26.5 32.7 7 7 39 39 10.5 10.5 Gambia, The 141 146 8 8 27 27 215.1 199.6 0.0 0.0 5 5 66 66 7.6 7.6 Ghana 77 67 7 7 12 12 24.8 20.3 13.4 11.0 5 5 34 34 1.1 1.0 Guinea 178 179 13 13 41 41 139.2 146.6 495.4 519.1 6 6 104 104 13.9 14.0 Guinea-Bissau 175 176 16 17 216 216 181.5 183.3 415.8 415.1 9 9 211 211 6.1 6.1 Kenya 94 98 12 11 34 33 36.5 38.3 0.0 0.0 8 8 64 64 4.2 4.2 Lesotho 137 138 7 7 40 40 27.0 26.0 11.9 12.0 6 6 101 101 8.0 8.0 Liberia 152 155 5 5 20 20 52.9 54.6 0.0 0.0 10 10 50 50 13.2 13.2 Madagascar 138 140 2 2 7 7 6.2 12.9 207.4 248.1 7 7 74 74 9.4 9.8 Malawi 132 133 10 10 39 39 108.0 108.4 0.0 0.0 6 6 88 49 3.2 3.2 Mali 155 153 6 6 8 8 86.9 79.7 334.6 306.8 5 5 29 29 20.0 11.9 Mauritania 167 165 9 9 19 19 34.7 33.6 450.4 412.1 4 4 49 49 5.2 5.2 Mauritius 20 20 5 5 6 6 4.1 3.8 0.0 0.0 4 4 26 26 10.7 10.6 Mozambique 130 126 10 9 26 13 19.3 13.9 0.0 0.0 8 8 42 42 11.3 9.9 Namibia 68 69 10 10 66 66 20.4 18.5 0.0 0.0 9 9 23 23 9.6 9.6 Niger 171 173 9 9 17 17 118.7 118.6 613.7 613.0 4 4 35 35 11.0 11.0 Nigeria 134 137 8 8 31 31 76.7 78.9 0.0 0.0 13 13 82 82 20.9 20.9 Rwanda 70 58 2 2 3 3 10.1 8.8 0.0 0.0 4 4 60 55 0.5 0.4 São Tomé and Príncipe 176 178 10 10 144 144 81.7 77.3 0.0 385.7 7 7 62 62 10.9 10.9 Senegal 151 152 4 4 8 8 63.7 63.1 206.9 205.1 6 6 124 122 20.6 20.6 Seychelles 92 95 10 10 39 39 19.2 17.5 0.0 0.0 4 4 33 33 7.0 7.0 Sierra Leone 143 143 6 6 12 12 118.8 110.7 0.0 0.0 7 7 236 86 12.4 12.2 Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa 32 34 6 6 22 22 5.9 6.0 0.0 0.0 6 6 24 24 8.7 8.8 Sudan 153 154 10 10 36 36 36.0 33.6 0.0 0.0 6 6 9 9 3.0 3.0 Swaziland 126 118 12 12 60 56 33.9 33.0 0.5 0.5 9 9 44 44 7.1 7.1 Tanzania 125 128 12 12 29 29 36.8 30.9 0.0 0.0 9 9 73 73 4.4 4.4 Togo 162 160 7 7 75 75 205.0 178.1 514.0 486.9 5 5 295 295 13.1 13.0 Uganda 129 122 18 18 25 25 84.4 94.4 0.0 0.0 13 13 77 77 3.5 3.2 Zambia 84 76 6 6 18 18 28.4 27.9 1.3 0.0 6 5 39 40 6.6 6.6 Zimbabwe 156 157 9 9 97 90 353.8 182.8 0.0 0.0 5 5 31 31 10.1 8.5 NORTH AFRICA 42 42 9 9 13.5 13.5 12.5 10.0 10.7 11.4 8 8 51 51 4.8 4.7 Algeria 136 136 14 14 24 24 12.1 12.9 31.0 34.4 11 11 47 47 7.1 7.1 Egypt, Arab Rep. 99 94 6 6 7 7 16.1 6.3 0.0 0.0 7 7 72 72 0.9 0.8 Libya .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco 114 114 6 6 12 12 16.1 15.8 11.8 11.2 8 8 47 47 4.9 4.9 Tunisia 58 55 10 10 11 11 5.7 5.0 0.0 0.0 4 4 39 39 6.1 6.1 (continued) Private sector development Part III. Development outcomes 59 Drivers of growth Table 4.1 Doing Business indicators (continued) Protecting investors (0 least protection to Enforcing contracts Dealing with construction permits 10 most protection) Cost Number of Time required Cost Number of Time required (% of GNI Disclosure Director liability procedures (days) (% of debt) procedures (days) per capita) index index 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 SUB–SAHARAN AFRICA 39 39 658 652 49.0 49.7 18 18 245 238 1,993.4 1,775.2 5 5 3 3 Angola 46 46 1,011 1,011 44.4 44.4 12 12 328 328 597.7 694.3 5 5 6 6 Benin 42 42 825 825 64.7 64.7 15 15 410 320 254.4 249.6 6 6 1 1 Botswana 29 29 687 625 28.1 28.1 24 24 167 167 246.2 264.5 7 7 8 8 Burkina Faso 37 37 446 446 83.0 81.7 15 15 132 122 721.2 576.1 6 6 1 1 Burundi 44 44 832 832 38.6 38.6 25 25 212 212 8,262.0 7,047.6 4 4 1 1 Cameroon 43 43 800 800 46.6 46.6 14 14 227 213 1,178.4 1,235.8 6 6 1 1 Cape Verde 37 37 425 425 21.8 21.8 18 18 120 120 523.3 570.7 1 1 5 5 Central African Republic 43 43 660 660 82.0 82.0 21 21 239 239 275.2 259.5 6 6 1 1 Chad 41 41 743 743 45.7 45.7 14 14 164 164 6,383.4 6,684.4 6 6 1 1 Comoros 43 43 506 506 89.4 89.4 18 18 164 164 72.6 68.1 6 6 1 1 Congo, Dem. Rep. 43 43 625 625 151.8 151.8 14 14 248 128 4,505.8 2,692.2 3 3 3 3 Congo, Rep. 44 44 560 560 53.2 53.2 17 17 169 169 179.3 241.1 6 6 1 1 Côte d’Ivoire 33 33 770 770 41.7 41.7 22 21 629 592 230.9 227.6 6 6 1 1 Djibouti 40 40 1,225 1,225 34.0 34.0 16 16 179 179 2,145.6 1,862.8 5 5 2 2 Equatorial Guinea 40 40 553 553 18.5 18.5 18 18 201 201 128.4 220.7 6 6 1 1 Eritrea 39 39 405 405 22.6 22.6 .. .. .. .. .. .. 4 4 5 5 Ethiopia 37 37 620 620 15.2 15.2 12 12 128 128 562.0 419.6 4 4 4 4 Gabon 38 38 1,070 1,070 34.3 34.3 16 16 210 210 34.5 42.9 6 6 1 1 Gambia, The 32 32 434 434 37.9 37.9 17 17 146 146 336.4 314.9 2 2 1 1 Ghana 36 36 487 487 23.0 23.0 18 18 220 220 1,099.0 1,017.7 7 7 5 5 Guinea 50 50 276 276 45.0 45.0 32 32 255 255 249.6 419.0 6 6 1 1 Guinea-Bissau 41 40 1,140 1,140 25.0 25.0 15 15 167 167 2,020.0 1,075.0 6 6 1 1 Kenya 40 40 465 465 47.2 47.2 11 11 120 120 161.7 167.8 3 3 2 2 Lesotho 41 41 785 785 19.5 19.5 15 15 601 601 1,278.8 1,290.7 2 2 1 1 Liberia 41 41 1,280 1,280 35.0 35.0 24 24 77 77 28,295.9 29,574.4 4 4 1 1 Madagascar 38 38 871 871 42.4 42.4 16 16 178 178 630.7 654.9 5 5 6 6 Malawi 42 42 432 312 142.4 94.1 21 21 213 268 1,311.3 1,316.7 4 4 7 7 Mali 36 36 626 620 52.0 52.0 14 15 185 168 818.5 505.0 6 6 1 1 Mauritania 46 46 370 370 23.2 23.2 25 25 201 201 506.3 463.2 5 5 3 3 Mauritius 36 36 720 645 17.4 17.4 18 18 107 107 35.5 32.3 6 6 8 8 Mozambique 30 30 730 730 142.5 142.5 17 17 381 381 632.0 530.3 5 5 4 4 Namibia 33 33 270 270 35.8 35.8 12 12 139 139 124.7 113.0 5 5 5 5 Niger 39 39 545 545 59.6 59.6 17 17 265 265 2,355.0 2,352.3 6 6 1 1 Nigeria 40 40 457 457 32.0 32.0 18 18 350 350 573.4 597.5 5 5 7 7 Rwanda 24 24 260 230 78.7 78.7 14 14 210 195 456.1 353.6 7 7 9 9 São Tomé and Príncipe 43 43 1,185 1,185 50.5 50.5 13 13 255 255 631.4 565.1 3 3 1 1 Senegal 44 44 780 780 26.5 26.5 16 16 220 210 463.1 459.0 6 6 1 1 Seychelles 37 37 720 720 14.3 15.4 20 20 144 144 30.3 38.0 4 4 8 8 Sierra Leone 40 40 515 515 149.5 149.5 25 25 283 252 368.5 343.3 6 6 7 7 Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa 30 30 600 600 33.2 33.2 17 17 174 174 24.5 23.1 8 8 8 8 Sudan 53 53 810 810 19.8 19.8 19 19 271 271 206.4 192.2 0 0 6 6 Swaziland 40 40 972 972 56.1 56.1 14 14 116 116 147.1 143.0 0 2 1 5 Tanzania 38 38 462 462 14.3 14.3 22 22 328 328 3,281.3 2,756.3 3 3 4 4 Togo 41 41 588 588 47.5 47.5 15 15 277 277 1,285.3 1,241.9 6 6 1 1 Uganda 38 38 510 490 44.9 44.9 18 18 171 171 1,510.5 1,287.8 2 2 5 5 Zambia 35 35 471 471 38.7 38.7 17 17 254 254 2,793.8 2,454.2 3 3 6 6 Zimbabwe 38 38 410 410 32.0 113.1 17 17 1012 1012 13,770.3 8,020.6 8 8 1 1 NORTH AFRICA 42 42 705 705 23.8 23.8 22 22 176 180 408.3 362.0 6 7 4 4 Algeria 46 46 630 630 21.9 21.9 22 22 240 240 39.6 44.0 6 6 6 6 Egypt, Arab Rep. 41 41 1,010 1,010 26.2 26.2 25 25 218 218 331.6 293.7 8 8 3 3 Libya .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco 40 40 615 615 25.2 25.2 19 19 163 163 263.7 251.5 6 7 2 2 Tunisia 39 39 565 565 21.8 21.8 20 20 84 97 998.3 858.7 5 5 5 5 a. Average of the disclosure, director liability, and shareholder suits indexes. b. Average of the rigidity of hours, dif�culty of hiring, and dif�culty of �ring indexes. 60 Part III. Development outcomes Private sector development Protecting investors (0 least protection to 10 most protection) Employing workers Rigidity of hours Difficulty of hiring Difficulty of firing Rigidity of employment Shareholder suits Investor protection index (0 least rigid index (0 least difficult index (0 least difficult Firing cost indexb (0 least rigid index indexa to 100 most rigid) to 100 most difficult) to 100 most difficult) (weeks of wages) to 100 most rigid) 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 2009 2010 5 5 4.3 4.4 30 30 38 38 40 40 68 67 36 36 6 6 5.7 5.7 60 60 67 67 70 70 58 58 66 66 3 3 3.3 3.3 40 40 39 39 40 40 36 36 40 40 3 3 6.0 6.0 0 0 0 0 40 40 90 90 13 13 4 4 3.7 3.7 20 20 33 33 10 10 34 34 21 21 5 5 3.3 3.3 53 53 0 0 30 30 26 26 28 28 6 6 4.3 4.3 20 20 28 28 70 70 33 33 39 39 6 6 4.0 4.0 33 33 33 33 70 70 93 93 46 46 5 5 4.0 4.0 40 40 61 61 50 50 22 22 50 50 3 3 3.3 3.3 20 20 39 39 40 40 36 36 33 33 5 5 4.0 4.0 40 40 39 39 40 40 100 100 40 40 4 4 3.3 3.3 47 47 50 72 70 70 31 31 63 63 3 3 3.3 3.3 40 40 78 78 70 70 33 33 63 63 3 3 3.3 3.3 47 47 33 33 20 20 49 49 33 33 0 0 2.3 2.3 40 40 67 67 30 30 56 56 46 46 4 4 3.7 3.7 60 60 67 67 70 70 133 133 66 66 5 5 4.7 4.7 40 40 0 0 20 20 69 69 20 20 5 5 4.3 4.3 20 20 33 33 30 30 40 40 28 28 3 3 3.3 3.3 60 60 17 17 80 80 43 43 52 52 5 5 2.7 2.7 40 40 0 0 40 40 26 26 27 27 6 6 6.0 6.0 20 20 11 11 50 50 178 178 27 27 1 1 2.7 2.7 20 20 33 33 20 20 26 26 24 24 5 5 4.0 4.0 27 27 67 67 70 70 87 87 54 54 10 10 5.0 5.0 0 0 22 22 30 30 47 47 17 17 8 8 3.7 3.7 20 20 22 22 0 0 44 44 14 14 6 6 3.7 3.7 20 20 22 22 40 40 84 84 27 27 6 6 5.7 5.7 40 40 89 89 40 40 30 30 56 56 5 5 5.3 5.3 0 0 44 44 20 20 84 84 21 21 4 4 3.7 3.7 20 20 33 33 40 40 31 31 31 31 3 3 3.7 3.7 20 20 56 56 40 40 31 31 39 39 9 9 7.7 7.7 13 33 0 0 40 20 35 4 18 18 9 9 6.0 6.0 33 33 67 67 20 20 134 134 40 40 6 6 5.3 5.3 20 20 0 0 20 20 24 24 13 13 3 3 3.3 3.3 53 53 100 100 50 50 35 35 68 68 5 5 5.7 5.7 0 0 0 0 20 20 50 50 7 7 3 3 6.3 6.3 40 0 44 11 30 10 26 26 7 7 6 6 3.3 3.3 67 67 50 50 60 60 91 91 59 59 2 2 3.0 3.0 53 53 72 72 50 50 38 38 59 59 5 5 5.7 5.7 13 13 44 44 50 50 39 39 36 36 6 6 6.3 6.3 40 40 33 33 50 50 189 189 41 41 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 8 8 8.0 8.0 20 20 56 56 30 30 24 24 35 35 4 4 3.3 3.3 20 20 39 39 50 50 118 118 36 36 5 6 2.0 4.3 0 0 11 11 20 20 53 53 10 10 8 8 5.0 5.0 13 13 100 100 50 50 18 18 54 54 4 4 3.7 3.7 40 40 61 83 40 40 36 36 54 54 5 5 4.0 4.0 0 0 0 0 0 0 13 13 0 0 7 7 5.3 5.3 33 33 22 11 20 20 178 178 21 21 4 4 4.3 4.3 40 40 0 0 60 60 446 446 33 33 4 4 4.7 4.8 28 28 43 40 58 58 63 63 42 42 4 4 5.3 5.3 40 40 44 44 40 40 17 17 41 41 5 5 5.3 5.3 20 20 0 0 60 60 132 132 27 27 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1 1 3.0 3.3 40 40 100 89 50 50 85 85 60 60 6 6 5.3 5.3 13 13 28 28 80 80 17 17 40 40 Private sector development Part III. Development outcomes 61 Drivers of growth Table 4.2 Investment climate Enterprise Surveys Private Domestic Firms that Viewed by �rms as a major constraint (% of �rms) sector �xed Net foreign credit to believe the court capital direct private system is fair, Crime, Customs formation investment sector impartial, and theft, and Tax Labor Labor Transpor- and trade (% of GDP) ($ millions) (% of GDP) uncorrupt (%) Corruption discord rates Finance Electricity regulations skills tation regulations 2009a 2009a 2009a 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b SUB–SAHARAN AFRICA 13.4 .. 64.4 Angola 2.4 2,198.5 21.2 23.7 75.6 28.1 26.4 38.5 35.7 26.1 25.9 25.3 35.8 Benin 15.4 .. 22.2 9.6 67.8 52.7 67.6 70.3 51.9 16.1 28.2 46.7 51.8 Botswana 8.9 251.3 25.5 79.5 27.4 22.6 16.9 25.5 34.8 14.0 32.2 20.1 15.8 Burkina Faso .. .. 17.5 38.7 70.5 42.2 75.7 75.0 53.9 26.0 37.5 40.3 42.6 Burundi .. 0.3 21.7 .. .. .. .. .. .. .. .. .. .. Cameroon 12.4 –50.0 11.3 32.6 61.3 41.5 45.9 55.1 58.6 21.5 37.8 27.7 26.3 Cape Verde 42.7 120.0 64.0 59.5 29.8 62.3 51.8 36.7 53.1 5.7 49.2 24.0 27.2 Central African Republic 6.9 .. 7.0 .. .. .. .. .. .. .. .. .. .. Chad 21.8 .. 5.2 31.0 67.2 45.8 59.7 46.5 74.6 28.4 53.1 45.5 57.4 Comoros 7.7 .. 16.0 .. .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 6.1 .. 7.5 17.2 72.7 63.3 39.5 73.3 51.7 20.0 65.0 38.8 54.0 Congo, Rep. 13.5 .. 4.8 32.3 65.0 44.1 40.9 44.8 71.1 24.5 51.5 48.4 45.9 Côte d’Ivoire 8.3 380.9 17.1 35.3 75.0 53.8 30.5 66.6 39.8 6.1 26.7 38.2 19.4 Djibouti .. 96.9 29.3 .. .. .. .. .. .. .. .. .. .. Equatorial Guinea 16.1 .. 7.7 .. .. .. .. .. .. .. .. .. .. Eritrea .. .. 16.6 100.0 0.0 0.0 1.1 0.9 0.2 0.2 1.2 2.2 2.0 Ethiopia 5.9 221.5 .. .. .. .. .. .. .. .. .. .. .. Gabon 23.2 .. 10.1 41.3 41.4 34.1 30.9 30.4 58.0 16.4 42.7 48.8 35.1 Gambia, The .. 39.4 18.9 .. .. .. .. .. .. .. .. .. .. Ghana 11.6 1,677.8 .. .. .. .. .. .. .. .. .. .. .. Guinea 17.0 140.9 .. .. .. .. .. .. .. .. .. .. .. Guinea-Bissau .. .. 5.6 .. .. .. .. .. .. .. .. .. .. Kenya 14.5 94.5 31.5 .. .. .. .. .. .. .. .. .. .. Lesotho 17.3 62.9 13.5 33.2 46.7 33.5 47.1 28.6 44.3 11.3 16.5 19.8 21.7 Liberia .. 217.8 16.1 44.3 31.2 26.8 19.0 35.0 59.1 2.6 5.1 39.3 15.6 Madagascar 29.4 .. 11.5 28.8 42.7 48.1 40.8 39.4 54.6 2.2 17.0 26.6 18.7 Malawi 14.9 .. 14.2 74.3 12.8 22.8 15.6 51.0 37.6 2.7 21.8 24.6 11.0 Mali .. .. 17.4 42.7 24.8 17.3 26.3 48.2 33.5 6.4 12.2 21.4 16.9 Mauritania .. .. .. .. .. .. .. .. .. .. .. .. .. Mauritius 19.5 218.9 85.1 63.6 50.7 41.5 25.1 46.3 42.9 8.8 45.7 45.8 17.7 Mozambique 7.9 878.4 25.1 .. .. .. .. .. .. .. .. .. .. Namibia 15.6 528.1 46.8 .. .. .. .. .. .. .. .. .. .. Niger .. .. 12.2 49.6 83.7 44.2 60.4 62.0 63.2 5.3 37.1 50.0 31.6 Nigeria .. 5,647.2 37.6 .. .. .. .. .. .. .. .. .. .. Rwanda 10.6 118.7 .. .. .. .. .. .. .. .. .. .. .. São Tomé and Príncipe .. 7.2 34.6 .. .. .. .. .. .. .. .. .. .. Senegal 17.8 .. 24.7 .. .. .. .. .. .. .. .. .. .. Seychelles 20.9 242.9 25.1 .. .. .. .. .. .. .. .. .. .. Sierra Leone 7.4 74.3 9.3 29.7 36.9 14.2 42.5 34.6 53.4 11.4 16.0 29.9 26.9 Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa 13.4 4,042.4 147.1 .. .. .. .. .. .. .. .. .. .. Sudan 16.3 2,682.2 12.3 .. .. .. .. .. .. .. .. .. .. Swaziland 3.0 58.7 25.0 .. .. .. .. .. .. .. .. .. .. Tanzania 20.5 414.5 15.3 .. .. .. .. .. .. .. .. .. .. Togo .. .. 21.9 14.1 70.2 22.6 43.5 58.6 50.9 3.1 17.2 32.1 27.5 Uganda 17.5 603.7 13.1 .. .. .. .. .. .. .. .. .. .. Zambia 17.8 699.2 12.0 .. .. .. .. .. .. .. .. .. .. Zimbabwe 1.7 .. .. .. .. .. .. .. .. .. .. .. .. NORTH AFRICA 19.9 9,702.9 35.2 Algeria 33.0 .. 16.2 .. .. .. .. .. .. .. .. .. .. Egypt, Arab Rep. 10.9 6,140.4 36.2 .. .. .. .. .. .. .. .. .. .. Libya .. 546.0 10.9 .. .. .. .. .. .. .. .. .. .. Morocco 24.8 1,491.3 64.4 .. .. .. .. .. .. .. .. .. .. Tunisia 23.2 1,525.2 68.4 .. .. .. .. .. .. .. .. .. .. a. Provisional. b. Data are for the most recent year available during the period speci�ed. 62 Part III. Development outcomes Private sector development Enterprise Surveys Regulation and tax administration Interest rate Time dealing Average time to clear customs spread Market Time to prepare, Highest marginal with of�cials (days) (lending rate Listed capitalization of Turnover ratio for Number of tax �le, and pay taxes Total tax rate tax rate, corporate (% of minus deposit domestic listed companies traded stocks payments (hours) (% of pro� t) (%) management time) Direct exports Imports rate) companies (% of GDP) (%) 2010 2010 2010 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009 2009 2009a 2009a 37 310 67 .. .. .. .. 31 282 53.2 35.0 12.2 6.7 11.4 8.1 .. .. .. 55 270 66.0 .. 20.7 9.6 33.0 .. .. .. .. 19 152 19.5 25.0 10.2 6.2 3.7 6.3 20 33.8 2.7 46 270 44.9 .. 22.2 7.4 16.4 .. .. .. .. 32 211 153.4 .. .. .. .. .. .. .. .. 44 654 49.1 .. 7.0 15.1 24.0 .. .. .. .. 43 186 37.1 .. 3.9 .. 20.5 8.1 .. .. .. 54 504 203.8 .. .. .. .. .. .. .. .. 54 732 65.4 .. 20.8 11.9 27.5 .. .. .. .. 20 100 217.9 .. .. .. .. 8.6 .. .. .. 32 336 339.7 38.0 29.4 18.0 45.4 49.5 .. .. .. 61 606 65.5 .. 6.0 .. 31.4 .. .. .. .. 64 270 44.4 25.0 1.6 16.6 31.2 .. 38 26.4 2.0 35 90 38.7 .. .. .. .. .. .. .. .. 46 492 59.5 .. .. .. .. .. .. .. .. 18 216 84.5 .. 0.5 9.6 20.1 .. .. .. .. 19 198 31.1 .. .. .. .. .. .. .. .. 26 488 43.5 .. 2.8 3.8 10.3 .. .. .. .. 50 376 292.3 .. .. .. .. 11.5 .. .. .. 33 224 32.7 25.0 .. .. .. .. 35 9.6 2.0 56 416 54.6 .. .. .. .. .. .. .. .. 46 208 45.9 .. .. .. .. .. .. .. .. 41 393 49.7 .. .. .. .. 8.8 55 36.6 4.6 21 324 19.6 .. 5.6 5.4 4.4 8.2 .. .. .. 32 158 43.7 .. 7.5 .. 6.7 10.1 .. .. .. 23 201 37.7 .. 17.1 14.2 19.3 33.5 .. .. .. 19 157 25.1 .. 3.5 9.9 11.2 21.8 15 29.3 .. 59 270 52.2 .. 2.0 12.9 16.5 .. .. .. .. 38 696 68.4 .. .. .. .. .. .. .. .. 7 161 24.1 15.0 9.4 10.3 9.8 10.8 88 55.2 8.1 37 230 34.3 32.0 .. .. .. 6.2 .. .. .. 37 375 9.6 35.0 .. .. .. 4.9 7 9.1 3.0 41 270 46.5 .. 22.9 2.6 9.3 .. .. .. .. 35 938 32.2 30.0 .. .. .. 5.1 214 19.3 11.0 26 148 31.3 .. .. .. .. .. .. .. .. 42 424 33.3 .. .. .. .. 19.7 .. .. .. 59 666 46.0 .. .. .. .. .. .. .. .. 16 76 44.1 .. .. .. .. 5.6 .. .. .. 29 357 235.6 .. 7.4 .. 12.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 9 200 30.5 34.6 .. .. .. 3.2 363 247.0 57.3 42 180 36.1 35.0 .. .. .. .. .. .. .. 33 104 36.8 30.0 .. .. .. 6.0 5 .. .. 48 172 45.2 30.0 .. .. .. 7.1 15 .. .. 53 270 50.8 .. 2.7 6.7 9.0 .. .. .. .. 32 161 35.7 45.0 .. .. .. 11.2 8 .. .. 37 132 16.1 35.0 .. .. .. 15.0 19 .. .. 49 242 40.3 30.9 .. .. .. .. 94 .. .. 25 347 54.8 5.5 .. .. .. 34 451 72.0 .. .. .. .. 6.3 .. .. .. 29 433 42.6 20.0 .. .. .. 5.5 305 47.7 60.1 .. .. .. 40.0 .. .. .. 3.5 .. .. .. 28 358 41.7 .. .. .. .. .. 78 68.8 45.7 8 144 62.8 30.0 .. .. .. .. 49 23.1 16.2 Private sector development Part III. Development outcomes 63 Drivers of growth Table 4.3 Financial sector infrastructure Macroeconomy Foreign currency sovereign ratings Gross national savings Money and quasi money (M2) Real interest rate Long-term Short-term (% of GDP) (% of GDP) (%) 2010–11b 2010–11b 2008 2009 c 2008 2009 c 2008 2009 c SUB–SAHARAN AFRICA 15.5 15.4 41.0 47.7 .. .. Angola B+ B 23.6 9.7 18.0 31.1 –8.2 22.8 Benin .. .. 10.6 .. 32.9 36.4 .. .. Botswana .. .. 34.8 16.4 39.0 46.8 –0.4 20.6 Burkina Faso .. .. .. .. 22.5 24.8 .. .. Burundi .. .. .. .. 34.2 36.7 –6.9 0.4 Cameroon .. .. .. .. 19.3 21.5 .. .. Cape Verde .. .. 26.7 31.3 85.2 84.2 8.9 6.9 Central African Republic .. .. .. .. 14.4 15.5 .. .. Chad .. .. .. .. 11.8 14.7 .. .. Comoros .. .. .. .. 27.1 28.6 4.7 5.7 Congo, Dem. Rep. .. .. .. .. 12.6 14.3 19.9 27.0 Congo, Rep. .. .. .. .. 16.0 22.2 .. .. Côte d’Ivoire .. .. 12.3 14.8 27.8 29.6 .. .. Djibouti .. .. .. .. 74.5 83.0 1.9 .. Equatorial Guinea .. .. .. .. 6.2 12.3 .. .. Eritrea .. .. .. .. 109.8 112.3 .. .. Ethiopia .. .. 17.1 16.1 30.9 0.0 –17.2 .. Gabon .. .. .. .. 16.8 22.1 .. .. Gambia, The .. .. 10.4 18.8 49.5 55.0 19.6 24.1 Ghana B+ B 8.8 15.5 23.6 0.0 .. .. Guinea .. .. 1.4 7.7 0.0 0.0 .. .. Guinea-Bissau .. .. .. .. 20.8 23.3 .. .. Kenya .. .. 14.2 15.4 40.3 42.7 1.9 7.6 Lesotho BB- B 33.5 28.1 34.0 38.6 2.4 9.2 Liberia .. .. –2.1 .. 27.8 35.4 3.6 6.3 Madagascar .. .. .. .. 20.5 22.0 32.8 33.8 Malawi .. .. .. .. 19.7 23.5 15.0 15.6 Mali .. .. .. .. 25.8 25.2 .. .. Mauritania .. .. .. .. 0.0 0.0 .. .. Mauritius .. .. 16.7 16.7 97.0 104.0 13.6 17.5 Mozambique .. .. 3.8 9.1 30.8 35.7 9.4 12.0 Namibia BBB- F3 31.6 26.5 36.5 38.5 –0.5 4.4 Niger .. .. .. .. 15.7 17.1 .. .. Nigeria BB- B .. .. 30.1 37.1 4.1 19.1 Rwanda B B 17.3 15.1 0.0 0.0 3.3 .. São Tomé and Príncipe .. .. .. .. 35.5 35.5 7.6 14.6 Senegal .. .. 16.1 .. 33.5 35.1 .. .. Seychelles B B 1.6 9.2 60.4 59.3 –13.0 –10.3 Sierra Leone .. .. 5.3 7.8 20.6 23.3 12.0 .. Somalia .. .. .. .. 0.0 0.0 .. .. South Africa BBB+ F2 14.9 15.4 78.4 80.2 5.4 4.1 Sudan .. .. 17.4 12.2 17.5 20.3 .. .. Swaziland .. .. 6.9 2.4 24.2 27.6 4.3 5.6 Tanzania .. .. 13.3 21.2 27.6 28.8 4.4 7.1 Togo .. .. .. .. 37.8 42.6 .. .. Uganda .. .. 21.9 17.5 20.8 20.6 13.1 3.8 Zambia B+ B 19.2 19.0 21.5 20.6 6.8 8.3 Zimbabwe .. .. .. .. 0.0 0.0 .. .. NORTH AFRICA 32.5 .. 67.0 75.7 .. .. Algeria .. .. .. .. 54.8 64.1 –5.8 19.2 Egypt, Arab Rep. BB B 23.6 16.7 84.2 79.8 0.1 1.0 Libya B B 67.1 .. 28.3 53.7 –15.5 57.8 Morocco BBB- F3 32.9 31.2 102.5 104.7 .. .. Tunisia BBB- F3 21.3 22.8 60.0 64.2 .. .. a. Data are consolidated for regional security markets where they exist. b. Data are for the most recent year available during the period speci�ed. c. Provisional. 64 Part III. Development outcomes Private sector development Intermediation Capital marketsa Domestic credit to Interest rate spread Ratio of bank Market capitalization Turnover ratio for private sector (lending rate minus nonperforming loans to of listed companies traded stocks (% of GDP) deposit rate) total gross loans (%) Listed domestic companies (% of GDP) (%) 2008 2009c 2008 2009 c 2008 2009 c 2008 2009 c 2008 2009 c 2008 2009c 56.0 64.4 8.6 .. .. .. .. .. .. .. .. .. 12.6 21.2 6.0 8.1 .. .. .. .. .. .. .. .. 20.9 22.2 .. .. .. .. .. .. .. .. .. .. 21.0 25.5 7.9 6.3 .. .. 19 20 26.3 33.8 3.1 2.7 18.4 17.5 .. .. .. .. .. .. .. .. .. .. 20.9 21.7 .. .. .. .. .. .. .. .. .. .. 10.2 11.3 .. .. .. .. .. .. .. .. .. .. 61.1 64.0 6.2 8.1 .. .. .. .. .. .. .. .. 7.0 7.0 .. .. .. .. .. .. .. .. .. .. 3.7 5.2 .. .. .. .. .. .. .. .. .. .. 11.5 16.0 8.0 8.6 .. .. .. .. .. .. .. .. 7.1 7.5 35.4 49.5 .. .. .. .. .. .. .. .. 3.2 4.8 .. .. .. .. .. .. .. .. .. .. 16.3 17.1 .. .. .. .. 38 38 30.2 26.4 4.1 2.0 24.7 29.3 9.4 .. .. .. .. .. .. .. .. .. 4.4 7.7 .. .. .. .. .. .. .. .. .. .. 18.4 16.6 .. .. .. .. .. .. .. .. .. .. 17.8 .. 3.3 .. .. .. .. .. .. .. .. .. 8.5 10.1 .. .. 8.5 9.8 .. .. .. .. .. .. 17.3 18.9 14.1 11.5 .. .. .. .. .. .. .. .. 15.9 .. .. .. 7.7 16.2 35 35 11.9 9.6 5.2 2.0 .. .. .. .. .. .. .. .. .. .. .. .. 4.9 5.6 .. .. .. .. .. .. .. .. .. .. 30.3 31.5 8.7 8.8 9.0 7.9 53 55 36.4 36.6 11.8 4.6 11.1 13.5 8.5 8.2 4.0 4.0 .. .. .. .. .. .. 12.5 16.1 10.4 10.1 .. .. .. .. .. .. .. .. 11.2 11.5 33.5 33.5 .. .. .. .. .. .. .. .. 11.9 14.2 21.8 21.8 .. .. 15 15 43.5 29.3 .. .. 17.2 17.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 87.8 85.1 11.4 10.8 .. .. 41 88 37.0 55.2 8.9 8.1 18.3 25.1 7.3 6.2 1.9 1.8 .. .. .. .. .. .. 44.9 46.8 5.4 4.9 3.1 2.7 7 7 6.9 9.1 2.8 3.0 10.9 12.2 .. .. .. .. .. .. .. .. .. .. 33.9 37.6 3.5 5.1 6.3 6.6 213 214 24.0 19.3 29.3 11.0 .. .. 9.8 .. 12.6 13.1 .. .. .. .. .. .. 29.9 34.6 19.7 19.7 .. .. .. .. .. .. .. .. 24.3 24.7 .. .. 19.1 18.7 .. .. .. .. .. .. 32.3 25.1 7.8 5.6 .. .. .. .. .. .. .. .. 7.1 9.3 14.8 .. 17.9 16.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 145.1 147.1 3.5 3.2 3.9 5.9 425 363 177.7 247.0 60.6 57.3 10.5 12.3 .. .. .. .. .. .. .. .. .. .. 23.6 25.0 6.7 6.0 7.6 8.1 7 5 .. .. .. .. 16.1 15.3 6.7 7.1 .. .. 14 15 6.2 .. .. .. 18.7 21.9 .. .. .. .. .. .. .. .. .. .. 13.9 13.1 9.8 11.2 2.2 4.2 6 8 .. .. .. .. 15.2 12.0 12.5 15.0 .. .. 19 19 .. .. .. .. .. .. .. .. .. .. 81 94 .. .. .. .. 32.6 35.2 5.7 5.5 14.8 13.2 .. .. .. .. .. .. 13.2 16.2 6.3 6.3 .. .. .. .. .. .. .. .. 42.8 36.2 5.7 5.5 14.8 13.4 373 305 52.7 47.7 61.9 60.1 6.8 10.9 3.5 3.5 .. .. .. .. .. .. .. .. 63.2 64.4 .. .. 6.0 5.5 77 78 74.0 68.8 31.1 45.7 65.8 68.4 .. .. 15.5 13.2 49 49 15.6 23.1 25.5 16.2 Private sector development Part III. Development outcomes 65 Drivers of growth Table 5.1 International trade and tariff barriers Trade Annual average Annual growth Exports of Imports of Exports of Imports of (% of GDP) (%) Merchan- goods and goods and goods and goods and Exports of Imports of Exports of Imports of Terms of Total dise Services services services services services goods and goods and goods and goods and trade index (% of GDP) (% of GDP) (% of GDP) ($ millions) ($ millions) (% of GDP) (% of GDP) services services services services (2000 = 100) 2009 a 2009 a 2009 a 2009 a 2009 a 2009 a 2009a 2000–09 2000–09 2009a 2009a 2009a SUB–SAHARAN AFRICA 63.3 53.6 13.4 298,039 317,933 29.8 33.5 32.4 33.9 .. .. .. Angola 98.5 75.6 26.2 39,432 34,901 52.2 46.2 73.6 54.4 .. .. .. Benin 42.0 45.7 .. 922 1,875 13.8 28.2 14.1 27.3 .. .. .. Botswana 78.2 69.2 15.9 3,971 5,273 33.6 44.6 45.5 37.0 –28.0 –9.3 82.7 Burkina Faso .. 36.0 .. .. .. .. .. 9.7 24.0 .. .. .. Burundi .. 35.2 17.1 .. .. .. .. 8.7 31.0 .. .. .. Cameroon 57.5 32.7 15.2 5,896 6,856 26.6 30.9 22.9 23.3 –4.8 –5.2 106.9 Cape Verde 89.0 48.1 52.3 366 1,013 23.6 65.4 24.1 60.6 11.9 13.0 58.7 Central African Republic 36.9 20.9 .. 290 449 14.5 22.4 14.5 21.4 .. .. .. Chad 112.2 69.5 .. 2,879 4,794 42.1 70.1 39.4 56.5 .. .. .. Comoros 62.8 30.4 .. 79 258 14.7 48.2 15.2 37.0 .. .. .. Congo, Dem. Rep. 31.3 63.4 .. 1,017 2,298 9.6 21.7 24.4 32.6 5.4 –11.9 85.9 Congo, Rep. 122.8 88.7 .. 6,884 4,876 71.9 50.9 79.1 54.9 .. .. .. Côte d’Ivoire 75.5 64.2 14.8 9,722 7,866 41.7 33.8 46.6 37.5 9.3 11.0 96.1 Djibouti .. 46.2 42.9 .. .. .. .. 40.7 53.6 .. .. .. Equatorial Guinea 115.6 137.3 .. 7,713 4,328 74.1 41.6 89.5 54.2 .. .. .. Eritrea 24.7 29.6 .. 84 379 4.5 20.3 8.1 53.0 .. .. .. Ethiopia 39.4 33.5 14.4 3,011 8,229 10.6 28.8 12.9 29.7 6.9 16.4 115.3 Gabon 85.5 66.0 .. 5,773 3,685 52.2 33.3 60.7 32.1 –4.9 –2.8 124.4 Gambia, The 80.6 43.5 25.5 223 368 30.4 50.1 38.8 53.6 2.5 3.8 71.3 Ghana 71.8 52.1 18.0 7,982 10,820 30.5 41.3 35.8 53.3 .. –14.1 .. Guinea 86.2 58.7 9.8 1,671 1,865 40.7 45.4 30.3 33.3 3.0 16.8 98.8 Guinea-Bissau .. 41.2 .. .. .. .. .. 30.1 55.3 .. .. .. Kenya 63.5 49.8 16.1 7,413 11,253 25.2 38.3 25.4 34.7 –7.0 –0.2 114.5 Lesotho 163.0 171.0 12.5 809 1,764 51.2 111.7 52.9 110.4 –17.2 –1.1 157.3 Liberia .. 80.1 162.0 .. .. .. .. 28.9 75.6 .. .. .. Madagascar 80.7 51.1 .. 2,447 4,484 28.5 52.2 27.5 42.5 9.3 –10.5 88.3 Malawi 67.8 55.4 .. 1,420 1,783 30.0 37.7 25.9 41.1 .. .. .. Mali .. 52.7 .. .. .. .. .. 28.5 39.6 .. .. .. Mauritania 117.3 92.6 .. 1,504 2,043 49.7 67.6 41.7 69.2 .. .. .. Mauritius 107.5 66.0 44.8 4,161 5,074 48.4 59.1 58.4 63.0 –4.8 –4.6 81.0 Mozambique 68.9 60.4 17.1 2,454 4,287 25.1 43.8 29.0 44.0 2.4 14.0 49.3 Namibia 106.5 93.6 12.2 4,319 5,548 46.6 59.9 44.2 48.9 –14.0 5.3 138.2 Niger .. 44.6 .. .. .. .. .. 16.2 25.0 .. .. .. Nigeria 63.0 52.9 11.4 62,054 46,999 35.9 27.2 42.3 31.0 .. .. .. Rwanda 40.9 27.2 16.5 610 1,524 11.7 29.2 10.4 26.3 .. .. .. São Tomé and Príncipe .. 64.4 15.4 .. .. .. .. .. .. .. .. .. Senegal 68.0 53.8 .. 3,082 5,637 24.0 44.0 26.7 42.2 –8.8 –17.1 91.9 Seychelles 246.9 162.6 93.2 912 975 119.3 127.6 94.0 105.2 10.8 1.7 100.0 Sierra Leone 44.2 38.7 8.7 305 554 15.7 28.5 19.9 33.8 .. .. .. Somalia .. .. .. .. .. .. .. .. .. .. .. .. South Africa 55.4 47.6 9.4 77,883 80,328 27.3 28.1 29.7 29.3 –19.5 –17.4 126.3 Sudan 35.9 32.1 5.6 8,230 11,391 15.1 20.8 16.6 22.0 .. .. .. Swaziland 136.3 103.3 25.4 1,794 2,295 59.8 76.5 83.5 91.2 –6.1 –3.5 100.0 Tanzania 58.4 44.2 16.7 4,963 7,511 23.2 35.2 20.0 28.7 15.5 14.1 119.3 Togo .. 80.6 .. .. .. .. .. 36.0 53.7 .. .. .. Uganda 58.0 42.3 14.9 3,753 5,557 23.4 34.6 15.1 26.9 16.2 25.2 67.2 Zambia 67.8 63.3 7.4 4,560 4,118 35.6 32.2 33.8 38.0 .. .. .. Zimbabwe 101.7 91.9 .. 2,040 3,678 36.3 65.4 36.5 46.4 5.2 36.0 102.7 NORTH AFRICA 68.7 53.3 18.0 200,244 193,682 32.1 36.6 35.6 31.4 –10.3 –7.5 .. Algeria 76.5 60.1 .. 56,798 50,772 40.4 36.1 42.0 24.6 –3.0 16.7 103.3 Egypt, Arab Rep. 56.9 36.1 18.8 47,185 60,048 25.0 31.9 25.1 29.1 –14.5 –17.9 89.6 Libya .. 73.4 8.7 .. .. .. .. 56.9 27.8 .. .. .. Morocco 68.1 51.2 21.1 26,121 36,088 28.6 39.5 31.4 37.6 –13.1 –6.0 99.5 Tunisia 107.3 84.8 21.4 20,568 21,894 52.0 55.3 49.4 52.6 –1.6 6.7 106.0 66 Part III. Development outcomes Trade and regional integration Structure of merchandise exports Structure of merchandise imports (% of total) (% of total) Agricultural Agricultural Food raw materials Fuel Ores and metals Manufactures Food raw materials Fuel Ores and metals Manufactures 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 13.7 3.0 36.9 15.3 30.8 11.2 1.0 16.8 1.7 66.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 5.2 0.2 0.3 16.1 78.0 13.1 0.9 13.3 2.1 69.5 26.8 60.5 0.0 0.6 12.1 15.7 0.7 23.6 0.7 59.0 67.5 4.8 1.9 4.8 20.6 12.5 1.4 2.4 0.6 80.9 .. .. .. .. .. .. .. .. .. .. 72.6 0.0 .. 0.7 26.7 29.4 1.3 11.6 1.2 56.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 48.2 5.7 30.0 0.4 15.2 23.2 0.8 25.0 1.2 48.6 0.4 0.0 6.5 0.3 90.7 29.3 0.6 6.5 0.8 62.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 77.5 11.9 0.0 0.8 8.7 10.9 0.5 15.9 1.2 71.5 .. .. .. .. .. .. .. .. .. .. 53.0 1.0 0.0 6.9 39.1 34.3 1.3 15.6 0.6 48.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 44.0 13.2 4.2 2.0 36.6 15.4 1.4 21.5 1.6 60.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 28.8 5.2 4.9 3.0 57.2 10.7 0.6 10.4 0.4 77.7 86.6 3.8 0.1 0.8 8.6 13.1 1.0 10.4 1.0 74.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 32.4 0.9 0.0 0.7 64.6 21.7 2.4 15.6 1.1 59.2 23.3 3.1 17.5 3.9 11.7 15.4 1.2 15.4 0.5 55.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 4.5 1.1 90.4 0.2 3.6 11.8 1.0 1.0 1.8 83.6 42.3 1.7 0.1 31.9 19.4 12.4 1.5 7.8 1.8 76.1 92.4 0.7 0.0 0.0 3.0 35.9 0.9 15.4 1.1 46.6 29.5 1.1 24.0 3.4 41.3 24.2 1.5 23.2 0.9 50.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 10.2 1.9 11.1 29.3 47.5 6.5 0.9 21.5 1.3 64.3 5.6 1.4 92.1 0.3 0.4 14.9 1.1 4.0 0.9 77.8 .. .. .. .. .. .. .. .. .. .. 35.5 9.8 1.0 24.6 24.6 8.9 0.9 22.6 1.0 66.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 7.5 1.4 0.9 81.1 8.4 6.5 0.7 13.9 13.3 65.1 19.4 23.1 0.9 22.3 34.3 22.4 0.4 12.9 5.2 57.6 6.3 0.4 63.6 2.4 27.2 .. .. .. .. .. 0.3 0.0 97.7 0.5 1.6 16.3 1.5 1.1 1.4 79.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 22.1 1.6 2.0 8.8 65.5 11.2 2.1 20.5 2.5 63.0 9.2 0.5 13.6 1.3 75.4 8.6 2.0 11.5 3.1 74.8 (continued) Trade and regional integration Part III. Development outcomes 67 Drivers of growth Table 5.1 International trade and tariff barriers (continued) Tariff barriers, all products (%) Export indexes Competitiveness Share of (0 low to 1 high) indicator (%) lines with Share of Share of Simple Dispersion inter- lines with Share of lines with Diversi- Concen- Sectoral Global Binding mean Simple around Weighted national domestic lines that specific fication tration effect effect coverage bound rate mean tariff the mean mean tariff peaks peaks are bound rates 2009 2009 2005–09 2005–09 2010 2010 2010 2010 2010 2010 2010 2009 2010 SUB–SAHARAN AFRICA 0.61 0.42 .. .. .. 0.9 .. .. .. 51.9 .. Angola 0.82 0.95 –0.2 16.0 .. .. .. 0.9 .. .. .. 100.0 .. Benin 0.75 0.35 –1.3 –13.9 39.5 28.7 13.3 0.6 15.4 50.2 0.0 39.3 0.0 Botswana 0.86 0.45 –15.8 –6.4 96.1 19.0 8.8 1.5 5.2 20.2 8.5 96.6 0.0 Burkina Faso 0.72 0.34 –8.2 5.7 39.4 42.5 12.4 .. 8.8 44.5 0.0 39.2 0.0 Burundi 0.80 0.59 6.5 –11.5 22.3 67.8 9.8 .. 5.5 29.8 1.1 21.8 0.0 Cameroon 0.79 0.48 –0.1 –2.7 .. .. .. 0.6 .. .. .. 13.3 .. Cape Verde 0.70 0.44 –0.7 11.5 100.0 15.8 14.7 1.3 11.6 44.3 11.9 100.0 0.0 Central African Republic 0.34 0.12 –3.2 –2.1 .. .. .. .. .. .. .. 62.5 .. Chad 0.70 0.40 0.9 –3.0 .. .. .. 0.6 .. .. .. 13.5 .. Comoros 0.75 0.51 –0.2 –3.0 .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 0.82 0.35 –2.8 20.3 .. .. .. 0.5 .. .. .. 100.0 .. Congo, Rep. 0.78 0.70 0.0 0.6 .. .. .. .. .. .. .. 16.1 .. Côte d’Ivoire 0.71 0.36 7.1 –3.1 33.8 11.2 13.1 0.6 7.3 47.9 0.0 33.1 0.0 Djibouti 0.65 0.33 1.4 12.3 .. .. .. 0.4 .. .. .. 100.0 .. Equatorial Guinea 0.74 0.73 –0.9 5.6 .. .. .. .. .. .. .. .. .. Eritrea 0.63 0.22 –2.5 2.0 .. .. .. .. .. .. .. .. .. Ethiopia 0.80 0.34 7.4 4.3 .. .. .. 0.7 .. .. .. .. .. Gabon 0.85 0.72 –0.1 –4.3 .. .. .. 0.6 .. .. .. 100.0 .. Gambia, The 0.63 0.26 0.4 19.1 .. .. .. 0.2 .. .. .. 13.7 .. Ghana 0.81 0.44 8.2 –0.8 .. .. .. 0.5 .. .. .. 14.3 .. Guinea 0.79 0.49 1.6 –6.4 .. .. .. 0.6 .. .. .. 38.9 .. Guinea-Bissau 0.80 0.93 –2.6 –3.4 97.6 48.6 13.3 0.6 9.9 51.8 0.0 97.8 0.0 Kenya 0.70 0.22 1.9 1.1 15.2 95.3 12.1 1.0 9.2 36.6 0.8 14.6 0.0 Lesotho 0.86 0.50 –3.0 –4.3 100.0 78.9 9.5 1.5 10.5 21.6 5.7 100.0 0.0 Liberia 0.77 0.60 11.4 –16.5 .. .. .. .. .. .. .. .. .. Madagascar 0.73 0.22 –0.8 0.3 .. .. .. .. .. .. .. 29.7 .. Malawi 0.81 0.62 9.2 –0.4 .. .. .. .. .. .. .. 31.2 .. Mali 0.87 0.75 –8.9 –5.2 40.5 28.9 12.8 0.6 8.4 47.9 0.0 40.6 0.0 Mauritania 0.82 0.50 12.4 4.5 .. .. .. .. .. .. .. 39.3 .. Mauritius 0.70 0.25 0.9 –2.9 .. .. .. 3.8 .. .. .. 17.8 .. Mozambique 0.73 0.32 –3.4 4.0 .. .. .. 0.8 .. .. .. 13.6 .. Namibia 0.87 0.31 –2.4 4.0 96.1 19.4 6.3 1.5 1.8 16.7 7.1 96.6 0.0 Niger 0.79 0.51 7.6 6.6 96.6 44.9 13.0 0.6 9.1 48.9 0.0 96.8 0.0 Nigeria 0.85 0.83 0.8 –0.4 19.5 119.4 10.9 0.7 10.6 34.9 0.0 19.2 0.0 Rwanda 0.82 0.40 1.7 21.0 100.0 89.3 9.9 .. 6.0 31.4 1.0 100.0 0.0 São Tomé and Príncipe 0.56 0.70 11.5 0.2 .. .. .. .. .. .. .. .. .. Senegal 0.69 0.23 2.0 –9.8 100.0 30.0 13.4 0.6 8.9 50.5 0.0 100.0 0.0 Seychelles 0.84 0.52 6.1 –14.2 .. .. .. .. .. .. .. .. .. Sierra Leone 0.62 0.27 –5.9 9.7 .. .. .. .. .. .. .. 100.0 .. Somalia 0.78 0.47 –0.2 5.0 .. .. .. .. .. .. .. .. .. South Africa 0.58 0.14 2.7 –0.5 96.1 19.4 7.6 1.6 4.4 17.9 7.5 96.6 0.0 Sudan 0.74 0.76 0.2 3.6 .. .. .. 0.9 .. .. .. .. .. Swaziland 0.71 0.24 1.8 –5.9 96.1 19.4 10.9 1.5 10.2 26.2 12.0 96.6 0.0 Tanzania 0.77 0.29 6.1 –3.6 13.8 120.0 12.9 0.9 8.2 39.9 1.0 13.4 0.0 Togo 0.71 0.25 1.6 –4.5 14.3 80.0 12.8 0.6 14.2 47.3 0.0 14.0 0.0 Uganda 0.73 0.23 4.4 6.5 16.1 73.5 12.1 1.0 8.2 37.5 1.1 15.8 0.0 Zambia 0.86 0.65 5.7 –2.4 .. .. .. 0.8 .. .. .. 16.7 .. Zimbabwe 0.75 0.19 2.7 –16.9 .. .. .. .. .. .. .. 21.0 .. NORTH AFRICA .. .. .. .. .. .. .. .. .. .. .. Algeria 0.80 0.56 1.9 –1.5 .. .. .. 0.7 .. .. .. .. .. Egypt, Arab Rep. 0.59 0.17 1.2 8.6 .. .. .. 4.7 .. .. .. 99.3 .. Libya 0.82 0.76 –0.3 2.8 .. .. .. .. .. .. .. .. .. Morocco 0.69 0.15 2.4 –2.2 .. .. .. 1.4 .. .. .. 100.0 .. Tunisia 0.55 0.16 –0.4 5.7 .. .. .. .. .. .. .. 57.6 .. a. Provisional. b. Data are for the most recent year available during the period speci�ed. 68 Part III. Development outcomes Trade and regional integration Tariff barriers, primary products (%) Tariff barriers, manufactured products (%) Average cost to ship 20 ft container from port to Average time to clear customs Simple Dispersion Weighted Simple Dispersion Weighted final destination ($) (days) mean tariff around the mean mean tariff mean tariff around the mean mean tariff Export Import Direct exports Imports 2010 2009 2010 2010 2009 2010 2010 2010 2009–10 b 2009–10 b .. 0.8 .. .. 0.9 .. 1,938 2,458 .. 0.7 .. .. 0.9 .. 1,850 2,840 6.7 11.4 15.5 0.5 12.4 12.9 0.6 11.7 1,251 1,400 9.6 33.0 6.1 1.4 0.5 9.0 1.5 8.0 3,010 3,390 6.2 3.7 11.4 0.5 8.1 12.5 .. 11.7 2,412 4,030 7.4 16.4 15.4 .. 9.4 9.1 .. 11.5 2,747 4,285 .. .. .. 0.5 .. .. 0.6 .. 1,379 1,978 15.1 24.0 16.2 1.1 12.2 14.3 1.3 9.8 1,200 1,000 .. 20.5 .. .. .. .. .. .. 5,491 5,554 .. .. .. 0.5 .. .. 0.6 .. 5,902 8,150 11.9 27.5 .. .. .. .. .. .. 1,073 1,057 .. .. .. 0.5 .. .. 0.5 .. 3,505 3,735 18.0 45.4 .. .. .. .. .. .. 3,818 7,709 .. 31.4 15.1 0.5 5.4 12.8 0.6 11.7 1,969 2,577 16.6 31.2 .. 0.7 .. .. 0.4 .. 836 911 .. .. .. .. .. .. .. .. 1,411 1,411 .. .. .. .. .. .. .. .. 1,431 1,581 9.6 20.1 .. 0.5 .. .. .. .. 1,890 2,993 .. .. .. 0.5 .. .. .. .. 1,945 1,955 3.8 10.3 .. 0.3 .. .. .. .. 831 975 .. .. .. 0.3 .. .. .. .. 1,013 1,203 .. .. .. 0.5 .. .. .. .. 855 1,391 .. .. 14.6 0.5 10.0 12.9 .. 11.7 1,545 2,349 .. .. 16.0 0.7 12.6 11.7 .. 11.5 2,055 2,190 .. .. 9.2 1.4 1.6 9.5 .. 8.0 1,680 1,610 5.4 4.4 .. .. .. .. .. .. 1,232 1,212 .. 6.7 .. .. .. .. .. .. 1,197 1,555 14.2 19.3 .. .. .. .. .. .. 1,713 2,570 9.9 11.2 12.8 .. 7.9 12.8 .. 11.7 2,202 3,067 12.9 16.5 .. .. .. .. .. .. 1,520 1,523 .. .. .. .. .. .. .. .. 737 689 10.3 9.8 .. .. .. .. .. .. 1,100 1,475 .. .. 4.1 .. 2.1 6.7 .. 8.0 1,686 1,813 .. .. 14.0 .. 10.7 12.8 .. 11.7 3,545 3,545 2.6 9.3 11.8 .. 9.1 10.7 .. 11.3 1,263 1,440 .. .. 11.5 .. 6.4 9.7 .. 11.5 3,275 4,990 .. .. .. .. .. .. .. .. 690 577 .. .. 14.1 .. 7.7 13.2 .. 11.7 1,098 1,940 .. .. .. .. .. .. .. .. 876 876 .. .. .. .. .. .. .. .. 1,573 1,639 .. 12.2 .. .. .. .. .. .. .. .. .. .. 5.4 1.5 1.9 7.8 1.6 8.0 1,531 1,807 .. .. .. 0.5 .. .. 0.9 .. 2,050 2,900 .. .. 9.7 1.4 1.3 11.1 1.5 8.0 1,754 1,849 .. .. 17.5 0.7 8.7 12.4 0.9 11.5 1,262 1,475 .. .. 14.4 0.5 12.4 12.6 0.6 11.7 940 963 6.7 9.0 15.7 0.7 8.8 11.6 1.0 11.5 2,780 2,940 .. .. .. 0.5 .. .. 0.8 .. 2,664 3,315 .. .. .. .. .. .. .. .. 3,280 5,101 .. .. .. .. .. .. .. .. 834 996 .. .. .. 0.5 .. .. 0.7 .. 1,248 1,428 .. .. .. 4.8 .. .. 4.7 .. 613 698 .. .. .. .. .. .. .. .. .. .. .. .. .. 1.2 .. .. 1.4 .. 700 1,000 .. .. .. .. .. .. .. .. 773 858 .. .. Trade and regional integration Part III. Development outcomes 69 Drivers of growth Table 5.2 Top three exports and share in total exports, 2009 First Second Share Share of total of total exports exports Product (%) Product (%) SUB–SAHARAN AFRICA Angola Petroleum oils and oils from bituminous minerals, crude 96.3 Benin Cashew nuts, in shells 29.5 Cotton, not carded or combed 28.7 Botswana Diamonds, nonindustrial, unworked or simply sawn or cleaved 27.9 Nickel mattes 19.9 Burkina Faso Cotton, not carded or combed 52.1 Gold, semi-manufactured, including platinum plated, nonmonetary 19.6 Burundi Coffee, not roasted, not decaffeinated 76.1 Black tea (fermented) and other partly fermented tea 9.3 Cameroon Petroleum oils and oils from bituminous minerals, crude 39.6 Cocoa beans, whole or broken, raw or roasted 18.7 Cape Verde Tunas, yellow�n 16.4 Fish, whole or in pieces 13.5 Central African Republic Logs, tropical hardwoods, not elsewhere speci�ed 25.8 Diamonds, not mounted or set, unsorted 25.4 Chad Petroleum oils and oils from bituminous minerals, crude 90.9 Petroleum oils and oils from bituminous minerals, noncrude 5.6 Comoros Cloves (whole fruit, cloves and stems) 32.1 Vessels and other floating structures for breaking up 26.8 Congo Petroleum oils and oils from bituminous minerals, crude 87.8 Congo, Dem. Rep. Cobalt ores and concentrates 20.7 Petroleum oils and oils from bituminous minerals, crude 16.6 Cote d'Ivoire Cocoa beans, whole or broken, raw or roasted 36.3 Petroleum oils and oils from bituminous minerals, crude 14.6 Djibouti Live bovine animals other than purebred breeding animals 27.4 Sheep, live 17.8 Equatorial Guinea Petroleum oils and oils from bituminous minerals, crude 72.7 Lique�ed natural gas 22.2 Eritrea Prefabricated buildings 19.3 Sheep, live 14.2 Ethiopia Coffee, not roasted, not decaffeinated 31.0 Sesamum seeds 24.9 Gabon Petroleum oils and oils from bituminous minerals, crude 69.9 Manganese ores and concentrates 9.8 Gambia, The Cashew nuts, in shells 44.5 Petroleum oils and oils from bituminous minerals, crude 14.3 Ghana Cocoa beans, whole or broken, raw or roasted 49.7 Manganese ores and concentrates 8.5 Guinea Aluminum ores and concentrates 62.9 Aluminum oxide not elsewhere speci�ed 11.2 Guinea-Bissau Cashew nuts, in shells 92.2 Kenya Black tea (fermented) and other partly fermented tea 14.3 Cut flowers and flower buds, fresh 13.8 Lesotho Diamonds, nonindustrial, unworked or simply sawn or cleaved 33.3 Men’s and boys’ trousers and shorts, of cotton, not knitted 13.8 Liberia Cargo vessels and other vessels for transport of goods or persons 42.1 Tankers 19.3 Madagascar Shrimps and prawns 9.3 Women’s and girls’ trousers, overalls, breeches, and shorts, of cotton 6.7 Malawi Tobacco, partly or wholly stemmed 63.0 Dried leguminous vegetables, shelled, not elsewhere speci�ed 8.8 Mali Cotton, not carded or combed 39.3 Mineral or chemical fertilizers containing nitrogen, phosphorus, potassium 12.5 Mauritania Iron ores and concentrates, nonagglomerated 45.4 Octopus, other than live, fresh, and chilled 14.4 Mauritius T-shirts, singlets, and other vests, knitted of cotton 13.4 Cane sugar, raw 12.2 Mozambique Aluminum, unwrought, not alloyed 38.1 Electrical energy 10.5 Namibia Natural uranium and its compounds 16.4 Unwrought zinc, containing by weight 99.99 percent or more of zinc 14.5 Niger Natural uranium and its compounds 70.5 Light oils and preparations 23.8 Nigeria Petroleum oils and oils from bituminous minerals, crude 86.3 Lique�ed natural gas 7.5 Rwanda Coffee, not roasted, not decaffeinated 29.0 Niobium, tantalum, and vanadium ores and concentrates 20.6 São Tomé & Príncipe Cocoa beans, whole or broken, raw or roasted 47.1 Wristwatches, other than automatic winding 12.3 Senegal Phosphoric acid and polyphosphoric acids 25.5 Fish, fresh and chilled, not elsewhere speci�ed 6.8 Seychelles Tunas, skipjack, and bonito 59.2 Tunas, bigeye (Thunnus obesus) 7.3 Sierra Leone Diamonds, nonindustrial, unworked or simply sawn or cleaved 21.5 Titanium ores and concentrates 11.8 Somalia Goats, live 28.3 Sheep, live 24.3 South Africa Platinum, unwrought or in powder form 9.3 Gold, unwrought, nonmonetary 6.4 Sudan Petroleum oils and oils from bituminous minerals, crude 91.3 Swaziland Cane sugar, raw 15.7 Mixtures of odoriferous substances for the food or drink industries 13.4 Tanzania Coffee, not roasted, not decaffeinated 9.6 Tobacco, partly or wholly stemmed 9.2 Togo Cocoa beans, whole or broken, raw or roasted 47.1 Ground 8.3 Uganda Coffee, not roasted, not decaffeinated 35.4 Fish �llets and other �sh meat, fresh or chilled 8.8 Zambia Re�ned copper, cathodes and sections of cathodes 49.8 Copper, unre�ned, and copper anodes for electrolytic re�ning 16.5 Zimbabwe Tobacco, partly or wholly stemmed 22.9 Ferro-chromium containing by weight more than 4% carbon 9.1 NORTH AFRICA Algeria Petroleum oils and oils from bituminous minerals, crude 46.8 Natural gas, in gaseous state 21.0 Egypt, Arab Rep. Lique�ed natural gas 15.8 Petroleum oils and oils from bituminous minerals, crude 15.3 Libya Petroleum oils and oils from bituminous minerals, crude 79.3 Natural gas, in gaseous state 9.1 Morocco Phosphoric acid and polyphosphoric acids 6.6 Ignition and other wiring sets of a kind used in vehicles, aircraft or ships 4.8 Tunisia Petroleum oils and oils from bituminous minerals, crude 9.4 Ignition and other wiring sets of a kind used in vehicles, aircraft or ships 6.1 AFRICAa Petroleum oils and oils from bituminous 44.8 Lique�ed natural gas 3.9 minerals, crude [18.5] [20.0] Note: Includes only products that account for more than 4 percent of total exports. a. Values in brackets are Africa’s share of total world exports. 70 Part III. Development outcomes Trade and regional integration Third Number of exports Share of total accounting for exports 75 percent of Product (%) total exports 1 Copper waste and scrap 6.0 6 Diamonds, nonindustrial, not mounted or set, not elsewhere speci�ed 8.6 16 Sesamum seeds 9.1 3 1 Bananas, including plantains, fresh 8.4 5 Men’s and boys’ trousers and shorts, of cotton, not knitted 10.4 9 Logs, tropical wood speci�ed in Subhe 16.7 4 1 Essential oils, not elsewhere speci�ed 18.6 3 1 Copper ores and concentrates 14.1 6 Cocoa paste, not defatted 8.0 7 Goats, live 13.2 5 2 Men’s and boys’ shirts, of cotton 6.9 19 Cut flowers and flower buds, fresh 10.9 7 Logs, tropical hardwoods, not elsewhere speci�ed 7.0 2 Titanium ores and concentrates 12.3 4 Cocoa butter, fat and oil 5.6 7 Coffee, not roasted, not decaffeinated 4.0 3 1 Coffee, not roasted, not decaffeinated 5.9 54 Pullovers, cardigans, and similar articles, knitted of cotton 11.0 6 Petroleum oils and oils from bituminous minerals, crude 13.3 4 Vanilla 5.6 31 Black tea (fermented) and other partly fermented tea 6.3 3 Sesamum seeds 8.1 8 Petroleum oils and oils from bituminous minerals, crude 13.2 4 Tunas, skipjack, and bonito 11.2 36 Light oils and preparations 9.0 8 Uranium ores and concentrates 13.3 7 2 1 Tin ores and concentrates 11.2 5 Aircraft, unladen weight of 2,000–15,000 kilograms 9.7 4 Fish, frozen, not elsewhere speci�ed 6.0 19 Skipjack and stripbellied bonito 5.4 4 Cocoa beans, whole or broken, raw or roasted 8.5 22 Live bovine animals 21.6 4 Iron ores and concentrates, nonagglomerated 5.6 103 1 Food preparations not elsewhere speci�ed 10.6 25 Precious metal ores and concentrates, other than silver 8.3 31 Gold, unwrought, nonmonetary 7.7 5 Tobacco, partly or wholly stemmed 7.5 15 Copper ores and concentrates 7.8 4 Cane sugar, raw 8.3 19 Lique�ed natural gas 10.8 3 Light oils and preparations 5.3 65 Petroleum oils and oils from bituminous minerals, noncrude 4.8 1 76 Men’s and boys’ trousers and shorts, of cotton, not knitted 5.5 94 Natural gas, in gaseous state 3.7 40 [9.9] Trade and regional integration Part III. Development outcomes 71 Drivers of growth Table 5.3 Regional integration, trade blocs Year of entry into force Type of of most most Merchandise exports within bloc Year recent recent ($ millions) established agreement agreementa 1990 1995 2000 2005 2007 2008 2009 Economic and Monetary Community of Central African States (CEMAC) 1994 1999 CU 139 120 96 201 305 355 300 Economic Community of the Great Lakes Countries (CEPGL) 1976 NNA 7 8 10 20 29 73 64 Common Market for Eastern and Southern Africa (COMESA) 1994 1994 FTA 1,146 1,367 1,443 2,695 4,021 6,676 6,114 East African Community (EAC) 1996 2000 CU 335 628 689 1075 1,385 1,797 1,572 Economic Community of Central African States (ECCAS) 1983 2004b NNA 160 157 182 255 385 449 378 Economic Community of West African States (ECOWAS) 1975 1993 PTA 1,532 1,875 2,715 5,497 6,717 9,355 7,312 Indian Ocean Commission (IOC) 1984 2005b NNA 63 113 106 162 214 217 183 Southern African Development Community (SADC) 1992 2000 FTA 1,655 3,615 4,427 7,799 12,051 16,011 11,697 West African Economic and Monetary Union (UEMOA) 1994 2000 CU 621 560 741 1,390 1,735 2,281 1,927 Year of entry into force Type of of most most Merchandise exports within bloc Year recent recent (% of total bloc exports) established agreement agreementa 1990 1995 2000 2005 2007 2008 2009 Economic and Monetary Community of Central African States (CEMAC) 1994 1999 CU 2.3 2.1 1.0 0.9 1.1 0.8 1.2 Economic Community of the Great Lakes Countries (CEPGL) 1976 NNA 0.5 0.5 0.8 1.2 1.4 1.9 2.2 Common Market for Eastern and Southern Africa (COMESA) 1994 1994 FTA 4.7 6.1 4.6 4.6 4.5 5.3 7.2 East African Community (EAC) 1996 2000 CU 17.7 19.5 22.6 18.0 17.8 19.2 18.9 Economic Community of Central African States (ECCAS) 1983 2004b NNA 1.4 1.5 1.0 0.6 0.6 0.4 0.6 Economic Community of West African States (ECOWAS) 1975 1993 PTA 8.0 9.0 7.6 9.3 7.8 8.5 9.9 Indian Ocean Commission (IOC) 1984 2005b NNA 3.9 5.9 4.4 4.9 5.8 5.7 5.8 Southern African Development Community (SADC) 1992 2000 FTA 6.6 10.2 9.5 9.3 10.2 10.3 11.0 West African Economic and Monetary Union (UEMOA) 1994 2000 CU 13.0 10.3 13.1 13.4 14.9 15.9 13.2 72 Part III. Development outcomes Trade and regional integration Year of entry into force Type of of most most Merchandise exports by bloc Year recent recent (% of world exports) established agreement agreementa 1990 1995 2000 2005 2007 2008 2009 Economic and Monetary Community of Central African States (CEMAC) 1994 1999 CU 0.2 0.1 0.1 0.2 0.2 0.2 0.2 Economic Community of the Great Lakes Countries (CEPGL) 1976 NNA 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Common Market for Eastern and Southern Africa (COMESA) 1994 1994 FTA 0.7 0.4 0.5 0.6 0.6 0.8 0.7 East African Community (EAC) 1996 2000 CU 0.1 0.1 0.0 0.1 0.1 0.1 0.1 Economic Community of Central African States (ECCAS) 1983 2004b NNA 0.3 0.2 0.3 0.4 0.5 0.7 0.5 Economic Community of West African States (ECOWAS) 1975 1993 PTA 0.6 0.4 0.6 0.6 0.6 0.7 0.6 Indian Ocean Commission (IOC) 1984 2005b NNA 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Southern African Development Community (SADC) 1992 2000 FTA 0.7 0.7 0.7 0.8 0.9 1.0 0.9 West African Economic and Monetary Union (WAEMU/UEMOA) 1994 2000 CU 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Note: Economic and Monetary Community of Central Africa (CEMAC; formerly Central African Customs and Economic Union [UDEAC]), Cameroon, the Central African Republic, Chad, the Republic of Congo, Equatorial Guinea, and Gabon; Economic Community of the Great Lakes Countries (CEPGL), Burundi, the Democratic Republic of the Congo, and Rwanda; Common Market for Eastern and Southern Africa (COMESA), Burundi, Comoros, the Democratic Republic of Congo, Djibouti, the Arab Republic of Egypt, Eritrea, Ethiopia, Kenya, Libya, Madagascar, Malawi, Mauritius, Rwanda, Seychelles, Sudan, Swaziland, Uganda, Zambia, and Zimbabwe; East African Community (EAC), Burundi, Kenya, Rwanda, Tanzania, and Uganda; Economic Community of Central African States (ECCAS), Angola, Burundi, Cameroon, the Central African Republic, Chad, the Democratic Republic of Congo, the Republic of Congo, Equatorial Guinea, Gabon, and São Tomé and Príncipe; Economic Community of West African States (ECOWAS), Benin, Burkina Faso, Cape Verde, Côte d’Ivoire, the Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, and Togo; Indian Ocean Commission (IOC), Comoros, Madagascar, Mauritius, Réunion, and Seychelles; Southern African Development Community (SADC; formerly Southern African Development Coordination Conference), Angola, Botswana, the Democratic Republic of the Congo, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia, and Zimbabwe; West African Economic and Monetary Union (UEMOA), Benin, Burkina Faso, Côte d’Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo. a. CU is customs union; FTA is free trade agreement; NNA is not noti�ed agreement, which refers to preferential trade agreements established among member countries that are not noti�ed to the World Trade Organization (these agreements may be functionally equivalent to any of the other agreements); and PTA is preferential trade agreement. b. From the of�cial website of the trade bloc. Trade and regional integration Part III. Development outcomes 73 Drivers of growth Table 6.1 Water and sanitation Financing Access, Quality Committed supply side Access, demand side of supply nominal Internal Population with sustainable access Population with sustainable investment in ODA gross fresh water to an improved water source access to improved sanitation Average water projects disbursements for resources per (% of (% of (% of (% of (% of (% of duration of with private water supply and capita (cubic total urban rural total urban rural insufficient participation sanitation sector meters) population) population) population) population) population) population) water supply ($ millions) ($ millions) 2007 2008 2008 2008 2008 2008 2008 2009–10 a 2000–09 a 2008 2009 SUB–SAHARAN AFRICA 4,850 60 83 47 31 44 24 .. 1,668.2 1,789.9 Angola 8,431 50 60 38 57 86 18 9.9 .. 22.3 13.9 Benin 1,227 75 84 69 12 24 4 19.0 .. 63.5 55.0 Botswana 1,268 95 99 90 60 74 39 3.2 .. 2.2 0.0 Burkina Faso 849 76 95 72 11 33 6 4.6 .. 60.5 70.7 Burundi 1,284 72 83 71 46 49 46 .. .. 15.7 19.2 Cameroon 14,630 74 92 51 47 56 35 23.5 0.0 18.5 8.7 Cape Verde 610 84 85 82 54 65 38 9.8 .. 6.4 20.4 Central African Republic 33,119 67 92 51 34 43 28 .. .. 1.9 6.7 Chad 1,412 50 67 44 9 23 4 2.7 .. 26.0 28.9 Comoros 1,910 95 91 97 36 50 30 .. .. 1.3 1.4 Congo, Dem. Rep. 14,395 46 80 28 23 23 23 13.6 .. 62.0 73.7 Congo, Rep. 62,516 71 95 34 30 31 29 45.3 0.0 1.8 0.4 Côte d’Ivoire 3,819 80 93 68 23 36 11 27.7 0.0 7.9 30.6 Djibouti 360 92 98 52 56 63 10 .. .. 3.2 7.1 Equatorial Guinea 40,485 .. .. .. .. .. .. .. .. 0.0 0.0 Eritrea 586 61 74 57 14 52 4 .. .. 8.2 7.4 Ethiopia 1,551 38 98 26 12 29 8 .. .. 107.1 142.6 Gabon 115,340 87 95 41 33 33 30 1.1 .. 18.6 3.2 Gambia, The 1,857 92 96 86 67 68 65 .. .. 9.1 5.0 Ghana 1,325 82 90 74 13 18 7 .. 0.0 124.4 56.3 Guinea 23,505 71 89 61 19 34 11 .. .. 14.7 11.2 Guinea-Bissau 10,383 61 83 51 21 49 9 .. .. 3.0 2.6 Kenya 548 59 83 52 31 27 32 .. .. 101.3 98.2 Lesotho 2,574 85 97 81 29 40 25 6.1 .. 18.8 23.1 Liberia 55,138 68 79 51 17 25 4 2.9 .. 7.1 13.1 Madagascar 18,114 41 71 29 11 15 10 8.0 .. 17.4 12.8 Malawi 1,118 80 95 77 56 51 57 4.7 .. 13.9 16.0 Mali 4,835 56 81 44 36 45 32 12.1 .. 47.1 78.0 Mauritania 127 49 52 47 26 50 9 .. .. 21.9 23.6 Mauritius 2,182 99 100 99 91 93 90 6.0 0.0 9.5 10.8 Mozambique 4,586 47 77 29 17 38 4 .. .. 81.6 95.5 Namibia 2,949 92 99 88 33 60 17 .. 0.0 11.8 12.0 Niger 248 48 96 39 9 34 4 .. 3.4 38.1 43.7 Nigeria 1,496 58 75 42 32 36 28 .. .. 108.7 105.5 Rwanda 1,005 65 77 62 54 50 55 .. .. 37.7 28.2 São Tomé and Príncipe 13,829 89 89 88 26 30 19 .. .. 0.9 1.0 Senegal 2,169 69 92 52 51 69 38 .. 0.0 76.2 58.3 Seychelles .. .. 100 .. .. 97 .. .. .. 0.2 0.6 Sierra Leone 29,518 49 86 26 13 24 6 0.0 .. 13.3 10.0 Somalia 687 30 67 9 23 52 6 .. .. 1.9 5.1 South Africa 928 91 99 78 77 84 65 .. 0.0 52.7 60.9 Sudan 742 57 64 52 34 55 18 .. 120.7 21.8 55.2 Swaziland 2,293 69 92 61 55 61 53 .. .. 1.1 0.3 Tanzania 2,035 54 80 45 24 32 21 .. 8.5 148.9 173.2 Togo 1,825 60 87 41 12 24 3 .. .. 3.0 5.8 Uganda 1,273 67 91 64 48 38 49 .. 0.0 64.2 86.4 Zambia 6,513 60 87 46 49 59 43 .. 0.0 39.5 50.5 Zimbabwe 985 82 99 72 44 56 37 .. .. 12.1 7.6 NORTH AFRICA 290 92 95 87 89 94 83 .. 464.0 542.1 Algeria 332 83 85 79 95 98 88 .. 468.0 4.7 9.0 Egypt, Arab Rep. 23 99 100 98 94 97 92 .. .. 56.7 106.0 Libya 97 .. .. .. 97 97 96 .. .. 0.0 0.0 Morocco 929 81 98 60 69 83 52 .. .. 301.0 319.4 Tunisia 410 94 99 84 85 96 64 .. .. 98.6 100.4 a. Data are for the most recent year available during the period speci�ed. 74 Part III. Development outcomes Infrastructure Drivers of growth 6.2 Table Transportation Access, supply side Access, demand side Road density Vehicle fleet (per 1,000 people) Ratio to total land Road network Rail lines (road km/100 sq km Commercial Passenger (km) (km) of land area) vehicles vehicles 2000–08a 2009 2000–08a 2000–08a 2000–08a SUB–SAHARAN AFRICA .. Angola 51,429 .. 4.0 40.0 8.0 Benin 19,000 .. 17.0 21.0 17.0 Botswana 25,798 888 4.0 113.0 56.0 Burkina Faso 92,495 622 34.0 11.0 7.0 Burundi 12,322 .. 44.0 6.0 2.0 Cameroon 51,346 977 11.0 .. 11.0 Cape Verde 1,350 .. 33.0 94.0 67.0 Central African Republic 24,307 .. 4.0 0.3 0.3 Chad 40,000 .. 3.0 6.0 .. Comoros 880 .. 39.0 33.0 31.0 Congo, Dem. Rep. 153,497 3,641 7.0 5.0 .. Congo, Rep. 17,000 .. 5.0 26.0 15.0 Côte d’Ivoire 81,996 639 25.0 20.0 16.0 Djibouti 3,065 .. 14.0 .. .. Equatorial Guinea 2,880 .. 10.0 .. .. Eritrea 4,010 .. 3.0 11.0 6.0 Ethiopia 44,359 .. 4.0 3.0 1.0 Gabon 9,170 810 3.0 .. .. Gambia, The 3,742 .. 33.0 7.0 5.0 Ghana 57,614 .. 24.0 33.0 21.0 Guinea 44,348 .. 18.0 .. .. Guinea-Bissau 3,455 .. 12.0 33.0 27.0 Kenya 63,265 .. 11.0 21.0 15.0 Lesotho 5,940 .. 20.0 .. .. Liberia 10,600 .. 10.0 3.0 2.0 Madagascar 49,827 .. 8.0 27.0 8.0 Malawi 15,451 .. 13.0 9.0 4.0 Mali 18,912 .. 2.0 9.0 7.0 Mauritania 11,066 728 1.0 .. .. Mauritius 2,028 .. 99.0 159.0 123.0 Mozambique 30,331 3,116 4.0 13.0 9.0 Namibia 66,467 .. 0.0 109.0 52.0 Niger 18,948 .. 1.0 5.0 4.0 Nigeria 193,200 .. 21.0 31.0 31.0 Rwanda 14,008 .. 53.0 4.0 2.0 São Tomé and Príncipe 320 .. 33.0 2.0 2.0 Senegal 14,805 .. 8.0 23.0 17.0 Seychelles 508 .. 110.0 173.0 103.0 Sierra Leone 11,300 .. .. 5.0 3.0 Somalia 22,100 .. 3.0 .. .. South Africa 362,099 22,051 30.0 159.0 108.0 Sudan 11,900 4,508 1.0 28.0 20.0 Swaziland 3,594 300 21.0 89.0 46.0 Tanzania 87,524 .. 9.0 73.0 4.0 Togo 11,652 .. 21.0 2.0 2.0 Uganda 70,746 .. 29.0 7.0 3.0 Zambia 66,781 .. 12.0 18.0 11.0 Zimbabwe 97,267 .. 25.0 106.0 91.0 NORTH AFRICA 14,019 Algeria 111,261 4,723 5.0 112.0 72.0 Egypt, Arab Rep. 104,918 5,195 10.0 43.0 31.0 Libya 83,200 .. 5.0 291.0 225.0 Morocco 58,256 2,110 13.0 71.0 53.0 Tunisia 19,371 1,991 12.0 114.0 76.0 (continued) Infrastructure Part III. Development outcomes 75 Drivers of growth Table 6.2 Transportation (continued) Quality Pricing Financing Committed nominal Price of Price of investment in transport ODA gross disbursements for Ratio of paved to diesel fuel gasoline projects with private transportation and storage total roads (%) ($ per liter) ($ per liter) participation ($ millions) ($ millions) 2000–08a 2010 2010 2000–08a 2008 2009 SUB–SAHARAN AFRICA 1.15 1.25 2,460.5 3,039.4 Angola 10.4 0.43 0.65 53.0 1.8 5.7 Benin 9.5 1.21 1.04 .. 99.4 92.3 Botswana 32.6 0.97 0.93 .. 0.1 12.9 Burkina Faso 4.2 1.28 1.44 .. 38.2 52.5 Burundi 10.4 1.42 1.43 .. 34.3 46.0 Cameroon 8.4 1.10 1.20 0.0 92.1 90.2 Cape Verde 69.0 1.33 1.84 .. 76.1 55.7 Central African Republic .. 1.69 1.71 .. 5.1 15.3 Chad 0.8 1.31 1.32 .. 58.2 45.3 Comoros 76.5 .. .. 0.5 0.6 2.2 Congo, Dem. Rep. 1.8 1.27 1.28 .. 159.4 138.3 Congo, Rep. 7.1 0.84 1.27 735.0 28.2 20.4 Côte d’Ivoire 7.9 1.30 1.68 0.0 6.7 16.0 Djibouti 45.0 1.07 1.63 396.0 3.6 93.8 Equatorial Guinea .. .. .. .. .. .. Eritrea 21.8 1.07 2.54 .. 1.8 2.9 Ethiopia 13.7 0.78 0.91 .. 313.8 251.8 Gabon 10.2 .. .. 3.9 7.0 75.9 Gambia, The 19.3 .. .. .. 6.4 9.7 Ghana 14.9 0.83 0.82 0.0 119.3 116.6 Guinea 9.8 0.95 0.95 159.0 35.5 28.6 Guinea-Bissau 27.9 .. .. .. 16.8 15.1 Kenya 14.1 1.27 1.33 404.0 97.5 115.3 Lesotho 18.3 1.07 0.97 .. 16.1 6.5 Liberia 6.2 0.96 0.98 .. 31.2 49.8 Madagascar 11.6 1.26 1.52 17.5 117.8 42.8 Malawi 45.0 1.54 1.71 .. 33.0 22.3 Mali 19.0 1.25 1.42 55.4 81.0 44.6 Mauritania 26.9 0.99 1.16 .. 41.6 22.9 Mauritius 98.0 1.23 1.55 .. 1.5 0.7 Mozambique 20.8 0.86 1.11 0.0 100.5 100.0 Namibia 12.8 1.09 1.06 .. 25.8 53.7 Niger 20.7 1.16 1.07 .. 60.7 38.8 Nigeria 15.0 0.77 0.44 382.0 44.4 108.7 Rwanda 19.0 1.62 1.63 .. 50.7 26.8 São Tomé and Príncipe 68.1 .. .. .. 3.7 1.6 Senegal 29.3 1.34 1.57 264.0 82.9 89.1 Seychelles 96.5 .. .. .. .. .. Sierra Leone 8.0 0.94 0.94 .. 22.6 34.2 Somalia 11.8 .. .. .. 0.1 1.7 South Africa 17.3 1.14 1.19 3,483.0 0.4 520.5 Sudan 36.3 0.43 0.62 30.0 29.3 78.3 Swaziland 30.0 1.10 1.07 .. 0.0 0.4 Tanzania 7.4 1.19 1.22 134.0 162.8 146.4 Togo 21.0 1.17 1.18 .. 0.0 0.6 Uganda 23.0 1.11 1.42 404.0 178.5 103.1 Zambia 22.0 1.52 1.66 15.6 77.1 34.6 Zimbabwe 19.0 1.15 1.29 .. 0.0 0.0 NORTH AFRICA 0.32 0.48 531.4 890.6 Algeria 73.5 0.19 0.32 108.0 90.4 76.0 Egypt, Arab Rep. 86.9 0.32 0.48 640.0 110.2 145.5 Libya 57.2 0.13 0.17 .. .. .. Morocco 67.8 0.88 1.23 200.0 179.2 344.2 Tunisia 75.2 0.82 0.94 840.0 144.7 320.3 a. Data are for the most recent year available during the period speci�ed. 76 Part III. Development outcomes Infrastructure Drivers of growth 6.3 Table Information and communication technology Access, supply side Access, demand side Quality Telephone subscribers (per 100 people) Unmet Average delay for Internet Telephone faults demand Households with firm in obtaining users Total Cleared by next Mainline Mobile (% of mainline own telephone a mainline phone (per 100 (per 100 working day Total telephone telephone telephones) (% of households) connection (days) people) mainlines) (%) 2009 2009 2009 2008 2008 2009–10a 2009 2009 2009 SUB–SAHARAN AFRICA 38.8 1.5 37.3 .. .. 8.8 .. .. Angola 45.5 1.6 43.8 .. .. 9.3 3.3 .. .. Benin 57.8 1.4 56.3 .. .. 89.4 2.2 6.6 40.7 Botswana 103.5 7.4 96.1 .. .. 17.1 6.2 .. .. Burkina Faso 22.0 1.1 20.9 .. .. 19.5 1.1 .. .. Burundi 10.5 0.4 10.1 0.1 .. .. 0.8 .. .. Cameroon 39.6 1.7 37.9 .. .. 19.2 3.8 .. .. Cape Verde 91.8 14.3 77.5 0.4 .. 8.2 29.7 3.0 93.0 Central African Republic 4.1 0.3 3.8 .. .. .. 0.5 .. .. Chad 24.1 0.1 24.0 .. .. 13.3 1.7 .. .. Comoros 19.0 3.9 15.2 28.3 .. .. 3.7 .. .. Congo, Dem. Rep. 15.5 0.1 15.4 .. .. 20.1 0.6 .. .. Congo, Rep. 59.6 0.7 58.9 .. .. 25.5 6.7 .. .. Côte d’Ivoire 64.7 1.3 63.3 .. .. 5.8 4.6 .. .. Djibouti 16.9 2.0 14.9 .. 7.2 .. 3.0 .. 31.0 Equatorial Guinea 67.3 1.5 65.8 .. .. .. 2.1 .. .. Eritrea 3.7 1.0 2.8 49.5 .. .. 4.9 50.2 24.0 Ethiopia 6.0 1.1 4.9 2.1 .. .. 0.5 4.9 66.0 Gabon 94.9 1.8 93.1 .. .. 8.6 6.7 .. .. Gambia, The 86.9 2.9 84.0 .. .. .. 7.6 .. .. Ghana 64.5 1.1 63.4 0.2 .. .. 5.4 1.1 60.0 Guinea 55.9 0.2 55.7 .. .. .. 0.9 .. .. Guinea-Bissau 35.1 0.3 34.8 .. .. .. 2.3 .. .. Kenya 50.3 1.7 48.7 0.4 .. .. 10.0 26.1 47.0 Lesotho 33.9 1.9 32.0 .. .. 53.7 3.7 .. .. Liberia 21.3 0.1 21.3 .. .. .. 0.5 .. .. Madagascar 31.5 0.9 30.6 0.1 2.4 29.9 1.6 9.5 92.4 Malawi 16.9 1.2 15.7 .. .. 45.9 4.7 .. .. Mali 29.4 0.6 28.8 .. .. 13.8 1.9 .. .. Mauritania 68.6 2.3 66.3 .. .. .. 2.3 .. .. Mauritius 114.9 29.7 85.2 .. 73.6 38.6 22.7 .. .. Mozambique 26.4 0.4 26.1 .. .. .. 2.7 .. .. Namibia 62.6 6.5 56.1 .. .. .. 5.9 .. .. Niger 17.4 0.4 17.0 .. 1.4 13.9 0.8 .. .. Nigeria 48.2 0.9 47.2 .. 1.8 .. 28.4 .. .. Rwanda 24.6 0.3 24.3 .. 1.1 .. 4.5 0.0 98.0 São Tomé and Príncipe 44.1 4.8 39.3 .. .. .. 16.4 .. .. Senegal 57.3 2.2 55.1 .. .. .. 7.4 .. 92.0 Seychelles 130.0 25.1 104.9 9.8 .. .. 38.7 5.0 95.0 Sierra Leone 20.9 0.6 20.4 .. 0.8 21.4 0.3 .. .. Somalia 8.1 1.1 7.0 .. .. .. 1.2 .. .. South Africa 102.9 8.8 94.2 .. 18.1 .. 9.0 .. .. Sudan 37.2 0.9 36.3 0.0 .. .. 9.9 5.0 95.0 Swaziland 59.1 3.7 55.4 0.2 .. .. 7.6 0.6 63.0 Tanzania 40.3 0.4 39.9 .. 0.7 .. 1.6 .. .. Togo 35.8 2.7 33.1 .. .. 51.0 5.4 .. .. Uganda 29.4 0.7 28.7 .. .. .. 9.8 .. .. Zambia 34.8 0.7 34.1 .. .. .. 6.3 .. .. Zimbabwe 27.0 3.1 23.9 .. .. .. 11.4 41.0 .. NORTH AFRICA 88.1 11.3 76.9 .. .. 21.3 .. .. Algeria 101.2 7.4 93.8 .. .. .. 13.5 .. .. Egypt, Arab Rep. 79.1 12.4 66.7 0.3 .. .. 20.0 0.1 98.3 Libya 95.1 17.2 77.9 .. .. .. 5.5 .. .. Morocco 90.1 11.0 79.1 .. 26.0 .. 32.2 .. .. Tunisia 105.8 12.3 93.5 0.9 .. .. 33.6 24.8 78.7 (continued) Infrastructure Part III. Development outcomes 77 Drivers of growth Table 6.3 Information and communication technology (continued) Pricing Cost of 3-minute call Cost of 3-minute call Connection charge Fixed during peak hours ($) during off-peak hours ($) ($) broadband Mobile cellular internet Fixed Fixed Fixed subscription telephone Cellular telephone Cellular Residential Business broadband ($ per month) local local local local telephone telephone Prepaid Postpaid internet 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 SUB–SAHARAN AFRICA 56.9 0.19 0.64 0.13 0.65 35.7 52.4 .. 2.1 72.0 Angola 154.3 0.29 0.65 0.23 0.65 56.7 56.7 .. .. 90.8 Benin 112.5 0.13 0.55 0.13 0.55 204.4 372.1 5.3 5.3 31.8 Botswana 56.9 0.19 0.75 0.14 0.75 35.4 51.9 1.4 1.4 94.7 Burkina Faso 87.2 0.24 0.95 0.14 0.95 53.0 53.0 .. 6.4 .. Burundi .. .. .. .. .. .. .. .. .. .. Cameroon 84.7 0.32 0.95 0.16 0.95 42.4 105.9 .. 5.3 105.9 Cape Verde 33.3 0.07 0.91 0.05 0.91 25.8 26.4 .. .. 29.0 Central African Republic 1,270.7 0.13 0.76 0.13 0.76 75.0 75.0 .. 2.1 .. Chad 12.5 0.37 1.14 0.37 1.14 112.5 112.5 1.7 1.7 309.2 Comoros 409.4 0.14 0.64 0.14 0.64 114.4 114.4 .. .. 169.4 Congo, Dem. Rep. .. .. .. .. .. .. .. .. .. .. Congo, Rep. .. .. .. .. .. .. .. .. .. .. Côte d’Ivoire 42.4 0.38 0.63 0.00 0.63 21.2 21.2 .. .. 53.0 Djibouti 56.3 0.09 0.54 0.09 0.54 56.3 56.3 28.1 28.1 28.1 Equatorial Guinea 254.1 .. .. .. .. .. .. .. .. 264.7 Eritrea .. 0.02 0.35 0.02 0.35 71.5 71.5 100.2 100.2 .. Ethiopia 517.6 0.02 0.21 0.02 0.21 20.6 20.6 14.4 14.4 .. Gabon .. .. .. .. .. .. .. .. .. .. Gambia, The .. .. .. .. .. .. .. .. .. .. Ghana 45.5 0.11 0.31 0.04 .. 28.4 28.4 0.7 0.7 63.9 Guinea .. .. .. .. .. .. .. .. .. .. Guinea-Bissau .. .. 0.57 .. 0.57 .. .. 1.1 1.1 .. Kenya 38.8 0.11 0.31 0.11 0.31 29.7 .. .. 1.3 .. Lesotho 43.7 0.20 0.70 0.15 0.70 39.7 .. .. 5.9 53.1 Liberia .. .. .. .. .. .. .. .. .. .. Madagascar 100.2 0.30 0.65 0.09 0.65 30.2 30.2 .. 0.5 0.0 Malawi 490.6 .. 0.59 .. 0.59 .. .. .. 2.8 613.3 Mali 53.0 0.11 0.70 0.11 0.70 81.9 81.9 .. 2.1 103.8 Mauritania 57.2 0.23 0.63 0.23 0.63 19.1 19.1 .. 1.9 26.6 Mauritius 15.1 0.07 0.13 0.06 0.13 36.0 72.0 3.1 3.1 72.0 Mozambique 80.6 0.18 0.72 0.14 0.72 17.8 17.8 .. 0.7 .. Namibia 41.2 0.16 0.89 0.08 0.89 34.6 34.6 .. 2.2 .. Niger 254.1 0.16 0.79 0.16 0.79 31.8 .. .. 3.2 103.8 Nigeria 105.8 0.20 0.60 0.18 0.60 .. .. .. .. .. Rwanda 88.0 0.20 0.45 0.20 0.45 52.8 .. .. 1.8 176.0 São Tomé and Príncipe 202.5 0.10 0.47 0.10 0.47 25.9 25.9 .. 8.6 81.0 Senegal 38.1 0.35 0.54 0.35 0.54 21.2 .. .. 4.2 40.2 Seychelles 42.8 0.07 0.92 0.05 0.92 48.1 48.1 3.7 3.7 45.9 Sierra Leone 29.3 .. .. .. .. .. .. .. .. .. Somalia .. .. .. .. .. .. .. .. .. .. South Africa 23.5 0.15 0.89 0.07 0.89 55.2 55.2 .. 17.6 64.2 Sudan 26.1 0.00 0.18 0.00 0.18 .. .. .. 2.2 43.4 Swaziland 749.2 0.07 0.78 0.04 0.78 25.1 42.0 .. 1.8 .. Tanzania 22.7 0.27 0.59 0.27 .. 15.2 15.2 0.4 0.4 18.9 Togo 1,049.6 0.19 0.73 0.10 0.73 75.0 75.0 .. 2.1 174.9 Uganda 41.9 0.18 0.50 0.11 .. 59.1 59.1 .. 1.5 145.3 Zambia 47.4 0.78 0.70 0.46 0.70 9.9 29.7 .. .. .. Zimbabwe .. .. .. .. .. .. .. .. .. .. NORTH AFRICA 15.1 0.05 0.41 0.04 0.41 14.8 90.2 3.7 5.3 .. Algeria 15.1 0.08 0.33 0.06 0.33 .. .. .. 6.9 .. Egypt, Arab Rep. 8.1 0.03 0.11 0.03 0.11 6.7 90.2 3.2 3.2 0.0 Libya 39.9 .. .. .. .. .. .. .. .. 119.6 Morocco 16.0 0.25 1.34 0.25 1.34 74.5 148.9 14.9 14.9 .. Tunisia 11.1 0.02 0.49 0.02 0.49 14.8 37.0 3.7 3.7 .. a. Data are for the most recent year available during the period speci�ed. 78 Part III. Development outcomes Infrastructure Financing Annual revenue ($ millions) Annual investment Committed nominal ($ millions) investment in telecommunica- ODA gross dis- tion projects with bursements for Fixed telephone Mobile private participa- communication Fixed telephone Mobile service communication Telecommunications tion ($ millions) ($ millions) service communication Telecommunications 2009a 2009 2009 2009 2009 2009 2009 2009 143.1 6,107.9 4,070.7 11,333.0 256.3 2,304.4 12,497.8 15,077.3 .. .. .. 354.0 0.6 .. .. .. 0.8 335.9 336.7 127.0 0.7 22.9 315.5 338.4 .. .. .. 86.0 0.1 .. 279.5 402.8 .. .. 118.0 193.0 4.3 .. .. .. .. .. .. – 1.8 .. .. .. .. .. .. 278.0 2.1 .. .. .. .. .. .. 23.0 0.8 .. .. .. .. .. .. 6.0 0.1 .. .. .. .. .. .. 68.0 .. .. .. .. .. .. 3.9 .. .. .. 7.6 27.9 .. 203.8 203.8 151.0 4.3 .. 726.5 .. .. .. .. 110.0 0.1 .. .. .. .. 271.5 298.6 318.0 0.9 292.7 1,173.8 1,466.5 7.1 1.2 8.6 .. 10.4 22.3 16.2 60.2 .. .. .. .. (0.0) .. .. .. .. .. .. – .. 25.0 28.8 54.5 .. .. .. .. 4.6 270.8 196.4 480.8 .. .. .. 91.0 .. .. .. .. .. .. .. – 0.4 .. .. .. .. 592.9 640.5 847.0 9.3 .. 1,067.3 1,174.0 .. .. .. 87.0 0.1 .. .. .. .. .. .. 28.0 0.2 .. .. .. 40.4 454.6 514.2 278.0 17.3 646.4 1,088.1 1,837.6 .. .. .. 11.0 .. .. .. .. .. .. .. 24.0 0.3 .. .. .. 7.6 .. .. 83.0 0.3 32.9 248.4 325.9 .. .. .. 73.0 2.0 .. .. .. .. .. 63.5 429.0 0.8 50.0 463.4 513.4 .. .. .. 43.0 0.0 .. .. .. .. .. .. 35.0 6.5 67.7 114.2 .. .. .. .. 52.0 19.0 .. .. .. .. .. .. – (8.7) .. .. .. .. .. .. 87.0 0.5 .. .. .. .. .. 644.7 3,057.0 22.8 280.7 5,990.1 6,270.8 .. .. 174.3 183.0 2.4 .. .. 152.8 .. .. .. .. 0.1 .. .. .. 38.2 227.2 265.4 256.0 2.4 593.0 692.5 1,285.5 .. .. .. .. .. .. .. .. .. .. .. 23.0 0.9 .. .. .. .. .. .. – 0.1 .. .. .. .. .. .. 2,387.0 6.2 .. .. .. .. .. .. 357.0 0.1 .. .. .. .. 20.7 .. 25.0 .. .. 89.5 .. .. .. .. 522.0 2.2 .. .. .. .. .. .. 44.0 .. .. .. .. .. .. 298.5 283.0 8.2 .. .. 686.2 .. .. .. 114.0 1.2 .. .. .. 49.0 4,000.0 500.0 200.0 0.3 .. .. .. 258.7 1,327.8 4,085.3 2,716.0 29.3 3,194.4 11,710.3 17,337.8 .. .. .. 398.0 0.7 798.4 3,057.2 5,011.9 177.9 1,166.2 3,135.4 1,791.0 2.8 1,039.5 4,717.0 6,513.4 .. .. .. .. .. .. .. .. .. .. 684.1 240.0 1.5 1,127.6 2,806.6 4,136.9 80.8 161.6 265.8 287.0 19.2 229.0 1,129.4 1,675.6 Infrastructure Part III. Development outcomes 79 Drivers of growth Table 6.4 Energy Access, demand side Energy production GDP per unit of Sourcea Electric power energy use (2005 Solid fuels use Total (% of total) consumption PPP $ per kg of (% of (billion kWh) Hydroelectric Coal Natural gas Nuclear Oil (kWh per capita) oil equivalent) population) 2008 2008 2008 2008 2008 2008 2008 2008 2006 SUB–SAHARAN AFRICA 423.9 17.2 58.0 4.4 3.1 3.8 530.9 3.2 81.6 Angola 4.0 96.3 0.0 0.0 0.0 3.7 189.3 8.8 47.7 Benin 0.1 0.7 0.0 0.0 0.0 99.3 76.3 3.9 94.3 Botswana 0.6 0.0 100.0 0.0 0.0 0.0 1,503.3 11.6 40.0 Burkina Faso .. .. .. .. .. .. .. .. 95.0 Burundi .. .. .. .. .. .. .. .. 95.0 Cameroon 5.6 76.2 0.0 7.7 0.0 15.9 262.6 5.4 80.6 Cape Verde .. .. .. .. .. .. .. .. 36.2 Central African Republic .. .. .. .. .. .. .. .. 95.0 Chad .. .. .. .. .. .. .. .. 93.0 Comoros .. .. .. .. .. .. .. .. 76.0 Congo, Dem. Rep. 7.5 99.4 0.0 0.4 0.0 0.2 95.1 0.8 95.0 Congo, Rep. 0.5 81.3 0.0 18.7 0.0 0.0 150.2 9.6 83.9 Côte d’Ivoire 5.8 32.7 0.0 65.1 0.0 0.2 186.3 3.1 79.0 Djibouti .. .. .. .. .. .. .. .. 16.0 Equatorial Guinea .. .. .. .. .. .. .. .. .. Eritrea 0.3 0.0 0.0 0.0 0.0 99.3 .. 3.8 62.7 Ethiopia 3.8 87.3 0.0 0.0 0.0 12.4 42.4 2.0 95.0 Gabon 2.0 43.8 0.0 24.7 0.0 31.2 1,158.0 9.4 27.0 Gambia, The .. .. .. .. .. .. .. .. 94.7 Ghana 8.4 74.1 0.0 0.0 0.0 25.9 267.7 3.4 85.9 Guinea .. .. .. .. .. .. .. .. 95.0 Guinea-Bissau .. .. .. .. .. .. .. .. 95.0 Kenya 7.1 40.4 0.0 0.0 0.0 38.4 155.3 3.1 75.0 Lesotho .. .. .. .. .. .. .. .. 71.0 Liberia .. .. .. .. .. .. .. .. 95.0 Madagascar .. .. .. .. .. .. .. .. 95.0 Malawi .. .. .. .. .. .. .. .. 95.0 Mali .. .. .. .. .. .. .. .. 95.0 Mauritania .. .. .. .. .. .. .. .. 60.0 Mauritius .. .. .. .. .. .. .. .. 5.0 Mozambique 15.1 99.9 0.0 0.1 0.0 0.0 461.4 1.9 95.0 Namibia 2.1 67.5 31.1 0.0 0.0 1.4 1,797.3 7.3 57.0 Niger .. .. .. .. .. .. .. .. 95.0 Nigeria 21.1 27.1 0.0 58.2 0.0 14.7 126.5 2.6 78.8 Rwanda .. .. .. .. .. .. .. .. 95.0 São Tomé and Principe .. .. .. .. .. .. .. .. .. Senegal 2.4 9.5 0.0 1.7 0.0 85.8 158.2 7.1 51.0 Seychelles .. .. .. .. .. .. .. .. 5.0 Sierra Leone .. .. .. .. .. .. .. .. 95.0 Somalia .. .. .. .. .. .. .. .. 95.0 South Africa 255.5 0.5 94.2 0.0 5.1 0.1 4,759.5 3.5 17.3 Sudan 4.5 32.4 0.0 0.0 0.0 67.6 96.4 5.3 89.9 Swaziland .. .. .. .. .. .. .. .. 58.0 Tanzania 4.4 60.1 2.7 36.2 0.0 0.9 83.9 2.6 94.0 Togo 0.1 74.0 0.0 0.0 0.0 24.4 98.8 1.9 95.0 Uganda .. .. .. .. .. .. .. .. 95.0 Zambia 9.7 99.7 0.0 0.0 0.0 0.3 602.4 2.1 85.7 Zimbabwe 8.0 53.4 46.3 0.0 0.0 0.3 1,022.2 .. 71.2 NORTH AFRICA 236.1 6.7 5.0 66.5 0.0 21.3 1,281.7 6.4 5.4 Algeria 40.2 0.7 0.0 97.3 0.0 2.0 957.1 6.8 5.0 Egypt, Arab Rep. 131.0 11.2 0.0 68.4 0.0 19.7 1,425.4 5.8 5.0 Libya 28.7 0.0 0.0 41.0 0.0 59.0 3,909.3 5.2 5.0 Morocco 20.8 4.5 56.2 13.8 0.0 24.2 735.6 8.4 6.8 Tunisia 15.3 0.2 0.0 88.7 0.0 10.8 1,298.0 8.3 5.0 a. Shares may not sum to 100 percent because other sources of generated electricity (such as geothermal, solar, and wind) are not shown. b. Data are for the most recent year available during the period speci�ed. 80 Part III. Development outcomes Infrastructure Quality Financing Firms identifying Average delay for Firms that Committed nominal electricity as major or firm in obtaining Electric power Electrical power share or own Firms using investment in energy ODA gross very severe obstacle electrical transmission and outages in a their electricity from projects with private disbursements to business operation connection distribution losses typical month own generator generator participation for energy and growth (%) (days) (% of output) (average) (%) (%) ($ millions) ($ millions) 2009–10 b 2009–10 b 2008 2009–10 b 2009–10 b 2009–10 b 2009 2009 10.5 .. 1,478.9 35.7 7.7 14.5 5.4 79.0 17.3 .. 4.7 51.9 86.8 92.6 13.9 50.5 10.1 .. 16.3 34.8 39.2 52.0 4.5 34.5 0.6 .. 0.3 53.9 23.1 .. 10.8 28.3 2.5 .. 26.1 .. .. .. .. .. .. .. 1.9 58.6 17.6 9.7 10.6 34.8 4.5 0.0 57.3 53.1 30.5 .. 4.9 48.8 10.9 .. 1.9 .. .. .. .. .. .. .. 3.4 74.6 10.6 .. 22.6 75.5 52.0 .. 0.8 .. .. .. .. .. .. .. .. 51.7 48.0 11.0 21.8 49.3 4.2 .. 132.8 71.1 8.5 76.8 25.3 81.8 43.2 .. 0.1 39.8 20.9 23.5 3.8 6.5 1.0 0.0 15.4 .. .. .. .. .. .. .. 22.5 .. .. .. .. .. .. .. 0.0 0.2 .. .. 3.0 36.8 1.0 .. 3.1 .. .. 9.5 .. .. .. 4.0 179.0 58.0 34.5 17.8 7.2 22.9 1.8 .. 0.1 .. .. .. .. .. .. .. 1.8 .. .. 22.1 .. .. .. .. 43.9 .. .. .. .. .. .. .. 0.8 .. .. .. .. .. .. .. 3.4 .. .. 14.7 .. .. .. 11.0 142.9 44.3 13.9 .. 6.8 30.9 0.0 .. 0.4 59.1 .. .. 5.4 66.5 63.1 .. 13.1 54.6 92.1 .. 13.6 29.3 5.2 .. 5.8 37.6 59.2 .. 1.0 25.3 2.1 .. 2.3 33.5 32.9 .. 5.3 20.1 0.5 .. 20.5 .. .. .. .. .. .. .. 11.2 42.9 18.7 .. 3.2 24.5 0.8 .. 5.8 .. .. 9.0 .. .. .. .. 57.6 .. .. 17.6 .. .. .. .. 4.5 63.2 37.1 .. 20.1 34.5 5.2 .. 0.6 .. .. 9.4 .. .. .. .. 72.7 .. .. .. .. .. .. .. 41.9 .. .. .. .. .. .. .. .. .. .. 19.5 .. .. .. .. 16.5 .. .. .. .. .. .. .. .. 53.4 14.8 .. 15.9 81.8 36.6 .. 30.1 .. .. .. .. .. .. .. .. .. .. 8.8 .. .. .. .. 4.8 .. .. 11.9 .. .. .. .. 2.0 .. .. .. .. .. .. .. .. .. .. 19.3 .. .. .. .. 121.4 50.9 53.9 122.8 11.1 63.6 9.3 .. 121.8 .. .. .. .. .. .. 27.0 163.0 .. .. 23.3 .. .. .. .. 8.1 .. .. 6.5 .. .. .. .. 1.3 12.5 .. 1,106.6 .. .. 18.1 .. .. .. .. 2.2 .. .. 10.6 .. .. .. .. 460.3 .. .. 14.0 .. .. .. .. 2.5 .. .. 11.0 .. .. .. .. 454.7 .. .. 12.4 .. .. .. .. 166.7 Infrastructure Part III. Development outcomes 81 Participating in growth Table 7.1 Education Primary education Literacy rate (%) Gross enrollment ratio Net enrollment ratio Student- Youth (ages 15–24) Adult (ages 15 and older) (% of relevant age group) (% of relevant age group) teacher Total Male Female Total Male Female Total Male Female Total Male Female ratio 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 SUB–SAHARAN AFRICA 75.2 79.5 70.9 65.5 74.8 56.3 .. .. .. .. .. .. .. Angola 73.1 80.8 65.5 70.0 82.9 57.6 .. .. .. .. .. .. .. Benin 54.3 64.9 43.4 41.7 54.2 29.1 121.9 129.2 114.2 94.7 .. .. .. Botswana 95.2 93.7 96.7 84.1 83.8 84.4 .. .. .. .. .. .. .. Burkina Faso .. .. .. .. .. .. 78.3 82.9 73.5 63.3 67.1 59.4 48.9 Burundi 76.6 76.9 76.3 66.6 72.6 60.9 146.6 149.1 144.2 98.9 98.2 99.6 51.4 Cameroon .. .. .. .. .. .. 113.8 122.0 105.5 91.6 97.5 85.6 46.3 Cape Verde 98.2 97.3 99.0 84.8 90.1 80.2 98.1 101.8 94.4 82.6 83.6 81.5 23.9 Central African Republic 64.7 72.2 57.3 55.2 69.1 42.1 88.6 103.8 73.6 66.7 76.9 56.6 94.6 Chad 46.3 53.5 39.0 33.6 44.5 23.1 89.7 105.2 74.2 .. .. .. 60.9 Comoros 85.3 85.8 84.7 74.2 79.7 68.7 .. .. .. .. .. .. .. Congo, Dem. Rep. 67.7 73.3 62.1 67.0 79.5 54.9 90.3 97.5 83.0 .. .. .. 37.3 Congo, Rep. .. .. .. .. .. .. 119.5 123.5 115.5 .. .. .. 64.4 Côte d’Ivoire 66.6 72.1 61.0 55.3 64.7 45.3 73.6 81.2 66.0 57.2 62.5 52.0 42.1 Djibouti .. .. .. .. .. .. 54.5 57.6 51.3 44.4 46.8 42.1 .. Equatorial Guinea 97.9 97.7 98.2 93.3 97.0 89.8 81.9 83.6 80.1 53.5 54.0 53.0 24.2 Eritrea 88.7 91.6 85.8 66.6 77.9 56.0 48.3 52.8 43.8 35.7 38.1 33.2 38.5 Ethiopia .. .. .. .. .. .. 102.5 107.1 97.8 82.7 85.2 80.1 57.9 Gabon 97.6 98.6 96.6 87.7 91.4 84.1 .. .. .. .. .. .. .. Gambia, The 65.5 71.0 60.0 46.5 57.6 35.8 .. .. .. .. .. .. .. Ghana 80.1 81.2 78.9 66.6 72.8 60.4 105.2 105.7 104.6 75.9 75.5 76.2 33.1 Guinea 61.1 68.1 53.8 39.5 50.8 28.1 89.8 96.7 82.8 72.9 77.9 67.8 .. Guinea-Bissau 70.9 78.2 63.6 52.2 66.9 38.0 .. .. .. .. .. .. .. Kenya 92.7 91.9 93.6 87.0 90.5 83.5 112.7 113.9 111.4 82.6 82.2 83.0 46.8 Lesotho 92.0 85.7 98.1 89.7 82.9 95.3 104.4 104.6 104.2 73.1 71.2 75.0 .. Liberia 75.6 70.4 80.9 59.1 63.7 54.5 .. .. .. .. .. .. .. Madagascar .. .. .. .. .. .. 160.4 162.3 158.5 .. .. .. 47.9 Malawi 86.5 86.9 86.0 73.7 80.6 67.0 119.3 117.6 121.1 90.8 88.5 93.2 .. Mali .. .. .. .. .. .. 94.7 102.9 86.3 72.9 79.3 66.4 50.1 Mauritania 67.7 70.9 64.3 57.5 64.5 50.3 104.4 100.6 108.4 76.3 73.9 78.8 39.1 Mauritius 96.5 95.5 97.6 87.9 90.6 85.3 100.0 100.0 100.1 94.0 93.4 94.6 21.6 Mozambique 70.9 78.1 63.7 55.1 70.1 41.5 114.4 120.7 108.1 90.6 93.2 87.9 61.3 Namibia 93.0 91.1 94.9 88.5 88.9 88.1 112.1 113.0 111.2 89.1 87.1 91.1 30.1 Niger .. .. .. .. .. .. 62.4 69.2 55.2 54.0 60.0 47.6 38.8 Nigeria 71.8 78.1 65.3 60.8 72.0 49.8 .. .. .. .. .. .. .. Rwanda 77.2 77.0 77.4 70.7 75.0 66.8 150.7 149.8 151.4 .. .. .. 68.3 São Tomé and Príncipe 95.3 94.9 95.8 88.8 93.7 84.0 131.2 130.7 131.8 97.5 95.5 99.5 26.2 Senegal 65.0 74.2 56.2 49.7 61.8 38.7 83.7 82.1 85.4 73.1 71.7 74.4 34.7 Seychelles .. .. .. .. .. .. 106.2 105.0 107.4 94.4 93.4 95.4 13.8 Sierra Leone 57.6 67.6 48.1 40.9 52.7 30.1 .. .. .. .. .. .. .. Somalia .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa .. .. .. .. .. .. 101.2 103.2 99.1 84.7 84.7 84.6 .. Sudan 85.9 89.1 82.7 70.2 79.6 60.8 74.0 77.8 70.0 .. .. .. 38.4 Swaziland 93.4 91.9 94.9 86.9 87.8 86.2 .. .. .. .. .. .. .. Tanzania 77.4 78.5 76.4 72.9 79.0 66.9 104.9 104.9 104.9 96.4 95.8 97.0 53.7 Togo .. .. .. .. .. .. 115.2 118.8 111.5 93.5 98.1 89.0 41.3 Uganda .. .. .. .. .. .. 121.6 120.8 122.4 92.2 90.9 93.6 49.3 Zambia 74.6 81.8 67.3 70.9 80.6 61.3 112.9 113.5 112.4 90.7 89.6 91.8 .. Zimbabwe 98.9 98.4 99.5 91.9 94.7 89.4 .. .. .. .. .. .. .. NORTH AFRICA .. .. .. .. .. .. .. .. .. .. .. .. .. Algeria .. .. .. .. .. .. 107.7 111.0 104.2 93.8 94.8 92.9 23.0 Egypt, Arab Rep. .. .. .. .. .. .. .. .. .. .. .. .. .. Libya 99.9 99.9 99.8 88.9 95.2 82.0 .. .. .. .. .. .. .. Morocco 79.5 86.7 72.1 56.1 68.9 43.9 107.4 111.9 102.7 89.7 91.2 88.1 26.6 Tunisia .. .. .. .. .. .. .. .. .. .. .. .. .. 82 Part III. Development outcomes Human development Public spending on Secondary education Tertiary education education (%) Gross enrollment ratio Net enrollment ratio Gross enrollment ratio Share of (% of relevant age group) (% of relevant age group) Student- (% of relevant age group) government Total Male Female Total Male Female teacher ratio Total Male Female expenditure Share of GDP 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 22.0 8.9 19.8 22.6 16.8 15.4 17.7 13.1 25.6 3.4 4.6 2.2 .. .. 21.2 24.6 17.8 .. .. .. 26.5 2.7 .. .. 23.4 8.3 41.5 45.2 37.7 .. .. .. .. 9.0 10.1 8.0 19.2 3.7 81.5 74.7 88.2 63.3 .. .. 18.2 14.9 13.1 16.7 15.9 5.9 13.6 17.5 9.8 10.4 13.2 7.7 80.1 2.5 3.5 1.5 .. 1.3 24.1 34.1 14.0 .. .. .. 32.3 2.0 3.4 0.6 12.6 3.2 .. .. .. .. .. .. .. 5.2 .. .. .. .. 36.7 47.0 26.2 .. .. .. 16.0 6.0 .. .. .. .. .. .. .. .. .. .. .. 6.4 10.6 2.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 30.5 35.1 25.8 .. .. .. .. 3.5 4.1 2.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 31.8 37.1 26.4 27.4 31.6 23.1 42.7 2.0 3.0 1.0 .. .. 34.4 38.8 30.0 .. .. .. 47.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 57.2 60.5 53.6 46.1 48.0 44.1 18.3 8.6 10.6 6.6 .. .. 37.0 46.3 27.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 59.5 62.4 56.5 49.6 51.1 48.1 29.7 4.1 4.8 3.3 .. .. 45.0 37.8 52.3 28.8 21.9 35.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 31.5 32.5 30.6 .. .. .. 23.5 3.6 3.8 3.4 .. 3.0 29.5 31.5 27.6 25.0 25.7 24.4 .. .. .. .. .. .. 38.3 46.4 30.1 30.1 36.6 23.5 .. 6.0 8.5 3.5 22.3 4.4 .. .. .. .. .. .. .. 3.8 5.3 2.2 .. .. 87.2 86.1 88.3 .. .. .. 16.0 .. .. .. 11.4 3.2 23.4 26.2 20.6 14.7 15.6 13.7 37.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 11.7 14.5 8.8 .. .. .. 27.6 1.4 2.2 0.7 19.3 4.5 .. .. .. .. .. .. .. .. .. .. .. .. 26.7 27.5 26.0 .. .. .. .. 4.8 5.5 4.1 .. .. 50.1 47.3 52.8 .. .. .. .. 4.1 4.2 3.9 .. .. .. .. .. .. .. .. .. 8.0 10.2 5.9 .. 5.8 105.0 102.6 107.5 97.3 95.4 99.2 12.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 18.1 4.3 .. .. .. .. .. .. .. .. .. .. .. .. 93.9 91.6 96.1 .. .. .. .. .. .. .. 16.9 5.4 38.0 40.3 35.5 .. .. .. 22.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 27.4 30.7 24.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 17.6 4.6 27.4 29.8 24.9 .. .. .. 18.1 4.1 4.5 3.6 15.0 3.2 48.7 52.8 44.5 46.2 50.5 41.8 .. .. .. .. .. .. .. .. .. .. .. .. .. 3.2 3.9 2.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 30.6 25.2 36.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 12.9 13.7 12.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. Human development Part III. Development outcomes 83 Participating in growth Table 7.2 Health Mortality Diseases Life expectancy at birth Infant mortality Maternal mortality Prevalence Malaria (years) Under-five rate ratio, modeled of HIV Incidence of Clinical mortality rate (per 1,000 estimate (per (% ages tuberculosis (per cases Reported Total Male Female (per 1,000) live births) 100,000 live births) 15–49) 100,000 people) reported deaths 2009 2009 2009 2009 2009 2008 2009 2009 2009 c 2009 SUB–SAHARAN AFRICA 52.5 51.5 53.6 130 81 646 5.4 344 71,675,530 113,326 Angola 47.6 45.6 49.6 161 98 610 2.0 298 2,221,076 10,530 Benin 61.8 60.7 63.0 118 75 410 1.2 93 1,256,708 1,375 Botswana 55.0 55.1 54.8 57 43 190 24.8 694 14,878 6 Burkina Faso 53.3 52.0 54.7 166 91 560 1.2 215 4,399,837 7,982 Burundi 50.9 49.4 52.4 166 101 970 3.3 348 1,757,387 714 Cameroon 51.4 50.8 51.9 154 95 600 5.3 182 1,883,199 4,943 Cape Verde 71.3 68.7 74.1 28 23 94 .. 148 65 2 Central African Republic 47.3 45.9 48.8 171 112 850 4.7 327 175,210 667 Chad 48.9 47.7 50.2 209 124 1,200 3.4 283 182,415 221 Comoros 65.8 63.6 68.1 104 75 340 0.1 39 49,679 .. Congo, Dem. Rep. 47.8 46.2 49.4 199 126 670 .. 372 6,749,112 21,168 Congo, Rep. 53.7 52.8 54.7 128 81 580 3.4 382 92,855 116 Côte d’Ivoire 58.0 56.7 59.3 119 83 470 3.4 399 1,847,367 18,156 Djibouti 55.7 54.4 57.2 94 75 300 2.5 620 7,120 0 Equatorial Guinea 50.6 49.5 51.8 145 88 280 5.0 117 78,983 23 Eritrea 59.9 57.6 62.2 55 39 280 0.8 99 21,298 23 Ethiopia 55.7 54.3 57.1 104 67 470 .. 359 3,043,203 1,121 Gabon 60.9 59.6 62.1 69 52 260 5.2 501 112,840 197 Gambia, The 56.2 54.6 58.0 103 78 400 2.0 269 479,409 240 Ghana 56.8 55.9 57.7 69 47 350 1.8 201 1,899,544 3,378 Guinea 58.3 56.4 60.4 142 88 680 1.3 318 812,471 586 Guinea-Bissau 48.2 46.7 49.8 193 115 1,000 2.5 229 143,011 369 Kenya 54.9 54.5 55.3 84 55 530 6.3 305 8,123,689 .. Lesotho 45.4 45.0 45.7 84 61 530 23.6 634 .. .. Liberia 58.7 57.3 60.1 112 80 990 1.5 288 871,560 1,706 Madagascar 60.8 59.2 62.5 58 41 440 0.2 261 215,110 173 Malawi 53.8 52.9 54.7 110 69 510 11.0 304 5,455,423 6,527 Mali 48.8 48.1 49.5 191 101 830 1.0 324 1,633,423 2,331 Mauritania 57.0 55.0 59.0 117 74 550 0.7 330 167,705 91 Mauritius 72.6 69.2 76.2 17 15 36 1.0 22 .. .. Mozambique 48.1 47.4 48.8 142 96 550 11.5 409 4,310,086 3,747 Namibia 61.6 60.8 62.4 48 34 180 13.1 727 81,812 46 Niger 52.0 51.1 52.9 160 76 820 0.8 181 309,675 2,159 Nigeria 48.1 47.6 48.7 138 86 840 3.6 295 4,295,686 7,522 Rwanda 50.6 48.8 52.5 111 70 540 2.9 376 1,247,583 809 São Tomé and Príncipe 65.8 63.9 67.7 78 52 .. .. 98 3,893 23 Senegal 55.9 54.4 57.5 93 51 410 0.9 282 222,232 574 Seychelles 73.7 68.5 79.2 12 11 .. .. 31 .. .. Sierra Leone 47.9 46.7 49.2 192 123 970 1.6 644 646,808 1,734 Somalia 50.1 48.7 51.5 180 109 1,200 0.7 285 56,153 45 South Africa 51.6 50.3 53.1 62 43 410 17.8 971 6,072 45 Sudan 58.5 57.0 60.1 108 69 750 1.1 119 2,686,822 1,396 Swaziland 46.3 47.1 45.5 73 52 420 25.9 1,257 6,639 13 Tanzania 56.3 55.5 57.1 108 68 790 5.6 183 40 840 Togo 62.9 61.2 64.6 98 64 350 3.2 446 618,842 1,556 Uganda 53.4 52.8 54.1 128 79 430 6.5 293 9,775,318 6,296 Zambia 46.3 45.8 46.9 141 86 470 13.5 433 2,976,395 3,862 Zimbabwe 45.4 45.3 45.6 90 56 790 14.3 742 736,897 14 NORTH AFRICA 71.5 69.7 73.4 26 23 92 0.1 43 239 3 Algeria 72.6 71.2 74.1 32 29 120 0.1 59 .. .. Egypt, Arab Rep. 70.3 68.6 72.2 21 18 82 0.1 19 94 2 Libya 74.5 72.0 77.2 19 17 64 .. 40 .. .. Morocco 71.6 69.4 73.9 38 33 110 0.1 92 145 1 Tunisia 74.5 72.5 76.5 21 18 60 0.1 24 .. .. 84 Part III. Development outcomes Human development Prevention and treatment Child immunization Contraceptive use Births Children with fever rate (% of (% of married women attended Children sleeping Tuberculosis Tuberculosis receiving any children ages Malnutrition (% of ages 15–49) by skilled under insecticide- case detection treatment antimalarial treatment 12–23 months) children under age 5) health staff Any Modern treated nets rate, all forms success rate (% of same or next day Measles DPT b Stunting Underweight (% of total) method method (% of under age 5) (%) registered cases) (% of under age 5) 2009 2009 2007–09a 2007–09a 2007–09a 2007–09a 2007–09a 2007–09a 2009 2008 2007–09a 68 70 .. 48.0 79.0 77 73 .. .. 47.3 .. .. 17.7 75.0 70.0 29.3 72 83 .. .. .. .. .. .. 47.0 89.0 .. 94 96 .. .. 94.6 52.8 .. .. 62.0 65.0 .. 75 82 35.1 26.0 .. .. .. .. 14.0 76.0 .. 91 92 .. .. .. .. .. .. 25.0 90.0 .. 74 80 .. .. .. .. .. .. 70.0 .. .. 96 99 .. .. .. .. .. .. 44.0 74.0 .. 62 54 .. .. 43.7 .. .. .. 60.0 71.0 .. 23 23 .. .. .. .. .. .. 26.0 .. .. 79 83 .. .. .. .. .. .. 46.0 90.0 .. 76 77 45.8 28.2 74.0 20.6 5.8 5.8 46.0 87.0 29.8 76 91 .. .. .. .. .. .. 69.0 76.0 .. 67 81 .. .. .. .. .. .. 27.0 76.0 .. 73 89 .. .. .. 22.5 .. 19.9 71.0 84.0 .. 51 33 .. .. .. .. .. .. 89.0 56.0 .. 95 99 .. .. .. .. .. .. 58.0 76.0 .. 75 79 .. .. .. .. .. 33.1 50.0 84.0 9.5 55 45 .. .. .. .. .. .. 42.0 53.0 .. 96 98 .. .. .. .. .. .. 47.0 84.0 .. 93 94 28.6 14.3 57.1 23.5 16.6 28.2 31.0 86.0 43.0 51 57 40.0 20.8 46.1 .. .. 4.5 26.0 78.0 .. 76 68 .. .. .. .. .. .. 59.0 70.0 .. 74 75 35.2 16.4 43.8 45.5 38.9 46.1 85.0 85.0 23.2 85 83 .. .. 61.5 47.0 .. .. 93.0 73.0 .. 64 64 39.4 20.4 46.3 11.4 10.3 26.4 52.0 79.0 67.2 64 78 49.2 .. 43.9 39.9 28.2 45.8 44.0 81.0 19.7 92 93 .. .. .. .. .. .. 49.0 87.0 .. 71 74 .. .. .. .. .. .. 16.0 82.0 .. 59 64 24.2 16.7 60.9 9.3 8.0 .. 24.0 68.0 20.7 99 99 .. .. .. .. .. .. 41.0 87.0 .. 77 76 .. .. 55.3 16.2 .. 22.8 46.0 84.0 36.7 76 83 29.6 17.5 81.4 55.1 53.5 .. 76.0 82.0 .. 73 70 .. .. .. .. .. 42.8 36.0 81.0 .. 41 42 41.0 26.7 38.9 14.6 8.1 5.5 19.0 78.0 33.2 92 97 .. .. 52.1 36.4 26.1 55.7 19.0 87.0 5.6 90 98 29.3 13.1 81.7 38.4 .. 56.2 49.0 94.0 8.4 79 86 .. .. .. .. .. 29.2 31.0 84.0 9.1 97 99 .. .. .. .. .. .. 57.0 100.0 .. 71 75 37.4 21.3 42.4 8.2 6.0 25.8 31.0 86.0 30.1 24 31 .. .. .. .. .. .. 42.0 81.0 .. 62 69 .. .. .. .. .. .. 74.0 76.0 .. 82 84 .. .. .. .. .. .. 52.0 81.0 .. 95 95 29.5 6.1 69.0 50.6 46.8 0.6 67.0 68.0 0.6 91 85 .. .. .. .. .. 25.7 77.0 88.0 56.7 84 89 .. .. .. .. .. .. 10.0 79.0 .. 68 64 .. .. .. .. .. .. 44.0 70.0 .. 85 81 45.8 14.9 46.5 40.8 26.5 41.1 80.0 88.0 43.3 76 73 .. .. 60.2 64.9 .. 17.3 46.0 74.0 23.6 94 97 .. 88 93 .. .. .. .. .. .. 100.0 90.0 .. 95 97 30.7 6.8 78.9 60.3 57.6 .. 63.0 89.0 .. 98 98 21.0 5.6 .. .. .. .. 82.0 69.0 .. 98 99 .. .. .. .. .. .. 93.0 85.0 .. 98 99 .. .. .. .. .. .. 86.0 86.0 .. (continued) Human development Part III. Development outcomes 85 Participating in growth Table 7.2 Health (continued) Water and sanitation Human resources Population with sustainable access Population with sustainable access Health workers to an improved water source to improved sanitation (per 1,000 people) (% of total (% of urban (% of rural (% of total (% of urban (% of rural Nurses and Community population) population) population) population) population) population) Physicians midwives workers 2008 2008 2008 2008 2008 2008 2008–09 a 2008–09 a 2008 SUB–SAHARAN AFRICA 60 83 47 31 44 24 .. Angola 50 60 38 57 86 18 .. .. .. Benin 75 84 69 12 24 4 0.1 0.8 .. Botswana 95 99 90 60 74 39 .. .. .. Burkina Faso 76 95 72 11 33 6 0.1 0.7 .. Burundi 72 83 71 46 49 46 .. .. .. Cameroon 74 92 51 47 56 35 .. .. .. Cape Verde 84 85 82 54 65 38 0.6 1.3 .. Central African Republic 67 92 51 34 43 28 .. .. .. Chad 50 67 44 9 23 4 .. .. .. Comoros 95 91 97 36 50 30 .. .. .. Congo, Dem. Rep. 46 80 28 23 23 23 .. .. .. Congo, Rep. 71 95 34 30 31 29 .. .. .. Côte d’Ivoire 80 93 68 23 36 11 0.1 0.5 .. Djibouti 92 98 52 56 63 10 .. 0.8 .. Equatorial Guinea .. .. .. .. .. .. .. .. .. Eritrea 61 74 57 14 52 4 .. .. .. Ethiopia 38 98 26 12 29 8 .. .. .. Gabon 87 95 41 33 33 30 .. .. .. Gambia, The 92 96 86 67 68 65 0.0 0.6 0.1 Ghana 82 90 74 13 18 7 0.1 1.1 0.2 Guinea 71 89 61 19 34 11 .. .. .. Guinea-Bissau 61 83 51 21 49 9 0.0 0.6 .. Kenya 59 83 52 31 27 32 .. .. .. Lesotho 85 97 81 29 40 25 .. .. .. Liberia 68 79 51 17 25 4 0.0 0.3 .. Madagascar 41 71 29 11 15 10 .. .. .. Malawi 80 95 77 56 51 57 0.0 0.3 0.7 Mali 56 81 44 36 45 32 0.0 0.3 .. Mauritania 49 52 47 26 50 9 0.1 0.7 .. Mauritius 99 100 99 91 93 90 .. .. .. Mozambique 47 77 29 17 38 4 .. .. .. Namibia 92 99 88 33 60 17 .. .. .. Niger 48 96 39 9 34 4 0.0 0.1 .. Nigeria 58 75 42 32 36 28 0.4 1.6 0.1 Rwanda 65 77 62 54 50 55 .. .. .. São Tomé and Príncipe 89 89 88 26 30 19 .. .. .. Senegal 69 92 52 51 69 38 0.1 0.4 .. Seychelles .. 100 .. .. 97 .. .. .. .. Sierra Leone 49 86 26 13 24 6 0.0 0.2 0.0 Somalia 30 67 9 23 52 6 .. .. .. South Africa 91 99 78 77 84 65 .. .. .. Sudan 57 64 52 34 55 18 0.3 0.8 .. Swaziland 69 92 61 55 61 53 .. .. .. Tanzania 54 80 45 24 32 21 .. .. .. Togo 60 87 41 12 24 3 0.1 0.3 .. Uganda 67 91 64 48 38 49 .. .. .. Zambia 60 87 46 49 59 43 .. .. .. Zimbabwe 82 99 72 44 56 37 .. .. .. NORTH AFRICA 92 95 87 89 94 83 .. Algeria 83 85 79 95 98 88 .. .. .. Egypt, Arab Rep. 99 100 98 94 97 92 2.8 3.5 .. Libya .. .. .. 97 97 96 1.9 6.8 .. Morocco 81 98 60 69 83 52 0.6 0.9 .. Tunisia 94 99 84 85 96 64 1.2 3.3 .. a. Data are for the most recent year available during the period speci�ed. b. Diphtheria, pertussis, and tetanus toxoid. c. Malaria cases reported before 2000 can be probable and con�rmed or only con�rmed, depending on the country. 86 Part III. Development outcomes Human development Health expenditure Private prepaid Share of GDP (%) Share of total health expenditure (%) Out-of-pocket plans (% of private (% of private External resources expenditure expenditure Health expenditure Total Public Private Public Private for health on health) on health) per capita ($) 2009 2009 2009 2009 2009 2009 2009 2009 2009 6.6 2.9 3.7 44.0 56.0 .. 62.9 .. 76.0 4.6 4.1 0.5 89.0 11.0 2.7 100.0 0.0 203.8 4.2 2.3 1.9 55.2 44.8 22.6 92.7 7.3 31.9 10.3 8.2 2.1 80.0 20.0 18.8 34.0 6.5 611.9 6.4 3.9 2.4 61.7 38.3 21.9 93.0 3.4 38.1 13.1 6.0 7.1 46.0 54.0 45.2 66.1 0.0 19.8 5.6 1.6 4.0 27.9 72.1 8.1 94.9 0.0 61.1 3.9 2.9 1.0 74.0 26.0 7.4 99.7 0.0 146.1 4.3 1.6 2.6 38.7 61.3 40.4 95.0 0.0 19.3 7.0 3.9 3.1 55.2 44.8 6.9 96.7 0.0 41.8 3.4 2.1 1.3 61.6 38.4 15.3 100.0 0.0 27.8 9.5 4.9 4.7 51.0 49.0 35.8 76.2 0.0 15.6 3.0 1.6 1.4 53.8 46.2 7.2 100.0 0.0 70.1 5.1 1.0 4.1 18.8 81.2 10.6 98.8 1.2 55.3 7.0 5.3 1.6 76.9 23.1 30.2 98.6 1.4 84.5 3.9 3.4 0.5 86.9 13.1 3.2 83.5 0.0 709.4 2.2 1.0 1.2 44.6 55.4 65.6 100.0 0.0 10.1 4.3 2.0 2.2 47.6 52.4 39.5 80.1 1.5 14.7 3.5 1.7 1.8 47.9 52.1 1.7 100.0 0.0 266.3 6.0 3.0 3.0 50.1 49.9 26.3 48.5 3.1 25.6 6.9 3.1 3.8 45.0 55.0 16.8 78.6 6.2 45.1 5.7 0.9 4.9 15.2 84.8 15.6 99.4 0.0 18.8 6.1 1.6 4.5 25.5 74.5 42.0 56.0 0.0 18.4 4.3 1.5 2.9 33.8 66.2 36.1 77.4 8.8 33.2 8.2 5.6 2.6 68.2 31.8 30.4 68.9 0.0 70.0 13.2 5.3 8.0 39.7 60.3 47.0 52.2 0.0 29.4 4.1 2.8 1.4 67.1 32.9 28.3 67.8 15.1 18.0 6.2 3.6 2.6 58.0 42.0 99.1 28.5 14.5 19.1 5.6 2.7 2.9 47.9 52.1 25.6 99.5 0.5 38.4 2.5 1.6 0.9 62.6 37.4 25.6 100.0 0.0 21.9 5.7 2.1 3.6 36.9 63.1 1.6 88.7 6.3 383.1 5.7 4.1 1.5 73.2 26.8 72.0 43.6 1.5 24.7 5.9 4.0 2.0 66.6 33.4 14.9 17.8 61.0 258.0 6.1 3.5 2.6 57.6 42.4 32.6 96.2 3.2 20.9 5.8 2.1 3.7 36.3 63.7 4.9 95.6 3.1 69.3 9.0 3.9 5.1 43.2 56.8 53.2 44.4 10.2 48.2 7.1 2.9 4.2 41.0 59.0 38.7 68.5 0.0 90.7 5.7 3.1 2.5 55.6 44.4 14.0 78.5 17.9 58.9 4.0 3.1 0.9 76.8 23.2 1.4 30.9 0.0 365.7 13.1 0.9 12.2 7.2 92.8 20.4 89.5 1.0 43.9 .. .. .. .. .. .. .. .. .. 8.5 3.4 5.1 40.1 59.9 1.9 29.6 66.1 485.4 7.3 2.0 5.3 27.4 72.6 3.2 96.2 1.0 94.6 6.3 4.0 2.3 63.3 36.7 12.2 42.3 18.9 155.8 5.1 3.8 1.4 73.6 26.4 56.5 65.1 14.5 25.3 5.9 1.7 4.2 28.2 71.8 17.4 84.2 4.3 28.9 8.2 1.6 6.7 19.0 81.0 20.9 65.4 0.0 42.5 4.8 2.5 2.2 53.0 47.0 50.3 74.5 4.1 47.1 .. .. .. .. .. .. .. .. .. 5.3 3.0 2.3 56.8 43.2 .. 93.4 .. 173.4 5.8 5.0 0.8 86.2 13.8 0.0 94.7 5.1 267.9 5.0 2.1 2.9 41.7 58.3 1.5 97.7 1.7 113.3 3.9 2.6 1.3 66.1 33.9 1.0 100.0 0.0 416.7 5.5 1.9 3.6 34.4 65.6 0.2 86.3 13.7 155.7 6.2 3.4 2.9 54.0 46.0 1.2 87.0 11.2 240.0 Human development Part III. Development outcomes 87 Participating in growth Table 8.1 Rural development Rural population (%) Rural population density (rural population per Share of total population Annual growth sq km of arable land) 1990 2008 2009 1990 2008 2009 1990 2008 SUB–SAHARAN AFRICA 71.8 63.5 63.0 2.2 1.7 1.7 286.0 358.0 Angola 62.9 43.3 42.4 0.7 0.6 0.5 231.2 229.5 Benin 65.5 58.8 58.4 2.2 2.5 2.4 194.5 199.7 Botswana 58.1 40.4 39.7 –2.1 –0.4 –0.4 187.0 310.6 Burkina Faso 86.2 80.4 80.0 2.4 2.9 2.9 215.8 194.5 Burundi 93.7 89.6 89.3 2.3 2.6 2.5 572.4 803.8 Cameroon 59.3 43.2 42.4 1.5 0.4 0.3 122.1 138.4 Cape Verde 55.9 40.4 39.6 –2.2 –0.4 –0.5 483.0 309.8 Central African Republic 63.2 61.4 61.3 1.9 1.6 1.6 96.4 138.1 Chad 79.2 73.3 72.9 2.9 2.1 2.0 147.7 186.1 Comoros 72.1 71.9 71.9 2.0 2.3 2.3 402.4 578.6 Congo, Dem. Rep. 72.2 66.0 65.4 3.7 1.8 1.8 400.7 633.4 Congo, Rep. 45.7 38.7 38.3 1.9 0.8 0.9 233.4 285.2 Côte d’Ivoire 60.3 51.2 50.6 3.1 1.0 1.0 312.9 376.7 Djibouti 24.3 12.7 12.3 4.1 –1.3 –1.5 13,614.8 10,785.4 Equatorial Guinea 65.3 60.6 60.5 1.9 2.3 2.3 190.5 305.0 Eritrea 84.2 79.3 78.8 1.3 2.4 2.4 .. 583.0 Ethiopia 87.4 83.0 82.7 3.1 2.2 2.2 .. 492.4 Gabon 30.9 15.0 14.5 –1.0 –1.3 –1.5 97.0 66.7 Gambia, The 61.7 43.6 42.7 2.3 0.8 0.7 303.6 185.5 Ghana 63.6 50.0 49.2 1.7 0.6 0.6 352.6 265.2 Guinea 72.0 65.6 65.1 3.2 1.5 1.6 547.8 268.6 Guinea-Bissau 71.9 70.2 70.1 0.8 2.1 2.1 294.0 368.4 Kenya 81.8 78.4 78.1 3.1 2.3 2.3 384.1 573.4 Lesotho 86.0 74.5 73.8 1.0 –0.1 –0.1 434.7 430.3 Liberia 54.7 39.9 39.2 –3.8 2.8 2.5 338.7 378.0 Madagascar 76.4 70.5 70.1 2.2 2.2 2.2 316.6 456.6 Malawi 88.4 81.2 80.7 3.5 2.2 2.2 371.3 344.4 Mali 76.7 67.8 67.3 1.4 1.5 1.5 323.3 177.7 Mauritania 60.3 59.0 58.8 1.0 2.1 2.0 299.7 474.2 Mauritius 56.1 57.5 57.5 0.2 0.5 0.4 593.0 838.9 Mozambique 78.9 63.2 62.4 0.2 1.1 1.0 309.7 314.2 Namibia 72.3 63.2 62.6 3.4 1.0 1.0 155.2 168.2 Niger 84.6 83.5 83.4 2.8 3.8 3.8 60.6 84.7 Nigeria 64.7 51.6 50.9 1.6 1.0 0.9 213.2 208.2 Rwanda 94.6 81.7 81.4 –0.4 2.4 2.5 768.7 615.3 São Tomé and Príncipe 56.4 39.4 38.6 0.2 –0.5 –0.5 3,274.5 701.9 Senegal 61.0 57.6 57.4 2.4 2.2 2.2 148.7 201.0 Seychelles 50.7 45.7 45.2 0.9 1.2 0.1 3,549.0 3,970.4 Sierra Leone 67.1 62.2 61.9 0.9 2.0 1.9 563.8 192.8 Somalia 70.3 63.5 63.0 0.0 1.5 1.6 453.7 566.6 South Africa 48.0 39.3 38.8 1.0 –0.1 –0.2 125.7 131.8 Sudan 73.4 56.6 55.7 1.2 0.7 0.6 155.4 113.0 Swaziland 77.1 75.1 74.8 3.2 1.0 1.1 370.2 492.5 Tanzania 81.1 74.5 74.0 2.7 2.3 2.3 229.4 329.6 Togo 69.9 58.0 57.3 1.9 1.3 1.2 130.7 152.3 Uganda 88.9 87.0 86.9 3.2 3.1 3.1 315.3 487.6 Zambia 60.6 64.6 64.4 3.1 2.2 2.2 209.1 346.1 Zimbabwe 71.0 62.7 62.2 1.9 –0.7 –0.3 257.0 209.4 NORTH AFRICA 51.5 47.2 46.9 1.7 1.1 1.1 823.3 1,078.3 Algeria 47.9 34.8 34.1 0.8 –0.3 –0.3 171.0 159.6 Egypt, Arab Rep. 56.5 57.3 57.2 2.5 1.7 1.7 1,429.4 1,684.1 Libya 24.3 22.5 22.3 2.0 1.2 1.2 58.8 80.8 Morocco 51.6 44.0 43.6 0.5 0.4 0.4 147.0 172.6 Tunisia 42.1 33.5 33.1 0.5 –0.2 –0.2 118.0 122.0 a. Data are for the most recent year available during the period speci�ed. 88 Part III. Development outcomes Agriculture, rural development, and environment Share of rural population with Share of rural population Rural population poverty gap at national poverty line sustainable access below the national poverty line (%) (%) To improved Surveys Surveys To an improved sanitation 1990–99a Surveys 2000–09a Surveys 1990–99a 2000–07a water source facilities Year Percent Year Percent Year Percent Year Percent 2008 2008 .. .. .. .. .. .. .. .. 46.8 24.1 .. .. .. .. .. .. .. .. 38.0 18.0 1999 33.0 2003 46.0 1999 9.4 2003 14.0 69.0 4.0 1993 55.0 2003 44.8 .. .. 2003 18.4 90.0 39.0 1998 50.7 2003 52.4 1998 15.7 2003 17.6 72.0 6.0 1998 83.2 2006 68.9 1998 45.9 2006 24.2 71.0 46.0 1996 59.6 2007 55.0 .. .. 2007 17.5 51.0 35.0 .. .. 2007 44.3 .. .. 2007 14.3 82.0 38.0 1992 74.4 2008 69.4 1992 42.5 2008 35.0 51.0 28.0 1995 48.6 2003 58.6 1995 26.3 2003 23.3 44.0 4.0 1995 69.4 2004 48.7 .. .. 2004 17.8 97.0 30.0 .. .. 2005 75.7 .. .. 2005 34.9 28.0 23.0 .. .. 2005 57.7 .. .. 2005 20.6 34.0 29.0 1998 41.5 2008 54.2 1998 14.3 2008 20.3 68.0 11.0 .. .. .. .. .. .. .. .. 52.0 10.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 57.0 4.0 1999 45.4 2004 39.3 1999 12.2 2004 8.5 26.0 8.0 .. .. 2005 44.6 .. .. 2005 16.0 41.0 30.0 1998 79.0 2003 67.8 .. .. 2003 30.5 86.0 65.0 1998 49.6 2006 39.2 1998 18.2 2006 13.5 74.0 7.0 1994 82.1 2007 63.0 1994 39.1 2007 22.0 61.0 11.0 .. .. 2002 69.1 .. .. 2002 27.8 51.0 9.0 1997 52.9 2005 49.1 1997 19.3 2005 17.5 52.0 32.0 1994 68.9 2003 60.5 1993 26.5 .. .. 81.0 25.0 .. .. 2007 67.7 .. .. 2007 26.3 51.0 4.0 1999 76.7 2005 73.5 1999 21.4 2005 28.9 29.0 10.0 1998 66.5 2004 55.9 1998 23.9 2004 8.6 77.0 57.0 .. .. 2006 57.6 .. .. .. .. 44.0 32.0 1996 68.1 2000 61.2 .. .. 2000 24.1 47.0 9.0 .. .. .. .. .. .. .. .. 99.0 90.0 1996 71.3 2008 56.9 1996 29.9 2008 22.2 29.0 4.0 1993 69.0 2003 49.0 1993 34.0 2003 16.0 88.0 17.0 1993 66.0 2007 63.9 1993 22.5 2007 21.2 39.0 4.0 1996 69.8 2004 63.8 1992 16.1 2004 26.6 42.0 28.0 .. .. 2006 64.2 .. .. 2006 26.0 62.0 55.0 .. .. 2001 64.9 .. .. 2001 24.7 88.0 19.0 1994 71.0 2005 61.9 1994 25.3 2005 21.5 52.0 38.0 .. .. .. .. .. .. .. .. .. .. 1990 88.3 2003 78.5 1990 73.1 2003 34.6 26.0 6.0 .. .. .. .. .. .. .. .. 9.0 6.0 .. .. .. .. .. .. .. .. 78.0 65.0 .. .. .. .. .. .. .. .. 52.0 18.0 .. .. 2001 75.0 .. .. 2001 37.0 61.0 53.0 1992 40.8 2007 37.4 1992 12.7 2007 11.0 45.0 21.0 .. .. 2006 74.3 .. .. 2006 29.3 41.0 3.0 1997 48.7 2009 27.2 1997 15.2 2009 7.6 64.0 49.0 1998 83.0 2006 76.8 1998 44.5 2006 38.8 46.0 43.0 1995 44.0 .. .. .. .. .. .. 72.0 37.0 .. .. .. .. .. .. .. .. 87.4 83.0 1995 30.3 .. .. 1995 4.5 .. .. 79.0 88.0 .. .. 2008 30.0 .. .. .. .. 98.0 92.0 .. .. .. .. .. .. .. .. .. 96.0 1999 24.2 2007 14.5 .. .. .. .. 60.0 52.0 .. .. .. .. .. .. .. .. 84.0 64.0 Agriculture, rural development, and environment Part III. Development outcomes 89 Participating in growth Table 8.2 Agriculture Agriculture Cereal Trade value Gross production index (1999–2001=100) (thousands of metric tons) Agricultural Food added Agriculture Exports Imports Exports Imports (% of GDP) total Crop Livestock Food Cereal Production Exports Imports ($ millions) ($ millions) ($ millions) ($ millions) 2009a 2009 2009 2009 2009 2009 2009 2008 2008 2008 2008 2008 2008 SUB–SAHARAN AFRICA 13.1 .. 128.7 125.1 130 .. 116,492 2,199 21,901 25,448 32,546 15,199 26,522 Angola Excluding South Africa 10.2 196.0 250.0 92.0 198.0 174.0 1,030 1 734 12 2,375 10 1,824 Benin Excl. S. Africa & Nigeria .. 112.0 110.0 135.0 116.0 136.0 1,508 5 226 450 791 300 745 Botswana Angola 3.1 113.0 120.0 112.0 113.0 182.0 56 2 177 150 609 115 467 Burkina Benin Faso .. 140.0 144.0 132.0 136.0 158.0 3,627 11 205 273 294 67 228 Burundi Botswana .. 109.0 108.0 118.0 110.0 114.0 300 0 29 57 49 2 44 Cameroon Burkina Faso .. 114.0 117.0 105.0 120.0 148.0 2,017 0 551 962 624 681 541 Cape Verde Burundi 9.2 118.0 107.0 141.0 118.0 43.0 7 1 103 1 194 1 190 Central African Republic Cameroon 55.5 119.0 110.0 132.0 123.0 148.0 251 0 31 23 33 16 27 Chad Cape Verde .. 118.0 118.0 120.0 125.0 172.0 2,193 0 147 87 143 54 111 Comoros Central African Republic 46.3 112.0 113.0 103.0 112.0 115.0 26 0 47 8 55 8 51 Congo, Chad Dem. Rep. 42.9 97.0 97.0 96.0 98.0 97.0 1,573 5 902 57 959 11 830 Congo, Rep. Comoros 4.5 124.0 116.0 157.0 123.0 183.0 23 0 175 67 469 23 413 Côte d’Ivoire Congo, Dem. Rep. 24.4 110.0 109.0 132.0 120.0 113.0 1,471 38 1,090 4,361 1,224 3,382 1,036 Djibouti Congo, Rep. .. 147.0 101.0 158.0 147.0 90.0 0 0 201 38 432 37 383 Equatorial Guinea Côte d’Ivoire 3.5 91.0 90.0 104.0 89.0 .. .. .. 30 3 85 3 53 Eritrea Djibouti 14.4 126.0 154.0 101.0 126.0 237.0 227 1 119 2 66 2 65 Ethiopia Equatorial Guinea 50.7 149.0 153.0 140.0 151.0 170.0 15,502 2 1,424 1,352 1,347 576 1,131 Gabon Eritrea 5.1 103.0 104.0 100.0 103.0 127.0 47 0 135 81 391 3 322 Gambia, Ethiopia The 27.5 118.0 114.0 132.0 117.0 177.0 311 0 169 16 111 15 89 Ghana Gabon 31.7 154.0 156.0 127.0 155.0 156.0 2,607 0 825 1,532 1,311 1,482 1,214 Guinea Gambia, The 17.2 130.0 133.0 167.0 133.0 169.0 2,659 15 324 58 264 28 220 Guinea-Bissau Ghana .. 123.0 120.0 128.0 122.0 146.0 215 0 32 96 67 96 52 Kenya Guinea 22.6 124.0 107.0 147.0 126.0 94.0 2,804 30 1,100 2,669 1,344 737 1,175 Lesotho Guinea-Bissau 8.4 75.0 72.0 78.0 72.0 37.0 75 0 259 1 138 1 112 Liberia Kenya .. 117.0 115.0 127.0 131.0 169.0 293 0 262 97 217 10 196 Madagascar Lesotho 29.1 113.0 115.0 111.0 114.0 120.0 4,388 3 276 193 401 150 331 Malawi Liberia 30.5 136.0 141.0 153.0 129.0 120.0 3,993 31 259 768 266 103 177 Mali Madagascar .. 157.0 162.0 153.0 183.0 240.0 6,335 4 252 351 416 144 341 Mauritania Malawi 20.6 116.0 116.0 115.0 116.0 129.0 213 .. 438 24 470 18 424 Mauritius Mali 4.3 105.0 95.0 138.0 106.0 182.0 1 18 282 372 746 326 562 Mozambique Mauritania 31.5 123.0 130.0 89.0 102.0 94.0 1,785 30 610 330 616 181 526 Namibia Mauritius 9.4 102.0 140.0 90.0 101.0 134.0 112 3 371 235 367 190 229 Niger Mozambique .. 185.0 210.0 153.0 186.0 175.0 3,451 30 320 97 335 87 282 Nigeria Namibia .. 134.0 134.0 121.0 135.0 142.0 20,983 5 1,364 856 3,400 696 2,991 Rwanda Niger 34.2 135.0 132.0 158.0 134.0 191.0 651 8 56 235 123 19 105 São Tomé and Príncipe Nigeria .. 111.0 110.0 125.0 111.0 145.0 4 .. 14 5 28 5 23 Senegal Rwanda 16.6 133.0 130.0 144.0 134.0 175.0 1,869 37 1,533 252 1,793 133 1,633 Seychelles São Tomé and Principe 2 39.0 61.0 44.0 38.0 .. .. 0 19 4 90 2 77 Sierra Leone Senegal 51.4 197.0 204.0 144.0 201.0 406.0 868 0 214 26 211 23 189 Somalia Seychelles .. 104.0 96.0 105.0 104.0 54.0 215 0 452 58 518 53 385 South Africa Sierra Leone 3 120.0 111.0 130.0 122.0 122.0 14,577 1,279 2,302 5,461 4,896 3,741 3,204 Sudan Somalia 29.7 118.0 112.0 123.0 119.0 144.0 5,552 170 1,664 457 1,543 319 1,290 Swaziland South Africa 7.3 110.0 101.0 140.0 115.0 24.0 61 1 182 256 224 242 184 Tanzania Sudan 28.8 135.0 154.0 104.0 134.0 154.0 5,683 136 546 954 643 361 555 Togo Swaziland .. 113.0 109.0 137.0 132.0 120.0 1,004 19 307 301 326 247 279 Uganda Tanzania 24.7 112.0 109.0 120.0 112.0 131.0 2,811 73 439 878 629 198 537 Zambia Togo 21.6 144.0 170.0 106.0 135.0 208.0 2,198 238 48 348 284 190 208 Zimbabwe Uganda 17.9 70.0 55.0 107.0 82.0 30.0 919 1 652 534 627 111 475 NORTH Zambia AFRICA 13.1 42,172 400 32,879 5,382 26,427 4,668 23,107 Algeria Zimbabwe 11.7 163.0 196.0 121.0 163.0 279.0 5,253 1 9,093 76 7,785 61 7,015 Egypt, Arab Rep. NORTH AFRICA 13.7 137.0 136.0 134.0 139.0 125.0 23,697 258 12,324 1,823 8,661 1,499 7,754 Libya Algeria .. 109.0 102.0 116.0 109.0 93.0 207 1 2,276 8 2,266 1 2,091 Morocco Egypt, Arab Rep. 16.4 139.0 142.0 128.0 140.0 163.0 10,430 95 6,127 1,919 5,157 1,718 4,140 Tunisia Libya 7.8 115.0 119.0 110.0 115.0 84.0 2,585 45 3,059 1,555 2,557 1,389 2,107 Morocco Tunisia ALL AFRICA Note: 90 Part III. Development outcomes Agriculture, rural development, and environment Fertilizer Share of land area (%) Agricultural consumption Agricultural Agricultural irrigated land (100 grams machinery employment Agriculture value Cereal yield Cereal (% of per hectare of (tractors per 100 sq (% of total added per worker (kilograms per Permanent cropland cropland agricultural land) arable land) km of arable land) employment) (2000 $) hectare) 2009 2009 2000–08b 2008 2000–08b 2000–08b 2009 2009 1.0 3.8 11.6 318.3 1,296.9 0.2 1.4 .. 8.3 .. .. 313.1 587.7 2.7 9.6 .. 0.0 .. .. .. 1,423.5 0.0 0.2 0.0 .. 134.8 .. 597.1 569.4 0.2 13.2 .. 3.9 .. .. .. 1,002.0 15.2 8.8 .. 2.2 .. .. .. 1,319.4 2.5 2.8 .. 8.6 .. .. .. 1,524.0 0.7 8.2 .. .. 11.2 11.2 2,224.8 223.6 0.1 0.4 .. .. .. .. .. 948.3 0.0 2.0 .. .. .. .. .. 879.9 29.6 12.9 .. .. .. .. 452.9 1,063.9 0.3 0.9 .. 0.9 .. .. 167.9 788.5 0.2 0.1 .. 1.1 .. .. .. 861.5 13.4 2.4 .. 18.9 32.1 32.1 925.6 1,899.7 .. 0.0 .. .. 46.2 46.2 .. 1,111.1 2.7 .. .. .. .. .. 1,004.8 .. 0.0 4.5 .. 0.0 8.3 8.3 66.1 500.0 0.9 9.2 0.5 7.7 .. .. 214.7 1,676.8 0.6 0.1 .. 14.1 .. .. 1,869.3 2,388.8 0.5 29.6 .. 2.6 .. .. 275.3 1,049.3 12.5 6.9 .. 6.4 4.5 4.5 .. 1,659.8 2.8 8.1 .. 1.5 39.3 39.3 225.4 1,339.2 8.9 5.3 .. .. .. .. .. 1,444.5 0.9 4.1 0.1 33.3 25.2 25.2 334.2 1,203.8 0.1 5.9 .. .. .. .. 207.0 421.0 2.3 1.9 .. .. .. .. .. 1,609.7 1.0 2.9 2.2 4.3 1.9 1.9 192.2 2,581.7 1.3 19.6 .. 1.7 .. .. 161.7 2,162.8 0.1 3.3 .. 9.0 2.7 2.7 .. 1,588.2 0.0 0.2 .. .. 9.8 9.8 407.5 875.8 2.0 0.0 21.4 210.1 .. .. 5,555.9 8,306.9 0.3 2.6 .. 0.0 .. .. 219.7 876.6 0.0 0.4 .. 0.3 .. .. 1,638.1 364.7 0.0 7.2 .. 0.4 .. .. .. 379.8 3.3 15.1 .. 13.3 6.6 6.6 .. 1,528.0 11.3 14.4 .. 8.3 0.5 0.5 .. 1,828.7 46.9 1.1 .. .. .. .. .. 4,056.2 0.3 8.6 0.7 2.4 2.1 2.1 245.4 1,134.5 6.5 .. .. 29.0 .. .. 724.9 .. 1.9 8.6 .. .. .. .. .. 1,402.3 0.0 0.9 .. .. 12.0 12.0 .. 371.4 0.8 2.7 .. 49.7 43.0 43.0 3,640.8 4,414.2 0.1 4.0 1.3 3.6 12.4 12.4 922.3 587.2 0.8 3.1 .. .. 87.1 87.1 1,176.0 1,147.5 1.5 5.8 .. 5.9 23.3 23.3 283.0 1,109.5 3.1 13.2 .. 4.9 0.5 0.5 .. 1,398.4 11.4 9.3 .. 3.4 .. .. 202.9 1,539.4 0.0 1.4 .. 50.1 .. .. 215.7 2,066.9 0.3 5.3 .. 27.9 .. .. 141.4 449.6 0.9 2.4 .. 2,929.4 3,111.3 0.4 1.3 2.1 6.8 139.6 139.6 2,183.7 1,653.9 0.8 3.1 .. 723.6 372.1 372.1 3,024.2 7,571.4 0.2 0.2 .. 27.3 218.9 218.9 .. 568.8 2.1 12.2 4.4 53.8 .. .. 3,306.3 1,910.7 14.2 9.2 4.0 32.1 142.6 142.6 3,602.4 1,812.9 a. Provisional. b. Data are for the most recent year available during the period speci�ed. Agriculture, rural development, and environment Part III. Development outcomes 91 Participating in growth Table 8.3 Producer food prices Rice, paddy Maize (current $ per metric ton) (current $ per metric ton) 1991 1995 2000 2005 2008 1991 1995 2000 2005 2008 SUB–SAHARAN AFRICA Angola .. .. .. .. .. .. .. .. .. .. Benin .. .. .. .. .. .. .. .. .. .. Botswana .. .. .. .. .. .. .. .. .. .. Burkina Faso 351.5 245.6 119.4 392.2 559.8 212.7 148.5 91.3 192.4 253.7 Burundi 220.4 272.3 277.5 609.2 814.9 270.0 208.2 253.0 314.3 325.2 Cameroon 177.2 136.2 144.6 269.1 337.2 283.6 152.3 163.7 113.2 140.6 Cape Verde .. .. .. .. .. 313.9 432.0 247.9 334.6 461.0 Central African Republic .. .. .. .. .. .. .. .. .. .. Chad .. .. .. .. .. .. .. .. .. .. Comoros .. .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. .. .. .. .. .. .. .. .. .. .. Congo, Rep. 265.9 150.3 178.4 220.1 362.9 212.7 200.3 262.6 359.6 587.8 Côte d’Ivoire 212.7 220.4 154.5 222.2 506.4 159.5 162.9 119.4 233.0 331.7 Djibouti .. .. .. .. .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. .. .. .. .. Eritrea .. .. .. .. .. .. 295.1 354.3 347.0 500.2 Ethiopia .. 260.8 201.6 127.7 734.4 294.7 154.3 119.3 144.7 350.0 Gabon .. .. .. .. .. .. .. .. .. .. Gambia, The 170.4 206.2 136.9 175.0 258.3 211.3 419.0 134.5 311.2 293.3 Ghana 416.9 393.3 306.6 577.8 826.0 188.9 215.1 171.7 366.5 445.6 Guinea 220.2 245.1 405.5 138.2 128.8 191.0 245.1 166.7 152.0 127.0 Guinea-Bissau .. .. 351.1 474.8 893.2 .. 76.2 842.7 1,168.0 1,382.3 Kenya 72.7 107.2 299.9 378.8 627.5 104.3 155.6 190.3 201.7 471.0 Lesotho .. .. .. .. .. .. .. .. .. .. Liberia .. .. .. .. .. .. .. .. .. .. Madagascar 119.9 170.0 190.6 125.9 314.9 337.8 178.6 143.8 84.5 226.5 Malawi 139.1 117.8 594.4 718.5 1,060.8 96.3 47.1 111.9 184.7 291.5 Mali 223.3 236.4 154.5 269.7 264.5 134.7 166.3 107.7 197.5 172.0 Mauritania .. .. .. .. .. .. .. .. .. .. Mauritius .. .. .. .. .. 303.5 287.6 171.4 185.9 221.1 Mozambique 181.1 135.8 90.6 163.3 .. 132.7 92.4 51.8 154.5 .. Namibia .. .. .. .. .. 166.6 193.3 145.1 276.6 262.6 Niger 260.4 214.4 154.5 201.0 260.2 163.0 138.2 118.0 173.0 226.4 Nigeria 761.3 652.2 279.4 545.1 519.4 334.8 661.3 198.4 477.5 486.9 Rwanda 199.7 873.4 582.1 480.2 659.2 259.0 194.5 211.0 104.2 138.5 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. Senegal .. .. .. .. .. .. .. .. .. .. Seychelles .. .. .. .. .. .. .. .. .. .. Sierra Leone .. .. .. .. .. .. .. .. .. .. Somalia .. .. .. .. .. .. .. .. .. .. South Africa .. .. .. .. .. 129.3 159.1 78.5 99.3 200.9 Sudan 962.2 205.2 388.9 497.3 125,651.2 1,538.6 328.1 621.9 184.6 42,295.8 Swaziland .. .. .. .. .. .. .. .. .. .. Tanzania .. .. .. .. .. .. .. .. .. .. Togo 283.6 232.4 165.7 258.3 375.2 205.6 190.3 120.8 294.4 495.8 Uganda .. .. .. .. .. .. .. .. .. .. Zambia .. .. .. .. .. .. .. .. .. .. Zimbabwe 215.4 288.5 255.1 346.4 .. 74.6 121.2 123.8 100.5 .. NORTH AFRICA Algeria 270.7 544.5 344.8 421.4 581.2 173.2 335.7 212.6 259.8 358.3 Egypt, Arab Rep. 127.5 193.4 167.9 185.0 269.7 140.5 151.5 174.8 179.3 260.3 Libya .. .. .. .. .. .. .. .. .. .. Morocco 436.5 445.0 276.4 325.2 405.1 242.3 292.7 223.0 225.8 398.7 Tunisia .. .. .. .. .. .. .. .. .. .. 92 Part III. Development outcomes Agriculture, rural development, and environment Sorghum Millet (current $ per metric ton) (current $ per metric ton) 1991 1995 2000 2005 2008 1991 1995 2000 2005 2008 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 212.7 134.4 84.3 178.7 225.3 212.7 152.9 84.3 178.7 217.0 330.6 328.3 374.7 324.2 430.5 .. .. .. .. .. 177.2 160.3 313.8 217.0 269.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 342.4 252.2 2,103.1 336.6 325.4 460.8 391.3 245.7 415.4 376.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 212.4 284.7 391.7 571.0 .. 337.2 434.3 645.3 939.4 362.3 193.2 142.1 188.7 446.4 294.7 216.0 144.8 170.0 461.5 .. .. .. .. .. .. .. .. .. .. 213.6 193.3 129.0 334.3 316.4 218.8 388.9 128.2 310.1 266.6 217.5 212.9 153.1 424.4 514.9 308.6 245.0 205.9 495.3 619.6 187.0 263.8 179.4 120.7 139.4 .. .. .. .. .. .. .. 351.1 854.6 1,287.9 .. .. .. .. .. 207.7 194.1 204.1 331.8 319.8 256.6 361.3 311.1 485.5 487.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 176.6 72.0 500.6 514.4 661.0 133.2 65.1 518.6 642.7 919.6 145.3 198.3 87.4 233.6 197.2 156.0 194.3 85.1 254.5 192.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 63.9 47.9 51.8 141.3 .. .. .. .. .. .. 147.8 182.0 157.4 263.2 244.4 147.8 209.5 157.4 263.2 244.4 140.2 96.2 77.3 117.4 154.2 150.1 96.2 108.2 135.1 175.8 368.1 847.7 190.3 509.0 370.2 339.6 413.3 184.5 493.7 402.1 234.0 450.1 211.0 138.8 186.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 106.8 132.9 74.9 70.9 214.7 .. .. .. .. .. 943.0 92.7 165.6 335.2 3,297.7 1,206.4 278.6 655.1 433.6 5,426.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 237.5 246.4 140.5 364.6 629.7 265.9 238.4 122.2 305.8 407.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 69.0 75.0 90.1 100.6 .. 71.8 60.0 90.1 100.6 .. 152.3 207.7 131.5 160.8 221.7 .. .. .. .. .. 141.2 166.9 184.0 186.7 264.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 218.2 402.8 218.3 292.5 384.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Agriculture, rural development, and environment Part III. Development outcomes 93 Participating in growth Table 8.4 Environment Renewable internal Water pollution fresh water resources Annual Water Emissions of Energy Total fresh water productivity (2000 organic water Forest area (billions Per capita withdrawals $ per cubic meter pollutants Energy production Energy use Combustible (% of land of cubic (cubic (billions of of fresh water (kilograms (kilotons of oil (kilotons of oil renewables and waste area) meters) meters) cubic meters) withdrawal) per day) equivalent) equivalent) (% of total energy use) 1990 2010 2007 2007 2000–05 a 2000–07 a 2000–07 a 1990 2008 1990 2008 1990 2008 SUB–SAHARAN AFRICA 31.3 28.0 3,884 4,850 103.6 475,369 809,956 310,313 497,224 56.6 57.7 Angola 48.9 46.9 148 8,431 0.6 14.3 .. 28,652 105,837 5,883 10,972 73.5 63.5 Benin 52.1 41.2 10 1,227 0.1 18.2 .. 1,774 1,833 1,661 3,005 94.2 61.0 Botswana 24.2 20.0 2 1,268 0.2 29.0 3,246 910 1,002 1,261 2,117 33.4 22.3 Burkina Faso 25.0 20.6 13 849 1.0 2.7 .. .. .. .. .. .. .. Burundi 11.3 6.7 10 1,284 0.3 2.5 .. .. .. .. .. .. .. Cameroon 51.4 42.1 273 14,630 1.0 10.5 .. 10,976 10,119 4,980 7,102 76.7 71.0 Cape Verde 14.3 21.1 0 610 0.0 27.2 .. .. .. .. .. .. .. Central African Republic 37.2 36.3 141 33,119 0.1 14.4 .. .. .. .. .. .. .. Chad 10.4 9.2 15 1,412 0.4 3.8 .. .. .. .. .. .. .. Comoros 6.4 1.6 1 1,910 .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. 70.7 68.0 900 14,395 0.6 6.9 .. 12,019 22,664 11,798 22,250 84.7 93.4 Congo, Rep. 66.5 65.6 222 62,516 0.0 76.0 .. 8,746 13,245 797 1,368 59.5 51.3 Côte d’Ivoire 32.1 32.7 77 3,819 1.4 7.4 .. 3,382 11,415 4,323 10,278 73.5 74.0 Djibouti 0.2 0.3 0 360 0.0 29.2 .. .. .. .. .. .. .. Equatorial Guinea 66.3 58.0 26 40,485 0.0 72.1 .. .. .. .. .. .. .. Eritrea .. 15.2 3 586 0.6 1.2 2,540 .. 546 .. 681 .. 80.0 Ethiopia 15.2 12.3 122 1,551 5.6 1.6 32,159 14,052 29,581 14,866 31,704 93.9 92.4 Gabon 85.4 85.4 164 115,340 0.1 39.0 .. 14,630 13,519 1,181 2,073 62.9 52.5 Gambia, The 44.2 48.0 3 1,857 0.1 5.9 .. .. .. .. .. .. .. Ghana 32.7 21.7 30 1,325 1.0 5.1 16,048 4,392 6,858 5,291 9,459 73.7 66.8 Guinea 29.6 26.6 226 23,505 1.6 1.9 .. .. .. .. .. .. .. Guinea-Bissau 78.8 71.9 16 10,383 0.2 1.2 .. .. .. .. .. .. .. Kenya 6.5 6.1 21 548 2.7 5.0 .. 9,013 15,108 10,940 18,021 77.9 76.9 Lesotho 1.3 1.4 5 2,574 0.1 14.9 5,252 .. .. .. .. .. .. Liberia 51.2 44.9 200 55,138 0.2 3.1 .. .. .. .. .. .. .. Madagascar 23.5 21.6 337 18,114 14.7 0.3 92,770 .. .. .. .. .. .. Malawi 41.4 34.4 16 1,118 1.0 1.8 32,672 .. .. .. .. .. .. Mali 11.5 10.2 60 4,835 6.5 0.4 .. .. .. .. .. .. .. Mauritania 0.4 0.2 0 127 1.6 0.7 .. .. .. .. .. .. .. Mauritius 19.1 17.2 3 2,182 0.7 6.9 15,446 .. .. .. .. .. .. Mozambique 55.2 49.6 100 4,586 0.7 5.7 .. 5,608 11,460 5,922 9,314 93.9 81.9 Namibia 10.6 8.9 6 2,949 0.3 13.0 .. .. 317 .. 1,752 .. 11.2 Niger 1.5 1.0 4 248 2.4 0.8 .. .. .. .. .. .. .. Nigeria 18.9 9.9 221 1,496 10.3 4.5 .. 150,452 226,793 70,582 111,156 80.2 81.2 Rwanda 12.9 17.6 10 1,005 0.2 11.6 .. .. .. .. .. .. .. São Tomé and Príncipe 28.1 28.1 2 13,829 .. .. .. .. .. .. .. .. .. Senegal 48.6 44.0 26 2,169 2.2 2.2 6,621 964 1,230 1,686 2,859 56.8 41.7 Seychelles 88.5 89.1 .. .. 0.0 47.1 .. .. .. .. .. .. .. Sierra Leone 43.5 38.1 160 29,518 0.5 1.3 .. .. .. .. .. .. .. Somalia 13.2 10.8 6 687 3.3 .. .. .. .. .. .. .. .. South Africa 7.6 4.7 45 928 12.5 10.6 229,582 114,535 162,951 90,860 134,489 11.5 10.4 Sudan 32.1 29.4 30 742 37.1 0.3 38,567 8,775 34,874 10,629 15,372 81.8 68.0 Swaziland 27.4 32.7 3 2,293 1.0 1.4 .. .. .. .. .. .. .. Tanzania 46.8 37.7 84 2,035 5.2 2.2 30,322 9,064 17,470 9,733 18,957 91.7 88.2 Togo 12.6 5.3 12 1,825 0.2 8.2 .. 1,054 2,138 1,263 2,563 82.8 83.1 Uganda 24.1 15.2 39 1,273 0.3 21.5 2,105 .. .. .. .. .. .. Zambia 71.0 66.5 80 6,513 1.7 1.9 .. 4,918 6,790 5,399 7,355 74.3 81.0 Zimbabwe 57.3 40.4 12 985 4.2 1.5 .. 8,550 8,533 9,297 9,506 50.9 65.3 NORTH AFRICA 1.3 1.4 47 290 234,657 361,445 77,234 150,155 2.8 2.3 Algeria 0.7 0.6 11 332 6.1 9.6 .. 100,114 162,044 22,192 37,069 0.1 0.1 Egypt, Arab Rep. 0.0 0.1 2 23 68.2 1.5 .. 54,869 87,487 31,825 70,710 3.3 2.1 Libya 0.1 0.1 1 97 4.3 7.9 .. 73,173 103,743 11,330 18,221 1.1 0.9 Morocco 11.3 11.5 29 929 12.6 2.9 73,989 773 637 6,941 14,977 4.6 3.2 Tunisia 4.1 6.5 4 410 2.8 7.2 .. 5,728 7,534 4,946 9,178 12.9 13.6 a. Data are for the most recent year available during the period speci�ed. b. Hydrofluorocarbons, perfluorocarbons, and sulphur hexafluoride. 94 Part III. Development outcomes Agriculture, rural development, and environment Greenhouse gas emissions Methane Nitrous oxide Other greenhouse ODA gross gasesb disbursements Total Total (thousands of ODA gross for general Carbon dioxide (kilotons of (metric tons of metric tons of disbursements environment (thousands of carbon dioxide Agricultural Industrial carbon dioxide Agricultural Industrial carbon dioxide for forestry protection metric tons) equivalent) (% of total) (% of total) equivalent) (% of total) (% of total) equivalent) ($ millions) ($ millions) 1990 2007 1990 2005 1990 2005 1990 2005 1990 2005 1990 2005 1990 2005 1990 2005 2009 2009 464,110 682,631 .. .. 44.0 44.0 32.1 30.2 .. .. 64.5 66.1 0.3 0.8 .. .. 120.8 588.2 4,426 24,743 49,530 45,409 26.4 27.9 21.6 11.6 41,667 38,881 39.2 38.4 0.0 0.0 0 20 0.9 2.5 715 3,873 4,847 4,080 36.7 47.8 16.1 8.9 3,695 2,902 50.5 61.5 0.0 0.0 0 0 0.0 13.2 2,169 4,994 5,812 4,501 90.5 84.1 7.7 17.9 5,511 3,081 90.9 92.0 .. 0.0 0 0 0.1 3.0 586 1,693 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.8 10.5 304 180 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 1.9 1,737 6,163 13,503 18,518 55.2 42.4 20.2 17.9 10,530 9,127 68.1 75.9 0.0 0.0 932 419 4.3 12.3 88 308 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 7.9 198 253 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.9 18.6 147 385 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 6.0 77 121 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 0.7 4,067 2,433 96,593 56,445 25.6 23.1 47.9 49.6 87,098 54,643 37.9 31.3 0.0 0.0 0 0 4.0 15.5 1,187 1,587 6,231 5,584 37.3 31.9 10.4 7.7 4,307 3,566 48.6 51.8 0.0 0.0 0 5 1.2 3.8 5,793 6,379 11,243 10,997 18.3 17.4 18.9 11.2 7,485 7,364 22.7 29.3 0.0 0.0 0 0 .. 1.3 399 487 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.2 0.5 121 4,793 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 0.5 .. 579 1,884 2,467 78.7 73.2 11.0 7.5 1,028 1,189 93.0 90.9 0.0 0.0 0 0 0.5 1.0 3,016 6,504 39,325 52,243 81.6 72.5 9.3 10.0 25,545 30,510 91.9 88.8 0.0 0.0 0 10 7.8 13.5 6,082 2,034 8,103 8,218 0.9 1.1 46.5 79.9 305 482 25.6 23.3 0.0 0.0 0 9 0.2 5.4 191 396 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.4 3,928 9,801 7,238 8,990 48.9 39.5 13.7 10.7 5,187 4,899 75.5 70.5 0.0 0.0 596 15 16.3 18.6 1,055 1,389 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.7 2.1 253 286 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.2 5,818 11,227 17,952 22,130 74.3 65.5 15.7 18.0 9,222 10,542 91.9 88.8 0.0 0.0 0 0 5.7 35.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 1.2 484 674 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.1 3.0 986 2,250 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.7 18.8 612 1,055 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.2 5.9 421 579 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 3.1 14.1 2,664 1,949 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 3.5 11.8 1,462 3,884 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 5.2 1,000 2,598 10,863 12,843 66.3 44.2 17.5 16.9 10,881 9,501 82.0 71.4 0.0 0.0 0 282 1.6 17.9 7 3,034 3,435 5,057 95.8 94.9 3.7 4.7 2,580 3,797 93.2 94.3 0.0 0.0 0 0 1.3 11.6 953 909 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.2 7.4 45,338 95,194 117,467 130,317 18.5 19.8 47.3 45.5 19,153 21,565 82.1 77.3 0.0 0.0 242 669 0.5 9.9 682 715 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.0 9.2 66 128 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.2 3,180 5,474 5,277 7,129 68.8 68.3 4.5 4.7 2,976 4,083 88.1 88.5 0.0 0.0 0 0 6.9 54.2 114 623 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 388 1,312 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.9 18 601 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 333,241 433,173 51,179 63,785 37.3 31.4 52.4 54.3 21,300 24,048 63.3 59.8 3.6 7.3 1,491 2,552 0.0 26.6 5,555 11,512 43,370 67,441 87.1 85.2 21.4 21.5 36,669 49,472 92.0 92.6 0.0 0.0 0 0 2.5 15.1 425 1,063 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 1.1 2,371 6,038 25,817 32,024 73.9 63.2 21.3 20.3 21,468 21,647 82.8 78.8 0.0 0.0 0 0 11.0 30.9 773 1,315 2,752 2,889 52.9 39.8 18.4 14.8 2,209 1,738 74.3 67.5 0.0 0.0 0 0 .. 1.2 817 3,202 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.9 16.9 2,444 2,689 26,944 19,294 66.1 59.3 8.1 5.7 35,669 25,068 75.1 71.7 0.0 3.7 0 0 0.5 11.6 15,510 9,629 10,112 9,539 79.1 73.3 22.2 24.8 7,284 6,114 84.2 85.2 5.9 0.0 0 0 0.0 1.0 231,777 452,017 104,128 134,629 21.6 20.6 51.5 48.2 24,023 33,358 72.0 75.3 5.6 7.9 2,668 3,950 5.7 109.9 78,831 140,005 40,726 54,219 9.1 8.2 61.2 66.3 3,843 4,898 64.3 58.6 4.4 7.2 326 489 0.2 4.6 75,881 184,508 27,839 46,996 38.0 31.7 33.4 31.2 11,818 18,996 71.5 80.0 8.2 11.5 2,059 3,181 0.0 35.6 40,286 57,287 22,473 14,682 4.9 5.7 79.1 77.6 1,176 1,285 67.2 51.9 0.0 0.0 282 280 .. 0.1 23,523 46,368 9,132 10,573 58.8 51.7 6.2 2.6 5,180 5,814 85.1 82.6 0.0 0.0 0 0 0.7 40.9 13,256 23,849 3,958 8,160 44.9 25.5 26.2 32.1 2,006 2,366 59.0 66.4 10.6 4.1 0 0 4.4 22.8 Agriculture, rural development, and environment Part III. Development outcomes 95 Participating in growth Table 8.5 Fossil fuel emissions Carbon dioxide emissions from fossil fuel Carbon dioxide emissions (thousands of metric tons) Total Per capita Solid fuel (thousands of metric tons) (metric tons) Total consumption 1990 2005 2007 1990 2005 2007 1990 2005 2007 1990 2005 2007 SUB–SAHARAN AFRICA 464,110 656,877 682,631 0.9 0.9 0.9 129,769 183,320 189,853 110,850 143,104 149,751 Angola 4,426 19,756 24,743 0.4 1.2 1.4 1,208 5,392 6,753 0 0 0 Benin 715 2,565 3,873 0.1 0.3 0.5 195 700 1,057 0 0 0 Botswana 2,169 4,521 4,994 1.6 2.5 2.6 592 1,234 1,363 592 702 796 Burkina Faso 586 1,173 1,693 0.1 0.1 0.1 160 320 462 0 0 0 Burundi 304 165 180 0.1 0.0 0.0 83 45 49 4 2 2 Cameroon 1,737 3,693 6,163 0.1 0.2 0.3 .. .. .. .. .. .. Cape Verde 88 297 308 0.2 0.6 0.6 24 81 84 0 0 0 Central African Republic 198 235 253 0.1 0.1 0.1 54 64 69 0 0 0 Chad 147 399 385 0.0 0.0 0.0 40 109 105 0 0 0 Comoros 77 110 121 0.2 0.2 0.2 21 30 33 0 0 0 Congo, Dem. Rep. 4,067 2,275 2,433 0.1 0.0 0.0 1,110 621 664 209 273 303 Congo, Rep. 1,187 1,605 1,587 0.5 0.5 0.4 324 438 433 0 0 0 Côte d’Ivoire 5,793 8,160 6,379 0.5 0.4 0.3 1,581 2,227 1,741 0 0 0 Djibouti 399 473 487 0.7 0.6 0.6 109 129 133 0 0 0 Equatorial Guinea 121 4,708 4,793 0.3 7.7 7.5 33 1,285 1,308 0 0 0 Eritrea .. 733 579 .. 0.2 0.1 .. 200 158 .. 0 0 Ethiopia 3,016 5,485 6,504 0.1 0.1 0.1 823 1,497 1,775 0 0 0 Gabon 6,082 1,861 2,034 6.6 1.4 1.4 1,660 508 555 0 0 0 Gambia, The 191 322 396 0.2 0.2 0.2 52 88 108 0 0 0 Ghana 3,928 7,467 9,801 0.3 0.3 0.4 1,072 2,038 2,675 2 0 0 Guinea 1,055 1,359 1,389 0.2 0.1 0.1 288 371 379 0 0 0 Guinea-Bissau 253 264 286 0.2 0.2 0.2 69 72 78 0 0 0 Kenya 5,818 10,944 11,227 0.2 0.3 0.3 1,588 2,987 3,064 110 78 80 Lesotho .. .. .. .. .. .. .. .. .. .. .. .. Liberia 484 737 674 0.2 0.2 0.2 132 201 184 0 0 0 Madagascar 986 2,173 2,250 0.1 0.1 0.1 269 593 614 9 7 7 Malawi 612 1,037 1,055 0.1 0.1 0.1 167 283 288 13 43 44 Mali 421 568 579 0.0 0.0 0.0 115 155 158 0 0 0 Mauritania 2,664 1,656 1,949 1.3 0.6 0.6 727 452 532 4 0 0 Mauritius 1,462 3,408 3,884 1.4 2.7 3.1 399 930 1,060 54 264 415 Mozambique 1,000 1,854 2,598 0.1 0.1 0.1 273 506 709 42 0 7 Namibia 7 2,656 3,034 0.0 1.3 1.5 2 725 828 0 14 56 Niger 953 824 909 0.1 0.1 0.1 260 225 248 98 103 105 Nigeria 45,338 110,371 95,194 0.5 0.8 0.6 12,374 30,123 25,981 35 8 8 Rwanda 682 689 715 0.1 0.1 0.1 186 188 195 0 0 0 São Tomé and Príncipe 66 128 128 0.6 0.8 0.8 18 35 35 0 0 0 Senegal 3,180 5,529 5,474 0.4 0.5 0.5 868 1,509 1,494 0 114 218 Seychelles 114 696 623 1.6 8.4 7.3 31 190 170 0 0 0 Sierra Leone 388 1,260 1,312 0.1 0.2 0.2 106 344 358 0 0 0 Somalia 18 579 601 0.0 0.1 0.1 5 158 164 0 0 0 South Africa 333,241 407,895 433,173 9.5 8.6 9.0 90,950 111,325 118,224 72,352 95,970 100,415 Sudan 5,555 10,992 11,512 0.2 0.3 0.3 1,516 3,000 3,142 0 0 0 Swaziland 425 1,019 1,063 0.5 0.9 0.9 116 278 290 116 104 109 Tanzania 2,371 5,082 6,038 0.1 0.1 0.1 647 1,387 1,648 3 54 62 Togo 773 1,337 1,315 0.2 0.2 0.2 211 365 359 0 0 0 Uganda 817 2,338 3,202 0.0 0.1 0.1 223 638 874 0 0 0 Zambia 2,444 2,363 2,689 0.3 0.2 0.2 667 645 734 227 98 111 Zimbabwe 15,510 10,780 9,629 1.5 0.9 0.8 4,233 2,942 2,628 3,666 2,318 2,073 NORTH AFRICA 231,777 424,566 452,017 1.9 2.7 2.8 63,258 115,875 123,367 3,567 6,292 6,878 Algeria 78,831 138,741 140,005 3.1 4.2 4.1 21,515 37,866 38,211 825 666 859 Egypt, Arab Rep. 75,881 163,220 184,508 1.3 2.1 2.3 20,710 44,547 50,357 917 924 966 Libya 40,286 55,997 57,287 9.2 9.5 9.3 10,995 15,283 15,635 4 0 0 Morocco 23,523 43,825 46,368 0.9 1.4 1.5 6,420 11,961 12,655 1,278 3,844 4,115 Tunisia 13,256 22,783 23,849 1.6 2.3 2.3 3,618 6,218 6,509 72 0 0 Note: 0 refers to a negligible value that rounds to 0. 96 Part III. Development outcomes Agriculture, rural development, and environment Carbon dioxide emissions from fossil fuel (thousands of metric tons) Liquid fuel consumption Gas fuel consumption Gas flaring Cement production 1990 2005 2007 1990 2005 2007 1990 2005 2007 1990 2005 2007 42,649 48,703 49,016 .. .. .. .. .. .. 2,906 4,815 6,229 489 1,460 2,296 276 341 435 409 3,412 3,832 35 179 190 154 666 846 0 0 0 0 0 0 41 34 211 0 532 568 0 0 0 0 0 0 0 0 0 160 316 458 0 0 0 0 0 0 0 4 4 79 43 47 0 0 0 0 0 0 0 0 0 .. .. .. .. .. .. .. .. .. .. .. .. 24 81 84 0 0 0 0 0 0 0 0 0 54 64 69 0 0 0 0 0 0 0 0 0 40 109 105 0 0 0 0 0 0 0 0 0 21 30 33 0 0 0 0 0 0 0 0 0 838 348 362 0 0 0 0 0 0 63 0 0 265 358 347 1 12 11 46 0 0 12 69 75 1,513 1,228 1,025 0 910 629 0 0 0 68 88 88 109 129 133 0 0 0 0 0 0 0 0 0 33 142 163 0 605 876 0 538 269 0 0 0 .. 194 152 .. 0 0 .. 0 0 .. 6 6 777 1,284 1,544 0 0 0 0 0 0 46 213 231 583 408 443 138 65 82 924 0 0 16 35 31 52 87 106 0 1 1 0 0 0 0 0 0 978 1,780 2,417 0 0 0 0 0 0 92 258 258 288 322 330 0 0 0 0 0 0 0 49 49 69 72 78 0 0 0 0 0 0 0 0 0 1,273 2,620 2,669 0 0 0 0 0 0 205 289 315 .. .. .. .. .. .. .. .. .. .. .. .. 125 181 163 0 0 0 0 0 0 7 20 21 252 566 570 0 0 0 0 0 0 8 20 37 141 217 219 0 0 0 0 0 0 13 23 25 112 155 158 0 0 0 0 0 0 3 0 0 709 411 476 0 0 0 0 0 0 14 41 56 345 666 645 0 0 0 0 0 0 0 0 0 220 392 505 0 38 82 0 0 0 11 76 116 2 711 772 0 0 0 0 0 0 0 0 0 159 115 136 0 0 0 0 0 0 3 7 7 9,823 12,143 7,789 2,041 5,572 5,594 0 12,075 11,707 476 326 884 177 173 181 0 0 0 0 0 0 8 14 14 18 35 35 0 0 0 0 0 0 0 0 0 801 1,031 841 3 7 5 0 0 0 64 357 429 31 190 170 0 0 0 0 0 0 0 0 0 106 321 326 0 0 0 0 0 0 0 23 32 0 158 164 0 0 0 0 0 0 5 0 0 16,596 11,526 13,599 940 2,269 2,353 0 0 0 1,062 1,559 1,857 1,493 2,955 3,115 0 0 0 0 0 0 23 45 27 0 173 181 0 0 0 0 0 0 0 0 0 571 962 1,102 0 185 278 0 0 0 73 186 206 157 256 250 0 0 0 0 0 0 54 109 109 219 552 786 0 0 0 0 0 0 4 86 88 381 488 535 0 0 0 0 0 0 59 59 88 471 542 502 0 0 0 0 0 0 95 82 54 34,171 58,630 63,212 17,482 39,841 39,810 .. .. .. 4,167 8,848 10,342 6,835 17,270 18,794 10,619 16,706 13,942 2,373 1,688 2,454 862 1,536 2,162 14,323 21,152 23,958 3,552 18,057 20,211 0 0 0 1,918 4,414 5,222 6,058 10,425 10,301 2,599 3,010 3,304 1,969 1,357 1,527 367 492 503 4,541 6,385 6,705 30 237 339 0 0 0 571 1,496 1,496 2,414 3,398 3,454 682 1,831 2,014 1 79 82 449 910 959 Agriculture, rural development, and environment Part III. Development outcomes 97 Participating in growth Table 9.1 Labor force participation Labor force ages 15 and older Participation rate, ages 15 and older Total Male Female Total Male Female (% of total (% of male (% of female (thousands) (% of total labor force) (% of total labor force) population) population) population) 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 SUB–SAHARAN AFRICA 263,550 341,616 57.0 56.4 43.0 43.6 69.9 70.7 81.1 80.8 59.1 60.9 Angola 6,237 8,278 53.3 53.1 46.7 46.9 82.5 81.3 90.2 88.4 75.2 74.5 Benin 2,670 3,699 55.1 53.8 44.9 46.2 72.5 72.7 81.4 77.9 63.9 67.4 Botswana 799 996 52.9 52.6 47.1 47.4 74.9 76.6 80.8 80.9 69.2 72.3 Burkina Faso 5,217 7,140 52.3 52.9 47.7 47.1 84.0 84.4 90.9 90.8 77.5 78.2 Burundi 3,138 4,569 47.0 47.4 53.0 52.6 90.2 89.3 90.0 87.5 90.5 91.0 Cameroon 5,995 7,727 60.9 59.9 39.1 40.1 66.2 67.0 81.4 80.7 51.2 53.5 Cape Verde 156 214 60.3 56.8 39.7 43.2 62.6 66.4 83.2 81.3 45.5 53.5 Central African Republic 1,703 2,074 53.7 53.5 46.3 46.5 78.3 79.0 86.8 86.7 70.4 71.6 Chad 3,277 4,283 54.5 54.8 45.5 45.2 72.3 70.4 80.2 78.2 64.6 62.7 Comoros 251 325 54.3 53.5 45.7 46.5 77.0 79.6 83.8 85.4 70.1 73.7 Congo, Dem. Rep. 18,605 24,927 59.7 59.4 40.3 40.6 70.5 70.8 86.1 85.6 55.5 56.5 Congo, Rep. 1,256 1,594 57.0 56.4 43.0 43.6 71.9 72.7 83.0 82.6 61.1 62.9 Côte d’Ivoire 6,728 8,369 64.8 63.1 35.2 36.9 66.5 66.9 82.1 82.1 49.2 50.8 Djibouti 295 387 58.5 55.9 41.5 44.1 68.8 70.1 81.2 78.7 56.6 61.5 Equatorial Guinea 186 262 72.5 69.2 27.5 30.8 62.8 65.5 93.1 92.0 33.8 39.7 Eritrea 1,383 2,154 58.0 55.5 42.0 44.5 68.4 72.6 82.6 83.4 55.2 62.5 Ethiopia 28,989 39,952 54.8 52.1 45.2 47.9 81.7 85.4 90.9 90.3 72.8 80.7 Gabon 537 711 55.4 53.3 44.6 46.7 73.7 75.5 83.0 81.1 64.6 70.0 Gambia, The 581 766 53.8 53.8 46.2 46.2 78.2 77.8 86.0 85.2 70.8 70.6 Ghana 8,554 10,951 51.6 50.9 48.4 49.1 74.6 74.6 76.6 75.2 72.6 73.8 Guinea 3,954 4,850 53.3 53.1 46.7 46.9 84.4 84.2 89.8 89.2 78.9 79.2 Guinea-Bissau 541 661 57.3 57.6 42.7 42.4 71.4 71.5 83.4 83.8 59.8 59.6 Kenya 14,321 18,712 53.4 53.3 46.6 46.7 81.6 82.2 88.2 88.1 75.2 76.4 Lesotho 810 935 48.0 47.6 52.0 52.4 73.9 74.0 80.1 77.7 68.9 70.8 Liberia 1,123 1,611 52.8 52.4 47.2 47.6 71.3 71.1 76.9 75.8 66.0 66.6 Madagascar 7,273 9,681 51.3 50.8 48.7 49.2 86.8 86.4 89.6 88.7 84.0 84.2 Malawi 4,953 6,309 49.9 50.2 50.1 49.8 77.4 76.8 79.1 78.8 75.8 75.0 Mali 2,959 3,770 64.2 62.7 35.8 37.3 51.6 51.9 68.2 67.0 35.9 37.6 Mauritania 1,031 1,394 59.2 58.0 40.8 42.0 68.5 70.0 81.5 81.0 55.6 59.0 Mauritius 528 567 65.9 63.9 34.1 36.1 60.2 57.5 80.4 74.8 40.6 40.8 Mozambique 8,914 11,004 46.9 48.0 53.1 52.0 86.7 85.8 87.4 86.9 86.0 84.8 Namibia 601 783 54.9 53.5 45.1 46.5 55.8 57.1 63.7 62.6 48.5 51.8 Niger 3,551 4,799 68.9 68.4 31.1 31.6 62.6 62.7 88.1 87.5 38.1 38.9 Nigeria 39,249 49,972 65.4 64.9 34.6 35.1 56.0 56.2 74.1 73.4 38.3 39.2 Rwanda 3,710 4,963 46.9 47.2 53.1 52.8 86.0 86.0 86.4 85.1 85.6 86.7 São Tomé and Príncipe 46 58 63.0 61.9 37.0 38.1 57.3 59.8 73.8 76.0 41.5 44.5 Senegal 4,089 5,405 57.9 56.7 42.1 43.3 75.8 76.4 89.2 88.6 62.8 64.8 Seychelles .. .. .. .. .. .. .. .. .. .. .. .. Sierra Leone 1,664 2,141 47.9 48.6 52.1 51.4 67.8 66.4 67.8 67.5 67.8 65.4 Somalia 2,944 3,538 58.3 59.1 41.7 40.9 71.3 70.3 84.7 84.7 58.4 56.5 South Africa 15,280 18,849 56.5 56.3 43.5 43.7 52.3 55.0 60.9 63.4 44.3 47.0 Sudan 10,494 13,462 72.1 70.5 27.9 29.5 52.0 52.3 75.1 73.9 28.9 30.8 Swaziland 373 457 58.5 56.6 41.5 43.4 62.3 63.6 78.2 74.9 48.4 53.1 Tanzania 16,767 21,382 50.2 50.6 49.8 49.4 88.9 88.4 90.8 90.6 87.0 86.3 Togo 2,183 2,960 58.0 56.5 42.0 43.5 72.9 74.4 86.3 85.7 60.0 63.6 Uganda 10,500 14,134 53.0 53.5 47.0 46.5 85.0 84.5 91.1 90.6 79.0 78.3 Zambia 4,024 4,812 55.1 56.6 44.9 43.4 70.2 69.2 78.6 79.2 62.1 59.5 Zimbabwe 5,110 5,028 53.2 52.5 46.8 47.5 71.0 66.8 78.5 74.3 64.0 60.0 NORTH AFRICA 48,019 60,451 74.4 74.1 25.6 25.9 51.2 51.7 76.4 77.0 26.1 26.6 Algeria 11,101 14,840 71.7 68.4 28.3 31.6 55.2 58.5 79.0 79.6 31.3 37.2 Egypt, Arab Rep. 21,655 27,417 75.6 77.0 24.4 23.0 48.9 48.8 74.1 75.3 23.8 22.4 Libya 1,831 2,368 78.7 77.5 21.3 22.5 50.5 52.8 75.5 78.9 22.7 24.7 Morocco 10,215 11,982 73.6 74.2 26.4 25.8 53.4 52.3 80.7 80.1 27.5 26.2 Tunisia 3,217 3,844 75.3 73.3 24.7 26.7 48.1 48.0 72.3 70.6 23.8 25.6 98 Part III. Development outcomes Labor, migration, and population Participation rate, ages 15–64 Labor force ages 15–24 Participation rate, ages 15–24 Total Male Female Male Female Total Male Female (% of total (% of male (% of female Total (% of total (% of total (% of total (% of male (% of female population) population) population) (thousands) labor force) labor force) population) population) population) 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 2000 2009 71.1 72.1 82.0 81.8 60.5 62.5 75,323 94,875 56.4 55.7 45.2 45.8 56.8 56.2 63.3 61.6 50.2 50.7 83.9 82.6 91.1 89.1 76.9 76.4 2,182 2,851 53.7 53.1 46.3 46.9 78.3 75.3 84.7 80.6 72.1 70.0 73.4 73.5 81.6 78.2 65.2 68.8 773 991 52.8 49.9 47.2 50.1 60.3 56.7 62.9 55.5 57.6 57.9 76.7 78.8 81.7 82.1 71.8 75.5 231 258 52.7 51.8 47.3 48.2 59.5 59.3 62.4 61.2 56.6 57.5 85.3 85.7 91.5 91.4 79.5 80.2 1,872 2,416 53.6 53.5 46.4 46.5 78.6 77.7 83.3 82.0 73.8 73.2 91.0 89.9 90.5 88.1 91.4 91.6 1,080 1,480 48.2 47.5 51.8 52.5 82.2 77.4 80.0 73.8 84.3 80.9 67.3 68.3 82.7 82.0 52.2 54.5 1,653 2,020 62.3 61.7 37.7 38.3 50.9 49.6 63.2 60.9 38.5 38.2 65.5 69.2 85.1 82.8 48.7 57.0 55 63 60.9 59.8 39.1 40.2 58.5 54.8 72.8 65.9 44.8 43.8 78.7 79.3 87.1 87.1 70.6 71.7 469 576 54.6 54.5 45.4 45.5 64.1 64.2 70.6 70.7 57.7 57.9 72.5 70.6 79.9 77.8 65.2 63.5 929 1,204 49.8 49.0 50.2 51.0 57.0 54.4 56.9 53.2 57.1 55.6 77.9 80.6 84.1 85.9 71.6 75.3 .. .. .. .. .. .. .. .. .. .. .. .. 71.9 72.1 87.6 87.0 56.7 57.7 6,353 8,643 58.7 58.6 41.3 41.4 65.9 65.0 77.4 76.2 54.4 53.8 72.3 73.1 84.0 83.5 60.9 62.8 351 414 59.3 58.7 40.7 41.3 55.7 54.1 65.7 63.1 45.6 45.0 67.0 67.5 82.4 82.6 49.9 51.5 1,806 2,177 60.8 60.4 39.2 39.6 51.6 51.8 62.3 62.5 40.8 41.1 70.3 71.8 82.3 80.0 58.4 63.6 80 95 56.8 55.1 43.2 44.9 54.4 50.9 61.4 55.6 47.3 46.0 64.5 66.9 95.2 93.8 34.8 40.7 .. .. .. .. .. .. 68.5 .. 89.0 .. 48.2 .. 69.7 74.0 83.6 84.6 56.6 63.9 529 617 58.1 56.2 41.9 43.8 61.2 59.4 71.0 67.2 51.4 51.7 83.7 87.0 92.1 90.9 75.5 83.1 9,679 13,294 53.0 51.2 47.0 48.8 79.0 78.5 83.7 80.3 74.2 76.7 75.9 77.5 84.9 82.8 67.2 72.1 150 186 53.4 53.3 46.6 46.7 62.8 59.9 67.7 63.2 58.0 56.5 78.5 78.0 85.9 85.1 71.2 71.1 157 210 50.8 50.7 49.2 49.3 66.6 65.5 68.0 66.4 65.1 64.6 75.5 75.6 77.1 75.8 73.9 75.3 2,132 2,478 50.5 49.5 49.5 50.5 53.9 51.1 53.5 49.6 54.3 52.6 86.3 86.3 90.5 89.9 82.1 82.6 1,250 1,518 53.1 52.7 46.9 47.3 77.3 76.2 80.4 78.9 74.0 73.4 73.2 73.3 85.1 85.6 61.7 61.3 145 178 57.3 57.7 42.7 42.3 59.4 60.2 68.1 69.5 50.6 51.0 82.9 83.5 89.0 88.8 77.0 78.2 5,033 6,069 53.4 53.1 46.6 46.9 73.4 72.4 78.3 76.8 68.6 68.0 75.1 75.2 81.0 78.5 70.4 72.4 273 299 53.2 52.4 46.8 47.6 64.4 62.0 70.1 66.0 58.9 58.2 73.1 72.9 77.9 76.8 68.4 69.1 333 458 50.9 50.4 49.1 49.6 60.1 58.5 61.4 59.0 58.8 58.0 88.1 87.7 90.4 89.4 85.9 86.0 2,167 2,850 50.5 50.1 49.5 49.9 75.1 73.0 75.8 73.2 74.4 72.8 76.8 76.1 78.2 77.9 75.4 74.4 1,262 1,615 46.0 46.2 54.0 53.8 53.9 53.5 49.7 49.3 58.2 57.7 52.9 53.1 69.9 68.3 37.0 38.7 882 1,072 62.0 60.7 38.0 39.3 41.3 39.3 51.1 47.5 31.4 31.0 70.0 71.6 82.5 82.0 57.4 60.9 298 355 58.1 57.2 41.9 42.8 55.8 53.6 63.1 59.7 48.0 47.2 64.5 62.6 84.7 79.8 44.2 45.4 101 83 64.3 57.6 35.7 42.4 49.2 40.8 62.5 46.4 35.6 35.0 86.8 86.1 87.2 86.6 86.5 85.6 2,662 3,255 46.2 46.9 53.8 53.1 73.7 72.5 69.6 68.3 77.5 76.8 57.2 58.6 65.0 63.9 49.9 53.5 115 136 54.2 52.1 45.8 47.9 30.6 28.9 33.2 30.1 28.0 27.7 63.0 63.3 88.6 88.0 38.6 39.4 1,071 1,511 65.8 66.3 34.2 33.7 53.7 55.1 76.3 76.1 34.2 35.7 56.9 57.3 75.4 74.7 38.7 39.9 7,942 9,312 68.9 68.0 31.1 32.0 31.4 30.0 43.0 40.4 19.6 19.4 87.4 87.2 87.3 86.0 87.5 88.4 1,316 1,664 48.5 48.1 51.5 51.9 76.9 75.1 76.3 73.2 77.5 76.9 60.0 62.5 76.6 78.5 44.0 47.1 14 14 68.5 68.1 31.5 31.9 41.4 40.6 56.3 54.6 26.2 26.2 76.8 77.5 90.4 89.7 63.6 65.7 1,396 1,741 60.4 60.1 39.6 39.9 67.9 66.4 82.0 79.7 53.9 53.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 68.9 67.4 68.5 67.9 69.2 66.8 392 480 43.4 42.7 56.6 57.3 45.4 43.6 40.6 38.2 49.9 48.8 72.8 71.8 86.1 86.1 59.8 57.9 .. .. .. .. .. .. 77.6 .. 88.7 .. 66.6 .. 54.8 58.6 63.1 66.6 46.9 50.8 2,629 3,099 54.5 54.9 45.5 45.1 28.7 30.8 31.3 33.7 26.2 27.8 52.7 53.2 75.3 74.0 30.0 32.2 2,434 2,794 63.3 62.1 36.7 37.9 35.1 32.7 43.8 40.0 26.1 25.1 63.8 65.3 79.0 75.8 50.4 55.5 121 147 55.3 55.1 44.7 44.9 52.3 50.0 59.1 55.0 45.8 45.0 90.3 90.0 91.5 91.2 89.1 88.8 5,663 7,077 50.0 49.8 50.0 50.2 82.2 81.4 82.2 81.0 82.2 81.8 73.9 75.6 86.9 86.4 61.3 65.0 674 827 57.7 57.1 42.3 42.9 62.1 60.7 71.9 69.5 52.4 51.9 86.4 85.8 91.8 91.2 81.1 80.5 3,878 5,259 53.2 53.0 46.8 47.0 79.8 78.7 84.6 83.1 74.9 74.2 70.5 69.7 78.7 79.3 62.5 60.0 1,210 1,489 56.1 56.0 43.9 44.0 57.1 57.0 64.0 63.7 50.3 50.3 71.6 67.9 79.0 75.4 64.7 61.2 1,579 1,597 54.5 53.7 45.5 46.3 54.6 50.4 59.7 54.6 49.5 46.3 53.7 54.5 79.6 80.5 27.7 28.3 11,760 12,769 69.8 72.3 30.3 28.0 40.6 39.8 55.7 56.7 25.1 22.5 57.7 61.1 82.2 82.8 32.7 38.8 3,168 3,455 71.6 68.6 28.4 31.4 45.9 47.1 64.5 63.3 26.6 30.1 51.3 51.6 77.1 79.1 25.2 23.9 5,291 6,257 68.6 73.3 31.4 26.7 36.1 36.5 48.8 52.6 23.0 19.8 52.1 55.0 77.6 81.6 23.7 26.1 453 421 74.0 74.8 26.0 25.2 34.9 36.3 50.8 53.2 18.4 18.7 56.3 55.3 84.3 83.7 29.5 28.3 2,848 2,637 69.5 73.8 30.5 26.2 46.7 41.1 65.3 60.7 28.3 21.5 51.0 50.9 76.0 73.8 25.8 27.8 .. .. .. .. .. .. 39.9 .. 50.3 .. 29.0 .. Labor, migration, and population Part III. Development outcomes 99 Participating in growth 9.2 Table Labor force composition Sectora Agriculture Industry Services Male (% of male Female (% of female Male (% of male Female (% of female Male (% of male Female (% of female employment) employment) employment) employment) employment) employment) 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b SUB–SAHARAN AFRICA .. .. .. .. .. .. Angola .. .. .. .. .. .. Benin .. .. .. .. .. .. Botswana 35.1 24.3 19.2 10.8 45.5 64.8 Burkina Faso .. .. .. .. .. .. Burundi .. .. .. .. .. .. Cameroon 53.1 68.4 14.1 3.9 25.5 22.5 Cape Verde .. .. .. .. .. .. Central African Republic .. .. .. .. .. .. Chad .. .. .. .. .. .. Comoros .. .. .. .. .. .. Congo, Dem. Rep. .. .. .. .. .. .. Congo, Rep. .. .. .. .. .. .. Côte d’Ivoire .. .. .. .. .. .. Djibouti .. .. .. .. .. .. Equatorial Guinea .. .. .. .. .. .. Eritrea .. .. .. .. .. .. Ethiopia 8.7 10.3 25.4 19.5 75.6 63.9 Gabon .. .. .. .. .. .. Gambia, The .. .. .. .. .. .. Ghana .. .. .. .. .. .. Guinea .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. Kenya .. .. .. .. .. .. Lesotho .. .. .. .. .. .. Liberia .. .. .. .. .. .. Madagascar 81.5 82.5 5.1 1.6 13.4 15.9 Malawi .. .. .. .. .. .. Mali 49.8 29.9 17.8 14.7 32.4 55.3 Mauritania .. .. .. .. .. .. Mauritius 9.9 7.6 35.5 25.8 53.9 66.1 Mozambique .. .. .. .. .. .. Namibia 22.7 8.2 24.3 9.1 48.7 63.1 Niger .. .. .. .. .. .. Nigeria .. .. .. .. .. .. Rwanda .. .. .. .. .. .. São Tomé and Príncipe 30.6 22.8 26.3 5.9 42.6 70.7 Senegal 34.1 33 20.2 4.9 32.5 42 Seychelles .. .. .. .. .. .. Sierra Leone 66 71.1 10.3 2.5 23.4 26.3 Somalia .. .. .. .. .. .. South Africa 5.4 3.4 31.2 12.5 57.3 79.1 Sudan .. .. .. .. .. .. Swaziland .. .. .. .. .. .. Tanzania 71.2 78 7.3 2.8 21.5 19.2 Togo .. .. .. .. .. .. Uganda 61.8 75.7 10.3 5.3 27.6 19.2 Zambia 65.2 78.6 8.8 2 26 18.4 Zimbabwe .. .. .. .. .. .. NORTH AFRICA 30.9 49.7 24.8 9 44.1 41.2 Algeria 20.4 22.3 25.6 28.2 53.8 49.4 Egypt, Arab Rep. 28.3 43.3 25.8 6 45.6 50.6 Libya .. .. .. .. .. .. Morocco 34.8 60.2 23.8 15.1 41.2 24.5 Tunisia .. .. .. .. .. .. a. Components may not sum to 100 percent because of unclassi�ed data. b. Data are for the most recent year available during the period speci�ed. 100 Part III. Development outcomes Labor, migration, and population Statusa Wage and salaried workers Self-employed workers Contributing family workers Total Male Female Total Male Female Total Male Female (% of total (% of males (% of females (% of total (% of males (% of females (% of total (% of males (% of females employed) employed) employed) employed) employed) employed) employed) employed) employed) 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 73.2 74.4 71.9 12.2 8.1 16.8 2.2 2.2 2.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 19.2 29.3 8.7 59.3 57 61.7 18.2 9.5 27.2 38.9 43.8 33 31.8 32.6 30.9 10.3 6.5 14.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 46.3 49.3 42.7 42.8 41.8 44 10 7.8 12.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 13.4 16 10.8 43.7 51.6 35.4 52.3 32.1 73 .. .. .. .. .. .. .. .. .. 13.6 15.2 11.4 71.4 66.4 78.4 15 18.4 10.2 .. .. .. .. .. .. .. .. .. 79.2 77.2 83.2 18 21.2 11.6 2.2 0.9 4.7 .. .. .. .. .. .. .. .. .. 81.3 82.2 80.3 22.3 20.4 26.6 1 0.9 1.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 7.6 11.3 3.7 .. .. .. 18.1 14.8 21.6 .. .. .. .. .. .. .. .. .. 82.4 83.5 80.8 17 16 18.3 0.4 0.3 0.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 10.5 15.3 6.1 78.1 75 80.9 11.4 9.7 13 .. .. .. .. .. .. .. .. .. 14.5 22.2 7.5 59.4 67.5 52.1 26.1 10.3 40.5 18.7 25.7 9 59.7 49 29.2 19.6 25.4 61.8 37.7 51 23.1 50.4 38.6 63.2 11.9 10.4 13.6 55.9 58.6 46.5 26.4 30.3 12.8 17.6 11.2 40.6 59.8 61.9 49.8 31.7 30.7 36.6 8.2 7.1 13.6 61.8 63.7 53.7 25.1 27.7 13.7 13.1 8.6 32.6 .. .. .. .. .. .. .. .. .. 44.8 48.8 34.1 28.9 34.5 13.9 26.1 16.5 51.8 64.3 .. .. 26.8 .. .. 8.7 .. .. Labor, migration, and population Part III. Development outcomes 101 Participating in growth 9.3 Table Unemployment Unemployment Youth unemployment (ages 15 and older) (ages 15–24) Total Male Female Total Male Female (% of total (% of male (% of female (% of total labor (% of male labor (% of female labor labor force) labor force) labor force) force ages 15–24) force ages 15–24) force ages 15–24) 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b SUB–SAHARAN AFRICA Angola .. .. .. .. .. .. Benin 0.7 0.9 0.4 0.8 1.1 0.6 Botswana 17.6 15.3 19.9 13.6 13.2 14.0 Burkina Faso .. .. .. .. .. .. Burundi .. .. .. .. .. .. Cameroon 2.9 2.5 3.3 .. .. .. Cape Verde .. .. .. .. .. .. Central African Republic .. .. .. .. .. .. Chad .. .. .. .. .. .. Comoros .. .. .. .. .. .. Congo, Dem. Rep. .. .. .. .. .. .. Congo, Rep. .. .. .. .. .. .. Côte d’Ivoire .. .. .. .. .. .. Djibouti 59.5 54.6 68.6 .. .. .. Equatorial Guinea .. .. .. .. .. .. Eritrea .. .. .. .. .. .. Ethiopia 20.5 12.1 29.9 24.9 19.5 29.4 Gabon .. .. .. .. .. .. Gambia, The .. .. .. .. .. .. Ghana 10.4 10.1 10.7 16.6 16.4 16.7 Guinea .. .. .. .. .. .. Guinea-Bissau .. .. .. .. .. .. Kenya .. .. .. .. .. .. Lesotho .. .. .. .. .. .. Liberia 5.6 6.8 4.2 4.7 5.7 3.7 Madagascar 2.6 1.7 3.5 2.3 1.7 2.8 Malawi 7.8 5.4 10.0 .. .. .. Mali 8.8 7.2 10.9 .. .. .. Mauritania 33.0 8.8 41.2 .. .. .. Mauritius 7.3 4.4 12.3 21.4 18.1 26.2 Mozambique .. .. .. .. .. .. Namibia 37.6 32.5 43.0 41.7 36.7 47.0 Niger 1.5 1.7 0.9 3.2 4.0 1.7 Nigeria .. .. .. .. .. .. Rwanda .. .. .. .. .. .. São Tomé and Príncipe 16.7 11.0 24.5 .. .. .. Senegal 10.0 7.9 13.6 14.8 11.9 20.1 Seychelles 5.5 6.1 4.9 20.3 .. .. Sierra Leone 3.4 4.5 2.3 5.2 7.3 3.5 Somalia .. .. .. .. .. .. South Africa 23.8 22.0 25.9 48.2 44.6 52.5 Sudan .. .. .. .. .. .. Swaziland .. .. .. .. .. .. Tanzania 4.3 2.8 5.8 8.8 7.4 10.1 Togo .. .. .. .. .. .. Uganda 3.2 2.5 3.9 .. .. .. Zambia 12.9 14.1 11.3 21.4 23.1 19.5 Zimbabwe 4.2 4.2 4.1 24.9 28.2 21.4 NORTH AFRICA Algeria 11.3 11.0 10.1 24.3 42.8 46.3 Egypt, Arab Rep. 9.4 5.2 22.9 24.8 17.2 47.9 Libya .. .. .. .. .. .. Morocco 10.0 9.8 10.5 21.9 22.8 19.4 Tunisia 14.2 13.1 17.3 30.7 31.4 29.3 a. Components may not sum to 100 percent because of unclassi�ed data. b. Data are for the most recent year available during the period speci�ed. 102 Part III. Development outcomes Labor, migration, and population Unemployment by education levela Primary Secondary Tertiary Total Male Female Total Male Female Total Male Female (% of total (% of male (% of female (% of total (% of male (% of female (% of total (% of male (% of female unemployment) unemployment) unemployment) unemployment) unemployment) unemployment) unemployment) unemployment) unemployment) 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b 2000–09 b .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 65.5 64.4 66.3 27.3 23.9 30.2 .. .. .. 47.0 44.4 58.3 19.7 16.7 33.3 6.1 5.6 8.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 35.9 50.6 30.8 13.3 19.0 11.3 3.2 5.7 2.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 43.9 42.9 44.4 23.8 25.8 22.7 9.3 14.0 6.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 44.2 49.5 39.7 48.5 41.4 53.2 6.4 8.1 3.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 60.7 62.8 59.4 24.1 23.0 24.9 5.9 0.5 9.4 .. .. .. .. .. .. .. .. .. 40.2 42.2 37.9 6.9 7.5 6.2 2.5 2.8 2.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 36.2 39.8 32.9 56.3 52.7 59.7 4.5 4.0 5.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 59.3 65.2 32.5 23.0 21.4 30.4 11.4 6.6 33.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 51.1 57.7 36.6 22.4 21.7 23.9 21.6 16.2 33.5 41.4 46.0 31.9 37.7 37.3 38.5 13.6 9.0 23.3 Labor, migration, and population Part III. Development outcomes 103 Participating in growth 9.4 Table Migration and population Population International migration Population dynamics Worker remittances, Migrant remittance Migrant stock received inflows Annual Fertility rate Share of Net Total Share of Total Share of Total Male Female growth rate (births per population (%) Total migration ($ millions) GDP (%) ($ millions) GDP (%) (millions) (% of total) (% of total) (%) woman) 2005 2005 2005 2009 2009 2009 2009 2009 2009 2009 2009 2009 SUB–SAHARAN AFRICA 2.1 16,338,433 –1,599,939 .. .. 20,791.3 2.2 841.0 49.8 50.2 2.5 5.0 Angola 0.3 56,055 175,000 0.2 0.0 .. .. 18.5 49.3 50.7 2.6 5.6 Benin 2.4 187,584 98,831 .. .. 251.3 3.8 8.9 50.5 49.5 3.1 5.4 Botswana 4.4 80,148 20,000 61.6 0.5 87.9 0.7 1.9 50.0 50.0 1.5 2.8 Burkina Faso 5.6 772,814 100,000 .. .. 99.3 1.2 15.8 49.9 50.1 3.4 5.8 Burundi 1.1 81,566 191,600 28.2 2.1 28.2 2.1 8.3 49.0 51.0 2.8 4.5 Cameroon 1.2 211,880 –12,121 129.2 0.6 147.6 0.7 19.5 50.0 50.0 2.2 4.5 Cape Verde 2.3 11,183 –12,500 145.8 9.4 146.2 9.4 0.5 47.8 52.2 1.4 2.7 Central African Republic 1.8 75,623 –45,000 .. .. .. .. 4.4 49.1 50.9 1.9 4.7 Chad 3.6 358,446 218,966 .. .. .. .. 11.2 49.7 50.3 2.6 6.1 Comoros 2.3 13,661 –10,000 .. .. .. .. 0.7 50.2 49.8 2.4 3.9 Congo, Dem. Rep. 0.8 480,105 –236,676 .. .. .. .. 66.0 49.6 50.4 2.7 5.9 Congo, Rep. 3.8 128,838 3,527 .. .. 14.8 0.2 3.7 49.9 50.1 1.9 4.3 Côte d’Ivoire 12.3 2,371,277 –338,732 .. .. 185.5 0.8 21.1 50.9 49.1 2.3 4.5 Djibouti 13.7 110,333 0 6.0 0.6 32.5 3.1 0.9 50.0 50.0 1.7 3.8 Equatorial Guinea 1 5,800 15,000 .. .. .. .. 0.7 49.6 50.4 2.6 5.3 Eritrea 0.3 14,612 229,376 .. .. .. .. 5.1 49.2 50.8 2.9 4.5 Ethiopia 0.7 554,021 –340,460 261.6 0.9 261.6 0.9 82.8 49.7 50.3 2.6 5.2 Gabon 17.9 244,550 9,566 .. .. .. .. 1.5 50.0 50.0 1.8 3.2 Gambia, The 15.2 231,739 31,127 72.2 9.8 79.8 10.9 1.7 49.6 50.4 2.7 5.0 Ghana 7.6 1,669,267 11,690 114.5 0.4 114.5 0.4 23.8 50.7 49.3 2.1 3.9 Guinea 4.4 401,217 –425,000 50.5 1.2 63.7 1.6 10.1 50.5 49.5 2.4 5.3 Guinea-Bissau 1.3 19,219 1,181 .. .. 49.5 5.9 1.6 49.5 50.5 2.2 5.7 Kenya 2.2 790,071 25,144 631.5 2.1 1,686.2 5.7 39.8 50.0 50.0 2.6 4.9 Lesotho 0.3 6,247 –36,000 28.5 1.8 414.1 26.2 2.1 47.2 52.8 0.8 3.3 Liberia 2.9 96,793 62,452 7.0 0.8 25.1 2.9 4.0 49.7 50.3 4.2 5.8 Madagascar 0.2 39,699 –5,000 .. .. .. .. 19.6 49.8 50.2 2.7 4.6 Malawi 2 278,806 –30,000 .. .. .. .. 15.3 49.7 50.3 2.8 5.5 Mali 1.4 165,448 –134,204 .. .. 431.0 4.8 13.0 49.4 50.6 2.4 6.5 Mauritania 2.2 66,053 30,000 .. .. .. .. 3.3 50.7 49.3 2.3 4.4 Mauritius 3.3 40,824 0 .. .. 211.2 2.5 1.3 49.6 50.4 0.5 1.5 Mozambique 1.9 406,075 –20,000 31.5 0.3 111.1 1.1 22.9 48.6 51.4 2.3 5.0 Namibia 6.6 131,630 –1,000 5.3 0.1 13.6 0.1 2.2 49.3 50.7 1.9 3.3 Niger 1.4 182,960 –28,497 .. .. 93.7 1.7 15.3 50.1 49.9 3.9 7.1 Nigeria 0.7 972,126 –170,000 18230.2 10.5 9,584.8 5.5 154.7 50.1 49.9 2.3 5.6 Rwanda 4.8 435,749 5,931 88.1 1.7 92.6 1.8 10.0 48.4 51.6 2.8 5.3 São Tomé and Príncipe 3.5 5,387 –7,000 2.0 1.0 2.0 1.0 0.2 49.5 50.5 1.6 3.7 Senegal 2 220,208 –100,000 .. .. 1,364.7 10.6 12.5 49.6 50.4 2.6 4.7 Seychelles 10.2 8,441 .. 11.6 1.5 12.5 1.6 0.1 .. .. 1.2 2.3 Sierra Leone 3 152,101 336,000 32.7 1.7 46.7 2.4 5.7 48.7 51.3 2.4 5.2 Somalia 0.3 21,271 –200,000 .. .. .. .. 9.1 49.6 50.4 2.3 6.4 South Africa 2.6 1,248,732 700,001 .. .. 902.3 0.3 49.3 49.3 50.7 1.1 2.5 Sudan 1.7 639,686 –531,781 .. .. 2,992.7 5.5 42.3 50.4 49.6 2.2 4.1 Swaziland 3.4 38,574 –46,077 2.0 0.1 93.5 3.1 1.2 48.9 51.1 1.5 3.5 Tanzania 2 797,701 –345,000 11.9 0.1 23.3 0.1 43.7 49.9 50.1 2.9 5.5 Togo 3.1 182,823 –3,570 .. .. 337.1 11.8 6.6 49.5 50.5 2.4 4.2 Uganda 2.3 652,408 –5,000 749.7 4.7 749.7 4.7 32.7 50.1 49.9 3.3 6.3 Zambia 2.4 287,337 –81,713 41.3 0.3 41.3 0.3 12.9 49.9 50.1 2.5 5.7 Zimbabwe 3.1 391,345 –700,000 .. .. .. .. 12.5 48.3 51.7 0.5 3.4 NORTH AFRICA 0.8 1,192,628 –1,048,004 15145.3 4.0 17,458.3 3.3 166.7 50.2 49.8 1.6 2.6 Algeria 0.7 242,446 –140,000 .. .. 2,058.7 1.5 34.9 50.5 49.5 1.5 2.3 Egypt, Arab Rep. 0.3 246,745 –291,405 7149.6 3.8 7,149.6 3.8 83.0 50.3 49.7 1.8 2.8 Libya 10.4 617,536 14,000 0.0 0.0 16.0 0.0 6.4 51.7 48.3 2.0 2.6 Morocco 0.2 51,020 –550,000 6269.1 6.9 6,269.5 6.9 32.0 49.1 50.9 1.2 2.3 Tunisia 0.3 34,881 –80,599 1726.6 4.4 1,964.5 5.0 10.4 50.3 49.7 1.0 2.1 104 Part III. Development outcomes Labor, migration, and population Population Age composition (% of total) Dependency Geographic distribution (%) ratio Ages 0–14 Ages 15–64 Ages 65 and older (% of Share of total population Annual growth working-age Rural Urban Rural Urban Total Male Female Total Male Female Total Male Female population) population population population population 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 42.6 43.1 42.0 54.3 54.1 54.5 3.1 2.8 3.4 84.8 63.0 37.0 1.7 3.8 45.0 45.4 44.5 52.6 52.4 52.8 2.5 2.2 2.7 90.2 42.4 57.6 0.5 4.2 43.1 43.4 42.7 53.7 54.0 53.4 3.2 2.6 3.9 86.2 58.4 41.6 2.4 4.1 33.3 33.6 33.0 62.9 63.3 62.5 3.8 3.1 4.5 58.9 39.7 60.3 –0.4 2.7 46.3 47.2 45.4 51.7 51.2 52.2 2.0 1.6 2.4 93.5 80.0 20.0 2.9 5.5 38.4 39.2 37.6 58.8 58.6 59.1 2.8 2.2 3.3 70.0 89.3 10.7 2.5 5.6 40.9 41.2 40.6 55.5 55.5 55.5 3.6 3.2 3.9 80.1 42.4 57.6 0.3 3.7 36.2 38.0 34.5 59.6 59.0 60.2 4.2 3.0 5.3 67.8 39.6 60.4 –0.5 2.6 40.6 41.2 40.1 55.5 55.3 55.6 3.9 3.5 4.3 80.2 61.3 38.7 1.6 2.3 45.7 46.2 45.3 51.4 51.3 51.6 2.8 2.6 3.1 94.4 72.9 27.1 2.0 4.4 38.1 38.6 37.7 58.8 58.7 58.9 3.1 2.7 3.4 70.1 71.9 28.1 2.3 2.6 46.7 47.2 46.2 50.7 50.5 50.8 2.6 2.3 3.0 97.3 65.4 34.6 1.8 4.5 40.5 40.8 40.1 55.7 55.7 55.8 3.8 3.5 4.2 79.5 38.3 61.7 0.9 2.5 40.6 40.1 41.3 55.5 56.0 55.0 3.9 4.0 3.7 80.2 50.6 49.4 1.0 3.7 36.1 36.4 35.7 60.7 60.7 60.7 3.2 2.9 3.6 64.8 12.3 87.7 –1.5 2.2 41.0 41.5 40.5 56.1 55.9 56.4 2.9 2.6 3.2 78.2 60.5 39.5 2.3 3.0 41.5 42.6 40.5 56.0 55.5 56.5 2.5 1.9 3.0 78.5 78.8 21.2 2.4 5.0 43.5 44.0 43.1 53.3 53.1 53.5 3.2 2.9 3.4 87.6 82.7 17.3 2.2 4.3 36.1 36.5 35.8 59.5 59.5 59.6 4.3 4.0 4.7 68.0 14.5 85.5 –1.5 2.4 42.3 42.9 41.7 54.9 54.5 55.3 2.8 2.6 3.0 82.2 42.7 57.3 0.7 4.2 38.4 38.8 38.0 58.0 57.8 58.1 3.6 3.4 3.8 72.5 49.2 50.8 0.6 3.5 42.8 43.2 42.4 54.0 54.0 53.9 3.3 2.8 3.7 85.3 65.1 34.9 1.6 3.8 42.6 43.2 42.1 53.9 53.7 54.1 3.5 3.2 3.8 85.5 70.1 29.9 2.1 2.5 42.8 43.1 42.5 54.6 54.5 54.6 2.6 2.4 2.8 83.3 78.1 21.9 2.3 4.0 38.8 41.4 36.6 56.4 54.4 58.2 4.7 4.2 5.2 77.3 73.8 26.2 –0.1 3.6 42.7 43.3 42.1 54.2 53.9 54.5 3.1 2.8 3.4 84.6 39.2 60.8 2.5 5.3 42.9 43.2 42.6 54.0 53.9 54.2 3.0 2.9 3.2 85.0 70.1 29.9 2.2 3.8 46.2 46.9 45.5 50.7 50.2 51.2 3.1 2.9 3.3 97.2 80.7 19.3 2.2 5.4 44.2 45.2 43.2 53.5 52.7 54.4 2.3 2.2 2.4 86.8 67.3 32.7 1.5 4.1 39.5 40.1 38.9 57.9 57.8 57.9 2.7 2.1 3.2 72.9 58.8 41.2 2.0 2.8 22.6 23.2 22.1 70.1 70.9 69.3 7.3 5.9 8.6 42.7 57.5 42.5 0.4 0.6 44.0 45.4 42.7 52.8 51.8 53.7 3.3 2.9 3.7 89.6 62.4 37.6 1.0 4.4 36.9 37.6 36.2 59.5 59.3 59.7 3.6 3.1 4.1 68.0 62.6 37.4 1.0 3.5 49.9 50.9 48.9 48.1 47.3 48.9 2.0 1.8 2.2 108.0 83.4 16.6 3.8 4.4 42.5 43.0 42.0 54.3 54.1 54.6 3.1 2.9 3.4 84.0 50.9 49.1 0.9 3.8 42.3 43.3 41.3 55.2 54.7 55.8 2.5 2.1 2.9 81.0 81.4 18.6 2.5 4.3 40.7 41.5 39.8 55.4 55.0 55.7 4.0 3.5 4.4 80.6 38.6 61.4 –0.5 2.9 43.6 44.3 42.8 54.0 53.4 54.7 2.4 2.3 2.5 85.0 57.4 42.6 2.2 3.2 .. .. .. .. .. .. .. .. .. .. 45.2 54.8 0.1 2.0 43.4 44.4 42.5 54.8 53.8 55.7 1.8 1.8 1.8 82.6 61.9 38.1 1.9 3.3 44.9 45.4 44.4 52.4 52.1 52.7 2.7 2.5 3.0 90.9 63.0 37.0 1.6 3.5 30.5 31.1 29.9 65.0 65.3 64.7 4.5 3.5 5.4 53.8 38.8 61.2 –0.2 1.9 39.1 39.6 38.7 57.3 57.1 57.4 3.6 3.3 3.9 74.6 55.7 44.3 0.6 4.2 39.3 40.4 38.3 57.3 56.7 57.9 3.3 2.9 3.8 74.5 74.8 25.2 1.1 2.6 44.7 45.2 44.2 52.2 52.0 52.4 3.1 2.8 3.4 91.6 74.0 26.0 2.3 4.6 39.9 40.3 39.5 56.6 56.5 56.6 3.5 3.1 3.9 76.7 57.3 42.7 1.2 4.1 48.9 49.1 48.6 48.6 48.6 48.6 2.5 2.3 2.8 105.8 86.9 13.1 3.1 4.5 46.2 46.6 45.9 50.7 50.6 50.8 3.0 2.8 3.3 97.1 64.4 35.6 2.2 2.9 39.9 41.4 38.5 56.0 54.9 57.0 4.1 3.7 4.5 78.5 62.2 37.8 –0.3 1.8 29.9 30.4 29.3 65.3 65.2 65.4 4.8 4.4 5.3 53.4 46.9 53.1 1.1 2.0 27.3 27.7 27.0 68.1 68.2 67.9 4.6 4.1 5.1 46.9 34.1 65.9 –0.3 2.5 32.3 32.9 31.8 63.1 63.0 63.3 4.6 4.1 5.0 58.4 57.2 42.8 1.7 1.9 30.1 29.8 30.5 65.6 66.1 65.1 4.2 4.1 4.4 52.4 22.3 77.7 1.2 2.2 28.4 29.4 27.4 66.3 65.7 66.8 5.4 4.9 5.8 50.9 43.6 56.4 0.4 1.8 23.2 23.8 22.6 70.0 69.9 70.2 6.7 6.2 7.2 42.8 33.1 66.9 –0.2 1.6 Labor, migration, and population Part III. Development outcomes 105 Participating in growth 10.1 Table HIV/AIDS Estimated HIV prevalence rate (%) Estimated number of people living with HIV/AIDS Adults (ages 15–49) (thousands) Point estimate Low estimate High estimate 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 SUB–SAHARAN AFRICA Angola 28 140 200 0.5 1.9 2.0 0.2 1.4 1.6 1.4 2.4 2.4 Benin 6 49 60 0.2 1.4 1.2 <0.1 1.2 1.0 3.7 1.7 1.3 Botswana 23 260 320 3.5 26.0 24.8 2.9 25.1 23.8 4.2 27.1 25.8 Burkina Faso 160 150 110 3.9 2.3 1.2 2.6 1.9 1.0 4.8 2.7 1.5 Burundi 93 170 180 3.9 5.2 3.3 3.7 5.1 2.9 4.0 5.4 3.5 Cameroon 33 460 610 0.6 5.5 5.3 0.3 5.0 4.9 2.4 6.0 5.8 Cape Verde .. .. .. .. .. .. .. .. .. .. .. Central African Republic 44 190 130 3.1 9.4 4.7 2.0 8.4 4.2 6.2 11.4 5.2 Chad 31 130 210 1.1 3.0 3.4 0.5 2.0 2.8 2.0 4.0 5.1 Comoros <1.0 <0.1 <0.5 <0.1 <0.1 0.1 <0.1 <0.1 0.1 <0.1 <0.1 0.1 Congo, Dem. Rep. .. .. .. .. ... .. 1.2 1.1 1.2 1.6 1.5 1.6 Congo, Rep. 63 68 77 5.2 3.9 3.4 3.6 3.5 3.1 6.4 4.5 3.8 Côte d’Ivoire 140 640 450 2.4 6.9 3.4 1.3 6.2 3.1 7.2 7.6 3.9 Djibouti 3 12 14 0.9 2.9 2.5 <0.1 2.0 .. 3.5 4.1 3.2 Equatorial Guinea <0.5 4 20 0.1 1.5 5.0 <0.1 1.0 3.5 0.2 2.5 6.6 Eritrea 5 25 25 0.3 1.2 0.8 0.1 0.9 0.6 0.9 1.6 1.0 Ethiopia .. .. .. .. ... .. .. .. .. .. .. .. Gabon 4 34 46 0.9 5.2 5.2 0.6 4.1 4.2 1.5 6.6 6.2 Gambia, The <1.0 4 18 0.1 0.5 2.0 0.1 0.3 1.3 1.7 1.1 2.9 Ghana 22 250 260 0.3 2.3 1.8 0.2 2.0 1.6 1.5 2.6 2.0 Guinea 34 78 79 1.1 1.7 1.3 0.5 1.1 1.1 7.6 2.7 1.6 Guinea-Bissau 1 13 22 0.3 1.8 2.5 0.1 1.5 2.0 0.4 2.2 3.0 Kenya 400 1,500 1,500 3.9 9.0 6.3 3.0 8.6 5.8 6.6 9.6 6.5 Lesotho 6 240 290 0.8 24.5 23.6 0.6 23.0 22.3 1.2 26.1 25.2 Liberia 3 52 37 0.3 3.3 1.5 0.1 2.2 1.3 0.6 4.5 1.8 Madagascar 12 17 24 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.3 Malawi 310 850 920 7.2 14.2 11.0 3.3 13.0 10.0 10.8 15.5 12.1 Mali 15 91 76 0.4 1.7 1.0 0.1 1.3 0.8 2.0 2.0 1.3 Mauritania 2 8 14 0.2 0.6 0.7 0.1 0.5 0.6 0.2 0.7 0.9 Mauritius <0.5 3 9 <0.1 0.3 1.0 <0.1 0.2 0.7 0.2 0.4 1.3 Mozambique 76 750 1,400 1.2 8.6 11.5 0.9 7.8 10.6 1.5 9.4 12.2 Namibia 11 150 180 1.6 15.3 13.1 0.9 12.9 11.1 2.3 18.1 15.5 Niger 4 51 61 0.1 1.0 0.8 0.1 1.0 0.8 0.1 1.0 0.9 Nigeria 590 2,600 3,300 1.3 3.9 3.6 0.2 3.3 3.3 2.1 4.3 4.0 Rwanda 160 170 170 5.2 3.8 2.9 4.3 3.5 2.5 8.4 4.6 3.3 São Tomé and Príncipe .. .. .. .. .. .. .. .. .. .. .. Senegal 6 30 59 0.2 0.6 0.9 0.1 0.5 0.7 0.2 0.7 1.0 Seychelles .. .. .. .. .. .. .. .. .. .. .. Sierra Leone <0.5 21 49 <0.1 0.9 1.6 <0.1 0.4 1.4 <0.1 1.6 2.1 Somalia 2 9 34 0.1 0.2 0.7 <0.1 <0.1 0.5 0.3 0.3 1.0 South Africa 140 4,200 5,600 0.7 16.1 17.8 0.6 15.7 17.2 0.9 16.6 18.3 Sudan 12 61 .. 0.1 0.3 1.1 <0.1 0.1 0.9 0.4 0.5 1.4 Swaziland 9 120 180 2.3 22.3 25.9 1.8 21.0 24.9 2.7 23.6 27.0 Tanzania 600 1,400 1,400 4.8 7.3 5.6 4.3 6.9 5.3 5.3 8.0 6.1 Togo 11 99 120 0.6 3.6 3.2 0.1 2.8 2.5 1.2 4.3 3.8 Uganda 870 980 1,200 10.2 7.3 6.5 8.6 6.7 5.9 11.5 7.7 6.9 Zambia 500 810 980 12.7 14.4 13.5 3.4 13.8 12.8 26.4 15.2 14.1 Zimbabwe 510 1,700 1,200 10.1 24.8 14.3 8.7 23.8 13.4 11.7 26.1 15.4 NORTH AFRICA Algeria .. 6 18 <0.1 <0.1 0.1 <0.1 <0.1 0.1 <0.1 <0.1 0.1 Egypt, Arab Rep. <0.5 3 11 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 Libya .. .. .. .. .. .. .. .. .. .. .. Morocco 3 13 3 <0.1 0.1 0.1 <0.1 0.1 0.1 <0.1 0.1 0.2 Tunisia <0.2 <1.0 2 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 0.1 106 Part III. Development outcomes HIV/AIDS Estimated HIV prevalence rate (%) Young men Young women (ages 15–24) (ages 15–24) Point estimate Low estimate High estimate Point estimate Low estimate High estimate 2009 2009 2009 2009 2009 2009 0.6 0.4 0.9 1.6 1.1 2.2 0.3 0.2 0.4 0.7 0.5 1.1 5.2 3.7 7.3 11.8 9.0 15.9 0.5 0.3 0.6 0.8 0.6 1.2 1.0 0.8 1.2 2.1 1.6 2.7 1.6 1.2 2.1 3.9 3.1 5.4 .. .. .. .. .. .. 1.0 0.6 1.4 2.2 1.4 3.1 1.0 0.7 2.0 2.5 1.7 5.2 0.1 0.1 0.1 <0.1 <0.1 <0.1 .. 0.4 0.6 .. 0.9 1.5 1.2 0.9 1.6 2.6 2.1 3.6 0.7 0.5 1.1 1.5 1.1 2.3 0.8 .. .. 1.9 .. .. 1.9 1.0 3.2 5.0 2.7 7.9 0.2 0.1 0.3 0.4 0.2 0.7 .. .. .. .. .. .. 1.4 0.8 2.0 3.5 2.1 5.2 0.9 0.5 1.6 2.4 1.4 4.0 0.5 0.4 0.7 1.3 0.9 1.8 0.4 0.3 0.6 0.9 0.6 1.3 0.8 0.5 1.1 2.0 1.5 2.9 1.8 1.3 2.4 4.1 3.0 5.4 5.4 4.1 7.4 14.2 11.2 19.2 0.3 0.1 0.5 0.7 0.2 1.2 0.1 0.1 0.4 0.1 <0.1 0.1 3.1 2.3 4.2 6.8 5.3 9.2 0.2 0.1 0.4 0.5 0.2 0.9 0.4 0.2 1.4 0.3 0.1 0.5 0.3 0.2 0.4 0.2 0.1 0.3 3.1 2.4 4.4 8.6 7.0 12.1 2.3 1.3 3.6 5.8 3.7 8.6 0.2 0.2 0.3 0.5 0.4 0.6 1.2 0.9 1.6 2.9 2.3 3.9 1.3 0.9 1.6 1.9 1.3 2.3 .. .. .. .. .. .. 0.3 0.2 0.4 0.7 0.5 1.0 .. .. .. .. .. .. 0.6 0.3 1.0 1.5 0.9 2.5 0.4 .. .. 0.6 .. .. 4.5 4.1 5.0 13.6 12.3 15.0 0.5 .. .. 1.3 .. .. 6.5 4.8 8.8 15.6 12.6 21.3 1.7 1.3 2.3 3.9 3.1 5.3 0.9 0.6 1.2 2.2 1.5 3.1 2.3 1.8 2.8 4.8 4.0 6.4 4.2 3.2 5.5 8.9 7.3 12.0 3.3 2.5 4.4 6.9 5.3 9.3 0.1 <0.1 0.2 <0.1 <0.1 0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 .. .. .. .. .. .. 0.1 <0.1 0.3 0.1 <0.1 0.1 <0.1 <0.1 0.1 <0.1 <0.1 <0.1 (continued) HIV/AIDS Part III. Development outcomes 107 Participating in growth 10.1 Table HIV/AIDS (continued) Deaths of adults and children due to HIV/AIDS AIDS orphans (thousands) (ages 0–17, thousands) Point estimate Low estimate High estimate Point estimate Low estimate High estimate 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 1990 2000 2009 SUB–SAHARAN AFRICA Angola <1.0 9.2 11.0 <0.5 5.6 7.7 3.2 13.0 16.0 2.1 54.0 140.0 <1.0 23.0 95.0 9.9 95.0 200.0 Benin <0.2 3.0 2.7 <0.1 1.7 1.8 18.0 5.4 3.7 <0.5 11.0 30.0 <0.1 3.7 18.0 470.0 110.0 53.0 Botswana <1.0 13.0 5.8 <0.5 11.0 2.3 <1.0 16.0 14.0 1.0 45.0 93.0 <1.0 36.0 71.0 1.7 59.0 120.0 Burkina Faso 6.7 15.0 7.1 4.1 11.0 4.8 11.0 19.0 9.7 13.0 130.0 140.0 5.2 96.0 100.0 71.0 180.0 170.0 Burundi 3.9 14.0 15.0 3.1 11.0 12.0 4.7 16.0 17.0 10.0 120.0 200.0 7.7 98.0 170.0 14.0 150.0 230.0 Cameroon <1.0 27.0 37.0 <0.5 22.0 29.0 9.3 33.0 46.0 1.3 100.0 330.0 <1.0 67.0 270.0 36.0 210.0 420.0 Cape Verde .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Central African Republic 1.0 14.0 11.0 <1.0 11.0 8.8 5.8 20.0 13.0 2.0 69.0 140.0 1.2 43.0 110.0 49.0 100.0 180.0 Chad 1.4 7.9 11.0 <1.0 4.7 8.1 2.9 12.0 15.0 5.1 43.0 120.0 2.1 22.0 79.0 11.0 79.0 170.0 Comoros <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 .. .. <0.1 .. .. <0.1 .. .. <0.1 Congo, Dem. Rep. .. .. .. 12.0 23.0 26.0 26.0 34.0 40.0 .. .. .. 46.0 270.0 350.0 210.0 430.0 510.0 Congo, Rep. 3.0 5.7 5.1 <1.0 4.8 4.1 6.2 7.1 6.4 6.9 48.0 51.0 <0.2 31.0 41.0 31.0 72.0 66.0 Côte d’Ivoire 3.9 48.0 36.0 2.1 34.0 29.0 12.0 65.0 44.0 7.3 230.0 440.0 4.0 140.0 330.0 16.0 410.0 550.0 Djibouti <0.1 <1.0 1.0 <0.1 <0.5 <1.0 <1.0 1.3 1.4 .. .. .. .. .. .. .. .. .. Equatorial Guinea <0.1 <0.2 <1.0 <0.1 <0.2 <1.0 <0.1 <0.5 1.4 <0.1 <0.5 4.1 <0.1 <0.2 2.5 <0.1 <1.0 6.4 Eritrea <0.2 1.6 1.7 <0.1 <1.0 1.0 <1.0 2.5 2.5 <0.5 7.0 19.0 <0.1 3.2 12.0 2.6 16.0 28.0 Ethiopia .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Gabon <0.2 1.8 2.4 <0.1 1.4 1.6 <0.5 2.5 3.4 <0.2 6.0 18.0 <0.1 4.1 12.0 <0.5 9.2 25.0 Gambia, The <0.1 <0.2 <1.0 <0.1 <0.1 <0.5 <1.0 <1.0 1.2 <0.1 <1.0 2.8 <0.1 <0.5 1.4 6.6 6.5 6.5 Ghana <1.0 15.0 18.0 <0.5 11.0 14.0 6.9 20.0 22.0 1.3 47.0 160.0 <1.0 33.0 120.0 58.0 110.0 210.0 Guinea 1.1 6.1 4.7 <0.5 2.5 3.1 15.0 14.0 6.9 2.5 36.0 59.0 1.1 9.9 34.0 110.0 97.0 120.0 Guinea-Bissau <0.1 <1.0 1.2 <0.1 <0.5 <1.0 <0.1 <1.0 1.6 <0.2 2.2 9.7 <0.1 1.3 7.7 <0.5 3.1 12.0 Kenya 10.0 120.0 80.0 6.7 98.0 61.0 22.0 140.0 99.0 17.0 710.0 1,200.0 10.0 550.0 980.0 40.0 960.0 1,400.0 Lesotho .. 12.0 14.0 <0.1 10.0 10.0 <0.2 15.0 18.0 <0.1 38.0 130.0 <0.1 29.0 110.0 <0.2 51.0 160.0 Liberia <0.1 3.5 3.6 <0.1 2.0 2.8 <0.2 5.7 4.6 <0.1 15.0 52.0 <0.1 7.3 34.0 <0.5 25.0 76.0 Madagascar <1.0 1.3 1.7 <1.0 1.0 1.4 1.4 1.5 2.0 6.6 9.4 11.0 4.0 7.3 9.3 12.0 12.0 14.0 Malawi 11.0 64.0 51.0 4.1 53.0 38.0 22.0 77.0 67.0 25.0 380.0 650.0 7.1 280.0 540.0 68.0 500.0 780.0 Mali <0.5 6.9 4.4 <0.1 3.8 3.0 4.3 11.0 6.1 <0.5 29.0 59.0 <0.1 11.0 36.0 15.0 82.0 93.0 Mauritania <0.1 <0.5 <1.0 <0.1 <0.5 <1.0 <0.2 <1.0 1.0 <0.5 1.3 3.6 <0.1 <1.0 2.7 <0.5 1.9 4.8 Mauritius <0.1 <0.1 <0.5 <0.1 <0.1 <0.5 <0.2 <0.2 <1.0 <0.1 <0.2 1.0 <0.1 <0.1 <0.5 <0.5 <0.5 <1.0 Mozambique 2.2 36.0 74.0 1.5 28.0 57.0 3.3 45.0 92.0 6.6 180.0 670.0 2.1 84.0 .. 5.6 150.0 .. Namibia <0.5 6.7 6.7 <0.2 5.1 2.5 <1.0 8.8 11.0 <1.0 23.0 70.0 <0.5 17.0 50.0 1.4 33.0 96.0 Niger <0.2 2.9 4.3 <0.1 2.3 3.3 <0.2 3.5 5.6 <0.5 13.0 57.0 <0.5 11.0 44.0 <0.5 16.0 73.0 Nigeria 10.0 200.0 220.0 <0.5 110.0 170.0 21.0 250.0 260.0 12.0 1,100.0 2,500.0 <0.5 300.0 1,800.0 94.0 1,700.0 3,100.0 Rwanda 8.4 15.0 4.1 5.6 12.0 <1.0 13.0 21.0 97.0 32.0 160.0 130.0 19.0 130.0 98.0 92.0 240.0 180.0 São Tomé and Principe .. – .. .. .. .. .. .. .. .. .. .. .. .. .. .. Senegal <0.5 1.6 2.6 <0.2 1.3 1.9 <0.5 2.0 3.5 <1.0 7.3 19.0 <0.5 5.4 15.0 1.4 9.4 25.0 Seychelles .. – .. .. .. .. .. .. .. .. .. .. .. .. .. .. Sierra Leone <0.1 <1.0 2.8 <0.1 <0.5 2.1 <0.1 1.9 3.7 <0.1 1.5 15.0 <0.1 <1.0 9.2 <0.1 5.1 26.0 Somalia <0.2 <0.5 .. <0.1 <0.1 .. <1.0 <1.0 .. .. .. .. .. .. .. .. .. .. South Africa 2.9 170.0 310.0 2.0 140.0 260.0 4.3 210.0 390.0 4.4 430.0 1,900.0 2.3 340.0 1,600.0 7.4 550.0 2,400.0 Sudan <1.0 3.0 .. <0.1 <0.5 .. 3.5 6.5 .. .. .. .. .. .. .. .. .. .. Swaziland <0.5 5.7 7.0 <0.2 4.7 4.6 <0.5 7.1 10.0 <1.0 23.0 69.0 <0.5 18.0 55.0 <1.0 29.0 86.0 Tanzania 21.0 110.0 86.0 16.0 90.0 69.0 27.0 130.0 110.0 53.0 750.0 1,300.0 37.0 610.0 1,100.0 75.0 940.0 1,500.0 Togo <0.5 5.6 7.7 <0.1 3.8 5.3 2.0 7.4 10.0 <0.5 19.0 66.0 <0.1 8.5 47.0 23.0 39.0 89.0 Uganda 37.0 89.0 64.0 22.0 76.0 49.0 83.0 100.0 80.0 280.0 1,000.0 1,200.0 180.0 800.0 1,000.0 770.0 1,400.0 1,400.0 Zambia 23.0 66.0 45.0 <1.0 55.0 30.0 46.0 76.0 60.0 74.0 540.0 690.0 <0.1 340.0 570.0 210.0 740.0 810.0 Zimbabwe 14.0 130.0 83.0 9.7 110.0 70.0 19.0 150.0 97.0 29.0 670.0 1,000.0 18.0 550.0 910.0 53.0 840.0 1,200.0 NORTH AFRICA Algeria <0.1 <0.2 <1.0 <0.1 <0.1 <1.0 <0.1 <0.5 1.1 .. .. .. .. .. .. .. .. .. Egypt, Arab Rep. <0.1 <0.2 <0.5 <0.1 <0.1 <0.5 <1.0 <0.5 <1.0 .. .. .. .. .. .. .. .. .. Libya .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco <0.2 <1.0 1.2 <0.1 <0.5 <1.0 0.5 <1.0 1.6 .. .. .. .. .. .. .. .. .. Tunisia <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.2 .. .. .. .. .. .. .. .. .. 108 Part III. Development outcomes HIV/AIDS HIV-positive pregnant women receiving antiretrovirals to reduce the risk of mother-to-child transmission Share of total ODA gross disbursements (WHO/UNAIDS methodology, %) ($ millions) Total Point estimate Low estimate High estimate For social mitigation of HIV/AIDS For STD control, including HIV/AIDS 2009 2009 2009 2009 2007 2009 2007 2009 76.7 91.9 2,777.2 3,776.4 3,053 19 12 36 1.8 0.5 22.8 13.9 1,703 46 29 92 0.0 0.0 9.6 17.1 12,406 >95 74 >95 2.3 1.5 43.1 211.8 2,084 32 19 60 1.0 0.3 22.7 37.6 1,837 12 9 22 0.7 1.1 12.0 30.7 9,092 27 18 50 0.0 0.2 31.8 28.5 61 .. .. .. .. .. 1.0 0.5 2,157 34 23 67 0.0 0.0 2.4 4.5 989 6 3 12 0.0 0.0 4.6 9.5 1 .. 10 33 .. .. 0.3 0.1 2,232 .. 4 11 1.2 0.3 41.2 40.1 441 12 8 23 .. 0.0 4.2 5.7 11,064 54 36 95 0.2 0.3 46.1 64.8 63 10 6 21 .. 0.0 5.4 0.7 365 26 16 50 .. .. 0.4 0.9 464 34 21 71 0.0 0.0 11.3 15.8 6,721 .. 13 40 1.4 3.7 246.5 206.7 577 30 20 60 0.0 .. 3.2 3.9 885 .. 43 95 0.0 .. 3.1 6.2 3,643 27 18 53 0.6 0.1 43.2 58.8 783 17 11 34 0.0 0.0 6.6 6.9 383 24 16 49 0.0 .. 2.4 5.9 58,591 73 50 95 4.7 5.2 223.7 377.1 8,846 64 48 95 2.7 5.3 19.2 29.6 377 16 10 33 .. 0.0 7.7 5.1 17 .. 1 5 0.0 0.0 12.1 9.7 33,156 58 40 95 3.8 3.1 149.4 150.1 1,710 .. 26 82 0.0 0.1 26.2 25.6 68 .. 12 37 0.0 .. 2.7 0.8 41 .. 33 95 .. .. 1.3 0.9 68,248 70 51 95 6.2 8.4 153.9 192.9 6,744 88 61 95 0.0 0.1 83.9 119.7 1,737 .. 25 74 0.0 0.0 6.9 13.2 44,723 22 15 42 1.0 0.0 222.1 356.2 7,030 65 43 95 1.6 0.5 101.4 135.1 11 .. .. .. .. 0.0 0.6 0.1 917 .. 16 45 .. 0.1 17.1 19.0 12 .. .. .. .. .. 0.0 0.0 637 19 12 36 0.0 0.2 6.9 13.2 .. .. 0 0 0.0 .. 7.9 1.3 188,200 88 66 95 9.9 11.4 284.2 560.1 245 2 1 3 0.2 0.1 14.4 12.0 8,182 88 68 95 0.2 0.6 20.1 27.2 58,833 70 48 95 6.1 7.1 206.5 257.1 1,451 26 15 67 0.0 0.0 11.6 17.2 46,948 53 37 95 5.4 7.2 241.3 259.0 47,175 69 50 95 1.6 3.4 145.2 223.8 28,208 56 41 95 2.4 7.2 97.5 71.2 0.0 0.0 15.8 14.7 65 .. 14 59 .. .. 1.7 1.2 11 .. 3 10 .. 0.0 1.4 4.2 .. .. .. .. .. .. 1.5 0.0 90 .. 13 49 .. .. 5.8 5.7 3 .. 6 25 0.0 .. 5.1 3.0 HIV/AIDS Part III. Development outcomes 109 Participating in growth 11.1 Table Malaria Children Children with Pregnant sleeping under fever receiving women receiving ODA Under-five insecticide- any antimalarial two doses of disbursements mortality treated nets treatment (% of intermittent for malaria Population Clinical cases of Reported deaths rate (% of children children under preventive control (millions) malaria reporteda due to malaria (per 1,000) under age 5) age 5 with fever) treatment (%) ($ millions) 2008 2009 2008 2009 2008 2009 2008 2009 2000–09 b 2000–09 b 2000–09 b 2008 2009 SUB–SAHARAN AFRICA 820.7 841.0 62,920,801 71,675,530 104,331 113,326 133 130 682.8 1,158.8 Angola 18.0 18.5 2,151,072 2,221,076 9,465 10,530 166 161 17.7 29.3 2.5 30.4 29.4 Benin 8.7 8.9 1,147,005 1,256,708 918 1,375 121 118 20.1 54.0 3.0 14.1 15.9 Botswana 1.9 1.9 17,886 14,878 12 6 59 57 .. .. .. 0.0 .. Burkina Faso 15.2 15.8 3,688,338 4,399,837 7,834 7,982 169 166 9.6 48.0 1.3 3.6 20.7 Burundi 8.1 8.3 1,424,026 1,757,387 1,511 714 168 166 8.3 30.0 .. 22.5 7.8 Cameroon 19.1 19.5 1,650,749 1,883,199 7,673 4,943 155 154 13.1 57.8 5.8 6.1 9.6 Cape Verde 0.5 0.5 35 65 2 2 29 28 .. .. .. .. .. Central African Republic 4.3 4.4 152,260 175,210 456 667 172 171 15.1 57.0 8.7 2.7 0.0 Chad 10.9 11.2 462,573 182,415 1,018 221 209 209 0.6 53.0 .. 0.8 0.3 Comoros 0.6 0.7 46,426 49,679 47 .. 105 104 9.3 62.7 .. 0.3 0.2 Congo, Dem. Rep. 64.3 66.0 3,938,597 6,749,112 17,940 21,168 199 199 5.8 29.8 5.1 36.4 89.0 Congo, Rep. 3.6 3.7 117,291 92,855 143 116 127 128 6.1 48.0 .. 0.1 0.2 Côte d’Ivoire 20.6 21.1 1,343,654 1,847,367 1,249 18,156 121 119 3.0 36.0 8.3 1.9 16.2 Djibouti 0.8 0.9 3,528 7,120 .. 0 95 94 19.9 9.5 .. 1.5 0.2 Equatorial Guinea 0.7 0.7 62,312 78,983 4 23 148 145 0.7 48.6 .. 6.3 3.4 Eritrea 4.9 5.1 10,572 21,298 19 23 58 55 4.2 3.6 .. 5.9 0.7 Ethiopia 80.7 82.8 2,532,645 3,043,203 1,169 1,121 109 104 33.1 9.5 .. 34.9 140.3 Gabon 1.4 1.5 77,278 112,840 156 197 71 69 .. .. .. 1.3 3.9 Gambia, The 1.7 1.7 508,846 479,409 403 240 106 103 49.0 62.6 32.5 5.7 6.0 Ghana 23.4 23.8 3,050,513 1,899,544 3,889 3,378 72 69 28.2 43.0 43.7 19.2 43.3 Guinea 9.8 10.1 657,003 812,471 441 586 146 142 4.5 43.5 2.9 1.2 0.0 Guinea-Bissau 1.6 1.6 128,758 143,011 487 369 195 193 39.0 45.7 7.4 1.5 1.6 Kenya 38.8 39.8 839,904 8,123,689 .. .. 86 84 46.1 23.2 15.0 39.8 73.5 Lesotho 2.0 2.1 .. .. .. .. 91 84 .. .. .. .. 0.0 Liberia 3.8 4.0 606,952 871,560 345 1,706 119 112 26.4 67.2 45.1 13.8 13.0 Madagascar 19.1 19.6 116,538 215,110 276 173 61 58 45.8 19.7 6.4 22.7 26.7 Malawi 14.8 15.3 4,580,226 5,455,423 6,748 6,527 115 110 24.7 24.9 44.5 30.7 20.4 Mali 12.7 13.0 1,045,424 1,633,423 1,227 2,331 194 191 27.1 31.7 4.0 9.6 14.7 Mauritania 3.2 3.3 199,791 167,705 .. 91 118 117 2.1 20.7 .. 1.4 – Mauritius 1.3 1.3 .. .. .. .. 17 17 .. .. .. .. .. Mozambique 22.4 22.9 4,831,491 4,310,086 4,424 3,747 147 142 22.8 36.7 43.1 31.5 26.6 Namibia 2.1 2.2 128,531 81,812 171 46 50 48 10.5 9.8 10.0 0.4 3.8 Niger 14.7 15.3 596,858 309,675 2,461 2,159 167 160 42.8 33.0 0.3 14.7 19.6 Nigeria 151.2 154.7 2,834,174 4,295,686 8,677 7,522 143 138 5.5 33.2 4.9 36.5 267.4 Rwanda 9.7 10.0 772,197 1,247,583 566 809 117 111 55.7 5.6 17.2 37.3 62.6 São Tomé and Príncipe 0.2 0.2 1,647 3,893 16 23 79 78 56.2 8.4 59.8 2.4 (0.0) Senegal 12.2 12.5 443,828 222,232 741 574 95 93 29.2 9.1 52.2 26.8 27.1 Seychelles 0.1 0.1 .. .. .. .. 13 12 .. .. .. .. .. Sierra Leone 5.6 5.7 851,478 646,808 871 1,734 198 192 25.8 30.1 10.3 7.1 5.8 Somalia 8.9 9.1 56,408 56,153 49 45 180 180 11.4 7.9 0.9 3.9 1.2 South Africa 48.8 49.3 7,796 6,072 43 45 65 62 .. .. .. .. 0.0 Sudan 41.3 42.3 3,145,944 2,686,822 1,388 1,396 109 108 27.6 54.2 .. 44.1 13.3 Swaziland 1.2 1.2 5,881 6,639 10 13 77 73 0.6 0.6 0.5 0.3 2.6 Tanzania 42.5 43.7 3,812,350 40 12,434 840 111 108 25.7 56.7 30.2 89.8 99.1 Togo 6.5 6.6 602,908 618,842 2,663 1,556 100 98 38.4 47.7 18.1 5.0 0.3 Uganda 31.7 32.7 10,184,961 9,775,318 2,372 6,296 130 128 9.7 61.3 16.2 25.2 54.4 Zambia 12.6 12.9 3,080,301 2,976,395 3,781 3,862 145 141 41.1 43.3 60.3 25.4 24.8 Zimbabwe 12.5 12.5 1,003,846 736,897 232 14 93 90 17.3 23.6 6.3 0.1 1.8 NORTH AFRICA 164.1 166.7 12,186 239 3 3 28 26 .. .. .. .. .. Algeria 34.4 34.9 11,964 .. .. .. 34 32 .. .. .. .. .. Egypt, Arab Rep. 81.5 83.0 80 94 2 2 23 21 .. .. .. .. .. Libya 6.3 6.4 .. .. .. .. 19 19 .. .. .. .. .. Morocco 31.6 32.0 142 145 1 1 39 38 .. .. .. .. .. Tunisia 10.3 10.4 .. .. .. .. 21 21 .. .. .. .. .. a. Malaria cases reported before 2000 can be probable and con�rmed or only con�rmed, depending on the country. b. Data are for the most recent year available during the period speci�ed. 110 Part III. Development outcomes Malaria Capable states and partnership 12.1 Table Aid and debt relief Net official development assistance ($ millions) From all donors From DAC donors From non-DAC donors From multilateral donors From other donors 2008 2009 2008 2009 2008 2009 2008 2009 2008 2009 SUB–SAHARAN AFRICA 40,484.5 44,704.2 21,336.6 22,660.0 322.7 201.5 14,295.0 16,248.1 41.1 32.1 Angola 368.8 239.5 209.9 131.5 8.3 9.7 150.6 98.4 0.0 0.0 Benin 641.4 682.9 305.0 325.7 4.3 3.4 332.0 353.8 0.1 0.1 Botswana 720.3 279.6 682.7 223.4 –1.5 –0.4 39.0 56.6 0.0 0.1 Burkina Faso 1,001.0 1,083.9 475.3 452.9 7.2 1.7 518.6 629.3 0.1 0.2 Burundi 508.5 548.8 255.1 260.9 0.2 0.2 253.2 287.8 0.1 0.1 Cameroon 548.8 649.4 298.4 267.7 9.9 1.0 240.5 380.7 0.3 0.3 Cape Verde 221.8 195.9 162.7 161.9 0.4 –0.4 58.6 34.5 .. 0.0 Central African Republic 256.4 236.9 128.5 98.6 0.2 0.5 127.7 137.7 .. .. Chad 418.7 561.2 277.5 355.5 0.4 –0.1 140.9 205.8 0.1 0.2 Comoros 37.3 50.6 20.8 28.1 1.2 0.9 15.2 21.6 .. .. Congo, Dem. Rep. 1,768.5 2,353.6 985.5 1,099.3 5.4 2.7 777.6 1,251.6 0.3 0.0 Congo, Rep. 485.1 283.0 382.6 226.1 0.2 0.4 102.3 56.4 0.0 0.1 Côte d’Ivoire 623.3 2,366.3 200.2 1,722.6 2.5 2.3 420.5 641.4 0.8 0.4 Djibouti 120.9 162.2 66.1 97.7 9.6 10.8 45.1 53.7 .. .. Equatorial Guinea 32.1 31.6 18.5 25.1 0.1 0.0 13.5 6.5 0.0 .. Eritrea 143.6 144.8 52.5 43.4 6.8 14.8 84.3 86.6 6.7 13.3 Ethiopia 3,327.8 3,820.0 1,843.4 1,816.6 31.0 19.6 1,453.4 1,983.9 20.2 8.0 Gabon 62.1 77.6 37.6 52.5 0.7 0.0 23.8 25.0 0.0 .. Gambia, The 93.8 128.0 27.9 21.9 4.4 1.1 61.6 105.1 0.1 0.1 Ghana 1,305.0 1,582.6 725.7 820.3 3.7 6.2 575.6 756.1 0.2 0.6 Guinea 327.6 214.7 209.9 171.0 0.5 –3.9 117.1 47.5 0.1 0.2 Guinea-Bissau 131.6 145.5 52.9 50.6 0.4 1.0 78.3 93.9 0.0 .. Kenya 1,362.7 1,778.0 953.2 1,224.0 1.9 5.4 407.5 548.6 0.8 0.7 Lesotho 143.8 123.0 66.0 70.7 –0.3 4.7 78.1 47.7 0.4 0.7 Liberia 1,249.5 505.0 819.2 340.8 27.0 1.0 403.3 163.3 0.4 0.1 Madagascar 842.9 445.5 274.5 241.6 3.9 1.5 564.6 202.4 0.3 0.3 Malawi 923.7 772.4 432.0 435.2 9.3 3.8 482.4 333.4 0.1 0.1 Mali 964.1 985.1 531.4 574.7 0.1 1.6 432.7 408.9 0.4 0.4 Mauritania 319.7 286.7 139.1 122.2 24.2 20.7 156.4 143.8 0.2 .. Mauritius 109.7 155.6 16.1 63.6 –1.9 –1.9 95.5 93.8 0.0 0.0 Mozambique 1,996.1 2,013.3 1,341.3 1,287.7 3.0 1.7 651.9 723.9 0.0 .. Namibia 210.2 326.2 150.0 246.5 2.4 1.3 57.8 78.4 0.1 0.0 Niger 606.7 470.0 269.1 255.3 1.7 2.0 336.0 212.7 0.1 0.1 Nigeria 1,290.2 1,659.1 637.2 687.5 2.0 2.2 651.0 969.4 0.9 1.2 Rwanda 933.2 934.4 451.6 519.8 1.7 2.8 479.9 411.8 0.2 0.0 São Tomé and Príncipe 47.3 30.7 26.4 19.7 0.1 0.0 20.8 11.0 .. .. Senegal 1,064.2 1,017.6 554.4 514.4 38.2 4.6 471.6 498.7 0.4 0.3 Seychelles 12.5 23.2 5.0 11.8 0.2 0.1 7.3 11.4 0.1 0.1 Sierra Leone 366.8 437.3 174.9 196.3 –0.9 0.4 192.9 240.5 0.1 0.1 Somalia 758.3 661.7 565.6 499.5 8.0 9.6 184.7 152.5 0.2 0.1 South Africa 1,124.9 1,075.0 881.7 861.3 1.6 2.6 241.6 211.1 1.3 1.5 Sudan 2,383.6 2,288.9 1,820.9 1,911.0 103.8 60.7 459.0 317.2 5.8 2.4 Swaziland 69.9 58.0 17.8 18.5 –0.7 –0.7 52.8 40.1 0.0 0.0 Tanzania 2,330.7 2,934.2 1,372.9 1,408.8 –2.3 –1.4 960.1 1,526.8 0.1 0.1 Togo 329.6 499.0 176.0 361.8 –0.6 1.0 154.2 136.2 0.1 0.1 Uganda 1,641.3 1,785.9 1,005.7 1,013.3 4.0 3.8 631.5 768.8 0.3 0.2 Zambia 1,116.2 1,268.7 703.9 700.6 0.4 2.1 412.0 566.0 0.0 0.0 Zimbabwe 612.4 736.8 532.4 620.4 0.1 0.4 80.0 115.9 0.0 0.1 NORTH AFRICA 3,375.9 2,870.5 2,129.1 1,866.5 151.8 31.0 837.1 771.4 1.3 0.7 Algeria 319.4 319.2 244.7 200.1 –26.7 11.8 101.4 107.3 0.1 0.0 Egypt, Arab Rep. 1,344.3 925.1 967.3 580.0 107.0 122.3 270.0 222.8 0.9 0.4 Libya 60.2 39.2 52.2 32.2 1.9 0.9 6.1 6.0 0.1 0.0 Morocco 1,062.6 911.6 614.4 704.7 78.4 –98.2 369.8 305.1 0.2 0.2 Tunisia 331.6 473.9 250.6 349.5 –8.8 –5.8 89.8 130.2 0.0 0.1 (continued) Capable states and partnership Part III. Development outcomes 111 Capable states and partnership 12.1 Table Aid and debt relief (continued) Net private official development assistance ($ millions) Net official development assistance Share of gross capital From all donors From DAC donors From non-DAC donors Share of GDP (%) Per capita ($) formation (%) 2008 2009 2008 2009 2008 2009 2008 2009 2008 2009 2008 2009 SUB–SAHARAN AFRICA 5,263.1 6,626.6 5,237.8 6,614.5 25.3 12.1 4.0 4.7 49.3 53.2 20.7 24.4 Angola 3,049.8 2,461.3 3,049.8 2,461.3 .. .. 0.4 0.3 20.5 12.9 2.7 2.1 Benin 3.8 –34.7 3.8 –34.7 .. .. 9.6 10.3 74.0 76.4 46.4 41.1 Botswana –92.1 2.0 –92.1 2.0 .. .. 5.3 2.4 374.9 143.4 16.4 9.8 Burkina Faso 16.5 2.1 16.5 2.1 .. .. 12.4 13.3 65.7 68.8 .. .. Burundi –37.8 –26.9 –37.8 –26.9 .. .. 43.5 41.4 63.0 66.1 .. .. Cameroon 93.3 45.7 93.3 45.7 .. .. 2.3 2.9 28.8 33.3 .. .. Cape Verde 44.5 49.0 44.5 49.0 .. .. 14.5 12.6 444.7 387.5 29.9 23.5 Central African Republic –22.3 5.9 –22.5 5.9 0.2 .. 12.9 11.8 59.1 53.6 111.2 111.2 Chad 43.5 20.2 43.5 20.2 .. .. 5.0 8.2 38.4 50.1 20.2 24.2 Comoros 1.4 0.3 1.4 0.3 .. .. 7.0 9.5 57.9 76.8 49.2 76.3 Congo, Dem. Rep. –1.9 –27.4 –1.9 –27.4 .. .. 15.3 22.3 27.5 35.6 64.0 74.6 Congo, Rep. 123.8 166.5 123.8 166.5 .. .. 4.1 3.0 134.2 76.8 18.6 12.0 Côte d’Ivoire 36.6 –1,886.0 36.6 –1,886.0 .. .. 2.7 10.2 30.3 112.3 26.2 90.4 Djibouti 32.6 50.4 32.6 50.4 .. .. 12.3 15.5 142.3 187.7 .. .. Equatorial Guinea –1,016.0 448.2 –1,016.0 448.2 .. .. 0.2 0.3 48.7 46.7 0.6 0.7 Eritrea –5.8 4.5 –5.8 4.5 .. .. 8.7 7.7 29.1 28.5 .. .. Ethiopia –137.8 240.3 –142.9 239.4 5.0 0.9 12.8 13.4 41.2 46.1 64.7 59.7 Gabon –241.6 –294.4 –241.6 –294.4 .. .. 0.4 0.7 42.8 52.6 1.8 2.5 Gambia, The 1.3 10.9 1.3 10.9 .. .. 11.4 17.5 56.5 75.1 46.2 67.3 Ghana 209.4 253.8 209.1 253.8 0.3 0.0 4.6 6.0 55.9 66.4 21.3 30.9 Guinea –59.0 0.6 –59.0 0.6 .. .. 8.7 5.2 33.3 21.3 55.7 24.2 Guinea-Bissau –15.1 –9.1 –15.1 –9.1 .. .. 15.5 17.4 83.5 90.3 .. .. Kenya –25.7 444.1 –25.7 444.1 .. .. 4.5 6.1 35.2 44.7 22.3 29.0 Lesotho –4.5 –2.8 –4.5 –2.8 .. .. 9.0 7.8 70.2 59.5 31.4 24.8 Liberia 559.9 1,132.7 559.9 1,132.7 .. .. 148.3 57.6 329.4 127.7 741.5 .. Madagascar 205.9 270.4 205.9 270.4 .. .. 8.9 5.2 44.1 22.7 22.2 15.9 Malawi –4.7 31.4 –4.7 31.4 .. .. 22.7 16.3 62.2 50.6 86.3 65.6 Mali –25.3 –26.5 –25.3 –26.7 .. 0.2 11.1 11.0 75.9 75.7 .. .. Mauritania –8.7 23.8 –8.7 23.8 .. .. 8.9 9.5 99.4 87.1 32.1 37.7 Mauritius 818.6 1,526.6 803.0 1,526.6 15.6 .. 1.2 1.8 86.4 122.0 4.3 8.5 Mozambique –52.5 58.2 –52.5 58.2 .. .. 20.2 20.6 89.2 87.9 128.9 98.2 Namibia 317.3 289.8 317.3 289.8 .. .. 2.3 3.5 98.7 150.2 8.3 13.0 Niger –30.2 16.7 –30.2 16.7 .. 0.1 11.3 8.7 41.3 30.7 .. .. Nigeria 1,713.2 1,209.8 1,713.2 1,209.8 .. .. 0.6 1.0 8.5 10.7 .. .. Rwanda 10.3 81.1 10.3 81.1 0.0 .. 19.9 17.9 96.0 93.5 87.2 82.3 São Tomé and Príncipe –4.9 3.1 –4.9 3.1 .. .. 27.3 16.1 295.5 188.7 .. .. Senegal 163.3 274.1 162.6 273.9 0.7 0.2 8.1 7.9 87.2 81.2 26.7 28.4 Seychelles 33.6 48.3 33.6 48.3 .. 0.0 1.4 3.0 144.0 263.7 5.3 12.5 Sierra Leone 1.8 11.6 1.8 11.6 .. .. 18.8 22.5 66.0 76.8 127.5 148.8 Somalia 3.7 6.1 3.7 6.1 .. .. .. .. 84.9 72.4 .. .. South Africa 5,504.6 –377.1 5,504.3 –377.3 0.3 0.2 0.4 0.4 23.1 21.8 1.9 1.9 Sudan –13.5 16.3 –16.8 5.7 3.3 10.6 4.1 4.2 57.6 54.1 15.8 16.6 Swaziland 1.9 –3.8 1.9 –3.8 .. .. 2.5 1.9 59.8 48.9 16.1 11.4 Tanzania 122.2 189.8 122.2 189.8 .. .. 11.3 13.7 54.9 67.1 42.1 46.1 Togo 31.6 –86.5 31.6 –86.5 .. .. 11.4 17.5 51.0 75.4 .. .. Uganda 111.7 64.0 111.7 64.0 .. .. 11.4 11.1 51.8 54.6 49.5 46.8 Zambia 380.2 –30.1 380.2 –30.1 .. .. 7.8 9.9 88.4 98.1 34.4 44.7 Zimbabwe 16.0 –96.5 16.0 –96.5 .. .. 14.4 13.1 49.1 58.8 252.5 581.9 NORTH AFRICA 20,880.4 9,244.6 20,693.6 9,167.0 186.8 77.6 0.6 0.5 20.6 17.2 2.1 1.8 Algeria 295.8 2,728.9 294.5 2,727.0 1.3 1.9 0.2 0.2 9.3 9.1 0.6 0.6 Egypt, Arab Rep. 15,267.8 4,392.2 15,252.5 4,357.5 15.3 34.7 0.8 0.5 16.5 11.1 3.7 2.5 Libya 1,914.2 1,073.7 1,910.0 1,035.6 4.2 38.1 0.1 0.1 9.6 6.1 0.2 .. Morocco 1,588.6 811.7 1,583.8 809.9 4.8 1.8 1.2 1.0 33.6 28.5 3.1 2.8 Tunisia 1,396.7 58.5 1,235.4 57.3 161.3 1.2 0.8 1.2 32.1 45.4 3.0 4.5 a. As of 2010. 112 Part III. Development outcomes Capable states and partnership Net official development assistance Food aid shipments (thousands of tons) Heavily Indebted Poor Countries (HIPC) Debt Initiative Share of central In nominal terms Share of imports of government goods and services (%) expenditures (%) Cereal Noncereal Debt service Assistance Total HIPC relief delivered and MDRI Decision Completion committed under MDRI assistance 2007 2008 2007 2008 2008 2009 2008 2009 pointa pointa ($ millions)a ($ millions)a ($ millions)a 8.8 12.0 .. .. 3,284.1 2,631.6 3,460.2 3,066.9 0.6 0.5 .. .. 24.3 9.4 0.0 0.0 .. .. .. .. .. 26.1 .. 64.3 68.2 12.5 5.2 9.7 16.7 Jul. 2000 Mar. 2003 460 1,130 1,590 10.7 4.7 .. .. 0.0 0.0 0.0 0.0 .. .. .. .. .. 34.0 .. 98.5 102.5 34.6 34.4 39.3 21.8 Jul. 2000 Apr. 2002 930 1,207 2,137 83.4 102.0 .. .. 57.8 50.9 24.3 47.7 Aug. 2005 Jan. 2009 1,366 93 1,459 6.5 9.4 .. .. 8.5 4.7 12.7 8.7 Oct. 2000 Apr. 2006 4,917 1,285 6,202 17.5 17.6 54.0 44.9 27.5 4.6 11.4 17.5 .. .. .. .. .. .. .. .. .. 7.5 20.4 13.1 17.4 Sep. 2007 Jun. 2009 804 280 1,084 .. .. .. .. 50.5 56.2 69.9 100.2 May 2001 .. 260 .. 260 .. .. .. .. 0.2 0.0 0.0 7.5 Jun. 2010 .. 136 .. 136 .. .. .. .. 90.6 78.2 86.3 141.4 Jul. 2003 Jul. 2010 15,222 1,035 16,257 .. .. .. .. 4.4 7.3 2.7 3.7 Mar. 2006 Jan. 2010 1,738 203 1,941 5.7 23.9 14.9 57.6 17.3 21.9 12.0 21.4 Mar. 2009 .. 3,415 .. 3,415 16.9 27.3 .. .. 8.8 7.1 7.6 21.0 .. .. .. .. .. .. .. .. .. 0.0 0.0 0.0 0.0 .. .. .. .. .. .. .. .. .. 32.0 14.8 17.2 0.0 .. .. .. .. .. 34.5 42.0 .. .. 679.7 571.2 979.1 904.1 Nov. 2001 Apr. 2004 3,275 3,277 6,552 .. .. .. .. 0.0 0.0 0.0 0.0 .. .. .. .. .. 23.5 35.3 .. .. 11.4 7.2 2.5 10.4 Dec. 2000 Dec. 2007 112 370 482 10.1 14.1 22.3 33.8 47.8 36.3 38.9 29.1 Feb. 2002 Jul. 2004 3,500 3,862 7,362 7.5 13.6 .. .. 22.3 14.7 30.0 11.3 Dec. 2000 .. 800 .. 800 44.0 .. .. .. 5.7 8.8 6.1 2.1 Dec. 2000 .. 790 .. 790 10.7 15.4 20.9 27.9 307.8 220.0 213.8 216.7 .. .. .. .. .. 8.0 6.7 17.3 .. 18.7 32.0 15.2 6.2 .. .. .. .. .. 54.1 27.3 43884.0 .. 53.8 33.9 35.0 22.3 Mar. 2008 Jun. 2010 4,600 265 4,865 .. .. 76.2 .. 41.5 43.1 28.5 20.7 Dec. 2000 Oct. 2004 1,900 2,385 4,285 .. .. .. .. 179.4 82.0 57.2 70.7 Dec. 2000 Aug. 2006 1,628 1,570 3,198 23.1 .. 82.1 74.9 35.2 43.6 19.1 23.0 Sep. 2000 Mar. 2003 895 1,977 2,872 .. .. .. .. 38.2 39.6 50.0 25.2 Feb. 2000 Jun. 2002 1,100 875 1,975 1.6 2.8 .. 8.4 0.0 0.0 0.0 0.0 .. .. .. .. .. 36.9 44.1 .. .. 133.7 80.1 135.4 157.4 Apr. 2000 Sep. 2001 4,300 2,029 6,329 4.3 5.9 .. .. 5.8 9.3 4.2 0.3 .. .. .. .. .. 30.2 .. .. .. 74.1 74.8 55.8 40.2 Dec. 2000 Apr. 2004 1,190 1,057 2,247 1.6 2.8 8.6 .. 0.0 0.0 0.0 0.0 .. .. .. .. .. 63.8 61.0 .. .. 31.6 16.9 16.1 22.4 Dec. 2000 Apr. 2005 1,316 510 1,826 40.9 29.3 .. .. 1.0 1.5 6.8 6.0 Dec. 2000 Mar. 2007 263 65 328 14.6 .. .. .. 10.6 20.4 24.9 11.3 Jun. 2000 Apr. 2004 850 2,460 3,310 0.9 2.0 4.5 9.3 0.0 0.0 3.5 0.0 .. .. .. .. .. 53.2 64.8 92.3 101.9 27.2 25.9 25.9 15.1 Mar. 2002 Dec. 2006 994 661 1,655 .. .. .. .. 180.1 92.9 317.9 281.8 .. .. .. .. .. 0.9 1.2 1.3 1.1 0.0 0.0 0.0 0.0 .. .. .. .. .. 17.1 16.8 .. .. 498.7 405.6 520.9 427.8 .. .. .. .. .. 2.8 2.1 .. .. 12.8 13.4 16.2 2.4 .. .. .. .. .. 25.9 37.2 .. .. 77.4 65.6 75.3 24.7 Apr. 2000 Nov. 2001 3,000 3,806 6,806 18.7 .. 75.3 100.6 0.6 1.8 5.0 25.0 Nov. 2008 .. 360 .. 360 28.9 32.0 75.1 86.9 208.0 223.7 158.2 96.0 Feb. 2000 May 2000 1,950 3,483 5,433 16.2 23.1 .. .. 89.1 32.7 24.5 11.8 Dec. 2000 Apr. 2005 3,900 2,742 6,642 .. .. .. .. 115.6 119.6 287.6 178.1 .. .. .. .. .. 1.5 1.6 7.0 .. 43.2 19.0 25.6 12.2 .. .. 0.8 0.9 16.5 17.1 21.4 11.5 .. .. .. .. .. 1.9 1.6 2.7 1.6 26.7 1.9 4.3 0.7 .. .. .. .. .. 0.2 0.1 .. .. .. .. .. .. .. .. .. .. .. 2.2 2.3 3.9 3.6 0.0 0.0 0.0 0.0 .. .. .. .. .. 1.1 2.0 2.7 4.0 0.0 0.0 0.0 0.0 .. .. .. .. .. Capable states and partnership Part III. Development outcomes 113 Capable states and partnership 12.2 Table Status of Paris Declaration indicators PDI-1 PDI-2 PDI-3 PDI-4 PDI-5 Reliable Technical Aid for government Aid for government country Government assistance aligned sectors uses country sectors uses Operational national Reliable public procure- budget estimates and coordinated public financial of country development financial ment comprehensive with country management procurement strategiesa managementb systemsc and realistic (%) programs (%) systems (%) systems (%) 2005 2007 2005 2007 2007 2005 2007 2005 2007 2005 2007 2005 2007 SUB–SAHARAN AFRICA Angolad .. .. .. .. .. .. .. .. .. .. .. .. .. Benin C C 4.0 3.5 .. 46.7 28.5 56.3 53.9 51.8 47.5 64.1 63.3 Botswanad .. .. .. .. .. .. .. .. .. .. .. .. .. Burkina Faso C B 4.0 4.0 .. 67.5 92.2 3.4 56.4 44.5 43.2 60.4 53.8 Burundi D C 2.5 3.0 .. 39.3 53.9 42.6 41.0 24.5 32.7 19.4 34.6 Cameroon C C 3.5 3.5 B .. 85.7 .. 29.9 .. 53.1 .. 63.1 Cape Verde C C 3.5 4.0 .. 85.1 90.2 92.7 39.3 64.1 22.5 53.5 22.1 Central African Republic D D 2.0 2.0 .. .. 36.4 .. 36.5 .. 23.8 .. 10.2 Chad C C 3.0 9.0 .. .. 87.9 .. 64.4 .. 1.0 .. 10.6 Comorosd .. .. .. .. .. .. .. .. .. .. .. .. .. Congo, Dem. Rep. D D 2.5 2.5 .. 81.0 58.3 10.7 38.1 12.9 0.0 30.8 0.8 Congo, Rep. .. .. .. .. .. .. .. .. .. .. .. .. .. Côte d’Ivoire D E 2.5 2.0 .. .. 64.4 .. 30.9 .. 0.0 .. 9.3 Djiboutid .. .. .. .. .. .. .. .. .. .. .. .. .. Equatorial Guinead .. .. .. .. .. .. .. .. .. .. .. .. .. Eritread .. .. .. .. .. .. .. .. .. .. .. .. .. Ethiopia C B 3.5 4.0 .. 74.4 61.7 27.3 66.8 45.2 46.7 42.8 41.4 Gabon .. .. 9.0 9.0 .. .. 22.4 .. 70.4 .. 4.7 .. 32.3 Gambia, Thed .. .. .. .. .. .. .. .. .. .. .. .. .. Ghana C B 3.5 4.0 C 96.1 94.5 40.4 73.8 62.1 50.8 51.9 56.1 Guinead .. .. .. .. .. .. .. .. .. .. .. .. .. Guinea-Bissaud .. .. .. .. .. .. .. .. .. .. .. .. .. Kenya D C 3.5 3.5 .. 90.9 64.2 60.2 63.8 47.3 53.6 44.7 36.8 Lesothod .. .. .. .. .. .. .. .. .. .. .. .. .. Liberia D D 9.0 9.0 .. .. 0.0 .. 35.3 .. 32.0 .. 0.0 Madagascar C C 3.0 3.5 .. .. 87.0 .. 70.9 .. 21.5 .. 25.9 Malawi C C 3.0 3.0 C 53.6 63.7 46.6 52.3 54.7 49.9 35.0 35.4 Mali C C 4.0 3.5 .. 60.0 72.6 15.1 75.4 29.5 34.4 44.6 34.8 Mauritania B C 2.0 2.5 .. 65.4 57.4 19.5 53.4 4.4 8.3 19.7 22.2 Mauritiusd .. .. .. .. .. .. .. .. .. .. .. .. .. Mozambique C C 3.5 3.5 .. 83.3 82.5 38.1 26.9 35.8 43.5 38.0 53.8 Namibiad .. .. .. .. .. .. .. .. .. .. .. .. .. Niger C C 3.5 3.5 B 99.5 90.7 15.3 50.2 27.1 25.5 48.7 36.5 Nigeria .. C 3.0 3.0 .. .. 6.3 .. 70.6 .. 0.0 .. 0.0 Rwanda B B 3.5 4.0 B 49.0 51.0 57.8 83.6 39.2 42.0 46.0 42.9 São Tomé and Prínciped .. .. .. .. .. .. .. .. .. .. .. .. .. Senegal C C 3.5 3.5 B 88.9 87.7 18.1 54.1 22.7 19.0 28.9 41.3 Seychellesd .. .. .. .. .. .. .. .. .. .. .. .. .. Sierra Leone D C 3.5 3.5 B .. 53.6 .. 22.5 .. 20.1 .. 38.3 Somaliad .. .. .. .. .. .. .. .. .. .. .. .. .. South Africa .. .. .. .. .. 70.8 .. 95.1 .. 38.1 .. 43.7 .. Sudan D D 2.5 2.0 .. .. 84.6 .. 53.2 .. 3.1 .. 0.4 Swazilandd .. .. .. .. .. .. .. .. .. .. .. .. .. Tanzania B B 4.5 4.0 B 89.5 83.6 49.5 60.5 65.9 71.5 61.2 68.5 Togo .. .. 2.0 2.0 .. .. 68.9 .. 28.9 .. 4.4 .. 15.5 Uganda B B 4.0 4.0 B 79.1 98.4 41.6 58.1 60.2 57.0 54.2 36.9 Zambia C B 3.0 3.5 C 51.9 73.5 32.4 34.5 34.1 59.4 43.5 71.0 Zimbabwed .. .. .. .. .. .. .. .. .. .. .. .. .. NORTH AFRICA Algeriad .. .. .. .. .. .. .. .. .. .. .. .. .. Egypt, Arab Rep. .. .. 9.0 9.0 .. 58.2 57.4 76.3 86.2 28.2 12.0 24.9 22.7 Libya .. .. .. .. .. .. .. .. .. .. .. .. .. Morocco .. .. 9.0 9.0 .. .. 79.8 .. 82.2 .. 78.9 .. 81.1 Tunisiad .. .. .. .. .. .. .. .. .. .. .. .. .. Note: See Technical notes for further details. PDI is Paris Declaration Indicator. Status will be updated in the fourth quarter of 2011. a. Ratings range from A to E, where A means the development strategy substantially achieves good practices; B means it is largely developed toward achieving good practices; C means it reflects action taken toward achieving good practices; D means it incorporates some elements of good practice; and E means it reflects little action toward achieving good practices. b. Ratings range from 1 (low) to 6 (high). c. Ratings range from A (high) to D (low). Indicator was not collected in 2005. d. Did not take part in the Survey on Monitoring the Paris Declaration. 114 Part III. Development outcomes Capable states and partnership PDI-6 PDI-7 PDI-8 PDI-9 PDI-10 PDI-11 PDI-12 Project Existence of implementation Aid disbursements Aid provided in a monitorable Existence units parallel to on schedule the framework of performance of a mutual country structures and recorded by Bilateral aid that program-based Donor missions Country analysis assessment accountability (number) government (%) is untied (%) approaches (%) coordinated (%) coordinated (%) frameworka reviewa 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 2005 2007 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 29.0 58.0 53.0 31.6 79.3 98.8 60.8 49.0 14.5 25.1 37.5 44.0 C C B B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 131.0 102.0 91.7 91.6 92.4 91.8 45.3 57.2 16.8 12.8 45.2 39.0 C C B B 37.0 29.0 52.5 44.4 59.8 90.6 53.6 35.5 24.3 13.5 55.0 73.8 D D B A .. 38.0 .. 50.8 .. 98.5 .. 39.6 .. 25.8 .. 49.2 D D .. B 10.0 18.0 92.2 96.4 22.3 60.3 36.7 30.9 10.5 43.4 34.1 64.5 D C A B .. 11.0 .. 45.2 .. 86.7 .. 34.3 .. 9.8 .. 23.2 D D .. B .. 17.0 .. 0.0 .. 81.2 .. 1.5 .. 18.1 .. 35.0 D D .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 34.0 146.0 82.9 19.5 88.1 93.9 53.8 20.8 38.4 21.3 35.2 22.9 D D B B .. .. .. .. .. .. .. .. .. .. .. .. D D .. .. .. 29.0 .. 67.0 .. 91.7 .. 2.6 .. 65.0 .. 75.0 D E .. B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 103.0 56.0 95.9 73.4 38.8 82.2 52.6 65.6 26.7 29.4 49.5 69.5 C C A A .. 5.0 .. 16.8 .. 99.7 .. 0.0 .. 4.7 .. 36.8 .. .. .. B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 45.0 16.0 91.6 82.3 89.9 91.8 52.7 68.8 19.7 39.0 39.9 59.8 C C A A .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 17.0 21.0 44.0 46.5 78.3 84.5 44.6 30.5 9.2 48.4 32.3 78.0 C C B B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 16.0 .. 0.0 .. 82.4 .. 21.3 .. 11.0 .. 65.6 D D .. B .. 48.0 .. 79.5 .. 83.9 .. 43.5 .. 23.8 .. 41.6 C C .. B 69.0 51.0 57.7 58.1 96.9 90.5 31.8 42.0 23.8 22.3 60.0 60.8 C C A A 65.0 60.0 70.7 68.2 95.0 93.4 48.1 40.6 7.4 15.2 30.0 39.3 D D B B 23.0 27.0 39.4 52.1 72.9 67.0 36.7 35.1 13.8 11.4 58.9 25.4 C C B B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 40.0 26.0 70.1 73.7 89.0 90.8 46.3 46.4 46.5 16.8 63.2 31.7 C B A A .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 52.0 47.0 73.2 77.5 83.8 84.3 31.2 49.0 20.9 15.4 39.9 31.8 D D B B .. 23.0 .. 7.1 .. 99.2 .. 3.9 .. 19.1 .. 32.8 .. C .. B 48.0 41.0 65.6 66.8 81.6 95.1 41.5 38.4 8.5 20.8 36.4 42.0 C C B B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 23.0 55.0 69.3 60.8 90.8 93.0 57.3 38.9 15.1 16.6 40.5 28.1 C C B B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.0 .. 29.7 .. 91.6 .. 26.9 .. 27.1 .. 56.3 D D .. B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 15.0 .. 44.2 .. 97.2 97.4 26.5 .. 18.8 .. 75.0 .. .. .. A .. .. 105.0 .. 51.6 .. 79.9 .. 19.2 .. 14.9 .. 44.7 D D .. B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 56.0 28.0 70.2 60.8 94.6 98.9 55.5 60.8 17.3 15.8 38.3 64.9 B B A A .. 13.0 .. 14.3 .. 56.1 .. 38.9 .. 15.1 .. 20.7 .. .. .. B 54.0 55.0 84.0 74.4 81.0 85.4 49.9 65.7 17.2 21.0 40.1 54.0 B B B B 24.0 34.0 50.1 85.1 99.1 99.6 47.1 46.8 14.7 15.9 45.8 46.4 D C A B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 100.0 32.0 29.2 78.9 46.7 75.0 61.2 48.9 18.1 21.6 40.0 56.1 .. .. A B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 47.0 .. 68.3 .. 90.1 .. 70.3 .. 11.7 .. 25.0 .. .. .. B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Capable states and partnership Part III. Development outcomes 115 Capable states and partnership 12.3 Table Capable states Investment climate Firms that believe Viewed by firms as major or very the court system is severe constraints (% of firms) Enforcing contracts fair, impartial, and Crime, theft, Number of Time required Cost uncorrupt (%) Corruption and disorder procedures (days) (% of claim) 2009–10 b 2009–10 b 2009–10 b 2010 2010 2010 SUB–SAHARAN AFRICA 39 652 49.7 Angola 23.7 75.6 28.1 46 1,011 44.4 Benin 9.6 67.8 52.7 42 825 64.7 Botswana 79.5 27.4 22.6 29 625 28.1 Burkina Faso 38.7 70.5 42.2 37 446 81.7 Burundi .. .. .. 44 832 38.6 Cameroon 32.6 61.3 41.5 43 800 46.6 Cape Verde 59.5 29.8 62.3 37 425 21.8 Central African Republic .. .. .. 43 660 82.0 Chad 31.0 67.2 45.8 41 743 45.7 Comoros .. .. .. 43 506 89.4 Congo, Dem. Rep. 17.2 72.7 63.3 43 625 151.8 Congo, Rep. 32.3 65.0 44.1 44 560 53.2 Côte d’Ivoire 35.3 75.0 53.8 33 770 41.7 Djibouti .. .. .. 40 1,225 34.0 Equatorial Guinea .. .. .. 40 553 18.5 Eritrea 100.0 0.0 0.0 39 405 22.6 Ethiopia .. .. .. 37 620 15.2 Gabon 41.3 41.4 34.1 38 1,070 34.3 Gambia, The .. .. .. 32 434 37.9 Ghana .. .. .. 36 487 23.0 Guinea .. .. .. 50 276 45.0 Guinea-Bissau .. .. .. 40 1,140 25.0 Kenya .. .. .. 40 465 47.2 Lesotho 33.2 46.7 33.5 41 785 19.5 Liberia 44.3 31.2 26.8 41 1,280 35.0 Madagascar 28.8 42.7 48.1 38 871 42.4 Malawi 74.3 12.8 22.8 42 312 94.1 Mali 42.7 24.8 17.3 36 620 52.0 Mauritania .. .. .. 46 370 23.2 Mauritius 63.6 50.7 41.5 36 645 17.4 Mozambique .. .. .. 30 730 142.5 Namibia .. .. .. 33 270 35.8 Niger 49.6 83.7 44.2 39 545 59.6 Nigeria .. .. .. 40 457 32.0 Rwanda .. .. .. 24 230 78.7 São Tomé and Príncipe .. .. .. 43 1,185 50.5 Senegal .. .. .. 44 780 26.5 Seychelles .. .. .. 37 720 15.4 Sierra Leone 29.7 36.9 14.2 40 515 149.5 Somalia .. .. .. .. .. .. South Africa .. .. .. 30 600 33.2 Sudan .. .. .. 53 810 19.8 Swaziland .. .. .. 40 972 56.1 Tanzania .. .. .. 38 462 14.3 Togo 14.1 70.2 22.6 41 588 47.5 Uganda .. .. .. 38 490 44.9 Zambia .. .. .. 35 471 38.7 Zimbabwe .. .. .. 38 410 113.1 NORTH AFRICA 42 705 23.8 Algeria .. .. .. 46 630 21.9 Egypt, Arab Rep. .. .. .. 41 1,010 26.2 Libya .. .. .. .. .. .. Morocco .. .. .. 40 615 25.2 Tunisia .. .. .. 39 565 21.8 a. Average of the disclosure, director liability, and shareholder suits indexes. b. Data are for the most recent year available during the period speci�ed. 116 Part III. Development outcomes Capable states and partnership Regulation and tax administration Protecting investors Time required (0 least desirable to 10 most desirable) to prepare, file, Extractive Industries Disclosure Director liability Shareholder Investor protection Number of tax and pay taxes Total tax rate Transparency index index suits index indexa payments (hours) (% of profit) Initiative status 2010 2010 2010 2010 2010 2010 2010 2010 5 3 5 4.4 37 310 67.4 5 6 6 5.7 31 282 53.2 6 1 3 3.3 55 270 66.0 7 8 3 6.0 19 152 19.5 6 1 4 3.7 46 270 44.9 Candidate 4 1 5 3.3 32 211 153.4 6 1 6 4.3 44 654 49.1 Candidate 1 5 6 4.0 43 186 37.1 6 1 5 4.0 54 504 203.8 6 1 3 3.3 54 732 65.4 Candidate 6 1 5 4.0 20 100 217.9 3 3 4 3.3 32 336 339.7 Candidate 6 1 3 3.3 61 606 65.5 Candidate 6 1 3 3.3 64 270 44.4 Candidate 5 2 0 2.3 35 90 38.7 6 1 4 3.7 46 492 59.5 Intent to implement 4 5 5 4.7 18 216 84.5 4 4 5 4.3 19 198 31.1 Intent to implement 6 1 3 3.3 26 488 43.5 Candidate 2 1 5 2.7 50 376 292.3 7 5 6 6.0 33 224 32.7 Compliant 6 1 1 2.7 56 416 54.6 Candidate 6 1 5 4.0 46 208 45.9 3 2 10 5.0 41 393 49.7 2 1 8 3.7 21 324 19.6 4 1 6 3.7 32 158 43.7 Compliant 5 6 6 5.7 23 201 37.7 Candidate 4 7 5 5.3 19 157 25.1 6 1 4 3.7 59 270 52.2 Candidate 5 3 3 3.7 38 696 68.4 Candidate 6 8 9 7.7 7 161 24.1 5 4 9 6.0 37 230 34.3 5 5 6 5.3 37 375 9.6 6 1 3 3.3 41 270 46.5 Compliant 5 7 5 5.7 35 938 32.2 Compliant 7 9 3 6.3 26 148 31.3 3 1 6 3.3 42 424 33.3 Intent to implement 6 1 2 3.0 59 666 46.0 4 8 5 5.7 16 76 44.1 6 7 6 6.3 29 357 235.6 Candidate .. .. .. .. .. .. .. 8 8 8 8.0 9 200 30.5 0 6 4 3.3 42 180 36.1 2 5 6 4.3 33 104 36.8 3 4 8 5.0 48 172 45.2 Candidate 6 1 4 3.7 53 270 50.8 Candidate 2 5 5 4.0 32 161 35.7 3 6 7 5.3 37 132 16.1 Candidate 8 1 4 4.3 49 242 40.3 7 4 4 4.8 25 347 54.8 6 6 4 5.3 34 451 72.0 8 3 5 5.3 29 433 42.6 .. .. .. .. .. .. .. 7 2 1 3.3 28 358 41.7 5 5 6 5.3 8 144 62.8 Capable states and partnership Part III. Development outcomes 117 Capable states and partnership 12.4 Table Governance and anticorruption indicators Governance indicatorsa Political stability Voice and and absence Government Regulatory Control of accountability of violence effectiveness quality Rule of law corruption 1996 2009 1996 2009 1996 2009 1996 2009 1996 2009 1996 2009 SUB–SAHARAN AFRICA Angola –1.5 –1.1 –2.3 –0.2 –1.3 –0.9 –1.1 –1.0 –1.6 –1.2 –1.1 –1.3 Benin 0.7 0.3 1.0 0.4 .. –0.5 –0.1 –0.4 –0.3 –0.7 .. –0.6 Botswana 0.8 0.4 0.7 0.9 0.3 0.6 0.9 0.6 0.6 0.6 0.5 0.9 Burkina Faso –0.3 –0.3 –0.2 –0.1 –0.9 –0.7 –0.2 –0.1 –0.3 –0.3 –0.3 –0.4 Burundi –1.5 –0.7 –2.0 –1.4 .. –1.1 –1.1 –1.2 –0.9 –1.2 .. –1.1 Cameroon –1.2 –1.0 –1.3 –0.4 –1.1 –0.8 –0.8 –0.7 –1.5 –1.1 –1.1 –0.9 Cape Verde 0.8 0.8 1.0 0.8 .. 0.0 –0.6 0.0 0.5 0.5 .. 0.7 Central African Republic –0.5 –1.0 –0.2 –2.0 .. –1.4 .. –1.1 –0.3 –1.3 .. –0.8 Chad –0.9 –1.4 –0.9 –1.8 .. –1.5 –1.1 –1.1 –0.9 –1.5 .. –1.4 Comoros 0.0 –0.3 1.0 –1.0 .. –1.8 .. –1.6 .. –1.1 .. –0.8 Congo, Dem. Rep. –1.6 –1.4 –1.9 –2.1 –1.5 –1.7 –2.3 –1.6 –2.3 –1.7 –2.5 –1.4 Congo, Rep. –0.5 –1.0 –0.8 –0.4 –0.9 –1.2 –1.2 –1.3 –1.4 –1.2 –0.3 –1.2 Côte d’Ivoire –0.8 –1.2 0.0 –1.5 0.2 –1.2 0.0 –1.0 –0.7 –1.3 0.5 –1.2 Djibouti –0.7 –1.1 0.2 0.5 .. –0.9 –0.1 –0.6 –0.2 –0.6 .. –0.3 Equatorial Guinea –1.7 –1.8 –0.9 0.0 –1.3 –1.7 –1.5 –1.3 –1.2 –1.3 –1.1 –1.6 Eritrea –1.1 –2.2 0.3 –0.8 .. –1.4 .. –2.3 –0.3 –1.2 .. –0.3 Ethiopia –0.8 –1.3 –1.0 –1.7 –1.3 –0.4 –1.9 –1.0 –1.0 –0.8 –1.1 –0.7 Gabon –0.4 –1.1 –0.2 0.1 –1.0 –0.7 0.0 –0.6 –0.9 –0.5 –1.1 –0.9 Gambia, The –1.3 –1.1 0.1 0.3 –0.2 –0.7 –1.8 –0.3 0.4 –0.4 0.4 –0.6 Ghana –0.3 0.5 –0.1 0.2 –0.5 0.1 0.1 0.1 –0.3 –0.1 –0.3 0.1 Guinea –1.1 –1.4 –1.4 –1.9 –0.9 –1.3 0.1 –1.2 –1.4 –1.6 0.4 –1.2 Guinea-Bissau –0.3 –0.8 –0.6 –0.5 –0.9 –1.1 0.4 –1.2 –1.7 –1.4 –1.0 –1.1 Kenya –0.8 –0.3 –0.7 –1.3 –0.2 –0.7 –0.4 –0.2 –1.1 –1.1 –1.1 –1.1 Lesotho –0.2 –0.1 0.6 0.4 .. –0.3 –0.6 –0.6 –0.3 –0.3 .. 0.1 Liberia –1.4 –0.3 –2.6 –1.0 –1.5 –1.2 –2.6 –1.2 –2.3 –1.1 –1.7 –0.6 Madagascar 0.4 –0.6 0.1 –0.7 –0.9 –0.6 –0.8 –0.5 –1.0 –0.7 0.4 –0.2 Malawi 0.0 –0.2 –0.3 –0.1 –0.9 –0.5 –0.2 –0.5 –0.4 –0.2 –0.3 –0.5 Mali 0.7 0.2 0.7 –0.3 –1.5 –0.8 0.1 –0.4 –0.6 –0.4 –0.3 –0.7 Mauritania –1.0 –1.0 0.6 –1.2 .. –0.9 –1.1 –0.7 –0.9 –0.8 .. –0.7 Mauritius 0.8 0.8 0.8 0.6 0.3 0.7 0.0 0.9 0.9 0.9 0.6 0.7 Mozambique 0.0 –0.1 –0.5 0.5 –0.1 –0.3 –1.0 –0.3 –0.8 –0.6 –0.2 –0.4 Namibia 0.6 0.3 0.5 0.8 0.5 0.2 0.2 0.1 0.3 0.3 0.6 0.2 Niger –1.0 –0.7 0.0 –1.2 –0.9 –0.8 –1.5 –0.5 –0.9 –0.6 –0.3 –0.7 Nigeria –1.8 –0.9 –1.6 –2.0 –1.2 –1.2 –1.1 –0.7 –1.6 –1.2 –1.1 –1.1 Rwanda –1.3 –1.3 –2.0 –0.3 .. –0.2 –1.6 –0.3 –1.4 –0.5 .. 0.1 São Tomé and Príncipe 0.5 0.2 1.0 0.2 .. –0.7 .. –0.8 .. –0.7 .. –0.4 Senegal –0.1 –0.3 –0.6 –0.1 –0.1 –0.4 –0.3 –0.3 –0.3 –0.3 –0.3 –0.5 Seychelles 0.0 0.0 1.0 0.7 .. 0.2 .. –0.6 .. 0.1 .. 0.3 Sierra Leone –0.9 –0.3 –2.3 –0.4 –1.5 –1.2 –1.2 –0.8 –1.3 –1.0 –1.7 –1.0 Somalia –1.9 –2.0 –2.3 –3.3 –1.5 –2.3 –2.5 –2.6 –2.1 –2.5 –1.7 –1.7 South Africa 0.9 0.6 –1.3 0.0 0.3 0.5 0.1 0.4 0.0 0.1 0.5 0.1 Sudan –2.0 –1.6 –2.6 –2.6 –1.3 –1.3 –1.5 –1.2 –1.6 –1.3 –1.1 –1.2 Swaziland –1.1 –1.2 0.0 0.0 .. –0.7 0.4 –0.5 0.8 –0.6 .. –0.3 Tanzania –0.6 –0.1 –0.2 0.1 –0.8 –0.4 0.1 –0.4 –0.3 –0.4 –1.1 –0.4 Togo –1.0 –1.0 –0.5 –0.2 –0.9 –1.4 0.4 –0.8 –1.4 –0.9 –1.0 –1.1 Uganda –0.5 –0.5 –1.2 –1.1 –0.6 –0.6 0.3 –0.2 –0.5 –0.4 –0.3 –0.9 Zambia –0.5 –0.3 –0.5 0.5 –0.7 –0.7 0.3 –0.5 –0.5 –0.5 –1.1 –0.5 Zimbabwe –0.6 –1.6 –0.6 –1.4 –0.3 –1.7 –0.8 –2.3 –0.9 –1.9 –0.3 –1.5 NORTH AFRICA Algeria –1.3 –1.0 –2.7 –1.2 –0.6 –0.6 –1.1 –0.9 –1.4 –0.7 –0.3 –0.5 Egypt, Arab Rep. –1.0 –1.1 –0.9 –0.6 0.2 –0.3 0.4 –0.1 0.1 0.0 –0.2 –0.4 Libya –1.8 –1.9 –1.8 0.6 –1.0 –1.1 –2.0 –1.0 –1.4 –0.8 –1.1 –1.1 Morocco –0.6 –0.8 –0.5 –0.4 0.2 –0.1 0.3 0.0 0.1 –0.2 0.5 –0.2 Tunisia –0.9 –1.3 0.0 0.2 0.5 0.4 0.7 0.1 –0.2 0.2 –0.2 0.0 a. The rating scale for each criterion ranges from –2.5 (weak performance) to 2.5 (very high performance). b. 0–20 indicates that budget documents provide scant or no information, 21–40 indicates minimal information, 41–60 indicates some information, 61–80 indicates signi�cant information, and 81–100 indicates extensive information. In 2008 the International Budget Partnership made three changes in the methodology applied to its Open Budget Survey, which is the basis for the open budget index. c. Data are for the most recent year available during the period speci�ed. 118 Part III. Development outcomes Capable states and partnership Share of firms (%) Expected to pay informal payment Expected to give Expected to give Expected to give Identifying Mean corruption to public officials gifts to obtain an gifts in meetings gifts to secure a corruption as a perceptions index score Open budget index to get things done operating license with tax officials government contract major constraint (0 low to 10 high) overall scoreb 2009–10 c 2009–10 c 2009–10 c 2009–10 c 2009–10 c 2008 2010 2008 2010 48.9 39.1 34.2 58.6 75.6 1.9 1.9 3.0 26.0 54.5 44.6 26.8 59 67.8 3.1 2.8 .. .. 7.3 2.9 8.4 1 27.4 5.8 5.8 62.0 51.0 8.5 4.1 6.7 11.8 70.5 3.5 3.1 14.0 5.0 .. .. .. .. .. 1.9 1.8 .. .. 51.2 39.6 30.8 58.8 61.3 2.3 2.2 5.0 2.0 6 0 1.1 0 29.8 5.1 5.1 .. .. .. .. .. .. .. 2.0 2.1 .. .. 41.8 52.6 21.2 47.3 67.2 1.6 1.7 7.0 0.4 .. .. .. .. .. 2.5 2.1 .. .. 65.7 53.8 54.4 75.7 72.7 1.7 2.0 0.0 6.0 81.8 .. 37.1 49.9 65 1.9 2.1 .. .. 38.5 31.8 13.6 28.5 75 2.0 2.2 .. .. .. .. .. .. .. .. 3.2 .. .. .. .. .. .. .. 1.7 1.9 0.0 0.0 0 0 0 0 0 2.6 2.6 .. .. .. .. .. .. .. 2.6 2.7 .. .. 41.8 0 22.8 26.6 41.4 3.1 2.8 .. .. .. .. .. .. .. 1.9 3.2 .. .. .. .. .. .. .. 3.9 4.1 49.0 54.0 .. .. .. .. .. 1.6 2.0 .. .. .. .. .. .. .. 1.9 2.1 .. .. .. .. .. .. .. 2.1 2.1 57.0 49.0 28.1 3.3 9.2 16.7 46.7 3.2 3.5 .. .. 55.4 49.6 54.4 51.6 31.2 2.4 3.3 2.0 40.0 21.8 18.6 6.8 9 42.7 3.4 2.6 .. .. 10.8 3.5 11.4 2.8 12.8 2.8 3.4 28.0 47.0 19.4 42.4 20.2 22.8 24.8 3.1 2.7 .. 35.0 .. .. .. .. .. 2.8 2.3 .. .. 5.9 0 0.3 8.8 50.7 5.5 5.4 .. .. .. .. .. .. .. 2.6 2.7 .. 28.0 .. .. .. .. .. 4.5 4.4 47.0 53.0 35.2 32.5 13.7 43.4 83.7 2.8 2.6 26.0 3.0 .. .. .. .. .. 2.7 2.4 19.0 18.0 .. .. .. .. .. 3.0 4.0 0.0 11.0 .. .. .. .. .. 2.7 3.0 0.0 0.0 .. .. .. .. .. 3.4 2.9 3.0 3.0 .. .. .. .. .. 4.8 4.8 .. .. 20.4 8.7 8.6 33.9 36.9 1.9 2.4 .. .. .. .. .. .. .. 1.0 1.1 .. .. .. .. .. .. .. 4.9 4.5 87.0 92.0 .. .. .. .. .. 1.6 1.6 0.0 8.0 .. .. .. .. .. 3.6 3.2 .. .. .. .. .. .. .. 3.0 2.7 35.0 45.0 16.7 15.7 16.4 5.5 70.2 2.7 2.4 .. .. .. .. .. .. .. 2.6 2.5 51.0 55.0 .. .. .. .. .. 2.8 3.0 47.0 36.0 .. .. .. .. .. 1.8 2.4 .. .. .. .. .. .. .. 3.2 2.9 1.0 1.0 .. .. .. .. .. 2.8 3.1 43.0 49.0 .. .. .. .. .. 2.6 2.2 .. .. .. .. .. .. .. 3.5 3.4 27.0 28.0 .. .. .. .. .. 4.4 4.3 .. .. Capable states and partnership Part III. Development outcomes 119 Capable states and partnership 12.5 Table Country Policy and Institutional Assessment ratings Economic management CPIA overall rating (IDA Macroeconomic resource allocation index)a Averageb management Fiscal policy Debt policy 2008 2009 2008 2009 2008 2009 2008 2009 2008 2009 SUB–SAHARAN AFRICA 3.2 3.2 3.4 3.4 3.5 3.6 3.4 3.4 3.2 3.1 Angola 2.7 2.8 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 Benin 3.6 3.5 4.0 3.7 4.5 4.0 4.0 3.5 3.5 3.5 Botswanac .. .. .. .. .. .. .. .. .. .. Burkina Faso 3.7 3.8 4.3 4.3 4.5 4.5 4.5 4.5 4.0 4.0 Burundi 3.0 3.1 3.3 3.3 3.5 3.5 3.5 3.5 3.0 3.0 Cameroon 3.2 3.2 3.7 3.7 4.0 4.0 4.0 4.0 3.0 3.0 Cape Verde 4.2 4.2 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 Central African Republic 2.5 2.6 2.8 3.0 3.5 3.5 3.0 3.0 2.0 2.5 Chad 2.5 2.5 2.7 2.5 2.5 2.5 2.5 2.5 3.0 2.5 Comoros 2.3 2.5 2.0 2.3 2.5 3.0 1.5 2.0 2.0 2.0 Congo, Dem. Rep. 2.7 2.7 3.2 3.2 3.5 3.5 3.5 3.5 2.5 2.5 Congo, Rep. 2.7 2.8 2.8 3.0 3.5 3.5 2.5 3.0 2.5 2.5 Côte d’Ivoire 2.7 2.8 2.5 2.8 3.0 3.5 2.5 2.5 2.0 2.5 Djibouti 3.1 3.2 3.0 3.0 3.5 3.5 3.0 3.0 2.5 2.5 Equatorial Guineac .. .. .. .. .. .. .. .. .. .. Eritrea 2.3 2.2 2.2 1.8 2.0 2.0 2.0 2.0 2.5 1.5 Ethiopia 3.4 3.4 3.3 3.7 2.5 3.5 4.0 4.0 3.5 3.5 Gabonc .. .. .. .. .. .. .. .. .. .. Gambia, The 3.2 3.3 3.5 3.5 4.0 4.0 3.5 3.5 3.0 3.0 Ghana 3.9 3.8 3.7 3.7 3.5 3.5 3.5 3.5 4.0 4.0 Guinea 3.0 2.8 3.0 2.3 3.0 2.5 3.5 2.5 2.5 2.0 Guinea-Bissau 2.6 2.6 1.8 2.2 2.0 2.5 2.5 2.5 1.0 1.5 Kenya 3.6 3.7 4.0 4.2 4.0 4.5 4.0 4.0 4.0 4.0 Lesotho 3.5 3.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 Liberiad .. 2.8 .. 3.2 .. 3.5 .. 3.5 .. 2.5 Madagascar 3.7 3.5 3.8 3.7 4.0 4.0 3.5 3.0 4.0 4.0 Malawi 3.4 3.4 3.3 3.2 3.5 3.0 3.5 3.5 3.0 3.0 Mali 3.7 3.7 4.3 4.3 4.5 4.5 4.0 4.0 4.5 4.5 Mauritania 3.3 3.2 3.5 3.2 3.5 3.5 3.0 2.5 4.0 3.5 Mauritiusc .. .. .. .. .. .. .. .. .. .. Mozambique 3.7 3.7 4.3 4.5 4.5 4.5 4.0 4.5 4.5 4.5 Namibiac .. .. .. .. .. .. .. .. .. .. Niger 3.3 3.3 3.7 3.8 4.0 4.0 3.5 3.5 3.5 4.0 Nigeria 3.4 3.5 4.3 4.3 4.0 4.0 4.5 4.5 4.5 4.5 Rwanda 3.7 3.8 3.8 3.8 4.0 4.0 4.0 4.0 3.5 3.5 São Tomé and Príncipe 3.0 2.9 2.8 2.8 3.0 3.0 3.0 3.0 2.5 2.5 Senegal 3.6 3.7 3.8 4.0 4.0 4.0 3.5 4.0 4.0 4.0 Seychellesc .. .. .. .. .. .. .. .. .. .. Sierra Leone 3.1 3.2 3.7 3.7 4.0 4.0 3.5 3.5 3.5 3.5 Somaliad .. .. .. .. .. .. .. .. .. .. South Africac .. .. .. .. .. .. .. .. .. .. Sudan 2.5 2.5 2.7 2.7 3.5 3.5 3.0 3.0 1.5 1.5 Swazilandc .. .. .. .. .. .. .. .. .. .. Tanzania 3.8 3.8 4.3 4.3 4.5 4.5 4.5 4.5 4.0 4.0 Togo 2.7 2.8 2.7 2.8 3.0 3.0 3.0 3.0 2.0 2.5 Uganda 3.9 3.9 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 Zambia 3.5 3.4 3.7 3.5 4.0 4.0 3.5 3.0 3.5 3.5 Zimbabwe 1.4 1.9 1.0 1.7 1.0 2.0 1.0 2.0 1.0 1.0 NORTH AFRICA Algeriac .. .. .. .. .. .. .. .. .. .. Egypt, Arab Rep.c .. .. .. .. .. .. .. .. .. .. Libyac .. .. .. .. .. .. .. .. .. .. Moroccoc .. .. .. .. .. .. .. .. .. .. Tunisiac .. .. .. .. .. .. .. .. .. .. 120 Part III. Development outcomes Capable states and partnership Structural policies Averageb Trade Financial sector Business regulatory environment 2008 2009 2008 2009 2008 2009 2008 2009 3.2 3.2 3.7 3.7 3.0 3.0 3.1 3.1 2.8 2.8 4.0 4.0 2.5 2.5 2.0 2.0 3.7 3.7 4.0 4.0 3.5 3.5 3.5 3.5 .. .. .. .. .. .. .. .. 3.5 3.5 4.0 4.0 3.0 3.0 3.5 3.5 2.8 3.0 3.5 4.0 2.5 2.5 2.5 2.5 3.2 3.2 3.5 3.5 3.0 3.0 3.0 3.0 3.8 3.8 4.0 4.0 4.0 4.0 3.5 3.5 2.7 2.7 3.5 3.5 2.5 2.5 2.0 2.0 2.8 2.8 3.0 3.0 3.0 3.0 2.5 2.5 2.7 2.7 3.0 3.0 2.5 2.5 2.5 2.5 2.7 2.5 4.0 3.5 2.0 2.0 2.0 2.0 2.8 3.0 3.5 3.5 2.5 3.0 2.5 2.5 3.3 3.3 4.0 4.0 3.0 3.0 3.0 3.0 3.7 3.7 4.0 4.0 3.5 3.5 3.5 3.5 .. .. .. .. .. .. .. .. 1.5 1.5 1.5 1.5 1.0 1.0 2.0 2.0 3.2 3.2 3.0 3.0 3.0 3.0 3.5 3.5 .. .. .. .. .. .. .. .. 3.3 3.3 3.5 3.5 3.0 3.0 3.5 3.5 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 3.3 3.3 4.0 4.0 3.0 3.0 3.0 3.0 3.2 3.2 4.0 4.0 3.0 3.0 2.5 2.5 3.8 4.0 4.0 4.0 3.5 4.0 4.0 4.0 3.3 3.3 3.5 3.5 3.5 3.5 3.0 3.0 .. 2.8 .. 3.0 .. 2.5 .. 3.0 3.5 3.5 4.0 4.0 3.0 3.0 3.5 3.5 3.5 3.5 4.0 4.0 3.0 3.0 3.5 3.5 3.5 3.5 4.0 4.0 3.0 3.0 3.5 3.5 3.3 3.3 4.0 4.0 2.5 2.5 3.5 3.5 .. .. .. .. .. .. .. .. 3.7 3.7 4.5 4.5 3.5 3.5 3.0 3.0 .. .. .. .. .. .. .. .. 3.3 3.3 4.0 4.0 3.0 3.0 3.0 3.0 3.3 3.5 3.5 3.5 3.5 3.5 3.0 3.5 3.5 3.8 3.5 4.0 3.5 3.5 3.5 4.0 3.2 3.0 4.0 4.0 2.5 2.5 3.0 2.5 3.8 3.8 4.0 4.0 3.5 3.5 4.0 4.0 .. .. .. .. .. .. .. .. 3.2 3.2 3.5 3.5 3.0 3.0 3.0 3.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.7 2.7 2.5 2.5 2.5 2.5 3.0 3.0 .. .. .. .. .. .. .. .. 3.8 3.8 4.0 4.0 4.0 4.0 3.5 3.5 3.2 3.2 4.0 4.0 2.5 2.5 3.0 3.0 3.8 3.8 4.0 4.0 3.5 3.5 4.0 4.0 3.7 3.5 4.0 4.0 3.5 3.5 3.5 3.0 1.5 2.2 2.0 3.0 1.0 1.5 1.5 2.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. (continued) Capable states and partnership Part III. Development outcomes 121 Capable states and partnership 12.5 Table Country Policy and Institutional Assessment ratings (continued) Policies for social inclusion and equity Policies and institutions for Equity of public Building human Social protection environmental Averageb Gender equality resource use resources and labor sustainability 2008 2009 2008 2009 2008 2009 2008 2009 2008 2009 2008 2009 SUB–SAHARAN AFRICA 3.1 3.1 3.2 3.2 3.2 3.2 3.3 3.3 3.0 3.0 2.9 2.9 Angola 2.7 2.9 3.0 3.5 2.5 2.5 2.5 2.5 2.5 3.0 3.0 3.0 Benin 3.3 3.3 3.5 3.5 3.0 3.0 3.5 3.5 3.0 3.0 3.5 3.5 Botswanac .. .. .. .. .. .. .. .. .. .. .. .. Burkina Faso 3.6 3.6 3.5 3.5 4.0 4.0 3.5 3.5 3.5 3.5 3.5 3.5 Burundi 3.3 3.3 4.0 4.0 3.5 3.5 3.0 3.0 3.0 3.0 3.0 3.0 Cameroon 3.1 3.1 3.0 3.0 3.0 3.0 3.5 3.5 3.0 3.0 3.0 3.0 Cape Verde 4.3 4.3 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 3.5 3.5 Central African Republic 2.2 2.5 2.5 2.5 2.0 2.5 2.0 2.5 2.0 2.0 2.5 3.0 Chad 2.4 2.4 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.0 2.0 Comoros 2.5 2.6 3.0 3.0 2.5 2.5 2.5 3.0 2.5 2.5 2.0 2.0 Congo, Dem. Rep. 2.9 2.8 3.0 2.5 3.0 3.0 3.0 3.0 3.0 3.0 2.5 2.5 Congo, Rep. 2.7 2.7 3.0 3.0 2.5 2.5 3.0 3.0 2.5 2.5 2.5 2.5 Côte d’Ivoire 2.3 2.4 2.5 2.5 1.5 2.0 2.5 2.5 2.5 2.5 2.5 2.5 Djibouti 3.0 3.2 2.5 3.0 3.0 3.0 3.5 3.5 3.0 3.0 3.0 3.5 Equatorial Guineac .. .. .. .. .. .. .. .. .. .. .. .. Eritrea 3.0 2.8 3.5 3.5 3.0 2.5 3.5 3.5 3.0 2.5 2.0 2.0 Ethiopia 3.6 3.6 3.0 3.0 4.5 4.5 4.0 4.0 3.5 3.5 3.0 3.0 Gabonc .. .. .. .. .. .. .. .. .. .. .. .. Gambia, The 3.2 3.3 3.5 3.5 3.0 3.5 3.5 3.5 2.5 2.5 3.5 3.5 Ghana 4.0 3.9 4.0 4.0 4.0 4.0 4.5 4.5 4.0 3.5 3.5 3.5 Guinea 3.0 3.0 3.5 3.5 3.0 3.0 3.0 3.0 3.0 3.0 2.5 2.5 Guinea-Bissau 2.6 2.5 2.5 2.5 3.0 3.0 2.5 2.0 2.5 2.5 2.5 2.5 Kenya 3.2 3.5 3.0 3.0 3.0 3.5 3.5 4.0 3.0 3.5 3.5 3.5 Lesotho 3.3 3.3 4.0 4.0 3.0 3.0 3.5 3.5 3.0 3.0 3.0 3.0 Liberiad .. 2.5 .. 2.5 .. 3.0 .. 2.5 .. 2.5 .. 2.0 Madagascar 3.7 3.6 3.5 3.5 4.0 4.0 3.5 3.5 3.5 3.5 4.0 3.5 Malawi 3.4 3.5 3.5 3.5 3.5 3.5 3.0 3.5 3.5 3.5 3.5 3.5 Mali 3.4 3.4 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.5 3.0 3.0 Mauritania 3.5 3.4 4.0 4.0 3.5 3.5 3.5 3.5 3.0 3.0 3.5 3.0 Mauritiusc .. .. .. .. .. .. .. .. .. .. .. .. Mozambique 3.4 3.3 3.5 3.5 3.5 3.5 4.0 3.5 3.0 3.0 3.0 3.0 Namibiac .. .. .. .. .. .. .. .. .. .. .. .. Niger 3.0 3.1 2.5 2.5 3.5 3.5 3.0 3.5 3.0 3.0 3.0 3.0 Nigeria 3.2 3.2 3.0 3.0 3.5 3.5 3.0 3.0 3.5 3.5 3.0 3.0 Rwanda 3.9 3.9 3.5 3.5 4.5 4.5 4.5 4.5 3.5 3.5 3.5 3.5 São Tomé and Príncipe 2.8 2.8 3.0 3.0 3.0 3.0 3.0 3.0 2.5 2.5 2.5 2.5 Senegal 3.4 3.4 3.5 3.5 3.5 3.5 3.5 3.5 3.0 3.0 3.5 3.5 Seychellesc .. .. .. .. .. .. .. .. .. .. .. .. Sierra Leone 2.9 3.1 3.0 3.0 3.0 3.0 3.5 3.5 3.0 3.5 2.0 2.5 Somaliad .. .. .. .. .. .. .. .. .. .. .. .. South Africac .. .. .. .. .. .. .. .. .. .. .. .. Sudan 2.3 2.3 2.0 2.0 2.5 2.5 2.5 2.5 2.5 2.5 2.0 2.0 Swazilandc .. .. .. .. .. .. .. .. .. .. .. .. Tanzania 3.7 3.7 3.5 3.5 4.0 4.0 4.0 4.0 3.5 3.5 3.5 3.5 Togo 2.7 2.7 3.0 3.0 2.0 2.0 3.0 3.0 3.0 3.0 2.5 2.5 Uganda 3.8 3.8 3.5 3.5 4.0 4.0 4.0 4.0 3.5 3.5 4.0 4.0 Zambia 3.5 3.5 3.5 3.5 3.5 3.5 4.0 4.0 3.0 3.0 3.5 3.5 Zimbabwe 1.5 1.6 2.5 2.5 1.0 1.5 1.0 1.0 1.0 1.0 2.0 2.0 NORTH AFRICA Algeriac .. .. .. .. .. .. .. .. .. .. .. .. Egypt, Arab Rep.c .. .. .. .. .. .. .. .. .. .. .. .. Libyac .. .. .. .. .. .. .. .. .. .. .. .. Moroccoc .. .. .. .. .. .. .. .. .. .. .. .. Tunisiac .. .. .. .. .. .. .. .. .. .. .. .. Note: The rating scale for each indicator ranges from 1 (low) to 6 (high). The most recent external review of the CPIA ratings and methodology was in 2004. a. Calculated as the average of the average ratings of each cluster. b. All criteria are weighted equally. c. Not an International Development Association (IDA) member. d. Not rated in the IDA resource allocation index. 122 Part III. Development outcomes Capable states and partnership Public sector management and institutions Transparency, Property rights and Quality of budgetary and Efficiency of revenue Quality of public accountability, and Averageb rule-based governance financial management mobilization administration corruption in public sector 2008 2009 2008 2009 2008 2009 2008 2009 2008 2009 2008 2009 2.9 3.0 2.8 2.8 3.0 3.0 3.4 3.4 2.9 2.9 2.7 2.7 2.4 2.4 2.0 2.0 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.5 3.3 3.3 3.0 3.0 3.5 3.5 3.5 3.5 3.0 3.0 3.5 3.5 .. .. .. .. .. .. .. .. .. .. .. .. 3.5 3.7 3.5 3.5 4.0 4.5 3.5 3.5 3.5 3.5 3.0 3.5 2.6 2.6 2.5 2.5 3.0 3.0 3.0 3.0 2.5 2.5 2.0 2.0 2.9 2.9 2.5 2.5 3.0 3.0 3.5 3.5 3.0 3.0 2.5 2.5 4.0 4.0 4.0 4.0 4.0 4.0 3.5 3.5 4.0 4.0 4.5 4.5 2.3 2.4 2.0 2.0 2.0 2.5 2.5 2.5 2.5 2.5 2.5 2.5 2.2 2.2 2.0 2.0 2.0 2.0 2.5 2.5 2.5 2.5 2.0 2.0 2.2 2.4 2.5 2.5 1.5 2.0 2.5 2.5 2.0 2.5 2.5 2.5 2.2 2.2 2.0 2.0 2.5 2.5 2.5 2.5 2.0 2.0 2.0 2.0 2.6 2.6 2.5 2.5 2.5 2.5 3.0 3.0 2.5 2.5 2.5 2.5 2.5 2.6 2.0 2.0 2.0 2.5 4.0 4.0 2.0 2.0 2.5 2.5 2.8 2.8 2.5 2.5 3.0 3.0 3.5 3.5 2.5 2.5 2.5 2.5 .. .. .. .. .. .. .. .. .. .. .. .. 2.7 2.7 2.5 2.5 2.5 2.5 3.5 3.5 3.0 3.0 2.0 2.0 3.3 3.2 3.0 3.0 4.0 3.5 4.0 3.5 3.0 3.5 2.5 2.5 .. .. .. .. .. .. .. .. .. .. .. .. 2.9 2.9 3.0 3.0 3.0 3.0 3.5 3.5 3.0 3.0 2.0 2.0 3.9 3.8 3.5 3.5 4.0 3.5 4.5 4.5 3.5 3.5 4.0 4.0 2.6 2.6 2.0 2.0 3.0 3.0 3.0 3.0 3.0 3.0 2.0 2.0 2.6 2.6 2.5 2.5 2.5 2.5 3.0 3.0 2.5 2.5 2.5 2.5 3.3 3.3 2.5 2.5 3.5 3.5 4.0 4.0 3.5 3.5 3.0 3.0 3.4 3.4 3.5 3.5 3.0 3.0 4.0 4.0 3.0 3.0 3.5 3.5 .. 2.8 .. 2.5 .. 2.5 .. 3.5 .. 2.5 .. 3.0 3.6 3.3 3.5 3.5 3.5 3.0 4.0 4.0 3.5 3.5 3.5 2.5 3.4 3.4 3.5 3.5 3.0 3.0 4.0 4.0 3.5 3.5 3.0 3.0 3.4 3.4 3.5 3.5 3.5 3.5 3.5 3.5 3.0 3.0 3.5 3.5 3.0 3.0 3.0 3.0 3.0 3.0 3.5 3.5 3.0 3.0 2.5 2.5 .. .. .. .. .. .. .. .. .. .. .. .. 3.3 3.4 3.0 3.0 3.5 4.0 4.0 4.0 3.0 3.0 3.0 3.0 .. .. .. .. .. .. .. .. .. .. .. .. 3.2 3.1 3.0 3.0 3.5 3.5 3.5 3.5 3.0 3.0 3.0 2.5 2.9 2.9 2.5 2.5 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.0 3.5 3.5 3.0 3.0 4.0 4.0 3.5 3.5 3.5 3.5 3.5 3.5 3.1 3.1 2.5 2.5 3.0 3.0 3.5 3.5 3.0 3.0 3.5 3.5 3.4 3.4 3.5 3.5 3.0 3.0 4.0 4.0 3.5 3.5 3.0 3.0 .. .. .. .. .. .. .. .. .. .. .. .. 2.7 2.9 2.5 2.5 3.5 3.5 2.5 2.5 2.5 3.0 2.5 3.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.3 2.2 2.0 2.0 2.0 2.0 3.0 3.0 2.5 2.5 2.0 1.5 .. .. .. .. .. .. .. .. .. .. .. .. 3.5 3.5 3.5 3.5 3.5 3.5 4.0 4.0 3.5 3.5 3.0 3.0 2.2 2.4 2.5 2.5 2.0 2.5 2.5 3.0 2.0 2.0 2.0 2.0 3.4 3.3 3.5 3.5 4.0 4.0 3.5 3.5 3.0 3.0 3.0 2.5 3.2 3.2 3.0 3.0 3.5 3.5 3.5 3.5 3.0 3.0 3.0 3.0 1.6 2.0 1.0 1.5 1.5 2.0 3.5 3.5 1.0 1.5 1.0 1.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. Capable states and partnership Part III. Development outcomes 123 Capable states and partnership 12.6 Table Polity indicators Revised combined polity score (–10 strongly autocratic to Institutionalized democracy Institutionalized autocracy 10 strongly democratic) (0 low to 10 high) (0 low to 10 high) 1995 2000 2009 1995 2000 2009 1995 2000 2009 SUB–SAHARAN AFRICA Angola –2.0 –3.0 –2.0 .. 1.0 2.0 .. 4.0 4.0 Benin 6.0 6.0 7.0 6.0 6.0 7.0 0.0 0.0 0.0 Botswana 7.0 8.0 8.0 7.0 8.0 8.0 0.0 0.0 0.0 Burkina Faso –5.0 –3.0 0.0 0.0 0.0 2.0 5.0 3.0 2.0 Burundi 0.0 –1.0 6.0 .. 1.0 7.0 .. 2.0 1.0 Cameroon –4.0 –4.0 –4.0 1.0 1.0 1.0 5.0 5.0 5.0 Cape Verde .. .. .. .. .. .. .. .. .. Central African Republic 5.0 5.0 –1.0 5.0 5.0 1.0 0.0 0.0 2.0 Chad –4.0 –2.0 –2.0 0.0 1.0 1.0 4.0 3.0 3.0 Comoros 0.0 –1.0 9.0 .. 1.0 9.0 .. 2.0 0.0 Congo, Dem. Rep. 0.0 0.0 5.0 .. .. 6.0 .. .. 1.0 Congo, Rep. 5.0 –6.0 –4.0 6.0 0.0 0.0 1.0 6.0 4.0 Côte d’Ivoire –6.0 4.0 0.0 0.0 5.0 .. 6.0 1.0 .. Djibouti –7.0 2.0 2.0 0.0 3.0 3.0 7.0 1.0 1.0 Equatorial Guinea –5.0 –5.0 –5.0 0.0 0.0 0.0 5.0 5.0 5.0 Eritrea –6.0 –6.0 –7.0 0.0 0.0 0.0 6.0 6.0 7.0 Ethiopia 1.0 1.0 1.0 3.0 3.0 3.0 2.0 2.0 2.0 Gabon –4.0 –4.0 3.0 0.0 0.0 4.0 4.0 4.0 1.0 Gambia, The –7.0 –5.0 –5.0 0.0 0.0 0.0 7.0 5.0 5.0 Ghana –1.0 2.0 8.0 1.0 3.0 8.0 2.0 1.0 0.0 Guinea –1.0 –1.0 –1.0 1.0 1.0 1.0 2.0 2.0 2.0 Guinea-Bissau 5.0 5.0 6.0 5.0 5.0 7.0 0.0 0.0 1.0 Kenya –5.0 –2.0 7.0 0.0 2.0 7.0 5.0 4.0 0.0 Lesotho 8.0 4.0 8.0 8.0 .. 8.0 0.0 .. 0.0 Liberia 0.0 0.0 6.0 .. 3.0 7.0 .. 3.0 1.0 Madagascar 9.0 7.0 0.0 9.0 7.0 3.0 0.0 0.0 3.0 Malawi 6.0 6.0 6.0 6.0 6.0 6.0 0.0 0.0 0.0 Mali 7.0 6.0 7.0 7.0 6.0 7.0 0.0 0.0 0.0 Mauritania –6.0 –6.0 –2.0 0.0 0.0 0.0 6.0 6.0 2.0 Mauritius 10.0 10.0 10.0 10.0 10.0 10.0 0.0 0.0 0.0 Mozambique 5.0 5.0 5.0 5.0 5.0 5.0 0.0 0.0 0.0 Namibia 6.0 6.0 6.0 6.0 6.0 6.0 0.0 0.0 0.0 Niger 8.0 5.0 –3.0 8.0 6.0 0.0 0.0 1.0 3.0 Nigeria –6.0 4.0 4.0 0.0 4.0 4.0 6.0 0.0 0.0 Rwanda –6.0 –4.0 –3.0 0.0 0.0 0.0 6.0 4.0 3.0 São Tomé and Principe .. .. .. .. .. .. .. .. .. Senegal –1.0 8.0 7.0 2.0 8.0 7.0 3.0 0.0 0.0 Seychelles .. .. .. .. .. .. .. .. .. Sierra Leone –7.0 0.0 7.0 0.0 .. 8.0 7.0 .. 1.0 Somalia 0.0 0.0 0.0 .. .. .. .. .. .. South Africa 9.0 9.0 9.0 9.0 9.0 9.0 0.0 0.0 0.0 Sudan –7.0 –7.0 –4.0 0.0 0.0 0.0 7.0 7.0 4.0 Swaziland –9.0 –9.0 –9.0 0.0 0.0 0.0 9.0 9.0 9.0 Tanzania –1.0 –1.0 –1.0 2.0 2.0 2.0 3.0 3.0 3.0 Togo –2.0 –2.0 –4.0 1.0 1.0 1.0 3.0 3.0 5.0 Uganda –4.0 –4.0 –1.0 0.0 0.0 1.0 4.0 4.0 2.0 Zambia 6.0 1.0 7.0 6.0 3.0 7.0 0.0 2.0 0.0 Zimbabwe –6.0 –3.0 1.0 0.0 1.0 3.0 6.0 4.0 2.0 NORTH AFRICA Algeria –3.0 –3.0 2.0 1.0 1.0 3.0 4.0 4.0 1.0 Egypt, Arab Rep. –6.0 –6.0 –3.0 0.0 0.0 1.0 6.0 6.0 4.0 Libya –7.0 –7.0 –7.0 0.0 0.0 0.0 7.0 7.0 7.0 Morocco –7.0 –6.0 –6.0 0.0 0.0 0.0 7.0 6.0 6.0 Tunisia –3.0 –3.0 –4.0 1.0 1.0 1.0 4.0 4.0 5.0 124 Part III. Development outcomes Capable states and partnership Technical notes 1. Basic indicators 1), divided by midyear population. It is simi- lar in concept to GNI per capita in current Table .. Basic indicators prices, except that the use of three-year av- Population is total population based on the de erages of exchange rates smooths out sharp facto de�nition of population, which counts fluctuations from year to year. all residents regardless of legal status or Gross domestic product (GDP) per capita is citizenship—except for refugees not perma- gross domestic product divided by midyear nently settled in the country of asylum, who population. GDP is the sum of gross value are generally considered part of the popula- added by all resident producers in the econ- tion of their country of origin. The values omy plus any product taxes and minus any shown are midyear estimates. subsidies not included in the value of the Population growth rate for year t is the expo- products. It is calculated without making de- nential rate of growth of midyear population ductions for depreciation of fabricated assets from year t–1 to t, expressed as a percentage. or for depletion and degradation of natural Population is based on the de facto de�ni- resources. Growth rates are in real terms and tion of population, which counts all residents have been calculated by the least-squares regardless of legal status or citizenship— method using constant 2000 exchange rates except for refugees not permanently settled (box 2). in the country of asylum, who are gener- Life expectancy at birth is the number of ally considered part of the population of the years a newborn infant would live if prevailing country of origin. patterns of mortality at the time of its birth Land area is the land surface area of a coun- were to remain the same throughout its life. try, excluding inland waters, national claims Under-�ve mortality rate is the probability to continental shelf, and exclusive economic that a newborn baby will die before reaching zones. age 5, if subject to current age-speci�c mor- Population density is midyear population tality rates. The probability is expressed as a divided by land area in square kilometers. rate per 1,000. Population is based on the de facto de�ni- Gini index is the most commonly used tion of population, which counts all residents measure of inequality. The coefficient ranges regardless of legal status or citizenship— from 0, which reflects complete equality, to except for refugees not permanently settled 100, which indicates complete inequality in the country of asylum, who are generally (one person has all the income or consump- considered part of the population of their tion, all others have none). Graphically, the country of origin. Land area is a country’s Gini index can be easily represented by the total area, excluding area under inland water area between the Lorenz curve and the line bodies, national claims to continental shelf, of equality. and exclusive economic zones. In most cases Adult literacy rate is the percentage of the de�nition of inland water bodies includes adults ages 15 and older who can, with un- major rivers and lakes. derstanding, read and write a short, simple Gross national income (GNI) per capita, statement on their everyday life. World Bank Atlas method, is GNI, calculated Net official development assistance per capita using the World Bank Atlas method (see box is calculated by dividing net disbursements Technical notes 125 Box 2 Growth rates Growth rates are calculated as annual averages and represented as which is equivalent to the logarithmic transformation of the com- percentages. Except where noted, growth rates of values are com- pound growth equation, puted from constant price series. Rates of change from one period to the next are calculated as proportional changes from the earlier X t = Xo(1 + r)2 period. Least squares growth rates are used wherever there is a suf- ficiently long time series to permit a reliable calculation. No growth In this equation X is the variable, t is time, and a = lnXo and b = ln(1 + r) rate is calculated if more than half the observations in a period are are parameters to be estimated. If b* is the least squares estimate missing. The least squares growth rate, r, is estimated by fitting a lin- of b, the average annual growth rate, r, is obtained as [exp(b*) – 1] ear regression trend line to the logarithmic annual values of the vari- multiplied by 100 for expression as a percentage. The calculated able in the relevant period. The regression equation takes the form growth rate is an average rate that is representative of the available observations over the entire period. It does not necessarily match ln Xt = a + bt the actual growth rate between any two periods. of loans and grants from all official sources from the World Bank Development Research on concessional �nancial terms by midyear Group and are based on primary household population. This indicator shows the impor- survey data obtained from government sta- tance of aid flows in sustaining per capita in- tistical agencies and World Bank country come and consumption levels, although ex- departments (http://iresearch.worldbank. change rate fluctuations, the actual rise of aid org/PovcalNet/jsp/index.jsp) and for high- flows, and other factors vary across countries income economies are from the Luxembourg and over time. Income Study database. Data on literacy are Regional aggregates for GNI per capita, GDP from United Nations Educational, Scienti�c per capita, life expectancy at birth, and adult and Cultural Organization Institute for Sta- literacy rates are weighted by population. tistics. Data on aid flows are from the OECD Geographic Distribution of Aid Flows to Devel- Source: Data on population and life expec- oping Countries. tancy are from the United Nations Popula- tion Division World Population Prospects: The 2. National and �scal accounts 2008 Revision, census reports and other sta- Africa Development Indicators uses the 1993 tistical publications from national statistical System of National Accounts (1993 SNA) to offices, Eurostat Demographic Statistics, Sec- compile national accounts data. Botswana, retariat of the Paci�c Community Statistics Cameroon, Chad, the Democratic Republic and Demography Programme, U.S. Census of the Congo, Ethiopia, Kenya, Lesotho, Na- Bureau International Database, and World mibia, Senegal, Sierra Leone, and South Afri- Bank estimates based on data from these ca report data using the 1993 SNA. Although sources as well as household surveys con- more countries are adopting the 1993 SNA, ducted by national agencies, Macro Interna- many still follow the 1968 SNA, and some tional, the U.S. Centers for Disease Control low-income countries use concepts from the and Prevention, and refugees statistics from 1953 SNA. the United Nations High Commissioner for Reporting periods: For most economies Refugees. Data on land are from Food and the �scal year is concurrent with the calen- Agriculture Organization electronic �les and dar year. However, there are few countries website. Data on GNI per capita and GDP whose ending date reported is for the �s- per capita are from World Bank national ac- cal year of the central government, though counts data and Organisation for Economic �scal years for other government levels Co-operation and Development (OECD) na- and reporting years for statistical surveys tional accounts data �les. Data on under-�ve may differ. Reporting end dates are as fol- mortality are from the Inter-agency Group lows for the following countries: Botswana for Child Mortality Estimation Level & (June  30); Egypt (June 30), Ethiopia (July Trends in Child Mortality: Report 2010. Data 7), Gambia, The (June 30), Kenya (June 30), on Gini index for developing countries are Lesotho (March 31), Malawi (March 31), 126 Africa Development Indicators 2011 African statistical systems Ghislaine Delaine and Antoine Simonpietri Most of the data used to compute the indicators in this volume of National Strategies for the Development of Statistics Africa Development Indicators come from the African country na- The National Strategy for the Development of Statistics approach tional statistical systems, the only primary source of the statistics developed by PARIS21 and endorsed by the Marrakech Action related to country economic, social, and environmental issues. Plan for Statistics in 2004 gives an efficient tool to organize the While international and specialized institutions may review, make development of national statistical systems. If the Poverty Reduc- comparable, and estimate missing values, the true sources of the tion Strategy Paper is the vehicle for coordination and prioritiza- data are the national statistical systems, and the data coverage tion for national development planning in the region, the National and quality improvement depend on strengthening their capacity. Strategy for the Development of Statistics is the equivalent for sta- tistical systems. Based on the principles of strategic management National statistical systems used in statistical systems in developed countries, the strategy’s In general a national statistical system consists of a central statisti- guidelines were discussed and reviewed by a number of managers cal office, a national office or institute of statistics, and its regional of statistical offices in developing countries and have taken into agencies, sectors’ statistical units in key ministries (finance, edu- account previous attempts of statistical planning. cation, health, transport, agriculture), and a Central Bank statisti- A National Strategy for the Development of Statistics provides cal unit. Some large programs may also have specialized statisti- a guide for strengthening statistical capacity across the entire na- cal units. tional statistical system. The strategy envisages where the national Africa’s national statistical systems were designed on Eu- statistical systems should be in 5–10 years and sets milestones for rope’s model, ruled by the same principles drafted in a statistical getting there. It presents a comprehensive and unified framework law—a law that ensures the independence of the system and the for continual assessment of evolving user needs and priorities essence of the role it plays within or together with the government for statistics and for building the capacity needed to meet these (produce and centralize, process, publish and disseminate basic needs in a more coordinated, synergistic, and efficient manner. It information needed for administrative management). In the past also provides a framework for mobilizing, harnessing, and leverag- most African countries reviewed and updated their statistical laws ing resources (both national and international) and a basis for ef- to address new aspects of statistical information. fective and results-oriented strategic management of the national The system is usually coordinated by a national council of statistical system. statistics, a multisector body at the ministerial level that approves The PARIS21 Report (March 2011) on National Strategy for the overall strategies and policies related to the statistical opera- the Development of Statistics status for International Development tions in the country as well as the yearly action plan for statistical Association countries shows that 22 countries are currently imple- production. It meets once or twice a year. In most countries, these menting a strategy and that 15 are designing a strategy or awaiting councils have been weak institutions incapable of playing their their adoption by country authorities. central role of coordination and quality control. It seems, however, that in recent years, thanks to PARIS21’s new National Strategy Role of partners for the Development of Statistics process and STATCAP, they have For a long time donors have substituted government at both the been able to play a stronger role in both developing and coordinat- demand and financial levels and provided methodological support ing national statistical systems. for the adoption of up to date techniques and measurements. Ac- The major element of the national statistical system is the cen- cording to the 2010 Partner Report on Support to Statistics, Af- tral statistical office. In the context of weak systems, these offices rica received nearly half of total statistical support, equivalent to tend to concentrate all national production, often substituting the $716 million in commitments, of which 9 countries (Burkina Faso, sector departments. However, that does not preclude most of Ethiopia, Kenya, Malawi, Mali, Mozambique, Nigeria, Sudan, and these offices from facing incredible difficulties that hamper their Tanzania) received a little less than half of this amount. power to produce statistics in a timely and accurate manner. Most African central statistical offices now have websites where the Challenges in supporting national capacity core of their production is displayed (see table). After years of decline, the capacity of African countries to produce In more and more countries, statistical training is provided by and disseminate good quality, reliable, relevant, and timely sta- national schools sometimes linked with central statistical offices, tistics has improved due in part to an increase in the demand for while regional schools of statistics train statisticians at high and data. However, this demand has rarely been used to build a sus- intermediate levels. As a result, most central statistical offices are tainable statistical capacity. Data production from some adminis- staffed with trained statisticians, but a critical mass of statisticians trative sources and surveys has improved, but large gaps remain is yet to be reached to support regular statistical production. In ad- in national accounts, household surveys, and most administrative dition, there is a concentration at the central statistical office, while data. If data dissemination has progressed with the development in general, sector departments of statistics lack trained statisticians. of national data archives, very few countries have adopted data (continued) Technical notes 127 African statistical systems (continued) access policies. The use of data by nationals, the raison d’être of Country Statistical of�ce website statistical capacity building, is still very limited. Angola   In the past, the policy environment has been friendlier to sta- Benin www.insae-bj.org tistical development, but progress remains precarious: Botswana www.cso.gov.bw/ • The industry of indicators has flourished with Poverty Re- Burkina Faso www.insd.bf/fr/ duction Strategy/Millennium Development Goals monitoring Burundi www.isteebu.bi/ and evaluation, but availability of good statistics has rarely Cameroon www.statistics-cameroon.org been cited as a condition for transparency, accountability, Cape Verde www.ine.cv/ and good governance in development policies. Hence, the Central African Republic www.stat-centrafrique.com/ commitment of governments continues to be fragile. Chad www.inseed-tchad.org • Most of the countries have designed National Strategies Comoros   for the Development of Statistics, but implementation of Congo, Dem. Rep. www.ins.cd/ action programs is still meager. National statistical offices Congo, Rep. www.cnsee.org have gained more autonomy despite the resistance to en- Côte d’Ivoire www.ins.ci/ forcing new laws or taking advantage of new institutional arrangements. Equatorial Guinea www.dgecnstat-ge.org • For more than 20 years, Africa has benefitted from a train- Eritrea   ing center network; however, trained statisticians are not Ethiopia www.csa.gov.et/ being adequately hired by statistical offices due to budget- Gabon www.stat-gabon.org ary constraints. Gambia www.gambia.gm/Statistics/ • Statistical knowledge and new techniques are available but Ghana www.statsghana.gov.gh/ transferred to African statisticians in ad hoc and uncoordi- Guinea www.stat-guinee.org nated manners, resulting in a permanent resort to techni- Guinea-Bissau www.stat-guinebissau.com/ cal assistance. Some attempts have been made to address Kenya www.knbs.or.ke/ this—but in an ad hoc manner and without a systematic ca- Lesotho www.bos.gov.ls/ pacity-building program approach. Liberia www.lisgis.org • Finally, despite recent efforts, inadequate financing of sta- Madagascar www.instat.mg/ tistical operations remains the major constraint to statistical Malawi www.nso.malawi.net/ development. Mali http://instat.gov.ml/ Mauritania www.ons.mr/ References PARIS21. 2004. “A Guide to Designing a National Strategy for Mauritius www.gov.mu/portal/site/cso the Development of Statistics (NSDS).� PARIS21 Secretariat, Mozambique www.ine.gov.mz/ Paris. Namibia www.npc.gov.na/cbs/ — . — — 2010. “Partner Report on Support to Statistics (PRESS).� Niger www.stat-niger.org PARIS21 Secretariat, Paris. Nigeria www.nigerianstat.gov.ng/ — . — — 2011. National Strategies for the Development of Statistics Rwanda www.statistics.gov.rw/ Progress Report: NSDS Summary Table for IDA and Lower São Tomé and Príncipe www.ine.st/ Middle Income Countries. Paris: PARIS21 Secretariat. Senegal www.ansd.sn/ World Bank. 2004. “Better Data for Better Results: An Action Plan Seychelles www.nsb.gov.sc/ for Improving Development Statistics.� Paper presented at the Sierra Leone www.statistics.sl/ Second International Roundtable on Managing for Develop- Somalia   ment Results, February 4–5, Marrakech, Morocco. South Africa www.statssa.gov.za/ South Sudan http://ssccse.org Sudan www.cbs.gov.sd/ Swaziland www.gov.sz/ Tanzania www.nbs.go.tz/ Togo www.stat-togo.org Uganda www.ubos.org Zambia www.zamstats.gov.zm/ Zimbabwe www.zimstat.co.zw Total 44 128 Africa Development Indicators 2011 Namibia (March 31), Sierra Leone (June pound sterling, euro, and U.S. dollar are in 30), South Africa (March 31), Swaziland use in Zimbabwe. However, data are report- (March 31), Uganda (June 30), and Zimba- ed in U.S. dollars, the most frequently used bwe (June 30). The reporting period for na- currency. tional accounts data is either calendar year or �scal year basis. Most economies report Table .. Gross domestic product, national accounts and balance of payments nominal data using calendar years, but some report Gross domestic product (GDP), nominal, is the on �scal years. Fiscal year data are assigned sum of gross value added by all resident pro- to the calendar year that contains the larger ducers in the economy plus any product taxes share of the �scal year. If a country’s �scal and minus any subsidies not included in the year ends before June 30, data are shown in value of the products. It is calculated without that �rst calendar year of the �scal year; if making deductions for depreciation of fabri- the �scal year ends on or after June 30, data cated assets or for depletion and degradation are shown in the second calendar year of the of natural resources. GDP �gures are shown �scal year. Balance of payments data are re- at market prices (also known as purchaser ported by calendar year. values) and converted from domestic cur- Revisions to national accounts data: National rencies using single-year official exchange accounts data are revised by national statis- rates. For the few countries where the of- tical offices when methodologies change or �cial exchange rate does not reflect the rate data sources improve. This in turn means effectively applied to actual foreign exchange that Africa Development Indicators nation- transactions, an alternative conversion factor al accounts data are also revised when data is used. sources change. The sum of the components of GDP by • Ghana: The Ghana Statistical Service industrial origin (presented here as value revised Ghana’s national accounts se- added) will not normally equal total GDP for ries from 1993 to 2006. New GDP data several reasons. First, components of GDP are about 60 percent higher than pre- by expenditure are individually rescaled and viously reported and incorporate im- summed to provide a partially rebased series proved data sources and methodology. for total GDP. Second, total GDP is shown • Guinea-Bissau: National accounts data at purchaser value, while value added com- for 2003–09 are revised. The new data ponents are conventionally reported at pro- have broader coverage of all sectors of ducer prices. As explained above, purchaser the economy, and the new base year is values exclude net indirect taxes, while pro- 2005. GDP in current prices is on av- ducer prices include indirect taxes. Third, cer- erage 89 percent higher than previous tain items, such as imputed bank charges, are estimates. added in total GDP. • Namibia: The Central Bureau of Sta- tistics has revised national accounts Source: World Bank and Organisation for data for 2000–07. An expanded survey Economic Co-operation and Development has resulted in a substantial upward national accounts data. adjustment to estimates of output, particularly in mining, services, and Table .. Gross domestic product, real manufacturing. The constant price se- Gross domestic product (GDP), real, is obtained ries were rebased from 1995 to 2004 by converting national currency GDP series prices. GDP in current prices aver- to U.S. dollars using constant 2000 exchange ages 14 percent higher than previous rates. For countries where the official ex- estimates. change rate does not effectively reflect the • South Africa: The base year has been rate applied to actual foreign exchange trans- changed from 2000 to 2005. Data are actions, an alternative currency conversion revised from 2000 onward with official factor has been used. Growth rates are in government data. real terms and calculated by the least-squares National currencies: As of January 2009, method using constant 2000 exchange rates multiple hard currencies such as the rand, (see box 2). Technical notes 129 Africa’s future and the World Bank’s support to it Shantayanan Devarajan Sub-Saharan Africa in 2011 has an unprecedented opportunity for as shown by the dynamic growth of the information, commu- transformation and sustained growth. Until the global economic nications, and technology sector in Africa. crisis, Africa’s economy had been growing 5 percent a year for a • Vulnerability and resilience. Africa’s poor are subject to a se- decade. Growth declined in 2009 but rebounded in 2010, thanks ries of shocks that conspire to keep them poor: macroeco- mainly to prudent macroeconomic policies (figure 1). Progress to- nomic shocks; health shocks such as malaria or HIV/AIDS; ward the Millennium Development Goals has been fast enough natural disasters, which are likely to increase with climate that several countries (Ethiopia, Ghana, and Malawi) are likely change; and conflict and political violence. The strategy seeks to achieve most of the goals. Africa’s private sector is increas- to build resilience to these shocks by, for example, improving ingly attracting investment, and—if policymakers’ response to the macroeconomic policies, promoting public health interven- global crisis is a guide—the climate for market-oriented, pro-poor tions, adapting to the effects of climate change with greater reforms is robust. use of irrigation and water management, and strengthening institutions of resource-sharing and consensus-building. The Figure 1 Growth and poverty reduction in Africa strategy will also support countries in the event of a shock through, for instance, health insurance and safety net pro- 10 grams, such as Rwanda’s nearly universal insurance scheme GDP growth (%) Oil exporters, excluding Nigeria 8 or Ethiopia’s public works program. Oil exporters Low income The foundation of the strategy is governance and public sec- 6 tor capacity. Of Africa’s $48 billion infrastructure deficit, $17 bil- 4 lion can be filled by efficiency improvements in the management Middle income of infrastructure. Teachers in public primary schools in Uganda 2 are absent about 20 percent of the time. Yet governance prob- Non-oil-exporting resource rich 0 lems—vested interests—stand in the way of these efficiency gains. The strategy will help address these problems by approaching –2 2006 2007 2008 2009 2010 2011 governance from both the demand and supply sides. We aim to strengthen citizen voice using data, knowledge, and the power of information, communications, and technology so that they can 70 demand good governance from their leaders. On the supply side, Poverty rate (%) Sub-Saharan Africa we will continue to strengthen the capacity of the public sector, 60 Actual $1.25 a day focusing on incentives within the civil service. Projected $1.25 a day The World Bank will implement the strategy using its three 50 After crisis instruments—finance, knowledge, and partnerships—but we will Path to 2015 40 38.0 reverse the order. The first instrument is partnership—with African governments, the domestic and international private sector, civil 30 36.0 society, and development partners. We will tailor our interventions Before crisis depending on what others are doing. Since Rwanda and Niger re- 20 1990 1995 2000 2005 2010 2015 ceive substantial amounts of money for “vertical health programs� such as HIV/AIDS or malaria, the Bank uses its resources to help But Africa continues to face long-term development chal- these countries improve their health systems. The second instru- lenges: dependence on a few primary commodities, low human ment is knowledge, which we will use to promote a more evidence- capital, weak governance, low youth employment, low empower- based public debate. Studies on leakage of public funds, teacher ment of women, and climate change, to name a few. If we can ad- absenteeism, and student learning outcomes, by informing the dress these challenges, Africa could be on the brink of a takeoff, public about the quality of public services, have stimulated a vig- much like China 30 years ago and India 20 years ago. orous debate, which has brought about change. The third instru- To that end, the World Bank’s strategy for Africa has two pillars ment, finance, will be used as a source of leveraging. How can we and a foundation. The two pillars are: turn a $500 million lending envelope to a country into $3 billion • Competitiveness and employment. The strategy seeks to in external resources to that country, just as the Bujagali dam in help diversify African countries’ exports and generate pro- Uganda used $150 million of the Bank’s IDA resources to crowd in ductive employment, especially for the 7–10 million young $650 million additional resources from public and private sources? people entering the labor force every year. The strategy will The strategy proposes a 10-year vision of a continent whose require a mix of proactive government policies that target per capita income is 50 percent higher than today, whose poverty sectors—which helped Kenya’s cut flowers and Mali’s man- rate has fallen 12 percentage points, whose area includes at least goes—with more “neutral� policies, including infrastructure 5 middle-income countries and 15 countries increasing agricul- and skill-building, that enable different industries to flourish, tural productivity faster than 5 percent a year, and whose share of 130 Africa Development Indicators 2011 Africa’s future and the World Bank’s support to it (continued) world trade has doubled to 8 percent. To track progress towards Needless to say, this strategy is not without risks. The global these goals, the strategy has a three-tier results monitoring frame- economy could face another serious downturn, political violence work based on a results chain that links Africa’s progress with the could break out in parts of the continent, and we may lack the re- World Bank’s contribution to those results with the use of World sources to carry out the plans. But the themes of the strategy, as Bank instruments (figure 2). well as the focus on partnerships—not to mention the palpable op- timism on the continent—make us confident that Africa can seize Figure 2 The Africa strategy’s three-tier results monitoring this opportunity and realize its full potential ti sustain growth and framework reduce poverty. Tier 2 Tier 1 Sector outcomes and Tier 3 References Results indicators Activities and inputs for regional development outputs contributing to in support of World Bank. 2011. Africa’s Future and the World’s Support to It. regional results, supported outcomes regional results Washington, DC: World Bank. through country programs Measures how the Measures the World Shows which instruments Africa Region makes Bank’s contribution and inputs the World Bank progress on key to achieving is using for results development indicators development results achievement Source: World Bank and Organisation for Table .. Gross national income, Economic Co-operation and Development nominal national accounts data. Gross national income, nominal, is the sum of value added by all resident producers plus any Table .. Gross domestic product product taxes (less subsidies) not included in growth the valuation of output plus net receipts of Gross domestic product (GDP) growth is the av- primary income (compensation of employees erage annual growth rate of real GDP (table and property income) from abroad. Data are 2.2) at market prices based on constant local converted from national currency in current currency. Aggregates are based on constant prices to U.S. dollars at official annual ex- 2000 U.S. dollars. change rates. Source: World Bank and Organisation for Source: World Bank and Organisation for Economic Co-operation and Development Economic Co-operation and Development national accounts data. national accounts data. Table .. Gross domestic product per Table .. Gross national income, capita, real World Bank Atlas method Gross domestic product (GDP) per capita, real, is Gross national income (GNI), World Bank At- calculated by dividing real GDP (table 2.2) by las method, (formerly GNP) is the sum of val- corresponding midyear population. ue added by all resident producers plus any product taxes (less subsidies) not included in Source: World Bank and Organisation for the valuation of output plus net receipts of Economic Co-operation and Development primary income (compensation of employ- national accounts data. ees and property income) from abroad. GNI, calculated in national currency, is usually Table .. Gross domestic product per converted to U.S. dollars at official exchange capita growth rates for comparisons across economies, al- Gross domestic product (GDP) per capita growth though an alternative rate is used when the is the average annual growth rate of real GDP official exchange rate is judged to diverge per capita (table 2.4). by an exceptionally large margin from the rate actually applied in international trans- Source: World Bank and Organisation for actions. To smooth fluctuations in prices Economic Co-operation and Development and exchange rates, the World Bank Atlas national accounts data. method (see box 1) of conversion is used. Technical notes 131 This method applies a conversion factor that Source: World Bank and Organisation for averages the exchange rate for a given year Economic Co-operation and Development and the two preceding years, adjusted for national accounts data. the difference between the rate of inflation in the country and that in Japan, the United Table .. Consumer price index Kingdom, the United States, and the euro Consumer price index reflects changes in the area. Growth rates are calculated by the least- cost to the average consumer of acquiring squares method (see box 2). a basket of goods and services that may be �xed or changed at speci�ed intervals, such Source: World Bank and Organisation for as yearly. The Laspeyres formula is generally Economic Co-operation and Development used. national accounts data. Source: International Monetary Fund In- Table .. Gross national income per ternational Financial Statistics database and capita, World Bank Atlas method data �les. Gross national income (GNI) per capita, World Bank Atlas method, is GNI, calculated using Table .. Price indexes the World Bank Atlas method (see box 1), di- Inflation, GDP deflator, is measured by the an- vided by midyear population. nual growth rate of the GDP implicit defla- tor and shows the rate of price change in the Source: World Bank and Organisation for economy as a whole. Economic Co-operation and Development Consumer price index is a change in the cost national accounts data. to the average consumer of acquiring a bas- ket of goods and services that may be �xed or Table .. Gross domestic product changed at speci�ed intervals, such as yearly. deflator (local currency series) The Laspeyres formula is generally used. Gross domestic product (GDP) deflator (local Exports of goods and services price index is currency series) is nominal GDP in current lo- calculated by dividing the national accounts cal currency divided by real GDP in constant exports of goods and services in current U.S. 2000 local currency, expressed as an index dollars by exports of goods and services in with base year 2000. GDP is the sum of gross constant 2000 U.S. dollars. domestic and foreign value added claimed by Imports of goods and services price index is residents plus net factor income from abroad calculated by dividing the national accounts (the income residents receive from abroad for imports of goods and services in current U.S. factor services including labor and capital) dollars by imports of goods and services in less similar payments made to nonresidents constant 2000 U.S. dollars. who contribute to the domestic economy, di- vided by midyear population. It is calculated Source: World Bank and Organisation for by the World Bank Atlas method using con- Economic Co-operation and Development stant 2000 exchange rates (see box 1). national accounts data. Source: World Bank and Organisation for Table .. Gross domestic savings Economic Co-operation and Development Gross domestic savings is calculated by de- national accounts data. ducting total consumption (table 2.17) from nominal gross domestic product (table 2.1). Table .. Gross domestic product deflator (U.S. dollar series) Source: World Bank and Organisation for Gross domestic product (GDP) deflator (U.S. Economic Co-operation and Development dollar series) is nominal GDP in current U.S. national accounts data. dollars (table 2.1) divided by real GDP in con- stant 2000 U.S. dollars (table 2.2), expressed Table .. Gross national savings as an index with base year 2000. The series Gross national savings is the sum of gross do- shows the effects of domestic price changes mestic savings (table 2.13), net factor income and exchange rate variations. from abroad, and net private transfers from 132 Africa Development Indicators 2011 abroad. Net public transfers from abroad are goods and services purchased or received as included. income in kind by households and nonpro�t institutions. It excludes purchases of dwell- Source: World Bank and Organisation for ings but includes imputed rent for owner-oc- Economic Co-operation and Development cupied dwellings. In practice, it includes any national accounts data. statistical discrepancy in the use of resources. Table .. General government final Source: World Bank and Organisation for consumption expenditure Economic Co-operation and Development General government �nal consumption expendi- national accounts data. ture is all current expenditure for purchases of goods and services by all levels of gov- Table .. Final consumption ernment, including capital expenditure on expenditure plus discrepancy per capita national defense and security. Other gov- Final consumption expenditure plus discrepancy ernment capital expenditure is included in per capita is �nal consumption expenditure capital formation. plus discrepancy in current U.S. dollars (table 2.17) divided by midyear population. Source: World Bank and Organisation for Economic Co-operation and Development Source: World Bank and Organisation for national accounts data. Economic Co-operation and Development national accounts data. Table .. Household final consumption expenditure Table .. Gross fixed capital formation Household �nal consumption expenditure (for- Gross �xed capital formation consists of gross merly private consumption) is the market domestic �xed capital formation plus net value of all goods and services, including changes in the level of inventories. Gross cap- durable products (such as cars, washing ma- ital formation comprises outlays by the pub- chines, and home computers), purchased by lic sector (table 2.20) and the private sector households. It excludes purchases of dwell- (table 2.21). Examples include improvements ings but includes imputed rent for owner- in land, dwellings, machinery, and other occupied dwellings. It also includes payments equipment. Due to statistical discrepancies, and fees to governments to obtain permits for some countries the sum of gross private and licenses. investment and gross public investment does Here, household consumption expendi- not total gross domestic investment. ture includes the expenditures of nonpro�t institutions serving households, even when Source: World Bank and Organisation for reported separately by the country. Economic Co-operation and Development national accounts data. Source: World Bank and Organisation for Economic Co-operation and Development Table .. Gross general government national accounts data. fixed capital formation Gross general government �xed capital forma- Table .. Final consumption tion is gross domestic �xed capital formation expenditure plus discrepancy (see table 2.19) for the public sector. Final consumption expenditure plus discrep- ancy (formerly total consumption) is the sum Source: World Bank and Organisation for of household �nal consumption expendi- Economic Co-operation and Development ture (table 2.16) and general government national accounts data. �nal consumption expenditure (table 2.15), shown as a share of gross domestic product. Table .. Private sector fixed capital This estimate includes any statistical discrep- formation ancy in the use of resources relative to the Private sector �xed capital formation is gross supply of resources. Private consumption, domestic �xed capital formation (see table not separately shown here, is the value of all 2.19) for the private sector. Technical notes 133 Source: World Bank and Organisation for Source: World Bank and Organisation for Economic Co-operation and Development Economic Co-operation and Development national accounts data. national accounts data. Table .. External trade balance Table .. Exports of goods and (exports minus imports) services as a share of GDP External trade balance is the difference be- Exports of goods and services represent the value tween free on board exports (table 2.23) and of all goods and other market services provided cost, insurance, and freight imports (table to the rest of the world. They include the value 2.24) of goods and services (or the difference of merchandise, freight, insurance, transport, between gross domestic savings and gross travel, royalties, license fees, and other ser- capital formation). The resource balance is vices, such as communication, construction, shown as a share of nominal gross domestic �nancial, information, business, personal, product (table 2.1). and government services. They exclude labor and property income (formerly called factor Source: World Bank and Organisation for services) as well as transfer payments and are Economic Co-operation and Development expressed as a proportion of real GDP. national accounts data. Source: World Bank and Organisation for Table .. Exports of goods and Economic Co-operation and Development services, nominal national accounts data. Exports of goods and services, nominal, rep- resent the value of all goods and other Table .. Imports of goods and market services provided to the rest of the services as a share of GDP world. They include the value of merchan- Imports of goods and services represent the value dise, freight, insurance, transport, travel, of all goods and other market services received royalties, license fees, and other services, from the rest of the world. They include the such as communication, construction, fi- value of merchandise, freight, insurance, trans- nancial, information, business, personal, port, travel, royalties, license fees, and other and government services. They exclude la- services, such as communication, construc- bor and property income (formerly called tion, �nancial, information, business, per- factor services) as well as transfer pay- sonal, and government services. They exclude ments and are expressed in current U.S. labor and property income (formerly called fac- dollars. tor services) as well as transfer payments and are expressed as a proportion of real GDP. Source: World Bank and Organisation for Economic Co-operation and Development Source: World Bank and Organisation for national accounts data. Economic Co-operation and Development national accounts data. Table .. Imports of goods and services, nominal Table .. Balance of payments and Imports of goods and services, nominal, repre- current account sent the value of all goods and other mar- Exports of goods and services represent the val- ket services received from the rest of the ue of all goods and other market services pro- world. They include the value of merchan- vided to the rest of the world. They include dise, freight, insurance, transport, travel, the value of merchandise, freight, insurance, royalties, license fees, and other services, transport, travel, royalties, license fees, and such as communication, construction, fi- other services, such as communication, con- nancial, information, business, personal, struction, �nancial, information, business, and government services. They exclude la- personal, and government services. They ex- bor and property income (formerly called clude labor and property income (formerly factor services) as well as transfer pay- called factor services) as well as transfer pay- ments and are expressed in current U.S. ments and are expressed in current U.S. dol- dollars. lars and as a proportion of real GDP. 134 Africa Development Indicators 2011 Imports of goods and services represent the goods and services in the domestic market as value of all goods and other market services a U.S. dollar would buy in the United States. received from the rest of the world. They in- Ratio of PPP conversion factor to market ex- clude the value of merchandise, freight, in- change rate is the national price level, making surance, transport, travel, royalties, license it possible to compare across countries the fees, and other services, such as commu- costs of the bundle of goods that make up nication, construction, �nancial, informa- gross domestic product. tion, business, personal, and government Real effective exchange rate is the nominal services. They exclude labor and property effective exchange rate (a measure of the income (formerly called factor services) as value of a currency against a weighted aver- well as transfer payments and are expressed age of several foreign currencies) divided by a in current U.S. dollars and as a proportion price deflator or index of costs. of real GDP. Gross domestic product (GDP), PPP, is gross Total trade is the sum of exports and im- domestic product converted to international ports of goods and services. dollars using purchasing power parity rates. Net income is the receipts and payments of An international dollar has the same pur- employee compensation paid to nonresident chasing power over GDP as the U.S. dollar workers and investment income (receipts has in the United States. GDP is the sum of and payments on direct investment, portfo- gross value added by all resident producers in lio investment, other investments, and re- the economy plus any product taxes and mi- ceipts on reserve assets). nus any subsidies not included in the value of Net current transfers are recorded in the the products. balance of payments whenever an economy It is calculated without making deductions provides or receives goods, services, income, for depreciation of fabricated assets or for de- or �nancial items without a quid pro quo. pletion and degradation of natural resources. Current account balance is the sum of net Gross domestic product (GDP) per capita, exports of goods, services, net income, and PPP, is GDP per capita based on purchasing net current transfers. All transfers not con- power parity (PPP). PPP GDP is gross domes- sidered to be capital are current. tic product converted to international dollars Total reserves including gold are the holdings using purchasing power parity rates. An in- of monetary gold, special drawing rights, ternational dollar has the same purchasing reserves of International Monetary Fund power over GDP as the U.S. dollar has in the (IMF) members held by the IMF, and hold- United States. GDP at purchaser prices is the ings of foreign exchange under the control of sum of gross value added by all resident pro- monetary authorities. ducers in the economy plus any product taxes and minus any subsidies not included in the Source: Data on exports and imports of value of the products. It is calculated without goods and services are from World Bank and making deductions for depreciation of fabri- Organisation for Economic Co-operation and cated assets or for depletion and degradation Development national accounts data. Data of natural resources. on net income, net current transfers, current account balance, and total reserves are from Source: International Monetary Fund In- the IMF International Financial Statistics da- ternational Financial Statistics database. tabase and data �les. Data on PPP are from the World Bank Inter- national Comparison Program database. Table .. Exchange rates and purchasing power parity Table .. Agriculture value added Official exchange rate is the exchange rate Agriculture value added is the gross output of determined by national authorities or the forestry, hunting, and �shing, as well as crop rate determined in the legally sanctioned ex- cultivation and livestock production (Inter- change market. national Standard Industrial Classi�cation Purchasing power parity (PPP) conversion [ISIC] revision 3 divisions 1–5) less the value factor is the number of units of a country’s of their intermediate inputs. It is calculated currency required to buy the same amount of without making deductions for depreciation Technical notes 135 of fabricated assets or depletion and degrada- activity, including wholesale and retail trade tion of natural resources. For countries that (including hotels and restaurants), transport, report national accounts data at producer and government, �nancial, professional, and prices (Angola, Benin, Cape Verde, Comoros, personal services, such as education, health the Republic of Congo, Côte d’Ivoire, Gabon, care, and real estate (International Standard Ghana, Liberia, Niger, Rwanda, São Tomé Industrial Classi�cation revision 3 divisions and Príncipe, Seychelles, Togo, and Tunisia), 50–99), less the value of their intermediate gross value added at market prices is used as inputs. Also included are imputed bank ser- the denominator. For countries that report vice charges, import duties, and any statisti- national accounts data at basic prices (all oth- cal discrepancies noted by national compil- er countries), gross value added at factor cost ers or arising from rescaling. It is calculated is used as the denominator. Value added at without making deductions for depreciation basic prices excludes net taxes on products; of fabricated assets or depletion and degrada- value added at producer prices includes net tion of natural resources. For countries that taxes on products paid by producers but ex- report national accounts data at producer cludes sales or value added taxes. prices (Angola, Benin, Cape Verde, Comoros, the Republic of Congo, Côte d’Ivoire, Gabon, Source: World Bank and Organisation for Ghana, Liberia, Niger, Rwanda, São Tomé Economic Co-operation and Development and Príncipe, Seychelles, Togo, and Tunisia), national accounts data �les. gross value added at market prices is used as the denominator. For countries that report Table .. Industry value added national accounts data at basic prices (all oth- Industry value added is the gross output of er countries), gross value added at factor cost mining, manufacturing, construction, elec- is used as the denominator. Value added at tricity, water, and gas (International Standard basic prices excludes net taxes on products; Industrial Classi�cation revision 3 divisions value added at producer prices includes net 10– 45) less the value of their intermediate taxes on products paid by producers but ex- inputs. It is calculated without making de- cludes sales or value added taxes. ductions for depreciation of fabricated as- sets or depletion and degradation of natural Source: World Bank and Organisation for resources For countries that report national Economic Co-operation and Development accounts data at producer prices (Angola, national accounts data �les. Benin, Cape Verde, Comoros, the Republic of Congo, Côte d’Ivoire, Gabon, Ghana, Liberia, Table .. Central government Niger, Rwanda, São Tomé and Príncipe, Sey- finances, expense, and revenue chelles, Togo, and Tunisia), gross value added Revenue, excluding grants, is cash receipts at market prices is used as the denominator. from taxes, social contributions, and other For countries that report national accounts revenues, such as �nes, fees, rent, and in- data at basic prices (all other countries), gross come from property or sales. Grants are also value added at factor cost is used as the de- considered as revenue but are excluded here. nominator. Value added at basic prices ex- Expense is cash payments for operating ac- cludes net taxes on products; value added at tivities of the government in providing goods producer prices includes net taxes on prod- and services. It includes compensation of ucts paid by producers but excludes sales or employees (such as wages and salaries), inter- value added taxes. est and subsidies, grants, social bene�ts, and other expenses such as rent and dividends. Source: World Bank and Organisation for Cash surplus or de�cit is revenue (including Economic Co-operation and Development grants) minus expense, minus net acquisi- national accounts data �les. tion of non�nancial assets. In the 1986 Gov- ernment Finance Statistics Manual non�nan- Table .. Services plus discrepancy cial assets were included under revenue and value added expenditure in gross terms. This cash surplus Services plus discrepancy value added is the or de�cit is closest to the earlier overall bud- gross output of all other branches of economic get balance (still missing is lending minus 136 Africa Development Indicators 2011 repayments, which are now a �nancing item including provision for consumption of �xed under net acquisition of �nancial assets). capital. Net incurrence of liabilities is domestic �- Interest payments (revenue) include interest nancing (obtained from residents) and for- payments on government debt—including eign �nancing (obtained from nonresidents), long-term bonds, long-term loans, and other or the means by which a government pro- debt instruments—to domestic and foreign vides �nancial resources to cover a budget residents, expressed as a proportion of revenue. de�cit or allocates �nancial resources arising Taxes on income, pro�ts, and capital gains are from a budget surplus. The net incurrence of levied on the actual or presumptive net in- liabilities should be offset by the net acqui- come of individuals, on the pro�ts of corpo- sition of �nancial assets (a third �nancing rations and enterprises, and on capital gains, item). The difference between the cash sur- whether realized or not, on land, securities, plus or de�cit and the three �nancing items and other assets. Intragovernmental pay- is the net change in the stock of cash. ments are eliminated in consolidation. Total debt is the entire stock of direct gov- Taxes on goods and services include general ernment �xed-term contractual obligations sales and turnover or value added taxes, se- to others outstanding on a particular date. It lective excises on goods, selective taxes on includes domestic and foreign liabilities such services, taxes on the use of goods or prop- as currency and money deposits, securities erty, taxes on extraction and production of other than shares, and loans. It is the gross minerals, and pro�ts of �scal monopolies. amount of government liabilities minus the Taxes on international trade include import amount of equity and �nancial derivatives duties, export duties, pro�ts of export or im- held by the government. Because debt is a port monopolies, exchange pro�ts, and ex- stock rather than a flow, it is measured as of change taxes. a given date, usually the last day of the �scal Other taxes include employer payroll or la- year. bor taxes, taxes on property, and taxes not al- Goods and services include all government locable to other categories, such as penalties payments in exchange for goods and services for late payment or nonpayment of taxes. used for the production of market and non- Social contributions include social security market goods and services. Own-account contributions by employees, employers, and capital formation is excluded. self-employed individuals, and other contri- Compensation of employees consists of all butions whose source cannot be determined. payments in cash and in kind (such as food They also include actual or imputed contribu- and housing) to employees in return for tions to social insurance schemes operated services rendered and of government con- by governments. tributions to social insurance schemes such Grants and other revenue include grants as social security and pensions that provide from other foreign governments, interna- bene�ts to employees. tional organizations, and other government Interest payments (expense) include interest units; interest; dividends; rent; requited, non- payments on government debt—including repayable receipts for public purposes (such long-term bonds, long-term loans, and other as �nes, administrative fees, and entrepre- debt instruments—to domestic and for- neurial income from government ownership eign residents, expressed as a proportion of of property); and voluntary, unrequited, non- expense. repayable receipts other than grants. Subsidies and other transfers include all un- requited, nonrepayable transfers on current Source: International Monetary Fund, Gov- accounts to private and public enterprises; ernment Finance Statistics Yearbook and data grants to foreign governments, international �les, and World Bank and Organisation for organizations, and other government units; Economic Co-operation and Development and social security, social assistance bene�ts, GDP estimates. and employer social bene�ts in cash and in kind. Table .. Structure of demand Other expenses are spending on dividends, Household �nal consumption expenditure (for- rent, and other miscellaneous expenses, merly private consumption) is the market Technical notes 137 value of all goods and services, including rates in this edition cannot be compared with durable products (such as cars, washing ma- those in editions before 2009. chines, and home computers), purchased by Poverty gap ratio at PPP $1.25 a day is the households. mean shortfall from the poverty line (count- General government �nal consumption ex- ing the nonpoor as having zero shortfall), ex- penditure (formerly general government con- pressed as a percentage of the poverty line. sumption) is all government current expen- This measure reflects the depth of poverty as ditures for purchases of goods and services. well as its incidence. Gross �xed capital formation (formerly gross Share of population below PPP $2 a day is the domestic investment) consists of outlays on percentage of the population living on less additions to the �xed assets of the economy than $2 a day at 2005 international prices. plus net changes in the level of inventories. As a result of revisions in PPP exchange rates, Exports of goods and services represent the poverty rates in this edition cannot be com- value of all goods and other market services pared with those in editions before 2009. provided to the rest of the world. They in- Poverty gap ratio at PPP $2 a day is the mean clude the value of merchandise, freight, in- shortfall from the poverty line (counting the surance, transport, travel, royalties, license nonpoor as having zero shortfall), expressed fees, and other services, such as communi- as a percentage of the poverty line. This mea- cation, construction, �nancial, information, sure reflects the depth of poverty as well as business, personal, and government services. its incidence. They exclude labor and property income (for- Share of population below national poverty merly called factor services) as well as transfer line (poverty headcount ratio) is the percentage payments and are expressed as a proportion of the population living below the national of real GDP. poverty line. National estimates are based Imports of goods and services represent the on population-weighted subgroup estimates value of all goods and other market services from household surveys. received from the rest of the world. They in- Share of poorest quintile in national consump- clude the value of merchandise, freight, in- tion or income is the share of consumption, or surance, transport, travel, royalties, license in some cases income, that accrues to the fees, and other services, such as communi- poorest 20 percent of the population. cation, construction, �nancial, information, Prevalence of child malnutrition, under- business, personal, and government services. weight, is the percentage of children under They exclude labor and property income (for- age 5 whose weight for age is more than two merly called factor services) as well as trans- standard deviations below the median for the fer payments and are expressed as a propor- international reference population ages 0–59 tion of real GDP. months. The reference population, adopted Gross national savings is the gross nation- by the World Health Organization in 1983, al income less total consumption, plus net is based on children from the United States, transfers. who are assumed to be well nourished. Population below minimum dietary energy Source: World Bank and Organisation for consumption (also referred to as prevalence of Economic Co-operation and Development undernourishment) is the population whose national accounts data �les. dietary energy consumption is continuously below a minimum dietary energy require- 3. Millennium Development Goals ment for maintaining a healthy life and car- rying out a light physical activity with an ac- Table .. Millennium Development ceptable minimum bodyweight for attained Goal : eradicate extreme poverty and height. hunger Share of population below PPP $1.25 a day is Source: Data on poverty are from the World the percentage of the population living on Bank Development Research Group. Data are less than $1.25 a day at 2005 international based on primary household survey data prices. As a result of revisions in purchasing obtained from government statistical agen- power parity (PPP) exchange rates, poverty cies and World Bank country departments 138 Africa Development Indicators 2011 Multidimensional indices of poverty Quy-Toan Do In developing countries, poverty measures are among the main The relevance and credibility of multidimensional indices of indicators of economic development and progress in alleviating poverty therefore depend crucially on the choice of social weights poverty. But poverty is multidimensional, and no single indicator assigned to each dimension of poverty (Alkire and others 2000). can adequately capture all its aspects. To do so, poverty measures On one hand, weights need to be sufficiently flexible to reflect must be sufficiently informative on social welfare and comparable a social welfare function that varies both over time and across over time and across space. The World Bank uses consumption space; on the other, the choice of welfare weights is politically poverty as its main index and sets the poverty line at $1.25 (in 2005 charged, so governments might not be able to afford such flex- purchasing power parity [PPP] terms; Chen and others 2008) per ibility without undermining the legitimacy of their choices. Gov- person per day; an alternative poverty line at $2 (2005 PPP) per ernments need transparency and accountability so that they can person per day measures extreme poverty. Consumption poverty produce an index that fully reflects social welfare. Then, if these alone does not give a full picture of a country’s economic condi- weights do not correspond to societal preferences, aggregating tion, let alone the priorities governments should set in their efforts consumption poverty and life expectancy into a single index will to alleviate poverty. Health, education, wealth inequality, and gen- not reduce the dimensionality of the problem at hand. A multidi- der equality are just some of the dimensions of poverty not fully mensional index of poverty constructed from consumption pov- captured. These topics are covered by the Millennium Develop- erty and life expectancy will still need to be complemented by ment Goals—in addition to poverty and hunger—ensuring that they those same indices of consumption poverty (or life expectancy) will receive international attention. to provide a full picture of social welfare, a prerequisite for policy A multidimensional index of poverty attempts to capture vari- decisions. The usefulness of such aggregation effort must then ous dimensions of welfare (Alkire and Foster 2007; Alkire and oth- be revisited. ers 2010). Can a single indicator combining measures of health and education, consumption poverty, and gender inequality be References sufficiently informative on social welfare to be policy relevant? The Alkire, Sabina, and James Foster. 2007. “Counting and Multidi- conceptual issues underlying the construction of these indices mensional Poverty Measurement.� Working Paper 7, Oxford are not new (see Ravallion 2010, 2011 for a discussion), and mea- Poverty and Human Development Initiative, University of sures of consumption poverty face similar challenges, but they Oxford. differ from multidimensional indices of poverty, especially in the Alkire, Sabina, and Maria Emma Santos. 2010. Acute Multidimen- assumptions underlying the aggregation of information. sional Poverty: A New Index for Developing Countries. Oxford, Constructing consumption poverty measures requires an ad- UK: University of Oxford, Oxford Poverty & Human Develop- equate protocol to aggregate several varieties into one measure. ment Initiative, Oxford Department of International Develop- The consumption aggregate rightly captures social welfare if the ment, Queen Elizabeth House. weights given to each variety consumed reflect societal prefer- Alkire, Sabina, Maria Emma Santos, Suman Seth, and Gatson Ya- ences. When goods making the consumption poverty index are lonetzky. 2010. Is the Multidimensional Poverty Index Robust marketable and markets are functioning properly, market prices to Different Weights? Oxford, UK: University of Oxford, Ox- reflect the weights that the consumption of these items have in the ford Poverty & Human Development Initiative, Queen Eliza- social welfare function. Thus, theoretically, all expenditure levels of beth House. marketable items can be aggregated into one index of consump- Chen, Shaohua, and Martin Ravallion. 2008. “The Developing tion that fully reflects social welfare. World is Poorer than We Thought, but No Less Successful Multidimensional indices of poverty extend this approach by in the Fight against Poverty.� Policy Research Working Paper adding the consumption of nonmarketable items. The key assump- 4703, World Bank, Washington, DC. tions underlying the construction of these indexes thus relate to the Deaton, A., and S. Zaidi. 2002. “A Guide to Aggregating Consump- weights (or prices) assigned to nonmarketable items entering into tion Expenditures.� Living Standards Measurement Study the aggregation. For example, how does one compare an individual Working Paper 135, World Bank, Washington, DC. with a $2 daily consumption level and a 75-year life expectancy with Hentschel, J., and P. Lanjouw. 1996. “Constructing an Indicator of an individual with a $3 daily consumption level but a 60-year life Consumption for the Analysis of Poverty.� Living Standards expectancy? In a perfect “market for life expectancy,� one could ob- Measurement Study Working Paper 124, World Bank, Wash- serve how much individuals might pay for a longer life expectancy, ington, DC. and assuming market perfection, willingness to pay would capture Ravallion, M. 2010. “Mashup Indices of Development.� Policy Re- the social weight of life expectancy in consumption terms. However, search Working Paper 5432, World Bank, Washington, DC. without observable prices, policymakers will need to choose social Ravallion, M. 2011. “On Multidimensional Indices of Poverty.� Jour- weights, an exercise highly arbitrary and subject to political capture. nal of Economic Inequality 9 (2): 235–248. Technical notes 139 (http://iresearch.worldbank.org/PovcalNet/ those published on the United Nations Mil- jsp/index.jsp). Data on national poverty are lennium Development Goals website (www. from the Global Poverty Working Group un.org/millenniumgoals), but some differenc- and are based on World Bank country pov- es in timing, sources, and de�nitions remain. erty assessments and country poverty re- duction strategies. Efforts have been made Table .. Millennium Development to harmonize these data series with those Goal : promote gender equality and published on the United Nations Millen- empower women nium Development Goals website (www. Ratio of girls to boys in primary and secondary un.org/millenniumgoals), but some differ- school is the ratio of female to male gross en- ences in timing, sources, and de�nitions re- rollment rate in primary and secondary school. main. Data on child malnutrition are from Ratio of literate young women to men is the World Health Organization Global Database ratio of the female youth literacy rate to the on Child Growth and Malnutrition. Data on male youth literacy rate. population below minimum dietary energy Women in national parliament are the per- consumption are from the Food and Agricul- centage of parliamentary seats in a single or ture Organization (www.fao.org/economic/ lower chamber occupied by women. ess/food-security-statistics/en/). Share of women employed in the nonagricul- tural sector is women wage employees in the Table .. Millennium Development nonagricultural sector as a share of total non- Goal : achieve universal primary agricultural employment. education Primary education provides children with ba- Source: Data on net enrollment and litera- sic reading, writing, and mathematics skills, cy are from the United Nations Educational, along with an elementary understanding of Scienti�c and Cultural Organization Insti- such subjects as history, geography, natural tute for Statistics. Data on women in nation- science, social science, art, and music. al parliaments are from the Inter-Parliamen- Net primary enrollment ratio is the ratio of tary Union Parline database (www.ipu.org). children of official primary school age, based Data on women’s employment are from the on the International Standard Classi�cation International Labour Organization Key Indi- of Education 1997, who are enrolled in pri- cators of the Labour Market database. mary school to the population of the corre- sponding official primary school age. Table .. Millennium Development Primary completion rate is the percentage of Goal : reduce child mortality students completing the last year of primary Under-�ve mortality rate is the probability school. It is calculated as the total number of that a newborn baby will die before reaching students in the last grade of primary school age 5, if subject to current age-speci�c mor- minus the number of repeaters in that grade tality rates. The probability is expressed as a divided by the total number of children of of- rate per 1,000. �cial graduation age. Infant mortality rate is the number of in- Share of cohort reaching grade 5 is the per- fants dying before reaching one year of age, centage of children enrolled in grade 1 of per 1,000 live births. primary school who eventually reach grade 5. Child immunization rate, measles, is the per- The estimate is based on the reconstructed centage of children ages 12–23 months who cohort method. received vaccinations for measles before 12 Youth literacy rate is the percentage of peo- months or at any time before the survey. A ple ages 15–24 who can, with understanding, child is considered adequately immunized both read and write a short, simple state- against measles after receiving one dose of ment about their everyday life. vaccine. Source: Data are from the United Nations Source: Data on under-�ve and infant Educational, Scienti�c and Cultural Organiza- mortality are from the Inter-agency Group tion Institute for Statistics. Efforts have been for Child Mortality Estimation Level & made to harmonize these data series with Trends in Child Mortality: Report 2010, based 140 Africa Development Indicators 2011 mainly on household surveys, censuses, Children sleeping under insecticide-treated and vital registration, supplemented by the nets are the percentage of children under age World Bank Human Development Network 5 with access to an insecticide-treated net to and Development Data Group estimates prevent malaria. based on vital registration and sample reg- Incidence of tuberculosis is the estimated istration. Data on child immunization are number of new tuberculosis cases (pulmo- from the World Health Organization and nary, smear positive, and extrapulmonary), the United Nations Children’s Fund (www.who. per 100,000 people. int/immunization_monitoring/routine/ Tuberculosis treatment success rate is the en/). percentage of new, registered smear-positive (infectious) cases that were cured or in which Table .. Millennium Development a full course of treatment was completed. Goal : improve maternal health Maternal mortality ratio, modeled estimate, is Source: Data on HIV prevalence are from the number of women who die from preg- the Joint United Nations Programme on nancy-related causes during pregnancy and HIV/AIDS and the World Health Organiza- childbirth, per 100,000 live births. Data are tion (WHO) Report on the Global AIDS Epi- estimated by a regression model using in- demic. Data on contraceptive use are from formation on fertility, birth attendants, and household surveys, including Demographic HIV prevalence. and Health Surveys by Macro International Maternal mortality ratio, national estimate, and Multiple Indicator Cluster Surveys by the is the number of women who die during United Nations Children’s Fund (UNICEF). pregnancy and childbirth, per 100,000 live Data on insecticide-treated net use are from births. UNICEF State of the World’s Children and Births attended by skilled health staff are the Childinfo and from Demographic and Health percentage of deliveries attended by person- Surveys by Macro International. Data on tu- nel who are trained to give the necessary su- berculosis are from the WHO Global Tubercu- pervision, care, and advice to women during losis Control Report. pregnancy, labor, and the postpartum period; to conduct deliveries on their own; and to Table .. Millennium Development care for newborns. Goal : ensure environment sustainability Source: Data on maternal mortality (mod- Forest area is land under natural or planted eled) are from the World Health Organization, stands of trees, whether productive or not. United Nations Children’s Fund (UNICEF), Terrestrial protected areas are those official- United Nations Population Fund, and the ly documented by national authorities. World Bank Trends in Maternal Mortal- Gross domestic product (GDP) per unit of ity: 1990–2008. Data on maternal mortal- energy use is the GDP in purchasing power ity (national) and births attended by skilled parity (PPP) U.S. dollars per kilogram of oil health staff are from UNICEF State of the equivalent of energy use. PPP GDP is gross World’s Children and Childinfo and from domestic product converted to 2000 con- Demographic and Health Surveys by Macro stant international dollars using PPP rates. International. An international dollar has the same pur- chasing power over GDP as a U.S. dollar has Table .. Millennium Development in the United States. Goal : combat HIV/AIDS, malaria, and Carbon dioxide emissions per capita are those other diseases stemming from the burning of fossil fuels Prevalence of HIV is the percentage of people and the manufacture of cement divided by ages 15–49 who are infected with HIV. midyear population. They include carbon di- Contraceptive use, any method, is the per- oxide produced during consumption of solid, centage of women ages 15–49, married liquid, and gas fuels and gas flaring. or in union, who are practicing, or whose Population with sustainable access to an sexual partners are practicing, any form of improved water source is the percentage of contraception. the population with reasonable access to an Technical notes 141 adequate amount of water from an improved develop and implement a poverty reduction source, such as a household connection, strategy. public standpipe, borehole, protected well or HIPC Debt Initiative completion point is the spring, or rainwater collection. Unimproved a country successfully completes the key sources include vendors, tanker trucks, and structural reforms agreed on at the decision unprotected wells and springs. Reasonable point, including developing and implement- access is de�ned as the availability of at least ing its poverty reduction strategy. The coun- 20 liters a person a day from a source within try then receives the bulk of debt relief un- 1 kilometer of the dwelling. der the HIPC Debt Initiative without further Population with sustainable access to im- policy conditions. proved sanitation is the percentage of the Debt service relief committed is the amount population with at least adequate access to of debt service relief, calculated at the En- excreta disposal facilities that can effectively hanced HIPC Initiative decision point, prevent human, animal, and insect contact that will allow the country to achieve debt with excreta. Improved facilities range from sustainability at the completion point. simple but protected pit latrines to flush toi- Public and publicly guaranteed debt service is lets with a sewerage connection. The excreta the sum of principal repayments and inter- disposal system is considered adequate if it est actually paid in foreign currency, goods, is private or shared (but not public) and if it or services on long-term obligations of pub- hygienically separates human excreta from lic debtors and long-term private obligations human contact. To be effective, facilities guaranteed by a public entity. Exports refer must be correctly constructed and properly to exports of goods, services, and income. maintained. Worker remittances are not included here, though they are included with income re- Source: Data on forest area are from the ceipts in other World Bank publications, such Food and Agricultural Organization Global as Global Development Finance. Forest Resources Assessment. Data on nation- Youth unemployment rate is the percentage ally protected areas are from the United of the labor force ages 15–24 without work Nations Environment Programme and the but available for and seeking employment. World Conservation Monitoring Centre, as De�nitions of labor force and unemploy- compiled by the World Resources Institute, ment may differ by country. and based on data from national authori- Fixed-line and mobile telephone subscribers ties, national legislation, and international are subscribers to a �xed-line telephone ser- agreements. Data on energy use are from vice, which connects a customer’s equipment electronic �les of the International Energy to the public switched telephone network, or Agency. Data on carbon dioxide emissions to a public mobile telephone service, which are from the Carbon Dioxide Information uses cellular technology. Analysis Center, Environmental Sciences Di- Personal computers are self-contained com- vision, Oak Ridge National Laboratory. Data puters designed for use by a single individual. on access to water and sanitation are from Internet users are people with access to the the World Health Organization and United Internet. Nations Children’s Fund Joint Monitoring Programme (www.wssinfo.org). Source: Data on HIPC countries are from the International Development Association Table .. Millennium Development and International Monetary Fund “Heavily Goal : develop a global partnership Indebted Poor Countries (HIPC) Initiative for development and Multilateral Debt Relief Initiative— Heavily Indebted Poor Countries (HIPC) Debt Status of Implementation.� Data on external Initiative decision point is the date at which debt are mainly from reports to the World a HIPC with an established track record of Bank through its Debtor Reporting System good performance under adjustment pro- from member countries that have received grams supported by the International Mon- International Bank for Reconstruction and etary Fund (IMF) and the World Bank com- Development loans or International Devel- mits to undertake additional reforms and to opment Association credits, as well as from 142 Africa Development Indicators 2011 World Bank and IMF �les. Data on youth Number of procedures to enforce a contract is unemployment are from the International the number of independent actions, mandat- Labour Organization Key Indicators of the ed by law or courts, that demand interaction Labour Market database. Data on telephone between the parties of a contract or between subscribers, personal computers, and Inter- them and the judge or court officer. net users are from the International Tele- Time required to enforce a contract is the communication Union World Telecommunica- number of calendar days from the �ling of tion/ICT Development Report and database, the lawsuit in court until the �nal determina- and from World Bank estimates. tion and, in appropriate cases, payment. Cost to enforce a contract is court and attor- 4. Private sector development ney fees, where the use of attorneys is man- datory or common, or the cost of an adminis- Table .. Doing Business indicators trative debt recovery procedure, expressed as Number of startup procedures to start a business a percentage of the debt value. is the number of procedures required to start Number of procedures to deal with construc- a business, including interactions to obtain tion permits is the number of procedures re- necessary permits and licenses and to com- quired to obtain construction-related permits. plete all inscriptions, veri�cations, and noti- Time required to deal with construction per- �cations to start operations. mits is the average wait, in days, to obtain a Time required for each procedure to start construction-related permit, from the day a business is the number of calendar days the establishment applied for it to the day it needed to complete each procedure to legally was granted. operate a business. If a procedure can be sped Cost to deal with construction permits is all up at additional cost, the fastest procedure, the fees associated with completing the pro- independent of cost, is chosen. cedures to legally build a warehouse, includ- Cost to start a business is normalized by ing those associated with obtaining land use presenting it as a percentage of gross nation- approvals and reconstruction design clear- al income (GNI) per capita. ances; receiving inspections before, during, Minimum capital is the paid-in minimum and after construction; getting utility con- capital requirement, which reflects the nections; and registering the warehouse amount an entrepreneur needs to deposit in property. Nonrecurring taxes required for a bank or with a notary before registration the completion of the warehouse project also and up to three months following incorpo- are recorded. The building code, information ration. It is reported as a percentage of the from local experts, and speci�c regulations country’s income per capita. and fee schedules are used as sources for Number of procedures to register property is costs. If several local partners provide dif- the number of procedures required for a busi- ferent estimates, the median reported value ness to secure rights to property. is used. It is reported as a percentage of the Time required to register property is the country’s income per capita. number of calendar days needed for a busi- Disclosure index measures the degree to ness to secure rights to property. which investors are protected through disclo- Cost to register property is the official costs sure of ownership and �nancial information. required by law to register a property, includ- Higher values indicate more disclosure. ing fees, transfer taxes, stamp duties, and Director liability index measures a plain- any other payment to the property registry, tiff ’s ability to hold directors of �rms liable notaries, public agencies, and lawyers. Other for damages to the company. Higher values taxes, such as capital gains tax or value added indicate greater liability. tax, are excluded from the cost measure. Both Shareholder suits index measures share- costs borne by the buyer and those borne by holders’ ability to sue officers and direc- the seller are included. If cost estimates differ tors for misconduct. Higher values indicate across sources, the median reported value is greater power for shareholders to challenge used. It is reported as a percentage of prop- transactions. erty value, which is assumed to be equivalent Investor protection index measures the de- to 50 times income per capita. gree to which investors are protected through Technical notes 143 disclosure of ownership and �nancial informa- Firing cost indicates the notice require- tion regulations. It is the average of the disclo- ments, severance, payments, and penalties sure, director liability, and shareholder suits in- due when terminating a redundant worker, dexes. Higher values indicate better protection. expressed in weeks of salary. Rigidity of hours index, a measure of em- Rigidity of employment index measures the ployment regulation, is an average of scores regulation of employment, speci�cally the in �ve areas: whether night work is unre- hiring and �ring of workers and the rigidity stricted, whether weekend work is unrestrict- of working hours. This index is the average of ed, whether the work week can consist of 5.5 three subindexes: the rigidity of hours index, days, whether the workweek can extend to the difficulty of hiring index, and the diffi- 50 hours or more (including overtime) for culty of �ring index. two months a year to respond to a seasonal increase in production, and whether paid an- Source: Data are from the World Bank Do- nual vacation is 21 working days or fewer. ing Business project (http://rru.worldbank. For each question the answer no is assigned a org/DoingBusiness/). score of 1 and the answer yes a 0. Difficulty of hiring index indicates the appli- Table .. Investment climate cability and maximum duration of �xed-term Private sector �xed capital formation is private contracts and minimum wage for a trainee or sector �xed capital formation (table 2.21) �rst-time employee. It measures whether divided by nominal gross domestic product �xed-term contracts are prohibited for per- (table 2.1). manent tasks, the maximum cumulative du- Net foreign direct investment is net inflows ration of �xed-term contracts, and the ratio of investment to acquire a lasting manage- of the minimum wage for a trainee or �rst ment interest (10 percent or more of vot- time employee to the average value added ing stock) in an enterprise operating in an per worker. economy other than that of the investor. It Difficulty of �ring index indicates the extent is the sum of equity capital, reinvestment of noti�cation and approval requirements for of earnings, other long-term capital, and termination of a redundant worker or group short-term capital as shown in the balance of redundant workers, obligation to reassign of payments. This series shows net inflows or retrain, and priority rules for redundancy (new investment inflows less disinvest- and reemployment. It has eight components: ment) in the reporting economy from for- whether redundancy is disallowed as a basis eign investors. for terminating workers, whether the em- Domestic credit to private sector is �nancial ployer needs to notify a third party (such as resources provided to the private sector, such a government agency) to terminate 1 redun- as through loans, purchases of nonequity dant worker, whether the employer needs securities, and trade credits and other ac- to notify a third party to terminate a group counts receivable that establish a claim for of 25 redundant workers, whether the em- repayment. For some countries these claims ployer needs approval from a third party to include credit to public enterprises. terminate 1 redundant worker, whether the Firms that believe the court system is fair, employer needs approval from a third party impartial, and uncorrupt are the percentage to terminate a group of 25 redundant work- of �rms that believe the court system is fair, ers, whether the law requires the employer to impartial, and uncorrupt. reassign or retrain a worker before making Corruption is the percentage of �rms iden- the worker redundant, whether priority rules tifying corruption as a major constraint to apply for redundancies, and whether priority current operation. rules apply for reemployment. For the �rst Crime, theft, and disorder are the percent- question the answer yes is assigned a score age of �rms identifying crime, theft, and of 10, and the rest of the questions do not disorder as a major constraint to current apply. For the fourth question the answer yes operation. is assigned a score of 2 and the answer no a 0. Tax rates are the percentage of �rms iden- For every other question the answer yes is as- tifying tax rates as a major constraint to cur- signed a score of 1 and the answer no a 0. rent operation. 144 Africa Development Indicators 2011 Finance is the percentage of �rms identify- commercial or similar banks for demand, ing access to �nance or cost of �nance as a time, or savings deposits. major constraint to current operation. Listed domestic companies are domestically Electricity is the percentage of �rms identi- incorporated companies listed on a coun- fying electricity as a major constraint to cur- try’s stock exchanges at the end of the year. rent operation. They exclude investment companies, mu- Labor regulations are the percentage of tual funds, and other collective investment �rms identifying labor regulations as a major vehicles. constraint to current operation. Market capitalization of listed companies, Labor skills are the percentage of �rms also known as market value, is the share price identifying skills of available workers as a of a listed domestic company’s stock times major constraint to current operation. the number of shares outstanding. Transportation is the percentage of �rms Turnover ratio for traded stocks is the total identifying transportation as a major con- value of shares traded during the period di- straint to current operation. vided by the average market capitalization Customs and trade regulations are the per- for the period. Average market capitalization centage of �rms identifying customs and is calculated as the average of the end-of- trade regulations as a major constraint to period values for the current period and the current operation. previous period. Number of tax payments is the number of taxes paid by businesses, including by elec- Source: Data on private sector �xed capital tronic �ling. The tax is counted as paid once formation are from the World Bank World a year even if payments are more frequent. Development Indicators database. Data on Time to prepare, �le, and pay taxes is the net foreign direct investment are from the number of hours it takes to prepare, �le, and International Monetary Fund (IMF) Bal- pay (or withhold) three major types of taxes: ance of Payments database, supplemented the corporate income tax, the value added or by data from the United Nations Confer- sales tax, and labor taxes, including payroll ence on Trade and Development and official taxes and social security contributions. national sources. Data on domestic credit to Total tax rate is the total amount of taxes the private sector are from the International payable by the business (except for labor Monetary Fund International Financial Sta- taxes) after accounting for deductions and tistics database and data �les, World Bank exemptions as a percentage of pro�t. and Organisation for Economic Co-operation Highest marginal tax rate, corporate, is and Development gross domestic product the highest rate shown on the schedule of (GDP) estimates, and the World Bank World tax rates applied to the taxable income of Development Indicators database. Data on corporations. investment climate constraints to �rms are Time dealing with officials is the average per- based on enterprise surveys conducted by centage of senior management’s time that is the World Bank and its partners (http://rru. spent in a typical week dealing with require- worldbank.org/EnterpriseSurveys). Data on ments imposed by government regulations regulation and tax administration and high- (for example, taxes, customs, labor regula- est marginal corporate tax rates are from the tions, licensing, and registration), including World Bank Doing Business project (http:// dealings with officials, completing forms, and rru.worldbank.org/DoingBusiness). Data the like. on time dealing with officials and average Average time to clear customs, direct exports, time to clear customs are from World Bank is the average number of days to clear direct Enterprise Surveys (http://rru.worldbank. exports through customs. org/EnterpriseSurveys/). Data on interest Average time to clear customs, imports, is rate spreads are from the IMF International the average number of days to clear imports Financial Statistics database and data �les through customs. and the World Bank World Development Interest rate spread is the interest rate Indicators database. Data on listed domestic charged by banks on loans to prime cus- companies, turnover ratios for traded stocks, tomers minus the interest rate paid by and market capitalization are from Standard Technical notes 145 & Poor’s Global Stock Markets Factbook and provisions). The loan amount recorded as supplemental Standard & Poor’s data. nonperforming should be the gross value of the loan as recorded on the balance sheet, Table .. Financial sector not just the amount overdue. infrastructure Listed domestic companies are domestically Foreign currency sovereign ratings are long- and incorporated companies listed on a coun- short-term foreign currency ratings that as- try’s stock exchanges at the end of the year. sess a sovereign’s capacity and willingness They exclude investment companies, mu- to honor in full and on time its existing and tual funds, and other collective investment future obligations issued in foreign curren- vehicles. cies. Short-term ratings have a time horizon Market capitalization of listed companies, of less than 13 months for most obligations, also known as market value, is the share price or up to 3 years for U.S. public �nance, in line of a listed domestic company’s stock times with industry standards, to reflect the unique the number of shares outstanding. risk characteristics of bond, tax, and revenue Turnover ratio for traded stocks is the total anticipation notes that are commonly issued value of shares traded during the period di- with terms up to 3 years. Short-term ratings vided by the average market capitalization thus place greater emphasis on the liquidity for the period. Average market capitalization necessary to meet �nancial commitments in is calculated as the average of the end-of- a timely manner. period values for the current period and the Gross national savings is the sum of gross previous period. domestic savings (table 2.13) and net fac- tor income and net private transfers from Source: Data on foreign currency sovereign abroad. The estimate here also includes net ratings are from Fitch Ratings (www.�tchrat- public transfers from abroad. ings.com/). Data on gross national savings Money and quasi money (M2) are the sum of are from World Bank national accounts data, currency outside banks, demand deposits oth- and Organisation for Economic Co-operation er than those of the central government, and and Development national accounts data the time, savings, and foreign currency depos- �les. Data on money and quasi money and its of resident sectors other than the central domestic credit to the private sector are from government. This de�nition of money supply the International Monetary Fund Interna- is frequently called M2 and corresponds to tional Financial Statistics and data �les and lines 34 and 35 in the International Monetary World Bank and OECD estimates of GDP. Fund International Financial Statistics. Data on real interest rates are from the IMF Real interest rate is the lending interest International Financial Statistics database rate adjusted for inflation as measured by the and data �les using World Bank data on the gross domestic product deflator. GDP deflator and the World Bank World De- Domestic credit to private sector is �nancial velopment Indicators database. Data on in- resources provided to the private sector, such terest rate spreads are from the International as through loans, purchases of nonequity Monetary Fund, International Financial Sta- securities, and trade credits and other ac- tistics and data �les. Data on ratios of bank counts receivable, that establish a claim for nonperforming loans to total are from the repayment. For some countries these claims International Monetary Fund Global Finan- include credit to public enterprises. cial Stability Report. Data on bank branches Interest rate spread is the interest rate are from surveys of banking and regulatory charged by banks on loans to prime custom- institutions by the World Bank Research ers minus the interest rate paid by commer- Department and Financial Sector and Op- cial or similar banks for demand, time, or erations Policy Department and the World savings deposits. Development Indicators database. Data on Ratio of bank nonperforming loans to total listed domestic companies and turnover ra- gross loans is the value of nonperforming tios for traded stocks are from Standard & loans divided by the total value of the loan Poor’s Emerging Stock Markets Factbook and portfolio (including nonperforming loans supplemental data and the World Bank’s before the deduction of speci�c loan-loss World Development Indicators database. 146 Africa Development Indicators 2011 Data on market capitalization of listed com- exclude labor and property income (formerly panies are from Standard & Poor’s Emerging called factor services) as well as transfer pay- Stock Markets Factbook and supplemental ments and are expressed in current U.S. dol- data, World Bank and OECD estimates of lars and as a proportion of nominal GDP. GDP, and the World Bank World Develop- Imports of goods and services represent the ment Indicators database. value of all goods and other market services received from the rest of the world. They in- 5. Trade and regional integration clude the value of merchandise, freight, in- surance, transport, travel, royalties, license Table .. International trade and fees, and other services, such as communi- tariff barriers cation, construction, �nancial, information, Total trade is the sum of exports and imports business, personal, and government services. of goods and services measured as a share of They exclude labor and property income (for- gross domestic product. merly called factor services) as well as trans- Merchandise trade is the sum of imports fer payments and are expressed in current and exports of merchandise divided by nomi- U.S. dollars and as a proportion of nominal nal gross domestic product. GDP. Services trade is the sum of imports and Annual growth of exports and imports is cal- exports of wholesale and retail trade (includ- culated using real imports and exports. ing hotels and restaurants), transport, and Terms of trade index measures the relative government, �nancial, professional, and movement of export and import prices. This personal services such as education, health series is calculated as the ratio of a country’s care, and real estate (International Standard export unit values or prices to its import unit Industrial Classi�cation revision 3 divisions values or prices and shows changes over a 50–99) less the value of their intermediate base year (2000) in the level of export unit inputs. Also included are imputed bank ser- values as a percentage of import unit values. vice charges, import duties, and any statisti- Structure of merchandise exports and imports cal discrepancies noted by national compil- components may not sum to 100 percent be- ers or arising from rescaling. It is calculated cause of unclassi�ed trade. without making deductions for depreciation Food comprises the commodities in Stan- of fabricated assets or depletion and degrada- dard International Trade Classi�cation tion of natural resources. For countries that (SITC) sections 0 (food and live animals), 1 report national accounts data at producer (beverages and tobacco), and 4 (animal and prices (Angola, Benin, Cape Verde, Comoros, vegetable oils and fats) and SITC division 22 the Republic of Congo, Côte d’Ivoire, Gabon, (oil seeds, oil nuts, and oil kernels). Ghana, Liberia, Niger, Rwanda, São Tomé Agricultural raw materials comprise the and Príncipe, Seychelles, Togo, and Tunisia), commodities in SITC section 2 (crude ma- gross value added at market prices is used as terials except fuels), excluding divisions 22, the denominator. For countries that report 27 (crude fertilizers and minerals excluding national accounts data at basic prices (all oth- coal, petroleum, and precious stones), and 28 er countries), gross value added at factor cost (metalliferous ores and scrap). is used as the denominator. Value added at Fuel comprises SITC section 3 (mineral basic prices excludes net taxes on products; fuels). value added at producer prices includes net Ores and metals comprise the commodities taxes on products paid by producers but ex- in SITC sections 27, 28, and 68 (nonferrous cludes sales or value added taxes. metals). Exports of goods and services represent the Manufactures comprise the commodi- value of all goods and other market services ties in SITC sections 5 (chemicals), 6 (basic provided to the rest of the world. They include manufactures), 7 (machinery and transport the value of merchandise, freight, insurance, equipment), and 8 (miscellaneous manufac- transport, travel, royalties, license fees, and tured goods), excluding division 68. other services, such as communication, con- Export diversi�cation index measures the struction, �nancial, information, business, extent to which exports are diversi�ed. It is personal, and government services. They constructed as the inverse of a Her�ndahl Technical notes 147 index, using disaggregated exports at four Simple mean bound rate is the unweighted digits (following the SITC revision 3). The average of all the lines in the tariff schedule total number of products exported includes in which bound rates have been set. only those whose value exceeds $100,000 or Simple mean tariff is the unweighted aver- 0.3  percent of the country’s total exports, age of effectively applied rates or most fa- whichever is smaller. The maximum num- vored nation rates for all products subject to ber of three-digit products that could be tariffs calculated for all traded goods. exported is 261. Ranging from 0 to 1, the Dispersion around the mean is calculated index reveals the extent of the differences as the coefficient of variation of the applied between the structure of trade of the coun- tariff rates, including preferential rates that try or country group and the world average. a country applies to its trading partners An index value closer to 1 indicates a bigger available at the six-digit product level of the difference from the world average. A higher Harmonized System in a country’s customs value indicates more export diversi�cation. schedule. The index is computed by measuring abso- Weighted mean tariff is the average of ef- lute deviation of the country share from fectively applied rates or most favored nation world structure. rates weighted by the product import shares Export concentration index, also known corresponding to each partner country. as the Her�ndahl-Hirschmann index, is a Share of lines with international peaks is the measure of the degree of market concentra- share of lines in the tariff schedule with tariff tion. The total number of products exported rates that exceed 15 percent. includes only those whose value exceeds Share of lines with domestic peaks is the $100,000 or 0.3  percent of the country’s share of lines in the tariff schedule with tar- total exports, whichever is smaller. The iff rates that are more than three times the maximum number of three-digit products simple average tariff . that could be exported is 261. It has been Share of lines that are bound is the share of normalized to a scale of 0–1. An index val- lines in the country’s tariff schedule bound ue close to 1 indicates a very concentrated subject to World Trade Organization negotia- market (maximum concentration). Values tion agreements. closer to 0 reflect a more equal distribution Share of lines with speci�c rates is the share of market shares among exporters or im- of lines in the tariff schedule that are set on porters. This type of concentration indica- a per unit basis or that combine ad valorem tor is vulnerable to cyclical fluctuations in and per unit rates. relative prices, with commodity price rises Primary products are commodities classi- making commodity exporters look more �ed in SITC revision 2 sections 0–4 plus divi- concentrated. sion 68. Competitiveness indicator has two aspects: Manufactured products are commodities sectoral effect and global effect. To calculate classi�ed in SITC revision 2 sections 5–8 ex- both indicators, growth of exports is decom- cluding division 68. posed into three components: the growth Average cost to ship 20 ft container from port rate of total international trade over the to destination is the cost of all operations as- reference period (2005–09); the sectoral ef- sociated with moving a container from on- fect, which measures the contribution to a board a ship to the considered economic cen- country’s export growth of the dynamics of ter, weighted based on container traffic for the sectoral markets where the country sells each corridor. its products, assuming that sectoral market Average time to clear customs, direct exports, shares are constant; and the competitiveness is the average number of days to clear direct effect, which measures the contribution of exports through customs. changes in sectoral market shares to a coun- Average time to clear customs, imports, is try’s export growth. the average number of days to clear imports Tariff barriers are a form of duty based on through customs. the value of an import. Binding coverage is the percentage of prod- Source: Data on trade and services are from uct lines with an agreed bound rate. World Bank and Organisation for Economic 148 Africa Development Indicators 2011 Co-operation and Development national substantially eliminate all tariff and nontar- accounts data. Data on merchandise trade iff barriers among themselves and establish are from the World Trade Organization and a common external tariff for nonmembers; World Bank GDP estimates. Data on the economic integration agreement, which lib- competitiveness indicator are from the Or- eralizes trade in services among members ganisation for Economic Co-operation and and covers a substantial number of sectors, Development African Economic Outlook 2011: affects a sufficient volume of trade, includes Africa and Its Emerging Partners. Data on the substantial modes of supply, and is non- export concentration index and diversi�ca- discriminatory (in the sense that similarly tion index data are from the United Nations situated service suppliers are treated the Conference on Trade and Development Sta- same); free trade agreement, under which tistical Office data �les (http://unctadstat. members substantially eliminate all tar- unctad.org), with Standard International iff and nontariff barriers but set tariffs on Trade Classi�cation groups from the United imports from nonmembers; partial scope Nations Statistics Division (http://unstats. agreement, which is a preferential trade un.org/unsd/cr/registry/regcst.asp?Cl=14). agreement noti�ed to the World Trade Or- Data on tariffs are calculated by World Bank ganization (WTO) that is not a free trade staff using the World Integrated Trade Solu- agreement, a customs union, or an econom- tion system (http://wits.worldbank.org) and ic integration; and not noti�ed agreement, data from the United Nations Conference which is a preferential trade arrangement on Trade and Development Trade Analy- established among member countries that sis and Information System database and is not noti�ed to the WTO (the agreement the World Trade Organization Integrated may be functionally equivalent to any of the Data Base and Consolidated Tariff Sched- other agreements). ules database. Data on global imports are Merchandise exports within bloc are the sum from the United Nations Statistics Division of merchandise exports by members of a COMTRADE database. Data on merchan- trade bloc to other members of the bloc. They dise exports and imports are from World are shown both in U.S. dollars and as a per- Bank country desks. Data on shipping costs centage of total merchandise exports by the are from the World Bank Sub-Saharan Africa bloc. Transport Policy Program. Data on average Merchandise exports by bloc are the sum time to clear customs are from World Bank of merchandise exports within bloc and Enterprise Surveys (http://rru.worldbank. to the rest of the world as a share of total org/EnterpriseSurveys/). merchandise exports by all economies in the world. Table . Top three exports and share in total exports,  Source: Data on merchandise trade flows Top exports and share of total exports are based are published in the International Monetary on exports disaggregated at the four-digit Fund (IMF) Direction of Trade Statistics Year- level (following the Standard International book and Direction of Trade Statistics Quar- Trade Classi�cation revision 3). terly. The data in the table were calculated Number of exports accounting for 75 percent using the IMF’s Direction of Trade database. of total exports is the number of exports in a The information on trade bloc membership country that account for 75 percent of the is from the World Bank Policy Research Re- country’s exports. port Trade Blocs (2000), the United Nations Conference on Trade and Development Trade Source: Organisation for Economic Co- and Development Report 2007, the World operation and Development African Economic Trade Organization Regional Trade Agree- Outlook 2011: Africa and Its Emerging Partners. ments Information System, and the World Bank and the Center for International Busi- Table . Regional integration, trade ness at the Tuck School of Business at Dart- blocs mouth College’s Global Preferential Trade Type of most recent agreement includes Agreements Database (http://wits.world- customs union, under which members abnk.org/gptad/). Technical notes 149 6. Infrastructure Source: Data on fresh water resources are from the Food and Agriculture Organiza- Table .. Water and sanitation tion AQUASTAT database. Data on access Internal fresh water resources per capita are to water and sanitation are from the World the sum of total renewable resources, which Health Organization and United Nations include internal flows of rivers and ground- Children’s Fund Joint Monitoring Pro- water from rainfall in the country and river gramme (www.wssinfo.org). Data on insuf- flows from other countries. �cient water supply are from World Bank Population with sustainable access to an im- Enterprise Surveys (http://rru.worldbank. proved water source is the percentage of the org/EnterpriseSurveys/). Data on commit- population with reasonable access to an ad- ted nominal investment in potable water equate amount of water from an improved projects with private participation are from source, such as a household connection, the World Bank Private Participation in In- public standpipe, borehole, protected well or frastructure Project Database (http://ppi. spring, or rainwater collection. Unimproved worldbank.org). Data on official develop- sources include vendors, tanker trucks, and ment assistance disbursements are from the unprotected wells and springs. Reasonable Development Assistance Committee of the access is de�ned as the availability of at least Organisation for Economic Co-operation and 20 liters a person a day from a source within Development Geographical Distribution of Fi- one kilometer of the user’s dwelling. nancial Flows to Developing Countries, Develop- Population with sustainable access to im- ment Co-operation Report, and International proved sanitation is the percentage of the Development Statistics database (www.oecd. population with at least adequate access to org/dac/stats/idsonline). excreta disposal facilities that can effectively prevent human, animal, and insect contact Table .. Transportation with excreta. Improved facilities range from Road network is the length of motorways, simple but protected pit latrines to flush toi- highways, main or national roads, secondary lets with a sewerage connection. The excreta or regional roads, and other roads. disposal system is considered adequate if it Rail lines are the length of railway route is private or shared (but not public) and if it available for train service, irrespective of the hygienically separates human excreta from number of parallel tracks. human contact. To be effective, facilities Road density, ratio to total land, is the to- must be correctly constructed and properly tal length of national road network per 100 maintained. square kilometers of total land area. Average duration of insufficient water supply Vehicle fleet is the number of motor ve- is the average duration of water shortages in hicles, including cars, buses, and freight ve- a typical month in the last �scal year. hicles but not two-wheelers. Committed nominal investment in water Commercial vehicles are the number of com- projects with private participation is annual mercial vehicles that use at least 24 liters of committed investment in water projects diesel fuel per 100 kilometers. with private investment, including projects Passenger vehicles are road motor vehicles, for potable water generation and distribu- other than two-wheelers, intended for the tion and sewerage collection and treatment carriage of passengers and designed to seat projects. no more than nine people (including the Official development assistance (ODA) gross driver). disbursements for water supply and sanitation Road network in good or fair condition is the sector are disbursements for water supply length of the national road network, includ- and sanitation by bilateral, multilateral, and ing the interurban classi�ed network without other donors. The release of funds to, or the the urban and rural network, that is in good purchase of goods or services for a recipient; or fair condition, as de�ned by each country’s by extension, the amount thus spent. Dis- road agency. bursements record the actual international Ratio of paved to total roads is the length of transfer of �nancial resources or of goods or paved roads—which are those surfaced with services valued at the cost of the donor. crushed stone (macadam) and hydrocarbon 150 Africa Development Indicators 2011 binder or bituminized agents, with concrete, Table .. Information and or with cobblestones—as a percentage of all communication technology the country’s roads. Telephone subscribers are subscribers to a Price of diesel fuel and gasoline is the price as main telephone line service, which con- posted at �lling stations in a country’s capital nects a customer’s equipment to the public city. When several fuel prices for major cit- switched telephone network or to a cellular ies were available, the unweighted average is telephone service. used. Since super gasoline (95 octane/A95/ Unmet demand is the number of applica- premium) is not available everywhere, it is tions for connection to the public switched sometime replaced by regular gasoline (92 telephone network that have been held back octane/A92), premium plus gasoline (98 oc- because of a lack of technical facilities (equip- tane/A98), or an average of the two. ment, lines, and the like) divided by the num- Committed nominal investment in transport ber of main telephone lines. projects with private participation is annual Households with own telephone are the committed investment in transport projects percentage of households possessing a with private investment, including projects telephone. for airport runways and terminals, railways Average delay for �rm in obtaining a mainline (including �xed assets, freight, intercity pas- phone connection is the average actual delay in senger, and local passenger), toll roads, bridg- days that �rms experience when obtaining es, and tunnels. a telephone connection, measured from the Official development assistance (ODA) gross day the establishment applied to the day it disbursements for transportation and storage received the service or approval. are disbursements for transportation and Internet users are people with access to the storage by bilateral, multilateral, and other Internet. donors. Telephone faults are the total number of re- Disbursements record the actual interna- ported faults for the year divided by the total tional transfer of �nancial resources or of number of mainlines in operation multiplied goods or services valued at the cost of the by 100. The de�nition of fault can vary. Some donor. countries include faulty customer equip- ment; others distinguish between reported Source: Data on length of road network and actual found faults. There is also some- and vehicle fleet are from the International times a distinction between residential and Road Federation World Road Statistics and business lines. Another consideration is the electronic �les, except where noted. Data on time period: some countries report this indi- rail lines and ratio of paved to total roads cator on a monthly basis; in these cases data are from the World Bank Transportation, are converted to yearly estimates. Water, and Information and Communica- Telephone faults cleared by next working day tions Technologies Department, Transport are the percentage of faults in the public Division. Data on fuel and gasoline prices switched telephone network that have been are from the German Agency for Technical corrected by the end of the next working day. Cooperation. Data on committed nominal Fixed broadband Internet monthly subscrip- investment in transport projects with pri- tion is the monthly subscription charge for vate participation are from the World Bank �xed (wired) broadband Internet service. Private Participation in Infrastructure Proj- Fixed (wired) broadband is considered any ect Database (http://ppi.worldbank.org). dedicated connection to the Internet at Data on official development assistance downstream speeds equal to, or greater than, disbursements are from the Development 256 kbit/s, using DSL. Where several offers Assistance Committee of the Organisation are available, preference should be given to for Economic Co-operation and Develop- the 256 kbit/s connection. Taxes should be ment Geographical Distribution of Financial included. If not included, it should be speci- Flows to Developing Countries, Development �ed in a note including the applicable tax Co-operation Report, and International De- rate. velopment Statistics database (www.oecd. Cost of 3-minute �xed telephone local org/dac/stats/idsonline). phone call during peak hours is the cost of a Technical notes 151 three-minute local call during peak hours. Annual investment in �xed telephone service Local call refers to a call within the same ex- is the annual investment in equipment for change area using the subscriber’s own ter- �xed telephone service. minal (that is, not from a public telephone). Annual investment in mobile communication Cost of 3-minute cellular local call during peak is the capital investment on equipment for hours is the cost of a three-minute cellular lo- mobile communication networks. cal call during peak hours. Annual investment in telecommunications Residential telephone connection charge is is the expenditure associated with acquir- the initial, one-time charge involved in ap- ing the ownership of telecommunication plying for basic telephone service. Where equipment infrastructure (including sup- charges differ by exchange areas, the charge porting land and buildings and intellectual reported is for the largest urban area. and nontangible property such as computer Business telephone connection charge is the software). It includes expenditure on initial one-time charge involved in applying for installations and on additions to existing business basic telephone service. Where installations. charges differ by exchange area, the charge Committed nominal investment in telecom- reported is for the largest urban area. munication projects with private participation Mobile cellular prepaid connection charge is is annual committed investment in telecom- the initial, one-time charge for a new sub- munication projects with private invest- scription. Refundable deposits should not ment, including projects for �xed or mobile be counted. Although some operators waive local telephony, domestic long-distance te- the connection charge, this does not include lephony, and international long-distance the cost of the Subscriber Identity Module telephony. (SIM) card. The price of the SIM card should Official development assistance (ODA) gross be included in the connection charge (for a disbursements for communication are disburse- prepaid service the cost of SIM is equivalent ments for communication by bilateral, multi- to connection charge). It should also be not- lateral, and other donors. Disbursements ed if free minutes or free SMS are included record the actual international transfer of in the connection charge. Taxes should be �nancial resources or of goods or services included. If not included, it should be speci- valued at the cost of the donor. �ed in a note including the applicable tax Revenue from �xed telephone services is rev- rate. enue received for the connection (installa- Mobile cellular postpaid connection charge tion) of telephone service (including charges is the initial, one-time charge for a new for transferring or cancelling a service); rev- postpaid subscription. Refundable depos- enue from recurring charges for subscription its should not be counted. Although some to telephone (and broadband and Internet operators waive the connection charge, this access if not able to be separated from �xed does not include the cost of the Subscriber telephone), including equipment rentals Identity Module (SIM) card. The price of the where relevant; and revenue from calls (local, SIM card should be included in the connec- national, and international). tion charge. It should also be noted if free Revenue from mobile networks is revenue minutes or free SMS are included in the con- from the provision of mobile cellular com- nection charge. Taxes should be included. If munications services, including all voice and not included, it should be speci�ed in a note data (narrowband and broadband) services. including the applicable tax rate. It refers to revenue earned by retailers, not Fixed broadband Internet connection charge by wholesalers. is the initial, one-time charge for a new �xed Total revenue from all telecommunication (wired) broadband Internet connection. services is the total (gross) telecommunica- The tariffs should represent the cheapest tion revenue earned from all (�xed, mobile, �xed (wired) broadband entry plan. Refund- and data, including Internet) operators (both able deposits should not be counted. Taxes network and virtual) offering services within should be included. If not included, it should the country. It excludes revenues from non- be speci�ed in a note including the applicable telecommunications services as well as repay- tax rate. able subscribers’ contributions or deposits. It 152 Africa Development Indicators 2011 refers to revenue earned by retailers, and by power plants, less distribution losses and wholesalers. own use by heat and power plants. GDP per unit of energy use is nominal GDP Source: Data on telephone subscribers, in purchasing power parity (PPP) U.S. dollars unmet demand, reported phone faults, cost of divided by apparent consumption, which is local and cellular calls, households with tele- equal to indigenous production plus imports phone, Internet users and pricing, telephone and stock changes minus exports and fuels and Internet connection charges, and annual supplied to ships and aircraft engaged in in- investment and revenue on telecommunica- ternational transport. tions are from the International Telecommu- Solid fuels use is the percentage of the nications Union data �les. Data on delays for population using solid fuels as opposed to �rms in obtaining a telephone connection are modern fuels. Solid fuels include fuel wood, from World Bank Enterprise Surveys (http:// straw, dung, coal, and charcoal. Modern fu- rru.worldbank.org/EnterpriseSurveys/). els include electricity, lique�ed petroleum Data on committed nominal investment are gas, natural gas, kerosene, and gasoline. The from the World Bank Private Participation indicator is based on the main type of fuel in Infrastructure Project Database (http:// used for cooking because cooking occupies ppi.worldbank.org). Data on official devel- the largest share of overall household en- opment assistance disbursements are from ergy needs. However, many households use the Development Assistance Committee of more than one type of fuel for cooking and, the Organisation for Economic Co-operation depending on climatic and geographical con- and Development Geographical Distribution ditions, heating with solid fuels can also con- of Financial Flows to Developing Countries, tribute to indoor air pollution. Development Co-operation Report, and In- Firms identifying electricity as major or very ternational Development Statistics database severe obstacle to business operation and growth (www.oecd.org/dac/stats/idsonline). are the percentage of �rms that responded “major� or “very severe� to the following Table .. Energy question: “Please tell us if any of the follow- Electricity production is measured at the ter- ing issues are a problem for the operation minals of all alternator sets in a station. In and growth of your business. If an issue (in- addition to hydropower, coal, oil, gas, and frastructure, regulation, and permits) poses nuclear power generation, it covers genera- a problem, please judge its severity as an ob- tion by geothermal, solar, wind, and tide and stacle on a �ve-point scale that ranges from wave energy, as well as that from combusti- 0 = no obstacle to 5 = very severe obstacle.� ble renewable and waste. Production includes Average delay for �rm in obtaining electri- the output of electricity plants that are de- cal connection is the average actual delay in signed to produce electricity only as well as days that �rms experience when obtaining that of combined heat and power plants. an electrical connection, measured from the Hydroelectric refers to electricity produced day the establishment applied to the day it by hydroelectric power plants. received the service or approval. Coal refers to all coal and brown coal, both Electric power transmission and distribution primary (including hard coal and lignite- losses are technical and nontechnical losses, brown coal) and derived fuels (including including electricity losses due to operation patent fuel, coke oven coke, gas coke, coke of the system and the delivery of electricity oven gas, and blast furnace gas). Peat is also as well as those caused by unmetered supply. included. This comprises all losses due to transport and Natural gas refers to natural gas but ex- distribution of electrical energy and heat. cludes natural gas liquids. Electrical power outages in a typical month is Nuclear refers to electricity produced by the average number of electrical power out- nuclear power plants. ages in a typical month. Oil refers to crude oil and petroleum Firms that share or own their own generator products. are the percentage of �rms that responded Electric power consumption is the produc- “Yes� to the following question: “Does your tion of power plants and combined heat and establishment own or share a generator?� Technical notes 153 Firms using electricity from generator are the Economic Co-operation and Development percentage of �rms using electricity supplied Geographical Distribution of Financial Flows to from a generator or generators that the �rm Developing Countries, Development Co-opera- owns or shares. tion Report, and International Development Committed nominal investment in energy Statistics database (www.oecd.org/dac/stats/ projects with private participation is annual idsonline). committed investment in energy projects with private investment, including projects 7. Human development for electricity generation, transmission, and distribution as well as natural gas transmis- Table .. Education sion and distribution. Youth literacy rate is the percentage of people Official development assistance (ODA) gross ages 15–24 who can, with understanding, disbursements for energy are disbursements both read and write a short, simple state- for energy by bilateral, multilateral, and oth- ment about their everyday life. er donors. Disbursements record the actual Adult literacy rate is the proportion of international transfer of �nancial resources adults ages 15 and older who can, with un- or of goods or services valued at the cost of derstanding, read and write a short, simple the donor. statement on their everyday life. Primary education provides children with Source: Data on electricity production and basic reading, writing, and mathematics consumption are from the International En- skills along with an elementary understand- ergy Agency (www.iea.org/stats/index.asp), ing of such subjects as history, geography, Energy Statistics of Non-OECD Countries, En- natural science, social science, art, and music. ergy Balances of Non-OECD Countries, Energy Secondary education completes the provi- Statistics of OECD Countries, and Energy Bal- sion of basic education that began at the pri- ances of OECD Countries. Data on PPP GDP mary level and aims to lay the foundations per unit of energy use are from the Interna- for lifelong learning and human development tional Energy Agency (www.iea.org/stats/ by offering more subject- or skill-oriented in- index.asp) and World Bank PPP data. Data struction using more specialized teachers. on solid fuels use are from household survey Tertiary education, whether or not at an data, supplemented by World Bank Project advanced research quali�cation, normally Appraisal Documents. Data on �rms iden- requires, as a minimum condition of admis- tifying electricity as a major or very severe sion, the successful completion of education obstacle to business operation and growth, at the secondary level. delays for �rms in obtaining an electrical Gross enrollment ratio is the ratio of total connection, electrical outages of �rms, �rms enrollment, regardless of age, to the popu- that share or own their own generator, and lation of the age group that officially corre- �rms using electricity from generator are sponds to the level of education shown. from World Bank Enterprise Surveys (http:// Net enrollment ratio is the ratio of children rru.worldbank.org/EnterpriseSurveys/). of official school age, based on the Interna- Data on transmission and distribution loss- tional Standard Classi�cation of Education es are from the International Energy Agency 1997, who are enrolled in school to the popu- (www.iea.org/stats/index.asp), Energy Sta- lation of the corresponding official school tistics of Non-OECD Countries, Energy Bal- age. ances of Non-OECD Countries, Energy Statis- Student-teacher ratio is the number of stu- tics of OECD Countries, and Energy Balances dents enrolled in school divided by the num- of OECD Countries and the United Nations ber of teachers, regardless of their teaching Energy Statistics Yearbook. Data on commit- assignment. ted nominal investment are from the World Public spending on education is current and Bank Private Participation in Infrastructure capital public expenditure on education plus Project Database (http://ppi.worldbank. subsidies to private education at the primary, org). Data on official development assistance secondary, and tertiary levels by local, region- disbursements are from the Development As- al, and national government, including munic- sistance Committee of the Organisation for ipalities. It excludes household contributions. 154 Africa Development Indicators 2011 Source: United Nations Educational, Sci- whether or not con�rmed by microscopy or enti�c and Cultural Organization (UNESCO) by rapid diagnostic test. Institute for Statistics. Child immunization rate is the percentage of children ages 12–23 months who received Table .. Health vaccinations before 12 months or at any time Life expectancy at birth is the number of years before the survey for four diseases—measles a newborn infant would live if prevailing and diphtheria, pertussis (whooping cough), patterns of mortality at the time of its birth and tetanus (DPT). A child is considered ad- were to remain the same throughout its life. equately immunized against measles after re- Data are World Bank estimates based on data ceiving one dose of vaccine and against DPT from the United Nations Population Divi- after receiving three doses. sion, the United Nations Statistics Division, Stunting is the percentage of children un- and national statistical offices. der age 5 whose height for age is more than Under-�ve mortality rate is the probability two standard deviations below the median for that a newborn baby will die before reaching the international reference population ages age 5, if subject to current age-speci�c mor- 0–59 months. For children up to age 2, height tality rates. The probability is expressed as a is measured by recumbent length. For older rate per 1,000. children, height is measured by stature while Infant mortality rate is the number of in- standing. The reference population adopted fants dying before reaching age 1, per 1,000 by the World Health Organization (WHO) live births. in 1983 is based on children from the United Maternal mortality ratio, modeled estimate, States, who are assumed to be well nourished. is the number of women who die from preg- Underweight is the percentage of children nancy-related causes during pregnancy and under age 5 whose weight for age is more childbirth, per 100,000 live births. The data than two standard deviations below the me- are estimated by a regression model using in- dian reference standard for their age as es- formation on fertility, birth attendants, and tablished by the WHO, the U.S. Centers for HIV prevalence. Disease Control and Prevention, and the U.S. Prevalence of HIV is the percentage of peo- National Center for Health Statistics. Data ple ages 15–49 who are infected with HIV. are based on children under age 3, 4, and 5, Incidence of tuberculosis is the number of depending on the country. tuberculosis cases (pulmonary, smear posi- Births attended by skilled health staff are the tive, and extrapulmonary) in a population percentage of deliveries attended by person- at a given point in time, per 100,000 people. nel trained to give the necessary supervision, This indicator is sometimes referred to as care, and advice to women during pregnancy, “point prevalence.� Estimates include cases labor, and the postpartum period; to con- of tuberculosis among people with HIV. duct deliveries on their own; and to care for Clinical malaria cases reported are the sum newborns. of cases con�rmed by slide examination or Contraceptive use is the percentage of wom- rapid diagnostic test and probable and uncon- en ages 15–49, married or in union, who are �rmed cases (cases that were not tested but practicing, or whose sexual partners are prac- treated as malaria). National malaria control ticing, any form of contraception. Modern programs often collect data on the number of methods of contraception include female suspected cases, those tested, and those con- and male sterilization, oral hormonal pills, �rmed. Probable or uncon�rmed cases are the intrauterine device, the male condom, in- calculated by subtracting the number tested jectables, the implant (including Norplant), from the number suspected. Not all cases re- vaginal barrier methods, the female condom, ported as malaria are true malaria cases; most and emergency contraception. health facilities lack appropriate diagnostic Children sleeping under insecticide-treated services. The misdiagnosis may have led to nets are the percentage of the children under under- or overreporting malaria cases and age 5 with access to an insecticide-treated net missing diagnosis of other treatable diseases. to prevent malaria. Reported malaria deaths are all deaths in Tuberculosis case detection rate, all forms, is health facilities that are attributed to malaria, the percentage of newly noti�ed tuberculosis Technical notes 155 cases (including relapses) to estimated inci- Total health expenditure is the sum of public dent cases (case detection, all forms). and private health expenditure. It covers the Tuberculosis treatment success rate is the provision of health services (preventive and percentage of new, registered smear-positive curative), family planning activities, nutri- (infectious) cases that were cured or in which tion activities, and emergency aid designated a full course of treatment was completed. for health but does not include provision of Children with fever receiving any antimalarial water and sanitation. treatment same or next day are the percent- Public health expenditure consists of recur- age of children under age 5 in malaria-risk rent and capital spending from government areas with fever being treated with any anti- (central and local) budgets, external borrow- malarial drugs. ings and grants (including donations from Population with sustainable access to an im- international agencies and nongovernmental proved water source is the percentage of popu- organizations), and social (or compulsory) lation with reasonable access to an adequate health insurance funds. amount of water from an improved source, Private health expenditure includes direct such as a household connection, public household (out-of-pocket) spending, private standpipe, borehole, protected well or spring, insurance, charitable donations, and direct or rainwater collection. Unimproved sources service payments by private corporations. include vendors, tanker trucks, and unpro- External resources for health are funds or tected wells and springs. Reasonable access is services in kind that are provided by entities de�ned as the availability of at least 20 liters not part of the country in question. The re- a person a day from a source within 1  kilo- sources may come from international orga- meter of the dwelling. nizations, other countries through bilateral Population with sustainable access to im- arrangements, or foreign nongovernmental proved sanitation is the percentage of the organizations. These resources are part of to- population with at least adequate access to tal health expenditure. excreta disposal facilities that can effectively Out-of-pocket expenditure is any direct out- prevent human, animal, and insect contact lay by households, including gratuities and with excreta. Improved facilities range from in-kind payments, to health practitioners simple but protected pit latrines to flush toi- and suppliers of pharmaceuticals, therapeu- lets with a sewerage connection. The excreta tic appliances, and other goods and services disposal system is considered adequate if it whose primary intent is to contribute to the is private or shared (but not public) and if it restoration or enhancement of the health hygienically separates human excreta from status of individuals or population groups. It human contact. To be effective, facilities is a part of private health expenditure. must be correctly constructed and properly Private prepaid plans are expenditure on maintained. health by private insurance institutions. Pri- Physicians are the number of physicians, vate insurance enrollment may be contrac- including generalists and specialists, per tual or voluntary, and conditions and ben- 1,000 people. e�ts or a basket of bene�ts are agreed on a Nurses and midwives are the number of voluntary basis between the insurance agent professional nurses, auxiliary nurses, en- and the bene�ciaries. They are thus not con- rolled nurses, and other nurses, such as den- trolled by government units for the purpose tal nurses and primary care nurses, and pro- of providing social bene�ts to members. fessional midwives, auxiliary midwives, and Health expenditure per capita is the sum of enrolled midwives, per 1,000 people. public and private health expenditures divided Community workers is the number of by total population. It covers the provision of community workers, which includes vari- health services (preventive and curative), fam- ous types of community health aides, many ily planning activities, nutrition activities, and with country-speci�c occupational titles emergency aid designated for health but does such as community health officers, commu- not include provision of water and sanitation. nity health-education workers, family health workers, woman health visitors, and health Source: Data on life expectancy at birth, extension package workers, per 1,000 people. under-�ve mortality, infant mortality, maternal 156 Africa Development Indicators 2011 mortality, prevalence of HIV, incidence of tu- Share of rural population with sustainable ac- berculosis, child immunization, malnutrition, cess to an improved water source is the percent- births attended by skilled health staff, con- age of the rural population with reasonable traceptive use, children sleeping under in- access to an adequate amount of water from secticide-treated nets, and children receiving an improved source, such as a household antimalarial drugs are from World Bank staff connection, public standpipe, borehole, pro- estimates based on various sources, including tected well or spring, or rainwater collection. census reports, the United Nations Popula- Unimproved sources include vendors, tanker tion Division World Population Prospects, na- trucks, and unprotected wells and springs. tional statistical offices, household surveys Reasonable access is de�ned as the avail- conducted by national agencies and Macro ability of at least 20 liters a person a day from International, the World Health Organization a source within 1 kilometer of the dwelling. (WHO), and the United Nations Children’s Share of rural population with sustainable ac- Fund (UNICEF). Data on clinical malaria cas- cess to improved sanitation facilities is the per- es reported and reported malaria deaths are centage of the rural population with at least from the WHO World Malaria Report 2010. adequate access to excreta disposal facilities Data on physicians, nurses, and community that can effectively prevent human, animal, health workers are from the WHO Global and insect contact with excreta. Improved Atlas of the Health Workforce (http://apps. facilities range from simple but protected who.int/globalatlas/). Data on tuberculosis pit latrines to flush toilets with a sewerage are from the WHO Global Tuberculosis Control connection. The excreta disposal system is Report. Data on access to water and sanita- considered adequate if it is private or shared tion are from the WHO and UNICEF Fund (but not public) and if it hygienically sepa- Joint Monitoring Programme (www.wssinfo. rates human excreta from human contact. To org). Data on health expenditure are from be effective, facilities must be correctly con- the WHO National Health Account database structed and properly maintained. (www.who.int/nha/en), supplemented by country data. Source: Data on rural population are calcu- lated from urban population shares from the 8. Agriculture, rural development, and United Nations Population Division World Environment Urbanization Prospects and from total popu- lation �gures from the World Bank. Data on Table .. Rural development rural population density are from the FAO Rural population is the difference between the and World Bank population estimates. Data total population and the urban population. on rural population below the poverty line Rural population density is the rural popula- and the rural population poverty gap are tion divided by the arable land area. Arable from the Global Poverty Working Group and land includes land de�ned by the Food and are based on World Bank’ country poverty Agriculture Organization (FAO) as land un- assessments and country poverty reduction der temporary crops (double-cropped areas strategies. Data on access to water and sani- are counted once), temporary meadows for tation are from the World Health Organiza- mowing or pasture, land under market or tion and United Nations Children’s Fund kitchen gardens, and land temporarily fallow. Joint Monitoring Programme (www.wssinfo. Land abandoned as a result of shifting culti- org). vation is excluded. Share of rural population below the national Table .. Agriculture poverty line is the percentage of the rural pop- Agriculture value added is the gross output of ulation living below the national poverty line. forestry, hunting, and �shing, crop cultiva- Rural population poverty gap at national pov- tion, and livestock production (International erty line is the mean shortfall from the pover- Standard Industrial Classi�cation [ISIC] revi- ty line (counting the nonpoor as having zero sion 3 divisions 1–5) less the value of their shortfall), expressed as a percentage of the intermediate inputs. It is calculated without poverty line. This measure reflects the depth making deductions for depreciation of fabri- of poverty as well as its incidence. cated assets or depletion and degradation of Technical notes 157 natural resources. For countries that report Cereal cropland refers to harvested area, al- national accounts data at producer prices though some countries report only sown or (Angola, Benin, Cape Verde, Comoros, the cultivated area. Republic of Congo, Côte d’Ivoire, Gabon, Agricultural irrigated land is areas equipped Ghana, Liberia, Niger, Rwanda, São Tomé to provide water to the crops, including ar- and Príncipe, Seychelles, Togo, and Tunisia), eas equipped for full and partial control irri- gross value added at market prices is used as gation, spate irrigation areas, and equipped the denominator. For countries that report wetland or inland valley bottoms. national accounts data at basic prices (all Fertilizer consumption is the aggregate of ni- other countries), gross value added at factor trogenous, phosphate, and potash fertilizers. cost is used as the denominator. Value added Agricultural machinery refers to the num- at basic prices includes net taxes on products; ber of wheel and crawler tractors (excluding value added at producer prices includes net garden tractors) in use in agriculture at the taxes on products paid by producers but ex- end of the calendar year speci�ed or during cludes sales or value added taxes. the �rst quarter of the following year. Arable Total agriculture gross production index is land includes land de�ned by the Food and total agricultural production relative to the Agriculture Organization (FAO) as land un- base period 1999–2001. der temporary crops (double-cropped areas Crop gross production index is agricultural crop are counted once), temporary meadows for production relative to the base period 1999– mowing or pasture, land under market or 2001. It includes all crops except fodder crops. kitchen gardens, and land temporarily fallow. Livestock gross production index covers meat Land abandoned as a result of shifting culti- and milk from all sources, cheese, eggs, hon- vation is excluded. ey, raw silk, wool, and hides and skins. Agricultural employment includes people Food gross production index covers food crops who work for a public or private employer that are considered edible and that contain nu- and who receive remuneration in wages, sal- trients. Coffee and tea are excluded because, ary, commission, tips, piece rates, or pay in although edible, they have no nutritive value. kind. Agriculture corresponds to division  1 Cereal gross production index covers cereals (ISIC revision 2) or tabulation categories A that are considered edible and that contain and B (ISIC revision 3) and includes hunting, nutrients. forestry, and �shing. Cereal production is crops harvested for dry Agriculture value added per worker is the grain only. Cereal crops harvested for hay or output of the agricultural sector (ISIC divi- harvested green for food, feed, or silage and sions 1–5) less the value of intermediate those used for grazing are excluded. inputs. Agriculture comprises value added Cereal includes wheat, rice, maize, barley, from forestry, hunting, �shing, crop cultiva- oats, rye, millet, sorghum, buckwheat, and tion, and livestock production. Data are in mixed grains. constant 2000 U.S. dollars. Agricultural exports and imports are ex- Cereal yield is dry grain only and includes pressed in current U.S. dollars at free on wheat, rice, maize, barley, oats, rye, mil- board prices. The term agriculture in trade let, sorghum, buckwheat, and mixed grains. refers to both food and agriculture and does Cereal crops harvested for hay or harvested not include forestry and �shery products. green for food, feed, or silage and those used Food exports and imports are expressed in for grazing are excluded. current U.S. dollars at free on board prices for exports and cost, insurance, and freight Source: Data on agriculture value added prices for imports. are from Organisation for Economic Co-op- Permanent cropland is land cultivated with eration and Development and World Bank crops that occupy the land for long periods national accounts data �les. Data on crop, and need not be replanted after each harvest, livestock, food, and cereal production, cereal such as cocoa, coffee, and rubber. It includes exports and imports, agricultural exports land under flowering shrubs, fruit trees, nut and imports, permanent cropland, cereal trees, and vines but excludes land under trees cropland, agricultural machinery, cereal yield, grown for wood or timber. and fertilizer consumption are from FAO 158 Africa Development Indicators 2011 Transformation of Rwanda’s coffee sector: an African success story Punam Chuhan-Pole and Manka S. Angwafo For many years, Rwanda’s coffee sector was stuck in a “low- as of 2006, and Rwandan coffee exports generated more than quality/low-quantity trap.� Compulsory production, substantial $47 million in revenue in 2008, compared with $35 million in 2007. export taxes, and a monopsony export control agency meant that producers had little incentive to invest in producing high-quality Figure 1 Average farmer and export prices, 2003–08 coffee. Highly volatile world coffee prices in the 1980s (and state 4 Green coffee price ($ per kilogram) capture during boom years), coupled with the country’s economic deterioration during the 1994 genocide, left coffee producers in an even worse situation. 3 Average export price The post-genocide regime set out to revitalize and transform Cherry price premium the coffee sector. Changes were implemented in several waves. 2 The first began in the late 1990s, when the government removed Cherry price OCIR Cafe a variety of trade barriers, created incentives for groups and indi- 1 viduals to transfer their efforts from semiwashed to fully washed (higher value) coffee as an end product, and facilitated entrepre- 0 neurship in the coffee industry. More substantial reform efforts 2003 2004 2005 2006 2007 2008 began in 2000, when the government, working with consultants Source: Rwanda Ministry of Agriculture and Animal Husbandry and Ministry of Trade and Industry (2008). and donors, studied the potential for adding value to Rwandan coffee by producing higher-quality, washed, and fermented spe- cialty coffee. In 2002, the government issued a national coffee Figure 2 Value chain for washed coffee strategy that outlined a plan for capturing a larger share of the Farmers Buyers— Millers and Auction Importers Retailers Consumers specialty-coffee sector. In the intervening years, more than 100 private CWS exporters (Mombasa) coffee washing stations were built (table 1). or Co-op Table 1 Growth in the specialty coffee sector 2001 2002 2003 2004 2005 2006 2007 2008 2009 Washing stations — 1 10 25 45 76 112 — 112 Green specialty coffee exported (tons) — 30 300 800 1,200 3,000 2,300 2,455 3,045 Specialty coffee buyers — 2 8 16 25 30 30 — — Rwanda’s experience shows that reforming policies can un- Total value of specialty cofee exported leash private sector activity and pave the way for growth. The will- ($ thousands) — 90 720 1,850 3,168 8,000 7,800 8,060 11,600 ingness of the government to allow liberalization of the coffee sec- — is not available. tor has paid off. Rwanda could further improve the performance of Source: U.S. Agency for International Development. this sector—for example, by implementing further price incentives Rwanda’s approach to liberalizing its coffee sector has re- for producers to focus on high-quality coffee, improving manage- sulted in the country’s coffee farmers having the opportunity to ment of producer cooperatives, and reducing still-high transpor- sell higher-quality beans for a higher price. Indeed, the average ex- tation costs related to poor infrastructure and the country’s land- port price of coffee nearly doubled over 2003–2008, from $1.60 to locked status. $3.10 (figure 1). For smallholder farmers and other participants in the coffee value chain (figure 2), producing specialty coffee means Source: Adapted from K. Boudreaux. 2010. “A Better Brew for Success not just more income but expanded connections to world markets in Rwanda: Economic Liberalization in the Coffee Sector.� In Yes Africa and positive effects from informal economic cooperation at coffee Can: Success Stories from a Dynamic Continent, ed. P. Chuhan-Pole and washing stations. Coffee washing stations had created 4,000 jobs M. Angwafo. World Bank: Washington, DC. electronic �les and website. Data on agricul- rate of the selected year. The main source tural employment are from the International for exchange rates is the International Mon- Labour Organization Key Indicators of the etary Fund. Where official and commercial Labour Market database. exchange rates differ signi�cantly, the com- mercial exchange rate may be applied. Pro- Table .. Producer food prices ducer prices are prices received by farmers Prices in U.S. dollars are equal to producer for primary agricultural products as de�ned prices in local currency times the exchange in the 1993 System of National Accounts. Technical notes 159 The producer price is the amount receivable sources), natural gas, solid fuels (coal, lignite, by the producer from the purchaser for a unit and other derived fuels), and combustible re- of a good or service produced as output mi- newable and waste—and primary electricity, nus any value added tax or similar deductible all converted into oil equivalents. tax invoiced to the purchaser. It excludes any Energy use refers to use of primary energy transport charges invoiced separately by the before transformation to other end-use fuels, producer. Time series refer to the national which is equal to indigenous production plus average prices of individual commodities imports and stock changes, minus exports comprising all grades, kinds, and varieties and fuels supplied to ships and aircraft en- received by farmers when they participate in gaged in international transport. their capacity as sellers of their own products Combustible renewables and waste comprise at the farm gate or �rst point of sale. solid biomass, liquid biomass, biogas, indus- trial waste, and municipal waste, measured Source: Data are from Food and Agriculture as a percentage of total energy use. Organization electronic �les and website. Carbon dioxide emissions are those stem- ming from the burning of fossil fuels and Table .. Environment the manufacture of cement. They include Forest area is land under natural or planted carbon dioxide produced during consump- stands of trees, whether productive or not. tion of solid, liquid, and gas fuels and gas Renewable internal fresh water resources re- flaring. fer to internal renewable resources (internal Methane emissions, total, are those from river flows and groundwater from rainfall) in human activities such as agriculture and the country. from industrial methane production. Annual fresh water withdrawals refer to to- Methane emissions, agricultural, are those tal water withdrawals, not counting evapora- from animals, animal waste, rice production, tion losses from storage basins. Withdrawals agricultural waste burning (nonenergy, on- also include water from desalination plants site), and savannah burning. in countries where they are a signi�cant Methane emissions, industrial, are those source. Withdrawals can exceed 100 percent from the handling, transmission, and com- of total renewable resources where extrac- bustion of fossil fuels and biofuels. tion from nonrenewable aquifers or desalina- Nitrous oxide emissions, total, are those tion plants is considerable or where there is from agricultural biomass burning, industri- signi�cant water reuse. Withdrawals for ag- al activities, and livestock management. riculture and industry are total withdrawals Nitrous oxide emissions, agricultural, are for irrigation and livestock production and those produced through fertilizer use (syn- for direct industrial use (including withdraw- thetic and animal manure), animal waste als for cooling thermoelectric plants). With- management, agricultural waste burning drawals for domestic uses include drinking (nonenergy, on-site), and savannah burning. water, municipal use or supply, and use for Nitrous oxide emissions, industrial, are those public services, commercial establishments, produced during the manufacturing of adipic and homes. acid and nitric acid. Water productivity is calculated as gross do- Other greenhouse gas emissions are by-prod- mestic product in constant prices divided by uct emissions of hydrofluorocarbons, per- annual total water withdrawal. fluorocarbons, and sulfur hexafluoride. Emissions of organic water pollutants are Official development assistance (ODA) gross measured in terms of biochemical oxygen de- disbursements for forestry are disbursements mand, which refers to the amount of oxygen for forestry by bilateral, multilateral, and oth- that bacteria in water will consume in break- er donors. Disbursements record the actual ing down waste. This is a standard water- international transfer of �nancial resources treatment test for the presence of organic or of goods or services valued at the cost of pollutants. the donor. Energy production refers to forms of pri- Official development assistance (ODA) mary energy—petroleum (crude oil, natural gross disbursements for general environment gas liquids, and oil from nonconventional protection are disbursements for general 160 Africa Development Indicators 2011 Food prices in Africa Sailesh Tiwari and Hassan Zaman Although global food prices remain high, the World Bank’s parts of a country, a primary reason some countries have isolated nominal food price index has stabilized in recent months after pockets of food insecurity. peaking during the food price crisis in February. Still, prices are Recent food price trends in Africa underscore this point. East- only 6 percent less than the 2008 peaks and continuing uncer- ern Africa was hit with a drought severely affecting the secondary tainties are likely to keep them volatile. The primary drivers of season harvests, and as a result the prices of maize and sorghum— the most recent surge in food prices include: severe weather the region’s two main staples—have risen sharply since February. events in key grain exporting countries, such as the Argentina, Maize prices in Kenya and Uganda had almost doubled by May, Australia, Canada, Kazakhstan, and the Russian Federation in and in Tanzania (Dar es Salaam) they were 59 percent higher than a the second half of 2010; broad increases in prices of agricul- year ago. By contrast, favorable prospects for maize harvests have tural commodities and the resultant increases in competition led to steady or declining prices across Southern Africa. for land and other inputs; and the link between higher oil prices Western Africa, where sorghum and millet are the staple and the diversion of key food commodities into the production crops, still enjoys adequate supplies from the bumper harvests of of biofuels. previous years. The prices of these crops have remained stable In Africa, however, domestic prices of key food commodities in Burkina Faso, Mali, and Niger, and even where there has been have been driven largely by the variability of local supply, as op- some seasonal increase, as in some markets in Chad, the price posed to global trends. The continent’s isolated agricultural mar- levels remain lower than where they were last year. However, rising kets might be a reason for the low pass-through of global prices. costs of importing fuel and food grains, such as rice and wheat, One particularly salient consequence is that local shortfalls in pose a significant threat to the region’s macroeconomic stability. production—related either to poor rains and drought or to supply Net importers of food and fuel will likely see external and fiscal disruptions resulting from conflict—often lead to significant dif- balances erode and inflationary pressures build up, as import bills ferences in price movements within countries. The price of rice in grow and governments shelter domestic consumers from high in- Benin, for instance, rose 33 percent in Bohicon but fell 4 percent ternational prices. Already, Sierra Leone has reduced import du- in Cotonou between March and April 2011. A low average increase ties on rice and petroleum products by 10 percent to avert growing in food prices can mask significant increases in poverty in specific unrest over rising prices of essential commodities. environment protection by bilateral, multi- Co-operation and Development Geographical lateral, and other donors. Disbursements Distribution of Financial Flows to Developing record the actual international transfer of Countries, Development Co-operation Report, �nancial resources or of goods or services and International Development Statistics da- valued at the cost of the donor. tabase (www.oecd.org/dac/stats/idsonline). Source: Data on forest area and deforesta- Table .. Fossil fuel emissions tion are from the Food and Agriculture Or- Carbon dioxide emissions are those stemming ganization (FAO) Global Forest Resources As- from the burning of fossil fuels and the man- sessment. Data on fresh water resources and ufacture of cement. They include carbon di- withdrawals are from the World Resources oxide produced during consumption of solid, Institute, supplemented by FAO AQUASTAT liquid, and gas fuels and gas flaring. data. Data on emissions of organic water pol- Carbon dioxide emissions per capita are car- lutants are from the World Bank. Data on en- bon dioxide emissions divided by midyear ergy production and use and combustible re- population. newable and waste are from the International Fossil fuel is any hydrocarbon deposit that Energy Agency. Data on carbon dioxide emis- can be burned for heat or power, such as pe- sions are from Carbon Dioxide Information troleum, coal, and natural gas. Analysis Center, Environmental Sciences Di- Total carbon dioxide emissions from fossil fu- vision, Oak Ridge National Laboratory. Data els is the sum of all fossil fuel emissions (solid on methane emissions, nitrous oxide emis- fuel consumption, liquid fuel consumption, sions, and other greenhouse gas emissions are gas fuel consumption, gas flaring, and ce- from the International Energy Agency. Data ment production). on official development assistance disburse- Carbon dioxide emissions from solid fuel ments are from the Development Assistance consumption refer mainly to emissions from Committee of the Organisation for Economic use of coal as an energy source and from Technical notes 161 secondary fuels derived from hard and soft Industry corresponds to divisions 2–5 coal (such as coke-oven coke). (ISIC revision 2) or tabulation categories C–F Carbon dioxide emissions from liquid fuel con- (ISIC revision 3) and includes mining and sumption refer to emissions from use of crude quarrying (including oil production), manu- petroleum and natural gas liquids as an en- facturing, construction, and public utilities ergy source and from secondary fuels derived (electricity, gas, and water). from oil (such as jet fuel). Services correspond to divisions 6–9 (ISIC Carbon dioxide emissions from gas fuel con- revision 2) or tabulation categories G–P (ISIC sumption refer mainly to emissions from use revision 3) and include wholesale and retail of natural gas as an energy source and from trade and restaurants and hotels; transport, secondary fuels derived from natural gas storage, and communications; �nancing, in- (such as blast furnace gas). surance, real estate, and business services; Carbon dioxide emissions from gas flaring refer and community, social, and personal services. mainly to emissions from gas flaring activities. Wage and salaried workers are workers who Carbon dioxide emissions from cement produc- hold the type of jobs de�ned as paid employ- tion refer mainly to emissions during cement ment jobs, where incumbents hold explicit production. Cement production is a multistep (written or oral) or implicit employment con- process, and carbon dioxide is actually released tracts that give them a basic remuneration from klinker production during the process. that is not directly dependent on the revenue of the unit for which they work. Source: Data on carbon dioxide emissions and Self-employed workers are self-employed fossil fuels are from Carbon Dioxide Informa- workers with employees (employers), self- tion Analysis Center Environmental Sciences employed workers without employees (own- Division, Oak Ridge National Laboratory. account workers), and members of producer cooperatives. Although the contributing 9. Labor, migration, and population family workers category is technically part of the self-employed according to the clas- Table .. Labor force participation si�cation used by the International Labour Labor force is people ages 15 and older who Organization (ILO), and could therefore meet the International Labour Organization be combined with the other self-employed (ILO) de�nition of the economically active categories to derive the total self-employed, population. It includes both the employed and they are reported here as a separate cat- the unemployed. While national practices vary egory to emphasize the difference between in the treatment of such groups as the armed the two statuses, since the socioeconomic forces and seasonal or part-time workers, the implications associated with each status labor force generally includes the armed forc- can vary substantially. This practice follows es, the unemployed, and �rst-time job seekers that of the ILO Key Indicators of the Labour but excludes homemakers and other unpaid Market. caregivers and workers in the informal sector. Contributing family workers are unpaid Participation rate is the percentage of the workers who hold self-employment jobs as population of the speci�ed age group that is own-account workers in a market-oriented economically active—that is, all people who establishment operated by a related person supply labor for the production of goods and living in the same household. services during a speci�ed period. Source: ILO Key Indicators of the Labour Source: ILO Key Indicators of the Labour Market database. Market database. Table .. Unemployment Table .. Labor force composition Unemployment is the share of the labor force Agriculture corresponds to division 1 (Inter- of the speci�ed subgroup without work but national Standard Industrial Classi�cation available for and seeking employment. [ISIC] revision 2) or tabulation categories A Primary education provides children with and B (ISIC revision 3) and includes hunting, basic reading, writing, and mathematics skills forestry, and �shing. along with an elementary understanding of 162 Africa Development Indicators 2011 such subjects as history, geography, natural Rural population is calculated as the differ- science, social science, art, and music. ence between the total population and the Secondary education completes the pro- urban population. vision of basic education that began at the Urban population is the midyear population primary level and aims to lay the founda- of areas de�ned as urban in each country. tions for lifelong learning and human devel- opment by offering more subject- or skill- Source: Data on migration are from the oriented instruction using more specialized United Nations Population Division Trends in teachers. Total Migrant Stock: The 2008 Revision. Data on Tertiary education, whether or not at an population are from the United Nations Popu- advanced research quali�cation, normally lation Division World Population Prospects: The requires, as a minimum condition of admis- 2008 Revision, census reports and other sta- sion, the successful completion of education tistical publications from national statistical at the secondary level. offices, Eurostat Demographic Statistics, Secre- tariat of the Paci�c Community Statistics and Source: International Labour Organiza- Demography Programme, U.S. Census Bureau tion Key Indicators of the Labour Market International Database, and World Bank esti- database. mates based on data from these sources as well as household surveys conducted by national Table .. Migration and population agencies, Macro International, the U.S. Cen- Migrant stock is the number of people born in ters for Disease Control and Prevention, and a country other than that in which they live. refugees statistics from the United Nations It includes refugees. High Commissioner for Refugees. Data on Net migration is the annual number of dependency ratio are from World Bank staff immigrants less the annual number of emi- estimates based on various sources, including grants, including both citizens and nonciti- census reports, the United Nations Popula- zens. Data are �ve-year estimates. tion Division World Population Prospects, na- Worker remittances, received, comprise cur- tional statistical offices, household surveys rent transfers by migrant workers and wages conducted by national agencies, and Macro and salaries by nonresident workers. International. Data on worker remittances are Migrant remittance flows are the sum of from the International Monetary Fund Bal- worker remittances, compensation of em- ance of Payments Statistics Yearbook and data ployees, and migrants’ transfers, as recorded �les. Data from migrant remittance flows are in the International Monetary Fund Balance from World Bank staff estimates based on the of Payments. International Monetary Fund Balance of Pay- Population is total population based on ments Statistics Yearbook 2008. the de facto de�nition of population, which counts all residents regardless of legal status 10. HIV/AIDS or citizenship, except for refugees not perma- nently settled in the country of asylum, who Table .. HIV/AIDS are generally considered part of the popula- Estimated number of people living with HIV/ tion of their country of origin. The values AIDS is the number of people in the speci�ed shown are midyear estimates. age group living with HIV. Fertility rate is the number of children that Estimated HIV prevalence rate is the per- would be born to a woman if she were to live centage of the population of the speci�ed to the end of her childbearing years and bear age subgroup who are infected with HIV. De- children in accordance with current age-spe- pending on the reliability of the data avail- ci�c fertility rates. able, there may be uncertainty surrounding Age composition refers to the percentage each estimate. Therefore, plausible bounds of the total population that is in speci�c age are presented for each subgroup rate (low groups. and high estimate). Dependency ratio is the ratio of dependents Deaths of adults and children due to —people younger than 15 or older than 64— HIV/AIDS are the estimated number of adults to the working-age population (ages 15–64). and children that have died in a speci�c year, Technical notes 163 Migration and remittances in Africa Dilip Ratha, Sanket Mohapatra, Caglar Ozden, Sonia Plaza, and Abebe Shimeles Every country in Africa has been affected by migration. Often Remittances tend to be more stable than other sources of viewed as a “brain drain,� migration can generate substantial ben- foreign exchange, are often countercyclical (helping sustain con- efits for origin countries through remittances, investments, con- sumption and investment during downturns), and improve sover- tacts with foreign markets, technology transfer, enhanced skills of eign creditworthiness and debt sustainability by increasing the returning emigrants, and even increased demand for education level and stability of foreign exchange receipts (Chami, Hakura, (World Bank 2011a). About 30 million Africans (roughly 3 percent and Montiel 2009; IMF 2010; Avendano, Gaillard, and Nieto-Parra of the population) have left their origin country—and sometimes 2009; World Bank 2006). At the micro level, both country and the continent. Some two-thirds of migrants from Sub-Saharan Af- cross-country analyses have shown that remittances reduce pov- rica, particularly the poorer, go to other countries in the region; erty (Adams and Page 2003, 2005; Gupta, Pattillo, and Wagh 2009; the bulk of migrants remain in their subregions.1 By contrast, more Anyanwu and Erhijakpor 2010). Studies of Burkina Faso (Wouterse than 90 percent of North African migrants leave the region, in part 2010), Ghana (Adams 2006; Quartey and Blankson 2004; Adams, because of their proximity to Europe and the Middle East. The top Cuecuecha, and Page 2008), Lesotho (Gustafsson and Makonnen destinations for African migrants are France (9 percent of total em- 1993), Morocco (Bourchachen 2000; Sorensen 2004), and Nige- igrants), Côte d’Ivoire (8 percent), South Africa (6 percent), Saudi ria (Odozia, Awoyemia, and Omonona 2010) conclude that remit- Arabia (5 percent), and the United States and the United Kingdom tances are associated with a reduced share of people in poverty, (4 percent each). The percentage of a country’s population that and in some cased reduced depth and severity of poverty as well. has emigrated is especially large in countries with small popula- Remittances also spur spending on health, education, housing, tions or histories of conflict. and investments.2 Migrant remittance flows to Africa reached nearly $40 billion The Africa Migration Project household surveys show that buy- (2.6 percent of GDP) in 2010 (roughly equally divided between ing land, building a home, and starting a business were among the North Africa and Sub-Saharan Africa), almost double the amount highest uses of remittances—15 percent in Senegal, 20 percent in in 2005 and more than four times the $9.1 billion received in 1990. Uganda, 36 percent in Burkina Faso, 55 percent in Kenya, and 57 Remittances are Africa’s largest source of foreign capital after percent in Nigeria (Plaza, Navarrete, and Ratha 2011). Education foreign direct investments (figure 1). Including flows through in- was the second highest use of remittances from outside Africa into formal channels, the volume of remittances is likely even higher Nigeria and Uganda, the third highest into Burkina Faso, and the (Ratha 2007; Ratha, Mohapatra, and Plaza 2009). Nigeria ac- fourth highest into Kenya. In addition, remittances insure against counted for about half the officially recorded remittances to Sub- adverse shocks. For example, Ethiopian households that receive Saharan Africa in 2010 (World Bank 2011). Other large remittance international remittances were less likely than other households to recipients include Ethiopia, Kenya, Senegal, South Africa, Sudan, sell their productive assets, such as livestock, to cope with food and Uganda. But smaller countries are not the largest recipients shortages (Mohapatra, Joseph, and Ratha 2009). And remittances of remittances as a share of GDP, which include Lesotho, which enable poorer households in KwaZulu-Natal province, South Af- received 27 percent of GDP in 2009. In Cape Verde, Gambia, rica, to access better medical care (Nagarajan 2009). Guinea-Bissau, Liberia, Senegal, Sierra Leone, and Togo remit- However, the cost of sending remittances continues to remain tances were 7–10 percent of GDP. Egypt and Morocco, the two high for Africa, averaging $23 for a $200 transaction, compared largest North African recipients both in dollar-denominated flows with less than $16 for most developing regions. The cost of cross- and as a share of GDP, account for three-quarters of flows to border remittances within Africa, if permitted at all, tends to be the region. even higher. These high costs reflect the limited reach and ex- pense of formal financial services (relative to average African in- Figure 1 Remittances and other resource flows to Africa, comes), the exchange controls on outward transfers in Africa, and 1990–2010 the dominance of a few large money transfer companies, which often work exclusively with commercial banks, post offices, and 60 other providers (IFAD 2009; Irving, Mohapatra, and Ratha 2010). $ billions Foreign direct investment Governments in Africa and in migrant-destination countries out- 40 side Africa should discourage such exclusive agreements. Post Of�cial aid Recorded offices, credit cooperatives, rural banks, and microfinance institu- remittances 20 tions have large networks (particularly among the poor), providing a unique opportunity to expand formal remittance markets among 0 the poor and in rural areas.3 Portfolio debt and private debt Despite these challenges, the rapid adoption of mobile money –20 transfer services is demonstrating enormous potential to broaden 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 (est.) the reach of formal remittance markets and expand access to for- mal financial services. Money transfer services through mobile Source: Authors’ analysis based on data from the World Bank Global Development Finance 2010 database. phone networks have increased significantly in Africa, for example 164 Africa Development Indicators 2011 Migration and remittances in Africa (continued) through M-pesa in Kenya (by end 2010, M-Pesa had more than 12 Adams, Richard H., and John Page. 2003. “International Migration, million customers), Zain/Airtel in more than 15 African countries, Remittances and Poverty in Developing Countries.� Policy Re- Orange Money in West Africa, MTN and Ecobank in Benin, Splash search Working Paper 3179, World Bank, Washington, DC. in Sierra Leone, and Wizzit in South Africa. Some mobile money — — —. 2005. “Do International Migration and Remittances Reduce transfer service providers offer basic deposit and savings ac- Poverty in Developing Countries?� World Development 33 counts in partnership with African banks, such as the “M-Kesho� (10): 1645–69. low-cost savings account offered by Safaricom, in partnership Anyanwu, John C., and Andrew E. O. Erhijakpor. 2010. “Do Interna- with Equity Bank. These services are used mostly for domestic tional Remittances Affect Poverty in Africa?� African Develop- money transfers, while their use for cross-border remittances re- ment Review 22 (1): 51–91 mains limited (other than a few pilots) because of concerns over Avendaño, Rolando, Norbert Gaillard, and Sebastián Nieto Parra. money laundering, insufficient maturity of branchless banking in- 2009. “Are Workers’ Remittances Relevant for Credit Rating frastructure on the receiving end, and lack of customer awareness Agencies?� OECD Development Centre Working Paper 282, Or- and trust in new services (Bold 2010). ganisation for Economic Cooperation and Development, Paris. Large remittance inflows can present a macroeconomic chal- Bold, Chris. 2010. “Borderless, Branchless Banking.� Consul- lenge, however, by causing the exchange rate to appreciate, po- tative Group to Assist the Poor. http://technology.cgap. tentially reducing the production of tradable goods. Policymakers org/2010/12/14/borderless-branchless-banking/ in countries that receive very large remittance flows should be Bourchachen, J. 2000. “Apports des transferts des résidents à alert to their impacts on the exchange rate. In addition to main- l’etranger à la réduction de la pauvreté : Cas du Maroc.� www. taining a flexible exchange rate and considering remittance in- yabiladi.com/clocs/Transfert_sociaux.rme.pdf. flows when crafting targets for reserves policies and money supply Chami, Ralph, Dalia Hakura, and Peter Montiel. 2009. “Remit- growth, African policymakers can implement microeconomic in- tances: An Automatic Stabilizer?� IMF Working Paper 09/91, terventions to ease labor market rigidities and reforms to improve International Monetary Fund, Washington, DC. competitiveness. Clemens, Michael. 2009 “Skill Flow: A Fundamental Reconsidera- African governments can potentially improve their access to tion of Skilled-Worker Mobility and Development�. Working international capital markets by issuing bonds that are securitized Paper 180, Center of Global Development, Washington, DC. by future remittance inflows (Ketkar and Ratha 2009) and by float- Elbadawi, Asmaa, and Rania Roushdy. 2009. “Impact of Inter- ing bonds aimed at the African diaspora (Okonjo-Iweala and Ratha national Migration and Remittances on Child Schooling and 2011). Some measures to expedite these instruments include fa- Child Work: The Case of Egypt.� Paper Prepared for the World cilitating flows through formal remittance channels, obtaining sov- Bank’s MENA International Migration Program Funded by the ereign ratings, and implementing a securitization law. Multilateral European Commission, World Bank, Washington, DC. and bilateral donors can play a role in such transactions. Any in- Gupta, Sanjeev, Catherine A. Pattillo, and Smita Wagh. 2009. “Im- crease in foreign currency debt, however, should be accompanied pact of Remittances on Poverty and Financial Development by prudential risk management. in Sub-Saharan Africa.� World Development 37 (1): 104–15. Gustafsson, Bjorn, and Negatu Makonnen. 1993. “Poverty and Re- Notes mittances in Lesotho.� Journal of African Economies 2 (1): 49–73. 1. In West Africa, for example, more than 70 percent of intra- IFAD (International Fund for Agriculture and Development). 2009. African emigration is within the subregion (World Bank 2011a). Sending Money Home to Africa. Rome: International Fund for 2. See Adams, Cuecuecha, and Page (2008a) for evidence from Agricultural Development. Ghana and Elbadawi and Roushdy (2009) for Egypt. IMF (International Monetary Fund). 2010. “Staff Guidance Note 3. A recent survey by the Universal Postal Union found that 81 on the Application of the Joint Bank-Fund Debt Sustainability percent of post offices in Sub-Saharan Africa are outside the Framework for Low-Income Countries.� Prepared by the staffs three largest cities, where more than 80 percent of Africans of the IMF and the World Bank, January 22. live; by contrast, mainstream commercial banks in Africa are Irving, Jacqueline, Sanket Mohapatra, and Dilip Ratha. 2010. “Mi- concentrated in the largest cities (Clotteau and Anson 2011). grant Remittance Flows: Findings from a Global Survey of Cen- tral Banks.� Working Paper 194, World Bank, Washington, DC. References Ketkar, Suhas, and Dilip Ratha, eds. 2009. Innovative Financing for Adams, Richard H. 2006. “Remittances and Poverty in Ghana.� Development. Washington, DC: World Bank. Policy Research Working Paper 3838, World Bank, Washing- Lachaud. Jean-Pierre. 1999. “Envoi de fonds, inegalite et pauvrete ton, DC. au Burkina Faso.� Documents de travail 40, Groupe d’Economie Adams, Richard H., Alfredo Cuecuecha, and John Page. 2008. du Développement de l’Université Montesquieu Bordeaux IV. “The Impact of Remittances on Poverty and Inequality in Lucas, Robert E.B., and Oded Stark. 1985. “Motivations to Remit: Ghana.� Policy Research Working Paper 4732, World Bank, Evidence from Botswana.� Journal of Political Economy 93 Washington, DC. (5): 901–18. (continued) Technical notes 165 Migration and remittances in Africa (continued) Mohapatra, Sanket, George Joseph, and Dilip Ratha. 2009. “Re- Remittances, Skills, Investments. A joint report of the Afri- mittances and Natural Disasters: Ex-Post Response and Con- can Development Bank and the World Bank, Washington, tribution to Ex-Ante Preparedness.� Policy Research Working DC. Paper 4972, World Bank, Washington, DC. Ratha, Dilip, Sanket Mohapatra, and Sonia Plaza. 2009. “Beyond Nagarajan, Subha. 2009. “Migration, Remittances, and House- Aid: New Sources and Innovative Mechanisms for Financing hold Health: Evidence from South Africa.� Ph.D. dissertation, Development in Sub-Saharan Africa.� In Innovative Financing George Washington University, Washington, DC. for Development, ed. Suhas Ketkar and Dilip Ratha, 143–183. Odozia, John C., Timothy T. Awoyemia, and Bolarin T. Omonona. Washington DC: World Bank. 2010. “Household Poverty and Inequality: The Implication of Sorensen, Ninna Nyberg. 2004. “Migrant Remittances as a Devel- Migrants’ Remittances in Nigeria.� Journal of Economic Policy opment Tool: The Case of Morocco.� IOM Working Paper 2, In- Reform 13 (2): 191–99 ternational Organization for Migration, Geneva. www.belgium. Okonjo-Iweala, Ngozi, and Dilip Ratha, 2011. “Homeward Bond.� iom.int/pan-europeandialogue/documents/remittances_mo- New York Times. rocco.pdf. Quartey, Peter. 2006. “The Impact of Migrant Remittances on House- Tevera, Daniel, and Abel Chikanda. 2009. “Migrant Remittances hold Welfare in Ghana.� Research Paper 158, AERC, Nairobi. and Household Survival in Zimbabwe.� Working Paper, South- Quartey, Peter, and Theresa Blankson. 2004. Do Migrant Remit- ern African Migration Project, Cape Town. tances Minimize the Impact of Macro-volatility on the Poor in World Bank. 2006. Diaspora Networks and the International Mi- Ghana. Report prepared for the Global Development Network, gration of Skills: How Countries Can Draw on Their Talent University of Ghana, Legon. Abroad, ed. Yevgeny Kuznetsov. World Bank: Washington, Plaza, Sonia, Mario Navarrete, and Dilip Ratha. 2011. “Migration DC. and Remittances Household Surveys in Sub-Saharan Africa: — — —. 2011. Leveraging Migration for Africa: Remittances, Skills, Methodological Aspects and Main Findings.� Background Investments. A joint report of the African Development Bank paper, World Bank, DEC-PREM, Migration and Remittances and the World Bank, Washington, DC. Unit, Washington, DC. Wouterse, Fleur. 2010. “Remittances, Poverty, Inequality and ˘ Ratha, Dilip, Sanket Mohapatra, Ça glar Özden, Sonia Plaza, Welfare: Evidence from the Central Plateau of Burkina Faso.� and Abebe Shimeles. 2011. Leveraging Migration for Africa: Journal of Development Studies 46 (4): 771–89. based on the modeling of HIV surveillance WHO/UNAIDS methodology may differ data using standard and appropriate tools. from country methodologies. AIDS orphans are the estimated number of Official development assistance (ODA) dis- children who have lost their mother or both bursements for social mitigation of HIV/AIDS parents to AIDS before age 17 since the epi- are spending on special programs to address demic began in 1990. Some of the orphaned the consequences of HIV/AIDS, such as so- children included in this cumulative total are cial, legal, and economic assistance to people no longer alive; others are no longer under living with HIV/AIDS (including food secu- age 17. rity and employment); spending on support HIV-positive pregnant women receiving to vulnerable groups and children orphaned antiretrovirals to reduce the risk of mother- as a result of HIV/AIDS; and spending on hu- to-child transmission are the number of man rights advocacy for people affected by pregnant women infected with HIV who HIV/AIDS. received antiretrovirals during the last 12 Official development assistance (ODA) dis- months to reduce the risk of mother-to-child bursements for sexually transmitted disease transmission. (STD) control, including HIV/AIDS, are spend- Share of HIV-positive pregnant women receiv- ing on all activities related to STDs and ing antiretrovirals, World Health Organization/ HIV/AIDS control, such as information, edu- Joint United Nations Programme on HIV/AIDS cation, communication, testing, prevention, (WHO/UNAIDS) methodology, is the percent- and treatment. age of pregnant women infected with HIV who received antiretrovirals to reduce the Source: Data on number of people liv- risk of mother-to-child transmission divided ing with HIV/AIDS, HIV prevalence rate, by the total number of pregnant women in- deaths due to HIV/AIDS, AIDS orphans, fected with HIV in the last 12 months. The and HIVpositive pregnant women receiving 166 Africa Development Indicators 2011 antiretrovirals are from UNAIDS and WHO age 5, if subject to current age-speci�c mor- Report on the Global AIDS Epidemic. A more tality rates. The probability is expressed as a detailed explanation of methods and assump- rate per 1,000. tions can be found on the UNAIDS reference Children sleeping under insecticide-treated group on estimates, modeling, and projections nets is the percentage of children under age website (www.unaids.org/en/KnowledgeCen- 5 with access to an insecticide-treated net to tre/HIVData/Epidemiology/) and in a series prevent malaria. of papers published in Sexually Transmitted Children with fever receiving any antimalarial Infections, “Improved Methods and Tools treatment are the percentage of children un- for HIV/AIDS Estimates and Projections,� der age 5 in malaria-risk areas with fever be- 2008, 84 (Suppl I); 2006, 82 (Suppl III); and ing treated with any antimalarial drugs. 2004, 80 (Suppl I). Data on official develop- Pregnant women receiving two doses of inter- ment assistance disbursements are from the mittent preventive treatment are the number Development Assistance Committee of the of pregnant women receiving two or more Organisation for Economic Co-operation and doses of sulfadoxine pyrimethamine dur- Development Geographical Distribution of Fi- ing an antenatal care visit. In some country nancial Flows to Developing Countries, Develop- surveys the site of treatment (during the ment Co-operation Report, and International antenatal care visit) is not speci�ed. This ap- Development Statistics database (www.oecd. proach has been shown to be safe, inexpen- org/dac/stats/idsonline). sive, and effective. Official development assistance (ODA) dis- 11. Malaria bursements for malaria control are spending on prevention and control of malaria. Table .. Malaria Population is total population based on the de Source: Data on population are from the facto de�nition of population, which counts United Nations Population Division World all residents regardless of legal status or Population Prospects: The 2008 Revision, citizenship—except for refugees not perma- census reports and other statistical pub- nently settled in the country of asylum, who lications from national statistical offices, are generally considered part of the popula- Eurostat Demographic Statistics, Secretariat tion of their country of origin. The values of the Paci�c Community Statistics and De- shown are midyear estimates. mography Programme, U.S. Census Bureau Clinical malaria cases reported are the sum International Database, and World Bank of cases con�rmed by slide examination or estimates based on data from these sources rapid diagnostic test and probable and un- as well as household surveys conducted by con�rmed cases (cases that were not tested national agencies, Macro International, the but treated as malaria). National malaria U.S. Centers for Disease Control and Preven- control programs often collect data on the tion, and refugees statistics from the United number of suspected cases, those tested, and Nations High Commissioner for Refugees. those con�rmed. Probable or uncon�rmed Data on clinical cases of malaria reported cases are calculated by subtracting the num- and reported malaria deaths are from the ber tested from the number suspected. Not World Health Organization (WHO) World all cases reported as malaria are true malaria Malaria Report 2009. Data on children cases; most health facilities lack appropriate with fever receiving antimalarial drugs and diagnostic services. The misdiagnosis may pregnant women receiving two doses of in- have led to under- or overreporting malaria termittent preventive treatment are from cases and missing diagnosis of other treat- Demographic Health Surveys, Multiple In- able diseases. dicator Cluster Surveys, and national statis- Reported malaria deaths are all deaths in tical offices. Data on deaths due to malaria health facilities that are attributed to malar- are from the United Nations Statistics Di- ia, whether or not con�rmed by microscopy vision and based on WHO estimates. Data or by rapid diagnostic test. on under-�ve mortality are harmonized es- Under-�ve mortality rate is the probability timates of the WHO, United Nations Chil- that a newborn baby will die before reaching dren’s Fund, and the World Bank, based Technical notes 167 mainly on household surveys, censuses, and Net official development assistance (ODA) vital registration, supplemented by World from non-DAC donors is net ODA from Bank estimates based on household surveys OECD’s non-DAC donors, which include the and vital registration. Data on insecticide- Czech Republic, Hungary, Iceland, Israel, the treated bednet use are from Demographic Republic of Korea, Kuwait, Poland, Saudi and Health Surveys and Multiple Indicator Arabia, the Slovak Republic, Taiwan (China), Cluster Surveys. Data on official develop- Thailand, Turkey, the United Arab Emirates, ment assistance disbursements are from the and other donors. Development Assistance Committee of the Net official development assistance (ODA) Organisation for Economic Co-operation from multilateral donors is net ODA from and Development Geographical Distribution multilateral sources, such as the African De- of Financial Flows to Developing Countries, velopment Fund, the European Development Development Co-operation Report, and Inter- Fund for the Commission of the European national Development Statistics database Communities, the International Develop- (www.oecd.org/dac/stats/idsonline). ment Association, the International Fund for Agricultural Development, Arab- and OPEC- 12. Capable states and partnership �nanced multilateral agencies, and UN pro- grams and agencies. Aid flows from the Inter- Table .. Aid and debt relief national Monetary Fund (IMF) Trust Fund Official development assistance is flows to de- and Structural Adjustment Facility are also veloping countries and multilateral institu- included. UN programs and agencies include tions provided by official agencies, including the United Nations Technical Assistance Pro- state and local governments, or by their ex- gramme, the United Nations Development ecutive agencies, that are administered with Programme, the United Nations Office of the the promotion of the economic development High Commissioner for Refugees, the United and welfare of developing countries as their Nations Children’s Fund, and the World Food main objective and that are concessional in Programme. Arab- and OPEC-�nanced multi- character and convey a grant element of at lateral agencies include the Arab Bank for least 25 percent. Economic Development in Africa, the Arab Net official development assistance (ODA) Fund for Economic and Social Development, from all donors is net ODA from the Organisa- the Islamic Development Bank, the OPEC tion for Economic Co-operation and Devel- Fund for International Development, the opment’s (OECD) Development Assistance Arab Authority for Agricultural Investment Committee (DAC), non-DAC bilateral donors and Development, the Arab Fund for Techni- (Organization of Petroleum Exporting Coun- cal Assistance to African and Arab Countries, tries [OPEC], the former Council for Mutual and the Islamic Solidarity Fund. Economic Assistance [CMEA] countries, and Net private official development assistance China), and multilateral donors. OPEC coun- (ODA) is private ODA transactions broken, tries are Algeria, Iran, Iraq, Kuwait, Libya, which comprise direct investment, portfolio Nigeria, Qatar, Saudi Arabia, the United Arab investment, and export credits (net). Private Emirates, and Venezuela. The former CMEA transactions are undertaken by �rms and in- countries are Bulgaria, Czechoslovakia, the dividuals resident in the reporting country. former German Democratic Republic, Hun- Portfolio investment corresponds to bonds gary, Poland, Romania, and the former Soviet and equities. Inflows into emerging coun- Union. tries’ stocks markets, are, however, heavily Net official development assistance (ODA) understated. from DAC donors is net ODA from OECD’s Accordingly, the coverage of portfolio in- DAC donors, which are Australia, Austria, vestment differs in these regards from the Belgium, Canada, Denmark, Finland, France, coverage of bank claims, which include ex- Germany, Greece, Ireland, Italy, Japan, Lux- port credit lending by banks. The bank claims embourg, the Netherlands, New Zealand, data represent the net change in bank claims Norway, Portugal, Spain, Sweden, Switzer- after adjusting for exchange rate changes and land, the United Kingdom, and the United are therefore a proxy for net flow data but are States. not themselves a net flow �gure. They differ 168 Africa Development Indicators 2011 in two further regards from other OECD under the 1999 Food Aid Convention to fa- data. First, they relate to loans by banks resi- cilitate comparisons between deliveries of dent in countries that report quarterly to the different commodities. Deliveries of food aid Bank for International Settlements. Second, refer to quantities of commodities that actu- no adjustment has been made to exclude ally reached the recipient country during a short-term claims. given period. For cereals the period refers to Net official development assistance (ODA) as July–June, beginning in the year shown. a share of gross domestic product (GDP) is calcu- Heavily Indebted Poor Countries (HIPC) Debt lated by dividing the nominal total net ODA Initiative decision point is the date at which from all donors by nominal GDP. For a given an HIPC with an established track record of level of aid flows, devaluation of a recipi- good performance under adjustment pro- ent’s currency may inflate the ratios shown grams supported by the International Mon- in the table. Thus, trends for a given country etary Fund and the World Bank commits to and comparisons across countries that have undertake additional reforms and to develop implemented different exchange rate policies and implement a poverty reduction strategy. should be interpreted carefully. HIPC Debt Initiative completion point is the Net official development assistance (ODA) date at which the country successfully com- per capita is calculated by dividing the nomi- pletes the key structural reforms agreed on at nal total net ODA (net disbursements of the decision point, including developing and loans and grants from all official sources on implementing its poverty reduction strategy. concessional �nancial terms) by midyear The country then receives the bulk of debt population. These ratios offer some indica- relief under the HIPC Initiative without fur- tion of the importance of aid flows in sus- ther policy conditions. taining per capita income and consumption Debt service relief committed is the amount levels, although exchange rate fluctuations, of debt service relief, calculated at the deci- the actual rise of aid flows, and other factors sion point, that will allow the country to vary across countries and over time. achieve debt sustainability at the completion Net official development assistance (ODA) as point. a share of gross capital formation is calculated The Multilateral Debt Relief Initiative (MDRI) by dividing the nominal total net ODA by is meant to provide additional support to gross capital formation. These data highlight HIPCs to achieve the Millennium Develop- the relative importance of the indicated aid ment Goals while ensuring that the �nancing flows in maintaining and increasing invest- capacity of the international �nancial insti- ment in these economies. The same caveats tutions is preserved. The MDRI provides a mentioned above apply to their interpreta- framework that commits to achieve two ob- tion. Furthermore, aid flows do not exclusive- jectives: deepening debt relief to HIPCs while ly �nance investment (for example, food aid safeguarding the long-term �nancial capac- �nances consumption), and the share of aid ity of the International Development Asso- going to investment varies across countries. ciation (IDA) and the African Development Net official development assistance (ODA) as Fund; and encouraging the best use of ad- a share of imports of goods and services is calcu- ditional donor resources for development by lated by dividing nominal total net ODA by allocating them to low-income countries on imports of goods and services. the basis of policy performance. Debt relief Net official development assistance (ODA) as to be provided under the MDRI will be in ad- a share of central government expenditure is cal- dition to existing debt relief commitments by culated by dividing nominal total net ODA by IDA and other creditors under the Enhanced central government expenditure. HIPC Debt Initiative. The MDRI calls for 100 Food aid shipments are transfers of food percent cancellation of IDA, African Devel- commodities (food aid received) from donor opment Fund, and IMF debt for countries to recipient countries on a total-grant basis that reach the HIPC completion point. The or on highly concessional terms. Processed costs include principal and interest forgone and blended cereals are converted into their for all multilateral �nancial institutions par- grain equivalent by applying the conversion ticipating in the initiative, except for the IMF, factors included in the Rule of Procedures whose costs reflect the stock of debt eligible Technical notes 169 for MDRI relief, which is the debt outstand- questionnaire for governments and donors ing (principal only) as of end-2004 that has are used to calculate the indicators. not been repaid by the member and is not PDI-1 Operational national development covered by HIPC assistance. strategies are the extent to which a country has an operational development strategy to Source: Data on net official development guide its aid coordination effort and over- assistance are from the Development As- all development. The score is based on the sistance Committee of the Organisation World Bank 2005 Comprehensive Development for Economic Co-operation and Develop- Framework Progress Report. An operational ment Geographical Distribution of Financial strategy calls for a coherent long-term strat- Flows to Developing Countries, Development egy derived from it; speci�c targets serving a Co-operation Report, and International De- holistic, balanced, and well sequenced devel- velopment Statistics database (www.oecd. opment strategy; and capacity and resources org/dac/stats/idsonline). Data on food aid for its implementation. shipments are based on data compiled by PDI-2a Reliable public �nancial management from the Food and Agriculture Organization is the World Bank annual Country Policy and based on information from the World Food Institutional Assessment rating for the quali- Programme. Data on HIPC countries are ty of public �nancial management. Measured from IDA and IMF “Heavily Indebted Poor on a scale of 1 (worst) to 5 (best), its focus Countries (HIPC) Initiative and Multilateral is on how much existing systems adhere to Debt Relief Initiative (MDRI)—Status of broadly accepted good practices and whether Implementation.� Data on external debt a reform program is in place to promote im- are mainly from reports to the World Bank proved practices. through its Debtor Reporting System from PDI-2b Reliable country procurement systems member countries that have received Inter- measure developing countries’ procurement national Bank for Reconstruction and De- systems. Donors use national procurement velopment loans or IDA credits, as well as procedures when the funds they provide World Bank and IMF �les. for the implementation of projects and pro- grams are managed according to the national Table .. Status of Paris Declaration procurement procedures as they were estab- indicators lished in the general legislation and imple- The third round of Monitoring the Paris Dec- mented by government. The use of national laration began in the fourth quarter of 2010 procurement procedures means that donors and was completed in March 2011. These do not make additional or special require- data will be updated online in the fourth ments for governments on the procurement quarter of 2011. of works, goods, and services. (Where weak- The Paris Declaration is the outcome of nesses in national procurement systems the 2005 Paris High-Level Forum on Aid have been identi�ed, donors may work with Effectiveness, where 60 partner countries, partner countries to improve the efficiency, 30 donor countries, and 30 development economy, and transparency of their imple- agencies committed to speci�c actions to mentation.) The objective of this indicator is further country ownership, harmonization, to measure and encourage improvements in alignment, managing for development re- developing countries’ procurement systems. sults, and mutual accountability for the use PDI-3 Government budget estimates com- of aid. Participants agreed on 12 indicators. prehensive and realistic are the percentage These indicators include good national de- of aid that is accurately recorded in the na- velopment strategies, reliable country sys- tional budget, thereby allowing scrutiny by tems for procurement and public �nancial parliaments. management, the development and use of PDI-4 Technical assistance aligned and coordi- results frameworks, and mutual assessment nated with country programs is the percentage of progress. Qualitative desk reviews by the of technical cooperation that is free stand- Organisation for Economic Co-operation ing and embedded and that respects own- and Development’s Development Assistance ership (partner countries exercise effective Committee and the World Bank and a survey leadership over their capacity development 170 Africa Development Indicators 2011 programs), alignment (technical cooperation uses it to purchase goods and services from in support of capacity development aligns suppliers based in the donor country. with countries’ development objectives and PDI-9 Aid provided in the framework of pro- strategies), and harmonization (when more gram-based approaches is the percentage of than one donor is involved in supporting development cooperation that is based on partner-led capacity development, donors co- the principles of coordinated support for a ordinate their activities and contributions). locally owned program of development, such PDI-5a and 5b Aid for government sectors as a national development strategy, a sector uses country public �nancial management and program, a thematic program, or a program country procurement systems is the percentage of a speci�c organization. Program-based ap- of donors that use country, rather than do- proaches share the following features: leader- nor, systems for managing aid disbursement. ship by the host country or organization; a PDI-6 Project implementation units parallel single comprehensive program and budget to country structures is the number of par- framework; a formalized process for donor allel project implementation units, which coordination and harmonization of donor refers to units created outside existing procedures for reporting, budgeting, �nancial country institutional structures. The sur- management, and procurement; and efforts vey guidance distinguishes between project to increase the use of local systems for pro- implementation units and executing agen- gram design and implementation, �nancial cies and describes three typical features of management, monitoring, and evaluation. parallel project implementation units: they PDI-10a Donor missions coordinated are the are accountable to external funding agen- percentage of missions undertaken jointly cies rather than to country implementing by two or more donors and missions under- agencies (ministries, departments, agencies, taken by one donor on behalf of another (del- and the like), most of the professional staff egated cooperation). is appointed by the donor, and the person- PDI-10b Country analysis coordinated is the nel salaries often exceed those of civil ser- percentage of country analytic work that is vice personnel. Interpretation of the Paris undertaken by one or more donors jointly or Declaration survey question on this subject undertaken by one donor on behalf of anoth- was controversial in a number of countries. er donor (including work undertaken by one It is unclear whether within countries all do- and used by another when it is co�nanced nors applied the same criteria with the same and formally acknowledged in official docu- degree of rigor or that across countries the mentation and undertaken with substantive same standards were used. In several cases involvement from government). the descriptive part of the survey results PDI-11 Existence of a monitorable perfor- indicates that some donors applied a legal- mance assessment framework measures the istic criterion of accountability to the formal extent to which the country has realized its executing agency, whereas the national co- commitment to establishing performance ordinator and other donors would have pre- frameworks. The indicator relies on the ferred greater recognition of the substantive scorings of the 2005 Comprehensive De- reality of accountability to the donor. Some velopment Framework Progress Report and respondents may have confused the de�ni- considers three criteria: the quality of devel- tional question (Is the unit “parallel�?) with opment information, stakeholder access to the aid management question (Is the paral- development information, and coordinated lelism justi�ed in terms of the developmen- country-level monitoring and evaluation. tal bene�ts and costs?). The assessments therefore reflect both the PDI-7 Aid disbursements on schedule and extent to which sound data on development recorded by government are the percentage of outputs, outcomes, and impacts are collected funds that are disbursed within the year they and various aspects of the way information is are scheduled and accurately recorded by used, disseminated among stakeholders, and partner authorities. fed back into policy. PDI-8 Bilateral aid that is untied is the per- PDI-12 Existence of a mutual accountability centage of aid that is untied. Tied aid is aid review indicates whether there is a mecha- provided on the condition that the recipient nism for mutual review of progress on aid Technical notes 171 effectiveness commitments. This is an im- for misconduct. Higher values indicate portant innovation of the Paris Declaration greater power for shareholders to challenge because it develops the idea that aid is more transactions. effective when both donors and partner Investor protection index measures the de- governments are accountable to their con- gree to which investors are protected through stituents for the use of resources to achieve disclosure of ownership and �nancial infor- development results and when they are ac- mation regulations. Higher values indicate countable to each other. The speci�c focus better protection. is mutual accountability for the implemen- Number of tax payments is the number of tation of the partnership commitments in- taxes paid by businesses, including electronic cluded in the Paris Declaration and any local �ling. The tax is counted as paid once a year agreements on enhancing aid effectiveness. even if payments are more frequent. Time required to prepare, �le, and pay taxes Source: Organisation for Economic Co- is the number of hours it takes to prepare, operation and Development 2008 Survey on �le, and pay (or withhold) three major types Monitoring the Paris Declaration: Making Aid of taxes: the corporate income tax, the More Effective by 2010. value added or sales tax, and labor taxes, including payroll taxes and social security Table .. Capable states contributions. Firms that believe the court system is fair, impar- Total tax rate is the total amount of taxes tial, and uncorrupt are the percentage of �rms payable by the business (except for labor that believe the court system is fair, impar- taxes) after accounting for deductions and tial, and uncorrupt. exemptions as a percentage of gross pro�t. Corruption is the percentage of �rms iden- For further details on the method used for tifying corruption as a major constraint to assessing the total tax payable, see the World current operation. Bank Doing Business 2006. Crime, theft, and disorder are the percentage Extractive Industries Transparency Initia- of �rms identifying crime, theft, and disorder tive (EITI) status refers to a country’s imple- as a major constraint to current operation. mentation status for the EITI, a multistake- Number of procedures to enforce a contract is holder approach to increasing governance the number of independent actions, mandat- and transparency in extractive industries. It ed by law or courts, that demand interaction includes civil society, the private sector, and between the parties of a contract or between government and requires a work plan with a them and the judge or court officer. timeline and budget to ensure sustainability, Time required to enforce a contract is the independent audit of payments and disclo- number of calendar days from the �ling of sure of revenues, publication of results in a the lawsuit in court until the �nal determina- publicly accessible manner, and an approach tion and, in appropriate cases, payment. that covers all companies and government Cost to enforce a contract is court and attor- agencies. The EITI supports improved gover- ney fees, where the use of attorneys is man- nance in resource-rich countries through the datory or common, or the cost of an adminis- veri�cation and full publication of company trative debt recovery procedure, expressed as payments and government revenues from a percentage of the debt value. oil, gas, and mining. Intent to implement in- Protecting investors disclosure index mea- dicates that a country intends to implement sures the degree to which investors are pro- the EITI but has not yet met the four initial tected through disclosure of ownership and requirements to join: an unequivocal pub- �nancial information. Higher values indicate lic statement of its intention to implement more disclosure. the EITI; a commitment to work with civil Director liability index measures a plain- society and companies on EITI implementa- tiff ’s ability to hold directors of �rms liable tion; a senior official appointed to lead EITI for damages to the company. Higher values implementation; and a widely distributed, indicate greater liability. fully costed work plan with measurable tar- Shareholder suits index measures share- gets, a timetable for implementation, and an holders’ ability to sue officers and directors assessment of government, private sector, 172 Africa Development Indicators 2011 and civil society capacity constraints. Can- credibility of the government’s commitment didate indicates that a country has met the to such policies. four initial requirements to join the EITI and Regulatory quality measures the ability of has begun a range of activities to strengthen the government to formulate and implement revenue transparency, as documented in the sound policies and regulations that permit country’s work plan. Once a country has be- and promote private sector development. come an EITI candidate, it has two years to Rule of law measures the extent to which be validated as compliant. Compliant indi- agents have con�dence in and abide by the cates that a country has successfully under- rules of society, in particular the quality of gone validation, an independent assessment contract enforcement, the police, and the of a country’s progress toward the EITI goals courts, as well as the likelihood of crime and by the EITI International Board. Validation is violence. based on the country’s work plan, the EITI Control of corruption measures the extent validation grid and indicator assessment to which public power is exercised for private tools, and company forms that detail private gain, including petty and grand forms of cor- companies’ extractive industry activities; ruption, as well as “capture� of the state by the board provides guidance for countries’ elites and private interests. future activity related to EITI compliance. Expected to pay informal payment to public Countries must undergo validation every �ve officials to get things done is the percentage of years or at the request of the EITI Interna- �rms that expected to make informal pay- tional Board. ments or give gifts to public officials to “get things done� with regard to customs, taxes, Source: Data on investment climate con- licenses, regulations, services, and the like. straints to �rms are World Bank Enterprise Expected to give gifts to obtain an operating Surveys (http://rru.worldbank.org/Enter- license is the percentage of �rms that expect- priseSurveys). Data on enforcing contracts, ed to give gifts or an informal payment to get protecting investors, and regulation and tax an operating license. administration are from the World Bank Do- Expected to give gifts in meetings with tax ing Business project (http://rru.worldbank. officials is the percentage of �rms that an- org/DoingBusiness/). Data on corruption swered yes to the question “Was a gift or in- perceptions index are from Transparency In- formal payment expected or requested dur- ternational (www.transparency.org/policy_re- ing a meeting with tax officials?� search/surveys_indices/cpi). Data on the EITI Expected to give gifts to secure a government are from the EITI website (www.eitranspar- contract is the percentage of �rms that ex- ency.org). pected to make informal payments or give gifts to public officials to secure a govern- Table .. Governance and ment contract. anticorruption indicators Share of �rms identifying control of corrup- Voice and accountability measure the extent tion as a major constraint measures the extent to which a country’s citizens are able to par- to which public power is exercised for private ticipate in selecting their government and to gain, including petty and grand forms of cor- enjoy freedom of expression, freedom of as- ruption, as well as “capture� of the state by sociation, and a free media. elites and private interests. Political stability and absence of violence Mean corruption perceptions index score is measure the perceptions of the likelihood the country’s score in Transparency Inter- that the government will be destabilized national’s annual corruption perceptions or overthrown by unconstitutional or vio- index, which ranks more than 150 countries lent means, including domestic violence or in terms of perceived levels of corruption, as terrorism. determined by expert assessments and opin- Government effectiveness measures the ion surveys. quality of public services, the quality and Open budget index overall score is the coun- degree of independence from political pres- try’s score on a subset of 91 questions from sures of the civil service, the quality of policy the Open Budget Survey. The questions fo- formulation and implementation, and the cus on the public availability of eight key Technical notes 173 budget documents (with a particular em- �scal policy (taking into account phasis on the executive’s budget proposal) monetary and exchange rate policy and the information they contain. The open and the sustainability of the public budget index is calculated based on detailed debt) and its impact on growth. questionnaires completed by local experts in • Debt policy assesses whether the 59 participating countries from every conti- debt management strategy is con- nent. In 2008, based on inputs received from ducive to minimize budgetary researchers and extensive in-house reviews, risks and ensure long-term debt the International Budget Partnership made sustainability. three changes in its methodology. The �rst • Structural policies change concerns the timing of the release of • Trade assesses how the policy the eight key budget documents assessed by framework fosters trade in goods. the survey. The second is the inclusion of the It covers two areas: trade regime enacted budget in calculating country scores restrictiveness—which focuses on for the index. The third is revisions to the an- the height of tariff barriers, the swers of a few questions used to assess Brazil extent to which nontariff barri- and Nigeria. ers are used, the transparency and predictability of the trade regime, Source: Data on governance indicators are and customs and trade facilitation from the World Bank Institute Worldwide —which includes the extent to Governance Indicators database, which relies which the customs service is free of on 33 sources, including surveys of enter- corruption, relies on risk manage- prises and citizens and expert polls, gathered ment, processes duty collections from 30 organizations around the world. and refunds promptly, and oper- Data on corruption perceptions index scores ates transparently. are from Transparency International (www. • Financial sector assesses the struc- transparency.org). Data on the open budget ture of the �nancial sector and the index are from www.openbudgetindex.org. policies and regulations that af- fect it. It covers three dimensions: Table .. Country Policy and �nancial stability; the sector’s ef- Institutional Assessment ratings �ciency, depth, and resource mo- The Country Policy and Institutional Assess- bilization strength; and access to ment (CPIA) assesses the quality of a coun- �nancial services. try’s present policy and institutional frame- • Business regulatory environment as- work. “Quality� means how conducive that sesses the extent to which the legal, framework is to fostering sustainable, pov- regulatory, and policy environment erty-reducing growth and the effective use helps or hinders private business of development assistance. The CPIA is con- in investing, creating jobs, and be- ducted annually for all International Bank coming more productive. The em- for Reconstruction and Development and phasis is on direct regulations of International Development Association bor- business activity and regulation of rowers and has evolved into a set of criteria goods and factor markets. It mea- grouped into four clusters with 16 criteria sures three subcomponents: regu- that reflect a balance between ensuring that lations affecting entry, exit, and all key factors that foster pro-poor growth competition; regulations of ongo- and poverty alleviation are captured, without ing business operations; and regu- overly burdening the evaluation process. lations of factor markets (labor and • Economic management land). • Macroeconomic management assess- • Policies for social inclusion and equity es the quality of the monetary, ex- • Gender equality assesses the extent change rate, and aggregate demand to which the country has enacted policy framework. and put in place institutions and • Fiscal policy assesses the short- and programs to enforce laws and poli- medium-term sustainability of cies that promote equal access for 174 Africa Development Indicators 2011 Conflict-affected and fragile states in Africa Bernard Harborne, Noro Aina Andriamihaja, and Viola Erdmannsdoerfer While the definition of armed conflict (associated with the num- level. However, World Development Report 2011 broadened the ber of battle-related deaths) is fairly well accepted, fragility re- definition to include conflict indicators, such as annual homicide mains somewhat ill-defi ned. Indeed, some people prefer the rates of more than 10 per 100,000 people, annual battle deaths term “fragile situations� to fragile states. Using the harmonized of more than 1,000 people, and the presence of a UN peace- Country Policy and Institutional Assessment (CPIA) score (less keeping mission. Using the World Development Report defini- than or equal to 3.2 as a threshold), the World Bank has defined tion, 20 of Sub-Saharan Africa’s 47 countries are either fragile fragile states as low-income countries with a low institutional or conflict-affected. Map 1 The cohort of fragile states was unchanged over 2005–09 Country Policy and Institutional Assessment (International Development Association countries only) scores 2005 2009 Lower than 3.2 Lower than 3.2 3.2–3.5 3.2–3.5 Higher than 3.5 Higher than 3.5 No data No data The cohort of fragile states (both core and marginal) remained Despite these trends, armed conflict and violence remain criti- fairly constant over 2005–09 (map 1), with only one country leaving cal challenges to development. The data remain unreliable, but the core set of fragile states (Nigeria) and two leaving the marginal some figures suggest the challenges are massive. Since 1998 the fragile states (Mozambique and Rwanda). While many countries conflict and humanitarian crisis in the Democratic Republic of the have stagnant CPIA scores, Angola, Burundi, Central African Re- Congo has caused the deaths of 5.4 million people (International public, Liberia, and Sierra Leone have slightly improved, but they Rescue Committee 2008), mostly from disease and malnutrition, are still on the fragility threshold. Five countries’ scores have fallen and the rape of some 1.8 million women (Peterman, Palermo, and (Chad, Côte d’Ivoire, Eritrea, Somalia, and Zimbabwe), and the num- Bredenkamp 2011). Some 2 million people were killed during the ber of violently disputed elections (Côte d’Ivoire, Kenya) and military civil war between northern and southern Sudan and between coups d’état (Mauritania, Guinea, Madagascar, Niger) has risen. 180,000–400,000 persons died as a result of armed conflict in Since the 1990s, Africa has had the most countries in armed Darfur (Degomme and Guha-Sapir 2010). And in 2010 there were conflict, with a peak in 1998–99 when almost half of the countries around 10.3 million internally displaced persons and 2.5 million in fragile or conflict situations in Sub-Saharan Africa were involved refugees across Sub-Saharan Africa. Violence is not simply re- in armed conflict. Global trends suggest a gradual decline in the lated to armed conflict; in 2006 the Southern Africa region had the numbers of both armed conflicts and battle-related deaths, both in highest intentional homicide rate in the world of 37 per 100,000 and outside Africa; the annual average number of conflict-affected people (United Nations Office on Drugs and Crime 2010). states in Sub-Saharan Africa fell from 16 in the 1990s to 6 in 2007 Fragile and conflict-affected states (both core and marginal) (Human Security Report Project 2008). This positive trend has in- are finding it hard to achieve the Millennium Development Goals creased the responsibility of post-conflict recovery interventions and are the most vulnerable to external shocks, such as oil and international peacekeeping—some 78,400 UN and AU peace- and food price increases. Most of the core fragile countries keeping troops work in Sub-Saharan Africa (map 2). have very high (more than 35 percent) and high (24–35 percent) (continued) Technical notes 175 Governance, conflict-affected and fragile states in Africa (continued) undernourishment (FAOSTAT 2010). Despite some success—in Democratic Republic of the Congo, and Sudan remain way off. Ethiopia, Guinea, and Niger—most fragile countries in Africa Most of those countries are also cereal net importers. Around are far from the maternal mortality and infant mortality tar- 6.4 million people in Sudan and 2.4 million in Somalia need ex- gets. While such countries as Cameroon are on target for ac- ternal assistance due to conflict and rising food prices (Barungi cess to safe water, core fragile countries such as Burundi, the and others 2011). Map 2 Conflict, political stability, and violence in Africa Political stability and absence of violence index, 2009 Refugees and peacekeeping operations, 2011 Former Former Spanish UN Spanish Sahara Sahara Cape Verde Mauritania Mauritania –1.17 Mali Mali Chad Sudan 0.82 Niger Chad Cape Verde Niger –0.27 –1.17 Sudan Eritrea Senegal 21,646 348,500 Eritrea Senegal –1.75 822 –2.65 –0.80 16,305 –0.15 UN UA 197,313 0.26 The Gambia Burkina Faso Darfur, Chad, The Gambia Burkina Faso Darfur, Chad, –0.49 Guinea-Bissau Guinea –0.12 Central African Guinea-Bissau Guinea Central African –1.90 Benin Nigeria Ethiopia Horn, Benin Nigeria Ethiopia Horn, Côte Ghana 0.44 Republic 10,920 Côte Republic –1.95 –1.73 Somalia 1,109 Ghana 15,608 Somalia –0.40 Sierra Leone d’Ivoire 0.16 South Sierra Leone d’Ivoire South 62,873 Central African Republic Sudan Central African Republic Sudan Liberia –1.53 Cameroon –2.03 Somalia 15,417 Cameroon Somalia UA Côte d’Ivoire, –0.99 Liberia 23,153 154,005 –0.21 Togo Equatorial –0.41 –3.31 Guinea, Uganda UN 71,572 UN Togo Equatorial Uganda 678,308 Guinea Kenya Guinea Kenya Sierra Leone, –0.02 Gabon Congo –1.06 –1.30 18,377 Gabon 7,544 Liberia 0.12 –0.41 Congo, Dem. Rep. Congo, Dem. Rep. 9,620 São Tomé and Príncipe –2.13 Côte d’Ivoire, Rwanda –0.33 São Tomé and Príncipe 455,852 Rwanda 129,109 0.22 Guinea, Congo Great Burundi –1.42 Sierra Leone, UN Great Burundi 94,239 Tanzania Seychelles 20,544 Tanzania Lakes 0.08 Liberia Lakes 0.71 Seychelles Angola Comoros –1.01 Angola Comoros –0.24 Malawi Malawi Zambia –0.06 141,021 Zambia 0.51 Madagascar Madagascar Zimbabwe Mozambique Zimbabwe Mozambique –1.44 –0.67 0.61 Mauritius Mauritius 0.48 22,449 Namibia Botswana Namibia Botswana 0.80 0.91 Lower than –1.5 Number of refugees originating in country –1.5 to 0 Swaziland 0.02 UN UN peacekeeping operation presence Swaziland Higher than 0 South Africa Lesotho 0.36 UA UA peacekeeping operation presence South Africa Lesotho 0.02 Fragile states Localized conflicts War-to-peace transitions Fragile states and Potential flashpoints Dangerous neighborhoods war-to-peace transitions According to the literature, risk factors associated with conflict to reintegrate former rebel soldiers into society while sustaining its and violence in Sub-Saharan Africa include low per capita income, objectives of increased and sustained inclusive economic growth. horizontal and vertical inequality between groups, ethnic fractional- ization, political repression, electoral crisis, legacies of colonialism, Figure 1 Net of�cial development aid to fragile states in superpower rivalry, and competition for natural resources (World Sub-Saharan Africa, 1960–2005 Bank 2011; African Development Bank 2008). While the causality 2,500 $ millions between natural resources and conflict is not empirical, the armed Congo, Rep. Côte d’Ivoire conflict in eastern Congo associated with the illicit exploitation of Liberia Mozambique minerals is but one example of the challenges confronting African Rwanda 2,000 Sierra Leone states. Most African countries are endowed with natural resources, Somalia Sudan some of which are fragile or conflict-affected, such as Namibia or Botswana. The connections between natural resources and 1,500 conflict highlight the presence of weak accountability, poor gov- ernance, and weak institutions. Other aggravating challenges are high levels of unemployment and underemployment, particularly in 1,000 urban areas, as well as rising food prices, the poor performance of security and justice institutions, and large-scale corruption. But all is not about failure in fragile and conflict-affected states. 500 The last years have also produced some post-conflict successes, such as in Mozambique, Sierra Leone, and Rwanda, which has focused on generating rapid economic growth to deal with its his- 0 tory of genocide. Also, Uganda implemented an amnesty program 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2009 176 Africa Development Indicators 2011 Governance, conflict-affected and fragile states in Africa (continued) World Development Report 2011 highlights ways external sup- FAOSTAT. 2010. “FAO Hunger MAP in 2010: Prevalence of Under- port can support such transitions. While official aid started to peak in nourishment in Developing Countries.� Food and Agriculture the 1990s and average volumes have been increasing, aid has been Organization, Rome. volatile. Sustained internal and external support is required to help Human Security Report Project. 2008. Human Security Brief 2007. countries move from fragility to peace and prosperity for the long term. Vancouver, Canada: Human Security Report Project. International Rescue Committee. 2008. Mortality in the DRC: An References Ongoing Crisis. New York: International Rescue Committee. African Development Bank. 2008. Africa Development Report Peterman, Amber, Tia Palermo, and Caryn Bredenkamp. 2011. “Es- 2008/2009: Conflict Resolution, Peace and Reconstruction in timates and Determinants of Sexual Violence against Women Africa. Oxford, UK: Oxford University Press. in the Democratic Republic of Congo.� American Journal of Barungi, Barbara, Kazuhiro Numasawa, Adeleke Salami, and Public Health 101 (6): 1060. Adalbert Nshimyumuremyi. 2011. “The Impact of the 2010–11 United Nations Office on Drugs and Crime. 2010. Update Report Surge in Food Prices on African Countries in Fragile Situa- No. 5. New York: United Nations. tions.� Africa Economic Brief 2 (4). World Bank. 2011. World Development Report 2011: Conflict, Se- Degomme, Olivier and Debarati Guha-Sapir. 2010. “Patterns of Mor- curity, and Development. Washington, DC: World Bank. tality Rates in Darfur conflict.� The Lancet 375 (9711): 294–300. men and women to human capital collection trends at the national and development and productive and subnational levels should be consid- economic resources and that give ered. The expenditure component men and women equal status and receives two-thirds of the weight in protection under the law. computing the overall rating. • Equity of public resource use assesses • Building human resources assesses the extent to which the pattern of the national policies and public public expenditures and revenue and private sector service delivery collection affects the poor and is that affect access to and quality of consistent with national poverty re- health and nutrition services, in- duction priorities. The assessment cluding: population and reproduc- of the consistency of government tive health; education, early child- spending with the poverty reduc- hood development, and training tion priorities takes into account and literacy programs; and preven- the extent to which individuals, tion and treatment of HIV/AIDS, groups, or localities that are poor, tuberculosis, and malaria. vulnerable, or have unequal access • Social protection and labor assess to services and opportunities are government policies in the area of identi�ed; a national development social protection and labor market strategy with explicit interventions regulation, which reduce the risk to assist those individuals, groups, of becoming poor, assist those who and localities has been adopted; are poor to better manage further and the composition and incidence risks, and ensure a minimal level of public expenditures are tracked of welfare for all people. Interven- systematically and their results fed tions include social safety net pro- back into subsequent resource al- grams, pension and old-age savings location decisions. The assessment programs, protection of basic labor of the revenue collection dimension standards, regulations to reduce takes into account the incidence of segmentation and inequity in la- major taxes—for example, whether bor markets, active labor market they are progressive or regressive programs (such as public works or —and their alignment with pov- job training), and community driv- erty reduction priorities. When en initiatives. In interpreting the relevant, expenditure and revenue guidelines it is important to take Technical notes 177 into account the size of the econo- (including teachers, health work- my and its level of development. ers, and police) are structured to • Policies and institutions for envi- design and implement government ronmental sustainability assess the policy and deliver services effec- extent to which environmental tively. Civilian central government policies foster the protection and staffs include the central executive sustainable use of natural resourc- together with all other ministries es and the management of pollu- and administrative departments, tion. Assessment of environmental including autonomous agencies. It sustainability requires multidimen- excludes the armed forces, state- sional criteria (that is, for air, water, owned enterprises, and subnation- waste, conservation management, al governments. coastal zones management, and • Transparency, accountability, and natural resources management). corruption in public sector assess • Public sector management and institu- the extent to which the executive tions branch can be held accountable for • Property rights and rule-based gov- its use of funds and the results of ernance assess the extent to which its actions by the electorate and by private economic activity is facili- the legislature and judiciary and to tated by an effective legal system which public employees within the and rule-based governance struc- executive branch are required to ac- ture in which property and con- count for the use of resources, ad- tract rights are reliably respected ministrative decisions, and results and enforced. Three dimensions are obtained. Both levels of account- rated separately: legal basis for se- ability are enhanced by transparen- cure property and contract rights; cy in decisionmaking, public audit predictability, transparency, and institutions, access to relevant and impartiality of laws and regula- timely information, and public and tions affecting economic activity media scrutiny. and their enforcement by the legal and judicial system; and crime and Source: World Bank Group CPIA database violence as an impediment to eco- (www.worldbank.org/ida). nomic activity. • Quality of budgetary and �nancial Table .. Polity indicators management assesses the extent to Revised combined polity score is computed by which there is a comprehensive and subtracting the institutionalized autocracy credible budget, linked to policy pri- score from the institutionalized democracy orities; effective �nancial manage- score. The resulting uni�ed polity scale rang- ment systems to ensure that the es from +10 (strongly democratic) to –10 budget is implemented as intended (strongly autocratic). in a controlled and predictable way; Institutionalized democracy is conceived and timely and accurate accounting as three essential, interdependent ele- and �scal reporting, including timely ments. One is the presence of institutions and audited public accounts and ef- and procedures through which citizens can fective arrangements for follow-up. express effective preferences about alter- • Efficiency of revenue mobilization as- native policies and leaders. Second is the sesses the overall pattern of reve- existence of institutionalized constraints nue mobilization—not only the tax on the exercise of power by the executive. structure as it exists on paper but Third is the guarantee of civil liberties to revenue from all sources as they are all citizens in their daily lives and in acts actually collected. of political participation. Other aspects of • Quality of public administration plural democracy —such as the rule of law, assesses the extent to which ci- systems of checks and balances, freedom vilian central government staffs of the press, and so on—are means to, or 178 Africa Development Indicators 2011 The political economy of public policies and government failures Stuti Khemani In the mid-1980s, Sub-Saharan Africa was dominated by fully au- public payroll is more important for political survival and extract- tocratic regimes—31 of 40 in the database were fully autocratic, ing rents from political office than it is for managing teachers better with just 3 full-fledged democracies (Botswana, Gambia, and and holding them accountable for quality learning outcomes. Cli- Mauritius) and 6 intermediate regimes, most of which had a heavy entelism has been traced to underlying conditions of entrenched weight of autocracy, according to Polity IV scores1 (figure 1). By inequality, social polarization, and lack of information and credible end 2009, it had 12 fully democratic regimes (Benin, Comoros, political promises. Ghana, Kenya, Lesotho, Mali, Senegal, Sierra Leone, South Africa Nevertheless, sustained political competition, democratic and Zambia, in addition to the already democratic Botswana and conditions, and new research in Africa suggest there is substan- Mauritius) and only 3 fully autocratic regimes (Eritrea, Somalia, tial scope to undercut clientelism through well designed (and eval- and Swaziland), with most countries classified as intermediate—a uated) interventions that better inform citizens and that enable remarkable shift. Most intermediate regimes now have significant them to deliberate, communicate, and hold governments more democratic elements (Burkina Faso, Côte d’Ivoire, the Democratic accountable for broad public interest policies. For example, in Republic of the Congo, Ethiopia, Mozambique, Nigeria, Rwanda, Benin, a civil society group organized town hall meetings with Uganda, Tanzania, and Zimbabwe). political candidates in the first round of the 2006 presidential elec- tions, to discuss specific policy proposals informed by empiri- Figure 1 Polity scores, 1985 and 2009 cal evidence. Where the meetings were held, voter turnout was higher and support for clientelist political platforms was lower 10 Democratic (Wantchekon 2009) than where they were not. Better data, bet- 8 6 ter evidence, and better communication with citizens could be 2009 the key to overcoming political constraints to good development 4 policies in Africa. Intermediate 2 0 –2 1985 Note –4 1. Polity IV is a database ranking countries on their levels of de- –6 Autocratic –8 mocracy, based on surveys of political scientists. –10 Sub-Saharan African countries References Glewwe, Paul, and Michael Kremer. 2006. “Schools, Teachers, and So, why has increasing democratization in the Africa region Education Outcomes in Developing Countries.� Handbook on not resulted in more substantial improvements in public policies the Economics of Education, ed. Erik Hanushek & F. Welch. for growth, poverty reduction, and human development? Although Oxford, UK: Elsevier. the democratic wave has been shown to influence public poli- Harding, Robin, and David Stasavage. 2011. “What Democracy cies, it has disappointed by not addressing critical accountabil- Does (and Doesn’t) Do for Basic Services: School Fees, ity relations in improving public goods for human development School Quality, and African Elections.� Working Paper, New and a competitive business sector. For example, the transition to York University, New York. competitive elections in African countries is associated with the Keefer, Philip, and Stuti Khemani. 2005. “Democracy, Public Ex- abolition of school fees, which in turn is associated with higher penditures, and the Poor.� World Bank Research Observer 20: rates of school attendance than in nondemocracies (Harding and 1–27. Stasavage 2011). Yet the quality of education services is poor, with Robinson, James A., and Thierry Verdier 2002. “The Political Econ- teachers on the public payroll often absent from their jobs (Glewwe omy of Clientelism.� CEPR Discussion Paper 3205, Center for and Kremer 2006) and learning among children falling far short of Economic Policy and Research, Washington, DC. functional literacy (Uwezo 2010). Uwezo. 2010. Are Our Children Learning? Annual Learning As- Political economy analysis suggests that the disappointments sessment. Nairobi, Kenya. http://uwezo.net/index.php?i=68 are due largely to widespread clientelistic practices in electoral Wantchekon, Leonard. 2009. “Can Informed Public Deliberation competition—the provision of private benefits to select citizens in Overcome Clientelism? Experimental Evidence from Benin.� exchange for political support (Robinson and Verdier 2002; Keefer Working Paper, New York University, New York. http://politics. and Khemani 2005). Providing secure jobs to teachers on the as.nyu.edu/docs/IO/2807/expertinformationjuly.pdf. speci�c manifestations of, these general the competitiveness of political participa- principles. Coded data on civil liberties are tion using weights. not included. This is an additive eleven- Institutionalized autocracy is a pejorative point scale (0–10). The operational indica- term for some very diverse kinds of politi- tor of democracy is derived from codings of cal systems whose common properties are Technical notes 179 a lack of regularized political competition directiveness over social and economic ac- and concern for political freedoms. The term tivity, but this is regarded here as a function autocracy is used and de�ned operationally of political ideology and choice, not a de�n- in terms of the presence of a distinctive set ing property of autocracy. Social democra- of political characteristics. In mature form cies also exercise relatively high degrees of autocracies sharply restrict or suppress com- directiveness. petitive political participation. Their chief executives are chosen in a regularized pro- Source: Data are from the Integrated Net- cess of selection within the political elite, work for Societal Conflict Research Pol- and once in office they exercise power with ity  IV Project, Political Regime Character- few institutional constraints. Most modern istics and Transitions, 1800–2009 (www. autocracies also exercise a high degree of systemicpeace.org/inscr/inscr.htm). 180 Africa Development Indicators 2011 Technical notes references Chen, Shaohua, and Martin Ravallion. 2008. “The Standard & Poor’s. 2000. The S&P Emerging Market Indices: WHO (World Health Organization). 2011. Global Atlas of the Developing World Is Poorer Than We Thought, But No Less Methodology, De�nitions, and Practices. New York: Health Workforce. Geneva: World Health Organization. Successful in the Fight Against Poverty.� Policy Research Standard & Poor’s. Working Paper 4703. World Bank, Washington, DC. ———. Various years. World Malaria Report. 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Geographical Distribution United Nations. of Financial Flows to Developing Economies. Paris: Organisation for Economic Co-operation and Development. ———. Various years. World Urbanization Prospects. New York: United Nations. Ravallion, Martin, Shaohua Chen, and Prem Sangraula. 2008. “Dollar a Day Revisited.� Policy Research Working United Nations Statistics Division. n.d. “International Standard Paper 4620. World Bank, Development Research Group, Industrial Classi�cation of All Economic Activities, Third Washington, DC. Revision.� [http://unstats.un.org/unsd/cr/registry/]. New York. Technical notes references 181 Map of Africa TUNISIA MOROCCO ALGERIA LIBYA ARAB REP. FORMER SPANISH OF EGYPT SAHARA CAPE VERDE MAURITANIA MALI NIGER ERITREA SENEGAL BURKINA CHAD THE GAMBIA FASO SUDAN DJIBOUTI GUINEA-BISSAU GUINEA BENIN NIGERIA CÔTE TOGO SIERRA LEONE D’IVOIRE ETHIOPIA GHANA CENTRAL AFRICAN REPUBLIC LIBERIA CAMEROON SOMALIA EQUATORIAL GUINEA UGANDA SÃO TOMÉ AND PR�NCIPE CONGO KENYA GABON DEM. REP. OF RWANDA CONGO BURUNDI TANZANIA SEYCHELLES COMOROS ANGOLA MALAWI Atlantic ZAMBIA Ocean MADAGASCAR MOZAMBIQUE ZIMBABWE MAURITIUS NAMIBIA BOTSWANA SWAZILAND SOUTH LESOTHO Indian AFRICA Ocean 182 Africa Development Indicators 2011 Users Guide Africa Development Indicators 2011–Multiple User CD-ROM Introduction all the troubleshooting steps you need to for de�ning reusable controls that perform This CD-ROM is part of the Africa resolve the issue. particular functions in Microsoft Windows. Development Indicators suite of products. If you receive this security alert, please click It was produced jointly by the Of�ce of the My Internet Explorer flickers when I try to Yes as the links are not a virus or security risk Chief Economist and the Operational Quality launch the application on my desktop to your computer. and Knowledge Services Departments of You may experience this problem if you are For detailed instructions, refer to the the Africa Region in collaboration with the using Microsoft Vista. This occurs because on-screen Help menu or tool tips (on-screen Development Data Group of the Development Internet Explorer 7 and higher versions block explanations of buttons that are displayed Economics Vice Presidency. It uses the latest the application when there is an IP address when the cursor rolls over them). version of the World Bank’s Data Platform in the URL for security reasons. ADI 2011 version 3.0. is a secure application. Please follow these Features and instructions The CD-ROM contains about 1,700 directions to resolve this issue: ADI 2011 has two main screens—a text macroeconomic, sectoral, and social 1. Go to Tools > Internet Options > Security window featuring the contents of the Africa indicators, covering 53 African countries. Tab Development Indicators 2011 book and Time series include data from 1961 to 2009. 2. Select Local Intranet other related tables, and a separate window Doing business and enterprise survey data 3. Check the Enabled Protected Mode featuring the ADI 2011 time series database. have data for 2010. It also contains the checkbox. full contents of the print version of Africa Home Development Indicators 2011 and The Little I am getting an Internet Explorer security On the opening text screen you can access Data Book on Africa. warning message. Is this a security risk? each element of the ADI 2011 CD-ROM. The new Data Platform version 3.0 has This is not a security risk. ADI 2011 is a Use the browser controls to link to the Africa sophisticated features: enhanced mapping secure application. You can continue working Development Indicators 2011 book, time series and charting, a choice of data selection if this message appears. To permanently database, and other related information. techniques and versatile display options. We disable this message, please follow these invite you to explore it. directions: Database 1. Go to Tools > Internet Options > Security Select variables A note about the data Tab 1. Click on each of the Country, Series, and Users should note that the data for the Africa 2. Select Local Intranet Year tabs and make your selections on Development Indicators suite of products are 3. Check the Enabled Protected Mode each screen. There are many ways to drawn from the same database. The cutoff checkbox. make a selection—see below, or use date for data is May 2011. the Help menu. A Search option is also I am getting the following message: “MSXML available. Help 5.0 from Microsoft Corporation. If you trust 2. Highlight the items you want. This guide explains how to use the main this website and the add-on and want to allow 3. Click on the Select button to move them functions of the CD-ROM. For details about it to run, click here.� into the Selected box. additional features, click Help on the menu This message occurs the �rst time a web 4. Deselect items at any time by highlighting bar or the Help icon; or call one of the hotline page attempts to execute a higher version of them and clicking on the Remove icon. numbers listed in the Help menu and on the a plug-in in Internet Explorer. This is to alert 5. When selection is complete, click on Next copyright page of this booklet. the user the plug-in has been updated with to move to the next screen. a newer version and prompts this message Installation for user approval. Please right click on the Making selections As is usual for Windows® products, you message and run the plug-in. To permanently • Country: You can select countries and should make sure that other applications are disable this message, please follow these group aggregates from an alphabetical closed while you install the CD-ROM. directions: list, group hierarchies, or by Classi�cation To install: 1. Go to Tools > Internet Options > Security (region, income group, or lending 1. Insert the CD-ROM into your CD drive. Tab category). Aggregate data have been The installation window should open 2. Select Local Intranet calculated only when there were adequate automatically. 3. Check the Enabled Protected Mode country data. 2. If the installation window does not open, checkbox. • Series: You can choose from an click on Start, select Run. Type D:\RUN.BAT This change requires Internet Explorer alphabetical list or by topic, or create and follow the instructions. to restart. Please close the existing browser your own custom indicators derived from 3. DataPlatform requires Microsoft® window and re-launch the application by indicators within the ADI database. Internet Explorer 6.0 or higher. If you clicking on the ADI 2011 shortcut desktop icon. • Year: Select time periods from the list box. do not have Internet Explorer, it may be NOTE: When ADI 2011 launches after On all screens you can click Notes to view downloaded at no charge from www. installation, the MS-DOS window remains on de�nition and source information for a microsoft.com. It does not need to be your top of the browser. You should NOT close the highlighted item. default browser. window, but you can minimize the MS-DOS You can delete this program at any time by window. View results clicking on the Remove ADI 2011 icon in the On the Report tab, data are presented in WB Development Data program folder. Operation a two-dimensional grid. Data for the third To start the CD-ROM, click on the ADI 2011 dimension are presented on separate Issues during installation CD-ROM icon on your desktop. An ActiveX screens. You can change the selection This section covers some of the issues that security pop-up warning may appear when displayed by clicking on the third dimension may occur during installation. It also provides clicking on a link. ActiveX is a framework list box. You can also change the scale (to Users guide 183 millions, for example) and the number of Flash Player. Please click “OK� when the originally or subsequently recorded. The not meeting the Bank’s limited warranty. digits after the decimal. Click on a column message appears. It will take you directly to Bank, however, retains title and ownership Defective CD-ROMs should be returned header to sort the results. 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You may make one copy of BUT NOT LIMITED TO, THE IMPLIED select the variables again. On the Map tab, selected countries are the program solely for backup purposes. WARRANTIES OF MERCHANTABILITY AND colored according to their data values for Unauthorized copying of the program FITNESS FOR A PARTICULAR PURPOSE. Changing the orientation. You can view the the selected indicator and year. The country or of the written materials is expressly THE BANK DOES NOT WARRANT THAT THE result in six different orientations (countries name and data value will appear as the forbidden and punishable by law. FUNCTIONS CONTAINED IN THE PROGRAM down/periods across, series down/countries cursor rolls over the map. The legend scale WILL MEET YOUR REQUIREMENTS OR THAT across, and so on). To change the orientation, is based on the report scale and precision 4. USE. You may not modify, adapt, THE OPERATION OF THE PROGRAM WILL click on Customize and drag and drop the settings. 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As a licensee you own the liability and your exclusive remedy shall Washington DC 20433, fax 202 522 will appear asking you to download Adobe physical media on which the program is be the replacement of any CD-ROMs 2422, e-mail pubrights@worldbank.org. 184 Africa Development Indicators 2011 2 0 1 1 Africa Development Indicators 2011 is the most detailed collection of data on Africa. It contains macroeconomic, sectoral, and social indicators for 53 countries. e companion CD-ROM has additional data, with some 1,700 indicators covering 1961–2009. • Basic indicators • National and �scal accounts • External accounts and exchange rates • Millennium Development Goals • Private sector development • Trade and regional integration • Infrastructure • Human development • Agriculture, rural development, and the environment • Labor, migration, and population • HIV/AIDS and malaria • Capable states and partnership • Paris Declaration indicators • Governance and polity Designed as both a quick reference and a reliable dataset for monitoring development programs and aid flows in the region, Africa Development Indicators 2011 is an invaluable tool for analysts and policymakers who want a better understanding of Africa’s economic and social development. ISBN 978-0-8213-8731-3 SKU 18731