Africa Development Indicators 2012/2013 by World Bank Publications

2012/13

© 2013 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org Some rights reserved 1 2 3 4 16 15 14 13 This work is a product of the staff of The World Bank with external contributions. Note that The World Bank does not necessarily own each component of the content included in the work. The World Bank therefore does not warrant that the use of the content contained in the work will not infringe on the rights of third parties. The risk of claims resulting from such infringement rests solely with you. The findings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance of such boundaries. Nothing herein shall constitute or be considered to be a limitation upon or waiver of the privileges and immunities of The World Bank, all of which are specifically reserved. Rights and Permissions

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Contents Foreword

vii

Acknowledgments

Indicator tables

Users guide

Part I. Basic indicators and national and fiscal accounts 1. Basic indicators 1.1 Basic indicators 2. National and fiscal accounts 2.1 Gross domestic product, nominal 2.2 Gross domestic product, nominal 2.3 Gross domestic product, nominal 2.4 Gross domestic product per capita, real 2.5 Gross domestic product per capita growth 2.6 Gross national income, nominal 2.7 Gross national income, World Bank Atlas method 2.8 Gross national income per capita, World Bank Atlas method 2.9 Gross domestic product deflator (U.S. dollar series) 2.10 Consumer price Index 2.11 Consumer price index, growth 2.12 Price indices 2.13 Gross domestic savings 2.14 Gross national savings 2.15 General government final consumption expenditure 2.16 Household final consumption expenditure 2.17 Final consumption expenditure plus discrepancy 2.18 Final consumption expenditure plus discrepancy per capita 2.19 Gross fixed capital formation 2.20 Gross general government fixed capital formation 2.21 Private sector fixed capital formation 2.22 External trade balance (exports minus imports) 2.23 Exports of goods and services, nominal 2.24 Imports of goods and services, nominal 2.25 Exports of goods and services as a share of GDP 2.26 Imports of goods and services as a share of GDP 2.27 Balance of payments and current account 2.28 Exchange rates and purchasing power parity 2.29 Agriculture value added 2.30 Industry value added

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 36 38 39 Contents

iii

2.31 Services plus discrepancy value added 2.32 Central government ﬁnances 2.33 Central government expenses 2.34 Central government revenues 2.35 Structure of demand

40 41 43 45 47

Part II. Millennium Development Goals 3. Millennium Development Goals 3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger 3.2 Millennium Development Goal 2: achieve universal primary education 3.3 Millennium Development Goal 3: promote gender equity and empower women 3.4 Millennium Development Goal 4: reduce child mortality 3.5 Millennium Development Goal 5: improve maternal health 3.6 Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases 3.7 Millennium Development Goal 7: ensure environmental sustainability 3.8 Millennium Development Goal 8: develop a global partnership for development

48 51 52 53 54 55 57 59

Part III. Development outcomes

Drivers of growth 4. Private sector development 4.1 Doing Business 4.2 Investment climate 4.3 Financial sector infrastructure

61 64 66

5. Trade and regional integration 5.1 International trade and tariﬀ barriers 5.2 Top three exports and share in total exports, 2010 5.3 Regional integration, trade blocs

68 72 74

6. Infrastructure 6.1 Water and sanitation 6.2 Transportation 6.3 Information and communication technology 6.4 Energy

74 75 77 80

Participating in growth 7. Human development 7.1 Education 7.2 Health

84 86

8. Agriculture, rural development, and environment 8.1 Rural development 8.2 Agriculture 8.3 Producer food prices 8.4 Environment 8.5 Fossil fuel emissions

90 92 94 96 98

Africa Development Indicators 2012/13

9. Labor, migration, and population 9.1 Labor force participation 9.2 Labor force composition 9.3 Unemployment 9.4 Migration and population

100 106 108 110

10. HIV/AIDS 10.1 HIV/AIDS

112

11. Malaria 11.1 Malaria

116

12. Capable states and partnership 12.1 Aid and debt relief 12.2 Status of Paris Declaration indicators 12.3 Capable states 12.4 Governance and anticorruption indicators 12.5 Country Policy and Institutional Assessment ratings 12.6 Polity indicators

117 120 122 124 126 130

Technical notes

131

Technical notes references

190

Primary data documentation

192

Map of Africa

198

Contents

Foreword For over a decade, Sub-Saharan Africa has been experiencing relatively rapid economic growth, averaging about 5 percent a year. Emblematic of this growth is the information and communications technology (ICT) revolution in Africa, with over 80 percent of urban Africans with access to cellphones. Thanks to economic growth, poverty has been declining, with the absolute number of people living on less than $1.25 a day falling (by about 9 million) for the ﬁrst time in history. At the same time, Africa has the lowest human development indicators, with one in 16 children dying before their ﬁfth birthday. Striking as they are, these averages mask the great diversity of the African continent. This year’s Africa Development Indicators, with data on 1,700 indicators stretching back to 1960, provides a detailed picture of the variety of the continent’s development experience, across space and over time. For instance: • While Africa’s gross national income per capita was US$1,589 in 2010, it ranged from US$180 to US$13,720. • Of the 89 million recorded internet users in SSA, half of them were in Nigeria. Two countries (Kenya and Nigeria) account for 62 percent of Internet users. However, Seychelles has the highest number of Internet users per 100 people. • Although poverty is declining, Africa has the highest poverty rate in the world, with 47.5 percent of the population living on $1.25 a day. They account for 30 percent of the world’s poor.

•

Thirty-nine countries had child mortality reductions of over 12 percent over the last 20 years with the largest decline of over 50 percent in Malawi, Madagascar, Eritrea and Liberia. A central question is why Africa is doing so much better today than it was, say, 20 years ago. The answer includes several factors, such as debt relief, increased aid, high commodity prices—and improved macroeconomic policies. These policies are the result of decisions by African policy makers who, in turn, are increasingly accountable to their citizens. And an informed citizenry is better able to hold its leaders to account. On its part, the World Bank continues to make all its data freely available, resulting in continually growing use of its online resources. This volume is part of the Africa Development Indicators suite of products, which also includes The Little Data Book on Africa 2012/13 and The Little Data Book on Gender in Africa 2012/13, the Africa Development Indicators 2012/13 CD-ROM, and a data query and charting application for mobile services. All of these publications help to equip the public with information, so they can contribute to an evidence-based debate that will eventually lead to better public policies. In short, Africa Development Indicators not only documents Africa’s transformation; it supports it. Makhtar Diop Vice President The World Bank Group Africa Region

Foreword

vii

Acknowledgments Africa Development Indicators is a product of the Africa Region of the World Bank. This report has been prepared by a core team led by Rose Mungai comprising Francoise Genouille and Ayago Esmubancha Wambile in the production of this book and its companions—Africa Development Indicators Online 2012/13, and The Little Data Book on Africa 2012/13 and The Little Data Book on Gender in Africa 2012/13. Yohannes Kebede coordinated the ADI Online Apps platform while Mapi Buitano coordinated the dissemination of the book and its companions. Aby Toure managed the communication aspect. Francoise Genouille coordinated all stages of production. The overall work was carried out under the guidance of Shantayanan Devarajan, Chief Economist of the Africa Region. The technical box contributors were: • Andrew Dabalen and Rose Mungai (Africa New Dollar Per Day [PPP] Poverty Estimates [$1.25/day] in 2008 ) • DIME (What’s the Coolest Region for doing Impact Evaluation? It’s Africa) • Jos Verbeek and Jose Alejandro Quijada (Africa and the MDGs: 2015 and Beyond) • Markus Goldstein (Gender) • Rabia Ali and Jishnu Das (Gender Diﬀerences in Risks of Death: Africa’s Excess Female Mortality and Trends Over Time) • Sumila Gulyani, Ellen Bassett and Debabrata Talukdar (A Multidimensional Portrait of Poverty and Living Conditions in Slums)

•

Punam Chuhan-Pole and Vijdan Korman (CPIA results for Africa) Azita Amjadi, Abdolreza Farivari, Shelley Lai Fu, Ugendran Machakkalai, Shanmugam Natarajan, and Malarvizhi Veerappan collaborated in the online data production. Mahyar Eshragh-Tabary, Masako Hiraga, Maurice Nsabimana, and Soong Sup Lee collaborated in the update of the live database. Software preparation and testing for mobile applications was managed by Shelley Lai Fu, with the assistance of Ramgopal Erabelly and Parastoo Oloumi. Federico Escaler and William Prince collaborated in the production of The Little Data Book on Africa 2012/13 and The Little Data Book on Gender in Africa 2012/13. Jeffrey Lecksell and Bruno Bonansea of the World Bank’s Map Design Unit coordinated preparation of the maps. Kenneth Omondi provided administrative and logistical support. The core would like to thank the many people who provided useful comments on the publication. Their feedback and suggestions helped improve this year’s edition. Staff from External Affairs oversaw printing and dissemination of the book and its companions. Several institutions provided data to Africa Development Indicators. Their contribution is very much appreciated. EEI provided design direction, editing, and layout, led by Sheila Gagen; Cindy Peters typeset the book.

Acknowledgments

Indicator tables Part I. Basic indicators and national and fiscal accounts 1. Basic indicators 1.1 Basic indicators 2. National and fiscal accounts 2.1 Gross domestic product, nominal 2.2 Gross domestic product, nominal 2.3 Gross domestic product, nominal 2.4 Gross domestic product per capita, real 2.5 Gross domestic product per capita growth 2.6 Gross national income, nominal 2.7 Gross national income, World Bank Atlas method 2.8 Gross national income per capita, World Bank Atlas method 2.9 Gross domestic product deflator (U.S. dollar series) 2.10 Consumer price Index 2.11 Consumer price index, growth 2.12 Price indices 2.13 Gross domestic savings 2.14 Gross national savings 2.15 General government final consumption expenditure 2.16 Household final consumption expenditure 2.17 Final consumption expenditure plus discrepancy 2.18 Final consumption expenditure plus discrepancy per capita 2.19 Gross fixed capital formation 2.20 Gross general government fixed capital formation 2.21 Private sector fixed capital formation 2.22 External trade balance (exports minus imports) 2.23 Exports of goods and services, nominal 2.24 Imports of goods and services, nominal 2.25 Exports of goods and services as a share of GDP 2.26 Imports of goods and services as a share of GDP 2.27 Balance of payments and current account 2.28 Exchange rates and purchasing power parity 2.29 Agriculture value added 2.30 Industry value added 2.31 Services plus discrepancy value added 2.32 Central government finances 2.33 Central government expenses 2.34 Central government revenues 2.35 Structure of demand

8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 36 38 39 40 41 43 45 47

48 51 52 Indicator tables

3.4 Millennium Development Goal 4: reduce child mortality 3.5 Millennium Development Goal 5: improve maternal health 3.6 Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases 3.7 Millennium Development Goal 7: ensure environmental sustainability 3.8 Millennium Development Goal 8: develop a global partnership for development

53 54 55 57 59

Part III. Development outcomes

Africa Development Indicators 2012/13

Drivers of growth 4. Private sector development 4.1 Doing Business 4.2 Investment climate 4.3 Financial sector infrastructure

61 64 66

5. Trade and regional integration 5.1 International trade and tariﬀ barriers 5.2 Top three exports and share in total exports, 2010 5.3 Regional integration, trade blocs

68 72 74

6. Infrastructure 6.1 Water and sanitation 6.2 Transportation 6.3 Information and communication technology 6.4 Energy

74 75 77 80

Participating in growth 7. Human development 7.1 Education 7.2 Health

84 86

8. Agriculture, rural development, and environment 8.1 Rural development 8.2 Agriculture 8.3 Producer food prices 8.4 Environment 8.5 Fossil fuel emissions

90 92 94 96 98

9. Labor, migration, and population 9.1 Labor force participation 9.2 Labor force composition 9.3 Unemployment 9.4 Migration and population

100 106 108 110

10. HIV/AIDS 10.1 HIV/AIDS

112

11. Malaria 11.1 Malaria

116

117 120 122 124 126 130

Users guide Tables The tables are numbered by section. Countries are listed alphabetically by subregion (Sub-Saharan Africa and North Africa). Indicators are shown for the most recent year or period for which data are available and, in most tables, for an earlier year or period (usually 1980, 1990, 1995, 2000 or 2005 in this edition). Time-series data are available on the Africa Development Indicators—CD-ROM and the World Bank’s Open Data website (http:// data.worldbank.org). The term country, used interchangeably with economy, does not imply political independence but refers to any territory for which authorities report separate social or economic statistics. Known deviations from standard definitions or breaks in comparability over time or across countries are noted in the tables. When available data are deemed too weak to provide reliable measures of levels and trends or do not adequately adhere to international standards, the data are not shown. Aggregate measure for region and sub-classifications The aggregates are based on the World Bank’s analytical regional classification for SubSaharan Africa and North Africa, which may differ from common geographic usage. Former Spanish Sahara and Mayotte are not included in any aggregates. Statistics Data are shown for economies as they were constituted in 2010, and historical data are revised to reflect current political arrangements. Exceptions are noted in the tables. Additional information about the data is provided in Primary data documentation, which summarizes national and international efforts to improve basic data collection and gives country-level information on primary

sources, census years, and other background information. Data consistency, reliability, and comparability Considerable effort has been made to harmonize the data, but full comparability cannot be assured, and care must be taken in interpreting indicators. Many factors affect data availability, comparability, and reliability. Statistical systems in many developing economies are still weak; statistical methods, coverage practices and definitions differ widely and cross-country and intertemporal comparisons involve complex technical and conceptual problems that cannot be resolved unequivocally. Data coverage may be incomplete because of circumstances affecting the collection and reporting of data, such as conflicts. Although drawn from sources thought to be the most authoritative, data should be construed as indicating trends and characterizing differences across economies. Discrepancies in data presented in earlier editions of Africa Development Indicators reflect updates from countries as well as revisions to historical series and changes in methodology. Readers are therefore advised not to compare data series between editions or across World Bank publications. Country notes South Sudan declared its independence on July 9, 2011. Data for Sudan include South Sudan unless otherwise noted. Classification of economies For operational and analytical purposes the World Bank’s main criterion for classifying economies is gross national income (GNI) per capita (calculated by the World Bank Atlas method; box 1). Every economy is classified as low income, middle income (subdivided Userstables guide Indicator

Box 1

The World Bank Atlas method for converting gross national income to a common denominator

In calculating GNI and GNI per capita in U.S. dollars for certain operational purposes, the World Bank uses the Atlas conversion factor. The purpose of the Atlas conversion factor is to reduce the impact of exchange rate fluctuations in the crosscountry comparison of national incomes. The Atlas conversion factor for any year is the average of the official exchange rate or alternative conversion factor for that year and for the two preceding years, adjusted for difference between the rate of inflation in the country and that in Japan, the United Kingdom, the United States, and the euro area. A country’s inflation rate is measured by the change in its GDP deflator. The inflation rate for Japan, the United Kingdom, the United States, and the euro area, representing international inflation, is measured by the change in the “SDR deflator.” The SDR (Special drawing rights or SDRs are the International Monetary Fund’s unit of

account) is calculated as a weighted average of these countries GDP deflators in SDR terms, the weights being the amount of each country’s currency in one SDR unit. Weights vary over time because both the composition of the SDR and the relative exchange rates for each currency change. The SDR deflator is calculated in SDR terms first and then converted to U.S. dollars using the SDR to dollar Atlas conversion factor. The Atlas conversion factor is then applied to a country’s GNI. The resulting GNI in U.S. dollars is divided by the midyear population for the latest of the three years to derive GNI per capita. When official exchange rates are deemed to be unreliable or unrepresentative of the effective exchange rate during a period, an alternative estimate of the exchange rate is used in the Atlas formula below. The following formulas describe the procedures for computing the conversion factor for year t:

into lower middle and upper middle), or high income (table 1). Low- and middle income economies are sometimes referred to as developing economies. The term is used for convenience; it is not intended to imply that all economies in the group are experiencing similar development or that other economies have reached a preferred or final stage of development. Classification by income does not necessarily reflect development status. Because GNI per capita changes over time, the country composition of income groups may change from one edition of Africa Development Indicators to the next. Once the classification is fixed for an edition, based on GNI per capita in the most recent year for which data are available (2010 in this edition), all historical data presented are based on the same country grouping. Low-income economies are those with a GNI per capita of $1,005 or less in 2010. Middle-income economies are those with a GNI per capita of more than $1,005 but less than $12,275. Lower middle-income and upper middle-income economies are separated at a GNI per capita of $3,976. High-income

Africa Development Indicators 2012/13

and for calculating per capita GNI in U.S. dollars for year t:

where et* is the Atlas conversion factor (national currency to the U.S. dollar) for year t, et is the average annual exchange rate (national currency to the U.S. dollar) for year t, pt is the GDP deflator for year t, ptS$ is the SDR deflator in U.S. dollar terms for year t, Yt$ is current GNI per capita in U.S. dollars in year t, Yt is current GNI (local currency) for year t, and Nt is midyear population for year t.

economies are those with a GNI per capita of $12,276 or more. Alternative conversion factors The World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. An alternative conversion factor is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate effectively applied to domestic transactions of foreign currencies and traded products. See Primary data documentation for list of countries using alternative conversion factors. Alternative conversion factors are used in the Atlas methodology and elsewhere in Africa Development Indicators as single-year conversion factors. Symbols .. means that data are not available or that aggregates cannot be calculated because of missing data in the years shown. $ means current U.S. dollars unless otherwise noted. < means less than

Table 1

World Bank classification of economies, 2010 (GNI per capita) Middle income Low income

Lower middle income

Upper middle income

High income

GNI per capita of $1,005 or less

GNI per capita higher than $1,006 and less than $3,975

GNI per capita of $3,976 but less than $12,275

GNI per capita of $12,276 and over

Benin Burkina Faso Burundi Central Africa Republic Chad Comoros Congo, Dem. Rep. Eritrea Ethiopia Gambia, The Guinea Guinea-Bissau Kenya Liberia Madagascar Malawi Mali Mozambique Niger Rwanda Sierra Leone Somalia Tanzania Togo Uganda Zimbabwe

Angola Cameroon Cape Verde Congo, Rep. Côte d’Ivoire Djibouti Egypt, Arab Rep. Ghana Lesotho Mauritania Morocco Nigeria São Tomé and Príncipe Senegal South Sudan Sudan Swaziland Zambia

Algeria Botswana Gabon Libya Mauritius Namibia Seychelles South Africa Tunisia

Equatorial Guinea

Source: World Bank.

> means more than 0 or 0.0 means zero or small enough that the number would round to zero at the displayed number of decimal places. / in dates, as in 2010/11, means that the period of time, usually covers 12 months, but straddles two calendar years and refers to a crop year, a survey year or a ﬁscal year. in dates, as in 2010-11, means that the period of time, refers to 2010 and/or 2011

Data presentation conventions • A blank means not applicable or, for an aggregate, not analytically meaningful. • A billion is 1,000 million. • A trillion is 1,000 billion. • Growth rates are in real terms, unless otherwise speciﬁed. The cutoﬀ date for data for this publication is August 2012. However, it must be noted that the database may have more recent data by the time of this publication.

Userstables guide Indicator

Participating in growth

Table

1.1

Basic indicators GDP per capita Adult Net official GNI literacy rate development Under-five Life Population per capita, Constant 2000 prices (% ages 15 Average expectancy mortality assistance World Bank Land area density and older) annual Total Growth (thousands (people Atlas method per capita rate Gini at birth growth (%) (years) (per 1,000) index Male Female (current $) (millions) (annual %) of sq km) per sq km) (current $) $ a b 2010 2010 2010 2010 2010 2010 2000–10 2010 2010 2000–10 2009 2009 2010 Population

SUB-SAHARAN AFRICA 844.0 Excluding South Africa 794.0 Excl. S. Africa & Nigeria 635.6 Angola 19.1 Benin 8.8 Botswana 2.0 Burkina Faso 16.5 Burundi 8.4 Cameroon 19.6 Cape Verde 0.5 Central African Republic 4.4 Chad 11.2 Comoros 0.7 Congo, Dem. Rep. 66.0 Congo, Rep. 4.0 Côte d’Ivoire 19.7 Equatorial Guinea 0.7 Eritrea 5.3 Ethiopia 82.9 Gabon 1.5 Gambia, The 1.7 Ghana 24.4 Guinea 10.0 Guinea-Bissau 1.5 Kenya 40.5 Lesotho 2.2 Liberia 4.0 Madagascar 20.7 Malawi 14.9 Mali 15.4 Mauritania 3.5 Mauritius 1.3 Mozambique 23.4 Namibia 2.3 Niger 15.5 Nigeria 158.4 Rwanda 10.6 São Tomé and Príncipe 0.2 Senegal 12.4 Seychelles 0.1 Sierra Leone 5.9 Somalia 9.3 South Africa 50.0 Sudan 33.6 Swaziland 1.1 Tanzania 44.8 Togo 6.0 Uganda 33.4 Zambia 12.9 Zimbabwe 12.6 NORTH AFRICA 166.3 Algeria 35.5 Djibouti 0.9 Egypt, Arab Rep. 81.1 Libya 6.4 Morocco 32.0 Tunisia 10.5 AFRICA 1,010.3

2.5 2.5 2.5 2.8 2.8 1.3 3.0 2.6 2.2 0.9 1.9 2.6 2.6 2.7 2.5 2.0 2.8 3.0 2.2 1.9 2.7 2.4 2.2 2.1 2.6 1.0 4.0 2.9 3.1 3.0 2.4 0.5 2.3 1.8 3.5 2.5 3.0 1.8 2.7 (0.9) 2.2 2.3 1.4 1.9 1.1 3.0 2.1 3.2 1.6 0.8 1.5 1.5 1.9 1.8 1.5 1.0 1.0 2.3

23,616 22,401 21,491 1,247 111 567 274 26 473 4 623 1,259 2 2,267 342 318 28 101 1,000 258 10 228 246 28 569 30 96 582 94 1,220 1,031 2 786 823 1,267 911 25 1 193 0 72 627 1,214 2,376 17 886 54 200 743 387 5,762 2,382 23 995 1,760 446 155 29,378

35.7 35.4 29.6 15.3 80.0 3.5 60.2 326.4 41.5 123.1 7.1 8.9 395.0 29.1 11.8 62.1 25.0 52.0 83.0 5.8 172.8 107.2 40.6 53.9 71.2 71.5 41.5 35.6 158.1 12.6 3.4 631.0 29.7 2.8 12.3 173.9 430.6 172.3 64.6 188.1 81.9 14.9 41.2 18.3 61.4 50.6 110.8 167.3 17.4 32.5 28.9 14.9 38.3 81.5 3.6 71.6 67.9 34.4

1,202 895 824 3,960 780 6,750 550 230 1,200 3,280 470 710 750 180 2,240 1,170 13,720 340 390 7,680 610 1,250 390 580 810 1,100 210 430 330 600 1,000 7,780 440 4,250 360 1,170 520 1,250 1,080 10,460 340 .. 6,090 1,300 2,930 530 550 500 1,070 480 3,533 4,390 .. 2,420 .. 2,850 4,140 1,586

653 458 437 1,369 377 4,190 283 138 714 1,959 240 300 336 106 1,253 588 8,537 147 221 4,214 704 360 550 161 469 496 261 243 185 273 609 5,181 384 2,696 179 540 337 .. 562 8,788 268 .. 3,753 524 1,811 459 265 380 432 321 2,313 2,232 .. 1,976 .. 1,844 3,144 926

2.6 3.2 3.0 9.4 0.8 2.7 2.9 0.5 1.0 5.0 -0.7 6.1 -0.8 2.5 1.7 -0.6 12.4 -2.9 6.3 0.2 1.4 3.4 5.2 -0.5 1.7 2.7 1.7 0.3 2.3 2.0 3.1 3.1 4.9 3.1 0.6 4.1 4.8 .. 1.5 1.8 5.0 .. 2.7 4.1 2.1 4.2 0.1 4.3 3.1 -6.2 3.2 2.3 2.0 3.2 3.3 3.7 3.7 2.6

54.2 54.3 55.0 50.7 55.6 53.1 54.9 49.9 51.1 73.8 47.6 49.2 60.6 48.1 57.0 54.7 50.8 61.0 58.7 62.3 58.2 63.8 53.6 47.7 56.5 47.4 56.2 66.5 53.5 51.0 58.2 73.0 49.7 62.1 54.3 51.4 55.1 64.4 59.0 73.0 47.4 50.9 52.1 61.1 48.3 57.4 56.6 53.6 48.5 49.9 72.8 72.9 57.5 73.0 74.8 71.9 74.6 57.2

122 125 120 161 115 48 176 142 136 36 159 173 86 170 93 123 121 61 106 74 98 74 130 150 85 85 103 62 92 178 111 15 135 40 143 143 91 80 75 14 174 180 57 103 78 92 103 99 111 80 27 36 91 22 17 36 16 113

.. .. 58.6 38.6 .. 39.8 33.3 38.9 50.5 56.3 39.8 64.3 44.4 47.3 41.5 .. .. 29.8 41.5 47.3 42.8 39.4 35.5 47.7 52.5 38.2 44.1 39.0 33.0 40.5 .. 45.7 63.9 34.6 48.8 53.1 50.8 39.2 65.8 42.5 .. 63.1 35.3 51.5 37.6 34.4 44.3 54.6 .. .. 40.0 30.8 .. 40.9 41.4 ..

.. 74.5 .. 82.9 54.2 83.8 .. 72.6 .. 90.1 69.1 44.5 79.7 79.5 .. 64.7 97.0 77.9 .. 91.4 57.6 72.8 50.8 66.9 90.5 82.9 63.7 .. 80.6 .. 64.5 90.6 70.1 88.9 .. 72.0 75.0 93.7 61.8 .. 52.7 .. .. .. 87.8 79.0 .. .. 80.6 94.7 .. .. .. .. 95.2 68.9 .. ..

.. 56.1 .. 57.6 29.1 84.4 .. 60.9 .. 80.3 42.1 23.1 68.7 54.9 .. 45.3 89.8 56.0 .. 84.1 35.8 60.4 28.1 38.0 83.5 95.3 54.5 .. 67.0 .. 50.3 85.3 41.5 88.1 .. 49.8 66.8 84.1 38.7 .. 30.1 .. .. .. 86.2 66.9 .. .. 61.3 89.4 .. .. .. .. 82.0 43.9 .. ..

52.8 54.7 65.1 12.5 77.9 77.8 64.5 75.2 27.6 661.1 59.3 43.3 91.5 53.7 324.6 42.8 121.0 30.6 42.5 69.1 69.5 69.4 21.8 92.0 40.2 118.0 355.3 22.7 68.6 70.8 108.2 97.8 83.4 112.3 48.0 13.0 97.2 298.1 74.6 647.7 79.6 53.3 20.6 61.8 86.6 66.0 69.5 51.6 70.7 58.3 16.4 5.6 148.8 7.3 1.3 31.1 52.2 47.3

a. Provisional. b. Data are for the most recent year available during the period speciﬁed.

BASIC INDICATORS

Part I. Basic indicators and national and fiscal accounts

Table

2.1

Gross domestic product, nominal

1980

SUB-SAHARAN AFRICA 271,551 Excluding South Africa 192,649 Excl. S. Africa & Nigeria 124,292 Angola .. Benin 1,405 Botswana 1,061 Burkina Faso 1,929 Burundi 920 Cameroon 6,741 Cape Verde 142 Central African Republic 797 Chad 1,033 Comoros 124 Congo, Dem. Rep. 14,395 Congo, Rep. 1,706 Côte d'Ivoire 10,175 Equatorial Guinea .. Eritrea .. Ethiopia .. Gabon 4,279 Gambia, The 241 Ghana 4,445 Guinea .. Guinea-Bissau 111 Kenya 7,265 Lesotho 431 Liberia 855 Madagascar 4,042 Malawi 1,238 Mali 1,787 Mauritania 709 Mauritius 1,137 Mozambique 3,526 Namibia 2,169 Niger 2,509 Nigeria 64,202 Rwanda 1,163 São Tomé and Príncipe .. Senegal 3,503 Seychelles 147 Sierra Leone 1,101 Somalia 604 South Africa 80,710 Sudan 7,617 Swaziland 543 Tanzania .. Togo 1,136 Uganda 1,245 Zambia 3,884 Zimbabwe 6,679 NORTH AFRICA 111,794 Algeria 42,345 Djibouti .. Egypt, Arab Rep. 22,912 Libya .. Morocco 18,821 Tunisia 8,743 AFRICA 386,370

1990

2004

300,415 188,529 160,121 10,260 1,845 3,792 3,101 1,132 11,152 307 1,488 1,739 250 9,350 2,799 10,796 132 .. 12,083 5,952 317 5,886 2,667 244 8,591 541 384 3,081 1,881 2,421 1,020 2,653 2,463 2,350 2,481 28,472 2,584 .. 5,717 369 650 917 112,014 12,409 1,115 4,259 1,628 4,304 3,288 8,784 172,644 62,045 452 43,130 28,905 25,821 12,291 472,965

558,699 339,519 251,329 19,775 4,047 10,049 5,109 899 15,775 924 1,270 4,415 362 6,512 4,649 15,481 5,241 1,109 10,054 7,178 579 8,872 3,666 523 16,096 1,234 467 4,364 2,625 4,874 1,833 6,386 5,698 6,606 3,053 87,845 2,089 107 8,030 700 1,096 .. 219,093 21,685 2,421 12,826 1,937 7,940 5,439 5,806 286,041 85,014 666 78,845 33,385 56,948 31,183 843,939

2005

Current prices ($ millions) 2006 2007

2008

2009

Annual average growth (%) 1980–89 1990–99 2000–10

2010a

651,778 760,711 881,782 1,009,242 953,418 1,117,459 404,659 499,793 595,804 735,892 670,761 754,176 291,954 352,311 429,206 527,924 501,543 556,563 28,234 41,789 60,449 84,178 75,492 82,471 4,287 4,735 5,546 6,683 6,585 6,558 10,255 11,256 12,379 13,443 11,537 14,905 5,463 5,845 6,756 8,351 8,348 8,825 1,117 1,237 1,319 1,621 1,815 2,027 16,588 17,957 20,684 23,736 22,182 22,480 972 1,108 1,331 1,562 1,601 1,659 1,350 1,477 1,696 1,983 1,980 1,985 5,302 6,099 7,016 8,357 7,085 8,541 387 403 465 530 535 541 7,191 8,824 10,014 11,675 11,204 13,110 6,087 7,731 8,395 11,859 9,594 12,008 16,363 17,367 19,796 23,414 23,042 22,921 8,217 9,603 12,575 18,424 12,233 14,500 1,098 1,211 1,318 1,380 1,857 2,117 12,307 15,164 19,553 26,642 31,963 29,684 8,666 9,546 11,571 14,530 10,946 13,200 636 667 833 1,037 983 1,050 10,720 20,388 24,632 28,527 25,979 32,175 2,937 2,821 4,209 3,778 4,165 4,736 573 579 691 847 835 835 18,738 22,504 27,237 30,519 30,580 32,198 1,368 1,429 1,597 1,626 1,711 2,179 542 604 739 851 879 988 5,039 5,515 7,343 9,395 8,488 8,721 2,755 3,117 3,458 4,074 4,728 5,054 5,305 5,866 7,146 8,738 8,965 9,422 2,184 3,041 3,357 3,585 3,027 3,614 6,284 6,507 7,792 9,641 8,825 9,714 6,579 7,096 8,030 9,891 9,674 9,209 7,262 7,981 8,806 8,840 8,931 11,133 3,405 3,645 4,291 5,370 5,254 5,411 112,249 146,867 165,921 207,118 168,568 196,838 2,581 3,111 3,738 4,712 5,253 5,624 114 124 144 183 196 201 8,714 9,378 11,320 13,386 12,769 12,855 917 1,020 1,019 962 841 963 1,239 1,422 1,664 1,955 1,856 1,910 .. .. .. .. .. .. 247,064 261,007 286,172 273,870 283,012 363,523 27,387 36,393 46,533 58,032 54,633 66,997 2,584 2,948 3,054 3,020 2,950 3,698 14,142 14,331 16,826 20,715 21,368 22,915 2,115 2,203 2,523 3,163 3,156 3,176 9,237 9,977 11,916 14,441 15,803 17,197 7,179 10,702 11,541 14,641 12,805 16,193 5,755 5,444 5,292 4,416 5,836 7,476 328,540 381,921 453,093 561,720 524,944 586,796 102,339 117,169 135,804 170,989 138,120 161,979 709 769 848 983 1,049 .. 89,686 107,484 130,478 162,818 188,984 218,894 44,000 56,484 71,803 93,168 62,360 .. 59,524 65,637 75,226 88,883 90,908 90,803 32,283 34,377 38,934 44,880 43,522 44,238 979,376 1,141,531 1,333,613 1,569,577 1,477,045 1,704,989

1.0 -0.7 3.0 .. 2.4 12.6 4.8 2.2 7.4 8.7 8.1 5.7 8.0 -6.2 2.3 2.0 .. .. 5.9 -0.5 1.7 3.2 .. 3.7 2.6 -0.8 0.8 -5.2 1.8 3.4 3.5 8.8 -4.7 0.1 -0.2 -12.0 8.6 .. 6.2 9.3 -4.3 6.4 4.2 10.1 1.9 .. 4.5 20.7 -3.1 -0.1 4.8 4.5 .. 6.8 .. 3.7 2.3 2.2

1.5 1.2 0.8 -3.8 3.5 4.7 0.0 -3.3 -2.5 7.0 -4.3 -1.3 -2.0 -7.1 -2.4 2.2 22.5 7.2 -5.7 -1.7 6.8 2.6 3.0 -0.6 7.7 4.1 1.8 3.4 0.2 0.4 1.7 5.8 8.3 4.6 -1.8 3.2 -2.0 .. -1.8 6.0 0.6 .. 2.1 0.8 4.5 10.1 -0.1 8.8 0.2 -1.4 4.3 -1.2 1.7 10.8 -0.9 5.1 7.3 2.6

14.6 15.9 15.1 30.4 12.6 10.3 13.9 10.7 10.2 13.3 8.9 21.4 11.1 12.3 17.7 9.6 31.4 12.6 17.4 12.5 5.3 23.8 4.0 17.4 11.7 12.6 7.6 9.2 11.1 15.4 13.1 8.7 10.7 11.7 12.8 18.2 15.1 11.7 12.4 5.2 11.9 .. 12.0 20.6 11.0 9.3 10.7 12.7 19.7 -1.2 11.1 13.7 7.6 9.2 15.0 10.9 8.6 13.2

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.2

Gross domestic product, real

1980

SUB-SAHARAN AFRICA 227,134 Excluding South Africa 131,834 Excl. S. Africa & Nigeria 98,923 Angola .. Benin 1,084 Botswana 1,150 Burkina Faso 1,101 Burundi 659 Cameroon 6,339 Cape Verde .. Central African Republic 735 Chad 665 Comoros 136 Congo, Dem. Rep. 7,016 Congo, Rep. 1,746 Côte d'Ivoire 7,727 Equatorial Guinea .. Eritrea .. Ethiopia .. Gabon 3,594 Gambia, The 399 Ghana 2,640 Guinea .. Guinea-Bissau 115 Kenya 7,078 Lesotho 377 Liberia 1,312 Madagascar 3,099 Malawi 1,000 Mali 1,536 Mauritania 825 Mauritius 1,519 Mozambique 2,462 Namibia 2,292 Niger 1,523 Nigeria 31,452 Rwanda 1,368 São Tomé and Príncipe .. Senegal 2,683 Seychelles 292 Sierra Leone 929 Somalia .. South Africa 95,503 Sudan 5,525 Swaziland 470 Tanzania .. Togo 939 Uganda .. Zambia 2,730 Zimbabwe 3,654 NORTH AFRICA 120,356 Algeria 35,291 Djibouti .. Egypt, Arab Rep. 38,506 Libya .. Morocco 20,086 Tunisia 9,545 AFRICA 350,017

1990

2004

2005

273,077 162,145 127,126 8,464 1,412 3,229 1,556 1,019 8,793 280 815 1,106 181 7,659 2,796 8,298 207 .. 6,234 4,298 569 3,267 2,088 186 10,544 504 408 3,266 1,243 1,630 972 2,726 2,499 2,591 1,507 34,978 1,673 .. 3,463 395 1,014 .. 110,945 7,062 1,139 7,547 1,043 3,293 3,028 5,622 180,141 46,367 660 65,579 .. 29,312 13,547 454,583

406,992 254,784 195,946 12,383 2,650 7,160 3,296 922 11,815 658 892 2,572 222 4,921 3,647 10,287 3,815 782 9,993 5,361 921 6,010 3,585 204 14,327 838 543 4,148 1,875 3,105 1,489 5,261 5,918 4,850 2,091 58,731 2,293 .. 5,579 556 1,125 .. 152,329 15,088 1,651 13,335 1,352 8,055 3,886 4,834 289,670 66,190 619 113,666 37,771 45,835 25,589 696,649

431,505 271,274 209,263 14,644 2,727 7,278 3,581 930 12,087 701 914 3,018 232 5,304 3,932 10,417 4,187 802 11,174 5,523 924 6,364 4,938 211 15,173 860 595 4,339 1,924 3,294 1,622 5,327 6,484 4,972 2,185 61,902 2,507 .. 5,893 598 1,206 .. 160,367 16,043 1,692 14,318 1,368 8,565 4,093 4,558 304,277 69,565 638 118,749 41,511 47,201 26,613 735,761

Constant prices (2000 $ millions) 2006 2007

458,686 289,484 223,630 17,680 2,839 7,652 3,823 980 12,476 772 949 3,024 234 5,600 4,173 10,488 4,239 794 12,384 5,588 955 6,771 5,062 215 16,134 898 653 4,557 2,072 3,469 1,928 5,537 6,893 5,324 2,312 65,740 2,737 .. 6,042 653 1,294 .. 169,354 17,855 1,748 15,282 1,423 9,489 4,348 4,400 321,442 70,956 669 126,876 43,960 50,863 28,118 780,101

488,918 310,343 240,245 21,675 2,970 8,020 3,961 1,027 12,913 838 984 3,030 236 5,950 4,107 10,668 5,148 805 13,803 5,899 1,012 7,209 5,150 222 17,262 940 755 4,842 2,192 3,618 1,960 5,862 7,395 5,610 2,391 69,980 2,888 .. 6,335 716 1,377 .. 178,749 19,669 1,809 16,375 1,456 10,287 4,617 4,239 338,372 73,085 703 135,869 46,598 52,240 29,878 827,251

2008

2009

2010a

513,732 328,716 254,412 24,669 3,121 8,255 4,191 1,079 13,287 890 1,003 3,018 238 6,316 4,335 10,916 5,698 726 15,292 6,036 1,076 7,817 5,405 229 17,526 991 835 5,187 2,375 3,799 2,028 6,186 7,901 5,799 2,599 74,179 3,211 .. 6,570 709 1,454 .. 185,217 21,014 1,852 17,593 1,491 11,183 4,880 3,490 355,930 74,839 744 145,592 48,368 55,158 31,228 869,622

524,769 342,653 263,133 25,265 3,240 7,857 4,315 1,117 13,553 923 1,020 2,982 242 6,495 4,659 11,331 6,025 754 16,638 5,951 1,147 8,129 5,390 236 17,990 1,019 944 4,949 2,590 3,970 2,004 6,373 8,401 5,774 2,575 79,372 3,343 .. 6,707 713 1,500 .. 182,370 21,847 1,874 18,652 1,539 11,993 5,192 3,699 369,193 76,635 781 152,415 49,384 57,783 32,196 893,935

550,762 363,414 277,664 26,126 3,337 8,408 4,656 1,159 13,987 972 1,054 3,369 247 6,961 5,067 11,603 5,979 771 18,291 6,344 1,217 8,779 5,494 244 18,988 1,076 1,041 5,027 2,758 4,200 2,108 6,636 8,972 6,155 2,781 85,582 3,584 .. 6,984 760 1,574 .. 187,640 22,819 1,912 19,966 1,596 12,701 5,587 4,032 384,775 79,164 .. 160,259 .. 59,908 33,161 935,730

Annual average growth (%) 1980–89 1990–99 2000–10

1.8 2.1 2.6 .. 2.7 10.9 4.0 4.5 4.5 6.3 1.6 6.7 2.9 2.1 3.8 0.7 .. .. 2.1 0.5 3.5 2.6 .. 3.8 4.1 2.4 -3.3 0.8 2.4 0.6 1.9 6.1 -0.9 1.1 -0.4 0.8 2.5 .. 2.7 3.1 0.5 .. 1.4 2.4 7.4 .. 1.5 2.3 1.0 3.3 4.2 2.9 .. 5.5 .. 4.2 3.2 2.6

2.4 2.7 2.8 1.0 4.7 5.5 5.5 -3.2 1.3 5.9 1.8 2.3 1.2 -5.0 0.8 3.5 20.7 7.9 3.7 2.9 2.7 4.3 4.5 1.4 2.2 4.0 0.2 1.7 3.8 3.9 3.2 5.0 6.0 4.0 2.4 2.4 -1.6 .. 2.8 4.5 -5.3 .. 2.0 5.4 3.3 2.8 3.6 7.2 0.3 2.9 3.2 1.7 -2.3 4.3 .. 2.4 4.6 2.7

5.2 5.9 5.7 12.9 4.0 4.1 5.9 3.4 3.3 6.3 1.0 9.4 1.9 5.5 4.4 1.1 15.7 0.7 8.8 2.2 4.4 5.9 7.1 1.5 4.4 3.7 5.2 3.4 5.3 5.2 5.9 3.9 7.6 5.0 4.2 6.7 7.5 .. 4.2 2.6 8.8 .. 3.9 6.7 2.5 7.1 2.3 7.7 5.6 -6.3 4.8 3.9 4.0 5.1 5.4 4.9 4.7 5.0

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.3

Gross domestic product growth

Annual growth (%)

SUB-SAHARAN AFRICA Excluding South Africa Excl. S. Africa & Nigeria Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco Tunisia AFRICA

1980

1990

2004

2005

2006

2007

2008

2009

2010a

4.0 1.8 0.7 .. 6.8 12.0 0.8 1.0 -2.0 .. -4.5 -6.1 .. 2.2 17.6 -11.0 .. .. .. 2.6 6.3 0.5 .. -16.0 5.6 -2.7 -4.1 0.8 0.4 -4.3 3.4 -10.1 .. .. -2.2 4.2 9.0 .. -3.3 -4.3 4.8 -3.9 6.6 1.5 12.5 .. 14.6 .. 3.0 14.4 5.2 0.8 .. 10.0 .. 3.6 7.4 4.4

1.2 2.2 0.7 -0.3 3.2 6.8 -0.6 3.5 -6.1 0.7 -2.2 -4.2 5.1 -6.6 1.0 -1.1 3.3 .. 2.7 5.2 3.6 3.3 4.3 6.1 4.2 6.5 -51.0 3.1 5.7 -1.9 -1.8 7.2 1.0 2.5 -1.3 8.2 -2.4 .. -0.7 7.0 3.4 -1.5 -0.3 -5.5 21.0 7.1 -0.2 6.5 -0.5 7.0 4.1 0.8 .. 5.7 .. 4.0 8.0 2.2

6.1 7.1 6.0 11.2 3.1 6.0 4.6 4.8 3.7 4.3 1.0 33.6 -0.2 6.6 3.5 1.8 38.0 1.5 13.6 1.4 7.1 5.6 2.3 2.2 5.1 2.3 -5.1 5.3 5.5 2.2 5.8 5.8 7.9 12.3 0.1 10.6 7.4 6.6 5.9 -2.9 7.5 .. 4.6 1.8 2.9 7.8 2.1 6.8 5.4 -5.8 4.7 5.2 3.8 4.1 4.4 4.8 6.0 5.5

6.0 6.5 6.8 18.3 2.9 1.6 8.7 0.9 2.3 6.5 2.4 17.3 4.2 7.8 7.8 1.3 9.8 2.6 11.8 3.0 0.3 5.9 37.8 3.5 5.9 2.7 9.5 4.6 2.6 6.1 9.0 1.2 9.6 2.5 4.5 5.4 9.3 -1.4 5.6 7.5 7.2 .. 5.3 6.3 2.5 7.4 1.2 6.3 5.3 -5.7 5.0 5.1 3.2 4.5 9.9 3.0 4.0 5.6

6.3 6.7 6.9 20.7 4.1 5.1 6.8 5.4 3.2 10.1 3.8 0.2 1.2 5.6 6.1 0.7 1.3 -1.0 10.8 1.2 3.4 6.4 2.5 2.1 6.3 4.3 9.8 5.0 7.7 5.3 18.9 4.0 6.3 7.1 5.8 6.2 9.2 6.7 2.5 9.3 7.3 .. 5.6 11.3 3.3 6.7 4.1 10.8 6.2 -3.5 5.6 2.0 4.8 6.8 5.9 7.8 5.7 6.0

6.6 7.2 7.4 22.6 4.6 4.8 3.6 4.8 3.5 8.7 3.7 0.2 0.5 6.3 -1.6 1.7 21.4 1.4 11.5 5.6 6.0 6.5 1.8 3.2 7.0 4.7 15.7 6.2 5.8 4.3 1.6 5.9 7.3 5.4 3.4 6.5 5.5 6.0 4.9 9.6 6.4 .. 5.6 10.2 3.5 7.2 2.3 8.4 6.2 -3.7 5.3 3.0 5.1 7.1 6.0 2.7 6.3 6.0

5.1 5.9 5.9 13.8 5.1 2.9 5.8 5.1 2.9 6.2 2.0 -0.4 1.0 6.2 5.6 2.3 10.7 -9.8 10.8 2.3 6.3 8.4 4.9 3.2 1.5 5.4 10.5 7.1 8.3 5.0 3.5 5.5 6.8 3.4 8.7 6.0 11.2 9.1 3.7 -1.0 5.5 .. 3.6 6.8 2.4 7.4 2.4 8.7 5.7 -17.7 5.2 2.4 5.8 7.2 3.8 5.6 4.5 5.1

2.2 4.2 3.4 2.4 3.8 -4.8 3.0 3.5 2.0 3.7 1.7 -1.2 1.8 2.8 7.5 3.8 5.7 3.9 8.8 -1.4 6.7 4.0 -0.3 3.0 2.6 2.9 13.1 -4.6 9.0 4.5 -1.2 3.0 6.3 -0.4 -0.9 7.0 4.1 4.0 2.1 0.5 3.2 .. -1.5 4.0 1.2 6.0 3.2 7.3 6.4 6.0 3.7 2.4 5.0 4.7 2.1 4.8 3.1 2.8

5.0 6.1 5.5 3.4 3.0 7.0 7.9 3.8 3.2 5.2 3.3 13.0 2.1 7.2 8.8 2.4 -0.8 2.2 9.9 6.6 6.1 8.0 1.9 3.5 5.6 5.6 10.3 1.6 6.5 5.8 5.2 4.1 6.8 6.6 8.0 7.8 7.2 4.5 4.1 6.7 5.0 .. 2.9 4.5 2.0 7.0 3.7 5.9 7.6 9.0 4.2 3.3 .. 5.2 .. 3.7 3.0 4.7

Annual average 1980–89 1990–99 2000–10

2.2 2.1 2.6 4.2 3.1 11.5 3.7 4.3 4.0 6.4 0.9 5.4 2.7 1.8 6.8 -0.2 0.9 .. 2.4 1.9 3.9 2.0 4.5 2.9 4.2 2.2 -4.5 0.4 1.7 0.6 2.2 4.3 0.4 1.1 0.0 0.9 3.2 .. 2.4 2.1 1.1 1.7 2.2 3.4 8.6 3.8 2.6 3.0 1.4 5.2 4.3 2.8 .. 5.9 .. 3.9 3.6 2.9

2.1 2.5 2.4 1.0 4.5 5.9 5.1 -1.4 0.4 5.2 1.3 2.2 1.6 -5.5 0.8 2.6 20.2 8.1 2.7 2.5 3.1 4.3 4.3 2.0 2.2 4.1 1.2 1.6 4.1 3.6 2.9 5.2 5.6 4.1 1.9 3.1 2.1 .. 2.7 4.9 -4.3 -1.5 1.4 4.4 4.9 3.3 2.6 6.9 0.4 2.9 3.3 1.6 -2.0 4.3 .. 2.8 5.1 2.5

4.8 5.4 5.2 10.6 4.2 4.3 5.6 3.0 3.4 7.1 1.1 8.8 2.0 3.9 5.0 0.7 17.7 0.8 8.3 1.9 4.6 5.7 5.9 1.9 3.8 3.9 10.1 3.0 4.5 5.5 4.6 4.3 7.2 4.6 4.0 6.4 7.6 5.8 4.0 2.5 9.2 .. 3.6 6.5 2.2 6.8 1.9 7.1 5.4 -4.4 4.4 3.6 3.6 4.9 4.3 4.6 4.4 4.6

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.4

Gross domestic product per capita, real

Constant prices (2000 $)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

594 372 354 .. 300 1,154 153 160 696 .. 323 146 412 260 971 909 .. .. .. 5,265 634 242 .. 137 435 288 682 360 160 212 544 1,573 203 2,263 259 416 264 .. 496 4,532 294 .. 3,463 275 779 .. 352 .. 473 501 1,293 1,876 .. 857 .. 1,019 1,495 736

539 344 340 819 296 2,336 167 182 722 804 278 184 413 210 1,170 663 555 .. 129 4,627 589 221 363 183 450 308 192 289 133 188 487 2,575 184 1,831 194 359 235 .. 478 5,645 255 .. 3,152 267 1,320 305 284 186 385 537 1,501 1,833 1,174 1,154 .. 1,172 1,661 725

558 373 359 776 358 3,866 239 131 688 1,409 226 271 355 88 1,058 580 6,468 181 138 3,988 631 285 403 152 413 409 176 239 150 243 502 4,266 292 2,373 167 431 255 .. 527 6,740 227 .. 3,264 402 1,625 363 256 293 347 384 1,909 2,043 779 1,560 6,682 1,503 2,576 791

577 387 373 888 357 3,880 252 128 689 1,482 227 308 360 92 1,113 578 6,889 179 150 4,029 614 294 546 154 426 417 187 243 150 250 532 4,284 312 2,391 168 443 272 .. 542 7,209 234 .. 3,398 418 1,663 380 253 301 357 363 1,975 2,115 789 1,600 7,195 1,531 2,654 816

599 403 389 1,039 361 4,025 261 131 695 1,614 232 300 355 95 1,150 572 6,774 171 163 4,000 617 305 550 154 442 430 197 247 157 255 616 4,420 324 2,513 172 459 290 .. 541 7,722 243 .. 3,548 454 1,716 394 257 323 370 351 2,054 2,125 812 1,679 7,459 1,632 2,776 846

623 421 408 1,237 366 4,161 263 133 704 1,736 236 292 347 98 1,101 572 7,995 168 178 4,143 636 317 549 156 461 446 217 255 161 258 610 4,651 339 2,599 171 476 297 .. 552 8,420 251 .. 3,704 487 1,773 411 258 339 383 340 2,129 2,155 837 1,766 7,737 1,659 2,922 877

639 435 421 1,368 374 4,223 270 136 708 1,827 237 283 341 101 1,130 575 8,603 147 192 4,162 657 336 565 158 456 466 228 265 170 263 616 4,876 354 2,636 180 492 321 .. 557 8,152 259 .. 3,796 507 1,795 429 258 357 394 280 2,205 2,174 869 1,859 7,865 1,734 3,023 901

637 443 425 1,362 377 3,965 270 137 707 1,878 236 273 338 101 1,182 586 8,845 148 205 4,028 682 341 552 159 456 474 246 246 179 266 593 4,998 368 2,575 172 514 324 .. 554 8,162 261 .. 3,698 514 1,796 442 261 371 408 297 2,253 2,193 895 1,912 7,885 1,797 3,084 905

Annual average growth (%) 1980–89 1990–99 2000–10

-0.9 -0.8 -0.2 .. -0.2 7.4 1.4 1.4 1.4 .. -1.2 3.4 -0.3 -1.2 2.3 -3.0 .. .. .. -1.6 -0.8 -1.1 .. 2.8 0.3 0.3 -6.3 -2.4 -2.3 -0.9 -0.7 4.8 -1.0 -2.2 -2.8 -2.3 -1.0 .. 0.0 1.8 -1.8 .. -0.8 0.5 4.1 .. -2.1 .. -1.9 0.3 1.5 -0.1 .. 2.9 .. 1.3 0.6 -0.1

-0.5 -0.2 -0.2 -2.5 1.4 3.1 2.8 -3.4 -1.5 3.2 -0.8 -0.5 -1.4 -8.8 -2.0 0.1 15.3 .. -0.7 -0.9 0.1 1.7 0.3 -1.2 -0.9 1.9 -2.4 -1.7 1.9 1.4 0.4 3.7 2.8 1.2 -1.3 0.1 -1.2 .. 0.3 2.9 -5.7 .. -0.7 2.8 1.3 -0.1 -0.2 3.5 -2.3 0.4 1.4 -0.3 -4.7 2.4 .. 0.9 3.0 0.0

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.5

Gross domestic product per capita growth

Annual growth (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

1.1 -1.1 -2.1 .. 4.0 7.9 -1.6 -1.8 -4.8 .. -7.0 -8.0 .. -0.7 14.3 -14.9 .. .. .. -0.3 2.7 -1.9 .. -18.5 1.7 -5.3 -7.1 -1.8 -2.6 -6.2 0.4 -11.4 .. .. -5.0 1.3 5.4 .. -5.7 -5.5 2.6 -9.0 4.2 -1.7 9.1 .. 11.5 .. -0.3 10.4 2.5 -2.5 .. 7.5 .. 1.0 4.6 1.6

-1.6 -0.6 -2.2 -3.0 0.1 3.6 -3.2 1.0 -8.8 -0.9 -4.4 -7.1 2.6 -9.9 -1.7 -4.4 0.1 .. -0.6 1.9 -0.5 0.5 -0.3 4.0 0.7 4.5 -50.3 0.1 2.0 -3.7 -4.4 6.2 -0.3 -1.4 -4.2 5.5 -2.2 .. -3.6 6.1 2.1 -1.9 -2.3 -7.7 17.0 3.7 -2.7 2.8 -3.2 3.9 1.8 -1.7 .. 3.5 .. 2.1 5.4 -0.5

3.5 4.4 3.3 7.4 -0.2 4.7 1.6 1.8 1.4 2.8 -0.6 29.1 -2.9 3.5 1.1 0.2 33.8 -2.6 10.8 -0.7 3.9 3.1 0.7 0.2 2.4 1.4 -6.8 2.1 2.7 -1.0 2.8 4.8 5.1 10.4 -3.3 7.9 5.6 5.0 3.1 -2.5 2.7 .. 3.3 -0.5 2.8 5.0 -0.2 3.4 3.0 -5.7 3.0 3.6 2.0 2.2 2.3 3.6 5.0 3.1

3.4 3.8 4.1 14.5 -0.3 0.4 5.5 -2.1 0.0 5.2 0.7 13.6 1.5 4.7 5.1 -0.4 6.5 -1.3 9.2 1.0 -2.6 3.4 35.4 1.4 3.2 1.8 6.4 1.5 -0.2 2.8 6.0 0.4 6.8 0.7 0.9 2.8 7.0 -2.9 2.8 7.0 3.0 .. 4.1 3.8 2.3 4.5 -1.1 2.9 2.9 -5.5 3.4 3.5 1.3 2.6 7.7 1.9 3.0 3.2

3.7 4.0 4.2 17.0 1.0 3.7 3.7 2.2 1.0 8.9 2.0 -2.8 -1.5 2.6 3.4 -1.0 -1.7 -4.4 8.3 -0.7 0.4 3.9 0.7 0.1 3.6 3.3 5.4 1.9 4.7 2.1 15.7 3.2 3.7 5.1 2.1 3.6 6.4 5.1 -0.2 7.1 3.8 .. 4.4 8.6 3.2 3.8 1.8 7.2 3.6 -3.2 4.0 0.5 2.9 4.9 3.7 6.6 4.6 3.6

4.0 4.5 4.8 19.0 1.5 3.4 0.6 1.6 1.2 7.6 1.9 -2.6 -2.2 3.3 -4.3 0.0 18.0 -1.8 9.0 3.6 3.1 3.9 -0.1 1.1 4.3 3.7 10.3 3.1 2.7 1.1 -1.0 5.2 4.7 3.4 -0.2 3.8 2.6 4.4 2.1 9.0 3.5 .. 4.4 7.4 3.4 4.2 0.1 5.0 3.5 -3.3 3.7 1.4 3.1 5.2 3.7 1.6 5.3 3.7

2.5 3.3 3.3 10.6 2.0 1.5 2.7 1.9 0.7 5.3 0.2 -3.0 -1.7 3.3 2.7 0.5 7.6 -12.5 8.4 0.4 3.4 5.9 2.9 1.1 -1.0 4.3 5.1 4.0 5.1 1.8 0.9 4.8 4.3 1.4 4.9 3.4 7.9 7.4 1.0 -3.2 3.0 .. 2.5 4.2 1.2 4.4 0.2 5.2 2.9 -17.5 3.6 0.9 3.8 5.3 1.7 4.5 3.5 2.8

-0.3 1.7 0.9 -0.4 0.8 -6.1 -0.1 0.6 -0.2 2.8 -0.2 -3.8 -0.9 0.1 4.6 1.9 2.8 0.8 6.5 -3.2 3.8 1.6 -2.3 0.9 0.0 1.8 7.8 -7.3 5.7 1.4 -3.6 2.5 3.9 -2.3 -4.4 4.4 1.0 2.3 -0.6 0.1 0.9 .. -2.6 1.4 0.1 3.0 1.0 3.8 3.5 5.8 2.2 0.9 3.0 2.9 0.3 3.7 2.0 0.5

2.4 3.4 2.9 0.6 0.1 5.7 4.7 1.2 1.0 4.3 1.4 10.1 -0.5 4.3 6.0 0.4 -3.5 -0.8 7.6 4.6 3.3 5.5 -0.3 1.4 2.8 4.5 5.9 -1.3 3.2 2.6 2.7 3.7 4.4 4.7 4.2 5.2 4.0 2.7 1.4 7.7 2.7 .. 1.5 1.9 0.8 3.9 1.5 2.6 5.9 8.2 2.7 1.8 .. 3.3 .. 2.6 1.9 2.3

Annual average 1980–89 1990–99 2000–10

-0.7 -0.8 -0.4 1.5 0.3 7.8 1.1 1.1 1.0 4.8 -1.7 2.6 -0.2 -1.1 3.8 -4.1 -2.8 .. -0.8 -1.2 -0.4 -1.0 1.5 0.8 0.4 -0.2 -5.9 -2.3 -2.3 -1.2 -0.6 3.3 -0.6 -2.2 -2.7 -1.7 -0.3 .. -0.5 1.2 -1.3 0.9 -0.3 0.5 4.8 0.6 -0.6 -0.5 -1.7 1.4 1.6 -0.3 .. 3.4 .. 1.4 1.0 0.1

-0.6 -0.2 -0.4 -1.9 1.3 3.2 2.3 -2.8 -2.1 2.9 -1.1 -0.9 -0.9 -8.4 -1.9 -0.4 16.3 6.5 -0.5 -0.5 0.0 1.6 0.2 0.0 -0.7 2.2 -2.3 -1.5 2.2 1.0 0.0 4.0 2.6 1.0 -1.5 0.6 1.1 .. -0.1 3.3 -4.5 -1.9 -0.8 1.8 2.9 0.3 -0.1 3.5 -2.2 0.9 1.5 -0.4 -4.5 2.5 .. 1.2 3.3 0.0

2.2 2.8 2.5 7.2 1.0 2.9 2.6 0.3 1.1 5.7 -0.6 5.4 -0.7 1.0 2.3 -1.1 14.2 -2.7 5.7 -0.1 1.6 3.1 4.1 -0.1 1.2 2.8 6.2 0.0 1.6 2.3 1.8 3.5 4.5 2.6 0.4 3.8 4.4 4.2 1.3 1.8 5.5 .. 2.2 4.0 1.8 3.9 -0.5 3.7 3.0 -4.6 2.8 2.1 1.5 3.0 2.3 3.5 3.4 2.2

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.6

Gross national income, nominal

Current prices ($ millions)

1980

1990

2004

260,972 185,402 120,233 .. 1,402 1,014 1,924 922 5,618 .. 800 1,038 124 14,102 1,544 9,680 .. .. .. 3,856 237 4,426 .. 105 7,043 695 930 4,024 1,138 1,768 682 1,113 3,550 1,818 2,476 61,079 1,165 .. 3,403 142 1,071 603 77,378 7,570 .. .. 1,096 1,237 3,594 6,530 103,562 41,147 .. 21,453 .. 18,402 8,450 369,500

283,962 176,347 150,842 8,214 1,806 3,686 3,094 1,117 10,674 309 1,465 1,721 249 8,579 2,324 9,209 124 .. 12,016 5,336 291 5,774 2,518 233 8,224 902 .. 2,958 1,837 2,405 961 2,631 2,320 2,388 2,423 25,585 2,572 .. 5,520 355 580 835 107,746 11,409 1,174 4,072 1,598 4,227 3,008 8,512 160,577 59,955 .. 42,025 .. 24,835 11,882 448,083

529,160 314,219 235,859 17,295 4,006 9,089 5,102 919 15,374 906 1,268 3,720 360 6,220 3,159 14,763 2,312 1,094 9,990 5,987 544 8,674 3,391 512 15,955 1,544 308 4,285 2,582 4,679 1,899 6,372 5,398 6,689 3,039 78,110 2,055 .. 7,938 666 1,034 .. 214,782 19,991 2,423 12,775 1,904 7,818 5,098 5,522 293,833 81,414 731 78,638 33,139 55,961 29,935 825,220

2005

2006

2007

2008

2009

2010a

614,359 722,408 827,628 944,668 907,409 1,057,639 372,086 466,485 551,236 679,974 630,840 701,347 272,875 324,716 396,646 484,618 476,342 522,707 24,203 35,612 52,850 70,460 68,669 74,299 4,259 4,623 5,428 6,672 6,618 6,576 9,420 10,483 11,641 12,811 11,496 14,699 5,420 5,842 6,754 8,348 8,343 8,819 1,135 1,246 1,325 1,625 1,821 2,033 16,126 17,706 20,606 23,407 22,051 22,250 938 1,063 1,300 1,515 1,557 1,586 1,348 1,473 1,686 1,961 1,974 1,981 4,277 4,888 5,817 6,687 6,678 7,850 386 404 467 530 535 539 6,684 8,354 9,380 10,345 10,418 12,199 4,032 5,105 5,774 8,768 6,979 9,024 15,643 16,589 18,913 22,434 22,031 21,925 4,173 5,223 6,678 11,471 9,085 9,338 1,089 1,202 1,311 1,368 1,839 2,097 12,271 15,126 19,567 26,662 31,922 29,576 7,708 8,187 10,082 12,673 9,862 11,424 593 619 786 991 940 1,011 10,590 17,422 21,392 25,362 25,881 31,643 2,647 2,501 3,814 3,340 3,710 4,297 561 573 687 833 824 834 18,732 22,433 27,093 30,473 30,543 32,040 1,870 1,872 2,025 2,156 2,259 2,711 394 452 585 691 735 809 4,960 5,435 7,288 9,344 8,397 8,628 2,714 3,078 3,437 4,050 4,656 4,928 5,099 5,524 7,146 8,425 8,508 9,003 2,249 2,963 3,348 3,616 3,079 3,545 6,276 6,559 8,016 9,714 8,785 9,833 6,219 6,472 7,445 9,263 9,430 9,127 7,149 7,929 8,629 8,622 8,849 10,709 3,397 3,645 4,290 5,351 5,220 5,379 98,881 141,275 154,068 194,690 154,005 178,059 2,554 3,083 3,721 4,676 5,216 5,580 112 127 149 185 198 203 8,559 9,290 11,224 13,339 12,591 12,722 877 976 955 894 795 896 1,176 1,364 1,629 1,916 1,856 1,910 .. .. .. .. .. .. 242,122 255,872 276,404 264,928 276,697 356,294 26,052 34,081 42,631 53,132 50,018 60,403 2,762 2,962 3,095 3,015 2,827 3,472 13,836 14,154 16,666 20,481 21,186 22,772 2,080 2,165 2,493 3,148 3,137 3,150 8,966 9,728 11,687 14,160 15,517 16,865 6,586 9,534 10,055 13,241 11,442 14,300 5,479 5,131 4,928 4,191 5,636 7,278 336,649 395,458 474,451 586,231 547,759 598,050 97,259 112,669 134,004 169,689 139,577 155,538 776 854 936 1,073 1,120 .. 89,432 108,015 131,655 164,178 189,146 214,530 43,719 57,559 74,070 93,533 61,985 .. 58,760 64,703 74,246 87,411 88,520 88,576 30,645 32,796 36,911 42,387 41,285 41,982 953,712 1,121,058 1,305,162 1,533,224 1,457,811 1,663,007

Annual average growth (%) 1980–89 1990–99 2000–10

0.9 -1.0 2.8 .. 2.1 11.2 4.8 1.9 9.0 18.8 7.8 5.5 7.9 -6.9 1.9 1.3 .. .. 5.8 -0.1 1.6 2.9 .. 3.4 2.6 -0.2 -3.2 -6.0 2.2 2.8 3.2 9.1 -5.6 0.2 0.1 -12.5 8.5 .. 6.1 8.9 -4.8 5.5 4.2 9.7 .. .. 4.6 20.7 -4.1 -0.2 4.9 4.5 .. 7.5 .. 3.3 2.0 2.1

1.8 1.5 1.1 -2.4 3.7 4.2 0.0 -3.4 -2.5 6.8 -4.3 -1.3 -2.0 -7.0 -5.2 3.3 16.9 7.3 -5.8 -1.9 7.1 2.6 3.3 -0.7 8.3 1.5 .. 3.8 0.2 0.1 2.7 5.8 8.6 4.5 -1.7 3.7 -2.0 .. -1.6 5.9 1.5 .. 2.2 1.9 4.6 10.6 -0.1 9.1 0.8 -1.7 5.5 -1.3 1.3 11.2 .. 5.3 7.4 3.0

14.5 15.8 14.9 31.4 12.7 11.0 13.9 10.5 10.8 13.1 9.0 20.1 11.1 12.2 18.0 9.8 33.8 12.6 17.5 12.7 5.4 23.2 3.0 18.2 11.8 12.7 8.4 9.3 11.1 15.5 12.8 8.9 11.0 11.2 12.9 18.7 15.1 13.9 12.5 5.0 12.3 .. 12.0 20.5 10.2 9.2 10.9 12.6 18.6 -1.1 11.5 14.1 8.4 9.0 22.8 10.9 8.5 13.3

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.7

Gross national income, World Bank Atlas method

Current prices ($ millions) 1980

SUB-SAHARAN AFRICA 253,599 Excluding South Africa 188,984 Excl. S. Africa & Nigeria 128,704 Angola .. Benin 1,433 Botswana 998 Burkina Faso 2,016 Burundi 897 Cameroon 5,432 Cape Verde .. Central African Republic 785 Chad 1,086 Comoros .. Congo, Dem. Rep. 17,085 Congo, Rep. 1,471 Côte d'Ivoire 9,318 Equatorial Guinea .. Eritrea .. Ethiopia .. Gabon 3,337 Gambia, The 243 Ghana 4,642 Guinea .. Guinea-Bissau 115 Kenya 7,445 Lesotho 594 Liberia 986 Madagascar 4,018 Malawi 1,169 Mali 1,752 Mauritania 730 Mauritius 1,203 Mozambique .. Namibia .. Niger 2,442 Nigeria 55,749 Rwanda 1,298 São Tomé and Príncipe .. Senegal 3,485 Seychelles 134 Sierra Leone 1,243 Somalia 656 South Africa 69,276 Sudan 9,123 Swaziland .. Tanzania .. Togo 1,137 Uganda .. Zambia 3,610 Zimbabwe 6,692 NORTH AFRICA 101,792 Algeria 38,811 Djibouti .. Egypt, Arab Rep. 21,725 Libya .. Morocco 18,733 Tunisia 8,689 AFRICA 359,659

1990

2004

299,653 180,486 155,042 7,700 1,723 3,505 2,923 1,187 11,128 303 1,384 1,591 234 8,370 2,184 9,253 124 .. 12,200 4,577 292 5,846 2,588 219 8,848 879 .. 2,785 1,723 2,270 984 2,579 2,338 2,429 2,368 25,519 2,546 .. 5,334 351 802 959 119,305 13,641 1,067 4,836 1,516 5,638 3,491 9,014 162,067 61,136 .. 42,479 .. 24,776 11,648 466,087

464,248 295,562 221,626 14,637 3,708 7,990 4,634 902 14,183 838 1,187 3,254 326 6,344 2,687 13,655 1,928 894 9,954 5,357 590 8,144 3,423 359 16,077 1,213 276 5,184 2,813 4,365 1,810 6,157 5,185 .. 2,812 73,419 2,036 .. 7,370 680 1,086 .. 169,045 18,105 1,876 13,313 1,807 7,537 4,648 5,417 283,763 73,987 754 90,591 28,214 53,196 29,106 747,924

2005

2006

2007

2008

2009

Annual average growth (%) 1980–89 1990–99 2000–10

2010a

582,188 686,195 782,645 900,718 952,737 1,014,422 353,255 424,704 504,622 615,609 670,550 710,604 264,952 304,185 361,608 437,395 490,592 523,557 20,870 30,332 45,315 59,978 71,970 75,621 4,316 4,605 5,091 6,063 6,729 6,918 9,508 10,640 11,474 12,610 12,429 13,543 5,591 6,130 6,475 7,497 8,302 9,132 1,009 1,174 1,330 1,507 1,683 1,906 16,295 17,781 19,486 21,733 23,168 23,429 982 1,091 1,240 1,419 1,562 1,627 1,358 1,469 1,597 1,789 1,963 2,058 4,219 4,625 5,212 5,846 7,149 7,987 390 411 435 483 531 550 6,851 7,835 8,799 9,849 10,871 11,907 3,451 4,414 5,239 7,177 7,806 9,071 15,691 16,519 17,769 20,267 22,358 23,005 3,170 4,346 6,239 9,544 11,382 9,612 1,101 1,184 1,245 1,252 1,500 1,792 12,197 14,297 17,647 22,781 28,571 32,342 7,009 7,663 9,209 10,876 11,259 11,567 585 622 723 871 991 1,057 10,019 11,436 16,044 24,088 28,394 30,485 3,828 3,130 3,085 3,347 3,750 3,900 563 592 645 730 824 875 18,609 20,944 24,678 28,331 30,890 32,736 1,744 1,908 2,001 2,238 2,314 2,395 380 459 579 684 791 832 5,377 5,352 6,359 7,906 8,431 8,820 2,828 3,093 3,382 3,907 4,466 4,872 5,195 5,546 6,534 7,457 8,413 9,207 2,186 2,703 3,095 3,570 3,468 3,465 6,658 6,935 7,630 8,658 9,257 9,960 6,152 6,590 7,383 8,566 9,772 10,212 6,864 7,966 8,566 8,971 9,100 9,695 3,347 3,703 4,044 4,819 5,163 5,640 87,688 119,713 142,057 177,029 178,734 185,766 2,469 2,895 3,402 4,258 4,910 5,524 113 127 144 167 189 207 8,680 9,325 10,367 12,045 12,962 13,452 814 943 1,041 983 907 905 1,200 1,341 1,543 1,789 1,946 2,011 .. .. .. .. .. .. 228,949 261,553 278,199 285,495 282,696 304,343 23,263 29,761 37,359 47,056 52,137 56,656 2,644 2,860 3,089 3,194 3,008 3,088 14,411 15,174 16,463 18,766 21,197 23,225 2,024 2,207 2,385 2,732 3,079 3,287 8,539 10,043 11,405 13,198 15,183 16,651 5,695 7,249 9,088 12,066 12,573 13,816 5,523 5,349 5,090 4,293 4,964 6,082 321,566 366,898 425,783 507,709 553,825 587,597 89,352 104,118 122,784 146,530 156,113 155,683 803 864 925 1,029 1,105 .. 92,773 101,664 120,047 146,926 172,125 196,217 37,263 49,547 63,050 77,909 77,140 .. 60,348 66,313 70,674 80,889 89,096 92,583 32,058 34,159 36,428 40,266 42,799 43,709 903,925 1,053,488 1,208,762 1,408,530 1,506,403 1,602,083

1.0 -1.0 2.3 .. 1.1 9.8 3.4 3.6 8.5 18.0 6.9 4.4 10.5 -8.4 2.2 0.8 .. .. 8.9 0.3 0.7 4.0 .. 3.4 2.4 0.9 -3.6 -4.3 2.0 1.3 3.2 7.7 -2.2 1.9 -0.3 -10.9 8.2 .. 4.9 9.5 -6.6 5.9 4.5 9.8 .. .. 3.2 24.5 -6.1 0.1 5.8 6.3 .. 8.6 .. 1.9 2.0 2.5

1.5 0.9 0.6 -2.3 3.2 4.4 -1.1 -4.1 -2.2 7.3 -4.1 -1.2 -1.7 -6.3 -5.8 2.9 15.5 4.2 -5.5 -1.4 10.8 1.9 4.2 -1.1 5.7 2.4 .. 4.1 0.7 0.7 3.8 6.3 6.6 4.7 -2.4 2.7 -3.5 .. -1.6 5.9 0.1 .. 2.3 -0.2 6.0 7.2 -0.3 5.6 -0.2 -2.2 4.3 -2.5 0.6 9.5 .. 4.7 7.2 2.4

14.4 16.0 14.5 33.2 12.8 10.9 13.7 9.3 10.9 12.4 8.7 20.1 11.2 12.2 19.0 9.7 36.2 10.8 16.2 13.5 3.5 20.7 1.5 19.1 11.3 11.9 7.5 9.2 11.7 15.3 12.6 8.9 10.6 11.4 12.8 21.0 12.7 13.4 12.3 6.3 12.1 .. 11.4 20.2 9.8 8.9 10.3 11.5 18.4 -1.9 10.7 14.4 8.5 7.1 20.7 10.6 8.4 12.9

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.8

Gross national income per capita, World Bank Atlas method

Current prices ($)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

663 533 461 .. 400 1,000 280 220 600 .. 350 240 .. 630 820 1,100 .. .. .. 4,890 390 430 .. 140 460 450 510 470 190 240 480 1,250 .. .. 420 740 250 .. 640 2,080 390 100 2,510 450 .. .. 430 .. 630 920 1,093 2,060 .. 480 .. 950 1,360 756

591 383 415 740 360 2,540 310 210 910 870 470 260 530 230 910 740 330 .. 250 4,930 300 400 450 220 380 540 .. 250 180 260 490 2,440 170 1,720 300 260 360 .. 740 5,020 200 150 3,390 510 1,240 200 410 320 440 860 1,351 2,420 .. 750 .. 990 1,430 744

637 433 406 920 500 4,310 340 130 830 1,800 300 340 520 110 780 770 3,270 210 140 3,990 400 390 390 270 460 590 90 300 230 340 610 4,990 260 .. 220 540 230 .. 700 8,240 220 .. 3,620 480 1,850 360 340 270 420 430 1,871 2,280 950 1,240 4,990 1,740 2,930 849

779 505 473 1,270 570 5,070 390 140 930 2,080 340 430 610 120 980 870 5,220 250 160 5,110 390 460 420 410 520 840 120 300 220 390 720 5,360 300 3,300 260 630 270 740 800 9,820 230 .. 4,850 610 2,600 380 370 300 500 440 2,087 2,720 990 1,250 6,460 1,960 3,200 1,003

896 591 529 1,780 590 5,600 420 160 990 2,280 360 460 620 130 1,220 900 6,940 250 190 5,480 400 520 340 420 570 910 140 290 230 410 860 5,540 310 3,760 280 840 310 820 830 11,150 250 .. 5,480 760 2,810 390 400 340 620 430 2,344 3,120 1,050 1,350 8,410 2,130 3,370 1,142

997 685 613 2,590 630 5,950 430 170 1,060 2,570 380 500 640 140 1,400 950 9,690 260 230 6,470 450 710 330 450 660 950 170 340 250 470 960 6,050 340 3,970 290 970 350 920 900 12,240 280 .. 5,760 930 3,030 410 420 380 750 410 2,679 3,620 1,100 1,560 10,470 2,240 3,560 1,281

1,120 815 724 3,330 730 6,450 480 190 1,160 2,910 420 550 690 160 1,870 1,070 14,410 250 290 7,500 530 1,040 350 500 740 1,050 190 400 280 520 1,080 6,830 380 4,080 330 1,170 430 1,050 1,020 11,300 320 .. 5,850 1,140 3,100 460 470 420 970 340 3,146 4,260 1,200 1,880 12,670 2,540 3,900 1,459

1,157 866 792 3,880 780 6,270 520 210 1,210 3,180 450 650 740 170 1,980 1,160 16,710 290 350 7,620 590 1,190 380 550 780 1,080 210 420 310 560 1,030 7,260 430 4,060 340 1,160 480 1,170 1,070 10,390 340 .. 5,730 1,230 2,880 500 520 470 990 400 3,380 4,470 1,270 2,160 12,320 2,770 4,100 1,525

Annual average growth (%) 1980-89 1990-99 2000-10

-1.9 -3.8 -0.7 .. -1.7 6.3 0.8 0.1 5.4 16.8 4.1 1.5 7.3 -11.0 -0.7 -3.1 .. .. 5.5 -2.7 -3.6 0.7 .. 1.3 -1.3 -1.3 -4.9 -6.8 -2.5 -0.5 0.5 6.7 -2.7 -1.8 -3.0 -13.1 4.4 .. 1.9 8.6 -8.7 6.0 1.9 6.8 .. .. -0.2 19.7 -9.0 -3.6 3.1 3.2 .. 6.1 .. -0.6 -0.6 -0.4

-1.2 -1.7 -2.1 -5.1 0.0 1.8 -3.9 -4.9 -4.6 4.8 -6.4 -4.3 -4.0 -9.4 -8.3 0.0 11.8 1.8 -8.1 -4.2 7.7 -0.8 0.0 -3.4 2.8 0.5 .. 1.0 -0.7 -1.9 1.0 5.1 3.5 1.7 -5.6 0.3 -3.7 .. -4.3 4.3 0.3 .. 0.1 -2.6 4.1 4.0 -3.0 2.2 -2.7 -4.0 2.5 -4.4 -1.9 7.6 .. 3.1 5.5 -0.1

11.6 13.1 11.7 29.2 9.4 9.4 10.4 6.4 8.5 11.0 6.8 16.5 8.3 8.6 16.0 7.8 32.2 6.6 13.3 11.3 0.5 17.7 -0.3 16.6 8.4 10.9 4.0 6.0 8.6 11.7 9.5 8.0 7.8 9.3 8.7 18.0 9.9 11.5 9.3 5.5 8.0 .. 10.0 17.4 9.4 5.8 7.8 8.0 15.5 -1.9 9.0 12.7 6.4 5.2 18.2 9.4 7.4 10.4

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.9

Gross domestic product deﬂator (U.S. dollar series)

Index (2000 = 100)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

119.6 146.1 125.6 .. 129.6 92.3 175.2 139.6 106.3 .. 108.4 155.4 91.1 205.2 97.7 131.7 .. .. .. 119.1 60.4 168.4 .. 96.6 102.7 114.5 65.1 130.4 123.8 116.4 85.9 74.8 143.2 94.6 164.7 204.1 85.0 .. 130.6 50.5 118.5 .. 84.5 137.9 115.4 .. 121.0 .. 142.3 182.8 92.9 120.0 .. 59.5 .. 93.7 91.6 110.4

110.0 116.3 126.0 121.2 130.7 117.4 199.4 111.1 126.8 109.6 182.6 157.2 138.2 122.1 100.1 130.1 63.7 .. 193.8 138.5 55.7 180.2 127.7 131.1 81.5 107.2 94.1 94.4 151.3 148.5 104.8 97.3 98.6 90.7 164.6 81.4 154.5 .. 165.1 93.3 64.0 .. 101.0 175.7 97.9 56.4 156.2 130.7 108.6 156.2 95.8 133.8 68.5 65.8 .. 88.1 90.7 104.0

137.3 133.3 128.3 159.7 152.7 140.3 155.0 97.5 133.5 140.5 142.3 171.6 163.2 132.3 127.5 150.5 137.4 141.9 100.6 133.9 62.8 147.6 102.3 256.6 112.3 147.3 86.0 105.2 140.0 157.0 123.2 121.4 96.3 136.2 146.0 149.6 91.1 .. 143.9 125.8 97.4 .. 143.8 143.7 146.6 96.2 143.3 98.6 140.0 120.1 98.7 128.4 107.7 69.4 88.4 124.2 121.9 121.1

151.0 149.2 139.5 192.8 157.2 140.9 152.5 120.1 137.2 138.7 147.7 175.7 167.2 135.6 154.8 157.1 196.3 137.0 110.1 156.9 68.9 168.5 59.5 271.8 123.5 159.0 91.2 116.1 143.2 161.1 134.7 118.0 101.5 146.0 155.8 181.3 103.0 .. 147.9 153.4 102.8 .. 154.1 170.7 152.7 98.8 154.6 107.8 175.4 126.3 108.0 147.1 111.1 75.5 106.0 126.1 121.3 133.1

165.8 172.6 157.5 236.4 166.8 147.1 152.9 126.2 143.9 143.6 155.7 201.7 172.0 157.6 185.3 165.6 226.5 152.6 122.5 170.8 69.9 301.1 55.7 268.7 139.5 159.2 92.5 121.0 150.4 169.1 157.7 117.5 102.9 149.9 157.7 223.4 113.7 .. 155.2 156.1 109.9 .. 154.1 203.8 168.7 93.8 154.8 105.1 246.1 123.7 118.8 165.1 115.0 84.7 128.5 129.0 122.3 146.3

180.4 192.0 178.7 278.9 186.8 154.4 170.5 128.4 160.2 158.8 172.4 231.6 197.4 168.3 204.4 185.6 244.3 163.7 141.7 196.2 82.3 341.7 81.7 310.9 157.8 169.9 97.9 151.7 157.7 197.5 171.3 132.9 108.6 157.0 179.5 237.1 129.4 .. 178.7 142.3 120.8 .. 160.1 236.6 168.8 102.8 173.3 115.8 250.0 124.8 133.9 185.8 120.6 96.0 154.1 144.0 130.3 161.2

196.5 223.9 207.5 341.2 214.1 162.8 199.2 150.2 178.6 175.4 197.6 276.9 222.9 184.8 273.5 214.5 323.3 190.0 174.2 240.7 96.4 365.0 69.9 369.3 174.1 164.1 101.9 181.1 171.5 230.0 176.8 155.9 125.2 152.4 206.6 279.2 146.7 .. 203.8 135.8 134.5 .. 147.9 276.2 163.1 117.7 212.2 129.1 300.0 126.5 157.8 228.5 132.1 111.8 192.6 161.1 143.7 180.5

181.7 195.8 190.6 298.8 203.3 146.8 193.5 162.6 163.7 173.3 194.0 237.6 221.1 172.5 205.9 203.4 203.0 246.1 192.1 183.9 85.7 319.6 77.3 353.4 170.0 167.9 93.2 171.5 182.5 225.8 151.1 138.5 115.2 154.7 204.0 212.4 157.1 .. 190.4 118.1 123.8 .. 155.2 250.1 157.4 114.6 205.1 131.8 246.6 157.8 142.2 180.2 134.4 124.0 126.3 157.3 135.2 165.2

202.9 207.5 200.4 315.7 196.5 177.3 189.6 174.9 160.7 170.8 188.3 253.5 218.9 188.3 237.0 197.5 242.5 274.5 162.3 208.1 86.3 366.5 86.2 341.8 169.6 202.5 94.9 173.5 183.2 224.3 171.5 146.4 102.6 180.9 194.5 230.0 156.9 .. 184.1 126.7 121.3 .. 193.7 293.6 193.4 114.8 199.0 135.4 289.8 185.4 152.5 204.6 .. 136.6 .. 151.6 133.4 182.2

Annual average 1980–89 1990–99 2000–10

105.7 119.2 115.8 95.2 103.3 81.4 147.1 130.1 102.4 80.0 117.3 120.8 89.0 132.9 83.5 108.1 54.3 .. 166.9 96.3 48.5 176.5 117.0 105.0 85.9 95.1 75.0 107.7 118.0 108.1 90.7 71.7 157.3 78.9 137.0 127.0 111.6 .. 119.9 64.8 98.2 .. 88.1 195.6 86.8 68.9 109.1 152.8 110.8 163.2 90.6 128.0 .. 62.3 .. 72.5 80.1 99.9

109.0 104.7 113.2 91.5 115.9 113.9 135.0 104.5 125.2 126.5 142.8 129.0 124.6 126.4 80.5 122.6 64.8 98.6 150.9 104.2 113.4 165.6 136.2 116.2 86.2 120.3 107.2 101.0 132.4 131.8 122.8 106.4 92.8 96.9 126.8 75.6 123.4 .. 135.6 102.7 98.6 .. 115.4 121.9 110.6 71.7 134.3 106.6 110.9 122.9 92.3 100.6 84.7 76.0 93.3 98.7 103.5 102.0

147.4 154.1 146.9 204.5 157.2 135.3 151.2 120.9 135.3 139.2 148.8 183.6 166.3 145.5 159.8 156.7 177.6 154.0 125.4 153.8 78.8 223.7 83.0 245.9 132.2 141.4 88.3 135.6 147.9 165.8 135.9 121.7 100.4 138.1 153.2 178.6 113.8 .. 149.2 127.2 110.0 .. 135.4 182.2 139.2 102.0 153.7 107.7 189.0 125.3 116.9 149.4 112.9 95.6 111.2 127.3 120.1 134.7

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.10

Consumer price Index

Index (2005 = 100)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

Annual average 1980–89 1990–99 2000–10

8.9 9.3 10.0 .. .. 9.3 39.6 8.3 25.1 .. 45.5 .. .. 0.0 .. 28.8 .. .. 25.8 41.6 8.4 0.1 .. .. 5.0 10.8 .. 2.6 0.7 .. .. 18.6 .. .. 47.9 0.7 12.4 .. 35.2 51.7 .. .. 8.5 0.0 7.7 0.9 32.2 0.1 .. 0.0 31.5 7.5 92.3 7.0 34.6 31.5 .. 9.3

35.5 37.8 38.1 0.0 .. 25.3 56.6 17.1 54.8 58.2 61.5 50.8 .. 0.0 45.6 47.5 38.4 .. 39.7 73.3 41.5 4.1 .. 5.4 15.6 37.8 .. 13.1 3.3 61.6 39.4 40.9 4.4 .. 59.1 3.9 19.0 .. 62.1 69.6 .. .. 33.2 0.4 29.5 12.8 46.2 32.3 0.4 0.0 56.6 19.0 .. 33.2 72.6 63.4 56.6 37.8

93.5 93.3 93.5 81.3 94.9 92.1 94.0 88.1 98.0 99.6 97.2 92.7 97.1 82.4 97.0 96.3 94.7 .. 89.6 96.4 95.4 86.9 76.1 96.8 90.7 96.7 90.2 84.4 86.7 94.0 89.2 95.3 93.3 97.8 92.8 84.8 91.7 85.3 98.3 99.1 .. .. 96.7 92.2 95.4 95.2 93.6 92.2 84.5 24.9 97.7 98.6 97.0 95.4 97.4 99.0 98.0 94.3

100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 .. 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 .. .. 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0

106.5 106.6 106.5 113.3 103.8 111.6 102.3 102.8 105.1 105.4 106.7 108.0 103.4 113.1 106.5 102.5 104.4 .. 112.3 98.6 102.1 110.9 134.7 102.0 114.5 106.1 107.3 110.8 114.0 101.5 106.2 108.9 113.2 105.1 100.0 108.2 108.9 124.6 102.1 99.7 100.0 .. 104.6 107.2 105.3 107.3 102.2 107.3 109.0 1,196.7 103.4 102.3 103.5 107.6 101.5 103.3 104.5 106.1

113.0 113.8 113.0 127.2 105.1 119.5 102.1 111.4 106.1 110.0 107.7 98.3 108.0 132.2 109.4 104.4 107.3 .. 131.7 103.6 107.5 122.8 165.5 106.7 125.6 114.6 119.6 122.2 123.0 103.0 114.0 118.5 122.5 112.1 100.1 114.1 118.8 158.9 108.1 105.0 111.7 .. 112.1 115.8 113.8 114.8 103.2 113.9 120.6 .. 107.9 106.1 108.6 117.7 107.8 105.4 108.1 111.9

127.1 127.3 127.2 143.1 113.5 134.6 113.0 138.2 111.8 117.5 117.7 108.5 109.8 155.1 117.4 111.0 114.4 .. 190.1 109.0 112.3 143.1 195.9 117.8 158.6 126.9 140.5 133.5 133.8 112.4 122.3 130.1 135.1 123.7 111.4 127.3 137.1 198.3 114.3 143.8 128.2 .. 125.0 132.3 128.2 126.6 112.2 127.6 135.7 .. 116.2 111.2 121.6 139.2 119.0 109.3 113.4 125.8

135.9 136.9 135.9 162.7 115.9 145.4 115.9 153.4 115.2 118.6 121.8 119.3 114.6 .. 123.6 112.1 119.7 .. 206.2 111.1 117.4 170.7 205.1 115.9 173.2 135.9 150.9 145.4 145.0 114.9 125.0 133.4 139.5 134.6 116.2 142.0 151.3 230.3 113.1 189.4 140.1 .. 133.9 147.2 137.8 142.0 114.4 144.2 153.8 .. 119.8 117.6 123.7 155.6 121.9 110.4 117.4 133.9

140.7 140.8 140.7 186.2 118.6 155.5 115.0 163.2 116.6 121.1 123.6 116.8 118.5 .. 129.8 114.0 129.1 .. 223.0 112.7 123.4 188.9 236.8 118.8 180.1 140.8 .. 158.9 155.8 116.2 132.9 137.2 157.3 140.6 117.1 161.4 154.8 259.9 114.5 184.8 163.4 .. 139.6 166.3 144.0 150.8 116.5 150.0 166.9 .. 123.7 122.2 128.5 173.1 124.9 111.5 122.6 138.4

19.0 20.0 21.0 .. .. 15.4 51.8 12.0 41.8 45.1 58.3 50.5 .. 0.0 44.2 38.5 39.6 .. 31.8 59.8 19.4 1.2 .. 2.6 8.7 20.4 .. 6.6 1.5 61.2 31.9 27.1 1.7 .. 62.5 1.5 16.1 .. 53.3 61.2 .. .. 16.8 0.1 15.5 3.8 43.4 4.7 0.1 0.0 43.3 11.6 102.5 14.7 52.8 47.2 43.2 20.6

54.1 54.2 54.9 0.2 68.6 43.8 71.4 32.0 71.1 77.1 74.8 67.3 .. 0.3 63.5 65.7 52.0 .. 64.5 78.8 53.9 14.7 .. 42.0 41.0 58.8 .. 31.7 14.4 75.1 53.8 56.5 27.6 .. 70.3 22.9 46.4 39.0 77.4 74.8 .. .. 54.3 22.8 46.2 40.6 66.4 59.8 12.0 0.1 72.3 54.9 .. 57.5 104.3 80.4 72.3 56.2

104.5 104.3 104.5 92.6 101.5 105.9 100.5 105.1 103.0 106.2 104.7 101.8 100.2 88.6 105.1 100.1 99.6 .. 124.1 100.7 94.7 104.9 159.1 103.9 112.6 103.2 103.8 102.7 101.7 101.8 99.3 105.7 103.3 110.6 100.4 98.4 106.1 128.8 103.2 117.2 128.7 .. 105.3 106.1 104.7 106.7 100.8 106.2 99.0 190.0 103.2 101.8 104.6 110.4 110.1 101.8 102.6 104.4

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.11

Consumer price index, growth

Annual growth (%)

SUB-SAHARAN AFRICA Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco Tunisia AFRICA

1980

1990

2004

2005

2006

2007

2008

.. .. .. 13.6 12.2 2.5 9.6 .. .. .. .. 46.6 .. 14.7 .. .. 4.5 12.3 6.8 50.1 .. .. 13.9 16.3 .. 18.2 .. .. .. 42.0 .. .. 10.3 10.0 7.3 .. 8.7 13.6 .. .. 13.7 25.4 18.7 30.2 12.3 .. .. 5.4 .. 9.5 12.1 20.8 9.7 9.4 .. ..

.. .. .. 11.4 -0.5 7.0 1.1 10.7 0.0 -0.7 .. 81.3 2.9 -0.8 0.9 .. 5.2 7.7 12.2 37.3 .. 33.0 17.8 11.6 .. 11.8 11.8 0.6 6.6 13.5 47.0 .. -0.8 7.4 4.2 .. 0.3 3.9 .. .. 14.3 65.2 13.1 35.8 1.0 33.1 107.0 17.4 .. 16.7 .. 16.8 8.5 6.8 6.6 ..

.. 43.5 0.9 7.0 -0.4 7.9 0.2 -1.9 -2.1 -5.4 4.5 4.0 2.4 1.4 4.2 .. 3.3 0.4 14.2 12.6 .. 0.9 11.6 5.0 7.8 13.8 11.4 -3.1 10.4 4.7 12.7 4.2 0.3 15.0 12.3 15.2 0.5 3.9 .. .. 1.4 8.4 3.5 4.7 0.4 3.7 18.0 282.4 .. 4.0 3.1 11.3 -2.2 1.5 3.6 ..

.. 23.0 5.4 8.6 6.4 13.5 2.0 0.4 2.9 7.9 3.0 21.3 3.1 3.9 5.6 .. 11.6 3.7 4.8 15.1 31.4 3.3 10.3 3.4 10.8 18.5 15.4 6.4 12.1 4.9 7.2 2.3 7.8 17.9 9.0 17.2 1.7 0.9 .. .. 3.4 8.5 4.8 5.0 6.8 8.5 18.3 302.1 .. 1.4 3.1 4.9 2.7 1.0 2.0 ..

.. 13.3 3.8 11.6 2.3 2.8 5.1 5.4 6.7 8.0 3.4 13.1 6.5 2.5 4.4 .. 12.3 -1.4 2.1 10.9 34.7 2.0 14.5 6.1 7.3 10.8 14.0 1.5 6.2 8.9 13.2 5.1 0.0 8.2 8.9 24.6 2.1 -0.4 .. .. 4.6 7.2 5.3 7.3 2.2 7.3 9.0 1,096.7 .. 2.3 3.5 7.6 1.5 3.3 4.5 ..

.. 12.3 1.3 7.1 -0.2 8.3 0.9 4.4 0.9 -9.0 4.5 17.0 2.7 1.9 2.8 .. 17.2 5.0 5.4 10.7 22.8 4.6 9.8 8.0 11.4 10.3 8.0 1.4 7.3 8.8 8.2 6.7 0.1 5.4 9.1 27.6 5.9 5.3 11.7 .. 7.1 8.0 8.1 7.0 1.0 6.1 10.7 .. .. 3.7 5.0 9.3 6.3 2.0 3.4 ..

.. 12.5 8.0 12.7 10.7 24.1 5.3 6.8 9.3 10.3 1.7 17.3 7.3 6.3 6.6 .. 44.4 5.3 4.5 16.5 18.4 10.5 26.2 10.7 17.5 9.2 8.7 9.2 7.4 9.7 10.3 10.4 11.3 11.6 15.4 24.8 5.8 37.0 14.8 .. 11.5 14.3 12.7 10.3 8.7 12.1 12.5 .. .. 4.9 12.0 18.3 10.4 3.7 4.9 ..

2009

.. 13.7 2.2 8.0 2.6 11.0 3.0 1.0 3.5 10.0 4.4 .. 5.3 1.0 4.7 .. 8.5 1.9 4.6 19.3 4.7 -1.7 9.2 7.2 7.4 9.0 8.4 2.2 2.2 2.6 3.3 8.8 4.3 11.5 10.4 16.1 -1.1 31.8 9.3 .. 7.1 11.3 7.5 12.1 2.0 13.0 13.4 .. .. 5.7 1.7 11.8 2.5 1.0 3.5 ..

2010a

.. 14.5 2.3 7.0 -0.8 6.4 1.3 2.1 1.5 -2.1 3.4 .. 5.0 1.7 7.8 .. 8.1 1.5 5.1 10.7 15.5 2.5 4.0 3.6 .. 9.3 7.4 1.1 6.3 2.9 12.7 4.5 0.8 13.7 2.3 12.9 1.3 -2.4 16.6 .. 4.3 13.0 4.5 6.2 1.8 4.0 8.5 .. .. 3.9 4.0 11.3 2.5 1.0 4.4 ..

Annual average 1980–89 1990–99 2000–10

.. .. .. 10.8 5.0 7.2 9.1 6.7 3.7 3.0 .. 57.0 1.0 6.8 -5.5 .. 4.6 6.5 17.5 48.3 .. 70.5 11.8 13.9 .. 18.6 16.8 -0.1 7.5 11.2 45.1 .. 3.6 20.9 4.7 .. 6.9 4.1 .. .. 14.6 36.2 15.0 30.1 5.0 111.2 69.3 12.8 .. 9.0 5.3 17.4 7.9 7.6 7.6 ..

.. 1,122.5 9.7 10.8 4.5 13.5 5.6 6.4 3.9 5.5 .. 3,367.2 8.5 6.0 6.6 .. 8.0 3.7 5.4 27.6 .. 37.5 17.4 12.4 .. 17.3 31.0 4.2 6.4 7.6 34.5 .. 4.3 30.6 8.6 38.0 4.5 2.0 .. .. 9.9 80.4 9.5 23.1 7.1 13.0 76.2 28.6 .. 18.6 .. 10.5 6.7 4.4 4.9 ..

.. 74.3 3.3 8.6 2.7 10.6 2.5 2.0 3.3 3.6 3.8 110.1 3.2 2.9 5.9 .. 10.7 1.9 6.5 17.8 21.2 3.1 10.3 7.4 10.9 10.4 13.6 2.5 6.3 5.7 10.9 6.1 3.0 12.4 7.6 16.0 2.0 8.3 13.1 .. 6.0 9.1 7.6 6.8 2.8 6.2 16.5 340.8 .. 3.3 3.7 7.9 0.0 1.8 3.4 ..

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.12

Price indices

Inflation, GDP deflator (annual %) Annual % Annual Average 1990–99 2000–10 2009 2010a

4.2 4.2 4.2 -7.4 0.1 -5.5 2.4 12.3 -3.4 4.2 3.5 -9.6 4.6 35.1 -20.6 0.0 -33.8 29.5 24.2 -19.4 6.7 16.6 6.8 1.1 9.2 5.0 -1.2 8.4 6.9 3.5 -5.9 -0.2 4.2 4.2 4.1 -4.5 11.3 13.6 -1.5 25.2 5.2 .. 7.7 -0.3 -1.0 7.4 1.9 14.6 10.7 24.7 1.6 -11.3 1.7 11.2 -32.8 1.5 3.1 3.8

7.0 6.9 6.7 22.4 1.4 14.6 2.8 7.6 3.0 3.3 1.8 11.9 3.8 22.1 20.7 1.9 25.3 11.6 3.9 18.6 5.9 16.5 20.2 1.7 2.2 4.2 6.4 8.1 7.0 4.2 19.4 1.8 10.0 1.0 0.0 9.3 2.5 11.7 1.4 -4.9 14.4 .. 7.9 17.6 6.2 6.9 1.8 9.5 11.7 17.5 7.4 16.3 .. 10.1 .. 0.7 4.6 7.0

9.4 9.4 9.2 1,178.8 7.4 9.6 3.2 11.9 5.6 7.1 3.8 6.4 3.5 3,658.0 6.9 7.5 12.8 6.2 7.2 6.8 16.6 25.8 8.6 36.7 16.1 10.6 380.9 18.1 29.9 6.1 11.2 7.0 36.7 9.4 4.5 29.2 14.3 .. 4.9 1.9 46.0 215.5 11.0 73.9 12.7 23.7 6.6 17.8 70.1 (3.9) 6.0 21.6 4.0 10.3 .. 4.6 5.7 8.5

6.7 6.8 6.6 79.9 3.2 8.5 2.4 13.8 2.1 0.7 2.8 6.0 4.2 98.3 10.0 2.9 11.1 17.1 10.1 6.5 6.3 26.7 11.5 10.9 5.9 7.4 4.2 10.2 18.7 4.7 7.2 5.3 8.8 8.6 3.2 15.7 8.1 14.4 2.5 10.1 8.6 .. 7.6 10.2 7.7 7.3 2.8 6.8 17.5 6.1 5.1 9.2 3.3 8.0 16.0 1.6 3.4 6.4

2009

Consumer price index (2005 = 100) Annual Average 2010a 1990–99 2000–10

Exports price index (goods and services, 2000 = 100) 2009 2010a

.. .. .. .. .. 143.1 .. .. 271.8 236.6 .. .. .. 135.1 .. 158.6 .. .. 155.4 204.4 139.9 .. 179.2 .. 171.7 91.7 70.0 135.3 .. .. 275.3 129.6 83.5 183.3 .. .. .. .. 177.6 73.1 .. .. 193.3 .. 101.6 125.9 203.0 99.5 .. 191.0 .. 154.4 .. 94.6 .. 162.1 174.7 ..

.. .. .. .. .. 161.7 .. .. 300.1 213.4 .. .. .. 158.1 .. 152.7 .. .. 136.3 260.2 140.8 .. 174.3 .. 176.9 109.0 92.8 .. .. .. 361.5 138.9 82.4 350.3 .. .. .. .. 171.9 .. .. .. 237.0 .. 122.9 158.4 208.6 102.6 .. 239.7 .. .. .. 96.6 .. 160.1 183.4 ..

Imports price index (goods and services, 2000 = 100) 2009 2010a

157.1 .. 161.1 .. .. 168.3 .. .. 258.5 143.7 .. .. .. 111.6 .. 165.0 .. .. 134.8 152.6 161.1 .. 181.3 .. 145.3 98.0 289.3 153.3 .. .. 127.8 165.7 169.3 132.6 .. .. .. .. 193.3 73.1 .. .. 153.0 .. 102.2 105.5 279.6 148.0 .. 183.9 140.9 141.6 .. 105.1 .. 160.1 172.9 150.2

176.3 .. .. .. .. 185.2 .. .. 247.0 134.1 .. .. .. 122.3 .. 161.2 .. .. 121.6 166.6 162.1 .. 180.6 .. 152.4 113.0 305.7 .. .. .. 137.7 186.3 164.8 276.5 .. .. .. .. 187.8 .. .. .. 174.7 .. 123.6 125.5 306.0 144.1 .. 219.2 147.2 .. .. 103.9 .. 167.4 190.9 165.5

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.13

Gross domestic savings

Share of GDP (%)

Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco Tunisia AFRICA

1980

1990

2004

2005

2006

2007

2008

2009

2010a

25.3 11.7 11.7 .. -6.4 26.7 -7.2 -0.6 21.7 .. -8.9 .. -10.1 10.1 35.7 20.4 .. .. .. 60.6 5.8 4.9 .. -1.0 18.1 -52.0 5.0 -1.4 10.8 1.1 -3.5 10.4 -8.9 38.4 14.6 .. 4.2 .. 2.1 27.1 0.9 -12.9 37.9 2.1 1.2 .. 23.2 -0.4 19.3 13.8 22.8 43.1 .. 15.2 .. 14.9 24.0 24.2

17.2 11.9 11.9 29.7 2.2 42.6 5.4 -5.4 20.7 25.3 -0.6 -7.7 -3.2 9.4 23.8 11.3 -20.1 .. 9.7 36.9 10.7 5.5 22.2 2.8 18.5 -49.1 .. 5.6 13.4 6.4 4.9 23.0 -5.8 18.2 1.2 .. 6.2 .. 2.4 20.3 8.7 -12.5 23.2 8.2 5.3 1.3 14.7 0.6 16.6 17.5 20.7 27.1 -10.5 16.2 27.2 19.9 20.0 18.8

15.8 14.1 14.1 25.1 5.5 40.5 1.8 -7.5 18.5 1.9 0.0 24.5 -8.5 4.0 52.2 20.0 78.9 -35.1 8.8 54.6 9.7 7.3 18.4 .. 10.7 -46.8 -34.6 8.5 0.0 8.6 6.3 22.1 7.7 16.8 3.9 .. 1.4 .. 7.9 14.7 -0.4 .. 17.8 18.7 12.7 16.2 -4.8 10.1 19.9 -2.6 27.6 47.7 4.3 15.6 42.7 24.2 20.8 21.1

15.8 14.4 14.4 41.3 6.9 43.1 4.8 -12.1 18.1 7.2 0.1 35.1 -12.3 5.9 49.8 17.2 83.7 -29.0 2.6 58.4 5.1 3.7 18.3 .. 9.5 -50.0 -39.1 4.9 -5.5 11.0 9.7 16.5 6.5 19.8 13.4 .. 2.0 .. 14.2 6.6 4.1 .. 17.5 19.0 10.9 16.2 -2.3 11.7 21.7 -7.4 29.8 54.9 8.6 15.7 48.1 23.2 21.3 22.1

15.9 14.6 14.6 56.2 6.9 40.0 2.8 -14.5 18.9 10.5 1.4 36.4 -14.8 -0.6 40.2 19.6 86.1 -18.2 1.5 56.0 10.7 6.1 13.9 .. 7.2 -44.9 -87.5 9.3 1.2 14.8 25.8 15.3 8.8 20.6 .. .. 1.8 .. 10.8 12.8 7.6 .. 17.2 18.6 10.4 14.5 -1.1 8.1 31.4 -9.3 33.4 56.6 12.1 17.1 66.8 24.0 21.6 23.8

16.6 15.0 15.0 43.9 6.1 39.3 .. -17.9 18.5 12.0 1.5 20.5 -15.4 8.7 46.8 14.6 86.9 -18.4 4.2 55.3 5.7 3.8 9.7 .. 8.1 -41.7 -61.9 10.6 14.4 13.0 18.5 17.6 6.3 22.4 .. .. 3.5 .. 8.6 -1.7 6.1 .. 18.3 26.7 11.0 12.8 -1.9 8.8 30.2 -1.5 32.8 57.5 17.4 16.3 63.6 23.4 21.9 24.0

16.3 13.5 13.5 41.3 7.1 32.0 .. -16.6 .. 13.2 -1.3 27.4 -20.1 8.6 46.5 17.9 73.1 .. 0.4 59.0 -1.3 2.0 10.3 .. 5.1 -36.9 -76.1 10.0 4.5 .. 12.5 14.1 1.6 21.8 .. .. 7.0 .. 3.9 5.8 1.7 .. 19.1 26.8 1.7 16.1 0.9 15.3 24.6 -21.5 33.7 56.7 .. 16.8 67.8 24.7 22.9 24.4

15.1 11.5 11.5 14.7 10.8 21.5 .. -9.3 .. 6.8 2.7 5.7 -21.1 15.3 42.7 19.4 58.8 .. 4.1 44.6 2.9 9.9 16.6 .. 6.9 -41.7 -55.8 9.0 9.0 .. 13.9 11.9 2.2 14.3 .. .. 4.2 .. 9.3 14.5 2.3 .. 18.7 19.4 -2.0 17.1 2.4 12.7 25.6 -29.8 25.0 51.2 .. 12.6 .. 24.7 21.9 19.3

16.8 .. 14.4 32.0 12.3 22.5 .. -12.4 .. 18.3 .. 10.7 .. .. 50.9 18.9 58.5 .. 0.4 51.9 2.4 15.0 16.0 .. 9.0 -42.1 -49.9 .. 8.2 .. 15.7 12.5 6.0 26.9 .. .. 1.2 .. 10.8 .. 3.3 .. 19.1 24.2 -2.3 17.2 2.4 13.3 31.5 -26.8 25.6 50.7 .. 14.1 .. 25.2 21.1 20.7

Annual average 1980–89 1990–99 2000–10

20.1 11.9 11.9 24.0 -2.4 35.3 -1.6 3.1 24.2 29.8 -1.1 -8.1 -4.5 10.9 31.9 19.6 .. .. 10.5 44.3 6.5 4.8 16.6 -0.9 18.3 -69.5 -8.0 2.9 12.7 -0.4 3.1 20.3 -6.2 10.8 7.3 .. 5.0 .. 4.3 24.1 9.1 -6.3 28.5 4.2 3.7 .. 12.3 2.3 14.1 16.5 20.3 31.5 .. 15.5 .. 16.7 22.7 20.2

15.5 11.9 11.9 22.0 3.8 38.8 9.0 -5.3 18.5 7.0 3.7 -0.5 -4.9 8.8 28.8 17.8 13.7 -29.7 9.7 43.6 3.9 7.5 18.3 1.5 14.6 -36.6 .. 4.2 3.4 7.6 10.8 24.1 -2.9 12.7 2.7 .. -5.5 .. 5.4 21.7 2.8 -12.5 19.4 9.6 2.0 2.9 6.7 4.3 9.0 17.1 19.1 30.1 -6.4 14.2 17.6 17.8 21.8 17.1

16.1 13.7 13.8 32.2 7.1 36.0 2.6 -10.9 18.8 5.6 1.9 13.5 -11.1 5.9 47.3 19.3 76.4 -28.2 5.3 52.9 4.4 6.8 15.1 -13.2 8.4 -37.2 -29.3 9.2 4.1 12.2 10.5 19.3 6.0 18.1 5.9 .. 2.3 .. 9.2 14.0 -1.2 .. 18.6 18.9 8.2 14.8 0.1 9.9 19.2 -6.1 27.8 49.8 5.7 14.8 46.6 23.8 21.5 21.3

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.14

Gross national savings

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

23.4 .. 10.9 .. 4.2 27.4 9.3 .. 5.2 .. 1.6 .. -0.4 .. 26.1 8.6 .. .. .. 47.8 16.4 6.3 .. .. 17.2 49.6 14.6 -0.7 7.9 8.4 5.4 10.4 -6.6 .. 17.1 .. 14.0 .. 2.7 32.4 2.9 20.1 33.9 4.5 .. .. 27.2 1.9 7.8 12.0 25.9 41.0 .. 21.0 .. 18.6 25.3 24.5

15.8 12.8 12.8 9.0 5.3 41.7 15.9 8.7 16.2 53.9 6.2 2.3 14.4 .. 6.9 -5.1 2.1 .. 12.8 24.3 21.9 10.5 19.2 14.5 18.5 70.5 .. 9.1 16.4 15.0 7.5 25.8 6.6 34.8 -0.6 .. 11.3 .. 1.6 21.7 -1.0 .. 19.1 1.2 19.7 10.1 21.0 5.6 19.6 15.6 27.6 24.3 .. 31.1 .. 25.1 23.4 20.8

16.3 17.5 17.5 12.6 6.8 36.2 5.4 12.0 17.1 25.3 .. .. .. .. 19.7 12.4 .. .. 22.1 35.4 15.0 22.9 11.4 .. 16.1 14.0 90.8 14.2 5.1 8.6 .. 22.6 8.0 28.2 6.9 .. 14.8 .. 14.7 12.4 4.8 .. 15.0 16.1 17.2 20.4 2.2 21.2 14.1 .. 25.2 .. 24.4 21.1 34.4 31.0 21.2 19.9

16.2 17.9 17.9 27.1 10.1 41.5 8.3 11.0 16.7 32.7 .. .. .. .. 16.6 10.0 .. .. 13.7 44.2 9.6 19.3 8.0 .. 16.1 21.2 77.4 8.0 1.6 11.4 .. 17.4 7.1 27.6 18.5 .. 15.1 .. 21.1 5.6 10.0 .. 14.5 19.4 21.6 17.5 4.9 20.0 14.9 .. 32.6 51.9 28.3 21.8 46.0 30.9 20.3 23.8

15.5 16.6 16.6 40.9 10.0 40.9 6.9 4.8 19.2 32.5 .. .. .. .. 5.9 12.1 .. .. 9.7 .. 16.7 2.6 1.8 .. 14.8 26.5 86.0 .. 7.6 14.5 .. 17.1 7.1 31.8 .. .. 10.4 .. 18.7 12.9 9.0 .. 14.4 15.5 15.4 17.4 8.2 16.7 23.9 .. 37.0 54.1 33.4 23.0 69.8 32.2 21.2 25.6

15.6 .. 17.2 31.0 8.8 43.3 .. 0.8 20.3 32.3 .. .. .. .. 15.2 8.4 .. .. 21.6 .. 10.9 -1.1 -2.8 .. 15.3 28.6 71.3 .. 17.2 18.6 .. 22.1 6.6 31.8 .. .. 14.1 .. 19.1 -6.6 10.3 .. 14.1 19.2 18.7 15.7 7.9 16.1 21.9 .. 37.6 57.9 37.1 23.6 66.5 32.3 20.9 26.0

15.4 .. 15.9 24.8 10.6 35.0 .. -4.8 .. 30.4 .. .. .. .. .. 12.2 .. .. 16.6 .. 2.2 -1.3 -0.8 .. 12.6 38.4 43.3 .. 10.6 .. .. 17.2 3.8 32.1 .. .. 17.2 .. 16.1 2.1 5.3 .. 15.0 19.0 8.5 18.0 10.6 21.9 18.9 .. 37.8 57.6 .. 23.6 67.1 32.9 21.6 26.3

15.5 .. 15.5 5.2 13.9 26.4 .. 5.2 .. 23.6 .. .. .. .. .. 14.5 .. .. 14.8 .. 12.2 17.5 6.5 .. 14.2 32.6 53.0 .. 12.8 .. .. 13.9 7.6 27.5 .. .. 15.0 .. 19.4 14.6 10.3 .. 15.5 12.8 0.4 19.5 12.4 18.2 19.0 .. 28.7 54.1 .. 16.9 .. 30.2 21.2 21.4

17.2 .. .. 21.6 .. 27.7 .. -5.4 .. 34.4 .. .. .. .. .. .. .. .. 16.6 .. 9.4 20.6 7.1 .. 15.6 12.7 29.0 .. .. .. .. 15.6 12.2 34.1 .. .. 12.2 .. .. .. 13.0 .. 16.5 17.5 2.4 20.1 .. 19.0 22.5 .. 27.7 48.4 .. 17.8 .. 30.8 20.3 22.2

Annual average 1980–89 1990–99 2000–10

18.6 13.1 12.4 13.8 4.6 34.3 14.6 11.2 18.8 59.2 6.1 6.2 15.0 .. 25.5 6.8 .. .. 13.4 33.7 16.9 7.3 12.4 1.8 18.0 42.0 -3.9 3.0 12.5 6.1 7.2 20.2 -2.3 .. 8.8 .. 12.0 .. 4.2 27.3 7.7 19.2 24.4 3.7 .. .. 16.8 5.5 3.2 14.6 23.6 29.4 .. 21.8 .. 20.5 23.7 20.8

15.2 14.0 14.0 1.6 7.8 40.5 21.5 6.2 13.4 34.9 8.1 4.6 15.4 .. 5.3 6.0 14.7 32.8 15.5 29.3 8.9 13.5 18.7 9.0 21.8 50.6 .. 5.1 8.1 14.7 17.3 26.5 6.0 27.5 3.7 .. 14.2 .. 6.3 21.5 0.8 .. 16.6 4.0 16.2 8.7 10.8 14.4 7.1 15.7 28.3 28.6 11.4 24.7 .. 21.6 21.7 18.4

15.9 16.3 16.2 18.5 9.8 35.8 6.7 4.4 16.5 27.0 .. .. .. .. 17.0 11.7 .. 4.4 17.5 37.1 10.4 14.2 8.4 -7.3 14.7 28.9 64.4 11.8 8.8 13.1 .. 21.2 8.1 28.8 8.6 .. 13.3 .. 16.4 11.1 6.6 .. 15.3 14.1 15.4 17.4 6.9 17.9 13.6 .. 30.3 54.0 22.3 20.1 49.7 30.5 21.1 21.6

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.15

General government ﬁnal consumption expenditure

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

15.1 .. 16.1 .. 8.6 21.3 9.2 9.2 9.7 .. 15.1 .. 30.9 8.4 17.6 16.9 .. .. .. 13.2 31.2 11.2 .. 27.6 19.8 21.8 21.3 12.1 19.3 11.6 45.3 14.0 12.2 17.4 10.4 .. 12.5 .. 24.8 28.7 8.4 15.6 14.3 16.0 27.0 .. 22.4 .. 25.5 18.5 15.9 15.2 .. 15.7 .. 18.3 14.5 15.5

17.5 15.6 15.6 34.5 11.0 24.1 21.1 10.8 12.8 16.3 14.9 10.1 24.5 11.5 13.9 16.8 39.7 .. 13.2 13.4 13.8 9.3 11.0 10.3 18.6 25.8 .. 8.0 15.1 13.8 25.9 13.6 13.5 30.6 15.0 .. 10.1 .. 18.4 27.7 7.8 .. 19.7 5.8 14.3 17.8 14.2 7.5 19.0 19.5 15.2 16.1 31.5 11.3 24.4 15.5 16.4 16.4

16.5 13.9 13.9 .. 13.6 21.1 21.6 19.6 10.2 28.7 10.6 4.9 14.3 8.2 15.0 8.3 2.9 44.8 13.1 9.3 7.1 12.2 7.0 .. 17.9 35.6 11.1 6.9 12.5 10.0 17.6 14.3 10.8 20.4 12.5 .. 18.4 .. 13.7 28.3 13.3 .. 19.4 11.8 15.1 16.9 10.3 13.9 18.0 21.0 14.3 13.8 29.7 12.8 13.1 18.7 16.9 15.5

16.7 14.2 14.2 20.0 15.0 22.4 22.2 19.0 10.0 28.5 13.3 5.1 13.5 8.2 13.0 8.3 2.7 39.7 12.3 8.3 7.7 15.3 7.0 .. 17.4 36.7 11.4 9.0 14.3 10.0 18.0 14.8 10.4 19.3 11.5 .. 18.2 .. 9.6 20.5 13.8 .. 19.5 18.2 15.2 17.6 11.5 14.5 9.7 15.2 13.8 11.6 27.1 12.7 11.8 19.4 16.9 15.4

16.4 13.4 13.4 18.5 .. 19.0 21.7 20.4 9.6 25.7 11.1 4.9 14.2 7.6 13.9 8.3 2.6 38.0 12.1 8.4 8.0 11.3 8.1 .. 17.6 35.4 9.4 8.8 14.6 9.9 15.2 14.2 10.7 19.5 .. .. 18.2 .. 9.7 18.8 13.8 .. 19.7 17.3 13.9 17.5 11.4 14.1 10.2 5.9 13.2 11.2 28.0 12.3 10.7 18.6 16.7 14.9

15.9 13.1 13.1 15.3 .. 19.4 .. 28.8 9.2 25.8 2.7 10.3 14.3 10.3 17.0 8.7 2.3 32.8 10.4 8.9 7.9 11.6 6.8 .. 17.9 35.7 13.6 12.3 14.1 10.3 14.8 12.9 11.8 20.7 .. .. 16.5 .. 10.0 16.2 11.8 .. 19.0 15.5 14.1 19.3 9.2 12.9 10.3 3.2 12.9 11.3 25.1 11.3 11.6 18.2 16.5 14.5

16.2 13.0 13.0 17.1 .. 18.9 .. 30.0 .. 25.6 6.6 12.4 15.3 11.0 12.0 8.6 2.7 .. 9.7 8.2 9.6 11.2 9.3 .. 16.5 36.9 18.3 11.3 17.3 .. 14.7 12.7 12.1 20.8 .. .. 14.7 .. 9.7 12.8 12.5 .. 19.3 15.8 13.4 17.4 .. 11.2 8.8 2.1 12.5 12.9 .. 10.9 9.3 17.2 16.1 14.5

17.5 13.8 13.8 17.4 .. 24.3 .. 26.9 .. 25.7 4.5 15.1 15.3 7.6 12.2 8.7 3.9 .. 8.2 11.5 9.3 11.7 7.9 .. 15.8 39.8 20.7 11.6 20.9 .. 16.2 14.1 13.3 25.0 .. .. 14.5 .. 8.7 11.1 14.0 .. 21.1 13.9 14.7 17.5 .. 11.6 13.1 13.3 13.7 14.2 .. 11.4 .. 18.2 16.2 15.8

18.2 .. 14.6 17.6 .. 20.9 .. 31.6 .. 26.1 .. 13.2 .. .. 10.4 8.6 .. .. 10.2 10.0 9.6 9.5 7.5 .. 16.7 37.2 18.6 .. 20.2 .. 13.1 13.9 12.7 24.2 .. .. 15.5 .. 8.7 .. 12.3 .. 21.5 15.2 26.8 18.2 .. 11.7 13.3 19.1 .. .. .. 11.2 .. 17.5 16.3 16.4

Annual average 1980–89 1990–99 2000–10

16.5 15.6 15.6 31.5 12.7 24.4 15.6 9.3 10.1 14.5 15.7 11.4 28.6 9.0 17.7 16.5 27.4 .. 11.2 18.3 29.1 9.0 11.6 18.9 18.3 23.3 24.3 9.8 17.5 12.3 30.7 12.6 13.8 27.9 11.9 .. 13.0 .. 19.3 33.1 7.7 17.6 17.4 11.1 21.5 .. 16.9 9.9 23.1 20.1 16.6 17.2 .. 16.2 .. 16.6 16.5 16.5

16.7 14.4 14.4 40.7 10.5 26.7 22.5 17.0 10.6 17.1 13.9 8.1 20.3 9.9 18.1 11.9 25.1 39.7 9.8 13.2 12.2 11.7 8.2 8.4 15.8 33.6 .. 7.9 16.6 12.7 15.5 14.0 9.7 31.0 14.6 .. 11.5 .. 15.1 29.0 10.6 .. 19.4 6.1 17.1 14.8 12.8 11.1 17.7 17.6 15.3 16.6 31.8 10.9 24.3 17.0 16.2 16.1

16.4 13.5 13.6 17.6 12.9 21.3 22.2 22.0 9.9 26.0 9.9 8.8 14.7 7.8 14.1 8.2 3.4 44.4 12.4 9.7 9.1 11.3 7.6 13.1 16.9 37.2 11.4 9.5 15.5 9.4 17.7 13.9 10.8 21.8 12.2 .. 15.0 .. 11.1 20.5 14.1 .. 19.4 13.2 16.3 16.0 10.2 13.9 11.8 14.3 13.9 13.3 28.0 11.8 14.4 18.3 16.7 15.3

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.16

Household ﬁnal consumption expenditure

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

59.0 .. 71.6 .. 97.7 52.0 98.0 91.4 68.6 .. 93.7 .. 79.2 81.6 46.8 62.8 .. .. .. 26.1 63.0 83.9 .. 73.3 62.1 130.3 73.7 89.3 69.9 87.4 58.2 75.6 96.7 44.2 75.1 .. 83.3 .. 73.1 44.2 90.7 97.3 47.8 81.9 71.8 .. 54.5 .. 55.2 67.7 61.3 41.7 .. 69.2 .. 66.8 61.5 60.0

65.2 72.3 72.3 35.8 86.8 33.2 73.5 94.6 66.6 58.5 85.7 97.6 78.7 79.1 62.4 71.9 80.3 .. 77.2 49.7 75.6 85.2 66.9 86.9 62.8 123.3 .. 86.4 71.5 79.8 69.2 63.4 92.3 51.2 83.8 .. 83.7 .. 79.2 52.0 83.5 .. 57.1 86.1 80.5 81.0 71.1 91.9 64.4 63.1 64.1 56.8 78.9 72.6 48.4 64.6 63.6 64.7

67.9 72.5 72.5 .. 80.9 38.4 76.6 87.9 71.4 69.4 89.5 70.6 94.2 87.8 32.8 71.7 18.2 90.4 78.2 36.2 83.2 80.5 74.6 .. 71.4 111.2 123.6 84.5 87.5 81.4 76.1 63.7 81.4 62.8 83.6 .. 80.3 .. 78.4 57.0 87.2 .. 62.9 69.5 72.2 66.9 94.5 76.0 62.1 81.6 58.1 38.5 66.0 71.7 44.2 57.2 62.3 63.4

67.5 71.4 71.4 38.7 78.1 34.5 73.0 93.1 72.0 64.2 86.6 59.8 98.8 85.9 37.2 74.5 13.6 89.3 85.1 33.3 87.2 81.0 74.8 .. 73.2 113.3 127.8 86.2 91.1 79.1 72.3 68.7 83.2 60.9 75.1 .. 79.8 .. 76.3 72.9 82.2 .. 63.1 62.8 73.9 66.3 90.8 73.8 68.6 92.2 56.4 33.6 64.3 71.6 40.2 57.5 61.8 62.5

67.7 71.9 71.9 25.4 .. 41.0 75.5 94.1 71.5 63.8 87.6 58.7 100.6 93.0 45.9 72.0 11.3 80.2 86.4 35.6 81.3 82.6 78.0 .. 75.2 109.5 178.2 82.0 84.2 75.3 59.0 70.5 80.5 60.0 .. .. 80.1 .. 79.6 68.4 78.6 .. 63.1 64.1 75.7 68.0 89.7 77.9 58.4 103.5 53.4 32.2 59.9 70.6 22.5 57.5 61.7 61.2

67.4 71.7 71.7 40.8 .. 41.4 .. 89.2 72.2 62.1 95.9 69.2 101.2 81.0 36.2 76.8 10.8 85.6 85.5 35.9 86.5 84.6 83.6 .. 74.0 106.0 148.3 77.1 71.5 76.8 66.7 69.5 81.9 56.9 .. .. 80.0 .. 81.4 85.6 82.0 .. 62.7 57.8 74.9 67.9 92.8 78.4 59.5 98.3 54.3 31.2 57.5 72.4 24.8 58.4 61.6 61.4

67.4 73.3 73.3 41.6 .. 49.2 .. 86.6 .. 61.2 94.7 60.2 104.8 80.4 41.6 73.6 24.2 .. 89.9 32.9 91.7 86.8 80.5 .. 78.4 100.0 157.8 78.8 78.2 .. 72.8 73.2 86.4 57.5 .. .. 78.4 .. 86.4 81.4 85.9 .. 61.6 57.5 84.9 66.4 .. 73.5 66.5 119.4 53.8 30.4 .. 72.3 22.9 58.1 61.0 61.0

67.3 74.6 74.6 67.9 .. 54.2 .. 82.4 .. 67.5 92.8 79.3 105.9 77.1 45.0 71.9 37.3 .. 87.6 43.8 87.8 78.4 75.5 .. 77.3 101.9 135.1 79.4 70.1 .. 69.9 74.1 84.5 60.6 .. .. 81.3 .. 82.0 74.5 83.7 .. 60.3 66.7 87.3 65.5 .. 75.7 61.3 116.4 61.3 34.7 .. 76.1 .. 57.1 61.9 64.7

64.9 .. 71.0 50.4 .. 56.6 .. 80.8 .. 55.6 .. 76.1 .. .. 38.6 72.5 .. .. 89.4 38.2 88.0 75.5 76.5 .. 74.4 104.8 131.3 .. 71.7 .. 71.2 73.6 81.4 49.0 .. .. 83.3 .. 80.5 .. 84.4 .. 59.4 60.6 75.5 64.7 .. 75.0 55.2 107.7 .. .. .. 74.7 .. 57.3 62.7 66.5

Annual average 1980–89 1990–99 2000–10

63.3 72.5 72.4 44.5 89.7 40.4 86.0 87.5 65.8 55.7 85.5 96.8 76.0 80.0 50.3 63.9 .. .. 78.4 37.4 64.4 86.2 71.8 82.0 63.3 146.3 83.7 87.2 69.8 88.1 66.3 67.1 92.3 61.3 80.8 .. 82.0 .. 76.4 42.7 83.2 100.6 54.2 84.8 74.7 .. 70.8 87.2 62.9 63.4 63.1 51.3 .. 68.3 .. 66.7 60.8 63.2

67.9 74.0 74.0 42.6 85.7 34.5 68.5 88.3 70.9 75.9 82.4 92.5 84.6 81.3 53.1 70.3 61.2 90.0 80.5 43.2 84.0 80.8 73.5 90.1 69.6 103.0 .. 87.9 80.0 79.7 73.7 62.0 93.2 56.3 82.7 .. 94.0 .. 79.6 49.3 86.6 .. 61.2 84.3 80.9 82.3 80.5 84.6 73.3 65.3 65.6 53.3 73.8 75.0 58.1 65.3 62.0 66.9

67.5 73.0 72.8 44.1 81.3 42.7 75.2 88.9 71.4 68.5 88.2 77.8 96.4 86.3 38.6 72.5 18.4 83.9 82.3 37.4 86.5 81.9 77.3 100.1 74.7 99.9 118.0 81.3 80.4 78.4 71.8 66.8 83.1 60.2 81.9 .. 82.7 .. 79.7 65.6 87.1 .. 62.0 67.9 75.5 69.1 90.4 76.3 69.0 91.7 58.1 37.0 66.3 73.4 39.0 58.0 61.9 63.7

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.17

Final consumption expenditure plus discrepancy

Share of GDP (%)

SUB-SAHARAN AFRICA Excl. South Africa Excl. S. Africa & Nigeria Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco Tunisia AFRICA

1980

1990

2004

2005

2006

2007

2008

2009

2010a

74.8 88.3 88.3 .. 106.4 73.3 107.2 100.6 78.3 .. 108.9 .. 110.1 89.9 64.4 79.6 .. .. .. 39.4 94.2 95.1 .. 101.0 81.9 152.0 95.0 101.4 89.2 98.9 103.5 89.6 108.9 61.6 85.4 .. 95.8 .. 97.9 72.9 99.1 112.9 62.1 97.9 98.8 .. 76.8 100.4 80.7 86.2 77.2 56.9 .. 84.8 .. 85.2 76.0 75.8

82.8 88.1 88.1 70.3 97.8 57.4 94.6 105.4 79.3 74.7 100.6 107.7 103.2 90.7 76.2 88.7 120.1 .. 90.4 63.1 89.3 94.5 77.8 97.2 81.5 149.1 .. 94.5 86.6 93.6 95.1 77.0 105.8 81.8 98.9 .. 93.8 .. 97.6 79.7 91.3 112.5 76.8 91.9 94.8 98.7 85.3 99.4 83.4 82.6 79.3 72.9 110.5 83.9 72.8 80.1 80.0 81.2

84.2 86.0 86.0 74.9 94.5 59.5 98.2 107.5 81.5 98.1 100.0 75.5 108.5 96.0 47.8 80.0 21.1 135.1 91.2 45.4 90.3 92.7 81.6 .. 89.3 146.8 134.6 91.5 100.0 91.4 93.7 78.0 92.3 83.2 96.1 .. 98.6 .. 92.1 85.3 100.4 .. 82.2 81.3 87.3 83.8 104.8 89.9 80.1 102.6 72.4 52.3 95.7 84.4 57.3 75.8 79.2 78.9

84.2 85.6 85.6 58.7 93.1 56.9 95.2 112.1 82.0 92.8 99.9 64.9 112.3 94.1 50.2 82.8 16.3 129.0 97.4 41.7 94.9 96.3 81.8 .. 90.6 150.0 139.1 95.1 105.5 89.0 90.3 83.5 93.5 80.2 86.6 .. 98.0 .. 85.8 93.4 95.9 .. 82.5 81.0 89.1 83.9 102.3 88.3 78.3 107.4 70.2 45.1 91.4 84.3 52.0 76.8 78.7 77.9

84.1 85.4 85.4 43.8 93.1 60.0 97.2 114.5 81.1 89.5 98.6 63.6 114.8 100.6 59.8 80.4 13.9 118.2 98.5 44.0 89.3 93.9 86.1 .. 92.8 144.9 187.5 90.8 98.8 85.3 74.2 84.7 91.2 79.5 .. .. 98.2 .. 89.3 87.2 92.4 .. 82.8 81.4 89.6 85.5 101.1 92.0 68.6 109.3 66.6 43.4 87.9 82.9 33.2 76.1 78.4 76.2

83.4 85.0 85.0 56.1 93.9 60.7 .. 117.9 81.5 88.0 98.5 79.5 115.4 91.3 53.2 85.4 13.1 118.4 95.8 44.7 94.4 96.2 90.3 .. 91.9 141.7 161.9 89.4 85.6 87.0 81.5 82.4 93.7 77.6 .. .. 96.5 .. 91.4 101.7 93.9 .. 81.7 73.3 89.0 87.2 101.9 91.2 69.8 101.5 67.2 42.5 82.6 83.7 36.4 76.6 78.1 76.1

83.7 86.5 86.5 58.7 92.9 68.0 .. 116.6 .. 86.8 101.3 72.6 120.1 91.4 53.6 82.2 26.9 .. 99.6 41.0 101.3 98.0 89.7 .. 94.9 136.9 176.1 90.0 95.5 .. 87.5 85.9 98.4 78.3 .. .. 93.1 .. 96.1 94.2 98.3 .. 80.9 73.2 98.3 83.9 99.1 84.7 75.4 121.5 66.3 43.3 .. 83.2 32.2 75.3 77.1 75.6

84.9 88.5 88.5 85.3 89.2 78.5 .. 109.3 .. 93.2 97.3 94.3 121.1 84.7 57.3 80.6 41.2 .. 95.9 55.4 97.1 90.2 83.4 .. 93.1 141.7 155.8 91.0 91.0 .. 86.1 88.1 97.8 85.7 .. .. 95.8 .. 90.7 85.5 97.7 .. 81.4 80.6 102.0 83.0 97.6 87.3 74.4 129.8 75.0 48.8 .. 87.5 .. 75.3 78.1 80.7

83.2 .. 85.6 68.0 87.7 77.5 .. 112.4 .. 81.7 .. 89.3 .. .. 49.1 81.1 41.5 .. 99.6 48.1 97.6 85.0 84.0 .. 91.1 142.1 149.9 .. 91.8 .. 84.3 87.5 94.0 73.1 .. .. 98.8 .. 89.2 .. 96.7 .. 80.9 75.8 102.3 82.8 97.7 86.7 68.5 126.8 74.4 49.3 .. 85.9 .. 74.8 78.9 79.3

Annual average 1980–89 1990–99 2000–10

79.9 88.1 88.1 76.0 102.4 64.7 101.6 96.9 75.8 70.2 101.1 108.1 104.5 89.1 68.1 80.4 .. .. 89.5 55.7 93.5 95.3 83.4 100.9 81.7 169.5 108.0 97.1 87.3 100.4 96.9 79.7 106.2 89.2 92.7 .. 95.0 .. 95.7 75.9 90.9 106.3 71.5 95.8 96.3 .. 87.7 97.7 86.0 83.5 79.7 68.5 .. 84.5 .. 83.3 77.4 79.8

84.6 88.1 88.1 78.0 96.2 61.2 91.0 105.3 81.5 93.0 96.3 100.5 104.9 91.2 71.2 82.2 86.3 129.7 90.3 56.4 96.1 92.5 81.7 98.5 85.4 136.6 .. 95.8 96.6 92.4 89.2 75.9 102.9 87.3 97.3 .. 105.5 .. 94.6 78.3 97.2 112.5 80.6 90.4 98.0 97.1 93.3 95.7 91.0 82.9 80.9 69.9 106.4 85.8 82.4 82.2 78.2 82.9

83.9 86.3 86.2 67.8 92.9 64.0 97.4 110.9 81.2 94.5 98.1 86.5 111.1 94.2 52.7 80.7 23.6 128.2 94.7 47.1 95.6 93.2 84.9 113.2 91.6 137.2 129.3 90.8 95.9 87.8 89.5 80.7 94.0 82.0 94.1 .. 97.7 .. 90.8 86.0 101.2 .. 81.4 81.1 91.8 85.2 100.0 90.1 80.8 106.1 72.2 50.2 94.3 85.2 53.4 76.2 78.5 78.7

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.18

Final consumption expenditure plus discrepancy per capita

Current prices ($)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

455 367 382 .. 414 781 287 224 579 .. 382 .. 413 479 610 953 .. .. .. 2,468 360 387 .. 134 366 501 422 476 177 244 484 1,054 316 1,320 365 .. 215 .. 633 1,667 345 106 1,818 494 888 .. 327 99 543 790 848 1,281 .. 432 .. 819 1,041 527

497 361 373 698 378 1,574 315 213 726 659 510 311 589 233 893 765 424 .. 226 4,046 293 376 360 233 299 492 .. 258 174 261 486 1,929 192 1,359 315 .. 341 .. 771 4,196 149 156 2,444 557 1,224 165 379 242 349 693 1,112 1,788 888 636 4,857 835 1,205 610

595 371 380 928 517 3,229 364 137 749 1,942 321 352 628 112 645 698 1,877 347 126 2,426 358 389 336 .. 414 885 203 230 211 349 580 4,036 260 2,690 234 .. 229 .. 699 7,234 222 .. 3,860 586 2,079 285 384 259 389 473 1,310 1,373 803 914 3,385 1,435 2,487 708

655 408 417 1,005 523 3,112 366 173 774 1,907 336 352 676 118 864 752 2,208 316 161 2,633 402 477 266 .. 476 994 237 268 227 359 647 4,219 296 2,799 227 .. 275 .. 688 10,330 231 .. 4,319 721 2,263 305 400 287 490 492 1,404 1,404 801 1,019 3,961 1,504 2,534 772

717 468 479 1,077 560 3,553 389 189 812 2,073 356 385 701 150 1,275 762 2,128 308 197 3,007 385 864 264 .. 571 993 342 272 233 368 721 4,402 304 2,993 .. .. 324 .. 749 10,510 247 .. 4,525 944 2,592 307 403 312 625 475 1,509 1,523 820 1,179 3,178 1,626 2,662 839

810 557 570 1,934 642 3,900 .. 202 918 2,424 402 538 791 150 1,197 907 2,562 325 241 3,636 494 1,043 406 .. 668 1,075 344 346 218 444 852 5,093 345 3,165 .. .. 372 .. 902 12,190 285 .. 4,843 1,068 2,664 357 455 358 668 430 1,773 1,701 834 1,420 4,338 1,859 2,973 959

881 675 691 2,739 743 4,679 .. 238 .. 2,781 474 570 913 171 1,655 1,013 7,478 .. 334 4,112 642 1,202 355 .. 753 1,046 409 433 278 .. 952 6,526 436 3,143 .. .. 438 .. 1,091 10,429 343 .. 4,540 1,310 2,876 411 543 390 891 431 2,118 2,149 .. 1,730 4,876 2,136 3,350 1,076

893 684 700 3,470 683 4,568 .. 243 .. 3,036 446 611 906 148 1,394 960 7,406 .. 377 4,101 568 983 356 .. 721 1,129 357 384 298 .. 772 6,100 414 3,412 .. .. 488 .. 957 8,243 316 .. 4,668 1,335 2,883 407 522 426 749 607 2,248 1,930 .. 2,073 .. 2,165 3,258 1,107

990 698 714 2,938 650 5,755 .. 272 .. 2,734 .. 680 .. .. 1,457 941 8,587 .. 356 4,221 593 1,121 399 .. 724 1,426 371 .. 311 .. 881 6,635 370 3,566 .. .. 523 .. 923 .. 315 .. 5,884 1,512 3,584 423 515 446 858 754 2,449 2,250 .. 2,318 .. 2,126 3,310 1,217

Annual average 1980–89 1990–99 2000–10

455 340 352 598 330 816 245 216 663 501 359 224 393 299 693 679 .. .. 200 2,564 278 353 348 171 299 453 436 320 150 203 451 1,103 275 1,437 278 .. 272 .. 574 2,170 255 138 2,094 670 754 .. 287 231 418 703 957 1,697 .. 529 .. 641 961 547

477 312 321 484 347 1,803 226 173 636 1,084 352 237 500 158 628 642 418 239 159 2,716 631 363 386 214 314 557 .. 245 183 237 532 2,484 187 1,662 219 .. 280 .. 602 5,142 192 156 2,782 415 1,490 197 334 221 346 544 1,150 1,216 830 832 5,175 987 1,527 597

658 457 468 1,483 530 3,409 300 180 682 2,061 338 400 639 122 955 742 3,210 282 203 2,925 481 655 328 184 530 859 256 295 225 307 666 4,459 297 2,730 196 .. 314 .. 728 8,404 253 .. 3,830 840 2,190 323 397 307 544 502 1,618 1,509 790 1,385 3,678 1,561 2,564 813

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.19

Gross ﬁxed capital formation

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

22.6 .. 18.9 .. .. 34.5 14.1 13.9 20.0 .. 7.0 .. 28.5 8.8 35.8 24.4 .. .. .. 26.7 .. 6.1 .. 28.2 18.3 35.6 .. 14.4 22.2 15.5 21.4 23.2 7.6 27.2 25.5 .. 12.2 .. 14.6 36.5 14.9 43.1 25.9 10.8 35.0 .. 28.2 .. 18.2 14.1 26.8 33.8 .. 24.6 .. 22.2 28.3 24.5

18.3 17.5 17.5 11.1 13.4 32.4 17.7 15.2 17.3 25.3 11.4 4.8 11.9 12.8 17.2 8.5 17.4 .. 12.9 21.5 22.3 14.4 22.9 29.9 20.7 57.0 .. 14.8 20.1 23.0 20.0 30.6 22.1 21.2 11.4 .. 14.7 .. 18.0 23.0 9.6 14.9 19.1 10.4 14.6 25.8 25.3 12.7 13.5 18.2 24.5 27.0 14.2 26.9 13.9 24.0 24.4 21.1

17.3 18.5 18.5 9.1 17.5 24.8 19.3 10.3 18.3 38.9 6.2 22.7 9.4 12.8 21.9 9.9 40.5 18.9 25.5 24.4 24.2 28.4 19.8 .. 16.3 26.5 6.3 23.4 16.2 21.0 44.4 21.6 18.7 18.6 15.8 .. 15.0 .. 22.7 12.7 10.5 .. 16.0 17.2 15.3 22.2 15.7 19.9 23.0 5.1 19.7 24.1 21.5 16.4 13.9 26.3 22.1 18.4

18.2 19.5 19.5 8.9 18.9 24.5 19.3 8.7 17.7 35.8 8.9 16.7 9.3 14.0 19.7 9.7 37.6 19.7 23.0 21.3 21.6 29.0 18.6 .. 18.7 21.1 13.3 22.2 20.2 22.7 59.0 21.4 18.7 18.6 18.5 .. 15.8 .. 29.6 23.8 17.0 .. 16.8 24.1 15.0 24.7 15.8 22.2 22.4 2.0 20.3 22.3 19.0 17.9 15.8 27.5 21.3 19.2

19.0 19.5 19.5 15.4 18.2 21.6 20.5 14.2 16.7 38.7 9.2 13.2 9.6 12.6 21.3 9.3 31.4 13.3 24.2 25.9 23.8 21.6 16.6 .. 19.1 21.5 24.4 25.3 22.7 22.9 27.4 24.3 17.7 21.6 .. .. 16.0 .. 28.2 24.8 15.2 .. 18.3 25.1 12.8 27.2 16.2 20.9 22.5 2.2 21.6 22.9 29.6 18.7 20.7 28.1 22.6 20.2

20.3 20.5 20.5 13.5 21.4 23.9 .. 18.2 17.1 46.4 9.0 17.0 11.2 19.5 21.4 8.7 33.3 11.0 23.5 25.9 18.3 20.1 13.9 .. 19.4 22.0 27.1 32.4 24.0 22.4 27.6 25.1 16.1 23.7 .. .. 18.1 .. 30.9 29.7 13.2 .. 20.2 26.5 12.3 29.2 14.4 21.9 23.8 5.1 24.3 26.0 37.5 20.9 25.0 31.3 23.0 22.1

21.8 20.9 20.9 16.2 20.7 22.8 .. 18.7 .. 46.2 11.6 23.9 14.3 23.8 18.0 10.1 28.4 .. 19.9 24.4 14.0 21.5 15.6 .. 19.4 28.2 34.2 40.4 23.3 .. 27.3 24.6 15.7 26.1 .. .. 22.7 .. 30.2 24.5 14.7 .. 22.7 22.7 11.1 29.4 14.0 22.8 22.2 3.3 25.6 26.4 .. 22.3 27.9 33.0 23.5 23.6

22.1 21.6 21.6 15.2 25.3 28.8 .. 18.8 .. 39.1 10.8 31.6 12.4 28.7 22.2 11.4 60.1 .. 22.5 27.0 18.0 19.7 21.3 .. 19.1 28.0 24.6 33.0 21.8 .. 24.6 26.4 20.7 25.5 .. .. 21.6 .. 27.9 22.0 15.4 .. 22.7 21.8 11.0 28.4 16.0 23.9 22.2 2.4 26.2 38.3 .. 18.9 .. 30.9 24.2 23.9

20.4 .. 21.3 12.6 26.1 27.1 .. 18.0 .. 46.8 .. 31.8 .. .. 20.3 13.8 .. .. 21.5 26.6 19.4 21.8 20.0 .. 19.9 28.5 34.5 .. 21.7 .. 24.5 24.9 24.7 25.7 .. .. 21.0 .. 29.0 .. 15.8 .. 19.6 20.4 11.1 28.4 18.9 23.3 22.4 5.7 .. .. .. 18.6 .. 30.7 24.3 21.0

Annual average 1980–89 1990–99 2000–10

20.1 16.6 17.1 14.2 14.8 29.0 17.4 16.1 21.1 29.8 10.2 4.5 24.3 11.4 32.5 15.8 .. .. 15.7 33.8 19.0 7.9 16.4 32.0 18.8 40.3 .. 10.8 15.8 17.2 27.1 21.2 12.2 18.6 14.2 .. 14.4 .. 17.4 25.6 11.4 26.9 23.1 12.4 25.4 .. 19.0 9.3 12.5 16.0 27.9 31.9 .. 27.8 .. 23.1 27.5 23.5

17.1 17.9 17.9 23.2 15.7 27.2 21.2 9.0 14.5 29.6 11.2 11.0 14.7 8.0 24.9 11.4 59.5 26.1 16.5 25.5 10.6 19.7 20.0 25.9 17.6 65.4 .. 12.4 15.2 22.5 20.2 26.9 20.7 21.0 9.0 .. 14.5 .. 19.9 29.2 7.2 14.9 16.3 10.6 16.7 21.5 15.6 15.9 12.4 19.0 21.3 26.2 11.1 20.4 12.7 22.2 25.0 19.0

18.7 19.3 19.4 13.2 20.2 24.9 18.2 11.7 18.0 38.3 8.9 29.3 10.8 14.1 21.8 10.4 43.9 22.3 22.5 24.7 15.7 23.1 17.6 12.0 18.2 29.5 17.2 24.2 19.0 23.4 28.1 23.5 21.4 21.5 14.2 .. 18.5 .. 26.3 23.9 12.7 .. 17.9 18.9 15.4 23.5 15.5 21.3 21.5 6.7 21.7 25.2 18.6 18.6 16.9 28.1 23.6 20.1

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.20

Gross general government ﬁxed capital formation

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

6.6 .. .. .. .. 0.0 .. 12.8 4.5 .. 3.7 .. 23.2 5.1 .. 11.4 .. .. .. 5.3 .. .. .. .. 0.0 9.9 .. .. 17.5 .. 21.4 8.4 7.6 15.7 20.4 .. 12.2 .. 4.7 .. 5.3 .. 6.4 6.9 11.9 .. 20.2 .. .. 1.8 .. 11.0 .. .. .. .. 15.0 ..

5.6 7.2 7.2 .. 7.4 8.6 9.7 12.5 5.5 11.3 4.7 .. 5.2 4.0 5.6 3.6 10.5 .. 4.0 3.9 7.4 7.5 9.7 27.4 9.7 26.2 .. 7.9 7.7 10.5 6.2 11.4 12.0 8.2 7.4 .. 5.9 .. 4.1 8.2 3.9 .. 3.9 .. 4.5 10.5 7.3 6.2 6.2 3.4 10.8 8.2 9.1 14.7 .. 4.8 8.7 7.8

5.4 6.3 6.3 4.9 5.4 8.3 7.2 7.6 2.6 10.8 2.0 7.8 4.4 2.8 6.5 2.8 13.1 14.4 15.8 4.2 10.0 12.4 3.7 .. 4.3 7.7 2.1 10.0 9.1 7.5 8.9 6.6 10.7 6.3 5.1 .. 8.9 .. 6.7 3.1 4.5 .. 4.3 5.0 8.1 5.7 1.6 4.9 8.7 5.1 8.4 10.6 7.7 8.8 12.3 3.8 3.5 6.7

5.2 6.1 6.1 5.5 6.7 7.2 7.3 4.7 2.5 12.9 4.0 7.8 4.5 3.7 6.3 2.7 10.3 17.9 14.7 4.2 8.0 12.0 2.8 .. 2.5 4.3 1.1 8.7 7.2 7.7 6.8 6.3 8.6 6.4 6.3 .. 8.7 .. 10.0 4.4 5.7 .. 4.3 5.9 7.9 6.0 2.8 5.0 7.0 2.0 8.9 10.8 9.3 9.3 14.1 3.7 3.0 6.9

5.8 6.5 6.5 13.0 4.6 6.2 7.9 6.2 2.4 12.8 3.7 8.1 5.0 3.0 9.5 3.1 15.1 12.2 16.7 4.8 8.4 8.8 2.6 .. 3.1 5.5 1.3 10.6 7.8 8.6 5.9 7.7 11.8 6.8 .. .. 7.5 .. 9.7 7.7 5.1 .. 5.0 6.7 6.8 5.9 3.4 4.6 4.1 2.2 8.9 12.0 7.5 8.0 16.7 3.6 3.1 7.2

6.5 6.8 6.8 11.5 7.5 8.6 .. 9.2 2.4 11.4 2.7 7.3 6.2 8.8 10.4 2.6 16.9 9.8 16.8 4.5 4.7 8.5 2.3 .. 3.9 4.7 2.2 7.0 14.8 8.4 6.7 5.4 11.7 2.9 .. .. 8.7 .. 11.2 4.5 3.5 .. 6.1 9.5 6.5 7.2 2.0 4.9 4.1 1.3 10.2 16.5 12.2 7.8 19.8 3.6 2.9 8.2

7.6 7.2 7.2 14.1 5.8 12.5 .. 9.4 .. 13.8 4.5 7.9 9.3 12.6 8.9 3.1 16.9 .. 14.0 4.6 3.7 9.4 3.5 .. 4.4 9.0 3.0 7.1 9.4 .. 6.5 4.1 11.5 3.5 .. .. 10.9 .. 10.0 3.2 6.2 .. 8.0 6.5 5.8 8.2 3.2 4.5 5.1 0.3 10.6 16.1 .. 7.9 22.0 4.6 2.8 9.0

8.6 8.0 8.0 12.4 9.7 15.8 .. 9.1 .. 14.0 3.8 10.5 4.7 22.9 10.8 3.0 43.0 .. 16.6 6.0 7.4 5.2 4.6 .. 5.3 11.5 3.5 3.2 6.9 .. 7.1 6.6 12.9 5.5 .. .. 11.1 .. 10.1 3.0 7.8 .. 9.2 5.5 5.8 8.6 5.5 6.2 4.4 0.8 11.1 24.0 .. 8.0 .. 6.0 3.5 9.7

7.6 .. 7.5 9.7 10.0 13.2 .. 8.0 .. 18.8 .. 9.1 .. .. 10.1 4.6 .. .. 16.5 9.2 8.2 3.9 4.3 .. 0.0 12.7 5.7 .. 10.1 .. 7.9 6.1 13.6 6.5 .. .. 11.5 .. 10.8 .. 7.7 .. 7.7 7.3 5.8 8.3 7.9 5.6 4.1 5.6 12.0 27.7 .. 6.4 .. 5.7 .. 9.4

Annual average 1980–89 1990–99 2000–10

6.1 6.6 6.3 .. 9.1 9.7 10.4 13.8 6.9 21.4 5.5 3.8 18.7 4.4 11.1 7.1 .. .. 4.9 6.7 10.4 6.3 7.5 33.3 0.8 17.2 .. 6.9 9.5 10.2 17.6 7.4 9.5 10.7 11.2 .. 12.1 .. 3.7 12.0 4.0 .. 5.7 4.3 8.0 .. 11.2 4.4 .. 2.9 13.0 13.8 .. 16.9 .. 7.1 14.1 8.9

4.7 6.5 6.5 7.8 7.5 11.7 10.5 9.3 2.9 20.2 6.2 7.4 7.0 1.7 6.4 5.6 6.9 17.6 6.6 6.5 7.4 11.1 6.1 20.2 7.1 18.7 .. 6.9 9.2 10.1 3.4 9.2 12.1 8.2 5.6 .. 7.2 .. 4.5 9.9 3.8 .. 2.8 0.7 5.4 6.0 3.7 5.6 6.8 3.0 10.4 7.2 6.1 14.5 .. 4.2 9.3 7.1

5.9 6.4 6.5 8.9 7.1 10.4 7.0 6.4 2.3 12.7 3.6 9.1 5.3 5.8 8.6 3.0 14.6 17.1 14.8 4.8 7.2 9.1 3.8 10.9 3.7 8.9 4.2 7.3 8.9 7.7 7.3 6.6 11.5 5.8 7.0 .. 8.2 .. 8.2 7.1 5.4 .. 5.3 5.2 6.4 6.0 3.1 5.3 7.5 2.2 9.2 14.1 6.6 8.4 14.9 4.4 3.5 7.4

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.21

Private sector ﬁxed capital formation

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

16.3 .. .. .. .. 34.5 .. 1.1 15.6 .. 3.2 .. 5.3 3.7 .. 13.0 .. .. .. 21.4 .. .. .. .. 8.2 25.7 .. .. 4.8 .. 0.0 14.9 0.0 11.4 5.1 .. .. .. 9.9 .. 9.5 .. 19.5 3.9 23.1 .. 8.0 .. .. 12.3 .. 22.8 .. .. .. 16.7 13.3 ..

13.0 10.8 10.8 1.7 6.0 23.8 8.0 2.7 11.9 14.0 6.7 .. 6.7 8.9 11.6 4.9 6.9 .. 8.9 17.6 14.9 6.9 8.8 8.4 10.9 30.8 .. 6.9 12.4 12.4 13.8 19.2 10.1 13.0 4.0 .. 8.7 .. 13.9 14.8 5.7 .. 15.3 .. 10.1 15.3 18.0 6.5 7.3 14.8 15.4 18.8 5.1 12.3 .. 19.2 15.6 14.0

12.0 12.3 12.3 4.2 12.1 16.5 .. 2.7 15.7 28.2 4.1 14.9 5.0 10.0 15.4 7.1 27.4 4.5 9.7 20.2 14.2 16.0 16.1 .. 12.0 18.7 4.2 13.4 7.1 13.5 35.5 15.0 8.0 15.7 10.7 .. 6.2 .. 16.0 9.7 5.9 .. 11.7 12.2 7.2 16.5 14.1 15.0 14.3 0.0 11.3 13.6 13.8 7.7 1.6 22.4 18.6 11.7

13.0 13.5 13.5 3.4 12.2 17.3 .. 4.0 15.2 23.0 4.9 8.9 4.8 10.4 13.5 7.0 27.4 1.9 8.3 17.1 13.6 17.0 15.8 .. 16.2 16.8 12.2 13.5 13.0 15.0 52.1 15.1 10.1 16.2 12.2 .. 7.0 .. 19.7 19.4 11.3 .. 12.5 18.2 7.1 18.7 13.1 17.2 15.5 0.0 11.4 11.5 9.7 8.6 1.7 23.8 18.3 12.3

13.2 13.1 13.1 2.4 13.6 15.4 .. 8.0 14.3 25.9 5.6 5.1 4.7 9.6 11.7 6.3 16.2 1.2 7.6 21.1 15.5 12.8 14.0 .. 16.0 16.0 23.1 14.8 15.0 14.3 21.4 16.6 5.8 18.4 .. .. 8.5 .. 18.5 17.2 10.1 .. 13.4 18.4 6.1 21.3 12.8 16.3 18.5 0.0 12.7 11.0 22.0 10.7 4.0 24.5 19.5 13.0

13.8 13.5 13.5 2.0 13.9 15.3 .. 9.0 14.7 35.0 6.3 9.7 5.0 10.7 11.1 6.1 16.4 1.3 6.7 21.5 13.6 11.6 11.6 .. 15.5 17.3 24.9 25.4 9.2 14.0 20.8 19.7 4.4 16.2 .. .. 9.3 .. 19.7 25.2 9.7 .. 14.1 17.0 5.8 22.1 12.4 16.9 19.8 3.8 14.1 9.5 25.2 13.1 5.2 27.6 20.2 13.9

14.1 13.5 13.5 2.1 14.9 10.3 .. 9.3 12.5 32.4 7.1 16.0 5.0 11.3 9.2 7.1 11.5 .. 5.9 19.8 10.3 12.1 12.1 .. 15.0 19.3 31.2 33.3 13.9 .. 20.8 20.5 4.1 14.9 .. .. 11.8 .. 20.2 21.3 8.6 .. 14.8 16.2 5.2 21.2 10.8 18.3 17.1 3.0 15.0 10.2 .. 14.4 5.9 28.4 20.7 14.5

13.4 13.4 13.4 2.8 15.6 13.1 .. 9.8 12.4 25.0 7.0 21.0 7.7 5.8 11.4 8.4 17.2 .. 5.9 21.0 10.6 14.6 16.7 .. 13.8 16.5 21.1 29.8 14.9 .. 17.5 19.8 7.8 16.1 .. .. 10.6 .. 17.8 19.0 7.6 .. 13.5 16.3 5.2 19.9 10.5 17.7 17.8 1.7 .. .. .. 10.9 .. 24.9 20.7 14.1

12.8 13.7 13.7 3.0 16.1 14.0 .. 10.0 12.6 28.1 .. 22.7 .. .. 10.2 9.2 .. .. 5.0 17.4 11.2 17.9 15.7 .. 19.9 15.8 28.8 .. 16.9 .. 16.6 18.8 11.0 16.3 .. .. 9.5 .. 18.2 .. 8.0 .. 11.9 13.1 5.3 20.1 11.0 17.7 18.3 0.1 .. .. .. 12.2 .. 24.9 .. 13.7

Annual average 1980–89 1990–99 2000–10

14.4 9.8 9.8 9.3 4.5 19.4 8.8 2.3 14.2 8.4 4.7 0.6 5.5 7.1 11.4 8.7 .. .. 12.8 27.2 8.6 3.8 8.9 10.0 10.7 23.1 .. 3.6 6.3 9.9 9.5 13.8 2.7 7.8 3.0 .. 7.8 .. 13.7 10.1 7.3 .. 17.4 8.9 17.3 .. 7.8 5.4 4.9 13.1 12.8 18.1 .. 9.3 .. 16.1 13.5 13.3

12.5 11.5 11.5 16.5 8.3 15.5 10.8 -0.3 11.7 9.4 5.0 4.3 7.7 6.3 18.5 6.2 52.6 8.6 9.9 18.9 14.9 8.6 11.7 7.7 9.8 46.8 .. 5.5 6.0 12.4 16.8 17.7 8.6 12.9 3.4 .. 7.2 .. 15.4 19.3 3.3 .. 13.5 9.9 11.3 15.6 11.8 10.3 5.7 16.0 12.2 19.0 5.8 5.9 .. 18.0 15.7 12.3

12.7 12.8 12.8 4.3 13.2 14.5 10.4 5.3 14.8 25.6 5.3 20.2 5.4 8.3 13.2 7.5 29.2 5.1 7.7 19.9 12.7 14.1 13.8 1.1 12.6 20.6 13.0 16.9 10.0 15.7 20.8 16.9 9.9 15.5 7.2 .. 10.2 .. 18.2 16.8 7.3 .. 12.6 13.8 9.1 17.5 12.4 16.0 14.0 4.5 12.7 12.3 11.9 10.2 3.2 23.7 20.0 12.9

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.22

External trade balance (exports minus imports)

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

Annual average 1980–89 1990–99 2000–10

1.1 -4.8 -8.7 .. -21.5 -13.4 -22.3 -14.5 0.8 -49.9 -15.9 -11.9 -43.2 0.1 -0.1 -6.2 .. .. .. 33.1 -20.9 -0.7 .. -29.2 -6.4 -89.1 -0.1 -16.4 -14.0 -14.4 -29.8 -10.2 -16.5 7.8 -13.6 10.2 -12.0 .. -14.5 -11.2 -15.4 -55.3 8.0 -12.6 -39.4 .. -5.3 -6.6 -4.0 -3.2 -7.2 4.0 .. -12.4 .. -9.4 -5.4 -2.3

1.0 -2.3 -6.1 18.0 -12.0 5.3 -13.5 -19.9 2.9 0.0 -12.9 -14.4 -22.9 0.3 7.9 4.6 -37.4 .. -3.3 15.2 -11.7 -9.0 -2.4 -27.1 -5.6 -105.2 .. -11.4 -9.6 -16.6 -15.1 -7.2 -27.9 -15.5 -6.9 14.6 -8.5 .. -6.8 -4.3 -1.3 -28.0 5.5 -3.0 -9.9 -24.8 -11.9 -12.1 -0.7 0.1 -6.0 -1.5 -24.6 -12.7 8.6 -5.4 -7.1 -2.0

-1.3 -2.0 -5.4 16.0 -12.7 7.3 -13.5 -18.0 -0.4 -37.6 -6.2 0.3 -17.9 -8.8 29.7 9.2 35.1 -54.0 -16.7 30.2 -14.5 -21.1 -2.3 .. -6.3 -73.4 -40.9 -14.9 -18.2 -12.4 -41.0 -2.4 -10.9 -2.3 -10.0 12.9 -13.6 .. -12.9 2.0 -10.9 .. -0.3 -3.8 -2.5 -6.4 -19.3 -10.1 -4.4 -7.1 5.6 14.4 -17.2 -1.4 31.1 -5.0 -2.5 1.6

-1.3 -1.9 -5.8 32.4 -12.7 16.8 -15.5 -20.7 -1.0 -28.8 -8.8 17.2 -21.6 -8.2 29.7 7.5 43.8 -48.8 -20.4 37.0 -16.5 -25.3 -1.3 .. -7.5 -72.0 -52.4 -17.3 -28.1 -11.7 -51.8 -6.0 -12.2 0.1 -9.2 15.5 -13.8 .. -15.6 -20.8 -12.9 .. -0.5 -9.9 -4.1 -8.9 -18.6 -10.6 -2.1 -9.0 8.1 23.4 -10.3 -2.3 38.1 -5.6 -0.4 2.7

-1.9 -1.6 -5.3 40.8 -11.3 16.4 -15.1 -28.6 2.1 -27.6 -7.9 22.0 -24.4 -13.2 18.5 10.3 53.7 -31.5 -22.7 30.1 -13.1 -15.5 -3.3 .. -10.7 -65.5 -111.9 -16.0 -24.5 -8.1 -4.2 -11.3 -8.9 -1.7 .. 15.1 -14.2 .. -17.5 -17.1 -7.6 .. -2.5 -10.9 -2.4 -13.1 -17.9 -13.1 8.4 -10.9 10.1 27.1 -17.4 -1.6 45.8 -5.5 -1.9 3.2

-2.5 -2.2 -6.1 30.4 -15.3 12.3 .. -36.1 0.8 -35.0 -7.5 2.5 -26.6 -10.7 25.0 5.9 51.6 -29.4 -19.3 29.4 -12.6 -16.3 -4.6 .. -10.9 -65.9 -89.0 -21.7 -12.6 -9.4 -18.0 -9.3 -9.8 -1.3 .. 15.1 -14.6 .. -22.3 -31.5 -7.0 .. -2.9 -3.8 -1.3 -16.9 -16.6 -13.3 6.4 -8.6 6.5 23.3 -20.1 -4.6 38.2 -9.1 -1.9 1.3

-3.7 -4.2 -8.1 25.1 -13.6 3.7 .. -35.3 -3.0 -33.0 -12.9 2.6 -34.4 -15.2 28.2 7.7 47.3 -21.7 -19.4 34.6 -15.3 -19.5 -5.3 .. -14.1 -64.7 -110.3 -30.4 -21.8 .. -23.0 -13.2 -14.1 -6.8 .. 12.3 -15.8 .. -26.3 -18.7 -13.1 .. -3.0 0.8 -9.3 -13.6 -16.4 -7.7 2.4 -26.6 5.6 23.4 .. -5.6 39.9 -13.4 -3.0 0.3

-4.3 -6.8 -10.4 -0.5 -14.5 -10.3 .. -28.2 -4.8 -32.3 -8.0 -27.0 -33.5 -13.4 20.2 8.1 12.2 -15.9 -18.3 17.6 -15.1 -13.0 -4.7 .. -12.5 -69.8 -80.4 -24.0 -15.9 .. -16.7 -9.4 -18.5 -13.7 .. 8.2 -17.4 .. -18.6 -7.5 -13.1 .. -0.9 -5.8 -13.0 -11.9 -15.6 -11.4 3.5 -31.9 -4.3 4.5 .. -6.6 .. -11.0 -2.9 -4.3

-2.7 -4.7 -7.5 19.4 -13.8 -7.0 .. -30.4 -3.1 -28.5 .. -22.0 .. -12.9 30.4 4.6 .. .. -21.1 25.3 -17.0 -11.8 -4.4 .. -10.3 -70.1 -84.4 .. -16.6 .. -11.6 -11.4 -18.7 1.2 .. 6.7 -19.8 .. -18.2 .. -12.4 .. -0.2 0.9 -13.4 -11.7 -16.5 -10.2 9.1 -29.7 -2.3 9.3 .. -4.8 .. -9.9 -5.3 -2.6

-0.5 -4.8 -6.2 9.1 -17.5 5.3 -19.6 -13.5 0.4 -32.0 -12.1 -13.5 -33.3 -0.8 -0.5 3.2 -28.6 .. -5.3 9.7 -13.2 -3.1 0.3 -32.9 -4.9 -110.0 3.2 -7.7 -6.7 -17.6 -24.4 -3.3 -18.4 -7.6 -8.0 1.1 -10.3 .. -12.1 -2.3 -3.1 -35.1 5.1 -8.3 -23.5 .. -7.2 -6.2 -2.1 -0.8 -8.9 -2.5 .. -13.2 .. -7.4 -6.1 -3.8

-1.5 -4.5 -6.5 2.2 -12.5 9.8 -13.5 -14.4 3.7 -22.6 -7.8 -13.6 -23.0 1.2 2.9 6.5 -45.8 -55.8 -6.8 17.7 -6.7 -12.4 -3.0 -24.5 -3.7 -101.9 -39.6 -8.2 -14.3 -14.9 -10.2 -4.1 -23.6 -10.0 -6.2 4.1 -19.9 .. -7.2 -8.6 -4.5 .. 2.8 -6.7 -15.2 -19.0 -9.6 -11.7 -5.6 -2.4 -3.1 1.6 -17.5 -6.7 3.6 -4.9 -4.2 -2.2

-1.7 -3.1 -6.2 19.1 -13.3 7.5 -14.2 -22.5 -0.7 -32.8 -6.9 -17.5 -21.8 -8.7 25.0 8.8 33.4 -44.2 -17.2 28.2 -11.3 -17.2 -3.1 -25.2 -9.4 -66.7 -46.6 -15.1 -16.9 -11.2 -21.6 -4.8 -15.4 -4.2 -8.8 10.9 -16.2 .. -15.7 -10.8 -13.9 .. 0.3 -4.8 -7.2 -9.1 -16.1 -11.6 -3.1 -11.7 3.6 16.7 -12.9 -4.1 29.1 -6.6 -3.0 0.6

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.23

Exports of goods and services, nominal

Current prices ($ millions) 1980

SUB-SAHARAN AFRICA 82,272 Excluding South Africa 53,753 Excl. S. Africa & Nigeria 33,576 Angola .. Benin 222 Botswana 563 Burkina Faso 173 Burundi 81 Cameroon 1,880 Cape Verde 24 Central African Republic 201 Chad 175 Comoros 11 Congo, Dem. Rep. 2,372 Congo, Rep. 1,024 Côte d'Ivoire 3,561 Equatorial Guinea .. Eritrea .. Ethiopia .. Gabon 2,770 Gambia, The 103 Ghana 376 Guinea .. Guinea-Bissau 14 Kenya 2,145 Lesotho 91 Liberia 614 Madagascar 539 Malawi 307 Mali 263 Mauritania 261 Mauritius 579 Mozambique 383 Namibia 1,712 Niger 617 Nigeria 18,859 Rwanda 168 São Tomé and Príncipe .. Senegal 837 Seychelles 100 Sierra Leone 252 Somalia 200 South Africa 28,555 Sudan 806 Swaziland 405 Tanzania .. Togo 580 Uganda 242 Zambia 1,608 Zimbabwe 1,561 NORTH AFRICA 37,700 Algeria 14,541 Djibouti .. Egypt, Arab Rep. 6,992 Libya .. Morocco 3,273 Tunisia 3,518 AFRICA 121,303

Annual average 1980–89 1990–99 2000–10

1990

2004

2005

2006

2007

2008

2009

2010a

79,567 52,145 40,208 3,993 264 2,087 340 89 2,251 0 220 234 36 2,759 1,502 3,421 42 .. 672 2,740 190 993 829 24 2,207 98 .. 512 447 415 465 1,724 201 1,220 372 12,366 145 .. 1,453 230 146 90 27,149 499 658 538 545 312 1,180 2,009 47,088 14,546 244 8,647 11,468 6,830 5,353 126,772

185,099 127,221 88,566 13,780 539 4,444 549 64 3,061 296 168 2,252 55 1,976 3,744 7,517 4,724 64 1,498 4,465 198 3,487 862 .. 4,283 696 124 1,424 655 1,237 470 3,450 1,759 2,630 491 38,609 232 .. 2,123 685 247 .. 57,890 3,822 2,056 2,520 747 1,008 2,079 2,001 107,580 34,067 246 22,258 21,117 16,726 13,166 292,638

233,717 166,090 113,791 24,286 577 5,256 542 92 3,393 367 170 3,234 55 2,450 5,123 8,354 7,183 68 1,858 5,610 204 3,907 994 .. 5,342 669 129 1,422 663 1,359 671 3,761 2,087 2,937 512 52,238 295 .. 2,344 717 292 .. 67,647 4,992 2,250 2,945 847 1,310 2,482 1,931 139,233 48,761 288 27,214 29,230 19,234 14,505 372,898

278,472 200,187 137,155 33,346 538 5,292 665 93 4,131 500 207 3,852 57 2,621 6,507 9,144 8,332 84 2,105 5,912 222 5,136 1,108 .. 6,101 765 186 1,640 705 1,884 1,454 4,009 2,722 3,180 .. 62,959 344 .. 2,401 860 355 .. 78,318 6,013 2,259 3,233 841 1,524 4,120 1,957 167,999 56,953 307 32,191 40,275 22,449 15,823 446,412

323,452 233,953 165,863 44,707 900 5,964 .. 93 4,563 570 254 3,845 68 2,707 6,592 9,466 10,298 86 2,489 7,203 231 6,041 1,267 .. 7,294 832 239 2,227 1,033 1,871 1,449 4,509 2,839 4,468 .. 68,061 410 .. 2,871 993 346 .. 89,549 9,288 2,311 4,079 957 1,993 4,802 2,000 198,536 63,297 484 39,469 48,510 26,892 19,883 521,931

397,178 299,421 213,004 64,243 1,019 5,662 .. 106 7,718 708 211 4,413 74 2,719 8,912 10,890 14,520 61 3,038 9,675 227 7,140 1,259 .. 8,411 915 292 2,498 1,206 .. 2,114 5,103 3,192 4,787 .. 86,396 680 .. 3,498 1,091 319 .. 98,005 12,974 1,793 5,208 1,123 3,506 5,267 1,831 254,602 79,123 .. 53,800 62,780 33,312 24,966 651,768

300,792 223,380 161,187 41,451 922 3,745 .. 98 5,895 570 290 2,879 79 1,908 6,756 9,722 8,549 84 3,381 6,143 229 7,609 1,671 .. 7,386 784 176 2,447 1,240 .. 1,521 4,323 2,398 4,301 .. 62,227 610 .. 3,117 912 296 .. 77,548 8,223 1,755 4,963 1,162 3,753 4,560 1,798 177,527 40,454 .. 47,164 .. 26,094 19,606 480,784

374,652 275,208 200,864 51,400 937 4,917 .. 124 6,502 640 .. 3,331 .. 3,412 10,221 9,316 .. .. 3,392 8,094 230 9,461 1,649 .. 8,861 955 247 .. 1,547 .. 2,241 5,098 2,421 4,738 .. 74,610 610 .. 3,186 .. 327 .. 99,399 13,242 2,027 5,975 1,185 4,087 7,142 3,608 197,350 49,939 .. 46,732 .. 29,965 21,569 578,332

64,895 38,474 30,911 2,613 214 999 189 111 2,240 18 181 153 22 2,016 1,092 3,142 32 .. 608 1,964 108 554 660 15 1,805 67 519 414 295 255 387 807 215 1,139 420 7,725 173 .. 989 123 187 119 26,088 841 394 .. 464 371 1,060 1,530 34,578 12,221 .. 6,654 .. 3,790 3,312 100,096

87,503 55,756 43,527 4,265 327 2,378 286 89 2,198 62 185 254 40 1,595 1,393 4,129 160 132 715 2,728 195 1,684 798 32 2,594 187 43 673 465 514 556 2,257 373 1,543 325 12,563 107 .. 1,347 298 155 90 31,523 579 886 949 441 500 1,099 2,467 49,081 12,420 210 12,435 8,527 8,363 7,126 136,621

234,335 168,508 119,586 27,851 636 4,314 417 78 4,058 402 197 2,292 55 2,026 5,263 7,734 6,160 77 1,986 5,398 201 4,849 1,091 62 5,478 645 204 1,613 834 1,262 1,036 3,845 1,961 3,224 403 48,935 342 .. 2,327 750 256 .. 65,869 6,070 1,798 3,283 820 1,812 3,149 2,175 139,197 41,927 276 30,567 27,469 20,236 15,249 374,308

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.24

Imports of goods and services, nominal

Current prices ($ millions) 1980

SUB-SAHARAN AFRICA 75,495 Excluding South Africa 53,607 Excl. S. Africa & Nigeria 40,487 Angola .. Benin 524 Botswana 705 Burkina Faso 603 Burundi 214 Cameroon 1,829 Cape Verde 95 Central African Republic 327 Chad 298 Comoros 64 Congo, Dem. Rep. 2,354 Congo, Rep. 1,026 Côte d'Ivoire 4,190 Equatorial Guinea .. Eritrea .. Ethiopia .. Gabon 1,354 Gambia, The 153 Ghana 407 Guinea .. Guinea-Bissau 46 Kenya 2,608 Lesotho 475 Liberia 614 Madagascar 1,202 Malawi 480 Mali 520 Mauritania 473 Mauritius 695 Mozambique 965 Namibia 1,542 Niger 957 Nigeria 12,324 Rwanda 307 São Tomé and Príncipe .. Senegal 1,344 Seychelles 117 Sierra Leone 421 Somalia 534 South Africa 22,073 Sudan 1,763 Swaziland 619 Tanzania .. Togo 640 Uganda 324 Zambia 1,764 Zimbabwe 1,771 NORTH AFRICA 38,418 Algeria 12,847 Djibouti .. Egypt, Arab Rep. 9,822 Libya .. Morocco 5,033 Tunisia 3,987 AFRICA 115,086

1990

2004

2005

2006

2007

2008

74,234 53,382 45,113 2,147 486 1,888 758 314 1,931 0 411 485 93 2,731 1,282 2,927 92 .. 1,069 1,837 227 1,522 892 90 2,691 666 .. 864 629 817 619 1,915 888 1,584 545 8,203 364 .. 1,840 246 154 346 21,016 877 768 1,595 738 834 1,203 2,002 53,378 15,472 355 14,109 8,996 8,227 6,220 127,918

181,588 123,074 95,531 10,621 1,055 3,707 1,240 225 3,128 643 246 2,241 120 2,551 2,363 6,093 2,882 663 3,175 2,299 282 5,356 947 .. 5,290 1,602 315 2,072 1,134 1,841 1,221 3,601 2,381 2,780 795 27,282 517 .. 3,162 671 367 .. 58,544 4,650 2,117 3,343 1,121 1,807 2,319 2,413 89,716 21,808 361 23,330 10,723 19,547 13,947 271,113

220,707 151,942 116,769 15,144 1,120 3,534 1,390 323 3,562 647 289 2,324 138 3,036 3,318 7,132 3,583 603 4,366 2,400 309 6,617 1,031 .. 6,740 1,654 413 2,296 1,438 1,979 1,802 4,138 2,891 2,927 825 34,849 651 .. 3,700 908 452 .. 68,809 7,701 2,356 4,205 1,241 2,292 2,631 2,446 104,096 24,838 361 29,246 12,452 22,569 14,630 324,566

259,629 174,943 133,839 16,289 1,075 3,451 1,547 447 3,763 805 324 2,509 156 3,789 5,073 7,356 3,179 465 5,548 3,037 309 8,304 1,202 .. 8,514 1,702 862 2,525 1,468 2,360 1,581 4,744 3,351 3,317 .. 40,726 787 .. 4,037 1,034 463 .. 84,706 9,992 2,329 5,116 1,236 2,829 3,221 2,551 116,482 25,211 441 33,931 14,383 26,044 16,471 375,813

306,452 208,566 165,191 26,305 1,750 4,438 .. 569 4,395 1,035 381 3,670 192 3,780 4,493 8,302 3,809 474 6,262 3,805 336 10,057 1,460 .. 10,268 1,885 897 3,823 1,469 2,542 2,054 5,234 3,626 4,583 .. 43,039 955 .. 5,400 1,313 462 .. 97,946 11,042 2,350 6,915 1,375 3,581 4,068 2,455 153,178 31,633 654 45,443 21,074 33,750 20,624 459,396

383,052 277,279 215,685 43,122 1,928 5,159 .. 677 8,435 1,224 468 4,195 256 4,499 5,574 9,085 5,814 361 8,215 4,652 385 12,690 1,460 .. 12,719 1,968 1,230 5,357 2,092 .. 2,937 6,373 4,585 5,387 .. 61,006 1,423 .. 7,018 1,271 575 .. 106,345 12,537 2,074 8,035 1,643 4,618 4,909 3,005 200,067 39,171 .. 62,909 25,589 45,214 26,329 582,915

2009

330,040 250,911 202,261 41,829 1,875 4,934 .. 609 6,967 1,087 449 4,794 258 3,413 4,816 7,866 7,063 380 9,240 4,215 377 10,989 1,865 .. 11,196 1,978 883 4,484 1,991 .. 2,027 5,151 4,190 5,524 .. 48,373 1,524 .. 5,497 975 539 .. 79,982 11,381 2,140 7,511 1,656 5,557 4,118 3,662 173,941 34,282 .. 59,713 .. 36,084 20,872 503,682

2010a

378,688 278,780 216,094 35,421 1,839 5,956 .. 740 7,200 1,113 .. 5,213 .. 5,097 6,568 8,270 .. .. 9,653 4,754 409 13,265 1,859 .. 12,192 2,482 1,081 .. 2,387 .. 2,661 6,202 4,144 4,603 .. 61,486 1,721 .. 5,530 .. 564 .. 100,119 12,665 2,522 8,653 1,709 5,833 5,672 5,831 178,504 34,820 .. 57,200 .. 38,969 23,921 557,929

Annual average 1980–89 1990–99 2000–10

66,191 44,684 37,060 1,895 447 842 567 254 2,219 62 292 305 67 2,107 1,093 2,906 61 .. 1,093 1,586 137 709 658 67 2,154 496 491 668 384 536 576 853 773 1,284 583 7,362 354 .. 1,408 123 225 403 21,441 1,744 515 .. 542 619 1,148 1,598 40,555 13,875 .. 10,787 .. 4,955 3,834 107,439

90,234 62,348 51,051 4,032 579 1,916 640 234 1,816 175 282 469 93 1,537 1,309 3,406 270 482 1,330 1,823 242 2,509 905 91 3,071 926 180 942 716 882 692 2,400 1,001 1,844 448 11,214 405 .. 1,719 344 191 346 27,961 1,289 1,109 1,986 586 1,039 1,283 2,644 53,671 11,636 295 16,572 7,464 9,907 7,797 144,006

230,880 164,173 128,053 19,734 1,241 3,688 1,016 380 4,239 746 301 2,740 143 2,854 3,581 6,340 3,238 498 4,980 2,905 291 7,433 1,206 114 7,608 1,513 572 2,624 1,378 1,742 1,524 4,275 2,962 3,514 629 35,781 850 .. 3,879 850 426 .. 66,885 7,383 1,971 4,804 1,178 2,947 3,022 2,854 116,148 24,192 365 36,045 12,328 25,027 16,219 346,946

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.25

Exports of goods and services as a share of GDP

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

31.9 29.0 28.9 .. 15.8 53.1 9.0 8.8 27.9 17.1 25.2 16.9 8.7 16.5 60.0 35.0 .. .. .. 64.7 42.7 8.5 .. 12.7 29.5 21.0 71.8 13.3 24.8 14.7 36.8 51.0 10.9 78.9 24.6 29.4 14.4 .. 23.9 68.0 22.9 33.2 35.4 10.6 74.6 .. 51.1 19.4 41.4 23.4 30.2 34.3 .. 30.5 .. 17.4 40.2 31.2

26.4 27.9 24.4 38.9 14.3 55.1 11.0 7.9 20.2 0.0 14.8 13.5 14.3 29.5 53.7 31.7 32.2 .. 5.6 46.0 59.9 16.9 31.1 9.9 25.7 18.1 .. 16.6 23.8 17.2 45.6 65.0 8.2 51.9 15.0 43.4 5.6 .. 25.4 62.5 22.5 9.8 24.2 4.0 59.0 12.6 33.5 7.2 35.9 22.9 26.5 23.4 53.8 20.1 39.7 26.5 43.6 26.4

31.1 34.5 32.4 69.7 13.3 44.2 10.7 7.1 19.4 32.0 13.2 51.0 15.1 30.4 80.5 48.6 90.1 5.8 14.9 62.2 34.2 39.3 23.5 .. 26.6 56.4 26.5 32.6 25.0 25.4 25.7 54.0 30.9 39.8 16.1 44.0 11.1 .. 26.4 97.8 22.5 .. 26.4 17.6 84.9 19.7 38.6 12.7 38.2 34.5 36.8 40.1 37.0 28.2 63.3 29.4 42.2 33.5

32.7 36.5 34.2 86.0 13.5 51.3 9.9 8.2 20.5 37.8 12.6 61.0 14.1 34.1 84.2 51.1 87.4 6.2 15.1 64.7 32.1 36.5 33.8 .. 28.5 48.9 23.8 28.2 24.1 25.6 30.7 59.9 31.7 40.5 15.0 46.5 11.4 .. 26.9 78.2 23.6 .. 27.4 18.2 87.1 20.8 40.0 14.2 34.6 33.6 40.4 47.7 40.6 30.3 66.4 32.3 44.9 35.9

33.4 35.8 34.3 79.8 11.4 47.0 11.4 7.5 23.0 45.1 14.0 63.2 14.2 29.7 84.2 52.7 86.8 6.9 13.9 61.9 33.2 25.2 39.3 .. 27.1 53.5 30.8 29.7 22.6 32.1 47.8 61.6 38.4 39.9 .. 42.9 11.1 .. 25.6 84.3 24.9 .. 30.0 16.5 76.6 22.6 38.2 15.3 38.5 36.0 41.4 48.6 39.9 30.0 71.3 34.2 46.0 36.8

33.7 35.5 34.2 74.0 16.2 48.2 .. 7.0 22.1 42.8 15.0 54.8 14.7 27.0 78.5 47.8 81.9 6.5 12.7 62.3 27.7 24.5 30.1 .. 26.8 52.1 32.4 30.3 29.9 26.2 43.2 57.9 35.4 50.7 .. 41.0 11.0 .. 25.4 97.4 20.8 .. 31.3 20.0 75.7 24.2 37.9 16.7 41.6 37.8 41.4 46.6 57.1 30.3 67.6 35.8 51.1 36.9

36.1 36.4 35.1 76.3 15.2 42.1 .. 6.5 32.5 45.3 10.7 52.8 13.9 23.3 75.2 46.5 78.8 4.4 11.4 66.6 21.8 25.0 33.3 .. 27.6 56.3 34.4 26.6 29.6 .. 59.0 52.9 32.3 54.2 .. 41.7 14.4 .. 26.1 113.3 16.3 .. 35.8 22.4 59.4 25.1 35.5 24.3 36.0 41.5 43.0 46.3 .. 33.0 67.4 37.5 55.6 39.1

29.9 31.8 30.6 54.9 14.0 32.5 .. 5.4 26.6 35.6 14.7 40.6 14.7 17.0 70.4 42.2 69.9 4.5 10.6 56.1 23.2 29.3 40.1 .. 24.2 45.8 20.1 28.8 26.2 .. 50.2 49.0 24.8 48.2 .. 36.9 11.6 .. 24.4 108.4 16.0 .. 27.4 15.1 59.5 23.2 36.8 23.8 35.6 30.8 28.7 29.3 .. 25.0 .. 28.7 45.1 29.4

31.2 34.3 33.4 62.3 14.3 33.0 .. 6.1 28.9 38.6 .. 39.0 .. 26.0 85.1 40.6 .. .. 11.4 61.3 21.9 29.4 34.8 .. 27.5 43.8 25.0 .. 30.6 .. 62.0 52.5 26.3 42.6 .. 37.9 10.9 .. 24.8 .. 17.1 .. 27.3 19.8 54.8 26.1 37.3 23.8 44.1 48.3 28.4 30.8 .. 21.4 .. 33.0 48.8 30.1

Annual average 1980–89 1990–99 2000–10

26.9 25.4 26.4 34.8 16.6 62.0 9.5 10.4 25.7 13.2 20.5 14.3 14.7 21.4 52.0 37.1 35.9 .. 6.6 53.3 47.8 11.2 30.2 9.9 25.7 16.9 61.2 13.6 23.7 15.8 47.9 54.4 6.8 61.2 21.0 21.4 10.4 .. 27.4 62.1 19.5 15.5 28.8 7.4 70.2 .. 46.1 11.6 34.4 21.4 24.1 23.8 .. 22.2 .. 22.2 36.9 25.8

27.2 29.9 27.1 63.5 16.4 51.5 11.1 9.0 20.9 12.4 16.2 16.1 17.3 23.1 60.2 36.8 52.9 22.0 8.1 54.0 28.8 25.2 23.8 13.3 27.6 25.0 11.4 20.1 25.1 20.8 41.2 61.5 12.8 49.7 16.2 42.0 6.1 .. 26.4 59.9 19.8 9.8 23.5 5.4 61.0 15.9 30.2 9.8 32.8 33.2 25.9 25.8 43.2 21.8 28.7 26.0 41.2 26.7

32.3 34.4 32.6 73.9 14.1 44.3 9.7 6.5 23.5 36.2 14.6 39.2 15.2 25.1 79.8 46.1 89.1 8.0 12.7 61.1 27.3 35.1 30.7 30.1 25.6 50.3 34.1 27.5 26.3 28.5 38.9 57.8 28.7 44.3 16.2 42.0 10.5 .. 26.5 91.8 19.7 .. 29.5 16.9 77.7 20.8 37.5 16.0 34.6 36.3 34.4 40.0 40.7 24.7 56.9 31.6 45.1 33.2

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.26

Imports of goods and services as a share of GDP

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2009

2010a

30.9 33.8 37.7 .. 37.3 66.4 31.3 23.3 27.1 67.0 41.1 28.9 51.9 16.4 60.1 41.2 .. .. .. 31.6 63.6 9.2 .. 41.8 35.9 110.1 71.8 29.7 38.8 29.1 66.7 61.2 27.4 71.1 38.1 19.2 26.4 .. 38.4 79.1 38.2 88.5 27.4 23.2 114.1 .. 56.4 26.0 45.4 26.5 37.3 30.3 .. 42.9 .. 26.7 45.6 33.5

25.4 30.2 30.5 20.9 26.3 49.8 24.5 27.8 17.3 0.0 27.6 27.9 37.2 29.2 45.8 27.1 69.6 .. 8.9 30.9 71.6 25.9 33.4 37.0 31.3 123.2 .. 28.0 33.4 33.7 60.7 72.2 36.1 67.4 22.0 28.8 14.1 .. 32.2 66.7 23.8 37.7 18.8 7.1 68.9 37.5 45.3 19.4 36.6 22.8 32.4 24.9 78.4 32.7 31.1 31.9 50.6 28.4

32.4 36.6 37.8 53.7 26.1 36.9 24.3 25.1 19.8 69.6 19.4 50.8 33.0 39.2 50.8 39.4 55.0 59.8 31.6 32.0 48.8 60.4 25.8 .. 32.9 129.8 67.4 47.5 43.2 37.8 66.6 56.4 41.8 42.1 26.0 31.1 24.8 .. 39.4 95.8 33.5 .. 26.7 21.5 87.5 26.1 57.9 22.8 42.6 41.6 31.2 25.7 54.2 29.6 32.1 34.3 44.7 31.9

34.0 38.4 40.0 53.6 26.1 34.5 25.5 28.9 21.5 66.6 21.4 43.8 35.8 42.2 54.5 43.6 43.6 54.9 35.5 27.7 48.6 61.7 35.1 .. 36.0 120.9 76.3 45.6 52.2 37.3 82.5 65.9 43.9 40.3 24.2 31.1 25.2 .. 42.5 99.0 36.5 .. 27.9 28.1 91.2 29.7 58.7 24.8 36.7 42.5 32.2 24.3 50.9 32.6 28.3 37.9 45.3 33.2

35.3 37.4 39.6 39.0 22.7 30.7 26.5 36.1 21.0 72.7 21.9 41.1 38.6 43.0 65.6 42.4 33.1 38.4 36.6 31.8 46.4 40.7 42.6 .. 37.8 119.1 142.7 45.8 47.1 40.2 52.0 72.9 47.2 41.6 .. 27.7 25.3 .. 43.1 101.4 32.5 .. 32.5 27.5 79.0 35.7 56.1 28.4 30.1 46.9 31.3 21.5 57.3 31.6 25.5 39.7 47.9 33.6

36.2 37.6 40.3 43.5 31.6 35.9 .. 43.1 21.3 77.8 22.5 52.3 41.3 37.7 53.5 41.9 30.3 36.0 32.0 32.9 40.3 40.8 34.7 .. 37.7 118.0 121.4 52.1 42.5 35.6 61.2 67.2 45.2 52.0 .. 25.9 25.6 .. 47.7 128.9 27.8 .. 34.2 23.7 77.0 41.1 54.5 30.1 35.2 46.4 34.9 23.3 77.2 34.8 29.4 44.9 53.0 35.6

39.8 40.6 43.2 51.2 28.9 38.4 .. 41.8 35.5 78.4 23.6 50.2 48.3 38.5 47.0 38.8 31.6 26.1 30.8 32.0 37.1 44.5 38.6 .. 41.7 121.0 144.6 57.0 51.4 .. 81.9 66.1 46.4 60.9 .. 29.5 30.2 .. 52.4 132.0 29.4 .. 38.8 21.6 68.7 38.8 51.9 32.0 33.5 68.1 37.4 22.9 .. 38.6 27.5 50.9 58.7 38.8

34.2 38.7 41.0 55.4 28.5 42.8 .. 33.6 31.4 67.9 22.7 67.7 48.2 30.5 50.2 34.1 57.7 20.4 28.9 38.5 38.3 42.3 44.8 .. 36.6 115.6 100.4 52.8 42.1 .. 67.0 58.4 43.3 61.9 .. 28.7 29.0 .. 43.1 115.9 29.0 .. 28.3 20.8 72.5 35.2 52.5 35.2 32.2 62.7 33.0 24.8 .. 31.6 .. 39.7 48.0 33.7

34.0 39.0 40.9 43.0 28.1 40.0 .. 36.5 32.0 67.1 .. 61.0 .. 38.9 54.7 36.1 .. .. 32.5 36.0 38.9 41.2 39.3 .. 37.9 113.9 109.5 .. 47.2 .. 73.6 63.8 45.0 41.3 .. 31.2 30.6 .. 43.0 .. 29.5 .. 27.5 18.9 68.2 37.8 53.8 33.9 35.0 78.0 30.7 21.5 .. 26.1 .. 42.9 54.1 32.7

Annual average 1980–89 1990–99 2000–10

27.4 30.1 32.6 25.6 34.1 56.7 29.2 23.8 25.3 45.2 32.5 27.7 47.9 22.2 52.6 33.9 64.5 .. 11.9 43.6 61.0 14.3 29.9 42.8 30.6 126.9 58.0 21.3 30.4 33.4 72.2 57.6 25.1 68.7 29.0 20.3 20.7 .. 39.6 64.4 22.5 50.6 23.8 15.7 93.7 .. 53.3 17.8 36.5 22.2 33.0 26.3 .. 35.4 .. 29.7 43.1 29.6

28.6 34.4 33.6 61.3 28.9 41.7 24.6 23.4 17.2 35.0 24.0 29.7 40.2 21.9 57.3 30.3 98.6 77.8 14.9 36.3 35.5 37.6 26.9 37.8 31.4 126.9 51.0 28.3 39.4 35.7 51.4 65.6 36.4 59.7 22.4 37.8 26.0 .. 33.5 68.4 24.2 37.7 20.7 12.1 76.1 34.9 39.8 21.5 38.4 35.6 29.1 24.2 60.7 28.5 25.1 30.9 45.3 28.8

34.0 37.4 38.9 54.8 27.4 36.9 23.9 29.0 24.2 69.0 21.5 56.7 37.0 33.8 54.9 37.4 55.8 52.2 30.0 32.9 38.6 52.3 33.8 55.3 35.1 117.0 80.7 42.6 43.2 39.6 60.5 62.7 44.1 48.4 25.0 31.1 26.7 .. 42.2 102.7 33.5 .. 29.2 21.7 84.9 29.9 53.6 27.6 37.6 48.0 30.7 23.3 53.6 28.8 27.8 38.1 48.1 32.6

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.27

Balance of payments and current account

Exports of goods and services Current prices Share of GDP ($ millions) (%) a 2010 2010a

Imports of goods and services Current prices Share of GDP ($ millions) (%) a 2010 2010a

378,688 278,780 216,094 35,421 1,839 5,956 .. 740 7,200 1,113 .. 5,213 .. 5,096 6,568 8,270 .. .. 9,653 4,754 409 13,265 1,859 .. 12,192 2,482 1,081 .. 2,387 .. 2,661 6,202 4,144 4,603 .. 61,486 1,721 .. 5,530 .. 564 .. 100,119 12,665 2,522 8,653 1,709 5,833 5,672 5,831 178,504 34,820 .. 57,200 .. 38,969 23,921 557,929

Total trade (exports and imports) Current prices Share of GDP ($ millions) (%) a 2010 2010a

753,340 553,987 416,958 86,822 2,776 10,873 .. 864 13,702 1,753 .. 8,544 .. 8,508 16,789 17,586 .. .. 13,045 12,848 639 22,726 3,508 .. 21,053 3,437 1,329 .. 3,934 .. 4,902 11,300 6,564 9,340 .. 136,096 2,332 .. 8,716 .. 891 .. 199,518 25,907 4,549 14,628 2,894 9,920 12,814 9,439 375,854 84,759 .. 103,932 .. 68,934 45,490 1,136,260

65.2 73.2 74.2 105.3 42.3 73.0 .. 42.7 61.0 105.7 .. 100.0 .. 64.9 139.8 76.7 .. .. 44.0 97.3 60.8 70.6 74.1 .. 65.4 157.7 134.5 .. 77.8 .. 135.6 116.3 71.3 83.9 .. 69.1 41.5 .. 67.8 .. 46.6 .. 54.9 38.7 123.0 63.8 91.1 57.7 79.1 126.3 59.2 52.3 .. 47.5 .. 75.9 102.8 62.8

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Net income Current prices Share of GDP ($ millions) (%) a 2010 2010a

.. .. .. -8,172 .. -243 .. -11 -239 -68 .. .. .. .. .. .. .. .. -64 .. -8 -535 -77 .. -155 532 24 .. .. .. .. 202 -85 -564 .. -18,623 -46 0 .. -65 -49 .. -7,224 -2,472 -226 -216 .. -291 -1,363 .. .. -368 17 -5,912 -30 -1,242 -1,925 ..

.. .. .. -9.9 .. -1.6 .. -0.5 -1.1 -4.1 .. .. .. .. .. .. .. .. -0.2 .. -0.8 -1.7 -1.6 .. -0.5 24.4 2.5 .. .. .. .. 2.1 -0.9 -5.1 .. -9.5 -0.8 -0.2 .. -6.7 -2.5 .. -2.0 -3.7 -6.1 -0.9 .. -1.7 -8.4 .. .. -0.2 .. -2.7 .. -1.4 -4.4 ..

NATIONAL AND FISCAL ACCOUNTS

Net current transfers Current prices Share of GDP ($ millions) (%) a 2010 2010a

.. .. .. -438 .. 979 .. 136 146 341 .. .. .. .. .. .. .. .. 4,905 .. 113 2,322 17 .. 2,286 661 959 .. .. .. .. 183 657 1,232 .. 20,093 657 3 .. 25 185 .. -2,278 2,131 400 824 .. 1,313 432 .. .. 2,650 95 12,439 -1,828 7,270 1,935 ..

.. .. .. -0.5 .. 6.6 .. 6.7 0.7 20.5 .. .. .. .. .. .. .. .. 16.5 .. 10.7 7.2 0.4 .. 7.1 30.3 97.1 .. .. .. .. 1.9 7.1 11.1 .. 10.2 11.7 1.3 .. 2.6 9.7 .. -0.6 3.2 10.8 3.6 .. 7.6 2.7 .. .. 1.6 .. 5.7 .. 8.0 4.4 ..

Current account balance Current prices Share of GDP ($ millions) (%) a 2010 2010a

-14,147 -4,029 -6,506 7,421 .. 46 .. -301 -856 -184 .. .. .. .. .. .. .. .. -425 .. 52 -2,700 -327 .. -2,512 -421 -415 .. .. .. .. -800 -1,113 30 .. 2,476 -421 -107 .. -225 -320 .. -10,117 157 -388 -1,978 .. -1,859 1,144 .. 18,464 12,146 50 -4,504 16,801 -3,925 -2,104 4,317

-1.5 -0.7 -1.7 9.0 .. 0.3 .. -14.8 -3.8 -11.1 .. .. .. .. .. .. .. .. -1.4 .. 5.0 -8.4 -6.9 .. -7.8 -19.3 -42.0 .. .. .. .. -8.2 -12.1 0.3 .. 1.3 -7.5 -53.4 .. -23.4 -16.8 .. -2.8 0.2 -10.5 -8.6 .. -10.8 7.1 .. 0.3 7.5 .. -2.1 .. -4.3 -4.8 -0.9

Total reserves including gold Current prices Share of GDP ($ millions) (%) a 2010 2010a

163,563 119,744 83,859 19,749 1,200 7,885 1,068 332 3,643 382 181 632 146 1,300 4,447 3,624 2,346 114 .. 1,736 202 5,158 .. 156 4,321 .. .. 1,172 325 1,344 288 2,619 2,265 1,696 760 35,885 813 49 2,047 236 409 .. 43,820 1,036 756 3,905 715 2,706 2,094 .. 347,256 170,461 249 37,029 106,144 23,609 9,764 510,820

14.6 15.9 15.1 24.0 18.3 52.9 12.1 16.4 16.2 23.0 9.1 7.4 27.0 9.9 37.0 15.8 16.2 5.4 .. 13.2 19.2 16.0 .. 18.7 13.4 .. .. 13.4 6.4 14.3 8.0 27.0 24.6 15.2 14.1 18.2 14.5 24.6 15.9 24.5 21.4 .. 12.1 1.6 20.5 17.0 22.5 15.7 12.9 .. 59.2 105.2 .. 16.9 .. 26.0 22.1 30.0

Part I. Basic indicators and national and fiscal accounts

Table

2.28

Exchange rates and purchasing power parity

Official exchange rate (local currency units to US$) 2008 2009 2010

Purchasing power parity (PPP) conversion factor (local currency units to international $) 2008 2009 2010

Ratio of PPP conversion factor to market exchange rate 2008 2009 2010

62.4 233.9 3.4 204.5 433.1 255.5 68.6 275.9 256.5 235.8 317.5 371.3 307.0 370.3 8.1 3.5 307.4 7.6 0.9 1,992.2 229.8 35.1 4.3 32.1 796.0 51.7 268.2 107.2 17.2 13.1 5.3 235.1 77.1 239.5 9,313.4 271.6 4.7 1,336.1 .. 4.5 1.4 4.2 460.4 258.0 667.2 3,193.3 ..

57.2 231.6 3.2 207.2 481.2 244.2 70.7 282.7 229.4 244.1 424.5 291.6 303.6 242.6 10.3 4.4 245.1 8.0 1.0 2,105.5 229.9 37.9 4.5 31.3 854.0 54.7 274.7 99.9 17.0 13.5 5.5 242.2 72.9 263.8 10,464.1 264.8 5.9 1,391.3 .. 4.7 1.4 4.1 489.1 260.2 756.4 3,498.9 ..

69.2 232.3 3.7 210.5 512.1 248.7 72.2 284.4 253.9 250.5 512.6 348.1 305.9 300.4 11.4 4.5 287.5 8.4 1.2 2,501.9 231.2 38.3 4.6 33.0 912.4 57.8 283.0 117.8 17.1 14.6 5.5 239.4 78.8 267.3 11,559.3 265.5 5.5 1,572.9 .. 5.1 1.6 4.3 517.1 261.8 818.9 3,864.3 ..

75.0 447.8 6.8 447.8 1,185.7 447.8 75.3 447.8 447.8 335.9 559.3 447.8 447.8 447.8 15.4 9.6 447.8 22.2 1.1 4,601.7 447.8 69.2 8.3 63.2 1,708.4 140.5 447.8 238.2 28.5 24.3 8.3 447.8 118.6 546.9 14,695.2 447.8 9.5 2,981.5 .. 8.3 2.1 8.3 1,196.3 447.8 1,720.4 3,745.7 ..

79.3 472.2 7.2 472.2 1,230.2 472.2 79.4 472.2 472.2 354.1 809.8 472.2 472.2 472.2 15.4 11.8 472.2 26.6 1.4 4,801.1 472.2 77.4 8.5 68.3 1,956.2 141.2 472.2 262.4 32.0 27.5 8.5 472.2 148.9 568.3 16,208.5 472.2 13.6 3,385.7 .. 8.5 2.3 8.5 1,320.3 472.2 2,030.5 5,046.1 ..

91.9 495.3 6.8 495.3 1,230.8 495.3 83.3 495.3 495.3 371.5 905.9 495.3 495.3 495.3 15.4 14.4 495.3 28.0 1.4 5,726.1 495.3 79.2 7.3 71.4 2,090.0 150.5 495.3 275.9 30.8 34.0 7.3 495.3 150.3 583.1 18,498.6 495.3 12.1 3,978.1 .. 7.3 2.3 7.3 1,409.3 495.3 2,177.6 4,797.1 ..

0.8 0.5 0.5 0.5 0.4 0.6 0.9 0.6 0.6 0.7 0.6 0.8 0.7 0.8 0.5 0.4 0.7 0.3 0.8 0.4 0.5 0.5 0.5 0.5 0.5 0.4 0.6 0.5 0.6 0.5 0.6 0.5 0.7 0.4 0.6 0.6 0.5 0.5 .. 0.5 0.7 0.5 0.4 0.6 0.4 0.9 ..

0.7 0.5 0.5 0.4 0.4 0.5 0.9 0.6 0.5 0.7 0.5 0.6 0.6 0.5 0.7 0.4 0.5 0.3 0.7 0.4 0.5 0.5 0.5 0.5 0.4 0.4 0.6 0.4 0.5 0.5 0.7 0.5 0.5 0.5 0.7 0.6 0.4 0.4 .. 0.6 0.6 0.5 0.4 0.6 0.4 0.7 ..

0.8 0.5 0.5 0.4 0.4 0.5 0.9 0.6 0.5 0.7 0.6 0.7 0.6 0.6 0.7 0.4 0.6 0.3 0.8 0.4 0.5 0.5 0.6 0.5 0.4 0.4 0.6 0.4 0.6 0.4 0.8 0.5 0.5 0.5 0.6 0.5 0.5 0.4 .. 0.7 0.7 0.6 0.4 0.5 0.4 0.8 ..

40.1 92.8 2.0 1.1 5.0 0.6

35.2 93.4 2.2 0.7 5.0 0.6

40.5 .. 2.4 .. 5.0 0.6

64.6 177.7 5.4 1.2 7.8 1.2

72.7 177.7 5.5 1.3 8.1 1.4

74.4 177.7 5.6 1.3 8.4 1.4

0.6 0.5 0.4 0.9 0.7 0.5

0.5 0.5 0.4 0.6 0.6 0.5

0.5 .. 0.4 .. 0.6 0.4

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Gross domestic product

2008

Real effective exchange rate (index: 2000 = 100) 2009

105.8 106.0 105.8 .. .. .. .. 100.6 105.6 .. 113.3 .. .. 106.3 .. 105.8 115.5 .. .. 104.5 114.8 99.5 .. .. .. 87.7 .. .. 98.2 .. .. .. .. .. .. 116.4 .. .. .. .. 112.5 .. 80.4 .. .. .. 104.3 106.3 138.7 .. 100.1 103.2 .. .. .. 100.1 95.4 105.0

107.6 107.7 107.6 .. .. .. .. 110.6 107.8 .. 115.6 .. .. 597.4 .. 105.5 119.3 .. .. 105.3 104.0 91.6 .. .. .. 93.2 .. .. 107.6 .. .. .. .. .. .. 109.0 .. .. .. .. 114.1 .. 87.6 .. .. .. 104.5 105.3 119.1 .. 102.0 102.0 .. .. .. 102.2 94.3 105.4

NATIONAL AND FISCAL ACCOUNTS

2010

106.1 108.2 106.1 .. .. .. .. 113.3 101.1 .. 110.3 .. .. 1,025.3 .. 99.6 120.5 .. .. 101.3 101.0 97.6 .. .. .. 106.1 .. .. 101.1 .. .. .. .. .. .. 117.9 .. .. .. .. 110.2 .. 101.2 .. .. .. 98.1 111.4 126.0 .. 98.0 102.4 .. .. .. 98.0 93.6 101.9

2008

PPP $ billions 2009

2010

1,749.2 1,249.0 926.3 101.2 12.8 26.7 18.3 4.4 41.6 1.7 3.2 14.6 0.8 20.6 14.3 34.2 22.3 2.6 70.2 21.2 3.0 34.9 10.4 1.6 60.1 3.1 1.7 20.2 11.1 14.6 8.0 15.9 18.4 13.7 10.2 318.3 10.8 0.3 22.1 1.9 4.4 .. 508.8 88.1 5.9 53.8 5.5 36.7 17.2 .. 1,052.1 275.4 1.9 443.5 102.3 137.2 91.8 2,798.5

1,814.6 1,318.0 968.8 104.7 13.4 25.6 19.0 4.6 42.9 1.8 3.3 14.6 0.8 21.4 15.5 35.8 23.8 2.8 77.2 21.1 3.3 36.6 10.5 1.7 62.4 3.2 1.9 19.4 12.2 15.4 8.0 16.6 19.8 13.8 10.2 344.2 11.3 0.3 22.8 2.0 4.5 .. 506.3 92.6 6.1 57.7 5.7 39.8 18.5 .. 1,102.7 285.0 2.0 469.3 105.6 145.3 95.6 2,914.5

1,931.6 1,415.5 1,034.4 109.5 14.0 27.8 20.8 4.9 44.8 1.9 3.5 16.7 0.8 23.2 17.1 37.1 23.9 2.9 85.8 22.7 3.5 40.0 10.8 1.8 66.6 3.5 2.1 20.0 13.2 16.5 8.5 17.5 21.4 14.9 11.2 375.4 12.3 0.3 24.0 2.1 4.8 .. 526.9 97.8 6.3 62.5 6.0 42.6 20.1 .. 1,162.2 297.8 .. 499.1 .. 152.4 99.6 3,091.5

2008

Per capita PPP $ 2009

2010

2,176.0 1,654.1 1,532.6 5,608.7 1,531.4 13,638.7 1,178.5 558.6 2,217.8 3,517.7 759.4 1,370.1 1,083.1 329.2 3,727.9 1,799.1 33,643.2 531.8 883.5 14,593.4 1,857.9 1,498.4 1,091.2 1,129.9 1,563.7 1,465.1 458.4 1,031.5 791.3 1,009.2 2,417.5 12,550.6 823.8 6,230.6 708.0 2,112.5 1,075.2 1,810.9 1,872.3 22,100.8 777.3 .. 10,427.4 2,127.4 5,747.0 1,312.0 950.5 1,171.6 1,387.2 .. 6,518.3 7,998.4 2,199.6 5,663.0 16,634.5 4,313.2 8,884.4 2,899.2

2,203.2 1,702.2 1,563.0 5,643.3 1,560.6 12,941.5 1,190.4 567.9 2,236.5 3,655.2 766.1 1,332.6 1,085.3 332.9 3,941.0 1,851.9 34,959.0 541.8 950.6 14,273.5 1,948.2 1,537.7 1,076.9 1,152.0 1,580.7 1,507.6 499.6 966.2 845.5 1,033.6 2,354.6 13,002.5 864.9 6,153.1 684.3 2,227.9 1,097.5 1,872.6 1,880.7 22,364.6 792.8 .. 10,265.3 2,179.3 5,812.0 1,365.4 970.6 1,229.5 1,451.4 .. 6,728.9 8,153.8 2,290.1 5,886.7 16,854.6 4,519.6 9,158.8 2,951.5

2,288.7 1,782.8 1,627.6 5,739.9 1,580.3 13,831.8 1,260.9 581.1 2,284.2 3,855.6 785.4 1,483.9 1,091.9 351.2 4,226.5 1,880.5 34,128.7 543.5 1,034.7 15,105.9 2,034.7 1,640.9 1,085.9 1,181.0 1,643.9 1,594.1 535.2 964.4 882.9 1,073.1 2,445.7 13,632.7 913.1 6,515.1 721.6 2,369.5 1,155.1 1,945.2 1,929.0 24,356.1 823.2 .. 10,540.2 2,245.8 5,928.3 1,435.1 996.9 1,275.5 1,555.1 .. 6,987.3 8,395.5 .. 6,152.6 .. 4,691.1 9,443.2 3,060.0

Part I. Basic indicators and national and fiscal accounts

Table

2.29

Agriculture value added

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2010a

18.5 31.5 31.5 .. 35.4 14.7 29.4 62.3 31.3 18.6 40.0 45.1 34.0 26.8 11.7 25.9 .. .. .. 6.8 30.9 60.1 .. 44.3 32.6 24.6 .. 30.1 43.7 48.3 30.4 13.1 37.1 11.2 43.1 .. 45.9 .. 20.1 6.8 33.0 68.4 6.2 32.9 22.7 .. 27.5 72.0 15.1 15.7 15.7 8.5 .. 18.3 .. 18.5 16.3 17.3

18.8 31.4 31.4 17.9 36.1 4.9 28.8 55.9 24.6 14.4 47.6 29.3 41.4 31.0 12.9 32.5 61.6 .. 54.3 7.3 29.0 45.1 23.8 60.8 29.5 25.0 .. 28.6 45.0 45.5 29.6 12.9 37.1 11.7 35.3 .. 32.6 .. 19.9 4.8 46.9 65.5 4.6 40.6 10.4 46.0 33.8 56.6 20.6 16.5 17.0 11.4 3.1 19.4 .. 18.3 17.7 18.1

17.1 27.2 25.7 8.6 32.1 2.0 32.9 44.6 20.5 9.9 55.3 23.5 50.9 47.3 5.5 23.2 4.1 11.6 44.2 5.6 28.7 41.6 25.1 .. 28.0 9.6 .. 28.8 34.6 36.4 35.5 6.5 27.4 9.7 .. 34.2 38.6 22.6 15.9 3.0 44.9 .. 3.1 35.2 8.9 33.3 36.2 22.9 23.0 19.6 12.3 10.2 3.6 15.2 3.0 16.3 11.0 15.0

16.5 26.6 25.3 8.5 32.2 1.8 34.1 44.5 19.5 9.0 54.4 12.3 51.0 45.5 4.5 22.8 2.6 24.2 46.7 4.9 28.4 40.9 24.2 .. 27.2 9.0 .. 28.3 32.6 36.6 30.5 6.0 27.0 11.3 .. 32.8 38.4 16.8 16.7 2.4 51.6 .. 2.7 32.0 8.8 31.8 39.4 26.7 23.3 18.6 11.3 8.2 3.5 14.9 2.3 14.7 10.1 14.3

16.0 25.7 24.2 7.7 .. 1.8 33.3 43.7 19.9 8.3 55.0 11.7 45.2 45.7 4.0 22.9 2.8 26.1 47.9 4.9 22.1 30.4 23.8 .. 26.8 7.9 .. 27.5 31.2 36.9 22.9 5.6 27.9 10.5 .. 32.0 38.4 .. 14.8 2.3 51.1 .. 2.9 30.1 7.8 30.4 35.9 25.6 22.4 20.3 11.2 8.0 3.5 14.1 2.0 16.9 10.2 14.0

15.8 25.1 23.3 7.9 .. 2.0 .. 37.8 19.5 7.2 53.9 12.5 45.3 42.5 4.3 23.9 2.7 25.4 46.2 4.9 21.0 29.1 25.4 .. 25.0 7.7 .. 25.7 30.3 36.5 25.6 4.5 27.7 9.4 .. 32.7 35.7 .. 13.4 2.1 49.9 .. 3.4 28.1 8.0 30.0 35.8 23.6 21.8 21.6 10.7 8.0 3.9 14.1 2.1 13.7 9.4 13.6

13.0 22.9 22.9 6.6 .. 2.0 .. 35.4 .. 6.4 52.9 13.6 45.8 40.2 3.7 25.0 2.0 17.4 43.9 4.1 24.8 31.0 24.9 .. 25.8 8.0 .. 24.8 30.1 .. 18.9 4.1 30.5 9.3 .. .. 32.4 .. 15.6 2.0 50.2 .. 3.2 26.3 7.9 29.7 40.7 22.7 19.0 19.4 10.2 6.9 .. 13.2 1.9 14.6 8.5 11.7

13.5 24.2 24.2 10.2 .. 3.0 .. 35.2 .. 8.8 56.5 .. 46.3 42.9 4.5 24.7 3.2 14.5 50.8 5.4 26.8 31.8 16.9 .. 27.2 7.7 .. 29.1 30.5 .. 20.2 3.9 31.5 9.4 .. .. 33.9 .. 17.2 1.8 52.3 .. 3.0 29.7 8.7 28.8 42.7 24.7 21.6 17.2 12.0 6.9 .. 13.7 .. 16.4 8.9 12.9

11.2 .. 21.1 9.8 .. 2.5 .. 35.2 .. 9.9 .. .. .. .. 3.8 22.8 .. .. 47.7 4.1 28.5 29.9 13.0 .. 25.2 8.6 .. .. .. .. 17.2 3.7 31.9 7.5 .. .. 32.2 .. 17.4 .. 49.0 .. 2.5 23.6 8.0 28.1 42.8 24.3 9.2 16.0 11.9 6.9 .. 14.0 .. 15.4 8.0 11.5

Annual average 1980–89 1990–99 2000–10

18.4 31.0 31.0 15.2 33.8 8.7 29.8 58.1 25.7 14.9 44.3 36.9 36.3 30.4 10.0 27.2 65.9 .. 56.5 7.7 34.0 52.5 24.0 48.6 32.4 24.7 .. 34.3 44.2 44.4 30.4 14.9 39.7 11.2 38.7 .. 40.2 .. 22.0 6.1 40.0 66.5 5.5 35.4 19.5 .. 31.8 57.6 15.9 16.2 16.4 9.9 3.3 19.8 .. 16.4 15.8 17.5

18.2 30.7 30.7 11.3 36.1 4.3 33.8 50.8 24.3 12.5 48.4 36.7 40.2 47.0 10.5 27.2 41.5 22.9 58.4 7.7 19.4 42.6 20.1 56.3 30.8 19.3 .. 28.6 37.3 46.7 35.6 10.2 34.7 11.3 39.4 .. 40.6 .. 19.7 3.9 47.9 65.5 4.1 42.1 12.0 44.5 37.4 47.9 21.1 17.0 15.6 11.2 3.4 17.3 .. 17.8 15.2 17.2

15.8 26.7 25.0 8.1 33.7 2.2 33.8 41.3 20.9 9.5 55.0 25.6 48.4 47.6 4.9 24.1 4.6 18.2 46.4 5.3 25.3 35.7 21.8 55.0 27.9 9.5 .. 28.2 34.0 37.5 28.7 5.6 27.8 10.1 39.3 37.2 36.1 20.0 16.5 2.6 49.9 .. 3.2 33.7 9.1 31.2 38.2 25.5 20.8 18.1 12.2 8.6 3.6 15.0 3.0 15.8 9.8 14.3

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.30

Industry value added

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2010a

37.8 .. 25.5 .. 12.3 50.7 20.5 12.6 25.6 17.0 20.1 8.9 13.2 35.0 46.6 19.7 .. .. .. 60.4 14.9 12.3 .. 19.7 20.9 26.5 .. 16.1 22.5 13.2 26.0 26.2 34.4 55.8 22.9 .. 21.6 .. 20.1 15.6 21.9 8.0 48.4 .. 30.2 .. 24.8 4.5 42.1 29.0 40.8 57.7 .. 36.8 .. 31.0 36.0 39.1

32.2 25.1 25.1 40.9 13.2 61.0 21.0 19.0 29.5 21.4 19.7 17.7 8.3 29.0 40.6 23.2 10.6 .. 11.1 43.0 13.1 16.9 33.3 18.6 19.0 34.4 .. 12.8 28.9 15.9 28.8 32.8 18.4 38.0 16.2 .. 24.6 .. 22.2 16.3 19.2 .. 40.1 15.3 43.2 17.7 22.5 11.1 51.3 33.1 34.7 48.2 22.1 28.7 .. 33.4 33.6 33.2

30.9 30.7 28.1 66.1 13.3 51.0 23.2 18.1 30.7 15.0 14.0 47.1 12.2 24.5 65.9 23.1 92.1 21.3 14.1 55.3 14.5 27.1 33.7 .. 18.2 32.5 .. 16.0 17.4 23.9 27.3 29.1 27.4 29.4 .. 42.1 13.9 21.1 24.9 28.2 24.2 .. 31.3 25.8 46.4 22.4 17.2 22.1 27.9 26.4 43.0 56.4 16.6 36.5 68.6 28.5 28.4 36.0

31.6 31.9 29.3 67.1 13.4 50.2 22.7 18.5 30.4 15.7 14.1 60.4 11.0 26.9 71.9 25.9 94.4 21.9 13.0 61.4 14.7 27.5 38.9 .. 19.1 33.1 .. 15.8 17.0 24.2 33.2 27.6 25.3 29.2 .. 43.5 14.1 20.5 23.8 21.2 23.6 .. 31.2 28.3 44.7 22.7 17.2 25.0 31.6 28.7 44.7 61.3 16.6 35.9 75.5 28.2 29.2 37.2

31.8 32.3 30.1 67.5 .. 54.0 22.4 18.5 31.4 16.0 14.2 60.6 11.8 27.7 75.5 25.9 94.4 19.3 12.7 61.2 15.5 20.8 43.4 .. 18.5 35.3 .. 16.1 17.0 24.0 46.5 27.6 26.4 34.6 .. 41.9 13.8 .. 23.1 19.4 23.2 .. 31.2 29.2 46.7 22.9 18.4 24.2 35.3 32.3 46.3 62.3 16.4 38.4 78.5 27.2 29.7 38.0

31.8 32.3 30.4 66.6 .. 52.6 .. 19.0 30.6 15.7 14.2 54.3 11.9 28.4 73.2 25.3 94.6 20.1 13.3 60.3 14.9 20.8 43.4 .. 18.5 35.9 .. 16.3 16.3 24.2 39.6 27.0 25.9 35.6 .. 40.7 14.0 .. 23.6 20.3 24.3 .. 31.2 31.2 46.5 23.3 18.7 26.6 38.5 33.1 45.1 61.3 16.9 36.3 76.4 27.3 31.3 37.5

32.0 31.1 31.1 67.5 .. 52.6 .. 17.9 .. 18.5 14.2 48.8 12.0 28.0 77.4 26.1 95.7 26.9 13.0 64.3 13.7 20.4 46.7 .. 19.8 37.3 .. 16.2 16.1 .. 40.5 28.1 23.7 37.8 .. .. 14.8 .. 22.2 19.4 23.5 .. 32.8 34.0 46.4 23.1 18.2 27.4 41.4 31.1 46.7 62.1 .. 37.5 78.2 30.3 33.1 38.8

29.7 28.1 28.1 59.1 .. 40.1 .. 18.1 .. 18.3 14.8 .. 12.1 24.0 71.1 25.5 92.6 22.4 10.8 53.5 12.4 19.0 52.1 .. 19.2 32.9 .. 16.0 16.1 .. 35.1 28.0 23.6 32.7 .. .. 14.4 .. 21.8 17.9 22.5 .. 31.3 26.0 50.6 24.3 16.0 25.8 34.1 27.8 41.3 62.1 .. 37.3 .. 28.6 31.6 34.7

30.4 .. 30.0 59.9 .. 45.0 .. 18.3 .. 18.0 .. .. .. .. 75.4 27.2 .. .. 14.3 59.4 12.3 18.6 47.2 .. 19.8 31.9 .. .. .. .. 43.9 27.0 23.4 19.6 .. .. 15.0 .. 22.4 .. 20.7 .. 30.8 33.0 46.5 25.5 15.7 25.5 37.2 26.8 41.6 62.1 .. 37.5 .. 29.7 32.3 35.4

Annual average 1980–89 1990–99 2000–10

.. .. 31.1 60.2 .. 46.8 .. 18.6 .. 17.8 .. .. .. .. 76.8 30.3 .. .. 12.6 60.7 12.0 25.3 .. .. 19.2 33.7 .. .. .. .. 46.3 26.6 24.2 19.6 .. .. .. .. 23.8 .. 18.2 .. .. 39.8 45.9 26.5 16.0 25.4 37.7 22.9 .. .. .. 36.7 .. 29.9 33.3 ..

34.4 24.9 24.9 39.4 14.0 57.5 21.0 15.1 31.8 18.0 16.2 13.5 12.5 30.1 45.1 20.9 8.9 .. 11.6 53.7 13.7 13.8 33.6 15.7 19.4 27.7 .. 13.8 22.7 14.8 27.0 28.9 24.8 44.3 19.8 .. 21.0 .. 20.7 16.5 15.9 8.0 43.8 15.4 32.3 .. 22.0 9.4 45.5 30.2 36.8 52.1 20.6 30.6 .. 33.2 36.1 35.4

29.6 24.9 24.9 56.9 13.7 54.9 21.1 18.7 30.3 19.2 20.2 13.7 11.4 20.6 45.4 22.2 38.5 18.4 10.2 48.2 6.2 24.5 30.1 12.5 17.8 42.3 .. 12.2 22.7 17.0 26.5 32.1 17.1 30.6 17.4 .. 19.5 .. 23.5 21.5 32.4 .. 35.0 13.5 43.4 16.4 21.0 14.9 39.2 30.5 36.1 49.7 16.6 31.8 .. 32.0 32.0 32.3

a. Provisional.

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.31

Services plus discrepancy value added

Share of GDP (%)

1980

1990

2004

2005

2006

2007

2008

2010a

44.7 43.9 43.9 .. 52.3 34.6 50.1 25.1 43.1 64.5 39.9 46.0 52.8 38.2 41.7 54.4 .. .. .. 32.8 54.3 27.6 .. 36.1 46.6 48.9 .. 53.9 33.7 38.5 43.6 60.7 28.5 33.0 34.0 .. 32.6 .. 59.9 77.5 45.0 23.6 45.4 53.0 47.1 .. 47.7 23.5 42.8 55.3 43.5 33.8 .. 45.0 .. 50.5 47.7 44.2

49.2 43.8 43.8 41.2 50.7 34.1 50.2 25.2 46.0 64.2 32.7 53.0 50.3 40.0 46.5 44.3 27.8 .. 34.5 49.7 57.9 38.1 42.9 20.6 51.4 40.7 .. 58.6 26.1 38.6 41.6 54.4 44.5 50.3 48.6 .. 42.8 .. 57.9 78.9 33.9 .. 55.3 44.2 46.5 36.4 43.7 32.4 28.1 50.4 48.3 40.5 74.9 52.0 .. 48.3 48.7 48.8

52.0 42.1 46.2 25.3 54.6 47.0 44.0 37.3 48.9 75.1 30.7 29.4 36.9 28.3 28.6 53.8 3.8 67.1 41.8 39.1 56.8 31.4 41.3 .. 53.7 57.9 .. 55.3 47.9 39.8 37.2 64.4 45.2 60.8 .. 23.7 47.6 56.4 59.2 68.8 30.9 .. 65.6 38.9 44.7 44.3 46.6 55.0 49.1 54.0 44.7 33.5 79.8 48.4 28.4 55.2 60.6 48.9

51.9 41.4 45.5 24.4 54.4 48.0 43.2 37.1 50.1 75.3 31.4 27.3 38.0 27.6 23.6 51.3 3.0 53.9 40.4 33.8 56.9 31.6 36.9 .. 53.7 57.9 .. 55.9 50.3 39.3 36.3 66.4 47.7 59.5 .. 23.7 47.6 62.7 59.6 72.9 24.8 .. 66.2 39.7 46.5 45.5 43.4 48.3 45.1 52.7 43.9 30.5 79.9 49.2 22.2 57.1 60.7 48.5

52.2 42.0 45.7 24.8 .. 44.2 44.4 37.9 48.8 75.6 30.7 27.8 43.0 26.6 20.5 51.2 2.9 54.6 39.4 33.9 62.4 48.8 32.8 .. 54.8 56.8 .. 56.4 51.9 39.1 30.5 66.9 45.7 54.9 .. 26.1 47.8 .. 62.2 73.2 25.7 .. 66.0 40.8 45.5 46.7 45.7 50.2 42.3 47.4 42.5 29.7 80.1 47.5 19.5 56.0 60.1 48.1

52.5 42.7 46.5 25.6 .. 45.4 .. 43.2 49.9 77.1 31.9 33.2 42.8 29.1 22.4 50.9 2.8 54.5 40.5 34.9 64.1 50.2 31.3 .. 56.5 56.4 .. 58.1 53.4 .. 34.8 68.6 46.4 55.0 .. 26.6 50.4 .. 63.1 77.5 25.9 .. 65.4 40.7 45.5 46.7 45.5 49.8 39.8 45.3 44.2 30.7 79.3 49.6 21.5 59.0 59.3 49.0

55.1 46.0 46.0 25.9 .. 45.4 .. 46.8 .. 75.1 32.9 37.5 42.2 31.8 18.9 48.9 2.3 55.8 43.1 31.6 61.5 48.6 28.4 .. 54.4 54.7 .. 59.0 53.8 .. 40.6 67.8 45.9 52.9 .. .. 52.8 .. 62.3 78.6 26.3 .. 64.0 39.7 45.7 47.2 41.1 49.9 39.7 49.5 43.2 31.0 .. 49.3 19.9 55.0 58.4 49.5

56.8 47.7 47.7 30.8 .. 56.9 .. 46.7 .. 72.9 28.7 .. 41.6 33.1 24.4 49.9 4.2 63.0 38.5 41.2 60.8 49.2 31.0 .. 53.6 59.4 .. 54.9 53.4 .. 44.7 68.1 44.9 58.0 .. .. 51.6 .. 61.0 80.3 25.2 .. 65.7 44.3 40.7 46.9 41.3 49.5 44.4 55.0 46.7 31.0 .. 49.0 .. 55.0 59.5 52.5

58.4 .. 48.9 30.2 .. 52.5 .. 46.6 .. 72.1 .. .. .. .. 20.8 50.0 .. .. 38.0 36.5 59.3 51.4 39.4 .. 55.0 59.5 .. .. .. .. 38.9 69.4 44.8 72.9 .. .. 52.8 .. 60.3 .. 30.4 .. 66.7 43.3 45.5 46.5 41.5 50.3 53.6 57.2 46.5 31.0 .. 48.5 .. 55.0 59.7 53.1

Annual average 1980–89 1990–99 2000–10

47.5 44.4 44.4 45.4 52.2 33.8 49.2 26.8 42.5 67.1 39.5 49.6 51.2 39.6 44.9 52.0 25.2 .. 31.9 38.6 52.3 33.6 42.4 35.7 48.2 47.6 .. 51.9 33.1 40.8 42.6 56.2 35.6 44.6 41.6 .. 38.8 .. 57.3 77.4 44.2 25.1 50.8 49.5 48.2 .. 46.2 33.0 38.6 53.6 46.8 38.0 76.1 49.7 .. 50.4 48.2 47.2

52.2 44.4 44.4 31.8 50.2 40.9 45.1 30.5 45.4 68.3 31.4 49.6 48.4 32.4 44.1 50.6 20.0 58.7 31.4 44.0 74.5 32.9 49.9 31.1 51.5 38.4 .. 59.3 40.1 36.4 37.9 57.7 48.2 58.1 43.3 .. 40.0 .. 56.8 74.7 19.7 .. 60.9 44.5 44.5 39.1 41.7 37.2 39.7 52.5 48.2 39.1 80.0 51.0 .. 50.2 52.8 50.5

53.6 43.6 46.3 25.9 52.6 46.9 44.2 40.5 47.3 74.5 30.3 37.1 39.8 28.1 24.9 51.1 3.8 59.7 40.5 37.7 63.1 40.1 38.4 32.0 53.7 56.6 .. 56.3 48.8 38.1 37.4 65.6 47.1 59.1 43.5 23.6 50.0 61.3 59.9 72.5 26.0 .. 65.2 39.9 44.6 46.4 44.2 49.9 47.4 55.1 45.3 32.5 80.2 49.0 23.0 55.9 59.8 50.0

a. Provisional.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.32

Central government ﬁnances

1990

SUB-SAHARAN AFRICA Angola Benina Botswanaa Burkina Faso Burundia Cameroona Cape Verde Central African Republica Chad Comoros Congo, Dem. Rep.a Congo, Rep.a Côte d'Ivoire Equatorial Guinea Eritrea Ethiopiaa Gabon Gambia, Thea Ghanaa Guineaa Guinea-Bissau Kenyaa Lesothoa Liberiaa Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibiaa Niger Nigeriaa Rwandaa São Tomé and Príncipe Senegala Seychelles Sierra Leonea Somalia South Africa Sudana Swazilanda Tanzania Togo Ugandaa Zambiaa Zimbabwea NORTH AFRICA Algeria Djibouti Egypt, Arab Rep.a Libya Moroccoa Tunisiaa ALL AFRICA

.. .. .. 50.8 .. .. 14.3 .. .. .. .. 10.1 .. .. .. .. 12.4 .. 19.4 12.5 .. .. .. 44.9 .. .. .. .. .. .. .. 31.3 .. .. 10.8 .. .. .. 5.6 .. .. .. .. .. .. .. 20.4 24.1 .. .. .. 23.0 .. .. 30.7 ..

Revenue, excluding grants 2000 2005

.. .. .. .. .. .. .. .. .. .. .. 3.7 28.7 .. .. .. .. .. .. .. .. .. 19.7 50.7 .. 11.7 .. 13.4 .. .. .. 30.1 .. .. .. .. 16.9 38.7 11.4 .. 26.4 .. 25.6 .. .. 10.8 .. .. .. .. .. .. .. .. 26.5 ..

23.3 .. 16.4 .. 12.8 .. .. 27.6 .. .. .. 14.7 39.9 12.1 .. .. 11.0 .. .. 23.7 .. .. 20.2 52.1 0.3 11.0 .. 18.0 .. .. .. 28.2 10.5 9.4 .. .. .. 44.8 11.5 .. 30.1 .. .. .. 14.7 11.9 17.6 .. .. .. .. 24.3 .. 30.7 26.2 24.3

2010

1990

Share of GDP (%) Expense 2000 2005

.. .. 18.2 .. 15.6 .. .. .. .. .. .. 23.4 .. .. .. .. .. .. .. .. .. .. 20.3 .. .. .. .. .. .. 22.8 .. .. .. .. .. .. .. 36.4 .. .. .. .. .. .. 17.6 .. 17.4 .. .. .. .. 24.8 .. 31.8 29.0 ..

.. .. .. 26.7 .. .. 14.6 .. .. .. .. 16.7 .. .. .. .. 16.2 .. 17.2 .. .. .. .. 33.6 .. .. .. .. .. .. .. .. .. .. 12.7 .. .. .. .. .. .. .. .. .. .. .. .. 24.5 .. .. .. 24.0 .. .. 30.4 ..

22.8 .. 13.6 .. 11.6 .. .. 30.2 .. .. .. 22.1 14.8 16.9 .. .. 15.0 .. .. 22.8 .. .. 18.2 41.9 0.2 11.0 .. 15.1 .. .. .. 25.6 9.1 5.0 .. .. .. 37.7 23.0 .. 29.9 .. .. .. 16.1 16.7 22.9 .. .. .. .. 27.4 .. 30.0 26.2 24.7

2010

1990

.. .. 15.0 .. 12.1 .. .. .. .. .. .. 13.7 .. .. .. .. .. .. .. .. .. .. 22.4 .. .. .. .. .. .. 22.7 .. .. .. .. .. .. .. 31.7 .. .. .. .. .. .. 14.5 .. 17.2 .. .. .. .. 28.9 .. 30.6 27.0 ..

.. .. .. 19.1 .. .. -5.6 .. .. .. .. -6.5 .. .. .. .. -6.6 .. 2.1 .. .. .. .. -0.6 .. .. .. .. .. .. .. .. .. .. -5.4 .. .. .. .. .. .. .. .. .. .. .. .. -2.6 .. .. .. -2.0 .. .. -3.2 ..

Cash surplus or deficit 2000 2005

.. .. .. 19.1 .. .. -5.6 .. .. .. .. -6.5 .. .. .. .. -6.6 .. 2.1 .. .. .. .. -0.6 .. .. .. .. .. .. .. .. .. .. -5.4 .. .. .. .. .. .. .. .. .. .. .. .. -2.6 .. .. .. -2.0 .. .. -3.2 ..

-0.3 .. -0.6 .. -5.4 .. .. -3.0 .. .. .. -1.0 19.5 -6.7 .. .. -4.5 .. .. -1.4 .. .. 1.5 4.2 0.0 -4.7 .. -2.5 .. .. .. -0.1 -1.9 2.5 .. .. .. 2.5 -1.7 .. -0.2 .. .. .. -5.7 -0.8 -4.7 .. .. .. .. -6.5 .. -2.5 -2.8 -2.2

2010

.. .. -1.0 .. -5.7 .. .. .. .. .. .. 3.8 .. .. .. .. .. .. .. .. .. .. -5.9 .. .. .. .. .. .. -2.4 .. .. .. .. .. .. .. 1.5 .. .. .. .. .. .. 0.6 .. -1.5 .. .. .. .. -7.7 .. -2.6 -1.3 .. (continued)

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.32

Central government ﬁnances (continued) Share of GDP (%) Net incurrence of liabilities 1990

.. .. .. -0.8 .. .. .. .. .. .. .. 6.5 .. .. .. .. 5.1 .. .. .. .. .. .. -7.9 .. .. .. .. .. .. .. .. .. .. 3.3 .. .. .. .. .. .. .. .. .. .. .. 6.8 .. .. .. .. .. .. .. 3.6 ..

Domestic 2000 2005

.. .. .. .. .. .. .. .. .. .. .. 4.1 .. .. .. .. .. .. .. .. .. .. .. .. .. 1.3 .. -1.0 .. .. .. 1.0 .. .. .. .. 0.3 0.7 .. .. 1.6 .. .. .. .. 0.6 .. .. .. .. .. .. .. .. 0.5 ..

.. .. .. .. 0.4 .. .. 4.9 .. .. .. 1.7 .. -0.1 .. .. 4.3 .. .. -1.7 .. .. -0.5 .. 0.0 1.3 .. -1.0 .. .. .. 1.5 -0.6 -0.1 .. .. .. -8.1 .. .. 2.5 .. .. .. .. 1.2 .. .. -0.2 .. .. 15.4 .. -0.2 -0.2 ..

2010

.. .. -0.3 .. 2.6 .. .. .. .. .. .. -4.7 .. .. .. .. .. .. .. .. .. .. 4.9 .. .. .. .. .. .. -0.2 .. .. .. .. .. .. .. 17.0 .. .. .. .. .. .. -2.7 .. .. .. 2.3 .. .. 9.2 .. 2.3 -0.6 ..

1990

.. .. .. 0.0 .. .. 5.3 .. .. .. .. .. .. .. .. .. 2.0 .. .. .. .. .. .. 9.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.1 .. .. .. .. .. .. .. 1.8 ..

Foreign 2000 2005

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.7 .. 3.0 .. .. .. 0.7 .. .. .. .. 0.5 13.1 .. .. 0.3 .. .. .. .. 2.0 .. .. .. .. .. .. .. .. -0.2 ..

.. .. .. .. 4.8 .. .. 3.0 .. .. .. -1.5 .. 1.8 .. .. 1.0 .. .. 2.5 .. .. .. .. 0.0 3.9 .. 3.9 .. .. .. -0.3 2.6 .. .. .. .. 2.9 .. .. 0.1 .. .. .. .. 0.8 .. .. -0.3 .. .. -0.8 .. -0.3 0.8 ..

2010

.. .. 2.0 .. 3.5 .. .. .. .. .. .. 5.6 .. .. .. .. .. .. .. .. .. .. 1.9 .. .. .. .. .. .. 1.8 .. .. .. .. .. .. .. -1.6 .. .. .. .. .. .. 1.9 .. .. .. 0.2 .. .. 0.2 .. 2.1 -0.4 ..

1990

.. 3.2 2.0 2.8 1.1 3.8 4.6 1.9 2.0 0.7 0.4 3.7 18.6 11.7 .. .. 2.0 3.0 11.9 6.2 6.3 3.5 9.2 4.3 0.8 7.2 7.1 2.8 14.3 5.7 3.2 .. 4.0 11.7 0.8 .. 5.7 5.8 3.3 1.2 .. 0.4 4.0 4.2 5.3 3.4 6.1 5.4 10.5 14.2 2.4 7.1 .. 7.0 11.7 7.9

Total debt 2000 2005

3.9 18.7 3.3 1.2 1.8 2.6 5.5 3.0 1.5 1.8 1.6 0.6 1.4 9.8 .. 0.5 1.7 6.9 2.7 7.8 5.0 2.4 4.7 8.3 0.1 3.0 3.6 3.8 6.4 9.9 2.3 .. 1.5 4.0 2.1 .. 4.8 3.4 7.3 .. 2.9 2.0 2.0 1.6 2.3 1.2 5.7 6.3 5.0 8.2 2.4 1.8 .. 7.3 8.9 4.4

3.1 9.2 1.1 0.5 0.8 3.5 5.0 3.7 0.5 1.0 1.0 3.0 1.8 1.9 .. 1.8 0.8 2.2 4.5 2.6 5.6 1.1 2.9 5.8 0.2 1.6 2.8 1.9 3.0 3.6 1.2 .. 1.2 7.9 1.1 5.8 2.3 6.4 1.4 .. 1.3 1.5 1.3 0.9 1.0 1.9 3.9 4.1 4.6 5.8 2.2 2.5 .. 4.6 6.3 3.5

2010

1.2 2.8 0.7 0.5 0.6 0.2 0.9 2.2 0.1 0.9 0.8 2.0 1.6 1.7 .. 1.1 0.7 3.4 1.9 1.0 1.9 2.1 1.2 1.6 0.6 0.6 0.4 0.7 3.0 1.4 1.0 .. 0.5 0.2 0.3 0.8 2.4 5.0 0.6 .. 1.4 0.7 1.1 0.9 1.1 0.4 0.9 1.5 1.8 0.4 .. 1.4 .. 3.7 5.3 1.4

a. Data were reported on a cash basis and have been adjusted to the accrual framework.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.33

Central government expenses

1990

.. .. .. 35.2 .. .. 16.7 .. .. .. .. 56.3 .. .. .. .. 43.1 .. 28.3 .. .. .. .. 30.8 .. .. .. .. .. .. .. .. .. .. 35.3 .. .. .. .. .. .. .. .. .. .. .. .. 21.7 .. .. .. 22.4 .. .. 7.0 ..

Goods and services 2000 2005

.. .. .. .. .. .. .. .. .. .. .. 56.1 25.6 .. .. .. .. .. .. .. .. .. 21.3 .. .. 17.7 .. 37.6 .. .. .. 20.8 .. .. .. .. 26.0 24.6 14.9 .. 11.3 .. 26.1 .. .. 55.1 .. .. .. .. .. .. .. .. 8.6 ..

.. .. 28.1 .. 22.7 .. .. 21.3 .. .. .. 22.0 30.0 29.0 .. .. 18.8 .. .. 18.2 .. .. 23.4 27.7 36.4 .. .. 33.3 .. .. .. 16.3 29.3 18.5 .. .. .. 25.3 25.6 .. 12.0 .. .. .. 48.3 29.2 25.5 .. 8.6 .. .. 8.6 .. 15.2 7.2 ..

2009

Share of expense (%) Compensation of employees 1990 2000 2005 2009

1990

Interest payments 2000 2005

2009

.. .. 17.7 .. 19.1 .. .. 16.3 .. .. .. 21.0 .. 29.5 .. .. .. .. .. 16.5 .. .. 20.2 .. .. .. .. 30.6 .. 11.3 .. .. .. .. .. .. .. 37.2 24.3 .. 12.9 .. .. .. 24.2 31.2 19.5 .. 8.5 11.3 .. 8.0 .. 9.0 6.6 ..

.. .. .. 29.1 .. .. 55.6 .. .. .. .. 25.4 .. .. .. .. 48.1 .. 28.7 .. .. .. .. 38.6 .. .. .. .. .. .. .. .. .. .. 43.6 .. .. .. .. .. .. .. .. .. .. .. .. 40.9 .. .. .. 26.6 .. .. 31.4 ..

.. .. .. 2.8 .. .. 7.8 .. .. .. .. 7.4 .. .. .. .. 5.6 .. 21.4 .. .. .. .. 18.8 .. .. .. .. .. .. .. .. .. .. 7.9 .. .. .. .. .. .. .. .. .. .. .. .. 17.8 .. .. .. 16.3 .. .. 10.9 ..

.. .. .. .. .. .. .. .. .. .. .. .. 35.2 .. .. .. .. .. .. .. .. .. 17.8 .. .. 13.4 .. 8.0 .. .. .. 6.6 .. .. .. .. 10.7 17.4 22.0 .. 18.1 .. 2.4 .. .. 5.2 .. .. .. .. .. .. .. .. 12.1 ..

.. .. 3.3 .. 3.4 .. .. 5.3 .. .. .. 3.7 .. 8.7 .. .. .. .. .. 15.7 .. .. 10.3 .. .. .. .. 2.5 .. 13.2 .. .. .. .. .. .. .. 20.1 7.1 .. 7.2 .. .. .. 5.5 8.6 10.1 .. 5.6 1.4 .. 14.0 .. 3.7 7.5 ..

.. .. .. .. .. .. .. .. .. .. .. 27.1 27.8 .. .. .. .. .. .. .. .. .. 55.2 .. .. 40.7 .. 36.5 .. .. .. 51.2 .. .. .. .. 41.4 36.3 23.4 .. 15.6 .. 44.6 .. .. 12.3 .. .. .. .. .. .. .. .. 39.8 ..

.. .. 42.5 .. 42.7 .. .. 42.2 .. .. .. 19.7 30.0 38.7 .. .. 12.3 .. .. 40.1 .. .. 59.8 37.2 48.4 40.9 .. 32.6 .. .. .. 49.8 38.5 30.9 .. .. .. 37.1 27.9 .. 14.3 .. .. .. 30.8 13.1 36.4 .. 39.0 .. .. 28.5 .. 47.2 39.0 ..

.. .. 47.2 .. 45.8 .. .. 43.3 .. .. .. 32.1 .. 38.4 .. .. .. .. .. 40.0 .. .. 37.3 .. .. .. .. 34.4 .. 35.7 .. .. .. .. .. .. .. 26.8 27.7 .. 13.4 .. .. .. 40.3 14.2 43.8 .. 34.9 33.7 .. 24.6 .. 47.8 36.1 ..

.. .. 2.3 .. 5.5 .. .. 7.4 .. .. .. 13.4 18.2 12.2 .. .. 7.0 .. .. 16.0 .. .. 10.4 6.2 1.3 23.9 .. 4.4 .. .. .. 9.8 6.4 9.0 .. .. .. 14.2 15.3 .. 10.9 .. .. .. 6.5 8.9 19.4 .. 9.7 .. .. 20.2 .. 7.8 9.7 ..

(continued)

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.33

Central government expense (continued)

Share of expense (%) 1990

.. .. .. 31.8 .. .. 13.3 .. .. .. .. .. .. .. .. .. 11.2 .. 12.2 .. .. .. .. 8.9 .. .. .. .. .. .. .. .. .. .. 15.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 44.9 ..

Subsidies and other transfers 2000 2005

.. .. .. .. .. .. .. .. .. .. .. 1.0 10.9 .. .. .. .. .. .. .. .. .. 3.4 .. .. 9.7 .. 0.5 .. .. .. 10.4 .. .. .. .. 18.7 21.6 5.5 .. 52.9 .. 27.0 .. .. 27.4 .. .. .. .. .. .. .. .. .. ..

.. .. 1.3 .. 10.0 .. .. 23.5 .. .. .. 11.0 19.4 14.9 .. .. 41.8 .. .. 25.5 .. .. .. 28.9 13.9 .. .. .. .. .. .. 10.4 4.1 41.7 .. .. .. 22.7 19.1 .. 57.7 .. .. .. 1.7 48.5 18.0 .. 26.7 .. .. 26.7 .. 24.7 33.6 ..

2009

.. .. 29.7 .. 11.1 .. .. 30.1 .. .. .. 35.7 .. 16.3 .. .. .. .. .. 27.9 .. .. 31.3 .. .. .. .. 15.0 .. 30.0 .. .. .. .. .. .. .. 15.8 22.6 .. 62.9 .. .. .. 17.6 44.7 22.0 .. 41.0 45.4 .. 44.8 .. 26.6 37.2 ..

1990

.. .. .. 1.2 .. .. .. .. .. .. .. .. .. .. .. .. 0.2 .. 9.5 .. .. .. .. 2.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 5.8 ..

Other expense 2000 2005

.. .. .. .. .. .. .. .. .. .. .. 15.8 0.5 .. .. .. .. .. .. .. .. .. 2.2 .. .. 18.6 .. 17.5 .. .. .. 11.0 .. .. .. .. .. .. 34.3 .. 2.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

.. .. 25.9 .. 19.1 .. .. 5.6 .. .. .. 33.8 2.5 5.3 .. .. 20.1 .. .. 0.2 .. .. .. 0.0 .. 8.6 .. .. .. .. .. 13.8 21.7 .. .. .. .. 0.7 12.1 .. 6.1 .. .. .. 12.7 0.4 0.7 .. 10.5 .. .. 16.0 .. 5.2 10.5 ..

2009

.. .. 2.1 .. 20.7 .. .. 5.0 .. .. .. 7.6 .. 7.1 .. .. .. .. .. .. .. .. 0.9 .. .. .. .. 17.5 .. 9.7 .. .. .. .. .. .. .. 0.1 18.4 .. 4.4 .. .. .. 12.5 1.4 4.6 .. 10.7 8.3 .. 8.7 .. 12.9 12.7 ..

a. Data were reported on a cash basis and have been adjusted to the accrual framework.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.34

Central government revenues

1990

Interest payments 2000 2005

2009

.. .. .. 1.4 .. .. 8.0 .. .. .. .. 10.1 .. .. .. .. 7.2 .. 14.3 10.2 .. .. .. 10.8 .. .. .. .. .. .. .. 1.3 .. .. 7.3 .. .. .. 25.7 .. .. .. .. .. .. .. 7.1 17.7 .. .. .. 16.0 .. .. 10.6 ..

.. .. .. .. .. .. .. .. .. .. .. .. 24.1 .. .. .. .. .. .. .. .. .. 15.2 10.0 .. 9.3 .. 5.0 .. .. .. 6.2 .. .. .. .. 7.4 18.6 32.5 .. 19.1 .. 2.0 .. .. 4.7 .. .. .. .. .. .. .. .. 11.3 ..

.. .. 2.5 .. 2.2 .. .. 4.2 .. .. .. 2.0 .. 7.1 .. .. .. .. .. 15.2 .. .. 10.4 .. .. .. .. 1.7 .. 11.7 .. .. .. .. .. .. .. 16.4 8.3 .. 8.4 .. .. .. 4.0 7.7 8.5 .. 5.0 1.0 .. 15.2 .. 3.1 6.9 ..

.. .. 1.6 .. 3.7 .. .. 6.3 .. .. .. 8.8 6.5 15.9 .. .. 6.5 .. .. 12.1 .. .. 8.9 4.8 1.0 15.8 .. 3.0 .. .. .. 8.9 3.2 4.7 .. .. .. 11.7 16.5 .. 10.8 .. .. .. 7.1 7.7 17.9 .. 9.6 .. .. 22.4 .. 7.5 9.6 ..

Share of revenues (%) Taxes on income, profits and capital gains 1990 2000 2005 2010

.. .. .. 37.6 .. .. 18.9 .. .. .. .. 21.9 .. .. .. .. 28.2 .. 9.7 20.6 .. .. .. 8.7 .. .. .. .. .. .. .. 32.6 .. .. 14.0 .. .. .. 29.7 .. .. .. .. .. .. .. 39.5 43.7 .. .. .. 18.1 .. .. 12.3 ..

.. .. .. .. .. .. .. .. .. .. .. 10.2 .. .. .. .. .. .. .. .. .. .. 28.5 17.2 .. 11.7 .. 12.5 .. .. .. 31.8 .. .. .. .. 21.3 17.3 15.4 .. 51.7 .. 24.1 .. .. 9.9 .. .. .. .. .. .. .. .. 20.4 ..

.. .. 18.7 .. 16.0 .. .. 18.3 .. .. .. 4.8 4.9 15.4 .. .. 9.9 .. .. 20.8 .. .. 33.0 19.5 34.5 9.2 .. 14.5 .. .. .. 35.0 8.9 0.1 .. .. .. 12.5 15.1 .. 48.8 .. .. .. 18.9 16.6 30.1 .. 26.1 .. .. 23.8 .. 26.1 26.2 ..

.. .. 17.0 .. 13.8 .. .. 18.2 .. .. .. 10.5 .. 15.3 .. .. .. .. .. 22.6 .. .. 40.0 .. .. .. .. 19.5 .. 22.2 .. .. .. .. .. .. .. 19.2 17.0 .. 52.6 .. .. .. 16.7 22.0 35.5 .. 28.1 59.7 .. 27.8 .. 28.4 27.3 ..

1990

.. .. .. 1.8 .. .. 22.2 .. .. .. .. 15.1 .. .. .. .. 24.3 .. 28.3 26.8 .. .. .. 16.0 .. .. .. .. .. .. .. 23.9 .. .. 27.1 .. .. .. 22.1 .. .. .. .. .. .. .. 37.4 25.6 .. .. .. 12.8 .. .. 19.1 ..

Taxes on goods and services 2000 2005 2010

.. .. .. .. .. .. .. .. .. .. .. 14.2 15.5 .. .. .. .. .. .. .. .. .. 41.4 12.5 .. 21.6 .. 41.6 .. .. .. 22.7 .. .. .. .. 33.7 5.1 7.6 .. 33.1 .. 13.2 .. .. 29.4 .. .. .. .. .. .. .. .. 37.1 ..

.. .. 36.0 .. 37.3 .. .. 41.1 .. .. .. 9.4 6.4 .. .. .. 10.6 .. .. 35.9 .. .. 44.2 16.1 16.6 17.2 .. 38.0 .. .. .. 24.5 13.7 1.8 .. .. .. 33.7 11.9 .. 33.0 .. .. .. 48.3 37.1 29.4 .. 30.2 .. .. 23.7 .. 30.2 34.8 ..

.. .. 37.9 .. 36.2 .. .. .. .. .. .. 13.9 .. .. .. .. .. .. .. .. .. .. 40.1 .. .. .. .. .. .. 49.6 .. .. .. .. .. .. .. 35.8 .. .. .. .. .. .. 37.4 .. 32.3 .. 31.3 .. .. 22.1 .. 36.1 31.3 .. (continued)

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

2.34

Central government revenues (continued)

Taxes on international trade 1990 2000 2005 2010

1990

Share of revenues (%) Other taxes Social contributions 2000 2005 2010 1990 2000 2005 2009

.. .. .. 12.9 .. .. 15.5 .. .. .. .. 37.8 .. .. .. .. 14.3 .. 32.4 34.7 .. .. .. 43.7 .. .. .. .. .. .. .. 25.3 .. .. 20.5 .. .. .. 38.1 .. .. .. .. .. .. .. 17.2 17.1 .. .. .. 12.9 .. .. 27.5 ..

.. .. .. 0.1 .. .. 4.7 .. .. .. .. 1.1 .. .. .. .. 2.2 .. 0.4 .. .. .. .. 0.1 .. .. .. .. .. .. .. 0.9 .. .. 3.1 .. .. .. 0.2 .. .. .. .. .. .. .. 0.2 1.1 .. .. .. 10.2 .. .. 4.8 ..

.. .. .. .. .. .. .. .. .. .. .. 20.1 0.0 .. .. .. .. .. .. .. .. .. 0.5 .. .. 1.2 .. 5.0 .. .. .. 1.4 .. .. .. .. 3.3 1.6 .. .. 2.8 .. 4.1 .. .. 0.1 .. .. .. .. .. .. .. .. 4.4 ..

.. .. .. .. .. .. .. .. .. .. .. 14.5 5.0 .. .. .. .. .. .. .. .. .. 15.0 41.4 .. 39.6 .. 11.3 .. .. .. 35.1 .. .. .. .. 29.6 41.0 29.4 .. 3.0 .. 49.9 .. .. 21.8 .. .. .. .. .. .. .. .. 10.7 ..

.. .. 21.6 .. 12.6 .. .. 0.1 .. .. .. 10.5 2.6 57.1 .. .. 33.9 .. .. 14.0 .. .. 10.2 49.5 36.6 29.1 .. 12.4 .. .. .. 29.8 29.9 .. .. .. .. 15.7 23.5 .. 3.8 .. .. .. 21.7 7.2 9.4 .. 6.7 .. .. 5.8 .. 8.4 6.7 ..

.. .. 22.1 .. 11.0 .. .. .. .. .. .. 14.3 .. .. .. .. .. .. .. .. .. .. 10.6 .. .. .. .. .. .. 2.2 .. .. .. .. .. .. .. 16.8 .. .. .. .. .. .. 18.8 .. 8.3 .. 5.6 .. .. 4.9 .. 5.6 6.2 ..

.. .. 6.5 .. 2.1 .. .. .. .. .. .. 4.8 1.1 3.1 .. .. 0.5 .. .. .. .. .. 0.4 0.1 0.4 5.0 .. 6.1 .. .. .. 1.7 3.6 .. .. .. .. 0.0 .. .. 3.6 .. .. .. 5.9 0.2 0.2 .. 4.1 .. .. 3.8 .. 6.2 4.1 ..

.. .. 5.8 .. 1.9 .. .. .. .. .. .. 0.4 .. .. .. .. .. .. .. .. .. .. 1.0 .. .. .. .. .. .. 7.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 6.4 .. 0.2 .. 4.2 .. .. 4.0 .. 5.8 4.2 ..

.. .. .. .. .. .. 1.8 .. .. .. .. 1.0 .. .. .. .. 2.0 .. 0.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 5.4 .. .. .. .. .. .. .. .. .. .. .. 0.0 3.3 .. .. .. 14.5 .. .. 13.0 ..

.. .. .. .. .. .. .. .. .. .. .. .. 3.1 .. .. .. .. .. .. .. .. .. 0.0 .. .. .. .. .. .. .. .. 0.5 .. .. .. .. .. 13.8 .. .. 2.1 .. .. .. .. .. .. .. .. .. .. .. .. .. 17.0 ..

.. .. .. .. .. .. .. 10.2 .. .. .. .. 0.9 10.2 .. .. .. .. .. .. .. .. 0.2 .. .. .. .. .. .. .. .. 0.6 .. .. .. .. .. 19.4 .. .. 2.0 .. .. .. .. .. .. .. .. .. .. .. .. 13.5 17.5 ..

.. .. 2.4 .. .. .. .. 10.1 .. .. .. .. .. 6.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 6.7 .. .. .. .. .. .. .. 9.0 .. .. 2.2 .. .. .. .. .. .. .. .. .. .. .. .. 12.1 20.2 ..

Grants and other revenue 1990 2000 2005 2010

.. .. .. 47.6 .. .. 27.5 .. .. .. .. 23.1 .. .. .. .. 29.1 .. 28.9 10.4 .. .. .. 31.6 .. .. .. .. .. .. .. 17.2 .. .. 30.0 .. .. .. 9.9 .. .. .. .. .. .. .. 5.8 9.2 .. .. .. 31.6 .. .. 23.4 ..

.. .. .. .. .. .. .. .. .. .. .. 41.1 76.4 .. .. .. .. .. .. .. .. .. 14.7 28.9 .. 26.0 .. 29.5 .. .. .. 8.5 .. .. .. .. 12.2 21.3 47.7 .. 7.4 .. 8.7 .. .. 38.7 .. .. .. .. .. .. .. .. 10.5 ..

.. .. 17.2 .. 32.0 .. .. 30.3 .. .. .. 70.5 84.0 14.2 .. .. 45.2 .. .. 29.3 .. .. 12.1 14.8 11.9 39.5 .. 29.1 .. .. .. 8.4 43.9 98.1 .. .. .. 18.8 49.5 .. 8.8 .. .. .. 5.2 38.9 31.0 .. 15.7 .. .. 43.0 .. 15.7 10.8 ..

.. .. 15.5 .. 35.7 .. .. .. .. .. .. 59.6 .. .. .. .. .. .. .. .. .. .. 7.5 .. .. .. .. .. .. 13.6 .. .. .. .. .. .. .. 16.8 .. .. .. .. .. .. 26.6 .. 15.1 .. 14.1 .. .. 43.8 .. 14.1 10.0 ..

a. Data were reported on a cash basis and have been adjusted to the accrual framework.

Part I. Basic indicators and national and fiscal accounts

NATIONAL AND FISCAL ACCOUNTS

Table

2.35

Structure of demand Share of GDP (%)

Household final consumption expenditure 1990 2000 2010a

SUB-SAHARAN AFRICA 65.2 68.4 64.9 Excluding South Africa 72.3 73.4 .. Excl. S. Africa & Nigeria 72.3 73.4 71.0 Angola 35.8 .. 50.4 Benin 86.8 82.4 .. Botswana 33.2 30.8 56.6 Burkina Faso 73.5 78.5 .. Burundi 94.6 92.0 80.8 Cameroon 66.6 70.2 .. Cape Verde 58.5 72.1 55.6 Central African Republic 85.7 80.8 .. Chad 97.6 86.8 76.1 Comoros 78.7 94.0 .. Congo, Dem. Rep. 79.1 88.0 .. Congo, Rep. 62.4 29.1 38.6 Côte d'Ivoire 71.9 74.9 72.5 Equatorial Guinea 80.3 20.9 .. Eritrea .. 79.1 .. Ethiopia 77.2 73.8 89.4 Gabon 49.7 32.2 38.2 Gambia, The 75.6 89.0 88.0 Ghana 85.2 84.3 75.5 Guinea 66.9 77.8 76.5 Guinea-Bissau 86.9 94.6 .. Kenya 62.8 77.7 74.4 Lesotho 123.3 83.4 104.8 Liberia .. 85.7 131.3 Madagascar 86.4 83.2 .. Malawi 71.5 81.6 71.7 Mali 79.8 79.4 .. Mauritania 69.2 74.5 71.2 Mauritius 63.4 60.3 73.6 Mozambique 92.3 80.6 81.4 Namibia 51.2 63.1 49.0 Niger 83.8 83.4 .. Nigeria .. .. .. Rwanda 83.7 87.7 83.3 São Tomé and Príncipe .. .. .. Senegal 79.2 76.0 80.5 Seychelles 52.0 53.9 .. Sierra Leone 83.5 100.0 84.4 Somalia .. .. .. South Africa 57.1 63.0 59.4 Sudan 86.1 76.5 60.6 Swaziland 80.5 77.3 75.5 Tanzania 81.0 78.3 64.7 Togo 71.1 87.6 .. Uganda 91.9 77.5 75.0 Zambia 64.4 87.4 55.2 Zimbabwe 63.1 59.9 107.7 NORTH AFRICA 64.1 61.2 .. Algeria 56.8 41.6 .. Djibouti 78.9 76.8 .. Egypt, Arab Rep. 72.6 75.9 74.7 Libya 48.4 45.7 .. Morocco 64.6 61.5 57.3 Tunisia 63.6 60.6 62.7 AFRICA 64.7 65.1 66.5

General government final consumption expenditure 1990 2000 2010a

15.6 13.3 13.3 .. 11.6 25.4 20.8 15.5 9.5 30.7 14.0 7.7 11.7 7.5 11.6 7.2 4.6 63.8 17.9 9.6 11.2 10.2 6.8 14.0 15.1 41.7 7.5 9.0 14.6 8.6 20.2 14.1 9.0 23.5 13.0 .. 11.0 .. 12.8 24.2 14.3 .. 18.2 7.6 18.2 11.7 10.5 14.5 9.5 24.3 14.6 13.6 29.7 11.2 20.8 18.4 16.7 15.1

Gross fixed capital formation 1990 2000 2010a

Exports of goods and services 1990 2000 2010a

16.3 17.3 17.3 15.1 18.9 25.8 18.7 4.2 16.0 30.5 9.5 20.9 10.1 3.5 20.9 11.2 61.3 23.8 20.3 21.9 4.6 23.1 18.9 11.3 16.7 42.5 7.5 15.0 12.3 24.6 16.2 22.9 31.0 16.6 11.2 .. 18.3 .. 22.4 25.2 6.9 .. 15.1 12.1 18.1 16.4 14.5 19.2 16.0 11.8 20.1 20.7 8.8 18.9 13.1 26.0 25.2 18.0

32.4 35.6 31.5 89.6 15.2 53.3 9.1 6.6 23.3 27.0 19.8 16.9 16.7 22.4 80.3 40.4 98.6 15.1 12.0 69.0 25.8 48.8 23.6 31.8 21.6 34.2 26.1 30.7 25.6 26.8 30.0 61.4 16.5 40.9 17.8 54.0 8.7 .. 27.9 78.2 18.1 .. 27.9 15.3 74.3 13.4 34.4 10.7 27.1 38.2 27.9 41.2 35.1 16.2 35.6 28.0 39.6 30.5

Imports of goods and services 1990 2000 2010a

31.2 25.4 30.6 34.0 34.3 30.2 34.8 39.0 33.4 30.5 35.4 40.9 62.3 20.9 62.8 43.0 14.3 26.3 28.1 28.1 33.0 49.8 41.2 40.0 .. 24.5 25.2 .. 6.1 27.8 16.9 36.5 28.9 17.3 19.7 32.0 38.6 0.0 60.5 67.1 .. 27.6 24.1 .. 39.0 27.9 34.7 61.0 .. 37.2 32.5 .. 26.0 29.2 21.4 38.9 85.1 45.8 43.6 54.7 40.6 27.1 33.3 36.1 .. 69.6 85.4 .. .. .. 81.8 .. 11.4 8.9 24.0 32.5 61.3 30.9 32.7 36.0 21.9 71.6 30.6 38.9 29.4 25.9 67.3 41.2 34.8 33.4 27.9 39.3 .. 37.0 51.6 .. 27.5 31.3 31.7 37.9 43.8 123.2 103.4 113.9 25.0 .. 26.9 109.5 .. 28.0 38.0 .. 30.6 33.4 35.3 47.2 .. 33.7 39.4 .. 62.0 60.7 45.3 73.6 52.5 72.2 61.9 63.8 26.3 36.1 37.0 45.0 42.6 67.4 44.6 41.3 .. 22.0 25.7 .. 37.9 28.8 32.0 31.2 10.9 14.1 25.7 30.6 .. .. .. .. 24.8 32.2 37.2 43.0 .. 66.7 81.4 .. 17.1 23.8 39.3 29.5 .. 37.7 .. .. 27.3 18.8 24.9 27.5 19.8 7.1 17.7 18.9 54.8 68.9 88.0 68.2 26.1 37.5 20.1 37.8 37.3 45.3 47.6 53.8 23.8 19.4 22.1 33.9 44.1 36.6 41.5 35.0 48.3 22.8 35.9 78.0 28.4 32.4 24.9 30.7 30.8 24.9 21.4 21.5 .. 78.4 50.4 .. 21.4 32.7 22.8 26.1 .. 31.1 15.5 .. 33.0 31.9 33.4 42.9 48.8 50.6 42.9 54.1 30.1 28.4 28.2 32.7

Gross national savings 1990 2000 2010a

15.6 15.5 15.5 23.8 10.4 41.4 5.1 1.1 15.3 19.6 .. .. .. .. 30.6 8.0 .. 4.4 15.9 41.7 .. 15.3 15.4 .. 13.5 37.3 .. 8.8 9.5 15.9 .. 26.3 10.4 25.4 5.3 .. 12.9 .. 13.8 18.5 -3.7 .. 15.8 9.3 13.3 13.2 5.0 14.4 -1.4 .. .. .. 5.4 18.1 .. 24.3 22.2 17.2

a. Provisional

NATIONAL AND FISCAL ACCOUNTS

Part I. Basic indicators and national and fiscal accounts

Table

3.1

Millennium Development Goal 1: eradicate extreme poverty and hunger Poverty headcount ratio at $1.25 a day (PPP) (% of population) Surveys Surveys 1990–99c 2000–11c Year Percent Year Percent

SUB-SAHARAN AFRICA Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somalia South Africa Sudan South Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco Tunisia

1994 1998 1998 1996 1992

1998

1995 .. 1998 1998 1994 1993 1997 1994 1999 1998 1994 1996 1996 1993 1994 1996

1994 1990 1995

1995 1992 1999 1998

1995 1996 1999 1995

.. .. 31.2 70.0 86.4 24.9 .. 83.2 .. .. .. .. 24.1 .. .. 60.5 .. 65.6 39.1 63.8 52.1 19.6 46.2 .. 82.3 83.1 86.1 23.4 .. 80.6 49.1 78.2 68.5 .. .. 53.6 .. 62.8 .. 21.4 .. .. 78.6 72.6 .. 60.5 55.7 .. 6.8 .. 2.5 .. 6.8 6.5

Part II. Millennium Development Goals

2000 2003 2009 2006 2007 2002 2008 2003 2004 2006 2005 2008

2005 2005 2003 2006 2007 2002 2005 2003 2007 2010 2004 2010 2008 2008 2004 2008 2010 2011 2001 2005 2007 2003 2009 2009 2010 2007 2006 2009 2006

2002 2008 2007 2005

54.31 47.3 .. 44.6 81.3 9.6 21.0 62.8 61.9 46.1 87.7 54.1 23.8 .. .. 39.0 4.8 33.6 28.6 43.3 48.9 43.4 43.4 83.8 81.3 73.9 50.4 23.4 .. 59.6 31.9 43.6 68.0 63.2 28.2 33.5 0.3 53.4 .. 13.8 19.8 .. 40.6 67.9 38.7 38.0 68.5 .. .. 18.8 1.7 .. 2.5 1.4

International poverty linea Poverty gap at $1.25 a day Poverty headcount ratio at $2 (PPP) (%) a day (PPP) (% of population) Surveys Surveys Surveys Surveys c c 1990–99 2000–11 1990–99c 2000–11c Year Percent Year Percent Year Percent Year Percent

1994 1998 1998 1996 1992

1998

1995 1998 1998 1994 1993 1997 1994 1999 1998 1994 1996 1996 1993 1994 1996

1994 1990 1995

1995 1992 .. 1999 1998

1995 1996 1999 1995

.. .. 11.0 30.2 47.3 6.3 .. 57.4 .. .. .. .. 6.7 .. .. 21.2 .. 33.8 14.4 29.7 20.6 4.6 25.6 .. 44.3 46.0 53.1 7.1 .. 41.2 24.6 38.6 32.1 .. .. 19.2 .. 44.8 .. 5.2 .. .. 47.7 29.7 .. 24.5 26.9 .. 1.4 .. 0.3 .. 1.2 1.3

2000 2003 2009 2006 2007 2002 2008 2003 2004 2006 2005 2008

2005 2005 2003 2006 2007 2002 2005 2003 2007 2010 2004 2010 2008 2008 2004 2008 2010 2011 2001 2005 2007 2003 2009 2009 2010 2007 2006 2009 2006

2002 2008 2007 2005

29.94 15.7 .. 14.7 36.4 1.2 6.1 31.3 25.6 20.8 52.8 22.8 7.5 .. .. 9.6 0.9 11.7 9.9 15.0 16.6 16.9 20.8 40.9 43.3 32.3 16.4 6.8 .. 25.1 9.5 12.4 33.7 26.6 7.9 10.8 0.1 20.3 .. 2.3 5.5 .. 16.0 28.1 11.4 12.2 37.0 .. .. 5.3 0.4 .. 0.5 0.3

1994 1998 1998 1996 1992

1998

1995 1998 1998 1994 1993 1997 1994 .. 1999 1998 1994 1996 1996 1993 1994 1996

1994 1990 1995

1995 1992 1999 1998

1995 1996 1999 1995

.. .. 49.4 87.6 95.4 51.8 .. 91.0 .. .. .. .. 49.2 .. .. 84.6 .. 81.2 63.3 81.7 75.7 42.7 59.7 .. 93.1 93.5 93.9 48.3 .. 92.6 62.2 91.6 86.4 .. .. 79.1 .. 75.0 .. 39.9 .. .. 89.3 91.3 .. 82.7 74.8 .. 23.6 .. 26.3 .. 24.4 20.4

2000 2003 2009 2006 2007 2002 2008 2003 2004 2006 2005 2008

2005 2005 2003 2006 2007 2002 2005 2003 2007 2010 2004 2010 2008 2008 2004 2008 2010 2006 2001 2005 2007 2003 2009 2009 2010 2007 2006 2009 2006

2002 2008 2007 2005

70.21 75.3 .. 72.6 93.5 30.4 40.9 80.1 83.3 65.0 95.2 74.4 46.3 .. .. 77.6 19.6 55.9 51.8 69.6 78.0 67.2 62.3 94.9 92.6 90.5 78.7 47.7 .. 81.8 51.1 75.2 84.5 87.4 54.2 60.4 1.8 76.1 .. 31.3 44.1 .. 60.4 87.9 69.3 64.7 82.6 .. .. 41.2 15.4 .. 14.0 8.1

Poverty gap at $2 a day (PPP) (%) Surveys Surveys c 1990–99 2000–11c Year Percent Year Percent

1994 1998 1998 1996 1992

1998

1995 1998 1998 1994 1993 1997 1994 1999 1998 1994 1996 1996 1993 1994 1996

1994 1990 1995

1995 1992 1999 1998

1995 1996 1999 1995

.. .. 22.3 49.1 64.1 18.4 .. 68.8 .. .. .. .. 18.2 .. .. 41.2 .. 49.1 28.5 46.3 37.4 14.7 36.1 .. 61.0 62.3 67.2 17.8 .. 58.7 36.5 56.5 49.7 .. .. 37.6 .. 54.0 .. 15.0 .. .. 61.7 50.1 .. 42.9 41.7 .. 6.5 .. 5.0 .. 6.5 5.8

2000 2003 .. 2009 2006 2007 2002 2008 2003 2004 2006 2005 2008 .. .. 2005 2005 2003 2006 2007 2002 2005 2003 2007 2010 2004 2010 2008 2008 2004 2008 2010 2006 2001 2005 2007 2003 2009 2009 2010 2007 2006 2009 2006

.. 2002 2008 2007 2005

42.35 33.5 .. 31.7 56.1 8.2 15.2 46.8 43.9 34.2 67.6 38.8 17.8 .. .. 28.9 5.0 24.4 21.3 31.0 34.9 31.8 33.1 59.6 60.1 51.8 35.2 17.7 .. 42.9 21.8 30.8 50.2 52.2 20.6 24.7 0.4 37.5 .. 10.2 15.4 .. 29.3 47.5 27.9 27.4 51.8 .. .. 14.6 2.8 .. 3.2 1.8

MILLENNIUM DEVELOPMENT GOALS

Share of population below national poverty line (poverty headcount ratio) Surveys 1990–99c Surveys 2000–11c Year Percent Year Percent

1993

1998 1993 1995

1998

1994 1999 1998

1996

1995

1999 1998

1995 1996

1995

.. .. 32.9 .. .. .. .. .. .. .. .. .. 36.4f .. 69.0 45.5 .. .. 39.5 .. .. .. 66.6f .. 71.3 65.3 .. .. .. 69.4 .. .. .. .. .. .. .. .. .. 31.0 .. .. .. .. .. 33.8 66.8 .. 22.6 .. 19.4 .. .. 6.2

2007e 2003 2009e 2006e 2007e 2007e 2008e 2003e 2004 2006 2005 2008 2006 2011 2005 2010e 2006 2007e 2002e 2005e 2003 2007 2005 2010 2010e 2008e 2008 2004e 2007e 2004e 2011e 2009e 2011e .. 2003 2006 2009e 2009e 2001e 2007e 2011e 2009 2010 2003e

2008 2007 2005

.. 33.3 30.6 46.7 66.9 39.9 26.6 62.0 55.0 44.8 71.3 50.1 42.7f 76.8 .. 29.6 32.7 48.4 28.5 53.0 64.7 45.9 56.6f 63.8f 68.7 50.7 43.6 42.0 .. 54.7 38.0 59.5 54.7 44.9 66.2 46.7 .. 66.4 .. 23.0 46.5 50.6 69.2 33.4 58.7 24.5 60.5 72.0 .. .. 22.0 .. 9.0 3.8

National poverty linea Share of urban population below national poverty line (poverty headcount ratio) Surveys 1990–99c Surveys 2000–11c Year Percent Year Percent

1993

1998 1993 1995

1998

1994 1999 1998

1996

.. .. 24.7 .. .. .. .. .. .. .. .. .. 28.6f .. 62.0 33.2 .. .. 19.4 .. .. .. 36.7f .. 52.1 54.9 .. .. .. 62.0 .. .. .. .. .. .. .. .. .. .. .. .. .. ..

1999 1998

1995

.. 9.6 39.5 .. 14.7 .. .. .. .. ..

2000e 2007 2003 2009e 2006e 2007e 2007e 2008e 2003e 2004 2006 2008 2006 2011 2005 2010 2006 2007e 2002e 2005e 2003 2007 2005 2010 2010e 2008e 2008 2004e 2007e 2004e 2011e 2001e 2011e 2003

2009e 2009e 2001e 2007e 2011e 2009 2010

2008 2007

62.3 28.3 19.4 27.9 34.0 12.2 13.2 49.6 24.6 34.5 61.5 .. 29.4f 31.5 .. 25.7 29.8 32.7 10.8 30.5 51.6 33.7 41.5f 55.1f 52.0 17.3 18.9 20.8 .. 49.6 17.0 36.7 43.1 22.1 45.0 33.1 .. 47.0 .. .. 26.5 24.2 49.0

Share of rural population below national poverty line (poverty headcount ratio) Surveys 1990–99c Surveys 2000–11c Year Percent Year Percent

1993

1998

1995

1998

1994 1999 1998

1996

21.8

34.6 9.1 27.5 … .. .. 10.6 .. 4.8 ..

1999 1998

1995

.. .. 40.4 .. .. .. .. .. .. .. .. .. 41.5f .. .. 47.5 .. .. 49.6 .. .. .. 68.9f .. 76.7 66.5 .. .. .. 71.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 37.4 83.0 .. 30.3 .. .. .. .. ..

2007 2003 2009e 2006e 2007e 2007e 2008e 2003e 2004 2006 2008 2006 2011 2005 2010 2006 2007e 2002e 2005e 2003 2007 2005 2010 2010e 2008e 2008 2004e 2007e 2004e 2011e 2001e 2011e 2003

2009e 2009e 2001e 2007e 2011e 2009 2010

2008 2007

.. 36.1 44.8 52.6 68.9 55.0 44.3 69.4 58.6 48.7 75.7 .. 54.2f 79.9 .. 30.4 44.6 73.9 39.2 63.0 69.1 49.1 60.5f 67.7f 73.5 56.6 50.6 59.4 .. 56.9 49.0 63.9 63.8 48.7 64.9 57.1 .. 78.5 .. .. 57.6 55.4 75.0 37.4 73.4 27.2 77.9 .. .. .. 30.0 .. 14.5 .. (continued)

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

Table

3.1

Millennium Development Goal 1: eradicate extreme poverty and hunger (continued)

Share of poorest quintile in national consumption or incomeb Surveys 1990–99c Surveys 2000–11c Year Percent Year Percent

SUB-SAHARAN AFRICA Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somalia South Africa Sudan South Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco Tunisia

1994

1998

1995

1998

1994 1999 1998

1996

1995

1999 1998

1995 1996

1995

.. .. 3.1 .. .. .. .. .. .. .. .. .. 5.8 .. .. 7.2 .. .. 5.6 .. .. .. 1.5 .. 5.9 4.8 .. .. .. 5.6 .. .. .. .. .. .. .. .. .. 3.6 .. .. .. .. .. 5.9 3.4 .. 7.0 .. 9.5 .. .. 5.7

2000 2003 2009 2006 2007 2002 2008 2003 2004 2006 2005 2008

2005 2005 2003 2006 2007 2002 2005 2003 2007 2010 2004 2010 2008 2008 2004 2008 2010 2011 2001 2005 2007 2003 2009 2009 2009 2010 2007 2006 2009 2006

2002 2008 2007 2005

2.0 7.0 .. 6.7 9.0 6.7 4.5 3.4 6.3 2.6 5.5 5.0 5.6 .. .. 9.3 6.2 4.8 5.2 6.4 7.3 4.8 3.0 6.4 5.4 7.0 8.0 6.0 .. 5.2 3.2 8.1 4.4 5.2 5.2 6.2 3.7 6.1 .. 2.7 6.8

Prevalence of child malnutrition, underweight (% of children under age 5) Surveys 1990–99c Surveys 2000–11c Year Percent Year Percent

1996 1996 1996 1999

1999 1993

37 26.8 15.1 33.7 .. 17.8 11.8 23.3 34.3 22.3 30.7 .. 18.2 13.8 38.3 .. .. 23.2 20.3 21.2 .. 17.6 18.9 .. 35.5 26.3 38.2 20.3 13.0 28.1 21.5 45.0 27.3 24.2 .. 19.6 .. 25.4 .. 10.1 31.8

4.1 6.8 7.6 5.8 3.6 ..

1999 1998 1995 1999 1999

.. 6.0 9.2 .. 6.5 5.9

1995 1996 1998 1995 1997 1997

1998 1994 1995 1997 1996 1995 1999 1997 1996

1996 1999 1999 1998 1993 1997 1998 1996 1996 1995 1997 1992 1998 1999 1996 1996 1990

2007 2006 2008 2009 2005 2006

Population below minimum dietary energy consumption Share (%) Total (millions) 2006–08d 2006–08d

2008 2006 2008 2006

15.6 20.2 11.2 26.0 35.2 16.6 .. 28.0 33.9 25.0 28.2 11.8 29.4 10.6 34.5 34.6 8.8 15.8 14.3 20.8 17.2 16.4 13.5 20.4 36.8 13.8 27.9 15.9 .. 18.3 17.5 39.9 26.7 18.0 14.4 14.5 .. 21.3 32.8 8.7 31.7

41 12 25 8 62 22 11 40 39 47 .. 13 14 .. 65 41 5 19 5 16 22 33 14 32 25 27 12 8 5 38 18 16 6 32 5 19 8 35 .. 5 22

7.2 1.0 0.5 1.2 4.9 4.2 0.1 1.7 4.1 0.4 36.7 0.5 2.9 .. 3.1 32.6 .. 0.3 1.1 1.6 0.3 12.4 0.3 1.1 4.7 3.9 1.5 0.2 0.1 8.3 0.4 2.3 9.4 3.0 0.0 2.3 0.0 1.9 .. .. 8.8

.. 25.3 23.2 21.5 19.6 11.5

2008 2010 2008 2006 2007 2006

7.3 16.2 20.5 16.4 14.9 14.0

11.3 16.0 10.2 4.2 7.7 3.3

2005 2006 2008 2007 2004 2006

3.7 29.6 6.8 5.6 9.9 3.3

19 34 30 22 44 30 5 <5 26 <5 <5 <5 <5

0.2 13.9 1.9 6.7 5.4 3.7 0.2 1.4 0.2 .. .. 1.6 ..

2006 2004 2000 2007 2005 2007 2004 2002 2005 2001 2006 2008 2008 2008 2009 2010 2007 2004 2010 2006 2008 2008 2007 2006 2008 2005 2009 2005

National poverty estimates for Côte d’Ivoire, Gambia, Lesotho, Liberia, and Senegal are World Bank estimates. a. Based on nominal per capita consumption expenditure average and distributions estimated from household survey data. 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 most recent year available during the period speciﬁed. d. Data for a 3-year period have been used for the estimation of the prevalence of undernourishment. e. Poverty estimates based on survey data from earlier year(s) are available, but not comparable with the most recent year reported here. f. World Bank estimates.

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Table

3.2

Millennium Development Goal 2: achieve universal primary education

Net primary enrollment ratio (% of relevant age group) 1990 2000 2010

Primary completion rate (% of relevant age group) 1990 2000 2010

Share of cohort reaching grade 5 (% of grade 1 students) 1990 2000 2008–09a

Youth literacy rate (% ages 15–24) 1991 2000 2009

.. 41.2 86.9 .. .. 71.1 92.7 57.9 .. .. .. .. .. .. .. .. .. 51.4 .. 24.9 .. .. 70.7 .. 70.3 .. .. .. 97.2 44.0 79.1 22.8 .. .. 96.1 45.1 .. .. .. .. .. 74.3 51.4 62.3 .. .. ..

.. .. 80.9 34.1 44.7 .. 98.9 .. 54.5 73.5 .. .. 56.0 72.1 37.7 40.3 .. 66.9 64.2 46.6 51.0 65.1 76.0 .. 67.0 .. .. 61.1 92.5 56.0 88.1 27.0 64.5 .. .. 59.6 .. .. .. 89.7 40.2 71.8 53.1 87.0 .. 70.3 ..

85.7 93.8 .. 58.1 .. 92.4 93.2 70.5 .. .. .. 90.8 .. 56.3 33.5 81.3 .. 65.5 .. 77.0 73.9 .. 73.4 .. .. .. 62.0 74.0 93.4 91.9 .. 57.2 57.6 98.8 98.4 75.5 .. .. .. .. .. 85.6 .. .. 90.9 91.4 ..

.. 19.5 89.8 19.3 40.9 54.2 53.6 30.4 16.3 .. .. 58.8 40.1 .. .. .. .. .. .. 18.8 .. .. 58.4 .. 37.0 28.1 .. 29.1 113.7 26.5 .. 15.8 .. 49.2 77.9 42.0 .. .. .. .. .. 62.7 .. 35.0 .. .. 93.6

.. 39.8 89.1 23.8 26.3 51.0 107.2 .. 22.9 .. .. .. 42.7 .. 36.2 23.0 .. 66.6 71.1 32.3 29.7 .. 59.8 .. 37.1 65.5 29.4 .. 95.6 16.2 91.4 18.7 .. 22.9 .. 40.3 106.6 .. .. 86.4 36.7 60.7 .. 69.0 .. 62.7 ..

46.6 .. .. 45.1 56.1 78.7 98.9 41.1 34.5 .. 58.7 70.8 .. 52.4 39.8 72.2 .. 70.5 .. 64.1 67.6 .. 69.6 .. 72.5 66.8 54.8 74.8 96.0 60.6 .. 41.2 74.4 69.6 85.3 59.2 133.2 .. .. .. .. 76.9 89.9 73.7 57.2 103.3 ..

.. 27.3 75.7 55.6 57.2 66.6 53.0 42.7 35.6 .. .. 70.6 60.8 .. .. .. .. .. .. 50.6 .. .. 66.3 .. 34.0 32.3 .. 63.8 .. 33.8 .. 57.0 .. 51.5 .. 72.8 .. .. .. .. .. 60.0 .. 44.5 .. .. 68.7

.. 84.2 89.0 69.1 58.8 .. 89.2 .. 54.9 .. .. .. 88.0 .. 60.5 64.6 .. 73.0 66.3 .. .. .. 67.2 .. 36.1 .. .. .. 98.4 52.5 90.9 74.0 .. 41.7 .. 72.3 91.0 .. .. .. .. 74.0 81.4 74.7 57.1 .. ..

44.8 60.4 96.6 75.1 62.4 76.3 .. 56.3 36.5 .. 60.0 .. 66.1 69.6 69.0 50.5 .. 65.1 78.4 68.6 .. .. 80.4 .. 34.6 60.9 84.0 74.3 98.0 53.7 91.5 64.3 86.3 47.2 77.4 73.7 94.9 .. .. .. .. 96.2 89.8 77.7 57.1 71.0 ..

.. .. 89.3 20.2 53.6 .. 88.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 91.2 .. 88.1 .. 71.2 74.9 93.9 .. .. .. .. .. .. .. .. .. 69.8 .. ..

.. .. .. .. 73.3 83.1 .. 58.5 37.6 80.2 .. .. 60.7 94.9 .. .. .. 52.6 70.7 .. 59.5 80.3 90.9 .. 70.2 .. .. 61.3 94.5 .. .. .. .. 77.6 .. .. .. .. .. .. .. 88.4 .. 74.4 .. .. ..

73.1 54.3 95.2 .. 76.6 .. 98.2 64.7 46.3 85.3 67.7 .. 66.6 97.9 88.7 .. 97.6 65.5 80.1 61.1 70.9 92.7 92.0 75.6 .. 86.5 .. 67.7 96.5 70.9 93.0 .. 71.8 77.2 95.3 65.0 .. 57.6 .. .. .. 93.4 77.4 .. .. 74.6 98.9

87.5 29.3 .. .. 56.2 92.6

91.6 26.7 90.4 .. 76.2 95.6

95.6 .. 94.4 .. 93.7 ..

80.8 32.0 .. .. 51.4 80.3

82.4 27.8 94.3 .. 57.4 88.2

96.0 .. 101.0 .. 84.7 ..

83.8 73.9 .. .. 68.9 80.0

97.1 .. .. .. 80.0 93.1

95.0 64.3 97.2 .. 93.9 96.1

.. .. .. .. .. ..

.. .. .. 99.9 79.5 ..

a. Data are for the most recent year available during the period speciﬁed.

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

Table

3.3

Millennium Development Goal 3: promote gender equity and empower women

Ratio of girls to boys in primary and secondary school (%) 1990 2000 2010

Ratio of young literate women to men (% ages 15–24) 1990 2000 2009

Women in national parliament (% of total seats) 1990 2000 2010

Share of women employed in the nonagricultural sector (%) 1990 2000 2000-10a

.. .. 108.0 .. 79.0 82.3 94.0 59.1 40.9 .. .. 88.5 .. .. .. .. .. .. 78.0 44.0 .. .. 123.8 .. 95.6 80.9 57.6 68.9 100.4 72.7 110.8 53.0 76.5 94.8 .. 67.4 .. 61.8 .. 103.5 .. .. 97.1 58.1 77.9 .. 96.4

.. 60.9 101.7 70.2 .. .. .. .. 55.9 84.2 .. 85.8 69.3 81.3 77.3 65.0 95.9 .. 90.2 .. 65.4 97.6 107.5 73.3 .. 92.8 71.1 93.1 98.1 75.0 103.7 65.1 82.0 96.6 .. 82.3 103.0 .. .. 100.4 .. 96.1 .. 69.1 91.1 .. ..

78.9 .. .. 87.7 93.9 85.4 104.2 69.4 65.8 .. 78.5 .. .. .. 80.1 88.8 .. 99.4 .. .. .. .. 106.1 .. .. 101.3 81.9 101.2 100.1 89.0 .. 78.3 90.1 101.9 100.4 100.0 104.0 .. .. .. .. 94.0 .. .. 98.5 .. ..

.. .. .. .. 80.7 .. 96.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 101.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 97.4 ..

.. .. .. .. 91.7 88.2 .. 66.6 41.7 92.4 .. .. 73.6 100.2 .. .. .. 64.3 86.2 .. 61.4 101.1 114.9 .. 93.9 .. .. 81.9 101.8 .. .. .. .. 97.9 .. .. .. .. .. .. .. 103.2 .. 76.0 .. .. ..

81.1 66.9 103.2 .. 99.2 .. 101.7 79.4 72.8 98.7 84.8 .. 84.6 100.5 93.6 .. 98.0 84.5 97.3 79.1 81.3 101.8 114.4 114.9 .. 99.0 .. 90.8 102.1 81.6 104.2 .. 83.6 100.5 101.0 75.7 .. 71.1 .. .. .. 103.2 97.3 .. .. 82.3 101.1

15.0 3.0 5.0 .. .. 14.0 12.0 4.0 .. 0.0 5.0 14.0 6.0 13.0 .. .. 13.0 8.0 .. .. 20.0 1.0 .. .. 7.0 10.0 .. .. 7.0 16.0 7.0 5.0 .. 17.0 12.0 13.0 16.0 .. 4.0 3.0 .. 4.0 .. 5.0 12.0 7.0 11.0

16.0 6.0 .. 8.0 6.0 6.0 11.0 7.0 2.0 .. .. 12.0 .. 5.0 15.0 2.0 8.0 2.0 9.0 9.0 .. 4.0 4.0 .. 8.0 8.0 12.0 4.0 8.0 .. 22.0 1.0 .. 17.0 9.0 12.0 24.0 9.0 .. 30.0 .. 3.0 16.0 .. 18.0 10.0 14.0

38.6 10.8 7.9 15.3 32.1 13.9 18.1 9.6 5.2 3.0 8.4 7.3 8.9 10.0 22.0 27.8 14.7 7.5 8.3 .. 10.0 9.8 24.2 12.5 .. 20.8 10.2 22.1 18.8 39.2 24.4 .. 7.0 56.3 18.2 22.7 23.5 13.2 6.8 44.5 25.6 13.6 30.7 11.1 31.5 14.0 15.0

.. .. 33.5 23.0 14.3 .. .. .. 3.8 .. 25.9 26.1 .. 10.5 .. .. .. .. .. .. 10.8 21.4 .. .. .. 10.5 .. .. 37.4 11.4 .. .. .. .. .. .. .. .. 21.7 .. 22.2 .. .. 41.0 .. 16.6 15.4

.. .. 42.9 23.2 .. .. 38.9 .. .. .. .. .. .. .. .. .. .. .. 31.7 24.2 .. .. .. .. .. .. .. 35.8 38.6 .. 42.8 .. 18.6 33.0 .. .. .. .. .. 41.1 .. .. .. .. .. 22.0 20.4

.. 24.3 45.2 26.5 .. 22.2 38.9 46.8 .. .. .. .. .. .. .. 47.3 .. .. 31.7 28.5 .. .. .. 11.4 37.7 .. 34.6 35.8 36.7 .. 41.4 36.1 21.1 33.0 .. 10.6 .. 23.2 .. 45.1 .. .. 30.5 .. 39.0 22.0 21.9

81.6 72.3 80.5 .. 68.8 84.6

.. 71.0 92.1 .. 82.6 97.6

.. .. 95.9 .. .. ..

.. .. .. .. .. ..

.. .. .. 99.9 83.2 ..

2.0 0.0 4.0 .. 0.0 4.0

3.0 0.0 2.0 .. 1.0 12.0

7.7 13.8 1.8 7.7 10.5 27.6

.. .. 20.5 .. .. ..

.. .. 19.0 .. .. 24.3

15.0 26.7 18.1 15.8 20.8 25.0

a. Data are for the most recent year available during the period speciﬁed.

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Table

3.4

Millennium Development Goal 4: reduce child mortality

1990

Under-five mortality rate (per 1,000) 2000 2009

2010

1990

Infant mortality rate (per 1,000 live births) 2000 2009

2010

Child immunization rate, measles (% of children ages 12–23 months) 1990 2000 2009 2010

243 178 59 205 183 137 59 165 207 125 181 116 151 190 141 184 93 165 122 229 210 99 89 227 159 222 255 124 24 219 73 311 213 163 94 139 17 276 180 60 125 96 155 147 175 183 78

200 143 96 191 164 148 46 176 190 104 181 104 148 152 93 141 88 128 99 175 177 111 127 169 102 167 213 116 19 177 74 218 186 177 87 119 14 233 180 78 114 114 130 124 144 157 115

164 118 49 178 143 138 37 161 175 87 172 94 125 125 63 109 75 101 77 134 152 87 92 109 65 98 182 112 15 140 44 150 147 98 81 79 14 180 180 61 104 82 80 106 103 116 83

161 115 48 176 142 136 36 159 173 86 170 93 123 121 61 106 74 98 74 130 150 85 85 103 62 92 178 111 15 135 40 143 143 91 80 75 14 174 180 57 103 78 92 103 99 111 80

144 107 46 103 110 85 46 110 113 88 117 74 105 118 87 111 68 78 77 135 125 64 72 151 97 131 131 80 21 146 49 132 126 99 61 70 14 162 108 47 78 70 95 87 106 109 52

119 89 64 98 100 91 37 115 105 75 117 67 100 98 60 87 63 66 64 106 107 69 88 115 65 99 113 77 16 119 49 98 112 106 57 63 12 142 108 54 72 77 81 76 88 94 69

100 75 37 93 89 85 30 107 100 64 113 61 87 82 44 70 55 58 51 84 93 56 67 78 45 61 101 75 13 95 32 75 90 63 54 51 12 117 108 43 67 57 53 67 65 72 52

98 73 36 93 88 84 29 106 99 63 112 61 86 81 42 68 54 57 50 81 92 55 65 74 43 58 99 75 13 92 29 73 88 59 53 50 12 114 108 41 66 55 60 66 63 69 51

38 79 87 79 74 56 79 82 32 87 38 75 56 88 .. 38 76 86 61 35 53 78 80 .. 47 81 43 38 76 59 .. 25 54 83 71 51 86 .. 30 79 57 85 80 73 52 90 87

41 70 91 59 76 49 86 36 28 70 46 34 68 51 76 52 55 89 98 42 71 75 74 63 55 73 55 62 84 71 69 37 33 74 69 48 97 37 24 72 58 92 78 58 57 85 75

77 72 94 94 91 74 96 62 49 79 67 76 67 51 95 75 55 99 93 51 61 88 85 64 64 92 60 59 99 67 76 69 64 93 90 79 97 78 43 65 82 94 91 84 63 87 76

93 69 94 94 92 79 96 62 46 72 68 76 70 51 99 81 55 97 93 51 61 86 85 64 67 93 63 67 99 70 75 71 71 82 92 60 99 82 46 65 90 94 92 84 55 91 84

68 123 94 45 86 49

49 106 47 27 55 28

37 93 24 18 37 17

36 91 22 17 36 16

55 95 68 33 67 39

41 83 37 22 46 24

32 74 20 14 32 15

31 73 19 13 30 14

83 85 86 89 79 93

80 50 98 93 93 95

92 84 95 98 98 98

95 85 96 98 98 97

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

Table

3.5

Millennium Development Goal 5: improve maternal health

1990

SUB–SAHARAN AFRICA Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco Tunisia

Maternal mortality ratio (per 100,000 live births) Modeled estimate National estimate 2000 2010 1990–99a 2000–10a

Births attended by skilled health staff (% of total) Surveys 1990–99a Surveys 2000–10a Year Percent Year Percent

1,200 770 140 700 1,100 670 200 930 920 440 930 420 710 1,200 880 950 270 700 580 1,200 1,100 400 520 1,200 640 1,100 1,100 760 68 910 200 1,200 1,100 910 150 670 .. 1,300 890 250 1,000 300 870 620 600 470 450

890 530 350 450 1,000 730 170 1,000 1,100 340 770 540 590 450 390 700 270 520 550 970 970 490 690 1,300 400 840 740 630 28 710 280 870 970 840 110 500 .. 1,300 1,000 330 870 360 730 440 530 540 640

450 350 160 300 800 690 79 890 1,100 280 540 560 400 240 240 350 230 360 350 610 790 360 620 770 240 460 540 510 60 490 200 590 630 340 70 370 .. 890 1,000 300 730 320 460 300 310 440 570

.. 498 326 484 .. .. .. 1,100 830 .. .. .. 600 .. 998 .. .. .. .. 530 910 .. .. .. .. .. .. .. .. .. .. 590 .. .. .. 560 .. .. 1,000 150 .. 229 .. 478 .. .. 700

.. 400 200 310 620 670 54 540 1,100 380 550 780 540 .. .. 670 520 730 450 980 410 488 1,200 990 500 810 460 690 22 500 450 650 550 750 160 400 57 860 1,000 400 1,100 589 450 .. 440 590 730

1996 1996 1996 1999 .. 1998 1998 1995 1997 1996 .. .. 1999 1994 1995 .. .. 1990 1998 1999 1995 1998 1993 .. 1997 1992 1996 1991 1999 1997 1992 1998 1999 1992 .. 1999 .. .. 1999 1998 1990 1994 1999 1998 1995 1999 1999

22.5 59.8 87 30.9 .. 58.2 88.5 45.9 15 51.6 .. .. 47.1 5 20.6 .. .. 44.1 44.3 34.8 25 44.3 60.9 .. 47.3 54.8 40 40 98.5 44.2 68.2 17.6 41.6 25.8 .. 48.3 .. .. 34.2 84.4 69.4 56 35.8 50.5 37.8 47.1 72.5

2007 2006 2007 2006 2010 2006 2005 2009 2010 2000 2010 2005 2006 2000 2002 2005 2000 2010 2008 2007 2010 2009 2009 2007 2009 2006 2006 2007 2005 2008 2007 2006 2008 2010 2009 2005 .. 2008 2006 2003 2006 2010 2010 2010 2006 2007 2009

47.3 74.0 94.6 53.5 60.3 63.0 77.5 43.7 22.7 61.8 79.3 83.4 56.8 64.6 28.3 5.7 85.5 56.7 57.1 46.1 44.0 43.8 61.5 46.3 43.9 53.6 49.0 60.9 99.2 55.3 81.4 17.7 38.9 69.0 81.7 51.9 .. 42.4 33.0 91.2 49.2 82.0 48.9 60.1 41.9 46.5 60.2

220 290 230 99 300 130

140 290 100 67 170 84

97 200 66 58 100 56

117 74 .. 77 332 69

.. 550 55 .. 130 ..

1992 .. 1998 1999 1995 1995

77 .. 55.2 99 39.6 80.5

2006 2006 2008 2008 2004 2006

95.2 92.9 78.9 99.8 62.6 94.6

a. Data are for the most recent year available during the period speciﬁed.

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Table

3.6

Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases

Children sleeping under insecticide-treated nets (% of children under age 5) Surveys 2000–10a Year Percent

Prevalence of HIV (% ages 15–49) 1990 2009

Contraceptive use, any method (% of married women ages 15–49) Surveys 1990–99a Surveys 2000–10a Year Percent Year Percent

0.5 0.2 3.5 3.9 3.9 0.6 .. 3.1 1.1 <0.1 .. 5.2 2.4 0.1 0.3 .. 0.9 0.1 0.3 1.1 0.3 3.9 0.8 0.3 0.2 7.2 0.4 0.2 <0.1 1.2 1.6 0.1 1.3 5.2 .. 0.2 .. <0.1 0.1 0.7 0.1 2.3 4.8 0.6 10.2 12.7 10.1

2.0 1.2 24.8 1.2 3.3 5.3 .. 4.7 3.4 0.1 .. 3.4 3.4 5.0 0.8 .. 5.2 2.0 1.8 1.3 2.5 6.3 23.6 1.5 0.2 11.0 1.0 0.7 1.0 11.5 13.1 0.8 3.6 2.9 .. 0.9 .. 1.6 0.7 17.8 1.1 25.9 5.6 3.2 6.5 13.5 14.3

1996 1996 1996 1999 .. 1998 1998 1995 1997 1996 1991 .. 1999 .. 1995 1997 .. 1990 1999 1999 .. 1998 1995 .. 1999 1996 1996 1992 1991 1997 1992 1998 1999 1996 .. 1999 .. 1992 1999 1998 1999 .. 1999 1998 1995 1999 1999

8.1 16.4 41.7 11.9 .. 19.3 52.9 14.8 4.1 21.0 7.7 .. 15.0 .. 8.0 3.3 .. 11.8 22.0 6.2 .. 39.0 29.1 .. 25.0 21.9 6.7 4.1 74.6 5.6 28.9 8.2 15.3 13.7 .. 10.5 .. 2.6 7.9 56.3 7.0 .. 25.4 23.5 14.8 22.0 53.5

2001 2006 2007 2006 2010 2006 2005 2006 2010 2000 2010 2005 2006 2000 2002 2005 2000 2001 2008 2005 2010 2009 2009 2007 2009 2006 2006 2007 2002 2008 2007 2010 2008 2010 2009 2005 .. 2008 2006 2004 2006 2010 2010 2010 2006 2007 2009

6.2 17.0 52.8 17.4 21.9 29.2 61.3 19.0 4.8 25.7 17.3 44.3 12.9 10.1 8.0 14.7 32.7 18.0 23.5 9.1 14.2 45.5 47.0 11.4 39.9 41.0 8.2 9.3 75.9 16.2 55.1 18.0 14.6 51.6 38.4 11.8 .. 8.2 14.6 59.9 7.6 49.3 34.4 15.2 23.7 40.8 64.9

2007 2006 .. 2006 2010 2006 .. 2006 2010 2000 2010 2005 2006 2000 2008 2007 2008 2006 2008 2008 2010 2009 .. 2009 2009 2010 2010 2004 .. 2008 2009 2010 2010 2010 2009 2009 .. 2008 2006 .. 2009 2007 2010 2010 2009 2010 2009

17.7 20.1 .. 9.6 45.2 13.1 .. 15.1 9.8 9.3 35.7 6.1 3.0 0.7 48.9 33.1 55.1 49.0 28.2 4.5 35.5 46.7 .. 26.4 45.8 56.5 70.2 2.1 .. 22.8 34.0 63.7 29.1 69.8 56.2 29.2 .. 25.8 11.4 .. 25.3 0.6 63.6 56.9 32.8 49.9 17.3

<0.1 0.9 <0.1 .. <0.1 <0.1

0.1 2.5 <0.1 .. 0.1 0.1

1995 .. 1998 1995 1997 1995

56.9 .. 51.7 45.2 58.4 60.0

2006 2008 2008 .. 2004 2006

61.4 22.5 60.3 .. 63.0 60.2

.. 2009 .. .. .. ..

.. 19.9 .. .. .. .. (continued)

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

Table

3.6

Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases (continued)

1990

Incidence of tuberculosis (per 100,000 people) 1999

2010

Tuberculosis treatment success rate (% of registered cases) Surveys 1990–99a Surveys 2000–09a Year Percent Year Percent

205 77 533 66 148 81 175 145 125 85 327 169 150 80 72 173 153 185 155 119 158 139 184 199 177 326 163 228 28 401 696 125 128 405 135 195 43 207 285 301 119 267 226 308 624 710 296

250 85 918 69 178 168 160 302 262 56 327 353 198 100 85 235 248 225 152 200 192 286 553 242 217 467 124 277 24 513 1077 152 172 286 114 237 37 377 285 576 119 803 236 374 427 713 726

304 94 503 55 129 177 147 319 276 37 327 372 139 135 100 261 553 273 86 334 233 298 633 293 266 219 68 337 22 544 603 185 133 106 96 288 31 682 286 981 119 1287 177 455 209 462 633

1998 1999 1999 1999 1998 1999 .. 1995 1998 1999 1999 1999 1999 1997 1999 1999 1998 1997 1999 1999 1999 1999 1999 1999 1997 1999 1999 .. 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 1999 .. 1999 1999 1999 1999 1999

68.0 77.0 71.0 61.0 74.0 75.0 .. 37.0 64.0 93.0 69.0 61.0 63.0 82.0 44.0 74.0 50.0 70.0 51.0 74.0 35.0 79.0 69.0 74.0 64.0 71.0 69.0 .. 87.0 71.0 51.0 60.0 75.0 67.0 81.0 58.0 91.0 75.0 88.0 57.0 80.0 .. 78.0 76.0 61.0 69.0 73.0

2009 2009 2009 2009 2009 2009 2008 2009 2009 2008 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009

72.0 90.0 79.0 76.0 90.0 78.0 74.0 53.0 76.0 90.0 88.0 78.0 79.0 66.0 85.0 84.0 55.0 89.0 87.0 79.0 67.0 86.0 70.0 83.0 82.0 88.0 78.0 63.0 88.0 85.0 85.0 79.0 83.0 85.0 98.0 85.0 64.0 79.0 85.0 73.0 80.0 69.0 88.0 81.0 67.0 90.0 78.0

66 619 34 40 147 29

87 619 26 40 109 24

90 620 18 40 91 25

1999 1999 1999 1999 1999 1999

87.0 72.0 85.0 67.0 88.0 91.0

2009 2009 2009 2008 2009 2009

91.0 79.0 88.0 69.0 84.0 83.0

a. Data are for the most recent year available during the period speciﬁed.

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Table

3.7

Millennium Development Goal 7: ensure environmental sustainability

1990

Forest area (% of total land area) 2000

2010

Terrestrial protected areas (% of total land area) 1990 2000 2010

GDP per unit of energy use (2005 PPP $ per kg of oil equivalent) 1990 2000 2009

48.9 52.1 24.2 25.0 11.3 51.4 14.4 37.3 10.4 6.5 70.7 66.6 32.1 66.3 16.1 13.7 85.4 44.2 32.7 29.6 78.8 6.5 1.3 51.2 23.5 41.3 11.5 0.4 19.2 55.2 10.6 1.5 18.9 12.9 28.1 48.6 89.1 43.5 13.2 6.8 32.2 27.4 46.8 12.6 23.8 71.0 57.3

47.9 45.8 22.1 22.8 7.7 46.8 20.4 36.8 9.8 4.3 69.4 66.1 32.5 62.1 15.6 13.7 85.4 46.1 26.8 28.1 75.4 6.3 1.4 48.1 22.6 37.8 10.9 0.3 19.2 52.4 9.8 1.1 14.4 13.9 28.1 46.2 89.1 40.8 12.0 5.7 29.7 30.1 42.3 8.9 19.4 68.8 48.8

46.9 41.2 20.0 20.7 6.7 42.1 21.1 36.3 9.2 1.6 68.0 65.6 32.7 58.0 15.2 12.3 85.4 48.0 21.7 26.6 71.9 6.1 1.5 44.9 21.6 34.3 10.2 0.2 17.2 49.6 8.9 1.0 9.9 17.6 28.1 44.0 89.1 38.1 10.8 4.7 29.4 32.7 37.7 5.3 15.0 66.5 40.4

12.4 23.8 30.3 13.7 3.8 7.0 2.5 17.5 9.4 0.0 10.0 .. 22.6 7.3 4.9 .. 4.6 1.5 14.6 6.8 7.7 11.6 0.5 .. 2.2 15.0 2.3 0.5 1.7 14.8 14.4 7.1 11.6 9.9 .. 24.1 42.0 5.0 .. 6.5 4.2 3.0 26.5 11.3 7.9 36.0 18.0

12.4 23.8 30.9 13.9 4.9 8.7 2.5 17.7 9.4 0.0 10.0 .. 22.6 19.2 4.9 .. 5.7 1.5 14.7 6.8 16.1 11.8 0.5 .. 3.1 15.0 2.3 0.5 4.5 14.8 14.5 7.1 12.8 9.9 .. 24.1 42.0 5.0 .. 6.9 4.2 3.0 26.9 11.3 8.5 36.0 18.1

12.4 23.8 30.9 14.2 4.9 9.2 2.5 17.7 9.4 .. 10.0 .. 22.6 19.2 5.0 .. 15.1 1.5 14.7 6.8 16.1 11.8 0.5 .. 3.1 15.0 2.4 0.5 4.5 15.8 14.9 7.1 12.8 10.0 .. 24.1 42.0 5.0 .. 6.9 4.2 3.0 .. 11.3 10.3 36.0 28.0

5.4 3.2 7.6 .. .. 5.1 17.1 .. .. 29.6 2.0 10.7 5.5 .. .. 1.8 11.8 24.0 2.5 .. 16.5 3.1 .. .. .. .. .. .. 13.5 0.9 .. .. 2.0 .. .. 6.4 26.3 .. .. 3.0 2.6 10.9 2.2 2.8 .. 1.8 ..

4.6 4.3 9.1 .. .. 4.6 .. .. .. .. 0.8 11.5 4.5 .. 3.0 1.9 11.2 .. 2.6 .. .. 2.9 .. .. .. .. .. .. .. 1.3 8.4 .. 2.0 .. .. 6.1 .. .. .. 2.9 3.5 .. 2.1 2.1 .. 1.7 ..

8.0 3.5 11.4 .. .. 5.7 .. .. .. .. 0.9 10.1 3.2 .. 3.5 2.2 10.7 .. 3.6 .. .. 3.0 .. .. .. .. .. .. .. 1.9 7.3 .. 2.9 .. .. 7.1 .. .. .. 3.2 5.3 .. 2.7 2.0 .. 2.1 ..

0.7 0.3 0.0 0.1 11.3 4.1

0.7 0.3 0.1 0.1 11.2 5.4

0.6 0.3 0.1 0.1 11.5 6.5

6.3 0.0 1.9 .. 1.2 1.3

6.3 0.0 4.3 .. 1.6 1.3

6.3 .. 5.9 .. 1.6 ..

7.1 11.8 5.8 .. 9.7 7.4

6.9 .. 6.2 4.0 8.3 8.0

6.5 .. 5.9 4.7 8.8 9.5 (continued)

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

Table

3.7

Millennium Development Goal 7: ensure environmental sustainability (continued)

Carbon dioxide emissions per capita (metric tons) 1990 2000 2010

Population with sustainable access to an improved water source (%) 1990 2000 2010

Population with sustainable access to improved sanitation (%) 1990 2000 2010

0.4 0.2 1.6 0.1 0.1 0.1 0.3 0.1 0.0 0.2 0.1 0.5 0.5 0.3 .. 0.1 5.2 0.2 0.3 0.2 0.3 0.3 .. 0.2 0.1 0.1 0.1 1.3 1.4 0.1 0.0 0.1 0.5 0.1 0.6 0.4 1.6 0.1 0.0 9.5 0.2 0.5 0.1 0.2 0.1 0.3 1.5

0.7 0.3 2.4 0.1 0.1 0.2 0.4 0.1 0.0 0.2 0.0 0.3 0.4 0.9 0.2 0.1 0.9 0.2 0.3 0.2 0.2 0.3 .. 0.2 0.1 0.1 0.1 0.5 2.3 0.1 0.9 0.1 0.6 0.1 0.6 0.4 7.0 0.2 0.1 8.4 0.2 1.2 0.1 0.3 0.1 0.2 1.1

1.4 0.5 2.5 0.1 0.0 0.3 0.6 0.1 0.1 0.2 0.1 0.5 0.4 7.3 0.1 0.1 1.7 0.3 0.4 0.2 0.2 0.3 .. 0.2 0.1 0.1 0.0 0.6 3.1 0.1 1.8 0.1 0.6 0.1 0.8 0.4 7.8 0.2 0.1 8.9 0.3 1.1 0.2 0.3 0.1 0.2 0.7

42.0 57.0 93.0 43.0 70.0 49.0 .. 58.0 39.0 87.0 45.0 .. 76.0 .. 43.0 14.0 .. 74.0 53.0 51.0 36.0 44.0 80.0 .. 29.0 41.0 28.0 30.0 99.0 36.0 64.0 35.0 47.0 66.0 .. 61.0 .. 38.0 .. 83.0 65.0 39.0 55.0 49.0 43.0 49.0 79.0

46.0 66.0 95.0 60.0 72.0 64.0 83.0 63.0 45.0 92.0 44.0 70.0 77.0 51.0 54.0 29.0 85.0 83.0 71.0 63.0 50.0 52.0 80.0 61.0 38.0 62.0 46.0 40.0 99.0 42.0 81.0 42.0 53.0 66.0 79.0 66.0 .. 46.0 22.0 86.0 62.0 52.0 54.0 55.0 58.0 54.0 80.0

51.0 75.0 96.0 79.0 72.0 77.0 88.0 67.0 51.0 95.0 45.0 71.0 80.0 .. .. 44.0 87.0 89.0 86.0 74.0 64.0 59.0 78.0 73.0 46.0 83.0 64.0 50.0 99.0 47.0 93.0 49.0 58.0 65.0 89.0 72.0 .. 55.0 29.0 91.0 58.0 71.0 53.0 61.0 72.0 61.0 80.0

29.0 5.0 38.0 8.0 44.0 48.0 .. 11.0 8.0 17.0 9.0 .. 20.0 .. 9.0 3.0 .. .. 7.0 10.0 .. 25.0 .. .. 9.0 39.0 15.0 16.0 89.0 11.0 24.0 5.0 37.0 36.0 .. 38.0 .. 11.0 .. 71.0 27.0 48.0 7.0 13.0 27.0 46.0 41.0

42.0 9.0 52.0 11.0 45.0 49.0 44.0 22.0 10.0 28.0 16.0 20.0 22.0 89.0 11.0 9.0 36.0 63.0 10.0 14.0 14.0 28.0 25.0 12.0 12.0 46.0 18.0 21.0 89.0 14.0 28.0 7.0 34.0 47.0 21.0 45.0 .. 11.0 22.0 75.0 27.0 52.0 9.0 13.0 30.0 47.0 40.0

58.0 13.0 62.0 17.0 46.0 49.0 61.0 34.0 13.0 36.0 24.0 18.0 24.0 .. .. 21.0 33.0 68.0 14.0 18.0 20.0 32.0 26.0 18.0 15.0 51.0 22.0 26.0 89.0 18.0 32.0 9.0 31.0 55.0 26.0 52.0 .. 13.0 23.0 79.0 26.0 57.0 10.0 13.0 34.0 48.0 40.0

3.1 0.7 1.3 9.3 1.0 1.6

2.9 0.6 2.1 9.5 1.2 2.1

3.2 0.6 2.7 9.5 1.5 2.4

94.0 78.0 93.0 54.0 73.0 81.0

89.0 82.0 96.0 54.0 78.0 90.0

83.0 88.0 99.0 .. 83.0 ..

88.0 66.0 72.0 97.0 53.0 74.0

92.0 60.0 86.0 97.0 64.0 81.0

95.0 50.0 95.0 97.0 70.0 ..

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Table

3.8

Millennium Development Goal 8: develop a global partnership for development

Debt sustainability Heavily Indebted Poor Countries (HIPC) Debt Initiative Decision pointa Completion pointa

Debt service relief committed ($ millions)a

Public and publicly guaranteed debt service (% of exports, excluding workers’ remittances) 1990 2000 2010

.. Jul. 2000 .. Jul. 2000 Aug. 2005 Oct. 2000 .. Sep. 2007 May 2001 Jun. 2010 Jul. 2003 Mar. 2006 Mar. 2009 .. .. Nov. 2001 .. Dec. 2000 Feb. 2002 Dec. 2000 Dec. 2000 .. .. Mar. 2008 Dec. 2000 Dec. 2000 Sep. 2000 Feb. 2000 .. Apr. 2000 .. Dec. 2000 .. Dec. 2000 Dec. 2000 Jun. 2000 .. Mar. 2002 .. .. .. .. Apr. 2000 Nov. 2008 Feb. 2000 Dec. 2000 ..

.. Mar. 2003 .. Apr. 2002 Jan. 2009 Apr. 2006 .. Jun. 2009 .. .. Jul. 2010 Jan. 2010 .. .. .. Apr. 2004 .. Dec. 2007 Jul. 2004 .. Dec. 2010 .. .. Jun. 2010 Oct. 2004 Aug. 2006 Mar. 2003 Jun. 2002 .. Sep. 2001 .. Apr. 2004 .. Apr. 2005 Mar. 2007 Apr. 2004 .. Dec. 2006 .. .. .. .. Nov. 2001 Dec. 2010 May. 2000 Apr. 2005 ..

.. 460 .. 930 1,366 4,917 .. 804 260 136 15,222 1,738 3,415 .. .. 3,275 .. 112 3,500 800 790 .. .. 4,600 1,900 1,628 895 1,100 .. 4,300 .. 1,190 .. 1,316 263 850 .. 994 .. .. .. .. 3,000 360 1,950 3,900 ..

7.1 8.4 4.3 7.7 40.7 12.5 8.9 7.5 2.3 2.5 .. 30.9 14.7 .. .. 33.2 3.8 17.3 19.9 17.7 22.0 22.7 4.1 .. 31.9 22.4 9.7 24.8 4.5 17.2 .. 3.2 22.3 9.4 28.6 13.7 7.6 7.8 .. .. 4.5 5.3 25.1 8.6 47.1 12.6 18.2

20.4 10.7 2.0 15.1 25.1 13.5 10.7 .. .. .. .. 0.5 14.9 .. 2.8 12.2 8.8 .. 12.0 17.6 .. 15.7 6.8 .. 8.4 10.8 10.2 .. 16.3 7.0 .. 6.0 8.2 15.3 19.9 13.2 3.3 29.6 .. 5.5 10.1 2.1 10.3 3.2 6.5 17.4 ..

4.4 .. 1.3 .. 1.8 2.7 5.0 .. .. .. .. .. .. .. .. 3.9 .. 7.0 2.8 4.9 .. 3.9 1.5 1.0 .. .. .. .. 1.5 2.8 .. .. 0.4 2.3 5.6 .. 3.7 2.0 .. 1.9 4.1 1.8 1.3 .. 1.7 0.8 ..

.. .. .. .. .. ..

63.3 .. 23.2 .. 23.1 23.0

.. 4.8 8.5 .. 23.0 20.0

0.6 6.8 5.7 .. 6.8 8.5 (continued)

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

Table

3.8

Millennium Development Goal 8: develop a global partnership for development (continued) Youth unemployment rate (ages 15–24) Female Male Total (share of female (share of male (share of total labor force) labor force) labor force) Year Percent Year Percent Year Percent

Information and communication Fixed-line and mobile telephone subscribers Internet users (per 100 people) (per 100 people) 1990 2000 2010 1995 2000 2010

.. 2002 2000 2006 .. .. .. .. .. .. .. .. .. .. .. 2006 .. .. 2000 .. .. .. 2008 2010 2005 .. .. .. 2010 .. 2004 2001 .. .. .. 2006 2002 2004 .. 2009 .. .. 2006 .. 2009 2005 2004

.. 0.8 13.6 3.8 .. .. .. .. .. .. .. .. .. .. .. 24.9 .. .. 16.6 .. .. .. 34.4 5.9 2.3 .. .. .. 23.4 .. 41.7 3.2 .. .. .. 14.8 20.3 5.2 .. 48.2 .. .. 8.8 .. 5.4 23.4 7.6

.. 2002 2000 2006 .. .. .. .. .. .. .. .. .. .. .. 2006 .. .. 2000 .. .. .. 2008 2010 2005 .. .. .. 2010 .. 2004 2001 .. .. .. 2006 .. 2004 .. 2009 .. .. 2006 .. .. 2000 2004

.. 1.1 13.2 4.6 .. .. .. .. .. .. .. .. .. .. .. 19.5 .. .. 16.4 .. .. .. 29 3.9 1.7 .. .. .. 19.4 .. 36.7 4 .. .. .. 11.9 .. 7.3 .. 44.6 .. .. 7.4 .. .. 23.1 7.6

.. 2002 2000 2006 .. .. .. .. .. .. .. .. .. .. .. 2006 .. .. 2000 .. .. .. 2008 2010 2005 .. .. .. 2010 .. 2004 2001 .. .. .. 2006 .. 2004 .. 2009 .. .. 2006 .. .. 2000 2004

.. 0.6 14 2.9 .. .. .. .. .. .. .. .. .. .. .. 29.4 .. .. 16.7 .. .. .. 41.9 7.7 2.8 .. .. .. 29 .. 47 1.7 .. .. .. 20.1 .. 3.5 .. 52.5 .. .. 10.1 .. .. 19.5 7.6

0.7 0.3 1.9 0.2 0.1 0.3 2.4 0.2 0.1 0.8 0.1 0.7 0.6 0.4 .. 0.3 2.2 0.6 0.3 0.2 0.6 0.8 0.8 0.4 0.3 0.3 0.1 0.3 5.5 0.4 3.8 0.1 0.3 0.2 1.9 0.6 12.4 0.3 0.2 9.4 0.2 1.6 0.3 0.3 0.2 0.8 1.2

0.7 1.6 20.4 0.6 0.6 1.3 17.0 0.4 0.2 1.2 0.1 2.9 4.4 2.1 0.8 0.4 12.9 3.0 1.8 0.8 0.9 1.3 2.2 0.3 0.8 0.9 0.4 1.3 38.8 0.8 10.1 0.2 0.5 0.7 3.3 4.8 57.4 0.8 1.4 30.2 1.2 6.4 0.8 1.9 0.8 1.8 4.1

48.3 81.5 124.6 35.5 14.1 46.8 89.5 22.4 24.3 25.4 18.0 94.2 77.6 59.0 4.6 9.4 109.0 88.3 72.6 40.3 39.5 62.6 47.3 39.5 37.9 21.5 49.2 81.4 123.2 31.3 73.9 25.1 55.8 33.8 66.8 69.9 160.5 34.3 8.0 109.2 41.4 73.6 47.2 44.2 39.4 42.8 64.3

.. .. 0.1 .. 0.0 .. .. .. .. .. .. .. 0.0 .. 0.0 0.0 .. 0.0 0.0 0.0 .. 0.0 .. .. .. .. .. .. .. .. 0.0 .. .. .. .. 0.0 .. 0.0 0.0 0.7 0.0 0.0 .. 0.0 0.0 0.0 0.0

0.1 0.2 2.9 0.1 0.1 0.3 1.8 0.1 0.0 0.3 0.0 0.0 0.2 0.1 0.1 0.0 1.2 0.9 0.2 0.1 0.2 0.3 0.2 0.0 0.2 0.1 0.1 0.2 7.3 0.1 1.6 0.0 0.1 0.1 4.6 0.4 7.2 0.1 0.0 5.4 0.0 1.0 0.1 1.9 0.2 0.2 0.4

10.0 3.1 6.0 1.4 2.1 4.0 30.0 2.3 1.7 5.1 0.7 5.0 2.6 6.0 5.4 0.8 7.2 9.2 9.6 1.0 2.5 25.9 3.9 7.0 1.7 2.3 2.7 3.0 28.7 4.2 6.5 0.8 28.4 13.0 18.8 16.0 41.0 .. .. 12.3 .. 9.0 11.0 5.4 12.5 10.1 11.5

2006 .. 2007 .. 2009 2005

24.3 .. 24.8 .. 21.9 30.7

2004 .. 2007 .. 2009 2005

42.8 .. 17.2 .. 22.8 31.4

2004 .. 2007 .. 2009 2005

46.3 .. 47.9 .. 19.4 29.3

3.2 1.0 2.8 5.1 1.6 3.7

6.1 1.4 10.1 12.3 13.1 11.2

100.7 20.7 99.0 190.9 111.8 117.6

0.0 0.0 0.0 .. 0.0 0.0

0.5 0.2 0.6 0.2 0.7 2.7

12.5 6.5 26.7 14.0 49.0 36.6

Note: 0.0 indicates less than 1. a. As of end-July 2011. b. Data are for the most recent year available during the period speciﬁed.

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Drivers of growth

Table

4.1

Doing Business

Overall ranking 2010 2011

171 173 52 151 177 165 129 183 182 156 176 180 170 161 178 104 160 145 60 179 181 106 142 155 144 141 148 162 21 132 74 172 133 50 174 157 109 150 .. 36 135 123 125 158 119 80 168

172 175 54 150 169 161 119 182 183 157 178 181 167 155 180 111 156 149 63 179 176 109 143 151 137 145 146 159 23 139 78 173 133 45 163 154 103 141 .. 35 135 124 127 162 123 84 171

143 167 108 .. 115 40

148 170 110 .. 94 46

Number of procedures 2010 2011

9 8 7 10 4 9 6 8 8 13 11 10 10 10 21 13 5 9 8 7 12 17 11 7 5 2 10 6 9 5 9 10 9 8 2 10 4 10 6 .. 6 10 12 12 7 18 6 9 9.4 14 11 6 .. 6 10

8 8 6 10 3 9 5 8 7 11 11 10 10 10 21 13 5 9 8 7 12 9 11 7 4 3 10 4 9 5 9 10 9 8 2 4 3 10 6 .. 5 10 12 12 7 16 6 9 9.4 14 11 6 .. 6 10

Starting a business Cost Time spent for (% of GNI each procedure per capita) (days) 2010 2011 2010 2011

45 68 31 61 14 14 19 11 22 75 24 84 160 40 137 84 9 58 27 12 40 216 33 40 20 7 39 8 19 6 13 66 17 31 3 144 8 39 12 .. 22 36 56 29 84 25 18 90 18.4 25 37 7 .. 12 11

37 68 29 61 13 14 15 11 21 66 24 65 160 32 137 84 9 58 27 12 40 9 33 40 6 8 39 8 19 6 13 66 17 34 3 10 5 39 12 .. 19 36 56 29 84 34 18 90 18.4 25 37 7 .. 12 11

97.4 163.0 154.3 2.2 53.4 124.3 51.2 18.5 228.4 226.9 176.5 735.1 111.4 133.0 147.9 69.2 14.1 21.9 199.6 11.9 147.7 183.3 38.3 26.0 88.3 12.9 108.4 79.7 56.0 3.8 13.9 18.5 118.6 78.9 8.8 77.3 63.1 17.5 110.7 .. 6.0 33.6 33.0 30.9 178.1 94.4 27.9 182.8 42.0 12.9 169.9 6.3 .. 15.8 5.0

81.2 118.9 149.9 1.8 47.7 116.8 45.5 17.0 175.5 208.5 176.2 551.4 85.2 132.6 101.4 62.6 12.8 17.3 206.1 17.3 118.0 49.8 37.8 24.9 68.4 12.1 90.9 90.5 48.3 3.6 11.7 17.2 114.4 70.6 4.7 24.5 68.0 16.0 93.3 .. 0.3 31.4 29.2 28.8 177.2 84.5 27.4 148.9 41.5 12.1 169.8 5.6 .. 15.7 4.2

Registering property Minimum capital (% of GNI per capita) 2010 2011

145.6 28.7 285.3 0.0 416.2 0.0 191.8 42.4 468.6 386.7 245.5 0.0 129.8 202.9 21.3 268.4 367.7 32.7 0.0 6.5 519.1 415.1 0.0 12.0 0.0 248.1 0.0 306.8 412.1 0.0 0.0 0.0 613.0 0.0 0.0 385.7 205.1 0.0 0.0 .. 0.0 0.0 0.5 0.0 486.9 0.0 0.0 0.0 95.9 34.4 434.1 0.0 .. 11.2 0.0

129.8 25.3 280.4 0.0 373.3 0.0 182.9 39.0 452.9 345.0 252.9 0.0 88.0 200.4 14.6 243.0 333.5 26.4 0.0 5.5 407.3 398.7 0.0 11.2 0.0 0.0 0.0 348.3 334.9 0.0 0.0 0.0 584.2 0.0 0.0 336.0 203.0 0.0 0.0 .. 0.0 0.0 0.5 0.0 484.5 0.0 0.0 0.0 95.1 30.6 434.0 0.0 .. 10.7 0.0

Number of procedures 2010 2011

6 7 4 5 4 5 5 6 5 6 4 6 6 6 6 11 10 7 5 5 6 8 8 6 10 6 6 5 4 4 8 7 4 13 4 7 6 4 7 .. 6 6 9 9 5 13 5 5 7 10 7 7 .. 8 4

6 7 4 5 4 5 5 6 5 6 4 6 6 6 6 11 10 7 5 5 6 8 8 6 10 6 6 5 4 4 8 7 4 13 5 7 6 4 7 .. 6 6 9 9 5 13 5 5 7 10 7 7 .. 8 4

Time required (days) 2010 2011

67 184 120 16 59 94 93 73 75 44 30 54 55 62 23 78 41 39 66 34 59 210 64 101 50 74 49 29 49 26 42 39 35 82 55 62 122 33 86 .. 24 9 44 73 295 77 40 31 55 48 40 72 .. 75 39

65 184 120 16 59 94 93 31 75 44 30 54 55 62 23 78 41 39 66 34 59 210 64 101 50 74 69 29 49 22 42 39 35 82 25 62 122 33 86 .. 23 9 21 73 295 48 40 31 55 48 40 72 .. 75 39

Cost (% of property value) 2010 2011

9.4 11.5 11.8 5.0 13.1 5.8 19.3 3.9 18.5 18.2 10.5 7.0 10.7 13.9 6.3 9.1 2.1 10.5 7.6 0.8 14.0 10.7 4.2 8.0 13.2 9.8 3.2 11.9 5.2 10.6 9.9 8.6 11.0 20.9 0.4 10.9 20.6 7.0 12.2 .. 8.8 3.0 7.1 4.4 13.0 3.2 6.6 8.5 6.4 7.1 13.0 0.8 .. 4.9 6.1

9.4 3.2 11.8 5.0 12.8 5.6 19.2 3.9 11.0 18.1 10.5 6.8 20.6 13.9 6.2 9.1 2.1 10.5 7.7 0.7 14.4 10.6 4.3 8.0 13.1 10.6 3.2 12.1 4.7 10.6 8.7 13.7 11.0 20.8 6.3 8.9 20.3 7.0 11.8 .. 5.6 3.0 7.1 4.4 13.0 2.9 8.3 8.0 6.4 7.1 13.0 0.8 .. 4.9 6.1 (continued)

PRIVATE SECTOR DEVELOPMENT

Part III. Development outcomes

Drivers of growth

Table

4.1

Doing Business (continued)

Enforcing contracts Number of procedures 2010 2011

39 46 42 29 37 44 43 37 43 41 43 43 44 33 40 39 37 38 33 36 49 40 40 41 41 38 42 36 46 36 30 33 39 40 24 43 44 37 40 .. 29 53 40 38 41 38 35 38 41 45 40 41 .. 40 39

655 1011 795 625 446 832 800 425 660 743 506 610 560 770 553 405 620 1070 434 487 276 1715 465 785 1280 871 312 620 370 645 730 270 545 457 230 1185 780 915 515 .. 600 810 972 462 588 490 471 410 788 630 1225 1010 .. 510 565

Time required (days) 2010 2011

Cost (% of debt) 2010 2011

651 1,011 825 625 446 832 800 425 660 743 506 610 560 770 553 405 620 1,070 434 487 276 1,715 465 785 1,280 871 312 620 370 645 730 270 545 457 230 1,185 780 720 515 .. 600 810 972 462 588 490 471 410 788 630 1,225 1,010 .. 510 565

39.1 46.0 42.0 29.0 37.0 44.0 43.0 37.0 43.0 41.0 43.0 43.0 44.0 33.0 40.0 39.0 37.0 38.0 33.0 36.0 49.0 40.0 40.0 41.0 41.0 38.0 42.0 36.0 46.0 36.0 30.0 33.0 39.0 40.0 24.0 43.0 44.0 37.0 40.0 .. 29.0 53.0 40.0 38.0 41.0 38.0 35.0 38.0 41.0 45.0 40.0 41.0 .. 40.0 39.0

50 44 65 28 82 39 47 20 82 46 89 152 53 42 19 23 15 34 38 23 45 25 47 20 35 42 94 52 23 17 143 36 60 32 79 51 27 15 150 .. 33 20 56 14 48 45 39 113 26 22 34 26 .. 25 22

39.0 46.0 42.0 28.0 37.0 44.0 43.0 37.0 43.0 41.0 43.0 43.0 44.0 33.0 40.0 39.0 37.0 38.0 33.0 36.0 49.0 40.0 40.0 40.0 41.0 38.0 42.0 36.0 46.0 36.0 30.0 33.0 39.0 40.0 24.0 43.0 43.0 37.0 39.0 .. 29.0 53.0 40.0 38.0 41.0 38.0 35.0 38.0 41.0 45.0 40.0 41.0 .. 40.0 39.0

Dealing with construction permits Number of Time required Cost procedures (days) (% of GNI per capita) 2010 2011 2010 2011 2010 2011

15 11 12 22 12 22 11 17 18 13 15 11 14 18 15 .. 9 13 14 16 29 12 8 12 23 16 18 11 22 16 13 12 12 15 12 13 13 17 20 .. 13 16 13 19 12 15 14 12 18 19 14 22 .. 16 17

15 11 12 22 12 22 11 17 18 13 15 11 14 18 15 .. 9 13 14 16 29 12 8 12 23 16 18 11 18 16 13 12 12 15 12 13 13 17 20 .. 13 16 13 19 12 15 14 12 18 19 15 22 .. 15 17

213 321 372 145 98 135 147 122 203 154 155 117 186 583 166 .. 128 201 143 218 287 170 125 510 75 172 200 187 168 136 370 139 326 85 164 211 210 126 238 .. 127 270 95 303 309 125 196 614 171 281 171 218 .. 104 88

211 321 372 145 98 135 147 122 203 154 155 117 186 583 166 .. 128 201 143 218 287 170 125 510 75 172 200 179 119 136 370 139 326 85 164 211 210 126 238 .. 127 270 95 303 309 125 196 614 171 281 172 218 .. 97 88

990.9 259.0 134.9 245.4 524.1 6,295.5 1,149.5 570.0 116.1 6,452.4 63.0 2,692.2 232.4 207.3 219.7 .. 406.9 26.6 207.3 598.7 351.5 1,075.0 164.4 1,122.1 824.4 468.8 1,304.7 390.0 61.4 32.3 146.0 113.0 2,323.9 564.2 349.8 565.1 439.6 34.7 325.2 .. 23.1 100.1 130.0 1,255.5 998.4 1,064.0 2,410.5 7,553.7 516.7 26.0 1,828.1 173.8 .. 246.1 309.7

823.7 180.3 132.6 203.0 345.0 4,065.7 1,096.2 523.8 112.2 5,756.5 62.8 1,670.7 157.7 204.8 150.6 .. 369.1 21.5 192.9 560.3 275.8 1,032.7 160.9 1,038.7 694.1 422.2 1,077.5 439.3 49.9 30.6 123.0 103.0 2,214.5 504.8 312.0 536.8 435.2 30.3 272.6 .. 21.2 88.0 115.2 1,170.1 994.0 946.8 2,015.2 6,154.3 591.9 23.1 2,285.7 155.3 .. 234.6 260.6

a. Average of the disclosure, director liability, and shareholder suits indexes.

Part III. Development outcomes

PRIVATE SECTOR DEVELOPMENT

Disclosure index 2010 2011

5 5 6 7 6 4 6 1 6 6 6 3 6 6 6 4 4 6 2 7 6 6 3 2 4 5 4 6 5 6 5 5 6 5 7 3 6 4 6 .. 8 0 2 3 6 2 3 8 6 6 5 8 .. 7 5

5 5 6 7 6 8 6 1 6 6 6 3 6 6 6 4 4 6 2 7 6 6 3 2 4 5 4 6 5 6 5 5 6 5 7 3 6 4 6 .. 8 0 2 3 6 2 3 8 6 6 5 8 .. 7 5

Protecting investors (0 least protection to 10 most protection) Director liability Shareholder suits index index 2010 2011 2010 2011

3 6 1 8 1 1 1 5 1 1 1 3 1 1 1 5 4 1 1 5 1 1 2 1 1 6 7 1 3 8 4 5 1 7 9 1 1 8 7 .. 8 6 5 4 1 5 6 1 4 6 2 3 .. 2 7

PRIVATE SECTOR DEVELOPMENT

4 6 1 8 1 6 1 5 1 1 1 3 1 1 1 5 4 1 1 5 1 1 2 1 1 6 7 1 3 8 4 5 1 7 9 1 1 8 7 .. 8 6 5 4 1 5 6 1 4 6 2 3 .. 2 7

5 6 3 3 4 5 6 6 5 3 5 4 3 3 4 5 5 3 5 6 1 5 10 8 6 6 5 4 3 9 9 6 3 5 3 6 2 5 6 .. 8 4 6 8 4 5 7 4 3 4 0 5 .. 1 6

5 6 3 3 4 4 6 6 5 3 5 4 3 3 4 5 5 3 5 6 1 5 10 8 6 6 5 4 3 9 9 6 3 5 3 6 2 5 6 .. 8 4 6 8 4 5 7 4 4 4 0 5 .. 6 6

Investor protection indexa 2010 2011

4.4 5.7 3.3 6.0 3.7 3.3 4.3 4.0 4.0 3.3 4.0 3.3 3.3 3.3 3.7 4.7 4.3 3.3 2.7 6.0 2.7 4.0 5.0 3.7 3.7 5.7 5.3 3.7 3.7 7.7 6.0 5.3 3.3 5.7 6.3 3.3 3.0 5.7 6.3 .. 8.0 3.3 4.3 5.0 3.7 4.0 5.3 4.3 4.4 5.3 2.3 5.3 .. 3.3 6.0

4.5 5.7 3.3 6.0 3.7 6.0 4.3 4.0 4.0 3.3 4.0 3.3 3.3 3.3 3.7 4.7 4.3 3.3 2.7 6.0 2.7 4.0 5.0 3.7 3.7 5.7 5.3 3.7 3.7 7.7 6.0 5.3 3.3 5.7 6.3 3.3 3.0 5.7 6.3 .. 8.0 3.3 4.3 5.0 3.7 4.0 5.3 4.3 4.8 5.3 2.3 5.3 .. 5.0 6.0

Time (years) 2010

3 6 4 2 4 .. 3 .. 5 4 .. 5 3 2 .. .. 3 5 3 2 4 .. 5 3 3 2 3 4 8 2 5 2 5 2 3 6 3 .. 3 .. 2 2 2 3 3 2 3 3 3 3 5 4 .. 2 1

2011

3 6 4 2 4 .. 3 .. 5 4 .. 5 3 2 .. .. 3 5 3 2 4 .. 5 3 3 2 3 4 8 2 5 2 5 2 3 6 3 .. 3 .. 2 2 2 3 3 2 3 3 3 3 5 4 .. 2 1

Resolving insolvency Cost (% of estate) 2010 2011

22.9 22.0 22.0 15.0 9.0 .. 34.0 .. 76.0 60.0 .. 29.0 25.0 18.0 .. .. 15.0 15.0 15.0 22.0 8.0 .. 22.0 8.0 43.0 30.0 25.0 18.0 9.0 15.0 9.0 15.0 18.0 22.0 50.0 22.0 7.0 .. 42.0 .. 18.0 20.0 15.0 22.0 15.0 30.0 9.0 22.0 14.4 7.0 18.0 22.0 .. 18.0 7.0

Recovery rate (cents on the dollar) 2010 2011

18.4 8.4 20.2 63.7 26.8 0.0 13.6 0.0 0.0 0.0 0.0 1.1 17.8 32.8 0.0 0.0 31.3 15.2 19.8 23.7 19.4 0.0 29.8 36.4 8.4 14.3 17.9 24.6 10.3 35.1 17.7 41.5 16.0 26.8 3.2 4.0 32.0 0.0 8.4 .. 34.4 32.3 37.6 21.9 30.6 39.7 27.2 0.2 33.0 41.7 15.6 17.4 .. 38.4 51.7

19.1 6.9 20.2 64.5 27.3 0.0 13.6 0.0 0.0 0.0 0.0 1.2 17.9 37.6 0.0 0.0 31.4 15.2 19.3 26.0 19.3 0.0 30.9 37.4 8.4 13.5 18.5 24.9 10.3 35.1 15.5 41.9 21.9 28.2 3.2 7.4 32.0 0.0 9.2 .. 35.2 33.2 38.2 22.0 30.5 40.2 29.3 10.0 33.3 41.7 16.5 17.7 .. 38.3 52.2

Part III. Development outcomes

Drivers of growth

Table

4.2

Investment climate Enterprise Surveys Viewed by firms as a major constraint (% of firms) Firms that Domestic Private sector fixed Net foreign credit to believe the court Customs Crime, system is fair, private direct capital theft, and Tax Labor Labor Transpor- and trade impartial, and sector formation investment regulations rates Finance Electricity regulations skills tation (% of GDP) ($ millions) (% of GDP) uncorrupt (%) Corruption discord 2010a 2010a 2010a 2010-11b 2010-11b 2010-11b 2010-11b 2010-11b 2010-11b 2010-11b 2010-11b 2010-11b 2010-11b

12.8 3.0 16.1 14.0 .. 10.0 12.6 28.1 .. 22.7 .. .. 10.2 9.2 .. .. 5.0 17.4 11.2 17.9 15.7 .. 19.9 15.8 28.8 .. 16.9 .. 16.6 18.8 11.0 16.3 .. .. 9.5 .. 18.2 .. 8.0 .. 11.9 13.1 5.3 20.1 11.0 17.7 18.3 0.1 .. .. .. 12.2 .. 24.9 ..

.. -4,567.6 .. 264.7 .. 0.8 35.3 111.9 .. .. .. .. .. .. .. .. 288.3 .. 37.4 2,527.4 101.4 .. 184.2 119.3 452.3 .. .. .. .. 301.7 789.8 802.7 .. 5,133.3 42.3 24.5 .. 161.2 86.6 .. 1,385.6 2,063.7 131.8 433.4 .. 547.3 633.9 .. 8,347.7 2,044.0 36.5 5,210.1 -938.0 660.6 1,334.5

64.1 20.9 23.3 23.3 17.6 18.7 13.2 62.1 8.9 5.1 19.1 6.6 5.5 18.0 7.5 16.0 .. 8.1 14.0 15.3 .. 6.2 33.8 13.8 19.4 11.7 16.0 18.0 27.9 87.9 26.8 49.9 13.0 29.0 .. 38.8 25.9 28.0 10.4 .. 145.6 11.6 23.0 16.2 22.8 15.6 11.5 .. 36.9 15.6 .. 33.1 .. 68.7 68.8

23.6 .. 6.4 .. .. .. .. 8.9 .. .. 33.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 15.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

75.6 .. 27.4 .. .. .. .. 41.4 .. .. 72.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 24.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

1.5 .. 1.5 .. .. .. .. 25.6 .. .. 1.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

26.4 .. 16.9 .. .. .. .. 31.9 .. .. 39.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 26.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

38.5 .. 25.5 .. .. .. .. 46.0 .. .. 73.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 48.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

35.7 .. 34.8 .. .. .. .. 76.1 .. .. 51.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 33.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

26.1 .. 14.0 .. .. .. .. .. .. .. 20.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 6.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

25.9 .. 32.2 .. .. .. .. .. .. .. 65.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 12.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

25.3 .. 20.1 .. .. .. .. 33.4 .. .. 38.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 21.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

35.8 .. 15.8 .. .. .. .. 31.9 .. .. 54.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 16.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

.. .. .. .. .. ..

a. Provisional. b. Data are for the most recent year available during the period speciﬁed.

Part III. Development outcomes

PRIVATE SECTOR DEVELOPMENT

Number of tax payments 2011

37 31 55 19 46 24 44 41 54 54 20 32 61 62 46 18 19 26 50 33 56 46 41 21 33 23 19 59 37 7 37 37 41 35 18 42 59 21 29 .. 9 42 33 48 53 32 37 49 24 29 35 29 .. 17 8

Time to prepare, ﬁle, and pay taxes (hours) 2011

Enterprise Surveys Regulation and tax administration Average time to clear customs Time dealing (days) Highest marginal with ofﬁcials (% of Total tax rate tax rate, corporate management time) Direct exports Imports (%) (% of proﬁ t) 2011 2009 2010-11b 2010-11b 2010-11b

318 282 270 152 270 274 654 186 504 732 100 336 606 270 492 216 198 488 376 224 416 208 393 324 158 201 157 270 696 161 230 375 270 938 148 424 666 76 357 .. 200 180 104 172 270 213 132 242 270 451 82 433 .. 238 144

PRIVATE SECTOR DEVELOPMENT

57 53.2 66.0 19.4 43.6 46.2 49.1 37.8 54.6 65.4 217.9 339.7 65.9 44.3 46.0 84.5 31.1 43.5 283.5 33.6 54.3 45.9 49.6 16.0 43.7 36.6 28.2 51.8 68.3 25.0 34.3 9.8 43.8 32.7 31.3 32.5 46.0 32.2 32.1 .. 33.1 36.1 36.8 45.5 49.5 35.7 14.5 35.6 53.4 72.0 38.7 43.6 .. 49.6 62.9

.. 35.0 .. 25.0 .. .. .. .. .. .. .. 38.0 .. 25.0 .. .. .. .. .. 25.0 .. .. .. .. .. .. .. .. .. 15.0 32.0 35.0 .. 30.0 .. .. .. .. .. .. 34.6 35.0 30.0 30.0 .. 45.0 35.0 30.9 .. .. .. 20.0 40.0 .. 30.0

12.2 .. 10.2 .. .. .. .. 9.2 .. .. 29.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

6.7 .. 6.2 .. .. .. .. 9.5 .. .. 18.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 12.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

11.4 .. 3.7 .. .. .. .. 11.9 .. .. 45.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 16.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

.. .. .. .. .. ..

Interest rate spread (lending rate minus deposit rate) 2010

Listed domestic companies 2010

9.7 9.8 .. 5.9 .. .. .. 7.9 .. .. 8.8 39.8 .. .. .. .. .. .. 12.4 .. .. .. 9.8 7.5 .. 38.5 21.0 .. 9.0 0.5 6.6 4.7 .. 11.1 9.6 17.8 .. 9.8 12.3 .. 3.4 .. 5.9 8.0 .. 12.5 13.5 .. 5.5 6.3 9.4 4.8 3.5 .. ..

950 .. .. 21 .. .. .. .. .. .. .. .. .. 38 .. .. .. .. .. 35 .. .. 55 .. .. .. 14 .. .. 86 .. 7 .. 215 .. .. .. .. .. .. 360 .. 5 11 .. 8 19 76 342 .. .. 213 .. 73 56

Market capitalization of Turnover ratio for listed companies traded stocks (%) (% of GDP) 2010a 2010a

148.8 .. .. 27.4 .. .. .. .. .. .. .. .. .. 31.0 .. .. .. .. .. 11.0 .. .. 44.9 .. .. .. 27.0 .. .. 67.0 .. 10.6 .. 25.9 .. .. .. .. .. .. 278.5 .. .. 5.5 .. 10.4 17.4 153.5 45.9 .. .. 37.7 .. 76.2 24.2

.. .. .. 3.4 .. .. .. .. .. .. .. .. .. 2.0 .. .. .. .. .. 3.4 .. .. 8.6 .. .. .. 1.5 .. .. 6.4 .. 1.8 .. 12.5 .. .. .. .. .. .. 39.6 .. .. .. .. 0.4 9.2 15.0 32.9 .. .. 43.0 .. 16.3 17.2

Part III. Development outcomes

Drivers of growth

Table

4.3

Financial sector infrastructure Macroeconomy Foreign currency sovereign ratings Long-term Short-term 2011–12b 2011–12b

B+ .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. B+ .. .. .. BB.. .. .. .. .. .. .. BBB.. BBB .. .. B .. .. BBB+ .. .. .. .. .. B+ ..

B .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. B .. .. .. B .. .. .. .. .. .. .. F3 .. B B .. .. B .. .. F2 .. .. .. .. .. B ..

.. .. BB B BBBBBB-

.. .. B B F3 F3

Gross national savings (% of GDP) 2009 2010 c

15.5 5.2 13.9 26.4 .. 5.2 .. 23.6 .. .. .. .. .. 14.5 .. .. 14.8 .. 12.2 17.5 6.5 .. 14.2 32.6 53.0 .. 12.8 .. .. 13.9 7.6 27.5 .. .. 15.0 .. 19.4 14.6 10.3 .. 15.5 12.8 0.4 19.5 12.4 18.2 19.0 .. 28.7 54.1 .. 16.9 .. 30.2 21.2

17.2 21.6 .. 27.7 .. -5.4 .. 34.4 .. .. .. .. .. .. .. .. 16.6 .. 9.4 20.6 7.1 .. 15.6 12.7 29.0 .. .. .. .. 15.6 12.2 34.1 .. .. 12.2 .. .. .. 13.0 .. 16.5 17.5 2.4 20.1 .. 19.0 22.5 .. 27.7 48.4 .. 17.8 .. 30.8 20.3

Money and quasi money (M2) (% of GDP) 2009 2010 c

47.1 31.1 36.8 47.2 24.2 23.1 20.1 81.5 15.8 14.2 28.6 13.8 22.2 29.9 11.1 113.3 .. 22.3 39.6 25.5 .. 23.5 41.0 36.7 33.8 22.3 23.5 25.3 32.7 101.2 35.3 51.4 17.6 38.1 .. 34.2 35.2 53.9 23.7 .. 80.5 20.3 27.6 28.8 38.5 20.9 20.6 .. 75.6 65.9 83.0 79.5 53.7 105.3 58.3

47.0 32.5 37.9 40.3 26.3 24.6 21.1 78.3 17.1 12.7 31.4 14.6 20.5 33.8 12.1 114.9 .. 19.5 41.1 26.0 .. 25.8 45.5 38.6 39.2 22.4 24.8 26.0 29.7 102.9 38.5 62.4 19.5 36.1 .. 34.3 37.5 58.8 25.8 .. 75.7 20.6 29.6 30.7 42.4 23.2 20.4 .. 75.1 59.2 .. 76.3 .. 107.8 60.6

Real interest rate (%) 2009 2010 c

.. 25.0 .. 20.4 .. 1.6 .. 6.5 .. .. 5.7 22.4 .. .. .. .. .. .. 19.0 .. .. .. 5.2 7.7 15.6 33.7 17.1 .. 26.9 9.5 11.1 6.6 .. 23.9 4.3 15.5 .. -7.8 16.1 .. 3.8 .. 12.5 7.1 .. 5.6 10.2 .. .. 21.7 9.3 0.7 57.8 .. ..

.. 0.1 .. -2.8 .. 4.4 .. 7.5 .. .. 6.4 28.2 .. .. .. .. .. .. 20.0 .. .. .. 11.9 6.8 7.4 37.9 16.5 .. -2.0 6.9 5.7 8.6 .. 7.6 13.8 15.3 .. 18.5 6.0 .. 1.8 .. 3.4 7.1 .. 9.7 8.2 .. .. -7.1 .. 0.8 .. .. ..

a. Data are consolidated for regional security markets where they exist. b. Data are for the most recent year available during the period speciﬁed. c. Provisional.

Part III. Development outcomes

PRIVATE SECTOR DEVELOPMENT

Capital marketsa

Intermediation Domestic credit to private sector (% of GDP) 2009 2010 c

Interest rate spread (lending rate minus deposit rate) 2009 2010 c

62.9 21.2 22.5 25.8 17.0 15.9 12.1 62.0 6.6 5.0 16.0 7.3 4.8 17.3 7.0 16.8 .. 10.2 13.5 15.7 .. 5.6 30.3 12.8 16.0 11.6 14.2 17.5 30.4 82.8 24.8 48.4 12.5 38.6 .. 33.4 24.8 22.8 9.5 .. 147.7 12.3 25.0 15.3 19.8 13.3 12.0 .. 35.1 16.5 29.4 36.1 10.9 64.7 62.2

8.4 8.1 .. 6.3 .. .. .. 8.1 .. .. 8.6 49.3 .. .. .. .. .. .. 11.5 .. .. .. 8.8 8.2 10.1 33.5 21.8 .. 11.5 0.8 6.2 4.9 .. 5.1 .. 19.2 .. 5.6 13.1 .. 3.2 .. 6.0 7.1 .. 11.2 15.0 .. 5.9 6.3 9.7 5.5 3.5 .. ..

PRIVATE SECTOR DEVELOPMENT

Ratio of bank nonperforming loans to total gross loans (%) 2009 2010 c

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 7.2 .. 16.2 .. .. 7.9 3.7 .. .. .. .. .. 3.3 1.8 2.7 .. 29.1 13.1 .. 18.7 3.8 10.6 .. 5.9 .. 8.1 .. .. 4.2 .. .. 13.2 .. .. 13.4 .. 5.5 13.2

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 9.9 .. 17.6 .. .. 6.3 3.7 .. .. .. .. .. 2.8 1.9 2.0 .. 17.2 10.8 .. 20.2 5.5 15.6 .. 5.8 .. 8.0 .. .. 2.1 .. .. 11.0 .. .. 11.0 .. 4.4 12.1

Listed domestic companies 2009 2010 c

.. .. .. 20 .. .. .. .. .. .. .. .. .. 38 .. .. .. .. .. 35 .. .. 55 .. .. .. 15 .. .. 89 .. 7 .. 214 .. .. .. .. .. .. 363 .. 5 15 .. 8 19 76 .. .. .. 305 .. 78 52

950 .. .. 21 .. .. .. .. .. .. .. .. .. 38 .. .. .. .. .. 35 .. .. 55 .. .. .. 14 .. .. 86 .. 7 .. 215 .. .. .. .. .. .. 360 .. 5 11 .. 8 19 76 342 .. .. 213 .. 73 56

Market capitalization of listed companies (% of GDP) 2009 2010 c

Turnover ratio for traded stocks (%) 2009 2010 c

.. .. .. 37.1 .. .. .. .. .. .. .. .. .. 26.7 .. .. .. .. .. 9.7 .. .. 35.2 .. .. .. 29.3 .. .. 53.7 .. 9.5 .. 19.8 .. .. .. .. .. .. 249.0 .. .. .. .. 23.7 21.9 65.6 .. .. .. 47.6 .. 69.2 21.0

.. .. .. 2.6 .. .. .. .. .. .. .. .. .. 2.0 .. .. .. .. .. 2.0 .. .. 4.6 .. .. .. 1.3 .. .. 8.1 .. 3.0 .. 11.0 .. .. .. .. .. .. 57.3 .. .. .. .. 0.3 .. .. .. .. .. 60.1 .. 45.7 16.2

.. .. .. 3.4 .. .. .. .. .. .. .. .. .. 2.0 .. .. .. .. .. 3.4 .. .. 8.6 .. .. .. 1.5 .. .. 6.4 .. 1.8 .. 12.5 .. .. .. .. .. .. 39.6 .. .. .. .. 0.4 9.2 15.0 32.9 .. .. 43.0 .. 16.3 17.2

Part III. Development outcomes

Drivers of growth

Table

5.1

International trade and tariff barriers Trade Annual average Merchan- Services trade Exports Imports Exports Imports dise trade Exports Imports Total (% of GDP) (% of GDP) (% of GDP) ($ millions) ($ millions) (% of GDP) (% of GDP) (% of GDP) (% of GDP) a a a a a a a 2010 2010 2010 2010 2010 2010 2010 2000-10 2000-10

65.2 105.3 42.3 73.0 .. 42.7 61.0 105.7 .. 100.0 .. 64.9 139.8 76.7 .. .. 44.0 97.3 60.8 70.6 74.1 .. 65.4 157.7 134.5 .. 77.8 .. 135.6 116.3 71.3 83.9 .. 69.1 41.5 .. 67.8 .. 46.6 .. 54.9 38.7 123.0 63.8 91.1 57.7 79.1 126.3 59.2 52.3 .. 47.5 .. 75.9 102.8

Part III. Development outcomes

58.4 90.9 51.8 69.4 37.8 30.1 39.4 47.4 24.2 70.8 38.4 74.8 92.4 79.2 111.7 33.2 36.4 93.6 27.7 57.8 49.6 41.3 53.6 138.6 94.2 42.9 58.7 55.2 106.7 68.4 83.6 84.5 56.9 64.1 30.7 61.3 54.0 109.1 58.0 .. 48.4 32.1 87.9 50.3 74.0 35.8 77.3 84.3 52.0 60.1 .. 36.3 .. 58.2 87.4

12.8 23.8 .. 8.5 .. 12.2 12.9 49.1 .. .. .. .. .. .. .. .. 16.1 .. 15.2 13.9 9.7 .. 17.7 25.9 125.2 .. .. .. .. 48.2 19.6 14.0 .. 12.9 15.4 23.0 .. 107.3 10.7 .. 8.9 3.8 25.1 17.2 .. 18.9 7.7 .. 16.1 9.6 .. 17.6 .. 22.0 20.7

374,652 51,400 937 4,917 .. 124 6,502 640 .. 3,331 .. 3,412 10,221 9,316 .. .. 3,392 8,094 230 9,461 1,649 .. 8,861 955 247 .. 1,547 .. 2,241 5,098 2,421 4,738 .. 74,610 610 .. 3,186 .. 327 .. 99,399 13,242 2,027 5,975 1,185 4,087 7,142 3,608 197,350 49,939 .. 46,732 .. 29,965 21,569

378,688 35,421 1,839 5,956 .. 740 7,200 1,113 .. 5,213 .. 5,096 6,568 8,270 .. .. 9,653 4,754 409 13,265 1,859 .. 12,192 2,482 1,081 .. 2,387 .. 2,661 6,202 4,144 4,603 .. 61,486 1,721 .. 5,530 .. 564 .. 100,119 12,665 2,522 8,653 1,709 5,833 5,672 5,831 178,504 34,820 .. 57,200 .. 38,969 23,921

31.2 62.3 14.3 33.0 .. 6.1 28.9 38.6 .. 39.0 .. 26.0 85.1 40.6 .. .. 11.4 61.3 21.9 29.4 34.8 .. 27.5 43.8 25.0 .. 30.6 .. 62.0 52.5 26.3 42.6 .. 37.9 10.9 .. 24.8 .. 17.1 .. 27.3 19.8 54.8 26.1 37.3 23.8 44.1 48.3 28.4 30.8 .. 21.4 .. 33.0 48.8

34.0 43.0 28.1 40.0 .. 36.5 32.0 67.1 .. 61.0 .. 38.9 54.7 36.1 .. .. 32.5 36.0 38.9 41.2 39.3 .. 37.9 113.9 109.5 .. 47.2 .. 73.6 63.8 45.0 41.3 .. 31.2 30.6 .. 43.0 .. 29.5 .. 27.5 18.9 68.2 37.8 53.8 33.9 35.0 78.0 30.7 21.5 .. 26.1 .. 42.9 54.1

32.3 73.9 14.1 44.3 9.7 6.5 23.5 36.2 14.6 39.2 15.2 25.1 79.8 46.1 89.1 8.0 12.7 61.1 27.3 35.1 30.7 30.1 25.6 50.3 34.1 27.5 26.3 28.5 38.9 57.8 28.7 44.3 16.2 42.0 10.5 .. 26.5 91.8 19.7 .. 29.5 16.9 77.7 20.8 37.5 16.0 34.6 36.3 34.4 40.0 40.7 24.7 56.9 31.6 45.1

34.0 54.8 27.4 36.9 23.9 29.0 24.2 69.0 21.5 56.7 37.0 33.8 54.9 37.4 55.8 52.2 30.0 32.9 38.6 52.3 33.8 55.3 35.1 117.0 80.7 42.6 43.2 39.6 60.5 62.7 44.1 48.4 25.0 31.1 26.7 .. 42.2 102.7 33.5 .. 29.2 21.7 84.9 29.9 53.6 27.6 37.6 48.0 30.7 23.3 53.6 28.8 27.8 38.1 48.1

Annual growth Terms of (%) trade index Exports Imports (2000 = 100) 2010a 2010a 2010a

.. -2.71 .. 16.2 .. 57.8 -0.1 24.5 .. .. .. 52.9 .. -0.5 .. .. 14.4 3.5 0.2 24.6 1.5 .. 16.5 2.4 5.8 .. .. .. 12.2 10.0 2.2 -42.4 .. .. .. .. 5.6 .. .. .. 4.6 .. -4.6 -4.3 -0.7 5.6 .. 60.0 .. .. .. -3.0 .. 16.3 4.8

.. -20.89 .. 9.7 .. 59.2 8.2 9.7 .. .. .. 36.3 .. 7.6 .. .. 15.9 3.3 7.7 21.0 0.1 .. 3.8 8.9 15.9 .. .. .. 21.8 7.1 1.7 -60.1 .. .. .. .. 3.5 .. .. .. 9.6 .. -2.6 -3.1 -5.7 7.8 .. 33.6 -0.7 .. .. -3.2 .. 3.3 3.8

.. .. .. 87.3 .. .. 121.5 159.1 .. .. .. 129.3 .. 94.8 .. .. 112.2 156.1 86.9 .. 96.5 .. 116.1 96.5 30.4 .. .. .. 262.5 74.6 50.0 126.7 .. .. .. .. 91.6 .. .. .. 135.6 .. 99.4 126.2 68.2 71.2 .. 109.3 .. .. .. 93.0 .. 95.6 96.1

TRADE AND REGIONAL INTEGRATION

Food 2009

13.7 .. .. 5.2 26.8 67.5 .. 72.6 .. .. .. .. .. 48.2 .. .. 77.5 .. 53.0 .. .. .. 44.0 .. .. 28.8 86.6 .. .. 32.4 23.3 .. .. 4.5 42.3 92.4 29.5 .. .. .. 10.2 5.6 .. 35.5 .. .. 7.5 19.4 6.3 0.3 0.4 .. .. 22.1 9.2

Structure of merchandise exports (% of total) Agricultural raw materials Fuel Ores and metals Manufactures 2009 2009 2010 2010

3.0 .. .. 0.2 60.5 4.8 .. 0.0 .. .. .. .. .. 5.7 .. .. 11.9 .. 1.0 .. .. .. 13.2 .. .. 5.2 3.8 .. .. 0.9 3.1 .. .. 1.1 1.7 0.7 1.1 .. .. .. 1.9 1.4 .. 9.8 .. .. 1.4 23.1 0.4 0.0 0.0 .. .. 1.6 0.5

36.9 .. .. 0.3 0.0 1.9 .. .. .. .. .. .. .. 30.0 .. .. 0.0 .. 0.0 .. .. .. 4.2 .. .. 4.9 0.1 .. .. 0.0 17.5 .. .. 90.4 0.1 0.0 24.0 .. .. .. 11.1 92.1 .. 1.0 .. .. 0.9 0.9 63.5 97.7 6.5 .. .. 2.0 13.6

17.7 .. .. 14.5 1.7 5.2 3.0 0.9 .. .. .. .. .. 0.3 .. .. 1.1 .. 9.7 11.3 .. .. 2.0 .. .. 9.5 11.1 0.7 30.4 0.4 54.5 .. 59.6 1.1 36.9 0.0 3.8 .. .. .. 32.7 .. .. 33.7 5.6 1.9 86.0 34.9 3.3 0.3 .. 6.3 .. 11.7 1.6

30.8 .. .. 79.5 9.1 5.9 7.5 17.5 .. .. .. .. .. 16.2 .. .. 8.9 .. 10.4 20.7 .. .. 34.7 .. .. 48.2 9.0 20.2 0.0 60.2 2.0 .. 14.1 6.7 7.6 4.7 40.1 .. .. .. 46.6 .. .. 24.1 74.2 22.9 6.3 36.4 29.5 1.8 .. 43.4 .. 66.3 76.0

Food 2010

10.5 .. .. 12.4 15.1 13.7 17.7 27.8 .. .. .. .. .. 19.2 .. .. 11.0 .. 36.1 15.3 .. .. 12.1 .. .. 13.6 13.6 11.6 19.4 21.1 11.6 .. 15.1 10.3 .. 29.8 22.4 .. .. .. 5.8 .. .. 10.0 15.7 12.4 4.7 18.8 14.5 16.3 .. 19.1 .. 11.5 9.4

Structure of merchandise imports (% of total) Agricultural raw materials Fuel Ores and metals Manufactures 2010 2010 2010 2010

1.0 .. .. 0.8 0.7 1.4 1.6 1.3 .. .. .. .. .. 0.9 .. .. 0.5 .. 0.9 1.1 .. .. 1.6 .. .. 1.0 1.1 0.5 0.5 2.2 1.0 .. 2.1 0.8 .. 0.8 1.5 .. .. .. 0.9 .. .. 0.9 1.4 1.1 0.6 2.6 2.4 1.6 .. 3.2 .. 2.2 2.1

16.7 .. .. 14.7 22.0 2.1 27.5 11.9 .. .. .. .. .. 23.7 .. .. 18.6 .. 20.4 1.0 .. .. 22.1 .. .. 15.2 10.0 26.0 26.4 19.3 19.9 .. 12.5 1.4 .. 16.1 29.9 .. .. .. 19.8 .. .. 27.6 13.9 20.0 11.6 11.2 13.5 2.1 .. 13.4 .. 23.1 12.6

2.0 .. .. 2.0 0.9 0.7 0.8 1.1 .. .. .. .. .. 1.2 .. .. 1.2 .. 0.9 1.2 .. .. 1.5 .. .. 0.4 1.0 0.6 0.2 1.1 0.5 .. 0.9 1.1 .. 1.1 1.7 .. .. .. 1.6 .. .. 1.1 1.9 1.3 21.0 13.8 3.2 1.5 .. 4.1 .. 3.3 3.6

66.5 .. .. 68.5 61.0 81.6 52.4 57.8 .. .. .. .. .. 54.6 .. .. 68.7 .. 40.9 81.1 .. .. 62.8 .. .. 69.5 74.1 61.2 52.9 56.4 49.6 .. 69.4 86.5 .. 52.0 44.4 .. .. .. 65.4 .. .. 60.4 67.2 65.1 61.6 52.2 66.0 78.4 .. 60.1 .. 58.8 72.3 (continued)

TRADE AND REGIONAL INTEGRATION

Part III. Development outcomes

Drivers of growth

Table

5.1

International trade and tariff barriers (continued) Export indexes (0 low to 1 high)

Import indexes (0 low to 1 high)

Diversification 2010

Concentration 2010

Diversification 2010

Concentration 2010

0.39 0.97 0.37 0.60 0.50 0.54 0.36 0.48 0.14 0.33 0.51 0.37 0.76 0.35 0.82 0.12 0.35 0.74 0.32 0.46 0.44 0.89 0.19 0.44 0.43 0.18 0.52 0.63 0.48 0.25 0.51 0.22 0.38 0.77 0.40 0.44 0.27 0.46 0.27 0.41 0.15 0.75 0.24 0.19 0.21 0.19 0.69 0.20

0.58 0.83 0.75 0.86 0.82 0.75 0.72 0.73 0.36 0.76 0.75 0.81 0.79 0.70 0.74 0.65 0.80 0.84 0.69 0.82 0.81 0.75 0.64 0.88 0.69 0.69 0.80 0.87 0.81 0.71 0.84 0.76 0.80 0.80 0.82 0.63 0.75 0.82 0.71 0.75 0.58 0.81 0.73 0.75 0.69 0.74 0.86 0.76

0.09 0.07 0.17 0.14 0.17 0.10 0.21 0.11 0.07 0.15 0.11 0.07 0.06 0.25 0.28 0.11 0.16 0.08 0.15 0.12 0.17 0.16 0.13 0.28 0.63 0.11 0.11 0.21 0.13 0.13 0.13 0.26 0.10 0.07 0.08 0.15 0.18 0.24 0.36 0.28 0.22 0.08 0.09 0.18 0.24 0.15 0.14 0.10

0.29 0.50 0.62 0.46 0.54 0.51 0.49 0.47 0.22 0.52 0.53 0.49 0.47 0.48 0.56 0.53 0.50 0.46 0.58 0.39 0.51 0.57 0.38 0.79 0.81 0.49 0.51 0.54 0.57 0.39 0.50 0.58 0.56 0.42 0.49 0.49 0.45 0.57 0.63 0.67 0.31 0.45 0.47 0.48 0.61 0.45 0.49 0.50

0.52 0.30 0.13 0.79 0.16 0.16

0.79 0.62 0.59 0.81 0.66 0.54

0.09 0.09 0.07 0.09 0.09 0.08

0.49 0.50 0.39 0.44 0.33 0.39

Competitiveness Indicator (%) Sectoral Global Binding effect effect coverage 2005–09 2005–09 2010

24.1 5.8 -16.8 -8.2 8.0 9.4 -5.1 -1.2 20.7 -23.3 3.2 24.2 2.9 21.9 -6.1 8.1 22.3 -2.6 6.2 17.3 8.8 0.4 -7.0 -19.3 -8.2 -3.9 -13.7 23.9 -5.0 -5.8 -4.4 4.3 23.5 20.2 1.7 5.9 2.9 -6.9 -4.3 9.3 19.1 -4.3 1.5 12.4 -0.7 12.4 2.4

63.8 -14.6 -13.9 -6.7 -1.3 -10.8 17.7 -10.9 7.4 3.0 31.1 11.8 -7.9 28.5 19.4 12.4 -17.2 -5.2 -2.0 -16.2 -20.9 -1.8 -9.7 -36.2 -9.0 -1.1 -12.1 10.4 -8.0 7.2 -9.0 -30.6 -1.5 -49.5 -26.7 -7.5 -19.7 1.0 -0.7 -5.8 23.8 -10.7 2.5 19.9 10.8 2.1 -16.2

21.6

-3.9

8.0 21.7 2.4 0.4

14.3 11.2 0.4 2.9

.. .. 39.5 96.1 39.4 22.3 .. 100.0 .. .. .. .. .. 33.8 .. .. .. .. .. .. .. 97.6 15.2 100.0 .. .. .. 40.5 .. .. .. 96.1 96.6 19.5 100.0 .. 100.0 .. .. .. 96.1 .. 96.1 13.8 14.3 16.1 .. .. .. .. .. .. .. .. ..

Simple mean bound rate 2010

.. .. 28.7 19.0 42.5 67.8 .. 15.8 .. .. .. .. .. 11.2 .. .. .. .. .. .. .. 48.6 95.3 78.9 .. .. .. 28.9 .. .. .. 19.4 44.9 119.4 89.3 .. 30.0 .. .. .. 19.4 .. 19.4 120.0 80.0 73.5 .. .. .. .. .. .. .. .. ..

Tariff barriers, all products (%) Share of lines with Share of Share of lines with lines with interSimple mean Weighted national domestic specific rates peaks tariff mean tariff peaks 2010 2010 2010 2010 2010

.. .. 13.3 8.8 12.4 9.8 .. 14.7 .. .. .. .. .. 13.1 .. .. .. .. .. .. .. 13.3 12.1 9.5 .. .. .. 12.8 .. .. .. 6.3 13.0 10.9 9.9 .. 13.4 .. .. .. 7.6 .. 10.9 12.9 12.8 12.1 .. .. .. .. .. .. .. .. ..

.. .. 15.4 5.2 8.8 5.5 .. 11.6 .. .. .. .. .. 7.3 .. .. .. .. .. .. .. 9.9 9.2 10.5 .. .. .. 8.4 .. .. .. 1.8 9.1 10.6 6.0 .. 8.9 .. .. .. 4.4 .. 10.2 8.2 14.2 8.2 .. .. .. .. .. .. .. .. ..

.. .. 50.2 20.2 44.5 29.8 .. 44.3 .. .. .. .. .. 47.9 .. .. .. .. .. .. .. 51.8 36.6 21.6 .. .. .. 47.9 .. .. .. 16.7 48.9 34.9 31.4 .. 50.5 .. .. .. 17.9 .. 26.2 39.9 47.3 37.5 .. .. .. .. .. .. .. .. ..

.. .. 0.0 8.5 0.0 1.1 .. 11.9 .. .. .. .. .. 0.0 .. .. .. .. .. .. .. 0.0 0.8 5.7 .. .. .. 0.0 .. .. .. 7.1 0.0 0.0 1.0 .. 0.0 .. .. .. 7.5 .. 12.0 1.0 0.0 1.1 .. .. .. .. .. .. .. .. ..

.. .. 0.0 0.0 0.0 0.0 .. 0.0 .. .. .. .. .. 0.0 .. .. .. .. .. .. .. 0.0 0.0 0.0 .. .. .. 0.0 .. .. .. 0.0 0.0 0.0 0.0 .. 0.0 .. .. .. 0.0 .. 0.0 0.0 0.0 0.0 .. .. .. .. .. .. .. .. ..

a. Provisional. b. Data are for the most recent year available during the period speciﬁed.

Part III. Development outcomes

TRADE AND REGIONAL INTEGRATION

Tariff barriers, primary products (%)

Tariff barriers, manufactured products (%)

Simple mean tariff 2010

Weighted mean tariff 2010

Simple mean tariff 2010

Weighted mean tariff 2010

.. .. 15.5 6.1 11.4 15.4 .. 16.2 .. .. .. .. .. 15.1 .. .. .. .. .. .. .. 14.6 16.0 9.2 .. .. .. 12.8 .. .. .. 4.1 14.0 11.8 11.5 .. 14.1 .. .. .. 5.4 .. 9.7 17.5 14.4 15.7 .. .. .. .. .. .. .. .. ..

.. .. 12.4 0.5 8.1 9.4 .. 12.2 .. .. .. .. .. 5.4 .. .. .. .. .. .. .. 10.0 12.6 1.6 .. .. .. 7.9 .. .. .. 2.1 10.7 9.1 6.4 .. 7.7 .. .. .. 1.9 .. 1.3 8.7 12.4 8.8 .. .. .. .. .. .. .. .. ..

.. .. 12.9 9.0 12.5 9.1 .. 14.3 .. .. .. .. .. 12.8 .. .. .. .. .. .. .. 12.9 11.7 9.5 .. .. .. 12.8 .. .. .. 6.7 12.8 10.7 9.7 .. 13.2 .. .. .. 7.8 .. 11.1 12.4 12.6 11.6 .. .. .. .. .. .. .. .. ..

.. .. 11.8 8.2 11.8 11.6 .. 10.1 .. .. 12.3 .. .. 11.8 .. .. 17.4 .. .. .. 11.8 11.8 11.6 8.2 .. 11.3 12.1 11.8 .. 1.2 9.6 8.2 11.8 11.5 11.6 .. 11.8 .. .. .. 8.2 18.1 8.2 11.6 11.8 11.6 .. .. .. .. .. .. .. .. ..

TRADE AND REGIONAL INTEGRATION

Average cost to ship 20 ft container from port to final destination ($) Export Import 2010 2010

1,960 1,850 1,049 3,185 2,412 2,965 1,379 1,200 5,491 5,902 1,207 3,055 3,818 1,969 1,411 1,431 1,760 1,945 831 1,013 855 1,448 2,055 1,680 1,220 1,197 1,675 2,202 1,520 737 1,100 1,800 3,545 1,263 3,275 690 1,098 876 1,573 .. 1,531 2,050 1,855 1,255 940 2,880 2,678 3,280 809 1,248 836 613 .. 577 773

2,502 2,690 1,496 3,420 4,030 4,855 2,167 1,000 5,554 8,525 1,191 3,285 7,709 2,577 1,411 1,581 2,660 1,955 885 1,315 1,391 2,006 2,190 1,665 1,200 1,555 2,570 3,067 1,523 689 1,545 1,905 3,545 1,440 4,990 577 1,740 876 1,639 .. 1,795 2,900 2,030 1,430 1,109 3,015 3,315 5,101 958 1,318 911 755 .. 950 858

Average time to clear customs (days) Direct exports Imports 2010-11b 2010–11b

6.7 .. 6.2 .. .. .. .. 9.5 .. .. 18.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 12.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

11.4 .. 3.7 .. .. .. .. 11.9 .. .. 45.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 16.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

.. .. .. .. .. ..

Part III. Development outcomes

Drivers of growth

Table

5.2

Top three exports and share in total exports, 2010 First

Product

SUB–SAHARAN AFRICA Angola Petroleum oils and oils obtained from bituminous minerals, crude Benin Petroleum oils & oils obtained from bituminous minerals (other than crude) & preparation Botswana Diamonds non-industrial unworked or simply sawn, cleaved or bruted Burkina Faso Cotton, not carded or combed

Second

97.3 35.3 43.7 37.4

Burundi Cameroon Cape Verde Central African Republic Chad

Coffee, not roasted, not decaffeinated Petroleum oils and oils obtained from bituminous minerals, crude Yellowﬁn tunas (Thunnus albacares) Wood in the rough, other Petroleum oils and oils obtained from bituminous minerals, crude

70.2 42.1 20.2 31.0 80.6

Comoros Congo Congo, Dem. Rep. Cote d'Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali

Cloves (whole fruit, cloves and stems) Petroleum oils and oils obtained from bituminous minerals, crude Cathodes and sections of cathodes Cocoa beans, whole or broken, raw or roasted Petroleum oils and oils obtained from bituminous minerals, crude Sheep Coffee, not roasted, not decaffeinated Petroleum oils and oils obtained from bituminous minerals, crude Cashew nuts, in shell Cocoa beans, whole or broken, raw or roasted Aluminium ores and concentrates Cashew nuts, in shell, fresh or dried Black tea (fermented) and other partly fermented tea Diamonds non-industrial unworked or simply sawn, cleaved or bruted Technically speciﬁed natural rubber Shrimps and prawns Tobacco, partly or wholly stemmed/stripped Cotton, not carded or combed

38.8 85.1 24.7 32.3 78.0 11.2 42.1 75.8 20.3 46.4 31.7 92.9 18.6 37.0 19.4 9.5 53.0 35.7

Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal

Iron ores & concentrates, non-agglomerated Tunas, skipjack and bonito Aluminium unwrought, not alloyed Natural uranium and its compounds Natural uranium and its compounds Petroleum oils and oils obtained from bituminous minerals, crude Coffee, not roasted, not decaffeinated Cocoa beans, whole or broken, raw or roasted Petroleum oils & oils obtained from bituminous minerals (other than crude) & preparations Tunas, skipjack and bonito Diamonds non-industrial unworked or simply sawn, cleaved or bruted Goats Platinum unwrought or in powder form Petroleum oils and oils obtained from bituminous minerals, crude Raw sugar, cane Other Precious metal ores and concentrates, other than silver Cocoa beans, whole or broken, raw or roasted Coffee, not roasted, not decaffeinated Copper cathodes and sections of cathodes unwrought Tobacco, partly or wholly stemmed/stripped

49.3 11.3 48.0 26.8 80.6 85.9 30.4 36.3 26.4 49.6 26.9 31.3 7.6 90.3 16.5 14.5 26.7 32.9 48.0 20.5

Petroleum oils and oils obtained from bituminous minerals, crude Live animals, n.e.s. Petroleum oils and oils obtained from bituminous minerals, crude Petroleum oils and oils obtained from bituminous minerals, crude Phosphoric acid and polyphosphoric acids

45.0 49.7 18.3 82.1 7.6

Tunisia

Petroleum oils and oils obtained from bituminous minerals, crude

11.7

Africaa

Petroleum oils and oils obtained from bituminous minerals, crude

Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco

Share of total exports (%)

Share of total exports (%) Product

46.6 [46.6]

Gold (incl. gold plated with platinum), in unwrought forms (excl. powder)

15.5

Nickel mattes Gold (incl. gold plated with platinum), non-monetary, in semi-manufactured forms Black tea (fermented) and other partly fermented tea Cocoa beans, whole or broken, raw or roasted Fish, whole or in pieces, but not minced :-- Other Diamonds unsorted whether or not worked Petroleum oils & oils obtained from bituminous minerals (other than crude) & preparations

21.9 15.8 13.1 15.8 19.6 22.3 8.6

Vessels for the transport of goods & for the transport of both persons & goods

20.3

Cobalt ores and concentrates Petroleum oils and oils obtained from bituminous minerals, crude Natural gas, liquefied Cardamoms Sesamum seeds Manganese ores and concentrates Crude oil Cocoa paste, not defatted Petroleum oils and oils obtained from bituminous minerals, crude Ferrous waste and scrap, iron or steel, nes Cut flowers fresh Mens/boys trousers and shorts, of cotton, not knitted Petroleum oils and oils obtained from bituminous minerals, crude Vanilla Black tea (fermented) and other partly fermented tea Petroleum oils & oils obtained from bituminous minerals (other than crude) & preparations Copper ores and concentrates T-shirts, singlets and other vests, of cotton, knitted Electrical energy Diamonds non-industrial unworked or simply sawn, cleaved or bruted Light oils and preparations Natural gas, liquefied Niobium, tantalum and vanadium ores and concentrates Wrist-watches other than automatic winding Portland cement (excl. white cement, whether/not artificially coloured), whether/not coloured Bigeye tunas (Thunnus obesus) Aluminium ores and concentrates Sheep Gold (incl. gold plated with platinum), in unwrought forms (excl. powder)

17.8 12.5 14.7 9.2 22.5 12.3 14.9 7.2 21.0 0.0 13.1 15.0 15.4 6.6 6.9 29.1

8.3 14.8 29.5 6.9

Mixtures of odoriferous substances, of a kind used in the food or drink industries Tobacco, partly or wholly stemmed/stripped Gold (incl. gold plated with platinum), in unwrought forms (excl. powder) Tobacco, partly or wholly stemmed/stripped Unreﬁned copper; copper anodes for electrolytic reﬁning Ferro-chromium containing by weight more than 4% of carbon

15.2 8.7 12.8 9.9 26.7 15.3

Natural gas, in gaseous state Coffee, not roasted, not decaffeinated Natural gas, liqueﬁed Natural gas, in gaseous state Ignition wiring sets and other wiring sets of a kind used in vehicles, aircraft or ships Ignition wiring sets and other wiring sets of a kind used in vehicles, aircraft or ships Natural gas, in gaseous state

20.0 12.3 9.5 6.9 6.5

13.6 11.0 7.5 16.1 7.6 6.9 24.8 17.4 10.5

6.8 3.2 [10.2]

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 for product.

Part III. Development outcomes

TRADE AND REGIONAL INTEGRATION

Third Share of total exports (%)

Number of exports accounting for 75 percent of total exports

9.3

1 6

Diamonds non-industrial nes excluding mounted or set diamonds Gold (incl. gold plated with platinum), in unwrought forms (excl. powder)

8.9 10.8

4 5

Tropical wood speciﬁed Mackerel Tropical wood speciﬁed

7.2 12.0 15.7

2 6 6 4 1

Essential oils, nes

15.6

Copper ores and concentrates Cocoa paste, not defatted

11.9 8.8

Men’s/boys’ shirts, of cotton Cut ﬂowers fresh

8.6 10.7

Titanium ores and concentrates Manganese ores and concentrates Natural gas, liqueﬁed Logs, non-coniferous nes Coffee, not roasted, not decaffeinated Women’s/girls’, trousers & shorts, of cotton, not knitted Vessels for the transport of goods & for the transport of both persons & goods Jerseys, pullovers, cardigans, waist-coats & similar articles, knitted/crocheted, of wool Natural uranium and its compounds Sesamum seeds

11.2 5.7 20.7 0.0 6.1 7.5 15.0 4.6 6.8 7.8

Octopus, other than live/fresh/chilled Cane/beet sugar & chemically pure sucrose, in solid form, not containing added ﬂavouring/colouring matter Natural gas, liqueﬁed Unwrought Zinc, containing by weight 99.99 % or more of zinc

7.0 6.4 5.0 13.4

Black tea (fermented) and other partly fermented tea Articles of jewelry & parts thereof , of silver, whether/not plated/clad with other precious metal Phosphoric acid and polyphosphoric acids

13.8 9.7 9.8

Yellowﬁn tunas (Thunnus albacares) Cocoa beans, whole or broken, raw or roasted Live bovine animals other than pure-bred breeding animals

6.9 11.8 13.1

Food preparations nes Coffee, not roasted, not decaffeinated Cement clinkers Fish ﬁllets and other ﬁsh meat (whether or not minced), fresh or chilled

10.7 6.4 10.1 9.3

Product

Light oils and preparations

4 1 6 10 1 19 3 1 9 9 4 1 48 6 6 32 5 4 4 43 8 6 1 1 4 8 18 5 11 4 92 1 20 24 8 13 3 17

Nickel, not alloyed, unwrought

7.1

Natural gas, liqueﬁed Sheep Light oils and preparations Petroleum oils & oils obtained from bituminous minerals (other than crude) & preparations

8.7 8.5 5.5 4.5

4 4 76 1 69

Mens/boys trousers and shorts, of cotton, not knitted

4.7

3.1 [16.3]

Natural gas, liquiﬁed

TRADE AND REGIONAL INTEGRATION

Part III. Development outcomes

Drivers of growth

Table

5.3

Regional integration, trade blocs Year of entry into force Type of of most most recent recent Year established agreement agreementa

Economic and Monetary Community of Central African States (CEMAC )

1994

Economic Community of the Great Lakes Countries (CEPGL)

1976

1999

CU NNA

1990

1995

Merchandise exports within bloc ($ millions) 2000 2005 2006 2007 2008

119.6

96.1

201.0

247.4

305.0

354.7

300.5

383.0

7.0

8.0

10.2

20.2

24.4

29.1

72.6

63.6

80.7

2,917.3

4,021.0

6,674.7

6,140.4

8,157.8

1,061.5 1,385.2

1,797.0

1,572.2 1,996.7

1994

FTA

East African Community (EAC)

1996

2000

334.5

628.4

689.4

1,075.3

Economic Community of Central African States (ECCAS)

1983

2004b

NNA

159.7

157.1

181.6

254.6

Economic Community of West African States (ECOWAS)

1975

1993

PTA

1,532.3

Indian Ocean Commission (IOC)

1984

2005b

NNA

62.6

Southern African Development Community (SADC)

1992

2000

FTA

1,655.3

West African Economic and Monetary Union (UEMOA)

1994

2000

620.8

Economic and Monetary Community of Central African States (CEMAC )

1994

Economic Community of the Great Lakes Countries (CEPGL)

1976

Common Market for Eastern and Southern Africa (COMESA)

1994

East African Community (EAC) Economic Community of Central African States (ECCAS)

2010

138.7

Common Market for Eastern and Southern Africa (COMESA)

Year of entry into force of most Type of recent most recent Year established agreement agreementa

2009

1,146.0 1,366.9

1990

1,442.6 2,694.4

449.2

378.3

482.5

1,874.8 2,728.2 5,546.1 5,955.4 6,802.2 9,469.9

7,319.6

8,910.7

182.4

184.1

113.0

106.0

3,615.4 4,426.5

162.1

312.8

181.7

385.4

214.0

217.7

7,798.5 8,700.2 12,050.6 16,009.9 12,003.3 14,575.9

559.7

760.4

1,412.1

1,531.7

1,779.4

2,339.1

1995

Merchandise exports within bloc (% of total bloc exports) 2000 2005 2006 2007 2008

1,937.6 2,250.3

2009

2010

2.3

2.1

1.0

0.9

1.1

0.8

1.2

NNA

0.5

0.8

1.2

1.3

1.4

1.9

2.2

1.5

1994

FTA

4.7

6.1

4.6

3.9

4.5

5.4

7.1

7.7

1996

2000

17.7

19.5

22.6

18.0

16.3

17.8

19.2

18.9

20.3

1983

2004b

NNA

1.4

1.5

1.0

0.6

0.5

0.6

0.4

0.6

1999

Economic Community of West African States (ECOWAS)

1975

1993

PTA

8.0

9.0

7.7

9.4

7.9

8.7

9.9

8.8

Indian Ocean Commission (IOC)

1984

2005b

NNA

3.9

5.9

4.4

4.9

5.0

5.8

5.7

5.8

5.3

Southern African Development Community (SADC)

1992

2000

FTA

6.6

10.2

9.5

9.3

9.1

10.2

10.3

11.3

9.8

West African Economic and Monetary Union (UEMOA)

1994

2000

13.0

10.3

13.5

13.7

13.3

15.4

16.4

13.2

14.6

Part III. Development outcomes

TRADE AND REGIONAL INTEGRATION

Year of entry into force Type of of most most recent recent Year established agreement agreementa

Economic and Monetary Community of Central African States (CEMAC )

1994

Economic Community of the Great Lakes Countries (CEPGL)

1976

1999

Merchandise exports by bloc (% of world exports) 2005 2006 2007

1990

1995

2000

2008

2009

2010

0.3

0.2

0.3

0.2

NNA

0.0

Common Market for Eastern and Southern Africa (COMESA)

1994

FTA

0.8

0.7

0.6

0.8

0.7

East African Community (EAC)

1996

2000

0.1

Economic Community of Central African States (ECCAS)

1983

2004b

NNA

0.6

0.4

0.5

0.7

0.5

0.6

Economic Community of West African States (ECOWAS)

1975

1993

PTA

0.9

0.7

0.6

0.7

0.6

0.7

Indian Ocean Commission (IOC)

1984

2005b

NNA

0.1

0.0

Southern African Development Community (SADC)

1992

2000

FTA

1.4

1.1

0.8

1.0

0.8

1.0

West African Economic and Monetary Union (UEMOA)

1994

2000

0.2

0.1

Note: Regional Bloc membership is as follows: 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 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, Libyan Arab Republic, 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, Comoros, Madagascar, Mauritius, Réunion, and Seychelles; Southern African Development Community (SADC), Angola, Botswana, the Democratic Republic of Congo, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia, and Zimbabwe; West African Economic and Monetary Union (WAEMU or UEMOA), Benin, Burkina Faso, Côte d’Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo. a. CU is customs union; EIA is economic integration agreement; FTA is free trade agreement; NNA is not notified agreement, which refers to preferential trade agreements established among member countries that are not notified 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 official website of the trade bloc.

TRADE AND REGIONAL INTEGRATION

Part III. Development outcomes

Drivers of growth

Table

6.1

Water and sanitation Financing Access, supply side Internal fresh water resources per capita (cubic meters) 2009

4,708 7,976 1,197 1,211 782 1,231 14,237 610 32,653 1,371 1,677 14,018 56,324 3,971 38,173 549 1,503 110,997 1,784 1,272 23,153 10,781 525 2,433 52,139 16,746 1,118 4,024 118 2,158 4,388 2,747 234 1,431 921 13,414 2,131 .. 27,878 658 908 706 2,530 1,930 1,949 1,205 6,303 983 288 322 344 23 96 917 402

Access, demand side Population with sustainable access Population with sustainable to an improved water source access to improved sanitation (% of (% of (% of (% of (% of (% of rural urban total rural urban total population) population) population) population) population) population) 2010 2010 2010 2010 2010 2010

61 51 75 96 79 72 77 88 67 51 95 45 71 80 .. .. 44 87 89 86 74 64 59 78 73 46 83 64 50 99 47 93 49 58 65 89 72 .. 55 29 91 58 71 53 61 72 61 80 92 83 88 99 .. 83 ..

83 60 84 99 95 83 95 90 92 70 91 79 95 91 .. .. 97 95 92 91 90 91 82 91 88 74 95 87 52 100 77 99 100 74 76 89 93 100 87 66 99 67 91 79 89 95 87 98 95 85 99 100 .. 98 99

49 38 68 92 73 71 52 85 51 44 97 27 32 68 .. .. 34 41 85 80 65 53 52 73 60 34 80 51 48 99 29 90 39 43 63 88 56 .. 35 7 79 52 65 44 40 68 46 69 88 79 54 99 .. 61 ..

31 58 13 62 17 46 49 61 34 13 36 24 18 24 .. .. 21 33 68 14 18 20 32 26 18 15 51 22 26 89 18 32 9 31 55 26 52 .. 13 23 79 26 57 10 13 34 48 40 90 95 50 95 97 70 ..

42 85 25 75 50 49 58 73 43 30 50 24 20 36 .. .. 29 33 70 19 32 44 32 32 29 21 49 35 51 91 38 57 34 35 52 30 70 98 23 52 86 44 64 20 26 34 57 52 94 98 63 97 97 83 96

23 19 5 41 6 46 36 43 28 6 30 24 15 11 .. 4 19 30 65 8 11 9 32 24 7 12 51 14 9 88 5 17 4 27 56 19 39 .. 6 6 67 14 55 7 3 34 43 32 84 88 10 93 96 52 ..

Committed nominal investment in water projects with private participation ($ millions) 2000-10a

.. .. .. .. .. 0.0 .. .. .. .. .. 0.0 0.0 .. .. .. .. .. 0.0 .. .. .. .. .. .. .. .. .. 0.0 .. 0.0 3.4 .. .. .. 0.0 .. .. .. 0.0 120.7 .. 8.5 .. 0.0 0.0 .. 468.0 .. .. .. .. ..

ODA gross disbursements for water supply and sanitation sector ($ millions) 2009 2010

1,786.4 15.1 54.1 0.0 58.9 19.5 6.5 20.4 9.4 28.6 1.4 65.2 0.4 30.7 0.0 7.4 114.4 2.1 5.0 56.2 11.3 2.6 94.7 23.1 8.1 12.3 16.1 69.2 82.7 1.1 94.8 12.0 42.2 102.4 19.5 1.0 58.3 0.6 9.7 5.2 60.9 55.2 0.3 190.3 5.3 105.9 50.8 7.6 370.6 10.9 6.8 129.0 0.0 122.3 94.3

1,892.8 8.7 69.1 0.8 64.9 31.5 17.7 11.8 5.4 34.5 0.8 98.6 2.0 36.2 .. 7.3 116.8 8.7 3.2 89.6 10.0 1.0 143.0 36.5 7.3 9.8 22.2 49.0 78.7 0.5 94.1 13.5 38.5 109.6 35.5 3.1 48.7 0.6 10.4 3.0 48.7 62.1 0.6 211.9 4.6 61.1 38.8 15.9 358.9 11.0 8.1 72.3 .. 145.2 116.6

a. Data are for the most recent year available during the period speciﬁed.

Part III. Development outcomes

INFRASTRUCTURE

Drivers of growth

Table

6.2

Transportation Access, supply side

Road network (km) 2000–09a

51,429 19,000 25,798 92,495 12,322 28,857 1,350 24,307 40,000 880 153,497 17,000 81,996 2,880 4,010 44,359 9,170 3,742 109,515 44,348 3,455 61,945 5,940 10,600 49,827 15,451 22,474 11,066 2,066 30,331 42,100 18,948 193,200 14,008 320 14,825 508 11,300 22,100 362,099 11,900 3,594 103,706 11,652 70,746 66,781 97,267 112,039 3,065 100,472 83,200 58,216 19,371

Rail lines (km) 2010

.. .. .. 888 622 .. 977 .. .. .. .. 3,641 .. 639 .. .. .. 810 .. .. .. .. .. .. .. .. .. .. 728 .. 3,116 .. .. .. .. .. .. .. .. .. 22,051 4,508 300 .. .. .. .. .. 11,935 3,512 .. 5,195 .. 2,109 1,119

Access, demand side Vehicle fleet (per 1,000 people)

Road density Ratio to total land (road km/100 sq km of land area) 2000–09a

Commercial vehicles 2000–09a

Passenger vehicles 2000–09a

4.0 17.0 4.0 34.0 44.0 11.0 33.0 4.0 3.0 39.0 7.0 5.0 25.0 10.0 3.0 4.0 3.0 33.0 24.0 18.0 12.0 11.0 20.0 10.0 8.0 13.0 2.0 1.0 99.0 4.0 0.0 1.0 21.0 53.0 33.0 8.0 110.0 .. 3.0 30.0 1.0 21.0 9.0 21.0 29.0 12.0 25.0

38.0 22.0 133.0 11.0 6.0 14.0 101.0 0.3 6.0 33.0 5.0 27.0 20.0 .. 11.0 3.0 .. 8.0 30.0 .. 33.0 23.0 .. 3.0 26.0 8.0 14.0 .. 166.0 12.0 103.0 8.0 31.0 5.0 2.0 22.0 173.0 6.0 .. 162.0 27.0 89.0 7.0 2.0 8.0 21.0 114.0

8.0 18.0 69.0 7.0 2.0 10.0 73.0 0.3 2.0 31.0 .. 16.0 16.0 .. 6.0 1.0 .. 5.0 18.0 .. 27.0 13.0 .. 2.0 7.0 4.0 8.0 .. 129.0 9.0 46.0 6.0 31.0 2.0 2.0 16.0 103.0 5.0 .. 110.0 19.0 45.0 4.0 2.0 3.0 13.0 98.0

5.0 14.0 10.0 5.0 13.0 12.0

112.0 .. 45.0 290.0 70.0 114.0

74.0 .. 33.0 225.0 53.0 76.0 (continued)

INFRASTRUCTURE

Part III. Development outcomes

Drivers of growth

Table

6.2

Transportation (continued) Quality

Ratio of paved to total roads (%) 2000–09a

10.4 9.5 32.6 4.2 10.4 17.0 69.0 .. 0.8 76.5 1.8 7.1 7.9 .. 21.8 13.7 12.0 19.3 12.6 9.8 27.9 14.3 18.3 6.2 11.6 45.0 24.6 26.9 98.0 20.8 14.7 20.7 15.0 19.0 68.1 32.0 96.5 8.0 11.8 17.3 36.3 30.0 6.7 21.0 23.0 22.0 19.0 74.0 45.0 89.4 57.2 70.3 75.2

Pricing Price of diesel fuel ($ per liter) 2010

1.15 0.43 1.21 0.97 1.28 1.42 1.10 1.33 1.69 1.31 .. 1.27 0.84 1.30 .. 1.07 0.78 .. .. 0.83 0.95 .. 1.27 1.07 0.96 1.26 1.54 1.25 0.99 1.23 0.86 1.09 1.16 0.77 1.62 .. 1.34 .. 0.94 .. 1.14 0.43 1.10 1.19 1.17 1.11 1.52 1.15 0.57 0.19 1.07 0.32 0.13 0.88 0.82

Financing Price of gasoline ($ per liter) 2010

1.22 0.65 1.04 0.93 1.44 1.43 1.20 1.84 1.71 1.32 .. 1.28 1.27 1.68 .. 2.54 0.91 .. .. 0.82 0.95 .. 1.33 0.97 0.98 1.52 1.71 1.42 1.16 1.55 1.11 1.06 1.07 0.44 1.63 .. 1.57 .. 0.94 .. 1.19 0.62 1.07 1.22 1.18 1.42 1.66 1.29 0.71 0.32 1.63 0.48 0.17 1.23 0.94

Committed nominal investment in transport projects with private participation ($ millions) 2000-09a

53.0 .. .. .. .. 0.0 .. .. .. 0.5 .. 0.0 0.0 .. .. .. 3.9 .. 0.0 159.0 .. 404.0 .. 120.0 17.5 .. 55.4 .. .. 0.0 .. .. 382.0 .. .. 264.0 .. 130.0 .. 3483.0 30.0 .. 134.0 .. 404.0 15.6 .. 108.0 396.0 640.0 .. 200.0 840.0

ODA gross disbursements for transportation and storage ($ millions) 2009 2010

2,254.6 8.3 92.1 12.9 60.6 46.0 92.0 56.0 17.8 45.3 2.2 136.6 21.2 17.6 .. 2.9 229.6 10.3 9.7 105.9 28.6 15.1 127.3 9.2 30.8 40.3 22.3 28.1 27.6 .. 103.0 52.9 39.2 57.7 34.7 1.6 89.7 .. 34.1 1.7 0.1 79.6 0.4 145.5 0.2 103.1 35.0 0.0 600.8 76.0 15.9 111.3 .. 304.3 88.4

2,714.0 25.0 116.6 6.3 59.8 55.7 94.7 73.7 27.0 5.0 1.8 146.1 9.2 26.8 .. 3.2 226.8 25.5 19.4 136.4 50.0 1.3 118.7 16.7 68.4 55.0 24.9 65.8 21.0 6.5 109.6 42.6 53.1 63.9 20.9 1.8 111.8 0.0 43.1 7.9 7.4 85.9 0.8 271.1 1.5 153.0 32.9 3.9 853.6 22.4 6.7 198.6 .. 487.6 130.6

a. Data are for the most recent year available during the period speciﬁed.

Part III. Development outcomes

INFRASTRUCTURE

Drivers of growth

Table

6.3

Information and communication technology Access, supply side Telephone subscribers (per 100 people)

SUB-SAHARAN AFRICA Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Cote d'Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco Tunisia

Total 2010

Mainline telephone 2010

Mobile telephone 2010

46.4 48.3 81.5 124.6 35.5 14.1 46.8 89.5 22.4 24.3 25.4 18.0 94.2 77.6 59.0 4.6 9.4 109.0 88.3 72.6 40.3 39.5 62.6 47.3 39.5 37.9 21.5 49.2 81.4 123.2 31.3 73.9 25.1 55.8 33.8 66.8 69.9 160.5 34.3 8.0 109.2 41.4 73.6 47.2 44.2 39.4 42.8 64.3 106.1 100.7 20.7 99.0 190.9 111.8 117.6

1.4 1.6 1.5 6.9 0.9 0.4 2.8 14.5 0.1 0.5 2.9 0.1 0.2 1.4 1.9 1.0 1.1 2.0 2.8 1.1 0.2 0.3 0.9 1.8 0.2 0.7 1.1 0.8 2.1 29.8 0.4 6.7 0.5 0.7 0.4 4.6 2.8 25.5 0.2 1.1 8.4 0.9 3.7 0.4 3.5 1.0 0.7 3.0 11.3 8.2 2.1 11.9 19.3 11.7 12.3

45.0 46.7 79.9 117.8 34.7 13.7 44.1 75.0 22.3 23.8 22.5 17.9 94.0 76.1 57.0 3.5 8.3 106.9 85.5 71.5 40.1 39.2 61.6 45.5 39.3 37.2 20.4 48.4 79.3 91.7 30.9 67.2 24.5 55.1 33.4 62.0 67.1 135.9 34.1 7.0 100.5 40.5 61.8 46.8 40.7 38.4 41.6 61.3 94.8 92.4 18.6 87.1 171.5 100.1 106.0

Access, demand side Average delay for Unmet Households with firm in obtaining demand (% of mainline own telephone a mainline phone telephones) (% of households) connection (days) 2008 2009-10a 2009-10a

.. .. .. .. .. 0.1 .. 0.4 .. .. 22.9 .. .. .. .. 49.5 2.1 .. .. 0.2 .. .. 0.4 .. .. 0.1 .. .. .. .. .. .. .. .. .. .. .. 9.8 .. .. .. 0.0 0.2 .. .. .. .. .. .. .. .. 0.3 .. .. 0.9

1.5 .. .. .. 16.4 .. .. .. .. .. .. 1.0 .. .. .. .. .. .. .. .. .. 1.2 .. .. 1.0 2.0 .. .. .. .. .. .. 0.9 0.3 .. 14.5 .. .. .. 16.7 .. .. .. .. .. .. 4.1

9.3 89.4 17.1 19.5 .. 19.2 8.2 .. 13.3 .. 20.1 25.5 5.8 .. .. .. 8.6 .. .. .. .. .. 53.7 .. 29.9 45.9 13.8 .. 38.6 .. .. 13.9 .. .. .. .. .. 21.4 .. .. .. .. .. 51.0 .. .. ..

24.8 .. 43.9 .. 39.4 24.1

.. .. .. .. .. ..

Internet users (per 100 people) 2010

11.3 10.0 3.1 6.0 1.4 2.1 4.0 30.0 2.3 1.7 5.1 0.7 5.0 2.6 6.0 5.4 0.8 7.2 9.2 9.6 1.0 2.5 25.9 3.9 7.0 1.7 2.3 2.7 3.0 28.7 4.2 6.5 0.8 28.4 13.0 18.8 16.0 41.0 .. .. 12.3 .. 9.0 11.0 5.4 12.5 10.1 11.5 28.0 12.5 6.5 26.7 14.0 49.0 36.6

Quality Telephone faults Cleared by next Total working day (per 100 (%) mainlines) 2010 2010

.. .. 6.0 .. .. .. .. 3.0 .. .. .. .. .. 10.2 .. 61.0 5.9 .. .. 1.1 .. .. 3.7 .. .. 12.4 .. .. .. .. .. .. .. .. 0.0 .. .. .. .. .. .. .. .. .. .. .. .. 36.0 .. .. .. 0.1 .. .. 29.0

.. .. 35.0 .. .. .. .. 93.0 .. .. .. .. .. .. .. 17.3 64.3 .. .. 72.0 .. .. 72.6 .. .. 83.5 .. .. .. .. .. .. .. .. 98.0 .. .. .. .. .. .. .. .. .. .. .. .. 87.0 .. .. .. 97.5 .. .. 90.0 (continued)

INFRASTRUCTURE

Part III. Development outcomes

Drivers of growth

Table

6.3

Information and communication technology (continued)

Cost of 3-minute call during peak hours ($)

Fixed broadband internet subscription ($ per month) 2010

Fixed telephone local 2010

55.6 133.2 50.5 29.3 83.2 .. 80.8 31.8 603.7 11.9 390.4 .. 180.1 40.4 242.3 .. 295.7 .. 292.9 31.5 903.5 .. 37.9 50.5 .. 89.5 562.2 50.5 23.6 16.2 50.1 117.7 60.1 53.2 162.9 282.8 36.3 47.2 .. .. 27.2 28.6 867.2 31.9 166.8 16.2 58.0 .. 13.3 14.8 60.2 8.0 39.5 11.8 10.5

0.23 0.25 0.12 0.23 0.30 0.06 0.36 0.14 .. 0.36 0.13 .. 0.61 0.36 .. .. 0.01 .. .. 0.13 0.03 .. 0.23 0.23 0.00 0.28 0.18 0.11 0.37 0.08 0.27 0.25 0.15 0.18 0.37 0.09 0.24 0.06 0.00 .. 0.27 .. 0.08 0.30 0.21 0.21 0.83 .. 0.09 0.15 0.09 0.03 .. 0.24 0.02

Pricing Cost of 3-minute call during off-peak hours ($)

Connection charge ($) Mobile cellular

Cellular local 2009

Fixed telephone local 2010

Cellular local 2009

Residential telephone 2010

Business telephone 2010

0.63 0.65 0.55 0.75 0.95 .. 0.95 0.91 0.76 1.14 0.64 .. .. 0.63 .. 0.35 0.21 .. 0.37 0.31 .. 0.57 0.31 0.70 .. 0.65 0.59 0.70 0.63 0.13 0.72 0.89 0.79 0.60 0.45 0.47 0.54 0.92 .. .. 0.89 0.18 0.78 0.59 0.73 0.50 0.70 .. 0.41 0.33 0.54 0.11 .. 1.34 0.49

0.13 0.2 0.1 0.2 0.2 0.1 0.4 0.1 .. 0.4 0.1 .. 0.6 0.0 .. .. 0.0 .. .. 0.1 0.0 .. 0.2 0.2 0.0 0.1 0.1 0.1 0.3 0.1 0.1 0.2 0.2 0.2 0.3 0.1 0.1 0.1 0.0 .. 0.2 .. 0.0 0.2 0.1 0.1 0.5 .. 0.1 0.2 0.1 0.0 .. 0.2 0.0

0.65 0.7 0.6 0.8 1.0 .. 1.0 0.9 0.8 1.1 0.6 .. .. 0.6 .. 0.4 0.2 .. 0.4 .. .. 0.6 0.3 0.7 .. 0.7 0.6 0.7 0.6 0.1 0.7 0.9 0.8 0.6 0.5 0.5 0.5 0.9 .. .. 0.9 0.2 0.8 .. 0.7 .. 0.7 .. 0.4 0.3 0.5 0.1 .. 1.3 0.5

37.6 49.0 194.8 37.9 59.6 22.8 48.2 36.0 .. 107.2 109.0 .. 168.1 20.2 47.4 .. 16.8 .. .. 31.5 5.2 .. 42.9 46.0 0.2 28.2 13.9 78.0 0.0 37.4 14.3 40.1 30.3 0.0 51.5 22.7 46.5 46.2 0.0 .. 67.1 .. 29.1 18.2 71.5 67.8 10.4 .. 14.0 5.4 56.3 6.1 .. 71.3 14.0

46.5 49.0 354.7 55.6 59.6 22.8 120.4 .. .. 107.2 109.0 .. 168.1 .. .. .. 16.8 .. .. 31.5 19.0 .. 42.9 .. .. 28.2 .. 78.0 18.1 74.7 14.3 40.1 30.3 .. .. 22.7 46.5 46.2 0.0 .. 67.1 .. 48.6 .. 71.5 67.8 31.3 .. 77.1 .. 56.3 97.8 .. 142.6 14.0

Prepaid 2009-10a

Postpaid 2009-10a

.. 2.1 1.5 .. .. 2.0 .. .. 1.1 .. .. 1.3 .. .. 50.1 2.7 2.0 0.3 0.7 .. 1.0 0.6 6.8 .. 1.0 .. 0.0 1.8 3.5 0.7 2.7 1.6 1.0 0.0 4.5 4.2 2.0 .. .. .. 2.2 2.1 0.5 2.1 .. .. ..

.. 5.3 1.4 6.4 .. 5.3 .. 2.1 1.0 .. .. .. .. .. 100.2 14.4 .. 11.3 0.7 .. 1.1 1.3 5.9 .. 0.5 2.8 2.1 1.9 3.1 0.7 2.2 3.2 .. 1.8 8.6 4.2 3.7 .. .. 17.6 2.2 1.8 0.4 2.1 1.5 .. ..

5.5 60.2 2.5 7.9 2.5 3.6

6.9 28.1 2.9 .. 14.9 3.7

Fixed broadband internet 2010

61.2 58.8 30.3 40.5 .. .. 101.0 27.6 199.9 506.8 161.5 .. 108.1 50.5 252.4 .. .. .. 35.7 38.4 2371.7 .. 50.5 61.5 .. 0.0 702.7 98.9 25.3 37.4 .. 40.1 48.1 0.0 171.5 113.1 50.5 60.9 .. .. 81.7 47.7 316.3 .. 119.1 135.5 962.8 .. 0.0 .. 60.2 0.0 55.3 0.0 0.0

a. Data are for the most recent year available during the period speciﬁed.

Part III. Development outcomes

INFRASTRUCTURE

Financing Annual investment ($ millions)

Fixed telephone service 2010

Mobile communication 2010

140.4 .. .. .. .. .. .. 0.3 .. .. 1.3 .. 31.4 .. 2.6 .. .. .. .. .. .. .. .. .. 12.6 .. 12.2 .. .. .. .. .. .. .. .. 48.5 .. .. .. .. .. .. .. 31.5 .. .. .. 193.1 .. .. 193.1 .. .. ..

1,477.2 .. 93.4 .. .. .. .. .. 26.8 .. .. 119.5 .. .. .. .. .. .. .. 752.3 .. .. .. 11.2 .. .. .. 180.8 .. .. .. .. .. .. .. .. 278.6 .. .. .. .. .. .. .. 14.6 .. .. .. 1,132.0 .. .. 1,132.0 .. .. ..

INFRASTRUCTURE

Annual revenue ($ millions)

Committed nominal investment in telecommunication projects with private participaTelecommunications tion ($ millions) 2010 2010

2,728.5 .. 93.4 .. .. .. .. .. 27.1 .. .. 120.9 .. .. .. .. .. .. .. 766.4 .. .. .. 11.2 .. .. .. 193.0 .. .. .. .. .. 740.6 181.5 .. 327.1 .. .. .. .. .. 26.9 .. 46.1 194.3 .. .. 4,252.9 .. .. 3,537.0 .. 715.9 ..

11,957.0 534.0 394.0 59.0 299.0 233.0 16.0 10.0 345.0 .. 174.0 77.0 319.0 .. 125.0 290.0 71.0 19.0 492.0 11.0 15.0 132.0 116.0 254.0 133.0 26.0 80.0 .. 107.0 3,036.0 63.0 .. 236.0 .. 38.0 2,101.0 478.0 15.0 625.0 23.0 257.0 453.0 301.0 4,440.0 237.0 .. 2,113.0 .. 1,124.0 966.0

ODA gross disbursements for communication ($ millions) 2010

Fixed telephone service 2010

Mobile communication 2010

Telecommunications 2010

145.3 2.9 2.1 0.4 3.1 1.3 1.2 0.2 0.5 0.2 0.0 2.0 0.2 0.7 .. .. 6.8 0.0 0.7 7.5 0.2 1.0 6.8 0.0 0.0 0.3 1.2 0.3 0.2 0.0 8.6 (5.5) 0.9 14.9 5.6 0.1 1.0 0.0 0.6 .. 21.2 1.6 0.0 6.2 0.0 2.5 1.2 0.4 19.4 0.4 9.1 1.5 0.0 2.0 5.6

1,914.6 .. 21.8 .. .. .. 138.4 .. 2.0 .. .. 5.7 .. .. .. 28.0 175.5 .. .. 102.6 .. .. .. .. .. 34.7 .. 47.7 .. 44.3 .. .. .. 346.9 .. .. 583.5 .. .. .. .. .. 94.0 .. 106.4 183.1 .. .. 2,207.8 .. .. 956.8 .. 1,251.0 ..

11,904.9 .. 339.0 .. .. .. 712.8 .. 54.3 221.4 .. 644.3 .. .. .. 38.8 313.8 .. .. 1,044.0 .. .. .. .. .. 210.3 .. 515.5 .. 154.9 .. .. .. 6,323.0 .. .. 698.6 .. .. .. .. .. .. .. 194.5 439.6 .. .. 7,632.0 .. .. 4,549.0 .. 3,083.0 ..

14,137.3 .. 360.8 .. .. .. 851.2 .. 57.8 228.2 .. 650.0 .. .. .. 67.7 489.3 .. .. 1,171.0 .. .. .. 66.2 .. 245.0 .. 563.3 .. 234.2 .. .. .. 6,670.0 167.1 .. 1,282.0 .. .. .. .. .. .. .. 300.9 732.6 .. .. 11,275.0 .. .. 6,974.0 .. 4,301.0 ..

Part III. Development outcomes

Drivers of growth

Table

6.4

Energy

Total (billion kWh) 2009

418.4 4.2 0.1 0.4 .. .. 5.7 .. .. .. .. 7.8 0.5 5.9 .. 0.3 4.1 1.7 .. 9.0 .. .. 6.9 .. .. .. .. .. .. .. 17.0 1.7 .. 19.8 .. .. 2.9 .. .. .. 246.8 6.8 .. 4.6 0.1 .. 10.3 7.9 249.9 42.8 .. 139.0 30.4 21.4 15.7

Hydroelectric 2009

18.2 76.1 0.0 0.0 .. .. 70.0 .. .. .. .. 99.6 64.0 35.9 .. 0.0 87.3 53.2 .. 76.8 .. .. 31.6 .. .. .. .. .. .. .. 99.9 82.0 .. 22.9 .. .. 8.4 .. .. .. 0.6 47.8 .. 60.2 73.8 .. 99.7 53.3 6.4 0.8 .. 9.3 0.0 12.1 0.5

Access, demand side Energy production Sourcea (% of total) Coal Natural gas Nuclear 2009 2009 2009

56.6 0.0 0.0 100.0 .. .. 0.0 .. .. .. .. 0.0 0.0 0.0 .. 0.0 0.0 0.0 .. 0.0 .. .. 0.0 .. .. .. .. .. .. .. 0.0 17.5 .. 0.0 .. .. 0.0 .. .. .. 94.1 0.0 .. 2.7 0.0 .. 0.0 46.4 4.5 0.0 .. 0.0 0.0 52.4 0.0

4.6 0.0 0.0 0.0 .. .. 7.2 .. .. .. .. 0.4 36.1 61.9 .. 0.0 0.0 26.4 .. 0.0 .. .. 0.0 .. .. .. .. .. .. .. 0.1 0.0 .. 64.3 .. .. 1.8 .. .. .. 0.0 0.0 .. 36.2 0.0 .. 0.0 0.0 66.6 97.2 .. 68.7 41.0 13.3 89.7

3.1 0.0 0.0 0.0 .. .. 0.0 .. .. .. .. 0.0 0.0 0.0 .. 0.0 0.0 0.0 .. 0.0 .. .. 0.0 .. .. .. .. .. .. .. 0.0 0.0 .. 0.0 .. .. 0.0 .. .. .. 5.2 0.0 .. 0.0 0.0 .. 0.0 0.0 0.0 0.0 .. 0.0 0.0 0.0 0.0

Oil 2009

4.2 24.0 100.0 0.0 .. .. 22.7 .. .. .. .. 0.1 0.0 0.1 .. 99.3 12.4 20.1 .. 23.2 .. .. 44.1 .. .. .. .. .. .. .. 0.0 0.5 .. 12.8 .. .. 86.4 .. .. .. 0.0 52.2 .. 0.9 24.6 .. 0.3 0.3 21.7 2.0 .. 21.3 59.0 20.3 9.2

GDP per unit of Electric power energy use (2005 PPP $ per kg of consumption (kWh per capita) oil equivalent) 2009 2009

517.4 202.2 91.3 1,503.4 .. .. 271.2 .. .. .. .. 103.9 146.4 203.5 .. 51.0 45.8 922.5 .. 265.1 .. .. 147.4 .. .. .. .. .. .. .. 453.4 1,576.2 .. 120.5 .. .. 196.0 .. .. .. 4,532.0 114.3 .. 85.7 110.8 .. 635.0 1,026.2 1,356.4 971.0 .. 1,548.6 4,170.1 755.6 1,311.3

3.2 8.0 3.5 11.4 .. .. 5.7 .. .. .. .. 0.9 10.1 3.2 .. 3.5 2.2 10.7 .. 3.6 .. .. 3.0 .. .. .. .. .. .. .. 1.9 7.3 .. 2.9 .. .. 7.1 .. .. .. 3.2 5.3 .. 2.7 2.0 .. 2.1 .. 6.4 6.5 .. 5.9 4.7 8.8 9.5

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 speciﬁed.

Part III. Development outcomes

INFRASTRUCTURE

Firms identifying electricity as major or very severe obstacle to business operation and growth (%) 2009–10 b

Quality Average delay for firm in obtaining Electric power electrical transmission and connection distribution losses (days) (% of output) b 2009–10 2009

35.7 51.9 34.8 53.9 .. 58.6 53.1 76.1 74.6 .. 51.6 71.1 39.8 .. 0.2 .. 58.0 .. .. .. .. .. 44.3 59.1 54.6 37.6 33.5 .. 42.9 .. .. 63.2 .. .. .. .. .. 53.4 .. .. .. .. .. 50.9 .. .. ..

7.7 86.8 39.2 23.1 .. 17.6 30.5 11.8 10.6 .. 48.0 8.4 20.9 .. 0.0 .. 34.5 .. .. .. .. .. 13.9 0.0 92.1 59.2 32.9 .. 18.6 .. .. 37.1 .. .. .. .. .. 14.8 .. .. .. .. .. 53.9 .. .. ..

.. .. .. .. .. ..

INFRASTRUCTURE

11.2 10.1 .. 79.3 .. .. 9.4 .. .. .. .. 4.9 73.5 25.0 .. 11.9 9.5 18.2 .. 23.3 .. .. 15.5 .. .. .. .. .. .. .. 9.0 15.3 .. 5.9 .. .. 17.0 .. .. .. 9.8 28.1 .. 19.4 .. .. 23.4 6.6 12.9 20.6 .. 10.5 14.0 11.7 13.0

Financing Committed nominal investment in energy ODA gross projects with private disbursements participation for energy ($ millions) ($ millions) b 2009-10 2010

Electric power outages in a typical month (number) 2009–10 b

Firms that share or own their own generator (%) 2009–10 b

Firms using electricity from generator (%) 2009–10 b

5.4 13.9 4.5 10.8 .. 10.6 4.9 32.7 22.6 .. 21.8 25.3 3.8 .. 3.0 .. 7.2 .. .. .. .. .. 6.8 5.4 13.6 1.0 5.3 .. 3.2 .. .. 20.1 .. .. .. .. .. 15.9 .. .. .. .. .. 11.1 .. .. ..

79.0 50.5 34.5 28.3 .. 34.8 48.8 81.5 75.5 .. 49.3 81.8 6.5 .. 36.8 .. 22.9 .. .. .. .. .. 30.9 66.5 29.3 25.3 20.1 .. 24.5 .. .. 34.5 .. .. .. .. .. 81.8 .. .. .. .. .. 63.6 .. .. ..

17.3 10.1 0.6 2.5 .. 4.5 10.9 14.8 52.0 .. 4.2 43.2 1.0 .. 1.0 .. 1.8 .. .. .. .. .. 0.0 63.1 5.2 2.0 0.5 .. 0.8 .. .. 5.2 .. .. .. .. .. 36.6 .. .. .. .. .. 9.3 .. .. ..

.. .. .. .. .. 0.0 .. .. .. .. .. .. 0.0 .. .. 4.0 .. .. .. .. .. 116.0 .. 170.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 27.0 .. ..

.. .. .. .. .. ..

1,278.1 1.3 13.8 13.2 28.7 14.9 5.4 63.0 0.1 1.2 .. 30.3 0.4 59.6 0.0 15.7 118.0 7.9 1.3 111.7 0.3 1.2 81.5 0.2 22.6 4.5 16.2 23.4 65.8 0.5 31.8 2.4 0.1 29.8 40.9 0.2 7.9 .. 14.1 0.3 9.6 37.6 .. 136.1 3.7 135.6 20.1 16.3 822.6 0.9 16.1 397.2 27.2 108.9 260.9

Part III. Development outcomes

Participating in growth

Table

7.1

Education Primary education Literacy rate (%) Youth (ages 15–24) Adult (ages 15 and older) Total Male Female Total Male Female 2009 2009 2009 2009 2009 2009

.. 73.1 54.3 95.2 .. 76.6 .. 98.2 64.7 46.3 85.3 67.7 .. 66.6 97.9 88.7 .. 97.6 65.5 80.1 61.1 70.9 92.7 92.0 75.6 .. 86.5 .. 67.7 96.5 70.9 93.0 .. 71.8 77.2 95.3 65.0 .. 57.6 .. .. .. 93.4 77.4 .. .. 74.6 98.9 .. .. .. .. 99.9 79.5 ..

Part III. Development outcomes

.. 80.8 64.9 93.7 .. 76.9 .. 97.4 72.2 53.5 85.8 73.3 .. 72.1 97.7 91.6 .. 98.6 71.0 81.2 68.1 78.2 91.9 85.7 70.4 .. 86.9 .. 70.9 95.5 78.1 91.1 .. 78.2 77.0 94.9 74.2 .. 67.6 .. .. .. 91.9 78.5 .. .. 81.8 98.4 .. .. .. .. 99.9 86.7 ..

.. 65.5 43.4 96.7 .. 76.3 .. 99.0 57.3 39.0 84.7 62.1 .. 61.0 98.2 85.8 .. 96.6 60.0 78.9 53.8 63.6 93.6 98.1 80.9 .. 86.0 .. 64.3 97.6 63.7 94.9 .. 65.3 77.4 95.8 56.2 .. 48.1 .. .. .. 94.9 76.4 .. .. 67.3 99.5 .. .. .. .. 99.8 72.2 ..

.. 70.0 41.7 84.1 .. 66.6 .. 84.8 55.2 33.6 74.2 67.0 .. 55.3 93.3 66.6 .. 87.7 46.5 66.6 39.5 52.2 87.0 89.7 59.1 .. 73.7 .. 57.5 87.9 55.1 88.5 .. 60.8 70.7 88.8 49.7 .. 40.9 .. .. .. 86.9 72.9 .. .. 70.9 91.9 .. .. .. .. 88.9 56.1 ..

.. 82.9 54.2 83.8 .. 72.6 .. 90.1 69.1 44.5 79.7 79.5 .. 64.7 97.0 77.9 .. 91.4 57.6 72.8 50.8 66.9 90.5 82.9 63.7 .. 80.6 .. 64.5 90.6 70.1 88.9 .. 72.0 75.0 93.7 61.8 .. 52.7 .. .. .. 87.8 79.0 .. .. 80.6 94.7 .. .. .. .. 95.2 68.9 ..

.. 57.6 29.1 84.4 .. 60.9 .. 80.3 42.1 23.1 68.7 54.9 .. 45.3 89.8 56.0 .. 84.1 35.8 60.4 28.1 38.0 83.5 95.3 54.5 .. 67.0 .. 50.3 85.3 41.5 88.1 .. 49.8 66.8 84.1 38.7 .. 30.1 .. .. .. 86.2 66.9 .. .. 61.3 89.4 .. .. .. .. 82.0 43.9 ..

Gross enrollment ratio (% of relevant age group) Total Male Female 2010 2010 2010

.. 124.5 125.9 .. 75.6 156.3 119.8 109.6 93.4 92.5 .. 93.7 115.0 .. 86.6 44.6 101.6 .. 82.6 .. 94.4 123.1 .. 103.2 .. 148.6 135.5 80.4 102.0 99.4 115.1 .. 66.3 83.3 142.6 130.7 86.8 117.2 .. .. .. .. 115.8 102.3 139.6 121.1 115.3 .. .. 110.2 .. 100.7 .. 111.4 ..

103.2 137.3 134.6 .. 79.1 157.3 128.6 113.9 109.3 107.0 .. 100.4 117.9 .. 87.9 48.5 106.2 .. 81.7 .. 102.6 127.1 .. 104.5 .. 149.8 133.0 85.9 99.5 99.1 121.1 .. 72.5 87.1 141.1 130.9 84.4 117.3 .. .. .. .. 120.7 101.5 147.1 120.3 114.5 .. .. 113.4 .. 102.8 .. 115.0 ..

95.8 111.6 117.1 .. 72.0 155.3 110.9 105.3 77.7 78.0 .. 87.0 112.0 .. 85.4 40.6 96.8 .. 83.5 .. 85.9 119.2 .. 102.0 .. 147.3 138.0 74.7 104.5 99.7 109.0 .. 59.7 79.3 144.0 130.4 89.3 117.2 .. .. .. .. 110.9 103.1 132.2 122.0 116.0 .. .. 106.8 .. 98.4 .. 107.6 ..

Net enrollment ratio (% of relevant age group) Total Male Female 2010 2010 2010

.. 85.7 93.8 .. 58.1 .. 92.4 93.2 70.5 .. .. .. 90.8 .. 56.3 33.5 81.3 .. 65.5 .. 77.0 73.9 .. 73.4 .. .. .. 62.0 74.0 93.4 91.9 .. 57.2 57.6 98.8 98.4 75.5 .. .. .. .. .. 85.6 .. .. 90.9 91.4 .. .. 95.6 .. 94.4 .. 93.7 ..

77.4 93.1 .. .. 60.4 .. 98.7 94.3 80.8 .. .. .. 92.3 .. 56.5 35.8 83.9 .. 64.4 .. 83.2 75.5 .. 72.0 .. .. .. 66.3 72.5 92.4 94.5 .. 62.8 60.2 .. 97.1 73.3 .. .. .. .. .. 86.1 .. .. 89.6 90.3 .. .. 96.6 .. .. .. 94.5 ..

73.1 78.2 .. .. 55.6 .. 85.9 92.1 60.4 .. .. .. 89.3 .. 56.0 31.0 78.6 .. 66.6 .. 70.5 72.4 .. 74.8 .. .. .. 57.4 75.7 94.5 89.2 .. 51.2 54.9 .. 99.7 77.7 .. .. .. .. .. 85.0 .. .. 92.1 92.5 .. .. 94.6 .. .. .. 92.8 ..

Studentteacher ratio 2010

45.7 45.8 46.4 .. 47.8 50.6 45.5 23.6 84.3 62.2 .. 37.0 49.2 .. 27.2 38.0 54.1 .. .. .. 42.2 51.9 .. 33.8 .. 40.1 79.3 50.4 37.2 21.5 58.5 .. 38.6 36.0 64.6 26.2 33.7 12.6 .. .. .. .. 32.3 50.8 40.6 48.6 58.0 .. 25.6 23.3 .. 26.3 .. 26.2 ..

HUMAN DEVELOPMENT

Secondary education Gross enrollment ratio Net enrollment ratio (% of relevant age group) (% of relevant age group) Total Male Female Total Male Female 2010 2010 2010 2010 2010 2010

.. 31.3 .. .. 20.7 24.8 42.2 87.5 12.6 24.6 .. 37.7 .. .. .. 31.9 35.7 .. 54.1 .. .. .. .. 46.4 .. .. 32.1 37.7 24.4 89.4 25.5 .. 13.4 44.1 32.2 50.9 37.4 119.3 .. .. .. .. 58.1 .. .. 28.1 .. .. .. .. .. 72.5 .. .. ..

43.5 37.2 .. .. 23.4 28.9 46.0 79.7 16.0 34.6 .. 47.8 .. .. .. 36.3 39.3 .. 55.6 .. .. .. .. 39.0 .. .. 33.6 44.3 26.4 89.5 28.0 .. 16.1 46.8 31.9 50.2 39.9 114.4 .. .. .. .. 58.1 .. .. 30.4 .. .. .. .. .. 73.9 .. .. ..

HUMAN DEVELOPMENT

35.6 25.5 .. .. 17.9 20.7 38.4 95.4 9.3 14.6 .. 27.6 .. .. .. 27.6 32.1 .. 52.6 .. .. .. .. 53.9 .. .. 30.6 30.9 22.4 89.3 22.9 .. 10.7 41.2 32.4 51.7 34.9 124.7 .. .. .. .. 58.1 .. .. 25.8 .. .. .. .. .. 71.1 .. .. ..

.. .. .. .. 15.6 16.2 .. 65.9 .. .. .. .. .. .. .. 28.6 .. .. .. .. .. .. .. 29.9 .. .. 27.5 29.5 .. .. 16.1 .. .. .. .. .. .. .. .. .. .. .. 32.8 .. .. .. .. .. .. .. .. 70.1 .. .. ..

.. .. .. .. 17.5 17.7 .. 61.1 .. .. .. .. .. .. .. 32.4 .. .. .. .. .. .. .. 22.8 .. .. 27.9 34.8 .. .. 17.0 .. .. .. .. .. .. .. .. .. .. .. 28.7 .. .. .. .. .. .. .. .. 71.4 .. .. ..

.. .. .. .. 13.6 14.6 .. 70.8 .. .. .. .. .. .. .. 24.9 .. .. .. .. .. .. .. 37.0 .. .. 27.2 23.9 .. .. 15.2 .. .. .. .. .. .. .. .. .. .. .. 37.0 .. .. .. .. .. .. .. .. 68.6 .. .. ..

Studentteacher ratio 2010

.. 38.7 .. .. 30.3 29.9 .. 17.5 52.3 32.5 .. 16.0 .. .. .. 38.7 43.1 .. .. .. .. .. .. .. .. .. .. .. .. 15.9 35.0 .. 29.6 33.1 .. .. 32.3 12.2 .. .. .. .. 18.2 .. .. .. .. .. .. .. .. 13.5 .. .. ..

Tertiary education Gross enrollment ratio (% of relevant age group) Total Male Female 2010 2010 2010

.. 3.7 .. .. 3.3 3.3 11.5 17.8 2.6 2.2 7.9 .. 5.5 .. .. 2.0 5.5 .. .. .. .. .. .. .. .. 3.7 0.7 5.8 4.4 .. .. .. 1.5 .. 5.5 4.5 7.9 .. .. .. .. .. .. 2.1 .. .. .. 6.2 .. 30.8 .. 32.4 .. .. ..

8.3 4.1 .. .. 4.5 4.2 12.6 15.6 3.9 3.7 9.1 .. .. .. .. 3.0 8.0 .. .. .. .. .. .. .. .. 3.9 0.9 8.1 6.2 .. .. .. 2.2 .. 6.2 4.5 9.9 .. .. .. .. .. .. 2.3 .. .. .. 6.9 .. 25.2 .. 34.0 .. .. ..

5.2 3.3 .. .. 2.2 2.3 10.3 20.2 1.3 0.6 6.7 .. .. .. .. 1.0 2.9 .. .. .. .. .. .. .. .. 3.5 0.6 3.4 2.5 .. .. .. 0.8 .. 4.8 4.4 5.9 .. .. .. .. .. .. 1.9 .. .. .. 5.5 .. 36.6 .. 30.7 .. .. ..

Public spending on education (%) Share of government expenditure Share of GDP 2010 2010

.. 8.5 .. .. 20.8 25.1 17.9 14.4 12.0 10.1 .. 8.9 .. .. .. .. 25.4 .. 22.8 24.4 .. .. 17.2 .. .. .. 12.1 22.0 15.3 .. .. .. 16.9 .. 18.2 .. .. .. .. .. 19.2 .. 16.0 18.3 .. .. .. 8.3 .. .. .. .. .. .. ..

4.7 3.4 .. .. 4.0 9.2 3.5 5.6 1.2 2.8 .. 2.5 6.2 .. .. .. 4.7 .. 5.0 5.5 .. .. 6.7 .. .. .. 4.6 4.5 4.3 .. .. 8.1 3.9 .. 5.0 .. 5.6 .. .. .. 6.0 .. 7.4 6.2 4.5 .. .. 2.5 .. .. .. .. .. .. ..

Part III. Development outcomes

Participating in growth

Table

7.2

Health Mortality Life expectancy at birth (years)

Total 2010

Male 2010

Female 2010

Under-five mortality rate (per 1,000) 2010

54.2 50.7 55.6 53.1 54.9 49.9 51.1 73.8 47.6 49.2 60.6 48.1 57.0 54.7 50.8 61.0 58.7 62.3 58.2 63.8 53.6 47.7 56.5 47.4 56.2 66.5 53.5 51.0 58.2 73.0 49.7 62.1 54.3 51.4 55.1 64.4 59.0 73.0 47.4 50.9 52.1 61.1 48.3 57.4 56.6 53.6 48.5 49.9 72.8 72.9 57.5 73.0 74.8 71.9 74.6

53.1 49.2 53.8 54.0 54.0 48.5 50.1 70.1 46.1 47.8 59.3 46.5 55.8 53.7 49.6 58.7 57.2 61.3 57.0 62.9 52.1 46.2 55.4 48.1 55.2 64.9 53.4 49.9 56.6 69.5 48.7 61.5 53.8 50.6 53.8 63.0 57.9 68.4 46.8 49.4 51.4 59.4 48.8 56.5 55.1 53.0 48.0 50.7 70.9 71.4 56.1 71.1 72.2 69.7 72.6

55.3 52.1 57.5 52.2 56.0 51.3 52.1 77.7 49.2 50.7 62.0 49.7 58.2 55.9 52.2 63.4 60.3 63.4 59.4 64.8 55.3 49.3 57.6 46.6 57.2 68.1 53.5 52.1 60.0 76.7 50.7 62.7 54.7 52.2 56.4 65.8 60.0 77.9 48.0 52.5 52.8 62.9 47.9 58.3 58.1 54.3 48.9 49.0 74.8 74.4 59.0 75.0 77.4 74.2 76.7

122 161 115 48 176 142 136 36 159 173 86 170 93 123 121 61 106 74 98 74 130 150 85 85 103 62 92 178 111 15 135 40 143 143 91 80 75 14 174 180 57 103 78 92 103 99 111 80 27 36 91 22 17 36 16

Part III. Development outcomes

Diseases Infant Maternal mortality mortality rate ratio, modeled (per 1,000 estimate (per live births) 100,000 live births) 2010 2008

77 98 73 36 93 88 84 29 106 99 63 112 61 86 81 42 68 54 57 50 81 92 55 65 74 43 58 99 75 13 92 29 73 88 59 53 50 12 114 108 41 66 55 60 66 63 69 51 23 31 73 19 13 30 14

505 450 350 160 300 800 690 79 890 1,100 280 540 560 400 240 240 350 230 360 350 610 790 360 620 770 240 460 540 510 60 490 200 590 630 340 70 370 .. 890 1,000 300 730 320 460 300 310 440 570 78 97 200 66 58 100 56

Prevalence of HIV (% ages 15–49) 2010

Incidence of tuberculosis (per 100,000 people) 2010

5.5 2.0 1.2 24.8 1.2 3.3 5.3 .. 4.7 3.4 0.1 .. 3.4 3.4 5.0 0.8 .. 5.2 2.0 1.8 1.3 2.5 6.3 23.6 1.5 0.2 11.0 1.0 0.7 1.0 11.5 13.1 0.8 3.6 2.9 .. 0.9 .. 1.6 0.7 17.8 1.1 25.9 5.6 3.2 6.5 13.5 14.3 0.1 0.1 2.5 <0.1 .. 0.1 <0.1

277 304 94 503 55 129 177 147 319 276 37 327 372 139 135 100 261 553 273 86 334 233 298 633 293 266 219 68 337 22 544 603 185 133 106 96 288 31 682 286 981 119 1,287 177 455 209 462 633 52 90 620 18 40 91 25

Malaria Clinical cases Reported reportedb deathsb 2010 2010

71,412,328 132,524 2,783,619 8,114 1,432,095 964 12,196 8 5,409,156 9,024 2,919,866 2,677 1,845,691 4,536 47 1 66,484 526 466,034 .. 47,364 53 7,439,440 23,476 0 .. .. 1,023 0 .. 53,750 27 4,068,764 1,581 159,313 182 116,353 151 2,642,221 3,859 1,092,554 735 0 .. 4,585,712 26,017 .. .. 2,263,973 1,422 202,450 122 6,851,108 8,206 1,018,846 3,006 238,565 211 .. .. 1,522,577 3,354 25,889 63 620,058 3,929 3,873,463 4,238 638,669 670 2,262 14 0 .. .. .. 934,028 8,188 24,553 6 8,060 83 1,465,496 1,023 1,722 8 0 .. 617,101 1,507 11,084,045 8,431 4,229,839 4,834 648,965 255 4,673 4 408 .. 3,962 0 85 2 .. .. 218 2 .. ..

HUMAN DEVELOPMENT

Prevention and treatment Child immunization rate (% of children ages 12–23 months) Measles DPT c 2010 2010

75 93 69 94 94 92 79 96 62 46 72 68 76 70 51 99 81 55 97 93 51 61 86 85 64 67 93 63 67 99 70 75 71 71 82 92 60 99 82 46 65 90 94 92 84 55 91 84 96 95 85 96 98 98 97

77 91 83 96 95 96 84 99 54 59 74 63 90 85 33 99 86 45 98 94 57 76 83 83 64 74 93 76 64 99 74 83 70 69 80 98 70 99 90 45 63 90 89 91 92 60 82 83 97 95 88 97 98 99 98

Malnutrition (% of children under age 5) Stunting Underweight 2007–10a 2007–10a

Contraceptive use (% of married women ages 15–49)

Births attended by skilled health staff (% of total) 2007–10a

Any method 2007–10a

29.2 .. 31.4 35.1 .. .. .. .. .. .. 45.8 .. 39.0 .. .. .. .. .. 28.6 40.0 28.1 35.2 39.0 39.4 49.2 47.8 .. 23.0 .. 43.7 29.6 .. 41.0 .. 31.6 .. .. 37.4 .. 23.9 .. 40.4 42.5 26.9 .. 45.8 ..

15.6 .. 11.2 26.0 .. .. .. .. .. .. 28.2 .. 29.4 .. .. .. .. .. 14.3 20.8 17.2 16.4 13.5 20.4 .. 13.8 .. 15.9 .. 18.3 17.5 .. 26.7 .. 14.4 .. .. 21.3 .. 8.7 .. 7.3 16.2 20.5 .. 14.9 ..

47.3 .. 94.6 .. 60.3 .. .. 43.7 22.7 .. 79.3 .. .. .. .. .. .. 56.7 57.1 46.1 44.0 43.8 61.5 46.3 43.9 .. .. 60.9 .. 55.3 81.4 .. 38.9 69.0 81.7 .. .. 42.4 .. .. .. 82.0 48.9 60.1 .. 46.5 60.2

.. .. 52.8 .. 21.9 .. .. .. 4.8 .. 17.3 .. .. .. .. .. .. .. 23.5 .. 14.2 45.5 47.0 11.4 39.9 .. .. 9.3 .. 16.2 55.1 18.0 14.6 51.6 38.4 .. .. 8.2 .. .. .. 49.3 34.4 15.2 .. 40.8 64.9

.. .. 30.7 21.0 .. ..

.. .. 6.8 5.6 .. ..

.. .. 78.9 99.8 .. ..

.. 22.5 60.3 .. .. ..

Modern method 2007–10a

Children under age 5 sleeping under insecticidetreated nets (% ) 2007–10a

Tuberculosis case detection rate (%, all forms) 2009

Tuberculosis treatment success rate (% of registered cases) 2009

.. .. .. 51.2 .. .. .. .. .. .. .. 5.5 .. .. .. .. .. .. .. 16.6 .. .. 38.9 45.6 10.3 28.2 42.2 .. 8.0 .. 12.2 53.5 .. 8.1 26.1 33.1 .. .. 6.0 .. .. .. 63.0 26.1 13.2 .. 26.5 .. .. .. .. 57.6 .. .. ..

.. 17.7 .. .. .. 45.2 .. .. .. 9.8 .. 35.7 .. .. .. 48.9 33.1 55.1 .. 28.2 4.5 35.5 46.7 .. 26.4 45.8 56.5 70.2 .. .. 22.8 34.0 63.7 29.1 69.8 56.2 29.2 .. 25.8 .. .. 25.3 0.6 63.6 56.9 32.8 49.9 17.3 .. .. 19.9 .. .. .. ..

48.0 75.0 47.0 62.0 14.0 25.0 70.0 44.0 60.0 26.0 46.0 46.0 69.0 27.0 89.0 58.0 50.0 42.0 47.0 31.0 26.0 59.0 85.0 93.0 52.0 44.0 49.0 16.0 24.0 41.0 46.0 76.0 36.0 19.0 19.0 49.0 31.0 57.0 31.0 42.0 74.0 52.0 67.0 77.0 10.0 44.0 80.0 46.0 .. 100.0 71.0 63.0 82.0 93.0 86.0

79.0 72.0 90.0 79.0 76.0 90.0 78.0 .. 53.0 76.0 .. 88.0 78.0 79.0 66.0 85.0 84.0 55.0 89.0 87.0 79.0 67.0 86.0 70.0 83.0 82.0 88.0 78.0 63.0 88.0 85.0 85.0 79.0 83.0 85.0 98.0 85.0 64.0 79.0 85.0 73.0 80.0 69.0 88.0 81.0 67.0 90.0 78.0 .. 91.0 79.0 88.0 .. 84.0 83.0

Children under age 5 with fever receiving any antimalarial treatment same or next day (%) 2007–10a

29.3 .. .. .. 17.2 .. .. .. 35.7 .. 39.1 .. .. .. 13.1 9.5 .. .. 43.0 73.9 51.2 23.2 .. 67.2 19.7 30.9 .. 20.7 .. 36.7 20.3 .. 49.1 10.8 8.4 9.1 .. 30.1 .. .. 35.8 0.6 59.1 33.8 59.6 34.0 23.6 .. 0.9 .. .. .. .. (continued)

HUMAN DEVELOPMENT

Part III. Development outcomes

Participating in growth

Table

7.2

Health (continued) Water and sanitation Population with sustainable access Population with sustainable access to an improved water source to improved sanitation (% of total (% of urban (% of rural (% of total (% of urban (% of rural population) population) population) population) population) population) 2010 2010 2010 2010 2010 2010

61 51 75 96 79 72 77 88 67 51 95 45 71 80 .. .. 44 87 89 86 74 64 59 78 73 46 83 64 50 99 47 93 49 58 65 89 72 .. 55 29 91 58 71 53 61 72 61 80 92 83 88 99 .. 83 ..

83 60 84 99 95 83 95 90 92 70 91 79 95 91 .. .. 97 95 92 91 90 91 82 91 88 74 95 87 52 100 77 99 100 74 76 89 93 100 87 66 99 67 91 79 89 95 87 98 95 85 99 100 .. 98 99

49 38 68 92 73 71 52 85 51 44 97 27 32 68 .. .. 34 41 85 80 65 53 52 73 60 34 80 51 48 99 29 90 39 43 63 88 56 .. 35 7 79 52 65 44 40 68 46 69 88 79 54 99 .. 61 ..

31 58 13 62 17 46 49 61 34 13 36 24 18 24 .. .. 21 33 68 14 18 20 32 26 18 15 51 22 26 89 18 32 9 31 55 26 52 .. 13 23 79 26 57 10 13 34 48 40 90 95 50 95 97 70 ..

42 85 25 75 50 49 58 73 43 30 50 24 20 36 .. .. 29 33 70 19 32 44 32 32 29 21 49 35 51 91 38 57 34 35 52 30 70 98 23 52 86 44 64 20 26 34 57 52 94 98 63 97 97 83 96

23 19 5 41 6 46 36 43 28 6 30 24 15 11 .. 4 19 30 65 8 11 9 32 24 7 12 51 14 9 88 5 17 4 27 56 19 39 .. 6 6 67 14 55 7 3 34 43 32 84 88 10 93 96 52 ..

Human resources Health workers (per 1,000 people) Nurses and Community Physicians midwives workers a a 2008–09 2008–09 2008–09a

.. .. 0.1 .. 0.1 .. .. 0.6 .. .. .. .. .. 0.1 .. .. .. .. 0.0 0.1 .. 0.1 .. .. 0.0 .. 0.0 0.1 0.1 .. 0.0 .. 0.0 0.4 .. .. 0.1 .. 0.0 .. .. 0.3 .. .. 0.1 .. .. .. 2.1 .. .. 2.8 1.9 0.6 1.2

.. .. 0.8 .. 0.7 .. .. 1.3 .. .. .. .. .. 0.5 .. .. .. .. 0.6 1.1 .. 0.6 .. .. 0.3 .. 0.3 0.3 0.7 .. 0.3 .. 0.1 1.6 .. .. 0.4 .. 0.2 .. .. 0.8 .. .. 0.3 .. .. .. 3.0 .. 0.8 3.5 6.8 0.9 3.3

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.1 0.2 .. .. .. .. .. .. 0.7 .. .. .. .. .. .. 0.1 .. .. .. .. 0.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

a. Data are for the most recent year available during the period speciﬁed. b. Data for Sudan, after 1999, only represents 15 northern states. c. Diphtheria, pertussis, and tetanus toxoid.

Part III. Development outcomes

HUMAN DEVELOPMENT

Expenditure on health Share of GDP (%)

Share of total expenditure on health (%)

Total 2010

Public 2009

Private 2009

Public 2010

Private 2010

External resources for health 2010

Out-of-pocket (% of private expenditure on health) 2010

6.5 2.9 4.1 8.3 6.7 11.6 5.1 4.1 4.0 4.5 4.5 7.9 2.5 5.3 4.5 2.7 4.9 3.5 5.7 5.2 4.9 8.5 4.8 11.1 11.9 3.8 6.6 5.0 4.4 6.0 5.2 6.8 5.2 5.1 10.5 7.2 5.7 3.4 13.1 .. 8.9 6.3 6.6 6.0 7.7 9.0 5.9 .. 4.7 4.2 7.2 4.7 3.9 5.2 6.2

2.9 4.1 2.3 8.2 3.9 6.0 1.6 2.9 1.7 3.9 2.1 4.9 1.6 1.0 3.4 1.0 2.0 1.7 3.0 3.1 0.9 1.6 1.5 5.6 5.3 2.8 3.6 2.7 1.6 2.1 4.1 4.0 3.5 2.1 3.9 2.9 3.1 3.1 0.9 .. 3.4 2.0 4.0 3.8 1.7 1.6 2.5 .. 3.0 5.0 5.4 2.1 2.6 1.9 3.4

3.7 0.5 1.9 2.1 2.4 7.1 4.0 1.0 2.6 3.1 1.3 4.7 1.4 4.1 0.5 1.2 2.2 1.9 3.0 3.8 4.9 4.5 2.9 2.6 8.0 1.4 2.6 2.9 1.0 3.6 1.5 2.0 2.6 3.7 5.1 4.2 2.5 0.9 12.2 .. 5.1 5.3 2.3 1.4 4.2 6.7 2.3 .. 2.3 0.8 1.6 2.9 1.3 3.6 2.9

45.2 82.5 49.5 72.5 51.0 38.2 29.6 75.0 35.4 25.0 67.2 42.5 46.7 21.6 75.9 48.2 53.5 52.9 50.9 59.5 11.3 10.0 44.3 76.2 32.5 60.3 60.2 46.6 53.1 41.7 71.7 58.4 50.9 37.9 50.1 38.3 55.5 91.9 11.3 .. 44.1 29.8 63.7 67.3 44.2 21.7 60.3 .. 50.6 77.9 65.3 37.4 68.8 38.0 54.3

54.8 17.5 50.5 27.5 49.0 61.8 70.4 25.0 64.6 75.0 32.8 57.5 53.3 78.4 24.1 51.8 46.5 47.1 49.2 40.5 88.7 90.0 55.7 23.8 67.5 39.7 39.8 53.4 46.9 58.3 28.3 41.6 49.1 62.1 49.9 61.7 44.5 8.1 88.7 .. 55.9 70.2 36.3 32.7 55.8 78.3 39.7 .. 49.4 22.1 34.7 62.6 31.2 62.0 45.7

10.4 2.9 35.9 18.3 22.9 45.8 13.2 11.9 13.4 7.9 19.2 32.7 4.1 9.8 2.0 38.0 39.4 2.4 41.2 16.9 10.8 23.3 36.1 19.5 55.1 9.0 63.8 27.4 10.1 2.0 24.2 19.0 29.4 9.2 47.0 21.0 18.5 4.2 20.6 .. 2.2 3.3 17.2 48.8 15.2 25.9 39.3 .. 0.4 0.0 23.9 0.6 0.6 0.4 0.3

58.6 100.0 92.7 29.5 73.8 61.4 94.5 99.7 95.0 96.7 100.0 62.5 100.0 98.8 92.1 100.0 80.1 100.0 48.4 66.4 99.4 73.8 76.7 69.0 52.2 68.3 27.9 99.5 94.5 88.8 48.3 17.9 84.1 95.3 44.4 86.7 78.5 67.7 89.5 .. 29.6 95.7 42.5 41.7 84.2 63.6 66.7 .. 93.5 94.7 99.1 97.7 100.0 86.3 87.0

HUMAN DEVELOPMENT

Private prepaid plans (% of private expenditure Health expenditure on health) per capita ($) 2010 2010

32.8 0.0 7.3 5.6 3.7 0.2 0.0 0.3 0.0 0.2 0.0 0.2 0.0 1.2 0.0 0.0 1.5 0.0 3.1 6.2 0.0 0.0 9.3 0.0 0.0 15.2 15.8 0.5 0.6 6.3 0.0 61.2 4.4 3.1 10.2 0.0 17.9 23.0 1.0 .. 66.1 1.0 19.0 10.1 4.3 0.2 3.6 .. 6.0 5.1 0.9 1.7 0.0 13.7 11.2

85.0 123.2 31.1 614.6 39.8 20.7 61.3 154.6 18.2 30.6 33.2 15.8 72.3 59.8 896.2 11.9 15.7 302.1 26.1 67.0 23.0 46.9 36.9 108.9 29.2 15.9 25.6 31.7 42.7 448.9 21.3 361.3 18.3 62.8 55.5 90.0 58.5 368.5 42.5 .. 648.7 83.9 203.1 30.9 40.6 46.7 72.9 .. 160.6 178.3 91.7 123.2 483.7 148.0 237.8

Part III. Development outcomes

Participating in growth

Table

8.1

Rural development

Rural population (%)

SUB-SAHARAN AFRICA Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somalia South Africa Sudan South Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Djibouti Egypt, Arab Rep. Libya Morocco Tunisia

Share of total population 1990 2000 2010

71.9 62.9 65.5 58.1 86.2 93.7 59.3 55.9 63.2 79.2 72.1 72.2 45.7 60.3 65.3 84.2 87.4 30.9 61.7 63.6 72.0 71.9 81.8 86.0 54.7 76.4 88.4 76.7 60.3 56.1 78.9 72.3 84.6 64.7 94.6 56.4 61.0 50.7 67.1 70.3 48.0 73.4 .. 77.1 81.1 69.9 88.9 60.6 71.0 51.4 47.9 24.3 56.5 24.3 51.6 42.1

67.4 51.0 61.7 46.8 83.4 91.7 50.1 46.6 62.4 76.6 71.9 70.2 41.7 56.5 61.2 82.2 85.1 19.9 50.9 56.0 69.0 70.3 80.3 80.0 45.7 72.9 84.8 72.1 60.0 57.3 69.3 67.6 83.8 57.5 86.2 46.6 59.4 49.0 64.5 66.8 43.1 63.9 .. 76.7 77.7 63.5 87.9 65.2 66.2 48.7 40.2 16.7 57.4 23.6 46.7 36.6

62.7 41.5 58.0 38.9 79.6 89.0 41.6 38.9 61.1 72.4 71.8 64.8 37.9 49.9 60.3 78.4 82.4 14.0 41.9 48.5 64.6 70.0 77.8 73.1 38.5 69.8 80.2 66.7 58.6 57.4 61.6 62.0 83.3 50.2 81.1 37.8 57.1 44.7 61.6 62.6 38.3 54.8 .. 74.5 73.6 56.6 86.7 64.3 61.7 46.3 33.5 11.9 57.2 22.1 43.3 32.7

1990

Annual growth 2000

2010

2.2 0.6 2.0 -2.1 2.3 2.2 1.4 -2.8 1.9 2.9 1.8 3.7 1.8 2.9 1.7 1.3 3.1 -1.0 2.3 1.7 4.1 0.4 3.1 1.3 -3.3 2.2 3.3 1.3 1.1 0.4 0.2 3.5 2.8 1.4 -0.3 0.2 2.5 0.9 0.9 0.0 1.0 1.9 .. 3.1 2.7 1.7 3.1 2.8 1.9 1.5 0.8 4.1 2.2 1.8 0.5 0.5

1.9 1.1 2.5 -0.1 2.5 1.2 0.5 -0.1 1.8 3.0 2.7 2.0 1.7 1.3 3.2 3.3 2.4 -2.3 0.8 1.0 1.0 2.0 2.4 0.8 3.0 2.8 2.3 2.3 2.8 1.2 1.3 1.6 3.4 1.1 5.3 -0.2 2.3 0.4 2.4 2.3 1.4 0.7 .. 0.1 2.0 2.0 3.0 3.3 0.2 1.1 -0.4 -1.4 1.9 1.5 0.5 0.1

1.7 0.7 2.2 -0.7 2.5 2.2 0.2 -1.0 1.6 2.0 2.5 1.8 1.5 0.7 2.5 2.5 1.8 -1.5 0.8 0.8 1.5 2.0 2.2 0.0 2.3 2.4 2.5 2.2 2.1 0.4 1.0 0.9 3.5 1.1 2.6 -0.4 2.2 -2.0 1.7 1.6 0.1 0.3 .. 0.8 2.4 0.9 3.0 1.4 0.0 1.0 -0.4 -1.4 1.7 0.7 0.2 -0.2

Rural population density (rural population per sq km of arable land) 1990 2000 2009

273.2 224.2 193.6 191.2 228.3 564.4 121.6 474.7 96.6 145.5 404.8 394.1 227.9 310.6 187.8 .. .. 97.3 327.5 348.5 145.4 292.4 384.4 444.7 332.4 316.9 368.6 324.0 300.8 594.0 309.8 155.0 59.7 213.7 764.3 3,274.5 142.9 3,549.0 549.7 453.9 125.7 117.3 .. 369.6 229.6 122.0 314.7 164.8 257.2 834.6 171.1 13,663.7 1,406.2 58.4 146.9 118.0

342.2 236.8 169.0 235.1 253.8 608.9 131.8 463.1 119.7 178.9 505.5 520.0 266.9 334.6 245.0 538.4 558.1 75.6 235.8 271.7 267.9 290.7 513.1 476.1 342.4 386.2 346.3 177.5 324.9 680.1 323.4 157.1 65.5 237.1 775.6 1,095.2 185.1 3,975.4 545.4 473.9 128.5 108.5 .. 435.6 300.5 121.3 401.6 236.2 231.3 862.5 160.2 12,223.2 1,386.3 68.0 153.4 122.2

352.4 196.7 205.0 314.4 216.8 810.7 136.4 324.8 135.7 185.3 642.9 626.9 301.8 349.4 312.0 582.5 481.4 65.8 179.7 266.6 222.9 346.7 570.7 473.6 375.7 478.5 323.8 157.7 509.2 842.1 282.4 175.4 83.6 231.4 645.5 627.6 180.4 3,944.1 327.5 574.9 133.3 91.1 .. 445.9 322.3 153.7 426.0 244.8 185.6 1,016.5 159.1 5,363.4 1,582.2 79.7 171.4 127.7

a. Data are for the most recent year available during the period speciﬁed. b. Poverty estimates based on survey data from earlier year(s) are available, but are not comparable with the most recent year reported here. c. World Bank estimates.

Part III. Development outcomes

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

Share of rural population below the national poverty line Surveys Surveys 1990–99a 2000–11a Year Percent Year Percent

1993

1998

1995

1998

1994 1999 1998

1996

1999 1998

1995

.. .. 40.4 .. .. .. .. .. .. .. .. .. 41.5c .. .. 47.5 .. .. 49.6 .. .. .. 68.9c .. 76.7 66.5 .. .. .. 71.3 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 37.4 83.0 .. 30.3 .. .. .. .. ..

2007 2003 2009b 2006b 2007b 2007b 2008b 2003b 2004 2006 2008 2006 2011 2005 2010 2006 2007b 2002b 2005b 2003 2007 2005 2010 2010b 2008b 2008 2004b 2007b 2004b 2011b 2001b 2011b 2003

2009b 2009b 2001b 2007b 2011b 2009 2010

2008 2007

.. 36.1 44.8 52.6 68.9 55.0 44.3 69.4 58.6 48.7 75.7 .. 54.2c 79.9 .. 30.4 44.6 73.9 39.2 63.0 69.1 49.1 60.5c 67.7c 73.5 56.6 50.6 59.4 .. 56.9 49.0 63.9 63.8 48.7 64.9 57.1 .. 78.5 .. .. 57.6 55.4 75.0 37.4 73.4 27.2 77.9 .. .. .. 30.0 .. 14.5 ..

Rural population poverty gap (%) Surveys Surveys 1990–99a 2000–11a Year Percent Year Percent

1998

1995

1998

1993 1999 1998

1996

1999 1998

1995

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

.. .. .. .. .. .. .. .. .. .. .. .. 14.3c .. .. 13.4 .. .. 18.2 .. .. .. 26.5c .. 21.4 23.9 .. .. .. 29.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 11.2 44.5 .. 4.5 .. .. .. .. ..

2003 2003 2009b 2006b 2007b 2007b 2008b 2003b 2004 2006 2005 2008 2006 2005 2005 2003 2006 2007b 2002b 2005b 2007 2005 2004 ..b 2008b 2008 2004b 2007b 2004b 2005b 2001b 2011b 2003

2009b ..b 2001b 2007b 2006b 2009 2006

.. 14.0 18.4 17.4 24.2 17.5 14.3 35.0 23.3 17.8 34.9 20.6 20.3c 49.8 .. 8.5 16.0 30.5 13.5 22.0 27.8 17.5 ..c 26.3c 28.9 8.6 .. 22.3 .. 22.2 16.0 21.2 26.6 26.0 24.7 18.6 .. 34.6 .. .. 21.3 37.0 11.0 29.3 7.6 38.8 .. .. .. .. .. .. ..

Share of rural population with sustainable access (%) To an improved To an improved water source sanitation facilities 1990 2000 2010 1990 2000 2010

35.2 40.0 49.0 88.0 38.0 68.0 31.0 .. 47.0 37.0 83.0 27.0 .. 67.0 .. 39.0 5.0 .. 67.0 36.0 37.0 32.0 33.0 78.0 .. 15.0 35.0 20.0 26.0 99.0 26.0 51.0 31.0 30.0 64.0 .. 43.0 .. 26.0 .. 66.0 58.0

41.6 40.0 59.0 90.0 55.0 70.0 42.0 81.0 49.0 41.0 92.0 27.0 36.0 67.0 42.0 50.0 19.0 47.0 77.0 58.0 52.0 43.0 43.0 76.0 50.0 24.0 57.0 36.0 37.0 99.0 27.0 72.0 35.0 36.0 63.0 70.0 49.0 .. 30.0 15.0 71.0 55.0

48.6 38.0 68.0 92.0 73.0 71.0 52.0 85.0 51.0 44.0 97.0 27.0 32.0 68.0 .. .. 34.0 41.0 85.0 80.0 65.0 53.0 52.0 73.0 60.0 34.0 80.0 51.0 48.0 99.0 29.0 90.0 39.0 43.0 63.0 88.0 56.0 .. 35.0 7.0 79.0 52.0

19.3 6.0 0.0 22.0 2.0 44.0 37.0 .. 5.0 4.0 11.0 4.0 .. 8.0 .. 0.0 1.0 .. .. 4.0 6.0 4.0 25.0 .. .. 7.0 38.0 10.0 8.0 88.0 4.0 9.0 2.0 36.0 34.0 .. 22.0 .. 5.0 .. 60.0 18.0

20.6 11.0 3.0 32.0 4.0 45.0 37.0 25.0 16.0 5.0 23.0 13.0 18.0 10.0 87.0 2.0 6.0 30.0 60.0 6.0 9.0 5.0 28.0 22.0 3.0 10.0 45.0 12.0 9.0 88.0 4.0 13.0 3.0 32.0 45.0 15.0 31.0 .. 5.0 10.0 63.0 16.0

23.4 19.0 5.0 41.0 6.0 46.0 36.0 43.0 28.0 6.0 30.0 24.0 15.0 11.0 .. 4.0 19.0 30.0 65.0 8.0 11.0 9.0 32.0 24.0 7.0 12.0 51.0 14.0 9.0 88.0 5.0 17.0 4.0 27.0 56.0 19.0 39.0 .. 6.0 6.0 67.0 14.0

25.0 46.0 36.0 39.0 23.0 71.0 79.9 88.0 70.0 90.0 55.0 54.0 62.0

41.0 45.0 38.0 54.0 36.0 70.0 84.2 84.0 63.0 95.0 55.0 58.0 77.0

65.0 44.0 40.0 68.0 46.0 69.0 88.4 79.0 54.0 99.0 .. 61.0 ..

44.0 6.0 8.0 26.0 37.0 35.0 54.6 77.0 45.0 57.0 96.0 27.0 44.0

49.0 7.0 5.0 30.0 40.0 34.0 71.7 82.0 30.0 79.0 96.0 43.0 57.0

55.0 7.0 3.0 34.0 43.0 32.0 84.4 88.0 10.0 93.0 96.0 52.0 ..

Part III. Development outcomes

Participating in growth

Table

8.2

Agriculture Agriculture Gross Production Index 2004-2006=100 value added Agriculture (% of GDP) total Crop Livestock Food Cereal 2010 2010 2010 2010 2010 2010a

SUB-SAHARAN AFRICA 11.2 Angola 9.8 151.2 163.2 114.3 Excluding South Africa Benin .. 116.2 117.0 106.5 Excl. S. Africa & Nigeria Botswana 2.5 113.3 89.8 118.5 Angola Burkina .. 111.9 111.4 113.1 Benin Faso Burundi 35.1 49.9 42.9 136.9 Botswana Cameroon .. 123.3 123.2 123.4 Burkina Faso Cape Verde 9.9 120.2 109.5 129.8 Burundi Central African Republic .. 114.4 112.9 116.0 Cameroon Chad .. 102.0 96.8 113.1 Cape Verde Comoros .. 93.4 91.5 112.1 Central African Republic Congo, .. 104.2 102.6 117.2 Chad Dem. Rep. Congo, Rep. 3.8 124.7 115.0 157.3 Comoros Côte d'Ivoire 22.8 105.8 104.6 120.1 Congo, Dem. Rep. Equatorial Guinea .. 108.2 108.3 107.6 Congo, Rep. Eritrea .. 101.3 81.4 117.7 Côte d’Ivoire Ethiopia 47.7 125.1 127.5 119.6 Equatorial Guinea Gabon 4.1 110.5 109.3 113.9 Eritrea Gambia, 28.5 133.3 138.7 107.9 Ethiopia The Ghana 29.9 125.2 124.9 128.8 Gabon Guinea 13.0 113.1 110.9 129.2 Gambia, The Guinea-Bissau .. 119.9 120.4 117.6 Ghana Kenya 25.2 123.5 112.9 136.0 Guinea Lesotho 8.6 112.2 116.7 109.3 Guinea-Bissau Liberia .. 101.6 97.6 134.1 Kenya Madagascar .. 121.6 121.7 121.4 Lesotho Malawi .. 165.9 166.2 162.4 Liberia Mali .. 147.9 152.0 140.6 Madagascar Mauritania 17.2 112.8 145.0 107.1 Malawi Mauritius 3.7 97.1 89.1 121.2 Mali Mozambique 31.9 114.9 117.8 100.7 Mauritania Namibia 7.5 93.1 111.1 87.4 Mauritius Niger .. 155.2 176.4 131.6 Mozambique Nigeria .. 89.4 86.9 115.2 Namibia Rwanda 32.2 137.1 137.3 135.5 Niger São Tomé and Príncipe .. 110.0 109.8 112.2 Nigeria Senegal 17.4 151.8 158.6 134.7 Rwanda Seychelles .. 76.9 70.4 81.2 São Tomé and Príncipe Sierra Leone 49.0 113.8 112.2 127.6 Senegal Somalia .. 114.5 100.0 116.7 Seychelles South Africa 2.5 120.4 107.0 136.2 Sierra Leone Sudan 23.6 118.6 97.5 129.5 Somalia Swaziland 8.0 103.9 101.8 111.8 South Africa Tanzania 28.1 110.0 109.7 111.1 Sudan Togo 42.8 119.9 119.0 126.0 Swaziland Uganda 24.3 108.1 107.1 112.6 Tanzania Zambia 9.2 142.9 161.2 108.7 Togo Zimbabwe 16.0 96.6 89.0 107.4 Uganda NORTH 11.9 Zambia AFRICA Algeria 6.9 123.6 131.5 110.2 Zimbabwe Djibouti .. 207.5 114.4 223.1 NORTH AFRICA Egypt, 14.0 110.0 105.5 123.9 AlgeriaArab Rep. Libya .. 111.6 108.7 116.5 Djibouti Morocco 15.4 125.7 123.0 131.9 Egypt, Arab Rep. Tunisia 8.0 103.1 100.8 110.0 Libya Morocco a. Provisional. b. Data are for the most recent year available during the period speciﬁed. Tunisia AFRICA

151.8 122.2 113.7 118.8 49.8 125.7 120.2 114.3 106.5 93.4 104.1 125.1 105.9 112.1 101.2 124.7 109.6 133.3 125.1 113.0 120.4 124.9 112.8 122.2 121.5 164.6 161.0 112.8 97.1 113.4 93.6 155.5 89.3 136.9 110.0 153.6 79.4 116.1 114.4 121.1 119.5 104.2 109.7 126.9 108.2 143.8 95.8

144.4 149.3 219.4 133.4 112.7 146.9 128.4 104.9 118.6 102.5 100.4 112.6 100.6 .. 95.6 126.5 120.2 181.3 156.2 129.8 132.8 115.3 153.3 207.2 141.4 209.3 201.0 180.3 254.6 181.2 95.6 148.0 73.8 189.4 130.0 170.7 .. 116.4 77.5 123.2 69.3 97.8 117.0 126.6 123.7 229.2 78.8

123.7 207.5 110.9 111.9 125.9 103.2

120.9 100.0 84.2 97.3 105.1 56.1

Cereal (thousands of metric tons) Production Exports Imports 2010 2009 2009

123,058 1,136 1,555 61 4,523 313 2,805 8 239 1,912 26 1,528 25 1,461 .. 247 15,638 41 364 2,907 2,859 237 4,100 173 296 5,164 4,039 6,418 276 1 2,506 116 5,204 19,512 746 4 1,768 .. 1,008 258 14,733 3,562 69 6,688 1,046 2,963 3,098 1,429 33,256 4,686 0 19,408 218 7,834 1,109

2,534 1 4 7 18 0 0 5 0 127 .. 1 0 1 0 15 19 0 0 1 15 4 .. 42 16 3 30 5 0 0 104 0 0 1,824 9 1 71 32 105 71 0 910 6 774 1 100 30

28,745 700 271 209 375 67 907 135 42 195 46 479 40 1,665 25 127 2,229 133 219 835 413 25 2,711 254 192 221 215 263 556 328 804 119 172 4,035 131 18 1,348 17 88 516 2,153 2,329 159 950 163 514 70 1,277 22,860 7,910 193 6,043 2,317 4,415 1,981

Trade Agricultural Food Exports Imports Exports Imports ($ millions) ($ millions) ($ millions) ($ millions) 2009 2009 2009 2009

26,440 9 432 177 364 60 970 1 19 76 10 55 29 5,101 2 15 1,318 27 49 1,655 55 102 2,479 1 83 187 1,038 203 24 307 308 228 90 985 82 6 303 5 26 88 5,458 563 222 827 372 774 390 860 7,747 124 63 4,522 9 1,811 1,218

31,202 2,061 734 616 312 81 799 202 67 148 52 859 92 1,342 84 77 1,184 412 134 1,281 306 65 1,618 144 167 333 281 413 504 669 663 349 273 4,244 164 35 1,190 78 143 418 4,362 1,503 219 604 208 542 248 926 22,012 6,459 440 7,605 2,079 3,785 1,644

16,849 8 321 150 104 6 749 0 17 54 10 13 11 4,272 2 15 774 2 44 1,607 25 101 589 1 11 166 160 127 18 261 155 182 80 819 7 6 192 1 23 87 3,852 451 208 316 325 208 205 115 6,631 98 62 3,806 1 1,585 1,079

25,748 1,555 683 473 244 76 722 169 59 120 49 756 78 1,157 51 76 1,109 332 105 1,167 261 48 1,473 116 145 278 209 341 438 517 582 209 203 3,789 146 28 1,074 67 123 355 2,742 1,259 178 530 187 463 182 825 18,236 5,470 397 6,329 1,895 2,904 1,241

Note:

Part III. Development outcomes

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

Share of land area (%) Permanent cropland 2008

Cereal cropland 2009

1.0 0.2 2.7 0.0 0.2 13.6 3.0 0.7 0.1 0.0 32.3 0.3 0.2 13.5 2.5 0.0 1.0 0.6 0.5 12.3 2.8 8.9 1.1 0.1 2.2 1.0 1.3 0.1 0.0 2.0 0.3 0.0 0.1 3.3 11.4 46.9 0.3 4.4 1.8 0.0 0.8 0.1 0.9 1.7 3.3 11.3 0.1 0.3 0.9 0.4 .. 0.8 0.2 2.2 14.4

4.0 1.4 10.0 0.2 15.7 9.1 3.5 8.5 0.3 2.0 12.0 0.9 0.1 2.7 .. 4.6 9.3 0.1 32.3 7.0 8.3 5.4 4.5 6.3 2.6 3.0 19.5 3.3 0.3 0.1 3.2 0.4 8.4 15.2 15.7 1.3 7.7 .. 9.1 1.0 2.9 3.3 3.3 5.7 16.2 9.4 1.6 4.9 2.1 1.3 0.0 3.0 0.2 11.3 4.2

Agricultural irrigated land (% of agricultural land) 2000–08b

.. .. 0.0 .. .. .. .. .. .. .. .. .. .. .. .. 0.5 .. .. .. .. .. 0.1 .. .. 2.2 .. .. .. 21.4 .. .. .. .. .. .. 0.7 .. .. .. .. 1.3 .. .. .. .. .. .. 2.1 .. .. .. 4.4 4.0

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

Fertilizer consumption (100 grams per hectare of arable land) 2009

10.5 1.1 .. .. 9.1 0.9 7.4 .. .. .. .. 0.5 1.1 15.9 .. .. 7.9 6.1 6.8 11.9 0.6 .. 32.5 .. .. 2.6 26.6 3.2 .. 209.5 .. 1.6 0.1 2.1 1.1 .. 5.0 36.0 .. .. 49.2 7.9 .. 8.7 3.3 2.1 27.3 28.0 .. 7.8 .. 502.8 40.3 20.8 42.3

Agricultural machinery (tractors per 100 sq km of arable land) 2000–08b

Agricultural employment (% of total employment) 2000–10 b

.. .. 134.8 .. .. .. 11.2 .. .. .. .. .. 32.1 .. 8.3 .. .. .. 4.5 25.1 .. 25.2 .. .. 1.9 .. 2.2 9.8 .. .. .. .. 6.6 0.5 .. 2.1 .. .. 12.0 43.0 13.8 87.1 23.3 0.6 .. .. ..

.. 42.7 29.9 84.8 .. 61.3 .. .. .. .. .. 35.4 .. .. .. 79.3 24.2 .. 57.2 .. .. 61.1 .. 48.9 80.4 .. 66.0 .. 8.7 80.5 16.3 56.9 44.6 78.8 27.9 33.7 .. 68.5 .. 5.1 .. .. 76.5 54.1 65.6 72.2 64.8

139.6 60.0 390.6 218.9 .. 142.6

20.7 .. 31.6 .. 40.9 ..

Agriculture value added per worker (2000 US$) 2010

.. 333 .. 534 .. 84 .. 3,335 .. .. .. .. .. 1,056 .. .. 226 1,825 440 .. 242 .. 351 215 672 .. 169 .. 813 5,692 234 881 .. .. .. .. 271 .. .. .. 3,951 929 1,213 289 531 200 214 161 3,028 2,254 .. 3,265 .. 3,315 3,050

Cereal yield (kilograms per hectare) 2010

1,336 644 1,402 544 1,054 1,346 1,711 222 1,466 775 1,157 772 785 1,717 .. 536 1,674 1,782 1,127 1,814 1,409 1,555 1,613 909 1,179 2,987 2,206 1,615 946 10,000 1,006 373 490 1,413 1,930 3,000 1,197 .. 1,554 432 4,162 452 1,226 1,333 1,187 1,608 2,547 752 2,772 1,568 1,111 6,541 662 1,548 1,702

Part III. Development outcomes

Participating in growth

Table

8.3

Producer food prices

1991

Rice, paddy (per tonne, current US$) 1995 2000 2005

2009

1991

Maize (per tonne, current US$) 1995 2000 2005

2009

.. .. .. 351.5 220.4 177.2 .. .. .. .. .. 265.9 212.7 .. .. .. .. 170.4 416.9 220.2 .. 72.7 .. .. 119.9 139.1 223.3 .. .. 181.1 .. 260.4 761.3 199.7 .. .. .. .. .. .. 962.2 .. .. 283.6 .. .. ..

.. .. .. 245.6 272.3 136.2 .. .. .. .. .. 150.3 220.4 .. .. 260.8 .. 206.2 393.3 245.1 .. 107.2 .. .. 170.0 117.8 236.4 .. .. 135.8 .. 214.4 652.2 873.4 .. .. .. .. .. .. 205.2 .. .. 232.4 .. .. ..

.. .. .. 119.4 277.5 144.6 .. .. .. .. .. 178.4 154.5 .. .. 201.6 .. 136.9 306.6 405.5 351.1 299.9 .. .. 190.6 594.4 154.5 .. .. 90.6 .. 154.5 279.4 582.1 .. .. .. .. .. .. 388.9 .. .. 165.7 .. .. ..

.. .. .. 392.2 609.2 269.1 .. .. .. .. .. 220.1 222.2 .. .. 127.7 .. 175.0 577.8 138.2 474.8 378.8 .. .. 203.4 718.5 269.7 .. .. 163.3 .. 201.0 545.1 480.2 .. .. .. .. .. .. 497.3 .. .. 258.3 .. .. ..

.. .. .. 643.6 841.0 309.7 .. .. .. .. .. 313.2 586.7 .. .. 1,028.1 .. 222.7 506.8 178.5 962.5 749.8 .. .. 314.5 1,293.9 316.4 .. .. 322.3 .. 259.8 426.9 1,094.9 .. .. .. .. .. .. 1,270.4 .. .. 341.9 .. .. ..

.. .. .. 212.7 270.0 283.6 313.9 .. .. .. .. 212.7 159.5 .. .. .. .. 211.3 188.9 191.0 .. 104.3 .. .. 337.8 96.3 134.7 .. 303.5 132.7 166.6 163.0 334.8 259.0 .. .. .. .. .. 129.3 1,538.6 .. .. 205.6 .. .. ..

.. .. .. 148.5 208.2 152.3 432.0 .. .. .. .. 200.3 162.9 .. 295.1 154.3 .. 419.0 215.1 245.1 76.2 155.6 .. .. 178.6 47.1 166.3 .. 287.6 92.4 193.3 138.2 661.3 194.5 .. .. .. .. .. 159.1 328.1 .. .. 190.3 .. .. ..

.. .. .. 91.3 253.0 163.7 247.9 .. .. .. .. 262.6 119.4 .. 354.3 119.3 .. 134.5 171.7 166.7 842.7 190.3 .. .. 143.8 111.9 107.7 .. 171.4 51.8 145.1 118.0 198.4 211.0 .. .. .. .. .. 78.5 621.9 .. .. 120.8 .. .. ..

.. .. .. 192.4 314.3 113.2 334.6 .. .. .. .. 359.6 233.0 .. 347.0 144.7 .. 311.2 366.5 152.0 1,168.0 201.7 .. .. 152.8 184.7 197.5 .. 185.9 154.5 276.6 173.0 477.5 104.2 .. .. .. .. .. 99.3 184.6 .. .. 294.4 .. .. ..

.. .. .. 259.9 336.9 129.1 449.5 .. .. .. .. 507.2 331.3 .. 573.6 388.5 .. 252.9 384.8 149.6 1,324.2 309.3 .. .. 220.4 365.1 176.2 .. 190.6 298.3 281.8 226.0 401.3 434.1 .. .. .. .. .. 156.3 427.6 .. .. 350.3 .. .. ..

270.7 .. 127.5 .. 436.5 ..

544.5 .. 193.4 .. 445.0 ..

344.8 .. 167.9 .. 276.4 ..

421.4 .. 185.0 .. 325.2 ..

516.7 .. 211.0 .. 294.7 ..

173.2 .. 140.5 .. 242.3 ..

335.7 .. 151.5 .. 292.7 ..

212.6 .. 174.8 .. 223.0 ..

259.8 .. 179.3 .. 225.8 ..

318.6 .. 208.0 .. 272.4 ..

Part III. Development outcomes

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

1991

1995

Sorghum (per tonne, current US$) 2000

.. .. .. 212.7 330.6 177.2 .. .. .. .. .. .. 342.4 .. .. .. .. 213.6 217.5 187.0 .. 207.7 .. .. .. 176.6 145.3 .. .. 63.9 147.8 140.2 368.1 234.0 .. .. .. .. .. 106.8 943.0 .. .. 237.5 .. .. ..

.. .. .. 134.4 328.3 160.3 .. .. .. .. .. .. 252.2 .. 212.4 193.2 .. 193.3 212.9 263.8 .. 194.1 .. .. .. 72.0 198.3 .. .. 47.9 182.0 96.2 847.7 450.1 .. .. .. .. .. 132.9 92.7 .. .. 246.4 .. .. ..

.. .. .. 84.3 374.7 313.8 .. .. .. .. .. .. 2,103.1 .. 284.7 142.1 .. 129.0 153.1 179.4 351.1 204.1 .. .. .. 500.6 87.4 .. .. 51.8 157.4 77.3 190.3 211.0 .. .. .. .. .. 74.9 165.6 .. .. 140.5 .. .. ..

.. .. .. 178.7 324.2 217.0 .. .. .. .. .. .. 336.6 .. 391.7 188.7 .. 334.3 424.4 120.7 854.6 331.8 .. .. .. 514.4 233.6 .. .. 141.3 263.2 117.4 509.0 138.8 .. .. .. .. .. 70.9 335.2 .. .. 364.6 .. .. ..

.. .. .. 217.8 439.5 247.5 .. .. .. .. .. .. 293.4 .. 657.5 487.9 .. 272.8 469.5 164.1 1,235.1 472.1 .. .. .. 753.2 235.7 .. .. 216.4 262.2 153.9 290.8 434.1 .. .. .. .. .. 179.0 312.7 .. .. 378.0 .. .. ..

.. .. .. 212.7 .. .. .. .. .. .. .. .. 460.8 .. .. .. .. 218.8 308.6 .. .. 256.6 .. .. .. 133.2 156.0 .. .. .. 147.8 150.1 339.6 .. .. .. .. .. .. .. 1,206.4 .. .. 265.9 .. .. ..

.. .. .. 152.9 .. .. .. .. .. .. .. .. 391.3 .. 337.2 216.0 .. 388.9 245.0 .. .. 361.3 .. .. .. 65.1 194.3 .. .. .. 209.5 96.2 413.3 .. .. .. .. .. .. .. 278.6 .. .. 238.4 .. .. ..

.. .. .. 84.3 .. .. .. .. .. .. .. .. 245.7 .. 434.3 144.8 .. 128.2 205.9 .. .. 311.1 .. .. .. 518.6 85.1 .. .. .. 157.4 108.2 184.5 .. .. .. .. .. .. .. 655.1 .. .. 122.2 .. .. ..

.. .. .. 178.7 .. .. .. .. .. .. .. .. 415.4 .. 645.3 170.0 .. 310.1 495.3 .. .. 485.5 .. .. .. 642.7 254.5 .. .. .. 263.2 135.1 493.7 .. .. .. .. .. .. .. 433.6 .. .. 305.8 .. .. ..

.. .. .. 210.9 .. .. .. .. .. .. .. .. 307.4 .. 1,070.2 507.9 .. 229.9 570.0 .. .. 672.6 .. .. .. 1,071.8 286.6 .. .. .. 262.2 175.5 323.1 .. .. .. .. .. .. .. 1,065.2 .. .. 361.0 .. .. ..

152.3 .. 141.2 .. 218.2 ..

207.7 .. 166.9 .. 402.8 ..

131.5 .. 184.0 .. 218.3 ..

160.8 .. 186.7 .. 292.5 ..

197.1 .. 251.4 .. 370.6 ..

.. .. .. .. .. ..

2005

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

2009

1991

1995

Millet (per tonne, current US$) 2000

2005

2009

Part III. Development outcomes

Participating in growth

Table

8.4

Environment Renewable internal fresh water resources Annual fresh water Total Forest area (billions Per capita withdrawals (cubic (billions of (% of land of cubic meters) cubic meters) meters) area) 1990 2010 2009 2009 2009

31.2 48.9 52.1 24.2 25.0 11.3 51.4 14.4 37.3 10.4 6.5 70.7 66.6 32.1 66.3 16.1 13.7 85.4 44.2 32.7 29.6 78.8 6.5 1.3 51.2 23.5 41.3 11.5 0.4 19.2 55.2 10.6 1.5 18.9 12.9 28.1 48.6 89.1 43.5 13.2 6.8 32.2 27.4 46.8 12.6 23.8 71.0 57.3 1.3 0.7 0.3 0.0 0.1 11.3 4.1

28.0 46.9 41.2 20.0 20.7 6.7 42.1 21.1 36.3 9.2 1.6 68.0 65.6 32.7 58.0 15.2 12.3 85.4 48.0 21.7 26.6 71.9 6.1 1.5 44.9 21.6 34.3 10.2 0.2 17.2 49.6 8.9 1.0 9.9 17.6 28.1 44.0 89.1 38.1 10.8 4.7 29.4 32.7 37.7 5.3 15.0 66.5 40.4 1.4 0.6 0.3 0.1 0.1 11.5 6.5

3,884 148 10 2 13 10 273 0 141 15 1 900 222 77 26 3 122 164 3 30 226 16 21 5 200 337 16 60 0 3 100 6 4 221 10 2 26 .. 160 6 45 30 3 84 12 39 80 12 47 11 0 2 1 29 4

124.6 0.6 0.1 0.2 1.0 0.3 1.0 0.0 0.1 0.4 0.0 0.6 0.1 1.4 0.0 0.6 5.6 0.1 0.1 1.0 1.6 0.2 2.7 0.1 0.2 14.7 1.0 6.6 1.6 0.7 0.7 0.3 2.4 10.3 0.2 0.0 2.2 0.0 0.5 3.3 12.5 37.1 1.0 5.2 0.2 0.3 1.7 4.2 94.3 6.2 0.0 68.3 4.3 12.6 2.9

Water productivity (2000 $ per cubic meter of fresh water withdrawal) 2009

4.3 39.5 24.9 40.5 4.4 3.9 14.1 42.0 15.3 8.1 24.2 10.4 101.3 8.0 346.3 1.3 3.0 45.8 16.1 8.3 3.3 1.4 6.6 20.4 5.3 0.3 2.7 0.6 1.3 8.8 11.3 19.3 1.1 7.7 22.3 .. 3.0 52.0 3.0 .. 14.6 0.6 1.8 3.6 9.1 36.4 3.0 0.9 3.9 12.4 41.1 2.2 11.4 4.6 11.3

Water pollution Emissions of organic water Energy production pollutants (kilotons of oil (kilograms equivalent) per day) a 1990 2009 2000–07

.. .. 3,246 .. .. .. .. .. .. .. .. .. .. .. 2,540 32,159 .. .. 16,048 .. .. .. 5,252 .. 92,770 32,672 .. .. 15,446 .. .. .. .. .. .. 6,621 .. .. .. 229,582 38,567 .. 30,322 .. 2,105 .. .. .. .. .. .. 73,989 ..

474,530 28,652 1,774 910 .. .. 10,976 .. .. .. .. 12,019 8,746 3,382 .. .. 14,052 14,630 .. 4,392 .. .. 9,013 .. .. .. .. .. .. .. 5,608 .. .. 150,452 .. .. 964 .. .. .. 114,535 8,775 .. 9,064 1,054 .. 4,918 8,550 235,228 100,114 .. 54,869 73,173 773 5,728

Energy Energy use (kilotons of oil equivalent) 1990 2009

808,735 313,233 511,206 100,958 5,883 11,896 1,996 1,661 3,475 938 1,261 2,048 .. .. .. .. .. .. 8,849 4,980 6,918 .. 29 .. .. .. .. .. .. .. .. 18 .. 23,346 11,798 22,921 15,276 797 1,402 11,891 4,323 10,353 .. .. .. 562 .. 726 30,373 14,866 32,678 13,587 1,181 1,794 .. 62 .. 7,047 5,291 9,240 .. .. .. .. 75 .. 15,573 10,940 18,723 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 480 .. 11,918 5,922 9,766 329 .. 1,713 .. .. .. 228,722 70,582 108,252 .. .. .. .. 23 .. 1,256 1,686 2,939 .. 38 .. .. .. .. .. .. .. 160,637 93,876 144,041 35,198 10,629 15,815 .. 309 .. 18,046 9,733 19,616 2,191 1,263 2,627 .. .. .. 7,241 5,399 7,856 8,530 9,297 9,514 337,026 77,423 156,831 152,292 22,192 39,758 .. 130 .. 88,186 31,825 72,015 87,136 11,330 20,405 782 6,941 15,083 7,811 4,946 9,200

Combustible renewables and waste (% of total energy use) 1990 2009

55.9 73.5 94.2 33.4 .. .. 76.7 .. .. .. .. 84.7 59.5 73.5 .. .. 93.9 62.9 .. 73.7 .. .. 77.9 .. .. .. .. .. .. .. 93.9 .. .. 80.2 .. .. 56.7 .. .. .. 11.1 81.8 .. 91.7 82.8 .. 74.3 50.9 2.8 0.1 .. 3.3 1.1 4.6 12.9

57.3 60.1 57.4 23.6 .. .. 64.1 .. .. .. .. 93.7 51.1 75.2 .. 77.4 92.0 61.8 .. 69.8 .. .. 76.0 .. .. .. .. .. .. .. 81.8 12.0 .. 84.9 .. .. 41.1 .. .. .. 9.8 68.0 .. 87.7 83.1 .. 80.9 65.6 2.3 0.1 .. 2.2 0.8 3.2 14.1

a. Data are for the most recent year available during the period specified. b. Hydrofluorocarbons, perfluorocarbons, and sulphur hexafluoride.

Part III. Development outcomes

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

Greenhouse gas emissions Nitrous oxide

Methane

Carbon dioxide (thousands of metric tons) 1990 2008

462,711 4,430 715 2,178 587 304 1,738 88 198 147 77 4,070 1,188 5,798 121 .. 3,018 4,844 191 3,931 1,056 253 5,823 .. 484 986 612 422 2,666 1,463 1,001 7 832 45,375 682 66 3,183 114 389 18 333,514 5,559 425 2,373 774 818 2,446 15,504 232,367 78,896 400 75,944 40,319 23,542 13,267

687,172 24,371 4,067 4,840 1,856 180 5,302 308 260 495 125 2,816 1,936 7,015 4,815 414 7,107 2,472 411 8,592 1,393 282 10,392 .. 609 1,911 1,228 594 1,999 3,953 2,314 3,968 851 95,756 704 128 4,976 682 1,335 649 435,878 14,052 1,093 6,465 1,419 3,748 1,889 9,076 453,399 111,304 524 210,321 58,331 47,906 25,013

Total (kilotons of carbon dioxide equivalent) 1990 2005

.. .. 49,530 45,409 4,847 4,080 5,812 4,501 .. .. .. .. 13,503 18,518 .. .. .. .. .. .. .. .. 96,593 56,445 6,231 5,584 11,243 10,997 .. .. 1,884 2,467 39,325 52,243 8,103 8,218 .. .. 7,238 8,990 .. .. .. .. 17,952 22,130 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 10,863 12,843 3,435 5,057 .. .. 117,467 130,317 .. .. .. .. 5,277 7,129 .. .. .. .. .. .. 51,179 63,785 43,370 67,441 .. .. 25,817 32,024 2,752 2,889 .. .. 26,944 19,294 10,112 9,539 104,128 134,629 40,726 54,219 .. .. 27,839 46,996 22,473 14,682 9,132 10,573 3,958 8,160

Agricultural (% of total) 1990 2005

Industrial (% of total) 1990 2005

44.0 26.4 36.7 90.5 .. .. 55.2 .. .. .. .. 25.6 37.3 18.3 .. 78.7 81.6 0.9 .. 49.0 .. .. 74.3 .. .. .. .. .. .. .. 66.3 95.8 .. 18.5 .. .. 68.8 .. .. .. 37.3 87.1 .. 73.9 52.9 .. 66.1 79.1 21.7 9.1 .. 38.0 4.9 58.8 44.9

32.1 21.6 16.1 7.7 .. .. 20.2 .. .. .. .. 47.9 10.4 18.9 .. 11.0 9.3 46.5 .. 13.8 .. .. 15.7 .. .. .. .. .. .. .. 17.5 3.7 .. 47.3 .. .. 4.5 .. .. .. 52.4 21.4 .. 21.3 18.4 .. 8.2 22.2 51.5 61.2 .. 33.4 79.1 6.2 26.2

44.0 27.9 47.8 84.1 .. .. 42.4 .. .. .. .. 23.1 31.9 17.4 .. 73.2 72.5 1.2 .. 39.5 .. .. 65.5 .. .. .. .. .. .. .. 44.2 94.9 .. 19.8 .. .. 68.3 .. .. .. 31.4 85.2 .. 63.2 39.9 .. 59.3 73.3 20.6 8.2 .. 31.7 5.7 51.8 25.5

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

30.2 11.6 8.9 17.9 .. .. 17.9 .. .. .. .. 49.6 7.7 11.2 .. 7.5 10.0 79.9 .. 10.7 .. .. 18.0 .. .. .. .. .. .. .. 16.9 4.7 .. 45.5 .. .. 4.7 .. .. .. 54.3 21.5 .. 20.3 14.8 .. 5.7 24.8 48.2 66.3 .. 31.2 77.6 2.6 32.1

Total (metric tons of carbon dioxide equivalent) 1990 2005

.. 41,667 3,695 5,511 .. .. 10,530 .. .. .. .. 87,098 4,307 7,485 .. 1,028 25,545 305 .. 5,187 .. .. 9,222 .. .. .. .. .. .. .. 10,881 2,580 .. 19,153 .. .. 2,976 .. .. .. 21,300 36,669 .. 21,468 2,209 .. 35,669 7,284 24,023 3,843 .. 11,818 1,176 5,180 2,006

.. 38,881 2,902 3,081 .. .. 9,127 .. .. .. .. 54,643 3,566 7,364 .. 1,189 30,510 482 .. 4,899 .. .. 10,542 .. .. .. .. .. .. .. 9,501 3,797 .. 21,565 .. .. 4,083 .. .. .. 24,048 49,472 .. 21,647 1,738 .. 25,068 6,114 33,358 4,898 .. 18,996 1,285 5,814 2,366

Agricultural (% of total) 1990 2005

Industrial (% of total) 1990 2005

Other greenhouse ODA gross gasesb disbursements (thousands of ODA gross for general metric tons of disbursements environment carbon dioxide for forestry protection equivalent) ($ millions) ($ millions) 1990 2005 2010 2010

64.5 39.2 50.5 90.9 .. .. 68.1 .. .. .. .. 37.9 48.6 22.7 .. 93.0 91.9 25.6 .. 75.5 .. .. 91.9 .. .. .. .. .. .. .. 82.0 93.2 .. 82.1 .. .. 88.1 .. .. .. 63.3 92.0 .. 82.8 74.3 .. 75.2 84.2 72.0 64.3 .. 71.5 67.2 85.1 59.0

0.3 0.0 0.0 .. .. .. 0.0 .. .. .. .. 0.0 0.0 0.0 .. 0.0 0.0 0.0 .. 0.0 .. .. 0.0 .. .. .. .. .. .. .. 0.0 0.0 .. 0.0 .. .. 0.0 .. .. .. 3.6 0.0 .. 0.0 0.0 .. 0.0 5.9 5.6 4.4 .. 8.2 0.0 0.0 10.6

.. 0 0 0 .. .. 932 .. .. .. .. 0 0 0 .. 0 0 0 .. 596 .. .. 0 .. .. .. .. .. .. .. 0 0 .. 242 .. .. 0 .. .. .. 1,491 0 .. 0 0 .. 0 0 2,668 326 .. 2,059 282 0 0

66.1 38.4 61.5 92.0 .. .. 75.9 .. .. .. .. 31.3 51.8 29.3 .. 90.9 88.8 23.3 .. 70.5 .. .. 88.8 .. .. .. .. .. .. .. 71.4 94.3 .. 77.3 .. .. 88.5 .. .. .. 59.8 92.6 .. 78.8 67.5 .. 71.7 85.2 75.3 58.6 .. 80.0 51.9 82.6 66.4

0.8 0.0 0.0 0.0 .. .. 0.0 .. .. .. .. 0.0 0.0 0.0 .. 0.0 0.0 0.0 .. 0.0 .. .. 0.0 .. .. .. .. .. .. .. 0.0 0.0 .. 0.0 .. .. 0.0 .. .. .. 7.3 0.0 .. 0.0 0.0 .. 3.7 0.0 7.9 7.2 .. 11.5 0.0 0.0 4.2

.. 20 0 0 .. .. 419 .. .. .. .. 0 5 0 .. 0 10 9 .. 15 .. .. 0 .. .. .. .. .. .. .. 282 0 .. 669 .. .. 0 .. .. .. 2,552 0 .. 0 0 .. 0 0 3,950 489 .. 3,181 280 0 0

245.8 0.5 0.6 0.1 3.8 0.0 12.2 0.5 1.4 0.0 0.0 15.8 0.8 17.1 0.1 0.8 26.1 8.0 0.1 15.6 1.1 0.1 22.0 0.1 0.2 1.3 20.7 2.2 0.0 .. 13.4 1.0 0.1 0.5 1.4 0.0 0.3 .. 0.0 .. 8.2 4.5 0.0 3.5 0.0 4.8 0.5 0.0 4.5 0.0 0.1 0.0 .. 0.3 3.4

683.0 2.6 20.2 3.9 13.9 5.5 20.4 9.2 0.7 6.7 1.2 35.9 11.3 4.9 0.3 0.7 16.9 7.6 6.3 29.1 1.3 2.0 62.0 0.8 4.9 12.4 13.7 10.7 9.0 37.9 16.8 13.6 6.4 8.0 8.7 0.2 43.8 0.1 2.6 0.0 27.5 10.2 0.3 30.1 9.2 13.9 10.3 0.9 71.4 4.6 0.4 12.6 0.0 25.5 23.1

Part III. Development outcomes

Participating in growth

Table

8.5

Fossil fuel emissions Carbon dioxide emissions from fossil fuel (thousand metric tons)

Carbon dioxide emissions Total (thousand metric tons of carbon dioxide) 1990 2005 2008

SUB-SAHARAN AFRICA 462,711 Angola 4,430 Benin 715 Botswana 2,178 Burkina Faso 587 Burundi 304 Cameroon 1,738 Cape Verde 88 Central African Republic 198 Chad 147 Comoros 77 Congo, Dem. Rep. 4,070 Congo, Rep. 1,188 Cote d'Ivoire 5,798 Equatorial Guinea 121 Eritrea .. Ethiopia 3,018 Gabon 4,844 Gambia, The 191 Ghana 3,931 Guinea 1,056 Guinea-Bissau 253 Kenya 5,823 Lesotho .. Liberia 484 Madagascar 986 Malawi 612 Mali 422 Mauritania 2,666 Mauritius 1,463 Mozambique 1,001 Namibia 7 Niger 832 Nigeria 45,375 Rwanda 682 São Tomé and Príncipe 66 Senegal 3,183 Seychelles 114 Sierra Leone 389 Somalia 18 South Africa 333,514 Sudan 5,559 Swaziland 425 Tanzania 2,373 Togo 774 Uganda 818 Zambia 2,446 Zimbabwe 15,504 NORTH AFRICA 232,367 Algeria 78,896 Djibouti 400 Egypt, Arab Rep. 75,944 Libya 40,319 Morocco 23,542 Tunisia 13,267

647,225 19,156 2,567 4,525 1,126 165 3,696 293 235 400 110 2,369 1,606 7,825 4,712 766 5,490 1,786 323 7,008 1,360 264 8,562 .. 741 1,705 917 568 1,657 3,410 1,823 2,659 825 104,044 689 128 5,860 697 1,261 579 408,199 11,995 1,019 5,086 1,338 2,340 2,259 10,774 399,960 107,128 473 174,641 52,093 42,823 22,801

1990

Per capita (metric tons) 2005

2008

0.9 0.4 0.2 1.6 0.1 0.1 0.1 0.3 0.1 0.0 0.2 0.1 0.5 0.5 0.3 .. 0.1 5.2 0.2 0.3 0.2 0.3 0.3 .. 0.2 0.1 0.1 0.1 1.3 1.4 0.1 0.0 0.1 0.5 0.1 0.6 0.4 1.6 0.1 0.0 9.5 0.2 0.5 0.1 0.2 0.1 0.3 1.5 1.9 3.1 0.7 1.3 9.3 1.0 1.6

0.9 1.2 0.3 2.4 0.1 0.0 0.2 0.6 0.1 0.0 0.2 0.0 0.5 0.4 7.8 0.2 0.1 1.3 0.2 0.3 0.2 0.2 0.2 .. 0.2 0.1 0.1 0.0 0.5 2.7 0.1 1.3 0.1 0.7 0.1 0.8 0.5 8.4 0.2 0.1 8.7 0.3 1.0 0.1 0.3 0.1 0.2 0.9 2.6 3.3 0.6 2.4 9.0 1.4 2.3

0.9 1.4 0.5 2.5 0.1 0.0 0.3 0.6 0.1 0.1 0.2 0.1 0.5 0.4 7.3 0.1 0.1 1.7 0.3 0.4 0.2 0.2 0.3 .. 0.2 0.1 0.1 0.0 0.6 3.1 0.1 1.8 0.1 0.6 0.1 0.8 0.4 7.8 0.2 0.1 8.9 0.3 1.1 0.2 0.3 0.1 0.2 0.7 2.8 3.2 0.6 2.7 9.5 1.5 2.4

1990

Total 2005

2008

129,277 1,208 195 594 160 83 .. 24 54 40 21 1,110 324 1,581 33 .. 823 1,321 52 1,072 288 69 1,588 .. 132 269 167 115 727 399 273 2 227 12,374 186 18 868 31 106 5 90,950 1,516 116 647 211 223 667 4,228 63,367 21,515 109 20,710 10,995 6,420 3,618

180,471 5,224 700 1,234 307 45 .. 80 64 109 30 646 438 2,134 1,285 209 1,497 487 88 1,911 371 72 2,335 .. 202 465 250 155 452 930 497 725 225 28,373 188 35 1,598 190 344 158 111,317 3,271 278 1,387 365 638 616 2,938 109,070 29,214 129 47,625 14,206 11,678 6,218

191,223 6,646 1,109 1,320 506 49 .. 84 71 135 34 768 528 1,913 1,313 113 1,938 674 112 2,343 380 77 2,834 .. 166 521 335 162 545 1,078 631 1,082 232 26,113 192 35 1,357 186 364 177 118,865 3,832 298 1,763 387 1,022 515 2,475 123,643 30,353 143 57,355 15,907 13,064 6,821

1990

Solid fuel consumption 2005

2008

110,635 0 0 592 0 4 .. 0 0 0 0 209 0 0 0 .. 0 0 0 2 0 0 110 .. 0 9 13 0 4 54 42 0 88 35 0 0 0 0 0 0 72,352 0 116 3 0 0 227 3,662 3,576 825 0 917 4 1,278 72

142,854 0 0 702 0 2 .. 0 0 0 0 273 0 0 0 0 0 0 0 0 0 0 91 .. 0 12 43 0 0 264 0 14 103 8 0 0 114 0 0 0 95,970 0 104 54 0 0 85 2,315 6,204 666 0 837 0 3,844 0

149,617 0 0 624 0 4 .. 0 0 0 0 317 0 0 0 0 0 0 0 0 0 0 112 .. 0 9 37 0 0 471 7 299 104 8 0 0 184 0 0 0 100,605 0 112 65 0 0 1 1,943 6,228 793 0 787 0 3,788 0

Note: 0 refers to a negligible value that rounds to 0.

Part III. Development outcomes

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

Liquid fuel consumption 1990 2005 2008

41,937 489 154 2 160 79 .. 24 54 40 21 838 265 1,513 33 .. 777 244 52 978 288 69 1,273 .. 125 252 141 112 709 345 220 2 136 9,823 177 18 801 31 106 0 16,596 1,493 0 571 157 219 381 471 34,280 6,835 109 14,323 6,058 4,541 2,414

46,087 1,292 666 532 303 43 .. 80 64 109 30 373 358 1,136 142 203 1,284 387 87 1,653 322 72 1,956 .. 182 433 184 155 411 666 392 711 115 10,616 173 35 1,120 190 321 158 11,519 3,226 173 962 256 552 471 542 51,706 8,413 129 24,317 9,347 6,102 3,398

50,785 2,476 891 696 502 45 .. 84 71 135 34 447 444 995 166 107 1,690 539 111 2,085 331 77 2,296 .. 144 475 265 162 501 607 472 783 121 8,695 177 35 733 186 332 177 13,846 3,787 186 1,192 278 934 419 478 61,967 11,299 143 29,438 10,217 7,484 3,386

Carbon dioxide emissions from fossil fuel (thousand metric tons) Gas fuel consumption Gas flaring 1990 2005 2008 1990 2005

.. 276 0 0 0 0 .. 0 0 0 0 0 1 0 0 .. 0 138 0 0 0 0 0 .. 0 0 0 0 0 0 0 0 0 2,041 0 0 3 0 0 0 940 0 0 0 0 0 0 0 17,525 10,619 0 3,552 2,599 30 682

.. 341 0 0 0 0 .. 0 0 0 0 0 12 910 605 0 0 65 1 0 0 0 0 .. 0 0 0 0 0 0 38 0 0 5,307 0 0 7 0 0 0 2,269 0 0 185 0 0 0 0 39,938 16,706 0 18,057 3,010 237 1,831

AGRICULTURE, RURAL DEVELOPMENT, AND ENVIRONMENT

.. 347 0 0 0 0 .. 0 0 0 0 4 13 829 865 0 0 104 1 0 0 0 0 .. 0 0 0 0 0 0 53 0 0 6,718 0 0 6 0 0 0 2,601 0 0 287 0 0 0 0 40,510 13,295 0 21,690 2,806 296 2,325

.. 409 0 0 0 0 .. 0 0 0 0 0 46 0 0 .. 0 924 0 0 0 0 0 .. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .. 2,373 0 0 1,969 0 1

.. 3,412 0 0 0 0 .. 0 0 0 0 0 0 0 538 0 0 0 0 0 0 0 0 .. 0 0 0 0 0 0 0 0 0 12,075 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .. 1,688 0 0 1,357 0 79

2008

1990

.. 3,633 0 0 0 0 .. 0 0 0 0 0 0 0 283 0 0 0 0 0 0 0 0 .. 0 0 0 0 0 0 0 0 0 10,013 0 0 0 0 0 0 0 0 0 0 0 0 0 0 .. 2,600 0 0 2,068 0 82

2,901 35 41 0 0 0 .. 0 0 0 0 63 12 68 0 .. 46 16 0 92 0 0 205 .. 7 8 13 3 14 0 11 0 3 476 8 0 64 0 0 5 1,062 23 0 73 54 4 59 95 4,177 862 0 1,918 367 571 449

Cement production 2005 2008

4,842 179 34 0 4 0 .. 0 0 0 0 0 69 88 0 6 213 35 0 258 49 0 289 .. 20 20 23 0 41 0 67 0 7 367 14 0 357 0 23 0 1,559 45 0 186 109 86 59 82 9,075 1,741 0 4,414 492 1,496 910

6,113 190 218 0 4 0 .. 0 0 0 0 0 71 88 0 6 248 31 0 258 49 0 426 .. 22 37 33 0 44 0 99 0 7 680 14 0 435 0 32 0 1,814 45 0 218 109 88 95 54 11,173 2,366 0 5,440 816 1,496 1,028

Part III. Development outcomes

Participating in growth

Table

9.1

Labor force participation Ages 15 and older

100

2000

Total (in thousands) 2005

2010

255,432 5,198 2,561 817 5,502 2,916 6,195 163 1,678 3,217 180 18,514 1,250 6,385 260 1,660 28,965 443 544 8,426 3,294 498 11,858 848 964 7,300 4,819 3,056 760 527 8,727 638 3,528 39,248 3,798 45 3,950 .. 1,561 2,347 15,233 8,318 315 16,702 2,151 10,128 4,476 5,469 44,267 8,796 210 20,077 1,801 10,197 3,186

293,820 6,063 3,049 924 6,433 3,518 7,147 193 1,840 3,827 210 21,499 1,441 6,989 313 2,179 34,881 505 640 9,112 3,619 568 13,236 850 1,088 8,584 5,718 3,609 934 550 9,882 782 4,284 43,730 4,497 52 4,617 .. 1,977 2,639 17,212 9,561 333 19,283 2,536 11,451 4,951 6,517 50,735 9,983 248 23,941 2,127 10,995 3,441

337,519 7,106 3,618 1,037 7,544 4,312 8,210 225 2,065 4,423 242 25,266 1,693 7,788 369 2,596 40,781 588 751 10,366 4,092 648 15,456 894 1,374 10,148 6,708 4,297 1,117 595 11,077 929 5,114 50,280 5,228 59 5,385 .. 2,261 2,924 18,163 10,791 368 22,138 2,939 13,426 5,511 6,617 56,192 11,204 292 27,104 2,379 11,386 3,827

Part III. Development outcomes

2000

Labor force Male (% of total labor force) 2005

2010

55.0 51.6 53.5 53.1 51.8 46.8 54.9 61.9 53.6 54.5 72.0 49.9 51.9 65.0 55.7 52.7 54.8 54.5 53.0 51.9 55.4 54.5 53.2 51.0 51.0 51.3 50.3 62.5 76.7 65.5 45.0 55.6 69.1 59.9 47.7 64.7 57.1 .. 46.8 67.2 56.9 72.1 59.7 50.3 51.0 50.0 52.8 53.6 78.1 86.3 67.6 78.5 73.9 72.1 75.1

54.2 53.1 52.5 53.3 52.2 47.4 54.6 61.7 53.2 54.6 70.9 49.8 51.2 63.8 55.5 51.7 53.1 53.8 52.5 52.1 55.3 53.4 53.5 52.5 51.3 51.1 51.5 63.9 74.9 64.2 45.7 54.2 69.1 56.7 47.8 63.9 56.6 .. 48.8 66.9 56.3 71.8 60.1 49.9 49.5 50.5 53.7 51.2 77.8 85.0 66.3 78.6 72.1 72.3 73.6

54.3 54.1 52.5 53.7 52.4 47.9 54.3 61.6 52.9 54.7 69.8 50.2 51.5 62.6 55.3 51.4 52.8 53.7 52.1 52.4 54.8 52.7 53.6 54.0 52.3 51.1 48.5 64.5 73.5 62.4 46.4 53.7 68.8 57.2 48.2 62.8 56.1 .. 49.3 66.4 57.2 71.3 60.3 50.2 49.5 50.7 53.9 50.7 76.3 83.1 65.2 75.8 72.0 72.9 73.1

2000

Female (% of total labor force) 2005

2010

45.0 48.4 46.6 46.9 48.2 53.2 45.1 38.2 46.4 45.5 28.0 50.1 48.1 35.0 44.3 47.4 45.2 45.6 47.0 48.2 44.6 45.5 46.8 49.1 49.0 48.7 49.7 37.5 23.3 34.5 55.0 44.4 31.0 40.1 52.3 35.3 42.9 .. 53.2 32.8 43.1 27.9 40.3 49.7 49.0 50.0 47.2 46.4 21.9 13.7 32.4 21.5 26.1 27.9 24.9

45.8 46.9 47.5 46.7 47.8 52.6 45.4 38.3 46.8 45.4 29.1 50.2 48.8 36.2 44.5 48.3 47.0 46.2 47.6 47.9 44.7 46.6 46.6 47.5 48.7 49.0 48.5 36.1 25.1 35.9 54.3 45.9 30.9 43.3 52.2 36.2 43.4 .. 51.3 33.1 43.8 28.2 39.9 50.1 50.5 49.5 46.4 48.8 22.2 15.0 33.7 21.4 27.9 27.7 26.4

45.7 45.9 47.5 46.3 47.6 52.1 45.7 38.4 47.1 45.3 30.2 49.9 48.6 37.4 44.7 48.6 47.2 46.3 47.9 47.6 45.2 47.3 46.5 46.0 47.7 48.9 51.5 35.5 26.5 37.7 53.6 46.3 31.2 42.8 51.8 37.2 43.9 .. 50.7 33.6 42.8 28.7 39.7 49.8 50.5 49.3 46.1 49.3 23.7 16.9 34.8 24.2 28.0 27.1 26.9

L ABOR, MIGRATION, AND POPULATION

Ages 15 and older

2000

Total (% of total population) 2005

2010

69.0 71.3 72.2 74.9 83.7 85.0 69.1 63.8 78.2 72.3 54.4 71.7 68.2 66.2 87.1 82.1 81.7 60.8 77.1 74.6 70.8 70.6 68.1 73.5 60.0 86.8 79.2 51.2 50.2 60.6 85.4 56.4 62.7 55.8 85.9 55.7 76.1 .. 65.4 56.8 52.2 52.3 56.3 88.8 79.0 81.6 80.2 75.0 47.5 43.8 48.8 46.4 50.9 53.3 47.6

69.2 70.2 72.1 75.7 83.8 83.3 69.7 64.9 78.4 72.2 56.0 71.3 69.5 66.6 86.7 83.7 84.6 60.0 77.4 69.8 71.0 72.1 64.9 68.1 60.3 86.6 82.7 51.8 52.1 58.8 85.5 61.5 64.5 54.7 84.8 57.9 76.4 .. 67.2 57.0 53.4 53.0 56.2 89.5 80.2 78.6 79.9 86.6 47.9 43.2 49.9 48.2 53.1 51.9 46.2

69.5 69.7 72.6 76.6 83.8 82.8 70.5 66.4 78.7 72.2 57.5 71.3 70.5 66.8 86.7 84.6 84.0 60.5 77.6 69.2 71.8 72.9 66.3 65.8 60.9 86.1 83.1 52.9 53.7 59.5 84.7 64.0 64.6 55.5 85.8 59.4 76.9 .. 67.6 56.9 52.0 53.6 56.6 89.3 80.8 77.9 79.5 86.1 47.8 43.3 51.2 48.8 53.8 49.5 47.4

L ABOR, MIGRATION, AND POPULATION

2000

Participation rate Male (% of male population) 2005

2010

76.9 75.4 81.2 80.4 90.6 84.3 76.9 83.8 86.1 80.2 78.6 72.9 71.4 81.9 93.3 90.3 90.9 67.2 83.4 76.6 78.3 78.5 73.2 80.1 61.8 89.7 81.2 66.3 78.1 80.7 82.7 64.5 88.4 66.8 85.4 73.8 88.5 .. 63.3 77.8 61.0 75.7 71.7 90.8 82.0 82.6 85.4 81.5 74.7 75.5 66.5 73.1 73.0 78.9 71.6

76.0 76.3 78.6 80.8 90.6 82.3 76.9 83.0 85.5 80.1 79.7 72.3 71.6 81.7 92.5 89.8 91.1 65.0 83.4 72.0 78.3 78.3 69.9 75.3 62.4 89.2 86.3 68.0 78.6 76.8 83.3 68.1 90.6 61.9 83.8 75.6 88.3 .. 67.8 77.6 61.5 76.1 70.8 90.5 80.9 80.0 86.0 90.1 75.0 73.2 66.5 75.8 75.3 77.4 68.3

76.1 77.0 78.3 81.5 90.5 81.9 77.3 83.1 85.2 80.2 80.4 72.4 72.7 81.3 92.3 90.0 89.9 64.9 83.2 71.6 78.3 78.2 71.5 73.3 64.0 88.7 81.2 69.7 79.1 75.7 83.0 69.8 90.1 63.0 85.2 76.4 88.3 .. 68.9 77.0 60.4 76.5 70.7 90.3 81.2 79.6 85.7 89.5 73.5 71.7 67.0 74.2 76.9 74.7 69.7

2000

Female (% of female population) 2005

2010

61.3 67.4 64.0 69.5 77.3 85.6 61.6 46.0 70.7 64.6 30.3 70.6 65.1 48.8 80.4 74.6 72.8 54.6 71.1 72.6 63.3 63.1 63.1 67.6 58.2 84.0 77.2 37.2 23.1 41.2 87.7 48.8 38.0 44.8 86.4 38.4 64.1 .. 67.3 36.6 43.8 29.1 42.7 87.0 76.0 80.7 75.1 68.7 20.7 12.0 31.4 19.9 27.4 29.0 23.7

62.7 64.4 66.1 70.7 77.4 84.1 62.6 48.0 71.7 64.5 32.5 70.5 67.5 50.2 80.4 78.0 78.4 55.1 71.8 67.7 63.7 66.1 60.0 61.6 58.3 84.1 79.2 36.4 26.0 41.4 87.4 55.2 39.2 47.5 85.7 40.9 64.9 .. 66.6 37.1 45.7 29.9 42.9 88.6 79.6 77.1 73.8 83.1 21.1 13.0 33.4 20.6 30.2 27.9 24.3

63.0 62.7 67.1 71.6 77.5 83.7 63.9 50.2 72.5 64.5 34.7 70.2 68.2 51.5 80.6 79.6 78.3 56.0 72.4 66.8 65.2 67.8 61.2 58.7 57.8 83.5 85.0 36.8 28.4 43.9 86.3 58.4 39.8 47.8 86.3 43.2 66.0 .. 66.4 37.6 43.8 30.8 43.5 88.3 80.3 76.2 73.3 82.9 22.5 14.7 35.5 23.5 30.4 25.9 25.3

Part III. Development outcomes

101

Participating in growth

Table

9.1

Labor force participation (continued) Ages 15–64

102

2000

Total (thousands) 2005

2010

2000

Labor force Male (% of total labor force) 2005

247,188 5033.0 2446.0 796.0 5359.0 2789.0 5889.0 156.0 1572.0 3041.0 172.0 17669.0 1190.0 6086.0 250.0 1619.0 28065.0 415.0 521.0 8046.0 3162.0 479.0 11286.0 797.0 926.0 6988.0 4523.0 2992.0 738.0 525.0 8252.0 618.0 3411.0 37176.0 3678.0 44.0 3821.0 .. 1527.0 2298.0 15334.0 9888.0 321.0 16079.0 2065.0 9722.0 4247.0 5177.0 43344.0 8732.0 207.0 19696.0 1769.0 9893.0 3047.0

284,133 5871.0 2920.0 898.0 6278.0 3381.0 6799.0 186.0 1723.0 3633.0 202.0 20536.0 1373.0 6630.0 303.0 2129.0 33599.0 478.0 616.0 8701.0 3474.0 547.0 12676.0 802.0 1046.0 8225.0 5425.0 3541.0 907.0 550.0 9324.0 758.0 4152.0 41202.0 4356.0 50.0 4474.0 .. 1938.0 2583.0 17311.0 11427.0 350.0 18501.0 2437.0 10961.0 4688.0 6172.0 49800.0 9912.0 245.0 23600.0 2090.0 10650.0 3303.0

326,648 6886.0 3462.0 1004.0 7369.0 4163.0 7831.0 218.0 1936.0 4214.0 234.0 24163.0 1617.0 7369.0 358.0 2534.0 39262.0 559.0 724.0 9885.0 3930.0 624.0 14860.0 850.0 1320.0 9739.0 6290.0 4220.0 1085.0 595.0 10445.0 902.0 4956.0 47331.0 5070.0 57.0 5231.0 .. 2221.0 2867.0 18055.0 13399.0 401.0 21193.0 2823.0 12866.0 5284.0 6246.0 55048.0 11129.0 289.0 26643.0 2333.0 10956.0 3698.0

55.7 51.6 53.6 53.0 51.7 47.2 54.5 60.9 53.9 54.5 72.1 50.0 52.2 64.7 56.0 52.5 54.5 55.2 52.6 51.8 55.5 54.5 53.3 51.1 50.9 51.0 50.3 62.5 76.7 65.3 45.0 55.7 69.0 60.1 47.7 63.6 57.1 .. 46.4 67.1 56.9 71.6 59.5 50.1 50.9 49.9 53.1 53.8 78.3 86.3 67.6 78.4 73.7 72.0 74.7

54.9 53.2 52.6 53.1 52.0 47.7 54.2 61.3 53.5 54.6 70.8 50.0 51.4 63.4 55.8 51.5 52.7 54.4 52.1 52.0 55.4 53.4 53.5 52.7 51.2 50.8 51.5 63.9 75.0 64.0 45.7 54.2 69.2 56.8 47.7 64.0 56.6 .. 48.4 66.7 56.3 71.2 60.0 50.0 49.5 50.5 53.9 51.3 78.0 84.9 66.1 78.3 71.9 72.4 73.2

Part III. Development outcomes

2010

55.0 54.1 52.5 53.5 52.3 48.2 54.0 61.0 53.3 54.8 69.7 50.2 51.5 62.3 55.3 51.4 52.5 54.0 51.8 52.2 54.9 52.7 53.7 54.4 52.1 50.9 48.5 64.6 73.6 62.2 46.6 53.9 69.0 57.2 48.1 63.2 56.2 .. 48.9 66.3 57.2 70.7 60.4 50.2 49.5 50.8 54.2 50.9 76.5 83.1 65.1 75.7 71.8 73.6 72.9

2000

Female (% of total labor force) 2005

2010

45.7 48.4 46.4 47.0 48.3 52.9 45.5 38.5 46.1 45.5 27.9 50.0 47.8 35.3 44.0 47.5 45.5 44.8 47.4 48.2 44.5 45.5 46.7 48.9 49.2 49.0 49.7 37.5 23.2 34.5 55.1 44.3 31.0 39.9 52.3 36.4 42.9 .. 53.6 32.9 43.2 28.4 40.5 49.9 49.1 50.1 46.9 46.2 23.1 13.7 32.4 21.7 26.3 28.0 25.4

46.3 46.8 47.4 46.9 48.0 52.3 45.8 38.7 46.5 45.4 29.2 50.0 48.7 36.6 44.2 48.5 47.3 45.6 47.9 48.0 44.6 46.6 46.5 47.3 48.9 49.2 48.5 36.1 25.0 36.0 54.3 45.8 30.8 43.2 52.3 36.0 43.4 .. 51.7 33.3 43.8 28.8 40.0 50.0 50.5 49.5 46.1 48.7 23.2 15.1 33.9 21.7 28.1 27.6 26.8

46.3 45.9 47.5 46.5 47.7 51.8 46.0 38.5 46.8 45.2 30.3 49.8 48.5 37.7 44.4 48.7 47.5 46.0 48.2 47.8 45.1 47.3 46.4 45.7 47.9 49.1 51.5 35.4 26.5 37.8 53.5 46.2 31.1 42.8 51.9 36.8 43.8 .. 51.1 33.7 42.8 29.3 39.7 49.8 50.6 49.2 45.8 49.2 24.2 16.9 35.0 24.3 28.2 26.4 27.1

L ABOR, MIGRATION, AND POPULATION

Ages 15â&#x20AC;&#x201C;64

2000

Total (% of total population) 2005

2010

2000

Participation rate Male (% of male population) 2005

70.0 72.5 73.0 76.7 85.1 86.0 70.0 67.2 78.6 72.6 54.8 72.1 69.3 66.6 89.2 83.8 83.7 61.9 77.2 75.5 72.3 72.0 68.3 74.7 60.5 88.1 78.8 52.7 51.1 64.9 85.6 57.8 63.2 56.0 87.4 58.4 77.2 .. 66.4 58.5 54.7 53.1 57.5 90.2 80.3 82.7 80.4 75.5 50.0 46.4 50.6 48.9 52.6 55.6 50.6

70.2 71.3 73.0 77.8 85.2 84.2 70.5 68.9 78.7 72.5 56.6 71.7 70.7 67.2 88.5 85.3 86.3 61.2 77.5 70.8 72.4 73.5 65.3 69.4 60.9 88.0 83.2 53.1 53.0 63.3 85.6 63.2 65.2 54.7 86.1 60.8 77.5 .. 68.2 58.7 56.4 53.9 57.5 90.8 81.6 79.2 80.1 87.6 50.6 45.8 51.9 51.1 55.2 54.4 49.4

70.5 70.8 73.4 78.9 85.3 83.8 71.5 70.5 79.1 72.6 58.2 71.7 71.8 67.5 88.3 86.3 85.8 61.7 77.8 70.4 73.2 74.4 66.8 67.1 61.5 87.5 82.6 54.2 54.6 64.3 84.9 66.0 65.4 55.5 87.2 62.1 78.0 .. 68.7 58.7 55.2 54.6 58.0 90.6 82.2 78.5 79.8 87.3 50.6 45.9 53.4 51.8 56.2 51.6 50.7

77.6 76.3 81.5 81.3 91.2 85.0 76.8 86.4 86.4 80.1 78.7 73.0 72.5 82.2 95.3 91.0 92.2 68.7 83.2 77.2 79.5 79.7 73.3 81.0 61.8 90.5 80.6 67.7 79.0 85.2 82.5 65.8 89.0 67.0 86.4 76.6 89.8 .. 63.9 79.7 63.2 75.9 72.8 91.4 82.9 83.1 85.7 81.8 78.0 79.4 68.4 76.2 75.2 82.0 75.7

76.6 77.2 78.8 81.8 91.2 83.0 76.9 85.9 85.8 80.1 79.9 72.3 72.7 82.2 94.4 90.5 91.9 66.5 83.2 72.5 79.5 79.5 70.2 76.4 62.5 90.0 86.5 69.3 79.5 81.5 83.0 69.6 91.6 61.7 84.7 78.5 89.7 .. 68.4 79.5 64.1 76.4 71.9 91.3 81.8 80.4 86.3 90.9 78.7 77.0 68.6 79.7 77.8 80.8 72.6

L ABOR, MIGRATION, AND POPULATION

2010

76.7 77.9 78.6 82.8 91.1 82.6 77.4 86.1 85.5 80.2 80.8 72.6 73.8 81.9 94.0 90.8 90.7 66.4 83.0 72.3 79.5 79.4 71.9 74.5 64.2 89.5 80.3 70.9 79.9 80.5 82.7 71.6 91.1 62.9 86.2 78.9 89.7 .. 69.6 78.9 63.2 76.8 71.8 91.2 82.3 79.9 86.1 90.4 77.3 75.4 69.3 78.1 79.9 78.3 74.0

2000

Female (% of female population) 2005

2010

62.5 68.8 65.2 72.1 79.5 86.8 63.2 49.8 71.1 65.2 30.8 71.3 66.1 49.5 82.6 77.0 75.5 55.2 71.5 73.9 64.9 64.6 63.3 69.0 59.1 85.9 77.0 38.5 23.6 44.8 88.3 50.2 38.4 44.9 88.3 40.8 65.0 .. 68.7 37.9 46.5 30.2 43.9 89.1 77.8 82.3 75.2 69.2 22.0 12.8 32.9 21.3 28.6 30.5 25.6

63.9 65.6 67.4 73.7 79.6 85.3 64.2 52.4 71.9 65.2 33.1 71.2 68.8 51.0 82.1 80.3 80.8 56.0 72.2 69.0 65.3 67.7 60.4 62.9 59.3 86.0 79.9 37.6 26.5 45.3 88.0 57.0 39.6 47.6 87.5 43.6 65.9 .. 67.9 38.5 48.9 31.2 44.2 90.3 81.4 78.0 74.0 84.3 22.6 14.0 35.1 22.3 31.6 29.3 26.4

64.3 64.0 68.5 74.8 79.8 84.9 65.6 54.8 72.8 65.2 35.4 70.9 69.7 52.4 82.0 82.0 80.9 57.1 72.8 68.4 66.8 69.4 61.8 60.0 58.9 85.4 84.9 37.9 29.0 48.3 86.8 60.5 40.2 48.0 88.2 45.8 66.9 .. 67.8 39.0 47.2 32.2 44.9 90.0 82.2 77.0 73.5 84.3 23.9 15.7 37.4 25.3 32.0 26.4 27.5

Part III. Development outcomes

103

Participating in growth

Table

9.1

Labor force participation (continued) Ages 15–24

104

2000

Total (thousands) 2005

2010

2000

Labor force Male (% of total labor force) 2005

70,787 1,450 755 234 1,998 903 1,530 55 467 908 50 4,339 287 1,739 57 684 9,641 70 180 2,097 858 128 3,049 274 206 2,171 1,305 946 205 106 2,579 119 1,024 8,899 1,317 13 1,338 .. 340 675 2,623 2,422 103 5,670 652 3,140 1,446 1,735 11,015 2,553 67 4,407 454 2,822 712

81,250 1,704 861 259 2,267 1,106 1,752 64 521 1,090 54 5,142 313 1,879 82 756 11,599 70 204 1,831 955 150 3,152 249 228 2,466 1,799 1,087 240 86 2,742 156 1,283 10,337 1,553 15 1,523 .. 451 700 2,902 2,695 116 6,457 745 3,496 1,607 2,506 12,306 2,422 77 5,968 487 2,676 676

90,735 1,994 995 264 2,562 1,239 1,939 68 571 1,255 53 6,057 352 2,047 103 818 13,562 80 228 1,879 1,077 167 3,372 229 274 2,992 1,812 1,240 276 88 3,045 192 1,610 11,557 1,625 15 1,715 .. 503 779 2,667 3,022 132 7,185 829 4,021 1,765 2,480 10,905 2,048 84 5,439 420 2,256 658

53.7 50.5 51.3 53.0 53.6 48.0 54.2 61.8 54.4 50.0 70.0 45.1 50.2 60.7 57.9 52.6 52.9 54.3 48.9 50.6 54.1 53.1 53.7 55.1 51.0 50.5 47.7 62.3 76.1 64.2 44.0 54.6 66.4 57.9 48.3 69.2 60.2 .. 42.4 64.9 54.8 63.2 57.3 50.1 50.2 48.5 51.9 54.2 73.2 83.1 55.2 70.4 69.4 69.4 66.2

53.1 51.8 49.3 52.5 53.6 47.7 54.0 62.5 54.3 50.3 70.4 44.9 50.2 60.5 58.5 51.6 51.9 54.3 49.5 51.0 53.8 52.0 55.0 57.4 50.9 50.3 51.1 62.4 74.2 60.5 45.2 53.2 67.7 54.2 48.3 66.7 60.2 .. 43.2 64.9 54.9 62.8 57.8 49.7 48.2 50.0 52.2 51.6 73.9 84.6 54.6 70.9 68.0 72.1 67.5

Part III. Development outcomes

2010

53.1 52.7 49.1 52.3 53.5 47.2 53.8 61.8 53.9 50.4 69.8 46.1 50.3 60.4 58.3 51.8 51.8 53.8 49.6 51.2 53.2 51.5 55.1 58.5 51.1 50.5 45.4 62.6 72.5 59.1 45.7 52.6 68.2 54.5 48.6 66.7 60.1 .. 43.9 64.6 55.3 62.4 58.3 49.9 48.3 50.0 52.2 51.1 74.2 84.5 54.8 71.2 68.3 73.6 67.5

2000

Female (% of total labor force) 2005

2010

47.5 49.5 48.7 47.0 46.5 52.1 45.8 38.2 45.6 50.0 30.0 54.9 49.8 39.3 42.1 47.4 47.1 45.7 51.1 49.4 45.9 46.9 46.3 44.9 49.0 49.5 52.3 37.7 23.9 35.9 56.0 45.4 33.6 42.1 51.7 30.8 39.8 .. 57.7 35.1 45.2 36.8 42.7 50.0 49.9 51.5 48.1 45.8 28.6 16.9 44.8 29.6 30.6 30.6 33.9

47.9 48.2 50.8 47.5 46.5 52.4 46.0 37.5 45.7 49.7 29.6 55.2 49.8 39.5 41.5 48.4 48.1 45.7 50.5 49.0 46.2 48.0 45.1 42.6 49.1 49.7 48.9 37.6 25.8 39.5 54.8 46.8 32.4 45.8 51.7 33.3 39.8 .. 56.8 35.1 45.1 37.2 42.2 50.3 51.8 50.0 47.9 48.4 27.8 15.4 45.5 29.1 32.0 28.0 32.5

47.9 47.3 51.0 47.7 46.5 52.8 46.2 38.2 46.1 49.6 30.2 53.9 49.7 39.6 41.8 48.2 48.2 46.3 50.4 48.8 46.8 48.5 44.9 41.5 48.9 49.5 54.6 37.4 27.5 40.9 54.3 47.4 31.8 45.5 51.4 33.3 39.9 .. 56.1 35.4 44.7 37.6 41.7 50.1 51.8 50.0 47.8 48.9 27.5 15.5 45.2 28.8 31.7 26.4 32.5

L ABOR, MIGRATION, AND POPULATION

Ages 15â&#x20AC;&#x201C;24

2000

Total (% of total population) 2005

2010

2000

Participation rate Male (% of male population) 2005

53.2 54.0 60.2 59.4 78.2 70.6 47.7 60.6 63.5 56.8 39.6 46.2 44.9 51.3 76.9 79.4 78.9 29.0 65.5 53.9 53.5 53.1 44.5 62.8 35.0 75.1 58.9 40.5 38.0 50.6 71.6 30.9 53.6 35.6 75.9 41.2 67.5 .. 40.6 47.3 28.7 35.7 45.1 82.1 65.9 65.4 68.4 59.6 36.2 36.9 45.3 31.5 35.2 46.4 36.4

53.3 53.2 57.7 59.8 77.7 67.6 47.8 60.2 63.3 56.7 40.5 45.8 44.8 51.5 76.0 77.4 79.3 25.5 65.3 41.7 53.7 54.8 39.7 51.8 35.1 73.7 71.4 40.7 39.0 42.7 67.7 36.6 56.1 36.8 73.1 42.8 66.9 .. 44.3 45.8 29.5 35.6 44.5 82.0 66.2 61.3 68.8 80.4 37.2 32.5 44.6 37.8 38.2 42.1 32.9

52.9 52.8 57.0 59.6 77.1 65.1 47.8 59.8 62.7 56.6 39.6 45.4 44.9 51.1 76.0 77.3 77.1 25.1 64.4 38.6 54.4 55.2 39.9 45.2 35.3 72.8 59.7 40.9 39.9 40.7 66.1 39.8 57.0 37.4 73.6 40.8 66.6 .. 44.2 45.0 26.5 35.3 44.5 81.0 66.2 59.9 67.7 79.6 33.2 28.1 44.1 34.0 37.4 36.0 33.0

56.3 54.9 62.9 62.3 82.8 68.3 51.5 74.8 69.8 56.9 54.9 41.6 44.9 62.0 89.3 83.5 83.7 31.5 66.4 53.5 56.8 56.6 47.7 68.9 35.5 75.8 56.1 49.7 56.9 64.4 64.4 33.5 76.8 40.4 74.8 55.9 81.2 .. 35.2 61.6 31.4 44.6 52.6 82.0 66.3 63.5 70.9 64.5 52.1 60.3 49.6 43.6 48.2 64.7 47.7

55.9 55.6 57.5 62.2 82.1 64.7 51.4 73.7 69.4 57.0 55.9 41.0 44.7 62.2 88.1 80.7 82.5 27.5 66.1 41.6 56.9 57.2 43.6 59.0 35.4 74.1 72.8 49.9 56.9 51.1 61.4 38.8 80.6 39.2 71.3 57.6 80.3 .. 39.3 59.5 32.2 44.0 51.6 81.5 64.1 61.5 71.5 83.5 54.0 54.0 48.5 52.8 51.1 61.1 43.9

L ABOR, MIGRATION, AND POPULATION

2010

55.4 56.1 56.4 61.8 81.4 61.7 51.2 72.6 68.3 57.0 54.1 41.8 45.1 61.7 88.0 80.4 79.8 26.9 64.6 38.7 56.9 56.7 43.9 52.6 35.7 73.6 53.9 50.3 56.8 47.3 60.6 41.7 80.4 40.0 72.1 54.4 79.6 .. 39.8 58.2 29.2 43.3 51.6 80.7 64.2 60.2 70.5 82.2 48.2 46.5 47.8 47.6 50.0 53.0 43.8

2000

Female (% of female population) 2005

2010

50.0 53.2 57.6 56.4 73.5 72.9 43.9 46.4 57.4 56.7 24.0 50.8 44.8 40.5 64.4 75.3 74.2 26.5 64.7 54.4 50.1 49.6 41.4 56.6 34.5 74.3 61.7 31.1 18.4 36.7 78.5 28.2 33.6 30.5 77.1 26.3 53.8 .. 45.9 33.1 26.0 26.7 37.9 82.1 65.5 67.3 65.9 54.6 20.0 12.7 41.0 19.0 21.8 28.2 24.9

50.7 50.9 58.0 57.3 73.1 70.5 44.1 46.3 57.3 56.5 24.7 50.6 44.9 40.8 63.7 74.3 76.2 23.4 64.6 41.9 50.5 52.5 35.9 44.4 34.8 73.2 69.9 31.2 20.6 34.1 74.1 34.3 34.3 34.4 74.9 27.8 53.5 .. 49.2 32.1 26.7 26.8 37.4 82.5 68.3 61.1 66.0 77.4 20.0 10.2 40.5 22.3 24.8 23.3 21.6

50.4 49.6 57.6 57.4 72.7 68.4 44.4 46.4 57.2 56.3 24.7 49.1 44.8 40.6 63.8 74.2 74.5 23.3 64.3 38.6 51.7 53.6 35.9 37.7 34.9 72.1 65.5 31.2 22.4 33.8 71.6 37.8 35.1 34.6 75.0 26.8 53.3 .. 48.5 31.8 23.8 26.9 37.3 81.2 68.2 59.6 64.8 77.1 17.7 8.9 40.3 19.9 24.2 19.0 21.8

Part III. Development outcomes

105

Participating in growth

Table

9.2

Labor force composition Sectora Industry

Agriculture

Services

Male (% of male employment) 2000–10 b

Female (% of female employment) 2000–10 b

Male (% of male employment) 2000–10 b

Female (% of female employment) 2000–10 b

Male (% of male employment) 2000–10 b

Female (% of female employment) 2000–10 b

.. 53.1 35.1 82.3 .. 57.7 .. .. .. .. .. 31.3 .. .. .. 8.7 17.3 .. 61.4 .. .. 54.5 .. 49.5 79.8 .. 67.8 .. 9.5 69.2 22.7 64.1 49.1 .. 30.6 34.1 .. 66.0 .. 6.3 .. .. 72.7 60.5 68.6 65.9 58.8

.. 32.7 24.3 87.2 .. 64.7 .. .. .. .. .. 39.3 .. .. .. 10.3 33.7 .. 53.2 .. .. 68.0 .. 48.3 81.1 .. 63.9 .. 7.8 89.9 8.2 37.8 38.7 .. 22.8 33.0 .. 71.1 .. 3.7 .. .. 80.0 48.2 81.7 78.9 71.1

.. 9.8 19.2 3.9 .. 10.9 .. .. .. .. .. 20.0 .. .. .. 25.4 18.6 .. 13.4 .. .. 10.8 .. 13.5 5.6 .. 8.0 .. 32.1 7.0 24.4 8.3 11.8 .. 26.3 20.2 .. 10.3 .. 34.5 .. .. 6.6 9.5 8.6 10.9 14.0

.. 9.2 10.8 2.1 .. 7.4 .. .. .. .. .. 21.2 .. .. .. 19.5 2.5 .. 13.8 .. .. 2.3 .. 4.8 1.8 .. 2.7 .. 22.0 0.4 9.1 18.4 11.2 .. 5.9 4.9 .. 2.5 .. 13.3 .. .. 2.1 4.4 2.8 3.1 4.4

.. 34.5 45.7 13.7 .. 23.5 .. .. .. .. .. 45.9 .. .. .. 75.6 64.1 .. 25.1 .. .. 34.6 .. 37.0 14.6 .. 24.1 .. 58.3 23.8 52.8 26.5 37.0 .. 42.6 32.7 .. 23.7 .. 59.2 .. .. 20.7 28.6 22.7 23.7 17.3

.. 57.5 64.9 10.2 .. 21.8 .. .. .. .. .. 38.7 .. .. .. 63.9 63.8 .. 33.0 .. .. 29.7 .. 46.8 17.1 .. 33.3 .. 70.4 9.7 82.6 43.0 47.9 .. 70.7 42.3 .. 26.4 .. 82.9 .. .. 17.9 45.7 15.5 17.3 13.2

20.4 .. 28.2 .. 34.2 ..

22.3 .. 45.6 .. 59.2 ..

25.6 .. 27.3 .. 24.0 ..

28.2 .. 5.6 .. 15.4 ..

53.8 .. 44.4 .. 41.6 ..

49.5 .. 48.8 .. 25.2 ..

a. Components may not sum to 100 percent because of unclassiﬁed data. b. Data are for the most recent year available during the period speciﬁed.

106

Part III. Development outcomes

L ABOR, MIGRATION, AND POPULATION

Wage and salaried workers Total Male Female (% of total (% of males (% of females employed) employed) employed) 2000–10 b 2000–10 b 2000–10 b

Statusa Self-employed workers Total Male Female (% of total (% of males (% of females employed) employed) employed) 2000–10 b 2000–10 b 2000–10 b

Contributing family workers Total Male Female (% of total (% of males (% of females employed) employed) employed) 2000–10 b 2000–10 b 2000–10 b

.. 10.1 60.5 7.1 5.2 16.0 38.9 .. .. .. .. 21.7 19.6 .. .. 7.9 44.8 .. 19.9 .. .. .. .. 18.1 13.4 .. 8.0 .. 80.0 8.8 72.8 5.3 .. .. .. 21.6 .. 7.6 .. 84.6 .. .. 10.5 10.9 23.6 17.0 37.7

.. 16.3 62.2 9.7 .. 29.3 43.8 .. .. .. .. 35.5 25.4 .. .. 9.3 52.2 .. 29.7 .. .. .. .. 27.5 16.0 .. 12.4 .. 77.9 15.7 76.0 5.9 .. .. .. 26.1 .. 11.3 .. 84.3 .. .. 15.3 16.6 22.2 25.7 51.0

.. 4.2 58.6 4.0 .. 8.7 33.0 .. .. .. .. 8.6 12.2 .. .. 6.2 34.5 .. 10.9 .. .. .. .. 8.7 10.8 .. 3.6 .. 83.8 3.0 68.8 3.9 .. .. .. 15.1 .. 3.7 .. 85.1 .. .. 6.1 5.7 7.5 9.0 23.1

.. 89.9 39.5 90.4 94.7 84.0 42.1 .. .. .. .. 76.2 76.3 .. .. 91.8 54.0 .. 79.9 .. .. .. .. 81.7 86.4 .. 82.9 .. 20.0 91.2 26.7 85.4 .. .. .. 77.7 .. 92.4 .. 15.4 .. .. 89.5 89.1 76.4 82.0 62.3

.. 83.7 37.8 87.8 .. 66.5 39.1 .. .. .. .. 61.7 70.1 .. .. 90.3 46.4 .. 70.2 .. .. .. .. 72.3 83.9 .. 76.5 .. 22.1 84.3 23.6 83.8 .. .. .. 73.2 .. 88.7 .. 15.8 .. .. 84.7 83.4 77.8 74.3 49.0

.. 95.8 41.4 93.5 .. 88.9 45.7 .. .. .. .. 89.9 84.3 .. .. 93.5 64.6 .. 89.1 .. .. .. .. 91.1 89.1 .. 89.0 .. 16.2 97.0 30.7 89.5 .. .. .. 84.1 .. 96.3 .. 14.9 .. .. 93.9 94.3 92.5 91.0 76.9

.. 16.1 3.2 46.0 30.8 26.8 10.3 .. .. .. .. 4.0 28.2 .. .. 50.3 4.1 .. 20.4 .. .. .. .. 16.1 52.3 .. 26.4 .. 2.4 36.7 4.4 3.2 .. .. .. 24.0 .. 18.1 .. 0.9 .. .. 11.4 25.9 29.2 38.0 11.9

.. 13.9 2.1 26.5 .. 9.5 6.5 .. .. .. .. 3.3 15.8 .. .. 34.6 2.3 .. 11.7 .. .. .. .. 12.5 32.1 .. 18.5 .. 1.0 12.7 3.2 3.3 .. .. .. 23.5 .. 14.8 .. 0.4 .. .. 9.7 23.1 10.3 25.4 10.4

.. 18.2 4.4 69.2 .. 27.2 14.8 .. .. .. .. 4.7 44.2 .. .. 68.5 6.7 .. 28.5 .. .. .. .. 19.7 73.0 .. 34.1 .. 4.9 56.8 5.8 2.8 .. .. .. 24.7 .. 21.6 .. 1.4 .. .. 13.0 28.4 40.5 61.8 13.6

38.2 .. 58.5 .. 44.4 64.3

36.0 .. 61.4 .. 47.5 ..

51.1 .. 47.9 .. 34.0 ..

34.4 .. 41.5 .. 53.3 35.6

34.4 .. 38.6 .. 52.4 ..

34.0 .. 52.1 .. 65.9 ..

7.2 .. 14.1 .. 22.9 8.7

7.2 .. 8.7 .. 15.0 ..

7.3 .. 33.9 .. 48.6 ..

L ABOR, MIGRATION, AND POPULATION

Part III. Development outcomes

107

Participating in growth

Table

9.3

Unemployment

Total 2000–10 b

Unemployment (% ages 15 and older) Male 2000–10 b

Total 2000–10 b

Youth unemployment (% ages 15–24) Male 2000–10 b

Female 2000–10 b

.. 0.7 17.6 3.3 .. 2.9 .. .. .. .. .. .. .. .. .. 20.5 .. .. 3.6 .. .. .. 25.3 3.7 2.6 7.8 8.8 33.0 7.7 .. 37.6 1.5 .. .. 16.7 10.0 5.5 3.4 .. 23.8 .. .. 4.3 .. 4.2 15.9 4.2

.. 0.9 15.3 2.9 .. 2.5 .. .. .. .. .. .. .. .. .. 12.1 .. .. 3.5 .. .. .. 23.0 3.4 1.7 5.4 7.2 8.9 4.6 .. 32.5 1.7 .. .. 11.0 7.9 6.1 4.5 .. 22.0 .. .. 2.8 .. 3.1 14.1 4.2

.. 0.4 19.9 1.7 .. 3.3 .. .. .. .. .. .. .. .. .. 29.9 .. .. 3.6 .. .. .. 28.0 4.1 3.5 10.0 10.9 41.2 12.8 .. 43.0 0.9 .. .. 24.5 13.6 4.9 2.3 .. 25.9 .. .. 5.8 .. 5.1 11.3 4.1

.. 0.8 13.6 3.8 .. .. .. .. .. .. .. .. .. .. .. 24.9 .. .. 16.6 .. .. .. 34.4 5.9 2.3 .. .. .. 23.4 .. 41.7 3.2 .. .. .. 14.8 20.3 5.2 .. 48.2 .. .. 8.8 .. 5.4 23.4 7.6

.. 1.1 13.2 4.6 .. .. .. .. .. .. .. .. .. .. .. 19.5 .. .. 16.4 .. .. .. 29.0 3.9 1.7 .. .. .. 19.4 .. 36.7 4.0 .. .. .. 11.9 .. 7.3 .. 44.6 .. .. 7.4 .. .. 23.1 7.6

.. 0.6 14.0 2.9 .. .. .. .. .. .. .. .. .. .. .. 29.4 .. .. 16.7 .. .. .. 41.9 7.7 2.8 .. .. .. 29.0 .. 47.0 1.7 .. .. .. 20.1 .. 3.5 .. 52.5 .. .. 10.1 .. .. 19.5 7.6

11.4 59.5 9.4 .. 10.0 14.2

10.0 54.6 5.2 .. 9.8 13.1

20.0 68.6 22.9 .. 10.5 17.3

24.3 .. 24.8 .. 21.9 30.7

42.8 .. 17.2 .. 22.8 31.4

46.3 .. 47.9 .. 19.4 29.3

a. Components may not sum to 100 percent because of unclassiﬁed data. b. Data are for the most recent year available during the period speciﬁed.

108

Part III. Development outcomes

L ABOR, MIGRATION, AND POPULATION

Unemployment by education levela (% of total unemployed) Secondary Total Male Female 2000–10 b 2000–10 b 2000–10 b

Total 2000–10 b

Primary Male 2000–10 b

Female 2000–10 b

.. .. 61.5 47.0 .. .. .. .. .. .. .. .. .. .. .. 35.9 .. .. .. .. .. .. 57.2 .. 43.9 .. .. .. 43.5 .. .. .. .. 60.7 .. 40.2 .. .. .. 15.4 .. .. 71.6 .. .. .. 16.2

.. .. 60.1 44.4 .. .. .. .. .. .. .. .. .. .. .. 50.6 .. .. .. .. .. .. 57.9 .. 42.9 .. .. .. 43.4 .. .. .. .. 62.8 .. 42.2 .. .. .. 18.6 .. .. 74.6 .. .. .. 14.3

.. .. 62.6 58.3 .. .. .. .. .. .. .. .. .. .. .. 30.8 .. .. .. .. .. .. 56.5 .. 44.4 .. .. .. 43.6 .. .. .. .. 59.4 .. 37.9 .. .. .. 12.5 .. .. 69.3 .. .. .. 17.2

.. .. 24.1 19.7 .. .. .. .. .. .. .. .. .. .. .. 13.3 .. .. .. .. .. .. 33.5 .. 23.8 .. .. .. 29.6 .. .. .. .. 24.1 .. 6.9 .. .. .. 80.7 .. .. 7.2 .. .. .. 82.0

.. .. 22.8 16.7 .. .. .. .. .. .. .. .. .. .. .. 19.0 .. .. .. .. .. .. 26.4 .. 25.8 .. .. .. 25.2 .. .. .. .. 23.0 .. 7.5 .. .. .. 77.0 .. .. 7.8 .. .. .. 83.6

59.3 .. .. .. 51.1 41.4

65.2 .. .. .. 57.7 46.0

32.5 .. .. .. 36.6 31.9

23.0 .. .. .. 22.4 37.7

21.4 .. .. .. 21.7 37.3

L ABOR, MIGRATION, AND POPULATION

Total 2000–10 b

Tertiary Male 2000–10 b

Female 2000–10 b

.. .. 25.2 33.3 .. .. .. .. .. .. .. .. .. .. .. 11.3 .. .. .. .. .. .. 40.4 .. 22.7 .. .. .. 32.2 .. .. .. .. 24.9 .. 6.2 .. .. .. 84.0 .. .. 6.7 .. .. .. 81.0

.. .. 28.2 6.1 .. .. .. .. .. .. .. .. .. .. .. 3.2 .. .. .. .. .. .. 0.4 .. 9.3 .. .. .. 7.9 .. .. .. .. 5.9 .. 2.5 .. .. .. 0.8 .. .. .. .. .. .. 0.3

.. .. 26.2 5.6 .. .. .. .. .. .. .. .. .. .. .. 5.7 .. .. .. .. .. .. 0.4 .. 14.0 .. .. .. 9.6 .. .. .. .. 0.5 .. 2.8 .. .. .. 0.9 .. .. .. .. .. .. 0.7

.. .. 29.8 8.3 .. .. .. .. .. .. .. .. .. .. .. 2.3 .. .. .. .. .. .. 0.4 .. 6.6 .. .. .. 7.0 .. .. .. .. 9.4 .. 2.1 .. .. .. 0.7 .. .. .. .. .. .. 0.1

30.4 .. .. .. 23.9 38.5

11.4 .. .. .. 21.6 13.6

6.6 .. .. .. 16.2 9.0

33.0 .. .. .. 33.5 23.3

Part III. Development outcomes

109

Participating in growth

Table

9.4

Migration and population

Migrant stock Share of population (%) Total 2010 2010

110

2.07 0.34 2.62 5.72 6.33 0.72 1 2.43 1.83 3.46 1.84 0.67 3.54 12.19 1.06 0.31 0.66 18.87 16.78 7.59 3.95 1.27 2.02 0.29 2.41 0.18 1.85 1.06 2.87 3.35 1.92 6.08 1.3 0.71 4.38 3.18 1.69 12.53 1.82 0.24 3.73 1.73 3.83 1.47 3.08 1.93 1.8 2.96 0.82 0.68 12.84 0.3 10.74 0.15 0.32

Part III. Development outcomes

International migration Worker remittances, Migrant remittance received inflows Net Total Share of Total Share of migration ($ millions) GDP (%) ($ millions) GDP (%) 2010 2010 2010 2010 2010

17,645,403 -1,985,547 .. 65,387 82,005 18.0 232,036 50,000 .. 114,838 18,730 12.1 1,043,035 -125,000 .. 60,770 370,000 34.5 196,570 -19,000 93.6 12,053 -17,279 130.4 80,492 5,000 .. 388,251 -75,000 .. 13,525 -10,000 .. 444,672 -23,975 .. 143,203 49,872 .. 2,406,713 -360,000 .. 7,447 20,000 .. 16,484 55,000 .. 547,984 -300,000 345.2 284,127 5,000 .. 290,104 -13,742 107.3 1,851,814 -51,258 135.9 394,557 -300,000 44.8 19,244 -10,000 .. 817,747 -189,330 683.7 6,328 -19,998 7.4 96,310 300,000 0.2 37,762 -5,000 .. 275,851 -20,000 .. 162,677 -100,823 .. 99,229 9,900 .. 42,917 0 .. 450,020 -20,000 33.4 138,870 -1,494 6.0 202,163 -28,497 .. 1,127,668 -300,000 19,650.7 465,480 15,109 98.2 5,253 -6,496 2.0 210,061 -132,842 .. 10,838 .. 16.5 106,776 60,000 41.6 22,843 -300,000 .. 1,862,889 700,001 .. 753,447 135,000 1,290.9 40,418 -6,000 1.9 659,202 -300,000 10.9 185,402 -5,430 .. 646,548 -135,000 768.0 233,140 -85,000 43.7 372,258 -900,000 .. 1,366,356 -1,202,222 20,673.0 242,324 -140,000 66.0 114,147 0 6.6 244,714 -346,922 12,453.1 682,482 -20,300 .. 49,098 -675,000 6,422.5 33,591 -20,000 1,724.8

.. 0.0 .. 0.1 .. 1.7 0.4 7.9 .. .. .. .. .. .. .. .. 1.2 .. 10.2 0.4 1.0 .. 2.1 0.3 0.0 .. .. .. .. .. 0.4 0.1 .. 10.0 1.8 1.0 .. 1.7 2.2 .. .. 1.9 0.1 0.1 .. 4.5 0.3 .. 4.0 0.0 .. 5.7 .. 7.1 3.9

20,501.5 18.0 149.9 62.6 110.6 34.5 114.9 132.5 .. .. .. .. .. 185.5 .. .. 345.2 .. 115.7 135.9 60.4 48.9 1,777.0 745.9 31.4 .. 16.7 453.7 .. 226.4 131.9 15.9 101.7 10,045.0 103.1 2.0 1,350.4 17.4 57.5 .. 1,119.3 1,419.6 54.7 24.8 334.5 914.5 43.7 .. 23,016.0 2,044.4 32.6 12,453.1 .. 6,422.5 2,063.3

1.8 0.0 2.3 0.4 1.3 1.7 0.5 8.0 .. .. .. .. .. 0.8 .. .. 1.2 .. 11.0 0.4 1.3 5.9 5.5 34.2 3.2 .. 0.3 4.8 .. 2.3 1.4 0.1 1.9 5.1 1.8 1.0 10.5 1.8 3.0 .. 0.3 2.1 1.5 0.1 10.5 5.3 0.3 .. 3.9 1.3 .. 5.7 .. 7.1 4.7

Population Population dynamics Annual Fertility rate Total Male Female growth rate (births per woman) (%) (millions) (% of total) (% of total) 2010 2010 2010 2010 2010

844.0 19.1 8.8 2.0 16.5 8.4 19.6 0.5 4.4 11.2 0.7 66.0 4.0 19.7 0.7 5.3 82.9 1.5 1.7 24.4 10.0 1.5 40.5 2.2 4.0 20.7 14.9 15.4 3.5 1.3 23.4 2.3 15.5 158.4 10.6 0.2 12.4 0.1 5.9 9.3 50.0 33.6 1.1 44.8 6.0 33.4 12.9 12.6 166.3 35.5 0.9 81.1 6.4 32.0 10.5

50.0 49.5 49.3 50.4 49.6 49.1 49.9 49.5 49.3 49.7 50.4 49.7 50.1 51.0 51.3 49.3 49.8 50.2 49.4 50.9 50.5 49.6 49.9 49.2 50.2 49.9 50.0 50.0 50.3 49.4 48.7 49.7 50.3 50.6 49.1 49.5 49.6 .. 48.9 49.6 49.5 50.4 49.2 50.0 49.5 50.0 50.1 49.3 50.1 50.5 50.0 50.2 50.7 49.0 50.0

50.0 50.5 50.7 49.6 50.4 50.9 50.1 50.5 50.7 50.3 49.7 50.3 50.0 49.0 48.7 50.8 50.2 49.9 50.6 49.1 49.5 50.4 50.1 50.9 49.8 50.2 50.0 50.0 49.8 50.6 51.4 50.3 49.7 49.4 50.9 50.5 50.4 .. 51.2 50.4 50.5 49.6 50.9 50.1 50.5 50.0 49.9 50.7 50.0 49.5 50.0 49.8 49.3 51.0 50.0

2.5 2.8 2.8 1.3 3.0 2.6 2.2 0.9 1.9 2.6 2.6 2.7 2.5 2.0 2.8 3.0 2.2 1.9 2.7 2.4 2.2 2.1 2.6 1.0 4.0 2.9 3.1 3.0 2.4 0.5 2.3 1.8 3.5 2.5 3.0 1.8 2.7 -0.9 2.2 2.3 1.4 1.9 1.1 3.0 2.1 3.2 1.6 0.8 1.5 1.5 1.9 1.8 1.5 1.0 1.0

4.9 5.4 5.3 2.8 5.9 4.3 4.5 2.4 4.6 6.0 4.9 5.8 4.5 4.4 5.2 4.5 4.2 3.3 4.9 4.2 5.3 5.1 4.7 3.2 5.2 4.7 6.0 6.3 4.5 1.5 4.9 3.2 7.1 5.5 5.4 3.7 4.8 2.5 5.0 6.3 2.5 4.4 3.4 5.5 4.1 6.2 6.3 3.3 2.5 2.3 3.8 2.7 2.6 2.3 2.0

L ABOR, MIGRATION, AND POPULATION

Population Age composition (% of total) Ages 0â&#x20AC;&#x201C;14

Ages 15â&#x20AC;&#x201C;64

Ages 65 and older

Total 2010

Male 2010

Female 2010

Total 2010

Male 2010

Female 2010

Total 2010

Male 2010

Female 2010

42.5 46.6 43.7 32.6 45.3 37.9 40.6 31.8 40.4 45.4 42.6 46.3 40.6 40.9 39.3 41.6 41.5 35.5 44.0 38.6 42.9 41.3 42.5 37.4 43.5 43.1 45.8 47.2 39.9 21.9 44.1 36.4 49.0 42.8 42.7 40.3 43.7 .. 43.0 44.9 30.1 40.1 38.4 44.7 39.7 48.4 46.4 38.9 29.4 27.1 35.8 31.5 30.4 28.0 23.5

42.9 47.2 44.5 32.6 46.5 38.7 40.9 32.2 40.8 45.9 43.1 46.7 40.9 40.3 38.5 42.7 41.9 35.7 44.9 38.9 43.3 41.8 42.8 38.3 44.1 43.5 46.3 48.2 40.4 22.6 45.5 37.0 49.9 43.2 43.3 41.1 44.5 .. 43.6 45.5 30.6 40.6 39.4 45.1 40.0 48.8 46.5 39.5 30.0 27.4 36.1 32.1 30.8 29.2 24.0

42.0 46.0 42.9 32.6 44.2 37.1 40.2 31.4 40.0 45.0 42.1 45.9 40.3 41.6 40.1 40.6 41.0 35.2 43.1 38.3 42.5 40.9 42.2 36.5 42.9 42.8 45.4 46.2 39.4 21.2 42.8 35.9 48.0 42.4 42.0 39.5 42.8 .. 42.5 44.4 29.7 39.6 37.5 44.3 39.3 48.1 46.2 38.2 28.7 26.7 35.5 31.0 30.0 26.9 23.0

54.4 51.0 53.3 63.5 52.5 59.3 55.9 62.3 55.6 51.7 54.7 51.1 55.7 55.3 57.9 55.9 55.2 60.2 53.9 57.6 53.8 55.4 54.9 58.3 53.7 53.8 51.1 50.6 57.4 71.2 52.6 59.9 48.8 53.8 54.7 55.8 53.9 .. 55.1 52.4 65.2 56.4 58.2 52.2 57.0 49.1 50.6 56.9 65.5 68.4 60.9 63.4 65.3 66.5 69.6

54.2 50.6 53.0 64.1 51.8 59.1 55.9 63.1 55.6 51.6 54.5 51.0 55.8 55.7 58.7 55.4 55.0 60.3 52.9 57.6 53.8 55.2 54.8 58.1 53.5 53.6 50.9 50.0 57.4 71.7 51.6 59.8 48.1 53.7 54.3 55.5 53.2 .. 54.4 52.1 65.8 56.2 57.8 52.1 56.9 49.0 50.8 56.7 65.4 68.5 60.9 63.4 65.1 65.8 69.5

54.5 51.3 53.5 62.8 53.1 59.5 55.9 61.5 55.7 51.8 54.8 51.1 55.7 54.8 56.9 56.4 55.4 60.1 54.8 57.7 53.8 55.5 55.0 58.5 54.0 53.9 51.3 51.3 57.5 70.8 53.5 60.0 49.6 53.9 55.1 56.2 54.6 .. 55.8 52.6 64.6 56.5 58.7 52.2 57.0 49.2 50.4 57.1 65.7 68.2 60.9 63.5 65.5 67.2 69.7

3.2 2.5 3.0 4.0 2.2 2.9 3.5 5.9 4.0 2.9 2.7 2.7 3.7 3.8 2.9 2.5 3.3 4.3 2.2 3.8 3.3 3.3 2.7 4.3 2.8 3.1 3.1 2.2 2.7 6.9 3.3 3.7 2.2 3.4 2.7 3.9 2.4 .. 1.9 2.7 4.6 3.6 3.4 3.1 3.4 2.5 3.1 4.2 5.1 4.6 3.3 5.0 4.3 5.5 7.0

2.9 2.2 2.5 3.3 1.8 2.3 3.2 4.7 3.6 2.6 2.4 2.3 3.4 4.0 2.8 1.9 3.1 4.0 2.3 3.6 3.0 3.0 2.4 3.6 2.5 3.0 2.8 1.8 2.2 5.7 2.9 3.2 2.0 3.1 2.4 3.4 2.3 .. 2.0 2.5 3.6 3.3 2.9 2.8 3.1 2.3 2.7 3.8 4.6 4.1 3.0 4.5 4.1 5.1 6.6

3.5 2.7 3.6 4.7 2.7 3.4 3.8 7.1 4.4 3.2 3.0 3.0 4.0 3.6 3.0 3.0 3.6 4.7 2.1 4.0 3.7 3.6 2.9 5.0 3.1 3.3 3.3 2.6 3.2 8.0 3.7 4.2 2.4 3.7 2.9 4.3 2.5 .. 1.8 3.0 5.7 3.9 3.8 3.5 3.7 2.8 3.4 4.7 5.6 5.1 3.7 5.6 4.5 5.9 7.3

L ABOR, MIGRATION, AND POPULATION

Geographic distribution (%) Dependency ratio Share of total population Annual growth (% of working-age Rural Urban Rural Urban population) population population population population 2010 2010 2010 2010 2010

84.8 96.3 87.7 57.6 90.7 68.7 78.9 60.5 79.7 93.5 82.9 95.9 79.4 80.9 72.9 78.8 81.2 66.1 85.7 73.6 86.0 80.6 82.2 71.5 86.2 86.0 95.7 97.5 74.2 40.4 90.1 66.9 104.8 85.9 82.8 79.2 85.5 .. 81.4 91.0 53.3 77.5 71.7 91.8 75.6 103.8 97.7 75.7 52.8 46.3 64.2 57.6 53.2 50.4 43.7

62.7 41.5 58.0 38.9 79.6 89.0 41.6 38.9 61.1 72.4 71.8 64.8 37.9 49.9 60.3 78.4 82.4 14.0 41.9 48.5 64.6 70.0 77.8 73.1 38.5 69.8 80.2 66.7 58.6 57.4 61.6 62.0 83.3 50.2 81.1 37.8 57.1 44.7 61.6 62.6 38.3 54.8 74.5 73.6 56.6 86.7 64.3 61.7 46.3 33.5 11.9 57.2 22.1 43.3 32.7

37.3 58.5 42.0 61.1 20.4 11.0 58.4 61.1 38.9 27.6 28.2 35.2 62.1 50.1 39.7 21.6 17.6 86.0 58.1 51.5 35.4 30.0 22.2 26.9 61.5 30.2 19.8 33.3 41.4 42.6 38.4 38.0 16.7 49.8 18.9 62.2 42.9 55.3 38.4 37.4 61.7 45.2 25.5 26.4 43.4 13.3 35.7 38.3 53.7 66.5 88.1 42.8 77.9 56.7 67.3

1.7 0.7 2.2 -0.7 2.5 2.2 0.2 -1.0 1.6 2.0 2.5 1.8 1.5 0.7 2.5 2.5 1.8 -1.5 0.8 0.8 1.5 2.0 2.2 0.0 2.3 2.4 2.5 2.2 2.1 0.4 1.0 0.9 3.5 1.1 2.6 -0.4 2.2 -2.0 1.7 1.6 0.1 0.3 0.8 2.4 0.9 3.0 1.4 0.0 1.0 -0.4 -1.4 1.7 0.7 0.2 -0.2

3.8 4.4 3.8 2.5 5.1 5.3 3.6 2.1 2.3 4.3 2.8 4.5 3.2 3.3 3.2 5.1 3.9 2.4 4.2 3.8 3.6 2.3 4.0 3.7 5.2 4.0 5.7 4.7 2.9 0.6 4.4 3.4 4.0 4.0 4.5 3.1 3.3 0.0 3.1 3.5 2.1 3.9 2.3 4.7 3.7 4.4 2.0 2.0 2.0 2.4 2.3 1.8 1.7 1.6 1.6

Part III. Development outcomes

111

Participating in growth

Table

10.1

HIV/AIDS Estimated prevalence rate (%)

112

Estimated number of people living with HIV/AIDS (thousands) 1990 2000 2009

Point estimate 1990 2000 2009

Adults (ages 15–49) Low estimate 1990 2000 2009

1990

28 6 23 160 93 33 .. 44 31 <1.0 .. 63 140 <0.5 5 .. 4 <1.0 22 34 1 400 6 3 12 310 15 2 <0.5 76 11 4 590 160 .. 6 .. <0.5 2 140 12 9 600 11 870 500 510

140 49 260 150 170 460 .. 190 130 <0.1 .. 68 640 4 25 .. 34 4 250 78 13 1,500 240 52 17 850 91 8 3 750 150 51 2,600 170 .. 30 .. 21 9 4,200 61 120 1,400 99 980 810 1,700

200 60 320 110 180 610 .. 130 210 <0.5 .. 77 450 20 25 .. 46 18 260 79 22 1,500 290 37 24 920 76 14 9 1,400 180 61 3,300 170 .. 59 .. 49 34 5,600 .. 180 1,400 120 1,200 980 1,200

0.5 0.2 3.5 3.9 3.9 0.6 .. 3.1 1.1 <0.1 .. 5.2 2.4 0.1 0.3 .. 0.9 0.1 0.3 1.1 0.3 3.9 0.8 0.3 0.2 7.2 0.4 0.2 <0.1 1.2 1.6 0.1 1.3 5.2 .. 0.2 .. <0.1 0.1 0.7 0.1 2.3 4.8 0.6 10.2 12.7 10.1

1.9 1.4 26.0 2.3 5.2 5.5

2.0 1.2 24.8 1.2 3.3 5.3 .. 4.7 3.4 0.1 .. 3.4 3.4 5.0 0.8 .. 5.2 2.0 1.8 1.3 2.5 6.3 23.6 1.5 0.2 11.0 1.0 0.7 1.0 11.5 13.1 0.8 3.6 2.9 .. 0.9 .. 1.6 0.7 17.8 1.1 25.9 5.6 3.2 6.5 13.5 14.3

0.2 <0.1 2.9 2.6 3.7 0.3 .. 2.0 0.5 <0.1 1.2 3.6 1.3 <0.1 0.1 .. 0.6 0.1 0.2 0.5 0.1 3.0 0.6 0.1 0.2 3.3 0.1 0.1 <0.1 0.9 0.9 0.1 0.2 4.3 .. 0.1 .. <0.1 <0.1 0.6 <0.1 1.8 4.3 0.1 8.6 3.4 8.7

1.4 1.2 25.1 1.9 5.1 5.0 .. 8.4 2.0 <0.1 1.1 3.5 6.2 1.0 0.9 .. 4.1 0.3 2.0 1.1 1.5 8.6 23.0 2.2 0.2 13.0 1.3 0.5 0.2 7.8 12.9 1.0 3.3 3.5 .. 0.5 .. 0.4 <0.1 15.7 0.1 21.0 6.9 2.8 6.7 13.8 23.8

1.6 1.0 23.8 1.0 2.9 4.9 .. 4.2 2.8 0.1 1.2 3.1 3.1 3.5 0.6 .. 4.2 1.3 1.6 1.1 2.0 5.8 22.3 1.3 0.2 10.0 0.8 0.6 0.7 10.6 11.1 0.8 3.3 2.5 .. 0.7 .. 1.4 0.5 17.2 0.9 24.9 5.3 2.5 5.9 12.8 13.4

1.4 3.7 4.2 4.8 4.0 2.4 .. 6.2 2.0 <0.1 1.6 6.4 7.2 0.2 0.9 .. 1.5 1.7 1.5 7.6 0.4 6.6 1.2 0.6 0.2 10.8 2.0 0.2 0.2 1.5 2.3 0.1 2.1 8.4 .. 0.2 .. <0.1 0.3 0.9 0.4 2.7 5.3 1.2 11.5 26.4 11.7

2.4 1.7 27.1 2.7 5.4 6.0 .. 11.4 4.0 <0.1 1.5 4.5 7.6 2.5 1.6 .. 6.6 1.1 2.6 2.7 2.2 9.6 26.1 4.5 0.2 15.5 2.0 0.7 0.4 9.4 18.1 1.0 4.3 4.6 .. 0.7 .. 1.6 0.3 16.6 0.5 23.6 8.0 4.3 7.7 15.2 26.1

2.4 1.3 25.8 1.5 3.5 5.8 .. 5.2 5.1 0.1 1.6 3.8 3.9 6.6 1.0 .. 6.2 2.9 2.0 1.6 3.0 6.5 25.2 1.8 0.3 12.1 1.3 0.9 1.3 12.2 15.5 0.9 4.0 3.3 .. 1.0 .. 2.1 1.0 18.3 1.4 27.0 6.1 3.8 6.9 14.1 15.4

.. 3 <0.5 .. 3 <0.2

6 12 3 .. 13 <1.0

18 14 11 .. 3 2

<0.1 0.9 <0.1 .. <0.1 <0.1

<0.1 2.9 <0.1

0.1 2.5 <0.1 .. 0.1 <0.1

<0.1 <0.1 <0.1 .. <0.1 <0.1

<0.1 2.0 <0.1 .. 0.1 <0.1

0.1 .. <0.1 .. 0.1 <0.1

<0.1 3.5 <0.1 .. <0.1 <0.1

<0.1 4.1 <0.1 .. 0.1 <0.1

0.1 3.2 <0.1 .. 0.2 0.1

Part III. Development outcomes

9.4 3.0 <0.1 ... 3.9 6.9 1.5 1.2 ... 5.2 0.5 2.3 1.7 1.8 9.0 24.5 3.3 0.2 14.2 1.7 0.6 0.3 8.6 15.3 1.0 3.9 3.8 0.6 0.9 0.2 16.1 0.3 22.3 7.3 3.6 7.3 14.4 24.8

0.1 <0.1

High estimate 2000 2009

HIV/AIDS

Estimated HIV prevalence rate (%)

Point estimate 2009

Young men (ages 15â&#x20AC;&#x201C;24) Low estimate 2009

High estimate 2009

Point estimate 2009

Young women (ages 15â&#x20AC;&#x201C;24) Low estimate 2009

High estimate 2009

0.6 0.3 5.2 0.5 1.0 1.6 .. 1.0 1.0 0.1 .. 1.2 0.7 1.9 0.2 .. 1.4 0.9 0.5 0.4 0.8 1.8 5.4 0.3 0.1 3.1 0.2 0.4 0.3 3.1 2.3 0.2 1.2 1.3 .. 0.3 .. 0.6 0.4 4.5 0.5 6.5 1.7 0.9 2.3 4.2 3.3

0.4 0.2 3.7 0.3 0.8 1.2 .. 0.6 0.7 0.1 0.4 0.9 0.5 1.0 0.1 .. 0.8 0.5 0.4 0.3 0.5 1.3 4.1 0.1 0.1 2.3 0.1 0.2 0.2 2.4 1.3 0.2 0.9 0.9 .. 0.2 .. 0.3 .. 4.1 .. 4.8 1.3 0.6 1.8 3.2 2.5

0.9 0.4 7.3 0.6 1.2 2.1 .. 1.4 2.0 0.1 0.6 1.6 1.1 3.2 0.3 .. 2.0 1.6 0.7 0.6 1.1 2.4 7.4 0.5 0.4 4.2 0.4 1.4 0.4 4.4 3.6 0.3 1.6 1.6 .. 0.4 .. 1.0 .. 5.0 .. 8.8 2.3 1.2 2.8 5.5 4.4

1.6 0.7 11.8 0.8 2.1 3.9 .. 2.2 2.5 <0.1 .. 2.6 1.5 5.0 0.4 .. 3.5 2.4 1.3 0.9 2.0 4.1 14.2 0.7 0.1 6.8 0.5 0.3 0.2 8.6 5.8 0.5 2.9 1.9 .. 0.7 .. 1.5 0.6 13.6 1.3 15.6 3.9 2.2 4.8 8.9 6.9

1.1 0.5 9.0 0.6 1.6 3.1 .. 1.4 1.7 <0.1 0.9 2.1 1.1 2.7 0.2 .. 2.1 1.4 0.9 0.6 1.5 3.0 11.2 0.2 <0.1 5.3 0.2 0.1 0.1 7.0 3.7 0.4 2.3 1.3 .. 0.5 .. 0.9 .. 12.3 .. 12.6 3.1 1.5 4.0 7.3 5.3

2.2 1.1 15.9 1.2 2.7 5.4 .. 3.1 5.2 <0.1 1.5 3.6 2.3 7.9 0.7 .. 5.2 4.0 1.8 1.3 2.9 5.4 19.2 1.2 0.1 9.2 0.9 0.5 0.3 12.1 8.6 0.6 3.9 2.3 .. 1.0 .. 2.5 .. 15.0 .. 21.3 5.3 3.1 6.4 12.0 9.3

0.1 0.8 <0.1 .. 0.1 <0.1

<0.1 .. <0.1 .. <0.1 <0.1

0.2 .. <0.1 .. 0.3 0.1

<0.1 1.9 <0.1 .. 0.1 <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

113

Participating in growth

Table

10.1

HIV/AIDS (continued)

Deaths of adults and children due to HIV/AIDS (thousands) Point estimate Low estimate High estimate 1990 2000 2009 1990 2000 2009 1990 2000 2009

<1.0 <0.2 <1.0 6.7 3.9 <1.0 .. 1.0 1.4 <0.1 .. 3.0 3.9 <0.1 <0.2 .. <0.2 <0.1 <1.0 1.1 <0.1 10.0 .. <0.1 <1.0 11.0 <0.5 <0.1 <0.1 2.2 <0.5 <0.2 10.0 8.4 .. <0.5 .. <0.1 <0.2 2.9 <1.0 <0.5 21.0 <0.5 37.0 23.0 14.0 <0.1 <0.1 <0.1 .. <0.2 <0.1

9.2 11.0 3.0 2.7 13.0 5.8 15.0 7.1 14.0 15.0 27.0 37.0 .. .. 14.0 11.0 7.9 11.0 <0.1 <0.1 .. .. 5.7 5.1 48.0 36.0 <0.2 <1.0 1.6 1.7 .. .. 1.8 2.4 <0.2 <1.0 15.0 18.0 6.1 4.7 <1.0 1.2 120.0 80.0 12.0 14.0 3.5 3.6 1.3 1.7 64.0 51.0 6.9 4.4 <0.5 <1.0 <0.1 <0.5 36.0 74.0 6.7 6.7 2.9 4.3 200.0 220.0 15.0 4.1 .. 1.6 2.6 .. <1.0 2.8 <0.5 .. 170.0 310.0 3.0 .. 5.7 7.0 110.0 86.0 5.6 7.7 89.0 64.0 66.0 45.0 130.0 83.0 <0.2 <1.0 <0.2 .. <1.0 <0.1

<1.0 1.0 <0.5 .. 1.2 <0.1

<0.5 5.6 7.7 <0.1 1.7 1.8 <0.5 11.0 2.3 4.1 11.0 4.8 3.1 11.0 12.0 <0.5 22.0 29.0 .. .. .. <1.0 11.0 8.8 <1.0 4.7 8.1 <0.1 <0.1 <0.1 12.0 23.0 26.0 <1.0 4.8 4.1 2.1 34.0 29.0 <0.1 <0.2 <1.0 <0.1 <1.0 1.0 .. .. .. <0.1 1.4 1.6 <0.1 <0.1 <0.5 <0.5 11.0 14.0 <0.5 2.5 3.1 <0.1 <0.5 <1.0 6.7 98.0 61.0 <0.1 10.0 10.0 <0.1 2.0 2.8 <1.0 1.0 1.4 4.1 53.0 38.0 <0.1 3.8 3.0 <0.1 <0.5 <1.0 <0.1 <0.1 <0.5 1.5 28.0 57.0 <0.2 5.1 2.5 <0.1 2.3 3.3 <0.5 110.0 170.0 5.6 12.0 <1.0 .. .. <0.2 1.3 1.9 .. .. <0.1 <0.5 2.1 <0.1 <0.1 .. 2.0 140.0 260.0 <0.1 <0.5 .. <0.2 4.7 4.6 16.0 90.0 69.0 <0.1 3.8 5.3 22.0 76.0 49.0 <1.0 55.0 30.0 9.7 110.0 70.0

3.2 18.0 <1.0 11.0 4.7 9.3 .. 5.8 2.9 <0.1 26.0 6.2 12.0 <0.1 <1.0 .. <0.5 <1.0 6.9 15.0 <0.1 22.0 <0.2 <0.2 1.4 22.0 4.3 <0.2 <0.2 3.3 <1.0 <0.2 21.0 13.0 .. <0.5 .. <0.1 <1.0 4.3 3.5 <0.5 27.0 2.0 83.0 46.0 19.0

<0.1 <0.1 <0.1 .. <0.1 <0.1

<0.1 <1.0 <1.0 .. 0.5 <0.1

<0.1 <0.5 <0.1 .. <0.5 <0.1

<1.0 <1.0 <0.5 .. <1.0 <0.1

Point estimate 1990 2000 2009

13.0 16.0 2.1 54.0 140.0 5.4 3.7 <0.5 11.0 30.0 16.0 14.0 1.0 45.0 93.0 19.0 9.7 13.0 130.0 140.0 16.0 17.0 10.0 120.0 200.0 33.0 46.0 1.3 100.0 330.0 .. .. .. .. .. 20.0 13.0 2.0 69.0 140.0 12.0 15.0 5.1 43.0 120.0 <0.1 <0.1 .. .. <0.1 34.0 40.0 .. .. .. 7.1 6.4 6.9 48.0 51.0 65.0 44.0 7.3 230.0 440.0 <0.5 1.4 <0.1 <0.5 4.1 2.5 2.5 <0.5 7.0 19.0 .. .. .. .. .. 2.5 3.4 <0.2 6.0 18.0 <1.0 1.2 <0.1 <1.0 2.8 20.0 22.0 1.3 47.0 160.0 14.0 6.9 2.5 36.0 59.0 <1.0 1.6 <0.2 2.2 9.7 140.0 99.0 17.0 710.0 1,200.0 15.0 18.0 <0.1 38.0 130.0 5.7 4.6 <0.1 15.0 52.0 1.5 2.0 6.6 9.4 11.0 77.0 67.0 25.0 380.0 650.0 11.0 6.1 <0.5 29.0 59.0 <1.0 1.0 <0.5 1.3 3.6 <0.2 <1.0 <0.1 <0.2 1.0 45.0 92.0 6.6 180.0 670.0 8.8 11.0 <1.0 23.0 70.0 3.5 5.6 <0.5 13.0 57.0 250.0 260.0 12.0 1,100.0 2,500.0 21.0 97.0 32.0 160.0 130.0 .. .. .. .. 2.0 3.5 <1.0 7.3 19.0 .. .. .. .. 1.9 3.7 <0.1 1.5 15.0 <1.0 .. .. .. .. 210.0 390.0 4.4 430.0 1,900.0 6.5 .. .. .. .. 7.1 10.0 <1.0 23.0 69.0 130.0 110.0 53.0 750.0 1,300.0 7.4 10.0 <0.5 19.0 66.0 100.0 80.0 280.0 1,000.0 1,200.0 76.0 60.0 74.0 540.0 690.0 150.0 97.0 29.0 670.0 1,000.0 <0.5 1.3 <0.5 <1.0 <0.1

1.1 1.4 <1.0 .. 1.6 <0.2

.. .. .. .. .. ..

AIDS orphans (ages 0–17, thousands) Low estimate 1990 2000 2009

High estimate 1990 2000 2009

<1.0 <0.1 <1.0 5.2 7.7 <1.0 .. 1.2 2.1 .. 46.0 <0.2 4.0 <0.1 <0.1 .. <0.1 <0.1 <1.0 1.1 <0.1 10.0 <0.1 <0.1 4.0 7.1 <0.1 <0.1 <0.1 2.1 <0.5 <0.5 <0.5 19.0 .. <0.5 .. <0.1 .. 2.3 .. <0.5 37.0 <0.1 180.0 <0.1 18.0

23.0 3.7 36.0 96.0 98.0 67.0 .. 43.0 22.0 .. 270.0 31.0 140.0 <0.2 3.2 .. 4.1 <0.5 33.0 9.9 1.3 550.0 29.0 7.3 7.3 280.0 11.0 <1.0 <0.1 84.0 17.0 11.0 300.0 130.0 .. 5.4 .. <1.0 .. 340.0 .. 18.0 610.0 8.5 800.0 340.0 550.0

95.0 18.0 71.0 100.0 170.0 270.0 .. 110.0 79.0 <0.1 350.0 41.0 330.0 2.5 12.0 .. 12.0 1.4 120.0 34.0 7.7 980.0 110.0 34.0 9.3 540.0 36.0 2.7 <0.5 .. 50.0 44.0 1,800.0 98.0 .. 15.0 .. 9.2 .. 1,600.0 .. 55.0 1,100.0 47.0 1,000.0 570.0 910.0

9.9 95.0 200.0 470.0 110.0 53.0 1.7 59.0 120.0 71.0 180.0 170.0 14.0 150.0 230.0 36.0 210.0 420.0 .. .. .. 49.0 100.0 180.0 11.0 79.0 170.0 .. .. <0.1 210.0 430.0 510.0 31.0 72.0 66.0 16.0 410.0 550.0 <0.1 <1.0 6.4 2.6 16.0 28.0 .. .. .. <0.5 9.2 25.0 6.6 6.5 6.5 58.0 110.0 210.0 110.0 97.0 120.0 <0.5 3.1 12.0 40.0 960.0 1,400.0 <0.2 51.0 160.0 <0.5 25.0 76.0 12.0 12.0 14.0 68.0 500.0 780.0 15.0 82.0 93.0 <0.5 1.9 4.8 <0.5 <0.5 <1.0 5.6 150.0 .. 1.4 33.0 96.0 <0.5 16.0 73.0 94.0 1,700.0 3,100.0 92.0 240.0 180.0 .. .. .. 1.4 9.4 25.0 .. .. .. <0.1 5.1 26.0 .. .. .. 7.4 550.0 2,400.0 .. .. .. <1.0 29.0 86.0 75.0 940.0 1,500.0 23.0 39.0 89.0 770.0 1,400.0 1,400.0 210.0 740.0 810.0 53.0 840.0 1,200.0

.. .. .. .. .. ..

Note: 0 refers to a negligible value that rounds to 0.

114

Part III. Development outcomes

HIV/AIDS

HIV-positive pregnant women receiving antiretrovirals to reduce the risk of mother-to-child transmission Share of total (WHO/UNAIDS methodology, %) Total Point estimate Low estimate High estimate 2009 2009 2009 2009

3,053 1,703 12,406 2,084 1,837 9,092 61 2,157 989 1 2,232 441 11,064 365 464 6,721 577 885 3,643 783 383 58,591 8,846 377 17 33,156 1,710 68 41 68,248 6,744 1,737 44,723 7,030 11 917 12 637 188,200 245 8,182 58,833 1,451 46,948 47,175 28,208

19 46 >95 32 12 27 .. 34 6 .. .. 12 54 26 34 .. 30 .. 27 17 24 73 64 16 .. 58 .. .. .. 70 88 .. 22 65 .. .. .. 19 .. 88 2 88 70 26 53 69 56

12 29 74 19 9 18 .. 23 3 10 4 8 36 16 21 13 20 43 18 11 16 50 48 10 1 40 26 12 33 51 61 25 15 43 .. 16 .. 12 0 66 1 68 48 15 37 50 41

36 92 >95 60 22 50 .. 67 12 33 11 23 95 50 71 40 60 95 53 34 49 95 95 33 5 95 82 37 95 95 95 74 42 95 .. 45 .. 36 0 95 3 95 95 67 95 95 95

65 63 11 .. 90 3

.. 10 .. .. .. ..

14 6 3 .. 13 6

59 21 10 .. 49 25

HIV/AIDS

ODA gross disbursements ($ millions) For social mitigation of HIV/AIDS For STD control, including HIV/AIDS 2009 2010 2009 2010

96.5 0.5 0.0 1.5 0.3 2.6 0.2 .. 0.0 0.0 .. 0.3 0.0 0.3 .. 0.0 3.7 .. .. 0.1 0.0 .. 6.1 5.3 0.0 0.0 3.1 0.1 .. .. 8.4 0.1 0.0 0.0 0.5 0.0 0.1 .. 0.2 .. 11.4 0.1 0.6 7.1 0.0 7.2 3.4 9.4 0.0 .. 0.0 0.0 .. .. ..

77.2 0.2 0.1 0.1 0.8 3.3 0.0 .. 0.5 1.0 .. 0.1 .. 1.0 .. .. 3.5 .. .. 0.2 0.1 0.0 5.5 8.6 .. .. 2.9 0.1 0.0 .. 7.3 0.1 0.0 0.0 0.3 0.0 0.1 .. 0.2 .. 7.2 0.0 0.3 4.4 0.0 2.8 2.0 3.1 0.0 .. 0.0 0.0 .. .. ..

3,791.1 12.2 22.9 211.8 41.2 30.0 28.4 0.5 4.5 9.2 0.1 27.6 6.9 67.5 0.9 15.7 211.0 3.9 6.2 58.6 6.9 5.9 377.3 29.6 5.1 9.4 150.1 25.4 0.8 0.9 192.1 119.7 13.0 369.1 135.1 0.1 19.0 0.0 13.2 1.3 564.7 12.0 27.2 257.1 17.2 259.0 223.8 71.2 15.4 1.2 0.7 4.2 0.0 5.7 3.0

4,372.8 24.8 30.2 73.9 40.8 16.1 18.2 2.0 10.4 13.3 0.5 71.5 12.7 90.8 1.6 19.5 464.2 2.2 6.5 33.5 7.2 6.8 399.4 47.7 15.3 11.1 123.0 18.9 0.2 2.1 244.8 123.2 6.4 418.8 202.8 0.1 24.8 0.0 21.5 12.5 567.1 45.0 57.9 361.8 11.3 282.6 218.3 106.4 18.4 1.1 1.9 3.8 .. 7.2 4.1

Part III. Development outcomes

115

Participating in growth

Table

11.1

Malaria

Population (millions) 2009 2010

Clinical cases of malaria reporteda 2009 2010

Reported deaths due to malaria 2009 2010

SUB-SAHARAN AFRICA 823.6 844.0 72,099,998 71,412,328 115,380 132,524 Angola 18.6 19.1 2,221,076 2,783,619 10,530 8,114 Benin 8.6 8.8 1,256,708 1,432,095 1,375 964 Botswana 2.0 2.0 14,878 12,196 6 8 Burkina Faso 16.0 16.5 4,399,837 5,409,156 7,982 9,024 Burundi 8.2 8.4 1,764,343 2,919,866 1,183 2,677 Cameroon 19.2 19.6 1,883,199 1,845,691 4,943 4,536 Cape Verde 0.5 0.5 65 47 2 1 Central African Republic 4.3 4.4 175,210 66,484 667 526 Chad 10.9 11.2 182,415 466,034 221 .. Comoros 0.7 0.7 49,679 47,364 .. 53 Congo, Dem. Rep. 64.2 66.0 6,749,112 7,439,440 21,168 23,476 Congo, Rep. 3.9 4.0 92,855 0 116 .. Côte d'Ivoire 19.4 19.7 1,847,367 .. 18,156 1,023 Equatorial Guinea 0.7 0.7 78,983 0 23 .. Eritrea 5.1 5.3 21,298 53,750 23 27 Ethiopia 81.2 82.9 3,043,203 4,068,764 1,121 1,581 Gabon 1.5 1.5 112,840 159,313 197 182 Gambia, The 1.7 1.7 479,409 116,353 240 151 Ghana 23.8 24.4 1,899,544 2,642,221 3,378 3,859 Guinea 9.8 10.0 812,471 1,092,554 586 735 Guinea-Bissau 1.5 1.5 143,011 0 369 .. Kenya 39.5 40.5 8,123,689 4,585,712 .. 26,017 Lesotho 2.1 2.2 .. .. .. .. Liberia 3.8 4.0 871,560 2,263,973 1,706 1,422 Madagascar 20.1 20.7 215,110 202,450 348 122 Malawi 14.4 14.9 6,183,816 6,851,108 8,915 8,206 Mali 14.9 15.4 1,633,423 1,018,846 2,331 3,006 Mauritania 3.4 3.5 167,705 238,565 91 211 Mauritius 1.3 1.3 .. .. .. .. Mozambique 22.9 23.4 4,310,086 1,522,577 3,747 3,354 Namibia 2.2 2.3 87,402 25,889 68 63 Niger 15.0 15.5 309,675 620,058 2,159 3,929 Nigeria 154.5 158.4 4,295,686 3,873,463 7,522 4,238 Rwanda 10.3 10.6 1,247,583 638,669 809 670 São Tomé and Príncipe 0.2 0.2 3,922 2,262 23 14 Senegal 12.1 12.4 222,232 0 574 .. Seychelles 0.1 0.1 .. .. .. .. Sierra Leone 5.7 5.9 646,808 934,028 1,734 8,188 Somalia 9.1 9.3 72,362 24,553 45 6 South Africa 49.3 50.0 6,117 8,060 45 83 Sudan 33.0 33.6 2,361,188 1,465,496 1,142 1,023 Swaziland 1.0 1.1 6,639 1,722 13 8 Tanzania 43.5 44.8 40 0 .. .. Togo 5.9 6.0 618,842 617,101 1,556 1,507 Uganda 32.4 33.4 9,775,318 11,084,045 6,296 8,431 Zambia 12.7 12.9 2,976,395 4,229,839 3,862 4,834 Zimbabwe 12.5 12.6 736,897 648,965 108 255 NORTH AFRICA 163.9 166.3 3,019 4,673 3 4 Algeria 35.0 35.5 94 408 .. .. Djibouti 0.9 0.9 2,686 3,962 0 0 Egypt, Arab Rep. 79.7 81.1 94 85 2 2 Libya 6.3 6.4 .. .. .. .. Morocco 31.6 32.0 145 218 1 2 Tunisia 10.4 10.5 .. .. .. ..

Children sleeping under insecticideUnder-five treated nets mortality (% of children rate under age 5) (per 1,000) 2009 2010 2000–10 b

125 164 118 49 178 143 138 37 161 175 87 172 94 125 125 63 109 75 101 77 134 152 87 92 109 65 98 182 112 15 140 44 150 147 98 81 79 14 180 180 61 104 82 80 106 103 116 83 29 37 93 24 18 37 17

122 161 115 48 176 142 136 36 159 173 86 170 93 123 121 61 106 74 98 74 130 150 85 85 103 62 92 178 111 15 135 40 143 143 91 80 75 14 174 180 57 103 78 92 103 99 111 80 27 36 91 22 17 36 16

Children with Pregnant fever receiving women receiving ODA any antimalarial two doses of disbursements treatment (% of intermittent for malaria children under preventive control age 5 with fever) treatment (%) ($ millions) b b 2000–10 2000–09 2009 2010

29.3 54.0 .. 48.0 17.2 57.8 .. 57.0 35.7 62.7 39.1 48.0 36.0 48.6 13.1 9.5 .. 63.0 43.0 73.9 51.2 23.2 .. 67.2 19.7 30.9 31.7 20.7 .. 36.7 20.3 33.0 49.1 10.8 8.4 9.1 .. 30.1 7.9 .. 35.8 0.6 59.1 33.8 59.6 34.0 23.6

2.5 3.0 .. 1.3 .. 5.8 .. 8.7 .. .. 5.1 .. 8.3 .. .. .. .. 32.5 43.7 2.9 7.4 15.0 .. 45.1 6.4 44.5 4.0 .. .. 43.1 10.0 0.3 4.9 17.0 59.8 52.2 .. 10.3 0.9 .. .. 0.5 30.2 18.1 16.2 60.3 6.3

.. 19.9 .. .. .. ..

.. 0.9 .. .. .. ..

.. .. .. .. .. ..

1,204.4 1,155.1 28.6 30.3 15.1 31.5 .. 0.0 21.8 51.3 7.6 22.0 9.6 2.1 .. .. 0.0 1.5 0.3 22.7 0.2 4.3 87.5 70.2 0.0 12.1 16.2 58.4 3.4 5.4 0.6 21.6 137.3 56.1 3.9 0.9 6.0 9.0 43.5 71.1 0.0 12.5 1.6 7.0 73.5 71.8 0.0 .. 13.0 21.1 26.7 86.3 20.4 29.4 14.7 17.6 0.0 0.5 .. .. 26.6 47.3 3.8 1.2 19.5 9.9 318.3 59.3 62.6 33.2 0.0 1.1 27.1 17.5 .. .. 4.9 8.5 1.2 5.2 0.0 .. 13.3 33.1 2.6 1.4 96.4 96.0 0.3 8.5 54.4 54.9 24.9 20.5 1.8 21.0 0.2 0.1 .. .. 0.2 0.1 .. .. .. .. .. .. .. ..

a. Malaria cases reported before 2000 can be probable and confirmed or only confirmed, depending on the country. b. Data are for the most recent year available during the period specified.

116

Part III. Development outcomes

MALARIA

Capable states and partnership

Table

12.1

Aid and debt relief

From all donors 2009 2010

44,070 239 682 279 1,083 561 648 196 242 561 50 2,357 283 2,402 31 144 3,819 77 127 1,582 214 147 1,776 122 513 444 771 984 373 155 2,012 326 469 1,657 934 31 1,016 23 448 662 1,075 2,351 56 2,933 499 1,785 1,267 736 3,159 319 167 999 41 930 503

44,589 238 689 156 1,062 630 541 328 261 486 67 3,543 1,312 845 85 161 3,525 104 120 1,693 218 139 1,629 256 1,419 470 1,023 1,089 374 125 1,952 256 745 2,062 1,032 49 928 56 467 498 1,031 2,076 91 2,958 419 1,723 914 732 2,730 198 132 592 9 993 550

Net official development assistance and official aid ($ millions) From DAC donors From non-DAC donors 2009 2010 2009 2010

22,564 131 326 223 453 264 268 162 99 356 28 1,099 226 1,721 25 43 1,817 53 22 821 171 51 1,224 71 341 242 435 575 122 64 1,288 247 255 688 520 20 514 12 196 500 861 1,911 19 1,409 362 1,013 701 620 1,965 200 98 580 32 705 350

23,912 150 339 106 456 283 266 248 113 285 22 2,387 1,215 438 79 34 1,927 84 33 900 92 54 1,159 94 703 214 517 684 106 58 1,357 211 381 849 548 33 534 29 200 308 822 1,509 31 1,655 253 1,033 593 521 1,579 143 99 366 17 599 355

191 10 3 0 2 0 1 0 1 0 1 3 0 2 0 15 20 0 1 6 -4 1 5 5 1 2 4 2 21 -2 2 1 2 2 3 0 5 0 0 10 3 61 -1 -1 1 4 2 0 42 12 11 122 1 -98 -6

248 3 1 0 5 0 0 -1 1 -1 16 8 1 2 0 20 35 0 1 4 -2 1 5 3 2 9 2 0 18 -2 4 1 3 3 2 .. 14 17 1 8 2 50 1 5 1 4 0 -2 100 -2 8 79 1 11 3

From multilateral donors 2009 2010

16,387 98 353 56 628 297 380 34 143 205 21 1,255 57 678 6 86 1,983 25 105 755 47 95 547 47 171 201 332 408 231 93 723 78 212 967 411 11 497 11 252 152 211 379 38 1,526 136 768 564 115 951 107 58 296 8 323 159

16,376 85 349 51 598 347 274 81 148 202 28 1,147 96 406 6 105 1,562 20 85 789 128 85 464 159 715 246 504 404 250 69 590 44 361 1,210 482 16 379 10 266 181 207 487 60 1,298 165 686 321 209 795 57 25 148 -10 382 192 (continued)

CAPABLE STATES AND PARTNERSHIP

Part III. Development outcomes

117

Capable states and partnership

Table

12.1

Aid and debt relief (continued) Net ODA private aid ($ millions)

From all donors

From DAC donors

Net ODA aid

From non-DAC donors

2009

2010

2009

2010

2009

10,992 3,957 -35 96 2 -27 41 17 6 20 -6 -29 160 -1,889 404 4 241 -294 11 345 -11 -12 595 -3 915 270 39 -26 50 1,628 43 307 17 2,299 81 3 292 39 12 6 1,247 16 -3 204 -86 98 -13 -95 10,730 2,917 50 5,601 1,157 792 54

19,305 289 24 84 9 64 -340 -28 -10 -21 1 -760 -32 -74 42 -1 108 457 -2 720 -10 7 -12 -4 890 104 42 -42 -48 4,029 847 -398 -64 -366 -35 -4 1 124 -13 -16 2,237 29 -6 94 -24 66 45 30 6,727 530 -49 4,896 -437 2,167 -533

10,980 3,957 -35 96 2 -27 41 17 6 20 -6 -29 160 -1,889 404 4 240 -294 11 345 -11 -12 595 -3 915 270 39 -27 50 1,628 43 307 17 2,299 81 3 292 39 12 6 1,247 5 -3 204 -86 98 -13 -95 10,653 2,915 50 5,566 1,119 790 53

19,275 289 24 84 9 64 -340 -28 -10 -21 1 -760 -32 -74 42 -1 108 457 -2 719 -10 7 -12 -4 890 104 42 -42 -48 4,029 847 -398 -64 -366 -35 -4 -19 124 -13 -16 2,229 29 -6 94 -24 66 45 30 6,685 529 -49 4,880 -447 2,160 -540

12 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1 .. .. 0 .. .. .. .. .. .. .. 0 .. .. .. .. 0 .. .. .. 0 0 .. .. 0 11 .. .. .. .. .. .. 78 2 .. 35 38 2 1

Share of GDP (%)

Per capita ($)

Share of gross capital formation (%)

2010

2009

2010

2009

2010

2009

2010

30 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1 .. .. .. .. .. .. .. 0 .. .. 0 .. .. .. 1 .. 20 .. .. .. 8 0 .. .. .. .. .. .. 42 1 .. 16 10 7 8

4.6 0.3 10.4 2.4 13.0 30.9 2.9 12.2 12.2 7.9 9.4 21.0 3.0 10.4 0.3 7.7 12.0 0.7 13.0 6.1 5.2 17.6 5.8 7.2 58.3 5.2 16.3 11.0 12.3 1.8 20.8 3.7 8.9 1.0 17.8 15.5 8.0 2.7 24.2 .. 0.4 4.3 1.9 13.7 15.8 11.3 9.9 12.6 0.6 0.2 15.9 0.5 0.1 1.0 1.2

4.0 0.3 10.5 1.1 12.0 31.1 2.4 19.8 13.2 5.7 12.4 27.0 10.9 3.7 0.6 7.6 11.9 0.8 11.5 5.3 4.6 16.7 5.1 11.8 143.7 5.4 20.2 11.6 10.4 1.3 21.2 2.3 13.8 1.1 18.4 24.5 7.2 5.8 24.5 .. 0.3 3.1 2.5 12.9 13.2 10.0 5.7 9.8 0.5 0.1 .. 0.3 .. 1.1 1.2

53.51 12.86 79.29 140.88 67.74 68.7 33.81 397.87 56.05 51.27 70.48 36.71 71.87 124.11 46.23 28.19 47.04 52.26 75.8 66.39 21.96 98.75 45.01 56.95 133.62 22.06 53.41 66.02 110.57 121.54 88.04 145.19 31.34 10.73 90.54 187.74 83.94 260.72 78.1 72.55 21.79 71.3 53.69 67.39 84.47 55.14 99.58 59.02 19.28 9.12 191.16 12.53 6.56 29.39 48.16

52.8 12.48 77.87 77.8 64.51 75.15 27.58 661.07 59.31 43.29 91.49 53.71 324.58 42.81 120.95 30.56 42.5 69.08 69.54 69.39 21.81 91.95 40.2 118.01 355.34 22.69 68.64 70.83 108.22 97.8 83.43 112.31 48 13.02 97.16 298.07 74.61 647.67 79.56 53.32 20.61 61.77 86.64 65.97 69.49 51.56 70.74 58.26 16.41 5.59 148.8 7.3 1.34 31.06 52.17

23.6 2.1 41.0 7.6 .. 164.3 .. 31.3 113.6 24.2 76.0 73.3 13.1 91.8 0.6 .. 53.2 2.6 72.1 26.6 24.2 .. 29.9 25.5 237.0 15.9 65.6 .. 40.3 8.3 100.4 13.0 .. .. 82.3 .. 28.5 12.3 156.8 .. 2.0 17.1 17.2 47.4 87.6 46.8 44.7 581.5 1.8 0.5 .. 2.8 .. 2.9 4.7

20.8 2.3 40.3 3.6 .. 172.6 .. 42.2 .. 17.4 .. .. 53.3 26.8 2.1 .. 55.2 3.0 59.0 19.6 23.0 .. 26.2 42.0 416.4 .. 81.7 .. 37.9 5.4 85.9 9.0 .. .. 87.4 .. 24.9 .. 155.1 .. 1.5 13.3 22.3 44.7 69.9 42.7 25.2 329.9 1.5 0.3 .. 1.4 .. 3.1 4.7

a. As of end-July 2011.

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Net ODA aid

Share of imports of goods and services (%)

Food aid shipments (thousands of tonnes)

Share of central government expenditures (%)

Cereal

Non-cereal

2009

2010

2009

2010

2009

2010

2009

2010

11.6 0.5 29.5 5.2 53.2 104.3 9.3 16.9 .. .. .. .. .. 24.2 .. .. 42.0 .. 35.2 13.8 13.6 47.9 15.4 5.4 27.7 .. 34.8 29.6 .. 2.8 40.9 5.9 17.7 2.6 61.0 29.1 18.1 1.9 65.8 .. 1.2 18.5 2.0 37.1 28.1 31.0 27.9 .. 1.7 0.6 28.1 1.8 0.1 2.3 2.2

9.8 0.5 .. 2.5 .. 101.8 8.0 27.5 .. .. .. .. .. .. .. .. 35.3 .. 36.4 11.7 11.5 .. 11.8 9.0 78.6 .. .. .. .. 2.0 39.7 4.0 .. 2.2 60.8 36.3 .. 4.5 49.8 .. 0.9 15.1 3.0 31.6 .. 25.6 13.0 .. 1.3 0.4 26.5 0.9 0.0 2.4 2.1

.. .. 68.1 .. 102.5 .. .. 44.8 .. .. .. 111.8 .. 58.5 .. .. .. .. .. 33.8 .. .. 27.8 .. .. .. .. 74.9 .. 8.1 .. .. .. .. .. .. .. 9.1 104.5 .. 1.2 .. .. .. 100.5 86.8 56.5 .. .. 0.9 .. 1.8 .. 3.7 4.3

.. .. 69.5 .. 99.3 .. .. .. .. .. .. 196.3 .. .. .. .. .. .. .. .. .. .. 22.6 .. .. .. .. .. .. 5.7 .. .. .. .. .. .. .. 18.9 .. .. .. .. .. .. 91.6 .. 32.9 .. .. .. .. 1.0 .. 3.6 4.6

3,305 0 17 0 22 48 9 18 17 100 8 151 4 30 0 0 1,036 0 2 38 11 2 217 6 22 21 91 23 28 0 166 0 41 0 22 5 14 0 15 318 0 433 2 24 25 121 12 185 33 12 21 1 .. 0 0

3,262 4 18 0 40 31 14 16 8 108 0 165 7 21 0 0 1,364 0 18 7 4 4 240 6 25 21 35 19 37 0 78 1 154 0 7 3 23 0 22 71 0 473 17 37 2 77 6 79 30 19 8 3 .. 0 0

469 0 2 0 6 15 1 1 5 10 0 39 3 4 0 0 85 0 2 1 4 0 53 1 4 2 6 7 2 0 3 0 7 0 7 0 5 0 2 44 0 79 0 5 0 16 4 44 12 9 2 1 .. 0 0

103 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 41 0 5 0 0 3 1 0 3 5 3 6 2 0 0 0 1 0 0 0 18 0 1 1 0 3 0 0 0 1 0 4 0 0 0 0 .. 0 0

CAPABLE STATES AND PARTNERSHIP

Heavily Indebted Poor Countries (HIPC) Debt Initiative

Decision pointa

In nominal terms Debt service Assistance Total HIPC delivered and MDRI relief Completion committed under MDRI assistance ($ millions)a ($ millions)a ($ millions)a pointa

.. 1,136 .. 1,217 102 1,285 .. 301 .. .. 1,051 204 .. .. .. 3,280 .. 383 3,868 .. 146 .. .. 266 2,393 1,577 1,992 883 .. 2,032 .. 1,062 .. 512 69 2,470 .. 665 .. .. .. .. 3,810 713 3,493 2,747 ..

.. 1,596 .. 2,147 1,468 6,202 .. 1,105 260 136 16,273 1,941 3,415 .. .. 6,555 .. 495 7,368 800 790 .. .. 4,866 4,293 3,205 2,887 1,983 .. 6,332 .. 2,252 .. 1,827 333 3,320 .. 1,659 .. .. .. .. 6,810 360 5,443 6,647 ..

.. .. .. .. .. ..

Part III. Development outcomes

119

Capable states and partnership

Table

12.2

Status of Paris Declaration indicators PDI-1

SUB-SAHARAN AFRICA Angolad Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep.d Côte d'Ivoired Equatorial Guinead Eritread Ethiopia Gabon Gambia, The Ghana Guinead Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritiusd Mozambique Namibia Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychellesd Sierra Leone Somaliad South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwed NORTH AFRICA Algeriad Djiboutid Egypt, Arab Rep. Libyad Morocco Tunisiad

PDI-2

PDI-3

Operational national development strategiesa 2010

Reliable public financial managementb 2010

.. B B C D C D D D D D .. .. .. .. B D C B .. D B C D D B C C .. B C C B A D C .. C .. B B D A B B B ..

.. 3.5 .. 4.5 3.0 3.0 4.0 3.0 2.0 2.0 2.5 .. .. .. .. 3.5 .. 3.5 3.5 .. 2.5 3.5 3.5 2.5 2.5 3.0 3.5 3.0 .. 4.0 .. 3.5 3.0 4.0 3.0 3.5 .. 3.5 .. .. 2.0 .. 3.5 3.0 3.5 3.5 ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. C .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

.. 43 63 84 52 84 51 0 43 97 53 .. .. .. .. 48 92 33 93 .. 39 72 66 5 46 90 66 .. .. 90 43 85 .. 71 91 67 .. 52 .. 0 35 .. 92 89 96 52 ..

.. 82 65 49 53 34 40 83 90 54 34 .. .. .. .. 86 50 68 59 .. 82 42 96 77 82 66 62 72 .. 28 48 55 80 92 73 80 .. 86 .. 88 78 83 26 37 76 79 ..

.. 29 65 53 23 11 29 29 7 15 13 .. .. .. .. 69 32 12 60 .. 15 58 38 42 12 66 32 31 .. 47 9 29 33 50 7 29 .. 37 .. 25 14 4 79 54 66 52 ..

.. 40 53 60 31 23 79 29 5 30 9 .. .. .. .. 55 30 33 56 .. 8 38 42 32 13 62 36 34 .. 56 14 23 36 64 43 38 .. 21 .. 30 8 12 72 47 43 54 ..

.. .. B .. .. ..

.. .. .. .. .. ..

.. .. 24 .. 98 ..

.. .. 78 .. 81 ..

.. .. 49 .. 86 ..

.. .. 56 .. 71 ..

Reliable country procurement systemsc 2007

Government budget estimates comprehensive and realistic (%) 2010

PDI-4 PDI-5 Technical Aid for government Aid for government assistance aligned sectors uses country sectors uses and coordinated public financial of country with country management procurement programs (%) systems (%) systems (%) 2010 2010 2010

Note: See technical notes for further details. PDI is a Paris Declaration Indicator. 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.

120

Part III. Development outcomes

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PDI-6 Project implementation units parallel to country structures (number) 2010

PDI-8

PDI-9

Aid disbursements on schedule and recorded by government (%) 2010

Bilateral aid that is untied (%) 2010

Aid provided in the framework of program-based approaches (%) 2010

Donor missions coordinated (%) 2010

Country analysis coordinated (%) 2010

.. 40 53 60 31 23 79 29 5 30 9 .. .. .. .. 55 30 33 56 .. 8 38 42 32 13 62 36 34 .. 56 14 23 36 64 43 38 .. 21 .. 30 8 12 72 47 43 54 ..

.. 18 0 75 48 36 55 0 84 11 59 .. .. .. .. 86 28 8 67 .. 22 45 25 2 59 96 34 .. .. 84 0 72 92 74 71 62 .. 58 .. 93 36 94 97 46 74 0 ..

.. 97 95 98 90 95 41 91 80 100 93 .. .. .. .. 86 100 55 92 .. 86 90 96 92 92 88 88 55 .. 90 99 84 100 97 90 95 .. 94 .. 99 88 92 96 98 95 98 ..

.. 50 12 50 49 28 33 0 11 19 37 .. .. .. .. 61 18 12 57 .. 31 36 43 12 9 51 44 27 .. 51 14 41 47 67 17 42 .. 34 .. 61 1 25 60 35 49 45 ..

.. 19 5 18 14 12 21 26 12 9 22 .. .. .. .. 25 12 8 15 .. 17 28 12 12 7 22 17 23 .. 15 17 3 11 44 13 25 .. 14 .. 52 12 18 26 12 24 27 ..

.. 61 62 48 33 40 48 26 41 20 36 .. .. .. .. 52 46 54 42 .. 44 56 54 43 29 51 40 50 .. 35 60 34 26 82 33 54 .. 34 .. 39 38 23 48 43 56 50 ..

.. D C C D B C C D D C .. .. .. .. B D D C .. D B C C D C C C .. C C C C C D C .. C .. B C D B C C C ..

.. Yes No No No No No Yes No No No .. .. .. .. Yes No No Yes .. No No No No No Yes Yes No .. Yes No No No Yes No Yes .. No .. No No No Yes No Yes No ..

.. .. 56 .. 71

.. .. 69 .. 79

.. .. 82 .. 57

.. .. 49 .. 59

.. .. 20 .. 19

.. .. 38 .. 44

.. .. B .. ..

.. .. No .. Yes

PDI-7

CAPABLE STATES AND PARTNERSHIP

PDI-10

PDI-11 Existence of a monitorable performance assessment frameworka 2010

PDI-12 Existence of a mutual accountability review 2010

Part III. Development outcomes

121

Capable states and partnership

Table

12.3

Capable states Firms that believe the court system is fair, impartial, and uncorrupt (%) 2009–11b

Investment climate Viewed by firms as major or very severe constraints (% of firms) Crime, theft, Corruption and disorder b 2009–11 2009–11b

23.6 .. 6.4 .. .. .. .. 8.9 .. .. 33.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 15.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

75.6 .. 27.4 .. .. .. .. 41.4 .. .. 72.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 24.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

1.5 .. 1.5 .. .. .. .. 25.6 .. .. 1.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

.. .. .. .. .. ..

Number of procedures 2011

655 1,011 795 625 446 832 800 425 660 743 506 610 560 770 553 405 620 1,070 434 487 276 1,715 465 785 1,280 871 312 620 370 645 730 270 545 457 230 1,185 780 915 515 .. 600 810 972 462 588 490 471 410 788 630 1,225 1,010 .. 510 565

Enforcing contracts Time required (days) 2011

50 44 65 28 82 39 47 20 82 46 89 152 53 42 19 23 15 34 38 23 45 25 47 20 35 42 94 52 23 17 143 36 60 32 79 51 27 15 150 .. 33 20 56 14 48 45 39 113 26 22 34 26 .. 25 22

Cost (% of claim) 2011

a. Average of the disclosure, director liability, and shareholder suits indexes. b. Data are for the most recent year available during the period speciﬁed.

122

Part III. Development outcomes

CAPABLE STATES AND PARTNERSHIP

Regulation and tax administration

Disclosure index 2011

5 5 6 7 6 8 6 1 6 6 6 3 6 6 6 4 4 6 2 7 6 6 3 2 4 5 4 6 5 6 5 5 6 5 7 3 6 4 6 .. 8 0 2 3 6 2 3 8 6 6 5 8 .. 7 5

Protecting investors (0 least desirable to 10 most desirable) Director liability Shareholder Investor protection index suits index indexa 2011 2011 2011

4 6 1 8 1 6 1 5 1 1 1 3 1 1 1 5 4 1 1 5 1 1 2 1 1 6 7 1 3 8 4 5 1 7 9 1 1 8 7 .. 8 6 5 4 1 5 6 1 4 6 2 3 .. 2 7

CAPABLE STATES AND PARTNERSHIP

5 6 3 3 4 4 6 6 5 3 5 4 3 3 4 5 5 3 5 6 1 5 10 8 6 6 5 4 3 9 9 6 3 5 3 6 2 5 6 .. 8 4 6 8 4 5 7 4 4 4 0 5 .. 6 6

Number of tax payments 2011

Time required to prepare, file, and pay taxes (hours) 2011

37 31 55 19 46 24 44 41 54 54 20 32 61 62 46 18 19 26 50 33 56 46 41 21 33 23 19 59 37 7 37 37 41 35 18 42 59 21 29 .. 9 42 33 48 53 32 37 49 24 29 35 29 .. 17 8

Total tax rate (% of profit) 2011

57.09 53.2 66.0 19.4 43.6 46.2 49.1 37.8 54.6 65.4 217.9 339.7 65.9 44.3 46.0 84.5 31.1 43.5 283.5 33.6 54.3 45.9 49.6 16.0 43.7 36.6 28.2 51.8 68.3 25.0 34.3 9.8 43.8 32.7 31.3 32.5 46.0 32.2 32.1 .. 33.1 36.1 36.8 45.5 49.5 35.7 14.5 35.6 53.4 72.0 38.7 43.6 .. 49.6 62.9

Extractive Industries Transparency Initiative status 2011

Candidate Candidate Compliant Candidate Candidate Candidate Candidate

Candidate Compliant Candidate

Compliant Suspended Compliant Compliant Candidate Compliant Compliant

Candidate

Candidate Candidate Candidate

Part III. Development outcomes

123

Capable states and partnership

Table

12.4

Governance and anticorruption indicators Governance indicatorsa

Voice and accountability 1996 2010

Political stability and absence of violence 1996 2010

Government effectiveness 1996 2010

Regulatory quality 1996 2010

Rule of law 1996 2010

Control of corruption 1996 2010

-1.6 0.1 0.9 -0.8 -1.6 -1.0 0.7 -0.9 -1.0 -0.7 -1.7 -1.0 -0.6 -1.5 -1.5 -1.1 -0.3 -1.3 -0.4 -1.4 -1.1 -0.6 -0.7 -1.5 -0.3 -0.2 -0.1 -0.5 0.8 -0.3 0.4 -1.7 -1.7 -1.5 0.0 0.0 0.0 -0.7 -2.1 0.8 -1.9 -1.3 -0.7 -1.0 -0.9 -0.4 -0.7

-1.1 0.3 0.4 -0.2 -0.9 -1.1 0.9 -1.1 -1.4 -0.4 -1.4 -1.0 -1.1 -1.9 -2.2 -1.3 -0.9 -1.1 0.5 -0.9 -0.9 -0.2 -0.2 -0.2 -0.8 -0.2 0.2 -0.9 0.7 -0.1 0.3 -0.6 -0.8 -1.3 0.1 -0.3 0.1 -0.2 -2.0 0.5 -1.7 -1.3 -0.1 -1.0 -0.5 -0.3 -1.5

-2.1 1.0 0.9 -0.4 -2.3 -1.1 1.0 -1.2 -1.0 0.4 -2.8 -1.3 -0.1 -0.3 -0.9 -1.0 0.0 0.4 -0.3 -1.2 -1.6 -0.8 0.2 -2.6 0.1 -0.5 0.3 0.3 0.9 -0.2 0.7 -0.2 -1.2 -2.1 1.0 -0.7 1.0 -2.0 -2.7 -0.5 -2.5 -0.1 -0.7 -0.5 -1.6 -0.2 -0.5

-0.2 0.3 0.9 -0.1 -1.5 -0.6 0.8 -2.1 -1.5 -0.4 -2.2 -0.2 -1.6 0.2 -0.9 -1.7 0.2 0.1 0.0 -1.8 -0.8 -1.2 0.5 -0.5 -1.1 0.1 -0.3 -1.3 0.5 0.3 0.8 -1.1 -2.0 -0.1 0.1 -0.4 0.8 -0.2 -3.1 0.0 -2.7 -0.1 0.0 -0.2 -1.1 0.5 -1.2

-0.8 -0.4 0.5 -1.0 -1.7 -1.0 .. -1.5 -0.7 -1.7 -1.7 -1.2 -0.1 -1.1 -1.2 -1.3 -0.3 -0.6 -0.1 -1.2 -1.5 -0.3 -0.1 -1.9 -0.6 -0.5 -1.2 -0.1 0.3 -0.1 0.5 -1.2 -1.0 -1.2 -0.4 0.0 0.6 -1.5 -2.1 0.9 -1.1 -0.7 -0.7 -0.8 -0.7 -1.1 -0.2

-1.1 -0.5 0.5 -0.6 -1.1 -0.9 -0.1 -1.4 -1.5 -1.7 -1.7 -1.2 -1.3 -1.7 -1.4 -0.3 -0.9 -0.7 0.0 -1.1 -1.0 -0.5 -0.4 -1.2 -0.8 -0.4 -0.9 -0.9 0.8 -0.5 0.1 -0.7 -1.2 -0.1 -0.7 -0.5 0.2 -1.2 -2.2 0.3 -1.4 -0.5 -0.5 -1.4 -0.6 -0.8 -1.6

-1.5 -0.2 0.7 -0.3 -1.7 -1.1 -0.6 -0.9 -1.3 -1.2 -1.8 -1.3 -0.5 -1.6 -1.2 -1.3 0.1 -0.9 -0.4 -0.7 -0.8 -0.4 -0.4 -2.0 -1.0 -0.3 -0.5 -0.5 0.0 -0.5 0.4 -1.1 -0.8 -1.5 -0.7 -0.2 0.3 -1.6 -2.5 0.4 -1.4 -0.2 -0.4 -0.4 0.2 -0.4 -1.0

-1.0 -0.3 0.5 -0.1 -1.1 -0.7 -0.1 -1.1 -1.1 -1.5 -1.6 -1.3 -0.9 -1.4 -2.2 -0.9 -0.6 -0.4 0.1 -1.1 -1.1 -0.1 -0.6 -1.1 -0.6 -0.6 -0.5 -0.8 0.8 -0.4 0.1 -0.5 -0.8 -0.2 -0.8 -0.3 -0.6 -0.7 -2.4 0.4 -1.4 -0.6 -0.4 -0.9 -0.1 -0.5 -2.0

-1.6 -0.1 0.5 -0.9 -1.5 -1.4 0.5 -1.5 -0.9 -1.1 -1.9 -1.5 -0.8 -1.0 -0.3 -0.8 -0.5 0.1 -0.3 -1.5 -2.1 -1.0 0.1 -2.2 -0.6 -0.4 -0.5 -0.3 0.9 -0.8 0.3 -1.0 -1.2 -1.5 0.2 -0.2 1.0 -1.5 -2.3 0.0 -1.6 -0.6 -0.2 -0.7 -0.6 -0.6 -0.7

-1.2 -0.7 0.7 -0.2 -1.2 -1.0 0.4 -1.3 -1.5 -1.1 -1.6 -1.1 -1.2 -1.3 -1.3 -0.8 -0.5 -0.5 -0.1 -1.5 -1.4 -1.0 -0.3 -1.0 -0.8 -0.1 -0.5 -0.9 0.8 -0.5 0.2 -0.6 -1.2 -0.3 -0.7 -0.4 0.0 -0.9 -2.4 0.1 -1.3 -0.5 -0.5 -0.9 -0.4 -0.5 -1.8

-1.2 -0.9 0.6 0.2 -1.4 -1.2 .. -1.4 -0.9 -0.9 -2.1 -1.1 0.2 -1.3 0.4 -1.2 -1.0 -0.4 -0.2 -0.5 -1.1 -1.0 -0.5 -1.7 0.2 -0.2 -0.4 0.0 0.5 -0.4 0.7 -1.1 -1.2 -0.9 0.0 -0.2 0.9 -0.8 -1.7 0.8 -1.3 0.0 -1.0 -0.8 -0.6 -1.0 -0.3

-1.3 -0.8 1.0 -0.4 -1.1 -1.0 0.8 -0.8 -1.3 -0.7 -1.4 -1.1 -1.1 -1.5 -0.5 -0.7 -0.8 -0.6 0.1 -1.2 -1.1 -0.9 0.2 -0.5 -0.3 -0.4 -0.7 -0.7 0.7 -0.4 0.3 -0.7 -1.0 0.5 -0.4 -0.7 0.3 -0.8 -1.7 0.1 -1.3 -0.2 -0.5 -1.0 -0.9 -0.6 -1.4

-1.3 -1.0 -0.7 -1.4 -0.4 -0.5

-1.0 -1.1 -1.2 -1.9 -0.8 -1.3

-2.0 -0.4 -0.6 -1.0 -0.3 0.1

-1.3 0.3 -0.9 -0.1 -0.5 0.1

-0.9 -0.9 -0.1 -0.9 0.0 0.4

-0.6 -1.0 -0.4 -1.2 -0.2 0.2

-0.8 -1.0 0.0 -1.8 -0.2 0.0

-1.1 -0.7 -0.2 -1.2 -0.1 0.0

-1.2 -0.8 0.1 -0.9 0.3 -0.1

-0.8 -0.7 -0.1 -1.0 -0.2 0.1

-0.5 -0.5 -0.1 -0.8 0.3 -0.2

-0.5 -0.3 -0.6 -1.3 -0.2 -0.1

a. The rating scale for each criterion varies from -2.5 (weak performance) to 2.5 (very high performance). b. A score of 81-100 indicates that a given country provides extensive information in its budget documents, a score of 61-80 indicates signiﬁcant information, 41-60 indicates some information, 21-40 indicates minimal information, and zero-20 indicates scant or no information. In 2008, based on inputs received, the International Budget Partnership (IBP) made three changes in the methodology applied to its Open Budget Survey, which is the basis for the Open Budget Index (OBI). c. Data are for the most recent year available during the period speciﬁed.

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Share of firms (%) Expected to pay informal payment to public officials to get things done 2010–11c

Expected to give gifts to obtain an operating license 2010–11c

Expected to give gifts in meetings with tax officials 2010–11c

Expected to give gifts to secure a government contract 2010–11c

Identifying corruption as a major constraint 2010–11c

48.9 .. 7.3 .. .. .. .. 41.8 .. .. 65.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 19.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

39.0 .. 2.9 .. .. .. .. 5.8 .. .. 53.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 42.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

34.2 .. 8.4 .. .. .. .. 16.8 .. .. 54.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 20.2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

58.5 .. 1.0 .. .. .. .. 40.8 .. .. 75.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 22.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

75.6 .. 27.4 .. .. .. .. 41.4 .. .. 72.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 24.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

1.9 2.8 5.8 3.1 1.8 2.2 5.1 2.1 1.7 2.1 2.0 2.1 2.2 1.9 2.6 2.7 2.8 3.2 4.1 2.0 2.1 2.1 3.5 3.3 2.6 3.4 2.7 2.3 5.4 2.7 4.4 2.6 2.4 4.0 3.0 2.9 4.8 2.4 1.1 4.5 1.6 3.2 2.7 2.4 2.5 3.0 2.4

2.0 3.0 6.1 3.0 1.9 2.5 5.5 2.2 2.0 2.4 2.0 2.2 2.2 1.9 2.5 2.7 3.0 3.5 3.9 2.1 2.2 2.2 3.5 3.2 3.0 3.0 2.8 2.4 5.1 2.7 4.4 2.5 2.4 5.0 3.0 2.9 4.8 2.5 1.0 4.1 1.6 3.1 3.0 2.4 2.4 3.2 2.2

3.0 .. 62.0 14.0 .. 5.0 .. .. 7.0 .. 0.0 .. .. .. 0.0 .. .. .. .. 49.0 .. .. 57.0 .. 2.0 .. 28.0 .. .. .. .. 47.0 26.0 19.0 0.0 0.0 3.0 .. .. .. 87.0 0.0 .. 35.0 .. 51.0 47.0

26.0 .. 51.0 5.0 .. 2.0 .. .. 0.4 .. 6.0 .. .. 0.0 .. .. .. .. 54.0 .. .. 49.0 .. 40.0 .. 47.0 35.0 .. .. 28.0 53.0 3.0 18.0 11.0 0.0 3.0 .. .. .. 92.0 8.0 .. 45.0 .. 55.0 36.0 ..

.. .. .. .. .. ..

2.9 3.2 3.1 2.2 3.4 4.3

2.9 3.0 2.9 2.0 3.4 3.8

.. 1.0 43.0 .. 27.0 ..

1.0 .. 49.0 .. 28.0 ..

CAPABLE STATES AND PARTNERSHIP

Mean corruption perceptions index score (0 low to 10 high) 2010 2011

Open Budget Index overall scoreb 2008 2011

Part III. Development outcomes

125

Capable states and partnership

Table

12.5

Country Policy and Institutional Assessment ratings

CPIA overall rating (IDA resource allocation index)a 2009 2011

SUB-SAHARAN AFRICA Angola Benin Botswanac Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Equatorial Guineac Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibiac Niger Nigeria Rwanda São Tomé and Príncipe Senegal Seychelles Sierra Leone Somaliad South Africac Sudan Swazilandc Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeriac Djibouti Egypt, Arab Rep.c Libyac Moroccoc Tunisiac

126

Averageb 2009

2011

Economic management Macroeconomic management Fiscal policy 2009 2011 2009 2011

Debt policy 2009 2011

3.2 2.8 3.5 .. 3.8 3.1 3.2 4.2 2.6 2.5 2.5 2.7 2.8 2.8 .. 2.2 3.4 .. 3.3 3.8 2.8 2.6 3.7 3.5 2.8 3.5 3.4 3.7 3.2 .. 3.7 .. 3.3 3.5 3.8 2.9 3.7 .. 3.2 .. .. 2.5 .. 3.8 2.8 3.9 3.4 1.9

3.2 2.7 3.5 .. 3.8 3.1 3.2 4.0 2.8 2.4 2.7 2.7 3.0 2.9 .. 2.2 3.5 .. 3.5 3.9 2.9 2.8 3.8 3.4 3.0 3.2 3.3 3.6 3.2 .. 3.7 .. 3.4 3.4 3.8 3.1 3.8 .. 3.3 .. .. 2.4 .. 3.7 3.0 3.8 3.5 2.2

3.4 3.0 3.7 .. 4.3 3.3 3.7 4.5 3.0 2.5 2.3 3.2 3.0 2.8 .. 1.8 3.7 .. 3.5 3.7 2.3 2.2 4.2 4.0 3.2 3.7 3.2 4.3 3.2 .. 4.5 .. 3.8 4.3 3.8 2.8 4.0 .. 3.7 .. .. 2.7 .. 4.3 2.8 4.5 3.5 1.7

3.4 3.0 3.5 .. 4.2 3.2 3.7 3.8 3.3 2.5 2.5 3.2 3.5 2.8 .. 1.8 3.7 .. 3.5 3.8 2.8 3.0 4.2 3.7 3.5 3.5 3.2 4.2 3.3 .. 4.5 .. 3.8 4.0 3.8 2.8 4.0 .. 3.7 .. .. 2.3 .. 4.2 3.2 4.2 3.7 1.8

3.6 3.0 4.0 .. 4.5 3.5 4.0 4.5 3.5 2.5 3.0 3.5 3.5 3.5 .. 2.0 3.5 .. 4.0 3.5 2.5 2.5 4.5 4.0 3.5 4.0 3.0 4.5 3.5 .. 4.5 .. 4.0 4.0 4.0 3.0 4.0 .. 4.0 .. .. 3.5 .. 4.5 3.0 4.5 4.0 2.0

3.6 3.0 4.0 .. 4.5 3.5 4.0 4.0 3.5 2.5 3.0 3.5 3.5 3.5 .. 2.0 3.0 .. 4.0 4.0 3.0 3.5 4.0 4.0 3.5 3.5 2.5 4.5 3.5 .. 4.5 .. 4.0 4.0 4.0 3.0 4.0 .. 4.0 .. .. 3.0 .. 4.5 3.5 4.0 4.0 2.0

3.4 3.0 3.5 .. 4.5 3.5 4.0 4.5 3.0 2.5 2.0 3.5 3.0 2.5 .. 2.0 4.0 .. 3.5 3.5 2.5 2.5 4.0 4.0 3.5 3.0 3.5 4.0 2.5 .. 4.5 .. 3.5 4.5 4.0 3.0 4.0 .. 3.5 .. .. 3.0 .. 4.5 3.0 4.5 3.0 2.0

3.4 3.0 3.0 .. 4.0 3.5 3.5 4.0 3.5 2.5 2.5 3.5 3.5 3.0 .. 2.0 4.0 .. 3.5 3.5 3.0 3.0 4.0 3.0 3.5 3.0 3.5 4.0 3.5 .. 4.5 .. 3.5 4.0 4.0 3.0 4.0 .. 3.5 .. .. 2.5 .. 4.0 3.0 4.0 3.5 2.0

3.2 3.0 3.5 .. 4.0 3.0 3.0 4.5 2.5 2.5 2.0 2.5 2.5 2.5 .. 1.5 3.5 .. 3.0 4.0 2.0 1.5 4.0 4.0 2.5 4.0 3.0 4.5 3.5 .. 4.5 .. 4.0 4.5 3.5 2.5 4.0 .. 3.5 .. .. 1.5 .. 4.0 2.5 4.5 3.5 1.0

3.3 3.0 3.5 .. 4.0 2.5 3.5 3.5 3.0 2.5 2.0 2.5 3.5 2.0 .. 1.5 4.0 .. 3.0 4.0 2.5 2.5 4.5 4.0 3.5 4.0 3.5 4.0 3.0 .. 4.5 .. 4.0 4.0 3.5 2.5 4.0 .. 3.5 .. .. 1.5 .. 4.0 3.0 4.5 3.5 1.5

.. 3.2 .. .. .. ..

.. .. .. .. .. ..

.. 3.0 .. .. .. ..

.. .. .. .. .. ..

.. 3.5 .. .. .. ..

.. .. .. .. .. ..

.. 3.0 .. .. .. ..

.. .. .. .. .. ..

.. 2.5 .. .. .. ..

.. .. .. .. .. ..

Part III. Development outcomes

CAPABLE STATES AND PARTNERSHIP

Structural policies Averageb

Trade

Financial sector 2009 2011

Business regulatory environment 2009 2011

2009

2011

2009

2011

3.2 2.8 3.7 .. 3.5 3.0 3.2 3.8 2.7 2.8 2.7 2.5 3.0 3.3 .. 1.5 3.2 .. 3.3 4.0 3.3 3.2 4.0 3.3 2.8 3.5 3.5 3.5 3.3 .. 3.7 .. 3.3 3.5 3.8 3.0 3.8 .. 3.2 .. .. 2.7 .. 3.8 3.2 3.8 3.5 2.2

3.2 2.7 3.7 .. 3.5 3.2 3.2 4.0 2.5 2.5 3.0 2.5 3.0 3.3 .. 1.5 3.2 .. 3.7 4.2 3.0 3.0 4.0 3.2 2.8 3.3 3.0 3.5 3.2 .. 3.5 .. 3.2 3.5 3.8 3.2 4.0 .. 3.2 .. .. 2.5 .. 3.8 3.0 4.0 3.7 2.3

3.7 4.0 4.0 .. 4.0 4.0 3.5 4.0 3.5 3.0 3.0 3.5 3.5 4.0 .. 1.5 3.0 .. 3.5 4.0 4.0 4.0 4.0 3.5 3.0 4.0 4.0 4.0 4.0 .. 4.5 .. 4.0 3.5 4.0 4.0 4.0 .. 3.5 .. .. 2.5 .. 4.0 4.0 4.0 4.0 3.0

3.6 3.5 4.0 .. 4.0 4.0 3.5 4.5 3.0 3.0 3.5 3.0 3.5 4.0 .. 1.5 3.0 .. 4.0 4.0 4.0 4.0 4.0 3.5 3.0 4.0 3.0 4.0 4.0 .. 4.0 .. 3.5 3.5 4.0 4.0 4.5 .. 3.5 .. .. 2.5 .. 4.0 4.0 4.5 4.0 3.0

3.0 2.5 3.5 .. 3.0 2.5 3.0 4.0 2.5 3.0 2.5 2.0 3.0 3.0 .. 1.0 3.0 .. 3.0 4.0 3.0 3.0 4.0 3.5 2.5 3.0 3.0 3.0 2.5 .. 3.5 .. 3.0 3.5 3.5 2.5 3.5 .. 3.0 .. .. 2.5 .. 4.0 2.5 3.5 3.5 1.5

3.0 2.5 3.5 .. 3.0 2.5 3.0 4.0 2.5 2.5 3.0 2.0 3.0 3.0 .. 1.0 3.0 .. 3.5 4.0 2.5 2.5 4.0 3.0 2.5 3.0 3.0 3.0 2.5 .. 3.5 .. 3.0 3.5 3.5 2.5 3.5 .. 3.0 .. .. 2.5 .. 4.0 2.5 3.5 3.5 2.0

3.1 2.0 3.5 .. 3.5 2.5 3.0 3.5 2.0 2.5 2.5 2.0 2.5 3.0 .. 2.0 3.5 .. 3.5 4.0 3.0 2.5 4.0 3.0 3.0 3.5 3.5 3.5 3.5 .. 3.0 .. 3.0 3.5 4.0 2.5 4.0 .. 3.0 .. .. 3.0 .. 3.5 3.0 4.0 3.0 2.0

3.0 2.0 3.5 .. 3.5 3.0 3.0 3.5 2.0 2.0 2.5 2.5 2.5 3.0 .. 2.0 3.5 .. 3.5 4.5 2.5 2.5 4.0 3.0 3.0 3.0 3.0 3.5 3.0 .. 3.0 .. 3.0 3.5 4.0 3.0 4.0 .. 3.0 .. .. 2.5 .. 3.5 2.5 4.0 3.5 2.0

.. 3.7 .. .. .. ..

.. .. .. .. .. ..

.. 4.0 .. .. .. ..

.. .. .. .. .. ..

.. 3.5 .. .. .. ..

.. .. .. .. .. ..

.. 3.5 .. .. .. ..

.. .. .. .. .. ..

CAPABLE STATES AND PARTNERSHIP

Part III. Development outcomes

127

Capable states and partnership

Table

12.5

Country Policy and Institutional Assessment ratings (continued)

Policies for social inclusion/equity

Averageb 2009 2011

Gender equality 2009 2011

Equity of public resource use 2009 2011

Building human resources 2009 2011

Social protection and labor 2009 2011

Policies and institutions for environmental sustainability 2009 2011

3.1 2.9 3.3 .. 3.6 3.3 3.1 4.3 2.5 2.4 2.6 2.8 2.7 2.4 .. 2.8 3.6 .. 3.3 3.9 3.0 2.5 3.5 3.3 2.5 3.6 3.5 3.4 3.4 .. 3.3 .. 3.1 3.2 3.9 2.8 3.4 .. 3.1 .. .. 2.3 .. 3.7 2.7 3.8 3.5 1.6

3.2 3.5 3.5 .. 3.5 4.0 3.0 4.5 2.5 2.5 2.5 2.5 3.0 2.5 .. 3.5 3.0 .. 3.5 4.0 3.0 2.5 3.5 4.0 3.0 3.5 3.5 3.5 4.0 .. 3.5 .. 2.5 3.0 4.0 3.0 3.5 .. 3.0 .. .. 2.5 .. 3.5 3.0 3.5 3.0 3.0

3.2 3.5 3.5 .. 3.5 4.0 3.0 4.5 2.5 2.5 3.0 2.5 3.0 2.5 .. 3.5 3.0 .. 3.5 4.0 3.5 2.5 3.0 4.0 2.5 3.5 3.5 3.5 4.0 .. 3.5 .. 2.5 3.0 3.5 3.0 3.5 .. 3.0 .. .. 2.0 .. 3.5 3.0 3.5 3.5 2.5

3.2 3.5 3.5 .. 3.5 4.0 3.0 4.5 2.5 2.5 2.5 2.5 3.0 2.5 .. 3.5 3.0 .. 3.5 4.0 3.0 2.5 3.5 4.0 3.0 3.5 3.5 3.5 4.0 .. 3.5 .. 2.5 3.0 4.0 3.0 3.5 .. 3.0 .. .. 2.5 .. 3.5 3.0 3.5 3.0 3.0

3.2 2.5 3.0 .. 4.0 3.5 3.0 4.5 2.5 2.5 2.5 3.0 2.5 2.0 .. 2.5 4.5 .. 3.5 4.0 3.0 3.0 3.5 3.0 3.0 4.0 3.5 3.5 3.5 .. 3.5 .. 3.5 3.5 4.5 3.0 3.5 .. 3.0 .. .. 2.5 .. 4.0 2.0 4.0 3.5 1.5

3.3 2.5 3.5 .. 4.0 3.5 3.0 4.0 3.0 2.5 2.5 3.0 2.5 2.5 .. 2.5 4.0 .. 4.0 3.5 3.0 3.0 4.0 3.0 4.0 4.0 3.5 4.0 3.5 .. 3.0 .. 4.0 3.5 4.5 3.0 3.5 .. 3.5 .. .. 2.5 .. 4.0 3.0 4.0 3.5 2.0

3.3 2.5 3.5 .. 3.5 3.0 3.5 4.5 2.5 2.5 3.0 3.0 3.0 2.5 .. 3.5 4.0 .. 3.5 4.5 3.0 2.0 4.0 3.5 2.5 3.5 3.5 3.5 3.5 .. 3.5 .. 3.5 3.0 4.5 3.0 3.5 .. 3.5 .. .. 2.5 .. 4.0 3.0 4.0 4.0 1.0

3.4 3.0 3.5 .. 3.5 3.5 3.0 4.5 2.5 2.5 3.0 3.5 3.5 3.0 .. 3.5 4.5 .. 4.0 4.5 3.5 2.5 4.0 3.5 2.5 3.0 3.5 3.5 3.5 .. 4.0 .. 3.5 3.0 4.5 3.5 4.0 .. 3.5 .. .. 2.5 .. 3.5 3.5 4.0 4.0 2.0

3.0 3.0 3.0 .. 3.5 3.0 3.0 4.5 2.0 2.5 2.5 3.0 2.5 2.5 .. 2.5 3.5 .. 2.5 3.5 3.0 2.5 3.5 3.0 2.5 3.5 3.5 3.5 3.0 .. 3.0 .. 3.0 3.5 3.5 2.5 3.0 .. 3.5 .. .. 2.5 .. 3.5 3.0 3.5 3.0 1.0

3.0 2.5 3.0 .. 3.5 3.0 3.0 4.5 2.0 2.5 3.0 2.5 2.5 2.5 .. 2.0 3.5 .. 2.5 4.0 3.0 2.5 3.5 3.0 2.5 2.5 3.5 3.5 2.5 .. 3.0 .. 3.0 3.5 3.5 2.5 3.0 .. 3.5 .. .. 2.5 .. 3.5 3.0 3.5 3.0 2.0

2.9 3.0 3.5 .. 3.5 3.0 3.0 3.5 3.0 2.0 2.0 2.5 2.5 2.5 .. 2.0 3.0 .. 3.5 3.5 2.5 2.5 3.5 3.0 2.0 3.5 3.5 3.0 3.0 .. 3.0 .. 3.0 3.0 3.5 2.5 3.5 .. 2.5 .. .. 2.0 .. 3.5 2.5 4.0 3.5 2.0

3.1 2.5 3.5 .. 4.0 3.0 3.0 3.5 3.0 2.5 2.5 2.5 3.0 2.5 .. 2.0 3.5 .. 3.5 3.5 2.5 3.0 3.5 3.5 3.0 3.5 4.0 3.5 3.0 .. 3.0 .. 4.0 3.5 3.5 3.5 3.5 .. 3.0 .. .. 2.0 .. 3.0 2.5 3.5 3.5 3.0

.. 3.2 .. .. .. ..

.. .. .. .. .. ..

.. 3.0 .. .. .. ..

.. .. .. .. .. ..

.. 3.0 .. .. .. ..

.. .. .. .. .. ..

.. 3.5 .. .. .. ..

.. .. .. .. .. ..

.. 3.0 .. .. .. ..

.. .. .. .. .. ..

.. 3.5 .. .. .. ..

.. .. .. .. .. ..

Note: The rating scale for each indicator ranges from 1 (low) to 6 (high). 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.

128

Part III. Development outcomes

CAPABLE STATES AND PARTNERSHIP

Public sector management and institutions

Averageb

Property rights and rule-based governance 2009 2011

Quality of budgetary and financial management 2009 2011

Efficiency of revenue mobilization 2009 2011

Quality of public administration 2009 2011

Transparency, accountability, and corruption in public sector 2009 2011

2009

2011

3.0 2.4 3.3 .. 3.7 2.6 2.9 4.0 2.4 2.2 2.4 2.2 2.6 2.6 .. 2.7 3.2 .. 2.9 3.8 2.6 2.6 3.3 3.4 2.8 3.3 3.4 3.4 3.0 .. 3.4 .. 3.1 2.9 3.5 3.1 3.4 .. 2.9 .. .. 2.2 .. 3.5 2.4 3.3 3.2 2.0

3.0 2.3 3.3 .. 3.7 2.7 2.9 4.0 2.6 2.2 2.4 2.2 2.6 2.7 .. 2.6 3.3 .. 3.2 3.7 2.6 2.6 3.3 3.5 2.8 2.8 3.3 3.3 3.0 .. 3.4 .. 3.2 2.9 3.6 3.1 3.6 .. 3.1 .. .. 2.2 .. 3.3 2.8 3.2 3.1 2.2

2.8 2.0 3.0 .. 3.5 2.5 2.5 4.0 2.0 2.0 2.5 2.0 2.5 2.0 .. 2.5 3.0 .. 3.0 3.5 2.0 2.5 2.5 3.5 2.5 3.5 3.5 3.5 3.0 .. 3.0 .. 3.0 2.5 3.0 2.5 3.5 .. 2.5 .. .. 2.0 .. 3.5 2.5 3.5 3.0 1.5

2.8 2.0 3.0 .. 3.5 2.5 2.5 4.0 2.0 2.0 2.5 2.0 2.5 2.0 .. 2.5 3.0 .. 3.0 3.5 2.0 2.5 2.5 3.5 2.5 3.0 3.5 3.0 3.0 .. 3.0 .. 3.0 2.5 3.5 2.5 3.5 .. 3.0 .. .. 2.0 .. 3.5 3.0 3.5 3.0 1.5

3.0 2.5 3.5 .. 4.5 3.0 3.0 4.0 2.5 2.0 2.0 2.5 2.5 2.5 .. 2.5 3.5 .. 3.0 3.5 3.0 2.5 3.5 3.0 2.5 3.0 3.0 3.5 3.0 .. 4.0 .. 3.5 3.0 4.0 3.0 3.0 .. 3.5 .. .. 2.0 .. 3.5 2.5 4.0 3.5 2.0

3.1 2.5 3.5 .. 4.5 3.0 3.0 4.0 3.0 2.0 2.0 2.5 2.5 3.0 .. 2.0 3.5 .. 3.5 3.5 3.0 2.5 3.5 3.5 2.5 2.5 3.0 3.5 3.0 .. 4.0 .. 3.5 3.0 4.0 3.0 3.5 .. 3.5 .. .. 2.5 .. 3.0 3.0 3.5 3.5 2.5

3.4 2.5 3.5 .. 3.5 3.0 3.5 3.5 2.5 2.5 2.5 2.5 3.0 4.0 .. 3.5 3.5 .. 3.5 4.5 3.0 3.0 4.0 4.0 3.5 4.0 4.0 3.5 3.5 .. 4.0 .. 3.5 3.0 3.5 3.5 4.0 .. 2.5 .. .. 3.0 .. 4.0 3.0 3.5 3.5 3.5

3.4 2.5 3.5 .. 3.5 3.5 3.5 3.5 3.0 2.5 2.5 2.5 3.0 3.5 .. 3.5 3.5 .. 3.5 4.0 3.0 3.0 4.0 4.0 3.5 3.5 4.0 3.5 3.5 .. 4.0 .. 3.5 3.0 3.5 3.5 4.0 .. 3.0 .. .. 3.0 .. 4.0 3.0 3.5 3.5 3.5

2.9 2.5 3.0 .. 3.5 2.5 3.0 4.0 2.5 2.5 2.5 2.0 2.5 2.0 .. 3.0 3.5 .. 3.0 3.5 3.0 2.5 3.5 3.0 2.5 3.5 3.5 3.0 3.0 .. 3.0 .. 3.0 3.0 3.5 3.0 3.5 .. 3.0 .. .. 2.5 .. 3.5 2.0 3.0 3.0 1.5

2.9 2.0 3.0 .. 3.5 2.5 3.0 4.0 2.5 2.5 2.5 2.0 2.5 2.5 .. 3.0 3.5 .. 3.5 3.5 3.0 2.5 3.5 3.0 2.5 2.5 3.0 3.0 3.0 .. 3.0 .. 3.0 3.0 3.5 3.0 3.5 .. 3.0 .. .. 2.0 .. 3.0 2.5 3.0 3.0 2.0

2.7 2.5 3.5 .. 3.5 2.0 2.5 4.5 2.5 2.0 2.5 2.0 2.5 2.5 .. 2.0 2.5 .. 2.0 4.0 2.0 2.5 3.0 3.5 3.0 2.5 3.0 3.5 2.5 .. 3.0 .. 2.5 3.0 3.5 3.5 3.0 .. 3.0 .. .. 1.5 .. 3.0 2.0 2.5 3.0 1.5

2.8 2.5 3.5 .. 3.5 2.0 2.5 4.5 2.5 2.0 2.5 2.0 2.5 2.5 .. 2.0 3.0 .. 2.5 4.0 2.0 2.5 3.0 3.5 3.0 2.5 3.0 3.5 2.5 .. 3.0 .. 3.0 3.0 3.5 3.5 3.5 .. 3.0 .. .. 1.5 .. 3.0 2.5 2.5 2.5 1.5

.. 2.8 .. .. .. ..

.. .. .. .. .. ..

.. 2.5 .. .. .. ..

.. .. .. .. .. ..

.. 3.0 .. .. .. ..

.. .. .. .. .. ..

.. 3.5 .. .. .. ..

.. .. .. .. .. ..

.. 2.5 .. .. .. ..

.. .. .. .. .. ..

.. 2.5 .. .. .. ..

.. .. .. .. .. ..

CAPABLE STATES AND PARTNERSHIP

Part III. Development outcomes

129

Capable states and partnership

Table

12.6

130

Polity indicators

Revised combined polity score (–10 strongly autocratic to 10 strongly democratic) 1995 2000 2005 2010

Institutionalized democracy (0 low to 10 high) 1995 2000 2005 2010

-2.0 6.0 7.0 -5.0 0.0 -4.0 8.0 5.0 -4.0 0.0 0.0 5.0 -6.0 -5.0 -6.0 1.0 -4.0 -7.0 -1.0 -1.0 5.0 -5.0 8.0 0.0 9.0 6.0 7.0 -6.0 10.0 5.0 6.0 8.0 -6.0 -6.0 .. -1.0 .. -7.0 0.0 9.0 -7.0 -9.0 -1.0 -2.0 -4.0 6.0 -6.0

-3.0 6.0 8.0 -3.0 -1.0 -4.0 8.0 5.0 -2.0 -1.0 0.0 -6.0 4.0 -5.0 -6.0 1.0 -4.0 -5.0 2.0 -1.0 5.0 -2.0 4.0 0.0 7.0 6.0 6.0 -6.0 10.0 5.0 6.0 5.0 4.0 -4.0 .. 8.0 .. 0.0 0.0 9.0 -7.0 -9.0 -1.0 -2.0 -4.0 1.0 -3.0

-2.0 6.0 8.0 0.0 6.0 -4.0 10.0 -1.0 -2.0 6.0 4.0 -4.0 0.0 -5.0 -7.0 1.0 -4.0 -5.0 8.0 -1.0 6.0 8.0 8.0 5.0 7.0 6.0 7.0 -5.0 10.0 5.0 6.0 6.0 4.0 -3.0 .. 8.0 .. 5.0 0.0 9.0 -4.0 -9.0 -1.0 -4.0 -1.0 5.0 -4.0

-2.0 7.0 8.0 0.0 6.0 -4.0 10.0 -1.0 -2.0 9.0 5.0 -4.0 0.0 -5.0 -7.0 1.0 3.0 -5.0 8.0 5.0 6.0 8.0 8.0 6.0 0.0 6.0 7.0 -2.0 10.0 5.0 6.0 3.0 4.0 -4.0 .. 7.0 .. 7.0 0.0 9.0 -2.0 -9.0 -1.0 -2.0 -1.0 7.0 1.0

.. 6.0 7.0 0.0 .. 1.0 8.0 5.0 0.0 .. .. 6.0 0.0 0.0 0.0 3.0 0.0 0.0 1.0 1.0 5.0 0.0 8.0 .. 9.0 6.0 7.0 0.0 10.0 5.0 6.0 8.0 0.0 0.0 .. 2.0 .. 0.0 .. 9.0 0.0 0.0 2.0 1.0 0.0 6.0 0.0

1.0 6.0 8.0 0.0 1.0 1.0 8.0 5.0 1.0 1.0 .. 0.0 5.0 0.0 0.0 3.0 0.0 0.0 3.0 1.0 5.0 2.0 .. 3.0 7.0 6.0 6.0 0.0 10.0 5.0 6.0 6.0 4.0 0.0 .. 8.0 .. .. .. 9.0 0.0 0.0 2.0 1.0 0.0 3.0 1.0

2.0 6.0 8.0 2.0 7.0 1.0 10.0 1.0 1.0 6.0 .. 0.0 .. 0.0 0.0 3.0 0.0 0.0 8.0 1.0 6.0 8.0 8.0 .. 7.0 6.0 7.0 0.0 10.0 5.0 6.0 7.0 4.0 0.0 .. 8.0 .. 5.0 .. 9.0 0.0 0.0 2.0 1.0 1.0 5.0 1.0

2.0 7.0 8.0 2.0 7.0 1.0 10.0 1.0 1.0 9.0 6.0 0.0 .. 0.0 0.0 3.0 4.0 0.0 8.0 6.0 7.0 8.0 8.0 7.0 3.0 6.0 7.0 0.0 10.0 5.0 6.0 4.0 4.0 0.0 .. 7.0 .. 8.0 .. 9.0 1.0 0.0 2.0 1.0 1.0 7.0 3.0

.. 0.0 0.0 5.0 .. 5.0 0.0 0.0 4.0 .. .. 1.0 6.0 5.0 6.0 2.0 4.0 7.0 2.0 2.0 0.0 5.0 0.0 .. 0.0 0.0 0.0 6.0 0.0 0.0 0.0 0.0 6.0 6.0 .. 3.0 .. 7.0 .. 0.0 7.0 9.0 3.0 3.0 4.0 0.0 6.0

4.0 0.0 0.0 3.0 2.0 5.0 0.0 0.0 3.0 2.0 .. 6.0 1.0 5.0 6.0 2.0 4.0 5.0 1.0 2.0 0.0 4.0 .. 3.0 0.0 0.0 0.0 6.0 0.0 0.0 0.0 1.0 0.0 4.0 .. 0.0 .. .. .. 0.0 7.0 9.0 3.0 3.0 4.0 2.0 4.0

4.0 0.0 0.0 2.0 1.0 5.0 0.0 2.0 3.0 0.0 .. 4.0 .. 5.0 7.0 2.0 4.0 5.0 0.0 2.0 0.0 0.0 0.0 .. 0.0 0.0 0.0 5.0 0.0 0.0 0.0 1.0 0.0 3.0 .. 0.0 .. 0.0 .. 0.0 4.0 9.0 3.0 5.0 2.0 0.0 5.0

4.0 0.0 0.0 2.0 1.0 5.0 0.0 2.0 3.0 0.0 1.0 4.0 .. 5.0 7.0 2.0 1.0 5.0 0.0 1.0 1.0 0.0 0.0 1.0 3.0 0.0 0.0 2.0 0.0 0.0 0.0 1.0 0.0 4.0 .. 0.0 .. 1.0 .. 0.0 3.0 9.0 3.0 3.0 2.0 0.0 2.0

-3.0 -7.0 -6.0 -7.0 -7.0 -3.0

-3.0 2.0 -6.0 -7.0 -6.0 -3.0

2.0 2.0 -3.0 -7.0 -6.0 -4.0

1.0 0.0 0.0 0.0 0.0 1.0

1.0 3.0 0.0 0.0 0.0 1.0

3.0 3.0 1.0 0.0 0.0 1.0

4.0 7.0 6.0 7.0 7.0 4.0

4.0 1.0 6.0 7.0 6.0 4.0

1.0 1.0 4.0 7.0 6.0 5.0

Part III. Development outcomes

Institutionalized autocracy (0 low to 10 high) 1995 2000 2005 2010

CAPABLE STATES AND PARTNERSHIP

Technical notes 1. Basic indicators Table .. Basic indicators Population is total population based on the de facto definition of population, which counts all residents regardless of legal status or citizenship—except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. The values shown are midyear estimates. Population growth rate for year t is the exponential rate of growth of midyear population from year t–1 to t, expressed as a percentage. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship—except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of the country of origin. Land area is the land surface area of a country, excluding area under inland waters, national claims to continental shelf, and exclusive economic zones. Population density is midyear population divided by land area in square kilometers. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship— except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. Land area is a country’s total area, excluding area under inland waters, national claims to continental shelf, and exclusive economic zones. In most cases the definition of inland waters includes major rivers and lakes. Gross national income (GNI) per capita, World Bank Atlas method, is GNI, calculated using the World Bank Atlas method (see box

1), divided by midyear population. It is similar in concept to GNI per capita in current prices, except that the use of three-year averages of exchange rates smooths out sharp fluctuations from year to year. Gross domestic product (GDP) per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Dollar figures for GDP are converted from domestic currencies using single-year official exchange rates. For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used. Growth rates are in real terms and have been calculated by the least-squares method using constant 2000 exchange rates (box 2). Life expectancy at birth is the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to remain the same throughout its life. Under-five mortality rate is the probability that a newborn baby will die before reaching age 5, if subject to current age-specific mortality rates. The probability is expressed as a rate per 1,000. Gini index is the most commonly used measure of inequality. The coefficient ranges from 0, which reflects complete equality, to 100, which indicates complete inequality (one person has all the income or consumption, all others have none). Graphically, the Gini index can be easily represented by the area between the Lorenz curve and the line of equality. Technical notes

131

Box 2

Growth rates

Growth rates are calculated as annual averages and represented as percentages. Except where noted, growth rates of values are computed from constant price series. Rates of change from one period to the next are calculated as proportional changes from the earlier period. Least squares growth rates are used wherever there is a sufficiently long time series to permit a reliable calculation. No growth rate is calculated if more than half the observations in a period are missing. The least squares growth rate, r, is estimated by fitting a linear regression trend line to the logarithmic annual values of the variable in the relevant period. The regression equation takes the form ln Xt = a + bt

which is equivalent to the logarithmic transformation of the compound growth equation, X t = Xo(1 + r) 2 In this equation X is the variable, t is time, and a = lnXo and b = ln(1 + r) are parameters to be estimated. If b* is the least squares estimate of b, then the average annual growth rate, r, is obtained as [exp(b*) – 1] and is multiplied by 100 for expression as a percentage. The calculated growth rate is an average rate that is representative of the available observations over the entire period. It does not necessarily match the actual growth rate between any two periods.

Adult literacy rate is the percentage of adults ages 15 and older who can, with understanding, read and write a short, simple statement on their everyday life. Net official development assistance per capita is calculated by dividing net disbursements of loans and grants from all official sources on concessional financial terms by midyear population. This indicator shows the importance of aid flows in sustaining per capita income and consumption levels, although exchange rate fluctuations, the actual rise of aid flows, and other factors vary across countries and over time. Regional aggregates for GNI per capita, GDP per capita, life expectancy at birth, and adult literacy rates are weighted by population. Source: Data on population and life expectancy are from the (1) United Nations Population Division: World Population Prospects, (2) United Nations Statistical Division: Population and Vital Statistics Report (various years), (3) Census reports and other statistical publications from national statistical offices, (4) Eurostat: Demographic Statistics, (5) Secretariat of the Pacific Community: Statistics and Demography Programme, and (6) U.S. Census Bureau: International Database. Data on land are from Food and Agriculture Organization electronic files and website. Data on GNI per capita and GDP per capita are from World Bank national accounts data and Organisation for Economic Co-operation and Development (OECD) national accounts data files. Data on under-five mortality are from the Inter-agency Group for Child Mortality Estimation Level & Trends in Child 132

Africa Development Indicators 2012/13

Mortality: Report 2010. Data on Gini index for developing countries are from the World Bank Development Research Group and are based on primary household survey data obtained from government statistical agencies and World Bank country departments (http://iresearch.worldbank.org/PovcalNet/ index.htm) and for high-income economies are from the Luxembourg Income Study database. Data on literacy are from United Nations Educational, Scientific and Cultural Organization Institute for Statistics. Data on aid flows are from the OECD Geographic Distribution of Aid Flows to Developing Countries (www.oecd.org/dac/stats/idsonline). 2. National and fiscal accounts Africa Development Indicators uses the 1993 System of National Accounts (1993 SNA) to compile national accounts data since 2001 (see Primary Data Documentation for details). Although more countries are adopting the 1993 SNA, many still follow the 1968 SNA, and some low-income countries use concepts from the 1953 SNA. Reporting periods: For most economies the fiscal year is concurrent with the calendar year. However, there are few countries whose ending date reported is for the fiscal year of the central government, though fiscal years for other government levels and reporting years for statistical surveys may differ. Reporting end dates are as follows for the following countries: Botswana (June 30), Egypt (June 30), Ethiopia (July 7), The Gambia (June 30), Kenya (June 30), Lesotho (March 31), Malawi (March 31), Namibia (March 31), Sierra Leone (June 30), South Africa (March

31), Swaziland (March 31), Uganda (June 30), and Zimbabwe (June 30). The reporting period for national accounts data is either calendar year or fiscal year. Most economies report national accounts and balance of payments data using calendar years, but some report on fiscal years. Fiscal year data are assigned to calendar year that contains the larger share of the fiscal year. If a country’s fiscal year ends before June 30, data are shown in that first year of the fiscal year; if the fiscal year ends on or after June 30, data are shown in the second year if the period. Balance of payments data are reported by calendar year. Revisions to national accounts data: National accounts data are revised by national statistical offices when methodologies change or data sources improve. This in turn means that Africa Development Indicators national accounts data are also revised when data sources change. • Botswana: The Central Statistical Office has revised national accounts series for 2004 onward. • Mauritania: Based on official government statistics, data have been revised for 1991 onward; the new base year for constant price series is 2004. • Swaziland: The Central Statistical Office has revised national accounts series for 1990 onward. • Tunisia: Based on data from the Central Bank and its Statistical Bulletin, national accounts have been revised from 1997 onward. • Uganda: The Bureau of Statistics has revised national accounts series for 1998 onward; the new base year for constant price series is 2001/02. National currencies: As of January 2009, multiple hard currencies such as rand, pound sterling, euro, and U.S. dollar are in use in Zimbabwe; however, data are reported in U.S. dollars, the most frequently used currency. Table .. Gross domestic product, nominal Gross domestic product (GDP), nominal, is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation

of natural resources. GDP figures are shown at market prices (also known as purchaser values) and converted from domestic currencies using single-year official exchange rates. For the few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used. The sum of the components of GDP by industrial origin (presented here as value added) will not normally equal total GDP for several reasons. First, components of GDP by expenditure are individually rescaled and summed to provide a partially rebased series for total GDP. Second, total GDP is shown at purchaser value, while value-added components are conventionally reported at producer prices. As explained above, purchaser values exclude net indirect taxes, while producer prices include indirect taxes. Third, certain items, such as imputed bank charges, are added in total GDP. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross domestic product, real Gross domestic product (GDP), real, is obtained by converting national currency GDP series to U.S. dollars using constant 2000 exchange rates. For countries where the official exchange rate does not effectively reflect the rate applied to actual foreign exchange transactions, an alternative currency conversion factor has been used. Growth rates are in real terms and calculated by the least-squares method using constant 2000 exchange rates (see box 2). Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross domestic product growth Gross domestic product (GDP) growth is the average annual growth rate of real GDP (table 2.2) at market prices based on constant local currency. Aggregates are based on constant 2000 U.S. dollars. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Technical notes

133

Table .. Gross domestic product per capita, real Gross domestic product (GDP) per capita, real, is calculated by dividing real GDP (table 2.2) by corresponding midyear population. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross domestic product per capita growth Gross domestic product (GDP) per capita growth is the average annual growth rate of real GDP per capita (table 2.4). Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross national income, nominal Gross national income (GNI), nominal, is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are converted from national currency in current prices to U.S. dollars at official annual exchange rates. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table 2.7. Gross national income, World Bank Atlas method Gross national income (GNI), World Bank Atlas method, (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, the World Bank Atlas method 134

Africa Development Indicators 2012/13

(see box 1) of conversion is used. This method applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for the difference between the rate of inflation in the country and that in Japan, the United Kingdom, the United States, and the euro area. Growth rates are calculated by the leastsquares method (see box 2). Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross national income per capita, World Bank Atlas method Gross national income (GNI) per capita, World Bank Atlas method, is GNI, calculated using the World Bank Atlas method (see box 1), divided by midyear population. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross domestic product deflator (U.S. dollar series) Gross domestic product (GDP) deflator (U.S. dollar series) is nominal GDP in current U.S. dollars (table 2.1) divided by real GDP in constant 2000 U.S. dollars (table 2.2), expressed as an index with base year 2000. The series shows the effects of domestic price changes and exchange rate variations. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Consumer price index Consumer price index reflects changes in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used. Source: International Monetary Fund, International Financial Statistics database and data files. Table .. Inflation Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer

of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used. Source: International Monetary Fund, International Financial Statistics database and data files. Table .. Price indexes Inflation, GDP deflator, is measured by the annual growth rate of the GDP implicit deflator and shows the rate of price change in the economy as a whole. Consumer price index is a change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used. Exports of goods and services price index is calculated by dividing the national accounts exports of goods and services in current U.S. dollars by exports of goods and services in constant 2000 U.S. dollars. Imports of goods and services price index is calculated by dividing the national accounts imports of goods and services in current U.S. dollars by imports of goods and services in constant 2000 U.S. dollars. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross domestic savings Gross domestic savings is calculated by deducting total consumption (table 2.17) from nominal gross domestic product (table 2.1). For 1994–2000, Nigeria’s values were distorted because the official exchange rate used by the government for oil exports and oil value added was significantly overvalued. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross national savings Gross national savings is the sum of gross domestic savings (table 2.13), net factor income from abroad, and net private transfers from abroad. The estimate here also includes net public transfers from abroad. For 1994– 2000, Nigeria’s values were distorted because

the official exchange rate used by the Government for oil exports and oil value added was significantly overvalued. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. General government final consumption expenditure General government final consumption expenditure is all current expenditure for purchases of goods and services by all levels of government, including capital expenditure on national defense and security. Other capital expenditure by government is included in capital formation. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Household final consumption expenditure Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. It also includes payments and fees to governments to obtain permits and licenses. Here, household consumption expenditure includes the expenditures of nonprofit institutions serving households, even when reported separately by the country. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Final consumption expenditure plus discrepancy Final consumption expenditure plus discrepancy (formerly total consumption) is the sum of household final consumption expenditure (table 2.16) and general government final consumption expenditure (table 2.15) shown as a share of gross domestic product. This estimate includes any statistical discrepancy in the use of resources relative to the supply of resources. Private consumption, not separately shown here, is the value of all goods Technical notes

135

and services purchased or received as income in kind by households and nonproﬁt institutions. It excludes purchases of dwellings, but includes imputed rent for owner-occupied dwellings. In practice, it includes any statistical discrepancy in the use of resources.

Table .. Private sector fixed capital formation Private sector fixed capital formation covers gross outlays by the private sector (including private nonproﬁt agencies) on additions to its ﬁxed domestic assets.

Source: World Bank and Organisation for Economic Co-operation and Development national accounts data.

Table .. Final consumption expenditure plus discrepancy per capita Final consumption expenditure plus discrepancy per capita is ﬁnal consumption expenditure plus discrepancy in current U.S. dollars (table 2.17) divided by midyear population.

Table .. External trade balance (exports minus imports) External trade balance is the difference between free on board exports (table 2.23) and cost, insurance, and freight imports (table 2.24) of goods and services (or the difference between gross domestic savings and gross capital formation). The resource balance is shown as a share of nominal gross domestic product (table 2.1). For 1994–2000, Nigeria’s values were distorted because the official exchange rate used by the government for oil exports and oil value added was significantly overvalued.

Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross fixed capital formation Gross fixed capital formation (formerly gross domestic fixed investment) includes land improvements (fences, ditches, drains, and so on); plant, machinery, and equipment purchases; and the construction of roads, railways, and the like, including schools, oﬃces, hospitals, private residential dwellings, and commercial and industrial buildings. According to the 1993 SNA, net acquisitions of valuables are also considered capital formation. It comprises outlays by the public sector (table 2.20) and the private sector (table 2.21). Examples include improvements in land, dwellings, machinery, and other equipment. For some countries the sum of gross private investment and gross public investment does not total gross domestic investment due to statistical discrepancies. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Gross general government fixed capital formation Gross general government fixed capital formation covers gross outlays by the public sector on additions to its ﬁxed domestic assets. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. 136

Africa Development Indicators 2012/13

Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Exports of goods and services, nominal Exports of goods and services, nominal, represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, ﬁnancial, information, business, personal, and government services. They exclude labor and property income (formerly called factor services) as well as transfer payments, and are expressed in current U.S. dollars. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Imports of goods and services, nominal Imports of goods and services, nominal, represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise,

freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude labor and property income (formerly called factor services) as well as transfer payments, and are expressed in current U.S. dollars. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data. Table .. Exports of goods and services as a share of gdp Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude labor and property income (formerly called factor 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 national accounts data. Table .. Imports of goods and services as a share of gdp Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude labor and property income (formerly called factor 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 national accounts data. Table .. Balance of payments and current account Exports of goods and services represent the value of all goods and other market services

provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude labor and property income (formerly called factor services) as well as transfer payments, and are expressed in current U.S. dollars and as a proportion of real GDP. Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude labor and property income (formerly called factor services) as well as transfer payments, and are expressed in current U.S. dollars and as a proportion of real GDP. Total trade is the sum of exports and imports of goods and services. Net income is the receipts and payments of employee compensation paid to nonresident workers and investment income (receipts and payments on direct investment, portfolio investment, other investments, and receipts on reserve assets). Net current transfers are recorded in the balance of payments whenever an economy provides or receives goods, services, income, or financial items without a quid pro quo. Current account balance is the sum of net exports of goods, services, net income, and net current transfers. All transfers not considered to be capital are current. Total reserves including gold are the holdings of monetary gold, special drawing rights, reserves of International Monetary Fund (IMF) members held by the IMF, and holdings of foreign exchange under the control of monetary authorities. Source: Data on exports and imports of goods and services are from World Bank and Organisation for Economic Co-operation and Development national accounts data. Data on net income, net current transfers, current account balance, and total reserves are from the International Monetary Fund, Balance of Payments Statistics Yearbook and data files, and World Bank and OECD GDP estimates. Technical notes

137

Table .. Exchange rates and purchasing power parity Official exchange rate is the exchange rate determined by national authorities or the rate determined in the legally sanctioned exchange market. Purchasing power parity (PPP) conversion factor is the number of units of a country’s currency required to buy the same amount of goods and services in the domestic market as a U.S. dollar would buy in the United States. Ratio of PPP conversion factor to market exchange rate is the national price level, making it possible to compare the cost of the bundle of goods that make up gross domestic product across countries. Real effective exchange rate is the nominal eﬀective exchange rate (a measure of the value of a currency against a weighted average of several foreign currencies) divided by a price deﬂator or index of costs. Gross domestic product (GDP), PPP, is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Gross domestic product (GDP) per capita, PPP, is GDP per capita based on purchasing power parity. PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser’s prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Source: International Monetary Fund International Financial Statistics database. Data on PPP are from the World Bank’s International Comparison Program database. 138

Africa Development Indicators 2012/13

Table .. Agriculture value added Agriculture value added is the gross output of forestry, hunting, and fishing, as well as cultivation of crops and livestock production (International Standard Industrial Classification [ISIC] revision 3 divisions 1–5) less the value of their intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. For countries that report national accounts data at producer prices (Angola, Benin, Cape Verde, Comoros, the Republic of Congo, Côte d’Ivoire, Gabon, Liberia, Niger, Rwanda, São Tomé and Príncipe, Seychelles, and Togo), gross value added at market prices is used as the denominator. For countries that report national accounts data at basic prices (all other countries), gross value added at factor cost is used as the denominator. Value added at basic prices excludes net taxes on products, while producer prices include net taxes on products paid by produces but exclude sales or value added taxes. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data files. Table .. Industry value added Industry value added is the gross output of mining, manufacturing, construction, electricity, water, and gas (ISIC revision 3 divisions 10–45) less the value of their intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. For countries that report national accounts data at producer prices (Angola, Benin, Cape Verde, Comoros, the Republic of Congo, Côte d’Ivoire, Gabon, Liberia, Niger, Rwanda, São Tomé and Príncipe, Seychelles, and Togo), gross value added at market prices is used as the denominator. For countries that report national accounts data at basic prices (all other countries), gross value added at factor cost is used as the denominator. Value added at basic prices excludes net taxes on products, while producer prices include net taxes on products paid by produces but exclude sales or value added taxes. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data files.

Table .. Services plus discrepancy value added Services plus discrepancy value added is the gross output of all other branches of economic activity, including wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate services (ISIC revision 3 divisions 50–99) less the value of their intermediate inputs. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers as well as discrepancies arising from rescaling. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. For countries that report national accounts data at producer prices (Angola, Benin, Cape Verde, Comoros, the Republic of Congo, Côte d’Ivoire, Gabon, Liberia, Niger, Rwanda, São Tomé and Príncipe, Seychelles, and Togo), gross value added at market prices is used as the denominator. For countries that report national accounts data at basic prices (all other countries), gross value added at factor cost is used as the denominator. Value added at basic prices exclude net taxes on products while producer prices include net taxes on products paid by produces but exclude sales or value added taxes. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data files. Table .. Central government finances Revenue, excluding grants, is cash receipts from taxes, social contributions, and other revenues such as fines, fees, rent, and income from property or sales. Grants are also considered as revenue but are excluded here. Expense is cash payments for operating activities of the government in providing goods and services. It includes compensation of employees (such as wages and salaries), interest and subsidies, grants, social benefits, and other expenses such as rent and dividends. Cash surplus or deficit is revenue (including grants) minus expense, minus net acquisition of nonfinancial assets. In the 1986

Government Finance Statistics Manual nonfinancial assets were included under revenue and expenditure in gross terms. This cash surplus or deficit is closest to the earlier overall budget balance (still missing is lending minus repayments, which are now a financing item under net acquisition of financial assets). Net incurrence of liabilities is domestic financing (obtained from residents) and foreign financing (obtained from nonresidents) and/or the means by which a government provides financial resources to cover a budget deficit or allocates financial resources arising from a budget surplus. The net incurrence of liabilities should be offset by the net acquisition of financial assets (a third financing item). The difference between the cash surplus or deficit and the three financing items is the net change in the stock of cash. Total debt is the entire stock of direct government fixed-term contractual obligations to others outstanding on a particular date. It includes domestic and foreign liabilities such as currency and money deposits, securities other than shares, and loans. It is the gross amount of government liabilities reduced by the amount of equity and financial derivatives held by the government. Because debt is a stock rather than a flow, it is measured as of a given date, usually the last day of the fiscal year. Source: International Monetary Fund, Government Finance Statistics Yearbook and data files, and World Bank and Organisation for Economic Co-operation and Development GDP estimates. Table .. Central government expenses Goods and services include all government payments in exchange for goods and services used for the production of market and nonmarket goods and services. Own-account capital formation is excluded. Compensation of employees consists of all payments in cash, as well as in kind (such as food and housing), to employees in return for services rendered, and government contributions to social insurance schemes such as social security and pensions that provide benefits to employees. Interest payments (expense) include interest payments on government debt—including Technical notes

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long-term bonds, long-term loans, and other debt instruments—to domestic and foreign residents, expressed as a proportion of expense. Subsidies and other transfers include all unrequited, nonrepayable transfers on current account to private and public enterprises; grants to foreign governments, international organizations, and other government units; and social security, social assistance benefits, and employer social benefits in cash and in kind. Other expenses are spending on dividends, rent, and other miscellaneous expenses, including provision for consumption of fixed capital. Source: International Monetary Fund, Government Finance Statistics Yearbook and data files, and World Bank and Organisation for Economic Co-operation and Development GDP estimates. Table .. Central government revenues Interest payments (revenue) include interest payments on government debt—including long-term bonds, long-term loans, and other debt instruments—to domestic and foreign residents, expressed as a proportion of revenue. Taxes on income, profits, and capital gains are levied on the actual or presumptive net income of individuals, on the profits of corporations and enterprises, and on capital gains, whether realized or not, on land, securities, and other assets. Intragovernmental payments are eliminated in consolidation. Taxes on goods and services include general sales and turnover or value added taxes, selective excises on goods, selective taxes on services, taxes on the use of goods or property, taxes on extraction and production of minerals, and profits of fiscal monopolies. Taxes on international trade include import duties, export duties, profits of export or import monopolies, exchange profits, and exchange taxes. Other taxes include employer payroll or labor taxes, taxes on property, and taxes not allocable to other categories, such as penalties for late payment or nonpayment of taxes. Social contributions include social security contributions by employees, employers, and 140

Africa Development Indicators 2012/13

self-employed individuals, and other contributions whose source cannot be determined. They also include actual or imputed contributions to social insurance schemes operated by governments. Grants and other revenue include grants from other foreign governments, international organizations, and other government units; interest; dividends; rent; requited, nonrepayable receipts for public purposes (such as fines, administrative fees, and entrepreneurial income from government ownership of property); and voluntary, unrequited, nonrepayable receipts other than grants. Source: International Monetary Fund, Government Finance Statistics Yearbook and data files, and World Bank and Organisation for Economic Co-operation and Development GDP estimates. Table .. Structure of demand Household final consumption expenditure (formerly private consumption) is the market value of all goods and services, including durable products (such as cars, washing machines, and home computers), purchased by households. General government final consumption expenditure (formerly general government consumption) is all government current expenditures for purchases of goods and services. Gross fixed capital formation (formerly gross domestic investment) consists of outlays on additions to the fixed assets of the economy plus net changes in the level of inventories. Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude labor and property income (formerly called factor services) as well as transfer payments, and are expressed as a proportion of real GDP. Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication,

construction, financial, information, business, personal, and government services. They exclude labor and property income (formerly called factor services) as well as transfer payments and are expressed as a proportion of real GDP. Gross national savings is the gross national income less total consumption, plus net transfers. Source: World Bank and Organisation for Economic Co-operation and Development national accounts data files. 3. Millennium Development Goals Table .. Millennium Development Goal : eradicate extreme poverty and hunger Share of population below PPP $1.25 a day is the percentage of the population living on less than $1.25 a day at 2005 international prices. As a result of revisions in purchasing power parity (PPP) exchange rates, poverty rates in this edition cannot be compared with those in previous editions. Poverty gap ratio at PPP $1.25 a day is the mean shortfall from the poverty line (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. Share of population below PPP $2 a day is the percentage of the population living on less than $2 a day at 2005 international prices. As a result of revisions in PPP exchange rates, poverty rates in this edition cannot be compared with those in previous editions. Poverty gap ratio at PPP $2 a day is the mean shortfall from the poverty line (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. Share of population below national poverty line (poverty headcount ratio) is the percentage of the population living below the national poverty line. National estimates are based on population-weighted subgroup estimates from household surveys. Share of poorest quintile in national consumption or income is the share of consumption, or in some cases income, that accrues to the poorest 20 percent of the population.

Prevalence of child malnutrition, underweight, is the percentage of children under age 5 whose weight for age is more than two standard deviations below the median for the international reference population ages 0–59 months. The reference population, adopted by the World Health Organization in 1983, is based on children from the United States, who are assumed to be well nourished. Population below minimum dietary energy consumption (also referred to as prevalence of undernourishment) is the population whose dietary energy consumption is continuously below a minimum dietary energy requirement for maintaining a healthy life and carrying out a light physical activity with an acceptable minimum body weight for attained height. Source: Data on poverty are from the World Bank Development Research Group. Data are based on primary household survey data obtained from government statistical agencies and World Bank country departments (http://iresearch.worldbank. org/PovcalNet/index.htm). Data on national poverty are from the Global Poverty Working Group and are based on World Bank country poverty assessments and country poverty reduction strategies. Data on child malnutrition are from the World Health Organization Global Database on Child Growth and Malnutrition. Data on population below minimum dietary energy consumption are from the Food and Agriculture Organization (http://www.fao.org/faostat/foodsecurity/ index_en.htm). Table .. Millennium Development Goal : achieve universal primary education Primary education provides children with basic reading, writing, and mathematics skills, along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music. Net primary enrollment ratio is the ratio of children of official primary school age, based on the International Standard Classification of Education 1997, who are enrolled in primary school to the population of the corresponding official primary school age. Primary completion rate is the percentage of students completing the last year of Technical notes

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Africa New Dollar Per Day (PPP) Poverty Estimates ($1.25/day) in 2008 Why PPP poverty estimates? When it comes to poverty measurement, each country calculates its own (national) poverty line and uses it to track progress in reducing poverty and setting social policy. National poverty lines may be obtained through a combination of methods: social norms about a minimum level of welfare each citizen is entitled to, some basic nutritional need, a multidimensional index, and so on. But if we need to obtain comparisons between countries of the world or countries in a region of the world (say, Africa), then the national poverty lines cannot be used because each country uses a different one. Therefore, the World Bank uses a common international poverty line to compare poverty across the world or in a region by collecting comparative price data and estimating purchasing power parities (PPPs) of the world economies. Using PPPs instead of country exchange rates to convert currencies allows welfare and the output of economies to be compared in real terms while controlling for differences in price levels. Traditionally, the World Bank counts the global (and/or regional) poor as the fraction of the population with incomes (or consumption) below two international poverty lines: $1.25/day and $2/day using PPP. The 2005 PPP revisions: In 2005, the World Bank undertook a major revision of the global poverty count by using a completely new set of international prices that became available through the worldwide effort of the International Comparison Program (ICP). The 2005 ICP round is widely considered to be better than the previous round of ICP in 1993, in that it covered more countries and collected more (and better quality) price data. As a result, the 2005 estimates differed significantly from the estimates based on the 1993 ICP round, which are then extrapolated forward. In particular, the 2005 revisions showed that the cost of livingâ&#x20AC;&#x201D;and, by consequence, povertyâ&#x20AC;&#x201D;was higher in the developing world than

Prepared by Andrew Dabalen and Rose Mungai

previously thought using the $1.25/day and $2/day international poverty lines. Why a 2008 PPP estimates? Every three years, the World Bank updates the global poverty count. On February 29, 2012, the World Bank released the 2008 global poverty estimates. These estimates have been revised for the period 1981â&#x20AC;&#x201C;2008 and may differ from previous estimates. To the extent possible, each global (or regional) poverty update would normally be based on the household surveys carried out in the year of the update. In practice, household surveys in many countries are not carried out every year so that the year of the update and the survey year may differ, sometimes by many years. When the survey year and the year of the update do not coincide, the international poverty line in local currency is projected backward or forward by adjusting the most recently available survey figure by the change in the CPI in the country. Benchmarking the 1990 poverty and global poverty trends: In addition to the three-year update, the latest release also revises the 1990 poverty count. The 1990 poverty estimate for the world and each country is an important benchmark to measure progress toward Millennium Development Goal 1 (MDG-1): reducing extreme poverty by half between 1990 and 2015. The current revision uses 2005 PPPs, projected backward or forward using the CPI in the country. Poverty in Africa is declining, but progress is slower than in other regions The new global estimates indicate a significant reduction in the proportion of world population below the $1.25 per day per capita poverty line, from 43.1 percent in 1990 to 22.4 percent in 2008 (table 1). Particularly, the East Asia and Pacific region made huge progress where the percentage of the poor, measured at the $1.25

Table 1: Regional aggregation, $1.25/day and $2.00/day poverty line The proportion of population below the international poverty lines (%)

Year 1990 1993 1996 1999 2002 2005 2008

All 43.1 41.0 34.8 34.1 30.8 25.1 22.4

1990 1993 1996 1999 2002 2005 2008

1908.5 1910.3 1703.8 1742.6 1639.2 1389.5 1289.0

East Asia and Pacific 56.2 50.7 35.9 35.6 27.6 17.1 14.3 926.4 870.8 639.7 655.6 523.1 332.1 284.4

$1.25 per day per capita $2 per day per capita Europe Latin Middle Europe Latin Middle and America East and SubEast Asia and America East and Central and the South North Saharan and Central and the North Asia Caribbean Africa Asia Africa All Pacific Asia Caribbean Africa 1.9 12.2 5.8 53.8 56.5 64.6 81.0 6.9 22.4 23.4 2.9 11.4 4.8 51.7 59.4 63.0 75.7 9.2 21.7 22.1 3.9 11.1 4.8 48.6 58.1 58.6 64.0 11.2 21.0 22.2 3.8 11.9 5.0 45.1 57.9 57.4 61.7 12.1 22.0 21.9 2.3 11.9 4.2 44.3 55.7 53.4 51.9 7.9 22.2 19.7 1.3 8.7 3.5 39.4 52.3 46.9 39.0 4.6 16.7 17.3 0.5 6.5 2.7 36.0 47.5 43.0 33.2 2.2 12.4 13.9 Population below the international poverty lines (millions) 8.9 53.4 13.0 617.3 289.7 2863.3 1333.5 31.9 97.6 52.8 13.7 52.5 11.5 631.9 330.0 2940.5 1300.3 43.0 99.9 53.4 18.2 53.6 12.3 630.8 349.2 2863.8 1139.5 52.7 101.7 57.0 17.8 60.1 13.6 619.5 376.0 2936.4 1137.2 57.0 111.3 59.7 10.6 62.7 12.0 640.5 390.2 2847.3 983.5 37.2 117.5 56.7 6.3 47.6 10.5 598.3 394.8 2594.4 756.9 21.6 91.7 52.6 2.2 36.9 8.6 570.9 386.0 2470.1 658.6 10.4 70.5 44.4

South Asia 83.6 82.6 80.7 77.8 77.4 73.3 70.9

SubSaharan Africa 75.9 78.1 77.5 77.4 76.1 74.1 69.2

958.5 1010.0 1047.0 1068.5 1119.2 1112.6 1124.2

389.1 433.9 465.8 502.7 533.2 558.9 562.1

Source: PovcalNet.

(continued)

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Africa Development Indicators 2012/13

Africa New Dollar Per Day (PPP) Poverty Estimates ($1.25/day) in 2008 (continued)

primary school. It is calculated as the total number of students in the last grade of primary school minus the number of repeaters in that grade divided by the total number of children of official graduation age. Share of cohort reaching grade 5 is the percentage of children enrolled in grade 1 of primary school who eventually reach grade 5. The estimate is based on the reconstructed cohort method. Youth literacy rate is the percentage of people ages 15–24 who can, with understanding, both read and write a short, simple statement about their everyday life. Source: Data are from the United Nations Educational, Scientific and Cultural Organization Institute for Statistics. Efforts have been made to harmonize these data series with those published on the United Nations Millennium Development Goals website (http://mdgs.un.org/unsd/mdg/default. aspx), but some differences in timing, sources, and definitions remain. Table .. Millennium Development Goal : promote gender equality and empower women Ratio of girls to boys in primary and secondary school is the ratio of female to male gross enrollment rate in primary and secondary school.

Poverty & Equity Data portal (http://povertydata.worldbank.org/ poverty/home/) uses the same data from Povcalnet and displays it in maps and charts at the regional and country levels. Both websites are updated periodically.

450

400 350

300

250

200 150

100

10 0

Number of poor (millions)

Figure 1

Headcount (%)

poverty line, declined from 56.2 percent to 14.3 percent between 1990 and 2008, while the number of poor people also declined from 926.4 million to 284.4 million for the same period. For the first time since 1993, the proportion of the people living below the international poverty lines in Africa (Figure 1 at right) is declining, based on existing data, although progress has been slower than in other regions. In addition, about 9 million Africans moved out of extreme poverty between 2005 and 2008. However, because of rapid population growth, the number of people living below the international poverty lines is higher in 2008 than in 1990. Where to obtain new estimates: The new poverty statistics based on international poverty lines are on the World Bank’s website Povcalnet (http://go.worldbank.org/WE8P1I8250), which allows users to compute poverty rates and populations, setting the poverty line at any level and following the same methodology as the World Bank estimates at the $1.25 and $2 poverty lines. The

50 1981

1984

1987 1990 1993 Headcount (%)

1996 1999 2002 2005 Num of poor (millions)

2008

Ratio of literate young women to men is the ratio of the female youth literacy rate to the male youth literacy rate. Women in national parliament are the percentage of parliamentary seats in a single or lower chamber occupied by women. Share of women employed in the nonagricultural sector is women wage employees in the nonagricultural sector as a share of total nonagricultural employment. Source: Data on net enrollment and literacy are from the United Nations Educational, Scientiﬁc and Cultural Organization Institute for Statistics. Data on women in national parliaments are from Inter-Parliamentary Union (IPU) (www.ipu.org). Data on women’s employment are from the International Labour Organization Key Indicators of the Labour Market database. Table .. Millennium Development Goal : reduce child mortality Under-five mortality rate is the probability that a newborn baby will die before reaching age 5, if subject to current age-speciﬁc mortality rates. The probability is expressed as a rate per 1,000. Infant mortality rate is the number of infants dying before reaching 1 year of age, per 1,000 live births. Child immunization rate, measles, is the percentage of children ages 12–23 months who Technical notes

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What’s the coolest region for doing impact evaluation? It’s Africa! Want to do IE? Come to Africa! The most recent count1 of active impact evaluations (IE) within the World Bank leaves no doubts: Africa is the place to be to do IE. The region had the highest number of active IEs in 2011 and the highest ratio of active IEs to active investment loans. However, it is not only about numbers. IEs in Africa are leading the way in at least three fronts: (1) IEs have generated knowledge on the effect of development policies and programs; (2) IEs are generating cross-sector evidence to understand the underlying behavioral and delivery mechanisms that make policies work; and (3) IE products and programs have been strengthening government capacity for IE evidence-based policy making. Impact Evaluations by Region Active IEs in 2010 vs 2011 by region

160 140

128

137

120 100 80

62 66

60 40

20 0

52 57

AFR

EAP

ECA Active in 2010

LAC

MENA

SAR

Active in 2011

Source: DIME Progress report FY10-11; AFR=Africa, EAP=East Asia Pacific, ECA=Europe Central Asia, LAC=Latin America and Caribbean, MENA=Middle East and North Africa, SAR=South Asia

IE programs More than half of all current IE activity within the World Bank is managed under impact evaluation programs. The programs help to maintain analytical quality of the activities they cover, take advantage of economies of scale in capacity development and dissemination of results, and use community of practice to encourage adoption and scale-up of good policies. The organization of IEs under thematic programs helps to maximize IE potential as a knowledge public good. The Development Impact Evaluation Initiative (DIME) Secretariat coordinates IE activities in 10 IE programs, 3 of which (education, HIV, and gender) are cosponsored by the Africa region, and 6 are cosponsored by networks or network units (FPD, adapt with ARD, local development and fragile states with SDV, malaria with HDNHE, and gender with PRMGE). A small program on urban and public sector governance (cosponsored by PREM and LEGJR) is also emerging in DIME. HDN coordinates IE activities in eight SIEF clusters (topics include active labor market policies, CCTs, ECD, and Result-based Financing in Health). WSS manages a program in the area of water supply and sanitation. The impact of Impact Evaluation The impact of IE affects the key stages of project design and implementation. First, IE researchers motivate the project team

to think about the mechanisms that induce behavioral responses or address principal agent problems. By introducing variation in treatment, the project incorporates a dynamic learning agenda and the ability to steer the project mid-course on the basis of good evidence. Second, IE data requirements provide for early planning of data collection rounds that will strengthen the M&E function and reporting of key indicators. Third, when the client is an integral part of designing and implementing the IE, the impact evaluation can have important effects on counterpart practices and decision making. These often transform line ministries’ ability to monitor programs, guide policy design, and encourage adoption and scale-up of successful interventions within a country and across other countries and global practices. Some examples of this follow. Bringing the problem of the commons into the design: Irrigation interventions hold tremendous potential to help farmers cope with increasing climate variability and to ensure food security in many poorer regions of the world. Yet improper management of irrigation schemes has led to numerous failures in this sector; empirical research in the field of water management is critical in responding to these operational challenges. DIME is taking principal agent theories to the field to support rigorous economic research on this topic in a variety of regions and contexts. By testing various institutional arrangements for water management, the IE is changing the way irrigation management will happen on the ground. In Ethiopia and Mozambique, tough questions about water management and maintenance will be tested by creating different leadership models for Water User Association groups, including one treatment arm that will reserve 30 percent of chairperson positions for women. Changing the way new policies are introduced: During a December 2008 workshop in Dakar, the Senegal HIV/AIDS agency revealed its plan for rolling out its new HIV prevention strategy (peer counseling) to replace the old strategy (social mobilization). During the clinic, the government decided to randomly phase in the new policy instead. This was instrumental in enabling DIME to measure the performance of the new strategy relative to the old. IE data collection helps build capacity: In the Central African Republic, as part of the community development IE, DIME is helping to build capacity in data collection and cleaning at the National Institute of Statistics. The IE data collection highlighted the institute’s weaknesses, which led to the preparation of a capacitybuilding plan to help it perform regular data collection. Making decisions on the basis of evidence: IE data and data analysis are used at various stages of the policy-making process to finetune interventions and to motivate adoption or scale-up. Baseline data can be used to fine-tune intervention. In The Gambia, the education IE baseline revealed pervasive school beating; this elicited a nationwide campaign against it. Later in the process, the results from experimental testing of alternative policy mechanisms led to changes in program design. In Zambia, the testing of alternative drug distribution systems led to the ongoing adaption of (continued)

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What’s the coolest region for doing impact evaluation? It’s Africa! (continued) the system that is better able to reduce drug attrition and secure effective delivery of drugs to frontline facilities. This will enable treatment of possibly hundreds of thousands of malaria cases. Finally, IE results are also used to motivate scale-up of policy at the national level. In Tanzania, the IE informed the scale-up of the CCT program as a pillar of the new safety-net strategy (0.2 percent of GDP per year) and provided guidance on the needed institutional adjustments and implementation arrangements. Mechanisms that make policies work A breathtaking evolution is taking place in the way impact evaluation is done. It is moving from the first-generation IE—focusing on showing whether interventions work, with less attention to the underlying channels—to Impact Evaluation 2.0, which focuses on generating cross-sector evidence to understand the underlying behavioral and delivery mechanisms that make policies work. Results from Africa point to the importance of mechanisms based on incentives for performance, timing, information and access, and accountability and collective action. Inputs for agricultural technology adoption: IDA clients are considering incentive schemes to improve the delivery of agricultural extension services at the community level. Increasing the supply of knowledge is among the main challenges, because extension workers rarely reach all villages; many countries have trained lead and peer farmers to disseminate information at the community level. Evidence from Malawi shows that incentives matter (Mobarak et al. 2012). Providing small in-kind incentives to peer and lead farmers results in a 12-percentage point increase in knowledge, which translates into a 3.6 percentage-point increase in adoption of new techniques. Furthermore, incentives have similar effects on the different types of lead/peer farmers. Incentivized women lead/peer farmers performed as well as men, fully offsetting the 11 percentage-point gender gap observed in the control group on farmers’ knowledge (or a 3 percentage-point gap in adoption). Similarly, incentives fully offset the poverty gradient in the control group: poor peer farmers receiving incentives increase farmers’ knowledge by 20 percentage points and adoption by 6 percentage points, while they have no significant impact in the treatment group. This evidence has motivated other countries, like Mozambique, to test similar interventions. Self-control and investment behavior: Results from an impact evaluation in Ghana (Fafchamps et al. 2011) comparing cash to in-kind grants for microenterprises showed in-kind grants having larger impacts on business profits. Whereas cash could be used for household consumption, in-kind grants commit business owners to channeling their grant to investment in their business. Similarly, a recent study in Malawi (Brune et al. 2011) identified large increases in savings and agricultural investment for farmers who were offered a precommitment savings instrument. Together, the results highlight the importance of behavioral elements (such as self-control) on decision making and their potential effect on development outcomes.

Boosting accountability in service provision: IEs assessed different approaches to strengthening of education service-provider accountability, such as supplying information, training, and/or control over resources to local stakeholders. To date, results show that these interventions are often successful in influencing behaviors of community members and service providers. An IE testing a package of management and accountability interventions in schools in Madagascar showed significant impacts on school functioning, student attendance, and grade repetition (DIME 2010). In Kenya, IE results indicated that when an extra contract teacher was hired at a school, impacts were strongest when that teacher was accountable to a school committee that included parents (Duflo, Dupas, and Kremer 2009). An IE in The Gambia showed that management training and school grants worked much better in places where adult literacy was high—pointing to potential complements between decentralized decision making and stakeholder capacity (Blimpo and Evans 2011). Property rights to boost investment: In Rwanda, improved property rights increased investment in soil and water conservation for both women and men (Ali, Deininger, and Goldstein 2011). The impact for women was double that of men (18 vs. 9 percentage-point increase in investment), proof of women’s less-secure property rights and how policies to address this can have a significant economic payoff. This research has important implications for agricultural practices that have high externalities (such as erosion and water management). Smart ways of boosting drug treatment adherence: The global HIV/ AIDS epidemic is fueled by risky sexual behavior. Prevention programs appear to have been fairly successful in increasing awareness and knowledge, but evidence on the link to changes in sexual behavior is weak. Similarly, on the treatment side, the emphasis had been on making antiretroviral therapy (ART) available and increasing the number of HIV-infected individuals on treatment. However, ART is only beneficial when patients have very high levels of adherence to the treatment. World Bank IE work in prevention and treatment is informing the next generation of HIV/AIDS programs. In rural Tanzania (de Walque et al. 2012), providing a $20 cash transfer every four months conditional on remaining free of sexually transmitted infections (STIs) resulted in a 25 percent reduction in the incidence of STIs. In Malawi (Baird et al. 2010), schoolgirls receiving payments from a cash-transfer program engage in safer sexual behavior. Eighteen months after the program began, the HIV prevalence among schoolgirls was 60 percent lower than the control group and 75 percent lower for HSV-2 (herpes simplex virus–type 2). Attaching sexual health conditions to cash transfer programs targeting young adults may help reduce risky sexual behavior. In Kenya (Pop-Eleches et al. 2011), an IE showed that the use of mobile text reminders increases HIV drug adherence by 33 percent and reduces treatment interruptions by 10 percent. This low-cost, high-coverage solution can be scaled up to improve treatment response, especially in resource-limited but high-mobile-coverage settings such as (continued)

Technical notes

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What’s the coolest region for doing impact evaluation? It’s Africa! (continued) Africa. Senegal is one country moving ahead with this approach. Impact evaluations are also changing the way new policies are introduced and evaluated. On the basis of these results, Senegal has asked DIME for technical support to conduct two new IEs on text messages for ART patients and to integrate health packages. The results from these pilots will inform the scale-up of national programs. Moving on IDA IE commitments to improve the effectiveness of the World Bank’s operations Under the IDA commitments, the World Bank committed to evaluate the impact of 51 IDA projects in the FY12–14 period and to improve selection of projects to reflect the composition of the IDA operations’ portfolio. This has given the operational VPUs, especially Africa, a new mandate and responsibility that they have started to implement by selecting operations for impact evaluation strategically and by planning their approach for conducting and financing IEs. Implementation challenges include absorptive capacity building for project teams and counterparts, allocation of regional operational and analytical budgets to IE activities, and a more strategic allocation of trust fund resources across themes. These issues are especially relevant to SDN sectors, with a large list of projects lined up for impact evaluation in sectors (water, energy, and transport) not currently attended to by existing IE programs. DIME and SDN have partnered to move this forward, and they jointly organized a workshop on Innovations and Solutions in Infrastructure, Agriculture and Environment, held in Naivasha, Kenya, April 23–27, 2012. The workshop attracted 12 IDA projects from the Africa region Sustainable Development Department, six Global Agriculture and Food Security Program (GAFSP) projects, and six projects from the Alliance for a Green Revolution in Africa (AGRA). The project teams were challenged to question their project and introduce testing of critical design elements that may affect policy results in significant ways. The idea was to think about the small things that make the big and expensive investments—like roads, pipes, and poles—deliver on their promises. A couple of examples of the things questioned: On quality of infrastructure, what type of contracts and demand-side measures (like audits and social monitoring) secure accountability in procurement? On operations and maintenance (O & M), what strategies improve energy reliability? What models of road O & M and local participation are more effective? What enforcement mechanisms and repayment schemes are needed for the financial sustainability of O & M of irrigation canals? Notes 1 See DIME Progress Report FY10-11

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References Ali, Daniel Ayalew, Klaus Deininger, and Markus Goldstein. 2011. “Environmental and Gender Impacts of Land Tenure Regularization in Africa—Pilot Evidence from Rwanda.” Policy Research Working Paper 5765, World Bank, World Bank. ht tp://w w w-wds.worldbank.org/ex ternal/default / WDS ContentServer/IW3P/IB/2011/08/18/000158349_20110818104 704/Rendered/PDF/WPS5765.pdf Baird, S., E. Chirwa, C. McIntosh, and B. Ozler. 2010. “The ShortTerm Impacts of a Schooling Conditional Cash Transfer Program on the Sexual Behavior of Young Women.” Health Economics 2010(19):55–68. Blimpo, Moussa P., and David K. Evans. 2011, “School-Based Management and Educational Outcomes: Lessons from a Randomized Field Experiment,” mimeo, The World Bank. http://siteresources.worldbank.org/EDUCATION/Resources/ Blimpo-Evans_WSD-2012-01-12.pdf Brune, Lasse, Xavier Giné, Jessica Goldberg, and Dean Yang. 2011. “Commitments to Save: A Field Experiment in Rural Malawi.” Policy Research Working Paper 5748, World Bank, Washington, DC. deWalque, D., W. H. Dow, R. Nathan, et al. 2012. “Incentivising Safe Sex: A Randomised Trial of Conditional Cash Transfers for HIV and Sexually Transmitted Infection Prevention in Rural Tanzania.” British Medical Journal Open 2012(2) DIME. 2010, “DIME BRIEF. The transformative effect of managing for results in primary education in Madagascar,” mimeo, DIME. http://siteresources.worldbank.org/INTDEVIMPEVAINI/ Resources/3998199-1285950237302/DIMEBRIEFMadagascar AGEMAD.pdf Dufl o, Esther, Pascaline Dupas, and Michael Kremer. 2009 “Additional Resources versus Organizational Changes in Education: Experimental Evidence from Kenya,” mimeo, MIT. http://economics.mit.edu/files/4286 Fafchamps, Marcel, David McKenzie, Simon Quinn, and Christopher Woodruff. 2011. “When Is Capital Enough to Get Female Microenterprises Growing? Evidence from a Randomized Experiment in Ghana.” Policy Research Working Paper 5706, World Bank, Washington, DC. Mobarak, Mushfiq, Ariel, BenYishay, Malawi. Ministry of Food and Agriculture, 2012. Agricultural Technology Diffusion through Social Networks, mimeo, DIME. Pop-Eleches, C., H. Thirumurthy, J. P. Habyarimana, J. G. Zivin, M. P. Goldstein, D. de Walque, L. Mackeen, J. Haberer, S. Kimaiyo, J. Sidle, D. Ngare, and D. R. Bangsberg. 2011. “Mobile Phone Technologies Improve Adherence to Antiretroviral Treatment in a Resource-Limited Setting: A Randomized Controlled Trial of Text Message Reminders.” AIDS 25(6):825–34.

received vaccinations for measles before 12 months or at any time before the survey. A child is considered adequately immunized against measles after receiving one dose of vaccine. Source: Data on under-five and infant mortality are from Level & Trends in Child Mortality. Report 2011. Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA, UNPD). Data on child immunization are from the World Health Organization and the United Nations Children’s Fund (www.who.int/immunization_monitoring/ routine/en/). Table .. Millennium Development Goal : improve maternal health Maternal mortality ratio, modeled estimate, is the number of women who die from pregnancy-related causes during pregnancy and childbirth, per 100,000 live births. Data are estimated by a regression model using information on fertility, birth attendants, and human immunodeficiency virus (HIV) prevalence. Maternal mortality ratio, national estimate, is the number of women who die during pregnancy and childbirth, per 100,000 live births. Births attended by skilled health staff are the percentage of deliveries attended by personnel who are trained to give the necessary supervision, care, and advice to women during pregnancy, labor, and the postpartum period; to conduct deliveries on their own; and to care for newborns. Source: Data on maternal mortality (modeled) are from Trends in Maternal Mortality: 1990–2010 estimates developed by the World Health Organization (WHO), United Nations Children’s Fund (UNICEF), United Nations Population Fund (UNFPA), and the World Bank. Data on maternal mortality (national) and births attended by skilled health staff are from UNICEF State of the World’s Children and Childinfo and from Demographic and Health Surveys by Macro International. Table .. Millennium Development Goal : combat HIV/AIDS, malaria, and other diseases Prevalence of HIV is the percentage of people ages 15–49 who are infected with HIV.

Contraceptive use, any method, is the percentage of women ages 15–49, married or in union, who are practicing, or whose sexual partners are practicing, any form of contraception. Children sleeping under insecticide-treated nets is the percentage of children under age 5 with access to an insecticide-treated net to prevent malaria. Incidence of tuberculosis is the estimated number of new tuberculosis cases (pulmonary, smear positive, and extrapulmonary), per 100,000 people. Tuberculosis treatment success rate is the percentage of new, registered smear-positive (infectious) cases that were cured or in which a full course of treatment was completed. Source: Data on HIV prevalence are from the Joint United Nations Programme on HIV/AIDS and the World Health Organization (WHO) Report on the Global AIDS Epidemic. Data on contraceptive use are from household surveys, including Demographic and Health Surveys by Macro International and Multiple Indicator Cluster Surveys, by the United Nations Children’s Fund (UNICEF). Data on insecticide-treated net use are from UNICEF State of the World’s Children and Childinfo and from Demographic and Health Surveys by Macro International. Data on tuberculosis are from the WHO Global Tuberculosis Control Report. Table .. Millennium Development Goal : ensure environment sustainability Forest area is land under natural or planted stands of trees, whether productive or not. Terrestrial protected areas are those oﬃcially documented by national authorities. Gross domestic product (GDP) per unit of energy use is the GDP in purchasing power parity (PPP) U.S. dollars per kilogram of oil equivalent of energy use. PPP GDP is gross domestic product converted to 2000 constant international dollars using PPP rates. An international dollar has the same purchasing power over GDP as a U.S. dollar has in the United States. Carbon dioxide emissions per capita are those stemming from the burning of fossil fuels and the manufacture of cement divided by midyear population. They include carbon Technical notes

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dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring. Population with sustainable access to an improved water source is the percentage of the population with reasonable access to an adequate amount of water from an improved source, such as a household connection, public standpipe, borehole, protected well or spring, or rainwater collection. Unimproved sources include vendors, tanker trucks, and unprotected wells and springs. Reasonable access is defined as the availability of at least 20 liters a person a day from a source within 1 kilometer of the dwelling. Population with sustainable access to improved sanitation is the percentage of the population with at least adequate access to excreta disposal facilities that can effectively prevent human, animal, and insect contact with excreta. Improved facilities range from simple but protected pit latrines to flush toilets with a sewerage connection. The excreta disposal system is considered adequate if it is private or shared (but not public) and if it hygienically separates human excreta from human contact. To be effective, facilities must be correctly constructed and properly maintained. Source: Data on forest area are from the Food and Agricultural Organization Global Forest Resources Assessment. Data on nationally protected areas are from the United Nations Environment Programme and the World Conservation Monitoring Centre, as compiled by the World Resources Institute, and based on data from national authorities, national legislation, and international agreements. Data on energy use are from electronic files of the International Energy Agency. Data on carbon dioxide emissions are from the Carbon Dioxide Information Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory. Data on access to water and sanitation are from the World Health Organization and United Nations Children’s Fund, Joint Measurement Programme (www.wssinfo.org). Table .. Millennium Development Goal : develop a global partnership for development Heavily Indebted Poor Countries (HIPC) Debt Initiative decision point is the date at which 148

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a HIPC with an established track record of good performance under adjustment programs supported by the International Monetary Fund (IMF) and the World Bank commits to undertake additional reforms and to develop and implement a poverty reduction strategy. HIPC Debt Initiative completion point is the date at which a country successfully completes the key structural reforms agreed on at the decision point, including developing and implementing its poverty reduction strategy. The country then receives the bulk of debt relief under the HIPC Debt Initiative without further policy conditions. Debt service relief committed is the amount of debt service relief, calculated at the Enhanced HIPC Initiative decision point, that will allow the country to achieve debt sustainability at the completion point. Public and publicly guaranteed debt service is the sum of principal repayments and interest actually paid in foreign currency, goods, or services on long-term obligations of public debtors and long-term private obligations guaranteed by a public entity. Exports refer to exports of goods, services, and income. Worker remittances are not included here, though they are included with income receipts in other World Bank publications, such as Global Development Finance. Youth unemployment rate is the percentage of the labor force ages 15–24 without work but available for and seeking employment. Definitions of labor force and unemployment may differ by country. Fixed-line and mobile telephone subscribers are subscribers to a fixed-line telephone service, which connects a customer’s equipment to the public switched telephone network, or to a public mobile telephone service, which uses cellular technology. Source: Data on HIPC countries are from the International Development Association and International Monetary Fund “Heavily Indebted Poor Countries (HIPC) Initiative and Multilateral Debt Relief Initiative—Status of Implementation.” Data on external debt are mainly from reports to the World Bank through its debtor Reporting System from member countries that have received International Bank for Reconstruction and Development loans or International

Prepared by Jos Verbeek and Jose Alejandro Quijada

Africa and the MDGs: 2015 and Beyond

Figure 1. Global and regional performances MDG 1a. Extreme poverty (% of population below $1.25 a day in 205 PPP)

100%

61%

MDG 2a. Primary completion rate, total (% of relevant age group)

87%

67%

MDG3a. Ratio of girls to boys in primary and secondary education (%)

88%

96%

51% 46%

MDG 4a. Mortality rate, infant (per 1,000 live births)

Developing countries Sub-Saharan Africa

52% 47%

MDG 4a. Mortality rate, under-5 (per 1,000) MDG 5a. Maternal mortality ratio (modeled estimate, per 100,000 live births)

38% 33%

MDG 7c. Improved water source (% of population without access)

100%

66%

MDG 7c. Improved sanitation facilities (% of population without access)

72%

54%

90%

100%

80%

70%

60%

50%

40%

30%

20%

10%

Current MDG Developments Sub-Saharan Africa is lagging behind other regions on most Millennium Development Goals (MDGs). However, the region has achieved more than 60 percent of the progress required to reach such goals as gender parity, primary school completion, access to safe water, and extreme poverty reduction by 2015. Progress in health-related MDGs, particularly maternal mortality, is significantly lagging with respect to the 2015 targets (figure 1). Despite adverse initial conditions, the region is making fast progress in many areas. For instance, between 1990 and 2009, the primary school completion rate in Sub-Saharan Africa improved by more than 1.5 times that of all developing countries (from 51.2 to 66.9 in the region vs. 77.5 to 87.4 at the global level). This is also the case for MDGs related to child and maternal mortality between 1990 and 2010, where relative regional improvement was larger than in other developing countries (figure 2). Sub-Saharan Africa is vulnerable to increases in international food prices. In most countries in this region, approximately 50 to 70 percent of household spending is devoted to food. Additionally, the region imports about 45 percent of its consumption of rice and 85 percent of its consumption of wheat. Further, high levels of malnutrition result in stunted growth for 38 percent of children. The situation is most perilous in the drought- and conflict-stricken countries of the Horn of Africa. Nevertheless, increases in cereal production, driven by higher yields since the middle of the past decade, improved the continent’s ability to cope with the food price spike of 2011, compared with the experience in 2008. In addition, nutrition has remained for decades a low government priority in the region. Nutrition in many African countries is trapped in a vicious “low priority cycle” that starts with little demand for nutrition services—followed by a weak response by governments, and ends up with ineffective implementation and poor results—which, in turn, feeds into low demand for nutrition. Senegal provides an example of a country that has made significant strides in the fight against undernutrition through its Multisectoral Forum for the Fight against Malnutrition, a National Executive Office, which ensures the day-today management, coordination, and monitoring of national nutrition policies. Recent estimates indicate that undernutrition reduction in Senegal is 16 times higher than the regional average.

Progress toward 2015 Note: A value of 100% means that respective MDG has been reached. Values denote present progress as illustrated by most recent available data: Extreme poverty—2010; Primary school completion rate—2009; Ratio of girls to boys in primary and secondary school—2009; Mortality rate, infant—2010; Mortality rate, under fi ve—2010; Maternal mortality ratio—2008; Improved water source—2010; Improved sanitation facilities—2008. Source: World Bank staff calculations based on data from the World Development Indicators database.

Figure 2. Improvement in MDG indicators relative to global performance MDG 7c. Improved sanitation facilities (% of population without access)

0.25

MDG 7c. Improved water source (% of population without access)

0.83

MDG 5a. Maternal mortality ratio (modeled estimate, per 100,000 live births)

1.47

MDG 4a. Mortality rate, under-5 (per 1,000)

1.44

MDG 4a. Mortality rate, infant (per 1,000 live births)

1.25

MDG3a. Ratio of girls to boys in primary and secondary education (%)

0.50

MDG 2a. Primary completion rate, total (% of relevant age group)

1.58

MDG 1a. Extreme poverty (% of population below $1.25 a day in 205 PPP)

0.48 0.00 0.50 1.00 1.50 2.00 Improvement in SSA / Improvement at the global level

Note: Chart depicts the ratio of absolute regional improvement to global improvement by MDG. Improvement is measured as the difference between latest available value (see note, figure 1) and starting value circa 1990. Source: World Bank staff calculations based on data from the World Development Indicators database.

Figure 3. Share of low- and middle-income countries since year 2000 90%

Post-2015 Developments Official Development Assistance (ODA) has become increasingly viewed as only one component of many international activities (such as trade and investment) that supports long-term sustainable development and poverty alleviation. Nevertheless, ODA remains a major instrument with which to engage in development cooperation. The international aid community needs to continue to improve information sharing and to facilitate the ongoing expansion of ODA agents’ participation in setting the global development agenda in order to better address the needs of the poor. Also, the group of low-income countries for which the MDGs were intended is shrinking, while large contingents of poor or underserved groups live or will live in middle-income countries in the coming decade (figure 3).

79%

80%

Developing countries

60% 50%

74%

Sub-Saharan Africa

70%

59%

54% 46%

41%

40% 30%

21%

20%

26%

10% 0%

Low

2000

Middle

Low

2011

Middle

Note: Chart depicts the percentage of countries in each income category per region. Source: World Bank staff calculations based on data from the World Development Indicators database.

(continued)

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Africa and the MDGs: 2015 and Beyond (continued) There is broad agreement that the country-based development model is the most effective approach for achieving results in terms of sustained economic growth and poverty reduction in developing countries. The country-based model consists of three main strands: (1) nationally owned development strategies; (2) donor alignment around country-driven goals, with increased use of country systems wherever feasible and efforts to increase aid predictability; and (3) mechanisms of mutual accountability encompassing both donors and governments in recipient countries. Accordingly, the interplay of these three strands strengthens domestic policies and systems in recipient countries, unites donors around clear development goals, and sets out a mutual accountability framework for all stakeholders. Henceforth, moving away from global goals to country-specific ones should improve effectiveness of the development process. Results-based monitoring and evaluation (M&E) can be a powerful public management tool if used to guide decisions on how goals can be reached most effectively and efficiently—that is, it can help ensure that countries and donors get value for money. It can be used in the context of the MDGs to help policymakers track

progress and demonstrate the outcomes and impacts of a given policy, program, or project. Results-based M&E differs from traditional implementation-focused M&E in that it emphasizes inputs, activities, and outputs with a sharp focus on outcomes and impacts while identifying the critical bottlenecks to achieving those outcomes. To identify those bottlenecks, the World Bank’s Country Policy and Institutional Assessment tool (CPIA) could perform a useful function in assisting countries with identifying some of those critical bottlenecks (Go and Quijada 2012). A functioning results-based M&E system provides information that is useful both internally and externally. Country use comes about when the information from the M&E system becomes a management tool for policy makers, managing to achieve results and accomplish specified targets. Likewise, the information from a results-based M&E system is crucial to donors who expect demonstrable results from government action and aid resources. Reference Go and Quijada. 2012. “The Odds of Achieving the MDGs.” World Bank Research Observer doi: 10.1093/wbro/lks005.

Development Association credits, as well as from World Bank and IMF files. Data on youth unemployment are from the International Labour Organization Key Indicators of the Labour Market database. Data on telephone subscribers and Internet users are from the International Telecommunication Union World Telecommunication/ICT Development Report and database, and from World Bank estimates. 4. Private sector development Table .. Doing Business indicators Number of startup procedures to start a business is the number of procedures required to start a business, including interactions to obtain necessary permits and licenses and to complete all inscriptions, verifications, and notifications to start operations. Time required for each procedure to start a business is the number of calendar days needed to complete each procedure to legally operate a business. If a procedure can be speeded up at additional cost, the fastest procedure, independent of cost, is chosen. Cost to start a business is normalized by presenting it as a percentage of gross national income (GNI) per capita. Minimum capital is the paid-in minimum capital requirement, which reflects the amount 150

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that the entrepreneur needs to deposit in a bank or with a notary before registration and up to three months following incorporation. It is reported as a percentage of the country’s income per capita. Number of procedures to register property is the number of procedures required for a business to secure rights to property. Time required to register property is the number of calendar days needed for a business to secure rights to property. Cost to register property is the official costs required by law to register a property, including fees, transfer taxes, stamp duties, and any other payment to the property registry, notaries, public agencies, and lawyers. Other taxes, such as capital gains tax or value added tax, are excluded from the cost measure. Both costs borne by the buyer and those borne by the seller are included. If cost estimates differ among sources, the median reported value is used. It is reported as a percentage of property value, which is assumed to be equivalent to 50 times income per capita. Number of procedures to enforce a contract is the number of independent actions, mandated by law or courts, that demand interaction between the parties of a contract or between them and the judge or court officer. Time required to enforce a contract is the number of calendar days from the filing of

the lawsuit in court until the final determination and, in appropriate cases, payment. Cost to enforce a contract is court and attorney fees, where the use of attorneys is mandatory or common, or the cost of an administrative debt recovery procedure, expressed as a percentage of the debt value. Number of procedures to deal with construction permits is the number of procedures required to obtain construction-related permits. Time required to deal with construction permits is the average wait, in days, experienced to obtain a construction-related permit from the day the establishment applied for it to the day it was granted. Cost to deal with construction permits is all the fees associated with completing the procedures to legally build a warehouse, including those associated with obtaining land use approvals and reconstruction design clearances; receiving inspections before, during, and after construction; getting utility connections; and registering the warehouse property. Nonrecurring taxes required for the completion of the warehouse project also are recorded. The building code, information from local experts, and specific regulations and fee schedules are used as sources for costs. If several local partners provide different estimates, the median reported value is used. It is reported as a percentage of the country’s income per capita. Disclosure index measures the degree to which investors are protected through disclosure of ownership and financial information. Higher values indicate more disclosure. Director liability index measures a plaintiff ’s ability to hold directors of firms liable for damages to the company. Higher values indicate greater liability. Shareholder suits index measures shareholders’ ability to sue officers and directors for misconduct. Higher values indicate greater power for shareholders to challenge transactions. Investor protection index measures the degree to which investors are protected through disclosure of ownership and financial information regulations. It is the average of the disclosure, director liability, and shareholder suits indexes. Higher values indicate better protection. Resolving insolvency time (years) is the average time to close a business. Information is

collected on the sequence of procedures and on whether any procedures can be carried out simultaneously. Cost (% of estate) is the average cost of bankruptcy proceedings. The cost of the proceedings is recorded as a percentage of the estate’s value. Recovery rate (cents on the dollar) is the recovery rate calculated on the basis of how many cents on the dollar claimants (creditors, tax authorities, and employees) recover from an insolvent firm. Source: Data are from the World Bank, Doing Business project (http://www.doing Business.org/). Table .. Investment climate Private sector fixed capital formation is private sector fixed capital formation (table 2.21) divided by nominal gross domestic product (table 2.1). Net foreign direct investment is net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. This series shows net inflows (new investment inflows less disinvestment) in the reporting economy from foreign investors. Domestic credit to private sector is financial resources provided to the private sector, such as through loans, purchases of nonequity securities, and trade credits and other accounts receivable that establish a claim for repayment. For some countries these claims include credit to public enterprises. Firms that believe the court system is fair, impartial, and uncorrupt are the percentage of firms that believe the court system is fair, impartial, and uncorrupt. Corruption is the percentage of firms identifying corruption as a major constraint to current operation. Crime, theft, and disorder are the percentage of firms identifying crime, theft, and disorder as a major constraint to current operation. Tax rates are the percentage of firms identifying tax rates as a major constraint to current operation. Technical notes

151

Finance is the percentage of firms identifying access to finance or cost of finance as a major constraint to current operation. Electricity is the percentage of firms identifying electricity as a major constraint to current operation. Labor regulations are the percentage of firms identifying labor regulations as a major constraint to current operation. Labor skills are the percentage of firms identifying skills of available workers as a major constraint to current operation. Transportation is the percentage of firms identifying transportation as a major constraint to current operation. Customs and trade regulations are the percentage of firms identifying customs and trade regulations as a major constraint to current operation. Number of tax payments is the number of taxes paid by businesses, including by electronic filing. The tax is counted as paid once a year even if payments are more frequent. Time to prepare, file, and pay taxes is the number of hours it takes to prepare, file, and pay (or withhold) three major types of taxes: the corporate income tax, the value added or sales tax, and labor taxes, including payroll taxes and social security contributions. Total tax rate is the total amount of taxes payable by the business (except for labor taxes) after accounting for deductions and exemptions as a percentage of profit. Highest marginal tax rate, corporate, is the highest rate shown on the schedule of tax rates applied to the taxable income of corporations. Time dealing with officials is the average percentage of senior management’s time that is spent in a typical week dealing with requirements imposed by government regulations (for example, taxes, customs, labor regulations, licensing, and registration), including dealings with officials, completing forms, and the like. Average time to clear customs, direct exports, is the average number of days to clear direct exports through customs. Average time to clear customs, imports, is the average number of days to clear imports through customs. Interest rate spread is the interest rate charged by banks on loans to prime customers minus the interest rate paid by commercial 152

Africa Development Indicators 2012/13

or similar banks for demand, time, or savings deposits. Listed domestic companies are domestically incorporated companies listed on a country’s stock exchanges at the end of the year. They exclude investment companies, mutual funds, and other collective investment vehicles. Market capitalization of listed companies, also known as market value, is the share price of a listed domestic company’s stock times the number of shares outstanding. Turnover ratio for traded stocks is the total value of shares traded during the period divided by the average market capitalization for the period. Average market capitalization is calculated as the average of the end-ofperiod values for the current period and the previous period. Source: Data on private sector fixed capital formation are from the World Bank World Development Indicators database. Data on net foreign direct investment are from the International Monetary Fund (IMF) Balance of Payments database, supplemented by data from the United Nations Conference on Trade and Development and official national sources. Data on domestic credit to the private sector are from the IMF International Financial Statistics database and data files, World Bank and Organisation for Economic Co-operation and Development gross domestic product (GDP) estimates, and the World Bank World Development Indicators database. Data on investment climate constraints to firms, data on time dealing with officials, and average time to clear customs are based on enterprise surveys conducted by the World Bank and its partners (http://www.enterpriseSurveys). Data on regulation and tax administration and highest marginal corporate tax rates are from the World Bank Doing Business project (http://www.doingBusiness). Data on interest rate spreads are from the IMF International Financial Statistics database and data files and the World Bank World Development Indicators database. Data on listed domestic companies, turnover ratios for traded stocks, and market capitalization are from Standard & Poor’s Global Stock Markets Factbook and supplemental Standard & Poor’s data.

Table .. Financial sector infrastructure Foreign currency sovereign ratings are long- and short-term foreign currency ratings that assess a sovereign’s capacity and willingness to honor in full and on time its existing and future obligations issued in foreign currencies. Short-term ratings have a time horizon of less than 13 months for most obligations, or up to 3 years for U.S. public finance, in line with industry standards, to reflect the unique risk characteristics of bond, tax, and revenue anticipation notes that are commonly issued with terms up to 3 years. Short-term ratings thus place greater emphasis on the liquidity necessary to meet financial commitments in a timely manner. Gross national savings is the sum of gross domestic savings (table 2.13) and net factor income and net private transfers from abroad. The estimate here also includes net public transfers from abroad. Money and quasi money (M2) are the sum of currency outside banks, demand deposits other than those of the central government, and the time, savings, and foreign currency deposits of resident sectors other than the central government. This definition of money supply is frequently called M2 and corresponds to lines 34 and 35 in the International Monetary Fund International Financial Statistics. Real interest rate is the lending interest rate adjusted for inflation as measured by the gross domestic product deflator. Domestic credit to private sector is financial resources provided to the private sector, such as through loans, purchases of nonequity securities, and trade credits and other accounts receivable, that establish a claim for repayment. For some countries these claims include credit to public enterprises. Interest rate spread is the interest rate charged by banks on loans to prime customers minus the interest rate paid by commercial or similar banks for demand, time, or savings deposits. Ratio of bank nonperforming loans to total gross loans is the value of nonperforming loans divided by the total value of the loan portfolio (including nonperforming loans before the deduction of specific loan-loss provisions). The loan amount recorded as nonperforming should be the gross value of the loan

as recorded on the balance sheet, not just the amount overdue. Listed domestic companies are domestically incorporated companies listed on a country’s stock exchanges at the end of the year. They exclude investment companies, mutual funds, and other collective investment vehicles. Market capitalization of listed companies, also known as market value, is the share price of a listed domestic company’s stock times the number of shares outstanding. Turnover ratio for traded stocks is the total value of shares traded during the period divided by the average market capitalization for the period. Average market capitalization is calculated as the average of the end-ofperiod values for the current period and the previous period. Source: Data on foreign currency sovereign ratings are from Fitch Ratings (www.fitch ratings.com/). Data on gross national savings are from World Bank national accounts data, and Organisation for Economic Co-operation and Development national accounts data files. Data on money and quasi money and domestic credit to the private sector are from the International Monetary Fund International Financial Statistics and data files and World Bank and OECD estimates of GDP. Data on real interest rates are from the IMF International Financial Statistics database and data files using World Bank data on the GDP deflator and the World Bank World Development Indicators database. Data on interest rate spreads are from the International Monetary Fund, International Financial Statistics and data files. Data on ratios of bank nonperforming loans to total are from the International Monetary Fund Global Financial Stability Report. Data on bank branches are from surveys of banking and regulatory institutions by the World Bank Research Department and Financial Sector and Operations Policy Department and the World Development Indicators database. Data on listed domestic companies and turnover ratios for traded stocks are from Standard & Poor’s Emerging Stock Markets Factbook and supplemental data and the World Bank’s World Development Indicators database. Data on market capitalization of listed companies are from Standard & Poor’s Emerging Technical notes

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Stock Markets Factbook and supplemental data, World Bank and OECD estimates of GDP, and the World Bank World Development Indicators database. 5. Trade and regional integration Table .. International trade and tariff barriers Total trade is the sum of exports and imports of goods and services measured as a share of gross domestic product. Merchandise trade is the sum of imports and exports of merchandise divided by nominal gross domestic product. Services trade is the sum of imports and exports of wholesale and retail trade (including hotels and restaurants), transport, and government, financial, professional, and personal services such as education, health care, and real estate (International Standard Industrial Classification revision 3 divisions 50–99) less the value of their intermediate inputs. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers or arising from rescaling. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. For countries that report national accounts data at producer prices (Angola, Benin, Cape Verde, Comoros, the Republic of Congo, Côte d’Ivoire, Gabon, Liberia, Niger, Rwanda, São Tomé and Príncipe, Seychelles, and Togo), gross value added at market prices is used as the denominator. For countries that report national accounts data at basic prices (all other countries), gross value added at factor cost is used as the denominator. Value added at basic prices excludes net taxes on products; value added at producer prices includes net taxes on products paid by producers but excludes sales or value added taxes. Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude labor and property income (formerly called factor services) as well as transfer 154

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payments and are expressed in current U.S. dollars and as a proportion of nominal GDP. Imports of goods and services represent the value of all goods and other market services received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other services, such as communication, construction, financial, information, business, personal, and government services. They exclude labor and property income (formerly called factor services) as well as transfer payments and are expressed in current U.S. dollars and as a proportion of nominal GDP. Annual growth of exports and imports is calculated using real imports and exports. Terms of trade index measures the relative movement of export and import prices. This series is calculated as the ratio of a country’s export unit values or prices to its import unit values or prices and shows changes over a base year (2000) in the level of export unit values as a percentage of import unit values. Structure of merchandise exports and imports components may not sum to 100 percent because of unclassified trade. Food comprises the commodities in Standard International Trade Classification (SITC) sections 0 (food and live animals), 1 (beverages and tobacco), and 4 (animal and vegetable oils and fats) and SITC division 22 (oil seeds, oil nuts, and oil kernels). Agricultural raw materials comprise the commodities in SITC section 2 (crude materials except fuels), excluding divisions 22, 27 (crude fertilizers and minerals excluding coal, petroleum, and precious stones), and 28 (metalliferous ores and scrap). Fuel comprises SITC section 3 (mineral fuels). Ores and metals comprise the commodities in SITC sections 27, 28, and 68 (nonferrous metals). Manufactures comprise the commodities in SITC sections 5 (chemicals), 6 (basic manufactures), 7 (machinery and transport equipment), and 8 (miscellaneous manufactured goods), excluding division 68. Export/import diversification index measures the extent to which exports/imports are diversified. It is constructed as the inverse of a Herfindahl index, using disaggregated exports/imports at four digits (following SITC revision 3). The total number of products

exported/imported includes only those whose value exceeds $100,000 or 0.3 percent of the country’s total exports/imports, whichever is smaller. The maximum number of three-digit products that could be exported is 261. Ranging from 0 to 1, the index reveals the extent of the differences between the structure of trade of the country or country group and the world average. An index value closer to 1 indicates a bigger difference from the world average. A higher value indicates more export/ import diversification. The index is computed by measuring absolute deviation of the country share from world structure. Export/import concentration index, also known as the Herfindahl-Hirschmann index, is a measure of the degree of market concentration. The total number of products exported/imported includes only those whose value exceeds $100,000 or 0.3 percent of the country’s total exports/imports, whichever is smaller. The maximum number of three-digit products that could be exported/imported is 261. It has been normalized to a scale of 0–1. An index value close to 1 indicates a very concentrated market (maximum concentration). Values closer to 0 reflect a more equal distribution of market shares among exporters or importers. This type of concentration indicator is vulnerable to cyclical fluctuations in relative prices, with commodity price rises making commodity exporters/importers look more concentrated. Competitiveness indicator has two aspects: sectoral effect and global effect. To calculate both indicators, growth of exports is decomposed into three components: the growth rate of total international trade over the reference period (2005–09); the sectoral effect, which measures the contribution to a country’s export growth of the dynamics of the sectoral markets where the country sells its products, assuming that sectoral market shares are constant; and the competitiveness effect, which measures the contribution of changes in sectoral market shares to a country’s export growth. Tariff barriers are a form of duty based on the value of an import. Binding coverage is the percentage of product lines with an agreed bound rate. Simple mean bound rate is the unweighted average of all the lines in the tariff schedule in which bound rates have been set.

Simple mean tariff is the unweighted average of effectively applied rates or most favored nation rates for all products subject to tariffs calculated for all traded goods. Dispersion around the mean is calculated as the coefficient of variation of the applied tariff rates, including preferential rates that a country applies to its trading partners available at the six-digit product level of the Harmonized System in a country’s customs schedule. Weighted mean tariff is the average of effectively applied rates or most favored nation rates weighted by the product import shares corresponding to each partner country. Share of lines with international peaks is the share of lines in the tariff schedule with tariff rates that exceed 15 percent. Share of lines with domestic peaks is the share of lines in the tariff schedule with tariff rates that are more than three times the simple average tariff. Share of lines that are bound is the share of lines in the country’s tariff schedule bound subject to World Trade Organization negotiation agreements. Share of lines with specific rates is the share of lines in the tariff schedule that are set on a per unit basis or that combine ad valorem and per unit rates. Primary products are commodities classified in SITC revision 2 sections 0–4 plus division 68. Manufactured products are commodities classified in SITC revision 2 sections 5–8 excluding division 68. Average cost to ship 20 ft container from port to destination is the cost of all operations associated with moving a container from onboard a ship to the considered economic center, weighted based on container traffic for each corridor. Average time to clear customs, direct exports, is the average number of days to clear direct exports through customs. Average time to clear customs, imports, is the average number of days to clear imports through customs. Source: Data on trade and services are from World Bank and Organisation for Economic Co-operation and Development national accounts data. Data on merchandise trade are from the World Trade Organization and Technical notes

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World Bank GDP estimates. Data on the competitiveness indicator are from the Organisation for Economic Co-operation and Development African Economic Outlook 2011: Africa and Its Emerging Partners. Data on the export concentration index and diversification index data are from the United Nations Conference on Trade and Development Statistical Office data files (http://unctadstat. unctad.org), with Standard International Trade Classification groups from the United Nations Statistics Division (http://unstats. un.org/unsd/cr/registry/regcst.asp?Cl=14). Data on tariffs are calculated by World Bank staff using the World Integrated Trade Solution system (http://wits.worldbank.org) and data from the United Nations Conference on Trade and Development Trade Analysis and Information System database and the World Trade Organization Integrated Data Base and Consolidated Tariff Schedules database. Data on global imports are from the United Nations Statistics Division COMTRADE database. Data on merchandise exports and imports are from World Bank country desks. Data on shipping costs are from the World Bank Sub-Saharan Africa Transport Policy Program. Data on average time to clear customs are from World Bank Enterprise Surveys (http://www.enterpriseSurveys/). Table . Top three exports and share in total exports,  Top exports and share of total exports are based on exports disaggregated at the four-digit level (following the Standard International Trade Classification revision 3). Number of exports accounting for 75 percent of total exports is the number of exports in a country that account for 75 percent of the country’s exports. Source: Organisation for Economic Cooperation and Development African Economic Outlook 2011: Africa and Its Emerging Partners. Table . Regional integration, trade blocs Type of most recent agreement includes customs union, under which members substantially eliminate all tariff and nontariff barriers among themselves and establish a common external tariff for nonmembers; economic integration agreement, which 156

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liberalizes trade in services among members and covers a substantial number of sectors, affects a sufficient volume of trade, includes substantial modes of supply, and is nondiscriminatory (in the sense that similarly situated service suppliers are treated the same); free trade agreement, under which members substantially eliminate all tariff and nontariff barriers but set tariffs on imports from nonmembers; partial scope agreement, which is a preferential trade agreement notified to the World Trade Organization (WTO) that is not a free trade agreement, a customs union, or an economic integration; and not notified agreement, which is a preferential trade arrangement established among member countries that is not notified to the WTO (the agreement may be functionally equivalent to any of the other agreements). Merchandise exports within bloc are the sum of merchandise exports by members of a trade bloc to other members of the bloc. They are shown both in U.S. dollars and as a percentage of total merchandise exports by the bloc. Merchandise exports by bloc are the sum of merchandise exports within bloc and to the rest of the world as a share of total merchandise exports by all economies in the world. Source: Data on merchandise trade flows are published in the International Monetary Fund (IMF) Direction of Trade Statistics Yearbook and Direction of Trade Statistics Quarterly. The data in the table were calculated using the IMF’s Direction of Trade database. The information on trade bloc membership is from the World Bank Policy Research Report Trade Blocs (2000), the United Nations Conference on Trade and Development Trade and Development Report 2007, the World Trade Organization Regional Trade Agreements Information System, and the World Bank and the Center for International Business at the Tuck School of Business at Dartmouth College’s Global Preferential Trade Agreements Database (http://wits.worldbank.org/gptad/). 6. Infrastructure Table .. Water and sanitation Internal fresh water resources per capita are the sum of total renewable resources, which include internal flows of rivers and

groundwater from rainfall in the country and river flows from other countries. Population with sustainable access to an improved water source is the percentage of the population with reasonable access to an adequate amount of water from an improved source, such as a household connection, public standpipe, borehole, protected well or spring, or rainwater collection. Unimproved sources include vendors, tanker trucks, and unprotected wells and springs. Reasonable access is defined as the availability of at least 20 liters a person a day from a source within one kilometer of the user’s dwelling. Population with sustainable access to improved sanitation is the percentage of the population with at least adequate access to excreta disposal facilities that can effectively prevent human, animal, and insect contact with excreta. Improved facilities range from simple but protected pit latrines to flush toilets with a sewerage connection. The excreta disposal system is considered adequate if it is private or shared (but not public) and if it hygienically separates human excreta from human contact. To be effective, facilities must be correctly constructed and properly maintained. Average duration of insufficient water supply is the average duration of water shortages in a typical month in the last fiscal year. Committed nominal investment in water projects with private participation is annual committed investment in water projects with private investment, including projects for potable water generation and distribution and sewerage collection and treatment projects. Official development assistance (ODA) gross disbursements for water supply and sanitation sector are disbursements for water supply and sanitation by bilateral, multilateral, and other donors. The release of funds to, or the purchase of goods or services for a recipient; by extension, the amount thus spent. Disbursements record the actual international transfer of financial resources or of goods or services valued at the cost of the donor. Source: Data on freshwater resources are from the Food and Agriculture Organization AQUASTAT database. Data on access to water and sanitation are from the World Health Organization and United Nations Children’s

Fund, Joint Measurement Programme (www. wssinfo.org). Data on insufficient water supply are from World Bank Enterprise Surveys (http://www.enterpriseSurveys/). Data on committed nominal investment in potable water projects with private participation are from the World Bank Private Participation in Infrastructure Project Database (http:// ppi.worldbank.org). Data on official development assistance disbursements are from the Development Assistance Committee of the Organisation for Economic Co-operation and Development Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database (www.oecd. org/dac/stats/idsonline). Table .. Transportation Road network is the length of motorways, highways, main or national roads, secondary or regional roads, and other roads. Rail lines are the length of railway route available for train service, irrespective of the number of parallel tracks. Road density, ratio to total land, is the total length of national road network per 100 square kilometers of total land area. Vehicle fleet is the number of motor vehicles, including cars, buses, and freight vehicles but not two-wheelers. Commercial vehicles are the number of commercial vehicles that use at least 24 liters of diesel fuel per 100 kilometers. Passenger vehicles are road motor vehicles, other than two-wheelers, intended for the carriage of passengers and designed to seat no more than nine people (including the driver). Road network in good or fair condition is the length of the national road network, including the interurban classified network without the urban and rural network, that is in good or fair condition, as defined by each country’s road agency. Ratio of paved to total roads is the length of paved roads—which are those surfaced with crushed stone (macadam) and hydrocarbon binder or bituminized agents, with concrete, or with cobblestones—as a percentage of all the country’s roads. Price of diesel fuel and gasoline is the price as posted at filling stations in a country’s capital city. When several fuel prices for major cities Technical notes

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were available, the unweighted average is used. Since super gasoline (95 octane/A95/ premium) is not available everywhere, it is sometime replaced by regular gasoline (92 octane/A92), premium plus gasoline (98 octane/A98), or an average of the two. Committed nominal investment in transport projects with private participation is annual committed investment in transport projects with private investment, including projects for airport runways and terminals, railways (including fixed assets, freight, intercity passenger, and local passenger), toll roads, bridges, and tunnels. Official development assistance (ODA) gross disbursements for transportation and storage are disbursements for transportation and storage by bilateral, multilateral, and other donors. Disbursements record the actual international transfer of financial resources or of goods or services valued at the cost of the donor. Source: Data on length of road network and vehicle fleet are from the International Road Federation World Road Statistics and electronic files, except where noted. Data on rail lines and ratio of paved to total roads are from the World Bank Transportation, Water, and Information and Communications Technologies Department, Transport Division. Data on fuel and gasoline prices are from the German Agency for Technical Cooperation. Data on committed nominal investment in transport projects with private participation are from the World Bank Private Participation in Infrastructure Project Database (http:// ppi.worldbank.org). Data on official development assistance disbursements are from the Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database (www.oecd.org/dac/stats/idsonline). Table .. Information and communication technology Telephone subscribers are subscribers to a main telephone line service, which connects a customer’s equipment to the public switched telephone network or to a cellular telephone service. 158

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Unmet demand is the number of applications for connection to the public switched telephone network that have been held back because of a lack of technical facilities (equipment, lines, and the like) divided by the number of main telephone lines. Households with own telephone are the percentage of households possessing a telephone. Average delay for firm in obtaining a mainline phone connection is the average actual delay in days that firms experience when obtaining a telephone connection, measured from the day the establishment applied to the day it received the service or approval. Internet users are people with access to the Internet. Telephone faults are the total number of reported faults for the year divided by the total number of mainlines in operation multiplied by 100. The definition of fault can vary. Some countries include faulty customer equipment; others distinguish between reported and actual found faults. There is also sometimes a distinction between residential and business lines. Another consideration is the time period: some countries report this indicator on a monthly basis; in these cases data are converted to yearly estimates. Telephone faults cleared by next working day are the percentage of faults in the public switched telephone network that have been corrected by the end of the next working day. Fixed broadband Internet monthly subscription is the monthly subscription charge for fixed (wired) broadband Internet service. Fixed (wired) broadband is considered any dedicated connection to the Internet at downstream speeds equal to, or greater than, 256 kbit/s, using DSL. Where several offers are available, preference should be given to the 256 kbit/s connection. Taxes should be included. If not included, it should be specified in a note including the applicable tax rate. Cost of 3-minute fixed telephone local phone call during peak hours is the cost of a threeminute local call during peak hours. Local call refers to a call within the same exchange area using the subscriber’s own terminal (that is, not from a public telephone). Cost of 3-minute cellular local call during peak hours is the cost of a three-minute cellular local call during peak hours. Residential telephone connection charge is the initial, one-time charge involved in applying

for basic telephone service. Where charges differ by exchange areas, the charge reported is for the largest urban area. Business telephone connection charge is the one-time charge involved in applying for business basic telephone service. Where charges differ by exchange area, the charge reported is for the largest urban area. Mobile cellular prepaid connection charge is the initial, one-time charge for a new subscription. Refundable deposits should not be counted. Although some operators waive the connection charge, this does not include the cost of the Subscriber Identity Module (SIM) card. The price of the SIM card should be included in the connection charge (for a prepaid service the cost of SIM is equivalent to connection charge). It should also be noted if free minutes or free SMS are included in the connection charge. Taxes should be included. If not included, it should be specified in a note including the applicable tax rate. Mobile cellular postpaid connection charge is the initial, one-time charge for a new postpaid subscription. Refundable deposits should not be counted. Although some operators waive the connection charge, this does not include the cost of the SIM card. The price of the SIM card should be included in the connection charge. It should also be noted if free minutes or free SMS are included in the connection charge. Taxes should be included. If not included, it should be specified in a note including the applicable tax rate. Fixed broadband Internet connection charge is the initial, one-time charge for a new fixed (wired) broadband Internet connection. The tariffs should represent the cheapest fixed (wired) broadband entry plan. Refundable deposits should not be counted. Taxes should be included. If not included, it should be specified in a note including the applicable tax rate. Annual investment in fixed telephone service is the annual investment in equipment for fixed telephone service. Annual investment in mobile communication is the annual investment on equipment for mobile communication networks. Annual investment in telecommunications is the expenditure associated with acquiring the ownership of telecommunication equipment infrastructure (including supporting land and buildings and intellectual

and nontangible property such as computer software). It includes expenditure on initial installations and on additions to existing installations. Committed nominal investment in telecommunication projects with private participation is annual committed investment in telecommunication projects with private investment, including projects for fixed or mobile local telephony, domestic long-distance telephony, and international long-distance telephony. Official development assistance (ODA) gross disbursements for communication are disbursements for communication by bilateral, multilateral, and other donors. Disbursements record the actual international transfer of financial resources or of goods or services valued at the cost of the donor. Revenue from fixed telephone services is revenue received for the connection (installation) of telephone service (including charges for transferring or cancelling a service); revenue from recurring charges for subscription to telephone (and broadband and Internet access if not able to be separated from fixed telephone), including equipment rentals where relevant; and revenue from calls (local, national, and international). Revenue from mobile networks is revenue from the provision of mobile cellular communications services, including all voice and data (narrowband and broadband) services. It refers to revenue earned by retailers, not by wholesalers. Total revenue from all telecommunication services is the total (gross) telecommunication revenue earned from all (fixed, mobile, and data, including Internet) operators (both network and virtual) offering services within the country. It excludes revenues from nontelecommunications services as well as repayable subscribers’ contributions or deposits. It refers to revenue earned by retailers and by wholesalers. Source: Data on telephone subscribers, unmet demand, reported phone faults, cost of local and cellular calls, households with telephone, Internet users and pricing, telephone and Internet connection charges, and annual investment and revenue on telecommunications are from the International Telecommunications Union data files. Data on delays for firms in obtaining a telephone Technical notes

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connection are from World Bank Enterprise Surveys (http://www.enterpriseSurveys/). Data on committed nominal investment are from the World Bank Private Participation in Infrastructure Project Database (http:// ppi.worldbank.org). Data on oﬃcial development assistance disbursements are from the Development Assistance Committee of the Organisation for Economic Co-operation and Development Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database (www.oecd.org/dac/stats/idsonline). Table .. Energy Electricity production is measured at the terminals of all alternator sets in a station. In addition to hydropower, coal, oil, gas, and nuclear power generation, it covers generation by geothermal, solar, wind, and tide and wave energy, as well as that from combustible renewable and waste. Production includes the output of electricity plants that are designed to produce electricity only as well as that of combined heat and power plants. Hydroelectric refers to electricity produced by hydroelectric power plants. Coal refers to all coal and brown coal, both primary (including hard coal and lignite brown coal) and derived fuels (including patent fuel, coke oven coke, gas coke, coke oven gas, and blast furnace gas). Peat is also included. Natural gas refers to natural gas but excludes natural gas liquids. Nuclear refers to electricity produced by nuclear power plants. Oil refers to crude oil and petroleum products. Electric power consumption is the production of power plants and combined heat and power plants, less distribution losses and own use by heat and power plants. GDP per unit of energy use is nominal GDP in purchasing power parity (PPP) U.S. dollars divided by apparent consumption, which is equal to indigenous production plus imports and stock changes minus exports and fuels supplied to ships and aircraft engaged in international transport. Firms identifying electricity as major or very severe obstacle to business operation and growth are the percentage of ﬁrms that responded 160

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“major” or “very severe” to the following question: “Please tell us if any of the following issues are a problem for the operation and growth of your business. If an issue (infrastructure, regulation, and permits) poses a problem, please judge its severity as an obstacle on a five-point scale that ranges from 0 = no obstacle to 5 = very severe obstacle.” Average delay for firm in obtaining electrical connection is the average actual delay in days that firms experience when obtaining an electrical connection, measured from the day the establishment applied to the day it received the service or approval. Electric power transmission and distribution losses are technical and nontechnical losses, including electricity losses due to operation of the system and the delivery of electricity as well as those caused by unmetered supply. This comprises all losses due to transport and distribution of electrical energy and heat. Electrical power outages in a typical month is the average number of electrical power outages in a typical month. Firms that share or own their own generator are the percentage of firms that responded “Yes” to the following question: “Does your establishment own or share a generator?” Firms using electricity from generator are the percentage of firms using electricity supplied from a generator or generators that the firm owns or shares. Committed nominal investment in energy projects with private participation is annual committed investment in energy projects with private investment, including projects for electricity generation, transmission, and distribution as well as natural gas transmission and distribution. Official development assistance (ODA) gross disbursements for energy are disbursements for energy by bilateral, multilateral, and other donors. Disbursements record the actual international transfer of financial resources or of goods or services valued at the cost of the donor. Source: Data on electricity production and consumption are from the International Energy Agency (www.iea.org/stats/index.asp), Energy Statistics of Non-OECD Countries, Energy Balances of Non-OECD Countries, Energy Statistics of OECD Countries, and Energy Balances of OECD Countries. Data on PPP GDP

per unit of energy use are from the International Energy Agency (www.iea.org/stats/ index.asp) and World Bank PPP data. Data on solid fuels use are from household survey data, supplemented by World Bank Project Appraisal Documents. Data on firms identifying electricity as a major or very severe obstacle to business operation and growth, delays for firms in obtaining an electrical connection, electrical outages of firms, firms that share or own their own generator, and firms using electricity from generator are from World Bank Enterprise Surveys (http:// www.enterpriseSurveys/). Data on transmission and distribution losses are from the International Energy Agency (www.iea.org/ stats/index.asp), Energy Statistics of NonOECD Countries, Energy Balances of NonOECD Countries, Energy Statistics of OECD Countries, and Energy Balances of OECD Countries and the United Nations Energy Statistics Yearbook. Data on committed nominal investment are from the World Bank Private Participation in Infrastructure Project Database (http://ppi.worldbank.org). Data on official development assistance disbursements are from the Development Assistance Committee of the Organisation for Economic Co-operation and Development Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database (www.oecd.org/dac/stats/idsonline). 7. Human development Table .. Education Youth literacy rate is the percentage of people ages 15–24 who can, with understanding, both read and write a short, simple statement about their everyday life. Adult literacy rate is the proportion of adults ages 15 and older who can, with understanding, read and write a short, simple statement on their everyday life. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music. Secondary education completes the provision of basic education that began at the primary level and aims to lay the foundations for lifelong learning and human development

by offering more subject- or skill-oriented instruction using more specialized teachers. Tertiary education, whether or not at an advanced research qualification, normally requires, as a minimum condition of admission, the successful completion of education at the secondary level. Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Net enrollment ratio is the ratio of children of official school age based on the International Standard Classification of Education 1997 who are enrolled in school to the population of the corresponding official school age. Student-teacher ratio is the number of students enrolled in school divided by the number of teachers, regardless of their teaching assignment. Public spending on education is current and capital public expenditure on education plus subsidies to private education at the primary, secondary, and tertiary levels by local, regional, and national government, including municipalities. It excludes household contributions. Source: United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics. Table .. Health Life expectancy at birth is the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to remain the same throughout its life. Data are World Bank estimates based on data from the United Nations Population Division, the United Nations Statistics Division, and national statistical offices. Under-five mortality rate is the probability that a newborn baby will die before reaching age 5, if subject to current age-specific mortality rates. The probability is expressed as a rate per 1,000. Infant mortality rate is the number of infants dying before reaching 1 year of age, per 1,000 live births. Maternal mortality ratio, modeled estimate, is the number of women who die from pregnancy-related causes during pregnancy and childbirth, per 100,000 live births. The data are estimated by a regression model using Technical notes

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Gender The 2012 World Development Report documents four central challenges to gender equality in Africa: reducing excess female mortality, closing gaps in earnings and productivity, shrinking differences in voice in households and society, and investing in youth to break intergenerational cycles of gender inequality. While the following box discusses the issue of mortality, here we explore the other three dimensions. Gaps in earnings and productivity Although many more women have joined the labor force throughout the developing world in the past 25 years, access to employment has led to neither equitable opportunities nor equitable earnings between women and men. There is considerable gender segregation in accessing labor force opportunities—women are more likely to work in low-productivity sectors, less-profitable areas, wage or unpaid family employment, or the informal wage sector. In agriculture, women have less access to inputs and manage smaller plots of land, particularly in Sub-Saharan Africa. There are three main factors that lead to gender segregation among female farmers, entrepreneurs, and wage workers: (1) gender differences in time use (primarily resulting from differences in care responsibilities); (2) gender differences in access to productive inputs (particularly land and credit); and (3) gender differences stemming from market and institutional failures. Employment: In Sub-Saharan Africa, firms managed by women have labor productivity 6 to 8 percent lower than firms managed by men. This number prevails when compared with Europe and Central Asia, where it is 34 percent lower, and in Latin America, where value added per worker is 35 percent lower in firms managed by women. The performance lag of female-owned firms is related to market segregation, where women are often constrained to less-productive sectors. For example, industry type accounts for 9 to 14 percent of the gender differential in earnings for self-employed workers. For formal firms in urban areas of SubSaharan Africa, this difference in operational sector accounts for more than 20 percent of the gap, while the size of the firm accounts for another 30 percent. Women are also overrepresented among unpaid and wage workers and in the informal sector. The region has the highest rate of unpaid female family workers, at 65 percent of total employed women. Eliminating barriers that prevent women from working in certain occupations or sectors would reduce the productivity gap between male and female workers by one-third to one-half and increase output per worker by 3 to 25 percent across a range of Sub-Saharan Africa countries. Agricultural productivity: Though 44 percent of Sub-Saharan Africa’s agricultural labor force is comprised of women, female farmers in the region are less productive than male farmers, likely due to limited access to inputs including fertilizer, seed variety, as well as substantial plots of land, credit, and extension services. Productivity on farms would increase between 10 and 30 percent if women were provided with equal access to inputs. If women were granted equal access to inputs and more secure access to

Prepared by Markus Goldstein land, gender gaps in agricultural production would disappear and yields on women’s farms would increase by 14 percent in Malawi, 17 percent in Ghana, 20 percent in Kenya, and 21 percent in Benin. Policy case study: For female farmers in Sub-Saharan Africa, barriers to land tenure significantly limit productive potential. Rwanda’s nationwide Land Tenure Regularization (LTR) program is one of a few models to address this issue at the required scale. An impact evaluation of a pilot version of this program highlights three main gender-specific effects: (1) significant and large investment impacts that are particularly pronounced for women. Households affected by LTR are almost 10 percentage points more likely to make or maintain soil conservation investments in structures such as bunds, terraces, and check dams. Women seem to benefit more in this respect; estimated effects of LTR on such investment by female-headed households is double that of men, with female-headed households exhibiting a roughly 19 percentagepoint increase in the construction or maintenance of these soil conservation structures. Another main gender-specific effect is (2) improved land access for legally married women and better recording of inheritance rights. For women who are part of a union formalized through a marriage certificate, the effect of the program is overwhelmingly positive—they are 17 percentage points more likely to be regarded as joint landowners after LTR than before. The final gender-specific effect is (3) a significant increase in the probability of having documented landownership for legally married women. For women who are married but do not have a legal certificate, LTR results in a small but statistically significant reduction (by 8 percentage points) of the probability of having documented landownership. Taken together, these impacts imply that women’s investments were especially hindered by a lack of tenure security, and that programs such as LTR can effectively remove this barrier. Shrinking differences in voice in the household and society Agency or voice is demonstrated through (1) control over resources—indicated by women’s ability to earn and control income and to own, use, and dispose of material assets; (2) ability to move freely—indicated by women’s freedom to decide their movements and their ability to move outside their homes; (3) decision making over family formation—measured by women’s and girls’ ability to decide when and whom to marry, when and how many children to have, and when to leave a marriage; (4) freedom from the risk of violence—indicated by the prevalence of domestic violence and other forms of sexual, physical, or emotional violence; and (5) the ability to have a voice in society and influence policy—indicated by participation and representation in formal politics and engagement in collective action and associations. Women’s earnings opportunities and owned assets promote their bargaining power within and outside of households. Decision making: Of the 48 countries in the region, 15 still have laws that give husbands most of the control over marital assets. Although women’s control is greater in wealthier households, the region still has the lowest share of women with some control (continued)

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Gender (continued) over decisions when it pertains to the issues of large purchases and visits to relatives. Sub-Saharan Africa also exhibits one of the highest shares of women who do not have control over decisions regarding how their own earnings are used —ranging from 34 percent of women in Malawi to 28 percent of women in the Democratic Republic of Congo. Decision-making roles outside of the household vary for women in the region and are heavily correlated with levels of education and affluence. Sub-Saharan Africa has a higher rate of female political-party membership when compared with the Middle East and North Africa, Latin America and the Caribbean, East Asia, and in OECD countries. The average rate of female parliamentarians in the region is 20 percent, and the global rate is 19 percent. Inheritance: Thirty-four percent of daughters have unequal inheritance, and 7 percent have customary inheritance. Forty-six percent of widows have unequal inheritance, and 10 percent of widows have customary inheritance. In South Asia, this number for both daughters and widows is 50 percent; in OECD countries, Latin America and the Caribbean, and Europe and Central Asia, all daughters and widows have equal inheritance. Gender-based violence: Violence is also a persistent issue, as, for example, 81 percent of women in Ethiopia think it is acceptable for a husband to beat his wife if the food is burned, she argues with him, or she refuses to have sex with him, and 37 percent of women in Cameroon report their first sexual intercourse as forced. Domestic violence results largely from a combination of strong social norms surrounding power within households as well as from women’s limited bargaining power in their households. Additionally, lack of awareness and biased services limit women’s demand for justice. Investing in youth to break the intergenerational cycles of gender inequality Girls’ early and risky sexual activity and low education levels, along with institutionalized inequality, mutually reinforce a cycle of gender inequality. Fertility: Currently, the fertility rate for youth between the ages of 15 and 19 in the region is 108 births per 1,000 girls, representing the highest rate of any region and nearly double the global average of 53. In East Asia, this number is 19 births per 1,000 women, and in South Asia, it is 75 births per 1,000 women. Approximately

information on fertility, birth attendants, and HIV prevalence. Prevalence of HIV is the percentage of people ages 15–49 who are infected with HIV. Incidence of tuberculosis is the number of tuberculosis cases (pulmonary, smear positive, and extrapulmonary) in a population at a given point in time, per 100,000 people. This indicator is sometimes referred to as “point prevalence.” Estimates include cases of tuberculosis among people with HIV.

22 percent of all women between the ages of 15 and 49 use contraception, and a little more than half of that number of girls between the ages of 15 and 24 use condoms. Young females in SubSaharan Africa are almost two-and-a-half times more likely to be infected with HIV than their male counterparts. For adolescents, the promotion of contraception, when combined with education interventions and skill building, and appropriately targeted to cultural and social settings, has been effective in reducing unplanned pregnancies. Education: While the ratio of females to males in primary school in the region decreased between 1990 and 2008 (from 0.78 to 0.91), girls in areas such as Central and West Africa, where the ratio is 8 to 10, are lagging behind. Gross secondary enrollment rates for women is 32 percent, compared with 40 percent for men; and for tertiary education, it is 5 percent compared to 8 percent of men. Policy case study: The Empowerment and Livelihood for Adolescents (ELA) program in Uganda—which includes girls’ clubs, life skills, and livelihoods training—aims to reach out to youth and disrupt this cycle of gender inequality. Preliminary evidence from a randomized evaluation suggests that the program improves girls’ health choices, their voice, and their economic activity. Compared with girls who did not participate in the program after two years, girls in program villages were 30 percent more likely to be working, they were 75 percent less likely to have had sex against their will, and they were 30 percent less likely to have had a child. Importantly, these improvements were achieved without increasing the school dropout rate or reducing time spent studying. Moving forward In all of the four priority areas, mechanisms have been identified that effectively address the existing gender disparities and thus provide potential solutions to close these gaps. Unfortunately, however, questions on how to best apply these solutions still remain unanswered. For example, we know that adequate and prompt medical attention reduces maternal mortality considerably, but we do not know how to enable mothers at risk to reach a functioning clinic in time. Programs such as ELA in Rwanda and LTR in Uganda are shedding light on what works best to address key gender inequalities in Sub-Saharan Africa, but more work needs to be done to identify innovative and effective programs.

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Gender Differences in Risks of Death: Africa’s Excess Female Mortality and Trends over Time The facts on dying and death in low-income countries In Iceland, 56 of every 1,000 people will die between the ages of 15 and 60; in the United States, that figure is 107. In China, that number rises to 113 and in India to 213. In Central and West Africa, these mortality rates regularly exceed 300, and in many countries it is closer to 400. And in HIV/AIDS-affected countries, the numbers rise to between 481 (Malawi) and 772 (Zimbabwe). Compare that to war-torn countries such as Iraq (285) or Afghanistan (479). Starkly put, the risk of dying for adults in many Sub-Saharan African countries is higher than being in the midst of a full-blown conflict. In Sub-Saharan Africa, over time, trends in adult mortality have diverged sharply from those in the rest of the world. Here are the patterns: • Infant and early childhood mortality (under-five mortality) has declined as in other parts of the world, although the rate of decline has been slower. • In other countries, adult mortality rates have remained roughly stable over the past 25 years, but they doubled between 1980 and 2000 in Sub-Saharan Africa. A large portion of this increase is attributable to HIV/AIDS, with adult mortality rates in high-HIV-prevalence countries reaching more than half the levels seen in the years of the genocides in Rwanda and Cambodia—but on a sustained and rising basis. • Particularly surprising is the fact that adult mortality did not decrease, and actually increased, in several countries in SubSaharan Africa with low HIV/AIDS prevalence, particularly those in Central and West Africa. In 2008, the 14 countries with the highest adult mortality risk for women globally (in descending order) were Zimbabwe, Lesotho, Swaziland, Zambia, South Africa, Malawi, the Central African Republic, Mozambique, Tanzania, Chad, Uganda, Cameroon, Burundi, and Nigeria. Afghanistan comes in at number 15 and Pakistan at number 64. For child mortality (under five, per 1,000 births), the worst places for girls (in descending order) were Afghanistan, Angola, Chad, Somalia, Mali, the Democratic Republic of the Congo, Nigeria, Sierra Leone, Guinea-Bissau, the Central African Republic, Burkina Faso, Niger, Burundi, Equatorial Guinea, and Liberia. By 2008, many African countries have become among the least hospitable places for women to live. The sex mortality rate Figure 1 presents the sex mortality rate (SMR), defined as the ratio of male to female mortality at every age for six African countries— South Africa and Kenya, with high HIV prevalence, Ethiopia and Eritrea with outright conflict between 1998 and 2000, and Nigeria and Burkina Faso in the western region of the continent. To interpret the SMR, it is useful to compare it to what we see in OECD countries (the thick black line in all of the figures). In OECD countries, men die at a faster rate than women throughout the life cycle (the SMR is above 1). This differential rate peaks around the early

Prepared by Rabia Ali and Jishnu Das

20s, when accidents, violence, drugs, and homicides disproportionately affect men. It then declines and slowly increases again around the 60s, potentially a legacy of differential smoking rates between men and women in these countries. South Africa looked precisely like the OECD countries in 1990, perhaps with even a higher SMR in the early 20s. By 2000, South Africa’s SMR had changed completely as HIV/AIDS-related mortality sharply increased. Although both men and women were affected, the rate at which women started dying relative to men increased very rapidly, and the groups hit hardest were between the ages of 15 and 50. By 2008, things had gotten even worse. Kenya saw a similar decline in the SMR, but there is no evidence of worsening between 2000 and 2008. Ethiopia’s SMR looks very much like that in several countries around the continent: In contrast to OECD countries, in 1990, women were dying at a higher rate relative to men from the age of 5 onward, almost to age 40 (SMR <1). The SMR has increased quite dramatically since 1990, in particular for those between 15 and 25, reflecting lower mortality risks for women. Eritrea’s SMR looks similar, except for the giant hump in 2000, reflecting the conflict with Ethiopia. The SMR shoots up from about 1 in the 20to-40 age group to a peak of 10, as men died at disproportionately large numbers in the war. It comes back down by 2008, but data for 1990 and 2008 look similar. Finally, Burkina Faso and Nigeria remain very puzzling. Like Ethiopia’s SMR in 1990, their SMR drops below 1 from the age of 5 onward and never really recovers until around 40, after which it hovers just above 1. A couple of things are truly worrying: First, the SMR dips down to below 0.5 at the age of 18. Why is late adolescence such a dangerous time for women in terms of mortality risks? Second, there has been no change since 1990; if anything, the SMR between 20 and 60 appears to have constantly declined. Excess female mortality in Sub-Saharan Africa Given these very different patterns, figure 2 presents additional information by adding in mortality risks—that is, we would perhaps worry less about Nigeria and Burkina Faso if between 1990 and 2008 the mortality risk had declined, but stable mortality risks and a worsening SMR imply a more risky environment for women. To present mortality risks in an easily comprehensible fashion, the World Development Report 2012 (2012 WDR) computed two measures. Missing girls at birth were estimated through comparisons of the sex ratio at birth in countries around the world with those in comparable populations with no discrimination. The report also computed excess female (and male) mortality by comparing the mortality risks of women relative to men in every country and every age with those seen in developed economies today—the “reference population”—using methods advanced by Anderson and Ray (2010). In essence, this method weights the difference between each country SMR and the OECD SMR in 2000 by the mortality risk and the overall populations to arrive at a single number for excess female mortality at every age. (continued)

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Gender Differences in Risks of Death: Africa’s Excess Female Mortality and Trends over Time (continued)

South Africa

3.0

Male mortality divided by female mortality

Figure 1. Sex ratios of mortality in six African countries Age-specific male mortality divided by female mortality

2.5 2.0 1.5 1.0 0.5 0

40 1990

Age 2000

1.5 1.0 0.5 40

80 2008

2.0 1.5 1.0 0.5 20

40 1990

Age 2000

80 2008

100 High-income countries

Age 2000

100 High-income countries

2008

Etritrea

10 8 6 4 2 0 0

High-income countries

2.5

0.5

100

40 1990

Nigeria

3.0

1.0

1990

Male mortality divided by female mortality

1990

Age 2000

1.5

Male mortality divided by female mortality

2.0

High-income countries

2008

2.5

100

Ethiopia

3.0

Kenya

3.0

Age 2000

100 High-income countries

2008

Burkino Faso

3.0 2.5 2.0 1.5 1.0 0.5 0

40 1990

Age 2000

80 2008

100 High-income countries

Note: A sex ratio of mortality (SRM) above the black dashed line indicates excess male mortality while an SRM below the line indicates excess female mortality.

Computations based on this excess mortality measure, conducted for all countries around the world at three points in time (1990, 2000, and 2008), suggested that missing girls at birth and excess female mortality after birth add up to more than 6 million women a year. While missing girls at birth are concentrated in India and China, excess female mortality after birth is highest in SubSaharan Africa, the only region where the numbers are increasing. These three population groupings—China (with a population of 1.3 billion), India (1.15 billion), and Sub-Saharan Africa (0.8 billion)— together account for 87 percent of the world’s missing girls and excess female mortality.

But the age profiles of excess female mortality are very different. In Sub-Saharan Africa—a point raised by Anderson and Ray (2010) and Obermeyer and others (2010)—excess female mortality in the reproductive years accounts for 78 percent in the high-HIV/ AIDS-prevalence countries and 55 percent in countries with low HIV rates. In China, by contrast, most excess female mortality is at birth, and in India, missing girls at birth and excess female mortality in early childhood and in the reproductive years each account for roughly a third. As figure 2 shows, Sub-Saharan Africa is the only region in the world where excess female mortality increased between 1990 and 2008—both absolutely (from 0.6 million a year to 1.1 million) and as a fraction of the female population. Among (continued)

Technical notes

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Gender Differences in Risks of Death: Africa’s Excess Female Mortality and Trends over Time (continued) women ages 15 to 50, excess female mortality has declined in absolute numbers and as a proportion of population in every region of the world except Sub-Saharan Africa, where four distinct patterns have emerged:

HIV/AIDS-affected countries: In these countries, excess female mortality has increased even as a fraction of the female population. Examples include Botswana, Lesotho, Swaziland, South Africa, Zambia, and Zimbabwe, where about one in six to

Figure 2. Excess female mortality across the world Excess female deaths after birth and change in excess female morality between 1990 and 2008

Excess female deaths in 2008 per 100,000 female population 0–100 100–300 300–600 No data

EXCESS FEMALE DEATHS AFTER BIRTH

Reference countries

Change in excess female deaths per 100,000 female population, 1990–2008 -300–0 0–300 300–600 No data

EXCESS FEMALE DEATHS AFTER BIRTH

Reference countries

(continued)

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Gender Differences in Risks of Death: Africa’s Excess Female Mortality and Trends over Time (continued) one in four adults between the ages of 15 and 49 were living with HIV/AIDS by the end of 2009. In 1990, mortality profiles for men and women in Botswana and South Africa were similar to those in high-income countries today. But by 2000, mortality risks increased in adulthood, more so for women. Progressive Africa: In countries such as Ethiopia, Ghana, and Madagascar, which have largely escaped the HIV/AIDS epidemic, excess female mortality has been decreasing over time. Mortality rates of children under age five are about 100 per 1,000 live births (less than 76 in Ghana). Fertility rates have declined, but they remain higher than in India and Pakistan, as do underfive mortality rates. Conflict Africa: Sub-Saharan Africa has experienced two types of conflicts over the past three decades, with different implications for mortality risks among men and women. During the 1980s and 1990s, outright war in countries like Eritrea and Liberia claimed the lives of many young men, leading to excess male mortality. Except for periodic flare-ups, these decreased over time. In other countries, widespread civil conflict continues to exact a heavy toll among women, leading to excess female mortality. One example is the Democratic Republic of Congo, where excess female mortality increased between 1980 and 2008. Central and West Africa: The real puzzles in Sub-Saharan Africa are the Central and West African countries, including Burkina Faso, Chad, Mali, Niger, and Nigeria, among others. These countries have largely escaped the HIV/AIDS epidemic and are relatively free of conflict, but excess female mortality has increased over time, as mortality risks for women systematically increased while overall mortality risks remained unchanged or worsened. Today, Burkina Faso, the Central African Republic, Chad, Mali, Niger, and Nigeria look very much like Afghanistan in their human development outcomes, including mortality risks. Under-five mortality ranges from 170 to 220 (Afghanistan is higher, at 257), total fertility rates range from 4.5 to above 7 (Afghanistan is 6.6), and adult mortality risks are virtually the same as those in Afghanistan.

cases; most health facilities lack appropriate diagnostic services. The misdiagnosis may have led to under- or overreporting malaria cases and missing diagnosis of other treatable diseases. Reported malaria deaths are all deaths in health facilities that are attributed to malaria, whether or not conﬁrmed by microscopy or by rapid diagnostic test. Child immunization rate is the percentage of children ages 12–23 months who received vaccinations before 12 months or at any time before the survey for four diseases—measles and diphtheria, pertussis (whooping cough), and tetanus (DPT). A child is considered adequately immunized against measles after

Drivers of excess female mortality in the reproductive years Maternal mortality: Higher maternal mortality ratios are historically associated with greater excess female mortality in adulthood, as the 2012 WDR illustrated using excess female mortality estimates for 13 high-income countries today, in some cases going as far back in time as 1800. In 2008, there were 203,300 maternal deaths in Sub-Saharan Africa (56.7 percent of the global total). One of every 14 women in Somalia and Chad will die from causes related to childbirth. As a proportion of all births, more women die in childbirth in Liberia today than did in Sweden in the 17th century. Reducing these high maternal mortality ratios in Sub-Saharan Africa will be critical for reducing excess female mortality in adulthood. The HIV/AIDS epidemic: In addition to maternal mortality, the HIV/AIDS epidemic is contributing to excess female mortality in Africa, where women account for 60 percent of all adult HIV infections, with the gender gap in prevalence largest for younger adults. The ratio of female-to-male prevalence for 15- to 24-yearolds is 2.4 across Sub-Saharan Africa. Not only has HIV/AIDS hit women the hardest, but coping with the crisis has had systemwide impacts on the delivery of health services. Prenatal care, care during birth, and children’s vaccination rates have suffered where HIV rates are the highest in Sub-Saharan Africa. Improved access to Anti-Retroviral Therapy (ART) in Africa will reduce the number of deaths from HIV/AIDS and decrease female mortality rates in adulthood. Further research: As seen above, the HIV/AIDS link to excess female mortality in Africa is not relevant for all countries in the region but is concentrated among the set of high-prevalence countries in southern Africa and parts of east Africa, which bear a disproportionate share of the burden of AIDS in Africa as well as globally. Central and West African countries do not belong in this category, and further research is direly needed to understand why these countries have experienced such little progress in reducing mortality risks, and why these have increased for women relative to men.

receiving one dose of vaccine and against DPT after receiving three doses. Stunting is the percentage of children under age 5 whose height for age is more than two standard deviations below the median for the international reference population ages 0–59 months. For children up to age 2 height is measured by recumbent length. For older children height is measured by stature while standing. The data are based on the WHO’s new child growth standards released in 2006. Underweight is the percentage of children under age 5 whose weight for age is more than two standard deviations below the median for the international reference Technical notes

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population ages 0–59 months. The data are based on the WHO’s new child growth standards released in 2006. Births attended by skilled health staff are the percentage of deliveries attended by personnel trained to give the necessary supervision, care, and advice to women during pregnancy, labor, and the postpartum period; to conduct deliveries on their own; and to care for newborns. Contraceptive use is the percentage of women ages 15–49, married or in union, who are practicing, or whose sexual partners are practicing, any form of contraception. Modern methods of contraception include female and male sterilization, oral hormonal pills, the intrauterine device, the male condom, injectables, the implant (including Norplant), vaginal barrier methods, the female condom, and emergency contraception. Children sleeping under insecticide-treated nets are the percentage of the children under age 5 with access to an insecticide-treated net to prevent malaria. Tuberculosis case detection rate (all forms) is the percentage of newly notiﬁed tuberculosis cases (including relapses) to estimated incident cases (case detection, all forms). Tuberculosis treatment success rate is the percentage of new smear-positive tuberculosis cases registered under DOTS in a given year that successfully completed treatment, whether with bacteriologic evidence of success (“cured”) or without (“treatment completed”). Children with fever receiving any antimalarial treatment same or next day are the percentage of children under age 5 in malaria-risk areas with fever being treated with any antimalarial drugs. Population with sustainable access to an improved water source is the percentage of the population with reasonable access to an adequate amount of water from an improved source, such as a household connection, public standpipe, borehole, protected well or spring, or rainwater collection. Unimproved sources include vendors, tanker trucks, and unprotected wells and springs. Reasonable access is deﬁned as the availability of at least 20 liters a person a day from a source within one kilometer of the dwelling. Population with sustainable access to improved sanitation is the percentage of the 168

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population with at least adequate access to excreta disposal facilities that can effectively prevent human, animal, and insect contact with excreta. Improved facilities range from simple but protected pit latrines to flush toilets with a sewerage connection. The excreta disposal system is considered adequate if it is private or shared (but not public) and if it hygienically separates human excreta from human contact. To be effective, facilities must be correctly constructed and properly maintained. Physicians are the number of physicians, including generalists and specialists. Nurses and midwives are professional nurses, auxiliary nurses, enrolled nurses, and other nurses, such as dental nurses and primary care nurses, and professional midwives, auxiliary midwives, and enrolled midwives. Community workers include various types of community health aides, many with countryspecific occupational titles such as community health officers, community healtheducation workers, family health workers, lady health visitors, and health extension package workers. Total health expenditure is the sum of public and private health expenditure. It covers the provision of health services (preventive and curative), family planning activities, nutrition activities, and emergency aid designated for health but does not include provision of water and sanitation. Public health expenditure consists of recurrent and capital spending from government (central and local) budgets, external borrowings and grants (including donations from international agencies and nongovernmental organizations), and social (or compulsory) health insurance funds. Private health expenditure includes direct household (out-of-pocket) spending, private insurance, charitable donations, and direct service payments by private corporations. External resources for health are funds or services in kind that are provided by entities not part of the country in question. The resources may come from international organizations, other countries through bilateral arrangements, or foreign nongovernmental organizations. These resources are part of total health expenditure. Out-of-pocket expenditure is any direct outlay by households, including gratuities and

in-kind payments, to health practitioners and suppliers of pharmaceuticals, therapeutic appliances, and other goods and services whose primary intent is to contribute to the restoration or enhancement of the health status of individuals or population groups. It is a part of private health expenditure. Private prepaid plans are expenditure on health by private insurance institutions. Private insurance enrollment may be contractual or voluntary, and conditions and benefits or basket of benefits are agreed on a voluntary basis between the insurance agent and the beneficiaries. They are thus not controlled by government units for the purpose of providing social benefits to members. Health expenditure per capita is the total health expenditure. It is the sum of public and private health expenditures as a ratio of total population. It covers the provision of health services (preventive and curative), family planning activities, nutrition activities, and emergency aid designated for health but does not include provision of water and sanitation. Data are in current U.S. dollars. Source: Data on life expectancy at birth, national maternal mortality, prevalence of HIV, incidence of tuberculosis, child immunization, malnutrition, births attended by skilled health staff, contraceptive use, children sleeping under insecticide-treated nets, and children receiving antimalarial drugs are from World Bank staff estimates based on various sources, including census reports, the United Nations Population Division’s World Population Prospects, national statistical offices, household surveys conducted by national agencies and Macro International, the World Health Organization (WHO), and the United Nations Children’s Fund. Data on under-five and infant mortality are from the from Level & Trends in Child Mortality. Report 2011. Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation (UNICEF, WHO, World Bank, UN DESA, UNPD). Data on maternal mortality (modeled) are Trends in Maternal Mortality: 1990–2010 estimates developed by WHO, UNICEF, UNFPA, and the World Bank. Data on clinical malaria cases reported and reported malaria deaths are from WHO’s World Malaria Report 2011. Data on physicians, nurses, and community health workers are from World Health

Organization, Global Atlas of the Health Workforce. For latest updates and metadata, see http://apps.who.int/globalatlas/. Data on tuberculosis are from World Health Organization, Global Tuberculosis Control Report. Data on access to water and sanitation are from World Health Organization and United Nations Children’s Fund, Joint Measurement Programme (JMP) (www.wssinfo.org/). Data on health expenditure are from the World Health Organization National Health Account database (www.who.int/nha/en) supplemented by country data. 8. Agriculture, rural development, and environment Table .. Rural development Rural population is the difference between the total population and the urban population. Rural population density is the rural population divided by the arable land area. Arable land includes land defined by the Food and Agriculture Organization (FAO) as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded. Share of rural population below the national poverty line is the percentage of the rural population living below the national poverty line. Rural population poverty gap is the mean shortfall from the poverty line (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence. Share of rural population with sustainable access to an improved water source is the percentage of the rural population with reasonable access to an adequate amount of water from an improved source, such as a household connection, public standpipe, borehole, protected well or spring, or rainwater collection. Unimproved sources include vendors, tanker trucks, and unprotected wells and springs. Reasonable access is defined as the availability of at least 20 liters a person a day from a source within 1 kilometer of the dwelling. Share of rural population with sustainable access to improved sanitation facilities is the percentage of the rural population with at least Technical notes

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adequate access to excreta disposal facilities that can effectively prevent human, animal, and insect contact with excreta. Improved facilities range from simple but protected pit latrines to flush toilets with a sewerage connection. The excreta disposal system is considered adequate if it is private or shared (but not public) and if it hygienically separates human excreta from human contact. To be effective, facilities must be correctly constructed and properly maintained. Share of rural population with access to transportation is the percentage of the rural population who live within 2 kilometers of an allseason passable road as a share of the total rural population. Source: Data on rural population are calculated from urban population shares from the United Nations Population Division’s World Urbanization Prospects and from total population figures from the World Bank. Data on rural population density are from the FAO and World Bank population estimates. Data on rural population below the poverty line and rural population poverty gap are Global Poverty Working Group. Data are based on World Bank’s country poverty assessments and country Poverty Reduction Strategies. Data on access to water and sanitation are from the World Health Organization and United Nations Children’s Fund, Joint Measurement Programme (JMP) (www.wssinfo.org/). Table .. Agriculture Agriculture value added is the gross output of forestry, hunting, and fishing, as well as cultivation of crops and livestock production (International Standard Industrial Classification [ISIC] revision 3 divisions 1–5) less the value of their intermediate inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural resources. For countries that report national accounts data at producer prices (Angola, Benin, Cape Verde, Comoros, the Republic of Congo, Côte d’Ivoire, Gabon, Liberia, Niger, Rwanda, São Tomé and Príncipe, Seychelles, and Togo), gross value added at market prices is used as the denominator. For countries that report national accounts data at basic prices (all other countries), gross value added at factor cost is used as the denominator. Value added at 170

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basic prices excludes net taxes on products, while producer prices include net taxes on products paid by producers but exclude sales or value added taxes. Total agriculture gross production index is total agricultural production relative to the base period 1999–2001. Crop gross production index is agricultural crop production relative to the base period 1999–2001. It includes all crops except fodder crops. Livestock gross production index covers meat and milk from all sources, dairy products such as cheese, and eggs, honey, raw silk, wool, and hides and skins. Food gross production index covers food crops that are considered edible and that contain nutrients. Coffee and tea are excluded because, although edible, they have no nutritive value. Cereal gross production index covers cereals that are considered edible and that contain nutrients. Cereal production is crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded. Cereal includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Agricultural exports and imports are expressed in current U.S. dollars at free on board prices. The term “agriculture” in trade refers to both food and agriculture and does not include forestry and fishery products. Food exports and imports are expressed in current U.S. dollars at free on board prices for exports and cost, insurance, and freight prices for imports. Permanent cropland is land cultivated with crops that occupy the land for long periods and need not be replanted after each harvest, such as cocoa, coffee, and rubber. It includes land under flowering shrubs, fruit trees, nut trees, and vines, but excludes land under trees grown for wood or timber. Cereal cropland refers to harvested area, although some countries report only sown or cultivated area. Agricultural irrigated land is areas equipped to provide water to the crops, including areas equipped for full and partial control irrigation, spate irrigation areas, and equipped wetland or inland valley bottoms.

Fertilizer consumption measures the quantity of plant nutrients used per unit of arable land. Fertilizer products cover nitrogenous, potash, and phosphate fertilizers (including ground rock phosphate). Traditional nutrients—animal and plant manures—are not included. For the purpose of data dissemination, the FAO has adopted the concept of a calendar year (January to December). Some countries compile fertilizer data on a calendar year basis, while others are on a splityear basis. Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded. Agricultural machinery refers to the number of wheel and crawler tractors (excluding garden tractors) in use in agriculture at the end of the calendar year specified or during the first quarter of the following year. Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded. Agricultural employment includes people who work for a public or private employer and who receive remuneration in wages, salary, commission, tips, piece rates, or pay in kind. Agriculture corresponds to division 1 (International Standard Industrial Classification [ISIC] revision 2) or tabulation categories A and B (ISIC revision 3) and includes hunting, forestry, and fishing. Agriculture value added per worker is the output of the agricultural sector (ISIC divisions 1–5) less the value of intermediate inputs. Agriculture comprises value added from forestry, hunting, and fishing as well as cultivation of crops and livestock production. Data are in constant 2000 U.S. dollars. Cereal yield, measured as kilograms per hectare of harvested land, includes wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded. The

FAO allocates production data to the calendar year in which the bulk of the harvest took place. Most of a crop harvested near the end of a year will be used in the following year. Source: Data on agriculture value added are from World Bank national accounts data, and OECD National Accounts data files. Data on crop, livestock, food, and cereal production, cereal exports and imports, agricultural exports and imports, permanent cropland, cereal cropland, agricultural machinery, cereal yield, and fertilizer consumption are from the Food and Agriculture Organization, electronic files and web site. Data on agricultural employment are from the International Labour Organization, Key Indicators of the Labour Market database. Table .. Producer food prices Prices in U.S. dollars are equal to producer prices in local currency times the exchange rate of the selected year. The main exchange rates source used is the IMF. Where official and commercial exchange rates differ significantly, the commercial exchange rate may be applied. Producer prices are prices received by farmers for primary agricultural products as defined in the SNA 93. The producer’s price is the amount receivable by the producer from the purchaser for a unit of a good or service produced as output minus any value added tax, or similar deductible tax, invoiced to the purchaser. It excludes any transport charges invoiced separately by the producer. Time series refer to the national average prices of individual commodities comprising all grades, kinds and varieties, received by farmers when they participate in their capacity as sellers of their own products at the farm gate or first-point-of-sale. Source: Data are from the Food and Agriculture Organization, electronic files and website. Table .. Environment Forest area is land under natural or planted stands of trees, whether productive or not. Renewable internal fresh water resources refer to internal renewable resources (internal river flows and groundwater from rainfall) in the country. Annual fresh water withdrawals refer to total water withdrawals, not counting evaporation Technical notes

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losses from storage basins. Withdrawals also include water from desalination plants in countries where they are a significant source. Withdrawals can exceed 100 percent of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is significant water reuse. Withdrawals for agriculture and industry are total withdrawals for irrigation and livestock production and for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking water, municipal use or supply, and use for public services, commercial establishments, and homes. Water productivity is calculated as gross domestic product in constant prices divided by annual total water withdrawal. Emissions of organic water pollutants are measured in terms of biochemical oxygen demand, which refers to the amount of oxygen that bacteria in water will consume in breaking down waste. This is a standard watertreatment test for the presence of organic pollutants. Energy production refers to forms of primary energy—petroleum (crude oil, natural gas liquids, and oil from nonconventional sources), natural gas, solid fuels (coal, lignite, and other derived fuels), and combustible renewable and waste—and primary electricity, all converted into oil equivalents. Energy use refers to use of primary energy before transformation to other end-use fuels, which is equal to indigenous production plus imports and stock changes, minus exports and fuels supplied to ships and aircraft engaged in international transport. Combustible renewables and waste comprise solid biomass, liquid biomass, biogas, industrial waste, and municipal waste, measured as a percentage of total energy use. Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring. Methane emissions, total, are those from human activities such as agriculture and from industrial methane production. Methane emissions, agricultural, are those from animals, animal waste, rice production, agricultural waste burning (nonenergy, onsite), and savannah burning. 172

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Methane emissions, industrial, are those from the handling, transmission, and combustion of fossil fuels and biofuels. Nitrous oxide emissions, total, are those from agricultural biomass burning, industrial activities, and livestock management. Nitrous oxide emissions, agricultural, are those produced through fertilizer use (synthetic and animal manure), animal waste management, agricultural waste burning (nonenergy, on-site), and savannah burning. Nitrous oxide emissions, industrial, are those produced during the manufacturing of adipic acid and nitric acid. Other greenhouse gas emissions are by-product emissions of hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride. Official development assistance (ODA) gross disbursements for forestry are disbursements for forestry by bilateral, multilateral, and other donors. Disbursements record the actual international transfer of financial resources or of goods or services valued at the cost of the donor. Official development assistance (ODA) gross disbursements for general environment protection are disbursements for general environment protection by bilateral, multilateral, and other donors. Disbursements record the actual international transfer of financial resources or of goods or services valued at the cost of the donor. Source: Data on forest area and deforestation are from the Food and Agriculture Organization’s (FAO) Global Forest Resources Assessment. Data on freshwater resources and withdrawals are from the World Resources Institute, supplemented by the FAO’s AQUASTAT data. Data on emissions of organic water pollutants are from the World Bank. Data on energy production and use and combustible renewable and waste are from the International Energy Agency. Data on carbon dioxide emissions are from the Carbon Dioxide Information Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory, in the U.S. state of Tennessee. Data on methane emissions, nitrous oxide emissions, and other greenhouse gas emissions are from the International Energy Agency. Data on official development assistance disbursements are from the Development Assistance Committee of the Organisation for Economic

Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at www.oecd.org/dac/stats/idsonline. Table .. Fossil fuel emissions Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring. Carbon dioxide emissions per capita are carbon dioxide emissions divided by midyear population. Fossil fuel is any hydrocarbon deposit that can be burned for heat or power, such as petroleum, coal, and natural gas. Total carbon dioxide emissions from fossil fuels is the sum of all fossil fuel emissions (solid fuel consumption, liquid fuel consumption, gas fuel consumption, gas flaring, and cement production). Carbon dioxide emissions from solid fuel consumption refer mainly to emissions from use of coal as an energy source and from secondary fuels derived from hard and soft coal (such as coke-oven coke). Carbon dioxide emissions from liquid fuel consumption refer to emissions from use of crude petroleum and natural gas liquids as an energy source, and secondary fuels derived from oil (such as jet fuel). Carbon dioxide emissions from gas fuel consumption refer mainly to emissions from use of natural gas as an energy source and from secondary fuels derived from natural gas (such as blast furnace gas). Carbon dioxide emissions from gas flaring refer mainly to emissions from gas flaring activities. Carbon dioxide emissions from cement production refer mainly to emissions during cement production. Cement production is a multistep process, and carbon dioxide is actually released from clinker production during the cement production process. Source: Data on carbon dioxide emissions are from the Carbon Dioxide Information Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory, in the U.S. state of Tennessee.

9. Labor, migration, and population Table .. Labor force participation Labor force is people ages 15 and older who meet the International Labour Organization (ILO) definition of the economically active population. It includes both the employed and the unemployed. While national practices vary in the treatment of such groups as the armed forces and seasonal or part-time workers, the labor force generally includes the armed forces, the unemployed, and firsttime job seekers, but excludes homemakers and other unpaid caregivers and workers in the informal sector. Participation rate is the percentage of the population of the specified age group that is economically active, that is, all people who supply labor for the production of goods and services during a specified period. Source: International Labour Organization, Key Indicators of the Labour Market database. Table .. Labor force composition Agriculture corresponds to division 1 (International Standard Industrial Classification [ISIC] revision 2) or tabulation categories A and B (ISIC revision 3) and includes hunting, forestry, and fishing. Industry corresponds to divisions 2–5 (ISIC revision 2) or tabulation categories C–F (ISIC revision 3) and includes mining and quarrying (including oil production), manufacturing, construction, and public utilities (electricity, gas, and water). Services correspond to divisions 6–9 (ISIC revision 2) or tabulation categories G–P (ISIC revision 3) and include wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social, and personal services. Wage and salaried workers are workers who hold the type of jobs defined as paid employment jobs, where incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent on the revenue of the unit for which they work. Self-employed workers are self-employed workers with employees (employers), selfemployed workers without employees (ownaccount workers), and members of producer Technical notes

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A multidimensional portrait of poverty and living conditions in slums The expansion of slums in the rapidly growing cities of the developing world is a well-known and thoroughly studied phenomenon. Studies of slums range from rich ethnographic micro-studies of specific cities, settlements, and individual residents within such settlements (for example, Peattie 1968; Perlman 1980, 2006) to macro-level analyses that present national and global urbanization trends, emphasize the inexorable increase in slum settlements, and discuss the implications of slum growth for urban service delivery and poverty (for example, UN Habitat 2003). Nevertheless, debates continue over what constitutes a slum and what policy makers should do to tackle this problem. In addition, there is a crucial gap in the literature on what might be called the “meso” level—analytical frameworks and analyses positioned between the micro-level studies that treat each neighborhood as unique and the macro-level national or global aggregations focusing on incidence of slums that lump all slums into one category. To help fill this gap, we propose a set of three interrelated frameworks to create a multidimensional portrait of poverty and living conditions in any given neighborhood, conduct comparative analyses across neighborhoods and cities, and aggregate data at levels that can better inform policies and programs. The three frameworks— termed the Development Diamond, the Living Conditions Diamond, and the Infrastructure Polygon—present a graphical comparative picture arrayed along 16 selected dimensions. We illustrate these frameworks using empirical data from the cities of Nairobi, Kenya, and Dakar, Senegal. Specifically, we use the frameworks to present a picture of living conditions and poverty emerging from a specially commissioned survey of 3,700 slum households in the two cities. The first framework—the Development Diamond (figure 1)— posits that poverty and development can and should be understood along at least four discrete but interrelated dimensions: monetary poverty, employment, education, and living conditions, including infrastructure access. Using this framework to analyze the situation in Nairobi and Dakar, we find that although slum residents are monetarily poor in both cities, the nature of their poverty differs dramatically. In Nairobi, slum residents are educated and

Prepared by Sumila Gulyani, Ellen Bassett, and Debabrata Talukdar

the majority are employed, but they have appalling living conditions. In Dakar, they have fairly decent living conditions but very low levels of education and paid employment. We next unpack living conditions through a framework termed the Living Conditions Diamond (figure 2). We posit that living conditions are themselves a composite of four dimensions: tenure, infrastructure, unit quality, and neighborhood and location. Figure 2 illustrates that, compared with Dakar, Nairobi’s slums are worse off on all four dimensions. Nairobi’s slums are characterized by highly mobile, tenure-insecure renters living in semi-permanent structures in poorly served neighborhoods that are widely perceived as unsafe. Dakar’s slums, by contrast, are peopled primarily with owner–occupants and have low resident turnover, permanent housing structures, and superior infrastructure access. Finally, the Infrastructure Polygon (figure 3) illustrates, in greater detail, the differences in infrastructure access and service levels across the two cities. A typical resident of Nairobi’s slums has no access to electricity or organized rubbish removal. She or he purchases water from kiosks and shares a public pit latrine with an average of 57 persons. Dakar’s slums are characterized by good infrastructure access, with the exception of storm-water drains. Taken together, the frameworks demonstrate the extent of heterogeneity across slums. They graphically reveal that slums in the two cities differ dramatically from each other on nearly every indicator examined and thus contradict the notion that most African cities face similar slum problems. By extension, they also challenge the idea that one approach to—or template for—the upgrading of slums can work in all African cities. At the same time, the frameworks serve as a tool that can help practitioners and policy makers better understand local needs and priorities, and tailor their interventions to the given context. This research also highlights the issue of living conditions. The findings from Nairobi and Dakar challenge the seemingly logical notion that education and jobs will (automatically) translate into lower poverty and improved living conditions or, conversely, the idea that poor citizens need to have education and employment before they

Figure 1 WELFARE 18% above poverty line

WELFARE 28% above poverty line

EMPLOYMENT 68% working (26% unemployed)

LIVING CONDITIONS 3% with water, electricity, and permanent walls

LIVING CONDITIONS 74% with water, electricity, and permanent walls

EMPLOYMENT 39% working (6% unemployed)

EDUCATION 79% completed primary

EDUCATION 36% completed primary

NAIROBI

DAKAR (continued)

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A multidimensional portrait of poverty and living conditions in slums (continued)

Figure 2 INFRASTRUCTURE Average % of households with access: 23%

TENURE 8% own homes

INFRASTRUCTURE Average % of households with access to a service: 59%

UNIT 12% have permanent walls

TENURE 74% own homes

UNIT 96% with permanent walls

NEITHBORHOOD & LOCATION 37% feel safe

NEITHBORHOOD & LOCATION 48% feel safe

NAIROBI

DAKAR

Figure 3 PIPED WATER 19%

PIPED WATER 84%

ELECTRICITY 22%

TOILET 25%

PHONE 23%

SEWAGE DISPOSAL 12%

PUBLIC TRANSIT 20% GARBAGE PICKUP 12%

DRAIN 25%

NAIROBI

can have access to decent living conditions and basic infrastructure. At a broader level, this research leads us to the argument that living conditions are an important—but poorly analyzed and understood—dimension of poverty, one that needs to be included in the ongoing analyses of and discussions on multidimensional poverty. References Gulyani, S., and E. Bassett. 2010. “The Living Conditions Diamond: A Theoretical and Analytical Framework for Understanding Slums.” Environment and Planning A 42: 2201–19. Gulyani, S., E. Bassett, and D. Talukdar. 2012. “Living Conditions, Rents and Their Determinants in the Slums of Nairobi and Dakar.” Land Economics 88 (2): 251–274. ——— . 2011. “A Tale of Two Cities: A Multi-Dimensional Portrait of Poverty and Living Conditions in the Slums of Dakar and Nairobi.”Africa Urban and Water Working Paper, Washington, DC, World Bank. Gulyani S., and D. Talukdar. 2008. “Slum Real Estate: The Low-Quality High-Price Puzzle in Nairobi’s Slums and Its

ELECTRICITY 82%

TOILET 94%

PHONE 58%

SEWAGE DISPOSAL 66%

PUBLIC TRANSIT 15% GARBAGE PICKUP 73%

DRAIN 5%

DAKAR Implications for Theory and Practice.” World Development 36 (10): 1916–37. ———. 2010. “Inside Informality: The Links Between Poverty, Microenterprises and Living Conditions in Nairobi’s Slums.” World Development 38 (12): 1710–26. Gulyani, S., D. Talukdar, and D. Jack. 2010. “Poverty, Living Conditions and Infrastructure Access: A Comparison of Slums in Dakar, Johannesburg and Nairobi.” Policy Research Working Paper 5388, Washington, DC, World Bank. Iskander, N., and S. Gulyani. 2010. “The Trouble with Silos: Water and Sanitation in the Sinking Slums of Dakar.” Africa Urban and Water Working Paper, Washington, DC, World Bank. Peattie, L. R. 1968. The View from the Barrio. Ann Arbor, MI: University of Michigan Press. Perlman, J. 2006. “The Metamorphosis of Marginality: Four Generations in the Favelas of Rio de Janeiro.” Annals of the American Academy of Political and Social Science 606: 154–77. ———. 1980. The Myth of Marginality: Urban Poverty and Politics in Rio de Janeiro. Berkeley, CA: University of California Press.

Technical notes

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cooperatives. Although the contributing family workers category is technically part of the self-employed according to the classification used by the International Labour Organization (ILO), and could therefore be combined with the other self-employed categories to derive the total self-employed, they are reported here as a separate category in order to emphasize the difference between the two statuses, since the socioeconomic implications associated with each status can be significantly varied. This practice follows that of the ILO’s Key Indicators of the Labour Market. Contributing family workers (unpaid workers) are workers who hold self-employment jobs as own-account workers in a marketoriented establishment operated by a related person living in the same household. Source: International Labour Organization, Key Indicators of the Labour Market database. Table .. Unemployment Unemployment is the share of the labor force of the specified subgroup without work but available for and seeking employment. Primary education provides children with basic reading, writing, and mathematics skills along with an elementary understanding of such subjects as history, geography, natural science, social science, art, and music. Secondary education completes the provision of basic education that began at the primary level and aims to lay the foundations for lifelong learning and human development by offering more subject- or skill-oriented instruction using more specialized teachers. Tertiary education, whether or not at an advanced research qualification, normally requires, as a minimum condition of admission, the successful completion of education at the secondary level. Source: International Labour Organization, Key Indicators of the Labour Market database. Table .. Migration and population Migrant stock is the number of people born in a country other than that in which they live. It includes refugees. Net migration is the net average annual number of migrants during the period, that is, the annual number of immigrants less the annual number of emigrants, including both 176

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citizens and noncitizens. Data are five-year estimates. Workers remittances, received, comprise current transfers by migrant workers and wages and salaries by nonresident workers. Migrant remittance flows are the sum of worker’s remittances, compensation of employees, and migrants’ transfers, as recorded in the International Monetary Fund’s Balance of Payments. Population is total population based on the de facto definition of population, which counts all residents regardless of legal status or citizenship, except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. The values shown are midyear estimates. Fertility rate is the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with current age-specific fertility rates. Age composition refers to the percentage of the total population that is in specific age groups. Dependency ratio is the ratio of dependents— people younger than 15 or older than 64— to the working-age population—those ages 15–64. Rural population is calculated as the difference between the total population and the urban population. Urban population is midyear population of areas defined as urban in each country. Source: Data on migration are from the United Nations Population Division, Trends in Total Migrant Stock: 2008 Revision. Data on population are from (1) United Nations Population Division, World Population Prospects; (2) United Nations Statistical Division, Population and Vital Statistics Report (various years); (3) census reports and other statistical publications from national statistical offices; (4) Eurostat: Demographic Statistics; (5) Secretariat of the Pacific Community: Statistics and Demography Programme; and (6) U.S. Census Bureau: International Database. Data on dependency ratio are from World Bank staff estimates from various sources including census reports, the United Nations Population Division’s World Population Prospects, national statistical offices,

household surveys conducted by national agencies, and Macro International. Data on workers’ remittances are from International Monetary Fund, Balance of Payments Statistics Yearbook, and data files, while data from migrant remittance flows are from World Bank staff estimates based on the International Monetary Fund’s Balance of Payments Statistics Yearbook 2008. 10. HIV/AIDS Table .. HIV/AIDS Estimated number of people living with HIV/ AIDS is the number of people in the relevant age group living with HIV. Estimated HIV prevalence rate is the percentage of the population of the relevant age subgroup who are infected with HIV. Depending on the reliability of the data available, there may be more or less uncertainty surrounding each estimate. Therefore, plausible bounds have been presented for each subgroup rate (low and high estimate). Deaths of adults and children due to HIV/ AIDS are the estimated number of adults and children who have died in a specific year based on the modeling of HIV surveillance data using standard and appropriate tools. AIDS orphans are the estimated number of children who have lost their mother or both parents to AIDS before age 17 since the epidemic began in 1990. Some of the orphaned children included in this cumulative total are no longer alive; others are no longer under age 17. HIV-positive pregnant women receiving antiretrovirals to reduce the risk of motherto-child transmission are the number of pregnant women infected with HIV who received antiretrovirals during the last 12 months to reduce the risk of mother-to-child transmission. Share of HIV-positive pregnant women receiving antiretrovirals, World Health Organization/Joint United Nations Programme on HIV/ AIDS (WHO/UNAIDS) methodology, is the percentage of pregnant women infected with HIV who received antiretrovirals to reduce the risk of mother-to-child transmission divided by the total number of infected pregnant women infected with HIV in the last 12 months. The WHO/UNAIDS methodology may differ from country methodologies.

Official development assistance (ODA) disbursements for social mitigation of HIV/AIDS are spending on special programs to address the consequences of HIV/AIDS, such as social, legal, and economic assistance to people living with HIV/AIDS (including food security and employment); spending on support to vulnerable groups and children orphaned by HIV/AIDS; and spending on human rights advocacy for people affected by HIV/AIDS. Official development assistance (ODA) disbursements for sexually transmitted diseases (STDs) control, including HIV/AIDS, are spending on all activities related to STDs and HIV/ AIDS control, such as information, education, and communication; testing; prevention; and treatment care. Source: Data on number of people living with HIV/AIDS, HIV prevalence rate, deaths due to HIV/AIDS, AIDS orphans, and HIVpositive pregnant women receiving antiretrovirals are from UNAIDS and WHO’s Report on the Global AIDS Epidemic. A more detailed explanation of methods and assumptions can be found on the UNAIDS reference group on estimates, modeling, and projections website (www.unaids.org/en/KnowledgeCentre/HIV Data/Epidemiology/) and in a series of papers published in Sexually Transmitted Infections, “Improved Methods and Tools for HIV/AIDS Estimates and Projections,” 2008, 84(Suppl I), 2006, 82(Suppl III), and 2004, 80(Suppl I). Data on official development assistance disbursements are from the Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Cooperation Report, and International Development Statistics database. Data are available online at www.oecd.org/dac/stats/idsonline. 11. Malaria Table .. Malaria Population is total population based on the de facto definition of population, which counts all residents regardless of legal status or citizenship, except for refugees not permanently settled in the country of asylum, who are generally considered part of the population of their country of origin. The values shown are midyear estimates. Technical notes

177

Clinical malaria cases reported are the sum of cases confirmed by slide examination or rapid diagnostic test and probable and unconfirmed cases (cases that were not tested but treated as malaria). National malaria control programs often collect data on the number of suspected cases, those tested, and those confirmed. Probable or unconfirmed cases are calculated by subtracting the number tested from the number suspected. Not all cases reported as malaria are true malaria cases; most health facilities lack appropriate diagnostic services. The misdiagnosis may have led to under- or overreporting malaria cases and missing diagnosis of other treatable diseases. Reported malaria deaths are all deaths in health facilities that are attributed to malaria, whether or not confirmed by microscopy or by rapid diagnostic test. Under-five mortality rate is the probability that a newborn baby will die before reaching age 5, if subject to current age-specific mortality rates. The probability is expressed as a rate per 1,000. Children sleeping under insecticide-treated nets is the percentage of children under age 5 with access to an insecticide-treated net to prevent malaria. Children with fever receiving any antimalarial treatment any time are the percentage of children under age 5 in malaria-risk areas with fever being treated with any antimalarial drugs. Pregnant women receiving two doses of intermittent preventive treatment are the number of pregnant women receiving two or more doses of sulfadoxine pyrimethamine (SP) during an antenatal care visit. In some country surveys, the site of treatment (e.g., “during the antenatal care visit”) is not specified. This approach has been shown to be safe, inexpensive, and effective. Official development assistance (ODA) disbursements for malaria control are spending on prevention and control of malaria. Source: Data on population are from the (1) United Nations Population Division, World Population Prospects,; (2) United Nations Statistical Division, Population and Vital Statistics Report (various years); (3) census reports and other statistical publications from national statistical offices; (4) Eurostat: 178

Africa Development Indicators 2012/13

Demographic Statistics, (5) Secretariat of the Pacific Community: Statistics and Demography Programme; and (6) U.S. Census Bureau: International Database.. Data on clinical cases of malaria reported and reported malaria deaths are from the World Health Organization’s (WHO) World Malaria Report 2009. Data on children with fever receiving antimalarial drugs, and pregnant women receiving two doses of intermittent preventive treatment, are from Demographic Health Surveys, Multiple Indicator Cluster Surveys, and national statistical offices. Data on deaths due to malaria are from the United Nations Statistics Division based on WHO estimates. Data on under-five mortality are harmonized estimates of the WHO, United Nations Children’s Fund, and the World Bank, based mainly on household surveys, censuses, and vital registration, supplemented by World Bank estimates based on household surveys and vital registration. Data on insecticidetreated bednet use are from Demographic and Health Surveys and Multiple Indicator Cluster Surveys. Data on official development assistance disbursements are from the Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at www.oecd.org/ dac/stats/idsonline. 12. Capable states and partnership Table .. Aid and debt relief Official development assistance is flows to developing countries and multilateral institutions provided by official agencies, including state and local governments, or by their executive agencies, that are administered with the promotion of the economic development and welfare of developing countries as their main objective and that are concessional in character and convey a grant element of at least 25 percent. Net official development assistance (ODA) from all donors is net ODA from the Development Assistance Committee (DAC) and multilateral donors. It is consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants

by oﬃcial agencies of the members of the DAC, by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). Net official development assistance (ODA) from DAC donors is net ODA from OECD’s DAC donors, which include Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Japan, Korea, Luxembourg, the Netherlands, New Zealand, Norway, Portugal, Spain, Sweden, Switzerland, the United Kingdom, and the United States. Net official development assistance (ODA) from non-DAC donors is net ODA from OECD’s non-DAC donors, which include the Chinese Taipei, Cyprus, Czech Republic, Estonia, Hungary, Iceland, Israel, Kuwait, Latvia, Lichtenstein, Lithuania, Malta, Poland, Romania, Russia, Saudi Arabia, the Slovak Republic, Slovenia, Thailand, Turkey, the United Arab Emirates, and other donors (includes data reported from Algeria, Iraq, Libya, and Qatar from 1970–1994). Net official development assistance (ODA) from multilateral donors is net ODA from multilateral sources, African Development Bank (AfDB), African Development Fund (AFDF), Arab Fund, Asian Development Bank (AsDB), Caribbean Development Bank (CarDB), Arab Bank for Economic Development in Africa (BADEA), European Bank for Reconstruction and Development (EBRD), European Union (EU) Institutions, GAVI Alliance (formerly the “Global Alliance for Vaccines and Immunisation”), Global Environment Facility (GEF), Global Fund, International Atomic Energy Agency (IAEA), International Bank for Reconstruction and Development (IBRD), International Development Association (IDA), Inter-American Development Bank (IDB) Special Fund, International Fund for Agricultural Development (IFAD), International Finance Corporation (IFC), International Monetary Fund (IMF) Concessional Trust Funds, Islamic Development Bank, Montreal Protocol, Nordic Development Fund, the OPEC Fund for International Development (OFID), Organization for Security and Cooperation in Europe (OSCE), Joint United

Nations Programme on HIV/AIDS (UNAIDS), United Nations Development Programme (UNDP), United Nations Economic Commission for Europe (UNECE), United Nations Population Fund (UNFPA), United Nations High Commissioner for Refugees (UNHCR), United Nations Children’s Fund (UNICEF), United Nations Peace Building Fund (UNPBF), United Nations Relief and Works Agency (UNRWA), United Nations Transitional Authority (UNTA), World Food Programme (WFP), and World Health Organization (WHO). Net private official development assistance (ODA) is private ODA transactions, which comprise direct investment, portfolio investment, and export credits (net). Private transactions are undertaken by firms and individuals resident in the reporting country. Portfolio investment corresponds to bonds and equities. Inflows into emerging countries’ stock markets, are, however, heavily understated. Accordingly, the coverage of portfolio investment differs in these regards from the coverage of bank claims, which include export credit lending by banks. The bank claims data represent the net change in bank claims after adjusting for exchange rate changes and are therefore a proxy for net flow data but are not themselves a net flow figure. They differ in two further regards from other OECD data. First, they relate to loans by banks resident in countries that report quarterly to the Bank for International Settlements. Second, no adjustment has been made to exclude short-term claims. Net official development assistance (ODA) as a share of gross domestic product (GDP) is calculated by dividing the nominal total net ODA from all donors by nominal GDP. For a given level of aid flows, devaluation of a recipient’s currency may inflate the ratios shown in the table. Thus, trends for a given country and comparisons across countries that have implemented different exchange rate policies should be interpreted carefully. Net official development assistance (ODA) per capita is calculated by dividing the nominal total net ODA (net disbursements of loans and grants from all official sources on concessional financial terms) by midyear population. These ratios offer some indication of the importance of aid flows in sustaining per capita income and consumption Technical notes

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levels, although exchange rate fluctuations, the actual rise of aid flows, and other factors vary across countries and over time. Net official development assistance (ODA) as a share of gross capital formation is calculated by dividing the nominal total net ODA by gross capital formation. These data highlight the relative importance of the indicated aid flows in maintaining and increasing investment in these economies. The same caveats mentioned above apply to their interpretation. Furthermore, aid flows do not exclusively finance investment (for example, food aid finances consumption), and the share of aid going to investment varies across countries. Net official development assistance (ODA) as a share of imports of goods and services is calculated by dividing nominal total net ODA by imports of goods and services. Net official development assistance (ODA) as a share of central government expenditure is calculated by dividing nominal total net ODA by central government expenditure. Food aid shipments are transfers of food commodities (food aid received) from donor to recipient countries on a total-grant basis or on highly concessional terms. Processed and blended cereals are converted into their grain equivalent by applying the conversion factors included in the Rule of Procedures under the 1999 Food Aid Convention to facilitate comparisons between deliveries of different commodities. Deliveries of food aid refer to quantities of commodities that actually reached the recipient country during a given period. For cereals the period refers to July–June, beginning in the year shown. Heavily Indebted Poor Countries (HIPC) Debt Initiative decision point is the date at which a HIPC with an established track record of good performance under adjustment programs supported by the International Monetary Fund and the World Bank commits to undertake additional reforms and to develop and implement a poverty reduction strategy. Countries reach the decision point if they have a track record of macroeconomic stability, have prepared a Poverty Reduction Strategy through a participatory process, and have debt burden indicators above the HIPC Initiative thresholds using the most recent data for the year immediately prior to the decision point. The amount of debt relief 180

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necessary to bring countries’ debt indicators to HIPC thresholds is calculated, and countries begin receiving interim debt relief on a provisional basis. HIPC Debt Initiative completion point is the date at which the country successfully completes the key structural reforms agreed on at the decision point, including developing and implementing its poverty reduction strategy. The country then receives the bulk of debt relief under the HIPC Initiative without further policy conditions. Burkina Faso, Mali, Mozambique, and Uganda also reached the completion point under the original HIPC Initiative, and the assistance includes original debt relief. Burkina Faso, Ethiopia, Guinea Bissau, Malawi, Niger, Rwanda, and São Tomé and Príncipe assistance includes topping up at the completion point. Liberia received Multilateral Debt Relief Initiative (MDRI)-type (beyond-HIPC) debt relief at end-June 2010, which was financed from the Liberia Administered Account. Countries reach the completion point if they maintain macroeconomic stability under an Extended Credit Facility (ECF)-supported program, carry out key structural and social reforms, and satisfactorily implement for a minimum of one year a Poverty Reduction Strategy. Debt relief is then provided irrevocably by the country’s creditors. MDRI relief is provided upon reaching the completion point. Eritrea, Somalia, and Sudan have been assessed to meet the income and indebtedness criteria at end-2004 and end-2010 and wish to avail themselves of the HIPC Initiative. Debt service relief committed is the amount of debt service relief, calculated at the decision point, that will allow the country to achieve debt sustainability at the completion point. Multilateral Debt Relief Initiative is meant to provide additional support to HIPCs to reach the Millennium Development Goals while ensuring that the financing capacity of the International Financial Institutions (IFIs) is preserved. The MDRI provides a framework that commits to achieve two objectives: deepening debt relief to HIPCs while safeguarding the long-term financial capacity of IDA and the AfDF; and encouraging the best use of additional donor resources for development by

allocating them to low-income countries on the basis of policy performance. Debt relief to be provided under the MDRI will be in addition to existing debt relief commitments by IDA and other creditors under the Enhanced HIPC Debt Initiative. The MDRI calls for 100 percent cancellation of IDA, AfDF, and International Monetary Fund (IMF) debt for countries that reach the HIPC completion point. The costs include principal and interest foregone for all multilaterals participating in the Initiative, except IMF, which only include principal. The estimated costs for IMF reflect the stock of debt eligible for MDRI relief, which is the debt outstanding (principal only) as of end-2004 and that has not been repaid by the member and is not covered by HIPC assistance (EBS/05/158 Revision 1, 12/15/2005). Source: Data on net official development assistance are from the Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Cooperation Report, and International Development Statistics database. Data are available online at www.oecd.org/dac/stats/idsonline. Data on food aid shipments are based on data compiled by the World Food Programme at www.wfp.org/fais/. Data on HIPC countries are from the International Development Association and International Monetary Fund “Heavily Indebted Poor Countries (HIPC) Initiative and Multilateral Debt Relief Initiative (MDRI)—Status of Implementation.” Data on external debt are mainly from reports to the World Bank through its Debtor Reporting System from member countries that have received International Bank for Reconstruction and Development loans or International Development Association credits, as well as World Bank and IMF files. Table .. Status of paris declaration indicators The Paris Declaration is the outcome of the 2005 Paris High-Level Forum on Aid Effectiveness, where 60 partner countries, 30 donor countries, and 30 development agencies committed to specific actions to further country ownership, harmonization, alignment, managing for development results,

and mutual accountability for the use of aid. Participants agreed on 12 indicators. These indicators include good national development strategies, reliable country systems for procurement and public financial management, the development and use of results frameworks, and mutual assessment of progress. Qualitative desk reviews by the Organisation for Economic Co-operation and Development’s Development Assistance Committee and the World Bank and a survey questionnaire for governments and donors are used to calculate the indicators. PDI-1 Operational national development strategies are the extent to which a country has an operational development strategy to guide its aid coordination effort and overall development. The score is based on the World Bank’s 2005 Comprehensive Development Framework Progress Report. An operational strategy calls for a coherent long-term strategy derived from it; specific targets serving a holistic, balanced, and well-sequenced development strategy; and capacity and resources for its implementation. PDI-2a Reliable public financial management is the World Bank’s annual Country Policy and Institutional Assessment rating for the quality of public financial management. Measured on a scale of 1 (worst) to 5 (best), its focus is on how much existing systems adhere to broadly accepted good practices and whether a reform program is in place to promote improved practices. PDI-2b Reliable country procurement systems measure developing countries’ procurement systems. Donors use national procurement procedures when the funds they provide for the implementation of projects and programs are managed according to the national procurement procedures as they were established in the general legislation and implemented by government. The use of national procurement procedures means that donors do not make additional, or special, requirements on governments for the procurement of works, goods, and services. (Where weaknesses in national procurement systems have been identified, donors may work with partner countries to improve the efficiency, economy, and transparency of their implementation.) The objective of this indicator is to measure and encourage improvements in developing countries’ procurement systems. Technical notes

181

PDI-3 Government budget estimates comprehensive and realistic are the percentage of aid that is accurately recorded in the national budget, thereby allowing scrutiny by parliaments. PDI-4 Technical assistance aligned and coordinated with country programs is the percentage of technical cooperation that is freestanding and embedded and that respects ownership (partner countries exercise effective leadership over their capacity development programs), alignment (technical cooperation in support of capacity development aligns with countries’ development objectives and strategies), and harmonization (when more than one donor is involved in supporting partnerled capacity development, donors coordinate their activities and contributions). PDI-5a and 5b Aid for government sectors uses country public financial management and procurement systems is the percentage of donors that use country, rather than donor, systems for managing aid disbursement. PDI-6 Project implementation units parallel to country structures is the number of parallel project implementation units, which refers to units created outside existing country institutional structures. The survey guidance distinguishes between project implementation units and executing agencies and describes three typical features of parallel project implementation units: they are accountable to external funding agencies rather than to country implementing agencies (ministries, departments, agencies, and the like), most of the professional staff is appointed by the donor, and the personnel salaries often exceed those of civil service personnel. Interpretation of the Paris Declaration survey question on this subject was controversial in a number of countries. It is unclear whether within countries all donors applied the same criteria with the same degree of rigor or that across countries the same standards were used. In several cases the descriptive part of the survey results indicates that some donors applied a legalistic criterion of accountability to the formal executing agency, whereas the national coordinator and other donors would have preferred greater recognition of the substantive reality of accountability to the donor. Some respondents may have confused the definitional question (Is the unit “parallel”?) with the aid management question (Is 182

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the parallelism justified in terms of the developmental benefits and costs?). PDI-7 Aid disbursements on schedule and recorded by government are the percentage of funds that are disbursed within the year they are scheduled and accurately recorded by partner authorities. PDI-8 Bilateral aid that is untied is the percentage of aid that is untied. Tied aid is aid provided on the condition that the recipient uses it to purchase goods and services from suppliers based in the donor country. PDI-9 Aid provided in the framework of program-based approaches is the percentage of development cooperation that is based on the principles of coordinated support for a locally owned program of development, such as a national development strategy, a sector program, a thematic program, or a program of a specific organization. Program-based approaches share the following features: leadership by the host country or organization, a single comprehensive program and budget framework, a formalized process for donor coordination and harmonization of donor procedures for reporting, budgeting, financial management, and procurement, and efforts to increase the use of local systems for program design and implementation, financial management, monitoring, and evaluation. PDI-10a Donor missions coordinated are the percentage of missions undertaken jointly by two or more donors and missions undertaken by one donor on behalf of another (delegated cooperation). PDI-10b Country analysis coordinated is the percentage of country analytic work that is undertaken by one or more donors jointly, undertaken by one donor on behalf of another donor (including work undertaken by one and used by another when it is co-financed and formally acknowledged in official documentation), and undertaken with substantive involvement from government. PDI-11 Existence of a monitorable performance assessment framework measures the extent to which the country has realized its commitment to establishing performance frameworks. The indicator relies on the scorings of the 2005 Comprehensive Development Framework Progress Report and considers three criteria: the quality of development information, stakeholder access to

development information, and coordinated country-level monitoring and evaluation. The assessments therefore reflect both the extent to which sound data on development outputs, outcomes, and impacts are collected, and various aspects of the way information is used, disseminated among stakeholders, and fed back into policy. PDI-12 Reviews of mutual accountability. All three of the following aspects of mutual accountability need to be met to consider a country as having a mutual review in place: i) Aid policy or strategy. Developing countries are expected to have a document that sets out agreed approaches to the delivery of aid in the country, containing agreed principles, processes, and/or targets designed to improve the effectiveness of aid. This may take the form of a stand-alone policy or strategy document, or may be addressed within another document (e.g., as part of a national development strategy). Such a document should have been the subject of consultation between the government and donors. ii) Country-level aid effectiveness targets. Country targets for improved aid effectiveness should have been established, including within the framework of the agreed partnership commitments and indicators of progress included in the Paris Declaration. They may go beyond the Paris Declaration wherever governments and donors agree to do so. There should be targets for both governments and donors. iii) Broad-based dialogue. Mutual assessments should engage a broad range of government ministries and donors in dialogue. Governments and donors should also consider engaging with nonexecutive stakeholders, including parliamentarians and civil society organizations. While the focus of the criteria remains unchanged from those used in previous surveys, three questions were introduced, drawing on clearer definitions to guide a more accurate assessment of progress. Source: Aid Effectiveness 2005–10: Progress in Implementing the Paris Declaration, OECD. Table .. Capable states Firms that believe the court system is fair, impartial, and uncorrupt are the percentage of firms that believe the court system is fair, impartial, and uncorrupted.

Corruption is the percentage of firms identifying corruption as a major constraint. Crime, theft, and disorder are the percentage of firms identifying crime, theft, and disorder as a major constraint to current operation. Number of procedures to enforce a contract is the number of independent actions, mandated by law or courts, that demand interaction between the parties of a contract or between them and the judge or court officer. Time required to enforce a contract is the number of calendar days from the filing of the lawsuit in court until the final determination and, in appropriate cases, payment. Cost to enforce a contract is court and attorney fees, where the use of attorneys is mandatory or common, or the cost of an administrative debt recovery procedure, expressed as a percentage of the debt value. Protecting investors disclosure index measures the degree to which investors are protected through disclosure of ownership and financial information. Higher values indicate more disclosure. Director liability index measures a plaintiff ’s ability to hold directors of firms liable for damages to the company. Higher values indicate greater liability. Shareholder suits index measures shareholders’ ability to sue officers and directors for misconduct. Higher values indicate greater power for shareholders to challenge transactions. Investor protection index measures the degree to which investors are protected through disclosure of ownership and financial information regulations. Higher values indicate better protection. Number of tax payments is the number of taxes paid by businesses, including electronic filing. The tax is counted as paid once a year even if payments are more frequent. Time required to prepare, file, and pay taxes is the number of hours it takes to prepare, file, and pay (or withhold) three major types of taxes: the corporate income tax, the value added or sales tax, and labor taxes, including payroll taxes and social security contributions. Total tax rate is the total amount of taxes payable by the business (except for labor taxes) after accounting for deductions and exemptions as a percentage of gross profit. Technical notes

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For further details on the method used for assessing the total tax payable, see the World Bank’s Doing Business reports. Extractive Industries Transparency Initiative (EITI) status refers to a country’s implementation status for the EITI, a multistakeholder approach to increasing governance and transparency in extractive industries. It includes civil society, the private sector, and government and requires a work plan with timeline and budget to ensure sustainability, independent audit of payments and disclosure of revenues, publication of results in a publicly accessible manner, and an approach that covers all companies and government agencies. The EITI supports improved governance in resource-rich countries through the verification and full publication of company payments and government revenues from oil, gas, and mining. Intent to implement indicates that a country intends to implement the EITI but has not yet met the four initial requirements to join: an unequivocal public statement of its intention to implement the EITI, a commitment to work with civil society and companies on EITI implementation, a senior official appointed to lead EITI implementation, and a widely distributed, fully costed work plan with measurable targets, a timetable for implementation, and an assessment of government, private sector, and civil society capacity constraints. Candidate indicates that a country has met the four initial requirements to join the EITI and has begun a range of activities to strengthen revenue transparency, as documented in the country’s work plan. Once a country has become an EITI candidate, it has two years to be validated as compliant. Compliant indicates that a country has successfully undergone validation, an independent assessment of a country’s progress toward the EITI goals by the EITI International Board. Validation is based on the country’s work plan, the EITI validation grid and indicator assessment tools, and company forms that detail private companies’ extractive industry activities; it provides guidance for countries’ future activity related to EITI compliance. Countries must undergo validation every five years or at the request of the EITI International Board. Source: Data on investment climate constraints to firms are World Bank, Enterprise Surveys (www.enterprisesurveys.org/). Data 184

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on enforcing contracts, protecting investors, and regulation and tax administration are from the World Bank’s Doing Business project (http://www.doingBusiness/). Data on corruption perceptions index are from Transparency International (www. transparency.org/policy_research/surveys_ indices/cpi). Data on the EITI are from the Extractive Industries Transparency Initiative website (www.eitransparency.org). Table .. Governance and anticorruption indicators Voice and accountability measure the extent to which a country’s citizens are able to participate in selecting their government and to enjoy freedom of expression, freedom of association, and a free media. Political stability and absence of violence measure the perceptions of the likelihood that the government will be destabilized or overthrown by unconstitutional or violent means, including domestic violence or terrorism. Government effectiveness measures the quality of public services, the quality and degree of independence from political pressures of the civil service, the quality of policy formulation and Implementation, and the credibility of the government’s commitment to such policies. Regulatory quality measures the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development. Rule of law measures the extent to which agents have confidence in and abide by the rules of society, in particular the quality of contract enforcement, the police, and the courts, as well as the Likelihood of crime and violence. Control of corruption measures the extent to which public power is exercised for private gain, including petty and grand forms of corruption, as well as “capture” of the state by elites and private interests. Expected to pay informal payment to public officials to get things done is the percentage of firms that expected to make informal payments or give gifts to public officials to “get things done” with regard to customs, taxes, licenses, regulations, services, and the like. Expected to give gifts to obtain an operating license is the percentage of firms that expected

to give gifts or an informal payment to get an operating license. Expected to give gifts in meetings with tax officials is the percentage of firms that answered “Yes” to the question, “Was a gift or informal payment expected or requested during a meeting with tax officials?” Expected to give gifts to secure a government contract is the percentage of firms that expected to make informal payments or give gifts to public officials to secure a government contract. Share of firms identifying control of corruption as a major constraint measures the extent to which public power is exercised for private gain, including petty and grand forms of corruption, as well as “capture” of the state by elites and private interests. Mean corruption perceptions index score is the country’s score in Transparency International’s annual corruption perceptions index, which ranks more than 150 countries in terms of perceived levels of corruption, as determined by expert assessments and opinion surveys. Open budget index overall score is the country’s score on a subset of 91 questions from the open budget survey. The questions focus on the public availability of eight key budget documents (with a particular emphasis on the executive’s budget proposal) and the information they contain. The open budget index is calculated based on detailed questionnaires completed by local experts in 59 participating countries from every continent. In 2008, based on inputs received from researchers and extensive in-house reviews, the International Budget Partnership made three changes in its methodology. The first change concerns the timing of the release of the eight key budget documents assessed by the survey. The second is the inclusion of the enacted budget in calculating country scores for the index. The third is revisions to the answers of a few questions used to assess Brazil and Nigeria. Source: Data on governance indicators are from the World Bank Institute’s Worldwide Governance Indicators database, which relies on 33 sources, including surveys of enterprises and citizens, and expert polls, gathered from 30 organizations around the world. Data on corruption perceptions index scores

are from Transparency International (www. transparency.org/). Data on the open budget index are from www.openbudgetindex.org. Table .. Country policy and institutional assessment ratings The Country Policy and Institutional Assessment (CPIA) assesses the quality of a country’s present policy and institutional framework. “Quality” means how conducive that framework is to fostering sustainable, poverty-reducing growth and the effective use of development assistance. The CPIA is conducted annually for all International Bank for Reconstruction and Development and International Development Association borrowers and has evolved into a set of criteria grouped into four clusters with 16 criteria that reflect a balance between ensuring that all key factors that foster pro-poor growth and poverty alleviation are captured, without overly burdening the evaluation process. • Economic management • Macroeconomic management assesses the quality of the monetary, exchange rate, and aggregate demand policy framework. • Fiscal policy assesses the short- and medium-term sustainability of fiscal policy (taking into account monetary and exchange rate policy and the sustainability of the public debt) and its impact on growth. • Debt policy assesses whether the debt management strategy is conducive to minimize budgetary risks and ensure long-term debt sustainability. • Structural policies • Trade assesses how the policy framework fosters trade in goods. It covers two areas: trade regime restrictiveness—which focuses on the height of tariff barriers, the extent to which nontariff barriers are used, and the transparency and predictability of the trade regime— and customs and trade facilitation—which includes the extent to which the customs service is free of corruption, relies on risk management, processes duty collections and refunds promptly, and operates transparently. Technical notes

185

Prepared by Punam Chuhan-Pole and Vijdan Korman

2011 CPIA Results for Africa

Figure 1: Overall CPIA score of African countries, 2011 Cape Verde Ghana Rwanda Kenya Senegal Burkina Faso Uganda Tanzania Mozambique Mali Benin Gambia, The Ethiopia Zambia Lesotho Nigeria Niger Sierra Leone Malawi Madagascar Mautitania SSA IDA Average Cameroon Burundi São Tomé and Príncipe Liberia Congo, Republic Togo Côte d’Ivoire Guinea Guinea-Bissau Central African Republic Angola Congo, Democratic.. Comoros Chad Sudan Eritrea Zimbabwe

4.0 3.9 3.8 3.8 3.8 3.8 3.8 3.7 3.7 3.6 3.5 3.5 3.5 3.5 3.4 3.4 3.4 3.3 3.3 3.2 3.2 3.2 3.2 3.1 3.1 3.0 3.0 3.0 2.9 2.9 2.8 2.8 2.7 2.7 2.7 2.4 2.4 2.2 2.2

Above SSA Average

Below SSA Average

Overall CPIA score, 2011

Increased Decreased No change

Source: CPIA Africa: Assessing Africa’s Policies and Institutions, June 2012, Africa Region, World Bank.

Figure 2: Overall CPIA score and change in score for African countries, 2011 Changes in overall CPIA score, 2010–11

The World Bank’s country policy and institutional assessment (CPIA) measures the strength of International Development Association countries’ policies and institutions across 16 dimensions grouped into four clusters: economic management, structural policies, policies for social inclusion and equity, and public sector management and institutions. Scores are on a scale of 1 to 6, with 6 the highest. The latest CPIA results show that despite difficult global economic conditions, the quality of policies and institutions in a majority of Sub-Saharan African countries remained stable or improved in 2011 (figure 1). The average CPIA score for IDA countries in the region was 3.2 in 2011, the same as in 2010. Nevertheless, for several countries the policy environment has improved and is the best in recent years. Of the 38 African countries with CPIA scores, 13 saw an improvement in the 2011 overall score by at least 0.1, twenty saw no change, and five witnessed a decline of 0.1 or more (figure 2). In short, despite a challenging global economic environment, African countries continued to pursue policies aligned with growth and poverty reduction. This pattern was observed in the aftermath of the global financial and economic crisis of 2008–09. During the global crisis, the payoffs to market-oriented, pro-poor economic reforms fell, prompting a concern that countries may backtrack on important policy gains. Yet policy makers continued with prudent policies, even in the face of contradictory policies elsewhere. There is considerable variation in overall CPIA scores across countries, from a high of 4.0 for Cape Verde, which continues to be in the top end of the score range despite a decline in its score in both 2010 and 2011, to a low of 2.2 for Eritrea and Zimbabwe. The variation is especially marked between “fragile situations” (also referred to as fragile states) and other countries.1 Sub-Saharan Africa has a large number of fragile states: 17 of the world’s 33, by the World Bank’s definition of fragile situations. The capacity of the public sector in most of these countries is exceptionally weak. Not surprisingly, the average CPIA score for these countries is much lower than that of non-fragile countries, at 2.7 and 3.5, respectively. Hampered with severe governance problems, including widespread corruption and civil conflict, Africa’s resource-rich countries on average tend to lag the non-resource-rich countries: overall CPIA scores are 3.0 for resource-rich and 3.3 for nonresource-rich countries. Nonetheless, many fragile states are making fast progress, albeit from a low base. The three countries that experienced the largest increase—of 0.2—in their overall CPIA score in 2011 were fragile states: Comoros, Cote d’Ivoire, and Zimbabwe. A pattern of larger gains for fragile states is evident over a longer time period as well. Given their weak policy and institutional capacity, fragile countries can also experience a rapid deterioration in the policy environment. By contrast, countries in the top range of scores typically show slow yet steady improvement in scores, although a few have seen policy slippages in recent years—for example, Cape Verde in 2010 and 2011, and Tanzania in 2011.

0.3 0.2 0.2 0.1

ZWE

COM

Below SSA average and catching up

0.1 0.0

GNB GIN COG LBR STP TGO

TDC SDN

ERI

-0.1

AGO

-0.2 -0.3 2.0

GMR ZMB ETH

2.2

2.4

2.6

2.8

TZA

LSO

SSA IDA average = 3.2

Below SSA average and decreasing

SEN

KEN UGA BDI MRT MWI NGA MLI MOZ BFA GHA CMR SLE NER BEN RWA

ZAR CAF

-0.1

-0.2

Above SSA average and increasing

CIV

3.0

Above SSA average and decreasing

MDG

3.2

CPV

3.4

Overall CPIA score, 2011

3.6

3.8

4.0

4.2

Source: CPIA Africa: Assessing Africa’s Policies and Institutions, June 2012, Africa Region, World Bank.

There are large differences in performance across components of the CPIA, reflecting the faster pace of reform in some policy areas. Not surprisingly, in components where reforms are deeply political (or contentious) or by nature incremental, scores (continued)

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2011 CPIA Results for Africa (continued) Figure 3: CPIA cluster scores by country group, 2011

4.0 3.5 3.0 2.9 2.8 2.8 2.5

2.5

2.7

Cluster A: Economic Management Cluster B: Structural Policies Cluster C: Policies for Social Inclusion/Equity Cluster D: Public Sector Management and Institutions Overall CPIA 3.8 3.6 3.5 3.5 3.3 3.3 3.3 3.1 3.1 3.0

3.7

3.6 3.6

3.4

3.6

2.0 1.5 1.0

SSA Fragile

Non-SSA Fragile

SSA Non Fragile

Non-SSA Non-Fragile

Source: CPIA Africa: Assessing Africa’s Policies and Institutions, June 2012, Africa Region, World Bank.

improve more slowly and lag scores in other components. Performance in the economic management cluster (Cluster A), which covers monetary and exchange rate policy, fiscal policy, and debt policy and management, leads that of all other clusters. To some extent, this reflects recognition of the importance of macroeconomic stability for creating an environment conducive to private sector activity; high commodity prices have also helped. Indeed, several years of prudent macroeconomic policies meant that African countries entered the 2008–09 global crisis with policy space to counter the sharp external shock. A close second in performance is the structural policies cluster (Cluster B)—covering trade, financial sector, and business regulatory environment—followed by the social inclusion and equity cluster (Cluster C)—covering gender equality, equity of public

•

Financial sector assesses the structure of the financial sector and the policies and regulations that affect it. It covers three dimensions: financial stability; the sector’s efficiency, depth, and resource mobilization strength; and access to financial services. Business regulatory environment assesses the extent to which the legal, regulatory, and policy environment helps or hinders private business in investing, creating jobs, and becoming more productive. The emphasis is on direct regulation of business activity and regulation of goods and factor markets. It measures three subcomponents: regulations affecting entry, exit, and competition; regulations of ongoing business operations; and regulations of factor markets (labor and land).

•

resource use, building human resources, social protection and labor, and environmental policies and institutions. The governance cluster (Cluster D)—which includes property rights and rule-based governance; quality of budgetary and financial management; efficiency of revenue mobilization; quality of public administration; and transparency, accountability, and corruption in the public sector—lags all other clusters. The overall CPIA score for African countries lags that of other IDA countries: the average score for the two groups are 3.2 and 3.4, respectively. But comparison by country groups yields a fairly uneven picture. Policies and institutions in African countries, excluding fragile states, compare well with those in similar countries in other regions, with the average scores being 3.5 and 3.6, respectively. But the comparison of fragile states across regions is starkly different, with African fragile states exhibiting much weaker performance than non-African fragile countries. The performance across areas of the CPIA follows a similar pattern, further highlighting the weakness of policies and institutions in the region’s fragile states. Notes The World Bank defines “fragile situations” as either: (a) IDAeligible countries with a harmonized average CPIA rating of 3.2 or less (or no CPIA), or (b) countries with the presence of a UN and/or regional peacekeeping or peace-building mission during the past three years. IBRD (International Bank for Reconstruction and Development)-only countries are not included in the fragile situations list.

Policies for social inclusion and equity • Gender equality assesses the extent to which the country has enacted and put in place institutions and programs to enforce laws and policies that promote equal access for men and women to human capital development and to productive and economic resources, and that give men and women equal status and protection under the law. • Equity of public resource use assesses the extent to which the pattern of public expenditures and revenue collection aﬀects the poor and is consistent with national poverty reduction priorities. The assessment of the consistency of government spending with the poverty reduction priorities takes into account the extent to which individuals, groups, or localities that are poor, vulnerable, or have unequal access Technical notes

187

•

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to services and opportunities are identiﬁed; a national development strategy with explicit interventions to assist those individuals, groups, and localities has been adopted; and the composition and incidence of public expenditures are tracked systematically and their results fed back into subsequent resource allocation decisions. The assessment of the revenue collection dimension takes into account the incidence of major taxes—for example, whether they are progressive or regressive—and their alignment with the poverty reduction priorities. When relevant, expenditure and revenue collection trends at the national and subnational levels should be considered. The expenditure component receives two-thirds of the weight in computing the overall rating. Building human resources assesses the national policies and public and private sector service delivery that aﬀect access to and quality of health and nutrition services, including: population and reproductive health; education, early childhood development, and training and literacy programs; and prevention and treatment of HIV/AIDS, tuberculosis, and malaria. Social protection and labor assess government policies in the area of social protection and labor market regulation, which reduce the risk of becoming poor, assist those who are poor to better manage further risks, and ensure a minimal level of welfare to all people. Interventions include social safety net programs, pension and old age savings programs, protection of basic labor standards, regulations to reduce segmentation and inequity in labor markets, active labor market programs (such as public works or job training), and community-driven initiatives. In interpreting the guidelines, it is important to take into account the size of the economy and its level of development.

•

Policies and institutions for environmental sustainability assess the extent to which environmental policies foster the protection and sustainable use of natural resources and the management of pollution. Assessment of environmental sustainability requires multidimensional criteria (that is, for air, water, waste, conservation management, coastal zones management, and natural resources management). Public sector management and institutions • Property rights and rule-based governance assess the extent to which private economic activity is facilitated by an effective legal system and rule-based governance structure in which property and contract rights are reliably respected and enforced. Three dimensions are rated separately: legal basis for secure property and contract rights; predictability, transparency, and impartiality of laws and regulations affecting economic activity, and their enforcement by the legal and judicial system; and crime and violence as an impediment to economic activity. • Quality of budgetary and financial management assesses the extent to which there is a comprehensive and credible budget, linked to policy priorities; effective financial management systems to ensure that the budget is implemented as intended in a controlled and predictable way; and timely and accurate accounting and fiscal reporting, including timely and audited public accounts and effective arrangements for follow-up. • Efficiency of revenue mobilization assesses the overall pattern of revenue mobilization—not only the tax structure as it exists on paper, but revenue from all sources as they are actually collected. • Quality of public administration assesses the extent to which civilian central government staffs (including teachers, health workers, and police)

•

are structured to design and implement government policy and deliver services eﬀectively. Civilian central government staﬀs include the central executive together with all other ministries and administrative departments, including autonomous agencies. It excludes the armed forces, state-owned enterprises, and subnational government. Transparency, accountability, and corruption in public sector assess the extent to which the executive branch can be held accountable for its use of funds and the results of its actions by the electorate and by the legislature and judiciary, and the extent to which public employees within the executive are required to account for the use of resources, administrative decisions, and results obtained. Both levels of accountability are enhanced by transparency in decision making, public audit institutions, access to relevant and timely information, and public and media scrutiny.

Source: World Bank Group, CPIA database (www.worldbank.org/ida). Table .. Polity indicators Revised combined polity score is computed by subtracting the institutionalized autocracy score from the institutionalized democracy score; the resulting uniﬁed polity scale ranges from +10 (strongly democratic) to –10 (strongly autocratic). Institutionalized democracy is conceived as three essential, interdependent elements. First is the presence of institutions and procedures through which citizens can express

effective preferences about alternative policies and leaders. Second is the existence of institutionalized constraints on the exercise of power by the executive. Third is the guarantee of civil liberties to all citizens in their daily lives and in acts of political participation. Other aspects of plural democracy, such as the rule of law, systems of checks and balances, freedom of the press, and so on are means to, or specific manifestations of, these general principles. Coded data on civil liberties are not included. This is an additive 11-point scale (0–10). The operational indicator of democracy is derived from codings of the competitiveness of political participation using some weights. Institutionalized autocracy is a pejorative term for some very diverse kinds of political systems whose common properties are a lack of regularized political competition and concern for political freedoms. The term autocracy is used and defined operationally in terms of the presence of a distinctive set of political characteristics. In mature form autocracies sharply restrict or suppress competitive political participation. Their chief executives are chosen in a regularized process of selection within the political elite, and once in office they exercise power with few institutional constraints. Most modern autocracies also exercise a high degree of directiveness over social and economic activity, but this is regarded here as a function of political ideology and choice, not a defining property of autocracy. Social democracies also exercise relatively high degrees of directiveness. Source: Data are from the Integrated Network for Societal Conflict Research (INSCR), Polity IV Project, Political Regime Characteristics and Transitions, 1800–2010 (www. systemicpeace.org/inscr/inscr.htm).

Technical notes

189

Technical notes references

CDIAC (Carbon Dioxide Information Analysis Center). n.d. Online database. [http://cdiac.ornl.gov/home.html]. Oak Ridge National Laboratory, Environment Sciences Division, Oak Ridge, Tenn. Chen, Shaohua, and Martin Ravallion. 2011. “The Developing World Is Poorer Than We Thought, But No Less Successful in the Fight Against Poverty.” Quarterly Journal of Economics 125 (4): 1577–1625. FAO (Food and Agriculture Organization of the United Nations). 2010. Global Forest Resources Assessment 2010. Rome: Food and Agriculture Organization. ———. n.d. AQUASTAT. [www.fao.org/nr/water/aquastat/ data/query/index.html]. Rome. ———. n.d. FAOSTAT. [http://faostat.fao.org]. ———. n.d. Food Security Statistics database. [www.fao.org/ economic/ess/food-security-statistics/]. Rome.

———. Various years. International Financial Statistics. Washington, DC: International Monetary Fund. ———. Various years. Direction of Trade Statistics Yearbook. Washington, DC: International Monetary Fund. ———. Various years. International Financial Statistics Yearbook. Washington, DC: International Monetary Fund. IRF (International Road Federation). 2011. World Road Statistics. Geneva: International Road Federation. ITU (International Telecommunication Union). n.d. World Telecommunication/ICT Indicators database. Geneva: International Telecommunication Union. OECD (Organisation for Economic Co-operation and Development). 2011. African Economic Outlook 2011: Africa and Its Emerging Partners. Paris: Organisation for Economic Co-operation and Development. ———. n.d. National Accounts Statistics database. Paris

IDA (International Development Association) and IMF (International Monetary Fund). 2011. “Heavily Indebted Poor Countries (HIPC) Initiative and Multilateral Debt Relief Initiative (MDRI)—Status of Implementation and Proposals for the Future of the HIPC Initiative.” International Development Association and International Monetary Fund, Washington, DC. IEA (International Energy Agency). Various years. Energy Statistics of OECD Countries. Paris: International Energy Agency. ILO (International Labour Organization). Various years. Key Indicators of the Labor Market. Geneva: International Labour Organization. IMF (International Monetary Fund). 1977. Balance of Payments Manual. 4th ed. Washington, DC: International Monetary Fund. ———. 1993. Balance of Payments Manual. 5th ed. Washington, DC: International Monetary Fund. ———. Various years. Balance of Payments Statistics Yearbook. Parts 1 and 2. Washington, DC: International Monetary Fund. ———. Various years. Direction of Trade Statistics Quarterly. Washington, DC: International Monetary Fund. ———. Various years. Government Finance Statistics Yearbook. Washington, DC: International Monetary Fund.

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Africa Development Indicators 2012/13

———. n.d. Creditor Reporting System database. [http:\stats. oecd.org/index.aspx?DatasetCode=CRSNEW]. Paris. ———. n.d. National Accounts database. Paris. ———. Various years. Geographical Distribution of Financial Flows to Developing Economies. Paris: Organisation for Economic Co-operation and Development. ———. Various years. National Accounts. Vol. 1. Main Aggregates. Paris: Organisation for Economic Co-operation and Development. ———. Various years. National Accounts. Vol. 2. Detailed Tables. Paris: Organisation for Economic Co-operation and Development. OECD (Organisation for Economic Co-operation and Development) DAC (Development Assistance Committee. Various years. Geographical Distribution of Financial Flows to Developing Economies. Paris: Organisation for Economic Co-operation and Development. ———. n.d. International Development Statistics. [www.oecd. org/dac/stats/idsonline]. Paris. Ravallion, Martin, Shaohua Chen, and Prem Sangraula. 2009. “Dollar a Day Revisited.” World Bank Economic Review 23 (2):163–84.

Standard & Poor’s. 2000. The S&P Emerging Market Indices: Methodology, Definitions, and Practices. New York: Standard & Poor’s. ———. 2012. Global Stock Markets Factbook 2011. New York: Standard & Poor’s. UNAIDS (Joint United Nations Programme on HIV/AIDS) and WHO (World Health Organization). Various years. Global Report: UNAIDS Report on the Global AIDS Epidemic. Geneva: Joint United Nations Programme on HIV/AIDS. UNCTAD (United Nations Conference on Trade and Development). 1995. Handbook of International Trade and Development. New York and Geneva: United Nations Conference on Trade and Development. ———. 2007. Trade and Development Report 2007: Regional Cooperation for Development. New York and Geneva: United Nations Conference on Trade and Development. ———. n.d. UNCTADStat. Information Economy. [http:// unctadstat.unctad.org]. Geneva. UNESCO (United Nations Educational, Scientific, and Cultural Organization). 1997. International Standard Classification of Education. Paris: United Nations Educational, Scientific, and Cultural Organization. UNESCO (United Nations Educational, Scientific, and Cultural Organization) Institute of Statistics. n.d. Online database. [www.uis.unesco.org]. Montreal. UNICEF (United Nations Children’s Fund). Various issues. Multiple Indicator Cluster surveys. [www.childinfo.org]. New York. ———. Various issues. The State of the World’s Children. New York: Oxford University Press. UNICEF (United Nations Children’s Fund), WHO (World Health Organization), World Bank, and United Nations Population Division. 2010. “Levels and Trends of Child Mortality in 2010: Estimates Developed by the UN Interagency Group for Child Mortality Estimation.” Working Paper. New York: United Nations. UN Inter-agency Group for Child Mortality Estimation. n.d. Child Mortality Estimation Info database. [www. childmortality.org]. New York. ———. 2011. Levels and Trends in Child Mortality: Report 2011. New York.

United Nations Statistics Division. n.d. “International Standard Industrial Classification of All Economic Activities, Third Revision.” [http://unstats.un.org/unsd/cr/registry/]. New York. United Nations Population Division. 2009. Trends in Total Migrant Stock: 2008 Revision. New York: United Nations, Department of Economic and Social Affairs. ———. 2011. World Population Prospects: The 2010 Revision. New York: United Nations, Department of Economic and Social Affairs. ———. Various years. World Population Prospects. New York: United Nations, Department of Economic and Social Affairs. United Nations Statistics Division. 2010. “Implementation of Population Census Topics in the 2010 Round.” [http:// unstats.un.org/unsd/demographic/sources/census/2010_ phc/census_clock/TopicsPerCountry.pdf]. New York. ———. Various years. National Accounts Statistics: Main Aggregates and Detailed Tables. Part 1 and 2. New York: United Nations. ———. Various years. National Income Accounts. New York: United Nations. ———. Various years. Energy Statistics Yearbook. New York: United Nations.

———. Center for Systemic Peace. 2011. Polity IV Project, Political Regime Characteristics and Transitions, 18002010 [www.systemicpeace.org/inscr/inscr.htm]. USA WHO (World Health Organization). n.d. Global Atlas of the Health Workforce. [http://apps.who.int/globalatlas/]. Geneva: World Health Organization. ———. n.d. National Health Account database. [www.who. int./nha/en/]. Geneva. ———. Various years. World Malaria Report. Geneva: World Health Organization. ———. Various years. World Health Statistics. Geneva: World Health Organization. ———. Various years. Global Tuberculosis Control Report. Geneva: World Health Organization. WHO (World Health Organization), UNICEF (United Nations Children’s Fund), UNFPA (United Nations Population Fund), and World Bank. 2010. Trends in Maternal Mortality: 1990–2008: Estimates Developed by WHO, UNICEF, UNFPA and the World Bank. Geneva: World Health Organization.

———. n.d. Doing Business Online. [http://doingbusiness. org]. Washington, DC. ———. n.d. Enterprise Surveys Online. [http:// enterprisesurveys.org]. Washington, D,.C. ———. n.d. Private Participation in Infrastructure database. [http://ppi.worldbank.org]. Washington, DC. ———. n.d. PovcalNet. Online database. [http://iresearch. worldbank.org/PovcalNet]. Washington, DC. ———. n.d. World trade Indicators Online database. [http:// worldbank.org/wti]. Washington, DC. ———. n.d. World Bank Economic Policy and Debt Online database. [http://worldbank.org/economicpolicyanddebt]. Washington, DC. ———. n.d. CPIA database [www.worldbank.org/ida]. Washington, DC. ———. Various years. Global Development Finance: External Debt of Developing Countries. Washington, DC: World Bank.

World Bank. 2000. Trade Blocs. New York: Oxford University Press.

WTO (World Trade Organization). n.d. Regional Trade Agreements Gateway. [www.wto.org/English/tratop_e/ region_e/region_e.htm]. Geneva.

———. 2011a. Doing Business 2012. Washington, DC: World Bank.

———. n.d. Regional Trade Agreements Information System. Online database. [http:/rtais.wto.org/]. Geneva.

Technical notes references

191

Primary data documentation Currency

National accounts

Base year

SUB-SAHARAN AFRICA Angola Angolan kwanza Benin CFA franc Botswana Botswana pula Burkina Faso CFA franc Burundi Burundi franc Cameroon CFA franc Cape Verde Cape Verde escudo Central African Republic CFA franc Chad CFA franc Comoros Comorian franc Congo, Dem. Rep. Congolese franc Congo, Rep. CFA franc Côte d'Ivoire CFA franc Equatorial Guinea CFA franc Eritrea Eritrean nakfa Ethiopia Ethiopian birr Gabon CFA franc Gambia, The Gambian dalasi Ghana New Ghanaian cedi Guinea Guinean franc Guinea-Bissau CFA franc Kenya Kenyan shilling Lesotho Lesotho loti Liberia Liberian dollar Madagascar Malagasy ariary Malawi Malawi kwacha Mali CFA franc Mauritania Mauritanian ouguiya Mauritius Mauritian rupee New Mozambican metical Mozambique Namibia Namibian dollar Niger CFA franc Nigeria Nigerian naira Rwanda Rwandan franc São Tomé and Príncipe São Tomé and Príncipe dobra Senegal CFA franc Seychelles Seychelles rupee Sierra Leone Sierra Leonean leone Somalia Somali shilling South Africa South African rand South Sudan South Sudanese Pound Sudan Sudanese pound Swaziland Swaziland lilangeni Tanzania Tanzanian shilling Togo CFA franc Uganda Ugandan shilling Zambia Zambian kwacha Zimbabwe U.S. dollar NORTH AFRICA Algeria Algerian dinar Djibouti Djibouti franc Egypt, Arab Rep. Egyptian pound Libya Libyan dinar Morocco Moroccan dirham Tunisia Tunisian dinar

Reference year

1997 1985 1993/94 1999 1980 2000 1980 2000 1995 1990 1987 1978 1996 2000 1992 1999/2000 1991 1987 2006 1996 2005 2001 1995 1992 1984 1994 1987 2004 2006 2003 2004/05 1987 2002 1995 2001 1999 1986 1990 1985 2005

1987

1981/82b 2000

1996

2001

1978 2001/02 1994 2009 1980 1990 1991/92 1999 1998 1990

System of national accounts

SNA price valuation

Alternative conversion factor

PPP survey year

1968 1968 1993 1993 1993 1993 1968 1968 1993 1968 1968 1968 1968 1968 1968 1993 1993 1993 1993 1993 1993 1993 1993 1968 1968 1993 1968 1993 1993 1993 1993 1993 1993 1993 1993

VAP VAP VAB VAB VAB VAB VAP VAB VAB VAP VAB VAP VAP VAB VAB VAB VAP VAB VAB VAB VAB VAB VAB VAP VAB VAB VAB VAB VAB VAB VAB VAP VAB VAP VAP

1991-96 1992

2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005

1993 1968 1993 1968 1993 2008 1968 1968 1993 1968 1968 1968 1993

VAB VAP VAB VAB VAB VAB VAB VAB VAP VAB VAB VAB VAB VAB VAB VAB VAB VAB

Note: For explanation of the abbreviations used in the table see notes following the table. b. Reporting period switch from fiscal year to calendar year from 1996. Pre-1996 data converted to calendar year. c. Original chained constant price data are rescaled.

192

Africa Development Indicators 2012/13

1992-93

1999-2001 1993 1965-84

1993 1973-87

1992-95 1993 1971-98 1994

Balance of payments and trade Balance of Payments Manual External System in use debt of trade

BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM4 BPM5 BPM5

S S G G S S G S S S S S S G

BPM4 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM4 BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM4

Actual Actual Actual Actual Actual Estimate Estimate Actual Actual Actual Actual Actual Actual Actual Actual Actual

2005

BPM5 BPM5 BPM5

2005

BPM5

Actual Actual Actual Estimate Preliminary

2005 2005 2005 2005 2005 2005 2005

BPM5 BPM5 BPM5 BPM5 BPM5 BPM5 BPM4

Actual Actual Actual Actual Actual Preliminary Actual

G G G S G S G

BPM5 BPM5 BPM5 BPM5 BPM5 BPM5

Actual Actual Actual

S G G G S G

2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005

1977-90

1990-92 1991, 1998

Actual Actual Actual Actual Preliminary Actual Actual Preliminary Actual Actual Estimate Estimate Estimate

2005 2005 1986 2005 2005

Actual Actual Actual Actual

Actual Actual

G S G G S G G G S S G S S G S G S G G S G G S

Government finance IMF data dissemination standard

Latest population census

Latest demographic, education or health household survey

Source of most recent income and expenditure data

B B B C B C B

G G G G G G G G G

C C C

G G G

MICS, 2001; MIS, 2006/07 DHS, 2006 MICS, 2000 MICS, 2006 MICS, 2005 MICS, 2006 DHS, 2005 MICS, 2006 DHS, 2004 MICS, 2000 MICS, 2010 AIS, 2009; DHS, 2005 MICS, 2006

IHS, 2000 CWIQ, 2003 ES/BS, 2003 CWIQ, 2009 CWIQ, 2006 PS, 2007 ES/BS, 2007 PS, 2008 PS, 2002/03 IHS, 2004 1-2-3, 2005/06 CWIQ/PS, 2005 IHS, 2008

G G G G G G G G G G G G G G G G G G G

1970 2002 2011 2006 2008 2005 2010 2003 2009 2003 1984 2007 1998 2002 1984 2007 2003 2003 2010 1996 2009 2009 2006 2008 1993 2008 2009 2000 2011 2007 2001 2001 2006 2002

DHS, 2002 DHS, 2005 DHS, 2000 MICS, 2005/06 DHS, 2008 DHS, 2005 MICS, 2010 DHS, 2008/09; MIS, 2010 DHS, 2009/10 DHS, 2007; MIS, 2009 DHS, 2008/09 DHS, 2010 DHS, 2006; Special, 2010 MICS, 2007

ES/BS, 2005 CWIQ/IHS, 2005 IHS, 2003 LSMS, 2006 CWIQ, 2007 CWIQ, 2002 IHS, 2005/06 ES/BS, 2002/03 CWIQ, 2007 PS, 2010 LSMS, 2004/05 IHS, 2010 IHS, 2008

DHS, 2003; AIS, 2009 DHS, 2006/07; HIV/MCH SPA, 2009 DHS, 2006 DHS, 2008 DHS, 2007/08

ES/BS, 2008 ES/BS, 2004 CWIQ/PS, 2008 IHS, 2010 IHS, 2011

Accounting concept

C B B B C B C B C B B B C

Latest Vital registration agricultural census complete

1964-65 2011-2012 1993 2010

Yes

Latest industrial data

Latest water withdrawal Latest data trade data

1991 2006 2010 2010 2010 2010 2010 2009 1995 2007 1986 2005 2010

2009-2010 1996-97 2005-2007 2007 2008

2010 2005 2010 2006 2005 2007 2009 2006 2008 2009 2009 2010 2010 2009 2009 2010 2010 2010 2010 2010 2002 2010 2010 2008 2009 2010 2007 2010 2010 2010 2010 2003 2006 2009

1984 2004 1985 2011 1990 1985-86 2001

2001-02 1974-75 2001-02 2011 2000-01 1988 1977-79 2010 2004 2006-2007

Yes

2005 2011 2010 2010 2010 2008 2005 2010 2008 1985 2010 2010 2010 2010 2010 2010 2008 2010 2010 2010

2000 2001 2000 2000 2000 2000 2000 2000 1999 2000 2002 2000 2000 2004 2002 2000 2000 2000 2000 2000 2003 2000 2000 2000 2000 2000 2000 2003 2000 2000 2000 2000 2000

2001

DHS, 2008/09

PS, 2000/01

2011

2005

2010

1993

B C B

G G G

DHS, 2005; MIS, 2008/09

PS, 2005 IHS, 2007 IHS, 2003

2011-2012 2011 1984-85

2011 2008 2002 1982 2010

2002 2005 2000 2003 2000

B B

G G G G G G G

2002 2010 2004 1987 2001 2008 2008 2007 2002 2010 2002 2010 2002

G G S G S S

2008 2009 2006 2006 2004 2004

B B B C B C C C

DHS, 2008 MICS, 2006 DHS, 2003

ES/BS, 2009

2012

2010 2009 2003 1990 2010

MICS, 2010 MICS, 2010 DHS, 2010 MICS, 2010 DHS, 2006; MIS, 2009/10 DHS, 2007 DHS, 2005/06

ES/BS, 2009 ES/BS, 2010 ES/BS, 2007 CWIQ, 2006 PS, 2009 IHS, 2006 IHS, 2003

2003 2007-2008 2011-2012 2008 1990 1960

2010 2010 2010 2005 2010 2010 2010

2009 2007 2011 2010 2010 2010 2010

2000 f 2000 2002 2002 2002 2000 2002

MICS, 2006 MICS, 2006 DHS, 2008 MICS, 2000 MICS, 2006 MICS, 2006

IHS, 1995 PS, 2002 ES/BS, 2008

2009 2007 2010 2008 2010 2010

2010 2009 2010 2004 2010 2010

2000 2000 2000 2000 2000 2001

ES/BS, 2007 IHS, 2005/06

Yes

2001 Yes

2010 2001 2012 2004

Primary data documentation

193

Primary data documentation notes Base year is the base or pricing period used for constant price calculations in the country’s national accounts. Price indexes derived from national accounts aggregates, such as the implicit deflator for gross domestic product (GDP), express the price level relative to base year prices. Reference year is the year in which the local currency, constant price series of a country is valued. The reference year is usually the same as the base year used to report the constant price series. However, when the constant price data are chain linked, the base year is changed annually, so the data are rescaled to a specific reference year to provide a consistent time series. When the country has not rescaled following a change in base year, World Bank staff rescale the data to maintain a longer historical series. To allow for cross-country comparison and data aggregation, constant price data reported in Africa Development Indicators are rescaled to a common reference year (2000) and currency (U.S. dollars). System of National Accounts identifies countries that use the 1993 System of National Accounts (1993 SNA), the terminology applied in Africa Development Indicators since 2001, to compile national accounts. Although more countries are adopting the 1993 SNA, many still follow the 1968 SNA, and some low-income countries use concepts from the 1953 SNA. Rebasing national accounts: When countries rebase their national accounts, they update the weights assigned to various components to better reflect current patterns of production or uses of output. The new base year should represent normal operation of the economy—it should be a year without major shocks or distortions. Some developing countries have not rebased their national accounts for many years. Using an old base year can be misleading because implicit price and volume weights become progressively less relevant and useful. To obtain comparable series of constant price data, the World Bank rescales GDP and value added by industrial origin to a common reference year. This year’s Africa Development Indicators continues to use 2000 as the reference year. Because rescaling changes the implicit weights 194

Africa Development Indicators 2012/13

used in forming regional and income group aggregates, aggregate growth rates in this year’s edition are not comparable with previous editions with different base years. Rescaling may result in a discrepancy between rescaled GDP and the sum of the rescale’s components. Because allocating the discrepancy would cause distortions in the growth rates, the discrepancy is left unallocated. As a result, the weighted average of the growth rates of the components generally will not equal the GDP growth rate. SNA price valuation shows whether value added In the national accounts is reported at basic prices (VAB) or producer prices (VAP). Producer prices include taxes paid by producers and thus tend to overstate the actual value added in production. However, VAB can be higher than VAP In countries with high agricultural subsidies. Alternative conversion factor identifies the countries and years for which a World Bank-estimated conversion factor has been used in place of the official exchange rate (line rf in the International Monetary Fund’s International Financial Statistics). Purchasing power parity (PPP) survey year is the latest available survey year tor the International Comparison Program’s (ICP) estimates of PPP. PPP rates are calculated by simultaneously comparing the prices of similar goods and services among a large number countries. In the most recent price survey conducted by the ICP, 146 countries and territories participated, including China and India. The PPP conversion factors are from three sources: (a) For 47 high- and upper middle-income countries, conversion factors are provided by Eurostat and the Organisation for Economic Co-operation and Development (OECD), with PPP estimates for 35 European countries new price data collected since 2005. (b) The remaining 2005 ICP countries’ PPP are extrapolated from the 2005 ICP benchmark results, which account for relative price changes between each economy and the United States. (c) For countries that did not participate in the 2005 ICP round, the PPP estimates are imputed using a statistical model. More information on the results of the 2005 ICP is available at www. worldbank.org/data/icp. Balance of Payments Manual in use refers to the classification system used to

compile and report data on balance of payments items. BPM4 refers to the 4th edition of the IMF’s Balance of Payments Manual (1977), and BPM5 to the 5th edition (1993). The BPM5 redefined as capital transfers some transactions previously included in the current account, such as debt forgiveness, migrants’ capital transfers, and foreign aid to acquire capital goods. Thus the current account balance now reflects more accurately net current transfer receipts in addition to transactions in goods, services (previously nonfactor services), and income (previously factor income). Many countries maintain their data collection systems according to BPM4. Where necessary, the IMF converts such reported data to conform with BPM5. The balance accounts are divided into two groups: (a) the current account, which records transactions in goods, services, income, and current transfers, and (b) the capital and financial account, which records capital transfers, acquisition or disposal of nonproduced, nonfinancial assets, and transactions in financial assets and liabilities. Discrepancies may arise in the balance of payments because there is no single source for balance of payments data and therefore no way to ensure that the data are fully consistent. Sources include customs data, monetary accounts of the banking system, external debt records, information provided by enterprises, surveys to estimate service transactions, and foreign exchange records. Differences in collection methods—such as in timing, definitions of residence and ownership, and the exchange rate used to value transactions—contribute to net errors and omissions. In addition, smuggling and other illegal or quasi-legal transactions may be unrecorded or misrecorded. External debt shows debt reporting status for 2010 data. Actual indicates that data are as reported, preliminary that data are based on reported or collected information but include an element of staff estimation, and estimate that data are World Bank staff estimates. System of trade refers to the United Nations general trade system (G) or special trade system (S). Under the general trade system, goods entering directly for domestic consumption and goods entered into customs storage are recorded as imports at arrival.

Under the special trade system, goods are recorded as imports when declared for domestic consumption whether at time of entry or on withdrawal from customs storage. Exports under the general system comprise outward-moving goods: (a) national goods wholly or partly produced in the country; (b) foreign goods, neither transformed nor declared for domestic consumption in the country, that move outward from customs storage; and (c) nationalized goods that have been declared for domestic consumption and move outward without being transformed. Under the special system of trade, exports are categories (a) and (c). In some compilations, categories (b) and (c) are classified as re-exports. Direct transit trade—goods entering or leaving for transport only—is excluded from both import and export statistics. Government finance accounting concept is the accounting basis for reporting central government financial data. For most countries, government finance data have been consolidated (C) into one set of accounts capturing all central government fiscal activities. Budgetary central government accounts (B) exclude some central government units and provide an incomplete picture. These are based on the concepts and recommendations of the second edition of the International Monetary Fund’s (IMF) Government Finance Statistics Manual 2001. The IMF reclassified historical Government Finance Statistics Yearbook data to conform to the 2001 manual’s format. IMF data dissemination standard shows the countries that subscribe to the IMF’s Special Data Dissemination Standard (SDDS) or General Data Dissemination System (GDDS). S refers to countries that subscribe to the SDDS and have posted data on the Dissemination Standards Bulletin Board at http://dsbb.imf.org. G refers to countries that subscribe to the GDDS. The SDDS was established for member countries that have or might seek access to international capital markets to guide them in providing their economic and financial data to the public. The GDDS helps countries disseminate comprehensive, timely, accessible, and reliable economic, financial, and socio-demographic statistics. IMF member countries elect to participate in either the SDDS or the GDDS. Both standards enhance the availability of Primary data documentation

195

timely and comprehensive data and therefore contribute to the pursuit of sound macroeconomic policies. The SDDS is also expected to improve the functioning of financial markets. Latest population census shows the most recent year in which a census was conducted and in which at least preliminary results have been released. The preliminary results from the very recent censuses could be reflected in timely revisions if basic data are available, such as population by age and sex, as well as the detailed definition of counting, coverage, and completeness. Countries that hold register-based censuses produce similar census tables every 5 or 10 years. Latest demographic, education, or health household survey indicates the household surveys used to compile the demographic, education, and health data. AIS is HIV/AIDS Indicator Survey, DHS is Demographic and Health Survey, LSMS is Living Standards Measurement Survey, MICS is Multiple Indicator Cluster Survey, MIS is Malaria Indicator Survey, and SPA is Service Provision Assessments. Detailed information for AIS, DHS, MIS, and SPA is available at www.measuredhs.com/WhatWe-Do/Survey-Types/DHS.cfm for MICS at www.childinfo.org. Source of most recent Income and expenditure data shows household surveys that collect Income and expenditure data. Names and detailed information on household surveys can be found on the website of the International Household Survey Network (www.surveynetwork.org). Core Welfare Indicator Questionnaire Surveys (CWIQ), developed by the World Bank, measure changes in key social indicators for different population groups—specifically indicators of access, utilization, and satisfaction with core social and economic services. Expenditure survey/budget surveys (ES/BS) collect detailed information on household consumption as well as on general demographic, social, and economic characteristics. Integrated household surveys (IHS) collect detailed information on a wide variety of topics, including health, education, economic activities, housing, and utilities. Income surveys (IS) collect information on the income and wealth of households as well as various social and economic characteristics. 196

Africa Development Indicators 2012/13

Labor force surveys (LFS) collect information on employment, unemployment, hours of work, income, and wages. Living Standards Measurement Surveys (LSMS), developed by the World Bank, provide a comprehensive picture of household welfare and the factors that affect it; they typically incorporate data collection at the individual, household, and community levels. Priority surveys (PS) are a light monitoring survey, designed by the World Bank, for collecting data from a large number of households cost-effectively and quickly. 1-2-3 surveys (1-2-3) are implemented in three phases and collect socio-demographic and employment data, data on the informal sector, and information on living conditions and household consumption. Vital registration complete identifies countries that report at least 90 percent complete registries of vital (birth and death) statistics to the United Nations Statistics Division and reported in Population and Vital Statistics Reports. Countries with complete vital statistics registries may have more accurate and more timely demographic indicators than other countries. Latest agricultural census shows the most recent year in which an agricultural census was conducted and reported to the Food and Agriculture Organization of the United Nations. Latest industrial data show the most recent year for which manufacturing value added data at the three-digit level of the International Standard Industrial Classification (ISIC, revision 2 or 3) are available in the United Nations Industrial Development Organization database. Latest trade data show the most recent year for which structure of merchandise trade data from the United Nations Statistics Division’s Commodity Trade (Comtrade) database are available. Latest water withdrawal data show the most recent year for which data on freshwater withdrawals have been compiled from a variety of sources. The freshwater resources are based on estimates of runoff into rivers and recharge of groundwater. These estimates are based on different sources and refer to different years, so cross-country comparisons should be made with caution. Because the data are collected intermittently,

they may hide signiďŹ cant variations in total renewable water resources from year to year. The data also fail to distinguish between seasonal and geographic variations in water

availability within countries. Data for small countries and countries in arid and semiarid zones are less reliable than those for larger counties and countries with greater rainfall.

Primary data documentation

197

Map of Africa

IBRD 39767 20° W

10° W

0°

20° E

30° E

40° E

50° E

Tunis

TUNISIA

Rabat

Madeira Islands (Por.)

10° E

Algiers

Mediterranean Sea

Tripoli

MOROCCO

30° N

Cairo

Canary Islands (Sp.)

ALGERIA

ARAB REPUBLIC OF EGYPT

LIBYA

WESTERN SAHARA

R e d

MAURITANIA

SUDAN

NIGER Dakar

THE GAMBIA

SENEGAL

BURKINA Ouagadougou FASO

Bamako

Banjul Bissau

10° N

MALI

Nouakchott

Praia

GUINEA

GUINEA-BISSAU

Conakry Freetown

SIERRA LEONE Monrovia

LIBERIA

20° N

e a

CAPE VERDE

20° N

Niamey

Asmara

DJIBOUTI Djibouti

São Tomé

Annobón I. (Eq. G.)

Gulf of Aden

Djibouti

NIGERIA

10° N

Addis Ababa

Abuja

PortoLomé Novo Accra Gulf of Guinea Malabo

EQUATORIAL GUINEA SÃO TOMÉ AND PRÍNCIPE

0°

ERITREA

Khartoum

N’Djamena

BENIN CÔTE GHANA TOGO D'IVOIRE Yamoussoukro

CHAD

SOUTH SUDAN

CENTRAL AFRICAN REP. REP.

CAMEROON

Bangui

ETHIOPIA SOMALIA

Juba

Yaoundé

UGANDA Libreville

GABON

CONGO

Brazzaville

Kampala

DEM.REP REP.. OF CONGO

RWANDA

0°

Nairobi

Kigali

Bujumbura

Mogadishu

KENYA

INDIAN

BURUNDI

Kinshasa

Victoria Dodoma

Ascension (U.K.)

SEYCHELLES

TANZANIA

Luanda

10° S

ANGOLA

O C E A N

ZAMBIA

Mayotte (Fr.)

Lilongwe

l ne

MADAGASCAR

Antananarivo

Réunion (Fr.)

BOTSWANA

Windhoek

MAURITIUS

Port-Louis

NAMIBIA

MOZAMBIQUE

iqu

ZIMBABWE

eC h

Harare 20° S

Agalega Is. (Mau.)

Moroni

Lusaka

St. Helena (U.K.)

10° S

COMOROS

MALAWI

A T L A N T I C

OCEAN

Gaborone Pretoria Maputo Mbabane

SOUTH AFRICA

30° S

SWAZILAND

Maseru

30° S

LESOTHO

GSDPM Map Design Unit 40° S

This map was produced by the Map Design Unit of The World Bank. The boundaries, colors, denominations and any other information shown on this map do not imply, on the part of The World Bank Group, any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.

20° W

10° W

40° S

0°

10° E

20° E

30° E

40° E

50° E

JANUARY 2013

198

Africa Development Indicators 2012/13