Africa Development Indicators 2011
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Africa Development Indicators 2011
Africa Development Indicators 2011 is the most detailed
collection of data on Africa. It contains macroeconomic,
sectoral, and social indicators for 53 countries.
The companion CD-ROM has additional data, with
some 1,700 indicators covering 1961–2009.
Basic indicators
National and fiscal accounts
External accounts and exchange rates
Millennium Development Goals
Private sector development
Trade and regional integration
Infrastructure
Human development
Agriculture, rural development, and the environment
Labor, migration, and population
HIV/AIDS and malaria
Capable states and partnership
Paris Declaration indicators
Governance and polity
Designed as both a quick reference and a reliable dataset
for monitoring development programs and aid flows in the
region, Africa Development Indicators 2011 is an invaluable
tool for analysts and policymakers who want a better
understanding of Africa’s economic and social development.
ISBN 978-0-8213-8731-3
SKU 18731
2 0 1 1
Copyright © 2011 by the International Bank
for Reconstruction and Development/The World Bank
1818 H Street, N.W.
Washington, D.C. 20433, U.S.A.
All rights reserved
Manufactured in the United States of America
First printing 2011
This volume is a product of the staff of the International Bank for Reconstruction and Development/The World Bank. The findings,
interpretations, and conclusions expressed in this volume do not necessarily reflect the views of the Executive Directors of The
World Bank or the governments they represent.
The World Bank does not guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and
other information shown on any map in this work do not imply any judgment on the part of The World Bank concerning the legal
status of any territory or the endorsement or acceptance of such boundaries.
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The material in this publication is copyrighted. Copying and/or transmitting portions or all of this work without permission may
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All other queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World
Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2422; e-mail: [email protected]
ISBN: 978-0-8213-8731-3
e-ISBN: 978-0-8213-8732-0
DOI: 10.1596/978-0-8213-8731-3
SKU: 18731
Library of Congress Cataloging-in-Publication data have been requested.
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Photo credits: front cover, Arne Hoel/World Bank; back cover, Arne Hoel/World Bank and Jonathan Ernst/World Bank.
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To order Africa Development Indicators 2011, The Little Data Book on Africa 2011 (available online only), or Africa Development Indicators 2011–Multiple User CD-ROM, please visit www.worldbank.org/publications. To subscribe to Africa Development Indicators Online please visit http://publications.worldbank.org/ADI.
For more information about Africa Development Indicators and its companion products, please visit www.worldbank.org/africa
or email [email protected]
Contents
Foreword
vii
Acknowledgments
ix
Indicator tables
1
Users guide
3
Part I. Basic indicators and national and fiscal accounts
1. Basic indicators
1.1 Basic indicators
2. National and fiscal accounts
2.1 Gross domestic product, nominal
2.2 Gross domestic product, real
2.3 Gross domestic product growth
2.4 Gross domestic product per capita, real
2.5 Gross domestic product per capita growth
2.6 Gross national income, nominal
2.7 Gross national income, World Bank Atlas method
2.8 Gross national income per capita, World Bank Atlas method
2.9 Gross domestic product deflator (local currency series)
2.10 Gross domestic product deflator (U.S. dollar series)
2.11 Consumer price index
2.12 Price indexes
2.13 Gross domestic savings
2.14 Gross national savings
2.15 General government final consumption expenditure
2.16 Household final consumption expenditure
2.17 Final consumption expenditure plus discrepancy
2.18 Final consumption expenditure plus discrepancy per capita
2.19 Gross fixed capital formation
2.20 Gross general government fixed capital formation
2.21 Private sector fixed capital formation
2.22 External trade balance (exports minus imports)
2.23 Exports of goods and services, nominal
2.24 Imports of goods and services, nominal
2.25 Exports of goods and services as a share of GDP
2.26 Imports of goods and services as a share of GDP
2.27 Balance of payments and current account
2.28 Exchange rates and purchasing power parity
2.29 Agriculture value added
2.30 Industry value added
2.31 Services plus discrepancy value added
2.32 Central government finances, expense, and revenue
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
36
38
39
40
41
Contents
iii
2.33 Structure of demand
45
Part II. Millennium Development Goals
3. Millennium Development Goals
3.1 Millennium Development Goal 1: eradicate extreme poverty and hunger
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
46
49
50
51
52
53
55
57
Part III. Development outcomes
iv
Africa Development Indicators 2011
Drivers of growth
4. Private sector development
4.1 Doing Business indicators
4.2 Investment climate
4.3 Financial sector infrastructure
59
62
64
5. Trade and regional integration
5.1 International trade and tariff barriers
5.2 Top three exports and share in total exports, 2009
5.3 Regional integration, trade blocs
66
70
72
6. Infrastructure
6.1 Water and sanitation
6.2 Transportation
6.3 Information and communication technology
6.4 Energy
74
75
77
80
Participating in growth
7. Human development
7.1 Education
7.2 Health
82
84
8. Agriculture, rural development, and environment
8.1 Rural development
8.2 Agriculture
8.3 Producer food prices
8.4 Environment
8.5 Fossil fuel emissions
88
90
92
94
96
9. Labor, migration, and population
9.1 Labor force participation
9.2 Labor force composition
9.3 Unemployment
9.4 Migration and population
98
100
102
104
10. HIV/AIDS
10.1 HIV/AIDS
106
11. Malaria
11.1 Malaria
110
12. Capable states and partnership
12.1 Aid and debt relief
12.2 Status of Paris Declaration indicators
12.3 Capable states
12.4 Governance and anticorruption indicators
12.5 Country Policy and Institutional Assessment ratings
12.6 Polity indicators
111
114
116
118
120
124
Technical notes
125
Technical notes references
181
Map of Africa
182
Users guide: Africa Development Indicators 2011–Multiple User CD-ROM
183
Contents
v
Foreword
This year’s Africa Development Indicators,
which covers some 1,700 macroeconomic,
sectoral, and human development indicators dating to the 1960s, comes at a critical
time for Sub-Saharan Africa’s 48 countries
and 841 million people. After a decade of
economic growth at nearly 5 percent a year,
Africa—along with the rest of the world—
was hit hard by the global economic crisis,
but it rebounded within a year. In 2011 the
continent’s growth is expected to return to
precrisis levels. The poverty rate has been
declining at about 1 percentage point a year,
and progress on the Millennium Development Goals, while insufficient to reach the
2015 targets in many countries, has been
substantial.
Yet, Africa faces some of the most formidable development challenges in the world.
First, growth has been uneven, with about
20 fragile and conflict-affected states seemingly trapped in persistent poverty. Second,
economic growth has not translated to productive jobs and more earning opportunities
for Africa’s labor force—most of which is
engaged in agriculture and informal enterprises—and especially for the 7‒10 million
young people entering the labor force each
year. And third, Africa’s growth could be
faster and more widespread (and abject poverty eliminated) if it could address its most
fundamental challenges—improving governance and increasing public sector capacity.
Just as the World Bank’s Africa strategy,
Africa’s Future and World Bank Support to It,
seeks to harness the continent’s recent dynamic growth to address these development
challenges, so too do statistics in general,
and Africa Development Indicators in particular, reflect both the progress and the potential of the continent. Africa Development Indicators permits policymakers, private actors,
civil society, development partners, and
citizens to monitor, study, and document
Africa’s economic and social development. It
also shows where we need to improve. Just
18 of 48 countries have poverty data for
2007‒10. And in the 2000s Africa averaged
1.5 poverty figures per country, less than
half the world’s average of 3.8. One reason
for the shortcomings is lack of statistical capacity—as of 2010 only six countries have
statistical capacity building indicators of
70‒84 percent. But here too there has been
progress: all but four countries now have an
official national statistics website, compared
with 50 percent a few years ago. More than
20 countries have made their household survey datasets available on their national data
archive website, and more than 75 percent
of Africa’s people are covered by a population census less than 10 years old.
Since 2005 countries have developed
their national statistical systems by designing and implementing a National Strategy for the Development of Statistics, which
links data with poverty reduction strategies.
The World Bank, in collaboration with other
partners, is providing financial support and
technical advice through lending operations
such as STATCAP, through trust funds (in
particular the Trust Fund for Statistical Capacity Building and the Statistics for Results
Catalytic Fund), and through international
initiatives. Moving forward, the Bank will
scale up its statistical capacity development
activities, not least because it is only with
credible statistics that progress on the Africa strategy can be monitored. In addition,
technology is being used to accelerate data
collection, especially in underserved areas.
For instance, in Africa’s newest country, the
Republic of South Sudan, the Bank is collaborating with the local statistics office to
Foreword
vii
collect information on people’s economic
situation, security, and outlook using cell
phones distributed to 1,000 households in
10 state capitals.
Africa Development Indicators has another,
more fundamental role in Africa’s development. Statistics—and the information contained in them—can empower citizens to
hold their governments accountable. From
the first public expenditure tracking survey
of education in Uganda to the Ushahidi platform for tracking political violence and natural disasters, Africans have demonstrated
how systematic data can mobilize citizens to
spur their governments to action. Inasmuch
as governance was identified as the fundamental constraint to African development,
Africa Development Indicators is a major instrument in relaxing that constraint.
viii
Africa Development Indicators 2011
To that end, since April 2010 the World
Bank has made all its data freely available,
resulting in continually growing use of its
online resources. This volume is part of the
Africa Development Indicators suite of products, which also includes The Little Data Book
on Africa 2011 (available online only), the Africa Development Indicators 2011–Multiple
User CD-ROM, and a data query and charting application for mobile services.
A tool for learning, capacity strengthening, and accountability, Africa Development
Indicators 2011 will continue to play a critical
role in Africa’s economic transformation.
Obiageli K. Ezekwesili
Vice President
The World Bank Group
Africa Region
Acknowledgments
Africa Development Indicators is a product of
the Africa Region of the World Bank.
This report has been prepared by a core
team led by Rose Mungai comprising Francoise Genouille and Jane Njuguna in the production of this book and its companions—
Africa Development Indicators Online 2011,
Africa Development Indicators 2011—Multiple User CD-ROM, and The Little Data
Book on Africa 2011 (online only). Yohannes
Kebede coordinated the Africa Development
Indicators Online apps platform while Mapi
Buitano coordinated the dissemination
of the book and its companions, and Jane
Njuguna coordinated production. The overall work was carried out under the guidance
of Shantayanan Devarajan, Chief Economist
of the Africa Region.
The technical box contributors were:
• Ghislaine Delaine and Antoine Simonpietri (African statistical systems).
• Shantayanan Devarajan (Africa’s future
and the World Bank’s support to it).
• Quy-Toan Do (Multidimensional indices
of poverty).
• Punam Chuhan-Pole and Manka S. Angwafo (Transformation of Rwanda’s coffee sector: an African success story).
• Sailesh Tiwari and Hassan Zaman (Food
prices in Africa).
• Dilip Ratha, Sanket Mohapatra, Caglar
Ozden, Sonia Plaza, and Abebe Shimeles
(Migration and remittances in Africa).
• Bernard Harborne, Noro Aina Andriamihaja, and Viola Erdmannsdoerfer
(Conflict-affected and fragile states in
Africa).
•
Stuti Khemani (The political economy of
public policies and government failures).
Azita Amjadi, Abdolreza Farivari,
Shelley Lai Fu, Ugendran Machakkalai,
Shanmugam Natarajan, Lakshmikanthan
Subramanian, and Malarvizhi Veerappan
collaborated in the online data production.
Maja Bresslauer, Mahyar Eshragh-Tabary,
Masako Hiraga, and Soong Sup Lee collaborated in the update of the live database. Software preparation and testing for
the CD-ROM and mobile applications was
managed by Vilas Mandelkar, with the assistance of Ramgopal Erabelly, Parastoo
Oloumi, William Prince, and Jomo Tariku.
William Prince also collaborated in the
production of The Little Data Book on Africa
2011.
Jeffrey Lecksell and Bruno Bonansea of
the World Bank’s Map Design Unit coordinated preparation of the maps.
Ann Karasanyi and Kenneth Omondi
provided administrative and logistical support. The core team would like to thank the
many people who provided useful comments on the publication. Their feedback
and suggestions helped improve this year’s
edition.
Staff from External Affairs oversaw
printing and dissemination of the book and
its companions.
Several institutions provided data to
Africa Development Indicators. Their contribution is very much appreciated.
Communications Development Incorporated provided design direction, editing, and
layout.
Acknowledgments
ix
Indicator tables
Part I. Basic indicators and national and fiscal accounts
1. Basic indicators
1.1 Basic indicators
2. National and fiscal accounts
2.1 Gross domestic product, nominal
2.2 Gross domestic product, real
2.3 Gross domestic product growth
2.4 Gross domestic product per capita, real
2.5 Gross domestic product per capita growth
2.6 Gross national income, nominal
2.7 Gross national income, World Bank Atlas method
2.8 Gross national income per capita, World Bank Atlas method
2.9 Gross domestic product deflator (local currency series)
2.10 Gross domestic product deflator (U.S. dollar series)
2.11 Consumer price index
2.12 Price indexes
2.13 Gross domestic savings
2.14 Gross national savings
2.15 General government final consumption expenditure
2.16 Household final consumption expenditure
2.17 Final consumption expenditure plus discrepancy
2.18 Final consumption expenditure plus discrepancy per capita
2.19 Gross fixed capital formation
2.20 Gross general government fixed capital formation
2.21 Private sector fixed capital formation
2.22 External trade balance (exports minus imports)
2.23 Exports of goods and services, nominal
2.24 Imports of goods and services, nominal
2.25 Exports of goods and services as a share of GDP
2.26 Imports of goods and services as a share of GDP
2.27 Balance of payments and current account
2.28 Exchange rates and purchasing power parity
2.29 Agriculture value added
2.30 Industry value added
2.31 Services plus discrepancy value added
2.32 Central government finances, expense, and revenue
2.33 Structure of demand
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
36
38
39
40
41
45
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
46
49
50
51
52
Indicator tables
1
3.6 Millennium Development Goal 6: combat HIV/AIDS, malaria, and other diseases
3.7 Millennium Development Goal 7: ensure environmental sustainability
3.8 Millennium Development Goal 8: develop a global partnership for development
53
55
57
Part III. Development outcomes
2
Africa Development Indicators 2011
Drivers of growth
4. Private sector development
4.1 Doing Business indicators
4.2 Investment climate
4.3 Financial sector infrastructure
59
62
64
5. Trade and regional integration
5.1 International trade and tariff barriers
5.2 Top three exports and share in total exports, 2009
5.3 Regional integration, trade blocs
66
70
72
6. Infrastructure
6.1 Water and sanitation
6.2 Transportation
6.3 Information and communication technology
6.4 Energy
74
75
77
80
Participating in growth
7. Human development
7.1 Education
7.2 Health
82
84
8. Agriculture, rural development, and environment
8.1 Rural development
8.2 Agriculture
8.3 Producer food prices
8.4 Environment
8.5 Fossil fuel emissions
88
90
92
94
96
9. Labor, migration, and population
9.1 Labor force participation
9.2 Labor force composition
9.3 Unemployment
9.4 Migration and population
98
100
102
104
10. HIV/AIDS
10.1 HIV/AIDS
106
11. Malaria
11.1 Malaria
110
12. Capable states and partnership
12.1 Aid and debt relief
12.2 Status of Paris Declaration indicators
12.3 Capable states
12.4 Governance and anticorruption indicators
12.5 Country Policy and Institutional Assessment ratings
12.6 Polity indicators
111
114
116
118
120
124
Users guide
Tables
The tables are numbered by section. Countries are listed alphabetically by subregion
(Sub-Saharan Africa and North Africa). Indicators are shown for the most recent year
or period for which data are available and, in
most tables, for an earlier year or period (usually 1980, 1990, or 1995). Time-series data
are available on the Africa Development Indicators—Multiple User CD-ROM and Africa
Development Indicators Online. The term
country, used interchangeably with economy,
does not imply political independence but
refers to any territory for which authorities
report separate social or economic statistics.
Known deviations from standard definitions
or breaks in comparability over time or across
countries are noted in the tables. When available data are deemed too weak to provide
reliable measures of levels and trends or do
not adequately adhere to international standards, the data are not shown.
Aggregate measure for region
and subclassifications
The aggregates are based on the World Bank’s
regional classification for Sub-Saharan Africa and North Africa, which may differ from
common geographic usage. Former Spanish
Sahara is not included in any aggregates.
Statistics
Data are shown for economies as they were
constituted in 2008, and historical data are
revised to reflect current political arrangements. Exceptions are noted in the tables.
Consistent time-series data for 1961–2009
are available on the Africa Development
Indicators—Multiple User CD-ROM and Africa Development Indicators Online. Data for
some indicators, including macroeconomic
statistics, Doing Business indicators, investment climate indicators, governance and
anticorruption indicators, and Country Policy and Institutional Assessment ratings are
provided for 2010.
Data consistency, reliability,
and comparability
Considerable effort has been made to harmonize the data, but full comparability cannot be
assured, and care must be taken in interpreting
indicators. Many factors affect data availability, comparability, and reliability. Data coverage
may be incomplete because of circumstances
affecting the collection and reporting of data,
such as conflicts. Although drawn from sources thought to be the most authoritative, data
should be construed as indicating trends and
characterizing differences across economies.
Discrepancies in data presented in earlier editions of Africa Development Indicators reflect
updates from countries as well as revisions to
historical series and changes in methodology.
Readers are therefore advised not to compare
data series between editions or across World
Bank publications.
Classification of economies
For operational and analytical purposes the
World Bank’s main criterion for classifying
economies is gross national income (GNI)
per capita (calculated by the World Bank Atlas
method; box 1). Every economy is classified
as low income, middle income (subdivided
into lower middle and upper middle), or high
income (table 1). Low- and middle-income
economies are sometimes referred to as developing economies. The term is used for
convenience; it is not intended to imply that
all economies in the group are experiencing
similar development or that other economies
have reached a preferred or final stage of development. Classification by income does not
necessarily reflect development status. Because GNI per capita changes over time, the
Indicator tables
3
Box 1
The World Bank Atlas method for converting gross national income to a common denominator
In calculating GNI and GNI per capita in
U.S. dollars for certain operational purposes, the World Bank Atlas conversion
factor is used to reduce the impact of exchange rate fluctuations in cross-country
comparison of national incomes. The World
Bank Atlas conversion factor for any year is
the average of the official exchange rate or
alternative conversion factor for that year
and the two preceding, adjusted for the difference between the rate of inflation in the
country and that in Japan, the United Kingdom, the United States, and the euro area.
A country’s inflation rate is measured by the
change in its GDP deflator.
The inflation rate for Japan, the United
Kingdom, the United States, and the euro
area, representing international inflation,
is measured by the change in the “special
drawing rights (SDR) deflator.” The SDR is
the International Monetary Fund’s unit of
account and is calculated as a weighted
average of these countries’ GDP deflators
in SDR terms, the weights being the amount
of each country’s currency in one SDR unit.
Weights vary over time because both the
composition of the SDR and the relative exchange rates for each currency change. The
SDR deflator is calculated in SDR terms first
and then converted to U.S. dollars using the
SDR-to-dollar World Bank Atlas conversion
factor. The conversion factor is then applied
to a country’s GNI. The resulting GNI in U.S.
dollars is divided by the midyear population
for the latest of the three years to derive GNI
per capita.
When official exchange rates are deemed
unreliable or unrepresentative of the effective exchange rate during a period, an alternative estimate of the exchange rate is used
in the World Bank Atlas formula below.
The following formulas describe the procedures for computing the conversion factor for year t:
country composition of income groups may
change from one edition of Africa Development
Indicators to the next. Once the classification is
fixed for an edition, based on GNI per capita in
the most recent year for which data are available (2008 in this edition), all historical data
are based on the same country grouping. Lowincome economies are those with a GNI per
capita of $995 or less in 2008. Middle-income
economies are those with a GNI per capita of
more than $995 but less than $12,126. Lower
middle-income and upper middle-income
economies are separated at a GNI per capita
of $3,945. High-income economies are those
with a GNI per capita of $12,126 or more.
Alternative conversion factors
The World Bank systematically assesses the
appropriateness of official exchange rates as
conversion factors. An alternative conversion
factor is used when the official exchange rate
is judged to diverge by an exceptionally large
margin from the rate effectively applied to domestic transactions of foreign currencies and
traded products. This applies to only a small
number of countries. Alternative conversion
factors are used in the Atlas methodology
4
Africa Development Indicators 2011
and for calculating per capita GNI in U.S.
dollars for year t:
where et* is the World Bank Atlas conversion factor (national currency to the U.S.
dollar) for year t, et is the average annual
exchange rate (national currency to the U.S.
dollar) for year t, pt is the GDP deflator for
year t, ptS$ is the SDR deflator in U.S. dollar
terms for year t, Yt$ is current GNI per capita
in U.S. dollars in year t, Yt is current GNI
(local currency) for year t, and Nt is midyear
population for year t.
and elsewhere in Africa Development Indicators as single-year conversion factors.
Symbols
..
means that data are not available
or that aggregates cannot be calculated because of missing data in
the years shown.
$
means current U.S. dollars unless
otherwise noted.
<
means less than
>
means greater than
0 or 0.0 means zero or small enough that
the number would round to zero
at the displayed number of decimal
places.
Data presentation conventions
A blank means not applicable or, for an aggregate, not analytically meaningful.
A billion is 1,000 million.
Growth rates are in real terms, unless
other wise specified.
The cutoff date for data is May 2011.
However, the database may have more
recent data by the time of publication.
Table 1
World Bank classification of economies, 2009 (GNI per capita)
Low income
Lower middle income
Upper middle income
High income
$995 or less
$996–$3,945
$3,946–$12,195
$12,196 or more
Benin
Burkina Faso
Burundi
Central African Republic
Chad
Comoros
Congo, Dem. Rep.
Côte d’Ivoire
Eritrea
Ethiopia
Gambia, The
Ghana
Guinea
Guinea-Bissau
Kenya
Liberia
Madagascar
Malawi
Mali
Mauritania
Mozambique
Niger
Nigeria
Rwanda
São Tomé and Príncipe
Senegal
Sierra Leone
Somalia
Tanzania
Togo
Uganda
Zambia
Zimbabwe
Algeria
Angola
Cameroon
Cape Verde
Congo, Rep.
Djibouti
Egypt, Arab Rep.
Lesotho
Morocco
Namibia
Sudan
Swaziland
Tunisia
Botswana
Gabon
Libya
Mauritius
Seychelles
South Africa
Equatorial Guinea
Source: World Bank.
Indicator tables
5
Table
Participating in growth
1.1
Basic indicators
GDP per capita
Adult
GNI
Net official
literacy rate development
Population per capita, Constant 2000 prices
Life
Under-five
(%
ages
15
Land area density
World Bank
Average expectancy mortality
assistance
and older)
at birth
rate
Gini
Total
Growth (thousands (people Atlas method
annual
per capita
(millions) (annual %) of sq km) per sq km) (current $)
$
growth (%) (years) (per 1,000) index
Male Female (current $)
a
b
2000–09
2009
2009
2000–09 2009 2009
2009
2009
2009
2009
2009
2009
2009
Population
SUB–SAHARAN AFRICA 841.0
Excluding South Africa
791.6
Excl. S. Africa & Nigeria 636.9
Angola
18.5
Benin
8.9
Botswana
1.9
Burkina Faso
15.8
Burundi
8.3
Cameroon
19.5
Cape Verde
0.5
Central African Republic
4.4
Chad
11.2
Comoros
0.7
Congo, Dem. Rep.
66.0
Congo, Rep.
3.7
Côte d’Ivoire
21.1
Djibouti
0.9
Equatorial Guinea
0.7
Eritrea
5.1
Ethiopia
82.8
Gabon
1.5
Gambia, The
1.7
Ghana
23.8
Guinea
10.1
Guinea-Bissau
1.6
Kenya
39.8
Lesotho
2.1
Liberia
4.0
Madagascar
19.6
Malawi
15.3
Mali
13.0
Mauritania
3.3
Mauritius
1.3
Mozambique
22.9
Namibia
2.2
Niger
15.3
Nigeria
154.7
Rwanda
10.0
São Tomé and Príncipe
0.2
Senegal
12.5
Seychelles
0.1
Sierra Leone
5.7
Somalia
9.1
South Africa
49.3
Sudan
42.3
Swaziland
1.2
Tanzania
43.7
Togo
6.6
Uganda
32.7
Zambia
12.9
Zimbabwe
12.5
NORTH AFRICA
166.7
Algeria
34.9
Egypt, Arab Rep.
83.0
Libya
6.4
Morocco
32.0
Tunisia
10.4
ALL AFRICA
1,007.7
2.5
2.6
2.6
2.6
3.1
1.5
3.4
2.8
2.2
1.4
1.9
2.6
2.4
2.7
1.9
2.3
1.7
2.6
2.9
2.6
1.8
2.7
2.1
2.4
2.2
2.6
0.8
4.2
2.7
2.8
2.4
2.3
0.5
2.3
1.9
3.9
2.3
2.8
1.6
2.6
1.2
2.4
2.3
1.1
2.2
1.5
2.9
2.4
3.3
2.5
0.5
1.6
1.5
1.8
2.0
1.2
1.0
2.3
23,636
22,422
21,511
1,247
111
567
274
26
473
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
1,031
2
786
823
1,267
911
25
1
193
0
72
627
1,214
2,376
17
886
54
197
743
387
5,738
2,382
995
1,760
446
155
29,375
35.6
35.3
29.6
14.8
80.8
3.4
57.6
323.3
41.3
125.5
7.1
8.9
354.2
29.1
10.8
66.3
37.3
24.1
50.2
82.8
5.7
170.5
104.8
41.0
57.3
69.9
68.1
41.1
33.7
162.2
10.7
3.2
628.2
29.1
2.6
12.1
169.9
405.3
169.5
65.1
191.2
79.5
14.6
40.6
17.8
68.9
49.4
121.7
166.0
17.4
32.4
29.1
14.7
83.4
3.6
71.7
67.2
34.3
1,130
844
757
3,750
750
6,260
510
150
1,190
3,010
450
600
810
160
2,080
1,070
1,280
12,420
320
330
7,370
440
1,190
370
510
760
980
160
430
290
680
990
7,250
440
4,270
340
1,190
490
1,130
1,040
8,480
340
..
5,760
1,220
2,470
490
440
460
960
360
3,280
4,420
2,070
12,020
2,810
3,720
1,487
618
428
408
1,313
363
4,082
264
112
694
1,763
233
265
367
97
1,267
536
904
8,011
133
201
4,054
382
343
400
143
452
471
148
255
168
304
462
4,917
371
2,673
173
506
334
..
534
7,389
265
..
3,689
537
1,553
426
247
366
401
288
2,191
2,190
1,836
7,692
1,809
2,805
879
2.6
3.1
2.8
9.9
0.6
3.0
1.9
0.2
1.0
4.8
–1.0
6.7
–0.3
2.1
1.8
–1.3
2.1
13.6
–3.4
5.7
0.1
2.1
3.5
1.0
–1.4
1.7
2.1
–3.5
0.8
1.9
2.8
2.0
2.9
5.2
3.3
0.5
4.0
5.1
..
1.6
0.9
5.8
..
2.8
5.0
1.6
4.2
–0.1
4.3
3.0
–7.4
3.1
2.5
3.0
3.3
3.8
3.9
2.6
52.5
52.6
53.6
47.6
61.8
55.0
53.3
50.9
51.4
71.3
47.3
48.9
65.8
47.8
53.7
58.0
55.7
50.6
59.9
55.7
60.9
56.2
56.8
58.3
48.2
54.9
45.4
58.7
60.8
53.8
48.8
57.0
72.6
48.1
61.6
52.0
48.1
50.6
65.8
55.9
73.7
47.9
50.1
51.6
58.5
46.3
56.3
62.9
53.4
46.3
45.4
71.5
72.6
70.3
74.5
71.6
74.5
55.6
130
132
131
161
118
57
166
166
154
28
171
209
104
199
128
119
94
145
55
104
69
103
69
142
193
84
84
112
58
110
191
117
17
142
48
160
138
111
78
93
12
192
180
62
108
73
108
98
128
141
90
26
32
21
19
38
21
119
58.6
38.6
..
39.6
33.3
44.6
50.4
43.6
39.8
64.3
44.4
47.3
41.5
39.9
..
..
29.8
41.5
47.3
42.8
39.4
35.5
47.7
52.5
38.2
47.2
39.0
39.0
39.0
..
45.6
..
34.0
42.9
53.1
50.6
39.2
65.8
42.5
..
57.8
..
50.7
37.6
34.4
44.3
50.7
..
..
32.1
..
40.9
40.8
74.8
74.8
..
82.9
54.2
83.8
..
72.6
..
90.1
69.1
44.5
79.7
79.5
..
64.7
..
97.0
77.9
..
91.4
57.6
72.8
50.8
66.9
90.5
82.9
63.7
..
80.6
..
64.5
90.6
70.1
88.9
..
72.0
75.0
93.7
61.8
..
52.7
..
..
79.6
87.8
79.0
..
..
80.6
94.7
..
..
..
95.2
68.9
..
..
56.3
56.3
..
57.6
29.1
84.4
..
60.9
..
80.2
42.1
23.1
68.7
54.9
..
45.3
..
89.8
56.0
..
84.1
35.8
60.4
28.1
38.0
83.5
95.3
54.5
..
67.0
..
50.3
85.3
41.5
88.1
..
49.8
66.8
84.0
38.7
..
30.1
..
..
60.8
86.2
66.9
..
..
61.3
89.4
..
..
..
82.0
43.9
..
..
53.2
55.1
65.9
12.9
76.4
143.4
68.8
66.1
33.3
387.5
53.6
50.1
76.8
35.6
76.8
112.3
187.7
46.7
28.5
46.1
52.6
75.1
66.4
21.3
90.3
44.7
59.5
127.7
22.7
50.6
75.7
87.1
122.0
87.9
150.2
30.7
10.7
93.5
188.7
81.2
263.7
76.8
72.4
21.8
54.1
48.9
67.1
75.4
54.6
98.1
58.8
17.2
9.1
11.1
6.1
28.5
45.4
47.2
a. Provisional.
b. Data are for the most recent year available during the period specified.
Basic indicators
Part I. Basic indicators and national and fiscal accounts
7
Table
2.1
Gross domestic product, nominal
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 Príncipe
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
2003
272,131
193,303
124,769
..
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
1,137
3,526
2,169
2,509
64,202
1,163
..
3,503
147
1,101
604
80,710
7,617
543
..
1,136
1,245
3,884
6,679
111,546
42,345
22,912
..
18,821
8,743
386,556
300,900
189,013
160,605
10,260
1,845
3,792
3,101
1,132
11,152
339
1,488
1,739
250
9,350
2,799
10,796
452
132
..
12,083
5,952
317
5,886
2,667
244
8,591
541
384
3,081
1,881
2,421
1,020
2,653
2,463
2,350
2,481
28,472
2,584
..
5,717
369
650
917
112,014
12,409
1,115
4,259
1,628
4,304
3,288
8,784
172,192
62,045
43,130
28,905
25,821
12,291
472,997
448,082
279,985
212,189
13,956
3,558
8,087
4,270
595
13,622
797
1,139
2,737
324
5,673
3,496
13,737
622
2,952
771
8,539
6,055
367
7,624
3,446
475
14,904
947
410
5,474
2,425
4,362
1,285
5,610
4,666
4,934
2,731
67,656
1,846
98
6,871
706
991
..
168,219
17,780
1,796
11,659
1,759
6,337
4,374
5,658
249,820
68,019
82,924
24,063
49,823
24,992
697,735
Current prices
($ millions)
2004
2005
559,094
340,092
252,030
19,775
4,047
10,049
5,109
664
15,775
925
1,270
4,415
362
6,570
4,649
15,481
666
5,241
939
10,034
7,178
401
8,872
3,666
535
16,096
1,206
460
4,364
2,625
4,874
1,548
6,386
5,698
6,606
3,053
87,845
2,089
107
8,041
700
1,096
..
219,093
21,684
2,282
12,826
2,061
8,469
5,423
5,671
282,321
85,014
78,845
33,385
56,948
28,129
841,140
2006
2007
2008
Annual average growth (%)
1980–89 1990–99 2000–09
2009a
653,676 763,395
879,541 1,009,865 954,357
406,780 502,768
593,774 734,377
669,740
294,213 355,441
427,372 526,649 496,310
30,632
45,163
59,263
84,179
75,493
4,287
4,735
5,546
6,683
6,656
10,255
11,255
12,386
13,545
11,823
5,427
5,771
6,767
8,046
8,141
796
919
980
1,169
1,325
16,588
17,957
20,686
23,736
22,186
999
1,108
1,331
1,531
1,549
1,350
1,477
1,712
1,988
2,006
5,302
6,099
7,016
8,357
6,839
387
403
465
530
535
7,104
8,543
9,977
11,588
10,575
6,087
7,731
8,344
11,789
9,580
16,363
17,367
19,796
23,414
23,304
709
769
848
983
1,049
8,217
9,603
12,576
18,525
10,413
1,171
1,281
1,374
1,654
1,873
12,286
15,134
19,182
25,899
28,526
8,666
9,546
11,571
14,535
11,062
461
508
651
822
733
10,720
20,388
24,632
28,527
26,169
2,937
2,821
4,209
3,778
4,103
590
597
692
847
837
18,738
22,502
27,166
30,031
29,376
1,315
1,417
1,577
1,594
1,579
530
612
735
843
876
5,039
5,515
7,343
9,424
8,590
2,755
3,117
3,458
4,074
4,727
5,305
5,866
7,146
8,722
8,996
1,858
2,699
2,838
3,589
3,024
6,284
6,507
7,521
9,310
8,589
6,579
7,096
8,030
9,867
9,790
7,262
7,981
8,806
8,970
9,265
3,405
3,645
4,246
5,357
5,383
112,249 146,867
165,921
207,118 173,004
2,581
3,111
3,741
4,691
5,216
114
125
145
174
191
8,703
9,378
11,334
13,175
12,822
884
968
1,026
926
764
1,239
1,422
1,664
1,955
1,942
..
..
..
..
..
247,064 261,007
286,302 276,451 285,366
27,386
36,401
46,531
58,032
54,681
2,524
2,670
2,950
2,840
3,001
14,142
14,331
16,826
20,715
21,368
2,108
2,218
2,499
2,899
2,855
9,000
9,922
11,892
14,441
16,043
7,157
10,675
11,410
14,382
12,805
5,583
5,203
5,018
4,247
5,625
324,517 377,737
448,926 556,721 522,285
102,339
117,169
135,804 170,989
140,577
89,686
107,484
130,473 162,836
188,413
44,000
56,484
71,803
93,168
62,360
59,524
65,637
75,226
88,883
91,375
28,968
30,962
35,620
40,845
39,561
977,859 1,140,739 1,328,046 1,566,195 1,476,265
1.0
–0.7
3.0
..
2.3
12.6
4.8
2.2
7.3
..
8.1
5.7
8.0
–6.2
2.3
2.0
..
..
..
5.9
–0.5
1.7
3.2
..
3.7
2.6
–0.8
–0.5
–5.2
1.8
3.4
3.5
8.8
–4.7
0.1
–0.2
–12.0
8.6
..
6.2
9.3
–4.3
6.4
4.1
10.1
1.9
..
4.5
20.7
–3.1
–0.1
4.8
4.5
6.8
..
3.7
2.3
2.2
1.5
1.2
0.8
–3.8
3.5
4.6
0.0
–3.3
–2.5
6.4
–4.3
–1.3
–2.0
–7.1
–2.4
2.2
1.7
22.5
7.2
–5.7
–1.7
3.6
2.6
3.0
–0.6
7.7
4.1
1.8
3.4
0.2
0.4
1.4
5.8
8.3
4.6
–1.8
3.2
–2.0
..
–1.8
6.0
0.6
..
2.1
0.8
4.4
10.1
–0.1
8.8
0.2
–1.5
4.2
–1.2
10.8
–0.9
5.1
6.0
2.5
15.2
16.7
15.7
32.9
13.8
10.8
14.4
8.4
11.2
14.1
9.5
23.2
12.0
12.0
18.2
10.4
7.6
34.1
13.7
16.9
13.4
8.6
25.0
3.2
19.4
11.8
11.8
6.1
9.5
10.9
16.3
15.9
8.5
11.8
13.3
13.8
19.9
15.0
11.5
13.4
4.9
13.1
..
12.2
21.2
11.3
9.1
10.0
12.6
20.3
–3.6
11.2
14.6
7.7
15.0
11.6
9.3
13.7
a. Provisional.
8
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.2
Gross domestic product, real
1980
SUB–SAHARAN AFRICA 227,433
Excluding South Africa
132,121
Excl. S. Africa & Nigeria
99,187
Angola
..
Benin
1,084
Botswana
1,209
Burkina Faso
1,101
Burundi
559
Cameroon
6,339
Cape Verde
..
Central African Republic
735
Chad
665
Comoros
136
Congo, Dem. Rep.
7,016
Congo, Rep.
1,746
Côte d’Ivoire
7,727
Djibouti
..
Equatorial Guinea
..
Eritrea
..
Ethiopia
..
Gabon
3,594
Gambia, The
213
Ghana
2,640
Guinea
..
Guinea-Bissau
115
Kenya
7,078
Lesotho
380
Liberia
1,391
Madagascar
3,099
Malawi
1,000
Mali
1,536
Mauritania
693
Mauritius
1,519
Mozambique
2,462
Namibia
2,292
Niger
1,523
Nigeria
31,452
Rwanda
1,368
São Tomé and Príncipe
..
Senegal
2,683
Seychelles
292
Sierra Leone
929
Somalia
..
South Africa
95,503
Sudan
5,525
Swaziland
470
Tanzania
..
Togo
964
Uganda
..
Zambia
2,730
Zimbabwe
3,699
NORTH AFRICA
118,981
Algeria
35,291
Egypt, Arab Rep.
38,506
Libya
..
Morocco
20,086
Tunisia
8,622
ALL AFRICA
348,882
1990
2003
273,288
162,355
127,336
8,464
1,412
3,395
1,556
865
8,793
303
815
1,106
181
7,659
2,796
8,298
660
207
..
6,234
4,298
305
3,267
2,088
186
10,544
504
433
3,266
1,243
1,630
816
2,726
2,499
2,591
1,507
34,978
1,673
..
3,463
395
1,014
..
110,945
7,062
1,033
7,547
1,071
3,215
3,028
5,691
178,165
46,367
65,579
..
29,312
12,237
452,854
383,153
237,556
184,367
11,137
2,571
6,751
3,150
747
11,393
613
884
1,925
223
4,614
3,524
10,106
596
2,764
692
8,798
5,290
460
5,691
3,503
195
13,631
819
411
3,941
1,778
3,039
1,188
4,975
5,485
4,320
2,089
53,102
2,135
..
5,268
572
1,047
..
145,693
14,821
1,592
12,367
1,419
7,542
3,687
5,069
273,922
62,918
109,198
36,180
43,735
21,891
657,068
Constant prices
(2000 $ millions)
2004
2005
2006
407,008
254,798
195,958
12,383
2,650
7,154
3,296
783
11,815
608
892
2,572
222
4,921
3,647
10,287
619
3,815
702
9,993
5,361
493
6,010
3,585
201
14,327
838
422
4,148
1,875
3,105
1,249
5,261
5,918
4,850
2,091
58,731
2,293
..
5,579
556
1,125
..
152,329
15,579
1,632
13,335
1,461
8,055
3,886
4,720
286,676
66,190
113,666
37,771
45,835
23,213
693,666
430,323
270,086
208,072
14,935
2,727
7,271
3,505
790
12,087
681
914
3,018
232
5,239
3,932
10,417
638
4,187
720
11,174
5,523
518
6,364
3,692
211
15,173
847
444
4,339
1,924
3,294
1,317
5,327
6,414
4,972
2,185
61,903
2,507
..
5,893
598
1,206
..
160,367
16,564
1,668
14,318
1,479
8,565
4,089
4,431
301,162
69,565
118,749
41,511
47,201
24,136
731,462
457,294
288,086
222,229
17,707
2,839
7,643
3,698
830
12,476
750
949
3,024
234
5,505
4,173
10,488
669
4,239
713
12,384
5,588
552
6,771
3,784
215
16,132
902
479
4,557
2,072
3,469
1,573
5,537
6,971
5,324
2,312
65,740
2,737
..
6,042
647
1,294
..
169,354
18,434
1,715
15,282
1,537
9,489
4,342
4,284
318,159
70,956
126,876
43,960
50,863
25,503
775,424
2007
2008
2009a
486,811
308,333
238,231
21,298
2,970
8,010
3,831
860
12,913
815
984
3,030
236
5,849
4,107
10,668
703
5,148
722
13,803
5,899
587
7,209
3,851
216
17,263
924
524
4,842
2,192
3,618
1,483
5,842
7,478
5,610
2,388
69,981
2,888
..
6,335
710
1,377
..
178,644
20,308
1,776
16,375
1,566
10,287
4,611
4,127
334,909
73,085
135,869
46,598
52,240
27,118
821,680
511,548
326,524
252,216
24,136
3,121
8,260
4,023
899
13,287
867
1,005
3,018
238
6,212
4,335
10,904
744
5,730
652
15,291
6,035
623
7,817
4,041
224
17,531
965
561
5,187
2,381
3,795
1,537
6,140
7,982
5,851
2,615
74,179
3,211
..
6,546
704
1,454
..
185,216
21,697
1,818
17,593
1,594
11,183
4,880
3,415
352,333
74,839
145,592
48,368
55,158
28,376
863,841
520,086
338,402
259,922
24,295
3,240
7,959
4,164
930
13,553
891
1,029
2,970
242
6,379
4,665
11,296
781
5,418
675
16,623
5,978
651
8,181
4,030
230
17,985
973
587
4,997
2,562
3,958
1,521
6,271
8,488
5,804
2,641
78,333
3,343
..
6,691
650
1,512
..
181,923
22,678
1,840
18,652
1,634
11,973
5,192
3,609
365,307
76,411
152,360
49,384
57,888
29,265
885,368
Annual average growth (%)
1980–89 1990–99 2000–09
1.8
2.1
2.6
..
2.7
10.9
4.0
4.5
4.5
6.3
1.6
6.7
2.9
2.1
3.8
0.7
..
..
..
2.1
0.5
3.5
2.6
..
3.8
4.1
2.3
–3.3
0.8
2.4
0.5
1.9
6.1
–0.9
1.1
–0.4
0.8
2.5
..
2.7
3.1
0.5
..
1.4
2.4
7.4
..
1.5
2.3
1.0
3.3
4.2
2.9
5.5
..
4.2
3.2
2.6
2.4
2.7
2.8
1.0
4.7
4.8
5.5
–3.2
1.3
5.9
1.8
2.3
1.2
–5.0
0.8
3.5
–2.3
20.7
7.9
3.7
2.9
2.7
4.3
4.4
1.4
2.2
4.0
0.2
1.7
3.8
3.9
2.9
5.0
6.0
4.0
2.4
2.4
–1.6
..
2.8
4.5
–5.3
..
2.0
5.4
3.1
2.8
3.6
7.4
0.2
2.7
3.2
1.7
4.3
..
2.4
4.6
2.7
5.1
5.8
5.5
13.1
4.0
4.4
5.4
3.0
3.3
6.4
0.8
10.2
1.9
5.2
4.0
0.8
4.0
16.8
0.2
8.5
2.1
5.2
5.8
3.0
1.0
4.4
3.1
0.0
3.6
4.8
5.3
4.7
3.7
7.9
5.3
4.3
6.6
7.6
..
4.3
1.7
9.5
..
4.1
7.3
2.6
7.1
2.5
7.8
5.4
–7.5
4.8
4.0
4.9
5.4
5.0
4.9
5.0
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
9
Table
2.3
Gross domestic product growth
Annual growth
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
4.0
1.7
0.7
..
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
–10.1
..
..
–2.2
4.2
9.0
..
–3.3
–4.2
4.8
..
6.6
1.5
12.4
..
14.6
..
3.0
14.4
5.2
0.8
10.0
..
3.6
7.4
4.4
1.1
2.1
0.6
–0.3
3.2
6.8
–0.6
3.5
–6.1
0.7
–2.1
–4.2
5.1
–6.6
1.0
–1.1
..
3.3
..
2.7
5.2
3.6
3.3
4.3
6.1
4.2
6.5
–51.0
3.1
5.7
–1.9
–1.8
7.2
1.0
2.5
–1.3
8.2
–2.4
..
–0.7
7.0
3.4
..
–0.3
–5.5
9.8
7.0
–0.2
6.5
–0.5
7.0
4.0
0.8
5.7
..
4.0
7.9
2.2
4.2
5.0
3.5
3.3
3.9
6.3
8.0
–1.2
4.0
6.2
–7.6
14.7
2.5
5.8
0.8
–1.6
3.2
14.0
–2.7
–2.2
2.5
6.9
5.2
5.4
–2.9
2.9
4.3
–31.3
9.8
5.5
7.4
5.6
3.7
6.0
4.2
5.3
10.3
2.2
..
6.7
–5.9
9.3
..
2.9
7.1
3.9
6.9
2.7
6.5
5.1
–17.2
5.9
6.9
3.2
13.0
6.3
5.6
4.9
6.2
7.3
6.3
11.2
3.1
6.0
4.6
4.8
3.7
–0.7
1.0
33.6
–0.2
6.6
3.5
1.8
3.8
38.0
1.5
13.6
1.3
7.1
5.6
2.3
3.1
5.1
2.3
2.6
5.3
5.5
2.2
5.2
5.7
7.9
12.3
0.1
10.6
7.4
..
5.9
–2.9
7.5
..
4.6
5.1
2.5
7.8
3.0
6.8
5.4
–6.9
4.7
5.2
4.1
4.4
4.8
6.0
5.6
5.7
6.0
6.2
20.6
2.9
1.6
6.4
0.9
2.3
11.9
2.4
17.3
4.2
6.5
7.8
1.3
3.2
9.7
2.6
11.8
3.0
5.1
5.9
3.0
5.0
5.9
1.1
5.3
4.6
2.6
6.1
5.4
1.2
8.4
2.5
4.5
5.4
9.3
..
5.6
7.5
7.2
..
5.3
6.3
2.2
7.4
1.2
6.3
5.2
–6.1
5.1
5.1
4.5
9.9
3.0
4.0
5.4
6.3
6.7
6.8
18.6
4.1
5.1
5.5
5.1
3.2
10.1
3.8
0.2
1.2
5.1
6.1
0.7
4.8
1.3
–1.0
10.8
1.2
6.6
6.4
2.5
2.2
6.3
6.5
7.8
5.0
7.7
5.3
19.4
3.9
8.7
7.1
5.8
6.2
9.2
..
2.5
8.3
7.3
..
5.6
11.3
2.9
6.7
3.9
10.8
6.2
–3.3
5.6
2.0
6.8
5.9
7.8
5.7
6.0
6.5
7.0
7.2
20.3
4.6
4.8
3.6
3.6
3.5
8.6
3.7
0.2
0.5
6.3
–1.6
1.7
5.1
21.4
1.3
11.5
5.6
6.3
6.5
1.8
0.3
7.0
2.4
9.4
6.2
5.8
4.3
–5.7
5.5
7.3
5.4
3.3
6.4
5.5
..
4.9
9.7
6.4
..
5.5
10.2
3.5
7.1
1.9
8.4
6.2
–3.7
5.3
3.0
7.1
6.0
2.7
6.3
6.0
5.1
5.9
5.9
13.3
5.1
3.1
5.0
4.5
2.9
6.5
2.2
–0.4
1.0
6.2
5.6
2.2
5.8
11.3
–9.8
10.8
2.3
6.1
8.4
4.9
3.5
1.6
4.5
7.1
7.1
8.6
4.9
3.7
5.1
6.7
4.3
9.5
6.0
11.2
..
3.3
–0.9
5.5
..
3.7
6.8
2.4
7.4
1.8
8.7
5.8
–17.3
5.2
2.4
7.2
3.8
5.6
4.6
5.1
2009a
1.7
3.6
3.1
0.7
3.8
–3.7
3.5
3.5
2.0
2.8
2.4
–1.6
1.8
2.7
7.6
3.6
5.0
–5.4
3.6
8.7
–1.0
4.6
4.7
–0.3
3.0
2.6
0.9
4.6
–3.7
7.6
4.3
–1.1
2.1
6.3
–0.8
1.0
5.6
4.1
..
2.2
–7.6
4.0
..
–1.8
4.5
1.2
6.0
2.5
7.1
6.4
5.7
3.7
2.1
4.6
2.1
4.9
3.1
2.5
Annual average
1980–89 1990–99 2000–09
2.2
2.1
2.5
4.2
3.1
11.5
3.7
4.3
4.0
6.4
0.9
5.4
2.7
1.8
6.8
–0.2
..
0.9
..
2.4
1.9
3.9
2.0
4.5
2.9
4.2
2.1
–4.5
0.4
1.7
0.6
2.2
4.3
0.4
1.1
0.0
0.9
3.2
..
2.4
2.1
1.1
..
2.2
3.4
8.6
3.8
2.6
3.0
1.4
5.2
4.3
2.8
5.9
..
3.9
3.6
2.9
2.1
2.5
2.4
1.0
4.5
5.3
5.1
–1.4
0.4
5.2
1.3
2.2
1.6
–5.5
0.8
2.6
–2.0
20.2
8.1
2.7
2.5
3.1
4.3
4.3
2.0
2.2
4.1
1.2
1.6
4.1
3.6
2.6
5.2
5.5
4.1
1.9
3.1
2.1
..
2.7
4.9
–4.3
..
1.4
4.4
3.7
3.3
2.6
7.1
0.4
2.6
3.3
1.6
4.3
..
2.8
5.1
2.5
4.6
5.2
5.0
10.9
4.3
4.2
5.0
2.7
3.4
6.0
1.0
8.3
2.0
3.4
4.6
0.5
3.6
18.5
–0.6
8.1
1.5
5.1
5.5
2.8
1.5
3.6
3.3
3.8
3.2
4.2
5.4
3.8
4.1
7.3
4.4
3.8
6.1
7.7
..
4.0
1.1
9.7
..
3.6
7.1
3.1
6.8
2.0
7.2
5.2
–5.9
4.5
3.6
4.9
4.3
4.8
4.7
4.6
a. Provisional.
10
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.4
Gross domestic product per capita, real
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 Príncipe
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
2003
587
367
347
..
305
1,227
160
135
698
..
324
144
405
258
962
918
..
..
..
..
5,274
346
239
..
137
435
293
728
360
161
214
454
1,573
203
2,262
257
422
263
..
476
4,532
285
..
3,463
269
780
..
346
..
473
508
1,290
1,876
867
..
1,027
1,351
727
530
338
332
794
294
2,512
177
152
719
854
278
181
416
207
1,143
658
1,178
547
..
129
4,640
340
218
340
182
450
315
200
290
132
188
410
2,579
185
1,828
191
359
234
..
460
5,645
248
..
3,152
261
1,196
297
273
181
383
544
1,480
1,834
1,135
..
1,182
1,501
712
528
350
338
712
349
3,764
245
107
670
1,325
223
206
387
83
1,081
548
767
4,796
167
124
4,020
321
272
395
139
401
419
131
237
138
270
420
4,069
277
2,233
171
396
246
..
492
6,913
221
..
3,159
399
1,437
335
249
281
329
405
1,808
1,973
1,470
6,364
1,467
2,225
749
Constant prices
(2000 $)
2004
2005
2006
547
365
350
767
348
3,941
248
109
678
1,294
222
265
378
86
1,092
546
782
6,439
163
137
3,993
333
280
397
140
411
424
131
242
141
269
430
4,266
291
2,460
166
427
260
..
508
6,740
229
..
3,264
411
1,463
351
250
290
339
378
1,862
2,045
1,501
6,509
1,520
2,337
773
564
378
362
899
347
3,954
255
107
678
1,426
223
301
386
89
1,151
541
793
6,877
161
150
4,034
340
290
400
143
424
424
133
246
141
278
441
4,284
308
2,475
167
439
279
..
522
7,209
236
..
3,398
428
1,483
367
247
298
348
355
1,925
2,117
1,539
7,009
1,548
2,407
796
585
393
377
1,036
349
4,099
260
109
684
1,547
227
293
382
91
1,197
533
816
6,779
154
162
4,004
351
302
402
143
439
448
138
252
148
286
514
4,419
326
2,599
170
456
297
..
522
7,651
246
..
3,548
466
1,509
381
250
320
361
344
2,001
2,128
1,614
7,272
1,649
2,518
825
2007
2008
2009a
608
410
394
1,213
354
4,233
260
110
692
1,657
231
285
375
94
1,157
530
843
8,017
151
176
4,148
363
315
401
140
457
455
144
260
152
292
472
4,634
342
2,686
169
474
306
..
533
8,350
254
..
3,702
502
1,542
397
249
336
375
332
2,073
2,159
1,697
7,554
1,673
2,652
854
623
423
406
1,339
360
4,300
264
111
696
1,739
232
277
370
97
1,199
530
876
8,692
132
189
4,168
375
335
411
142
452
471
148
271
160
299
478
4,839
357
2,747
178
491
330
..
536
8,092
261
..
3,796
525
1,557
414
247
353
387
274
2,147
2,177
1,786
7,685
1,745
2,748
877
618
428
408
1,313
363
4,082
264
112
694
1,763
233
265
367
97
1,267
536
904
8,011
133
201
4,054
382
343
400
143
452
471
148
255
168
304
462
4,917
371
2,673
173
506
334
..
534
7,389
265
..
3,689
537
1,553
426
247
366
401
288
2,191
2,190
1,836
7,692
1,809
2,805
879
Annual average growth (%)
1980–89 1990–99 2000–09
–0.9
–0.8
–0.2
..
–0.4
7.6
1.4
1.2
1.4
..
–1.2
3.4
0.0
–1.3
2.1
–3.2
..
..
..
..
–1.6
–0.2
–1.1
..
2.8
0.3
0.3
–6.7
–2.4
–2.4
–1.0
–0.6
4.8
–1.0
–2.2
–2.8
–2.4
–1.1
..
0.0
1.8
–1.7
..
–0.8
0.5
4.1
..
–2.3
..
–2.0
0.3
1.3
–0.1
2.6
..
1.3
0.6
–0.2
–0.6
–0.2
–0.3
–2.4
1.3
2.5
2.8
–3.4
–1.6
3.4
–0.9
–0.6
–1.1
–8.8
–1.4
–0.3
–4.7
15.2
..
–0.7
–0.9
–0.8
1.6
1.0
–1.6
–1.0
2.1
–1.9
–1.7
1.4
2.1
0.2
3.6
2.8
1.6
–1.2
0.0
–0.9
..
0.3
2.9
–5.7
..
–0.7
2.8
0.7
–0.2
–0.4
3.7
–2.5
0.1
1.3
–0.3
2.1
..
0.9
3.0
0.0
2.6
3.1
2.8
9.9
0.6
3.0
1.9
0.2
1.0
4.8
–1.0
6.7
–0.3
2.1
1.8
–1.3
2.1
13.6
–3.4
5.7
0.1
2.1
3.5
1.0
–1.4
1.7
2.1
–3.5
0.8
1.9
2.8
2.0
2.9
5.2
3.3
0.5
4.0
5.1
..
1.6
0.9
5.8
..
2.8
5.0
1.6
4.2
–0.1
4.3
3.0
–7.4
3.1
2.5
3.0
3.3
3.8
3.9
2.6
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
11
Table
2.5
Gross domestic product per capita growth
Annual growth
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
1.0
–1.3
–2.3
..
3.8
8.0
–1.4
–1.9
–4.8
..
–7.0
–8.0
..
–0.7
14.0
–15.0
..
..
..
..
–0.3
2.7
–1.9
..
–18.5
1.7
–5.2
–7.3
–1.8
–2.6
–6.0
0.5
–11.4
..
..
–5.1
1.2
5.4
..
–6.0
–5.4
2.6
–9.0
4.2
–1.7
9.1
..
11.1
..
–0.3
10.4
2.4
–2.5
7.4
..
1.0
4.6
1.4
–1.6
–0.7
–2.3
–3.1
–0.1
3.7
–3.3
0.9
–8.9
–1.5
–4.4
–7.2
2.4
–9.9
–1.8
–4.6
..
–0.1
..
–0.6
1.9
–0.5
0.5
0.6
3.6
0.7
4.9
–50.0
0.1
1.8
–3.8
–4.3
6.4
–0.3
–1.3
–4.3
5.4
–2.0
..
–3.5
6.1
2.1
–1.9
–2.3
–7.7
6.0
3.7
–3.0
2.7
–3.4
3.9
1.6
–1.7
3.2
..
2.1
5.4
–0.6
1.6
2.3
0.9
0.1
0.4
5.0
4.6
–3.9
1.6
4.4
–9.2
10.6
0.3
2.5
–1.7
–3.6
1.3
10.8
–6.7
–4.7
0.4
3.5
2.8
3.5
–5.3
0.3
3.3
–33.1
6.7
2.6
4.9
2.7
2.6
3.2
2.3
1.8
7.7
0.5
3.6
3.9
–4.9
4.8
..
1.6
5.0
3.3
4.1
0.1
3.1
2.8
–17.1
4.3
5.3
1.2
10.7
5.2
4.9
2.5
3.6
4.6
3.6
7.8
–0.3
4.7
1.2
1.8
1.3
–2.3
–0.8
29.1
–2.3
3.4
1.0
–0.3
2.0
34.2
–2.6
10.7
–0.7
3.8
3.2
0.4
0.6
2.4
1.3
–0.2
2.3
2.6
–0.2
2.4
4.8
5.1
10.2
–3.3
8.0
5.8
4.8
3.2
–2.5
3.3
..
3.3
3.0
1.9
4.9
0.4
3.4
3.1
–6.7
3.0
3.6
2.1
2.3
3.7
5.1
3.1
3.2
3.3
3.5
17.1
–0.5
0.3
2.8
–2.1
0.0
10.2
0.6
13.6
2.1
3.3
5.4
–0.9
1.4
6.8
–1.2
9.0
1.0
2.0
3.6
1.0
2.6
3.2
0.1
1.8
1.7
–0.2
3.6
2.7
0.4
5.7
0.6
0.8
2.9
7.2
3.9
2.9
7.0
3.4
..
4.1
4.1
1.4
4.4
–1.3
2.9
2.8
–6.0
3.4
3.5
2.5
7.7
1.8
3.0
3.0
3.7
4.0
4.1
15.3
0.8
3.7
2.0
2.0
0.9
8.5
1.9
–2.8
–0.9
2.1
4.0
–1.5
2.9
–1.4
–4.3
8.0
–0.7
3.5
4.1
0.4
–0.1
3.6
5.5
3.6
2.2
4.7
2.8
16.4
3.1
6.0
5.0
1.9
3.7
6.6
5.0
–0.1
6.1
3.9
..
4.4
8.9
1.8
3.8
1.3
7.2
3.7
–3.2
4.0
0.5
4.9
3.8
6.5
4.6
3.6
3.9
4.3
4.5
17.1
1.3
3.3
0.1
0.5
1.2
7.1
1.8
–2.6
–1.9
3.3
–3.4
–0.6
3.2
18.3
–1.9
8.6
3.6
3.4
4.2
–0.4
–1.9
4.2
1.5
4.7
3.4
2.9
1.9
–8.0
4.9
4.8
3.3
–0.6
4.0
2.8
4.3
2.1
9.1
3.5
..
4.3
7.7
2.2
4.1
–0.6
4.9
3.7
–3.6
3.6
1.5
5.1
3.9
1.5
5.3
3.5
2.5
3.3
3.2
10.4
1.8
1.6
1.5
1.4
0.6
5.0
0.3
–3.1
–1.4
3.3
3.7
–0.1
3.9
8.4
–12.5
7.9
0.5
3.2
6.2
2.6
1.2
–1.1
3.6
2.4
4.3
5.6
2.4
1.2
4.4
4.3
2.3
5.3
3.6
8.2
4.1
0.6
–3.1
2.9
..
2.5
4.5
1.0
4.4
–0.7
5.2
3.3
–17.3
3.5
0.9
5.2
1.7
4.3
3.6
2.7
–0.8
1.1
0.4
–1.9
0.6
–5.1
0.1
0.6
–0.3
1.4
0.5
–4.2
–0.6
0.0
5.6
1.2
3.2
–7.8
0.6
5.9
–2.7
1.8
2.5
–2.6
0.7
–0.1
0.0
0.3
–6.2
4.7
1.9
–3.3
1.6
4.0
–2.7
–2.9
3.2
1.2
2.4
–0.4
–8.7
1.5
..
–2.8
2.2
–0.3
3.0
0.0
3.6
3.8
5.2
2.1
0.6
2.8
0.1
3.7
2.1
0.2
Annual average
1980–89 1990–99 2000–09
–0.7
–0.9
–0.4
1.5
0.2
7.9
1.2
1.0
1.0
4.2
–1.6
2.6
0.1
–1.2
3.6
–4.3
..
–2.9
..
–0.8
–1.2
0.2
–1.0
1.4
0.8
0.4
–0.1
–6.2
–2.3
–2.4
–1.3
–0.5
3.3
–0.6
–2.2
–2.8
–1.8
–0.4
..
–0.5
1.2
–1.2
0.9
–0.3
0.5
4.8
0.6
–0.9
–0.5
–1.7
1.4
1.5
–0.3
3.2
..
1.4
1.0
0.0
–0.6
–0.2
–0.4
–1.9
1.1
3.2
2.2
–2.8
–2.2
3.0
–1.2
–1.0
–0.7
–8.5
–1.4
–0.7
–4.5
16.3
6.5
–0.5
–0.5
–0.7
1.5
1.0
–0.5
–0.8
2.4
–2.3
–1.4
1.8
1.6
–0.1
4.0
2.6
1.4
–1.4
0.5
1.3
..
–0.1
3.3
–4.5
–1.9
–0.8
1.8
1.2
0.2
–0.3
4.1
–2.4
0.6
1.3
–0.4
2.3
..
1.2
3.3
–0.1
2.1
2.6
2.3
7.7
0.9
2.7
1.6
0.0
1.1
4.4
–0.9
4.9
–0.2
0.4
2.4
–1.8
1.6
15.3
–4.1
5.3
–0.5
1.9
3.2
0.8
–0.9
1.0
2.2
–0.4
0.4
1.2
3.0
1.1
3.3
4.6
2.4
0.1
3.6
4.5
4.7
1.3
0.2
6.2
..
2.2
4.9
2.0
3.9
–0.6
3.8
2.7
–6.0
2.8
2.1
2.9
2.2
3.5
3.6
2.2
a. Provisional.
12
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.6
Gross national income, nominal
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 Príncipe
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
2003
261,499
186,001
120,669
..
1,402
1,028
1,924
922
5,618
..
800
1,038
124
14,102
1,544
9,680
..
..
..
..
3,856
237
4,426
..
105
7,043
695
930
4,024
1,138
1,768
672
1,113
3,550
1,818
2,476
61,079
1,165
..
3,403
142
1,071
603
77,378
7,570
..
..
1,096
1,237
3,594
6,530
103,183
41,147
21,453
..
18,402
8,450
369,585
284,576
176,977
151,469
8,214
1,806
3,686
3,094
1,117
10,674
340
1,465
1,721
249
8,579
2,324
9,209
..
124
..
12,016
5,336
291
5,774
2,518
233
8,224
902
..
2,958
1,837
2,405
1,076
2,631
2,320
2,388
2,423
25,585
2,572
..
5,520
355
580
835
107,746
11,409
1,174
4,072
1,598
4,227
3,008
8,512
159,989
59,955
42,025
..
24,835
11,882
448,242
425,226
261,709
201,604
12,230
3,515
7,368
4,269
577
13,097
781
1,137
2,279
322
5,485
2,580
13,018
673
1,392
761
8,473
5,342
336
7,459
3,201
463
14,738
1,202
350
5,394
2,385
4,203
1,343
5,580
4,469
5,163
2,718
59,996
1,816
..
6,766
663
958
..
163,610
16,428
1,754
11,601
1,736
6,219
4,231
5,439
257,561
65,319
82,816
24,603
48,783
23,957
684,475
Current prices
($ millions)
2004
2005
529,902
315,160
236,870
17,295
4,006
9,089
5,102
646
15,374
907
1,268
3,720
360
6,276
3,159
14,763
731
2,312
923
9,971
5,987
366
8,674
3,391
524
15,955
1,515
373
4,285
2,582
4,679
1,613
6,371
5,398
6,689
3,039
78,110
2,055
..
7,949
666
1,034
..
214,782
19,990
2,284
12,775
2,033
8,338
5,026
5,388
289,635
81,414
78,638
33,139
55,961
26,895
822,420
2006
2007
2008
2009a
616,553 728,169
827,908
947,512 909,888
374,531
472,616
551,831
680,851 631,533
275,384 330,873
397,306
485,559 468,215
26,601
39,679
50,485
69,675
67,478
4,259
4,623
5,428
6,672
6,646
9,420
10,482
11,647
12,843
11,341
5,411
5,756
6,752
7,932
8,019
776
910
974
1,165
1,331
16,126
17,706
20,608
23,407
22,059
966
1,063
1,305
1,484
1,499
1,348
1,473
1,702
1,966
1,983
4,277
4,888
5,817
6,687
6,124
386
404
467
530
535
6,760
8,143
9,621
10,266
9,831
4,039
5,105
5,747
8,728
6,869
15,643
16,589
18,911
22,438
22,406
776
854
936
1,073
1,120
4,173
5,163
6,674
11,868
6,715
1,162
1,272
1,365
1,642
1,856
12,250
15,095
19,196
25,931
28,489
7,708
7,902
10,044
12,364
9,549
418
460
597
776
690
10,590
20,261
24,494
28,268
25,871
2,658
2,496
3,819
3,321
3,692
579
588
681
834
826
18,732
22,540
27,208
30,134
29,311
1,619
1,797
1,995
2,014
1,934
417
444
560
673
645
4,960
5,435
7,288
9,372
8,498
2,714
3,078
3,437
4,051
4,656
5,099
5,524
7,146
8,722
8,996
1,922
2,334
2,828
3,619
3,041
6,276
6,559
7,746
9,482
8,874
6,219
6,472
7,445
9,239
9,696
7,149
7,928
8,629
8,752
9,174
3,397
3,645
4,246
5,338
5,281
98,881
141,275
154,068
194,690 162,901
2,554
3,083
3,724
4,656
5,179
111
127
151
178
194
8,546
9,290
11,238
13,127
12,778
844
924
954
823
655
1,176
1,364
1,629
1,916
1,901
..
..
..
..
..
242,122 255,872
276,534
267,509 279,023
25,397
33,503
41,985
52,236
49,255
2,702
2,684
2,991
2,833
2,874
14,114
14,331
16,839
20,731
21,385
2,073
2,180
2,478
2,892
2,850
8,771
9,679
11,664
14,161
15,711
6,761
9,506
10,026
12,982
11,444
5,308
4,890
4,654
3,879
5,213
332,058 390,836
469,628
580,537 542,401
97,259 112,669
134,004
169,689 139,577
89,432 108,015
131,650
164,196 188,575
43,719
57,559
74,070
93,533
61,985
58,760
64,703
74,246
87,411
89,489
27,309
29,553
33,625
38,471
37,328
952,088 1,123,145 1,301,612 1,531,638 1,456,113
Annual average growth (%)
1980–89 1990–99 2000–09
0.9
–1.0
2.8
..
2.1
10.8
4.8
1.9
9.0
..
7.8
5.5
7.9
–6.8
1.9
1.3
..
..
..
5.8
–0.1
1.6
2.9
..
3.4
2.6
–0.2
–3.2
–6.0
2.2
2.8
4.8
9.1
–5.6
0.2
0.1
–12.5
8.5
..
6.1
8.9
–4.8
5.5
4.2
9.7
..
..
4.6
20.7
–4.1
–0.2
4.9
4.5
7.5
..
3.3
2.0
2.1
1.8
1.5
1.1
–2.4
3.7
4.2
0.0
–3.3
–2.4
6.2
–4.3
–1.2
–2.0
–7.0
–5.2
3.3
1.3
16.9
7.3
–5.8
–1.9
3.7
2.6
3.3
–0.7
8.3
1.5
..
3.8
0.2
0.1
1.8
5.7
8.6
4.5
–1.7
3.7
–2.0
..
–1.6
5.9
1.5
..
2.2
1.9
4.5
10.6
–0.1
9.1
0.7
–1.7
5.4
–1.3
11.2
..
5.3
6.0
3.0
15.1
16.7
15.4
33.5
13.8
11.0
14.2
8.5
12.0
13.8
9.5
20.7
12.0
12.0
18.1
10.7
8.4
35.3
13.7
17.0
13.2
8.5
25.3
1.9
20.2
12.0
11.5
6.3
9.6
11.1
17.0
15.3
8.9
11.9
12.8
13.8
20.8
15.1
..
13.6
4.0
13.3
..
12.2
20.9
10.7
9.3
10.2
12.5
19.2
–4.0
11.8
15.1
7.6
22.8
11.7
9.1
13.9
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
13
Table
2.7
Gross national income,
World Bank Atlas method
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 Príncipe
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
2003
248,179
183,411
122,461
..
1,433
860
2,016
897
4,613
..
785
929
..
14,859
1,471
9,319
..
..
..
..
3,337
243
4,643
..
115
7,446
502
849
4,018
1,169
1,752
719
1,203
..
..
2,442
55,754
1,298
..
2,977
134
1,074
656
69,282
7,909
..
..
1,137
..
3,610
6,692
101,468
38,814
21,726
..
18,734
8,689
353,620
296,836
177,652
152,211
7,700
1,723
3,311
2,923
1,187
10,553
334
1,384
1,504
234
7,912
2,185
9,253
..
124
..
11,542
4,577
292
5,847
2,588
219
8,848
879
..
2,785
1,723
2,270
1,102
2,579
2,338
2,300
2,368
25,520
2,546
..
5,046
351
768
959
119,309
12,988
940
4,836
1,516
5,396
3,491
9,014
161,543
61,138
42,481
..
24,777
11,649
462,592
372,146
240,847
184,869
10,678
2,985
6,616
3,684
623
11,393
678
1,003
1,999
270
5,455
2,365
11,191
675
1,232
707
8,162
4,727
369
6,549
3,096
235
14,032
987
342
4,858
2,290
3,477
1,310
5,164
4,491
4,292
2,382
55,622
1,806
..
5,878
620
1,026
..
131,765
15,277
1,418
11,853
1,561
6,548
4,007
5,186
255,081
62,070
92,987
26,540
44,364
22,258
627,017
Current prices
($ millions)
2004
2005
464,775
296,269
222,371
14,638
3,708
7,991
4,634
666
14,184
807
1,187
3,254
326
6,365
2,687
13,655
754
1,928
818
9,942
5,357
392
8,144
3,424
358
16,078
1,211
365
5,184
2,813
4,366
1,532
6,158
5,186
5,537
2,812
73,423
2,037
..
7,378
680
1,086
..
169,056
18,512
1,804
13,314
1,877
7,692
4,593
5,289
279,856
73,991
90,595
28,216
53,199
26,325
744,930
2006
2007
2008
Annual average growth (%)
1980–89 1990–99 2000–09
2009a
582,430
688,914 784,038 902,495 950,647
354,076
428,060 506,838
617,236
667,916
265,832
307,548 363,836 439,072 482,054
21,938
32,662
45,510
60,022
69,373
4,316
4,606
5,091
6,062
6,715
9,506
10,640
11,477
12,592
12,211
5,527
5,990
6,399
7,242
8,036
723
843
956
1,093
1,232
16,293
17,783
19,489
21,731
23,189
1,001
1,119
1,257
1,411
1,520
1,358
1,470
1,602
1,799
1,975
4,218
4,625
5,213
5,845
6,692
390
411
435
483
531
6,950
7,741
8,899
9,702
10,609
3,456
4,414
5,238
7,158
7,671
15,689
16,521
17,770
20,252
22,545
803
864
925
1,029
1,106
3,170
4,296
6,236
9,874
8,398
1,019
1,163
1,312
1,368
1,620
12,172
14,272
17,525
22,441
27,149
7,009
7,398
9,175
10,606
10,869
417
456
537
668
743
10,018
13,302
18,374
26,845
28,383
3,272
2,921
3,090
3,328
3,771
580
609
641
732
826
18,607
21,046
24,831
28,305
30,269
1,523
1,819
1,941
2,075
2,036
407
431
531
645
651
5,377
5,353
6,359
7,911
8,533
2,828
3,094
3,382
3,913
4,433
5,194
5,546
6,534
7,723
8,862
1,797
2,043
2,532
3,153
3,250
6,658
6,935
7,535
8,523
9,243
6,107
6,663
7,437
8,552
9,964
6,863
7,966
8,567
9,071
9,264
3,347
3,703
4,029
4,821
5,199
87,677
119,729
142,074 177,005 184,656
2,469
2,896
3,403
4,252
4,896
117
130
145
164
185
8,684
9,327
10,368
11,960
13,062
803
909
1,004
915
746
1,200
1,341
1,543
1,788
1,938
..
..
..
..
..
228,919
261,586
278,167 286,605 284,270
22,943
29,254
36,800
46,260
51,524
2,542
2,685
2,930
2,991
2,932
14,699
15,366
16,636
18,992
21,411
2,104
2,253
2,382
2,652
2,883
8,678
10,153
11,280
13,163
15,200
5,847
7,222
9,117
11,929
12,473
5,357
5,157
4,858
3,958
4,564
316,979
362,189 420,732 502,217 546,929
89,341
104,132 122,798 146,510 154,202
92,761
101,678 120,059 146,909
172,048
37,258
49,554
63,057
77,898
77,185
60,341
66,321
70,682
80,878
89,933
28,750
30,761
32,816
36,510
38,845
900,271 1,052,308 1,206,017 1,405,886 1,498,551
0.8
–1.2
2.1
..
1.1
9.4
3.4
3.6
8.7
..
6.9
4.5
10.5
–8.4
2.2
0.8
..
..
..
6.4
0.3
0.7
4.0
..
3.4
2.4
2.5
–3.2
–4.3
2.0
1.2
4.8
7.6
–2.2
0.2
–0.3
–10.9
8.2
..
5.0
9.5
–6.6
5.9
4.5
10.0
..
..
3.2
21.2
–6.1
0.1
5.8
6.3
8.6
..
1.9
2.0
2.4
1.6
1.1
0.8
–2.3
3.2
5.1
–1.1
–4.1
–1.5
6.3
–4.1
–0.6
–1.7
–5.7
–5.8
2.9
0.6
15.5
4.2
–4.9
–1.4
3.5
1.9
4.1
–1.1
5.7
2.4
..
4.1
0.7
0.6
3.1
6.3
6.6
5.4
–2.4
2.7
–3.5
..
–1.0
5.9
0.6
..
2.3
0.4
7.3
7.2
–0.3
6.3
–0.2
–2.3
4.2
–2.5
9.5
..
4.7
6.2
2.5
15.0
16.5
14.6
34.9
13.3
11.3
13.6
6.0
11.6
13.4
8.8
20.4
11.7
12.2
18.8
9.9
8.5
37.4
11.9
14.9
13.8
6.8
21.7
0.8
20.4
11.2
11.1
5.8
9.1
11.7
16.2
13.7
8.7
10.7
13.5
13.1
22.8
11.9
..
12.3
5.6
12.5
..
12.2
20.5
10.0
8.8
9.4
11.1
18.7
–4.0
10.6
15.2
5.7
20.7
11.0
8.8
13.3
a. Provisional.
14
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.8
Gross national income per capita,
World Bank Atlas method
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 Príncipe
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
2003
640
509
429
..
400
870
290
220
510
..
350
200
..
550
810
1,110
..
..
..
..
4,900
390
420
..
140
460
390
440
470
190
240
470
1,250
..
..
410
750
250
..
530
2,080
330
100
2,510
390
..
..
410
..
630
920
1,100
2,060
490
..
960
1,360
737
576
370
397
720
360
2,450
330
210
860
940
470
250
540
210
890
730
..
330
..
240
4,940
330
390
420
210
380
550
..
250
180
260
550
2,440
170
1,620
300
260
360
..
670
5,020
190
150
3,390
480
1,090
190
390
300
440
860
1,342
2,420
740
..
1,000
1,430
727
513
354
339
680
410
3,690
290
90
670
1,470
250
210
470
100
730
610
870
2,140
170
120
3,590
260
310
350
170
410
500
110
290
180
310
460
4,220
230
2,220
200
410
210
..
550
7,490
220
..
2,860
410
1,280
320
270
240
360
410
1,683
1,950
1,250
4,670
1,490
2,260
715
Current prices
($)
2004
2005
625
425
397
910
490
4,400
350
90
810
1,720
290
340
550
110
800
720
950
3,250
190
140
3,990
260
380
380
250
460
610
110
300
210
380
530
4,990
260
2,810
220
530
230
..
670
8,240
220
..
3,620
490
1,620
350
320
280
400
420
1,818
2,290
1,200
4,860
1,760
2,650
830
764
495
463
1,320
550
5,170
400
100
910
2,100
330
420
650
120
1,010
820
1,000
5,210
230
160
5,120
270
460
350
390
520
760
120
310
210
440
600
5,350
290
3,420
260
620
270
760
770
9,680
240
..
4,850
590
2,260
380
350
300
500
430
2,026
2,720
1,200
6,290
1,980
2,870
980
2006
2007
2008
2009a
882
583
522
1,910
570
5,710
420
110
980
2,310
350
450
670
130
1,270
840
1,050
6,870
250
190
5,300
290
590
310
400
570
900
120
300
220
460
670
5,540
310
3,890
270
830
310
840
810
10,740
250
..
5,480
740
2,360
380
370
340
600
410
2,278
3,120
1,290
8,200
2,150
3,040
1,119
979
673
602
2,590
610
6,060
430
120
1,040
2,560
380
490
690
140
1,470
880
1,110
9,710
270
220
6,450
330
800
320
420
660
960
150
340
230
530
810
5,980
340
4,100
280
960
360
920
870
11,800
280
..
5,760
910
2,540
400
380
370
740
390
2,605
3,630
1,500
10,220
2,260
3,210
1,253
1,100
800
707
3,330
700
6,550
480
140
1,140
2,830
410
540
750
150
1,980
980
1,210
14,980
280
280
7,320
400
1,150
340
460
730
1,010
170
410
260
610
980
6,720
380
4,260
330
1,170
440
1,020
980
10,530
320
..
5,870
1,120
2,560
450
410
420
950
320
3,060
4,260
1,800
12,380
2,560
3,540
1,428
1,130
844
757
3,750
750
6,260
510
150
1,190
3,010
450
600
810
160
2,080
1,070
1,280
12,420
320
330
7,370
440
1,190
370
510
760
980
160
430
290
680
990
7,250
440
4,270
340
1,190
490
1,130
1,040
8,480
340
..
5,760
1,220
2,470
490
440
460
960
360
3,280
4,420
2,070
12,020
2,810
3,720
1,487
Annual average growth (%)
1980–89 1990–99 2000–09
–2.0
–4.0
–0.8
..
–1.9
6.0
1.0
0.3
5.4
..
4.2
1.7
7.4
–11.1
–0.8
–3.3
..
..
..
3.3
–2.7
–3.1
0.9
..
1.3
–1.3
0.3
–4.8
–6.8
–2.5
–0.6
2.1
6.7
–2.7
–3.5
–3.0
–13.2
4.3
..
1.9
8.6
–8.8
6.0
1.9
6.8
..
..
–0.5
17.0
–9.0
–3.6
3.0
3.2
5.7
..
–0.6
–0.5
–0.5
–1.1
–1.6
–1.9
–5.0
–0.2
2.5
–3.9
–5.3
–4.1
4.0
–6.4
–3.6
–3.9
–8.5
–7.8
–0.3
–2.1
11.5
1.7
–7.6
–4.2
–0.4
–0.9
0.8
–3.3
2.5
0.7
..
1.0
–1.3
–1.4
0.4
5.0
3.5
2.8
–5.5
0.1
–3.6
..
–3.6
4.3
0.8
..
0.0
–2.2
4.9
4.1
–3.0
3.1
–3.0
–4.1
2.3
–4.4
7.4
..
3.1
4.5
–0.1
12.2
13.6
11.7
31.1
9.7
9.8
9.8
3.3
9.1
11.6
6.9
16.6
9.3
9.1
16.2
7.6
6.5
33.7
7.8
11.7
11.5
3.5
19.0
–1.2
17.2
8.4
10.1
1.8
6.0
8.2
13.3
10.9
7.9
7.9
11.3
9.1
19.9
9.3
..
9.4
4.7
8.8
..
10.9
18.0
8.9
5.9
6.7
7.5
15.8
–4.0
8.8
13.5
3.7
18.2
9.7
7.7
10.7
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
15
Table
2.9
Gross domestic product deflator (local currency series)
Index
(2000 = 100)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
20
20
20
..
38
14
52
21
34
..
32
46
36
0
29
39
..
..
..
..
35
15
0
..
0
10
13
2
4
2
35
20
22
0
11
49
2
20
..
39
56
0
..
9
0
13
..
35
..
0
181
21
6
13
..
35
30
20
40
41
42
0
50
43
76
31
58
66
70
60
70
0
38
50
69
24
..
49
53
64
11
48
6
24
40
2
21
7
57
42
55
6
34
63
7
33
..
63
87
5
..
38
1
40
14
58
29
1
154
54
16
43
..
68
64
42
118
117
117
931
113
116
111
120
106
106
105
116
119
722
81
111
104
87
161
102
93
170
213
112
199
109
126
145
127
223
117
119
120
131
124
107
162
119
..
107
117
106
..
126
122
123
122
101
109
180
112
111
111
112
166
103
107
117
127
127
127
1,329
113
129
115
130
107
113
106
127
121
766
95
112
108
102
192
106
99
191
244
130
198
117
134
146
145
256
116
133
127
141
127
108
195
135
..
107
121
126
..
134
140
130
131
105
126
214
120
123
123
125
224
104
110
127
140
139
139
1,780
116
141
115
151
110
109
109
130
124
931
115
116
111
145
260
117
116
199
280
166
208
122
142
166
172
285
119
157
133
153
134
115
234
147
..
110
142
142
..
141
157
139
139
106
124
251
126
133
143
133
279
105
114
139
149
148
147
2,041
122
168
115
158
115
109
114
148
126
1,053
136
122
115
166
287
130
125
202
506
228
203
132
153
181
192
344
124
193
142
167
146
116
280
161
..
114
144
156
..
150
167
152
147
106
127
285
121
143
159
143
321
107
118
148
164
164
162
2,126
126
186
119
171
117
110
117
156
133
1,276
137
125
121
164
304
153
132
216
589
258
215
139
174
210
210
371
133
207
154
180
159
120
293
182
..
121
170
172
..
163
180
169
160
107
136
318
122
161
171
161
367
111
123
163
189
192
189
2,606
135
217
126
214
122
111
124
174
140
1,523
171
135
132
203
406
200
151
229
708
294
238
155
197
232
229
404
145
233
164
194
182
129
325
205
..
128
218
192
..
178
217
186
176
114
145
355
124
181
196
181
460
118
129
186
195
196
195
2,455
136
205
130
243
118
115
129
153
147
1,983
136
137
134
135
443
248
123
234
826
310
241
166
204
249
248
437
151
218
167
201
194
135
323
228
..
127
280
204
..
191
216
196
189
116
169
400
156
178
178
200
309
120
133
194
Annual average
1980–89 1990–99 2000–09
26
27
27
0
47
23
67
24
50
60
54
55
54
0
39
50
..
26
..
42
44
31
3
31
1
16
22
2
10
3
50
29
34
1
19
63
3
25
..
55
70
1
..
18
0
19
10
49
4
0
161
33
9
20
..
50
46
26
67
68
69
3
73
66
84
51
79
81
83
78
82
2
50
75
85
41
66
79
63
82
37
77
47
57
68
22
54
29
79
75
76
45
55
78
41
70
..
81
92
41
..
65
35
69
46
78
70
32
122
77
50
73
84
84
82
69
140
140
139
1,404
118
150
114
150
110
108
112
133
123
948
114
117
113
128
241
134
113
179
377
180
180
124
146
168
165
275
122
158
133
151
140
114
217
147
..
112
151
140
..
141
151
142
138
106
124
238
118
134
138
136
248
107
114
139
a. Provisional.
16
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.10
Gross domestic product deflator
(U.S. dollar series)
Index
(2000 = 100)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
120
146
126
..
130
88
175
164
106
..
108
155
91
205
98
132
..
..
..
..
119
113
168
..
97
103
114
69
130
124
116
102
75
143
95
165
204
85
..
131
50
119
..
85
138
115
..
118
..
142
181
94
120
60
..
94
101
111
110
116
126
121
131
112
199
131
127
112
183
157
138
122
100
130
69
64
..
194
138
104
180
128
131
81
107
89
94
151
149
125
97
99
91
165
81
154
..
165
93
64
..
101
176
108
56
152
134
109
154
97
134
66
..
88
100
104
117
118
115
125
138
120
136
80
120
130
129
142
146
123
99
136
104
107
111
97
114
80
134
98
244
109
116
100
139
136
144
108
113
85
114
131
127
86
..
130
123
95
..
115
120
113
94
124
84
119
112
91
108
76
67
114
114
106
137
133
129
160
153
140
155
85
134
152
142
172
163
134
127
150
108
137
134
100
134
81
148
102
267
112
144
109
105
140
157
124
121
96
136
146
150
91
..
144
126
97
..
144
139
140
96
141
105
140
120
98
128
69
88
124
121
121
152
151
141
205
157
141
155
101
137
147
148
176
167
136
155
157
111
196
163
110
157
89
168
80
280
123
155
119
116
143
161
141
118
103
146
156
181
103
..
148
148
103
..
154
165
151
99
143
105
175
126
108
147
76
106
126
120
134
167
175
160
255
167
147
156
111
144
148
156
202
172
155
185
166
115
227
180
122
171
92
301
75
277
139
157
128
121
150
169
172
118
102
150
158
223
114
..
155
150
110
..
154
197
156
94
144
105
246
121
119
165
85
128
129
121
147
181
193
179
278
187
155
177
114
160
163
174
232
197
171
203
186
121
244
190
139
196
111
342
109
320
157
171
140
152
158
198
191
129
107
157
178
237
130
..
179
145
121
..
160
229
166
103
160
116
247
122
134
186
96
154
144
131
162
197
225
209
349
214
164
200
130
179
177
198
277
223
187
272
215
132
323
254
169
241
132
365
93
379
171
165
150
182
171
230
233
152
124
153
205
279
146
..
201
132
134
..
149
267
156
118
182
129
295
124
158
228
112
193
161
144
181
184
198
191
311
205
149
196
142
164
174
195
230
221
166
205
206
134
192
278
172
185
113
320
102
363
163
162
149
172
185
227
199
137
115
160
204
221
156
..
192
118
128
..
157
241
163
115
175
134
247
156
143
184
124
126
158
135
167
Annual average
1980–89 1990–99 2000–09
106
119
116
95
103
77
147
153
102
95
117
121
89
133
84
108
..
54
..
167
96
91
177
117
105
86
95
76
108
118
108
108
72
157
79
137
127
112
..
120
65
98
..
88
196
87
69
106
157
111
161
91
128
62
..
72
89
100
109
105
113
91
116
110
135
123
125
117
143
129
125
126
81
123
85
65
99
151
104
109
166
136
116
86
120
101
101
132
132
140
106
93
97
127
76
123
..
136
103
99
..
115
122
123
72
131
109
111
122
93
101
76
93
99
111
102
142
150
142
198
154
132
149
104
133
140
145
176
161
141
152
153
113
170
160
119
148
98
209
94
242
127
134
118
132
145
160
147
118
100
129
149
174
109
..
146
126
109
..
130
167
131
101
137
105
178
118
113
144
91
111
125
119
130
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
17
Table
2.11
Consumer price index
Annual growth
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
..
..
..
13.6
12.2
2.5
9.6
..
..
..
..
46.6
..
14.7
12.1
..
..
4.5
12.3
6.8
50.1
..
..
13.9
16.3
14.7
18.2
..
..
..
42.0
..
..
10.3
10.0
7.2
..
8.7
13.6
..
..
13.7
25.4
18.7
30.2
12.3
..
..
5.4
..
9.5
20.8
9.7
9.4
..
..
..
..
..
11.4
–0.5
7.0
1.1
10.7
0.0
–0.7
..
81.3
2.9
–0.8
..
0.9
..
5.2
7.7
12.2
37.3
..
33.0
17.8
11.6
..
11.8
11.8
0.6
6.6
13.5
47.0
..
–0.8
7.4
4.2
..
0.3
3.9
..
..
14.3
65.2
13.1
35.8
1.0
33.1
107.0
17.4
..
16.7
16.8
8.5
6.8
6.5
..
..
98.2
1.5
9.2
2.0
10.8
0.6
1.2
4.1
–1.8
..
12.9
–0.6
3.3
2.0
7.3
..
17.8
2.2
17.0
26.7
..
–3.5
9.8
6.7
..
–1.2
9.6
–1.3
5.2
3.9
13.4
7.2
–1.6
14.0
7.4
..
0.0
3.3
..
..
5.9
7.7
7.3
5.3
–1.0
8.7
21.4
431.7
..
2.6
4.5
–2.2
1.2
2.7
..
..
43.5
0.9
6.9
–0.4
7.9
0.2
–1.9
–2.1
–5.4
..
4.0
2.4
1.4
3.1
4.2
..
3.3
0.4
14.2
12.6
..
0.9
11.6
5.0
..
13.8
11.4
–3.1
10.4
4.7
12.7
4.1
0.3
15.0
12.3
..
0.5
3.9
..
..
1.4
8.4
3.4
4.7
0.4
3.7
18.0
282.4
..
3.6
11.3
–2.2
1.5
3.6
..
..
23.0
5.4
8.6
6.4
13.5
2.0
0.4
2.9
7.9
..
21.3
3.1
3.9
3.1
5.6
..
11.6
3.7
4.8
15.1
..
3.3
10.3
3.4
..
18.5
15.4
6.4
12.1
4.9
7.2
2.3
7.8
17.9
9.0
..
1.7
0.9
..
..
3.4
8.5
4.8
5.0
6.8
8.4
18.3
302.1
..
1.6
4.9
2.7
1.0
2.0
..
..
13.3
3.8
11.6
2.3
2.8
5.1
5.4
6.7
8.0
..
13.1
6.5
2.5
3.5
4.4
..
12.3
–1.4
2.1
10.9
..
2.0
14.5
6.0
..
10.8
14.0
1.5
6.2
8.9
13.2
5.1
0.0
8.2
8.9
..
2.1
–0.4
..
..
4.6
7.2
5.3
7.3
2.2
7.3
9.0
1,096.7
..
2.5
7.6
1.5
3.3
4.5
..
..
12.2
1.3
7.1
–0.2
8.3
0.9
4.4
0.9
–9.0
..
16.9
2.7
1.9
5.0
2.8
..
17.2
5.0
5.4
10.7
..
4.6
9.8
8.0
..
10.3
8.0
1.4
7.3
8.8
8.2
6.7
0.1
5.4
9.1
..
5.9
5.3
11.6
..
7.1
8.0
9.5
7.0
1.0
6.1
10.7
24,411.0
..
3.5
9.3
6.3
2.0
3.1
..
2008
..
12.5
7.9
12.7
10.7
24.1
5.3
6.8
9.3
10.3
..
17.3
7.3
6.3
12.0
6.6
..
44.4
5.3
4.5
16.5
18.4
10.5
26.2
10.7
..
9.2
8.7
9.2
7.3
9.7
10.3
10.4
11.3
11.6
15.4
..
5.8
37.0
14.8
..
11.5
14.3
13.4
10.3
8.7
11.6
12.4
..
..
4.4
18.3
10.4
3.7
4.9
..
2009a
..
13.7
2.2
8.0
2.6
11.0
3.0
1.0
3.5
10.0
..
..
5.0
1.0
1.7
..
..
8.5
1.9
4.6
19.3
4.7
–1.7
9.2
7.2
..
9.0
8.4
2.2
2.2
2.5
3.3
8.8
4.3
11.5
10.4
..
–1.1
31.8
9.3
..
7.1
11.2
7.3
12.1
2.0
13.4
13.4
..
..
5.7
11.8
2.5
1.0
3.8
..
Annual average
1980–89 1990–99 2000–09
..
..
..
10.8
5.0
7.2
9.1
6.7
3.6
3.0
..
57.0
1.0
6.7
5.3
–5.5
..
4.6
6.5
17.5
48.3
..
70.5
11.8
13.9
5.6
18.6
16.8
–0.1
7.5
11.2
–3.2
..
3.6
20.9
4.7
..
6.9
4.0
..
..
14.6
36.2
15.0
30.1
5.0
111.2
69.3
12.8
..
9.0
17.4
7.9
7.6
7.6
..
..
1,122.5
9.7
10.8
4.5
13.5
5.6
6.4
3.9
5.5
..
3,367.2
–3.5
6.0
..
6.6
..
8.0
3.7
5.4
27.6
..
37.5
17.4
–1.7
..
17.3
31.0
4.2
6.4
7.6
34.5
..
4.3
30.6
–3.4
..
4.5
2.0
..
..
9.9
80.4
9.5
23.1
7.1
13.0
76.2
28.6
..
18.6
10.5
6.7
4.4
4.9
..
..
80.3
3.4
8.7
3.0
11.1
2.6
2.0
3.5
4.2
..
110.1
3.0
3.0
3.6
5.8
..
10.9
2.0
6.6
18.5
11.5
3.1
10.9
7.7
..
10.5
14.3
2.6
6.3
6.0
10.7
6.4
3.2
12.2
8.2
..
2.1
9.4
11.9
..
6.1
8.7
8.1
6.8
2.9
6.4
17.3
3,349.6
..
3.0
7.5
–0.3
1.9
3.2
..
a. Provisional.
18
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.12
Price indexes
Inflation, GDP deflator
(annual %)
2008
2009a
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 Príncipe
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
10.6
10.8
10.6
22.6
7.1
17.0
5.8
25.1
4.2
1.0
6.2
11.9
5.5
19.4
25.1
8.1
9.5
23.7
33.4
30.5
14.7
6.2
20.2
14.1
10.6
11.9
13.4
10.4
9.2
8.9
8.7
12.4
7.0
8.2
14.3
7.7
11.0
12.7
23.1
5.9
28.5
11.2
..
9.2
21.0
10.1
10.1
6.5
6.5
11.5
2.3
12.2
14.6
12.2
25.4
5.9
5.4
10.8
4.3
4.1
4.3
–5.8
1.2
–5.7
3.1
13.6
–3.4
3.8
3.9
–12.4
4.6
30.2
–20.4
1.3
1.7
–33.5
9.3
24.4
–19.0
2.4
16.7
5.2
1.1
6.7
3.4
7.4
8.3
8.4
4.3
–6.2
1.5
3.3
6.5
4.9
–0.6
11.0
15.6
–0.5
28.6
6.3
..
7.3
–0.8
5.5
7.4
1.3
16.5
12.7
25.3
1.8
–9.4
10.8
–32.8
1.8
2.9
3.8
Consumer price index
(2000 = 100)
2008
2009a
126.6
126.7
126.6
143.0
113.5
134.6
113.0
138.2
111.7
117.5
117.7
108.5
..
155.1
117.4
111.0
121.6
114.4
..
190.1
109.0
112.3
143.1
118.4
117.8
158.6
126.8
..
133.5
133.8
112.4
122.3
130.1
135.1
123.7
111.4
127.3
137.1
1,171.2
114.3
143.8
128.2
..
125.0
132.3
130.7
126.6
112.2
127.2
135.7
..
113.1
110.9
139.2
119.0
109.3
113.1
124.4
134.2
134.6
134.0
162.7
115.9
145.4
115.9
153.4
115.2
118.6
121.8
119.3
..
..
123.3
112.1
123.6
..
..
206.2
111.1
117.4
170.7
123.9
115.9
173.2
135.9
..
145.4
145.0
114.9
125.0
133.4
139.5
134.6
116.2
142.0
151.3
..
113.1
189.4
140.1
..
133.9
147.2
140.3
142.0
114.4
144.3
153.8
..
117.4
117.2
155.6
121.9
110.4
117.4
133.4
Exports of goods and
services price index
(2000 = 100)
2008
2009a
..
..
..
..
..
138.8
..
..
338.8
74.2
..
..
..
179.4
..
194.2
..
..
..
145.0
330.3
121.3
..
139.1
..
174.8
130.4
..
151.0
..
..
..
142.7
113.8
175.5
..
..
..
..
183.3
96.9
..
..
196.5
255.0
97.2
137.4
..
108.0
..
187.3
..
292.8
92.2
..
176.3
198.7
..
..
..
..
..
..
135.2
..
..
271.8
70.4
..
..
..
64.1
..
158.6
..
..
..
138.4
207.2
108.5
..
179.2
..
168.1
136.0
..
135.3
..
..
..
126.6
85.5
184.1
..
..
..
..
178.1
73.1
..
..
194.1
..
103.4
125.9
..
99.5
..
201.5
..
216.7
94.6
..
159.2
168.9
..
Imports of goods and
services price index
(2000 = 100)
2008
2009a
173.0
..
178.1
..
..
159.8
..
..
296.7
126.5
..
..
..
127.8
..
211.5
..
..
..
135.4
204.3
170.5
..
165.7
..
163.6
87.1
..
164.0
..
..
..
185.1
211.2
136.1
..
..
..
..
198.8
96.9
..
..
168.0
254.3
97.2
129.7
..
153.9
..
217.9
160.1
188.8
90.9
..
188.5
204.5
167.6
153.9
..
..
..
..
163.5
..
..
254.4
120.0
..
..
..
74.6
..
165.0
..
..
..
120.1
166.6
152.1
..
181.3
..
146.8
86.5
..
153.3
..
..
..
156.4
173.3
133.2
..
..
..
..
193.8
73.1
..
..
153.7
..
103.4
105.5
..
148.0
..
196.2
152.8
209.7
105.6
..
160.0
159.4
153.4
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
19
Table
2.13
Gross domestic savings
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
25.3
..
11.7
..
–6.3
26.7
–7.2
–0.6
21.7
..
–8.9
..
–10.1
10.1
35.7
20.4
..
..
..
..
60.6
5.8
4.9
..
–1.0
18.1
–52.0
14.8
–1.4
10.8
1.1
–3.5
10.4
–8.9
38.4
14.6
..
4.2
..
2.1
27.1
0.9
–12.9
37.9
2.1
1.2
..
23.2
–0.4
19.3
13.8
22.8
43.1
15.2
..
14.9
24.0
24.2
17.1
11.7
11.7
29.7
2.2
42.6
5.4
–5.4
20.7
–8.1
–0.6
–7.7
–3.2
9.3
23.8
11.3
–10.4
–20.1
..
9.6
36.9
10.7
5.5
22.2
2.8
18.5
–49.1
..
5.5
13.4
6.4
4.9
23.0
–5.8
18.2
1.2
..
6.2
..
2.4
20.3
8.7
–12.5
23.2
8.2
5.3
1.3
14.7
0.6
16.6
17.5
20.8
27.1
16.1
27.2
19.9
20.0
18.8
16.0
13.4
13.4
19.2
6.0
41.0
4.5
–8.7
17.8
–15.8
1.6
18.0
–3.4
5.0
30.9
21.0
5.3
80.1
–40.9
7.7
48.2
11.1
7.0
21.5
..
10.5
–25.9
–3.2
8.9
3.2
13.3
–5.0
24.9
3.5
10.3
5.0
..
0.4
..
8.8
21.5
–3.7
..
19.0
15.7
18.1
16.1
5.3
7.2
13.0
2.3
27.2
44.9
14.3
46.8
24.5
21.2
21.0
15.9
14.2
14.2
25.1
5.5
40.5
1.8
–11.0
18.5
–1.5
0.0
24.5
–8.5
4.0
52.2
20.0
4.3
78.9
–41.5
8.8
54.6
8.9
7.3
18.4
..
10.8
–25.7
–0.7
8.5
0.0
8.6
–3.1
22.0
7.7
16.8
3.9
..
1.4
..
7.9
14.7
–0.4
..
17.8
18.7
13.5
15.2
4.5
10.1
19.9
–2.8
27.7
47.7
15.6
42.7
24.2
21.2
21.2
15.7
14.2
14.2
37.9
6.9
43.1
4.8
–23.1
18.1
4.4
0.1
35.1
–12.3
5.9
52.0
17.2
8.6
83.7
–27.2
2.6
58.3
4.0
3.7
18.3
..
9.5
–27.9
2.4
4.9
–5.5
11.0
–15.0
16.5
6.5
19.8
13.4
..
2.0
..
14.1
3.1
4.1
..
17.5
19.0
11.2
14.0
1.5
11.7
21.8
–7.6
29.9
54.9
15.7
48.1
23.2
21.4
22.1
15.9
14.6
14.6
49.1
6.9
40.4
2.8
–19.9
18.9
5.0
1.4
36.4
–14.8
–0.6
43.3
19.6
12.1
86.1
–17.2
1.5
56.0
11.2
6.1
13.9
..
8.1
–23.6
–34.6
9.3
1.2
14.8
18.6
15.3
8.8
20.6
..
..
1.8
..
10.7
8.1
7.6
..
17.2
18.6
11.5
11.0
..
8.1
31.5
–9.8
33.5
56.6
17.1
66.8
24.0
21.5
23.8
16.7
15.2
15.2
45.0
6.1
37.8
..
..
18.5
5.8
1.5
20.5
–15.4
8.8
49.6
14.6
17.4
86.9
–17.7
4.2
55.3
6.6
3.8
9.7
..
8.0
–27.1
–142.5
10.6
18.9
13.0
8.0
16.6
6.3
22.4
..
..
3.5
..
8.6
–1.7
6.1
..
18.3
26.7
12.7
12.6
..
8.8
30.5
–1.6
32.8
57.5
16.3
63.6
23.4
22.0
24.0
16.1
13.3
13.3
41.1
7.1
32.3
..
..
..
9.2
–1.0
27.4
–20.1
8.6
48.4
17.9
..
72.8
..
0.4
58.9
6.1
2.0
10.3
..
6.1
–25.3
–121.5
9.9
8.9
..
5.6
12.5
1.6
21.4
..
..
7.0
..
3.6
6.0
1.7
..
18.9
26.8
–0.2
10.3
..
15.3
25.1
–22.6
33.7
56.7
16.8
67.8
24.7
22.4
24.3
15.5
12.5
12.5
20.8
10.7
13.0
..
..
..
12.0
2.7
5.9
–21.1
17.7
45.5
19.2
..
72.2
..
4.1
47.3
6.3
8.7
16.9
..
7.8
–29.1
..
8.9
17.2
..
7.4
10.8
2.2
13.9
..
..
4.2
..
8.0
15.9
2.3
..
18.6
19.4
0.2
17.9
..
12.5
25.6
–26.9
23.8
45.5
12.4
..
25.1
23.5
19.1
Annual average
1980–89 1990–99 2000–09
20.1
11.9
11.8
24.0
–2.4
35.3
–1.6
3.1
24.2
–2.2
–1.1
–8.1
–4.5
10.9
31.9
19.6
..
..
..
10.5
44.3
6.5
4.8
16.6
–0.9
18.3
–69.5
2.2
2.9
12.7
–0.4
3.1
20.3
–6.2
10.8
7.3
..
5.0
..
4.3
24.1
9.1
–6.3
28.5
4.2
3.7
..
12.3
2.3
14.0
16.5
20.3
31.5
15.5
..
16.7
22.7
20.2
15.4
11.7
11.7
22.0
3.8
38.8
9.0
–5.2
18.5
–5.6
3.7
–0.5
–4.9
8.8
28.8
17.8
–6.4
13.7
–29.7
9.7
43.6
7.4
7.5
18.3
1.5
14.6
–37.6
..
4.2
3.4
7.6
2.4
24.1
–2.9
12.7
2.7
..
–5.5
..
5.4
21.7
2.8
–12.5
19.4
9.6
2.0
2.9
6.7
4.3
9.0
17.1
19.2
30.1
14.2
17.6
17.8
22.3
17.1
16.0
13.7
13.7
31.9
6.5
36.5
2.6
–12.3
18.8
–2.6
2.0
13.8
–11.1
6.1
48.3
19.4
5.7
79.5
–29.2
5.7
53.2
8.8
5.9
15.1
–13.2
8.7
–26.4
–38.4
9.2
5.4
12.2
0.9
19.6
6.0
17.1
5.9
..
2.4
..
8.9
13.3
–1.6
..
18.5
18.4
9.4
13.7
1.8
9.5
18.1
–3.9
27.9
49.1
14.8
46.6
23.7
22.2
21.4
a. Provisional.
b. For 1994–2000 Nigeria’s values were distorted because the official exchange rate used by the government for oil exports and oil value added was significantly overvalued.
20
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.14
Gross national savings
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
23.4
..
10.9
..
4.2
28.7
9.3
..
5.2
..
1.6
..
–0.4
..
26.1
8.6
..
..
..
..
47.8
16.4
6.3
..
..
17.2
49.6
13.1
–0.7
7.8
8.4
3.9
10.4
–6.6
..
17.1
..
14.0
..
2.7
32.4
2.9
20.1
33.9
4.5
..
..
27.2
1.9
7.8
12.0
25.9
41.0
21.0
..
18.6
25.3
24.5
15.8
12.8
12.8
9.0
5.3
41.6
15.9
8.7
16.2
17.8
6.2
2.3
14.4
..
6.9
–5.1
..
2.1
..
12.8
24.3
21.9
10.5
19.2
14.5
18.5
70.5
..
9.1
16.4
15.0
18.8
25.8
6.6
34.8
–0.6
..
11.3
..
1.6
21.7
–1.0
..
19.1
1.2
19.7
10.1
21.0
5.6
19.6
15.6
27.6
24.3
31.1
..
25.1
23.4
20.8
16.0
16.3
16.3
7.6
6.7
35.7
9.4
9.1
14.9
9.3
..
..
..
..
4.2
12.3
24.6
..
..
21.4
33.4
17.1
21.1
18.3
..
15.2
18.9
..
13.0
..
14.4
..
25.3
4.1
24.3
7.2
..
11.0
..
15.0
17.2
9.1
..
15.7
12.2
24.1
20.0
11.3
17.6
10.8
..
25.2
..
18.5
42.2
30.7
21.8
19.7
16.4
17.8
17.8
12.6
6.8
36.2
5.4
9.5
17.0
22.0
..
..
..
..
19.7
12.4
24.4
..
..
22.1
35.4
16.7
22.9
11.4
..
16.2
20.6
142.2
14.1
..
8.6
..
22.6
8.0
28.2
6.9
..
14.8
..
14.6
12.4
4.8
..
15.0
16.0
18.3
19.4
11.4
20.4
13.1
..
25.3
..
21.1
34.4
31.0
21.7
20.0
16.4
18.3
18.3
24.8
10.1
41.5
8.8
4.5
16.7
29.1
..
..
..
..
18.9
10.0
28.3
..
..
13.7
44.2
10.2
19.2
..
..
16.1
18.0
128.1
8.0
..
11.4
..
17.4
7.1
27.5
18.5
..
15.1
..
21.0
2.1
10.0
..
14.5
17.0
22.1
17.3
8.7
20.7
17.7
..
27.4
..
21.8
46.0
30.9
20.2
20.9
16.1
..
18.0
36.5
10.0
41.2
7.0
4.1
19.2
27.1
..
..
..
..
9.0
12.1
33.4
..
..
9.7
..
18.9
16.5
..
..
16.2
30.7
134.1
..
..
14.5
..
17.1
7.1
31.7
..
..
10.4
..
18.7
8.2
9.0
..
14.4
13.9
17.0
15.2
..
16.9
23.9
..
32.5
..
23.0
69.8
32.2
21.7
23.0
15.9
..
18.0
29.9
8.8
40.8
..
..
20.3
26.5
..
..
..
..
18.0
8.4
37.1
..
..
21.9
..
17.3
11.5
–1.6
..
16.0
39.0
–11.4
..
..
18.6
..
21.3
6.6
31.8
..
..
14.1
..
19.1
–3.9
10.3
..
14.1
17.8
20.6
16.6
..
16.2
23.1
..
32.2
..
23.6
66.5
32.3
21.0
22.7
15.5
..
16.2
23.6
10.6
34.8
..
..
..
26.7
..
..
..
..
..
12.3
..
..
..
17.1
..
10.4
8.8
1.4
..
14.2
33.5
–2.1
..
..
..
..
16.7
3.8
31.6
..
..
17.3
..
16.1
1.6
5.3
..
14.9
17.4
6.9
13.3
..
21.9
19.2
..
32.5
..
23.6
67.1
32.9
21.3
22.8
15.4
..
..
9.7
..
16.4
..
..
..
31.3
..
..
..
..
..
14.8
..
..
..
16.1
..
18.8
15.5
7.7
..
15.4
28.1
..
..
..
..
..
16.7
9.1
26.5
..
..
15.1
..
..
9.2
7.8
..
15.4
12.2
2.4
21.2
..
17.5
19.0
..
..
..
16.7
..
31.2
22.8
17.6
Annual average
1980–89 1990–99 2000–09
18.6
13.0
12.4
13.8
4.6
33.8
14.6
11.2
18.8
24.3
6.1
6.2
15.0
..
25.5
6.8
..
..
..
13.4
33.7
16.9
7.3
12.4
1.8
18.0
42.0
–3.5
3.0
12.5
6.1
12.2
20.2
–2.2
..
8.8
..
12.0
..
4.2
27.3
7.7
19.2
24.4
3.7
..
..
16.8
5.5
3.2
14.6
23.6
29.4
21.8
..
20.5
23.7
20.8
15.2
13.9
13.9
1.6
7.8
40.5
21.5
6.2
13.4
21.8
8.1
4.6
15.4
..
5.3
6.0
11.4
14.7
32.8
15.5
29.3
16.9
13.5
18.7
9.0
21.8
49.5
..
5.1
8.1
14.7
10.5
26.5
6.0
27.5
3.6
..
14.2
..
6.3
21.5
0.8
..
16.6
4.0
16.2
8.7
10.8
14.4
7.1
15.7
28.3
28.6
24.7
..
21.6
22.2
18.4
15.8
16.3
16.7
17.7
9.3
35.4
6.8
5.8
16.5
19.8
..
..
..
..
18.0
11.7
22.3
..
4.4
17.8
37.1
15.6
17.4
9.9
–7.3
15.1
24.9
78.2
11.8
8.9
13.1
..
21.9
7.8
27.8
8.6
..
13.4
..
16.0
10.0
5.7
..
15.2
13.0
17.1
16.9
7.0
17.6
13.0
..
28.1
..
20.3
49.7
30.6
21.9
20.0
a. Provisional.
b. For 1994–2000 Nigeria’s values were distorted because the official exchange rate used by the government for oil exports and oil value added was significantly overvalued.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
21
Table
2.15
General government final
consumption expenditure
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
15.1
..
16.1
..
8.6
21.3
9.2
9.2
9.7
..
15.1
..
30.9
8.4
17.6
16.9
..
..
..
..
13.2
31.2
11.2
..
27.6
19.8
21.8
19.1
12.1
19.3
11.6
45.3
14.0
12.2
17.4
10.4
..
12.5
..
24.8
28.7
8.4
15.6
14.3
16.0
27.0
..
22.4
..
25.5
18.5
15.9
15.2
15.7
..
18.3
14.5
15.5
17.5
15.6
15.6
34.5
11.0
24.1
21.1
10.8
12.8
14.7
14.9
10.0
24.5
11.5
13.8
16.8
31.5
39.7
..
13.2
13.4
13.7
9.3
11.0
10.3
18.6
25.8
..
8.0
15.1
13.8
25.9
13.6
13.5
30.6
15.0
..
10.1
..
18.4
27.7
7.8
..
19.7
5.8
14.3
17.8
14.2
7.5
19.0
19.4
15.1
16.1
11.3
24.4
15.5
16.4
16.4
16.4
13.8
13.8
..
13.3
22.3
22.2
22.7
10.0
14.7
11.0
7.6
14.7
6.3
17.4
8.2
29.5
3.8
50.3
13.4
10.1
11.0
11.5
8.2
..
18.1
37.4
8.5
9.2
12.4
8.4
30.1
14.2
10.2
22.2
11.3
..
13.8
..
13.3
25.5
15.6
..
19.2
10.8
15.3
15.4
9.8
15.7
14.4
17.9
14.3
14.8
12.7
13.6
18.1
15.7
15.5
16.6
14.1
14.1
..
13.6
21.1
21.6
26.1
10.2
20.6
10.5
4.9
14.3
8.2
15.0
8.3
29.7
2.9
52.9
13.1
9.3
16.9
12.2
6.9
..
17.9
37.4
10.4
6.9
12.5
10.0
21.9
14.3
10.8
20.4
12.5
..
18.4
..
13.7
28.3
13.3
..
19.4
11.8
16.0
16.9
9.7
13.9
18.1
21.0
14.1
13.8
12.8
13.1
18.7
15.4
15.5
16.7
14.2
14.2
..
15.0
22.4
22.3
26.5
10.0
20.4
13.3
5.1
13.5
8.3
13.0
8.3
27.1
2.7
37.2
12.3
8.3
18.4
15.3
7.0
..
17.4
39.2
11.1
9.0
14.3
9.9
22.7
14.8
10.4
19.3
11.5
..
18.2
..
9.6
21.3
13.8
..
19.5
18.2
15.6
17.6
11.5
14.5
9.7
15.7
13.6
11.5
12.7
11.8
19.4
15.4
15.3
16.4
13.4
13.4
..
..
19.0
22.0
28.8
9.6
22.1
11.1
4.9
14.2
7.8
13.9
8.3
28.0
2.6
35.9
12.1
8.4
18.1
11.3
8.1
..
17.5
40.4
11.5
8.7
14.6
9.9
17.5
14.2
10.7
19.5
..
..
18.1
..
9.7
19.8
13.8
..
19.7
17.3
15.3
17.5
11.3
14.1
10.2
6.2
13.0
11.2
12.3
10.7
18.5
14.7
14.9
16.0
13.1
13.1
..
..
19.4
..
..
9.2
22.4
2.7
10.3
14.3
10.4
17.1
8.7
25.1
2.3
31.4
10.4
8.9
16.0
11.6
6.8
..
17.9
38.7
14.6
12.3
14.1
10.3
21.6
13.1
11.8
20.7
..
..
16.5
..
10.0
16.0
11.8
..
19.0
15.5
14.6
19.3
9.3
12.9
10.4
3.4
12.6
11.3
11.3
11.6
18.2
14.1
14.4
16.3
..
13.2
..
..
19.8
..
..
..
20.7
6.6
12.4
15.3
11.0
12.0
8.6
..
2.6
..
9.7
8.2
15.6
11.2
9.3
..
16.7
44.0
19.3
11.2
17.3
..
18.8
13.2
12.1
20.5
..
..
14.7
..
9.7
13.3
12.5
..
19.1
15.8
23.6
20.0
..
11.2
9.0
2.1
12.3
12.9
10.9
9.3
17.1
14.4
14.4
17.6
..
13.9
..
..
24.2
..
..
..
20.8
4.5
15.6
15.3
7.9
12.2
8.6
..
3.4
..
8.2
11.6
15.9
9.6
8.0
..
16.3
50.4
..
11.5
20.9
..
20.6
14.6
13.4
24.2
..
..
14.6
..
8.7
12.2
13.8
..
21.0
13.9
27.0
19.8
..
11.4
13.1
13.8
13.3
13.9
11.4
..
18.0
13.1
15.7
Annual average
1980–89 1990–99 2000–09
16.5
15.6
15.6
31.5
12.7
24.3
15.6
9.3
10.0
13.1
15.6
11.3
28.6
9.0
17.7
16.5
..
27.4
..
11.2
18.3
29.1
9.0
11.6
18.9
18.3
23.3
22.0
9.8
17.5
12.3
30.6
12.6
13.8
27.9
11.9
..
13.0
..
19.3
33.1
7.7
17.6
17.4
11.1
21.5
..
16.9
9.9
23.0
20.1
16.6
17.2
16.2
..
16.6
16.5
16.5
16.8
14.4
14.4
40.7
10.5
26.7
22.5
17.0
10.6
17.0
13.9
8.1
20.3
9.9
18.1
11.9
31.8
25.1
39.7
9.8
13.2
13.8
11.7
8.2
8.4
15.8
33.6
..
7.9
16.6
12.7
14.5
14.0
9.7
31.0
14.6
..
11.5
..
15.0
29.0
10.6
..
19.4
6.1
17.2
14.8
12.8
11.1
17.7
17.6
15.2
16.6
10.9
24.3
17.0
16.0
16.1
16.3
13.5
13.5
..
12.9
21.4
22.3
22.9
9.9
18.6
9.8
8.4
14.7
7.9
14.5
8.1
28.0
3.3
45.4
12.6
9.7
15.3
11.2
7.6
13.1
17.0
40.2
12.9
9.5
15.0
9.4
22.5
14.0
10.7
21.5
12.2
..
15.0
..
11.3
20.8
14.3
..
19.2
13.0
18.1
16.3
10.0
14.1
11.6
14.0
13.8
13.3
11.9
14.4
18.3
15.0
15.1
a. Provisional.
22
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.16
Household final consumption
expenditure
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
58.9
..
71.6
..
97.7
52.0
98.0
91.4
68.6
..
93.7
..
79.2
81.5
46.8
62.8
..
..
..
..
26.1
63.0
83.9
..
73.3
62.1
130.2
66.1
89.3
69.9
87.4
58.2
75.6
96.7
44.2
75.1
..
83.3
..
73.1
44.2
90.7
97.3
47.8
81.9
71.8
..
54.5
..
55.2
67.7
61.3
41.7
69.2
..
66.8
61.5
60.0
65.3
72.5
72.5
35.8
86.8
33.2
73.5
94.5
66.6
93.4
85.7
97.6
78.7
79.1
62.4
71.9
78.9
80.3
..
77.2
49.7
75.6
85.2
66.9
86.9
62.8
123.3
..
86.4
71.5
79.8
69.2
63.4
92.3
51.2
83.8
..
83.7
..
79.2
52.0
83.5
..
57.1
86.1
80.4
80.9
71.1
91.9
64.4
63.1
64.1
56.8
72.6
48.4
64.6
63.6
64.7
67.7
73.0
73.0
..
80.7
36.7
73.3
85.9
72.2
101.1
87.4
74.4
88.7
88.7
51.8
70.8
65.2
16.1
90.6
78.8
41.7
78.0
81.5
70.3
..
71.3
88.6
94.7
81.9
84.4
78.3
74.9
60.9
86.3
67.5
83.7
..
85.8
..
77.9
52.9
88.1
..
61.8
73.5
66.6
68.6
84.8
77.1
72.6
79.8
58.5
40.4
73.0
39.5
57.3
63.1
63.5
67.7
72.1
72.1
..
80.9
38.4
76.6
84.9
71.4
80.9
89.5
70.6
94.2
87.8
32.8
71.7
66.0
18.2
88.6
78.2
36.2
74.2
80.5
74.6
..
71.3
88.3
90.3
84.5
87.5
81.4
81.2
63.7
81.4
62.8
83.6
..
80.3
..
78.4
57.0
87.2
..
62.9
69.5
70.5
67.9
85.8
76.0
62.0
81.8
58.1
38.5
71.7
44.2
57.1
63.4
63.4
68.0
72.6
72.6
..
78.1
34.5
72.8
96.6
72.0
75.2
86.6
59.8
98.8
85.8
35.0
74.5
64.2
13.6
90.0
85.1
33.3
77.6
81.0
74.8
..
73.2
88.7
86.4
86.2
91.1
79.1
92.3
68.7
83.2
60.9
75.1
..
79.8
..
76.3
75.6
82.2
..
63.1
62.8
73.2
68.4
87.0
73.7
68.5
92.0
56.5
33.6
71.6
40.2
57.5
63.3
62.8
68.3
73.3
73.3
..
..
40.7
75.2
91.1
71.5
72.9
87.5
58.7
100.6
92.8
42.8
72.0
59.9
11.3
81.3
86.4
35.6
70.7
82.6
78.0
..
74.5
83.2
123.1
82.0
84.2
75.3
63.9
70.5
80.5
60.0
..
..
80.1
..
79.6
72.1
78.6
..
63.1
64.1
73.2
71.4
..
77.8
58.3
103.6
53.5
32.2
70.6
22.5
57.5
63.7
61.5
67.8
72.8
72.8
..
..
42.8
..
..
72.2
71.8
95.9
69.2
101.2
80.9
33.3
76.8
57.5
10.8
86.2
85.5
35.9
77.4
84.6
83.6
..
74.0
88.4
228.0
77.1
67.0
76.8
70.4
70.3
81.9
56.9
..
..
80.0
..
81.4
85.7
82.0
..
62.7
57.8
72.7
68.1
..
78.3
59.0
98.2
54.5
31.2
72.4
24.8
58.4
63.8
61.7
68.1
..
74.7
..
..
47.9
..
..
..
70.0
94.4
60.2
104.8
80.4
39.6
73.6
..
24.5
..
89.9
32.9
78.4
86.8
80.5
..
77.2
81.3
202.3
78.8
73.8
..
75.6
74.3
86.3
58.1
..
..
78.3
..
86.7
80.7
85.8
..
61.9
57.4
76.6
69.7
..
73.5
65.9
120.5
54.0
30.4
72.3
22.9
58.1
63.2
61.4
66.9
..
74.0
..
..
62.8
..
..
..
67.2
92.9
78.5
105.8
74.4
42.2
72.2
..
24.3
..
87.7
41.1
77.8
81.7
75.2
..
75.9
78.8
..
79.7
61.9
..
72.1
74.6
84.4
61.9
..
..
81.1
..
83.3
71.9
84.0
..
60.4
66.7
72.8
62.3
..
76.1
61.3
113.1
62.9
40.6
76.2
..
57.0
63.4
65.2
Annual average
1980–89 1990–99 2000–09
63.3
72.5
72.4
44.5
89.7
40.4
86.0
87.5
65.8
89.1
85.5
96.8
75.9
80.0
50.3
63.9
..
..
..
78.4
37.4
64.4
86.2
71.8
82.0
63.3
146.2
75.8
87.2
69.8
88.1
66.3
67.1
92.3
61.3
80.8
..
82.0
..
76.4
42.7
83.2
100.6
54.2
84.8
74.7
..
70.8
87.2
62.9
63.4
63.1
51.3
68.3
..
66.7
60.8
63.2
68.0
74.1
74.1
42.6
85.7
34.5
68.5
88.3
70.9
88.6
82.4
92.5
84.6
81.3
53.1
70.3
73.8
61.2
90.0
80.5
43.2
78.8
80.8
73.5
90.1
69.6
104.0
..
87.9
80.0
79.7
83.0
61.9
93.2
56.3
82.7
..
94.0
..
79.6
49.3
86.6
..
61.2
84.3
80.8
82.3
80.5
84.6
73.3
65.2
65.6
53.3
75.0
58.1
65.3
61.7
66.9
68.0
73.2
73.4
..
81.3
42.1
75.2
89.4
71.4
84.0
88.2
77.9
96.4
86.0
37.3
72.5
66.3
17.1
83.8
81.6
37.1
76.0
82.9
77.3
100.1
74.4
86.1
125.4
81.3
79.5
78.4
76.6
66.4
83.3
61.5
81.9
..
82.6
..
79.8
65.9
87.4
..
62.3
68.7
72.6
70.0
88.3
76.4
70.3
89.9
58.3
37.5
73.3
39.0
58.0
62.8
63.5
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
23
Table
2.17
Final consumption expenditure
plus discrepancy
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
74.7
..
88.3
..
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
152.0
85.2
101.4
89.2
98.9
103.5
89.6
108.9
61.6
85.4
..
95.8
..
97.9
72.9
99.1
112.9
62.1
97.9
98.8
..
76.8
100.4
80.7
86.2
77.2
56.9
84.8
..
85.1
76.0
75.8
82.9
88.3
88.3
70.3
97.8
57.4
94.6
105.4
79.3
108.1
100.6
107.7
103.2
90.7
76.2
88.7
110.4
120.1
..
90.4
63.1
89.3
94.5
77.8
97.2
81.5
149.1
..
94.5
86.6
93.6
95.1
77.0
105.8
81.8
98.8
..
93.8
..
97.6
79.7
91.3
112.5
76.8
91.8
94.7
98.7
85.3
99.4
83.4
82.5
79.2
72.9
83.9
72.8
80.1
80.0
81.2
84.0
86.6
86.6
80.8
94.0
59.0
95.5
108.7
82.2
115.8
98.4
82.0
103.4
95.0
69.1
79.0
94.7
19.9
140.9
92.3
51.8
88.9
93.0
78.5
..
89.5
125.9
103.2
91.1
96.8
86.7
105.0
75.1
96.5
89.7
95.0
..
99.6
..
91.2
78.5
103.7
..
81.0
84.3
81.9
83.9
94.7
92.8
87.0
97.7
72.8
55.1
85.7
53.2
75.5
78.8
79.0
84.1
85.8
85.8
74.9
94.5
59.5
98.2
111.0
81.5
101.5
100.0
75.5
108.5
96.0
47.8
80.0
95.7
21.1
141.5
91.2
45.4
91.1
92.7
81.6
..
89.2
125.7
100.7
91.5
100.0
91.4
103.1
78.0
92.3
83.2
96.1
..
98.6
..
92.1
85.3
100.4
..
82.2
81.3
86.5
84.8
95.5
89.9
80.1
102.8
72.3
52.3
84.4
57.3
75.8
78.8
78.8
84.3
85.8
85.8
62.1
93.1
56.9
95.2
123.1
81.9
95.6
99.9
64.9
112.3
94.1
48.0
82.8
91.4
16.3
127.2
97.4
41.7
96.0
96.3
81.7
..
90.5
127.9
97.6
95.1
105.5
89.0
115.0
83.5
93.5
80.2
86.6
..
98.0
..
85.9
96.9
95.9
..
82.5
81.0
88.8
86.0
98.5
88.3
78.2
107.6
70.1
45.1
84.3
51.9
76.8
78.6
77.9
84.1
85.4
85.4
50.9
93.1
59.6
97.2
119.9
81.1
95.0
98.6
63.6
114.8
100.6
56.7
80.4
87.9
13.9
117.2
98.5
44.0
88.8
93.9
86.1
..
91.9
123.6
134.6
90.7
98.8
85.2
81.4
84.7
91.2
79.4
..
..
98.2
..
89.3
91.9
92.4
..
82.8
81.4
88.5
89.0
..
91.9
68.5
109.8
66.5
43.4
82.9
33.2
76.0
78.5
76.2
83.3
84.8
84.8
55.0
93.9
62.2
..
..
81.5
94.2
98.5
79.5
115.4
91.2
50.4
85.4
82.6
13.1
117.7
95.8
44.7
93.4
96.2
90.3
..
92.0
127.1
242.5
89.4
81.1
87.0
92.0
83.4
93.7
77.6
..
..
96.5
..
91.4
101.7
93.9
..
81.7
73.3
87.3
87.4
..
91.2
69.5
101.6
67.2
42.5
83.7
36.4
76.6
78.0
76.0
83.9
86.7
86.7
58.9
92.9
67.7
..
..
..
90.8
101.0
72.6
120.1
91.4
51.6
82.1
..
27.2
..
99.6
41.1
93.9
98.0
89.7
..
93.9
125.3
221.5
90.1
91.1
..
94.4
87.5
98.4
78.6
..
..
93.0
..
96.4
94.0
98.3
..
81.1
73.2
100.2
89.7
..
84.7
74.9
122.6
66.3
43.3
83.2
32.2
75.3
77.6
75.7
84.5
87.5
87.5
79.2
89.3
87.0
..
..
..
88.0
97.3
94.1
121.1
82.3
54.5
80.8
..
27.8
..
95.9
52.7
93.7
91.3
83.1
..
92.2
129.1
..
91.1
82.8
..
92.6
89.2
97.8
86.1
..
..
95.8
..
92.0
84.1
97.7
..
81.4
80.6
99.8
82.1
..
87.5
74.4
126.9
76.2
54.5
87.6
..
74.9
76.5
80.9
Annual average
1980–89 1990–99 2000–09
79.9
88.1
88.2
76.0
102.4
64.7
101.6
96.9
75.8
102.2
101.1
108.1
104.5
89.1
68.1
80.4
..
..
..
89.5
55.7
93.5
95.2
83.4
100.9
81.7
169.5
97.8
97.1
87.3
100.4
96.9
79.7
106.2
89.2
92.7
..
95.0
..
95.7
75.9
90.9
106.3
71.5
95.8
96.3
..
87.7
97.7
86.0
83.5
79.7
68.5
84.5
..
83.3
77.3
79.8
84.6
88.3
88.3
78.0
96.2
61.2
91.0
105.2
81.5
105.6
96.3
100.5
104.9
91.2
71.2
82.2
106.4
86.3
129.7
90.3
56.4
92.6
92.5
81.7
98.5
85.4
137.6
..
95.8
96.6
92.4
97.6
75.9
102.9
87.3
97.3
..
105.5
..
94.6
78.3
97.2
112.5
80.6
90.4
98.0
97.1
93.3
95.7
91.0
82.9
80.8
69.9
85.8
82.4
82.2
77.7
82.9
84.0
86.3
86.3
68.1
93.5
63.5
97.4
112.3
81.2
102.6
98.0
86.2
111.1
93.9
51.7
80.6
94.3
20.5
129.2
94.3
46.8
91.2
94.1
84.9
113.2
91.3
126.4
138.4
90.8
94.6
87.8
99.1
80.4
94.0
82.9
94.1
..
97.6
..
91.1
86.7
101.6
..
81.5
81.6
90.6
86.3
98.2
90.5
81.9
103.9
72.1
50.9
85.2
53.4
76.3
77.8
78.6
a. Provisional.
24
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.18
Final consumption expenditure
plus discrepancy per capita
Current prices
($)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
450
362
375
..
420
790
301
224
581
..
382
..
406
476
605
962
..
..
..
..
2,472
368
383
..
134
366
506
425
477
178
246
481
1,054
316
1,319
362
..
214
..
608
1,667
335
106
1,818
364
889
..
314
99
543
791
853
1,281
438
..
819
1,041
522
490
355
365
677
376
1,609
333
210
723
1,034
511
307
593
229
872
760
892
418
..
226
4,057
316
372
338
232
299
503
..
258
172
262
488
1,933
193
1,357
310
..
339
..
741
4,196
145
156
2,444
421
1,222
165
354
241
347
693
1,104
1,789
626
4,823
834
1,206
601
487
323
330
721
455
2,661
317
93
658
1,997
283
240
583
97
741
588
758
1,019
263
111
2,383
227
338
305
..
392
609
135
299
182
335
477
3,446
228
2,288
213
..
212
..
586
6,688
217
..
2,955
404
1,328
265
292
219
339
442
1,179
1,176
957
2,250
1,261
2,001
600
584
364
372
918
503
3,294
378
103
738
1,996
315
344
669
110
665
657
806
1,869
308
126
2,429
247
384
331
..
411
767
144
233
198
386
549
4,036
259
2,788
232
..
234
..
674
7,234
224
..
3,860
465
1,770
287
337
274
379
467
1,270
1,374
879
3,298
1,432
2,231
692
646
404
412
1,144
507
3,174
376
133
763
2,001
329
343
724
113
855
704
805
2,204
333
160
2,636
290
471
260
..
474
843
155
272
213
399
716
4,219
295
2,898
225
..
281
..
663
10,330
233
..
4,319
573
1,994
312
347
277
477
482
1,362
1,405
980
3,859
1,499
2,271
757
709
466
475
1,346
543
3,599
394
145
799
2,171
349
376
754
141
1,258
710
825
2,129
324
195
3,010
287
855
258
..
563
870
237
276
219
413
718
4,401
303
3,095
..
..
332
..
723
10,510
249
..
4,526
750
2,078
318
..
308
609
458
1,465
1,525
1,133
3,099
1,618
2,398
824
792
543
554
1,855
621
4,068
..
..
903
2,550
396
525
854
146
1,184
841
839
2,569
338
234
3,640
376
1,036
395
..
662
987
491
353
194
501
832
4,973
344
3,271
..
..
382
..
871
12,276
288
..
4,845
843
2,238
356
..
354
644
409
1,724
1,703
1,365
4,236
1,846
2,716
936
867
663
676
2,753
717
4,774
..
..
..
2,788
463
556
989
165
1,683
934
..
7,637
..
320
4,121
465
1,197
345
..
727
974
492
444
250
..
1,054
6,422
434
3,309
..
..
449
..
1,040
10,010
346
..
4,593
1,028
2,436
437
..
387
854
418
2,060
2,152
1,662
4,764
2,117
3,070
1,055
864
654
666
3,232
666
5,273
..
..
..
2,696
441
574
984
132
1,417
894
..
4,274
..
330
3,954
403
1,002
339
..
680
986
..
399
256
..
852
6,009
418
3,675
..
..
500
..
941
7,305
333
..
4,711
1,043
2,527
401
..
429
737
570
2,240
2,197
1,988
..
2,140
2,902
1,082
Annual average
1980–89 1990–99 2000–09
449
335
345
581
332
830
260
215
663
809
360
221
394
296
681
681
..
..
..
200
2,570
290
350
323
171
299
458
437
320
150
205
450
1,103
275
1,435
274
..
270
..
550
2,170
248
138
2,094
496
753
..
271
231
418
704
957
1,697
529
..
641
961
541
469
306
314
469
343
1,844
238
170
631
1,201
352
232
508
155
620
630
834
410
240
160
2,723
324
358
382
208
313
581
..
245
179
244
560
2,486
187
1,691
216
..
283
..
580
5,142
188
156
2,782
325
1,469
197
308
220
340
543
1,132
1,217
809
5,111
986
1,467
586
612
424
432
1,343
503
3,306
311
114
672
2,057
332
361
684
117
915
677
793
2,371
281
180
2,785
310
605
315
175
501
740
254
301
200
340
648
4,210
290
2,626
194
..
299
..
683
8,277
249
..
3,635
610
1,770
315
290
292
498
466
1,497
1,463
1,242
3,590
1,497
2,242
756
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
25
Table
2.19
Gross fixed capital formation
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
22.6
..
18.8
..
..
34.5
14.1
13.9
20.0
..
6.9
..
28.5
8.8
35.8
24.4
..
..
..
..
26.7
..
6.1
..
28.2
18.3
35.6
..
14.4
22.2
15.5
..
23.2
7.6
27.2
25.5
..
12.2
..
14.6
36.5
14.9
43.1
25.9
10.8
35.0
..
28.2
..
18.2
14.1
26.8
33.8
24.6
..
22.2
28.3
24.5
18.2
17.4
17.4
11.1
13.4
32.4
17.7
15.2
17.3
22.9
11.4
4.8
11.9
12.8
17.2
8.5
14.1
17.4
..
12.9
21.4
22.3
14.4
22.9
29.9
20.6
57.0
..
14.8
20.1
23.0
20.0
30.6
22.1
21.2
11.4
..
14.6
..
18.0
23.0
9.6
14.9
19.1
10.4
14.5
25.8
25.3
12.7
13.5
18.2
24.5
27.0
26.9
13.9
24.0
24.4
21.1
17.1
18.5
18.5
12.7
18.1
26.0
17.5
10.6
18.1
18.7
6.1
48.6
10.3
12.2
25.5
9.7
14.4
41.6
28.1
21.8
24.0
19.2
22.9
19.8
..
15.8
34.0
9.4
17.9
14.1
24.2
25.9
22.7
22.3
19.1
14.0
..
17.9
..
21.2
10.4
13.9
..
15.5
14.1
19.1
20.0
20.9
20.7
24.1
13.8
19.0
24.0
16.3
9.8
25.1
23.4
17.9
17.4
18.6
18.6
9.1
17.5
24.8
19.3
13.0
18.3
37.4
6.2
22.7
9.4
12.8
21.9
9.8
21.5
40.5
22.3
25.5
24.4
24.8
28.4
19.7
..
16.3
27.2
13.2
23.4
16.2
21.0
46.4
21.6
18.6
18.6
15.8
..
15.0
..
22.7
12.7
10.5
..
16.0
17.2
16.2
21.2
21.2
20.0
23.1
5.1
19.7
24.1
16.4
13.9
26.3
22.6
18.4
18.2
19.4
19.4
8.1
18.9
24.5
19.4
10.5
17.7
37.3
8.9
16.7
9.3
14.2
21.9
9.7
19.0
37.6
18.5
23.0
21.3
..
29.0
18.6
..
18.7
25.7
16.4
22.2
20.2
22.6
44.8
21.4
18.7
18.6
18.5
..
15.8
..
29.7
24.7
17.0
..
16.8
24.0
15.4
22.5
22.3
22.2
22.5
2.1
20.4
22.3
17.9
15.8
27.5
22.2
19.2
18.9
19.3
19.3
11.3
18.2
21.6
20.8
16.4
16.7
40.6
9.2
13.2
9.6
13.0
24.4
9.3
29.6
31.4
12.6
24.2
25.9
..
21.6
16.6
..
19.1
24.8
..
25.3
22.7
22.9
29.5
24.3
17.7
21.6
..
..
16.0
..
28.2
26.1
15.2
..
18.3
25.1
14.1
23.8
..
21.0
22.6
2.3
21.7
22.9
18.7
20.7
28.1
23.5
20.1
20.3
20.4
20.4
14.0
21.4
23.9
..
..
17.1
43.8
8.9
17.0
11.2
19.5
26.0
8.7
37.5
33.3
10.6
23.5
25.9
..
20.1
13.9
..
19.4
25.8
..
32.4
24.0
22.4
22.4
25.1
16.1
23.7
..
..
18.0
..
30.9
29.5
13.2
..
20.2
26.5
14.0
25.0
..
21.9
24.1
5.4
24.2
26.0
20.9
25.0
31.2
23.2
22.1
21.7
21.0
21.0
16.0
20.7
23.3
..
..
..
48.4
11.6
23.9
14.3
23.9
21.8
10.1
..
28.2
..
19.8
24.4
..
21.5
15.6
..
19.7
28.8
..
40.3
23.3
..
27.8
24.6
15.7
25.7
..
..
22.8
..
30.2
25.4
14.7
..
22.5
22.7
15.3
26.3
..
22.7
22.6
3.8
25.7
26.3
22.3
27.9
33.0
25.0
23.6
22.3
22.0
22.0
14.8
25.0
28.2
..
..
..
53.8
10.6
32.7
12.4
29.8
24.3
11.2
..
36.6
..
22.4
28.4
..
19.6
21.6
..
20.1
31.5
..
32.6
21.8
..
25.2
26.2
21.0
24.7
..
..
21.8
..
27.9
24.2
15.1
..
22.6
21.8
16.9
29.3
..
23.5
22.1
2.5
25.1
33.0
19.0
..
30.7
25.9
23.5
Annual average
1980–89 1990–99 2000–09
20.1
16.6
17.1
14.2
14.8
29.0
17.4
16.1
21.1
26.9
10.2
4.4
24.3
11.4
32.5
15.8
..
..
..
15.7
33.8
18.9
7.9
16.4
32.0
18.8
40.3
..
10.8
15.8
17.2
26.6
21.2
12.2
18.6
14.2
..
14.4
..
17.4
25.6
11.4
26.9
23.1
12.4
25.4
..
19.0
9.3
12.4
16.0
27.9
31.9
27.8
..
23.1
27.5
23.5
17.1
17.8
17.8
23.2
15.7
27.2
21.2
9.0
14.5
29.6
11.2
11.0
14.6
8.0
24.9
11.4
11.1
59.5
26.1
16.5
25.4
20.1
19.7
20.0
25.9
17.6
64.4
..
12.4
15.2
22.5
13.6
26.9
20.7
21.0
9.0
..
14.5
..
19.9
29.2
7.2
14.9
16.3
10.6
16.7
21.5
15.6
15.9
12.4
19.0
21.3
26.2
20.4
12.7
22.2
25.3
19.0
18.5
19.3
19.3
12.7
19.6
24.6
18.2
9.9
18.0
33.9
8.8
29.2
10.8
14.3
23.5
10.1
18.6
41.5
22.8
22.6
24.6
20.0
23.2
17.4
12.0
18.1
31.2
9.7
24.2
18.7
23.4
28.4
23.3
21.1
20.9
14.2
..
18.2
..
26.1
24.5
12.3
..
17.7
18.8
17.1
22.0
20.4
21.0
21.5
6.9
21.6
24.6
18.6
16.9
27.8
24.3
19.9
a. Provisional.
26
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.20
Gross general government fixed capital formation
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
6.6
..
..
..
..
0.0
..
12.8
4.4
..
3.7
..
23.2
5.1
..
11.4
..
..
..
..
5.3
..
..
..
..
0.0
9.9
..
..
17.5
..
..
8.4
7.6
15.7
20.4
..
12.2
..
4.7
..
5.3
..
6.4
6.9
11.9
..
20.2
..
..
1.8
..
11.0
..
..
..
15.0
..
5.6
7.2
7.2
..
7.4
8.6
9.7
12.5
5.5
10.3
4.7
..
5.2
4.0
5.6
3.6
9.1
10.5
..
4.0
3.9
7.4
7.5
9.7
27.4
9.7
26.2
..
7.9
7.7
10.5
6.2
11.4
12.0
8.2
7.4
..
5.9
..
4.1
8.2
3.9
..
3.9
..
4.5
10.5
7.3
6.2
6.2
3.4
10.8
8.2
14.7
..
4.8
8.7
7.8
5.2
6.0
6.0
7.6
6.1
10.6
6.3
8.3
2.3
9.8
2.2
12.5
5.4
2.7
6.7
2.7
6.7
9.9
20.4
12.8
3.7
5.7
8.9
3.9
..
4.2
9.6
0.0
7.8
..
6.9
12.0
8.9
10.5
6.4
8.3
..
5.1
..
6.2
1.7
4.8
..
4.3
2.9
13.0
5.1
3.7
5.1
11.4
2.1
8.1
10.8
8.3
7.9
3.8
..
6.4
5.4
6.5
6.5
4.9
5.4
8.5
7.2
10.7
2.6
7.7
2.0
7.8
4.4
2.8
6.5
2.8
7.7
13.1
17.0
15.7
4.2
10.9
12.4
3.7
..
4.3
8.1
0.0
10.0
..
7.5
9.1
6.6
10.7
6.3
5.1
..
8.9
..
6.7
3.1
4.5
..
4.3
5.0
10.7
7.1
5.3
4.9
8.7
5.1
8.9
10.5
8.7
12.3
3.8
..
6.9
5.4
6.3
6.3
5.0
6.7
7.3
7.4
8.8
2.5
9.0
4.0
7.8
4.5
3.7
6.2
2.7
9.3
10.3
16.8
14.7
4.2
9.0
12.0
2.8
..
3.8
8.1
0.0
8.7
..
7.7
8.1
6.3
8.6
6.4
6.3
..
8.7
..
10.0
4.6
5.7
..
4.3
5.8
9.8
8.1
2.8
5.0
7.0
2.1
9.5
10.8
9.3
14.1
3.7
9.8
7.2
5.8
6.6
6.6
8.9
4.6
6.1
8.0
..
2.4
9.3
3.7
8.1
5.0
3.1
9.5
3.1
7.5
15.1
11.5
16.7
4.8
7.9
8.8
2.6
..
4.9
7.6
..
10.5
..
8.6
..
7.7
11.8
6.8
..
..
7.5
..
9.7
8.1
5.1
..
5.0
6.7
8.7
7.5
3.6
4.6
4.1
2.3
9.5
12.0
8.0
16.7
3.6
..
7.4
6.5
6.8
6.8
11.7
7.5
7.8
..
..
2.4
10.9
2.7
7.3
6.1
8.8
10.4
2.6
12.2
16.9
9.4
16.8
4.5
3.7
8.5
2.3
..
3.9
10.4
..
7.0
..
8.4
..
5.5
11.7
2.9
..
..
8.7
..
11.2
4.5
3.5
..
6.1
9.5
8.0
7.5
2.0
4.9
4.1
1.4
10.9
16.5
7.8
19.8
3.6
..
8.4
7.6
7.3
7.3
14.1
5.8
12.5
..
..
..
10.4
4.5
7.9
9.3
12.6
8.9
3.0
..
16.8
..
14.0
4.6
..
9.4
3.5
6.5
4.4
11.0
..
7.1
..
..
..
4.2
11.6
3.4
..
..
11.0
..
10.0
3.3
6.2
..
7.9
6.5
9.8
8.0
..
4.4
5.2
0.3
11.3
16.1
7.9
22.0
4.6
..
9.2
8.7
8.3
8.3
12.4
9.6
15.1
..
..
..
11.0
3.7
10.9
4.7
23.8
10.7
3.0
..
20.6
..
16.5
5.2
..
8.0
4.6
9.6
5.6
14.2
..
3.1
..
..
..
6.7
13.1
5.3
..
..
11.1
..
10.1
3.3
7.7
..
9.2
5.5
10.6
8.8
..
6.1
4.3
0.8
5.5
0.0
8.0
..
5.9
..
7.4
Annual average
1980–89 1990–99 2000–09
6.1
6.6
6.3
..
9.1
9.7
10.4
13.8
6.9
19.3
5.5
3.8
18.7
4.4
11.1
7.1
..
..
..
4.9
6.7
10.4
6.3
7.5
33.3
0.8
17.2
..
6.9
9.5
10.2
7.6
7.4
9.5
10.7
11.2
..
12.1
..
3.7
12.0
4.0
..
5.7
4.3
8.0
..
11.2
4.4
..
2.9
13.0
13.8
16.9
..
7.1
14.1
8.9
4.8
6.5
6.5
7.8
7.5
11.7
10.5
9.3
2.9
20.3
6.2
7.4
7.0
1.7
6.4
5.6
6.1
6.9
17.6
6.6
6.5
7.8
11.1
6.1
20.2
7.0
18.7
..
6.9
9.2
10.1
5.0
9.2
12.1
8.2
5.6
..
7.2
..
4.5
9.9
3.8
..
2.8
0.7
5.4
6.0
3.7
5.6
6.8
3.0
10.6
7.2
14.5
..
4.2
11.5
7.2
5.8
6.5
6.5
8.4
6.8
10.0
7.0
6.9
2.3
10.4
3.6
9.2
5.3
5.9
8.5
2.8
6.6
12.4
17.5
14.7
4.3
7.6
9.8
3.8
9.8
4.4
10.1
0.0
7.3
10.2
7.7
9.1
6.6
11.3
5.6
7.0
..
7.9
..
7.9
7.2
5.1
..
5.0
5.0
9.9
6.3
3.0
5.3
7.8
1.9
8.9
10.3
8.6
14.9
4.3
11.1
7.2
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
27
Table
2.21
Private sector fixed capital formation
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
16.4
..
..
..
..
34.5
..
1.1
15.6
..
3.2
..
5.3
3.7
..
13.0
..
..
..
..
21.4
..
..
..
..
8.2
25.7
..
..
4.7
..
..
14.9
0.0
11.4
5.1
..
..
..
9.9
..
9.5
..
19.5
3.8
23.1
..
8.0
..
..
12.3
..
22.8
..
..
16.7
13.3
..
12.9
10.7
10.7
1.7
6.0
23.8
8.0
2.7
11.9
12.6
6.7
..
6.7
8.9
11.6
4.9
5.1
6.9
..
8.9
17.6
14.9
6.9
8.8
8.4
10.9
30.8
..
6.9
12.4
12.4
13.7
19.2
10.1
13.0
4.0
..
8.7
..
13.9
14.8
5.7
..
15.3
..
10.1
15.3
18.0
6.5
7.2
14.8
15.4
18.8
12.3
..
19.2
15.6
14.0
11.8
12.4
12.4
5.1
12.0
15.4
11.1
2.3
15.8
8.9
3.9
36.1
4.9
9.5
18.8
7.0
7.7
31.7
7.7
9.0
20.2
13.5
14.0
15.9
..
7.8
24.4
4.8
10.1
7.4
17.3
13.9
13.9
11.8
20.1
5.7
..
12.8
..
15.0
8.7
9.0
..
11.2
11.2
6.0
14.9
17.2
15.6
12.7
11.7
10.5
13.2
8.1
1.9
21.3
..
11.3
11.8
11.9
11.9
4.2
12.1
16.3
..
2.3
15.7
29.7
4.1
14.9
5.0
10.0
15.4
7.1
13.8
27.4
5.3
9.7
20.2
13.9
16.0
16.1
..
7.5
19.2
4.2
13.4
7.1
13.5
37.3
15.0
8.0
15.7
10.7
..
6.2
..
16.0
9.7
5.9
..
11.7
12.2
5.5
14.2
15.9
15.1
14.3
0.0
10.5
13.6
7.7
1.6
22.4
..
11.3
12.5
12.5
12.5
3.0
12.2
17.3
..
1.7
15.2
28.4
4.9
8.9
4.8
10.5
15.7
7.0
9.7
27.4
1.8
8.3
17.1
..
17.0
15.8
..
6.7
17.5
4.3
13.5
13.0
15.0
36.7
15.1
10.1
16.2
12.2
..
7.0
..
19.7
20.1
11.3
..
12.5
18.2
5.6
14.4
19.5
17.3
15.5
0.0
10.9
11.5
8.6
1.7
23.8
12.3
11.8
13.5
13.6
13.6
2.4
13.6
15.5
..
..
14.3
31.3
5.6
5.1
4.7
9.9
14.9
6.3
22.0
16.2
1.1
7.6
21.1
..
12.8
14.0
..
25.4
17.3
..
14.7
15.0
14.3
..
16.6
5.8
18.4
..
..
8.5
..
18.5
18.1
10.1
..
13.4
18.4
6.7
16.3
..
16.4
18.5
0.0
12.1
11.0
10.7
4.0
24.5
..
12.9
13.7
13.3
13.3
2.3
13.9
16.1
..
..
14.7
32.9
6.2
9.7
5.0
10.7
15.6
6.1
25.2
16.4
1.2
6.7
21.5
..
11.6
11.5
..
15.5
15.5
..
25.4
9.2
14.0
..
19.6
4.4
16.1
..
..
9.3
..
19.7
25.0
9.7
..
14.1
17.0
6.0
17.5
..
16.9
20.0
4.0
13.5
9.5
13.1
5.2
27.6
..
13.6
14.2
13.7
13.7
1.9
14.9
21.3
..
..
12.5
38.0
7.1
16.0
5.0
11.3
12.9
7.1
..
11.4
..
5.9
19.8
..
12.1
12.1
..
15.3
17.8
..
33.2
13.9
..
..
20.4
4.1
14.7
..
..
11.8
..
20.2
22.2
8.6
..
14.6
16.2
5.6
18.3
..
18.3
17.4
3.5
14.5
10.2
14.4
5.9
28.4
..
14.3
13.4
13.3
13.3
2.4
15.4
8.9
..
..
12.4
42.7
6.9
21.8
7.7
6.1
13.5
8.3
..
16.1
..
5.9
23.2
..
11.6
17.0
..
14.5
17.3
..
29.4
14.9
..
..
19.5
7.9
15.6
..
..
10.6
..
17.8
20.9
7.4
..
13.4
16.3
3.0
20.5
..
17.5
17.8
1.7
19.9
33.0
10.9
..
24.8
23.2
16.1
Annual average
1980–89 1990–99 2000–09
14.4
9.8
9.8
9.2
4.5
19.4
8.8
2.3
14.2
7.6
4.7
0.6
5.5
7.1
11.4
8.7
..
..
..
12.8
27.2
8.6
3.8
8.9
10.0
10.7
23.1
..
3.6
6.3
9.9
19.0
13.8
2.7
7.8
3.0
..
7.8
..
13.7
10.1
7.3
..
17.4
8.9
17.3
..
7.8
5.4
4.9
13.1
12.8
18.1
9.3
..
16.1
13.5
13.3
12.4
11.5
11.5
16.5
8.3
15.5
10.8
–0.3
11.7
9.3
5.0
4.3
7.7
6.3
18.5
6.2
5.8
52.6
8.6
9.9
18.9
12.3
8.6
11.7
7.7
9.8
46.8
..
5.5
6.0
12.4
13.9
17.7
8.6
12.8
3.4
..
7.2
..
15.4
19.3
3.3
..
13.5
9.9
11.3
15.6
11.8
10.3
5.7
16.0
12.0
19.0
5.9
..
18.0
13.8
12.2
12.6
12.6
12.6
4.3
12.8
15.3
10.4
1.9
15.0
23.5
5.3
20.0
5.4
8.4
15.1
7.3
11.9
29.1
5.3
7.9
20.4
11.9
13.4
13.6
1.1
11.5
21.1
3.5
16.9
9.6
15.7
22.9
16.7
9.8
15.4
7.2
..
10.3
..
18.2
17.2
7.2
..
12.7
13.8
7.0
15.7
17.3
15.8
13.7
5.0
12.8
14.4
10.0
3.2
23.5
16.4
12.7
a. Provisional.
28
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.22
External trade balance (exports minus imports)
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
Annual average
1980–89 1990–99 2000–09
1.2
–4.6
–8.6
..
–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
–89.1
–0.1
–16.4
–14.0
–14.4
–29.8
–10.2
–16.5
7.8
–13.5
10.2
–11.9
..
–14.5
–11.2
–15.4
–55.3
8.0
–12.6
–39.4
..
–5.3
–6.6
–4.0
–3.2
–7.2
4.0
–12.4
..
–9.4
–5.4
–2.2
0.8
–2.5
–6.3
18.0
–12.0
5.3
–13.5
–19.9
2.9
–31.0
–12.9
–14.4
–22.9
0.3
7.9
4.6
–24.6
–37.4
..
–3.3
15.2
–11.7
–9.0
–2.4
–27.1
–5.6
–105.1
..
–11.4
–9.6
–16.6
–15.1
–7.2
–27.9
–15.5
–6.9
14.6
–8.5
..
–6.8
–4.3
–1.3
–28.0
5.5
–3.0
–9.9
–24.8
–11.9
–12.1
–0.7
0.1
–5.9
–1.5
–12.7
8.6
–5.4
–7.0
–2.0
–1.5
–4.3
–5.7
6.6
–12.8
11.0
–12.9
–19.3
0.3
–34.5
–4.5
–34.1
–13.7
–7.2
4.8
10.9
–9.2
20.4
–69.0
–14.1
24.3
–9.2
–15.9
–0.1
..
–6.0
–58.3
–12.6
–9.0
–13.9
–10.9
–30.9
1.3
–18.7
–9.1
–9.2
2.3
–17.6
..
–12.1
11.2
–17.6
..
2.3
–4.2
–1.0
–4.2
–13.6
–13.8
–12.4
–5.7
4.6
14.4
–2.6
25.7
–2.8
–3.9
1.1
–1.3
–2.0
–5.3
16.0
–12.7
7.3
–13.5
–24.3
–0.4
–38.9
–6.2
0.2
–17.9
–8.8
29.7
9.2
–17.2
35.1
–63.8
–16.7
30.2
–21.1
–21.1
–2.3
..
–6.3
–52.2
–13.9
–14.8
–18.2
–12.4
–49.4
–2.4
–10.9
–2.3
–10.0
12.9
–13.6
..
–12.9
2.0
–10.9
..
–0.3
–3.8
–2.7
–6.4
–13.5
–10.1
–4.4
–7.3
5.6
14.4
–1.4
31.1
–5.0
–2.9
1.6
–1.3
–1.9
–5.8
29.8
–12.6
16.8
–15.6
–33.9
–1.0
–32.9
–8.8
17.2
–21.6
–8.2
29.7
7.5
–10.3
43.8
–45.7
–20.4
37.0
–22.8
–25.3
–1.3
..
–7.5
–53.8
–14.0
–17.3
–28.1
–11.7
–59.8
–6.0
–12.2
0.1
–9.2
15.5
–13.8
..
–15.6
–21.6
–12.9
..
–0.5
–9.9
–4.2
–8.9
–16.9
–10.7
–2.1
–9.2
8.2
23.4
–2.3
38.1
–5.6
–0.4
2.7
–1.9
–1.6
–5.3
37.8
–11.3
16.4
–15.3
–36.2
2.1
–35.6
–7.9
22.0
–24.4
–13.7
18.5
10.3
–17.4
53.7
–29.7
–22.7
30.1
–17.2
–15.5
–3.3
..
–9.9
–49.6
–54.6
–16.0
–24.5
–8.1
–11.0
–11.3
–8.9
–1.7
..
15.1
–14.2
..
–17.5
–18.0
–7.6
..
–2.4
–10.9
–2.6
–13.1
–19.5
–13.1
8.4
–11.4
10.1
27.1
–1.6
45.8
–5.5
–2.3
3.1
–2.4
–2.0
–5.9
31.1
–15.3
12.0
..
..
0.8
–38.0
–7.4
2.5
–26.6
–10.8
23.2
5.9
–20.1
51.6
–28.2
–19.3
29.4
–16.3
–16.3
–4.6
..
–11.0
–52.8
–162.5
–21.7
–8.1
–9.4
–14.3
–10.3
–9.8
–1.3
..
15.1
–14.6
..
–22.3
–31.2
–7.0
..
–2.9
–3.8
–1.3
–12.8
–20.5
–13.3
6.4
–9.1
6.5
23.3
–4.6
38.2
–9.1
–2.4
1.4
–3.8
–4.4
–8.4
25.1
–13.6
–0.1
..
..
–3.0
–39.2
–12.6
2.6
–34.4
–15.2
26.3
7.7
..
46.1
–18.1
–19.4
34.6
–18.6
–19.5
–5.3
..
–14.2
–54.0
–141.5
–30.3
–17.4
..
–22.2
–14.7
–14.1
–6.7
..
12.3
–15.8
..
–26.6
–19.4
–13.0
..
–3.0
0.8
–15.5
–16.4
..
–7.7
2.5
–28.3
5.5
23.4
–5.6
39.9
–13.4
–4.2
0.2
–3.7
–5.9
–9.4
6.0
–14.3
–11.0
..
..
–4.3
–41.8
–7.9
–28.0
–33.5
–12.1
21.0
8.0
..
32.5
–15.8
–18.3
18.9
–19.7
–10.8
–4.7
..
–13.1
–60.5
..
–23.7
–7.7
..
–17.8
–10.6
–18.7
–13.3
..
8.7
–17.5
..
–19.9
–8.3
–12.8
..
–0.9
–5.8
–16.7
–11.9
..
–11.2
3.4
–29.1
–4.5
4.3
–6.8
..
–10.9
–3.4
–4.0
–0.4
–4.7
–6.1
9.1
–17.5
5.3
–19.6
–13.5
0.4
–29.0
–12.1
–13.5
–33.3
–0.8
–0.5
3.2
..
–28.6
..
–5.3
9.7
–13.2
–3.1
0.3
–32.9
–4.9
–110.0
2.9
–7.7
–6.7
–17.6
–24.4
–3.3
–18.4
–7.6
–8.0
1.1
–10.3
..
–12.1
–2.3
–3.1
–35.1
5.1
–8.3
–23.5
..
–7.2
–6.2
–2.1
–0.8
–8.9
–2.5
–13.2
..
–7.4
–6.1
–3.8
–1.5
–4.6
–6.6
2.2
–12.5
9.8
–13.5
–14.4
3.7
–35.2
–7.7
–13.6
–23.0
1.2
2.9
6.5
–17.5
–45.8
–55.8
–6.8
17.7
–12.6
–12.4
–3.0
–24.5
–3.7
–101.9
–39.6
–8.2
–14.3
–14.9
–11.2
–4.1
–23.6
–10.0
–6.2
4.1
–19.9
..
–7.1
–8.6
–4.5
–28.0
2.8
–6.7
–15.2
–19.0
–9.6
–11.7
–5.6
–2.3
–3.1
1.6
–6.7
3.6
–4.9
–4.3
–2.2
–1.5
–2.9
–6.1
19.2
–13.2
8.4
–14.2
–22.3
–0.4
–36.5
–6.9
–17.1
–21.8
–8.2
24.2
9.2
–12.9
35.3
–44.9
–16.9
28.6
–14.8
–17.5
–3.0
–25.2
–9.3
–57.5
–46.7
–15.0
–15.2
–11.2
–27.5
–4.6
–15.0
–4.6
–8.8
11.4
–15.8
..
–15.6
–11.1
–14.0
..
0.3
–5.4
–7.7
–8.7
–17.7
–11.8
–4.3
–9.9
4.2
17.4
–4.1
29.1
–6.2
–3.2
0.9
a. Provisional.
b. For 1994–2000 Nigeria’s values were distorted because the official exchange rate used by the government for oil exports and oil value added was significantly overvalued.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
29
Table
2.23
Exports of goods and services, nominal
Current prices
($ millions)
1980
SUB–SAHARAN AFRICA 82,540
Excluding South Africa
54,029
Excl. S. Africa & Nigeria
33,788
Angola
..
Benin
222
Botswana
563
Burkina Faso
173
Burundi
81
Cameroon
1,880
Cape Verde
..
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
91
Liberia
613
Madagascar
539
Malawi
307
Mali
263
Mauritania
261
Mauritius
579
Mozambique
383
Namibia
1,712
Niger
617
Nigeria
18,859
Rwanda
168
São Tomé and Príncipe
..
Senegal
837
Seychelles
100
Sierra Leone
252
Somalia
200
South Africa
28,555
Sudan
806
Swaziland
405
Tanzania
..
Togo
580
Uganda
242
Zambia
1,608
Zimbabwe
1,561
NORTH AFRICA
37,505
Algeria
14,541
Egypt, Arab Rep.
6,992
Libya
..
Morocco
3,273
Tunisia
3,518
ALL AFRICA
121,315
Annual average
1980–89 1990–99 2000–09
1990
2003
2004
2005
2006
2007
2008
2009a
79,795
52,368
40,438
3,992
264
2,087
340
89
2,251
43
220
234
36
2,759
1,502
3,421
244
42
..
672
2,740
190
993
829
24
2,207
98
..
512
447
415
465
1,724
201
1,220
372
12,366
145
..
1,453
230
146
90
27,149
499
658
538
545
312
1,180
2,009
46,844
14,546
8,647
11,468
6,830
5,353
126,751
145,376
98,474
69,589
9,716
487
3,668
376
50
2,757
253
154
674
57
1,483
2,825
6,297
248
2,859
56
1,137
3,350
158
3,101
865
..
3,590
520
133
1,264
647
1,153
356
3,180
1,348
2,141
438
28,891
139
..
1,830
671
230
..
46,900
2,613
1,872
2,164
595
722
1,256
1,856
84,346
26,028
18,074
15,011
14,282
10,950
229,724
185,542
127,656
89,049
13,780
539
4,444
549
64
3,061
138
168
2,252
55
1,994
3,744
7,517
246
4,724
64
1,495
4,465
184
3,487
862
..
4,283
721
171
1,424
655
1,237
473
3,450
1,759
2,630
491
38,609
232
..
2,126
684
247
..
57,890
3,822
2,056
2,520
691
1,077
2,079
2,001
107,367
34,067
22,258
21,117
16,726
13,199
292,911
234,188
166,562
114,319
24,286
577
5,256
542
91
3,393
171
170
3,234
55
2,450
5,123
8,354
288
7,183
68
1,855
5,610
185
3,907
994
..
5,342
703
201
1,422
663
1,359
667
3,761
2,087
2,937
512
52,238
295
..
2,344
717
292
..
67,647
4,992
2,250
2,945
850
1,278
2,482
1,931
138,842
48,761
27,214
29,230
19,234
14,402
373,037
278,709
200,430
137,465
33,343
538
5,292
665
99
4,131
229
207
3,852
57
2,621
6,507
9,144
307
8,332
84
2,101
5,912
203
5,136
1,108
..
5,945
759
175
1,640
705
1,884
1,366
4,009
2,722
3,180
..
62,959
344
..
2,401
860
355
..
78,318
6,015
2,259
3,233
938
1,519
4,120
1,957
167,469
56,953
32,191
40,275
22,449
15,600
446,193
323,596
234,106
166,118
44,707
900
5,877
..
..
4,563
285
254
3,845
68
2,711
6,402
9,465
484
10,299
86
2,442
7,203
214
6,041
1,267
..
7,062
880
208
2,227
936
1,871
1,548
4,422
2,839
4,468
..
68,061
410
..
2,875
993
346
..
89,549
9,287
2,311
4,093
1,048
1,991
4,802
2,000
197,126
63,297
39,469
48,510
26,892
18,958
520,752
396,735
299,097
212,813
64,243
1,019
5,660
..
..
7,718
345
215
4,413
74
2,701
8,642
10,890
..
14,498
61
2,950
9,675
244
7,140
1,259
..
8,291
936
262
2,498
1,203
..
1,952
4,926
3,192
4,787
..
86,396
680
..
3,477
1,091
319
..
98,005
12,974
1,795
4,689
..
3,506
5,267
1,802
253,603
79,123
53,800
62,780
33,312
24,588
650,506
298,039
220,322
158,411
39,432
922
3,971
..
..
5,896
366
290
2,879
79
1,017
6,884
9,722
..
7,713
84
3,011
5,773
223
7,982
1,671
..
7,413
809
..
2,447
1,420
..
1,504
4,161
2,454
4,319
..
62,054
610
..
3,082
912
305
..
77,883
8,230
1,794
4,963
..
3,753
4,560
2,040
200,244
56,798
47,185
..
26,121
20,568
496,886
65,089
38,654
31,094
2,613
214
999
189
111
2,240
41
181
153
22
2,016
1,092
3,142
..
32
..
608
1,964
108
554
660
15
1,805
67
519
414
295
255
387
807
215
1,139
420
7,725
173
..
989
123
187
119
26,088
841
394
..
464
371
1,060
1,530
34,399
12,221
6,654
..
3,790
3,312
100,090
87,615
55,868
43,640
4,265
327
2,378
286
89
2,198
79
185
254
40
1,595
1,393
4,129
210
160
132
715
2,728
195
1,684
798
32
2,594
187
43
673
465
514
465
2,257
373
1,543
325
12,563
107
..
1,347
298
155
90
31,523
579
886
949
441
500
1,099
2,467
48,912
12,420
12,435
8,527
8,363
7,168
136,561
220,178
157,694
111,379
25,294
606
4,268
417
63
3,813
229
197
2,189
55
1,799
4,734
7,576
276
6,074
77
1,794
5,091
192
4,425
1,036
62
5,092
629
168
1,613
771
1,262
913
3,677
1,920
2,907
403
46,350
315
..
2,237
750
250
..
62,550
5,353
1,779
2,963
681
1,587
2,749
2,053
135,256
42,760
28,952
27,469
19,266
14,598
355,318
a. Provisional.
30
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.24
Imports of goods and services, nominal
Current prices
($ millions)
1980
SUB–SAHARAN AFRICA 75,861
Excluding South Africa
53,970
Excl. S. Africa & Nigeria
40,777
Angola
..
Benin
524
Botswana
705
Burkina Faso
603
Burundi
214
Cameroon
1,829
Cape Verde
..
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
475
Liberia
614
Madagascar
1,202
Malawi
480
Mali
520
Mauritania
473
Mauritius
695
Mozambique
965
Namibia
1,542
Niger
957
Nigeria
12,324
Rwanda
307
São Tomé and Príncipe
..
Senegal
1,344
Seychelles
117
Sierra Leone
421
Somalia
534
South Africa
22,073
Sudan
1,763
Swaziland
619
Tanzania
..
Togo
640
Uganda
324
Zambia
1,764
Zimbabwe
1,771
NORTH AFRICA
38,163
Algeria
12,847
Egypt, Arab Rep.
9,822
Libya
..
Morocco
5,033
Tunisia
3,987
ALL AFRICA
115,055
1990
2003
2004
2005
2006
74,537
53,674
45,400
2,147
486
1,888
758
314
1,931
148
411
485
93
2,731
1,282
2,927
355
92
..
1,069
1,837
227
1,522
892
90
2,691
666
..
864
629
817
619
1,915
888
1,584
545
8,203
364
..
1,840
246
154
346
21,016
877
768
1,595
738
834
1,203
2,002
53,024
15,472
14,109
8,996
8,227
6,220
127,845
149,688
106,770
79,350
8,801
944
2,780
928
165
2,712
529
205
1,608
101
1,892
2,659
4,796
305
2,256
588
2,341
1,882
192
4,316
868
..
4,478
1,072
184
1,756
984
1,630
753
3,107
2,222
2,589
688
27,360
464
..
2,662
593
404
..
42,967
3,367
1,889
2,660
833
1,597
1,796
2,180
72,890
16,239
20,219
8,823
15,691
11,918
222,549
181,775
123,252
95,931
10,621
1,055
3,707
1,240
225
3,128
497
246
2,241
120
2,573
2,363
6,093
361
2,882
663
3,169
2,299
269
5,356
947
..
5,290
1,350
235
2,072
1,134
1,841
1,239
3,601
2,381
2,780
795
27,282
517
..
3,166
671
367
..
58,544
4,650
2,117
3,343
969
1,932
2,319
2,413
89,433
21,808
23,330
10,723
19,547
14,026
271,175
220,807
152,038
117,132
15,144
1,119
3,534
1,390
360
3,562
500
289
2,324
138
3,036
3,318
7,132
361
3,583
603
4,359
2,400
290
6,617
1,031
..
6,740
1,411
275
2,296
1,438
1,979
1,778
4,138
2,891
2,927
825
34,849
651
..
3,700
908
452
..
68,809
7,701
2,357
4,205
1,206
2,237
2,631
2,446
103,625
24,838
29,246
12,452
22,569
14,521
324,379
259,550
174,847
134,048
16,287
1,075
3,451
1,547
432
3,763
624
324
2,509
156
3,789
5,073
7,356
441
3,179
465
5,537
3,037
290
8,304
1,202
..
8,171
1,462
509
2,525
1,468
2,360
1,662
4,744
3,351
3,317
..
40,726
787
..
4,037
1,034
463
..
84,706
9,995
2,329
5,116
1,371
2,820
3,221
2,551
115,892
25,211
33,931
14,383
26,044
16,322
375,349
2007
306,358
208,464
165,502
26,304
1,750
4,386
..
..
4,395
791
381
3,670
192
3,785
4,464
8,302
654
3,809
474
6,143
3,805
320
10,057
1,460
..
10,059
1,713
1,403
3,823
1,215
2,542
1,955
5,193
3,626
4,583
..
43,039
955
..
5,407
1,313
462
..
97,946
11,041
2,350
6,250
1,561
3,577
4,068
2,455
151,699
31,633
45,443
21,074
33,750
19,799
458,104
2008
384,534
279,044
217,932
43,121
1,928
5,679
..
..
8,435
945
464
4,195
256
4,468
5,541
9,085
..
5,953
361
7,976
4,652
397
12,690
1,460
..
12,563
1,796
1,454
5,357
1,911
..
2,747
6,295
4,585
5,387
..
61,006
1,423
..
6,976
1,271
575
..
106,345
12,537
2,234
8,090
..
4,618
4,909
3,005
199,201
39,171
62,909
25,589
45,214
26,317
583,978
2009a
317,933
238,718
191,987
34,901
1,875
5,273
..
..
6,856
1,013
449
4,794
258
2,298
4,876
7,866
..
4,328
379
8,229
3,685
368
10,820
1,865
..
11,253
1,764
..
4,484
1,783
..
2,043
5,074
4,287
5,548
..
46,999
1,524
..
5,637
975
554
..
80,328
11,391
2,295
7,511
..
5,557
4,118
3,678
193,682
50,772
60,048
..
36,088
21,894
509,907
Annual average
1980–89 1990–99 2000–09
66,471
44,946
37,295
1,895
447
842
567
254
2,219
118
292
305
67
2,107
1,093
2,906
..
61
..
1,093
1,586
137
709
658
67
2,154
496
491
668
384
536
576
853
773
1,284
583
7,362
354
..
1,408
123
225
403
21,441
1,744
515
..
542
619
1,148
1,598
40,285
13,875
10,787
..
4,955
3,834
107,382
90,422
62,531
51,235
4,032
579
1,916
640
234
1,816
237
282
469
93
1,537
1,309
3,406
295
270
482
1,330
1,823
242
2,509
905
91
3,071
926
180
942
716
882
607
2,400
1,001
1,844
448
11,214
405
..
1,719
344
191
346
27,961
1,289
1,109
1,986
586
1,039
1,283
2,644
53,422
11,636
16,572
7,464
9,907
7,842
143,939
215,193
151,820
118,742
17,472
1,181
3,542
1,016
229
3,931
600
300
2,493
143
2,518
3,282
6,147
365
2,978
498
4,373
2,667
273
6,833
1,140
114
7,085
1,287
504
2,624
1,213
1,742
1,422
4,063
2,853
3,218
629
33,073
762
..
3,725
850
414
..
63,596
6,856
1,948
4,358
1,007
2,664
2,757
2,558
111,461
24,778
33,962
12,328
23,634
15,503
326,492
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
31
Table
2.25
Exports of goods and services
as a share of GDP
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
31.9
29.1
29.0
..
15.8
53.1
9.0
8.8
27.9
..
25.2
16.9
8.7
16.5
60.0
35.0
..
..
..
..
64.7
42.7
8.5
..
12.7
29.5
21.0
64.3
13.3
24.8
14.7
36.8
51.0
10.9
78.9
24.6
29.4
14.4
..
23.9
68.0
22.9
33.2
35.4
10.6
74.6
..
51.1
19.4
41.4
23.4
30.2
34.3
30.5
..
17.4
40.2
31.2
26.4
28.0
24.6
38.9
14.3
55.1
11.0
7.9
20.2
12.7
14.8
13.5
14.3
29.5
53.7
31.7
53.8
32.2
..
5.6
46.0
59.9
16.9
31.1
9.9
25.7
18.1
..
16.6
23.8
17.1
45.6
65.0
8.2
51.9
15.0
43.4
5.6
..
25.4
62.5
22.4
9.8
24.2
4.0
59.0
12.6
33.5
7.2
35.9
22.9
26.4
23.4
20.0
39.7
26.5
43.6
26.4
31.0
33.2
31.1
69.6
13.7
45.4
8.8
8.4
20.2
31.7
13.5
24.6
17.5
26.1
80.8
45.8
39.9
96.8
7.3
13.3
55.3
43.1
40.7
25.1
..
24.1
54.9
32.4
23.1
26.7
26.4
27.7
56.7
28.9
43.4
16.0
42.7
7.6
..
26.6
95.1
23.2
..
27.9
14.7
104.2
18.6
33.8
11.4
28.7
32.8
33.6
38.3
21.8
62.4
28.7
43.8
32.1
31.2
34.6
32.6
69.7
13.3
44.2
10.7
9.6
19.4
14.9
13.2
51.0
15.1
30.4
80.5
48.6
37.0
90.1
6.8
14.9
62.2
46.0
39.3
23.5
..
26.6
59.8
37.3
32.6
25.0
25.4
30.6
54.0
30.9
39.8
16.1
44.0
11.1
..
26.4
97.8
22.5
..
26.4
17.6
90.1
19.7
33.5
12.7
38.3
35.3
37.2
40.1
28.2
63.3
29.4
46.9
33.7
32.6
36.4
34.1
79.3
13.5
51.2
10.0
11.4
20.5
17.1
12.6
61.0
14.1
34.5
84.2
51.1
40.6
87.4
5.8
15.1
64.7
40.0
36.4
33.8
..
28.5
53.4
37.9
28.2
24.0
25.6
35.9
59.9
31.7
40.5
15.0
46.5
11.4
..
26.9
81.1
23.6
..
27.4
18.2
89.1
20.8
40.3
14.2
34.7
34.6
40.8
47.6
30.3
66.4
32.3
49.7
36.1
33.3
35.8
34.2
73.8
11.4
47.0
11.5
10.7
23.0
20.7
14.0
63.2
14.2
30.7
84.2
52.7
39.9
86.8
6.5
13.9
61.9
39.8
25.2
39.3
..
26.4
53.6
28.6
29.7
22.6
32.1
50.6
61.6
38.4
39.9
..
42.9
11.1
..
25.6
88.8
24.9
..
30.0
16.5
84.6
22.6
42.3
15.3
38.6
37.6
41.8
48.6
29.9
71.3
34.2
50.4
36.9
33.8
35.8
34.5
75.4
16.2
47.5
..
..
22.1
21.4
14.8
54.8
14.7
27.2
76.7
47.8
57.1
81.9
6.3
12.7
62.2
32.9
24.5
30.1
..
26.0
55.8
28.3
30.3
27.1
26.2
54.5
58.8
35.4
50.7
..
41.0
11.0
..
25.4
96.7
20.8
..
31.3
20.0
78.3
24.3
41.9
16.7
42.1
39.8
41.5
46.6
30.3
67.6
35.7
53.2
37.1
36.0
36.3
35.1
76.3
15.2
41.8
..
..
32.5
22.5
10.8
52.8
13.9
23.3
73.3
46.5
..
78.3
3.7
11.4
66.6
29.6
25.0
33.3
..
27.6
58.7
31.1
26.5
29.5
..
54.4
52.9
32.3
53.4
..
41.7
14.5
..
26.4
117.8
16.3
..
35.5
22.4
63.2
22.6
..
24.3
36.6
42.4
43.4
46.3
33.0
67.4
37.5
60.2
39.2
29.8
31.7
30.7
52.2
13.8
33.6
..
..
26.6
23.6
14.5
42.1
14.7
9.6
71.9
41.7
..
74.1
4.5
10.6
52.2
30.4
30.5
40.7
..
25.2
51.2
..
28.5
30.0
..
49.7
48.4
25.1
46.6
..
35.9
11.7
..
24.0
119.3
15.7
..
27.3
15.1
59.8
23.2
..
23.4
35.6
36.3
32.1
40.4
25.0
..
28.6
52.0
30.7
Annual average
1980–89 1990–99 2000–09
26.9
25.4
26.4
34.8
16.6
62.0
9.5
10.4
25.7
15.5
20.5
14.3
14.7
21.4
52.0
37.1
..
35.9
..
6.6
53.3
47.8
11.2
30.2
9.9
25.7
16.9
55.3
13.6
23.7
15.8
47.9
54.4
6.8
61.2
21.0
21.4
10.4
..
27.4
62.1
19.5
15.5
28.8
7.4
70.2
..
46.1
11.6
34.4
21.4
24.1
23.8
22.2
..
22.2
36.9
25.8
27.2
29.9
27.3
63.4
16.4
51.5
11.1
9.0
20.9
16.9
16.2
16.1
17.3
23.1
60.2
36.8
43.2
52.9
22.0
8.1
54.0
52.6
25.2
23.8
13.3
27.6
25.0
11.4
20.1
25.1
20.8
36.7
61.5
12.8
49.7
16.2
42.0
6.0
..
26.4
59.9
19.8
9.8
23.5
5.4
61.1
15.9
30.2
9.8
32.8
33.3
26.0
25.8
21.8
28.7
25.9
42.5
26.7
32.4
34.4
32.6
73.6
14.1
45.5
9.7
8.7
22.9
24.1
14.5
39.4
15.2
24.4
79.1
46.6
40.7
89.5
8.1
12.9
60.7
38.8
35.8
30.3
30.1
25.4
52.9
28.9
27.5
25.9
28.5
41.7
58.4
29.0
44.2
16.2
42.3
10.4
..
26.7
94.0
19.9
..
29.7
16.6
83.5
20.0
36.0
15.1
33.8
36.5
35.6
42.0
25.1
56.9
31.4
49.4
33.8
a. Provisional.
32
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.26
Imports of goods and services
as a share of GDP
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
30.8
33.6
37.5
..
37.3
66.4
31.3
23.3
27.1
..
41.1
28.9
51.9
16.4
60.1
41.2
..
..
..
..
31.6
63.6
9.2
..
41.8
35.9
110.1
64.4
29.7
38.8
29.1
66.7
61.2
27.4
71.1
38.1
19.2
26.4
..
38.4
79.1
38.2
88.5
27.3
23.1
114.0
..
56.4
26.0
45.4
26.5
37.3
30.3
42.9
..
26.7
45.6
33.4
25.6
30.5
30.8
20.9
26.3
49.8
24.5
27.8
17.3
43.7
27.6
27.9
37.1
29.2
45.8
27.1
78.4
69.6
..
8.8
30.9
71.6
25.9
33.4
37.0
31.3
123.2
..
28.0
33.4
33.7
60.7
72.2
36.1
67.4
22.0
28.8
14.1
..
32.2
66.7
23.8
37.7
18.8
7.1
68.9
37.5
45.3
19.4
36.6
22.8
32.3
24.9
32.7
31.1
31.9
50.6
28.4
32.5
37.4
36.8
63.1
26.5
34.4
21.7
27.7
19.9
66.3
18.0
58.7
31.2
33.3
76.0
34.9
49.1
76.4
76.3
27.4
31.1
52.3
56.6
25.2
..
30.0
113.2
44.9
32.1
40.6
37.4
58.6
55.4
47.6
52.5
25.2
40.4
25.1
..
38.7
84.0
40.8
..
25.5
18.9
105.2
22.8
47.4
25.2
41.1
38.5
29.0
23.9
24.4
36.7
31.5
47.7
31.0
32.5
36.6
37.8
53.7
26.1
36.9
24.3
33.9
19.8
53.8
19.4
50.8
33.0
39.2
50.8
39.4
54.2
55.0
70.7
31.6
32.0
67.1
60.4
25.8
..
32.9
112.0
51.2
47.5
43.2
37.8
80.0
56.4
41.8
42.1
26.0
31.1
24.8
..
39.4
95.8
33.5
..
26.7
21.4
92.8
26.1
47.0
22.8
42.8
42.6
31.6
25.7
29.6
32.1
34.3
49.9
32.1
33.9
38.3
39.9
49.4
26.1
34.5
25.6
45.3
21.5
50.1
21.4
43.8
35.8
42.7
54.5
43.6
50.9
43.6
51.5
35.5
27.7
62.8
61.7
35.1
..
36.0
107.3
51.9
45.6
52.2
37.3
95.7
65.9
43.9
40.3
24.2
31.0
25.2
..
42.5
102.7
36.5
..
27.9
28.1
93.4
29.7
57.2
24.9
36.8
43.8
32.6
24.3
32.6
28.3
37.9
50.1
33.4
35.3
37.4
39.5
36.1
22.7
30.7
26.8
47.0
21.0
56.3
21.9
41.1
38.6
44.4
65.6
42.4
57.3
33.1
36.3
36.6
31.8
57.0
40.7
42.6
..
36.3
103.2
83.2
45.8
47.1
40.2
61.6
72.9
47.2
41.6
..
27.7
25.3
..
43.0
106.9
32.5
..
32.5
27.5
87.2
35.7
61.8
28.4
30.2
49.0
31.7
21.5
31.6
25.5
39.7
52.7
33.8
36.2
37.7
40.5
44.4
31.6
35.4
..
..
21.2
59.4
22.3
52.3
41.3
37.9
53.5
41.9
77.1
30.3
34.5
32.0
32.9
49.2
40.8
34.7
..
37.0
108.6
190.9
52.1
35.1
35.6
68.9
69.0
45.2
52.0
..
25.9
25.5
..
47.7
127.9
27.8
..
34.2
23.7
79.7
37.1
62.5
30.1
35.6
48.9
35.0
23.3
34.8
29.4
44.9
55.6
35.7
39.8
40.7
43.4
51.2
28.8
41.9
..
..
35.5
61.7
23.4
50.2
48.3
38.6
47.0
38.8
..
32.1
21.8
30.8
32.0
48.3
44.5
38.6
..
41.8
112.7
172.6
56.8
46.9
..
76.6
67.6
46.5
60.1
..
29.5
30.3
..
53.0
137.2
29.4
..
38.5
21.6
78.7
39.1
..
32.0
34.1
70.8
37.9
22.9
38.6
27.5
50.9
64.4
39.0
33.5
37.6
40.1
46.2
28.2
44.6
..
..
30.9
65.4
22.4
70.1
48.2
21.7
50.9
33.8
..
41.6
20.3
28.8
33.3
50.1
41.3
45.4
..
38.3
111.7
..
52.2
37.7
..
67.6
59.1
43.8
59.9
..
27.2
29.2
..
44.0
127.6
28.5
..
28.1
20.8
76.5
35.2
..
34.6
32.2
65.4
36.6
36.1
31.9
..
39.5
55.3
34.7
Annual average
1980–89 1990–99 2000–09
27.3
30.1
32.5
25.6
34.1
56.7
29.2
23.8
25.3
44.6
32.5
27.7
47.9
22.2
52.6
33.9
..
64.5
..
11.9
43.6
61.0
14.3
29.9
42.8
30.6
126.9
52.4
21.3
30.4
33.4
72.2
57.6
25.1
68.7
29.0
20.3
20.7
..
39.6
64.4
22.5
50.6
23.8
15.7
93.7
..
53.3
17.8
36.5
22.2
33.0
26.3
35.4
..
29.6
43.0
29.6
28.8
34.6
33.8
61.3
28.9
41.7
24.6
23.4
17.2
52.1
24.0
29.7
40.2
21.9
57.3
30.3
60.7
98.6
77.8
14.9
36.3
65.3
37.6
26.9
37.7
31.3
126.9
51.0
28.3
39.4
35.7
47.9
65.6
36.4
59.7
22.4
37.8
26.0
..
33.5
68.4
24.2
37.7
20.7
12.1
76.3
34.9
39.8
21.5
38.4
35.6
29.1
24.2
28.5
25.1
30.9
46.8
28.9
33.9
37.3
38.7
54.4
27.3
37.0
24.0
31.0
23.3
60.6
21.4
56.5
37.0
32.6
54.9
37.5
53.6
54.2
53.0
29.7
32.1
53.6
53.3
33.3
55.3
34.7
110.4
75.6
42.5
41.1
39.6
69.2
63.0
44.0
48.9
25.0
31.0
26.3
..
42.2
105.2
33.8
..
29.3
22.0
91.2
28.7
53.7
26.9
38.0
46.4
31.4
24.6
29.1
27.8
37.6
52.6
32.9
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
33
Table
2.27
Balance of payments
and current account
Exports of goods and services
Current prices
Share of GDP
($ millions)
(%)
a
2009
2009a
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 Príncipe
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
298,039
220,322
158,411
39,432
922
3,971
..
..
5,896
366
290
2,879
79
1,017
6,884
9,722
..
7,713
84
3,011
5,773
223
7,982
1,671
..
7,413
809
..
2,447
1,420
..
1,504
4,161
2,454
4,319
..
62,054
610
..
3,082
912
305
..
77,883
8,230
1,794
4,963
..
3,753
4,560
2,040
200,244
56,798
47,185
..
26,121
20,568
496,886
29.8
31.7
30.7
52.2
13.8
33.6
..
..
26.6
23.6
14.5
42.1
14.7
9.6
71.9
41.7
..
74.1
4.5
10.6
52.2
30.4
30.5
40.7
..
25.2
51.2
..
28.5
30.0
..
49.7
48.4
25.1
46.6
..
35.9
11.7
..
24.0
119.3
15.7
..
27.3
15.1
59.8
23.2
..
23.4
35.6
36.3
32.1
40.4
25.0
..
28.6
52.0
30.7
Imports of goods and services
Current prices
Share of GDP
($ millions)
(%)
a
2009
2009a
317,933
238,718
191,987
34,901
1,875
5,273
..
..
6,856
1,013
449
4,794
258
2,298
4,876
7,866
..
4,328
379
8,229
3,685
368
10,820
1,865
..
11,253
1,764
..
4,484
1,783
..
2,043
5,074
4,287
5,548
..
46,999
1,524
..
5,637
975
554
..
80,328
11,391
2,295
7,511
..
5,557
4,118
3,678
193,682
50,772
60,048
..
36,088
21,894
509,907
33.5
37.6
40.1
46.2
28.2
44.6
..
..
30.9
65.4
22.4
70.1
48.2
21.7
50.9
33.8
..
41.6
20.3
28.8
33.3
50.1
41.3
45.4
..
38.3
111.7
..
52.2
37.7
..
67.6
59.1
43.8
59.9
..
27.2
29.2
..
44.0
127.6
28.5
..
28.1
20.8
76.5
35.2
..
34.6
32.2
65.4
36.6
36.1
31.9
..
39.5
55.3
34.7
Total trade (exports and imports)
Current prices
Share of GDP
($ millions)
(%)
a
2009
2009a
615,972
459,041
350,398
74,333
2,797
9,245
..
..
12,752
1,379
739
7,673
336
3,315
11,760
17,589
..
12,040
464
11,240
9,458
591
18,802
3,535
..
18,666
2,572
..
6,930
3,203
..
3,547
9,235
6,741
9,868
..
109,052
2,135
..
8,720
1,887
859
..
158,210
19,622
4,089
12,475
..
9,309
8,678
5,718
393,926
107,570
107,233
..
62,209
42,463
1,006,794
63.3
69.3
70.8
98.5
42.0
78.2
..
..
57.5
89.0
36.9
112.2
62.8
31.3
122.8
75.5
..
115.6
24.7
39.4
85.5
80.6
71.8
86.2
..
63.5
163.0
..
80.7
67.8
..
117.3
107.5
68.9
106.5
..
63.0
40.9
..
68.0
246.9
44.2
..
55.4
35.9
136.3
58.4
..
58.0
67.8
101.7
68.7
76.5
56.9
..
68.1
107.3
65.4
a. Provisional.
34
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Net income
Current prices
Share of GDP
($ millions)
(%)
a
2009
2009a
..
..
..
–6,823
..
–452
..
–17
–303
–54
..
..
..
..
..
–890
22
..
..
–37
..
–8
–296
–168
..
–58
424
–128
..
..
..
..
27
–95
–70
..
–10,020
–37
0
..
–111
–36
..
–6,389
–2,402
–123
–175
..
–329
–1,363
..
..
..
–2,076
578
–1,495
–2,011
..
..
..
..
–9.0
..
–3.8
..
–1.3
–1.4
–3.5
..
..
..
..
..
–3.8
2.1
..
..
–0.1
..
–1.1
–1.1
–4.1
..
–0.2
26.8
–14.6
..
..
..
..
0.3
–1.0
–0.8
..
–5.8
–0.7
–0.1
..
–14.5
–1.8
..
–2.2
–4.4
–4.1
–0.8
..
–2.0
–10.6
..
..
..
–1.1
0.9
–1.6
–5.1
..
national and fiscal accounts
Net current transfers
Current prices
Share of GDP
($ millions)
(%)
a
2009
2009a
..
..
..
–370
..
878
..
257
393
349
..
..
..
..
..
–115
86
..
..
3,459
..
135
2,078
34
..
2,297
547
1,101
..
..
..
..
224
764
1,261
..
17,977
604
5
..
58
148
..
–2,684
1,480
192
683
..
1,133
516
..
..
..
7,960
–1,572
7,451
1,951
..
..
..
..
–0.5
..
7.4
..
19.4
1.8
22.5
..
..
..
..
..
–0.5
8.2
..
..
12.1
..
18.4
7.9
0.8
..
7.8
34.7
125.6
..
..
..
..
2.6
7.8
13.6
..
10.4
11.6
2.4
..
7.5
7.6
..
–0.9
2.7
6.4
3.2
..
7.1
4.0
..
..
..
4.2
–2.5
8.2
4.9
..
Current account balance
Current prices
Share of GDP
($ millions)
(%)
a
2009
2009a
–12,976
–1,649
–23,308
–7,572
..
–526
..
–164
–1,137
–154
..
..
..
..
..
1,670
–71
..
..
–2,191
..
63
–1,198
–403
..
–1,661
–32
–277
..
..
..
..
–675
–1,171
120
..
21,659
–379
–79
..
–284
–193
..
–11,327
–3,908
–414
–1,816
..
–451
–406
..
–174
..
–3,349
9,381
–4,971
–1,234
–13,150
–1.6
–0.3
–6.3
–10.0
..
–4.4
..
–12.3
–5.1
–9.9
..
..
..
..
..
7.2
–6.8
..
..
–7.7
..
8.6
–4.6
–9.8
..
–5.7
–2.0
–31.6
..
..
..
..
–7.9
–12.0
1.3
..
12.5
–7.3
–41.3
..
–37.2
–9.9
..
–4.0
–7.1
–13.8
–8.5
..
–2.8
–3.2
..
0.0
..
–1.8
15.0
–5.4
–3.1
–1.1
Total reserves including gold
Current prices
Share of GDP
($ millions)
(%)
a
2009
2009a
160,688
121,086
75,576
13,664
1,230
8,704
1,296
323
3,676
366
211
617
..
1,615
3,806
3,267
242
3,252
..
1,781
1,993
224
..
..
169
3,850
..
372
1,135
163
1,604
238
2,316
2,181
2,051
656
45,510
743
..
2,123
191
405
..
39,603
1,094
959
3,470
703
2,994
1,892
..
328,625
155,112
34,897
103,754
23,568
11,294
489,313
16.8
18.1
15.2
18.1
18.5
73.6
15.9
24.4
16.6
23.6
10.5
9.0
..
15.3
39.7
14.0
23.1
31.2
..
6.2
18.0
30.6
..
..
20.1
13.1
..
42.5
13.2
3.5
17.8
7.9
27.0
22.3
22.1
12.2
26.3
14.2
..
16.6
24.9
20.9
..
13.9
2.0
32.0
16.2
24.6
18.7
14.8
..
62.9
110.3
18.5
166.4
25.8
28.5
33.1
Part I. Basic indicators and national and fiscal accounts
35
Table
2.28
Exchange rates and
purchasing power parity
Official exchange rate
(local currency units to $)
2007
2008
2009
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 Príncipe
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
36
Purchasing power parity (PPP)
conversion factor
(local currency units to international $)
2007
2008
2009
Ratio of PPP conversion factor
to market exchange rate
2007
2008
2009
49.7
222.0
3.0
194.3
363.1
249.3
65.7
264.4
232.9
227.2
274.8
300.1
288.9
86.1
304.3
6.9
2.8
272.6
7.7
0.7
1,775.0
211.2
31.4
4.0
33.2
743.2
48.1
250.5
122.3
15.9
12.0
4.8
220.0
70.7
215.1
7,514.7
259.5
3.8
1,221.5
..
4.2
1.2
3.7
425.0
229.0
638.1
2,866.3
..
59.7
232.7
3.4
201.2
444.6
254.2
64.9
274.7
255.2
234.6
321.0
367.3
305.7
92.3
368.3
9.0
3.5
306.0
8.0
0.9
1,981.9
228.5
34.4
4.4
35.9
794.4
51.3
266.6
134.5
16.7
12.7
5.3
231.8
76.7
237.3
9,049.2
268.9
4.7
1,329.2
..
4.5
1.4
4.0
458.0
238.6
664.8
3,126.6
..
55.7
233.3
3.2
205.5
500.6
243.3
66.8
282.8
221.6
243.2
414.3
289.8
306.9
93.0
242.6
9.8
4.3
245.7
8.1
1.0
2,066.8
229.0
36.3
4.5
38.2
852.8
55.0
275.4
125.0
16.8
13.0
5.6
241.0
75.6
261.0
10,364.2
265.2
6.0
1,399.7
..
4.7
1.3
4.2
487.3
239.5
767.5
3,492.7
..
76.7
479.3
6.1
479.3
1,081.9
479.3
80.6
479.3
479.3
359.5
516.7
479.3
479.3
177.7
479.3
15.4
9.0
479.3
24.9
0.9
4,122.8
479.3
67.3
7.0
61.3
1,873.9
140.0
479.3
258.6
31.3
25.8
7.0
479.3
125.8
547.0
13,536.8
479.3
6.7
2,985.2
..
7.0
2.0
7.0
1,245.0
479.3
1,723.5
4,002.5
9,675.8
75.0
447.8
6.8
447.8
1,185.7
447.8
75.3
447.8
447.8
335.9
559.3
447.8
447.8
177.7
447.8
15.4
9.6
447.8
22.2
1.1
5,500.0
447.8
69.2
8.3
63.2
1,708.4
140.5
447.8
238.2
28.5
24.3
8.3
447.8
118.5
546.8
14,695.2
447.8
9.5
2,981.5
..
8.3
2.1
8.3
1,196.3
447.8
1,720.4
3,745.7
6,715,424,238.8
79.3
472.2
7.2
472.2
1,230.2
472.2
79.4
472.2
472.2
354.1
809.8
472.2
472.2
177.7
472.2
15.4
11.8
472.2
26.6
1.4
..
472.2
77.4
8.5
68.3
1,956.2
141.2
472.2
262.4
32.0
27.5
8.5
472.2
148.9
568.3
16,208.5
472.2
13.6
3,385.7
..
8.5
2.3
8.5
1,320.3
472.2
2,030.3
5,046.1
..
0.6
0.5
0.5
0.4
0.3
0.5
0.8
0.6
0.5
0.6
0.5
0.6
0.6
0.5
0.6
0.4
0.3
0.6
0.3
0.8
0.4
0.4
0.5
0.6
0.5
0.4
0.3
0.5
0.5
0.5
0.5
0.7
0.5
0.6
0.4
0.6
0.5
0.6
0.4
..
0.6
0.6
0.5
0.3
0.5
0.4
0.7
..
0.8
0.5
0.5
0.4
0.4
0.6
0.9
0.6
0.6
0.7
0.6
0.8
0.7
0.5
0.8
0.6
0.4
0.7
0.4
0.8
0.4
0.5
0.5
0.5
0.6
0.5
0.4
0.6
0.6
0.6
0.5
0.6
0.5
0.6
0.4
0.6
0.6
0.5
0.4
..
0.5
0.7
0.5
0.4
0.5
0.4
0.8
..
0.7
0.5
0.5
0.4
0.4
0.5
0.8
0.6
0.5
0.7
0.5
0.6
0.6
0.5
0.5
0.6
0.4
0.5
0.3
0.7
0.4
0.5
0.5
0.5
0.6
0.4
0.4
0.6
0.5
0.5
0.5
0.7
0.5
0.5
0.5
0.6
0.6
0.4
0.4
..
0.6
0.6
0.5
0.4
0.5
0.4
0.7
..
35.6
1.8
0.9
4.8
0.6
39.9
2.0
1.1
5.0
0.6
35.8
2.2
0.7
5.0
0.6
69.3
5.6
1.3
8.2
1.3
64.6
5.4
1.2
7.8
1.2
72.6
5.5
1.3
8.1
1.4
0.5
0.3
0.7
0.6
0.5
0.6
0.4
0.9
0.6
0.5
0.5
0.4
0.6
0.6
0.5
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Gross domestic product
Real effective exchange rate
(index: 2000 = 100)
2007
2008
101.5
102.0
101.5
..
..
..
..
96.7
102.5
..
105.3
..
..
106.7
..
101.0
..
106.4
..
..
101.0
108.3
104.6
..
..
..
96.5
..
..
95.0
..
..
..
..
..
..
104.9
..
..
..
..
96.2
..
90.4
..
..
..
98.9
101.5
120.5
..
98.5
98.5
..
..
99.7
96.1
101.0
104.5
105.0
104.5
..
..
..
..
99.3
105.6
..
113.4
..
..
106.3
..
105.8
..
115.5
..
..
104.5
114.8
99.5
..
..
..
87.7
..
..
97.8
..
..
..
..
..
..
116.5
..
..
..
..
102.8
..
80.4
..
..
..
104.3
103.6
138.8
..
100.1
103.7
..
..
100.1
82.2
104.0
national and fiscal accounts
2009
2007
PPP $ billions
2008
105.7
106.6
105.7
..
..
..
..
109.4
108.0
..
115.8
..
..
597.2
..
105.7
..
118.1
..
..
105.3
104.4
91.8
..
..
..
93.2
..
..
107.5
..
..
..
..
..
..
109.4
..
..
..
..
104.5
..
87.8
..
..
..
104.8
103.1
119.5
..
102.1
102.1
..
..
102.4
94.2
105.0
1,630.7
1,155.6
856.1
91.4
12.0
25.5
16.7
2.9
39.8
1.6
3.1
14.4
0.7
18.7
13.3
32.8
1.7
19.8
3.1
62.3
20.3
2.1
31.6
9.8
1.6
58.3
2.8
1.4
18.5
10.1
13.7
6.0
14.8
17.3
13.0
9.2
295.3
9.5
0.3
20.9
1.8
4.1
..
482.7
81.1
5.5
49.3
5.2
33.2
15.9
..
974.0
264.5
407.1
96.9
127.8
77.5
2,602.1
1,759.6
1,256.7
932.4
105.8
12.9
26.8
17.9
3.1
41.8
1.8
3.2
14.7
0.8
20.3
14.4
34.3
1.9
22.5
2.8
70.5
21.3
2.3
35.0
10.5
1.7
60.5
3.0
1.5
20.3
11.2
14.7
6.4
15.9
18.9
13.9
10.3
319.9
10.8
0.3
22.1
1.8
4.4
..
511.4
88.6
5.8
54.1
5.4
36.8
17.2
..
1,046.3
276.8
445.8
102.8
137.9
82.9
2,803.0
2009
1,812.9
1,315.6
969.7
107.5
13.5
26.1
18.7
3.3
43.0
1.8
3.3
14.6
0.8
21.1
15.6
35.9
2.0
21.5
2.9
77.4
21.3
2.4
37.0
10.5
1.7
62.6
3.0
1.6
19.7
12.1
15.4
6.3
16.4
20.3
13.9
10.5
340.9
11.4
0.3
22.8
1.7
4.6
..
506.9
93.4
5.9
57.9
5.6
39.8
18.5
..
1,094.3
285.2
470.8
105.9
146.1
86.3
2,904.5
2007
Per capita
PPP $
2008
2009
2,036.1
1,535.4
1,415.3
5,206.4
1,426.9
13,459.8
1,133.6
372.4
2,131.2
3,320.3
729.0
1,357.0
1,170.3
299.6
3,752.4
1,631.7
2,097.3
30,836.7
639.2
792.3
14,309.1
1,304.7
1,382.6
1,016.9
1,018.6
1,543.1
1,374.2
373.7
995.1
696.8
1,101.7
1,911.7
11,733.3
791.7
6,245.8
654.1
1,999.4
1,006.3
1,656.1
1,757.7
21,463.1
750.1
..
10,002.5
2,006.2
4,813.6
1,194.1
830.2
1,082.7
1,293.9
..
6,029.5
7,812.4
5,085.5
15,713.7
4,094.6
7,584.0
2,703.7
2,144.0
1,628.1
1,502.2
5,873.0
1,484.8
13,971.3
1,175.4
386.1
2,190.6
3,561.3
747.0
1,344.4
1,179.1
316.4
3,976.3
1,665.5
2,227.5
34,166.0
571.8
874.0
14,689.5
1,376.5
1,500.5
1,066.2
1,053.7
1,559.6
1,454.2
391.1
1,060.5
752.1
1,153.3
1,977.2
12,518.9
843.8
6,527.5
703.8
2,115.7
1,112.2
1,762.0
1,807.6
21,255.3
788.6
..
10,480.9
2,141.8
4,966.0
1,273.6
842.4
1,164.0
1,365.2
..
6,374.8
8,052.2
5,468.4
16,335.9
4,364.5
8,028.9
2,846.2
2,155.8
1,661.8
1,522.6
5,812.0
1,507.9
13,384.5
1,186.9
392.1
2,204.9
3,643.6
757.4
1,300.1
1,182.9
319.1
4,238.0
1,701.2
2,319.5
31,779.1
580.5
934.4
14,419.2
1,414.6
1,552.4
1,047.8
1,071.2
1,572.6
1,467.6
396.0
1,004.0
794.3
1,185.5
1,928.7
12,838.4
885.2
6,410.1
689.8
2,203.3
1,136.0
1,820.0
1,816.6
19,587.0
808.0
..
10,277.8
2,209.7
4,998.4
1,323.6
850.3
1,217.2
1,430.2
..
6,563.2
8,172.5
5,672.6
16,502.0
4,566.5
8,272.5
2,882.3
Part I. Basic indicators and national and fiscal accounts
37
Table
2.29
Agriculture value added
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
18.5
31.6
31.6
..
35.4
14.7
29.4
62.2
31.3
..
40.0
45.1
34.0
26.8
11.7
25.9
..
..
..
..
6.8
30.8
60.1
..
44.3
32.6
24.6
35.9
30.1
43.7
48.3
30.4
13.1
37.1
11.2
43.1
..
45.8
..
20.1
6.8
33.0
68.4
6.2
32.9
22.7
..
27.5
72.0
15.1
15.7
15.5
8.5
18.3
..
18.5
14.1
17.2
18.9
31.3
31.3
17.9
36.1
4.9
28.8
55.9
24.6
14.4
47.6
29.3
41.4
31.0
12.9
32.5
3.1
61.5
..
54.3
7.3
29.0
45.1
23.8
60.8
29.5
24.9
54.4
28.6
45.0
45.5
29.6
12.9
37.1
11.7
35.3
..
32.5
..
19.9
4.8
46.9
65.5
4.6
40.6
10.4
46.0
33.8
56.6
20.6
16.5
16.9
11.4
19.4
..
18.3
15.7
18.0
18.6
29.6
26.7
8.3
32.1
2.5
35.6
40.1
21.7
6.8
59.7
33.6
50.5
51.0
6.3
25.6
3.6
5.5
14.7
41.9
6.1
31.1
40.2
22.3
..
29.0
10.2
71.6
29.2
35.7
38.8
27.5
6.3
28.0
10.9
39.6
42.7
37.0
21.1
17.6
3.0
46.7
..
3.4
38.8
9.6
32.5
40.8
26.1
22.6
16.8
13.3
10.5
16.3
4.3
17.3
12.1
16.4
17.1
27.3
25.7
8.6
32.1
2.0
32.9
40.1
20.5
9.7
55.3
23.5
50.9
47.3
5.5
23.2
3.6
4.1
13.9
44.2
5.6
33.7
41.5
25.1
..
28.0
10.1
68.2
28.8
34.6
36.4
25.6
6.4
27.4
9.7
..
34.2
38.6
22.6
15.9
3.0
44.9
..
3.1
35.2
8.9
33.3
41.2
22.9
23.0
20.1
12.5
10.2
15.2
3.0
16.3
12.7
15.1
16.5
26.6
25.2
7.7
32.2
1.8
34.1
34.8
19.5
9.2
54.4
12.3
51.0
45.5
4.5
22.8
3.5
2.6
22.6
46.7
4.9
32.1
40.9
24.2
..
27.2
8.6
65.8
28.3
32.6
36.6
23.7
6.0
27.0
11.3
..
32.8
38.4
16.8
16.7
2.5
51.6
..
2.7
32.0
8.5
31.8
43.7
26.7
23.3
19.2
11.4
8.2
14.9
2.3
14.7
11.2
14.4
15.9
25.6
24.1
8.9
..
1.8
33.3
..
19.9
9.4
55.0
11.7
45.2
45.7
4.0
22.9
3.5
2.8
24.6
47.9
4.9
30.3
30.4
23.8
..
26.7
9.8
56.9
27.5
31.2
36.9
14.6
5.6
27.9
10.5
..
32.0
38.4
..
14.8
2.4
51.1
..
2.9
30.1
7.5
30.4
..
25.6
22.4
21.3
11.3
8.0
14.1
2.0
16.9
10.8
13.9
15.5
24.7
22.8
8.0
..
2.1
..
..
19.5
9.2
53.9
12.5
45.3
42.5
4.4
23.9
3.9
2.7
24.3
46.2
4.8
28.7
29.0
25.3
..
20.1
8.2
55.0
25.7
30.3
36.5
18.8
4.9
27.7
9.4
..
32.7
35.6
..
13.4
2.1
49.9
..
3.4
28.1
7.3
30.0
..
23.6
21.8
22.8
10.8
8.0
14.1
2.1
13.7
10.2
13.5
12.7
22.4
22.4
6.6
..
1.9
..
..
..
9.1
52.9
13.6
45.8
40.2
3.7
25.0
..
2.0
14.4
43.8
4.1
28.5
31.0
24.9
..
21.0
7.8
61.3
24.8
30.1
..
18.9
4.4
30.5
9.3
..
..
32.5
..
15.5
2.1
50.2
..
3.2
26.2
7.3
29.7
..
22.7
18.9
20.2
10.3
6.9
13.2
1.9
14.6
9.8
11.6
13.1
23.5
23.5
10.2
..
3.1
..
..
..
9.2
55.5
..
46.3
42.9
4.5
24.4
..
3.5
14.4
50.7
5.1
27.5
31.7
17.2
..
22.6
8.4
..
29.1
30.5
..
20.6
4.3
31.5
9.4
..
..
34.2
..
16.6
2.0
51.4
..
3.0
29.7
7.3
28.8
..
24.7
21.6
17.9
13.1
11.7
13.7
..
16.4
7.8
13.1
Annual average
1980–89 1990–99 2000–09
18.4
31.1
31.1
15.2
33.8
8.7
29.8
58.1
25.7
16.6
44.3
36.9
36.3
30.4
10.0
27.1
3.3
65.8
..
56.5
7.7
34.0
52.5
24.0
48.6
32.4
24.7
35.8
34.3
44.2
44.4
30.4
14.9
39.7
11.2
38.6
..
40.2
..
22.0
6.1
40.0
66.5
5.5
35.4
19.5
..
31.8
57.6
15.9
16.2
16.2
9.9
19.8
..
16.4
13.8
17.4
18.3
30.7
30.7
11.3
36.1
4.2
33.8
50.8
24.3
12.9
48.4
36.7
40.2
47.0
10.5
27.2
3.4
41.5
22.9
58.4
7.7
28.7
42.6
20.1
56.3
30.8
19.3
67.2
28.6
37.3
46.7
33.9
10.2
34.7
11.3
39.4
..
40.6
..
19.7
3.9
47.9
65.5
4.1
42.1
12.1
44.5
37.4
47.9
21.1
17.0
15.5
11.2
17.2
..
17.8
14.0
17.1
16.2
26.6
25.2
8.0
33.7
2.2
33.8
39.2
20.9
9.0
54.9
25.6
48.4
47.6
5.0
24.2
3.6
4.6
17.8
46.2
5.4
31.1
36.3
22.8
55.0
26.8
9.9
66.6
28.2
34.0
37.4
23.0
5.8
27.4
10.4
39.3
37.2
36.5
20.0
16.4
2.6
49.9
..
3.3
34.7
9.1
31.5
39.3
25.6
22.0
18.8
12.4
9.3
15.1
3.0
15.8
10.9
14.6
a. Provisional.
38
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.30
Industry value added
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
36.9
24.6
24.6
..
12.3
50.7
20.5
12.6
25.6
..
20.1
8.9
13.2
35.0
46.6
19.7
..
..
..
..
60.4
14.9
12.3
..
19.7
20.8
26.5
28.1
16.1
22.5
13.2
26.0
26.2
34.4
55.8
22.9
..
21.5
..
20.1
15.6
21.9
8.0
48.4
14.1
30.2
..
24.8
4.5
42.1
29.0
40.3
57.7
36.8
..
31.0
31.1
38.4
32.1
25.1
25.1
40.8
13.2
61.0
21.0
19.0
29.5
21.4
19.7
17.7
8.3
29.0
40.6
23.2
22.0
10.6
..
11.1
43.0
13.1
16.9
33.3
18.6
19.0
34.4
16.8
12.8
28.9
15.9
28.8
32.8
18.4
38.0
16.2
..
24.6
..
22.2
16.3
19.2
..
40.1
15.3
43.2
17.7
22.5
11.1
51.3
33.1
34.3
48.2
28.7
..
33.4
29.8
33.0
29.9
28.7
26.9
67.4
13.7
49.5
21.6
18.9
30.7
19.7
15.7
24.4
12.7
21.5
61.2
21.6
16.2
89.2
24.5
14.1
52.0
14.0
27.8
31.5
..
17.6
33.9
10.6
15.4
19.4
23.6
23.6
30.3
26.1
28.3
17.1
36.8
12.3
17.8
24.3
27.4
24.7
..
31.7
22.0
47.9
22.5
22.2
24.2
26.5
21.6
43.0
54.8
35.2
75.1
27.9
28.3
35.4
30.9
30.7
28.2
66.1
13.3
51.0
23.2
18.9
30.7
15.2
14.0
47.1
12.2
24.5
65.9
23.1
16.6
92.1
25.6
14.1
55.3
13.2
27.1
33.7
..
18.2
33.9
13.4
15.9
17.4
23.9
28.1
29.1
27.4
29.4
..
42.1
13.9
21.0
24.9
28.2
24.2
..
31.3
25.8
46.7
22.3
22.8
22.1
27.8
27.1
43.0
56.4
36.5
68.6
28.5
28.2
36.0
31.7
32.1
29.5
72.6
13.4
50.6
22.7
20.0
30.4
16.8
14.1
60.4
11.0
26.9
71.9
25.9
16.6
94.4
20.5
13.0
61.4
13.3
27.5
38.9
..
19.1
35.1
15.7
15.8
17.0
24.2
29.3
27.6
25.3
29.2
..
43.5
14.1
20.5
23.8
21.9
23.6
..
31.2
28.3
45.6
22.7
24.0
25.0
31.6
29.6
44.8
61.3
35.9
75.5
28.2
28.9
37.2
32.0
32.6
30.4
69.7
..
54.3
22.4
..
31.4
17.4
14.2
60.6
11.8
27.7
75.5
25.9
16.4
94.4
18.2
12.7
61.2
14.3
20.8
43.4
..
18.5
36.7
17.1
16.1
17.0
24.0
56.3
27.6
26.4
34.6
..
41.9
13.8
..
23.0
20.5
23.2
..
31.2
29.2
48.5
22.9
..
24.2
35.3
33.9
46.3
62.3
38.4
78.5
27.2
29.2
38.1
31.9
32.4
30.4
67.9
..
53.1
..
..
30.6
17.8
14.2
54.3
11.9
28.4
73.1
25.3
16.9
94.6
19.2
13.3
60.3
14.8
20.7
43.4
..
14.9
39.0
18.9
16.3
16.3
24.2
38.3
28.0
25.9
35.6
..
40.7
13.9
..
23.6
20.2
24.3
..
31.2
31.2
49.4
23.3
..
26.6
38.5
34.9
45.0
61.3
36.3
76.4
27.3
29.1
37.5
31.7
31.0
31.0
67.5
..
52.9
..
..
..
18.8
14.2
48.8
12.0
28.0
77.3
26.1
..
95.7
22.3
13.0
64.3
15.1
20.4
46.7
..
15.1
37.9
16.8
16.2
16.1
..
40.6
29.2
23.7
37.8
..
..
14.9
..
21.7
20.2
23.5
..
32.5
34.0
49.4
23.1
..
27.4
41.4
32.4
46.6
62.1
37.5
78.2
30.3
32.1
38.7
29.6
28.0
28.0
59.0
..
39.6
..
..
..
20.1
14.6
..
12.1
24.0
71.1
25.2
..
91.9
22.2
10.7
53.8
15.5
18.9
53.0
..
15.3
34.1
..
16.0
16.1
..
34.7
29.1
23.6
32.7
..
..
14.5
..
21.7
19.7
22.1
..
31.1
26.0
49.4
24.3
..
25.8
34.1
29.0
39.3
54.5
37.3
..
28.5
30.0
33.8
Annual average
1980–89 1990–99 2000–09
34.2
24.7
24.7
39.4
14.0
57.5
21.0
15.1
31.8
19.0
16.2
13.5
12.5
30.1
45.1
20.8
20.6
8.9
..
11.6
53.7
13.7
13.8
33.6
15.7
19.4
27.7
27.8
13.8
22.7
14.8
27.0
28.9
24.8
44.2
19.8
..
21.0
..
20.7
16.5
15.9
8.0
43.8
15.2
32.3
..
22.0
9.4
45.5
30.2
36.3
52.1
30.6
..
33.2
31.5
35.1
29.6
24.9
24.9
56.9
13.7
54.8
21.1
18.7
30.3
19.7
20.2
13.7
11.4
20.6
45.4
22.2
16.6
38.5
18.4
10.2
48.2
13.7
24.5
30.0
12.5
17.8
42.3
11.0
12.1
22.7
17.0
26.6
32.1
17.1
30.6
17.4
..
19.5
..
23.5
21.5
32.4
..
35.0
13.5
43.5
16.4
21.0
14.9
39.2
30.6
35.9
49.7
31.8
..
32.0
28.8
32.2
30.6
29.7
28.6
67.5
13.7
51.5
22.1
19.0
31.8
17.5
14.8
37.3
11.8
24.3
69.7
24.5
16.2
91.5
22.0
13.0
56.7
14.1
24.8
39.1
13.0
17.0
35.0
13.5
15.5
17.2
24.3
33.4
29.4
25.2
31.9
17.2
39.2
13.9
18.7
23.6
24.5
24.4
..
31.7
25.8
47.6
22.1
20.4
24.5
31.2
27.7
42.4
57.8
35.8
74.1
28.2
29.3
35.7
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
39
Table
2.31
Services plus discrepancy value added
Share of GDP
(%)
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 Príncipe
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
2003
2004
2005
2006
2007
2008
2009a
44.6
43.8
43.8
..
52.3
34.6
50.1
25.1
43.1
..
39.9
46.0
52.8
38.2
41.7
54.4
..
..
..
..
32.8
54.3
27.6
..
36.1
46.6
48.9
36.0
53.9
33.7
38.5
43.6
60.7
28.5
33.0
34.0
..
32.6
..
59.9
77.5
45.0
23.6
45.4
53.0
47.1
..
47.7
23.5
42.8
55.3
44.2
33.8
45.0
..
50.5
54.8
44.4
49.2
43.9
43.9
41.2
50.7
34.1
50.2
25.2
46.0
64.3
32.7
53.0
50.3
40.0
46.5
44.3
74.9
27.8
..
34.5
49.7
57.9
38.1
42.9
20.6
51.4
40.7
28.8
58.6
26.1
38.6
41.6
54.4
44.5
50.2
48.6
..
42.8
..
57.9
78.9
33.9
..
55.3
44.2
46.5
36.4
43.7
32.4
28.1
50.4
48.8
40.5
52.0
..
48.3
54.5
49.1
51.4
41.8
46.5
24.3
54.2
48.0
42.8
41.0
47.6
73.4
24.6
42.0
36.7
27.5
32.6
52.8
80.2
5.3
60.8
44.0
41.9
54.9
32.0
46.3
..
53.4
55.9
17.7
55.4
44.9
37.6
48.9
63.4
45.9
60.7
43.2
20.5
50.7
61.2
58.2
69.6
28.6
..
64.9
39.3
42.5
45.0
37.1
49.7
50.9
61.6
43.7
34.7
48.4
20.6
54.8
59.7
48.2
52.0
42.0
46.2
25.3
54.6
47.0
44.0
41.0
48.9
75.1
30.7
29.4
36.9
28.3
28.6
53.7
79.8
3.8
60.5
41.8
39.1
53.1
31.4
41.3
..
53.7
56.0
18.4
55.3
47.9
39.8
46.3
64.4
45.2
60.8
..
23.7
47.6
56.4
59.2
68.8
30.9
..
65.6
38.9
44.4
44.3
36.0
55.0
49.1
52.7
44.5
33.5
48.3
28.4
55.2
59.1
48.8
51.8
41.3
45.2
19.8
54.4
47.6
43.2
45.1
50.1
74.0
31.4
27.3
38.0
27.5
23.6
51.3
79.9
3.0
56.9
40.3
33.8
54.6
31.6
36.9
..
53.7
56.3
18.4
55.9
50.3
39.3
47.0
66.4
47.7
59.5
..
23.7
47.5
62.7
59.5
75.6
24.8
..
66.2
39.7
45.8
45.5
32.4
48.3
45.1
51.2
43.8
30.5
49.2
22.2
57.1
59.9
48.4
52.1
41.8
45.5
21.4
..
43.9
44.4
..
48.8
73.2
30.7
27.8
..
26.6
20.5
51.2
80.1
2.9
57.2
39.4
33.9
55.5
48.8
32.8
..
54.8
53.5
26.0
56.4
51.9
39.1
29.1
66.9
45.7
54.9
..
26.1
47.8
..
62.2
77.1
25.7
..
66.0
40.8
43.9
46.7
..
50.2
42.3
44.8
42.4
29.7
47.5
19.5
56.0
60.1
48.0
52.8
43.0
47.0
24.1
..
44.8
..
..
49.9
73.0
31.9
33.2
..
29.1
22.6
50.9
79.3
2.8
56.5
40.5
34.9
56.5
50.2
31.3
..
65.0
52.8
26.1
58.1
53.4
..
42.9
67.1
46.4
55.0
..
26.6
50.4
..
63.0
77.7
25.9
..
65.5
40.7
43.3
46.7
..
49.8
39.8
42.3
44.2
30.7
49.6
21.5
59.0
60.7
49.1
55.6
46.6
46.6
25.9
..
45.2
..
..
..
72.1
32.9
37.5
..
31.8
19.0
48.9
..
2.3
63.3
43.2
31.7
56.4
48.6
28.4
..
63.9
54.3
21.9
59.0
53.8
..
40.6
66.4
45.9
52.8
..
..
52.6
..
62.8
77.7
26.3
..
64.3
39.7
43.3
47.2
..
49.9
39.7
47.5
43.1
31.0
49.2
19.9
55.0
58.1
49.8
57.3
48.5
48.5
30.8
..
57.3
..
..
..
70.7
29.9
..
..
33.0
24.4
50.4
..
4.7
63.4
38.6
41.2
57.1
49.5
29.8
..
62.1
57.5
..
54.9
53.4
..
44.8
66.6
44.9
58.0
..
..
51.3
..
61.7
78.3
26.6
..
65.8
44.3
43.3
46.9
..
49.5
44.3
53.0
47.7
33.7
49.0
..
55.1
62.3
53.1
Annual average
1980–89 1990–99 2000–09
47.5
44.3
44.3
45.4
52.2
33.8
49.2
26.8
42.5
64.4
39.5
49.6
51.2
39.6
44.9
52.0
76.1
25.2
..
31.9
38.6
52.3
33.6
42.3
35.7
48.2
47.6
36.4
51.9
33.1
40.8
42.6
56.2
35.6
44.6
41.6
..
38.8
..
57.3
77.4
44.2
25.1
50.8
49.5
48.2
..
46.2
33.0
38.6
53.6
47.5
38.0
49.7
..
50.4
54.8
47.5
52.1
44.4
44.4
31.8
50.2
40.9
45.1
30.5
45.4
67.4
31.4
49.6
48.4
32.4
44.1
50.6
80.0
20.0
58.7
31.4
44.0
57.6
32.9
49.9
31.1
51.5
38.4
21.8
59.3
40.1
36.4
39.4
57.7
48.2
58.1
43.2
..
39.9
..
56.8
74.6
19.7
..
60.9
44.5
44.4
39.1
41.7
37.2
39.7
52.4
48.6
39.1
51.0
..
50.2
57.3
50.7
53.2
43.7
46.2
24.5
52.6
46.3
44.1
41.7
47.3
73.6
30.4
37.1
38.0
28.1
25.3
51.3
80.2
3.8
60.1
40.8
37.8
54.8
38.9
38.1
32.0
56.2
55.1
19.8
56.3
48.8
38.1
43.6
64.8
47.4
57.7
43.5
23.6
49.6
61.3
60.0
72.8
25.7
..
65.1
39.6
43.3
46.4
40.3
49.8
46.8
53.5
45.2
32.9
49.1
23.0
56.0
59.9
49.8
a. Provisional.
40
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.32
SUB–SAHARAN AFRICA
Excluding South Africa
Excl. S. Africa & Nigeria
Angola
Benina
Botswanaa
Burkina Faso
Burundia
Cameroona
Cape Verde
Central African Republic
Chad
Comoros
Congo, Dem. Rep.a
Congo, Rep.
Côte d’Ivoirea
Djibouti
Equatorial Guinea
Eritrea
Ethiopia a
Gabon
Gambia, Thea
Ghanaa
Guineaa
Guinea-Bissau
Kenya
Lesotho
Liberia
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mozambique
Namibia
Niger
Nigeria
Rwanda a
São Tomé and Príncipe
Senegal
Seychelles
Sierra Leonea
Somalia
South Africa
Sudana
Swazilanda
Tanzania
Togoa
Ugandaa
Zambiaa
Zimbabwea
NORTH AFRICA
Algeriaa
Egypt, Arab Rep.a
Libya
Morocco
Tunisiaa
ALL AFRICA
Central government finances,
expense, and revenue
Revenue, excluding grants
1990
2000
2009
1990
Finances
Share of GDP
(%)
Expense
2000
..
..
..
..
..
50.8
..
..
14.3
..
..
..
..
10.1
..
..
..
..
..
12.4
..
19.4
12.5
..
..
..
44.9
..
..
..
..
..
..
..
31.3
..
..
10.8
..
..
..
5.6
..
..
..
..
..
..
..
20.4
24.1
..
..
..
..
..
..
..
..
..
..
..
..
..
3.7
28.6
..
..
..
..
..
..
..
..
..
..
19.7
50.7
..
11.7
..
13.4
..
..
..
30.1
..
..
..
..
16.9
38.7
11.4
..
26.3
..
26.2
..
..
10.8
..
..
..
..
..
..
17.6
..
14.0
..
..
28.7
..
..
..
..
..
18.7
..
..
..
..
..
..
15.3
..
..
20.5
..
..
..
..
17.1
..
23.5
..
..
..
..
..
..
..
36.6
11.6
..
28.2
..
..
..
18.8
12.4
..
..
..
..
..
..
..
26.7
..
..
14.6
..
..
..
..
16.7
..
..
..
..
..
16.2
..
17.2
..
..
..
..
33.6
..
..
..
..
..
..
..
..
..
..
12.7
..
..
..
..
..
..
..
..
..
..
..
..
24.5
..
..
..
..
..
..
..
..
..
..
..
..
..
8.6
19.9
..
..
..
..
..
..
..
..
..
..
16.8
..
..
10.6
..
11.6
..
..
..
28.5
..
..
..
..
12.8
43.1
28.7
..
27.9
..
22.6
..
..
15.5
..
..
..
..
..
..
15.0
..
13.0
..
..
28.2
..
..
..
..
..
17.6
..
..
..
..
..
..
17.9
..
..
21.7
..
..
..
..
14.6
..
21.6
..
..
..
..
..
..
..
32.7
22.5
..
33.0
..
..
..
17.4
13.7
..
..
..
..
..
..
..
19.1
..
..
–5.6
..
..
..
..
–6.5
..
..
..
..
..
–6.6
..
2.1
..
..
..
..
–0.6
..
..
..
..
..
..
..
..
..
..
–5.4
..
..
..
..
..
..
..
..
..
..
..
..
–2.6
..
..
..
..
..
..
..
..
..
..
..
..
..
–4.0
1.9
..
..
..
..
..
..
..
..
..
..
2.0
..
..
–2.0
..
–3.4
..
..
..
–1.6
..
..
..
..
–0.9
–13.9
–9.3
..
–2.0
..
–0.8
..
..
–1.9
..
..
..
..
..
..
–4.5
..
–4.8
..
..
–3.8
..
..
..
..
..
0.9
..
..
..
..
..
..
–5.6
..
..
–5.5
..
..
..
..
–2.1
..
0.6
..
..
..
..
..
..
..
4.3
–3.1
..
–4.9
..
..
..
–0.6
–0.9
..
..
..
23.0
..
..
30.7
..
..
..
..
29.2
36.6
27.0
..
33.1
31.4
..
24.0
..
..
30.4
..
..
..
..
27.6
25.0
30.2
..
27.9
29.9
..
–2.0
..
..
–3.2
..
..
..
..
–2.7
–4.4
–6.6
..
1.0
–1.7
2009
1990
Cash surplus or deficit
2000
2009
(continued)
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
41
Table
2.32
Central government finances,
expense, and revenue (continued)
Finances
Share of GDP
(%)
Net incurrance of liabilities
SUB–SAHARAN AFRICA
Excluding South Africa
Excl. S. Africa & Nigeria
Angola
Benina
Botswanaa
Burkina Faso
Burundia
Cameroona
Cape Verde
Central African Republic
Chad
Comoros
Congo, Dem. Rep.a
Congo, Rep.
Côte d’Ivoirea
Djibouti
Equatorial Guinea
Eritrea
Ethiopiaa
Gabon
Gambia, Thea
Ghanaa
Guineaa
Guinea-Bissau
Kenya
Lesotho
Liberia
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mozambique
Namibia
Niger
Nigeria
Rwandaa
São Tomé and Príncipe
Senegal
Seychelles
Sierra Leonea
Somalia
South Africa
Sudana
Swazilanda
Tanzania
Togoa
Ugandaa
Zambiaa
Zimbabwea
NORTH AFRICA
Algeriaa
Egypt, Arab Rep.a
Libya
Morocco
Tunisiaa
ALL AFRICA
42
1990
Domestic
2000
2009
1990
Foreign
2000
2009
1990
Total debt
2000
2009
..
..
..
..
..
–0.8
..
..
..
..
..
..
..
6.5
..
..
..
..
..
5.1
..
..
..
..
..
..
–7.9
..
..
..
..
..
..
..
..
..
..
3.3
..
..
..
..
..
..
..
..
..
..
..
6.8
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
1.3
..
–1.0
..
..
..
1.0
..
..
..
..
0.3
0.7
..
..
1.6
..
..
..
..
0.6
..
..
..
..
..
..
2.2
..
4.5
..
..
4.2
..
..
..
..
..
..
..
..
..
..
..
..
2.8
..
..
3.0
..
..
..
..
–4.4
..
3.1
..
..
..
..
..
..
..
–6.0
..
..
7.0
..
..
..
2.7
1.5
..
..
..
..
..
..
..
0.0
..
..
5.2
..
..
..
..
..
..
..
..
..
..
2.0
..
..
..
..
..
..
9.1
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
1.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
1.7
..
3.0
..
..
..
0.7
..
..
..
..
0.5
13.1
..
..
0.3
..
..
..
..
2.0
..
..
..
..
..
..
2.1
..
2.9
..
..
5.1
..
..
..
..
..
..
..
..
..
..
..
..
2.6
..
..
..
..
..
..
..
2.6
..
1.3
..
..
..
..
..
..
..
–2.7
..
..
1.0
..
..
..
–0.5
1.8
..
..
..
5.8
4.7
3.2
2.0
2.8
1.1
3.7
4.6
1.7
2.0
0.7
0.4
3.7
18.6
11.7
2.4
..
..
2.0
3.0
11.9
6.2
6.3
3.5
9.2
4.3
0.8
7.2
7.1
2.8
14.3
5.7
3.2
..
4.0
11.7
0.8
..
5.7
5.8
3.3
1.2
..
0.4
4.0
4.2
5.3
3.4
6.1
5.4
..
4.6
4.8
18.7
3.3
1.2
1.8
3.1
5.5
3.0
1.5
1.8
1.6
0.6
1.4
9.8
2.4
..
0.5
1.7
6.9
5.1
7.8
5.0
2.4
4.7
8.2
0.1
3.0
3.6
3.8
7.7
9.9
2.3
..
1.4
4.0
2.1
..
4.8
3.4
7.3
..
2.9
2.0
2.1
1.6
2.2
1.2
5.7
6.4
..
1.5
2.0
4.6
0.6
0.4
0.5
1.5
1.8
2.1
1.6
1.1
2.2
6.6
1.7
4.7
2.8
..
1.2
0.4
4.2
3.5
0.9
3.1
1.2
1.3
2.4
7.3
0.5
0.8
0.9
2.6
1.5
0.4
..
0.8
0.3
0.5
1.8
1.6
8.2
0.4
..
2.7
0.9
1.5
0.8
1.9
0.4
1.3
1.8
..
..
..
..
3.6
..
..
..
..
0.6
5.9
9.9
..
0.1
0.3
..
..
..
..
1.8
..
..
..
..
–0.2
0.0
–0.2
..
1.7
0.0
14.2
7.1
..
6.9
11.6
8.2
1.8
..
7.3
9.8
0.7
1.6
..
3.7
5.3
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Goods and services
1990
2000
2009
Compensation of employees
1990
2000
2009
Expense
Share of expense
(%)
Interest payments
1990
2000
2009
Subsidies and other transfers
1990
2000
2009
1990
Other expenses
2000
2009
..
..
..
..
..
35.2
..
..
16.7
..
..
..
..
56.3
..
..
..
..
..
43.1
..
28.3
..
..
..
..
30.8
..
..
..
..
..
..
..
..
..
..
35.3
..
..
..
..
..
..
..
..
..
..
..
..
21.7
..
..
..
..
..
..
..
..
..
..
..
..
..
59.4
25.6
..
..
..
..
..
..
..
..
..
..
21.3
..
..
17.7
..
37.6
..
..
..
20.8
..
..
..
..
26.0
24.6
14.9
..
11.3
..
26.1
..
..
55.1
..
..
..
..
..
..
17.7
..
19.1
..
..
16.3
..
..
..
..
..
29.5
..
..
..
..
..
..
16.5
..
..
20.2
..
..
..
..
30.6
..
11.7
..
..
..
..
..
..
..
37.2
24.3
..
12.9
..
..
..
24.1
31.2
..
..
..
..
..
..
..
29.1
..
..
55.6
..
..
..
..
25.4
..
..
..
..
..
48.1
..
28.7
..
..
..
..
38.6
..
..
..
..
..
..
..
..
..
..
43.5
..
..
..
..
..
..
..
..
..
..
..
..
40.9
..
..
..
..
..
..
..
..
..
..
..
..
..
27.4
27.8
..
..
..
..
..
..
..
..
..
..
55.2
..
..
40.7
..
36.5
..
..
..
51.2
..
..
..
..
41.4
36.3
23.4
..
15.6
..
44.6
..
..
12.3
..
..
..
..
..
..
47.2
..
45.8
..
..
43.3
..
..
..
..
..
38.4
..
..
..
..
..
..
39.9
..
..
37.3
..
..
..
..
34.4
..
33.7
..
..
..
..
..
..
..
26.8
27.6
..
13.4
..
..
..
40.3
14.2
..
..
..
..
..
..
..
2.8
..
..
7.8
..
..
..
..
7.4
..
..
..
..
..
5.6
..
21.4
..
..
..
..
18.7
..
..
..
..
..
..
..
..
..
..
7.9
..
..
..
..
..
..
..
..
..
..
..
..
17.8
..
..
..
..
..
..
..
..
..
..
..
..
..
..
35.2
..
..
..
..
..
..
..
..
..
..
17.8
..
..
13.4
..
8.0
..
..
..
6.6
..
..
..
..
10.7
17.3
21.9
..
18.1
..
2.3
..
..
5.2
..
..
..
..
..
..
3.3
..
3.4
..
..
5.3
..
..
..
..
..
8.7
..
..
..
..
..
..
15.6
..
..
10.3
..
..
..
..
2.5
..
13.6
..
..
..
..
..
..
..
20.1
7.1
..
7.2
..
..
..
5.5
8.6
..
..
..
..
..
..
..
31.8
..
..
13.3
..
..
..
..
..
..
..
..
..
..
11.2
..
12.2
..
..
..
..
8.9
..
..
..
..
..
..
..
..
..
..
15.5
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
13.2
10.9
..
..
..
..
..
..
..
..
..
..
3.4
..
..
9.7
..
0.4
..
..
..
10.4
..
..
..
..
18.7
21.6
5.5
..
52.9
..
27.0
..
..
27.4
..
..
..
..
..
..
29.7
..
11.1
..
..
30.1
..
..
..
..
..
16.3
..
..
..
..
..
..
27.9
..
..
31.3
..
..
..
..
15.0
..
31.0
..
..
..
..
..
..
..
15.8
22.6
..
62.9
..
..
..
17.6
44.7
..
..
..
..
..
..
..
1.1
..
..
..
..
..
..
..
..
..
..
..
..
..
0.2
..
9.4
..
..
..
..
2.9
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
0.5
..
..
..
..
..
..
..
..
..
..
2.2
..
..
18.6
..
17.5
..
..
..
11.0
..
..
..
..
..
..
34.3
..
2.2
..
..
..
..
..
..
..
..
..
..
..
2.1
..
20.7
..
..
4.9
..
..
..
..
..
7.1
..
..
..
..
..
..
..
..
..
0.9
..
..
..
..
17.5
..
10.0
..
..
..
..
..
..
..
0.1
18.3
..
4.4
..
..
..
12.5
1.4
..
..
..
22.4
..
..
7.0
..
..
..
..
8.6
11.3
8.0
..
8.9
6.6
..
26.6
..
..
31.4
..
..
..
..
39.8
33.7
24.6
..
47.8
35.8
..
16.3
..
..
10.9
..
..
..
..
12.1
1.4
14.0
..
3.7
7.4
..
..
..
..
44.9
..
..
..
..
..
45.4
44.7
..
26.6
37.7
..
..
..
..
5.8
..
..
..
..
..
8.3
8.7
..
12.9
12.5
(continued)
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
43
Table
2.32
Central government finances,
expense, and revenue (continued)
Revenue
Share of revenue
(%)
Interest
payments
1990 2000 2009
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 Príncipe
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
..
..
..
..
..
12.9
..
..
15.5
..
..
..
..
37.8
..
..
..
..
..
14.3
..
32.4
34.7
..
..
..
43.6
..
..
..
..
..
..
..
25.3
..
..
20.5
..
..
..
38.1
..
..
..
..
..
..
..
17.2
17.1
..
..
..
..
..
..
..
..
..
..
..
..
..
16.4
5.0
..
..
..
..
..
..
..
..
..
..
15.0
41.4
..
39.6
..
11.3
..
..
..
35.1
..
..
..
..
29.5
41.0
29.4
..
3.0
..
49.9
..
..
21.8
..
..
..
..
12.9
..
..
..
..
..
27.5 10.7
..
..
..
..
18.4
..
11.6
..
..
12.0
..
..
..
..
..
32.5
..
..
..
..
..
..
15.9
..
..
10.1
..
..
..
..
9.9
..
2.2
..
..
..
..
..
..
..
10.8
14.4
..
2.7
..
..
..
18.3
9.6
..
..
Taxes on income,
profits, and
capital gains
1990 2000 2009
..
..
..
..
..
37.6
..
..
18.9
..
..
..
..
21.9
..
..
..
..
..
28.2
..
9.7
20.6
..
..
..
8.7
..
..
..
..
..
..
..
32.6
..
..
14.0
..
..
..
29.7
..
..
..
..
..
..
..
39.5
43.7
..
..
..
..
..
..
..
..
..
..
..
..
..
8.4
..
..
..
..
..
..
..
..
..
..
..
28.5
17.2
..
11.6
..
12.5
..
..
..
31.8
..
..
..
..
21.3
17.3
15.4
..
51.7
..
24.1
..
..
9.9
..
..
..
..
..
..
17.0
..
13.8
..
..
18.2
..
..
..
..
..
15.3
..
..
..
..
..
..
22.6
..
..
40.0
..
..
..
..
19.5
..
22.8
..
..
..
..
..
..
..
19.2
16.9
..
52.6
..
..
..
16.7
22.0
..
..
Taxes on goods
Taxes on
and services
international trade
1990 2000 2009 1990 2000 2009
..
..
..
..
..
1.8
..
..
22.2
..
..
..
..
15.1
..
..
..
..
..
24.3
..
28.3
26.8
..
..
..
16.0
..
..
..
..
..
..
..
23.9
..
..
27.1
..
..
..
22.1
..
..
..
..
..
..
..
37.4
25.6
..
..
..
..
..
..
..
..
..
..
..
..
..
15.8
15.5
..
..
..
..
..
..
..
..
..
..
41.4
12.5
..
21.5
..
41.6
..
..
..
22.7
..
..
..
..
33.7
5.1
7.6
..
33.1
..
13.2
..
..
29.4
..
..
..
..
..
..
38.8
..
36.7
..
..
27.6
..
..
..
..
..
20.3
..
..
..
..
..
..
29.3
..
..
40.6
..
..
..
..
29.2
..
46.3
..
..
..
..
..
..
..
39.7
24.6
..
31.8
..
..
..
34.3
46.8
..
..
..
..
..
..
..
12.9
..
..
15.5
..
..
..
..
37.8
..
..
..
..
..
14.3
..
32.4
34.7
..
..
..
43.6
..
..
..
..
..
..
..
25.3
..
..
20.5
..
..
..
38.1
..
..
..
..
..
..
..
17.2
17.1
..
..
..
..
..
..
..
..
..
..
..
..
..
16.4
5.0
..
..
..
..
..
..
..
..
..
..
15.0
41.4
..
39.6
..
11.3
..
..
..
35.1
..
..
..
..
29.5
41.0
29.4
..
3.0
..
49.9
..
..
21.8
..
..
..
..
..
..
18.4
..
11.6
..
..
12.0
..
..
..
..
..
32.5
..
..
..
..
..
..
15.9
..
..
10.1
..
..
..
..
9.9
..
2.2
..
..
..
..
..
..
..
10.8
14.4
..
2.7
..
..
..
18.3
9.6
..
..
4.5
..
.. 59.7
..
4.9 18.1
.. 27.8 12.8
..
..
..
..
..
6.0
..
.. 28.4
..
5.8 12.3 20.4 27.4 19.1
..
..
..
..
37.1
28.0
..
..
21.7 12.9
..
..
..
..
..
31.4
..
31.3 27.5 10.7
4.5
4.9
..
6.0
5.8
Other
taxes
1990 2000 2009
..
..
..
..
..
..
..
..
..
..
..
..
..
.. 5.9
0.1
..
..
..
.. 2.0
..
..
..
4.6
..
..
..
..
0.1
..
..
..
..
..
..
..
..
..
1.1 25.7
..
.. 0.0
..
..
..
7.9
..
..
..
..
..
..
..
..
..
2.2
..
..
..
..
..
0.4
..
..
..
..
..
..
..
..
..
..
..
.. 0.5
1.0
0.1
..
..
..
..
..
.. 1.2
..
..
..
..
.. 5.0 10.0
..
..
..
..
..
7.1
..
..
..
0.9
1.4
..
..
..
..
..
..
..
3.1
..
..
..
..
..
.. 3.3
..
..
1.6
..
0.2
..
..
..
..
..
.. 2.8 2.4
..
..
..
..
4.1
..
..
..
..
..
.. 2.8
..
0.1
..
0.2
..
..
1.1
..
..
..
10.2
..
..
4.8
..
..
..
..
4.4
Social
contributions
1990 2000 2009
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
1.8
..
..
..
..
..
..
..
..
..
1.0
..
..
3.1
..
..
..
..
..
..
..
..
1.9
..
..
..
0.2
..
..
..
..
..
..
..
.. 0.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
.. 0.5
..
..
..
..
5.4
..
..
..
..
..
.. 13.8
..
..
..
..
..
2.1
..
..
..
..
..
..
..
..
..
..
0.0
..
3.3
..
1.5
..
2.2 14.5
..
..
5.4
..
4.4 13.0
..
..
..
..
17.0
..
..
..
..
2.4
..
..
..
..
10.1
..
..
..
..
..
6.4
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
4.1
..
..
..
..
..
..
..
9.0
..
..
2.2
..
..
..
..
..
..
..
Grants and
other revenue
1990 2000 2009
..
..
..
..
..
47.6
..
..
27.5
..
..
..
..
23.1
..
..
..
..
..
29.1
..
28.9
10.4
..
..
..
31.6
..
..
..
..
..
..
..
17.2
..
..
30.0
..
..
..
9.9
..
..
..
..
..
..
..
5.8
9.2
..
..
..
..
..
..
..
..
..
..
..
..
..
33.7
76.4
..
..
..
..
..
..
..
..
..
..
14.7
28.9
..
26.0
..
29.5
..
..
..
8.5
..
..
..
..
12.2
21.3
47.7
..
7.4
..
8.7
..
..
38.7
..
..
..
..
..
..
17.5
..
35.9
..
..
32.0
..
..
..
..
..
17.6
..
..
..
..
..
..
32.1
..
..
8.2
..
..
..
..
31.4
..
17.4
..
..
..
..
..
..
..
21.3
44.1
..
8.2
..
..
..
28.0
21.6
..
..
..
..
.. 6.3
.. 31.5
.. 43.4
..
..
..
..
12.1
..
.. 16.7
19.1 23.4 10.5 11.9
a. Data were reported on a cash basis and have been adjusted to the accrual framework.
44
Part I. Basic indicators and national and fiscal accounts
national and fiscal accounts
Table
2.33
Structure of demand
Share of GDP (%)
Household final
consumption
expenditure
1990 2000 2009a
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 Príncipe
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
65.3 68.5 66.9
72.5 73.5
..
72.5 73.5 74.0
35.8
..
..
86.8 82.4
..
33.2 30.8 62.8
73.5 78.5
..
94.5 88.5
..
66.6 70.2
..
93.4 92.9 67.2
85.7 80.8 92.9
97.6 86.8 78.5
78.7 94.0 105.8
79.1 88.0 74.4
62.4 29.1 42.2
71.9 74.9 72.2
78.9 76.8
..
80.3 20.9 24.3
.. 79.1
..
77.2 73.8
87.7
49.7 32.2
41.1
75.6 77.8 77.8
85.2 84.3 81.7
66.9
77.7 75.2
86.9 94.6
..
62.8
77.7 75.9
123.3 83.3 78.8
..
..
..
86.4 83.2 79.7
71.5 81.6 61.9
79.8 79.4
..
69.2 82.8 72.1
63.4 60.3 74.6
92.3 80.6 84.4
51.2 63.1 61.9
83.8 83.4
..
..
..
..
83.7
87.7
81.1
..
..
..
79.2 76.0 83.3
52.0 53.9 71.9
83.5 100.0 84.0
..
..
..
57.1 63.0 60.4
86.1 76.5 66.7
80.4 78.0 72.8
80.9 78.3 62.3
71.1 92.0
..
91.9 77.5 76.1
64.4
87.4 61.3
63.1 59.9 113.1
64.1 61.1 62.9
56.8 41.6 40.6
72.6 75.9 76.2
48.4 45.7
..
64.6 61.4
57.0
63.6 60.7 63.4
64.7 65.1 65.2
General government
final consumption
expenditure
1990 2000 2009a
Gross fixed capital
formation
1990 2000 2009a
Exports of goods
and services
1990 2000 2009a
17.5
15.6
15.6
34.5
11.0
24.1
21.1
10.8
12.8
14.7
14.9
10.0
24.5
11.5
13.8
16.8
31.5
39.7
..
13.2
13.4
13.7
9.3
11.0
10.3
18.6
25.8
..
8.0
15.1
13.8
25.9
13.6
13.5
30.6
15.0
..
10.1
..
18.4
27.7
7.8
..
19.7
5.8
14.3
17.8
14.2
7.5
19.0
19.4
15.1
16.1
11.3
24.4
15.5
16.4
16.4
18.2
17.4
17.4
11.1
13.4
32.4
17.7
15.2
17.3
22.9
11.4
4.8
11.9
12.8
17.2
8.5
14.1
17.4
..
12.9
21.4
22.3
14.4
22.9
29.9
20.6
57.0
..
14.8
20.1
23.0
20.0
30.6
22.1
21.2
11.4
..
14.6
..
18.0
23.0
9.6
14.9
19.1
10.4
14.5
25.8
25.3
12.7
13.5
18.2
24.5
27.0
26.9
13.9
24.0
24.4
21.1
26.4
28.0
24.6
38.9
14.3
55.1
11.0
7.9
20.2
12.7
14.8
13.5
14.3
29.5
53.7
31.7
53.8
32.2
..
5.6
46.0
59.9
16.9
31.1
9.9
25.7
18.1
..
16.6
23.8
17.1
45.6
65.0
8.2
51.9
15.0
43.4
5.6
..
25.4
62.5
22.4
9.8
24.2
4.0
59.0
12.6
33.5
7.2
35.9
22.9
26.4
23.4
20.0
39.7
26.5
43.6
26.4
15.7
13.4
13.4
..
11.6
25.4
20.8
17.5
9.5
21.3
14.0
7.7
11.7
7.5
11.6
7.2
29.7
4.6
63.8
17.9
9.6
13.7
10.2
6.8
14.0
15.1
41.7
..
9.0
14.6
8.6
25.8
14.1
9.0
23.5
13.0
..
11.0
..
12.8
24.2
14.3
..
18.1
7.6
18.7
11.7
10.2
14.5
9.5
24.3
14.4
13.6
11.2
20.8
18.4
15.6
15.1
17.6
..
13.9
..
..
24.2
..
..
..
20.8
4.5
15.6
15.3
7.9
12.2
8.6
..
3.4
..
8.2
11.6
15.9
9.6
8.0
..
16.3
50.4
..
11.5
20.9
..
20.6
14.6
13.4
24.2
..
..
14.6
..
8.7
12.2
13.8
..
21.0
13.9
27.0
19.8
..
11.4
13.1
13.8
13.3
13.9
11.4
..
18.0
13.1
15.7
16.3
17.4
17.4
15.1
18.9
25.8
18.7
6.1
16.0
19.7
9.5
20.9
10.1
3.5
20.9
11.2
8.8
61.3
23.8
20.3
21.9
17.4
23.1
18.9
11.3
16.7
42.5
..
15.0
12.3
24.6
19.4
22.9
31.0
16.6
11.2
..
18.3
..
22.4
25.2
6.9
..
15.1
12.1
17.4
16.4
17.8
19.2
16.0
11.8
20.2
20.7
18.9
13.1
26.0
26.0
18.1
22.3
22.0
22.0
14.8
25.0
28.2
..
..
..
53.8
10.6
32.7
12.4
29.8
24.3
11.2
..
36.6
..
22.4
28.4
..
19.6
21.6
..
20.1
31.5
..
32.6
21.8
..
25.2
26.2
21.0
24.7
..
..
21.8
..
27.9
24.2
15.1
..
22.6
21.8
16.9
29.3
..
23.5
22.1
2.5
25.1
33.0
19.0
..
30.7
25.9
23.5
Imports of goods
and services
1990 2000 2009a
32.4 29.8 25.6 30.8 33.5
35.7 31.7 30.5 35.1
37.6
31.7 30.7 30.8 35.8 40.1
89.6 52.2 20.9 62.8 46.2
15.2 13.8 26.3 28.1 28.2
53.3 33.6 49.8 41.2 44.6
9.1
.. 24.5 25.2
..
7.8
.. 27.8 19.9
..
23.3 26.6
17.3 19.7 30.9
27.5 23.6 43.7 61.4 65.4
19.8 14.5
27.6
24.1 22.4
16.9 42.1 27.9 34.7 70.1
16.7 14.7
37.1 32.5 48.2
22.4
9.6 29.2 21.4 21.7
80.3 71.9 45.8 43.6 50.9
40.4
41.7
27.1 33.3 33.8
35.1
.. 78.4 50.4
..
98.6
74.1 69.6 85.4 41.6
15.1
4.5
.. 81.8 20.3
12.0 10.6
8.8 24.0 28.8
69.0 52.2 30.9 32.7 33.3
48.0 30.4 71.6 56.8 50.1
48.8 30.5 25.9 67.2 41.3
23.6 40.7 33.4 27.9 45.4
31.8
..
37.0 51.6
..
21.6 25.2 31.3 31.7 38.3
34.2 51.2 123.2 103.4 111.7
21.5
..
.. 26.0
..
30.7 28.5 28.0 38.0 52.2
25.6 30.0 33.4 35.3
37.7
26.8
.. 33.7 39.4
..
46.2 49.7 60.7 74.2
67.6
61.4 48.4 72.2 61.9 59.1
16.5 25.1 36.1
37.0 43.8
40.9 46.6
67.4 44.5 59.9
17.8
.. 22.0 25.7
..
54.0 35.9 28.8 32.0 27.2
8.7
11.7
14.1 25.7 29.2
..
..
..
..
..
27.9 24.0 32.2 37.2 44.0
78.2 119.3 66.7 81.4 127.6
18.1 15.7 23.8 39.3 28.5
..
..
37.7
..
..
27.9 27.3 18.8 24.9 28.1
15.3
15.1
7.1
17.7 20.8
76.1 59.8 68.9 90.1 76.5
13.4 23.2 37.5 20.1 35.2
30.7
.. 45.3 50.7
..
10.7 23.4 19.4 22.1 34.6
27.1 35.6 36.6 41.5 32.2
38.6 36.3 22.8 36.4 65.4
28.3 32.1 32.3 25.3 36.6
41.2 40.4 24.9 21.4 36.1
16.2 25.0 32.7 22.8 31.9
35.6
..
31.1 15.5
..
28.0 28.6 31.9 33.4 39.5
44.5 52.0 50.6 48.2 55.3
30.7 30.7 28.4 28.5 34.7
Gross national
savings
1990 2000 2009a
15.8
12.8
12.8
9.0
5.3
41.6
15.9
8.7
16.2
17.8
6.2
2.3
14.4
..
6.9
–5.1
..
2.1
..
12.8
24.3
21.9
10.5
19.2
14.5
18.5
70.5
..
9.1
16.4
15.0
18.8
25.8
6.6
34.8
–0.6
..
11.3
..
1.6
21.7
–1.0
..
19.1
1.2
19.7
10.1
21.0
5.6
19.6
15.6
27.6
24.3
31.1
..
25.1
23.4
20.8
15.5
15.2
15.2
23.8
10.4
41.4
5.1
4.4
15.3
9.0
..
..
..
..
30.6
8.0
5.4
..
4.4
15.9
41.7
..
15.3
15.4
..
13.5
24.1
..
8.8
9.5
15.9
..
26.3
10.4
25.4
5.3
..
12.9
..
13.8
18.5
–3.7
..
15.8
9.3
12.4
12.7
0.8
14.4
–1.4
..
..
..
18.0
..
24.3
23.2
17.2
15.4
..
..
9.7
..
16.4
..
..
..
31.3
..
..
..
..
..
14.8
..
..
..
16.1
..
18.8
15.5
7.7
..
15.4
28.1
..
..
..
..
..
16.7
9.1
26.5
..
..
15.1
..
..
9.2
7.8
..
15.4
12.2
2.4
21.2
..
17.5
19.0
..
..
..
16.7
..
31.2
22.8
17.6
a. Provisional.
national and fiscal accounts
Part I. Basic indicators and national and fiscal accounts
45
Table
3.1
Millennium Development Goal 1:
eradicate extreme poverty and hunger
Share of population
below PPP $1.25 a day
Surveys
Surveys
1990–99c
2000–09c
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
46
International poverty linea
Poverty gap ratio
Share of population
at PPP $1.25 a day
below PPP $2 a day
Surveys
Surveys
Surveys
Surveys
1990–99c
2000–09c
1990–99c
2000–09c
Poverty gap ratio
at PPP $2 a day
Surveys
Surveys
1990–99c
2000–09c
Year
Percent
Year
Percent
Year
Percent
Year
Percent
Year
Percent
Year
Percent
Year
Percent
Year
Percent
..
..
1994
1998
1998
1996
..
1992
..
..
..
..
1998
1996
..
..
1995
..
1998
1998
1994
1993
1997
1994
..
1999
1998
1994
1996
..
1997
1993
1994
1996
..
..
1995
..
1990
..
1995
..
1995
1992
..
1996
1998
..
..
..
31.2
70.0
86.4
51.5
..
83.2
..
..
..
..
24.1
4.8
..
..
60.5
..
66.7
39.1
36.8
52.1
19.6
46.2
..
82.3
83.1
86.1
23.4
..
81.3
49.1
78.2
68.5
..
..
54.1
..
62.8
..
21.4
..
78.6
72.6
..
64.4
55.4
..
2000
2003
..
2003
2006
2007
2002
2008
2003
2004
2006
2005
2008
2002
..
..
2005
2005
2003
2006
2007
2002
2005
2003
2007
2005
2004
2006
2000
..
2008
..
2007
2004
2005
2001
2005
2007
2003
..
2006
..
2001
2007
2006
2009
2004
..
54.3
47.3
..
56.5
81.3
9.6
21.0
62.8
61.9
46.1
59.2
54.1
23.8
18.8
..
..
39.0
4.8
34.3
30.0
43.3
48.8
19.7
43.4
83.7
67.8
73.9
51.4
21.2
..
60.0
..
43.1
64.4
76.8
28.6
33.5
0.3
53.4
..
17.4
..
62.9
67.9
38.7
28.7
64.3
..
..
..
1994
1998
1998
1996
..
1992
..
..
..
..
1998
1996
..
..
1995
..
1998
1998
1994
1993
1997
1994
..
1999
1998
1994
1996
..
1997
1993
1994
1996
..
..
1995
..
1990
..
1995
..
1995
1992
..
1996
1998
..
..
..
11.0
30.2
47.3
18.9
..
57.4
..
..
..
..
6.7
1.6
..
..
21.2
..
34.7
14.4
11.5
20.6
4.6
25.6
..
44.3
46.0
53.1
7.1
..
42.0
24.6
38.6
32.1
..
..
19.5
..
44.8
..
5.2
..
47.7
29.7
..
24.8
26.9
..
2000
2003
..
2003
2006
2007
2002
2008
2003
2004
2006
2005
2008
2002
..
..
2005
2005
2003
2006
2007
2002
2005
2003
2007
2005
2004
2006
2000
..
2008
..
2007
2004
2005
2001
2005
2007
2003
..
2006
..
2001
2007
2006
2009
2004
..
29.9
15.7
..
20.3
36.4
1.2
6.1
31.3
25.6
20.8
25.3
22.8
7.5
5.3
..
..
9.6
0.9
12.1
10.5
15.0
16.5
6.1
20.8
40.8
26.5
32.3
18.8
5.7
..
25.2
..
11.9
29.6
40.9
8.2
10.8
0.1
20.3
..
3.3
..
29.4
28.1
11.4
8.3
32.8
..
..
..
1994
1998
1998
1996
..
1992
..
..
..
..
1998
1996
..
..
1995
..
1998
1998
1994
1993
1997
1994
..
1999
1998
1994
1996
..
1997
1993
1994
1996
..
..
1995
..
1990
..
1995
..
1995
1992
..
1996
1998
..
..
..
49.4
87.6
95.4
74.5
..
91.0
..
..
..
..
49.2
15.1
..
..
84.6
..
82.0
63.3
63.8
75.7
42.7
59.7
..
93.1
93.5
93.9
48.3
..
92.9
62.2
91.6
86.4
..
..
79.4
..
75.0
..
39.9
..
89.3
91.3
..
86.0
74.8
..
2000
2003
..
2003
2006
2007
2002
2008
2003
2004
2006
2005
2008
2002
..
..
2005
2005
2003
2006
2007
2002
2005
2003
2007
2005
2004
2006
2000
..
2008
..
2007
2004
2005
2001
2005
2007
2003
..
2006
..
2001
2007
2006
2009
2004
..
70.2
75.3
..
81.2
93.5
30.4
40.9
80.1
83.3
65.0
79.6
74.4
46.3
41.2
..
..
77.6
19.6
56.7
53.6
69.6
77.9
39.9
62.3
94.8
89.6
90.5
77.1
44.1
..
81.6
..
75.9
83.9
89.6
57.3
60.4
1.8
76.1
..
35.7
..
81.0
87.9
69.3
55.3
81.5
..
..
..
1994
1998
1998
1996
..
1992
..
..
..
..
1998
1996
..
..
1995
..
1998
1998
1994
1993
1997
1994
..
1999
1998
1994
1996
..
1997
1993
1994
1996
..
..
1995
..
1990
..
1995
..
1995
1992
..
1996
1998
..
..
..
22.3
49.1
64.1
36.0
..
68.8
..
..
..
..
18.2
4.5
..
..
41.2
..
50.0
28.5
26.5
37.4
14.7
36.1
..
61.0
62.3
67.2
17.8
..
59.4
36.5
56.5
49.7
..
..
37.9
..
54.0
..
15.0
..
61.7
50.1
..
44.5
41.7
..
2000
2003
..
2003
2006
2007
2002
2008
2003
2004
2006
2005
2008
2002
..
..
2005
2005
2003
2006
2007
2002
2005
2003
2007
2005
2004
2006
2000
..
2008
..
2007
2004
2005
2001
2005
2007
2003
..
2006
..
2001
2007
2006
2009
2004
..
42.4
33.5
..
39.3
56.1
8.2
15.2
46.8
43.9
34.2
42.4
38.8
17.8
14.6
..
..
28.9
5.0
24.9
22.3
31.0
34.8
15.1
33.1
59.5
46.9
51.8
36.5
15.9
..
42.9
..
30.6
46.9
57.2
21.6
24.7
0.4
37.5
..
12.3
..
45.8
47.5
27.9
21.3
48.3
..
1995
1996
..
1999
1995
6.8
2.5
..
6.8
6.5
..
2005
..
2007
2000
..
<2
..
2.5
2.6
1995
1996
..
1999
1995
1.4
0.3
..
1.2
1.3
..
2005
..
2007
2000
..
0.4
..
0.5
0.5
1995
1996
..
1999
1995
23.6
26.3
..
24.4
20.4
..
2005
..
2007
2000
..
18.5
..
14.0
12.8
1995
1996
..
1999
1995
6.5
5.0
..
6.5
5.8
..
2005
..
2007
2000
..
3.5
..
3.2
3.0
Part II. Millennium Development Goals
MillenniuM developMent Goals
Share of population below
national poverty linea
(poverty headcount ratio)
Surveys 1990–99c
Surveys 2000–09c
Share of urban population below
national poverty linea
(poverty headcount ratio)
Surveys 1990–99c
Surveys 2000–09c
Share of rural population below
national poverty linea
(poverty headcount ratio)
Surveys 1990–99c
Surveys 2000–09c
Year
Percent
Year
Percent
Year
Percent
Year
Year
Percent
62.3
29.0
19.4
19.2
34.0
12.2
13.2
49.6
24.6
34.5
61.5
..
29.4f
..
..
..
35.1
29.8
39.6f
10.8
30.5
51.6
33.7
41.5f
55.1f
52.0
25.4
25.5
25.4
..
49.6
17.0
36.7
43.1
23.2
45.0
35.1f
..
47.0
..
..
..
49.0
..
16.7
39.5
..
2000e
2003e
2003
2003e
2006e
2007e
2007e
2008e
2003e
2004e
2005
..
2008
..
..
..
2004
2005
2003e
2006
2007e
2002e
2005e
2003
2007
2005
2004
2006e
2000e
..
2008
2003e
2007e
2004e
2006e
2001
2005e
..
2003e
..
..
..
2001e
..
2006
2009
2006
..
14.7
..
..
..
..
..
2008
..
2007
..
..
..
1993
..
..
..
..
..
..
..
..
..
1998
..
..
1993
1999
..
..
1998
..
..
..
1994
..
1999
1998
..
..
..
1996
..
..
..
..
..
..
..
..
..
1995
..
..
..
..
1997
1998
..
..
..
47.0
..
..
..
..
..
..
..
..
..
36.4f
..
..
69.0
44.2
..
..
39.5
..
..
..
66.6f
..
71.3
65.3
..
..
..
69.4
..
..
..
..
..
..
..
..
..
31.0
..
..
..
..
44.4
66.8
..
..
2003e
2003
2003e
2006e
2007e
2007e
2008e
2003e
2004e
2005
2005
2008
..
..
..
2004
2005
2003e
2006
2007e
2002e
2005e
2003
2007
2005
2004
2006e
2000e
..
2008
2003e
2007e
2004e
2006e
2001
2005e
..
2003e
..
2005
..
2001e
2007e
2006
2009
2006
2003e
..
39.0
30.6
46.4
66.9
39.9
26.6
62.0
55.0
44.8
71.3
50.1
42.7f
..
..
..
38.9
32.7
58.0f
28.5
53.0
64.7
45.9
56.6f
63.8f
68.7
52.4
47.4
46.3
..
54.7
38.0
59.5
54.7
58.5
53.8
50.8f
..
66.4
..
23.0
..
69.2
33.4
61.7
24.5
59.3
72.0
..
..
1993
..
..
..
..
..
..
..
..
..
1998
..
..
1993
1999
..
..
1998
..
..
..
1994
..
1999
1998
..
..
..
1996
..
..
..
..
..
..
..
..
..
..
..
..
..
..
1997
1998
..
..
..
29.0
..
..
..
..
..
..
..
..
..
28.6f
..
..
62.0
36.9
..
..
19.4
..
..
..
36.7f
..
52.1
54.9
..
..
..
62.0
..
..
..
..
..
..
..
..
..
..
..
..
1995
1996
..
..
1995
22.6
19.4
..
..
6.2
..
2008
..
2007
2005
..
22.0
..
9.0
3.8
1995
..
..
..
..
..
Percent
Year
Percent
36.8
9.1
26.7
..
..
..
1993
..
..
..
..
..
..
..
..
..
1998
..
..
..
1999
..
..
1998
..
..
..
1994
..
1999
1998
..
..
..
1996
..
..
..
..
..
..
..
..
..
..
..
..
..
..
1997
1998
..
..
..
55.0
..
..
..
..
..
..
..
..
..
41.5f
..
..
..
45.4
..
..
49.6
..
..
..
68.9f
..
76.7
66.5
..
..
..
71.3
..
..
..
..
..
..
..
..
..
..
..
..
..
..
48.7
83.0
..
..
2003e
2003
2003e
2006e
2007e
2007e
2008e
2003e
2004e
2005
2005
2008
..
..
..
2004
2005
2003e
2006
2007e
2002e
2005e
2003
2007
2005
2004
2006e
2000e
..
2008
2003e
2007e
2004e
2006e
2001
2005e
..
2003e
..
..
..
2001e
2007e
2006
2009
2006
..
..
46.0
44.8
52.4
68.9
55.0
44.3
69.4
58.6
48.7
75.7
57.7
54.2f
..
..
..
39.3
44.6
67.8f
39.2
63.0
69.1
49.1
60.5f
67.7f
73.5
55.9
57.6
61.2
..
56.9
49.0
63.9
63.8
64.2
64.9
61.9f
..
78.5
..
..
..
75.0
37.4
74.3
27.2
76.8
..
..
10.6
..
4.8
..
1995
..
..
..
..
30.3
..
..
..
..
..
2008
..
2007
..
..
30.0
..
14.5
..
..
(continued)
MillenniuM developMent Goals
Part II. Millennium Development Goals
47
Table
3.1
Millennium Development Goal 1:
eradicate extreme poverty and hunger (continued)
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Population below
minimum dietary
energy consumption
Share (%) Total (millions)
2005–07d
2005–07d
Share of poorest quintile in national
consumption or incomeb
Surveys 1990–99c
Surveys 2000–09c
Prevalence of child malnutrition, underweight
(% of children under age 5)
Surveys 1990–99c
Surveys 2000–09c
Year
Percent
Year
Year
Percent
Year
Percent
..
..
1994
1998
1998
1996
..
1993
..
..
..
..
1998
1996
..
..
1995
..
1998
1998
1994
1993
1997
1995
..
1999
1998
1994
1996
..
1997
1993
1994
1996
..
..
1995
..
1990
..
1995
..
1995
1992
..
1999
1998
1995
..
..
3.1
5.9
5.1
5.7
..
2.0
..
..
..
..
5.8
6.4
..
..
7.2
..
4.0
5.6
6.4
5.2
6.0
1.5
..
5.9
4.8
4.6
6.3
..
5.7
1.5
6.0
5.0
..
..
6.5
..
1.1
..
3.6
..
2.7
7.4
..
5.9
3.3
4.6
2000
2003
..
2003
2006
2001
2001
2003
2003
2004
2006
2005
2008
2002
..
..
2005
2005
2003
2006
2007
2002
2005
2003
2007
2005
2004
2006
2000
..
2008
..
2007
2004
2006
2001
2005
2007
2003
..
2000
..
2001
2007
2006
2009
2004
..
2
6.9
..
7.0
9.0
5.6
4.5
5.2
6.3
2.6
5.5
5.0
5.6
6.0
..
..
9.3
6.1
4.8
5.2
6.4
7.2
4.7
3.0
6.4
6.2
7.0
6.5
6.2
..
5.2
..
8.3
5.1
4.2
5.2
6.2
10.8
6.1
..
3.1
..
4.5
6.8
5.4
5.8
3.6
..
1996
1996
1996
1999
..
1998
1994
1995
1997
1996
1995
..
1999
1996
1997
1996
..
..
1996
1999
1999
..
1998
1992
..
1997
1998
1996
1996
1995
1997
1992
1998
1999
1996
..
1996
..
1990
..
1999
1993
..
1999
1998
1995
1999
1999
37
26.8
15.1
33.7
..
17.8
11.8
23.3
34.3
22.3
30.7
..
18.2
16.0
13.8
38.3
..
..
23.2
20.3
21.2
..
17.6
13.8
..
35.5
26.3
38.2
20.3
13.0
28.1
21.5
45.0
27.3
24.2
..
19.6
..
25.4
..
10.1
31.8
..
25.3
23.2
21.5
19.6
11.5
2001
2006
2000
2009
2000
2006
..
2000
2004
2000
2007
2005
2006
2006
2004
2002
2005
2001
2006
2008
2008
2006
2009
2005
2007
2004
2006
2006
2008
..
2003
2007
2006
2008
2005
2009
2005
..
2008
2006
..
2006
2007
2005
2006
2006
2007
2006
27.5
20.2
10.7
26.0
38.9
16.6
..
21.8
33.9
25.0
28.2
11.8
16.7
29.6
10.6
34.5
34.6
8.8
15.8
14.3
20.8
17.4
16.4
16.6
20.4
36.8
15.5
27.9
16.7
..
21.2
17.5
39.9
26.7
18.0
13.1
14.5
..
21.3
32.8
..
31.7
6.1
16.7
22.3
16.4
14.9
14.0
41
12
25
9
62
21
10
40
37
46
69
15
14
28
..
64
41
<5
19
5
17
22
31
14
33
25
28
12
7
5
38
19
20
6
34
<5
17
7
35
..
<5
22
18
34
30
21
43
30
7.1
1.0
0.5
1.2
4.7
3.9
0.0
1.7
3.8
0.4
41.9
0.5
2.8
0.2
..
3.0
31.6
..
0.3
1.2
1.6
0.3
11.2
0.3
1.2
4.5
3.9
1.5
0.2
0.1
8.1
0.4
2.7
9.2
3.1
0.0
2.0
0.0
1.8
..
..
8.8
0.2
13.7
1.8
6.1
5.2
3.7
1995
1996
..
1999
1995
6.9
9.5
..
6.4
5.6
..
2005
..
2007
2000
..
9.0
..
6.5
5.9
1995
1998
1995
1997
1997
11.3
10.2
4.2
7.7
3.3
2005
2008
2007
2004
2006
3.7
6.8
5.6
9.9
3.3
<5
<5
<5
<5
<5
1.4
..
..
1.6
..
Percent
a. Based on nominal per capita consumption average and distributions estimated from household surveys.
b. Expenditure shares by percentiles of population, ranked by per capita expenditure.
c. Survey year refers to the year in which the underlying household survey data were collected; in cases for which the data collection period bridged two calendar years, the year in which
most of the data were collected is reported as the reference year. Data are for the most recent year available during the period specified.
d. Data for a three-year period are used for the estimation of the prevalence of undernourishment.
e. Poverty estimates based on survey data from earlier years are available but not comparable with the most recent year reported here.
f. World Bank estimates.
48
Part II. Millennium Development Goals
MillenniuM developMent Goals
Table
3.2
Millennium Development Goal 2:
achieve universal primary education
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Net primary enrollment ratio
(% of relevant age group)
1990
2000
2009
Primary completion rate
(% of relevant age group)
1990
2000
2009
Share of cohort reaching grade 5
(% of grade 1 students)
1990
2000
2007–08 a
Youth literacy rate
(% ages 15–24)
1991
2000
2009
..
41.2
86.9
..
..
71.1
92.7
57.9
..
..
..
..
..
29.3
..
..
..
..
51.4
..
24.9
..
..
70.7
..
70.3
..
..
..
97.2
44.0
79.1
22.8
..
..
96.0
45.1
..
..
..
..
..
74.3
51.4
62.3
..
..
..
..
..
82.5
36.0
43.2
..
98.9
..
53.5
72.9
..
..
54.7
26.9
68.8
37.9
40.5
..
72.1
62.9
46.6
52.1
64.9
77.5
75.2
67.6
..
..
62.6
92.9
56.0
88.8
26.7
63.0
..
..
57.5
..
..
..
89.8
39.2
71.1
52.9
80.2
..
68.5
83.9
..
94.7
..
63.3
98.9
91.6
82.6
66.7
..
..
..
..
57.2
44.4
53.5
35.7
82.7
..
..
75.9
72.9
..
82.6
73.1
..
..
90.8
72.9
76.3
94.0
90.6
89.1
54.0
..
..
97.5
73.1
94.4
..
..
84.7
..
..
96.4
93.5
92.2
90.7
..
..
19.5
89.8
19.3
40.9
54.2
53.6
30.4
16.3
..
..
58.8
40.1
32.0
..
..
..
..
..
..
18.8
..
..
58.4
..
37.0
28.1
..
29.1
113.7
26.4
..
15.8
..
49.2
77.9
41.9
..
..
..
..
..
62.7
..
35.0
..
..
93.6
..
39.3
91.0
25.1
24.6
49.9
103.2
..
22.4
..
..
..
41.8
28.0
..
36.4
23.0
..
74.1
69.5
32.1
30.7
..
60.1
..
37.6
65.4
30.8
..
102.8
16.1
91.6
17.9
..
22.3
..
39.1
107.2
..
..
86.6
35.8
60.3
..
63.2
..
61.4
..
..
62.0
..
43.0
52.4
73.4
86.6
38.0
33.5
..
55.9
74.1
46.5
35.4
46.5
47.8
55.2
..
..
82.7
61.7
..
..
70.3
..
78.8
59.2
59.4
..
89.4
56.6
87.1
40.3
..
..
83.2
56.9
105.1
..
..
93.2
57.2
..
102.3
61.4
72.5
87.1
..
..
27.3
75.7
55.6
57.2
66.6
53.0
42.7
35.6
..
..
70.6
60.8
73.9
..
..
..
..
..
..
50.6
..
..
66.3
..
34.0
32.3
..
63.8
..
33.8
..
57.0
..
51.5
..
72.8
..
..
..
..
..
60.0
..
44.5
..
..
68.7
..
84.2
89.0
69.1
58.8
..
89.1
..
54.9
..
..
..
88.0
..
..
60.5
64.6
..
73.0
66.2
..
..
..
67.2
..
36.1
..
..
..
98.4
52.5
90.9
74.0
..
41.7
..
72.3
91.0
..
..
..
..
74.0
81.4
74.7
56.7
..
..
..
..
..
75.1
72.6
77.7
..
53.6
..
..
..
..
66.1
64.3
60.9
73.1
45.9
..
..
79.0
68.6
..
..
..
..
49.4
50.7
86.9
..
97.2
53.7
91.5
64.3
..
48.5
..
69.8
94.9
..
..
..
86.0
..
80.9
..
57.7
71.0
..
..
..
..
..
53.6
..
88.2
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
91.2
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
66.4
..
..
..
..
..
73.3
83.1
..
58.5
37.6
80.2
..
..
60.7
..
94.9
..
..
..
52.6
70.7
..
59.5
80.3
90.9
..
70.2
..
..
61.3
94.5
..
..
..
..
77.6
..
..
..
..
..
..
77.2
88.4
..
74.4
..
..
..
73.1
54.3
95.2
..
76.6
..
98.2
64.7
46.3
85.3
67.7
..
66.6
..
97.9
88.7
..
97.6
65.5
80.1
61.1
70.9
92.7
92.0
75.6
..
86.5
..
67.7
96.5
70.9
93.0
..
71.8
77.2
95.3
65.0
..
57.6
..
..
85.9
93.4
77.4
..
..
74.6
98.9
87.5
..
..
56.2
92.6
91.6
86.0
..
75.8
95.8
93.8
..
..
89.7
..
80.8
..
..
51.4
80.3
82.6
87.7
..
56.7
88.5
90.5
..
..
80.4
..
83.8
..
..
68.9
80.0
97.1
99.0
..
80.1
93.1
94.5
..
..
84.2
..
..
..
..
..
..
..
..
..
..
..
..
..
99.9
79.5
..
a. Data are for the most recent year available during the period specified.
MillenniuM developMent Goals
Part II. Millennium Development Goals
49
Table
3.3
Millennium Development Goal 3:
promote gender equity and empower women
Ratio of girls to boys in primary
and secondary school
(%)
1991
2000
2009
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 Príncipe
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 literate young
women to men
(% ages 15–24)
1990
2000
2009
Women in
national parliament
(% of total seats)
1990
2000
2009
Share of women employed in
the nonagricultural sector
(%)
1990
2000
2000–09 a
..
..
108.0
..
79.0
82.3
94.0
59.1
40.9
..
..
88.5
..
72.2
..
..
..
..
..
78.0
44.0
..
..
123.8
..
95.6
80.9
57.6
68.9
100.4
72.7
110.8
53.0
76.5
94.8
..
67.4
..
61.8
..
103.5
..
..
97.1
58.1
77.9
..
96.4
..
64.2
101.6
70.1
..
..
..
..
55.8
84.1
..
85.7
69.3
71.0
81.1
77.4
65.1
95.9
81.6
89.7
61.5
65.5
97.6
107.2
71.9
..
92.6
69.5
95.3
98.6
74.9
103.2
65.0
80.2
96.0
..
81.9
103.7
..
..
100.3
..
95.5
97.5
69.1
92.8
91.4
94.4
..
..
..
85.6
92.7
85.6
103.4
68.7
63.6
..
76.8
..
..
82.0
..
77.3
87.9
..
..
95.4
77.2
..
95.4
107.1
..
96.9
100.0
78.4
..
101.3
88.3
..
75.3
..
100.3
103.1
..
103.5
..
..
99.4
89.4
..
96.1
..
98.7
95.8
..
..
..
107.4
52.9
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
105.5
..
76.8
100.0
95.9
..
..
..
..
..
..
..
..
..
81.7
..
..
..
..
..
..
91.6
88.2
..
66.6
41.7
92.4
..
..
73.6
..
100.2
..
..
..
64.3
86.2
..
61.4
101.1
114.9
..
93.9
..
..
81.9
101.7
..
..
..
..
97.9
..
..
..
..
..
..
84.4
103.2
..
76.0
..
..
..
81.1
66.9
103.2
..
99.2
..
101.7
79.4
72.8
98.7
84.7
..
84.6
..
100.5
93.6
..
98.0
84.5
97.3
79.1
81.3
101.8
114.4
114.9
..
99.0
..
90.8
102.1
81.6
104.2
..
83.6
100.5
101.0
75.7
..
71.1
..
..
92.8
103.2
97.3
..
..
82.3
101.1
15.0
3.0
5.0
..
..
14.0
12.0
4.0
..
0.0
5.0
14.0
6.0
0.0
13.0
..
..
13.0
8.0
..
..
20.0
1.0
..
..
7.0
10.0
..
..
7.0
16.0
7.0
5.0
..
17.0
12.0
13.0
16.0
..
4.0
3.0
..
4.0
..
5.0
12.0
7.0
11.0
16.0
6.0
..
8.0
6.0
6.0
11.0
7.0
2.0
..
..
12.0
..
0.0
5.0
15.0
2.0
8.0
2.0
9.0
9.0
..
4.0
4.0
..
8.0
8.0
12.0
4.0
8.0
..
22.0
1.0
..
17.0
9.0
12.0
24.0
9.0
..
30.0
..
3.0
16.0
..
18.0
10.0
14.0
37.3
10.8
11.1
15.3
30.5
13.9
18.1
10.5
5.2
3.0
8.4
7.3
8.9
13.8
10.0
22.0
21.9
16.7
9.4
8.3
..
10.0
9.8
25.0
12.5
..
20.8
10.2
22.1
17.1
34.8
26.9
12.4
7.0
56.3
7.3
22.0
23.5
13.2
6.1
44.5
18.1
13.6
30.4
11.1
30.7
15.2
15.2
..
..
33.5
12.5
14.3
..
..
..
3.8
..
25.9
26.1
..
..
10.5
..
..
..
20.9
..
..
10.8
21.4
..
..
..
10.5
..
..
37.4
11.4
..
..
..
..
..
..
..
..
21.7
..
22.2
..
..
41.0
..
16.6
15.4
..
..
42.9
..
..
..
38.9
..
..
..
..
..
..
..
..
..
..
..
..
31.7
..
..
..
..
..
..
..
..
35.8
38.6
..
42.8
..
18.6
33.0
..
..
..
..
..
41.1
..
..
..
..
..
22.0
20.4
..
24.3
43.4
..
..
22.2
38.9
46.8
..
..
..
..
..
26.7
..
..
47.3
..
..
31.7
..
..
..
..
11.4
37.7
..
34.6
35.8
37.1
..
41.4
36.1
21.1
33.0
..
10.6
..
23.2
..
44.0
..
..
30.5
..
39.0
22.0
21.9
81.6
80.5
..
68.8
84.6
..
92.5
..
82.4
99.5
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
99.9
83.2
..
2.0
4.0
..
0.0
4.0
3.0
2.0
..
1.0
12.0
7.7
1.8
7.7
10.5
22.8
..
20.5
..
..
..
..
19.0
..
..
24.3
13.1
19.0
15.8
20.8
25.0
a. Data are for the most recent year available during the period specified.
50
Part II. Millennium Development Goals
MillenniuM developMent Goals
Table
3.4
Millennium Development Goal 4:
reduce child mortality
1990
SUB–SAHARAN AFRICA
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Cape Verde
Central African Republic
Chad
Comoros
Congo, Dem. Rep.
Congo, Rep.
Côte d’Ivoire
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Under-five mortality rate
(per 1,000)
2000
2008
2009
1990
Infant mortality rate
(per 1,000 live births)
2000
2008
2009
Child immunization rate, measles
(% of children ages 12–23 months)
1990
2000
2008
2009
258
184
60
201
189
148
63
175
201
128
199
104
152
123
198
150
210
93
153
120
231
240
99
93
247
167
218
250
129
24
232
73
305
212
171
95
151
15
285
180
62
124
92
162
150
184
179
81
212
144
99
188
178
156
41
184
205
114
199
116
142
106
168
89
148
83
131
106
185
218
105
124
198
100
164
217
122
19
183
76
227
190
180
86
120
14
250
180
77
115
105
139
124
154
166
116
166
121
59
169
168
155
29
172
209
105
199
127
121
95
148
58
109
71
106
72
146
195
86
91
119
61
115
194
118
17
147
50
167
143
117
79
95
13
198
180
65
109
77
111
100
130
145
93
161
118
57
166
166
154
28
171
209
104
199
128
119
94
145
55
104
69
103
69
142
193
84
84
112
58
110
191
117
17
142
48
160
138
111
78
93
12
192
180
62
108
73
108
98
128
141
90
153
111
46
110
114
91
49
115
120
90
126
67
105
95
120
92
124
68
104
76
137
142
64
74
165
102
129
139
81
21
155
49
144
126
103
62
73
13
166
109
48
78
67
99
89
111
108
54
126
89
66
102
107
96
33
119
122
81
126
74
97
84
102
58
91
61
93
68
111
129
66
86
134
65
99
120
77
17
123
50
107
114
108
56
61
12
150
109
54
73
71
86
78
94
99
69
101
76
44
92
102
95
24
113
124
76
126
80
85
76
90
41
69
53
80
49
90
117
56
66
85
43
71
103
75
15
99
35
79
89
74
52
52
11
126
109
45
70
53
70
66
81
88
58
98
75
43
91
101
95
23
112
124
75
126
81
83
75
88
39
67
52
78
47
88
115
55
61
80
41
69
101
74
15
96
34
76
86
70
52
51
11
123
109
43
69
52
68
64
79
86
56
38
79
87
79
74
56
79
82
32
87
38
75
56
85
88
..
38
76
86
61
35
53
78
80
..
47
81
43
38
76
59
..
25
54
83
71
51
86
..
30
79
57
85
80
73
52
90
87
41
70
91
51
76
49
86
36
28
70
46
34
71
50
51
86
52
55
92
90
42
71
78
74
63
55
73
55
62
84
71
69
37
33
74
69
48
97
37
35
72
58
92
78
58
57
85
75
79
66
94
75
84
80
96
62
23
76
67
79
63
73
51
95
74
55
91
86
51
76
76
85
64
70
88
71
65
98
77
73
66
41
92
93
77
99
66
24
62
79
95
88
77
68
85
70
77
72
94
75
91
74
96
62
23
79
76
76
67
73
51
95
75
55
96
93
51
76
74
85
64
64
92
71
59
99
77
76
73
41
92
90
79
97
71
24
62
82
95
91
84
68
85
76
61
90
36
89
50
46
47
25
55
27
34
23
19
39
21
32
21
19
38
21
51
66
32
69
40
40
38
23
46
23
30
20
17
35
18
29
18
17
33
18
83
86
89
79
93
80
98
93
93
95
88
92
98
96
98
88
95
98
98
98
MillenniuM developMent Goals
Part II. Millennium Development Goals
51
Table
3.5
Millennium Development Goal 5:
improve maternal health
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Maternal mortality ratio
(per 100,000 live births)
Modeled estimate
National estimate
1990
2008
1990–99a
2000–09a
Births attended by skilled health staff
(% of total)
Surveys 1990–99a
Surveys 2000–09a
Year
1,000
790
83
770
1,200
680
230
880
1,300
530
900
460
690
370
1,000
930
990
260
750
630
1,200
1,200
380
370
1,100
710
910
1,200
780
72
1,000
180
1,400
1,100
1,100
..
750
..
1,300
1,100
230
830
260
880
650
670
390
390
610
410
190
560
970
600
94
850
1,200
340
670
580
470
300
280
280
470
260
400
350
680
1,000
530
530
990
440
510
830
550
36
550
180
820
840
540
..
410
..
970
1,200
410
750
420
790
350
430
470
790
..
..
498
326
484
..
..
..
1,100
830
..
..
..
600
74
..
998
..
..
..
..
530
910
..
..
..
..
..
..
..
..
..
..
590
..
..
..
560
..
..
1,000
150
..
229
..
478
..
..
..
397
198
307
615
669
16
543
1,099
380
549
781
543
546
..
..
673
519
730
451
980
405
488
762
994
498
807
464
686
22
408
449
648
545
750
148
401
57
857
1,044
166
1,107
589
578
..
435
591
555
250
220
100
270
130
120
82
64
110
60
..
117
..
77
332
..
55
..
132
..
Percent
Year
Percent
1996
1996
1996
1999
..
1998
1998
1995
1997
1996
..
..
1999
..
1994
1995
..
..
1990
1998
1999
1995
1998
1993
..
1997
1992
1996
1991
1999
1997
1992
1998
1999
1992
..
1999
..
..
1999
1998
1999
1994
1999
1998
1995
1999
1999
22.5
59.8
87
31
..
55
88.5
45.9
15
51.6
..
..
47.1
..
5
20.6
..
..
44.1
44.3
34.8
25
44.3
49.6
..
47.3
54.8
40
40
98.5
44.2
68.2
17.6
41.6
25.8
..
48.3
..
..
32.2
84.4
56.9
56
43.8
50.5
37.8
47.1
72.5
2007
2006
2007
2006
2005
2006
2005
2009
2004
2000
2007
2005
2006
2006
2000
2002
2005
2000
2006
2008
2007
2006
2009
2009
2007
2009
2006
2006
2007
2005
2008
2007
2006
2008
2008
2009
2005
..
2008
2006
2003
2006
2007
2005
2006
2006
2007
2009
47.3
74.0
94.6
53.5
33.6
63.0
77.5
43.7
14.4
61.8
74.0
83.4
56.8
92.9
64.6
28.3
5.7
85.5
56.8
57.1
46.1
38.8
43.8
61.5
46.3
43.9
53.6
49.0
60.9
99.2
55.3
81.4
32.9
38.9
52.1
81.7
51.9
..
42.4
33.0
91.2
49.2
69.0
43.4
62.0
41.9
46.5
60.2
1992
1998
1999
1995
1995
77
55.2
99
39.6
80.5
2006
2008
..
2004
2006
95.2
78.9
..
62.6
94.6
a. Data are for the most recent year available during the period specified.
52
Part II. Millennium Development Goals
MillenniuM developMent Goals
Table
3.6
Millennium Development Goal 6:
combat HIV/AIDS, malaria, and other diseases
Prevalence of HIV
(% ages 15–49)
1990
2009
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Contraceptive use, any method
(% of married women ages 15–49)
Surveys 2000–09a
Surveys 1990–99a
Children sleeping under
insecticide-treated nets
(% of children under age 5)
Surveys 2000–09a
Year
Percent
Year
Percent
Year
Percent
0.5
0.2
3.5
3.9
3.9
0.6
..
3.1
1.1
<0.1
..
5.2
2.4
0.9
0.1
0.3
..
0.9
0.1
0.3
1.1
0.3
3.9
0.8
0.3
0.2
7.2
0.4
0.2
<0.1
1.2
1.6
0.1
1.3
5.2
..
0.2
..
<0.1
0.1
0.7
0.1
2.3
4.8
0.6
10.2
12.7
10.1
2.0
1.2
24.8
1.2
3.3
5.3
..
4.7
3.4
0.1
..
3.4
3.4
2.5
5.0
0.8
..
5.2
2.0
1.8
1.3
2.5
6.3
23.6
1.5
0.2
11.0
1.0
0.7
1.0
11.5
13.1
0.8
3.6
2.9
..
0.9
..
1.6
0.7
17.8
1.1
25.9
5.6
3.2
6.5
13.5
14.3
1996
1996
..
1999
..
1998
1998
1995
1997
1996
1991
..
1999
..
..
1995
1990
..
1990
1999
1999
..
1998
1992
..
1997
1996
1996
1991
1999
1997
1992
1998
1999
1996
..
1999
..
..
1999
1998
1993
..
1999
1999
1995
1999
1999
8.1
16.4
..
11.9
..
19.3
52.9
14.8
4.2
21.0
7.7
..
15.0
..
..
8.0
4.3
..
11.8
22.0
6.2
..
39.0
23.2
..
19.3
21.9
6.7
3.3
26.0
5.6
28.9
8.2
15.3
13.7
..
10.5
..
..
7.9
56.3
9.9
..
25.4
23.5
14.8
22.0
53.5
2001
2006
2007
2006
2005
2006
2005
2006
2004
2000
2007
2005
2006
2008
..
2002
2005
2000
2001
2008
2005
2006
2009
2009
2007
2009
2006
2006
2007
2002
2008
2007
2006
2008
2008
2009
2005
..
2008
2006
2003
2006
2007
2005
2006
2006
2007
2009
6.2
17.0
52.8
17.4
9.1
29.2
61.3
19.0
2.8
25.7
20.6
44.3
12.9
22.5
..
8.0
14.7
32.7
17.5
23.5
9.1
10.3
45.5
47.0
11.4
39.9
41.0
8.2
9.3
75.9
16.2
55.1
11.2
14.6
36.4
38.4
11.8
..
8.2
14.6
59.9
7.6
50.6
26.4
16.8
23.7
40.8
64.9
2007
2006
..
2006
2005
2006
..
2006
2000
2000
2007
2005
2006
2009
2000
2002
2007
..
2006
2008
2008
2006
2009
..
2009
2009
2006
2006
2004
..
2008
2006
2009
2008
2008
2009
2009
..
2008
2006
..
2006
2007
2008
2006
2006
2008
2009
18
20
..
10
8
13
..
15
1
9
6
6
3
20
1
4
33
..
49
28
5
39
46
..
26
46
25
27
2
..
23
11
43
6
56
56
29
..
26
11
..
28
1
26
38
10
41
17
<0.1
<0.1
..
<0.1
<0.1
0.1
<0.1
..
0.1
<0.1
1995
1998
1995
1997
1995
52.0
51.7
45.2
58.8
60.0
2006
2008
..
2004
2006
61.4
60.3
..
63.0
60.2
..
..
..
..
..
..
..
..
..
..
(continued)
MillenniuM developMent Goals
Part II. Millennium Development Goals
53
Table
3.6
Millennium Development Goal 6:
combat HIV/AIDS, malaria, and other diseases (continued)
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Tuberculosis treatment success rate
(% of registered cases)
Surveys 2000–08a
Surveys 1990–99a
1990
Incidence of tuberculosis
(per 100,000 people)
1999
2009
Year
Percent
Year
205
77
307
95
154
81
175
145
125
85
165
169
177
619
86
72
159
153
185
223
119
158
112
184
199
177
258
275
228
28
181
322
125
131
167
135
195
43
207
285
301
119
267
226
308
163
297
329
245
84
588
182
295
154
162
277
240
59
315
324
338
619
97
84
304
210
221
212
190
188
382
519
237
213
417
297
272
25
347
616
149
250
319
116
232
37
355
285
479
119
691
232
367
324
603
628
298
93
694
215
348
182
148
327
283
39
372
382
399
620
117
99
359
501
269
201
318
229
305
634
288
261
304
324
330
22
409
727
181
295
376
98
282
31
644
285
971
119
1257
183
446
293
433
742
1998
1999
1999
1999
1998
1999
..
1995
1998
1999
1999
1999
1999
1999
1997
1999
1999
1998
1997
1999
1999
1999
1999
1999
1999
1997
1999
1999
..
1999
1999
1999
1999
1999
1999
1999
1999
1999
1999
1999
1999
1999
..
1999
1999
1999
1999
1999
68.0
77.0
71.0
61.0
74.0
75.0
..
37.0
64.0
93.0
69.0
61.0
63.0
72.0
82.0
44.0
74.0
50.0
70.0
51.0
74.0
35.0
79.0
69.0
74.0
64.0
71.0
69.0
..
87.0
71.0
51.0
60.0
75.0
67.0
81.0
58.0
91.0
75.0
88.0
57.0
80.0
..
78.0
76.0
61.0
69.0
73.0
2008
2008
2008
2008
2008
2007
2008
2008
2006
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
2008
70.0
89.0
65.0
76.0
90.0
76.0
74.0
71.0
54.0
90.0
87.0
76.0
76.0
84.0
56.0
76.0
84.0
53.0
84.0
86.0
78.0
70.0
85.0
73.0
79.0
81.0
87.0
82.0
68.0
87.0
84.0
82.0
81.0
78.0
87.0
94.0
84.0
100.0
86.0
81.0
76.0
81.0
68.0
88.0
79.0
70.0
88.0
74.0
38
34
40
147
29
47
27
40
123
26
59
19
40
92
24
1999
1999
1999
1999
1999
87.0
85.0
67.0
88.0
91.0
2008
2008
2008
2008
2008
90.0
89.0
69.0
85.0
86.0
Percent
a. Data are for the 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
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
1990
Forest area
(% of total land area)
2000
2010
Terrestrial protected areas
(% of total land area)
1990
2000
2009
GDP per unit of energy use
(2005 PPP $ per kg of oil equivalent)
1990
2000
2008
48.9
52.1
24.2
25.0
11.3
51.4
14.3
37.2
10.4
6.4
70.7
66.5
32.1
0.2
66.3
..
15.2
85.4
44.2
32.7
29.6
78.8
6.5
1.3
51.2
23.5
41.4
11.5
0.4
19.1
55.2
10.6
1.5
18.9
12.9
28.1
48.6
88.5
43.5
13.2
7.6
32.1
27.4
46.8
12.6
24.1
71.0
57.3
47.9
45.8
22.1
22.8
7.7
46.8
20.4
36.8
9.8
4.3
69.4
66.1
32.5
0.2
62.1
15.6
13.7
85.4
46.1
26.8
28.1
75.4
6.3
1.4
48.1
22.6
37.9
10.9
0.3
19.1
52.4
9.8
1.0
14.4
13.9
28.1
46.2
88.5
40.8
12.0
7.6
29.7
30.1
42.3
8.9
19.6
68.8
48.8
46.9
41.2
20.0
20.6
6.7
42.1
21.1
36.3
9.2
1.6
68.0
65.6
32.7
0.3
58.0
15.2
12.3
85.4
48.0
21.7
26.6
71.9
6.1
1.4
44.9
21.6
34.4
10.2
0.2
17.2
49.6
8.9
1.0
9.9
17.6
28.1
44.0
89.1
38.1
10.8
4.7
29.4
32.7
37.7
5.3
15.2
66.5
40.4
12.4
23.8
30.3
13.3
3.8
7.0
2.5
14.4
9.4
0.0
10.0
5.4
22.6
0.0
7.3
4.9
17.7
4.2
1.5
13.9
6.8
7.6
11.5
0.5
18.1
2.1
15.0
2.3
0.5
1.7
14.8
14.4
6.8
11.6
9.9
..
24.1
42.0
5.0
0.6
6.5
4.7
3.0
26.5
11.3
7.3
36.0
18.0
12.4
23.8
30.9
13.5
4.8
8.7
2.5
14.7
9.4
0.0
10.0
7.8
22.6
0.0
19.2
4.9
17.7
5.2
1.5
14.0
6.8
16.1
11.6
0.5
18.1
2.9
15.0
2.3
0.5
4.5
14.8
14.5
6.8
12.8
9.9
..
24.1
42.0
5.0
0.6
6.9
4.9
3.0
26.9
11.3
7.9
36.0
18.0
12.4
23.8
30.9
13.9
4.8
9.2
2.5
14.7
9.4
0.0
10.0
9.4
22.6
0.0
19.2
5.0
18.4
14.9
1.5
14.0
6.8
16.1
11.6
0.5
18.1
2.9
15.0
2.4
0.5
4.5
15.8
14.5
6.8
12.8
10.0
..
24.1
42.0
5.0
0.6
6.9
4.9
3.0
27.7
11.3
9.7
36.0
28.0
5.8
3.2
7.6
..
..
5.1
..
..
..
..
1.9
10.7
5.5
..
..
..
1.8
11.8
..
2.5
..
..
3.0
..
..
..
..
..
..
..
0.9
..
..
2.0
..
..
6.3
..
..
..
3.1
2.5
..
2.2
2.7
..
1.8
..
4.9
4.3
9.1
..
..
4.6
..
..
..
..
0.8
11.5
4.5
..
..
3.5
1.9
11.2
..
2.6
..
..
2.9
..
..
..
..
..
..
..
1.3
8.4
..
2.0
..
..
6.0
..
..
..
3.0
3.4
..
2.1
2.0
..
1.7
..
8.8
3.9
11.6
..
..
5.4
..
..
..
..
0.8
9.6
3.1
..
..
3.8
2.0
9.4
..
3.4
..
..
3.1
..
..
..
..
..
..
..
1.9
7.3
..
2.6
..
..
7.1
..
..
..
3.5
5.3
..
2.6
1.9
..
2.1
..
0.7
0.0
0.1
11.3
4.1
0.7
0.1
0.1
11.2
5.4
0.6
0.1
0.1
11.5
6.5
6.3
1.9
0.1
1.2
1.3
6.3
4.3
0.1
1.5
1.3
6.3
5.9
0.1
1.5
1.3
7.1
5.8
..
9.7
6.6
6.9
6.2
4.0
8.3
7.1
6.8
5.8
5.2
8.4
8.3
(continued)
MillenniuM developMent Goals
Part II. Millennium Development Goals
55
Table
3.7
Millennium Development Goal 7:
ensure environmental sustainability (continued)
Carbon dioxide emissions
per capita
(metric tons)
1990
2000
2007
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
56
Population with sustainable access
to an improved water source
(%)
1990
2000
2008
Population with sustainable access
to improved sanitation
(%)
1990
2000
2008
0.4
0.1
1.6
0.1
0.1
0.1
0.2
0.1
0.0
0.2
0.1
0.5
0.5
0.7
0.3
..
0.1
6.6
0.2
0.3
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
9.5
0.2
0.5
0.1
0.2
0.0
0.3
1.5
0.7
0.2
2.5
0.1
0.0
0.2
0.4
0.1
0.0
0.2
0.0
0.3
0.4
0.6
0.9
0.2
0.1
1.0
0.2
0.3
0.2
0.2
0.3
..
0.2
0.2
0.1
0.1
0.5
2.3
0.1
1.0
0.1
0.6
0.1
0.6
0.4
7.0
0.1
0.1
8.4
0.2
1.1
0.1
0.3
0.1
0.2
1.1
1.4
0.5
2.6
0.1
0.0
0.3
0.6
0.1
0.0
0.2
0.0
0.4
0.3
0.6
7.5
0.1
0.1
1.4
0.2
0.4
0.1
0.2
0.3
..
0.2
0.1
0.1
0.0
0.6
3.1
0.1
1.5
0.1
0.6
0.1
0.8
0.5
7.3
0.2
0.1
9.0
0.3
0.9
0.1
0.2
0.1
0.2
0.8
36.0
56.0
93.0
41.0
70.0
50.0
..
58.0
38.0
87.0
45.0
..
76.0
77.0
..
43.0
17.0
..
74.0
54.0
52.0
..
43.0
61.0
58.0
31.0
40.0
29.0
30.0
99.0
36.0
64.0
35.0
47.0
68.0
..
61.0
..
..
..
83.0
65.0
..
55.0
49.0
43.0
49.0
78.0
41.0
66.0
94.0
60.0
72.0
64.0
83.0
63.0
45.0
92.0
44.0
70.0
78.0
84.0
43.0
54.0
28.0
85.0
84.0
71.0
62.0
55.0
52.0
74.0
65.0
37.0
63.0
44.0
40.0
99.0
42.0
81.0
42.0
53.0
67.0
79.0
65.0
..
55.0
23.0
86.0
61.0
55.0
54.0
55.0
57.0
54.0
80.0
50.0
75.0
95.0
76.0
72.0
74.0
84.0
67.0
50.0
95.0
46.0
71.0
80.0
92.0
..
61.0
38.0
87.0
92.0
82.0
71.0
61.0
59.0
85.0
68.0
41.0
80.0
56.0
49.0
99.0
47.0
92.0
48.0
58.0
65.0
89.0
69.0
..
49.0
30.0
91.0
57.0
69.0
54.0
60.0
67.0
60.0
82.0
25.0
5.0
36.0
6.0
44.0
47.0
..
11.0
6.0
17.0
9.0
..
20.0
66.0
..
9.0
4.0
..
..
7.0
9.0
..
26.0
32.0
11.0
8.0
42.0
26.0
16.0
91.0
11.0
25.0
5.0
37.0
23.0
..
38.0
..
..
..
69.0
34.0
..
24.0
13.0
39.0
46.0
43.0
40.0
9.0
50.0
8.0
45.0
47.0
45.0
22.0
7.0
28.0
16.0
30.0
22.0
63.0
51.0
11.0
8.0
36.0
63.0
9.0
15.0
18.0
29.0
29.0
14.0
10.0
50.0
32.0
21.0
91.0
14.0
29.0
7.0
34.0
40.0
21.0
45.0
..
11.0
22.0
73.0
34.0
49.0
24.0
12.0
44.0
47.0
44.0
57.0
12.0
60.0
11.0
46.0
47.0
54.0
34.0
9.0
36.0
23.0
30.0
23.0
56.0
..
14.0
12.0
33.0
67.0
13.0
19.0
21.0
31.0
29.0
17.0
11.0
56.0
36.0
26.0
91.0
17.0
33.0
9.0
32.0
54.0
26.0
51.0
..
13.0
23.0
77.0
34.0
55.0
24.0
12.0
48.0
49.0
44.0
3.1
1.3
9.2
0.9
1.6
3.8
2.0
9.3
1.2
2.1
4.1
2.3
9.3
1.5
2.3
94.0
90.0
54.0
74.0
81.0
89.0
96.0
54.0
78.0
90.0
83.0
99.0
..
81.0
94.0
88.0
72.0
97.0
53.0
74.0
92.0
86.0
97.0
64.0
81.0
95.0
94.0
97.0
69.0
85.0
Part II. Millennium Development Goals
MillenniuM developMent Goals
Table
3.8
Millennium Development Goal 8:
develop a global partnership for development
Heavily Indebted Poor Countries
(HIPC) Debt Initiative
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Debt sustainability
Debt service relief
Public and publicly guaranteed debt service
committed
(% of exports, excluding worker remittances)
($ millions)a
1990
2000
2009
Decision pointa
Completion pointa
..
Jul. 2000
..
Jul. 2000
Aug. 2005
Oct. 2000
..
Sep. 2007
May 2001
Jun. 2010
Jul. 2003
Mar. 2006
Mar. 2009
..
..
..
Nov. 2001
..
Dec. 2000
Feb. 2002
Dec. 2000
Dec. 2000
..
..
Mar. 2008
Dec. 2000
Dec. 2000
Sep. 2000
Feb. 2000
..
Apr. 2000
..
Dec. 2000
..
Dec. 2000
Dec. 2000
Jun. 2000
..
Mar. 2002
..
..
..
..
Apr. 2000
Nov. 2008
Feb. 2000
Dec. 2000
..
..
Mar. 2003
..
Apr. 2002
Jan. 2009
Apr. 2006
..
Jun. 2009
..
..
Jul. 2010
Jan. 2010
..
..
..
..
Apr. 2004
..
Dec. 2007
Jul. 2004
..
..
..
..
Jun. 2010
Oct. 2004
Aug. 2006
Mar. 2003
Jun. 2002
..
Sep. 2001
..
Apr. 2004
..
Apr. 2005
Mar. 2007
Apr. 2004
..
Dec. 2006
..
..
..
..
Nov. 2001
..
May 2000
Apr. 2005
..
..
460
..
930
1,366
4,917
..
804
260
136
15,222
1,738
3,415
..
..
..
3,275
..
112
3,500
800
790
..
..
4,600
1,900
1,628
895
1,100
..
4,300
..
1,190
..
1,316
263
850
..
994
..
..
..
..
3,000
360
1,950
3,900
..
7.1
8.4
4.3
7.7
40.7
12.5
8.9
7.5
2.3
2.5
..
30.9
14.7
..
..
..
33.2
3.8
17.3
19.9
17.7
22.0
22.7
4.1
..
31.9
22.4
9.7
24.8
4.5
17.2
..
3.2
22.3
9.4
28.6
13.7
7.6
7.8
..
..
4.5
5.3
25.1
8.6
47.1
12.6
18.2
20.4
10.7
2.0
15.1
25.1
14.0
10.5
..
..
..
..
0.5
14.9
4.8
..
2.8
12.2
8.8
..
12.0
17.6
..
15.7
10.3
..
8.4
10.8
10.2
..
16.4
7.0
..
6.0
8.2
15.3
20.3
13.2
3.3
29.6
..
5.5
10.1
2.1
10.3
3.2
6.5
17.2
..
8.4
..
1.0
..
10.1
2.5
5.1
..
..
..
..
..
6.6
5.7
..
..
3.0
..
8.7
2.5
10.1
..
4.5
2.5
11.2
..
..
..
..
1.9
1.4
..
..
0.7
4.7
16.2
..
6.2
2.1
..
2.4
5.6
2.1
1.0
..
1.7
1.6
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
63.3
23.2
..
23.1
23.0
..
8.5
..
23.0
20.0
..
6.2
..
6.4
9.0
(continued)
MillenniuM developMent Goals
Part II. Millennium Development Goals
57
Table
3.8
Millennium Development Goal 8:
develop a global partnership for development (continued)
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Youth unemployment rate (ages 15–24)
Total
Male
Female
(share of total
(share of male
(share of female
labor force)
labor force)
labor force)
Year
Percent
Year
Year
Percent
Percent
Fixed-line and mobile
telephone subscribers
(per 100 people)
1990
2000
2009
Information and communication
..
2002
2000
..
..
..
..
..
..
..
..
..
..
..
..
..
2006
..
..
2000
..
..
..
..
2007
2005
..
..
..
2009
..
2004
2001
..
..
..
2006
2002
2004
..
2009
..
..
2006
..
..
2000
2002
..
0.82
13.6
..
..
..
..
..
..
..
..
..
..
..
..
..
24.89
..
..
16.55
..
..
..
..
4.73
2.27
..
..
..
21.36
..
41.7
3.16
..
..
..
14.8
20.33
5.15
..
48.15
..
..
8.84
..
..
21.36
24.88
..
2002
2000
..
..
..
..
..
..
..
..
..
..
..
..
..
2006
..
..
2000
..
..
..
..
2007
2005
..
..
..
2009
..
2004
2001
..
..
..
2006
..
2004
..
2009
..
..
2006
..
..
2000
2002
..
1.07
13.23
..
..
..
..
..
..
..
..
..
..
..
..
..
19.51
..
..
16.42
..
..
..
..
5.73
1.74
..
..
..
18.08
..
36.68
3.95
..
..
..
11.92
..
7.27
..
44.59
..
..
7.39
..
..
23.11
28.18
..
2002
2000
..
..
..
..
..
..
..
..
..
..
..
..
..
2006
..
..
2000
..
..
..
..
2007
2005
..
..
..
2009
..
2004
2001
..
..
..
2006
..
2004
..
2009
..
..
2006
..
..
2000
2002
..
0.61
14.01
..
..
..
..
..
..
..
..
..
..
..
..
..
29.42
..
..
16.68
..
..
..
..
3.73
2.77
..
..
..
26.25
..
47.05
1.67
..
..
..
20.11
..
3.5
..
52.51
..
..
10.11
..
..
19.48
21.4
0.7
0.3
2.0
0.2
0.1
0.3
2.3
0.2
0.1
0.8
0.1
0.7
0.6
1.0
0.3
..
0.3
2.2
0.7
0.3
0.2
0.6
0.8
0.8
0.4
0.3
0.3
0.1
0.3
5.5
0.4
3.7
0.1
0.3
0.2
1.9
0.6
12.4
0.3
0.2
9.4
0.2
1.6
0.3
0.3
0.2
0.8
1.2
0.6
1.6
20.8
0.7
0.6
1.3
16.9
0.4
0.2
1.3
0.1
3.0
4.3
1.4
2.1
0.8
0.4
12.9
3.0
1.8
0.8
0.9
1.3
2.3
0.3
0.8
0.8
0.5
1.3
38.8
0.8
10.5
0.2
0.5
0.7
3.3
4.6
57.4
0.7
1.4
30.2
1.2
6.0
0.8
1.8
0.8
1.7
4.1
45.5
57.8
103.5
22.0
10.5
39.6
91.8
4.1
24.1
19.0
15.5
59.6
64.7
16.9
67.3
3.7
6.0
94.9
86.9
64.5
55.9
35.1
50.3
33.9
21.3
31.5
16.9
29.4
68.6
114.9
26.4
62.6
17.4
48.2
24.6
44.1
57.3
130.0
20.9
8.1
102.9
37.2
59.1
40.3
35.8
29.4
34.8
27.0
..
..
..
0.0
..
..
..
..
..
0.0
..
..
..
0.2
..
..
..
..
..
0.0
..
..
0.0
..
..
..
..
..
..
0.4
..
..
..
..
..
..
0.2
..
..
..
0.7
..
..
..
..
..
..
0.0
0.1
0.2
3.5
0.1
0.1
0.3
5.7
0.2
0.1
0.6
..
0.4
0.5
0.9
0.4
0.2
0.1
1.0
1.2
0.3
0.4
..
0.5
..
..
0.2
0.1
0.1
1.0
10.1
0.3
4.1
0.1
0.6
..
..
1.6
13.6
..
..
6.6
0.3
1.1
0.3
1.9
0.3
0.7
1.6
0.7
0.7
6.3
0.6
0.9
1.1
14.0
0.3
0.2
0.9
0.0
0.6
1.7
4.3
1.5
1.0
0.7
3.4
3.5
1.1
0.5
0.2
1.4
0.3
..
0.6
0.2
0.8
4.5
17.6
1.4
23.9
0.1
0.9
0.3
3.9
2.2
21.2
..
0.9
8.4
10.7
3.7
0.9
3.1
1.7
1.1
7.6
..
..
0.1
..
0.0
..
..
..
..
..
..
..
0.0
0.0
..
0.0
0.0
..
0.0
0.0
0.0
..
0.0
..
..
..
..
..
..
..
..
0.0
..
..
..
..
0.0
..
0.0
0.0
0.7
0.0
0.0
..
0.0
0.0
0.0
0.0
0.1
0.2
2.9
0.1
0.1
0.3
1.8
0.1
0.0
0.3
0.0
0.0
0.2
0.2
0.1
0.1
0.0
1.2
0.9
0.2
0.1
0.2
0.3
0.2
0.0
0.2
0.1
0.1
0.2
7.3
0.1
1.6
0.0
0.1
0.1
4.6
0.4
7.4
0.1
0.2
5.5
0.0
0.9
0.1
1.9
0.2
0.2
0.4
3.3
2.2
6.2
1.1
0.8
3.8
29.7
0.5
1.7
3.7
0.6
6.7
4.6
3.0
2.1
4.9
0.5
6.7
7.6
5.4
0.9
2.3
10.0
3.7
0.5
1.6
4.7
1.9
2.3
22.7
2.7
5.9
0.8
28.4
4.5
16.4
7.4
38.7
0.3
1.2
9.0
9.9
7.6
1.6
5.4
9.8
6.3
11.4
2006
2007
..
2009
2005
24.3
24.8
..
21.88
30.68
2004
2007
..
2009
2005
42.85
17.16
..
22.77
31.35
2004
2007
..
2009
2005
46.27
47.89
..
19.37
29.32
3.2
2.8
5.0
1.6
3.7
6.1
9.8
12.1
13.1
11.2
101.2
79.1
95.1
90.1
105.8
0.1
..
..
..
0.3
0.7
1.1
..
1.2
2.2
1.1
3.9
2.2
5.7
9.7
0.0
0.0
..
0.0
0.0
0.5
0.6
0.2
0.7
2.7
13.5
20.0
5.5
32.2
33.6
Personal computers
(per 100 people)
1990
2000 2005–09b
Internet users
(per 100 people)
1995
2000
2009
Note: 0.0 indicates less than 1 but more than 0.
a. As of 2010.
b. Data are for the most recent year available during the period specified.
58
Part II. Millennium Development Goals
MillenniuM developMent Goals
Table
Drivers of growth
4.1
Doing Business indicators
Overall ranking
2009
2010
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
164
172
50
154
181
173
142
182
183
159
179
177
168
157
161
180
103
158
141
77
178
175
94
137
152
138
132
155
167
20
130
68
171
134
70
176
151
92
143
..
32
153
126
125
162
129
84
156
42
136
99
..
114
58
163
170
52
151
181
168
132
182
183
159
175
177
169
158
164
180
104
156
146
67
179
176
98
138
155
140
133
153
165
20
126
69
173
137
58
178
152
95
143
..
34
154
118
128
160
122
76
157
42
136
94
..
114
55
Number of
procedures
2009
2010
Starting a business
Time required
for each
Cost
procedure
(% of GNI
(days)
per capita)
2009
2010
2009
2010
9
8
7
10
4
11
10
9
8
13
11
14
10
10
11
20
13
5
9
8
7
13
16
12
7
5
2
10
6
9
5
10
10
9
8
2
10
4
10
6
..
6
10
12
12
7
18
6
9
9
14
6
..
6
10
47
68
31
61
14
32
35
24
22
75
24
127
160
40
37
136
84
9
58
27
12
41
216
34
40
20
7
39
8
19
6
26
66
17
31
3
144
8
39
12
..
22
36
60
29
75
25
18
97
13.5
24
7
..
12
11
9
8
7
10
4
11
6
8
8
13
11
10
10
10
11
20
13
5
9
8
7
13
17
11
7
5
2
10
6
9
5
9
10
9
8
2
10
4
10
6
..
6
10
12
12
7
18
6
9
9
14
6
..
6
10
45
68
31
61
14
32
19
11
22
75
24
84
160
40
37
136
84
9
58
27
12
41
216
33
40
20
7
39
8
19
6
13
66
17
31
3
144
8
39
12
..
22
36
56
29
75
25
18
90
13.5
24
7
..
12
11
106.8
151.1
155.5
2.1
50.3
151.6
115.0
17.0
244.9
246.4
182.1
847.6
86.5
133.3
195.1
100.4
76.5
18.9
17.8
215.1
24.8
139.2
181.5
36.5
27.0
52.9
6.2
108.0
86.9
34.7
4.1
19.3
20.4
118.7
76.7
10.1
81.7
63.7
19.2
118.8
..
5.9
36.0
33.9
36.8
205.0
84.4
28.4
353.8
12.5
12.1
16.1
..
16.1
5.7
97.0
163.0
152.6
2.2
49.8
129.3
51.2
18.5
228.4
226.9
176.5
735.1
111.4
133.0
169.9
104.3
69.2
14.1
21.9
199.6
20.3
146.6
183.3
38.3
26.0
54.6
12.9
108.4
79.7
33.6
3.8
13.9
18.5
118.6
78.9
8.8
77.3
63.1
17.5
110.7
..
6.0
33.6
33.0
30.9
178.1
94.4
27.9
182.8
10.0
12.9
6.3
..
15.8
5.0
Registering property
Minimum capital
(% of GNI
per capita)
2009
2010
149.0
29.0
290.8
0.0
428.2
0.0
182.9
38.9
507.1
369.3
261.8
0.0
96.5
204.9
500.5
12.4
297.0
492.4
26.5
0.0
13.4
495.4
415.8
0.0
11.9
0.0
207.4
0.0
334.6
450.4
0.0
0.0
0.0
613.7
0.0
0.0
0.0
206.9
0.0
0.0
..
0.0
0.0
0.5
0.0
514.0
0.0
1.3
0.0
10.7
31.0
0.0
..
11.8
0.0
151.9
28.7
285.3
0.0
416.2
0.0
191.8
42.4
468.6
386.7
245.5
0.0
129.8
202.9
434.1
21.3
268.4
367.7
32.7
0.0
11.0
519.1
415.1
0.0
12.0
0.0
248.1
0.0
306.8
412.1
0.0
0.0
0.0
613.0
0.0
0.0
385.7
205.1
0.0
0.0
..
0.0
0.0
0.5
0.0
486.9
0.0
0.0
0.0
11.4
34.4
0.0
..
11.2
0.0
Number of
procedures
2009
2010
7
7
4
5
4
5
5
6
5
6
5
6
6
6
7
6
11
10
7
5
5
6
9
8
6
10
7
6
5
4
4
8
9
4
13
4
7
6
4
7
..
6
6
9
9
5
13
6
5
8
11
7
..
8
4
7
7
4
5
4
5
5
6
5
6
5
6
6
6
7
6
11
10
7
5
5
6
9
8
6
10
7
6
5
4
4
8
9
4
13
4
7
6
4
7
..
6
6
9
9
5
13
5
5
8
11
7
..
8
4
Time required
(days)
2009
2010
72
184
120
16
59
94
93
73
75
44
24
54
55
62
40
23
78
41
39
66
34
104
211
64
101
50
74
88
29
49
26
42
23
35
82
60
62
124
33
236
..
24
9
44
73
295
77
39
31
51
47
72
..
47
39
67
184
120
16
59
94
93
73
75
44
24
54
55
62
40
23
78
41
39
66
34
104
211
64
101
50
74
49
29
49
26
42
23
35
82
55
62
122
33
86
..
24
9
44
73
295
77
40
31
51
47
72
..
47
39
Cost
(% of property
value)
2009
2010
10.0
11.4
11.8
5.0
13.2
6.3
19.2
7.6
18.6
18.7
20.8
9.8
10.3
13.9
13.2
6.2
9.1
2.2
10.5
7.6
1.1
13.9
6.1
4.2
8.0
13.2
9.4
3.2
20.0
5.2
10.7
11.3
9.6
11.0
20.9
0.5
10.9
20.6
7.0
12.4
..
8.7
3.0
7.1
4.4
13.1
3.5
6.6
10.1
4.8
7.1
0.9
..
4.9
6.1
9.6
11.5
11.8
5.0
13.1
5.8
19.3
3.9
18.5
18.2
20.8
7.0
10.7
13.9
13.0
6.3
9.1
2.1
10.5
7.6
1.0
14.0
6.1
4.2
8.0
13.2
9.8
3.2
11.9
5.2
10.6
9.9
9.6
11.0
20.9
0.4
10.9
20.6
7.0
12.2
..
8.8
3.0
7.1
4.4
13.0
3.2
6.6
8.5
4.7
7.1
0.8
..
4.9
6.1
(continued)
private sector developMent
Part III. Development outcomes
59
Table
Drivers of growth
4.1
Doing Business indicators (continued)
Enforcing contracts
Number of
procedures
2009
2010
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
39
46
42
29
37
44
43
37
43
41
43
43
44
33
40
40
39
37
38
32
36
50
41
40
41
41
38
42
36
46
36
30
33
39
40
24
43
44
37
40
..
30
53
40
38
41
38
35
38
42
46
41
..
40
39
39
46
42
29
37
44
43
37
43
41
43
43
44
33
40
40
39
37
38
32
36
50
40
40
41
41
38
42
36
46
36
30
33
39
40
24
43
44
37
40
..
30
53
40
38
41
38
35
38
42
46
41
..
40
39
Time required
(days)
2009
2010
658
1,011
825
687
446
832
800
425
660
743
506
625
560
770
1,225
553
405
620
1,070
434
487
276
1,140
465
785
1,280
871
432
626
370
720
730
270
545
457
260
1,185
780
720
515
..
600
810
972
462
588
510
471
410
705
630
1,010
..
615
565
652
1,011
825
625
446
832
800
425
660
743
506
625
560
770
1,225
553
405
620
1,070
434
487
276
1,140
465
785
1,280
871
312
620
370
645
730
270
545
457
230
1,185
780
720
515
..
600
810
972
462
588
490
471
410
705
630
1,010
..
615
565
Cost
(% of debt)
2009
2010
49.0
44.4
64.7
28.1
83.0
38.6
46.6
21.8
82.0
45.7
89.4
151.8
53.2
41.7
34.0
18.5
22.6
15.2
34.3
37.9
23.0
45.0
25.0
47.2
19.5
35.0
42.4
142.4
52.0
23.2
17.4
142.5
35.8
59.6
32.0
78.7
50.5
26.5
14.3
149.5
..
33.2
19.8
56.1
14.3
47.5
44.9
38.7
32.0
23.8
21.9
26.2
..
25.2
21.8
49.7
44.4
64.7
28.1
81.7
38.6
46.6
21.8
82.0
45.7
89.4
151.8
53.2
41.7
34.0
18.5
22.6
15.2
34.3
37.9
23.0
45.0
25.0
47.2
19.5
35.0
42.4
94.1
52.0
23.2
17.4
142.5
35.8
59.6
32.0
78.7
50.5
26.5
15.4
149.5
..
33.2
19.8
56.1
14.3
47.5
44.9
38.7
113.1
23.8
21.9
26.2
..
25.2
21.8
Protecting investors
(0 least protection to
10 most protection)
Dealing with construction permits
Cost
Number of
Time required
(% of GNI
procedures
(days)
per capita)
2009
2010
2009
2010
2009
2010
18
12
15
24
15
25
14
18
21
14
18
14
17
22
16
18
..
12
16
17
18
32
15
11
15
24
16
21
14
25
18
17
12
17
18
14
13
16
20
25
..
17
19
14
22
15
18
17
17
22
22
25
..
19
20
18
12
15
24
15
25
14
18
21
14
18
14
17
21
16
18
..
12
16
17
18
32
15
11
15
24
16
21
15
25
18
17
12
17
18
14
13
16
20
25
..
17
19
14
22
15
18
17
17
22
22
25
..
19
20
245
328
410
167
132
212
227
120
239
164
164
248
169
629
179
201
..
128
210
146
220
255
167
120
601
77
178
213
185
201
107
381
139
265
350
210
255
220
144
283
..
174
271
116
328
277
171
254
1012
176
240
218
..
163
84
Disclosure
index
2009 2010
238 1,993.4 1,775.2
328
597.7
694.3
320
254.4
249.6
167
246.2
264.5
122
721.2
576.1
212 8,262.0 7,047.6
213
1,178.4 1,235.8
120
523.3
570.7
239
275.2
259.5
164 6,383.4 6,684.4
164
72.6
68.1
128 4,505.8 2,692.2
169
179.3
241.1
592
230.9
227.6
179
2,145.6 1,862.8
201
128.4
220.7
..
..
..
128
562.0
419.6
210
34.5
42.9
146
336.4
314.9
220 1,099.0 1,017.7
255
249.6
419.0
167 2,020.0 1,075.0
120
161.7
167.8
601 1,278.8 1,290.7
77 28,295.9 29,574.4
178
630.7
654.9
268
1,311.3 1,316.7
168
818.5
505.0
201
506.3
463.2
107
35.5
32.3
381
632.0
530.3
139
124.7
113.0
265 2,355.0 2,352.3
350
573.4
597.5
195
456.1
353.6
255
631.4
565.1
210
463.1
459.0
144
30.3
38.0
252
368.5
343.3
..
..
..
174
24.5
23.1
271
206.4
192.2
116
147.1
143.0
328 3,281.3 2,756.3
277 1,285.3 1,241.9
171
1,510.5 1,287.8
254 2,793.8 2,454.2
1012 13,770.3 8,020.6
180
408.3
362.0
240
39.6
44.0
218
331.6
293.7
..
..
..
163
263.7
251.5
97
998.3
858.7
5
5
6
7
6
4
6
1
6
6
6
3
6
6
5
6
4
4
6
2
7
6
6
3
2
4
5
4
6
5
6
5
5
6
5
7
3
6
4
6
..
8
0
0
3
6
2
3
8
6
6
8
..
6
5
5
5
6
7
6
4
6
1
6
6
6
3
6
6
5
6
4
4
6
2
7
6
6
3
2
4
5
4
6
5
6
5
5
6
5
7
3
6
4
6
..
8
0
2
3
6
2
3
8
7
6
8
..
7
5
Director liability
index
2009 2010
3
6
1
8
1
1
1
5
1
1
1
3
1
1
2
1
5
4
1
1
5
1
1
2
1
1
6
7
1
3
8
4
5
1
7
9
1
1
8
7
..
8
6
1
4
1
5
6
1
4
6
3
..
2
5
3
6
1
8
1
1
1
5
1
1
1
3
1
1
2
1
5
4
1
1
5
1
1
2
1
1
6
7
1
3
8
4
5
1
7
9
1
1
8
7
..
8
6
5
4
1
5
6
1
4
6
3
..
2
5
a. Average of the disclosure, director liability, and shareholder suits indexes.
b. Average of the rigidity of hours, difficulty of hiring, and difficulty of firing indexes.
60
Part III. Development outcomes
private sector developMent
Protecting investors
(0 least protection to
10 most protection)
Shareholder suits
index
2009
2010
5
6
3
3
4
5
6
6
5
3
5
4
3
3
0
4
5
5
3
5
6
1
5
10
8
6
6
5
4
3
9
9
6
3
5
3
6
2
5
6
..
8
4
5
8
4
5
7
4
4
4
5
..
1
6
5
6
3
3
4
5
6
6
5
3
5
4
3
3
0
4
5
5
3
5
6
1
5
10
8
6
6
5
4
3
9
9
6
3
5
3
6
2
5
6
..
8
4
6
8
4
5
7
4
4
4
5
..
1
6
Investor protection
indexa
2009
2010
4.3
5.7
3.3
6.0
3.7
3.3
4.3
4.0
4.0
3.3
4.0
3.3
3.3
3.3
2.3
3.7
4.7
4.3
3.3
2.7
6.0
2.7
4.0
5.0
3.7
3.7
5.7
5.3
3.7
3.7
7.7
6.0
5.3
3.3
5.7
6.3
3.3
3.0
5.7
6.3
..
8.0
3.3
2.0
5.0
3.7
4.0
5.3
4.3
4.7
5.3
5.3
..
3.0
5.3
private sector developMent
4.4
5.7
3.3
6.0
3.7
3.3
4.3
4.0
4.0
3.3
4.0
3.3
3.3
3.3
2.3
3.7
4.7
4.3
3.3
2.7
6.0
2.7
4.0
5.0
3.7
3.7
5.7
5.3
3.7
3.7
7.7
6.0
5.3
3.3
5.7
6.3
3.3
3.0
5.7
6.3
..
8.0
3.3
4.3
5.0
3.7
4.0
5.3
4.3
4.8
5.3
5.3
..
3.3
5.3
Rigidity of hours
index (0 least rigid
to 100 most rigid)
2009
2010
30
60
40
0
20
53
20
33
40
20
40
47
40
47
40
60
40
20
60
40
20
20
27
0
20
20
40
0
20
20
13
33
20
53
0
40
67
53
13
40
..
20
20
0
13
40
0
33
40
28
40
20
..
40
13
30
60
40
0
20
53
20
33
40
20
40
47
40
47
40
60
40
20
60
40
20
20
27
0
20
20
40
0
20
20
33
33
20
53
0
0
67
53
13
40
..
20
20
0
13
40
0
33
40
28
40
20
..
40
13
Difficulty of hiring
index (0 least difficult
to 100 most difficult)
2009
2010
38
67
39
0
33
0
28
33
61
39
39
50
78
33
67
67
0
33
17
0
11
33
67
22
22
22
89
44
33
56
0
67
0
100
0
44
50
72
44
33
..
56
39
11
100
61
0
22
0
43
44
0
..
100
28
38
67
39
0
33
0
28
33
61
39
39
72
78
33
67
67
0
33
17
0
11
33
67
22
22
22
89
44
33
56
0
67
0
100
0
11
50
72
44
33
..
56
39
11
100
83
0
11
0
40
44
0
..
89
28
Employing workers
Difficulty of firing
index (0 least difficult
to 100 most difficult)
2009
2010
40
70
40
40
10
30
70
70
50
40
40
70
70
20
30
70
20
30
80
40
50
20
70
30
0
40
40
20
40
40
40
20
20
50
20
30
60
50
50
50
..
30
50
20
50
40
0
20
60
58
40
60
..
50
80
40
70
40
40
10
30
70
70
50
40
40
70
70
20
30
70
20
30
80
40
50
20
70
30
0
40
40
20
40
40
20
20
20
50
20
10
60
50
50
50
..
30
50
20
50
40
0
20
60
58
40
60
..
50
80
Firing cost
(weeks of wages)
2009
2010
68
58
36
90
34
26
33
93
22
36
100
31
33
49
56
133
69
40
43
26
178
26
87
47
44
84
30
84
31
31
35
134
24
35
50
26
91
38
39
189
..
24
118
53
18
36
13
178
446
63
17
132
..
85
17
67
58
36
90
34
26
33
93
22
36
100
31
33
49
56
133
69
40
43
26
178
26
87
47
44
84
30
84
31
31
4
134
24
35
50
26
91
38
39
189
..
24
118
53
18
36
13
178
446
63
17
132
..
85
17
Rigidity of employment
indexb (0 least rigid
to 100 most rigid)
2009
2010
36
66
40
13
21
28
39
46
50
33
40
63
63
33
46
66
20
28
52
27
27
24
54
17
14
27
56
21
31
39
18
40
13
68
7
7
59
59
36
41
..
35
36
10
54
54
0
21
33
42
41
27
..
60
40
36
66
40
13
21
28
39
46
50
33
40
63
63
33
46
66
20
28
52
27
27
24
54
17
14
27
56
21
31
39
18
40
13
68
7
7
59
59
36
41
..
35
36
10
54
54
0
21
33
42
41
27
..
60
40
Part III. Development outcomes
61
Table
Drivers of growth
4.2
Investment climate
Enterprise Surveys
Viewed by firms as a major constraint (% of firms)
Private
Firms that
Domestic
sector fixed Net foreign credit to believe the court
Crime,
Customs
capital
direct
system is fair,
private
theft, and
Tax
Labor
Labor
Transpor- and trade
formation investment
impartial, and
sector
rates
Finance Electricity regulations
skills
tation
regulations
(% of GDP) ($ millions) (% of GDP) uncorrupt (%) Corruption discord
2009a
2009a
2009a
2009–10 b
2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b 2009–10 b
SUB–SAHARAN AFRICA
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
13.4
2.4
15.4
8.9
..
..
12.4
42.7
6.9
21.8
7.7
6.1
13.5
8.3
..
16.1
..
5.9
23.2
..
11.6
17.0
..
14.5
17.3
..
29.4
14.9
..
..
19.5
7.9
15.6
..
..
10.6
..
17.8
20.9
7.4
..
13.4
16.3
3.0
20.5
..
17.5
17.8
1.7
19.9
33.0
10.9
..
24.8
23.2
..
2,198.5
..
251.3
..
0.3
–50.0
120.0
..
..
..
..
..
380.9
96.9
..
..
221.5
..
39.4
1,677.8
140.9
..
94.5
62.9
217.8
..
..
..
..
218.9
878.4
528.1
..
5,647.2
118.7
7.2
..
242.9
74.3
..
4,042.4
2,682.2
58.7
414.5
..
603.7
699.2
..
9,702.9
..
6,140.4
546.0
1,491.3
1,525.2
64.4
21.2
22.2
25.5
17.5
21.7
11.3
64.0
7.0
5.2
16.0
7.5
4.8
17.1
29.3
7.7
16.6
..
10.1
18.9
..
..
5.6
31.5
13.5
16.1
11.5
14.2
17.4
..
85.1
25.1
46.8
12.2
37.6
..
34.6
24.7
25.1
9.3
..
147.1
12.3
25.0
15.3
21.9
13.1
12.0
..
35.2
16.2
36.2
10.9
64.4
68.4
23.7
9.6
79.5
38.7
..
32.6
59.5
..
31.0
..
17.2
32.3
35.3
..
..
100.0
..
41.3
..
..
..
..
..
33.2
44.3
28.8
74.3
42.7
..
63.6
..
..
49.6
..
..
..
..
..
29.7
..
..
..
..
..
14.1
..
..
..
75.6
67.8
27.4
70.5
..
61.3
29.8
..
67.2
..
72.7
65.0
75.0
..
..
0.0
..
41.4
..
..
..
..
..
46.7
31.2
42.7
12.8
24.8
..
50.7
..
..
83.7
..
..
..
..
..
36.9
..
..
..
..
..
70.2
..
..
..
28.1
52.7
22.6
42.2
..
41.5
62.3
..
45.8
..
63.3
44.1
53.8
..
..
0.0
..
34.1
..
..
..
..
..
33.5
26.8
48.1
22.8
17.3
..
41.5
..
..
44.2
..
..
..
..
..
14.2
..
..
..
..
..
22.6
..
..
..
26.4
67.6
16.9
75.7
..
45.9
51.8
..
59.7
..
39.5
40.9
30.5
..
..
1.1
..
30.9
..
..
..
..
..
47.1
19.0
40.8
15.6
26.3
..
25.1
..
..
60.4
..
..
..
..
..
42.5
..
..
..
..
..
43.5
..
..
..
38.5
70.3
25.5
75.0
..
55.1
36.7
..
46.5
..
73.3
44.8
66.6
..
..
0.9
..
30.4
..
..
..
..
..
28.6
35.0
39.4
51.0
48.2
..
46.3
..
..
62.0
..
..
..
..
..
34.6
..
..
..
..
..
58.6
..
..
..
35.7
51.9
34.8
53.9
..
58.6
53.1
..
74.6
..
51.7
71.1
39.8
..
..
0.2
..
58.0
..
..
..
..
..
44.3
59.1
54.6
37.6
33.5
..
42.9
..
..
63.2
..
..
..
..
..
53.4
..
..
..
..
..
50.9
..
..
..
26.1
16.1
14.0
26.0
..
21.5
5.7
..
28.4
..
20.0
24.5
6.1
..
..
0.2
..
16.4
..
..
..
..
..
11.3
2.6
2.2
2.7
6.4
..
8.8
..
..
5.3
..
..
..
..
..
11.4
..
..
..
..
..
3.1
..
..
..
25.9
28.2
32.2
37.5
..
37.8
49.2
..
53.1
..
65.0
51.5
26.7
..
..
1.2
..
42.7
..
..
..
..
..
16.5
5.1
17.0
21.8
12.2
..
45.7
..
..
37.1
..
..
..
..
..
16.0
..
..
..
..
..
17.2
..
..
..
25.3
46.7
20.1
40.3
..
27.7
24.0
..
45.5
..
38.8
48.4
38.2
..
..
2.2
..
48.8
..
..
..
..
..
19.8
39.3
26.6
24.6
21.4
..
45.8
..
..
50.0
..
..
..
..
..
29.9
..
..
..
..
..
32.1
..
..
..
35.8
51.8
15.8
42.6
..
26.3
27.2
..
57.4
..
54.0
45.9
19.4
..
..
2.0
..
35.1
..
..
..
..
..
21.7
15.6
18.7
11.0
16.9
..
17.7
..
..
31.6
..
..
..
..
..
26.9
..
..
..
..
..
27.5
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
a. Provisional.
b. Data are for the most recent year available during the period specified.
62
Part III. Development outcomes
private sector developMent
Number of tax
payments
2010
37
31
55
19
46
32
44
43
54
54
20
32
61
64
35
46
18
19
26
50
33
56
46
41
21
32
23
19
59
38
7
37
37
41
35
26
42
59
16
29
..
9
42
33
48
53
32
37
49
25
34
29
..
28
8
Time to prepare,
file, and pay taxes
(hours)
2010
Enterprise Surveys
Regulation and tax administration
Time dealing
Average time to clear customs
Highest marginal with officials
(days)
Total tax rate tax rate, corporate
(% of
(% of profit)
(%)
management time) Direct exports
Imports
2010
2009–10 b
2009–10 b
2009–10 b
2009–10 b
310
282
270
152
270
211
654
186
504
732
100
336
606
270
90
492
216
198
488
376
224
416
208
393
324
158
201
157
270
696
161
230
375
270
938
148
424
666
76
357
..
200
180
104
172
270
161
132
242
347
451
433
..
358
144
private sector developMent
67
53.2
66.0
19.5
44.9
153.4
49.1
37.1
203.8
65.4
217.9
339.7
65.5
44.4
38.7
59.5
84.5
31.1
43.5
292.3
32.7
54.6
45.9
49.7
19.6
43.7
37.7
25.1
52.2
68.4
24.1
34.3
9.6
46.5
32.2
31.3
33.3
46.0
44.1
235.6
..
30.5
36.1
36.8
45.2
50.8
35.7
16.1
40.3
54.8
72.0
42.6
..
41.7
62.8
35.0
..
25.0
..
..
..
..
..
..
..
38.0
..
25.0
..
..
..
..
..
..
25.0
..
..
..
..
..
..
..
..
..
15.0
32.0
35.0
..
30.0
..
..
..
..
..
..
34.6
35.0
30.0
30.0
..
45.0
35.0
30.9
12.2
20.7
10.2
22.2
..
7.0
3.9
..
20.8
..
29.4
6.0
1.6
..
..
0.5
..
2.8
..
..
..
..
..
5.6
7.5
17.1
3.5
2.0
..
9.4
..
..
22.9
..
..
..
..
..
7.4
..
..
..
..
..
2.7
..
..
..
6.7
9.6
6.2
7.4
..
15.1
..
..
11.9
..
18.0
..
16.6
..
..
9.6
..
3.8
..
..
..
..
..
5.4
..
14.2
9.9
12.9
..
10.3
..
..
2.6
..
..
..
..
..
..
..
..
..
..
..
6.7
..
..
..
11.4
33.0
3.7
16.4
..
24.0
20.5
..
27.5
..
45.4
31.4
31.2
..
..
20.1
..
10.3
..
..
..
..
..
4.4
6.7
19.3
11.2
16.5
..
9.8
..
..
9.3
..
..
..
..
..
12.2
..
..
..
..
..
9.0
..
..
..
..
20.0
40.0
..
30.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
Interest rate
spread
(lending rate
minus deposit
rate)
2009
Listed
domestic
companies
2009
..
8.1
..
6.3
..
..
..
8.1
..
..
8.6
49.5
..
..
..
..
..
..
..
11.5
..
..
..
8.8
8.2
10.1
33.5
21.8
..
..
10.8
6.2
4.9
..
5.1
..
19.7
..
5.6
..
..
3.2
..
6.0
7.1
..
11.2
15.0
..
5.5
6.3
5.5
3.5
..
..
..
..
..
20
..
..
..
..
..
..
..
..
..
38
..
..
..
..
..
..
35
..
..
55
..
..
..
15
..
..
88
..
7
..
214
..
..
..
..
..
..
363
..
5
15
..
8
19
94
..
..
305
..
78
49
Market
capitalization of Turnover ratio for
listed companies traded stocks
(% of GDP)
(%)
2009a
2009a
..
..
..
33.8
..
..
..
..
..
..
..
..
..
26.4
..
..
..
..
..
..
9.6
..
..
36.6
..
..
..
29.3
..
..
55.2
..
9.1
..
19.3
..
..
..
..
..
..
247.0
..
..
..
..
..
..
..
..
..
47.7
..
68.8
23.1
..
..
..
2.7
..
..
..
..
..
..
..
..
..
2.0
..
..
..
..
..
..
2.0
..
..
4.6
..
..
..
..
..
..
8.1
..
3.0
..
11.0
..
..
..
..
..
..
57.3
..
..
..
..
..
..
..
..
..
60.1
..
45.7
16.2
Part III. Development outcomes
63
Table
Drivers of growth
4.3
Financial sector infrastructure
Macroeconomy
Foreign currency sovereign ratings
Long-term
Short-term
2010–11b
2010–11b
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
B+
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
B+
..
..
..
BB..
..
..
..
..
..
..
BBB..
BBB
..
..
B
..
..
BBB+
..
..
..
..
..
B+
..
B
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
B
..
..
..
B
..
..
..
..
..
..
..
F3
..
B
B
..
..
B
..
..
F2
..
..
..
..
..
B
..
..
BB
B
BBBBBB-
..
B
B
F3
F3
Gross national savings
(% of GDP)
2008
2009 c
15.5
23.6
10.6
34.8
..
..
..
26.7
..
..
..
..
..
12.3
..
..
..
17.1
..
10.4
8.8
1.4
..
14.2
33.5
–2.1
..
..
..
..
16.7
3.8
31.6
..
..
17.3
..
16.1
1.6
5.3
..
14.9
17.4
6.9
13.3
..
21.9
19.2
..
32.5
..
23.6
67.1
32.9
21.3
15.4
9.7
..
16.4
..
..
..
31.3
..
..
..
..
..
14.8
..
..
..
16.1
..
18.8
15.5
7.7
..
15.4
28.1
..
..
..
..
..
16.7
9.1
26.5
..
..
15.1
..
..
9.2
7.8
..
15.4
12.2
2.4
21.2
..
17.5
19.0
..
..
..
16.7
..
31.2
22.8
Money and quasi money (M2)
(% of GDP)
2008
2009c
41.0
18.0
32.9
39.0
22.5
34.2
19.3
85.2
14.4
11.8
27.1
12.6
16.0
27.8
74.5
6.2
109.8
30.9
16.8
49.5
23.6
0.0
20.8
40.3
34.0
27.8
20.5
19.7
25.8
0.0
97.0
30.8
36.5
15.7
30.1
0.0
35.5
33.5
60.4
20.6
0.0
78.4
17.5
24.2
27.6
37.8
20.8
21.5
0.0
67.0
54.8
84.2
28.3
102.5
60.0
47.7
31.1
36.4
46.8
24.8
36.7
21.5
84.2
15.5
14.7
28.6
14.3
22.2
29.6
83.0
12.3
112.3
0.0
22.1
55.0
0.0
0.0
23.3
42.7
38.6
35.4
22.0
23.5
25.2
0.0
104.0
35.7
38.5
17.1
37.1
0.0
35.5
35.1
59.3
23.3
0.0
80.2
20.3
27.6
28.8
42.6
20.6
20.6
0.0
75.7
64.1
79.8
53.7
104.7
64.2
Real interest rate
(%)
2008
2009 c
..
–8.2
..
–0.4
..
–6.9
..
8.9
..
..
4.7
19.9
..
..
1.9
..
..
–17.2
..
19.6
..
..
..
1.9
2.4
3.6
32.8
15.0
..
..
13.6
9.4
–0.5
..
4.1
3.3
7.6
..
–13.0
12.0
..
5.4
..
4.3
4.4
..
13.1
6.8
..
..
–5.8
0.1
–15.5
..
..
..
22.8
..
20.6
..
0.4
..
6.9
..
..
5.7
27.0
..
..
..
..
..
..
..
24.1
..
..
..
7.6
9.2
6.3
33.8
15.6
..
..
17.5
12.0
4.4
..
19.1
..
14.6
..
–10.3
..
..
4.1
..
5.6
7.1
..
3.8
8.3
..
..
19.2
1.0
57.8
..
..
a. Data are consolidated for regional security markets where they exist.
b. Data are for the most recent year available during the period specified.
c. Provisional.
64
Part III. Development outcomes
private sector developMent
Capital marketsa
Intermediation
Domestic credit to
private sector
(% of GDP)
2008
2009 c
Interest rate spread
(lending rate minus
deposit rate)
2008
2009 c
56.0
12.6
20.9
21.0
18.4
20.9
10.2
61.1
7.0
3.7
11.5
7.1
3.2
16.3
24.7
4.4
18.4
17.8
8.5
17.3
15.9
..
4.9
30.3
11.1
12.5
11.2
11.9
17.2
..
87.8
18.3
44.9
10.9
33.9
..
29.9
24.3
32.3
7.1
..
145.1
10.5
23.6
16.1
18.7
13.9
15.2
..
32.6
13.2
42.8
6.8
63.2
65.8
8.6
6.0
..
7.9
..
..
..
6.2
..
..
8.0
35.4
..
..
9.4
..
..
3.3
..
14.1
..
..
..
8.7
8.5
10.4
33.5
21.8
..
..
11.4
7.3
5.4
..
3.5
9.8
19.7
..
7.8
14.8
..
3.5
..
6.7
6.7
..
9.8
12.5
..
5.7
6.3
5.7
3.5
..
..
64.4
21.2
22.2
25.5
17.5
21.7
11.3
64.0
7.0
5.2
16.0
7.5
4.8
17.1
29.3
7.7
16.6
..
10.1
18.9
..
..
5.6
31.5
13.5
16.1
11.5
14.2
17.4
..
85.1
25.1
46.8
12.2
37.6
..
34.6
24.7
25.1
9.3
..
147.1
12.3
25.0
15.3
21.9
13.1
12.0
..
35.2
16.2
36.2
10.9
64.4
68.4
private sector developMent
..
8.1
..
6.3
..
..
..
8.1
..
..
8.6
49.5
..
..
..
..
..
..
..
11.5
..
..
..
8.8
8.2
10.1
33.5
21.8
..
..
10.8
6.2
4.9
..
5.1
..
19.7
..
5.6
..
..
3.2
..
6.0
7.1
..
11.2
15.0
..
5.5
6.3
5.5
3.5
..
..
Ratio of bank
nonperforming loans to
total gross loans (%)
2008
2009 c
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
8.5
..
7.7
..
..
9.0
4.0
..
..
..
..
..
..
1.9
3.1
..
6.3
12.6
..
19.1
..
17.9
..
3.9
..
7.6
..
..
2.2
..
..
14.8
..
14.8
..
6.0
15.5
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
9.8
..
16.2
..
..
7.9
4.0
..
..
..
..
..
..
1.8
2.7
..
6.6
13.1
..
18.7
..
16.5
..
5.9
..
8.1
..
..
4.2
..
..
13.2
..
13.4
..
5.5
13.2
Listed domestic companies
2008
2009 c
..
..
..
19
..
..
..
..
..
..
..
..
..
38
..
..
..
..
..
..
35
..
..
53
..
..
..
15
..
..
41
..
7
..
213
..
..
..
..
..
..
425
..
7
14
..
6
19
81
..
..
373
..
77
49
..
..
..
20
..
..
..
..
..
..
..
..
..
38
..
..
..
..
..
..
35
..
..
55
..
..
..
15
..
..
88
..
7
..
214
..
..
..
..
..
..
363
..
5
15
..
8
19
94
..
..
305
..
78
49
Market capitalization
of listed companies
(% of GDP)
2008
2009 c
Turnover ratio for
traded stocks
(%)
2008
2009 c
..
..
..
26.3
..
..
..
..
..
..
..
..
..
30.2
..
..
..
..
..
..
11.9
..
..
36.4
..
..
..
43.5
..
..
37.0
..
6.9
..
24.0
..
..
..
..
..
..
177.7
..
..
6.2
..
..
..
..
..
..
52.7
..
74.0
15.6
..
..
..
3.1
..
..
..
..
..
..
..
..
..
4.1
..
..
..
..
..
..
5.2
..
..
11.8
..
..
..
..
..
..
8.9
..
2.8
..
29.3
..
..
..
..
..
..
60.6
..
..
..
..
..
..
..
..
..
61.9
..
31.1
25.5
..
..
..
33.8
..
..
..
..
..
..
..
..
..
26.4
..
..
..
..
..
..
9.6
..
..
36.6
..
..
..
29.3
..
..
55.2
..
9.1
..
19.3
..
..
..
..
..
..
247.0
..
..
..
..
..
..
..
..
..
47.7
..
68.8
23.1
..
..
..
2.7
..
..
..
..
..
..
..
..
..
2.0
..
..
..
..
..
..
2.0
..
..
4.6
..
..
..
..
..
..
8.1
..
3.0
..
11.0
..
..
..
..
..
..
57.3
..
..
..
..
..
..
..
..
..
60.1
..
45.7
16.2
Part III. Development outcomes
65
Table
Drivers of growth
5.1
International trade and tariff barriers
Trade
Annual average
Annual growth
(% of GDP)
(%)
Exports of Imports of Exports of Imports of
Merchangoods and goods and goods and goods and Exports of Imports of Exports of Imports of Terms of
Total
dise
Services
services
services
services
services goods and goods and goods and goods and trade index
(% of GDP) (% of GDP) (% of GDP) ($ millions) ($ millions) (% of GDP) (% of GDP) services
services
services
services (2000 = 100)
a
a
a
a
a
a
2009
2009
2009
2009
2009
2009
2009a
2000–09 2000–09
2009a
2009a
2009a
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
66
63.3
98.5
42.0
78.2
..
..
57.5
89.0
36.9
112.2
62.8
31.3
122.8
75.5
..
115.6
24.7
39.4
85.5
80.6
71.8
86.2
..
63.5
163.0
..
80.7
67.8
..
117.3
107.5
68.9
106.5
..
63.0
40.9
..
68.0
246.9
44.2
..
55.4
35.9
136.3
58.4
..
58.0
67.8
101.7
68.7
76.5
56.9
..
68.1
107.3
Part III. Development outcomes
53.6
75.6
45.7
69.2
36.0
35.2
32.7
48.1
20.9
69.5
30.4
63.4
88.7
64.2
46.2
137.3
29.6
33.5
66.0
43.5
52.1
58.7
41.2
49.8
171.0
80.1
51.1
55.4
52.7
92.6
66.0
60.4
93.6
44.6
52.9
27.2
64.4
53.8
162.6
38.7
..
47.6
32.1
103.3
44.2
80.6
42.3
63.3
91.9
53.3
60.1
36.1
73.4
51.2
84.8
13.4
26.2
..
15.9
..
17.1
15.2
52.3
..
..
..
..
..
14.8
42.9
..
..
14.4
..
25.5
18.0
9.8
..
16.1
12.5
162.0
..
..
..
..
44.8
17.1
12.2
..
11.4
16.5
15.4
..
93.2
8.7
..
9.4
5.6
25.4
16.7
..
14.9
7.4
..
18.0
..
18.8
8.7
21.1
21.4
298,039
39,432
922
3,971
..
..
5,896
366
290
2,879
79
1,017
6,884
9,722
..
7,713
84
3,011
5,773
223
7,982
1,671
..
7,413
809
..
2,447
1,420
..
1,504
4,161
2,454
4,319
..
62,054
610
..
3,082
912
305
..
77,883
8,230
1,794
4,963
..
3,753
4,560
2,040
200,244
56,798
47,185
..
26,121
20,568
317,933
34,901
1,875
5,273
..
..
6,856
1,013
449
4,794
258
2,298
4,876
7,866
..
4,328
379
8,229
3,685
368
10,820
1,865
..
11,253
1,764
..
4,484
1,783
..
2,043
5,074
4,287
5,548
..
46,999
1,524
..
5,637
975
554
..
80,328
11,391
2,295
7,511
..
5,557
4,118
3,678
193,682
50,772
60,048
..
36,088
21,894
29.8
52.2
13.8
33.6
..
..
26.6
23.6
14.5
42.1
14.7
9.6
71.9
41.7
..
74.1
4.5
10.6
52.2
30.4
30.5
40.7
..
25.2
51.2
..
28.5
30.0
..
49.7
48.4
25.1
46.6
..
35.9
11.7
..
24.0
119.3
15.7
..
27.3
15.1
59.8
23.2
..
23.4
35.6
36.3
32.1
40.4
25.0
..
28.6
52.0
33.5
46.2
28.2
44.6
..
..
30.9
65.4
22.4
70.1
48.2
21.7
50.9
33.8
..
41.6
20.3
28.8
33.3
50.1
41.3
45.4
..
38.3
111.7
..
52.2
37.7
..
67.6
59.1
43.8
59.9
..
27.2
29.2
..
44.0
127.6
28.5
..
28.1
20.8
76.5
35.2
..
34.6
32.2
65.4
36.6
36.1
31.9
..
39.5
55.3
32.4
73.6
14.1
45.5
9.7
8.7
22.9
24.1
14.5
39.4
15.2
24.4
79.1
46.6
40.7
89.5
8.1
12.9
60.7
38.8
35.8
30.3
30.1
25.4
52.9
28.9
27.5
25.9
28.5
41.7
58.4
29.0
44.2
16.2
42.3
10.4
..
26.7
94.0
19.9
..
29.7
16.6
83.5
20.0
36.0
15.1
33.8
36.5
35.6
42.0
25.1
56.9
31.4
49.4
33.9
54.4
27.3
37.0
24.0
31.0
23.3
60.6
21.4
56.5
37.0
32.6
54.9
37.5
53.6
54.2
53.0
29.7
32.1
53.6
53.3
33.3
55.3
34.7
110.4
75.6
42.5
41.1
39.6
69.2
63.0
44.0
48.9
25.0
31.0
26.3
..
42.2
105.2
33.8
..
29.3
22.0
91.2
28.7
53.7
26.9
38.0
46.4
31.4
24.6
29.1
27.8
37.6
52.6
..
..
..
–28.0
..
..
–4.8
11.9
..
..
..
5.4
..
9.3
..
..
..
6.9
–4.9
2.5
..
3.0
..
–7.0
–17.2
..
9.3
..
..
..
–4.8
2.4
–14.0
..
..
..
..
–8.8
10.8
..
..
–19.5
..
–6.1
15.5
..
16.2
..
5.2
–10.3
–3.0
–14.5
..
–13.1
–1.6
..
..
..
–9.3
..
..
–5.2
13.0
..
..
..
–11.9
..
11.0
..
..
..
16.4
–2.8
3.8
–14.1
16.8
..
–0.2
–1.1
..
–10.5
..
..
..
–4.6
14.0
5.3
..
..
..
..
–17.1
1.7
..
..
–17.4
..
–3.5
14.1
..
25.2
..
36.0
–7.5
16.7
–17.9
..
–6.0
6.7
..
..
..
82.7
..
..
106.9
58.7
..
..
..
85.9
..
96.1
..
..
..
115.3
124.4
71.3
..
98.8
..
114.5
157.3
..
88.3
..
..
..
81.0
49.3
138.2
..
..
..
..
91.9
100.0
..
..
126.3
..
100.0
119.3
..
67.2
..
102.7
..
103.3
89.6
..
99.5
106.0
trade and reGional inteGration
Food
2009
13.7
..
..
5.2
26.8
67.5
..
72.6
..
..
..
..
..
48.2
0.4
..
..
77.5
..
53.0
..
..
..
44.0
..
..
28.8
86.6
..
..
32.4
23.3
..
..
4.5
42.3
92.4
29.5
..
..
..
10.2
5.6
..
35.5
..
..
7.5
19.4
6.3
0.3
..
..
22.1
9.2
Structure of merchandise exports
(% of total)
Agricultural
raw materials
Fuel
Ores and metals Manufactures
2009
2009
2009
2009
3.0
..
..
0.2
60.5
4.8
..
0.0
..
..
..
..
..
5.7
0.0
..
..
11.9
..
1.0
..
..
..
13.2
..
..
5.2
3.8
..
..
0.9
3.1
..
..
1.1
1.7
0.7
1.1
..
..
..
1.9
1.4
..
9.8
..
..
1.4
23.1
0.4
0.0
..
..
1.6
0.5
36.9
..
..
0.3
0.0
1.9
..
..
..
..
..
..
..
30.0
6.5
..
..
0.0
..
0.0
..
..
..
4.2
..
..
4.9
0.1
..
..
0.0
17.5
..
..
90.4
0.1
0.0
24.0
..
..
..
11.1
92.1
..
1.0
..
..
0.9
0.9
63.6
97.7
..
..
2.0
13.6
15.3
..
..
16.1
0.6
4.8
..
0.7
..
..
..
..
..
0.4
0.3
..
..
0.8
..
6.9
..
..
..
2.0
..
..
3.0
0.8
..
..
0.7
3.9
..
..
0.2
31.9
0.0
3.4
..
..
..
29.3
0.3
..
24.6
..
..
81.1
22.3
2.4
0.5
..
..
8.8
1.3
30.8
..
..
78.0
12.1
20.6
..
26.7
..
..
..
..
..
15.2
90.7
..
..
8.7
..
39.1
..
..
..
36.6
..
..
57.2
8.6
..
..
64.6
11.7
..
..
3.6
19.4
3.0
41.3
..
..
..
47.5
0.4
..
24.6
..
..
8.4
34.3
27.2
1.6
..
..
65.5
75.4
Food
2009
11.2
..
..
13.1
15.7
12.5
..
29.4
..
..
..
..
..
23.2
29.3
..
..
10.9
..
34.3
..
..
..
15.4
..
..
10.7
13.1
..
..
21.7
15.4
..
..
11.8
12.4
35.9
24.2
..
..
..
6.5
14.9
..
8.9
..
..
6.5
22.4
..
16.3
..
..
11.2
8.6
Structure of merchandise imports
(% of total)
Agricultural
raw materials
Fuel
Ores and metals Manufactures
2009
2009
2009
2009
1.0
..
..
0.9
0.7
1.4
..
1.3
..
..
..
..
..
0.8
0.6
..
..
0.5
..
1.3
..
..
..
1.4
..
..
0.6
1.0
..
..
2.4
1.2
..
..
1.0
1.5
0.9
1.5
..
..
..
0.9
1.1
..
0.9
..
..
0.7
0.4
..
1.5
..
..
2.1
2.0
16.8
..
..
13.3
23.6
2.4
..
11.6
..
..
..
..
..
25.0
6.5
..
..
15.9
..
15.6
..
..
..
21.5
..
..
10.4
10.4
..
..
15.6
15.4
..
..
1.0
7.8
15.4
23.2
..
..
..
21.5
4.0
..
22.6
..
..
13.9
12.9
..
1.1
..
..
20.5
11.5
1.7
..
..
2.1
0.7
0.6
..
1.2
..
..
..
..
..
1.2
0.8
..
..
1.2
..
0.6
..
..
..
1.6
..
..
0.4
1.0
..
..
1.1
0.5
..
..
1.8
1.8
1.1
0.9
..
..
..
1.3
0.9
..
1.0
..
..
13.3
5.2
..
1.4
..
..
2.5
3.1
66.2
..
..
69.5
59.0
80.9
..
56.5
..
..
..
..
..
48.6
62.4
..
..
71.5
..
48.1
..
..
..
60.0
..
..
77.7
74.2
..
..
59.2
55.0
..
..
83.6
76.1
46.6
50.1
..
..
..
64.3
77.8
..
66.5
..
..
65.1
57.6
..
79.8
..
..
63.0
74.8
(continued)
trade and reGional inteGration
Part III. Development outcomes
67
Table
Drivers of growth
5.1
International trade and tariff barriers (continued)
Export indexes
(0 low to 1 high)
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Diversification
2009
Concentration
2009
0.61
0.82
0.75
0.86
0.72
0.80
0.79
0.70
0.34
0.70
0.75
0.82
0.78
0.71
0.65
0.74
0.63
0.80
0.85
0.63
0.81
0.79
0.80
0.70
0.86
0.77
0.73
0.81
0.87
0.82
0.70
0.73
0.87
0.79
0.85
0.82
0.56
0.69
0.84
0.62
0.78
0.58
0.74
0.71
0.77
0.71
0.73
0.86
0.75
..
0.80
0.59
0.82
0.69
0.55
0.42
0.95
0.35
0.45
0.34
0.59
0.48
0.44
0.12
0.40
0.51
0.35
0.70
0.36
0.33
0.73
0.22
0.34
0.72
0.26
0.44
0.49
0.93
0.22
0.50
0.60
0.22
0.62
0.75
0.50
0.25
0.32
0.31
0.51
0.83
0.40
0.70
0.23
0.52
0.27
0.47
0.14
0.76
0.24
0.29
0.25
0.23
0.65
0.19
..
0.56
0.17
0.76
0.15
0.16
Tariff barriers, all products (%)
Share of
lines with Share of
Share of
Simple
Dispersion
interlines with Share of lines with
Binding
mean
Simple
around Weighted national domestic lines that specific
Sectoral Global
coverage bound rate mean tariff the mean mean tariff peaks
effect
effect
peaks are bound
rates
2005–09 2005–09
2010
2010
2010
2010
2010
2010
2010
2009
2010
Competitiveness
indicator (%)
–0.2
–1.3
–15.8
–8.2
6.5
–0.1
–0.7
–3.2
0.9
–0.2
–2.8
0.0
7.1
1.4
–0.9
–2.5
7.4
–0.1
0.4
8.2
1.6
–2.6
1.9
–3.0
11.4
–0.8
9.2
–8.9
12.4
0.9
–3.4
–2.4
7.6
0.8
1.7
11.5
2.0
6.1
–5.9
–0.2
2.7
0.2
1.8
6.1
1.6
4.4
5.7
2.7
16.0
–13.9
–6.4
5.7
–11.5
–2.7
11.5
–2.1
–3.0
–3.0
20.3
0.6
–3.1
12.3
5.6
2.0
4.3
–4.3
19.1
–0.8
–6.4
–3.4
1.1
–4.3
–16.5
0.3
–0.4
–5.2
4.5
–2.9
4.0
4.0
6.6
–0.4
21.0
0.2
–9.8
–14.2
9.7
5.0
–0.5
3.6
–5.9
–3.6
–4.5
6.5
–2.4
–16.9
1.9
1.2
–0.3
2.4
–0.4
–1.5
8.6
2.8
–2.2
5.7
..
..
39.5
96.1
39.4
22.3
..
100.0
..
..
..
..
..
33.8
..
..
..
..
..
..
..
..
97.6
15.2
100.0
..
..
..
40.5
..
..
..
96.1
96.6
19.5
100.0
..
100.0
..
..
..
96.1
..
96.1
13.8
14.3
16.1
..
..
..
..
..
..
..
..
..
..
28.7
19.0
42.5
67.8
..
15.8
..
..
..
..
..
11.2
..
..
..
..
..
..
..
..
48.6
95.3
78.9
..
..
..
28.9
..
..
..
19.4
44.9
119.4
89.3
..
30.0
..
..
..
19.4
..
19.4
120.0
80.0
73.5
..
..
..
..
..
..
..
..
..
..
13.3
8.8
12.4
9.8
..
14.7
..
..
..
..
..
13.1
..
..
..
..
..
..
..
..
13.3
12.1
9.5
..
..
..
12.8
..
..
..
6.3
13.0
10.9
9.9
..
13.4
..
..
..
7.6
..
10.9
12.9
12.8
12.1
..
..
..
..
..
..
..
..
0.9
0.9
0.6
1.5
..
..
0.6
1.3
..
0.6
..
0.5
..
0.6
0.4
..
..
0.7
0.6
0.2
0.5
0.6
0.6
1.0
1.5
..
..
..
0.6
..
3.8
0.8
1.5
0.6
0.7
..
..
0.6
..
..
..
1.6
0.9
1.5
0.9
0.6
1.0
0.8
..
..
0.7
4.7
..
1.4
..
..
..
15.4
5.2
8.8
5.5
..
11.6
..
..
..
..
..
7.3
..
..
..
..
..
..
..
..
9.9
9.2
10.5
..
..
..
8.4
..
..
..
1.8
9.1
10.6
6.0
..
8.9
..
..
..
4.4
..
10.2
8.2
14.2
8.2
..
..
..
..
..
..
..
..
..
..
50.2
20.2
44.5
29.8
..
44.3
..
..
..
..
..
47.9
..
..
..
..
..
..
..
..
51.8
36.6
21.6
..
..
..
47.9
..
..
..
16.7
48.9
34.9
31.4
..
50.5
..
..
..
17.9
..
26.2
39.9
47.3
37.5
..
..
..
..
..
..
..
..
..
..
0.0
8.5
0.0
1.1
..
11.9
..
..
..
..
..
0.0
..
..
..
..
..
..
..
..
0.0
0.8
5.7
..
..
..
0.0
..
..
..
7.1
0.0
0.0
1.0
..
0.0
..
..
..
7.5
..
12.0
1.0
0.0
1.1
..
..
..
..
..
..
..
..
51.9
100.0
39.3
96.6
39.2
21.8
13.3
100.0
62.5
13.5
..
100.0
16.1
33.1
100.0
..
..
..
100.0
13.7
14.3
38.9
97.8
14.6
100.0
..
29.7
31.2
40.6
39.3
17.8
13.6
96.6
96.8
19.2
100.0
..
100.0
..
100.0
..
96.6
..
96.6
13.4
14.0
15.8
16.7
21.0
..
..
99.3
..
100.0
57.6
..
..
0.0
0.0
0.0
0.0
..
0.0
..
..
..
..
..
0.0
..
..
..
..
..
..
..
..
0.0
0.0
0.0
..
..
..
0.0
..
..
..
0.0
0.0
0.0
0.0
..
0.0
..
..
..
0.0
..
0.0
0.0
0.0
0.0
..
..
..
..
..
..
..
..
a. Provisional.
b. Data are for the most recent year available during the period specified.
68
Part III. Development outcomes
trade and reGional inteGration
Tariff barriers, primary products (%)
Simple
mean tariff
2010
Dispersion
around the mean
2009
Weighted
mean tariff
2010
..
..
15.5
6.1
11.4
15.4
..
16.2
..
..
..
..
..
15.1
..
..
..
..
..
..
..
..
14.6
16.0
9.2
..
..
..
12.8
..
..
..
4.1
14.0
11.8
11.5
..
14.1
..
..
..
5.4
..
9.7
17.5
14.4
15.7
..
..
..
..
..
..
..
..
0.8
0.7
0.5
1.4
0.5
..
0.5
1.1
..
0.5
..
0.5
..
0.5
0.7
..
..
0.5
0.5
0.3
0.3
0.5
0.5
0.7
1.4
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
1.5
0.5
1.4
0.7
0.5
0.7
0.5
..
..
0.5
4.8
..
1.2
..
..
..
12.4
0.5
8.1
9.4
..
12.2
..
..
..
..
..
5.4
..
..
..
..
..
..
..
..
10.0
12.6
1.6
..
..
..
7.9
..
..
..
2.1
10.7
9.1
6.4
..
7.7
..
..
..
1.9
..
1.3
8.7
12.4
8.8
..
..
..
..
..
..
..
..
trade and reGional inteGration
Tariff barriers, manufactured products (%)
Simple
mean tariff
2010
..
..
12.9
9.0
12.5
9.1
..
14.3
..
..
..
..
..
12.8
..
..
..
..
..
..
..
..
12.9
11.7
9.5
..
..
..
12.8
..
..
..
6.7
12.8
10.7
9.7
..
13.2
..
..
..
7.8
..
11.1
12.4
12.6
11.6
..
..
..
..
..
..
..
..
Dispersion
around the mean
2009
Weighted
mean tariff
2010
0.9
0.9
0.6
1.5
..
..
0.6
1.3
..
0.6
..
0.5
..
0.6
0.4
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
1.6
0.9
1.5
0.9
0.6
1.0
0.8
..
..
0.7
4.7
..
1.4
..
..
..
11.7
8.0
11.7
11.5
..
9.8
..
..
..
..
..
11.7
..
..
..
..
..
..
..
..
11.7
11.5
8.0
..
..
..
11.7
..
..
..
8.0
11.7
11.3
11.5
..
11.7
..
..
..
8.0
..
8.0
11.5
11.7
11.5
..
..
..
..
..
..
..
..
Average cost to ship 20 ft
container from port to
final destination ($)
Export
Import
2010
2010
1,938
1,850
1,251
3,010
2,412
2,747
1,379
1,200
5,491
5,902
1,073
3,505
3,818
1,969
836
1,411
1,431
1,890
1,945
831
1,013
855
1,545
2,055
1,680
1,232
1,197
1,713
2,202
1,520
737
1,100
1,686
3,545
1,263
3,275
690
1,098
876
1,573
..
1,531
2,050
1,754
1,262
940
2,780
2,664
3,280
834
1,248
613
..
700
773
2,458
2,840
1,400
3,390
4,030
4,285
1,978
1,000
5,554
8,150
1,057
3,735
7,709
2,577
911
1,411
1,581
2,993
1,955
975
1,203
1,391
2,349
2,190
1,610
1,212
1,555
2,570
3,067
1,523
689
1,475
1,813
3,545
1,440
4,990
577
1,940
876
1,639
..
1,807
2,900
1,849
1,475
963
2,940
3,315
5,101
996
1,428
698
..
1,000
858
Average time to clear customs
(days)
Direct exports
Imports
2009–10 b
2009–10 b
6.7
9.6
6.2
7.4
..
15.1
..
..
11.9
..
18.0
..
16.6
..
..
9.6
..
3.8
..
..
..
..
..
5.4
..
14.2
9.9
12.9
..
10.3
..
..
2.6
..
..
..
..
..
..
..
..
..
..
..
6.7
..
..
..
..
..
..
..
..
..
11.4
33.0
3.7
16.4
..
24.0
20.5
..
27.5
..
45.4
31.4
31.2
..
..
20.1
..
10.3
..
..
..
..
..
4.4
6.7
19.3
11.2
16.5
..
9.8
..
..
9.3
..
..
..
..
..
12.2
..
..
..
..
..
9.0
..
..
..
..
..
..
..
..
..
Part III. Development outcomes
69
Table
Drivers of growth
5.2
Top three exports and share in total exports, 2009
First
Product
SUB–SAHARAN AFRICA
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Cape Verde
Central African Republic
Chad
Comoros
Congo
Congo, Dem. Rep.
Cote 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 & Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
AFRICAa
Second
Share
of total
exports
(%)
Product
Petroleum oils and oils from bituminous minerals, crude
Cashew nuts, in shells
Diamonds, nonindustrial, unworked or simply sawn or cleaved
Cotton, not carded or combed
Coffee, not roasted, not decaffeinated
Petroleum oils and oils from bituminous minerals, crude
Tunas, yellowfin
Logs, tropical hardwoods, not elsewhere specified
Petroleum oils and oils from bituminous minerals, crude
Cloves (whole fruit, cloves and stems)
Petroleum oils and oils from bituminous minerals, crude
Cobalt ores and concentrates
Cocoa beans, whole or broken, raw or roasted
Live bovine animals other than purebred breeding animals
Petroleum oils and oils from bituminous minerals, crude
Prefabricated buildings
Coffee, not roasted, not decaffeinated
Petroleum oils and oils from bituminous minerals, crude
Cashew nuts, in shells
Cocoa beans, whole or broken, raw or roasted
Aluminum ores and concentrates
Cashew nuts, in shells
Black tea (fermented) and other partly fermented tea
Diamonds, nonindustrial, unworked or simply sawn or cleaved
Cargo vessels and other vessels for transport of goods or persons
Shrimps and prawns
Tobacco, partly or wholly stemmed
Cotton, not carded or combed
Iron ores and concentrates, nonagglomerated
T-shirts, singlets, and other vests, knitted of cotton
Aluminum, unwrought, not alloyed
Natural uranium and its compounds
Natural uranium and its compounds
Petroleum oils and oils from bituminous minerals, crude
Coffee, not roasted, not decaffeinated
Cocoa beans, whole or broken, raw or roasted
Phosphoric acid and polyphosphoric acids
Tunas, skipjack, and bonito
Diamonds, nonindustrial, unworked or simply sawn or cleaved
Goats, live
Platinum, unwrought or in powder form
Petroleum oils and oils from bituminous minerals, crude
Cane sugar, raw
Coffee, not roasted, not decaffeinated
Cocoa beans, whole or broken, raw or roasted
Coffee, not roasted, not decaffeinated
Refined copper, cathodes and sections of cathodes
Tobacco, partly or wholly stemmed
96.3
29.5
27.9
52.1
76.1
39.6
16.4
25.8
90.9
32.1
87.8
20.7
36.3
27.4
72.7
19.3
31.0
69.9
44.5
49.7
62.9
92.2
14.3
33.3
42.1
9.3
63.0
39.3
45.4
13.4
38.1
16.4
70.5
86.3
29.0
47.1
25.5
59.2
21.5
28.3
9.3
91.3
15.7
9.6
47.1
35.4
49.8
22.9
Petroleum oils and oils from bituminous minerals, crude
Liquefied natural gas
Petroleum oils and oils from bituminous minerals, crude
Phosphoric acid and polyphosphoric acids
Petroleum oils and oils from bituminous minerals, crude
46.8
15.8
79.3
6.6
9.4
Petroleum oils and oils from bituminous
minerals, crude
44.8 Liquefied natural gas
[18.5]
Share
of total
exports
(%)
Cotton, not carded or combed
Nickel mattes
Gold, semi-manufactured, including platinum plated, nonmonetary
Black tea (fermented) and other partly fermented tea
Cocoa beans, whole or broken, raw or roasted
Fish, whole or in pieces
Diamonds, not mounted or set, unsorted
Petroleum oils and oils from bituminous minerals, noncrude
Vessels and other floating structures for breaking up
28.7
19.9
19.6
9.3
18.7
13.5
25.4
5.6
26.8
Petroleum oils and oils from bituminous minerals, crude
Petroleum oils and oils from bituminous minerals, crude
Sheep, live
Liquefied natural gas
Sheep, live
Sesamum seeds
Manganese ores and concentrates
Petroleum oils and oils from bituminous minerals, crude
Manganese ores and concentrates
Aluminum oxide not elsewhere specified
16.6
14.6
17.8
22.2
14.2
24.9
9.8
14.3
8.5
11.2
Cut flowers and flower buds, fresh
Men’s and boys’ trousers and shorts, of cotton, not knitted
Tankers
Women’s and girls’ trousers, overalls, breeches, and shorts, of cotton
Dried leguminous vegetables, shelled, not elsewhere specified
Mineral or chemical fertilizers containing nitrogen, phosphorus, potassium
Octopus, other than live, fresh, and chilled
Cane sugar, raw
Electrical energy
Unwrought zinc, containing by weight 99.99 percent or more of zinc
Light oils and preparations
Liquefied natural gas
Niobium, tantalum, and vanadium ores and concentrates
Wristwatches, other than automatic winding
Fish, fresh and chilled, not elsewhere specified
Tunas, bigeye (Thunnus obesus)
Titanium ores and concentrates
Sheep, live
Gold, unwrought, nonmonetary
13.8
13.8
19.3
6.7
8.8
12.5
14.4
12.2
10.5
14.5
23.8
7.5
20.6
12.3
6.8
7.3
11.8
24.3
6.4
Mixtures of odoriferous substances for the food or drink industries
Tobacco, partly or wholly stemmed
Ground
Fish fillets and other fish meat, fresh or chilled
Copper, unrefined, and copper anodes for electrolytic refining
Ferro-chromium containing by weight more than 4% carbon
13.4
9.2
8.3
8.8
16.5
9.1
Natural gas, in gaseous state
Petroleum oils and oils from bituminous minerals, crude
Natural gas, in gaseous state
Ignition and other wiring sets of a kind used in vehicles, aircraft or ships
Ignition and other wiring sets of a kind used in vehicles, aircraft or ships
21.0
15.3
9.1
4.8
6.1
3.9
[20.0]
Note: Includes only products that account for more than 4 percent of total exports.
a. Values in brackets are Africa’s share of total world exports.
70
Part III. Development outcomes
trade and reGional inteGration
Third
Product
Copper waste and scrap
Diamonds, nonindustrial, not mounted or set, not elsewhere specified
Sesamum seeds
Bananas, including plantains, fresh
Men’s and boys’ trousers and shorts, of cotton, not knitted
Logs, tropical wood specified in Subhe
Essential oils, not elsewhere specified
Share of total
exports
(%)
6.0
8.6
9.1
8.4
10.4
16.7
18.6
Copper ores and concentrates
Cocoa paste, not defatted
Goats, live
14.1
8.0
13.2
Men’s and boys’ shirts, of cotton
Cut flowers and flower buds, fresh
Logs, tropical hardwoods, not elsewhere specified
Titanium ores and concentrates
Cocoa butter, fat and oil
Coffee, not roasted, not decaffeinated
6.9
10.9
7.0
12.3
5.6
4.0
Coffee, not roasted, not decaffeinated
Pullovers, cardigans, and similar articles, knitted of cotton
Petroleum oils and oils from bituminous minerals, crude
Vanilla
Black tea (fermented) and other partly fermented tea
Sesamum seeds
Petroleum oils and oils from bituminous minerals, crude
Tunas, skipjack, and bonito
Light oils and preparations
Uranium ores and concentrates
5.9
11.0
13.3
5.6
6.3
8.1
13.2
11.2
9.0
13.3
Tin ores and concentrates
Aircraft, unladen weight of 2,000–15,000 kilograms
Fish, frozen, not elsewhere specified
Skipjack and stripbellied bonito
Cocoa beans, whole or broken, raw or roasted
Live bovine animals
Iron ores and concentrates, nonagglomerated
11.2
9.7
6.0
5.4
8.5
21.6
5.6
Food preparations not elsewhere specified
Precious metal ores and concentrates, other than silver
Gold, unwrought, nonmonetary
Tobacco, partly or wholly stemmed
Copper ores and concentrates
Cane sugar, raw
10.6
8.3
7.7
7.5
7.8
8.3
Liquefied natural gas
Light oils and preparations
Petroleum oils and oils from bituminous minerals, noncrude
10.8
5.3
4.8
Men’s and boys’ trousers and shorts, of cotton, not knitted
Natural gas, in gaseous state
trade and reGional inteGration
5.5
3.7
[9.9]
Number
of exports
accounting for
75 percent of
total exports
1
6
16
3
1
5
9
4
1
3
1
6
7
5
2
19
7
2
4
7
3
1
54
6
4
31
3
8
4
36
8
7
2
1
5
4
19
4
22
4
103
1
25
31
5
15
4
19
3
65
1
76
94
40
Part III. Development outcomes
71
Table
Drivers of growth
5.3
Regional integration, trade blocs
Year of
entry into
force
Type of
of most
most
Year
recent
recent
established agreement agreementa
Economic and Monetary Community
of Central African States (CEMAC)
1994
Economic Community of the
Great Lakes Countries (CEPGL)
1976
1999
Merchandise exports within bloc
($ millions)
2000
2005
2007
1990
1995
139
120
96
201
NNA
7
8
10
20
CU
2008
2009
305
355
300
29
73
64
Common Market for Eastern and
Southern Africa (COMESA)
1994
1994
FTA
1,146
1,367
1,443
2,695
4,021
6,676
6,114
East African Community (EAC)
1996
2000
CU
335
628
689
1075
1,385
1,797
1,572
Economic Community of Central
African States (ECCAS)
1983
2004b
NNA
160
157
182
255
385
449
378
Economic Community of West
African States (ECOWAS)
1975
1993
PTA
1,532
1,875
2,715
5,497
6,717
9,355
7,312
Indian Ocean Commission (IOC)
1984
2005b
NNA
63
113
106
162
214
217
183
Southern African Development
Community (SADC)
1992
2000
FTA
1,655
3,615
4,427
7,799
12,051
16,011
11,697
West African Economic and
Monetary Union (UEMOA)
1994
2000
CU
621
560
741
1,390
1,735
2,281
1,927
2008
2009
Year of
entry into
force
Type of
of most
most
Year
recent
recent
established agreement agreementa
Economic and Monetary Community
of Central African States (CEMAC)
1994
Economic Community of the
Great Lakes Countries (CEPGL)
1976
1999
Merchandise exports within bloc
(% of total bloc exports)
2000
2005
2007
1990
1995
CU
2.3
2.1
1.0
0.9
1.1
0.8
1.2
NNA
0.5
0.5
0.8
1.2
1.4
1.9
2.2
Common Market for Eastern and
Southern Africa (COMESA)
1994
1994
FTA
4.7
6.1
4.6
4.6
4.5
5.3
7.2
East African Community (EAC)
1996
2000
CU
17.7
19.5
22.6
18.0
17.8
19.2
18.9
Economic Community of Central
African States (ECCAS)
1983
2004b
NNA
1.4
1.5
1.0
0.6
0.6
0.4
0.6
Economic Community of West
African States (ECOWAS)
1975
1993
PTA
8.0
9.0
7.6
9.3
7.8
8.5
9.9
Indian Ocean Commission (IOC)
1984
2005b
NNA
3.9
5.9
4.4
4.9
5.8
5.7
5.8
Southern African Development
Community (SADC)
1992
2000
FTA
6.6
10.2
9.5
9.3
10.2
10.3
11.0
West African Economic and
Monetary Union (UEMOA)
1994
2000
CU
13.0
10.3
13.1
13.4
14.9
15.9
13.2
72
Part III. Development outcomes
trade and reGional inteGration
Year of
entry into
force
Type of
of most
most
Year
recent
recent
established agreement agreementa
Economic and Monetary Community
of Central African States (CEMAC)
1994
Economic Community of the
Great Lakes Countries (CEPGL)
1976
1999
Merchandise exports by bloc
(% of world exports)
2000
2005
2007
1990
1995
2008
2009
CU
0.2
0.1
0.1
0.2
0.2
0.2
0.2
NNA
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Common Market for Eastern and
Southern Africa (COMESA)
1994
1994
FTA
0.7
0.4
0.5
0.6
0.6
0.8
0.7
East African Community (EAC)
1996
2000
CU
0.1
0.1
0.0
0.1
0.1
0.1
0.1
Economic Community of Central
African States (ECCAS)
1983
2004b
NNA
0.3
0.2
0.3
0.4
0.5
0.7
0.5
Economic Community of West
African States (ECOWAS)
1975
1993
PTA
0.6
0.4
0.6
0.6
0.6
0.7
0.6
Indian Ocean Commission (IOC)
1984
2005b
NNA
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Southern African Development
Community (SADC)
1992
2000
FTA
0.7
0.7
0.7
0.8
0.9
1.0
0.9
West African Economic and
Monetary Union (WAEMU/UEMOA)
1994
2000
CU
0.1
0.1
0.1
0.1
0.1
0.1
0.1
Note: Economic and Monetary Community of Central Africa (CEMAC; formerly Central African Customs and Economic Union [UDEAC]), Cameroon, the Central African Republic,
Chad, the Republic of Congo, Equatorial Guinea, and Gabon; Economic Community of the Great Lakes Countries (CEPGL), Burundi, the Democratic Republic of the Congo, and
Rwanda; Common Market for Eastern and Southern Africa (COMESA), Burundi, Comoros, the Democratic Republic of Congo, Djibouti, the Arab Republic of Egypt, Eritrea, Ethiopia,
Kenya, Libya, Madagascar, Malawi, Mauritius, Rwanda, Seychelles, Sudan, Swaziland, Uganda, Zambia, and Zimbabwe; East African Community (EAC), Burundi, Kenya, Rwanda,
Tanzania, and Uganda; Economic Community of Central African States (ECCAS), Angola, Burundi, Cameroon, the Central African Republic, Chad, the Democratic Republic of Congo,
the Republic of Congo, Equatorial Guinea, Gabon, and São Tomé and Príncipe; Economic Community of West African States (ECOWAS), Benin, Burkina Faso, Cape Verde, Côte d’Ivoire,
the Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone, and Togo; Indian Ocean Commission (IOC), Comoros, Madagascar, Mauritius, Réunion,
and Seychelles; Southern African Development Community (SADC; formerly Southern African Development Coordination Conference), Angola, Botswana, the Democratic Republic
of the Congo, Lesotho, Madagascar, Malawi, Mauritius, Mozambique, Namibia, Seychelles, South Africa, Swaziland, Tanzania, Zambia, and Zimbabwe; West African Economic and
Monetary Union (UEMOA), Benin, Burkina Faso, Côte d’Ivoire, Guinea-Bissau, Mali, Niger, Senegal, and Togo.
a. CU is customs union; FTA is free trade agreement; NNA is not notified agreement, which refers to preferential trade agreements established among member countries that are not notified
to the World Trade Organization (these agreements may be functionally equivalent to any of the other agreements); and PTA is preferential trade agreement.
b. From the official website of the trade bloc.
trade and reGional inteGration
Part III. Development outcomes
73
Table
Drivers of growth
6.1
Water and sanitation
Access,
supply side
Access, demand side
Population with sustainable access
Population with sustainable
Internal
to an improved water source
access to improved sanitation
fresh water
resources per
(% of
(% of
(% of
(% of
(% of
(% of
capita (cubic
total
urban
rural
total
urban
rural
meters)
population) population) population) population) population) population)
2007
2008
2008
2008
2008
2008
2008
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
4,850
8,431
1,227
1,268
849
1,284
14,630
610
33,119
1,412
1,910
14,395
62,516
3,819
360
40,485
586
1,551
115,340
1,857
1,325
23,505
10,383
548
2,574
55,138
18,114
1,118
4,835
127
2,182
4,586
2,949
248
1,496
1,005
13,829
2,169
..
29,518
687
928
742
2,293
2,035
1,825
1,273
6,513
985
290
332
23
97
929
410
60
50
75
95
76
72
74
84
67
50
95
46
71
80
92
..
61
38
87
92
82
71
61
59
85
68
41
80
56
49
99
47
92
48
58
65
89
69
..
49
30
91
57
69
54
60
67
60
82
92
83
99
..
81
94
83
60
84
99
95
83
92
85
92
67
91
80
95
93
98
..
74
98
95
96
90
89
83
83
97
79
71
95
81
52
100
77
99
96
75
77
89
92
100
86
67
99
64
92
80
87
91
87
99
95
85
100
..
98
99
47
38
69
90
72
71
51
82
51
44
97
28
34
68
52
..
57
26
41
86
74
61
51
52
81
51
29
77
44
47
99
29
88
39
42
62
88
52
..
26
9
78
52
61
45
41
64
46
72
87
79
98
..
60
84
31
57
12
60
11
46
47
54
34
9
36
23
30
23
56
..
14
12
33
67
13
19
21
31
29
17
11
56
36
26
91
17
33
9
32
54
26
51
..
13
23
77
34
55
24
12
48
49
44
89
95
94
97
69
85
44
86
24
74
33
49
56
65
43
23
50
23
31
36
63
..
52
29
33
68
18
34
49
27
40
25
15
51
45
50
93
38
60
34
36
50
30
69
97
24
52
84
55
61
32
24
38
59
56
94
98
97
97
83
96
24
18
4
39
6
46
35
38
28
4
30
23
29
11
10
..
4
8
30
65
7
11
9
32
25
4
10
57
32
9
90
4
17
4
28
55
19
38
..
6
6
65
18
53
21
3
49
43
37
83
88
92
96
52
64
Quality
of supply
Average
duration of
insufficient
water supply
2009–10 a
..
9.9
19.0
3.2
4.6
..
23.5
9.8
..
2.7
..
13.6
45.3
27.7
..
..
..
..
1.1
..
..
..
..
..
6.1
2.9
8.0
4.7
12.1
..
6.0
..
..
..
..
..
..
..
..
0.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
Financing
Committed
nominal
investment in
ODA gross
water projects disbursements for
with private
water supply and
participation
sanitation sector
($ millions)
($ millions)
a
2000–09
2008
2009
..
..
..
..
..
0.0
..
..
..
..
..
0.0
0.0
..
..
..
..
..
..
0.0
..
..
..
..
..
..
..
..
..
0.0
..
0.0
3.4
..
..
..
0.0
..
..
..
0.0
120.7
..
8.5
..
0.0
0.0
..
468.0
..
..
..
..
1,668.2
22.3
63.5
2.2
60.5
15.7
18.5
6.4
1.9
26.0
1.3
62.0
1.8
7.9
3.2
0.0
8.2
107.1
18.6
9.1
124.4
14.7
3.0
101.3
18.8
7.1
17.4
13.9
47.1
21.9
9.5
81.6
11.8
38.1
108.7
37.7
0.9
76.2
0.2
13.3
1.9
52.7
21.8
1.1
148.9
3.0
64.2
39.5
12.1
464.0
4.7
56.7
0.0
301.0
98.6
1,789.9
13.9
55.0
0.0
70.7
19.2
8.7
20.4
6.7
28.9
1.4
73.7
0.4
30.6
7.1
0.0
7.4
142.6
3.2
5.0
56.3
11.2
2.6
98.2
23.1
13.1
12.8
16.0
78.0
23.6
10.8
95.5
12.0
43.7
105.5
28.2
1.0
58.3
0.6
10.0
5.1
60.9
55.2
0.3
173.2
5.8
86.4
50.5
7.6
542.1
9.0
106.0
0.0
319.4
100.4
a. Data are for the most recent year available during the period specified.
74
Part III. Development outcomes
infrastructure
Table
Drivers of growth
6.2
Transportation
Access, supply side
Road network
(km)
2000–08 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 Príncipe
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
19,000
25,798
92,495
12,322
51,346
1,350
24,307
40,000
880
153,497
17,000
81,996
3,065
2,880
4,010
44,359
9,170
3,742
57,614
44,348
3,455
63,265
5,940
10,600
49,827
15,451
18,912
11,066
2,028
30,331
66,467
18,948
193,200
14,008
320
14,805
508
11,300
22,100
362,099
11,900
3,594
87,524
11,652
70,746
66,781
97,267
111,261
104,918
83,200
58,256
19,371
Rail lines
(km)
2009
..
..
..
888
622
..
977
..
..
..
..
3,641
..
639
..
..
..
..
810
..
..
..
..
..
..
..
..
..
..
728
..
3,116
..
..
..
..
..
..
..
..
..
22,051
4,508
300
..
..
..
..
..
14,019
4,723
5,195
..
2,110
1,991
Access, demand side
Vehicle fleet (per 1,000 people)
Road density
Ratio to total land
(road km/100 sq km
of land area)
2000–08 a
Commercial
vehicles
2000–08 a
Passenger
vehicles
2000–08 a
4.0
17.0
4.0
34.0
44.0
11.0
33.0
4.0
3.0
39.0
7.0
5.0
25.0
14.0
10.0
3.0
4.0
3.0
33.0
24.0
18.0
12.0
11.0
20.0
10.0
8.0
13.0
2.0
1.0
99.0
4.0
0.0
1.0
21.0
53.0
33.0
8.0
110.0
..
3.0
30.0
1.0
21.0
9.0
21.0
29.0
12.0
25.0
40.0
21.0
113.0
11.0
6.0
..
94.0
0.3
6.0
33.0
5.0
26.0
20.0
..
..
11.0
3.0
..
7.0
33.0
..
33.0
21.0
..
3.0
27.0
9.0
9.0
..
159.0
13.0
109.0
5.0
31.0
4.0
2.0
23.0
173.0
5.0
..
159.0
28.0
89.0
73.0
2.0
7.0
18.0
106.0
8.0
17.0
56.0
7.0
2.0
11.0
67.0
0.3
..
31.0
..
15.0
16.0
..
..
6.0
1.0
..
5.0
21.0
..
27.0
15.0
..
2.0
8.0
4.0
7.0
..
123.0
9.0
52.0
4.0
31.0
2.0
2.0
17.0
103.0
3.0
..
108.0
20.0
46.0
4.0
2.0
3.0
11.0
91.0
5.0
10.0
5.0
13.0
12.0
112.0
43.0
291.0
71.0
114.0
72.0
31.0
225.0
53.0
76.0
(continued)
infrastructure
Part III. Development outcomes
75
Table
Drivers of growth
6.2
Transportation (continued)
Quality
Ratio of paved to
total roads (%)
2000–08 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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
10.4
9.5
32.6
4.2
10.4
8.4
69.0
..
0.8
76.5
1.8
7.1
7.9
45.0
..
21.8
13.7
10.2
19.3
14.9
9.8
27.9
14.1
18.3
6.2
11.6
45.0
19.0
26.9
98.0
20.8
12.8
20.7
15.0
19.0
68.1
29.3
96.5
8.0
11.8
17.3
36.3
30.0
7.4
21.0
23.0
22.0
19.0
73.5
86.9
57.2
67.8
75.2
Pricing
Financing
Price of
diesel fuel
($ per liter)
2010
Price of
gasoline
($ per liter)
2010
1.15
0.43
1.21
0.97
1.28
1.42
1.10
1.33
1.69
1.31
..
1.27
0.84
1.30
1.07
..
1.07
0.78
..
..
0.83
0.95
..
1.27
1.07
0.96
1.26
1.54
1.25
0.99
1.23
0.86
1.09
1.16
0.77
1.62
..
1.34
..
0.94
..
1.14
0.43
1.10
1.19
1.17
1.11
1.52
1.15
0.32
0.19
0.32
0.13
0.88
0.82
1.25
0.65
1.04
0.93
1.44
1.43
1.20
1.84
1.71
1.32
..
1.28
1.27
1.68
1.63
..
2.54
0.91
..
..
0.82
0.95
..
1.33
0.97
0.98
1.52
1.71
1.42
1.16
1.55
1.11
1.06
1.07
0.44
1.63
..
1.57
..
0.94
..
1.19
0.62
1.07
1.22
1.18
1.42
1.66
1.29
0.48
0.32
0.48
0.17
1.23
0.94
Committed nominal
investment in transport
projects with private
participation ($ millions)
2000–08 a
53.0
..
..
..
..
0.0
..
..
..
0.5
..
735.0
0.0
396.0
..
..
..
3.9
..
0.0
159.0
..
404.0
..
..
17.5
..
55.4
..
..
0.0
..
..
382.0
..
..
264.0
..
..
..
3,483.0
30.0
..
134.0
..
404.0
15.6
..
108.0
640.0
..
200.0
840.0
ODA gross disbursements for
transportation and storage
($ millions)
2008
2009
2,460.5
1.8
99.4
0.1
38.2
34.3
92.1
76.1
5.1
58.2
0.6
159.4
28.2
6.7
3.6
..
1.8
313.8
7.0
6.4
119.3
35.5
16.8
97.5
16.1
31.2
117.8
33.0
81.0
41.6
1.5
100.5
25.8
60.7
44.4
50.7
3.7
82.9
..
22.6
0.1
0.4
29.3
0.0
162.8
0.0
178.5
77.1
0.0
531.4
90.4
110.2
..
179.2
144.7
3,039.4
5.7
92.3
12.9
52.5
46.0
90.2
55.7
15.3
45.3
2.2
138.3
20.4
16.0
93.8
..
2.9
251.8
75.9
9.7
116.6
28.6
15.1
115.3
6.5
49.8
42.8
22.3
44.6
22.9
0.7
100.0
53.7
38.8
108.7
26.8
1.6
89.1
..
34.2
1.7
520.5
78.3
0.4
146.4
0.6
103.1
34.6
0.0
890.6
76.0
145.5
..
344.2
320.3
a. Data are for the most recent year available during the period specified.
76
Part III. Development outcomes
infrastructure
Table
Drivers of growth
6.3
Information and communication technology
Access, supply side
Telephone subscribers (per 100 people)
Total
2009
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
38.8
45.5
57.8
103.5
22.0
10.5
39.6
91.8
4.1
24.1
19.0
15.5
59.6
64.7
16.9
67.3
3.7
6.0
94.9
86.9
64.5
55.9
35.1
50.3
33.9
21.3
31.5
16.9
29.4
68.6
114.9
26.4
62.6
17.4
48.2
24.6
44.1
57.3
130.0
20.9
8.1
102.9
37.2
59.1
40.3
35.8
29.4
34.8
27.0
88.1
101.2
79.1
95.1
90.1
105.8
Mainline
telephone
2009
1.5
1.6
1.4
7.4
1.1
0.4
1.7
14.3
0.3
0.1
3.9
0.1
0.7
1.3
2.0
1.5
1.0
1.1
1.8
2.9
1.1
0.2
0.3
1.7
1.9
0.1
0.9
1.2
0.6
2.3
29.7
0.4
6.5
0.4
0.9
0.3
4.8
2.2
25.1
0.6
1.1
8.8
0.9
3.7
0.4
2.7
0.7
0.7
3.1
11.3
7.4
12.4
17.2
11.0
12.3
Mobile
telephone
2009
37.3
43.8
56.3
96.1
20.9
10.1
37.9
77.5
3.8
24.0
15.2
15.4
58.9
63.3
14.9
65.8
2.8
4.9
93.1
84.0
63.4
55.7
34.8
48.7
32.0
21.3
30.6
15.7
28.8
66.3
85.2
26.1
56.1
17.0
47.2
24.3
39.3
55.1
104.9
20.4
7.0
94.2
36.3
55.4
39.9
33.1
28.7
34.1
23.9
76.9
93.8
66.7
77.9
79.1
93.5
Access, demand side
Unmet
Average delay for
demand
Households with firm in obtaining
(% of mainline own telephone a mainline phone
telephones) (% of households) connection (days)
2008
2008
2009–10a
..
..
..
..
..
0.1
..
0.4
..
..
28.3
..
..
..
..
..
49.5
2.1
..
..
0.2
..
..
0.4
..
..
0.1
..
..
..
..
..
..
..
..
..
..
..
9.8
..
..
..
0.0
0.2
..
..
..
..
..
..
..
0.3
..
..
0.9
..
..
..
..
..
..
..
..
..
..
..
..
..
..
7.2
..
..
..
..
..
..
..
..
..
..
..
2.4
..
..
..
73.6
..
..
1.4
1.8
1.1
..
..
..
0.8
..
18.1
..
..
0.7
..
..
..
..
..
..
..
..
26.0
..
9.3
89.4
17.1
19.5
..
19.2
8.2
..
13.3
..
20.1
25.5
5.8
..
..
..
..
8.6
..
..
..
..
..
53.7
..
29.9
45.9
13.8
..
38.6
..
..
13.9
..
..
..
..
..
21.4
..
..
..
..
..
51.0
..
..
..
..
..
..
..
..
Internet
users
(per 100
people)
2009
8.8
3.3
2.2
6.2
1.1
0.8
3.8
29.7
0.5
1.7
3.7
0.6
6.7
4.6
3.0
2.1
4.9
0.5
6.7
7.6
5.4
0.9
2.3
10.0
3.7
0.5
1.6
4.7
1.9
2.3
22.7
2.7
5.9
0.8
28.4
4.5
16.4
7.4
38.7
0.3
1.2
9.0
9.9
7.6
1.6
5.4
9.8
6.3
11.4
21.3
13.5
20.0
5.5
32.2
33.6
Quality
Telephone faults
Total
Cleared by next
(per 100
working day
mainlines)
(%)
2009
2009
..
..
6.6
..
..
..
..
3.0
..
..
..
..
..
..
..
..
50.2
4.9
..
..
1.1
..
..
26.1
..
..
9.5
..
..
..
..
..
..
..
..
0.0
..
..
5.0
..
..
..
5.0
0.6
..
..
..
..
41.0
..
..
0.1
..
..
24.8
..
..
40.7
..
..
..
..
93.0
..
..
..
..
..
..
31.0
..
24.0
66.0
..
..
60.0
..
..
47.0
..
..
92.4
..
..
..
..
..
..
..
..
98.0
..
92.0
95.0
..
..
..
95.0
63.0
..
..
..
..
..
..
..
98.3
..
..
78.7
(continued)
infrastructure
Part III. Development outcomes
77
Table
Drivers of growth
6.3
Information and communication technology (continued)
Fixed
broadband
internet
subscription
($ per month)
2009
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
56.9
154.3
112.5
56.9
87.2
..
84.7
33.3
1,270.7
12.5
409.4
..
..
42.4
56.3
254.1
..
517.6
..
..
45.5
..
..
38.8
43.7
..
100.2
490.6
53.0
57.2
15.1
80.6
41.2
254.1
105.8
88.0
202.5
38.1
42.8
29.3
..
23.5
26.1
749.2
22.7
1,049.6
41.9
47.4
..
15.1
15.1
8.1
39.9
16.0
11.1
Cost of 3-minute call
during peak hours ($)
Fixed
telephone
local
2009
0.19
0.29
0.13
0.19
0.24
..
0.32
0.07
0.13
0.37
0.14
..
..
0.38
0.09
..
0.02
0.02
..
..
0.11
..
..
0.11
0.20
..
0.30
..
0.11
0.23
0.07
0.18
0.16
0.16
0.20
0.20
0.10
0.35
0.07
..
..
0.15
0.00
0.07
0.27
0.19
0.18
0.78
..
0.05
0.08
0.03
..
0.25
0.02
Pricing
Cost of 3-minute call
during off-peak hours ($)
Connection charge
($)
Mobile cellular
Cellular
local
2009
Fixed
telephone
local
2009
Cellular
local
2009
Residential
telephone
2009
Business
telephone
2009
Prepaid
2009
Postpaid
2009
Fixed
broadband
internet
2009
0.64
0.65
0.55
0.75
0.95
..
0.95
0.91
0.76
1.14
0.64
..
..
0.63
0.54
..
0.35
0.21
..
..
0.31
..
0.57
0.31
0.70
..
0.65
0.59
0.70
0.63
0.13
0.72
0.89
0.79
0.60
0.45
0.47
0.54
0.92
..
..
0.89
0.18
0.78
0.59
0.73
0.50
0.70
..
0.41
0.33
0.11
..
1.34
0.49
0.13
0.23
0.13
0.14
0.14
..
0.16
0.05
0.13
0.37
0.14
..
..
0.00
0.09
..
0.02
0.02
..
..
0.04
..
..
0.11
0.15
..
0.09
..
0.11
0.23
0.06
0.14
0.08
0.16
0.18
0.20
0.10
0.35
0.05
..
..
0.07
0.00
0.04
0.27
0.10
0.11
0.46
..
0.04
0.06
0.03
..
0.25
0.02
0.65
0.65
0.55
0.75
0.95
..
0.95
0.91
0.76
1.14
0.64
..
..
0.63
0.54
..
0.35
0.21
..
..
..
..
0.57
0.31
0.70
..
0.65
0.59
0.70
0.63
0.13
0.72
0.89
0.79
0.60
0.45
0.47
0.54
0.92
..
..
0.89
0.18
0.78
..
0.73
..
0.70
..
0.41
0.33
0.11
..
1.34
0.49
35.7
56.7
204.4
35.4
53.0
..
42.4
25.8
75.0
112.5
114.4
..
..
21.2
56.3
..
71.5
20.6
..
..
28.4
..
..
29.7
39.7
..
30.2
..
81.9
19.1
36.0
17.8
34.6
31.8
..
52.8
25.9
21.2
48.1
..
..
55.2
..
25.1
15.2
75.0
59.1
9.9
..
14.8
..
6.7
..
74.5
14.8
52.4
56.7
372.1
51.9
53.0
..
105.9
26.4
75.0
112.5
114.4
..
..
21.2
56.3
..
71.5
20.6
..
..
28.4
..
..
..
..
..
30.2
..
81.9
19.1
72.0
17.8
34.6
..
..
..
25.9
..
48.1
..
..
55.2
..
42.0
15.2
75.0
59.1
29.7
..
90.2
..
90.2
..
148.9
37.0
..
..
5.3
1.4
..
..
..
..
..
1.7
..
..
..
..
28.1
..
100.2
14.4
..
..
0.7
..
1.1
..
..
..
..
..
..
..
3.1
..
..
..
..
..
..
..
3.7
..
..
..
..
..
0.4
..
..
..
..
3.7
..
3.2
..
14.9
3.7
2.1
..
5.3
1.4
6.4
..
5.3
..
2.1
1.7
..
..
..
..
28.1
..
100.2
14.4
..
..
0.7
..
1.1
1.3
5.9
..
0.5
2.8
2.1
1.9
3.1
0.7
2.2
3.2
..
1.8
8.6
4.2
3.7
..
..
17.6
2.2
1.8
0.4
2.1
1.5
..
..
5.3
6.9
3.2
..
14.9
3.7
72.0
90.8
31.8
94.7
..
..
105.9
29.0
..
309.2
169.4
..
..
53.0
28.1
264.7
..
..
..
..
63.9
..
..
..
53.1
..
0.0
613.3
103.8
26.6
72.0
..
..
103.8
..
176.0
81.0
40.2
45.9
..
..
64.2
43.4
..
18.9
174.9
145.3
..
..
..
..
0.0
119.6
..
..
a. Data are for the most recent year available during the period specified.
78
Part III. Development outcomes
infrastructure
Financing
Annual investment
($ millions)
Fixed telephone
service
2009a
Mobile
communication
2009
143.1
..
0.8
..
..
..
..
..
..
..
..
..
..
..
7.1
..
..
..
..
..
..
..
..
40.4
..
..
7.6
..
..
..
..
..
..
..
..
..
..
38.2
..
..
..
..
..
..
..
..
..
..
49.0
258.7
..
177.9
..
..
80.8
6,107.9
..
335.9
..
..
..
..
..
..
..
..
203.8
..
271.5
1.2
..
..
..
..
..
592.9
..
..
454.6
..
..
..
..
..
..
..
..
..
..
..
..
..
227.2
..
..
..
..
..
20.7
..
..
..
..
4,000.0
1,327.8
..
1,166.2
..
..
161.6
infrastructure
Annual revenue ($ millions)
Committed nominal
investment in
telecommunication projects with
private participaTelecommunications
tion ($ millions)
2009
2009
4,070.7
..
336.7
..
118.0
..
..
..
..
..
3.9
203.8
..
298.6
8.6
..
..
..
..
..
640.5
..
..
514.2
..
..
..
..
63.5
..
..
..
..
..
644.7
174.3
..
265.4
..
..
..
..
..
..
..
..
298.5
..
500.0
4,085.3
..
3,135.4
..
684.1
265.8
11,333.0
354.0
127.0
86.0
193.0
–
278.0
23.0
6.0
68.0
..
151.0
110.0
318.0
..
..
–
..
91.0
–
847.0
87.0
28.0
278.0
11.0
24.0
83.0
73.0
429.0
43.0
35.0
52.0
–
87.0
3,057.0
183.0
..
256.0
..
23.0
–
2,387.0
357.0
25.0
522.0
44.0
283.0
114.0
200.0
2,716.0
398.0
1,791.0
..
240.0
287.0
ODA gross disbursements for
communication
($ millions)
2009
Fixed telephone
service
2009
Mobile
communication
2009
Telecommunications
2009
256.3
0.6
0.7
0.1
4.3
1.8
2.1
0.8
0.1
..
..
4.3
0.1
0.9
10.4
(0.0)
..
4.6
..
0.4
9.3
0.1
0.2
17.3
..
0.3
0.3
2.0
0.8
0.0
6.5
19.0
(8.7)
0.5
22.8
2.4
0.1
2.4
..
0.9
0.1
6.2
0.1
..
2.2
..
8.2
1.2
0.3
29.3
0.7
2.8
..
1.5
19.2
2,304.4
..
22.9
..
..
..
..
..
..
..
..
..
..
292.7
22.3
..
25.0
270.8
..
..
..
..
..
646.4
..
..
32.9
..
50.0
..
67.7
..
..
..
280.7
..
..
593.0
..
..
..
..
..
..
..
..
..
..
..
3,194.4
798.4
1,039.5
..
1,127.6
229.0
12,497.8
..
315.5
279.5
..
..
..
..
..
..
7.6
726.5
..
1,173.8
16.2
..
28.8
196.4
..
..
1,067.3
..
..
1,088.1
..
..
248.4
..
463.4
..
114.2
..
..
..
5,990.1
..
..
692.5
..
..
..
..
..
89.5
..
..
..
..
..
11,710.3
3,057.2
4,717.0
..
2,806.6
1,129.4
15,077.3
..
338.4
402.8
..
..
..
..
..
..
27.9
..
..
1,466.5
60.2
..
54.5
480.8
..
..
1,174.0
..
..
1,837.6
..
..
325.9
..
513.4
..
..
..
..
..
6,270.8
152.8
..
1,285.5
..
..
..
..
..
..
..
..
686.2
..
..
17,337.8
5,011.9
6,513.4
..
4,136.9
1,675.6
Part III. Development outcomes
79
Table
Drivers of growth
6.4
Energy
Access, demand side
Total
(billion kWh) Hydroelectric
2008
2008
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
423.9
4.0
0.1
0.6
..
..
5.6
..
..
..
..
7.5
0.5
5.8
..
..
0.3
3.8
2.0
..
8.4
..
..
7.1
..
..
..
..
..
..
..
15.1
2.1
..
21.1
..
..
2.4
..
..
..
255.5
4.5
..
4.4
0.1
..
9.7
8.0
236.1
40.2
131.0
28.7
20.8
15.3
17.2
96.3
0.7
0.0
..
..
76.2
..
..
..
..
99.4
81.3
32.7
..
..
0.0
87.3
43.8
..
74.1
..
..
40.4
..
..
..
..
..
..
..
99.9
67.5
..
27.1
..
..
9.5
..
..
..
0.5
32.4
..
60.1
74.0
..
99.7
53.4
6.7
0.7
11.2
0.0
4.5
0.2
Energy production
Sourcea
(% of total)
Coal
Natural gas
2008
2008
58.0
0.0
0.0
100.0
..
..
0.0
..
..
..
..
0.0
0.0
0.0
..
..
0.0
0.0
0.0
..
0.0
..
..
0.0
..
..
..
..
..
..
..
0.0
31.1
..
0.0
..
..
0.0
..
..
..
94.2
0.0
..
2.7
0.0
..
0.0
46.3
5.0
0.0
0.0
0.0
56.2
0.0
4.4
0.0
0.0
0.0
..
..
7.7
..
..
..
..
0.4
18.7
65.1
..
..
0.0
0.0
24.7
..
0.0
..
..
0.0
..
..
..
..
..
..
..
0.1
0.0
..
58.2
..
..
1.7
..
..
..
0.0
0.0
..
36.2
0.0
..
0.0
0.0
66.5
97.3
68.4
41.0
13.8
88.7
Nuclear
2008
Oil
2008
3.1
0.0
0.0
0.0
..
..
0.0
..
..
..
..
0.0
0.0
0.0
..
..
0.0
0.0
0.0
..
0.0
..
..
0.0
..
..
..
..
..
..
..
0.0
0.0
..
0.0
..
..
0.0
..
..
..
5.1
0.0
..
0.0
0.0
..
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
3.8
3.7
99.3
0.0
..
..
15.9
..
..
..
..
0.2
0.0
0.2
..
..
99.3
12.4
31.2
..
25.9
..
..
38.4
..
..
..
..
..
..
..
0.0
1.4
..
14.7
..
..
85.8
..
..
..
0.1
67.6
..
0.9
24.4
..
0.3
0.3
21.3
2.0
19.7
59.0
24.2
10.8
GDP per unit of
Electric power energy use (2005 Solid fuels use
consumption
PPP $ per kg of
(% of
(kWh per capita) oil equivalent)
population)
2008
2008
2006
530.9
189.3
76.3
1,503.3
..
..
262.6
..
..
..
..
95.1
150.2
186.3
..
..
..
42.4
1,158.0
..
267.7
..
..
155.3
..
..
..
..
..
..
..
461.4
1,797.3
..
126.5
..
..
158.2
..
..
..
4,759.5
96.4
..
83.9
98.8
..
602.4
1,022.2
1,281.7
957.1
1,425.4
3,909.3
735.6
1,298.0
3.2
8.8
3.9
11.6
..
..
5.4
..
..
..
..
0.8
9.6
3.1
..
..
3.8
2.0
9.4
..
3.4
..
..
3.1
..
..
..
..
..
..
..
1.9
7.3
..
2.6
..
..
7.1
..
..
..
3.5
5.3
..
2.6
1.9
..
2.1
..
6.4
6.8
5.8
5.2
8.4
8.3
81.6
47.7
94.3
40.0
95.0
95.0
80.6
36.2
95.0
93.0
76.0
95.0
83.9
79.0
16.0
..
62.7
95.0
27.0
94.7
85.9
95.0
95.0
75.0
71.0
95.0
95.0
95.0
95.0
60.0
5.0
95.0
57.0
95.0
78.8
95.0
..
51.0
5.0
95.0
95.0
17.3
89.9
58.0
94.0
95.0
95.0
85.7
71.2
5.4
5.0
5.0
5.0
6.8
5.0
a. Shares may not sum to 100 percent because other sources of generated electricity (such as geothermal, solar, and wind) are not shown.
b. Data are for the most recent year available during the period specified.
80
Part III. Development outcomes
infrastructure
Firms identifying
electricity as major or
very severe obstacle
to business operation
and growth (%)
2009–10 b
Quality
Average delay for
firm in obtaining
Electric power
Electrical power
electrical
transmission and
outages in a
connection
distribution losses
typical month
(days)
(% of output)
(average)
2009–10 b
2008
2009–10 b
35.7
51.9
34.8
53.9
..
58.6
53.1
..
74.6
..
51.7
71.1
39.8
..
..
0.2
..
58.0
..
..
..
..
..
44.3
59.1
54.6
37.6
33.5
..
42.9
..
..
63.2
..
..
..
..
..
53.4
..
..
..
..
..
50.9
..
..
..
7.7
86.8
39.2
23.1
..
17.6
30.5
..
10.6
..
48.0
8.5
20.9
..
..
..
..
34.5
..
..
..
..
..
13.9
..
92.1
59.2
32.9
..
18.7
..
..
37.1
..
..
..
..
..
14.8
..
..
..
..
..
53.9
..
..
..
..
..
..
..
..
..
..
..
..
..
infrastructure
10.5
14.5
92.6
52.0
..
..
9.7
..
..
..
..
11.0
76.8
23.5
..
..
..
9.5
17.8
..
22.1
..
..
14.7
..
..
..
..
..
..
..
9.0
17.6
..
9.4
..
..
19.5
..
..
..
8.8
11.9
..
19.3
122.8
..
23.3
6.5
12.5
18.1
10.6
14.0
11.0
12.4
Firms that
share or own
their
own generator
(%)
2009–10 b
Firms using
electricity from
generator
(%)
2009–10 b
5.4
13.9
4.5
10.8
..
10.6
4.9
..
22.6
..
21.8
25.3
3.8
..
..
3.0
..
7.2
..
..
..
..
..
6.8
5.4
13.6
1.0
5.3
..
3.2
..
..
20.1
..
..
..
..
..
15.9
..
..
..
..
..
11.1
..
..
..
79.0
50.5
34.5
28.3
..
34.8
48.8
..
75.5
..
49.3
81.8
6.5
..
..
36.8
..
22.9
..
..
..
..
..
30.9
66.5
29.3
25.3
20.1
..
24.5
..
..
34.5
..
..
..
..
..
81.8
..
..
..
..
..
63.6
..
..
..
17.3
10.1
0.6
2.5
..
4.5
10.9
..
52.0
..
4.2
43.2
1.0
..
..
1.0
..
1.8
..
..
..
..
..
0.0
63.1
5.2
2.1
0.5
..
0.8
..
..
5.2
..
..
..
..
..
36.6
..
..
..
..
..
9.3
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
Financing
Committed nominal
investment in energy
ODA gross
projects with private
disbursements
participation
for energy
($ millions)
($ millions)
2009
2009
..
..
..
..
..
..
0.0
..
..
..
..
..
..
0.0
..
..
..
4.0
..
..
..
..
..
11.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
27.0
..
..
..
..
..
..
..
..
1,478.9
4.7
16.3
0.3
26.1
1.9
57.3
1.9
3.4
0.8
..
132.8
0.1
15.4
22.5
0.0
3.1
179.0
0.1
1.8
43.9
0.8
3.4
142.9
0.4
13.1
5.8
2.3
20.5
11.2
5.8
57.6
4.5
0.6
72.7
41.9
..
16.5
..
30.1
..
4.8
2.0
..
121.4
121.8
163.0
8.1
1.3
1,106.6
2.2
460.3
2.5
454.7
166.7
Part III. Development outcomes
81
Table
Participating in growth
7.1
Education
Primary education
Literacy rate (%)
Youth (ages 15–24)
Adult (ages 15 and older)
Total
Male
Female
Total
Male
Female
2009
2009
2009
2009
2009
2009
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
82
75.2
73.1
54.3
95.2
..
76.6
..
98.2
64.7
46.3
85.3
67.7
..
66.6
..
97.9
88.7
..
97.6
65.5
80.1
61.1
70.9
92.7
92.0
75.6
..
86.5
..
67.7
96.5
70.9
93.0
..
71.8
77.2
95.3
65.0
..
57.6
..
..
85.9
93.4
77.4
..
..
74.6
98.9
..
..
..
99.9
79.5
..
Part III. Development outcomes
79.5
80.8
64.9
93.7
..
76.9
..
97.3
72.2
53.5
85.8
73.3
..
72.1
..
97.7
91.6
..
98.6
71.0
81.2
68.1
78.2
91.9
85.7
70.4
..
86.9
..
70.9
95.5
78.1
91.1
..
78.1
77.0
94.9
74.2
..
67.6
..
..
89.1
91.9
78.5
..
..
81.8
98.4
..
..
..
99.9
86.7
..
70.9
65.5
43.4
96.7
..
76.3
..
99.0
57.3
39.0
84.7
62.1
..
61.0
..
98.2
85.8
..
96.6
60.0
78.9
53.8
63.6
93.6
98.1
80.9
..
86.0
..
64.3
97.6
63.7
94.9
..
65.3
77.4
95.8
56.2
..
48.1
..
..
82.7
94.9
76.4
..
..
67.3
99.5
..
..
..
99.8
72.1
..
65.5
70.0
41.7
84.1
..
66.6
..
84.8
55.2
33.6
74.2
67.0
..
55.3
..
93.3
66.6
..
87.7
46.5
66.6
39.5
52.2
87.0
89.7
59.1
..
73.7
..
57.5
87.9
55.1
88.5
..
60.8
70.7
88.8
49.7
..
40.9
..
..
70.2
86.9
72.9
..
..
70.9
91.9
..
..
..
88.9
56.1
..
74.8
82.9
54.2
83.8
..
72.6
..
90.1
69.1
44.5
79.7
79.5
..
64.7
..
97.0
77.9
..
91.4
57.6
72.8
50.8
66.9
90.5
82.9
63.7
..
80.6
..
64.5
90.6
70.1
88.9
..
72.0
75.0
93.7
61.8
..
52.7
..
..
79.6
87.8
79.0
..
..
80.6
94.7
..
..
..
95.2
68.9
..
56.3
57.6
29.1
84.4
..
60.9
..
80.2
42.1
23.1
68.7
54.9
..
45.3
..
89.8
56.0
..
84.1
35.8
60.4
28.1
38.0
83.5
95.3
54.5
..
67.0
..
50.3
85.3
41.5
88.1
..
49.8
66.8
84.0
38.7
..
30.1
..
..
60.8
86.2
66.9
..
..
61.3
89.4
..
..
..
82.0
43.9
..
Gross enrollment ratio
(% of relevant age group)
Total
Male
Female
2009
2009
2009
..
..
121.9
..
78.3
146.6
113.8
98.1
88.6
89.7
..
90.3
119.5
73.6
54.5
81.9
48.3
102.5
..
..
105.2
89.8
..
112.7
104.4
..
160.4
119.3
94.7
104.4
100.0
114.4
112.1
62.4
..
150.7
131.2
83.7
106.2
..
..
101.2
74.0
..
104.9
115.2
121.6
112.9
..
..
107.7
..
..
107.4
..
..
..
129.2
..
82.9
149.1
122.0
101.8
103.8
105.2
..
97.5
123.5
81.2
57.6
83.6
52.8
107.1
..
..
105.7
96.7
..
113.9
104.6
..
162.3
117.6
102.9
100.6
100.0
120.7
113.0
69.2
..
149.8
130.7
82.1
105.0
..
..
103.2
77.8
..
104.9
118.8
120.8
113.5
..
..
111.0
..
..
111.9
..
..
..
114.2
107.9
73.5
144.2
105.5
94.4
73.6
74.2
114.1
83.0
115.5
66.0
51.3
80.1
43.8
97.8
133.9
88.6
104.6
82.8
64.8
111.4
104.2
85.6
158.5
121.1
86.3
108.4
100.1
108.1
111.2
55.2
86.8
151.4
131.8
85.4
107.4
148.0
23.1
99.1
70.0
103.8
104.9
111.5
122.4
112.4
103.1
102.7
104.2
97.1
107.5
102.7
105.8
Net enrollment ratio
(% of relevant age group)
Total
Male
Female
2009
2009
2009
..
..
94.7
..
63.3
98.9
91.6
82.6
66.7
..
..
..
..
57.2
44.4
53.5
35.7
82.7
..
..
75.9
72.9
..
82.6
73.1
..
..
90.8
72.9
76.3
94.0
90.6
89.1
54.0
..
..
97.5
73.1
94.4
..
..
84.7
..
..
96.4
93.5
92.2
90.7
..
..
93.8
..
..
89.7
..
..
..
..
..
67.1
98.2
97.5
83.6
76.9
..
..
..
..
62.5
46.8
54.0
38.1
85.2
..
..
75.5
77.9
..
82.2
71.2
..
..
88.5
79.3
73.9
93.4
93.2
87.1
60.0
..
..
95.5
71.7
93.4
..
..
84.7
..
..
95.8
98.1
90.9
89.6
..
..
94.8
..
..
91.2
..
..
..
..
..
59.4
99.6
85.6
81.5
56.6
..
..
..
..
52.0
42.1
53.0
33.2
80.1
..
..
76.2
67.8
..
83.0
75.0
..
..
93.2
66.4
78.8
94.6
87.9
91.1
47.6
..
..
99.5
74.4
95.4
..
..
84.6
..
..
97.0
89.0
93.6
91.8
..
..
92.9
..
..
88.1
..
Studentteacher
ratio
2009
..
..
..
..
48.9
51.4
46.3
23.9
94.6
60.9
..
37.3
64.4
42.1
..
24.2
38.5
57.9
..
..
33.1
..
..
46.8
..
..
47.9
..
50.1
39.1
21.6
61.3
30.1
38.8
..
68.3
26.2
34.7
13.8
..
..
..
38.4
..
53.7
41.3
49.3
..
..
..
23.0
..
..
26.6
..
HuMan developMent
Secondary education
Gross enrollment ratio
Net enrollment ratio
(% of relevant age group)
(% of relevant age group)
Total
Male
Female
Total
Male
Female
2009
2009
2009
2009
2009
2009
..
..
..
..
19.8
21.2
41.5
81.5
13.6
24.1
..
36.7
..
..
30.5
..
31.8
34.4
..
..
57.2
37.0
..
59.5
45.0
..
31.5
29.5
38.3
..
87.2
23.4
..
11.7
..
26.7
50.1
..
105.0
..
..
93.9
38.0
..
27.4
..
27.4
48.7
..
..
..
..
..
..
..
..
..
..
..
22.6
24.6
45.2
74.7
17.5
34.1
..
47.0
..
..
35.1
..
37.1
38.8
..
..
60.5
46.3
..
62.4
37.8
..
32.5
31.5
46.4
..
86.1
26.2
..
14.5
..
27.5
47.3
..
102.6
..
..
91.6
40.3
..
30.7
..
29.8
52.8
..
..
..
..
..
..
..
HuMan developMent
..
..
..
..
16.8
17.8
37.7
88.2
9.8
14.0
..
26.2
..
..
25.8
..
26.4
30.0
..
..
53.6
27.4
..
56.5
52.3
..
30.6
27.6
30.1
..
88.3
20.6
..
8.8
..
26.0
52.8
..
107.5
..
..
96.1
35.5
..
24.1
..
24.9
44.5
..
..
..
..
..
..
..
..
..
..
..
15.4
..
..
63.3
10.4
..
..
..
..
..
..
..
27.4
..
..
..
46.1
..
..
49.6
28.8
..
..
25.0
30.1
..
..
14.7
..
..
..
..
..
..
97.3
..
..
..
..
..
..
..
..
46.2
..
..
..
..
..
..
..
..
..
..
..
17.7
..
..
..
13.2
..
..
..
..
..
..
..
31.6
..
..
..
48.0
..
..
51.1
21.9
..
..
25.7
36.6
..
..
15.6
..
..
..
..
..
..
95.4
..
..
..
..
..
..
..
..
50.5
..
..
..
..
..
..
..
..
..
..
..
13.1
..
..
..
7.7
..
..
..
..
..
..
..
23.1
..
..
..
44.1
..
..
48.1
35.7
..
..
24.4
23.5
..
..
13.7
..
..
..
..
..
..
99.2
..
..
..
..
..
..
..
..
41.8
..
..
..
..
..
..
..
Studentteacher ratio
2009
..
..
..
..
25.6
26.5
..
18.2
80.1
32.3
..
16.0
..
..
..
..
42.7
47.9
..
..
18.3
..
..
29.7
..
..
23.5
..
..
..
16.0
37.9
..
27.6
..
..
..
..
12.6
..
..
..
22.2
..
..
..
18.1
..
..
..
..
..
..
..
..
Tertiary education
Gross enrollment ratio
(% of relevant age group)
Total
Male
Female
2009
2009
2009
..
..
..
..
3.4
2.7
9.0
14.9
2.5
2.0
5.2
6.0
6.4
..
3.5
..
2.0
..
..
..
8.6
..
..
4.1
..
..
3.6
..
6.0
3.8
..
..
..
1.4
..
4.8
4.1
8.0
..
..
..
..
..
..
..
..
4.1
..
3.2
..
30.6
..
..
12.9
..
..
..
..
..
4.6
..
10.1
13.1
3.5
3.4
..
..
10.6
..
4.1
..
3.0
..
..
..
10.6
..
..
4.8
..
..
3.8
..
8.5
5.3
..
..
..
2.2
..
5.5
4.2
10.2
..
..
..
..
..
..
..
..
4.5
..
3.9
..
25.2
..
..
13.7
..
..
..
..
..
2.2
..
8.0
16.7
1.5
0.6
..
..
2.2
..
2.8
..
1.0
..
..
..
6.6
..
..
3.3
..
..
3.4
..
3.5
2.2
..
..
..
0.7
..
4.1
3.9
5.9
..
..
..
..
..
..
..
..
3.6
..
2.5
..
36.3
..
..
12.0
..
Public spending on
education (%)
Share of
government
expenditure Share of GDP
2009
2009
..
..
..
22.0
..
23.4
19.2
15.9
..
12.6
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
22.3
..
11.4
..
..
19.3
..
..
..
..
..
18.1
..
16.9
..
..
..
17.6
15.0
..
..
..
..
..
..
..
..
..
..
..
8.9
..
8.3
3.7
5.9
1.3
3.2
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
3.0
..
4.4
..
3.2
..
..
4.5
..
..
..
5.8
..
4.3
..
5.4
..
..
..
4.6
3.2
..
..
..
..
..
..
..
..
Part III. Development outcomes
83
Table
Participating in growth
7.2
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
84
Total
2009
Male
2009
Female
2009
52.5
47.6
61.8
55.0
53.3
50.9
51.4
71.3
47.3
48.9
65.8
47.8
53.7
58.0
55.7
50.6
59.9
55.7
60.9
56.2
56.8
58.3
48.2
54.9
45.4
58.7
60.8
53.8
48.8
57.0
72.6
48.1
61.6
52.0
48.1
50.6
65.8
55.9
73.7
47.9
50.1
51.6
58.5
46.3
56.3
62.9
53.4
46.3
45.4
71.5
72.6
70.3
74.5
71.6
74.5
51.5
45.6
60.7
55.1
52.0
49.4
50.8
68.7
45.9
47.7
63.6
46.2
52.8
56.7
54.4
49.5
57.6
54.3
59.6
54.6
55.9
56.4
46.7
54.5
45.0
57.3
59.2
52.9
48.1
55.0
69.2
47.4
60.8
51.1
47.6
48.8
63.9
54.4
68.5
46.7
48.7
50.3
57.0
47.1
55.5
61.2
52.8
45.8
45.3
69.7
71.2
68.6
72.0
69.4
72.5
53.6
49.6
63.0
54.8
54.7
52.4
51.9
74.1
48.8
50.2
68.1
49.4
54.7
59.3
57.2
51.8
62.2
57.1
62.1
58.0
57.7
60.4
49.8
55.3
45.7
60.1
62.5
54.7
49.5
59.0
76.2
48.8
62.4
52.9
48.7
52.5
67.7
57.5
79.2
49.2
51.5
53.1
60.1
45.5
57.1
64.6
54.1
46.9
45.6
73.4
74.1
72.2
77.2
73.9
76.5
Part III. Development outcomes
Diseases
Infant mortality Maternal mortality
Under-five
rate
ratio, modeled
mortality rate
(per 1,000
estimate (per
(per 1,000)
live births)
100,000 live births)
2009
2009
2008
130
161
118
57
166
166
154
28
171
209
104
199
128
119
94
145
55
104
69
103
69
142
193
84
84
112
58
110
191
117
17
142
48
160
138
111
78
93
12
192
180
62
108
73
108
98
128
141
90
26
32
21
19
38
21
81
98
75
43
91
101
95
23
112
124
75
126
81
83
75
88
39
67
52
78
47
88
115
55
61
80
41
69
101
74
15
96
34
76
86
70
52
51
11
123
109
43
69
52
68
64
79
86
56
23
29
18
17
33
18
646
610
410
190
560
970
600
94
850
1,200
340
670
580
470
300
280
280
470
260
400
350
680
1,000
530
530
990
440
510
830
550
36
550
180
820
840
540
..
410
..
970
1,200
410
750
420
790
350
430
470
790
92
120
82
64
110
60
Prevalence
of HIV
(% ages
15–49)
2009
Incidence of
tuberculosis (per
100,000 people)
2009
5.4
2.0
1.2
24.8
1.2
3.3
5.3
..
4.7
3.4
0.1
..
3.4
3.4
2.5
5.0
0.8
..
5.2
2.0
1.8
1.3
2.5
6.3
23.6
1.5
0.2
11.0
1.0
0.7
1.0
11.5
13.1
0.8
3.6
2.9
..
0.9
..
1.6
0.7
17.8
1.1
25.9
5.6
3.2
6.5
13.5
14.3
0.1
0.1
0.1
..
0.1
0.1
344
298
93
694
215
348
182
148
327
283
39
372
382
399
620
117
99
359
501
269
201
318
229
305
634
288
261
304
324
330
22
409
727
181
295
376
98
282
31
644
285
971
119
1,257
183
446
293
433
742
43
59
19
40
92
24
Malaria
Clinical
Reported
cases
deaths
reported
c
2009
2009
71,675,530 113,326
2,221,076 10,530
1,256,708
1,375
14,878
6
4,399,837
7,982
1,757,387
714
1,883,199
4,943
65
2
175,210
667
182,415
221
49,679
..
6,749,112 21,168
92,855
116
1,847,367 18,156
7,120
0
78,983
23
21,298
23
3,043,203
1,121
112,840
197
479,409
240
1,899,544
3,378
812,471
586
143,011
369
8,123,689
..
..
..
871,560
1,706
215,110
173
5,455,423
6,527
1,633,423
2,331
167,705
91
..
..
4,310,086
3,747
81,812
46
309,675
2,159
4,295,686
7,522
1,247,583
809
3,893
23
222,232
574
..
..
646,808
1,734
56,153
45
6,072
45
2,686,822
1,396
6,639
13
40
840
618,842
1,556
9,775,318
6,296
2,976,395
3,862
736,897
14
239
3
..
..
94
2
..
..
145
1
..
..
HuMan developMent
Prevention and treatment
Child
immunization
rate (% of
children ages
Malnutrition (% of
12–23 months)
children under age 5)
b
Stunting Underweight
Measles DPT
2009
2009 2007–09a 2007–09a
68
77
72
94
75
91
74
96
62
23
79
76
76
67
73
51
95
75
55
96
93
51
76
74
85
64
64
92
71
59
99
77
76
73
41
92
90
79
97
71
24
62
82
95
91
84
68
85
76
94
88
95
98
98
98
70
73
83
96
82
92
80
99
54
23
83
77
91
81
89
33
99
79
45
98
94
57
68
75
83
64
78
93
74
64
99
76
83
70
42
97
98
86
99
75
31
69
84
95
85
89
64
81
73
97
93
97
98
99
99
Contraceptive use
(% of married women
ages 15–49)
Births
attended
by skilled
health staff
(% of total)
2007–09a
Any
method
2007–09a
Modern
method
2007–09a
Children sleeping
under insecticidetreated nets
(% of under age 5)
2007–09a
Tuberculosis
case detection
rate, all forms
(%)
2009
Tuberculosis
treatment
success rate (% of
registered cases)
2008
79.0
70.0
89.0
65.0
76.0
90.0
..
74.0
71.0
..
90.0
87.0
76.0
76.0
84.0
56.0
76.0
84.0
53.0
84.0
86.0
78.0
70.0
85.0
73.0
79.0
81.0
87.0
82.0
68.0
87.0
84.0
82.0
81.0
78.0
87.0
94.0
84.0
100.0
86.0
81.0
76.0
81.0
68.0
88.0
79.0
70.0
88.0
74.0
..
90.0
89.0
69.0
85.0
86.0
..
..
..
35.1
..
..
..
..
..
..
45.8
..
..
..
..
..
..
..
..
28.6
40.0
..
35.2
..
39.4
49.2
..
..
24.2
..
..
29.6
..
41.0
..
29.3
..
..
37.4
..
..
..
29.5
..
..
..
45.8
..
..
..
..
26.0
..
..
..
..
..
..
28.2
..
..
..
..
..
..
..
..
14.3
20.8
..
16.4
..
20.4
..
..
..
16.7
..
..
17.5
..
26.7
..
13.1
..
..
21.3
..
..
..
6.1
..
..
..
14.9
..
47.3
..
94.6
..
..
..
..
43.7
..
..
74.0
..
..
..
..
..
..
..
..
57.1
46.1
..
43.8
61.5
46.3
43.9
..
..
60.9
..
55.3
81.4
..
38.9
52.1
81.7
..
..
42.4
..
..
..
69.0
..
..
..
46.5
60.2
..
..
52.8
..
..
..
..
..
..
..
20.6
..
..
22.5
..
..
..
..
..
23.5
..
..
45.5
47.0
11.4
39.9
..
..
9.3
..
16.2
55.1
..
14.6
36.4
38.4
..
..
8.2
..
..
..
50.6
..
..
..
40.8
64.9
..
..
..
..
..
..
..
..
..
..
5.8
..
..
..
..
..
..
..
..
16.6
..
..
38.9
..
10.3
28.2
..
..
8.0
..
..
53.5
..
8.1
26.1
..
..
..
6.0
..
..
..
46.8
..
..
..
26.5
..
..
17.7
..
..
..
..
..
..
..
..
..
5.8
..
..
19.9
..
..
33.1
..
..
28.2
4.5
..
46.1
..
26.4
45.8
..
..
..
..
22.8
..
42.8
5.5
55.7
56.2
29.2
..
25.8
..
..
..
0.6
25.7
..
..
41.1
17.3
48.0
75.0
47.0
62.0
14.0
25.0
70.0
44.0
60.0
26.0
46.0
46.0
69.0
27.0
71.0
89.0
58.0
50.0
42.0
47.0
31.0
26.0
59.0
85.0
93.0
52.0
44.0
49.0
16.0
24.0
41.0
46.0
76.0
36.0
19.0
19.0
49.0
31.0
57.0
31.0
42.0
74.0
52.0
67.0
77.0
10.0
44.0
80.0
46.0
..
30.7
21.0
..
..
..
6.8
5.6
..
..
..
78.9
..
..
..
..
60.3
..
..
..
..
57.6
..
..
..
..
..
..
..
..
100.0
63.0
82.0
93.0
86.0
Children with fever
receiving any
antimalarial treatment
same or next day
(% of under age 5)
2007–09a
29.3
..
..
..
..
..
..
..
..
..
29.8
..
..
..
..
..
9.5
..
..
43.0
..
..
23.2
..
67.2
19.7
..
..
20.7
..
36.7
..
..
33.2
5.6
8.4
9.1
..
30.1
..
..
..
0.6
56.7
..
..
43.3
23.6
..
..
..
..
..
(continued)
HuMan developMent
Part III. Development outcomes
85
Table
Participating in growth
7.2
Health (continued)
Water and sanitation
Population with sustainable access
Population with sustainable access
to an improved water source
to improved sanitation
(% of total
(% of urban
(% of rural
(% of total
(% of urban
(% of rural
population)
population)
population)
population)
population)
population)
2008
2008
2008
2008
2008
2008
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
60
50
75
95
76
72
74
84
67
50
95
46
71
80
92
..
61
38
87
92
82
71
61
59
85
68
41
80
56
49
99
47
92
48
58
65
89
69
..
49
30
91
57
69
54
60
67
60
82
92
83
99
..
81
94
83
60
84
99
95
83
92
85
92
67
91
80
95
93
98
..
74
98
95
96
90
89
83
83
97
79
71
95
81
52
100
77
99
96
75
77
89
92
100
86
67
99
64
92
80
87
91
87
99
95
85
100
..
98
99
47
38
69
90
72
71
51
82
51
44
97
28
34
68
52
..
57
26
41
86
74
61
51
52
81
51
29
77
44
47
99
29
88
39
42
62
88
52
..
26
9
78
52
61
45
41
64
46
72
87
79
98
..
60
84
31
57
12
60
11
46
47
54
34
9
36
23
30
23
56
..
14
12
33
67
13
19
21
31
29
17
11
56
36
26
91
17
33
9
32
54
26
51
..
13
23
77
34
55
24
12
48
49
44
89
95
94
97
69
85
44
86
24
74
33
49
56
65
43
23
50
23
31
36
63
..
52
29
33
68
18
34
49
27
40
25
15
51
45
50
93
38
60
34
36
50
30
69
97
24
52
84
55
61
32
24
38
59
56
94
98
97
97
83
96
24
18
4
39
6
46
35
38
28
4
30
23
29
11
10
..
4
8
30
65
7
11
9
32
25
4
10
57
32
9
90
4
17
4
28
55
19
38
..
6
6
65
18
53
21
3
49
43
37
83
88
92
96
52
64
Human resources
Health workers
(per 1,000 people)
Nurses and
Community
Physicians
midwives
workers
a
a
2008–09
2008–09
2008
..
0.1
..
0.1
..
..
0.6
..
..
..
..
..
0.1
..
..
..
..
..
0.0
0.1
..
0.0
..
..
0.0
..
0.0
0.0
0.1
..
..
..
0.0
0.4
..
..
0.1
..
0.0
..
..
0.3
..
..
0.1
..
..
..
..
0.8
..
0.7
..
..
1.3
..
..
..
..
..
0.5
0.8
..
..
..
..
0.6
1.1
..
0.6
..
..
0.3
..
0.3
0.3
0.7
..
..
..
0.1
1.6
..
..
0.4
..
0.2
..
..
0.8
..
..
0.3
..
..
..
..
2.8
1.9
0.6
1.2
..
3.5
6.8
0.9
3.3
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
0.1
0.2
..
..
..
..
..
..
0.7
..
..
..
..
..
..
0.1
..
..
..
..
0.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
a. Data are for the most recent year available during the period specified.
b. Diphtheria, pertussis, and tetanus toxoid.
c. Malaria cases reported before 2000 can be probable and confirmed or only confirmed, depending on the country.
86
Part III. Development outcomes
HuMan developMent
Health expenditure
Share of GDP (%)
Share of total health expenditure (%)
Total
2009
Public
2009
Private
2009
Public
2009
Private
2009
External resources
for health
2009
Out-of-pocket
(% of private
expenditure
on health)
2009
6.6
4.6
4.2
10.3
6.4
13.1
5.6
3.9
4.3
7.0
3.4
9.5
3.0
5.1
7.0
3.9
2.2
4.3
3.5
6.0
6.9
5.7
6.1
4.3
8.2
13.2
4.1
6.2
5.6
2.5
5.7
5.7
5.9
6.1
5.8
9.0
7.1
5.7
4.0
13.1
..
8.5
7.3
6.3
5.1
5.9
8.2
4.8
..
5.3
5.8
5.0
3.9
5.5
6.2
2.9
4.1
2.3
8.2
3.9
6.0
1.6
2.9
1.6
3.9
2.1
4.9
1.6
1.0
5.3
3.4
1.0
2.0
1.7
3.0
3.1
0.9
1.6
1.5
5.6
5.3
2.8
3.6
2.7
1.6
2.1
4.1
4.0
3.5
2.1
3.9
2.9
3.1
3.1
0.9
..
3.4
2.0
4.0
3.8
1.7
1.6
2.5
..
3.0
5.0
2.1
2.6
1.9
3.4
3.7
0.5
1.9
2.1
2.4
7.1
4.0
1.0
2.6
3.1
1.3
4.7
1.4
4.1
1.6
0.5
1.2
2.2
1.8
3.0
3.8
4.9
4.5
2.9
2.6
8.0
1.4
2.6
2.9
0.9
3.6
1.5
2.0
2.6
3.7
5.1
4.2
2.5
0.9
12.2
..
5.1
5.3
2.3
1.4
4.2
6.7
2.2
..
2.3
0.8
2.9
1.3
3.6
2.9
44.0
89.0
55.2
80.0
61.7
46.0
27.9
74.0
38.7
55.2
61.6
51.0
53.8
18.8
76.9
86.9
44.6
47.6
47.9
50.1
45.0
15.2
25.5
33.8
68.2
39.7
67.1
58.0
47.9
62.6
36.9
73.2
66.6
57.6
36.3
43.2
41.0
55.6
76.8
7.2
..
40.1
27.4
63.3
73.6
28.2
19.0
53.0
..
56.8
86.2
41.7
66.1
34.4
54.0
56.0
11.0
44.8
20.0
38.3
54.0
72.1
26.0
61.3
44.8
38.4
49.0
46.2
81.2
23.1
13.1
55.4
52.4
52.1
49.9
55.0
84.8
74.5
66.2
31.8
60.3
32.9
42.0
52.1
37.4
63.1
26.8
33.4
42.4
63.7
56.8
59.0
44.4
23.2
92.8
..
59.9
72.6
36.7
26.4
71.8
81.0
47.0
..
43.2
13.8
58.3
33.9
65.6
46.0
..
2.7
22.6
18.8
21.9
45.2
8.1
7.4
40.4
6.9
15.3
35.8
7.2
10.6
30.2
3.2
65.6
39.5
1.7
26.3
16.8
15.6
42.0
36.1
30.4
47.0
28.3
99.1
25.6
25.6
1.6
72.0
14.9
32.6
4.9
53.2
38.7
14.0
1.4
20.4
..
1.9
3.2
12.2
56.5
17.4
20.9
50.3
..
..
0.0
1.5
1.0
0.2
1.2
62.9
100.0
92.7
34.0
93.0
66.1
94.9
99.7
95.0
96.7
100.0
76.2
100.0
98.8
98.6
83.5
100.0
80.1
100.0
48.5
78.6
99.4
56.0
77.4
68.9
52.2
67.8
28.5
99.5
100.0
88.7
43.6
17.8
96.2
95.6
44.4
68.5
78.5
30.9
89.5
..
29.6
96.2
42.3
65.1
84.2
65.4
74.5
..
93.4
94.7
97.7
100.0
86.3
87.0
HuMan developMent
Private prepaid
plans
(% of private
expenditure
Health expenditure
on health)
per capita ($)
2009
2009
..
0.0
7.3
6.5
3.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.2
1.4
0.0
0.0
1.5
0.0
3.1
6.2
0.0
0.0
8.8
0.0
0.0
15.1
14.5
0.5
0.0
6.3
1.5
61.0
3.2
3.1
10.2
0.0
17.9
0.0
1.0
..
66.1
1.0
18.9
14.5
4.3
0.0
4.1
..
..
5.1
1.7
0.0
13.7
11.2
76.0
203.8
31.9
611.9
38.1
19.8
61.1
146.1
19.3
41.8
27.8
15.6
70.1
55.3
84.5
709.4
10.1
14.7
266.3
25.6
45.1
18.8
18.4
33.2
70.0
29.4
18.0
19.1
38.4
21.9
383.1
24.7
258.0
20.9
69.3
48.2
90.7
58.9
365.7
43.9
..
485.4
94.6
155.8
25.3
28.9
42.5
47.1
..
173.4
267.9
113.3
416.7
155.7
240.0
Part III. Development outcomes
87
Table
Participating in growth
8.1
Rural development
Rural population (%)
SUB–SAHARAN AFRICA
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Cape Verde
Central African Republic
Chad
Comoros
Congo, Dem. Rep.
Congo, Rep.
Côte d’Ivoire
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
1990
Share of total population
2008
2009
1990
Annual growth
2008
2009
71.8
62.9
65.5
58.1
86.2
93.7
59.3
55.9
63.2
79.2
72.1
72.2
45.7
60.3
24.3
65.3
84.2
87.4
30.9
61.7
63.6
72.0
71.9
81.8
86.0
54.7
76.4
88.4
76.7
60.3
56.1
78.9
72.3
84.6
64.7
94.6
56.4
61.0
50.7
67.1
70.3
48.0
73.4
77.1
81.1
69.9
88.9
60.6
71.0
51.5
47.9
56.5
24.3
51.6
42.1
63.5
43.3
58.8
40.4
80.4
89.6
43.2
40.4
61.4
73.3
71.9
66.0
38.7
51.2
12.7
60.6
79.3
83.0
15.0
43.6
50.0
65.6
70.2
78.4
74.5
39.9
70.5
81.2
67.8
59.0
57.5
63.2
63.2
83.5
51.6
81.7
39.4
57.6
45.7
62.2
63.5
39.3
56.6
75.1
74.5
58.0
87.0
64.6
62.7
47.2
34.8
57.3
22.5
44.0
33.5
63.0
42.4
58.4
39.7
80.0
89.3
42.4
39.6
61.3
72.9
71.9
65.4
38.3
50.6
12.3
60.5
78.8
82.7
14.5
42.7
49.2
65.1
70.1
78.1
73.8
39.2
70.1
80.7
67.3
58.8
57.5
62.4
62.6
83.4
50.9
81.4
38.6
57.4
45.2
61.9
63.0
38.8
55.7
74.8
74.0
57.3
86.9
64.4
62.2
46.9
34.1
57.2
22.3
43.6
33.1
2.2
0.7
2.2
–2.1
2.4
2.3
1.5
–2.2
1.9
2.9
2.0
3.7
1.9
3.1
4.1
1.9
1.3
3.1
–1.0
2.3
1.7
3.2
0.8
3.1
1.0
–3.8
2.2
3.5
1.4
1.0
0.2
0.2
3.4
2.8
1.6
–0.4
0.2
2.4
0.9
0.9
0.0
1.0
1.2
3.2
2.7
1.9
3.2
3.1
1.9
1.7
0.8
2.5
2.0
0.5
0.5
1.7
0.6
2.5
–0.4
2.9
2.6
0.4
–0.4
1.6
2.1
2.3
1.8
0.8
1.0
–1.3
2.3
2.4
2.2
–1.3
0.8
0.6
1.5
2.1
2.3
–0.1
2.8
2.2
2.2
1.5
2.1
0.5
1.1
1.0
3.8
1.0
2.4
–0.5
2.2
1.2
2.0
1.5
–0.1
0.7
1.0
2.3
1.3
3.1
2.2
–0.7
1.1
–0.3
1.7
1.2
0.4
–0.2
1.7
0.5
2.4
–0.4
2.9
2.5
0.3
–0.5
1.6
2.0
2.3
1.8
0.9
1.0
–1.5
2.3
2.4
2.2
–1.5
0.7
0.6
1.6
2.1
2.3
–0.1
2.5
2.2
2.2
1.5
2.0
0.4
1.0
1.0
3.8
0.9
2.5
–0.5
2.2
0.1
1.9
1.6
–0.2
0.6
1.1
2.3
1.2
3.1
2.2
–0.3
1.1
–0.3
1.7
1.2
0.4
–0.2
Rural population density
(rural population per
sq km of arable land)
1990
2008
286.0
231.2
194.5
187.0
215.8
572.4
122.1
483.0
96.4
147.7
402.4
400.7
233.4
312.9
13,614.8
190.5
..
..
97.0
303.6
352.6
547.8
294.0
384.1
434.7
338.7
316.6
371.3
323.3
299.7
593.0
309.7
155.2
60.6
213.2
768.7
3,274.5
148.7
3,549.0
563.8
453.7
125.7
155.4
370.2
229.4
130.7
315.3
209.1
257.0
823.3
171.0
1,429.4
58.8
147.0
118.0
358.0
229.5
199.7
310.6
194.5
803.8
138.4
309.8
138.1
186.1
578.6
633.4
285.2
376.7
10,785.4
305.0
583.0
492.4
66.7
185.5
265.2
268.6
368.4
573.4
430.3
378.0
456.6
344.4
177.7
474.2
838.9
314.2
168.2
84.7
208.2
615.3
701.9
201.0
3,970.4
192.8
566.6
131.8
113.0
492.5
329.6
152.3
487.6
346.1
209.4
1,078.3
159.6
1,684.1
80.8
172.6
122.0
a. Data are for the most recent year available during the period specified.
88
Part III. Development outcomes
aGriculture, rural developMent, and environMent
Share of rural population
below the national poverty line
Surveys
1990–99a
Year
..
..
1999
1993
1998
1998
1996
..
1992
1995
1995
..
..
1998
..
..
..
1999
..
1998
1998
1994
..
1997
1994
..
1999
1998
..
1996
..
1996
1993
1993
1996
..
..
1994
..
1990
..
..
..
..
1992
..
1997
1998
1995
..
1995
..
..
1999
..
Rural population poverty gap at national poverty line
(%)
Surveys 2000–09a
Percent
..
..
33.0
55.0
50.7
83.2
59.6
..
74.4
48.6
69.4
..
..
41.5
..
..
..
45.4
..
79.0
49.6
82.1
..
52.9
68.9
..
76.7
66.5
..
68.1
..
71.3
69.0
66.0
69.8
..
..
71.0
..
88.3
..
..
..
..
40.8
..
48.7
83.0
44.0
..
30.3
..
..
24.2
..
Year
..
..
2003
2003
2003
2006
2007
2007
2008
2003
2004
2005
2005
2008
..
..
..
2004
2005
2003
2006
2007
2002
2005
2003
2007
2005
2004
2006
2000
..
2008
2003
2007
2004
2006
2001
2005
..
2003
..
..
..
2001
2007
2006
2009
2006
..
..
..
2008
..
2007
..
Percent
..
..
46.0
44.8
52.4
68.9
55.0
44.3
69.4
58.6
48.7
75.7
57.7
54.2
..
..
..
39.3
44.6
67.8
39.2
63.0
69.1
49.1
60.5
67.7
73.5
55.9
57.6
61.2
..
56.9
49.0
63.9
63.8
64.2
64.9
61.9
..
78.5
..
..
..
75.0
37.4
74.3
27.2
76.8
..
..
..
30.0
..
14.5
..
aGriculture, rural developMent, and environMent
Surveys
2000–07a
Surveys 1990–99a
Year
..
..
1999
..
1998
1998
..
..
1992
1995
..
..
..
1998
..
..
..
1999
..
..
1998
1994
..
1997
1993
..
1999
1998
..
..
..
1996
1993
1993
1992
..
..
1994
..
1990
..
..
..
..
1992
..
1997
1998
..
..
1995
..
..
..
..
Percent
..
..
9.4
..
15.7
45.9
..
..
42.5
26.3
..
..
..
14.3
..
..
..
12.2
..
..
18.2
39.1
..
19.3
26.5
..
21.4
23.9
..
..
..
29.9
34.0
22.5
16.1
..
..
25.3
..
73.1
..
..
..
..
12.7
..
15.2
44.5
..
..
4.5
..
..
..
..
Year
..
..
2003
2003
2003
2006
2007
2007
2008
2003
2004
2005
2005
2008
..
..
..
2004
2005
2003
2006
2007
2002
2005
..
2007
2005
2004
..
2000
..
2008
2003
2007
2004
2006
2001
2005
..
2003
..
..
..
2001
2007
2006
2009
2006
..
..
..
..
..
..
..
Percent
..
..
14.0
18.4
17.6
24.2
17.5
14.3
35.0
23.3
17.8
34.9
20.6
20.3
..
..
..
8.5
16.0
30.5
13.5
22.0
27.8
17.5
..
26.3
28.9
8.6
..
24.1
..
22.2
16.0
21.2
26.6
26.0
24.7
21.5
..
34.6
..
..
..
37.0
11.0
29.3
7.6
38.8
..
..
..
..
..
..
..
Share of rural population with
sustainable access
(%)
To improved
To an improved
sanitation
water source
facilities
2008
2008
46.8
38.0
69.0
90.0
72.0
71.0
51.0
82.0
51.0
44.0
97.0
28.0
34.0
68.0
52.0
..
57.0
26.0
41.0
86.0
74.0
61.0
51.0
52.0
81.0
51.0
29.0
77.0
44.0
47.0
99.0
29.0
88.0
39.0
42.0
62.0
88.0
52.0
..
26.0
9.0
78.0
52.0
61.0
45.0
41.0
64.0
46.0
72.0
87.4
79.0
98.0
..
60.0
84.0
24.1
18.0
4.0
39.0
6.0
46.0
35.0
38.0
28.0
4.0
30.0
23.0
29.0
11.0
10.0
..
4.0
8.0
30.0
65.0
7.0
11.0
9.0
32.0
25.0
4.0
10.0
57.0
32.0
9.0
90.0
4.0
17.0
4.0
28.0
55.0
19.0
38.0
..
6.0
6.0
65.0
18.0
53.0
21.0
3.0
49.0
43.0
37.0
83.0
88.0
92.0
96.0
52.0
64.0
Part III. Development outcomes
89
Table
Participating in growth
8.2
Agriculture
Agriculture
Gross production index (1999–2001=100)
value
added Agriculture
(% of GDP)
total
Crop Livestock Food
Cereal
2009
2009
2009
2009
2009
2009a
SUB–SAHARAN AFRICA
Angola
Excluding
South Africa
Benin S. Africa & Nigeria
Excl.
Botswana
Angola
Burkina
Benin Faso
Burundi
Botswana
Cameroon
Burkina Faso
Cape
Verde
Burundi
Central
African Republic
Cameroon
Chad
Cape Verde
Comoros
Central African Republic
Congo,
Chad Dem. Rep.
Congo,
Rep.
Comoros
Côte
d’Ivoire
Congo,
Dem. Rep.
Djibouti
Congo, Rep.
Equatorial
Guinea
Côte d’Ivoire
Eritrea
Djibouti
Ethiopia
Equatorial Guinea
Gabon
Eritrea
Gambia,
Ethiopia The
Ghana
Gabon
Guinea
Gambia, The
Guinea-Bissau
Ghana
Kenya
Guinea
Lesotho
Guinea-Bissau
Liberia
Kenya
Madagascar
Lesotho
Malawi
Liberia
Mali
Madagascar
Mauritania
Malawi
Mauritius
Mali
Mozambique
Mauritania
Namibia
Mauritius
Niger
Mozambique
Nigeria
Namibia
Rwanda
Niger
São Tomé and Príncipe
Nigeria
Senegal
Rwanda
Seychelles
São
Tomé and Principe
Sierra Leone
Senegal
Somalia
Seychelles
South Leone
Africa
Sierra
Sudan
Somalia
Swaziland
South
Africa
Tanzania
Sudan
Togo
Swaziland
Uganda
Tanzania
Zambia
Togo
Zimbabwe
Uganda
NORTH AFRICA
Zambia
Algeria
Zimbabwe
Egypt, Arab
Rep.
NORTH
AFRICA
Libya
Algeria
Morocco
Egypt,
Arab Rep.
Tunisia
Libya
Morocco
Tunisia
ALL AFRICA
13.1
10.2
..
3.1
..
..
..
9.2
55.5
..
46.3
42.9
4.5
24.4
..
3.5
14.4
50.7
5.1
27.5
31.7
17.2
..
22.6
8.4
..
29.1
30.5
..
20.6
4.3
31.5
9.4
..
..
34.2
..
16.6
2
51.4
..
3
29.7
7.3
28.8
..
24.7
21.6
17.9
13.1
11.7
13.7
..
16.4
7.8
..
196.0
112.0
113.0
140.0
109.0
114.0
118.0
119.0
118.0
112.0
97.0
124.0
110.0
147.0
91.0
126.0
149.0
103.0
118.0
154.0
130.0
123.0
124.0
75.0
117.0
113.0
136.0
157.0
116.0
105.0
123.0
102.0
185.0
134.0
135.0
111.0
133.0
39.0
197.0
104.0
120.0
118.0
110.0
135.0
113.0
112.0
144.0
70.0
128.7
250.0
110.0
120.0
144.0
108.0
117.0
107.0
110.0
118.0
113.0
97.0
116.0
109.0
101.0
90.0
154.0
153.0
104.0
114.0
156.0
133.0
120.0
107.0
72.0
115.0
115.0
141.0
162.0
116.0
95.0
130.0
140.0
210.0
134.0
132.0
110.0
130.0
61.0
204.0
96.0
111.0
112.0
101.0
154.0
109.0
109.0
170.0
55.0
125.1
92.0
135.0
112.0
132.0
118.0
105.0
141.0
132.0
120.0
103.0
96.0
157.0
132.0
158.0
104.0
101.0
140.0
100.0
132.0
127.0
167.0
128.0
147.0
78.0
127.0
111.0
153.0
153.0
115.0
138.0
89.0
90.0
153.0
121.0
158.0
125.0
144.0
44.0
144.0
105.0
130.0
123.0
140.0
104.0
137.0
120.0
106.0
107.0
130
198.0
116.0
113.0
136.0
110.0
120.0
118.0
123.0
125.0
112.0
98.0
123.0
120.0
147.0
89.0
126.0
151.0
103.0
117.0
155.0
133.0
122.0
126.0
72.0
131.0
114.0
129.0
183.0
116.0
106.0
102.0
101.0
186.0
135.0
134.0
111.0
134.0
38.0
201.0
104.0
122.0
119.0
115.0
134.0
132.0
112.0
135.0
82.0
..
174.0
136.0
182.0
158.0
114.0
148.0
43.0
148.0
172.0
115.0
97.0
183.0
113.0
90.0
..
237.0
170.0
127.0
177.0
156.0
169.0
146.0
94.0
37.0
169.0
120.0
120.0
240.0
129.0
182.0
94.0
134.0
175.0
142.0
191.0
145.0
175.0
..
406.0
54.0
122.0
144.0
24.0
154.0
120.0
131.0
208.0
30.0
163.0
137.0
109.0
139.0
115.0
196.0
136.0
102.0
142.0
119.0
121.0
134.0
116.0
128.0
110.0
163.0
139.0
109.0
140.0
115.0
279.0
125.0
93.0
163.0
84.0
Cereal
(thousands of metric tons)
Production Exports Imports
2009
2008
2008
116,492
1,030
1,508
56
3,627
300
2,017
7
251
2,193
26
1,573
23
1,471
0
..
227
15,502
47
311
2,607
2,659
215
2,804
75
293
4,388
3,993
6,335
213
1
1,785
112
3,451
20,983
651
4
1,869
..
868
215
14,577
5,552
61
5,683
1,004
2,811
2,198
919
42,172
5,253
23,697
207
10,430
2,585
2,199
1
5
2
11
0
0
1
0
0
0
5
0
38
0
..
1
2
0
0
0
15
0
30
0
0
3
31
4
..
18
30
3
30
5
8
..
37
0
0
0
1,279
170
1
136
19
73
238
1
400
1
258
1
95
45
21,901
734
226
177
205
29
551
103
31
147
47
902
175
1,090
201
30
119
1,424
135
169
825
324
32
1,100
259
262
276
259
252
438
282
610
371
320
1,364
56
14
1,533
19
214
452
2,302
1,664
182
546
307
439
48
652
32,879
9,093
12,324
2,276
6,127
3,059
Trade
Agricultural
Food
Exports
Imports
Exports
Imports
($ millions) ($ millions) ($ millions) ($ millions)
2008
2008
2008
2008
25,448
12
450
150
273
57
962
1
23
87
8
57
67
4,361
38
3
2
1,352
81
16
1,532
58
96
2,669
1
97
193
768
351
24
372
330
235
97
856
235
5
252
4
26
58
5,461
457
256
954
301
878
348
534
5,382
76
1,823
8
1,919
1,555
32,546
2,375
791
609
294
49
624
194
33
143
55
959
469
1,224
432
85
66
1,347
391
111
1,311
264
67
1,344
138
217
401
266
416
470
746
616
367
335
3,400
123
28
1,793
90
211
518
4,896
1,543
224
643
326
629
284
627
26,427
7,785
8,661
2,266
5,157
2,557
15,199
10
300
115
67
2
681
1
16
54
8
11
23
3,382
37
3
2
576
3
15
1,482
28
96
737
1
10
150
103
144
18
326
181
190
87
696
19
5
133
2
23
53
3,741
319
242
361
247
198
190
111
4,668
61
1,499
1
1,718
1,389
26,522
1,824
745
467
228
44
541
190
27
111
51
830
413
1,036
383
53
65
1,131
322
89
1,214
220
52
1,175
112
196
331
177
341
424
562
526
229
282
2,991
105
23
1,633
77
189
385
3,204
1,290
184
555
279
537
208
475
23,107
7,015
7,754
2,091
4,140
2,107
Note:
90
Part III. Development outcomes
aGriculture, rural developMent, and environMent
Share of land area (%)
Permanent cropland
2009
Cereal
cropland
2009
1.0
0.2
2.7
0.0
0.2
15.2
2.5
0.7
0.1
0.0
29.6
0.3
0.2
13.4
..
2.7
0.0
0.9
0.6
0.5
12.5
2.8
8.9
0.9
0.1
2.3
1.0
1.3
0.1
0.0
2.0
0.3
0.0
0.0
3.3
11.3
46.9
0.3
6.5
1.9
0.0
0.8
0.1
0.8
1.5
3.1
11.4
0.0
0.3
0.9
0.4
0.8
0.2
2.1
14.2
3.8
1.4
9.6
0.2
13.2
8.8
2.8
8.2
0.4
2.0
12.9
0.9
0.1
2.4
0.0
..
4.5
9.2
0.1
29.6
6.9
8.1
5.3
4.1
5.9
1.9
2.9
19.6
3.3
0.2
0.0
2.6
0.4
7.2
15.1
14.4
1.1
8.6
..
8.6
0.9
2.7
4.0
3.1
5.8
13.2
9.3
1.4
5.3
2.4
1.3
3.1
0.2
12.2
9.2
Agricultural
irrigated land
(% of
agricultural land)
2000–08 b
..
..
0.0
..
..
..
..
..
..
..
..
..
..
..
..
..
0.5
..
..
..
..
..
0.1
..
..
2.2
..
..
..
21.4
..
..
..
..
..
..
0.7
..
..
..
..
1.3
..
..
..
..
..
..
2.1
..
..
4.4
4.0
Fertilizer
consumption
(100 grams
per hectare of
arable land)
2008
11.6
8.3
0.0
..
3.9
2.2
8.6
..
..
..
..
0.9
1.1
18.9
..
..
0.0
7.7
14.1
2.6
6.4
1.5
..
33.3
..
..
4.3
1.7
9.0
..
210.1
0.0
0.3
0.4
13.3
8.3
..
2.4
29.0
..
..
49.7
3.6
..
5.9
4.9
3.4
50.1
27.9
..
6.8
723.6
27.3
53.8
32.1
Agricultural
machinery
(tractors per 100 sq
km of arable land)
2000–08 b
Agricultural
employment
(% of total
employment)
2000–08 b
..
..
134.8
..
..
..
11.2
..
..
..
..
..
32.1
46.2
..
8.3
..
..
..
4.5
39.3
..
25.2
..
..
1.9
..
2.7
9.8
..
..
..
..
6.6
0.5
..
2.1
..
..
12.0
43.0
12.4
87.1
23.3
0.5
..
..
..
..
..
..
..
..
..
11.2
..
..
..
..
..
32.1
46.2
..
8.3
..
..
..
4.5
39.3
..
25.2
..
..
1.9
..
2.7
9.8
..
..
..
..
6.6
0.5
..
2.1
..
..
12.0
43.0
12.4
87.1
23.3
0.5
..
..
..
139.6
372.1
218.9
..
142.6
139.6
372.1
218.9
..
142.6
Agriculture value
added per worker
(2000 $)
2009
Cereal yield
(kilograms per
hectare)
2009
318.3
313.1
..
597.1
..
..
..
2,224.8
..
..
452.9
167.9
..
925.6
..
1,004.8
66.1
214.7
1,869.3
275.3
..
225.4
..
334.2
207.0
..
192.2
161.7
..
407.5
5,555.9
219.7
1,638.1
..
..
..
..
245.4
724.9
..
..
3,640.8
922.3
1,176.0
283.0
..
202.9
215.7
141.4
2,929.4
2,183.7
3,024.2
..
3,306.3
3,602.4
1,296.9
587.7
1,423.5
569.4
1,002.0
1,319.4
1,524.0
223.6
948.3
879.9
1,063.9
788.5
861.5
1,899.7
1,111.1
..
500.0
1,676.8
2,388.8
1,049.3
1,659.8
1,339.2
1,444.5
1,203.8
421.0
1,609.7
2,581.7
2,162.8
1,588.2
875.8
8,306.9
876.6
364.7
379.8
1,528.0
1,828.7
4,056.2
1,134.5
..
1,402.3
371.4
4,414.2
587.2
1,147.5
1,109.5
1,398.4
1,539.4
2,066.9
449.6
3,111.3
1,653.9
7,571.4
568.8
1,910.7
1,812.9
a. Provisional.
b. Data are for the most recent year available during the period specified.
aGriculture, rural developMent, and environMent
Part III. Development outcomes
91
Table
Participating in growth
8.3
Producer food prices
1991
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
92
Rice, paddy
(current $ per metric ton)
1995
2000
2005
2008
1991
Maize
(current $ per metric ton)
1995
2000
2005
2008
..
..
..
351.5
220.4
177.2
..
..
..
..
..
265.9
212.7
..
..
..
..
..
170.4
416.9
220.2
..
72.7
..
..
119.9
139.1
223.3
..
..
181.1
..
260.4
761.3
199.7
..
..
..
..
..
..
962.2
..
..
283.6
..
..
215.4
..
..
..
245.6
272.3
136.2
..
..
..
..
..
150.3
220.4
..
..
..
260.8
..
206.2
393.3
245.1
..
107.2
..
..
170.0
117.8
236.4
..
..
135.8
..
214.4
652.2
873.4
..
..
..
..
..
..
205.2
..
..
232.4
..
..
288.5
..
..
..
119.4
277.5
144.6
..
..
..
..
..
178.4
154.5
..
..
..
201.6
..
136.9
306.6
405.5
351.1
299.9
..
..
190.6
594.4
154.5
..
..
90.6
..
154.5
279.4
582.1
..
..
..
..
..
..
388.9
..
..
165.7
..
..
255.1
..
..
..
392.2
609.2
269.1
..
..
..
..
..
220.1
222.2
..
..
..
127.7
..
175.0
577.8
138.2
474.8
378.8
..
..
125.9
718.5
269.7
..
..
163.3
..
201.0
545.1
480.2
..
..
..
..
..
..
497.3
..
..
258.3
..
..
346.4
..
..
..
559.8
814.9
337.2
..
..
..
..
..
362.9
506.4
..
..
..
734.4
..
258.3
826.0
128.8
893.2
627.5
..
..
314.9
1,060.8
264.5
..
..
..
..
260.2
519.4
659.2
..
..
..
..
..
..
125,651.2
..
..
375.2
..
..
..
..
..
..
212.7
270.0
283.6
313.9
..
..
..
..
212.7
159.5
..
..
..
294.7
..
211.3
188.9
191.0
..
104.3
..
..
337.8
96.3
134.7
..
303.5
132.7
166.6
163.0
334.8
259.0
..
..
..
..
..
129.3
1,538.6
..
..
205.6
..
..
74.6
..
..
..
148.5
208.2
152.3
432.0
..
..
..
..
200.3
162.9
..
..
295.1
154.3
..
419.0
215.1
245.1
76.2
155.6
..
..
178.6
47.1
166.3
..
287.6
92.4
193.3
138.2
661.3
194.5
..
..
..
..
..
159.1
328.1
..
..
190.3
..
..
121.2
..
..
..
91.3
253.0
163.7
247.9
..
..
..
..
262.6
119.4
..
..
354.3
119.3
..
134.5
171.7
166.7
842.7
190.3
..
..
143.8
111.9
107.7
..
171.4
51.8
145.1
118.0
198.4
211.0
..
..
..
..
..
78.5
621.9
..
..
120.8
..
..
123.8
..
..
..
192.4
314.3
113.2
334.6
..
..
..
..
359.6
233.0
..
..
347.0
144.7
..
311.2
366.5
152.0
1,168.0
201.7
..
..
84.5
184.7
197.5
..
185.9
154.5
276.6
173.0
477.5
104.2
..
..
..
..
..
99.3
184.6
..
..
294.4
..
..
100.5
..
..
..
253.7
325.2
140.6
461.0
..
..
..
..
587.8
331.7
..
..
500.2
350.0
..
293.3
445.6
127.0
1,382.3
471.0
..
..
226.5
291.5
172.0
..
221.1
..
262.6
226.4
486.9
138.5
..
..
..
..
..
200.9
42,295.8
..
..
495.8
..
..
..
270.7
127.5
..
436.5
..
544.5
193.4
..
445.0
..
344.8
167.9
..
276.4
..
421.4
185.0
..
325.2
..
581.2
269.7
..
405.1
..
173.2
140.5
..
242.3
..
335.7
151.5
..
292.7
..
212.6
174.8
..
223.0
..
259.8
179.3
..
225.8
..
358.3
260.3
..
398.7
..
Part III. Development outcomes
aGriculture, rural developMent, and environMent
1991
1995
Sorghum
(current $ per metric ton)
2000
..
..
..
212.7
330.6
177.2
..
..
..
..
..
..
342.4
..
..
..
362.3
..
213.6
217.5
187.0
..
207.7
..
..
..
176.6
145.3
..
..
63.9
147.8
140.2
368.1
234.0
..
..
..
..
..
106.8
943.0
..
..
237.5
..
..
69.0
..
..
..
134.4
328.3
160.3
..
..
..
..
..
..
252.2
..
..
212.4
193.2
..
193.3
212.9
263.8
..
194.1
..
..
..
72.0
198.3
..
..
47.9
182.0
96.2
847.7
450.1
..
..
..
..
..
132.9
92.7
..
..
246.4
..
..
75.0
..
..
..
84.3
374.7
313.8
..
..
..
..
..
..
2,103.1
..
..
284.7
142.1
..
129.0
153.1
179.4
351.1
204.1
..
..
..
500.6
87.4
..
..
51.8
157.4
77.3
190.3
211.0
..
..
..
..
..
74.9
165.6
..
..
140.5
..
..
90.1
..
..
..
178.7
324.2
217.0
..
..
..
..
..
..
336.6
..
..
391.7
188.7
..
334.3
424.4
120.7
854.6
331.8
..
..
..
514.4
233.6
..
..
141.3
263.2
117.4
509.0
138.8
..
..
..
..
..
70.9
335.2
..
..
364.6
..
..
100.6
..
..
..
225.3
430.5
269.4
..
..
..
..
..
..
325.4
..
..
571.0
446.4
..
316.4
514.9
139.4
1,287.9
319.8
..
..
..
661.0
197.2
..
..
..
244.4
154.2
370.2
186.0
..
..
..
..
..
214.7
3,297.7
..
..
629.7
..
..
..
..
..
..
212.7
..
..
..
..
..
..
..
..
460.8
..
..
..
294.7
..
218.8
308.6
..
..
256.6
..
..
..
133.2
156.0
..
..
..
147.8
150.1
339.6
..
..
..
..
..
..
..
1,206.4
..
..
265.9
..
..
71.8
..
..
..
152.9
..
..
..
..
..
..
..
..
391.3
..
..
337.2
216.0
..
388.9
245.0
..
..
361.3
..
..
..
65.1
194.3
..
..
..
209.5
96.2
413.3
..
..
..
..
..
..
..
278.6
..
..
238.4
..
..
60.0
..
..
..
84.3
..
..
..
..
..
..
..
..
245.7
..
..
434.3
144.8
..
128.2
205.9
..
..
311.1
..
..
..
518.6
85.1
..
..
..
157.4
108.2
184.5
..
..
..
..
..
..
..
655.1
..
..
122.2
..
..
90.1
..
..
..
178.7
..
..
..
..
..
..
..
..
415.4
..
..
645.3
170.0
..
310.1
495.3
..
..
485.5
..
..
..
642.7
254.5
..
..
..
263.2
135.1
493.7
..
..
..
..
..
..
..
433.6
..
..
305.8
..
..
100.6
..
..
..
217.0
..
..
..
..
..
..
..
..
376.9
..
..
939.4
461.5
..
266.6
619.6
..
..
487.7
..
..
..
919.6
192.7
..
..
..
244.4
175.8
402.1
..
..
..
..
..
..
..
5,426.7
..
..
407.5
..
..
..
152.3
141.2
..
218.2
..
207.7
166.9
..
402.8
..
131.5
184.0
..
218.3
..
160.8
186.7
..
292.5
..
221.7
264.3
..
384.5
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
2005
2008
aGriculture, rural developMent, and environMent
1991
1995
Millet
(current $ per metric ton)
2000
2005
2008
Part III. Development outcomes
93
Table
Participating in growth
8.4
Environment
Water pollution
Renewable internal
fresh water resources
Emissions of
Annual
Water
Total
fresh water productivity (2000 organic water
Forest area (billions Per capita withdrawals $ per cubic meter
pollutants
Energy production
(% of land of cubic
(cubic
(kilograms
(kilotons of oil
(billions of
of fresh water
area)
meters)
meters) cubic meters)
per day)
equivalent)
withdrawal)
a
a
a
1990 2010
2007
2007
2000–05
2000–07
2000–07
1990
2008
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
31.3
48.9
52.1
24.2
25.0
11.3
51.4
14.3
37.2
10.4
6.4
70.7
66.5
32.1
0.2
66.3
..
15.2
85.4
44.2
32.7
29.6
78.8
6.5
1.3
51.2
23.5
41.4
11.5
0.4
19.1
55.2
10.6
1.5
18.9
12.9
28.1
48.6
88.5
43.5
13.2
7.6
32.1
27.4
46.8
12.6
24.1
71.0
57.3
1.3
0.7
0.0
0.1
11.3
4.1
28.0
46.9
41.2
20.0
20.6
6.7
42.1
21.1
36.3
9.2
1.6
68.0
65.6
32.7
0.3
58.0
15.2
12.3
85.4
48.0
21.7
26.6
71.9
6.1
1.4
44.9
21.6
34.4
10.2
0.2
17.2
49.6
8.9
1.0
9.9
17.6
28.1
44.0
89.1
38.1
10.8
4.7
29.4
32.7
37.7
5.3
15.2
66.5
40.4
1.4
0.6
0.1
0.1
11.5
6.5
3,884
148
10
2
13
10
273
0
141
15
1
900
222
77
0
26
3
122
164
3
30
226
16
21
5
200
337
16
60
0
3
100
6
4
221
10
2
26
..
160
6
45
30
3
84
12
39
80
12
47
11
2
1
29
4
4,850
8,431
1,227
1,268
849
1,284
14,630
610
33,119
1,412
1,910
14,395
62,516
3,819
360
40,485
586
1,551
115,340
1,857
1,325
23,505
10,383
548
2,574
55,138
18,114
1,118
4,835
127
2,182
4,586
2,949
248
1,496
1,005
13,829
2,169
..
29,518
687
928
742
2,293
2,035
1,825
1,273
6,513
985
290
332
23
97
929
410
103.6
0.6
0.1
0.2
1.0
0.3
1.0
0.0
0.1
0.4
..
0.6
0.0
1.4
0.0
0.0
0.6
5.6
0.1
0.1
1.0
1.6
0.2
2.7
0.1
0.2
14.7
1.0
6.5
1.6
0.7
0.7
0.3
2.4
10.3
0.2
..
2.2
0.0
0.5
3.3
12.5
37.1
1.0
5.2
0.2
0.3
1.7
4.2
14.3
18.2
29.0
2.7
2.5
10.5
27.2
14.4
3.8
..
6.9
76.0
7.4
29.2
72.1
1.2
1.6
39.0
5.9
5.1
1.9
1.2
5.0
14.9
3.1
0.3
1.8
0.4
0.7
6.9
5.7
13.0
0.8
4.5
11.6
..
2.2
47.1
1.3
..
10.6
0.3
1.4
2.2
8.2
21.5
1.9
1.5
..
..
3,246
..
..
..
..
..
..
..
..
..
..
..
..
2,540
32,159
..
..
16,048
..
..
..
5,252
..
92,770
32,672
..
..
15,446
..
..
..
..
..
..
6,621
..
..
..
229,582
38,567
..
30,322
..
2,105
..
..
6.1
68.2
4.3
12.6
2.8
9.6
1.5
7.9
2.9
7.2
..
..
..
73,989
..
475,369
28,652
1,774
910
..
..
10,976
..
..
..
..
12,019
8,746
3,382
..
..
..
14,052
14,630
..
4,392
..
..
9,013
..
..
..
..
..
..
..
5,608
..
..
150,452
..
..
964
..
..
..
114,535
8,775
..
9,064
1,054
..
4,918
8,550
234,657
100,114
54,869
73,173
773
5,728
Energy
Energy use
(kilotons of oil
equivalent)
1990
2008
809,956 310,313 497,224
105,837
5,883 10,972
1,833
1,661
3,005
1,002
1,261
2,117
..
..
..
..
..
..
10,119
4,980
7,102
..
..
..
..
..
..
..
..
..
..
..
..
22,664 11,798 22,250
13,245
797
1,368
11,415
4,323 10,278
..
..
..
..
..
..
546
..
681
29,581 14,866 31,704
13,519
1,181
2,073
..
..
..
6,858
5,291
9,459
..
..
..
..
..
..
15,108 10,940 18,021
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
11,460
5,922
9,314
317
..
1,752
..
..
..
226,793 70,582 111,156
..
..
..
..
..
..
1,230
1,686
2,859
..
..
..
..
..
..
..
..
..
162,951 90,860 134,489
34,874 10,629 15,372
..
..
..
17,470
9,733 18,957
2,138
1,263
2,563
..
..
..
6,790
5,399
7,355
8,533
9,297
9,506
361,445 77,234 150,155
162,044 22,192 37,069
87,487 31,825 70,710
103,743 11,330 18,221
637
6,941 14,977
7,534
4,946
9,178
Combustible
renewables and waste
(% of total energy use)
1990
2008
56.6
73.5
94.2
33.4
..
..
76.7
..
..
..
..
84.7
59.5
73.5
..
..
..
93.9
62.9
..
73.7
..
..
77.9
..
..
..
..
..
..
..
93.9
..
..
80.2
..
..
56.8
..
..
..
11.5
81.8
..
91.7
82.8
..
74.3
50.9
2.8
0.1
3.3
1.1
4.6
12.9
57.7
63.5
61.0
22.3
..
..
71.0
..
..
..
..
93.4
51.3
74.0
..
..
80.0
92.4
52.5
..
66.8
..
..
76.9
..
..
..
..
..
..
..
81.9
11.2
..
81.2
..
..
41.7
..
..
..
10.4
68.0
..
88.2
83.1
..
81.0
65.3
2.3
0.1
2.1
0.9
3.2
13.6
a. Data are for the most recent year available during the period specified.
b. Hydrofluorocarbons, perfluorocarbons, and sulphur hexafluoride.
94
Part III. Development outcomes
aGriculture, rural developMent, and environMent
Greenhouse gas emissions
Methane
Carbon dioxide
(thousands of
metric tons)
1990
2007
464,110
4,426
715
2,169
586
304
1,737
88
198
147
77
4,067
1,187
5,793
399
121
..
3,016
6,082
191
3,928
1,055
253
5,818
..
484
986
612
421
2,664
1,462
1,000
7
953
45,338
682
66
3,180
114
388
18
333,241
5,555
425
2,371
773
817
2,444
15,510
231,777
78,831
75,881
40,286
23,523
13,256
682,631
24,743
3,873
4,994
1,693
180
6,163
308
253
385
121
2,433
1,587
6,379
487
4,793
579
6,504
2,034
396
9,801
1,389
286
11,227
..
674
2,250
1,055
579
1,949
3,884
2,598
3,034
909
95,194
715
128
5,474
623
1,312
601
433,173
11,512
1,063
6,038
1,315
3,202
2,689
9,629
452,017
140,005
184,508
57,287
46,368
23,849
Total
(kilotons of
carbon dioxide
equivalent)
1990
2005
..
..
49,530 45,409
4,847 4,080
5,812 4,501
..
..
..
..
13,503 18,518
..
..
..
..
..
..
..
..
96,593 56,445
6,231 5,584
11,243 10,997
..
..
..
..
1,884 2,467
39,325 52,243
8,103 8,218
..
..
7,238 8,990
..
..
..
..
17,952 22,130
..
..
..
..
..
..
..
..
..
..
..
..
..
..
10,863 12,843
3,435 5,057
..
..
117,467 130,317
..
..
..
..
5,277
7,129
..
..
..
..
..
..
51,179 63,785
43,370 67,441
..
..
25,817 32,024
2,752 2,889
..
..
26,944 19,294
10,112 9,539
104,128 134,629
40,726 54,219
27,839 46,996
22,473 14,682
9,132 10,573
3,958 8,160
Agricultural
(% of total)
1990 2005
Industrial
(% of total)
1990 2005
44.0
26.4
36.7
90.5
..
..
55.2
..
..
..
..
25.6
37.3
18.3
..
..
78.7
81.6
0.9
..
48.9
..
..
74.3
..
..
..
..
..
..
..
66.3
95.8
..
18.5
..
..
68.8
..
..
..
37.3
87.1
..
73.9
52.9
..
66.1
79.1
21.6
9.1
38.0
4.9
58.8
44.9
32.1
21.6
16.1
7.7
..
..
20.2
..
..
..
..
47.9
10.4
18.9
..
..
11.0
9.3
46.5
..
13.7
..
..
15.7
..
..
..
..
..
..
..
17.5
3.7
..
47.3
..
..
4.5
..
..
..
52.4
21.4
..
21.3
18.4
..
8.1
22.2
51.5
61.2
33.4
79.1
6.2
26.2
44.0
27.9
47.8
84.1
..
..
42.4
..
..
..
..
23.1
31.9
17.4
..
..
73.2
72.5
1.1
..
39.5
..
..
65.5
..
..
..
..
..
..
..
44.2
94.9
..
19.8
..
..
68.3
..
..
..
31.4
85.2
..
63.2
39.8
..
59.3
73.3
20.6
8.2
31.7
5.7
51.7
25.5
Agricultural
(% of total)
1990 2005
Industrial
(% of total)
1990 2005
ODA gross
Other greenhouse
disbursements
gasesb
ODA gross
(thousands of
for general
metric tons of disbursements environment
for forestry
carbon dioxide
protection
($ millions)
equivalent)
($ millions)
1990
2005
2009
2009
64.5
39.2
50.5
90.9
..
..
68.1
..
..
..
..
37.9
48.6
22.7
..
..
93.0
91.9
25.6
..
75.5
..
..
91.9
..
..
..
..
..
..
..
82.0
93.2
..
82.1
..
..
88.1
..
..
..
63.3
92.0
..
82.8
74.3
..
75.1
84.2
72.0
64.3
71.5
67.2
85.1
59.0
0.3
0.0
0.0
..
..
..
0.0
..
..
..
..
0.0
0.0
0.0
..
..
0.0
0.0
0.0
..
0.0
..
..
0.0
..
..
..
..
..
..
..
0.0
0.0
..
0.0
..
..
0.0
..
..
..
3.6
0.0
..
0.0
0.0
..
0.0
5.9
5.6
4.4
8.2
0.0
0.0
10.6
..
0
0
0
..
..
932
..
..
..
..
0
0
0
..
..
0
0
0
..
596
..
..
0
..
..
..
..
..
..
..
0
0
..
242
..
..
0
..
..
..
1,491
0
..
0
0
..
0
0
2,668
326
2,059
282
0
0
Nitrous oxide
aGriculture, rural developMent, and environMent
30.2
11.6
8.9
17.9
..
..
17.9
..
..
..
..
49.6
7.7
11.2
..
..
7.5
10.0
79.9
..
10.7
..
..
18.0
..
..
..
..
..
..
..
16.9
4.7
..
45.5
..
..
4.7
..
..
..
54.3
21.5
..
20.3
14.8
..
5.7
24.8
48.2
66.3
31.2
77.6
2.6
32.1
Total
(metric tons of
carbon dioxide
equivalent)
1990 2005
..
41,667
3,695
5,511
..
..
10,530
..
..
..
..
87,098
4,307
7,485
..
..
1,028
25,545
305
..
5,187
..
..
9,222
..
..
..
..
..
..
..
10,881
2,580
..
19,153
..
..
2,976
..
..
..
21,300
36,669
..
21,468
2,209
..
35,669
7,284
24,023
3,843
11,818
1,176
5,180
2,006
..
38,881
2,902
3,081
..
..
9,127
..
..
..
..
54,643
3,566
7,364
..
..
1,189
30,510
482
..
4,899
..
..
10,542
..
..
..
..
..
..
..
9,501
3,797
..
21,565
..
..
4,083
..
..
..
24,048
49,472
..
21,647
1,738
..
25,068
6,114
33,358
4,898
18,996
1,285
5,814
2,366
66.1
38.4
61.5
92.0
..
..
75.9
..
..
..
..
31.3
51.8
29.3
..
..
90.9
88.8
23.3
..
70.5
..
..
88.8
..
..
..
..
..
..
..
71.4
94.3
..
77.3
..
..
88.5
..
..
..
59.8
92.6
..
78.8
67.5
..
71.7
85.2
75.3
58.6
80.0
51.9
82.6
66.4
0.8
0.0
0.0
0.0
..
..
0.0
..
..
..
..
0.0
0.0
0.0
..
..
0.0
0.0
0.0
..
0.0
..
..
0.0
..
..
..
..
..
..
..
0.0
0.0
..
0.0
..
..
0.0
..
..
..
7.3
0.0
..
0.0
0.0
..
3.7
0.0
7.9
7.2
11.5
0.0
0.0
4.1
..
20
0
0
..
..
419
..
..
..
..
0
5
0
..
..
0
10
9
..
15
..
..
0
..
..
..
..
..
..
..
282
0
..
669
..
..
0
..
..
..
2,552
0
..
0
0
..
0
0
3,950
489
3,181
280
0
0
120.8
0.9
0.0
0.1
2.8
0.0
4.3
..
2.9
0.0
0.0
4.0
1.2
..
0.2
0.1
0.5
7.8
0.2
..
16.3
0.7
..
5.7
0.1
1.1
0.7
2.2
3.1
3.5
..
1.6
1.3
0.2
0.5
1.0
..
6.9
..
..
..
0.0
2.5
0.0
11.0
..
2.9
0.5
0.0
5.7
0.2
0.0
..
0.7
4.4
588.2
2.5
13.2
3.0
10.5
1.9
12.3
7.9
18.6
6.0
0.7
15.5
3.8
1.3
0.5
0.5
1.0
13.5
5.4
0.4
18.6
2.1
2.2
35.2
1.2
3.0
18.8
5.9
14.1
11.8
5.2
17.9
11.6
7.4
9.9
9.2
0.2
54.2
0.1
1.9
0.1
26.6
15.1
1.1
30.9
1.2
16.9
11.6
1.0
109.9
4.6
35.6
0.1
40.9
22.8
Part III. Development outcomes
95
Table
Participating in growth
8.5
Fossil fuel emissions
Carbon dioxide emissions
Total
Per capita
(thousands of metric tons)
(metric tons)
1990
2005
2007
1990
2005
SUB–SAHARAN AFRICA 464,110
Angola
4,426
Benin
715
Botswana
2,169
Burkina Faso
586
Burundi
304
Cameroon
1,737
Cape Verde
88
Central African Republic
198
Chad
147
Comoros
77
Congo, Dem. Rep.
4,067
Congo, Rep.
1,187
Côte d’Ivoire
5,793
Djibouti
399
Equatorial Guinea
121
Eritrea
..
Ethiopia
3,016
Gabon
6,082
Gambia, The
191
Ghana
3,928
Guinea
1,055
Guinea-Bissau
253
Kenya
5,818
Lesotho
..
Liberia
484
Madagascar
986
Malawi
612
Mali
421
Mauritania
2,664
Mauritius
1,462
Mozambique
1,000
Namibia
7
Niger
953
Nigeria
45,338
Rwanda
682
São Tomé and Príncipe
66
Senegal
3,180
Seychelles
114
Sierra Leone
388
Somalia
18
South Africa
333,241
Sudan
5,555
Swaziland
425
Tanzania
2,371
Togo
773
Uganda
817
Zambia
2,444
Zimbabwe
15,510
NORTH AFRICA
231,777
Algeria
78,831
Egypt, Arab Rep.
75,881
Libya
40,286
Morocco
23,523
Tunisia
13,256
656,877
19,756
2,565
4,521
1,173
165
3,693
297
235
399
110
2,275
1,605
8,160
473
4,708
733
5,485
1,861
322
7,467
1,359
264
10,944
..
737
2,173
1,037
568
1,656
3,408
1,854
2,656
824
110,371
689
128
5,529
696
1,260
579
407,895
10,992
1,019
5,082
1,337
2,338
2,363
10,780
424,566
138,741
163,220
55,997
43,825
22,783
682,631
24,743
3,873
4,994
1,693
180
6,163
308
253
385
121
2,433
1,587
6,379
487
4,793
579
6,504
2,034
396
9,801
1,389
286
11,227
..
674
2,250
1,055
579
1,949
3,884
2,598
3,034
909
95,194
715
128
5,474
623
1,312
601
433,173
11,512
1,063
6,038
1,315
3,202
2,689
9,629
452,017
140,005
184,508
57,287
46,368
23,849
0.9
0.4
0.1
1.6
0.1
0.1
0.1
0.2
0.1
0.0
0.2
0.1
0.5
0.5
0.7
0.3
..
0.1
6.6
0.2
0.3
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
9.5
0.2
0.5
0.1
0.2
0.0
0.3
1.5
1.9
3.1
1.3
9.2
0.9
1.6
0.9
1.2
0.3
2.5
0.1
0.0
0.2
0.6
0.1
0.0
0.2
0.0
0.5
0.4
0.6
7.7
0.2
0.1
1.4
0.2
0.3
0.1
0.2
0.3
..
0.2
0.1
0.1
0.0
0.6
2.7
0.1
1.3
0.1
0.8
0.1
0.8
0.5
8.4
0.2
0.1
8.6
0.3
0.9
0.1
0.2
0.1
0.2
0.9
2.7
4.2
2.1
9.5
1.4
2.3
2007
1990
0.9
1.4
0.5
2.6
0.1
0.0
0.3
0.6
0.1
0.0
0.2
0.0
0.4
0.3
0.6
7.5
0.1
0.1
1.4
0.2
0.4
0.1
0.2
0.3
..
0.2
0.1
0.1
0.0
0.6
3.1
0.1
1.5
0.1
0.6
0.1
0.8
0.5
7.3
0.2
0.1
9.0
0.3
0.9
0.1
0.2
0.1
0.2
0.8
2.8
4.1
2.3
9.3
1.5
2.3
129,769
1,208
195
592
160
83
..
24
54
40
21
1,110
324
1,581
109
33
..
823
1,660
52
1,072
288
69
1,588
..
132
269
167
115
727
399
273
2
260
12,374
186
18
868
31
106
5
90,950
1,516
116
647
211
223
667
4,233
63,258
21,515
20,710
10,995
6,420
3,618
Carbon dioxide emissions from fossil fuel
(thousands of metric tons)
Solid fuel
Total
consumption
2005
2007
1990
2005
183,320
5,392
700
1,234
320
45
..
81
64
109
30
621
438
2,227
129
1,285
200
1,497
508
88
2,038
371
72
2,987
..
201
593
283
155
452
930
506
725
225
30,123
188
35
1,509
190
344
158
111,325
3,000
278
1,387
365
638
645
2,942
115,875
37,866
44,547
15,283
11,961
6,218
189,853
6,753
1,057
1,363
462
49
..
84
69
105
33
664
433
1,741
133
1,308
158
1,775
555
108
2,675
379
78
3,064
..
184
614
288
158
532
1,060
709
828
248
25,981
195
35
1,494
170
358
164
118,224
3,142
290
1,648
359
874
734
2,628
123,367
38,211
50,357
15,635
12,655
6,509
110,850
0
0
592
0
4
..
0
0
0
0
209
0
0
0
0
..
0
0
0
2
0
0
110
..
0
9
13
0
4
54
42
0
98
35
0
0
0
0
0
0
72,352
0
116
3
0
0
227
3,666
3,567
825
917
4
1,278
72
143,104
0
0
702
0
2
..
0
0
0
0
273
0
0
0
0
0
0
0
0
0
0
0
78
..
0
7
43
0
0
264
0
14
103
8
0
0
114
0
0
0
95,970
0
104
54
0
0
98
2,318
6,292
666
924
0
3,844
0
2007
149,751
0
0
796
0
2
..
0
0
0
0
303
0
0
0
0
0
0
0
0
0
0
0
80
..
0
7
44
0
0
415
7
56
105
8
0
0
218
0
0
0
100,415
0
109
62
0
0
111
2,073
6,878
859
966
0
4,115
0
Note: 0 refers to a negligible value that rounds to 0.
96
Part III. Development outcomes
aGriculture, rural developMent, and environMent
Liquid fuel consumption
1990
2005
2007
42,649
489
154
0
160
79
..
24
54
40
21
838
265
1,513
109
33
..
777
583
52
978
288
69
1,273
..
125
252
141
112
709
345
220
2
159
9,823
177
18
801
31
106
0
16,596
1,493
0
571
157
219
381
471
34,171
6,835
14,323
6,058
4,541
2,414
48,703
1,460
666
532
316
43
..
81
64
109
30
348
358
1,228
129
142
194
1,284
408
87
1,780
322
72
2,620
..
181
566
217
155
411
666
392
711
115
12,143
173
35
1,031
190
321
158
11,526
2,955
173
962
256
552
488
542
58,630
17,270
21,152
10,425
6,385
3,398
49,016
2,296
846
568
458
47
..
84
69
105
33
362
347
1,025
133
163
152
1,544
443
106
2,417
330
78
2,669
..
163
570
219
158
476
645
505
772
136
7,789
181
35
841
170
326
164
13,599
3,115
181
1,102
250
786
535
502
63,212
18,794
23,958
10,301
6,705
3,454
Carbon dioxide emissions from fossil fuel
(thousands of metric tons)
Gas fuel consumption
Gas flaring
1990
2005
2007
1990
2005
..
276
0
0
0
0
..
0
0
0
0
0
1
0
0
0
..
0
138
0
0
0
0
0
..
0
0
0
0
0
0
0
0
0
2,041
0
0
3
0
0
0
940
0
0
0
0
0
0
0
17,482
10,619
3,552
2,599
30
682
..
341
0
0
0
0
..
0
0
0
0
0
12
910
0
605
0
0
65
1
0
0
0
0
..
0
0
0
0
0
0
38
0
0
5,572
0
0
7
0
0
0
2,269
0
0
185
0
0
0
0
39,841
16,706
18,057
3,010
237
1,831
aGriculture, rural developMent, and environMent
..
435
0
0
0
0
..
0
0
0
0
0
11
629
0
876
0
0
82
1
0
0
0
0
..
0
0
0
0
0
0
82
0
0
5,594
0
0
5
0
0
0
2,353
0
0
278
0
0
0
0
39,810
13,942
20,211
3,304
339
2,014
..
409
0
0
0
0
..
0
0
0
0
0
46
0
0
0
..
0
924
0
0
0
0
0
..
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
..
2,373
0
1,969
0
1
..
3,412
0
0
0
0
..
0
0
0
0
0
0
0
0
538
0
0
0
0
0
0
0
0
..
0
0
0
0
0
0
0
0
0
12,075
0
0
0
0
0
0
0
0
0
0
0
0
0
0
..
1,688
0
1,357
0
79
2007
1990
..
3,832
0
0
0
0
..
0
0
0
0
0
0
0
0
269
0
0
0
0
0
0
0
0
..
0
0
0
0
0
0
0
0
0
11,707
0
0
0
0
0
0
0
0
0
0
0
0
0
0
..
2,454
0
1,527
0
82
2,906
35
41
0
0
0
..
0
0
0
0
63
12
68
0
0
..
46
16
0
92
0
0
205
..
7
8
13
3
14
0
11
0
3
476
8
0
64
0
0
5
1,062
23
0
73
54
4
59
95
4,167
862
1,918
367
571
449
Cement production
2005
2007
4,815
179
34
0
4
0
..
0
0
0
0
0
69
88
0
0
6
213
35
0
258
49
0
289
..
20
20
23
0
41
0
76
0
7
326
14
0
357
0
23
0
1,559
45
0
186
109
86
59
82
8,848
1,536
4,414
492
1,496
910
6,229
190
211
0
4
0
..
0
0
0
0
0
75
88
0
0
6
231
31
0
258
49
0
315
..
21
37
25
0
56
0
116
0
7
884
14
0
429
0
32
0
1,857
27
0
206
109
88
88
54
10,342
2,162
5,222
503
1,496
959
Part III. Development outcomes
97
Table
Participating in growth
9.1
Labor force participation
Labor force ages 15 and older
Total
(thousands)
2000
2009
SUB–SAHARAN AFRICA 263,550
Angola
6,237
Benin
2,670
Botswana
799
Burkina Faso
5,217
Burundi
3,138
Cameroon
5,995
Cape Verde
156
Central African Republic
1,703
Chad
3,277
Comoros
251
Congo, Dem. Rep.
18,605
Congo, Rep.
1,256
Côte d’Ivoire
6,728
Djibouti
295
Equatorial Guinea
186
Eritrea
1,383
Ethiopia
28,989
Gabon
537
Gambia, The
581
Ghana
8,554
Guinea
3,954
Guinea-Bissau
541
Kenya
14,321
Lesotho
810
Liberia
1,123
Madagascar
7,273
Malawi
4,953
Mali
2,959
Mauritania
1,031
Mauritius
528
Mozambique
8,914
Namibia
601
Niger
3,551
Nigeria
39,249
Rwanda
3,710
São Tomé and Príncipe
46
Senegal
4,089
Seychelles
..
Sierra Leone
1,664
Somalia
2,944
South Africa
15,280
Sudan
10,494
Swaziland
373
Tanzania
16,767
Togo
2,183
Uganda
10,500
Zambia
4,024
Zimbabwe
5,110
NORTH AFRICA
48,019
Algeria
11,101
Egypt, Arab Rep.
21,655
Libya
1,831
Morocco
10,215
Tunisia
3,217
98
Part III. Development outcomes
341,616
8,278
3,699
996
7,140
4,569
7,727
214
2,074
4,283
325
24,927
1,594
8,369
387
262
2,154
39,952
711
766
10,951
4,850
661
18,712
935
1,611
9,681
6,309
3,770
1,394
567
11,004
783
4,799
49,972
4,963
58
5,405
..
2,141
3,538
18,849
13,462
457
21,382
2,960
14,134
4,812
5,028
60,451
14,840
27,417
2,368
11,982
3,844
Male
Female
(% of total labor force) (% of total labor force)
2000
2009
2000
2009
57.0
53.3
55.1
52.9
52.3
47.0
60.9
60.3
53.7
54.5
54.3
59.7
57.0
64.8
58.5
72.5
58.0
54.8
55.4
53.8
51.6
53.3
57.3
53.4
48.0
52.8
51.3
49.9
64.2
59.2
65.9
46.9
54.9
68.9
65.4
46.9
63.0
57.9
..
47.9
58.3
56.5
72.1
58.5
50.2
58.0
53.0
55.1
53.2
74.4
71.7
75.6
78.7
73.6
75.3
56.4
53.1
53.8
52.6
52.9
47.4
59.9
56.8
53.5
54.8
53.5
59.4
56.4
63.1
55.9
69.2
55.5
52.1
53.3
53.8
50.9
53.1
57.6
53.3
47.6
52.4
50.8
50.2
62.7
58.0
63.9
48.0
53.5
68.4
64.9
47.2
61.9
56.7
..
48.6
59.1
56.3
70.5
56.6
50.6
56.5
53.5
56.6
52.5
74.1
68.4
77.0
77.5
74.2
73.3
43.0
46.7
44.9
47.1
47.7
53.0
39.1
39.7
46.3
45.5
45.7
40.3
43.0
35.2
41.5
27.5
42.0
45.2
44.6
46.2
48.4
46.7
42.7
46.6
52.0
47.2
48.7
50.1
35.8
40.8
34.1
53.1
45.1
31.1
34.6
53.1
37.0
42.1
..
52.1
41.7
43.5
27.9
41.5
49.8
42.0
47.0
44.9
46.8
25.6
28.3
24.4
21.3
26.4
24.7
43.6
46.9
46.2
47.4
47.1
52.6
40.1
43.2
46.5
45.2
46.5
40.6
43.6
36.9
44.1
30.8
44.5
47.9
46.7
46.2
49.1
46.9
42.4
46.7
52.4
47.6
49.2
49.8
37.3
42.0
36.1
52.0
46.5
31.6
35.1
52.8
38.1
43.3
..
51.4
40.9
43.7
29.5
43.4
49.4
43.5
46.5
43.4
47.5
25.9
31.6
23.0
22.5
25.8
26.7
Participation rate, ages 15 and older
Total
Male
Female
(% of total
(% of male
(% of female
population)
population)
population)
2000
2009
2000
2009
2000
2009
69.9
82.5
72.5
74.9
84.0
90.2
66.2
62.6
78.3
72.3
77.0
70.5
71.9
66.5
68.8
62.8
68.4
81.7
73.7
78.2
74.6
84.4
71.4
81.6
73.9
71.3
86.8
77.4
51.6
68.5
60.2
86.7
55.8
62.6
56.0
86.0
57.3
75.8
..
67.8
71.3
52.3
52.0
62.3
88.9
72.9
85.0
70.2
71.0
51.2
55.2
48.9
50.5
53.4
48.1
70.7
81.3
72.7
76.6
84.4
89.3
67.0
66.4
79.0
70.4
79.6
70.8
72.7
66.9
70.1
65.5
72.6
85.4
75.5
77.8
74.6
84.2
71.5
82.2
74.0
71.1
86.4
76.8
51.9
70.0
57.5
85.8
57.1
62.7
56.2
86.0
59.8
76.4
..
66.4
70.3
55.0
52.3
63.6
88.4
74.4
84.5
69.2
66.8
51.7
58.5
48.8
52.8
52.3
48.0
81.1
90.2
81.4
80.8
90.9
90.0
81.4
83.2
86.8
80.2
83.8
86.1
83.0
82.1
81.2
93.1
82.6
90.9
83.0
86.0
76.6
89.8
83.4
88.2
80.1
76.9
89.6
79.1
68.2
81.5
80.4
87.4
63.7
88.1
74.1
86.4
73.8
89.2
..
67.8
84.7
60.9
75.1
78.2
90.8
86.3
91.1
78.6
78.5
76.4
79.0
74.1
75.5
80.7
72.3
80.8
88.4
77.9
80.9
90.8
87.5
80.7
81.3
86.7
78.2
85.4
85.6
82.6
82.1
78.7
92.0
83.4
90.3
81.1
85.2
75.2
89.2
83.8
88.1
77.7
75.8
88.7
78.8
67.0
81.0
74.8
86.9
62.6
87.5
73.4
85.1
76.0
88.6
..
67.5
84.7
63.4
73.9
74.9
90.6
85.7
90.6
79.2
74.3
77.0
79.6
75.3
78.9
80.1
70.6
59.1
75.2
63.9
69.2
77.5
90.5
51.2
45.5
70.4
64.6
70.1
55.5
61.1
49.2
56.6
33.8
55.2
72.8
64.6
70.8
72.6
78.9
59.8
75.2
68.9
66.0
84.0
75.8
35.9
55.6
40.6
86.0
48.5
38.1
38.3
85.6
41.5
62.8
..
67.8
58.4
44.3
28.9
48.4
87.0
60.0
79.0
62.1
64.0
26.1
31.3
23.8
22.7
27.5
23.8
60.9
74.5
67.4
72.3
78.2
91.0
53.5
53.5
71.6
62.7
73.7
56.5
62.9
50.8
61.5
39.7
62.5
80.7
70.0
70.6
73.8
79.2
59.6
76.4
70.8
66.6
84.2
75.0
37.6
59.0
40.8
84.8
51.8
38.9
39.2
86.7
44.5
64.8
..
65.4
56.5
47.0
30.8
53.1
86.3
63.6
78.3
59.5
60.0
26.6
37.2
22.4
24.7
26.2
25.6
l aBor, MiGration, and population
Participation rate, ages 15–64
Total
Male
Female
(% of total
(% of male
(% of female
population)
population)
population)
2000
2009
2000
2009
2000
2009
71.1
83.9
73.4
76.7
85.3
91.0
67.3
65.5
78.7
72.5
77.9
71.9
72.3
67.0
70.3
64.5
69.7
83.7
75.9
78.5
75.5
86.3
73.2
82.9
75.1
73.1
88.1
76.8
52.9
70.0
64.5
86.8
57.2
63.0
56.9
87.4
60.0
76.8
..
68.9
72.8
54.8
52.7
63.8
90.3
73.9
86.4
70.5
71.6
53.7
57.7
51.3
52.1
56.3
51.0
72.1
82.6
73.5
78.8
85.7
89.9
68.3
69.2
79.3
70.6
80.6
72.1
73.1
67.5
71.8
66.9
74.0
87.0
77.5
78.0
75.6
86.3
73.3
83.5
75.2
72.9
87.7
76.1
53.1
71.6
62.6
86.1
58.6
63.3
57.3
87.2
62.5
77.5
..
67.4
71.8
58.6
53.2
65.3
90.0
75.6
85.8
69.7
67.9
54.5
61.1
51.6
55.0
55.3
50.9
82.0
91.1
81.6
81.7
91.5
90.5
82.7
85.1
87.1
79.9
84.1
87.6
84.0
82.4
82.3
95.2
83.6
92.1
84.9
85.9
77.1
90.5
85.1
89.0
81.0
77.9
90.4
78.2
69.9
82.5
84.7
87.2
65.0
88.6
75.4
87.3
76.6
90.4
..
68.5
86.1
63.1
75.3
79.0
91.5
86.9
91.8
78.7
79.0
79.6
82.2
77.1
77.6
84.3
76.0
81.8
89.1
78.2
82.1
91.4
88.1
82.0
82.8
87.1
77.8
85.9
87.0
83.5
82.6
80.0
93.8
84.6
90.9
82.8
85.1
75.8
89.9
85.6
88.8
78.5
76.8
89.4
77.9
68.3
82.0
79.8
86.6
63.9
88.0
74.7
86.0
78.5
89.7
..
67.9
86.1
66.6
74.0
75.8
91.2
86.4
91.2
79.3
75.4
80.5
82.8
79.1
81.6
83.7
73.8
60.5
76.9
65.2
71.8
79.5
91.4
52.2
48.7
70.6
65.2
71.6
56.7
60.9
49.9
58.4
34.8
56.6
75.5
67.2
71.2
73.9
82.1
61.7
77.0
70.4
68.4
85.9
75.4
37.0
57.4
44.2
86.5
49.9
38.6
38.7
87.5
44.0
63.6
..
69.2
59.8
46.9
30.0
50.4
89.1
61.3
81.1
62.5
64.7
27.7
32.7
25.2
23.7
29.5
25.8
l aBor, MiGration, and population
62.5
76.4
68.8
75.5
80.2
91.6
54.5
57.0
71.7
63.5
75.3
57.7
62.8
51.5
63.6
40.7
63.9
83.1
72.1
71.1
75.3
82.6
61.3
78.2
72.4
69.1
86.0
74.4
38.7
60.9
45.4
85.6
53.5
39.4
39.9
88.4
47.1
65.7
..
66.8
57.9
50.8
32.2
55.5
88.8
65.0
80.5
60.0
61.2
28.3
38.8
23.9
26.1
28.3
27.8
Labor force ages 15–24
Male
Female
Total
(% of total
(% of total
(thousands)
labor force)
labor force)
2000
2009
2000
2009
2000
2009
75,323 94,875
2,182
2,851
773
991
231
258
1,872
2,416
1,080
1,480
1,653
2,020
55
63
469
576
929
1,204
..
..
6,353 8,643
351
414
1,806
2,177
80
95
..
..
529
617
9,679 13,294
150
186
157
210
2,132
2,478
1,250
1,518
145
178
5,033 6,069
273
299
333
458
2,167 2,850
1,262
1,615
882
1,072
298
355
101
83
2,662 3,255
115
136
1,071
1,511
7,942
9,312
1,316
1,664
14
14
1,396
1,741
..
..
392
480
..
..
2,629 3,099
2,434
2,794
121
147
5,663
7,077
674
827
3,878 5,259
1,210
1,489
1,579
1,597
11,760 12,769
3,168 3,455
5,291
6,257
453
421
2,848
2,637
..
..
56.4
53.7
52.8
52.7
53.6
48.2
62.3
60.9
54.6
49.8
..
58.7
59.3
60.8
56.8
..
58.1
53.0
53.4
50.8
50.5
53.1
57.3
53.4
53.2
50.9
50.5
46.0
62.0
58.1
64.3
46.2
54.2
65.8
68.9
48.5
68.5
60.4
..
43.4
..
54.5
63.3
55.3
50.0
57.7
53.2
56.1
54.5
69.8
71.6
68.6
74.0
69.5
..
55.7
53.1
49.9
51.8
53.5
47.5
61.7
59.8
54.5
49.0
..
58.6
58.7
60.4
55.1
..
56.2
51.2
53.3
50.7
49.5
52.7
57.7
53.1
52.4
50.4
50.1
46.2
60.7
57.2
57.6
46.9
52.1
66.3
68.0
48.1
68.1
60.1
..
42.7
..
54.9
62.1
55.1
49.8
57.1
53.0
56.0
53.7
72.3
68.6
73.3
74.8
73.8
..
45.2
46.3
47.2
47.3
46.4
51.8
37.7
39.1
45.4
50.2
..
41.3
40.7
39.2
43.2
..
41.9
47.0
46.6
49.2
49.5
46.9
42.7
46.6
46.8
49.1
49.5
54.0
38.0
41.9
35.7
53.8
45.8
34.2
31.1
51.5
31.5
39.6
..
56.6
..
45.5
36.7
44.7
50.0
42.3
46.8
43.9
45.5
30.3
28.4
31.4
26.0
30.5
..
45.8
46.9
50.1
48.2
46.5
52.5
38.3
40.2
45.5
51.0
..
41.4
41.3
39.6
44.9
..
43.8
48.8
46.7
49.3
50.5
47.3
42.3
46.9
47.6
49.6
49.9
53.8
39.3
42.8
42.4
53.1
47.9
33.7
32.0
51.9
31.9
39.9
..
57.3
..
45.1
37.9
44.9
50.2
42.9
47.0
44.0
46.3
28.0
31.4
26.7
25.2
26.2
..
Participation rate, ages 15–24
Total
Male
Female
(% of total
(% of male
(% of female
population)
population)
population)
2000
2009
2000
2009
2000
2009
56.8
78.3
60.3
59.5
78.6
82.2
50.9
58.5
64.1
57.0
..
65.9
55.7
51.6
54.4
68.5
61.2
79.0
62.8
66.6
53.9
77.3
59.4
73.4
64.4
60.1
75.1
53.9
41.3
55.8
49.2
73.7
30.6
53.7
31.4
76.9
41.4
67.9
..
45.4
77.6
28.7
35.1
52.3
82.2
62.1
79.8
57.1
54.6
40.6
45.9
36.1
34.9
46.7
39.9
56.2
75.3
56.7
59.3
77.7
77.4
49.6
54.8
64.2
54.4
..
65.0
54.1
51.8
50.9
..
59.4
78.5
59.9
65.5
51.1
76.2
60.2
72.4
62.0
58.5
73.0
53.5
39.3
53.6
40.8
72.5
28.9
55.1
30.0
75.1
40.6
66.4
..
43.6
..
30.8
32.7
50.0
81.4
60.7
78.7
57.0
50.4
39.8
47.1
36.5
36.3
41.1
..
63.3
84.7
62.9
62.4
83.3
80.0
63.2
72.8
70.6
56.9
..
77.4
65.7
62.3
61.4
89.0
71.0
83.7
67.7
68.0
53.5
80.4
68.1
78.3
70.1
61.4
75.8
49.7
51.1
63.1
62.5
69.6
33.2
76.3
43.0
76.3
56.3
82.0
..
40.6
88.7
31.3
43.8
59.1
82.2
71.9
84.6
64.0
59.7
55.7
64.5
48.8
50.8
65.3
50.3
61.6
80.6
55.5
61.2
82.0
73.8
60.9
65.9
70.7
53.2
..
76.2
63.1
62.5
55.6
..
67.2
80.3
63.2
66.4
49.6
78.9
69.5
76.8
66.0
59.0
73.2
49.3
47.5
59.7
46.4
68.3
30.1
76.1
40.4
73.2
54.6
79.7
..
38.2
..
33.7
40.0
55.0
81.0
69.5
83.1
63.7
54.6
56.7
63.3
52.6
53.2
60.7
..
50.2
72.1
57.6
56.6
73.8
84.3
38.5
44.8
57.7
57.1
..
54.4
45.6
40.8
47.3
48.2
51.4
74.2
58.0
65.1
54.3
74.0
50.6
68.6
58.9
58.8
74.4
58.2
31.4
48.0
35.6
77.5
28.0
34.2
19.6
77.5
26.2
53.9
..
49.9
66.6
26.2
26.1
45.8
82.2
52.4
74.9
50.3
49.5
25.1
26.6
23.0
18.4
28.3
29.0
50.7
70.0
57.9
57.5
73.2
80.9
38.2
43.8
57.9
55.6
..
53.8
45.0
41.1
46.0
..
51.7
76.7
56.5
64.6
52.6
73.4
51.0
68.0
58.2
58.0
72.8
57.7
31.0
47.2
35.0
76.8
27.7
35.7
19.4
76.9
26.2
53.1
..
48.8
..
27.8
25.1
45.0
81.8
51.9
74.2
50.3
46.3
22.5
30.1
19.8
18.7
21.5
..
Part III. Development outcomes
99
Table
Participating in growth
9.2
Labor force composition
Sectora
Industry
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Services
Male (% of male
employment)
2000–09 b
Female (% of female
employment)
2000–09 b
Male (% of male
employment)
2000–09 b
Female (% of female
employment)
2000–09 b
Male (% of male
employment)
2000–09 b
Female (% of female
employment)
2000–09 b
..
..
..
35.1
..
..
53.1
..
..
..
..
..
..
..
..
..
..
8.7
..
..
..
..
..
..
..
..
81.5
..
49.8
..
9.9
..
22.7
..
..
..
30.6
34.1
..
66
..
5.4
..
..
71.2
..
61.8
65.2
..
30.9
20.4
28.3
..
34.8
..
..
..
..
24.3
..
..
68.4
..
..
..
..
..
..
..
..
..
..
10.3
..
..
..
..
..
..
..
..
82.5
..
29.9
..
7.6
..
8.2
..
..
..
22.8
33
..
71.1
..
3.4
..
..
78
..
75.7
78.6
..
49.7
22.3
43.3
..
60.2
..
..
..
..
19.2
..
..
14.1
..
..
..
..
..
..
..
..
..
..
25.4
..
..
..
..
..
..
..
..
5.1
..
17.8
..
35.5
..
24.3
..
..
..
26.3
20.2
..
10.3
..
31.2
..
..
7.3
..
10.3
8.8
..
24.8
25.6
25.8
..
23.8
..
..
..
..
10.8
..
..
3.9
..
..
..
..
..
..
..
..
..
..
19.5
..
..
..
..
..
..
..
..
1.6
..
14.7
..
25.8
..
9.1
..
..
..
5.9
4.9
..
2.5
..
12.5
..
..
2.8
..
5.3
2
..
9
28.2
6
..
15.1
..
..
..
..
45.5
..
..
25.5
..
..
..
..
..
..
..
..
..
..
75.6
..
..
..
..
..
..
..
..
13.4
..
32.4
..
53.9
..
48.7
..
..
..
42.6
32.5
..
23.4
..
57.3
..
..
21.5
..
27.6
26
..
44.1
53.8
45.6
..
41.2
..
..
..
..
64.8
..
..
22.5
..
..
..
..
..
..
..
..
..
..
63.9
..
..
..
..
..
..
..
..
15.9
..
55.3
..
66.1
..
63.1
..
..
..
70.7
42
..
26.3
..
79.1
..
..
19.2
..
19.2
18.4
..
41.2
49.4
50.6
..
24.5
..
a. Components may not sum to 100 percent because of unclassified data.
b. Data are for the most recent year available during the period specified.
100
Part III. Development outcomes
l aBor, MiGration, and population
Wage and salaried workers
Total
Male
Female
(% of total
(% of males
(% of females
employed)
employed)
employed)
2000–09 b
2000–09 b
2000–09 b
..
..
..
73.2
..
..
19.2
38.9
..
..
..
..
..
..
..
..
..
46.3
..
..
..
..
..
..
..
..
13.4
..
13.6
..
79.2
..
81.3
..
..
..
..
..
..
7.6
..
82.4
..
..
10.5
..
14.5
18.7
37.7
55.9
59.8
61.8
..
44.8
64.3
..
..
..
74.4
..
..
29.3
43.8
..
..
..
..
..
..
..
..
..
49.3
..
..
..
..
..
..
..
..
16
..
15.2
..
77.2
..
82.2
..
..
..
..
..
..
11.3
..
83.5
..
..
15.3
..
22.2
25.7
51
58.6
61.9
63.7
..
48.8
..
l aBor, MiGration, and population
..
..
..
71.9
..
..
8.7
33
..
..
..
..
..
..
..
..
..
42.7
..
..
..
..
..
..
..
..
10.8
..
11.4
..
83.2
..
80.3
..
..
..
..
..
..
3.7
..
80.8
..
..
6.1
..
7.5
9
23.1
46.5
49.8
53.7
..
34.1
..
Statusa
Self-employed workers
Total
Male
Female
(% of total
(% of males
(% of females
employed)
employed)
employed)
2000–09 b
2000–09 b
2000–09 b
..
..
..
12.2
..
..
59.3
31.8
..
..
..
..
..
..
..
..
..
42.8
..
..
..
..
..
..
..
..
43.7
..
71.4
..
18
..
22.3
..
..
..
..
..
..
..
..
17
..
..
78.1
..
59.4
59.7
50.4
26.4
31.7
25.1
..
28.9
26.8
..
..
..
8.1
..
..
57
32.6
..
..
..
..
..
..
..
..
..
41.8
..
..
..
..
..
..
..
..
51.6
..
66.4
..
21.2
..
20.4
..
..
..
..
..
..
..
..
16
..
..
75
..
67.5
49
38.6
30.3
30.7
27.7
..
34.5
..
..
..
..
16.8
..
..
61.7
30.9
..
..
..
..
..
..
..
..
..
44
..
..
..
..
..
..
..
..
35.4
..
78.4
..
11.6
..
26.6
..
..
..
..
..
..
..
..
18.3
..
..
80.9
..
52.1
29.2
63.2
12.8
36.6
13.7
..
13.9
..
Contributing family workers
Total
Male
Female
(% of total
(% of males
(% of females
employed)
employed)
employed)
2000–09 b
2000–09 b
2000–09 b
..
..
..
2.2
..
..
18.2
10.3
..
..
..
..
..
..
..
..
..
10
..
..
..
..
..
..
..
..
52.3
..
15
..
2.2
..
1
..
..
..
..
..
..
18.1
..
0.4
..
..
11.4
..
26.1
19.6
11.9
17.6
8.2
13.1
..
26.1
8.7
..
..
..
2.2
..
..
9.5
6.5
..
..
..
..
..
..
..
..
..
7.8
..
..
..
..
..
..
..
..
32.1
..
18.4
..
0.9
..
0.9
..
..
..
..
..
..
14.8
..
0.3
..
..
9.7
..
10.3
25.4
10.4
11.2
7.1
8.6
..
16.5
..
..
..
..
2.2
..
..
27.2
14.8
..
..
..
..
..
..
..
..
..
12.7
..
..
..
..
..
..
..
..
73
..
10.2
..
4.7
..
1.1
..
..
..
..
..
..
21.6
..
0.6
..
..
13
..
40.5
61.8
13.6
40.6
13.6
32.6
..
51.8
..
Part III. Development outcomes
101
Table
Participating in growth
9.3
Unemployment
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Total
2000–09 b
Unemployment
(% ages 15 and older)
Male
2000–09 b
Total
2000–09 b
Youth unemployment
(% ages 15–24)
Male
2000–09 b
Female
2000–09 b
Female
2000–09 b
..
0.7
17.6
..
..
2.9
..
..
..
..
..
..
..
59.5
..
..
20.5
..
..
10.4
..
..
..
..
5.6
2.6
7.8
8.8
33.0
7.3
..
37.6
1.5
..
..
16.7
10.0
5.5
3.4
..
23.8
..
..
4.3
..
3.2
12.9
4.2
..
0.9
15.3
..
..
2.5
..
..
..
..
..
..
..
54.6
..
..
12.1
..
..
10.1
..
..
..
..
6.8
1.7
5.4
7.2
8.8
4.4
..
32.5
1.7
..
..
11.0
7.9
6.1
4.5
..
22.0
..
..
2.8
..
2.5
14.1
4.2
..
0.4
19.9
..
..
3.3
..
..
..
..
..
..
..
68.6
..
..
29.9
..
..
10.7
..
..
..
..
4.2
3.5
10.0
10.9
41.2
12.3
..
43.0
0.9
..
..
24.5
13.6
4.9
2.3
..
25.9
..
..
5.8
..
3.9
11.3
4.1
..
0.8
13.6
..
..
..
..
..
..
..
..
..
..
..
..
..
24.9
..
..
16.6
..
..
..
..
4.7
2.3
..
..
..
21.4
..
41.7
3.2
..
..
..
14.8
20.3
5.2
..
48.2
..
..
8.8
..
..
21.4
24.9
..
1.1
13.2
..
..
..
..
..
..
..
..
..
..
..
..
..
19.5
..
..
16.4
..
..
..
..
5.7
1.7
..
..
..
18.1
..
36.7
4.0
..
..
..
11.9
..
7.3
..
44.6
..
..
7.4
..
..
23.1
28.2
..
0.6
14.0
..
..
..
..
..
..
..
..
..
..
..
..
..
29.4
..
..
16.7
..
..
..
..
3.7
2.8
..
..
..
26.2
..
47.0
1.7
..
..
..
20.1
..
3.5
..
52.5
..
..
10.1
..
..
19.5
21.4
11.3
9.4
..
10.0
14.2
11.0
5.2
..
9.8
13.1
10.1
22.9
..
10.5
17.3
24.3
24.8
..
21.9
30.7
42.8
17.2
..
22.8
31.4
46.3
47.9
..
19.4
29.3
a. Components may not sum to 100 percent because of unclassified data.
b. Data are for the most recent year available during the period specified.
102
Part III. Development outcomes
l aBor, MiGration, and population
Unemployment by education levela
(% of total unemployed)
Secondary
Total
Male
Female
2000–09 b
2000–09 b
2000–09 b
Total
2000–09 b
Primary
Male
2000–09 b
Female
2000–09 b
..
..
65.5
47.0
..
..
..
..
..
..
..
..
..
..
..
..
35.9
..
..
..
..
..
..
..
..
43.9
..
..
..
44.2
..
..
..
..
60.7
..
40.2
..
..
..
36.2
..
..
..
..
..
..
..
..
..
64.4
44.4
..
..
..
..
..
..
..
..
..
..
..
..
50.6
..
..
..
..
..
..
..
..
42.9
..
..
..
49.5
..
..
..
..
62.8
..
42.2
..
..
..
39.8
..
..
..
..
..
..
..
..
..
66.3
58.3
..
..
..
..
..
..
..
..
..
..
..
..
30.8
..
..
..
..
..
..
..
..
44.4
..
..
..
39.7
..
..
..
..
59.4
..
37.9
..
..
..
32.9
..
..
..
..
..
..
..
..
..
27.3
19.7
..
..
..
..
..
..
..
..
..
..
..
..
13.3
..
..
..
..
..
..
..
..
23.8
..
..
..
48.5
..
..
..
..
24.1
..
6.9
..
..
..
56.3
..
..
..
..
..
..
..
..
..
23.9
16.7
..
..
..
..
..
..
..
..
..
..
..
..
19.0
..
..
..
..
..
..
..
..
25.8
..
..
..
41.4
..
..
..
..
23.0
..
7.5
..
..
..
52.7
..
..
..
..
..
..
..
59.3
..
..
51.1
41.4
65.2
..
..
57.7
46.0
32.5
..
..
36.6
31.9
23.0
..
..
22.4
37.7
21.4
..
..
21.7
37.3
l aBor, MiGration, and population
Total
2000–09 b
Tertiary
Male
2000–09 b
Female
2000–09 b
..
..
30.2
33.3
..
..
..
..
..
..
..
..
..
..
..
..
11.3
..
..
..
..
..
..
..
..
22.7
..
..
..
53.2
..
..
..
..
24.9
..
6.2
..
..
..
59.7
..
..
..
..
..
..
..
..
..
..
6.1
..
..
..
..
..
..
..
..
..
..
..
..
3.2
..
..
..
..
..
..
..
..
9.3
..
..
..
6.4
..
..
..
..
5.9
..
2.5
..
..
..
4.5
..
..
..
..
..
..
..
..
..
..
5.6
..
..
..
..
..
..
..
..
..
..
..
..
5.7
..
..
..
..
..
..
..
..
14.0
..
..
..
8.1
..
..
..
..
0.5
..
2.8
..
..
..
4.0
..
..
..
..
..
..
..
..
..
..
8.3
..
..
..
..
..
..
..
..
..
..
..
..
2.3
..
..
..
..
..
..
..
..
6.6
..
..
..
3.5
..
..
..
..
9.4
..
2.1
..
..
..
5.0
..
..
..
..
..
..
..
30.4
..
..
23.9
38.5
11.4
..
..
21.6
13.6
6.6
..
..
16.2
9.0
33.0
..
..
33.5
23.3
Part III. Development outcomes
103
Table
Participating in growth
9.4
Migration and population
Migrant stock
Share of
population (%)
Total
2005
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
104
2.1
0.3
2.4
4.4
5.6
1.1
1.2
2.3
1.8
3.6
2.3
0.8
3.8
12.3
13.7
1
0.3
0.7
17.9
15.2
7.6
4.4
1.3
2.2
0.3
2.9
0.2
2
1.4
2.2
3.3
1.9
6.6
1.4
0.7
4.8
3.5
2
10.2
3
0.3
2.6
1.7
3.4
2
3.1
2.3
2.4
3.1
0.8
0.7
0.3
10.4
0.2
0.3
Part III. Development outcomes
International migration
Worker remittances, Migrant remittance
received
inflows
Net
Total
Share of
Total
Share of
migration ($ millions) GDP (%) ($ millions) GDP (%)
2005
2009
2009
2009
2009
16,338,433 –1,599,939
..
56,055
175,000
0.2
187,584
98,831
..
80,148
20,000
61.6
772,814
100,000
..
81,566
191,600
28.2
211,880
–12,121
129.2
11,183
–12,500
145.8
75,623
–45,000
..
358,446
218,966
..
13,661
–10,000
..
480,105 –236,676
..
128,838
3,527
..
2,371,277 –338,732
..
110,333
0
6.0
5,800
15,000
..
14,612
229,376
..
554,021 –340,460
261.6
244,550
9,566
..
231,739
31,127
72.2
1,669,267
11,690
114.5
401,217 –425,000
50.5
19,219
1,181
..
790,071
25,144
631.5
6,247
–36,000
28.5
96,793
62,452
7.0
39,699
–5,000
..
278,806
–30,000
..
165,448
–134,204
..
66,053
30,000
..
40,824
0
..
406,075
–20,000
31.5
131,630
–1,000
5.3
182,960
–28,497
..
972,126
–170,000 18230.2
435,749
5,931
88.1
5,387
–7,000
2.0
220,208 –100,000
..
8,441
..
11.6
152,101
336,000
32.7
21,271 –200,000
..
1,248,732
700,001
..
639,686
–531,781
..
38,574
–46,077
2.0
797,701 –345,000
11.9
182,823
–3,570
..
652,408
–5,000
749.7
287,337
–81,713
41.3
391,345 –700,000
..
1,192,628 –1,048,004 15145.3
242,446
–140,000
..
246,745
–291,405 7149.6
617,536
14,000
0.0
51,020 –550,000 6269.1
34,881
–80,599 1726.6
..
0.0
..
0.5
..
2.1
0.6
9.4
..
..
..
..
..
..
0.6
..
..
0.9
..
9.8
0.4
1.2
..
2.1
1.8
0.8
..
..
..
..
..
0.3
0.1
..
10.5
1.7
1.0
..
1.5
1.7
..
..
..
0.1
0.1
..
4.7
0.3
..
4.0
..
3.8
0.0
6.9
4.4
20,791.3
..
251.3
87.9
99.3
28.2
147.6
146.2
..
..
..
..
14.8
185.5
32.5
..
..
261.6
..
79.8
114.5
63.7
49.5
1,686.2
414.1
25.1
..
..
431.0
..
211.2
111.1
13.6
93.7
9,584.8
92.6
2.0
1,364.7
12.5
46.7
..
902.3
2,992.7
93.5
23.3
337.1
749.7
41.3
..
17,458.3
2,058.7
7,149.6
16.0
6,269.5
1,964.5
2.2
..
3.8
0.7
1.2
2.1
0.7
9.4
..
..
..
..
0.2
0.8
3.1
..
..
0.9
..
10.9
0.4
1.6
5.9
5.7
26.2
2.9
..
..
4.8
..
2.5
1.1
0.1
1.7
5.5
1.8
1.0
10.6
1.6
2.4
..
0.3
5.5
3.1
0.1
11.8
4.7
0.3
..
3.3
1.5
3.8
0.0
6.9
5.0
Population
Population dynamics
Annual Fertility rate
Total
Male
Female growth rate (births per
(millions) (% of total) (% of total)
(%)
woman)
2009
2009
2009
2009
2009
841.0
18.5
8.9
1.9
15.8
8.3
19.5
0.5
4.4
11.2
0.7
66.0
3.7
21.1
0.9
0.7
5.1
82.8
1.5
1.7
23.8
10.1
1.6
39.8
2.1
4.0
19.6
15.3
13.0
3.3
1.3
22.9
2.2
15.3
154.7
10.0
0.2
12.5
0.1
5.7
9.1
49.3
42.3
1.2
43.7
6.6
32.7
12.9
12.5
166.7
34.9
83.0
6.4
32.0
10.4
49.8
49.3
50.5
50.0
49.9
49.0
50.0
47.8
49.1
49.7
50.2
49.6
49.9
50.9
50.0
49.6
49.2
49.7
50.0
49.6
50.7
50.5
49.5
50.0
47.2
49.7
49.8
49.7
49.4
50.7
49.6
48.6
49.3
50.1
50.1
48.4
49.5
49.6
..
48.7
49.6
49.3
50.4
48.9
49.9
49.5
50.1
49.9
48.3
50.2
50.5
50.3
51.7
49.1
50.3
50.2
50.7
49.5
50.0
50.1
51.0
50.0
52.2
50.9
50.3
49.8
50.4
50.1
49.1
50.0
50.4
50.8
50.3
50.0
50.4
49.3
49.5
50.5
50.0
52.8
50.3
50.2
50.3
50.6
49.3
50.4
51.4
50.7
49.9
49.9
51.6
50.5
50.4
..
51.3
50.4
50.7
49.6
51.1
50.1
50.5
49.9
50.1
51.7
49.8
49.5
49.7
48.3
50.9
49.7
2.5
2.6
3.1
1.5
3.4
2.8
2.2
1.4
1.9
2.6
2.4
2.7
1.9
2.3
1.7
2.6
2.9
2.6
1.8
2.7
2.1
2.4
2.2
2.6
0.8
4.2
2.7
2.8
2.4
2.3
0.5
2.3
1.9
3.9
2.3
2.8
1.6
2.6
1.2
2.4
2.3
1.1
2.2
1.5
2.9
2.4
3.3
2.5
0.5
1.6
1.5
1.8
2.0
1.2
1.0
5.0
5.6
5.4
2.8
5.8
4.5
4.5
2.7
4.7
6.1
3.9
5.9
4.3
4.5
3.8
5.3
4.5
5.2
3.2
5.0
3.9
5.3
5.7
4.9
3.3
5.8
4.6
5.5
6.5
4.4
1.5
5.0
3.3
7.1
5.6
5.3
3.7
4.7
2.3
5.2
6.4
2.5
4.1
3.5
5.5
4.2
6.3
5.7
3.4
2.6
2.3
2.8
2.6
2.3
2.1
l aBor, MiGration, and population
Population
Age composition (% of total)
Ages 0–14
Ages 15–64
Ages 65 and older
Total
2009
Male
2009
Female
2009
Total
2009
Male
2009
Female
2009
Total
2009
Male
2009
Female
2009
42.6
45.0
43.1
33.3
46.3
38.4
40.9
36.2
40.6
45.7
38.1
46.7
40.5
40.6
36.1
41.0
41.5
43.5
36.1
42.3
38.4
42.8
42.6
42.8
38.8
42.7
42.9
46.2
44.2
39.5
22.6
44.0
36.9
49.9
42.5
42.3
40.7
43.6
..
43.4
44.9
30.5
39.1
39.3
44.7
39.9
48.9
46.2
39.9
29.9
27.3
32.3
30.1
28.4
23.2
43.1
45.4
43.4
33.6
47.2
39.2
41.2
38.0
41.2
46.2
38.6
47.2
40.8
40.1
36.4
41.5
42.6
44.0
36.5
42.9
38.8
43.2
43.2
43.1
41.4
43.3
43.2
46.9
45.2
40.1
23.2
45.4
37.6
50.9
43.0
43.3
41.5
44.3
..
44.4
45.4
31.1
39.6
40.4
45.2
40.3
49.1
46.6
41.4
30.4
27.7
32.9
29.8
29.4
23.8
42.0
44.5
42.7
33.0
45.4
37.6
40.6
34.5
40.1
45.3
37.7
46.2
40.1
41.3
35.7
40.5
40.5
43.1
35.8
41.7
38.0
42.4
42.1
42.5
36.6
42.1
42.6
45.5
43.2
38.9
22.1
42.7
36.2
48.9
42.0
41.3
39.8
42.8
..
42.5
44.4
29.9
38.7
38.3
44.2
39.5
48.6
45.9
38.5
29.3
27.0
31.8
30.5
27.4
22.6
54.3
52.6
53.7
62.9
51.7
58.8
55.5
59.6
55.5
51.4
58.8
50.7
55.7
55.5
60.7
56.1
56.0
53.3
59.5
54.9
58.0
54.0
53.9
54.6
56.4
54.2
54.0
50.7
53.5
57.9
70.1
52.8
59.5
48.1
54.3
55.2
55.4
54.0
..
54.8
52.4
65.0
57.3
57.3
52.2
56.6
48.6
50.7
56.0
65.3
68.1
63.1
65.6
66.3
70.0
54.1
52.4
54.0
63.3
51.2
58.6
55.5
59.0
55.3
51.3
58.7
50.5
55.7
56.0
60.7
55.9
55.5
53.1
59.5
54.5
57.8
54.0
53.7
54.5
54.4
53.9
53.9
50.2
52.7
57.8
70.9
51.8
59.3
47.3
54.1
54.7
55.0
53.4
..
53.8
52.1
65.3
57.1
56.7
52.0
56.5
48.6
50.6
54.9
65.2
68.2
63.0
66.1
65.7
69.9
54.5
52.8
53.4
62.5
52.2
59.1
55.5
60.2
55.6
51.6
58.9
50.8
55.8
55.0
60.7
56.4
56.5
53.5
59.6
55.3
58.1
53.9
54.1
54.6
58.2
54.5
54.2
51.2
54.4
57.9
69.3
53.7
59.7
48.9
54.6
55.8
55.7
54.7
..
55.7
52.7
64.7
57.4
57.9
52.4
56.6
48.6
50.8
57.0
65.4
67.9
63.3
65.1
66.8
70.2
3.1
2.5
3.2
3.8
2.0
2.8
3.6
4.2
3.9
2.8
3.1
2.6
3.8
3.9
3.2
2.9
2.5
3.2
4.3
2.8
3.6
3.3
3.5
2.6
4.7
3.1
3.0
3.1
2.3
2.7
7.3
3.3
3.6
2.0
3.1
2.5
4.0
2.4
..
1.8
2.7
4.5
3.6
3.3
3.1
3.5
2.5
3.0
4.1
4.8
4.6
4.6
4.2
5.4
6.7
2.8
2.2
2.6
3.1
1.6
2.2
3.2
3.0
3.5
2.6
2.7
2.3
3.5
4.0
2.9
2.6
1.9
2.9
4.0
2.6
3.4
2.8
3.2
2.4
4.2
2.8
2.9
2.9
2.2
2.1
5.9
2.9
3.1
1.8
2.9
2.1
3.5
2.3
..
1.8
2.5
3.5
3.3
2.9
2.8
3.1
2.3
2.8
3.7
4.4
4.1
4.1
4.1
4.9
6.2
3.4
2.7
3.9
4.5
2.4
3.3
3.9
5.3
4.3
3.1
3.4
3.0
4.2
3.7
3.6
3.2
3.0
3.4
4.7
3.0
3.8
3.7
3.8
2.8
5.2
3.4
3.2
3.3
2.4
3.2
8.6
3.7
4.1
2.2
3.4
2.9
4.4
2.5
..
1.8
3.0
5.4
3.9
3.8
3.4
3.9
2.8
3.3
4.5
5.3
5.1
5.0
4.4
5.8
7.2
l aBor, MiGration, and population
Geographic distribution (%)
Dependency
ratio
Share
of
total
population
Annual growth
(% of
Rural
Urban
Rural
Urban
working-age
population) population population population population
2009
2009
2009
2009
2009
84.8
90.2
86.2
58.9
93.5
70.0
80.1
67.8
80.2
94.4
70.1
97.3
79.5
80.2
64.8
78.2
78.5
87.6
68.0
82.2
72.5
85.3
85.5
83.3
77.3
84.6
85.0
97.2
86.8
72.9
42.7
89.6
68.0
108.0
84.0
81.0
80.6
85.0
..
82.6
90.9
53.8
74.6
74.5
91.6
76.7
105.8
97.1
78.5
53.4
46.9
58.4
52.4
50.9
42.8
63.0
42.4
58.4
39.7
80.0
89.3
42.4
39.6
61.3
72.9
71.9
65.4
38.3
50.6
12.3
60.5
78.8
82.7
14.5
42.7
49.2
65.1
70.1
78.1
73.8
39.2
70.1
80.7
67.3
58.8
57.5
62.4
62.6
83.4
50.9
81.4
38.6
57.4
45.2
61.9
63.0
38.8
55.7
74.8
74.0
57.3
86.9
64.4
62.2
46.9
34.1
57.2
22.3
43.6
33.1
37.0
57.6
41.6
60.3
20.0
10.7
57.6
60.4
38.7
27.1
28.1
34.6
61.7
49.4
87.7
39.5
21.2
17.3
85.5
57.3
50.8
34.9
29.9
21.9
26.2
60.8
29.9
19.3
32.7
41.2
42.5
37.6
37.4
16.6
49.1
18.6
61.4
42.6
54.8
38.1
37.0
61.2
44.3
25.2
26.0
42.7
13.1
35.6
37.8
53.1
65.9
42.8
77.7
56.4
66.9
1.7
0.5
2.4
–0.4
2.9
2.5
0.3
–0.5
1.6
2.0
2.3
1.8
0.9
1.0
–1.5
2.3
2.4
2.2
–1.5
0.7
0.6
1.6
2.1
2.3
–0.1
2.5
2.2
2.2
1.5
2.0
0.4
1.0
1.0
3.8
0.9
2.5
–0.5
2.2
0.1
1.9
1.6
–0.2
0.6
1.1
2.3
1.2
3.1
2.2
–0.3
1.1
–0.3
1.7
1.2
0.4
–0.2
3.8
4.2
4.1
2.7
5.5
5.6
3.7
2.6
2.3
4.4
2.6
4.5
2.5
3.7
2.2
3.0
5.0
4.3
2.4
4.2
3.5
3.8
2.5
4.0
3.6
5.3
3.8
5.4
4.1
2.8
0.6
4.4
3.5
4.4
3.8
4.3
2.9
3.2
2.0
3.3
3.5
1.9
4.2
2.6
4.6
4.1
4.5
2.9
1.8
2.0
2.5
1.9
2.2
1.8
1.6
Part III. Development outcomes
105
Table
Participating in growth
10.1
HIV/AIDS
Estimated HIV prevalence rate (%)
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
106
Estimated number of people
living with HIV/AIDS
(thousands)
1990
2000
2009
Point estimate
1990
2000
2009
Adults (ages 15–49)
Low estimate
1990
2000
2009
1990
28
6
23
160
93
33
..
44
31
<1.0
..
63
140
3
<0.5
5
..
4
<1.0
22
34
1
400
6
3
12
310
15
2
<0.5
76
11
4
590
160
..
6
..
<0.5
2
140
12
9
600
11
870
500
510
140
49
260
150
170
460
..
190
130
<0.1
..
68
640
12
4
25
..
34
4
250
78
13
1,500
240
52
17
850
91
8
3
750
150
51
2,600
170
..
30
..
21
9
4,200
61
120
1,400
99
980
810
1,700
200
60
320
110
180
610
..
130
210
<0.5
..
77
450
14
20
25
..
46
18
260
79
22
1,500
290
37
24
920
76
14
9
1,400
180
61
3,300
170
..
59
..
49
34
5,600
..
180
1,400
120
1,200
980
1,200
0.5
0.2
3.5
3.9
3.9
0.6
..
3.1
1.1
<0.1
..
5.2
2.4
0.9
0.1
0.3
..
0.9
0.1
0.3
1.1
0.3
3.9
0.8
0.3
0.2
7.2
0.4
0.2
<0.1
1.2
1.6
0.1
1.3
5.2
..
0.2
..
<0.1
0.1
0.7
0.1
2.3
4.8
0.6
10.2
12.7
10.1
1.9
1.4
26.0
2.3
5.2
5.5
2.0
1.2
24.8
1.2
3.3
5.3
..
4.7
3.4
0.1
..
3.4
3.4
2.5
5.0
0.8
..
5.2
2.0
1.8
1.3
2.5
6.3
23.6
1.5
0.2
11.0
1.0
0.7
1.0
11.5
13.1
0.8
3.6
2.9
..
0.9
..
1.6
0.7
17.8
1.1
25.9
5.6
3.2
6.5
13.5
14.3
0.2
<0.1
2.9
2.6
3.7
0.3
..
2.0
0.5
<0.1
1.2
3.6
1.3
<0.1
<0.1
0.1
..
0.6
0.1
0.2
0.5
0.1
3.0
0.6
0.1
0.2
3.3
0.1
0.1
<0.1
0.9
0.9
0.1
0.2
4.3
..
0.1
..
<0.1
<0.1
0.6
<0.1
1.8
4.3
0.1
8.6
3.4
8.7
1.4
1.2
25.1
1.9
5.1
5.0
..
8.4
2.0
<0.1
1.1
3.5
6.2
2.0
1.0
0.9
..
4.1
0.3
2.0
1.1
1.5
8.6
23.0
2.2
0.2
13.0
1.3
0.5
0.2
7.8
12.9
1.0
3.3
3.5
..
0.5
..
0.4
<0.1
15.7
0.1
21.0
6.9
2.8
6.7
13.8
23.8
1.6
1.0
23.8
1.0
2.9
4.9
..
4.2
2.8
0.1
1.2
3.1
3.1
..
3.5
0.6
..
4.2
1.3
1.6
1.1
2.0
5.8
22.3
1.3
0.2
10.0
0.8
0.6
0.7
10.6
11.1
0.8
3.3
2.5
..
0.7
..
1.4
0.5
17.2
0.9
24.9
5.3
2.5
5.9
12.8
13.4
1.4
3.7
4.2
4.8
4.0
2.4
..
6.2
2.0
<0.1
1.6
6.4
7.2
3.5
0.2
0.9
..
1.5
1.7
1.5
7.6
0.4
6.6
1.2
0.6
0.2
10.8
2.0
0.2
0.2
1.5
2.3
0.1
2.1
8.4
..
0.2
..
<0.1
0.3
0.9
0.4
2.7
5.3
1.2
11.5
26.4
11.7
2.4
1.7
27.1
2.7
5.4
6.0
..
11.4
4.0
<0.1
1.5
4.5
7.6
4.1
2.5
1.6
..
6.6
1.1
2.6
2.7
2.2
9.6
26.1
4.5
0.2
15.5
2.0
0.7
0.4
9.4
18.1
1.0
4.3
4.6
..
0.7
..
1.6
0.3
16.6
0.5
23.6
8.0
4.3
7.7
15.2
26.1
2.4
1.3
25.8
1.5
3.5
5.8
..
5.2
5.1
0.1
1.6
3.8
3.9
3.2
6.6
1.0
..
6.2
2.9
2.0
1.6
3.0
6.5
25.2
1.8
0.3
12.1
1.3
0.9
1.3
12.2
15.5
0.9
4.0
3.3
..
1.0
..
2.1
1.0
18.3
1.4
27.0
6.1
3.8
6.9
14.1
15.4
..
<0.5
..
3
<0.2
6
3
..
13
<1.0
18
11
..
3
2
<0.1
<0.1
..
<0.1
<0.1
<0.1
<0.1
0.1
<0.1
..
0.1
<0.1
<0.1
<0.1
..
<0.1
<0.1
<0.1
<0.1
..
0.1
<0.1
0.1
<0.1
..
0.1
<0.1
<0.1
<0.1
..
<0.1
<0.1
<0.1
<0.1
..
0.1
<0.1
0.1
<0.1
..
0.2
0.1
Part III. Development outcomes
9.4
3.0
<0.1
...
3.9
6.9
2.9
1.5
1.2
...
5.2
0.5
2.3
1.7
1.8
9.0
24.5
3.3
0.2
14.2
1.7
0.6
0.3
8.6
15.3
1.0
3.9
3.8
0.6
0.9
0.2
16.1
0.3
22.3
7.3
3.6
7.3
14.4
24.8
0.1
<0.1
High estimate
2000
2009
Hiv/aids
Estimated HIV prevalence rate (%)
Point estimate
2009
Young men
(ages 15–24)
Low estimate
2009
High estimate
2009
Point estimate
2009
Young women
(ages 15–24)
Low estimate
2009
High estimate
2009
0.6
0.3
5.2
0.5
1.0
1.6
..
1.0
1.0
0.1
..
1.2
0.7
0.8
1.9
0.2
..
1.4
0.9
0.5
0.4
0.8
1.8
5.4
0.3
0.1
3.1
0.2
0.4
0.3
3.1
2.3
0.2
1.2
1.3
..
0.3
..
0.6
0.4
4.5
0.5
6.5
1.7
0.9
2.3
4.2
3.3
0.4
0.2
3.7
0.3
0.8
1.2
..
0.6
0.7
0.1
0.4
0.9
0.5
..
1.0
0.1
..
0.8
0.5
0.4
0.3
0.5
1.3
4.1
0.1
0.1
2.3
0.1
0.2
0.2
2.4
1.3
0.2
0.9
0.9
..
0.2
..
0.3
..
4.1
..
4.8
1.3
0.6
1.8
3.2
2.5
0.9
0.4
7.3
0.6
1.2
2.1
..
1.4
2.0
0.1
0.6
1.6
1.1
..
3.2
0.3
..
2.0
1.6
0.7
0.6
1.1
2.4
7.4
0.5
0.4
4.2
0.4
1.4
0.4
4.4
3.6
0.3
1.6
1.6
..
0.4
..
1.0
..
5.0
..
8.8
2.3
1.2
2.8
5.5
4.4
1.6
0.7
11.8
0.8
2.1
3.9
..
2.2
2.5
<0.1
..
2.6
1.5
1.9
5.0
0.4
..
3.5
2.4
1.3
0.9
2.0
4.1
14.2
0.7
0.1
6.8
0.5
0.3
0.2
8.6
5.8
0.5
2.9
1.9
..
0.7
..
1.5
0.6
13.6
1.3
15.6
3.9
2.2
4.8
8.9
6.9
1.1
0.5
9.0
0.6
1.6
3.1
..
1.4
1.7
<0.1
0.9
2.1
1.1
..
2.7
0.2
..
2.1
1.4
0.9
0.6
1.5
3.0
11.2
0.2
<0.1
5.3
0.2
0.1
0.1
7.0
3.7
0.4
2.3
1.3
..
0.5
..
0.9
..
12.3
..
12.6
3.1
1.5
4.0
7.3
5.3
2.2
1.1
15.9
1.2
2.7
5.4
..
3.1
5.2
<0.1
1.5
3.6
2.3
..
7.9
0.7
..
5.2
4.0
1.8
1.3
2.9
5.4
19.2
1.2
0.1
9.2
0.9
0.5
0.3
12.1
8.6
0.6
3.9
2.3
..
1.0
..
2.5
..
15.0
..
21.3
5.3
3.1
6.4
12.0
9.3
0.1
<0.1
..
0.1
<0.1
<0.1
<0.1
..
<0.1
<0.1
0.2
<0.1
..
0.3
0.1
<0.1
<0.1
..
0.1
<0.1
<0.1
<0.1
..
<0.1
<0.1
0.1
<0.1
..
0.1
<0.1
(continued)
Hiv/aids
Part III. Development outcomes
107
Table
Participating in growth
10.1
HIV/AIDS (continued)
Deaths of adults and children due to HIV/AIDS
(thousands)
Point estimate
Low estimate
High estimate
1990 2000 2009
1990 2000 2009
1990 2000 2009
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
108
<1.0
<0.2
<1.0
6.7
3.9
<1.0
..
1.0
1.4
<0.1
..
3.0
3.9
<0.1
<0.1
<0.2
..
<0.2
<0.1
<1.0
1.1
<0.1
10.0
..
<0.1
<1.0
11.0
<0.5
<0.1
<0.1
2.2
<0.5
<0.2
10.0
8.4
..
<0.5
..
<0.1
<0.2
2.9
<1.0
<0.5
21.0
<0.5
37.0
23.0
14.0
<0.1
<0.1
..
<0.2
<0.1
9.2
11.0
3.0
2.7
13.0
5.8
15.0
7.1
14.0 15.0
27.0
37.0
..
..
14.0
11.0
7.9
11.0
<0.1 <0.1
..
..
5.7
5.1
48.0 36.0
<1.0
1.0
<0.2 <1.0
1.6
1.7
..
..
1.8
2.4
<0.2 <1.0
15.0 18.0
6.1
4.7
<1.0
1.2
120.0 80.0
12.0 14.0
3.5
3.6
1.3
1.7
64.0 51.0
6.9
4.4
<0.5 <1.0
<0.1 <0.5
36.0 74.0
6.7
6.7
2.9
4.3
200.0 220.0
15.0
4.1
–
..
1.6
2.6
–
..
<1.0
2.8
<0.5
..
170.0 310.0
3.0
..
5.7
7.0
110.0 86.0
5.6
7.7
89.0 64.0
66.0 45.0
130.0 83.0
<0.2
<0.2
..
<1.0
<0.1
Part III. Development outcomes
<1.0
<0.5
..
1.2
<0.1
<0.5
5.6
7.7
<0.1
1.7
1.8
<0.5
11.0
2.3
4.1
11.0
4.8
3.1
11.0 12.0
<0.5 22.0 29.0
..
..
..
<1.0
11.0
8.8
<1.0
4.7
8.1
<0.1 <0.1 <0.1
12.0 23.0 26.0
<1.0
4.8
4.1
2.1 34.0 29.0
<0.1 <0.5 <1.0
<0.1 <0.2 <1.0
<0.1 <1.0
1.0
..
..
..
<0.1
1.4
1.6
<0.1 <0.1 <0.5
<0.5
11.0 14.0
<0.5
2.5
3.1
<0.1 <0.5 <1.0
6.7 98.0 61.0
<0.1 10.0 10.0
<0.1
2.0
2.8
<1.0
1.0
1.4
4.1 53.0 38.0
<0.1
3.8
3.0
<0.1 <0.5 <1.0
<0.1 <0.1 <0.5
1.5 28.0
57.0
<0.2
5.1
2.5
<0.1
2.3
3.3
<0.5 110.0 170.0
5.6 12.0 <1.0
..
..
<0.2
1.3
1.9
..
..
<0.1 <0.5
2.1
<0.1 <0.1
..
2.0 140.0 260.0
<0.1 <0.5
..
<0.2
4.7
4.6
16.0 90.0 69.0
<0.1
3.8
5.3
22.0 76.0 49.0
<1.0 55.0 30.0
9.7 110.0 70.0
3.2
18.0
<1.0
11.0
4.7
9.3
..
5.8
2.9
<0.1
26.0
6.2
12.0
<1.0
<0.1
<1.0
..
<0.5
<1.0
6.9
15.0
<0.1
22.0
<0.2
<0.2
1.4
22.0
4.3
<0.2
<0.2
3.3
<1.0
<0.2
21.0
13.0
..
<0.5
..
<0.1
<1.0
4.3
3.5
<0.5
27.0
2.0
83.0
46.0
19.0
<0.1
<0.1
..
<0.1
<0.1
<0.1
<1.0
..
0.5
<0.1
<0.1
<0.1
..
<0.5
<0.1
<1.0
<0.5
..
<1.0
<0.1
AIDS orphans
(ages 0–17, thousands)
Low estimate
High estimate
1990 2000 2009 1990 2000
2009
Point estimate
1990 2000 2009
13.0 16.0
2.1
54.0 140.0
5.4
3.7 <0.5
11.0
30.0
16.0 14.0
1.0
45.0
93.0
19.0
9.7 13.0 130.0 140.0
16.0
17.0 10.0 120.0 200.0
33.0 46.0
1.3 100.0 330.0
..
..
..
..
..
20.0 13.0
2.0
69.0 140.0
12.0 15.0
5.1
43.0 120.0
<0.1 <0.1
..
..
<0.1
34.0 40.0
..
..
..
7.1
6.4
6.9
48.0
51.0
65.0 44.0
7.3 230.0 440.0
1.3
1.4
..
..
..
<0.5
1.4 <0.1
<0.5
4.1
2.5
2.5 <0.5
7.0
19.0
..
..
..
..
..
2.5
3.4 <0.2
6.0
18.0
<1.0
1.2 <0.1
<1.0
2.8
20.0 22.0
1.3
47.0 160.0
14.0
6.9
2.5
36.0
59.0
<1.0
1.6 <0.2
2.2
9.7
140.0 99.0
17.0 710.0 1,200.0
15.0 18.0 <0.1
38.0 130.0
5.7
4.6 <0.1
15.0
52.0
1.5
2.0
6.6
9.4
11.0
77.0 67.0 25.0 380.0 650.0
11.0
6.1 <0.5
29.0
59.0
<1.0
1.0 <0.5
1.3
3.6
<0.2 <1.0 <0.1
<0.2
1.0
45.0 92.0
6.6 180.0 670.0
8.8
11.0 <1.0
23.0
70.0
3.5
5.6 <0.5
13.0
57.0
250.0 260.0 12.0 1,100.0 2,500.0
21.0
97.0 32.0 160.0 130.0
..
..
..
..
2.0
3.5 <1.0
7.3
19.0
..
..
..
..
1.9
3.7 <0.1
1.5
15.0
<1.0
..
..
..
..
210.0 390.0
4.4 430.0 1,900.0
6.5
..
..
..
..
7.1 10.0 <1.0
23.0
69.0
130.0 110.0 53.0 750.0 1,300.0
7.4 10.0 <0.5
19.0
66.0
100.0 80.0 280.0 1,000.0 1,200.0
76.0 60.0
74.0 540.0 690.0
150.0
97.0 29.0 670.0 1,000.0
<0.5
<0.5
<1.0
<0.1
1.1
<1.0
..
1.6
<0.2
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
<1.0
<0.1
<1.0
5.2
7.7
<1.0
..
1.2
2.1
..
46.0
<0.2
4.0
..
<0.1
<0.1
..
<0.1
<0.1
<1.0
1.1
<0.1
10.0
<0.1
<0.1
4.0
7.1
<0.1
<0.1
<0.1
2.1
<0.5
<0.5
<0.5
19.0
..
<0.5
..
<0.1
..
2.3
..
<0.5
37.0
<0.1
180.0
<0.1
18.0
..
..
..
..
..
23.0
95.0
3.7
18.0
36.0
71.0
96.0 100.0
98.0 170.0
67.0 270.0
..
..
43.0 110.0
22.0
79.0
..
<0.1
270.0 350.0
31.0
41.0
140.0 330.0
..
..
<0.2
2.5
3.2
12.0
..
..
4.1
12.0
<0.5
1.4
33.0 120.0
9.9
34.0
1.3
7.7
550.0 980.0
29.0 110.0
7.3
34.0
7.3
9.3
280.0 540.0
11.0
36.0
<1.0
2.7
<0.1
<0.5
84.0
..
17.0
50.0
11.0
44.0
300.0 1,800.0
130.0
98.0
..
..
5.4
15.0
..
..
<1.0
9.2
..
..
340.0 1,600.0
..
..
18.0
55.0
610.0 1,100.0
8.5
47.0
800.0 1,000.0
340.0 570.0
550.0 910.0
..
..
..
..
..
..
..
..
..
..
9.9
95.0 200.0
470.0 110.0
53.0
1.7
59.0 120.0
71.0 180.0 170.0
14.0 150.0 230.0
36.0 210.0 420.0
..
..
..
49.0 100.0 180.0
11.0
79.0 170.0
..
..
<0.1
210.0 430.0 510.0
31.0
72.0
66.0
16.0 410.0 550.0
..
..
..
<0.1
<1.0
6.4
2.6
16.0
28.0
..
..
..
<0.5
9.2
25.0
6.6
6.5
6.5
58.0 110.0 210.0
110.0
97.0 120.0
<0.5
3.1
12.0
40.0 960.0 1,400.0
<0.2
51.0 160.0
<0.5
25.0
76.0
12.0
12.0
14.0
68.0 500.0 780.0
15.0
82.0
93.0
<0.5
1.9
4.8
<0.5
<0.5
<1.0
5.6 150.0
..
1.4
33.0
96.0
<0.5
16.0
73.0
94.0 1,700.0 3,100.0
92.0 240.0 180.0
..
..
..
1.4
9.4
25.0
..
..
..
<0.1
5.1
26.0
..
..
..
7.4 550.0 2,400.0
..
..
..
<1.0
29.0
86.0
75.0 940.0 1,500.0
23.0
39.0
89.0
770.0 1,400.0 1,400.0
210.0 740.0 810.0
53.0 840.0 1,200.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
Hiv/aids
HIV-positive pregnant women receiving antiretrovirals to
reduce the risk of mother-to-child transmission
Share of total
(WHO/UNAIDS methodology, %)
Total
Point estimate
Low estimate
High estimate
2009
2009
2009
2009
3,053
1,703
12,406
2,084
1,837
9,092
61
2,157
989
1
2,232
441
11,064
63
365
464
6,721
577
885
3,643
783
383
58,591
8,846
377
17
33,156
1,710
68
41
68,248
6,744
1,737
44,723
7,030
11
917
12
637
..
188,200
245
8,182
58,833
1,451
46,948
47,175
28,208
19
46
>95
32
12
27
..
34
6
..
..
12
54
10
26
34
..
30
..
27
17
24
73
64
16
..
58
..
..
..
70
88
..
22
65
..
..
..
19
..
88
2
88
70
26
53
69
56
12
29
74
19
9
18
..
23
3
10
4
8
36
6
16
21
13
20
43
18
11
16
50
48
10
1
40
26
12
33
51
61
25
15
43
..
16
..
12
0
66
1
68
48
15
37
50
41
36
92
>95
60
22
50
..
67
12
33
11
23
95
21
50
71
40
60
95
53
34
49
95
95
33
5
95
82
37
95
95
95
74
42
95
..
45
..
36
0
95
3
95
95
67
95
95
95
65
11
..
90
3
..
..
..
..
..
14
3
..
13
6
59
10
..
49
25
Hiv/aids
ODA gross disbursements
($ millions)
For social mitigation of HIV/AIDS
For STD control, including HIV/AIDS
2007
2009
2007
2009
76.7
1.8
0.0
2.3
1.0
0.7
0.0
..
0.0
0.0
..
1.2
..
0.2
..
..
0.0
1.4
0.0
0.0
0.6
0.0
0.0
4.7
2.7
..
0.0
3.8
0.0
0.0
..
6.2
0.0
0.0
1.0
1.6
..
..
..
0.0
0.0
9.9
0.2
0.2
6.1
0.0
5.4
1.6
2.4
0.0
..
..
..
..
0.0
91.9
0.5
0.0
1.5
0.3
1.1
0.2
..
0.0
0.0
..
0.3
0.0
0.3
0.0
..
0.0
3.7
..
..
0.1
0.0
..
5.2
5.3
0.0
0.0
3.1
0.1
..
..
8.4
0.1
0.0
0.0
0.5
0.0
0.1
..
0.2
..
11.4
0.1
0.6
7.1
0.0
7.2
3.4
7.2
0.0
..
0.0
..
..
..
2,777.2
22.8
9.6
43.1
22.7
12.0
31.8
1.0
2.4
4.6
0.3
41.2
4.2
46.1
5.4
0.4
11.3
246.5
3.2
3.1
43.2
6.6
2.4
223.7
19.2
7.7
12.1
149.4
26.2
2.7
1.3
153.9
83.9
6.9
222.1
101.4
0.6
17.1
0.0
6.9
7.9
284.2
14.4
20.1
206.5
11.6
241.3
145.2
97.5
15.8
1.7
1.4
1.5
5.8
5.1
3,776.4
13.9
17.1
211.8
37.6
30.7
28.5
0.5
4.5
9.5
0.1
40.1
5.7
64.8
0.7
0.9
15.8
206.7
3.9
6.2
58.8
6.9
5.9
377.1
29.6
5.1
9.7
150.1
25.6
0.8
0.9
192.9
119.7
13.2
356.2
135.1
0.1
19.0
0.0
13.2
1.3
560.1
12.0
27.2
257.1
17.2
259.0
223.8
71.2
14.7
1.2
4.2
0.0
5.7
3.0
Part III. Development outcomes
109
Table
Participating in growth
11.1
Malaria
Population
(millions)
2008 2009
Clinical cases of
malaria reporteda
2008
2009
Reported deaths
due to malaria
2008
2009
SUB–SAHARAN AFRICA 820.7 841.0 62,920,801 71,675,530 104,331 113,326
Angola
18.0 18.5
2,151,072 2,221,076
9,465 10,530
Benin
8.7
8.9
1,147,005 1,256,708
918
1,375
Botswana
1.9
1.9
17,886
14,878
12
6
Burkina Faso
15.2 15.8 3,688,338 4,399,837
7,834
7,982
Burundi
8.1
8.3
1,424,026 1,757,387
1,511
714
Cameroon
19.1 19.5
1,650,749 1,883,199
7,673
4,943
Cape Verde
0.5
0.5
35
65
2
2
Central African Republic
4.3
4.4
152,260
175,210
456
667
Chad
10.9
11.2
462,573
182,415
1,018
221
Comoros
0.6
0.7
46,426
49,679
47
..
Congo, Dem. Rep.
64.3 66.0 3,938,597
6,749,112 17,940 21,168
Congo, Rep.
3.6
3.7
117,291
92,855
143
116
Côte d’Ivoire
20.6
21.1 1,343,654 1,847,367
1,249 18,156
Djibouti
0.8
0.9
3,528
7,120
..
0
Equatorial Guinea
0.7
0.7
62,312
78,983
4
23
Eritrea
4.9
5.1
10,572
21,298
19
23
Ethiopia
80.7 82.8 2,532,645 3,043,203
1,169
1,121
Gabon
1.4
1.5
77,278
112,840
156
197
Gambia, The
1.7
1.7
508,846
479,409
403
240
Ghana
23.4 23.8
3,050,513 1,899,544
3,889
3,378
Guinea
9.8
10.1
657,003
812,471
441
586
Guinea-Bissau
1.6
1.6
128,758
143,011
487
369
Kenya
38.8 39.8
839,904 8,123,689
..
..
Lesotho
2.0
2.1
..
..
..
..
Liberia
3.8
4.0
606,952
871,560
345
1,706
Madagascar
19.1
19.6
116,538
215,110
276
173
Malawi
14.8 15.3 4,580,226 5,455,423
6,748
6,527
Mali
12.7
13.0
1,045,424 1,633,423
1,227
2,331
Mauritania
3.2
3.3
199,791
167,705
..
91
Mauritius
1.3
1.3
..
..
..
..
Mozambique
22.4 22.9
4,831,491 4,310,086
4,424
3,747
Namibia
2.1
2.2
128,531
81,812
171
46
Niger
14.7 15.3
596,858
309,675
2,461
2,159
Nigeria
151.2 154.7
2,834,174 4,295,686
8,677
7,522
Rwanda
9.7 10.0
772,197 1,247,583
566
809
São Tomé and Príncipe
0.2
0.2
1,647
3,893
16
23
Senegal
12.2
12.5
443,828
222,232
741
574
Seychelles
0.1
0.1
..
..
..
..
Sierra Leone
5.6
5.7
851,478
646,808
871
1,734
Somalia
8.9
9.1
56,408
56,153
49
45
South Africa
48.8 49.3
7,796
6,072
43
45
Sudan
41.3 42.3
3,145,944 2,686,822
1,388
1,396
Swaziland
1.2
1.2
5,881
6,639
10
13
Tanzania
42.5 43.7
3,812,350
40 12,434
840
Togo
6.5
6.6
602,908
618,842
2,663
1,556
Uganda
31.7
32.7 10,184,961 9,775,318
2,372
6,296
Zambia
12.6
12.9 3,080,301 2,976,395
3,781
3,862
Zimbabwe
12.5
12.5 1,003,846
736,897
232
14
NORTH AFRICA
164.1 166.7
12,186
239
3
3
Algeria
34.4 34.9
11,964
..
..
..
Egypt, Arab Rep.
81.5 83.0
80
94
2
2
Libya
6.3
6.4
..
..
..
..
Morocco
31.6 32.0
142
145
1
1
Tunisia
10.3
10.4
..
..
..
..
Children
sleeping under
Under-five
insecticidemortality
treated nets
rate
(% of children
(per 1,000)
under age 5)
2008 2009
2000–09 b
133
166
121
59
169
168
155
29
172
209
105
199
127
121
95
148
58
109
71
106
72
146
195
86
91
119
61
115
194
118
17
147
50
167
143
117
79
95
13
198
180
65
109
77
111
100
130
145
93
28
34
23
19
39
21
130
161
118
57
166
166
154
28
171
209
104
199
128
119
94
145
55
104
69
103
69
142
193
84
84
112
58
110
191
117
17
142
48
160
138
111
78
93
12
192
180
62
108
73
108
98
128
141
90
26
32
21
19
38
21
17.7
20.1
..
9.6
8.3
13.1
..
15.1
0.6
9.3
5.8
6.1
3.0
19.9
0.7
4.2
33.1
..
49.0
28.2
4.5
39.0
46.1
..
26.4
45.8
24.7
27.1
2.1
..
22.8
10.5
42.8
5.5
55.7
56.2
29.2
..
25.8
11.4
..
27.6
0.6
25.7
38.4
9.7
41.1
17.3
..
..
..
..
..
..
Children with
Pregnant
fever receiving women receiving
ODA
any antimalarial two doses of
disbursements
treatment (% of
intermittent
for malaria
children under
preventive
control
age 5 with fever) treatment (%)
($ millions)
b
b
2000–09
2000–09
2008
2009
29.3
54.0
..
48.0
30.0
57.8
..
57.0
53.0
62.7
29.8
48.0
36.0
9.5
48.6
3.6
9.5
..
62.6
43.0
43.5
45.7
23.2
..
67.2
19.7
24.9
31.7
20.7
..
36.7
9.8
33.0
33.2
5.6
8.4
9.1
..
30.1
7.9
..
54.2
0.6
56.7
47.7
61.3
43.3
23.6
..
..
..
..
..
..
2.5
3.0
..
1.3
..
5.8
..
8.7
..
..
5.1
..
8.3
..
..
..
..
..
32.5
43.7
2.9
7.4
15.0
..
45.1
6.4
44.5
4.0
..
..
43.1
10.0
0.3
4.9
17.2
59.8
52.2
..
10.3
0.9
..
..
0.5
30.2
18.1
16.2
60.3
6.3
..
..
..
..
..
..
682.8 1,158.8
30.4
29.4
14.1
15.9
0.0
..
3.6
20.7
22.5
7.8
6.1
9.6
..
..
2.7
0.0
0.8
0.3
0.3
0.2
36.4
89.0
0.1
0.2
1.9
16.2
1.5
0.2
6.3
3.4
5.9
0.7
34.9
140.3
1.3
3.9
5.7
6.0
19.2
43.3
1.2
0.0
1.5
1.6
39.8
73.5
..
0.0
13.8
13.0
22.7
26.7
30.7
20.4
9.6
14.7
1.4
–
..
..
31.5
26.6
0.4
3.8
14.7
19.6
36.5
267.4
37.3
62.6
2.4
(0.0)
26.8
27.1
..
..
7.1
5.8
3.9
1.2
..
0.0
44.1
13.3
0.3
2.6
89.8
99.1
5.0
0.3
25.2
54.4
25.4
24.8
0.1
1.8
..
..
..
..
..
..
..
..
..
..
..
..
a. Malaria cases reported before 2000 can be probable and confirmed or only confirmed, depending on the country.
b. Data are for the most recent year available during the period specified.
110
Part III. Development outcomes
Malaria
Table
Capable states and partnership
12.1
Aid and debt relief
From all donors
2008
2009
SUB–SAHARAN AFRICA 40,484.5
Angola
368.8
Benin
641.4
Botswana
720.3
Burkina Faso
1,001.0
Burundi
508.5
Cameroon
548.8
Cape Verde
221.8
Central African Republic
256.4
Chad
418.7
Comoros
37.3
Congo, Dem. Rep.
1,768.5
Congo, Rep.
485.1
Côte d’Ivoire
623.3
Djibouti
120.9
Equatorial Guinea
32.1
Eritrea
143.6
Ethiopia
3,327.8
Gabon
62.1
Gambia, The
93.8
Ghana
1,305.0
Guinea
327.6
Guinea-Bissau
131.6
Kenya
1,362.7
Lesotho
143.8
Liberia
1,249.5
Madagascar
842.9
Malawi
923.7
Mali
964.1
Mauritania
319.7
Mauritius
109.7
Mozambique
1,996.1
Namibia
210.2
Niger
606.7
Nigeria
1,290.2
Rwanda
933.2
São Tomé and Príncipe
47.3
Senegal
1,064.2
Seychelles
12.5
Sierra Leone
366.8
Somalia
758.3
South Africa
1,124.9
Sudan
2,383.6
Swaziland
69.9
Tanzania
2,330.7
Togo
329.6
Uganda
1,641.3
Zambia
1,116.2
Zimbabwe
612.4
NORTH AFRICA
3,375.9
Algeria
319.4
Egypt, Arab Rep.
1,344.3
Libya
60.2
Morocco
1,062.6
Tunisia
331.6
44,704.2
239.5
682.9
279.6
1,083.9
548.8
649.4
195.9
236.9
561.2
50.6
2,353.6
283.0
2,366.3
162.2
31.6
144.8
3,820.0
77.6
128.0
1,582.6
214.7
145.5
1,778.0
123.0
505.0
445.5
772.4
985.1
286.7
155.6
2,013.3
326.2
470.0
1,659.1
934.4
30.7
1,017.6
23.2
437.3
661.7
1,075.0
2,288.9
58.0
2,934.2
499.0
1,785.9
1,268.7
736.8
2,870.5
319.2
925.1
39.2
911.6
473.9
Net official development assistance
($ millions)
From DAC donors
From non-DAC donors
From multilateral donors
2008
2009
2008
2009
2008
2009
21,336.6
209.9
305.0
682.7
475.3
255.1
298.4
162.7
128.5
277.5
20.8
985.5
382.6
200.2
66.1
18.5
52.5
1,843.4
37.6
27.9
725.7
209.9
52.9
953.2
66.0
819.2
274.5
432.0
531.4
139.1
16.1
1,341.3
150.0
269.1
637.2
451.6
26.4
554.4
5.0
174.9
565.6
881.7
1,820.9
17.8
1,372.9
176.0
1,005.7
703.9
532.4
2,129.1
244.7
967.3
52.2
614.4
250.6
22,660.0
131.5
325.7
223.4
452.9
260.9
267.7
161.9
98.6
355.5
28.1
1,099.3
226.1
1,722.6
97.7
25.1
43.4
1,816.6
52.5
21.9
820.3
171.0
50.6
1,224.0
70.7
340.8
241.6
435.2
574.7
122.2
63.6
1,287.7
246.5
255.3
687.5
519.8
19.7
514.4
11.8
196.3
499.5
861.3
1,911.0
18.5
1,408.8
361.8
1,013.3
700.6
620.4
1,866.5
200.1
580.0
32.2
704.7
349.5
322.7
8.3
4.3
–1.5
7.2
0.2
9.9
0.4
0.2
0.4
1.2
5.4
0.2
2.5
9.6
0.1
6.8
31.0
0.7
4.4
3.7
0.5
0.4
1.9
–0.3
27.0
3.9
9.3
0.1
24.2
–1.9
3.0
2.4
1.7
2.0
1.7
0.1
38.2
0.2
–0.9
8.0
1.6
103.8
–0.7
–2.3
–0.6
4.0
0.4
0.1
151.8
–26.7
107.0
1.9
78.4
–8.8
201.5
9.7
3.4
–0.4
1.7
0.2
1.0
–0.4
0.5
–0.1
0.9
2.7
0.4
2.3
10.8
0.0
14.8
19.6
0.0
1.1
6.2
–3.9
1.0
5.4
4.7
1.0
1.5
3.8
1.6
20.7
–1.9
1.7
1.3
2.0
2.2
2.8
0.0
4.6
0.1
0.4
9.6
2.6
60.7
–0.7
–1.4
1.0
3.8
2.1
0.4
31.0
11.8
122.3
0.9
–98.2
–5.8
14,295.0
150.6
332.0
39.0
518.6
253.2
240.5
58.6
127.7
140.9
15.2
777.6
102.3
420.5
45.1
13.5
84.3
1,453.4
23.8
61.6
575.6
117.1
78.3
407.5
78.1
403.3
564.6
482.4
432.7
156.4
95.5
651.9
57.8
336.0
651.0
479.9
20.8
471.6
7.3
192.9
184.7
241.6
459.0
52.8
960.1
154.2
631.5
412.0
80.0
837.1
101.4
270.0
6.1
369.8
89.8
16,248.1
98.4
353.8
56.6
629.3
287.8
380.7
34.5
137.7
205.8
21.6
1,251.6
56.4
641.4
53.7
6.5
86.6
1,983.9
25.0
105.1
756.1
47.5
93.9
548.6
47.7
163.3
202.4
333.4
408.9
143.8
93.8
723.9
78.4
212.7
969.4
411.8
11.0
498.7
11.4
240.5
152.5
211.1
317.2
40.1
1,526.8
136.2
768.8
566.0
115.9
771.4
107.3
222.8
6.0
305.1
130.2
From other donors
2008
2009
41.1
0.0
0.1
0.0
0.1
0.1
0.3
..
..
0.1
..
0.3
0.0
0.8
..
0.0
6.7
20.2
0.0
0.1
0.2
0.1
0.0
0.8
0.4
0.4
0.3
0.1
0.4
0.2
0.0
0.0
0.1
0.1
0.9
0.2
..
0.4
0.1
0.1
0.2
1.3
5.8
0.0
0.1
0.1
0.3
0.0
0.0
1.3
0.1
0.9
0.1
0.2
0.0
32.1
0.0
0.1
0.1
0.2
0.1
0.3
0.0
..
0.2
..
0.0
0.1
0.4
..
..
13.3
8.0
..
0.1
0.6
0.2
..
0.7
0.7
0.1
0.3
0.1
0.4
..
0.0
..
0.0
0.1
1.2
0.0
..
0.3
0.1
0.1
0.1
1.5
2.4
0.0
0.1
0.1
0.2
0.0
0.1
0.7
0.0
0.4
0.0
0.2
0.1
(continued)
capaBle states and partnersHip
Part III. Development outcomes
111
Table
Capable states and partnership
12.1
Aid and debt relief (continued)
Net private official development assistance ($ millions)
From all donors
2008
SUB–SAHARAN AFRICA 5,263.1
Angola
3,049.8
Benin
3.8
Botswana
–92.1
Burkina Faso
16.5
Burundi
–37.8
Cameroon
93.3
Cape Verde
44.5
Central African Republic
–22.3
Chad
43.5
Comoros
1.4
Congo, Dem. Rep.
–1.9
Congo, Rep.
123.8
Côte d’Ivoire
36.6
Djibouti
32.6
Equatorial Guinea
–1,016.0
Eritrea
–5.8
Ethiopia
–137.8
Gabon
–241.6
Gambia, The
1.3
Ghana
209.4
Guinea
–59.0
Guinea-Bissau
–15.1
Kenya
–25.7
Lesotho
–4.5
Liberia
559.9
Madagascar
205.9
Malawi
–4.7
Mali
–25.3
Mauritania
–8.7
Mauritius
818.6
Mozambique
–52.5
Namibia
317.3
Niger
–30.2
Nigeria
1,713.2
Rwanda
10.3
São Tomé and Príncipe
–4.9
Senegal
163.3
Seychelles
33.6
Sierra Leone
1.8
Somalia
3.7
South Africa
5,504.6
Sudan
–13.5
Swaziland
1.9
Tanzania
122.2
Togo
31.6
Uganda
111.7
Zambia
380.2
Zimbabwe
16.0
NORTH AFRICA
20,880.4
Algeria
295.8
Egypt, Arab Rep.
15,267.8
Libya
1,914.2
Morocco
1,588.6
Tunisia
1,396.7
2009
From DAC donors
2008
6,626.6
5,237.8
2,461.3
3,049.8
–34.7
3.8
2.0
–92.1
2.1
16.5
–26.9
–37.8
45.7
93.3
49.0
44.5
5.9
–22.5
20.2
43.5
0.3
1.4
–27.4
–1.9
166.5
123.8
–1,886.0
36.6
50.4
32.6
448.2 –1,016.0
4.5
–5.8
240.3
–142.9
–294.4
–241.6
10.9
1.3
253.8
209.1
0.6
–59.0
–9.1
–15.1
444.1
–25.7
–2.8
–4.5
1,132.7
559.9
270.4
205.9
31.4
–4.7
–26.5
–25.3
23.8
–8.7
1,526.6
803.0
58.2
–52.5
289.8
317.3
16.7
–30.2
1,209.8
1,713.2
81.1
10.3
3.1
–4.9
274.1
162.6
48.3
33.6
11.6
1.8
6.1
3.7
–377.1
5,504.3
16.3
–16.8
–3.8
1.9
189.8
122.2
–86.5
31.6
64.0
111.7
–30.1
380.2
–96.5
16.0
9,244.6 20,693.6
2,728.9
294.5
4,392.2 15,252.5
1,073.7
1,910.0
811.7
1,583.8
58.5
1,235.4
2009
6,614.5
2,461.3
–34.7
2.0
2.1
–26.9
45.7
49.0
5.9
20.2
0.3
–27.4
166.5
–1,886.0
50.4
448.2
4.5
239.4
–294.4
10.9
253.8
0.6
–9.1
444.1
–2.8
1,132.7
270.4
31.4
–26.7
23.8
1,526.6
58.2
289.8
16.7
1,209.8
81.1
3.1
273.9
48.3
11.6
6.1
–377.3
5.7
–3.8
189.8
–86.5
64.0
–30.1
–96.5
9,167.0
2,727.0
4,357.5
1,035.6
809.9
57.3
Net official development assistance
From non-DAC donors
2008
25.3
..
..
..
..
..
..
..
0.2
..
..
..
..
..
..
..
..
5.0
..
..
0.3
..
..
..
..
..
..
..
..
..
15.6
..
..
..
..
0.0
..
0.7
..
..
..
0.3
3.3
..
..
..
..
..
..
186.8
1.3
15.3
4.2
4.8
161.3
Share of GDP (%)
Per capita ($)
Share of gross capital
formation (%)
2009
2008
2009
2008
2009
2008
2009
12.1
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
0.9
..
..
0.0
..
..
..
..
..
..
..
0.2
..
..
..
..
0.1
..
..
..
0.2
0.0
..
..
0.2
10.6
..
..
..
..
..
..
77.6
1.9
34.7
38.1
1.8
1.2
4.0
0.4
9.6
5.3
12.4
43.5
2.3
14.5
12.9
5.0
7.0
15.3
4.1
2.7
12.3
0.2
8.7
12.8
0.4
11.4
4.6
8.7
15.5
4.5
9.0
148.3
8.9
22.7
11.1
8.9
1.2
20.2
2.3
11.3
0.6
19.9
27.3
8.1
1.4
18.8
..
0.4
4.1
2.5
11.3
11.4
11.4
7.8
14.4
0.6
0.2
0.8
0.1
1.2
0.8
4.7
0.3
10.3
2.4
13.3
41.4
2.9
12.6
11.8
8.2
9.5
22.3
3.0
10.2
15.5
0.3
7.7
13.4
0.7
17.5
6.0
5.2
17.4
6.1
7.8
57.6
5.2
16.3
11.0
9.5
1.8
20.6
3.5
8.7
1.0
17.9
16.1
7.9
3.0
22.5
..
0.4
4.2
1.9
13.7
17.5
11.1
9.9
13.1
0.5
0.2
0.5
0.1
1.0
1.2
49.3
20.5
74.0
374.9
65.7
63.0
28.8
444.7
59.1
38.4
57.9
27.5
134.2
30.3
142.3
48.7
29.1
41.2
42.8
56.5
55.9
33.3
83.5
35.2
70.2
329.4
44.1
62.2
75.9
99.4
86.4
89.2
98.7
41.3
8.5
96.0
295.5
87.2
144.0
66.0
84.9
23.1
57.6
59.8
54.9
51.0
51.8
88.4
49.1
20.6
9.3
16.5
9.6
33.6
32.1
53.2
12.9
76.4
143.4
68.8
66.1
33.3
387.5
53.6
50.1
76.8
35.6
76.8
112.3
187.7
46.7
28.5
46.1
52.6
75.1
66.4
21.3
90.3
44.7
59.5
127.7
22.7
50.6
75.7
87.1
122.0
87.9
150.2
30.7
10.7
93.5
188.7
81.2
263.7
76.8
72.4
21.8
54.1
48.9
67.1
75.4
54.6
98.1
58.8
17.2
9.1
11.1
6.1
28.5
45.4
20.7
2.7
46.4
16.4
..
..
..
29.9
111.2
20.2
49.2
64.0
18.6
26.2
..
0.6
..
64.7
1.8
46.2
21.3
55.7
..
22.3
31.4
741.5
22.2
86.3
..
32.1
4.3
128.9
8.3
..
..
87.2
..
26.7
5.3
127.5
..
1.9
15.8
16.1
42.1
..
49.5
34.4
252.5
2.1
0.6
3.7
0.2
3.1
3.0
24.4
2.1
41.1
9.8
..
..
..
23.5
111.2
24.2
76.3
74.6
12.0
90.4
..
0.7
..
59.7
2.5
67.3
30.9
24.2
..
29.0
24.8
..
15.9
65.6
..
37.7
8.5
98.2
13.0
..
..
82.3
..
28.4
12.5
148.8
..
1.9
16.6
11.4
46.1
..
46.8
44.7
581.9
1.8
0.6
2.5
..
2.8
4.5
a. As of 2010.
112
Part III. Development outcomes
capaBle states and partnersHip
Net official development assistance
Share of central
Share of imports of
government
goods and services (%)
expenditures (%)
Food aid shipments (thousands of tons)
Cereal
Noncereal
2007
2008
2007
2008
2008
2009
2008
2009
8.8
0.6
26.1
10.7
34.0
83.4
6.5
17.5
..
..
..
..
..
5.7
16.9
..
..
34.5
..
23.5
10.1
7.5
44.0
10.7
8.0
54.1
..
..
23.1
..
1.6
36.9
4.3
30.2
1.6
63.8
40.9
14.6
0.9
53.2
..
0.9
17.1
2.8
25.9
18.7
28.9
16.2
..
1.5
..
1.9
0.2
2.2
1.1
12.0
0.5
..
4.7
..
102.0
9.4
17.6
..
..
..
..
..
23.9
27.3
..
..
42.0
..
35.3
14.1
13.6
..
15.4
6.7
27.3
..
..
..
..
2.8
44.1
5.9
..
2.8
61.0
29.3
..
2.0
64.8
..
1.2
16.8
2.1
37.2
..
32.0
23.1
..
1.6
..
1.6
0.1
2.3
2.0
..
..
64.3
..
98.5
..
..
54.0
..
..
..
..
..
14.9
..
..
..
..
..
..
22.3
..
..
20.9
17.3
43884.0
76.2
..
82.1
..
..
..
..
..
8.6
..
..
..
4.5
92.3
..
1.3
..
..
..
75.3
75.1
..
..
7.0
0.8
2.7
..
3.9
2.7
..
..
68.2
..
102.5
..
..
44.9
..
..
..
..
..
57.6
..
..
..
..
..
..
33.8
..
..
27.9
..
..
..
..
74.9
..
8.4
..
..
..
..
..
..
..
9.3
101.9
..
1.1
..
..
..
100.6
86.9
..
..
..
0.9
1.6
..
3.6
4.0
3,284.1
24.3
12.5
0.0
34.6
57.8
8.5
27.5
7.5
50.5
0.2
90.6
4.4
17.3
8.8
0.0
32.0
679.7
0.0
11.4
47.8
22.3
5.7
307.8
18.7
53.8
41.5
179.4
35.2
38.2
0.0
133.7
5.8
74.1
0.0
31.6
1.0
10.6
0.0
27.2
180.1
0.0
498.7
12.8
77.4
0.6
208.0
89.1
115.6
43.2
16.5
26.7
..
0.0
0.0
2,631.6
9.4
5.2
0.0
34.4
50.9
4.7
4.6
20.4
56.2
0.0
78.2
7.3
21.9
7.1
0.0
14.8
571.2
0.0
7.2
36.3
14.7
8.8
220.0
32.0
33.9
43.1
82.0
43.6
39.6
0.0
80.1
9.3
74.8
0.0
16.9
1.5
20.4
0.0
25.9
92.9
0.0
405.6
13.4
65.6
1.8
223.7
32.7
119.6
19.0
17.1
1.9
..
0.0
0.0
3,460.2
0.0
9.7
0.0
39.3
24.3
12.7
11.4
13.1
69.9
0.0
86.3
2.7
12.0
7.6
0.0
17.2
979.1
0.0
2.5
38.9
30.0
6.1
213.8
15.2
35.0
28.5
57.2
19.1
50.0
0.0
135.4
4.2
55.8
0.0
16.1
6.8
24.9
3.5
25.9
317.9
0.0
520.9
16.2
75.3
5.0
158.2
24.5
287.6
25.6
21.4
4.3
..
0.0
0.0
3,066.9
0.0
16.7
0.0
21.8
47.7
8.7
17.5
17.4
100.2
7.5
141.4
3.7
21.4
21.0
0.0
0.0
904.1
0.0
10.4
29.1
11.3
2.1
216.7
6.2
22.3
20.7
70.7
23.0
25.2
0.0
157.4
0.3
40.2
0.0
22.4
6.0
11.3
0.0
15.1
281.8
0.0
427.8
2.4
24.7
25.0
96.0
11.8
178.1
12.2
11.5
0.7
..
0.0
0.0
capaBle states and partnersHip
Heavily Indebted Poor Countries (HIPC) Debt Initiative
Decision
pointa
In nominal terms
Debt service Assistance Total HIPC
relief
delivered
and MDRI
Completion committed under MDRI assistance
($ millions)a ($ millions)a ($ millions)a
pointa
..
Jul. 2000
..
Jul. 2000
Aug. 2005
Oct. 2000
..
Sep. 2007
May 2001
Jun. 2010
Jul. 2003
Mar. 2006
Mar. 2009
..
..
..
Nov. 2001
..
Dec. 2000
Feb. 2002
Dec. 2000
Dec. 2000
..
..
Mar. 2008
Dec. 2000
Dec. 2000
Sep. 2000
Feb. 2000
..
Apr. 2000
..
Dec. 2000
..
Dec. 2000
Dec. 2000
Jun. 2000
..
Mar. 2002
..
..
..
..
Apr. 2000
Nov. 2008
Feb. 2000
Dec. 2000
..
..
Mar. 2003
..
Apr. 2002
Jan. 2009
Apr. 2006
..
Jun. 2009
..
..
Jul. 2010
Jan. 2010
..
..
..
..
Apr. 2004
..
Dec. 2007
Jul. 2004
..
..
..
..
Jun. 2010
Oct. 2004
Aug. 2006
Mar. 2003
Jun. 2002
..
Sep. 2001
..
Apr. 2004
..
Apr. 2005
Mar. 2007
Apr. 2004
..
Dec. 2006
..
..
..
..
Nov. 2001
..
May 2000
Apr. 2005
..
..
460
..
930
1,366
4,917
..
804
260
136
15,222
1,738
3,415
..
..
..
3,275
..
112
3,500
800
790
..
..
4,600
1,900
1,628
895
1,100
..
4,300
..
1,190
..
1,316
263
850
..
994
..
..
..
..
3,000
360
1,950
3,900
..
..
1,130
..
1,207
93
1,285
..
280
..
..
1,035
203
..
..
..
..
3,277
..
370
3,862
..
..
..
..
265
2,385
1,570
1,977
875
..
2,029
..
1,057
..
510
65
2,460
..
661
..
..
..
..
3,806
..
3,483
2,742
..
..
1,590
..
2,137
1,459
6,202
..
1,084
260
136
16,257
1,941
3,415
..
..
..
6,552
..
482
7,362
800
790
..
..
4,865
4,285
3,198
2,872
1,975
..
6,329
..
2,247
..
1,826
328
3,310
..
1,655
..
..
..
..
6,806
360
5,433
6,642
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
Part III. Development outcomes
113
Table
Capable states and partnership
12.2
Status of Paris Declaration indicators
PDI-1
PDI-2
Operational national
development
strategiesa
2005
2007
SUB–SAHARAN AFRICA
Angolad
Benin
Botswanad
Burkina Faso
Burundi
Cameroon
Cape Verde
Central African Republic
Chad
Comorosd
Congo, Dem. Rep.
Congo, Rep.
Côte d’Ivoire
Djiboutid
Equatorial Guinead
Eritread
Ethiopia
Gabon
Gambia, Thed
Ghana
Guinead
Guinea-Bissaud
Kenya
Lesothod
Liberia
Madagascar
Malawi
Mali
Mauritania
Mauritiusd
Mozambique
Namibiad
Niger
Nigeria
Rwanda
São Tomé and Prínciped
Senegal
Seychellesd
Sierra Leone
Somaliad
South Africa
Sudan
Swazilandd
Tanzania
Togo
Uganda
Zambia
Zimbabwed
NORTH AFRICA
Algeriad
Egypt, Arab Rep.
Libya
Morocco
Tunisiad
Reliable public
financial
managementb
2005
2007
PDI-3
Reliable
country
procurement
systemsc
2007
Government
budget estimates
comprehensive
and realistic (%)
2005
2007
PDI-4
PDI-5
Technical
Aid for government Aid for government
assistance aligned sectors uses country
sectors uses
and coordinated
public financial
of country
with country
management
procurement
programs (%)
systems (%)
systems (%)
2005
2007
2005
2007
2005
2007
..
C
..
C
D
C
C
D
C
..
D
..
D
..
..
..
C
..
..
C
..
..
D
..
D
C
C
C
B
..
C
..
C
..
B
..
C
..
D
..
..
D
..
B
..
B
C
..
..
C
..
B
C
C
C
D
C
..
D
..
E
..
..
..
B
..
..
B
..
..
C
..
D
C
C
C
C
..
C
..
C
C
B
..
C
..
C
..
..
D
..
B
..
B
B
..
..
4.0
..
4.0
2.5
3.5
3.5
2.0
3.0
..
2.5
..
2.5
..
..
..
3.5
9.0
..
3.5
..
..
3.5
..
9.0
3.0
3.0
4.0
2.0
..
3.5
..
3.5
3.0
3.5
..
3.5
..
3.5
..
..
2.5
..
4.5
2.0
4.0
3.0
..
..
3.5
..
4.0
3.0
3.5
4.0
2.0
9.0
..
2.5
..
2.0
..
..
..
4.0
9.0
..
4.0
..
..
3.5
..
9.0
3.5
3.0
3.5
2.5
..
3.5
..
3.5
3.0
4.0
..
3.5
..
3.5
..
..
2.0
..
4.0
2.0
4.0
3.5
..
..
..
..
..
..
B
..
..
..
..
..
..
..
..
..
..
..
..
..
C
..
..
..
..
..
..
C
..
..
..
..
..
B
..
B
..
B
..
B
..
..
..
..
B
..
B
C
..
..
46.7
..
67.5
39.3
..
85.1
..
..
..
81.0
..
..
..
..
..
74.4
..
..
96.1
..
..
90.9
..
..
..
53.6
60.0
65.4
..
83.3
..
99.5
..
49.0
..
88.9
..
..
..
70.8
..
..
89.5
..
79.1
51.9
..
..
28.5
..
92.2
53.9
85.7
90.2
36.4
87.9
..
58.3
..
64.4
..
..
..
61.7
22.4
..
94.5
..
..
64.2
..
0.0
87.0
63.7
72.6
57.4
..
82.5
..
90.7
6.3
51.0
..
87.7
..
53.6
..
..
84.6
..
83.6
68.9
98.4
73.5
..
..
56.3
..
3.4
42.6
..
92.7
..
..
..
10.7
..
..
..
..
..
27.3
..
..
40.4
..
..
60.2
..
..
..
46.6
15.1
19.5
..
38.1
..
15.3
..
57.8
..
18.1
..
..
..
95.1
..
..
49.5
..
41.6
32.4
..
..
53.9
..
56.4
41.0
29.9
39.3
36.5
64.4
..
38.1
..
30.9
..
..
..
66.8
70.4
..
73.8
..
..
63.8
..
35.3
70.9
52.3
75.4
53.4
..
26.9
..
50.2
70.6
83.6
..
54.1
..
22.5
..
..
53.2
..
60.5
28.9
58.1
34.5
..
..
51.8
..
44.5
24.5
..
64.1
..
..
..
12.9
..
..
..
..
..
45.2
..
..
62.1
..
..
47.3
..
..
..
54.7
29.5
4.4
..
35.8
..
27.1
..
39.2
..
22.7
..
..
..
38.1
..
..
65.9
..
60.2
34.1
..
..
47.5
..
43.2
32.7
53.1
22.5
23.8
1.0
..
0.0
..
0.0
..
..
..
46.7
4.7
..
50.8
..
..
53.6
..
32.0
21.5
49.9
34.4
8.3
..
43.5
..
25.5
0.0
42.0
..
19.0
..
20.1
..
..
3.1
..
71.5
4.4
57.0
59.4
..
..
64.1
..
60.4
19.4
..
53.5
..
..
..
30.8
..
..
..
..
..
42.8
..
..
51.9
..
..
44.7
..
..
..
35.0
44.6
19.7
..
38.0
..
48.7
..
46.0
..
28.9
..
..
..
43.7
..
..
61.2
..
54.2
43.5
..
..
63.3
..
53.8
34.6
63.1
22.1
10.2
10.6
..
0.8
..
9.3
..
..
..
41.4
32.3
..
56.1
..
..
36.8
..
0.0
25.9
35.4
34.8
22.2
..
53.8
..
36.5
0.0
42.9
..
41.3
..
38.3
..
..
0.4
..
68.5
15.5
36.9
71.0
..
..
..
..
..
..
..
..
..
..
..
..
9.0
..
9.0
..
..
9.0
..
9.0
..
..
..
..
..
..
..
58.2
..
..
..
..
57.4
..
79.8
..
..
76.3
..
..
..
..
86.2
..
82.2
..
..
28.2
..
..
..
12.0
..
78.9
..
24.9
..
..
..
22.7
..
81.1
..
..
..
..
Note: See Technical notes for further details. PDI is Paris Declaration Indicator. Status will be updated in the fourth quarter of 2011.
a. Ratings range from A to E, where A means the development strategy substantially achieves good practices; B means it is largely developed toward achieving good practices; C means it
reflects action taken toward achieving good practices; D means it incorporates some elements of good practice; and E means it reflects little action toward achieving good practices.
b. Ratings range from 1 (low) to 6 (high).
c. Ratings range from A (high) to D (low). Indicator was not collected in 2005.
d. Did not take part in the Survey on Monitoring the Paris Declaration.
114
Part III. Development outcomes
capaBle states and partnersHip
PDI-6
Project
implementation
units parallel to
country structures
(number)
2005
2007
PDI-7
Aid disbursements
on schedule
and recorded by
government (%)
2005
2007
PDI-8
PDI-9
PDI-10
Bilateral aid that
is untied (%)
2005
2007
Aid provided in
the framework of
program-based
approaches (%)
2005
2007
Donor missions
coordinated (%)
2005
2007
Country analysis
coordinated (%)
2005
2007
PDI-11
Existence of
a monitorable
performance
assessment
frameworka
2005
2007
PDI-12
Existence
of a mutual
accountability
reviewa
2005
2007
..
29.0
..
131.0
37.0
..
10.0
..
..
..
34.0
..
..
..
..
..
103.0
..
..
45.0
..
..
17.0
..
..
..
69.0
65.0
23.0
..
40.0
..
52.0
..
48.0
..
23.0
..
..
..
15.0
..
..
56.0
..
54.0
24.0
..
..
58.0
..
102.0
29.0
38.0
18.0
11.0
17.0
..
146.0
..
29.0
..
..
..
56.0
5.0
..
16.0
..
..
21.0
..
16.0
48.0
51.0
60.0
27.0
..
26.0
..
47.0
23.0
41.0
..
55.0
..
2.0
..
..
105.0
..
28.0
13.0
55.0
34.0
..
..
53.0
..
91.7
52.5
..
92.2
..
..
..
82.9
..
..
..
..
..
95.9
..
..
91.6
..
..
44.0
..
..
..
57.7
70.7
39.4
..
70.1
..
73.2
..
65.6
..
69.3
..
..
..
44.2
..
..
70.2
..
84.0
50.1
..
..
31.6
..
91.6
44.4
50.8
96.4
45.2
0.0
..
19.5
..
67.0
..
..
..
73.4
16.8
..
82.3
..
..
46.5
..
0.0
79.5
58.1
68.2
52.1
..
73.7
..
77.5
7.1
66.8
..
60.8
..
29.7
..
..
51.6
..
60.8
14.3
74.4
85.1
..
..
79.3
..
92.4
59.8
..
22.3
..
..
..
88.1
..
..
..
..
..
38.8
..
..
89.9
..
..
78.3
..
..
..
96.9
95.0
72.9
..
89.0
..
83.8
..
81.6
..
90.8
..
..
..
97.2
..
..
94.6
..
81.0
99.1
..
..
98.8
..
91.8
90.6
98.5
60.3
86.7
81.2
..
93.9
..
91.7
..
..
..
82.2
99.7
..
91.8
..
..
84.5
..
82.4
83.9
90.5
93.4
67.0
..
90.8
..
84.3
99.2
95.1
..
93.0
..
91.6
..
97.4
79.9
..
98.9
56.1
85.4
99.6
..
..
60.8
..
45.3
53.6
..
36.7
..
..
..
53.8
..
..
..
..
..
52.6
..
..
52.7
..
..
44.6
..
..
..
31.8
48.1
36.7
..
46.3
..
31.2
..
41.5
..
57.3
..
..
..
26.5
..
..
55.5
..
49.9
47.1
..
..
49.0
..
57.2
35.5
39.6
30.9
34.3
1.5
..
20.8
..
2.6
..
..
..
65.6
0.0
..
68.8
..
..
30.5
..
21.3
43.5
42.0
40.6
35.1
..
46.4
..
49.0
3.9
38.4
..
38.9
..
26.9
..
..
19.2
..
60.8
38.9
65.7
46.8
..
..
14.5
..
16.8
24.3
..
10.5
..
..
..
38.4
..
..
..
..
..
26.7
..
..
19.7
..
..
9.2
..
..
..
23.8
7.4
13.8
..
46.5
..
20.9
..
8.5
..
15.1
..
..
..
18.8
..
..
17.3
..
17.2
14.7
..
..
25.1
..
12.8
13.5
25.8
43.4
9.8
18.1
..
21.3
..
65.0
..
..
..
29.4
4.7
..
39.0
..
..
48.4
..
11.0
23.8
22.3
15.2
11.4
..
16.8
..
15.4
19.1
20.8
..
16.6
..
27.1
..
..
14.9
..
15.8
15.1
21.0
15.9
..
..
37.5
..
45.2
55.0
..
34.1
..
..
..
35.2
..
..
..
..
..
49.5
..
..
39.9
..
..
32.3
..
..
..
60.0
30.0
58.9
..
63.2
..
39.9
..
36.4
..
40.5
..
..
..
75.0
..
..
38.3
..
40.1
45.8
..
..
44.0
..
39.0
73.8
49.2
64.5
23.2
35.0
..
22.9
..
75.0
..
..
..
69.5
36.8
..
59.8
..
..
78.0
..
65.6
41.6
60.8
39.3
25.4
..
31.7
..
31.8
32.8
42.0
..
28.1
..
56.3
..
..
44.7
..
64.9
20.7
54.0
46.4
..
..
C
..
C
D
D
D
D
D
..
D
D
D
..
..
..
C
..
..
C
..
..
C
..
D
C
C
D
C
..
C
..
D
..
C
..
C
..
D
..
..
D
..
B
..
B
D
..
..
C
..
C
D
D
C
D
D
..
D
D
E
..
..
..
C
..
..
C
..
..
C
..
D
C
C
D
C
..
B
..
D
C
C
..
C
..
D
..
..
D
..
B
..
B
C
..
..
B
..
B
B
..
A
..
..
..
B
..
..
..
..
..
A
..
..
A
..
..
B
..
..
..
A
B
B
..
A
..
B
..
B
..
B
..
..
..
A
..
..
A
..
B
A
..
..
B
..
B
A
B
B
B
..
..
B
..
B
..
..
..
A
B
..
A
..
..
B
..
B
B
A
B
B
..
A
..
B
B
B
..
B
..
B
..
..
B
..
A
B
B
B
..
..
100.0
..
..
..
32.0
..
47.0
..
29.2
..
..
..
78.9
..
68.3
..
46.7
..
..
..
75.0
..
90.1
..
61.2
..
..
..
48.9
..
70.3
..
18.1
..
..
..
21.6
..
11.7
..
40.0
..
..
..
56.1
..
25.0
..
..
..
..
..
..
..
..
..
A
..
..
..
B
..
B
..
..
..
..
..
..
..
..
..
..
..
..
capaBle states and partnersHip
..
..
..
Part III. Development outcomes
..
115
Table
Capable states and partnership
12.3
Capable states
Firms that believe
the court system is
fair, impartial, and
uncorrupt (%)
2009–10 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 Príncipe
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 or very
severe constraints (% of firms)
Crime, theft,
Corruption
and disorder
b
2009–10
2009–10 b
23.7
9.6
79.5
38.7
..
32.6
59.5
..
31.0
..
17.2
32.3
35.3
..
..
100.0
..
41.3
..
..
..
..
..
33.2
44.3
28.8
74.3
42.7
..
63.6
..
..
49.6
..
..
..
..
..
29.7
..
..
..
..
..
14.1
..
..
..
75.6
67.8
27.4
70.5
..
61.3
29.8
..
67.2
..
72.7
65.0
75.0
..
..
0.0
..
41.4
..
..
..
..
..
46.7
31.2
42.7
12.8
24.8
..
50.7
..
..
83.7
..
..
..
..
..
36.9
..
..
..
..
..
70.2
..
..
..
28.1
52.7
22.6
42.2
..
41.5
62.3
..
45.8
..
63.3
44.1
53.8
..
..
0.0
..
34.1
..
..
..
..
..
33.5
26.8
48.1
22.8
17.3
..
41.5
..
..
44.2
..
..
..
..
..
14.2
..
..
..
..
..
22.6
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
Number of
procedures
2010
Enforcing contracts
Time required
(days)
2010
Cost
(% of claim)
2010
39
46
42
29
37
44
43
37
43
41
43
43
44
33
40
40
39
37
38
32
36
50
40
40
41
41
38
42
36
46
36
30
33
39
40
24
43
44
37
40
..
30
53
40
38
41
38
35
38
42
46
41
..
40
39
652
1,011
825
625
446
832
800
425
660
743
506
625
560
770
1,225
553
405
620
1,070
434
487
276
1,140
465
785
1,280
871
312
620
370
645
730
270
545
457
230
1,185
780
720
515
..
600
810
972
462
588
490
471
410
705
630
1,010
..
615
565
49.7
44.4
64.7
28.1
81.7
38.6
46.6
21.8
82.0
45.7
89.4
151.8
53.2
41.7
34.0
18.5
22.6
15.2
34.3
37.9
23.0
45.0
25.0
47.2
19.5
35.0
42.4
94.1
52.0
23.2
17.4
142.5
35.8
59.6
32.0
78.7
50.5
26.5
15.4
149.5
..
33.2
19.8
56.1
14.3
47.5
44.9
38.7
113.1
23.8
21.9
26.2
..
25.2
21.8
a. Average of the disclosure, director liability, and shareholder suits indexes.
b. Data are for the most recent year available during the period specified.
116
Part III. Development outcomes
capaBle states and partnersHip
Regulation and tax administration
Disclosure
index
2010
5
5
6
7
6
4
6
1
6
6
6
3
6
6
5
6
4
4
6
2
7
6
6
3
2
4
5
4
6
5
6
5
5
6
5
7
3
6
4
6
..
8
0
2
3
6
2
3
8
7
6
8
..
7
5
Protecting investors
(0 least desirable to 10 most desirable)
Director liability
Shareholder
Investor protection
index
suits index
indexa
2010
2010
2010
3
6
1
8
1
1
1
5
1
1
1
3
1
1
2
1
5
4
1
1
5
1
1
2
1
1
6
7
1
3
8
4
5
1
7
9
1
1
8
7
..
8
6
5
4
1
5
6
1
4
6
3
..
2
5
capaBle states and partnersHip
5
6
3
3
4
5
6
6
5
3
5
4
3
3
0
4
5
5
3
5
6
1
5
10
8
6
6
5
4
3
9
9
6
3
5
3
6
2
5
6
..
8
4
6
8
4
5
7
4
4
4
5
..
1
6
4.4
5.7
3.3
6.0
3.7
3.3
4.3
4.0
4.0
3.3
4.0
3.3
3.3
3.3
2.3
3.7
4.7
4.3
3.3
2.7
6.0
2.7
4.0
5.0
3.7
3.7
5.7
5.3
3.7
3.7
7.7
6.0
5.3
3.3
5.7
6.3
3.3
3.0
5.7
6.3
..
8.0
3.3
4.3
5.0
3.7
4.0
5.3
4.3
4.8
5.3
5.3
..
3.3
5.3
Number of tax
payments
2010
Time required
to prepare, file,
and pay taxes
(hours)
2010
37
31
55
19
46
32
44
43
54
54
20
32
61
64
35
46
18
19
26
50
33
56
46
41
21
32
23
19
59
38
7
37
37
41
35
26
42
59
16
29
..
9
42
33
48
53
32
37
49
25
34
29
..
28
8
310
282
270
152
270
211
654
186
504
732
100
336
606
270
90
492
216
198
488
376
224
416
208
393
324
158
201
157
270
696
161
230
375
270
938
148
424
666
76
357
..
200
180
104
172
270
161
132
242
347
451
433
..
358
144
Total tax rate
(% of profit)
2010
67.4
53.2
66.0
19.5
44.9
153.4
49.1
37.1
203.8
65.4
217.9
339.7
65.5
44.4
38.7
59.5
84.5
31.1
43.5
292.3
32.7
54.6
45.9
49.7
19.6
43.7
37.7
25.1
52.2
68.4
24.1
34.3
9.6
46.5
32.2
31.3
33.3
46.0
44.1
235.6
..
30.5
36.1
36.8
45.2
50.8
35.7
16.1
40.3
54.8
72.0
42.6
..
41.7
62.8
Extractive Industries
Transparency
Initiative status
2010
Candidate
Candidate
Candidate
Candidate
Candidate
Candidate
Intent to implement
Intent to implement
Candidate
Compliant
Candidate
Compliant
Candidate
Candidate
Candidate
Compliant
Compliant
Intent to implement
Candidate
Candidate
Candidate
Candidate
Part III. Development outcomes
117
Table
Capable states and partnership
12.4
Governance and anticorruption indicators
Governance indicatorsa
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 Príncipe
Senegal
Seychelles
Sierra Leone
Somalia
South Africa
Sudan
Swaziland
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeria
Egypt, Arab Rep.
Libya
Morocco
Tunisia
Voice and
accountability
1996
2009
Political stability
and absence
of violence
1996
2009
Government
effectiveness
1996
2009
Regulatory
quality
1996
2009
Rule of law
1996
2009
Control of
corruption
1996
2009
–1.5
0.7
0.8
–0.3
–1.5
–1.2
0.8
–0.5
–0.9
0.0
–1.6
–0.5
–0.8
–0.7
–1.7
–1.1
–0.8
–0.4
–1.3
–0.3
–1.1
–0.3
–0.8
–0.2
–1.4
0.4
0.0
0.7
–1.0
0.8
0.0
0.6
–1.0
–1.8
–1.3
0.5
–0.1
0.0
–0.9
–1.9
0.9
–2.0
–1.1
–0.6
–1.0
–0.5
–0.5
–0.6
–1.1
0.3
0.4
–0.3
–0.7
–1.0
0.8
–1.0
–1.4
–0.3
–1.4
–1.0
–1.2
–1.1
–1.8
–2.2
–1.3
–1.1
–1.1
0.5
–1.4
–0.8
–0.3
–0.1
–0.3
–0.6
–0.2
0.2
–1.0
0.8
–0.1
0.3
–0.7
–0.9
–1.3
0.2
–0.3
0.0
–0.3
–2.0
0.6
–1.6
–1.2
–0.1
–1.0
–0.5
–0.3
–1.6
–2.3
1.0
0.7
–0.2
–2.0
–1.3
1.0
–0.2
–0.9
1.0
–1.9
–0.8
0.0
0.2
–0.9
0.3
–1.0
–0.2
0.1
–0.1
–1.4
–0.6
–0.7
0.6
–2.6
0.1
–0.3
0.7
0.6
0.8
–0.5
0.5
0.0
–1.6
–2.0
1.0
–0.6
1.0
–2.3
–2.3
–1.3
–2.6
0.0
–0.2
–0.5
–1.2
–0.5
–0.6
–0.2
0.4
0.9
–0.1
–1.4
–0.4
0.8
–2.0
–1.8
–1.0
–2.1
–0.4
–1.5
0.5
0.0
–0.8
–1.7
0.1
0.3
0.2
–1.9
–0.5
–1.3
0.4
–1.0
–0.7
–0.1
–0.3
–1.2
0.6
0.5
0.8
–1.2
–2.0
–0.3
0.2
–0.1
0.7
–0.4
–3.3
0.0
–2.6
0.0
0.1
–0.2
–1.1
0.5
–1.4
–1.3
..
0.3
–0.9
..
–1.1
..
..
..
..
–1.5
–0.9
0.2
..
–1.3
..
–1.3
–1.0
–0.2
–0.5
–0.9
–0.9
–0.2
..
–1.5
–0.9
–0.9
–1.5
..
0.3
–0.1
0.5
–0.9
–1.2
..
..
–0.1
..
–1.5
–1.5
0.3
–1.3
..
–0.8
–0.9
–0.6
–0.7
–0.3
–0.9
–0.5
0.6
–0.7
–1.1
–0.8
0.0
–1.4
–1.5
–1.8
–1.7
–1.2
–1.2
–0.9
–1.7
–1.4
–0.4
–0.7
–0.7
0.1
–1.3
–1.1
–0.7
–0.3
–1.2
–0.6
–0.5
–0.8
–0.9
0.7
–0.3
0.2
–0.8
–1.2
–0.2
–0.7
–0.4
0.2
–1.2
–2.3
0.5
–1.3
–0.7
–0.4
–1.4
–0.6
–0.7
–1.7
–1.1
–0.1
0.9
–0.2
–1.1
–0.8
–0.6
..
–1.1
..
–2.3
–1.2
0.0
–0.1
–1.5
..
–1.9
0.0
–1.8
0.1
0.1
0.4
–0.4
–0.6
–2.6
–0.8
–0.2
0.1
–1.1
0.0
–1.0
0.2
–1.5
–1.1
–1.6
..
–0.3
..
–1.2
–2.5
0.1
–1.5
0.4
0.1
0.4
0.3
0.3
–0.8
–1.0
–0.4
0.6
–0.1
–1.2
–0.7
0.0
–1.1
–1.1
–1.6
–1.6
–1.3
–1.0
–0.6
–1.3
–2.3
–1.0
–0.6
–0.3
0.1
–1.2
–1.2
–0.2
–0.6
–1.2
–0.5
–0.5
–0.4
–0.7
0.9
–0.3
0.1
–0.5
–0.7
–0.3
–0.8
–0.3
–0.6
–0.8
–2.6
0.4
–1.2
–0.5
–0.4
–0.8
–0.2
–0.5
–2.3
–1.6
–0.3
0.6
–0.3
–0.9
–1.5
0.5
–0.3
–0.9
..
–2.3
–1.4
–0.7
–0.2
–1.2
–0.3
–1.0
–0.9
0.4
–0.3
–1.4
–1.7
–1.1
–0.3
–2.3
–1.0
–0.4
–0.6
–0.9
0.9
–0.8
0.3
–0.9
–1.6
–1.4
..
–0.3
..
–1.3
–2.1
0.0
–1.6
0.8
–0.3
–1.4
–0.5
–0.5
–0.9
–1.2
–0.7
0.6
–0.3
–1.2
–1.1
0.5
–1.3
–1.5
–1.1
–1.7
–1.2
–1.3
–0.6
–1.3
–1.2
–0.8
–0.5
–0.4
–0.1
–1.6
–1.4
–1.1
–0.3
–1.1
–0.7
–0.2
–0.4
–0.8
0.9
–0.6
0.3
–0.6
–1.2
–0.5
–0.7
–0.3
0.1
–1.0
–2.5
0.1
–1.3
–0.6
–0.4
–0.9
–0.4
–0.5
–1.9
–1.1
..
0.5
–0.3
..
–1.1
..
..
..
..
–2.5
–0.3
0.5
..
–1.1
..
–1.1
–1.1
0.4
–0.3
0.4
–1.0
–1.1
..
–1.7
0.4
–0.3
–0.3
..
0.6
–0.2
0.6
–0.3
–1.1
..
..
–0.3
..
–1.7
–1.7
0.5
–1.1
..
–1.1
–1.0
–0.3
–1.1
–0.3
–1.3
–0.6
0.9
–0.4
–1.1
–0.9
0.7
–0.8
–1.4
–0.8
–1.4
–1.2
–1.2
–0.3
–1.6
–0.3
–0.7
–0.9
–0.6
0.1
–1.2
–1.1
–1.1
0.1
–0.6
–0.2
–0.5
–0.7
–0.7
0.7
–0.4
0.2
–0.7
–1.1
0.1
–0.4
–0.5
0.3
–1.0
–1.7
0.1
–1.2
–0.3
–0.4
–1.1
–0.9
–0.5
–1.5
–1.3
–1.0
–1.8
–0.6
–0.9
–1.0
–1.1
–1.9
–0.8
–1.3
–2.7
–0.9
–1.8
–0.5
0.0
–1.2
–0.6
0.6
–0.4
0.2
–0.6
0.2
–1.0
0.2
0.5
–0.6
–0.3
–1.1
–0.1
0.4
–1.1
0.4
–2.0
0.3
0.7
–0.9
–0.1
–1.0
0.0
0.1
–1.4
0.1
–1.4
0.1
–0.2
–0.7
0.0
–0.8
–0.2
0.2
–0.3
–0.2
–1.1
0.5
–0.2
–0.5
–0.4
–1.1
–0.2
0.0
a. The rating scale for each criterion ranges from –2.5 (weak performance) to 2.5 (very high performance).
b. 0–20 indicates that budget documents provide scant or no information, 21–40 indicates minimal information, 41–60 indicates some information, 61–80 indicates significant information, and
81–100 indicates extensive information. In 2008 the International Budget Partnership made three changes in the methodology applied to its Open Budget Survey, which is the basis for the
open budget index.
c. Data are for the most recent year available during the period specified.
118
Part III. Development outcomes
capaBle states and partnersHip
Share of firms
(%)
Expected to pay
informal payment
to public officials
to get things done
2009–10 c
Expected to give
gifts to obtain an
operating license
2009–10 c
Expected to give
gifts in meetings
with tax officials
2009–10 c
Expected to give
gifts to secure a
government contract
2009–10 c
Identifying
corruption as a
major constraint
2009–10 c
48.9
54.5
7.3
8.5
..
51.2
6
..
41.8
..
65.7
81.8
38.5
..
..
0
..
41.8
..
..
..
..
..
28.1
55.4
21.8
10.8
19.4
..
5.9
..
..
35.2
..
..
..
..
..
20.4
..
..
..
..
..
16.7
..
..
..
39.1
44.6
2.9
4.1
..
39.6
0
..
52.6
..
53.8
..
31.8
..
..
0
..
0
..
..
..
..
..
3.3
49.6
18.6
3.5
42.4
..
0
..
..
32.5
..
..
..
..
..
8.7
..
..
..
..
..
15.7
..
..
..
34.2
26.8
8.4
6.7
..
30.8
1.1
..
21.2
..
54.4
37.1
13.6
..
..
0
..
22.8
..
..
..
..
..
9.2
54.4
6.8
11.4
20.2
..
0.3
..
..
13.7
..
..
..
..
..
8.6
..
..
..
..
..
16.4
..
..
..
58.6
59
1
11.8
..
58.8
0
..
47.3
..
75.7
49.9
28.5
..
..
0
..
26.6
..
..
..
..
..
16.7
51.6
9
2.8
22.8
..
8.8
..
..
43.4
..
..
..
..
..
33.9
..
..
..
..
..
5.5
..
..
..
75.6
67.8
27.4
70.5
..
61.3
29.8
..
67.2
..
72.7
65
75
..
..
0
..
41.4
..
..
..
..
..
46.7
31.2
42.7
12.8
24.8
..
50.7
..
..
83.7
..
..
..
..
..
36.9
..
..
..
..
..
70.2
..
..
..
1.9
3.1
5.8
3.5
1.9
2.3
5.1
2.0
1.6
2.5
1.7
1.9
2.0
..
1.7
2.6
2.6
3.1
1.9
3.9
1.6
1.9
2.1
3.2
2.4
3.4
2.8
3.1
2.8
5.5
2.6
4.5
2.8
2.7
3.0
2.7
3.4
4.8
1.9
1.0
4.9
1.6
3.6
3.0
2.7
2.6
2.8
1.8
1.9
2.8
5.8
3.1
1.8
2.2
5.1
2.1
1.7
2.1
2.0
2.1
2.2
3.2
1.9
2.6
2.7
2.8
3.2
4.1
2.0
2.1
2.1
3.5
3.3
2.6
3.4
2.7
2.3
5.4
2.7
4.4
2.6
2.4
4.0
3.0
2.9
4.8
2.4
1.1
4.5
1.6
3.2
2.7
2.4
2.5
3.0
2.4
3.0
..
62.0
14.0
..
5.0
..
..
7.0
..
0.0
..
..
..
0.0
..
..
..
..
49.0
..
..
57.0
..
2.0
..
28.0
..
..
..
..
47.0
26.0
19.0
0.0
0.0
3.0
..
..
..
87.0
0.0
..
35.0
..
51.0
47.0
..
26.0
..
51.0
5.0
..
2.0
..
..
0.4
..
6.0
..
..
..
0.0
..
..
..
..
54.0
..
..
49.0
..
40.0
..
47.0
35.0
..
..
28.0
53.0
3.0
18.0
11.0
0.0
3.0
..
..
..
92.0
8.0
..
45.0
..
55.0
36.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
3.2
2.8
2.6
3.5
4.4
2.9
3.1
2.2
3.4
4.3
1.0
43.0
..
27.0
..
1.0
49.0
..
28.0
..
capaBle states and partnersHip
Mean corruption
perceptions index score
(0 low to 10 high)
2008
2010
Open budget index
overall scoreb
2008
2010
Part III. Development outcomes
119
Table
Capable states and partnership
12.5
Country Policy and Institutional Assessment ratings
CPIA overall rating (IDA
resource allocation index)a
2008
2009
SUB–SAHARAN AFRICA
Angola
Benin
Botswanac
Burkina Faso
Burundi
Cameroon
Cape Verde
Central African Republic
Chad
Comoros
Congo, Dem. Rep.
Congo, Rep.
Côte d’Ivoire
Djibouti
Equatorial Guineac
Eritrea
Ethiopia
Gabonc
Gambia, The
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberiad
Madagascar
Malawi
Mali
Mauritania
Mauritiusc
Mozambique
Namibiac
Niger
Nigeria
Rwanda
São Tomé and Príncipe
Senegal
Seychellesc
Sierra Leone
Somaliad
South Africac
Sudan
Swazilandc
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeriac
Egypt, Arab Rep.c
Libyac
Moroccoc
Tunisiac
120
Averageb
2008
2009
Economic management
Macroeconomic
management
Fiscal policy
2008
2009
2008
2009
Debt policy
2008
2009
3.2
2.7
3.6
..
3.7
3.0
3.2
4.2
2.5
2.5
2.3
2.7
2.7
2.7
3.1
..
2.3
3.4
..
3.2
3.9
3.0
2.6
3.6
3.5
..
3.7
3.4
3.7
3.3
..
3.7
..
3.3
3.4
3.7
3.0
3.6
..
3.1
..
..
2.5
..
3.8
2.7
3.9
3.5
1.4
3.2
2.8
3.5
..
3.8
3.1
3.2
4.2
2.6
2.5
2.5
2.7
2.8
2.8
3.2
..
2.2
3.4
..
3.3
3.8
2.8
2.6
3.7
3.5
2.8
3.5
3.4
3.7
3.2
..
3.7
..
3.3
3.5
3.8
2.9
3.7
..
3.2
..
..
2.5
..
3.8
2.8
3.9
3.4
1.9
3.4
3.0
4.0
..
4.3
3.3
3.7
4.5
2.8
2.7
2.0
3.2
2.8
2.5
3.0
..
2.2
3.3
..
3.5
3.7
3.0
1.8
4.0
4.0
..
3.8
3.3
4.3
3.5
..
4.3
..
3.7
4.3
3.8
2.8
3.8
..
3.7
..
..
2.7
..
4.3
2.7
4.5
3.7
1.0
3.4
3.0
3.7
..
4.3
3.3
3.7
4.5
3.0
2.5
2.3
3.2
3.0
2.8
3.0
..
1.8
3.7
..
3.5
3.7
2.3
2.2
4.2
4.0
3.2
3.7
3.2
4.3
3.2
..
4.5
..
3.8
4.3
3.8
2.8
4.0
..
3.7
..
..
2.7
..
4.3
2.8
4.5
3.5
1.7
3.5
3.0
4.5
..
4.5
3.5
4.0
4.5
3.5
2.5
2.5
3.5
3.5
3.0
3.5
..
2.0
2.5
..
4.0
3.5
3.0
2.0
4.0
4.0
..
4.0
3.5
4.5
3.5
..
4.5
..
4.0
4.0
4.0
3.0
4.0
..
4.0
..
..
3.5
..
4.5
3.0
4.5
4.0
1.0
3.6
3.0
4.0
..
4.5
3.5
4.0
4.5
3.5
2.5
3.0
3.5
3.5
3.5
3.5
..
2.0
3.5
..
4.0
3.5
2.5
2.5
4.5
4.0
3.5
4.0
3.0
4.5
3.5
..
4.5
..
4.0
4.0
4.0
3.0
4.0
..
4.0
..
..
3.5
..
4.5
3.0
4.5
4.0
2.0
3.4
3.0
4.0
..
4.5
3.5
4.0
4.5
3.0
2.5
1.5
3.5
2.5
2.5
3.0
..
2.0
4.0
..
3.5
3.5
3.5
2.5
4.0
4.0
..
3.5
3.5
4.0
3.0
..
4.0
..
3.5
4.5
4.0
3.0
3.5
..
3.5
..
..
3.0
..
4.5
3.0
4.5
3.5
1.0
3.4
3.0
3.5
..
4.5
3.5
4.0
4.5
3.0
2.5
2.0
3.5
3.0
2.5
3.0
..
2.0
4.0
..
3.5
3.5
2.5
2.5
4.0
4.0
3.5
3.0
3.5
4.0
2.5
..
4.5
..
3.5
4.5
4.0
3.0
4.0
..
3.5
..
..
3.0
..
4.5
3.0
4.5
3.0
2.0
3.2
3.0
3.5
..
4.0
3.0
3.0
4.5
2.0
3.0
2.0
2.5
2.5
2.0
2.5
..
2.5
3.5
..
3.0
4.0
2.5
1.0
4.0
4.0
..
4.0
3.0
4.5
4.0
..
4.5
..
3.5
4.5
3.5
2.5
4.0
..
3.5
..
..
1.5
..
4.0
2.0
4.5
3.5
1.0
3.1
3.0
3.5
..
4.0
3.0
3.0
4.5
2.5
2.5
2.0
2.5
2.5
2.5
2.5
..
1.5
3.5
..
3.0
4.0
2.0
1.5
4.0
4.0
2.5
4.0
3.0
4.5
3.5
..
4.5
..
4.0
4.5
3.5
2.5
4.0
..
3.5
..
..
1.5
..
4.0
2.5
4.5
3.5
1.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
Part III. Development outcomes
capaBle states and partnersHip
Structural policies
Averageb
Trade
Financial sector
2008
2009
Business regulatory environment
2008
2009
2008
2009
2008
2009
3.2
2.8
3.7
..
3.5
2.8
3.2
3.8
2.7
2.8
2.7
2.7
2.8
3.3
3.7
..
1.5
3.2
..
3.3
4.0
3.3
3.2
3.8
3.3
..
3.5
3.5
3.5
3.3
..
3.7
..
3.3
3.3
3.5
3.2
3.8
..
3.2
..
..
2.7
..
3.8
3.2
3.8
3.7
1.5
3.2
2.8
3.7
..
3.5
3.0
3.2
3.8
2.7
2.8
2.7
2.5
3.0
3.3
3.7
..
1.5
3.2
..
3.3
4.0
3.3
3.2
4.0
3.3
2.8
3.5
3.5
3.5
3.3
..
3.7
..
3.3
3.5
3.8
3.0
3.8
..
3.2
..
..
2.7
..
3.8
3.2
3.8
3.5
2.2
3.7
4.0
4.0
..
4.0
3.5
3.5
4.0
3.5
3.0
3.0
4.0
3.5
4.0
4.0
..
1.5
3.0
..
3.5
4.0
4.0
4.0
4.0
3.5
..
4.0
4.0
4.0
4.0
..
4.5
..
4.0
3.5
3.5
4.0
4.0
..
3.5
..
..
2.5
..
4.0
4.0
4.0
4.0
2.0
3.7
4.0
4.0
..
4.0
4.0
3.5
4.0
3.5
3.0
3.0
3.5
3.5
4.0
4.0
..
1.5
3.0
..
3.5
4.0
4.0
4.0
4.0
3.5
3.0
4.0
4.0
4.0
4.0
..
4.5
..
4.0
3.5
4.0
4.0
4.0
..
3.5
..
..
2.5
..
4.0
4.0
4.0
4.0
3.0
3.0
2.5
3.5
..
3.0
2.5
3.0
4.0
2.5
3.0
2.5
2.0
2.5
3.0
3.5
..
1.0
3.0
..
3.0
4.0
3.0
3.0
3.5
3.5
..
3.0
3.0
3.0
2.5
..
3.5
..
3.0
3.5
3.5
2.5
3.5
..
3.0
..
..
2.5
..
4.0
2.5
3.5
3.5
1.0
3.0
2.5
3.5
..
3.0
2.5
3.0
4.0
2.5
3.0
2.5
2.0
3.0
3.0
3.5
..
1.0
3.0
..
3.0
4.0
3.0
3.0
4.0
3.5
2.5
3.0
3.0
3.0
2.5
..
3.5
..
3.0
3.5
3.5
2.5
3.5
..
3.0
..
..
2.5
..
4.0
2.5
3.5
3.5
1.5
3.1
2.0
3.5
..
3.5
2.5
3.0
3.5
2.0
2.5
2.5
2.0
2.5
3.0
3.5
..
2.0
3.5
..
3.5
4.0
3.0
2.5
4.0
3.0
..
3.5
3.5
3.5
3.5
..
3.0
..
3.0
3.0
3.5
3.0
4.0
..
3.0
..
..
3.0
..
3.5
3.0
4.0
3.5
1.5
3.1
2.0
3.5
..
3.5
2.5
3.0
3.5
2.0
2.5
2.5
2.0
2.5
3.0
3.5
..
2.0
3.5
..
3.5
4.0
3.0
2.5
4.0
3.0
3.0
3.5
3.5
3.5
3.5
..
3.0
..
3.0
3.5
4.0
2.5
4.0
..
3.0
..
..
3.0
..
3.5
3.0
4.0
3.0
2.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
(continued)
capaBle states and partnersHip
Part III. Development outcomes
121
Table
Capable states and partnership
12.5
Country Policy and Institutional Assessment ratings
(continued)
Policies for social inclusion and equity
Averageb
2008
2009
SUB–SAHARAN AFRICA
Angola
Benin
Botswanac
Burkina Faso
Burundi
Cameroon
Cape Verde
Central African Republic
Chad
Comoros
Congo, Dem. Rep.
Congo, Rep.
Côte d’Ivoire
Djibouti
Equatorial Guineac
Eritrea
Ethiopia
Gabonc
Gambia, The
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberiad
Madagascar
Malawi
Mali
Mauritania
Mauritiusc
Mozambique
Namibiac
Niger
Nigeria
Rwanda
São Tomé and Príncipe
Senegal
Seychellesc
Sierra Leone
Somaliad
South Africac
Sudan
Swazilandc
Tanzania
Togo
Uganda
Zambia
Zimbabwe
NORTH AFRICA
Algeriac
Egypt, Arab Rep.c
Libyac
Moroccoc
Tunisiac
Gender equality
2008
2009
Equity of public
resource use
2008
2009
Building human
resources
2008
2009
Social protection
and labor
2008
2009
Policies and
institutions for
environmental
sustainability
2008
2009
3.1
2.7
3.3
..
3.6
3.3
3.1
4.3
2.2
2.4
2.5
2.9
2.7
2.3
3.0
..
3.0
3.6
..
3.2
4.0
3.0
2.6
3.2
3.3
..
3.7
3.4
3.4
3.5
..
3.4
..
3.0
3.2
3.9
2.8
3.4
..
2.9
..
..
2.3
..
3.7
2.7
3.8
3.5
1.5
3.1
2.9
3.3
..
3.6
3.3
3.1
4.3
2.5
2.4
2.6
2.8
2.7
2.4
3.2
..
2.8
3.6
..
3.3
3.9
3.0
2.5
3.5
3.3
2.5
3.6
3.5
3.4
3.4
..
3.3
..
3.1
3.2
3.9
2.8
3.4
..
3.1
..
..
2.3
..
3.7
2.7
3.8
3.5
1.6
3.2
3.0
3.5
..
3.5
4.0
3.0
4.5
2.5
2.5
3.0
3.0
3.0
2.5
2.5
..
3.5
3.0
..
3.5
4.0
3.5
2.5
3.0
4.0
..
3.5
3.5
3.5
4.0
..
3.5
..
2.5
3.0
3.5
3.0
3.5
..
3.0
..
..
2.0
..
3.5
3.0
3.5
3.5
2.5
3.2
3.5
3.5
..
3.5
4.0
3.0
4.5
2.5
2.5
3.0
2.5
3.0
2.5
3.0
..
3.5
3.0
..
3.5
4.0
3.5
2.5
3.0
4.0
2.5
3.5
3.5
3.5
4.0
..
3.5
..
2.5
3.0
3.5
3.0
3.5
..
3.0
..
..
2.0
..
3.5
3.0
3.5
3.5
2.5
3.2
2.5
3.0
..
4.0
3.5
3.0
4.5
2.0
2.5
2.5
3.0
2.5
1.5
3.0
..
3.0
4.5
..
3.0
4.0
3.0
3.0
3.0
3.0
..
4.0
3.5
3.5
3.5
..
3.5
..
3.5
3.5
4.5
3.0
3.5
..
3.0
..
..
2.5
..
4.0
2.0
4.0
3.5
1.0
3.2
2.5
3.0
..
4.0
3.5
3.0
4.5
2.5
2.5
2.5
3.0
2.5
2.0
3.0
..
2.5
4.5
..
3.5
4.0
3.0
3.0
3.5
3.0
3.0
4.0
3.5
3.5
3.5
..
3.5
..
3.5
3.5
4.5
3.0
3.5
..
3.0
..
..
2.5
..
4.0
2.0
4.0
3.5
1.5
3.3
2.5
3.5
..
3.5
3.0
3.5
4.5
2.0
2.5
2.5
3.0
3.0
2.5
3.5
..
3.5
4.0
..
3.5
4.5
3.0
2.5
3.5
3.5
..
3.5
3.0
3.5
3.5
..
4.0
..
3.0
3.0
4.5
3.0
3.5
..
3.5
..
..
2.5
..
4.0
3.0
4.0
4.0
1.0
3.3
2.5
3.5
..
3.5
3.0
3.5
4.5
2.5
2.5
3.0
3.0
3.0
2.5
3.5
..
3.5
4.0
..
3.5
4.5
3.0
2.0
4.0
3.5
2.5
3.5
3.5
3.5
3.5
..
3.5
..
3.5
3.0
4.5
3.0
3.5
..
3.5
..
..
2.5
..
4.0
3.0
4.0
4.0
1.0
3.0
2.5
3.0
..
3.5
3.0
3.0
4.5
2.0
2.5
2.5
3.0
2.5
2.5
3.0
..
3.0
3.5
..
2.5
4.0
3.0
2.5
3.0
3.0
..
3.5
3.5
3.5
3.0
..
3.0
..
3.0
3.5
3.5
2.5
3.0
..
3.0
..
..
2.5
..
3.5
3.0
3.5
3.0
1.0
3.0
3.0
3.0
..
3.5
3.0
3.0
4.5
2.0
2.5
2.5
3.0
2.5
2.5
3.0
..
2.5
3.5
..
2.5
3.5
3.0
2.5
3.5
3.0
2.5
3.5
3.5
3.5
3.0
..
3.0
..
3.0
3.5
3.5
2.5
3.0
..
3.5
..
..
2.5
..
3.5
3.0
3.5
3.0
1.0
2.9
3.0
3.5
..
3.5
3.0
3.0
3.5
2.5
2.0
2.0
2.5
2.5
2.5
3.0
..
2.0
3.0
..
3.5
3.5
2.5
2.5
3.5
3.0
..
4.0
3.5
3.0
3.5
..
3.0
..
3.0
3.0
3.5
2.5
3.5
..
2.0
..
..
2.0
..
3.5
2.5
4.0
3.5
2.0
2.9
3.0
3.5
..
3.5
3.0
3.0
3.5
3.0
2.0
2.0
2.5
2.5
2.5
3.5
..
2.0
3.0
..
3.5
3.5
2.5
2.5
3.5
3.0
2.0
3.5
3.5
3.0
3.0
..
3.0
..
3.0
3.0
3.5
2.5
3.5
..
2.5
..
..
2.0
..
3.5
2.5
4.0
3.5
2.0
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
Note: The rating scale for each indicator ranges from 1 (low) to 6 (high). The most recent external review of the CPIA ratings and methodology was in 2004.
a. Calculated as the average of the average ratings of each cluster.
b. All criteria are weighted equally.
c. Not an International Development Association (IDA) member.
d. Not rated in the IDA resource allocation index.
122
Part III. Development outcomes
capaBle states and partnersHip
Public sector management and institutions
Averageb
Property rights and
rule-based governance
2008
2009
Quality of budgetary and
financial management
2008
2009
Efficiency of revenue
mobilization
2008
2009
Quality of public
administration
2008
2009
Transparency,
accountability, and
corruption in public sector
2008
2009
2008
2009
2.9
2.4
3.3
..
3.5
2.6
2.9
4.0
2.3
2.2
2.2
2.2
2.6
2.5
2.8
..
2.7
3.3
..
2.9
3.9
2.6
2.6
3.3
3.4
..
3.6
3.4
3.4
3.0
..
3.3
..
3.2
2.9
3.5
3.1
3.4
..
2.7
..
..
2.3
..
3.5
2.2
3.4
3.2
1.6
3.0
2.4
3.3
..
3.7
2.6
2.9
4.0
2.4
2.2
2.4
2.2
2.6
2.6
2.8
..
2.7
3.2
..
2.9
3.8
2.6
2.6
3.3
3.4
2.8
3.3
3.4
3.4
3.0
..
3.4
..
3.1
2.9
3.5
3.1
3.4
..
2.9
..
..
2.2
..
3.5
2.4
3.3
3.2
2.0
2.8
2.0
3.0
..
3.5
2.5
2.5
4.0
2.0
2.0
2.5
2.0
2.5
2.0
2.5
..
2.5
3.0
..
3.0
3.5
2.0
2.5
2.5
3.5
..
3.5
3.5
3.5
3.0
..
3.0
..
3.0
2.5
3.0
2.5
3.5
..
2.5
..
..
2.0
..
3.5
2.5
3.5
3.0
1.0
2.8
2.0
3.0
..
3.5
2.5
2.5
4.0
2.0
2.0
2.5
2.0
2.5
2.0
2.5
..
2.5
3.0
..
3.0
3.5
2.0
2.5
2.5
3.5
2.5
3.5
3.5
3.5
3.0
..
3.0
..
3.0
2.5
3.0
2.5
3.5
..
2.5
..
..
2.0
..
3.5
2.5
3.5
3.0
1.5
3.0
2.5
3.5
..
4.0
3.0
3.0
4.0
2.0
2.0
1.5
2.5
2.5
2.0
3.0
..
2.5
4.0
..
3.0
4.0
3.0
2.5
3.5
3.0
..
3.5
3.0
3.5
3.0
..
3.5
..
3.5
3.0
4.0
3.0
3.0
..
3.5
..
..
2.0
..
3.5
2.0
4.0
3.5
1.5
3.0
2.5
3.5
..
4.5
3.0
3.0
4.0
2.5
2.0
2.0
2.5
2.5
2.5
3.0
..
2.5
3.5
..
3.0
3.5
3.0
2.5
3.5
3.0
2.5
3.0
3.0
3.5
3.0
..
4.0
..
3.5
3.0
4.0
3.0
3.0
..
3.5
..
..
2.0
..
3.5
2.5
4.0
3.5
2.0
3.4
2.5
3.5
..
3.5
3.0
3.5
3.5
2.5
2.5
2.5
2.5
3.0
4.0
3.5
..
3.5
4.0
..
3.5
4.5
3.0
3.0
4.0
4.0
..
4.0
4.0
3.5
3.5
..
4.0
..
3.5
3.0
3.5
3.5
4.0
..
2.5
..
..
3.0
..
4.0
2.5
3.5
3.5
3.5
3.4
2.5
3.5
..
3.5
3.0
3.5
3.5
2.5
2.5
2.5
2.5
3.0
4.0
3.5
..
3.5
3.5
..
3.5
4.5
3.0
3.0
4.0
4.0
3.5
4.0
4.0
3.5
3.5
..
4.0
..
3.5
3.0
3.5
3.5
4.0
..
2.5
..
..
3.0
..
4.0
3.0
3.5
3.5
3.5
2.9
2.5
3.0
..
3.5
2.5
3.0
4.0
2.5
2.5
2.0
2.0
2.5
2.0
2.5
..
3.0
3.0
..
3.0
3.5
3.0
2.5
3.5
3.0
..
3.5
3.5
3.0
3.0
..
3.0
..
3.0
3.0
3.5
3.0
3.5
..
2.5
..
..
2.5
..
3.5
2.0
3.0
3.0
1.0
2.9
2.5
3.0
..
3.5
2.5
3.0
4.0
2.5
2.5
2.5
2.0
2.5
2.0
2.5
..
3.0
3.5
..
3.0
3.5
3.0
2.5
3.5
3.0
2.5
3.5
3.5
3.0
3.0
..
3.0
..
3.0
3.0
3.5
3.0
3.5
..
3.0
..
..
2.5
..
3.5
2.0
3.0
3.0
1.5
2.7
2.5
3.5
..
3.0
2.0
2.5
4.5
2.5
2.0
2.5
2.0
2.5
2.5
2.5
..
2.0
2.5
..
2.0
4.0
2.0
2.5
3.0
3.5
..
3.5
3.0
3.5
2.5
..
3.0
..
3.0
3.0
3.5
3.5
3.0
..
2.5
..
..
2.0
..
3.0
2.0
3.0
3.0
1.0
2.7
2.5
3.5
..
3.5
2.0
2.5
4.5
2.5
2.0
2.5
2.0
2.5
2.5
2.5
..
2.0
2.5
..
2.0
4.0
2.0
2.5
3.0
3.5
3.0
2.5
3.0
3.5
2.5
..
3.0
..
2.5
3.0
3.5
3.5
3.0
..
3.0
..
..
1.5
..
3.0
2.0
2.5
3.0
1.5
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
..
capaBle states and partnersHip
Part III. Development outcomes
123
Table
Capable states and partnership
12.6
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
124
Polity indicators
Revised combined polity score
(–10 strongly autocratic to
10 strongly democratic)
1995
2000
2009
Institutionalized democracy
(0 low to 10 high)
1995
2000
2009
–2.0
6.0
7.0
–5.0
0.0
–4.0
..
5.0
–4.0
0.0
0.0
5.0
–6.0
–7.0
–5.0
–6.0
1.0
–4.0
–7.0
–1.0
–1.0
5.0
–5.0
8.0
0.0
9.0
6.0
7.0
–6.0
10.0
5.0
6.0
8.0
–6.0
–6.0
..
–1.0
..
–7.0
0.0
9.0
–7.0
–9.0
–1.0
–2.0
–4.0
6.0
–6.0
–3.0
6.0
8.0
–3.0
–1.0
–4.0
..
5.0
–2.0
–1.0
0.0
–6.0
4.0
2.0
–5.0
–6.0
1.0
–4.0
–5.0
2.0
–1.0
5.0
–2.0
4.0
0.0
7.0
6.0
6.0
–6.0
10.0
5.0
6.0
5.0
4.0
–4.0
..
8.0
..
0.0
0.0
9.0
–7.0
–9.0
–1.0
–2.0
–4.0
1.0
–3.0
–2.0
7.0
8.0
0.0
6.0
–4.0
..
–1.0
–2.0
9.0
5.0
–4.0
0.0
2.0
–5.0
–7.0
1.0
3.0
–5.0
8.0
–1.0
6.0
7.0
8.0
6.0
0.0
6.0
7.0
–2.0
10.0
5.0
6.0
–3.0
4.0
–3.0
..
7.0
..
7.0
0.0
9.0
–4.0
–9.0
–1.0
–4.0
–1.0
7.0
1.0
..
6.0
7.0
0.0
..
1.0
..
5.0
0.0
..
..
6.0
0.0
0.0
0.0
0.0
3.0
0.0
0.0
1.0
1.0
5.0
0.0
8.0
..
9.0
6.0
7.0
0.0
10.0
5.0
6.0
8.0
0.0
0.0
..
2.0
..
0.0
..
9.0
0.0
0.0
2.0
1.0
0.0
6.0
0.0
1.0
6.0
8.0
0.0
1.0
1.0
..
5.0
1.0
1.0
..
0.0
5.0
3.0
0.0
0.0
3.0
0.0
0.0
3.0
1.0
5.0
2.0
..
3.0
7.0
6.0
6.0
0.0
10.0
5.0
6.0
6.0
4.0
0.0
..
8.0
..
..
..
9.0
0.0
0.0
2.0
1.0
0.0
3.0
1.0
2.0
7.0
8.0
2.0
7.0
1.0
..
1.0
1.0
9.0
6.0
0.0
..
3.0
0.0
0.0
3.0
4.0
0.0
8.0
1.0
7.0
7.0
8.0
7.0
3.0
6.0
7.0
0.0
10.0
5.0
6.0
0.0
4.0
0.0
..
7.0
..
8.0
..
9.0
0.0
0.0
2.0
1.0
1.0
7.0
3.0
..
0.0
0.0
5.0
..
5.0
..
0.0
4.0
..
..
1.0
6.0
7.0
5.0
6.0
2.0
4.0
7.0
2.0
2.0
0.0
5.0
0.0
..
0.0
0.0
0.0
6.0
0.0
0.0
0.0
0.0
6.0
6.0
..
3.0
..
7.0
..
0.0
7.0
9.0
3.0
3.0
4.0
0.0
6.0
4.0
0.0
0.0
3.0
2.0
5.0
..
0.0
3.0
2.0
..
6.0
1.0
1.0
5.0
6.0
2.0
4.0
5.0
1.0
2.0
0.0
4.0
..
3.0
0.0
0.0
0.0
6.0
0.0
0.0
0.0
1.0
0.0
4.0
..
0.0
..
..
..
0.0
7.0
9.0
3.0
3.0
4.0
2.0
4.0
4.0
0.0
0.0
2.0
1.0
5.0
..
2.0
3.0
0.0
1.0
4.0
..
1.0
5.0
7.0
2.0
1.0
5.0
0.0
2.0
1.0
0.0
0.0
1.0
3.0
0.0
0.0
2.0
0.0
0.0
0.0
3.0
0.0
3.0
..
0.0
..
1.0
..
0.0
4.0
9.0
3.0
5.0
2.0
0.0
2.0
–3.0
–6.0
–7.0
–7.0
–3.0
–3.0
–6.0
–7.0
–6.0
–3.0
2.0
–3.0
–7.0
–6.0
–4.0
1.0
0.0
0.0
0.0
1.0
1.0
0.0
0.0
0.0
1.0
3.0
1.0
0.0
0.0
1.0
4.0
6.0
7.0
7.0
4.0
4.0
6.0
7.0
6.0
4.0
1.0
4.0
7.0
6.0
5.0
Part III. Development outcomes
Institutionalized autocracy
(0 low to 10 high)
1995
2000
2009
capaBle states and partnersHip
Technical notes
1. Basic indicators
Table 1.1. Basic indicators
Population is total population based on the de
facto definition of population, which counts
all residents regardless of legal status or
citizenship—except for refugees not permanently settled in the country of asylum, who
are generally considered part of the population of their country of origin. The values
shown are midyear estimates.
Population growth rate for year t is the exponential rate of growth of midyear population
from year t–1 to t, expressed as a percentage.
Population is based on the de facto definition of population, which counts all residents
regardless of legal status or citizenship—
except for refugees not permanently settled
in the country of asylum, who are generally considered part of the population of the
country of origin.
Land area is the land surface area of a country, excluding inland waters, national claims
to continental shelf, and exclusive economic
zones.
Population density is midyear population
divided by land area in square kilometers.
Population is based on the de facto definition of population, which counts all residents
regardless of legal status or citizenship—
except for refugees not permanently settled
in the country of asylum, who are generally
considered part of the population of their
country of origin. Land area is a country’s
total area, excluding area under inland water
bodies, national claims to continental shelf,
and exclusive economic zones. In most cases
the definition of inland water bodies includes
major rivers and lakes.
Gross national income (GNI) per capita,
World Bank Atlas method, is GNI, calculated
using the World Bank Atlas method (see box
1), divided by midyear population. It is similar in concept to GNI per capita in current
prices, except that the use of three-year averages of exchange rates smooths out sharp
fluctuations from year to year.
Gross domestic product (GDP) per capita is
gross domestic product divided by midyear
population. GDP is the sum of gross value
added by all resident producers in the economy plus any product taxes and minus any
subsidies not included in the value of the
products. It is calculated without making deductions for depreciation of fabricated assets
or for depletion and degradation of natural
resources. Growth rates are in real terms and
have been calculated by the least-squares
method using constant 2000 exchange rates
(box 2).
Life expectancy at birth is the number of
years a newborn infant would live if prevailing
patterns of mortality at the time of its birth
were to remain the same throughout its life.
Under-five mortality rate is the probability
that a newborn baby will die before reaching
age 5, if subject to current age-specific mortality rates. The probability is expressed as a
rate per 1,000.
Gini index is the most commonly used
measure of inequality. The coefficient ranges
from 0, which reflects complete equality, to
100, which indicates complete inequality
(one person has all the income or consumption, all others have none). Graphically, the
Gini index can be easily represented by the
area between the Lorenz curve and the line
of equality.
Adult literacy rate is the percentage of
adults ages 15 and older who can, with understanding, read and write a short, simple
statement on their everyday life.
Net official development assistance per capita
is calculated by dividing net disbursements
Technical notes
125
Box 2
Growth rates
Growth rates are calculated as annual averages and represented as
percentages. Except where noted, growth rates of values are computed from constant price series. Rates of change from one period
to the next are calculated as proportional changes from the earlier
period. Least squares growth rates are used wherever there is a sufficiently long time series to permit a reliable calculation. No growth
rate is calculated if more than half the observations in a period are
missing. The least squares growth rate, r, is estimated by fitting a linear regression trend line to the logarithmic annual values of the variable in the relevant period. The regression equation takes the form
ln Xt = a + bt
which is equivalent to the logarithmic transformation of the compound growth equation,
X t = Xo(1 + r)2
In this equation X is the variable, t is time, and a = lnXo and b = ln(1 + r)
are parameters to be estimated. If b* is the least squares estimate
of b, the average annual growth rate, r, is obtained as [exp(b*) – 1]
multiplied by 100 for expression as a percentage. The calculated
growth rate is an average rate that is representative of the available
observations over the entire period. It does not necessarily match
the actual growth rate between any two periods.
of loans and grants from all official sources
on concessional financial terms by midyear
population. This indicator shows the importance of aid flows in sustaining per capita income and consumption levels, although exchange rate fluctuations, the actual rise of aid
flows, and other factors vary across countries
and over time.
Regional aggregates for GNI per capita, GDP
per capita, life expectancy at birth, and adult
literacy rates are weighted by population.
Source: Data on population and life expectancy are from the United Nations Population Division World Population Prospects: The
2008 Revision, census reports and other statistical publications from national statistical
offices, Eurostat Demographic Statistics, Secretariat of the Pacific Community Statistics
and Demography Programme, U.S. Census
Bureau International Database, and World
Bank estimates based on data from these
sources as well as household surveys conducted by national agencies, Macro International, the U.S. Centers for Disease Control
and Prevention, and refugees statistics from
the United Nations High Commissioner for
Refugees. Data on land are from Food and
Agriculture Organization electronic files and
website. Data on GNI per capita and GDP
per capita are from World Bank national accounts data and Organisation for Economic
Co-operation and Development (OECD) national accounts data files. Data on under-five
mortality are from the Inter-agency Group
for Child Mortality Estimation Level &
Trends in Child Mortality: Report 2010. Data
on Gini index for developing countries are
126
Africa Development Indicators 2011
from the World Bank Development Research
Group and are based on primary household
survey data obtained from government statistical agencies and World Bank country
departments (http://iresearch.worldbank.
org/PovcalNet/jsp/index.jsp) and for highincome economies are from the Luxembourg
Income Study database. Data on literacy are
from United Nations Educational, Scientific
and Cultural Organization Institute for Statistics. Data on aid flows are from the OECD
Geographic Distribution of Aid Flows to Developing Countries.
2. National and fiscal accounts
Africa Development Indicators uses the 1993
System of National Accounts (1993 SNA) to
compile national accounts data. Botswana,
Cameroon, Chad, the Democratic Republic
of the Congo, Ethiopia, Kenya, Lesotho, Namibia, Senegal, Sierra Leone, and South Africa report data using the 1993 SNA. Although
more countries are adopting the 1993 SNA,
many still follow the 1968 SNA, and some
low-income countries use concepts from the
1953 SNA.
Reporting periods: For most economies
the fiscal year is concurrent with the calendar year. However, there are few countries
whose ending date reported is for the fiscal year of the central government, though
fiscal years for other government levels
and reporting years for statistical surveys
may differ. Reporting end dates are as follows for the following countries: Botswana
(June 30); Egypt (June 30), Ethiopia (July
7), Gambia, The (June 30), Kenya (June 30),
Lesotho (March 31), Malawi (March 31),
African statistical systems
Most of the data used to compute the indicators in this volume of
Africa Development Indicators come from the African country national statistical systems, the only primary source of the statistics
related to country economic, social, and environmental issues.
While international and specialized institutions may review, make
comparable, and estimate missing values, the true sources of the
data are the national statistical systems, and the data coverage
and quality improvement depend on strengthening their capacity.
National statistical systems
In general a national statistical system consists of a central statistical office, a national office or institute of statistics, and its regional
agencies, sectors’ statistical units in key ministries (finance, education, health, transport, agriculture), and a Central Bank statistical unit. Some large programs may also have specialized statistical units.
Africa’s national statistical systems were designed on Europe’s model, ruled by the same principles drafted in a statistical
law—a law that ensures the independence of the system and the
essence of the role it plays within or together with the government
(produce and centralize, process, publish and disseminate basic
information needed for administrative management). In the past
most African countries reviewed and updated their statistical laws
to address new aspects of statistical information.
The system is usually coordinated by a national council of
statistics, a multisector body at the ministerial level that approves
the overall strategies and policies related to the statistical operations in the country as well as the yearly action plan for statistical
production. It meets once or twice a year. In most countries, these
councils have been weak institutions incapable of playing their
central role of coordination and quality control. It seems, however,
that in recent years, thanks to PARIS21’s new National Strategy
for the Development of Statistics process and STATCAP, they have
been able to play a stronger role in both developing and coordinating national statistical systems.
The major element of the national statistical system is the central statistical office. In the context of weak systems, these offices
tend to concentrate all national production, often substituting the
sector departments. However, that does not preclude most of
these offices from facing incredible difficulties that hamper their
power to produce statistics in a timely and accurate manner. Most
African central statistical offices now have websites where the
core of their production is displayed (see table).
In more and more countries, statistical training is provided by
national schools sometimes linked with central statistical offices,
while regional schools of statistics train statisticians at high and
intermediate levels. As a result, most central statistical offices are
staffed with trained statisticians, but a critical mass of statisticians
is yet to be reached to support regular statistical production. In addition, there is a concentration at the central statistical office, while
in general, sector departments of statistics lack trained statisticians.
Ghislaine Delaine and Antoine Simonpietri
National Strategies for the Development of Statistics
The National Strategy for the Development of Statistics approach
developed by PARIS21 and endorsed by the Marrakech Action
Plan for Statistics in 2004 gives an efficient tool to organize the
development of national statistical systems. If the Poverty Reduction Strategy Paper is the vehicle for coordination and prioritization for national development planning in the region, the National
Strategy for the Development of Statistics is the equivalent for statistical systems. Based on the principles of strategic management
used in statistical systems in developed countries, the strategy’s
guidelines were discussed and reviewed by a number of managers
of statistical offices in developing countries and have taken into
account previous attempts of statistical planning.
A National Strategy for the Development of Statistics provides
a guide for strengthening statistical capacity across the entire national statistical system. The strategy envisages where the national
statistical systems should be in 5–10 years and sets milestones for
getting there. It presents a comprehensive and unified framework
for continual assessment of evolving user needs and priorities
for statistics and for building the capacity needed to meet these
needs in a more coordinated, synergistic, and efficient manner. It
also provides a framework for mobilizing, harnessing, and leveraging resources (both national and international) and a basis for effective and results-oriented strategic management of the national
statistical system.
The PARIS21 Report (March 2011) on National Strategy for
the Development of Statistics status for International Development
Association countries shows that 22 countries are currently implementing a strategy and that 15 are designing a strategy or awaiting
their adoption by country authorities.
Role of partners
For a long time donors have substituted government at both the
demand and financial levels and provided methodological support
for the adoption of up to date techniques and measurements. According to the 2010 Partner Report on Support to Statistics, Africa received nearly half of total statistical support, equivalent to
$716 million in commitments, of which 9 countries (Burkina Faso,
Ethiopia, Kenya, Malawi, Mali, Mozambique, Nigeria, Sudan, and
Tanzania) received a little less than half of this amount.
Challenges in supporting national capacity
After years of decline, the capacity of African countries to produce
and disseminate good quality, reliable, relevant, and timely statistics has improved due in part to an increase in the demand for
data. However, this demand has rarely been used to build a sustainable statistical capacity. Data production from some administrative sources and surveys has improved, but large gaps remain
in national accounts, household surveys, and most administrative
data. If data dissemination has progressed with the development
of national data archives, very few countries have adopted data
(continued)
Technical notes
127
African statistical systems (continued)
access policies. The use of data by nationals, the raison d’être of
statistical capacity building, is still very limited.
In the past, the policy environment has been friendlier to statistical development, but progress remains precarious:
• The industry of indicators has flourished with Poverty Reduction Strategy/Millennium Development Goals monitoring
and evaluation, but availability of good statistics has rarely
been cited as a condition for transparency, accountability,
and good governance in development policies. Hence, the
commitment of governments continues to be fragile.
• Most of the countries have designed National Strategies
for the Development of Statistics, but implementation of
action programs is still meager. National statistical offices
have gained more autonomy despite the resistance to enforcing new laws or taking advantage of new institutional
arrangements.
• For more than 20 years, Africa has benefitted from a training center network; however, trained statisticians are not
being adequately hired by statistical offices due to budgetary constraints.
• Statistical knowledge and new techniques are available but
transferred to African statisticians in ad hoc and uncoordinated manners, resulting in a permanent resort to technical assistance. Some attempts have been made to address
this—but in an ad hoc manner and without a systematic capacity-building program approach.
• Finally, despite recent efforts, inadequate financing of statistical operations remains the major constraint to statistical
development.
Country
Statistical office website
Angola
Benin
www.insae-bj.org
Botswana
www.cso.gov.bw/
Burkina Faso
www.insd.bf/fr/
Burundi
www.isteebu.bi/
Cameroon
www.statistics-cameroon.org
Cape Verde
www.ine.cv/
Central African Republic
www.stat-centrafrique.com/
Chad
www.inseed-tchad.org
Comoros
Congo, Dem. Rep.
www.ins.cd/
Congo, Rep.
www.cnsee.org
Côte d’Ivoire
www.ins.ci/
Equatorial Guinea
www.dgecnstat-ge.org
Eritrea
Ethiopia
www.csa.gov.et/
Gabon
www.stat-gabon.org
Gambia
www.gambia.gm/Statistics/
Ghana
www.statsghana.gov.gh/
Guinea
www.stat-guinee.org
Guinea-Bissau
www.stat-guinebissau.com/
Kenya
www.knbs.or.ke/
Lesotho
www.bos.gov.ls/
Liberia
www.lisgis.org
Madagascar
www.instat.mg/
Malawi
www.nso.malawi.net/
Mali
http://instat.gov.ml/
References
PARIS21. 2004. “A Guide to Designing a National Strategy for
the Development of Statistics (NSDS).” PARIS21 Secretariat,
Paris.
———. 2010. “Partner Report on Support to Statistics (PRESS).”
PARIS21 Secretariat, Paris.
———. 2011. National Strategies for the Development of Statistics
Progress Report: NSDS Summary Table for IDA and Lower
Middle Income Countries. Paris: PARIS21 Secretariat.
World Bank. 2004. “Better Data for Better Results: An Action Plan
for Improving Development Statistics.” Paper presented at the
Second International Roundtable on Managing for Development Results, February 4–5, Marrakech, Morocco.
Mauritania
www.ons.mr/
Mauritius
www.gov.mu/portal/site/cso
Mozambique
www.ine.gov.mz/
Namibia
www.npc.gov.na/cbs/
Niger
www.stat-niger.org
Nigeria
www.nigerianstat.gov.ng/
Rwanda
www.statistics.gov.rw/
São Tomé and Príncipe
www.ine.st/
Senegal
www.ansd.sn/
Seychelles
www.nsb.gov.sc/
Sierra Leone
www.statistics.sl/
Somalia
South Africa
www.statssa.gov.za/
South Sudan
http://ssccse.org
Sudan
www.cbs.gov.sd/
Swaziland
www.gov.sz/
Tanzania
www.nbs.go.tz/
Togo
www.stat-togo.org
Uganda
www.ubos.org
Zambia
www.zamstats.gov.zm/
Zimbabwe
www.zimstat.co.zw
Total
44
128
Africa Development Indicators 2011
Namibia (March 31), Sierra Leone (June
30), South Africa (March 31), Swaziland
(March 31), Uganda (June 30), and Zimbabwe (June 30). The reporting period for national accounts data is either calendar year
or fiscal year basis. Most economies report
national accounts and balance of payments
data using calendar years, but some report
on fiscal years. Fiscal year data are assigned
to the calendar year that contains the larger
share of the fiscal year. If a country’s fiscal
year ends before June 30, data are shown in
that first calendar year of the fiscal year; if
the fiscal year ends on or after June 30, data
are shown in the second calendar year of the
fiscal year. Balance of payments data are reported by calendar year.
Revisions to national accounts data: National
accounts data are revised by national statistical offices when methodologies change or
data sources improve. This in turn means
that Africa Development Indicators national accounts data are also revised when data
sources change.
• Ghana: The Ghana Statistical Service
revised Ghana’s national accounts series from 1993 to 2006. New GDP data
are about 60 percent higher than previously reported and incorporate improved data sources and methodology.
• Guinea-Bissau: National accounts data
for 2003–09 are revised. The new data
have broader coverage of all sectors of
the economy, and the new base year is
2005. GDP in current prices is on average 89 percent higher than previous
estimates.
• Namibia: The Central Bureau of Statistics has revised national accounts
data for 2000–07. An expanded survey
has resulted in a substantial upward
adjustment to estimates of output,
particularly in mining, services, and
manufacturing. The constant price series were rebased from 1995 to 2004
prices. GDP in current prices averages 14 percent higher than previous
estimates.
• South Africa: The base year has been
changed from 2000 to 2005. Data are
revised from 2000 onward with official
government data.
National currencies: As of January 2009,
multiple hard currencies such as the rand,
pound sterling, euro, and U.S. dollar are in
use in Zimbabwe. However, data are reported in U.S. dollars, the most frequently used
currency.
Table 2.1. Gross domestic product,
nominal
Gross domestic product (GDP), nominal, is the
sum of gross value added by all resident producers in the economy plus any product taxes
and minus any subsidies not included in the
value of the products. It is calculated without
making deductions for depreciation of fabricated assets or for depletion and degradation
of natural resources. GDP figures are shown
at market prices (also known as purchaser
values) and converted from domestic currencies using single-year official exchange
rates. For the few countries where the official exchange rate does not reflect the rate
effectively applied to actual foreign exchange
transactions, an alternative conversion factor
is used.
The sum of the components of GDP by
industrial origin (presented here as value
added) will not normally equal total GDP for
several reasons. First, components of GDP
by expenditure are individually rescaled and
summed to provide a partially rebased series
for total GDP. Second, total GDP is shown
at purchaser value, while value added components are conventionally reported at producer prices. As explained above, purchaser
values exclude net indirect taxes, while producer prices include indirect taxes. Third, certain items, such as imputed bank charges, are
added in total GDP.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.2. Gross domestic product, real
Gross domestic product (GDP), real, is obtained
by converting national currency GDP series
to U.S. dollars using constant 2000 exchange
rates. For countries where the official exchange rate does not effectively reflect the
rate applied to actual foreign exchange transactions, an alternative currency conversion
factor has been used. Growth rates are in
real terms and calculated by the least-squares
method using constant 2000 exchange rates
(see box 2).
Technical notes
129
Africa’s future and the World Bank’s support to it
Shantayanan Devarajan
Sub-Saharan Africa in 2011 has an unprecedented opportunity for
transformation and sustained growth. Until the global economic
crisis, Africa’s economy had been growing 5 percent a year for a
decade. Growth declined in 2009 but rebounded in 2010, thanks
mainly to prudent macroeconomic policies (figure 1). Progress toward the Millennium Development Goals has been fast enough
that several countries (Ethiopia, Ghana, and Malawi) are likely
to achieve most of the goals. Africa’s private sector is increasingly attracting investment, and—if policymakers’ response to the
global crisis is a guide—the climate for market-oriented, pro-poor
reforms is robust.
GDP growth (%)
Figure 1
Growth and poverty reduction in Africa
10
Oil exporters, excluding Nigeria
8
Oil exporters
Low income
6
4
Middle income
2
Non-oil-exporting resource rich
0
Poverty rate (%)
–2
2006
2007
2008
2009
70
2010
Sub-Saharan Africa
60
Actual $1.25 a day
Projected $1.25 a day
50
After crisis
Path to 2015
40
38.0
30
20
2011
36.0
Before crisis
1990
1995
2000
2005
2010
2015
But Africa continues to face long-term development challenges: dependence on a few primary commodities, low human
capital, weak governance, low youth employment, low empowerment of women, and climate change, to name a few. If we can address these challenges, Africa could be on the brink of a takeoff,
much like China 30 years ago and India 20 years ago.
To that end, the World Bank’s strategy for Africa has two pillars
and a foundation. The two pillars are:
• Competitiveness and employment. The strategy seeks to
help diversify African countries’ exports and generate productive employment, especially for the 7–10 million young
people entering the labor force every year. The strategy will
require a mix of proactive government policies that target
sectors—which helped Kenya’s cut flowers and Mali’s mangoes—with more “neutral” policies, including infrastructure
and skill-building, that enable different industries to flourish,
130
Africa Development Indicators 2011
as shown by the dynamic growth of the information, communications, and technology sector in Africa.
• Vulnerability and resilience. Africa’s poor are subject to a series of shocks that conspire to keep them poor: macroeconomic shocks; health shocks such as malaria or HIV/AIDS;
natural disasters, which are likely to increase with climate
change; and conflict and political violence. The strategy seeks
to build resilience to these shocks by, for example, improving
macroeconomic policies, promoting public health interventions, adapting to the effects of climate change with greater
use of irrigation and water management, and strengthening
institutions of resource-sharing and consensus-building. The
strategy will also support countries in the event of a shock
through, for instance, health insurance and safety net programs, such as Rwanda’s nearly universal insurance scheme
or Ethiopia’s public works program.
The foundation of the strategy is governance and public sector capacity. Of Africa’s $48 billion infrastructure deficit, $17 billion can be filled by efficiency improvements in the management
of infrastructure. Teachers in public primary schools in Uganda
are absent about 20 percent of the time. Yet governance problems—vested interests—stand in the way of these efficiency gains.
The strategy will help address these problems by approaching
governance from both the demand and supply sides. We aim to
strengthen citizen voice using data, knowledge, and the power of
information, communications, and technology so that they can
demand good governance from their leaders. On the supply side,
we will continue to strengthen the capacity of the public sector,
focusing on incentives within the civil service.
The World Bank will implement the strategy using its three
instruments—finance, knowledge, and partnerships—but we will
reverse the order. The first instrument is partnership—with African
governments, the domestic and international private sector, civil
society, and development partners. We will tailor our interventions
depending on what others are doing. Since Rwanda and Niger receive substantial amounts of money for “vertical health programs”
such as HIV/AIDS or malaria, the Bank uses its resources to help
these countries improve their health systems. The second instrument is knowledge, which we will use to promote a more evidencebased public debate. Studies on leakage of public funds, teacher
absenteeism, and student learning outcomes, by informing the
public about the quality of public services, have stimulated a vigorous debate, which has brought about change. The third instrument, finance, will be used as a source of leveraging. How can we
turn a $500 million lending envelope to a country into $3 billion
in external resources to that country, just as the Bujagali dam in
Uganda used $150 million of the Bank’s IDA resources to crowd in
$650 million additional resources from public and private sources?
The strategy proposes a 10-year vision of a continent whose
per capita income is 50 percent higher than today, whose poverty
rate has fallen 12 percentage points, whose area includes at least
5 middle-income countries and 15 countries increasing agricultural productivity faster than 5 percent a year, and whose share of
Africa’s future and the World Bank’s support to it (continued)
world trade has doubled to 8 percent. To track progress towards
these goals, the strategy has a three-tier results monitoring framework based on a results chain that links Africa’s progress with the
World Bank’s contribution to those results with the use of World
Bank instruments (figure 2).
Figure 2 The Africa strategy’s three-tier results monitoring
framework
Needless to say, this strategy is not without risks. The global
economy could face another serious downturn, political violence
could break out in parts of the continent, and we may lack the resources to carry out the plans. But the themes of the strategy, as
well as the focus on partnerships—not to mention the palpable optimism on the continent—make us confident that Africa can seize
this opportunity and realize its full potential ti sustain growth and
reduce poverty.
Tier 2
Sector outcomes and
outputs contributing to
regional results, supported
through country programs
References
World Bank. 2011. Africa’s Future and the World’s Support to It.
Washington, DC: World Bank.
Tier 1
Results indicators
for regional development
outcomes
Measures how the
Africa Region makes
progress on key
development indicators
Measures the World
Bank’s contribution
to achieving
development results
Tier 3
Activities and inputs
in support of
regional results
Shows which instruments
and inputs the World Bank
is using for results
achievement
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.3. Gross domestic product
growth
Gross domestic product (GDP) growth is the average annual growth rate of real GDP (table
2.2) at market prices based on constant local
currency. Aggregates are based on constant
2000 U.S. dollars.
Table 2.6. Gross national income,
nominal
Gross national income, nominal, is the sum of
value added by all resident producers plus any
product taxes (less subsidies) not included in
the valuation of output plus net receipts of
primary income (compensation of employees
and property income) from abroad. Data are
converted from national currency in current
prices to U.S. dollars at official annual exchange rates.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.4. Gross domestic product per
capita, real
Gross domestic product (GDP) per capita, real, is
calculated by dividing real GDP (table 2.2) by
corresponding midyear population.
Table 2.7. Gross national income,
World Bank Atlas method
Gross national income (GNI), World Bank Atlas method, (formerly GNP) is the sum of value added by all resident producers plus any
product taxes (less subsidies) not included in
the valuation of output plus net receipts of
primary income (compensation of employees and property income) from abroad. GNI,
calculated in national currency, is usually
converted to U.S. dollars at official exchange
rates for comparisons across economies, although an alternative rate is used when the
official exchange rate is judged to diverge
by an exceptionally large margin from the
rate actually applied in international transactions. To smooth fluctuations in prices
and exchange rates, the World Bank Atlas
method (see box 1) of conversion is used.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.5. Gross domestic product per
capita growth
Gross domestic product (GDP) per capita growth
is the average annual growth rate of real GDP
per capita (table 2.4).
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Technical notes
131
This method applies a conversion factor that
averages the exchange rate for a given year
and the two preceding years, adjusted for
the difference between the rate of inflation
in the country and that in Japan, the United
Kingdom, the United States, and the euro
area. Growth rates are calculated by the leastsquares method (see box 2).
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.8. Gross national income per
capita, World Bank Atlas method
Gross national income (GNI) per capita, World
Bank Atlas method, is GNI, calculated using
the World Bank Atlas method (see box 1), divided by midyear population.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.9. Gross domestic product
deflator (local currency series)
Gross domestic product (GDP) deflator (local
currency series) is nominal GDP in current local currency divided by real GDP in constant
2000 local currency, expressed as an index
with base year 2000. GDP is the sum of gross
domestic and foreign value added claimed by
residents 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 using constant 2000 exchange rates (see box 1).
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.10. Gross domestic product
deflator (U.S. dollar series)
Gross domestic product (GDP) deflator (U.S.
dollar series) is nominal GDP in current U.S.
dollars (table 2.1) divided by real GDP in constant 2000 U.S. dollars (table 2.2), expressed
as an index with base year 2000. The series
shows the effects of domestic price changes
and exchange rate variations.
132
Africa Development Indicators 2011
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.11. Consumer price index
Consumer price index reflects changes in the
cost to the average consumer of acquiring
a basket of goods and services that may be
fixed or changed at specified intervals, such
as yearly. The Laspeyres formula is generally
used.
Source: International Monetary Fund International Financial Statistics database and
data files.
Table 2.12. Price indexes
Inflation, GDP deflator, is measured by the annual growth rate of the GDP implicit deflator and shows the rate of price change in the
economy as a whole.
Consumer price index is a change in the cost
to the average consumer of acquiring a basket of goods and services that may be fixed or
changed at specified intervals, such as yearly.
The Laspeyres formula is generally used.
Exports of goods and services price index is
calculated by dividing the national accounts
exports of goods and services in current U.S.
dollars by exports of goods and services in
constant 2000 U.S. dollars.
Imports of goods and services price index is
calculated by dividing the national accounts
imports of goods and services in current U.S.
dollars by imports of goods and services in
constant 2000 U.S. dollars.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.13. Gross domestic savings
Gross domestic savings is calculated by deducting total consumption (table 2.17) from
nominal gross domestic product (table 2.1).
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.14. Gross national savings
Gross national savings is the sum of gross domestic savings (table 2.13), net factor income
from abroad, and net private transfers from
abroad. Net public transfers from abroad are
included.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.15. General government final
consumption expenditure
General government final consumption expenditure is all current expenditure for purchases
of goods and services by all levels of government, including capital expenditure on
national defense and security. Other government capital expenditure is included in
capital formation.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.16. Household final
consumption expenditure
Household final consumption expenditure (formerly private consumption) is the market
value of all goods and services, including
durable products (such as cars, washing machines, and home computers), purchased by
households. It excludes purchases of dwellings but includes imputed rent for owneroccupied dwellings. It also includes payments
and fees to governments to obtain permits
and licenses.
Here, household consumption expenditure includes the expenditures of nonprofit
institutions serving households, even when
reported separately by the country.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.17. Final consumption
expenditure plus discrepancy
Final consumption expenditure plus discrepancy (formerly total consumption) is the sum
of household final consumption expenditure (table 2.16) and general government
final consumption expenditure (table 2.15),
shown as a share of gross domestic product.
This estimate includes any statistical discrepancy in the use of resources relative to the
supply of resources. Private consumption,
not separately shown here, is the value of all
goods and services purchased or received as
income in kind by households and nonprofit
institutions. It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings. In practice, it includes any
statistical discrepancy in the use of resources.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.18. Final consumption
expenditure plus discrepancy per capita
Final consumption expenditure plus discrepancy
per capita is final consumption expenditure
plus discrepancy in current U.S. dollars (table
2.17) divided by midyear population.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.19. Gross fixed capital formation
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 2.20) and the private sector
(table 2.21). Examples include improvements
in land, dwellings, machinery, and other
equipment. Due to statistical discrepancies,
for some countries the sum of gross private
investment and gross public investment does
not total gross domestic investment.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.20. Gross general government
fixed capital formation
Gross general government fixed capital formation is gross domestic fixed capital formation
(see table 2.19) for the public sector.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.21. Private sector fixed capital
formation
Private sector fixed capital formation is gross
domestic fixed capital formation (see table
2.19) for the private sector.
Technical notes
133
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.22. External trade balance
(exports minus imports)
External trade balance is the difference between free on board exports (table 2.23) and
cost, insurance, and freight imports (table
2.24) of goods and services (or the difference
between gross domestic savings and gross
capital formation). The resource balance is
shown as a share of nominal gross domestic
product (table 2.1).
Table 2.25. Exports of goods and
services as a share of GDP
Exports of goods and services represent the value
of all goods and other market services provided
to the rest of the world. They include the value
of merchandise, freight, insurance, transport,
travel, royalties, license fees, and other services, such as communication, construction,
financial, information, business, personal,
and government services. They exclude labor
and property income (formerly called factor
services) as well as transfer payments and are
expressed as a proportion of real GDP.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.23. Exports of goods and
services, nominal
Exports of goods and services, nominal, represent the value of all goods and other
market services provided to the rest of the
world. They include the value of merchandise, freight, insurance, transport, travel,
royalties, license fees, and other services,
such as communication, construction, financial, information, business, personal,
and government services. They exclude labor and property income (formerly called
factor services) as well as transfer payments and are expressed in current U.S.
dollars.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.24. Imports of goods and
services, nominal
Imports of goods and services, nominal, represent the value of all goods and other market services received from the rest of the
world. They include the value of merchandise, freight, insurance, transport, travel,
royalties, license fees, and other services,
such as communication, construction, financial, information, business, personal,
and government services. They exclude labor and property income (formerly called
factor services) as well as transfer payments and are expressed in current U.S.
dollars.
134
Africa Development Indicators 2011
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.26. Imports of goods and
services as a share of GDP
Imports of goods and services represent the value
of all goods and other market services received
from the rest of the world. They include the
value of merchandise, freight, insurance, transport, travel, royalties, license fees, and other
services, such as communication, construction, financial, information, business, personal, and government services. They exclude
labor and property income (formerly called factor services) as well as transfer payments and
are expressed as a proportion of real GDP.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data.
Table 2.27. Balance of payments and
current account
Exports of goods and services represent the value of all goods and other market services provided to the rest of the world. They include
the value of merchandise, freight, insurance,
transport, travel, royalties, license fees, and
other services, such as communication, construction, financial, information, business,
personal, and government services. They exclude labor and property income (formerly
called factor services) as well as transfer payments and are expressed in current U.S. dollars and as a proportion of real GDP.
Imports of goods and services represent the
value of all goods and other market services
received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license
fees, and other services, such as communication, construction, financial, information, business, personal, and government
services. They exclude labor and property
income (formerly called factor services) as
well as transfer payments and are expressed
in current U.S. dollars and as a proportion
of real GDP.
Total trade is the sum of exports and imports of goods and services.
Net income is the receipts and payments of
employee compensation paid to nonresident
workers and investment income (receipts
and payments on direct investment, portfolio investment, other investments, and receipts on reserve assets).
Net current transfers are recorded in the
balance of payments whenever an economy
provides or receives goods, services, income,
or financial items without a quid pro quo.
Current account balance is the sum of net
exports of goods, services, net income, and
net current transfers. All transfers not considered to be capital are current.
Total reserves including gold are the holdings
of monetary gold, special drawing rights,
reserves of International Monetary Fund
(IMF) members held by the IMF, and holdings of foreign exchange under the control of
monetary authorities.
Source: Data on exports and imports of
goods and services are from World Bank and
Organisation for Economic Co-operation and
Development national accounts data. Data
on net income, net current transfers, current
account balance, and total reserves are from
the IMF International Financial Statistics database and data files.
Table 2.28. Exchange rates and
purchasing power parity
Official exchange rate is the exchange rate
determined by national authorities or the
rate determined in the legally sanctioned exchange market.
Purchasing power parity (PPP) conversion
factor is the number of units of a country’s
currency required to buy the same amount of
goods and services in the domestic market as
a U.S. dollar would buy in the United States.
Ratio of PPP conversion factor to market exchange rate is the national price level, making
it possible to compare across countries the
costs of the bundle of goods that make up
gross domestic product.
Real effective exchange rate is the nominal
effective exchange rate (a measure of the
value of a currency against a weighted average of several foreign currencies) divided by a
price deflator or index of costs.
Gross domestic product (GDP), PPP, is gross
domestic product converted to international
dollars using purchasing power parity rates.
An international dollar has the same purchasing power over GDP as the U.S. dollar
has in the United States. GDP is the sum of
gross value added by all resident producers in
the economy plus any product taxes and minus any subsidies not included in the value of
the products.
It is calculated without making deductions
for depreciation of fabricated assets or for depletion and degradation of natural resources.
Gross domestic product (GDP) per capita,
PPP, is GDP per capita based on purchasing
power parity (PPP). PPP GDP is gross domestic product converted to international dollars
using purchasing power parity rates. An international dollar has the same purchasing
power over GDP as the U.S. dollar has in the
United States. GDP at purchaser prices is the
sum of gross value added by all resident producers in the economy plus any product taxes
and minus any subsidies not included in the
value of the products. It is calculated without
making deductions for depreciation of fabricated assets or for depletion and degradation
of natural resources.
Source: International Monetary Fund International Financial Statistics database.
Data on PPP are from the World Bank International Comparison Program database.
Table 2.29. Agriculture value added
Agriculture value added is the gross output of
forestry, hunting, and fishing, as well as crop
cultivation and livestock production (International Standard Industrial Classification
[ISIC] revision 3 divisions 1–5) less the value
of their intermediate inputs. It is calculated
without making deductions for depreciation
Technical notes
135
of fabricated assets or depletion and degradation of natural resources. For countries that
report national accounts data at producer
prices (Angola, Benin, Cape Verde, Comoros,
the Republic of Congo, Côte d’Ivoire, Gabon,
Ghana, Liberia, Niger, Rwanda, São Tomé
and Príncipe, Seychelles, Togo, and Tunisia),
gross value added at market prices is used as
the denominator. For countries that report
national accounts data at basic prices (all other countries), gross value added at factor cost
is used as the denominator. Value added at
basic prices excludes net taxes on products;
value added at producer prices includes net
taxes on products paid by producers but excludes sales or value added taxes.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data files.
Table 2.30. Industry value added
Industry value added is the gross output of
mining, manufacturing, construction, electricity, water, and gas (International Standard
Industrial Classification revision 3 divisions
10– 45) less the value of their intermediate
inputs. It is calculated without making deductions for depreciation of fabricated assets or depletion and degradation of natural
resources For countries that report national
accounts data at producer prices (Angola,
Benin, Cape Verde, Comoros, the Republic of
Congo, Côte d’Ivoire, Gabon, Ghana, Liberia,
Niger, Rwanda, São Tomé and Príncipe, Seychelles, Togo, and Tunisia), gross value added
at market prices is used as the denominator.
For countries that report national accounts
data at basic prices (all other countries), gross
value added at factor cost is used as the denominator. Value added at basic prices excludes net taxes on products; value added at
producer prices includes net taxes on products paid by producers but excludes sales or
value added taxes.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data files.
Table 2.31. Services plus discrepancy
value added
Services plus discrepancy value added is the
gross output of all other branches of economic
136
Africa Development Indicators 2011
activity, including wholesale and retail trade
(including hotels and restaurants), transport,
and government, financial, professional, and
personal services, such as education, health
care, and real estate (International Standard
Industrial Classification revision 3 divisions
50–99), less the value of their intermediate
inputs. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers or arising from rescaling. It is calculated
without making deductions for depreciation
of fabricated assets or depletion and degradation of natural resources. For countries that
report national accounts data at producer
prices (Angola, Benin, Cape Verde, Comoros,
the Republic of Congo, Côte d’Ivoire, Gabon,
Ghana, Liberia, Niger, Rwanda, São Tomé
and Príncipe, Seychelles, Togo, and Tunisia),
gross value added at market prices is used as
the denominator. For countries that report
national accounts data at basic prices (all other countries), gross value added at factor cost
is used as the denominator. Value added at
basic prices excludes net taxes on products;
value added at producer prices includes net
taxes on products paid by producers but excludes sales or value added taxes.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data files.
Table 2.32. Central government
finances, expense, and revenue
Revenue, excluding grants, is cash receipts
from taxes, social contributions, and other
revenues, such as fines, fees, rent, and income from property or sales. Grants are also
considered as revenue but are excluded here.
Expense is cash payments for operating activities of the government in providing goods
and services. It includes compensation of
employees (such as wages and salaries), interest and subsidies, grants, social benefits, and
other expenses such as rent and dividends.
Cash surplus or deficit is revenue (including
grants) minus expense, minus net acquisition of nonfinancial assets. In the 1986 Government Finance Statistics Manual nonfinancial assets were included under revenue and
expenditure in gross terms. This cash surplus
or deficit is closest to the earlier overall budget balance (still missing is lending minus
repayments, which are now a financing item
under net acquisition of financial assets).
Net incurrence of liabilities is domestic financing (obtained from residents) and foreign financing (obtained from nonresidents),
or the means by which a government provides financial resources to cover a budget
deficit or allocates financial resources arising
from a budget surplus. The net incurrence of
liabilities should be offset by the net acquisition of financial assets (a third financing
item). The difference between the cash surplus or deficit and the three financing items
is the net change in the stock of cash.
Total debt is the entire stock of direct government fixed-term contractual obligations
to others outstanding on a particular date. It
includes domestic and foreign liabilities such
as currency and money deposits, securities
other than shares, and loans. It is the gross
amount of government liabilities minus the
amount of equity and financial derivatives
held by the government. Because debt is a
stock rather than a flow, it is measured as of
a given date, usually the last day of the fiscal
year.
Goods and services include all government
payments in exchange for goods and services
used for the production of market and nonmarket goods and services. Own-account
capital formation is excluded.
Compensation of employees consists of all
payments in cash and in kind (such as food
and housing) to employees in return for
services rendered and of government contributions to social insurance schemes such
as social security and pensions that provide
benefits to employees.
Interest payments (expense) include interest
payments on government debt—including
long-term bonds, long-term loans, and other
debt instruments—to domestic and foreign residents, expressed as a proportion of
expense.
Subsidies and other transfers include all unrequited, nonrepayable transfers on current
accounts to private and public enterprises;
grants to foreign governments, international
organizations, and other government units;
and social security, social assistance benefits,
and employer social benefits in cash and in
kind.
Other expenses are spending on dividends,
rent, and other miscellaneous expenses,
including provision for consumption of fixed
capital.
Interest payments (revenue) include interest
payments on government debt—including
long-term bonds, long-term loans, and other
debt instruments—to domestic and foreign
residents, expressed as a proportion of revenue.
Taxes on income, profits, and capital gains are
levied on the actual or presumptive net income of individuals, on the profits of corporations and enterprises, and on capital gains,
whether realized or not, on land, securities,
and other assets. Intragovernmental payments are eliminated in consolidation.
Taxes on goods and services include general
sales and turnover or value added taxes, selective excises on goods, selective taxes on
services, taxes on the use of goods or property, taxes on extraction and production of
minerals, and profits of fiscal monopolies.
Taxes on international trade include import
duties, export duties, profits of export or import monopolies, exchange profits, and exchange taxes.
Other taxes include employer payroll or labor taxes, taxes on property, and taxes not allocable to other categories, such as penalties
for late payment or nonpayment of taxes.
Social contributions include social security
contributions by employees, employers, and
self-employed individuals, and other contributions whose source cannot be determined.
They also include actual or imputed contributions to social insurance schemes operated
by governments.
Grants and other revenue include grants
from other foreign governments, international organizations, and other government
units; interest; dividends; rent; requited, nonrepayable receipts for public purposes (such
as fines, administrative fees, and entrepreneurial income from government ownership
of property); and voluntary, unrequited, nonrepayable receipts other than grants.
Source: International Monetary Fund, Government Finance Statistics Yearbook and data
files, and World Bank and Organisation for
Economic Co-operation and Development
GDP estimates.
Table 2.33. Structure of demand
Household final consumption expenditure (formerly private consumption) is the market
Technical notes
137
value of all goods and services, including
durable products (such as cars, washing machines, and home computers), purchased by
households.
General government final consumption expenditure (formerly general government consumption) is all government current expenditures for purchases of goods and services.
Gross fixed capital formation (formerly gross
domestic investment) consists of outlays on
additions to the fixed assets of the economy
plus net changes in the level of inventories.
Exports of goods and services represent the
value of all goods and other market services
provided to the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license
fees, and other services, such as communication, construction, financial, information,
business, personal, and government services.
They exclude labor and property income (formerly called factor services) as well as transfer
payments and are expressed as a proportion
of real GDP.
Imports of goods and services represent the
value of all goods and other market services
received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license
fees, and other services, such as communication, construction, financial, information,
business, personal, and government services.
They exclude labor and property income (formerly called factor services) as well as transfer payments and are expressed as a proportion of real GDP.
Gross national savings is the gross national income less total consumption, plus net
transfers.
Source: World Bank and Organisation for
Economic Co-operation and Development
national accounts data files.
3. Millennium Development Goals
Table 3.1. Millennium Development
Goal 1: eradicate extreme poverty and
hunger
Share of population below PPP $1.25 a day is
the percentage of the population living on
less than $1.25 a day at 2005 international
prices. As a result of revisions in purchasing
power parity (PPP) exchange rates, poverty
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Africa Development Indicators 2011
rates in this edition cannot be compared with
those in editions before 2009.
Poverty gap ratio at PPP $1.25 a day is the
mean shortfall from the poverty line (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line.
This measure reflects the depth of poverty as
well as its incidence.
Share of population below PPP $2 a day is the
percentage of the population living on less
than $2 a day at 2005 international prices.
As a result of revisions in PPP exchange rates,
poverty rates in this edition cannot be compared with those in editions before 2009.
Poverty gap ratio at PPP $2 a day is the mean
shortfall from the poverty line (counting the
nonpoor as having zero shortfall), expressed
as a percentage of the poverty line. This measure reflects the depth of poverty as well as
its incidence.
Share of population below national poverty
line (poverty headcount ratio) is the percentage
of the population living below the national
poverty line. National estimates are based
on population-weighted subgroup estimates
from household surveys.
Share of poorest quintile in national consumption or income is the share of consumption, or
in some cases income, that accrues to the
poorest 20 percent of the population.
Prevalence of child malnutrition, underweight, is the percentage of children under
age 5 whose weight for age is more than two
standard deviations below the median for the
international reference population ages 0–59
months. The reference population, adopted
by the World Health Organization in 1983,
is based on children from the United States,
who are assumed to be well nourished.
Population below minimum dietary energy
consumption (also referred to as prevalence of
undernourishment) is the population whose
dietary energy consumption is continuously
below a minimum dietary energy requirement for maintaining a healthy life and carrying out a light physical activity with an acceptable minimum bodyweight for attained
height.
Source: Data on poverty are from the World
Bank Development Research Group. Data are
based on primary household survey data
obtained from government statistical agencies and World Bank country departments
Multidimensional indices of poverty
In developing countries, poverty measures are among the main
indicators of economic development and progress in alleviating
poverty. But poverty is multidimensional, and no single indicator
can adequately capture all its aspects. To do so, poverty measures
must be sufficiently informative on social welfare and comparable
over time and across space. The World Bank uses consumption
poverty as its main index and sets the poverty line at $1.25 (in 2005
purchasing power parity [PPP] terms; Chen and others 2008) per
person per day; an alternative poverty line at $2 (2005 PPP) per
person per day measures extreme poverty. Consumption poverty
alone does not give a full picture of a country’s economic condition, let alone the priorities governments should set in their efforts
to alleviate poverty. Health, education, wealth inequality, and gender equality are just some of the dimensions of poverty not fully
captured. These topics are covered by the Millennium Development Goals—in addition to poverty and hunger—ensuring that they
will receive international attention.
A multidimensional index of poverty attempts to capture various dimensions of welfare (Alkire and Foster 2007; Alkire and others 2010). Can a single indicator combining measures of health
and education, consumption poverty, and gender inequality be
sufficiently informative on social welfare to be policy relevant? The
conceptual issues underlying the construction of these indices
are not new (see Ravallion 2010, 2011 for a discussion), and measures of consumption poverty face similar challenges, but they
differ from multidimensional indices of poverty, especially in the
assumptions underlying the aggregation of information.
Constructing consumption poverty measures requires an adequate protocol to aggregate several varieties into one measure.
The consumption aggregate rightly captures social welfare if the
weights given to each variety consumed reflect societal preferences. When goods making the consumption poverty index are
marketable and markets are functioning properly, market prices
reflect the weights that the consumption of these items have in the
social welfare function. Thus, theoretically, all expenditure levels of
marketable items can be aggregated into one index of consumption that fully reflects social welfare.
Multidimensional indices of poverty extend this approach by
adding the consumption of nonmarketable items. The key assumptions underlying the construction of these indexes thus relate to the
weights (or prices) assigned to nonmarketable items entering into
the aggregation. For example, how does one compare an individual
with a $2 daily consumption level and a 75-year life expectancy with
an individual with a $3 daily consumption level but a 60-year life
expectancy? In a perfect “market for life expectancy,” one could observe how much individuals might pay for a longer life expectancy,
and assuming market perfection, willingness to pay would capture
the social weight of life expectancy in consumption terms. However,
without observable prices, policymakers will need to choose social
weights, an exercise highly arbitrary and subject to political capture.
Quy-Toan Do
The relevance and credibility of multidimensional indices of
poverty therefore depend crucially on the choice of social weights
assigned to each dimension of poverty (Alkire and others 2000).
On one hand, weights need to be sufficiently flexible to reflect
a social welfare function that varies both over time and across
space; on the other, the choice of welfare weights is politically
charged, so governments might not be able to afford such flexibility without undermining the legitimacy of their choices. Governments need transparency and accountability so that they can
produce an index that fully reflects social welfare. Then, if these
weights do not correspond to societal preferences, aggregating
consumption poverty and life expectancy into a single index will
not reduce the dimensionality of the problem at hand. A multidimensional index of poverty constructed from consumption poverty and life expectancy will still need to be complemented by
those same indices of consumption poverty (or life expectancy)
to provide a full picture of social welfare, a prerequisite for policy
decisions. The usefulness of such aggregation effort must then
be revisited.
References
Alkire, Sabina, and James Foster. 2007. “Counting and Multidimensional Poverty Measurement.” Working Paper 7, Oxford
Poverty and Human Development Initiative, University of
Oxford.
Alkire, Sabina, and Maria Emma Santos. 2010. Acute Multidimensional Poverty: A New Index for Developing Countries. Oxford,
UK: University of Oxford, Oxford Poverty & Human Development Initiative, Oxford Department of International Development, Queen Elizabeth House.
Alkire, Sabina, Maria Emma Santos, Suman Seth, and Gatson Yalonetzky. 2010. Is the Multidimensional Poverty Index Robust
to Different Weights? Oxford, UK: University of Oxford, Oxford Poverty & Human Development Initiative, Queen Elizabeth House.
Chen, Shaohua, and Martin Ravallion. 2008. “The Developing
World is Poorer than We Thought, but No Less Successful
in the Fight against Poverty.” Policy Research Working Paper
4703, World Bank, Washington, DC.
Deaton, A., and S. Zaidi. 2002. “A Guide to Aggregating Consumption Expenditures.” Living Standards Measurement Study
Working Paper 135, World Bank, Washington, DC.
Hentschel, J., and P. Lanjouw. 1996. “Constructing an Indicator of
Consumption for the Analysis of Poverty.” Living Standards
Measurement Study Working Paper 124, World Bank, Washington, DC.
Ravallion, M. 2010. “Mashup Indices of Development.” Policy Research Working Paper 5432, World Bank, Washington, DC.
Ravallion, M. 2011. “On Multidimensional Indices of Poverty.” Journal of Economic Inequality 9 (2): 235–248.
Technical notes
139
(http://iresearch.worldbank.org/PovcalNet/
jsp/index.jsp). Data on national poverty are
from the Global Poverty Working Group
and are based on World Bank country poverty assessments and country poverty reduction strategies. 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. Data on child malnutrition are from
World Health Organization Global Database
on Child Growth and Malnutrition. Data on
population below minimum dietary energy
consumption are from the Food and Agriculture Organization (www.fao.org/economic/
ess/food-security-statistics/en/).
Table 3.2. Millennium Development
Goal 2: achieve universal primary
education
Primary education provides children with basic reading, writing, and mathematics skills,
along with an elementary understanding of
such subjects as history, geography, natural
science, social science, art, and music.
Net primary enrollment ratio is the ratio of
children of official primary school age, based
on the International Standard Classification
of Education 1997, who are enrolled in primary school to the population of the corresponding official primary school age.
Primary completion rate is the percentage of
students completing the last year of primary
school. It is calculated as the total number of
students in the last grade of primary school
minus the number of repeaters in that grade
divided by the total number of children of official graduation age.
Share of cohort reaching grade 5 is the percentage of children enrolled in grade 1 of
primary school who eventually reach grade 5.
The estimate is based on the reconstructed
cohort method.
Youth literacy rate is the percentage of people ages 15–24 who can, with understanding,
both read and write a short, simple statement about their everyday life.
Source: Data are from the United Nations
Educational, Scientific and Cultural Organization Institute for Statistics. Efforts have been
made to harmonize these data series with
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Africa Development Indicators 2011
those published on the United Nations Millennium Development Goals website (www.
un.org/millenniumgoals), but some differences in timing, sources, and definitions remain.
Table 3.3. Millennium Development
Goal 3: promote gender equality and
empower women
Ratio of girls to boys in primary and secondary
school is the ratio of female to male gross enrollment rate in primary and secondary school.
Ratio of literate young women to men is the
ratio of the female youth literacy rate to the
male youth literacy rate.
Women in national parliament are the percentage of parliamentary seats in a single or
lower chamber occupied by women.
Share of women employed in the nonagricultural sector is women wage employees in the
nonagricultural sector as a share of total nonagricultural employment.
Source: Data on net enrollment and literacy are from the United Nations Educational,
Scientific and Cultural Organization Institute for Statistics. Data on women in national parliaments are from the Inter-Parliamentary Union Parline database (www.ipu.org).
Data on women’s employment are from the
International Labour Organization Key Indicators of the Labour Market database.
Table 3.4. Millennium Development
Goal 4: reduce child mortality
Under-five mortality rate is the probability
that a newborn baby will die before reaching
age 5, if subject to current age-specific mortality rates. The probability is expressed as a
rate per 1,000.
Infant mortality rate is the number of infants dying before reaching 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 from the Inter-agency Group
for Child Mortality Estimation Level &
Trends in Child Mortality: Report 2010, based
mainly on household surveys, censuses,
and vital registration, supplemented by the
World Bank Human Development Network
and Development Data Group estimates
based on vital registration and sample registration. Data on child immunization are
from the World Health Organization and
the United Nations Children’s Fund (www.who.
int/immunization_monitoring/routine/
en/).
Table 3.5. Millennium Development
Goal 5: improve maternal health
Maternal mortality ratio, modeled estimate, is
the number of women who die from pregnancy-related causes during pregnancy and
childbirth, per 100,000 live births. Data are
estimated by a regression model using information on fertility, birth attendants, and
HIV prevalence.
Maternal mortality ratio, national estimate,
is the number of women who die during
pregnancy and childbirth, per 100,000 live
births.
Births attended by skilled health staff are the
percentage of deliveries attended by personnel who are trained to give the necessary supervision, care, and advice to women during
pregnancy, labor, and the postpartum period;
to conduct deliveries on their own; and to
care for newborns.
Source: Data on maternal mortality (modeled) are from the World Health Organization,
United Nations Children’s Fund (UNICEF),
United Nations Population Fund, and the
World Bank Trends in Maternal Mortality: 1990–2008. Data on maternal mortality (national) and births attended by skilled
health staff are from UNICEF State of the
World’s Children and Childinfo and from
Demographic and Health Surveys by Macro
International.
Table 3.6. Millennium Development
Goal 6: combat HIV/AIDS, malaria, and
other diseases
Prevalence of HIV is the percentage of people
ages 15–49 who are infected with HIV.
Contraceptive use, any method, is the percentage of women ages 15–49, married
or in union, who are practicing, or whose
sexual partners are practicing, any form of
contraception.
Children sleeping under insecticide-treated
nets are the percentage of children under age
5 with access to an insecticide-treated net to
prevent malaria.
Incidence of tuberculosis is the estimated
number of new tuberculosis cases (pulmonary, smear positive, and extrapulmonary),
per 100,000 people.
Tuberculosis treatment success rate is the
percentage of new, registered smear-positive
(infectious) cases that were cured or in which
a full course of treatment was completed.
Source: Data on HIV prevalence are from
the Joint United Nations Programme on
HIV/AIDS and the World Health Organization (WHO) Report on the Global AIDS Epidemic. Data on contraceptive use are from
household surveys, including Demographic
and Health Surveys by Macro International
and Multiple Indicator Cluster Surveys by the
United Nations Children’s Fund (UNICEF).
Data on insecticide-treated net use are from
UNICEF State of the World’s Children and
Childinfo and from Demographic and Health
Surveys by Macro International. Data on tuberculosis are from the WHO Global Tuberculosis Control Report.
Table 3.7. Millennium Development
Goal 7: ensure environment
sustainability
Forest area is land under natural or planted
stands of trees, whether productive or not.
Terrestrial protected areas are those officially documented by national authorities.
Gross domestic product (GDP) per unit of
energy use is the GDP in purchasing power
parity (PPP) U.S. dollars per kilogram of oil
equivalent of energy use. PPP GDP is gross
domestic product converted to 2000 constant international dollars using PPP rates.
An international dollar has the same purchasing power over GDP as a U.S. dollar has
in the United States.
Carbon dioxide emissions per capita are those
stemming from the burning of fossil fuels
and the manufacture of cement divided by
midyear population. They include carbon dioxide produced during consumption of solid,
liquid, and gas fuels and gas flaring.
Population with sustainable access to an
improved water source is the percentage of
the population with reasonable access to an
Technical notes
141
adequate amount of water from an improved
source, such as a household connection,
public standpipe, borehole, protected well or
spring, or rainwater collection. Unimproved
sources include vendors, tanker trucks, and
unprotected wells and springs. Reasonable
access is defined as the availability of at least
20 liters a person a day from a source within
1 kilometer of the dwelling.
Population with sustainable access to improved sanitation is the percentage of the
population with at least adequate access to
excreta disposal facilities that can effectively
prevent human, animal, and insect contact
with excreta. Improved facilities range from
simple but protected pit latrines to flush toilets with a sewerage connection. The excreta
disposal system is considered adequate if it
is private or shared (but not public) and if it
hygienically separates human excreta from
human contact. To be effective, facilities
must be correctly constructed and properly
maintained.
Source: Data on forest area are from the
Food and Agricultural Organization Global
Forest Resources Assessment. Data on nationally protected areas are from the United
Nations Environment Programme and the
World Conservation Monitoring Centre, as
compiled by the World Resources Institute,
and based on data from national authorities, national legislation, and international
agreements. Data on energy use are from
electronic files of the International Energy
Agency. Data on carbon dioxide emissions
are from the Carbon Dioxide Information
Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory. Data
on access to water and sanitation are from
the World Health Organization and United
Nations Children’s Fund Joint Monitoring
Programme (www.wssinfo.org).
Table 3.8. Millennium Development
Goal 8: develop a global partnership
for development
Heavily Indebted Poor Countries (HIPC) Debt
Initiative decision point is the date at which
a HIPC with an established track record of
good performance under adjustment programs supported by the International Monetary Fund (IMF) and the World Bank commits to undertake additional reforms and to
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Africa Development Indicators 2011
develop and implement a poverty reduction
strategy.
HIPC Debt Initiative completion point is the
a country successfully completes the key
structural reforms agreed on at the decision
point, including developing and implementing its poverty reduction strategy. The country then receives the bulk of debt relief under the HIPC Debt Initiative without further
policy conditions.
Debt service relief committed is the amount
of debt service relief, calculated at the Enhanced HIPC Initiative decision point,
that will allow the country to achieve debt
sustainability at the completion point.
Public and publicly guaranteed debt service is
the sum of principal repayments and interest actually paid in foreign currency, goods,
or services on long-term obligations of public debtors and long-term private obligations
guaranteed by a public entity. Exports refer
to exports of goods, services, and income.
Worker remittances are not included here,
though they are included with income receipts in other World Bank publications, such
as Global Development Finance.
Youth unemployment rate is the percentage
of the labor force ages 15–24 without work
but available for and seeking employment.
Definitions of labor force and unemployment may differ by country.
Fixed-line and mobile telephone subscribers
are subscribers to a fixed-line telephone service, which connects a customer’s equipment
to the public switched telephone network, or
to a public mobile telephone service, which
uses cellular technology.
Personal computers are self-contained computers designed for use by a single individual.
Internet users are people with access to the
Internet.
Source: Data on HIPC countries are from
the International Development Association
and International Monetary Fund “Heavily
Indebted Poor Countries (HIPC) Initiative
and Multilateral Debt Relief Initiative—
Status of Implementation.” Data on external
debt are mainly from reports to the World
Bank through its Debtor Reporting System
from member countries that have received
International Bank for Reconstruction and
Development loans or International Development Association credits, as well as from
World Bank and IMF files. Data on youth
unemployment are from the International
Labour Organization Key Indicators of the
Labour Market database. Data on telephone
subscribers, personal computers, and Internet users are from the International Telecommunication Union World Telecommunication/ICT Development Report and database,
and from World Bank estimates.
4. Private sector development
Table 4.1. Doing Business indicators
Number of startup procedures to start a business
is the number of procedures required to start
a business, including interactions to obtain
necessary permits and licenses and to complete all inscriptions, verifications, and notifications to start operations.
Time required for each procedure to start
a business is the number of calendar days
needed to complete each procedure to legally
operate a business. If a procedure can be sped
up at additional cost, the fastest procedure,
independent of cost, is chosen.
Cost to start a business is normalized by
presenting it as a percentage of gross national income (GNI) per capita.
Minimum capital is the paid-in minimum
capital requirement, which reflects the
amount an entrepreneur needs to deposit in
a bank or with a notary before registration
and up to three months following incorporation. It is reported as a percentage of the
country’s income per capita.
Number of procedures to register property is
the number of procedures required for a business to secure rights to property.
Time required to register property is the
number of calendar days needed for a business to secure rights to property.
Cost to register property is the official costs
required by law to register a property, including fees, transfer taxes, stamp duties, and
any other payment to the property registry,
notaries, public agencies, and lawyers. Other
taxes, such as capital gains tax or value added
tax, are excluded from the cost measure. Both
costs borne by the buyer and those borne by
the seller are included. If cost estimates differ
across sources, the median reported value is
used. It is reported as a percentage of property value, which is assumed to be equivalent
to 50 times income per capita.
Number of procedures to enforce a contract is
the number of independent actions, mandated by law or courts, that demand interaction
between the parties of a contract or between
them and the judge or court officer.
Time required to enforce a contract is the
number of calendar days from the filing of
the lawsuit in court until the final determination and, in appropriate cases, payment.
Cost to enforce a contract is court and attorney fees, where the use of attorneys is mandatory or common, or the cost of an administrative debt recovery procedure, expressed as
a percentage of the debt value.
Number of procedures to deal with construction permits is the number of procedures required to obtain construction-related permits.
Time required to deal with construction permits is the average wait, in days, to obtain a
construction-related permit, from the day
the establishment applied for it to the day it
was granted.
Cost to deal with construction permits is all
the fees associated with completing the procedures to legally build a warehouse, including those associated with obtaining land use
approvals and reconstruction design clearances; receiving inspections before, during,
and after construction; getting utility connections; and registering the warehouse
property. Nonrecurring taxes required for
the completion of the warehouse project also
are recorded. The building code, information
from local experts, and specific regulations
and fee schedules are used as sources for
costs. If several local partners provide different estimates, the median reported value
is used. It is reported as a percentage of the
country’s income per capita.
Disclosure index measures the degree to
which investors are protected through disclosure of ownership and financial information.
Higher values indicate more disclosure.
Director liability index measures a plaintiff’s ability to hold directors of firms liable
for damages to the company. Higher values
indicate greater liability.
Shareholder suits index measures shareholders’ ability to sue officers and directors for misconduct. Higher values indicate
greater power for shareholders to challenge
transactions.
Investor protection index measures the degree to which investors are protected through
Technical notes
143
disclosure of ownership and financial information regulations. It is the average of the disclosure, director liability, and shareholder suits indexes. Higher values indicate better protection.
Rigidity of hours index, a measure of employment regulation, is an average of scores
in five areas: whether night work is unrestricted, whether weekend work is unrestricted, whether the work week can consist of 5.5
days, whether the workweek can extend to
50 hours or more (including overtime) for
two months a year to respond to a seasonal
increase in production, and whether paid annual vacation is 21 working days or fewer.
For each question the answer no is assigned a
score of 1 and the answer yes a 0.
Difficulty of hiring index indicates the applicability and maximum duration of fixed-term
contracts and minimum wage for a trainee or
first-time employee. It measures whether
fixed-term contracts are prohibited for permanent tasks, the maximum cumulative duration of fixed-term contracts, and the ratio
of the minimum wage for a trainee or first
time employee to the average value added
per worker.
Difficulty of firing index indicates the extent
of notification and approval requirements for
termination of a redundant worker or group
of redundant workers, obligation to reassign
or retrain, and priority rules for redundancy
and reemployment. It has eight components:
whether redundancy is disallowed as a basis
for terminating workers, whether the employer needs to notify a third party (such as
a government agency) to terminate 1 redundant worker, whether the employer needs
to notify a third party to terminate a group
of 25 redundant workers, whether the employer needs approval from a third party to
terminate 1 redundant worker, whether the
employer needs approval from a third party
to terminate a group of 25 redundant workers, whether the law requires the employer to
reassign or retrain a worker before making
the worker redundant, whether priority rules
apply for redundancies, and whether priority
rules apply for reemployment. For the first
question the answer yes is assigned a score
of 10, and the rest of the questions do not
apply. For the fourth question the answer yes
is assigned a score of 2 and the answer no a 0.
For every other question the answer yes is assigned a score of 1 and the answer no a 0.
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Africa Development Indicators 2011
Firing cost indicates the notice requirements, severance, payments, and penalties
due when terminating a redundant worker,
expressed in weeks of salary.
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 of
three subindexes: the rigidity of hours index,
the difficulty of hiring index, and the difficulty of firing index.
Source: Data are from the World Bank Doing Business project (http://rru.worldbank.
org/DoingBusiness/).
Table 4.2. Investment climate
Private sector fixed capital formation is private
sector fixed capital formation (table 2.21)
divided by nominal gross domestic product
(table 2.1).
Net foreign direct investment is net inflows
of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an
economy other than that of the investor. It
is the sum of equity capital, reinvestment
of earnings, other long-term capital, and
short-term capital as shown in the balance
of payments. This series shows net inflows
(new investment inflows less disinvestment) in the reporting economy from foreign investors.
Domestic credit to private sector is financial
resources provided to the private sector, such
as through loans, purchases of nonequity
securities, and trade credits and other accounts receivable that establish a claim for
repayment. For some countries these claims
include credit to public enterprises.
Firms that believe the court system is fair,
impartial, and uncorrupt are the percentage
of firms that believe the court system is fair,
impartial, and uncorrupt.
Corruption is the percentage of firms identifying corruption as a major constraint to
current operation.
Crime, theft, and disorder are the percentage of firms identifying crime, theft, and
disorder as a major constraint to current
operation.
Tax rates are the percentage of firms identifying tax rates as a major constraint to current operation.
Finance is the percentage of firms identifying access to finance or cost of finance as a
major constraint to current operation.
Electricity is the percentage of firms identifying electricity as a major constraint to current operation.
Labor regulations are the percentage of
firms identifying labor regulations as a major
constraint to current operation.
Labor skills are the percentage of firms
identifying skills of available workers as a
major constraint to current operation.
Transportation is the percentage of firms
identifying transportation as a major constraint to current operation.
Customs and trade regulations are the percentage of firms identifying customs and
trade regulations as a major constraint to
current operation.
Number of tax payments is the number of
taxes paid by businesses, including by electronic filing. The tax is counted as paid once
a year even if payments are more frequent.
Time to prepare, file, and pay taxes is the
number of hours it takes to prepare, file, and
pay (or withhold) three major types of taxes:
the corporate income tax, the value added or
sales tax, and labor taxes, including payroll
taxes and social security contributions.
Total tax rate is the total amount of taxes
payable by the business (except for labor
taxes) after accounting for deductions and
exemptions as a percentage of profit.
Highest marginal tax rate, corporate, is
the highest rate shown on the schedule of
tax rates applied to the taxable income of
corporations.
Time dealing with officials is the average percentage of senior management’s time that is
spent in a typical week dealing with requirements imposed by government regulations
(for example, taxes, customs, labor regulations, licensing, and registration), including
dealings with officials, completing forms, and
the like.
Average time to clear customs, direct exports,
is the average number of days to clear direct
exports through customs.
Average time to clear customs, imports, is
the average number of days to clear imports
through customs.
Interest rate spread is the interest rate
charged by banks on loans to prime customers minus the interest rate paid by
commercial or similar banks for demand,
time, or savings deposits.
Listed domestic companies are domestically
incorporated companies listed on a country’s stock exchanges at the end of the year.
They exclude investment companies, mutual funds, and other collective investment
vehicles.
Market capitalization of listed companies,
also known as market value, is the share price
of a listed domestic company’s stock times
the number of shares outstanding.
Turnover ratio for traded stocks is the total
value of shares traded during the period divided by the average market capitalization
for the period. Average market capitalization
is calculated as the average of the end-ofperiod values for the current period and the
previous period.
Source: Data on private sector fixed capital
formation are from the World Bank World
Development Indicators database. Data on
net foreign direct investment are from the
International Monetary Fund (IMF) Balance of Payments database, supplemented
by data from the United Nations Conference on Trade and Development and official
national sources. Data on domestic credit to
the private sector are from the International
Monetary Fund International Financial Statistics database and data files, World Bank
and Organisation for Economic Co-operation
and Development gross domestic product
(GDP) estimates, and the World Bank World
Development Indicators database. Data on
investment climate constraints to firms are
based on enterprise surveys conducted by
the World Bank and its partners (http://rru.
worldbank.org/EnterpriseSurveys). Data on
regulation and tax administration and highest marginal corporate tax rates are from the
World Bank 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 interest
rate spreads are from the IMF International
Financial Statistics database and data files
and the World Bank World Development
Indicators database. Data on listed domestic
companies, turnover ratios for traded stocks,
and market capitalization are from Standard
Technical notes
145
& Poor’s Global Stock Markets Factbook and
supplemental Standard & Poor’s data.
Table 4.3. Financial sector
infrastructure
Foreign currency sovereign ratings are long- and
short-term foreign currency ratings that assess a sovereign’s capacity and willingness
to honor in full and on time its existing and
future obligations issued in foreign currencies. Short-term ratings have a time horizon
of less than 13 months for most obligations,
or up to 3 years for U.S. public finance, in line
with industry standards, to reflect the unique
risk characteristics of bond, tax, and revenue
anticipation notes that are commonly issued
with terms up to 3 years. Short-term ratings
thus place greater emphasis on the liquidity
necessary to meet financial commitments in
a timely manner.
Gross national savings is the sum of gross
domestic savings (table 2.13) and net factor income and net private transfers from
abroad. The estimate here also includes net
public transfers from abroad.
Money and quasi money (M2) are the sum of
currency outside banks, demand deposits other than those of the central government, and
the time, savings, and foreign currency deposits of resident sectors other than the central
government. This definition of money supply
is frequently called M2 and corresponds to
lines 34 and 35 in the International Monetary
Fund International Financial Statistics.
Real interest rate is the lending interest
rate adjusted for inflation as measured by the
gross domestic product deflator.
Domestic credit to private sector is financial
resources provided to the private sector, such
as through loans, purchases of nonequity
securities, and trade credits and other accounts receivable, that establish a claim for
repayment. For some countries these claims
include credit to public enterprises.
Interest rate spread is the interest rate
charged by banks on loans to prime customers minus the interest rate paid by commercial or similar banks for demand, time, or
savings deposits.
Ratio of bank nonperforming loans to total
gross loans is the value of nonperforming
loans divided by the total value of the loan
portfolio (including nonperforming loans
before the deduction of specific loan-loss
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provisions). The loan amount recorded as
nonperforming should be the gross value of
the loan as recorded on the balance sheet,
not just the amount overdue.
Listed domestic companies are domestically
incorporated companies listed on a country’s stock exchanges at the end of the year.
They exclude investment companies, mutual funds, and other collective investment
vehicles.
Market capitalization of listed companies,
also known as market value, is the share price
of a listed domestic company’s stock times
the number of shares outstanding.
Turnover ratio for traded stocks is the total
value of shares traded during the period divided by the average market capitalization
for the period. Average market capitalization
is calculated as the average of the end-ofperiod values for the current period and the
previous period.
Source: Data on foreign currency sovereign
ratings are from Fitch Ratings (www.fitchratings.com/). Data on gross national savings
are from World Bank national accounts data,
and Organisation for Economic Co-operation
and Development national accounts data
files. Data on money and quasi money and
domestic credit to the private sector are from
the International Monetary Fund International Financial Statistics and data files and
World Bank and OECD estimates of GDP.
Data on real interest rates are from the IMF
International Financial Statistics database
and data files using World Bank data on the
GDP deflator and the World Bank World Development Indicators database. Data on interest rate spreads are from the International
Monetary Fund, International Financial Statistics and data files. Data on ratios of bank
nonperforming loans to total are from the
International Monetary Fund Global Financial Stability Report. Data on bank branches
are from surveys of banking and regulatory
institutions by the World Bank Research
Department and Financial Sector and Operations Policy Department and the World
Development Indicators database. Data on
listed domestic companies and turnover ratios for traded stocks are from Standard &
Poor’s Emerging Stock Markets Factbook and
supplemental data and the World Bank’s
World Development Indicators database.
Data on market capitalization of listed companies are from Standard & Poor’s Emerging
Stock Markets Factbook and supplemental
data, World Bank and OECD estimates of
GDP, and the World Bank World Development Indicators database.
5. Trade and regional integration
Table 5.1. International trade and
tariff barriers
Total trade is the sum of exports and imports
of goods and services measured as a share of
gross domestic product.
Merchandise trade is the sum of imports
and exports of merchandise divided by nominal gross domestic product.
Services trade is the sum of imports and
exports of wholesale and retail trade (including hotels and restaurants), transport, and
government, financial, professional, and
personal services such as education, health
care, and real estate (International Standard
Industrial Classification revision 3 divisions
50–99) less the value of their intermediate
inputs. Also included are imputed bank service charges, import duties, and any statistical discrepancies noted by national compilers or arising from rescaling. It is calculated
without making deductions for depreciation
of fabricated assets or depletion and degradation of natural resources. For countries that
report national accounts data at producer
prices (Angola, Benin, Cape Verde, Comoros,
the Republic of Congo, Côte d’Ivoire, Gabon,
Ghana, Liberia, Niger, Rwanda, São Tomé
and Príncipe, Seychelles, Togo, and Tunisia),
gross value added at market prices is used as
the denominator. For countries that report
national accounts data at basic prices (all other countries), gross value added at factor cost
is used as the denominator. Value added at
basic prices excludes net taxes on products;
value added at producer prices includes net
taxes on products paid by producers but excludes sales or value added taxes.
Exports of goods and services represent the
value of all goods and other market services
provided to the rest of the world. They include
the value of merchandise, freight, insurance,
transport, travel, royalties, license fees, and
other services, such as communication, construction, financial, information, business,
personal, and government services. They
exclude labor and property income (formerly
called factor services) as well as transfer payments and are expressed in current U.S. dollars and as a proportion of nominal GDP.
Imports of goods and services represent the
value of all goods and other market services
received from the rest of the world. They include the value of merchandise, freight, insurance, transport, travel, royalties, license
fees, and other services, such as communication, construction, financial, information,
business, personal, and government services.
They exclude labor and property income (formerly called factor services) as well as transfer payments and are expressed in current
U.S. dollars and as a proportion of nominal
GDP.
Annual growth of exports and imports is calculated using real imports and exports.
Terms of trade index measures the relative
movement of export and import prices. This
series is calculated as the ratio of a country’s
export unit values or prices to its import unit
values or prices and shows changes over a
base year (2000) in the level of export unit
values as a percentage of import unit values.
Structure of merchandise exports and imports
components may not sum to 100 percent because of unclassified trade.
Food comprises the commodities in Standard International Trade Classification
(SITC) sections 0 (food and live animals), 1
(beverages and tobacco), and 4 (animal and
vegetable oils and fats) and SITC division 22
(oil seeds, oil nuts, and oil kernels).
Agricultural raw materials comprise the
commodities in SITC section 2 (crude materials except fuels), excluding divisions 22,
27 (crude fertilizers and minerals excluding
coal, petroleum, and precious stones), and 28
(metalliferous ores and scrap).
Fuel comprises SITC section 3 (mineral
fuels).
Ores and metals comprise the commodities
in SITC sections 27, 28, and 68 (nonferrous
metals).
Manufactures comprise the commodities in SITC sections 5 (chemicals), 6 (basic
manufactures), 7 (machinery and transport
equipment), and 8 (miscellaneous manufactured goods), excluding division 68.
Export diversification index measures the
extent to which exports are diversified. It is
constructed as the inverse of a Herfindahl
Technical notes
147
index, using disaggregated exports at four
digits (following the SITC revision 3). The
total number of products exported includes
only those whose value exceeds $100,000 or
0.3 percent of the country’s total exports,
whichever is smaller. The maximum number of three-digit products that could be
exported is 261. Ranging from 0 to 1, the
index reveals the extent of the differences
between the structure of trade of the country or country group and the world average.
An index value closer to 1 indicates a bigger
difference from the world average. A higher
value indicates more export diversification.
The index is computed by measuring absolute deviation of the country share from
world structure.
Export concentration index, also known
as the Herfindahl-Hirschmann index, is a
measure of the degree of market concentration. The total number of products exported
includes only those whose value exceeds
$100,000 or 0.3 percent of the country’s
total exports, whichever is smaller. The
maximum number of three-digit products
that could be exported is 261. It has been
normalized to a scale of 0–1. An index value close to 1 indicates a very concentrated
market (maximum concentration). Values
closer to 0 reflect a more equal distribution
of market shares among exporters or importers. This type of concentration indicator is vulnerable to cyclical fluctuations in
relative prices, with commodity price rises
making commodity exporters look more
concentrated.
Competitiveness indicator has two aspects:
sectoral effect and global effect. To calculate
both indicators, growth of exports is decomposed into three components: the growth
rate of total international trade over the
reference period (2005–09); the sectoral effect, which measures the contribution to a
country’s export growth of the dynamics of
the sectoral markets where the country sells
its products, assuming that sectoral market
shares are constant; and the competitiveness
effect, which measures the contribution of
changes in sectoral market shares to a country’s export growth.
Tariff barriers are a form of duty based on
the value of an import.
Binding coverage is the percentage of product lines with an agreed bound rate.
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Africa Development Indicators 2011
Simple mean bound rate is the unweighted
average of all the lines in the tariff schedule
in which bound rates have been set.
Simple mean tariff is the unweighted average of effectively applied rates or most favored nation rates for all products subject to
tariffs calculated for all traded goods.
Dispersion around the mean is calculated
as the coefficient of variation of the applied
tariff rates, including preferential rates that
a country applies to its trading partners
available at the six-digit product level of the
Harmonized System in a country’s customs
schedule.
Weighted mean tariff is the average of effectively applied rates or most favored nation
rates weighted by the product import shares
corresponding to each partner country.
Share of lines with international peaks is the
share of lines in the tariff schedule with tariff
rates that exceed 15 percent.
Share of lines with domestic peaks is the
share of lines in the tariff schedule with tariff rates that are more than three times the
simple average tariff .
Share of lines that are bound is the share of
lines in the country’s tariff schedule bound
subject to World Trade Organization negotiation agreements.
Share of lines with specific rates is the share
of lines in the tariff schedule that are set on
a per unit basis or that combine ad valorem
and per unit rates.
Primary products are commodities classified in SITC revision 2 sections 0–4 plus division 68.
Manufactured products are commodities
classified in SITC revision 2 sections 5–8 excluding division 68.
Average cost to ship 20 ft container from port
to destination is the cost of all operations associated with moving a container from onboard a ship to the considered economic center, weighted based on container traffic for
each corridor.
Average time to clear customs, direct exports,
is the average number of days to clear direct
exports through customs.
Average time to clear customs, imports, is
the average number of days to clear imports
through customs.
Source: Data on trade and services are from
World Bank and Organisation for Economic
Co-operation and Development national
accounts data. Data on merchandise trade
are from the World Trade Organization and
World Bank GDP estimates. Data on the
competitiveness indicator are from the Organisation for Economic Co-operation and
Development African Economic Outlook 2011:
Africa and Its Emerging Partners. Data on the
export concentration index and diversification index data are from the United Nations
Conference on Trade and Development Statistical Office data files (http://unctadstat.
unctad.org), with Standard International
Trade Classification groups from the United
Nations Statistics Division (http://unstats.
un.org/unsd/cr/registry/regcst.asp?Cl=14).
Data on tariffs are calculated by World Bank
staff using the World Integrated Trade Solution system (http://wits.worldbank.org) and
data from the United Nations Conference
on Trade and Development Trade Analysis and Information System database and
the World Trade Organization Integrated
Data Base and Consolidated Tariff Schedules database. Data on global imports are
from the United Nations Statistics Division
COMTRADE database. Data on merchandise exports and imports are from World
Bank country desks. Data on shipping costs
are from the World Bank Sub-Saharan Africa
Transport Policy Program. Data on average
time to clear customs are from World Bank
Enterprise Surveys (http://rru.worldbank.
org/EnterpriseSurveys/).
Table 5.2 Top three exports and share
in total exports, 2009
Top exports and share of total exports are based
on exports disaggregated at the four-digit
level (following the Standard International
Trade Classification revision 3).
Number of exports accounting for 75 percent
of total exports is the number of exports in a
country that account for 75 percent of the
country’s exports.
Source: Organisation for Economic Cooperation and Development African Economic
Outlook 2011: Africa and Its Emerging Partners.
Table 5.3 Regional integration, trade
blocs
Type of most recent agreement includes
customs union, under which members
substantially eliminate all tariff and nontariff barriers among themselves and establish
a common external tariff for nonmembers;
economic integration agreement, which liberalizes trade in services among members
and covers a substantial number of sectors,
affects a sufficient volume of trade, includes
substantial modes of supply, and is nondiscriminatory (in the sense that similarly
situated service suppliers are treated the
same); free trade agreement, under which
members substantially eliminate all tariff and nontariff barriers but set tariffs on
imports from nonmembers; partial scope
agreement, which is a preferential trade
agreement notified to the World Trade Organization (WTO) that is not a free trade
agreement, a customs union, or an economic integration; and not notified agreement,
which is a preferential trade arrangement
established among member countries that
is not notified to the WTO (the agreement
may be functionally equivalent to any of the
other agreements).
Merchandise exports within bloc are the sum
of merchandise exports by members of a
trade bloc to other members of the bloc. They
are shown both in U.S. dollars and as a percentage of total merchandise exports by the
bloc.
Merchandise exports by bloc are the sum
of merchandise exports within bloc and
to the rest of the world as a share of total
merchandise exports by all economies in
the world.
Source: Data on merchandise trade flows
are published in the International Monetary
Fund (IMF) Direction of Trade Statistics Yearbook and Direction of Trade Statistics Quarterly. The data in the table were calculated
using the IMF’s Direction of Trade database.
The information on trade bloc membership
is from the World Bank Policy Research Report Trade Blocs (2000), the United Nations
Conference on Trade and Development Trade
and Development Report 2007, the World
Trade Organization Regional Trade Agreements Information System, and the World
Bank and the Center for International Business at the Tuck School of Business at Dartmouth College’s Global Preferential Trade
Agreements Database (http://wits.worldabnk.org/gptad/).
Technical notes
149
6. Infrastructure
Table 6.1. Water and sanitation
Internal fresh water resources per capita are
the sum of total renewable resources, which
include internal flows of rivers and groundwater from rainfall in the country and river
flows from other countries.
Population with sustainable access to an improved water source is the percentage of the
population with reasonable access to an adequate amount of water from an improved
source, such as a household connection,
public standpipe, borehole, protected well or
spring, or rainwater collection. Unimproved
sources include vendors, tanker trucks, and
unprotected wells and springs. Reasonable
access is defined as the availability of at least
20 liters a person a day from a source within
one kilometer of the user’s dwelling.
Population with sustainable access to improved sanitation is the percentage of the
population with at least adequate access to
excreta disposal facilities that can effectively
prevent human, animal, and insect contact
with excreta. Improved facilities range from
simple but protected pit latrines to flush toilets with a sewerage connection. The excreta
disposal system is considered adequate if it
is private or shared (but not public) and if it
hygienically separates human excreta from
human contact. To be effective, facilities
must be correctly constructed and properly
maintained.
Average duration of insufficient water supply
is the average duration of water shortages in
a typical month in the last fiscal year.
Committed nominal investment in water
projects with private participation is annual
committed investment in water projects
with private investment, including projects
for potable water generation and distribution and sewerage collection and treatment
projects.
Official development assistance (ODA) gross
disbursements for water supply and sanitation
sector are disbursements for water supply
and sanitation by bilateral, multilateral, and
other donors. The release of funds to, or the
purchase of goods or services for a recipient;
by extension, the amount thus spent. Disbursements record the actual international
transfer of financial resources or of goods or
services valued at the cost of the donor.
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Source: Data on fresh water resources are
from the Food and Agriculture Organization AQUASTAT database. Data on access
to water and sanitation are from the World
Health Organization and United Nations
Children’s Fund Joint Monitoring Programme (www.wssinfo.org). Data on insufficient water supply are from World Bank
Enterprise Surveys (http://rru.worldbank.
org/EnterpriseSurveys/). Data on committed nominal investment in potable water
projects with private participation are from
the World Bank Private Participation in Infrastructure Project Database (http://ppi.
worldbank.org). Data on official development assistance disbursements are from the
Development Assistance Committee of the
Organisation for Economic Co-operation and
Development Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International
Development Statistics database (www.oecd.
org/dac/stats/idsonline).
Table 6.2. Transportation
Road network is the length of motorways,
highways, main or national roads, secondary
or regional roads, and other roads.
Rail lines are the length of railway route
available for train service, irrespective of the
number of parallel tracks.
Road density, ratio to total land, is the total length of national road network per 100
square kilometers of total land area.
Vehicle fleet is the number of motor vehicles, including cars, buses, and freight vehicles but not two-wheelers.
Commercial vehicles are the number of commercial vehicles that use at least 24 liters of
diesel fuel per 100 kilometers.
Passenger vehicles are road motor vehicles,
other than two-wheelers, intended for the
carriage of passengers and designed to seat
no more than nine people (including the
driver).
Road network in good or fair condition is the
length of the national road network, including the interurban classified network without
the urban and rural network, that is in good
or fair condition, as defined by each country’s
road agency.
Ratio of paved to total roads is the length of
paved roads—which are those surfaced with
crushed stone (macadam) and hydrocarbon
binder or bituminized agents, with concrete,
or with cobblestones—as a percentage of all
the country’s roads.
Price of diesel fuel and gasoline is the price as
posted at filling stations in a country’s capital
city. When several fuel prices for major cities were available, the unweighted average is
used. Since super gasoline (95 octane/A95/
premium) is not available everywhere, it is
sometime replaced by regular gasoline (92
octane/A92), premium plus gasoline (98 octane/A98), or an average of the two.
Committed nominal investment in transport
projects with private participation is annual
committed investment in transport projects
with private investment, including projects
for airport runways and terminals, railways
(including fixed assets, freight, intercity passenger, and local passenger), toll roads, bridges, and tunnels.
Official development assistance (ODA) gross
disbursements for transportation and storage
are disbursements for transportation and
storage by bilateral, multilateral, and other
donors.
Disbursements record the actual international transfer of financial resources or of
goods or services valued at the cost of the
donor.
Source: Data on length of road network
and vehicle fleet are from the International
Road Federation World Road Statistics and
electronic files, except where noted. Data on
rail lines and ratio of paved to total roads
are from the World Bank Transportation,
Water, and Information and Communications Technologies Department, Transport
Division. Data on fuel and gasoline prices
are from the German Agency for Technical
Cooperation. Data on committed nominal
investment in transport projects with private participation are from the World Bank
Private Participation in Infrastructure Project Database (http://ppi.worldbank.org).
Data on official development assistance
disbursements are from the Development
Assistance Committee of the Organisation
for Economic Co-operation and Development Geographical Distribution of Financial
Flows to Developing Countries, Development
Co-operation Report, and International Development Statistics database (www.oecd.
org/dac/stats/idsonline).
Table 6.3. Information and
communication technology
Telephone subscribers are subscribers to a
main telephone line service, which connects a customer’s equipment to the public
switched telephone network or to a cellular
telephone service.
Unmet demand is the number of applications for connection to the public switched
telephone network that have been held back
because of a lack of technical facilities (equipment, lines, and the like) divided by the number of main telephone lines.
Households with own telephone are the
percentage of households possessing a
telephone.
Average delay for firm in obtaining a mainline
phone connection is the average actual delay in
days that firms experience when obtaining
a telephone connection, measured from the
day the establishment applied to the day it
received the service or approval.
Internet users are people with access to the
Internet.
Telephone faults are the total number of reported faults for the year divided by the total
number of mainlines in operation multiplied
by 100. The definition of fault can vary. Some
countries include faulty customer equipment; others distinguish between reported
and actual found faults. There is also sometimes a distinction between residential and
business lines. Another consideration is the
time period: some countries report this indicator on a monthly basis; in these cases data
are converted to yearly estimates.
Telephone faults cleared by next working day
are the percentage of faults in the public
switched telephone network that have been
corrected by the end of the next working day.
Fixed broadband Internet monthly subscription is the monthly subscription charge for
fixed (wired) broadband Internet service.
Fixed (wired) broadband is considered any
dedicated connection to the Internet at
downstream speeds equal to, or greater than,
256 kbit/s, using DSL. Where several offers
are available, preference should be given to
the 256 kbit/s connection. Taxes should be
included. If not included, it should be specified in a note including the applicable tax
rate.
Cost of 3-minute fixed telephone local
phone call during peak hours is the cost of a
Technical notes
151
three-minute local call during peak hours.
Local call refers to a call within the same exchange area using the subscriber’s own terminal (that is, not from a public telephone).
Cost of 3-minute cellular local call during peak
hours is the cost of a three-minute cellular local call during peak hours.
Residential telephone connection charge is
the initial, one-time charge involved in applying for basic telephone service. Where
charges differ by exchange areas, the charge
reported is for the largest urban area.
Business telephone connection charge is the
one-time charge involved in applying for
business basic telephone service. Where
charges differ by exchange area, the charge
reported is for the largest urban area.
Mobile cellular prepaid connection charge is
the initial, one-time charge for a new subscription. Refundable deposits should not
be counted. Although some operators waive
the connection charge, this does not include
the cost of the Subscriber Identity Module
(SIM) card. The price of the SIM card should
be included in the connection charge (for a
prepaid service the cost of SIM is equivalent
to connection charge). It should also be noted if free minutes or free SMS are included
in the connection charge. Taxes should be
included. If not included, it should be specified in a note including the applicable tax
rate.
Mobile cellular postpaid connection charge
is the initial, one-time charge for a new
postpaid subscription. Refundable deposits should not be counted. Although some
operators waive the connection charge, this
does not include the cost of the Subscriber
Identity Module (SIM) card. The price of the
SIM card should be included in the connection charge. It should also be noted if free
minutes or free SMS are included in the connection charge. Taxes should be included. If
not included, it should be specified in a note
including the applicable tax rate.
Fixed broadband Internet connection charge
is the initial, one-time charge for a new fixed
(wired) broadband Internet connection.
The tariffs should represent the cheapest
fixed (wired) broadband entry plan. Refundable deposits should not be counted. Taxes
should be included. If not included, it should
be specified in a note including the applicable
tax rate.
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Africa Development Indicators 2011
Annual investment in fixed telephone service
is the annual investment in equipment for
fixed telephone service.
Annual investment in mobile communication
is the capital investment on equipment for
mobile communication networks.
Annual investment in telecommunications
is the expenditure associated with acquiring the ownership of telecommunication
equipment infrastructure (including supporting land and buildings and intellectual
and nontangible property such as computer
software). It includes expenditure on initial
installations and on additions to existing
installations.
Committed nominal investment in telecommunication projects with private participation
is annual committed investment in telecommunication projects with private investment, including projects for fixed or mobile
local telephony, domestic long-distance telephony, and international long-distance
telephony.
Official development assistance (ODA) gross
disbursements for communication are disbursements for communication by bilateral, multilateral, and other donors. Disbursements
record the actual international transfer of
financial resources or of goods or services
valued at the cost of the donor.
Revenue from fixed telephone services is revenue received for the connection (installation) of telephone service (including charges
for transferring or cancelling a service); revenue from recurring charges for subscription
to telephone (and broadband and Internet
access if not able to be separated from fixed
telephone), including equipment rentals
where relevant; and revenue from calls (local,
national, and international).
Revenue from mobile networks is revenue
from the provision of mobile cellular communications services, including all voice and
data (narrowband and broadband) services.
It refers to revenue earned by retailers, not
by wholesalers.
Total revenue from all telecommunication
services is the total (gross) telecommunication revenue earned from all (fixed, mobile,
and data, including Internet) operators (both
network and virtual) offering services within
the country. It excludes revenues from nontelecommunications services as well as repayable subscribers’ contributions or deposits. It
refers to revenue earned by retailers, and by
wholesalers.
Source: Data on telephone subscribers,
unmet demand, reported phone faults, cost of
local and cellular calls, households with telephone, Internet users and pricing, telephone
and Internet connection charges, and annual
investment and revenue on telecommunications are from the International Telecommunications Union data files. Data on delays for
firms in obtaining a telephone connection are
from World Bank Enterprise Surveys (http://
rru.worldbank.org/EnterpriseSurveys/).
Data on committed nominal investment are
from the World Bank Private Participation
in Infrastructure Project Database (http://
ppi.worldbank.org). Data on official development assistance disbursements are from
the Development Assistance Committee of
the Organisation for Economic Co-operation
and Development Geographical Distribution
of Financial Flows to Developing Countries,
Development Co-operation Report, and International Development Statistics database
(www.oecd.org/dac/stats/idsonline).
Table 6.4. Energy
Electricity production is measured at the terminals of all alternator sets in a station. In
addition to hydropower, coal, oil, gas, and
nuclear power generation, it covers generation by geothermal, solar, wind, and tide and
wave energy, as well as that from combustible renewable and waste. Production includes
the output of electricity plants that are designed to produce electricity only as well as
that of combined heat and power plants.
Hydroelectric refers to electricity produced
by hydroelectric power plants.
Coal refers to all coal and brown coal, both
primary (including hard coal and lignitebrown coal) and derived fuels (including
patent fuel, coke oven coke, gas coke, coke
oven gas, and blast furnace gas). Peat is also
included.
Natural gas refers to natural gas but excludes natural gas liquids.
Nuclear refers to electricity produced by
nuclear power plants.
Oil refers to crude oil and petroleum
products.
Electric power consumption is the production of power plants and combined heat and
power plants, less distribution losses and
own use by heat and power plants.
GDP per unit of energy use is nominal GDP
in purchasing power parity (PPP) U.S. dollars
divided by apparent consumption, which is
equal to indigenous production plus imports
and stock changes minus exports and fuels
supplied to ships and aircraft engaged in international transport.
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. The
indicator is based on the main type of fuel
used for cooking because cooking occupies
the largest share of overall household energy needs. However, many households use
more than one type of fuel for cooking and,
depending on climatic and geographical conditions, heating with solid fuels can also contribute to indoor air pollution.
Firms identifying electricity as major or very
severe obstacle to business operation and growth
are the percentage of firms that responded
“major” or “very severe” to the following
question: “Please tell us if any of the following issues are a problem for the operation
and growth of your business. If an issue (infrastructure, regulation, and permits) poses
a problem, please judge its severity as an obstacle on a five-point scale that ranges from
0 = no obstacle to 5 = very severe obstacle.”
Average delay for firm in obtaining electrical connection is the average actual delay in
days that firms experience when obtaining
an electrical connection, measured from the
day the establishment applied to the day it
received the service or approval.
Electric power transmission and distribution
losses are technical and nontechnical losses,
including electricity losses due to operation
of the system and the delivery of electricity
as well as those caused by unmetered supply.
This comprises all losses due to transport and
distribution of electrical energy and heat.
Electrical power outages in a typical month is
the average number of electrical power outages in a typical month.
Firms that share or own their own generator
are the percentage of firms that responded
“Yes” to the following question: “Does your
establishment own or share a generator?”
Technical notes
153
Firms using electricity from generator are the
percentage of firms using electricity supplied
from a generator or generators that the firm
owns or shares.
Committed nominal investment in energy
projects with private participation is annual
committed investment in energy projects
with private investment, including projects
for electricity generation, transmission, and
distribution as well as natural gas transmission and distribution.
Official development assistance (ODA) gross
disbursements for energy are disbursements
for energy by bilateral, multilateral, and other donors. Disbursements record the actual
international transfer of financial resources
or of goods or services valued at the cost of
the donor.
Source: Data on electricity production and
consumption are from the International Energy Agency (www.iea.org/stats/index.asp),
Energy Statistics of Non-OECD Countries, Energy Balances of Non-OECD Countries, Energy
Statistics of OECD Countries, and Energy Balances of OECD Countries. Data on PPP GDP
per unit of energy use are from the International Energy Agency (www.iea.org/stats/
index.asp) and World Bank PPP data. Data
on solid fuels use are from household survey
data, supplemented by World Bank Project
Appraisal Documents. Data on firms identifying electricity as a major or very severe
obstacle to business operation and growth,
delays for firms in obtaining an electrical
connection, electrical outages of firms, firms
that share or own their own generator, and
firms using electricity from generator are
from World Bank Enterprise Surveys (http://
rru.worldbank.org/EnterpriseSurveys/).
Data on transmission and distribution losses are from the International Energy Agency
(www.iea.org/stats/index.asp), Energy Statistics of Non-OECD Countries, Energy Balances of Non-OECD Countries, Energy Statistics of OECD Countries, and Energy Balances
of OECD Countries and the United Nations
Energy Statistics Yearbook. Data on committed nominal investment are from the World
Bank Private Participation in Infrastructure
Project Database (http://ppi.worldbank.
org). Data on official development assistance
disbursements are from the Development Assistance Committee of the Organisation for
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Africa Development Indicators 2011
Economic Co-operation and Development
Geographical Distribution of Financial Flows to
Developing Countries, Development Co-operation Report, and International Development
Statistics database (www.oecd.org/dac/stats/
idsonline).
7. Human development
Table 7.1. Education
Youth literacy rate is the percentage of people
ages 15–24 who can, with understanding,
both read and write a short, simple statement about their everyday life.
Adult literacy rate is the proportion of
adults ages 15 and older who can, with understanding, read and write a short, simple
statement on their everyday life.
Primary education provides children with
basic reading, writing, and mathematics
skills along with an elementary understanding of such subjects as history, geography,
natural science, social science, art, and music.
Secondary education completes the provision of basic education that began at the primary level and aims to lay the foundations
for lifelong learning and human development
by offering more subject- or skill-oriented instruction using more specialized teachers.
Tertiary education, whether or not at an
advanced research qualification, normally
requires, as a minimum condition of admission, the successful completion of education
at the secondary level.
Gross enrollment ratio is the ratio of total
enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown.
Net enrollment ratio is the ratio of children
of official school age, based on the International Standard Classification of Education
1997, who are enrolled in school to the population of the corresponding official school
age.
Student-teacher ratio is the number of students enrolled in school divided by the number of teachers, regardless of their teaching
assignment.
Public spending on education is current and
capital public expenditure on education plus
subsidies to private education at the primary,
secondary, and tertiary levels by local, regional, and national government, including municipalities. It excludes household contributions.
Source: United Nations Educational, Scientific and Cultural Organization (UNESCO)
Institute for Statistics.
Table 7.2. Health
Life expectancy at birth is the number of years
a newborn infant would live if prevailing
patterns of mortality at the time of its birth
were to remain the same throughout its life.
Data are World Bank estimates based on data
from the United Nations Population Division, the United Nations Statistics Division,
and national statistical offices.
Under-five mortality rate is the probability
that a newborn baby will die before reaching
age 5, if subject to current age-specific mortality rates. The probability is expressed as a
rate per 1,000.
Infant mortality rate is the number of infants dying before reaching age 1, per 1,000
live births.
Maternal mortality ratio, modeled estimate,
is the number of women who die from pregnancy-related causes during pregnancy and
childbirth, per 100,000 live births. The data
are estimated by a regression model using information on fertility, birth attendants, and
HIV prevalence.
Prevalence of HIV is the percentage of people ages 15–49 who are infected with HIV.
Incidence of tuberculosis is the number of
tuberculosis cases (pulmonary, smear positive, and extrapulmonary) in a population
at a given point in time, per 100,000 people.
This indicator is sometimes referred to as
“point prevalence.” Estimates include cases
of tuberculosis among people with HIV.
Clinical malaria cases reported are the sum
of cases confirmed by slide examination or
rapid diagnostic test and probable and unconfirmed cases (cases that were not tested but
treated as malaria). National malaria control
programs often collect data on the number of
suspected cases, those tested, and those confirmed. Probable or unconfirmed cases are
calculated by subtracting the number tested
from the number suspected. Not all cases reported as malaria are true malaria cases; most
health facilities lack appropriate diagnostic
services. The misdiagnosis may have led to
under- or overreporting malaria cases and
missing diagnosis of other treatable diseases.
Reported malaria deaths are all deaths in
health facilities that are attributed to malaria,
whether or not confirmed by microscopy or
by rapid diagnostic test.
Child immunization rate is the percentage
of children ages 12–23 months who received
vaccinations before 12 months or at any time
before the survey for four diseases—measles
and diphtheria, pertussis (whooping cough),
and tetanus (DPT). A child is considered adequately immunized against measles after receiving one dose of vaccine and against DPT
after receiving three doses.
Stunting is the percentage of children under age 5 whose height for age is more than
two standard deviations below the median for
the international reference population ages
0–59 months. For children up to age 2, height
is measured by recumbent length. For older
children, height is measured by stature while
standing. The reference population adopted
by the World Health Organization (WHO)
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 reference standard for their age as established by the WHO, the U.S. Centers for
Disease Control and Prevention, and the U.S.
National Center for Health Statistics. Data
are based on children under age 3, 4, and 5,
depending on the country.
Births attended by skilled health staff are the
percentage of deliveries attended by personnel trained to give the necessary supervision,
care, and advice to women during pregnancy,
labor, and the postpartum period; to conduct deliveries on their own; and to care for
newborns.
Contraceptive use is the percentage of women ages 15–49, married or in union, who are
practicing, or whose sexual partners are practicing, any form of contraception. Modern
methods of contraception include female
and male sterilization, oral hormonal pills,
the intrauterine device, the male condom, injectables, the implant (including Norplant),
vaginal barrier methods, the female condom,
and emergency contraception.
Children sleeping under insecticide-treated
nets are the percentage of the children under
age 5 with access to an insecticide-treated net
to prevent malaria.
Tuberculosis case detection rate, all forms, is
the percentage of newly notified tuberculosis
Technical notes
155
cases (including relapses) to estimated incident cases (case detection, all forms).
Tuberculosis treatment success rate is the
percentage of new, registered smear-positive
(infectious) cases that were cured or in which
a full course of treatment was completed.
Children with fever receiving any antimalarial
treatment same or next day are the percentage of children under age 5 in malaria-risk
areas with fever being treated with any antimalarial drugs.
Population with sustainable access to an improved water source is the percentage of 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.
Physicians are the number of physicians,
including generalists and specialists, per
1,000 people.
Nurses and midwives are the number of
professional nurses, auxiliary nurses, enrolled nurses, and other nurses, such as dental nurses and primary care nurses, and professional midwives, auxiliary midwives, and
enrolled midwives, per 1,000 people.
Community workers is the number of
community workers, which includes various types of community health aides, many
with country-specific occupational titles
such as community health officers, community health-education workers, family health
workers, woman health visitors, and health
extension package workers, per 1,000 people.
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Africa Development Indicators 2011
Total health expenditure is the sum of public
and private health expenditure. It covers the
provision of health services (preventive and
curative), family planning activities, nutrition activities, and emergency aid designated
for health but does not include provision of
water and sanitation.
Public health expenditure consists of recurrent and capital spending from government
(central and local) budgets, external borrowings and grants (including donations from
international agencies and nongovernmental
organizations), and social (or compulsory)
health insurance funds.
Private health expenditure includes direct
household (out-of-pocket) spending, private
insurance, charitable donations, and direct
service payments by private corporations.
External resources for health are funds or
services in kind that are provided by entities
not part of the country in question. The resources may come from international organizations, other countries through bilateral
arrangements, or foreign nongovernmental
organizations. These resources are part of total health expenditure.
Out-of-pocket expenditure is any direct outlay by households, including gratuities and
in-kind payments, to health practitioners
and suppliers of pharmaceuticals, therapeutic appliances, and other goods and services
whose primary intent is to contribute to the
restoration or enhancement of the health
status of individuals or population groups. It
is a part of private health expenditure.
Private prepaid plans are expenditure on
health by private insurance institutions. Private insurance enrollment may be contractual or voluntary, and conditions and benefits or a basket of benefits are agreed on a
voluntary basis between the insurance agent
and the beneficiaries. They are thus not controlled by government units for the purpose
of providing social benefits to members.
Health expenditure per capita is the sum of
public and private health expenditures divided
by total population. It covers the provision of
health services (preventive and curative), family planning activities, nutrition activities, and
emergency aid designated for health but does
not include provision of water and sanitation.
Source: Data on life expectancy at birth,
under-five mortality, infant mortality, maternal
mortality, prevalence of HIV, incidence of tuberculosis, child immunization, malnutrition,
births attended by skilled health staff, contraceptive use, children sleeping under insecticide-treated nets, and children receiving
antimalarial drugs are from World Bank staff
estimates based on various sources, including
census reports, the United Nations Population Division World Population Prospects, national statistical offices, household surveys
conducted by national agencies and Macro
International, the World Health Organization
(WHO), and the United Nations Children’s
Fund (UNICEF). Data on clinical malaria cases reported and reported malaria deaths are
from the WHO World Malaria Report 2010.
Data on physicians, nurses, and community
health workers are from the WHO Global
Atlas of the Health Workforce (http://apps.
who.int/globalatlas/). Data on tuberculosis
are from the WHO Global Tuberculosis Control
Report. Data on access to water and sanitation are from the WHO and UNICEF Fund
Joint Monitoring Programme (www.wssinfo.
org). Data on health expenditure are from
the WHO National Health Account database
(www.who.int/nha/en), supplemented by
country data.
8. Agriculture, rural development, and
Environment
Table 8.1. Rural development
Rural population is the difference between the
total population and the urban population.
Rural population density is the rural population divided by the arable land area. Arable
land includes land defined by the Food and
Agriculture Organization (FAO) as land under temporary crops (double-cropped areas
are counted once), temporary meadows for
mowing or pasture, land under market or
kitchen gardens, and land temporarily fallow.
Land abandoned as a result of shifting cultivation is excluded.
Share of rural population below the national
poverty line is the percentage of the rural population living below the national poverty line.
Rural population poverty gap at national poverty line is the mean shortfall from the poverty line (counting the nonpoor as having zero
shortfall), expressed as a percentage of the
poverty line. This measure reflects the depth
of poverty as well as its incidence.
Share of rural population with sustainable access to an improved water source is the percentage of the rural population with reasonable
access to an adequate amount of water from
an improved source, such as a household
connection, public standpipe, borehole, protected well or spring, or rainwater collection.
Unimproved sources include vendors, tanker
trucks, and unprotected wells and springs.
Reasonable access is defined as the availability of at least 20 liters a person a day from
a source within 1 kilometer of the dwelling.
Share of rural population with sustainable access to improved sanitation facilities is the percentage of the rural population with at least
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 rural population are calculated from urban population shares from the
United Nations Population Division World
Urbanization Prospects and from total population figures from the World Bank. Data on
rural population density are from the FAO
and World Bank population estimates. Data
on rural population below the poverty line
and the rural population poverty gap are
from the Global Poverty Working Group and
are based on World Bank’ country poverty
assessments and country poverty reduction
strategies. Data on access to water and sanitation are from the World Health Organization and United Nations Children’s Fund
Joint Monitoring Programme (www.wssinfo.
org).
Table 8.2. Agriculture
Agriculture value added is the gross output of
forestry, hunting, and fishing, crop cultivation, and livestock production (International
Standard Industrial Classification [ISIC] revision 3 divisions 1–5) less the value of their
intermediate inputs. It is calculated without
making deductions for depreciation of fabricated assets or depletion and degradation of
Technical notes
157
natural resources. For countries that report
national accounts data at producer prices
(Angola, Benin, Cape Verde, Comoros, the
Republic of Congo, Côte d’Ivoire, Gabon,
Ghana, Liberia, Niger, Rwanda, São Tomé
and Príncipe, Seychelles, Togo, and Tunisia),
gross value added at market prices is used as
the denominator. For countries that report
national accounts data at basic prices (all
other countries), gross value added at factor
cost is used as the denominator. Value added
at basic prices includes net taxes on products;
value added at producer prices includes net
taxes on products paid by producers but excludes sales or value added taxes.
Total agriculture gross production index is
total agricultural production relative to the
base period 1999–2001.
Crop gross production index is agricultural crop
production relative to the base period 1999–
2001. It includes all crops except fodder crops.
Livestock gross production index covers meat
and milk from all sources, cheese, eggs, honey, raw silk, wool, and hides and skins.
Food gross production index covers food crops
that are considered edible and that contain nutrients. Coffee and tea are excluded because,
although edible, they have no nutritive value.
Cereal gross production index covers cereals
that are considered edible and that contain
nutrients.
Cereal production is crops harvested for dry
grain only. Cereal crops harvested for hay or
harvested green for food, feed, or silage and
those used for grazing are excluded.
Cereal includes wheat, rice, maize, barley,
oats, rye, millet, sorghum, buckwheat, and
mixed grains.
Agricultural exports and imports are expressed in current U.S. dollars at free on
board prices. The term agriculture in trade
refers to both food and agriculture and does
not include forestry and fishery products.
Food exports and imports are expressed in
current U.S. dollars at free on board prices
for exports and cost, insurance, and freight
prices for imports.
Permanent cropland is land cultivated with
crops that occupy the land for long periods
and need not be replanted after each harvest,
such as cocoa, coffee, and rubber. It includes
land under flowering shrubs, fruit trees, nut
trees, and vines but excludes land under trees
grown for wood or timber.
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Africa Development Indicators 2011
Cereal cropland refers to harvested area, although some countries report only sown or
cultivated area.
Agricultural irrigated land is areas equipped
to provide water to the crops, including areas equipped for full and partial control irrigation, spate irrigation areas, and equipped
wetland or inland valley bottoms.
Fertilizer consumption 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 Food and
Agriculture Organization (FAO) as land under temporary crops (double-cropped areas
are counted once), temporary meadows for
mowing or 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
and B (ISIC revision 3) and includes hunting,
forestry, and fishing.
Agriculture value added per worker is the
output of the agricultural sector (ISIC divisions 1–5) less the value of intermediate
inputs. Agriculture comprises value added
from forestry, hunting, fishing, crop cultivation, and livestock production. Data are in
constant 2000 U.S. dollars.
Cereal yield is dry grain only and includes
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.
Source: Data on agriculture value added
are from Organisation for Economic Co-operation and Development and World Bank
national accounts data files. Data on crop,
livestock, food, and cereal production, cereal
exports and imports, agricultural exports
and imports, permanent cropland, cereal
cropland, agricultural machinery, cereal yield,
and fertilizer consumption are from FAO
Transformation of Rwanda’s coffee sector: an African success story
Table 1
as of 2006, and Rwandan coffee exports generated more than
$47 million in revenue in 2008, compared with $35 million in 2007.
Figure 1
Green coffee price ($ per kilogram)
For many years, Rwanda’s coffee sector was stuck in a “lowquality/low-quantity trap.” Compulsory production, substantial
export taxes, and a monopsony export control agency meant that
producers had little incentive to invest in producing high-quality
coffee. Highly volatile world coffee prices in the 1980s (and state
capture during boom years), coupled with the country’s economic
deterioration during the 1994 genocide, left coffee producers in an
even worse situation.
The post-genocide regime set out to revitalize and transform
the coffee sector. Changes were implemented in several waves.
The first began in the late 1990s, when the government removed
a variety of trade barriers, created incentives for groups and individuals to transfer their efforts from semiwashed to fully washed
(higher value) coffee as an end product, and facilitated entrepreneurship in the coffee industry. More substantial reform efforts
began in 2000, when the government, working with consultants
and donors, studied the potential for adding value to Rwandan
coffee by producing higher-quality, washed, and fermented specialty coffee. In 2002, the government issued a national coffee
strategy that outlined a plan for capturing a larger share of the
specialty-coffee sector. In the intervening years, more than 100
coffee washing stations were built (table 1).
Punam Chuhan-Pole and Manka S. Angwafo
Average farmer and export prices, 2003–08
4
3
Average export price
Cherry price premium
2
Cherry price OCIR Cafe
1
0
2003
2004
2005
2006
2007
2008
Source: Rwanda Ministry of Agriculture and Animal Husbandry and Ministry of Trade and Industry (2008).
Figure 2
Farmers
Value chain for washed coffee
Buyers—
private CWS
or Co-op
Millers and
exporters
Auction
(Mombasa)
Importers
Retailers
Consumers
Growth in the specialty coffee sector
2001 2002 2003 2004 2005 2006 2007 2008
Washing stations
—
1
10
Green specialty
coffee exported (tons) —
30
300
—
2
8
Total value of specialty
cofee exported
($ thousands)
—
90
720
Specialty coffee
buyers
25
45
76
112
—
2009
112
800 1,200 3,000 2,300 2,455 3,045
16
25
30
30
—
—
1,850 3,168 8,000 7,800 8,060 11,600
— is not available.
Source: U.S. Agency for International Development.
Rwanda’s approach to liberalizing its coffee sector has resulted in the country’s coffee farmers having the opportunity to
sell higher-quality beans for a higher price. Indeed, the average export price of coffee nearly doubled over 2003–2008, from $1.60 to
$3.10 (figure 1). For smallholder farmers and other participants in
the coffee value chain (figure 2), producing specialty coffee means
not just more income but expanded connections to world markets
and positive effects from informal economic cooperation at coffee
washing stations. Coffee washing stations had created 4,000 jobs
electronic files and website. Data on agricultural employment are from the International
Labour Organization Key Indicators of the
Labour Market database.
Table 8.3. Producer food prices
Prices in U.S. dollars are equal to producer
prices in local currency times the exchange
Rwanda’s experience shows that reforming policies can unleash private sector activity and pave the way for growth. The willingness of the government to allow liberalization of the coffee sector has paid off. Rwanda could further improve the performance of
this sector—for example, by implementing further price incentives
for producers to focus on high-quality coffee, improving management of producer cooperatives, and reducing still-high transportation costs related to poor infrastructure and the country’s landlocked status.
Source: Adapted from K. Boudreaux. 2010. “A Better Brew for Success
in Rwanda: Economic Liberalization in the Coffee Sector.” In Yes Africa
Can: Success Stories from a Dynamic Continent, ed. P. Chuhan-Pole and
M. Angwafo. World Bank: Washington, DC.
rate of the selected year. The main source
for exchange rates is the International Monetary Fund. Where official and commercial
exchange rates differ significantly, the commercial exchange rate may be applied. Producer prices are prices received by farmers
for primary agricultural products as defined
in the 1993 System of National Accounts.
Technical notes
159
The producer price is the amount receivable
by the producer from the purchaser for a unit
of a good or service produced as output minus any value added tax or similar deductible
tax invoiced to the purchaser. It excludes any
transport charges invoiced separately by the
producer. Time series refer to the national
average prices of individual commodities
comprising all grades, kinds, and varieties
received by farmers when they participate in
their capacity as sellers of their own products
at the farm gate or first point of sale.
Source: Data are from Food and Agriculture
Organization electronic files and website.
Table 8.4. Environment
Forest area is land under natural or planted
stands of trees, whether productive or not.
Renewable internal fresh water resources refer to internal renewable resources (internal
river flows and groundwater from rainfall) in
the country.
Annual fresh water withdrawals refer to total water withdrawals, not counting evaporation losses from storage basins. Withdrawals
also include water from desalination plants
in countries where they are a significant
source. Withdrawals can exceed 100 percent
of total renewable resources where extraction from nonrenewable aquifers or desalination plants is considerable or where there is
significant water reuse. Withdrawals for agriculture and industry are total withdrawals
for irrigation and livestock production and
for direct industrial use (including withdrawals for cooling thermoelectric plants). Withdrawals for domestic uses include drinking
water, municipal use or supply, and use for
public services, commercial establishments,
and homes.
Water productivity is calculated as gross domestic product in constant prices divided by
annual total water withdrawal.
Emissions of organic water pollutants are
measured in terms of biochemical oxygen demand, which refers to the amount of oxygen
that bacteria in water will consume in breaking down waste. This is a standard watertreatment test for the presence of organic
pollutants.
Energy production refers to forms of primary energy—petroleum (crude oil, natural
gas liquids, and oil from nonconventional
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Africa Development Indicators 2011
sources), natural gas, solid fuels (coal, lignite,
and other derived fuels), and combustible renewable and waste—and primary electricity,
all converted into oil equivalents.
Energy use refers to use of primary energy
before transformation to other end-use fuels,
which is equal to indigenous production plus
imports and stock changes, minus exports
and fuels supplied to ships and aircraft engaged in international transport.
Combustible renewables and waste comprise
solid biomass, liquid biomass, biogas, industrial waste, and municipal waste, measured
as a percentage of total energy use.
Carbon dioxide emissions are those stemming from the burning of fossil fuels and
the manufacture of cement. They include
carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas
flaring.
Methane emissions, total, are those from
human activities such as agriculture and
from industrial methane production.
Methane emissions, agricultural, are those
from animals, animal waste, rice production,
agricultural waste burning (nonenergy, onsite), and savannah burning.
Methane emissions, industrial, are those
from the handling, transmission, and combustion of fossil fuels and biofuels.
Nitrous oxide emissions, total, are those
from agricultural biomass burning, industrial activities, and livestock management.
Nitrous oxide emissions, agricultural, are
those produced through fertilizer use (synthetic and animal manure), animal waste
management, agricultural waste burning
(nonenergy, on-site), and savannah burning.
Nitrous oxide emissions, industrial, are those
produced during the manufacturing of adipic
acid and nitric acid.
Other greenhouse gas emissions are by-product emissions of hydrofluorocarbons, perfluorocarbons, and sulfur hexafluoride.
Official development assistance (ODA) gross
disbursements for forestry are disbursements
for forestry by bilateral, multilateral, and other donors. Disbursements record the actual
international transfer of financial resources
or of goods or services valued at the cost of
the donor.
Official development assistance (ODA)
gross disbursements for general environment
protection are disbursements for general
Food prices in Africa
Sailesh Tiwari and Hassan Zaman
Although global food prices remain high, the World Bank’s
nominal food price index has stabilized in recent months after
peaking during the food price crisis in February. Still, prices are
only 6 percent less than the 2008 peaks and continuing uncertainties are likely to keep them volatile. The primary drivers of
the most recent surge in food prices include: severe weather
events in key grain exporting countries, such as the Argentina,
Australia, Canada, Kazakhstan, and the Russian Federation in
the second half of 2010; broad increases in prices of agricultural commodities and the resultant increases in competition
for land and other inputs; and the link between higher oil prices
and the diversion of key food commodities into the production
of biofuels.
In Africa, however, domestic prices of key food commodities
have been driven largely by the variability of local supply, as opposed to global trends. The continent’s isolated agricultural markets might be a reason for the low pass-through of global prices.
One particularly salient consequence is that local shortfalls in
production—related either to poor rains and drought or to supply
disruptions resulting from conflict—often lead to significant differences in price movements within countries. The price of rice in
Benin, for instance, rose 33 percent in Bohicon but fell 4 percent
in Cotonou between March and April 2011. A low average increase
in food prices can mask significant increases in poverty in specific
parts of a country, a primary reason some countries have isolated
pockets of food insecurity.
Recent food price trends in Africa underscore this point. Eastern Africa was hit with a drought severely affecting the secondary
season harvests, and as a result the prices of maize and sorghum—
the region’s two main staples—have risen sharply since February.
Maize prices in Kenya and Uganda had almost doubled by May,
and in Tanzania (Dar es Salaam) they were 59 percent higher than a
year ago. By contrast, favorable prospects for maize harvests have
led to steady or declining prices across Southern Africa.
Western Africa, where sorghum and millet are the staple
crops, still enjoys adequate supplies from the bumper harvests of
previous years. The prices of these crops have remained stable
in Burkina Faso, Mali, and Niger, and even where there has been
some seasonal increase, as in some markets in Chad, the price
levels remain lower than where they were last year. However, rising
costs of importing fuel and food grains, such as rice and wheat,
pose a significant threat to the region’s macroeconomic stability.
Net importers of food and fuel will likely see external and fiscal
balances erode and inflationary pressures build up, as import bills
grow and governments shelter domestic consumers from high international prices. Already, Sierra Leone has reduced import duties on rice and petroleum products by 10 percent to avert growing
unrest over rising prices of essential commodities.
environment protection by bilateral, multilateral, and other donors. Disbursements
record the actual international transfer of
financial resources or of goods or services
valued at the cost of the donor.
Co-operation and Development Geographical
Distribution of Financial Flows to Developing
Countries, Development Co-operation Report,
and International Development Statistics database (www.oecd.org/dac/stats/idsonline).
Source: Data on forest area and deforestation are from the Food and Agriculture Organization (FAO) Global Forest Resources Assessment. Data on fresh water resources and
withdrawals are from the World Resources
Institute, supplemented by FAO AQUASTAT
data. Data on emissions of organic water pollutants are from the World Bank. Data on energy production and use and combustible renewable and waste are from the International
Energy Agency. Data on carbon dioxide emissions are from Carbon Dioxide Information
Analysis Center, Environmental Sciences Division, Oak Ridge National Laboratory. Data
on methane emissions, nitrous oxide emissions, and other greenhouse gas emissions are
from the International Energy Agency. Data
on official development assistance disbursements are from the Development Assistance
Committee of the Organisation for Economic
Table 8.5. Fossil fuel emissions
Carbon dioxide emissions are those stemming
from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid,
liquid, and gas fuels and gas flaring.
Carbon dioxide emissions per capita are carbon dioxide emissions divided by midyear
population.
Fossil fuel is any hydrocarbon deposit that
can be burned for heat or power, such as petroleum, coal, and natural gas.
Total carbon dioxide emissions from fossil fuels is the sum of all fossil fuel emissions (solid
fuel consumption, liquid fuel consumption,
gas fuel consumption, gas flaring, and cement production).
Carbon dioxide emissions from solid fuel
consumption refer mainly to emissions from
use of coal as an energy source and from
Technical notes
161
secondary fuels derived from hard and soft
coal (such as coke-oven coke).
Carbon dioxide emissions from liquid fuel consumption refer to emissions from use of crude
petroleum and natural gas liquids as an energy source and from secondary fuels derived
from oil (such as jet fuel).
Carbon dioxide emissions from gas fuel consumption refer mainly to emissions from use
of natural gas as an energy source and from
secondary fuels derived from natural gas
(such as blast furnace gas).
Carbon dioxide emissions from gas flaring refer
mainly to emissions from gas flaring activities.
Carbon dioxide emissions from cement production refer mainly to emissions during cement
production. Cement production is a multistep
process, and carbon dioxide is actually released
from klinker production during the process.
Source: Data on carbon dioxide emissions and
fossil fuels are from Carbon Dioxide Information Analysis Center Environmental Sciences
Division, Oak Ridge National Laboratory.
9. Labor, migration, and population
Table 9.1. Labor force participation
Labor force is people ages 15 and older who
meet the International Labour Organization
(ILO) definition of the economically active
population. It includes both the employed and
the unemployed. While national practices vary
in the treatment of such groups as the armed
forces and seasonal or part-time workers, the
labor force generally includes the armed forces, the unemployed, and first-time job seekers
but excludes homemakers and other unpaid
caregivers and workers in the informal sector.
Participation rate is the percentage of the
population of the specified age group that is
economically active—that is, all people who
supply labor for the production of goods and
services during a specified period.
Source: ILO Key Indicators of the Labour
Market database.
Table 9.2. Labor force composition
Agriculture corresponds to division 1 (International Standard Industrial Classification
[ISIC] revision 2) or tabulation categories A
and B (ISIC revision 3) and includes hunting,
forestry, and fishing.
162
Africa Development Indicators 2011
Industry corresponds to divisions 2–5
(ISIC revision 2) or tabulation categories C–F
(ISIC revision 3) and includes mining and
quarrying (including oil production), manufacturing, construction, and public utilities
(electricity, gas, and water).
Services correspond to divisions 6–9 (ISIC
revision 2) or tabulation categories G–P (ISIC
revision 3) and include wholesale and retail
trade and restaurants and hotels; transport,
storage, and communications; financing, insurance, real estate, and business services;
and community, social, and personal services.
Wage and salaried workers are workers who
hold the type of jobs defined as paid employment jobs, where incumbents hold explicit
(written or oral) or implicit employment contracts that give them a basic remuneration
that is not directly dependent on the revenue
of the unit for which they work.
Self-employed workers are self-employed
workers with employees (employers), selfemployed workers without employees (ownaccount workers), and members of producer
cooperatives. Although the contributing
family workers category is technically part
of the self-employed according to the classification used by the International Labour
Organization (ILO), and could therefore
be combined with the other self-employed
categories to derive the total self-employed,
they are reported here as a separate category to emphasize the difference between
the two statuses, since the socioeconomic
implications associated with each status
can vary substantially. This practice follows
that of the ILO Key Indicators of the Labour
Market.
Contributing family workers are unpaid
workers who hold self-employment jobs as
own-account workers in a market-oriented
establishment operated by a related person
living in the same household.
Source: ILO Key Indicators of the Labour
Market database.
Table 9.3. Unemployment
Unemployment is the share of the labor force
of the specified subgroup without work but
available for and seeking employment.
Primary education provides children with
basic reading, writing, and mathematics skills
along with an elementary understanding of
such subjects as history, geography, natural
science, social science, art, and music.
Secondary education completes the provision of basic education that began at the
primary level and aims to lay the foundations for lifelong learning and human development by offering more subject- or skilloriented instruction using more specialized
teachers.
Tertiary education, whether or not at an
advanced research qualification, normally
requires, as a minimum condition of admission, the successful completion of education
at the secondary level.
Source: International Labour Organization Key Indicators of the Labour Market
database.
Table 9.4. Migration and population
Migrant stock is the number of people born in
a country other than that in which they live.
It includes refugees.
Net migration is the annual number of
immigrants less the annual number of emigrants, including both citizens and noncitizens. Data are five-year estimates.
Worker remittances, received, comprise current transfers by migrant workers and wages
and salaries by nonresident workers.
Migrant remittance flows are the sum of
worker remittances, compensation of employees, and migrants’ transfers, as recorded
in the International Monetary Fund Balance
of Payments.
Population is total population based on
the de facto definition of population, which
counts all residents regardless of legal status
or citizenship, except for refugees not permanently settled in the country of asylum, who
are generally considered part of the population of their country of origin. The values
shown are midyear estimates.
Fertility rate is the number of children that
would be born to a woman if she were to live
to the end of her childbearing years and bear
children in accordance with current age-specific fertility rates.
Age composition refers to the percentage
of the total population that is in specific age
groups.
Dependency ratio is the ratio of dependents
—people younger than 15 or older than 64—
to the working-age population (ages 15–64).
Rural population is calculated as the difference between the total population and the
urban population.
Urban population is the midyear population
of areas defined as urban in each country.
Source: Data on migration are from the
United Nations Population Division Trends in
Total Migrant Stock: The 2008 Revision. Data on
population are from the United Nations Population Division World Population Prospects: The
2008 Revision, census reports and other statistical publications from national statistical
offices, Eurostat Demographic Statistics, Secretariat of the Pacific Community Statistics and
Demography Programme, U.S. Census Bureau
International Database, and World Bank estimates based on data from these sources as well
as household surveys conducted by national
agencies, Macro International, the U.S. Centers for Disease Control and Prevention, and
refugees statistics from the United Nations
High Commissioner for Refugees. Data on
dependency ratio are from World Bank staff
estimates based on various sources, including
census reports, the United Nations Population Division World Population Prospects, national statistical offices, household surveys
conducted by national agencies, and Macro
International. Data on worker remittances are
from the International Monetary Fund Balance of Payments Statistics Yearbook and data
files. Data from migrant remittance flows are
from World Bank staff estimates based on the
International Monetary Fund Balance of Payments Statistics Yearbook 2008.
10. HIV/AIDS
Table 10.1. HIV/AIDS
Estimated number of people living with HIV/
AIDS is the number of people in the specified
age group living with HIV.
Estimated HIV prevalence rate is the percentage of the population of the specified
age subgroup who are infected with HIV. Depending on the reliability of the data available, there may be uncertainty surrounding
each estimate. Therefore, plausible bounds
are presented for each subgroup rate (low
and high estimate).
Deaths of adults and children due to
HIV/AIDS are the estimated number of adults
and children that have died in a specific year,
Technical notes
163
Migration and remittances in Africa
Dilip Ratha, Sanket Mohapatra, Caglar Ozden, Sonia Plaza, and Abebe Shimeles
Every country in Africa has been affected by migration. Often
viewed as a “brain drain,” migration can generate substantial benefits for origin countries through remittances, investments, contacts with foreign markets, technology transfer, enhanced skills of
returning emigrants, and even increased demand for education
(World Bank 2011a). About 30 million Africans (roughly 3 percent
of the population) have left their origin country—and sometimes
the continent. Some two-thirds of migrants from Sub-Saharan Africa, particularly the poorer, go to other countries in the region;
the bulk of migrants remain in their subregions.1 By contrast, more
than 90 percent of North African migrants leave the region, in part
because of their proximity to Europe and the Middle East. The top
destinations for African migrants are France (9 percent of total emigrants), Côte d’Ivoire (8 percent), South Africa (6 percent), Saudi
Arabia (5 percent), and the United States and the United Kingdom
(4 percent each). The percentage of a country’s population that
has emigrated is especially large in countries with small populations or histories of conflict.
Migrant remittance flows to Africa reached nearly $40 billion
(2.6 percent of GDP) in 2010 (roughly equally divided between
North Africa and Sub-Saharan Africa), almost double the amount
in 2005 and more than four times the $9.1 billion received in 1990.
Remittances are Africa’s largest source of foreign capital after
foreign direct investments (figure 1). Including flows through informal channels, the volume of remittances is likely even higher
(Ratha 2007; Ratha, Mohapatra, and Plaza 2009). Nigeria accounted for about half the officially recorded remittances to SubSaharan Africa in 2010 (World Bank 2011). Other large remittance
recipients include Ethiopia, Kenya, Senegal, South Africa, Sudan,
and Uganda. But smaller countries are not the largest recipients
of remittances as a share of GDP, which include Lesotho, which
received 27 percent of GDP in 2009. In Cape Verde, Gambia,
Guinea-Bissau, Liberia, Senegal, Sierra Leone, and Togo remittances were 7–10 percent of GDP. Egypt and Morocco, the two
largest North African recipients both in dollar-denominated flows
and as a share of GDP, account for three-quarters of flows to
the region.
$ billions
Figure 1 Remittances and other resource flows to Africa,
1990–2010
60
Foreign direct investment
40
Official aid
20
Recorded
remittances
0
Portfolio debt and private debt
–20
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010
(est.)
Source: Authors’ analysis based on data from the World Bank Global Development Finance 2010 database.
164
Africa Development Indicators 2011
Remittances tend to be more stable than other sources of
foreign exchange, are often countercyclical (helping sustain consumption and investment during downturns), and improve sovereign creditworthiness and debt sustainability by increasing the
level and stability of foreign exchange receipts (Chami, Hakura,
and Montiel 2009; IMF 2010; Avendano, Gaillard, and Nieto-Parra
2009; World Bank 2006). At the micro level, both country and
cross-country analyses have shown that remittances reduce poverty (Adams and Page 2003, 2005; Gupta, Pattillo, and Wagh 2009;
Anyanwu and Erhijakpor 2010). Studies of Burkina Faso (Wouterse
2010), Ghana (Adams 2006; Quartey and Blankson 2004; Adams,
Cuecuecha, and Page 2008), Lesotho (Gustafsson and Makonnen
1993), Morocco (Bourchachen 2000; Sorensen 2004), and Nigeria (Odozia, Awoyemia, and Omonona 2010) conclude that remittances are associated with a reduced share of people in poverty,
and in some cased reduced depth and severity of poverty as well.
Remittances also spur spending on health, education, housing,
and investments.2
The Africa Migration Project household surveys show that buying land, building a home, and starting a business were among the
highest uses of remittances—15 percent in Senegal, 20 percent in
Uganda, 36 percent in Burkina Faso, 55 percent in Kenya, and 57
percent in Nigeria (Plaza, Navarrete, and Ratha 2011). Education
was the second highest use of remittances from outside Africa into
Nigeria and Uganda, the third highest into Burkina Faso, and the
fourth highest into Kenya. In addition, remittances insure against
adverse shocks. For example, Ethiopian households that receive
international remittances were less likely than other households to
sell their productive assets, such as livestock, to cope with food
shortages (Mohapatra, Joseph, and Ratha 2009). And remittances
enable poorer households in KwaZulu-Natal province, South Africa, to access better medical care (Nagarajan 2009).
However, the cost of sending remittances continues to remain
high for Africa, averaging $23 for a $200 transaction, compared
with less than $16 for most developing regions. The cost of crossborder remittances within Africa, if permitted at all, tends to be
even higher. These high costs reflect the limited reach and expense of formal financial services (relative to average African incomes), the exchange controls on outward transfers in Africa, and
the dominance of a few large money transfer companies, which
often work exclusively with commercial banks, post offices, and
other providers (IFAD 2009; Irving, Mohapatra, and Ratha 2010).
Governments in Africa and in migrant-destination countries outside Africa should discourage such exclusive agreements. Post
offices, credit cooperatives, rural banks, and microfinance institutions have large networks (particularly among the poor), providing
a unique opportunity to expand formal remittance markets among
the poor and in rural areas.3
Despite these challenges, the rapid adoption of mobile money
transfer services is demonstrating enormous potential to broaden
the reach of formal remittance markets and expand access to formal financial services. Money transfer services through mobile
phone networks have increased significantly in Africa, for example
Migration and remittances in Africa (continued)
through M-pesa in Kenya (by end 2010, M-Pesa had more than 12
million customers), Zain/Airtel in more than 15 African countries,
Orange Money in West Africa, MTN and Ecobank in Benin, Splash
in Sierra Leone, and Wizzit in South Africa. Some mobile money
transfer service providers offer basic deposit and savings accounts in partnership with African banks, such as the “M-Kesho”
low-cost savings account offered by Safaricom, in partnership
with Equity Bank. These services are used mostly for domestic
money transfers, while their use for cross-border remittances remains limited (other than a few pilots) because of concerns over
money laundering, insufficient maturity of branchless banking infrastructure on the receiving end, and lack of customer awareness
and trust in new services (Bold 2010).
Large remittance inflows can present a macroeconomic challenge, however, by causing the exchange rate to appreciate, potentially reducing the production of tradable goods. Policymakers
in countries that receive very large remittance flows should be
alert to their impacts on the exchange rate. In addition to maintaining a flexible exchange rate and considering remittance inflows when crafting targets for reserves policies and money supply
growth, African policymakers can implement microeconomic interventions to ease labor market rigidities and reforms to improve
competitiveness.
African governments can potentially improve their access to
international capital markets by issuing bonds that are securitized
by future remittance inflows (Ketkar and Ratha 2009) and by floating bonds aimed at the African diaspora (Okonjo-Iweala and Ratha
2011). Some measures to expedite these instruments include facilitating flows through formal remittance channels, obtaining sovereign ratings, and implementing a securitization law. Multilateral
and bilateral donors can play a role in such transactions. Any increase in foreign currency debt, however, should be accompanied
by prudential risk management.
Notes
1. In West Africa, for example, more than 70 percent of intraAfrican emigration is within the subregion (World Bank 2011a).
2. See Adams, Cuecuecha, and Page (2008a) for evidence from
Ghana and Elbadawi and Roushdy (2009) for Egypt.
3. A recent survey by the Universal Postal Union found that 81
percent of post offices in Sub-Saharan Africa are outside the
three largest cities, where more than 80 percent of Africans
live; by contrast, mainstream commercial banks in Africa are
concentrated in the largest cities (Clotteau and Anson 2011).
References
Adams, Richard H. 2006. “Remittances and Poverty in Ghana.”
Policy Research Working Paper 3838, World Bank, Washington, DC.
Adams, Richard H., Alfredo Cuecuecha, and John Page. 2008.
“The Impact of Remittances on Poverty and Inequality in
Ghana.” Policy Research Working Paper 4732, World Bank,
Washington, DC.
Adams, Richard H., and John Page. 2003. “International Migration,
Remittances and Poverty in Developing Countries.” Policy Research Working Paper 3179, World Bank, Washington, DC.
———. 2005. “Do International Migration and Remittances Reduce
Poverty in Developing Countries?” World Development 33
(10): 1645–69.
Anyanwu, John C., and Andrew E. O. Erhijakpor. 2010. “Do International Remittances Affect Poverty in Africa?” African Development Review 22 (1): 51–91
Avendaño, Rolando, Norbert Gaillard, and Sebastián Nieto Parra.
2009. “Are Workers’ Remittances Relevant for Credit Rating
Agencies?” OECD Development Centre Working Paper 282, Organisation for Economic Cooperation and Development, Paris.
Bold, Chris. 2010. “Borderless, Branchless Banking.” Consultative Group to Assist the Poor. http://technology.cgap.
org/2010/12/14/borderless-branchless-banking/
Bourchachen, J. 2000. “Apports des transferts des résidents à
l’etranger à la réduction de la pauvreté : Cas du Maroc.” www.
yabiladi.com/clocs/Transfert_sociaux.rme.pdf.
Chami, Ralph, Dalia Hakura, and Peter Montiel. 2009. “Remittances: An Automatic Stabilizer?” IMF Working Paper 09/91,
International Monetary Fund, Washington, DC.
Clemens, Michael. 2009 “Skill Flow: A Fundamental Reconsideration of Skilled-Worker Mobility and Development”. Working
Paper 180, Center of Global Development, Washington, DC.
Elbadawi, Asmaa, and Rania Roushdy. 2009. “Impact of International Migration and Remittances on Child Schooling and
Child Work: The Case of Egypt.” Paper Prepared for the World
Bank’s MENA International Migration Program Funded by the
European Commission, World Bank, Washington, DC.
Gupta, Sanjeev, Catherine A. Pattillo, and Smita Wagh. 2009. “Impact of Remittances on Poverty and Financial Development
in Sub-Saharan Africa.” World Development 37 (1): 104–15.
Gustafsson, Bjorn, and Negatu Makonnen. 1993. “Poverty and Remittances in Lesotho.” Journal of African Economies 2 (1): 49–73.
IFAD (International Fund for Agriculture and Development). 2009.
Sending Money Home to Africa. Rome: International Fund for
Agricultural Development.
IMF (International Monetary Fund). 2010. “Staff Guidance Note
on the Application of the Joint Bank-Fund Debt Sustainability
Framework for Low-Income Countries.” Prepared by the staffs
of the IMF and the World Bank, January 22.
Irving, Jacqueline, Sanket Mohapatra, and Dilip Ratha. 2010. “Migrant Remittance Flows: Findings from a Global Survey of Central Banks.” Working Paper 194, World Bank, Washington, DC.
Ketkar, Suhas, and Dilip Ratha, eds. 2009. Innovative Financing for
Development. Washington, DC: World Bank.
Lachaud. Jean-Pierre. 1999. “Envoi de fonds, inegalite et pauvrete
au Burkina Faso.” Documents de travail 40, Groupe d’Economie
du Développement de l’Université Montesquieu Bordeaux IV.
Lucas, Robert E.B., and Oded Stark. 1985. “Motivations to Remit:
Evidence from Botswana.” Journal of Political Economy 93
(5): 901–18.
(continued)
Technical notes
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Mohapatra, Sanket, George Joseph, and Dilip Ratha. 2009. “Remittances and Natural Disasters: Ex-Post Response and Contribution to Ex-Ante Preparedness.” Policy Research Working
Paper 4972, World Bank, Washington, DC.
Nagarajan, Subha. 2009. “Migration, Remittances, and Household Health: Evidence from South Africa.” Ph.D. dissertation,
George Washington University, Washington, DC.
Odozia, John C., Timothy T. Awoyemia, and Bolarin T. Omonona.
2010. “Household Poverty and Inequality: The Implication of
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Okonjo-Iweala, Ngozi, and Dilip Ratha, 2011. “Homeward Bond.”
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Quartey, Peter. 2006. “The Impact of Migrant Remittances on Household Welfare in Ghana.” Research Paper 158, AERC, Nairobi.
Quartey, Peter, and Theresa Blankson. 2004. Do Migrant Remittances Minimize the Impact of Macro-volatility on the Poor in
Ghana. Report prepared for the Global Development Network,
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Plaza, Sonia, Mario Navarrete, and Dilip Ratha. 2011. “Migration
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based on the modeling of HIV surveillance
data using standard and appropriate tools.
AIDS orphans are the estimated number of
children who have lost their mother or both
parents to AIDS before age 17 since the epidemic began in 1990. Some of the orphaned
children included in this cumulative total are
no longer alive; others are no longer under
age 17.
HIV-positive pregnant women receiving
antiretrovirals to reduce the risk of motherto-child transmission are the number of
pregnant women infected with HIV who
received antiretrovirals during the last 12
months to reduce the risk of mother-to-child
transmission.
Share of HIV-positive pregnant women receiving antiretrovirals, World Health Organization/
Joint United Nations Programme on HIV/AIDS
(WHO/UNAIDS) methodology, is the percentage of pregnant women infected with HIV
who received antiretrovirals to reduce the
risk of mother-to-child transmission divided
by the total number of pregnant women infected with HIV in the last 12 months. The
166
Africa Development Indicators 2011
WHO/UNAIDS methodology may differ
from country methodologies.
Official development assistance (ODA) disbursements for social mitigation of HIV/AIDS
are spending on special programs to address
the consequences of HIV/AIDS, such as social, legal, and economic assistance to people
living with HIV/AIDS (including food security and employment); spending on support
to vulnerable groups and children orphaned
as a result of HIV/AIDS; and spending on human rights advocacy for people affected by
HIV/AIDS.
Official development assistance (ODA) disbursements for sexually transmitted disease
(STD) control, including HIV/AIDS, are spending on all activities related to STDs and
HIV/AIDS control, such as information, education, communication, testing, prevention,
and treatment.
Source: Data on number of people living with HIV/AIDS, HIV prevalence rate,
deaths due to HIV/AIDS, AIDS orphans,
and HIVpositive pregnant women receiving
antiretrovirals are from UNAIDS and WHO
Report on the Global AIDS Epidemic. A more
detailed explanation of methods and assumptions can be found on the UNAIDS reference
group on estimates, modeling, and projections
website (www.unaids.org/en/KnowledgeCentre/HIVData/Epidemiology/) and in a series
of papers published in Sexually Transmitted
Infections, “Improved Methods and Tools
for HIV/AIDS Estimates and Projections,”
2008, 84 (Suppl I); 2006, 82 (Suppl III); and
2004, 80 (Suppl I). Data on official development assistance disbursements are from the
Development Assistance Committee of the
Organisation for Economic Co-operation and
Development Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International
Development Statistics database (www.oecd.
org/dac/stats/idsonline).
11. Malaria
Table 11.1. Malaria
Population is total population based on the de
facto definition of population, which counts
all residents regardless of legal status or
citizenship—except for refugees not permanently settled in the country of asylum, who
are generally considered part of the population of their country of origin. The values
shown are midyear estimates.
Clinical malaria cases reported are the sum
of cases confirmed by slide examination or
rapid diagnostic test and probable and unconfirmed cases (cases that were not tested
but treated as malaria). National malaria
control programs often collect data on the
number of suspected cases, those tested, and
those confirmed. Probable or unconfirmed
cases are calculated by subtracting the number tested from the number suspected. Not
all cases reported as malaria are true malaria
cases; most health facilities lack appropriate
diagnostic services. The misdiagnosis may
have led to under- or overreporting malaria
cases and missing diagnosis of other treatable diseases.
Reported malaria deaths are all deaths in
health facilities that are attributed to malaria, whether or not confirmed by microscopy
or by rapid diagnostic test.
Under-five mortality rate is the probability
that a newborn baby will die before reaching
age 5, if subject to current age-specific mortality rates. The probability is expressed as a
rate per 1,000.
Children sleeping under insecticide-treated
nets is the percentage of children under age
5 with access to an insecticide-treated net to
prevent malaria.
Children with fever receiving any antimalarial
treatment are the percentage of children under age 5 in malaria-risk areas with fever being treated with any antimalarial drugs.
Pregnant women receiving two doses of intermittent preventive treatment are the number
of pregnant women receiving two or more
doses of sulfadoxine pyrimethamine during an antenatal care visit. In some country
surveys the site of treatment (during the
antenatal care visit) is not specified. This approach has been shown to be safe, inexpensive, and effective.
Official development assistance (ODA) disbursements for malaria control are spending on
prevention and control of malaria.
Source: Data on population are from the
United Nations Population Division World
Population Prospects: The 2008 Revision,
census reports and other statistical publications from national statistical offices,
Eurostat Demographic Statistics, Secretariat
of the Pacific Community Statistics and Demography Programme, U.S. Census Bureau
International Database, and World Bank
estimates based on data from these sources
as well as household surveys conducted by
national agencies, Macro International, the
U.S. Centers for Disease Control and Prevention, and refugees statistics from the United
Nations High Commissioner for Refugees.
Data on clinical cases of malaria reported
and reported malaria deaths are from the
World Health Organization (WHO) World
Malaria Report 2009. Data on children
with fever receiving antimalarial drugs and
pregnant women receiving two doses of intermittent preventive treatment are from
Demographic Health Surveys, Multiple Indicator Cluster Surveys, and national statistical offices. Data on deaths due to malaria
are from the United Nations Statistics Division and based on WHO estimates. Data
on under-five mortality are harmonized estimates of the WHO, United Nations Children’s Fund, and the World Bank, based
Technical notes
167
mainly on household surveys, censuses, and
vital registration, supplemented by World
Bank estimates based on household surveys
and vital registration. Data on insecticidetreated bednet use are from Demographic
and Health Surveys and Multiple Indicator
Cluster Surveys. Data on official development assistance disbursements are from the
Development Assistance Committee of the
Organisation for Economic Co-operation
and Development Geographical Distribution
of Financial Flows to Developing Countries,
Development Co-operation Report, and International Development Statistics database
(www.oecd.org/dac/stats/idsonline).
12. Capable states and partnership
Table 12.1. Aid and debt relief
Official development assistance is flows to developing countries and multilateral institutions provided by official agencies, including
state and local governments, or by their executive agencies, that are administered with
the promotion of the economic development
and welfare of developing countries as their
main objective and that are concessional in
character and convey a grant element of at
least 25 percent.
Net official development assistance (ODA)
from all donors is net ODA from the Organisation for Economic Co-operation and Development’s (OECD) Development Assistance
Committee (DAC), non-DAC bilateral donors
(Organization of Petroleum Exporting Countries [OPEC], the former Council for Mutual
Economic Assistance [CMEA] countries, and
China), and multilateral donors. 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.
Net official development assistance (ODA)
from DAC donors is net ODA from OECD’s
DAC donors, which are Australia, Austria,
Belgium, Canada, Denmark, Finland, France,
Germany, Greece, Ireland, Italy, Japan, Luxembourg, the Netherlands, New Zealand,
Norway, Portugal, Spain, Sweden, Switzerland, the United Kingdom, and the United
States.
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Africa Development Indicators 2011
Net official development assistance (ODA)
from non-DAC donors is net ODA from
OECD’s non-DAC donors, which include the
Czech Republic, Hungary, Iceland, Israel, the
Republic of Korea, Kuwait, Poland, Saudi
Arabia, the Slovak Republic, Taiwan (China),
Thailand, Turkey, the United Arab Emirates,
and other donors.
Net official development assistance (ODA)
from multilateral donors is net ODA 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 OPECfinanced multilateral agencies, and UN programs and agencies. Aid flows from the International Monetary Fund (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 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.
Net private official development assistance
(ODA) is private ODA transactions broken,
which comprise direct investment, portfolio
investment, and export credits (net). Private
transactions are undertaken by firms and individuals resident in the reporting country.
Portfolio investment corresponds to bonds
and equities. Inflows into emerging countries’ stocks markets, are, however, heavily
understated.
Accordingly, the coverage of portfolio investment differs in these regards from the
coverage of bank claims, which include export credit lending by banks. The bank claims
data represent the net change in bank claims
after adjusting for exchange rate changes and
are therefore a proxy for net flow data but are
not themselves a net flow figure. They differ
in two further regards from other OECD
data. First, they relate to loans by banks resident in countries that report quarterly to the
Bank for International Settlements. Second,
no adjustment has been made to exclude
short-term claims.
Net official development assistance (ODA) as
a share of gross domestic product (GDP) is calculated by dividing the nominal total net ODA
from all donors by nominal GDP. For a given
level of aid flows, devaluation of a recipient’s currency may inflate the ratios shown
in the table. Thus, trends for a given country
and comparisons across countries that have
implemented different exchange rate policies
should be interpreted carefully.
Net official development assistance (ODA)
per capita is calculated by dividing the nominal total net ODA (net disbursements of
loans and grants from all official sources on
concessional financial terms) by midyear
population. These ratios offer some indication of the importance of aid flows in sustaining per capita income and consumption
levels, although exchange rate fluctuations,
the actual rise of aid flows, and other factors
vary across countries and over time.
Net official development assistance (ODA) as
a share of gross capital formation is calculated
by dividing the nominal total net ODA by
gross capital formation. These data highlight
the relative importance of the indicated aid
flows in maintaining and increasing investment in these economies. The same caveats
mentioned above apply to their interpretation. Furthermore, aid flows do not exclusively finance investment (for example, food aid
finances consumption), and the share of aid
going to investment varies across countries.
Net official development assistance (ODA) as
a share of imports of goods and services is calculated by dividing nominal total net ODA by
imports of goods and services.
Net official development assistance (ODA) as
a share of central government expenditure is calculated by dividing nominal total net ODA by
central government expenditure.
Food aid shipments are transfers of food
commodities (food aid received) from donor
to recipient countries on a total-grant basis
or on highly concessional terms. Processed
and blended cereals are converted into their
grain equivalent by applying the conversion
factors included in the Rule of Procedures
under the 1999 Food Aid Convention to facilitate comparisons between deliveries of
different commodities. Deliveries of food aid
refer to quantities of commodities that actually reached the recipient country during a
given period. For cereals the period refers to
July–June, beginning in the year shown.
Heavily Indebted Poor Countries (HIPC) Debt
Initiative decision point is the date at which
an HIPC with an established track record of
good performance under adjustment programs supported by the International Monetary Fund and the World Bank commits to
undertake additional reforms and to develop
and implement a poverty reduction strategy.
HIPC Debt Initiative completion point is the
date at which the country successfully completes the key structural reforms agreed on at
the decision point, including developing and
implementing its poverty reduction strategy.
The country then receives the bulk of debt
relief under the HIPC Initiative without further policy conditions.
Debt service relief committed is the amount
of debt service relief, calculated at the decision point, that will allow the country to
achieve debt sustainability at the completion
point.
The Multilateral Debt Relief Initiative (MDRI)
is meant to provide additional support to
HIPCs to achieve the Millennium Development Goals while ensuring that the financing
capacity of the international financial institutions is preserved. The MDRI provides a
framework that commits to achieve two objectives: deepening debt relief to HIPCs while
safeguarding the long-term financial capacity of the International Development Association (IDA) and the African Development
Fund; and encouraging the best use of additional donor resources for development by
allocating them to low-income countries on
the basis of policy performance. Debt relief
to be provided under the MDRI will be in addition to existing debt relief commitments by
IDA and other creditors under the Enhanced
HIPC Debt Initiative. The MDRI calls for 100
percent cancellation of IDA, African Development Fund, and IMF debt for countries
that reach the HIPC completion point. The
costs include principal and interest forgone
for all multilateral financial institutions participating in the initiative, except for the IMF,
whose costs reflect the stock of debt eligible
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169
for MDRI relief, which is the debt outstanding (principal only) as of end-2004 that has
not been repaid by the member and is not
covered by HIPC assistance.
Source: Data on net official development
assistance are from the Development Assistance Committee of the Organisation
for Economic Co-operation and Development Geographical Distribution of Financial
Flows to Developing Countries, Development
Co-operation Report, and International Development Statistics database (www.oecd.
org/dac/stats/idsonline). Data on food aid
shipments are based on data compiled by
from the Food and Agriculture Organization
based on information from the World Food
Programme. Data on HIPC countries are
from IDA and IMF “Heavily Indebted Poor
Countries (HIPC) Initiative and Multilateral
Debt Relief Initiative (MDRI)—Status of
Implementation.” Data on external debt
are mainly from reports to the World Bank
through its Debtor Reporting System from
member countries that have received International Bank for Reconstruction and Development loans or IDA credits, as well as
World Bank and IMF files.
Table 12.2. Status of Paris Declaration
indicators
The third round of Monitoring the Paris Declaration began in the fourth quarter of 2010
and was completed in March 2011. These
data will be updated online in the fourth
quarter of 2011.
The Paris Declaration is the outcome of
the 2005 Paris High-Level Forum on Aid
Effectiveness, where 60 partner countries,
30 donor countries, and 30 development
agencies committed to specific actions to
further country ownership, harmonization,
alignment, managing for development results, and mutual accountability for the use
of aid. Participants agreed on 12 indicators.
These indicators include good national development strategies, reliable country systems for procurement and public financial
management, the development and use of
results frameworks, and mutual assessment
of progress. Qualitative desk reviews by the
Organisation for Economic Co-operation
and Development’s Development Assistance
Committee and the World Bank and a survey
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Africa Development Indicators 2011
questionnaire for governments and donors
are used to calculate the indicators.
PDI-1 Operational national development
strategies are the extent to which a country
has an operational development strategy to
guide its aid coordination effort and overall development. The score is based on the
World Bank 2005 Comprehensive Development
Framework Progress Report. An operational
strategy calls for a coherent long-term strategy derived from it; specific targets serving a
holistic, balanced, and well sequenced development strategy; and capacity and resources
for its implementation.
PDI-2a Reliable public financial management
is the World Bank annual Country Policy and
Institutional Assessment rating for the quality of public financial management. Measured
on a scale of 1 (worst) to 5 (best), its focus
is on how much existing systems adhere to
broadly accepted good practices and whether
a reform program is in place to promote improved practices.
PDI-2b Reliable country procurement systems
measure developing countries’ procurement
systems. Donors use national procurement
procedures when the funds they provide
for the implementation of projects and programs are managed according to the national
procurement procedures as they were established in the general legislation and implemented by government. The use of national
procurement procedures means that donors
do not make additional or special requirements for governments on the procurement
of works, goods, and services. (Where weaknesses in national procurement systems
have been identified, donors may work with
partner countries to improve the efficiency,
economy, and transparency of their implementation.) The objective of this indicator is
to measure and encourage improvements in
developing countries’ procurement systems.
PDI-3 Government budget estimates comprehensive and realistic are the percentage
of aid that is accurately recorded in the national budget, thereby allowing scrutiny by
parliaments.
PDI-4 Technical assistance aligned and coordinated with country programs is the percentage
of technical cooperation that is free standing and embedded and that respects ownership (partner countries exercise effective
leadership over their capacity development
programs), alignment (technical cooperation
in support of capacity development aligns
with countries’ development objectives and
strategies), and harmonization (when more
than one donor is involved in supporting
partner-led capacity development, donors coordinate their activities and contributions).
PDI-5a and 5b Aid for government sectors
uses country public financial management and
country procurement systems is the percentage
of donors that use country, rather than donor, systems for managing aid disbursement.
PDI-6 Project implementation units parallel
to country structures is the number of parallel project implementation units, which
refers to units created outside existing
country institutional structures. The survey guidance distinguishes between project
implementation units and executing agencies and describes three typical features of
parallel project implementation units: they
are accountable to external funding agencies rather than to country implementing
agencies (ministries, departments, agencies,
and the like), most of the professional staff
is appointed by the donor, and the personnel salaries often exceed those of civil service personnel. Interpretation of the Paris
Declaration survey question on this subject
was controversial in a number of countries.
It is unclear whether within countries all donors applied the same criteria with the same
degree of rigor or that across countries the
same standards were used. In several cases
the descriptive part of the survey results
indicates that some donors applied a legalistic criterion of accountability to the formal
executing agency, whereas the national coordinator and other donors would have preferred greater recognition of the substantive
reality of accountability to the donor. Some
respondents may have confused the definitional question (Is the unit “parallel”?) with
the aid management question (Is the parallelism justified in terms of the developmental benefits and costs?).
PDI-7 Aid disbursements on schedule and
recorded by government are the percentage of
funds that are disbursed within the year they
are scheduled and accurately recorded by
partner authorities.
PDI-8 Bilateral aid that is untied is the percentage of aid that is untied. Tied aid is aid
provided on the condition that the recipient
uses it to purchase goods and services from
suppliers based in the donor country.
PDI-9 Aid provided in the framework of program-based approaches is the percentage of
development cooperation that is based on
the principles of coordinated support for a
locally owned program of development, such
as a national development strategy, a sector
program, a thematic program, or a program
of a specific organization. Program-based approaches share the following features: leadership by the host country or organization; a
single comprehensive program and budget
framework; a formalized process for donor
coordination and harmonization of donor
procedures for reporting, budgeting, financial
management, and procurement; and efforts
to increase the use of local systems for program design and implementation, financial
management, monitoring, and evaluation.
PDI-10a Donor missions coordinated are the
percentage of missions undertaken jointly
by two or more donors and missions undertaken by one donor on behalf of another (delegated cooperation).
PDI-10b Country analysis coordinated is the
percentage of country analytic work that is
undertaken by one or more donors jointly or
undertaken by one donor on behalf of another donor (including work undertaken by one
and used by another when it is cofinanced
and formally acknowledged in official documentation and undertaken with substantive
involvement from government).
PDI-11 Existence of a monitorable performance assessment framework measures the
extent to which the country has realized its
commitment to establishing performance
frameworks. The indicator relies on the
scorings of the 2005 Comprehensive Development Framework Progress Report and
considers three criteria: the quality of development information, stakeholder access to
development information, and coordinated
country-level monitoring and evaluation.
The assessments therefore reflect both the
extent to which sound data on development
outputs, outcomes, and impacts are collected
and various aspects of the way information is
used, disseminated among stakeholders, and
fed back into policy.
PDI-12 Existence of a mutual accountability
review indicates whether there is a mechanism for mutual review of progress on aid
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171
effectiveness commitments. This is an important innovation of the Paris Declaration
because it develops the idea that aid is more
effective when both donors and partner
governments are accountable to their constituents for the use of resources to achieve
development results and when they are accountable to each other. The specific focus
is mutual accountability for the implementation of the partnership commitments included in the Paris Declaration and any local
agreements on enhancing aid effectiveness.
Source: Organisation for Economic Cooperation and Development 2008 Survey on
Monitoring the Paris Declaration: Making Aid
More Effective by 2010.
Table 12.3. Capable states
Firms that believe the court system is fair, impartial, and uncorrupt are the percentage of firms
that believe the court system is fair, impartial, and uncorrupt.
Corruption is the percentage of firms identifying corruption as a major constraint to
current operation.
Crime, theft, and disorder are the percentage
of firms identifying crime, theft, and disorder
as a major constraint to current operation.
Number of procedures to enforce a contract is
the number of independent actions, mandated by law or courts, that demand interaction
between the parties of a contract or between
them and the judge or court officer.
Time required to enforce a contract is the
number of calendar days from the filing of
the lawsuit in court until the final determination and, in appropriate cases, payment.
Cost to enforce a contract is court and attorney fees, where the use of attorneys is mandatory or common, or the cost of an administrative debt recovery procedure, expressed as
a percentage of the debt value.
Protecting investors disclosure index measures the degree to which investors are protected through disclosure of ownership and
financial information. Higher values indicate
more disclosure.
Director liability index measures a plaintiff’s ability to hold directors of firms liable
for damages to the company. Higher values
indicate greater liability.
Shareholder suits index measures shareholders’ ability to sue officers and directors
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Africa Development Indicators 2011
for misconduct. Higher values indicate
greater power for shareholders to challenge
transactions.
Investor protection index measures the degree to which investors are protected through
disclosure of ownership and financial information regulations. Higher values indicate
better protection.
Number of tax payments is the number of
taxes paid by businesses, including electronic
filing. The tax is counted as paid once a year
even if payments are more frequent.
Time required to prepare, file, and pay taxes
is the number of hours it takes to prepare,
file, and pay (or withhold) three major types
of taxes: the corporate income tax, the
value added or sales tax, and labor taxes,
including payroll taxes and social security
contributions.
Total tax rate is the total amount of taxes
payable by the business (except for labor
taxes) after accounting for deductions and
exemptions as a percentage of gross profit.
For further details on the method used for
assessing the total tax payable, see the World
Bank Doing Business 2006.
Extractive Industries Transparency Initiative (EITI) status refers to a country’s implementation status for the EITI, a multistakeholder approach to increasing governance
and transparency in extractive industries. It
includes civil society, the private sector, and
government and requires a work plan with a
timeline and budget to ensure sustainability,
independent audit of payments and disclosure of revenues, publication of results in a
publicly accessible manner, and an approach
that covers all companies and government
agencies. The EITI supports improved governance in resource-rich countries through the
verification and full publication of company
payments and government revenues from
oil, gas, and mining. Intent to implement indicates that a country intends to implement
the EITI but has not yet met the four initial
requirements to join: an unequivocal public statement of its intention to implement
the EITI; a commitment to work with civil
society and companies on EITI implementation; a senior official appointed to lead EITI
implementation; and a widely distributed,
fully costed work plan with measurable targets, a timetable for implementation, and an
assessment of government, private sector,
and civil society capacity constraints. Candidate indicates that a country has met the
four initial requirements to join the EITI and
has begun a range of activities to strengthen
revenue transparency, as documented in the
country’s work plan. Once a country has become an EITI candidate, it has two years to
be validated as compliant. Compliant indicates that a country has successfully undergone validation, an independent assessment
of a country’s progress toward the EITI goals
by the EITI International Board. Validation is
based on the country’s work plan, the EITI
validation grid and indicator assessment
tools, and company forms that detail private
companies’ extractive industry activities;
the board provides guidance for countries’
future activity related to EITI compliance.
Countries must undergo validation every five
years or at the request of the EITI International Board.
Source: Data on investment climate constraints to firms are World Bank Enterprise
Surveys (http://rru.worldbank.org/EnterpriseSurveys). Data on enforcing contracts,
protecting investors, and regulation and tax
administration are from the World Bank Doing Business project (http://rru.worldbank.
org/DoingBusiness/). Data on corruption
perceptions index are from Transparency International (www.transparency.org/policy_research/surveys_indices/cpi). Data on the EITI
are from the EITI website (www.eitransparency.org).
Table 12.4. Governance and
anticorruption indicators
Voice and accountability measure the extent
to which a country’s citizens are able to participate in selecting their government and to
enjoy freedom of expression, freedom of association, and a free media.
Political stability and absence of violence
measure the perceptions of the likelihood
that the government will be destabilized
or overthrown by unconstitutional or violent means, including domestic violence or
terrorism.
Government effectiveness measures the
quality of public services, the quality and
degree of independence from political pressures of the civil service, the quality of policy
formulation and implementation, and the
credibility of the government’s commitment
to such policies.
Regulatory quality measures the ability of
the government to formulate and implement
sound policies and regulations that permit
and promote private sector development.
Rule of law measures the extent to which
agents have confidence in and abide by the
rules of society, in particular the quality of
contract enforcement, the police, and the
courts, as well as the likelihood of crime and
violence.
Control of corruption measures the extent
to which public power is exercised for private
gain, including petty and grand forms of corruption, as well as “capture” of the state by
elites and private interests.
Expected to pay informal payment to public
officials to get things done is the percentage of
firms that expected to make informal payments or give gifts to public officials to “get
things done” with regard to customs, taxes,
licenses, regulations, services, and the like.
Expected to give gifts to obtain an operating
license is the percentage of firms that expected to give gifts or an informal payment to get
an operating license.
Expected to give gifts in meetings with tax
officials is the percentage of firms that answered yes to the question “Was a gift or informal payment expected or requested during a meeting with tax officials?”
Expected to give gifts to secure a government
contract is the percentage of firms that expected to make informal payments or give
gifts to public officials to secure a government contract.
Share of firms identifying control of corruption as a major constraint measures the extent
to which public power is exercised for private
gain, including petty and grand forms of corruption, as well as “capture” of the state by
elites and private interests.
Mean corruption perceptions index score is
the country’s score in Transparency International’s annual corruption perceptions
index, which ranks more than 150 countries
in terms of perceived levels of corruption, as
determined by expert assessments and opinion surveys.
Open budget index overall score is the country’s score on a subset of 91 questions from
the Open Budget Survey. The questions focus on the public availability of eight key
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173
budget documents (with a particular emphasis on the executive’s budget proposal)
and the information they contain. The open
budget index is calculated based on detailed
questionnaires completed by local experts in
59 participating countries from every continent. In 2008, based on inputs received from
researchers and extensive in-house reviews,
the International Budget Partnership made
three changes in its methodology. The first
change concerns the timing of the release of
the eight key budget documents assessed by
the survey. The second is the inclusion of the
enacted budget in calculating country scores
for the index. The third is revisions to the answers of a few questions used to assess Brazil
and Nigeria.
Source: Data on governance indicators are
from the World Bank Institute Worldwide
Governance Indicators database, which relies
on 33 sources, including surveys of enterprises and citizens and expert polls, gathered
from 30 organizations around the world.
Data on corruption perceptions index scores
are from Transparency International (www.
transparency.org). Data on the open budget
index are from www.openbudgetindex.org.
Table 12.5. Country Policy and
Institutional Assessment ratings
The Country Policy and Institutional Assessment (CPIA) assesses the quality of a country’s present policy and institutional framework. “Quality” means how conducive that
framework is to fostering sustainable, poverty-reducing growth and the effective use
of development assistance. The CPIA is conducted annually for all International Bank
for Reconstruction and Development and
International Development Association borrowers and has evolved into a set of criteria
grouped into four clusters with 16 criteria
that reflect a balance between ensuring that
all key factors that foster pro-poor growth
and poverty alleviation are captured, without
overly burdening the evaluation process.
• Economic management
• Macroeconomic management assesses the quality of the monetary, exchange rate, and aggregate demand
policy framework.
• Fiscal policy assesses the short- and
medium-term sustainability of
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Africa Development Indicators 2011
fiscal policy (taking into account
monetary and exchange rate policy
and the sustainability of the public
debt) and its impact on growth.
• Debt policy assesses whether the
debt management strategy is conducive to minimize budgetary
risks and ensure long-term debt
sustainability.
• Structural policies
• Trade assesses how the policy
framework fosters trade in goods.
It covers two areas: trade regime
restrictiveness—which focuses on
the height of tariff barriers, the
extent to which nontariff barriers are used, the transparency and
predictability of the trade regime,
and customs and trade facilitation
—which includes the extent to
which the customs service is free of
corruption, relies on risk management, processes duty collections
and refunds promptly, and operates transparently.
• Financial sector assesses the structure of the financial sector and the
policies and regulations that affect it. It covers three dimensions:
financial stability; the sector’s efficiency, depth, and resource mobilization strength; and access to
financial services.
• Business regulatory environment assesses the extent to which the legal,
regulatory, and policy environment
helps or hinders private business
in investing, creating jobs, and becoming more productive. The emphasis is on direct regulations of
business activity and regulation of
goods and factor markets. It measures three subcomponents: regulations affecting entry, exit, and
competition; regulations of ongoing business operations; and regulations of factor markets (labor and
land).
• Policies for social inclusion and equity
• Gender equality assesses the extent
to which the country has enacted
and put in place institutions and
programs to enforce laws and policies that promote equal access for
Conflict-affected and fragile states in Africa
While the definition of armed conflict (associated with the number of battle-related deaths) is fairly well accepted, fragility remains somewhat ill-defined. Indeed, some people prefer the
term “fragile situations” to fragile states. Using the harmonized
Country Policy and Institutional Assessment (CPIA) score (less
than or equal to 3.2 as a threshold), the World Bank has defined
fragile states as low-income countries with a low institutional
Map 1
Bernard Harborne, Noro Aina Andriamihaja, and Viola Erdmannsdoerfer
level. However, World Development Report 2011 broadened the
definition to include conflict indicators, such as annual homicide
rates of more than 10 per 100,000 people, annual battle deaths
of more than 1,000 people, and the presence of a UN peacekeeping mission. Using the World Development Report definition, 20 of Sub-Saharan Africa’s 47 countries are either fragile
or conflict-affected.
The cohort of fragile states was unchanged over 2005–09
Country Policy and Institutional Assessment (International Development Association countries only) scores
2005
Lower than 3.2
3.2–3.5
Higher than 3.5
No data
The cohort of fragile states (both core and marginal) remained
fairly constant over 2005–09 (map 1), with only one country leaving
the core set of fragile states (Nigeria) and two leaving the marginal
fragile states (Mozambique and Rwanda). While many countries
have stagnant CPIA scores, Angola, Burundi, Central African Republic, Liberia, and Sierra Leone have slightly improved, but they
are still on the fragility threshold. Five countries’ scores have fallen
(Chad, Côte d’Ivoire, Eritrea, Somalia, and Zimbabwe), and the number of violently disputed elections (Côte d’Ivoire, Kenya) and military
coups d’état (Mauritania, Guinea, Madagascar, Niger) has risen.
Since the 1990s, Africa has had the most countries in armed
conflict, with a peak in 1998–99 when almost half of the countries
in fragile or conflict situations in Sub-Saharan Africa were involved
in armed conflict. Global trends suggest a gradual decline in the
numbers of both armed conflicts and battle-related deaths, both in
and outside Africa; the annual average number of conflict-affected
states in Sub-Saharan Africa fell from 16 in the 1990s to 6 in 2007
(Human Security Report Project 2008). This positive trend has increased the responsibility of post-conflict recovery interventions
and international peacekeeping—some 78,400 UN and AU peacekeeping troops work in Sub-Saharan Africa (map 2).
2009
Lower than 3.2
3.2–3.5
Higher than 3.5
No data
Despite these trends, armed conflict and violence remain critical challenges to development. The data remain unreliable, but
some figures suggest the challenges are massive. Since 1998 the
conflict and humanitarian crisis in the Democratic Republic of the
Congo has caused the deaths of 5.4 million people (International
Rescue Committee 2008), mostly from disease and malnutrition,
and the rape of some 1.8 million women (Peterman, Palermo, and
Bredenkamp 2011). Some 2 million people were killed during the
civil war between northern and southern Sudan and between
180,000–400,000 persons died as a result of armed conflict in
Darfur (Degomme and Guha-Sapir 2010). And in 2010 there were
around 10.3 million internally displaced persons and 2.5 million
refugees across Sub-Saharan Africa. Violence is not simply related to armed conflict; in 2006 the Southern Africa region had the
highest intentional homicide rate in the world of 37 per 100,000
people (United Nations Office on Drugs and Crime 2010).
Fragile and conflict-affected states (both core and marginal)
are finding it hard to achieve the Millennium Development Goals
and are the most vulnerable to external shocks, such as oil
and food price increases. Most of the core fragile countries
have very high (more than 35 percent) and high (24–35 percent)
(continued)
Technical notes
175
Governance, conflict-affected and fragile states in Africa (continued)
undernourishment (FAOSTAT 2010). Despite some success—in
Ethiopia, Guinea, and Niger—most fragile countries in Africa
are far from the maternal mortality and infant mortality targets. While such countries as Cameroon are on target for access to safe water, core fragile countries such as Burundi, the
Democratic Republic of the Congo, and Sudan remain way off.
Most of those countries are also cereal net importers. Around
6.4 million people in Sudan and 2.4 million in Somalia need external assistance due to conflict and rising food prices (Barungi
and others 2011).
Map 2 Conflict, political stability, and violence in Africa
Political stability and absence of violence index, 2009
Refugees and peacekeeping operations, 2011
Former
Spanish
Sahara
Former
UN Spanish
Sahara
Mauritania
Cape Verde
–1.17
0.82
Senegal
–0.15
The Gambia
–0.49 Guinea-Bissau
0.26
Mauritania
Mali
Niger
–0.27
–0.12
Benin
Côte Ghana 0.44
d’Ivoire 0.16
–1.90
–0.40
–1.53
–0.21
Togo Equatorial
Guinea
–0.02
São Tomé and Príncipe
Sudan
–1.75
Nigeria
–1.95
Cameroon
Central African Republic
–2.03
0.12
–0.41
–3.31
Congo, Dem. Rep.
–1.30
–2.13
Great
Lakes
Rwanda –0.33
Burundi –1.42
Tanzania
0.08
Seychelles
0.71
Comoros –1.01
–0.24
Zambia
–1.44
Mozambique
0.48
Madagascar
–0.67
0.61
Mauritius
Namibia
Swaziland 0.02
UN
Lesotho 0.36
UA
Number of refugees originating in country
UN peacekeeping operation presence
UA peacekeeping operation presence
0.02
Localized conflicts
War-to-peace transitions
According to the literature, risk factors associated with conflict
and violence in Sub-Saharan Africa include low per capita income,
horizontal and vertical inequality between groups, ethnic fractionalization, political repression, electoral crisis, legacies of colonialism,
superpower rivalry, and competition for natural resources (World
Bank 2011; African Development Bank 2008). While the causality
between natural resources and conflict is not empirical, the armed
conflict in eastern Congo associated with the illicit exploitation of
minerals is but one example of the challenges confronting African
states. Most African countries are endowed with natural resources,
some of which are fragile or conflict-affected, such as Namibia
or Botswana. The connections between natural resources and
conflict highlight the presence of weak accountability, poor governance, and weak institutions. Other aggravating challenges are
high levels of unemployment and underemployment, particularly in
urban areas, as well as rising food prices, the poor performance of
security and justice institutions, and large-scale corruption.
But all is not about failure in fragile and conflict-affected states.
The last years have also produced some post-conflict successes,
such as in Mozambique, Sierra Leone, and Rwanda, which has
focused on generating rapid economic growth to deal with its history of genocide. Also, Uganda implemented an amnesty program
176
Africa Development Indicators 2011
Fragile states and
war-to-peace transitions
Zambia
Botswana
Malawi
Zimbabwe Mozambique
22,449
Madagascar
Mauritius
Swaziland
Lesotho
South Africa
Potential flashpoints
Dangerous neighborhoods
to reintegrate former rebel soldiers into society while sustaining its
objectives of increased and sustained inclusive economic growth.
Figure 1 Net official development aid to fragile states in
Sub-Saharan Africa, 1960–2005
$ millions
Fragile states
Comoros
Angola
141,021
0.91
South Africa
UN UA
–0.06
Zimbabwe
Botswana
Sudan
348,500
Chad
21,646
Niger
822
Malawi
0.51
Namibia
Kenya
–1.06
Angola
Lower than –1.5
–1.5 to 0
Higher than 0
Somalia
Uganda
0.22
0.80
–1.73
Mali
Eritrea
197,313
Darfur, Chad,
The Gambia
Burkina Faso
Guinea
Central African
Guinea-Bissau
Benin
Nigeria
Horn,
Ethiopia
Republic
10,920 Côte
1,109
15,608
Somalia
Ghana
South
62,873
Sierra Leone
d’Ivoire
Central African Republic
Sudan
Cameroon
Somalia UA
15,417
23,153
154,005
Liberia
Uganda
678,308
Togo Equatorial
71,572 UN
UN
Kenya
Guinea
Gabon
18,377
7,544
Congo, Dem. Rep.
9,620
Côte d’Ivoire,
129,109
455,852
Rwanda
São Tomé and Príncipe
Guinea,
Congo
Burundi
94,239
UN
Sierra Leone,
Great
Tanzania
20,544
Liberia
Lakes
Seychelles
Horn,
Somalia
Ethiopia
Senegal
16,305
–0.80
South
Sudan
–0.41
Gabon Congo
Cape Verde
Eritrea
–2.65
Darfur, Chad,
Central African
Republic
Burkina Faso
Guinea
Sierra Leone
Liberia
Côte d’Ivoire, –0.99
Guinea,
Sierra Leone,
Liberia
Chad
–1.17
2,500
2,000
Congo, Rep.
Côte d’Ivoire
Liberia
Mozambique
Rwanda
Sierra Leone
Somalia
Sudan
1,500
1,000
500
0
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005 2009
Governance, conflict-affected and fragile states in Africa (continued)
World Development Report 2011 highlights ways external support can support such transitions. While official aid started to peak in
the 1990s and average volumes have been increasing, aid has been
volatile. Sustained internal and external support is required to help
countries move from fragility to peace and prosperity for the long term.
References
African Development Bank. 2008. Africa Development Report
2008/2009: Conflict Resolution, Peace and Reconstruction in
Africa. Oxford, UK: Oxford University Press.
Barungi, Barbara, Kazuhiro Numasawa, Adeleke Salami, and
Adalbert Nshimyumuremyi. 2011. “The Impact of the 2010–11
Surge in Food Prices on African Countries in Fragile Situations.” Africa Economic Brief 2 (4).
Degomme, Olivier and Debarati Guha-Sapir. 2010. “Patterns of Mortality Rates in Darfur conflict.” The Lancet 375 (9711): 294–300.
men and women to human capital
development and productive and
economic resources and that give
men and women equal status and
protection under the law.
• Equity of public resource use assesses
the extent to which the pattern of
public expenditures and revenue
collection affects the poor and is
consistent with national poverty reduction priorities. The assessment
of the consistency of government
spending with the poverty reduction priorities takes into account
the extent to which individuals,
groups, or localities that are poor,
vulnerable, or have unequal access
to services and opportunities are
identified; a national development
strategy with explicit interventions
to assist those individuals, groups,
and localities has been adopted;
and the composition and incidence
of public expenditures are tracked
systematically and their results fed
back into subsequent resource allocation decisions. The assessment
of the revenue collection dimension
takes into account the incidence of
major taxes—for example, whether
they are progressive or regressive
—and their alignment with poverty reduction priorities. When
relevant, expenditure and revenue
FAOSTAT. 2010. “FAO Hunger MAP in 2010: Prevalence of Undernourishment in Developing Countries.” Food and Agriculture
Organization, Rome.
Human Security Report Project. 2008. Human Security Brief 2007.
Vancouver, Canada: Human Security Report Project.
International Rescue Committee. 2008. Mortality in the DRC: An
Ongoing Crisis. New York: International Rescue Committee.
Peterman, Amber, Tia Palermo, and Caryn Bredenkamp. 2011. “Estimates and Determinants of Sexual Violence against Women
in the Democratic Republic of Congo.” American Journal of
Public Health 101 (6): 1060.
United Nations Office on Drugs and Crime. 2010. Update Report
No. 5. New York: United Nations.
World Bank. 2011. World Development Report 2011: Conflict, Security, and Development. Washington, DC: World Bank.
collection trends at the national and
subnational levels should be considered. The expenditure component
receives two-thirds of the weight in
computing the overall rating.
• Building human resources assesses
the national policies and public
and private sector service delivery
that affect access to and quality of
health and nutrition services, including: population and reproductive health; education, early childhood development, and training
and literacy programs; and prevention and treatment of HIV/AIDS,
tuberculosis, and malaria.
• Social protection and labor assess
government policies in the area of
social protection and labor market
regulation, which reduce the risk
of becoming poor, assist those who
are poor to better manage further
risks, and ensure a minimal level
of welfare for all people. Interventions include social safety net programs, pension and old-age savings
programs, protection of basic labor
standards, regulations to reduce
segmentation and inequity in labor markets, active labor market
programs (such as public works or
job training), and community driven initiatives. In interpreting the
guidelines it is important to take
Technical notes
177
into account the size of the economy and its level of development.
• Policies and institutions for environmental sustainability assess the
extent to which environmental
policies foster the protection and
sustainable use of natural resources and the management of pollution. Assessment of environmental
sustainability requires multidimensional criteria (that is, for air, water,
waste, conservation management,
coastal zones management, and
natural resources management).
• Public sector management and institutions
• Property rights and rule-based governance assess the extent to which
private economic activity is facilitated by an effective legal system
and rule-based governance structure in which property and contract rights are reliably respected
and enforced. Three dimensions are
rated separately: legal basis for secure property and contract rights;
predictability, transparency, and
impartiality of laws and regulations affecting economic activity
and their enforcement by the legal
and judicial system; and crime and
violence as an impediment to economic activity.
• Quality of budgetary and financial
management assesses the extent to
which there is a comprehensive and
credible budget, linked to policy priorities; effective financial management systems to ensure that the
budget is implemented as intended
in a controlled and predictable way;
and timely and accurate accounting
and fiscal reporting, including timely
and audited public accounts and effective arrangements for follow-up.
• Efficiency of revenue mobilization assesses the overall pattern of revenue mobilization—not only the tax
structure as it exists on paper but
revenue from all sources as they are
actually collected.
• Quality of public administration
assesses the extent to which civilian central government staffs
178
Africa Development Indicators 2011
(including teachers, health workers, and police) are structured to
design and implement government
policy and deliver services effectively. Civilian central government
staffs include the central executive
together with all other ministries
and administrative departments,
including autonomous agencies. It
excludes the armed forces, stateowned enterprises, and subnational governments.
• Transparency, accountability, and
corruption in public sector assess
the extent to which the executive
branch can be held accountable for
its use of funds and the results of
its actions by the electorate and by
the legislature and judiciary and to
which public employees within the
executive branch are required to account for the use of resources, administrative decisions, and results
obtained. Both levels of accountability are enhanced by transparency in decisionmaking, public audit
institutions, access to relevant and
timely information, and public and
media scrutiny.
Source: World Bank Group CPIA database
(www.worldbank.org/ida).
Table 12.6. Polity indicators
Revised combined polity score is computed by
subtracting the institutionalized autocracy
score from the institutionalized democracy
score. The resulting unified polity scale ranges from +10 (strongly democratic) to –10
(strongly autocratic).
Institutionalized democracy is conceived
as three essential, interdependent elements. One is the presence of institutions
and procedures through which citizens can
express effective preferences about alternative policies and leaders. Second is the
existence of institutionalized constraints
on the exercise of power by the executive.
Third is the guarantee of civil liberties to
all citizens in their daily lives and in acts
of political participation. Other aspects of
plural democracy —such as the rule of law,
systems of checks and balances, freedom
of the press, and so on—are means to, or
The political economy of public policies and government failures
In the mid-1980s, Sub-Saharan Africa was dominated by fully autocratic regimes—31 of 40 in the database were fully autocratic,
with just 3 full-fledged democracies (Botswana, Gambia, and
Mauritius) and 6 intermediate regimes, most of which had a heavy
weight of autocracy, according to Polity IV scores1 (figure 1). By
end 2009, it had 12 fully democratic regimes (Benin, Comoros,
Ghana, Kenya, Lesotho, Mali, Senegal, Sierra Leone, South Africa
and Zambia, in addition to the already democratic Botswana and
Mauritius) and only 3 fully autocratic regimes (Eritrea, Somalia,
and Swaziland), with most countries classified as intermediate—a
remarkable shift. Most intermediate regimes now have significant
democratic elements (Burkina Faso, Côte d’Ivoire, the Democratic
Republic of the Congo, Ethiopia, Mozambique, Nigeria, Rwanda,
Uganda, Tanzania, and Zimbabwe).
Democratic
Figure 1
10
8
6
4
Intermediate
Polity scores, 1985 and 2009
2009
2
public payroll is more important for political survival and extracting rents from political office than it is for managing teachers better
and holding them accountable for quality learning outcomes. Clientelism has been traced to underlying conditions of entrenched
inequality, social polarization, and lack of information and credible
political promises.
Nevertheless, sustained political competition, democratic
conditions, and new research in Africa suggest there is substantial scope to undercut clientelism through well designed (and evaluated) interventions that better inform citizens and that enable
them to deliberate, communicate, and hold governments more
accountable for broad public interest policies. For example, in
Benin, a civil society group organized town hall meetings with
political candidates in the first round of the 2006 presidential elections, to discuss specific policy proposals informed by empirical evidence. Where the meetings were held, voter turnout was
higher and support for clientelist political platforms was lower
(Wantchekon 2009) than where they were not. Better data, better evidence, and better communication with citizens could be
the key to overcoming political constraints to good development
policies in Africa.
0
–2
1985
–4
Autocratic
Stuti Khemani
–6
–8
–10
Sub-Saharan African countries
So, why has increasing democratization in the Africa region
not resulted in more substantial improvements in public policies
for growth, poverty reduction, and human development? Although
the democratic wave has been shown to influence public policies, it has disappointed by not addressing critical accountability relations in improving public goods for human development
and a competitive business sector. For example, the transition to
competitive elections in African countries is associated with the
abolition of school fees, which in turn is associated with higher
rates of school attendance than in nondemocracies (Harding and
Stasavage 2011). Yet the quality of education services is poor, with
teachers on the public payroll often absent from their jobs (Glewwe
and Kremer 2006) and learning among children falling far short of
functional literacy (Uwezo 2010).
Political economy analysis suggests that the disappointments
are due largely to widespread clientelistic practices in electoral
competition—the provision of private benefits to select citizens in
exchange for political support (Robinson and Verdier 2002; Keefer
and Khemani 2005). Providing secure jobs to teachers on the
specific manifestations of, these general
principles. Coded data on civil liberties are
not included. This is an additive elevenpoint scale (0–10). The operational indicator of democracy is derived from codings of
Note
1. Polity IV is a database ranking countries on their levels of democracy, based on surveys of political scientists.
References
Glewwe, Paul, and Michael Kremer. 2006. “Schools, Teachers, and
Education Outcomes in Developing Countries.” Handbook on
the Economics of Education, ed. Erik Hanushek & F. Welch.
Oxford, UK: Elsevier.
Harding, Robin, and David Stasavage. 2011. “What Democracy
Does (and Doesn’t) Do for Basic Services: School Fees,
School Quality, and African Elections.” Working Paper, New
York University, New York.
Keefer, Philip, and Stuti Khemani. 2005. “Democracy, Public Expenditures, and the Poor.” World Bank Research Observer 20:
1–27.
Robinson, James A., and Thierry Verdier 2002. “The Political Economy of Clientelism.” CEPR Discussion Paper 3205, Center for
Economic Policy and Research, Washington, DC.
Uwezo. 2010. Are Our Children Learning? Annual Learning Assessment. Nairobi, Kenya. http://uwezo.net/index.php?i=68
Wantchekon, Leonard. 2009. “Can Informed Public Deliberation
Overcome Clientelism? Experimental Evidence from Benin.”
Working Paper, New York University, New York. http://politics.
as.nyu.edu/docs/IO/2807/expertinformationjuly.pdf.
the competitiveness of political participation using weights.
Institutionalized autocracy is a pejorative
term for some very diverse kinds of political systems whose common properties are
Technical notes
179
a lack of regularized political competition
and concern for political freedoms. The term
autocracy is used and defined operationally
in terms of the presence of a distinctive set
of political characteristics. In mature form
autocracies sharply restrict or suppress competitive political participation. Their chief
executives are chosen in a regularized process of selection within the political elite,
and once in office they exercise power with
few institutional constraints. Most modern
autocracies also exercise a high degree of
180
Africa Development Indicators 2011
directiveness over social and economic activity, but this is regarded here as a function
of political ideology and choice, not a defining property of autocracy. Social democracies also exercise relatively high degrees of
directiveness.
Source: Data are from the Integrated Network for Societal Conflict Research Polity IV Project, Political Regime Characteristics and Transitions, 1800–2009 (www.
systemicpeace.org/inscr/inscr.htm).
Technical notes references
Chen, Shaohua, and Martin Ravallion. 2008. “The
Developing World Is Poorer Than We Thought, But No Less
Successful in the Fight Against Poverty.” Policy Research
Working Paper 4703. World Bank, Washington, DC.
FAO (Food and Agriculture Organization of the United
Nations). 2010. Global Forest Resources Assessment
2010. Rome: Food and Agriculture Organization.
IDA (International Development Association) and IMF
(International Monetary Fund). 2010. “Heavily Indebted
Poor Countries (HIPC) Initiative and Multilateral Debt Relief
Initiative (MDRI)—Status of Implementation.” International
Development Association and International Monetary Fund,
Washington, DC.
IEA (International Energy Agency). Various years. Energy
Statistics of OECD Countries. Paris: International Energy
Agency.
ILO (International Labour Organization). Various years.
Key Indicators of the Labor Market. Geneva: International
Labour Organization.
IMF (International Monetary Fund). 2010. Global Financial
Stability. Washington, DC: International Monetary Fund.
———. Various years. Balance of Payments Statistics
Yearbook. Parts 1 and 2. Washington, DC: International
Monetary Fund.
———. Various years. Direction of Trade Statistics Quarterly.
Washington, DC: International Monetary Fund.
———. Various years. Direction of Trade Statistics Yearbook.
Washington, DC: International Monetary Fund.
IRF (International Road Federation). 2010. World Road
Statistics. Geneva.
OECD (Organisation for Economic Co-operation and
Development). 2011. African Economic Outlook 2011:
Africa and its Emerging Partners. Paris: Organisation for
Economic Co-operation and Development.
OECD (Organisation for Economic Co-operation and
Development) DAC (Development Assistance
Committee). Various years. Geographical Distribution
of Financial Flows to Developing Economies. Paris:
Organisation for Economic Co-operation and Development.
Ravallion, Martin, Shaohua Chen, and Prem Sangraula.
2008. “Dollar a Day Revisited.” Policy Research Working
Paper 4620. World Bank, Development Research Group,
Washington, DC.
Standard & Poor’s. 2000. The S&P Emerging Market Indices:
Methodology, Definitions, and Practices. New York:
Standard & Poor’s.
———. 2010. Global Stock Markets Factbook 2010. New
York: Standard & Poor’s.
WHO (World Health Organization). 2011. Global Atlas of the
Health Workforce. Geneva: World Health Organization.
———. Various years. World Malaria Report. Geneva: World
Health Organization.
UNAIDS (Joint United Nations Programme on HIV/AIDS)
and WHO (World Health Organization). Various years.
Report on the Global AIDS Epidemic. Geneva: Joint United
nations Programme on HIV/AIDS.
WHO (World Health Organization), UNICEF (United Nations
Children’s Fund), UNFPA (United Nations Population
Fund), and World Bank. 2010. Trends in Maternal
Mortality: 1990–2008: Estimates Developed by WHO,
UNICEF, UNFPA and the World Bank. Geneva: World Health
Organization.
UNCTAD (United Nations Conference on Trade and
Development). 1995. Handbook of International Trade
and Development. New York and Geneva: United Nations
Conference on Trade and Development.
World Bank. 2000. Trade Blocs. New York: Oxford University
Press.
———. 2007. Trade and Development Report 2007: Regional
Cooperation for Development. New York and Geneva:
United Nations Conference on Trade and Development.
UNESCO (United Nations Educational, Scientific, and
Cultural Organization). 1997. International Standard
Classification of Education. Paris: United Nations
Educational, Scientific, and Cultural Organization.
———. Various years. Global Development Finance: External
Debt of Developing Countries. Washington, DC: World
Bank.
WTO (World Trade Organization). n.d. Regional Trade
Agreements Gateway. [www.wto.org/English/tratop_e/
region_e/region_e.htm]. Geneva.
UNICEF (United Nations Children’s Fund). Various issues.
The State of the World’s Children. New York: Oxford
University Press.
United Nations. 2006. Standard International Trade
Classification Revision 4. New York: United Nations,
Department of Economic and Social Affairs.
United Nations Population Division. 2009a. Trends in Total
Migrant Stock: The 2008 Revision. New York: United
Nations, Department of Economic and Social Affairs.
———. 2009b. World Population Prospects: The 2008
Revision. New York: United Nations, Department of
Economic and Social Affairs.
———. Various years. World Population Prospects. New
York: United Nations, Department of Economic and Social
Affairs.
———. Various years. Energy Statistics Yearbook. New York:
United Nations.
———. Various years. World Urbanization Prospects. New
York: United Nations.
United Nations Statistics Division. n.d. “International Standard
Industrial Classification of All Economic Activities, Third
Revision.” [http://unstats.un.org/unsd/cr/registry/]. New York.
Technical notes references
181
Map of Africa
TUNISIA
MOROCCO
ALGERIA
LIBYA
FORMER
SPANISH
SAHARA
ARAB REP.
OF EGYPT
MAURITANIA
CAPE VERDE
MALI
THE GAMBIA
GUINEA-BISSAU
SENEGAL
NIGER
GUINEA
SIERRA LEONE
LIBERIA
BENIN
CÔTE
TOGO
D’IVOIRE
GHANA
ERITREA
CHAD
BURKINA
FASO
SUDAN
DJIBOUTI
NIGERIA
EQUATORIAL GUINEA
SÃO TOMÉ AND PRÍNCIPE
CAMEROON
ETHIOPIA
CENTRAL
AFRICAN REPUBLIC
SOMALIA
UGANDA
GABON
CONGO
DEM. REP.
RWANDA
OF
BURUNDI
CONGO
KENYA
TANZANIA
SEYCHELLES
Atlantic
Ocean
COMOROS
ANGOLA
ZAMBIA
ZIMBABWE
NAMIBIA
Africa Development Indicators 2011
MOZAMBIQUE
MADAGASCAR
MAURITIUS
BOTSWANA
SOUTH
AFRICA
182
MALAWI
LESOTHO
SWAZILAND
Indian
Ocean
Users Guide
Africa Development Indicators 2011–Multiple User CD-ROM
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2. Highlight the items you want.
3. Click on the Select button to move them
into the Selected box.
4. Deselect items at any time by highlighting
them and clicking on the Remove icon.
5. When selection is complete, click on Next
to move to the next screen.
Making selections
• Country: You can select countries and
group aggregates from an alphabetical
list, group hierarchies, or by Classification
(region, income group, or lending
category). Aggregate data have been
calculated only when there were adequate
country data.
• Series: You can choose from an
alphabetical list or by topic, or create
your own custom indicators derived from
indicators within the ADI database.
• Year: Select time periods from the list box.
On all screens you can click Notes to view
definition and source information for a
highlighted item.
View results
On the Report tab, data are presented in
a two-dimensional grid. Data for the third
dimension are presented on separate
screens. You can change the selection
displayed by clicking on the third dimension
list box. You can also change the scale (to
Users guide
183
millions, for example) and the number of
digits after the decimal. Click on a column
header to sort the results. Select Show Notes
to view source notes and footnotes. To scale
series individually click the Series Level
Settings icon.
Please do not use the browser Back and
Forward buttons on the View Report window.
This will cause you to lose the report. You will
not be able to retrieve data and will have to
select the variables again.
Changing the orientation. You can view the
result in six different orientations (countries
down/periods across, series down/countries
across, and so on). To change the orientation,
click on Customize and drag and drop the
dimensions to your desired orientation.
Customize also has various formatting
options for the report.
Saving. You can save the report or you can
save the data in another format. You can also
save your query selections for later use.
• Saving the report in Excel. Select the
Export Report as Excel File icon on the
toolbar. This will save the report in the
same format.
• Saving the report in PDF. Select the
Export Report as PDF File icon on the
toolbar. This will save the report in the
same format. Adobe Reader is required
to view files downloaded in PDF format. If
you do not have Adobe Reader, it can be
downloaded from www.Adobe.com.
• Saving the data or notes in another
format. Select the Export Data and Notes
as CSV File icon on the toolbar. Saving
data as a CSV file will allow you to export
all countries, series, and years on to
one file. The file will not retain the report
format.
• Saving a query. Select the Save Selections
as Query icon on the toolbar. Your query
will be saved as “XXXYYY.dp.” There
is no need to open the file. If you wish
to manually edit the query file, select
Notepad.
Click on Help for more details.
Chart
On the Chart tab, data are displayed based
on the report orientation setting. Click on
Customize to change the chart type, add a
title and to access various formatting options.
You can set different chart types for each
variable.
Adobe Flash Player 8 or higher is required
to view the new features of the charts. It is a
free and lightweight installation from www.
Adobe.com. If you do not have the application
already installed on your desktop, a message
will appear asking you to download Adobe
184
Africa Development Indicators 2011
Flash Player. Please click “OK” when the
message appears. It will take you directly to
the Adobe website.
Printing and saving. Right-click on the
chart image to print the chart. Click on the
appropriate icon to save the chart or save the
underlying data.
Map
On the Map tab, selected countries are
colored according to their data values for
the selected indicator and year. The country
name and data value will appear as the
cursor rolls over the map. The legend scale
is based on the report scale and precision
settings. To activate the zoom option for
a closer look at the map, click directly on
the desired location. Click the Reset link to
zoom out.
Adobe Flash Player 8 or higher is required
to view the new features of the maps. It is a
free and lightweight installation from www.
Adobe.com. If you do not have the application
already installed on your desktop, a message
will appear asking you to download Adobe
Flash Player. Please click “OK” when the
message appears. It will take you directly to
the Adobe website.
Changing the map intervals and colors.
The default interval range is an equal number
of countries. Use the list boxes to set an
equal interval range or to change the map
color palette. You can also choose to map all
countries or only your selected ones.
Printing and saving. Right-click on the
map image to print the map. Click on the
appropriate icon to save the map or save the
underlying data.
License agreement
You must read and agree to the terms of
this License Agreement prior to using this
CD-ROM 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
enclosed data and DataPlatform 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 title and ownership
of the program recorded on the original
CD-ROM and all subsequent copies of the
program. This license is not 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 and punishable by law.
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 used by one
person and you may not distribute copies
of the Program or accompanying written
materials to others.
If you have purchased the multiple-user
version of this product, the license is valid
for up to 15 authorized users. Should you
need to make the program available for
additional users through a network, including
an intranet, please send a request, indicating
the number of users you would like to add,
to: World Bank Publications, Marketing
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[email protected] The Bank will
invoice you for an additional fee, depending
on the number of users added to the license.
For additional information, please contact
World Bank Publications, Marketing and
Rights, 1818 H Street NW, Washington
DC 20433, fax 202 522 2422, e-mail
[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
the CD-ROM on which the program
is furnished to be free from defects in
materials and workmanship under normal
use for a period of ninety (90) days from
the delivery to you as evidenced by a
copy of your receipt. The Bank’s entire
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Defective CD-ROMs should be returned
within the warranty period, with a copy of
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EXCEPT AS PROVIDED ABOVE, THE
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EXPRESSED OR IMPLIED, INCLUDING,
BUT NOT LIMITED TO, THE IMPLIED
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THE BANK DOES NOT WARRANT THAT THE
FUNCTIONS CONTAINED IN THE PROGRAM
WILL MEET YOUR REQUIREMENTS OR THAT
THE OPERATION OF THE PROGRAM WILL
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IN NO EVENT WILL THE BANK BE LIABLE
TO YOU FOR ANY DAMAGES ARISING OUT
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THE ABOVE WARRANTY GIVES YOU
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8. GOVERNING LAW. This license shall be
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Columbia, in the United States of America,
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9. GENERAL. If you have any questions
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Marketing and Rights, 1818 H Street NW,
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2422, e-mail [email protected]
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Africa Development Indicators 2011
Africa Development Indicators 2011 is the most detailed
collection of data on Africa. It contains macroeconomic,
sectoral, and social indicators for 53 countries.
The companion CD-ROM has additional data, with
some 1,700 indicators covering 1961–2009.
Basic indicators
National and fiscal accounts
External accounts and exchange rates
Millennium Development Goals
Private sector development
Trade and regional integration
Infrastructure
Human development
Agriculture, rural development, and the environment
Labor, migration, and population
HIV/AIDS and malaria
Capable states and partnership
Paris Declaration indicators
Governance and polity
Designed as both a quick reference and a reliable dataset
for monitoring development programs and aid flows in the
region, Africa Development Indicators 2011 is an invaluable
tool for analysts and policymakers who want a better
understanding of Africa’s economic and social development.
ISBN 978-0-8213-8731-3
SKU 18731
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