Africa Development Indicators 2006 (African Development Indicators)

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FROM PROMISES TO RESULTS

AFRICA

DEVELOPMENT INDICATORS

2006

from the World Bank Africa Database

THE WORLD BANK Washington, D.C.

Copyright © 2006 by the International Bank for Reconstruction and Development/The World Bank 1818 H Street, N.W. Washington, D.C. 20433, U.S.A. All rights reserved Manufactured in the United States of America First printing September 2006 1 2 3 4 08 07 06 The ﬁndings, interpretations, and conclusions expressed in this book are entirely those of the authors and should not be attributed in any manner to the World Bank, to its aﬃliated organizations, or to members of its Board of Executive Directors or the countries they represent. The World Bank does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The boundaries, colors, denominations, and other information shown on any map in this volume do not imply on the part of the World Bank Group any judgment on the legal status of any territory or the endorsement or acceptance of such boundaries. The material in this publication is copyrighted. The World Bank encourages dissemination of its work and will normally grant permission to reproduce portions of the work promptly. Permission to photocopy items for internal or personal use, for the internal or personal use of speciﬁc clients, or for classroom use is granted by the World Bank, provided that the appropriate fee is paid directly to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA; telephone 978-750-8400, fax 978-750-4470. Please contact the Copyright Clearance Center before photocopying items. For permission to reprint individual articles or chapters, please fax a request with complete information to the Republication Department, Copyright Clearance Center, fax 978-750-4470. All other queries on rights and licenses should be addressed to the Oﬃce of the Publisher, World Bank, at the address above or faxed to 202-522-2422. To order the Africa Development Indicators 2006, The Little Data Book on Africa 2006, and World Bank Africa Database 2006 (Multipleuser CD-ROM), please visit the publications web site at www.worldbank.org/publications. For more information about the Africa Development Indicators and its companion products, please visit our web site at www.worldbank.org/africa. You can email us at [email protected]. Cover design by Michael Diavolikis of Communications Development Incorporated. Photo credits: front cover, Curt Carnemark; top row, left to right, Trevor Samson/World Bank; Curt Carnemark/World Bank; Scott Wallace/World Bank; Eric Miller/World Bank; Curt Carnemark/World Bank; back cover, small top inset, Eric Miller/World Bank; large top inset, Curt Carnemark/World Bank; bottom, left to right: Scott Wallace/World Bank; Eric Miller/World Bank; Curt Carnemark/World Bank; Ray Witlin/World Bank; Eric Miller/World Bank. ISBN-10: 0-8213-6537-1 ISBN-13: 978-0-8213-6537-3 eISBN: 0-8213-6538-X DOI: 10.1596/978-0-8213-6537-3

Contents Foreword Acknowledgments

vi vii

Moving from the Year of Africa to the Decade of Africa— From Promises to Results Notes References

1 20 21

Indicator tables Part I. Basic indicators and national accounts

23

1. Basic indicators 1.1 Basic indicators

25

2. National accounts 2.1 Gross domestic product, real 2.2 Gross domestic product per capita, real 2.3 Agriculture value added 2.4 Industry value added 2.5 Services value added 2.6 Gross domestic product, nominal 2.7 Total consumption 2.8 General government consumption 2.9 Gross ﬁxed capital formation 2.10 General government ﬁxed capital formation 2.11 Private sector ﬁxed capital formation 2.12 Gross domestic savings 2.13 Gross national savings 2.14 Resource balance (exports minus imports) 2.15 Exports of goods and services, nominal 2.16 Imports of goods and services, nominal 2.17 Exports of goods and services, real 2.18 Imports of goods and services, real 2.19 Gross domestic product growth 2.20 Gross domestic product per capita growth 2.21 Gross national income per capita 2.22 Total consumption per capita

26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

Contents

iii

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 equality 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 50 51 52 53 54 55 56

Part III. Development outcomes Results framework 4.1 Status of Paris Declaration indicators

58

Drivers of growth 5. Private sector development 5.1 Business environment 5.2 Investment climate

59 60

6. Trade 6.1 International trade and tariﬀ barriers 6.2 Regional integration, trade blocs

62 65

7. Infrastructure 7.1 Water and sanitation 7.2 Transportation 7.3 Information and communication technology 7.4 Energy 7.5 Financial sector infrastructure

66 68 70 72 74

Participating in growth

iv

Africa Development Indicators 2006

8. Human development 8.1 Education 8.2 Health

76 78

9. Agriculture and rural development 9.1 Rural development 9.2 Agriculture

81 82

10. Labor, migration, and population 10.1 Labor 10.2 Migration and population

84 86

11. HIV/AIDS 11.1 HIV/AIDS

87

12. Malaria 12.1 Malaria

88

13. Capable states and partnership 13.1 Aid and debt relief 13.2 Capable states 13.3 Governance and anticorruption indicators 13.4 Country Policy and Institutional Assessment ratings, 2005

89 90 92 94

Part IV: Household Welfare 14. Household welfare 14.1 Burkina Faso household survey, 2003 14.2 Burundi household survey, 1998 14.3 Cameroon household survey, 2001 14.4 Côte d’Ivoire household survey, 1998 14.5 Ethiopia household survey, 2000 14.6 Gambia household survey, 1998 14.7 Ghana household survey, 1998/99 14.8 Kenya household survey, 1997 14.9 Madagascar household survey, 1999 14.10 Malawi household survey, 1997/98 14.11 Mozambique household survey, 1996 14.12 Nigeria household survey, 2004 14.13 São Tomé and Principe household survey, 2000 14.14 Sierra Leone household survey, 2002/03 14.15 Uganda household survey, 2002/03 14.16 Zambia household survey, 1998

95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110

Technical notes

111

Statistical references

147

Users guide: World Bank Africa Database 2006 and Africa Development Indicators CD-ROM

151

Contents

v

Foreword Making headway against African poverty and meeting the Millennium Development Goals are raising diﬃcult challenges in most African countries. Despite pockets of success, nearly half the region’s population still lives in extreme poverty, and Africa still houses about three-fourths of the world’s poorest countries. But Africa is today a continent on the move. Average economic growth remains strong, exports are increasing, and many countries are making tangible progress on delivering better health and education outcomes. Africa Development Indicators 2006 is the latest annual report from the World Bank on social and economic conditions across the continent. It was revamped this year to better report and monitor the challenges and transformations in Africa. Africa Development Indicators has evolved from a single data book, and this year consists of three independent but complementary products: this book, which brings together an essay and key outcome indicators for Africa, The Little Data Book on Africa 2006, and the World Bank Africa Database (CD-ROM). Each year’s essay will discuss a topic of relevance for Africa. Starting the new series is an essay about the Year and the Decade of Africa. The essay takes stock of how countries and donors performed during 2005, which was marked by meetings of the UN Millennium Task Force, the U.K. Commission for Africa, and the Group of Eight Summit at Gleneagles, Scotland, and culminated in the UN Millennium+5 Summit in New York. The essay reﬂects both the magnitude of the challenges and the strength of the response and also sounds a clear warning on the need to move from promises to results to meet the Millennium Development Goals by 2015. Data in the book have been assembled from a variety of sources to present a broad vi

Africa Development Indicators 2006

picture of development across Africa. The book is designed to provide a set of key indicators to monitor development outcomes in the region. It is an important reference tool for those who want a better understanding of the economic and social developments occurring in Africa. The tables comprise a selection of key development outcome indicators from 1980 to 2004. They oﬀer detailed information in areas such as the Millennium Development Goals, private sector development, trade, agriculture and rural development, HIV/AIDS and malaria, infrastructure, the Paris Declaration, governance, and aid. The Little Data Book on Africa 2006 is a pocket edition of Africa Development Indicators and is intended as a quick reference on the most recent key indicators for users of Africa Development Indicators 2006. The World Bank Africa Database 2006 offers the most comprehensive database on Africa, covering about 1,200 indicators of macroeconomic, sectoral, and human development variables, with time series of many indicators going back to 1965. The CD-ROM also oﬀers country at-a-glance tables for all African countries and map tools for Africa. Despite the rich data reﬂected in this family of products, the lack of data for Africa is still a major impediment to monitoring development progress. As users will notice, many variables have few country observations and underline the need to improve data collection across the continent. I hope that this new series will contribute to the way countries, development partners, analysts, academics, and others understand and design development policies in Africa.

John Page Chief Economist, Africa Region

Acknowledgments Africa Development Indicators 2006 was produced by the Oﬃce of the Chief Economist and the Operational Quality and Knowledge Services Group of the Africa Region. The Development Data Group of the Development Economics Vice Presidency collaborated in the production of The Little Data Book on Africa 2006 and the World Bank Africa Database 2006. This book and its companions, The Little Data Book on Africa 2006 and World Bank Africa Database 2006, were prepared by a team led by Jorge Arbache and Vildan VerbeekDemiraydin, comprising Zena Angesom, Francoise Genouille, Rose Mungai, Joan Pandit, and Christophe Rockmore. Mehdi Akhlaghi provided technical support for The Little Data Book on Africa 2006, and William Prince provided technical support for the World Bank Africa Database CD-ROM. John Page, Chief Economist, Africa Region, provided overall guidance and supervision. The essay and Africa Development Indicator tables beneﬁted from contributions from a large number of people. Ivar Andersen, Jorge Araujo, Demba Ba, Thorsten Beck, Misha Belkindas, Harry Broadman, Karen Brooks, Derek Byerlee, Michael Fuchs, Madhur Gautam, Linda Van Gelder, Delﬁn Go,

Catalina Gutierrez, Katie Heller, Lawrence E. Hinkle, Stefan Hochhuth, James Keough, Mohamed Khatouri, Jean Michel Marchat, Sergio Margulis, Celestin Monga, Anna Muganba, Jonathan Munemo, Francois Nankobogo, Benno Nludu, Essama Nssah, Sonia Plaza, Francesca Recanatini, Ivan Rossignol, Francis Rowe, Pieter Serneels, Sudhir Shetty, Stephanie H. Tam, Mark Roland Thomas, Robert Townsend, Dileep Wagle, Naoko Watanabe, Elizabeth White, and Yutaka Yoshino provided inputs in the form of comments, suggestions, background notes, and boxes. Xiao Ye helped the team in preparing tables and charts for the essay and provided a box. Cecilia Briceno-Garmendia, Arnaud Desmarchelier, Vivien Foster, Sudeshna Ghosh Banerjee, and Kavita Sethi contributed to the infrastructure indicators and a box. Communications Development Incorporated provided overall design direction, editing, and layout, led by Bruce Ross-Larson, Meta de Coquereaumont, and Christopher Trott. Richard Fix supported the concept and production of The Little Data Book on Africa 2006. Staﬀ from the World Bank Oﬃce of the Publisher oversaw publication and dissemination of the book and its companions.

Acknowledgments

vii

Moving from the Year of Africa to the Decade of Africa— from promises to results In 2005, in what came to be called the Year of Africa, the region’s leaders reaﬃrmed their commitment to achieve the Millennium Development Goals by accelerating growth, creating jobs, delivering human services, and ﬁghting poverty. They also challenged the international community to support their efforts. Why the Year of Africa? In the view of many Africans and their international partners, 2005 marked a turning point in the region’s evolution. Africa is indeed on the move. In contrast with the 1990s, conﬂicts in Africa have declined, economic performance has improved, and some clear “high performers” are beginning to emerge. Since the late 1990s, 14 African countries have had average growth rates of above 5 percent.1 Across the continent countries are advancing in all spheres of transformation. • Growth for all Sub-Saharan Africa, which averaged 2.4 percent in the 1990s, rose to 4.0 percent in 2000–04 (indicator table 2.19) and came in at an estimated 4.3 percent in 2005. • Macroeconomic indicators have improved, with inﬂation down to historic lows, exchange rate distortions mostly eliminated, and ﬁscal deﬁcits dropping. • Progress toward the Millennium Development Goals (MDGs), while slow, improved in some countries (indicator tables 3.1–3.8). Cape Verde, Comoros, Eritrea, Guinea, and Mozambique have recorded signiﬁcant reductions in child (under-ﬁve) mortality. In education, Mauritania has made progress in increasing the primary enrollment of girls. • There is a growing awareness by governments of the need to be accountable to their people. The African Union has an-

nounced that it will not recognize governments that come to power through unconstitutional means. Many countries have increased exports by more than 8 percent a year since the late 1990s (indicator table 2.17), despite falling prices in some of their primary commodities. These export successes—in cut ﬂowers, vegetables, and clothing—show an Africa capable of both diversifying and building a constructive relationship with global markets. Progress is also being made in human development. With political support, The Gambia is advancing toward the Millennium Development Goal nutrition targets, and in ﬁve years, Niger has gone from being one of the worst performers in expanding primary education to one of the best.2 Some of the fastest growing countries have also done well in reducing poverty (indicator table 3.1). Since the second half of the 1990s, many low-income African countries, including Burkina Faso, Cameroon, Cape Verde, Ghana, Mozambique, Senegal, and Uganda, have lifted signiﬁcant percentages of their citizens above the poverty line. While in some countries growth and poverty reduction have recently declined moderately, many countries are still on course to meet the income poverty MDG target of halving poverty by 2015.3 Despite this progress, a lot more has to be done, especially in areas such as governance, civil society, private sector development, and human development, to make economic growth more sustainable, less exposed, and more resilient to shocks. Drawing on the indicator tables, this analysis takes stock of how countries and development partners performed during the Year of Africa. It then spells out what countries, with the support of their partners, are doing Moving from the Year of Africa to the Decade of Africa

1

to transform their eﬀorts into the Decade of Africa. The main message: Africans and their development partners need to increase their focus on supporting the drivers of growth, sharing participation in and the beneﬁts of growth, and building capable states. For shared growth to become a reality, the Decade of Africa must be about results not promises. T    Y  A The year 2005 was marked by the UN Millennium Project, the UK Commission for Africa, and the G-8 Summit at Gleneagles, Scotland, all culminating in the UN Millennium+5 Summit in New York. African governments committed to improving their economic and political institutions, accelerating economic growth, and achieving real progress toward the MDGs. Developed countries pledged to increase aid to Africa by $25 billion a year by 2010, more than doubling the assistance to the region, to open their markets to African products, and to forgive the debts of 25 of the continent’s poorest countries.4 The Multilateral Debt Relief Initiative for Africa would reduce debt to the International Development Association (IDA), the International Monetary Fund, and the African Development Fund by $42.1 billion. African governments are taking more control of their destiny African leaders are increasing ownership of their development strategies in new ways, helping to end conﬂicts through the African Union, and pushing for accountability in economic and political governance through the Peer Review Mechanism of the New Partnership for Africa’s Development. After a peak in 2002 the number of African conﬂicts has declined from 16 to 5.5 The transitions to peace include some of the longest running civil wars, such as the 21-year conﬂict between North and South Sudan and the protracted wars in Angola and Liberia. African governments are also taking action to improve the region’s reputation by certifying good practices in governance for a critical mass of African countries under the Africa Peer Review Mechanism. They are increasing regional connectivity to improve 2

Africa Development Indicators 2006

the capacity to trade—within the region and with the rest of the world. They are also enhancing the capacity of a rationalized system of regional bodies to provide regional public goods—such as cross-country transportation and power sharing, coordinating the management of pandemics, and protecting such regional commons as the Nile and the Great Lakes. And African enterprises, too long marginalized, have begun to show that they can connect constructively to world markets, with pockets of export successes outside commodities. More African states are choosing democratic arrangements, with elected oﬃcials in charge in many countries formerly ruled by military regimes or authoritarian governments. In addition, new arrangements and new spaces are being created to enable citizens to express their views and articulate their demands. Some African civil society leaders, for example, are studying Asian experiences with citizen report cards to assess the quality of service delivery. An invigorated media and civil society are making themselves heard, often leading the drive for greater accountability. The average scores on the World Bank’s Country Policy and Institutional Assessment have been rising, as has the number of African countries with scores above the good performance threshold of 3.5 (indicator table 13.4).6 Recent economic progress continued during the past year In 2005 higher oil prices did not strongly aﬀect economic growth, and real GDP is expected to have grown by 4.3 percent, compared with 5.1 percent in 2004 (indicator table 2.19). Oil-importing countries did well, with their economies growing by 4.5 percent, above the 4.2 percent seen in 2004.7 Economic growth in the main oil-exporting countries slowed somewhat to 4.7 percent from 8.4 percent in 2004 and 6.2 percent in 2003, mainly because of constraints on oil supply in Chad, Equatorial Guinea, and Nigeria (indicator table 2.19). Also in 2005 the recent gains in reducing inﬂation were maintained, suggesting prudent macroeconomic management during external shocks. As expected, there was a pass-through of high oil prices to consumer

prices in both oil-importing and oil-exporting countries. So inﬂation crept up slightly to 10.8 percent, from 9.8 percent in 2004.8 The continent remained vulnerable to terms of trade shocks and the negative eﬀects of exchange rate volatility. Because of the oil price increases in the ﬁrst half of 2005, there was an equivalent, cumulative loss of around 3.5 percent of GDP in Sub-Saharan Africa’s net oil-importing countries.9 And nonoil commodity prices, while strong, were subject to volatility and could be an area of signiﬁcant vulnerability in the future. Private investors—both domestic and foreign—were still reluctant to invest, except in minerals and some services. World Bank Doing Business surveys show that the continent continues to trail most other developing regions in starting a business, registering property, trading across borders, and accessing credit. Fast and slow growth countries remained on divergent paths The development pattern in Sub-Saharan Africa has become increasingly diverse over the last decade. Since the mid-1990s, 16 countries have had annual GDP growth rates in Table 1

excess of 4.5 percent (table 1). For several of them—including Ghana, Mozambique, Senegal, Tanzania, and Uganda—higher growth has been accompanied by diversiﬁcation of their economies and exports. Excluding the oil-rich countries, the fastest growing group of African countries has had an average growth rate of 5.5 percent. These countries host 35 percent of the region’s people. The 13 slowest growing economies, by contrast, have seen an average growth of only 1.3 percent, with some having near zero or negative growth. These countries—many either engaged in conﬂict or having recently emerged from conﬂict—host 20 percent of the region’s people. Increasing macroeconomic divergence is also observed in other dimensions. The standard deviation of the average annual growth rate in Sub-Saharan Africa has jumped from 2 percent in the 1980s to 4 percent in 2000– 04. The standard deviation across countries has also risen signiﬁcantly over time for exports and imports, value added of industry, agriculture, and services, and other variables, thus reinforcing that Africa is becoming increasingly diverse.

Divergent growth paths

Average annual GDP growth, 1996–2005 (%) Little or no growth countries Average: 1.3 percent 20 percent of African population

Slow growth countries Average: 3.4 percent 16 percent of population

Sustained growth countries Average: 5.5 percent 35 percent of population

Oil-exporting countries Average: 7.4 percent 29 percent of population

Swaziland

2.8 Nambia

4.0 Mozambique

8.4 Equitorial Guinea

Kenya

2.8 Zambia

3.6 Rwuanda

7.5 Angola

20.9 7.9

Lesotho

2.7 Guinea

3.6 Cape Verde

6.5 Chad

7.8 6.4

Eritrea

2.2 Niger

3.5 Uganda

6.1 Sudan

Comoros

2.0 Togo

3.3 Mali

5.7 Nigeria

4.0

Seychelles

2.0 Madagascar

3.3 Botswana

5.7 Congo, Rep.

3.5

Côte d’lvoire

1.5 Malawi

3.2 Ethiopia

5.5 Gabon

1.7

Burundi

1.2 South Africa

3.1 Tanzania

5.4

Sierra Leone

1.1 São Tomé and Principe

3.1 Mauritius

4.9

Central African Republic

0.9

Mauritania

4.9

Guinea-Bissau

0.6

Benin

4.8

0.0

Ghana

4.7

–2.4

Senegal

4.6

Congo, Dem. Rep. Zimbabwe

Burkina Faso

4.6

Gambia, The

4.5

Cameroon

4.5

Note: Data on growth rates are not presented for Liberia and Somalia, but they are included in the denominator in the calculation of population shares.

Moving from the Year of Africa to the Decade of Africa

3

Table 2

Debt service relief under the Heavily Indebted Poor Country Debt Relief Initiative

$ millions Countries that have reached HIPC completion point

Estimated total nominal debt service relief

Countries between HIPC decision point and completion point

Estimated total nominal debt service relief

Benin

460

Burundi

1,472

Burkina Faso

930

Cameroon

2,800

Ethiopia

3,275

Chad

Ghana

3,500

Congo, Dem. Rep.

Madagascar

1,900

Congo, Rep.

895

Gambia, The

Mali

260 10,389 2,881 90

Mauritania

1,100

Guinea

Mozambique

4,300

Guinea-Bissau

Niger

1,190

Malawi

Rwanda

1,400

São Tomé and Prince

200

Senegal

850

Sierra Leone

950

Tanzania

3,000

Uganda

1,950

Zambia

3,900

800 790 1,000

Source: Indicator table 13.1.

The international community had mixed results in living up to its ﬁnancial commitments Because of their performance, 14 countries in Africa are already eligible for the 100 percent debt relief initiative agreed at the G-8 Summit in Gleneagles. This number will grow to 25 as countries reach their completion points under the Heavily Indebted Poor Country (HIPC) Debt Relief Initiative (table 2 Box 1

Africa and trade reform

Sub-Saharan Africa would see a $4.8 billion increase in real income thanks to deep, multilateral reform of global merchandise trade, according to new World Bank estimates. Although small in absolute terms, this increase is signiﬁcant relative to initial incomes and trade ﬂows. Two-thirds of the gains would come from reforms by other countries (including other countries in Sub-Saharan Africa) and one-third from countries’ own liberalization. Reform in the agricultural sector would account for an estimated 78 percent of the total gain for Sub-Saharan Africa, of which 12 percent (if Southern Africa is excluded) would come from cotton. Although reform in cotton trade would contribute a negligible amount (0.5 percent) to the global gains, the sector is very important to Africa. Source: World Bank 2006b.

4

Africa Development Indicators 2006

and indicator table 13.1). As of March 2006, the debt service relief committed in nominal terms was $50.3 billion. The debt relief initiative will have important consequences for African countries and development partners, allowing treasuries to retain general budget resources that would otherwise have gone to debt repayment— and placing greater responsibility on African governments to build honest, eﬃcient, and results-focused public expenditure systems. While there is still room for optimism that the Gleneagles pledges can be achieved by 2010, the Organisation for Economic Co-operation and Development’s Development Assistance Committee and the Strategic Partnership with Africa10 both estimate that much of the increase in development assistance to Africa between 2006 and 2008 will be more apparent than real, consisting mainly of debt relief and emergency food aid. Progress by the rich countries in bringing the Doha Round of trade negotiations to a successful conclusion has been disappointing. Trade barriers need to be dismantled to level the playing ﬁeld. With the end of the Multiﬁbre Arrangement, World Trade Organization members have yet to deﬁne the nature and extent of preferences to be extended to the least developed countries and the role of “aid for trade” in the multilateral system (box 1).

While Sub-Saharan Africa as a whole would gain from multilateral trade reform, some countries on the continent would lose from preference erosion or, in the case of net food importers, from higher food prices. Losses from preferences, as with beneﬁts, would be less than expected due to strict rules of origin and because they are highly concentrated among relatively few countries and products (mostly those with quota rents, such as sugar). But even relatively small losses can pose signiﬁcant adjustment problems for some African countries, underlining the need for increased assistance for domestic implementation of reforms—“aid for trade”—to support and complement trade reform.

Box 2

The World Bank Group’s Africa Action Plan

The World Bank Group’s Africa Action Plan, launched in September 2005, is a resultsdriven partnership strategy with 25 priority initiatives designed to support African countries in implementing their national strategies to accelerate growth and reduce poverty. The plan is the core of the World Bank’s commitment to supporting improved development outcomes in Africa. The new replenishment for the International Development Association (IDA-14) is projected to increase resources in 2006–08 by an average of just under $1 billion a year over IDA13 in 2003–05. Under the Africa Action Plan, most of the increase in IDA will target strengthening Africa’s development by: • Ensuring that development support is implemented, monitored, and evaluated within a country-led results-oriented framework. • Increasing the rate of shared growth by developing infrastructure, fostering regional integration to boost export competitiveness, and improving health and human development, so that all citizens, including the poor and women, participate in and beneﬁt from greater economic development. • Building capable states that practice sound governance, transparency, and accountability.

•

Leveraging the IDA-14 partnership through more effective collaboration and harmonization among development partners. The World Bank is supporting shared growth by enlarging investment in African infrastructure from $600 million in 2000 to a projected $2.4 billion in 2008. It is working as part of the Africa Infrastructure Consortium in bilateral and multilateral partnerships. It is also signiﬁcantly increasing support for regional integration and regional approaches to support national development strategies. And the Malaria Booster Program is to be expanded by 150 percent in 17 countries by the end of 2008, meaning that a total commitment of $500 million to $1 billion may be required over the next ﬁve years. The Africa Catalytic Growth Fund, established in March 2006 with a grant from the United Kingdom, is a key element for leveraging the IDA-14 partnership. The fund allows the World Bank to increase support to investments that: • Ease the constraints to growth in well performing economies. • Lay the groundwork for sustained growth in transforming economies, where dedicated leadership can strengthen economic reforms. • Support regional programs, where problems of collective action and donor practices result in too little investment.

Source: www.worldbank.org/afr/aap.

The suspension of the World Trade Organization talks in Geneva will hit poor Sub-Saharan African countries hardest—and the talks may well not start up again until sometime in 2007 or even 2008. Now entering the last decade to achieve the MDGs, Africa and its development partners have to move from promises to results—from the Year of Africa to the Decade of Africa. M    D  A The Year of Africa focused global attention on Africa. But rebuilding infrastructure, tackling the disease burdens posed by HIV/AIDS and malaria, addressing the potential impact of avian ﬂu, and building competitive exportoriented businesses are all medium- to long-

term challenges. Realistically, the work will be done over a decade or more. And as in any region, the progress of economic development among African countries is bound to move at diﬀerent speeds, depending on countries’ initial conditions, their historical legacies, and the impact of weather and other natural shocks. In contrast with past decades, economic, political, and social outcomes are more varied, with more positive and negative aspects sometimes coinciding, sometimes in opposition. Both Africans and their development partners need to focus on ways to address the key challenges to progress by: • Supporting the drivers of growth. • Participating in and sharing the beneﬁts of growth. Moving from the Year of Africa to the Decade of Africa

5

Figure 1

Nigeria and South Africa account for more than half of Africa’s GDP

$ billions, 2004

Nigeria, 72

Rest of Africa, 234

South Africa, 215 Source: Indicator table 2.6

•

Providing the underpinnings for shared growth by building capable states and improving governance.

Supporting the drivers of growth One major international development objective is for African countries to increase their growth to the 7 percent a year needed to Box 3

substantially reduce income poverty. Africa’s slow growth is due mainly to much slower productivity growth (box 3). Accelerating and sustaining high growth rates in Africa are major challenges, however, and there is no obvious or unique recipe for success. The region’s economic activity is highly concentrated. Of Sub-Saharan Africa’s nominal GDP of $526 billion in 2004, South Africa accounted for the largest share ($215 billion), followed by Nigeria ($72 billion), Sudan ($21 billion), Angola ($20 billion), and Kenya ($16 billion) (ﬁgure 1 and indicator table 2.6). Of industry value added of $116 billion in 2004, Nigeria accounted for $21 billion and South Africa $42 billion (indicator table 2.4). And of service value added of $182 billion in 2004, South Africa accounted for $92 billion (indicator table 2.5). Because most African economies are fairly small, a regional approach is required to achieve sustainable growth.

Sources of economic growth in Africa—an international perspective

Africa is the slowest growing region in the world. Average per capita output growth in the 1990s was negative due mainly to very low growth rates. But what explains such a performance from an international perspective? Growth decomposition is a widely used tool to assess the contributions of changes in factor inputs (human and physical capital) and total factor productivity to economic growth. (Total factor productivity measures changes in economic efﬁciency in the use of inputs and changes in technology for observed output growth.)

Growth accounting shows that growth in physical capital per worker in Africa has been less than 0.5 percent a year since 1960, far slower than the world average of 1 percent, and was negative between 1990 and 2003, suggesting low capital investment in the region. The contribution of human capital to growth kept pace with the rest of the world and has increased lately, mainly as a result of rising average years of schooling. But the main contributor to Africa’s disappointing growth is total factor productivity, negative since the 1960s and –0.4 percent between 1990 and 2003.

Sources of growth—a decomposition analysis, 1990–2003

Region

Africa Development Indicators 2006

Growth in output per worker (%)

Growth in physical capital per worker (%)

Education per worker (%)

Total factor productivity (%)

World

3.09

1.88

0.93

0.27

0.67

Africa

2.48

–0.09

–0.05

0.40

–0.44

Industrial countries

2.31

1.55

0.84

0.22

0.49

China

9.70

8.51

3.32

0.29

4.72

East Asia less China

5.24

3.12

2.05

0.47

0.58

Latin America

2.61

0.33

0.14

0.34

–0.16

South Asia

5.34

3.10

1.29

0.40

1.38

Middle East

3.64

0.61

0.20

0.51

–0.11

Source: Bosworth and Collins 2006.

6

Growth in output (%)

Developing the private sector What has been missing in most of Africa is a buoyant private sector. Building the African private sector is crucial for growth and for fostering a national consensus for growthoriented policies. It is also critical for reassuring the African public that a growth process led by the private sector is one that everyone can participate in and beneﬁt from. Central to this eﬀort is improving the investment climate and enhancing the capacity of African and foreign entrepreneurs to invest. There is considerable room for improvement: net foreign direct investment in Africa was a mere $10.1 billion in 2004, 1.6 percent of global ﬂows, with more than half going to Nigeria and Sudan (ﬁgure 2 and indicator table 5.2). Improving the business environment. According to Doing Business 2006: Creating Jobs (World Bank 2006a), 6 of the 10 countries judged as having the most diﬃcult environment for starting a business are in Africa. It takes an average of 64 days to start a business, ranging from 14 in the Central African Republic to 155 in the Democratic Republic of Congo (ﬁgure 3 and indicator table 5.1). Enforcing a contract is no less onerous, running an average of 439 days, ranging from 154 in Botswana to 1,011 in Angola. Investment Climate Assessments in more than a dozen countries point to speciﬁc changes that governments can eﬀect to encourage higher levels of investment and faster job growth. Figure 3

Figure 2

More than half of Africa’s foreign direct investment goes to Nigeria and Sudan

$ million, 2004

Rest of Africa, $4,227

Nigeria, $4,409

Sudan, $1,481 Source: Indicator table 5.2.

The payoﬀs can be signiﬁcant. In Madagascar a garment exporter estimated that if port clearance were reduced to one day, it would cut total costs by a sum equal to as much as 30 percent of the wage bill. Africa has not attracted many foreign investors because the prevailing business environment and the market conditions failed to attract even domestic investors. Fundamental obstacles remain throughout much of the region—economic and policy barriers to new business entry, poor governance, limited property rights protection, weak market institutions, undeveloped infrastructure, low technical capacity of ﬁrms, low skill of management and workers, and size of markets.

Fast starters—and slow starters

Time required to start a business (days)

Central Africa Republic Rwanda Sierra Leone Benin Ethiopia Botswana Angola Mozambique Congo, Dem. Rep. São Tomé and Principe

0

50

100

150

200

Source: World Bank 2006a.

Moving from the Year of Africa to the Decade of Africa

7

The private sector’s participation in policy matters is increasing. Investor councils in Ghana, Senegal, and Tanzania are showing the beneﬁts of a constructive, problem-solving interaction between government and business in tackling ineﬃcient customs and inconsistent tax enforcement. New councils started in Mali and Uganda will add to the experience. A more engaged private sector in Africa should be able to push for regulatory and infrastructure changes that will make Africa less of a high-cost, high-risk place to do business. Strengthening ﬁnancial systems. Improving the performance of Africa’s ﬁnancial systems is also high on the agenda for enterprise development. Despite numerous reforms over several decades, most Sub-Saharan ﬁnancial systems remain weak, with Kenya, Mauritius, and South Africa among the exceptions. Little savings are mobilized from domestic or foreign sources. Credit to the private sector is limited and costly. Many national ﬁnancial sectors are dominated by a few banks providing an uncompetitive, small range of services. The assets of banks exceed $10 billion only in Nigeria ($22 billion) and South Africa ($219 billion) and are less than $1 billion in 24 SubSaharan countries (indicator table 7.5). Financial reform programs anticipated an initial increase and then a reduction in the spread between lending and deposit interest rates, but the spread remains large in many countries. And since liberalization, many ﬁnancial systems have seen high real interest rates. Financial deepening has also been lacking. Although Africa has about a dozen stock markets—several opened in the 1990s— they have been inconsequential for economic growth and investment. Simply put, there are too few opportunities for sharing risk, trading shares, and providing liquidity. Except for South Africa, the stock markets are by far the smallest of any region, both in the number of listed companies and in market capitalization. They are also highly illiquid, seriously constraining their ability to contribute to economic growth. Tackling these ﬁnancial development challenges will require enlarging access to ﬁnancial services—particularly savings facilities. This will require strengthening links between formal and informal ﬁnancial systems—because most Africans do not have access to the 8

Africa Development Indicators 2006

formal ﬁnancial sector. And given the small size of many African economies, a regional approach to ﬁnancial sector development is needed to increase competition, cut costs, and lower risks. Closing the infrastructure gaps. Africa has a major infrastructure deﬁcit, slowing economic growth, reducing trade and international competitiveness, and retarding poverty reduction (indicator tables 7.1–7.4). Nearly 40 percent of Africa’s people live in landlocked countries with high transport costs and poor trade links.11 Transport costs for intra-Africa trade (including trans-shipment) are unusually high, estimated at nearly twice the levels in other developing regions. GDP per square kilometer in Africa (excluding South Africa) is one-tenth the level in Latin America and one-twentieth that in India.12 Improving infrastructure is thus central to the growth and the development of the private sector, especially of nontraditional, noncommodity sectors that require more intensive inputs of infrastructure and logistics. African enterprises can be competitive in factory ﬂoor direct costs for the production of manufactures, but their indirect costs, especially the high costs of poor infrastructure services, are a major bottleneck for ﬁrms.13 Surveys of African ﬁrms indicate that inadequate roads, ineﬃcient ports, and power outages hobble African enterprises in their push to secure a place in global markets. For example, clothing exports from Uganda are an estimated 80 percent more expensive because of transport costs. Rwandan farmers, who are making great strides in exporting coﬀee, receive only 20 percent of the price of their coﬀee as it is loaded onto ships in Mombassa. The other 80 percent disappears into transport costs—a combination of poor roads and administrative hurdles—between Rwanda and Kenya. Kenya loses the equivalent of 9 percent of its output to power outages—compared with 2 percent in China.14 To achieve the 7 percent growth rates needed to halve income poverty, Africa will need to invest 5 percent of GDP in infrastructure and an additional 4 percent of GDP to cover operation and maintenance requirements. To reach this goal, Africa’s infrastructure investment needs will amount to around $20 billion a year, twice what the region has been investing.15 The road sector alone accounts for

about 40 percent of total investment needs, with the energy and water sectors accounting for 20 percent each. While private capital has contributed to infrastructure ﬁnance in Africa, it is concentrated in a few countries (South Africa accounted for half of total investment) and sectors (70 percent went to telecommunications). Furthermore, private capital ﬂows have declined steadily since 2001, reﬂecting a global trend toward disengagement from emerging markets. Total annual oﬃcial development assistance for infrastructure in Africa has also been on the decline, accounting for an average of about $826 million in 2000–04 (indicator tables 7.1–7.4). Because of its magnitude, ﬁnancing infrastructure requires concerted eﬀort from all funding sources, both public and private. The Gleneagles G-8 summit emphasized investing in Africa’s infrastructure. It agreed to support an Africa Infrastructure Consortium—led by the African Union and the New Partnership for Africa’s Development and including the African Development Bank and the World Bank—to mobilize infrastructure resources to both national and regional projects. Creating an export push and fostering regional integration Global trade has increased at unprecedented levels over the last three decades, and the world marketplace has become ever more competitive. Yet Africa lost market share in traditional exports and made little progress in diversiﬁcation of exports. Of the region’s exports of $128 billion in exports (in 2000 prices), only Angola, Nigeria, and South Africa had exports of more than $5 billion Box 4

(indicator table 2.17). Imports that year totaled $144 billion. Expanding and diversifying exports. Entering new markets and diversifying into nontraditional exports can spur productivity, innovation, and competitiveness in Africa. Asia—particularly China and India—with its rising incomes and consumer demand, oﬀers new prospects for growth in exports by African producers in markets for tea, coﬀee, and cocoa. Global competition in mass manufacturing is ﬁerce in some of Africa’s existing export markets, such as textiles and clothing, where competition increased substantially with the expiration of the Multiﬁbre Arrangement in 2005, and some footloose investors left Africa. On the other hand, exports of services—including tourism and back-oﬃce support—oﬀer new opportunities. Indeed, new World Bank research on Africa’s trade and investment relations with China and India suggests that countries such as Ghana, Kenya, and Tanzania, among others, have the ability to compete eﬀectively in certain global services markets.16 To be sure, the prospects for boosting and diversifying Africa’s export ﬂows depend signiﬁcantly on improved market access and reduced subsidies in world markets. The beneﬁts of preferential access provisions currently enjoyed by African countries would be far greater if they were more certain, not subject to burdensome rules of origin, and applied more uniformly across the continent. To this end, reforms are called for in the U.S. African Growth and Opportunity Act and the EU’s Everything But Arms initiative. Improvements could also come from further multilateral liberalization that opens

Information and communication technology improvements in Ghana

Ghana suffered from a very weak investment climate in the telecom sector in early 2004 due to international disputes in telecommunications, a lack of formal licenses for mobile operators, and an outdated regulatory framework. The result was a low ﬁxed and mobile telephone penetration rate of 5 percent in early 2004. Today, there is a 15 percent penetration rate, and all telecom operators are investing heavily in the sector. How was this accomplished? In partnership with the U.S. Agency for International Develop-

ment, the World Bank ﬁnanced the formulation of the National Telecommunication Policy and has been deeply engaged in policy advice on current reforms related to new legislation. The Bank’s Africa Aid Program helped accelerate the preparation of an “eGhana” project aimed at creating jobs, diversifying global information and communication technology services, and providing more efﬁcient government services delivery through the use of information and communication technology applications and public-private partnerships.

Moving from the Year of Africa to the Decade of Africa

9

Figure 4

Intraregional trade is small but increasing

$ billions

150 Exports to Africa Exports to the rest of the world 120

90

60

30

0 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 Source: International Monitary Fund’s Direction of Trade Statistics.

developed country and other developing country markets for speciﬁc crops, such as cotton, sugar, and groundnuts, and for processed agricultural products. Improvements would also arise from a reduction of barriers in nonagricultural sectors, especially in other developing country markets. For example, some countries in Latin America heavily protect their own garment manufacturers and other labor-intensive manufactures, reducing the opportunity for African products to penetrate those markets. But even if there were signiﬁcant reforms in market access, reductions in tariﬀs and subsidies, and elimination of nontariﬀ barriers in overseas markets, for African ﬁrms to be able to eﬀectively exploit the export opportunities created, signiﬁcant changes must take place “behind the border”—that is, within African countries themselves.17 One such precondition is speeding the clearance of goods through customs. Moving goods to and from African countries takes the longest of any region—60 days on average to import, 48 to export. Regulations in the typical African country require 30 signatures to import, 19 to export. Integrating regional markets. Equally important to African trade and enterprise is a framework for regional integration that will foster competitiveness and promote economic eﬃciencies. But promoting eco10

Africa Development Indicators 2006

nomic integration in Africa is not an easy task because there is limited economic complementarity among countries, and they are potential competitors in resource-intensive products. But as African economies are too small and too fragmented, regional integration can promote internal and external economies of scale, encourage product differentiation and diversiﬁcation, intra-industry trade, and a learning-by-exporting process, which would help make local ﬁrms more competitive in international markets. Eﬀective regional integration is particularly important for landlocked countries. Currently, intraregional trade generally amounts to only a single-digit ﬁgure in most trade blocs of Africa (ﬁgure 4 and indicator table 6.2). It is African leaders who will build and sustain the regional economic alliances that African economies require to compete internationally. The New Partnership for Africa’s Development has regional integration as a core objective. It is encouraging the continent’s multiple and often overlapping regional organizations to deﬁne their roles and responsibilities and to focus on “open regionalism,” regional (rather than national) trading agreements, and greater competitiveness in global markets. Similarly, the European Union is supporting the rationalization of regional bodies to spur progress toward more competitive subregional economic groupings. Most countries are now giving more attention to regional integration as a means to sharpen competitiveness, expand trade, and accelerate growth. Successful regional integration will require better regional customs arrangements, lower tariﬀs, and much improved infrastructure and logistics to speed the movement and reduce costs of inputs, goods, and services within subregions to facilitate trade outside the region. Participating in and sharing the beneﬁts of growth World Development Report 2006: Equity and Development (World Bank 2005c) showed that inequalities in income—and thus in opportunities—waste much productive potential and lead to ineﬃcient resource allocations. Such inequalities impair the development of institutions that might lift the

Box 5

Growth is central to sustained poverty reduction

Like other developing regions, most countries in Sub-Saharan Africa either have negative

tribution of changes in inequality to changes

growth rates and increasing poverty or posi-

the developing world as a whole. Together

tive growth rates and declining poverty. Sub-

these ﬁndings suggest that poverty reduction in Sub-Saharan Africa has been disappointing primarily because of its slow growth and low sensitivity of poverty to growth (holding constant the distribution of income). This low sensitivity can be traced to the region’s low incomes and high inequality (Sub-Saharan Africa and Latin America are the world’s most unequal regions). What are the implications for policy? At a basic level, growth remains crucial for reducing poverty in Africa—all the more so given that the region’s low incomes imply a relatively low sensitivity of poverty to growth. Moreover, the importance of growth as the driver of changes in poverty seems to be even clearer over longer periods, suggesting that growth remains critical for sustained reductions in poverty, though it is not the only factor.

Saharan countries have a median per capita growth rate of 0.8 percent a year, substantially lower than the overall median of 2.1 percent, and most are above the regression line, indicating lower poverty reduction performance than for a typical developing country with similar growth performance. There are important differences across countries. For example, Ghana’s annual growth rate over 1987–99 was 1 percent and Uganda’s was 3 percent over 1989–96, but their annual rate of change in poverty ranged from about –8 percent to 2 percent. Differences in the Gini coefﬁcient and differences in the change of income distribution over time may account for these results. Sub-Saharan countries tend to have a low sensitivity of poverty to growth, and the con-

in poverty in the region is similar to that in

Source: Adapted from World Bank 2005d.

constraints on people’s economic pursuits and improve the way markets work. And it is precisely those weak institutions that perpetuate the unequal distribution of income. They are also bad for the investment and risktaking that underpin long-term growth and poverty reduction. The poor have been ill equipped to participate in and beneﬁt from the growth that has taken place in the region. Women in particular have suﬀered from the inability to own assets and from discrimination in economic activity. In short, growth alone will not be enough to achieve the MDGs in Africa. What is needed in addition? • Making agriculture more productive and sustainable. • Connecting poor people to markets. • Enhancing human development. • Getting services to poor rural populations, especially to women. • Using natural resource rents well. Making agriculture more productive and sustainable With poverty largely a rural phenomenon in Sub-Saharan Africa, agricultural and ru-

ral development are essential for the broad growth needed to achieve the MDGs (indicator tables 9.1 and 9.2). Agriculture still dominates the economies of most African countries, accounting for about 17 percent of the region’s GDP, 40 percent of exports, and a substantial share of employment (indicators tables 2.3, 6.1, and 10.1). In addition, agricultural and rural development can reduce poverty more than in other regions. A 1 percent increase in crop yield in Sub-Saharan Africa translates into a 0.7 percent reduction in the number of poor people, more than the 0.5 percent reduction in East and South Asia and seven times the 0.1 percent reduction in Latin America.18 Agricultural growth, important to all the MDGs, has the greatest impact on poverty and hunger, and empirical evidence for poor countries show that it can be an engine of growth.19 Findings from countries with signiﬁcant poverty reduction achievements suggest that agricultural productivity growth may be responsible for as much as 40–70 percent of those reductions.20 The challenge for Sub-Saharan Africa is to commit to policy and investment improvements that will have explicit productivity-enhancing outcomes. Moving from the Year of Africa to the Decade of Africa

11

Figure 5

Rural access to transportation networks varies widely...

Share of rural population within 2 kilometers of an all-season road (%)

Nigeria Tanzania Niger Benin Congo, Dem. Rep. Burkina Faso Cameroon Ethiopia Chad

0

10

20

30

40

50

Source: Indicator table 7.2.

Productivity growth in agriculture is linked to higher income, increased employment, and improved well-being. Growth in productivity increases production and lowers food prices, which in turn holds down urban wages and encourages industrialization. Increased production also creates more jobs for the poor both on and oﬀ the farm. Agricultural production growth of 1 percent typically leads to agricultural employment growth of 0.3–0.6 percent and nonagricultural employment growth of around 0.9 percent.21 These growth and employment eﬀects have proven most powerful when agricultural growth is driven by broad-based productivity increases in rural economies dominated by small farms. One reason that African agricultural productivity is far below that of other regions is that the percentage of irrigated area is very small—less than 4 percent of the total cropped area (indicator table 9.2). Governments will be expanding their eﬀorts in water management, using lessons from successful irrigation programs, both small (the fadama projects in Nigeria) and large (rehabilitation of the Oﬃce du Niger in Mali). African farming can also be improved by employing environmentally sustainable farming methods, including appropriate use of fertilizer and improved seeds, better soil conservation practices, and longer fallows and rotations. 12

Africa Development Indicators 2006

Connecting poor people to markets Interventions to connect the rural poor to the modern economy through investments in rural roads, electriﬁcation, and communications are central elements of the shared growth strategy. The share of the rural population within two kilometers of an all-season road ranges from 5 percent in Chad and Uganda to more than 50 percent in Madagascar, Mali, Niger, and Zambia (ﬁgure 5 and indicator table 7.2). Rural access to electricity is also low, ranging from 0.2 percent in Burkina Faso and Niger to more than 20 percent in Cameroon, Côte d’Ivoire, Ghana, and Nigeria (ﬁgure 6 and indicator table 7.4). Infrastructure is important to integrate markets and therefore essential for poor people to be able to develop their businesses, get contracts, enhance the value of their assets, have access to new technologies, and above all, beneﬁt from the growth of the economy. Lack of access to credit, education, raw materials, goods, and public services also isolate poor people and expose them to emergencies, poor harvests, health problems, and economic crisis. If isolation raises the costs of obtaining education, for instance, the accumulation of human capital becomes economically infeasible. One consequence of low integration of the poor to markets is that poor people, especially those in rural areas, usually end up hostages of intermediaries who sell them

Figure 6

... as does rural access to electricity

Share of rural population with access to electricity (%)

Nigeria Côte d’lvoire Cameroon Ghana Comoros Burundi Central African Republic Niger Burkina Faso Chad

0

5

10

15

20

25

30

Source: Indicator table 7.4.

provisions, seeds, and domestic utensils during the planting season or during the production of some agricultural or other product and who then buy their entire output for a very low price. The same happens with moneylenders who take advantage of the poor in urban areas and take possession of their income and goods. Building the assets of women and connecting them to markets are essential for shared growth. Much of Africa’s economic activity is in the hands of women. Data from Uganda suggest that women contribute about 50 percent to GDP and that women and men are not equally distributed across productive sectors. Time allocation studies throughout Sub-Saharan Africa conﬁrm women’s preponderant role in agriculture. Because men and women diﬀer in their access to, and control over, productive and other assets, economic capacities and incentives are gender-diﬀerentiated in ways that aﬀect resource allocation within the household, labor productivity, and welfare. These difBox 6

ferences have implications for the ﬂexibility, responsiveness, and dynamism of the economy. A study in Burkina Faso showed that shifting existing resources between men’s and women’s plots in the same household could increase agricultural output by 10–20 percent. Another study in Kenya concluded that giving female farmers the same level of agricultural inputs and education as male farmers could increase their yields by more than 20 percent. Enhancing human development Half the population in Sub-Saharan Africa is between the ages of 5 and 24, indicating that the population will continue to rise well into the twenty-ﬁrst century. There is a substantial need for future scaling up of human development, notably in health and education, which can only be met by high and sustainable economic growth rates.22 If this large cohort requires massive resources, the increasing working-age population can potentially contribute to boost economic growth.

Scaling up support for education in Ethiopia has large payoffs

In 1991 only 30 percent of Ethiopian children attended school. Addressing this challenge has involved mobilizing communities, training teachers, and obtaining ﬁnancing for the effort. Development partners are supporting a

sectorwide education reform program. One of the results has been a rise in the gross enrollment rate to 77 percent in 2004 thanks to annual reviews and a good monitoring system. But improving quality remains a challenge.

Moving from the Year of Africa to the Decade of Africa

13

Box 7

Responding aggressively to malaria in Sub-Saharan Africa

The Booster Program for Malaria Control supports country efforts to deliver concrete and measurable results. Currently targeting 19 countries, the program has a 10-year horizon, with the initial three-year “Intensive Phase” already well under way. Four projects have been approved—for Eritrea, Democratic Republic of Congo, Niger, and Zambia—and preparations are proceeding rapidly in nine more countries and on a regional project. Strong collaboration and partnership with key agen-

Africa’s human development indicators have traditionally been among the lowest in the world, but they are on the rise in many areas. Gross primary enrollment rates as a share of the relevant age group shot up to 93 percent in 2004 from 72 percent in 1990, holding the promise that many more Africans will contribute to and beneﬁt from an expanding economy (indicator table 8.1). Indeed, the increase appears to have already contributed to a rise in literacy rates from 50 percent in 1997 to 65 percent in 2002. A further challenge now is to improve quality of primary education. In most countries, however, retention to the end of the primary cycle remains a problem, and the result is to undermine attainment of the education MDGs (universal primary school completion and gender parity in education—indicator table 3.3). In 2004 primary school completion rates in African countries averaged no more than 62 percent, up from 51 percent in 1991, and in only a few countries did the rate exceed 90 percent. Success will require, among other measures, improving the quality and relevance of schooling services and encouraging parents to let their children, particularly girls, complete the full cycle of primary schooling. With progress toward universal primary school completion, the number of students aspiring to post-primary education has been growing rapidly, and the pace can be expected to pick up in the coming years. The magnitude of the expected increase poses major policy challenges regarding the resources required to expand capacity without diluting the quality of services and the reforms needed to manage costs and ensure equitable 14

Africa Development Indicators 2006

cies and countries are moving the work program forward rapidly by focusing on results and strengthening donor harmonization and partnerships, including the U.S. Presidential Initiative for Malaria Control, the Bill & Melinda Gates Foundation, ExxonMobil, the United Nations Children’s Fund, the World Health Organization’s Regional Ofﬁce for Africa, and the Global Fund to Fight AIDS, Tuberculosis, and Malaria.

distribution of the burden of ﬁnancing. Yet in too many African countries, these issues have received inadequate attention at best. In the meantime, conditions in post-primary education have deteriorated. Enrollments have grown, public budgets have stagnated and private sources of funding remain untapped. Moreover, post-primary education tends to be poorly diversiﬁed and typically leaves students unprepared for most employment opportunities. Many African national health care systems are under stress due to weakening human resource capacity and ﬁnancing constraints. Solid evidence and best-practice examples show how sectorwide approaches are among the best options for ensuring that strengthened public and private health care systems are mutually reinforcing with disease-speciﬁc programs. It is necessary to scale up policies to address the systemic constraints in human resources for health, which include the dramatic brain drain of physicians and nurses from Africa.23 Despite the recent progress on treatment and prevention, HIV/AIDS remains a major development challenge in the region, particularly in Southern Africa, the epicenter of the epidemic. It continues to reverse life expectancy gains, consume savings, dilute poverty eﬀorts, erode productivity, and threaten economic growth.24 Malaria, a completely preventable and treatable disease, has taken the heaviest toll on Africa (indicator table 12.1). Each year, it kills more than 1 million people around the world—90 percent of them in Africa. Every 30 seconds, an African child dies of malaria, making it the largest single killer of African children.25

Box 8

Investing smartly across sectors

Water supply and sanitation investments have important implications for health, especially child health. Nearby water and school latrines can dramatically increase mothers’ ability to care for their children and can increase girls’ school attendance. Better roads improve

school attendance and the use of health facilities. And health and education investments have clear complementary effects: mothers’ education is strongly correlated with child survival, and school attainment is directly affected by family illness, especially HIV/AIDS.

Source: World Bank 2006b.

The disease takes a high toll on households and health care systems and increases poverty by signiﬁcantly reducing productivity and social stability. The annual economic burden in Sub-Saharan Africa is estimated to be about $12 billion. Although the disease is preventable and curable with available technology, coverage with eﬀective interventions has remained low, particularly among poor and rural populations. In Sub-Saharan Africa 38 of 47 countries fall short of the World Health Organization’s standard of at least 20 physicians per 100,000 people.26 The March 2005 report of the Commission for Africa called for a tripling of the healthcare workforce in Africa. Africa will need to train an additional 1 million workers over a decade in the health sector and provide an improved workplace environment (salary, equipment, supplies) to make that happen. Getting services to poor rural populations, especially women Since 1999, when the Poverty Reduction Strategy approach became the key policy framework for development partners, many African governments have been consciously investing more in pro-poor service delivery, especially in health, education, HIV/AIDS, rural development (roads), agriculture, and water. According to World Development Report 2004: Making Services Work for Poor People (World Bank 2003), the biggest payoﬀs to service delivery are likely to come from a few key actions: spending smartly and predictably in line with priorities and coordinated across sectors; managing decentralization to reap the beneﬁts of being closer to clients; developing and deploying administrative capacity to take sound decisions at the top and to implement them well; curtailing corruption; and learning from success and failure. Reforming basic incentives that strengthen

accountability and that raise performance closer to formal standards is the place to start. As incentives become better aligned and internalized and as administrative capacity grows, more advanced reforms can be deployed to support deeper institutional change and scaling up. The rural-urban divide can be enormous. In Kenya the share of the population with access to an improved water source is 39 percent in rural areas and 86 percent in urban; the share with a health center less than an hour away is 65 percent in rural areas and 98 percent in urban (indicator table 14.8). The male-female divide can also be wide. The diﬀerent roles of men and women in the market economy are coupled with their equally diﬀerent—and unbalanced—roles in the household. In addition to their prominence in agriculture, women take on most domestic tasks: processing food crops, providing water and ﬁrewood, and caring for the elderly and the sick. Providing women in particular with better services could enable them to be much more productive, and improve quality of life. Using natural resource rents well Resource-based rents are widespread and growing due to new discoveries and favorable prices. During the 1990s, 65 percent of all foreign direct investment was concentrated in oil, gas, and mining, and 45 percent of exports came from the oil and mining sectors. Those ﬁgures have substantially increased in recent years. Between 2000 and 2010, $200 billion in oil revenue will accrue to African governments. Estimates of the value of the oil price windfall to African oil- producers in 2004 range from 9 percent of government revenue in Gabon to 56 percent in Equatorial Guinea.27 Mineral-dependent countries in Africa tend to have higher poverty rates, greater income Moving from the Year of Africa to the Decade of Africa

15

Box 9

Governance is being tackled in Nigeria

Nigeria has long suffered the effects of massive corruption and weak governance, making it difﬁcult for investors to do business in Nigeria, wasting public resources, and impoverishing the average Nigerian. Today, all of Nigeria’s governance and corruption indicators show an improvement. How has this been accomplished? The government has embarked on a comprehensive effort to ﬁght corruption and improve governance: • Its targeted anticorruption efforts have yielded about 40 convictions, including

inequality, less spending on health care, higher prevalence of child malnutrition, and lower literacy and school enrollments than other countries at the same income level. But mineral-exporting economies can share growth. Chile, Indonesia, and Malaysia have all used natural resource wealth to provide a basis for a more diversiﬁed economy in which poor people can participate in and contribute to the process of growth. The Extractive Industries Transparency Initiative (EITI) aims to increase transparency in transactions between governments and companies within extractive industries. It shows what African governments, development partners, and private business can achieve when they act together to improve the transparency and accountability of natural resource ﬂows. Revenues from oil, gas, and mining companies—in the form of taxes, royalties, signature bonuses, and other payments—can be an important engine for economic growth and social development. To date, 14 African countries have committed to implement the EITI, twice as many as a year ago (indicator table 13.2).28 In many of those countries EITI programs are for the ﬁrst time involving local civil society groups in the direct oversight of natural resource revenues. The resource ﬂows that could be overseen by the programs are staggering. Nigeria’s ﬁrst EITI report, released in early 2006, reported an average of more than $15 billion in annual payments to government by oil and gas companies. Compare that with $4.7 billion in IDA commitments for all Africa in 2006. 16

Africa Development Indicators 2006

of high-ranking ofﬁcials, and forfeiture of about $3 billion in cash and assets to the public treasury. • It has introduced a new Virtual Poverty Fund to help ensure that the federal government’s $750 million in annual savings on debt service payments go to the right uses and are tracked and monitored. • It has moved to open and competitive procurement systems. It is conducting independent audits of the oil accounts conducted under the Extractive Industries Transparency Initiative.

Providing the underpinning for shared growth by building capable states and improving governance Without institutions that can deliver basic services, the rule of law, predictable administration, and responsive regulation, Africa’s plans and ambitions are not likely to gain traction. Support to the drivers of growth and a focus on strategies for shared growth must be complemented by a stronger focus on governance. This will require a strong civil society presence in order to make governments more accountable and to allow them to actively participate in building their country’s destiny. Furthermore, countries must identify their greatest shortcomings and challenges in order to ﬁnd entry points where reforms can make the biggest diﬀerence. A country that has already dealt with electoral reforms might focus on tax system or state procurement. And the private sector, an independent media, and civil society organizations can help build demand for good governance. Developing institutional capacity Capacity development is a regionwide challenge for Africa, although countries are at various points on the spectrum from weak to strong capacity and from low to high accountability (indicators tables 13.2–13.4). To varying degrees, African countries all face the task of mitigating the brain drain of highly skilled workers with incentives for capacity retention and utilization. They have to revive failing service delivery systems to help achieve the MDGs, promote a competitive environment for private sector–led growth,

Box 10

A vision for capacity development

The World Bank Task Force on Capacity Development in Africa’s September 2005 report, Building Effective States, Forging Engaged Societies (World Bank 2005a) highlighted the need for African countries to implement homegrown, fully owned strategies for capacity development as an explicit part of their mediumterm development programs. They should take the lead in determining their capacity needs and set priorities for implementation in line with their poverty reduction strategies and other national development strategies.

The focus should be on strengthening the capabilities of the state. This means strengthening the skills and professional proﬁles of the public sector, increasing organizational effectiveness, and developing institutions capable of supporting change management. Many African countries are still far from taking strong leadership in programming and implementation, but the experiences of Botswana, Mauritius, and South Africa, for example, show that this can be done successfully.

Source: World Bank 2005a.

safeguard their people from civil strife and crime by strengthening the rule of law, and use open decisionmaking processes to include the voices of civil society and citizens. Capacity development eﬀorts need clear objectives and should not rely on fragmented, project-centered approaches. They need time to be institutionalized, require followthrough by political and technical leaders, and must be supported by appropriate incentives. To be sure, training, equipment, and technical assistance are needed, but they should be provided in response to clear and eﬀective demand so that they can be eﬀectively absorbed. The successful cases—such as community-driven development in Malawi, performance management in Tanzania, public ﬁnancial management in Burkina Faso and Madagascar, and decentralization in Uganda and Ethiopia—rely on strong leadership, use ﬂexible and programmatic approaches to ﬁnancing, and match existing capacities with global and local knowledge. Strengthening public expenditure management and ﬁnancial accountability Sound public ﬁnancial management is fundamental for eﬀective use of domestic resources and of external aid. In most African countries expenditure and revenue accountability remains a challenge. Past eﬀorts have addressed regulatory changes, the rehabilitation of existing systems, the establishment of internal and external audits, and procurement reforms. There has been progress in the development of an indicator-based approach to public ﬁnancial management system assessment, evolving from the approach used

in assessing progress in the HIPC Debt Relief Initiative during 2001–04 and further reﬁned by the Public Expenditure and Financial Accountability initiative.29 Reforming legal and judicial systems Early reforms focused on adjusting legal and regulatory frameworks to facilitate economic development, such as protecting property. Regional economic integration triggered reforms of the regulatory frameworks for commercial and business laws. An important issue is the relationship between the formal judicial system and informal conﬂict resolution mechanisms. Many African countries have a well functioning system of village or community courts where decisions are made by laypersons in accordance with traditional rules. Judicial reforms must appreciate the role and importance of these traditional systems for African societies and their relevance for the judiciary. Improving public sector management The public sector is critical for good governance and development. In many countries civil services are overstaﬀed, overly bureaucratic, and ineﬃcient, with limited motivation and user-orientation. Well functioning administrative systems and a motivated, appropriately sized civil service are important for eﬃcient service delivery and optimal use of public resources. To address existing dysfunctions in the civil service, countries are reforming civil service with diﬀering emphases—in Nigeria and Zambia, improving the operational eﬃciency and rationalizing complex bureaucratic structures; and in MozamMoving from the Year of Africa to the Decade of Africa

17

bique, Nigeria, Sierra Leone, and Tanzania, pursuing bottom-up administrative reforms by building demand for change and capacity to implement development programs and to absorb aid. This also includes cross-cutting institutional reforms aimed at comprehensive decentralization and capacity development in the context of far-reaching political reforms, as in Ethiopia. Strengthening local governments Recognizing that decentralization is a political choice made by many African countries, governments are addressing the political, regulatory, administrative, and ﬁnancial implications of a decentralized state. In Ethiopia, Lesotho, Madagascar, Sierra Leone, Tanzania, and Uganda governments are developing or reforming the system of intergovernmental ﬁscal relations. Multisectoral public sector operations complement community-driven activities, especially where linked to local governance development. Community-driven development has proved an eﬀective means for rebuilding societies emerging from conﬂict. It addresses urgent local needs and restores collapsed trust and relationships. By engaging people in addressing problems at the local level, community-driven development can yield an invaluable peace dividend. Rwanda created the Community Reintegration and Development Project, which largely emphasized decentralization and encouraging local government. To involve local people in decisionmaking, community development committees give an active role to local governments and voice and inﬂuence to communities. Citizens have more decisionmaking power through an approach that links community participation with local management of resources, making both citizens and politicians accountable for results. Managing the impact of shocks Low-income countries in Africa are disproportionately aﬀected by outside economic shocks, in part due to continued heavy reliance on primary commodity exports or large swings in world prices of important inputs, such as the signiﬁcant rise in oil prices and other minerals, which has had adverse eﬀects on other sectors of the economy thanks to the exchange rate appreciation. These coun18

Africa Development Indicators 2006

tries have been buﬀeted by droughts, locusts, and other natural disasters while frequently lacking economic cushions, such as large foreign exchange reserves or insurance markets to protect themselves. Terms of trade shocks, for example, which tend to take several years to dissipate if triggered by export price declines, have very signiﬁcant negative impacts on growth rates. Weak capacity to manage terms of trade volatility has led to ﬁscal volatility as country authorities ﬁnd it diﬃcult to shield public expenditures (especially public consumption) from shocks. Negative shocks very often lead to increases in poverty. In the absence of stabilizing mechanisms, an “input shock,” such as a drought, very quickly translates into an “output shock,” leading to a fall in consumption. Since adequate social safety nets are usually lacking, poor people are hurt disproportionately, often being forced to sell their meager assets to try to maintain consumption. National strategies for the development of statistics Without baseline data and good information on trends, it’s not easy to put a target-driven development strategy into gear. Yet, with the MDG time horizon of 2015 rapidly approaching, many countries still do not collect the statistics they need to track progress. In many Sub-Saharan countries, policymakers do not know how many people are living in poverty or whether the number is growing or shrinking. Building a sustainable statistical system that can produce and disseminate statistics to manage development results has been a focus of many countries struggling to meet demand for data. Recognizing the importance of strategic planning to guide the improvement of statistical systems, the Marrakech Action Plan for Statistics endorsed by developing countries and development agencies recommended that all low-income countries prepare a national strategy for the development of statistics by the end of 2006. This recommendation was further supported by the Reference Regional Strategic Framework for Statistical Capacity Building in Africa, which aims to help African countries meet the data challenges of the results agenda by 2015.

M     For shared growth to become a reality, the Decade of Africa must be about results not promises. In the ﬁnal push to achieve as many of the MDGs in every African country, the ability to track progress is of enormous value. For example, the share of the population lacking access to safe water has dropped to 42 percent, from 51 percent in 1990, but an accelerated eﬀort is needed to reach the goal of lowering this to 26 percent by 2015. The basis for realistic optimism is based primarily on changes in Africa and in new approaches among the continent’s global partners. First, the African leadership—in government, the private sector, and civil society—is taking ownership for development on the continent. Complementing this initiative, we see a new international commitment to increase assistance and make it more eﬀective, and to open markets

to African products. Meanwhile, the signiﬁcant growth in Asia, particularly in China and India, opens new opportunities for increased trade and investment. It is critical that the global conversation about the challenge of Africa’s economic development continue. But it must be more than a discussion about how much aid or market access wealthy developed countries will oﬀer—important as these considerations are. It must also focus on the quality of development assistance and on the resourcefulness that Africans can bring to the challenges of building honest and capable states, and encouraging competitive companies that can generate jobs in agriculture, manufacturing, and services. Without Africans’ own investment and leadership, outside eﬀorts—however generous—will falter or worse, create new problems. In short, Africa’s future will be most signiﬁcantly determined by what Africans do.

Moving from the Year of Africa to the Decade of Africa

19

Notes

1

2 3 4 5 6

7 8

9 10

11

12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

20

Africa Development Indicators 2006

Throughout this essay Africa and African refer to Sub-Saharan Africa. The 14 countries are Angola (6.4 percent), Botswana (5.8 percent), Cape Verde (5.9 percent), Chad (9.9 percent), Equatorial Guinea (15.5 percent), Liberia (8 percent), Mali (6 percent), Mauritania (5.3 percent), Mozambique (8.4 percent), Rwanda (6.2 percent), Sierra Leone (6.7 percent), Sudan (6.2 percent), Tanzania (5.7 percent), and Uganda (5.7 percent). World Bank 2006b. World Bank Africa Region Poverty Studies. World Bank 2006b. Tcheyan 2006. 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: economic management, structural policies, policies for social inclusion and equity, and public sector management and institutions. Data on GDP growth for 2005 is preliminary. These ﬁgures include Zimbabwe, which experienced inﬂation rates of 350 percent in 2004 and 237 percent in 2005. Removing Zimbabwe from the calculation substantially reduces the average inﬂation to about half those rates (IMF 2006). Bacon and Mattar 2005. Established in 1987, the Strategic Partnership for Africa is an informal association of donors and African partners that works to improve the quality and increase the quantity of assistance to Africa. For more information, see www.spa-psa.org. This ﬁgure includes the Democratic Republic of Congo, a coastal country whose population is virtually landlocked. Eifert, Gelb, and Ramachandran 2005. Eifert, Gelb, and Ramachandran 2005. Tcheyan 2006. World Bank 2005b. Broadman 2006. Broadman 2006. Thirtle, Piesse, and Lin 2003. Tifﬁn and Irz 2006. Thirtle, Piesse, and Lin 2003. Mellor 2001. World Bank 2006c. High-Level Forum on the Health MDGs 2004. Haacker 2004. WHO and UNICEF 2005. Page and Plaza 2005. Page forthcoming. Angola, Cameroon, Chad, Democratic Republic of Congo, Republic of Congo, Equatorial Guinea, Gabon, Ghana, Guinea, Mauritania, Niger, Nigeria, São Tomé and Principe, and Sierra Leone.

29

The Public Expenditure and Financial Accountability initiative, started in December 2001, is jointly ﬁnanced by the World Bank’s Development Grant Facilities, the European Commission, the U.K. Department for International Development, the Swiss State Secretariat for Economic Affairs, the Royal Norwegian Ministry of Foreign Affairs, and the French Ministry of Foreign Affairs. The International Monetary Fund and the Strategic Partnership with Africa are also partners. A steering committee, comprising members of these agencies, manages the initiative, and a secretariat has been set up at the World Bank in Washington, D.C.

References

Bacon, Robert, and Adib Mattar. 2005. “The Vulnerability of African Countries to Oil Price Shocks: Major Factors and Policy Options.” World Bank, Washington, D.C. Bosworth, B., and S. Collins. 2006. “Economics of Developing Countries.” Brookings Institutions, Washington, D.C. [www. brookings.edu/es/research/projects/develop/develop.htm]. Broadman, Harry G. 2006. “Africa’s Silk Road: China and India’s New Economic Frontier.” World Bank, Washington, D.C. Eifert, Benn, Alan Gelb, and Vijaya Ramachandran. 2005. “Business Environment and Comparative Advantage in Africa: Evidence from the Investment Climate Data.” Working Paper 52. Center for Global Development, Washington, D.C. Haacker, Markus. 2004. “HIV/AIDS: The Impact on the Social Fabric and the Economy.” In The Macroeconomics of HIV/AIDS. Washington, D.C.: International Monetary Fund. High-Level Forum on the Health MDGs. 2004. “Addressing Africa’s Health Workforce Crisis: An Avenue for Action.” Background paper for the Second High-Level Forum on the Health MDGs, December 2–3, Abuja, Nigeria. [www. hlfhealthmdgs.org/Documents/AfricasWorkforce-Final.pdf] IMF (International Monetary Fund). 2006. Regional Economic Outlook: Sub-Saharan Africa. May. Washington, D.C.

WHO (World Health Organization) and UNICEF (United Nations Children’s Fund). 2005. World Malaria Report. Geneva. World Bank. 2003. World Development Report 2004: Making Services Work for Poor People. Washington, D.C. ———. 2005a. “Building Effective States, Forging Engaged Societies.” Task Force on Capacity Development in Africa. World Bank, Washington, D.C. ———. 2005b. “Infrastructure in Sub-Saharan Africa: The Role of the World Bank and the Donor Community.” World Bank, Africa Region, Financial, Private Sector and Infrastructure Department, Washington, D.C. ———. 2005c. World Development Report 2006: Equity and Development. Washington, D.C. ———. 2005d. Global Monitoring Report. Washington, D.C. ———. 2006a. Doing Business 2006: Creating Jobs. Washington, D.C. ———. 2006b. Global Monitoring Report. Washington, D.C. ———. 2006c. World Development Indicators 2006. Washington, D.C.

———. Various years. Directory of Trade Statistics. Washington, D.C. Mellor, J. 2001. “Reducing Poverty, Buffering Economic Shocks— Agriculture and the Non-Tradable Economy.” Background paper prepared for Experts’ Meeting, Roles of Agriculture Project, Food and Agricultural Organization, March 19–21, Rome. Page, John. Forthcoming. “Strategies for Pro-Poor Growth: ProPoor, Pro-Growth or Both?” Journal of African Economies. Page, John, and Sonia Plaza. 2005. “Migration, Remittances and Development: A Review of Global Evidence.” Paper presented at the Plenary Session of the African Economic Research Consortium, May 29, Nairobi. Tcheyan, Nils. 2006. “Revisioning Africa outside the Old Categories.” Paper presented at the University of California at Berkeley, April 8. Thirtle, C., J. Piesse, and L. Lin. 2003. “The Impact of ResearchLed Productivity Growth on Poverty in Africa, Asia and Latin America.” World Development 31 (12): 1959–75. Tifﬁn, Richard, and Xavier Irz. 2006. “Is Agriculture the Engine of Growth?” Agricultural Economics 35 (1): 79–89.

References

21

Indicator tables Part I. Basic indicators and national accounts 1. Basic indicators 1.1 Basic indicators

25

2. National accounts 2.1 Gross domestic product, real 2.2 Gross domestic product per capita, real 2.3 Agriculture value added 2.4 Industry value added 2.5 Services value added 2.6 Gross domestic product, nominal 2.7 Total consumption 2.8 General government consumption 2.9 Gross ﬁxed capital formation 2.10 General government ﬁxed capital formation 2.11 Private sector ﬁxed capital formation 2.12 Gross domestic savings 2.13 Gross national savings 2.14 Resource balance (exports minus imports) 2.15 Exports of goods and services, nominal 2.16 Imports of goods and services, nominal 2.17 Exports of goods and services, real 2.18 Imports of goods and services, real 2.19 Gross domestic product growth 2.20 Gross domestic product per capita growth 2.21 Gross national income per capita 2.22 Total consumption per capita

26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 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 equality 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 50 51 52 53 54 55 56

Part III. Development outcomes 4. Results framework 4.1 Status of Paris Declaration indicators

58

Drivers of growth 5. Private sector development

Contents

23

5.1 Business environment 5.2 Investment climate

59 60

6. Trade 6.1 International trade and tariﬀ barriers 6.2 Regional integration, trade blocs

62 65

7. Infrastructure 7.1 Water and sanitation 7.2 Transportation 7.3 Information and communication technology 7.4 Energy 7.5 Financial sector infrastructure

66 68 70 72 74

Participating in growth 8. Human development 8.1 Education 8.2 Health

76 78

9. Agriculture and rural development 9.1 Rural development 9.2 Agriculture

81 82

10. Labor, migration, and population 10.1 Labor 10.2 Migration and population

84 86

11. HIV/AIDS 11.1 HIV/AIDS

87

12. Malaria 12.1 Malaria

88

13. Capable states and partnership 13.1 Aid and debt relief 13.2 Capable states 13.3 Governance and anticorruption indicators 13.4 Country Policy and Institutional Assessment ratings, 2005

89 90 92 94

Part IV: Household Welfare 14. Household welfare 14.1 Burkina Faso household survey, 2003 14.2 Burundi household survey, 1998 14.3 Cameroon household survey, 2001 14.4 Côte d’Ivoire household survey, 1998 14.5 Ethiopia household survey, 2000 14.6 Gambia household survey, 1998 14.7 Ghana household survey, 1998/99 14.8 Kenya household survey, 1997 14.9 Madagascar household survey, 1999 14.10 Malawi household survey, 1997/98 14.11 Mozambique household survey, 1996 14.12 Nigeria household survey, 2004 14.13 São Tomé and Principe household survey, 2000 14.14 Sierra Leone household survey, 2002/03 14.15 Uganda household survey, 2002/03 14.16 Zambia household survey, 1998 24

Africa Development Indicators 2006

95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110

Table

Participating in growth

1.1

Basic indicators GNI per capita

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

Population (millions) 2004

Land area (thousands of sq km) 2004

Dollarsa 2004

726.4 680.9 552.2 15.5 8.2 1.8 12.8 7.3 16.0 0.5 4.0 9.4 0.6 55.9 3.9 17.9 0.8 0.5 4.2 70.0 1.4 1.5 21.7 9.2 1.5 33.5 1.8 3.2 18.1 12.6 13.1 3.0 1.2 19.4 2.0 13.5 128.7 8.9 0.2 11.4 0.1 5.3 8.0 45.5 35.5 1.1 37.6 6.0 27.8 11.5 12.9 150.5 32.4 72.6 5.7 29.8 9.9 876.9

23,619 22,405 21,494 1,247 111 567 274 26 465 4 623 1,259 2 2,267 342 318 23 28 101 1,000 258 10 228 246 28 569 30 96 582 94 1,220 1,025 2 784 823 1,267 911 25 1 193 0 72 627 1,214 2,376 17 884 54 197 743 387 5,738 2,382 995 1,760 446 155 29,358

600 397 390 930 450 4,360 350 90 810 1,720 310 250 560 110 760 760 950 .. 190 110 4,080 280 380 410 160 480 730 120 290 160 330 530 4,640 270 2,380 210 430 210 390 630 8,190 210 .. 3,630 530 1,660 320 310 250 400 620 1,784 2,270 1,250 4,400 1,570 2,650 803

Life expectancy Under-five Average at birth mortality rate Gini annual growth (years) (per 1,000) coefficient (%) 2000–04 2004 1996–2004b 1996–2004b

1.7 2.0 1.9 4.6 1.2 5.7 0.3 0.0 2.7 40.0 0.3 3.6 –0.1 0.0 –0.5 –2.4 0.0 0.0 –3.4 1.3 0.3 0.8 2.4 1.0 3.8 0.3 1.9 –2.8 –1.5 –0.3 2.3 4.0 2.9 6.2 3.2 0.0 2.7 0.3 2.3 1.6 –2.3 5.3 0.0 2.2 7.5 –0.7 4.6 –0.7 1.8 0.3 –6.2 0.0 3.0 0.0 0.0 3.0 3.4 1.9

46 46 47 41 55 35 48 44 46 70 39 44 63 44 52 46 53 43 54 42 54 56 57 54 45 48 36 42 56 40 48 53 73 42 47 45 44 44 63 56 .. 41 47 45 57 42 46 55 49 38 37 71 71 70 74 70 73 50

168.2 172.2 166.4 260.0 152.0 116.0 192.0 190.0 149.4 36.4 193.0 200.0 70.0 205.0 108.0 193.6 125.6 204.0 82.0 166.4 91.0 122.0 112.0 155.0 203.0 119.5 112.2 235.0 122.6 175.2 219.0 125.0 15.2 151.6 63.4 258.8 196.6 203.0 118.0 136.6 13.5 282.8 225.0 67.0 91.4 156.4 126.0 139.6 137.8 182.0 129.0 32.8 40.0 36.0 20.0 43.0 25.0 137.6

.. .. .. .. 36.5 .. 39.5 42.4 44.6 .. .. .. .. .. .. 44.6 38.6 .. .. 30.0 .. 50.2 40.8 .. .. 42.5 .. .. 47.5 50.3 .. 39.0 .. 39.6 .. .. 43.7 .. .. .. .. .. .. 57.8 .. .. 34.6 .. 43.0 42.1 .. 32.0 34.4 .. 39.5 39.8 .. ..

Adult literacy rate (% ages 15 and older) Male 2000–04b

Female 2000–04b

.. .. .. 83 48 80 29 67 77 .. 65 41 .. 81 .. 61 .. 93 .. .. .. .. 66 43 .. 78 74 .. 77 75 27 60 88 .. 87 43 .. 71 .. 51 91 47 .. 84 71 81 78 69 77 76 .. .. 80 .. .. 66 83 ..

.. .. .. 54 23 82 15 52 60 .. 33 13 .. 54 .. 39 .. 80 .. .. .. .. 50 18 .. 70 90 .. 65 54 12 43 81 .. 83 15 .. 60 .. 29 92 24 .. 81 52 78 62 38 58 60 .. .. 60 .. .. 40 65 ..

Total net official development assistance per capita (current $)

2004

33 34 41 74 46 22 48 48 47 282 26 34 42 32 30 9 82 60 61 26 28 43 63 30 50 19 57 65 68 38 43 60 31 63 89 40 4 53 218 92 124 67 24 14 25 104 46 10 42 94 14 19 10 20 .. 24 33 31

a. Calculated by the World Bank Atlas method. b. Data are for most recent year available during the period specified.

BASIC INDICATORS

Part I. Basic indicators and national accounts

25

Table

2.1

Gross domestic product, real

Constant prices (2000 $ millions)

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

Average annual growth (%)

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

222,703 127,255 97,330 6,746 1,084 1,130 1,263 559 6,339 .. 730 661 136 7,025 1,727 7,706 .. .. .. .. 3,265 213 2,640 .. 115 7,087 400 1,391 3,099 1,000 1,536 582 1,517 2,157 2,002 1,523 29,112 1,457 .. 2,417 290 754 .. 95,503 5,538 554 .. 964 .. 2,730 4,376 114,040 34,268 37,658 .. 18,307 8,630 339,883

269,422 158,478 126,079 8,464 1,412 3,175 1,750 865 8,793 303 809 1,099 181 7,670 2,765 8,274 608 248 .. 6,241 3,904 305 3,267 2,113 186 10,557 614 433 3,266 1,243 1,630 686 2,676 2,189 2,263 1,507 32,376 1,782 38 3,281 393 824 .. 110,945 7,079 1,024 6,801 1,071 3,077 3,028 6,734 172,850 45,148 65,727 .. 26,717 12,255 444,006

317,026 192,437 152,452 8,584 2,036 4,631 2,399 722 9,262 459 899 1,398 195 4,838 3,068 10,618 537 934 729 6,986 5,154 375 4,597 2,920 186 12,348 846 363 3,537 1,666 2,199 940 4,056 3,446 3,191 1,835 39,942 1,588 44 4,010 576 607 .. 124,638 10,887 1,315 8,344 1,307 5,192 3,058 8,334 222,130 50,583 91,404 .. 33,045 17,538 539,713

324,192 196,664 156,242 8,862 2,131 4,881 2,560 715 9,669 498 931 1,389 200 4,625 2,976 10,786 549 1,322 729 6,161 4,835 399 4,800 3,054 200 12,630 848 446 3,701 1,716 2,347 1,013 4,292 3,706 3,298 1,824 40,382 1,709 45 4,257 587 594 .. 127,577 11,577 1,361 8,639 1,340 5,610 3,126 8,034 228,009 52,057 93,967 .. 33,056 18,586 552,702

334,895 202,061 159,937 9,129 2,255 5,251 2,601 709 10,075 531 953 1,383 204 4,306 3,220 10,425 553 1,341 634 6,528 4,932 421 4,978 3,112 215 12,705 859 561 3,878 1,744 2,422 1,081 4,465 3,778 3,414 1,798 42,078 1,811 46 4,385 615 634 .. 132,878 12,330 1,389 9,079 1,329 5,926 3,238 7,399 236,346 53,306 98,782 .. 33,344 19,462 571,694

346,453 209,994 166,568 9,416 2,368 5,526 2,754 724 10,530 552 967 1,527 209 4,215 3,342 10,436 .. 1,361 692 7,104 5,055 445 5,187 3,237 216 13,262 887 577 4,111 1,657 2,716 1,120 4,713 4,273 3,495 1,926 43,382 1,933 48 4,591 601 588 .. 136,512 13,082 1,414 9,646 1,327 6,219 3,396 7,199 246,041 55,232 102,042 .. 35,512 20,513 592,841

358,273 216,776 172,685 10,768 2,474 5,804 2,875 756 10,952 577 959 1,655 213 4,363 3,496 10,266 .. 1,600 697 7,239 5,055 431 5,420 3,373 201 13,314 918 599 3,590 1,704 2,828 1,146 4,851 4,621 3,729 1,984 44,054 2,114 50 4,642 609 754 .. 141,549 13,867 1,455 10,345 1,382 6,622 3,508 6,883 254,992 57,138 105,103 .. 37,074 21,744 613,581

372,971 227,280 178,445 11,139 2,571 6,193 3,062 747 11,393 613 886 1,902 218 4,612 3,524 10,095 .. 1,835 724 6,972 5,187 460 5,675 3,413 202 13,683 946 411 3,941 1,808 3,039 1,219 4,992 4,986 3,858 2,090 48,766 2,133 52 4,946 571 828 .. 145,761 14,699 1,490 11,081 1,419 6,912 3,688 6,167 266,091 59,356 109,832 .. 38,335 23,157 639,340

391,961 239,766 187,999 12,378 2,650 6,494 3,182 783 11,815 640 898 2,463 222 4,925 3,651 10,261 .. 2,019 738 7,904 5,259 484 5,959 3,505 206 14,276 976 422 4,149 1,936 3,105 1,303 5,212 5,360 4,088 2,090 51,692 2,218 54 5,251 559 908 .. 152,276 15,581 1,521 11,822 1,461 7,300 3,887 5,908 279,378 62,064 115,873 .. 39,715 24,547 671,651

1.8 2.2 2.6 3.5 2.7 10.9 3.9 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 4.1 –3.3 0.8 2.4 0.5 1.9 5.9 –0.9 1.1 –0.4 0.8 2.5 .. 3.2 3.1 0.5 .. 1.4 2.4 6.5 .. 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 4.7 4.1 –3.2 1.3 5.9 1.8 2.3 1.2 –5.0 0.9 3.5 –1.7 20.7 7.9 4.0 3.2 2.7 4.3 4.5 1.4 2.2 4.2 0.2 1.7 3.8 3.9 4.5 5.3 6.3 4.0 2.4 2.4 –1.6 1.7 3.0 4.5 –3.7 .. 2.0 5.3 3.3 2.7 3.6 7.2 0.2 2.7 3.3 1.7 4.4 .. 2.4 4.6 2.7

4.0 4.3 4.0 8.1 4.1 5.5 5.2 2.3 4.1 4.9 –2.0 14.7 2.2 3.7 3.1 –0.6 .. 11.8 3.6 3.7 1.6 3.2 4.6 3.0 –1.5 2.7 3.2 –8.7 0.9 3.0 6.3 4.7 3.7 8.9 4.7 3.9 5.4 5.2 4.0 4.4 –2.4 11.2 .. 3.4 6.0 2.4 6.9 2.6 5.4 4.6 –5.9 4.2 3.8 4.0 .. 4.4 6.0 4.1

a. Preliminary.

26

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.2

Gross domestic product per capita, real

Constant prices (2000 $)

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

Average annual growth (%)

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

581 359 341 861 292 1,077 192 135 724 .. 314 143 405 251 958 924 .. .. .. .. 4,689 327 234 .. 144 435 310 744 342 162 220 362 1,570 179 2,029 246 425 280 .. 406 4,507 233 .. 3,463 277 981 .. 346 .. 451 599 1,261 1,827 880 .. 950 1,353 718

523 330 324 804 273 2,222 205 153 755 852 270 182 416 203 1,113 654 1,089 703 .. 122 4,078 325 211 340 183 451 386 203 271 131 183 338 2,532 163 1,619 178 358 251 330 411 5,614 202 .. 3,152 272 1,330 259 270 173 361 637 1,473 1,785 1,181 .. 1,117 1,503 702

502 326 319 651 300 2,706 225 115 650 1,067 247 182 376 101 952 664 802 2,183 220 114 4,243 304 242 361 144 421 482 134 232 153 200 376 3,497 201 1,767 167 356 232 327 407 7,302 142 .. 2,975 346 1,327 251 261 227 298 675 1,633 1,708 1,411 .. 1,215 1,879 703

503 327 322 656 305 2,812 233 112 664 1,132 251 175 378 94 894 658 792 3,015 213 119 3,885 313 247 370 151 421 478 153 235 153 207 395 3,655 211 1,780 160 352 228 329 422 7,294 136 .. 2,972 359 1,335 254 258 238 298 644 1,676 1,738 1,469 .. 1,200 1,967 709

507 328 321 660 313 2,994 230 109 678 1,179 252 168 377 86 937 623 774 2,988 178 122 3,877 320 251 369 158 414 481 183 239 151 208 409 3,762 211 1,802 153 358 226 332 424 7,579 141 .. 3,020 375 1,329 261 248 244 303 587 1,712 1,755 1,519 .. 1,197 2,036 717

512 333 327 662 319 3,130 237 109 695 1,196 252 180 378 82 942 612 .. 2,961 187 129 3,897 328 255 376 154 423 494 183 247 140 226 411 3,927 234 1,811 158 360 231 338 433 7,405 126 .. 3,046 390 1,324 272 240 248 311 567 1,749 1,774 1,543 .. 1,258 2,110 727

517 335 330 737 323 3,277 239 111 709 1,221 247 188 379 83 956 592 .. 3,403 180 126 3,830 308 261 383 138 416 510 187 209 141 229 408 4,009 247 1,902 157 358 245 344 428 7,277 154 .. 3,122 405 1,337 286 243 255 316 538 1,778 1,819 1,562 .. 1,284 2,122 735

526 343 333 740 325 3,496 247 106 723 1,267 225 208 379 85 935 573 .. 3,815 179 120 3,867 320 268 379 135 418 526 128 224 146 239 422 4,085 262 1,943 160 387 244 349 445 6,893 162 .. 3,181 422 1,347 300 243 257 327 479 1,834 1,923 1,579 .. 1,339 2,228 751

541 354 343 799 324 3,671 248 107 737 1,292 225 261 378 88 940 574 .. 4,101 174 132 3,860 327 275 381 134 427 543 130 229 154 237 437 4,223 276 2,035 155 402 250 354 461 6,688 170 .. 3,346 439 1,358 314 244 262 339 457 1,879 1,992 1,615 .. 1,349 2,341 771

–1.1 –0.8 –0.4 0.5 –0.7 7.5 1.3 1.1 1.6 4.1 –1.0 3.9 0.3 –0.8 0.6 –3.5 .. .. .. –1.1 –2.7 –0.2 –0.6 .. 1.4 0.3 1.8 –4.9 –2.0 –1.9 –1.9 –0.5 4.9 –1.9 –2.3 –3.4 –2.0 –1.2 .. 0.2 2.3 –1.9 .. –1.2 –0.4 3.3 .. –2.1 –1.3 –2.3 –0.5 1.6 –0.1 2.9 .. 2.0 0.6 –0.2

–0.2 0.1 0.2 –1.8 1.3 2.4 1.2 –4.4 –1.2 3.4 –0.6 –0.8 –1.0 –7.7 –2.3 0.6 –3.8 17.8 6.2 1.1 0.2 –0.8 1.7 1.2 –1.6 –0.6 3.0 –3.3 –1.3 2.0 1.2 1.8 4.0 3.0 0.8 –0.9 –0.3 –1.7 –0.1 0.4 2.9 –4.3 .. –0.3 2.8 0.1 –0.2 0.5 3.9 –2.2 0.8 1.5 –0.3 2.5 .. 0.8 2.9 0.3

1.6 1.8 1.5 5.1 0.9 5.3 1.9 –0.6 2.1 2.4 –3.3 10.8 0.0 0.8 0.0 –2.3 .. 9.3 –0.9 0.8 –0.2 0.2 2.4 0.7 –4.5 0.5 3.1 –9.9 –1.8 0.7 3.2 1.6 2.7 6.7 3.2 0.4 3.1 2.6 1.6 2.0 –3.2 6.5 .. 2.5 4.0 0.6 4.8 –0.2 1.9 2.8 –6.5 2.4 3.4 1.5 .. 3.0 3.4 1.8

a. Preliminary.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

27

Table

2.3

Agriculture value added

Constant prices (2000 $ millions)

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

Average annual growth (%)

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

36,019 32,933 25,571 .. 316 133 410 218 1,877 23 298 306 43 1,565 118 1,628 .. .. .. .. 320 87 1,227 .. 45 2,192 104 .. 690 263 656 107 224 .. 179 479 7,011 535 .. 495 18 370 .. 3,073 1,713 126 .. 220 .. 371 599 17,093 2,300 8,668 .. 4,023 1,201 53,056

44,387 40,677 32,242 686 467 155 531 300 2,380 50 332 321 59 2,011 166 1,756 18 54 .. 2,901 342 89 1,269 457 79 3,138 137 .. 852 302 792 127 274 707 223 537 8,447 558 6 654 17 489 .. 3,692 2,144 144 2,767 342 1,401 471 858 23,548 3,112 11,478 .. 5,925 1,792 67,896

55,544 51,989 41,163 467 744 151 819 272 3,388 65 433 597 69 2,353 174 2,265 18 78 170 3,282 293 93 1,653 647 100 3,452 135 .. 972 536 958 186 298 947 294 782 10,839 633 9 720 15 305 .. 3,557 4,244 144 3,505 453 1,803 576 1,091 29,317 4,521 14,496 .. 6,567 2,189 84,817

57,763 53,986 42,596 473 774 139 850 269 3,619 59 450 578 72 2,407 164 2,216 18 86 157 2,806 306 120 1,717 699 108 3,696 141 .. 1,005 590 1,046 195 300 1,000 312 743 11,399 687 9 818 17 323 .. 3,777 4,653 156 3,650 477 1,908 634 1,137 28,745 4,529 14,909 .. 5,378 2,415 86,505

58,916 54,959 43,236 517 824 139 881 255 3,782 64 478 563 83 2,126 171 2,400 18 94 89 2,868 318 133 1,757 697 112 3,649 145 .. 1,013 622 938 193 230 887 338 680 11,730 750 9 850 17 349 .. 3,956 4,963 150 3,773 455 2,014 644 1,174 28,100 4,302 15,418 .. 4,509 2,390 87,042

61,159 57,335 45,168 610 849 144 848 247 3,923 64 498 621 88 2,043 180 2,407 .. 100 115 3,197 331 145 1,822 740 114 4,012 145 .. 1,054 585 1,043 187 304 971 304 770 12,176 812 10 879 17 218 .. 3,827 5,239 136 3,980 461 2,111 627 1,128 .. 4,604 .. .. 5,546 2,426 91,549

62,702 58,626 45,936 691 911 143 919 257 4,067 60 517 617 90 2,053 188 2,351 .. 104 80 3,124 348 104 1,896 778 113 3,870 139 .. 1,041 600 1,005 182 318 1,076 334 785 12,692 930 10 700 17 284 .. 4,077 5,633 138 4,178 494 2,193 616 872 .. 4,788 .. .. 5,934 2,584 94,379

64,769 60,782 47,263 772 932 145 919 248 4,209 63 536 648 93 2,078 200 2,379 .. 92 89 2,730 366 124 1,984 801 121 3,967 137 .. 1,054 636 1,183 193 269 1,173 347 832 13,513 901 10 836 15 305 .. 3,991 6,006 142 4,346 489 2,243 647 863 .. 4,979 .. .. 5,993 2,752 97,466

67,503 63,593 49,184 886 985 149 1,086 247 4,393 67 533 614 95 2,090 212 2,474 .. .. 95 3,247 388 142 2,075 834 128 4,024 137 .. 1,086 653 1,128 188 278 1,271 336 .. 14,392 901 10 872 15 323 .. 3,923 5,943 144 4,604 505 2,361 675 838 .. 5,178 .. .. 6,053 2,931 101,399

2.3 2.2 2.1 .. 5.2 1.7 3.6 3.1 2.5 15.3 1.7 3.1 4.0 2.5 3.3 –0.4 .. .. .. 0.1 1.5 1.2 0.9 .. 5.0 3.2 2.1 .. 2.4 2.1 2.6 2.0 3.1 7.3 1.3 1.8 2.9 0.8 .. 2.8 –1.7 3.5 .. 2.9 2.3 2.0 .. 5.7 1.5 4.1 2.8 3.9 4.3 2.7 .. 7.0 2.0 2.8

3.2 3.4 3.5 –2.9 5.8 –1.0 4.3 –1.9 5.3 4.2 3.6 5.5 2.3 2.2 1.0 3.2 0.7 7.2 5.4 2.0 –1.9 2.2 3.3 4.7 4.3 1.8 1.7 .. 1.8 8.5 3.1 4.8 0.7 5.3 3.5 3.6 3.3 1.5 3.6 2.5 –0.5 –2.9 .. 0.7 9.1 1.0 3.2 4.5 3.6 4.3 4.2 2.4 4.0 3.1 .. 0.1 2.1 2.9

3.3 3.6 3.1 14.0 4.6 1.5 5.1 –0.6 3.8 0.9 3.0 2.2 3.3 –0.2 5.5 0.5 .. –0.1 –1.2 0.9 5.1 –0.2 4.3 4.5 3.3 1.9 –1.7 .. 1.4 1.8 5.1 –0.2 2.6 9.5 1.2 6.4 5.3 4.8 3.0 0.0 –3.1 1.9 .. 0.3 5.1 –0.3 5.0 2.7 3.9 1.3 –9.0 .. 4.6 .. .. 6.9 5.5 3.7

a. Preliminary.

28

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.4

Industry value added

Constant prices (2000 $ millions) 1980

SUB–SAHARAN AFRICA 74,683 excluding South Africa 41,975 23,829 excl. S. Africa & Nigeria Angola .. Benin 115 Botswana 550 Burkina Faso 252 Burundi 98 Cameroon 1,029 Cape Verde 23 Central African Republic 146 Chad 62 Comoros 20 Congo, Dem. Rep. 2,497 Congo, Rep. 958 Côte d’Ivoire 1,227 Djibouti .. Equatorial Guinea .. Eritrea .. Ethiopia .. Gabon 1,743 Gambia, The 28 Ghana 866 Guinea .. Guinea-Bissau 24 Kenya 1,189 Lesotho 117 Liberia .. Madagascar 461 Malawi 175 Mali 166 Mauritania 193 Mauritius 319 Mozambique .. Namibia 689 Niger 306 Nigeria 16,961 Rwanda 459 São Tomé and Principe .. Senegal 399 Seychelles 44 Sierra Leone 231 Somalia .. South Africa 32,864 Sudan 1,210 Swaziland 107 Tanzania .. Togo 216 Uganda .. Zambia 886 Zimbabwe 1,235 NORTH AFRICA 48,101 Algeria 19,763 Egypt, Arab Rep. 12,108 Libya .. Morocco 5,929 Tunisia 2,488 ALL AFRICA 124,438

Average annual growth (%)

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

83,702 48,249 33,018 4,861 203 1,682 333 159 1,930 59 157 170 16 2,288 1,735 1,575 107 32 .. 812 2,260 42 962 712 34 1,752 186 .. 398 236 248 271 704 308 670 275 15,230 566 7 630 65 303 .. 35,440 1,431 313 967 212 381 1,018 1,714 64,746 25,325 17,338 .. 8,041 3,523 149,895

92,831 56,253 39,103 5,973 281 2,113 375 121 1,564 84 152 167 24 802 2,191 2,532 69 746 141 825 2,545 45 1,151 974 24 1,990 301 .. 458 276 433 351 1,088 698 856 306 17,150 340 8 841 170 189 .. 36,574 2,358 418 1,166 221 929 756 1,832 83,581 27,559 27,341 .. 10,075 5,028 176,978

94,133 57,621 40,912 6,359 287 2,223 398 127 1,663 97 159 158 24 1,061 2,226 2,573 69 1,202 145 559 2,581 46 1,208 1,026 25 1,943 303 .. 478 285 443 359 1,158 817 861 313 16,713 358 8 864 158 161 .. 36,511 2,558 427 1,232 228 1,040 709 1,770 86,894 28,968 28,019 .. 10,461 5,330 181,412

97,639 59,247 41,516 6,584 313 2,480 422 119 1,746 95 173 155 24 863 2,323 2,288 70 1,178 135 569 2,624 48 1,265 1,075 26 1,908 320 .. 504 282 464 380 1,208 906 873 319 17,732 371 8 901 178 170 .. 38,387 2,523 432 1,319 237 1,095 729 1,586 93,288 30,221 31,577 .. 10,727 5,609 191,046

100,381 61,247 43,050 6,853 341 2,608 457 111 1,764 95 180 177 26 840 2,253 2,214 .. 1,156 144 597 2,676 51 1,325 1,133 28 1,946 334 .. 543 252 561 366 1,294 1,095 905 327 18,199 399 8 940 177 153 .. 39,132 2,904 444 1,410 230 1,168 796 1,456 .. 30,452 .. .. 11,048 5,900 195,797

102,596 62,416 45,690 7,841 362 2,694 460 104 1,777 108 187 220 27 909 2,336 2,117 .. 1,420 155 632 2,749 56 1,409 1,186 31 1,996 357 .. 430 248 661 394 1,328 1,203 975 337 16,741 431 9 1,032 187 193 .. 40,177 3,122 451 1,542 255 1,260 873 1,296 .. 31,483 .. .. 11,435 6,219 201,034

109,853 69,354 48,874 8,138 372 2,887 460 98 1,787 114 200 344 28 1,025 2,292 1,960 .. 1,782 158 661 2,828 60 1,510 1,191 30 2,108 373 .. 492 261 599 416 1,335 1,324 1,021 350 20,484 450 9 1,084 165 219 .. 40,507 4,528 460 1,702 291 1,351 949 1,108 .. 32,888 .. .. 11,835 6,555 213,482

116,040 73,740 52,341 9,127 370 3,032 .. 92 1,783 124 205 780 29 1,162 2,469 2,034 .. .. 158 707 2,913 64 .. 1,225 30 2,181 384 .. 525 288 597 440 1,356 1,392 1,170 .. 21,434 460 .. 1,165 171 263 .. 42,338 5,044 468 1,873 312 1,426 1,050 1,069 .. 34,735 .. .. 12,297 6,909 225,199

1.0 1.3 3.6 .. 3.3 11.8 4.2 4.6 7.5 14.6 1.6 7.9 –2.3 2.3 5.5 5.1 .. .. .. 3.9 0.4 4.3 2.6 .. 1.3 3.7 4.1 .. 0.7 2.4 4.7 5.4 9.0 –4.5 –0.3 –2.0 –2.1 2.8 .. 4.4 3.8 0.2 .. 0.5 0.9 11.8 .. 0.7 4.4 0.7 2.9 2.9 2.9 3.2 .. 2.7 2.9 1.7

1.7 2.2 2.8 3.9 4.1 3.0 2.2 –4.7 –2.0 5.1 0.2 0.5 4.6 –8.9 3.0 6.6 –6.2 50.0 18.3 3.5 2.6 0.7 2.3 4.6 –2.5 1.5 5.4 .. 2.0 2.0 6.4 3.5 5.5 11.9 2.5 1.8 0.9 –5.5 1.4 4.0 11.9 –5.1 .. 0.9 6.0 3.9 2.5 1.7 12.6 –4.4 1.1 3.0 1.4 4.5 .. 3.1 4.5 2.2

4.5 5.8 6.1 8.6 4.3 5.2 2.7 –6.2 0.6 7.4 4.6 47.7 4.1 8.2 1.4 –3.5 .. 15.6 4.1 5.5 2.7 7.2 6.1 3.2 4.0 3.5 4.9 .. –0.2 0.8 5.9 4.3 2.7 11.1 7.3 3.1 5.1 5.7 4.3 6.8 –1.5 13.1 .. 2.3 20.1 2.0 9.3 8.2 7.0 9.5 –10.1 .. 3.6 .. .. 3.5 5.4 4.2

a. Preliminary.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

29

Table

2.5

Services value added

Constant prices (2000 $ millions) 1980

SUB–SAHARAN AFRICA 95,542 excluding South Africa 47,353 41,590 excl. S. Africa & Nigeria Angola .. Benin 679 Botswana 292 Burkina Faso 598 Burundi 163 Cameroon 3,695 Cape Verde 92 Central African Republic 236 Chad 308 Comoros 78 Congo, Dem. Rep. 3,931 Congo, Rep. 458 Côte d’Ivoire 4,857 Djibouti .. Equatorial Guinea .. Eritrea .. Ethiopia .. Gabon 1,226 Gambia, The 100 Ghana 673 Guinea .. Guinea-Bissau 38 Kenya 2,625 Lesotho 149 Liberia .. Madagascar 1,612 Malawi 445 Mali 531 Mauritania 236 Mauritius 778 Mozambique .. Namibia 775 Niger 738 Nigeria 5,636 Rwanda 500 São Tomé and Principe .. Senegal 1,518 Seychelles 228 Sierra Leone 81 Somalia .. South Africa 48,244 Sudan 2,684 Swaziland 165 Tanzania .. Togo 539 Uganda .. Zambia 1,250 Zimbabwe 1,993 NORTH AFRICA 43,930 Algeria 9,623 Egypt, Arab Rep. 15,159 Libya .. Morocco 8,690 Tunisia 4,924 ALL AFRICA 140,764

Average annual growth (%)

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

123,949 62,710 54,454 2,556 752 1,091 877 298 4,443 196 254 528 114 4,607 690 4,958 410 25 .. 2,219 1,364 136 1,117 901 59 4,235 218 .. 1,609 592 636 244 1,316 970 1,185 695 8,267 712 27 1,995 310 82 .. 61,244 3,072 264 2,444 516 1,065 1,159 2,893 75,732 13,481 32,594 .. 13,209 6,908 200,440

146,380 73,858 63,114 2,103 1,011 1,992 1,206 243 4,169 312 228 577 106 1,656 687 5,854 390 54 356 2,429 2,262 187 1,785 1,168 50 5,498 317 .. 1,769 695 771 333 2,157 1,497 1,733 746 10,746 621 28 2,455 391 77 .. 72,527 3,655 351 2,947 634 2,004 1,364 3,780 95,710 15,267 41,259 .. 16,810 10,317 242,506

150,717 75,339 64,522 2,035 1,073 2,118 1,311 242 4,160 342 233 602 107 1,328 638 6,043 396 60 364 2,362 1,949 185 1,869 1,192 54 5,613 317 .. 1,866 685 819 382 2,285 1,522 1,797 768 10,820 666 28 2,575 412 75 .. 75,379 4,024 367 3,100 633 2,147 1,449 3,856 101,743 15,379 45,328 .. 17,393 10,827 252,642

155,862 77,419 66,170 2,028 1,118 2,233 1,298 258 4,306 373 215 612 96 1,265 726 5,738 403 66 365 2,586 1,990 190 1,956 1,224 61 5,718 315 .. 1,967 669 854 431 2,429 1,611 1,869 798 11,251 690 29 2,633 419 79 .. 78,441 4,377 383 3,286 637 2,285 1,512 3,588 104,152 15,634 45,827 .. 18,109 11,462 260,285

162,027 80,740 69,115 1,935 1,178 2,377 1,439 304 4,715 393 204 670 93 1,249 804 5,811 .. 74 382 2,708 2,045 203 2,044 1,249 60 5,899 322 .. 2,086 671 905 473 2,583 1,832 1,942 828 11,628 721 30 2,772 408 83 .. 81,288 4,530 396 3,467 635 2,474 1,585 3,610 .. 16,102 .. .. 19,037 12,198 271,028

168,823 84,135 71,741 2,219 1,195 2,483 1,490 338 5,091 407 173 735 94 1,294 848 5,796 .. 83 383 2,832 1,977 221 2,133 1,273 67 6,030 329 .. 1,756 691 911 484 2,726 1,940 2,064 862 12,393 748 32 2,929 405 106 .. 84,690 4,713 416 3,682 627 2,672 1,647 3,877 .. 16,990 .. .. 19,851 12,954 283,009

175,089 86,760 73,505 2,194 1,266 2,567 1,671 346 5,504 433 112 797 95 1,376 865 5,741 .. 80 408 2,897 2,015 227 2,220 1,293 63 6,171 341 .. 1,940 701 994 516 2,870 2,030 2,135 907 13,248 783 33 3,038 390 117 .. 88,325 4,576 428 3,887 631 2,841 1,726 3,293 .. 18,074 .. .. 20,627 13,869 294,719

182,315 89,825 75,629 2,335 1,292 2,673 2,111 396 5,873 447 121 859 96 1,497 859 5,729 .. .. 414 3,092 1,995 238 .. 1,313 63 6,497 356 .. 2,056 738 1,084 570 3,025 2,209 2,223 .. 14,167 860 .. 3,228 373 129 .. 92,466 4,944 439 4,120 634 3,022 1,763 2,541 .. 19,298 .. .. 21,461 14,727 307,862

2.5 2.6 2.6 .. 1.1 15.2 3.9 5.5 3.5 8.5 1.3 7.4 3.3 2.3 3.0 –0.1 .. .. .. 4.5 0.3 2.5 5.3 .. 3.1 4.9 3.9 .. –0.2 3.2 2.1 –0.1 4.8 7.3 3.7 –1.3 2.7 3.9 .. 2.9 3.3 –1.1 .. 2.4 0.7 4.7 .. –0.5 2.1 0.0 2.8 5.6 3.3 8.2 .. 4.2 3.7 3.5

2.4 2.3 2.1 –2.8 4.0 8.0 4.6 –3.4 0.0 6.4 –0.3 0.6 –0.4 –13.0 –1.1 2.5 –0.8 9.7 6.9 6.1 4.5 3.9 5.9 3.6 –0.7 3.4 4.8 .. 2.0 1.9 2.8 4.9 6.4 4.7 4.6 1.6 3.1 –2.5 0.7 2.9 2.6 –2.6 .. 2.6 2.2 3.5 2.4 3.7 8.3 2.0 3.4 3.7 1.8 4.5 .. 2.7 5.3 2.9

4.0 3.8 3.3 4.2 3.7 4.5 11.9 10.4 8.1 4.7 –16.0 8.9 0.2 4.4 4.2 –0.2 .. 6.9 3.2 4.3 –0.1 5.9 4.3 1.8 1.2 3.1 3.2 .. 0.2 2.4 5.9 6.7 5.6 7.6 4.5 4.3 6.1 5.4 4.6 5.1 –2.7 14.1 .. 4.2 2.6 3.6 5.8 –0.2 7.2 4.0 –7.5 .. 5.5 .. .. 4.3 6.5 4.3

a. Preliminary.

30

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.6

Gross domestic product, nominal Current prices ($ millions) Annual average

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

261,288 181,358 116,062 .. 1,405 1,061 1,929 920 6,741 .. 797 1,033 124 14,395 1,706 10,175 .. .. .. .. 4,279 241 4,445 .. 111 7,265 431 954 4,042 1,238 1,787 709 1,153 3,526 2,169 2,509 64,202 1,163 47 2,987 147 1,101 604 80,710 7,617 543 .. 1,136 1,245 3,884 6,679 126,527 42,345 22,912 35,545 18,821 8,743 392,413

301,381 189,495 161,088 10,260 1,845 3,792 3,120 1,132 11,152 339 1,488 1,739 263 9,350 2,799 10,796 418 132 .. 12,083 5,952 317 5,886 2,818 244 8,591 615 384 3,081 1,881 2,421 1,020 2,383 2,463 2,350 2,481 28,472 2,584 58 5,699 369 650 917 112,014 13,167 882 4,259 1,628 4,304 3,288 8,784 165,240 62,045 43,130 .. 25,784 12,291 470,822

328,394 194,115 161,994 6,445 2,335 4,932 2,794 894 8,703 540 1,047 1,745 216 6,218 1,949 12,783 514 456 746 7,724 4,619 417 7,474 3,588 206 14,093 890 360 3,739 1,751 2,597 1,133 4,146 3,874 3,399 2,077 32,144 1,989 41 4,678 608 672 .. 134,296 11,086 1,346 8,383 1,587 6,585 3,237 6,066 216,647 47,357 84,829 .. 35,817 19,813 546,688

327,604 194,442 159,668 6,154 2,387 5,025 2,811 808 10,904 583 1,051 1,537 223 4,711 2,354 12,556 536 872 689 6,498 4,352 432 7,710 3,461 224 12,896 911 442 3,717 1,776 2,570 1,126 4,258 3,985 3,386 2,018 34,776 1,931 47 4,757 623 664 .. 133,184 10,702 1,377 8,638 1,576 5,999 3,131 5,964 222,680 47,592 89,207 .. 35,277 20,970 551,406

334,895 202,061 159,937 9,129 2,255 5,251 2,601 709 10,075 531 953 1,383 204 4,306 3,220 10,425 553 1,341 634 6,528 4,932 421 4,978 3,112 215 12,705 859 561 3,878 1,744 2,422 1,081 4,465 3,778 3,414 1,798 42,078 1,811 46 4,385 615 634 .. 132,878 12,330 1,389 9,079 1,329 5,926 3,238 7,399 236,346 53,306 98,782 .. 33,344 19,462 571,694

334,599 216,299 168,215 8,936 2,372 5,184 2,814 662 9,598 550 967 1,702 220 4,690 2,788 10,554 .. 1,702 671 6,510 4,334 418 5,309 3,042 199 13,059 763 543 4,529 1,717 2,630 1,098 4,534 3,697 3,216 1,945 48,000 1,703 48 4,564 619 814 .. 118,479 13,345 1,260 9,441 1,328 5,681 3,637 12,879 240,489 56,689 97,545 .. 34,219 20,032 575,198

356,494 245,948 199,234 10,835 2,807 5,423 3,203 628 10,880 616 1,046 1,982 247 5,547 3,017 11,482 .. 2,118 631 6,058 4,971 370 6,160 3,208 201 13,192 699 559 4,397 1,935 3,343 1,116 4,555 4,092 3,122 2,170 46,711 1,732 54 4,998 698 946 .. 110,882 15,054 1,192 9,772 1,476 5,848 3,697 30,853 240,231 57,990 90,650 .. 37,555 22,067 598,100

434,165 268,110 209,726 13,825 3,558 7,737 4,182 595 13,672 797 1,195 2,671 318 5,671 3,564 13,734 .. 2,915 747 6,651 6,055 367 7,521 3,638 235 15,036 1,065 435 5,474 1,764 4,362 1,340 5,237 4,786 4,473 2,731 58,294 1,684 60 7,501 703 999 .. 166,169 17,550 1,906 10,291 1,759 6,255 4,327 7,913 254,856 64,097 84,395 .. 45,817 26,632 693,664

526,485 311,836 239,628 19,564 4,047 8,974 4,824 664 15,775 948 1,307 4,307 369 6,632 4,343 15,475 .. 3,235 928 8,075 7,229 401 8,620 3,775 270 16,088 1,367 492 4,364 1,903 4,882 1,534 6,038 5,912 5,712 3,053 72,053 1,835 57 7,775 703 1,085 .. 214,663 21,463 2,517 11,311 2,061 6,822 5,423 4,696 269,150 75,068 75,744 .. 52,528 29,993 804,404

250,845 160,131 124,270 3,780 1,318 1,576 2,002 1,065 9,159 187 929 1,068 144 10,028 2,106 8,609 380 107 .. 6,594 3,676 225 4,692 2,230 156 7,069 412 935 3,124 1,255 1,609 806 1,387 3,375 1,859 2,000 35,577 1,761 52 3,341 197 963 855 90,894 12,478 552 5,009 1,021 3,611 3,171 7,204 135,859 53,750 31,646 26,527 16,987 8,923 391,471

313,764 179,741 149,758 7,042 2,005 4,511 2,629 979 10,052 448 1,177 1,602 238 7,161 2,343 11,200 485 294 609 7,115 5,062 374 6,576 3,376 242 9,906 847 264 3,326 1,900 2,486 1,085 3,563 2,766 3,119 2,013 30,007 1,771 48 4,922 494 779 917 134,007 9,644 1,186 5,904 1,458 4,835 3,349 7,375 179,698 47,968 59,638 .. 31,339 16,839 497,210

397,327 248,851 195,348 12,458 3,008 6,514 3,525 652 12,000 689 1,094 2,409 272 5,369 3,386 12,334 553 2,262 722 6,764 5,504 395 6,517 3,355 224 14,016 951 518 4,528 1,812 3,528 1,234 4,966 4,453 3,987 2,340 53,427 1,753 53 5,845 668 895 .. 148,614 15,948 1,653 9,979 1,591 6,107 4,064 12,748 248,214 61,430 89,423 .. 40,693 23,637 648,612

a. Preliminary.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

31

Table

2.7

Total consumption Share of GDP (%) Annual average

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

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

72.4 76.7 83.3 .. 106.3 73.3 107.2 100.6 78.3 .. 108.9 .. 110.1 89.9 64.3 79.6 .. .. .. .. 39.4 94.2 95.1 .. 101.0 81.9 151.9 85.2 101.4 89.2 98.9 103.5 85.5 108.9 61.6 85.4 68.6 95.8 111.6 105.0 72.9 99.1 112.9 62.1 97.9 98.8 .. 76.8 100.4 80.7 86.2 59.5 56.9 84.8 43.1 86.3 76.0 68.4

80.1 82.6 84.9 70.3 97.8 57.4 94.8 105.4 79.3 108.1 100.6 107.7 103.0 90.7 76.2 88.7 .. 120.1 .. 90.4 63.1 89.3 94.5 82.3 97.2 81.5 152.9 .. 94.5 86.6 93.6 95.1 76.5 105.8 81.8 98.8 70.6 93.8 142.4 91.1 79.7 91.3 112.5 76.8 .. 90.8 98.7 85.3 99.4 83.4 82.5 77.7 72.9 83.9 .. 80.7 74.5 79.3

84.7 86.7 88.0 80.7 93.4 60.2 88.4 104.7 80.8 115.3 94.7 94.1 104.7 101.0 69.7 80.3 100.8 80.1 132.9 86.9 61.0 88.2 89.7 82.7 110.1 89.7 133.5 .. 93.0 91.9 89.6 95.6 75.1 89.2 86.3 97.3 80.4 102.8 107.0 88.1 81.3 97.5 .. 81.9 94.2 98.6 100.8 97.2 94.4 96.1 81.0 81.8 72.9 88.0 .. 81.9 76.4 83.7

83.8 85.8 86.9 79.3 95.2 61.3 91.9 102.5 68.8 117.5 89.0 100.2 105.7 90.9 59.0 78.7 105.5 .. 141.2 97.9 65.2 89.0 96.5 82.7 101.2 89.3 122.4 .. 92.8 100.6 90.5 95.0 76.7 86.3 87.5 96.3 80.9 100.0 110.3 88.7 74.4 110.3 .. 81.0 92.3 99.7 97.2 96.8 91.9 101.1 84.0 78.2 68.6 83.1 .. 80.4 75.4 81.7

80.9 80.8 84.6 60.5 94.0 58.3 93.5 107.3 79.7 114.2 92.2 94.5 98.9 95.5 42.3 82.1 105.3 .. 134.7 99.1 71.7 91.5 94.4 83.2 108.5 90.6 120.4 .. 92.3 96.2 88.0 86.8 76.1 88.4 86.0 96.5 66.6 98.7 104.1 89.1 77.7 113.3 .. 81.1 84.1 95.7 90.7 102.2 90.8 91.7 86.7 74.9 55.8 82.7 .. 81.8 76.1 78.7

81.7 82.1 86.1 84.9 93.5 59.5 95.0 109.0 81.0 115.1 88.9 94.7 100.9 96.6 46.9 81.0 .. .. 127.1 96.9 49.7 88.0 93.0 84.3 119.3 88.7 116.3 103.4 84.7 96.2 86.0 101.4 74.0 92.0 83.0 95.6 68.3 97.4 122.9 90.5 80.1 111.5 .. 80.8 90.2 96.9 91.4 99.0 93.7 82.7 89.8 75.1 59.1 82.3 .. 80.7 75.5 79.1

82.5 83.8 86.1 74.8 96.3 61.1 95.3 111.4 81.0 115.7 89.7 102.5 98.2 96.0 50.0 73.7 .. .. 133.7 97.5 51.6 87.1 92.6 90.9 112.1 87.2 118.0 103.3 92.3 110.1 88.7 104.9 74.9 89.0 82.2 94.7 74.2 100.0 117.2 94.4 76.7 109.3 .. 79.8 86.7 80.5 88.4 99.4 94.5 82.3 94.0 75.6 62.0 82.2 .. 80.9 75.1 80.0

80.0 81.0 84.7 80.6 94.0 61.4 96.1 108.2 81.4 115.8 85.6 81.5 98.7 95.0 52.6 79.4 .. .. 160.4 99.0 54.7 88.9 90.9 92.5 98.8 87.0 112.2 103.0 91.1 110.7 86.8 117.6 75.0 89.9 73.8 95.0 67.6 100.8 122.1 92.3 80.4 107.4 .. 78.3 84.3 82.4 90.5 94.7 93.5 81.3 94.1 75.2 63.6 81.5 .. 80.2 74.4 78.3

78.1 78.0 83.3 75.5 94.5 61.8 94.4 108.4 81.5 112.2 86.8 69.5 101.5 96.1 48.6 79.5 .. .. 162.9 99.5 53.6 89.5 89.7 93.5 101.7 87.4 107.7 100.6 92.2 109.1 89.3 118.8 76.4 87.7 73.3 94.2 60.4 97.6 129.0 90.2 78.6 104.9 .. 78.3 81.3 85.9 91.5 95.5 90.9 81.8 95.2 74.4 64.3 81.0 .. 79.9 73.3 77.0

78.0 81.7 82.7 76.0 102.4 64.7 102.7 96.9 75.8 101.8 101.1 108.1 104.5 89.1 68.1 80.4 .. .. .. 93.1 55.7 93.5 95.2 83.6 100.9 82.1 166.4 97.8 97.1 87.3 100.4 96.9 80.0 106.2 89.2 92.7 82.5 95.0 116.2 99.9 75.9 90.9 106.3 71.5 95.0 96.3 89.3 87.7 97.7 86.0 83.5 71.6 68.5 84.5 53.1 84.1 77.3 75.7

83.4 85.6 87.5 77.5 96.2 60.7 92.4 105.2 79.9 105.6 96.3 100.5 104.4 91.2 71.2 82.2 105.4 86.3 130.9 94.7 58.3 92.6 92.5 84.2 98.5 84.4 138.1 .. 95.8 96.6 92.4 92.6 75.9 99.0 87.3 97.3 76.0 105.5 120.0 89.9 78.3 97.1 112.5 80.6 94.4 97.7 98.6 93.3 94.2 92.9 83.1 79.2 69.9 86.0 .. 83.0 76.0 82.0

80.6 81.2 85.0 75.3 94.5 60.4 94.9 108.9 80.9 114.6 88.6 88.6 99.6 95.8 48.1 79.2 105.3 .. 143.7 98.4 56.2 89.0 92.1 88.9 108.1 88.2 114.9 102.6 90.5 104.5 87.8 105.9 75.3 89.4 79.7 95.2 67.4 98.9 119.1 91.3 78.7 109.3 .. 79.7 85.3 88.3 90.5 98.2 92.7 84.0 91.9 75.0 61.0 81.9 .. 80.7 74.9 78.6

a. Preliminary. b. The variability in the data are due to weaknesses in national account statistics. c. Since 1994 Nigeria’s ratios have been distorted because the official exchange rate used by the government for oil exports and oil value added is significantly overvalued.

32

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.8

General government consumption Share of GDP (%) Annual average

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 Djibouti Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeriab Rwanda São Tomé and Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

14.1 13.9 .. .. 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 21.4 19.1 12.1 19.3 11.6 45.3 14.4 12.2 17.4 10.4 12.1 12.5 34.5 20.3 28.7 8.4 15.6 14.3 16.0 27.0 .. 22.4 .. 25.5 18.5 12.5 15.2 15.7 21.8 18.3 14.5 13.3

16.8 15.2 15.2 34.5 11.0 24.1 13.2 10.8 12.8 14.7 14.9 10.0 23.4 11.5 13.8 16.8 .. 39.7 .. 13.2 13.4 13.7 9.3 8.9 10.3 18.6 14.1 .. 8.0 15.1 13.8 25.9 12.8 13.5 30.6 15.0 15.1 10.1 27.6 14.7 27.7 7.8 .. 19.7 .. 18.1 17.8 14.2 7.5 19.0 19.4 14.6 16.1 11.3 .. 15.5 16.4 16.1

15.2 12.6 13.2 30.0 9.4 28.9 13.2 17.1 9.2 15.0 11.6 5.6 15.7 8.1 24.2 6.5 23.5 21.0 52.3 12.0 16.9 12.7 10.3 6.1 9.3 16.2 20.8 .. 7.8 14.7 14.7 12.8 12.9 8.4 29.6 13.1 9.7 10.0 25.6 11.8 31.2 9.1 .. 18.8 6.3 22.2 7.8 10.9 12.9 15.8 15.8 14.8 18.1 11.3 .. 18.0 15.6 15.0

16.0 14.3 14.5 59.7 10.0 30.4 12.5 18.2 8.4 19.4 11.5 6.9 14.6 6.0 15.1 6.5 26.4 .. 69.5 18.8 16.6 13.0 10.8 5.9 10.8 15.8 18.6 .. 7.2 13.4 15.9 12.9 12.7 9.5 30.3 14.9 13.4 11.0 29.8 12.7 26.9 10.5 .. 18.4 6.5 24.6 7.9 9.7 12.9 12.9 13.6 14.0 17.1 10.1 .. 19.2 15.5 15.3

17.0 16.2 14.4 42.5 11.6 30.4 12.6 17.6 9.5 21.3 11.3 7.7 13.3 7.5 11.6 7.2 25.2 .. 63.8 22.7 10.0 13.7 10.2 3.8 14.0 15.1 19.1 .. 6.8 14.6 8.6 15.0 13.1 10.1 28.8 13.0 22.8 10.5 50.9 14.0 24.2 13.2 .. 18.1 7.6 24.1 8.5 10.2 13.7 9.5 13.9 13.0 14.1 9.7 .. 19.1 15.7 15.4

17.3 16.8 13.9 34.9 11.6 31.9 12.2 19.9 10.2 11.3 11.4 7.5 16.3 6.0 14.1 7.5 .. .. 51.5 16.8 .. 14.4 9.7 6.8 12.6 15.6 17.8 14.4 8.3 15.8 9.2 13.7 12.9 10.0 28.4 12.4 26.5 11.7 64.2 12.6 24.8 17.4 .. 18.3 8.6 17.7 9.3 10.0 13.8 12.8 14.6 12.9 14.2 10.3 .. 17.9 13.6 15.6

16.9 16.2 14.2 36.9 12.5 33.1 13.1 19.1 10.2 11.7 11.8 7.8 15.9 5.5 18.4 7.8 .. .. 44.0 19.3 .. 12.9 9.9 7.5 13.0 16.7 15.6 13.7 8.2 14.7 8.7 16.4 12.8 9.7 26.4 12.2 24.7 11.8 66.7 13.3 22.7 16.2 .. 18.4 8.4 18.6 9.6 8.4 15.2 13.0 13.4 12.6 14.8 9.5 .. 15.8 13.7 15.3

17.9 17.0 15.1 34.0 13.3 33.8 12.8 22.7 10.1 14.7 10.5 7.8 13.9 6.3 17.0 8.2 .. .. 51.9 23.8 .. 11.0 8.9 7.5 12.8 17.8 15.4 8.0 9.1 16.3 8.4 15.7 14.1 10.3 26.5 11.3 23.7 15.1 36.4 13.4 25.6 15.2 .. 19.3 10.9 18.6 11.4 9.8 14.8 13.5 16.7 12.7 15.3 9.1 .. 15.1 13.7 16.1

18.0 16.8 15.1 29.3 13.6 34.3 13.0 25.8 10.2 14.8 11.6 5.0 13.2 8.2 16.0 8.3 .. .. 53.5 22.4 .. 11.1 8.4 5.7 14.5 17.0 14.2 9.7 9.6 16.9 10.0 14.9 13.2 10.4 24.5 12.5 22.1 12.9 33.7 13.9 25.2 13.4 .. 19.7 11.9 21.0 12.8 9.7 14.5 12.7 21.1 12.8 15.5 8.7 .. 14.5 13.7 16.4

15.5 14.4 14.5 31.5 12.7 24.3 12.2 9.3 10.0 10.8 15.6 11.3 28.6 9.0 17.7 16.5 .. 27.4 .. 15.7 18.3 29.1 9.0 8.9 18.9 18.3 19.4 22.0 9.8 17.5 12.3 30.6 13.5 13.8 27.9 11.9 13.9 13.0 36.6 17.3 33.1 7.7 17.6 17.4 12.1 21.5 14.1 16.9 9.9 23.0 20.1 15.6 17.2 16.2 30.0 16.6 16.5 15.4

16.7 14.7 15.1 43.9 10.5 27.3 13.6 17.0 10.5 17.0 13.9 8.1 19.8 9.9 18.0 11.9 27.6 25.1 39.7 13.5 14.5 13.8 11.7 7.1 8.4 15.8 16.7 .. 7.9 16.6 12.7 16.6 13.0 11.0 31.0 14.6 12.9 11.5 30.3 13.2 29.0 10.2 .. 19.4 6.3 22.6 14.0 12.8 11.1 17.7 17.2 14.4 16.7 10.5 .. 17.2 16.1 15.9

17.4 16.6 14.5 35.5 12.5 32.7 12.7 21.0 10.0 14.8 11.3 7.2 14.5 6.7 15.4 7.8 25.2 .. 52.9 21.0 10.0 12.6 9.4 6.3 13.4 16.4 16.4 11.4 8.4 15.7 9.0 15.1 13.2 10.1 26.9 12.3 24.0 12.4 50.4 13.4 24.5 15.1 .. 18.8 9.5 20.0 10.3 9.6 14.4 12.3 15.9 12.8 14.8 9.4 .. 16.5 14.1 15.8

a. Preliminary. b. Since 1994 Nigeria’s ratios have been distorted because the official exchange rate used by the government for oil exports and oil value added is significantly overvalued.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

33

Table

2.9

Gross fixed capital formation Share of GDP (%) Annual average

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 Djibouti Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeriab Rwanda São Tomé and Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

22.0 18.6 17.1 .. 15.2 40.1 15.1 13.9 21.0 .. 7.0 .. 33.2 10.0 35.8 26.5 .. .. .. .. 27.5 26.7 5.6 .. 28.2 24.5 37.0 .. 15.0 24.7 15.5 26.3 25.4 7.6 30.6 28.1 21.3 16.1 16.8 11.7 38.3 16.2 42.4 29.9 14.7 40.7 .. 28.4 6.2 23.3 16.9 28.2 39.1 27.5 22.1 24.2 29.4 23.5

16.4 15.7 15.8 11.7 14.2 37.4 18.2 14.5 17.8 22.9 12.3 6.8 18.8 9.1 15.9 6.7 .. 17.4 .. 12.9 21.7 22.3 14.4 17.5 29.9 24.2 52.7 .. 17.0 23.0 23.0 20.0 30.7 22.1 33.7 8.1 14.7 14.6 15.6 13.8 24.6 10.0 15.5 17.7 .. 19.1 26.1 26.6 12.7 17.3 17.4 28.4 28.6 28.8 .. 25.3 32.5 20.3

19.0 20.4 19.6 35.5 17.0 33.5 27.2 6.8 17.5 19.8 13.5 16.9 17.9 2.1 26.7 13.3 15.3 91.6 32.4 21.1 37.3 18.4 23.1 21.0 11.3 16.7 47.1 .. 14.8 13.5 20.9 16.7 27.6 24.2 25.8 11.3 24.1 14.8 35.8 18.6 34.6 5.3 .. 17.0 18.0 22.4 13.8 16.4 16.4 16.4 20.8 23.6 27.0 21.5 .. 22.2 26.9 20.7

18.2 19.4 18.6 27.1 17.5 28.0 23.8 5.9 15.7 20.9 14.4 13.7 14.9 3.1 27.8 13.1 8.9 .. 36.0 16.9 28.0 17.8 21.0 22.1 16.8 15.5 48.6 .. 14.9 14.7 21.2 16.2 25.5 36.7 23.3 10.2 23.4 17.2 39.0 18.5 43.3 5.4 .. 16.4 16.8 18.7 15.5 13.3 19.5 17.6 14.4 25.8 27.8 25.5 .. 23.4 26.8 21.0

17.1 17.8 17.9 12.7 18.9 20.0 22.7 6.1 16.7 19.7 10.8 23.3 13.1 3.5 21.0 10.8 12.9 .. 31.9 15.9 26.1 17.4 24.0 22.0 11.3 17.4 42.2 .. 15.0 13.6 24.6 26.5 25.9 33.5 19.5 11.4 17.7 17.5 43.6 20.9 25.2 8.0 .. 15.9 18.3 19.9 17.6 17.8 20.0 18.7 13.6 24.3 23.8 23.9 .. 24.4 27.4 19.8

17.8 19.2 18.1 13.4 19.2 23.0 18.9 6.2 20.3 18.3 14.0 40.5 11.8 5.4 26.4 11.2 .. .. 28.7 17.8 30.5 17.4 26.6 17.6 15.0 19.2 40.2 4.9 18.5 14.9 31.0 14.5 23.3 25.9 23.4 12.1 22.8 18.4 35.8 19.2 40.3 6.6 .. 15.3 17.6 18.4 17.0 20.4 18.6 20.0 9.3 24.4 25.8 22.7 .. 24.6 28.1 20.3

17.7 18.5 16.6 13.3 17.7 27.8 17.8 6.4 19.8 20.9 14.8 60.5 12.2 8.9 23.3 10.1 .. .. 26.0 20.5 28.4 21.2 19.7 13.1 9.6 16.3 42.3 4.7 14.3 11.4 18.6 14.8 21.4 29.8 19.7 14.2 26.1 16.9 32.8 16.7 25.6 10.0 .. 16.1 19.4 19.8 19.1 18.5 19.3 23.0 7.1 25.4 28.4 23.0 .. 25.0 28.6 20.6

18.8 20.0 18.9 12.8 18.8 29.6 18.7 11.3 18.3 18.7 16.6 53.5 11.6 12.2 22.9 10.1 .. .. 25.4 20.5 23.9 20.3 23.0 9.9 12.6 17.4 44.8 8.8 17.9 11.8 24.2 19.5 22.8 25.9 29.8 14.2 23.8 18.4 30.4 20.7 10.1 13.8 .. 16.9 20.0 18.0 18.6 18.9 20.5 26.1 10.6 26.5 30.0 23.5 .. 25.3 29.1 21.4

18.9 19.9 19.1 9.2 18.2 30.6 19.1 13.7 18.9 20.4 17.5 24.9 10.2 12.8 24.2 10.8 .. .. 22.8 19.8 25.4 28.1 24.2 10.8 13.2 18.3 41.1 12.3 24.3 15.3 19.0 21.5 24.2 20.7 25.5 15.8 22.4 20.5 34.5 23.4 14.7 10.5 .. 17.5 22.5 17.4 18.4 18.0 22.5 26.0 12.8 27.3 30.9 23.9 .. 25.4 29.9 21.5

18.5 15.9 15.6 14.8 15.1 30.0 17.4 16.6 23.8 40.5 10.9 6.3 28.8 11.7 32.5 16.5 .. .. .. 14.3 34.6 19.7 7.8 16.1 32.0 22.7 39.9 .. 10.6 19.4 17.2 27.5 23.5 12.2 18.4 15.3 16.5 15.3 15.8 12.1 26.4 12.2 28.8 23.4 14.4 27.2 16.8 19.5 8.5 16.1 17.3 29.0 33.9 28.6 26.5 24.4 28.8 21.8

17.3 17.8 17.4 20.7 16.3 29.5 21.7 9.1 16.0 29.6 11.4 13.1 17.7 7.6 25.9 11.3 10.2 59.5 25.0 14.5 25.7 20.1 19.9 19.5 25.9 18.3 56.3 .. 12.4 17.7 22.5 18.7 28.4 25.2 22.6 8.9 19.8 14.5 41.6 16.1 30.3 7.4 15.5 16.7 15.7 21.1 21.0 16.3 16.1 14.1 19.5 24.5 28.9 20.8 .. 22.2 28.3 19.7

18.1 19.1 18.1 12.3 18.6 26.2 19.4 8.8 18.8 19.6 14.8 40.5 11.8 8.6 23.6 10.6 12.9 .. 27.0 18.9 26.9 20.9 23.5 14.7 12.3 17.7 42.1 7.7 18.0 13.4 23.5 19.4 23.5 27.2 23.6 13.5 22.5 18.4 35.4 20.2 23.2 9.8 .. 16.3 19.6 18.7 18.2 18.7 20.2 22.8 10.7 25.6 27.8 23.4 .. 24.9 28.6 20.7

a. Preliminary. b. Since 1994 Nigeria’s ratios have been distorted because the official exchange rate used by the government for oil exports and oil value added is significantly overvalued.

34

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.10

General government fixed capital formation Share of GDP (%) Annual average

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 Djibouti Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeriab Rwanda São Tomé and Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

.. .. .. .. .. 0.0 .. 12.8 4.4 .. 3.7 .. 23.2 5.1 .. 11.4 .. .. .. .. 5.3 .. .. .. .. 0.0 0.0 .. .. 17.5 .. .. 9.1 7.6 15.7 20.4 .. 12.2 .. 5.5 .. 5.3 .. 0.0 6.9 11.9 .. 20.2 .. .. 1.8 .. 11.0 .. 19.4 9.8 15.0 ..

4.0 6.5 5.7 5.1 7.4 12.7 3.9 12.5 5.5 10.3 4.7 10.0 5.0 4.0 5.6 3.6 .. 10.5 .. 4.0 3.9 7.4 7.5 9.2 27.4 9.7 23.0 .. 7.9 7.7 10.5 6.2 4.6 12.0 8.2 7.4 10.8 5.9 .. 4.1 8.2 3.9 .. 0.0 .. 5.7 10.5 7.3 6.2 6.2 3.4 9.8 8.2 14.7 .. 4.8 11.0 5.9

4.8 6.9 6.0 5.9 5.8 13.2 12.4 5.5 2.0 21.3 7.1 7.6 7.7 0.1 4.7 6.0 6.6 7.5 26.2 6.2 13.4 5.2 11.3 5.6 6.2 4.9 12.0 .. 7.9 8.8 9.5 4.9 3.1 9.8 7.7 6.4 11.3 6.8 19.8 7.0 2.9 4.9 .. 1.8 0.7 6.0 3.3 3.8 4.7 11.3 1.7 10.3 7.6 14.1 .. 4.2 11.6 6.8

4.7 6.9 6.2 12.8 6.3 13.2 14.9 5.4 2.0 6.5 6.8 9.6 5.4 1.1 6.1 4.2 .. .. 30.3 8.1 7.3 4.7 9.8 7.2 10.8 4.5 8.7 .. 6.9 10.3 9.4 6.2 3.4 11.6 11.0 6.4 10.4 6.3 26.0 8.1 1.4 2.4 .. 1.5 1.2 6.7 3.1 3.1 5.4 10.6 1.7 8.9 5.9 9.8 .. .. 12.4 6.1

4.4 6.4 5.7 6.1 7.6 12.6 12.1 5.4 2.1 12.5 7.1 10.5 3.8 0.4 7.0 2.8 .. .. 26.8 5.2 4.8 4.6 10.4 7.1 10.3 4.6 8.0 .. 6.7 10.0 8.6 17.5 3.7 10.4 6.1 6.6 9.3 6.0 26.1 5.8 13.8 6.3 .. 1.4 2.3 6.2 6.0 3.0 6.4 10.0 0.7 8.3 8.0 7.5 .. .. 12.5 5.7

5.3 7.2 5.8 6.4 7.8 10.8 8.2 3.7 2.2 10.8 7.4 8.9 4.4 0.1 10.1 1.9 .. .. 23.5 8.5 5.6 11.2 10.4 7.1 14.8 4.4 10.3 0.0 7.3 10.3 7.0 10.6 6.7 15.4 8.7 7.1 12.1 6.6 21.6 6.9 25.2 4.4 .. 1.9 2.3 8.0 5.6 2.3 5.8 11.9 1.3 .. .. 6.4 .. .. .. 6.2

4.7 6.3 5.4 7.1 6.6 11.4 7.2 4.6 2.3 13.0 7.6 10.2 5.9 1.0 8.6 3.2 .. .. 21.7 11.5 5.4 7.9 9.6 4.0 9.0 4.3 11.0 0.0 4.8 7.7 7.0 10.4 7.0 12.5 6.6 8.8 10.2 4.9 14.8 7.9 9.4 4.3 .. 1.3 3.0 7.4 7.6 1.4 5.3 11.8 1.0 .. .. 6.1 .. .. .. 5.5

4.7 6.8 6.1 7.7 6.1 11.9 7.5 8.3 2.3 9.8 2.1 12.8 5.5 2.7 6.5 2.7 .. .. 17.8 10.5 3.7 5.7 7.8 3.7 13.1 4.2 8.5 0.0 7.8 9.3 6.9 14.7 7.8 11.7 8.1 8.3 9.7 5.6 16.4 9.1 2.3 4.8 .. 1.2 3.0 5.7 7.4 3.7 4.7 11.5 1.6 .. .. 5.7 .. .. .. 5.3

4.6 6.9 6.3 4.9 5.4 11.4 8.3 10.7 2.6 8.8 2.0 8.0 4.3 2.8 7.0 2.8 .. .. 17.5 10.8 5.5 10.9 7.2 3.7 19.9 4.3 7.1 0.0 12.5 12.6 7.5 15.5 7.7 9.4 7.2 9.0 9.1 8.5 19.4 10.2 3.7 4.6 .. 1.2 5.0 7.7 7.3 5.3 5.2 9.2 2.1 .. .. 5.3 .. .. .. 5.2

3.6 .. 5.1 5.0 9.1 0.0 6.7 13.8 6.9 19.3 5.5 3.8 18.7 4.4 11.1 7.1 .. .. .. 6.9 6.7 10.4 6.3 7.4 33.3 0.8 4.6 .. 6.9 9.5 10.2 7.6 6.0 9.5 10.7 11.2 .. 12.1 .. 4.2 12.0 4.0 .. 0.0 4.3 8.0 3.5 11.2 4.4 .. 2.9 11.7 13.8 12.6 19.4 10.3 14.1 6.1

3.8 6.4 6.0 6.4 7.5 12.6 9.5 9.3 2.2 20.3 6.2 7.6 6.8 1.7 6.4 5.6 4.6 6.9 16.4 6.4 6.6 7.8 11.1 7.0 20.2 7.0 16.1 .. 6.9 9.2 10.1 4.9 3.7 11.7 8.2 5.6 8.9 7.2 25.3 5.4 9.9 3.3 .. 0.3 0.6 6.6 5.8 3.7 5.6 6.8 2.9 8.9 7.3 8.4 .. 8.8 12.1 5.4

4.7 6.7 5.8 6.4 6.7 11.6 8.7 6.5 2.3 11.0 5.2 10.1 4.8 1.4 7.8 2.7 .. .. 21.5 9.3 5.0 8.0 9.1 5.1 13.4 4.3 9.0 0.0 7.8 10.0 7.4 13.7 6.6 11.9 7.4 7.9 10.1 6.3 19.7 8.0 10.9 4.9 .. 1.4 3.1 7.0 6.8 3.1 5.5 10.9 1.3 8.3 8.0 6.2 .. .. 12.5 5.6

a. Preliminary. b. Since 1994 Nigeria’s ratios have been distorted because the official exchange rate used by the government for oil exports and oil value added is significantly overvalued.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

35

Table

2.11

Private sector fixed capital formation Share of GDP (%) Annual average

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 Djibouti Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeriab Rwanda São Tomé and Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

12.7 .. .. .. .. 34.5 .. 1.1 15.6 .. 3.2 .. 5.3 3.7 .. 13.0 .. .. .. .. 21.4 .. .. .. .. 8.2 35.6 .. .. 4.7 .. .. 15.1 0.0 11.4 5.1 .. .. .. 7.7 .. 9.5 .. 25.9 3.8 23.1 .. 8.0 .. .. 12.3 .. 22.8 .. 1.8 16.7 13.3 ..

12.6 8.6 9.5 1.7 6.0 19.7 13.6 2.7 11.9 12.6 6.7 1.3 6.4 8.9 11.6 4.9 .. 6.9 .. 8.9 17.6 14.9 6.9 8.3 8.4 10.9 29.7 .. 6.9 12.4 12.4 13.7 23.7 10.1 13.0 4.0 3.8 8.7 .. 8.8 14.8 5.7 .. 19.1 .. 12.7 15.3 18.0 6.5 7.2 14.8 16.8 18.8 12.3 .. 19.3 19.7 14.0

13.9 12.9 13.0 29.6 11.2 14.2 14.8 0.4 15.5 -1.5 6.5 6.5 7.0 2.0 19.6 9.9 8.6 84.1 6.2 14.8 23.9 13.2 11.1 14.0 5.2 8.5 37.0 .. 6.9 2.3 11.4 11.8 21.7 14.5 15.3 4.6 12.8 8.0 16.0 10.5 31.1 0.4 .. 15.2 17.3 16.4 10.3 12.5 11.3 3.5 18.9 12.7 19.0 7.2 .. 17.8 13.3 13.5

13.0 12.3 12.2 16.0 11.2 14.8 8.9 0.4 13.8 14.4 7.7 7.4 6.5 2.0 20.4 10.2 .. .. 5.6 8.9 20.8 13.1 10.7 14.0 6.0 7.9 38.9 .. 8.0 2.4 11.8 10.0 21.6 25.1 12.0 3.6 13.0 10.9 14.0 11.3 40.1 3.0 .. 13.9 15.6 12.1 12.3 10.3 13.8 5.4 11.6 16.2 20.1 13.0 .. 20.7 12.9 14.2

12.0 10.9 11.5 6.6 11.3 12.9 10.6 0.8 13.9 7.2 3.7 10.5 6.5 3.0 12.3 7.5 .. .. 5.1 10.7 21.3 12.8 12.7 14.0 1.0 7.5 36.6 .. 8.3 2.3 15.9 9.1 21.6 23.2 12.7 4.6 8.4 11.6 17.6 11.1 11.4 1.7 .. 13.8 16.0 13.7 11.4 14.8 13.3 7.2 11.1 15.0 13.5 14.1 .. 20.7 13.8 13.2

12.1 11.6 11.9 7.1 11.4 13.4 10.8 2.5 18.1 7.5 6.6 27.9 4.9 5.3 16.3 10.6 .. .. 5.2 9.3 24.9 6.2 16.7 9.5 0.2 7.6 32.5 2.0 11.2 3.5 24.0 3.9 16.4 10.5 13.2 4.8 10.7 11.8 14.2 11.9 15.1 2.2 .. 13.2 15.3 10.4 11.2 19.0 12.4 6.8 9.7 19.2 24.6 14.4 .. 21.2 23.7 14.9

12.5 12.0 11.1 6.1 11.6 12.6 10.6 1.5 17.5 7.9 7.2 49.9 4.4 8.0 13.8 6.0 .. .. 4.3 9.0 23.0 13.3 9.2 8.9 0.6 7.7 33.1 2.2 9.5 2.7 11.6 4.4 15.3 17.3 14.6 5.2 15.9 12.0 18.0 8.4 16.2 5.7 .. 13.7 16.4 12.3 11.4 17.4 13.7 9.8 8.0 18.8 19.2 16.1 .. 21.7 24.2 14.9

13.4 12.6 12.1 5.1 12.0 12.0 11.2 3.0 15.7 8.9 3.9 37.1 4.3 9.5 16.4 7.8 .. .. 7.6 10.0 20.2 13.5 14.4 6.1 1.5 7.8 35.7 4.5 10.1 1.5 17.3 4.8 14.4 14.2 21.1 5.7 14.1 12.8 14.0 11.3 7.8 9.0 .. 14.6 17.0 12.3 11.1 17.2 15.4 13.3 11.2 19.9 20.1 17.1 .. 22.1 24.7 15.6

13.3 12.2 11.8 4.3 12.1 13.2 10.8 2.7 15.7 11.6 4.1 15.3 4.2 10.0 16.6 7.1 .. .. 5.3 9.0 19.9 13.9 16.2 7.1 2.1 7.5 33.9 3.9 11.8 1.8 11.5 6.0 14.5 11.3 17.9 6.8 13.2 12.0 15.1 12.9 10.9 5.9 .. 14.9 17.5 9.7 11.0 15.9 16.9 15.4 13.4 20.8 20.7 17.9 .. 22.5 25.5 15.6

13.5 8.3 9.3 9.2 4.5 29.0 11.5 2.3 14.2 7.4 4.7 0.6 5.5 7.1 11.4 8.7 .. .. .. 9.1 27.2 8.6 3.8 8.7 10.0 10.7 34.9 .. 3.6 6.3 9.9 19.0 15.1 2.7 7.8 3.0 5.9 7.8 .. 8.4 10.1 7.3 .. 23.1 8.9 17.3 10.4 7.8 5.4 4.9 13.1 14.4 17.7 11.0 1.8 18.0 13.5 13.7

13.2 11.3 11.4 17.0 8.3 15.0 12.2 –0.3 13.8 9.3 5.0 4.0 7.5 6.3 18.5 7.3 5.9 52.6 8.6 8.1 18.8 12.3 8.6 11.8 7.7 9.8 40.6 .. 5.5 6.0 12.4 13.8 23.4 13.6 12.8 3.4 10.9 7.2 19.3 9.9 19.3 3.5 .. 16.0 15.1 13.8 15.0 11.8 10.3 5.8 17.2 15.8 19.2 11.9 .. 18.5 14.9 14.1

12.7 11.8 11.7 5.8 11.7 12.8 10.8 2.1 16.2 8.6 5.1 28.1 4.9 7.2 15.1 7.8 .. .. 5.5 9.6 21.9 11.9 13.8 9.1 1.1 7.6 34.4 3.2 10.2 2.4 16.1 5.6 16.5 15.3 15.9 5.4 12.5 12.0 15.8 11.1 12.3 4.9 .. 14.0 16.5 11.7 11.2 16.9 14.3 10.5 10.7 18.7 19.6 15.9 .. 21.6 22.4 14.8

a. Preliminary. b. Since 1994 Nigeria’s ratios have been distorted because the official exchange rate used by the government for oil exports and oil value added is significantly overvalued.

36

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.12

Gross domestic savings Share of GDP (%) Annual average

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 Djibouti Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeriab Rwanda São Tomé and Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

27.6 23.3 16.7 .. –6.3 26.7 –7.2 –0.6 21.7 .. –8.9 .. –10.1 10.1 35.7 20.4 .. .. .. .. 60.6 5.8 .. .. –1.0 18.1 –51.9 14.8 –1.4 10.8 1.1 –3.5 14.5 –8.9 38.4 14.6 31.4 4.2 –11.6 –5.0 27.1 0.9 –12.9 37.9 2.1 1.2 .. 23.2 –0.4 19.3 13.8 40.5 43.1 15.2 56.9 13.7 24.0 31.6

19.9 17.4 15.1 29.7 2.2 42.6 5.2 –5.4 20.7 –8.1 –0.6 –7.7 –3.0 9.3 23.8 11.3 .. –20.1 .. 9.6 36.9 10.7 .. 17.7 2.8 18.5 –52.9 .. 5.5 13.4 6.4 4.9 23.5 –5.8 18.2 1.2 29.4 6.2 –42.4 8.9 20.3 8.7 –12.5 23.2 .. 9.2 1.3 14.7 0.6 16.6 17.5 22.3 27.1 16.1 .. 19.3 25.5 20.7

15.3 13.3 12.0 19.3 6.6 39.8 11.6 –4.7 19.2 –15.3 5.3 5.9 –4.7 –1.0 30.3 19.7 –0.8 19.9 –32.9 13.1 39.0 11.8 .. 17.3 –10.1 10.3 –33.5 .. 7.0 8.1 10.4 4.4 24.9 10.8 13.7 2.7 19.6 –2.8 –7.0 11.9 18.7 2.5 .. 18.1 5.8 1.4 –0.8 2.8 5.6 3.9 19.0 18.2 27.1 12.0 .. 18.1 23.6 16.3

16.2 14.2 13.1 20.7 4.8 38.7 8.1 –2.5 31.2 –17.5 11.0 –0.2 –5.7 9.1 41.0 21.3 –5.5 .. –41.2 2.1 34.8 11.0 .. 17.3 –1.2 10.7 –22.4 .. 7.2 –0.6 9.5 5.0 23.3 13.7 12.5 3.7 19.1 0.0 –10.3 11.3 25.6 –10.3 .. 19.0 7.7 0.3 2.8 3.2 8.1 –1.1 16.0 21.8 31.4 16.9 .. 19.6 .. 18.3

19.1 19.2 15.4 39.5 6.0 41.7 6.5 –7.3 20.3 –14.2 7.8 5.5 1.1 4.5 57.7 17.9 –5.3 .. –34.7 0.9 28.3 8.5 .. 16.8 –8.5 9.4 –20.4 .. 7.7 3.8 12.0 13.2 23.9 11.6 14.0 3.5 33.4 1.3 –4.1 10.9 22.3 –13.3 .. 18.9 15.9 4.3 9.3 –2.2 9.2 8.3 13.3 25.1 44.2 17.3 .. 18.2 25.3 21.3

18.3 17.9 13.9 15.1 6.5 40.5 5.0 –9.0 19.0 –15.1 11.1 5.3 –0.9 3.4 53.1 19.0 .. .. –27.1 3.1 50.3 12.0 .. 15.7 –19.3 11.3 –16.3 –3.4 15.3 3.8 14.0 –1.4 26.0 8.0 17.0 4.4 31.7 2.6 –22.9 9.5 19.9 –11.5 .. 19.2 9.8 3.1 8.6 1.0 6.3 17.3 10.2 24.9 40.9 17.7 .. 19.3 24.5 20.9

17.5 16.2 13.9 25.2 3.7 38.9 4.7 –11.4 19.0 –15.7 10.3 –1.3 1.8 4.0 50.0 26.3 .. .. –33.7 2.5 48.4 12.9 .. 9.1 –12.1 12.8 –18.0 –3.3 7.7 –10.1 11.3 –4.9 25.1 11.0 17.8 5.3 25.8 0.0 –17.2 5.6 23.3 –9.3 .. 20.2 13.3 19.5 11.6 0.6 5.5 17.7 6.0 24.4 38.0 17.8 .. 19.1 24.9 20.0

20.0 19.0 15.3 19.4 6.0 38.6 3.9 –8.2 18.6 –15.8 14.4 18.5 1.3 5.0 47.4 20.6 .. .. –60.4 1.0 45.3 11.1 9.1 7.5 1.2 13.0 –12.2 –3.0 8.9 –10.7 13.2 –17.6 25.0 10.1 26.2 5.0 32.4 –0.8 –22.1 7.7 19.6 –7.4 .. 21.7 15.7 17.6 9.5 5.3 6.5 18.7 5.9 24.8 36.4 18.5 .. 19.8 25.6 21.7

21.9 22.0 16.7 24.5 5.5 38.2 4.8 –8.4 18.5 –12.2 13.2 30.5 –1.5 3.9 51.4 20.5 .. .. –62.9 0.5 46.4 10.5 11.4 6.5 –1.7 12.6 –7.7 –0.6 7.8 –9.1 10.7 –18.8 23.6 12.3 26.7 5.8 39.6 2.4 –29.0 9.8 21.4 –4.9 .. 21.7 18.7 14.1 8.5 4.5 9.1 18.2 4.8 25.6 35.7 19.0 .. 20.1 26.7 23.0

22.0 18.3 17.3 24.0 –2.4 35.3 –2.7 3.1 24.2 –1.8 –1.1 –8.1 –4.5 10.9 31.9 19.6 .. .. .. 6.9 44.3 6.5 .. 16.4 –0.9 17.9 –66.4 2.2 2.9 12.7 –0.4 3.1 20.0 –6.2 10.8 7.3 17.5 5.0 –16.2 0.1 24.1 9.1 –6.3 28.5 5.0 3.7 8.8 12.3 2.3 14.0 16.5 28.4 31.5 15.5 46.9 15.9 20.5 24.3

16.6 14.4 12.5 22.5 3.8 39.3 7.6 –5.2 20.1 –5.6 3.7 –0.5 –4.4 8.8 28.8 17.8 –5.4 13.7 –30.9 5.3 41.7 7.4 .. 15.8 1.5 15.6 –38.1 .. 4.2 3.4 7.6 7.4 24.1 1.0 12.7 2.7 24.0 –5.5 –20.0 10.1 21.7 2.9 –12.5 19.4 5.6 2.3 1.4 6.7 5.8 7.1 16.9 20.8 30.1 14.0 .. 17.0 21.2 18.0

19.4 18.8 15.0 24.7 5.5 39.6 5.0 –8.9 19.1 –14.6 11.4 11.7 0.4 4.2 51.9 20.8 –5.3 .. –43.7 1.6 43.8 11.0 10.2 11.1 –8.1 11.8 –14.9 –2.6 9.5 –4.5 12.2 –5.9 24.7 10.6 20.3 4.8 32.6 1.1 –19.1 8.7 21.3 –9.3 .. 20.3 14.7 11.7 9.5 1.8 7.3 16.0 8.1 25.0 39.0 18.1 .. 19.3 25.4 21.4

a. Preliminary. b. Since 1994 Nigeria’s ratios have been distorted because the official exchange rate used by the government for oil exports and oil value added is significantly overvalued.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

37

Table

2.13

Gross national savings Share of GDP (%) Annual average

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 Djibouti Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeriab Rwanda São Tomé and Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

27.2 23.7 18.8 .. 1.1 28.7 .. .. 5.1 .. 1.6 .. –0.4 7.9 .. .. .. .. .. .. .. .. .. .. –6.3 15.4 34.6 .. –2.4 6.6 1.9 3.9 14.0 –6.9 26.9 13.0 26.1 .. –5.5 –7.4 .. 0.5 –5.8 33.9 4.0 16.7 .. 26.4 –0.9 7.3 .. 37.1 .. .. 53.5 .. 25.0 30.2

16.0 13.4 12.1 5.5 5.8 43.3 13.4 .. 16.1 17.6 –0.4 –2.7 9.7 0.8 6.6 –4.3 .. –22.0 .. 11.9 25.4 .. .. 10.6 15.3 18.6 39.0 .. 9.2 15.4 15.1 17.6 26.3 2.1 34.8 –1.2 19.4 .. –51.1 6.0 21.7 2.6 –21.9 19.1 .. 27.4 5.9 17.8 0.6 6.7 15.7 19.8 .. .. .. .. .. 18.5

13.3 12.0 11.3 5.1 11.3 47.1 15.1 –0.2 15.0 8.4 5.9 8.7 8.3 –6.8 7.4 10.7 .. 9.7 8.3 19.7 23.9 16.4 .. 14.3 –7.8 12.8 14.3 .. 7.3 4.3 12.9 14.3 26.7 9.8 28.2 1.6 15.4 –4.0 –18.1 14.4 16.9 2.7 .. 15.2 0.4 15.5 –1.9 5.8 6.0 –3.6 16.4 20.8 .. 18.9 .. 21.8 23.4 16.1

14.0 12.7 11.2 –1.7 9.9 38.5 6.6 –0.1 28.0 8.1 12.0 2.4 2.5 1.1 11.0 11.7 .. .. 4.9 8.5 18.9 14.2 .. 14.8 –3.3 13.7 22.4 .. 9.5 –2.5 11.9 18.7 24.9 14.7 24.3 2.8 13.9 –1.3 –19.0 12.7 23.2 –5.6 .. 15.9 0.0 16.2 0.9 3.8 8.2 –6.6 16.1 20.1 .. .. .. 22.5 .. 17.7

15.7 15.6 12.6 21.4 10.9 39.1 5.6 –0.1 15.4 9.1 8.0 7.9 14.8 –1.3 28.5 8.0 .. .. 20.4 10.5 11.5 13.6 .. 14.7 –2.7 15.2 22.6 .. 9.4 2.2 16.0 24.0 25.3 15.4 27.7 2.8 27.2 –0.5 –11.4 14.6 15.7 –7.9 .. 15.8 3.4 14.5 7.5 0.4 9.6 2.9 9.6 23.3 40.6 23.0 .. 22.8 24.7 19.9

15.1 14.9 11.9 –1.4 12.5 41.7 6.9 0.4 13.5 8.0 12.3 6.6 14.8 0.3 23.3 10.1 .. .. 28.7 13.0 33.7 14.8 .. 14.3 –15.7 15.6 26.2 –21.4 17.2 2.4 12.9 7.6 27.6 6.4 27.7 4.4 25.4 0.2 –29.6 14.5 15.5 –3.1 .. 15.4 2.8 13.9 7.5 3.1 6.9 12.1 9.3 26.7 38.1 22.7 .. 23.8 23.8 19.6

14.0 12.4 11.8 10.4 7.3 30.0 6.8 1.3 15.0 9.4 7.6 –3.0 11.6 5.3 23.0 16.3 .. .. 26.3 12.6 29.2 18.2 .. 8.8 –8.0 16.3 25.6 –11.1 8.3 –12.0 8.5 15.6 26.5 11.1 27.7 4.7 15.1 –2.3 –20.7 10.8 15.2 5.2 .. 17.2 8.1 24.7 10.8 4.1 6.7 13.7 5.7 26.2 35.9 22.5 .. 23.2 24.2 18.5

16.4 15.1 13.3 7.6 9.4 38.8 7.7 6.5 16.3 9.2 14.7 5.1 7.3 10.3 22.8 11.9 .. .. –6.4 13.7 28.2 18.6 21.5 6.5 5.1 17.1 29.3 –10.1 13.0 –5.1 14.5 –3.8 26.5 11.3 41.6 5.5 21.5 –3.8 –24.4 14.2 14.8 6.2 .. 18.4 10.0 19.9 9.5 7.3 7.3 15.2 4.8 26.4 34.7 22.9 .. 24.1 25.0 19.8

18.3 17.8 15.0 13.4 8.9 41.8 10.5 7.9 16.9 14.2 13.2 18.3 7.6 6.9 26.6 13.6 .. .. –20.8 14.3 29.5 14.3 22.8 4.6 9.8 16.9 35.8 28.7 13.5 –5.3 11.0 –5.4 24.0 12.5 39.7 6.3 27.1 –0.6 –33.0 16.7 18.5 5.6 .. 19.0 16.5 19.0 8.0 6.5 10.4 10.0 3.1 26.8 34.3 23.1 .. 24.2 26.1 20.9

20.7 18.1 18.3 19.9 2.1 33.7 .. .. 19.3 21.8 5.6 –3.3 15.0 5.9 18.0 8.6 .. .. .. 8.8 23.5 .. .. 8.7 –0.3 15.8 32.9 .. 2.1 11.1 3.5 17.1 19.7 –3.8 18.5 5.3 13.4 .. –17.6 –4.2 .. 7.2 3.2 24.3 6.5 20.2 18.1 13.3 2.6 2.2 17.3 24.6 .. .. 40.5 .. 20.9 22.7

13.9 11.8 10.3 12.1 7.3 41.3 14.6 1.4 14.9 21.2 3.9 3.5 6.6 1.1 5.0 6.2 .. 6.0 14.2 12.2 26.6 16.2 .. 11.6 5.5 16.1 29.4 .. 4.9 2.5 14.4 14.0 26.5 4.0 27.3 1.0 17.0 –9.2 –28.9 10.1 21.5 0.1 –21.9 16.6 –0.8 19.9 2.9 8.2 8.0 –1.2 16.0 18.2 .. .. .. 21.9 20.7 16.9

15.9 15.2 12.9 10.3 9.8 38.3 7.5 3.2 15.4 10.0 11.2 7.0 11.2 4.3 24.8 12.0 .. .. 9.6 12.8 26.4 15.9 22.2 9.8 –2.3 16.2 27.9 –3.5 12.3 –3.6 12.6 7.6 26.0 11.4 32.9 4.8 23.3 –1.4 –23.8 14.2 15.9 1.2 .. 17.2 8.2 18.4 8.7 4.3 8.2 10.8 6.5 25.9 36.7 22.8 .. 23.6 24.8 19.8

a. Preliminary. b. Since 1994 Nigeria’s ratios have been distorted because the official exchange rate used by the government for oil exports and oil value added is significantly overvalued.

38

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.14

Resource balance (exports minus imports) Share of GDP (%) Annual average

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 Djibouti Equatorial Guinea Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mozambique Namibia Niger Nigeriab Rwanda São Tomé and Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

3.1 0.8 –5.1 .. –21.5 –13.4 –22.3 –14.5 0.8 .. –15.9 –11.9 –43.2 0.1 –0.1 –6.2 .. .. .. .. 33.1 –20.9 –0.7 .. –29.2 –6.4 –89.0 –0.1 –16.4 –14.0 –14.4 –29.8 –10.9 –16.5 7.8 –13.5 10.2 –11.9 –28.4 –16.7 –11.2 –15.4 –55.3 8.0 –12.6 –39.4 .. –5.3 –6.6 –4.0 –3.2 4.7 4.0 –12.4 34.8 –10.5 –5.4 3.6

1.7 –0.7 –3.3 18.0 –12.0 5.3 –13.0 –19.9 2.9 –31.0 –12.9 –14.4 –21.8 0.3 7.9 4.6 .. –37.4 .. –3.3 15.2 –11.7 –9.0 0.2 –27.1 –5.6 –105.6 .. –11.4 –9.6 –16.6 –15.1 –7.2 –27.9 –15.5 –6.9 14.6 –8.5 –58.0 –4.9 –4.3 –1.3 –28.0 5.5 .. –12.5 –24.8 –11.9 –12.1 –0.7 0.1 –3.4 –1.5 –12.7 .. –6.0 –7.0 0.1

–3.7 –7.0 –7.5 –16.3 –10.4 6.3 –15.6 –11.4 1.7 –35.1 –8.2 –11.1 –22.6 –3.1 3.7 6.4 –16.1 –71.7 –65.3 –8.0 1.7 –6.6 –12.9 –3.7 –21.4 –6.3 –80.6 .. –7.8 –5.3 –10.5 –12.3 –2.7 –13.5 –12.0 –8.6 –4.5 –17.6 –42.8 –6.7 –15.9 –2.8 .. 1.1 –12.2 –21.0 –14.7 –13.6 –10.8 –12.5 –1.7 –2.8 0.1 –9.5 .. –4.1 –3.4 –3.2

–2.7 –6.3 –6.8 –6.4 –12.7 10.7 –15.7 –8.4 –0.2 –38.4 –3.4 –13.9 –20.7 6.0 13.2 8.2 –14.4 .. –77.2 –14.8 6.8 –6.8 –17.5 –4.8 –18.0 –4.9 –71.0 .. –7.7 –15.3 –11.7 –11.2 –2.2 –22.9 –10.8 –6.5 –4.2 –17.3 –49.3 –7.2 –17.6 –15.7 .. 2.6 –9.1 –18.4 –12.7 –10.1 –12.0 –18.7 1.6 –1.4 3.5 –8.6 .. –3.8 –2.2 –2.1

1.6 0.7 –3.2 26.8 –12.9 21.7 –16.2 –13.5 3.6 –33.9 –3.1 –17.8 –12.0 1.0 36.7 7.1 –18.2 .. –66.6 –15.0 2.2 –8.9 –18.4 –5.1 –19.8 –8.0 –62.7 .. –7.3 –9.7 –12.6 –13.3 –1.9 –21.9 –5.5 –7.9 15.7 –16.2 –47.7 –10.0 –2.9 –21.3 .. 3.0 –2.4 –15.6 –8.3 –20.0 –11.9 –10.4 –0.3 3.5 20.4 –6.6 .. –6.1 –3.5 2.4

0.2 –1.9 –4.9 1.7 –12.7 17.5 –13.9 –15.2 –1.3 –33.4 –2.9 –35.2 –12.6 –2.0 26.6 7.8 .. .. –55.8 –14.7 19.8 –5.4 –19.6 –1.9 –34.3 –7.9 –56.5 –8.4 –3.2 –11.1 –17.0 –16.0 2.7 –17.9 –6.4 –7.7 8.9 –15.8 –58.7 –9.7 –20.4 –18.1 .. 3.9 –7.8 –15.4 –8.4 –19.4 –12.1 –2.8 0.8 3.3 15.0 –5.0 .. –5.3 –3.6 1.4

–0.7 –2.9 –3.5 12.0 –13.9 11.1 –13.1 –17.8 –0.8 –36.6 –4.5 –60.7 –10.4 –4.9 26.7 16.2 .. .. –59.7 –18.0 20.0 –8.3 –12.3 –4.0 –21.7 –3.5 –60.4 –8.1 –6.6 –21.4 –7.3 –19.7 3.8 –18.8 –2.0 –8.9 –0.2 –16.9 –50.0 –11.2 –2.3 –19.3 .. 4.2 –6.2 –0.3 –7.5 –18.0 –14.7 –5.3 –1.1 1.8 9.6 –5.2 .. –5.9 –3.7 0.3

0.6 –1.9 –4.8 6.6 –12.8 8.9 –14.8 –19.5 0.4 –34.5 –2.2 –35.0 –10.3 –7.2 24.5 10.4 .. .. –85.8 –19.4 21.4 –9.2 –13.9 –2.3 –11.4 –4.4 –57.0 –11.8 –9.0 –22.5 –10.9 –37.1 2.1 –15.8 –3.6 –9.2 8.6 –19.3 –52.5 –13.0 9.6 –21.1 .. 4.7 –4.3 –0.3 –9.1 –13.6 –14.1 –7.4 –4.7 1.3 6.3 –5.0 .. –5.5 –3.5 1.0

2.5 1.3 –3.5 15.3 –12.7 7.5 –14.3 –22.0 –0.4 –32.6 –4.4 5.6 –11.6 –8.9 27.2 9.7 .. .. –85.7 –19.4 21.0 –17.6 –13.9 –4.3 –14.9 –5.6 –48.8 –13.0 –16.5 –24.4 –8.3 –40.3 –0.6 –8.3 1.2 –10.0 17.2 –18.1 –63.5 –13.6 6.7 –15.4 .. 4.2 –3.9 –3.3 –9.9 –13.5 –13.9 –7.7 –8.0 1.4 4.8 –4.9 .. –5.3 –3.2 2.4

–0.1 –3.1 –4.4 9.1 –17.5 5.3 –20.2 –13.5 0.4 –42.3 –12.1 –13.5 –33.3 –0.8 –0.5 3.2 .. –28.6 .. –7.4 9.7 –13.2 –3.1 0.2 –32.9 –4.9 –106.3 2.9 –7.7 –6.7 –17.6 –24.4 –3.5 –18.4 –7.6 –8.0 1.1 –10.3 –32.0 –12.0 –2.3 –3.1 –35.1 5.1 –9.4 –23.5 –12.3 –7.2 –6.2 –2.1 –0.8 –3.1 1.5 –13.2 20.4 –8.5 –6.1 –1.0

1990–99

2000–04

–1.0 –3.8 –5.3 1.8 –12.5 9.8 –14.1 –14.4 2.5 –35.2 –7.7 –13.6 –22.2 1.2 2.9 6.5 –15.7 –45.8 –55.8 –9.2 16.0 –12.6 –12.4 –3.7 –24.5 –2.7 –94.4 .. –8.2 –14.3 –14.9 –11.3 –4.3 –24.2 –10.0 –6.2 4.1 –19.9 –61.7 –5.9 –8.6 –4.5 –28.0 2.8 –10.2 –19.1 –19.6 –9.6 –11.7 –7.0 –2.6 –0.9 1.3 –6.7 .. –5.2 –4.3 –0.8

0.8 –0.9 –4.0 12.5 –13.0 13.4 –14.5 –17.6 0.3 –34.2 –3.4 –28.6 –11.4 –4.4 28.3 10.3 –18.2 .. –70.7 –17.3 16.9 –9.9 –15.6 –3.5 –20.4 –5.9 –57.1 –10.3 –8.5 –17.8 –11.2 –25.3 1.2 –16.5 –3.3 –8.7 10.0 –17.3 –54.5 –11.5 –1.9 –19.0 .. 4.0 –4.9 –7.0 –8.7 –16.9 –13.3 –6.7 –2.6 2.3 11.2 –5.3 .. –5.6 –3.5 1.5

a. Preliminary. b. Since 1994 Nigeria’s ratios have been distorted because the official exchange rate used by the government for oil exports and oil value added is significantly overvalued.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

39

Table

2.15

Exports of goods and services, nominal Current prices ($ millions) Annual average 1980

SUB–SAHARAN AFRICA 79,589 excluding South Africa 51,112 31,308 excl. S. Africa & Nigeria Angola .. Benin 222 Botswana 563 Burkina Faso 173 Burundi 81 Cameroon 1,880 Cape Verde 19 Central African Republic 201 Chad 175 Comoros 11 Congo, Dem. Rep. 2,372 Congo, Rep. 1,024 Côte d’Ivoire 3,561 Djibouti .. Equatorial Guinea .. Eritrea .. Ethiopia .. Gabon 2,770 Gambia, The 103 Ghana 376 Guinea .. Guinea-Bissau 14 Kenya 2,144 Lesotho 86 Liberia 613 Madagascar 539 Malawi 307 Mali 263 Mauritania 261 Mauritius 539 Mozambique 383 Namibia 1,712 Niger 617 Nigeria 18,859 Rwanda 168 São Tomé and Principe 10 Senegal 803 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 41,644 Algeria 14,541 Egypt, Arab Rep. 6,992 Libya 23,523 Morocco 3,273 Tunisia 3,518 ALL AFRICA 119,851

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

77,334 50,175 37,841 3,993 264 2,087 352 89 2,251 43 220 234 36 2,759 1,502 3,421 .. 42 .. 672 2,740 190 993 870 24 2,207 104 .. 512 447 415 465 1,529 201 1,220 372 12,366 145 8 1,450 230 146 90 27,149 .. 658 538 545 312 1,180 2,009 42,750 14,546 8,647 .. 6,830 5,353 120,832

90,678 56,228 45,451 3,666 399 2,537 362 71 2,306 109 178 323 26 1,852 1,487 5,038 244 464 111 1,038 2,119 213 2,532 770 30 2,843 239 .. 805 574 644 399 2,653 519 1,562 369 10,776 111 12 1,419 370 109 .. 34,451 607 1,059 1,144 471 635 865 2,632 52,125 10,880 13,754 .. 9,970 8,529 143,447

93,010 59,268 46,437 5,311 385 2,743 287 61 2,241 113 117 282 29 1,109 1,702 5,067 250 .. 66 918 1,964 199 2,473 759 56 2,687 216 .. 909 498 680 370 2,716 586 1,563 321 12,832 114 16 1,466 422 84 .. 33,742 828 1,006 1,166 455 735 701 2,767 55,873 13,259 13,500 .. 10,624 8,852 149,272

110,599 73,564 51,149 8,182 342 3,222 237 55 2,343 146 126 234 31 964 2,586 4,211 247 .. 96 984 1,825 202 2,429 735 68 2,743 256 .. 1,190 446 649 379 2,801 744 1,558 320 22,416 151 15 1,310 464 115 .. 37,034 1,891 1,133 1,307 409 663 682 2,660 69,479 22,579 15,940 .. 10,409 8,566 180,196

107,305 71,811 51,042 6,847 360 2,835 260 45 2,104 167 121 251 35 875 2,232 4,357 .. .. 133 980 2,619 150 2,401 822 57 2,968 319 126 1,317 480 876 379 2,978 1,004 1,446 329 20,774 157 16 1,402 490 129 .. 35,495 1,711 1,156 1,537 421 690 980 2,357 70,139 21,701 17,072 .. 10,405 8,863 177,254

110,298 74,034 55,002 8,406 380 2,504 272 39 2,169 194 126 253 39 1,174 2,434 5,695 .. .. 128 983 2,957 157 2,625 785 61 3,281 390 111 704 471 1,066 382 2,757 1,188 1,548 330 19,044 132 20 1,527 555 153 .. 36,266 1,996 1,131 1,667 498 697 875 2,012 69,781 20,578 16,332 .. 11,152 9,682 180,144

140,988 94,618 65,625 9,709 487 3,232 357 55 2,762 253 138 675 58 1,482 2,766 6,280 .. .. 103 1,139 3,781 158 3,066 807 77 3,590 520 133 1,264 480 1,153 359 3,099 1,353 2,300 438 28,997 139 22 2,137 648 197 .. 46,372 2,613 1,641 1,881 595 778 891 1,855 76,628 21,804 16,009 .. 13,886 11,711 219,111

177,280 120,252 80,879 13,722 539 3,570 416 59 3,061 295 150 2,274 60 2,023 3,669 7,445 .. .. 122 1,369 4,420 184 3,349 824 98 4,207 763 171 1,425 511 1,341 451 3,356 1,828 2,644 491 39,372 189 25 2,165 663 240 .. 57,032 3,822 2,357 2,016 691 933 1,059 1,694 83,995 25,103 14,997 .. 16,128 13,279 264,541

62,624 36,479 28,593 2,613 214 999 184 111 2,240 37 181 153 22 2,016 1,092 3,142 .. 32 .. 607 1,964 108 554 660 15 1,805 66 519 414 295 255 387 764 215 1,139 420 7,725 173 12 924 123 187 119 26,088 875 394 478 464 371 1,060 1,530 32,437 12,221 6,654 17,320 3,790 3,312 95,467

85,417 53,877 41,344 4,223 327 2,350 287 89 2,179 79 185 254 40 1,595 1,393 4,129 222 160 132 727 2,621 195 1,684 740 32 2,594 187 .. 673 465 514 448 2,191 373 1,543 325 12,563 107 11 1,376 298 155 90 31,523 682 886 913 441 500 1,083 2,469 49,017 12,508 12,493 .. 8,399 7,161 135,057

129,294 86,856 60,739 9,373 422 3,073 308 51 2,488 211 132 738 44 1,304 2,737 5,598 247 .. 116 1,091 3,120 170 2,774 794 72 3,358 450 135 1,180 478 1,017 390 2,998 1,223 1,899 382 26,120 154 20 1,708 564 167 .. 42,440 2,407 1,484 1,681 523 752 897 2,116 74,004 22,353 16,070 .. 12,396 10,420 204,249

a. Preliminary.

40

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.16

Imports of goods and services, nominal Current prices ($ millions) Annual average 1980

SUB–SAHARAN AFRICA 71,605 excluding South Africa 49,598 37,269 excl. S. Africa & Nigeria Angola .. Benin 524 Botswana 705 Burkina Faso 603 Burundi 214 Cameroon 1,829 Cape Verde 100 Central African Republic 327 Chad 298 Comoros 64 Congo, Dem. Rep. 2,354 Congo, Rep. 1,026 Côte d’Ivoire 4,190 Djibouti .. Equatorial Guinea .. Eritrea .. Ethiopia .. Gabon 1,354 Gambia, The 153 Ghana 407 Guinea .. Guinea-Bissau 46 Kenya 2,608 Lesotho 470 Liberia 614 Madagascar 1,202 Malawi 480 Mali 520 Mauritania 473 Mauritius 665 Mozambique 965 Namibia 1,542 Niger 957 Nigeria 12,324 Rwanda 307 São Tomé and Principe 24 Senegal 1,302 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 35,735 Algeria 12,847 Egypt, Arab Rep. 9,822 Libya 11,167 Morocco 5,247 Tunisia 3,987 ALL AFRICA 105,915

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

72,339 51,408 43,207 2,147 486 1,888 758 314 1,931 148 411 485 93 2,731 1,282 2,927 .. 92 .. 1,069 1,837 227 1,522 864 90 2,691 753 .. 864 629 817 619 1,701 888 1,584 545 8,203 364 42 1,728 246 154 346 21,016 .. 768 1,595 738 834 1,203 2,002 48,320 15,472 14,109 .. 8,374 6,220 120,427

102,796 69,879 57,643 4,714 642 2,229 798 174 2,159 298 264 516 75 2,045 1,416 4,224 327 791 597 1,655 2,041 240 3,492 903 74 3,737 956 .. 1,095 667 915 538 2,767 1,041 1,972 547 12,236 462 30 1,733 467 128 .. 32,917 1,955 1,342 2,375 687 1,344 1,268 2,737 58,282 10,850 21,812 .. 11,425 9,194 161,198

101,854 71,567 57,263 5,705 688 2,204 729 129 2,268 337 153 495 75 827 1,391 4,041 327 .. 597 1,882 1,669 228 3,826 924 96 3,312 864 .. 1,197 769 982 495 2,808 1,500 1,927 452 14,304 448 40 1,806 531 188 .. 30,287 1,802 1,260 2,263 615 1,455 1,287 2,670 59,057 11,571 21,144 .. 11,959 9,317 160,957

105,173 72,066 56,271 5,736 634 2,080 658 151 1,981 326 155 480 55 920 1,404 3,471 347 .. 518 1,961 1,718 239 3,347 894 111 3,757 794 .. 1,474 616 954 523 2,888 1,571 1,746 462 15,794 445 38 1,746 482 250 .. 33,107 2,189 1,349 2,064 674 1,366 1,018 2,680 61,124 11,709 22,457 .. 12,458 9,257 166,337

106,736 75,860 59,350 6,697 662 1,930 650 146 2,228 351 149 850 63 971 1,490 3,529 .. .. 507 1,938 1,761 173 3,441 880 125 4,002 750 171 1,463 672 1,322 554 2,854 1,665 1,652 479 16,511 427 44 1,844 616 276 .. 30,889 2,756 1,350 2,333 678 1,378 1,080 2,249 62,285 13,177 21,963 .. 12,220 9,583 169,047

112,819 81,220 62,065 7,110 772 1,900 693 151 2,254 419 174 1,457 65 1,447 1,629 3,837 .. .. 505 2,073 1,962 188 3,380 913 105 3,741 812 156 993 886 1,311 601 2,584 1,958 1,610 523 19,151 425 46 2,085 572 336 .. 31,615 2,924 1,134 2,403 763 1,554 1,072 2,341 65,481 14,998 21,010 .. 13,362 10,494 178,347

138,198 99,694 75,690 8,801 944 2,542 977 171 2,712 529 164 1,611 91 1,891 1,891 4,848 .. .. 744 2,430 2,484 192 4,113 892 104 4,257 1,127 184 1,756 878 1,630 856 2,988 2,108 2,461 688 23,997 464 54 3,110 581 408 .. 38,525 3,367 1,648 2,816 833 1,662 1,212 2,225 73,361 17,742 20,264 .. 16,426 12,636 211,993

164,342 116,289 89,320 10,728 1,055 2,893 1,104 205 3,128 604 207 2,034 103 2,610 2,488 5,939 .. .. 917 2,934 2,902 255 4,550 986 138 5,114 1,430 235 2,146 974 1,747 1,069 3,393 2,320 2,573 795 26,965 521 61 3,223 616 407 .. 48,071 4,650 2,441 3,138 969 1,879 1,478 2,068 80,245 21,472 18,706 .. 18,932 14,251 245,485

62,943 41,489 34,079 1,895 447 842 579 254 2,219 104 292 305 67 2,107 1,093 2,906 .. 61 .. 1,096 1,586 137 709 658 67 2,154 503 491 668 384 536 576 809 773 1,284 583 7,362 354 28 1,283 123 225 403 21,441 1,853 515 1,060 542 619 1,148 1,598 36,910 13,875 10,787 10,722 5,136 3,834 99,277

88,497 60,580 49,338 4,019 579 1,896 659 234 1,926 237 282 469 93 1,537 1,309 3,406 302 270 482 1,351 1,797 242 2,509 867 91 2,942 977 .. 942 716 882 571 2,334 1,001 1,844 448 11,214 405 41 1,664 344 191 346 27,961 1,750 1,116 1,977 586 1,042 1,313 2,661 50,712 11,907 16,635 .. 9,979 7,840 139,313

125,453 89,026 68,539 7,814 813 2,269 816 165 2,461 446 170 1,286 75 1,568 1,780 4,325 347 .. 638 2,267 2,165 209 3,766 913 117 4,174 983 187 1,566 805 1,393 721 2,941 1,925 2,008 589 20,484 456 49 2,401 573 335 .. 36,442 3,177 1,584 2,551 784 1,568 1,172 2,312 68,499 15,820 20,880 .. 14,680 11,244 194,242

a. Preliminary.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

41

Table

2.17

Exports of goods and services, real

Constant prices (2000 $ millions)

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

Average annual growth (%)

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

66,392 46,987 24,776 3,618 391 691 226 10 1,054 31 .. 159 9 667 1,118 3,048 .. .. .. .. 1,118 112 853 .. 22 1,479 58 .. 976 315 175 338 732 436 1,096 257 21,726 171 .. 520 .. 199 .. 19,504 764 424 .. 499 .. 812 638 28,647 10,759 6,893 .. 2,848 3,205 96,405

72,535 49,929 33,884 4,804 247 1,993 253 18 1,870 42 .. 214 28 1,224 2,024 4,084 .. .. .. 579 1,647 182 1,005 501 17 2,374 83 .. 756 354 266 412 1,739 237 954 214 16,042 210 9 807 252 144 .. 22,613 334 778 685 414 229 559 1,011 46,965 16,228 11,050 .. 6,337 5,248 119,419

105,566 71,807 46,903 8,223 351 2,509 297 30 2,184 93 .. 259 28 669 3,032 4,203 .. .. 111 704 2,027 191 2,139 691 33 2,482 178 .. 893 574 559 363 2,726 572 1,504 291 24,883 116 10 1,203 360 96 .. 33,766 462 1,058 1,200 432 566 759 2,377 61,588 19,562 14,282 .. 9,495 7,625 167,789

105,105 70,917 49,120 8,499 344 2,680 262 41 2,466 96 .. 254 32 1,000 2,553 4,337 .. .. 67 761 1,893 184 2,409 713 55 2,712 204 .. 1,031 479 657 377 2,859 564 1,571 261 21,797 138 14 1,364 378 95 .. 34,192 845 1,006 1,120 426 715 797 2,502 65,859 20,735 15,584 .. 10,196 7,985 171,093

110,601 73,566 51,151 8,182 342 3,222 237 55 2,343 146 .. 234 31 964 2,586 4,211 .. .. 96 984 1,825 202 2,429 735 68 2,743 256 .. 1,190 446 649 379 2,801 744 1,558 320 22,416 151 15 1,310 464 115 .. 37,034 1,891 1,133 1,307 409 663 682 2,660 69,829 22,560 16,175 .. 10,452 8,597 180,508

112,092 74,403 52,877 7,951 359 3,063 244 69 2,387 167 .. 225 27 983 2,635 4,152 .. .. 131 1,032 1,857 160 2,430 791 71 2,878 339 .. 1,304 491 811 365 3,101 1,127 1,525 298 21,536 264 22 1,424 503 128 .. 37,687 1,736 1,318 1,500 460 757 880 2,521 72,299 21,951 16,707 .. 11,529 9,641 184,300

112,871 74,981 55,871 9,753 359 2,736 273 66 2,363 182 .. 211 28 1,062 2,917 4,372 .. .. 127 1,172 1,915 183 2,389 781 71 3,134 430 .. 706 499 1,067 338 3,394 1,310 1,739 286 19,138 279 26 1,470 533 128 .. 37,888 1,790 1,345 1,559 476 844 939 2,210 72,627 22,983 15,406 .. 12,276 9,434 185,426

120,689 82,709 57,458 9,443 376 2,603 300 116 2,453 208 .. 481 24 1,065 2,800 4,263 .. .. 86 1,351 1,976 200 2,453 739 76 3,340 395 .. 993 480 907 306 3,632 1,485 2,139 282 25,252 274 28 1,472 613 232 .. 37,991 2,135 1,264 1,649 508 911 1,034 1,942 76,518 24,959 17,226 .. 12,083 9,050 197,256

127,834 88,916 62,879 10,632 378 2,595 307 89 2,495 226 .. 1,301 32 1,279 3,027 4,997 .. .. 80 1,842 2,041 211 2,547 765 79 4,002 447 .. 1,008 465 905 332 3,570 1,840 1,994 287 26,045 304 34 1,526 638 261 .. 38,937 2,434 1,278 1,534 523 968 1,164 1,981 84,537 25,808 21,981 .. 12,647 9,520 212,036

0.0 –0.3 0.0 1.6 –4.5 13.8 –1.7 3.8 6.5 0.3 –1.3 7.4 11.0 11.2 4.9 1.2 .. .. .. 3.6 1.8 0.5 1.4 .. –3.9 3.3 4.7 .. –1.8 2.1 4.7 3.5 10.1 –8.9 1.4 –3.2 –1.5 4.2 .. 3.7 .. –1.1 .. 1.6 –5.0 7.5 .. 0.4 1.4 –3.0 4.3 4.9 4.2 4.4 .. 7.6 5.1 0.9

5.0 4.8 4.7 7.2 2.0 4.0 –0.1 5.2 2.7 13.9 .. 2.8 –2.2 –2.5 5.6 1.5 .. .. –1.4 5.9 2.3 –1.1 10.5 4.4 14.2 1.2 10.7 .. 3.3 4.8 10.1 –1.5 5.8 10.5 4.3 3.1 5.1 –6.4 1.5 6.2 4.9 –7.8 .. 5.6 8.8 3.5 7.8 1.4 16.0 3.5 10.8 3.7 2.9 3.3 .. 5.0 5.1 4.6

3.7 4.9 5.0 7.2 2.5 –5.8 7.5 16.0 1.5 11.5 –8.4 52.1 –0.2 6.7 3.8 3.8 .. .. –7.4 14.6 2.9 3.2 1.0 0.1 3.7 9.5 13.5 .. –5.9 0.6 8.1 –4.3 6.6 23.2 8.7 –2.7 4.7 15.5 19.6 3.4 8.7 25.0 .. 1.1 7.4 2.0 4.2 6.1 9.9 13.1 –8.2 4.3 2.7 6.0 .. 2.8 6.9 3.9

a. Preliminary.

42

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.18

Imports of goods and services, real

Constant prices (2000 $ millions)

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

Average annual growth (%)

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

31,471 18,973 9,032 3,008 797 715 517 51 795 122 110 318 83 566 1,031 3,345 .. .. .. .. 1,662 303 1,888 .. 79 1,913 520 .. 1,827 803 392 518 829 1,232 1,107 1,017 25,771 177 .. 1,040 .. 381 .. 19,907 1,742 580 .. 708 .. 1,977 618 48,971 16,346 19,678 .. 4,291 4,456 66,055

63,935 45,474 35,618 2,461 484 1,729 650 66 1,261 145 99,316 535 84 1,063 1,044 2,313 .. .. .. 1,116 1,729 218 1,541 780 84 1,854 761 .. 1,027 743 683 625 1,793 851 1,151 569 9,462 210 41 1,295 209 176 .. 18,795 1,083 770 1,829 803 687 1,180 984 50,959 14,285 18,158 .. 7,787 6,357 112,065

101,955 67,641 55,134 4,871 560 2,159 816 93 1,658 254 .. 413 69 492 1,135 4,398 .. .. 596 1,679 2,009 216 3,673 834 64 3,742 951 .. 1,139 688 869 531 2,691 1,146 1,817 468 12,527 532 30 1,548 496 178 .. 34,297 2,739 1,313 2,047 776 1,283 1,253 2,414 57,810 11,799 21,571 .. 11,284 8,196 159,877

102,576 71,152 56,769 5,410 615 2,172 752 110 1,706 288 149 447 75 785 1,344 4,316 .. .. 607 1,967 1,679 211 4,082 864 82 3,687 846 .. 1,209 787 938 483 2,853 1,610 1,842 378 14,392 496 38 1,702 489 158 .. 31,429 2,064 1,260 2,062 710 1,397 1,274 2,470 57,821 10,943 21,914 .. 11,560 8,444 160,531

105,176 72,071 56,278 5,736 634 2,080 658 151 1,981 326 155 480 55 920 1,404 3,471 .. .. 518 1,961 1,718 239 3,347 894 111 3,757 794 .. 1,474 616 954 523 2,888 1,571 1,746 462 15,794 445 38 1,746 482 250 .. 33,107 2,189 1,349 2,064 674 1,366 1,018 2,680 61,124 11,709 22,457 .. 12,458 9,257 166,339

111,306 78,138 60,712 6,833 660 2,064 718 175 2,213 351 135 762 65 1,012 1,493 3,624 .. .. 520 1,952 1,757 184 3,606 921 107 4,489 850 .. 1,647 704 1,238 612 2,955 1,246 1,918 504 17,425 447 63 1,965 632 380 .. 33,179 2,182 1,480 2,049 681 1,408 1,295 2,434 63,329 13,722 21,597 .. 12,743 9,835 174,748

120,963 86,122 66,628 7,885 668 2,048 762 204 2,416 393 72 3,550 63 1,387 1,854 3,554 .. .. 502 2,148 1,806 219 3,449 1,004 92 4,132 989 .. 1,235 907 1,110 685 3,108 1,756 1,983 526 19,492 422 62 2,094 548 512 .. 34,859 2,346 1,477 2,129 716 1,623 1,219 2,556 67,352 14,970 22,571 .. 13,601 10,432 188,518

129,714 91,787 70,018 10,188 670 2,012 1,000 289 2,353 435 110 1,147 73 1,767 2,178 3,984 .. .. 508 2,515 1,865 242 3,713 881 84 4,240 966 .. 1,638 806 1,260 754 3,233 1,985 2,096 533 21,761 445 67 2,180 549 553 .. 37,943 2,470 1,418 2,472 736 1,640 1,264 2,256 70,614 15,771 23,501 .. 14,184 11,100 200,632

143,743 100,476 78,220 11,166 678 2,067 1,035 309 2,450 448 101 1,163 74 2,233 3,531 4,486 .. .. 434 3,028 1,936 260 4,134 912 91 4,889 1,009 .. 2,045 800 1,225 828 3,230 2,067 1,868 558 22,257 464 83 2,310 593 487 .. 43,278 4,643 1,437 2,527 758 1,723 1,401 2,248 74,372 16,501 24,613 .. 15,073 11,805 218,660

6.6 8.4 14.9 –1.8 –7.4 8.2 2.6 1.8 4.9 –1.9 96.5 11.5 0.3 13.1 –4.7 –2.2 .. .. .. 4.6 –2.1 –7.5 –0.5 .. 1.1 0.9 3.4 .. –7.7 –1.5 6.8 0.7 9.5 –4.4 0.5 –6.7 –15.4 4.3 .. 1.7 .. –5.3 .. –1.0 –7.5 2.6 .. 3.0 4.7 –1.7 2.7 –2.0 –4.0 –2.2 .. 2.4 0.6 4.2

6.1 5.2 5.6 9.3 1.8 3.7 1.7 1.8 4.1 8.2 .. –2.8 –0.9 –6.5 2.5 8.9 .. .. 9.9 5.3 0.9 –1.6 11.8 1.0 –2.5 10.3 2.1 .. 3.3 –0.3 3.1 –0.8 5.2 5.5 6.0 –2.1 3.9 6.1 –2.3 2.9 11.1 –1.7 .. 7.9 9.6 4.7 0.1 1.0 10.7 2.6 9.8 2.5 –1.4 3.0 .. 5.7 3.5 4.8

8.1 8.6 8.3 18.9 1.5 –0.4 13.2 21.4 5.0 8.9 –10.0 24.4 7.4 26.2 24.9 6.3 .. .. –3.7 11.9 3.0 4.5 4.6 0.0 –6.3 4.8 6.3 .. 6.7 6.8 5.3 12.0 3.2 10.7 2.3 4.4 9.5 0.8 17.9 6.9 2.8 18.7 .. 6.9 17.7 0.8 6.1 3.2 6.4 6.3 –4.2 5.1 8.6 2.7 .. 5.0 6.3 7.1

a. Preliminary.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

43

Table

2.19

Gross domestic product growth Annual growth (%) Annual average

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

4.2 2.0 1.1 .. 6.8 12.0 0.8 1.0 –2.0 .. –4.5 –6.0 .. 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 .. .. .. –2.2 4.2 9.0 .. –3.3 –4.2 4.8 .. 6.6 1.5 12.4 .. 14.6 .. 3.0 14.4 5.3 0.8 10.0 .. 3.6 7.4 4.6

1.1 2.1 0.6 –0.3 3.2 6.8 –1.5 3.5 –6.1 0.7 –2.1 –4.2 5.1 –6.6 1.0 –1.1 –1.9 3.3 .. 2.1 5.2 3.6 3.3 4.4 6.1 4.2 6.4 –51.0 3.1 5.7 –1.9 –1.8 5.8 1.0 2.5 –1.3 8.2 –2.4 1.8 3.9 7.0 3.3 .. –0.3 –5.5 8.6 7.0 –0.2 6.5 –0.5 7.0 4.1 0.8 5.7 .. 4.0 8.0 2.1

2.3 3.5 4.0 6.8 4.5 6.0 1.0 4.8 5.0 7.4 4.7 7.0 0.9 –1.6 3.7 4.8 0.5 21.9 1.8 –4.3 2.1 3.5 4.7 4.8 –28.1 3.3 –4.6 29.7 3.9 3.9 6.0 3.5 6.0 12.6 3.3 10.4 1.9 8.9 2.5 4.5 8.4 1.7 .. 0.5 6.4 3.3 3.7 –2.3 4.9 –1.9 2.9 6.0 5.1 6.2 .. 7.7 4.8 3.7

2.6 2.8 3.3 3.2 4.7 5.4 6.7 –1.0 4.4 8.6 3.6 –0.7 2.9 –4.4 –3.0 1.6 2.2 41.4 0.0 5.4 –6.2 6.4 4.4 4.6 7.8 2.3 0.2 22.9 4.7 3.0 6.7 7.8 5.8 7.5 3.4 –0.6 1.1 7.6 2.5 6.2 1.9 –2.1 .. 2.4 6.3 3.5 3.5 2.5 8.1 2.2 –3.6 4.2 3.2 6.0 .. 0.0 6.1 3.2

3.3 2.7 2.4 3.0 5.8 7.6 1.6 –0.9 4.2 6.6 2.3 –0.4 1.9 –6.9 8.2 –3.3 0.7 1.5 –13.1 6.0 2.0 5.5 3.7 1.9 7.5 0.6 1.3 25.7 4.8 1.6 3.2 6.7 4.0 1.9 3.5 –1.4 4.2 6.0 3.0 3.0 4.8 6.7 .. 4.2 6.5 2.0 5.1 –0.8 5.6 3.6 –7.9 3.7 2.4 5.1 .. 0.9 4.7 3.4

3.5 3.9 4.1 3.1 5.0 5.2 5.9 2.1 4.5 3.8 1.5 10.4 2.3 –2.1 3.8 0.1 .. 1.5 9.2 8.8 2.5 5.8 4.2 4.0 0.2 4.4 3.2 2.9 6.0 –5.0 12.1 3.6 5.6 13.1 2.4 7.1 3.1 6.7 4.0 4.7 –2.2 .. .. 2.7 6.1 1.8 6.2 –0.2 4.9 4.9 –2.7 4.1 3.6 3.3 .. 6.5 5.4 3.7

3.4 3.2 3.7 14.4 4.5 5.0 4.4 4.4 4.0 4.6 –0.8 8.4 2.3 3.5 4.6 –1.6 .. 17.6 0.7 1.9 0.0 –3.2 4.5 4.2 –7.1 0.4 3.5 3.7 –12.7 2.9 4.2 2.3 2.9 8.2 6.7 3.0 1.5 9.4 4.1 1.1 1.3 28.2 .. 3.7 6.0 2.9 7.2 4.1 6.5 3.3 –4.4 3.6 3.4 3.0 .. 4.4 6.0 3.5

4.1 4.8 3.3 3.4 3.9 6.7 6.5 –1.2 4.0 6.2 –7.6 14.9 2.1 5.7 0.8 –1.7 .. 14.7 3.9 –3.7 2.6 6.9 4.7 1.2 0.6 2.8 3.1 –31.3 9.8 6.1 7.4 6.4 2.9 7.9 3.5 5.3 10.7 0.9 4.0 6.5 –6.3 9.8 .. 3.0 6.0 2.4 7.1 2.7 4.4 5.1 –10.4 4.4 3.9 4.5 .. 3.4 6.5 4.2

5.1 5.5 5.4 11.1 3.1 4.9 3.9 4.8 3.7 4.4 1.3 29.5 1.9 6.8 3.6 1.6 .. 10.0 2.0 13.4 1.4 5.1 5.0 2.7 2.2 4.3 3.1 2.6 5.3 7.1 2.2 6.9 4.4 7.5 6.0 0.0 6.0 4.0 3.8 6.2 –2.0 9.6 .. 4.5 6.0 2.1 6.7 3.0 5.6 5.4 –4.2 5.0 4.6 5.5 .. 3.6 6.0 5.1

1.8 2.2 2.6 3.5 2.7 10.9 3.9 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 4.1 –3.3 0.8 2.4 0.5 1.9 5.9 –0.9 1.1 –0.4 0.8 2.5 .. 3.2 3.1 0.5 .. 1.4 2.4 6.5 .. 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 4.7 4.1 –3.2 1.3 5.9 1.8 2.3 1.2 –5.0 0.9 3.5 –1.7 20.7 7.9 4.0 3.2 2.7 4.3 4.5 1.4 2.2 4.2 0.2 1.7 3.8 3.9 4.5 5.3 6.3 4.0 2.4 2.4 –1.6 1.7 3.0 4.5 –3.7 .. 2.0 5.3 3.3 2.7 3.6 7.2 0.2 2.7 3.3 1.7 4.4 .. 2.4 4.6 2.7

4.0 4.3 4.0 8.1 4.1 5.5 5.2 2.3 4.1 4.9 –2.0 14.7 2.2 3.7 3.1 –0.6 .. 11.8 3.6 3.7 1.6 3.2 4.6 3.0 –1.5 2.7 3.2 –8.7 0.9 3.0 6.3 4.7 3.7 8.9 4.7 3.9 5.4 5.2 4.0 4.4 –2.4 11.2 .. 3.4 6.0 2.4 6.9 2.6 5.4 4.6 –5.9 4.2 3.8 4.0 .. 4.4 6.0 4.1

a. Preliminary.

44

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.20

Gross domestic product per capita growth Annual growth (%) Annual average

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

1.1 –1.1 –2.1 .. 3.5 8.2 –1.3 –1.9 –4.8 .. –7.0 –8.0 .. –0.9 14.0 –15.1 .. .. .. .. –0.5 2.9 –2.0 .. –18.8 1.7 –5.2 –7.2 –2.0 –2.6 –6.5 0.9 .. .. .. –5.2 1.2 5.5 .. –5.8 –5.4 2.9 .. 4.2 –1.7 9.0 .. 11.1 .. –0.3 10.5 2.5 –2.5 7.5 .. 1.1 4.6 1.5

–1.8 –0.9 –2.3 –3.0 –0.3 3.9 –4.4 1.0 –8.8 –1.6 –4.4 –7.0 2.4 –9.7 –2.2 –4.4 –6.4 1.4 .. –1.6 1.8 –0.3 0.5 0.9 3.1 0.8 5.0 –50.5 0.2 1.7 –4.3 –4.0 5.0 –0.3 –1.8 –4.3 5.1 –2.1 –0.4 0.9 6.1 1.6 .. –2.3 –7.5 5.2 3.5 –3.1 2.7 –3.4 3.8 1.8 –1.7 3.5 .. 1.9 5.4 –0.6

–0.2 0.9 1.3 4.4 1.6 4.2 –1.7 3.9 2.8 5.0 2.6 3.7 –1.2 –3.5 0.3 2.1 –3.0 19.0 –1.1 –6.7 –0.6 0.1 2.4 2.6 –30.0 0.9 –5.8 19.0 0.8 1.0 3.2 0.7 4.9 10.0 0.4 6.7 –0.6 –1.7 0.7 1.9 6.3 0.1 .. –1.8 4.0 0.0 1.4 –5.8 1.8 –4.1 1.6 4.4 3.6 4.3 .. 6.4 3.5 1.3

0.1 0.3 0.8 0.9 1.7 3.9 3.8 –2.1 2.2 6.1 1.7 –3.8 0.7 –6.3 –6.1 –0.8 –1.2 38.1 –3.3 4.0 –8.4 3.0 2.1 2.5 4.9 0.0 –0.8 14.2 1.6 0.2 3.8 4.8 4.5 5.2 0.8 –3.9 –1.3 –1.8 0.6 3.5 –0.1 –4.3 .. –0.1 4.0 0.6 1.3 –1.1 4.8 0.0 –4.7 2.6 1.8 4.1 .. –1.2 4.7 0.9

0.8 0.3 –0.1 0.5 2.7 6.5 –1.3 –2.5 2.1 4.1 0.6 –3.7 –0.3 –8.9 4.8 –5.4 –2.3 –0.9 –16.3 2.9 –0.2 2.2 1.4 –0.2 4.5 –1.6 0.6 19.3 1.7 –1.1 0.3 3.6 2.9 –0.2 1.2 –4.7 1.8 –1.0 0.9 0.5 3.9 3.5 .. 1.6 4.3 –0.4 2.9 –4.0 2.4 1.5 –8.8 2.2 1.0 3.4 .. –0.2 3.5 1.1

1.0 1.4 1.6 0.4 1.8 4.6 2.7 –0.2 2.4 1.4 0.0 6.7 0.2 –4.5 0.6 –1.8 .. –0.9 4.8 5.5 0.5 2.6 1.9 1.8 –2.7 2.1 2.7 –0.2 3.0 –7.3 8.9 0.6 4.4 10.7 0.5 3.5 0.7 2.2 1.8 2.2 –2.3 .. .. 0.9 4.0 –0.4 4.1 –3.1 1.6 2.9 –3.5 2.2 1.1 1.5 .. 5.1 3.7 1.3

1.0 0.7 1.1 11.2 1.2 4.7 1.1 1.6 2.0 2.2 –2.1 4.6 0.2 0.8 1.4 –3.2 .. 14.9 –3.7 –2.2 –1.7 –6.1 2.2 2.0 –9.8 –1.7 3.3 2.2 –15.1 0.5 1.1 –0.7 2.1 6.0 5.0 –0.5 –0.7 6.5 1.8 –1.3 –1.7 22.7 .. 2.5 4.0 1.0 5.1 1.3 3.0 1.5 –5.1 1.6 2.5 1.2 .. 2.0 0.5 1.1

1.8 2.4 0.9 0.5 0.6 6.7 3.1 –4.3 2.1 3.7 –8.8 10.9 0.0 2.7 –2.2 –3.2 .. 12.1 –0.7 –5.1 1.0 3.9 2.5 –1.0 –2.4 0.6 3.1 –31.6 6.8 3.8 4.3 3.2 1.9 5.8 2.1 1.8 8.3 –0.8 1.6 4.0 –5.3 4.9 .. 1.9 4.0 0.8 5.0 0.0 0.9 3.4 –10.9 3.1 5.7 1.1 .. 4.3 5.0 2.2

2.9 3.1 2.9 7.9 –0.2 5.0 0.6 1.3 1.8 2.0 0.0 25.2 –0.2 3.7 0.6 0.1 .. 7.5 –2.3 10.1 –0.2 2.2 2.8 0.5 –0.8 2.0 3.3 2.0 2.4 4.8 –0.8 3.7 3.4 5.4 4.7 –3.3 3.7 2.5 1.4 3.7 –3.0 5.2 .. 5.2 4.0 0.8 4.7 0.4 2.0 3.7 –4.7 2.5 3.6 2.2 .. 0.7 5.1 2.7

–0.8 –0.9 –0.5 –0.3 –0.2 8.0 1.1 1.0 1.1 4.2 –1.6 2.7 0.1 –1.2 3.5 –4.4 –6.8 –1.6 .. –0.9 –1.3 0.3 –1.1 1.6 0.4 0.5 1.3 –6.2 –2.4 –2.4 –1.8 –0.2 4.9 –0.6 –2.3 –3.0 –1.9 –0.3 –0.6 –0.4 1.2 –1.2 .. –0.3 0.6 3.6 0.4 –0.9 –0.6 –1.8 1.4 1.7 –0.3 3.4 .. 1.6 1.0 0.0

–0.6 –0.2 –0.3 –1.7 1.1 2.8 0.9 –2.8 –2.1 2.8 –1.1 –0.8 –0.6 –8.2 –2.3 –0.3 –3.8 17.4 6.4 –0.1 –0.2 –0.4 1.6 0.9 –1.0 –0.6 2.7 –3.2 –1.3 2.0 0.9 1.2 4.2 2.8 0.8 –1.4 0.4 1.2 –0.1 0.4 3.3 –3.5 .. –0.8 2.1 0.6 0.2 –0.4 3.5 –2.1 0.6 1.5 –0.4 2.6 .. 1.1 3.3 0.1

1.5 1.6 1.3 4.1 1.2 5.5 1.2 –0.8 2.1 2.7 –2.1 8.7 0.0 –1.2 1.0 –2.7 –2.3 6.5 –3.7 2.3 –0.1 1.0 2.2 0.6 –2.3 0.3 2.6 –1.7 –0.2 0.2 2.7 2.1 2.9 5.5 2.7 –0.6 2.7 1.9 1.5 1.8 –1.7 5.1 .. 2.4 4.1 0.3 4.4 –1.1 2.0 2.6 –6.6 2.3 2.8 1.9 .. 2.4 3.6 1.7

a. Preliminary.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

45

Table

2.21

Gross national income per capita Dollarsa Annual average

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004b

1980–89

1990–99

2000–04

650 519 434 .. 390 960 310 220 620 .. 340 230 .. 600 820 1,120 .. .. .. .. 4,790 370 410 .. 150 460 490 530 440 190 250 450 .. .. .. 390 810 250 .. 500 2,080 380 100 2,510 450 960 .. 410 .. 600 930 1,276 2,060 500 10,460 970 1,360 769

577 372 393 730 330 2,450 350 210 960 940 460 260 550 220 880 730 .. 350 .. 170 4,780 310 380 430 220 380 640 .. 230 180 260 540 2,300 170 1,740 280 280 360 420 660 5,020 200 140 3,390 550 1,200 200 380 320 420 850 1,375 2,420 760 .. 1,030 1,430 732

514 317 325 460 340 3,100 260 140 610 1,240 290 210 420 110 530 740 750 1,070 220 100 3,820 320 370 460 140 440 680 130 240 200 240 440 3,760 200 2,020 190 280 270 280 470 7,320 160 .. 3,280 300 1,460 250 290 280 310 570 1,534 1,560 1,240 .. 1,290 2,050 697

498 309 315 390 340 2,860 260 130 600 1,290 280 200 410 100 450 710 760 830 210 100 3,180 320 380 440 150 440 650 120 240 180 230 440 3,710 220 1,890 170 280 270 290 460 7,290 150 .. 3,150 310 1,470 270 280 280 310 500 1,578 1,540 1,350 .. 1,240 2,080 689

482 300 304 430 340 2,870 250 110 580 1,280 270 180 400 80 520 650 780 650 180 110 3,090 320 330 400 160 430 630 130 240 150 220 460 3,690 210 1,870 160 280 250 300 450 7,320 140 .. 3,050 310 1,370 280 270 260 290 460 1,641 1,570 1,460 .. 1,220 2,080 685

473 306 303 470 330 3,000 240 100 560 1,240 260 190 400 80 570 600 780 710 180 110 3,080 310 290 370 140 420 590 130 250 140 220 410 3,850 210 1,770 160 320 230 310 440 7,220 150 .. 2,830 340 1,380 290 240 240 300 580 1,674 1,660 1,480 .. 1,230 2,060 681

464 313 311 610 330 2,700 250 100 570 1,210 250 200 400 90 620 570 790 .. 170 100 2,990 270 270 360 130 400 540 140 220 140 220 450 3,850 210 1,740 160 320 210 320 420 6,800 160 .. 2,630 390 1,190 300 240 230 310 890 1,634 1,710 1,390 4,760 1,220 1,990 666

510 349 343 690 380 3,500 290 90 650 1,400 260 230 460 100 640 630 870 .. 170 90 3,340 270 310 380 140 430 590 100 280 150 270 460 4,100 230 1,990 180 380 200 350 510 7,430 190 .. 2,850 440 1,310 310 260 230 350 920 1,670 1,930 1,310 4,350 1,370 2,260 709

600 397 390 930 450 4,360 350 90 810 1,720 310 250 560 110 760 760 950 .. 190 110 4,080 280 380 410 160 480 730 120 290 160 330 530 4,640 270 2,380 210 430 210 390 630 8,190 210 .. 3,630 530 1,660 320 310 250 400 620 1,784 2,270 1,250 4,400 1,570 2,650 803

576 412 386 740 319 1,202 284 231 883 910 345 217 383 347 990 811 .. 343 .. 156 4,403 304 370 415 178 381 522 399 320 168 204 458 1,390 251 1,466 289 496 289 485 474 2,764 280 127 2,797 528 934 .. 306 285 432 858 1,305 2,462 631 7,826 806 1,264 716

534 322 335 452 329 2,876 287 166 749 1,122 365 236 512 154 658 712 790 546 208 131 4,232 333 379 460 202 348 724 120 232 187 253 480 3,199 167 1,991 213 270 282 355 560 6,420 173 140 3,471 326 1,404 205 324 245 346 659 1,380 1,755 956 .. 1,170 1,808 692

506 333 330 626 366 3,286 276 98 634 1,370 270 210 444 92 622 642 834 680 178 104 3,316 290 316 384 146 432 616 124 256 148 252 462 4,026 226 1,950 174 346 220 334 490 7,392 170 .. 2,998 402 1,382 300 264 242 330 694 1,681 1,828 1,378 4,503 1,322 2,208 709

a. Calculated by the World Bank Atlas method. b. Preliminary.

46

Part I. Basic indicators and national accounts

NATIONAL ACCOUNTS

Table

2.22

Total consumption per capita

Dollars Annual average

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

1980

1990

1998

1999

2000

2001

2002

2003

2004 a

1980–89

1990–99

2000–04

491 389 334 .. 403 742 314 224 603 458 373 .. 406 462 609 971 .. .. .. .. 2,420 348 374 .. 141 365 507 435 452 179 254 456 1,020 319 1,354 345 643 214 555 526 1,667 337 105 1,818 373 949 .. 314 99 518 788 824 1,281 443 5,040 843 1,041 563

469 326 352 685 349 1,523 347 210 759 1,030 499 309 622 224 859 757 .. 450 .. 213 3,926 303 359 373 233 299 591 .. 242 172 255 478 1,725 194 1,376 289 222 342 702 651 4,196 145 155 2,444 .. 1,041 160 351 241 328 686 1,094 1,789 650 .. 870 1,124 590

440 285 298 394 321 1,736 232 148 494 1,446 272 213 436 131 421 642 774 853 299 110 2,320 298 353 367 176 431 676 .. 228 148 211 434 2,686 202 1,624 184 231 299 325 419 6,270 153 .. 2,624 332 1,339 254 308 272 303 398 1,303 1,166 1,152 .. 1,078 1,623 596

424 276 283 361 325 1,774 236 130 515 1,558 252 194 445 88 417 603 815 .. 284 101 2,280 302 383 346 171 384 628 .. 219 159 206 416 2,780 196 1,598 171 245 258 378 418 5,762 167 .. 2,514 307 1,347 247 294 234 302 401 1,259 1,088 1,122 .. 1,030 1,672 573

408 264 270 399 295 1,746 215 117 540 1,347 233 159 373 82 396 512 815 .. 240 101 2,779 293 237 307 171 375 579 .. 221 146 183 355 2,861 186 1,549 147 238 223 345 378 5,891 159 .. 2,450 315 1,271 237 253 221 277 509 1,261 976 1,214 .. 979 1,550 559

402 280 282 534 299 1,747 229 109 513 1,373 224 190 402 88 369 501 .. .. 230 96 1,659 271 243 298 169 369 494 178 230 140 188 409 2,796 186 1,383 152 273 198 411 390 6,101 194 .. 2,137 359 1,144 243 238 212 276 911 1,265 1,084 1,171 .. 981 1,563 553

423 317 326 554 353 1,870 254 103 570 1,509 241 231 430 101 413 488 .. .. 218 88 1,942 231 275 331 156 359 459 180 237 176 240 417 2,818 195 1,310 163 281 201 430 435 6,398 211 .. 1,950 382 881 239 258 213 274 2,267 1,251 1,145 1,065 .. 1,066 1,694 569

488 326 329 741 422 2,684 324 91 706 1,910 260 238 544 99 497 620 .. .. 296 96 2,468 227 322 374 155 400 664 139 283 158 297 545 3,215 226 1,662 199 313 194 487 623 6,823 210 .. 2,840 424 1,421 252 285 218 311 579 1,300 1,280 965 .. 1,276 2,013 633

566 357 361 953 468 3,136 355 99 802 2,148 285 317 637 114 543 688 .. .. 357 115 2,844 243 357 384 178 420 819 153 222 165 332 611 3,736 267 2,083 213 338 202 482 616 6,609 213 .. 3,694 491 1,932 275 329 223 386 345 1,330 1,491 844 .. 1,408 2,215 706

445 321 309 586 313 780 277 215 691 550 352 221 394 288 681 681 .. .. .. 140 2,501 276 340 324 177 301 475 446 301 150 206 433 1,078 277 1,474 259 385 272 579 480 2,170 250 136 2,094 488 812 204 270 231 397 700 944 1,697 540 5,044 667 961 545

452 285 300 460 317 1,714 252 171 618 1,189 344 235 519 154 592 637 828 463 251 121 2,713 315 348 388 205 312 690 .. 231 180 230 442 2,413 173 1,666 202 221 283 462 498 5,142 181 155 2,782 319 1,297 189 303 217 330 531 1,107 1,212 832 .. 1,001 1,440 576

458 309 314 636 367 2,236 276 104 626 1,657 249 227 477 97 444 562 815 .. 268 99 2,339 253 287 339 166 385 603 162 239 157 248 467 3,085 212 1,597 175 289 203 431 488 6,364 197 .. 2,614 394 1,330 249 273 217 305 922 1,282 1,195 1,052 .. 1,142 1,807 604

a. Preliminary.

NATIONAL ACCOUNTS

Part I. Basic indicators and national accounts

47

Table

3.1

Millennium Development Goal 1: eradicate extreme poverty and hunger Share of population below national poverty linea (poverty headcount ratio) Survey year

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

Percentage

International poverty line Share of population below PPP $1 a daya Survey year

Percentage

Poverty gap ratio at $1 a daya (incidence x depth of poverty) Survey year

Percentage

.. 1999 .. 2003 1990 2001 .. .. 1996 .. .. .. .. .. .. 1994 2000 .. 1998 1998–99 1994 .. 1997 .. .. 1999 1998 1998 2000 .. 1996–97 .. 1993 1992 1999 .. 1992 .. 2003 .. .. .. .. 2000–01 .. 2003 1998 1996

.. 29.0 .. 46.4 36.4 40.2 .. .. 64.0 .. .. .. .. .. .. 53.0 44.2 .. 57.6 39.5 40.0 .. 52.0 .. .. 71.3 65.3 63.8 46.3 .. 69.4 .. 63.0 34.1 60.3 .. 33.4 .. 70.2 .. .. .. .. 35.7 .. 37.7 72.9 34.9

.. 2003 1993 2003 1998 2001 .. 1993 .. .. .. .. 2002 .. .. .. 2000 .. 1998 1998–99 .. .. 1997 1995 .. 2001 1998 1994 2000 .. 1996–97 1993 1995 2003 2000 .. 1995 .. .. .. 2000 .. .. 2000–01 .. .. 2002–03 1995

.. 30.9 23.5 27.2 54.6 17.1 .. 66.6 .. .. .. .. 14.8 .. .. .. 23.0 .. 59.3 44.8 .. .. 22.8 36.4 .. 61.0 41.7 72.3 25.9 .. 37.8 34.9 60.6 70.8 51.7 .. 22.3 .. .. .. 10.7 .. .. 57.8 .. .. 75.8 56.1

.. 2003 1993 2003 1998 2001 .. 1993 .. .. .. .. 2002 .. .. .. 2000 .. 1998 1998–99 .. .. 1997 1995 .. 2001 1998 1994 2000 .. 1996–97 1993 1995 2003 2000 .. 1995 .. .. .. 2000 .. .. 2000–01 .. .. 2002–03 1995

.. 8.2 7.7 7.3 22.7 4.1 .. 38.1 .. .. .. .. 4.1 .. .. .. 4.8 .. 28.8 17.3 .. .. 5.9 19.0 .. 27.9 14.8 37.4 7.6 .. 12.0 14.0 34.0 34.5 20.0 .. 5.7 .. .. .. 1.7 .. .. 20.7 .. .. 36.4 24.2

1995 1999–2000 .. 1998–99 1995

22.6 16.7 .. 19.0 7.6

1995 1999–2000 .. 1998–99 2000

2.0 3.1 .. 2.0 2.0

1995 1999–2000 .. 1998–99 2000

0.5 0.5 .. 0.5 0.5

a. Data are based on expenditure shares, except for Namibia and Swaziland, where data are based on income shares b. Data are for most recent year available during the period specified.

48

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Share of poorest quintile in national consumption or income a Survey year

Share of population below minimum dietary energy consumption (%)

Prevalence of child malnutrition, underweight (% of children under age 5)

Percentage

1989–94b

2000–04b

2003

.. 2003 1993 2003 1998 2001 .. 1993 .. .. .. .. 2002 .. .. .. 2000 .. 1998 1998–99 1994 1993 1997 1995 .. 2001 1997 1994 2000 .. 1996–97 1993 1995 2003 .. .. 1995 .. .. .. 2000 .. 1994 2000–01 .. 1999 2002–03 1995

.. 7.4 2.2 6.9 5.1 5.6 .. 2.0 .. .. .. .. 5.2 .. .. .. 9.1 .. 4.8 5.6 6.4 5.2 6.0 1.5 .. 4.9 4.9 4.6 6.2 .. 6.5 1.4 2.6 5.0 .. .. 6.4 .. .. .. 3.5 .. 2.7 7.3 .. 5.9 6.1 4.6

20.0 .. .. 32.7 .. 15.1 13.5 .. .. 18.5 .. .. 23.8 22.9 .. 41.0 47.7 .. .. 27.3 26.8 .. 22.5 21.4 .. 45.2 27.6 .. 47.6 .. .. 26.2 42.6 39.1 29.4 .. 22.2 .. 28.7 .. .. 33.9 .. 28.9 .. 23.0 25.2 15.5

30.5 22.9 12.5 37.7 45.1 18.1 .. 24.3 36.7 25.4 31.0 .. 17.2 .. 18.6 39.6 47.2 11.9 17.2 22.1 32.7 25.0 19.9 18.0 26.5 41.9 21.9 33.2 31.8 .. 23.7 24.0 40.1 28.7 24.3 12.9 22.7 .. 27.2 25.8 .. 40.7 10.3 .. .. 22.9 23.0 ..

38 14 30 17 67 25 .. 45 33 62 72 34 14 26 .. 73 46 5 27 12 24 37 31 12 49 38 34 28 10 6 45 23 32 9 36 12 23 9 50 .. .. 27 19 44 25 19 47 45

1995 1999–2000 .. 1998–99 2000

7.0 8.6 .. 6.5 6.0

9.2 9.9 .. 9.5 ..

10.4 8.6 .. 10.2 4.0

5 3 3 6 3

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

49

Table

3.2

Millennium Development Goal 2: achieve universal primary education

Net primary enrollment ratio (% of relevant age group)

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

Primary completion rate (% of relevant age group)

Share of cohort reaching grade 5 (% of grade 1 students)

Youth literacy rate (% ages 15–24)

1991

2004a

1991

2004a

1991

2003

1990

2004

50 41 83 29 53 74 91 52 35 57 54 79 45 29 91 16 22 85 48 54 27 38 .. 71 .. 64 48 21 35 91 43 .. 22 .. 66 .. 43 .. 43 9 90 40 75 49 64 .. .. ..

.. 83 82 40 57 .. 92 .. 57 55 .. .. 56 33 59 48 46 77 73 58 64 45 76 86 66 89 95 46 74 95 71 74 39 88 73 .. 66 100 .. .. 89 43 77 86 79 98 80 82

35 21 79 21 46 56 .. 27 18 .. 46 54 43 27 .. .. .. .. .. 63 17 .. .. 58 .. 33 31 11 33 102 26 .. 17 .. 47 .. .. .. .. .. 75 40 62 61 35 .. .. 91

.. 49 92 29 33 63 95 .. 29 50 .. 66 .. 29 .. 44 51 .. .. 65 48 .. 89 71 .. 45 58 44 43 100 29 .. 25 75 37 75 45 106 .. .. .. 49 .. 57 66 57 66 ..

.. 55 84 70 62 .. .. 23 51 .. 55 60 73 87 .. .. 18 .. .. 80 59 .. 77 66 .. 21 64 70 75 97 34 62 62 89 60 .. 85 93 .. .. .. 94 77 81 48 36 .. 76

.. 69 .. 76 63 .. 91 .. 46 63 .. .. .. .. .. 80 .. .. .. .. 82 .. 75 63 .. 57 .. 79 82 99 .. .. 74 35 46 .. 78 .. .. .. .. 92 .. 88 76 .. .. ..

.. 40 83 .. 52 81 81 52 48 57 69 93 53 73 93 61 43 .. 42 82 44 .. 90 87 57 72 63 .. 46 91 49 87 17 74 73 .. 40 .. .. .. 88 65 85 83 63 70 81 94

72 45 94 31 73 .. .. 59 38 .. 70 .. 61 .. 95 .. .. .. .. 71 47 .. 80 .. .. 70 76 24 61 95 .. 92 37 .. 78 .. 49 99 48 .. 94 77 88 78 74 77 69 ..

89 84 96 56 94

97 94 .. 87 97

79 .. .. 46 74

94 95 .. 75 97

95 .. .. 75 86

96 .. .. .. ..

77 61 91 55 84

90 .. .. 70 94

a. Provisional.

50

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Table

3.3

Millennium Development Goal 3: promote gender equality and empower women

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

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

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

Women in national parliaments (% of total seats)

Share of women in wage employment in the nonagricultural sector (%)

1991

2004a

1990

2004

1990

2006

2000

2003

.. 49 109 62 82 83 .. 60 41 71 .. 85 65 70 .. .. 68 .. 64 79 46 .. 94 124 .. 98 81 59 67 102 72 108 57 79 96 .. 69 .. 67 .. 104 78 98 97 59 82 .. 92

.. 71 .. 76 82 87 100 .. 58 84 .. .. .. 75 .. 73 73 .. .. 91 72 .. 94 104 .. .. 98 74 96 103 82 .. 71 84 100 .. 90 .. .. .. .. 88 .. .. 73 97 93 ..

.. 44 110 .. 77 88 87 60 65 78 72 95 62 78 92 68 66 .. 68 86 43 .. 93 126 51 86 68 .. 65 100 48 104 37 82 86 .. 60 .. .. .. 100 71 101 87 60 76 88 95

75 56 104 65 92 .. .. 67 42 .. 81 .. 74 .. 100 .. .. .. .. 86 57 .. 101 .. .. 94 86 52 82 102 .. 103 44 .. 98 .. 70 101 63 .. 101 84 103 94 76 86 91 ..

15 3 5 .. .. 14 12 4 .. 0 5 14 6 0 13 .. .. 13 8 .. .. 20 1 .. .. 7 10 .. .. 7 16 7 5 .. 17 12 13 16 .. 4 3 .. 4 .. 5 12 7 11

15 7 11 12 31 9 .. 11 7 .. 12 9 9 .. .. 22 21 9 13 19 .. 14 7 12 13 7 14 10 .. 17 35 27 12 6 49 .. 19 .. 15 8 33 15 11 30 7 24 13 16

.. .. 45 15 .. .. .. .. .. .. .. .. 21 .. .. 34 .. .. .. .. .. .. 34 .. .. .. 12 .. .. 39 .. 49 .. .. .. .. .. .. .. .. .. 20 32 .. .. .. .. 20

.. .. 47 15 .. .. .. .. .. .. .. .. 20 .. .. 35 .. .. .. .. .. .. 39 .. .. .. 13 .. .. 35b .. 51 .. .. .. .. .. .. .. .. .. 19 31 .. .. .. .. 22

83 81 .. 70 86

99 .. .. 88 ..

79 72 84 62 81

92 .. .. 75 96

2 4 .. 0 4

6 2 5 11 23

12 19 .. 26 25

16 22 .. 26 25

a. Provisional. b. Data are for 2004.

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

51

Table

3.4

Millennium Development Goal 4: reduce child mortality

Under-five mortality rate (per 1,000)

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

52

Infant mortality rate (per 1,000 live births)

Child immunization rate, measles (% of children ages 12–23 months)

1990

2004

1990

2004

1990

2004

260 185 58 210 190 139 60 168 203 120 205 110 157 163 170 147 204 92 154 122 240 253 97 104 235 168 241 250 133 23 235 86 320 230 173 118 148 19 302 225 60 120 110 161 152 160 180 80

260 152 116 192 190 149 36 193 200 70 205 108 194 126 204 82 166 91 122 112 155 203 120 112 235 123 175 219 125 15 152 63 259 197 203 118 137 14 283 225 67 91 156 126 140 138 182 129

154 111 45 113 114 85 45 102 117 88 129 83 103 122 103 88 131 60 103 75 145 153 64 74 157 103 146 140 85 20 158 60 191 120 103 75 90 17 175 133 45 74 78 102 88 93 101 53

154 90 84 97 114 87 27 115 117 52 129 81 117 101 122 52 110 60 89 68 101 126 79 80 157 76 110 121 78 14 104 47 152 101 118 75 78 12 165 133 54 63 108 78 78 80 102 79

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

64 85 90 78 75 64 69 35 56 73 64 65 49 60 51 84 71 55 90 83 73 80 73 70 42 59 80 75 64 98 77 70 74 35 84 91 57 99 64 40 81 59 70 94 70 91 84 80

69 104 41 89 52

40 36 20 43 25

54 76 35 69 41

35 26 18 38 21

83 86 89 80 93

81 97 99 95 95

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Table

3.5

Millennium Development Goal 5: improve maternal health Births attended by skilled health staff (% of total)

Maternal mortality ratio, modeled estimate (per 100,000 live births)

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

2000

1989–94a

2000–04a

1,700 850 100 1,000 1,000 730 150 1,100 1,100 480 990 510 690 730 880 630 850 420 540 540 740 1,100 1,000 550 760 550 1,800 1,200 1,000 24 1,000 300 1,600 800 1,400 .. 690 .. 2,000 1,100 230 590 370 1,500 570 880 750 1,100

.. .. .. 42 .. 58 .. .. .. .. .. .. 45 .. 5 .. .. .. 44 44 31 .. 45 50 .. 57 55 .. 40 97 .. 68 15 31 26 .. 47 .. .. .. .. 86 56 44 .. 38 51 69

45 66 94 38 25 62 .. 44 14 62 61 .. 68 61 65 28 6 86 55 47 56 35 42 60 51 51 61 41 57 99 48 76 16 35 31 76 58 .. 42 25 .. 87 74 46 61 39 43 ..

140 84 97 220 120

77 41 .. 31 ..

96 69 .. 63 90

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

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

53

Table

3.6

Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases Prevalence of HIV (% ages 15–49) 2005

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

Contraceptive prevalence rate Share of women ages 15–49

Deaths due Malaria prevention to malaria Children sleeping under (per 100,000 insecticide-treated bednets people) (% of children under age 5)

Survey year Percentage 1997–2004a

6.1 3.7 1.8 24.1 2.0 3.3 5.4 .. 10.7 3.5 <0.1 3.2 5.3 7.1 3.1 3.2 2.4 .. 7.9 2.4 2.3 1.5 3.8 6.1 23.2 .. 0.5 14.1 1.7 0.7 0.6 16.1 19.6 1.1 3.9 3.1 .. 0.9 .. 1.6 0.9 18.8 1.6 33.4 6.5 3.2 6.7 17.0 20.1 0.2 0.1 <0.1 .. 0.1 0.1

.. 2001 2001 2000 2003 2000 2004 1998 2000 2004 2000 2001 .. 1998 .. .. 2002 2000 2000 2001 2003 2003 2000 2003 2000 2000 2004 2000 2001 2001 2002 2003 2000 2000 2003 2000 2000 2000 .. 2000 .. 1998 2000 2002 1999 2000 2001 2002 1999 .. 2002 2003 .. 2004 2000

.. 6 19 48 14 16 26 53 28 3 26 31 .. 15 .. .. 8 8 33 18 25 7 8 39 30 10 27 31 8 8 76 17 44 14 13 13 29 11 .. 4 .. 56 7 48 25 26 23 34 54 .. 57 60 .. 63 66

.. 354 177 .. 292 .. .. .. .. .. .. 224 .. .. .. .. 74 198 .. .. 70 .. .. 63 .. 201 .. 275 454 .. .. 232 .. 469 141 200 .. 72 .. .. .. .. 70 .. 130 .. 152 141 .. .. .. .. .. .. ..

Incidence of tuberculosis (per 100,000 people)

Tuberculosis cases detected under DOTS (% of estimated cases)

2000

2001–04a

1990

2004

1995

2004

.. .. .. .. .. 1.3 1.3 .. 1.5 0.6 9.3 .. .. 1.1 .. 0.7 .. .. .. 14.7 .. .. 7.4 2.9 .. .. 0.2 2.9 .. .. .. .. 3.4 5.8 .. 5.0 22.8 1.7 .. 1.5 .. .. 0.4 0.1 .. 2.0 .. .. .. .. .. .. .. .. ..

.. 2.3 7.4 .. 2.0 .. .. .. .. .. .. 0.7 .. 4.0 .. .. 4.2 .. .. .. 4.0 4.0 .. 5.0 .. .. .. .. 8.4 .. .. .. .. .. 1.0 .. .. .. .. .. .. .. .. .. 10.0 .. 0.2 6.5 .. .. .. .. .. .. ..

.. 214 79 236 158 125 65 158 117 101 88 133 137 143 608 87 225 128 144 193 223 122 165 108 179 112 192 257 304 238 68 167 260 131 105 135 135 203 43 224 341 268 182 263 179 351 161 297 135 .. 37 42 31 135 33

.. 259 87 670 191 343 179 172 322 279 46 366 377 393 734 239 271 353 280 233 206 240 199 619 696 310 218 413 281 287 64 460 717 157 290 371 107 245 34 443 411 718 220 1,226 347 355 402 680 674 .. 54 27 20 110 22

32 .. 81 72 12 20 .. .. .. 37 54 42 67 52 .. 83 .. 15 .. 75 16 43 .. 56 63 .. 51 38 14 .. 34 54 22 .. 11 34 .. 61 .. 28 .. .. .. .. 56 13 .. .. .. 58 .. 43 .. 93 ..

45 94 82 67 18 29 91 .. 4 16 39 70 65 38 43 82 14 36 81 66 37 52 75 46 86 58 74 40 19 43 33 46 88 46 21 29 .. 52 106 36 44 83 35 38 47 17 43 54 42 80 105 61 169 80 95

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

54

Part II. Millennium Development Goals

MILLENNIUM DEVELOPMENT GOALS

Table

3.7

Millennium Development Goal 7: ensure environmental sustainability Nationally GDP per unit protected areas of energy use as share of total (constant 2000 PPP $ land area Forest area per kg of oil equivalent) (%) (% of total land area)

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

Carbon dioxide emissions (metric tons per capita)

Population with Solid fuel sustainable access to an improved use water source (% of (%) population)

Population with sustainable access to improved sanitation (%)

1990

2005

2004

1990

2003

1990

2002

2000–04 a

1990

2002

1990

2002

49 30 24 26 11 53 14 37 10 5 62 67 32 0 66 .. .. 85 44 33 30 79 7 0 42 24 41 12 0 19 26 11 2 19 13 28 49 87 43 13 8 32 27 47 13 25 66 57

47 21 21 25 6 46 21 37 9 2 59 66 33 0 58 15 13 85 47 24 27 74 6 0 33 22 36 10 0 18 25 9 1 12 19 28 45 87 38 11 8 28 31 40 7 18 57 45

6.6 11.4 18.5 11.5 5.7 4.5 .. 8.7 9.1 .. 5.0 6.5 6.0 .. .. 4.3 16.9 0.7 2.3 5.6 0.7 .. 8.0 0.2 1.7 4.3 11.2 3.7 1.7 .. 8.4 13.6 7.7 3.3 6.2 .. 11.6 .. 2.1 0.8 5.5 5.2 .. 29.8 7.9 24.6 31.9 12.1

3.7 2.6 .. .. .. 4.7 .. .. .. .. 5.0 2.3 5.2 .. .. .. 2.1 4.8 .. 4.6 .. .. 2.2 .. .. .. .. .. .. .. 1.3 .. .. 1.1 .. .. 5.0 .. .. .. 3.8 2.7 .. 1.4 4.3 .. 1.5 3.0

3.1 3.5 .. .. .. 4.6 .. .. .. .. 2.1 3.3 3.8 .. .. .. 2.1 4.9 .. 5.0 .. .. 2.1 .. .. .. .. .. .. .. 2.5 9.9 .. 1.3 .. .. 5.2 .. .. .. 3.9 3.7 .. 1.3 3.2 .. 1.4 2.6

0.4 0.1 1.5 0.1 0.0 0.1 0.2 0.1 0.0 0.2 0.1 0.5 0.4 0.6 0.3 .. 0.1 6.3 0.2 0.2 0.2 0.2 0.2 .. 0.2 0.1 0.1 0.0 1.3 1.4 0.1 0.0 0.1 0.5 0.1 0.6 0.4 1.6 0.1 0.0 8.1 0.2 0.6 0.1 0.2 0.0 0.3 1.6

0.5 0.3 2.3 0.1 0.0 0.2 0.3 0.1 0.0 0.1 0.0 0.6 0.4 0.5 0.4 0.2 0.1 2.6 0.2 0.4 0.1 0.2 0.2 .. 0.1 0.1 0.1 0.0 1.1 2.6 0.1 1.1 0.1 0.4 0.1 0.6 0.4 6.4 0.1 .. 7.6 0.3 0.9 0.1 0.3 0.1 0.2 1.0

95 95 .. 95 100 83 .. .. 95 .. .. 84 74

32 60 93 39 69 50 .. 48 20 89 43 .. 69 78 .. 40 25 .. .. 54 42 .. 45 .. 56 40 41 34 41 100 .. 58 40 49 58 .. 66 .. .. .. 83 64 .. 38 49 44 50 77

50 68 95 51 79 63 80 75 34 94 46 46 84 80 44 57 22 87 82 79 51 59 62 76 62 45 67 48 56 100 42 80 46 60 73 79 72 87 57 29 87 69 52 73 51 56 55 83

30 11 38 13 44 21 .. 23 6 23 18 .. 31 48 .. 8 4 .. .. 43 17 .. 42 37 38 12 36 36 28 99 .. 24 7 39 37 .. 35 .. .. .. 63 33 .. 47 37 43 41 49

30 32 41 12 36 48 42 27 8 23 29 9 40 50 53 9 6 36 53 58 13 34 48 37 26 33 46 45 42 99 27 30 12 38 41 24 52 .. 39 25 67 34 52 46 34 41 45 57

1 0 0 10 4

1 0 0 10 7

5.0 9.7 0.1 0.7 0.3

5.7 5.1 .. 11.9 6.7

5.6 5.1 .. 10.2 8.1

3.0 1.4 8.7 1.0 1.6

2.9 2.1 9.1 1.5 2.3

95 94 71 75 77

87 98 72 80 82

88 54 97 57 75

92 68 97 61 80

.. 80 95 .. .. 88 .. .. 82 83 .. 99 95 98 .. .. .. 63 98 86 100 .. 41 .. .. .. .. .. .. .. .. 97 85 73 5 5 5 5 5 5

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

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

55

Table

3.8

Millennium Development Goal 8: develop a global partnership for development Debt sustainability Heavily Indebted Poor Country (HIPC) Debt Initiative Decision point

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

56

Completion point

Estimated total nominal debt service relief committed under Enhanced HIPC Initiative ($ millions) as of Mar. 2006

Jul. 2000

Mar. 2003

460

Jul. 2000 Jul. 2005 Oct. 2000

Apr. 2002 Floating Floating

930 1,472 2,800

May 2001

Floating

260

Jul. 2003 Mar. 2006

Floating 2,881

10,389

Nov. 2001

Apr. 2004

3,275

Dec. 2000 Feb. 2002 Dec. 2000 Dec. 2000

Floating Jul. 2004 Floating Floating

90 3,500 800 790

Dec. 2000 Dec. 2000 Sep. 2000 Feb. 2000

Oct. 2004 Floating Mar. 2003 Jun. 2002

1,900 1,000 895 1,100

Apr. 2000

Sep. 2001

4,300

Dec. 2000

Apr. 2004

1,190

Dec. 2000 Dec. 2000 Jun. 2000

Apr. 2005 Floating Apr. 2004

1,400 200 850

Mar. 2002

Floating

Apr. 2000

Nov. 2001

3,000

Feb. 2000 Dec. 2000

May. 2000 Apr. 2005

1,950 3,900

Part II. Millennium Development Goals

950

Debt service (% of exports) 1990

2004

13.5 8.1 8.2 4.3 6.8 43.4 20.5 4.8 13.2 4.4 2.3 .. 35.3 35.4 .. 12.1 .. 39.0 6.4 22.2 38.1 20.0 31.0 35.4 4.2 .. 45.5 29.3 12.3 29.8 8.8 26.2 .. 17.4 22.6 14.2 34.0 20.0 9.0 10.1 .. .. 8.7 5.7 32.9 11.9 81.4 14.7 23.1 .. 63.4 20.4 .. 21.5 24.5

7.9 14.8 .. .. .. .. .. .. .. .. .. .. .. 6.9 .. .. .. 5.3 .. .. 6.6 19.9 .. 8.6 4.5 .. .. .. .. .. 7.4 4.5 .. .. 8.2 11.2 .. .. 8.1 10.9 .. 6.4 6.0 1.7 5.3 .. 6.9 .. .. .. .. 7.6 .. 14.0 13.7

MILLENNIUM DEVELOPMENT GOALS

Youth unemployment rate Total Share of total labor force ages 15–24

Men Share of male labor force ages 15–24

Information and communications Women Share of female labor force ages 15–24

Fixed-line and mobile phone subscribers (per 1,000 people)

Personal computers (per 1,000 people)

Internet users (per 1,000 people)

Year

Percentage

Year

Percentage

Year

Percentage

1990

2004

1996

2004

1996

2004

.. .. .. 2001 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2000 .. .. .. .. .. .. .. .. .. .. .. 2001 .. .. .. .. .. .. .. .. 2003 .. .. .. .. .. .. 2002 .. .. 2001 .. 2003 ..

.. .. .. 40 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 16 .. .. .. .. .. .. .. .. .. .. .. 45 .. .. .. .. .. .. .. .. 60 .. .. .. .. .. .. 25 .. .. 28 .. 17 ..

.. .. .. 2001 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2000 .. .. .. .. .. .. .. .. .. .. .. 2001 .. .. .. .. .. .. .. .. 2003 .. .. .. .. .. .. 2002 .. .. 2001 .. 2003 ..

.. .. .. 34 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 13 .. .. .. .. .. .. .. .. .. .. .. 40 .. .. .. .. .. .. .. .. 56 .. .. .. .. .. .. 28 .. .. 19 .. 17 ..

.. .. .. 2001 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2000 .. .. .. .. .. .. .. .. .. .. .. 2001 .. .. .. .. .. .. .. .. 2003 .. .. .. .. .. .. 2002 .. .. 2001 .. 2003 ..

.. .. .. 46 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 19 .. .. .. .. .. .. .. .. .. .. .. 49 .. .. .. .. .. .. .. .. 65 .. .. .. .. .. .. 21 .. .. 51 .. 16 ..

10 7 3 18 2 1 3 23 2 1 8 1 6 6 10 4 .. 2 22 7 3 2 6 7 8 4 3 3 1 3 55 4 38 1 3 1 19 6 124 3 2 94 2 18 3 3 2 8 12 .. 32 29 51 17 37

84 54 .. 396 37 .. 103 281 18 14 .. 37 102 98 .. .. 14 .. 388 .. 93 .. .. 85 109 .. .. 25 36 .. 700 .. 206 13 79 18 .. .. 842 27 88 .. 58 .. .. .. 44 34 55 .. 215 235 .. 357 480

.. .. 1 12 0 .. 2 .. .. .. .. .. .. 1 7 .. .. .. 6 2 1 2 .. 2 .. .. .. .. 0 6 53 1 12 .. 5 .. .. 9 .. .. .. 36 1 .. .. 4 1 .. 7 .. 5 6 .. 4 ..

.. 3 4 45 2 5 10 97 3 2 9 .. 4 15 27 14 4 3 29 16 5 5 .. 13 .. .. 5 2 3 14 279 6 109 1 7 .. .. 21 179 .. 6 82 17 32 7 29 4 10 77 .. 9 32 .. 21 48

.. 0 0 2 0 0 .. .. 0 .. .. 0 0 0 0 .. 0 0 0 0 0 0 .. 0 0 .. 0 .. 0 .. 2 0 0 0 0 0 .. 0 7 0 0 9 0 1 0 0 0 0 0 .. 0 1 .. 0 0

.. 11 12 34 4 3 10 50 2 6 14 .. 9 17 12 10 12 2 29 33 17 5 17 45 24 .. 5 4 4 5 146 7 37 2 14 4 131 42 239 2 25 78 32 32 9 37 7 20 63 .. 26 54 36 117 84

MILLENNIUM DEVELOPMENT GOALS

Part II. Millennium Development Goals

57

Table

Results framework

4.1

Status of Paris Declaration indicators PDI-1. Operational PDI-2a. Reliable public development strategies financial management

PDI-2b. Reliable country procurement systems

Comprehensive Development Framework composite rating of national development strategya

Benchmark rating of public expenditure management (PEM) systems (0–15) b

C

8

C C C C D C

9

55.0

7

40.3

C C D C

3

C

7

D C C E C

7 5 0

Angola Benin Botswana Burkina Faso Burundi Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d’Ivoire Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe

7

C C C B

4 5 11

C

4

C

5

B D C

8 4 7

D

7

B

11

B C

8 3

System adheres to broadly accepted good Benchmark Indicator Reform program in place System (BIS) AFR Observatory Indexd (0–100) c

Yes Yes No Yes Yes Yes Yes No Yes No Yes No Yes No No Yes Yes No Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes No Yes Yes Yes No Yes No Yes No Yes No No Yes Yes Yes Yes No

PDI-6. Avoidance of parallel project implementation units (PIUs) Number of parallel PIUs

PDI-12. Mutual accountability

Independent assessment framework in place

No No

1

107 7 21

3

22 22 35 19 46 54

72

25 39 24

No No No No No No No No No No No No No Yes No No Yes

No No No No No No No No Yes No No No No No No No No No No No No Yes No Yes No No

Note: See technical notes for further details. PDI is Paris Declaration Indicator. a. Comprehensive Development Framework Ratings 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 practices; and E means it reflects little action toward achieving good practices. b. Public expenditure and financial accountability benchmark rating of public expenditure management systems ranges from 0 to 15 and indicates the total number of the 15 required standard benchmarks that a country has met. The higher the number the less system upgrading is required. c. The Benchmark Indicator System ranges from 0 to 100 and assesses a country’s procurement system based on 4 pillars and 12 indicators. It does not provide information on the performance of the system but rather on the available procurement framework. Indicators on performance are being developed. The procurement system has not been measured yet for most countries. d. The AFR Observatory was put in place in 2000 to monitor procurement reform efforts. These efforts are measured against an action plan prepared in partnership with the country.

58

Part III. Development outcomes

PARIS DECLARATION INDICATORS

Table

Drivers of growth

5.1

Business environment Number of startup Time required Cost to start procedures to start a business for new a business (% of GNI business (days) per capita)

Number of Time required Number of Time required procedures to register procedures to enforce to register a property to enforce a contract a property (days) a contract (days)

Protecting investors disclosure index (0 low to 10 high)

Time to resolve insolvency (years)

Rigidity of employment index (0 least rigid to 100 most rigid)

2005

2005

2005

2005

2005

2005

2005

2005

2005

2005

11 14 8 11 12 11 12 .. 10 19 .. 13 8 11 .. .. 13 7 .. .. 12 13 .. 13 9 .. 11 10 13 11 6 14 10 13 9 9 9 9 .. 9 .. 9 10 .. 13 13 17 .. .. 11 14 10 .. 5 9

64 146 32 108 45 43 37 .. 14 75 .. 155 67 45 .. .. 91 32 .. .. 81 49 .. 54 92 .. 38 35 42 82 46 153 95 35 43 21 192 57 .. 26 .. 38 38 .. 35 53 36 .. .. 28 26 34 .. 11 14

215 643 191 11 150 201 173 .. 212 361 .. 503 289 134 .. .. 129 65 .. .. 79 179 .. 48 56 .. 54 140 191 144 9 95 19 465 74 280 97 109 .. 835 .. 9 68 .. 161 218 118 .. .. 37 25 105 .. 12 10

7 7 3 6 8 5 5 .. 3 6 .. 8 6 7 .. .. 6 15 .. .. 7 6 .. 8 6 .. 8 6 5 4 5 8 9 5 21 5 6 6 .. 8 .. 6 .. .. 12 6 8 .. .. 9 16 7 .. 3 5

118 334 50 69 107 94 93 .. 69 44 .. 106 103 369 .. .. 91 56 .. .. 382 104 .. 73 101 .. 134 118 44 49 210 42 28 49 274 371 51 114 .. 58 .. 23 .. .. 61 212 48 .. .. 112 52 193 .. 82 57

36 47 49 26 41 47 58 .. 45 52 .. 51 47 25 .. .. 27 30 .. .. 23 44 .. 25 49 .. 29 16 28 28 17 38 31 33 23 27 67 33 .. 58 .. 26 67 .. 21 37 15 .. .. 41 49 55 .. 17 14

439 1,011 570 154 446 433 585 .. 660 526 .. 909 560 525 .. .. 385 420 .. .. 200 306 .. 360 285 .. 280 277 340 410 367 580 270 330 730 310 405 485 .. 305 .. 277 915 .. 242 535 209 .. .. 333 407 410 .. 240 27

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

3 6 3 2 4 4 3 .. 5 10 .. 5 3 2 .. .. 2 2 .. .. 2 4 .. 5 3 .. .. 3 4 8 2 5 1 5 2 .. .. 3 .. 3 .. 2 .. .. 3 3 2 .. .. 3 4 4 .. 2 1

53 64 53 30 84 69 56 .. 76 72 .. 90 80 45 .. .. 27 41 .. .. 34 48 .. 28 42 .. 59 21 66 73 37 61 27 90 38 59 60 64 .. 80 .. 52 43 .. 69 79 13 .. .. 57 51 53 .. 60 54

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

PRIVATE SECTOR DEVELOPMENT

Part III. Development outcomes

59

Table

Drivers of growth

5.2

Investment climate Viewed by firms as a major constraint (% of firms) Net Domestic Lack of foreign credit to confidence Private direct private courts will investment investment sector Policy uphold Labor Labor (% of GDP) ($ millions) (% of GDP) uncertainty Corruption Courts property rights Crime Tax rates Finance Electricity regulation skills 2004 2004 2000–05b 2000–05 b 2000–05b 2000–05 b 2000–05 b 2000–05 b 2000–05 b 2000–05b 2000–05b 2000–05b 2004a

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

.. 4.3 12.1 13.2 10.8 2.7 15.7 11.6 4.1 15.3 4.2 10.0 16.6 7.1 .. .. 5.3 9.0 19.9 13.9 16.2 7.1 2.1 7.5 33.9 3.9 11.8 1.8 11.5 6.0 14.5 11.3 17.9 6.8 13.2 12.0 15.1 12.9 10.9 5.9 .. 14.9 17.5 9.7 11.0 15.9 16.9 15.4 13.4 .. 20.7 17.9 .. 22.5 25.5

10,117 853 47 58 21 12 242 39 6 479 1 435 551 175 9 –159 10 101 –51 50 70 98 .. 108 53 0 53 44 62 7 35 245 246 18 4,409 4 9 109 30 .. .. –1,021 1,481 65 478 125 202 239 9 1,442 0 0 .. 822 620

.. 5.4 14.5 19.0 14.9 22.6 9.9 37.3 7.2 3.3 9.0 1.5 3.2 14.4 .. 3.6 32.8 24.3 8.6 11.7 13.1 3.6 1.5 26.8 6.5 6.1 10.0 8.4 20.1 25.9 59.5 2.1 50.4 6.2 15.6 10.7 33.1 21.2 37.5 4.7 .. 141.3 7.7 19.5 9.0 16.0 6.8 8.0 .. .. 11.0 54.5 16.9 56.7 65.2

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 31.5 39.3 .. .. .. .. .. 51.5 .. .. 41.5 .. 21.9 .. .. .. .. .. .. .. .. 31.3 .. .. .. 17.9 .. .. 31.5 .. 27.6 57.0 .. .. .. 65.8 .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.7 39.0 .. .. .. .. .. 73.8 .. .. 46.6 .. 48.7 .. .. .. .. .. .. .. .. 39.9 .. .. .. 16.1 .. .. 51.1 .. 38.2 46.4 .. .. 35.2 51.3 .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 34.8 .. 16.9 .. .. .. .. .. .. .. .. 13.3 .. .. .. 8.8 .. .. 20.0 .. .. 38.6 .. .. .. 27.4 .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 51.3 .. .. 44.6 .. 33.1 .. .. .. .. .. .. .. .. 40.5 .. .. .. 20.8 .. .. 55.1 .. 30.1 .. .. .. 27.3 .. .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.3 9.5 .. .. .. .. .. 69.8 .. .. 37.7 .. 22.1 .. .. .. .. .. 36.3 .. .. 15.4 .. .. .. 29.0 .. .. 25.5 .. 26.8 48.8 .. .. .. .. .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 31.1 73.6 .. .. .. .. .. 68.2 .. .. 44.9 .. 36.6 .. .. .. .. .. .. .. .. 50.8 .. .. .. 18.6 .. .. 73.4 .. 48.3 .. .. .. 44.8 81.8 .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 53.7 40.2 .. .. .. .. .. 58.3 .. .. 62.9 .. 57.0 .. .. .. .. .. .. .. .. 60.3 .. .. .. 14.5 .. .. 53.0 .. 52.8 67.7 .. .. 51.3 39.0 .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 38.2 42.5 .. .. .. .. .. 48.1 .. .. 41.3 .. 24.2 .. .. .. .. .. 97.4 .. .. 30.7 .. .. .. 9.0 .. .. 58.9 .. 44.5 39.6 .. .. 11.5 26.5 .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 5.2 4.6 .. .. .. .. .. 22.5 .. .. 14.8 .. 3.9 .. .. .. .. .. .. .. .. 16.3 .. .. .. 32.9 .. .. 12.1 .. 10.8 16.9 .. .. 12.9 28.1 .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 41.0 17.9 .. .. .. .. .. 27.6 .. .. 30.5 .. 20.8 .. .. .. .. .. .. .. .. 18.5 .. .. .. 35.5 .. .. 25.0 .. 30.8 35.7 .. .. 25.5 29.8 .. .. ..

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

60

Part III. Development outcomes

PRIVATE SECTOR DEVELOPMENT

Regulation and tax administration Total tax Time to prepare payable Number of and pay taxes (% of tax payments (hours) gross profits) 2005 2005 2005

41 30 75 24 40 41 51 .. 66 65 .. 34 94 71 .. .. 18 20 .. .. 35 55 .. 17 19 .. 29 33 60 61 7 35 23 44 36 42 29 59 .. 20 .. 32 .. .. 48 51 31 36 59 .. 63 39 .. 28 31

394 656 270 140 270 140 1,300 .. 504 122 .. 312 576 270 .. .. 216 52 .. .. 304 416 .. 372 564 .. 400 782 270 696 158 230 50 270 1,120 168 1,008 696 .. 399 .. 350 .. .. 248 270 237 132 216 .. 504 504 .. 690 112

PRIVATE SECTOR DEVELOPMENT

58.1 32.5 53.1 52.9 48.3 173.5 47.6 .. 60.9 51.3 .. 134.7 66.9 46.9 .. .. 66.3 43.6 .. .. 45.3 51.2 .. 68.2 37.7 .. 58.9 56.5 44.0 75.8 38.2 50.9 43.9 49.4 27.1 53.9 27.4 45.0 .. 163.9 .. 43.8 .. .. 51.3 50.9 42.9 38.6 48.6 .. 58.5 32.1 .. 54.8 52.7

Highest marginal tax rate, corporate (%) 2000–05 b

Time dealing with officials (% of management time) 2000–05b

Average time to clear customs (days) 2000–05b

Bank branches (per 100,000 people) 2004

Interest rate spread (lending rate minus deposit rate) 2004

.. .. .. 15.0 .. .. 38.5 .. .. .. .. 40.0 .. 35.0 .. .. .. .. 35.0 .. 32.5 .. .. 30.0 .. .. .. 38.0 .. .. 25.0 32.0 35.0 .. 30.0 .. .. 35.0 .. .. .. 30.0 .. 30.0 30.0 .. 30.0 35.0 30.0 .. .. 40.0 .. 35.0 ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 5.9 5.7 .. .. .. .. .. 13.8 .. .. 25.4 .. 10.8 .. .. .. .. .. .. .. .. 13.8 .. .. .. 10.7 .. .. 16.2 .. 5.0 .. .. .. .. .. .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 9.1 13.5 .. .. .. .. .. 8.9 .. .. 7.0 .. 10.0 .. .. .. .. .. 17.8 .. .. 7.0 .. .. .. 6.5 .. .. 17.5 .. .. .. .. .. 21.6 9.9 .. 2.7 ..

.. .. .. 3.8 .. .. .. .. .. .. .. .. .. .. .. .. .. 0.4 .. .. 1.6 .. .. 1.4 .. .. 0.7 .. .. .. 11.9 .. 4.5 .. 1.6 .. .. .. .. .. .. 6.0 .. .. 0.6 .. 0.5 1.5 3.3 .. .. 3.6 .. 6.6 ..

12.5 66.9 .. 5.9 .. .. 13.0 9.2 13.0 13.0 7.5 .. 13.0 .. 10.4 13.0 .. 3.6 13.0 14.5 .. 11.9 .. 10.1 8.1 14.3 10.3 23.1 .. 13.0 12.9 12.2 5.0 .. 5.5 .. 18.3 .. 6.6 11.9 .. 4.7 .. 6.7 9.7 .. 12.9 19.2 175.7 .. 5.5 5.7 4.0 7.9 ..

Listed domestic companies 2000–05 b

Market capitalization of listed companies (% of GDP) 2000–05b

Turnover ratio for traded stocks (%) 2000–05b

904 .. .. 18 .. .. .. .. .. .. .. .. .. 39 .. .. .. .. .. .. 30 .. .. 47 .. .. .. 8 .. 40 42 .. 13 .. 214 .. .. .. .. .. .. 388 .. 6 6 .. 5 11 79 .. .. 744 .. 56 46

129.6 .. .. 28.4 .. .. .. .. .. .. .. .. .. 13.5 .. .. .. .. .. .. 29.8 .. .. 24.2 .. .. .. 9.1 .. 99.3 39.4 .. 7.7 .. 20.1 .. .. .. .. .. .. 214.1 .. 9.4 6.2 .. 1.4 8.0 41.3 .. .. 48.9 .. 50.1 9.4

27.6 .. .. 2.0 .. .. .. .. .. .. .. .. .. 1.5 .. .. .. .. .. .. 3.2 .. .. 9.6 .. .. .. 13.8 .. .. 6.1 .. 1.6 .. 11.5 .. .. .. .. .. .. 41.6 .. 0.0 1.9 .. .. 22.5 6.4 .. .. 42.4 .. 16.4 16.8

Part III. Development outcomes

61

Table

Drivers of growth

6.1

International trade and tariff barriers Trade

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

62

Annual growth (%)

Merchandise trade (% of GDP) 2004a

Exports ($ millions) 2004a

Imports ($ millions) 2004a

Exports (% of GDP) 2004a

Imports (% of GDP) 2004a

Exports 2003–04a

Imports 2003–04a

Terms of trade index 2000=100 2004a

65 125 39 72 32 40 39 95 27 100 44 70 142 86 .. .. 112 44 101 110 92 48 87 58 160 83 82 78 63 99 112 70 91 42 92 39 151 69 182 60 .. 49 39 191 46 81 41 47 80 59 55 43 .. 70 98

177,280 13,722 539 3,570 416 59 3,061 295 150 2,274 60 2,023 3,669 7,445 .. .. 122 1,369 4,420 184 3,349 824 98 4,207 763 171 1,425 511 1,341 451 3,356 1,828 2,644 491 39,372 189 25 2,165 663 240 .. 57,032 3,822 2,357 2,016 691 933 1,059 1,694 83,995 25,103 14,997 .. 16,128 13,279

164,342 10,728 1,055 2,893 1,104 205 3,128 604 207 2,034 103 2,610 2,488 5,939 .. .. 917 2,934 2,902 255 4,550 986 138 5,114 1,430 235 2,146 974 1,747 1,069 3,393 2,320 2,573 795 26,965 521 61 3,223 616 407 .. 48,071 4,650 2,441 3,138 969 1,879 1,478 2,068 80,245 21,472 18,706 .. 18,932 14,251

33.7 70.1 13.3 39.8 8.6 8.9 19.4 31.2 11.5 52.8 16.1 30.5 84.5 48.1 .. .. 13.2 17.0 61.1 46.0 38.9 21.8 36.2 26.2 55.8 34.8 32.6 26.8 27.5 29.4 55.6 30.9 46.3 16.1 54.6 10.3 43.9 27.8 94.3 22.1 .. 26.6 17.8 93.6 17.8 33.5 13.7 19.5 36.1 31.2 33.4 19.8 .. 30.7 44.3

31.2 54.8 26.1 32.2 22.9 30.9 19.8 63.7 15.8 47.2 27.8 39.4 57.3 38.4 .. .. 98.8 36.3 40.1 63.7 52.8 26.1 51.1 31.8 104.6 47.8 49.2 51.2 35.8 69.7 56.2 39.2 45.0 26.0 37.4 28.4 107.5 41.5 87.6 37.5 .. 22.4 21.7 97.0 27.7 47.0 27.5 27.3 44.0 .. 28.6 24.7 .. 36.0 47.5

.. 12.6 0.4 –0.3 2.4 –24.0 1.7 8.4 9.6 170.4 33.2 20.1 8.1 17.2 .. .. –7.4 17.3 3.3 5.4 3.8 3.6 4.1 19.8 13.0 .. 1.5 –3.0 –0.2 8.5 –1.7 23.9 –6.8 1.6 3.1 11.2 20.7 3.6 4.2 12.6 .. 2.5 14.0 1.1 –7.0 3.0 6.2 12.6 2.0 .. 6.1 6.4 .. 5.2 7.1

10.8 9.6 1.3 2.7 3.5 6.8 4.1 3.0 –8.2 1.4 1.1 26.4 62.1 12.6 .. .. –14.6 20.4 3.8 7.2 11.3 3.5 7.2 15.3 4.5 .. 24.8 –0.7 –2.8 9.8 –0.1 4.2 –10.9 4.8 2.3 4.2 23.5 5.9 8.0 –11.9 .. 14.1 88.0 1.3 2.2 3.0 5.1 10.9 –0.4 5.3 4.6 4.7 .. 6.3 6.3

.. 134.3 91.8 98.3 126.9 .. 96.1 97.2 77.7 .. 133.4 135.3 172.0 112.5 .. .. 72.2 84.4 144.4 89.0 119.5 99.6 80.8 100.5 120.6 .. 134.7 90.0 103.8 105.2 89.5 88.5 96.2 120.3 124.8 55.3 .. 101.7 .. 110.0 .. 131.9 156.7 108.5 105.8 103.5 88.4 86.2 93.0 94.5 76.9 97.7 .. 110.0 98.4

Part III. Development outcomes

TRADE

Structure of merchandise exports (% of total)

Structure of merchandise imports (% of total)

Food 2000–04b

Agricultural raw materials 2000–04b

Fuel 2000–04b

Ores and metals 2000–04b

Manufactures 2000–04b

Food 2000–04b

Agricultural raw materials 2000–04b

Fuel 2000–04b

Ores and metals 2000–04b

.. .. 40.8 3.1 16.4 92.2 19.3 6.4 1.5 .. 88.7 .. .. 55.8 .. .. .. 62.0 1.2 63.3 71.6 2.0 .. 39.7 .. .. 60.7 77.8 9.6 .. 27.0 19.1 48.3 30.4 0.0 52.3 .. 35.0 63.3 91.6 .. 8.8 10.2 14.6 52.7 24.0 64.3 15.5 30.9 .. 0.2 9.8 .. 19.0 11.1

.. .. 49.4 0.5 72.3 1.2 23.7 5.9 25.2 .. 0.0 .. .. 9.2 .. .. .. 25.9 9.8 7.3 9.9 0.8 .. 12.0 .. .. 6.2 5.3 22.3 .. 0.5 5.6 1.3 3.6 0.0 7.3 .. 2.8 0.0 0.8 .. 2.3 6.1 7.8 12.9 15.6 15.5 10.3 15.7 .. 0.0 7.0 .. 1.7 0.7

.. .. 0.4 0.1 2.8 0.0 46.7 48.5 0.1 .. .. .. .. 12.8 .. .. .. 0.0 76.2 0.8 0.1 0.1 .. 23.0 .. .. 4.4 0.2 11.3 .. 0.1 16.4 1.0 1.6 97.9 6.8 .. 19.4 30.0 .. .. 9.1 81.2 0.7 2.2 0.4 4.6 1.7 1.6 .. 97.4 43.1 .. 2.0 9.6

.. .. 0.1 5.5 0.6 1.5 5.1 0.0 36.1 .. 0.0 .. .. 0.2 .. .. .. 0.7 5.5 1.6 3.9 71.6 .. 4.2 .. .. 5.1 0.3 0.3 .. 0.4 54.8 7.3 54.9 0.0 23.3 .. 3.9 0.0 0.1 .. 22.2 0.4 0.2 12.0 12.7 0.4 62.4 23.2 .. 0.4 3.7 .. 8.2 1.1

.. .. 9.3 90.6 8.0 5.1 5.2 87.7 37.1 .. 8.2 .. .. 20.0 .. .. .. 11.4 7.0 27.0 14.4 25.3 .. 21.1 .. .. 22.5 16.4 54.6 .. 70.9 3.1 40.9 7.9 2.1 10.3 .. 38.5 6.4 7.5 .. 57.6 1.6 76.4 20.2 47.3 15.3 10.0 28.5 .. 2.0 30.6 .. 69.1 77.6

.. .. 23.9 13.9 12.0 9.0 18.3 30.9 23.4 .. 21.9 .. .. 21.7 .. .. .. 21.5 24.2 37.6 20.8 23.1 .. 10.4 .. .. 13.5 12.7 16.2 .. 17.5 10.6 14.9 33.5 15.5 11.7 .. 28.3 28.3 22.5 .. 5.0 16.4 18.2 15.0 18.4 16.8 6.5 18.7 .. 21.9 22.2 16.8 10.9 8.6

.. .. 5.3 0.8 0.6 1.1 1.7 2.5 5.4 .. 0.4 .. .. 0.6 .. .. .. 0.7 0.6 2.2 1.3 1.2 .. 2.1 .. .. 0.4 1.2 0.7 .. 2.3 0.7 0.7 4.3 0.6 4.0 .. 2.0 0.7 7.6 .. 1.3 0.9 2.2 1.6 0.8 1.9 1.1 1.8 .. 1.9 5.1 0.6 3.0 2.8

.. .. 17.4 6.5 24.4 16.5 17.8 13.1 11.0 .. 4.1 .. .. 17.1 .. .. .. 12.0 3.2 10.6 1.6 21.7 .. 24.3 .. .. 23.3 2.7 21.9 .. 13.2 11.7 10.4 16.9 16.0 15.6 .. 18.3 26.3 39.7 .. 14.5 3.1 12.6 16.5 23.0 10.0 11.2 13.7 .. 0.9 8.3 0.7 16.7 10.3

.. .. 0.8 2.0 0.6 1.1 1.3 0.6 4.2 .. 0.2 .. .. 1.2 .. .. .. 1.5 1.2 0.9 2.1 0.8 .. 1.6 .. .. 0.4 1.2 0.7 .. 1.0 0.2 3.6 1.2 1.6 2.0 .. 2.5 0.4 0.8 .. 2.0 0.8 1.0 1.1 2.2 1.5 2.6 9.8 .. 1.3 3.5 0.9 2.9 2.7

Export diversification index (0 low to Manufactures 100 high) 2000–04b 2003

.. .. 52.6 71.8 62.5 72.2 60.9 52.9 55.9 .. 72.5 .. .. 48.5 .. .. .. 64.0 69.7 48.7 74.2 53.0 .. 61.3 .. .. 61.8 82.2 60.3 .. 65.9 43.3 69.4 44.0 66.3 66.7 .. 48.9 44.2 29.3 .. 68.8 78.2 64.4 65.8 55.5 69.5 78.5 54.2 .. 73.9 49.8 81.1 66.5 75.6

.. 1.1 2.1 .. 2.2 1.6 4.4 9.2 3.4 2.6 1.3 3.0 1.6 .. 5.9 1.2 5.2 4.0 1.6 5.2 4.0 4.2 4.8 16.0 .. 2.0 8.1 3.0 1.3 3.8 11.7 2.0 .. 1.9 1.3 2.4 1.5 12.2 2.7 3.8 6.1 .. 1.6 .. 21.7 5.3 7.3 5.0 8.1 .. 3.3 20.4 1.4 38.3 31.2

(continues) TRADE

Part III. Development outcomes

63

Table

Drivers of growth

6.1

International trade and tariff barriers (continued) Tariff barriers, all products Tariff barriers, Tariff barriers, Shipping 20 ft (%) primary products manufactured products container from port Average (%) (%) to final destination time to Simple Share of Share of clear mean Simple Weighted lines with lines with Average Simple Weighted Simple Weighted Average Binding customs bound mean mean international specific cost time mean mean mean mean coverage (days) rate tariff tariff peaks rates ($) (days) tariff tariff tariff tariff 2000–04b 2000–04b 2000–04b 2000–04b 2000–04b 2000–04b 2000–04b 2000–04b 2000–04b 2000–04b 2000–04b 2000–04b 2000–05 b

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

.. .. 39.1 89.0 39.3 20.9 31.0 .. .. .. .. .. .. .. 100.0 .. .. .. 100.0 13.6 14.3 39.0 .. 14.0 .. .. 29.7 30.2 40.7 39.4 18.0 .. 88.9 96.8 19.3 100.0 .. 100.0 .. 100.0 .. 88.9 .. 88.9 13.4 13.2 14.9 15.9 20.8 .. .. 99.0 .. 100.0 57.8

.. .. 28.6 17.3 41.9 67.6 79.9 .. .. .. .. .. .. .. 40.9 .. .. .. 21.4 100.6 92.1 20.1 .. 95.1 .. .. 27.4 75.0 28.8 19.6 94.0 .. 17.3 44.3 118.0 89.1 .. 30.0 .. 47.4 .. 17.3 .. 17.3 120.0 80.0 73.5 105.6 91.3 .. .. 37.2 .. 41.3 57.7

.. 8.1 14.0 5.0 13.2 20.0 18.1 .. .. .. .. .. .. .. 30.9 .. .. 19.4 18.6 .. 13.1 .. 13.9 16.2 10.8 .. 5.2 12.9 12.8 12.8 23.5 12.7 4.5 12.8 24.8 8.3 .. 13.4 27.2 .. .. 8.5 21.1 1.8 14.1 14.4 6.7 13.2 15.9 .. 17.9 18.9 20.2 28.3 25.3

.. 8.5 12.7 1.0 11.4 14.7 15.0 .. .. .. .. .. .. .. 26.8 .. .. 13.5 14.7 .. 11.0 .. 13.6 10.3 17.8 .. 3.6 10.2 10.7 9.3 13.0 9.9 0.5 13.8 18.5 6.6 .. 9.2 23.4 .. .. 5.6 19.6 0.6 8.2 10.8 5.4 9.6 18.7 .. 12.0 13.9 25.2 24.9 22.3

.. 15.2 54.1 16.0 49.5 32.6 49.5 .. .. .. .. .. .. .. 92.3 .. .. 52.0 52.3 .. 45.0 .. 56.0 39.1 42.1 .. 4.4 40.4 45.9 51.5 40.0 36.8 13.8 48.3 51.8 10.7 .. 50.4 57.6 .. .. 30.9 43.8 7.0 37.4 55.7 0.0 29.5 36.3 .. 39.4 46.2 46.6 75.1 65.6

.. 1.6 0.0 1.4 0.0 0.6 .. .. .. .. .. .. .. .. 2.3 .. .. 0.2 .. .. 0.2 .. 0.0 0.1 2.9 .. 0.0 0.0 0.0 0.0 0.1 0.0 2.4 0.0 1.0 0.0 .. 0.0 0.3 .. .. 2.0 0.0 0.8 0.0 0.0 0.0 0.0 5.7 .. 0.0 6.8 2.1 0.0 0.0

.. 11.6 15.5 2.1 13.7 22.4 21.1 .. .. .. .. .. .. .. 21.9 .. .. 22.0 23.2 .. 17.6 .. 16.6 19.5 16.0 .. 5.5 12.6 15.4 12.6 19.6 16.0 3.5 15.6 36.8 11.8 .. 14.7 38.8 .. .. 6.7 28.2 0.9 15.2 15.5 9.5 13.4 19.2 .. 18.1 18.1 19.2 33.5 36.8

.. 14.7 12.9 0.3 11.3 10.6 16.5 .. .. .. .. .. .. .. 19.7 .. .. 6.7 19.7 .. 17.1 .. 14.5 10.1 9.2 .. 1.7 9.0 11.5 7.9 9.9 9.9 0.4 15.9 26.7 6.4 .. 8.1 46.6 .. .. 3.9 24.0 0.1 7.4 10.1 6.4 11.4 27.2 .. 10.5 7.9 15.1 25.4 18.4

.. 7.5 13.7 5.4 13.1 19.6 17.7 .. .. .. .. .. .. .. 32.6 .. .. 19.1 17.9 .. 12.3 .. 13.4 15.8 10.5 .. 5.1 12.9 12.4 12.8 23.8 12.1 4.6 12.4 23.2 7.9 .. 13.2 25.4 .. .. 8.6 20.5 2.0 14.0 14.1 6.4 13.1 15.4 .. 17.8 19.0 20.1 27.8 24.2

.. 5.9 12.5 1.1 11.5 16.9 14.4 .. .. .. .. .. .. .. 32.3 .. .. 15.7 13.5 .. 8.8 .. 12.9 10.2 17.8 .. 4.6 10.7 10.4 10.0 14.4 9.9 0.6 13.0 15.7 6.6 .. 10.5 18.5 .. .. 5.8 18.9 0.9 8.6 11.3 5.0 9.0 15.7 .. 12.5 16.9 28.5 24.6 23.5

.. .. .. .. 1,310 .. .. .. .. .. .. 2,400 .. .. .. .. 771 451 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1,310 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

.. .. .. .. 17.1 .. 17.1 .. .. .. .. 7.0 .. 3.0 .. .. 10.0 3.0 .. 15.0 5.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 14.0 .. .. .. .. .. .. 12.7 .. .. .. .. .. .. .. .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 9 14 .. .. .. .. .. 9 .. .. 7 .. 10 .. .. .. .. .. 18 .. .. 7 .. .. .. 7 .. .. 18 .. .. 5 .. .. .. 10 .. 3 ..

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

64

Part III. Development outcomes

TRADE

Drivers of growth

Table

6.2

Regional integration, trade blocs

Year established

Economic and Monetary Community of Central African States (CEMAC ) Economic Community of the Countries of the Great Lakes (CEPGL) Common Market for Eastern and Southern Africa (COMESA) Cross-Border Initiative (CBI) East African Community (EAC) Economic Community of Central African States (ECCAS) Economic Community of West African States (ECOWAS) Indian Ocean Commission (IOC) Mano River Union (MRU) Southern African Development Community (SADC) Central African Customs and Economic Union (UDEAC) West African Economic and Monetary Union (WAEMU/UEMOA)

Value of trade ($ millions) 1990

1995

2000

Share of total bloc exports (%) 2004

Share of world exports (%)

1990

1995

2000

2004

1990

1995

2000

2004

1994

139

120

97

176

2.3

2.1

1.1

1.3

0.2

0.1

0.1

0.2

1976

7

8

10

19

0.5

0.5

0.8

1.2

0.0

0.0

0.0

0.0

1994 1992 1996

963 613 230

1,386 1,002 530

1,536 1,058 485

2,848 1,700 753

6.6 10.3 13.4

7.7 11.9 17.4

5.7 10.6 16.1

6.7 13.2 14.6

0.4 0.2 0.1

0.4 0.2 0.1

0.4 0.2 0.1

0.5 0.1 0.1

1983

163

163

191

238

1.4

1.5

1.1

0.9

0.3

0.2

0.3

0.3

1975 1984 1973

1,557 73 0

1,936 127 1

2,835 106 5

3,973 155 6

7.9 4.1 0.0

9.0 6.0 0.1

7.9 4.4 0.4

8.5 4.3 0.3

0.6 0.1 0.1

0.4 0.0 0.0

0.6 0.0 0.0

0.5 0.0 0.0

1992

1,630

3,373

4,282

6,384

4.8

8.7

9.3

9.5

1.0

0.8

0.7

0.7

1964

139

120

96

174

2.3

2.1

1.0

1.2

0.2

0.1

0.1

0.2

1994

621

560

741

1,283

13.0

10.3

13.1

13.9

0.1

0.1

0.1

0.1

Note: Regional bloc memberships are as follows: Economic and Monetary Community of Central Africa (CEMAC), Cameroon, the Central African Republic, Chad, the Republic of Congo, Equatorial Guinea, Gabon, and São Tomé and Principe; Economic Community of the Countries of the Great Lakes (CEPGL), Burundi, the Democratic Republic of Congo, and Rwanda; Common Market for Eastern and Southern Africa (COMESA), Angola, Burundi, Comoros, the Democratic Republic of Congo, Djibouti, the Arab Republic of Egypt, Eritrea, Ethiopia, Kenya, Madagascar, Malawi, Mauritius, Namibia, Rwanda, Seychelles, Sudan, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe; Cross Border Initiative (CBI), Burundi, Comoros, Kenya, Madagascar, Malawi, Mauritius, Namibia, Rwanda, Seychelles, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe; East African Community (EAC), Kenya, 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, Rwanda, and São Tomé and Principe; Economic Community of West African States (ECOWAS), Benin, Burkina Faso, Cape Verde, Côte d’Ivoire, the Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Mauritania, Niger, Nigeria, Senegal, Sierra Leone, and Togo; Indian Ocean Commission (IOC), Comoros, Madagascar, Mauritius, Réunion, and Seychelles; Mano River Union (MRU), Guinea, Liberia, and Sierra Leone; Southern African Development Community (SADC; formerly Southern African Development Coordination Conference), Angola, Botswana, the Democratic Republic of Congo, Lesotho, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia, and Zimbabwe; Central African Customs and Economic Union (UDEAC; formerly Union Douanière et Economique de l’Afrique Centrale), Cameroon, the Central African Republic, Chad, the Republic of Congo, Equatorial Guinea, and Gabon; West African Economic and Monetary Union (UEMOA), Benin, Burkina Faso, Côte d’Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo.

TRADE

Part III. Development outcomes

65

Table

Drivers of growth

7.1

Water and sanitation Access, supply side

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

Access, demand side Population with sustainable access to an improved water source (% of population with access)

Population with sustainable access to improved sanitation (% of population with access)

Internal fresh water resources per capita (cubic meters)

Total

Urban

Rural

Total

Urban

Rural

2000–04a

2000–04a

2000–04a

2000–04a

2000–04a

2000–04a

2000–04a

13,607 1,488 1,742 1,074 555 16,970 .. 36,332 1,748 .. 16,932 59,086 4,574 .. 52,632 683 1,603 121,984 2,111 1,451 28,575 10,744 627 2,789 59,285 19,948 1,460 5,150 .. .. 5,268 2,978 340 1,620 596 .. 2,539 .. .. 623 982 894 .. 2,285 2,468 1,543 7,690 1,069

50 68 95 51 79 63 80 75 34 94 46 46 84 80 44 57 22 87 82 79 51 59 62 76 62 45 67 48 56 100 42 80 46 60 73 79 72 87 57 29 87 69 52 73 51 56 55 83

70 79 100 82 90 84 86 93 40 90 83 72 98 82 45 72 81 95 95 93 78 79 89 88 72 75 96 76 63 100 76 98 80 72 92 89 90 100 75 32 98 78 87 92 80 87 90 100

40 60 90 44 78 41 73 61 32 96 29 17 74 67 42 54 11 47 77 68 38 49 46 74 52 34 62 35 45 100 24 72 36 49 69 73 54 75 46 27 73 64 42 62 36 52 36 74

30 32 41 12 36 48 42 27 8 23 29 9 40 50 53 9 6 36 53 58 13 34 48 37 26 33 46 45 42 99 27 30 12 38 41 24 52 .. 39 25 67 34 52 46 34 41 45 57

56 58 57 45 47 63 61 47 30 38 43 14 61 55 60 34 19 37 72 74 25 57 56 61 49 49 66 59 64 100 51 66 43 48 56 32 70 .. 53 47 86 50 78 54 71 53 68 69

16 12 25 5 35 33 19 12 0 15 23 2 23 27 46 3 4 30 46 46 6 23 43 32 7 27 42 38 9 99 14 14 4 30 38 20 34 100 30 14 44 24 44 41 15 39 32 51

440 30 180 963 404

87 98 72 80 82

92 100 72 99 94

80 97 68 56 60

92 68 97 61 80

99 84 97 83 90

82 56 96 31 62

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

66

Part III. Development outcomes

INFRASTRUCTURE

Financing Quality of supply

Pricing

Average nonrevenue water (% of total water supplied)

Water supply failure for firms receiving water (average days per year)

Average household tariffs for water services, largest city ($ per cubic meter)

Committed nominal investment in potable water projects with private participation (2000 $ millions)

2000–04a

2000–04a

2000–04a

2000–04a

.. .. .. 21 44 34 .. .. .. .. .. .. 20 .. .. .. 40 16 .. .. .. .. 50 30 .. .. 30 27 .. .. 60 .. 17 .. .. .. 20 .. .. .. .. .. .. 40 .. .. 55 ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 79.2 .. .. .. .. .. .. 85.2 .. .. 5.2 .. 2.1 .. .. .. .. .. .. .. .. 5.6 .. .. .. 4.8 .. .. 105.0 .. 2.7 13.6 ..

.. .. 0.4 0.8 0.2 0.6 .. .. .. .. 0.7 .. 0.6 .. .. .. 0.4 0.5 .. .. .. .. 0.3 0.7 .. .. 0.3 0.5 .. .. 0.5 .. 0.5 0.4 .. ..

.. .. .. 31 14

41.8 8.5 .. .. ..

INFRASTRUCTURE

Average annual ODA disbursements for water and sanitation ($ millions) 2000–04

.. .. 0.4 .. .. 0.6 ..

.. .. .. .. .. .. .. .. 0.0 .. .. .. .. .. .. .. .. .. .. 0.0 .. .. .. .. .. .. .. 73.2 .. .. .. 0.0 3.4 .. 0.0 .. .. .. .. .. 6.3 .. .. 2.1 0.0 .. .. ..

3.4 7.9 2.5 14.9 0.8 3.1 1.8 1.1 8.1 0.2 2.2 0.2 4.2 2.8 1.1 1.3 12.1 0.0 0.5 21.7 8.7 1.1 14.8 2.8 0.1 3.7 5.2 9.4 5.3 7.1 15.7 2.8 6.4 3.6 2.5 0.8 9.9 0.0 1.1 1.2 8.1 2.1 1.0 16.5 3.6 18.8 15.5 4.1

0.2 0.9 .. 1.0 ..

182.0 .. .. 172.3 ..

7.7 48.4

.. .. ..

43.6 34.5

Part III. Development outcomes

67

Table

Drivers of growth

7.2

Transportation Access, supply side

Access, demand side Road density

Road network (km)

Total length 2000–04a

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

51,429 .. 25,233 .. .. 80,932 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 63,942 .. .. .. .. .. .. 2,015 .. 42,237 .. .. .. .. 13,576 11,300 .. .. 362,099 .. .. 78,891 .. 70,746 91,440 97,267 .. .. .. .. ..

Total length of national network 2000–04a

.. .. .. 15,272 4,478 21,083 .. .. .. .. 41,453 .. 15,413 .. .. 18,540 8,755 1,159 11,177 7,254 .. .. .. .. .. .. .. 13,013 .. .. 12,155 .. 9,677 .. 5,408 .. 10,261 .. .. .. .. .. .. 67,718 .. 10,500 .. ..

Energy Rural access consumption for (rural population Ratio to Ratio to Vehicle fleet transportation within 2 km of an allarable land total land Rail lines (road km/thousand (road km/thousand (thousand tons season road as % of Commercial Passenger (total route km) sq km arable land) sq km of land area) of oil equivalent) total rural population) vehicles cars 2000–04a 2000–04a 2000–04a 2000–04a 2000–04a 2000–04a 2000–04a

2,761 438 888 .. .. 988 .. .. .. .. 4,499 .. 639 .. .. 306 .. 731 .. 977 837 .. 2,634 .. 490 .. .. 733 717 .. .. .. .. 3,557 .. .. 906 .. .. .. 20,041 4,578 301 2,600 568 259 1,273 ..

5,637 58,051 19,505

1,919 1,939

.. .. .. 316 452 354 .. .. .. .. 619 .. 467 .. .. 3,299 79 357 3,548 173 .. .. .. .. .. .. .. 279 .. .. 279 .. 67 .. 451 .. 417 .. .. .. .. .. .. 1,693 .. 202 .. .. .. .. .. .. ..

.. .. .. 56 174 45 .. .. .. .. 18 .. 49 .. .. 184 9 5 1,118 32 .. .. .. .. .. .. .. 11 .. .. 16 .. 8 .. 219 .. 53 .. .. .. .. .. .. 77 .. 53 .. ..

884 371 .. .. .. 769 .. .. .. .. 285 220 .. .. .. 102 893 198 .. 1,168 .. .. 1,372 .. .. .. .. .. .. .. 309 529 .. .. .. .. 607 .. .. .. 14,834 1,469 .. .. 284 .. 328 644

.. 32 .. 25 .. 20 .. .. 5 .. 26 .. .. .. .. .. 17 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 37 47 .. .. .. .. .. .. .. .. .. 38 .. .. .. ..

129 122

.. .. .. .. ..

.. .. .. .. ..

.. .. 13,850 44,324 .. .. 25,749 44,805 .. .. 80,178 149,934 .. .. .. .. 21,082 13,050 .. .. .. .. .. .. 92,826 415,013 .. .. .. .. 385 6,774 52,169 67,614 18,170 28,005 .. .. 48,158 102,494 24,080 16,520 .. .. 96,726 244,836 .. .. .. .. .. .. 33,045 31,152 22,000 30,547 13,068 22,153 33,615 92,969 28,021 28,951 81,002 82,580 17,248 41,206 573,273 976,376 19,648 15,035 .. .. 35,753 98,260 .. .. 7,615 11,353 .. .. 2,386,968 4,162,933 .. .. 38,201 37,272 46,799 28,701 .. .. .. .. .. .. .. .. .. .. .. .. ..

.. .. .. .. ..

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

68

Part III. Development outcomes

INFRASTRUCTURE

Quality Pricing Financing Roads Average annual Average time to Firms identifying transport Average cost to Committed nominal Length of national Ratio of ship 20 ft container as major or very severe ship 20 ft container investment in transport ODA disbursements for transportation from port to final network in good obstacle to business paved to from port to final Price of Price of super projects with private and storage Existence of destination condition operation and growth total roads destination diesel fuel gasoline participation ($ millions) road fund (days) (km) (%) (%) ($) ($/liter) ($/liter) (2000 $ millions) 2000–04a 2000–04a 2000–04a 2000–04a 2000–04a 2000–04a 2000–04a 2000–04 2000–04 a 2000–04a

.. .. .. 52.7 24.1 8.9 .. .. .. .. 1.2 .. 44.4 .. .. 37.0 24.1 28.0 42.4 27.4 .. .. .. .. .. .. .. 18.5 .. .. 50.0 .. 65.2 .. .. .. 44.3 .. .. .. .. .. .. 43.6 .. 30.1 .. .. .. .. .. .. ..

INFRASTRUCTURE

10.4 .. 35.1 .. .. .. .. .. .. .. .. .. .. .. .. .. 12.9 3.7 19.3 17.9 9.8 .. 12.1 .. .. .. .. .. .. 100.0 .. 12.8 .. .. .. .. 29.3 .. 8.0 .. 20.3 .. .. 8.6 .. 23.0 22.0 19.0

.. .. .. 17.1 .. 17.1 .. .. .. .. 7.0 .. 3.0 .. .. 10.0 3.0 .. 15.0 5.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 14.0 .. .. .. .. .. .. 12.7 .. .. .. ..

56.4 65.4

.. .. .. .. ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 11.7 15.0 .. .. .. .. .. 37.4 .. .. 16.1 .. 20.1 .. .. .. .. .. 10.4 .. .. 36.0 .. .. .. 10.1 .. .. 22.9 .. 22.9 30.4 ..

4.6 4.6 4.9

.. .. .. 1,310 .. .. .. .. .. .. 2,400 .. .. .. .. 771 451 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1,310 .. .. .. .. .. .. .. .. .. .. ..

0.3 0.7 0.6 0.9 1.1 0.8 0.8 1.1 1.0 .. 0.8 0.6 0.9 .. .. 0.4 0.4 0.7 0.7 0.4 0.7 .. 0.8 0.7 0.8 0.8 0.9 0.9 0.6 0.6 0.8 0.6 0.9 0.5 1.0 .. 0.9 .. 0.9 0.9 0.8 0.3 0.7 0.9 0.8 0.9 1.0 0.7

0.4 0.8 0.7 1.2 1.0 0.9 1.4 1.3 1.2 .. 0.9 0.9 1.1 .. .. 0.8 0.6 0.9 0.8 0.5 0.8 .. 0.9 0.7 0.8 1.1 1.0 1.2 0.8 0.7 0.9 0.7 1.0 0.9 1.0 .. 0.9 .. 0.8 1.4 0.8 0.5 0.8 0.9 0.8 1.0 1.1 0.6

13.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 35.0 .. 5.8 0.0 0.0 21.4 0.0 1.3 0.0 0.0 0.0 0.0 0.0 5.1 0.0 0.0 0.0 0.0 158.1 112.5 0.0 5.7 0.0 0.0 0.0 0.0 0.0 0.0 63.1 0.0 0.0 1.6 0.0 0.0 0.0 0.0

3.0 25.5 0.0 16.4 0.8 32.7 2.2 8.6 13.2 0.1 2.1 0.7 2.0 .. 0.5 0.2 36.2 6.4 0.1 27.4 8.8 4.7 12.5 9.5 0.0 10.7 16.7 16.7 5.7 0.2 28.3 8.3 8.6 0.7 2.4 0.4 7.9 0.0 1.6 .. 0.5 0.0 1.7 33.7 0.3 12.5 26.6 3.8

Yes Yes .. No Yes Yes Yes Yes Yes .. No .. Yes .. .. Yes Yes Yes Yes Yes .. .. Yes Yes .. Yes Yes Yes .. .. Yes .. Yes No Yes .. No .. .. .. .. .. .. Yes Yes No Yes Yes

.. .. .. .. ..

.. 0.1 0.1 0.7 0.4

.. .. .. .. ..

.. 367.0 .. .. ..

0.8 5.1 .. 13.9 17.4

.. .. .. .. ..

Part III. Development outcomes

69

Table

Drivers of growth

7.3

Information and communication technology Access, supply side

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

Access, demand side

Total 2000–04a

Telephone subscribers (per 1,000 people) Main telephone line 2000–04a

Cellular telephone 2000–04a

84.4 54.0 38.2 395.8 37.4 12.5 102.7 281.1 17.6 14.4 26.5 37.0 102.4 98.3 43.4 106.2 14.0 7.8 387.6 99.0 92.7 15.3 7.9 85.0 109.1 2.8 19.5 25.0 36.2 134.5 699.9 26.9 206.1 12.8 79.1 18.2 78.9 72.4 841.9 27.2 87.9 473.1 58.5 118.7 32.2 48.1 44.4 33.7 55.2 .. 215.4 235.5 155.8 356.9 479.9

10.3 6.2 8.9 77.1 6.3 3.4 6.9 148.3 2.5 1.4 23.0 0.2 3.6 12.6 14.3 20.0 9.3 6.3 28.4 27.4 14.5 2.9 7.1 8.9 20.7 2.2 3.4 7.4 5.7 13.2 286.7 4.1 63.7 1.8 8.0 2.6 46.6 20.6 253.4 4.9 25.1 105.2 29.0 41.8 4.0 10.4 2.6 7.6 24.5 .. 70.7 130.3 133.2 43.9 121.2

74.1 47.8 29.8 318.7 31.0 9.1 95.8 132.8 15.1 13.0 3.5 36.8 98.8 85.7 30.1 112.8 4.7 2.5 359.2 118.4 78.2 12.4 0.9 76.1 88.4 14.7 18.4 17.6 30.5 175.3 413.2 36.4 142.4 11.0 71.1 15.6 32.2 90.3 588.6 22.3 62.8 428.5 29.5 100.9 43.6 37.7 41.9 26.1 30.7 .. 144.7 105.2 22.6 313.1 358.7

Unmet demand (% of main telephone lines in operation) 2000–04a

Households with own telephone Total Urban Rural (% of total (% of urban (% of rural households) households) households) 2000–04a 2000–04a 2000–04a

Delay for firm in obtaining a telephone connection (average number of days) 2000–04a

.. 44.5 .. 20.1 22.8 .. 1.1 13.3 .. 32.9 .. .. 1.4 .. .. 121.4 33.6 10.8 27.7 63.9 5.6 45.8 34.2 72.9 .. 3.1 23.8 .. .. 4.1 15.1 2.1 .. 0.0 .. 10.4 4.1 9.0 .. 625.0 1.0 99.1 49.0 4.9 53.7 .. 13.3 43.5

.. 3.7 .. 3.8 .. 1.8 .. .. .. .. .. .. .. .. .. 4.4 1.3 12.8 .. 6.9 .. .. 12.8 .. .. .. .. 2.4 2.9 .. 1.6 .. .. 5.5 1.1 .. .. .. .. .. .. .. .. .. .. 2.7 3.8 ..

.. 8.7 .. 17.6 .. 3.5 .. .. .. .. .. .. .. .. .. 11.3 7.9 17.2 .. 14.3 .. .. 32.7 .. .. .. .. 9.3 6.8 .. 5.5 .. .. 11.8 7.8 .. .. .. .. .. .. .. .. .. .. 14.5 10.2 ..

.. 0.7 .. 0.3 .. 0.1 .. .. .. .. .. .. .. .. .. 0.1 0.0 1.1 .. 0.7 .. .. 6.2 .. .. .. .. 0.1 0.2 .. 0.1 .. .. 1.9 0.1 .. .. .. .. .. .. .. .. .. .. 0.6 0.4 ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 256.3 130.8 .. .. .. .. .. 80.6 .. .. 54.1 .. 51.0 .. .. .. .. .. .. .. .. 10.8 .. .. .. 6.6 .. .. 18.3 .. 25.4 54.8 ..

.. 1.1 .. 0.4 11.3

.. 27.8 .. 51.8 ..

.. 44.7 .. 65.8 ..

.. 11.0 .. 29.0 ..

.. .. .. .. ..

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

70

Part III. Development outcomes

INFRASTRUCTURE

Quality

Pricing

Firms identifying telecommunications as major or very severe Duration of Reported obstacle to business telephone outages phone faults operation and growth (hours) (per 100 mainlines) (%) 2000–04a 2000–04a 2000–04a

Cost of cellular local call (US cents per 3 off-peak min) 2000–04a

Cost of local phone call (US cents per 3 peak min) 2000–04a

Cost of phone call to the United States (US cents per 3 min) 2000–04a

Financing Committed nominal Committed nominal investment in fixedinvestment in Average line and long distance mobile phone annual ODA projects with private projects with disbursements for participation private participation communications (2000 $ millions) (2000 $ millions) ($ millions) a 2000–04 2000–04a 2000–04

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 20.2 .. .. 14.3 .. 10.3 .. .. .. .. .. .. .. .. 9.5 .. .. .. .. .. .. 49.6 .. 17.8 40.0 ..

.. 6.0 .. 19.7 .. .. 43.0 .. 60.8 55.8 .. .. 81.0 .. .. 51.1 100.0 0.5 .. 67.4 1.6 70.5 149.0 75.0 .. 42.5 .. 177.6 .. 41.5 70.0 40.4 104.6 20.6 .. .. 17.3 6.0 .. .. 48.2 .. 70.0 24.0 6.2 .. 90.8 ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 9.0 29.4 .. .. .. .. .. 44.1 .. .. 16.4 .. 14.3 .. .. .. .. .. 59.4 .. .. 3.5 .. .. .. 3.0 .. .. 11.8 .. 3.5 32.9 ..

8.0 59.4 33.3 103.2 67.9 103.2 89.5 51.6 .. 73.4 .. .. 61.9 .. .. 0.0 10.5 64.5 47.8 70.9 45.6 0.0 57.1 25.6 0.0 58.0 64.5 98.2 .. 10.0 34.7 29.9 22.5 89.6 36.8 0.0 42.8 48.6 48.0 1.0 24.8 25.3 33.7 40.8 71.0 42.8 76.7 32.7

9.0 11.4 2.2 10.2 6.7 5.7 4.6 43.0 10.8 17.2 .. .. 9.1 .. .. 2.9 2.3 25.8 2.8 2.5 7.6 .. 9.4 22.2 .. 7.3 5.9 7.0 11.4 4.3 7.9 4.4 10.2 10.0 8.8 16.5 20.3 16.2 2.9 5.0 14.7 3.4 5.2 12.1 10.2 20.9 9.1 1.3

134.0 576.2 .. 258.0 371.0 .. .. 1,359.0 910.6 .. .. .. 638.0 .. .. 355.0 705.0 1,088.0 346.0 113.0 461.4 .. 436.0 230.7 .. 741.0 6.0 1,227.8 .. 250.0 .. 427.5 876.6 .. .. 495.0 180.9 .. .. .. 58.3 391.8 242.0 528.0 215.0 351.0 645.0 436.3

.. .. .. .. .. .. 0.0 .. .. .. .. .. 0.0 .. .. .. .. .. .. 11.7 6.0 5.0 .. 18.7 .. 12.6 .. .. 24.0 101.5 54.5 .. 25.8 409.2 .. 2.4 65.8 .. .. 0.5 1,115.3 62.0 .. 43.6 .. 37.4 .. ..

69.7 21.4 17.0 8.4 10.7 73.1 0.0 .. 2.8 .. 86.3 12.4 23.0 .. 0.0 40.0 .. 5.3 3.3 20.2 4.5 6.3 157.4 17.1 25.0 0.0 2.3 27.5 29.9 101.1 27.3 8.8 20.0 1,036.8 7.9 .. 68.5 7.2 9.7 0.5 713.5 136.2 4.9 78.2 0.0 48.5 16.3 14.8

5.1 0.2 0.1 1.4 0.3 2.6 0.1 0.2 0.5 0.0 0.2 0.0 0.1 .. .. 0.3 0.9 0.5 0.0 0.4 0.2 0.4 0.3 0.0 0.0 0.7 0.4 2.0 0.0 0.2 3.3 0.6 0.2 0.8 0.9 0.2 0.3 0.0 0.6 0.2 1.8 0.1 0.1 5.6 0.1 0.5 0.4 11.2

.. .. .. .. ..

.. 0.5 .. 24.8 28.0

.. .. .. .. ..

.. 12.8 .. 32.7 40.7

.. 1.5 .. 16.9 2.3

.. 257.0 .. 163.0 228.0

.. .. .. .. ..

.. .. .. .. ..

0.7 0.4 0.0 1.1 18.1

INFRASTRUCTURE

Part III. Development outcomes

71

Table

Drivers of growth

7.4

Energy Access, supply side Installed capacity (MW) 2000–04a

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

Access, demand side Energy use per PPP GDP (kg of oil Electric power equivalent per consumption 2000 PPP $, (kWh per capita) thousands) 2000–04a 2000–04a

618.0 120.6 132.0 121.0 43.0 880.0 7.0 39.9 29.0 5.0 2,515.5 121.0 915.0 .. 12.0 .. 533.8 403.3 29.0 1,227.5 261.3 21.0 1,084.3 75.8 330.0 285.0 272.5 208.5 114.5 582.6 2,378.0 .. 105.0 5,888.0 34.3 10.1 237.5 28.0 124.0 79.5 41,365.5 727.3 127.5 847.3 35.5 291.5 1,786.0 1,942.0

103.5 12.2 538.5 36.6 18.0 212.2 87.3 .. 10.9 34.2 109.9 77.3 219.4 45.4 44.4 25.7 957.3 162.2 334.1 97.4 63.9 119.7 173.6 112.2 48.5 68.8 46.7 65.4 1,487.6 462.6 695.4 26.7 140.2 19.9 105.9 166.3 2,573.9 33.8 24.2 4,559.5 71.3 359.0 67.8 9.1 68.5 739.4 532.0

6,400.0 .. 4,700.0 17,600.0 2,900.0

913.5 1,337.4 3,338.5 592.1 1,239.6

312.9 329.7 .. .. .. 212.6 .. .. .. .. 463.4 268.0 267.4 .. .. .. 417.3 196.3 .. 201.0 .. .. 498.1 .. .. .. .. .. .. .. 433.1 98.5 .. 788.9 .. .. 208.3 .. .. .. 256.6 278.2 .. 728.8 203.0 .. 792.4 333.3

215.2 99.0 130.0

Access to electricity Total (% of total population) 2000–04a

Solid fuels use

Urban access (% of urban population) 2000–04a

Rural access (% of rural population) 2000–04a

Total (% of total population) 2000–04a

Urban (% of urban population) 2000–04a

Rural (% of rural population) 2000–04a

6.7 20.9 38.5

.. 49.6 .. 39.7 45.1 84.6 .. 8.0 9.4 51.8 .. .. 85.9

.. 5.5 .. 0.2 0.4 21.0 .. 0.3 0.1 19.6 .. .. 22.5

95.0 95.0 .. 95.0 99.8 83.0 .. .. 95.0 .. .. 84.0 74.0

.. 87.5 .. .. 98.1 62.2 .. .. .. .. .. .. ..

.. 98.7 .. .. 99.9 98.2 .. .. .. .. .. .. ..

.. 17.0 4.7 31.0 5.0 50.0 5.0 7.9 7.9 5.0 .. 8.0 5.0 7.6 50.0 100.0 7.2 34.0 7.9 40.0 5.0 .. 30.1 .. 5.0 .. 66.1 30.0 20.0 10.5 9.0 3.7 12.0 39.7

.. 80.6 76.2 .. .. 82.4 53.8 .. 47.5 .. .. 47.8 28.7 37.0 49.7 .. 25.8 .. 36.5 84.3 38.9 .. 68.9 .. .. .. .. .. .. 27.3 41.2 43.9 45.1 87.4

.. 2.1 0.4 .. .. 20.9 1.5 .. 4.3 .. .. 5.2 1.0 2.2 2.5 .. 2.1 .. 0.2 27.9 0.9 .. 6.0 .. .. .. .. .. .. 1.1 2.4 2.4 2.9 8.3

.. 79.7 95.0 .. .. 88.0 .. .. 81.8 83.0 .. 98.6 95.0 97.9 .. .. .. 63.0 97.8 85.7 99.8 .. 41.0 .. .. .. .. .. .. .. .. 96.8 85.0 73.0

.. 30.4 72.9 .. .. 88.0 .. .. 33.8 .. .. 96.2 83.0 98.4 .. .. .. .. 94.8 57.4 98.1 .. .. .. .. .. .. .. .. .. .. 85.0 62.4 4.7

.. 97.4 99.9 .. .. 99.4 .. .. 94.7 .. .. 98.9 99.6 99.8 .. .. .. .. 98.4 94.2 99.9 .. .. .. .. .. .. .. .. .. .. 98.7 98.1 93.6

98.0 93.8 99.8 71.1 94.6

.. .. .. .. ..

.. .. .. .. ..

5.0 5.0 5.0 5.0 5.0

.. .. .. .. ..

.. .. .. .. ..

12.0 22.0 22.0 13.0 5.0 20.0 .. 5.0 3.0

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

72

Part III. Development outcomes

INFRASTRUCTURE

Quality Delay for firm in Electric power obtaining electrical transmission and connection (average number distribution losses (% of output) of days) 2000–05a 2000–04a

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

.. .. .. 65.4 105.5 .. .. .. .. .. 43.7 .. .. 49.5

.. 17.4 .. 8.0 .. .. 15.0 .. 30.0 .. .. .. .. 18.0 23.0 .. ..

25.6 142.4 ..

.. .. 18.7 .. .. .. .. .. 26.0 .. 21.0 .. .. 34.0 22.0 .. 17.5 .. 33.0 .. .. .. .. 24.0 .. 19.6 .. 3.6

.. .. .. .. ..

.. 21.0 .. 6.0 ..

32.0 .. .. .. .. .. .. .. .. 10.3 .. .. .. 5.3 .. .. 44.0

INFRASTRUCTURE

Electrical outages of firms (average number of days per year) 2000–05a

Pricing Firms that share or own their own generator (% of total) 2000–05a

Firms identifying electricity as major or very severe obstacle to business operation and growth (%) 2000–05a

Electricity end-user prices (US cents per kWh) Households 2000–04a

Industry 2000–04a

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

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

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

.. .. 4.0 .. .. .. .. .. .. ..

.. .. 2.9 .. .. .. .. .. .. ..

.. .. .. 93.9 .. .. .. .. .. .. 83.6 .. .. 78.0

.. .. .. 43.0 17.1 .. .. .. .. .. 70.9 .. .. 21.5

.. .. .. 38.2 42.5 .. .. .. .. .. 48.1 .. .. 41.3

10.5 .. .. .. .. .. .. .. .. 26.1 .. .. .. 5.5 .. .. 60.6

45.3 .. .. .. .. .. .. .. .. 62.5 .. .. .. 9.5 .. .. 55.4

24.2 .. .. .. .. .. 97.4 .. .. 30.7 .. .. .. 9.0 .. .. 58.9

.. .. .. .. .. .. .. .. .. .. 8.2 8.0 .. .. 4.4 .. .. 14.3 3.1 3.6 .. 7.0 .. .. .. .. .. .. 3.1 .. 3.9 5.1

.. .. .. .. .. .. .. .. .. .. 6.7 2.6 .. .. 4.7 .. .. 10.0 2.2 2.4 .. .. .. .. .. .. .. .. 2.0 .. 3.1 8.6

70.8 30.0 ..

36.0 38.2 ..

44.5 39.6 ..

8.6 2.4 5.7

6.6 2.6 10.3

11.5 26.5 .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

16.7

Financing Committed nominal Average investment in annual ODA energy projects disbursements with private for energy participation ($ millions) (2000 $ millions) a 2000–04 2000–04

42.1 .. .. .. .. 44.5 143.4 .. .. .. .. .. .. .. .. .. 280.6 .. .. 167.7 .. .. .. .. .. .. .. 697.3 .. .. 1,122.5 1.0 .. 227.1 .. .. .. .. .. .. 388.7 .. .. 330.8 67.7 16.9 12.4 ..

659.6 336.8

4.4 0.9 0.2 1.9 0.2 2.3 0.1 0.6 1.4 0.4 0.1 0.0 3.2 .. 0.1 4.6 1.1 .. 0.1 8.6 1.7 0.2 21.3 0.2 .. 0.6 4.4 3.4 1.1 0.1 25.9 1.7 0.4 6.4 0.7 0.6 4.5 .. 0.2 0.1 1.4 0.0 0.0 10.0 0.1 3.3 1.4 0.9 0.9 44.1 0.0 25.2 0.2

Part III. Development outcomes

73

Table

Drivers of growth

7.5

Financial sector infrastructure Macroeconomy

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

Sovereign ratings (long-term foreign currency)

Gross national savings (% of GDP)

2006

2004

2004

.. B .. ..

.. .. .. .. .. .. CCC B+ .. .. .. BB– .. .. CCC B– .. .. B BBB– .. BB– .. .. .. .. .. .. BBB+ .. .. .. .. .. .. ..

13 9 42 10 8 17 14 13 18 8 7 27 14 .. .. –21 14 29 14 23 5 10 17 36 29 14 –5 11 –5 24 12 40 6 27 –1 –33 17 18 6 .. 19 17 19 8 6 10 10 3

.. BB+ .. .. BBB

34 23 .. 24 26

B– B+ .. .. ..

Size

Claims on governments and Money and quasi other public entities money (M2) (% of GDP) (% of GDP)

Bank assets

Real interest rate (%)

Value ($ millions)

Share of GDP (%)

2004

2004

2004

2004

–1 –5 –22 –1 16 5 31 10 5 1 0 9 4 6 –19 109 35 3 8 17 12 7 10 –8 213 5 11 –2 .. 23 3 .. 5 –3 .. 8 1 103 25 .. 3 4 –4 0 1 4 27 25

13 25 28 24 26 18 69 15 8 23 7 13 23 70 11 147 53 16 40 29 15 25 37 28 15 22 20 30 .. 85 25 .. 13 22 .. 48 34 110 17 .. 62 16 20 22 26 19 19 25

28 .. 10 .. 11 18 10 20 4 8 .. 10 .. 8 29 .. –2 10 19 .. .. .. 5 10 16 10 23 .. .. 14 8 8 .. –1 .. 20 .. 6 5 .. 5 .. 6 10 .. 14 9 –16

3,825 1,144 2,801 1,162 201 2,839 753 134 311 64 436 384 3,468 536 428 1,313 4,722 1,478 163 3,121 529 27 7,096 396 123 975 348 1,496 396b 6,132 1,680 2,507 343 22,153 330 38c 2,737 941 160 .. 219,303 2,332 633 2,196 594 1,738 1,392 5,979

19.0 28.1 32.3 24.1 30.6 19.3 79.4 10.2 7.3 17.4 6.6 8.8 22.7 80.9 13.2 142.0 58.5 20.4 39.2 36.2 15.1 9.6 45.5 28.8 27.5 22.3 19.2 30.8 25.8b 84.3 30.3 45.9 11.1 30.7 17.9 61.4c 35.7 133.7 14.9 .. 103.1 11.9 26.2 20.2 28.8 25.4 25.8 33.7

14 50 –20 17 6

57 89 31 90 55

–2 2 –11 10 ..

42,860 95,367 13,162 47,828 20,409

50.6 121.0 45.2 95.6 72.4

a. Data are consolidated for regional security markets where they exist. b. Data are for 2003. c. Calculated using 2003 exchange rate.

74

Part III. Development outcomes

INFRASTRUCTURE

Capital marketsa

Intermediation Domestic credit to private sector (% of GDP)

Interest rate spread (lending rate minus deposit rate)

Ratio of bank nonperfoming loans to total (%)

2004

2004

2004

2004

2004

2004

2004

5 14 19 15 23 10 37 7 3 9 2 3 14 21 4 33 24 9 12 13 4 2 27 7 6 10 8 20 .. 59 2 .. 6 16 .. 33 21 37 5 .. 141 8 20 9 16 7 8 22

67 .. 6 .. .. 13 9 13 13 8 .. 13 .. 10 13 .. 4 13 15 .. .. .. 10 8 14 10 23 .. .. 13 12 5 .. 5 .. 18 .. 7 12 .. 5 .. 7 10 .. 13 19 176

13.3 .. 2.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 15.8 .. 16.1 .. .. 22.9 .. .. 11.4 .. .. .. .. 6.4 .. .. 21.6 .. .. 14.2 .. 14.8 .. 1.8 .. .. .. .. 2.2 7.6 ..

.. .. 3.8 .. .. .. .. .. .. .. .. .. .. .. .. .. 0.4 .. .. 1.6 .. .. 1.4 .. .. 0.7 .. .. .. 11.9 .. 4.5 .. 1.6 .. .. .. .. .. .. 6.0 .. .. 0.6 .. 0.5 1.5 3.3

.. .. 18 .. .. .. .. .. .. .. .. .. 39 .. .. .. .. .. .. 29 .. .. 47 .. .. .. .. .. .. 41 .. 13 .. 207 .. .. .. .. .. .. 403 .. 6 6 .. 5 11 79

.. .. 28.4 .. .. .. .. .. .. .. .. .. 13.5 .. .. .. .. .. .. 29.8 .. .. 24.2 .. .. .. .. .. .. 39.4 .. 7.7 .. 20.1 .. .. .. .. .. .. 214.1 .. 9.4 6.2 .. 1.4 8.0 41.3

.. .. 2 .. .. .. .. .. .. .. .. .. 3 .. .. .. .. .. .. 3 .. .. 8 .. .. .. .. .. .. 4 .. 5 .. 14 .. .. .. .. .. .. 47 .. .. .. .. .. .. 9

11 55 17 57 65

6 6 4 8 ..

.. 24.2 .. 19.4 23.7

.. 3.6 .. 6.6 ..

.. 792 .. 52 44

.. 48.9 .. 50.1 9.4

.. 17 .. 9 9

INFRASTRUCTURE

Bank branches (per 100,000 people)

Listed domestic companies

Market capitalization of listed companies (% of GDP)

Turnover ratio for traded stocks (%)

Part III. Development outcomes

75

Table

Participating in growth

8.1

Education Literacy rate (%)

Youth

Primary education Gross enrollment ratio (% of relevant age group)

Adult

Total Male Female Total Male Female 2000–04a 2000–04a 2000–04a 2000–04a 2000–04a 2000–04a

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

.. 72 45 94 31 73 .. .. 59 38 .. 70 .. 61 .. 95 .. .. .. .. 71 47 .. 80 .. .. 70 76 24 61 95 .. 92 37 .. 78 .. 49 99 48 .. 94 77 88 78 74 77 69 .. .. 90 .. .. 70 94

.. 84 59 92 38 77 .. .. 70 56 .. 78 .. 71 .. 95 .. .. .. .. 76 59 .. 80 .. .. 73 82 32 68 94 .. 91 52 .. 79 .. 58 99 59 .. 93 85 87 81 84 83 73 .. .. 94 .. .. 81 96

.. 63 33 96 25 70 .. .. 47 23 .. 63 .. 52 .. 95 .. .. .. .. 65 34 .. 81 .. .. 68 71 17 55 95 .. 93 23 .. 77 .. 41 99 37 .. 94 71 90 76 64 71 66 .. .. 86 .. .. 60 92

.. 67 35 81 22 59 68 .. 49 26 .. 67 .. 49 .. 87 .. .. .. .. 58 29 .. 74 82 .. 71 64 19 51 84 .. 85 29 .. 65 .. 39 92 35 .. 82 61 80 69 53 67 68 .. .. 70 .. .. 52 74

.. 83 48 80 29 67 77 .. 65 41 .. 81 .. 61 .. 93 .. .. .. .. 66 43 .. 78 74 .. 77 75 27 60 88 .. 87 43 .. 71 .. 51 91 47 .. 84 71 81 78 69 77 76 .. .. 80 .. .. 66 83

.. 54 23 82 15 52 60 .. 33 13 .. 54 .. 39 .. 80 .. .. .. .. 50 18 .. 70 90 .. 65 54 12 43 81 .. 83 15 .. 60 .. 29 92 24 .. 81 52 78 62 38 58 60 .. .. 60 .. .. 40 65

Net enrollment ratio (% of relevant age group)

Total 2004

Male 2004

Female 2004

Total 2004

Male 2004

Female 2004

Studentteacher ratio 2004

93 .. 99 104 53 80 114 111 64 71 85 64 89 72 39 99 66 77 130 79 81 79 70 111 131 99 134 125 64 94 103 95 101 45 99 119 131 76 113 79 .. 105 60 101 101 101 125 99 96 .. 112 100 112 106 111

98 .. 111 105 59 87 123 113 76 86 91 .. 92 80 44 102 74 85 130 82 84 87 84 114 131 115 136 123 71 95 103 104 100 52 107 118 134 78 116 93 .. 107 64 103 103 110 126 101 97 .. 116 103 113 111 113

87 .. 86 104 47 73 105 108 52 56 80 .. 85 63 35 96 59 69 129 75 79 71 56 108 131 83 131 126 56 93 103 86 102 37 91 120 129 74 110 65 .. 103 56 98 99 92 125 97 95 .. 107 98 112 100 109

64 .. 83 82 40 57 .. 92 .. 57 55 .. .. 56 33 59 48 46 77 73 58 64 45 76 86 66 89 95 46 74 95 71 74 39 88 73 .. 66 100 .. .. 89 43 77 86 79 98 80 82 .. 97 94 .. 87 97

68 .. 93 80 46 60 .. 92 .. 68 60 .. .. 62 36 61 52 49 77 76 62 69 53 76 83 74 89 93 50 75 94 75 71 46 95 72 .. 68 100 .. .. 88 47 76 87 85 97 80 81 .. 98 96 .. 89 97

60 .. 72 84 35 54 .. 91 .. 46 50 .. .. 50 29 58 44 44 77 70 62 58 37 77 88 58 89 98 43 74 96 67 76 32 81 75 .. 64 99 .. .. 89 39 77 85 72 99 80 82 .. 96 93 .. 84 97

49 .. 52 26 49 51 53 27 .. 69 35 .. 83 42 34 30 47 65 36 37 32 45 44 40 44 38 52 .. 52 45 22 65 28 44 36 62 33 43 14 37 .. 34 29 31 58 44 50 49 39 .. 27 22 .. 28 22

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

76

Part III. Development outcomes

HUMAN DEVELOPMENT

Secondary education Gross enrollment ratio (% of relevant age group)

Tertiary education Gross enrollment ratio (% of relevant age group)

Public spending on education (%)

Total

Male

Female

Total

Male

Female

Share of government expenditure

Share of GDP

2004

2004

2004

2001

2001

2001

2000–05a

2002

30 17 26 74 12 12 44 66 12 15 35 23 32 25 22 30 28 28 50 34 42 26 18 48 36 32 .. 29 22 20 80 11 58 8 35 14 39 19 112 26 .. 90 33 42 .. 39 19 26 36 .. 81 87 104 47 77

33 19 34 71 14 14 46 63 .. 23 40 24 37 32 25 38 35 34 49 40 45 34 23 50 32 37 .. 32 28 22 78 13 54 9 38 15 42 22 113 31 .. 87 34 42 .. 52 21 29 38 .. 78 90 101 51 74

26 15 18 76 10 10 42 69 .. 7 30 12 27 18 18 22 21 21 42 28 38 17 13 46 41 27 .. 26 17 18 82 9 62 6 31 14 36 16 111 22 .. 94 32 42 .. 26 17 23 35 .. 84 84 107 43 80

5 1 3 6 1 2 5 6 2 1 2 .. 4 .. 2 3 1 2 .. 1 3 2 0 .. 3 16 3 0 2 3 17 1 6 1 10 3 1 5 .. 2 .. 15 6 4 1 4 3 2 4 .. 20 29 56 11 26

.. 1 5 7 2 3 6 5 3 1 3 .. 6 .. 2 4 2 4 .. 2 4 4 1 .. 2 18 3 1 3 5 14 2 6 1 13 3 1 .. .. 3 .. 14 6 4 2 6 4 3 5 .. 19 .. 54 11 23

.. 1 1 6 1 1 4 6 1 0 2 .. 1 .. 1 2 0 1 .. 0 2 1 0 .. 3 13 2 0 1 2 20 1 7 0 7 2 1 .. .. 1 .. 17 6 5 1 1 3 1 3 .. 20 .. 59 10 29

.. .. .. 25.6 .. 13.0 17.2 20.7 .. .. 24.1 .. 12.6 21.5 20.5 1.6 .. 20.4 .. 8.9 .. 25.6 .. 29.2 18.5 .. 18.2 .. .. .. 15.7 .. 21.0 .. .. .. .. .. .. .. .. 18.1 .. .. .. 13.6 18.3 14.8 .. .. .. .. .. 27.8 18.2

3.4 3.0 3.3 2.2 .. 5.2 3.8 7.3 .. .. 3.9 .. 3.2 4.6 6.1 0.6 3.8 6.1 3.9 1.9 .. 1.8 .. 7.0 9.0 .. 3.3 6.0 .. 3.4 4.7 .. 7.2 2.3 .. 2.8 .. 4.0 5.4 3.7 .. 5.4 .. 6.2 .. 2.6 5.2 2.8 4.7 .. .. .. .. 6.3 6.4

HUMAN DEVELOPMENT

Part III. Development outcomes

77

Table

Participating in growth

8.2

Health Mortality Life expectancy at birth (years)

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

78

Diseases

Under-five mortality rate (per,1 000)

Male 2004

Female 2004

Male 2004

Female 2004

38 52 40 47 42 50 67 40 45 62 42 53 41 54 42 58 49 55 55 56 52 45 51 39 39 55 41 44 55 69 44 52 42 45 44 57 54 67 37 .. 47 .. 36 47 52 48 40 ..

42 53 40 48 47 51 71 41 48 67 47 55 47 57 44 62 51 59 59 58 55 48 50 44 44 59 41 47 60 75 46 55 41 46 47 60 57 78 40 .. 49 .. 39 49 56 51 40 ..

276 152 123 193 196 156 38 201 212 76 217 113 225 131 213 89 175 102 129 113 160 212 129 87 249 128 179 230 134 17 154 70 256 198 211 122 141 14 296 .. 72 .. 163 134 151 144 190 ..

69 66 70 69 70

72 70 75 73 74

41 36 20 47 29

Part III. Development outcomes

Infant Maternal mortality rate mortality ratio (per 1,000 (per 100,000 live births) live births)

Deaths due to HIV/AIDS (thousands)

Prevalence of HIV (% ages 15–49)

Incidence of Deaths due to tuberculosis malaria (per 100,000 (per 100,000 people) people)

2004

2000

2005

2005

2004

1997–2004b

243 153 109 191 184 143 35 185 188 64 192 103 162 120 195 75 158 80 115 111 150 194 110 76 220 117 172 208 115 14 150 57 262 195 195 114 132 13 269 .. 62 .. 150 117 128 132 173 ..

154 90 84 97 114 87 27 115 117 52 129 81 117 101 122 52 110 60 89 68 101 126 79 80 157 76 110 121 78 14 104 47 152 101 118 75 78 12 165 133 54 63 108 78 78 80 102 79

1,700 850 100 1,000 1,000 730 150 1,100 1,100 480 990 510 690 730 880 630 850 420 540 540 740 1,100 1,000 550 760 550 1,800 1,200 1,000 24 1,000 300 1,600 800 1,400 .. 690 .. 2,000 1,100 230 590 370 1,500 570 880 750 1,100

30 10 18 12 13 46 .. 24 11 <0.1 90 11 65 1 <1 6 .. 5 1 29 7 3 140 23 .. 3 78 11 <1 <0.1 140 17 8 220 21 .. 5 .. 5 4 320 34 16 140 9 91 98 180

3.7 1.8 24.1 2.0 3.3 5.4 .. 10.7 3.5 <0.1 3.2 5.3 7.1 3.1 3.2 2.4 .. 7.9 2.4 2.3 1.5 3.8 6.1 23.2 .. 0.5 14.1 1.7 0.7 0.6 16.1 19.6 1.1 3.9 3.1 .. 0.9 .. 1.6 0.9 18.8 1.6 33.4 6.5 3.2 6.7 17.0 20.1

259 87 670 191 343 179 172 322 279 46 366 377 393 734 239 271 353 280 233 206 240 199 619 696 310 218 413 281 287 64 460 717 157 290 371 107 245 34 443 411 718 220 1,226 347 355 402 680 674

354 177 .. 292 .. .. .. .. .. .. 224 .. .. .. .. 74 198 .. .. 70 .. .. 63 .. 201 .. 275 454 .. .. 232 .. 469 141 200 .. 72 .. .. .. .. 70 .. 130 .. 152 141 ..

39 36 19 38 22

35 26 18 38 21

140 84 97 220 120

<0.5 <0.5 .. 1 <0.1

0.1 <0.1 .. 0.1 0.1

54 27 20 110 22

.. .. .. .. ..

HUMAN DEVELOPMENT

Prevention and treatment

Child immunization rate (% of children ages 12–23 months)

Contraceptive prevalance rate (%) 1997–2004b

Children sleeping under insecticidetreated bednets (% of children under age 5) 2000–04b

People with advanced HIV infection receiving antiretroviral combination therapy (%) 2005

Tuberculosis cases detected under DOTS (% of estimated cases) 2004

Children with DOTS treatment fever receiving success rate antimalarial drugs (% of (% of children registered cases) under age 5 with fever) 2003 2001

Measles 2004

DPT3a 2004

Births attended by skilled health staff (%) 2000–04b

64 85 90 78 75 64 69 35 56 73 64 65 49 60 51 84 71 55 90 83 73 80 73 70 42 59 80 75 64 98 77 70 74 35 84 91 57 99 64 40 81 59 70 94 70 91 84 80

59 83 97 88 74 73 75 40 50 76 64 67 50 64 33 83 80 38 92 80 69 80 73 78 31 61 89 76 70 98 72 81 62 25 89 99 87 99 61 .. 93 .. 83 95 71 87 80 ..

45 66 94 38 25 62 .. 44 14 62 61 .. 68 61 65 28 6 86 55 47 56 35 42 60 51 51 61 41 57 99 48 76 16 35 31 76 58 .. 42 25 .. 87 74 46 61 39 43 ..

6 19 48 14 16 26 53 28 3 26 31 .. 15 .. .. 8 8 33 18 25 7 8 39 30 10 27 31 8 8 76 17 44 14 13 13 29 11 .. 4 .. 56 7 48 25 26 23 34 54

2.3 7.4 .. 1.6 1.3 0.9 .. 1.5 0.6 9.3 0.7 .. 1.1 .. 0.7 4.2 .. .. 14.7 3.5 .. 7.4 4.6 .. .. 0.2 35.5 .. 2.1 .. .. .. 1.0 1.2 5.0 22.8 1.7 .. 1.5 .. .. .. 0.1 2.1 2.0 0.2 6.5 ..

6 33 85 24 14 36 .. .. 3 43 4 .. 80 16 0 5 7 23 9 7 9 1 24 14 3 0 20 31 40 .. 9 71 5 6 39 .. 47 .. 2 .. 21 .. 31 7 27 51 26 ..

94 82 67 18 29 91 .. 4 16 39 70 65 38 43 82 14 36 81 66 37 52 75 46 86 58 74 40 19 43 33 46 88 46 21 29 .. 52 106 36 44 83 35 38 47 17 43 54 42

68 81 77 66 79 .. .. 59 78 .. 83 69 72 73 51 85 70 34 75 66 75 80 80 70 73 71 73 65 58 87 76 63 70 59 67 .. 70 100 83 .. 67 .. 42 81 63 68 75 ..

63 60 .. 50 31 53 .. 69 56 63 45 .. 58 .. 49 4 3 .. 55 63 .. 58 27 .. .. 41 32 38 33 .. .. 14 48 34 13 61 36 .. 61 .. .. .. 26 53 60 .. 52 ..

81 97 99 95 95

86 97 97 97 97

96 69 .. 63 90

57 60 .. 63 66

.. .. .. .. ..

39 12 35 48 34

105 61 169 80 95

90 80 62 86 91

.. .. .. .. ..

(continues) HUMAN DEVELOPMENT

Part III. Development outcomes

79

Table

Participating in growth

8.2

Health (continued) Water and sanitation Population with sustainable access to improved water source (%)

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

Human resources

Population with sustainable access to improved sanitation (%)

Expenditure on health General government Out-of-pocket expenditure on health expenditure (%) (% of general Health workers government Share of total Share of total (per 1,000 people) expenditure expenditure government on health) on health Physicians Nurses Midwives expenditure 1997 1997 1997 2003 2003 2003

Per capita government expenditure on health at average exchange rate 2003

Total 2002

Urban 2002

Rural 2002

Total 2002

Urban 2002

Rural 2002

50 68 95 51 79 63 80 75 34 94 46 46 84 80 44 57 .. 87 82 79 51 59 62 76 62 45 67 48 56 100 42 80 46 60 73 79 72 87 57 .. 87 .. 52 73 51 56 55 ..

70 79 100 82 90 84 86 93 40 90 83 72 98 82 45 72 81 95 95 93 78 79 89 88 72 75 96 76 63 100 76 98 80 72 92 89 90 100 75 .. 98 .. 87 92 80 87 90 ..

40 60 90 44 78 41 73 61 32 96 29 17 74 67 42 54 11 47 77 68 38 49 46 74 52 34 62 35 45 100 24 72 36 49 69 73 54 75 46 .. 73 .. 42 62 36 52 36 ..

30 32 41 12 36 48 42 27 8 23 29 9 40 50 53 9 .. 36 53 58 13 34 48 37 26 33 46 45 42 99 27 30 12 38 41 24 52 .. 39 .. 67 .. 52 46 34 41 45 ..

56 58 57 45 47 63 61 47 30 38 43 14 61 55 60 34 19 37 72 74 25 57 56 61 49 49 66 59 64 100 51 66 43 48 56 32 70 .. 53 .. 86 .. 78 54 71 53 68 ..

16 12 25 5 35 33 19 12 0 15 23 2 23 27 46 3 4 30 46 46 6 23 43 32 7 27 42 38 9 99 14 14 4 30 38 20 34 100 30 .. 44 .. 44 41 15 39 32 ..

0.1 0.0 0.4 0.1 0.0 0.2 0.5 0.1 0.0 0.1 0.1 0.2 0.1 0.2 0.3 0.1 0.0 0.3 0.1 0.2 0.1 0.1 0.1 0.0 0.0 0.3 0.0 0.1 0.1 1.1 0.0 0.3 0.0 0.3 0.0 0.5 0.1 1.5 0.0 .. 0.8 .. 0.2 0.0 0.0 0.1 0.1 ..

1.1 0.8 2.6 0.4 0.2 1.6 0.9 0.3 0.3 0.7 0.5 1.0 0.6 0.4 0.4 0.6 0.2 5.2 1.2 0.9 0.6 0.7 1.1 0.6 0.2 0.3 0.6 0.5 0.6 3.7 0.2 3.1 0.2 1.7 0.4 1.6 0.3 7.9 0.4 .. 4.1 .. 6.3 0.4 0.4 0.6 1.7 ..

0.0 .. .. 0.1 .. .. .. 0.1 0.0 .. .. .. .. 0.1 0.1 .. 0.0 .. 0.1 .. 0.0 0.0 .. .. 0.1 .. .. 0.0 .. 0.0 0.1 .. 0.0 .. 0.0 0.3 .. .. .. .. .. .. .. .. 0.0 0.1 0.3 ..

84 43 58 47 23 29 73 39 40 54 18 64 28 67 68 46 58 67 40 32 17 46 39 80 57 63 35 57 77 61 62 70 53 26 44 84 42 73 58 .. 39 .. 57 55 25 30 51 ..

5 10 8 13 2 8 11 12 11 6 5 4 5 11 7 4 10 13 14 5 5 7 7 10 18 9 9 9 14 9 11 12 12 3 7 11 9 10 8 .. 10 .. 11 13 9 11 12 ..

100 90 29 98 100 98 100 95 96 100 100 100 91 100 81 100 79 100 67 100 99 80 83 18 99 92 43 89 100 100 39 19 89 91 42 100 95 63 100 .. 17 .. 42 81 88 53 68 ..

22 9 135 9 1 11 57 5 7 6 1 12 8 31 65 4 3 130 8 5 4 4 8 25 4 5 5 9 13 105 7 101 5 6 3 29 12 382 4 .. 114 .. 61 7 4 5 11 ..

87 98 72 80 82

92 100 72 99 94

80 97 68 56 60

92 68 97 61 80

99 84 97 83 90

82 56 96 31 62

1.1 0.5 1.3 0.5 1.3

2.2 2.0 3.6 0.8 2.9

0.0 .. .. .. ..

81 43 63 33 46

10 8 6 6 7

95 93 100 76 83

71 24 108 24 63

a. Diphtheria, pertussis, and tetanus toxoid. b. Data are for most recent year available during the period specified.

80

Part III. Development outcomes

HUMAN DEVELOPMENT

Table

Participating in growth

9.1

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

Share of total population 2004

Annual growth 2004

64 64 55 48 82 90 48 43 57 75 64 68 46 55 16 51 80 84 16 74 54 64 65 60 82 53 73 83 67 37 56 63 67 77 53 80 62 50 50 60 65 43 60 76 64 64 88 64 65 .. 41 58 13 42 36

1.2 1.7 1.8 –1.1 2.8 3.1 0.2 0.4 0.4 2.9 1.2 2.2 2.0 0.7 –1.0 0.4 3.8 1.6 –3.1 2.8 1.2 1.0 1.8 0.3 –0.3 –0.6 2.5 1.7 2.0 –0.5 0.6 0.1 0.4 2.7 0.6 –0.6 2.2 0.9 0.8 3.0 2.5 –1.8 0.3 1.1 0.3 1.7 3.4 1.2 –0.1 .. 0.2 1.9 –0.5 1.9 0.0

Share of rural population with sustainable access (%) Rural population Share of rural density households (rural population To transportation with own per sq km of Rural population below To an improved To improved To (within 2 km of an telephone arable land) the poverty line water source sanitation electricity all-season road) (%) 2004 Survey year Percentage 2004 2004 2000–04 a 2000–04a 2000–04a

355 293 166 228 211 640 129 464 117 190 467 552 354 294 12,513 192 577 523 67 337 277 533 329 427 447 450 438 421 185 227 693 282 165 70 220 595 1,162 228 4,138 550 480 134 125 475 596 151 453 137 260 .. 174 1,409 43 145 128

2003 2001

2000

2000

2003

2000–01 2003

.. .. .. .. 52 .. 50 .. .. .. .. .. .. .. .. .. .. 45 .. .. .. .. .. .. .. .. .. .. .. 61 .. .. .. .. .. .. .. .. .. 79 .. .. .. .. 39 .. 42 .. .. .. .. .. .. .. ..

45 40 60 90 44 78 41 73 61 32 96 29 17 74 67 42 54 11 47 77 68 38 49 46 74 52 34 62 35 45 100 24 72 36 49 69 73 54 75 46 27 73 64 42 62 36 52 36 74 .. 80 97 68 56 60

26 16 12 25 5 35 33 19 12 0 15 23 2 23 27 46 3 4 30 46 46 6 23 43 32 7 27 42 38 9 99 14 14 4 30 38 20 34 100 30 14 44 24 44 41 15 39 32 51 .. 82 56 96 31 62

6.1 .. 5.5 .. 0.2 0.4 21.0 .. 0.3 0.1 19.6 .. .. 22.5 .. 2.1 0.4 .. .. 20.9 1.5 .. 4.3 .. .. 5.2 1.0 2.2 2.5 .. 2.1 .. 0.2 27.9 0.9 .. 6.0 .. .. .. .. .. .. 1.1 2.4 2.4 2.9 8.3 .. .. .. .. ..

.. .. 32 .. 25 .. 20 .. .. 5 .. 26 .. .. .. .. .. 17 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 37 47 .. .. .. .. .. .. .. .. .. 38 .. .. .. .. .. .. .. .. .. ..

0.8 .. 0.7 .. 0.3 .. 0.1 .. .. .. .. .. .. .. .. .. 0.1 0.0 1.1 .. 0.7 .. .. 6.2 .. .. .. .. 0.1 0.2 .. 0.1 .. .. 1.9 0.1 .. .. .. .. .. .. .. .. .. .. 0.6 0.4 .. .. .. .. .. .. ..

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

AGRICULTURE AND RURAL DEVELOPMENT

Part III. Development outcomes

81

Table

Participating in growth

9.2

Agriculture

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

Cereal production (thousands of metric tons) 2004

Livestock production index (1999– 2001=100) 2004

Food production per capita index (1999– 2001=100) 2004

Agricultural exports ($ millions) 2004

Agricultural imports ($ millions) 2004

89 108 91 183 94 102 100 31 121 103 84 102 81 .. 100 98 114 100 180 74 71 115 109 103 110 100 86 133 .. 92 129 118 25 103 103 61 230 95 113 .. 87 129 44 137 137 111 73 56

626 1,102 45 3,063 280 1,412 4 202 1,394 21 1,570 9 2,205 0 .. 102 9,280 32 162 1,943 1,142 193 2,709 248 110 3,391 1,847 2,728 153 0 1,813 98 3,169 22,783 319 3 1,200 .. 309 .. 12,225 3,792 71 4,458 787 2,625 1,364 1,227

100 116 102 110 100 103 102 115 108 96 100 121 111 109 102 100 116 102 103 112 115 109 109 100 110 104 102 118 110 114 101 114 105 109 110 108 101 91 105 .. 109 107 111 110 109 110 99 99

100 124 100 103 93 97 85 103 100 93 87 98 95 102 84 74 102 95 62 111 107 98 98 105 82 96 88 97 97 102 97 107 103 96 102 99 74 88 97 .. 103 99 102 98 95 96 103 85

2 228 52 314 23 654 0 1 123 26 39 40 3,093 11 7 3 380 17 22 1,212 51 62 1,296 6 96 118 392 336 18 407 124 237 27 487 34 4 182 6 14 .. 3,421 395 269 481 131 359 201 846

983 381 155 152 42 401 113 29 74 34 317 261 711 163 57 130 423 226 163 1,038 216 41 483 65 118 90 58 148 345 408 342 280 136 2,264 60 20 847 49 153 .. 2,650 638 71 406 98 281 97 465

104 111 109 98 96

3,994 20,261 213 8,591 2,155

105 122 101 100 99

109 102 96 124 97

55 1,314 12 964 974

4,050 3,014 1,148 2,058 1,181

Agriculture value added (% of GDP) 2004

Crop production index (1999– 2001=100) 2004

Food production index (1999– 2001=100) 2004

Nonfood production index (1999– 2001=100) 2004

8.5 32.1 2.3 30.8 36.1 40.0 6.8 57.0 23.5 36.2 47.4 6.0 22.1 .. .. 12.6 41.4 8.1 30.0 35.3 24.3 63.4 23.9 15.5 54.9 26.2 33.7 33.4 17.0 5.4 21.2 9.0 0.0 16.3 41.2 18.5 17.0 2.6 43.2 .. 2.7 33.2 6.5 42.3 41.2 29.5 18.8 14.2

119 134 113 130 104 105 85 98 116 106 97 106 97 115 94 72 111 102 66 121 110 110 102 111 99 109 92 111 101 104 107 111 122 106 113 109 77 94 115 .. 103 110 101 107 111 109 108 66

113 137 104 115 104 105 92 108 112 105 98 109 101 110 93 86 112 102 69 121 114 110 104 106 97 108 96 110 109 106 104 114 118 106 113 109 82 92 114 .. 106 108 106 106 104 109 108 86

8.6 .. .. 15.2 11.9

128 106 100 149 102

117 111 104 132 102

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

82

Part III. Development outcomes

AGRICULTURE AND RURAL DEVELOPMENT

Permanent cropland (thousands of hectares)

Land under cereal production (thousands of Irrigated land hectares) (% of cropland)

Fertilizer consumption (hundred grams per hectare of arable land)

Agricultural machinery (tractors per 100 hectares of arable land)

Agricultural employment (% of total employment)

Incidence of drought

Agricultural productivity (agriculture value added per worker 2000 $)

Cereal yield (kilograms per hectare)

2003

2004

2003

2002

2003

2000–03 a

2005

2003

2005

290 267 3 60 365 1,200 3 94 30 52 1,100 52 3,600 .. 100 3 713 170 5 2,200 650 250 562 4 220 600 140 40 12 6 230 5 17 2,900 270 47 47 6 75 26 959 420 14 1,100 120 2,150 29 130

1,388 968 188 3,085 211 881 26 185 1,807 16 2,048 11 1,747 0 .. 364 7,405 20 189 1,333 778 141 2,085 265 120 1,424 1,683 3,391 148 0 2,132 244 6,739 21,563 324 1 1,081 .. 253 .. 4,330 9,105 61 3,410 744 1,549 855 1,501

2.2 0.4 0.3 0.5 1.5 0.4 6.1 0.1 0.8 .. 0.1 0.4 1.1 .. .. 3.7 2.5 1.4 0.6 0.5 5.4 4.5 2.0 0.9 0.5 30.6 2.2 5.0 9.8 20.8 2.6 1.0 0.5 0.8 0.6 18.2 4.8 .. 4.7 18.7 9.5 10.7 26.0 3.6 0.3 0.1 2.9 5.2

0.0 187.6 122.0 3.6 25.8 58.6 47.8 3.1 48.6 37.5 15.7 4.8 330.3 0.0 0.0 65.4 151.0 9.2 25.4 74.2 30.5 80.0 310.3 342.4 0.0 30.9 839.2 90.1 59.4 2,500.0 59.3 3.7 3.4 55.0 137.1 .. 136.1 170.0 5.6 4.8 654.2 42.8 393.3 17.9 67.9 18.2 123.9 341.6

0.3 0.0 1.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.6 0.1 0.1 0.0 0.5 0.0 0.1 0.1 0.0 0.3 0.6 0.1 0.1 0.1 0.1 0.1 0.4 0.1 0.4 0.0 0.1 0.0 1.6 0.0 4.0 0.0 0.2 0.4 0.1 2.2 0.2 0.0 0.1 0.1 0.7

.. .. 12 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 55 .. .. .. .. .. 78 .. .. .. 9 .. 31 .. .. .. .. .. .. .. .. 10 .. .. 82 .. 69 .. ..

No No Yes No Yes No No No No No No No No Yes No Yes Yes No No No No No Yes No No Yes Yes No No No Yes No No No Yes No No No No Yes No No No Yes No Yes Yes Yes

175 610 412 164 101 1,215 1,666 423 199 353 197 347 763 70 654 57 109 1,805 220 346 231 229 319 491 .. 173 134 245 287 4,659 147 1,122 174 890 224 226 254 554 .. .. 2,372 688 1,180 290 405 231 210 241

597 1,147 241 941 1,329 1,727 156 1,042 671 1,338 767 806 1,262 1,500 .. 405 1,244 1,641 1,123 1,458 1,468 1,220 1,322 936 917 2,380 1,097 839 1,448 3,455 959 447 394 1,057 1,016 2,455 975 .. 1,223 .. 3,330 398 1,160 1,472 1,058 1,695 1,595 717

670 502 335 892 2,140

2,726 2,822 341 5,708 1,590

6.9 99.9 21.9 15.4 8.0

129.9 4,342.2 341.0 475.2 368.1

1.3 3.1 2.2 0.6 1.3

21 28 .. 44 ..

No No No No No

2,113 2,048 .. 1,711 2,639

1,466 7,516 627 814 1,450

AGRICULTURE AND RURAL DEVELOPMENT

Part III. Development outcomes

83

Table

Participating in growth

10.1

Labor Employment

Labor force

Total (millions) 2000–04a

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

298.5 6.8 3.2 0.6 5.6 3.7 6.2 0.2 1.8 3.6 0.2 22.3 1.5 6.7 0.3 0.2 1.7 30.9 0.6 0.6 9.6 4.3 0.6 15.1 0.6 1.2 8.3 5.8 5.3 1.2 0.6 9.1 0.6 5.7 46.7 4.1 0.0 4.5 .. 2.3 3.4 19.1 10.3 0.3 18.9 2.4 11.5 4.9 5.7 .. 12.9 22.3 2.2 10.9 3.7

Participation rate (% ages 15–64) Male 2000–04a

Female 2000–04a

.. 92 87 69 90 93 82 79 89 77 87 91 87 89 84 .. 94 91 91 84 87 76 89 93 90 74 84 86 90 86 85 84

.. 76 55 47 80 93 54 37 71 66 60 63 56 40 55 .. 52 60 74 64 60 72 83 63 71 49 56 80 86 75 56 46

83 65 96 86 85 77 84 .. 94 95 82 73 75 91 90 88 91 85 .. 83 77 82

85 49 73 47 82 32 59 .. 58 61 50 24 33 88 52 81 68 65 .. 37 22 32

Agriculture

Industry

Services

Male (% of male employment) 2000–04a

Female (% of female employment) 2000–04a

Male (% of male employment) 2000–04a

Female (% of female employment) 2000–04a

Male (% of male employment) 2000–04a

Female (% of female employment) 2000–04a

.. .. .. 16.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 59.8 .. .. .. .. .. 76.7 .. .. .. 11.0 .. 32.8 .. .. .. .. .. .. .. .. 12.6 .. .. 80.2 .. 60.1 .. .. .. .. 27.5 .. 39.2 ..

.. .. .. 5.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 50.3 .. .. .. .. .. 79.3 .. .. .. 6.1 .. 29.1 .. .. .. .. .. .. .. .. 7.4 .. .. 84.0 .. 77.3 .. .. .. .. 27.6 .. 56.8 ..

.. .. .. 31.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 13.5 .. .. .. .. .. 7.4 .. .. .. 35.7 .. 17.2 .. .. .. .. .. .. .. .. 33.3 .. .. 4.0 .. 10.7 .. .. .. .. 22.9 .. 20.7 ..

.. .. .. 17.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 14.5 .. .. .. .. .. 6.0 .. .. .. 39.6 .. 6.7 .. .. .. .. .. .. .. .. 13.6 .. .. 1.2 .. 4.8 .. .. .. .. 10.4 .. 18.6 ..

.. .. .. 51.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 26.5 .. .. .. .. .. 16.0 .. .. .. 53.2 .. 49.4 .. .. .. .. .. .. .. .. 53.9 .. .. 15.7 .. 28.8 .. .. .. .. 49.6 .. 40.0 ..

.. .. .. 75.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 35.6 .. .. .. .. .. 14.6 .. .. .. 54.2 .. 63.3 .. .. .. .. .. .. .. .. 78.9 .. .. 14.8 .. 17.8 .. .. .. .. 61.9 .. 24.5 ..

a. Data are for most recent year available during the period specified. b. Components may not sum to 100 percent because of unclassified data.

84

Part III. Development outcomes

L ABOR, MIGRATION, AND POPULATION

Employment Status in employmentb (%)

Composition of self-employmentb (%)

Wage and salaried workers (employees) Total Male Female 1999– 1999– 1999– 2003 a 2003 a 2003 a

Self-employed workers Total Male Female 1999– 1999– 1999– 2003 a 2003 a 2003 a

.. .. .. 82.7 .. .. 19.2 .. .. .. .. .. .. .. .. .. .. .. .. .. 13.8 .. .. 33.4 .. .. 15.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 81.8 .. .. 6.9 .. 14.5 .. 37.7 .. .. .. .. ..

.. .. .. 83.2 .. .. 29.3 .. .. .. .. .. .. .. .. .. .. .. .. .. 23.0 .. .. 46.4 .. .. 17.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 82.4 .. .. 9.8 .. 22.2 .. 51.0 .. .. .. .. ..

.. .. .. 81.9 .. .. 8.7 .. .. .. .. .. .. .. .. .. .. .. .. .. 6.1 .. .. 19.3 .. .. 12.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 81.1 .. .. 4.0 .. 7.5 .. 23.1 .. .. .. .. ..

.. .. .. 15.9 .. .. 59.3 .. .. .. .. .. .. .. .. .. .. .. .. .. 68.8 .. .. 23.8 .. .. 43.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 17.4 .. .. 89.3 .. 59.4 .. 50.4 .. .. .. .. ..

.. .. .. 15.3 .. .. 57.0 .. .. .. .. .. .. .. .. .. .. .. .. .. 66.0 .. .. 23.1 .. .. 51.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 17.1 .. .. 87.2 .. 67.5 .. 38.6 .. .. .. .. ..

.. .. .. 16.8 .. .. 61.7 .. .. .. .. .. .. .. .. .. .. .. .. .. 70.5 .. .. 24.6 .. .. 35.4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 17.7 .. .. 91.4 .. 52.1 .. 63.2 .. .. .. .. ..

.. .. .. 1.3 .. .. 18.2 .. .. .. .. .. .. .. .. .. .. .. .. .. 17.2 .. .. 39.6 .. .. 40.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.8 .. .. 3.8 .. 26.1 .. 11.9 .. .. .. .. ..

.. .. .. 1.4 .. .. 9.5 .. .. .. .. .. .. .. .. .. .. .. .. .. 10.7 .. .. 26.9 .. .. 29.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.5 .. .. 3.0 .. 10.3 .. 10.4 .. .. .. .. ..

.. .. .. 1.2 .. .. 27.2 .. .. .. .. .. .. .. .. .. .. .. .. .. 23.2 .. .. 53.2 .. .. 51.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.1 .. .. 4.6 .. 40.5 .. 13.6 .. .. .. .. ..

.. .. .. 3.6 .. .. 1.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.1 .. .. .. .. .. 5.8 .. .. .. .. .. .. .. .. 15.1 .. .. .. .. 0.3 .. 0.5 .. .. 17.4 .. 2.5

.. .. .. 4.2 .. .. 2.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.5 .. .. .. .. .. 6.8 .. .. .. .. .. .. .. .. 14.8 .. .. .. .. 0.4 .. 0.6 .. .. 20.1 .. 3.3

.. .. .. 2.9 .. .. 1.1 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.7 .. .. .. .. .. 4.5 .. .. .. .. .. .. .. .. 15.4 .. .. .. .. 0.2 .. 0.3 .. .. 5.7 .. 0.5

.. .. .. 12.3 .. .. 57.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 41.6 .. .. .. .. .. 10.2 .. .. .. .. .. .. .. .. 2.3 .. .. .. .. 59.1 .. 49.9 .. .. 11.9 .. 26.1

.. .. .. 11.2 .. .. 54.9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 49.2 .. .. .. .. .. 8.3 .. .. .. .. .. .. .. .. 2.3 .. .. .. .. 67.1 .. 38.0 .. .. 13.1 .. 31.2

.. .. .. 13.9 .. .. 60.6 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 33.7 .. .. .. .. .. 12.7 .. .. .. .. .. .. .. .. 2.3 .. .. .. .. 51.9 .. 62.9 .. .. 6.8 .. 12.1

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 2.5

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 3.1

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.9

..

..

..

..

..

..

..

..

..

..

..

..

..

..

..

..

..

..

L ABOR, MIGRATION, AND POPULATION

Contributing family workers (unpaid workers) Total Male Female 1999– 1999– 1999– 2003 a 2003 a 2003 a

Employers Total Male Female 1999– 1999– 1999– 2003 a 2003 a 2003 a

Own-account workers Total Male Female 1999– 1999– 1999– 2003 a 2003 a 2003 a

Members of producer cooperatives Total Male Female 1999– 1999– 1999– 2003 a 2003 a 2003 a

Part III. Development outcomes

85

Table

Participating in growth

10.2

Migration and population

International migration Population Stock Age composition Geographic Population dynamics (%) distribution Share Workers of Rural remittances Urban Growth Fertility rate Ages Ages Ages Dependency population Net areas received areas (births rate Total per woman) 0–14 15–64 65+ (%) Total migration ($ millions) (millions) (%) (% of total) (% of total) ratio 2004 2004 2004 2004 2000–04 a 2000–04a 2000–04a 2000–04a 2004 2004 2000–04a 2000–04a 2000–04b

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

.. 0.3 1.9 3.2 5.1 1.2 1.0 2.3 1.9 1.3 11.3 1.4 6.4 14.0 4.0 1.0 0.4 1.0 16.5 14.1 7.6 8.7 1.4 1.1 0.3 5.2 0.4 2.4 0.4 2.4 1.3 2.0 7.5 1.0 0.6 1.1 5.2 2.9 5.6 1.0 0.3 2.3 2.6 4.0 2.6 3.3 2.2 3.3 5.2 .. 0.8 0.3 10.5 0.4 0.4

.. .. 46,108 –120,090 133,730 –29,290 55,890 –7,000 572,829 –120,590 76,990 –400,000 147,573 –250 10,375 –5,000 71,612 11,290 104,825 99,440 60,792 –6,000 717,082 –1,410,320 220,493 41,550 2,336,362 150,000 28,481 20,280 4,517 0 12,952 –8,890 662,444 –76,910 210,486 14,370 185,116 45,000 1,504,715 –51,310 735,231 –227,000 19,233 –10,700 327,446 –21,390 5,462 –36,000 159,586 555,110 61,237 –3,000 280,096 –50,000 48,093 –283,900 62,514 9,900 15,539 –2,000 366,694 75,000 142,638 20,100 120,494 –5,940 751,126 –95,030 89,003 1,977,020 7,314 –5,000 297,216 –100,000 4,527 .. 46,662 –110,120 21,937 –214,310 1,022,374 364,290 853,867 –206,850 41,504 –12,000 892,553 –205,880 176,117 127,710 528,562 –66,000 357,469 86,210 655,671 –125,000 .. .. 250,110 –184,880 169,147 –500,000 558,770 10,000 116,715 –300,000 37,901 –20,000

7,339 .. 55 55 50 .. 11 92 .. .. 12 .. 1 148 .. .. 3 133 6 8 82 42 23 494 355 .. 16 1 154 2 215 58 15 26 2,273 10 1 511 2 25 .. 521 1,403 89 11 149 306 .. .. .. 2,460 3,341 10 4,221 1,432

725.8 15.5 1.8 8.2 12.8 7.3 16.0 0.5 4.0 9.4 0.6 55.9 3.9 17.9 0.8 0.5 4.2 70.0 1.4 1.5 21.7 9.2 1.5 33.5 1.8 3.2 18.1 12.6 13.1 3.0 1.2 19.4 2.0 13.5 128.7 8.9 0.2 11.4 0.1 5.3 8.0 45.5 35.5 1.1 37.6 6.0 27.8 11.5 12.9 .. 32.4 72.6 5.7 29.8 9.9

2.1 2.9 0.1 3.2 3.2 3.4 1.8 2.3 1.2 3.4 2.1 2.9 3.0 1.5 1.8 2.3 4.3 1.9 1.6 2.7 2.1 2.2 3.0 2.2 –0.1 0.6 2.7 2.2 3.0 3.0 1.0 1.9 1.2 3.4 2.2 1.4 2.3 2.4 1.0 4.2 3.3 –0.7 1.9 1.3 1.9 2.6 3.5 1.6 0.6 .. 1.5 1.9 2.0 3.4 0.9

5.3 6.6 3.1 5.7 6.5 6.8 4.8 3.6 4.8 6.4 4.1 6.7 6.3 4.8 4.9 5.9 5.3 5.4 3.8 4.5 4.2 5.8 7.1 5.0 3.5 6.8 5.1 5.9 6.8 5.7 2.0 5.4 3.8 7.7 5.6 5.5 3.9 4.8 2.1 6.5 6.3 2.7 4.2 4.0 4.8 5.1 7.1 5.5 3.4 .. 2.5 3.2 2.9 2.5 2.0

.. 47 44 38 47 46 42 40 43 47 42 47 47 42 42 44 45 45 40 40 39 44 47 43 39 47 44 47 48 43 25 44 42 49 45 44 40 43 .. 43 44 33 40 42 43 44 50 46 40 .. 30 34 30 31 27

.. 51 53 59 50 52 55 56 53 50 55 50 50 55 55 52 53 52 55 56 57 53 50 54 56 51 53 50 49 54 69 53 54 49 52 53 56 54 .. 54 53 63 57 55 54 53 47 51 56 .. 65 61 66 64 67

.. 2 3 3 3 3 4 4 4 3 3 3 3 3 3 4 2 3 4 4 4 4 3 3 5 2 3 3 3 3 7 3 3 2 3 2 4 3 .. 3 3 4 4 3 3 3 2 3 4 .. 5 5 4 5 6

.. 1.0 0.9 0.7 1.0 0.9 0.8 0.8 0.9 1.0 0.8 1.0 1.0 0.8 0.8 0.9 0.9 0.9 0.8 0.8 0.8 0.9 1.0 0.8 0.8 1.0 0.9 1.0 1.0 0.9 0.5 0.9 0.8 1.0 0.9 0.9 0.8 0.9 .. 0.9 0.9 0.6 0.8 0.8 0.9 0.9 1.1 1.0 0.8 .. 0.5 0.6 0.5 0.6 0.5

63.6 63.5 54.7 48.0 81.8 89.7 47.8 43.3 56.8 74.6 64.3 67.7 46.0 54.6 15.9 51.0 79.6 84.1 15.6 73.8 54.2 64.3 65.2 59.5 81.9 52.7 73.2 83.3 67.0 37.0 56.5 63.2 67.0 77.3 52.5 79.9 62.1 49.7 49.9 60.5 64.6 42.6 60.2 76.3 63.5 64.3 87.7 63.8 64.6 .. 40.6 57.8 13.4 41.9 35.9

36.4 36.5 45.3 52.0 18.2 10.3 52.2 56.7 43.3 25.4 35.7 32.3 54.0 45.4 84.1 49.0 20.4 15.9 84.4 26.1 45.8 35.7 34.8 40.5 18.1 47.3 26.8 16.7 33.0 63.0 43.5 36.8 33.0 22.7 47.5 20.1 37.9 50.3 50.1 39.5 35.4 57.4 39.8 23.7 36.5 35.8 12.4 36.2 35.4 .. 59.4 42.2 86.6 58.1 64.1

a. Data are for most recent year available during the period specified. b. Data are five-year estimates.

86

Part III. Development outcomes

L ABOR, MIGRATION, AND POPULATION

Table

Participating in growth

11.1

HIV/AIDS Estimated number of people living with HIV/AIDS (thousands) Total

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 Djibouti 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 Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe NORTH AFRICA Algeria Egypt, Arab Rep. Libya Morocco Tunisia ALL AFRICA

HIV/AIDS

Adults (ages 15–49)

Women (ages 15–49)

Children (ages 0–14)

Estimated prevalence rate (%) Adults Young women (ages 15–49) (ages 15–24)

Young men (ages 15–24)

Deaths due to HIV/AIDS (thousands)

AIDS orphans (ages 0–17, thousands)

2005

2005

2005

2005

2005

2005

2005

2005

2005

24,500 19,000 16,100 320 87 270 150 150 510 .. 250 180 <0.5 1,000 120 750 15 9 59 .. 60 20 320 85 32 1,300 270 .. 49 940 130 12 4 1,800 230 79 2,900 190 .. 61 .. 48 44 5,500 350 220 1,400 110 1,000 1,100 1,700 440 19 5 .. 19 9 24,940

22,400 17,100 14,500 280 77 260 140 130 470 .. 230 160 <0.5 890 100 680 14 8 53 .. 56 19 300 78 29 1,200 250 .. 47 850 110 11 4 1,600 210 71 2,600 160 .. 56 .. 43 40 5,300 320 210 1,300 100 900 1,000 1,500 400 19 5 .. 19 9 22,800

13,200 10,100 8,500 170 45 140 80 79 290 .. 130 90 <0.1 520 61 400 8 5 31 .. 33 11 180 53 17 740 150 .. 13 500 66 6 <1 960 130 42 1,600 91 .. 33 .. 26 23 3,100 180 120 710 61 520 570 890 190 4 <1 .. 4 2 13,390

2,000 1,760 1,520 35 10 14 17 20 43 .. 24 16 <0.1 120 15 74 1 <1 7 .. 4 1 25 7 3 150 18 .. 2 91 16 1 .. 140 17 9 240 27 .. 5 .. 5 5 240 30 15 110 10 110 130 160 31 .. .. .. .. .. 2,031

6.1 .. .. 3.7 1.8 24.1 2.0 3.3 5.4 .. 10.7 3.5 <0.1 3.2 5.3 7.1 3.1 3.2 2.4 .. 7.9 2.4 2.3 1.5 3.8 6.1 23.2 .. 0.5 14.1 1.7 0.7 0.6 16.1 19.6 1.1 3.9 3.1 .. 0.9 .. 1.6 0.9 18.8 1.6 33.4 6.5 3.2 6.7 17.0 20.1 0.22 0.1 <0.1 .. 0.1 0.1 ..

4.3 .. .. 2.5 1.1 15.3 1.4 2.3 4.9 .. 7.3 2.2 <0.1 2.2 3.7 5.1 2.1 2.3 1.6 .. 5.4 1.7 1.3 1.4 2.5 5.2 14.1 .. 0.3 9.6 1.2 0.5 .. 10.7 13.4 0.8 2.7 1.9 .. 0.6 .. 1.1 0.6 14.8 .. 22.7 3.8 2.2 5.0 12.7 14.7 0.20 .. .. .. .. .. ..

1.5 .. .. 0.9 0.4 5.7 0.5 0.8 1.4 .. 2.5 0.9 <0.1 0.8 1.2 1.7 0.7 0.7 0.6 .. 1.8 0.6 0.2 0.5 0.9 1.0 5.9 .. 0.6 3.4 0.4 0.2 .. 3.6 4.4 0.2 0.9 0.8 .. 0.2 .. 0.4 0.2 4.5 .. 7.7 2.8 0.8 2.3 3.8 4.4 0.10 .. .. .. .. .. ..

2,000 1,680 1,460 30 10 18 12 13 46 .. 24 11 <0.1 90 11 65 1 <1 6 .. 5 1 29 7 3 140 23 .. 3 78 11 <1 <0.1 140 17 8 220 21 .. 5 .. 5 4 320 34 16 140 9 91 98 180 37 <0.5 <0.5 .. 1 <0.1 2,037

12,000 10,800 9,870 160 62 120 120 120 240 .. 140 57 .. 680 110 450 6 5 36 .. 20 4 170 28 11 1,100 97 .. 13 550 94 7 .. 510 85 46 930 210 .. 25 .. 31 23 1,200 .. 63 1,100 88 1,000 710 1,100 .. .. .. .. .. 12,000

Part III. Development outcomes

87

Table

Participating in growth

12.1

Malaria Children with fever receiving Children Pregnant women antimalarial drugs sleeping under receiving two doses (% of children under Deaths due insecticideof intermittent Risk of malaria age 5 with fever) to malaria Under-five treated bednets preventive (% of population) Population (per 100,000 mortality rate (% of children Any antimalarial Effective treatment (millions) people) (per 1,000) under age 5) Endemic Epidemic Negligible drugs antimalarial drugs (%) 2000–04a 1997–2004a 1997–2004a 1997–2004 a 1997–2004a 1997–2004 a 1997–2004a 1997–2004a 1997–2004 a 1997–2004 a

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

15.5 8.2 1.8 12.8 7.3 16.0 0.5 4.0 9.4 0.6 55.9 3.9 17.9 0.8 0.5 4.2 70.0 1.4 1.5 21.7 9.2 1.5 33.5 1.8 3.2 18.1 12.6 13.1 3.0 1.2 19.4 2.0 13.5 128.7 8.9 0.2 11.4 0.1 5.3 8.0 45.5 35.5 1.1 37.6 6.0 27.8 11.5 12.9

90 100 .. 100 68 94 .. 100 96 .. 92 100 100 .. 98 92 40 96 100 100 100 100 53 .. 100 89 97 99 65 .. 100 .. 97 100 53 0 100 .. 100 20 .. 74 .. 93 100 90 96 ..

8 0 .. 0 17 4 .. 0 4 .. 3 0 0 .. 1 7 24 0 0 0 0 0 24 .. 0 7 3 1 35 .. 0 .. 3 0 14 0 0 .. 0 79 .. 25 .. 3 0 3 3 ..

1 0 .. 0 15 2 .. 0 0 .. 6 0 0 .. 1 1 36 4 0 0 0 0 22 .. 0 4 1 0 0 .. 0 .. 0 0 33 100 0 .. 0 1 .. 1 .. 4 0 7 1 ..

354 177 .. 292 .. .. .. .. .. .. 224 .. .. .. .. 74 198 .. .. 70 .. .. 63 .. 201 .. 275 454 .. .. 232 .. 469 141 200 .. 72 .. .. .. .. 70 .. 130 .. 152 141 ..

260 152 116 192 190 149 36 193 200 70 205 108 194 126 204 82 166 91 122 112 155 203 120 112 235 123 175 219 125 15 152 63 259 197 203 118 137 14 283 225 67 91 156 126 140 138 182 129

2.3 7.4 .. 1.6 1.3 0.9 .. 1.5 0.6 9.3 0.7 .. 1.1 .. 0.7 4.2 .. .. 14.7 3.5 .. 7.4 4.6 .. .. 0.2 35.5 .. 2.1 .. .. .. 1.0 1.2 5.0 22.8 1.7 .. 1.5 .. .. .. 0.1 2.1 2.0 0.2 6.5 ..

63 60 .. 50 .. .. .. .. .. .. 45 .. .. .. .. 4 3 .. .. 63 .. .. 27 .. .. .. 27 38 .. .. .. .. 48 34 13 .. 36 .. .. .. .. 61 .. 53 .. .. 52 ..

20 19 .. 45 .. .. .. .. .. .. .. .. .. .. .. 7 .. .. .. 44 .. .. 11 .. .. .. .. .. .. .. .. .. .. 25 .. .. .. .. .. .. .. .. .. 11 .. 7 50 ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1 .. .. 4 .. .. .. 47 .. .. .. .. .. .. 1 .. .. .. .. .. .. .. .. .. .. .. 33 .. ..

32.4 72.6 5.7 29.8 9.9

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

40 36 20 43 25

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

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

88

Part III. Development outcomes

MALARIA

Table

Capable states and partnership

13.1

Aid and debt relief Net aid (2003 $ millions)

From all donors 2004

SUB–SAHARAN AFRICA 21,740 Angola 1,036 Benin 343 Botswana 343 Burkina Faso 553 Burundi 320 Cameroon 688 Cape Verde 126 Central African Republic 95 Chad 292 Comoros 22 Congo, Dem. Rep. 1,645 Congo, Rep. 105 Côte d’Ivoire 138 Djibouti 59 Equatorial Guinea 26 Eritrea 242 Ethiopia 1,682 Gabon 34 Gambia, The 58 Ghana 1,234 Guinea 256 Guinea-Bissau 69 Kenya 586 Lesotho 93 Liberia 197 Madagascar 1,119 Malawi 432 Mali 516 Mauritania 163 Mauritius 34 Mozambique 1,117 Namibia 164 Niger 485 Nigeria 525 Rwanda 426 São Tomé and Principe 30 Senegal 953 Seychelles 9 Sierra Leone 326 Somalia 174 South Africa 560 Sudan 821 Swaziland 105 Tanzania 1,583 Togo 55 Uganda 1,062 Zambia 974 Zimbabwe 169 NORTH AFRICA 2,578 Algeria 279 Egypt, Arab Rep. 1,368 Libya .. Morocco 636 Tunisia 295

CAPABLE STATES AND PARTNERSHIP

From From DAC multilateral donors donors 2004 2004

13,961 919 191 191 299 169 515 82 50 149 12 1,053 42 177 36 20 168 952 21 11 812 165 26 436 31 153 616 280 299 75 13 661 119 276 289 198 20 682 6 147 127 420 696 95 929 47 627 669 150 1,887 209 1,115 .. 354 208

Net aid (%)

Aid

8,446 131 168 168 278 166 189 49 50 154 11 650 68 –43 27 7 86 760 14 51 451 101 48 166 68 48 552 166 241 96 25 497 34 230 260 250 12 296 3 196 51 156 112 12 714 9 475 333 21 677 78 261 .. 242 96

Share of GDP (%) 2004

Per capita ($) 2004

Share of gross capital formation 2004

Share of imports of goods and services 2004

4.5 5.8 9.3 0.4 12.6 52.8 4.8 14.7 8.0 7.4 6.6 27.4 2.7 1.0 .. 0.9 28.0 22.6 0.5 15.7 15.7 7.4 28.2 3.9 7.5 42.8 28.3 25.0 11.6 11.7 0.6 20.8 3.1 17.6 0.8 25.5 58.5 13.5 1.5 33.2 .. 0.3 4.1 4.6 15.4 3.0 17.0 19.9 4.0 1.2 0.4 1.9 .. 1.3 1.1

32.9 73.9 46.2 22.1 47.6 48.2 47.5 282.4 26.2 33.8 41.7 32.5 29.9 8.6 82.3 60.3 61.3 26.1 27.7 42.5 62.7 30.3 49.5 19.0 56.8 65.0 68.2 37.8 43.2 60.3 30.7 63.2 89.1 39.7 4.5 52.6 218.5 92.4 123.6 67.4 24.0 13.6 24.8 104.1 46.4 10.3 41.7 94.2 14.4 19.4 9.7 20.1 .. 23.7 33.0

23.9 63.5 51.2 51.2 66.2 386.6 25.5 72.3 45.6 29.7 65.1 213.7 11.0 9.2 .. .. 122.6 88.2 2.1 55.8 65.1 68.6 213.9 21.6 18.2 346.8 116.6 163.8 61.1 54.5 2.6 100.6 12.3 111.2 3.6 124.5 169.5 57.9 10.0 316.8 .. 1.6 18.2 26.6 83.8 16.5 75.5 76.8 31.0 12.5 .. .. .. 5.6 4.7

17.8 18.0 47.9 47.9 77.0 245.6 28.9 35.8 105.4 43.2 37.6 88.3 11.0 3.8 .. .. 56.4 70.5 3.4 26.7 .. 39.4 78.9 14.7 8.3 78.5 85.6 55.0 49.6 19.4 1.6 60.4 8.5 96.0 3.0 169.4 91.8 42.4 2.5 .. .. 1.3 33.5 6.1 73.8 7.3 87.7 62.6 9.4 9.1 .. .. .. 4.3 2.7

Estimated total nominal debt service relief Share of committed central under Enhanced government HIPC Initiative expenditure Decision point Completion point ($ millions) 2004 as of Mar. 2006 as of Mar. 2006 as of Mar. 2006 Heavily Indebted Poor Country (HIPC) Debt Initiative

.. 15.8 46.5 46.5 55.9 132.6 30.1 49.4 58.9 50.4 33.7 178.1 9.3 4.9 .. .. 34.9 74.7 2.4 50.3 57.7 42.5 57.1 17.1 17.9 307.5 112.9 57.0 51.4 36.8 2.4 84.3 9.1 89.2 2.2 97.7 65.5 55.2 2.9 128.4 .. 1.1 22.3 14.3 75.7 20.4 72.6 74.7 9.7 .. .. .. .. 4.7 4.4

50,282 Jul. 2000

Mar.2003

460

Jul. 2000 Jul. 2005 Oct. 2000

Apr. 2002 Floating Floating

930 1,472 2,800

May 2001

Floating

260

Jul. 2003 Mar. 2006

Floating

10,389 2,881

..

Nov. 2001

Apr. 2004

3,275

Dec. 2000 Feb. 2002 Dec. 2000 Dec. 2000

Floating Jul. 2004 Floating Floating

90 3,500 800 790

Dec. 2000 Dec. 2000 Sep. 2000 Feb. 2000

Oct. 2004 Floating Mar.2003 Jun. 2002

1,900 1,000 895 1,100

Apr. 2000

Sep. 2001

4,300

Dec. 2000

Apr. 2004

1,190

Dec. 2000 Dec. 2000 Jun. 2000

Apr. 2005 Floating Apr. 2004

1,400 200 850

Mar. 2002

Floating

Apr. 2000

Nov. 2001

3,000

Feb. 2000 Dec. 2000

May. 2000 Apr. 2005

1,950 3,900

950

Part III. Development outcomes

89

Table

Capable states and partnership

13.2

Capable states

Public financial management (number of HIPC benchmarks met) as of Mar 2006

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

Investment climate (viewed by firms as major constraint, %)

Protecting investorsa

Enforcing contracts Time required (days) 2005

Cost (% of debt) 2005

Disclosure index 2005

Director liability index 2005

Shareholder suits index 2005

Investor protection indexb 2005

Courts 2005

Crime 2005

Number of procedures 2005

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 34.8 .. 16.9 .. .. .. .. .. .. .. .. 13.3 .. .. .. 8.8 .. .. 20.0 ..

47 49 26 41 47 58 .. 45 52 .. 51 47 25 .. .. 27 30 .. .. 23 44 .. 25 49 .. 29 16 28 28 17 38 31 33 23 27 67 33 .. 58 .. 26 67 .. 21 37 15 16 33

1,011 570 154 446 433 585 .. 660 526 .. 909 560 525 .. .. 385 420 .. .. 200 306 .. 360 285 .. 280 277 340 410 367 580 270 330 730 310 405 485 .. 305 .. 277 915 .. 242 535 209 274 350

11.2 29.6 24.8 95.4 32.5 36.4 .. 72.2 54.9 .. 256.8 43.0 47.6 .. .. 19.9 14.8 .. .. 14.4 27.6 .. 41.3 23.9 .. 22.8 136.5 34.6 29.3 8.6 16.0 28.3 42.0 37.2 43.2 69.5 23.8 .. 31.0 .. 11.5 30.0 .. 35.3 24.3 22.3 28.7 19.1

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

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

6 4 3 3 .. 6 .. .. 5 .. 5 6 3 .. .. 5 3 .. .. 4 3 .. 10 8 .. 6 5 3 .. 9 .. 7 3 4 .. 6 3 .. 5 .. 8 .. .. .. 5 4 8 4

5.7 5.7 4.3 4.7 .. 5.7 .. .. 4.7 .. 4.0 5.0 4.7 .. .. 4.7 2.7 .. .. 6.0 4.7 .. 5.3 4.0 .. 5.7 5.3 4.7 .. 7.7 .. 6.7 4.7 5.7 .. 4.3 3.7 .. 4.7 .. 8.0 .. .. 2.0 4.0 5.0 7.3 4.3

49 55 .. 17 14

407 410 .. 240 27

28.7 18.4 .. 17.7 12.0

8 5 .. 6 0

5 2 .. 5 3

1 5 .. 1 6

4.7 4.0 .. 4.0 3.0

.. 8 .. 9 .. 7 .. .. 7 .. 3 .. .. .. .. .. 7 .. 3 7 5 0 .. .. .. 4 5 11 .. .. 4 .. 5 .. 8 4 7 .. 7 .. .. .. .. 11 .. 8 3 ..

38.6 ..

.. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 1.3 9.5 .. .. .. .. .. 69.8 .. .. 37.7 .. 22.1 .. .. .. .. .. 36.3 .. .. 15.4 .. .. .. 29.0 .. .. 25.5 .. 26.8 48.8 ..

.. .. .. .. ..

.. 27.4 .. .. ..

.. .. .. .. ..

a. Indexes run from 0 least desirable to 10 most desirable. b. Average of the disclosure, director liability, and shareholder suits indexes.

90

Part III. Development outcomes

CAPABLE STATES AND PARTNERSHIP

Number of tax payments 2005

Regulation and tax administration Time to prepare and pay taxes (hours) 2005

Total tax payable (% of gross profits) 2005

Extractive Industries Transparency Initiative implementing or endorsed since 2003

Corruption Perceptions Index transparency indexa (mean score) 2005

30 75 24 40 41 51 .. 66 65 .. 34 94 71 .. .. 18 20 .. .. 35 55 .. 17 19 .. 29 33 60 61 7 35 23 44 36 42 29 59 .. 20 .. 32 .. .. 48 51 31 36 59

656 270 140 270 140 1,300 .. 504 122 .. 312 576 270 .. .. 216 52 .. .. 304 416 .. 372 564 .. 400 782 270 696 158 230 50 270 1,120 168 1,008 696 .. 399 .. 350 .. .. 248 270 237 132 216

32.5 53.1 52.9 48.3 173.5 47.6 .. 60.9 51.3 .. 134.7 66.9 46.9 .. .. 66.3 43.6 .. .. 45.3 51.2 .. 68.2 37.7 .. 58.9 56.5 44.0 75.8 38.2 50.9 43.9 49.4 27.1 53.9 27.4 45.0 .. 163.9 .. 43.8 .. .. 51.3 50.9 42.9 38.6 48.6

Endorsed .. .. .. .. Endorsed .. .. Endorsed .. Endorsed Implementing .. .. Endorsed .. .. Endorsed .. Implementing Endorsed .. .. .. .. .. .. .. Endorsed .. .. .. Endorsed Implementing .. Implementing .. .. Endorsed .. .. .. .. .. .. .. .. ..

2.0 2.9 5.9 3.4 2.3 2.2 3.4 2.4 1.7 2.6 2.1 2.3 1.9 2.6 1.9 2.6 2.2 2.9 2.7 3.5 1.7 4.4 2.1 3.4 2.2 2.8 2.8 2.9 4.9 4.2 2.8 4.3 2.4 1.9 3.1 2.6 3.2 4.0 2.4 2.1 4.5 2.1 2.7 2.9 2.7 2.5 2.6 2.6

63 39 .. 28 31

504 504 .. 690 112

58.5 32.1 .. 54.8 52.7

.. .. .. .. ..

2.8 3.4 2.5 3.2 4.9

CAPABLE STATES AND PARTNERSHIP

Part III. Development outcomes

91

Table

Capable states and partnership

13.3

Governance and anticorruption indicators

Composite aggregate indicator Voice and accountability

Bottom quintile <–1.09 Burundi, Cameroon, Central African Republic, Chad, Côte d’Ivoire, Congo, Dem. Rep., Equatorial Guinea, Eritrea, Ethiopia, Guinea, Liberia, Mauritania, Rwanda, Somalia, Sudan, Swaziland, Togo, Tunisia, Zimbabwe

Political stability

Government effectiveness

2nd quintile –1.04 to –0.34 Algeria, Angola, Burkina Faso, Djibouti, Egypt, Gabon, Gambia, Guinea-Bissau, Kenya, Malawi, Morocco, Nigeria, Sierra Leone, Tanzania, Uganda, Zambia

3rd quintile 0.14 to 0.39 Benin, Comoros, Congo, Rep., Ghana, Lesotho, Madagascar, Mali, Mozambique, Niger, Senegal, Seychelles

4th quintile 0.47 to 0.94 Botswana, Cape Verde, Mauritius, Namibia, São Tomé and Principe, South Africa

<–0.91

–1.04 to –0.34

–0.21 to 0.38

Algeria, Angola, Burundi, Central African Republic, Chad, Congo, Dem. Rep., Congo, Rep., Côte d’Ivoire, Ethiopia, Guinea, Kenya, Liberia, Nigeria, Rwanda, Somalia, Sudan, Uganda, Zimbabwe

Benin, Burkina Faso, Cameroon, Djibouti, Equatorial Guinea, Guinea-Bissau, Malawi, Niger, Sierra Leone, South Africa, Tanzania, Togo

Comoros, Eritrea, Gabon, Gambia, Ghana, Lesotho, Libya, Madagascar, Mali, Mauritania, Mozambique, São Tomé and Principe, Senegal, Swaziland, Tunisia, Zambia

–0.87

–0.84 to –0.39

–0.37 to –0.03

0.22 to 0.83

Algeria, Benin, Burkina Faso, Cameroon, Djibouti, Gabon, Gambia, Kenya, Libya, Madagascar, Malawi, Mozambique, Rwanda, Swaziland, Uganda, Zambia, Zimbwabwe

Cape Verde, Egypt, Ghana, Lesotho, Mali, Morocco, Senegal, Seychelles, Tanzania, Tunisia

Botswana, Mauritania, Mauritius, Namibia, South Africa

Angola, Burundi, Central African Republic, Chad, Comoros, Congo, Dem. Rep., Congo, Rep., Côte d’Ivoire, Equatorial Guinea, Eritrea, Ethiopia, Guinea, GuineaBissau, Liberia, Niger, Nigeria, São Tomé and Principe, Sierra Leone, Somalia, Sudan, Togo

Top quintile

0.46 to 0.91 Botswana, Cape Verde, Mauritius, Namibia, Senegal

Note: Within each quintile, countries are listed in alphabetical order.

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Part III. Development outcomes

CAPABLE STATES AND PARTNERSHIP

Composite aggregate indicator Regulatory quality

Rule of law

Control of corruption

Bottom quintile <–0.83

–0.78 to –0.36

Algeria, Angola, Burundi, Central African Republic, Chad, Comoros, Congo, Dem. Rep., Congo, Rep., Côte d’Ivoire, Eritrea, Ethiopia, Guinea, GuineaBissau, Liberia, Libya, Nigeria, Seychelles, Sierra Leone, Somalia, Sudan

Benin, Cameroon, Djibouti, Egypt, Equatorial Guinea, Gabon, Kenya, Lesotho, Malawi, Niger, Rwanda, São Tomé and Principe, Swaziland, Tanzania, Togo, Zambia, Zimbwabwe

3rd quintile 0.31 to 0.10 Burkina Faso, Gambia, Ghana, Madagascar, Mali, Mauritania, Morocco, Mozambique, Senegal, Tunisia, Uganda

<–0.95

–0.92 to –0.49

–0.47 to 0.26

Angola, Burundi, Cameroon, Central African Republic, Chad, Comoros, Congo, Dem. Rep., Congo, Rep., Côte d’Ivoire, Equatorial Guinea, Ethiopia, Guinea, GuineaBissau, Kenya, Liberia, Nigeria, Sierra Leone, Somalia, Sudan, Swaziland, Togo, Zimbabwe

Algeria, Burkina Faso, Djibouti, Eritrea, Gabon, Libya, Mauritania, Niger, Rwanda, São Tomé and Principe, Tanzania, Uganda, Zambia

Benin, Cape Verde, Egypt, Gambia, Ghana, Madagascar, Malawi, Mali, Morocco, Namibia, Senegal, Seychelles, Tunisia

<–0.88

–0.87 to –0.52

–0.49 to 0.02

Angola, Burundi, Cameroon, Central African Republic, Chad, Comoros, Congo, Dem. Rep., Congo, Rep., Côte d’Ivoire, Djibouti, Equatorial Guinea, Kenya, Libya, Nigeria, Sierra Leone, Somalia, Sudan, Swaziland, Togo, Zimbabwe

CAPABLE STATES AND PARTNERSHIP

2nd quintile

Cameroon, Eritrea, Ethiopia, Gabon, Gambia, Guinea, GuineaBissau, Liberia, Malawi, Mali, Mozambique, Niger, São Tomé and Principe, Tanzania, Uganda, Zambia

Algeria, Benin, Burkina Faso, Egypt, Ghana, Lesotho, Madagascar, Mauritania, Morocco, Rwanda, Senegal, Seychelles

4th quintile

Top quintile

0.27 to 0.96 Botswana, Cape Verde, Mauritius, Namibia, South Africa

0.32 to 0.84 Botswana, Mauritius, South Africa

0.18 to 0.48 Cape Verde, Mauritius, Namibia, South Africa, Tunisia

>0.80 Botswana

Part III. Development outcomes

93

Table

Capable states and partnership

13.4

Cluster

Country Policy and Institutional Assessment ratings, 2005

Criterion indicators

<2.6

2.6 to 2.9

3.0 to 3.2

3.3 to 3.5

>3.5

Overall rating

Economic management, structural policies, policies for social inclusion and equity, and public sector management and institutions

Central African Republic, Comoros, Côte d’Ivoire, Eritrea, Togo, Zimbabwe

Angola, Chad, Congo, Dem. Rep., Congo, Rep., GuineaBissau, Sudan

Burundi, Djibouti, Gambia, Guinea, Mauritania, Nigeria, São Tomé and Principe, Sierra Leone

Cameroon, Ethiopia, Lesotho, Madagascar, Malawi, Mozambique, Niger, Rwanda, Zambia

Benin, Burkina Faso, Cape Verde, Ghana Kenya, Mali, Senegal, Tanzania, Uganda

Economic management

Macroeconomic management, fiscal policy, and debt policy

Angola, Central African Republic, Côte d’Ivoire, Eritrea, GuineaBissau, Togo, Zimbabwe

Guinea, Mauritania, São Tomé and Principe, Sudan

Congo, Dem. Rep., Congo, Rep., Djibouti, Gambia, Malawi

Burundi, Cameroon, Chad, Madagascar, Niger, Rwanda, Zambia

Benin, Burkina Faso, Cape Verde, Ethiopia, Ghana, Kenya, Lesotho, Mali, Mozambique, Nigeria, Senegal, Sierra Leone, Tanzania, Uganda

Structual policies

Trade, financial sector and business regulatory environment

Comoros, Eritrea, Zimbabwe

Angola, Burundi, Central African Republic, Congo, Rep., Nigeria, Sudan

Chad, Congo, Dem. Rep., Côte d’Ivoire, Ethiopia, Guinea-Bissau, Mozambique, São Tomé and Principe, Sierra Leone, Togo

Burkina Faso, Cameroon, Djibouti, Gambia, Guinea, Lesotho, Malawi, Mali, Mauritania, Nigeria, Rwanda, Zambia

Benin, Cape Verde, Ghana, Kenya, Madagascar, Senegal, Tanzania, Uganda

Policies for social inclusion and equity

Gender equality, equity of public resource use, building human resources, social protection and labor, and policies and institutions for environmental sustainability

Cape Verde, Côte d’Ivoire, Sudan, Zimbabwe

Angola, Chad, Comoros, Congo, Dem. Rep., Guinea-Bissau, São Tomé and Principe, Sierra Leone, Togo

Benin, Burundi, Djibouti, Eritrea, Gambia, Guinea, Kenya, Niger, Nigeria

Cameroon, Lesotho, Malawi, Mali, Mauritania, Mozambique, Senegal, Zambia

Burkina Faso, Cape Verde, Ethiopia, Ghana, Madagascar, Rwanda, Tanzania, Uganda

Public sector management and institutions

Property rights and rule-based governance, quality of budgetary and financial management, quality of public administration and transparency accountability and corruption in public sector

Central African Republic, Chad, Comoros, Congo, Dem. Rep., Côte d’Ivoire, Sudan, Togo, Zimbabwe

Burundi, Congo, Rep., Djibouti, Eritrea, Gambia, Guinea, Guinea-Bissau, Mauritania, Nigeria, Sierra Leone

Cameroon, Ethiopia, Mozambique, Nigeria, São Tomé and Principe, Zambia

Benin, Kenya, Lesotho, Madagascar, Malawi, Rwanda, Uganda

Burkina Faso, Cape Verde, Ghana, Mali, Senegal, Tanzania

Note: Within each range of ratings, countries are listed in alphabetical order. Only members of the International Development Association are included. Ratings for each indicator are averaged to calculate the rating for each cluster; the ratings for each cluster are averaged to calculate the overall rating.

94

Part III. Development outcomes

CAPABLE STATES AND PARTNERSHIP

Table

14.1

Burkina Faso household survey, 2003 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (CFA francs) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Missionary or nongovernmental organization Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

Rural

National total

All

8,494 11,385 1.0 6.4 4 60 29 0 7

Q1

Q2

5,894 9,317 1.1 6.6

618 1,387 1.3 9.8

853 1,672 1.2 8.4

3 59 33 0 5

0 44 53 0 3

1 50 44 0 4

Urban Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

1,020 1,804 1.2 7.5

1,278 1,947 1.1 6.5

2,125 2,506 0.8 4.7

2,600 2,068 0.6 5.6

253 319 0.9 8.4

326 349 0.8 7.4

387 390 0.7 6.8

573 458 0.6 5.5

1,061 554 0.5 3.9

1 57 37 .. 4

2 60 33 .. 5

5 68 21 0 6

10 63 13 0 13

1 60 24 .. 14

3 59 25 .. 13

4 67 18 .. 12

5 68 12 .. 14

21 62 5 0 12

75,614 65,140 36,960 46,013 58,598 71,470 112,679 129,090 55,311 81,398 106,453 146,524 256,278 58 65 72 70 69 65 57 42 54 51 48 44 34 5 5 2 3 3 3 9 6 3 2 6 7 8 3 1 2 1 2 1 1 8 4 8 8 7 8 63

55

56

58

58

54

53

91

87

86

89

93

93

93 93 92

91 91 91

87 88 84

90 90 90

92 94 90

91 90 92

93 93 94

96 96 95

95 95 94

95 93 97

94 96 93

97 96 97

97 98 95

34 32 36

21 21 21

16 19 9

20 18 24

17 14 24

23 26 19

27 29 23

48 47 48

24 26 23

36 34 38

42 41 43

52 51 53

68 70 66

22 29 15

13 19 7

9 14 4

11 18 5

10 17 5

12 17 7

17 23 11

56 66 47

34 44 25

43 54 33

49 58 39

57 67 49

76 83 69

31 38 25

19 26 13

15 22 8

20 26 13

19 26 12

18 24 13

20 28 14

71 78 65

53 58 47

70 76 62

70 75 63

74 83 67

80 90 72

65 6 64

57 6 62

56 3 44

55 4 49

55 6 56

57 6 65

59 8 71

95 7 71

91 5 55

89 4 54

94 6 72

95 7 77

97 10 77

70 7 17 ..

72 2 20 ..

57 1 39 ..

62 4 28 ..

67 2 25 ..

70 2 18 ..

79 2 14 ..

62 25 8 ..

66 8 22 ..

67 13 14 ..

57 27 12 ..

64 25 6 ..

61 31 3 ..

52 .. .. 43 31 47

43 .. .. 46 32 50

32 .. .. 45 35 52

42 .. .. 46 32 51

43 .. .. 47 33 51

46 .. .. 44 32 49

50 .. .. 47 30 48

94 .. .. 33 28 35

86 .. .. 34 24 31

94 .. .. 29 33 38

93 .. .. 36 33 43

96 .. .. 36 28 38

98 .. .. 31 24 28

35 90 83

20 88 80

12 88 80

16 90 80

18 90 80

20 88 81

25 85 79

91 98 97

70 98 94

85 97 96

92 97 96

95 97 96

97 98 98

27 19 .. 9

15 5 .. 10

14 4 .. 10

16 5 .. 11

15 4 .. 11

15 5 .. 11

16 6 .. 10

72 70 .. 3

52 44 .. 8

63 59 .. 4

75 71 .. 5

76 74 .. 2

77 76 .. 1

95 91 4

98 96 2

99 97 2

99 98 1

99 98 1

99 97 2

96 94 3

85 73 12

99 99 1

99 94 5

98 93 5

93 82 11

67 47 21

a. Components may not sum to total because of rounding.

HOUSEHOLD WELFARE

Part IV. Household welfare

95

Table

14.2

Burundi household survey, 1998 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (Burundi francs) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

Rural

Urban

National total

All

Q1

Q2

Q3

Q4

6,668 6,026 1.1 4.9

3,908 5,717 1.1 4.9

740 1,143 1.4 5.5

649 1,153 1.2 5.5

723 1,135 1.2 5.1

817 1,143 1.0 4.7

979 1,144 0.9 4.0

68 0 5 3 23

68 0 5 3 23

57 0 4 2 37

67 0 4 1 27

71 0 4 5 20

71 0 6 3 20

74 0 6 4 17

6,574 74 2 1

5,438 75 2 1

1,438 69 3 2

2,925 77 2 1

4,221 77 2 1

5,910 77 2 1

72

70

63

73

70

73

73

97

94

96

98

99

98

56 60 51

55 59 50

40 44 36

50 56 44

59 62 55

63 69 57

66 67 65

83 83 83

67 67 66

84 84 83

90 89 91

93 93 93

94 94 94

9 10 9 11

7 8 7 ..

2 3 1 ..

4 6 3 ..

7 6 8 ..

13 15 12 ..

11 11 11 ..

48 48 48 ..

14 16 13 ..

34 33 35 ..

56 56 56 ..

74 71 76 ..

74 73 74 ..

49 58 42

47 56 39

33 43 26

45 55 37

47 55 40

52 61 44

54 62 47

84 90 79

58 70 50

76 85 68

87 90 83

95 97 93

97 98 97

71 72 71

70 71 70

55 56 55

71 72 70

66 66 66

77 78 77

77 79 76

90 92 89

72 75 69

88 91 86

91 93 90

98 99 97

99 98 100

66 21 60

65 21 59

64 22 51

66 18 54

59 19 59

66 21 62

67 25 69

98 15 72

94 18 52

97 17 69

99 17 77

99 13 86

99 11 87

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. 56 8 44

.. .. .. 59 8 47

.. .. .. 62 8 48

.. .. .. 64 8 50

.. .. .. 56 9 54

.. .. .. 59 9 44

.. .. .. 52 9 38

.. .. .. 30 7 15

.. .. .. 47 5 25

.. .. .. 31 6 19

.. .. .. 23 6 12

.. .. .. 22 5 9

.. .. .. 23 11 9

.. 88 77

.. 87 76

.. 84 76

.. 88 80

.. 87 72

.. 87 77

.. 89 76

.. 97 100

.. 98 100

.. 96 100

.. 98 100

.. 97 100

.. 96 100

85 4 16 66

84 1 14 69

80 1 14 65

83 1 17 66

85 0 14 71

84 1 12 71

87 2 14 71

98 57 40 1

94 11 80 3

96 28 66 2

98 50 48 1

99 76 23 0

100 88 11 1

99 94 5

99 98 1

100 99 0

100 100 ..

98 98 0

100 100 0

98 95 4

97 15 82

99 54 46

100 23 77

99 11 88

98 4 94

93 2 91

Q5

All

Q1

Q2

Q3

Q4

Q5

2,760 309 0.7 4.8

473 62 1.1 6.4

494 62 0.9 6.1

562 62 0.7 5.0

541 62 0.6 4.7

690 62 0.4 3.3

66 0 14 3 17

62 0 5 4 29

72 0 5 3 19

68 .. 10 4 18

68 .. 14 4 13

61 .. 25 3 11

10,765 27,314 4,454 75 48 59 2 3 3 1 3 4

9,137 58 3 4

15,444 26,007 58,137 52 44 37 3 2 2 3 4 2

a. Components may not sum to total because of rounding.

96

Part IV. Household welfare

HOUSEHOLD WELFARE

Table

14.3

Cameroon household survey, 2001 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (CFA francs) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

Q1

10,992 6,017 15,473 10,089 0.9 1.0 5.0 5.0 44 14 18 4 19

46 16 15 4 19

Urban

Q2

Q3

Q4

646 2,019 1.4 7.2

764 2,016 1.3 6.8

1,026 2,019 1.1 5.5

1,217 2,018 0.9 5.0

2,364 2,018 0.6 3.0

50 22 5 5 18

50 22 6 5 17

50 16 11 5 18

48 17 11 4 20

40 11 26 3 20

30,619 22,063 6,609 59 69 68 7 7 7 4 3 3

Q5

All

Q1

Q2

Q3

Q4

Q5

4,975 5,383 0.7 4.9

759 1,077 1.0 7.3

786 1,076 0.8 6.3

886 1,076 0.7 5.7

1,061 1,076 0.5 4.5

1,483 1,078 0.4 3.1

40 9 25 4 21

47 16 15 5 17

49 11 15 4 20

46 10 17 5 22

38 9 26 4 23

32 6 38 4 21

10,217 13,705 18,951 40,025 46,540 11,847 18,846 25,889 37,099 93,334 71 70 69 68 42 48 45 44 42 36 6 7 7 8 7 6 6 7 7 8 3 3 3 3 6 6 7 7 6 5

85

79

75

77

79

77

83

96

96

96

96

95

96

93 93 92

92 93 92

92 93 90

91 92 90

93 94 93

93 93 93

92 90 93

94 94 93

94 94 94

95 95 96

95 95 95

93 94 92

89 91 87

40 39 41 89

29 29 28 ..

14 15 12 ..

22 22 21 ..

28 28 27 ..

33 33 33 ..

48 49 47 ..

57 55 58 ..

38 35 40 ..

53 49 57 ..

59 59 59 ..

64 64 64 ..

72 73 71 ..

68 77 60

56 67 47

50 61 42

50 60 42

55 66 46

58 69 49

62 72 51

88 92 83

76 83 70

85 91 80

89 94 84

92 96 88

94 96 92

82 88 77

73 82 66

69 76 62

69 78 61

76 85 69

74 84 67

78 85 71

94 96 93

89 90 87

93 95 91

95 97 93

96 97 95

97 98 95

90 31 ..

84 31 ..

77 28 ..

83 29 ..

84 31 ..

84 33 ..

88 35 ..

100 31 ..

99 30 ..

100 31 ..

100 31 ..

100 30 ..

100 33 ..

53 13 15 2

55 7 18 3

53 6 18 2

53 5 21 3

53 7 21 4

59 8 15 3

58 9 14 4

48 23 11 1

44 19 18 1

49 20 12 0

51 20 9 1

49 24 7 1

48 31 6 1

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

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

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

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

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

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

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

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

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

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

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

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

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

43 68 90

26 75 85

13 71 82

15 80 85

21 73 84

29 74 86

36 76 88

75 56 99

58 56 99

68 59 99

75 61 99

79 57 100

84 50 99

66 15 27 24

50 6 14 31

47 3 12 32

44 4 11 30

47 4 11 32

48 5 13 30

58 10 17 31

96 32 52 12

88 11 58 19

94 17 62 15

97 24 59 14

97 35 51 10

98 49 41 8

75 75 0

94 93 0

99 99 ..

99 99 ..

97 96 0

96 96 0

86 85 0

41 40 1

75 75 0

58 58 1

51 49 2

34 33 1

17 16 1

a. Components may not sum to total because of rounding.

HOUSEHOLD WELFARE

Part IV. Household welfare

97

Table

14.4

Côte d’Ivoire household survey, 1998 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (CFA francs) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

Q1

Urban

Q2

Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

4,200 16,816 0.8 5.7

2,280 9,225 1.0 5.9

445 2,724 1.2 8.3

403 2,173 1.2 6.9

459 1,880 0.9 6.1

475 1,470 0.8 5.0

498 978 0.7 3.6

1,920 7,590 0.7 5.6

154 578 1.0 8.5

270 1,143 1.0 7.7

307 1,471 0.8 6.7

427 1,889 0.6 5.7

762 2,509 0.5 3.9

58 13 14 3 12

58 18 12 2 10

49 30 7 1 12

63 18 8 2 8

62 18 9 3 7

57 19 12 3 10

59 7 20 2 12

58 7 16 5 14

51 22 6 7 14

52 14 10 5 19

65 9 9 5 12

66 5 11 4 13

55 2 25 4 14

35,406 28,573 57 65 6 6 2 2

7,452 68 4 2

12,962 18,475 27,084 69,649 43,455 65 66 65 63 47 6 5 6 7 7 3 2 2 1 3

8,148 56 5 4

13,222 18,741 27,490 78,858 54 51 49 41 6 6 7 7 4 3 3 3

..

..

..

..

..

..

..

..

..

..

..

..

..

52 55 49

43 47 40

32 37 27

43 45 42

45 51 40

50 52 48

59 65 54

64 67 61

55 58 52

56 59 52

61 66 54

65 68 64

79 84 75

21 26 16 62

10 14 6 ..

5 7 2 ..

8 10 7 ..

13 18 7 ..

16 21 10 ..

13 20 7 ..

31 40 24 ..

15 20 10 ..

20 23 18 ..

34 45 23 ..

36 48 25 ..

39 51 31 ..

48 61 35

33 46 21

24 36 14

31 45 18

34 48 21

38 52 24

43 54 31

64 77 51

44 57 32

56 69 44

61 76 45

64 79 52

76 86 65

61 72 50

47 59 36

38 48 29

46 59 32

50 61 38

51 64 39

55 65 46

73 86 61

60 71 50

70 79 62

75 88 61

71 89 58

79 91 68

.. 15 54

.. 14 48

.. 11 35

.. 11 51

.. 14 48

.. 17 51

.. 17 58

.. 16 60

.. 13 43

.. 14 55

.. 14 58

.. 17 65

.. 20 65

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

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

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

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

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

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

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

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

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

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

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

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

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

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

67 64 ..

42 70 ..

33 65 ..

41 72 ..

41 68 ..

41 69 ..

51 71 ..

96 55 ..

94 55 ..

92 57 ..

95 60 ..

96 56 ..

97 49 ..

78 19 7 51

82 6 2 73

84 4 1 79

83 4 2 77

82 4 3 76

77 8 2 68

84 11 3 69

72 35 13 25

79 18 3 58

72 24 11 37

72 30 9 33

69 34 14 22

74 44 16 14

89 64 25

93 90 3

96 96 0

98 97 1

96 95 2

93 88 4

86 79 7

83 32 51

94 75 19

92 57 35

94 44 50

90 29 60

69 13 56

a. Components may not sum to total because of rounding.

98

Part IV. Household welfare

HOUSEHOLD WELFARE

Table

14.5

Ethiopia household survey, 2000 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (birr) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 5 km away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 5 km away (% of population) Market less than 5 km away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

Q1

16,672 8,459 1,469 54,756 47,531 9,502 1.0 1.1 1.3 4.9 4.9 5.9

Urban

Q2

Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

1,382 9,513 1.2 5.4

1,519 9,504 1.1 5.2

1,678 9,507 1.0 4.8

2,411 9,505 0.8 3.8

8,213 7,225 0.7 4.5

1,118 1,446 1.0 5.6

1,358 1,443 0.9 5.1

1,506 1,446 0.8 4.7

1,883 1,445 0.6 4.3

2,348 1,445 0.5 3.5

68 1 6 1 25

71 1 5 1 23

75 1 3 1 20

72 1 4 1 22

74 1 3 1 21

74 0 4 0 22

64 1 8 1 27

48 0 11 3 38

53 0 6 2 39

50 0 4 4 42

50 0 7 4 39

49 0 10 3 38

41 0 23 2 34

103 66 1 1

93 68 1 0

42 72 1 0

60 71 1 0

75 69 1 0

95 68 1 0

161 62 1 0

162 55 1 2

49 66 1 2

76 62 1 1

103 59 1 2

147 53 1 2

346 43 1 2

..

..

..

..

..

..

..

..

..

..

..

..

..

30 32 29

25 27 22

19 20 18

23 25 20

29 30 28

25 27 21

32 35 29

75 75 75

66 68 64

70 68 71

76 75 77

84 85 82

85 86 84

9 10 8 10

3 4 2 ..

2 4 1 ..

3 3 2 ..

3 3 2 ..

3 5 2 ..

5 7 3 ..

40 43 38 ..

30 29 30 ..

36 38 35 ..

41 47 36 ..

50 54 46 ..

47 54 42 ..

28 41 17

21 34 9

15 26 6

19 32 8

20 33 8

23 39 9

25 39 11

67 81 56

54 70 43

59 75 47

66 80 56

71 86 61

79 91 69

39 50 28

29 43 17

24 35 12

32 47 17

29 43 16

30 45 16

31 42 20

84 90 80

80 84 76

81 86 78

86 91 82

87 95 81

86 95 81

47 26 41

38 27 39

37 27 30

39 27 36

40 27 40

37 26 41

37 31 46

98 20 67

97 20 60

98 20 65

99 20 68

99 19 70

98 20 71

45 45 1 6

44 45 1 7

44 46 0 6

49 40 0 7

45 46 1 5

42 46 1 9

41 48 1 7

52 42 1 4

56 36 0 4

59 36 0 3

52 41 1 4

49 43 2 3

43 51 1 4

.. 45 51 59 11 45

.. 41 47 61 11 46

.. 35 44 64 12 53

.. 48 50 60 11 46

.. 42 47 61 11 48

.. 38 49 61 9 41

.. 45 46 55 11 43

.. 85 90 47 7 27

.. 81 84 56 8 36

.. 81 88 51 9 30

.. 84 90 49 6 27

.. 96 98 43 4 22

.. 88 94 29 7 14

17 90 58

9 99 52

7 90 54

8 89 52

7 88 52

9 90 52

11 87 50

71 98 98

48 97 98

63 98 98

72 98 99

78 98 99

86 99 97

29 0 17 11

19 0 7 12

15 0 7 8

18 0 7 11

18 0 6 12

19 0 6 13

21 0 8 13

92 1 82 8

83 1 74 9

91 1 79 11

93 1 84 8

92 2 83 7

96 2 88 6

77 75 1

78 78 0

82 82 0

78 78 ..

77 77 ..

78 78 ..

77 77 0

66 58 8

80 75 5

74 67 7

70 61 9

65 57 8

51 40 11

a. Components may not sum to total because of rounding.

HOUSEHOLD WELFARE

Part IV. Household welfare

99

Table

14.6

Gambia household survey, 1998 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (dalasi) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

Rural

Urban

National total

All

Q1

Q2

Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

1,958 1,699 0.9 7.8

933 942 1.1 9.2

138 190 1.1 13.6

158 189 1.2 11.2

166 188 1.2 10.2

191 187 1.1 8.6

280 188 0.9 6.1

1,025 757 0.7 6.5

119 151 0.9 11.3

148 152 0.9 8.8

177 151 0.8 7.4

230 151 0.6 5.8

351 153 0.6 3.9

50 27 7 9 7

49 38 4 5 3

36 55 4 5 1

39 48 4 5 3

46 42 2 6 4

57 31 2 6 4

58 28 6 4 4

51 17 10 12 10

43 38 6 9 4

48 27 3 12 9

57 17 6 13 7

55 14 8 12 10

48 8 18 11 14

393 66 1 3

203 73 1 3

51 70 1 3

85 71 1 4

119 73 1 3

166 75 1 3

415 74 1 2

560 60 1 3

121 68 1 4

196 65 1 4

284 65 1 4

423 61 1 3

1,111 52 1 3

..

..

..

..

..

..

..

..

..

..

..

..

..

49 51 46

44 47 41

30 37 23

49 50 47

44 45 42

50 50 50

48 53 44

57 59 54

44 46 42

49 58 42

56 57 54

64 62 67

75 75 75

18 22 14 7

8 11 5 ..

1 1 .. ..

8 11 4 ..

10 15 3 ..

10 12 7 ..

14 18 9 ..

30 36 24 ..

16 21 12 ..

20 28 12 ..

31 34 27 ..

35 40 30 ..

54 57 50 ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. 7 75

.. 8 72

.. 8 72

.. 7 69

.. 8 79

.. 9 75

.. 9 65

.. 6 81

.. 4 78

.. 5 85

.. 6 86

.. 7 81

.. 5 78

82 14 3 ..

82 13 4 ..

84 10 6 ..

80 18 2 ..

82 18 1 ..

80 15 6 ..

87 6 7 ..

82 16 2 ..

77 17 6 ..

88 9 3 ..

90 9 1 ..

78 21 1 ..

75 24 1 ..

.. .. .. 24 7 21

.. .. .. 28 8 26

.. .. .. 34 8 33

.. .. .. 21 6 22

.. .. .. 27 9 23

.. .. .. 29 7 26

.. .. .. 31 8 27

.. .. .. 17 7 13

.. .. .. 27 3 14

.. .. .. 21 7 14

.. .. .. 15 5 17

.. .. .. 10 10 11

.. .. .. 12 13 9

95 .. ..

92 .. ..

96 .. ..

90 .. ..

92 .. ..

93 .. ..

90 .. ..

97 .. ..

99 .. ..

97 .. ..

95 .. ..

96 .. ..

98 .. ..

79 21 38 20

66 2 25 40

74 1 19 54

74 .. 23 51

73 1 32 40

56 2 24 31

63 3 25 34

90 39 50 2

78 15 60 4

85 16 65 4

89 26 63 1

92 39 52 1

96 64 31 1

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

a. Components may not sum to total because of rounding.

100

Part IV. Household welfare

HOUSEHOLD WELFARE

Table

14.7

Ghana household survey, 1998/99 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (cedi) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 5 km away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

Q1

5,998 3,799 18,239 11,493 0.9 1.0 4.4 4.7 53 3 12 12 21

56 4 10 10 20

Urban

Q2

Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

568 2,295 1.2 6.3

625 2,191 1.2 5.7

665 2,267 1.1 5.3

776 2,241 1.0 4.7

1,165 2,500 0.7 3.1

2,199 6,746 0.8 4.0

310 1,150 1.1 5.7

343 1,265 0.9 5.2

403 1,331 0.8 4.5

435 1,440 0.7 4.3

708 1,559 0.5 2.6

63 7 5 8 16

57 5 6 10 21

63 3 4 13 16

57 4 8 9 22

48 2 17 10 23

48 1 15 14 22

49 4 6 20 21

54 2 7 12 25

54 1 7 15 23

57 1 11 14 17

37 0 28 12 24

119,877 91,524 23,107 39,132 55,065 77,592 176,149 161,067 38,436 66,819 96,992 136,526 286,033 59 62 63 64 63 62 61 55 59 56 55 53 53 4 4 3 4 4 4 4 3 3 3 4 4 3 4 3 3 4 4 3 2 5 6 5 5 7 4 ..

..

..

..

..

..

..

..

..

..

..

..

..

61 61 61

54 53 56

39 38 40

48 50 46

53 50 58

68 70 67

68 64 71

74 77 71

67 68 65

70 76 65

73 73 74

81 87 75

79 79 80

10 11 10 13

7 8 6 ..

3 3 3 ..

6 6 6 ..

6 10 3 ..

8 10 7 ..

12 12 12 ..

16 16 15 ..

7 5 9 ..

12 10 13 ..

19 22 17 ..

21 21 21 ..

19 23 16 ..

53 67 40

43 59 29

24 36 13

35 50 23

44 63 28

50 66 36

55 72 39

67 79 57

45 60 34

59 75 47

64 76 54

75 84 67

82 91 73

66 73 59

57 65 47

42 47 34

48 56 39

56 69 42

66 77 55

68 77 58

78 85 72

67 74 59

74 80 67

79 86 70

80 87 75

86 91 81

.. 26 44

.. 28 40

.. 24 33

.. 26 37

.. 27 39

.. 28 39

.. 34 47

.. 23 53

.. 23 42

.. 22 49

.. 21 53

.. 22 56

.. 27 62

47 44 5 4

47 42 6 4

47 43 8 2

39 52 6 3

59 33 4 4

47 42 7 4

45 44 5 6

46 45 5 4

50 35 9 6

49 37 6 7

38 51 7 4

52 42 3 3

45 52 2 2

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

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

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

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

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

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

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

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

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

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

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

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

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

72 98 100

67 97 100

36 98 100

58 97 100

71 97 100

79 98 100

76 97 100

79 98 100

73 97 100

79 96 100

77 97 100

80 99 100

81 99 100

61 4 40 17

48 1 19 28

44 .. 7 38

43 .. 15 28

47 0 15 32

48 1 19 29

54 2 29 22

79 8 70 1

62 0 60 2

74 2 70 3

77 4 71 2

81 8 72 2

86 14 72 1

92 57 35

97 81 16

95 93 2

98 91 7

99 89 10

99 83 16

96 65 31

85 23 62

99 64 35

98 37 61

89 24 65

83 17 66

74 6 68

a. Components may not sum to total because of rounding.

HOUSEHOLD WELFARE

Part IV. Household welfare

101

Table

14.8

Kenya household survey, 1997 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (Kenyan shillings) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

Q1

10,874 8,963 1,339 25,468 21,490 4,298 0.9 1.0 1.3 4.6 4.9 6.4

Urban

Q2

Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

1,521 4,299 1.1 5.8

1,646 4,293 1.0 5.4

1,813 4,303 0.9 4.8

2,644 4,298 0.7 3.3

1,911 3,978 0.6 3.5

273 797 1.0 5.3

262 793 0.8 4.3

327 798 0.5 3.8

514 795 0.4 2.9

535 795 0.3 2.5

58 7 7 12 17

56 8 6 14 17

57 11 2 16 14

55 12 3 14 15

57 7 4 14 17

59 8 4 15 15

53 5 11 11 19

66 4 10 4 17

76 6 2 6 10

63 6 2 3 27

58 4 12 5 20

64 2 12 4 17

68 2 16 2 12

2,244 70 0 3

1,716 74 0 3

455 77 0 3

711 76 0 3

998 77 0 3

1,431 75 0 4

3,569 69 0 3

4,299 57 0 4

1,048 65 0 2

1,637 64 0 4

2,255 58 0 4

3,541 57 0 4

9,396 48 0 5

69

63

57

63

62

64

66

91

88

89

93

90

95

73 72 75

73 71 74

65 64 66

73 71 74

72 69 74

77 77 78

82 82 81

78 77 78

69 66 72

81 87 74

83 81 85

82 78 85

80 74 86

12 12 11 28

10 9 10 ..

4 3 4 ..

6 5 7 ..

9 8 10 ..

13 13 13 ..

18 19 17 ..

29 36 22 ..

10 18 3 ..

14 13 14 ..

22 34 14 ..

38 42 33 ..

62 73 49 ..

78 86 71

75 83 67

67 77 59

72 80 64

74 82 67

78 86 71

79 88 71

92 96 89

87 92 83

91 93 89

94 98 89

93 96 90

95 98 91

94 95 92

93 94 92

91 92 90

91 93 90

94 96 92

94 95 93

95 96 94

95 98 93

92 95 90

98 99 98

95 99 90

95 98 93

96 98 93

72 16 90

65 15 90

56 12 86

62 15 89

61 14 87

66 17 93

73 18 92

98 17 92

98 14 88

99 13 93

98 22 96

98 17 96

99 21 88

32 51 3 7

31 49 3 8

34 48 3 7

30 46 4 12

38 41 4 11

28 53 3 7

27 55 1 6

36 59 2 1

54 41 3 0

35 56 1 1

31 65 2 2

39 54 2 2

28 69 0 1

47 72 83 38 6 22

42 68 80 40 6 24

30 52 69 50 7 32

37 74 80 40 5 26

40 69 83 34 8 21

50 72 83 35 6 19

61 80 91 35 6 19

75 86 92 32 5 13

62 73 87 44 5 20

71 96 96 31 7 12

76 83 91 26 8 14

88 97 100 28 2 7

94 92 92 21 2 8

66 68 82

65 62 78

53 53 77

59 59 79

61 61 78

66 61 77

75 68 79

71 92 99

61 89 99

56 96 98

66 90 99

75 92 99

82 94 100

49 17 19 13

39 10 14 16

29 3 10 16

39 6 15 18

34 8 10 17

41 9 14 18

46 17 17 12

86 44 40 2

81 32 42 6

82 33 46 3

83 38 44 1

91 45 45 1

90 59 30 1

82 73 8

96 91 5

100 99 1

99 97 2

99 97 2

97 93 4

89 78 11

26 5 21

48 16 32

26 5 21

28 2 26

26 4 22

13 2 12

Note: Due to logisitcal and financial constraints, the survey did not adequately cover the northeastern provinces and parts of the eastern provinces. a. Components may not sum to total because of rounding.

102

Part IV. Household welfare

HOUSEHOLD WELFARE

Table

14.9

Madagascar household survey, 1999 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (Malagasy francs) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 5 km away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

5,120 2,880 14,631 11,377 0.9 1.0 5.1 5.2 76 .. 7 8 10

77 .. 7 8 9

Urban

Q1

Q2

Q3

Q4

Q5

All

Q1

Q2

452 2,277 1.3 6.7

495 2,275 1.2 6.1

554 2,277 1.0 5.4

622 2,272 0.9 4.9

757 2,275 0.7 3.8

2,240 3,254 0.7 4.9

298 652 1.1 6.8

367 649 0.9 5.5

415 651 0.7 5.1

487 650 0.6 4.5

673 651 0.5 3.5

77 .. 5 10 8

81 .. 4 7 8

81 .. 4 8 7

80 .. 6 7 8

69 .. 12 8 11

72 .. 6 8 14

74 .. 3 10 13

73 .. 5 11 11

73 .. 3 7 17

73 .. 7 8 12

67 .. 12 5 16

67,747 54,210 15,780 26,142 36,507 51,866 108,173 112,001 26,008 72 75 75 77 76 77 73 63 68 3 3 3 3 3 3 3 4 4 2 2 2 2 2 1 1 3 3

Q3

Q4

Q5

47,759 72,121 107,535 226,090 65 63 62 60 4 4 4 4 4 4 3 2

..

..

..

..

..

..

..

..

..

..

..

..

..

67 67 68

64 63 64

52 55 50

66 63 68

64 65 64

64 63 65

77 74 81

82 82 82

67 66 68

78 74 81

84 91 79

94 97 92

97 95 98

10 9 11 8

6 6 6 ..

2 1 2 ..

4 3 4 ..

4 3 5 ..

6 8 4 ..

16 14 19 ..

24 23 25 ..

6 5 8 ..

18 20 16 ..

24 18 28 ..

34 30 37 ..

46 53 40 ..

67 71 63

61 66 57

44 49 40

58 64 52

58 62 54

66 71 61

74 77 70

84 87 82

66 68 63

81 86 76

85 87 83

90 93 87

94 95 93

70 70 70

64 65 64

47 47 48

60 62 58

63 64 63

72 74 71

78 76 79

87 87 88

69 66 72

89 92 86

91 89 93

91 92 91

95 96 94

.. 11 46

.. 11 42

.. 10 29

.. 10 39

.. 11 41

.. 12 48

.. 13 52

.. 9 61

.. 9 56

.. 11 58

.. 8 61

.. 9 64

.. 9 68

59 32 4 2

61 30 4 3

76 20 3 1

69 22 6 2

68 23 6 2

59 32 2 3

47 42 5 4

53 36 4 1

62 23 4 1

70 21 5 2

56 36 4 1

39 48 5 1

39 53 2 1

.. 61 .. 49 14 35

.. 57 .. 50 15 35

.. 45 .. 50 16 40

.. 57 .. 48 15 33

.. 51 .. 50 16 40

.. 63 .. 52 13 33

.. 76 .. 49 10 29

.. 76 .. 44 14 31

.. 70 .. 48 17 36

.. 78 .. 51 17 36

.. 63 .. 44 11 27

.. 84 .. 42 15 34

.. 91 .. 32 11 18

46 98 ..

38 98 ..

27 99 ..

30 99 ..

34 100 ..

40 99 ..

49 97 ..

72 97 ..

50 98 ..

64 98 ..

73 98 ..

74 96 ..

86 97 ..

24 4 19 1

10 1 8 1

3 .. 3 0

6 .. 5 1

6 .. 6 0

10 1 8 1

19 2 15 2

70 15 52 3

43 1 40 2

57 3 51 3

71 7 60 4

76 16 54 6

85 32 51 2

98 80 18

99 92 7

99 99 0

99 98 1

99 96 3

98 92 6

98 80 18

95 40 55

98 84 14

98 63 35

97 39 59

96 28 69

89 14 75

a. Components may not sum to total because of rounding.

HOUSEHOLD WELFARE

Part IV. Household welfare

103

Table

14.10

Malawi household survey, 1997/98 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (Malawi kwacha) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

Rural

Urban

National total

All

Q1

Q2

Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

6,586 9,795 0.9 4.4

5,657 8,795 0.9 4.4

902 1,760 1.2 5.3

1,024 1,759 1.0 4.8

1,106 1,758 0.9 4.5

1,198 1,759 0.8 4.2

1,427 1,759 0.7 3.6

929 1,000 0.6 4.1

200 200 0.9 5.4

184 200 0.7 4.5

174 200 0.6 4.2

194 200 0.5 3.5

177 200 0.4 3.6

68 1 6 7 18

68 1 5 8 18

65 0 2 10 23

68 1 3 8 20

71 1 3 8 18

70 1 6 6 18

66 1 11 7 15

70 .. 14 3 13

78 .. 4 5 13

80 .. 4 3 13

75 .. 9 2 13

65 .. 21 2 11

56 .. 24 4 17

431 71 1 0

308 74 1 0

91 78 1 0

155 77 1 0

218 77 1 0

310 75 1 0

637 67 1 1

1,456 42 2 2

298 56 1 0

510 52 2 1

759 46 1 1

1,212 40 2 1

3,820 26 2 4

..

..

..

..

..

..

..

..

..

..

..

..

..

62 61 63

61 60 62

60 58 63

58 59 57

59 55 62

61 59 63

68 70 66

70 70 70

70 62 80

63 66 60

76 80 72

75 76 73

68 71 65

5 5 5 4

3 3 3 ..

1 1 .. ..

3 4 3 ..

2 2 2 ..

3 3 3 ..

6 7 5 ..

20 21 19 ..

11 12 9 ..

13 11 15 ..

21 25 16 ..

20 20 19 ..

34 36 33 ..

51 62 41

47 58 37

35 47 26

44 55 33

44 55 35

50 61 40

58 68 48

85 89 82

74 83 65

80 88 73

93 96 90

91 90 92

86 86 87

63 69 58

59 66 54

50 58 42

57 62 53

57 64 51

63 68 58

66 73 61

88 90 87

79 85 75

84 88 81

96 98 95

94 93 95

87 87 87

52 28 ..

48 29 ..

46 24 ..

45 27 ..

46 30 ..

48 31 ..

52 34 ..

90 15 ..

78 16 ..

85 18 ..

92 15 ..

96 15 ..

96 13 ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. 87 89 56 11 25

.. 86 89 56 11 26

.. 89 91 58 11 33

.. 85 89 56 12 22

.. 83 87 57 11 27

.. 90 91 58 9 23

.. 84 85 51 11 25

.. 97 99 57 10 17

.. 91 96 54 14 27

.. 100 100 47 17 18

.. 100 100 67 7 11

.. 100 100 68 4 3

.. 100 100 55 .. 5

.. .. 68

.. .. 64

.. .. 63

.. .. 63

.. .. 63

.. .. 65

.. .. 66

.. .. 98

.. .. 96

.. .. 98

.. .. 99

.. .. 98

.. .. 99

50 6 21 23

45 1 19 25

47 0 20 27

46 0 21 24

43 1 18 25

43 1 18 25

46 3 20 24

89 43 39 8

79 13 52 14

83 22 51 11

92 44 45 3

96 49 35 11

93 72 19 2

94 92 2

98 97 0

99 99 0

99 99 0

97 97 ..

97 97 1

96 96 1

67 49 18

94 76 18

88 68 20

78 56 22

59 40 18

29 18 12

a. Components may not sum to total because of rounding.

104

Part IV. Household welfare

HOUSEHOLD WELFARE

Table

14.11

Mozambique household survey, 1996 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (meticais) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 5 km away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

8,250 5,811 15,867 12,634 0.9 0.9 4.8 4.7 65 8 5 6 15

65 9 5 6 15

Urban

Q1

Q2

Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

987 2,527 1.2 6.6

948 2,518 1.1 5.8

1,059 2,536 1.0 5.1

1,215 2,527 0.9 4.3

1,602 2,527 0.6 3.2

2,439 3,233 0.9 5.5

337 646 1.3 6.2

383 647 1.1 6.1

463 647 0.9 5.7

519 647 0.8 5.2

737 646 0.6 4.5

66 15 2 5 13

68 10 2 9 12

67 10 4 6 14

66 8 4 6 16

60 7 9 7 17

66 3 8 5 17

63 2 2 7 25

71 5 6 4 15

67 5 6 5 18

65 4 10 5 16

65 2 14 6 13

192,481 182,572 53,118 86,604 119,027 164,442 350,674 237,861 52,180 93,179 132,226 203,191 592,973 68 70 68 71 72 71 69 59 63 65 61 60 51 0 0 0 0 0 0 0 1 1 1 0 0 0 0 0 1 1 0 0 0 1 2 1 1 1 1 ..

..

..

..

..

..

..

..

..

..

..

..

..

36 38 33

32 35 29

25 27 22

30 32 27

33 36 31

36 39 33

39 42 35

54 54 53

34 34 34

48 53 43

60 63 57

68 70 67

71 66 76

10 10 9 7

5 6 4 ..

3 4 2 ..

3 3 3 ..

6 7 4 ..

7 8 5 ..

7 9 5 ..

26 26 25 ..

11 14 8 ..

15 19 11 ..

23 22 24 ..

34 37 31 ..

44 40 47 ..

41 58 25

33 51 17

28 44 14

33 51 16

35 53 19

33 52 16

35 53 20

72 84 60

52 70 36

62 80 45

73 84 63

79 88 70

86 94 78

51 64 40

42 56 29

35 42 28

42 56 28

47 61 34

39 57 25

45 63 32

82 88 76

71 79 61

75 87 65

83 89 78

86 91 82

90 93 88

.. 11 60

.. 12 57

.. 9 54

.. 10 58

.. 11 55

.. 13 59

.. 15 59

.. 11 74

.. 11 64

.. 10 71

.. 10 73

.. 12 83

.. 11 76

78 6 14 2

74 5 18 2

68 3 23 6

76 6 16 2

73 6 18 2

82 4 13 1

72 6 21 1

88 9 2 0

90 10 0 ..

83 13 4 0

94 4 2 0

85 13 2 0

89 7 4 0

.. 43 57 55 9 37

.. 35 50 61 9 40

.. 30 42 61 11 49

.. 32 56 62 7 38

.. 36 46 62 7 39

.. 38 48 59 11 36

.. 41 56 58 8 37

.. 76 88 34 9 25

.. 82 84 49 13 38

.. 53 84 36 11 27

.. 86 93 30 6 20

.. 85 92 27 6 18

.. 80 91 24 7 19

35 94 ..

29 93 ..

26 92 ..

29 94 ..

28 92 ..

29 93 ..

29 94 ..

67 99 ..

44 99 ..

55 98 ..

70 99 ..

76 98 ..

81 100 ..

18 2 16 ..

11 0 11 ..

9 0 9 ..

8 0 8 ..

10 0 10 ..

10 0 10 ..

14 1 14 ..

51 9 41 ..

42 0 41 ..

40 2 38 ..

48 5 43 ..

53 9 44 ..

65 25 40 ..

97 90 7

99 99 0

99 99 0

99 99 0

99 99 0

98 98 0

99 98 1

87 50 37

97 70 27

96 66 30

94 51 44

86 41 45

70 31 38

a. Components may not sum to total because of rounding.

HOUSEHOLD WELFARE

Part IV. Household welfare

105

Table

14.12

Nigeria household survey, 2004 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (Nigerian naira) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

Q1

Q2

Urban Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

19,158 14,512 2,321 2,446 2,717 3,120 3,908 4,646 783 779 834 988 1,262 126,305 70,599 14,115 14,127 14,116 14,122 14,118 55,706 11,144 11,138 11,140 11,131 11,153 0.8 0.9 1.1 1.0 0.9 0.8 0.6 0.8 0.8 0.9 0.8 0.7 0.5 4.7 4.8 6.5 6.0 5.2 4.5 3.4 4.6 5.6 5.7 5.1 4.4 3.3 58 15 11 3 13

58 18 9 2 12

54 32 4 2 8

63 26 3 2 7

65 20 5 2 9

62 14 8 2 14

51 8 19 3 19

57 12 14 3 14

56 16 10 4 13

9,939 16,272 13,705 64 54 45 7 16 7 3 3 8

4,548 36 4 11

61 17 7 3 12

59 15 8 4 14

59 10 13 3 16

51 7 25 3 14

11,635 54 8 5

9,924 61 8 3

3,922 57 3 4

6,391 65 4 3

8,008 65 5 3

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

62 69 54

50 57 43

38 44 31

42 49 36

48 55 41

55 62 49

63 71 54

75 83 68

71 78 65

68 77 59

73 81 65

80 86 73

83 89 75

78 82 73

68 74 62

55 60 50

60 67 53

66 75 58

72 81 65

81 86 77

88 90 86

84 85 82

86 88 84

89 92 85

93 96 90

89 92 87

.. 12 57

.. 12 57

.. 8 31

.. 10 41

.. 11 50

.. 14 62

.. 21 74

.. 11 57

.. 7 30

.. 9 50

.. 10 56

.. 11 58

.. 17 71

38 57 2 3

37 58 2 3

27 69 1 3

26 69 1 4

31 63 2 4

32 64 1 3

47 49 2 3

40 55 1 4

36 58 6

41 54 2 4

41 56 0 3

39 56 1 4

40 53 2 4

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

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

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

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

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

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

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

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

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

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

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

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

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

60 .. ..

50 .. ..

47 .. ..

48 .. ..

50 .. ..

50 .. ..

52 .. ..

72 .. ..

73 .. ..

71 .. ..

71 .. ..

72 .. ..

75 .. ..

61 13 11 38

42 4 4 34

41 3 3 35

41 3 4 35

43 4 5 35

41 3 4 34

43 5 5 33

83 23 18 42

81 18 24 39

82 21 18 43

82 23 17 42

86 24 17 45

84 28 16 40

65 64 1

88 87 0

92 92 0

93 93 0

91 90 1

89 89 0

79 79 1

38 37 1

44 42 2

52 51 1

43 42 1

36 35 1

24 23 2

8,809 11,580 14,279 22,892 51 51 50 41 5 6 6 13 7 8 7 7

Note: Data are provisional. a. Components may not sum to total because of rounding.

106

Part IV. Household welfare

HOUSEHOLD WELFARE

Table

14.13

São Tomé and Principe household survey, 2000 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (dobras) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

Q1

Q2

Urban Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

2,416 128 0.9 4.6

1,173 57 1.0 4.5

179 11 1.3 6.3

197 11 1.1 5.7

215 11 1.0 4.9

244 11 1.0 4.2

338 11 0.6 3.0

1,243 71 0.8 4.6

187 14 1.1 6.2

202 14 1.0 5.5

242 14 0.8 4.9

264 14 0.8 4.4

348 14 0.6 3.3

51 .. 16 7 25

53 .. 18 6 23

62 .. 9 5 25

66 .. 5 5 24

66 .. 10 5 19

48 .. 16 8 27

37 .. 36 7 20

50 .. 15 8 27

51 .. 4 7 37

50 .. 9 11 29

46 .. 12 12 30

56 .. 14 5 25

46 .. 26 8 20

451,490 318,313 80,362 128,371 175,196 243,054 679,373 560,829 108,471 179,366 252,850 359,041 1,403,366 72 75 78 77 78 76 71 69 76 74 69 68 62 3 3 3 3 2 3 3 4 3 3 4 3 5 2 2 2 2 2 2 1 3 2 3 3 3 2 34

33

46

44

37

35

16

35

51

39

35

38

23

70 71 69

67 70 64

68 67 68

68 75 60

63 62 63

68 71 64

67 70 63

73 73 73

71 72 69

73 71 75

78 75 81

73 80 65

74 66 79

43 43 42 ..

29 29 28 ..

13 15 11 ..

26 24 28 ..

23 24 22 ..

34 42 25 ..

50 47 51 ..

52 52 52 ..

32 30 35 ..

39 41 37 ..

64 65 62 ..

62 66 59 ..

64 66 63 ..

83 92 76

80 89 72

76 87 67

82 89 76

79 89 70

77 87 69

85 92 77

86 94 79

78 90 68

83 92 75

85 92 80

89 95 84

91 97 84

94 95 93

92 93 91

90 95 86

92 91 92

91 90 92

91 94 88

95 96 95

96 96 95

91 94 88

94 96 92

98 97 98

98 98 98

96 98 95

84 18 48

81 15 45

77 12 41

74 14 45

81 14 40

82 17 50

85 20 47

87 19 50

86 12 38

90 19 44

85 19 50

89 22 56

87 24 57

70 25 3 1

81 14 2 2

94 4 .. 2

88 9 3 ..

78 16 .. 6

83 10 3 3

68 27 4 1

64 31 4 1

80 15 5 ..

78 18 1 3

68 29 3 ..

62 32 6 ..

53 43 2 2

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

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

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

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

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

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

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

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

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

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

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

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

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

28 88 87

21 93 81

18 93 74

12 94 73

20 93 80

20 95 86

27 92 86

35 84 92

14 82 90

26 80 88

36 87 91

41 86 93

46 85 94

77 20 8 49

67 10 13 44

74 7 19 48

70 9 15 46

64 7 15 42

70 13 11 46

63 12 10 41

84 27 4 53

82 12 4 65

79 20 3 56

81 26 5 49

89 29 5 56

88 40 4 43

84 73 11

95 91 4

100 98 1

98 96 2

99 97 2

94 90 4

88 82 6

75 59 16

96 88 8

83 74 9

81 63 18

72 50 22

57 36 20

a. Components may not sum to total because of rounding.

HOUSEHOLD WELFARE

Part IV. Household welfare

107

Table

14.14

Sierra Leone household survey, 2002/03 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (leones) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

Q1

Q2

Urban Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

3,713 5,337 0.9 7.4

2,396 3,440 1.0 7.3

412 688 1.1 8.2

451 689 1.0 7.6

453 688 1.0 7.5

511 688 0.9 6.8

569 688 0.9 6.3

1,317 1,897 0.8 7.5

223 379 1.0 8.4

246 379 1.0 7.6

277 380 0.8 7.1

276 379 0.7 7.2

295 380 0.6 7.4

61 19 4 2 14

60 23 3 2 12

52 31 2 3 12

56 28 2 1 13

61 26 3 1 10

65 19 3 2 11

64 15 4 2 15

63 10 6 2 19

56 13 2 1 27

62 13 3 3 19

66 13 3 2 16

67 8 7 2 16

64 6 14 1 16

294,515 239,364 103,175 150,703 197,851 237,999 438,780 378,978 154,151 242,246 322,612 385,918 685,453 52 59 60 61 62 61 53 42 49 46 45 43 32 10 2 6 9 7 10 14 13 9 10 12 12 19 4 2 3 2 2 2 2 6 5 6 6 6 5

73 72 74

67 66 68

62 58 66

64 65 63

67 66 68

69 70 67

75 72 77

86 85 86

78 78 78

85 83 87

89 88 90

87 88 87

91 93 89

19 22 17 ..

10 13 7 ..

7 9 4 ..

7 10 3 ..

11 12 9 ..

10 13 7 ..

18 22 13 ..

33 36 30 ..

27 31 23 ..

23 28 18 ..

24 24 24 ..

37 47 27 ..

51 48 54 ..

27 35 19

13 20 8

11 17 6

10 17 5

11 17 6

14 21 8

20 27 14

49 58 40

32 43 24

37 50 26

41 49 33

52 59 46

75 81 68

40 47 33

23 31 16

18 26 12

17 24 11

17 25 11

28 36 20

35 42 27

62 68 55

49 59 39

51 62 42

56 64 48

62 65 60

81 85 78

.. 44 59

.. 42 65

.. 34 49

.. 40 64

.. 42 67

.. 42 68

.. 49 75

.. 45 56

.. 37 41

.. 44 50

.. 45 49

.. 45 58

.. 54 75

53 30 9 8

55 27 11 7

50 16 23 11

39 31 16 14

53 27 12 8

51 33 8 9

61 25 9 5

51 36 4 8

51 18 6 25

52 32 5 11

49 28 12 12

55 31 5 10

51 48

.. 72 16 .. .. ..

.. 72 16 .. .. ..

.. 74 16 .. .. ..

.. 57 24 .. .. ..

.. 64 15 .. .. ..

.. 71 13 .. .. ..

.. 96 8 .. .. ..

.. 73 18 .. .. ..

.. 70 19 .. .. ..

.. 75 17 .. .. ..

.. 71 21 .. .. ..

.. 63 21 .. .. ..

.. 87 9 .. .. ..

4 .. ..

2 .. ..

2 .. ..

2 .. ..

1 .. ..

2 .. ..

4 .. ..

7 .. ..

1 .. ..

2 .. ..

4 .. ..

5 .. ..

23 .. ..

37 7 12 18

25 1 5 19

24 0 6 18

25 1 8 17

23 1 5 17

22 0 3 20

31 4 5 22

59 18 24 17

40 0 19 21

51 3 23 24

52 10 19 22

67 20 33 15

79 49 23 7

97 93 5

99 98 1

99 98 1

99 98 1

99 98 1

99 98 0

98 97 1

95 83 12

99 98 1

98 96 2

98 91 7

95 83 12

86 55 32

2

Note: Data are provisional. a. Components may not sum to total because of rounding.

108

Part IV. Household welfare

HOUSEHOLD WELFARE

Table

14.15

Uganda household survey, 2002/03 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (Ugandan shillings) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 1 hour away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Missionary or nongovernmental organization Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 1 hour away (% of population) Market less than 1 hour away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total

Rural All

Q1

9,710 5,648 937 25,273 21,795 4,359 1.2 1.3 1.7 5.1 5.3 6.4

Urban

Q2

Q3

Q4

Q5

All

Q1

Q2

Q3

Q4

Q5

1,019 4,358 1.5 5.9

1,036 4,358 1.4 5.8

1,182 4,363 1.2 5.3

1,474 4,357 0.9 4.0

4,062 3,477 0.8 4.1

894 695 1.3 5.7

877 696 1.1 4.6

766 696 0.8 4.3

701 696 0.6 4.0

824 695 0.4 3.0

54 12 8 8 18

56 13 7 8 16

56 13 3 10 18

61 12 3 9 15

60 14 4 8 14

57 14 6 8 15

50 12 15 7 17

45 7 12 9 27

52 9 5 8 25

53 8 6 8 25

45 7 13 6 28

45 8 14 7 27

37 3 18 12 30

1,523 56 4 4

1,322 58 4 4

593 60 2 4

854 62 3 3

1,121 61 3 4

1,393 59 4 4

2,175 52 6 5

2,499 43 7 4

864 52 5 3

1,208 49 6 3

1,689 45 6 5

2,281 42 6 4

4,926 34 9 3

..

..

..

..

..

..

..

..

..

..

..

..

..

63 62 64

62 61 63

50 51 50

59 58 60

63 63 64

67 65 68

73 72 74

73 71 75

64 63 64

69 65 73

80 77 82

75 75 75

82 78 86

13 13 14 3

11 11 12 ..

2 1 2 ..

5 4 5 ..

10 7 14 ..

15 19 11 ..

22 21 23 ..

26 26 27 ..

15 13 17 ..

19 23 16 ..

27 26 28 ..

30 29 31 ..

40 39 41 ..

70 80 61

66 77 56

49 66 34

61 75 48

66 75 58

71 81 62

79 85 73

87 91 84

72 80 65

83 91 77

86 90 82

92 93 92

95 95 94

80 85 76

78 83 73

62 72 52

73 84 63

79 83 76

81 86 77

86 88 84

90 91 89

78 80 77

89 92 86

88 88 88

94 93 94

95 96 95

.. 29 93

.. 29 92

.. 28 87

.. 28 91

.. 28 94

.. 29 94

.. 33 95

.. 28 94

.. 25 91

.. 29 91

.. 29 96

.. 28 96

.. 28 97

30 64 1 5 0

32 62 1 5 0

44 51 1 4 0

36 59 1 3 1

29 63 2 5 0

25 67 1 6 0

26 65 1 7 1

18 76 1 5 1

28 66 2 4 0

23 72 1 3 0

18 77 0 5 0

15 78 0 7 ..

10 84 0 4 2

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

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

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

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

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

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

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

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

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

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

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

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

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

76 .. ..

72 .. ..

50 .. ..

67 .. ..

74 .. ..

77 .. ..

84 .. ..

95 .. ..

86 .. ..

94 .. ..

96 .. ..

98 .. ..

99 .. ..

60 .. 9 51

56 .. 2 54

57 .. 1 56

55 .. 1 54

55 .. 1 54

56 .. 2 54

57 .. 5 52

81 .. 48 34

77 .. 22 55

79 .. 34 45

81 .. 46 35

82 .. 58 24

85 .. 65 20

97 79 18

98 90 8

99 97 1

99 96 3

99 97 3

99 92 8

97 76 20

89 22 67

99 54 45

97 33 64

93 19 74

93 12 81

73 7 66

Note: The survey did not collect data in the Kitgum, Gulu, Kasese, and Bundibugio districts. a. Components may not sum to total because of rounding.

HOUSEHOLD WELFARE

Part IV. Household welfare

109

Table

14.16

Zambia household survey, 1998 Expenditure quintile

Indicator Demographic indicators Sample size (households) Total population (thousands) Age dependency ratio Average household size Marital status of head of household (%) Monogamous male Polygamous male Single male De facto female De jure female MDG 1: extreme poverty and hunger Mean monthly expenditure (Zambian kwacha) Mean monthly share on food (%) Mean monthly share on health (%) Mean monthly share on education (%) MDGs 2 and 3: education and literacy; gender equality Primary school within 30 minutes (% of households) Net primary enrollment rate (% of relevant age group) Total Male Female Net secondary enrollment rate (% of relevant age group) Total Male Female Tertiary enrollment rate (per 10,000) Adult literacy rate (%) Total Male Female Youth literacy rate (% ages 15–24) Total Male Female MDGs 4 and 5: child mortality; maternal health Health center less than 5 km away (% of population) Morbidity (% of population) Health care provider consulted when sick (%) Type of health care provider consulted (% of total) Public Private, modern medicine Private, traditional healers Other Child survival and malnutrition (%) Birth assisted by trained staff Immunization coverage, 1-year-olds Measles immunization coverage, 1-year-olds Stunting (6–59 months) Wasting (6–59 months) Underweight (6–59 months) MDG 7: environmental sustainability Access to sanitation facilities (% of population) Water source less than 5 km away (% of population) Market less than 5 km away (% of population) Access to improved water source (% of population) Totala Own tap Other piped Well, protected Traditional fuel use (%) Totala Firewood Charcoal

National total 16,422 9,989 0.9 5.4 70 .. 7 3 19

Rural All

Q1

8,317 1,414 6,276 1,239 0.9 1.0 5.3 6.0 70 .. 6 4 19

66 .. 3 4 26

46,798 32,948 5,268 68 74 76 1 1 1 2 2 3

Urban

Q2

Q3

Q4

Q5

All

Q1

1,461 1,252 1.0 5.7

1,561 1,265 0.9 5.5

1,655 1,260 0.9 5.2

2,226 1,260 0.8 4.3

8,105 3,712 0.8 5.5

69 .. 5 5 21

75 .. 4 4 17

73 .. 7 3 17

67 .. 11 4 18

70 .. 10 2 18

Q2

Q3

Q4

Q5

1,298 712 1.0 6.9

1,384 743 0.9 6.3

1,518 752 0.8 6.0

1,752 752 0.7 5.2

2,153 753 0.5 4.2

68 .. 6 2 23

74 .. 6 2 18

76 .. 7 2 16

72 .. 9 3 16

62 .. 17 2 19

11,113 17,218 27,740 85,708 71,512 13,061 25,361 37,361 56,295 174,264 77 75 72 70 57 67 63 59 56 45 1 1 1 2 2 1 2 2 2 2 2 2 1 1 4 4 4 4 3 3

..

..

..

..

..

..

..

..

..

..

..

..

..

66 65 66

59 59 59

46 49 44

55 56 55

60 59 60

67 66 68

70 70 69

77 77 77

65 64 65

75 77 73

78 77 79

84 82 84

86 87 86

23 25 22 34

14 16 12 ..

8 10 5 ..

10 11 8 ..

14 16 12 ..

18 20 17 ..

21 24 18 ..

38 40 36 ..

21 21 21 ..

31 33 28 ..

36 38 34 ..

45 52 40 ..

55 58 53 ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

.. .. ..

67 11 37

50 12 33

47 9 30

49 12 31

51 12 31

50 14 34

52 15 38

97 10 46

96 10 38

97 9 43

97 8 43

98 10 45

98 11 56

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. .. .. ..

.. 59 89 62 6 27

.. 56 87 66 6 30

.. 46 79 70 8 37

.. 54 88 65 5 30

.. 56 88 65 6 32

.. 57 90 62 5 26

.. 67 92 65 5 24

.. 64 94 57 5 23

.. 64 95 64 6 31

.. 68 92 64 5 27

.. 58 93 55 5 20

.. 61 92 54 5 20

.. 70 95 45 5 14

78 98 60

68 98 38

57 98 35

65 97 36

69 98 34

70 98 40

74 98 43

98 100 99

95 100 97

97 100 99

98 100 99

98 100 99

99 100 99

56 16 17 23

37 1 4 32

33 0 3 29

35 0 3 31

38 1 3 34

36 1 4 31

42 4 5 33

89 41 40 8

79 27 41 11

87 35 42 9

91 39 43 8

91 42 43 7

93 55 32 6

85 62 23

99 90 9

100 95 5

100 93 7

99 91 9

99 89 9

97 84 13

60 12 48

85 29 57

74 11 63

65 9 56

54 6 47

37 8 29

a. Components may not sum to total because of rounding.

110

Part IV. Household welfare

HOUSEHOLD WELFARE

Technical notes General notes .. means that data are not available or that aggregates cannot be calculated because of missing data in the years shown $ means U.S. dollars A blank means not applicable or, for an aggregate, not analytically meaningful. A billion is 1,000 million. 1. Basic indicators T .. B  Population is World Bank estimates, usually projected from the most recent population censuses or surveys (mostly from 1980– 2004). Refugees not permanently settled in the country of asylum are generally considered to be part of the population of their country of origin. Land area is the land surface area of a country, excluding inland waters. Gross national income (GNI) per capita is the total domestic and foreign value added claimed by residents, which comprises gross domestic Box 1

product plus net factor income from abroad (the income residents receive from abroad for factor services including labor and capital) less similar payments made to nonresidents who contribute to the domestic economy, divided by midyear population. It is calculated by the World Bank Atlas method (box 1). Growth rates are shown in real terms. They have been calculated by the least-squares method using constant (2000) GNI per capita series in national currency (see also table 2.21). 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.

The World Bank Atlas method

The World Bank Atlas method uses a three-year average of conversion factors to convert gross national income (GNI) data, expressed in different national currencies, to a common denomination, conventionally U.S. dollars. 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, after adjusting them for differences in relative inflation between that country and the United States. This three-year average smoothes fluctuations in prices and exchange rates for each country. 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.

The following formulas describe the procedures for computing the conversion factor for year t:

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

where Yt = current GNI (local currency) for year t, Pt = GNI deflator for year t, Nt midyear population for year t, and P$ t = U.S. GNI deflator for year t.

Technical notes

111

Gini coeﬃcient is the most commonly used measure of inequality. The coeﬃcient varies between 0, which reﬂects complete equality, and 1, which indicates complete inequality (one person has all the income or consumption, all others have none). Graphically, the Gini coeﬃcient can be easily represented by the area between the Lorenz curve and the line of equality. 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. Total net oﬃcial development assistance per capita is net disbursements of loans and grants from all oﬃcial sources on concessional ﬁnancial terms divided by the midyear population for the corresponding year Regional aggregates for GNI per capita, life expectancy at birth, and adult literacy rates are weighted by population.

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 country desk data. T .. G    ,  Gross domestic product (GDP) per capita, real, is calculated by dividing GDP (see table 2.1) by corresponding midyear population. Source: World Bank country desk data.

Source: Data on population, land area, GNI per capita, life expectancy at birth, under-ﬁve mortality, Gini coeﬃcient, and adult literacy are from the World Bank’s World Development Indicators database. Data on aid ﬂows are from the Organisation for Economic Cooperation and Development’s Geographic Distribution of Aid Flows to Developing Countries database. 2. National accounts T .. G  ,  Gross domestic product (GDP), real, is the total output of goods and services for ﬁnal use produced by residents and nonresidents, regardless of the allocation to domestic and foreign claims. It is calculated without making deductions for depreciation of fabricated capital assets or depletion and degradation of natural resources. GDP ﬁgures are shown at market prices (also known as purchaser values) and have been converted 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. The sum of the components of GDP by industrial origin (presented here as value 112

Africa Development Indicators 2006

T .. A   Agriculture value added is shown at factor cost. It comprises the gross output of forestry, hunting, and ﬁshing less the value of their intermediate inputs. However, for Botswana, Cameroon, Chad, Democratic Republic of Congo, Republic of Congo, Gabon, Guinea, Madagascar, Mali, Morocco, Niger, Rwanda, Senegal, Togo, and Zambia, it is shown at market prices, that is, including intermediate inputs. Source: World Bank country desk data. T .. I   Industry value added is shown at factor cost. It comprises the gross output of mining, manufacturing, construction, electricity, water, and gas, less the value of their intermediate inputs. However, for Botswana, Cameroon, Chad, Democratic Republic of Congo, Republic of Congo, Gabon, Guinea, Madagascar, Mali, Morocco, Niger, Rwanda, Senegal, Togo, and Zambia, it is shown at market prices, that is, including intermediate inputs. Source: World Bank country desk data. T .. S   Services value added is shown at factor cost and consists of the gross output of all other

branches of economic activity, including government, less the value of their intermediate inputs. However, for Botswana, Cameroon, Chad, Democratic Republic of Congo, Republic of Congo, Gabon, Guinea, Madagascar, Mali, Morocco, Niger, Rwanda, Senegal, Togo, and Zambia, it is shown at market prices, that is, including intermediate inputs. Other items, such as imputed bank service charges (which are diﬃcult to assess in the same fashion for all countries) and any corrections for statistical discrepancies, are not included. Source: World Bank country desk data. T .. G  ,  Gross domestic product (GDP), nominal is obtained by converting national currency GDP series in current prices to U.S. dollars at ofﬁcial annual exchange rates. Source: World Bank country desk data. T .. Total consumption Total consumption is the sum of private consumption and general government consumption (table 2.8). Private consumption, not separately shown here, is the value of all goods and services purchased or received as income in kind by households and nonproﬁt institutions. It excludes purchases of dwellings, but includes imputed rent for owneroccupied dwellings. In practice, it includes any statistical discrepancy in the use of resources. Source: World Bank country desk data. T .. G   General government consumption includes 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 country desk data. T .. G    Gross ﬁxed capital formation consists of gross domestic ﬁxed capital formation plus net changes in the level of inventories. Gross

capital formation comprises outlays by the public sector (table 2.10) and the private sector (table 2.11). 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 country desk data. T .. G     General government ﬁxed capital formation is gross domestic ﬁxed capital formation (see table 2.9) for the public sector. Source: World Bank country desk data. T .. P     Private sector ﬁxed capital formation is gross domestic ﬁxed capital formation (see table 2.9) for the private sector. Source: World Bank country desk data. T .. G   Gross domestic savings is calculated by deducting total consumption (table 2.7) from nominal gross domestic product (table 2.6). Source: World Bank country desk data. T .. G   Gross national savings is the sum of gross domestic savings (table 2.12), net factor income from abroad, and net private transfers from abroad. The estimate here also includes net public transfers from abroad. Source: World Bank country desk data. T .. R  (  ) Resource balance is the diﬀerence between free on board exports (table 2.15) and cost, insurance, and freight imports (table 2.16) 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 2.6). Source: World Bank country desk data. Technical notes

113

Box 2

Discrepancies in gross domestic product growth estimates for Sub-Saharan Africa

Three major databases supply information on gross domestic product (GDP) growth rates: the World Bank Africa Region Live Database (AFRLDB), the World Bank World Development Indicators (WDI) database, and the International Monetary Fund (IMF) World Economic Outlook (WEO) database. The GDP growth rates presented in the World Bank databases and the IMF database often differ, sometimes substantially. For example, the 2004 GDP regional growth rate was cited as 4.3 percent by the AFRLDB and 5.2 percent by the WEO (see figure).

To calculate the growth of regional aggregates, the two World Bank databases use the ratio of the sum method. This method converts individual country GDP in current local currency into base year U.S. dollars using the base year exchange rate. The aggregate GDP growth rate is then calculated as the total regional GDP in base year U.S. dollars (the ratio of the sum). The implicit weighting variable of this method is the country GDP in constant U.S. dollars. The IMF database uses the sum of the ratios method. This method first calculates the

Sub-Saharan Africa annual GDP growth reported by different databases Percentage

6 5 4 3 2 1 0 –1 –2

1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 WDI

AFRLDB

IMF

Source: World Bank Africa Region Live Database, World Bank World Development Indicators database, and International Monetary Fund World Economic Outlook database.

The minor difference between the two World Bank databases is due to different frequencies of data updates. The sometimes substantial differences between the World Bank and the IMF databases are due to three main reasons: data source, aggregation methodology, and selection of the weighting variable. For data sources, the two World Bank databases use the GDP estimates reported by the Bank’s country economists, while the IMF database uses the estimates reported by IMF country economists. Although the World Bank and the IMF country economists coordinate their GDP estimates, some differences remain.

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GDP growth rates of each individual country using the country GDP in constant local currency. The aggregate GDP growth rate is then calculated using the country growth rates and the country GDP in current purchasing power parity U.S. dollars as the weighting variable (the sum of ratios). The implications of these differences are twofold. If the difference is small, it causes confusion. If the difference is large, it can cause serious miscalculation in economic planning or in policymaking. For further details visit the Africa Region Office of the Chief Economist’s website at www.worldbank.org/afr/ce.

T .  .. E      ,  Exports and imports of goods and services, nominal, comprise all transactions between residents of an economy and the rest of the world involving a change in ownership of general merchandise, goods sent for processing and repairs, nonmonetary gold, and services expressed in current U.S dollars. Source: World Bank country desk data. T .  .. E      ,  Exports and imports of goods and services, real, are deﬁned as in tables 2.15 and 2.16, but expressed in constant 2000 U.S. dollars. Source: World Bank country desk data. T .. G    Gross domestic product (GDP) growth is the average annual growth rates of real GDP (table 2.1). See box 2 for information on discrepancies in GDP growth estimates for Sub-Saharan Africa.

dollars (see table 2.7) by the corresponding midyear population. Source: World Bank country desk data. 3. Millennium Development Goals T .. M D G :      Survey year is the year in which the underlying data were collected. 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 population below purchasing power parity (PPP) $1 a day is the percentage of the Table 1

Method used to calculate regional aggregates and period averages in section 2

Table 2.1 Gross domestic product, real

Method 1

T .. G      Gross domestic product (GDP) per capita growth is the average annual growth rate of real GDP per capita (table 2.2). Source: World Bank country desk data. T .. G     Gross national income (GNI) per capita is calculated using the World Bank Atlas method (see box 1). It similar in concept to GNI per capita in current prices, except that the use of threeyear averages of exchange rates smoothes out sharp ﬂuctuations from year to year. Source: World Bank country desk data. T .. T    Total consumption per capita is obtained by dividing total consumption at current U.S.

Method 3

Method 4

Method 5

X

2.2 Gross domestic product per capita, real

Source: World Bank country desk data.

Method 2

X X

X

2.3 Agriculture value added

X

X

2.4 Industry value added

X

X

2.5 Services value added

X

2.6 Gross domestic product, nominal

X

X X

2.7 Total consumption

X

X

2.8 General government consumption

X

X

2.9 Gross fixed capital formation

X

X

2.10 General government fixed capita formation

X

X

2.11 Private sector fixed capital formation

X

X

2.12 Gross domestic savings

X

X

2.13 Gross national savings

X

2.15 Exports of goods and services, nominal

X X

2.14 Resource balance (exports minus imports)

X

X

X X

2.16 Imports of goods and services, nominal

X

2.17 Exports of goods and services, real

X

X

2.18 Imports of goods and services, real

X

X

2.19 Gross domestic product growth

X

2.20 Gross domestic product per capita growth

X

X X

2.21 Gross national income per capita

X

X

2.22 Total consumption per capita

X

X

Note: Method 1 is the simple total of the gap-filled indicator; method 2 is the simple total of the gap-filled main indicator divided by the simple total of the gap-filled secondary indicator; method 3 is the simple total of the first gap-filled main indicator minus the simple total of the second gap-filled main indicator, divided by the simple total of the secondary indicator; method 4 is the arithmetic mean (using the same series as shown in the table; that is, ratio if the rest of the table is shown as ratio, level if the rest of the table is shown as level, growth rate if the rest is shown as growth rate, and so on); method 5 is the least-squares growth rate (using the main indicator).

Technical notes

115

population living on less than $1.08 a day at 1993 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions. Poverty gap ratio at $1 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 prevalence. 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. Share of population below minimum dietary energy consumption (also referred to as prevalence of undernourishment) is the percentage of the population whose food intake is insuﬃcient to meet dietary energy requirements continuously. A value of 2.5 percent signiﬁes a prevalence of undernourishment of 2.5 percent or less. Source: Data on poverty measures are prepared by the World Bank’s Development Research Group. The national poverty lines are based on the World Bank’s country poverty assessments. The international poverty lines are based on nationally representative primary household surveys conducted by national statistical oﬃces or by private agencies under the supervision of government or international agencies and obtained from government statistical oﬃces and World Bank country departments. The World Bank has prepared an annual review of its poverty work since 1993. For details on data sources and methods used in deriving the World Bank’s latest estimates, see Chen and Ravallion (2004). Data have been compiled by World Bank staﬀ from primary and secondary sources. Eﬀorts have been made to harmonize these 116

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data series with those published on the United Nations Millennium Development Goals website (www.un.org/millenniumgoals), but some diﬀerences in timing, sources, and deﬁnitions remain. Data on child malnutrition and share of population below minimum dietary energy consumption are from the Food and Agriculture Organization (see www.fao.org/faostat/ foodsecurity/index_en.htm). T .. M D G :     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 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. Data have been compiled by World Bank staﬀ from primary and secondary sources. Eﬀorts have been made to harmonize these data series with those published on the United Nations Millennium Development Goals website (www. un.org/millenniumgoals), but some diﬀerences in timing, sources, and deﬁnitions remain.

T .. M D G :       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. Ratio of young literate women to men is the ratio of the female to male youth literacy rate. Women in national parliaments are the percentage of parliamentary seats in a single or lower chamber occupied by women. Share of women in wage employment in the nonagricultural sector are 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 the InterParliamentary Union. Data on women’s employment are from the International Labour Organization’s Key Indicators of the Labour Market, fourth edition. T .. M D G :    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 one year of age, per 1,000 live births. Child immunization rate, measles, is the percentage of children ages 12–23 months who 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 the harmonized estimates of the World Health Organization, United Nations Children’s Fund (UNICEF), and the World Bank, based mainly on household surveys, censuses, and vital registration, supplemented by the World Bank’s estimates based on household surveys and vital registration. Other estimates are compiled and produced

by the World Bank’s Human Development Network and Development Data Group in consultation with its operational staﬀ and country oﬃces. Data on child immunization are from the World Health Organization and UNICEF estimates of national immunization coverage. T .. M D G :    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. 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. Source: Data on maternal mortality are from AbouZahr and Wardlaw (2003). Data on births attended by skilled health staﬀ are from the United Nations Children’s Fund’s State of the World’s Children 2006 and Childinfo, and Demographic and Health Surveys by Macro International. T .. M D G :  HIV/AIDS, ,    Prevalence of HIV is the percentage of people ages 15–49 who are infected with HIV. Contraceptive prevalence rate is the percentage of women who are practicing, or whose sexual partners are practicing, any form of contraception. It is usually measured for married women ages 15–49 only. Deaths due to malaria is the number of malaria deaths per 100,000 people. Children sleeping under insecticide-treated bednets are the percentage of children under age 5 who slept under an insecticide-treated bednet to prevent malaria. Incidence of tuberculosis is the estimated number of new tuberculosis cases (pulmonary, smear positive, and extrapulmonary), per 100,000 people. Tuberculosis cases detected under DOTS is the percentage of estimated new infectious tuberculosis cases detected under DOTS, the internationally recommended tuberculosis control strategy. Technical notes

117

Source: Data on HIV prevalence are from the Joint United Nations Programme on HIV/AIDS and the World Health Organization’s (WHO) 2006 Report on the Global AIDS Epidemic. Data on contraceptive prevalence 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 deaths due to malaria are from the WHO. Data on children sleeping under insecticide-treated bednets are from UNICEF’s State of the World’s Children 2006 and Childinfo, and Demographic and Health Surveys by Macro International. Data on tuberculosis are from the WHO’s Global Tuberculosis Control Report 2006. T .. M D G :    Forest area is land under natural or planted stands of trees, whether productive or not. Nationally protected areas as share of total land area are totally or partially protected areas of at least 1,000 hectares that are designated as scientiﬁc reserves with limited public access, national parks, natural monuments, nature reserves or wildlife sanctuaries, and protected landscapes. Marine areas, unclassiﬁed areas, and litoral (intertidal) areas are not included. The data also do not include sites protected under local or provincial law. 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 purchasing power parity rates. An international dollar has the same purchasing power over GDP as a U.S. dollar has in the United States. 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. Solid fuel use is the percentage of the population using solid fuels as opposed to modern fuels. Solid fuels are deﬁned to include fuel wood, straw, dung, coal, and charcoal. Modern fuels are deﬁned to include electricity, liqueﬁed petroleum gas, natural gas, kerosene, and gasoline. 118

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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’s Global Forest Resources Assessment. Data on nationally protected areas are from the United Nations Environment Programme and the World Conservation Monitoring Centre. 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, in the U.S. state of Tennessee. Data on solid fuel use are from household survey data, supplemented by World Bank estimates. Data on access to water and sanitation are from the World Health Organization and United Nations Children’s Fund’s Meeting the MDG Drinking Water and Sanitation Target (www.unicef.org/wes/ mdgreport). T .. M D G :       Heavily Indebted Poor Country (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 (IMF) and the World Bank commits to undertake additional reforms and to develop and implement a poverty reduction strategy. HIPC 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. Estimated total nominal debt service relief committed under Enhanced HIPC Initiative 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. Debt service is the sum of principal repayments and interest actually paid on total long-term debt (public and publicly guaranteed and private nonguaranteed), use of IMF credit, and interest on short-term debt. 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 phone 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. Personal computers are self-contained computers designed for use by a single individual. Internet users are people with access to the worldwide network. Source: Data on HIPC countries are from the IMF’s March 2006 “HIPC Status Reports.” 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. Data on youth unemployment are from the International Labour Organization’s Key Indicators of the Labour Market, fourth edition. Data on phone subscribers, personal computers, and Internet users are from the International Telecommunication Union’s (ITU) World

Telecommunication Development Report database and World Bank estimates. 4. Paris Declaration indicators T .. S  P D  Source: World Bank data (see box 3). 5. Private sector development T .. B  Number of startup procedures for new 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 to start a business is the number of calendar days needed to complete the procedures 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. Number of procedures to register a property is the number of procedures required for a business to secure rights to property. Time required to register a property is the number of calendar days needed for a business to secure rights to property. 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. Protecting investors disclosure index measures the degree to which investors are protected through disclosure of ownership and ﬁnancial information. Time to resolve insolvency is the number of years from the ﬁling for insolvency in court until the resolution of distressed assets. Rigidity of employment index measures the regulation of employment, speciﬁcally the hiring and ﬁring of workers and the rigidity of working hours. This index is the average Technical notes

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Box 3

About the Paris Declaration

In the Paris Declaration, partner countries and donors agreed on an international monitoring process to track and encourage progress in implementing the Paris Declaration at the country level. As much as possible, surveys will use local processes to build a common understanding of how more effective aid contributes to achieving development results, to provide an accurate picture of how aid is managed, and to support broad-based dialogue at the country level on how to make aid more effective. The multidonor Working Party on Aid Effectiveness has created a subgroup to develop technical guidance, survey instruments, and a methodology for collecting and reporting on country-level data for most of the Paris Declaration indicators.

and a questionnaire for governments and donors (remaining eight indicators; see table). The assessment criteria for indicators 1 and 11 are based on analysis by the World Bank for the 2005 Comprehensive Development Framework Progress Report “Enabling Country Capacity to Achieve Results.” The World Bank is now conducting an Aid Effectiveness Review that will build on this earlier work and will provide information on these two qualitative indicators. The survey-based tool was launched in May 2006. As of June 2006, 26 countries had confirmed their participation in the 2006 Survey of Monitoring the Paris Declaration. An international report on this first round is targeted for publication at the end of 2006. Other

Status of Paris Declaration indicators Number

Indicator

Source of assessment

1

Ownership; operational poverty reduction strategies

Qualitative review, Comprehensive Development Framework method: desk review (World Bank)

2a

Quality of public financial management system

World Bank Country Policy and Institutional Assessment desk review

2b

Quality procurement system

Organisation for Economic Co-operation and Development’s Development Assistance Committee desk review

3

Aid reported on budget

Questionaire

4

Coordinated capacity building

Questionaire

5a

Use of country public financial managment systems

Questionaire

5b

Use of country procurement systems

Questionaire

6

Parallel project implementation units

Questionaire

7

In year predicitability

Questionaire

8

Untied aid

Questionaire

9

Use of program-based approaches

Questionaire

10

Joint missions and country analytical work

Questionaire

11

Sound performance assessment framework

Qualitative review, Comprehensive Development Framwork method: desk review (World Bank)

12

Review of mutual accountability

Questionaire

Twelve indicators were agreed on at Paris. They are measured through qualitative desk reviews undertaken by the Organisation for Economic Co-operation and Development’s Development Assistance Committee (indicator 2b), the World Bank (indicators 1, 2a, and 11),

of three subindexes: a diﬃculty of hiring index, a rigidity of hours index, and a difﬁculty of ﬁring index. 120

Africa Development Indicators 2006

monitoring rounds will be undertaken in early 2008 and 2010. To reduce the level of detail and complexity, the definitions and guidance are principle based and objective oriented. Detailed guidance on each of the eight indicators is provided.

Source: Data are from the World Bank’s Doing Business project (http://rru.worldbank.org/DoingBusiness/).

T .. I  Private investment is private sector ﬁxed capital formation (table 2.11) divided by nominal gross domestic product (table 2.6). Net foreign direct investment is investment by residents of the Organisation for Economic Co-operation and Development’s (OECD) Development Assistance Committee (DAC) member countries to acquire a lasting management interest (at least 10 percent of voting stock) in an enterprise operating in the recipient country. The data reﬂect changes in the net worth of subsidiaries in recipient countries whose parent company is in the DAC source country. 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. Policy uncertainty is the share of senior managers who ranked economic and regulatory policy uncertainty as a major or very severe constraint. Corruption is the share of senior managers who ranked corruption as a major or very severe constraint. Courts are the share of senior managers who ranked courts and dispute resolution systems as a major or very severe constraint. Lack of conﬁdence courts will uphold property rights is the share of senior managers who do not agree with the statement: “I am conﬁdent that the judicial system will enforce my contractual and property rights in business disputes.” Crime is the share of senior managers who ranked crime, theft, and disorder as a major or very severe constraint. Tax rates are the share of senior managers who ranked tax rates as a major or very severe constraint. Finance is the share of senior managers who ranked access to ﬁnance or cost of ﬁnance as a major or very severe constraint. Electricity is the share of senior managers who ranked electricity as a major or severe constraint. Labor regulation is the share of senior managers who ranked labor regulations as a major or severe constraint. Labor skills are the share of senior manag-

ers who ranked skills of available workers as a major or severe constraint. 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 to prepare 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 payable 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. For further details on the method used for assessing the total tax payable. 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 is the number of days to clear an imported good through customs. Bank branches are deposit money bank branches. 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. 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 Technical notes

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Box 4

Investment climate survey data and perception of constraints by firms

Investment climate surveys or Enterprise surveys have been undertaken by the World Bank on an Africawide basis since 2003. Enterprise surveys measure business perceptions of the investment climate and can be used to analyze the link to job creation and productivity growth. Surveys are undertaken on the basis of a standardized survey instrument, identical for each country. The data gathered during these surveys fall into two categories: objective data, such as accounting or labor data, and perception data, where interviewees are asked to provide their own assessment of specific issues. Inferences from the use of survey data and of perception information must be done carefully, as sampling and contextual issues may affect the numbers reported. Sector coverage in samples. Until 2005 enterprise surveys mostly surveyed manufacturing firms across countries, which implies that the reported data will not cover the entire economy. Hence, some of the reported issues may be sector specific.

Inference. The data reported are unweighted numbers from random stratified samples, which implies that population estimates of the same variable may differ somewhat. Although experience shows that it does not often change the ranking of the most important constraints, reported numbers may vary slightly from population estimates (see figure for a hypothetical example). Context for perception data. The social environment in which a survey takes place may affect the nature of the replies. The sense of responsibility of managers and the perceived legitimacy of the survey itself (and of its questions) will affect the replies: for example, a survey taking place in a country with no tradition in survey data gathering—and thus with little perceived legitimacy for a survey—will yield more uncertain answers. Some topics, by their sensitive nature—for example, questions on corruption—may yield unexpected results. In addition, the psychology of the respondent and the overall socioeconomic context of the interview may affect the answers. For example, assume a country Items perceived as a severe constraint (percent) where a survey takes place between period t–1 and t+1. In period t, a major dispute erupts between manufacturers and the authorities about 70 tax issues. It is most likely that replies provided in t+1 will be much more negative when as60 sessing tax issues than the ones provided in 50 t–1. In this case, samplewide computations may be misleading, and it is better for analyti40 cal purposes to separate the answers into before and after the event. 30 These issues have two major implications. First, it is often better to also refer to the In20 vestment Climate Assessment reports for each 10 country to know the sampling methodology used in order to assess how generalizations can 0 be made from the data. Second, these replies, Access Tax Courts Corruption Policy Electricity Labor Labor Crime to rates undertainty skills regulation because of their contextual nature, should be Finance correlated with other sources of information, Sample numbers Weighted population estimates which can be found in Investment Climate AsSource: World Bank Investment Climate Surveys. sessment reports or other analytical works.

is calculated as the average of the end-of-period values for the current period and the previous period. Source: Data on private investment are from the World Bank’s World Development Indicators database. Data on net foreign direct investment are from the World Bank’s World Development Indicators database. Data on domestic credit to the private sector are from the International Monetary Fund’s International Financial Statistics database and data ﬁles, World Bank and OECD gross domestic product (GDP) estimates, and the 122

Africa Development Indicators 2006

World Bank’s World Development Indicators database. Data on investment climate constraints to ﬁrms are based on enterprise surveys conducted by the World Bank and its partners during 2001–05 (http://rru. worldbank.org/EnterpriseSurveys) (box 4). Data on regulation and tax administration and highest marginal corporate tax rates are from the World Bank’s Doing Business project (http://rru.worldbank.org/DoingBusiness). Data on time dealing with oﬃcials and average time to clear customs are from World Bank Enterprise Surveys (http:// rru.worldbank.org/EnterpriseSurveys/).

Data on bank branches are from surveys of banking and regulatory institutions by the World Bank’s Research Department and Financial Sector and Operations Policy Department and the World Development Indicators database. Data on interest rate spreads are from the IMF’s International Financial Statistics database and data ﬁles and the World Bank’s 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 Stock Markets Factbook and supplemental data, World Bank and OECD estimates of GDP, and the World Bank’s World Development Indicators database. 6. Trade T .. I     Merchandise trade is the sum of imports and exports of divided by nominal gross domestic product. Exports and imports comprise all transactions between residents of an economy and the rest of the world involving a change in ownership of general merchandise, goods sent for processing and repairs, and nonmonetary gold. Data are shown in current U.S. dollars. Exports and imports as a share of gross domestic product (GDP) are calculated as merchandise exports and imports divided by nominal GDP. Annual growth of exports and imports is calculated using the real imports and exports series in tables 2.17 and 2.18. 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 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). Fuels comprise 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 diversiﬁcation index measures the extent to which exports are diversiﬁed. It is constructed as the inverse of a Herﬁndahl index, using disaggregated exports at four digits (following the SITC). A higher index indicates more export diversiﬁcation. 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. 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 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 0ñ4 plus division 68. Manufactured products are commodities classiﬁed in SITC revision 2 sections 5ñ8 excluding division 68. Tariﬀ barriers are a form of duty based on the value of the import. Average cost to ship 20 ft container from port Technical notes

123

to ﬁnal destination is the cost of all operations associated with bringing a container from onboard a ship to the considered economic center, weighted based on container traﬃc for each corridor. Average time to ship 20 ft container from port to ﬁnal destination is the time in days from when the ship is available for unloading (be it moored at the berth or oﬀshore) until the content of the container is made available to the ﬁnal customer at the destination in the considered economic center, weighted based on container traﬃc for each corridor. Average time to clear customs is the number of days to clear an imported good through customs. Source: All indicators in the table were calculated by World Bank staﬀ using the World Integrated Trade Solution system. Data on the export diversiﬁcation index are from the Organisation for Economic Co-operation and Development. Data on tariﬀs are from the United Nations Conference on Trade and Development and the World Trade Organization. Data on global imports are from the United Nations Statistics Division’s COMTRADE database. Data on merchandise exports and imports are from World Bank country desks. Data on shipping time and costs are from the World Bank’s Sub-Saharan Africa Transport Policy Program (SSATP). Data on average time to clear customs are from World Bank Enterprise Surveys (http://rru.worldbank. org/EnterpriseSurveys/). T . R ,   Value of trade is the sum of merchandise exports by members of a trade bloc . Share of total bloc exports is the sum of merchandise exports by members of a trade bloc as a percentage of total merchandise exports by the bloc. Share of world exports is the ratio of the bloc’s total merchandise exports (within the bloc and to the rest of the world) to total merchandise exports by all economies in the world. Source: Data on merchandise trade ﬂows are published in the International Monetary Fund’s (IMF) Direction of Trade Statistics Yearbook and Direction of Trade Statistics Quarterly. The data in the table were calculated 124

Africa Development Indicators 2006

using the IMF’s Direction of Trade database. The United Nations Conference on Trade and Development publishes data on intraregional trade in its Handbook of International Trade and Development Statistics. The information on trade bloc membership is from World Bank (2000), the World Bank’s Global Economic Prospects 2005, and the World Bank’s International Trade Unit. 7. Infrastructure T .. W   Internal fresh water resources per capita is 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 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 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 nonrevenue water is the diﬀerence between water supplied and water sold (that is, the volume of water “lost”) expressed as a percentage of net water supplied. Water supply failure for ﬁrms receiving water is the average number of days per year that ﬁrms experienced insuﬃcient water supply for production. Average household tariﬀs for water services, largest city are the average tariﬀs for wastewa-

ter services for household consumers in the largest city. Committed nominal investment in potable water projects with private participation is annual committed investment in potable water projects with private investment. Average annual oﬃcial development assistance (ODA) disbursements for water and sanitation are average annual ODA for water and sanitation, including bilateral, multilateral, and other donors. Source: Data on fresh water resources are from the World Bank’s World Development Indicators database. Data on access to water and sanitation are from the World Health Organization and United Nations Children’s Fund’s Meeting the MDG Drinking Water and Sanitation Target (www.unicef.org/wes/ mdgreport). Data on average nonrevenue water and average household tariﬀs for water services in the largest city are from the International Benchmarking Network for Water and Sanitation Utilities (IBNET). Data on water supply failure are from World Bank Investment Climate Surveys. Data on committed nominal investment in potable water projects with private participation are from the World Bank’s Private Participation in Infrastructure database. Data on ODA disbursements are from the Organisation for Economic Co-operation and Development. T .. T Total length of road network is the length of motorways, highways, main or national roads, secondary or regional roads, and other roads. Total length of national road network is the length of the interurban classiﬁed network without the urban and rural network. Rail lines are the length of railway route available for train service, irrespective of the number of parallel tracks. Road density, ratio to arable land is the total length of national road network per 1,000 square kilometers of arable land area. The use of arable land area in the denominator focuses on inhabited sectors of total land area by excluding wilderness areas. Road density, ratio to total land is the total length of national road network per 1,000 square kilometers of total land area. Energy consumption for transportation is the

transportation sector’s contribution to total ﬁnal energy consumption. Rural access is the percentage of the rural population who live within 2 kilometers of an all-season passable road as a share of the total rural population. Commercial vehicles are the number of commercial vehicles, which use at least 24 liters of diesel fuel per 100 kilometers. Passenger cars are the number of passenger vehicles, which use at least 9 liters of gasoline fuel per 100 kilometers. Length of national network in good condition is the length of the national road network, including the interurban classiﬁed network without the urban and rural network, that is in good condition, as deﬁned by each country’s road agency. Ratio of paved to total roads is the length of paved roadsówhich are those surfaced with crushed stone (macadam) and hydrocarbon binder or bituminized agents, with concrete, or with cobblestonesóas a percentage of all the country’s roads. Average time to ship 20 ft container from port to ﬁnal destination is the time in days from when the ship is available for unloading (be it moored at the berth or oﬀshore) until the content of the container is made available to the ﬁnal customer at the destination in the considered economic center, weighted based on container traﬃc for each corridor. Firms identifying transport as major or very severe obstacle to business operation and growth is the percentage of ﬁrms that responded “major” or “very severe” obstacle 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 cost to ship 20 ft container from port to ﬁnal destination is the costs of all operations associated with bringing a container from onboard a ship to the considered economic center, weighted based on container traﬃc for each corridor. Price of diesel fuel and super gasoline is the price as posted at ﬁlling stations in a country’s capital city. When several fuel prices for major cities were available, the unweighted Technical notes

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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 (including roads, airport, seaport, toll road, and railroad) projects with private investment. Average annual oﬃcial development assistance (ODA) disbursements for transportation and storage are average annual ODA for transportation and storage, including bilateral, multilateral, and other donors. Existence of road fund includes ﬁrst generation (funded primarily by earmarked taxes) and second generation (funded primarily by user charges) road funds. Source: Data on total length of road network are from the International Road Federation’s World Road Statistics. Data on total length of national network, length of national network in good condition, average time and cost to ship 20 ft container, and existence of a road fund are from the World Bank’s Sub-Saharan Africa Transport Policy Program (SSATP). Data on rail lines and ratio of paved to total roads are from the World Bank’s World Development Indicators database. Data on road density and rural access to roads are from the World Bank’s SSATP and World Development Indicators database. Data on energy consumption for transportation are from the International Energy Agency. Data on vehicle ﬂeet and fuel and gasoline prices are from the German Society for Technical Cooperation (GTZ). Data on ﬁrms identifying transport as a major or very severe constraint to business operation and growth are from World Bank Investment Climate Surveys. Data on committed nominal investment in transport projects with private participation are from the World Bank’s Private Participation in Infrastructure database. Data on ODA disbursements are from the Organisation for Economic Co-operation and Development. T .. I    Telephone subscribers are subscribers to a main telephone line service, which connects a customer’s equipment to the public switched 126

Africa Development Indicators 2006

telephone network, or to a cellular telephone service, which uses cellular technology. Unmet demand is unmet applications for connection to the public switched telephone network that have had to be held over owing to a lack of technical facilities (equipment, lines, and the like) divided by the number of main telephone lines in operation. Households with own telephone is the percentage of households possessing a telephone. Delay for ﬁrm in obtaining a telephone 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. Duration of telephone outages is the average duration in hours of instances of telephone unavailability related to production. Reported phone faults is 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. Firms identifying telecommunications as major or very severe obstacle to business operation and growth is the percentage of ﬁrms that responded “major” or “very severe” obstacle 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.” Cost of a cellular local call is the cost of a three-minute cellular local call during oﬀpeak hours. Cost of a local phone call 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 phone call to the United States is the cost of a three-minute call to the United States during peak hours.

Committed nominal investment in ﬁxed-line and long distance projects with private participation is annual committed investment in ﬁxed-line and long distance projects with private investment. Committed nominal investment in mobile projects with private participation is annual committed investment in mobile projects with private investment. Average annual oﬃcial development assistance (ODA) disbursements for communications are average annual ODA for communications, including bilateral, multilateral, and other donors. Source: Data on telephone subscribers, reported phone faults, and cost of local and cellular calls are from the International Telecommunications Union. Data on unmet demand are from the World Bank’s Infrastructure Vice Presidency. Data on households with own telephone are from Demographic and Health Surveys. Data on delays for ﬁrms in obtaining a telephone connection, duration of telephone outages, and ﬁrms identifying telecommunications as a major or very severe obstacle to business operation and growth are from World Bank Investment Climate Assessments. Data on cost of a call to the United States are from the World Bank’s Global Development Finance and World Development Indicator databases. Data on committed nominal investment are from the World Bank’s Private Participation in Infrastructure database. Data on ODA disbursements are from the Organisation for Economic Co-operation and Development. T .. E Installed capacity is the sum of conventional thermal electricity installed capacity; hydroelectricity installed capacity; nuclear electricity installed capacity; and geothermal, solar, wind, wood, and waste electricity installed capacity. 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. Energy use per purchasing power parity (PPP) gross domestic product (GDP) is 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,

divided by nominal GDP in PPP U.S. dollars. Access to electricity is the percentage of the population living in households with access to electricity. Solid fuels use is the percentage of the population using solid fuels as opposed to modern fuels. Solid fuels include fuel wood, straw, dung, coal, and charcoal. Modern fuels include electricity, liqueﬁed petroleum gas, natural gas, kerosene, and gasoline. 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 outages of ﬁrms are the average number of days per year that establishments experienced power outages or surges from the public grid. Firms that share or own their own generator is the percentage of ﬁrms that responded “Yes”to the following question: “Does your establishment own or share a generator?” Firms identifying electricity as major or very severe obstacle to business operation and growth is the percentage of ﬁrms that responded “major” or “very severe” obstacle 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.” Electricity end-user prices are prices actually paid, net of rebates and including transport costs to the consumer and taxes that have to be paid as part of the transaction and that are not refundable (this excludes value added tax). Committed nominal investment in energy projects with private participation is annual committed investment in energy projects with private investment. Average annual oﬃcial development assistance (ODA) disbursements for energy are averTechnical notes

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age annual overseas ODA for energy, including bilateral, multilateral, and other donors). Source: Data on installed capacity are from the U.S. Department of Energy’s International Energy Annual 2004. Data on electric power consumption and energy use per PPP GDP are from the World Bank’s World Development Indicators database. Data on access to electricity and solid fuels use are from household survey data, supplemented by World Bank Project Appraisal Documents. Data on delays for ﬁrms in obtaining an electrical connection, electrical outages of ﬁrms, ﬁrms that share or own their own generator, and ﬁrms identifying electricity as a major or very severe obstacle to business operation and growth are from World Bank Investment Climate Assessments. Data on transmission and distribution losses are from the World Bank’s World Development Indicators database, supplemented by World Bank Project Appraisal Documents. Data on end-user prices are from South African Development through Electricity (SAD-ELEC). Data on committed nominal investment are from the World Bank’s Private Participation in Infrastructure database. Data on ODA disbursements are from the Organisation for Economic Cooperation and Development. T .. F   Sovereign ratings are long-term foreign currency ratings. Gross national savings are the sum of gross domestic savings (table 2.12) and net factor income and net private transfers from abroad. The estimate here also includes net public transfers from abroad. Claims on governments and other public entities correspond to the sum of lines 32an, 32b, 32bx, and 32c in the International Monetary Fund’s (IMF) International Financial Statistics and usually comprise direct credit for speciﬁc purposes such as ﬁnancing of the government budget deﬁcit or loans to state enterprises, advances against future credit authorizations, and purchases of treasury bills and bonds, net of deposits by the public sector. Public sector deposits with the banking system also include sinking funds for the service of debt and temporary 128

Africa Development Indicators 2006

deposits of government revenues. Data are in current local currency. 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 IMF’s International Financial Statistics. Real interest rate is the lending interest rate adjusted for inﬂation as measured by the gross domestic product (GDP) deﬂator. Bank assets include deposit money bank reserves (line 20 of the IMF’s International Financial Statistics), claims on monetary authorities, securities (line 20c), other claims on monetary authorities (line 20n), foreign assets (line 21), and claims on other resident sectors (lines 22). Calculated using period average exchange rate (line rf). 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 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 that is overdue. Bank branches are deposit money bank branches. 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.

Box 5

Infrastructure indicators

The availability of performance indicators for the infrastructure sector is unfortunately rather sparse. One reason for the difficulties with data collection is the institutional fragmentation of the sectors, with information dispersed across a wide range of institutions including ministries, (often subnational) state-owned enterprises, roads funds, and regulatory entities. Efforts have been made across all sectors to organize the limited data available according to a common conceptual framework that shed lights on some of the key policy issues affecting the sector, namely access, quality of service, pricing, and financing. The access indicators are further broken down between the supply side, which reflects the situation from the service provider’s perspective, and the demand side, which reflects the situation from the user’s perspective. The disconnect that sometimes exists between these two sets of indicators itself reveals some of the challenges inherent in providing effective infrastructure services. Water and sanitation There has been a great deal of international effort to improve measurement of access to water and sanitation, since increasing access is one of the Millennium Development Goals. The latest figures suggest that an average of 64 percent of the population has access to an improved water source and 37 percent to improved sanitation. Less than half of those with access to an improved water source enjoy a piped connection to the household. Transportation Road density for the region remains low by international standards. Due to the existence of relatively large sparsely populated areas in many countries, road density is less dramatic when measured relative to total arable land rather than total land area. Nevertheless, only about 33 percent of the rural population lives within 2 kilometers of an all-season road. Road quality is also a major concern, with only around 30 percent of the national network classified as being in reasonable condition. One area where significant progress has been made is the creation of road funds, which aim to provide a stable source of finance for road maintenance. More than 80 percent of countries for which data are available report having such a fund. Information and communication technology The information and communication technology sector is by far the best documented. The data testify to the huge expansion of cellular telephone coverage across Africa during the last decade, with the average number of mobile subscribers at the country level rising from 13 per 1,000 people in the late 1990s to 73 in the early 2000s. Nevertheless, unmet demand for fixed telephone lines remains high at 46 percent of existing capacity, and firms report average wait times of 69 days for a new connection. The cost of international telephone calls has declined significantly since the late 1990s but remains very high in absolute terms, with an average rate of $4.85 for a three minute call to the United States. Energy Access and use of modern energy remains extremely limited in the region. In countries for which data are available around 27 percent of the population has access to electricity and 13 percent

to modern cooking fuels. Investment Climate Surveys indicate that unreliable power supply is a major constraint for firms in the region, with around 40 percent of enterprises identifying deficient power supply as a major constraint to doing business and as many as 50 percent maintaining their own generation facilities to insulate themselves from unreliable public supplies. Notwithstanding the major shortfalls in access, official development assistance flows to the sector are very low, at no more than a few million dollars per country per year. Financial sector infrastructure Macroeconomics. Low domestic savings and limited access to foreign savings through international borrowing constrain the supply of funding for viable investments. Domestic savings to gross domestic product (GDP) amounts to a low 15.5 percent on average for all of Africa and 15.2 percent for Sub-Saharan Africa. Low savings coupled with inefficient intermediation capacity of the financial sector result in high cost of finance. Interest rates average above 10 percent for the region, in some countries interest rates reach 20 percent and higher. Size. Although figures vary drastically between countries, on average the size of the financial sector remains small. For a bankdominated financial system, the economies exhibit a very low penetration of bank assets at 39 percent of GDP. The data also show the stark contrast between the average amount of bank assets in Sub-Saharan Africa and North Africa. While Sub-Saharan Africa bank assets stand at 35 percent of GDP, with assets standing as low as 7 percent in some countries, North Africa registers a deep banking system with assets averaging 77 percent of GDP. Intermediation. With very few exceptions, financial systems in the region fulfill their intermediation function poorly. Cross-country, industry-level, firm-level, and country case studies confirm that countries with higher levels of financial development experience better resource allocation, higher GDP per capita growth, and faster rates of poverty reduction. Financial intermediation contributes to economic growth through mobilizing savings and identifying, assessing, and monitoring productive investments in an economy. However, capacity for intermediation in many African countries is strained by inefficiency, high costs, and lack of outreach. Typically, banks have very high liquidity but fail to deploy funds into productive investments, and lending to the private sector is constrained. Domestic credit to the private sector averages less than 20 percent of GDP in Africa. Lack of competition and high overhead costs contribute to high interest rate spreads, which average 18 percent. Access to finance and outreach of the banking system are limited with many countries having less then 3 bank branches per 100,000 people. Financial systems are dominated by banks and lack product and institutional diversity. The share of nonbank financial institutions in the financial system, including pension funds and insurance companies, which have an important role in promoting long-term savings, remains negligible. At the same time, ongoing reforms in the pension and insurance sector in several African countries set the basis for in-

Technical notes

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Box 5

Infrastructure indicators

creased long-term savings which, subject to efficient intermediation, can be channeled to long-term investments in the future. Capital markets. Capital markets act as a natural source of long-term finance in developed financial systems. Although capital markets are growing in Africa, most markets still play a limited role in funding investments. Security markets are small, underdeveloped, and illiquid both by global and emerging market standards, although 12 countries have set up stock exchanges in Sub-

Saharan Africa in addition to one regional exchange, the Bourse des Valeurs d’Abidjan. The markets suffer from poor liquidity and limited secondary market activity. Only 4 exchanges listed more than 50 domestic companies in 2004, and turnover averaged less than 10 percent of their market capitalization. While limited trading discourages further listings on the exchanges, additional listings can also contribute to improved scale and liquidity.

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-of-period values for the current period and the previous period. Source: Data on sovereign ratings are from Fitch Ratings. Data on gross national savings are from World Bank country desks. Data on claims on governments and other public entities are from the IMF’s International Financial Statistics database and data ﬁles and the World Bank’s World Development Indicators database. Data on money and quasi money and domestic credit to the private sector are from the IMF’s International Financial Statistics database and data ﬁles, World Bank and OECD estimates of GDP, and the World Bank’s World Development Indicators database. Data on real interest rates are from the IMF’s International Financial Statistics database and data ﬁles using World Bank data on the GDP deﬂator and the World Bank’s World Development Indicators database. Data on bank assets are from the IMF’s International Financial Statistics database. Data on interest rate spreads are from the IMF’s International Financial Statistics database and data ﬁles and the World Bank’s World Development Indicators database. Data on ratios of bank nonperforming loans to total are from the IMF’s Global Financial Stability Report and the World Bank’s World Development Indicators database. Data on bank branches are from surveys of banking and regulatory institutions by the World Bank’s Research Department and Financial Sector and Operations Policy Department and the World Development Indicators database. Data on listed domestic companies and turnover ratios 130

Africa Development Indicators 2006

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 Stock Markets Factbook and supplemental data, World Bank and OECD estimates of GDP, and the World Bank’s World Development Indicators database. 8. Human development T .. E 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 to 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. Source: United Nations Educational, Scientiﬁc, and Cultural Organization Institute for Statistics. T .. H 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 one year of age, per 1,000 live births. Maternal mortality ratio is the number of women who die from pregnancy-related causes during pregnancy and childbirth, per 100,000 live births. Deaths due to HIV/AIDS are the estimated number of adults and children that have died in a speciﬁc year based in the modeling of HIV surveillance data using standard and appropriate tools. Prevalence of HIV is the percentage of people ages 15–49 who are infected with HIV. Prevalence 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.

Deaths due to malaria is the number of malaria deaths per 100,000 people. 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 diseasesómeasles and diphtheria, pertussis (whooping cough), and tetanus (DPT). A child is considered adequately immunized against measles after receiving one dose of vaccine and against DPT after receiving three doses. 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 prevalence rate is the percentage of women who are practicing, or whose sexual partners are practicing, any form of contraception. It is usually measured for married women ages 15–49 only. Children sleeping under insecticide-treated bednets are the percentage of children under age 5 who slept under an insecticide-treated bednet to prevent malaria. People with advanced HIV infection receiving antiretroviral combination therapy are the percentage of people with advanced HIV infection receiving antiretroviral therapy according to nationally approved treatment protocol (or World Health Organization/ Joint United Nations Programme on HIV/ AIDS standards). Tuberculosis cases detected under DOTS are the percentage of estimated new infectious tuberculosis cases detected under DOTS, the internationally recommended tuberculosis control strategy. DOTS 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 antimalarial drugs are the percentage of children under age 5 in malaria-risk areas with fever being treated with eﬀective 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, Technical notes

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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. Physicians are the number of physicians, including generalists and specialists. Nurses are the number of nurses, including professional nurses, auxiliary nurses, enrolled nurses, and other nurses, such as dental nurses and primary care nurses. Midwives are the number of midwives, including professional midwives, auxiliary midwives, and enrolled midwives. Traditional birth attendants, who are counted as community health workers, are not included. General government expenditure on health is the direct outlays earmarked for the enhancement of the health status of the population and for the distribution of medical goods and services among the population. They can be ﬁnanced through domestic funds or through external resources. 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. Total government expenditure includes consolidated direct outlays and indirect outlays, including capital of all levels of government, social security institutions, autonomous bodies, and other extrabudgetary funds Source: Data are from the latest Core Health 132

Africa Development Indicators 2006

Indicators from World Health Organization sources, including World Health Statistics 2006 and World Health Report 2006 (http:// www3.who.int/whosis/core/core_select.cfm ?path=whosis,core&language=english). 9. Agriculture T .. R  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. Rural population below the poverty line is the percentage of the rural population living below the national poverty line. 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 is the percentage of the rural 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. Share of rural population with access to electricity is the percentage of the rural population living in households with access to electricity. Share of rural population with access to transportation is the percentage of the rural

population who live within 2 kilometers of an all-season passable road as a share of the total rural population. Share of rural households with own telephone is the percentage of rural households possessing a telephone. 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 are national estimates based on populationweighted subgroup estimates from household surveys. Data on rural population with access to water and rural population with access to sanitation are from World Health Organization and United Nations Children’s Fund’s Meeting the MDG Water and Sanitation Target (www.unicef.org/wes/mdgreport). Data on rural population with access to electricity are from household survey data, supplemented by World Bank Project Appraisal Documents. Data on rural population with access to transport are from the World Bank’s Sub-Saharan Africa Transport Policy Program (SSATP). Data on rural households with own telephone are from Demographic and Health Surveys. T .. A Agriculture value added is shown at factor cost in current U.S. dollars divided by nominal gross domestic product. Value added in agriculture comprises the gross output of forestry, hunting, and ﬁshing less the value of their intermediate inputs. However, for Botswana, Cameroon, Chad, Democratic Republic of Congo, Republic of Congo, Gabon, Guinea, Madagascar, Mali, Morocco, Niger, Rwanda, Senegal, Togo, and Zambia, it is shown at market prices, that is, including intermediate inputs. Crop production index shows agricultural production for each year relative to the base period 1999–2001. It includes all crops except fodder crops. Regional and income group aggregates for the Food and Agriculture Organization’s (FAO) production indexes are calculated from the underlying values in international dollars, normalized to the base period 1999–2001.

Food 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. Nonfood production index includes 29 products that are not considered nutritious, including coﬀee, rubber, cotton lint, and tobacco leaves. Cereal production is crops harvested for dry grain only. Cereals include wheat, rice, maize, barley, oats, rye, millet, sorghum, buckwheat, and mixed grains. Cereal crops harvested for hay or harvested green for food, feed, or silage and those used for grazing are excluded. Livestock production index includes meat and milk from all sources, dairy products such as cheese, and eggs, honey, raw silk, wool, and hides and skins. Food production index per capita is the ratio of food production index to the estimated total midyear population ﬁgures. Agricultural exports and imports are expressed in current U.S. dollars at free on board prices. Permanent cropland is land under permanent crops as deﬁned and reported by the FAO. Land under cereal production refers to harvested area, although some countries report only sown or cultivated area. 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 is the aggregate of nitrogenous, phosphate, and potash fertilizers. 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 (ISIC revision 2) or tabulation categories A Technical notes

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and B (ISIC revision 3) and includes hunting, forestry, and ﬁshing. Incidence of drought shows whether a country experienced a signiﬁcant shortage of rain that unfavorably aﬀected agricultural production. Agricultural productivity measures agriculture value added per worker. Value added in agriculture measures the output of the agricultural sector (ISIC divisions 1ñ5) 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 crop yield is 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.. Source: Data on agriculture value added are from World Bank country desks. Data on crop, food, nonfood, cereal, and livestock production, agricultural exports and imports, permanent cropland, land under cereal production, and agricultural machinery are from the FAO. Data on irrigated land are from the FAO’s Production Yearbook and data ﬁles. Data on fertilizer consumption are from the FAO database for the Fertilizer Yearbook. Data on agricultural employment are from the International Labour Organization. Data on incidence of drought are from the Southern Africa Flood and Drought Network and East Africa Drought (CE). Data on agricultural productivity are from World Bank national accounts ﬁles and the FAO’s Production Yearbook and data ﬁles. 10. Labor, migration, and population T .. L 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 134

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and other unpaid caregivers and workers in the informal sector. Participation rate is the percentage of the population ages 15–64 that is economically active: all people who supply labor for the production of goods and services during a speciﬁed period. Agriculture corresponds to division 1 (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 (employees) 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), self-employed workers with without employees (ownaccount workers), and members of producer cooperatives. Although the contributing family workers category is technically part of the self-employed according to the classiﬁcation used by the 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. Employers are workers who, working on their own account or with one or a few

Box 6

Labor market indicators for Sub-Saharan Africa: availability, comparability, and conceptual relevance

Data availability. The main source for labor market indicators is the International Labour Organization. It has two main data repositories: LABORSTA and Key Indicators of the Labour Market. LABORSTA has information on labor force, employment, unemployment, wages, and hours worked. Key Indicators of the Labour Market includes these indicators as well as others on status in employment, time-related underemployment, long-term unemployed, part-time workers, youth unemployment, and employment in the informal economy) It also contains some estimated and predicted indicators, which are an attempt to remedy data unavailability (labor force participation rates, inactivity rates, working poor, labor productivity and labor cost, and employment elasticities) as well as indicators indirectly related to labor markets that come from other sources (inequality, poverty, and educational attainment). However, in both sources coverage of Sub-Saharan Africa is low. For example, the most available indicator in LABORSTA is unemployment, with only 40 percent of the countries having at least one data point between 1985 and 2005. The most available indicators in Key Indicators of the Labour Market are the ones that are estimated or predicted, as well as those indirectly related to the labor market. Unemployment follows, with 55 percent of the countries having at least one data point between 1985 and 2005. Information on informal employment, which can account for more than 60 percent of employment in some countries, is scarce. The most available indicator, employment in the informal economy according to national definitions, is available for only 11 countries, with coverage varying from national to only urban population to capital cities to excluding agriculture. Data comparability. The lack of comparability has to do with differences in measurement. Although there are standard definitions,

partners, hold the type of jobs defined as a self-employment jobs (that is, jobs where the remuneration is directly dependent on the profits derived from the goods and services produced), and, in this capacity, have engaged, on a continuous basis, one or more persons to work for them as employees.

in practice, the indicators are constructed from different sources of information. The data on which they rely vary widely by country: from administrative records, such as social security registries and employment offices, to labor force surveys, household budget surveys, population censuses, establishment surveys or censuses, and economic censuses. Countries also vary in whether they include specific professional categories such as family workers, particularly women, who assist in family enterprises, people in the military, clergy, seasonal workers, part-time workers, sexworkers, and the like. There is also variation in the age brackets used to construct some indicators. Data measurement. The underlying concepts are less appropriate and more difficult to measure in low-income countries. For example, unemployment, which is the most available and used indicator, is typically different in nature in low-income countries, where it is often concentrated among middle class workers. The prevalence of unemployment among poor people is relatively low, since they cannot afford to be unemployed. The current definition relies very much on whether a person has actively searched for a job, which seems less appropriate when labor markets are less developed and mechanisms for looking for jobs are less institutionalized. Both labor supply and income are more difficult to measure for informal activities, the self-employed, and unpaid family workers, which often account for more than half of employment. Multiple jobholdings are common. Current data provide underestimates of labor supply and earnings when they do not take second or third jobs into account. Agriculture accounts for a large share of the labor force, and its inherent seasonality makes labor market indicators more sensitive to the chosen reference period.

Own-account workers are workers who, working on their own-account or with one or more partners, hold the type of jobs deﬁned as a selfemployment jobs, as have engaged on a continuous basis any employees to work for them. Members of producer cooperatives are workers who hold self-employment jobs in a cooperative producing goods and services. Technical notes

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Source: The ILO publishes estimates of the economically active population in its Yearbook of Labour Statistics. Labor force numbers were calculated by World Bank staﬀ, applying labor force participation rates from the ILO database to population estimates. The labor force participation rates are from the ILO’s Estimates and Projections of the Economically Active Population, 1980–2020, ﬁfth edition. The World Bank’s population estimates are compiled and produced by its Human Development Network and Development Data Group in consultation with its operational staﬀ and country oﬃces. Important inputs to the World Bank’s demographic work come from the United Nations Population Division’s World Population Prospects: The 2004 Revision; census reports and other statistical publications from national statistical oﬃces; household surveys conducted by national agencies, Macro International, and the U.S. Centers for Disease Control and Prevention; Eurostat, Demographic Statistics (various years); Centro Latinoamericano de Demografía, Boletín Demográﬁco (various years); and U.S. Bureau of the Census, International Database. Data on status in employment and composition of self-employment are from the ILO’s Key Indicators of the Labour Market, fourth edition. T .. M   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 citizens and noncitizens. Data are ﬁve-year estimates. Workers remittances received comprise current transfers by migrant workers and wages and salaries by nonresident workers. Population is World Bank estimates, usually projected from the most recent population censuses or surveys (mostly from 1980– 2004). Refugees not permanently settled in the country of asylum are generally considered to be part of the population of their country of origin. 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. 136

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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 area population is calculated as the diﬀerence between the total population and the urban population. Urban area population is midyear population of areas deﬁned as urban in each country. Source: World Bank’s World Development Indicators database. 11. HIV/AIDS T .. HIV/AIDS Estimated number of people with HIV/AIDS is the number of people in the relevant age group living 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 adult rate. Estimated prevalence rate is the percentage of the population of the relevant age group who are infected with HIV. Deaths due to HIV/AIDS are the estimated number of adults and children that have died in a speciﬁc year based in 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. Source: The Joint United Nations Programme on HIV/AIDS and the World Health Organization’s 2006 Report on the Global AIDS Epidemic. 12. Malaria T .. M Population is World Bank estimates, usually projected from the most recent population censuses or surveys (mostly from 1980– 2004). Refugees not permanently settled in the country of asylum are generally con-

Box 7

What is causing the apparent stabilization of HIV prevalence in Sub-Saharan Africa?

Two factors are causing the apparent stabilization or leveling off of HIV prevalence rates observed in much of Sub-Saharan Africa: AIDS mortality rates and HIV incidence. High and, in some countries, rising rates of AIDS mortality and continuing high HIV incidence offsetting this mortality are the cause of this appearance of leveling off. In Zambia, for example, national HIV prevalence appears to have stayed relatively stable for the past 8–10 years. Since it is estimated that close to 100,000 people living in Zambia have been newly infected annually over that period, overall prevalence has remained level because AIDS has killed about the same number of people each year. HIV prevalence might therefore appear stable, but it hides a persistently high number of annual, new HIV infections and an equally high number of AIDS deaths. On the other hand, as antiretroviral therapy coverage increases, it is possible that prevalence levels will increase as more people infected with HIV live longer. But we are not, unfortunately, witnessing a regionwide decline in the epidemic. In the absence of effective

interventions, the epidemic will continue to wreak havoc in these countries. It is important to remember that there is not one typical African AIDS epidemic. In 10 countries adult HIV prevalence is below 2 percent, while in 5 other countries it is over 20 percent. These extreme differences in prevalence rates fall roughly into geographically separate areas. Eight countries of Southern Africa (Botswana, Lesotho, Mozambique, Namibia, South Africa, Swaziland, Zambia, and Zimbabwe) have prevalence rates above 15 percent, with Swaziland over 30 percent. In West Africa HIV prevalence is much lower, with no country having a prevalence rate above 10 percent and most having prevalence between 1 percent and 5 percent. Adult prevalence in countries in Central and East Africa falls somewhere between these two groups. The countries of the region also differ in the time course of their epidemics, with epidemics starting earlier in East and Central Africa and much later in Southern Africa. Uganda is an example where adult HIV prevalence peaked in the early 1990.

Source: UNAIDS 2006.

sidered to be part of the population of their country of origin. Endemic risk of malaria is the percentage of the population living in areas with signiﬁcant annual transmission of malaria, be it seasonal or perennial. Epidemic risk of malaria is the percentage of the population living in areas prone to distinct interannual variation, with no transmission taking place at all in some years. Negligible risk of malaria is the percentage of the population living in areas where malaria is ordinarily not present and where the risk of malaria outbreaks is negligible. Deaths due to malaria are the number of malaria deaths per 100,000 people. 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 bednets are the percentage of children under

age 5 who slept under an insecticide-treated bednet to prevent malaria. Children with fever receiving antimalarial drugs are the percentage of children under age 5 in malaria-risk areas with fever being treated with antimalarial drugs. Pregnant women receiving two doses of intermittent preventive treatment are the number of pregnant women who receive at least two preventive treatment doses of an eﬀective antimalarial drug during routine antenatal clinic visits. This approach has been shown to be safe, inexpensive, and eﬀective. Source: Data on population are from the World Bank’s Development Data Platform. Data on risk of malaria, children with fever receiving antimalarial drugs, and pregnanet 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 World Technical notes

137

Health Organization (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 children sleeping under insecticide-treated bednets are from Demographic and Health Surveys and Multiple Indicator Cluster Surveys. 13. Capable States and partnership T .. A    Net aid from all donors is net aid from DAC, non-DAC bilateral (Organization of Petroleum Exporting Countries (OPEC), the former Council for Mutual Economic Assistance (CMEA) countries, and China (OECD data). OPEC countries are Algeria, Iran, Iraq, Kuwait, Libya, Nigeria, Qatar, Saudi Arabia, the United Arab Emirates, and Venezuela. The former CMEA countries are Bulgaria, Czechoslovakia, the former German Democratic Republic, Hungary, Poland, Romania, and the former Soviet Union) and multilateral donors. Net aid from DAC donors is net aid from OECD’s DAC donors, which include Australia, Austria, Belgium, Canada, Denmark, Finland, France, Germany, Italy, Japan, the Netherlands, Norway, Sweden, Switzerland, the United Kingdom, and the United States. Ireland and New Zealand have been excluded in this compilation because their aid to Africa is negligible. Net aid from multilateral donors is net aid from multilateral sources, such as the African Development Fund, the European Development Fund for the Commission of the European Communities, the International Development Association, the International Fund for Agricultural Development, Arab and OPEC ﬁnanced multilateral agencies, and UN programs and agencies. Aid ﬂows from the International Monetary Fund’s (IMF) Trust Fund and Structural Adjustment Facility are also included. UN programs and agencies include the United Nations Technical Assistance Programme, the United Nations Development Programme, the United Nations Oﬃce of the High Commissioner for Refugees, the United Nations Children’s 138

Africa Development Indicators 2006

Fund, and the World Food Programme. Arab and OPEC ﬁnanced multilateral agencies include the Arab Bank for Economic Development in Africa, the Arab Fund for Economic and Social Development, the Islamic Development Bank, the OPEC Fund for International Development, the Arab Authority for Agricultural Investment and Development, the Arab Fund for Technical Assistance to African and Arab Countries, and the Islamic Solidarity Fund. Aid as a share of gross domestic product (GDP) is calculated by dividing the nominal total net aid 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. Aid per capita is calculated by dividing the nominal total net aid by midyear population. These ratios oﬀer some indication of 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. Net aid as a share of gross capital formation is calculated by dividing the nominal total net aid 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. Total net aid as a share of imports of goods and services is calculated by dividing nominal total net aid by imports of goods and services. Total net aid as a share of central government expenditure is calculated by dividing nominal total net aid by central government expenditure. Heavily Indebted Poor Country (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 (IMF) and the World Bank commits to undertake additional reforms and to develop and implement a poverty reduction strategy.

Box 8

Leveraging IDA14 for greater impact

The Fourteenth Replenishment of the International Development Association (IDA14) in fiscal 2006–08 provides for approximately $33 billion in development assistance, about $18 billion of which is from 40 donor countries. As in IDA13, IDA14 places special emphasis on meeting the exceptional development challenges faced by Africa by directing half of its resources to the region, subject to performance. This translates into an approximately 25 percent increase over the amount of IDA financing available for Africa in IDA13. These resources account for 13 percent of all external aid to Africa (Development Committee 2006). While this is a large share for one institution, it is clear that IDA alone cannot address the analytical and operational challenges to accelerate growth and progress toward the Millennium Development Goals in every African country. IDA therefore strives to work effectively with other donors and with governments to maximize the impact of all external aid. A key focus during IDA14 is the debt sustainability of African countries. To this end, financial support from IDA to poor countries now takes systematic account of countries’ risk of debt distress. The countries facing the greatest risk of debt distress—most of which are in Sub-Saharan Africa—will receive all of their support in the form of grants, while less debt-burdened countries will receive credits or a 50-50 mix of grants and credits. As a result, grant-financed operations will account for a substantial share of total IDA14 commitments (initial estimates point to 30 percent). Over 70 percent of total grant resources would likely go to Africa. Africa will also benefit greatly from the ongoing Heavily Indebted Poor Country Debt Relief Initiative and from the recently approved Multilateral Debt Relief Initiative (MDRI). To maximize the impact of increased concessionality and debt reduction, these initiatives must be complemented by increased

HIPC 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.

development assistance. Donors therefore agreed to offset the financial impact of grants on IDA’s finances, and to compensate dollar-for-dollar IDA’s forgone credit reflows that result from the MDRI debt cancellation. The agreements on financial compensation to offset the cost of debt relief will ensure that IDA’s financial integrity is preserved and additional resources are available to help poor countries achieve the Millennium Development Goals and support their development efforts. To encourage effective use of these additional resources, they will be allocated on the basis of policy performance to IDA-only countries, which in turns means that a large share will go to Africa. Africa also receives the lion’s share of the resources allocated under IDA’s allocation system for post-conflict countries. These special post-conflict allocations are provided for a limited period of time to support the exceptional needs of countries emerging from conflict. In these difficult situations, it is critical that IDA work closely with other partners— particularly the United Nations—to ensure that countries receive timely and appropriate support throughout the recovery period, while maintaining a strong focus on performance. During IDA14 it is envisaged that around $450 million will be committed each year for regional projects, $300 million of which will come from a special provision, with the rest contributed from each participating country’s allocation. This regional program is particularly important for Africa, where there is significant potential for countries to work together on a regional basis to achieve greater economies of scale. During IDA13, 88 percent of regional projects were in Africa, and in July 2004 the Bank established a regional integration department for the Africa region that will fund regional pilot projects worth about $500 million by fiscal 2007.

Estimated total nominal debt service relief committed under Enhanced HIPC Initiative 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. Source: OECD and World Bank data. Technical notes

139

T .. C  Public ﬁnancial management is the number of Heavily Indebted Poor Country (HIPC) Debt Initiative benchmarks on managing and tracking public spending that have been met, as reported to the executive boards of the World Bank and the International Monetary Fund Courts are the share of senior managers who ranked courts and dispute resolution systems as a major or very severe constraint. Crime is the share of senior managers who ranked crime, theft, and disorder as a major or very severe constraint. 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. Director liability index measures a plaintiﬀ ’s ability to hold directors of ﬁrms liabile for damages to the company). Shareholder suits index measures shareholders’ ability to sue oﬃcers and directors for misconduct. Investor protection index measures the degree to which investors are protected through disclosure of ownership and ﬁnancial information regulations. 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 to prepare 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 payable is the total amount of taxes payable by the business (except for labor 140

Africa Development Indicators 2006

taxes) after accounting for deductions and exemptions as a percentage of gross proﬁt. For further details on the method used for assessing the total tax payable, see the World Bank’s Doing Business 2006. Extractive Industries Transparency Initiative (EITI) implementing or endorsed indicates whether a country has implemented or endorsed the EITI, a multistakeholder approach to increasing governance and transparency in extractive industries. The EITI 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. Corruption perceptions index transparency index is the annual Transparency International corruption perceptions index, which ranks more than 150 countries in terms of perceived levels of corruption, as determined by expert assessments and opinion surveys. Source: Data on public ﬁnancial management are from the World Bank and the IMF. Data on investment climate constraints to ﬁrms are based on enterprise surveys conducted by the World Bank and its partners during 2001–05 (http://rru.worldbank.org/ EnterpriseSurveys) (see box 4). Data on enforcing contracts, protecting investors, and regulation and tax administration are from the World Bank’s Doing Business project (http://rru.worldbank.org/DoingBusiness/). Data on the EITI are from the EITI website, www.eitransparency.org. Data on corruption perceptions index are from Transparency International (www.transparency.org/policy_ research/surveys_indices/cpi). T .. G     Source: World Bank Institute (see box 9). T .. C P  I A  The Country Policy and Institutional Assessment (CPIA) assess 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 devel-

Box 9

Governance in Sub-Saharan Africa: selected findings and issues

Governance is a key determinant for development and poverty alleviation. To improve governance, however, it is essential to be able to measure it. Skeptical views abound among practitioners: • The composite and subjective nature of governance makes it difficult to measure it correctly. • Where aspects of governance have been measured, the tendency has been to provide a single aggregate rating per country that has little value for policy at the country level. • Measures of governance are also subject to such large errors because they are based on unreliable perceptions, and, even if governance could be measured with some accuracy, the measures would merely confirm what is widely known by country observers. But researchers have increasingly challenged these views, used to criticize existing measures, leading to a growth in governance indicators in recent years. This box focuses on a few selected indicators developed by the World Bank Institute on quality of governance and presents some recent empirical findings for Sub-Saharan Africa (Kaufman, Mraay, and Mastruzzi 2005). The first group of indicators, the Kaufmann-Kraay indicators, uses different sources, as well as a new aggregation technique, to trace six areas of governance from 1996 to the present in almost 200 countries: • Voice and accountability. • Political stability. • Government effectiveness. • Regulatory quality. • Rule of law. • Control of corruption. These indicators show, on average, a marginal deterioration of governance in Sub-Saharan Africa since 2000. A closer look at each indicator reveals, however, significant differences in term of quality of governance across countries. Consider, for example, control of graft. Burkina Faso and Madagascar’s scores significantly improved, while Namibia’s significantly deteriorated. Overall, these indicators can help countries identify general areas of governance weakness. However, the authors caution against using this data to run “horse races” among countries with similar ratings. While the methodology used reduces the margins of error,

the margins of error can still be large enough to make precise rankings of similarly rated countries impossible. The second group of indicators attempts to provide operational guidance either to policymakers or to donors on specific governance challenges. Such more comprehensive unbundling of governance can be achieved through country-level diagnostic surveys. These tools attempt to measure governance through surveys of three different respondents—public officials, firms, and households—and focus on state-firm and state-citizen interactions, as well as on the institutional arrangements in the public sector that drive good or bad performance. These surveys are calibrated to the country context and collect a core of detail data that can be used to benchmark performance across agencies and over time. The wealth of information collected allows also policymakers to prioritize governance challenges and design appropriate policy responses. The availability of such data has deepened the understanding of the costs of poor governance on users of public services. Poor accountability systems and limited transparency can allow public officials to set different prices for the same public service and to limit access. Thus, the cost and the access of publicly provided services may differ across citizens because of bribery. In SubSaharan Africa the data offer ample evidence on how bribery can limit access to specific public services by discouraging users who need that service. These tools collect information also from public officials, allowing an examination of the quality of governance by public agency. The cross-evidence available suggests that governance has an important within-country variation that needs to be explained. In the presence of such diverse patterns across and within countries, the key question becomes whether any general conclusion can be drawn on specific measures that might help these countries curb corruption. Most recently, Recanatini, Prati, and Tabellini (2005) analyzed the data from diagnostic surveys in eight countries and found that specific agency-level institutions—such as auditing mechanisms, publicly announced budget and personnel decisions, and merit-based personnel management—are associated with lower corruption in public agencies.

Source: World Bank Institute.

opment 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: • Economic management. • Structural policies. • Policies for social inclusion and equity. • Public sector management and institutions.

Within these clusters are 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. Country scores reﬂect a variety of indicators and judgments that are based on country’s knowledge; analytic work, policy dialogue, or work done by partners; and relevant publicly available indicators. The rating scale for each criterion varies from 1 (low) to 6 (high). A Technical notes

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rating of 1 indicates a very weak performance and a rating of 6 very strong performance. However, intermediate scores of 1.5, 2.5, 3.5, 4.5, and 5.5 may be given to a country. The ratings derived are the main determinant of present aid eﬀectiveness prospects. Improvements in policies and institutions during the course of the year are reﬂected in the subsequent year’s performance ratings. Source: World Bank’s Country Policy and Institutional Assessment 2005. . H  The questions asked in household surveys vary by country. Quintiles are derived by ranking weighted sample population by area of residence (rural and urban) and per capita expenditure. Two sets of quintiles are calculated, one for rural and one for urban. Each quintile contains an equal number of people rather than households. The deﬁnition of rural and urban also vary by country. Sample size is the number of households surveyed in the country. Total population is the weighted estimate of all the surveyed population in the country based on the survey—that is, it is the weighted sample population. Age dependency ratio is the ratio of dependents—people younger than 15 or older than 64—to the working-age population—those ages 15–64. Average household size is the average number of people in a household. Monogamous male is a household headed by man who has no more than one spouse (wife). Polygamous male is a household headed by a man who has more than one spouse (wife). Single male is a household headed by a man who is widowed or divorced or who has never married. De facto female refers to a household without a resident male head or where the male head is not present and the wife is the head by default and serves as the main decisionmaker in his absence or a household where the resident male head has lost most of his functions as the economic provider due to inﬁrmity, inability to work, or the like. De jure female refers to a household headed by a woman who is widowed, separated, or divorced or who has never been married. Mean monthly expenditure is the average 142

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monthly expenditure on both food and nonfood items. Mean monthly share on food is total monthly food expenditure and food own consumption as a share of total household expenditure. Mean monthly share on health is total health expenditure (consultation, medical procedure, among other) as a share of total household expenditure. Health expenditure excludes hospitalization. Mean monthly share on education is total education expenditure (tuition, transport, and the like) as a share of total household expenditure Primary school within 30 minutes is the share of households that live within 30 minutes of a primary school. Net primary enrollment rate is the ratio of children of a country’s oﬃcial primary school age who are enrolled in primary school to the total population of the corresponding ofﬁcial primary school age. 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 secondary enrollment rate is the ratio of children of a country’s oﬃcial secondary school age who are enrolled in secondary school to the total population of the corresponding oﬃcial secondary school age. 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 enrolment rate is the number of students currently in tertiary education per 10,000 people. Tertiary education, whether or not to an advanced research qualiﬁcation, normally requires, as a minimum condition of admission, the successful completion of education at the secondary level. Adult literacy rate is the percentage of adults ages 15 and older who can both read and write a simple sentence in any language. Youth literacy rate is the percentage of youth ages 15–24 who can both read and write a simple sentence in any language. Health center less than 1 hour away is the percentage of the population living less than 1 hour away from a health center.

Health center less than 5 km away is the percentage of the population living less than 5 kilometers away from a health center Morbidity is the percentage of the population who were sick or injured within a given number of weeks before the survey. Health care provider consulted when sick is the percentage of sick people who took any remedial action when sick. Type of health care provider consulted is the type of facility visited by a sick household member. Public includes fully governmentowned as well as semi-public health facilities. Private, modern medicine, is facilities set up with proﬁt as their main focus and includes private doctors. Private, traditional healers refer to health care providers whose knowledge, skills, and practices are based on the experiences indigenous to diﬀerent cultures and whose services are directed toward the maintenance of health, as well as the prevention, diagnosis, and improvement of physical and mental illness. Other is other types of health providers that cannot be classiﬁed by the categories described above. Birth assisted by trained 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. Immunization coverage, 1-year-olds, is the percentage of children ages 12–23 months at the time of survey who received one dose of Bacille Calmette Guerin vaccine, three doses of polio vaccine, three doses of diphtheria, pertussis, and tetanus vaccine, and one does of measles vaccine. Measles immunization coverage, 1-year-olds, is the percentage of children ages 12–23 months at the time of survey who received a dose of measles vaccine. A child is considered adequately immunized against measles after receiving one dose of vaccine. 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 6–59 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. Wasting is the percentage of children under

age 5 whose weight for height is more than two standard deviations below the median for the international reference population ages 6–59 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. 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 6–59 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. Water source less than 1 hour away is the percentage of the population living less than 1 hour away from a water source. Water source less than 5 km away is the percentage of the population living less than 5 kilometers away from a water source. Market less than 1 hour away is the percentage of the population living less than 1 hour away from a market. Market less than 5 km away is the percentage of the population living less than 5 kilometers away from a market. Access to improved water source refers to 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. Own tap is a household water connection. Other piped is a public water connection. Well, protected, is a ground water source. Traditional fuel use is the percentage of the population using traditional fuels such as ﬁrewood and charcoal as the main source of cooking fuel T .. B F  ,  Household is the basic socioeconomic unit in which the diﬀerent members—related or living in the same house or property—put together their resources and jointly meet their basic needs, including food, under the authority of one person who is recognized as the head. Technical notes

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Source: Burkina Faso’s Institut National de la Statistique et de la Démographie carried out the Enquête Prioritaire II sur les Conditions de Vie des Ménages au Burkina. Data were collected in 2003. The project was funded by the government of Burkina Faso, the World Bank, the African Development Bank, and the United Nations through the United Nations Development Programme. T .. B  ,  Household is people who habitually live and eat their meals in the same compound. One member is recognized as the head. Source: The Institut de Statistiques et d’Études économiques of Burundi, in conjunction with the United Nations Development Programme, carried out the Enquête Prioritaire—Étude nationale sur les conditions de vie des populations. Data were collected in 1998. T .. C  ,  Household is people who live under the same roof, take their meals together or in little groups, and put some or all of their incomes together for the group’s spending purposes, at the head of household’s discretion. Source: Cameroon’s Bureau Central des Recensements et des Enquêtes of the Direction de la Statistique et de la Comptabilité carried out the Enquête Camerounaise auprès des Ménages in 2001. T .. C ’I  ,  Household is a person or a group of people who live under the same roof, share the same meals, and recognize one person as the head. Source: The Institut National de la Statistique carried out the Enquête Niveau de Vie, a priority survey, in 1998. T .. E  ,  Household is a person or a group of people who live under the same roof, share the same meals, and recognize one person as the head. 144

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Source: The 1999/2000 Household Income, Consumption, and Expenditure Survey was carried out by the Central Statistical Oﬃce. The data collection process was carried out from June 1999 to February 2000. T .. G  ,  Household is the set of people who normally ate and lived together for at least 6 of the 12 months preceding the survey. Information on literacy is not reliably available from this survey; less than one in 1,100 who could have responded did so. Source: The Central Department of Statistics of the Ministry of Economic Planning and Industrial Development of Ghana carried out the 1998 National Household Poverty Survey, an integrated survey. Data were collected between April 1998 and May 1998. T .. G  , / Household is a group of people who have usually slept in the same dwelling and have taken their meals together for at least 9 of the 12 months preceding the interview. Source: The Ghana Statistical Service carried out the Ghana Living Standards Survey IV, an integrated survey. Data were collected between April 1998 and March 1999. T .. K  ,  Household is the set of people who normally ate and lived together for 6 of the 12 months preceding the survey. Source: The Kenya Central Bureau of Statistics collected data for the 1997 Welfare Monitoring Survey III, a priority survey, in March and April 1997. T .. M  ,  Household is the set of people who may but do not necessarily have family links between them, who live and sleep in the same housing, and who take their meals together regularly. The housing may be an individual house, an apartment, or one or more rooms in a larger building. The household is headed by one in-

dividual whose authority is recognized by all in the household. Literacy measures the number of household members ages 5 and older who completed at least four years of primary school or who could read and write. Source: The Institut National de la Statistiques carried out the Enquête Prioritaire auprès des ménages in 1999. The project was funded by the government of Madagascar and the World Bank (International Development Association). T .. M  , / Household is a person living alone or a group of people, either related or unrelated, who live together as a single unit in the sense that they have common housekeeping arrangements (that is, share or are supported by a common budget). Someone who did not live with the household during the survey period was not counted as a current member of the household. Literacy measures the ability to read and write a simple sentence for those who had not attended school in the past two months and was deﬁned based on education attainment for those who had attended school in the past two months. Source: The Malawi National Statistics Ofﬁce carried out the Integrated Household Survey from November 1997 to October 1998. T .. M  ,  Household is the set of people who partly or totally shared their expenditures, had not been absent for more than 6 of the 12 months preceding the survey, and were not domestic help. In the case of polygamous households, each wife and her children were considered to be a separate household. Literacy measures the number of people with ability to read and write in Portuguese. Source: The Instituto Nacional de Estatistiqua carried out the Inquérito Nacional aos Agregados Familiares sobre as Condições de Vida, an integrated survey undertaken in 1996.

T .. N  ,  Household is a group of persons who normally cook, eat, and live together. Number of months sharing in these activities was another criterion used to qualify as a household a member (minimum of three months). However, all heads of households irrespective of number of months living elsewhere were included as household members. These people may or may not be related by blood, but make common provision for food or other essentials for living, and they have one person whom they all regard as the head of the household. Literacy measures the number of people with the ability to read and write either in English or any of the local languages. Source: The Federal Oﬃce of Statistics, Abuja, of Nigeria carried out the Nigeria Living Standards Survey, an integrated survey. Data were collected between September 2003 and August 2004. T .. S T  P  ,  Household is the set of people, related or not, who live together under the same roof, put their resources together, and address as a unit their primary needs, under the authority of one person whom they recognize as the head of the household. Literacy measures the number of people with the ability to read and write a simple sentence. Source: The Instituto Nacional de Estatistica of the Ministério de Planomento, Finanças e Cooperaçao carried out the Enquête sur les Conditions de Vie des Ménages in 2000. The project was ﬁnanced by the government of São Tomé and Principe with assistance from the African Development Bank and the United Nations Development Programme. Technical assistance was provided by the International Labour Organization. T .. S L  , / Household is a group of people who normally cook, eat, and live together. Number of months sharing in these activities was another criterion used to qualify as a household a Technical notes

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member (minimum three months). However, all heads of households irrespective of number of months living elsewhere were included as household members. These people may or may not be related by blood, but make common provision for food or other essentials for living, and they have one person whom they all regarded as the head of the household. Literacy measures the number of people with the ability to read and write a simple sentence in either English or the local languages. Source: The Sierra Leone Central Statistical Oﬃce carried out the Living Conditions Monitoring Survey. Data were collected between 2002 and 2003. T .. U  , / Household is individuals who normally eat and live together. Literacy measures the number of people who responded that they could both read and

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write. The level of education was also used to determine literacy. Source: The Uganda Bureau of Statistics carried out the National Household Survey. Data collection occurred between May 2002 and April 2003. The project was funded by the government of Uganda and the World Bank. Statistics Denmark and the World Bank provided consultants for technical support. T .. Z  ,  Household is a group of persons who normally cooked, ate, and lived together. These people may or may not be related by blood, but make common provision for food or other essentials for living, and they have one person whom they all regarded as the head of the household. Source: The Zambian Central Statistical Ofﬁce carried out the Living Conditions Monitoring Survey II. Data were collected between November 1998 and December 1998.

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IMF (International Monetary Fund). 2006a. “HIPC Status Report.” March. Washington, D.C. ———. 2006b. International Financial Statistics database. Washington, D.C. ———. 2006c. World Economic Outlook database. Washington, D.C. ———. Various issues. Direction of Trade Statistics Quarterly. Washington, D.C. ———. Various years. Direction of Trade Statistics Yearbook. Washington, D.C. ———. Various issues. Global Financial Stability Report: Market Developments and Issues. Washington, D.C.

Chen, Shaohua, and Martin Ravallion. 2004. “How Have the World’s Poorest Fared since the Early 1980s?” World Bank Research Observer 19 (2): 141–69.

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———. Various years. Production Yearbook. Rome.

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Mozambique, Instituto Nacional de Estatistiqua. 1996. “Inquérito Nacional aos Agregados Familiares sobre as Condições de Vida.” Maputo.

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———. 2005. Key Indicators of the Labour Market. 4th ed. Geneva: International Labour Office.

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———. Various years. Yearbook of Labour Statistics. Geneva: International Labour Office.

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Standard & Poor’s. 2005. Emerging Stock Markets Factbook. New York: The McGraw Hill Companies.

———. 2006a. Africa Live Database. Washington, D.C. [http:// www4.worldbank.org/afr/stats/ldb.cfm].

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———. 2006b. “Doing Business Project.” Washington, D.C. [http:// www.doingbusiness.org/]. ———. 2006c. “Enterprise Surveys.” [www.enterprisesurveys.org].

Uganda, Bureau of Statistics. 2003. “National Household Survey.” Kampala. UNAIDS (Joint United Nations Programme on HIV/AIDS). 2006. 2006 Report on the Global AIDS Epidemic. Geneva UNCTAD (United Nations Conference on Trade and Development). Various years. Handbook of International Trade and Development Statistics. New York. UNICEF (United Nations Children’s Fund). 2006. State of the World’s Children 2006. New York. United Nations Population Division. World Population Prospects: The 2004 Revision. Population database. [http://esa.un.org/ unpp/]. United Nations Statistics Division. United Nations Commodity Trade Statistics Database (COMTRADE). [http://unstats. un.org/unsd/comtrade/]. U.S. Department of Energy. 2004. International Energy Annual 2004. Energy Administration Information, Washington, D.C. WHO (World Health Organization). 2006a. Global Tuberculosis Control Report 2006. Geneva. ———. 2006b. World Health Report, 2006 edition. Geneva. [http:// www3.who.int/whosis/core/core_select.cfm?path=whosis,cor e&language=english] ———. 2006c. World Health Statistics 2006. Geneva. [http:// www3.who.int/whosis/core/core_select.cfm?path=whosis,cor e&language=english] WHO (World Health Organization) and UNICEF (United Nations Children’s Fund) Joint Monitoring Programme for Water Supply and Sanitation. 2006. Meeting the MDG Drinking Water and Sanitation Target. New York and Geneva. [www.unicef. org/wes/mdgreport/]. World Bank. 2005a. “Enabling Country Capacity to Achieve Results.” Comprehensive Development Framework Progress Report. Washington, D.C. ———. 2005b. Global Economic Prospects 2005: Trade, Regionalism and Development. Washington, D.C.

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———. 2006d. Global Development Finance database. Washington, D.C. ———. 2006e. Private Participation in Infrastructure database. [http://ppi.worldbank.org/]. ———. Various years. World Bank Atlas. Washington, D.C. ———. Various years. World Development Indicators. Washington, D.C. Zambia, Central Statistical Office. 1998. “Living Conditions Monitoring Survey.” Lusaka.

Users Guide

World Bank Africa Database 2006 and Africa Development Indicators CD-ROM Introduction This CD-ROM is part of the World Bank Africa Database family of products. It was produced by the Operational Quality and Knowledge Services and the Office of the Chief Economist for the Africa Region, in collaboration with the Development Data Group of the Development Economics Vice Presidency. It uses the latest version of the World Bank’s *STARS* data retrieval system, Win*STARS version 5.0. The CD-ROM contains about 1,200 macroeconomic, sectoral, and social indicators, covering 53 African countries. Time series include data from 1965 to 2004. The CD-ROM includes two sets of tables: Countryat-a-Glance and Africa Development Indicators. It also contains a query tool that allows the user to display about 1,200 time series. Win*STARS 5.0 features mapping and charting and several data export formats (Access™, ASCII, dBASE™, Excel™, and SAS™). We invite you to explore it.

A note about the data Users should note that the data for Africa Development Indicators, The Little Data Book on Africa, and the World Bank Africa Database CD-ROM are drawn from the same database. The general cutoff date for data is May 2006.

Help This guide explains how to use the main functions of the CD-ROM. For details about additional features, click Help on the menu bar or the Help icon; or call one of the hotline numbers listed in the Help menu and on the copyright page of this booklet.

Installation As is usual for Windows™ products, you should make sure that other applications are closed while you install the CD-ROM. To install the single-user version: 1. Insert the CD-ROM into your CD drive. 2. Click on Start and select Run. Type D:\SETUP.EXE (where D: is your CD-ROM drive letter), click OK and follow the instructions. 3. Win*STARS 5.0 requires Microsoft Internet Explorer™ 4.0 or higher. If you do not have Internet Explorer, it may be downloaded at no charge from www. microsoft.com. It does not need to be your default browser. If you do not wish to use Internet Explorer, you have the option to install Win*STARS 4.2. You can delete this program at any time by clicking on Start, Settings, Control

Panel, Add/Remove Programs. To reinstall it, reboot your computer first.

Operation To start the CD-ROM, go to the WB Development Data program group and click on the WB Africa 2006 Database CD-ROM icon. Note that standard Windows™ controls are used for most functions. For detailed instructions, refer to the on-screen Help menu or tool tips (on-screen explanations of buttons that are displayed when the cursor rolls over them).

Features and instructions Win*STARS has four main functions—Home, Query, Result, and Map. Move among them at any time by clicking on the respective tabs.

Home On the Home screen you can access each element of the World Bank Africa Database CD-ROM. Use the browser controls to link to the Africa Development Indicator tables, Country-at-a-Glance tables, time series database, world map, and other related information.

Query 1. Click on the Query button to start your time series selection. 2. Click on each of the Country, Series, and Periods buttons and make your selections on each screen. There are many ways to make a selection—see below, or use the Help menu. 3. Highlight the items you want. 4. Click on the Select button to move them into the Selected box. 5. Deselect items at any time by highlighting them and clicking on the Remove icon. 6. When selection is complete, click on OK to return to the main Query screen. 7. If you want to, you can display information on data availability by clicking on the Availability icon. You can choose to count time series or total observations. 8. Click on View Data to see the data on the Result screen. Making selections. Countries: You can select countries from an alphabetical list, by Classification (region, income group, or indebtedness), by Criteria (up to two can be specified), or by Group (aggregates have been calculated only when there were adequate data). Series: You can choose from an alphabetical list or by Category. When selecting series by category, the subcategory buttons change with each category. Periods: Select time periods from the Periods list box.

Creating your own country or indicator list. You can create your own group of countries, series, or periods by saving your query on the appropriate screen. You can also save all elements of the query on the Query screen. You can reload a saved query in a future session. To save a query: 1. Highlight items on any of the Countries, Series, or Periods (or any two or all three) selection screens and click on Select to place them in the Selected box. 2. Click on the Save Query icon and follow the naming prompts. To load a query: 1. Go to the selection screen in which your query is saved. For example, if you have saved a set of countries, go to the Countries selection screen. 2. Click on the Load Query icon, select the query you want, and click on OK. To modify a saved query: 1. Load the query. 2. In the Selected box, highlight the items to be removed and click on the Remove icon. 3. Add new items if necessary. 4. Resave the query.

Result On the Result screen, data are presented in a three-dimensional spreadsheet and, initially, in scientific notation. Data for the third dimension are presented on separate screens. You can change the selection displayed by clicking on the third dimension scroll box. You can also change the scale and the number of digits after the decimal. If the column is too narrow to present all the digits, they will appear as a series of ######. Double click on the column’s guideline to widen it, or choose a larger scale (millions, for example). To scale series individually, click Options and check Enable Series-Level Scaling. Click the far right scroll box to view the percentage change over each selected period or to index the data. Changing the orientation. You can view the result in six different orientations (countries down/periods across, series down/countries across, etc.). To change the orientation, click on the Orientation scroll box. Charting and mapping data. On the Result screen, you can chart or map the data displayed. Highlight a set of cells for charting or a particular cell for mapping. Click on the Chart or Map icon on the toolbar accordingly. The charting function has many features.

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After you have displayed a chart, right click on the chart to open the Chart Wizard for more options. Mapping is described on page 8. From this screen you can choose to map all countries or only your selected countries. Cutting, pasting, printing, and saving. You can cut, paste, and print the result, or you can save the spreadsheet in another format. Click on the appropriate icon on the toolbar and follow the prompts. Click on Help for more details.

Map On the Map screen, you can select a country and view a set of tables describing it, or you can map a series for all countries. In the upper left corner of the screen, the country name will appear as the cursor rolls slowly over the map. To zoom in for a closer look at the map, click on the Zoom icon. Selecting a country or viewing country tables. To highlight a country and view any of its tables, click on the country on the map or select it in the Locate a Country scroll box in the upper right corner. Mapping a series. On the Map screen, click on the Series icon. A list of key indicators will be displayed. (To show all available indicators, click on the box by Show default series to remove the X.) Highlight a series, select a period from the Available Periods list box (the default is the latest available) and click on Paint Map. The map will be colored according to the legend settings, any of which you can change. Note that as the cursor moves across the map, the series value is now also displayed in the upper left corner. Changing the map legend and colors. The default interval range is an equal number of countries. To set an equal interval range or to map multiple periods, click on the Recalculate icon. Set your own intervals by editing the legend. To change map colors, double click on the legend color boxes. Press the Remap icon to see your changes. Printing and saving. Click on the appropriate icon to print the map or save it as a bitmap or metafile.

License agreement You must read and agree to the terms of this License Agreement prior to using this CDROM product. Use of the software and data contained on the CD-ROM is governed by the terms of this License Agreement. If you do not agree with these terms, you may return the product unused to the World Bank for a full refund of the purchase price. 1. LICENSE. In consideration of your payment of the required license fee, the WORLD BANK (the “Bank”) hereby grants you a nonexclusive license to use the

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enclosed data and Win*STARS retrieval program (collectively, the “Program”) subject to the terms and conditions set forth in this license agreement. 2. OWNERSHIP. As a licensee you own the physical media on which the Program is originally or subsequently recorded. The Bank, however, retains the title and ownership of the program recorded on the original CD-ROMs and all subsequent copies of the Program. This license is not considered to be a sale of the Program or any copy thereof. 3. COPY RESTRICTIONS. The Program and accompanying written materials are copyrighted. You may make one copy of the Program solely for backup purposes. Unauthorized copying of the Program or of the written materials is expressly forbidden. 4. USE. You may not modify, adapt, translate, reverse-engineer, decompile, or disassemble the Program. You may not modify, adapt, translate, or create derivative works based on any written materials without the prior written consent of the Bank. If you have purchased the single-user version of this product, you may use the Program only on a single laptop/desktop computer. You may not distribute copies of the Program or accompanying written materials to others. You may not use the Program on any network, including an Intranet or the Internet, without obtaining prior written permission from the Bank. If you have purchased the multiple-user version of this product, your license is valid only up to 15 users. Should you need to add additional users, please send a request, indicating the number of users you would like to add, to: World Bank Publications, Marketing and Rights, 1818 H Street, N.W., Washington, D.C. 20433, fax: 202-522-2422, email: [email protected]. 5. TRANSFER RESTRICTIONS. This Program is licensed only to you, the licensee, and may not be transferred to anyone without prior written consent of the Bank. 6. LIMITED WARRANTY AND LIMITATIONS OF REMEDIES. The Bank warrants that under normal use the CDROMs on which the Program is furnished are free from defects in materials and workmanship for a period of ninety (90) days from delivery to you, as evidenced by a copy of your receipt. The Bank’s entire liability and your exclusive remedy shall be the replacement of any CD-ROMs that do not meet the Bank’s limited warranty. Defective CD-ROMs should be returned within the warranty period, with

a copy of your receipt, to the address specified in section 9 below. EXCEPT AS SPECIFIED ABOVE, THE PRODUCT IS PROVIDED “AS IS” WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE BANK DOES NOT WARRANT THAT THE FUNCTIONS CONTAINED IN THE PROGRAM WILL MEET YOUR REQUIREMENTS OR THAT THE OPERATION OF THE PROGRAM WILL BE UNINTERRUPTED OR ERROR-FREE. IN NO EVENT WILL THE BANK BE LIABLE TO YOU FOR ANY DAMAGES ARISING OUT OF THE USE OF OR THE INABILITY TO USE THE PROGRAM. THE ABOVE WARRANTY GIVES YOU SPECIFIC LEGAL RIGHTS IN THE UNITED STATES THAT MAY VARY FROM STATE TO STATE. BECAUSE SOME STATES DO NOT ALLOW THE EXCLUSION OF IMPLIED WARRANTIES OR LIMITATION OF EXCLUSION OF LIABILITY FOR INCIDENTAL OR CONSEQUENTIAL DAMAGES, PARTS OF THE ABOVE LIMITATIONS AND EXCLUSIONS MAY NOT APPLY TO YOU. 7. TERMINATION. This license is effective from the date you open the package until the license is terminated. You may terminate it by destroying the Program and its documentation and any backup copy thereof or by returning these materials to the Bank. If any of the terms or conditions of this license are broken, the Bank may terminate the license and demand that you return the Program. 8. GOVERNING LAW. This license shall be governed by the laws of the District of Columbia, without reference to conflicts of law thereof. 9. GENERAL. If you have any questions concerning this product, you may contact the Bank by writing to World Bank Publications, CD-ROM Inquiries, The World Bank, 1818 H Street, N.W., Washington, D.C. 20433, fax: 202-522-1498, email: [email protected]. All queries on rights and licenses should be addressed to World Bank Publications, Marketing and Rights, 1818 H Street, N.W., Washington, D.C. 20433, fax: 202-522-2422, email: [email protected].

AFRICA

DEVELOPMENT INDICATORS

2006 Africa Development Indicators 2006 provides the most detailed collection of data on Africa available in one volume. It contains about 450 macroeconomic, sectoral, and social indicators, covering 53 African countries. Additional data may be found on the companion CD-ROM, World Bank Africa Database 2006, covering about 1,200 indicators from 1965 to 2004.

• • • • • • • • • • • • • •

Basic indicators National accounts Millennium Development Goals Paris Declaration indicators Private sector development Trade Infrastructure Human development Agriculture and rural development Labor, migration, and population HIV/AIDS Malaria Capable states and partnership Household welfare

Designed to provide all those interested in Africa with a focused and convenient set of data to monitor development programs and aid ﬂows in the region, this is an invaluable reference tool for analysts and policymakers who want a better understanding of the economic and social developments occurring in Africa.

ISBN 0-8213-6537-1