Issuu on Google+

SKU18709 18709 SKU 18709

The world by region

East Asia and Pacific American Samoa Cambodia China Fiji Indonesia Kiribati Korea, Dem. Rep. Lao PDR Malaysia Marshall Islands Micronesia, Fed. Sts. Mongolia Myanmar Palau Papua New Guinea Philippines Samoa Solomon Islands Thailand Timor-Leste Tonga Tuvalu Vanuatu Vietnam

Colombia Costa Rica Cuba Dominica Dominican Republic Ecuador El Salvador Grenada Guatemala Guyana Haiti Honduras Jamaica Mexico Nicaragua Panama Paraguay Peru St. Kitts and Nevis St. Lucia St. Vincent and the Grenadines Suriname Uruguay Venezuela, RB

Europe and Central Asia Albania Armenia Azerbaijan Belarus Bosnia and Herzegovina Bulgaria Georgia Kazakhstan Kosovo Kyrgyz Republic Lithuania Macedonia, FYR Moldova Montenegro Romania Russian Federation Serbia Tajikistan Turkey Turkmenistan Ukraine Uzbekistan

Middle East and North Africa Algeria Djibouti Egypt, Arab Rep. Iran, Islamic Rep. Iraq Jordan Lebanon Libya Morocco Syrian Arab Republic Tunisia West Bank and Gaza Yemen, Rep.

Latin America and the Caribbean Antigua and Barbuda Argentina Belize Bolivia Brazil Chile

South Asia Afghanistan Bangladesh Bhutan India Maldives Nepal Pakistan Sri Lanka Sub-Saharan Africa Angola Benin Botswana Burkina Faso Burundi Cameroon

20433 20433USA USA 20433 USA Telephone: Telephone:202 202473 4731000 1000 Telephone: 202 473 1000 Fax: Fax:202 202477 4776391 6391 Fax: 202 477 6391 Web Website: site:data.worldbank.org data.worldbank.org Web site: data.worldbank.org

Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Eritrea Ethiopia Gabon Gambia, The Ghana Guinea Guinea-Bissau Kenya Lesotho Liberia Madagascar Malawi Mali Mauritania Mauritius Mayotte Mozambique Namibia Niger Nigeria Rwanda São Tomé and Principe Senegal Seychelles Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe High-income OECD Australia Austria * Belgium * Canada Czech Republic Denmark Estonia * Finland * France * Germany * Greece * Hungary Iceland Ireland * Israel Italy *

Japan Korea, Rep. Luxembourg * Netherlands * New Zealand Norway Poland Portugal * Slovak Republic * Slovenia * Spain * Sweden Switzerland United Kingdom United States Other high income Andorra Aruba Bahamas, The Bahrain Barbados Bermuda Brunei Darussalam Cayman Islands Channel Islands Croatia Cyprus * Equatorial Guinea Faeroe Islands French Polynesia Gibraltar Greenland Guam Hong Kong SAR, China Isle of Man Kuwait Latvia Liechtenstein Macao SAR, China Malta * Monaco Netherlands Antilles New Caledonia Northern Mariana Islands Oman Puerto Rico Qatar San Marino Saudi Arabia Singapore Taiwan, China Turks and Caicos Islands Trinidad and Tobago United Arab Emirates Virgin Islands (U.S.) * Member of the Euro area

Email: Email:data@worldbank.org data@worldbank.org Email: data@worldbank.org

The World World Development Development Indicators Indicators The Development Indicators Includes more more than than 800 800 indicators indicators for •• Includes than 800 indicators for 155 155 economies economies Provides definitions, definitions, sources, sources, and the data data •• Provides definitions, sources, and other other information information about about the Organizes the the data data into into six six thematic •• Organizes into six thematic areas areas

WORLD WORLD VIEW VIEW

11

PEOPLE PEOPLE

ENVIRONMENT ENVIRONMENT

Living standards Living standards standards and development and development development progress progress

Gender, Gender, health, health, and and employment employment

Natural Naturalresources resources Natural resources and andenvironmental environmental and environmental changes changes changes

ECONOMY ECONOMY

STATES STATES && MARKETS MARKETS

GLOBAL GLOBAL LINKS LINKS

New New opportunities opportunities opportunities for for growth growth

Elements Elements of of aa good good investment investment climate climate

Evidence Evidence Evidenceon on on globalization globalization globalization

Saved: Saved: Saved:91 91 91trees trees trees 29 29 29million million millionBtu Btu Btuofofof total total total energy energy energy 8,609 8,609 8,609pounds pounds poundsofofof net net net greenhouse greenhouse greenhouse gases gases gases 41,465 41,465 41,465gallons gallons gallons ofofof waste waste waste water water water 2,518 2,518 2,518pounds pounds poundsofofof solid solid solid waste waste waste

WORLD WORLD DEVELOPMENT DEVELOPMENT INDICATORS INDICATORS

The world by income

11

Low income Afghanistan Bangladesh Benin Burkina Faso Burundi Cambodia Central African Republic Chad Comoros Congo, Dem. Rep. Eritrea Ethiopia Gambia, The Ghana Guinea Guinea-Bissau Haiti Kenya Korea, Dem. Rep. Kyrgyz Republic Lao PDR Liberia Madagascar Malawi Mali Mauritania Mozambique Myanmar Nepal Niger Rwanda Sierra Leone Solomon Islands Somalia Tajikistan Tanzania Togo Uganda Zambia Zimbabwe Lower middle income Angola Armenia Belize Bhutan Bolivia Cameroon Cape Verde China Congo, Rep. Côte d'Ivoire Djibouti Ecuador Egypt, Arab Rep. El Salvador Georgia Guatemala Guyana

Honduras India Indonesia Iraq Jordan Kiribati Kosovo Lesotho Maldives Marshall Islands Micronesia, Fed. Sts. Moldova Mongolia Morocco Nicaragua Nigeria Pakistan Papua New Guinea Paraguay Philippines Samoa São Tomé and Principe Senegal Sri Lanka Sudan Swaziland Syrian Arab Republic Thailand Timor-Leste Tonga Tunisia Turkmenistan Tuvalu Ukraine Uzbekistan Vanuatu Vietnam West Bank and Gaza Yemen, Rep. Upper middle income Albania Algeria American Samoa Antigua and Barbuda Argentina Azerbaijan Belarus Bosnia and Herzegovina Botswana Brazil Bulgaria Chile Colombia Costa Rica Cuba Dominica Dominican Republic Fiji Gabon

Grenada Iran, Islamic Rep. Jamaica Kazakhstan Lebanon Libya Lithuania Macedonia, FYR Malaysia Mauritius Mayotte Mexico Montenegro Namibia Palau Panama Peru Romania Russian Federation Serbia Seychelles South Africa St. Kitts and Nevis St. Lucia St. Vincent and the Grenadines Suriname Turkey Uruguay Venezuela, RB High income Andorra Aruba Australia Austria Bahamas, The Bahrain Barbados Belgium Bermuda Brunei Darussalam Canada Cayman Islands Channel Islands Croatia Cyprus Czech Republic Denmark Equatorial Guinea Estonia Faeroe Islands Finland France French Polynesia Germany Gibraltar Greece Greenland Guam

Hong Kong SAR, China Hungary Iceland Ireland Isle of Man Israel Italy Japan Korea, Rep. Kuwait Latvia Liechtenstein Luxembourg Macao SAR, China Malta Monaco Netherlands Netherlands Antilles New Caledonia New Zealand Northern Mariana Islands Norway Oman Poland Portugal Puerto Rico Qatar San Marino Saudi Arabia Singapore Slovak Republic Slovenia Spain Sweden Switzerland Trinidad and Tobago Turks and Caicos Islands United Arab Emirates United Kingdom United States Virgin Islands (U.S.)

INCOME MAP

ISBN978-0-8213-8709-2 978-0-8213-8709-2 ISBN 978-0-8213-8709-2

WORLD DEVELOPMENT INDICATORS

REGION MAP

The TheWorld WorldBank Bank The World Bank 1818 1818HHHStreet StreetN.W. N.W. 1818 Street N.W. Washington, Washington,D.C. D.C. Washington, D.C.


Economy


Introduction

4

R

ecently revised data now confirm that in 2009 the world economy experienced the steepest global recession since the Great Depression. World gross domestic product (GDP) contracted 1.9 percent in 2009, with high-income economies contracting 3.3 percent and developing economies expanding just 2.7 percent, down from 8.6 percent in 2008. Among developing country regions, Europe and Central Asia fared the worst, contracting 5.8 percent (figure 4a). Contrast that with East Asia and Pacific, which grew at 7.4 percent, and South Asia, at 7 percent. The global economy rebounded in 2010, with domestic demand in developing countries accounting for 46 percent of global growth. Developing economies’ contribution to global growth has been rising since 2000 and was more stable than that of high-income economies during the recent recession (figure 4b). Preliminary estimates, often revised, indicate that the world economy grew 3.9 percent—2.8 percent in high-income economies and 7 percent in developing economies (figure 4c). Revisions to GDP Revisions to GDP usually occur one to two months after the initial release, as additional data sources become available. For example, the U.S. Bureau of Economic Analysis releases three versions of quarterly GDP estimates—advance (about a month after the quarter ends), preliminary (two months after), and final (three months after). Other countries follow a similar process, although the reporting lag varies. And some countries compile GDP only annually not quarterly. The differences between GDP estimates decline with each revision, and GDP data become more stable on average (figure 4d). More significant revisions to GDP involve new methodologies and new or improved data sources and data collection practices. Countries with advanced statistical capacity comprehensively revise GDP estimates every five years. These revisions take into account the latest recommendations of the Intersecretariat Working Group on National Accounts. They may also incorporate a change in the base year used for the constant price data (rebasing). Rebasing adjusts the weights used to compute aggregate measures by selecting a new set of relative component prices in the newly chosen base year. Comprehensive revisions of GDP estimates are usually higher as improved data sources increase the coverage of the economy and new weights for growing industries more accurately reflect contributions

Differences in GDP growth among developing country regions

4a 2008

GDP growth (percent)

2009

2010a

10 5 0 –5 –10

East Asia & Pacific

Europe & Central Asia

Latin America & Caribbean

Middle East & North Africa

South Asia

Sub-Saharan Africa

a. Data are preliminary estimates. Source: World Development Indicators data files.

Developing countries are contributing more to global growth Contribution to GDP growth (percent)

4b

High-income economies

Developing economies

World GDP

6 4 2 0 –2 –4

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010a

a. Data are preliminary estimates. Source: World Development Indicators data files.

2011 World Development Indicators

189


4c

Economies—both developing and high income—rebounded in 2010 GDP growth (percent) 10 Developing economies

5 World

0 High-income economies –5

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010a

a. Data are preliminary estimates. Source: World Development Indicators data files.

Revisions to GDP decline over time, and GDP data become more stable on average

4d

Average difference in GDP (percent) 3

2

1

0

2000

2001

2002

2003

2004

2005

2006

2007

2008

Note: Average differences in current price GDP between World Development Indicators 2010 and 2011. Source: World Development Indicators data files.

4e

Ghana’s revised GDP was 60 percent higher in the new base year, 2006 GDP ($ billions)

World Development Indicators 2010

World Development Indicators 2011

30

20

10

0

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

Source: World Development Indicators data files.

4f

Revised data for Ghana show a larger share of services in GDP 2008 value added by industry (percent of GDP)

World Development Indicators 2010

World Development Indicators 2011

50 40

Broader measures of income and savings

30 20 10 0

Agriculture

Source: World Development Indicators data files.

190

to the economy. This has been the case for several countries that recently undertook such revisions to their national accounts statistics. In November 2010 the Ghana Statistical Service revised Ghana’s national accounts series, increasing GDP 60  percent in 2006, the new base year (figure 4e). Of the increase, 11  percentage points are in agriculture, 6 in industry, and 44 in services (figure 4f). Other countries have made similar revisions to their national accounts, incorporating improved methodology and data sources. Namibia revised its national accounts in 2008, resulting in 10–30 percent higher GDP estimates for 2000–07. Malawi revised its national accounts in 2007, raising GDP 37  percent. São Tomé and Príncipe revised its national accounts in 2006, resulting in 47.5 percent higher GDP in the new base year 2001. For more information on countries that have recently revised their national accounts data, see Primary data documentation. Many countries do not incorporate new sources of data into national accounts data compilation until they change the base year, which is the base or pricing period for constant price calculations. Such revisions can be substantial because of the long lag between rebasing exercises. The adjustments arising from rebasing can be reduced by incorporating new data sources in a timely manner and ensuring that the accounts are rebased at least every five years. Data users should be aware that rebasing creates a break in the time series. New data sources and methodologies are usually implemented only for recent years, creating a jump in GDP between the last year of the old data and the first year of the new. For constant price GDP these breaks can be eliminated by linking the old series to the new using historical growth rates. But for nominal GDP data the break in the time series cannot be avoided unless the statistics office revises historical series backward at a detailed level.

2011 World Development Indicators

Industry

Services

Two tables have been added to the Economy section this year. Table 4.10 contains new measures of adjusted net national income, and table 4.11 contains measures of adjusted net savings, previously included in the Environment section. Both tables follow recommendations of


economy

the recently published The Changing Wealth of Nations (World Bank 2011a). Adjusted net savings measures the change in a country’s national wealth. It begins with gross national savings and then adjusts for consumption of fixed capital, depletion of natural resources, changes in human capital, and damages from carbon dioxide and particulate emissions. If adjusted net savings is negative, capital stocks are declining and future well-being is reduced. The report argues that the key to increasing living standards is building national wealth through investment and national savings to finance the investment. The table on adjusted net national income presents growth rates of GDP, gross national income (GNI), and adjusted net national income. GNI is more useful than GDP for measuring the economic resources available to residents of an economy because it takes into account inflows of income (profits, wages, and rents) from outside the economy, net of outflows to other economies (box 4g). Adjusted net national income goes one step further by subtracting from GNI a charge for the consumption of fixed capital (or depreciation) and the depletion of natural resources. For some countries, adjusted net national income growth rates tell a story quite different from that of the more widely used GDP growth rates.

Changes to monetary indicators The monetary indicators in table 4.15 have been revised to reflect the International Monetary Fund’s (IMF) new presentation of monetary data for countries reporting in compliance with the Monetary and Financial Statistics Manual (IMF 2000) and Monetary and Financial Statistics Compilation Guide (IMF 2008). More than 120 countries report their monetary data under

Commission on the Measurement of Economic and Social Progress

4g

Gross domestic product (GDP), the most quoted measure of economic activity, is often used as a measure of welfare. But as the Commission on the Measurement of Economic and Social Progress points out, GDP has many shortcomings as the sole measure of well-being. The commission’s report identified problems with the GDP measure itself and recommended including additional measures of the objective and subjective dimensions of well-being and measures of the sustainability of current consumption levels. The commission endorsed the adjusted net savings approach as the “relevant economic counterpart of the notion of sustainability” (Stiglitz, Sen, and Fitoussi 2009, p. 108). But it pointed out that the adjustment for environmental degradation has so far been limited mostly to carbon dioxide emissions. The report also notes the difficulties of pricing natural resources and environmental degradation. Other recommendations for improving GDP measurement include accounting more accurately for improvements in the quality of goods and services produced and the value of government services (usually based on inputs rather than on actual outputs produced).

this new presentation. A majority of these countries transmit the data on standardized report forms for the country’s monetary aggregates and for the assets and liabilities of the central bank, other depository corporations, and other financial corporations. This new presentation better classifies financial institution assets and liabilities by financial instrument, sector of the domestic economy, and residency. For many countries the new presentation provides broader institutional coverage of other depository corporations and monetary aggregates. In the new presentation, the IMF has adopted broad money as the flagship concept. Broad money consists of currency in circulation outside depository corporations, transferable deposits, and other liquid components. Table 4.15 has replaced money and quasi money with broad money. Claims on the private sector have been replaced with other claims on the domestic economy, consisting of the private sector plus state and local governments, public nonfinancial corporations, and other financial corporations. Claims on governments and other public entities have been replaced with net claims on the central government.

2011 World Development Indicators

191


Tables

4.a Albania Algeria Angola Argentinab Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Bolivia Botswana Brazil Bulgaria Cambodia Cameroon Canada Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Costa Rica Côte d’Ivoire Croatia Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Haiti Honduras Hungary India Indonesia Iran, Islamic Rep. Ireland Israel Italy Jamaica Japan Jordan

192

Recent economic performance Gross domestic product

Exports of goods and services

Imports of goods and services

GDP deflator

average annual % growth 2009 2010a

average annual % growth 2009 2010a

average annual % growth 2009 2010a

average annual % growth 2009 2010a

2.5 2.1 0.7 0.9 –14.4 1.3 –3.9 9.3 5.7 1.4 –2.8 3.4 –3.7 –0.6 –4.9 –1.9 2.0 –2.5 –1.5 9.1 –2.8 0.8 2.7 –1.5 3.6 –5.8 –4.2 –4.9 3.5 0.4 4.6 –3.5 –14.1 8.7 –8.0 –2.6 –1.0 4.6 –3.9 –4.7 4.7 –2.0 0.6 2.9 –1.9 –6.3 9.1 4.5 1.8 –7.1 0.8 –5.0 –3.0 –5.2 2.3

3.0 2.4 3.0 8.0 4.0 2.8 1.5 3.7 5.8 7.0 2.1 4.1 7.8 7.6 0.0 4.9 3.0 3.0 5.5 10.0 6.0 4.3 5.2 3.6 3.0 –0.8 1.7 2.1 4.4 2.3 5.1 1.3 1.0 9.0 3.0 1.6 5.1 5.0 5.5 3.5 6.6 –4.0 2.2 –8.5 2.4 0.3 9.5 5.9 1.5 –0.6 3.8 1.1 0.6 4.4 4.0

2011 World Development Indicators

5.9 –3.0 2.4 –6.4 –32.8 2.9 –16.1 2.8 0.0 –8.2 –11.4 –10.8 –28.0 –10.2 –10.3 –6.3 –4.8 –14.2 –5.6 –10.3 –10.1 –2.8 5.4 0.6 9.3 –16.2 –10.2 –9.7 –7.4 –6.4 –14.5 –16.4 –11.2 6.9 –20.5 –12.2 –4.9 2.5 –8.4 –14.3 12.6 –6.2 –6.2 9.9 –12.6 –9.1 –6.7 –9.7 8.5 –4.2 –11.9 –19.1 –10.8 –24.2 –2.7

12.7 3.0 10.0 12.8 8.5 15.0 8.2 11.0 –9.0 6.0 9.7 11.4 12.0 26.0 11.0 8.0 17.0 15.5 8.5 33.0 22.1 17.4 9.3 6.2 4.4 2.5 9.4 5.1 8.1 –2.0 11.8 9.4 5.4 11.7 6.8 6.6 7.0 5.2 11.0 10.7 8.9 0.5 9.9 –7.1 4.5 6.8 8.1 24.7 –3.0 1.7 17.8 8.0 5.7 28.7 5.2

–12.0 16.7 6.6 –19.0 –21.0 –9.0 –14.4 –5.3 –2.6 –8.6 –11.1 –10.2 –9.3 –11.5 –21.5 –4.9 –5.2 –13.9 –14.3 4.1 –8.8 –7.9 –11.9 –12.4 11.0 –20.7 –10.2 –12.5 –9.8 –8.0 –17.9 –23.3 –26.8 16.4 –18.1 –10.7 –2.8 3.8 –6.4 –9.4 –14.1 –18.6 –9.4 5.8 –26.0 –15.4 –7.3 –15.0 7.8 –9.7 –17.7 –14.5 –11.4 –16.7 –7.8

5.2 12.5 8.5 23.1 4.2 28.7 6.8 3.5 –12.5 3.4 8.2 12.3 8.9 35.1 3.0 12.6 12.0 14.6 25.5 35.0 22.5 21.4 10.8 13.1 5.0 1.5 10.4 1.0 11.8 5.0 12.0 15.2 4.0 4.4 3.5 5.2 4.8 3.1 9.0 9.1 10.5 –12.1 14.3 5.9 10.4 5.4 6.8 32.5 16.5 2.1 17.5 9.4 9.3 15.6 6.5

2.3 –9.4 –5.8 10.0 1.4 4.9 0.8 –16.8 6.5 3.9 1.1 –2.4 –5.7 5.7 4.1 5.1 –3.4 –2.1 4.2 –0.6 0.2 4.9 30.2 8.9 1.3 3.3 2.7 0.4 3.0 4.3 10.8 –1.0 –0.6 24.4 0.9 0.5 –19.0 2.4 –2.0 1.4 16.7 1.3 2.4 3.5 4.4 4.6 7.5 8.4 0.6 –3.2 5.2 2.1 6.5 –0.9 8.1

2.0 8.6 36.1 9.4 7.5 5.7 0.6 –2.7 10.7 6.4 –2.8 6.5 6.0 5.3 –0.6 3.9 3.4 2.7 6.6 1.7 0.3 4.8 21.7 7.9 1.3 1.6 1.6 5.3 7.1 4.4 11.2 3.6 –1.1 9.9 –0.4 1.4 9.1 4.8 7.4 1.6 10.6 4.8 6.4 12.6 10.5 2.7 11.5 6.2 15.0 0.6 4.6 1.6 16.7 –1.0 8.5

Current account balance

Gross international reserves

% of GDP 2009 2010a

months of import coverage 2010a

–15.6 –10.0 –10.0 2.8 –15.7 –4.2 2.9 23.7 3.7 –13.0 0.7 4.7 –4.4 –1.5 –9.8 –8.8 –5.1 –2.9 2.6 6.0 8.3 –2.1 –13.7 –1.8 7.2 –5.3 –1.1 3.6 –4.6 –0.5 –1.8 –1.8 4.7 –7.7 2.9 –2.0 .. 8.6 –11.3 5.0 –4.6 –10.9 0.0 –3.6 –3.1 –0.5 –1.9 2.0 3.4 –2.9 3.9 –3.1 –9.3 2.8 –5.0

–12.2 4.6 –5.1 1.8 –12.7 –2.2 3.9 27.2 2.4 –14.0 0.6 8.0 –2.1 –2.7 –2.4 –8.6 –2.7 –2.0 0.6 5.5 22.0 –2.7 –17.2 –3.2 4.1 –4.4 –2.7 5.6 –5.9 –0.8 –4.1 –3.1 4.0 –8.5 3.7 –2.1 12.7 5.2 –12.1 5.9 –3.6 –8.5 –2.5 –13.6 –4.7 –0.4 –3.8 2.6 6.1 –3.6 4.9 –3.6 –7.9 3.8 –4.6

$ millions 2010a

2,496 166,989 .. 52,208 1,859 42,268 22,339 6,409 11,175 5,025 26,779 .. .. 288,575 17,223 3,787 .. 57,151 27,827 2,711,162 266,055 28,076 1,768 4,630 3,502 14,133 42,328 75,077 3,501 2,622 36,517 2,897 2,567 .. 9,547 165,852 .. .. 2,264 215,978 .. 6,352 5,949 1,282 .. 44,988 300,480 92,815 .. 2,114 70,914 158,478 2,330 1,096,069 13,388

4.5 42.0 .. 10.2 6.7 1.8 1.4 7.0 6.4 2.0 0.9 .. .. 13.9 7.6 6.0 .. 1.4 5.4 21.6 6.7 6.6 7.3 4.1 4.8 7.1 3.9 6.7 2.7 1.1 5.7 3.9 2.3 .. 1.4 2.9 .. .. 5.0 2.0 .. 0.9 5.1 5.3 .. 5.5 9.7 7.1 .. 0.2 12.0 3.5 4.0 17.6 9.5


Kazakhstan Kenya Korea, Rep. Kuwait Latvia Lebanon Lithuania Malaysia Mauritius Mexico Morocco Namibia Nepal Netherlands New Zealand Nigeria Norway Oman Pakistan Panama Paraguay Peru Philippines Poland Portugal Romania Russian Federation Saudi Arabia Senegal Singapore Slovak Republic Slovenia South Africa Spain Sri Lanka Sudan Sweden Switzerland Syrian Arab Republic Tanzania Thailand Trinidad and Tobago Tunisia Turkey Uganda Ukraine United Kingdom United States Uruguay Venezuela, RB Vietnam Yemen, Rep. Zambia Zimbabwe

Gross domestic product

Exports of goods and services

Imports of goods and services

GDP deflator

average annual % growth 2009 2010a

average annual % growth 2009 2010a

average annual % growth 2009 2010a

average annual % growth 2009 2010a

1.2 2.6 0.2 –4.0 –18.0 9.0 –15.0 –1.7 2.1 –6.5 4.9 –0.8 4.7 –4.0 –0.4 5.6 –1.6 3.6 3.6 2.4 –3.8 0.9 1.1 1.7 –2.6 –8.5 –7.9 0.6 2.2 –1.3 –6.2 –7.8 –1.8 –3.6 3.5 4.5 –5.1 –1.9 4.0 6.0 –2.2 –3.0 3.1 –4.7 7.1 –15.1 –4.9 –2.6 2.9 –3.3 5.3 3.8 6.4 5.7

5.5 5.0 6.2 1.9 –2.2 8.0 0.4 7.4 4.2 5.2 3.5 4.2 3.3 1.7 2.2 7.6 –0.2 4.8 4.4 5.7 8.5 8.0 6.8 3.5 1.4 –1.9 3.8 3.7 4.0 17.5 3.7 1.5 2.7 –0.4 7.1 5.9 5.2 2.7 5.0 7.0 7.5 2.2 3.8 8.1 6.3 4.3 1.7 2.8 7.9 –2.3 6.7 8.0 6.4 5.7

–6.2 –7.0 –0.8 –11.1 –13.9 5.3 –14.3 –10.4 –4.8 –14.8 –13.1 –14.0 38.4 –7.9 0.4 1.1 –3.9 –0.4 –3.3 –0.9 –12.8 –2.5 –13.4 –9.1 –11.7 –11.8 –4.7 –2.8 –8.8 –10.1 8.8 –19.3 –19.5 –11.6 –12.3 –4.4 –13.3 –8.7 5.6 15.5 –12.7 –3.8 –1.6 –5.3 16.2 –25.6 –10.1 –9.5 2.5 –12.9 11.1 –16.3 21.5 5.2

13.0 12.0 28.0 –2.0 4.0 20.0 6.5 28.0 –4.0 15.5 18.4 5.3 6.4 11.7 10.5 5.9 4.6 8.0 14.1 5.3 30.1 –4.1 23.0 6.4 7.4 12.0 5.2 1.5 6.8 29.7 6.9 1.4 6.5 7.8 2.0 7.2 12.2 6.7 –2.0 5.3 21.0 3.0 13.0 6.5 3.4 9.5 7.0 15.0 15.6 3.2 25.0 43.6 20.0 10.5

–15.9 –0.2 –8.2 –17.0 –34.2 6.5 –29.4 –12.3 –4.6 –18.2 –6.0 5.3 20.2 –8.5 –14.8 7.3 –11.4 –13.0 –15.2 –5.6 –13.2 –11.9 –1.9 –14.3 –10.8 –24.6 –30.4 –8.8 –17.1 –11.7 8.4 –7.9 –17.4 –17.8 –9.1 –7.3 –13.2 –5.4 6.4 14.1 –21.8 –4.1 6.7 –14.3 25.2 –38.6 –12.3 –13.8 –8.6 –19.6 6.7 –4.7 15.6 36.0

6.0 14.5 28.0 22.0 1.6 18.5 4.2 30.0 3.9 19.4 7.6 8.3 6.8 12.7 17.5 8.2 8.1 18.0 11.2 13.1 30.3 15.3 23.8 7.5 3.6 8.5 17.5 7.5 4.0 26.7 6.0 –4.1 12.7 7.0 11.5 7.2 15.0 8.3 4.5 6.2 32.0 4.2 16.1 16.0 10.5 5.5 9.4 18.8 19.2 –3.0 32.5 14.2 12.3 6.2

4.7 6.7 3.4 –14.7 –0.7 5.8 –2.1 –6.7 1.5 4.3 1.8 6.5 12.1 –0.3 1.7 –0.6 –4.0 –26.0 20.0 4.1 –0.1 3.0 2.6 3.7 0.1 6.5 2.5 –21.6 –0.5 –1.8 0.0 1.9 7.3 0.2 5.7 –0.8 2.0 0.3 –7.6 7.4 2.0 –15.7 2.9 5.2 16.5 13.4 1.4 0.9 5.9 8.4 6.0 –4.1 12.7 25.3

6.9 4.8 –0.5 13.9 –4.9 4.5 0.0 1.5 2.1 4.9 2.2 4.3 15.1 2.9 4.4 17.0 7.9 21.2 13.4 2.4 4.8 3.2 5.6 2.4 1.0 5.5 8.0 16.7 0.7 –2.2 2.9 –0.2 5.6 0.1 8.2 13.0 0.9 0.9 10.2 8.7 –1.9 4.6 3.8 7.1 6.1 9.2 3.0 0.6 7.1 38.5 12.5 13.8 –5.8 4.2

4.a

economy

Recent economic performance Current account balance

Gross international reserves

% of GDP 2009 2010a

months of import coverage 2010a

–3.7 –5.7 5.1 25.6 8.7 –21.9 4.4 16.5 –7.9 –0.7 –5.4 1.3 –0.1 4.6 –2.9 12.5 13.1 –0.6 –2.2 –0.2 0.6 0.2 5.3 –2.2 –10.3 –4.5 4.0 6.1 –13.6 17.9 –3.2 –1.5 –4.0 –5.5 –0.5 –7.1 7.7 7.9 –4.5 –8.5 8.3 21.8 –3.1 –2.3 –2.8 –1.5 –1.7 –2.7 0.7 2.6 –7.0 –9.7 –3.2 –1.8

3.8 –5.7 3.7 25.1 1.4 –23.6 2.6 14.7 –9.4 –1.0 –3.2 –1.6 –3.0 5.6 –2.5 10.7 11.8 8.5 –3.1 –6.1 –1.8 –1.7 5.3 –3.1 –10.6 –6.3 5.1 7.8 –14.3 22.6 –0.1 –2.2 –4.1 –6.0 –3.6 –1.9 6.7 7.7 –3.9 –8.3 6.0 25.7 –4.8 –5.9 –3.6 –2.2 –2.9 –3.3 –0.6 5.9 –15.5 –0.6 –4.5 –1.3

$ millions 2010a

28,281 4,327 292,143 24,805 7,604 44,476 6,836 106,501 2,619 120,583 23,585 .. .. 46,147 15,787 .. 50,036 13,025 17,256 .. 3,962 44,215 62,324 93,472 20,937 48,048 479,222 452,391 1,911 .. 2,156 1,108 43,820 31,872 7,240 .. 48,246 269,396 .. .. 172,028 .. .. 85,959 .. 34,571 82,365 488,928 7,744 27,700 .. 5,986 2,094 ..

8.4 4.1 7.0 8.2 7.9 27.3 4.1 6.9 5.7 4.7 7.7 .. .. 1.0 4.8 .. 5.3 7.3 5.7 .. 5.0 17.1 12.1 6.3 2.9 8.0 19.2 32.9 3.9 .. 0.3 0.5 5.8 1.0 6.7 .. 2.9 14.5 .. .. 10.4 .. .. 5.3 .. 7.2 1.4 2.3 9.7 5.9 .. 10.0 5.6 ..

a. Data are preliminary estimates based on World Bank staff estimates and National Sources. b. Private analysts estimate that consumer price index inflation was considerably higher for 2007–09 and believe that GDP volume growth has been significantly higher than official reports indicate since the last quarter of 2008. Source: World Development Indicators data files, the World Bank’s Global Economic Prospects 2011, and the International Monetary Fund’s International Financial Statistics. 2011 World Development Indicators

193


4.1

Growth of output Gross domestic product

average annual % growth 1990–2000 2000–09

Afghanistan Albania Algeria Angolaa Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benina Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile Chinaa Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep.a Costa Rica Côte d’Ivoirea Croatia Cuba Czech Republic Denmark Dominican Republica Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabona Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

194

.. 3.8 1.9 1.6 4.3 –1.9 3.7 2.4 –6.3 4.8 –1.6 2.2 4.8 4.0 .. 5.0 2.7 –1.1 5.5 –2.9 7.0 1.7 3.1 2.0 2.2 6.6 10.6 3.6 2.8 –4.9 1.0 5.3 3.2 0.5 –0.7 1.1 2.7 6.3 1.9 4.4 4.8 5.7 0.4 3.8 2.7 1.9 2.3 3.0 –7.1 1.8 4.3 2.2 4.2 4.4 1.2 0.5 3.2

2011 World Development Indicators

10.5 5.4 4.0 13.1 5.4b 10.5 3.3 2.0 17.9 5.9 8.4 1.7 4.0 4.1 5.0 4.4 3.6 5.4 5.4 3.0 9.0 3.3 2.1 0.8 10.2 4.1 10.9 4.7 4.5 5.2 4.0 5.1 0.8 3.9 6.7 4.1 1.2 5.5 5.0 4.9 2.6 0.2 5.9 8.5 2.5 1.5 2.1 5.2 7.4 1.0 5.8 3.6 3.7 3.0 1.0 0.7 4.9

Agriculture

average annual % growth 1990–2000 2000–09

.. 4.3 3.6 –1.4 3.5 0.5 3.1 –0.1 –1.7 2.9 –4.0 2.7 5.8 2.9 .. –0.5 3.6 –3.9 5.9 –1.9 3.7 5.4 1.1 3.8 4.9 2.2 4.1 .. –2.7 1.4 .. 4.1 3.5 –5.5 –3.3 0.0 4.6 1.9 –1.7 3.1 1.2 1.5 –6.2 2.6 –0.3 2.0 2.0 3.3 –11.0 0.1 .. 0.5 2.8 4.3 .. .. 2.2

4.9 1.4 4.6 14.0 2.5 6.6 0.0 1.3 5.3 3.3 5.2 –1.0 4.6 3.1 4.9 1.2 3.7 –2.5 6.2 –1.5 5.7 3.4 1.4 0.3 .. 5.2 4.4 –3.3 2.5 1.7 .. 3.5 1.4 2.0 –0.9 0.1 –1.8 3.2 3.7 3.3 3.6 2.7 –2.9 7.0 2.4 0.3 1.4 3.0 0.6 –0.3 .. –1.4 2.9 6.7 .. .. 3.3

Industry

average annual % growth 1990–2000 2000–09

.. –0.5 1.8 4.4 3.8 –7.8 2.7 2.5 –2.1 7.3 –1.8 1.8 4.1 4.1 .. 3.7 2.4 –19.5 5.9 –4.3 14.3 –0.9 3.2 0.7 0.6 5.6 13.7 .. 1.4 –8.0 .. 6.2 6.3 –2.2 –1.0 0.2 2.5 7.1 2.6 5.1 5.1 15.0 –2.4 4.1 3.8 1.1 1.6 1.0 –8.1 –0.1 .. 1.0 4.3 4.9 .. .. 3.6

14.5 4.4 3.3 13.4 6.1 11.3 2.6 2.3 23.1 7.8 12.3 0.7 3.8 5.3 6.8 2.5 2.8 5.9 7.3 –6.2 12.0 –0.4 0.1 –0.4 .. 2.7 11.8 –2.6 4.4 8.7 .. 5.1 –0.2 4.6 2.3 5.7 –0.5 2.4 4.2 5.3 1.7 0.6 8.6 9.3 3.6 0.5 0.9 7.4 10.0 0.3 .. 1.4 2.8 4.4 .. .. 4.1

Manufacturing

average annual % growth 1990–2000 2000–09

.. .. –2.1 –0.3 2.7 –4.3 1.8 2.5 –15.7 7.2 –0.7 .. 5.8 3.8 .. 4.7 2.0 .. 5.9 .. 18.6 1.4 4.5 –0.2 .. 4.4 12.9 .. –2.5 –8.7 .. 6.8 5.5 –3.5 0.8 4.3 2.2 7.0 1.5 6.3 5.2 10.6 7.3 3.9 6.4 .. 3.0 0.9 .. 0.1 .. .. 2.8 4.0 .. .. 4.0

8.7 .. 2.6 20.2 5.8 4.6 1.3 2.9 10.8 7.9 10.8 .. 2.7 4.5 7.6 4.8 2.6 6.2 6.3 .. 11.3 .. –1.6 –0.1 .. 3.2 11.4 .. 4.0 6.3 .. 4.7 –1.7 3.7 –1.5 7.0 0.4 2.7 5.3 4.7 2.1 –6.0 8.9 7.2 4.1 0.1 3.1 .. 10.9 0.8 .. 1.7 2.8 3.1 .. .. 4.6

Services

average annual % growth 1990–2000 2000–09

.. 6.9 1.8 –2.2 4.5 6.4 4.2 2.5 –2.7 4.5 –0.4 2.0 4.2 4.3 .. 9.1 3.8 .. 3.9 –2.8 7.1 0.2 3.1 0.2 0.8 6.9 11.0 .. 4.1 –13.0 .. 4.7 2.0 2.2 –0.7 1.2 2.7 5.9 2.4 4.1 4.0 5.7 3.2 5.2 2.6 2.2 3.1 3.7 –0.3 2.9 .. 2.6 4.7 3.6 .. .. 3.8

13.5 8.3 5.3 12.1 4.7 12.1 3.7 2.1 10.6 6.1 5.9 2.0 3.2 3.1 4.4 5.6 3.8 6.1 5.5 10.4 9.5 6.2 3.0 –2.5 .. 4.6 11.6 5.3 4.7 11.2 .. 5.6 1.0 4.0 8.3 4.3 1.5 7.1 3.6 5.4 3.2 0.5 7.1 10.2 1.6 1.9 3.2 6.1 8.9 1.5 .. 4.7 4.4 –2.7 .. .. 6.2


Gross domestic product

average annual % growth 1990–2000 2000–09

Hungary India Indonesiaa Iran, Islamic Rep. Iraq Ireland Israela Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait a Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysiaa Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar a Namibia Nepal Netherlands New Zealand Nicaragua Niger a Nigeria Norway Omana Pakistan Panama Papua New Guinea Paraguaya Peru Philippinesa Poland Portugal Puerto Ricoa Qatar

1.5 5.9 4.2 3.1 .. 7.4 5.5 1.5 1.6 1.0 5.0 –4.1 2.2 .. 5.8 .. 4.9 –4.1 6.4 –1.5 5.3 4.0 4.1 .. –2.5 –0.8 2.0 3.7 7.0 4.1 2.9 5.2 3.1 –9.6 1.0 2.4 6.1 .. 4.0 4.9 3.2 3.2 3.7 2.4 2.5 3.9 4.5 3.8 4.7 3.8 2.2 4.7 3.3 4.7 2.9 4.2 ..

2.9 7.9 5.3 5.4 –0.3 3.9 3.6 0.5 1.5 1.1 6.9 8.8 4.4 .. 4.2 4.8 8.4 4.6 6.9 6.2 4.6 3.1 0.0 5.4 6.3 3.1 3.6 4.8 5.1 5.3 4.7 3.7 2.2 5.6 7.4 5.0 7.9 .. 5.3 3.7 1.7 2.5 3.3 4.3 6.6 2.1 4.5 5.2 6.9 3.4 3.4 6.0 4.9 4.4 0.8 .. 14.2

Agriculture

average annual % growth 1990–2000 2000–09

–1.9 3.2 2.0 3.2 .. 0.0 .. 2.1 –0.6 –1.3 –3.0 –8.0 1.9 .. 1.6 .. 1.0 1.5 4.8 –5.2 2.9 2.8 .. .. –0.4 0.2 1.8 8.6 0.3 2.6 –0.2 0.0 1.5 –11.2 2.5 –0.4 5.2 .. 3.8 2.5 1.8 2.9 4.7 3.0 .. 2.6 5.0 4.4 3.1 4.5 3.3 5.5 1.7 0.5 –0.6 .. ..

5.3 2.9 3.4 5.9 .. –4.6 .. –0.2 –0.7 –0.3 8.3 4.6 2.2 .. 2.0 .. .. 1.8 3.3 2.7 1.4 –2.4 .. .. 1.7 2.2 2.4 2.4 3.5 4.8 0.9 –0.8 2.0 –0.6 5.9 5.8 8.2 .. 0.5 3.1 1.5 1.8 2.7 .. .. 2.4 .. 3.5 3.5 2.2 2.3 4.1 3.6 0.8 –0.3 .. ..

Industry

average annual % growth 1990–2000 2000–09

3.5 6.1 5.2 2.6 .. 11.6 .. 1.0 –0.8 –0.3 5.2 –8.6 1.2 .. 6.0 .. 0.3 –10.3 11.1 –8.3 –0.2 5.5 .. .. 3.3 –2.3 2.4 2.0 8.6 6.4 3.4 5.4 3.8 –13.6 –2.5 3.2 12.3 .. 2.4 7.1 1.7 2.5 5.5 2.0 .. 3.8 3.9 4.1 6.0 5.4 0.6 5.4 3.5 7.1 3.1 .. ..

3.5 8.6 4.1 6.9 .. 4.0 .. –0.5 0.2 1.7 8.4 9.6 4.8 .. 5.4 .. .. 0.8 11.9 5.2 4.4 3.6 .. .. 9.6 3.5 4.2 5.5 3.5 4.5 5.0 1.7 1.3 –1.7 6.5 4.1 9.1 .. 6.2 2.8 0.9 1.9 3.7 .. .. –0.3 .. 6.8 5.7 4.1 1.8 6.5 4.0 5.8 –0.8 .. ..

4.1

Manufacturing

average annual % growth 1990–2000 2000–09

7.7 6.7 6.7 5.1 .. .. .. 1.6 –1.8 0.5 5.6 .. 1.3 .. 7.3 .. –0.1 –7.5 11.7 –7.3 1.9 7.9 .. .. 6.6 –5.3 2.0 0.5 9.5 –1.4 5.8 5.3 4.3 –7.1 –9.7 2.6 10.2 .. 7.4 8.9 2.6 .. 5.3 2.6 .. 1.5 6.0 3.8 2.7 4.6 1.4 3.8 3.0 9.9 2.7 .. ..

5.0 8.7 4.7 9.9 .. .. .. –1.1 –1.5 2.8 9.6 6.6 4.3 .. 6.3 .. .. –1.2 –1.9 3.1 2.2 5.7 .. .. 9.0 2.9 5.1 5.0 4.3 5.1 –1.4 0.4 1.1 1.3 7.1 3.1 7.9 .. 5.6 1.0 1.2 .. 4.8 .. .. 2.6 .. 8.7 1.5 3.8 1.2 6.2 3.9 8.5 –0.6 .. ..

economy

Growth of output

Services

average annual % growth 1990–2000 2000–09

1.3 7.7 4.0 3.8 .. 8.7 .. 1.6 3.8 1.8 5.0 1.1 3.2 .. 5.6 .. 3.5 –5.2 6.6 2.7 1.5 4.5 .. .. 5.8 0.5 2.3 1.6 8.2 3.0 4.9 6.3 2.9 0.7 0.7 3.1 5.0 .. 4.2 6.2 3.6 3.6 5.0 1.9 .. 3.8 5.0 4.4 4.5 –0.6 2.5 4.0 4.0 5.1 2.5 .. ..

2011 World Development Indicators

3.4 9.5 6.2 5.3 .. 4.4 .. 1.0 1.9 1.5 6.1 8.6 4.5 .. 3.7 .. .. 7.9 7.6 7.0 4.3 3.7 .. .. 7.4 3.0 3.6 6.5 6.4 6.5 5.5 5.7 2.6 10.5 8.7 5.0 7.0 .. 5.5 4.1 2.1 3.4 3.7 .. .. 3.0 .. 5.9 7.4 3.8 4.3 6.0 6.1 3.7 1.6 .. ..

195


4.1

Growth of output Gross domestic product

average annual % growth 1990–2000 2000–09

Romania Russian Federation Rwandaa Saudi Arabiaa Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lankaa Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzaniac Thailanda Timor-Lestea Togoa Trinidad and Tobago Tunisiaa Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnama West Bank and Gaza Yemen, Rep.a Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

–0.6 –4.7 –0.2 2.1 3.0 –4.2 –5.0 7.6 2.2 2.7 .. 2.1 2.7 5.3 5.5 3.4 2.3 1.0 5.1 –10.4 3.0 4.2 .. 3.5 3.2 4.7 3.9 –4.9 7.2 –9.3 4.8 2.8 3.6 3.3 –0.2 1.6 7.9 7.3 6.0 0.5 2.3 2.9 w 3.1 3.9 6.5 2.1 3.9 8.5 –1.8 3.2 3.8 5.5 2.5 2.7 2.1

5.6 6.0 7.6 3.8 4.3 5.0 9.5 6.5 5.8 3.8 .. 4.1 2.8 5.5 7.3 2.6 2.4 1.9 4.4 8.2 7.1 4.6 2.4 2.5 7.4 4.9 4.9 13.9 7.8 5.6 7.0 2.0 2.0 3.4 6.9 4.9 7.6 –0.9 3.9 5.4 –7.5 2.9 w 5.4 6.4 8.5 4.4 6.4 9.4 5.9 3.8 4.7 7.3 5.1 2.0 1.5

Agriculture

average annual % growth 1990–2000 2000–09

–1.9 –4.9 2.5 1.6 2.4 .. .. .. 0.2 0.4 .. 1.0 3.1 1.8 7.4 0.9 –0.8 –0.9 6.0 –6.8 3.2 1.0 .. 4.0 2.7 2.3 1.3 –4.7 3.9 –5.6 13.2 –1.3 3.8 2.6 0.5 1.2 4.3 .. 5.6 4.2 4.3 1.9 w 2.9 2.4 3.1 0.9 2.4 3.4 –2.1 2.0 2.9 3.3 3.2 1.2 1.5

7.3 2.1 .. 1.4 2.0 .. .. 2.3 5.0 –0.7 .. 1.5 –0.2 2.8 2.4 1.3 3.5 0.3 3.8 7.7 4.4 2.3 .. 2.8 –7.2 2.6 1.5 14.3 2.3 3.1 3.6 0.6 2.1 2.9 6.5 3.6 3.8 .. .. 1.2 –10.8 2.5 w 3.6 3.6 3.8 3.0 3.6 4.1 3.0 3.0 4.4 3.0 3.2 0.9 0.0

Industry

average annual % growth 1990–2000 2000–09

–1.2 –7.1 –3.8 2.2 3.8 .. .. 7.8 3.7 1.6 .. 1.0 2.3 6.9 8.5 3.2 4.6 0.3 9.2 –11.4 3.1 5.7 .. 1.8 3.2 4.6 4.7 –2.7 12.0 –12.6 3.0 1.3 3.8 1.1 –3.4 1.2 11.9 .. 8.2 –4.2 0.4 2.4 w 3.4 4.5 8.7 1.3 4.5 11.0 –4.3 3.0 4.2 6.0 1.9 1.9 1.1

6.0 4.6 .. 3.6 3.3 .. .. 5.4 10.5 4.1 .. 2.9 1.3 5.5 10.2 1.7 2.8 2.1 2.4 9.2 9.5 5.6 .. 8.1 10.2 3.6 5.4 30.3 9.5 4.6 6.0 –0.6 0.9 4.0 4.7 3.3 9.6 .. .. 9.2 –5.8 2.8 w 7.4 7.2 9.6 3.9 7.2 10.2 6.2 3.2 3.6 8.2 4.9 1.1 0.7

Manufacturing

average annual % growth 1990–2000 2000–09

.. .. –5.8 5.6 3.1 .. .. .. 9.3 1.8 .. 1.6 5.2 8.1 7.5 2.8 8.9 1.0 .. –12.6 2.8 6.9 .. 1.8 4.9 5.5 4.7 .. 13.9 –11.2 11.9 .. .. –0.1 0.7 4.5 11.2 .. 5.7 0.8 0.4 .. w 3.7 6.2 9.2 3.3 6.2 10.9 .. 2.9 4.3 6.4 2.2 .. 2.4

.. .. .. 5.9 1.4 .. .. .. 10.7 3.7 .. 3.1 –0.2 4.4 4.4 1.8 3.3 2.5 14.5 8.6 8.7 6.6 .. 7.5 9.5 3.6 5.3 .. 6.7 7.8 8.1 .. 2.4 6.2 2.3 3.6 11.3 .. .. 5.0 –6.6 4.0 w 6.4 7.6 9.8 3.6 7.6 10.2 .. 2.9 6.0 8.5 3.4 2.9 0.5

Services

average annual % growth 1990–2000 2000–09

0.9 –1.7 –0.9 2.2 3.0 .. .. 7.8 5.4 3.3 .. 3.0 2.7 5.7 1.9 3.9 1.8 1.2 1.5 –10.8 2.6 3.7 .. 3.9 3.2 5.3 4.0 –5.8 8.3 –8.1 7.2 3.5 3.6 1.5 0.4 –0.1 7.5 .. 5.0 2.5 3.0 3.2 w 2.9 4.3 6.8 3.0 4.3 8.6 0.3 3.5 3.3 6.9 2.6 3.0 2.5

5.2 7.0 .. 4.2 6.3 .. .. 6.2 2.4 4.0 .. 4.1 3.5 6.2 10.1 3.9 2.2 1.8 7.7 8.3 7.8 4.2 .. –0.7 5.3 5.9 5.3 16.0 8.5 5.8 9.5 2.9 2.3 3.4 8.5 5.9 7.5 .. .. 5.6 –4.8 2.9 w 5.9 6.6 9.3 4.5 6.6 10.0 6.3 3.9 5.5 8.7 4.8 2.2 1.9

a. Components are at producer prices. b. Private analysts estimate that consumer price index inflation was considerably higher for 2007–09 and believe that GDP volume growth has been significantly higher than official reports indicate since the last quarter of 2008. c. Covers mainland Tanzania only.

196

2011 World Development Indicators


About the data

4.1

economy

Growth of output Definitions

An economy’s growth is measured by the change in

Rebasing national accounts

• Gross domestic product (GDP) at purchaser prices

the volume of its output or in the real incomes of

When countries rebase their national accounts, they

is the sum of gross value added by all resident pro-

its residents. The 1993 United Nations System of

update the weights assigned to various components

ducers in the economy plus any product taxes (less

National Accounts (1993 SNA) offers three plausible

to better reflect current patterns of production or

subsidies) not included in the valuation of output. It

indicators for calculating growth: the volume of gross

uses of output. The new base year should represent

is calculated without deducting for depreciation of

domestic product (GDP), real gross domestic income,

normal operation of the economy—it should be a

fabricated capital assets or for depletion and degra-

and real gross national income. The volume of GDP

year without major shocks or distortions. Some

dation of natural resources. Value added is the net

is the sum of value added, measured at constant

developing countries have not rebased their national

output of an industry after adding up all outputs and

prices, by households, government, and industries

accounts for many years. Using an old base year

subtracting intermediate inputs. The industrial origin

operating in the economy.

can be misleading because implicit price and vol-

of value added is determined by the International

ume weights become progressively less relevant

Standard Industrial Classification (ISIC) revision

and useful.

3. •  Agriculture is the sum of gross output less

Each industry’s contribution to growth in the economy’s output is measured by growth in the industry’s value added. In principle, value added in constant

To obtain comparable series of constant price data,

the value of intermediate input used in production

prices can be estimated by measuring the quantity

the World Bank rescales GDP and value added by

for industries classified in ISIC divisions 1–5 and

of goods and services produced in a period, valu-

industrial origin to a common reference year. This

includes forestry and fishing. • Industry is the sum

ing them at an agreed set of base year prices, and

year’s World Development Indicators continues to

of gross output less the value of intermediate input

subtracting the cost of intermediate inputs, also in

use 2000 as the reference year. Because rescaling

used in production for industries classified in ISIC

constant prices. This double-deflation method, rec-

changes the implicit weights used in forming regional

divisions 10–45, which cover mining, manufactur-

ommended by the 1993 SNA and its predecessors,

and income group aggregates, aggregate growth

ing (also reported separately), construction, electric-

requires detailed information on the structure of

rates in this year’s edition are not comparable with

ity, water, and gas. • Manufacturing is the sum of

prices of inputs and outputs.

those from earlier editions with different base years.

gross output less the value of intermediate input

In many industries, however, value added is

Rescaling may result in a discrepancy between

used in production for industries classified in ISIC

extrapolated from the base year using single volume

the rescaled GDP and the sum of the rescaled com-

divisions 15–37. • Services correspond to ISIC divi-

indexes of outputs or, less commonly, inputs. Par-

ponents. Because allocating the discrepancy would

sions 50–99. This sector is derived as a residual

ticularly in the services industries, including most of

cause distortions in the growth rates, the discrep-

(from GDP less agriculture and industry) and may not

government, value added in constant prices is often

ancy is left unallocated. As a result, the weighted

properly reflect the sum of services output, including

imputed from labor inputs, such as real wages or

average of the growth rates of the components gen-

banking and financial services. For some countries

number of employees. In the absence of well defined

erally will not equal the GDP growth rate.

it includes product taxes (minus subsidies) and may also include statistical discrepancies.

measures of output, measuring the growth of services remains difficult.

Computing growth rates

Moreover, technical progress can lead to improve-

Growth rates of GDP and its components are calcu-

ments in production processes and in the quality of

lated using the least squares method and constant

goods and services that, if not properly accounted

price data in the local currency. Constant price U.S.

for, can distort measures of value added and thus

dollar series are used to calculate regional and

of growth. When inputs are used to estimate output,

income group growth rates. Local currency series are

as for nonmarket services, unmeasured technical

converted to constant U.S. dollars using an exchange

progress leads to underestimates of the volume of

rate in the common reference year. The growth rates

output. Similarly, unmeasured improvements in qual-

in the table are average annual compound growth

ity lead to underestimates of the value of output and

rates. Methods of computing growth are described

value added. The result can be underestimates of

in Statistical methods.

growth and productivity improvement and overesti-

Data sources Data on national accounts for most developing

Changes in the System of National Accounts

countries are collected from national statistical

Informal economic activities pose a particular mea-

World Development Indicators adopted the termi-

organizations and central banks by visiting and

surement problem, especially in developing coun-

nology of the 1993 SNA in 2001. Although many

resident World Bank missions. Data for high

tries, where much economic activity is unrecorded.

countries continue to compile their national accounts

income economies are from Organisation for

A complete picture of the economy requires estimat-

according to the SNA version 3 (referred to as the

Economic Co-operation and Development (OECD)

ing household outputs produced for home use, sales

1968 SNA), more and more are adopting the 1993

data files. The United Nations Statistics Division

in informal markets, barter exchanges, and illicit or

SNA. Some low-income countries still use concepts

publishes detailed national accounts for UN mem-

deliberately unreported activities. The consistency

from the even older 1953 SNA guidelines, including

ber countries in National Accounts Statistics: Main

and completeness of such estimates depend on the

valuations such as factor cost, in describing major

Aggregates and Detailed Tables and publishes

skill and methods of the compiling statisticians.

economic aggregates. Countries that use the 1993

updates in the Monthly Bulletin of Statistics.

mates of inflation.

SNA are identified in Primary data documentation.

2011 World Development Indicators

197


4.2

Structure of output Gross domestic product

Agriculture

$ millions

Afghanistan Albania Algeria Angolaa Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benina Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile Chinaa Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep.a Costa Rica Côte d’Ivoirea Croatia Cuba Czech Republic Denmark Dominican Republica Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabona Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

198

% of GDP

1995

2009

1995

.. 2,424 41,764 5,040 258,032 1,468 371,091 238,314 3,052 37,940 13,973 284,142 2,009 6,715 1,867 4,774 768,951 13,069 2,380 1,000 3,441 8,733 590,517 1,122 1,446 71,349 728,007 144,230 92,507 5,643 2,116 11,722 11,000 22,046 30,428 55,257 181,984 16,358 20,206 60,159 9,500 578 4,353 7,606 130,700 1,569,983 4,959 382 2,694 2,522,792 6,457 131,718 14,657 3,694 254 2,695 3,911

14,483 12,015 140,577 75,493 307,155 8,714 924,843 381,084 43,019 89,360 49,037 471,161 6,656 17,340 17,042 11,823 1,594,490 48,722 8,141 1,325 10,447 22,186 1,336,068 2,006 6,839 163,669 4,985,461 210,568 234,045 10,575 9,580 29,240 23,304 63,034 62,705 190,274 309,596 46,788 57,249 188,413 21,101 1,873 19,084 28,526 237,989 2,649,390 11,062 733 10,744 3,330,032 26,169 329,924 37,322 4,103 837 6,479 14,318

.. 56 11 7 6 42 3 3 27 26 17 2 34 17 21 4 6 16 35 48 50 24 3 46 36 9 20 .. 15 57 10 14 25 7 9 5 3 10 .. 17 14 21 6 57 4 3 8 30 52 1 43 9 24 19 55 .. 22

2011 World Development Indicators

Industry

Manufacturing

% of GDP 2009

33 21 12 10 8 21 3 2 8 19 10 1 .. 14 8 3 6 6 .. .. 35 19 .. 56 14 3 10 .. 7 43 5 7 24 7 5 2 1 6 6 14 12 14 3 51 3 2 5 27 10 1 32 3 12 17 55 .. 12

Services

% of GDP

% of GDP

1995

2009

1995

2009

1995

2009

.. 23 50 66 28 32 29 31 34 25 37 28 15 33 26 51 28 28 21 19 15 31 31 21 14 35 47 15 32 17 45 30 21 32 23 38 25 36 .. 32 30 17 33 10 33 25 52 13 16 32 27 21 20 29 12 .. 31

22 20 55 59 32 35 29 29 60 29 42 22 .. 36 28 40 25 30 .. .. 23 31 .. 15 49 42 46 8 34 24 71 27 25 27 20 37 22 32 23 37 27 22 29 11 28 19 54 15 21 26 19 18 28 53 13 .. 27

.. 14 12 4 18 25 15 20 13 15 31 20 9 19 11 5 19 26 15 9 10 22 18 10 11 18 34 8 16 9 8 22 15 23 15 24 17 26 .. 17 23 9 21 5 25 .. 5 6 11 23 10 .. 14 4 8 .. 18

13 20 6 6 21 16 10 19 4 18 30 14 .. 14 13 4 16 15 .. .. 15 17 .. .. 7 13 34 2 14 5 4 19 18 16 10 23 13 24 10 16 21 6 17 4 18 11 4 5 12 19 7 10 20 5 10 .. 19

.. 22 39 26 66 26 68 67 39 49 46 70 51 50 54 45 67 56 43 33 36 45 66 33 51 55 33 85 53 26 45 57 55 61 68 57 71 54 .. 51 56 62 61 33 62 72 40 57 32 67 31 70 56 52 33 .. 48

45 60 34 31 61 45 68 69 32 53 48 78 .. 50 64 57 69 64 .. .. 42 50 .. 30 38 55 43 92 58 33 24 66 50 66 75 61 77 61 71 49 60 63 68 39 69 79 41 57 69 73 49 79 59 30 32 .. 60


Gross domestic product

Agriculture

$ millions

Hungary India Indonesiaa Iran, Islamic Rep. Iraq Ireland Israela Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait a Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysiaa Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar a Namibia Nepal Netherlands New Zealand Nicaragua Niger a Nigeria Norway Omana Pakistan Panama Papua New Guinea Paraguaya Peru Philippinesa Poland Portugal Puerto Ricoa Qatar

Industry

% of GDP

1995

2009

1995

44,656 356,299 202,132 90,829 10,114 67,061 96,065 1,126,041 5,813 5,264,380 6,727 20,374 9,046 .. 517,118 .. 27,192 1,661 1,764 5,236 11,719 814 135 25,541 7,905 4,449 3,160 1,397 88,832 2,466 1,415 4,040 286,698 1,753 1,227 32,986 2,247 .. 3,503 4,401 418,969 62,795 3,191 1,881 28,109 148,920 13,803 60,636 7,906 4,636 8,066 53,674 74,120 139,062 116,419 42,647 8,138

128,964 1,377,265 540,274 331,015 65,837 227,193 195,392 2,112,780 12,070 5,068,996 25,092 115,306 29,376 .. 832,512 5,387 148,024 4,578 5,939 26,195 34,528 1,579 876 62,360 37,206 9,221 8,590 4,727 193,093 8,996 3,024 8,589 874,810 5,405 4,202 91,375 9,790 .. 9,265 12,531 792,128 126,679 6,140 5,383 173,004 381,766 46,114 161,990 24,711 7,893 14,236 130,325 161,196 430,076 232,874 .. 98,313

7 26 17 18 9 7 .. 3 9 2 4 13 31 .. 6 .. 0 44 56 9 8 19 82 .. 11 13 27 30 13 50 37 10 6 33 41 15 35 60 12 42 3 7 23 40 .. 3 3 26 8 35 21 9 22 8 6 1 ..

Manufacturing

% of GDP 2009

4 18 16 10 .. 1 .. 2 6 1 3 6 23 .. 3 12 .. 29 35 3 5 8 61 2 4 11 29 31 10 37 21 4 4 10 24 16 31 .. 9 34 2 .. 19 .. 33 1 .. 22 6 36 19 7 15 4 2 .. ..

4.2

economy

Structure of output

Services

% of GDP

% of GDP

1995

2009

1995

2009

1995

2009

32 28 42 34 75 38 .. 30 37 34 29 31 16 .. 42 .. 55 20 19 30 25 43 5 .. 31 30 9 20 41 19 25 32 28 32 29 34 15 10 28 23 27 27 27 17 .. 34 46 24 18 34 23 31 32 35 28 44 ..

29 27 49 44 .. 31 .. 25 22 28 32 40 15 .. 37 20 .. 19 28 20 17 34 17 78 31 36 16 16 44 24 35 29 35 13 33 29 24 .. 33 16 24 .. 30 .. 41 40 .. 24 17 45 21 34 30 30 23 .. ..

24 18 24 12 1 30 .. 22 16 23 15 15 10 .. 28 .. 4 9 14 21 14 17 3 .. 19 23 8 16 26 8 8 23 21 26 12 19 8 7 13 10 17 18 19 6 .. 13 5 16 9 8 16 17 23 21 19 42 ..

22 15 27 11 .. 24 .. 16 9 20 20 11 9 .. 28 17 .. 13 9 10 9 17 13 4 18 23 14 10 25 3 4 19 17 13 5 16 14 .. 15 7 13 .. 20 .. .. 10 .. 17 6 6 13 14 20 16 13 .. ..

61 46 41 47 16 55 .. 66 54 64 67 56 53 .. 52 .. 45 37 25 61 68 38 13 .. 58 57 64 50 46 32 37 58 66 35 30 51 51 30 60 35 69 66 49 43 .. 63 51 50 74 31 56 60 46 57 66 55 ..

66 55 35 45 .. 68 .. 73 72 71 65 53 62 .. 61 68 .. 51 37 77 78 58 22 20 64 52 55 53 46 .. 45 67 61 77 44 55 45 .. 58 50 74 .. 51 .. 27 59 .. 54 77 20 59 59 55 66 75 .. ..

2011 World Development Indicators

199


4.2

Structure of output Gross domestic product

Agriculture

$ millions

Romania Russian Federation Rwandaa Saudi Arabiaa Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lankaa Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzaniab Thailanda Timor-Lestea Togoa Trinidad and Tobago Tunisiaa Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnama West Bank and Gaza Yemen, Rep.a Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

% of GDP

1995

2009

35,477 395,528 1,293 142,458 4,879 21,381 871 84,291 25,240 20,814 .. 151,113 596,751 13,030 13,830 1,699 253,680 315,940 11,397 1,232 5,255 168,019 .. 1,309 5,329 18,031 169,486 2,482 5,756 48,214 42,807 1,157,119 7,359,300 19,298 13,350 74,889 20,736 3,220 4,236 3,478 7,111 29,692,820 t 153,755 4,811,047 1,992,261 2,818,895 4,965,895 1,312,902 763,913 1,770,557 315,651 476,175 327,608 24,722,778 7,286,803

161,110 1,231,893 5,216 375,766 12,822 42,984 1,942 182,232 87,642 48,477 .. 285,366 1,460,250 41,979 54,681 3,001 406,072 491,924 52,177 4,978 21,368 263,772 558 2,855 21,204 39,561 614,603 19,947 16,043 113,545 230,252 2,174,530 14,119,000 31,511 32,104 326,133 97,180 .. 26,365 12,805 5,625 58,259,785 t 432,171 16,213,154 8,887,269 7,318,398 16,657,552 6,353,790 2,591,705 4,017,912 1,062,419 1,700,339 945,923 41,607,730 12,465,331

1995

21 7 44 6 21 .. 43 .. 6 4 .. 4 5 23 39 12 3 2 32 38 47 10 .. 38 2 11 16 17 49 15 3 2 2 9 32 6 27 .. 20 18 15 4w 37 14 21 8 15 19 14 7 16 26 18 2 3

a. Components are at producer prices. b. Covers mainland Tanzania only.

200

2011 World Development Indicators

Industry

Manufacturing

% of GDP 2009

7 5 34 3 17 13 51 .. 3 2 .. 3 3 13 30 7 2 1 21 22 29 12 .. .. 0 8 9 12 25 8 2 1 1 10 20 .. 21 .. .. 22 18 3w 26 10 13 6 10 11 8 6 11 18 13 1 2

1995

43 37 16 49 24 .. 39 35 38 35 .. 35 29 27 11 45 30 30 20 39 15 41 .. 22 47 29 33 63 14 43 52 31 26 29 28 41 29 .. 32 36 29 30 w 20 35 39 32 34 44 35 29 34 27 29 30 29

Services

% of GDP 2009

26 33 15 51 22 28 22 26 35 34 .. 31 26 30 26 49 25 27 34 24 24 43 .. .. 52 30 26 54 26 29 61 21 21 26 33 .. 40 .. .. 34 29 27 w 24 35 39 31 35 45 30 31 43 27 30 25 24

1995

29 .. 10 10 17 .. 9 27 27 26 .. 21 18 16 5 39 22 20 15 28 7 30 .. 10 9 19 23 40 7 35 10 21 19 20 12 15 15 .. 14 11 22 21 w 11 23 26 19 22 31 22 19 15 17 16 20 21

% of GDP 2009

22 15 6 10 13 .. .. 19 19 22 .. 15 13 18 7 44 16 19 13 11 10 34 .. .. 6 17 17 47 8 18 12 11 13 16 13 .. 20 .. .. 10 17 17 w 12 21 26 17 21 32 17 17 12 15 13 16 15

1995

36 56 40 45 55 .. 18 65 56 60 .. 61 66 50 51 43 66 68 48 22 38 50 .. 40 51 59 50 20 36 42 45 67 72 62 40 53 44 .. 48 46 56 65 w 43 51 40 60 51 36 51 64 50 46 53 68 68

2009

67 62 51 46 62 59 27 74 63 64 .. 66 71 58 44 43 73 72 45 54 47 45 .. .. 47 62 65 34 50 62 38 78 77 64 47 .. 39 .. .. 44 53 70 w 50 55 48 62 55 43 62 63 46 55 57 74 74


About the data

4.2

economy

Structure of output Definitions

An economy’s gross domestic product (GDP) rep-

Ideally, industrial output should be measured

• Gross domestic product (GDP) at purchaser prices

resents the sum of value added by all its produc-

through regular censuses and surveys of firms.

is the sum of gross value added by all resident pro-

ers. Value added is the value of the gross output of

But in most developing countries such surveys are

ducers in the economy plus any product taxes (less

producers less the value of intermediate goods and

infrequent, so earlier survey results must be extrapo-

subsidies) not included in the valuation of output.

services consumed in production, before accounting

lated using an appropriate indicator. The choice of

It is calculated without deducting for depreciation

for consumption of fixed capital in production. The

sampling unit, which may be the enterprise (where

of fabricated assets or for depletion and degrada-

United Nations System of National Accounts calls

responses may be based on financial records) or

tion of natural resources. Value added is the net

for value added to be valued at either basic prices

the establishment (where production units may be

output of an industry after adding up all outputs and

(excluding net taxes on products) or producer prices

recorded separately), also affects the quality of

subtracting intermediate inputs. The industrial origin

(including net taxes on products paid by producers

the data. Moreover, much industrial production is

of value added is determined by the International

but excluding sales or value added taxes). Both valu-

organized in unincorporated or owner-operated ven-

Standard Industrial Classification (ISIC) revision

ations exclude transport charges that are invoiced

tures that are not captured by surveys aimed at the

3. •  Agriculture is the sum of gross output less

separately by producers. Total GDP shown in the

formal sector. Even in large industries, where regu-

the value of intermediate input used in production

table and elsewhere in this volume is measured at

lar surveys are more likely, evasion of excise and

for industries classified in ISIC divisions 1–5 and

purchaser prices. Value added by industry is normally

other taxes and nondisclosure of income lower the

includes forestry and fishing. • Industry is the sum

measured at basic prices. When value added is mea-

estimates of value added. Such problems become

of gross output less the value of intermediate input

sured at producer prices, this is noted in Primary data

more acute as countries move from state control of

used in production for industries classified in ISIC

documentation and footnoted in the table.

industry to private enterprise, because new firms and

divisions 10–45, which cover mining, manufactur-

While GDP estimates based on the production

growing numbers of established firms fail to report.

ing (also reported separately), construction, electric-

approach are generally more reliable than estimates

In accordance with the System of National Accounts,

ity, water, and gas. • Manufacturing is the sum of

compiled from the income or expenditure side, dif-

output should include all such unreported activity

gross output less the value of intermediate input

ferent countries use different definitions, methods,

as well as the value of illegal activities and other

used in production for industries classified in ISIC

and reporting standards. World Bank staff review the

unrecorded, informal, or small-scale operations.

divisions 15–37. • Services correspond to ISIC divi-

quality of national accounts data and sometimes

Data on these activities need to be collected using

sions 50–99. This sector is derived as a residual

make adjustments to improve consistency with

techniques other than conventional surveys of firms.

(from GDP less agriculture and industry) and may not

international guidelines. Nevertheless, significant

In industries dominated by large organizations

properly reflect the sum of services output, including

discrepancies remain between international stan-

and enterprises, such as public utilities, data on

banking and financial services. For some countries

dards and actual practice. Many statistical offices,

output, employment, and wages are usually read-

it includes product taxes (minus subsidies) and may

especially those in developing countries, face severe

ily available and reasonably reliable. But in the

also include statistical discrepancies.

limitations in the resources, time, training, and bud-

services industry the many self-employed workers

gets required to produce reliable and comprehensive

and one-person businesses are sometimes difficult

series of national accounts statistics.

to locate, and they have little incentive to respond to surveys, let alone to report their full earnings.

Data problems in measuring output

Compounding these problems are the many forms

Among the difficulties faced by compilers of national

of economic activity that go unrecorded, including

accounts is the extent of unreported economic activ-

the work that women and children do for little or no

ity in the informal or secondary economy. In develop-

pay. For further discussion of the problems of using

ing countries a large share of agricultural output is

national accounts data, see Srinivasan (1994) and

either not exchanged (because it is consumed within

Heston (1994). Data sources

the household) or not exchanged for money. Dollar conversion

Data on national accounts for most developing

indirectly, using a combination of methods involv-

To produce national accounts aggregates that are

countries are collected from national statistical

ing estimates of inputs, yields, and area under cul-

measured in the same standard monetary units,

organizations and central banks by visiting and

tivation. This approach sometimes leads to crude

the value of output must be converted to a single

resident World Bank missions. Data for high

approximations that can differ from the true values

common currency. The World Bank conventionally

income economies are from Organisation for

over time and across crops for reasons other than

uses the U.S. dollar and applies the average official

Economic Co-operation and Development (OECD)

climate conditions or farming techniques. Similarly,

exchange rate reported by the International Monetary

data files. The United Nations Statistics Division

agricultural inputs that cannot easily be allocated to

Fund for the year shown. An alternative conversion

publishes detailed national accounts for UN mem-

specific outputs are frequently “netted out” using

factor is applied if the official exchange rate is judged

ber countries in National Accounts Statistics: Main

equally crude and ad hoc approximations. For further

to diverge by an exceptionally large margin from the

Aggregates and Detailed Tables and publishes

discussion of the measurement of agricultural pro-

rate effectively applied to transactions in foreign cur-

updates in the Monthly Bulletin of Statistics.

duction, see About the data for table 3.3.

rencies and traded products.

Agricultural production often must be estimated

2011 World Development Indicators

201


4.3

Structure of manufacturing Manufacturing value added

$ millions 1998 2009

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

202

.. 268 4,372 407 53,326 377 51,505 37,828 370 6,887 4,487 45,588 200 1,189 497 253 117,276 2,180 387 64 436 1,843 104,352 91 188 13,540 324,603 8,868 13,770 370 136 2,972 2,499 4,163 3,103 14,416 24,894 5,136 2,912 14,403 2,569 64 870 373 29,158 209,123 252 22 307 449,216 672 12,338 2,631 132 19 .. 826

1,632 1,995 7,315 4,586 60,116 1,213 95,726 64,124 1,927 15,472 12,638 59,032 .. 2,014 1,816 475 216,924 6,424 .. .. 1,403 3,328 172,050 .. 381 19,665 1,691,153 4,971 30,690 582 429 5,034 4,187 8,789 4,955 39,662 34,971 10,577 5,316 28,712 4,319 102 2,393 1,071 37,557 253,608 479 32 1,073 567,902 1,759 29,718 6,937 201 44 .. 2,470

2011 World Development Indicators

Food, beverages, and tobacco

Textiles and clothing

Machinery and transport equipment

Chemicals

Other manufacturinga

% of total 1998 2007

% of total 1998 2007

% of total 1998 2007

% of total 1998 2007

% of total 1998 2007

.. 20 33 .. 26 .. .. 10 .. 24 .. 13 .. 35 .. 23 20 22 .. .. 7 35 14 .. .. 32 16 12 32 .. .. 46 42 .. .. 13 19 .. 22 16 29 49 17 55 8 13 .. .. 37 8 .. 24 .. .. .. .. 42

.. 17 .. .. .. .. 19 9 18 .. .. 12 .. .. .. 22 18 16 .. .. .. .. .. .. .. 14 12 14 27 .. .. 44 .. .. .. 9 17 .. 30 .. .. 44 12 41 6 14 .. .. 34 8 .. 22 .. .. .. .. ..

.. 27 8 .. 8 .. .. 5 .. 40 .. 6 .. 5 .. 8 7 13 .. .. 87 9 4 .. .. 4 12 22 10 .. .. 8 10 .. .. 6 3 .. 3 16 28 12 15 13 2 5 .. .. 1 3 .. 12 .. .. .. .. 22

.. 22 .. .. .. .. 3 2 1 .. .. 4 .. .. .. 5 6 12 .. .. .. .. .. .. .. 2 10 12 9 .. .. 5 .. .. .. 3 2 .. 4 .. .. 19 4 9 2 3 .. .. 2 2 .. 8 .. .. .. .. ..

.. 3 .. .. 13 .. .. 24 .. 3 .. 19 .. 0 .. 15 20 18 .. .. 0 1 29 .. .. 3 15 15 5 .. .. 3 2 .. .. 23 22 .. 2 12 2 1 10 1 30 26 .. .. 12 35 .. 11 .. .. .. .. 1

.. 3 .. .. .. .. 14 28 9 .. .. 19 .. .. .. .. 21 14 .. .. .. .. .. .. .. 2 24 13 6 .. .. 3 .. .. .. 29 19 .. 3 .. .. 1 10 5 32 24 .. .. 6 36 .. 10 .. .. .. .. ..

.. 5 11 .. 15 .. .. 7 .. 11 .. 18 .. 5 .. 5 13 9 .. .. 0 6 9 .. .. 10 11 3 17 .. .. 11 12 .. .. 6 10 .. 3 21 16 6 4 7 6 12 .. .. 7 10 .. 10 .. .. .. .. 5

.. 17 .. .. .. .. 7 7 5 .. .. 23 .. .. .. .. 11 7 .. .. .. .. .. .. .. 14 11 5 13 .. .. 10 .. .. .. 6 13 .. 5 .. .. 5 4 5 6 13 .. .. 8 10 .. 6 .. .. .. .. ..

.. 46 48 .. 38 .. .. 54 .. 21 .. 44 .. 55 .. 69 40 39 .. .. 7 49 44 .. .. 52 46 49 36 .. .. 32 34 .. .. 52 46 .. 69 35 25 31 53 24 54 44 .. .. 43 44 .. 43 .. .. .. .. 30

.. 41 .. .. .. .. 58 54 66 .. .. 43 .. .. .. 73 44 50 .. .. .. .. .. .. .. 69 43 55 45 .. .. 39 .. .. .. 53 50 .. 58 .. .. 31 69 40 54 45 .. .. 50 45 .. 54 .. .. .. .. ..


Manufacturing value added

$ millions 1998 2009

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

9,959 59,562 23,857 13,607 91 26,279 .. 236,315 914 868,624 1,047 2,659 1,540 .. 85,569 .. 1,037 233 216 965 2,144 140 17 .. 1,807 645 399 216 20,774 101 100 877 82,015 238 46 6,136 422 .. 369 436 58,120 8,495 538 128 .. 16,863 654 9,131 1,135 351 1,239 8,080 14,254 30,022 19,959 22,994 ..

28,619 190,333 142,532 29,832 .. 48,709 .. 306,459 973 970,204 4,416 12,536 2,801 .. 208,142 773 .. 570 478 2,278 2,645 243 105 3,879 7,562 1,816 1,115 447 49,213 195 115 1,483 144,431 568 176 12,909 1,219 .. 1,247 807 89,029 17,968 1,086 .. .. 32,575 .. 26,290 1,490 464 1,850 16,897 32,889 61,948 26,690 .. ..

4.3

economy

Structure of manufacturing Food, beverages, and tobacco

Textiles and clothing

Machinery and transport equipment

Chemicals

Other manufacturinga

% of total 1998 2007

% of total 1998 2007

% of total 1998 2007

% of total 1998 2007

% of total 1998 2007

15 13 21 13 31 17 12 9 48 11 27 .. 46 .. 9 .. 8 .. 46 26 26 .. .. .. 27 31 31 44 10 .. .. 22 24 .. 53 34 .. .. .. 35 18 30 .. .. 30 16 17 23 52 .. .. 26 35 25 12 10 4

11 9 26 10 .. 18 10 9 .. 11 23 .. 30 .. 6 .. .. .. .. 20 .. .. .. .. 23 18 0 .. 9 .. .. 31 25 39 38 30 .. .. .. .. 18 27 .. .. .. 20 8 22 .. .. .. 30 24 16 14 9 1

7 12 18 8 15 2 6 13 7 4 6 .. 8 .. 9 .. 5 .. 22 11 10 .. .. .. 18 21 33 8 4 .. .. 51 4 .. 33 18 .. .. .. 34 2 .. .. .. 11 2 7 26 7 .. .. 10 7 7 20 4 8

3 9 13 4 .. 0 3 10 .. 2 10 .. 4 .. 5 .. .. .. .. 7 .. .. .. .. 9 17 30 .. 2 .. .. 31 3 15 17 13 .. .. .. .. 2 2 .. .. .. 1 0 29 .. .. .. 12 6 4 12 1 2

27 15 14 16 2 16 24 23 .. 33 4 .. 4 .. 35 .. 2 .. 8 8 3 .. .. .. 12 9 .. 5 8 .. .. 1 23 .. 0 4 .. .. .. 0 15 .. .. .. 7 23 2 5 .. .. .. 4 21 16 15 5 0

31 19 18 24 .. 16 22 23 .. 37 3 .. 2 .. 46 .. .. .. .. 10 .. .. .. .. 10 4 1 .. 30 .. .. 1 18 4 1 5 .. .. .. .. 19 13 .. .. .. 25 1 8 .. .. .. 2 25 20 11 9 0

11 24 13 13 23 38 12 8 19 10 21 .. 8 .. 11 .. 3 .. 3 3 6 .. .. .. 3 8 6 16 11 .. .. 4 15 .. 2 15 .. .. .. 6 13 .. .. .. 26 8 7 16 7 .. .. 10 10 7 6 62 21

10 16 11 13 .. 33 20 7 .. 11 17 .. 4 .. 8 .. .. .. .. 4 .. .. .. .. 9 6 2 .. 15 .. .. .. 19 .. 3 16 .. .. .. .. 14 .. .. .. .. 9 12 14 .. .. .. 12 8 8 6 62 17

40 37 33 49 29 28 46 47 27 42 42 .. 34 .. 36 .. 83 .. 22 52 55 .. .. .. 40 31 30 28 67 .. .. 26 32 .. 12 28 .. .. .. 26 51 70 .. .. 26 51 67 30 34 .. .. 51 28 45 46 20 67

2011 World Development Indicators

44 47 32 50 .. 33 44 51 .. 39 48 .. 62 .. 35 .. .. .. .. 60 .. .. .. .. 48 55 67 .. 44 .. .. 37 35 42 41 35 .. .. .. .. 47 58 .. .. .. 45 79 26 .. .. .. 44 38 52 63 20 80

203


4.3

Structure of manufacturing Manufacturing value added

$ millions 1998 2009

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania b Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

9,601 .. 223 15,492 723 .. 26 18,839 6,036 4,860 .. 23,678 103,971 2,343 957 519 48,915 51,047 1,286 255 919 34,534 9 110 552 3,660 64,408 452 545 10,578 6,532 251,809 1,440,500 3,598 1,346 17,380 4,666 .. 638 372 923 5,516,751 t 20,369 1,085,340 535,090 563,006 1,105,587 425,997 .. 334,974 49,450 78,797 43,316 4,411,013 1,250,663

31,753 161,878 335 39,128 1,490 .. .. 33,499 15,375 10,566 .. 39,014 172,433 7,618 3,515 1,114 56,948 88,054 6,686 479 1,844 89,881 .. .. 1,334 6,527 92,715 9,158 1,190 17,992 24,643 217,594 1,779,474 4,377 3,979 .. 18,099 .. .. 1,192 826 9,102,310 t 44,786 3,432,566 2,342,311 1,036,562 3,479,229 2,036,104 .. 570,166 117,926 241,774 83,017 5,603,504 1,686,936

a. Includes unallocated data. b. Covers mainland Tanzania only.

204

2011 World Development Indicators

Food, beverages, and tobacco

Textiles and clothing

Machinery and transport equipment

Chemicals

Other manufacturinga

% of total 1998 2007

% of total 1998 2007

% of total 1998 2007

% of total 1998 2007

% of total 1998 2007

29 22 75 .. 44 .. .. 4 12 10 .. 18 15 39 .. .. 8 10 .. .. 45 25 .. .. 30 17 15 .. 65 .. .. 13 13 36 .. 22 30 15 45 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

15 15 .. 19 .. .. .. 2 7 7 .. 17 15 29 .. .. 7 .. .. .. 62 16 .. .. 11 .. 12 .. .. .. .. 16 14 42 .. .. .. 27 60 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

11 3 2 .. 3 .. .. 1 7 10 .. 6 7 30 .. .. 1 3 .. .. 0 12 .. .. 1 36 18 .. 5 .. .. 5 4 9 .. 2 22 23 5 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

12 2 .. 5 .. .. .. 1 3 6 .. 3 4 29 .. .. 1 .. .. .. 8 9 .. .. 1 .. 19 .. .. .. .. 3 2 7 .. .. .. 13 9 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

14 18 .. .. 0 .. .. 52 21 17 .. 14 20 4 .. .. 37 15 .. .. 2 27 .. .. 1 3 14 .. .. .. .. 26 30 3 .. 9 11 2 0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

17 10 .. 6 .. .. .. 45 27 20 .. 14 17 0 .. .. 34 .. .. .. 1 35 .. .. 0 .. 20 .. .. .. .. 23 25 4 .. .. .. 1 0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

5 9 6 .. 29 .. .. 13 9 11 .. 11 10 7 .. .. 9 .. .. .. 7 4 .. .. 26 11 8 .. 10 .. .. 10 12 8 .. 34 7 5 2 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

5 8 .. 27 .. .. .. 32 4 14 .. 7 8 14 .. .. 13 .. .. .. 2 6 .. .. 39 .. 7 .. .. .. .. 11 15 8 .. .. .. 4 4 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

40 48 17 .. 24 .. .. 30 52 51 .. 51 47 21 .. .. 46 71 .. .. 46 32 .. .. 42 33 45 .. 20 .. .. 46 41 44 .. 41 30 55 48 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

51 65 .. 43 .. .. .. 20 59 53 .. 58 55 27 .. .. 46 .. .. .. 29 34 .. .. 49 .. 42 .. .. .. .. 47 44 39 .. .. .. 55 27 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..


About the data

4.3

economy

Structure of manufacturing Definitions

The data on the distribution of manufacturing value

revision 3. Concordances matching ISIC categories

• Manufacturing value added is the sum of gross

added by industry are provided by the United Nations

to national classification systems and to related

output less the value of intermediate inputs used

Industrial Development Organization (UNIDO). UNIDO

systems such as the Standard International Trade

in production for industries classified in ISIC major

obtains the data from a variety of national and inter-

Classification are available.

division D. • Food, beverages, and tobacco cor-

national sources, including the United Nations Sta-

In establishing classifications systems compil-

respond to ISIC divisions 15 and 16. • Textiles

tistics Division, the World Bank, the Organisation for

ers must define both the types of activities to be

and clothing correspond to ISIC divisions 17–19.

Economic Co-operation and Development, and the

described and the units whose activities are to

• Machinery and transport equipment correspond to

International Monetary Fund. To improve comparabil-

be reported. There are many possibilities, and the

ISIC divisions 29, 30, 32, 34, and 35. • Chemicals

ity over time and across countries, UNIDO supple-

choices affect how the statistics can be interpreted

correspond to ISIC division 24. • Other manufactur-

ments these data with information from industrial

and how useful they are in analyzing economic

ing is calculated as a residual. It covers wood and

censuses, statistics from national and international

behavior. The ISIC emphasizes commonalities in the

related products (ISIC division 20), paper and related

organizations, unpublished data that it collects in the

production process and is explicitly not intended to

products (ISIC divisions 21 and 22), petroleum and

field, and estimates by the UNIDO Secretariat. Nev-

measure outputs (for which there is a newly devel-

related products (ISIC division 23), basic metals and

ertheless, coverage may be incomplete, particularly

oped Central Product Classification). Nevertheless,

mineral products (ISIC division 27), fabricated metal

for the informal sector. When direct information on

the ISIC views an activity as defined by “a process

products and professional goods (ISIC division 28),

inputs and outputs is not available, estimates may

resulting in a homogeneous set of products” (United

and other industries (ISIC divisions 25, 26, 31, 33,

be used, which may result in errors in industry totals.

Nations 1990 [ISIC, series M, no. 4, rev. 3], p. 9).

36, and 37).

Moreover, countries use different reference periods

Firms typically use multiple processes to produce

(calendar or fiscal year) and valuation methods (basic

a product. For example, an automobile manufac-

or producer prices) to estimate value added. (See

turer engages in forging, welding, and painting as

About the data for table 4.2.)

well as advertising, accounting, and other service

The data on manufacturing value added in U.S. dol-

activities. Collecting data at such a detailed level

lars are from the World Bank’s national accounts files

is not practical, nor is it useful to record produc-

and may differ from those UNIDO uses to calculate

tion data at the highest level of a large, multiplant,

shares of value added by industry, in part because

multiproduct firm. The ISIC has therefore adopted as

of differences in exchange rates. Thus value added

the definition of an establishment “an enterprise or

in a particular industry estimated by applying the

part of an enterprise which independently engages in

shares to total manufacturing value added will not

one, or predominantly one, kind of economic activity

match those from UNIDO sources. Classification of

at or from one location . . . for which data are avail-

manufacturing industries in the table accords with

able . . .” (United Nations 1990, p. 25). By design,

the United Nations International Standard Industrial

this definition matches the reporting unit required

Classification (ISIC) revision  3. Editions of World

for the production accounts of the United Nations

Development Indicators prior to 2008 used revision

System of National Accounts. The ISIC system is

2, first published in 1948. Revision 3 was completed

described in the United Nations’ International Stan-

in 1989, and many countries now use it. But revi-

dard Industrial Classification of All Economic Activi-

sion 2 is still widely used for compiling cross-country

ties, Third Revision (1990). The discussion of the ISIC

data. UNIDO has converted these data to accord with

draws on Ryten (1998).

4.3a

Manufacturing continues to show strong growth in East Asia and Pacific through 2009 Value added in manufacturing (index, 1990 = 100) 600 East Asia & Pacific 500 400

South Asia

300 Latin America & Caribbean

Middle East & North Africa

Data sources

200

Data on manufacturing value added are from

100 Sub-Saharan Africa 0

1990

1995

2000

2005

2009

the World Bank’s National Accounts files. Data used to calculate shares of industry value added are provided to the World Bank in electronic files

Manufacturing continues to be the dominant sector in East Asia and Pacific, growing an average of about

by UNIDO. The most recent published source is

10.5 percent a year between 1990 and 2009.

UNIDO’s International Yearbook of Industrial Sta-

Source: World Development Indicators data files.

tistics 2010.

2011 World Development Indicators

205


4.4 Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China† Hong Kong SAR, Chinab Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras †Data for Taiwan, China

206

Structure of merchandise exports Merchandise exports

Food

Agricultural raw materials

Fuels

Ores and metals

Manufactures

$ millions 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

166 202 10,258 3,642 20,967 271 53,111 57,738 635 3,501 4,803 178,265a 420 1,100 152 2,142 46,506 5,355 276 105 855 1,651 192,197 171 243 16,024 148,780 173,871 10,056 1,563 1,172 3,453 3,806 4,517 1,600 21,335 50,906 3,780 4,307 3,450 1,652 86 1,840 422 40,490 301,162 2,713 16 151 523,461 1,724 11,054 2,155 702 24 110 1,769 113,047

560 1,088 45,194 40,080 55,668 698 154,234 137,672 21,097 15,084 21,283 369,854 1,000 4,848 3,929 3,458 152,995 16,455 850 64 4,200 3,000 316,713 120 2,800 53,735 1,201,534 329,422 32,853 3,100 5,600 8,788 8,900 10,474 3,109 113,437 93,344 5,463 13,799 23,062 3,797 15 9,031 1,596 62,798 484,725 5,100 15 1,135 1,126,383 5,500 20,093 7,214 1,010 115 576 5,196 203,675

2011 World Development Indicators

.. 11 1 .. 50 11 22 4 4 10 .. 10a 14 21 .. .. 29 18 25 91 .. 27 8 4 .. 24 8 3 31 .. 1 63 63 11 .. 6 24 19 53 10 57 .. 16 73 2 14 0 60 29 5 58 30 65 8 89 37 87 3

55 6 0 .. 50 20 14 7 4 7 11 10 .. 20 8 5 34 17 27 67 1 .. 11 .. .. 21 3 7 16 .. .. 25 48 13 .. 5 19 25 36 11 23 .. 10 77 2 12 .. 53 18 6 63 25 44 2 .. .. 54 1

.. 9 0 .. 4 5 8 3 8 3 .. 1a 75 10 .. .. 5 3 69 4 .. 28 9 20 .. 12 2 0 5 .. 8 5 20 5 .. 4 3 0 3 6 1 .. 10 13 8 1 13 1 3 1 15 4 4 1 11 0 3 2

8 3 0 .. 1 1 2 2 0 3 2 1 .. 1 6 0 4 1 60 5 1 .. 4 .. .. 5 0 2 4 .. .. 2 6 4 .. 1 2 1 4 2 1 .. 4 12 4 1 .. 1 2 1 9 3 3 5 .. .. 1 1

.. 3 95 .. 10 1 19 1 66 0 .. 3a 5 15 .. .. 1 7 0 0 .. 29 9 1 .. 0 4 0 28 .. 88 1 10 9 .. 4 3 0 36 37 0 .. 6 3 2 2 83 0 19 1 5 7 2 0 0 0 0 1

.. 12 98 .. 10 0 32 3 93 2 37 7 .. 40 13 0 9 13 0 2 0 .. 25 .. .. 1 2 4 51 .. .. 1 30 13 .. 4 8 0 50 44 3 .. 16 0 7 4 .. 0 3 2 2 9 4 2 .. .. 4 6

.. 12 1 .. 2 26 18 3 1 0 .. 4a 0 35 .. .. 10 10 0 1 .. 8 7 30 .. 48 2 1 1 .. 0 1 0 2 .. 3 1 0 0 6 3 .. 3 0 3 3 2 1 8 3 9 7 0 67 0 0 0 1

0 10 0 .. 4 47 27 3 0 0 1 3 .. 33 9 16 12 15 1 5 3 .. 7 .. .. 58 1 6 2 .. .. 1 0 4 .. 2 1 3 0 6 1 .. 2 1 4 2 .. 7 22 2 6 7 5 59 .. .. 4 2

.. 65 4 .. 34 54 30 88 20 85 .. 77a 6 19 .. .. 54 60 6 3 .. 8 63 45 .. 13 84 94 35 .. 3 25 7 74 .. 82 60 78 8 40 39 .. 65 11 83 79 2 36 41 87 13 50 28 24 0 62 9 93

18 70 2 .. 33 33 19 81 3 88 48 77 .. 6 61 78 39 53 12 21 96 .. 50 .. .. 11 94 79 28 .. .. 47 15 66 .. 87 65 70 9 37 72 .. 62 9 77 79 .. 39 55 82 19 54 43 32 .. .. 35 89


Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

4.4

economy

Structure of merchandise exports Merchandise exports

Food

Agricultural raw materials

Fuels

Ores and metals

Manufactures

$ millions 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

12,865 30,630 45,417 18,360 496 44,705 19,046 233,766 1,427 443,116 1,769 5,250 1,878 959 125,058 .. 12,785 409 311 1,305 816 160 820 8,975 2,705 1,204 507 405 73,914 441 488 1,538 79,542 745 473 6,881 168 860 1,409 345 203,171 13,645 466 288 12,342 41,992 6,068 8,029 625 2,654 919 5,575 17,502 22,895 22,783 .. 3,651

83,778 162,613 119,481 78,113 39,500 114,587 47,935 405,777 1,316 580,719 6,366 43,196 4,421 1,550 363,534 .. 50,328 1,439 940 7,688 4,187 750 150 35,600 16,452 2,692 1,140 920 157,433 2,100 1,370 1,942 229,637 1,288 1,903 13,863 2,147 6,710 3,553 813 498,330 24,932 1,391 900 52,500 120,880 27,651 17,680 948 4,328 3,167 26,885 38,436 134,466 43,358 .. 40,500

21 19 11 4 .. 19 5 7 22 0 25 10 56 .. 2 .. 0 23 .. 14 20 .. .. 0 18 18 69 90 10 23 57 29 8 72 2 31 66 .. .. 8 20 45 75 17 2 8 5 12 75 13 44 31 13 10 7 .. 0

8 8 17 .. 0 9 3 8 27 1 17 4 44 .. 1 .. 0 24 .. 17 16 .. .. .. 19 18 29 87 11 28 12 32 7 74 2 22 23 .. 23 25 15 56 87 18 5 6 3 17 84 .. 85 23 8 11 11 .. 0

2 1 7 1 .. 1 2 1 0 1 2 3 7 .. 1 .. 0 13 .. 23 2 .. .. 0 8 5 6 2 6 75 0 1 1 2 28 3 16 .. .. 1 4 19 3 1 2 2 0 4 0 20 36 3 1 3 5 .. 0

1 1 5 .. 0 0 1 1 0 1 0 0 13 .. 1 .. 0 4 .. 10 1 .. .. .. 2 1 5 4 2 42 0 1 0 1 12 2 3 .. 0 3 3 10 1 4 1 0 0 2 1 .. 4 1 1 1 2 .. 0

3 2 25 86 .. 0 0 1 1 1 0 25 6 .. 2 .. 95 11 .. 2 0 .. .. 95 11 0 1 0 7 0 1 0 10 1 0 2 2 .. .. 0 7 2 1 0 96 47 79 1 3 38 0 5 2 8 3 .. 82

2 13 28 .. 99 1 0 4 17 2 1 71 4 .. 6 .. 93 6 .. 5 0 .. .. .. 21 1 5 0 15 6 22 0 14 0 10 2 17 .. 0 0 8 5 1 2 90 65 79 4 1 .. 0 10 2 3 5 .. 94

5 3 6 1 .. 1 1 1 6 1 24 24 3 .. 1 .. 0 13 .. 1 8 .. .. 0 5 18 7 0 1 0 42 0 3 3 60 12 2 .. .. 0 3 5 1 80 0 9 2 0 1 25 0 46 4 7 2 .. 0

1 6 9 .. 0 1 1 2 8 3 9 11 2 .. 2 .. 0 3 .. 3 8 .. .. .. 1 3 3 1 2 1 60 1 3 2 70 9 4 .. 31 5 2 3 1 69 0 5 4 1 4 .. 1 49 4 4 3 .. 0

68 74 51 9 .. 72 89 89 71 95 49 38 28 .. 93 .. 5 40 .. 58 70 .. .. 5 58 58 14 7 75 2 0 70 78 23 10 51 13 .. .. 84 63 29 21 1 1 27 14 83 20 4 19 15 42 71 83 .. 17

2011 World Development Indicators

82 67 41 .. 0 86 94 83 47 88 73 14 37 .. 90 .. 6 34 .. 61 72 .. .. .. 55 51 57 9 70 22 0 65 76 23 6 65 12 .. 45 67 56 23 10 7 4 20 10 76 10 .. 11 16 86 80 72 .. 5

207


4.4 Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singaporeb Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

Structure of merchandise exports Merchandise exports

Food

Agricultural raw materials

Fuels

Ores and metals

Manufactures

$ millions 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

7,910 40,633 81,095 303,388 54 193 50,040 192,296 993 2,180 .. 8,345 42 231 118,268 269,832 8,580 55,980 8,316 26,369 .. .. 62,603 27,853c 97,849 218,511 3,798 7,345 555 7,834 866 1,500 80,440 131,243 81,641 172,850 3,563 10,400 750 1,009 682 3,096 56,439 152,498 .. .. 378 800 2,455 9,126 5,475 14,445 21,637 102,129 1,880 6,595 460 2,478 13,128 39,703 28,364 175,000 237,953 352,491 584,743 1,056,043 2,106 5,386 3,430 10,735 18,457 57,595 5,449 57,096 .. .. 1,945 5,594 1,040 4,312 2,118 2,269 5,172,552 t 12,492,190 t 24,093 76,170 894,340 3,720,635 400,844 2,099,993 493,582 1,619,211 918,419 3,796,791 354,784 1,747,540 154,880 650,244 223,980 677,205 62,002 276,399 46,657 204,760 76,554 242,566 4,253,742 8,697,557 1,744,036 3,597,614

7 2 57 1 9 28 .. 4 6 4 .. 8c 15 21 44 .. 2 3 12 .. 65 19 .. 19 8 10 20 1 90 19 8 8 11 44 .. 3 30 .. 3 3 43 9w 31 14 14 15 15 11 8 20 6 17 18 8 11

7 3 42 1 30 19 .. 2 5 4 .. 10 16 26 6 21 5 4 22 .. 35 15 .. 16 3 9 11 .. 63 24 1 7 10 64 .. 0 20 .. 6 8 19 8w 25 11 9 12 11 8 8 18 .. 11 14 8 10

3 3 16 0 7 4 .. 1 4 2 .. 4c 2 4 47 .. 6 1 7 .. 23 5 .. 42 0 1 1 13 5 1 0 1 4 15 .. 0 3 .. 1 1 7 3w 10 3 3 4 3 4 3 3 1 2 7 2 2

2 2 2 0 1 2 .. 0 1 2 .. 2 1 3 1 7 4 0 1 .. 10 4 .. 9 0 0 0 .. 6 1 0 1 2 8 .. 0 3 .. 0 1 23 2w 8 2 2 2 2 2 2 2 .. 1 3 1 1

8 43 0 88 22 2 .. 7 4 1 .. 9c 2 0 0 .. 2 0 63 .. 0 1 .. 0 48 8 1 77 0 4 9 6 2 1 .. 77 18 .. 95 3 1 7w 2 12 8 15 11 6 29 15 73 1 36 6 2

6 67 0 88 24 3 .. 15 5 4 .. 11 4 0 92 1 6 3 39 .. 1 5 .. 0 79 14 4 .. 1 5 65 11 6 1 .. 96 20 .. 92 1 1 12 w 3 22 14 29 22 8 45 20 .. 11 37 9 4

3 10 12 1 12 15 .. 2 4 3 .. 8c 2 1 0 .. 3 3 1 .. 0 1 .. 32 0 2 3 1 1 7 55 3 3 1 .. 6 0 .. 1 87 12 3w 11 5 3 6 5 2 9 7 3 3 8 3 3

Note: Components may not sum to 100 percent because of unclassified trade. Exports of gold are excluded. a. Includes Luxembourg. b. Includes re-exports. c. Refers to the South African Customs Union (Botswana, Lesotho, Namibia, South Africa, and Swaziland).

208

2011 World Development Indicators

4 6 32 0 3 10 .. 1 2 3 .. 29 3 1 0 1 4 3 4 .. 25 1 .. 13 2 1 3 .. 2 6 1 3 4 0 .. 1 1 .. 0 81 22 4w 14 5 3 7 5 2 5 8 .. 5 15 3 2

78 26 14 10 48 49 .. 84 82 90 .. 44 c 78 73 6 .. 79 94 17 .. 10 73 .. 7 43 79 74 8 4 68 28 81 77 39 .. 14 44 .. 1 7 37 76 w 44 63 69 58 63 74 42 55 17 76 28 78 80

79 17 19 8 41 66 .. 74 87 87 .. 47 73 67 0 70 76 90 33 .. 25 75 .. 62 15 75 80 .. 27 63 4 72 67 26 .. 3 55 .. 2 8 34 70 w 50 59 71 48 59 80 37 51 .. 68 31 73 77


About the data

4.4

economy

Structure of merchandise exports Definitions

Data on merchandise trade are from customs

b and c are classified as re-exports. Because of dif-

• Merchandise exports are the f.o.b. value of goods

reports of goods moving into or out of an economy

ferences in reporting practices, data on exports may

provided to the rest of the world. • Food corresponds

or from reports of financial transactions related to

not be fully comparable across economies.

to the commodities in SITC sections 0 (food and live

merchandise trade recorded in the balance of pay-

The data on total exports of goods (merchandise)

animals), 1 (beverages and tobacco), and 4 (animal

ments. Because of differences in timing and defi-

are from the World Trade Organization (WTO), which

and vegetable oils and fats) and SITC division 22

nitions, trade flow estimates from customs reports

obtains data from national statistical offices and the

(oil seeds, oil nuts, and oil kernels). • Agricultural

and balance of payments may differ. Several inter-

IMF’s International Financial Statistics, supplemented

raw materials correspond to SITC section 2 (crude

national agencies process trade data, each correct-

by the Comtrade database and publications or data-

materials except fuels), excluding divisions 22, 27

ing unreported or misreported data, leading to other

bases of regional organizations, specialized agen-

(crude fertilizers and minerals excluding coal, petro-

differences.

cies, economic groups, and private sources (such as

leum, and precious stones), and 28 (metalliferous

The most detailed source of data on international

Eurostat, the Food and Agriculture Organization, and

ores and scrap). • Fuels correspond to SITC section

trade in goods is the United Nations Statistics Divi-

country reports of the Economist Intelligence Unit).

3 (mineral fuels). • Ores and metals correspond to

sion’s Commodity Trade (Comtrade) database. The

Country websites and email contact have improved

the commodities in SITC divisions 27, 28, and 68

International Monetary Fund (IMF) also collects

collection of up-to-date statistics, reducing the pro-

(nonferrous metals). • Manufactures correspond to

customs-based data on trade in goods. Exports are

portion of estimates. The WTO database now covers

the commodities in SITC sections 5 (chemicals), 6

recorded as the cost of the goods delivered to the

most major traders in Africa, Asia, and Latin America,

(basic manufactures), 7 (machinery and transport

frontier of the exporting country for shipment—the

which together with high-income countries account

equipment), and 8 (miscellaneous manufactured

free on board (f.o.b.) value. Many countries report

for nearly 95 percent of world trade. Reliability of

goods), excluding division 68.

trade data in U.S. dollars. When countries report in

data for countries in Europe and Central Asia has

local currency, the United Nations Statistics Division

also improved.

applies the average official exchange rate to the U.S. dollar for the period shown.

Export shares by major commodity group are from Comtrade. The values of total exports reported

Countries may report trade according to the gen-

here have not been fully reconciled with the esti-

eral or special system of trade. Under the general

mates from the national accounts or the balance

system exports comprise outward-moving goods that

of payments.

are (a) goods wholly or partly produced in the country;

The classification of commodity groups is based

(b) foreign goods, neither transformed nor declared

on the Standard International Trade Classification

for domestic consumption in the country, that move

(SITC) revision 3. Previous editions contained data

outward from customs storage; and (c) goods previ-

based on the SITC revision 1. Data for earlier years in

ously included as imports for domestic consumption

previous editions may differ because of this change

but subsequently exported without transformation.

in methodology. Concordance tables are available

Under the special system exports comprise cat-

to convert data reported in one system to another.

egories a and c. In some compilations categories Developing economies’ share of world merchandise exports continues to expand 1995 ($5.2 trillion)

High income 82% East Asia & Pacific 7% Europe & Central Asia 3% Latin America & Caribbean 4% Middle East & N. Africa 1% South Asia 1% Sub-Saharan Africa 2%

4.4a

2009 ($12.5 trillion)

Data sources Data on merchandise exports are from the WTO. Data on shares of exports by major commodity group are from Comtrade. The WTO publishes data

High income 70%

East Asia & Pacific 14%

on world trade in its Annual Report. The IMF publishes estimates of total exports of goods in its International Financial Statistics and Direction of

Europe & Central Asia 5% Latin America & Caribbean 5% Middle East & N. Africa 2% South Asia 2% Sub-Saharan Africa 2%

Developing economies’ share of world merchandise exports increased 12 percentage points from 1995 to 2009. East Asia and the Pacific was the biggest gainer, capturing an additional 7 percentage points. All other developing country regions also increased their share in world trade. Source: World Development Indicators data files and World Trade Organization.

Trade Statistics, as does the United Nations Statistics Division in its Monthly Bulletin of Statistics. And the United Nations Conference on Trade and Development publishes data on the structure of exports in its Handbook of Statistics. Tariff line records of exports are compiled in the United Nations Statistics Division’s Comtrade database.

2011 World Development Indicators

209


4.5

Structure of merchandise imports Merchandise imports

$ millions 1995 2009

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China† Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras †Data for Taiwan, China

210

387 714 10,100 1,468 20,122 674 61,283 66,237 668 6,694 5,564 164,934 a 746 1,424 1,082 1,911 54,137 5,660 455 234 1,187 1,199 168,426 175 365 15,900 132,084 196,072 13,853 871 670 4,036 2,931 7,352 2,825 25,085 45,939 5,170 4,152 11,760 3,329 454 2,546 1,145 29,470 289,391 882 182 392 463,872 1,906 25,898 3,292 819 133 653 1,879 103,558

3,970 4,548 39,294 17,000 38,780 3,304 165,471 143,382 6,514 21,833 28,563 351,945 2,040 4,410 8,773 4,728 133,669 23,330 2,083 402 6,200 4,250 329,904 300 1,950 42,427 1,005,688 352,241 32,898 3,600 2,900 11,395 6,050 21,203 9,623 105,179 82,947 12,283 15,093 44,946 7,255 540 10,122 7,963 60,753 559,817 2,200 304 4,378 938,295 8,140 59,858 11,531 1,400 230 2,050 7,788 174,371

2011 World Development Indicators

Food

Agricultural raw materials

Fuels

Ores and metals

Manufactures

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

.. 34 29 .. 5 31 5 6 39 17 .. 11a 27 10 .. .. 11 8 21 21 .. 17 6 16 24 7 7 5 9 .. 21 10 21 12 .. 7 12 .. 8 28 15 .. 14 14 6 11 19 36 36 10 8 16 12 31 44 .. 13 6

18 17 16 .. 4 19 6 8 16 22 8 9 .. 9 19 13 5 10 16 13 7 .. 8 .. .. 7 5 4 10 .. .. 7 23 10 .. 6 13 14 9 17 19 .. 12 11 7 9 .. 34 15 8 15 13 14 13 .. .. 19 5

.. 1 3 .. 2 0 2 3 1 3 .. 2a 3 2 .. .. 3 3 2 2 .. 3 2 10 1 2 5 2 3 .. 1 1 1 2 .. 3 3 .. 3 7 2 .. 3 2 4 3 1 1 0 3 1 2 2 1 0 .. 1 4

0 1 1 .. 1 1 1 2 1 8 1 1 .. 1 1 1 1 1 1 1 1 .. 1 .. .. 1 3 1 1 .. .. 1 1 1 .. 1 2 1 1 3 2 .. 2 1 2 1 .. 1 1 1 1 1 1 0 .. .. 1 1

.. 2 1 .. 4 27 5 4 4 8 .. 6a 9 5 .. .. 12 34 14 11 .. 3 4 9 18 9 4 2 3 .. 20 9 19 12 .. 8 3 .. 6 1 9 .. 11 11 9 7 4 14 39 6 6 7 12 19 16 .. 12 7

24 12 1 .. 6 16 13 11 1 11 40 12 .. 11 15 13 15 20 24 2 8 .. 10 .. .. 21 13 3 4 .. .. 9 25 17 .. 9 6 21 12 11 15 .. 19 16 15 13 .. 16 18 11 14 15 19 33 .. .. 19 21

.. 1 2 .. 2 0 1 4 2 2 .. 5a 1 3 .. .. 3 4 1 1 .. 2 3 2 1 2 4 2 2 .. 1 2 1 3 .. 4 2 .. 2 3 2 .. 1 1 6 4 1 0 0 4 0 3 1 1 0 .. 1 6

0 2 1 .. 2 4 1 4 1 3 3 3 .. 1 2 2 3 7 1 1 2 .. 2 .. .. 2 14 2 2 .. .. 1 1 2 .. 3 2 1 1 8 1 .. 1 1 5 2 .. 1 2 3 1 2 1 0 .. .. 1 7

.. 61 65 .. 86 39 86 82 53 69 .. 71a 59 82 .. .. 71 48 62 64 .. 76 83 64 56 79 79 88 78 .. 58 78 57 67 .. 77 73 .. 82 61 72 .. 71 72 74 76 75 46 24 73 77 71 73 47 40 .. 74 75

17 68 80 .. 86 59 76 75 79 54 45 73 .. 78 62 70 76 59 59 81 82 .. 77 .. .. 59 64 89 82 .. .. 60 49 70 .. 78 74 63 76 60 63 .. 60 72 64 74 .. 48 64 67 69 69 64 53 .. .. 60 65


Merchandise imports

$ millions 1995 2009

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

15,465 34,707 40,630 13,882 665 32,340 29,578 205,990 2,818 335,882 3,697 3,807 2,991 1,380 135,119 .. 7,790 522 589 1,815 7,278 1,107 510 5,392 3,650 1,719 628 475 77,691 772 431 1,976 74,427 840 415 10,023 704 1,348 1,616 1,333 185,232 13,957 975 374 8,222 32,968 4,379 11,515 2,510 1,452 3,144 7,584 28,341 29,050 32,610 .. 3,398

78,175 249,590 91,749 50,375 37,000 62,507 49,278 412,721 5,064 551,960 14,075 28,409 10,207 2,080 323,085 .. 17,920 3,037 1,260 9,765 16,574 1,950 552 10,150 18,234 5,043 3,250 1,700 123,832 2,644 1,430 3,728 241,515 3,278 2,131 32,892 3,764 4,316 5,120 4,392 445,496 25,545 3,477 1,500 39,000 69,292 18,020 31,710 7,801 3,200 6,940 21,706 45,878 146,626 69,844 .. 23,000

economy

4.5

Structure of merchandise imports Food

Agricultural raw materials

Fuels

Ores and metals

Manufactures

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

6 4 9 21 .. 8 7 12 14 16 21 10 10 .. 6 .. 16 18 .. 10 21 .. .. 23 13 17 16 14 5 20 24 17 6 8 14 20 22 .. .. 12 14 7 18 32 18 7 20 18 11 .. 19 14 8 10 14 .. 9

5 4 9 .. .. 12 8 10 18 10 17 9 15 .. 5 .. 15 17 .. 17 15 .. .. .. 14 13 11 13 8 12 28 22 7 15 12 11 15 .. 14 15 11 11 18 25 12 8 11 11 12 .. 8 11 12 8 13 .. 6

3 4 6 2 .. 1 2 6 2 6 2 2 2 .. 6 .. 1 3 .. 2 2 .. .. 1 4 3 2 1 1 1 1 3 2 3 1 6 3 .. .. 3 2 1 1 1 1 3 1 6 1 .. 0 2 2 3 4 .. 1

1 2 3 .. .. 1 1 2 1 1 1 1 1 .. 2 .. 1 1 .. 1 1 .. .. .. 2 1 1 1 2 0 1 2 1 1 0 2 1 .. 1 2 1 1 1 5 1 1 1 4 0 .. 1 1 1 2 1 .. 0

12 24 8 2 .. 3 6 7 13 16 13 25 15 .. 14 .. 1 36 .. 21 9 .. .. 0 19 12 14 11 2 16 22 7 2 46 19 14 10 .. .. 12 8 5 18 13 1 3 2 16 14 .. 7 9 9 9 8 .. 1

8 34 20 .. .. 10 17 18 28 28 18 10 21 .. 28 .. 1 4 .. 16 21 .. .. .. 28 5 10 10 8 21 35 16 7 22 27 21 15 .. 14 17 13 15 22 17 1 5 5 28 17 .. 15 14 17 9 13 .. 1

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

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

75 54 73 71 .. 76 82 68 68 54 61 59 71 .. 68 .. 81 40 .. 66 66 .. .. 75 58 64 65 73 86 62 53 72 80 42 65 56 62 .. .. 46 72 83 63 51 77 81 70 57 73 .. 74 75 58 74 72 .. 87

2011 World Development Indicators

72 52 65 .. .. 68 72 65 51 52 60 80 60 .. 58 .. 81 50 .. 56 61 .. .. .. 53 62 78 74 76 65 36 59 80 61 60 63 55 .. 70 62 58 72 59 52 84 79 77 52 70 .. 76 72 67 74 62 .. 90

211


4.5

Structure of merchandise imports Merchandise imports

$ millions 1995 2009

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

10,278 54,247 60,945 191,803 236 1,227 28,091 95,567 1,412 4,713 .. 15,582 133 520 124,507 245,785 8,770 55,301 9,492 26,464 .. .. 73,172 30,546 b 113,537 287,567 5,306 10,207 1,218 9,691 1,008 1,600 65,036 119,839 80,152 155,706 4,709 16,300 810 2,569 1,675 6,347 70,786 133,801 .. .. 594 1,500 1,714 6,955 7,902 19,096 35,709 140,921 1,365 6,750 1,056 4,310 15,484 45,436 23,778 140,000 267,250 481,707 770,852 1,605,296 2,867 6,907 2,750 9,023 12,649 40,597 8,155 69,949 .. .. 1,582 8,500 700 3,793 2,660 2,900 5,228,194 t 12,595,548 t 36,735 127,386 947,153 3,519,888 434,758 2,038,080 512,441 1,475,992 983,905 3,647,212 366,062 1,493,538 163,415 626,665 240,278 668,496 77,167 289,612 60,322 323,199 78,377 253,161 4,244,063 8,955,148 1,647,277 3,519,840

Food

Agricultural raw materials

Fuels

Ores and metals

Manufactures

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

% of total 1995 2009

8 18 19 17 25 14 .. 5 9 8 .. 7b 14 16 24 .. 7 6 17 .. 10 4 .. 18 16 13 7 24 16 8 15 10 5 10 .. 14 5 .. 29 10 6 9w 16 8 9 8 8 6 12 8 22 8 12 9 11

9 17 12 11 24 6 .. 3 7 9 .. 7 11 16 15 21 10 6 14 .. 9 6 .. 15 10 9 4 .. 13 11 7 11 5 10 .. 16 7 .. 28 6 22 8w 16 8 7 9 8 7 10 8 .. 7 11 8 10

2 1 3 1 2 4 .. 1 3 5 .. 2b 3 2 2 .. 2 2 3 .. 1 4 .. 2 1 4 6 0 3 2 0 2 2 4 .. 4 2 .. 2 2 2 3w 3 4 5 3 4 4 3 2 4 4 2 3 3

1 1 1 0 2 2 .. 0 1 3 .. 1 1 1 1 1 1 1 3 .. 1 2 .. 1 1 2 2 .. 1 1 0 1 1 2 .. 1 3 .. 1 1 0 1w 3 2 2 1 2 3 2 1 .. 2 1 1 1

21 3 12 0 30 14 .. 8 13 7 .. 8b 8 6 14 .. 6 3 1 .. 1 7 .. 30 1 7 13 3 2 48 4 4 8 10 .. 1 10 .. 8 13 9 7w 12 7 8 6 7 5 15 5 6 21 10 7 7

9 2 8 0 23 17 .. 24 12 11 .. 21 16 19 4 14 12 7 31 .. 23 19 .. 27 33 11 14 .. 19 32 1 10 17 24 .. 1 16 .. 21 14 13 15 w 16 14 18 11 14 14 14 10 .. 31 17 15 13

Note: Components may not sum to 100 percent because of unclassified trade. a. Includes Luxembourg. b. Refers to the South African Customs Union (Botswana, Lesotho, Namibia, South Africa, and Swaziland).

212

2011 World Development Indicators

4 2 3 4 1 7 .. 2 6 4 .. 2b 4 1 0 .. 4 3 1 .. 4 3 .. 1 6 3 6 2 2 3 6 3 3 1 .. 4 2 .. 1 2 2 4w 2 3 4 3 3 4 4 2 3 6 2 4 4

2 2 2 3 1 6 .. 2 2 4 .. 1 3 1 1 1 3 4 4 .. 1 4 .. 2 3 3 7 .. 1 3 5 3 2 1 .. 1 4 .. 1 13 5 3w 2 5 8 3 5 9 4 2 .. 5 2 3 3

63 45 64 76 42 60 .. 83 70 74 .. 78b 71 75 59 .. 80 85 76 .. 84 81 .. 49 76 73 68 71 78 38 75 80 79 74 .. 77 76 .. 59 72 78 75 w 66 75 72 77 75 78 57 78 66 56 73 75 73

75 76 76 36 50 69 .. 67 78 72 .. 64 68 62 78 63 70 81 47 .. 66 69 .. 55 53 75 64 .. 66 52 73 69 70 62 .. 79 70 .. 50 65 58 69 w 60 69 64 74 69 68 66 77 .. 53 66 69 68


About the data

4.5

economy

Structure of merchandise imports Definitions

Data on imports of goods are derived from the

and free trade zones. Goods transported through a

• Merchandise imports are the c.i.f. value of goods

same sources as data on exports. In principle, world

country en route to another are excluded.

purchased from the rest of the world valued in U.S.

exports and imports should be identical. Similarly,

The data on total imports of goods (merchandise)

dollars. • Food corresponds to the commodities in

exports from an economy should equal the sum of

in the table come from the World Trade Organization

SITC sections 0 (food and live animals), 1 (beverages

imports by the rest of the world from that economy.

(WTO). For further discussion of the WTO’s sources

and tobacco), and 4 (animal and vegetable oils and

But differences in timing and definitions result in dis-

and methodology, see About the data for table 4.4.

fats) and SITC division 22 (oil seeds, oil nuts, and oil

crepancies in reported values at all levels. For further

The import shares by major commodity group are

kernels). • Agricultural raw materials correspond to

discussion of indicators of merchandise trade, see

from the United Nations Statistics Division’s Com-

SITC section 2 (crude materials except fuels), exclud-

About the data for tables 4.4 and 6.2.

modity Trade (Comtrade) database. The values of

ing divisions 22, 27 (crude fertilizers and minerals

The value of imports is generally recorded as the

total imports reported here have not been fully recon-

excluding coal, petroleum, and precious stones),

cost of the goods when purchased by the importer

ciled with the estimates of imports of goods and ser-

and 28 (metalliferous ores and scrap). • Fuels cor-

plus the cost of transport and insurance to the fron-

vices from the national accounts (shown in table 4.8)

respond to SITC section 3 (mineral fuels). •  Ores

tier of the importing country—the cost, insurance,

or those from the balance of payments (table 4.17).

and metals correspond to the commodities in SITC

and freight (c.i.f.) value, corresponding to the landed

The classification of commodity groups is based

divisions 27, 28, and 68 (nonferrous metals). • Man-

cost at the point of entry of foreign goods into the

on the Standard International Trade Classification

ufactures correspond to the commodities in SITC

country. A few countries, including Australia, Canada,

(SITC) revision 3. Previous editions contained data

sections 5 (chemicals), 6 (basic manufactures), 7

and the United States, collect import data on a free

based on the SITC revision 1. Data for earlier years in

(machinery and transport equipment), and 8 (miscel-

on board (f.o.b.) basis and adjust them for freight and

previous editions may differ because of this change

laneous manufactured goods), excluding division 68.

insurance costs. Many countries report trade data in

in methodology. Concordance tables are available

U.S. dollars. When countries report in local currency,

to convert data reported in one system to another.

the United Nations Statistics Division applies the average official exchange rate to the U.S. dollar for the period shown. Countries may report trade according to the general or special system of trade. Under the general system imports include goods imported for domestic consumption and imports into bonded warehouses and free trade zones. Under the special system imports comprise goods imported for domestic consumption (­including transformation and repair) and withdrawals for domestic consumption from bonded warehouses

4.5a

Top 10 developing economy exporters of merchandise goods in 2009 1995

Merchandise exports ($ billions)

2009

1,500

Data sources Data on merchandise imports are from the WTO.

1,200

Data on shares of imports by major commodity group are from Comtrade. The WTO publishes data

900

on world trade in its Annual Report. The International Monetary Fund publishes estimates of total

600

imports of goods in its International Financial Statistics and Direction of Trade Statistics, as does the

300

United Nations Statistics Division in its Monthly Bulletin of Statistics. And the United Nations Con-

0 China

Russian Mexico Federation

India

Malaysia

Brazil

Thailand Indonesia

Turkey

Iran, Islamic Rep.

ference on Trade and Development publishes data on the structure of imports in its Handbook of Sta-

China continues to dominate merchandise exports among developing economies. Even when developed

tistics. Tariff line records of imports are compiled

economies are included, China ranks as the second leading merchandise exporter.

in the United Nations Statistics Division’s Com-

Source: World Development Indicators data files and World Trade Organization.

trade database.

2011 World Development Indicators

213


4.6

Structure of service exports Commercial service exports

$ millions 1995 2009

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

214

.. 94 .. 113 3,676 27 16,076 31,692 166 469 466 35,466a 159 174 457 236 6,005 1,431 38 4 103 242 25,425 0 23 3,249 18,430 33,790 1,641 .. 61 957 426 2,223 .. 6,638 15,171 1,894 687 8,262 342 49 868 310 7,334 83,108 191 38 188 73,576 139 9,528 628 17 2 98 221

.. 2,348 .. 623 10,758 580 44,513 54,080 1,670 935 3,453 79,815a 328 498 1,396 842 26,245 6,889 109 2 1,592 1,158 57,476 .. .. 8,401 128,600 86,306 4,109 .. 303 3,694 816 11,889 .. 20,278 55,346 4,864 1,130 21,302 806 .. 4,368 1,676 27,536 142,487 .. 104 1,225 226,638 1,722 37,690 1,818 67 44 327 933

2011 World Development Indicators

Transport

Travel

% of total

Insurance and financial services

% of total

Computer, information, communications, and other commercial services

% of total

% of total

1995

2009

1995

2009

1995

2009

1995

2009

.. 19 .. 32 27 53 29 12 46 15 65 ..a 26 45 4 16 43 35 17 46 31 48 21 34 5 37 18 33 34 .. 52 14 29 32 .. 22 45 2 47 39 28 70 43 77 28 25 46 22 48 27 59 4 9 75 18 5 26

.. 11 .. 5 15 19 18 22 40 15 66 27a 4 13 20 10 15 21 19 22 12 41 15 .. .. 56 18 31 28 .. 4 8 29 9 .. 27 .. 9 31 31 34 .. 37 59 10 23 .. 19 51 23 19 50 14 22 0 .. 5

.. 69 .. 1 60 5 51 42 42 5 5 ..a 53 32 54 68 16 33 48 32 52 15 31 34 50 28 47 17 40 .. 22 71 21 61 .. 43 24 83 37 32 25 3 41 5 22 33 9 73 25 25 8 43 34 5 14 92 36

.. 78 .. 86 37 58 56 35 21 7 11 12a 72 56 49 54 20 55 57 62 74 19 24 .. .. 19 31 17 49 .. 18 49 14 76 .. 32 .. 83 59 50 40 .. 25 20 10 35 .. 60 39 15 56 39 65 4 87 96 66

.. 1 .. 9 0 7 5 4 0 0 0 ..a 7 10 3 8 17 0 0 0 0 7 11 20 2 7 10 9 6 .. 0 0 12 1 .. 1 .. 0 0 1 8 1 0 2 2 5 3 0 0 5 3 0 4 1 0 1 2

.. 0 .. 0 0 3 3 4 0 6 0 5a 2 14 1 4 7 3 2 14 0 2 11 .. .. 4 2 13 1 .. 31 0 0 1 .. 1 .. 1 0 1 4 .. 2 1 2 2 .. 0 2 7 1 2 2 9 1 0 2

.. 10 .. 59 12 41 15 42 12 80 30 ..a 14 14 39 7 24 32 35 21 18 30 37 12 44 28 24 41 19 .. 25 15 38 6 .. 34 31 15 16 28 39 27 16 16 48 37 41 5 27 44 30 52 54 18 82 2 36

.. 11 .. 9 48 21 22 38 39 72 23 55a 22 17 30 33 57 22 21 2 13 38 50 .. .. 22 49 39 23 .. 47 43 57 15 .. 40 .. 7 10 17 23 .. 36 20 78 41 .. 21 8 54 24 9 20 65 12 4 28


Commercial service exports

$ millions 1995 2009

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

5,086 6,763 5,342 533 .. 4,799 7,906 61,173 1,568 63,966 1,689 535 1,183 .. 22,133 .. 1,124 39 68 718 .. 30 .. 20 482 151 219 24 11,438 68 19 773 9,585 143 47 2,020 242 353 301 592 44,646 4,401 94 12 608 13,458 13 1,432 1,298 321 566 1,042 9,323 10,637 8,161 .. ..

18,419 90,193 13,238 .. 1,721 92,964 21,961 101,237 2,616 125,918 4,192 3,813 2,198 .. 57,304 .. 10,425 850 368 3,812 16,869 63 142 385 3,769 845 .. .. 28,727 442 .. 2,225 15,420 647 412 11,892 544 256 505 548 90,853 7,760 429 126 1,769 38,537 1,792 2,463 5,463 162 1,288 3,517 10,101 28,856 22,539 .. ..

Transport

Travel

% of total

Insurance and financial services

% of total

4.6 Computer, information, communications, and other commercial services

% of total

1995

2009

1995

2009

8 28 1 26 .. 22 25 18 16 35 25 66 59 .. 42 .. 84 40 23 92 .. 7 .. 63 60 32 30 28 22 32 9 26 12 30 32 20 25 6 .. 9 40 35 18 3 16 63 100 58 60 11 13 32 3 29 19 .. ..

19 12 18 .. 22 4 14 13 13 25 19 57 48 .. 51 .. 30 16 8 51 2 1 10 68 56 30 .. .. 15 7 .. 15 10 39 33 18 28 51 23 7 27 19 10 9 62 41 32 44 56 9 13 21 11 30 26 .. ..

58 38 98 13 .. 46 38 47 68 5 39 23 36 .. 23 .. 11 12 76 3 .. 91 .. 12 16 14 26 72 35 37 58 56 64 40 44 64 .. 43 92 30 15 53 52 58 3 17 81 8 24 8 24 41 12 22 59 .. ..

31 12 48 .. 0 5 17 40 74 8 69 25 31 .. 16 .. 2 54 73 19 40 64 87 13 30 26 .. .. 55 62 .. 50 73 26 57 56 36 18 72 68 14 59 81 62 34 11 39 11 27 1 16 58 23 31 43 .. ..

economy

Structure of service exports

% of total

1995

2009

3 3 0 9 .. 0 0 7 1 1 0 0 1 .. 0 .. 6 0 1 2 .. 1 .. .. 1 4 2 0 0 5 0 0 7 12 5 1 .. 0 1 0 1 0 2 0 1 4 0 1 6 1 5 7 1 8 5 .. ..

1 5 2 .. 0 20 0 9 2 4 0 4 1 .. 5 .. 1 2 3 7 2 1 .. 16 1 2 .. .. 2 1 .. 4 10 1 1 2 1 .. 1 0 2 1 1 7 1 5 1 6 7 7 2 9 1 2 2 .. ..

1995

2009

31 31 2 53 .. 32 36 29 15 59 36 12 3 .. 34 .. 0 48 1 3 .. 1 .. 25 23 51 42 0 44 25 33 19 17 19 19 14 75 51 6 61 44 13 27 39 80 16 0 33 10 80 57 19 84 41 18 .. ..

49 70 32 .. 78 70 68 38 11 62 12 14 20 .. 28 .. 66 28 16 23 56 34 3 3 14 43 .. .. 28 30 .. 30 6 34 9 25 35 31 4 25 57 21 8 21 3 44 28 39 9 84 69 12 65 37 30 .. ..

2011 World Development Indicators

215


4.6

Structure of service exports Commercial service exports

$ millions 1995 2009

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

1,476 9,737 10,567 41,068 11 249 3,475 9,335 364 1,177 .. 3,478 71 53 27,234 90,690 2,378 6,259 2,016 5,999 .. .. 4,414 11,656 40,019 122,101 800 1,874 82 392 150 191 15,336 59,073 25,179 72,309 1,632 3,770 .. 142 566 1,795 14,652 29,677 .. .. 64 253 331 918 2,401 5,241 14,475 32,758 79 .. 104 854 2,846 13,324 .. .. 77,549 236,254 198,501 475,979 1,309 2,132 .. .. 1,529 1,805 2,243 5,656 265 407 141 1,085 112 241 353 .. 1,228,960 t 3,417,725 t 6,429 21,036 174,925 641,508 87,678 377,784 87,180 264,293 180,841 660,929 62,745 220,270 35,079 131,431 38,013 98,855 .. .. 10,333 97,113 12,144 35,613 1,047,874 2,755,581 425,302 1,087,280

a. Includes Luxembourg.

216

2011 World Development Indicators

Transport

Travel

% of total 1995

32 36 61 .. 15 .. 14 30 26 25 .. 24 16 42 1 18 32 15 15 .. 0 17 .. 34 59 25 12 80 18 76 .. 21 23 31 .. 38 .. 0 22 64 26 27 w 28 25 21 27 25 17 38 24 .. 32 26 27 25

Insurance and financial services

% of total 2009

30 30 22 20 12 21 35 34 30 25 .. 12 15 46 4 4 16 8 5 50 19 19 .. 43 24 26 23 .. 4 47 .. 13 13 16 .. 39 .. 4 4 48 .. 21 w 20 21 21 22 21 17 33 18 .. 20 28 21 21

1995

40 41 22 .. 46 .. 80 28 26 54 .. 48 63 28 10 32 23 38 77 .. 89 55 .. 20 23 64 34 9 75 7 .. 26 38 47 .. 56 .. 96 35 26 51 33 w 28 45 46 43 44 49 34 51 .. 30 31 30 33

Computer, information, communications, and other commercial services

% of total 2009

13 23 70 64 46 25 48 10 37 42 .. 65 44 19 76 21 17 19 84 2 65 53 .. 16 43 53 65 .. 78 27 .. 13 25 62 .. 44 .. 66 83 41 .. 26 w 37 42 36 47 42 40 29 54 .. 13 53 22 24

% of total

1995

2009

5 1 0 .. 1 .. 0 15 5 1 .. 10 4 3 4 0 2 28 0 .. 0 1 .. 2 9 2 2 1 0 3 .. 18 4 1 .. 0 .. 0 0 0 0 5w 1 5 5 5 5 5 1 7 .. 2 6 6 4

2 4 1 13 1 1 1 12 6 2 .. 8 5 4 15 11 4 30 4 5 1 1 .. 5 25 2 3 .. 4 3 .. 28 15 4 .. 0 .. 0 0 2 .. 8w 3 4 2 5 4 1 3 7 .. 5 4 9 6

1995

23 23 18 .. 38 .. 6 27 43 21 .. 18 17 27 86 50 43 20 8 .. 11 28 .. 44 9 10 52 10 7 15 .. 35 35 21 .. 6 .. 4 43 10 23 36 w 44 27 30 25 28 31 27 18 .. 36 40 38 37

2009

56 44 8 3 40 53 15 44 26 31 .. 15 36 31 24 64 62 43 7 44 16 27 .. 36 8 18 9 .. 14 23 .. 46 47 18 .. 18 .. 30 13 9 .. 45 w 41 33 42 25 33 41 34 21 .. 62 16 48 49


About the data

4.6

economy

Structure of service exports Definitions

Balance of payments statistics, the main source of

affiliates. Another important dimension of service

•  Commercial service exports are total service

information on international trade in services, have

trade not captured by conventional balance of pay-

exports minus exports of government services not

many weaknesses. Disaggregation of important

ments statistics is establishment trade—sales in

included elsewhere. • Transport covers all transport

components may be limited and varies considerably

the host country by foreign affiliates. By contrast,

services (sea, air, land, internal waterway, space,

across countries. There are inconsistencies in the

cross-border intrafirm transactions in merchandise

and pipeline) performed by residents of one economy

methods used to report items. And the recording of

may be reported as exports or imports in the balance

for those of another and involving the carriage of

major flows as net items is common (for example,

of payments.

passengers, movement of goods (freight), rental of

insurance transactions are often recorded as premi-

The data on exports of services in the table and on

carriers with crew, and related support and auxiliary

ums less claims). These factors contribute to a down-

imports of services in table 4.7, unlike those in edi-

services. Excluded are freight insurance, which is

ward bias in the value of the service trade reported

tions before 2000, include only commercial services

included in insurance services; goods procured in

in the balance of payments.

and exclude the category “government services not

ports by nonresident carriers and repairs of trans-

Efforts are being made to improve the coverage,

included elsewhere.” The data are compiled by the

port equipment, which are included in goods; repairs

quality, and consistency of these data. Eurostat and

IMF based on returns from national sources. Data on

of harbors, railway facilities, and airfield facilities,

the Organisation for Economic Co-operation and

total trade in goods and services from the IMF’s Bal-

which are included in construction services; and

Development, for example, are working together

ance of Payments database are shown in table 4.17.

rental of carriers without crew, which is included

to improve the collection of statistics on trade in

International transactions in services are defined

in other services. •  Travel covers goods and ser-

services in member countries. In addition, the Inter-

by the IMF’s Balance of Payments Manual (1993) as

vices acquired from an economy by travelers in that

national Monetary Fund (IMF) has implemented

the economic output of intangible commodities that

economy for their own use during visits of less than

the new classification of trade in services intro-

may be produced, transferred, and consumed at the

one year for business or personal purposes. • Insur-

duced in the fifth edition of its Balance of Payments

same time. Definitions may vary among reporting

ance and financial services cover freight insurance

Manual (1993).

economies. Travel services include the goods and

on goods exported and other direct insurance such

Still, difficulties in capturing all the dimensions of

services consumed by travelers, such as meals,

as life insurance; financial intermediation services

international trade in services mean that the record

lodging, and transport (within the economy visited),

such as commissions, foreign exchange transac-

is likely to remain incomplete. Cross-border intrafirm

including car rental.

tions, and brokerage services; and auxiliary services

service transactions, which are usually not captured

such as financial market operational and regulatory

in the balance of payments, have increased in recent

services. •  Computer, information, communica-

years. An example is transnational corporations’ use

tions, and other commercial services cover such

of mainframe computers around the clock for data

activities as international telecommunications and

processing, exploiting time zone differences between

postal and courier services; computer data; news-

their home country and the host countries of their

related service transactions between residents and nonresidents; construction services; royalties and

4.6a

Top 10 developing economy exporters of commercial services in 2009 Commercial service exports ($ billions)

1995

2009

license fees; miscellaneous business, professional, and technical services; and personal, cultural, and recreational services.

150

120

90

60

30

0 China

India

Russian Federation

Turkey

Thailand Malaysia

Brazil

Egypt, Arab Rep.

Mexico

Lebanona

The top 10 developing country exporters of commercial services accounted for almost 68 percent of developing country commercial service exports and 13 percent of world commercial service exports. a. Data are unavailable for 1995. Source: International Monetary Fund balance of payments data files.

Data sources Data on exports of commercial services are from the IMF, which publishes balance of payments data in its International Financial Statistics and Balance of Payments Statistics Yearbook.

2011 World Development Indicators

217


4.7

Structure of service imports Commercial service imports

$ millions 1995 2009

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

218

.. 98 .. 1,665 6,992 52 16,979 27,552 297 1,192 276 33,134 a 235 321 262 440 13,161 1,278 116 62 181 485 32,985 114 174 3,524 24,635 24,962 2,813 .. 690 895 1,235 1,373 .. 4,860 13,945 957 1,141 4,511 488 45 420 337 9,418 64,523 832 47 249 128,865 331 4,003 672 252 27 236 326

.. 2,215 .. 18,210 11,445 839 47,613 36,894 3,297 3,202 2,031 73,008 500 993 625 1,040 44,074 5,037 564 160 939 2,081 77,579 .. .. 9,351 158,107 44,379 6,860 .. 3,523 1,407 2,324 3,812 .. 18,887 50,912 1,733 2,556 12,765 1,231 .. 2,496 2,190 25,687 126,425 .. 83 910 253,467 2,166 19,525 2,058 288 85 736 1,077

2011 World Development Indicators

Transport

Travel

% of total

Insurance and financial services

% of total

Computer, information, communications, and other commercial services

% of total

% of total

1995

2009

1995

2009

1995

2009

1995

2009

.. 61 .. 18 30 83 37 12 31 65 36 24 a 59 66 51 43 44 42 56 49 46 35 24 44 55 54 39 22 42 .. 19 41 50 28 .. 16 45 61 42 35 55 2 53 63 23 33 18 60 27 18 61 30 41 58 53 78 60

.. 15 .. 23 23 46 31 29 24 83 40 25 62 38 32 40 18 22 59 53 58 33 22 .. .. 52 29 34 34 .. 15 36 58 18 .. 21 .. 58 54 45 57 .. 33 67 19 26 .. 46 54 21 41 51 46 37 38 72 42

.. 7 .. 5 47 6 30 40 49 20 32 28a 15 15 31 33 26 15 20 41 5 22 31 38 15 20 15 54 31 .. 8 36 15 31 .. 34 31 18 21 28 15 7 22 8 24 25 17 30 63 47 6 33 21 8 14 15 18

.. 72 .. 1 39 39 39 29 11 8 29 25 13 29 38 22 25 35 11 39 11 17 31 .. .. 17 28 34 26 .. 5 26 15 27 .. 22 .. 20 21 20 15 .. 24 6 17 31 .. 11 20 32 27 17 35 5 54 9 27

.. 22 .. 3 7 10 7 6 1 6 4 10a 10 9 10 8 10 0 5 6 4 7 11 8 2 4 17 6 12 .. 7 5 11 3 .. 5 .. 10 6 5 11 0 5 7 5 6 9 6 8 2 6 5 9 7 5 2 2

.. 5 .. 4 5 7 3 4 3 2 4 4 5 13 4 4 8 8 17 3 5 4 12 .. .. 10 8 8 8 .. 5 9 0 5 .. 3 .. 9 6 11 15 .. 2 4 2 3 .. 8 14 4 4 8 10 9 5 1 6

.. 10 .. 75 16 1 26 43 19 10 29 38a 16 10 8 16 21 43 20 4 45 36 34 10 29 22 29 18 15 .. 67 18 23 38 .. 45 24 11 31 32 19 93 21 22 48 36 57 4 2 33 26 33 29 26 28 6 20

.. 9 .. 72 33 8 27 38 62 8 28 47 20 19 25 34 49 35 13 6 27 45 35 .. .. 20 35 24 32 .. 75 29 27 51 .. 54 .. 13 18 24 13 .. 41 22 62 41 .. 36 12 43 28 24 9 50 4 19 25


Commercial service imports

$ millions 1995 2009

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

3,765 10,062 13,230 2,192 .. 11,252 8,131 54,613 1,073 121,547 1,385 776 900 .. 25,394 .. 3,826 193 119 225 .. 58 .. 510 457 300 277 151 14,821 412 197 630 9,021 193 87 1,350 350 233 538 305 43,618 4,571 207 120 4,398 13,052 985 2,431 1,049 642 676 1,781 6,906 7,008 6,339 .. ..

16,407 80,274 27,625 .. 7,565 104,551 16,865 114,581 1,824 146,965 3,657 9,881 1,634 .. 74,978 .. 11,297 858 114 2,260 14,301 91 141 4,323 2,883 789 .. .. 27,257 1,022 .. 1,586 21,402 678 545 5,302 1,004 547 602 771 84,625 7,825 517 599 16,127 36,504 5,555 5,844 2,118 1,915 511 4,619 8,344 23,789 14,186 .. ..

Transport

Travel

% of total

Insurance and financial services

% of total

4.7

economy

Structure of service imports

Computer, information, communications, and other commercial services

% of total

% of total

1995

2009

1995

2009

1995

2009

1995

2009

13 57 37 43 .. 16 45 24 46 30 52 38 46 .. 38 .. 39 27 43 68 .. 75 .. 60 64 50 56 67 38 60 62 40 38 52 70 48 33 11 37 36 29 41 39 74 22 38 42 67 71 25 66 51 30 25 27 .. ..

17 44 44 .. 53 2 32 20 43 28 53 19 51 .. 31 .. 31 48 12 26 15 79 60 48 38 39 .. .. 34 63 .. 32 13 38 37 44 35 46 37 28 21 29 48 67 38 26 38 54 58 23 61 37 44 22 30 .. ..

40 10 16 11 .. 18 26 27 14 30 31 36 21 .. 25 .. 59 3 25 11 .. 23 .. 15 23 9 21 26 16 12 12 25 35 29 22 22 .. 8 17 45 27 28 19 11 21 32 5 18 12 9 20 17 6 6 33 .. ..

22 12 19 .. 10 8 17 24 12 17 29 11 14 .. 18 .. 66 31 72 35 28 15 20 37 41 13 .. .. 24 14 .. 22 33 36 39 21 21 7 18 56 25 33 28 11 25 34 16 12 16 2 25 24 29 31 27 .. ..

5 6 3 10 .. 1 3 10 9 2 6 0 10 .. 2 .. 2 4 4 7 .. 0 .. .. 1 21 4 0 0 1 1 5 12 9 0 4 2 1 9 3 3 5 3 3 3 6 5 4 9 3 12 10 2 14 9 .. ..

3 10 5 .. 27 14 2 5 11 6 8 6 8 .. 2 .. 1 2 –4 5 2 0 2 14 2 4 .. .. 4 5 .. 5 52 3 3 5 2 .. 4 4 3 4 11 4 3 4 10 4 15 12 11 11 4 6 4 .. ..

43 28 43 36 .. 65 26 39 31 38 11 25 22 .. 36 .. 0 65 28 14 .. 2 .. 25 12 21 20 7 47 27 25 30 14 10 8 26 65 81 37 16 41 26 38 12 54 24 49 10 9 63 1 22 63 55 31 .. ..

57 35 32 .. 10 76 48 50 34 50 10 64 26 .. 49 .. 2 19 20 34 55 6 17 2 19 45 .. .. 38 18 .. 40 2 24 21 30 42 47 41 12 51 34 13 18 34 37 36 30 11 63 3 28 23 41 40 .. ..

2011 World Development Indicators

219


4.7

Structure of service imports Commercial service imports

$ millions 1995 2009

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

1,801 10,154 20,205 59,241 58 503 8,670 45,540 405 1,384 .. 3,406 79 107 21,111 82,189 1,800 7,933 1,429 4,330 .. .. 5,756 14,390 22,354 86,988 1,169 2,487 150 2,684 206 539 17,112 44,373 14,899 38,867 1,358 3,127 .. 289 729 1,685 18,629 37,541 .. .. 148 358 223 271 1,245 2,812 4,654 15,607 403 .. 563 1,408 1,334 11,070 .. .. 62,524 160,036 129,227 334,311 814 1,072 .. .. 4,654 9,223 2,304 7,044 349 786 604 2,038 282 674 645 .. 1,221,691 t 3,144,723 t 9,833 29,059 218,955 749,008 109,579 443,081 109,232 304,268 228,417 777,282 82,593 272,307 35,575 139,286 52,313 127,915 19,571 62,588 15,377 93,734 24,587 88,519 992,976 2,368,417 422,763 995,810

a. Includes Luxembourg.

220

2011 World Development Indicators

Transport

Travel

% of total 1995

34 16 73 25 57 .. 17 44 17 31 .. 40 31 58 27 16 28 35 57 .. 30 42 .. 71 42 45 30 40 38 34 .. 27 32 46 .. 31 .. 28 36 79 56 31 w 51 39 42 38 40 38 30 41 45 59 40 29 25

Insurance and financial services

% of total 2009

28 16 63 25 55 27 57 32 22 20 .. 41 20 62 51 33 16 19 58 49 36 45 .. 71 47 53 42 .. 61 32 .. 18 20 42 .. 44 .. 8 46 57 .. 25 w 58 32 38 27 33 35 30 24 47 51 42 22 23

1995

39 57 17 .. 18 .. 63 22 18 40 .. 32 20 16 29 21 32 50 37 .. 49 23 .. 12 31 20 20 18 14 16 .. 40 36 29 .. 37 .. 46 12 9 19 31 w 18 24 16 30 23 16 33 31 21 13 24 33 32

Computer, information, communications, and other commercial services

% of total 2009

15 35 14 41 13 28 12 19 26 31 .. 29 19 17 32 13 27 27 26 2 45 12 .. 5 28 15 27 .. 13 30 .. 32 24 31 .. 17 .. 68 11 6 .. 25 w 18 26 22 28 25 24 29 29 19 13 23 25 27

1995

5 0 0 3 7 .. 4 10 5 2 .. 14 7 5 0 4 1 1 6 .. 3 5 .. 4 8 6 8 7 4 7 .. 4 6 5 .. 3 .. 3 7 0 3 6w 5 9 10 8 9 10 5 10 .. 5 9 5 5

% of total 2009

7 4 1 6 11 4 9 6 14 4 .. 4 8 6 1 6 1 8 9 10 4 5 .. 10 3 10 13 .. 10 13 .. 7 21 6 .. 6 .. 1 9 11 .. 10 w 4 14 7 20 14 6 8 30 11 8 4 9 4

1995

22 26 10 72 18 .. 16 24 60 27 .. 14 41 21 44 59 38 14 6 .. 18 30 .. 12 19 28 42 35 43 43 .. 29 26 20 .. 30 .. 25 45 12 23 32 w 27 28 32 25 28 37 33 17 28 23 28 33 38

2009

51 45 22 28 21 40 22 42 37 45 .. 26 52 15 68 48 56 46 7 38 15 38 .. 14 22 23 19 .. 16 25 .. 44 35 21 .. 33 .. 23 35 26 .. 40 w 19 28 32 25 28 35 33 17 23 29 31 43 46


About the data

4.7

economy

Structure of service imports Definitions

Trade in services differs from trade in goods because

•  Commercial service imports are total service

services are produced and consumed at the same

imports minus imports of government services not

time. Thus services to a traveler may be consumed

included elsewhere. • Transport covers all transport

in the producing country (for example, use of a hotel

services (sea, air, land, internal waterway, space,

room) but are classified as imports of the traveler’s

and pipeline) performed by residents of one economy

country. In other cases services may be supplied

for those of another and involving the carriage of

from a remote location; for example, insurance

passengers, movement of goods (freight), rental of

services may be supplied from one location and

carriers with crew, and related support and auxiliary

consumed in another. For further discussion of the

services. Excluded are freight insurance, which is

problems of measuring trade in services, see About

included in insurance services; goods procured in

the data for table 4.6.

ports by nonresident carriers and repairs of trans-

The data on imports of services in the table and on

port equipment, which are included in goods; repairs

exports of services in table 4.6, unlike those in edi-

of harbors, railway facilities, and airfield facilities,

tions before 2000, include only commercial services

which are included in construction services; and

and exclude the category “government services not

rental of carriers without crew, which is included

included elsewhere.” The data are compiled by the

in other services. •  Travel covers goods and ser-

International Monetary Fund (IMF) based on returns

vices acquired from an economy by travelers in that

from national sources.

economy for their own use during visits of less than

International transactions in services are defined

one year for business or personal purposes. • Insur-

by the IMF’s Balance of Payments Manual (1993) as

ance and financial services cover freight insurance

the economic output of intangible commodities that

on goods imported and other direct insurance such

may be produced, transferred, and consumed at the

as life insurance; financial intermediation services

same time. Definitions may vary among reporting

such as commissions, foreign exchange transac-

economies.

tions, and brokerage services; and auxiliary services

Travel services include the goods and services

such as financial market operational and regulatory

consumed by travelers, such as meals, lodging, and

services. •  Computer, information, communica-

transport (within the economy visited), including car

tions, and other commercial services cover such

rental.

activities as international telecommunications, and postal and courier services; computer data; newsrelated service transactions between residents and nonresidents; construction services; royalties and license fees; miscellaneous business, professional,

The mix of commercial service imports by developing economies is changing 1995 ($228 billion)

Other 28%

Insurance and financial 9%

Transport 40%

4.7a

and technical services; and personal, cultural, and recreational services.

2009 ($777 billion)

Other 28%

Transport 33%

Travel 23% Insurance and financial 14% Travel 25%

Data sources Between 1995 and 2009 developing economies’ commercial service imports more than tripled. Insur-

Data on imports of commercial services are from

ance and financial services and travel services are displacing transport as the most important services

the IMF, which publishes balance of payments

imported.

data in its International Financial Statistics and

Source: International Monetary Fund balance of payments data files.

Balance of Payments Statistics Yearbook.

2011 World Development Indicators

221


4.8 Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

222

Structure of demand Household final consumption expenditure

General government final consumption expenditure

Gross capital formation

Exports of goods and services

Imports of goods and services

Gross savings

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

.. 87 55 34 69 109 60 56 77 83 59 54 82 76 .. 34 62 66 63 89 95 72 57 79 91 61 43 62 65 81 49 71 66 67 71 51 51 81 68 74 87 94 54 80 52 57 41 90 102 58 76 76 86 74 95 86 64

88 87 41 .. 59 82 57 54 37 77 56 52 .. 66 80 63 62 66 .. .. 74 72 59 93 79 60 35 62 64 74 42 62 72 57 54 51 49 85 69 76 92 86 53 88 54 58 41 78 83 59 82 75 86 75 83 .. 80

2011 World Development Indicators

.. 14 17 40 13 11 18 20 13 5 21 21 11 14 .. 29 21 17 25 19 6 9 21 15 7 10 14 8 15 5 13 14 11 26 24 21 25 5 13 11 9 44 26 8 23 24 12 14 11 20 12 15 6 8 6 7 9

9 10 14 .. 15 11 17 20 14 5 17 25 .. 15 23 24 22 16 .. .. 8 9 22 4 16 13 13 9 16 8 12 17 9 20 33 22 30 8 10 11 10 31 22 8 25 25 12 16 24 20 10 19 10 8 14 .. 19

.. 21 31 35 18 18 24 25 24 19 25 21 20 15 20 25 18 16 24 6 15 13 19 14 13 26 42 34 26 9 37 18 16 16 7 33 20 18 22 20 20 23 28 18 18 19 23 20 4 22 20 18 15 21 22 26 32

25 29 41 15 21 31 28 21 22 24 38 20 25 17 22 24 17 26 .. .. 21 18 21 11 34 19 48 23 23 30 25 20 11 27 11 22 17 15 32 19 13 11 19 22 18 19 28 26 12 16 20 16 13 22 23 27 20

.. 12 26 82 10 24 18 35 28 11 50 65 20 23 20 51 7 52 14 13 31 24 37 20 22 29 20 143 15 28 65 38 42 33 13 51 38 36 26 23 22 22 68 10 37 23 59 49 26 24 24 17 19 21 12 9 44

16 29 40 52 21 12 20 51 52 19 51 73 14 36 33 34 11 48 .. .. 60 27 29 14 42 38 27 194 16 10 72 43 42 36 20 70 48 22 37 25 22 4 71 11 37 23 52 30 30 41 31 19 23 41 26 14 42

.. 35 29 68 10 62 20 36 42 17 54 62 33 27 71 38 9 50 27 27 47 18 34 28 34 27 19 148 21 24 64 40 34 42 16 55 33 39 28 28 38 83 76 16 29 22 36 73 42 23 33 27 25 25 35 29 48

48 54 36 46 16 36 22 46 25 27 62 70 28 33 58 45 11 56 .. .. 63 31 30 22 70 30 22 187 18 22 51 42 34 39 18 64 44 30 48 32 38 20 65 29 35 25 33 50 49 36 41 29 33 45 47 44 61

.. 20 .. 78 16 –9 18 22 13 22 21 29 11 11 .. 36 16 15 29 6 6 14 18 11 12 25 42 .. 19 .. –2 15 12 11 .. 29 22 16 17 22 18 19 24 21 22 19 33 8 1 20 18 18 11 21 10 .. 27

.. 17 .. 10 23 20 21 24 45 39 25 22 11 23 13 16 15 16 .. .. 19 20 18 .. .. 22 54 31 18 .. 18 20 15 22 .. 20 22 10 24 17 11 .. 24 16 20 16 .. 19 0 21 16 3 12 8 .. .. 16


Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

4.8

economy

Structure of demand Household final consumption expenditure

General government final consumption expenditure

Gross capital formation

Exports of goods and services

Imports of goods and services

Gross savings

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

68 64 62 46 .. 54 56 58 70 55 65 71 70 .. 52 .. 43 75 .. 63 103 93 .. 59 68 70 90 79 48 83 77 63 67 57 56 68 90 .. 54 75 49 59 83 86 .. 50 51 72 52 44 76 71 74 60 65 .. 32

67 56 57 45 .. 52 57 60 81 60 83 50 76 .. 54 .. 28 86 66 61 79 79 202 23 65 81 80 62 50 77 72 75 67 87 55 57 84 .. 62 81 46 60 91 .. .. 43 34 80 49 69 78 64 74 61 67 .. 21

11 11 8 16 .. 16 28 18 11 15 24 14 15 .. 11 .. 32 20 .. 24 12 35 .. 22 21 19 7 21 12 10 11 14 10 27 13 17 8 .. 30 9 24 17 11 14 .. 22 25 12 15 17 10 10 11 20 17 .. 32

9 12 10 11 .. 19 24 22 16 20 24 12 16 .. 16 18 13 23 8 21 16 50 19 9 19 18 11 21 14 10 21 15 12 22 1 18 13 .. 24 11 29 20 12 .. .. 22 15 8 10 11 12 10 11 19 21 .. 25

21 27 32 29 .. 18 25 20 29 28 33 20 22 .. 38 .. 15 18 .. 14 36 76 .. 12 21 21 11 17 44 23 20 26 20 25 32 21 27 14 22 25 21 23 22 7 .. 22 15 19 30 22 26 25 22 19 24 .. 35

22 36 31 33 .. 14 16 19 21 20 15 30 21 .. 26 28 19 22 37 19 30 31 20 28 27 24 33 25 14 22 25 21 22 27 50 36 21 .. 27 30 18 18 23 .. .. 20 30 19 25 20 16 22 15 20 20 .. 39

46 11 26 22 .. 76 29 26 51 9 52 39 33 .. 29 .. 52 29 23 43 11 24 9 29 47 33 24 30 94 21 37 59 30 49 48 27 16 1 49 25 59 29 19 17 44 38 44 17 101 61 59 13 36 23 27 72 44

81 20 24 32 .. 89 35 24 35 13 43 42 25 .. 50 14 66 50 33 42 22 51 31 67 60 44 28 30 96 26 50 48 28 37 56 29 25 .. 47 16 69 28 35 .. 36 42 59 13 77 58 47 24 32 39 28 .. 47

46 12 28 13 .. 65 37 22 61 8 73 44 39 .. 30 .. 42 42 37 45 62 128 72 22 58 43 32 48 98 36 45 61 28 58 49 34 41 2 56 35 54 28 35 24 42 32 36 19 98 44 71 18 44 21 34 97 43

80 24 21 22 .. 74 32 24 53 12 65 34 38 .. 46 54 26 81 44 43 47 112 173 27 72 67 52 38 75 36 68 59 29 73 63 39 44 .. 60 37 62 27 61 .. 27 27 38 20 61 57 52 20 31 39 36 .. 31

17 27 28 37 .. 23 13 22 25 30 29 15 23 .. 36 .. 38 8 .. 14 .. 39 .. .. 12 13 2 8 34 15 14 25 19 18 35 17 9 .. 32 21 27 18 –1 –1 .. 26 10 21 30 35 18 16 19 20 24 .. ..

2011 World Development Indicators

15 35 23 .. .. 9 20 16 13 24 10 28 15 .. 30 .. 59 14 25 29 13 28 –2 67 15 18 .. .. 31 19 .. 17 22 19 42 31 9 .. 27 38 22 16 10 .. .. 32 39 22 35 20 12 23 40 19 10 .. ..

223


4.8

Structure of demand

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzaniaa Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

Household final consumption expenditure

General government final consumption expenditure

Gross capital formation

Exports of goods and services

Imports of goods and services

Gross savings

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

68 52 97 47 80 73 88 41 52 60 .. 63 60 73 85 82 49 60 66 62 86 55 .. 77 53 63 68 44 85 55 48 63 68 73 51 69 74 98 71 72 65 61 w 81 60 55 63 60 48 61 66 63 67 69 61 57

61 54 81 38 83 74 84 43 47 55 .. 60 56 64 67 73 49 58 72 93 62 54 .. .. 49 63 72 49 76 65 46 65 71 68 56 64 66 .. .. 61 113 62 w 78 56 50 62 57 42 62 64 55 61 67 63 58

a. Covers mainland Tanzania only.

224

2011 World Development Indicators

14 19 10 24 13 23 14 8 22 19 .. 18 18 11 5 15 27 12 13 16 12 10 .. 12 12 16 11 12 11 21 16 20 15 12 22 7 8 18 14 15 18 17 w 9 14 12 15 14 13 16 15 15 10 16 17 20

15 20 15 25 9 19 14 10 20 20 .. 21 21 18 14 27 28 11 14 28 20 13 .. 9 10 13 15 10 11 19 10 23 17 13 18 13 6 .. .. 13 14 19 w 10 15 13 16 15 13 17 16 13 11 18 20 22

24 25 13 20 14 12 6 34 24 24 .. 18 22 26 14 16 17 23 27 29 20 42 .. 16 21 25 25 49 12 27 30 17 18 15 27 18 27 35 22 16 20 22 w 18 27 34 22 27 40 25 20 25 25 18 21 21

31 19 22 26 28 24 15 29 38 23 .. 19 24 25 25 17 17 20 16 22 30 22 .. .. 12 27 15 11 24 17 20 14 14 18 26 25 38 .. .. 22 2 19 w 24 28 37 20 28 40 19 20 28 33 21 17 19

28 29 5 38 31 17 19 .. 58 50 .. 23 22 36 5 60 40 36 31 66 24 42 .. 32 54 45 20 84 12 47 69 28 11 19 28 27 33 16 51 36 38 21 w 18 23 23 23 23 27 29 18 26 12 28 21 29

33 28 12 54 24 27 16 221 99 59 .. 27 23 21 15 60 49 52 34 13 23 68 .. 42 68 52 23 76 23 46 87 28 11 26 36 18 68 .. .. 36 36 24 w 23 27 29 25 27 35 30 21 38 19 30 24 36

33 26 26 28 37 24 26 .. 56 52 .. 22 22 46 10 74 33 31 38 72 42 49 .. 37 39 49 24 84 21 50 63 28 12 19 28 22 42 68 58 40 41 21 w 26 24 24 23 24 28 31 19 29 15 30 20 28

40 20 29 43 44 44 29 203 104 57 .. 28 26 28 21 76 42 41 36 56 35 58 .. 62 39 55 24 46 35 48 64 30 14 26 36 20 79 .. .. 32 65 24 w 36 26 28 24 26 30 29 21 33 24 34 24 35

19 28 20 20 8 .. –3 53 27 23 .. 17 22 20 3 16 20 30 27 .. 7 34 .. 17 27 20 22 50 13 23 .. 15 16 14 .. 21 20 12 26 9 18 22 w 17 26 33 20 26 38 23 18 .. 25 16 21 21

29 23 15 32 16 17 8 45 29 22 .. 15 20 24 12 2 24 32 14 12 21 30 .. .. 31 23 13 .. 18 16 .. 12 10 17 .. 22 29 .. .. 19 .. 19 w 24 29 40 19 29 47 19 19 .. 34 15 16 19


About the data

4.8

economy

Structure of demand Definitions

Gross domestic product (GDP) from the expenditure

1993 SNA ­guidelines are capital outlays on defense

• Household final consumption expenditure is the

side is made up of household final consumption

establishments that may be used by the general pub-

market value of all goods and services, including

expenditure, general government final consumption

lic, such as schools, airfields, and hospitals, and

durable products (such as cars and computers),

expenditure, gross capital formation (private and

intangibles such as computer software and mineral

purchased by households. It excludes purchases

public investment in fixed assets, changes in inven-

exploration outlays. Data on capital formation may

of dwellings but includes imputed rent for owner-

tories, and net acquisitions of valuables), and net

be estimated from direct surveys of enterprises and

occupied dwellings. It also includes government fees

exports (exports minus imports) of goods and ser-

administrative records or based on the commodity

for permits and licenses. Expenditures of nonprofit

vices. Such expenditures are recorded in purchaser

flow method using data from production, trade, and

institutions serving households are included, even

prices and include net taxes on products.

construction activities. The quality of data on govern-

when reported separately. Household consumption

Because policymakers have tended to focus on

ment fixed capital formation depends on the quality

expenditure may include any statistical discrepancy

fostering the growth of output, and because data on

of government accounting systems (which tend to

in the use of resources relative to the supply of

production are easier to collect than data on spend-

be weak in developing countries). Measures of fixed

resources. •  General government final consump-

ing, many countries generate their primary estimate

capital formation by households and ­corporations—

tion expenditure is all government current expendi-

of GDP using the production approach. Moreover,

particularly capital outlays by small, unincorporated

tures for purchases of goods and services (including

many countries do not estimate all the components

enterprises—are usually unreliable.

compensation of employees). It also includes most

of national expenditures but instead derive some

Estimates of changes in inventories are rarely

expenditures on national defense and security but

of the main aggregates indirectly using GDP (based

complete but usually include the most important

excludes military expenditures with potentially wider

on the production approach) as the control total.

activities or commodities. In some countries these

public use that are part of government capital forma-

Household final consumption expenditure (private

estimates are derived as a composite residual along

tion. • Gross capital formation is outlays on addi-

consumption in the 1968 United Nations System of

with household final consumption expenditure.

tions to fixed assets of the economy, net changes in

National Accounts, or SNA) is often estimated as

According to national accounts conventions, adjust-

inventories, and net acquisitions of valuables. Fixed

a residual, by subtracting all other known expendi-

ments should be made for appreciation of the value

assets include land improvements (fences, ditches,

tures from GDP. The resulting aggregate may incor-

of inventory holdings due to price changes, but this

drains); plant, machinery, and equipment purchases;

porate fairly large discrepancies. When household

is not always done. In highly inflationary economies

and construction (roads, railways, schools, buildings,

consumption is calculated separately, many of the

this element can be substantial.

and so on). Inventories are goods held to meet tem-

estimates are based on household surveys, which

Data on exports and imports are compiled from

porary or unexpected fluctuations in production or

tend to be one-year studies with limited coverage.

customs reports and balance of payments data.

sales, and “work in progress.” • Exports and imports

Thus the estimates quickly become outdated and

Although the data from the payments side provide

of goods and services are the value of all goods and

must be supplemented by estimates using price- and

reasonably reliable records of cross-border transac-

other market services provided to or received from

quantity-based statistical procedures. Complicating

tions, they may not adhere strictly to the appropriate

the rest of the world. They include the value of mer-

the issue, in many developing countries the distinc-

definitions of valuation and timing used in the bal-

chandise, freight, insurance, transport, travel, royal-

tion between cash outlays for personal business

ance of payments or correspond to the change-of-

ties, license fees, and other services (communica-

and those for household use may be blurred. World

ownership criterion. This issue has assumed greater

tion, construction, financial, information, business,

Development Indicators includes in household con-

significance with the increasing globalization of inter-

personal, government services, and so on). They

sumption the expenditures of nonprofit institutions

national business. Neither customs nor balance of

exclude compensation of employees and investment

serving households.

payments data usually capture the illegal transac-

income (factor services in the 1968 SNA) and trans-

General government final consumption expenditure

tions that occur in many countries. Goods carried

fer payments. •  Gross savings are gross national

(general government consumption in the 1968 SNA)

by travelers across borders in legal but unreported

income less total consumption, plus net transfers.

includes expenditures on goods and services for

shuttle trade may further distort trade statistics.

individual consumption as well as those on services

Gross savings represent the difference between

for collective consumption. Defense expenditures,

disposable income and consumption and replace

including those on capital outlays (with certain excep-

gross domestic savings, a concept used by the World

tions), are treated as current spending.

Bank and included in World Development Indicators Data sources

Gross capital formation (gross domestic invest-

editions before 2006. The change was made to con-

ment in the 1968 SNA) consists of outlays on

form to SNA concepts and definitions. For further

Data on national accounts indicators for most

additions to the economy’s fixed assets plus net

discussion of the problems in compiling national

developing countries are collected from national

changes in the level of inventories. It is generally

accounts, see Srinivasan (1994), Heston (1994),

statistical organizations and central banks by vis-

obtained from industry reports of acquisitions and

and Ruggles (1994). For an analysis of the reliability

iting and resident World Bank missions. Data for

distinguishes only the broad categories of capital

of foreign trade and national income statistics, see

high-income economies are from Organisation for

formation. The 1993 SNA recognizes a third cat-

Morgenstern (1963).

Economic Co-operation and Development (OECD)

egory of capital formation: net acquisitions of valu-

data files.

ables. Included in gross capital formation under the

2011 World Development Indicators

225


4.9

Growth of consumption and investment Household final consumption expenditure

General government final consumption expenditure

Gross capital formation

Goods and services

average annual % growth average annual average annual Total Per capita Exports Imports % growth % growth 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 average annual % growth

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

226

.. 1.3 –0.1 .. 2.8 –0.5 3.2 1.7 2.0 2.6 –0.5 1.8 2.6 3.6 .. 3.9 3.7 –2.6 5.7 .. 6.0 3.1 2.6 .. 1.5 7.3 8.9 3.8 2.4 –1.1 .. 5.1 4.1 2.3 4.0 3.0 2.2 6.1 2.1 3.7 5.3 –5.0 0.6 3.6 1.8 1.6 –0.3 3.6 .. 1.9 .. 2.2 4.2 5.2 .. .. 3.0

.. 5.3 3.6 .. 4.7 8.8 3.9 1.4 14.0 4.5 11.2 1.2 2.3 3.4 .. 6.7 3.6 6.3 4.5 .. 8.2 4.5 3.4 –0.9 2.7 5.5 7.7 3.7 4.0 .. .. 4.2 .. 3.5 5.0 3.6 2.1 6.7 5.4 4.4 3.3 1.6 6.8 10.7 3.1 2.1 4.5 .. .. 0.3 .. 3.8 3.8 4.1 .. .. 5.2

2011 World Development Indicators

.. 2.2 –1.9 .. 1.5 1.1 2.0 1.4 1.0 0.6 –0.3 1.6 –0.7 1.4 .. 1.4 2.2 –2.0 2.8 .. 3.4 0.5 1.6 .. –1.7 5.6 7.7 2.0 0.6 –3.8 .. 2.5 0.9 3.0 3.5 3.0 1.8 4.2 0.3 1.7 4.1 –6.6 2.1 0.4 1.4 1.2 –3.1 –0.2 .. 1.6 .. 1.4 1.8 2.0 .. .. 0.6

.. 4.9 2.1 .. 3.7 8.7 2.4 0.9 12.9 2.8 11.7 0.6 –1.1 1.5 .. 5.2 2.4 6.9 1.1 .. 6.4 2.1 2.3 –2.7 –0.8 4.4 7.1 3.1 2.4 .. .. 2.4 .. 3.5 4.9 3.3 1.7 5.1 4.3 2.5 2.9 –2.2 7.1 7.9 2.7 1.4 2.5 .. .. 0.4 .. 3.4 1.3 2.1 .. .. 3.1

.. 14.5 3.6 .. 2.2 –1.5 2.9 2.7 –4.8 4.7 –1.9 1.6 4.4 3.6 .. 6.9 1.0 –8.0 2.9 .. 7.2 0.7 0.3 .. –8.3 3.7 9.6 3.7 10.9 –20.4 .. 2.0 0.8 1.7 –2.9 –0.9 2.4 7.0 –1.5 4.4 2.8 22.6 5.7 9.0 0.9 1.4 3.7 –2.2 .. 1.9 .. 2.1 5.1 –0.5 .. .. 2.0

.. 7.9 9.0 .. 3.6 10.9 3.2 1.6 23.0 8.8 0.0 1.6 8.3 3.5 .. 4.9 3.2 2.0 8.7 .. 11.4 2.8 2.7 –1.3 2.7 4.8 8.8 1.6 4.0 .. .. 2.7 3.1 2.9 7.6 2.2 1.8 4.9 4.2 2.7 1.5 1.2 2.2 0.7 1.6 1.7 2.1 .. .. 0.9 .. 3.1 3.0 0.3 .. .. 6.6

.. 25.8 –0.6 .. 7.4 –1.9 5.1 2.3 41.6 9.2 –7.5 2.4 12.2 8.5 .. 5.3 4.2 –5.3 3.1 .. 10.3 0.4 4.6 .. 4.0 9.3 10.8 4.8 2.1 2.6 .. 5.1 8.1 7.2 0.7 4.6 5.7 11.7 –0.6 5.8 7.1 19.1 0.5 6.5 3.2 1.8 3.0 1.9 .. 1.1 .. 4.1 6.1 0.1 .. 9.0 6.9

.. 6.1 8.8 .. 11.1 18.3 7.6 1.2 19.3 7.8 18.8 3.0 7.7 3.9 5.3 3.0 4.0 13.5 9.0 .. 14.2 4.4 4.7 –0.1 –2.4 7.7 13.9 2.2 9.8 .. .. 5.8 2.5 9.2 8.8 2.9 1.3 1.7 7.8 7.3 0.7 –1.0 14.6 11.3 2.0 1.8 5.6 .. .. –0.1 .. 1.9 0.5 –0.5 .. 1.5 3.9

.. 18.9 3.2 .. 8.7 –18.4 7.7 5.8 5.7 13.1 –4.8 5.3 1.8 4.5 .. 4.9 5.9 4.3 4.4 .. 21.7 3.2 8.7 .. 2.3 9.4 15.5 7.8 5.0 –0.5 .. 10.9 1.9 6.3 –9.0 8.7 5.0 8.3 5.3 3.5 13.4 –2.5 11.0 7.1 10.3 6.9 2.1 0.1 .. 6.0 .. 7.6 6.1 0.3 .. 10.1 1.6

.. 9.8 2.3 .. 6.3 5.0 2.2 4.7 23.0 11.5 5.7 2.8 2.7 7.7 9.0 2.8 7.1 7.9 10.9 .. 15.2 –0.4 –0.4 –3.6 33.6 5.6 20.2 9.7 5.7 6.5 .. 6.9 2.4 3.8 12.2 10.5 3.4 1.1 6.1 16.8 2.9 –6.3 6.7 10.1 4.5 1.4 –2.0 1.1 .. 5.9 .. 2.9 2.1 2.3 .. 4.4 5.1

.. 15.7 –1.0 .. 15.6 –12.7 7.6 4.8 14.1 9.7 –8.7 5.0 2.1 6.0 .. 4.9 11.6 2.9 1.9 .. 14.8 5.1 7.1 .. –1.8 11.7 16.7 8.4 9.3 –2.4 .. 9.2 8.2 4.9 –2.9 12.0 6.0 9.9 2.8 3.0 11.6 7.5 12.0 5.8 6.7 5.7 0.1 0.1 .. 5.8 .. 7.4 9.2 –1.1 .. 19.4 3.8

.. 13.7 7.8 .. 9.2 8.6 9.2 3.9 19.7 8.8 10.9 2.9 1.8 5.6 2.6 4.8 7.5 10.5 7.2 .. 14.8 3.8 3.3 –3.9 –3.7 10.5 16.9 7.8 9.7 16.3 .. 5.4 3.9 5.7 10.1 9.1 5.3 2.4 8.7 14.4 3.3 –3.7 7.4 16.5 5.1 3.3 3.8 1.3 .. 4.7 .. 2.7 2.1 0.5 .. 2.1 5.4


Household final consumption expenditure

General government final consumption expenditure

Gross capital formation

4.9

economy

Growth of consumption and investment

Goods and services

average annual % growth average annual average annual Total Per capita Exports Imports % growth % growth 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 average annual % growth

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

–0.1 4.8 6.6 3.2 .. 5.6 5.0 1.6 .. 1.4 4.9 –7.5 3.6 .. 4.9 .. 4.5 –4.8 .. –3.9 –0.2 1.8 .. .. 5.3 2.2 2.2 5.4 5.3 3.0 .. 5.1 3.9 9.9 .. 1.8 5.8 .. 4.8 .. 3.1 3.2 6.1 .. .. 3.5 5.4 4.9 6.4 2.5 2.6 4.0 3.7 5.2 3.0 .. ..

3.8 6.9 4.3 7.4 .. 3.7 3.4 0.6 .. 1.0 7.5 9.3 4.0 .. 3.0 .. .. 9.9 –7.8 8.0 .. 9.5 .. .. 9.7 4.8 2.2 .. 7.5 0.9 7.4 5.6 3.2 7.9 .. 4.7 6.2 .. 5.7 .. 0.6 3.4 3.7 .. .. 3.7 .. 4.6 7.2 .. 3.0 5.2 5.1 3.7 1.5 .. ..

0.1 2.9 5.0 1.6 .. 4.7 2.5 1.5 .. 1.1 1.1 –6.4 0.6 .. 3.9 .. 0.6 –5.8 .. –2.7 –1.9 0.1 .. .. 6.1 1.7 –0.8 3.2 2.6 1.0 .. 3.9 2.2 10.0 .. 0.3 2.6 .. 2.3 .. 2.5 2.0 3.9 .. .. 3.0 2.6 2.3 4.2 –0.2 0.3 2.2 1.5 5.1 2.7 .. ..

4.1 5.4 2.9 5.8 .. 1.8 1.5 –0.1 .. 0.9 5.0 8.5 1.3 .. 2.6 .. .. 9.0 –9.4 8.6 .. 8.4 .. .. 10.3 4.6 –0.7 .. 5.6 –1.5 4.5 4.7 2.1 8.2 .. 3.5 3.6 .. 3.7 .. 0.3 2.0 2.3 .. .. 2.9 .. 2.2 5.4 .. 1.1 3.9 3.1 3.7 1.1 .. ..

0.9 6.6 0.1 1.6 .. 4.1 2.7 –0.2 .. 2.9 4.7 –7.1 6.9 .. 4.7 .. –2.4 –7.2 .. 1.8 10.9 8.1 .. .. 1.9 –0.4 0.0 –4.4 4.8 3.2 .. 3.6 1.8 –12.4 .. 3.9 3.2 .. 3.3 .. 2.0 2.4 –1.5 .. .. 2.7 2.4 0.7 1.7 2.5 2.5 5.2 3.8 3.7 2.9 .. ..

1.3 5.7 8.2 3.6 .. 4.3 1.4 1.6 .. 1.6 6.7 7.8 2.3 .. 4.9 .. .. 4.2 9.7 2.1 .. 6.4 .. .. 4.3 0.0 5.5 .. 7.9 .. 3.1 3.8 0.8 5.9 .. 3.8 –4.6 .. 4.5 .. 3.2 4.1 2.7 .. .. 2.4 .. 8.3 3.6 .. 3.3 5.2 3.1 4.2 1.5 .. ..

9.6 6.9 –0.6 –0.1 .. 9.9 2.0 1.6 .. –0.8 0.3 –19.0 6.1 .. 3.4 .. 1.0 –1.1 .. –3.7 –5.8 0.2 .. .. 11.1 3.6 3.3 –8.4 5.3 0.4 .. 4.8 4.7 –15.5 .. 2.5 8.6 .. 7.3 .. 4.4 6.1 11.3 .. .. 6.0 4.0 1.8 10.4 1.9 0.7 7.4 4.1 10.6 5.9 .. ..

1.3 13.4 5.9 8.3 .. 1.5 2.3 0.3 .. –0.9 6.7 17.2 9.0 .. 3.1 .. .. 3.8 15.2 16.4 6.3 –0.5 .. .. 13.6 4.7 14.1 .. 2.1 6.2 23.8 5.3 0.4 9.8 .. 8.9 5.9 .. 9.4 .. 1.1 3.7 2.1 .. .. 5.0 .. 6.3 10.2 .. 3.0 10.5 1.3 5.9 –1.8 .. ..

9.9 12.3 5.9 1.2 .. 15.7 10.9 5.9 .. 4.3 2.6 –1.9 1.0 .. 16.0 .. –1.6 –1.6 .. 4.3 18.6 10.3 .. .. 4.9 4.2 3.8 4.0 12.0 9.9 –1.3 5.6 14.6 0.7 .. 5.9 13.1 .. 3.8 .. 7.3 5.2 9.3 .. .. 5.5 6.2 1.7 –0.4 5.1 3.1 8.5 7.8 11.3 5.7 1.6 ..

11.2 16.0 7.8 5.0 .. 4.2 5.9 0.4 .. 5.5 5.7 5.9 6.6 .. 10.6 .. .. 5.1 –7.6 7.1 10.2 10.0 .. .. 11.2 2.4 6.7 .. 5.3 6.3 –2.1 2.0 4.3 9.1 .. 6.4 16.0 .. 6.0 .. 4.1 2.2 8.3 .. .. 0.7 .. 7.1 7.8 .. 7.0 7.8 5.2 9.0 3.3 .. ..

11.4 14.4 5.7 –6.8 .. 14.5 7.6 4.4 .. 4.3 1.5 –12.7 9.4 .. 10.0 .. 0.8 –8.2 .. 7.6 –1.1 2.7 .. .. 7.5 7.5 4.1 –1.1 10.3 3.5 0.6 5.1 12.3 5.6 .. 5.1 7.6 .. 5.4 .. 7.6 6.2 12.2 .. .. 5.8 5.9 2.5 1.2 3.4 2.9 9.0 7.8 16.7 7.6 4.5 ..

2011 World Development Indicators

10.0 16.5 8.6 13.2 .. 3.9 3.8 1.2 .. 2.5 6.9 5.6 8.3 .. 8.3 .. .. 16.0 –7.2 8.0 6.3 12.2 .. .. 14.0 4.0 9.3 .. 6.1 3.9 14.1 2.3 4.7 11.1 .. 8.3 6.2 .. 9.5 .. 3.8 4.5 5.1 .. .. 5.0 .. 7.3 6.9 .. 6.0 9.5 2.9 8.0 2.7 .. ..

227


4.9

Growth of consumption and investment Household final consumption expenditure

General government final consumption expenditure

Gross capital formation

Goods and services

average annual % growth average annual average annual Total Per capita Exports Imports % growth % growth 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09 average annual % growth

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzaniaa Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

1.3 –0.9 .. .. 2.6 .. .. .. 6.0 3.9 .. 2.9 2.4 .. 3.7 7.3 1.5 1.1 3.0 –11.8 5.1 3.7 .. 5.0 0.7 4.3 3.8 .. 6.7 –6.9 7.1 3.0 3.7 5.0 .. 0.6 5.4 5.3 3.2 2.4 .. 3.0 w 2.9 4.1 5.7 3.0 4.0 7.4 0.5 3.6 2.8 4.6 3.3 2.8 2.0

6.2 9.9 .. 5.3 5.3 3.3 .. .. 5.3 3.2 .. 4.6 2.8 .. 5.9 2.0 2.2 1.4 7.5 6.1 6.2 4.0 .. 0.5 13.3 5.3 5.3 .. 1.9 12.1 .. 2.1 2.4 2.9 .. 8.7 7.8 –1.5 .. 0.1 .. 2.7 w 4.5 5.7 6.6 5.0 5.7 6.9 7.6 4.1 5.3 6.4 4.9 2.0 1.4

a. Covers mainland Tanzania only.

228

2011 World Development Indicators

1.7 –0.7 .. .. –0.2 .. .. .. 5.8 4.0 .. 0.6 2.0 .. 1.1 4.9 1.1 0.5 0.3 –13.1 2.0 2.7 .. 2.0 0.1 2.6 2.1 .. 3.3 –6.4 1.2 2.8 2.5 4.3 .. –1.5 3.9 1.1 –0.7 –0.5 .. 1.6 w 0.5 2.6 4.1 1.8 2.4 6.1 0.4 2.0 0.6 2.6 0.6 2.1 1.6

6.7 10.3 .. 2.9 2.5 3.6 .. .. 5.2 3.0 .. 3.4 1.2 .. 3.7 1.0 1.7 0.6 4.6 4.8 3.3 3.1 .. –2.1 12.9 4.3 3.9 .. –1.3 12.9 .. 1.5 1.4 2.8 .. 6.8 6.4 –4.9 .. –2.1 .. 1.5 w 2.2 4.5 5.3 4.1 4.3 6.0 7.5 2.9 3.3 4.8 2.4 1.3 0.8

0.8 –2.2 .. .. 0.9 .. .. .. 1.8 2.2 .. 0.3 2.7 10.5 5.5 7.1 0.7 0.5 2.0 –15.7 –8.8 5.1 .. 0.0 0.3 4.1 4.6 .. 7.7 –4.1 6.8 1.0 0.7 2.3 .. 3.7 3.2 12.7 1.7 –8.1 .. 1.7 w –1.3 3.3 6.6 1.4 3.3 8.0 –0.8 1.9 3.5 5.9 0.3 1.5 1.5

4.3 2.1 .. 7.6 –0.6 4.5 .. .. 3.3 3.2 .. 5.0 5.1 .. 8.4 6.0 0.9 1.2 8.4 1.6 13.5 5.3 .. 1.3 4.3 4.4 4.0 .. 4.0 2.6 .. 2.2 2.1 1.3 .. 7.0 7.7 1.3 .. 24.9 .. 2.6 w 6.8 5.4 7.4 3.7 5.5 8.4 3.3 3.3 3.6 6.1 5.1 2.1 1.9

–5.1 –19.1 .. .. 3.5 .. .. .. 7.7 10.4 .. 4.7 3.2 6.9 22.0 –4.7 2.0 0.7 3.3 –17.6 –1.1 –4.0 .. –0.1 12.5 3.6 4.7 .. 9.2 –18.5 5.5 4.7 7.6 6.1 –2.5 11.0 19.8 9.2 11.4 3.9 .. 3.3 w 5.5 2.6 6.3 –0.5 2.7 7.8 –11.2 5.4 1.2 6.5 4.6 3.4 2.2

11.5 9.0 .. 11.4 9.6 18.3 .. .. 7.8 7.5 .. 9.1 3.3 .. 11.2 –0.3 3.3 0.4 –0.4 7.3 12.8 4.8 .. 5.9 4.2 2.9 6.9 1.6 12.0 5.1 .. 1.6 0.0 6.6 4.7 11.2 12.3 –3.0 .. 6.6 .. 3.1 w 8.7 9.9 12.2 6.3 9.9 12.4 9.1 5.0 7.4 12.4 8.5 0.8 1.2

8.1 0.8 .. .. 4.1 .. .. .. 9.6 1.7 .. 5.8 10.5 7.5 11.6 6.4 8.6 4.1 12.0 –5.3 11.7 9.5 .. 1.2 6.9 5.1 11.1 –2.4 15.4 –3.6 5.5 6.5 7.3 6.0 2.5 1.0 19.2 8.7 16.6 6.7 3.9 7.0 w 5.5 7.5 9.3 6.3 7.4 11.8 1.8 8.1 4.0 10.0 .. 6.9 6.8

9.6 7.1 .. 6.9 4.0 10.5 .. .. 11.0 9.1 .. 2.7 2.9 .. 14.3 5.2 4.6 4.7 6.5 9.5 11.6 5.8 .. 6.0 5.8 4.1 6.4 22.4 19.5 1.1 .. 3.1 4.5 7.8 4.9 –2.0 11.4 –3.1 .. 21.9 –10.7 5.9 w 9.7 10.4 14.7 5.5 10.4 14.5 7.2 5.0 7.7 14.6 .. 4.6 3.8

6.0 –6.1 .. .. 2.0 .. .. .. 12.4 5.2 .. 7.1 9.4 8.6 8.4 6.2 6.4 4.3 4.4 –6.0 4.7 4.5 .. 1.1 9.9 3.8 10.8 7.2 9.7 –6.6 6.4 6.8 9.8 9.9 –0.4 8.2 19.5 7.5 8.3 15.5 3.1 7.0 w 5.3 6.4 8.3 5.1 6.4 10.9 –2.3 10.4 0.0 11.2 5.7 7.2 6.3

13.5 15.9 .. 16.9 7.8 10.7 .. .. 9.6 8.9 .. 8.1 4.7 .. 12.0 4.7 4.2 3.6 11.3 10.6 15.9 5.7 .. 3.1 9.5 3.6 8.8 15.2 11.2 5.2 .. 3.4 3.3 6.4 4.2 13.8 13.6 –2.3 .. 15.6 –5.8 5.7 w 9.4 10.7 12.9 8.5 10.7 12.6 11.9 6.7 9.9 14.8 8.8 4.3 3.8


About the data

4.9

economy

Growth of consumption and investment Definitions

Measures of growth in consumption and capital for-

the change in government employment. Neither

• Household final consumption expenditure is the

mation are subject to two kinds of inaccuracy. The

technique captures improvements in productivity

market value of all goods and services, including

first stems from the difficulty of measuring expendi-

or changes in the quality of government services.

durable products (such as cars and computers),

tures at current price levels, as described in About

Deflators for household consumption are usually cal-

purchased by households. It excludes purchases

the data for table 4.8. The second arises in deflat-

culated on the basis of the consumer price index.

of dwellings but includes imputed rent for owner-

ing current price data to measure volume growth,

Many countries estimate household consumption

occupied dwellings. It also includes government fees

where results depend on the relevance and reliabil-

as a residual that includes statistical discrepancies

for permits and licenses. Expenditures of nonprofit

ity of the price indexes and weights used. Measur-

associated with the estimation of other expenditure

institutions serving households are included, even

ing price changes is more difficult for investment

items, including changes in inventories; thus these

when reported separately. Household consumption

goods than for consumption goods because of the

estimates lack detailed breakdowns of household

expenditure may include any statistical discrepancy

one-time nature of many investments and because

consumption expenditures.

in the use of resources relative to the supply of

the rate of technological progress in capital goods

resources. • Household final consumption expen-

makes capturing change in quality difficult. (An

diture per capita is household final consumption

example is c­ omputers—prices have fallen as qual-

expenditure divided by midyear population. • Gen-

ity has improved.) Several countries estimate capital

eral government final consumption expenditure is

formation from the supply side, identifying capital

all government current expenditures for goods and

goods entering an economy directly from detailed

services (including compensation of employees). It

production and international trade statistics. This

also includes most expenditures on national defense

means that the price indexes used in deflating pro-

and security but excludes military ­expenditures with

duction and international trade, reflecting delivered

potentially wider public use that are part of govern-

or offered prices, will determine the deflator for capi-

ment capital formation. • Gross capital formation is

tal formation expenditures on the demand side.

outlays on additions to fixed assets of the economy,

Growth rates of household final consumption

net changes in inventories, and net acquisitions

expenditure, household final consumption expen-

of valuables. Fixed assets include land improve-

diture per capita, general government final con-

ments (fences, ditches, drains); plant, machinery,

sumption expenditure, gross capital formation, and

and equipment purchases; and construction (roads,

exports and imports of goods and services are esti-

railways, schools, buildings, and so on). Inventories

mated using constant price data. (Consumption, cap-

are goods held to meet temporary or unexpected

ital formation, and exports and imports of goods and

fluctuations in production or sales, and “work in prog-

services as shares of GDP are shown in table 4.8.)

ress.” • Exports and imports of goods and services

To obtain government consumption in constant

are the value of all goods and other market services

prices, countries may deflate current values by

provided to or received from the rest of the world.

applying a wage (price) index or extrapolate from

They include the value of merchandise, freight, insurance, transport, travel, royalties, license fees, and

4.9a

GDP per capita is still lagging in some regions

other services (communication, construction, financial, information, business, personal, government

GDP per capita (2000 $) 5,000

services, and so on). They exclude compensation of Latin America & Caribbean

employees and investment income (factor services in the 1968 System of National Accounts) and transfer

4,000

payments. 3,000 Europe & Central Asia

2,000

Middle East & North Africa

Data sources

East Asia & Pacific

1,000

South Asia

Data on national accounts indicators for most

Sub-Saharan Africa

0 1990

1995

2000

2005

developing countries are collected from national 2009

statistical organizations and central banks by visiting and resident World Bank missions. Data for

Although GDP per capita has more than tripled in East Asia and Pacific between 1990 and 2009,

high-income economies are from Organisation for

it is still less than GDP per capita in Latin America and Carribean and in Europe and Central Asia.

Economic Co-operation and Development (OECD)

Source: World Development Indicators data files.

data files.

2011 World Development Indicators

229


4.10

Toward a broader measure of national income Gross domestic product

$ billions 2009

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

230

14.5 12.0 140.6 75.5 307.2 8.7 924.8 381.1 43.0 89.4 49.0 471.2 6.7 17.3 17.0 11.8 1,594.5 48.7 8.1 1.3 9.9 22.2 1,336.1 2.0 6.8 163.7 4,985.5 210.6 234.0 10.6 9.6 29.2 23.3 63.0 62.7 190.3 309.6 46.8 57.2 188.4 21.1 1.9 19.1 28.5 238.0 2,649.4 11.1 0.7 10.7 3,330.0 26.2 329.9 37.3 4.1 0.8 6.5 14.3

2011 World Development Indicators

Gross national income

$ billions 2009

10.6 11.9 139.6 67.5 297.7 8.9 900.7 377.1 40.3 97.5 47.9 475.0 6.6 16.7 17.4 11.3 1,562.4 46.6 8.0 1.3 9.4 22.1 1,317.3 2.0 6.1 153.4 5,028.8 216.9 224.5 9.8 6.9 28.8 22.4 60.5 61.8 178.1 318.3 45.0 56.1 188.6 20.4 1.9 18.5 28.5 238.1 2,671.2 9.5 0.7 10.6 3,377.0 25.9 320.8 36.1 3.7 0.8 .. 13.8

Adjustments

Consumption of fixed capital % of GNI 2009

Natural resource depletion % of GNI 2009

7.7 10.5 10.5 11.7 11.8 9.7 14.4 14.3 11.5 6.8 11.1 14.0 7.9 9.5 10.4 11.5 11.8 11.7 7.4 5.5 8.1 8.6 14.2 7.2 9.9 12.6 10.2 13.6 11.3 5.9 13.6 11.3 8.8 12.9 .. 13.6 16.5 11.1 10.7 9.6 10.5 6.8 12.8 6.7 17.0 14.2 13.2 7.5 8.8 13.8 8.6 13.9 10.1 7.7 7.4 .. 9.6

3.4 1.3 16.9 29.1 4.9 0.5 5.1 0.1 32.7 2.6 0.9 0.0 1.2 11.2 .. 2.8 3.1 1.1 1.6 10.6 0.2 4.8 2.3 0.0 25.2 10.0 3.1 0.0 6.2 10.7 50.6 0.2 3.1 0.8 3.3 0.3 1.5 0.5 9.9 7.3 0.5 0.8 0.7 4.5 0.1 0.0 29.2 1.0 0.1 0.1 6.9 0.2 1.2 6.6 0.0 .. 0.4

Adjusted net national income

Gross domestic product

Gross national income

Adjusted net national income

$ billions 2009

% growth 2000–2009

% growth 2000–2009

% growth 2000–2009

9.5 10.5 101.2 40.0 248.2 8.0 725.2 322.8 22.5 88.3 42.2 408.7 6.0 13.2 .. 9.7 1,330.0 40.7 7.3 1.1 8.6 19.1 1,100.4 1.8 4.1 118.8 4,355.8 188.5 185.3 8.2 2.5 25.5 19.7 52.2 52.8 153.3 261.1 39.8 44.5 156.9 18.2 1.7 16.0 25.3 197.6 2,292.1 5.5 0.6 9.6 2,908.2 19.7 275.8 32.0 3.2 0.8 .. 12.4

.. 5.4 4.0 13.1 5.4 10.5 3.3 2.0 17.9 5.9 8.4 1.7 4.0 4.1 5.0 4.4 3.6 5.4 5.4 3.0 9.0 3.3 2.1 0.8 10.2 4.1 10.9 4.7 4.5 5.2 4.0 5.1 0.8 3.9 6.7 4.1 1.2 5.5 5.0 4.9 2.6 0.2 5.9 8.5 2.5 1.5 2.1 5.2 7.4 1.0 5.8 3.6 3.7 3.0 1.0 0.7 4.9

.. 5.8 3.7 .. 5.1 10.5 3.6 1.9 19.4 5.3 8.6 1.9 3.9 4.3 5.9 4.2 3.4 6.1 6.0 .. 9.3 2.7 1.9 –0.9 20.2 5.0 10.6 4.4 4.7 5.5 .. 4.6 0.6 4.0 6.6 4.6 0.7 5.4 4.5 5.0 2.7 1.4 6.1 8.4 2.4 1.5 2.6 5.4 .. 0.6 .. 4.1 3.8 4.1 .. .. 4.8

.. 7.3 4.9 .. 5.4 11.4 3.3 2.0 19.8 5.9 10.6 1.3 3.6 3.0 .. 3.0 3.6 4.9 5.5 .. 10.2 4.4 2.9 –1.2 –5.5 4.9 9.9 4.2 4.3 7.5 .. 4.0 0.6 5.2 6.7 4.6 2.0 5.1 5.2 2.8 2.3 4.0 6.7 10.3 1.7 1.4 3.3 3.6 .. 1.4 .. 3.0 3.2 0.9 .. .. 3.0


Gross domestic product

$ billions 2009

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

129.0 1,377.3 540.3 331.0 65.8 227.2 195.4 2,112.8 12.1 5,069.0 25.1 115.3 29.4 .. 832.5 5.4 148.0 4.6 5.9 26.2 34.5 1.6 0.9 62.4 37.2 9.2 8.6 4.7 193.1 9.0 3.0 8.6 874.8 5.4 4.2 91.4 9.8 .. 9.3 12.5 792.1 126.7 6.1 5.4 173.0 381.8 46.1 162.0 24.7 7.9 14.2 130.3 161.2 430.1 232.9 .. 98.3

Gross national income

$ billions 2009

121.2 1,369.3 478.4 328.6 61.8 184.4 190.8 2,076.3 11.4 5,228.3 25.7 103.4 29.3 .. 836.9 5.6 158.1 4.4 5.8 28.1 35.4 1.9 0.6 62.0 37.2 9.0 8.5 4.7 188.9 9.0 3.0 8.9 860.2 5.7 4.0 89.5 9.7 .. 9.2 12.8 773.9 121.4 5.9 5.3 162.9 376.4 58.1 166.4 23.1 7.8 14.0 122.6 161.1 416.1 225.1 .. ..

Adjustments

Consumption of fixed capital % of GNI 2009

Natural resource depletion % of GNI 2009

13.0 8.6 10.9 10.7 10.1 17.7 13.6 14.0 11.2 13.5 10.3 12.7 7.4 .. 13.3 .. 5.2 8.4 8.4 11.3 11.2 6.4 8.2 11.9 12.0 10.9 7.3 7.4 11.6 7.7 8.1 10.9 11.7 8.5 9.5 10.1 7.1 .. 10.6 6.8 14.6 14.1 8.8 2.9 9.0 15.2 13.5 8.0 12.1 8.6 9.7 11.3 8.0 12.4 17.2 .. ..

0.2 4.2 6.5 17.9 45.7 0.1 0.2 0.1 0.7 0.0 1.1 22.0 1.2 .. 0.0 .. 37.0 0.5 0.0 0.3 0.0 1.4 11.0 30.5 0.2 0.1 0.2 0.9 7.9 0.0 18.8 0.0 5.4 0.2 11.1 1.4 3.8 .. 0.3 4.2 0.8 0.9 0.8 1.2 15.0 10.6 37.8 3.1 0.0 19.9 0.0 5.9 1.0 1.0 0.1 .. ..

4.10

economy

Toward a broader measure of national income Adjusted net national income

Gross domestic product

Gross national income

Adjusted net national income

$ billions 2009

% growth 2000–2009

% growth 2000–2009

% growth 2000–2009

105.2 1,194.1 395.3 234.7 27.4 151.8 164.4 1,784.1 10.1 4,521.8 22.8 67.6 26.8 .. 725.3 .. 91.3 4.0 5.3 24.8 31.4 1.8 0.5 35.8 32.7 8.0 7.9 4.3 152.3 8.3 2.2 7.9 713.2 5.2 3.1 79.2 8.6 .. 8.2 11.4 654.9 103.3 5.3 5.1 123.8 279.2 28.3 147.8 20.3 5.6 12.6 101.6 168.2 360.4 186.1 .. ..

2.9 7.9 5.3 5.4 –0.3 3.9 3.6 0.5 1.5 1.1 6.9 8.8 4.4 .. 4.2 4.8 8.4 4.6 6.9 6.2 4.6 3.1 0.0 5.4 6.3 3.1 3.6 4.8 5.1 5.3 4.7 3.7 2.2 5.6 7.4 5.0 7.9 .. 5.3 3.7 1.7 2.5 3.3 4.3 6.6 2.1 4.5 5.2 6.9 3.4 3.4 6.0 4.9 4.4 0.8 .. 14.2

4.0 7.8 5.1 6.2 .. 3.8 2.6 0.6 .. 0.8 6.7 9.9 4.2 .. 4.1 .. .. 4.3 6.6 6.0 3.9 0.8 .. .. 8.1 3.2 3.5 .. 4.5 5.9 3.2 3.3 2.1 5.0 .. 4.8 7.7 .. 5.7 .. 2.1 2.6 3.0 .. .. 2.2 .. 4.8 7.2 .. 3.7 6.7 4.1 4.7 1.0 .. ..

2011 World Development Indicators

3.1 7.5 3.0 6.7 .. 2.4 4.4 0.4 .. 1.5 6.9 9.1 5.1 .. 3.3 .. .. 4.8 1.0 8.2 4.7 8.9 .. .. 9.3 2.9 2.3 .. 7.2 5.7 5.1 2.2 1.5 6.1 .. 4.4 6.3 .. 6.1 .. 1.3 2.8 2.5 .. .. 3.7 .. 4.7 6.7 .. 3.3 5.2 4.3 4.2 0.5 .. ..

231


4.10

Toward a broader measure of national income Gross domestic product

$ billions 2009

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzaniaa Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

161.1 1,231.9 5.2 375.8 12.8 43.0 1.9 182.2 87.6 48.5 .. 285.4 1,460.3 42.0 54.7 3.0 406.1 491.9 52.2 5.0 21.4 263.8 0.6 2.9 21.2 39.6 614.6 19.9 16.0 113.5 230.3 2,174.5 14,119.0 31.5 32.1 326.1 90.1 .. 26.4 12.8 5.6 58,252.1 w 431.5 16,206.0 8,880.2 7,318.4 16,649.8 6,346.0 2,591.7 4,017.9 1,062.4 1,700.3 945.9 41,607.7 12,465.3

a. Covers mainland Tanzania only.

232

2011 World Development Indicators

Gross national income

$ billions 2009

164.1 1,192.4 5.2 384.4 12.8 42.3 1.9 179.2 84.7 47.3 .. 279.0 1,430.2 41.5 49.3 2.9 413.4 512.3 50.9 4.9 21.4 252.0 2.9 2.8 20.7 37.3 606.9 19.2 15.7 111.1 .. 2,218.1 14,011.0 30.8 32.5 323.5 85.2 .. 24.9 11.4 5.2 57,867.2 w 433.8 16,112.0 8,952.6 7,173.2 16,558.2 6,307.5 2,521.8 3,921.9 1,192.9 1,702.0 904.2 41,369.3 12,368.9

Adjustments

Consumption of fixed capital % of GNI 2009

11.2 12.0 7.4 12.6 8.4 .. 6.8 14.1 13.0 13.5 .. 14.1 13.9 9.5 9.7 10.2 13.3 14.1 9.9 7.9 7.3 10.9 1.2 7.0 12.9 11.0 11.7 10.8 7.4 9.9 .. 13.5 14.3 12.0 8.4 12.2 8.8 .. 9.0 9.3 .. 13.1 w 7.2 10.7 9.9 11.8 10.7 10.3 11.7 11.7 10.4 8.4 10.6 14.1 14.2

Natural resource depletion % of GNI 2009

1.3 14.5 2.4 28.9 0.3 .. 2.1 0.0 0.3 0.2 .. 5.4 0.0 0.5 11.1 0.1 0.2 0.0 10.2 0.2 2.5 3.2 .. 3.6 28.2 4.6 0.2 .. 4.7 3.8 .. 1.2 0.7 0.4 17.8 9.8 7.2 .. 13.2 11.5 3.5 2.4 w 3.8 5.8 4.5 7.5 5.8 3.6 9.2 4.8 14.8 3.9 9.3 1.0 0.1

Adjusted net national income

Gross domestic product

Gross national income

Adjusted net national income

$ billions 2009

% growth 2000–2009

% growth 2000–2009

% growth 2000–2009

5.6 6.0 7.6 3.8 4.3 5.0 9.5 6.5 5.8 3.8 .. 4.1 2.8 5.5 7.3 2.6 2.4 1.9 4.4 8.2 7.1 4.6 2.4 2.5 7.4 4.9 4.9 13.9 7.8 5.6 7.0 2.0 2.0 3.4 6.9 4.9 7.6 –0.9 3.9 5.4 –7.5 2.9 w 5.4 6.4 8.5 4.4 6.4 9.4 5.9 3.8 4.7 7.3 5.1 2.0 1.5

5.4 6.1 .. 3.4 4.1 5.3 .. .. 6.1 4.7 .. 4.1 2.9 .. 7.5 3.2 2.0 2.6 4.0 7.8 6.9 4.8 .. 2.3 8.3 5.0 4.8 14.0 7.8 5.6 .. 1.8 2.2 3.7 5.0 4.6 8.0 0.2 .. 7.4 –7.2 2.8 w 5.6 6.4 8.4 4.3 6.3 9.2 5.9 3.7 4.9 7.3 4.5 1.9 1.4

7.2 8.4 .. 6.2 .. .. .. .. 5.6 4.4 .. 3.8 2.7 .. 5.7 1.7 2.5 1.5 6.3 5.5 6.4 4.4 .. 3.0 5.7 3.7 4.0 .. 7.5 8.1 .. 2.1 1.4 2.8 –6.4 8.6 7.0 .. .. 5.3 –9.0 2.6 w 5.6 6.2 7.8 4.7 6.2 8.6 6.8 3.8 5.0 7.0 4.2 1.7 1.4

143.5 876.2 4.7 226.8 11.7 .. 1.7 154.0 73.4 40.8 .. 224.6 1,231.5 37.3 39.0 2.6 357.4 440.2 40.7 4.5 19.3 216.6 .. 2.5 12.2 31.5 534.7 .. 13.8 95.9 .. 1,892.3 11,909.0 27.0 24.0 252.4 71.5 .. 19.4 9.1 4.6 48,996.8 w 383.4 13,495.7 7,727.3 5,782.6 13,887.1 5,456.9 1,977.5 3,277.5 945.9 1,492.3 722.6 35,134.3 10,599.8


About the data

4.10

Definitions

An economy’s growth is typically measured by the

control of institutional units. The calculation of

• Gross domestic product is the sum of value

change in the volume of its output, as shown in table

adjusted net national income, which accounts for

added by all resident producers plus any product

4.1. However the widely tracked gross domestic prod-

net forest, energy, and mineral depletion, thus

taxes (less subsidies) not included in the valu-

uct (GDP) may not always be the most relevant sum-

remains within the SNA boundaries. This point is

ation of output. • Gross national income is GDP

mary of aggregated economic performance for all

critical because it allows for comparisons across

plus net receipts of primary income (compensation

economies, such as when production occurs at the

GDP, GNI, and adjusted net national income; such

of employees and property income) from abroad.

expense of consuming capital stock. For countries

comparisons reveal the impact of natural resource

• Consumption of fixed capital is the replacement

with significant exhaustible natural resources and

depletion, which is otherwise ignored by the popular

value of capital used up in production. • Natural

important foreign-investor presence, adjusted net

economic indicators.

resource depletion is the sum of net forest deple-

Adjusted net national income is particularly useful

tion, energy depletion, and mineral depletion. Net for-

in monitoring low-income, resource-rich economies,

est depletion is unit resource rents times the excess

The table presents three measures of economic

like many countries in Sub-Saharan Africa, because

of roundwood harvest over natural growth. Energy

progress: GDP, gross national income (GNI), and

such economies often see large natural resources

depletion is the ratio of the value of the stock of

adjusted net national income. GDP accounts for

depletion as well as substantial exports of resource

energy resources to the remaining reserve lifetime

all domestic production, regardless of whether the

rents to foreign mining companies. For recent years

(capped at 25 years). It covers coal, crude oil, and

income accrues to domestic or foreign institutions.

adjusted net national income gives a picture of eco-

natural gas. Mineral depletion is the ratio of the value

GNI accounts for the operation of foreign inves-

nomic growth that is strikingly different from the one

of the stock of mineral resources to the remaining

tors, who may be repatriating some of the income

provided by GDP.

reserve lifetime (capped at 25 years). It covers tin,

national income complements GDP in assessing economic progress (Hamilton and Ley 2010).

produced domestically. GNI comprises GDP plus

The key to increasing future consumption and

gold, lead, zinc, iron, copper, nickel, silver, bauxite,

net receipts of primary income from nonresident

thus the standard of living lies in increasing national

and phosphate. • Adjusted net national income is

sources. Adjusted net national income goes a step

wealth—including not only the traditional measures

GNI minus consumption of fixed capital and natural

further by subtracting from GNI a charge for the con-

of capital (such as produced and human capital),

resources depletion.

sumption of fixed capital (a calculation that yields

but also natural capital. Natural capital comprises

net national income) and for the depletion of natural

such assets as land, forests, and subsoil resources.

resources. The deduction for the depletion of natural

All three types of capital are key to sustaining eco-

resources, which covers net forest depletion, energy

nomic growth. By accounting for the consumption

depletion, and mineral depletion, reflects the decline

of fixed and natural capital depletion, adjusted net

in asset values associated with the extraction and

national income better measures the income avail-

harvest of natural resources. For more discussion

able for consumption or for investment to increase

of the estimates and methodology of produced capi-

a country’s future consumption. For a measure of

tal consumption and natural capital depletion, see

how comprehensive wealth is changing over time,

About the data in table 4.11.

see table 4.11.

The United Nations System of National Accounts

Methods of computing growth are described in Sta-

(SNA) includes nonproduced natural assets (such

tistical methods. For a detailed note on methodology,

as land, mineral resources, and forests) within the

see data.worldbank.org/.

asset boundary when they are under the effective GDP and adjusted net national income in Sub-Saharan Africa, 2000–09 (2000 $ billions)

4.10a

Data sources GNI and GDP are estimated by World Bank staff

(2000 $ billions)

based on national accounts data collected by

550

World Bank staff during economic missions or

GDP

reported by national statistical offices to other

500

international organizations such as the OECD. Data on consumption of fixed capital are from

450

the United Nations Statistics Division’s National

Adjusted net national income

400

Accounts Statistics: Main Aggregates and Detailed Tables, extrapolated to 2009. Data on energy, min-

350

eral, and forest depletion are estimates based on sources and methods in World Bank’s The

300 2000

2002

Source: World Development Indicators data files.

2004

2006

2008

2009

Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium (2011a).

2011 World Development Indicators

233

economy

Toward a broader measure of national income


4.11 Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

234

Toward a broader measure of saving Gross savings

Consumption of fixed capital

Education expenditure

Net forest depletion

Energy depletion

Mineral depletion

Carbon dioxide damage

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

.. 17.6 .. 10.9 23.9 19.5 22.4 24.4 48.0 35.3 25.7 21.7 10.6 23.8 12.9 17.1 15.0 16.7 .. .. 20.3 20.4 18.0 .. .. 23.0 53.2 30.3 19.2 .. 26.2 20.8 15.4 22.6 .. 21.8 21.4 10.5 24.1 16.7 11.7 .. 24.2 16.2 19.8 16.3 .. 20.0 0.2 21.2 15.7 3.4 12.9 8.5 .. .. 16.6

7.7 10.5 10.5 11.7 11.8 9.7 14.4 14.3 11.5 6.8 11.1 14.0 7.9 9.5 10.4 11.5 11.8 11.7 7.4 5.5 8.1 8.6 14.2 7.2 9.9 12.6 10.2 13.6 11.3 5.9 13.6 11.3 8.8 12.9 .. 13.6 16.5 11.1 10.7 9.6 10.5 6.8 12.8 6.7 17.0 14.2 13.2 7.5 8.8 13.8 8.6 13.9 10.1 7.7 7.4 .. 9.6

0.0 1.3 16.7 29.1 4.5 0.0 1.9 0.1 32.7 2.1 0.9 0.0 0.0 9.7 0.7 0.3 1.6 0.4 0.0 0.0 0.0 4.7 1.9 0.0 25.2 0.1 2.9 0.0 5.9 2.9 50.6 0.0 3.1 0.7 2.4 0.3 1.5 0.0 9.8 7.0 0.0 0.0 0.7 0.0 0.0 0.0 29.1 0.0 0.1 0.1 0.0 0.1 0.4 0.0 0.0 .. 0.0

0.0 0.0 0.1 0.0 0.3 0.5 3.1 0.0 0.0 0.0 0.0 0.0 0.0 1.5 0.9 2.5 1.5 0.7 0.0 0.8 0.0 0.1 0.4 0.0 0.0 9.9 0.2 0.0 0.3 7.9 0.0 0.1 0.0 0.0 1.0 0.0 0.0 0.5 0.0 0.1 0.0 0.0 0.0 0.1 0.1 0.0 0.1 0.0 0.0 0.0 4.8 0.0 0.0 3.7 0.0 .. 0.4

0.1 0.3 0.8 0.3 0.5 0.5 0.3 0.1 1.0 0.4 1.3 0.2 0.4 0.6 1.3 0.3 0.2 0.9 0.1 0.1 0.4 0.2 0.3 0.1 0.0 0.4 1.1 0.1 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.6 0.1 0.4 0.4 0.8 0.3 0.2 0.8 0.2 0.2 0.1 0.2 0.4 0.4 0.2 0.3 0.2 0.3 0.3 0.3 .. 0.5

0.7 0.2 0.2 1.2 1.1 1.6 0.0 0.1 0.3 0.4 0.0 0.1 0.3 1.0 0.1 0.2 0.1 0.8 0.6 0.1 0.3 0.4 0.0 0.2 1.0 0.5 0.8 .. 0.1 0.5 0.7 0.1 0.3 0.2 0.1 0.0 0.0 0.0 0.0 0.5 0.1 0.3 0.0 0.2 0.0 0.0 0.0 0.4 0.7 0.0 0.0 0.3 0.1 0.5 0.6 0.4 0.2

.. 8.2 .. –29.2 10.6 9.6 1.7 15.0 5.4 27.1 16.9 13.2 4.1 6.2 .. 9.6 4.6 6.1 .. .. 13.0 6.8 5.8 .. .. 3.2 39.7 .. 5.4 .. –44.7 15.2 7.3 12.3 .. 11.3 10.7 0.4 4.4 3.1 3.7 .. 14.4 8.3 8.1 7.0 .. 12.9 –7.1 11.4 –4.7 –7.9 4.0 –4.2 .. .. 9.5

2011 World Development Indicators

.. 2.8 4.5 2.3 4.9 2.2 4.5 5.2 2.9 2.0 4.4 5.8 3.3 4.7 .. 7.4 4.8 3.8 4.3 7.1 1.6 3.1 4.7 1.3 2.3 3.6 1.8 3.0 4.0 0.9 2.5 6.2 4.3 3.9 13.6 4.0 7.4 1.9 1.4 4.4 3.3 1.6 4.4 3.7 5.5 5.0 3.1 2.1 2.8 4.3 4.7 3.3 2.9 2.3 2.3 1.5 3.5

3.4 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.6 0.0 0.0 1.2 0.0 .. 0.0 0.0 0.0 1.6 9.8 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.2 0.0 0.0 0.0 0.0 0.0 0.1 0.5 0.8 0.0 4.4 0.0 0.0 0.0 1.0 0.0 0.0 2.1 0.0 0.8 2.9 0.0 .. 0.0

Local pollution Adjusted net damage savings


Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

4.11

economy

Toward a broader measure of saving Gross savings

Consumption of fixed capital

Education expenditure

Net forest depletion

Energy depletion

Mineral depletion

Carbon dioxide damage

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

16.0 35.2 26.2 .. .. 11.5 20.8 16.3 13.5 22.9 9.6 30.8 15.4 .. 30.1 .. 55.5 14.4 25.7 26.6 12.9 22.9 –2.7 66.8 15.1 18.8 .. .. 31.7 18.6 .. 16.2 22.1 17.8 44.7 31.8 9.2 .. 26.8 36.8 22.7 16.6 10.6 .. .. 32.6 40.3 21.5 37.4 19.7 12.3 24.0 35.0 19.2 10.4 .. ..

13.0 8.6 10.9 10.7 10.1 17.7 13.6 14.0 11.2 13.5 10.3 12.7 7.4 .. 13.3 .. 5.2 8.4 8.4 11.3 11.2 6.4 8.2 11.9 12.0 10.9 7.3 7.4 11.6 7.7 8.1 10.9 11.7 8.5 9.5 10.1 7.1 .. 10.6 6.8 14.6 14.1 8.8 2.9 9.0 15.2 13.5 8.0 12.1 8.6 9.7 11.3 8.0 12.4 17.2 .. ..

5.3 3.1 3.3 4.0 .. 5.2 5.7 4.1 6.2 3.2 5.6 4.4 6.6 .. 3.9 .. 3.2 5.2 1.1 5.6 1.6 9.4 3.1 .. 4.4 4.9 2.6 3.5 4.0 3.3 3.1 3.1 4.8 8.4 4.6 5.2 4.0 0.8 6.4 3.5 4.7 6.6 3.0 3.6 0.9 6.2 3.7 1.9 3.5 .. 3.6 2.4 2.5 4.8 5.3 .. ..

0.4 0.9 0.6 1.1 1.3 0.2 0.3 0.2 0.8 0.2 0.7 1.6 0.3 .. 0.5 0.0 0.4 1.1 0.2 0.2 0.4 0.0 1.0 0.8 0.3 1.0 0.2 0.2 0.8 0.1 0.5 0.3 0.4 0.7 2.1 0.4 0.2 .. 0.2 0.2 0.2 0.2 0.6 0.1 0.5 0.1 0.5 0.7 0.3 0.5 0.2 0.3 0.3 0.6 0.2 .. ..

0.0 0.5 0.5 0.5 2.6 0.0 0.1 0.1 0.2 0.2 0.2 0.1 0.1 0.8 0.3 .. 0.3 0.2 0.4 0.0 0.2 0.1 0.3 1.0 0.1 0.1 0.1 0.1 0.0 1.1 0.4 0.0 0.2 0.6 1.6 0.1 0.1 0.4 0.0 0.0 0.2 0.0 0.0 1.1 0.5 0.0 0.0 0.8 0.1 0.0 0.8 0.4 0.1 0.2 0.0 .. 0.1

4.5 24.1 11.0 .. .. –1.1 12.2 6.1 6.9 12.1 3.0 –1.2 13.1 .. 20.0 .. 15.7 9.4 17.8 20.4 2.7 24.4 –18.3 .. 6.0 11.6 .. .. 15.4 13.5 .. 8.0 9.1 16.2 24.9 25.0 2.0 .. 21.9 29.1 11.6 8.0 3.4 .. .. 12.8 –7.9 10.7 28.4 .. 5.2 8.6 28.0 9.7 –1.8 .. ..

0.0 0.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.2 .. 0.0 .. 0.0 0.0 0.0 0.3 0.0 1.4 10.4 0.0 0.1 0.1 0.2 0.9 0.0 0.0 0.5 0.0 0.0 0.1 0.0 0.0 0.5 .. 0.0 4.2 0.0 0.0 0.1 1.2 0.3 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 .. ..

0.2 2.2 5.3 17.7 45.7 0.0 0.1 0.1 0.0 0.0 0.1 20.8 0.0 .. 0.0 .. 37.0 0.5 0.0 0.0 0.0 0.0 0.0 30.4 0.1 0.0 0.0 0.0 7.9 0.0 0.0 0.0 5.1 0.1 3.8 0.0 3.2 .. 0.0 0.0 0.8 0.6 0.0 0.0 14.7 10.6 37.8 2.2 0.0 0.0 0.0 0.7 0.3 0.7 0.0 .. ..

0.0 1.1 1.2 0.2 0.0 0.0 0.1 0.0 0.7 0.0 1.0 1.2 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 0.0 18.3 0.0 0.3 0.0 7.3 1.4 0.0 .. 0.3 0.0 0.0 0.3 0.7 0.0 0.0 0.0 0.0 0.0 0.0 19.9 0.0 5.2 0.7 0.2 0.1 .. ..

Local pollution Adjusted net damage savings

2011 World Development Indicators

235


4.11 Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzaniaa Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

Toward a broader measure of saving Gross savings

Consumption of fixed capital

Education expenditure

Net forest depletion

Energy depletion

Mineral depletion

Carbon dioxide damage

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

% of GNI 2009

3.4 3.5 3.6 7.2 5.4 4.7 3.4 2.8 3.6 4.9 .. 5.4 4.0 2.6 0.9 7.2 6.1 4.8 2.6 3.2 2.4 4.6 1.6 4.5 4.0 6.7 2.6 .. 3.0 5.9 .. 5.1 4.8 2.3 9.4 3.6 2.8 .. 4.2 1.3 6.9 4.2 w 3.2 3.2 2.4 4.1 3.2 2.1 3.6 4.4 4.3 2.9 3.6 4.6 4.5

0.0 0.0 2.4 0.0 0.0 .. 1.7 0.0 0.3 0.1 .. 0.3 0.0 0.5 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.2 .. 2.3 0.0 0.1 0.0 .. 4.7 0.0 .. 0.0 0.0 0.4 0.0 0.0 0.2 .. 0.0 0.0 0.0 0.0 w 1.4 0.1 0.2 0.0 0.1 0.0 0.0 0.0 0.0 0.9 0.6 0.0 0.0

1.4 13.8 0.0 28.9 0.0 0.4 0.0 0.0 0.0 0.1 .. 2.8 0.0 0.0 11.1 0.0 0.0 0.0 10.0 0.2 0.2 3.0 0.0 0.0 28.2 3.5 0.2 30.4 0.0 3.8 .. 1.2 0.7 0.0 17.8 9.5 7.0 .. 13.2 0.0 2.2 2.0 w 1.2 5.1 4.0 6.4 5.0 3.3 8.7 3.5 14.5 2.1 7.5 0.9 0.1

0.0 0.7 0.0 0.0 0.3 0.0 0.4 0.0 0.0 0.0 .. 2.2 0.0 0.0 0.0 0.0 0.2 0.0 0.1 0.0 2.3 0.0 0.0 1.3 0.0 1.0 0.0 0.0 0.0 0.0 .. 0.0 0.1 0.0 0.0 0.3 0.0 .. 0.0 11.5 1.3 0.3 w 1.3 0.7 0.4 1.0 0.7 0.3 0.4 1.3 0.3 0.9 1.2 0.1 0.0

0.5 1.1 0.1 0.8 0.3 0.0 0.5 0.3 0.4 0.3 .. 1.2 0.2 0.2 0.2 0.3 0.1 0.1 1.1 1.1 0.2 0.9 0.0 0.4 1.4 0.5 0.3 2.1 0.1 2.4 .. 0.2 0.3 0.2 3.2 0.4 1.1 .. 0.7 0.2 1.1 0.4 w 0.3 0.8 1.0 0.6 0.8 1.0 0.9 0.3 0.9 0.9 0.6 0.2 0.2

0.0 0.1 0.1 0.7 0.5 .. 0.8 0.4 0.0 0.1 0.4 0.1 0.2 0.2 0.5 0.0 0.0 0.1 0.7 0.3 0.1 0.2 .. 0.1 0.2 0.1 0.6 0.9 0.0 0.1 0.5 0.0 0.1 1.1 0.3 0.0 0.3 .. .. 0.2 0.2 0.2 w 0.3 0.5 0.7 0.2 0.5 0.7 0.2 0.3 0.6 0.5 0.3 0.1 0.1

28.4 23.4 15.2 31.5 16.1 17.5 8.0 45.2 29.9 22.7 .. 15.8 19.9 24.3 13.5 2.5 23.6 31.0 13.9 12.4 21.1 31.0 .. .. 34.3 24.1 13.0 .. 17.9 15.9 .. 11.9 9.8 17.5 .. 21.8 31.2 .. .. 21.3 .. 21.1 w 23.9 33.2 43.3 20.0 33.0 48.7 21.1 18.9 .. 33.6 15.4 16.5 18.6

11.2 12.0 7.4 12.6 8.4 .. 6.8 14.1 13.0 13.5 .. 14.1 13.9 9.5 9.7 10.2 13.3 14.1 9.9 7.9 7.3 10.9 1.2 7.0 12.9 11.0 11.7 10.8 7.4 9.9 .. 13.5 14.3 12.0 8.4 12.2 8.8 .. 9.0 9.3 .. 13.1 w 7.2 10.7 9.9 11.8 10.7 10.3 11.7 11.7 10.4 8.4 10.6 14.1 14.2

a. Covers mainland Tanzania only.

236

2011 World Development Indicators

Local pollution Adjusted net damage savings

% of GNI 2009

18.8 –0.8 8.8 –3.9 7.8 .. 1.2 33.0 19.8 13.6 .. 0.4 9.7 16.4 –7.1 –0.9 16.0 21.6 –14.1 6.2 13.5 20.5 .. .. –32.4 14.6 2.9 .. 8.6 5.6 .. 2.2 –0.8 6.1 .. 2.9 16.6 .. .. 1.4 .. 6.4 w .. 14.5 26.2 3.9 14.6 33.1 1.4 6.8 .. 21.6 –1.8 5.2 8.7


About the data

4.11

economy

Toward a broader measure of saving Definitions

Adjusted net savings measures the change in

of production. Natural resources give rise to rents

• Gross savings is the difference between gross

value of a specified set of assets, excluding capital

because they are not produced; in contrast, for pro-

national income and public and private consump-

gains. If a country’s net savings are positive and

duced goods and services competitive forces will

tion, plus net current transfers. • Consumption of

the accounting includes a sufficiently broad range

expand supply until economic profits are driven to

fixed capital is the replacement value of capital

of assets, economic theory suggests that the pres-

zero. For each type of resource and each country, unit

used up in production. • Education expenditure

ent value of social welfare is increasing. Conversely,

resource rents are derived by taking the difference

is public current operating expenditures in educa-

persistently negative adjusted net savings indicate

between world prices (to reflect the social oppor-

tion, including wages and salaries and excluding

that an economy is on an unsustainable path.

tunity cost of resource extraction) and the average

capital investments in buildings and equipment.

The table shows the extent to which today’s rents

unit extraction or harvest costs (including a “normal”

• Net forest depletion is unit resource rents times

from natural resources and changes in human capital

return on capital). Unit rents are then multiplied by

the excess of roundwood harvest over natural

are balanced by net savings—that is, this genera-

the physical quantity extracted or harvested to arrive

growth. • Energy depletion is the ratio of the value

tion’s bequest to future generations.

at total rent. To estimate the value of the resource,

of the stock of energy resources to the remaining

Adjusted net savings is derived from standard

rents are assumed to be constant over the life of the

reserve lifetime (capped at 25 years). It covers coal,

national accounting measures of gross savings

resource (the El Serafy approach), and the present

crude oil, and natural gas. • Mineral depletion is the

by making four adjustments. First, estimates of

value of the rent flow is calculated using a 4 percent

ratio of the value of the stock of mineral resources to

fixed capital consumption of produced assets are

social discount rate. For details on the estimation of

the remaining reserve lifetime (capped at 25 years).

deducted to obtain net savings. Second, current

natural wealth see World Bank (2011a).

It covers tin, gold, lead, zinc, iron, copper, nickel,

public expenditures on education are added to net

A positive net depletion figure for forest resources

silver, bauxite, and phosphate. • Carbon dioxide

savings (in standard national accounting these

implies that the harvest rate exceeds the rate of

damage is estimated at $20 per ton of carbon (the

expenditures are treated as consumption). Third,

natural growth; this is not the same as deforesta-

unit damage in 1995 U.S. dollars) times tons of

estimates of the depletion of a variety of natural

tion, which represents a change in land use (see

carbon emitted. • Particulate emissions damage

resources are deducted to reflect the decline in asset

Definitions for table 3.4). In principle, there should

is the willingness to pay to avoid illness and death

values associated with their extraction and harvest.

be an addition to savings in countries where growth

attributable to particulate emissions. • Adjusted net

And fourth, deductions are made for damages from

exceeds harvest, but empirical estimates suggest

savings is net savings plus education expenditure

carbon dioxide and particulate emissions.

that most of this net growth is in forested areas that

minus energy depletion, mineral depletion, net for-

The exercise treats public education expenditures

cannot currently be exploited economically. Because

est depletion, and carbon dioxide and particulate

as an addition to savings. However, because of the

the depletion estimates reflect only timber values,

emissions damage.

wide variability in the effectiveness of public edu-

they ignore all the external and nontimber benefits

cation expenditures, these figures cannot be con-

associated with standing forests.

strued as the value of investments in human capital.

Pollution damage from emissions of carbon dioxide

A current expenditure of $1 on education does not

is calculated as the marginal social cost per unit mul-

necessarily yield $1 of human capital. The calcula-

tiplied by the increase in the stock of carbon dioxide.

Data on gross savings are from World Bank

tion should also consider private education expen-

The unit damage figure represents the present value

national accounts data files (see table 4.8).

diture, but data are not available for a large number

of global damage to economic assets and to human

Data on consumption of fixed capital are from

of countries.

welfare over the time the unit of pollution remains

the United Nations Statistics Division’s National

in the atmosphere.

Accounts Statistics: Main Aggregates and Detailed

While extensive, the accounting of natural

Data sources

resources depletion and pollution costs still has

Pollution damage from particulate emissions is

Tables, extrapolated to 2009. Data on educa-

some gaps. Key estimates missing on the resource

estimated by valuing the human health effects from

tion expenditure are from the United Nations

side include the value of fossil water extracted from

exposure to particulate matter pollution in urban

Educational, Scientific, and Cultural Organization

aquifers, net depletion of fish stocks, and depletion

areas. The estimates are calculated as willingness to

Institute for Statistics online database; missing

and degradation of soils. Important pollutants affect-

pay to avoid illness and death, from cardiopulmonary

data are estimated by World Bank staff. Data on

ing human health and economic assets are excluded

disease and lung cancer in adults and acute respira-

energy, mineral, and forest depletion are esti-

because no internationally comparable data are

tory infections in children, that are attributable to

mates based on sources and methods in World

widely available on damage from ground-level ozone

particulate emissions.

Bank (2011a). Data on carbon dioxide damage

or sulfur oxides.

Adjusted net savings aims to be as comprehensive

are from Fankhauser’s Valuing Climate Change:

Estimates of resource depletion are based on the

a measure as possible to provide a better under-

The Economics of the Greenhouse (1995). Data

“change in real wealth” method described in Hamil-

standing of the rate of country wealth creation or

on particulate emissions damage are from Pandey

ton and Ruta (2008), which estimates depletion as

depletion. To do so, it treats education as investment

and others’ “The Human Cost of Air Pollution: New

the ratio between the total value of the resource

and accounts for pollution damages to assets and

Estimates for Developing Countries” (2006). The

and the remaining reserve lifetime. The total value

human welfare, which goes outside the boundaries

conceptual underpinnings of the savings measure

of the resource is the present value of current and

of the United Nations System of National Accounts.

appear in Hamilton and Clemens’ “Genuine Sav-

future rents from resource extractions. An economic

For a detailed note on methodology, see data.

rent represents an excess return to a given factor

ings Rates in Developing Countries” (1999).

worldbank.org/.

2011 World Development Indicators

237


4.12

Central government finances Revenuea

Afghanistanb Albaniab Algeria Angola Argentina Armeniab Australia Austria Azerbaijanb Bangladeshb Belarusb Belgium Beninb Bolivia Bosnia and Herzegovina Botswanab Brazilb Bulgariab Burkina Faso Burundib Cambodia Cameroonb Canadab Central African Republicb Chad Chile Chinab Hong Kong SAR, China Colombia Congo, Dem. Rep.b Congo, Rep.b Costa Rica Côte d’Ivoire Croatiab Cuba Czech Republicb Denmark Dominican Republic Ecuadorb Egypt, Arab Rep.b El Salvador Eritrea Estonia Ethiopiab Finland France Gabon Gambia, Theb Georgiab Germany Ghanab Greece Guatemalab Guineab Guinea-Bissau Haiti Honduras

238

Expense

Cash surplus or deficit

Net incurrence of liabilities

% of GDP

% of GDP 1995 2009

% of GDP 1995 2009

% of GDP 1995 2009

Domestic 1995 2009

1995

.. 21.2 .. .. .. .. .. 36.6 .. .. 30.0 41.5 .. .. .. 40.5 26.9 35.6 .. 19.3 .. 11.8 19.8 .. .. .. 5.4 .. .. 5.3 23.6 .. .. 36.8 .. 33.2 37.6 .. 30.9 34.8 .. .. 36.2 12.2 40.4 43.3 .. .. 12.2 29.9 17.0 35.3 8.4 11.2 .. .. ..

.. 25.6 .. .. .. .. .. 42.5 .. .. 28.7 45.7 .. .. .. 30.3 32.9 39.5 .. 23.6 .. 10.6 23.8 .. .. .. .. .. .. 8.2 29.8 .. .. 36.2 .. 32.6 41.5 .. 26.3 28.1 .. .. 32.8 12.0 49.7 47.6 .. .. 15.4 38.6 .. 44.3 7.6 12.1 .. .. ..

.. –8.9 .. .. .. .. .. –5.5 .. .. –2.7 –3.9 .. .. .. 4.9 –2.7 –5.1 .. –4.7 .. 0.2 –4.0 .. .. .. .. .. .. 0.0 –8.2 .. .. –1.1 .. –0.9 –3.7 .. 0.1 3.4 .. .. 1.6 –3.1 –7.5 –4.1 .. .. –4.3 –8.3 .. –9.1 –0.5 –4.3 .. .. ..

.. 7.4 .. .. .. .. .. .. .. .. 2.2 .. .. .. .. 0.2 .. 7.5 .. 3.1 .. –0.3 .. .. .. .. 1.6 .. .. 0.0 .. .. .. –2.3 .. –0.5 .. .. .. .. .. .. .. 1.8 8.9 .. .. .. 2.2 .. .. .. .. –0.1 .. .. ..

.. 2.1 .. .. .. .. .. .. .. .. 0.4 –0.5 .. .. .. –0.4 .. –0.8 .. 4.0 .. 0.3 .. .. .. .. .. .. .. 0.2 .. .. .. 0.7 .. –0.4 .. .. .. .. .. .. .. 2.6 0.2 .. .. .. 2.4 .. .. .. 0.4 4.5 .. .. ..

9.1 .. 36.6 .. .. 22.1 24.6 36.6 27.3 11.1 35.4 40.3 17.6 23.3 38.6 .. 23.1 32.3 14.0 .. 11.0 .. 17.4 .. .. 20.1 11.1 19.7 17.0 .. .. 24.7 18.7 34.1 .. 29.1 40.0 16.4 .. 27.0 17.5 .. 37.1 .. 39.0 40.5 .. .. 25.2 29.4 15.3 36.2 11.0 .. .. .. 20.8

2011 World Development Indicators

38.0 .. 25.0 .. .. 23.7 26.6 39.6 15.5 11.3 33.0 45.3 15.0 21.8 41.2 .. 25.6 31.6 13.0 .. 11.0 .. 19.2 .. .. 22.6 .. 18.9 19.5 .. .. 26.0 17.6 36.2 .. 37.3 42.4 16.2 .. 30.2 21.6 .. 36.8 .. 35.0 47.6 .. .. 31.0 31.7 17.9 50.7 12.6 .. .. .. 24.1

0.2 .. –4.4 .. .. –7.5 –2.4 –2.6 0.4 –1.7 0.2 –5.1 –4.5 1.2 –4.3 .. –3.5 –0.1 –4.8 .. –2.3 .. –1.9 .. .. –4.5 .. 0.6 –4.0 .. .. –3.4 0.9 –3.0 .. –6.1 –2.1 –3.8 .. –6.6 –5.0 .. –1.3 .. 4.6 –7.3 .. .. –7.8 –2.2 –5.6 –15.2 –3.2 .. .. .. –4.5

0.1 .. 5.9 .. .. 1.3 .. .. 0.0 3.1 –2.5 1.0 2.2 –0.2 3.7 .. 8.3 –0.4 4.5 .. –2.0 .. .. .. .. 0.8 0.4 1.0 5.8 .. .. .. .. 3.0 .. 2.9 .. 2.4 .. 9.9 2.0 .. .. .. –0.2 .. .. .. 1.3 3.1 2.8 .. 1.4 .. .. .. 5.0

Debt and interest payments

Foreign 2009

0.8 .. 0.0 .. .. 12.3 .. .. 0.2 0.4 8.4 6.5 2.1 –0.1 3.2 .. –0.1 0.5 2.9 .. 2.3 .. .. .. .. –0.4 0.0 –0.1 0.9 .. .. .. .. 2.2 .. 1.9 .. 1.5 .. –0.2 5.9 .. .. .. –0.6 .. .. .. 3.7 –0.2 2.6 .. 1.4 .. .. .. 1.0

Total debt % of GDP 2009

Interest % of revenue 2009

.. .. .. .. .. .. 24.1 70.7 .. .. 18.1 92.4 .. .. .. .. 61.0 .. .. .. .. .. 53.2 .. .. .. .. 30.5 59.3 .. .. .. .. .. .. 31.9 41.0 .. .. 79.5 48.5 .. 9.1 .. 36.2 82.8 .. .. 34.7 47.2 .. 138.5 23.3 .. .. .. ..

0.0 .. 1.0 .. .. 2.3 3.7 7.0 0.3 21.7 2.1 8.5 2.5 8.0 1.2 .. 20.7 2.2 2.2 .. 1.3 .. 10.1 .. .. 2.8 .. 0.3 18.9 .. .. 8.8 7.1 4.8 .. 4.1 4.9 9.7 .. 15.2 12.3 .. 0.6 .. 3.2 5.4 .. .. 3.4 5.5 15.2 14.3 12.6 .. .. .. 2.9


Revenuea

Hungary Indiab Indonesiab Iran, Islamic Rep.b Iraq Ireland Israel Italy Jamaica Japan Jordanb Kazakhstanb Kenyab Korea, Dem. Rep. Korea, Rep.b Kosovo Kuwaitb Kyrgyz Republicb Lao PDR Latviab Lebanon Lesothob Liberiab Libya Lithuania Macedonia, FYRb Madagascar Malawi Malaysiab Mali Mauritania Mauritius Mexicob Moldovab Mongoliab Moroccob Mozambique Myanmar b Namibiab Nepalb Netherlands New Zealand Nicaraguab Niger Nigeriab Norway Omanb Pakistanb Panamab Papua New Guineab Paraguay b Perub Philippinesb Poland Portugal Puerto Rico Qatar b

Expense

% of GDP 1995 2009

% of GDP 1995 2009

43.0 12.3 15.6 24.2 .. 35.5 .. 40.4 .. .. 28.2 14.0 21.6 .. 17.8 .. 36.8 16.7 .. 25.8 .. 57.1 .. .. .. .. .. .. 23.3 .. .. .. 15.3 28.4 19.0 .. .. 6.4 31.7 10.5 41.5 .. 12.8 .. .. .. 27.8 17.2 26.1 22.7 17.2 17.4 17.7 .. 33.2 .. ..

53.2 14.4 9.5 15.8 .. 37.5 .. 48.0 .. .. 26.1 18.7 25.8 .. 14.3 .. 44.0 25.6 .. 28.3 .. 39.4 .. .. .. .. .. .. 18.7 .. .. .. 15.0 38.4 13.8 .. .. .. 35.7 .. 50.8 .. 14.2 .. .. .. 32.4 19.1 22.0 24.5 14.5 17.4 15.9 .. 37.1 .. ..

40.5 11.9 15.4 31.9 .. 30.4 34.6 38.5 27.0 .. 23.5 9.2 20.5 .. 23.1 .. 47.1 19.2 13.9 24.9 22.5 66.4 0.4 .. 28.3 34.0 14.1 .. 23.3 17.1 .. 23.5 .. 33.1 29.2 33.1 .. .. 29.2 14.5 41.0 36.1 19.1 13.6 9.7 47.2 .. 14.0 .. .. 19.0 17.2 14.6 30.1 34.7 .. 47.2

45.3 16.2 15.7 24.7 .. 43.4 40.6 44.0 41.5 .. 28.6 16.9 21.7 .. 21.9 .. 21.9 19.3 11.3 34.8 29.5 52.1 0.3 .. 38.8 31.3 11.7 .. 22.7 14.6 .. 21.6 .. 38.3 28.8 27.9 .. .. 24.1 .. 45.6 32.1 20.9 11.8 7.2 35.9 .. 16.8 .. .. 17.1 17.1 18.6 35.8 43.2 .. 19.3

Cash surplus or deficit

% of GDP 1995 2009

–9.1 –2.2 1.7 1.1 .. –2.2 .. –7.5 .. .. 0.9 –1.8 –5.1 .. 2.4 .. –9.9 –10.8 .. –2.7 .. 5.8 .. .. .. .. .. .. 1.5 .. .. .. –0.6 –6.3 2.9 .. .. .. –5.0 .. –9.2 .. 0.6 .. .. .. –8.9 –5.3 1.5 –0.5 0.2 –1.3 –0.8 .. –5.1 .. ..

–4.0 –4.9 –1.7 0.6 .. –13.9 –4.3 –4.9 –15.9 .. –8.5 –2.0 –5.5 .. 0.0 .. 20.0 –1.4 –1.6 –6.4 –8.3 5.8 0.0 .. –9.0 –0.8 –1.9 .. –6.4 –2.1 .. 0.6 .. –5.7 –4.5 1.0 .. .. 2.0 .. –4.8 3.1 –2.3 –0.9 –1.7 10.7 .. –4.8 .. .. 0.1 –1.5 –3.9 –6.1 –8.7 .. 15.2

Net incurrence of liabilities

% of GDP

Domestic 1995 2009

1995

17.0 5.1 .. .. .. .. .. .. .. .. –2.5 0.8 3.9 .. –0.3 .. .. .. .. 2.4 .. 0.0 .. .. .. .. .. .. .. .. .. .. .. 3.0 1.6 .. .. .. .. 0.6 .. .. .. .. .. .. –0.1 .. .. 1.5 0.0 .. –0.5 .. –1.2 .. ..

0.2 0.0 –0.4 0.1 .. .. .. .. .. .. 6.1 2.8 –1.3 .. –0.1 .. .. .. .. 1.5 .. 7.2 .. .. .. .. .. .. .. .. .. .. 5.5 2.7 1.3 .. .. .. .. 2.5 .. .. 3.4 .. .. .. 0.0 .. .. –0.7 –0.8 3.9 –0.7 .. 4.2 .. ..

–1.9 5.6 0.9 1.4 .. .. .. .. 7.4 .. 7.6 2.8 3.0 .. 5.4 .. .. 0.5 –0.3 –2.7 11.8 –0.4 0.0 .. 1.9 –0.6 0.6 .. 6.5 –4.4 .. 3.1 .. 2.7 8.6 0.1 .. .. –0.8 3.2 .. .. .. –1.9 0.1 6.3 .. .. .. .. 1.3 0.2 1.2 1.6 3.4 .. ..

4.12 Debt and interest payments

Foreign 2009

5.8 0.2 0.4 0.0 .. .. .. .. 4.7 .. 1.2 0.5 0.1 .. –0.1 .. .. 7.7 2.1 15.1 0.3 1.6 0.0 .. 9.1 0.2 3.0 .. 0.9 2.6 .. 1.3 .. 3.3 5.2 1.7 .. .. –0.1 0.0 .. .. .. 2.4 .. –15.3 .. .. .. .. 0.1 1.1 2.0 3.6 5.9 .. ..

Total debt % of GDP 2009

Interest % of revenue 2009

81.7 53.0 28.3 .. .. 69.2 .. 118.9 115.8 157.7 57.9 9.5 .. .. .. .. .. .. .. 41.8 .. .. .. .. 33.3 .. .. .. 53.3 .. .. 38.9 .. 24.4 64.8 46.9 .. .. .. 43.7 58.3 37.9 .. .. 3.0 36.3 .. .. .. .. .. 23.6 .. 48.1 84.4 .. ..

10.6 28.5 10.9 0.6 .. 6.9 9.7 11.1 64.5 .. 8.7 2.5 10.4 .. 4.7 .. 0.0 3.3 3.2 3.8 48.7 1.3 2.1 .. 4.0 1.9 3.9 .. 9.0 1.7 .. 12.0 .. 4.0 1.6 3.1 .. .. 6.3 4.9 4.6 3.4 6.4 1.8 6.6 2.1 .. 41.7 .. .. 3.1 7.2 25.7 8.1 7.7 .. 2.1

2011 World Development Indicators

239

economy

Central government finances


4.12

Central government finances Revenuea

Expense

Cash surplus or deficit

Net incurrence of liabilities

Debt and interest payments

Total debt % of GDP

Interest % of revenue

2009

2009

2009

0.9 –0.2 .. .. .. 1.2 .. .. 3.0 –1.2 .. 1.0 4.8 –0.1 .. .. .. .. .. .. .. 0.0 .. –0.5 0.5 0.0 0.6 .. 1.8 4.9 .. .. 4.7 2.4 .. .. .. .. .. .. .. .. m .. 0.2 .. 0.9 .. 2.0 3.3 –0.2 0.1 0.3 .. .. 0.4

.. 8.6 .. .. .. .. .. 113.3 38.1 .. .. .. 46.5 85.0 .. .. 44.0 28.9 .. .. .. 28.6 .. .. 14.1 47.1 51.4 .. 32.7 .. .. 73.2 67.1 49.5 .. .. .. .. .. .. .. .. m .. .. .. .. .. .. .. .. .. 56.5 .. 55.7 69.9

% of GDP % of GDP

Romania Russian Federation Rwandab Saudi Arabia Senegalb Serbiab Sierra Leoneb Singaporeb Slovak Republic Sloveniab Somalia South Africa Spain Sri Lankab Sudanb Swazilandb Sweden Switzerlandb Syrian Arab Republicb Tajikistanb Tanzania Thailand Timor-Leste Togo Trinidad and Tobagob Tunisiab Turkey b Turkmenistan Ugandab Ukraineb United Arab Emiratesb United Kingdom United States Uruguay b Uzbekistan Venezuela, RB b Vietnam West Bank and Gaza Yemen, Rep.b Zambiab Zimbabweb World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

% of GDP

1995

2009

1995

2009

.. .. 10.6 .. 15.2 .. 9.4 26.7 .. 35.8 .. .. 32.0 20.4 7.2 .. 38.6 22.6 22.9 9.3 .. .. .. .. 27.2 30.0 .. .. 10.6 .. 10.1 35.2 .. 27.6 .. 16.9 .. .. 17.3 20.0 26.7 .. w .. 14.6 10.7 .. 14.6 7.2 .. 21.2 .. 13.1 .. .. 34.9

30.9 35.4 .. .. .. 36.3 11.6 18.2 28.5 37.5 .. 28.2 22.4 14.9 .. .. 34.7 18.4 .. .. .. 18.6 .. 18.8 36.1 31.4 21.8 .. 12.4 34.5 .. 35.9 15.9 29.4 .. .. .. .. .. 17.6 .. 24.3 w .. 20.0 14.7 .. 19.8 13.4 29.3 .. 30.6 12.1 24.5 24.7 34.5

.. .. 15.0 .. .. .. .. 12.4 .. 34.3 .. .. 37.1 26.0 6.8 .. .. 25.7 .. 11.4 .. .. .. .. 25.3 28.4 .. .. .. .. 11.0 40.4 .. 27.1 .. 18.5 .. .. 19.1 21.4 32.1 .. w .. .. .. .. .. .. .. 23.3 .. 15.3 .. .. 42.3

33.8 30.9 .. .. .. 37.7 22.5 15.2 37.6 42.7 .. 33.0 30.7 19.2 .. .. .. 17.0 .. .. .. 19.6 .. 17.4 28.4 29.9 27.3 .. 13.7 40.6 .. 46.4 26.3 29.3 .. .. .. .. .. 22.9 .. 31.1 w .. .. .. .. .. .. 30.1 .. 27.3 16.0 24.2 32.2 39.8

% of GDP 1995

2009

.. .. –5.6 .. .. .. .. 19.8 .. –0.1 .. .. –5.8 –7.6 –0.4 .. .. –0.6 .. –3.3 .. .. .. .. –0.1 –2.4 .. .. .. .. 0.5 –5.5 .. –1.2 .. –2.3 .. .. –3.9 –3.1 –5.4 .. w .. .. .. .. .. .. .. –1.4 .. –2.7 .. .. –7.4

–4.6 5.3 .. .. .. –2.6 –3.1 1.7 –7.3 –5.5 .. –4.9 –8.6 –6.6 .. .. .. 1.3 .. .. .. –3.0 .. –0.6 2.3 –1.7 –5.5 .. –0.9 –5.6 .. –10.9 –10.4 –1.5 .. .. .. .. .. –0.8 .. –7.1 w .. .. .. .. .. .. –0.4 .. –3.0 –4.6 –1.0 –7.7 –5.2

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

240

2011 World Development Indicators

Foreign

Domestic 1995 2009

1995

.. .. 2.9 .. .. .. 0.3 10.3 .. –0.4 .. .. .. 5.2 0.3 .. .. –0.5 .. 0.1 .. .. .. .. 2.8 0.9 .. .. .. .. .. .. .. 7.9 .. 1.1 .. .. .. 28.0 –1.4 .. m .. .. .. .. .. .. .. .. .. 3.8 .. .. ..

.. .. .. .. .. .. .. 0.0 .. 0.3 .. .. .. 3.2 .. .. .. .. .. 2.3 .. .. .. .. 2.6 2.9 .. .. .. .. .. .. .. 1.1 .. 0.1 .. .. .. 16.2 1.6 .. m .. .. .. .. .. .. .. .. .. 1.1 .. .. ..

2.4 0.8 .. .. .. 2.8 .. 13.7 2.9 12.4 .. 7.0 6.4 6.9 .. .. .. 2.0 .. .. .. 5.3 .. 2.7 –0.6 0.3 6.1 .. 1.5 6.7 .. .. 6.5 3.8 .. .. .. .. .. .. .. .. m .. 0.9 0.5 3.7 0.6 1.2 1.9 0.1 6.7 3.2 .. .. 0.8

2.0 1.3 .. .. .. 2.0 8.3 0.1 4.7 2.9 .. 8.4 6.1 31.0 .. .. .. 3.5 .. .. .. 5.8 .. 4.0 5.0 7.0 24.1 .. 7.7 3.1 .. 5.3 11.4 9.3 .. .. .. 1.1 .. 7.2 .. 5.4 m .. 7.0 6.0 7.2 4.5 5.8 2.5 9.1 7.0 21.7 .. 5.3 6.1


About the data

4.12

Definitions

Tables 4.12–4.14 present an overview of the size and

borrowing for temporary periods can also be used.

• Revenue is cash receipts from taxes, social con-

role of central governments relative to national econo-

Government excludes public corporations and quasi

tributions, and other revenues such as fines, fees,

mies. The tables are based on the concepts and recom-

corporations (such as the central bank).

rent, and income from property or sales. Grants, usu-

mendations of the second edition of the International

Units of government at many levels meet this defini-

ally considered revenue, are excluded. • Expense is

Monetary Fund’s (IMF) Government Finance Statistics

tion, from local administrative units to the national

cash payments for government operating activities in

Manual 2001. Before 2005 World Development Indica-

government, but inadequate statistical coverage pre-

providing goods and services. It includes compensa-

tors reported data derived on the basis of the 1986

cludes presenting subnational data. Although data for

tion of employees, interest and subsidies, grants,

manual’s cash-based method. The 2001 manual,

general government under the 2001 manual are avail-

social benefits, and other expenses such as rent

harmonized with the 1993 United Nations System of

able for a few countries, only data for the central gov-

and dividends. • Cash surplus or deficit is revenue

National Accounts, recommends an accrual account-

ernment are shown to minimize disparities. Still, differ-

(including grants) minus expense, minus net acquisi-

ing method, focusing on all economic events affecting

ent accounting concepts of central government make

tion of nonfinancial assets. In editions before 2005

assets, liabilities, revenues, and expenses, not only

cross-country comparisons potentially misleading.

nonfinancial assets were included under revenue

those represented by cash transactions. It takes all

Central government can refer to consolidated or bud-

and expenditure in gross terms. This cash surplus

stocks into account, so that stock data at the end of an

getary accounting. For most countries central govern-

or deficit is close to the earlier overall budget balance

accounting period equal stock data at the beginning of

ment finance data have been consolidated into one

(still missing is lending minus repayments, which are

the period plus flows over the period. The 1986 manual

account, but for others only budgetary central gov-

included as a financing item under net acquisition

considered only the debt stock data. Further, the new

ernment accounts are available. Countries reporting

of financial assets). • Net incurrence of liabilities

manual no longer distinguishes between current and

budgetary data are noted in Primary data documenta-

is domestic financing (obtained from residents) and

capital revenue or expenditures, and it introduces the

tion. Because budgetary accounts may not include

foreign financing (obtained from nonresidents), or

concepts of nonfinancial and financial assets. Most

all central government units (such as social security

the means by which a government provides financial

countries still follow the 1986 manual, however. The

funds), they usually provide an incomplete picture.

resources to cover a budget deficit or allocates finan-

IMF has reclassified historical Government Finance Sta-

Data on government revenue and expense are col-

cial resources arising from a budget surplus. The net

tistics Yearbook data to conform to the 2001 manual’s

lected by the IMF through questionnaires to member

incurrence of liabilities should be offset by the net

format. Because of reporting differences, the reclassi-

countries and by the Organisation for Economic Co-

acquisition of financial assets (a third financing item).

fied data understate both revenue and expense.

operation and Development. Despite IMF efforts to

The difference between the cash surplus or deficit

The 2001 manual describes government’s eco-

standardize data collection, statistics are often incom-

and the three financing items is the net change in

nomic functions as the provision of goods and ser-

plete, untimely, and not comparable across countries.

the stock of cash. • Total debt is the entire stock of

vices on a nonmarket basis for collective or individual

Government finance statistics are reported in local

direct government fixed-term contractual obligations

consumption, and the redistribution of income and

currency. The indicators here are shown as percent-

to others outstanding on a particular date. It includes

wealth through transfer payments. Government

ages of GDP. Many countries report government

domestic and foreign liabilities such as currency and

activities are financed mainly by taxation and other

finance data by fiscal year; see Primary data docu-

money deposits, securities other than shares, and

income transfers, though other financing such as

mentation for information on fiscal year end by country.

loans. It is the gross amount of government liabilities reduced by the amount of equity and financial

Twenty selected economies had a central government debt to GDP ratio of 65 percent or higher

derivatives held by the government. Because debt

4.12a

Central government debt, 2009 (percent of GDP) 160

is a stock rather than a flow, it is measured as of a given date, usually the last day of the fiscal year. • Interest payments are interest payments on government debt—including long-term bonds, long-term loans, and other debt instruments—to domestic and

120

foreign residents.

80

Data sources Data on central government finances are from the

40

IMF’s Government Finance Statistics database. Each country’s accounts are reported using the system of common definitions and classifications Gr

Ja pa n ee ce Ita Ja ly m ai Si c ng a ap or e Ic el an d St . K Cy pr itt u s s & Ne Ba vis rb ad o Be s lg iu m Sr iL an ka Po r tu ga l Fr an c Hu e ng ar Eg y yp t, Mal A t a Un ra ite b R e d Ki p. ng do m Au st ria Un Ire ite lan d d St at es

0

Note: Data are for the most recent year for 2005–2009. Source: International Monetary Fund, Government Finance Statistics data files, and World Development Indicators data files.

in the IMF’s Government Finance Statistics Manual 2001. See these sources for complete and authoritative explanations of concepts, definitions, and data sources.

2011 World Development Indicators

241

economy

Central government finances


4.13 Afghanistana Albaniaa Algeria Angola Argentina Armeniaa Australia Austria Azerbaijana Bangladesha Belarusa Belgium Benina Bolivia Bosnia and Herzegovina Botswanaa Brazila Bulgariaa Burkina Faso Burundia Cambodia Cameroona Canadaa Central African Republica Chad Chile Chinaa Hong Kong SAR, China Colombia Congo, Dem. Rep.a Congo, Rep.a Costa Rica Côte d’Ivoire Croatiaa Cuba Czech Republica Denmark Dominican Republic Ecuadora Egypt, Arab Rep.a El Salvador Eritrea Estonia Ethiopiaa Finland France Gabon Gambia, Thea Georgiaa Germany Ghanaa Greece Guatemalaa Guineaa Guinea-Bissau Haiti Honduras

242

Central government expenses Goods and services

Compensation of employees

Interest payments

Subsidies and other transfers

Other expense

% of expense 1995 2009

% of expense 1995 2009

% of expense 1995 2009

% of expense 1995 2009

% of expense 1995 2009

.. 18 .. .. .. .. .. 5 .. .. 39 3 .. .. .. 32 5 18 .. 20 .. 17 8 .. .. .. .. .. .. 37 7 .. .. 35 .. 7 8 .. 6 18 .. .. 21 35 8 8 .. .. 52 4 .. 10 15 17 .. .. ..

2011 World Development Indicators

72 .. 11 .. .. 13 10 6 9 12 12 3 18 14 23 .. 13 9 19 .. 32 .. 8 .. .. 10 .. 26 6 .. .. 11 29 8 .. 6 9 15 .. 8 15 .. 13 .. 10 6 .. .. 19 5 16 12 15 .. .. .. 17

.. 14 .. .. .. .. .. 14 .. .. 5 7 .. .. .. 30 8 7 .. 30 .. 40 10 .. .. .. .. .. .. 58 35 .. .. 27 .. 9 12 .. 49 22 .. .. 23 40 9 23 .. .. 11 5 .. 21 50 34 .. .. ..

23 .. 34 .. .. 25 10 14 12 19 11 7 47 22 28 .. 19 19 46 .. 43 .. 12 .. .. 20 .. 22 16 .. .. 46 38 26 .. 8 13 31 .. 25 36 .. 21 .. 10 21 .. .. 17 5 40 24 29 .. .. .. 54

.. 9 .. .. .. .. .. 9 .. .. 1 18 .. .. .. 2 45 37 .. 6 .. 26 24 .. .. .. .. .. .. 1 47 .. .. 3 .. 3 14 .. 26 26 .. .. 1 15 8 6 .. .. 10 6 .. 25 12 28 .. .. ..

0 .. 1 .. .. 2 3 7 1 22 2 8 3 10 1 .. 19 2 3 .. 2 .. 9 .. .. 2 .. 0 17 .. .. 8 9 5 .. 3 5 10 .. 14 10 .. 1 .. 4 5 .. .. 3 5 16 10 11 .. .. .. 3

.. 59 .. .. .. .. .. 68 .. .. 55 71 .. .. .. 36 45 38 .. 14 .. 14 57 .. .. .. .. .. .. 2 10 .. .. 32 .. 75 59 .. .. 6 .. .. 39 18 68 59 .. .. 26 67 .. 38 18 9 .. .. ..

4 .. 45 .. .. 37 73 71 18 35 70 53 30 47 44 .. 49 64 11 .. 21 .. 69 .. .. 51 .. 17 47 .. .. 21 16 56 .. 72 17 39 .. 45 22 .. 48 .. 71 54 .. .. 49 81 28 50 33 .. .. .. 7

.. 0 .. .. .. .. .. 6 .. .. 0 2 .. .. .. 2 1 2 .. 10 .. .. 3 .. .. .. .. .. .. .. .. .. .. 3 .. 5 10 .. .. .. .. .. 4 0 11 6 .. .. .. 20 .. 8 6 1 .. .. ..

0 .. 8 .. .. 23 6 5 61 12 6 0 2 7 4 .. 0 6 21 .. 2 .. 3 .. .. 19 .. 38 15 .. .. 14 7 5 .. 11 2 5 .. 9 18 .. 4 .. 8 2 .. .. 12 4 12 7 12 .. .. .. 19


Hungary Indiaa Indonesiaa Iran, Islamic Rep.a Iraq Ireland Israel Italy Jamaica Japan Jordana Kazakhstana Kenyaa Korea, Dem. Rep. Korea, Rep.a Kosovo Kuwaita Kyrgyz Republica Lao PDR Latviaa Lebanon Lesothoa Liberiaa Libya Lithuania Macedonia, FYRa Madagascar Malawi Malaysiaa Mali Mauritania Mauritius Mexicoa Moldovaa Mongoliaa Moroccoa Mozambique Myanmara Namibiaa Nepala Netherlands New Zealand Nicaraguaa Niger Nigeriaa Norway Omana Pakistana Panamaa Papua New Guineaa Paraguaya Perua Philippinesa Poland Portugal Puerto Rico Qatara

4.13

Goods and services

Compensation of employees

Interest payments

Subsidies and other transfers

Other expense

% of expense 1995 2009

% of expense 1995 2009

% of expense 1995 2009

% of expense 1995 2009

% of expense 1995 2009

8 14 22 21 .. 5 .. 4 .. .. 7 .. 15 .. 16 .. 34 32 .. 20 .. 32 .. .. .. .. .. .. 14 .. .. .. 9 10 30 .. .. .. 28 .. 5 .. 14 .. .. .. 55 .. 16 19 12 20 15 .. 9 .. ..

10 11 9 11 .. 10 27 4 6 .. 11 19 20 .. 11 .. 10 30 27 8 3 42 37 .. 10 28 15 .. 17 31 .. 12 .. 19 20 9 .. .. 20 .. 8 30 13 30 15 11 .. 22 .. .. 9 20 28 5 7 .. 25

10 10 20 56 .. 15 .. 14 .. .. 67 .. 28 .. 15 .. 33 36 .. 20 .. 45 .. .. .. .. .. .. 34 .. .. .. 19 8 12 .. .. .. 53 .. 8 .. 25 .. .. .. 30 .. 45 36 51 19 34 .. 30 .. ..

13 10 14 40 .. 23 25 15 14 .. 50 8 37 .. 10 .. 16 29 49 15 21 35 36 .. 16 17 40 .. 28 34 .. 34 .. 15 33 48 .. .. 45 .. 7 25 39 30 24 16 .. 4 .. .. 50 18 30 12 24 .. 32

17 27 17 0 .. 14 .. 24 .. .. 11 3 46 .. 3 .. 5 5 .. 3 .. 5 .. .. .. .. .. .. 14 .. .. .. 19 11 2 .. .. .. 1 .. 9 .. 17 .. .. .. 7 28 8 20 5 19 33 .. 15 .. ..

10 21 11 1 .. 5 9 10 43 .. 8 2 10 .. 5 .. 0 4 5 3 38 2 2 .. 3 2 7 .. 9 2 .. 14 .. 4 2 4 .. .. 8 .. 4 4 7 3 9 3 .. 35 .. .. 4 7 20 7 6 .. 5

56 33 40 .. .. 33 .. 54 .. .. 12 58 .. .. 63 .. 21 27 .. 56 .. 8 .. .. .. .. .. .. 36 .. .. .. .. 71 56 .. .. .. .. .. 77 .. 29 .. .. .. 8 2 30 26 31 33 15 .. 43 .. ..

63 51 54 34 .. 40 32 66 6 .. 30 69 31 .. 57 .. 58 34 10 70 36 14 24 .. 68 49 25 .. 46 15 .. 31 .. 56 45 27 .. .. 13 .. 79 38 36 9 53 67 .. 21 .. .. 29 47 20 71 51 .. 21

13 0 2 .. .. 1 .. 6 .. .. 4 .. 2 .. 3 .. 7 .. .. 0 .. 3 .. .. .. .. .. .. 1 .. .. .. .. 1 0 .. .. .. 4 .. 3 .. 14 .. .. .. 0 .. 1 1 0 8 .. .. 7 .. ..

2011 World Development Indicators

8 7 12 14 .. 1 9 6 31 .. 2 2 1 .. 17 .. 15 3 10 4 2 6 .. .. 6 4 14 .. 0 17 .. 10 .. 6 1 13 .. .. 14 .. 4 7 5 28 .. 5 .. 18 .. .. 9 7 2 7 1 .. 16

243

economy

Central government expenses


4.13 Romania Russian Federation Rwandaa Saudi Arabia Senegala Serbiaa Sierra Leonea Singaporea Slovak Republic Sloveniaa Somalia South Africa Spain Sri Lankaa Sudana Swazilanda Sweden Switzerlanda Syrian Arab Republica Tajikistana Tanzania Thailand Timor-Leste Togo Trinidad and Tobagoa Tunisiaa Turkeya Turkmenistan Ugandaa Ukrainea United Arab Emiratesa United Kingdom United States Uruguaya Uzbekistan Venezuela, RBa Vietnam West Bank and Gaza Yemen, Rep.a Zambiaa Zimbabwea World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

Central government expenses Goods and services

Compensation of employees

Interest payments

Subsidies and other transfers

Other expense

% of expense 1995 2009

% of expense 1995 2009

% of expense 1995 2009

% of expense 1995 2009

% of expense 1995 2009

.. .. 52 .. .. .. .. 38 .. 19 .. .. 5 23 44 .. .. 24 .. 47 .. .. .. .. 20 7 .. .. .. .. 48 14 .. 13 .. 6 .. .. 8 32 16 .. m .. .. .. .. .. .. .. .. .. .. .. 10 5

13 12 .. .. .. 13 24 36 7 13 .. 13 4 14 .. .. .. 6 .. .. .. 31 .. 24 14 7 10 .. 31 12 .. 18 15 12 .. .. .. 12 .. 32 .. 12 m .. 12 15 12 15 27 13 13 9 17 .. 9 7

.. .. 36 .. .. .. .. 39 .. 21 .. .. 14 20 38 .. .. 6 .. 8 .. .. .. .. 36 37 .. .. .. .. 33 15 .. 17 .. 22 .. .. 67 35 34 .. m .. .. .. .. .. .. .. .. .. .. .. 15 14

19 16 .. .. .. 26 28 27 12 20 .. 13 8 28 .. .. .. 6 .. .. .. 36 .. 40 21 36 23 .. 14 13 .. 14 12 25 .. .. .. 67 .. 30 .. 21 m .. 25 31 20 27 33 17 27 36 14 .. 14 15

Note: Components may not sum to 100 percent because of rounding or missing data. a. Data were reported on a cash basis and have been adjusted to the accrual framework.

244

2011 World Development Indicators

.. .. 12 .. .. .. .. 8 .. 3 .. .. 11 22 8 .. .. 4 .. 12 .. .. .. .. 20 13 .. .. .. .. .. 9 .. 6 .. 27 .. .. 16 16 31 .. m .. .. .. .. .. .. .. .. .. 27 .. 9 10

2 1 .. .. .. 2 7 0 4 3 .. 7 5 25 .. .. .. 4 .. .. .. 5 .. 5 6 7 20 .. 9 3 .. 4 7 9 .. .. .. 1 .. 7 .. 5m .. 7 7 7 6 5 2 9 7 21 .. 5 5

.. .. 5 .. .. .. .. 15 .. 55 .. .. 42 24 10 .. .. 66 .. 33 .. .. .. .. 24 36 .. .. .. .. .. 57 .. 64 .. 61 .. .. 8 19 19 .. m .. .. .. .. .. .. .. .. .. 24 .. 56 55

60 68 .. .. .. 58 23 0 68 62 .. 63 80 23 .. .. .. 83 .. .. .. 28 .. 18 38 38 44 .. 45 70 .. 53 62 47 .. .. .. 18 .. 24 .. 46 m .. 45 36 47 37 28 58 35 36 28 .. 62 62

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

8 10 .. .. .. 1 18 .. 14 3 .. 4 5 10 .. .. .. 3 .. .. .. 3 .. 13 21 13 5 .. 1 2 .. 12 6 7 .. .. .. 1 .. 7 .. 6m .. 7 8 6 7 2 6 13 9 10 .. 5 4


About the data

4.13

Definitions

The term expense has replaced expenditure in the

to households are shown as subsidies and other

• Goods and services are all government payments

table since the 2005 edition of World Development

transfers, and other expenses. The economic clas-

in exchange for goods and services used for the

Indicators in accordance with use in the International

sification can be problematic. For example, subsidies

production of market and nonmarket goods and ser-

Monetary Fund’s (IMF) Government Finance Statis-

to public corporations or banks may be disguised

vices. Own-account capital formation is excluded.

tics Manual 2001. Government expenses include all

as capital financing or hidden in special contractual

• Compensation of employees is all payments in

nonrepayable payments, whether current or capital,

pricing for goods and services. For further discussion

cash, as well as in kind (such as food and hous-

requited or unrequited. The concept of total central

of government finance statistics, see About the data

ing), to employees in return for services rendered,

government expense as presented in the IMF’s Gov-

for tables 4.12 and 4.14.

and government contributions to social insurance

ernment Finance Statistics Yearbook is comparable to

schemes such as social security and pensions that

the concept used in the 1993 United Nations System

provide benefits to employees. • Interest payments

of National Accounts.

are payments made to nonresidents, to residents,

Expenses can be measured either by function

and to other general government units for the use of

(health, defense, education) or by economic type

borrowed money. (Repayment of principal is shown

(interest payments, wages and salaries, purchases

as a financing item, and commission charges are

of goods and services). Functional data are often

shown as purchases of services.) • Subsidies and

incomplete, and coverage varies by country because

other transfers include all unrequited, nonrepayable

functional responsibilities stretch across levels of

transfers on current account to private and public

government for which no data are available. Defense

enterprises; grants to foreign governments, inter-

expenses, usually the central government’s respon-

national organizations, and other government units;

sibility, are shown in table 5.7. For more information

and social security, social assistance benefits, and

on education expenses, see table 2.11; for more on

employer social benefits in cash and in kind. • Other

health expenses, see table 2.16.

expense is spending on dividends, rent, and other

The classification of expenses by economic type in

miscellaneous expenses, including provision for con-

the table shows whether the government produces

sumption of fixed capital.

goods and services and distributes them, purchases the goods and services from a third party and distributes them, or transfers cash to households to make the purchases directly. When the government produces and provides goods and services, the cost is reflected in compensation of employees, use of goods and services, and consumption of fixed capital. Purchases from a third party and cash transfers Interest payments are a large part of government expenses for some developing economies

4.13a

Central government interest payments as a share of total expense, 2009 (percent) 50 40 30 20

Data sources

10

Data on central government expenses are from the s

M

au

rit

iu

p.

a

Re

Eg

yp

t,

Ar

ab

a bi

an Gh

m

az il Br

lo Co

ke y Tu r

in es Se yc he lle s

h

di a

pp

Ph

ili

In

es

ka an

la d ng

iL

Ba

& s itt

.K St

Sr

n

Ne vis

n no

is ta Pa k

ba Le

Ja

m

ai

ca

0

Interest payments accounted for more than 14 percent of total expenses in 2009 for 15 countries.

IMF’s Government Finance Statistics database. Each country’s accounts are reported using the system of common definitions and classifications in the IMF’s Government Finance Statistics Manual 2001. See these sources for complete and authoritative explanations of concepts, definitions, and

Source: International Monetary Fund, Government Finance Statistics data files.

data sources.

2011 World Development Indicators

245

economy

Central government expenses


4.14

Central government revenues Taxes on income, profits, and capital gains

Taxes on goods and services

Taxes on International trade

Other taxes

Social contributions

Grants and other revenue

% of revenue

% of revenue 1995 2009

% of revenue 1995 2009

% of revenue 1995 2009

% of revenue 1995 2009

% of revenue 1995 2009

1995

Afghanistana Albaniaa Algeria Angola Argentina Armeniaa Australia Austria Azerbaijana Bangladesha Belarusa Belgium Benina Bolivia Bosnia and Herzegovina Botswanaa Brazila Bulgariaa Burkina Faso Burundia Cambodia Cameroona Canadaa Central African Republica Chad Chile Chinaa Hong Kong SAR, China Colombia Congo, Dem. Rep.a Congo, Rep.a Costa Rica Côte d’Ivoire Croatiaa Cuba Czech Republica Denmark Dominican Republic Ecuadora Egypt, Arab Rep.a El Salvador Eritrea Estonia Ethiopiaa Finland France Gabon Gambia, Thea Georgiaa Germany Ghanaa Greece Guatemalaa Guineaa Guinea-Bissau Haiti Honduras

246

2009

.. 8 .. .. .. .. .. 21 .. .. 16 36 .. .. .. 21 14 17 .. 14 .. 17 48 .. .. .. 9 .. .. 21 6 .. .. 11 .. 15 37 .. 50 17 .. .. 18 19 16 17 .. .. 7 16 15 17 19 8 .. .. ..

2011 World Development Indicators

4 .. 60 .. .. 20 65 23 33 19 6 34 17 10 5 .. 30 16 14 .. 11 .. 55 .. .. 28 26 44 26 .. .. 17 15 10 .. 15 45 22 .. 28 27 .. 8 .. 20 22 .. .. 32 16 23 21 29 .. .. .. 20

.. 39 .. .. .. .. .. 22 .. .. 33 23 .. .. .. 4 24 28 .. 30 .. 25 18 .. .. .. 61 .. .. 12 21 .. .. 42 .. 32 40 .. 26 13 .. .. 35 13 31 25 .. .. 48 20 31 32 46 4 .. .. ..

3 .. 28 .. .. 41 23 23 23 29 29 24 39 43 43 .. 33 45 37 .. 36 .. 15 .. .. 46 55 9 32 .. .. 32 20 43 .. 27 36 54 .. 22 39 .. 39 .. 32 23 .. .. 51 24 29 29 56 .. .. .. 39

.. 14 .. .. .. .. .. 0 .. .. 6 .. .. .. .. 15 2 8 .. 20 .. 28 3 .. .. .. 7 .. .. 21 18 .. .. 9 .. 4 .. .. 11 10 .. .. 0 27 0 0 .. .. 10 .. 24 0 23 62 .. .. ..

5 .. 4 .. .. 3 2 0 4 24 16 .. 18 3 0 .. 2 1 12 .. 16 .. 1 .. .. 1 5 0 5 .. .. 4 33 2 .. 0 .. 10 .. 5 5 .. .. .. .. 0 .. .. 1 .. 16 0 7 .. .. .. 3

.. 1 .. .. .. .. .. 5 .. .. 11 2 .. .. .. 0 4 3 .. 1 .. 3 .. .. .. .. 0 .. .. 5 1 .. .. 1 .. 1 8 .. 1 10 .. .. 0 3 1 3 .. .. .. 0 .. 3 3 2 .. .. ..

0 .. 1 .. .. 8 0 5 1 3 3 0 6 9 2 .. 2 0 2 .. 0 .. .. .. .. 2 3 13 5 .. .. 3 8 2 .. 1 5 5 .. 2 0 .. .. .. 2 4 .. .. 1 .. .. 3 2 .. .. .. 1

.. 15 .. .. .. .. .. 43 .. .. 31 36 .. .. .. .. 31 21 .. 5 .. 2 21 .. .. .. .. .. .. 1 .. .. .. 33 .. 40 4 .. .. 10 .. .. 34 1 34 47 .. .. 13 58 .. 31 2 1 .. .. ..

0 .. .. .. .. 14 .. 42 .. .. 33 37 2 7 39 .. 26 23 .. .. .. .. 24 .. .. 7 .. 0 6 .. .. 34 6 35 .. 45 3 2 .. .. 12 .. 36 .. 31 45 .. .. 17 55 .. 36 3 .. .. .. 13

.. 22 .. .. .. .. .. 9 .. .. 3 3 .. .. .. 59 26 23 .. 30 .. 25 10 .. .. .. 22 .. .. 41 54 .. .. 4 .. 8 11 .. 12 41 .. .. .. 36 17 8 .. .. 22 6 9 16 6 23 .. .. ..

88 .. 6 .. .. 14 10 7 39 24 13 3 18 28 11 .. 6 16 36 .. 37 .. 8 .. .. 16 12 34 25 .. .. 10 18 9 .. 12 .. 8 .. 43 17 .. .. .. 15 6 .. .. 15 4 32 12 4 .. .. .. 23


Taxes on income, profits, and capital gains

Taxes on goods and services

Taxes on International trade

Other taxes

Social contributions

Grants and other revenue

% of revenue

% of revenue 1995 2009

% of revenue 1995 2009

% of revenue 1995 2009

% of revenue 1995 2009

% of revenue 1995 2009

1995

Hungary Indiaa Indonesiaa Iran, Islamic Rep.a Iraq Ireland Israel Italy Jamaica Japan Jordana Kazakhstana Kenyaa Korea, Dem. Rep. Korea, Rep.a Kosovo Kuwaita Kyrgyz Republica Lao PDR Latviaa Lebanon Lesothoa Liberiaa Libya Lithuania Macedonia, FYRa Madagascar Malawi Malaysiaa Mali Mauritania Mauritius Mexicoa Moldovaa Mongoliaa Moroccoa Mozambique Myanmar a Namibiaa Nepala Netherlands New Zealand Nicaraguaa Niger Nigeriaa Norway Omana Pakistana Panamaa Papua New Guineaa Paraguaya Perua Philippinesa Poland Portugal Puerto Rico Qatar a

4.14

16 23 52 12 .. 37 .. 32 .. .. 10 11 35 .. 31 .. 1 26 .. 7 .. 15 .. .. .. .. .. .. 38 .. .. .. 27 6 31 .. .. 20 27 10 26 .. 9 .. .. .. 21 18 20 40 15 15 33 .. 23 .. ..

2009

23 47 37 19 .. 33 26 32 25 .. 17 24 40 .. 28 .. 1 12 21 8 15 17 28 .. 10 13 12 .. 46 19 .. 23 .. 1 21 28 .. .. 28 14 26 57 29 12 1 28 .. 25 .. .. 16 30 39 14 23 .. 40

28 28 32 5 .. .. .. 21 .. .. 23 28 40 .. 32 .. 0 56 .. 41 .. 12 .. .. .. .. .. .. 27 .. .. .. 54 38 18 .. .. 26 32 33 24 .. 52 .. .. .. 1 27 17 8 36 46 26 .. 33 .. ..

32 23 31 3 .. .. 31 20 37 .. 38 20 41 .. 26 .. .. 42 46 35 44 12 15 .. 36 40 15 .. 16 29 .. 46 .. 46 30 31 .. .. 19 35 27 26 49 18 2 24 .. 32 .. .. 43 39 29 37 31 .. ..

10 24 5 9 .. 0 .. .. .. .. 22 3 14 .. 7 .. 2 5 .. 3 .. 49 .. .. .. .. .. .. 12 .. .. .. 4 5 9 .. .. 12 28 26 .. .. 7 .. .. .. 3 24 11 27 18 10 29 .. 0 .. ..

0 13 2 6 .. 0 1 .. 7 .. 6 6 10 .. 4 .. 1 9 9 0 6 57 39 .. .. 5 31 .. 2 10 .. 2 .. 4 6 6 .. .. 44 16 .. 3 4 26 .. 0 .. 8 .. .. 7 2 20 0 0 .. 2

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

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

35 0 .. 6 .. 17 .. 35 .. .. .. 48 0 .. 8 .. .. .. .. 35 .. .. .. .. .. .. .. .. .. .. .. .. 14 38 15 .. .. .. .. .. 40 .. .. .. .. .. .. .. 16 0 6 10 .. .. 30 .. ..

32 0 .. 19 .. 22 17 36 3 .. 0 .. .. .. 16 .. .. .. .. 31 1 .. .. .. 42 29 4 .. .. .. .. 4 .. 33 17 12 .. .. 0 .. 35 0 .. .. .. 21 .. .. .. .. 7 10 .. 37 33 .. ..

9 25 10 66 .. .. .. 6 .. .. 36 6 10 .. 12 .. 97 11 .. 13 .. 24 .. .. .. .. .. .. 17 .. .. .. 16 2 27 .. .. 42 11 27 8 .. 31 .. .. .. 74 24 34 23 22 11 8 .. .. .. ..

2011 World Development Indicators

12 18 26 52 .. .. 19 5 18 .. 36 51 8 .. 17 .. 98 37 22 26 23 11 18 .. 13 13 32 .. 33 31 .. 17 .. 16 26 17 .. .. 7 29 10 15 18 41 97 26 .. 35 .. .. 26 13 13 10 .. .. 58

247

economy

Central government revenues


4.14

Central government revenues Taxes on income, profits, and capital gains

Taxes on goods and services

Taxes on International trade

Other taxes

Social contributions

Grants and other revenue

% of revenue

% of revenue 1995 2009

% of revenue 1995 2009

% of revenue 1995 2009

% of revenue 1995 2009

% of revenue 1995 2009

1995

Romania Russian Federation Rwandaa Saudi Arabia Senegala Serbiaa Sierra Leonea Singaporea Slovak Republic Sloveniaa Somalia South Africa Spain Sri Lankaa Sudana Swazilanda Sweden Switzerlanda Syrian Arab Republica Tajikistana Tanzania Thailand Timor-Leste Togo Trinidad and Tobagoa Tunisiaa Turkeya Turkmenistan Ugandaa Ukrainea United Arab Emiratesa United Kingdom United States Uruguaya Uzbekistan Venezuela, RBa Vietnam West Bank and Gaza Yemen, Rep.a Zambiaa Zimbabwea World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

2009

.. .. 11 .. 17 .. 15 26 .. 13 .. .. 28 12 17 .. 13 11 23 6 .. .. .. .. 50 16 .. .. 10 .. .. 37 .. 10 .. 38 .. .. 17 27 36 .. m .. .. 17 .. .. 32 .. .. 16 15 .. 21 22

22 1 .. .. .. 9 17 36 9 13 .. 53 24 18 .. .. 11 24 .. .. .. 38 .. 17 63 27 26 .. 22 10 .. 36 47 18 .. .. .. 2 .. 33 .. 23 m .. 25 26 23 21 37 10 27 27 19 .. 24 23

.. .. 25 .. 19 .. 34 20 .. 33 .. .. 21 49 41 .. 33 21 37 63 .. .. .. .. 26 20 .. .. 45 .. 15 32 .. 32 .. 33 .. .. 10 22 22 .. m .. .. 27 .. .. 26 .. .. 16 31 .. 28 24

35 16 .. .. .. 43 25 26 33 33 .. 32 13 45 .. .. 37 26 .. .. .. 38 .. 34 13 31 51 .. 47 34 .. 28 3 41 .. .. .. 21 .. 36 .. 32 m .. 36 33 36 36 31 42 39 31 29 .. 27 27

.. .. 23 .. 36 .. 39 1 .. 9 .. .. 0 17 27 .. .. 1 13 12 .. .. .. .. 6 28 .. .. 7 .. .. .. .. 4 .. 9 .. .. 18 36 17 .. m .. .. 16 .. .. 10 .. .. 16 24 .. .. 0

0 18 .. .. .. 5 14 0 0 0 .. 3 .. 14 .. .. .. 6 .. .. .. 5 .. 18 4 6 1 .. 10 2 .. .. 1 3 .. .. .. 11 .. 8 .. 5m .. 5 6 4 7 6 4 4 6 13 .. 0 0

Note: Components may not sum to 100 percent because of missing data or adjustment to tax revenue. a. Data were reported on a cash basis and have been adjusted to the accrual framework.

248

2011 World Development Indicators

.. .. 3 .. 2 .. 0 15 .. 0 .. .. 0 4 1 .. 4 2 8 0 .. .. .. .. 1 4 .. .. 2 .. .. 6 .. 10 .. 0 .. .. 3 0 3 .. m .. .. 2 .. .. 2 .. .. 6 4 .. 2 2

0 0 .. .. .. 0 .. 14 0 0 .. 2 0 8 .. .. 13 3 .. .. .. 1 .. 3 8 4 5 .. 0 0 .. 7 1 2 .. .. .. 0 .. 0 .. 2m .. 2 1 2 2 1 0 2 3 0 .. 2 2

.. .. 2 .. .. .. .. .. .. 42 .. .. 40 1 .. .. 32 49 0 13 .. .. .. .. 2 15 .. .. .. .. 1 20 .. 31 .. 4 .. .. .. 0 2 .. m .. .. .. .. .. .. .. .. .. .. .. 34 36

33 17 .. .. .. 35 .. .. 43 41 .. 2 58 1 .. .. 25 36 .. .. .. 5 .. .. 4 19 .. .. .. 37 .. 23 43 30 .. .. .. 0 .. .. .. .. m .. .. .. 22 .. .. 29 10 6 0 .. 36 37

.. .. 36 .. 26 .. 12 38 .. 3 .. .. .. 18 14 .. .. 17 19 5 .. .. .. .. 15 17 .. .. 37 .. 84 5 .. 8 .. 19 .. .. 51 15 19 .. m .. .. 23 .. .. 23 .. .. 38 25 .. 10 7

10 48 .. .. .. 7 44 24 15 12 .. 8 4 14 .. .. .. 5 .. .. .. 14 .. 28 9 12 16 .. 22 17 .. 6 6 6 .. .. .. 66 .. 23 .. 17 m .. 17 17 16 18 26 16 17 23 29 .. 12 8


About the data

4.14

Definitions

The International Monetary Fund (IMF) classifies

Direct taxes tend to be progressive, whereas indirect

• Taxes on income, profits, and capital gains are

government revenues as taxes, grants, and property

taxes are proportional.

levied on the actual or presumptive net income

income. Taxes are classified by the base on which

Social security taxes do not reflect compulsory pay-

of individuals, on the profits of corporations and

the tax is levied, grants by the source, and property

ments made by employers to provident funds or other

enterprises, and on capital gains, whether real-

income by type (for example, interest, dividends,

agencies with a like purpose. Similarly, expenditures

ized or not, on land, securities, and other assets.

or rent). The most important source of revenue is

from such funds are not reflected in government

taxes. Grants are unrequited, nonrepayable, non-

expenses (see table 4.13). For further discussion of

compulsory receipts from other government units

taxes and tax policies, see About the data for table

and foreign governments or from international orga-

5.6. For further discussion of government revenues

nizations. Transactions are generally recorded on an

and expenditures, see About the data for tables 4.12

accrual basis.

and 4.13.

Intra-governmental 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

The IMF’s Government Finance Statistics Manual

trade include import duties, export duties, profits

2001 describes taxes as compulsory, unrequited

of export or import monopolies, exchange profits,

payments made to governments by individuals, busi-

and exchange taxes. • Other taxes include employer

nesses, or institutions. Taxes are classified in six

payroll or labor taxes, taxes on property, and taxes

major groups by the base on which the tax is levied:

not allocable to other categories, such as penalties

income, profits, and capital gains; payroll and work-

for late payment or nonpayment of taxes. • Social

force; property; goods and services; international

contributions include social security contributions by

trade and transactions; and other. However, the dis-

employees, employers, and self-employed individu-

tinctions are not always clear. Taxes levied on the

als, and other contributions whose source cannot be determined. They also include actual or imputed

income and profits of individuals and corporations

contributions to social insurance schemes operated

are classified as direct taxes, and taxes and duties

by governments. • Grants and other revenue include

levied on goods and services are classified as indi-

grants from other foreign governments, international

rect taxes. This distinction may be a useful simplifica-

organizations, and other government units; interest;

tion, but it has no particular analytical significance

dividends; rent; requited, nonrepayable receipts

except with respect to the capacity to fix tax rates.

for public purposes (such as fines, administrative

4.14a

Rich economies rely more on direct taxes

fees, and entrepreneurial income from government ownership of property); and voluntary, unrequited, nonrepayable receipts other than grants.

Taxes on income and capital gains as a share of central government revenue, 2009 (percent) 70

60

50

40

30

Data sources

20

Data on central government revenues are from the 10

IMF’s Government Finance Statistics database. Each country’s accounts are reported using the

0 100

10,000

1,000

100,000

GNI per capita ($, log scale) Low income

Middle income

system of common definitions and classifications in the IMF’s Government Finance Statistics Manual 2001. The IMF receives additional information

High income

from the Organisation for Economic Co-operation

High-income economies tend to tax income and property, whereas low-income economies tend to rely

and Development on the tax revenues of some of

on indirect taxes on international trade and goods and services. But there are exceptions in all groups.

its members. See the IMF sources for complete

Note: Data are for the most recent year for 2005–09. Source: International Monetary Fund, Government Finance Statistics data files, and World Development Indicators data files.

and authoritative explanations of concepts, definitions, and data sources.

2011 World Development Indicators

249

economy

Central government revenues


4.15

Monetary indicators Broad money

annual % growth 2000 2009

Afghanistan Albania Algeria Angolaa Argentinaa Armenia Australiaa Austriab Azerbaijan Bangladesh Belarus Belgiumb Benina Bolivia Bosnia and Herzegovinaa Botswana Brazil Bulgaria Burkina Fasoa Burundi Cambodia Cameroona Canada Central African Republica Chada Chile Chinaa Hong Kong SAR, Chinaa Colombia Congo, Dem. Rep.a Congo, Rep.a Costa Rica Côte d’Ivoirea Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopiaa Finlandb Franceb Gabona Gambia, Thea Georgia Germany b Ghana Greeceb Guatemala Guineaa Guinea-Bissaua Haiti Honduras

250

.. 12.0 14.1 303.7 1.5 38.6 3.7 .. 73.4 19.3 219.3 .. 26.0 1.6 11.3 1.4 19.7 30.8 6.2 15.5 26.9 19.1 6.6 2.4 19.4 9.1 12.3 9.3 3.6 40.0 58.5 24.0 –1.9 29.1 .. 16.0 –12.1 16.8 47.0 11.6 1.6 17.3 25.7 13.1 .. .. 18.3 34.8 39.2 .. 54.2 .. 21.4 12.9 60.8 20.3 15.4

33.0 6.8 1.6 62.6 17.0 16.4 0.5 .. –0.3 20.3 25.9 .. 8.0 11.8 –0.1 –1.3 15.8 4.2 22.3 14.5 35.6 6.3 15.1 13.3 1.1 1.3 28.4 5.2 8.1 50.4 5.0 8.0 17.2 –0.6 .. 0.2 7.0 13.4 10.1 9.5 2.1 15.7 –0.1 23.4 .. .. 2.1 19.4 8.2 .. 39.2 .. 11.3 .. 6.9 10.3 0.6

2011 World Development Indicators

Claims on domestic economy

Claims on central government

Annual growth % of broad money 2000 2009

Annual growth % of broad money 2000 2009

.. 0.9 8.4 35.8 –2.9 0.3 13.3 .. –23.9 10.7 59.9 .. 8.5 –1.3 10.3 10.3 8.3 6.5 8.3 15.0 5.4 7.4 3.6 2.9 0.4 4.1 9.5 1.7 8.9 3.8 –23.0 14.1 2.9 21.3 .. –11.0 26.1 13.2 –10.8 4.1 2.6 3.7 .. 3.0 .. .. 6.2 4.2 18.7 .. 7.5 .. 4.2 2.3 5.5 12.3 7.9

8.0 5.4 7.7 33.3 5.1 15.0 8.7 .. 13.2 13.3 64.6 .. 6.7 6.0 –3.8 5.3 6.7 4.2 1.0 8.3 6.3 4.5 23.3 2.8 5.7 –0.6 22.7 3.6 2.7 19.2 5.2 4.9 6.0 –0.6 .. 0.7 –4.4 5.3 5.5 0.5 –4.1 0.2 –9.0 17.7 .. .. –2.6 5.4 –18.1 .. 30.4 .. –2.4 .. 3.9 6.2 7.1

.. 4.8 –11.6 –413.7 –0.8 –5.7 –1.8 .. 15.4 5.6 22.2 .. 0.9 3.1 –0.4 –56.2 13.5 8.5 5.3 –22.6 –6.9 –12.3 2.4 6.8 15.1 4.0 0.0 0.4 6.0 –34.0 –11.7 –0.2 –7.6 2.0 .. 2.6 3.0 2.8 –28.1 7.7 2.3 25.7 –3.2 19.8 .. .. –42.2 2.7 19.8 .. 32.9 .. 10.2 7.9 16.2 13.8 –2.6

–9.5 2.4 0.2 48.1 18.9 –11.8 –2.7 .. 4.3 1.3 –40.9 .. 7.5 –3.0 –0.1 18.7 1.2 2.5 2.7 13.0 5.7 0.9 4.7 –0.3 72.5 0.6 0.6 8.8 7.2 –14.5 12.0 2.8 7.4 0.2 .. 3.9 6.3 8.0 8.8 10.5 –1.3 11.9 –3.6 2.5 .. .. 4.0 5.2 11.0 .. 22.1 .. 6.8 .. –13.3 –12.4 4.8

Interest rate

% Lending

Deposit

Real

2000

2009

2000

2009

2000

2009

.. 8.3 7.5 39.6 8.3 18.1 4.2 2.2 12.9 8.6 37.6 3.6 3.5 11.0 14.7 9.4 17.2 3.1 3.5 .. 6.8 5.0 3.5 5.0 5.0 9.2 2.3 4.8 12.1 .. 5.0 13.4 3.5 3.7 .. 3.4 3.2 17.7 8.8 9.5 9.3 .. 3.8 6.0 1.6 2.6 5.0 12.5 10.2 3.4 28.6 6.1 10.2 7.5 3.5 12.1 15.9

.. 6.8 1.8 7.6 11.6 8.7 2.8 .. 12.2 8.2 10.7 .. 3.5 3.4 3.6 7.5 9.3 6.2 3.5 .. 1.7 3.3 0.1 3.3 3.3 2.0 2.3 0.0 6.1 15.9 3.3 7.0 3.5 3.2 .. 1.3 .. 7.8 4.8 6.5 .. .. 4.8 4.7 .. 1.9 3.3 15.5 10.3 .. 17.1 .. 5.6 .. 3.5 1.1 10.8

.. 22.1 10.0 103.2 11.1 31.6 9.3 5.6 19.7 15.5 67.7 8.0 .. 34.6 30.5 15.5 56.8 11.3 .. 15.8 .. 22.0 7.3 22.0 22.0 14.8 5.9 9.5 18.8 .. 22.0 24.9 .. 12.1 .. 7.2 8.1 26.8 17.1 13.2 14.0 .. 7.4 10.9 5.6 6.7 22.0 24.0 32.8 9.6 .. 12.3 20.9 19.4 .. 19.1 26.8

15.0 12.7 8.0 15.7 15.7 18.8 6.0 .. 20.0 14.6 11.7 9.2 .. 12.4 7.9 13.8 44.7 11.3 .. 14.1 .. 15.0 2.4 15.0 15.0 7.3 5.3 5.0 13.0 65.4 15.0 19.7 .. 11.6 .. 6.0 .. 18.1 12.1 12.0 .. .. 9.4 8.0 .. .. 15.0 27.0 25.5 .. .. .. 13.8 .. .. 17.3 19.4

.. 17.0 –11.7 –60.8 9.9 33.4 6.5 5.2 6.4 13.4 –41.2 5.9 .. 27.9 1.3 15.4 47.7 4.4 .. 2.3 .. 18.6 3.0 18.3 15.9 9.8 3.7 13.6 –10.3 .. –17.0 16.7 .. 7.1 .. 5.6 4.9 18.6 26.0 7.9 10.5 .. 2.4 3.8 2.9 5.2 –4.8 19.6 26.8 10.4 .. 8.6 13.2 7.4 .. 7.3 –3.1

36.1 10.1 19.2 22.8 5.2 17.1 1.0 .. 44.2 7.6 7.5 7.1 .. 15.1 7.9 20.6 36.8 7.0 .. 0.4 .. 12.7 4.6 12.2 9.4 2.9 6.0 4.8 7.7 27.0 14.4 9.9 .. 8.0 .. 3.2 .. 14.7 6.3 1.0 .. .. 10.0 –17.2 .. .. 9.3 24.1 28.1 .. .. .. 11.2 .. .. 13.3 14.4


Broad money

annual % growth 2000 2009

Hungary Indiaa Indonesia Iran, Islamic Rep.a Iraq Irelandb Israela Italy b Jamaica Japan Jordana Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep.a Kosovo Kuwait Kyrgyz Republica Lao PDRa Latvia Lebanona Lesotho Liberiaa Libyaa Lithuania Macedonia, FYR Madagascar a Malawia Malaysia Malia Mauritaniaa Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar a Namibia Nepal Netherlandsb New Zealanda Nicaragua Niger a Nigeria Norwaya Oman Pakistan Panama Papua New Guinea Paraguay Perua Philippines Poland Portugalb Puerto Rico Qatar

12.6 15.2 16.6 22.4 .. .. 8.0 .. –7.0 1.3 7.6 45.0 4.9 .. 25.4 –12.2 6.3 11.7 46.0 27.0 9.8 1.4 18.3 3.1 16.5 22.2 17.2 45.5 10.0 12.2 16.1 9.2 –4.5 41.7 17.6 8.4 38.3 42.5 13.2 18.8 .. 1.5 9.4 12.4 48.1 8.7 6.0 12.1 9.3 5.0 2.8 –0.4 8.1 11.6 .. .. 10.7

3.3 18.0 13.0 27.7 26.7 .. 6.1 .. 5.4 2.1 24.3 19.5 16.5 .. 12.2 11.2 13.4 33.2 18.3 –2.7 19.6 17.7 43.4 17.4 0.6 5.5 11.3 24.6 7.7 14.6 .. 8.1 11.5 3.2 26.9 5.8 32.6 30.6 5.9 29.4 .. –0.6 14.3 18.7 14.4 .. 4.7 14.8 10.3 21.9 22.2 2.6 10.0 8.1 .. .. 16.9

Claims on domestic economy

Claims on central government

Annual growth % of broad money 2000 2009

Annual growth % of broad money 2000 2009

14.5 9.9 7.2 15.8 .. .. 10.7 .. 9.1 –5.4 3.2 32.2 4.7 .. 21.9 12.1 8.5 3.5 22.4 31.2 2.9 6.6 –10.0 0.2 14.4 2.7 7.9 16.5 5.5 –1.5 41.1 5.8 10.1 24.4 29.6 3.6 11.9 13.9 19.4 –4.6 .. 8.0 7.0 14.8 5.8 18.0 1.1 2.0 –8.4 1.2 1.7 –2.7 2.2 .. .. .. –1.7

–4.2 7.8 6.9 10.2 2.0 .. –0.5 .. 2.6 –2.9 0.8 14.1 11.5 .. 3.9 7.6 7.1 29.2 19.4 –25.9 4.8 7.2 17.1 2.0 –12.9 3.1 3.7 19.3 5.5 7.0 .. 0.8 8.1 –4.0 1.2 9.0 32.7 5.2 11.3 26.4 .. 1.3 –7.4 12.1 17.5 .. 7.3 8.0 2.5 8.4 14.8 0.8 5.4 7.9 .. .. 2.9

–2.0 4.7 17.2 –7.9 .. .. –4.8 .. –2.3 2.6 –1.2 –3.2 –2.1 .. –1.4 –37.7 –7.4 7.8 –17.6 7.8 10.5 14.9 197.0 –10.4 0.5 –15.9 0.1 7.7 2.1 –5.0 –64.3 –4.7 3.5 –5.7 –7.1 3.6 6.9 25.0 –4.0 2.6 .. –0.9 10.0 –14.1 –43.0 –4.8 9.5 2.6 0.2 –4.6 4.7 2.3 1.5 –5.8 .. .. –23.1

0.1 9.4 2.5 2.0 33.6 .. 1.1 .. 9.4 4.4 2.5 –4.7 8.2 .. 2.2 1.8 –1.0 –8.8 –3.4 –9.6 4.5 –0.5 47.7 1.8 –4.1 1.3 8.9 21.2 3.3 –13.3 .. 1.1 4.1 4.0 –6.4 –1.1 0.2 29.9 –4.1 –1.6 .. 2.7 7.0 28.9 12.7 .. 1.4 7.4 –0.6 10.1 –3.5 0.3 2.5 1.7 .. .. 26.7

4.15

Interest rate

% Lending

Deposit

Real

2000

2009

2000

2009

2000

2009

9.5 .. 12.5 11.7 .. 0.1 8.6 1.8 11.6 0.1 7.0 .. 8.1 .. 7.9 .. 5.9 18.4 12.0 4.4 11.2 4.9 6.2 3.0 3.9 11.2 15.0 33.3 3.4 3.5 9.4 9.6 8.3 24.9 16.8 5.2 9.7 9.8 7.4 6.0 2.9 6.4 10.8 3.5 11.7 6.7 7.6 .. 7.1 8.5 15.7 9.8 8.3 14.2 2.4 .. 0.0

5.8 .. 9.3 13.1 7.8 .. 1.1 .. 7.0 0.4 4.9 .. 6.0 .. 3.5 4.0 2.8 3.9 4.7 8.0 7.3 4.9 4.1 2.5 4.8 7.0 11.5 3.5 2.1 3.5 8.0 8.4 2.0 14.9 13.3 3.8 9.5 12.0 6.2 2.5 2.6 4.0 6.0 3.5 13.3 2.3 4.1 8.7 3.5 2.3 1.5 2.8 2.7 2.2 .. .. 4.2

12.6 12.3 18.5 .. .. 4.8 12.9 7.0 23.3 2.1 11.8 .. 22.3 .. 8.5 .. 8.9 51.9 32.0 11.9 18.2 17.1 20.5 7.0 12.1 18.9 26.5 53.1 7.7 .. 25.6 20.8 16.9 33.8 37.0 13.3 19.0 15.3 15.3 9.5 4.8 9.3 18.1 .. 21.3 8.9 10.1 .. 10.5 17.5 26.8 30.0 10.9 20.0 5.2 .. ..

11.0 12.2 14.5 12.0 15.6 .. 3.7 4.8 16.4 1.7 9.2 .. 14.8 .. 5.6 14.1 6.2 23.0 24.0 16.2 9.6 13.0 14.2 6.0 8.4 10.1 45.0 25.3 5.1 .. 23.5 19.3 7.1 20.5 21.7 .. 15.7 17.0 11.1 8.0 2.0 10.4 14.0 .. 18.4 4.3 7.4 14.5 8.2 10.1 28.3 21.0 8.6 5.5 .. .. 7.0

0.9 8.5 –1.7 .. .. –1.1 11.1 5.0 11.5 3.9 12.2 .. 15.3 .. 3.4 .. –9.7 19.5 5.5 7.4 20.7 14.4 22.1 –9.6 11.1 9.9 18.0 17.3 –1.1 .. 23.9 18.3 4.3 5.1 8.6 14.0 6.3 12.5 –9.0 4.8 0.6 5.9 8.8 .. –12.2 –5.8 –8.3 .. 11.9 3.9 13.1 25.4 4.3 12.0 1.8 .. ..

6.1 4.3 5.6 11.3 61.5 .. –1.4 2.6 9.3 2.7 1.1 .. 7.6 .. 2.2 18.1 2.5 20.5 14.4 17.1 3.5 9.2 6.3 57.8 10.8 7.1 33.8 15.6 12.6 .. 15.1 17.5 2.7 18.1 21.3 .. 12.0 .. 4.4 –3.6 2.3 8.6 –2.0 .. 19.1 8.7 –16.0 –4.6 4.0 14.2 28.4 17.5 5.9 3.9 .. .. 31.0

2011 World Development Indicators

251

economy

Monetary indicators


4.15

Monetary indicators Broad money

annual % growth 2000 2009

Romania Russian Federation Rwandaa Saudi Arabiaa Senegala Serbia Sierra Leonea Singaporea Slovak Republicb Sloveniab Somalia South Africa Spainb Sri Lankaa Sudan Swaziland Sweden Switzerlanda Syrian Arab Republic Tajikistana Tanzania Thailand Timor-Leste Togoa Trinidad and Tobagoa Tunisiaa Turkey Turkmenistana Uganda Ukraine United Arab Emiratesa United Kingdoma United States Uruguay Uzbekistan Venezuela, RBa Vietnama West Bank and Gaza Yemen, Rep.a Zambia Zimbabwea

40.8 57.9 15.6 4.5 10.7 160.8 12.1 –2.0 .. .. .. 7.2 .. 12.9 36.9 –6.6 1.9 –16.9 19.0 63.3 14.8 4.9 41.1 15.2 11.7 14.1 40.7 83.3 18.1 44.5 15.3 11.1 8.1 9.5 .. 33.7 35.4 .. 25.3 73.8 45.7

9.0 16.4 .. 10.8 11.4 21.3 27.5 11.3 .. .. .. 1.8 .. 18.7 23.7 26.8 2.5 7.6 8.6 –3.6 17.7 6.8 39.3 16.0 30.6 12.5 12.7 .. 17.5 –5.5 9.8 0.0 –0.6 –2.6 .. 26.1 26.2 .. 12.8 7.7 111.3

Claims on domestic economy

Claims on central government

Annual growth % of broad money 2000 2009

Annual growth % of broad money 2000 2009

20.0 33.2 10.3 3.3 19.1 –71.0 1.6 5.1 .. .. .. –11.8 .. 9.1 16.9 16.9 8.5 –1.2 –4.1 8.2 12.2 6.2 45.7 0.5 8.8 23.7 16.2 10.8 8.2 30.9 8.7 17.4 5.0 45.1 .. 14.3 29.6 .. 3.6 –11.4 27.2

1.9 2.1 .. 0.0 2.6 18.1 14.2 1.6 .. .. .. 0.1 .. –4.6 13.6 12.5 3.8 5.1 8.6 145.1 5.8 3.6 0.6 9.7 –3.1 9.7 9.4 .. 10.1 –3.4 1.4 –2.6 –1.3 –10.3 .. 18.6 35.0 .. –1.2 –3.4 56.4

–1.1 –18.1 –11.4 –3.5 –3.9 22.5 54.6 –1.6 .. .. .. 0.2 .. 12.5 33.9 1.7 2.4 2.1 –6.1 36.6 0.7 0.5 –36.8 –0.5 –13.2 5.6 26.8 –53.4 29.4 –1.7 –9.6 –2.4 0.5 –1.8 .. –6.4 –2.4 .. –45.6 162.0 29.5

10.7 14.0 .. 8.9 4.3 4.9 4.0 8.9 .. .. .. 5.5 .. 4.4 13.0 17.4 1.6 0.6 1.4 –9.8 6.2 0.9 12.1 6.3 25.3 1.4 12.4 .. 0.4 9.4 13.3 7.9 4.5 3.0 .. –1.9 7.0 .. 26.2 16.2 –28.7

Interest rate

% Lending

Deposit

Real

2000

2009

2000

2009

2000

2009

33.1 6.5 10.1 .. 3.5 78.7 9.2 1.7 8.5 10.0 .. 9.2 3.0 9.2 .. 6.5 2.2 3.0 4.0 1.3 7.4 3.3 0.8 3.5 8.2 .. 47.2 .. 9.8 13.7 6.2 4.5 .. 18.3 .. 16.3 3.7 .. 14.0 20.2 50.2

12.0 8.6 6.7 .. 3.5 11.8 9.7 0.3 3.7 1.4 .. 8.5 .. 10.6 .. 5.4 .. 0.1 6.4 5.8 8.0 1.0 0.8 3.5 3.4 .. 17.6 .. 9.8 13.8 .. .. .. 4.4 .. 16.4 12.7 .. 10.7 7.1 121.5

53.9 24.4 17.0 .. .. 6.3 26.3 5.8 14.9 15.8 .. 14.5 5.2 16.2 .. 14.0 5.8 4.3 9.0 25.6 21.6 7.8 16.7 .. 16.5 .. .. .. 22.9 41.5 9.7 6.0 9.2 46.1 .. 25.2 10.6 .. 19.5 38.8 68.2

17.3 15.3 16.5 .. .. 11.8 24.5 5.4 5.8 5.9 .. 11.7 .. 15.7 .. 11.4 .. 2.8 10.0 22.9 15.0 6.0 11.2 .. 11.9 .. .. .. 21.0 20.9 .. 0.6 3.3 15.3 .. 19.9 10.1 .. 18.0 22.1 579.0

6.7 –9.6 20.6 .. .. –40.1 19.0 2.0 5.0 9.9 .. 5.2 1.7 8.3 .. 13.8 4.3 3.1 –0.6 2.4 13.0 6.4 11.4 .. 3.2 .. .. .. 10.6 15.0 –9.9 4.7 6.9 41.1 .. –3.3 6.9 .. –4.9 6.7 67.8

10.1 12.5 3.3 .. .. 1.6 12.0 7.4 2.8 4.0 .. 4.1 .. 9.5 .. 5.6 .. 2.5 19.0 8.5 7.1 3.9 1.1 .. 32.8 .. .. .. 3.8 6.6 .. –0.7 2.3 8.9 .. 10.6 3.8 .. 23.1 8.3 ..

a. For these countries data reported under Claims on domestic economy include claims on private sector only. b. As members of the European Monetary Union, these countries share a single currency, the euro.

252

2011 World Development Indicators


About the data

4.15

Definitions

Money and the financial accounts that record the

reporting period. The valuation of financial deriva-

• Broad money (IFS line 35L..ZK) is the sum of

supply of money lie at the heart of a country’s

tives and the net liabilities of the banking system

currency outside banks; demand deposits other

financial system. There are several commonly used

can also be difficult. The quality of commercial bank

than those of the central government; the time,

definitions of the money supply. The narrowest,

reporting also may be adversely affected by delays in

savings, and foreign currency deposits of resident

M1, encompasses currency held by the public and

reports from bank branches, especially in countries

sectors other than the central government; bank

demand deposits with banks. M2 includes M1 plus

where branch accounts are not computerized. Thus

and traveler’s checks; and other securities such

time and savings deposits with banks that require

the data in the balance sheets of commercial banks

as certificates of deposit and commercial paper.

prior notice for withdrawal. M3 includes M2 as well

may be based on preliminary estimates subject to

Change in broad money is measured as the differ-

as various money market instruments, such as cer-

constant revision. This problem is likely to be even

ence in end-of-year totals relative to the preceding

tificates of deposit issued by banks, bank deposits

more serious for nonbank financial intermediaries.

year. For countries reporting under the old presen-

denominated in foreign currency, and deposits with

Many interest rates coexist in an economy, reflect-

tation of monetary statistics and for all countries

financial institutions other than banks. However

ing competitive conditions, the terms governing

prior to 2001, data are based on money plus quasi

defined, money is a liability of the banking system,

loans and deposits, and differences in the position

money. • Claims on domestic economy (IFS line

distinguished from other bank liabilities by the spe-

and status of creditors and debtors. In some econo-

32S..ZK) include gross credit from the financial

cial role it plays as a medium of exchange, a unit of

mies interest rates are set by regulation or adminis-

system to households, nonprofit institutions serv-

account, and a store of value.

trative fiat. In economies with imperfect markets, or

ing households, nonfinancial corporations, state

The banking system’s assets include its net for-

where reported nominal rates are not indicative of

and local governments, and social security funds.

eign assets and net domestic credit. Net domestic

effective rates, it may be difficult to obtain data on

For countries where claims on domestic economy

credit includes credit extended to the private sector

interest rates that reflect actual market transactions.

are not available, data are claims on private sec-

and general government and credit extended to the

Deposit and lending rates are collected by the Inter-

tor (IFS line 32D..ZK or 32D..ZF) • Claims on cen-

nonfinancial public sector in the form of investments

national Monetary Fund (IMF) as representative inter-

tral government (IFS line 32AN..ZK) include loans

in short- and long-term government securities and

est rates offered by banks to resident customers.

to central government institutions net of deposits.

loans to state enterprises; liabilities to the public

The terms and conditions attached to these rates

• Deposit interest rate is the rate paid by commer-

and private sectors in the form of deposits with the

differ by country, however, limiting their comparabil-

cial or similar banks for demand, time, or savings

banking system are netted out. Net domestic credit

ity. Real interest rates are calculated by adjusting

deposits. • Lending interest rate is the rate charged

also includes credit to banking and nonbank financial

nominal rates by an estimate of the inflation rate in

by banks on loans to prime customers. • Real inter-

institutions.

the economy. A negative real interest rate indicates

est rate is the lending interest rate adjusted for infla-

Domestic credit is the main vehicle through which

a loss in the purchasing power of the principal. The

tion as measured by the GDP deflator.

changes in the money supply are regulated, with cen-

real interest rates in the table are calculated as (i –

tral bank lending to the government often playing the

P) / (1 + P), where i is the nominal lending interest

most important role. The central bank can regulate

rate and P is the inflation rate (as measured by the

lending to the private sector in several ways—for

GDP deflator).

example, by adjusting the cost of the refinancing

In 2009 the IMF began publishing a new presenta-

facilities it provides to banks, by changing market

tion of monetary statistics for countries that report

interest rates through open market operations, or by

data in accordance with the IMF’s Monetary and

controlling the availability of credit through changes

Financial Statistics Manual 2000. The presentation

in the reserve requirements imposed on banks and

for countries that report data in accordance with the

Data on monetary and financial statistics are

ceilings on the credit provided by banks to the pri-

IMF’s International Financial Statistics (IFS) remains

published by the IMF in its monthly International

vate sector.

the same.

Financial Statistics and annual International Finan-

Data sources

Monetary accounts are derived from the balance

cial Statistics Yearbook. The IMF collects data on

sheets of financial institutions—the central bank,

the financial systems of its member countries. The

commercial banks, and nonbank financial interme-

World Bank receives data from the IMF in elec-

diaries. Although these balance sheets are usually reliable, they are subject to errors of classification,

tronic files that may contain more recent revisions Data sources than the published sources. The discussion of

valuation, and timing and to differences in account-

monetary indicators draws from an IMF publication

ing practices. For example, whether interest income

by Marcello Caiola, A Manual for Country Econo-

is recorded on an accrual or a cash basis can make

mists (1995). Also see the IMF’s Monetary and

a substantial difference, as can the treatment of non-

Financial Statistics Manual (2000) for guidelines

performing assets. Valuation errors typically arise

for the presentation of monetary and financial sta-

for foreign exchange transactions, particularly in

tistics. Data on real interest rates are derived from

countries with flexible exchange rates or in countries

World Bank data on the GDP deflator.

that have undergone currency devaluation during the

2011 World Development Indicators

253

economy

Monetary indicators


4.16 Afghanistan Albania Algeria Angola Argentina Armenia Australia Austriac Azerbaijan Bangladesh Belarus Belgiumc Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong, SAR China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland c Francec Gabon Gambia, The Georgia Germanyc Ghana Greecec Guatemala Guinea Guinea-Bissau Haiti Honduras

254

Exchange rates and prices Official exchange rate

Purchasing power parity (PPP) conversion factor

local currency units to $ 2009 2010a

local currency units to international $ 1995 2009

50.23 94.98 72.65 79.33 3.71 363.28 1.28 0.72 0.80 69.04 2,789.49 0.72 472.19 7.02 1.41 7.16 2.00 1.41 472.19 1,230.18 4,139.33 472.19 1.14 472.19 472.19 560.86 6.83 7.75 2,166.79 809.79 472.19 573.29 472.19 5.28 .. 19.06 5.36 36.03 .. 5.54 8.75 15.38 11.26 11.78 0.72 0.72 472.19 26.64 1.67 0.72 1.41 0.72 8.16 .. 472.19 41.20 18.90

45.21 .. 104.95 24.4 74.25 15.3 92.35 0.0 3.96 1.0 360.50 116.6 1.01 1.3 0.76 0.9 0.80 0.2 70.63 19.2 3,010.98 3.4 0.76 0.9 496.24 187.4 7.02 1.7 1.48 0.6 6.58 1.4 1.70 0.7 1.48 0.0 496.24 189.5 1,230.91 126.6 4,096.00 1,142.3 496.24 241.1 1.01 1.2 496.24 271.9 496.24 163.1 474.78 264.1 6.65 3.4 7.77 7.9 1,925.90 417.8 907.62 0.0 496.24 149.2 512.34 103.0 496.24 261.8 5.59 3.1 .. .. 19.03 11.1 5.64 8.5 37.41 7.3 .. 0.4 5.74 1.2 8.75 0.4 15.38 1.9 11.82 4.8 .. 2.1 0.76 1.0 0.76 1.0 496.24 187.9 28.12 3.9 1.76 0.4 0.76 1.0 1.49 0.1 0.76 0.6 7.98 2.9 .. 747.4 496.24 58.6 39.90 5.8 18.90 3.0

2011 World Development Indicators

18.1 41.5 35.8 55.7 2.0 194.5 1.5 0.8 0.4 26.8 1,085.6 0.9 233.3 2.8 0.7 3.2 1.6 0.7 205.5 500.6 1,526.8 243.3 1.2 282.8 221.6 377.1 3.8 5.4 1,233.7 414.3 289.8 329.5 306.9 3.8 .. 13.5 8.0 19.7 0.5 2.2 0.5 9.8 8.1 4.3 0.9 0.9 245.7 8.1 0.9 0.8 1.0 0.7 4.6 2,066.8 229.0 23.1 9.4

Ratio of PPP conversion factor to market exchange rate

2009

0.4 0.4 0.5 0.7 0.5 0.5 1.1 1.2 0.5 0.4 0.4 1.2 0.5 0.4 0.5 0.5 0.8 0.5 0.4 0.4 0.4 0.5 1.1 0.6 0.5 0.7 0.6 0.7 0.6 0.5 0.6 0.6 0.7 0.7 .. 0.7 1.5 0.6 0.5 0.4 0.5 0.6 0.7 0.4 1.3 1.2 0.5 0.3 0.5 1.1 0.7 1.0 0.6 0.4 0.5 0.6 0.5

Real effective exchange rate

GDP implicit deflator

Consumer price index

Wholesale price index

Index average annual average annual average annual 2000 = 100 % growth % growth % growth 2009 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09

.. .. 102.1 .. .. 124.4 100.8 101.5 .. .. .. 104.3 .. 127.6 .. .. .. 126.0 .. 109.4 .. 108.0 96.8 115.8 .. 100.3 119.8 .. 113.1 597.2 .. 108.4 105.7 108.6 .. 120.4 105.6 96.2 98.8 .. .. .. .. .. 103.8 101.8 105.3 104.4 124.3 102.3 91.9 106.9 .. .. .. .. ..

.. 37.7 18.5 739.4 5.2 212.5 1.4 1.6 203.0 4.1 355.1 1.8 8.7 8.6 4.1 9.7 211.8 102.1 3.7 13.4 4.4 6.3 1.5 4.5 7.1 7.9 7.9 4.5 22.6 964.9 9.0 15.9 9.2 90.0 6.4 12.8 1.6 9.8 4.4 8.7 6.2 7.9 53.7 6.5 1.9 1.3 7.0 4.2 356.7 1.7 26.7 9.2 10.4 5.5 32.5 18.1 19.9

9.0 3.5 8.6 41.1 12.9b 4.5 4.1 1.7 9.9 5.2 23.1 2.1 3.4 6.9 3.9 9.0 8.3 6.0 2.5 10.4 5.0 2.1 2.6 2.7 5.6 6.3 4.3 –1.3 6.1 27.2 7.4 10.2 3.5 3.9 3.3 2.2 2.3 13.7 9.1 8.3 3.6 18.6 5.3 10.8 1.1 2.1 5.0 9.8 7.0 1.1 27.2 3.1 5.4 16.1 11.8 15.3 6.4

.. 27.8 17.3 711.0 8.9 70.5 2.1 2.2 179.7 5.5 271.3 1.9 8.7 8.7 .. 10.4 199.5 117.5 5.5 16.1 6.3 6.5 1.7 5.3 6.9 .. 8.6 5.9 20.2 930.2 9.3 15.6 7.2 86.3 .. 7.8 2.1 8.7 37.1 8.8 8.5 .. 21.6 5.5 1.5 1.6 4.6 4.0 24.7 2.1 28.4 9.0 10.1 .. 34.0 21.9 18.8

9.5 2.8 3.0 41.1 10.0 4.0 3.0 2.0 8.3 6.8 18.7 2.1 3.2 5.3 .. 8.9 6.9 6.4 3.1 9.2 6.0 2.5 2.1 3.2 2.7 .. 2.3 0.3 5.8 26.9 3.4 11.2 3.0 2.9 .. 2.5 2.0 14.6 6.6 8.0 3.9 .. 4.4 12.3 1.5 1.8 2.1 7.6 7.0 1.7 16.2 3.2 7.3 .. 2.4 16.5 7.9

.. .. .. .. 0.1 .. 1.1 0.3 .. .. 267.8 1.2 .. .. .. .. 204.9 85.7 .. .. .. .. 2.7 6.0 .. 7.0 .. 0.6 16.4 .. .. 14.1 .. 69.8 .. 8.2 1.1 .. .. 6.1 .. .. 8.1 .. 0.9 .. .. .. .. 0.4 .. 3.6 .. .. .. .. ..

.. 4.5 4.0 .. 15.7 1.3 3.6 2.4 .. .. 22.5 2.9 .. .. .. .. 10.0 6.2 .. .. .. .. 1.4 4.4 .. 6.5 .. –0.2 4.9 .. .. 13.0 .. 3.0 .. 2.3 2.4 .. 7.9 9.6 4.7 .. 3.4 .. 2.1 1.8 .. .. 6.7 2.5 .. 4.3 .. .. .. .. ..


Hungary India Indonesia Iran, Islamic Rep. Iraq Irelandc Israel Italyc Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlandsc New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugalc Puerto Rico Qatar

Official exchange rate

Purchasing power parity (PPP) conversion factor

local currency units to $ 2009 2010a

local currency units to international $ 1995 2009

202.34 48.41 10,389.94 9,864.30 1,170.00 0.72 3.93 0.72 87.89 93.57 0.71 147.50 77.35 .. 1,276.93 0.72 0.29 42.90 8,516.05 0.51 1,507.50 8.47 68.29 1.25 2.48 44.10 1,956.21 141.17 3.52 472.19 262.37 31.96 13.51 11.11 1,437.80 8.06 27.52 5.52 8.47 77.55 0.72 1.60 20.34 472.19 148.90 6.29 0.38 81.71 1.00 2.76 4,965.39 3.01 47.68 3.12 0.72 .. 3.64

209.67 61.7 45.16 10.8 8,948.00 1,031.3 10,364.64 567.2 1,170.00 252.5 0.76 0.8 3.60 2.8 0.76 0.8 85.67 14.6 83.43 175.0 0.71 0.4 147.41 17.5 80.57 15.8 .. .. 1,146.23 709.6 0.76 .. 0.28 0.2 47.00 3.5 8,245.42 327.6 0.53 0.2 1,507.50 774.7 6.84 2.1 71.85 0.6 1.23 .. 2.61 1.2 46.55 18.0 2,117.83 287.5 150.80 4.2 3.13 1.4 496.24 226.7 .. 62.4 30.54 10.5 12.40 2.9 12.15 1.2 1,256.47 158.6 8.43 4.9 35.64 4.0 5.42 .. 6.84 2.2 72.38 15.4 0.76 0.9 1.29 1.5 21.84 3.5 496.24 203.1 148.57 15.5 5.98 9.2 0.38 0.2 85.77 10.1 1.00 0.5 2.64 0.7 4,667.57 948.9 2.82 1.2 43.95 14.1 3.02 1.2 0.76 0.7 .. .. 3.64 ..

128.2 17.2 5,813.6 3,875.0 689.4 0.9 3.7 0.8 52.0 114.7 0.5 93.0 36.3 .. 804.7 .. 0.3 16.2 3,548.2 0.4 942.9 4.5 38.2 0.7 1.6 17.8 852.8 55.1 1.8 275.4 125.0 16.8 7.7 5.9 643.7 5.0 13.0 .. 5.6 28.4 0.9 1.5 8.2 241.0 75.6 8.9 0.3 28.8 0.6 1.4 2,462.5 1.6 23.6 1.9 0.6 .. 2.8

Ratio of PPP conversion factor to market exchange rate

2009

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

Real effective exchange rate

GDP implicit deflator

Consumer price index

Wholesale price index

Index average annual average annual average annual 2000 = 100 % growth % growth % growth 2009 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09

103.8 .. .. 142.1 .. 107.4 110.2 103.2 .. 101.4 .. .. .. .. .. .. .. .. .. .. .. 93.2 .. .. .. 104.2 .. 107.5 103.3 .. .. .. .. 135.3 .. 102.4 .. .. .. .. 102.7 86.4 107.8 .. 109.4 97.8 .. 98.6 .. 116.1 135.7 .. 121.3 98.5 102.1 .. ..

19.6 8.1 15.8 27.7 .. 3.6 11.0 3.8 24.8 0.0 3.2 204.7 16.6 .. 5.9 .. 1.5 110.6 27.2 48.0 19.0 9.7 51.8 .. 75.0 79.3 19.1 33.6 4.1 7.0 8.7 6.3 19.0 119.6 57.8 4.0 34.1 25.3 11.1 8.0 2.1 1.7 42.4 6.0 29.5 2.7 0.1 11.1 3.6 7.6 11.5 26.7 8.4 24.7 5.2 3.0 ..

4.9 5.6 11.1 16.4 11.6 2.1 1.3 2.6 11.2 –1.1 6.1 14.9 6.0 .. 2.2 0.8 9.8 8.3 8.9 8.8 2.6 8.1 10.3 17.9 4.1 3.8 11.2 17.0 4.0 4.5 10.8 6.0 7.8 11.0 14.6 2.0 8.0 .. 7.1 6.6 2.1 3.1 7.7 3.1 15.3 4.6 9.8 8.5 2.4 6.5 10.2 3.5 5.1 2.7 2.6 .. 10.6

20.3 9.1 13.7 26.0 .. 2.3 9.7 3.7 23.5 0.8 3.5 67.8 15.6 .. 5.1 .. 2.0 23.3 28.3 29.2 .. 5.9 .. 5.6 32.6 10.6 18.7 33.8 3.6 5.2 6.1 6.9 19.5 21.4 35.7 3.9 31.8 25.9 .. 8.7 2.4 1.8 .. 6.1 32.5 2.2 .. 9.7 1.1 9.3 13.1 27.3 7.7 25.3 4.5 .. 2.8

5.5 5.3 9.1 15.4 .. 3.2 1.8 2.3 11.7 –0.1 4.4 8.6 11.3 .. 3.1 1.5 3.4 6.9 8.3 6.5 .. 7.8 .. 0.4 3.1 2.4 10.7 12.2 2.4 2.5 7.3 6.3 4.5 10.8 8.7 2.0 10.9 22.4 5.9 6.2 1.9 2.7 8.8 2.8 12.5 1.8 2.9 8.0 2.5 5.9 8.4 2.4 5.5 2.5 2.7 .. 7.2

16.8 7.4 15.4 28.4 .. 1.6 8.1 2.9 .. –1.0 .. 16.3 .. .. 3.7 .. 1.4 35.6 .. 12.0 .. .. .. .. 24.8 8.5 .. .. 3.4 .. .. .. 18.4 .. .. 2.9 .. .. .. .. 1.3 1.5 .. .. .. 1.6 .. 10.4 1.0 .. .. 23.7 6.3 19.8 .. .. ..

2011 World Development Indicators

3.5 5.1 11.2 10.8 .. –0.1 4.5 2.7 .. 0.7 9.1 13.3 .. .. 2.5 .. 2.5 10.2 .. 7.3 .. .. .. .. 4.8 2.5 .. .. 4.8 .. .. .. 6.1 .. .. .. .. .. .. .. 2.7 3.3 .. .. .. 7.9 .. 8.9 3.8 .. 10.3 2.8 7.0 2.7 2.6 .. ..

255

economy

4.16

Exchange rates and prices


4.16 Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republicc Sloveniac Somalia South Africa Spainc Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe

Exchange rates and prices Official exchange rate

Purchasing power parity (PPP) conversion factor

local currency units to $ 2009 2010a

local currency units to international $ 1995 2009

3.05 3.24 0.1 31.74 30.85 1.7 568.28 594.45 126.3 3.75 3.75 1.8 472.19 496.24 251.9 67.58 80.39 2.9 3,385.65 .. 379.5 1.45 1.31 1.3 0.72 0.76 0.4 0.72 0.76 0.4 .. .. .. 8.47 6.84 2.3 0.72 0.76 0.7 114.94 111.11 18.2 2.30 .. 0.3 8.47 6.84 2.2 7.65 6.85 9.4 1.09 0.97 2.0 11.23 11.23 12.8 4.14 4.40 0.0 1,320.31 1,462.88 159.4 34.29 30.12 15.1 .. .. .. 472.19 496.24 238.5 6.32 6.37 2.8 1.35 1.45 0.5 1.55 1.52 0.0 .. .. 0.0 2,030.31 .. 500.3 7.79 7.96 0.3 3.67 3.67 1.7 0.64 0.64 0.6 1.00 1.00 1.0 22.57 19.99 5.5 .. .. 11.2 2.15 2.59 0.1 17,065.08 18,932.00 3,168.8 .. .. .. 202.85 214.40 22.1 5,046.11 4,735.74 404.0 .. .. ..

1.6 14.6 261.0 2.4 265.2 33.4 1,399.7 1.1 0.5 0.6 .. 4.8 0.7 49.8 1.4 4.2 8.9 1.5 24.4 1.5 487.3 16.7 0.6 239.5 3.9 0.6 0.9 1.5 767.5 3.2 3.2 0.6 1.0 16.1 602.5 2.0 6,434.3 .. 91.8 3,492.7 ..

Ratio of PPP conversion factor to market exchange rate

2009

0.5 0.5 0.5 0.6 0.6 0.5 0.4 0.7 0.7 0.9 .. 0.6 1.0 0.4 0.6 0.5 1.2 1.4 0.5 0.4 0.4 0.5 0.6 0.5 0.6 0.5 0.6 0.5 0.4 0.4 0.9 1.0 1.0 0.7 0.4 0.9 0.4 .. 0.5 0.7 ..

Real effective exchange rate

GDP implicit deflator

Consumer price index

Wholesale price index

Index average annual average annual average annual 2000 = 100 % growth % growth % growth 2009 1990–2000 2000–09 1990–2000 2000–09 1990–2000 2000–09

102.2 115.3 .. 103.8 .. .. 104.5 107.9 137.2 .. .. 87.8 106.2 .. .. .. 89.5 101.6 .. .. .. .. .. 104.8 123.7 94.2 .. .. 103.2 96.8 .. 80.8 95.2 120.9 .. 191.2 .. .. .. 119.5 ..

98.0 161.5 14.3 1.6 6.0 .. 31.9 1.3 11.1 29.3 .. 9.9 3.9 9.1 65.5 10.5 2.2 1.1 7.9 235.0 23.0 4.2 .. 7.0 5.4 4.4 81.7 408.2 11.6 271.0 2.2 2.8 2.0 32.6 245.8 45.3 15.2 5.7 22.4 52.1 –3.9

15.9 15.8 10.5 7.6 2.8 16.5 9.5 1.2 3.4 4.0 .. 7.2 3.7 10.7 10.0 7.9 1.7 1.2 8.0 20.9 7.3 3.2 4.5 1.4 6.5 3.2 15.3 13.0 5.6 16.4 10.2 2.6 2.6 8.4 24.7 25.0 8.3 3.4 13.0 16.4 4.1

100.5 99.1 16.2 1.0 5.4 50.2 .. 1.7 8.4 12.0 .. 8.7 3.8 9.9 72.0 9.5 1.9 1.6 6.4 .. 20.9 4.9 .. 8.5 5.7 4.4 79.9 .. 8.3 155.7 .. 2.9 2.7 33.9 .. 49.0 4.1 .. 26.3 57.0 29.0

11.5 12.5 8.9 2.2 2.2 15.4 .. 1.5 4.8 4.2 .. 5.7 3.1 11.1 8.6 7.3 1.5 1.0 6.2 12.7 6.5 2.9 5.1 2.8 6.5 3.3 16.9 .. 6.7 10.9 .. 2.9 2.7 9.1 .. 21.2 7.8 .. 11.4 15.9 497.7

93.8 99.8 .. 1.3 .. .. .. –1.0 9.5 9.1 .. 7.7 2.4 8.1 .. .. 2.5 –0.4 4.7 .. .. 3.8 .. .. 2.8 3.6 75.2 .. .. 161.6 .. 2.4 1.2 27.2 .. 44.1 .. .. .. 101.4 25.9

15.3 15.7 .. 2.5 .. .. .. 2.8 4.7 3.9 .. 6.7 3.2 12.4 .. .. 2.9 1.1 3.2 .. .. 5.5 .. .. 3.8 4.5 16.9 .. .. 14.6 .. 1.8 4.2 13.6 .. 26.0 .. .. .. .. ..

Note: The differences in the growth rates of the GDP deflator and the consumer and wholesale price indexes are due mainly to differences in data availability for each of the indexes during the period. a. Average for December or latest monthly data available. b. Private analysts estimate that consumer price index inflation was considerably higher for 2007–09 and that GDP volume growth has been significantly lower than official reports indicate since the last quarter of 2008. c. As members of the euro area, these countries share a single currency, the euro.

256

2011 World Development Indicators


About the data

4.16

Definitions

In a market-based economy, household, producer,

cost indicator of relative normalized unit labor costs

• Official exchange rate is the exchange rate deter-

and government choices about resource allocation

in manufacturing. For selected other countries the

mined by national authorities or the rate determined

are influenced by relative prices, including the real

nominal effective exchange rate index is based on

in the legally sanctioned exchange market. It is cal-

exchange rate, real wages, real interest rates, and

manufactured goods and primary products trade with

culated as an annual average based on monthly aver-

other prices in the economy. Relative prices also

partner or competitor countries. For these countries

ages (local currency units relative to the U.S. dollar).

largely reflect these agents’ choices. Thus relative

the real effective exchange rate index is the nomi-

• Purchasing power parity (PPP) conversion factor

prices convey vital information about the interaction

nal index adjusted for relative changes in consumer

is the number of units of a country’s currency required

of economic agents in an economy and with the rest

prices; an increase represents an appreciation of

to buy the same amount of goods and services in the

of the world.

the local currency. Because of conceptual and data

domestic market that a U.S. dollar would buy in the

limitations, changes in real effective exchange rates

United States. • Ratio of PPP conversion factor to

should be interpreted with caution.

market exchange rate is the result obtained by divid-

The exchange rate is the price of one currency in terms of another. Official exchange rates and exchange rate arrangements are established by

Inflation is measured by the rate of increase in a

ing the PPP conversion factor by the market exchange

governments. Other exchange rates recognized by

price index, but actual price change can be nega-

rate. • Real effective exchange rate is the nominal

governments include market rates, which are deter-

tive. The index used depends on the prices being

effective exchange rate (a measure of the value of a

mined largely by legal market forces, and for coun-

examined. The GDP deflator reflects price changes

currency against a weighted average of several for-

tries with multiple exchange arrangements, principal

for total GDP. The most general measure of the over-

eign currencies) divided by a price deflator or index

rates, secondary rates, and tertiary rates.

all price level, it accounts for changes in government

of costs. • GDP implicit deflator measures the aver-

Official or market exchange rates are often used

consumption, capital formation (including inventory

age annual rate of price change in the economy as a

to convert economic statistics in local currencies to

appreciation), international trade, and the main com-

whole for the periods shown. • Consumer price index

a common currency in order to make comparisons

ponent, household final consumption expenditure.

reflects changes in the cost to the average consumer

across countries. Since market rates reflect at best

The GDP deflator is usually derived implicitly as the

of acquiring a basket of goods and services that may

the relative prices of tradable goods, the volume of

ratio of current to constant price GDP—or a Paasche

be fixed or may change at specified intervals, such

goods and services that a U.S. dollar buys in the

index. It is defective as a general measure of inflation

as yearly. The Laspeyres formula is generally used.

United States may not correspond to what a U.S.

for policy use because of long lags in deriving esti-

• Wholesale price index refers to a mix of agricul-

dollar converted to another country’s currency at

mates and because it is often an annual measure.

tural and industrial goods at various stages of pro-

the official exchange rate would buy in that country,

Consumer price indexes are produced more fre-

particularly when nontradable goods and services

quently and so are more current. They are also con-

account for a significant share of a country’s output.

structed explicitly, based on surveys of the cost of

An alternative exchange rate—the purchasing power

a defined basket of consumer goods and services.

parity (PPP) conversion factor—is preferred because

Nevertheless, consumer price indexes should be

it reflects differences in price levels for both tradable

interpreted with caution. The definition of a house-

and nontradable goods and services and therefore

hold, the basket of goods, and the geographic (urban

provides a more meaningful comparison of real out-

or rural) and income group coverage of consumer

put. See table 1.1 for further discussion.

price surveys can vary widely by country. In addi-

The ratio of the PPP conversion factor to the official

tion, weights are derived from household expendi-

exchange rate—the national price level or compara-

ture surveys, which, for budgetary reasons, tend to

tive price level—measures differences in the price

be conducted infrequently in developing countries,

level at the gross domestic product (GDP) level. The

impairing comparability over time. Although useful for

price level index tends to be lower in poorer coun-

measuring consumer price inflation within a country,

tries and to rise with income. The real effective

consumer price indexes are of less value in compar-

exchange rate is a nominal effective exchange rate

ing countries.

duction and distribution, including import duties. The Laspeyres formula is generally used.

index adjusted for relative movements in national

Wholesale price indexes are based on the prices

price or cost indicators of the home country, selected

at the first commercial transaction of commodities

countries, and the euro area. A nominal effective

that are important in a country’s output or consump-

exchange rate index is the ratio (expressed on the

tion. Prices are farm-gate for agricultural commodi-

base 2000 = 100) of an index of a currency’s period-

ties and ex-factory for industrial goods. Preference

Data on official and real effective exchange rates

average exchange rate to a weighted geometric aver-

is given to indexes with the broadest coverage of

and consumer and wholesale price indexes are

age of exchange rates for currencies of selected

the economy. The least squares method is used to

from the International Monetary Fund’s Interna-

countries and the euro area. For most high-income

calculate growth rates of the GDP implicit deflator,

tional Financial Statistics. PPP conversion fac-

countries weights are derived from industrial coun-

consumer price index, and wholesale price index.

tors and GDP deflators are from the World Bank’s

try trade in manufactured goods. Data are compiled

Data sources

data files.

from the nominal effective exchange rate index and a

2011 World Development Indicators

257

economy

Exchange rates and prices


4.17

Balance of payments current account Goods and services

$ millions

Exports 1995

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China† Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras †Data for Taiwan, China

258

2009

.. .. 304 3,458 .. .. 3,836 41,451 24,987 66,563 300 1,338 69,710 234,298 89,906 189,999 785 22,847 4,431 17,011 5,269 24,843 334,175b 190,686b 614 1,630 1,234 5,433 .. 5,480 2,421 4,179 52,641 180,723 6,776 23,270 272 744 129 116 969 5,927 2,040 5,313 219,501 383,759 179 .. 190 .. 19,358 62,242 147,240 1,333,346 .. 408,142 12,294 38,222 .. .. 1,374 6,127 4,451 12,566 4,337 11,478 6,972 22,626 .. .. 28,202 132,920 65,655 147,276 5,731 10,465 5,196 15,574 13,260 44,609 2,040 4,696 135 .. 2,573 13,539 768 3,433 47,973 90,571 362,717 617,335 2,945 .. 175 278 575 3,207 600,347 1,376,861 1,582 7,809 15,523 59,150 2,823 9,220 700 1,122 30 172 192 933 1,635 6,028 128,369 235,091

2011 World Development Indicators

Imports 1995

2009

Net income

Net current transfers

Current account balance

Total reservesa

$ millions 1995 2009

$ millions 1995 2009

$ millions 1995 2009

$ millions 1995 2009

.. .. .. 836 6,495 44 .. .. .. 3,519 41,829 –767 26,066 48,951 –4,636 726 3,688 40 74,841 242,311 –14,036 92,055 175,559 –1,597 1,290 9,872 –6 7,589 23,165 68 5,752 30,360 –51 178,798 b 328,387b ..b 895 2,400 –8 1,574 5,159 –207 .. 9,464 .. 2,050 5,131 –32 63,293 174,679 –11,105 6,502 27,196 –432 483 2,858 –29 259 520 –13 1,375 6,898 –57 1,608 6,540 –412 200,991 407,655 –22,721 244 .. –23 411 .. –7 18,301 49,335 –2,714 135,282 1,113,234 –11,774 .. 393,077 .. 16,012 38,404 –1,596 .. .. .. 1,346 6,386 –695 4,717 12,286 –226 3,806 8,803 –787 9,152 24,900 –53 .. .. .. 30,044 122,069 –104 57,860 134,738 –4,549 6,137 14,160 –769 5,708 16,876 –930 17,140 53,842 –405 3,623 7,966 –67 498 .. 8 2,860 12,435 3 1,446 9,046 –19 37,705 83,807 –4,440 333,746 663,242 –8,964 1,723 .. –665 230 343 –5 1,413 5,266 127 586,662 1,212,133 –2,814 2,120 10,789 –129 24,711 84,204 –1,684 3,728 12,726 –159 1,011 1,391 –85 89 284 –21 802 2,813 –31 1,852 8,641 –226 124,171 202,629 4,188

.. .. .. .. –145 477 1,307 –12 .. .. .. .. –6,823 156 –370 –295 –9,013 597 34 –5,118 166 168 814 –218 –39,399 –109 –374 –19,277 –1,148 –1,702 –2,296 –5,448 –3,519 111 722 –401 –1,376 2,265 10,875 –824 –1,114 76 242 –458 6,641b 7,822b –8,907b ..b –11 121 245 –167 –674 244 1,213 –303 535 .. 2,275 .. –452 –39 878 300 –33,684 3,621 3,338 –18,136 –2,116 132 1,291 –26 –4 255 409 15 –17 153 257 10 –468 277 574 –186 –303 69 393 90 –12,591 –117 –1,892 –4,328 .. 63 .. –25 .. 191 .. –38 –10,306 307 1,616 –1,350 43,282 1,435 33,748 1,618 5,530 .. –3,177 .. –9,432 799 4,614 –4,516 .. .. .. .. –1,885 42 –38 –625 –1,176 134 359 –358 –890 –237 –115 –492 –2,491 802 1,450 –1,431 .. .. .. .. –12,194 572 –805 –1,374 3,933 –1,391 –5,248 1,855 –1,769 992 3,305 –183 –1,463 442 2,497 –1,000 –2,076 4,031 7,960 –254 –664 1,389 3,561 –262 .. 324 .. –31 –529 126 318 –158 –37 736 3,459 39 2,394 –597 –2,344 5,231 31,844 –9,167 –37,796 10,840 .. –42 .. 515 –8 52 135 –8 –118 197 967 –514 47,352 –38,768 –46,610 –27,897 –296 523 2,078 –144 –12,516 8,008 1,657 –2,864 –1,111 491 4,626 –572 –168 179 34 –216 –15 46 98 –35 13 553 1,635 –87 –487 243 2,652 –201 12,512 –2,912 .. 5,474

.. .. .. –1,875 265 2,369 .. 4,164 155,112 –7,572 213 13,664 8,632 15,979 48,007 –1,369 111 2,004 –47,786 14,952 41,742 10,995 23,369 17,904 10,178 121 5,364 3,345 2,376 10,342 –6,389 377 5,640 3,522b 24,120 b 23,862b –536 198 1,230 813 1,005 8,575 –1,175 80 3,245 –526 4,695 8,704 –24,302 51,477 238,539 –4,751 1,635 18,522 –1,709 347 1,296 –164 216 323 –866 192 3,286 –1,137 15 3,676 –38,380 16,369 54,356 .. 238 211 .. 147 617 4,217 14,860 25,292 297,142 80,288 2,452,899 17,418 55,424 255,841 –5,001 8,452 24,987 157 1,615 .. –2,181 64 3,806 –537 1,060 4,068 1,670 529 3,267 –3,314 1,896 14,895 .. .. .. –2,147 14,613 41,608 11,222 11,652 76,618 –2,159 373 2,905 –268 1,788 3,792 –3,349 17,122 34,897 –373 940 3,122 .. 40 58 893 583 3,981 –2,191 815 1,781 6,814 10,657 11,429 –51,857 58,510 131,786 .. 153 1,993 63 106 224 –1,210 199 2,110 165,471 121,816 179,040 –1,198 804 .. –35,913 16,119 5,486 8 783 5,205 –403 87 .. –29 20 169 –232 199 790 –449 270 2,492 42,911 95,559 363,010


Goods and services

Exports

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

$ millions

Imports

1995

2009

1995

19,765 38,013 52,923 18,953 .. 49,439 27,478 295,618 3,394 493,991 3,479 5,975 3,526 .. 147,761 .. 14,215 448 408 2,088 .. 199 .. 7,513 3,191 1,302 749 470 83,369 529 504 2,349 89,321 884 508 9,044 411 1,307 1,734 1,029 241,517 17,883 662 321 12,342 56,058 6,078 10,214 7,610 2,992 4,802 6,622 26,795 35,716 32,260 .. ..

100,098 258,822 133,255 .. 65,695 199,942 67,877 509,797 4,038 673,615 10,915 48,258 7,414 .. 432,097 .. 61,692 2,560 1,444 11,231 21,600 789 454 37,440 20,309 3,548 .. .. 186,424 2,551 .. 4,181 245,206 2,000 2,300 26,381 2,464 .. 4,057 1,493 518,122 33,210 2,857 1,043 61,545 160,687 29,443 22,220 16,652 4,579 7,253 30,538 47,611 171,071 67,268 .. ..

19,916 48,225 54,461 15,113 .. 42,169 35,287 250,319 3,729 419,556 4,903 6,102 5,922 .. 155,104 .. 12,615 726 748 2,193 .. 1,046 .. 5,755 3,902 1,773 987 660 86,851 991 510 2,454 82,168 1,006 521 11,243 1,055 2,020 2,100 1,624 216,558 17,248 1,150 457 12,841 46,848 5,035 14,185 7,768 1,905 5,200 9,597 33,317 33,825 39,545 .. ..

2009

4.17

economy

Balance of payments current account Net income

Net current transfers

Current account balance

Total reservesa

$ millions 1995 2009

$ millions 1995 2009

$ millions 1995 2009

$ millions 1995 2009

93,412 –1,701 –7,890 328,036 –3,734 –6,514 112,233 –5,874 –15,140 .. –478 .. 37,731 .. 2,106 166,569 –7,325 –38,752 63,129 –2,654 –4,558 520,563 –15,644 –38,480 6,356 –371 –668 650,364 44,285 131,339 16,300 –279 612 38,877 –146 –12,729 11,314 –219 –58 .. .. .. 393,172 –1,303 4,554 .. .. .. 30,679 4,881 7,726 3,680 –35 –190 1,581 –6 –47 11,486 19 1,655 30,215 .. –767 1,792 314 424 1,704 .. –128 27,065 133 578 20,605 –13 318 5,665 –30 –128 .. –167 .. .. –44 .. 144,873 –4,144 –4,170 3,760 –41 –313 .. –48 .. 5,106 –19 27 257,976 –12,689 –14,925 3,989 –18 303 2,632 –25 –195 37,307 –1,318 –1,495 4,305 –140 –95 .. –110 .. 5,128 139 –70 5,086 9 158 459,194 7,247 –12,001 31,953 –3,955 –5,148 4,482 –372 –235 1,951 –47 26 47,843 –2,878 –10,020 104,496 –1,919 –1,660 21,607 –374 –2,810 35,008 –1,939 –3,619 15,446 –466 –1,460 4,802 –488 –625 7,374 110 –312 25,777 –2,482 –7,371 54,950 3,662 –69 170,631 –1,995 –16,575 83,259 21 –10,952 .. .. .. .. .. ..

203 8,382 981 –4 .. 1,776 5,673 –4,579 607 –7,676 1,444 59 1,037 .. –19 .. –1,465 79 110 71 .. 210 .. –220 109 213 129 157 –1,017 219 76 101 3,960 56 77 2,330 339 562 403 230 –6,434 255 138 31 799 –2,059 –1,469 2,562 153 75 195 832 880 958 7,132 .. ..

505 49,102 4,861 .. –2,936 –1,109 7,402 –16,952 1,860 –12,397 3,523 –900 2,297 .. –811 .. –10,133 1,208 193 883 1,827 547 1,101 –1,572 1,625 1,599 .. .. –5,580 455 .. 224 21,468 1,221 186 7,451 764 .. 1,261 3,426 –10,345 267 1,018 230 17,977 –4,408 –5,313 12,824 210 176 519 2,856 15,960 6,537 2,992 .. ..

–1,650 –5,563 –6,431 3,358 .. 1,721 –4,790 25,076 –99 111,044 –259 –213 –1,578 .. –8,665 .. 5,016 –235 –237 –16 .. –323 .. 1,672 –614 –288 –276 –78 –8,644 –284 22 –22 –1,576 –85 39 –1,186 –445 –261 176 –356 25,773 –3,065 –722 –152 –2,578 5,233 –801 –3,349 –471 674 –92 –4,625 –1,980 854 –132 .. ..

–699 –26,626 10,743 .. 27,133 –6,488 7,592 –66,199 –1,126 142,194 –1,251 –4,248 –1,661 .. 42,668 .. 28,605 –102 9 2,284 –7,555 –32 –277 9,381 1,646 –646 .. .. 31,801 –1,066 .. –675 –6,228 –465 –342 –4,971 –1,171 .. 120 –10 36,581 –3,624 –841 –651 21,659 50,122 –287 –3,583 –44 –672 86 247 8,552 –9,598 –23,952 .. ..

12,017 22,865 14,908 .. 8,347 8,770 8,123 60,690 681 192,620 2,279 1,660 384 .. 32,804 .. 4,543 134 99 602 8,100 457 28 7,415 829 275 109 115 24,699 323 90 887 17,046 257 158 3,874 195 651 221 646 47,162 4,410 142 95 1,709 22,976 1,943 2,528 781 267 1,106 8,653 7,781 14,957 22,063 .. 848

2011 World Development Indicators

44,181 284,683 66,119 .. 46,461 2,151 60,611 131,497 2,076 1,048,991 12,135 23,183 3,850 .. 270,437 830 23,028 1,584 1,010 6,902 39,132 .. 372 103,754 6,657 2,288 1,135 163 96,704 1,604 238 2,316 99,889 1,480 1,327 23,568 2,181 .. 2,051 .. 39,284 15,594 1,573 656 45,510 48,859 12,204 13,606 3,028 2,629 3,862 33,225 44,206 79,522 15,829 .. 18,804

259


4.17

Balance of payments current account Goods and services

$ millions

Exports 1995

2009

Romania 9,404 50,491 Russian Federation 92,987 344,934 Rwanda 75 534 Saudi Arabia 53,450 201,964 Senegal 1,506 3,500 Serbia .. 11,858 Sierra Leone 128 323 Singapore 159,488 364,332 Slovak Republic 10,969 61,792 Slovenia 10,377 28,542 Somalia .. .. South Africa 34,402 78,563 Spain 133,910 346,893 Sri Lanka 4,617 8,977 Sudan 681 8,226 Swaziland 1,020 1,860 Sweden 95,525 194,516 Switzerland 123,320 280,162 Syrian Arab Republic 5,757 19,374 Tajikistan .. 1,218 Tanzania 1,265 5,219 Thailand 70,292 180,653 Timor-Leste .. .. Togo 465 1,136 Trinidad and Tobago 2,799 19,622 Tunisia 7,979 19,917 Turkey 36,581 142,865 Turkmenistan 1,774 .. Uganda 664 3,954 Ukraine 17,090 54,253 United Arab Emirates .. .. United Kingdom 322,114 595,914 United States 794,397 1,570,797 Uruguay 3,507 8,557 Uzbekistan .. .. Venezuela, RB 20,753 59,600 Vietnam 9,498 62,752 West Bank and Gaza 764 1,168 Yemen, Rep. 2,160 7,092 Zambia 1,222 4,560 Zimbabwe 2,344 .. World 6,395,661 t 15,641,184 t Low income 29,028 104,191 Middle income 1,087,422 4,483,392 Lower middle income 492,428 2,563,013 Upper middle income 594,996 1,906,819 Low & middle income 1,115,105 4,583,161 East Asia & Pacific 397,583 1,969,911 Europe & Central Asia 193,610 795,858 Latin America & Carib. 273,265 796,196 Middle East & N. Africa .. .. South Asia 58,893 310,779 Sub-Saharan Africa 89,266 296,829 High income 5,304,481 11,224,885 Euro area 2,100,300 4,450,297

Imports 1995

2009

11,306 60,470 82,809 253,233 374 1,479 44,874 160,639 1,821 7,020 .. 18,486 260 628 144,904 325,605 10,658 61,806 10,749 27,980 .. .. 33,375 80,816 135,000 374,259 5,982 11,708 1,238 11,212 1,274 2,344 81,142 165,275 108,916 243,800 5,541 19,309 .. 3,062 2,139 7,543 82,246 155,777 .. .. 671 1,666 2,110 9,948 8,811 21,091 40,113 151,453 1,796 .. 1,490 5,210 18,280 56,206 .. .. 327,000 650,834 890,784 1,945,705 3,568 7,794 .. .. 16,905 48,064 12,334 72,446 2,789 4,962 2,471 10,001 1,338 4,119 2,515 .. 6,248,111 t 15,144,783 t 46,738 149,627 1,137,135 4,125,043 532,363 2,390,741 604,453 1,722,447 1,182,581 4,271,461 413,806 1,684,481 205,686 759,347 288,584 781,728 106,423 334,137 78,652 407,949 99,774 327,513 5,072,079 11,020,075 1,977,018 4,275,187

Net income

Net current transfers

Current account balance

Total reservesa

$ millions 1995 2009

$ millions 1995 2009

$ millions 1995 2009

$ millions 1995 2009

–241 –3,372 7 2,800 –124 .. –30 541 –14 201 .. –2,875 –5,402 –137 –3 81 –6,473 10,708 –560 .. –110 –2,114 .. –34 –390 –716 –3,204 17 –96 –434 .. 3,393 20,899 –227 .. –1,943 –384 607 –561 –249 –294 .. .. .. .. .. .. .. .. .. .. .. .. .. ..

a. International reserves including gold valued at London gold price. b. Includes Luxembourg.

260

2011 World Development Indicators

–2,968 –39,474 –37 8,613 –48 –710 –36 –3,061 –1,837 –1,081 .. –6,389 –42,120 –488 –2,402 –123 7,303 14,922 –1,149 –71 –175 –7,499 .. –15 –1,202 –2,011 –8,121 .. –329 –2,440 .. 40,655 121,418 –689 .. –2,652 –3,028 911 –1,171 –1,363 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

369 5,649 –1,774 157 –2,862 6,963 350 604 57 –16,694 –27,172 –5,318 195 1,685 –244 .. 4,925 .. 43 148 –118 –894 –3,037 14,230 93 –959 390 95 –202 –75 .. .. .. –645 –2,684 –2,493 4,525 –10,889 –1,967 732 3,005 –770 60 1,480 –500 144 192 –30 –2,970 –5,083 4,940 –4,409 –12,312 20,703 607 1,150 263 .. 1,735 .. 395 683 –590 487 4,484 –13,582 .. .. .. 118 324 –122 –4 47 294 774 1,951 –774 4,398 2,299 –2,338 5 .. 0 639 1,133 –281 472 2,661 –1,152 .. .. .. –11,943 –22,786 –13,436 –38,073 –124,944 –113,561 76 140 –213 .. .. .. 109 –323 2,014 1,200 6,448 –2,020 435 3,418 –984 1,056 1,515 184 182 516 –182 40 .. –425 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

–7,298 2,624 49,365 18,024 –379 99 22,765 10,399 –1,884 272 –2,412 .. –193 35 32,628 68,816 –2,810 3,863 –720 1,821 .. .. –11,327 4,464 –80,375 40,531 –215 2,112 –3,908 163 –414 298 31,460 25,870 38,972 68,620 66 448 –180 39 –1,816 270 21,861 36,939 .. .. –222 130 8,519 379 –1,234 1,689 –14,410 13,891 .. 1,168 –451 459 –1,732 1,069 .. 7,778 –37,050 49,144 –378,435 175,996 215 1,813 .. .. 8,561 10,715 –6,274 1,324 535 .. –2,565 638 –406 223 .. 888 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..

44,383 439,342 743 420,984 2,123 15,228 405 187,803 1,804 1,078 .. 39,603 28,051 5,354 1,094 959 47,255 134,566 18,300 .. 3,470 138,419 250 703 9,245 11,294 74,933 .. 2,994 26,501 36,104 66,550 404,099 8,038 .. 34,318 16,447 .. 6,990 1,892 .. .. .. .. .. .. .. .. .. .. .. .. .. .. ..


About the data

4.17

Definitions

The balance of payments records an economy’s

system, external debt records, information provided

• Exports and imports of goods and services are all

transactions with the rest of the world. Balance of

by enterprises, surveys to estimate service transac-

transactions between residents of an economy and

payments accounts are divided into two groups:

tions, and foreign exchange records. Differences in

the rest of the world involving a change in ownership

the current account, which records transactions in

collection methods—such as in timing, definitions

of general merchandise, goods sent for processing

goods, services, income, and current transfers, and

of residence and ownership, and the exchange rate

and repairs, nonmonetary gold, and services. • Net

the capital and financial account, which records capi-

used to value transactions—contribute to net errors

income is receipts and payments of employee com-

tal transfers, acquisition or disposal of nonproduced,

and omissions. In addition, smuggling and other ille-

pensation for nonresident workers, and investment

nonfinancial assets, and transactions in financial

gal or quasi-legal transactions may be unrecorded or

income (receipts and payments on direct investment,

assets and liabilities. The table presents data from

misrecorded. For further discussion of issues relat-

portfolio investment, and other investments and

the current account plus gross international reserves.

ing to the recording of data on trade in goods and

receipts on reserve assets). Income derived from

services, see About the data for tables 4.4–4.7.

the use of intangible assets is recorded under busi-

The balance of payments is a double-entry accounting system that shows all flows of goods and

The concepts and definitions underlying the data in

ness services. • Net current transfers are recorded

services into and out of an economy; all transfers

the table are based on the fifth edition of the Inter-

in the balance of payments whenever an economy

that are the counterpart of real resources or financial

national Monetary Fund’s (IMF) Balance of Payments

provides or receives goods, services, income, or

claims provided to or by the rest of the world without

Manual (1993). That edition redefined as capital

financial items without a quid pro quo. All transfers

a quid pro quo, such as donations and grants; and

transfers some transactions previously included in the

not considered to be capital are current. • Current

all changes in residents’ claims on and liabilities to

current account, such as debt forgiveness, migrants’

account balance is the sum of net exports of goods

nonresidents that arise from economic transactions.

capital transfers, and foreign aid to acquire capital

and services, net income, and net current transfers.

All transactions are recorded twice—once as a credit

goods. Thus the current account balance now reflects

• Total reserves are holdings of monetary gold, spe-

and once as a debit. In principle the net balance

more accurately net current transfer receipts in addi-

cial drawing rights, reserves of IMF members held by

should be zero, but in practice the accounts often do

tion to transactions in goods, services (previously

the IMF, and holdings of foreign exchange under the

not balance, requiring inclusion of a balancing item,

nonfactor services), and income (previously factor

control of monetary authorities. The gold component

net errors and omissions.

income). Many countries maintain their data collection

of these reserves is valued at year-end (December

Discrepancies may arise in the balance of pay-

systems according to the fourth edition of the Balance

31) London prices ($386.75 an ounce in 1995 and

ments because there is no single source for balance

of Payments Manual (1977). Where necessary, the IMF

$1,087.50 an ounce in 2009).

of payments data and therefore no way to ensure

converts such reported data to conform to the fifth

that the data are fully consistent. Sources include

edition (see Primary data documentation). Values are

customs data, monetary accounts of the banking

in U.S. dollars converted at market exchange rates.

4.17a

Top 15 economies with the largest reserves in 2009 Total reserves ($ billions)

Share of world total (%) 2009

Annual change (%) 2008–09

Months of imports 2009

2008

2009

China

1,966

2,453

26.1

24.8

25.0

Japan

1,031

1,049

11.2

1.8

18.1

426

439

4.7

3.0

16.1 29.4

Russian Federation Saudi Arabia

451

421

4.5

–6.7

United States

294

404

4.3

37.4

2.0

Taiwan, China

304

363

3.9

19.6

20.7

India

257

285

3.0

10.6

9.8

Korea, Rep.

202

270

2.9

34.2

8.0

Hong Kong SAR, China

183

256

2.7

40.2

6.3

Data sources Data on the balance of payments are published in the IMF’s Balance of Payments Statistics Yearbook and International Financial Statistics. The World Data sources Bank exchanges data with the IMF through elec-

Brazil

194

239

2.5

23.1

13.2

Singapore

174

188

2.0

7.8

5.9

Germany

139

179

1.9

29.1

1.5

Algeria

148

155

1.7

4.7

..

Thailand

111

138

1.5

24.7

9.8

the IMF’s Balance of Payments Manual, fifth edition

74

135

1.4

81.6

5.0

(1993), Balance of Payments Textbook (1996), and

Switzerland

Source: International Monetary Fund, International Financial Statistics data files.

tronic files that in most cases are more timely and cover a longer period than the published sources. More information about the design and compilation of the balance of payments can be found in

Balance of Payments Compilation Guide (1995).

2011 World Development Indicators

261

economy

Balance of payments current account


States and Markets


Introduction

N

ew firm creation recently declined sharply in most countries, according to the 2010 World Bank Group Entrepreneurial Snapshots. The economic and financial crisis that began in 2008 increased unemployment in many countries, and the fight against poverty could be hampered as spending for human and productive capital is strained. Governments around the world face fiscal deficits and pressure to improve public spending and accelerate business reforms. Partnership between the private sector, which employs people and makes investments, and a capable public sector, which creates a stable regulatory environment, is a key ingredient to successful development. This section includes a range of indicators showing how effective and accountable government, together with a vibrant private sector, produces employment opportunities and services that empower poor people. Its 13 tables cover cross-cutting themes: private sector development, public sector policies, infrastructure, information, communications, telecommunications, and science and technology. New data show that business reforms are making it easier to do business and create new firms and that more-inclusive financial systems are removing barriers to economic growth and development.

Businesses are created faster in a good business environment The World Bank Group Entrepreneurship Snapshots (www.enterprisesurveys.org), which cover 112 countries, show that new businesses are created faster in countries with good governance, low corporate taxes, minimal red tape, and a strong legal and regulatory environment. Countries with well developed financial markets also have higher new firm creation than countries with less developed financial markets. The downside is that countries with well developed financial markets also had steeper declines in new firm creation during the recent financial and economic crisis, probably due to the credit crunch. High-income countries created more new limited liability firms—more than 4 per 1,000 working-age people, compared with only about 0.3 in low-income countries. Data on business entry and density are in table 5.1. The Doing Business database (www.doing business.org) shows that between June 2009 and May 2010, 117 countries adopted 216 business

regulation reforms, making it easier to start and operate businesses, strengthening property rights, and improving commercial dispute resolution and bankruptcy procedures. Using data from the Enterprise Snapshots and Doing Business to analyze whether some reforms are more important than others, Klapper and Love (2010a) find that small reforms that reduce costs, time, or number of procedures to register a business by less than 40 percent do not have a significant impact on new firm registration. This suggests that “token” reforms do not boost private sector activity and that countries with weak business environments require larger reforms to increase new firm registration. They find that two reforms occurring simultaneously tend to have more impact than two reforms occuring sequentially over a longer period.

5

Forty countries made it easier to pay taxes between 2009 and 2010 The World Bank’s Doing Business project collects information for 183 countries on tax payments, time spent paying taxes, and the total tax rate borne by a standard firm. In cooperation with PricewaterhouseCoopers, the project collects information on business tax systems around the world, allowing governments to benchmark their tax system with others to identify good practices, and researchers to analyze the impact of higher corporate tax rates on business start-ups and investments. Over June 2009–May 2010, 40 countries made tax compliance easier, reducing costs for firms and encouraging job creation. Higher tax compliance costs are associated with larger informal sectors and more corruption, ultimately limiting employment, investment, and growth. Keeping rules simple

2011 World Development Indicators

263


and clear improves compliance and reduces tax evasion. And better compliance keeps the system working and supports government programs and services. In the past six years more than 60 percent of the countries covered by the Doing Business project made paying taxes easier or lowered the tax burden for local enterprises. Countries that make paying taxes easy for domestic firms usually offer electronic systems for tax filing and payment, have one tax per tax base, and use a filing system based on self-assessment. In high-income countries the average business spends about 180 hours a year preparing, filing, and paying taxes; in Latin America and the Caribbean, more than 400 hours a year (figure 5a). Previous editions of World Development Indicators included data on the highest marginal corporate tax rate (the statutory rate of corporate income tax). It is not a comprehensive indicator of the amount of tax a company pays, however, because it is only one of the many taxes businesses pay. Generous tax allowances in some countries significantly reduce the corporate income tax paid, while The average business in Latin America and the Caribbean spends about 400 hours a year in preparing, filing, and paying business taxes, 2009

5a

Time to prepare, file, and pay taxes (hours a year) 500 400 300 200 100 0

East Asia & Pacific

Europe & Central Asia

Latin America Middle East & & Caribbean North Africa

South Asia

Sub-Saharan Africa

High income

Source: Doing Business 2011.

Firms in East Asia and the Pacific have the lowest business tax rate, 2010

5b

Total tax rate (% of commercial profits) 80 60 40

East Asia & Pacific

Europe & Central Asia

Latin America Middle East & & Caribbean North Africa

Source: Doing Business 2011.

264

Benchmarking the quality of the business environment— Doing Business and Enterprise Surveys are complementary The World Bank’s Enterprise Surveys are based on firm-level surveys of a representative sample of the nonagricultural private sector in a country. The surveys cover a broad range of business environment topics including corruption, infrastructure, crime, competition, performance measures, and access to finance. Data from Enterprise Surveys are presented in table 5.2. The Doing Business project uses indicator sets and rankings to measure business regulations and quantify the ease of doing business across countries. The indicators cover common transactions such as starting a business or registering property based on standardized case studies. Data are collected through surveys of local experts on business transactions and reflect the country’s laws and regulations. Data on Doing Business indicators are in tables 5.3 and 5.6. Box 5c compares the data sources, coverage, and information collected by Enterprise Surveys and the Doing Business project.

About half the world’s households do not have deposit accounts in formal financial institutions

20 0

disallowances in others can increase the effective rate. In this year’s edition table 5.6 on tax policies includes the total business tax rate as a percent of commercial profit, with details on corporate taxes, labor taxes paid by the employer, social contributions, and other taxes. The total tax rate is a comprehensive measure of the cost of all the taxes a business bears. It differs from the statutory tax rate, which merely provides the factor to be applied to the tax base. In computing the total tax rate, tax payable is divided by commercial profit. The total tax rate is lowest in East Asia and Pacific and is highest in Sub-Saharan Africa (figure 5b). Note that these tax rates are “de jure” tax rates based on case studies of a “standardized business” as defined by the Doing Business project.

2011 World Development Indicators

South Asia

Sub-Saharan Africa

High income

Financial exclusion is a barrier to economic development. Evidence from household surveys indicates that access to basic financial


states and markets

services such as savings, payments, and credit can make an important difference in poor people’s lives. For firms, lack of access to finance is often the main obstacle to growth. In an increasingly digitized and globalized world many countries are promoting access to financial services—from establishing a credit facility for indigenous farmers in rural areas to introducing broad consumer protection legislation. Although financial inclusion mandates, from consumer protection to rural finance promotion, are on the agenda of many financial regulators, insufficient authority and resources to provide broad financial access limit implementation capacity in many developing countries. Nevertheless, more than 70 percent of financial regulators in developing countries have programs to protect consumers, and almost 60 percent promote financial literacy. Five new financial indicators from Financial Access 2010 (www.cgap.org/financialindicators) are included in table 5.5 this year: commercial bank deposits, commercial bank loans, commercial bank branches, automated teller machines (ATMs), and point-of-sale terminals. Although many nonbank institutions (cooperatives, specialized state financial institutions, and microfinance institutions) provide financial services, the most complete information available to central banks and financial regulators is on commercial banks, which account for 85 percent of deposits and 96 percent of accounts. Although financial inclusion, measured as people with commercial bank accounts, is high in some developing country regions such as East Asia and Pacific, it remains low in Sub-Saharan Africa (figure 5d). Access to deposit and credit services varies by region. Access is greater in countries with higher incomes, better infrastructure, and a well functioning legal environment. People without access to bank accounts and credit from regulated institutions have to rely on informal nonregulated financial services, often more costly and less reliable. Low- and middle-­ income countries lag behind high-income countries in the number of bank branches, ATMs, and point-of-sale terminals, but the number of ATMs exceeds the number of bank branches in low-income countries. And new technology, including the expansion of electronic payments through mobile and Internet banking, offer hope for bringing financial services to the unbanked.

Two approaches to collecting business environment data: Doing Business and Enterprise Surveys

5c

Topic

Enterprise Surveys

Global coverage

125 countries

Doing Business

Data source

Collects firm-level data; face-toface interview with owner or top manager. Businesses surveyed include manufacturing, retail, construction, transport, communications, and other services

Collects information through surveys administered by local experts (lawyers, accountants, and architects). The information is confirmed through the underlying laws and regulations

Number of observations

150–360 observations in smaller countries; 1,200–1,800 interviews in larger countries

Underlying laws and regulations in addition to an average of 39 surveys per country

183 countries

Geographical Main cities or regions of coverage within economic activity a country

Main (most populous) business city and subnational studies in other cities

Information gathered

Time and cost to complete common business transactions based on standardized case studies; underlying laws and regulations

Objective data on the business environment as experienced by firms, performance measures, firm characteristics, and perceptions regarding obstacles to growth

Business characteristics; approxiStandardized business; 10 mately 20 Investment climate topics  business regulation topics Examples of data

Hard data: number of days to obtain a construction permit. Soft data: opinion on whether access to land is an obstacle faced by the establishment 

Hard data: laws and regulations, number of procedures, and costs to build a warehouse. Soft data: experts’ estimates on the number of days required for each procedure

Inference from the data

Stratified random sampling design of the surveys, which ensures that data are representative of the universe of formal firms (with five or more employees)

Standardized case studies that relate to a common business situation, which makes comparisons and benchmarks valid across countries

Measures what happens to existing firms—their actual experiences with investment climate issues such as payment of taxes. Also surveys obstacles to business growth

Expectations of a standardized firm following official legal requirements and costs. For instance, “paying taxes” measures the number of payments, time to file, and tax rates

Measures what happens in practice in the normal course of business; for instance, whether a firm pays a bribe when obtaining an import license and the actual time it takes to obtain the license

Assumes that firms comply with all formal regulations and minimize information gathering time and that all regulations are enforced. Measures what would happen if the firm complied with all regulatory requirements in a lawful manner.

Can be used to identify potential areas of reform in the business environment as well as assess the impact of reforms on businesses.

Can be used to identify areas for reform based on bottlenecks or weaknesses in specific areas of private sector regulation and learn from practices in other countries.

Source: Summary of www.enterprisesurveys.org/Methodology/Compare.aspx.

People living in developing countries of East Asia and Pacific have more commercial bank accounts than those in other developing country regions, 2009

5d

Deposit accounts in commercial banks (median per 1,000 adults) 2,000 1,500 1,000

Developing country median

500 0

East Asia & Pacific

Europe & Central Asia

Latin America Middle East & & Caribbean North Africa

South Asia

Sub-Saharan Africa

High income

Source: Financial Access 2010, CGAP and World Bank.

2011 World Development Indicators

265


Tables

5.1

Private sector in the economy Investment commitments in infrastructure projects with private participationa

$ millions Telecommunications

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

266

Energy

2000–05

2006–09

2000–05

466.1 569.2 3,422.5 278.7 5,836.8 317.1 .. .. 355.6 1,294.3 735.4 .. 116.9 520.5 0.0 104.0 41,053.8 2,179.1 41.9 53.6 136.1 394.4 .. 0.0 11.0 3,561.6 8,548.0 .. 1,570.9 473.4 61.8 .. 134.9 1,205.7 60.0 .. .. 393.0 357.8 3,471.9 1,110.6 40.0 .. .. .. .. 26.6 6.6 173.8 .. 156.5 .. 560.1 50.6 21.9 18.0 135.0

1,040.4 670.0 1,925.0 1,129.0 5,033.6 488.8 .. .. 1,283.5 3,729.8 2,219.2 .. 399.7 284.7 1,086.6 183.9 31,121.4 1,866.5 680.6 0.0 436.9 701.4 .. 20.8 246.4 4,167.6 0.0 .. 5,294.7 880.0 330.7 .. 885.4 3,035.0 0.0 .. .. 220.1 1,764.7 8,864.0 901.9 0.0 .. .. .. .. 278.8 35.0 612.2 .. 2,916.0 .. 1,511.4 242.2 96.4 306.0 930.5

1.6 790.6 962.0 45.0 3,826.9 74.0 .. .. 375.2 501.5 .. .. 590.0 884.4 .. .. 26,171.6 3,253.5 .. .. 82.1 91.8 .. .. 0.0 1,590.5 10,970.9 .. 351.6 .. .. 80.0 0.0 7.1 116.0 .. .. 1,306.6 302.0 678.0 85.0 .. .. .. .. .. 0.0 .. 40.0 .. 590.0 .. 110.0 .. .. 5.5 358.8

2011 World Development Indicators

2006–09

Transport 2000–05

.. .. 664.0 308.0 2,320.0 120.9 9.4 .. 3,479.0 203.6 127.0 63.0 .. .. .. .. .. .. 243.5 0.0 1,875.0 .. .. .. .. .. 137.3 16.6 800.0 .. .. .. 46,690.5 3,398.4 2,246.7 2.1 .. .. .. .. 695.8 125.3 440.0 0.0 .. .. .. .. .. .. 2,397.7 4,821.2 7,170.5 15,350.1 .. .. 944.6 1,005.4 .. .. .. .. 190.0 465.2 0.0 176.4 85.0 451.0 60.0 0.0 .. .. .. .. 0.0 898.9 129.0 685.0 469.0 821.5 0.0 .. .. .. .. .. 4.0 .. .. .. .. .. 0.0 177.4 0.0 .. 634.2 .. .. .. 100.0 10.0 .. .. 263.8 .. .. .. .. .. .. .. .. 120.0

2006–09

.. .. 269.0 53.0 1,402.6 715.0 .. .. .. 0.0 4.0 .. .. .. .. .. 22,086.9 536.2 .. .. 40.1 .. .. .. .. 1,311.1 15,795.0 .. 2,344.4 .. 735.0 373.0 .. 492.0 .. .. .. 879.9 766.0 1,370.0 .. .. .. .. .. .. 3.9 .. 573.0 .. .. .. .. 159.0 .. .. ..

Domestic credit to private sector

Water and sanitation 2000–05

.. 8.0 510.0 .. 791.6 0.0 .. .. 0.0 .. .. .. .. .. .. .. 1,234.4 152.0 .. .. .. .. .. .. .. 1,495.2 3,505.2 .. 314.3 .. 0.0 .. .. 298.7 600.0 .. .. .. 510.0 .. .. .. .. .. .. .. .. .. .. .. 0.0 .. .. .. .. .. 207.9

2006–09

.. 0.0 1,572.0 .. .. 0.0 .. .. .. .. .. .. .. .. .. .. 1,365.4 .. .. .. .. 0.0 .. .. .. 3.1 3,992.2 .. 305.0 .. .. .. 0.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 435.0 .. .. .. 6.7 .. .. 0.0 ..

Businesses registered

% of GDP

New

Entry density

2009

2009

2009

9.1 37.0 16.2 21.2 13.5 23.1 127.8 126.9 19.6 41.5 37.3 97.9 22.2 37.0 57.3 25.5 54.0 75.6 17.5 21.7 24.5 11.3 128.6 7.0 5.2 97.5 127.3 158.0 29.9 7.5 4.8 49.4 17.1 66.3 .. 55.3 231.6 21.3 25.3 36.2 41.3 16.6 110.2 17.8 94.4 110.3 10.1 18.9 31.2 112.3 15.9 91.7 25.4 .. 5.6 14.5 52.6

.. 2,045 10,544 .. 11,924 2,698 89,960 3,228 5,314 .. 5,508 29,548 .. 2,504 1,896 .. 315,645 35,545 610 .. 2,003 .. 174,000 .. .. 23,541 .. 101,023 31,132 .. .. 26,765 .. 7,800 .. 21,717 16,519 12,881 .. 6,291 4,400 .. 7,199 1,327 11,820 128,906 3,490 .. 7,226 64,840 9,606 8,426 5,133 .. .. .. ..

.. 0.84 0.44 .. 0.46 1.28 6.38 0.58 0.93 .. 0.80 4.28 .. 0.43 0.58 .. 2.38 7.20 0.08 .. 0.22 .. 7.56 .. .. 2.12 .. 19.19 1.07 .. .. 8.78 .. 2.57 .. 3.00 4.57 2.13 .. 0.13 1.19 .. 8.10 0.03 3.37 3.08 4.27 .. 2.32 1.19 0.72 1.18 0.68 .. .. .. ..


Investment commitments in infrastructure projects with private participationa

$ millions Telecommunications

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

Energy

2000–05

2006–09

2000–05

2006–09

5,172.8 20,030.5 6,557.2 695.0 984.0 .. .. .. 700.3 .. 1,589.0 1,153.7 1,434.0 .. .. .. .. 11.5 87.7 700.0 138.1 88.4 70.3 .. 993.0 706.6 12.6 36.3 3,777.0 82.6 92.1 413.0 18,758.0 46.1 22.1 6,139.5 123.0 .. 35.0 109.3 .. .. 218.5 85.5 6,949.7 .. .. 6,594.9 211.4 .. 199.0 2,241.4 4,616.4 16,800.1 .. .. ..

1,523.3 33,682.4 9,748.1 1,506.0 4,521.0 .. .. .. 301.6 .. 648.6 3,170.2 2,973.8 400.0 .. .. .. 115.9 135.0 468.1 0.0 30.6 73.8 .. 490.2 489.6 304.8 197.7 1,700.0 583.0 133.1 102.1 12,622.6 392.3 0.0 2,549.6 156.2 .. 8.5 26.0 .. .. 380.1 251.7 11,348.1 .. .. 8,706.5 1,224.0 150.0 591.4 2,485.0 4,177.0 7,750.0 .. .. ..

851.6 8,369.2 1,860.5 650.0 .. .. .. .. 201.0 .. .. 300.0 .. .. .. .. .. .. 1,250.0 158.1 .. 0.0 .. .. 514.3 .. 0.0 0.0 6,637.6 365.9 .. 0.0 6,749.3 227.2 .. 1,049.0 1,205.8 .. 1.0 15.1 .. .. 126.3 .. 1,920.0 .. .. 375.4 449.3 .. .. 2,498.9 3,428.4 2,620.5 .. .. ..

1,707.0 50,754.4 3,779.3 .. 590.0 .. .. .. 78.0 .. 989.0 0.0 332.7 .. .. .. .. .. 1,425.0 184.0 .. .. .. .. 417.6 655.0 .. .. 384.5 .. .. .. 1,483.0 68.0 .. .. .. 556.1 .. .. .. .. 95.0 .. 280.0 .. .. 4,058.2 576.7 .. .. 1,142.9 9,463.3 2,475.4 .. .. ..

Transport 2000–05

3,297.5 4,172.2 159.2 .. .. .. .. .. 565.0 .. 0.0 231.0 .. .. .. .. .. .. 0.0 .. 153.0 .. .. .. .. .. 61.0 .. 4,263.0 55.4 .. .. 2,970.4 0.0 .. 200.0 334.6 .. .. .. .. .. 104.0 .. 2,355.4 .. .. 112.8 51.4 .. .. 522.5 943.5 1,672.0 .. .. ..

2006–09

1,588.0 23,012.8 1,731.5 .. .. .. .. .. .. .. 1,380.0 31.0 404.0 .. .. .. .. .. .. 135.0 .. .. .. .. .. 295.0 17.5 .. 1,379.0 .. .. .. 11,434.1 60.0 .. 200.0 0.0 .. .. .. .. .. .. .. 644.1 .. .. 923.7 0.0 .. .. 3,157.6 678.9 3,642.3 .. .. ..

Domestic credit to private sector

Water and sanitation 2000–05

0.0 112.9 44.8 .. .. .. .. .. .. .. 169.0 .. .. .. .. .. .. 0.0 .. .. 0.0 .. .. .. .. .. .. .. 6,502.2 .. .. .. 523.7 .. .. .. .. .. 0.0 .. .. .. .. 3.4 .. .. .. .. .. .. .. 152.0 0.0 64.3 .. .. ..

2006–09

0.0 241.7 20.2 .. .. .. .. .. .. .. 951.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 0.0 .. .. 0.0 303.8 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 530.5 0.8 .. .. ..

% of GDP 2009

71.3 46.8 27.6 36.7 6.4 230.3 84.5 110.8 28.5 171.0 71.7 50.3 31.5 .. 107.6 36.1 63.3 15.1 9.5 107.8 73.9 13.5 16.1 10.9 70.9 44.3 11.5 14.2 117.1 17.4 .. 85.1 23.3 36.2 43.9 64.4 25.1 .. 46.8 59.4 215.3 147.0 34.4 12.2 37.6 .. 49.0 23.5 85.7 32.1 29.1 24.1 30.3 52.9 187.8 .. 51.5

5.1

states and markets

Private sector in the economy

Businesses registered

New 2009

42,951 84,800 28,998 .. .. 13,188 19,758 68,508 2,003 105,698 2,737 27,978 17,896 .. 60,039 141 .. 4,412 .. 7,175 .. .. .. .. 5,399 8,074 724 619 41,638 .. .. 6,626 44,084 4,180 .. 26,166 .. .. .. .. 35,100 47,897 .. 24 65,089 13,805 3,165 2,759 548 .. .. 51,151 11,435 14,434 27,759 .. ..

2011 World Development Indicators

Entry density 2009

6.26 0.12 0.18 .. .. 4.67 4.46 1.78 1.16 1.28 0.74 2.59 0.85 .. 1.72 0.12 .. 1.26 .. 4.62 .. .. .. .. 2.18 5.63 0.07 0.08 2.55 .. .. 7.33 0.61 1.32 .. 1.28 .. .. .. .. 3.10 17.08 .. 0.00 0.79 4.49 1.67 0.03 0.26 .. .. 2.65 0.19 0.52 3.92 .. ..

267


5.1

Private sector in the economy Investment commitments in infrastructure projects with private participationa

$ millions Telecommunications 2000–05

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

2006–09

Energy 2000–05

3,906.9 4,188.9 1,240.8 22,049.4 24,525.8 1,726.0 72.3 351.0 1.6 .. .. .. 593.1 1,333.0 93.3 563.5 3,297.4 .. 48.8 111.2 .. .. .. .. .. .. .. .. .. .. 13.4 0.0 .. 10,519.5 7,714.0 1,251.3 .. .. .. 766.1 1,444.5 270.8 747.7 1,748.3 .. 27.7 48.3 .. .. .. .. .. .. .. 583.0 307.7 .. 8.5 125.0 16.0 515.3 1,484.5 348.0 5,602.7 3,106.0 4,693.3 0.0 0.0 .. 0.0 44.0 657.7 .. .. .. 751.0 2,805.0 30.0 12,788.6 12,068.7 6,754.8 20.0 158.1 .. 387.6 1,463.0 113.9 3,162.9 4,508.8 160.0 .. .. .. .. .. .. .. .. .. 114.2 158.5 330.0 285.6 942.1 .. 3,337.0 2,619.8 39.5 430.0 1,593.7 2,360.6 279.8 47.0 150.0 376.8 392.2 .. 208.3 624.0 3.0 72.0 343.0 .. .. s .. s .. s 6,362.3 20,932.3 .. 227,575.0 248,323.5 107,077.9 84,109.2 27,585.0 38,840.9 143,465.8 134,452.2 49,324.0 233,937.3 269,255.8 87,324.8 29,862.2 4,662.0 31,290.4 50,274.6 62,911.8 5,316.0 81,401.1 72,021.9 45,682.0 13,435.4 23,566.1 .. 29,314.5 48,647.1 9,533.6 24,654.4 40,481.6 .. .. .. .. .. .. ..

2006–09

Transport 2000–05

6,288.7 .. 27,214.2 109.4 .. .. .. .. .. 55.4 .. .. 1.2 .. .. .. .. .. .. .. .. .. 9.9 504.7 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 28.4 27.7 2,341.0 939.0 .. .. 190.0 .. .. .. .. .. 8,862.7 3,118.6 .. .. 1,000.6 .. 54.0 .. .. .. .. .. .. .. .. 251.1 .. .. .. 34.0 297.0 20.0 .. .. 15.8 .. .. 15.6 .. .. .. s .. s .. .. 191,687.3 50,686.8 82,564.1 26,511.7 109,123.2 5,696.9 196,264.6 5,403.2 26,112.4 21,800.1 47,981.4 .. 57,940.1 16,150.3 .. .. 55,257.1 4,285.0 .. .. .. .. .. ..

2006–09

Domestic credit to private sector

Water and sanitation 2000–05

2006–09

116.8 116.0 41.0 191.0 904.7 1,241.7 .. .. .. .. .. .. 398.0 0.0 0.0 .. 0.0 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 3,483.0 31.3 0.0 .. .. .. .. .. .. 30.0 .. 120.7 .. .. .. .. .. .. .. .. .. 82.0 .. .. .. .. .. 134.0 8.5 .. .. 522.7 18.8 .. .. .. .. .. .. .. .. .. 840.0 .. .. 4,138.5 .. .. .. .. .. 404.0 0.0 .. 130.0 100.0 102.0 .. .. .. .. .. .. .. .. .. .. 368.0 .. 25.0 0.0 .. .. 15.0 .. 965.0 266.0 .. .. .. .. 220.0 .. .. .. 0.0 .. .. .. .. .. s .. s .. s .. .. .. 105,160.9 16,175.1 6,654.9 51,724.0 3,704.9 5,271.6 41,208.8 407.0 .. 86,781.7 .. .. 20,589.5 10,840.9 4,561.7 .. .. .. 43,755.5 2,516.1 .. .. .. .. 23,936.5 112.9 241.7 .. .. .. .. .. .. .. .. ..

% of GDP

New

2009

2009

47.1 56,698 45.3 261,633 .. 3,028 52.1 .. 24.7 1,636 42.2 9,715 9.3 .. 103.2 26,416 44.7 15,825 94.0 5,836 .. .. 147.1 24,700 211.5 79,757 24.8 4,223 12.3 .. 25.0 .. 139.3 24,228 174.8 25,250 20.3 .. 29.0 2,171 15.3 .. 116.3 27,520 18.6 .. 21.9 125 31.5 .. 68.4 9,079 36.5 44,472 .. .. 13.1 11,152 73.3 19,300 93.0 .. 213.5 330,100 202.9 .. 20.6 4,664 .. 14,428 21.7 .. 112.7 .. .. .. 7.4 .. 12.0 5,509 .. .. 138.2 w   26.4   72.8   92.9   47.8   72.0   117.1   45.0   40.8   34.5   43.5   65.1   165.1   133.0  

a. Data refer to total for the period shown. Includes infrastructure projects with private sector participation that reached financial closure in 1990–2009.

268

2011 World Development Indicators

Businesses registered

Entry density 2009

3.66 2.61 0.51 .. 0.22 1.94 .. 7.40 4.04 4.16 .. 0.77 2.92 0.29 .. .. 4.09 4.88 .. 0.48 .. 0.59 .. 0.04 .. 1.23 0.87 .. 0.72 0.60 .. 8.05 .. 2.08 0.78 .. .. .. .. 0.88 ..                            


About the data

5.1

states and markets

Private sector in the economy Definitions

Private sector development and investment—tapping

involving local and small-scale operators—may be

•  Investment commitments in infrastructure

private sector initiative and investment for socially

omitted because they are not publicly reported.

projects with private participation refers to infra-

useful purposes—are critical for poverty reduction.

The database is a joint product of the World Bank’s

structure projects in telecommunications, energy

In parallel with public sector efforts, private invest-

Finance, Economics, and Urban Development

(electricity and natural gas transmission and dis-

ment, especially in competitive markets, has tre-

Department and the Public-Private Infrastructure

tribution), transport, and water and sanitation that

mendous potential to contribute to growth. Private

Advisory Facility. Geographic and income aggregates

have reached financial closure and directly or indi-

markets are the engine of productivity growth, creat-

are calculated by the World Bank’s Development

rectly serve the public. Incinerators, movable assets,

ing productive jobs and higher incomes. And with gov-

Data Group. For more information, see http://ppi.

standalone solid waste projects, and small projects

ernment playing a complementary role of regulation,

worldbank.org/.

such as windmills are excluded. Included are opera-

funding, and service provision, private initiative and

Credit is an important link in money transmission;

tion and management contracts, concessions (oper-

investment can help provide the basic services and

it finances production, consumption, and capital for-

ation and management contracts with major capital

conditions that empower poor people—by improving

mation, which in turn affect economic activity. The

expenditure), greenfield projects (new facilities built

health, education, and infrastructure.

data on domestic credit to the private sector are

and operated by a private entity or a public-private

Investment in infrastructure projects with private

taken from the banking survey of the International

joint venture), and divestitures. Investment commit-

participation has made important contributions to

Monetary Fund’s (IMF) International Financial Statistics

ments are the sum of investments in physical assets

easing fiscal constraints, improving the efficiency

or, when unavailable, from its monetary survey. The

and payments to the government. Investments in

of infrastructure services, and extending delivery

monetary survey includes monetary authorities (the

physical assets are resources the project company

to poor people. Developing countries have been in

central bank), deposit money banks, and other bank-

commits to invest during the contract period in new

the forefront, pioneering better approaches to infra-

ing institutions, such as finance companies, develop-

facilities or in expansion and modernization of exist-

structure services and reaping the benefits of greater

ment banks, and savings and loan institutions. Credit

ing facilities. Payments to the government are the

competition and customer focus.

to the private sector may sometimes include credit

resources the project company spends on acquir-

to state-owned or partially state-owned enterprises.

ing government assets such as state-owned enter-

The data on investment in infrastructure projects with private participation refer to all investment (pub-

Entrepreneurship is essential to the dynamism of

prises, rights to provide services in a specific area, or

lic and private) in projects in which a private com-

the modern market economy, and a greater entry rate

use of specific radio spectrums. • Domestic credit

pany assumes operating risk during the operating

of new businesses can foster competition and eco-

to private sector is financial resources provided

period or development and operating risk during the

nomic growth. The table includes data on business

to the private sector—such as through loans, pur-

contract period. Investment refers to commitments

registrations from the 2008 World Bank Group Entre-

chases of nonequity securities, and trade credits and

not disbursements. Foreign state-owned companies

preneurship Survey, which includes entrepreneurial

other accounts receivable—that establish a claim for

are considered private entities for the purposes of

activity in more than 100 countries for 2000–08.

repayment. For some countries these claims include

this measure.

Survey data are used to analyze firm creation, its

credit to public enterprises. • New businesses regis-

Investments are classified into two types: invest-

relationship to economic growth and poverty reduc-

tered are the number of limited liability corporations

ments in physical assets—the resources a com-

tion, and the impact of regulatory and institutional

registered in the calendar year. • Entry density is the

pany commits to invest in expanding and modern-

reforms. The 2008 survey improves on earlier sur-

number of newly registered limited liability corpora-

izing facilities—and payments to the government to

veys’ methodology and country coverage for better

tions per 1,000 people ages 15–64.

acquire state-owned enterprises or rights to provide

cross-country comparability. Data on total and newly

services in a specific area or to use part of the radio

registered businesses were collected directly from

spectrum.

national registrars of companies. For cross-country

The data are from the World Bank’s Private Par-

comparability, only limited liability corporations

ticipation in Infrastructure (PPI) Project database,

that operate in the formal sector are included. For

which tracks infrastructure projects with private par-

additional information on sources, methodology,

ticipation in developing countries. It provides infor-

calculation of entrepreneurship rates, and data limi-

mation on more than 4,600 infrastructure projects

tations see http://econ.worldbank.org/research/

in 137 developing economies from 1984 to 2009.

entrepreneurship.

Data sources Data on investment commitments in infra-

The database contains more than 30 fields per proj-

structure projects with private participation are

ect record, including country, financial closure year,

from the World Bank’s PPI Project database

infrastructure services provided, type of private par-

(http://ppi.worldbank.org). Data on domestic

ticipation, investment, technology, capacity, project

credit are from the IMF’s International Financial

location, contract duration, private sponsors, bidding

Statistics. Data on business registration are from

process, and development bank support. Data on the

the World Bank’s Entrepreneurship Survey and

projects are compiled from publicly available infor-

database (http://econ.worldbank.org/research/

mation. The database aims to be as comprehensive

entrepreneurship).

as possible, but some projects—particularly those

2011 World Development Indicators

269


5.2

Business environment: Enterprise Surveys Survey year

Regulations and tax

Time dealing with officials

Average number of times % of management meeting with tax officials time

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

270

2008 2007 2007 2006 2006 2009

2009 2007 2008 2009 2006 2009 2006 2009 2009 2009 2006 2007 2009

2009 2006 2003 2006 2010 2009 2005 2009 2007 2009 2005 2006 2008 2006 2009 2009 2006

2009 2006 2008 2005 2007 2005 2006 2006 2006 2006

6.8 18.7 25.1 7.1 13.8 10.3 .. .. 3.0 3.2 13.6 .. 20.7 13.5 11.2 5.0 18.7 10.6 22.2 5.7 5.6 7.0 .. .. 20.8 9.0 18.3 .. 14.3 29.4 6.0 9.6 1.8 10.9 .. 10.4 .. 8.8 17.3 8.8 9.2 0.5 5.5 3.8 .. .. 2.8 7.3 2.1 1.2 4.0 1.8 9.2 2.7 2.9 .. 4.6

2011 World Development Indicators

1.2 3.9 2.3 3.3 2.2 2.1 .. .. 2.1 1.3 1.1 .. 1.2 1.7 1.0 0.9 1.2 2.2 1.5 1.8 1.0 4.4 .. .. 3.4 3.0 14.4 .. 0.6 8.0 2.7 0.5 3.6 0.7 .. 1.5 .. 0.5 0.6 3.4 2.7 0.2 0.4 1.1 .. .. 15.2 2.5 0.6 1.3 4.1 1.7 2.1 2.8 3.4 .. 1.5

Permits Corruption and licenses

Crime

Informality

Firms formally registered when operations started % of firms

Time required to obtain operating license

Informal payments to public officials

Losses due to theft, robbery, vandalism, and arson

days

% of firms

% of sales

13.8 21.2 19.3 24.1 78.3 20.0 .. .. 15.8 6.0 38.2 .. 64.3 26.0 21.4 13.7 83.5 20.8 35.8 27.3 .. 30.0 .. .. 24.3 67.7 11.6 .. 28.2 40.0 .. .. 14.5 26.5 .. 19.9 .. .. 19.9 90.6 35.4 .. 8.3 11.4 .. .. 12.1 8.4 11.8 .. 6.4 .. 75.4 13.0 30.4 .. 31.6

41.5 57.7 64.7 46.8 18.7 11.6 .. .. 32.0 85.1 13.5 .. 54.5 32.4 8.1 27.6 9.7 8.5 8.5 56.5 61.2 50.8 .. .. 41.8 8.2 72.6 .. 8.2 65.7 49.2 33.8 30.6 14.5 .. 8.7 .. 26.3 21.5 15.2 34.3 0.0 1.6 12.4 .. .. 26.1 52.4 4.1 .. 38.8 21.6 15.7 84.8 62.7 .. 16.7

1.5 0.5 0.9 0.4 1.5 0.6 .. .. 0.3 0.1 0.4 .. 1.9 0.9 0.2 1.3 1.7 0.5 0.3 1.1 0.0 1.7 .. .. 2.5 0.6 0.1 .. 0.7 1.8 3.3 0.4 3.4 0.2 .. 0.4 .. 0.7 0.9 3.0 2.6 0.0 0.9 1.4 .. .. 0.4 2.7 0.7 0.5 0.9 0.0 1.5 2.0 1.1 .. 2.2

88.0 89.4 98.3 .. 93.8 96.2 .. .. 85.1 .. 98.5 .. 87.9 90.5 98.6 .. 95.8 98.5 77.7 .. 87.5 82.1 .. .. 77.1 97.8 .. .. 85.6 61.9 84.3 .. 56.4 98.1 .. 98.0 .. .. 91.1 14.3 79.5 100.0 97.4 .. .. .. 63.7 .. 99.6 .. 66.4 .. 91.3 .. .. .. 89.4

Gender

Finance

Firms with Firms using banks to female finance participation in ownership investment % of firms

% of firms

2.8 10.8 15.0 23.4 30.3 31.8 .. .. 10.8 16.1 52.9 .. 43.9 41.1 32.8 40.9 59.3 33.9 19.2 34.8 .. 15.7 .. .. 40.1 27.8 .. .. 43.0 38.9 31.8 65.3 61.9 33.5 .. 25.0 .. .. 32.7 34.0 39.6 4.2 36.3 30.9 .. .. 33.1 21.3 40.8 20.3 44.0 24.4 28.4 25.4 19.9 .. 39.9

1.4 12.4 8.9 2.1 6.9 31.9 .. .. 19.0 24.7 35.8 .. 4.2 22.2 59.7 11.3 48.4 34.7 25.6 12.3 11.3 31.4 .. .. 4.2 29.1 28.8 .. 30.6 6.7 7.7 14.9 13.9 60.0 .. 33.4 .. 12.5 24.0 5.6 17.3 11.9 41.5 11.0 .. .. 6.3 7.6 38.2 45.0 16.0 25.9 12.8 0.9 0.7 .. 8.5

Infrastructure Innovation

Trade

Average Inter­ time to nationally recognized clear direct exports quality Value lost due to electrical certification through customs ownership outages % of sales

6.5 13.7 4.0 3.7 1.6 1.8 .. .. 1.8 10.6 0.8 .. 7.5 4.4 1.9 1.4 3.0 1.6 5.8 10.7 2.4 4.9 .. .. 3.3 1.8 1.3 .. 2.3 22.7 16.4 1.9 5.0 0.8 .. 0.6 .. 15.2 2.7 3.4 2.9 0.2 0.5 0.9 .. .. 1.7 11.8 1.4 .. 6.0 .. 4.5 14.0 5.3 .. 3.8

% of firms

8.5 24.6 5.0 5.1 26.9 26.9 .. .. 18.2 7.8 13.9 .. 7.3 13.8 30.1 12.7 25.7 19.9 14.4 7.1 2.8 20.4 .. .. 43.3 22.0 35.9 .. 5.9 8.5 19.6 10.5 4.3 16.5 .. 43.5 .. 9.6 18.2 21.1 11.0 15.1 21.2 4.2 .. .. 18.6 22.2 16.0 .. 6.8 11.7 8.0 5.2 8.4 .. 16.5

days

14.6 1.9 14.1 16.5 5.5 3.3 .. .. 1.9 8.4 2.6 .. 9.6 15.3 1.4 1.4 15.9 4.2 7.4 .. 1.5 15.1 .. .. 11.9 5.8 6.6 .. 7.0 18.0 .. 3.5 16.6 1.3 .. 5.7 .. 11.4 7.0 6.2 2.5 9.6 1.8 4.3 .. .. 3.8 5.0 3.8 4.7 7.8 5.5 4.5 4.3 5.6 .. 6.0

Workforce

Firms offering formal traininga % of firms

14.6 19.9 17.3 19.4 52.2 30.4 .. .. 10.5 16.2 44.4 .. 32.4 53.9 66.5 37.7 52.9 30.7 24.8 22.1 48.4 25.5 .. .. 43.4 46.9 84.8 .. 39.5 24.1 37.5 46.4 19.1 28.0 .. 70.7 .. 53.3 61.6 21.7 49.6 26.1 69.3 38.2 .. .. 30.9 25.6 14.5 35.4 33.0 20.0 28.1 21.1 12.4 .. 33.3


Survey year

Regulations and tax

Time dealing with officials

Average number of times % of management meeting with tax officials time

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

2009 2006 2009

2005

2005 2006 2009 2007 2005 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2009 2007 2007 2006 2009 2006 2009 2009 2007 2007 2006 2009

2006 2009 2007 2003 2007 2006 2006 2006 2009 2009 2005

13.5 6.7 1.9 .. .. 2.3 .. .. 6.3 .. 6.7 4.7 5.1 .. 0.1 9.8 .. 4.9 1.6 9.7 8.9 5.6 7.5 .. 9.3 14.5 17.1 3.5 7.8 2.4 5.8 9.4 20.5 7.0 12.1 11.4 3.3 .. 2.9 6.5 .. .. 9.3 21.1 6.1 .. .. 2.2 10.3 .. 7.9 13.5 9.1 12.8 1.1 .. ..

0.8 2.6 0.2 .. .. 1.3 .. .. 1.8 .. 1.7 2.6 6.7 .. 2.2 4.5 .. 2.1 4.4 1.5 2.2 1.8 6.5 .. 0.8 3.0 0.9 2.7 2.6 1.6 1.8 0.5 0.6 1.9 2.0 0.9 1.9 .. 0.3 1.3 .. .. 1.3 1.6 3.0 .. 4.4 1.6 1.4 .. 0.7 1.4 1.6 0.6 1.6 .. ..

Permits Corruption and licenses

Crime

Informality

Firms formally registered when operations started % of firms

Time required to obtain operating license

Informal payments to public officials

Losses due to theft, robbery, vandalism, and arson

days

% of firms

% of sales

35.6 .. 21.1 .. .. .. .. .. .. .. 6.4 30.8 23.4 .. .. 18.8 .. 18.0 13.6 11.5 81.0 16.4 16.0 .. 65.5 33.8 41.3 15.0 22.4 41.0 10.7 19.1 11.2 13.9 43.5 3.4 35.2 .. 9.6 14.5 .. .. 19.7 39.7 12.1 .. 11.8 16.4 41.2 .. 37.8 81.1 10.6 14.6 .. .. ..

4.0 47.5 14.6 .. .. 8.3 .. .. 17.7 .. 18.1 23.3 79.2 .. 14.1 2.2 .. 37.5 39.8 11.3 23.0 14.0 55.2 .. 8.5 11.5 19.2 10.8 .. 28.9 82.1 1.6 22.6 25.4 30.4 13.4 14.8 .. 11.4 15.2 .. .. 17.2 35.2 40.9 .. 33.2 27.2 25.4 .. 84.8 11.3 18.6 5.0 14.5 .. ..

0.1 0.1 0.3 .. .. 0.3 .. .. 1.1 .. 0.1 1.0 3.9 .. 0.0 0.3 .. 0.3 0.3 0.3 0.0 2.9 2.8 .. 0.4 0.7 1.2 5.7 1.0 0.6 0.6 1.4 0.7 0.4 0.6 0.0 1.8 .. 1.3 0.9 .. .. 0.9 0.9 4.1 .. .. 0.5 0.5 .. 0.9 0.4 1.1 0.5 0.2 .. ..

100.0 .. 29.1 .. .. .. .. .. .. .. .. 97.4 .. .. .. 89.2 .. 95.9 93.5 98.5 97.6 86.8 73.8 .. 97.1 99.2 97.5 78.6 53.0 85.4 .. 84.2 94.1 97.9 90.1 86.0 85.9 .. .. 94.0 .. .. 85.4 90.5 .. .. .. .. 98.0 .. 94.0 99.2 97.5 99.3 .. .. ..

Gender

Finance

Firms with Firms using banks to female finance participation in ownership investment % of firms

% of firms

42.4 9.1 42.8 .. .. 41.6 .. .. 32.2 .. 13.1 34.4 37.1 .. 19.1 10.9 .. 60.4 39.4 46.3 33.5 18.4 53.0 .. 38.7 36.4 50.0 23.9 13.1 18.4 17.3 16.9 24.8 53.1 52.0 13.1 24.4 .. 33.4 27.4 .. .. 41.4 17.6 20.0 .. .. 6.7 37.1 .. 44.8 32.8 69.4 47.9 50.8 .. ..

48.7 46.7 11.7 .. .. 37.4 .. .. 37.0 .. 8.6 31.0 22.9 .. 39.9 25.3 .. 17.9 0.0 37.3 23.8 32.7 10.1 .. 47.4 47.0 12.2 20.6 48.6 7.0 3.2 37.5 2.6 30.8 26.5 12.3 10.5 .. 8.1 17.5 .. .. 13.0 9.3 2.7 .. 31.0 9.7 19.2 .. 8.2 30.9 22.0 40.7 24.4 .. ..

Infrastructure Innovation

Trade

Average Inter­ time to nationally recognized clear direct exports quality Value lost due to electrical certification through customs ownership outages % of sales

0.9 6.6 2.4 .. .. 1.5 .. .. 11.8 .. 1.7 3.7 6.4 .. .. 17.1 .. 10.5 4.3 1.1 9.4 6.7 2.9 .. 0.7 5.9 7.7 17.0 3.0 1.8 1.6 2.2 2.4 2.0 0.8 1.3 2.4 .. 0.7 27.0 .. .. 8.7 1.9 8.9 .. 4.2 9.9 2.4 .. 2.5 3.2 3.4 1.9 .. .. ..

% of firms

39.4 22.5 2.9 .. .. 17.2 .. .. 16.4 .. 15.5 10.8 9.8 .. 17.6 7.9 .. 16.2 7.2 18.2 17.9 24.7 2.4 .. 15.6 21.5 8.7 17.9 54.1 8.6 5.9 11.1 20.3 9.1 16.7 17.3 18.7 .. 17.6 3.1 .. .. 18.7 4.6 8.5 .. 10.8 9.6 14.7 .. 7.1 14.6 15.7 17.3 12.7 .. ..

days

4.3 15.1 2.4 .. .. 2.6 .. .. 4.3 .. 3.8 8.5 5.6 .. 7.2 1.7 .. 15.8 7.5 1.9 7.6 5.4 .. .. 2.4 2.5 14.2 4.9 2.7 4.8 3.9 10.3 5.2 2.4 18.6 1.8 10.1 .. 1.4 5.6 .. .. 5.0 2.6 7.5 .. 3.4 4.8 5.7 .. 5.5 5.4 8.1 6.0 7.2 .. ..

2011 World Development Indicators

states and markets

5.2

Business environment: Enterprise Surveys

Workforce

Firms offering formal traininga % of firms

14.8 15.9 4.7 .. .. 73.2 .. .. 53.5 .. 23.9 40.9 40.7 .. 39.5 24.6 .. 29.7 11.1 43.4 52.4 42.5 17.0 .. 46.0 19.0 27.0 48.4 50.1 22.5 25.5 25.6 24.6 33.1 61.2 24.7 22.1 .. 44.5 8.8 .. .. 28.9 32.1 25.7 .. 20.9 6.7 43.9 .. 46.9 57.7 31.1 60.9 31.9 .. ..

271


5.2

Business environment: Enterprise Surveys Survey year

Regulations and tax

Time dealing with officials

Average number of times % of management meeting with tax officials time

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe

2009 2009 2006 2007 2009 2009 2009 2009 2007 2005 2004 2006

2009 2008 2006 2006 2009 2009

2008 2006 2008

2006 2008 2006 2009 2006 2010 2007

9.2 19.9 5.9 .. 2.9 12.2 7.4 .. 6.7 7.3 .. 6.0 0.8 3.5 .. 4.4 .. .. 12.2 11.7 4.0 0.4 4.1 2.7 .. .. 27.1 .. 5.2 11.3 .. .. .. 7.0 11.1 33.6 4.9 5.7 11.8 4.6 ..

2.3 1.6 3.3 .. 1.3 1.4 1.9 .. 0.9 0.3 .. 0.8 1.5 4.9 .. 1.4 .. .. 2.3 1.4 2.7 1.0 0.9 1.2 .. .. 1.3 .. 2.4 2.1 .. .. .. 0.7 0.7 2.9 1.1 1.7 7.3 1.9 ..

Permits Corruption and licenses

Crime

Informality

Firms formally registered when operations started % of firms

Time required to obtain operating license

Informal payments to public officials

Losses due to theft, robbery, vandalism, and arson

days

% of firms

% of sales

9.8 29.4 20.0 .. 18.1 18.0 18.8 .. 9.1 5.4 .. 15.1 4.4 16.3 .. 40.6 .. .. 83.8 40.5 49.5 .. 19.4 16.7 .. .. 17.7 .. 51.7 22.9 .. .. .. 7.3 56.2 .. 52.1 13.3 68.2 14.3 ..

0.3 0.8 1.3 .. 0.5 0.6 0.8 .. 0.7 0.4 .. 1.0 0.2 0.5 .. 1.3 .. .. 0.8 0.3 1.2 0.1 1.5 2.4 .. .. 0.4 .. 1.0 0.6 .. .. .. 0.7 0.7 1.4 0.3 1.2 0.6 1.0 ..

23.7 57.4 6.5 .. 21.4 28.0 12.6 .. 32.1 56.1 .. 36.2 .. 49.5 .. 24.0 .. .. 169.2 22.6 15.9 32.1 16.6 56.4 .. .. 36.0 .. 9.3 31.0 .. .. .. 133.8 9.1 41.6 15.9 21.3 6.5 48.3 ..

98.7 94.7 .. .. 78.9 95.0 89.2 .. 100.0 99.9 .. 91.0 .. .. .. .. .. .. .. 92.7 .. .. 91.8 75.8 .. .. 94.1 .. .. 95.8 .. .. .. 97.8 100.0 97.3 87.5 .. 81.7 96.2 ..

Gender

Firms with Firms using banks to female finance participation in ownership investment % of firms

% of firms

47.9 33.1 41.0 .. 26.3 28.8 7.9 .. 29.6 42.2 .. 22.6 34.1 .. .. 28.6 .. .. 14.4 34.4 30.9 .. 42.9 31.8 .. .. 40.7 .. 34.7 47.1 .. .. .. 41.6 39.8 .. 59.2 18.0 6.4 37.2 ..

37.3 30.6 15.9 .. 19.8 42.8 6.9 .. 33.5 52.2 .. 34.8 32.6 26.2 .. 7.7 .. .. 20.7 21.4 6.8 74.4 1.6 16.9 .. .. 51.9 .. 7.7 32.1 .. .. .. 6.9 8.2 35.7 21.5 4.2 4.2 10.2 ..

Note: Enterprise surveys are updated several times a year; see www.enterprisesurveys.org for the most recent updates. a. For survey data collected in 2006 and 2007, data refer to the manufacturing module only.

272

2011 World Development Indicators

Finance

Infrastructure Innovation

Trade

Average Inter­ time to nationally recognized clear direct exports quality Value lost due to electrical certification through customs ownership outages % of sales

2.2 1.2 8.7 .. 5.0 1.3 6.6 .. 0.3 0.5 .. 1.6 3.0 .. .. 2.5 .. .. 8.6 15.1 9.6 1.5 7.6 10.5 .. .. 2.8 .. 10.2 4.4 .. .. .. 0.9 5.4 4.4 3.7 4.6 13.2 3.7 ..

% of firms

26.1 11.7 10.8 .. 6.1 21.8 13.8 .. 28.6 28.0 .. 26.4 21.3 .. .. 22.1 .. .. 7.4 16.7 14.7 39.0 2.2 6.6 .. .. 30.0 .. 15.5 13.0 .. .. .. 6.8 1.3 12.5 16.7 18.2 4.4 17.2 ..

days

2.0 4.6 6.7 .. 7.4 1.6 .. .. 2.4 2.2 .. 4.5 4.9 7.6 .. 2.1 .. .. 5.1 20.4 5.7 1.3 .. 6.7 .. .. 5.2 .. 3.2 3.4 .. .. .. 2.5 5.1 14.1 4.5 6.0 6.2 2.3 ..

Workforce

Firms offering formal traininga % of firms

24.9 52.2 27.6 .. 16.3 36.5 18.6 .. 33.1 47.5 .. 36.8 51.3 32.6 .. 51.0 .. .. 38.3 21.1 36.5 75.3 49.7 31.0 .. .. 28.8 .. 35.0 24.8 .. .. .. 24.6 9.6 42.3 43.6 26.5 12.9 26.0 ..


About the data

5.2

states and markets

Business environment: Enterprise Surveys Definitions

The World Bank Group’s Enterprise Survey gath-

The reliability and availability of infrastructure ben-

• Survey year is the year in which the underlying data

ers firm-level data on the business environment

efit households and support development. Firms with

were collected. • Time dealing with officials is the

to assess constraints to private sector growth and

access to modern and efficient infrastructure—tele-

average percentage of senior management’s time

enterprise performance. Standardized surveys are

communications, electricity, and transport—can be

that is spent in a typical week dealing with require-

conducted all over the world, and data are available

more productive. Firm-level innovation and use of

ments imposed by government regulations. • Aver-

on more than 120,000 firms in 125 countries. The

modern technology may help firms compete.

age number of times meeting with tax officials is

survey covers 11 dimensions of the business envi-

Delays in clearing customs can be costly, deterring

the average number of visits or required meetings

ronment, including regulation, corruption, crime,

firms from engaging in trade or making them uncom-

with tax officials. • Time required to obtain operat-

informality, finance, infrastructure, trade. For some

petitive globally. Ill-considered labor regulations dis-

ing license is the average wait to obtain an operating

countries, firm-level panel data are available, making

courage firms from creating jobs, and while employed

license from the day applied for to the day granted.

it possible to track changes in the business environ-

workers may benefit, unemployed, low-skilled, and

•  Informal payments to public officials are the

ment over time.

informally employed workers will not. A trained labor

percentage of firms that answered positively to the

force enables firms to thrive, compete, innovate, and

question “Was a gift or informal payment expected

adopt new technology.

or requested during a meeting with tax officials?”

Firms evaluating investment options, governments interested in improving business conditions, and economists seeking to explain economic perfor-

The data in the table are from Enterprise Surveys

•  Losses due to theft, robbery, vandalism, and

mance have all grappled with defining and measur-

implemented by the World Bank’s Financial and Pri-

arson are the estimated losses from those causes

ing the business environment. The firm-level data

vate Sector Development Enterprise Analysis Unit. All

that occurred on establishments’ premises as a

from Enterprise Surveys provide a useful tool for

economies in East Asia and Pacific, Europe and Cen-

percentage of annual sales. • Firms formally regis-

benchmarking economies across a large number of

tral Asia, Latin America and the Caribbean, Middle

tered when operations started are the percentage

indicators measured at the firm level.

East and North Africa, and Sub-Saharan Africa (for

of firms formally registered when they started opera-

Most countries can improve regulation and taxa-

2009) and Afghanistan, Bangladesh, and India draw

tions in the country. Firms not formally registered (the

tion without compromising broader social interests.

a sample of registered nonagricultural businesses,

residual) are in the informal sector of the economy.

Excessive regulation may harm business perfor-

excluding those in the financial and public sectors.

• Firms with female participation in ownership are

mance and growth. For example, time spent with

Samples for other economies are drawn only from the

the percentage of firms with a woman among the own-

tax officials is a burden firms may face in paying

manufacturing sector and are footnoted in the table.

ers. • Firms using banks to finance investment are

taxes. The business environment suffers when gov-

Typical Enterprise Survey sample sizes range from

the percentage of firms that invested in fixed assets

ernments increase uncertainty and risks or impose

150 to 1,800, depending on the size of the economy.

during the last fiscal year that used banks to finance

unnecessary costs and unsound regulation and taxa-

In each country samples are selected by stratified

fixed assets. • Value lost due to electrical outages

tion. Time to obtain licenses and permits and the

random sampling, unless otherwise noted. Stratified

is losses that resulted from power outages as a per-

associated red tape constrain firm operations.

random sampling allows indicators to be computed

centage of annual sales. • Internationally recognized

In some countries doing business requires informal

by sector, firm size, and region and increases the

quality certification ownership is the percentage of

payments to “get things done” in customs, taxes,

precision of economywide indicators compared with

firms that have an internationally recognized quality

licenses, regulations, services, and the like. Such

alternative simple random sampling. Stratification

certification, such as International Organization for

corruption harms the business environment by dis-

by sector of activity divides the economy into manu-

Standardization 9000, 9001, 9002, or 14000 or

torting policymaking, undermining government cred-

facturing and retail and other services sectors. For

Hazard Analysis and Critical Control Points. • Aver-

ibility, and diverting public resources. Crime, theft,

medium-size and large economies the manufacturing

age time to clear direct exports through customs

and disorder also impose costs on businesses and

sector is further stratified by industry. Firm size is

is the average number of days to clear direct exports

society.

stratified into small (5–19 employees), medium-size

through customs. • Firms offering formal training

In many developing countries informal businesses

(20–99 employees), and large (more than 99 employ-

are the percentage of firms offering formal training

operate without formal registration. These firms have

ees). Geographic stratification divides the national

programs for their permanent, full-time employees.

less access to financial and public services and can

economy into the main centers of economic activity.

engage in fewer types of contracts and investments, constraining growth. Equal opportunities for men and women contribute to development. Female participation in firm ownership is a measure of women’s integration as decision makers. Financial markets connect firms to lenders and investors, allowing firms to grow their businesses:

Data sources

creditworthy firms can obtain credit from financial

Data on the business environment are from the

intermediaries at competitive prices. But too often

World Bank Group’s Enterprise Surveys website

market imperfections and government-induced distor-

(www.enterprisesurveys.org).

tions limit access to credit and thus restrain growth.

2011 World Development Indicators

273


5.3

Business environment: Doing Business indicators Starting a business

Number of procedures June 2010

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

274

4 5 14 8 14 6 2 8 6 7 5 3 7 15 12 10 15 4 4 11 9 6 1 8 13 8 14 3 9 10 10 12 10 6 .. 9 4 8 13 6 8 13 5 5 3 5 9 8 3 9 7 15 12 13 17 13 13

Time required days June 2010

7 5 24 68 26 15 2 28 8 19 5 4 31 50 55 61 120 18 14 32 85 19 5 22 75 22 38 6 14 84 160 60 40 7 .. 20 6 19 56 7 17 84 7 9 14 7 58 27 3 15 12 19 37 41 216 105 14

2011 World Development Indicators

Registering property

Cost % of per capita income June 2010

26.7 16.8 12.9 163.0 14.2 3.1 0.7 5.2 3.1 33.3 1.6 5.4 152.6 100.8 17.7 2.2 7.3 1.6 49.8 129.3 128.3 51.2 0.4 228.4 226.9 6.8 4.5 2.0 14.7 735.1 111.4 10.5 133.0 8.6 .. 9.3 0.0 19.2 32.6 6.3 45.0 69.2 1.9 14.1 1.1 0.9 21.9 199.6 5.0 4.8 20.3 20.7 49.1 146.6 183.3 212.0 47.2

Number of procedures June 2010

9 6 11 7 6 3 5 3 4 8 3 8 4 7 7 5 14 8 4 5 7 5 6 5 6 6 4 5 7 6 6 6 6 5 .. 4 3 7 9 7 5 11 3 10 3 8 7 5 1 5 5 11 4 6 9 5 7

Time required days June 2010

250 42 47 184 52 7 5 21 11 245 15 79 120 92 33 16 42 15 59 94 56 93 17 75 44 31 29 36 20 54 55 21 62 104 .. 43 42 60 16 72 31 78 18 41 14 59 39 66 2 40 34 22 23 104 211 405 23

Dealing with construction permits

Number of procedures to build a warehouse June 2010

13 24 22 12 28 20 16 14 31 14 16 14 15 17 16 24 18 24 15 25 23 14 14 21 14 18 37 7 10 14 17 23 21 13 .. 36 6 17 19 25 34 .. 14 12 18 13 16 17 10 12 18 15 22 32 15 11 17

Time required to build a warehouse days June 2010

340 331 240 328 338 137 221 194 207 231 151 169 320 249 255 167 411 139 122 212 709 213 75 239 164 155 336 67 50 128 169 191 592 315 .. 150 69 214 155 218 155 .. 134 128 66 137 210 146 98 100 220 169 178 255 167 1,179 106

Enforcing contracts

Number of procedures June 2010

47 39 46 46 36 49 28 25 39 41 28 26 42 40 37 29 45 39 37 44 44 43 36 43 41 36 34 24 34 43 44 40 33 38 .. 27 35 34 39 41 30 39 36 37 32 29 38 32 36 30 36 39 31 50 40 35 45

Time required days June 2010

1,642 390 630 1,011 590 285 395 397 237 1,442 225 505 825 591 595 625 616 564 446 832 401 800 570 660 743 480 406 280 1,346 625 560 852 770 561 .. 611 410 460 588 1,010 786 405 425 620 375 331 1,070 434 285 394 487 819 1,459 276 1,140 508 900

Protecting Closing a investors business

Disclosure index 0–10 (least to most disclosure) June 2010

Time to resolve insolvency years June 2010

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

.. .. 2.5 6.2 2.8 1.9 1.0 1.1 2.7 4.0 5.8 0.9 4.0 1.8 3.3 1.7 4.0 3.3 4.0 .. .. 3.2 0.8 4.8 .. 4.5 1.7 1.1 3.0 5.2 3.3 3.5 2.2 3.1 .. 3.2 1.1 3.5 5.3 4.2 4.0 .. 3.0 3.0 0.9 1.9 5.0 3.0 3.3 1.2 1.9 2.0 3.0 3.8 .. 5.7 3.8


Starting a business

Number of procedures June 2010

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

4 12 9 6 11 4 5 6 6 8 8 6 11 .. 8 10 13 2 7 5 5 7 5 .. 6 3 2 10 9 6 9 5 6 8 7 6 9 .. 10 7 6 1 6 9 8 5 5 10 6 6 7 6 15 6 6 7 8

Time required days June 2010

4 29 47 8 77 13 34 6 8 23 13 19 33 .. 14 58 35 10 100 16 9 40 20 .. 22 3 7 39 17 8 19 6 9 10 13 12 13 .. 66 31 8 1 39 17 31 7 12 21 9 51 35 27 38 32 6 7 12

Registering property

Cost % of per capita income June 2010

8.2 56.5 22.3 4.0 107.8 0.4 4.3 18.5 5.2 7.5 44.6 1.0 38.3 .. 14.7 28.7 1.3 3.7 11.3 1.5 75.0 26.0 54.6 .. 2.8 2.5 12.9 108.4 17.5 79.7 33.6 3.8 12.3 10.9 3.2 15.8 13.9 .. 18.5 46.6 5.7 0.4 117.9 118.6 78.9 1.8 3.3 10.7 10.3 17.7 55.1 13.6 29.7 17.5 6.5 0.7 9.7

Number of procedures June 2010

4 5 6 9 5 5 7 8 6 6 7 4 8 .. 7 8 8 4 9 6 8 6 10 .. 3 5 7 6 5 5 4 4 5 5 5 8 8 .. 9 3 5 2 8 4 13 1 2 6 8 4 6 4 8 6 1 8 10

Time required days June 2010

17 44 22 36 51 38 144 27 37 14 21 40 64 .. 11 33 55 5 135 42 25 101 50 .. 3 58 74 49 56 29 49 26 74 5 11 47 42 .. 23 5 7 2 124 35 82 3 16 50 32 72 46 7 33 152 1 194 16

Dealing with construction permits

Enforcing contracts

Number of procedures to build a warehouse June 2010

Time required to build a warehouse days June 2010

Number of procedures June 2010

31 37 14 17 14 11 20 14 10 15 19 34 11 .. 13 21 25 13 24 24 21 15 24 .. 17 21 16 21 25 15 25 18 11 30 21 19 17 .. 12 15 18 7 17 17 18 14 15 12 20 24 13 19 26 32 19 22 19

189 195 160 322 215 192 235 257 156 187 87 219 120 .. 34 320 104 143 172 186 218 601 77 .. 162 146 178 268 261 168 201 107 105 292 215 163 381 .. 139 424 230 65 219 265 350 252 186 223 116 217 179 188 169 311 272 209 76

35 46 40 39 51 20 35 41 35 30 38 38 40 .. 35 53 50 39 42 27 37 41 41 .. 30 37 38 42 30 36 46 36 38 31 32 40 30 .. 33 39 26 30 35 39 40 33 51 47 31 42 38 41 37 38 31 39 43

Time required days June 2010

395 1,420 570 505 520 515 890 1,210 655 360 689 390 465 .. 230 420 566 260 443 309 721 785 1,280 .. 275 370 871 312 585 620 370 645 415 365 314 615 730 .. 270 735 514 216 540 545 457 280 598 976 686 591 591 428 842 830 547 620 570

5.3

states and markets

Business environment: Doing Business indicators

Protecting Closing a investors business

Disclosure index 0–10 (least to most disclosure) June 2010

Time to resolve insolvency years June 2010

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

2.0 7.0 5.5 4.5 .. 0.4 4.0 1.8 1.1 0.6 4.3 1.5 4.5 .. 1.5 2.0 4.2 4.0 .. 3.0 4.0 2.6 3.0 .. 1.5 2.9 .. 2.6 2.3 3.6 8.0 1.7 1.8 2.8 4.0 1.8 5.0 .. 1.5 5.0 1.1 1.3 2.2 5.0 2.0 0.9 4.0 2.8 2.5 3.0 3.9 3.1 5.7 3.0 2.0 3.8 2.8

2011 World Development Indicators

275


5.3

Business environment: Doing Business indicators Starting a business

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

Number of procedures June 2010

Time required days June 2010

Cost % of per capita income June 2010

6 9 2 4 4 7 6 3 6 2 .. 6 10 4 10 12 3 6 7 8 12 7 10 7 9 10 6 .. 18 10 8 6 6 11 7 17 9 11 6 6 9 8u 8 8 8 8 8 8 6 9 8 7 9 6 6

10 30 3 5 8 13 12 3 16 6 .. 22 47 35 36 56 15 20 13 27 29 32 83 75 43 11 6 .. 25 27 15 13 6 65 15 141 44 49 12 18 90 34 u 41 39 35 43 39 40 18 60 23 25 43 18 14

2.6 3.6 8.8 7.0 63.1 7.9 110.7 0.7 1.9 0.0 .. 6.0 15.1 5.4 33.6 33.0 0.6 2.1 38.1 36.9 30.9 5.6 18.4 178.1 0.8 5.0 17.2 .. 94.4 6.1 6.4 0.7 1.4 42.1 11.9 30.2 12.1 93.7 82.1 27.9 182.8 40.7 u 107.9 31.7 44.4 16.1 52.6 31.5 8.9 39.6 54.6 24.5 95.2 7.3 6.7

Note: Regional aggregates are for developing countries only.

276

Registering property

2011 World Development Indicators

Dealing with construction permits

Number of procedures June 2010

Time required days June 2010

Number of procedures to build a warehouse June 2010

Time required to build a warehouse days June 2010

8 6 4 2 6 6 7 3 3 6 .. 6 4 8 6 9 1 4 4 6 9 2 .. 5 8 4 6 .. 13 10 1 2 4 8 12 8 4 7 6 5 5 6u 7 6 6 6 6 5 6 7 7 6 7 5 5

48 43 55 2 122 91 86 5 17 113 .. 24 18 83 9 44 7 16 19 37 73 2 .. 295 162 39 6 .. 77 117 2 8 12 66 78 47 57 47 19 40 31 58 u 94 54 65 41 65 99 36 62 39 100 69 38 35

17 53 14 12 16 20 25 11 13 14 .. 17 11 22 19 14 8 14 26 30 22 11 22 15 20 20 25 .. 18 22 17 11 19 30 28 11 13 21 15 17 17 18 u 18 19 18 19 19 19 23 16 20 18 18 17 14

228 540 195 89 210 279 252 25 287 199 .. 174 233 214 271 116 116 154 128 228 328 156 208 277 261 97 188 .. 171 374 64 95 40 234 274 395 194 199 107 254 1,012 207 u 275 201 197 206 221 181 235 220 181 241 240 169 227

Enforcing contracts

Protecting Closing a investors business

Number of procedures June 2010

Time required days June 2010

Disclosure index 0–10 (least to most disclosure) June 2010

31 37 24 43 44 36 40 21 31 32 .. 30 39 40 53 40 30 31 55 34 38 36 51 41 42 39 35 .. 38 30 49 28 32 41 42 29 34 44 36 35 38 38 u 39 39 40 38 39 37 38 39 42 44 39 35 31

512 281 230 635 780 635 515 150 565 1,290 .. 600 515 1,318 810 972 508 417 872 430 462 479 1,285 588 1,340 565 420 .. 490 345 537 399 300 720 195 510 295 540 520 471 410 605 u 613 638 679 588 631 564 382 698 701 1,053 641 532 602

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

Time to resolve insolvency years June 2010

3.3 3.8 .. 1.5 3.0 2.7 2.6 0.8 4.0 2.0 .. 2.0 1.0 1.7 .. 2.0 2.0 3.0 4.1 1.7 3.0 2.7 .. 3.0 .. 1.3 3.3 .. 2.2 2.9 5.1 1.0 1.5 2.1 4.0 4.0 5.0 .. 3.0 2.7 3.3 2.9 u 3.7 3.1 3.3 2.9 3.3 3.1 2.9 3.2 3.5 4.5 3.4 2.1 1.6


About the data

5.3

states and markets

Business environment: Doing Business indicators Definitions

The economic health of a country is measured not

The Doing Business project encompasses two

• Number of procedures for starting a business is the

only in macroeconomic terms but also by other

types of data: data from readings of laws and regu-

number of procedures required to start a business,

factors that shape daily economic activity such as

lations and data on time and motion indicators that

including interactions to obtain necessary permits and

laws, regulations, and institutional arrangements.

measure efficiency in achieving a regulatory goal.

licenses and to complete all inscriptions, verifications,

The Doing Business indicators measure business

Within the time and motion indicators cost estimates

and notifications to start operations for businesses

regulation, gauge regulatory outcomes, and measure

are recorded from official fee schedules where appli-

with specific characteristics of ownership, size, and

the extent of legal protection of property, the flex-

cable. The data from surveys are subjected to numer-

type of production. • Time required for starting a

ibility of employment regulation, and the tax burden

ous tests for robustness, which lead to revision or

business is the number of calendar days to complete

on businesses.

expansion of the information collected.

the procedures for legally operating a business using

The table presents a subset of Doing Business

The Doing Business methodology has limitations

the fastest procedure, independent of cost. • Cost

indicators covering 6 of the 10 sets of indicators:

that should be considered when interpreting the

for starting a business is normalized as a percentage

starting a business, registering property, dealing with

data. First, the data collected refer to businesses

of gross national income (GNI) per capita. It includes

construction permits, enforcing contracts, protecting

in the economy’s largest city and may not represent

all official fees and fees for legal or professional ser-

investors, and closing a business. Table 5.5 includes

regulations in other locations of the economy. To

vices if such services are required by law. • Number of

Doing Business measures of getting credit, and table

address this limitation, subnational indicators are

procedures for registering property is the number of

5.6 presents data on paying taxes.

being collected for selected economies. These sub-

procedures required for a business to legally transfer

The fundamental premise of the Doing Business

national studies point to significant differences in

property. • Time required for registering property is

project is that economic activity requires good rules

the speed of reform and the ease of doing business

the number of calendar days for a business to legally

and regulations that are efficient, accessible to all

across cities in the same economy. Second, the data

transfer property. • Number of procedures for deal-

who need to use them, and simple to implement.

often focus on a specific business form—generally

ing with licenses to build a warehouse is the number

Thus some Doing Business indicators give a higher

a limited liability company of a specified size—and

of interactions of a company’s employees or manag-

score for more regulation, such as stricter disclosure

may not represent regulation for other types of busi-

ers with external parties, including government staff,

requirements in related-party transactions, and oth-

nesses such as sole proprietorships. Third, transac-

public inspectors, notaries, land registry and cadastre

ers give a higher score for simplified regulations,

tions described in a standardized business case refer

staff, and technical experts apart from architects and

such as a one-stop shop for completing business

to a specific set of issues and may not represent the

engineers. • Time required for dealing with construc-

startup formalities.

full set of issues a business encounters. Fourth, the

tion permits to build a warehouse is the number of

In constructing the indicators, it is assumed that

time measures involve an element of judgment by the

calendar days to complete the required procedures

entrepreneurs know about all regulations and comply

expert respondents. When sources indicate different

for building a warehouse using the fastest procedure,

with them; in practice, entrepreneurs may not be

estimates, the Doing Business time indicators repre-

independent of cost. • Number of procedures for

aware of all required procedures or may avoid legally

sent the median values of several responses given

enforcing contracts is the number of independent

required procedures altogether. But where regula-

under the assumptions of the standardized case.

actions, mandated by law or court regulation, that

tion is particularly onerous, levels of informality are

Fifth, the methodology assumes that a business has

demand interaction between the parties to a con-

higher, which comes at a cost: firms in the informal

full information on what is required and does not

tract or between them and the judge or court officer.

sector usually grow more slowly, have less access

waste time when completing procedures.

• Time required for enforcing contracts is the number

to credit, and employ fewer workers—and those

of calendar days from the time of the filing of a law-

workers remain outside the protections of labor law.

suit in court to the final determination and payment.

The indicators in the table can help policymakers

• Extent of disclosure index measures the degree

understand the business environment in a country

to which investors are protected through disclosure

and—along with information from other sources such

of ownership and financial information. Higher values

as the World Bank’s Enterprise Surveys—provide

indicate more disclosure. • Time to resolve insolvency

insights into potential areas of reform.

is the number of years from time of filing for insolvency

Doing Business data are collected with a standardized survey that uses a simple business case

in court until resolution of distressed assets and payment of creditors.

to ensure comparability across economies and over time—with assumptions about the legal form of the business, its size, its location, and nature of its operation. Surveys in 183 countries are administered through more than 8,200 local experts, including

Data sources

lawyers, business consultants, accountants, freight

Data on the business environment are from

forwarders, government officials, and other profes-

the World Bank’s Doing Business project

sionals who routinely administer or advise on legal

(www.doingbusiness.org).

and regulatory requirements.

2011 World Development Indicators

277


5.4

Stock markets Market capitalization

$ millions 2000

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

278

.. .. .. .. 166,068 2 372,794 29,935 3 1,186 .. 182,481 .. 1,742 .. 978 226,152 617 .. .. .. .. 841,385 .. .. 60,401 580,991 623,398 9,560 .. .. 2,924 1,185 2,742 .. 11,002 107,666 .. 704 28,741 2,041 .. 1,846 .. 293,635 1,446,634 .. .. 24 1,270,243 502 110,839 172 .. .. .. 458

% of GDP 2010

2000

.. .. .. .. 63,910 28 1,454,547 67,683 .. 47,000 .. 269,342 .. 3,388 .. 4,076 1,545,566 7,276 .. .. .. .. 2,160,229 .. .. 341,584 4,762,837 2,711,334 208,502 .. .. 1,445 7,099 24,912 .. 43,056 231,746 .. 5,263 82,495 4,227 .. 2,260 .. 118,160 1,926,488 .. .. 1,060 1,429,707 3,531 72,639 .. .. .. .. ..

.. .. .. .. 58.4 0.1 89.4 15.7 0.1 2.5 .. 78.5 .. 20.7 .. 17.4 35.1 4.8 .. .. .. .. 116.1 .. .. 80.3 48.5 368.6 9.5 .. .. 18.3 11.4 12.8 .. 19.4 67.3 .. 4.4 28.8 15.5 .. 32.5 .. 241.2 108.9 .. .. 0.8 66.8 10.1 88.3 0.9 .. .. .. 8.8

2011 World Development Indicators

2009

.. .. .. .. 15.9 1.6 136.1 14.1 .. 7.9 .. 55.5 .. 16.1 .. 33.8 73.2 14.6 .. .. .. .. 125.8 .. .. 128.0 100.4 1,088.3 57.0 .. .. 5.0 26.4 40.7 .. 27.7 60.4 .. 7.4 47.7 21.0 .. 13.9 .. 38.2 74.4 .. .. 6.8 39.0 9.6 16.6 .. .. .. .. ..

Market liquidity

Turnover ratio

Value of shares traded % of GDP

Value of shares traded % of market capitalization

Listed domestic companies

number

S&P/Global Equity Indices

% change

2000

2009

2000

2010

2000

2010

2009

2010

.. .. .. .. 2.1 0.0 54.3 4.9 .. 1.6 .. 16.4 .. 0.8 .. 0.8 15.7 0.4 .. .. .. .. 87.6 .. .. 8.1 60.2 223.4 0.4 .. .. 0.7 0.3 0.9 .. 11.6 57.2 .. 0.1 11.1 0.2 .. 5.7 .. 169.8 81.6 .. .. 0.1 56.3 0.2 75.7 0.1 .. .. .. ..

.. .. .. .. 0.9 0.0 82.4 6.7 .. 16.3 .. 27.1 .. 0.1 .. 0.9 40.7 0.8 .. .. .. .. 92.8 .. .. 23.0 179.6 707.4 5.5 .. .. 0.1 0.6 2.3 .. 10.8 47.9 .. 2.4 28.0 .. .. 2.0 .. 38.3 51.6 .. .. 0.0 38.7 0.2 15.7 .. .. .. .. ..

.. .. .. .. 4.8 11.9 56.5 29.8 .. 74.8 .. 20.7 .. 5.7 .. 4.7 44.6 8.7 .. .. .. .. 77.3 .. .. 9.5 158.3 61.3 3.8 .. .. 4.0 2.5 7.1 .. 57.7 86.0 .. 2.0 36.1 1.2 .. 18.0 .. 64.3 74.1 .. .. 11.3 79.1 1.4 60.4 6.4 .. .. .. ..

.. .. .. .. 4.6 0.2 90.1 79.4 .. 54.4 .. 42.0 .. 0.4 .. 3.5 66.4 2.8 .. .. .. .. 71.1 .. .. 19.7 164.4 63.9 13.4 .. .. 2.8 2.0 4.1 .. 29.4 69.1 .. 3.8 43.0 .. .. 13.1 .. 97.4 42.5 .. .. 0.3 103.0 3.4 67.7 .. .. .. .. ..

.. .. .. .. 127 105 1,330 97 2 221 .. 174 .. 26 .. 16 459 503 .. .. .. .. 1,418 .. .. 258 1,086 779 126 .. .. 21 41 64 .. 131 225 .. 30 1,076 40 .. 23 .. 154 808 .. .. 269 1,022 22 329 7 .. .. .. 94

.. .. .. .. 101 2 1,913 72 .. 302 .. 161 .. 38 .. 21 373 390 .. .. .. .. 3,805 .. .. 227 2,063 1,396 84 .. .. 9 38 221 .. 16 196 .. 40 211 61 .. 15 .. 123 901 .. .. 143 571 35 287 .. .. .. .. ..

.. .. .. .. 97.8 a .. 72.4 57.0 .. 38.6a .. 54.5 .. .. .. 24.3a 125.1 17.2a .. .. .. .. 57.5 .. .. 84.0 66.3 67.1 75.7a .. .. .. –10.7a 31.1a .. 23.0 40.6 .. –13.1a 35.6 .. .. 32.9a .. 17.5 25.6b .. .. .. 25.8 c –42.7a 22.1 .. .. .. .. ..

.. .. .. .. 55.3a .. 12.5 10.9 .. 37.6a .. 0.5 .. .. .. –6.8a 6.5 –15.2a .. .. .. .. 22.0 .. .. 47.2 6.9 21.3 44.1a .. .. .. 19.3a –0.4 a .. 0.2 25.1 .. 9.7a 11.5 .. .. 56.0a .. 10.7 –9.9b .. .. .. 7.4 c 94.1a –43.8 .. .. .. .. ..


Market capitalization

$ millions 2000

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

12,021 148,064 26,834 7,350 .. 81,882 64,081 768,364 3,582 3,157,222 4,943 1,342 1,283 .. 171,587 .. 20,772 4 .. 563 1,583 .. .. .. 1,588 7 .. .. 116,935 .. .. 1,331 125,204 38 37 10,899 .. .. 311 790 640,456 18,866 .. .. 4,237 65,034 3,463 6,581 2,794 1,520 224 10,562 25,957 31,279 60,681 .. 5,152

% of GDP 2010

27,708 1,615,860 360,388 86,616 .. 33,722 218,055 318,140 6,626 4,099,591 30,864 60,742 14,461 .. 1,089,217 .. 119,621 79 .. 1,252 12,586 .. .. .. 5,661 2,647 .. 1,363 410,534 .. .. 6,506 454,345 .. 1,093 69,153 .. .. 1,176 4,843 661,204 36,295 .. .. 50,883 250,922 20,267 38,169 10,917 9,742 42 99,831 157,321 190,235 81,996 .. 123,592

2000

25.1 32.2 16.3 7.3 .. 84.8 51.4 70.0 39.8 67.6 58.4 7.3 10.1 .. 32.2 .. 55.1 0.3 .. 7.2 9.2 .. .. .. 13.9 0.2 .. .. 124.7 .. .. 29.0 21.5 3.2 3.4 29.4 .. .. 8.0 14.4 166.3 36.7 .. .. 9.2 38.6 17.4 8.9 24.0 49.3 3.5 19.8 34.2 18.3 51.9 .. 29.0

Market liquidity

Turnover ratio

Listed domestic companies

Value of shares traded % of GDP

Value of shares traded % of market capitalization

number

5.4

states and markets

Stock markets

S&P/Global Equity Indices

% change

2009

2000

2009

2000

2010

2000

2010

2009

2010

21.9 85.6 33.0 19.1 .. 13.2 93.2 15.0 51.4 66.6 127.0 50.0 36.6 .. 100.5 .. 72.4 1.6 .. 7.0 37.3 .. .. .. 12.0 10.0 .. 29.3 132.6 .. .. 55.2 38.9 .. 10.2 68.8 .. .. 9.1 43.8 68.5 52.9 .. .. 19.3 59.5 37.5 20.5 32.6 116.1 0.3 53.5 49.7 31.5 42.4 .. 89.4

25.4 110.8 8.7 1.1 .. 14.9 18.8 70.9 0.8 57.7 4.9 0.5 0.4 .. 200.2 .. 11.2 1.7 .. 2.9 0.7 .. .. .. 1.8 3.3 .. .. 62.4 .. .. 1.6 7.8 1.9 0.7 3.0 .. .. 0.6 0.6 175.9 21.0 .. .. 0.6 35.7 2.8 44.6 1.3 0.0 0.1 2.9 10.8 8.5 46.5 .. 1.3

20.1 79.1 21.3 5.2 .. 8.1 45.2 21.8 1.0 82.7 54.4 3.5 1.7 .. 190.0 .. 82.9 1.5 .. 0.1 3.0 .. .. .. 0.8 0.7 .. 0.4 37.8 .. .. 3.8 8.8 0.2 0.4 32.2 .. .. 0.2 1.8 76.3 29.4 .. .. 2.6 64.9 12.6 14.5 0.2 0.2 0.1 2.4 10.7 13.0 19.7 .. 25.9

85.8 306.5 31.5 7.4 .. 19.2 36.6 104.0 2.5 69.9 7.7 4.9 3.5 .. 376.6 .. 21.3 580.6 .. 47.8 6.7 .. .. .. 14.8 1,612.9 .. .. 44.6 .. .. 5.1 32.5 80.2 23.2 8.9 .. .. 4.4 5.4 101.4 45.9 .. .. 7.3 93.4 14.2 486.8 4.7 0.1 3.5 12.7 24.1 48.1 85.5 .. 4.5

94.5 75.6 48.1 22.9 .. 52.9 66.7 169.7 3.3 114.5 30.1 3.9 8.6 .. 168.9 .. 38.8 11.9 .. 1.8 14.7 .. .. .. 5.8 2.0 .. 1.5 27.1 .. .. 6.4 27.3 .. 6.4 16.3 .. .. 1.8 1.9 98.4 20.8 .. .. 12.5 90.8 18.2 36.2 2.0 .. .. 4.7 22.6 47.6 34.6 .. 17.3

60 5,937 290 304 .. 76 654 291 46 2,561 163 23 57 .. 1,308 .. 77 80 .. 64 12 .. .. .. 54 1 .. .. 795 .. .. 40 179 34 410 53 .. .. 13 110 234 142 .. .. 195 191 131 762 29 7 56 230 228 225 109 .. 22

48 4,987 420 341 .. 50 596 291 39 3,553 277 60 53 .. 1,781 .. 215 11 .. 33 10 .. .. .. 39 34 .. 14 957 .. .. 86 130 .. 336 73 .. .. 7 190 113 102 .. .. 215 195 120 644 34 10 50 199 251 569 47 .. 43

73.0 94.1 130.1 .. .. 44.7 56.8 23.1 –15.8a 16.4 d –13.9a 1.5a 0.6a .. 67.2 .. –10.4 a .. .. 2.2a 43.4 a .. .. .. 36.7a .. .. .. 46.7 .. .. 44.2a 55.8 .. .. –1.7 .. .. 22.6a .. 41.7 40.4 .. .. –35.4 a 91.4 22.0a 56.7a 15.4 a .. .. 79.3 71.5 41.9 35.0 .. 5.1a

–10.8 18.7 37.9 .. .. –7.7 7.4 –17.4 22.4 a 9.6d –8.6a –1.0a 33.8a .. 25.3 .. 29.1a .. .. 39.4 a –8.7a .. .. .. 44.0a .. .. .. 35.1 .. .. 8.2a 26.6 .. .. 13.1 .. .. 24.2a .. 1.2 5.2 .. .. 20.3a 13.7 12.2a 15.3a 12.8a .. .. 51.3 56.7 11.3 –16.6 .. 27.7a

2011 World Development Indicators

279


5.4

Stock markets Market capitalization

$ millions 2000

% of GDP 2010

Romania 1,069 32,385 Russian Federation 38,922 1,004,525 Rwanda .. .. Saudi Arabia 67,171 353,414 Senegal .. .. Serbia 734 9,690 Sierra Leone .. .. Singapore 152,827 370,091 Slovak Republic 1,217 4,150 Slovenia 2,547 9,428 Somalia .. .. South Africa 204,952 1,012,538 Spain 504,219 1,171,615 Sri Lanka 1,074 19,924 Sudan .. .. Swaziland 73 .. Sweden 328,339 581,174 Switzerland 792,316 1,229,357 Syrian Arab Republic .. .. Tajikistan .. .. Tanzania 233 1,264 Thailand 29,489 277,732 Timor-Leste .. .. Togo .. .. Trinidad and Tobago 4,330 12,158 Tunisia 2,828 10,682 Turkey 69,659 306,662 Turkmenistan .. .. Uganda 35 .. Ukraine 1,881 39,457 United Arab Emirates 5,727 104,669 United Kingdom 2,576,992 3,107,038 United States 15,104,037 17,138,978 Uruguay 161 157 Uzbekistan 32 .. Venezuela, RB 8,128 3,991 Vietnam .. 20,385 West Bank and Gaza 765 2,450 Yemen, Rep. .. .. Zambia 236 2,817 Zimbabwe 2,432 11,476 World 32,187,124 s 56,172,634 s Low income .. 86,835 Middle income 1,941,548 13,277,006 Lower middle income 879,123 7,570,880 Upper middle income 1,062,425 5,706,126 Low & middle income 1,948,214 13,363,841 East Asia & Pacific 780,487 6,001,435 Europe & Central Asia 115,145 1,473,816 Latin America & Carib. 620,023 2,750,758 Middle East & N. Africa 57,110 294,845 South Asia 157,695 1,725,795 Sub-Saharan Africa 217,754 1,117,191 High income 30,238,910 42,808,793 Euro area 5,435,393 6,276,893

2000

2.9 15.0 .. 35.6 .. 4.9 .. 164.8 4.2 12.8 .. 154.2 86.8 6.6 .. 4.9 132.8 317.0 .. .. 2.3 24.0 .. .. 53.1 14.5 26.1 .. 0.6 6.0 8.1 174.4 152.6 0.7 0.2 6.9 .. 18.6 .. 7.3 36.8 101.7 w .. 36.5 36.2 36.8 36.1 47.1 17.5 31.7 19.9 26.1 89.8 115.2 86.8

Market liquidity

Turnover ratio

Value of shares traded % of GDP

Value of shares traded % of market capitalization

2009

2000

18.8 69.9 .. 84.8 .. 26.8 .. 170.5 5.3 24.3 .. 247.0 88.8 19.4 .. 6.9 106.5 217.7 .. .. 5.4 52.4 .. .. 52.6 23.1 36.7 .. .. 14.8 47.6 128.6 106.8 0.4 .. 2.7 21.8 .. .. 17.4 161.4 85.2 w 37.7 73.2 82.2 62.1 72.6 91.0 50.8 52.9 38.0 73.3 154.1 89.9 49.3

0.6 7.8 .. 9.2 .. 0.1 .. 98.7 3.1 2.3 .. 58.3 169.8 0.9 .. 0.0 157.7 243.7 .. .. 0.4 19.0 .. .. 1.7 3.2 67.2 .. 0.0 0.9 0.2 124.2 321.9 0.0 0.1 0.6 .. 4.6 .. 0.2 4.2 151.4 w .. 34.5 54.6 17.5 34.0 49.8 30.1 8.4 5.1 90.2 32.3 175.5 80.2

2009

1.2 55.4 .. 89.7 .. 1.3 .. 138.4 0.2 2.1 .. 120.0 109.5 2.1 .. .. 96.1 161.7 .. .. 0.1 51.2 .. .. 1.1 3.2 39.6 .. .. 0.5 28.5 156.5 331.0 0.0 0.0 0.0 6.8 .. .. 0.8 16.1 142.5 w 7.9 82.7 124.3 31.5 81.9 149.0 38.3 20.9 16.2 67.0 48.1 165.3 45.6

2000

24.3 36.6 .. 27.1 .. .. .. 52.1 78.7 19.7 .. 33.2 210.7 10.8 .. 0.3 111.2 82.0 .. .. 19.4 52.9 .. .. 3.1 22.6 196.5 .. 1.7 19.2 1.8 66.6 200.8 0.9 25.7 8.8 .. 23.4 .. 3.1 11.3 140.2 w 18.3 93.8 162.2 44.2 93.5 116.2 131.0 27.1 21.4 308.8 31.7 143.0 90.1

2010

5.4 85.7 .. 60.5 .. 2.2 .. 82.9 3.9 2.6 .. 39.6 76.0 23.6 .. .. 86.8 75.6 .. .. .. 104.8 .. .. 1.2 17.2 158.4 .. .. 7.5 25.6 101.9 189.1 .. .. 0.8 141.4 18.7 .. .. .. 122.0 w 32.5 101.1 132.4 55.7 100.8 146.0 91.2 46.1 27.7 73.5 37.1 128.5 75.0

Listed domestic companies

number 2000

2010

S&P/Global Equity Indices

% change 2009

5,555 1,383 26.1a 249 345 106.6 .. .. .. 75 146 28.5e .. .. .. 6 7 .. .. .. .. 418 461 76.7 493 90 –23.1a 38 71 16.1a .. .. .. 616 360 53.7 1,019 3,310 29.0 239 241 118.0a .. .. .. 6 5 .. 292 331 66.0 252 246 24.5 .. .. .. .. .. .. 4 11 .. 381 541 72.8 .. .. .. .. .. .. 27 37 –10.2a 44 54 40.6a 315 337 99.6 .. .. .. 2 8 .. 139 183 31.1a 54 101 24.6a 1,904 2,056 35.2f 7,524 4,279 23.5g 16 6 .. 5 .. .. 85 55 .. .. 164 46.9a 24 41 .. .. .. .. 9 19 16.7a 69 76 –83.8 47,751 s 47,071 s .. 719 21,522 16,778 11,444 11,088 10,078 5,690 22,094 17,497 3,190 4,758 7,199 2,963 1,672 1,457 1,676 1,007 7,269 6,364 1,088 948 25,657 29,574 5,051 6,278

2010

–6.6a 21.7 .. 9.0e .. .. .. 18.4 5.4 a –20.3a .. 32.1 –24.5 84.6a .. .. 32.6 11.0 .. .. .. 52.1 .. .. 0.8 a 11.7a 21.4 .. .. 53.8a –6.8a 5.2f 12.8g .. .. .. 0.5a .. .. 17.4 a ..

a. Refers to the S&P Frontier BMI index. b. Refers to the CAC 40 index. c. Refers to the DAX index. d. Refers to the Nikkei 225 index. e. Refers to Saudi Arabia country index. f. Refers to the FTSE 100. g. Refers to the S&P 500 index.

280

2011 World Development Indicators


About the data

5.4

states and markets

Stock markets Definitions

The development of an economy’s financial markets

countries. Market capitalization shows the overall

•  Market capitalization (also known as market

is closely related to its overall development. Well

size of the stock market in U.S. dollars and as a

value) is the share price times the number of shares

functioning financial systems provide good and eas-

percentage of GDP. The number of listed domestic

outstanding. •  Market liquidity is the total value

ily accessible information. That lowers transaction

companies is another measure of market size. Mar-

of shares traded during the period divided by gross

costs, which in turn improves resource allocation and

ket size is positively correlated with the ability to

domestic product (GDP). This indicator complements

boosts economic growth. Both banking systems and

mobilize capital and diversify risk.

the market capitalization ratio by showing whether

stock markets enhance growth, the main factor in

Market liquidity, the ability to easily buy and sell

market size is matched by trading. • Turnover ratio

poverty reduction. At low levels of economic develop-

securities, is measured by dividing the total value

is the total value of shares traded during the period

ment commercial banks tend to dominate the finan-

of shares traded by GDP. The turnover ratio—the

divided by the average market capitalization for the

cial system, while at higher levels domestic stock

value of shares traded as a percentage of market

period. Average market capitalization is calculated as

markets tend to become more active and efficient

­capitalization—is also a measure of liquidity as well

the average of the end-of-period values for the cur-

relative to domestic banks.

as of transaction costs. (High turnover indicates low

rent period and the previous period. • Listed domes-

Open economies with sound macroeconomic poli-

transaction costs.) The turnover ratio complements

tic companies are the domestically incorporated

cies, good legal systems, and shareholder protection

the ratio of value traded to GDP, because the turn-

companies listed on the country’s stock exchanges

attract capital and therefore have larger financial mar-

over ratio is related to the size of the market and the

at the end of the year. This indicator does not include

kets. Recent research on stock market development

value traded ratio to the size of the economy. A small,

investment companies, mutual funds, or other col-

shows that modern communications technology and

liquid market will have a high turnover ratio but a low

lective investment vehicles. •  S&P/Global Equity

increased financial integration have resulted in more

value of shares traded ratio. Liquidity is an impor-

Indices measure the U.S. dollar price change in the

cross-border capital flows, a stronger presence of

tant attribute of stock markets because, in theory,

stock markets.

financial firms around the world, and the migration of

liquid markets improve the allocation of capital and

stock exchange activities to international exchanges.

enhance prospects for long-term economic growth.

Many firms in emerging markets now cross-list on inter-

A more comprehensive measure of liquidity would

national exchanges, which provides them with lower

include trading costs and the time and uncertainty

cost capital and more liquidity-traded shares. However,

in finding a counterpart in settling trades.

this also means that exchanges in emerging markets

Standard & Poor’s Index Services, the source for

may not have enough financial activity to sustain them,

all the data in the table, provides regular updates on

putting pressure on them to rethink their operations.

21 emerging stock markets and 36 frontier markets.

The indicators in the table are from Standard &

Standard & Poor’s maintains a series of indexes for

Poor’s Emerging Markets Data Base. They include

investors interested in investing in stock markets in

measures of size (market capitalization, number of

developing countries. The S&P/IFCI index, Standard

listed domestic companies) and liquidity (value of

& Poor’s leading emerging markets index, is designed

shares traded as a percentage of gross domestic

to be sufficiently investable to support index tracking

product, value of shares traded as a percentage of

portfolios in emerging market stocks that are legally

market capitalization). The comparability of such indi-

and practically open to foreign portfolio investment.

cators across countries may be limited by concep-

The S&P/Frontier BMI measures the performance of

tual and statistical weaknesses, such as inaccurate

36 smaller and less liquid markets. The individual

reporting and differences in accounting standards.

country indexes include all publicly listed equities

The percentage change in stock market prices in U.S.

representing an aggregate of at least 80 percent or

dollars for developing economies is from Standard

more of market capitalization in each market. These

& Poor’s Global Equity Indices (S&P IFCI) and Stan-

indexes are widely used benchmarks for international

dard & Poor’s Frontier Broad Market Index (BMI). The

portfolio management. See www.standardandpoors.

percentage change for France, Germany, Japan, the

com for further information on the indexes. Data sources

United Kingdom, and the United States is from local

Because markets included in Standard & Poor’s

stock market prices. The indicator is an important

emerging markets category vary widely in level of

Data on stock markets are from Standard & Poor’s

measure of overall performance. Regulatory and

development, it is best to look at the entire category

Global Stock Markets Factbook 2010, which draws

institutional factors that can affect investor confi-

to identify the most significant market trends. And it

on the Emerging Markets Data Base, supple-

dence, such as entry and exit restrictions, the exis-

is useful to remember that stock market trends may

mented by other data from Standard & Poor’s.

tence of a securities and exchange commission, and

be distorted by currency conversions, especially when

The firm collects data through an annual survey

the quality of laws to protect investors, may influence

a currency has registered a significant devaluation.

of the world’s stock exchanges, supplemented by

the functioning of stock markets but are not included in the table. Stock market size can be measured in various

About the data is based on Demirgüç-Kunt and

information provided by its network of correspon-

Levine (1996), Beck and Levine (2001), and Claes-

dents and by Reuters. Data on GDP are from the

sens, Klingebiel, and Schmukler (2002).

World Bank’s national accounts data files.

ways, and each may produce a different ranking of

2011 World Development Indicators

281


5.5

Financial access, stability, and efficiency Getting credit Strength of legal  rights index 0–10 (weak to strong)

Financial access and outreach

Deposit Loan accounts accounts Depth of at at Commercial Automated Pointcredit commercial commercial bank teller of-sale information banks banks branches machines terminals index per per per per per 0–6 100,000 100,000 100,000 1,000 1,000 (low to high) adults adults adults adults adults

June 2010 June 2010

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

282

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

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

2011 World Development Indicators

2009

2009

2009

.. 451 683 .. 875 572 .. 2,442 702 319 .. 3,725 .. 274 380 481 .. 1,987 .. 21 76 .. .. .. .. 746 .. .. 1,151 6 .. .. .. .. .. 1,680 .. .. 494 .. 737 .. 2,752 82 .. .. .. 269 661 .. 270 3,219 1,050 .. .. 330 744

4 102 .. .. 503 192 .. .. .. 42 .. .. .. 72 344 80 390 456 .. 1 25 .. .. .. .. 629 .. .. .. .. .. .. .. .. .. .. .. 310 .. .. .. .. 1,022 1 .. .. .. 44 349 .. .. 1,297 374 .. .. 11 ..

1.1 21.4 5.3 5.5 13.3 15.7 31.8 .. 8.6 5.2 44.9 50.0 .. 6.3 25.0 6.9 12.2 88.1 .. 1.7 3.7 .. 23.7 .. .. 15.0 .. 24.4 13.7 0.3 .. .. .. 33.2 .. 22.4 46.7 10.0 1.6 .. 8.2 .. 22.2 1.2 18.5 23.0 .. 5.5 18.6 16.3 4.4 38.8 33.1 .. .. .. 1.5

2009

0.18 26.87 4.13 7.82 33.04 22.22 159.30 118.37 23.05 .. 29.71 85.96 .. 15.11 27.14 29.26 110.19 78.22 .. 0.04 .. .. 202.78 .. .. 55.56 .. .. 26.31 .. .. 53.35 .. 88.62 .. 38.40 70.42 27.21 26.01 .. 22.86 .. 89.09 .. 38.74 102.55 .. 1.48 28.77 79.74 4.16 76.06 22.18 .. .. 0.58 21.89

Ratio of Bank bank noncapital to asset performing loans to total ratio gross loans

Domestic credit provided by banking sector

Interest rate spread

Risk premium on lending Prime lending rate minus treasury bill rate percentage points 2009

%

%

% of GDP

Lending rate minus deposit rate percentage points

2009

2009

2009

2009

2009

.. 123 8 25 .. 94 3,939 4,890 112 .. 165 1,086 .. 33 502 .. 1,471 683 .. 0 36 .. 2,202 .. .. 450 .. .. .. .. .. 0 .. 2,121 .. 651 2,023 .. .. .. 250 .. 1,417 .. 66 2,153 .. 5 169 799 4 3,827 486 .. .. .. ..

.. 8.7 .. .. 13.3 21.0 5.0 7.0 .. 6.5 16.6 4.5 .. 8.7 15.2 .. 9.5 10.8 .. .. .. .. 5.7 .. .. 7.4 5.6 12.7 13.6 .. .. 13.9 .. 13.9 .. 6.1 5.7 9.1 7.7 6.4 13.2 .. 8.5 .. 6.4 4.5 16.2 .. 18.3 4.8 17.0 6.1 10.5 .. .. .. ..

1.5 68.5 -8.9 29.2 28.0 19.9 143.6 141.1 23.1 60.4 34.6 119.3 19.1 49.5 58.3 -1.0 97.5 69.4 15.2 36.5 19.0 6.9 178.1 17.2 8.3 98.8 145.2 166.8 37.2 7.6 -15.9 54.3 22.8 76.9 .. 62.4 223.0 40.6 18.9 75.4 44.5 112.1 106.2 37.1 98.7 128.4 7.5 38.7 33.2 131.8 27.9 112.7 37.7 .. 4.9 25.8 54.1

.. 5.9 6.3 8.1 4.1 10.1 3.2 .. 7.8 6.4 1.0 .. .. 8.9 4.3 6.3 35.4 5.2 .. .. .. 10.8 2.3 10.8 10.8 5.2 3.1 5.0 6.9 49.5 10.8 12.8 .. 8.4 .. 4.7 .. 10.3 7.1 5.5 .. .. 4.6 3.3 .. .. 10.8 11.5 15.2 .. .. .. 8.3 .. .. 16.2 8.6

.. 10.5 .. .. 3.0 4.8 1.2 2.3 .. 11.2 4.2 2.7 .. 3.5 5.9 .. 4.2 6.4 .. .. .. .. 1.3 .. .. 3.0 1.6 1.1 4.1 .. .. 2.0 .. 7.8 .. 4.6 0.3 4.0 2.9 13.4 3.6 .. 5.2 .. 0.7 3.6 9.8 .. 6.3 3.3 16.2 7.7 2.7 .. .. .. ..

.. 6.4 7.3 .. .. 9.3 2.9 .. 16.7 .. .. 5.6 .. 9.5 .. .. 34.9 6.2 .. .. .. .. 2.0 .. .. .. .. 4.9 .. .. .. .. .. .. .. 4.7 .. .. .. 2.1 .. .. .. 7.3 .. .. .. .. 19.5 .. .. .. .. .. .. .. ..


Getting credit Strength of legal  rights index 0–10 (weak to strong)

Financial access and outreach

Deposit Loan accounts accounts Depth of at at Commercial Automated Pointcredit commercial commercial bank teller of-sale information banks banks branches machines terminals index per per per per per 0–6 100,000 100,000 100,000 1,000 1,000 (low to high) adults adults adults adults adults

June 2010 June 2010

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

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

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

2009

2009

2009

1,571 680 484 .. .. .. 2,254 763 1,172 .. 814 .. 296 .. .. .. .. 115 .. 1,219 1,310 199 .. .. 2,142 1,302 34 124 2,227 .. 37 2,110 1,014 .. 1,935 277 112 .. 466 165 1,772 .. 198 .. .. .. .. 226 757 .. 80 716 517 1,527 .. 1,026 ..

.. 124 181 .. .. .. 1,055 597 215 .. 160 .. 70 .. .. .. .. 25 .. 687 .. 18 .. .. 381 962 21 17 973 .. .. 417 .. .. 272 .. 20 .. 356 38 .. .. 185 .. .. .. .. 47 435 .. 89 367 .. .. .. .. ..

17.1 9.3 6.7 28.8 .. 34.1 19.8 53.0 7.2 12.5 16.2 21.6 4.0 .. 12.6 .. 15.1 6.3 1.7 12.0 29.1 1.9 .. .. 28.8 22.1 1.0 1.8 11.6 .. 3.8 19.4 14.0 9.7 56.7 11.6 2.9 .. 7.3 3.2 26.1 31.7 6.8 .. .. 35.0 22.1 7.5 18.9 2.8 6.2 7.5 10.5 32.6 55.9 16.6 ..

2009

54.24 3.55 13.44 23.97 .. .. 47.38 93.93 21.89 .. .. 52.83 6.67 .. .. .. 50.05 .. 3.06 .. 38.55 7.13 .. .. 51.69 45.98 0.96 1.48 43.25 .. 0.74 37.71 40.15 .. 18.18 16.65 4.32 .. 27.31 1.13 63.78 72.34 .. .. .. 59.73 .. 3.39 36.94 .. .. 17.67 13.33 42.16 189.60 43.33 ..

Ratio of Bank bank noncapital to asset performing loans to total ratio gross loans

Domestic credit provided by banking sector

5.5 Interest rate spread

Risk premium on lending Prime lending rate minus treasury bill rate percentage points 2009

%

%

% of GDP

Lending rate minus deposit rate percentage points

2009

2009

2009

2009

2009

585 .. 120 1,353 .. .. .. 2,386 674 .. .. 173 .. .. .. .. 904 .. .. .. 1,293 .. .. .. 1,413 1,297 2 2 941 .. .. 647 .. .. 448 46 34 .. 217 .. 2,286 3,916 .. .. .. 2,827 .. 47 427 .. .. 40 .. 253 2,548 1,398 ..

8.5 6.4 10.3 .. .. 5.6 6.0 8.0 .. 4.7 11.0 -9.3 12.7 .. 10.9 .. 12.1 .. .. 7.4 7.0 7.9 .. .. 7.9 11.4 .. .. 9.0 .. .. .. 9.7 16.0 .. 7.6 7.7 .. 7.9 .. 4.3 .. .. .. 18.4 6.0 13.5 10.1 11.7 .. 8.7 9.9 11.1 9.0 6.5 .. ..

79.9 69.4 36.9 37.2 -16.3 219.8 78.1 141.6 59.8 320.5 99.3 54.6 44.8 .. 112.4 14.3 65.1 14.0 10.5 93.2 165.0 -15.5 149.5 -65.9 69.3 44.0 11.6 32.0 137.4 10.7 .. 109.7 44.1 41.6 32.2 100.5 22.8 .. 43.5 69.6 224.4 154.2 67.5 12.2 35.9 .. 41.9 48.4 81.6 39.1 25.5 18.1 49.4 61.5 196.1 .. 75.7

5.2 .. 5.2 -1.1 7.8 .. 2.6 .. 9.5 1.3 4.3 .. 8.8 .. 2.2 10.1 3.3 19.2 19.3 8.2 2.3 8.2 10.1 3.5 3.6 3.0 33.5 21.8 3.0 .. 15.5 10.8 5.1 5.6 8.4 .. 6.2 5.0 4.9 5.5 -0.6 6.3 8.0 .. 5.1 2.0 3.3 5.9 4.8 7.8 26.8 18.2 5.8 .. .. .. 2.8

6.7 2.3 3.3 .. .. 9.0 1.5 7.0 .. 1.7 6.7 21.2 7.9 .. 1.2 4.4 9.7 .. .. 16.4 6.0 4.0 .. .. 19.3 8.9 .. .. 3.7 .. .. .. 3.1 16.3 .. 5.5 1.8 .. 2.7 .. .. .. .. .. 6.6 1.5 3.5 12.2 1.4 .. 1.6 2.7 4.1 7.6 3.2 .. ..

states and markets

Financial access, stability, and efficiency

2011 World Development Indicators

2.6 .. .. .. 1.8 .. 2.3 3.8 -3.5 1.6 .. .. 7.4 .. .. .. 5.2 12.5 11.5 5.8 4.7 5.2 .. .. -0.1 .. 37.4 15.1 3.0 .. 13.1 .. 1.6 9.2 15.0 .. 5.1 .. 2.9 1.7 .. 7.6 .. .. 14.6 .. .. 2.0 .. 3.0 .. .. 5.3 .. .. .. ..

283


5.5

Financial access, stability, and efficiency Getting credit Strength of legal  rights index 0–10 (weak to strong)

Financial access and outreach

Deposit Loan accounts accounts Depth of at at Commercial Automated Pointcredit commercial commercial bank teller of-sale banks banks branches machines terminals information per per per per per index 100,000 100,000 100,000 1,000 1,000 0–6 adults adults adults adults adults (low to high)

June 2010 June 2010

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

284

8 3 8 5 3 8 6 10 9 5 .. 9 6 4 5 6 5 8 1 3 8 4 1 3 8 3 4 .. 7 9 4 9 8 5 2 2 8 0 2 9 6 5.5 u 4.9 5.1 4.6 5.7 5.0 5.8 6.3 5.2 2.5 5.4 4.6 6.7 6.3

5 5 4 6 1 5 0 4 4 2 .. 6 5 5 0 5 4 5 2 0 0 5 0 1 4 5 5 .. 4 3 5 6 6 6 3 0 5 3 2 5 0 3.0 u 1.3 3.1 2.6 3.6 2.6 1.9 4.1 3.4 3.1 2.1 1.6 4.3 4.1

2011 World Development Indicators

2009

2009

2009

.. .. 202 .. .. .. .. 2,305 .. 1,394 .. 788 741 1,652 .. 270 .. .. 157 .. .. 1,498 .. .. .. 672 1,851 .. 154 3,755 .. .. 1,761 507 .. 518 .. .. 106 293 139

431 .. 2 .. .. .. .. 899 .. .. .. 297 310 487 .. 98 .. .. 23 .. .. 276 .. .. .. 176 315 .. 21 .. .. .. .. 439 .. 484 .. .. 6 19 ..

27.6 2.9 3.1 .. .. 44.9 .. 11.0 25.7 15.7 .. 8.0 40.5 9.1 .. 2.9 22.8 .. 2.2 3.9 1.8 10.9 .. .. .. 13.6 17.3 .. 1.9 3.3 .. .. 35.4 13.9 .. 18.5 3.3 .. 1.8 3.5 2.8

2009

50.63 65.60 0.38 .. .. 41.31 .. 50.64 47.76 99.47 .. 54.85 157.10 10.46 .. 15.96 36.94 93.70 0.95 2.97 2.63 65.48 .. .. .. 14.26 40.99 .. 2.24 70.09 .. 127.07 169.23 30.57 .. 27.99 .. .. 2.44 4.54 ..

2009

460 275 1 .. .. 959 .. 1,887 611 1,925 .. .. 3,523 .. .. 52 .. 2,004 .. 2 11 .. .. .. .. 172 3,046 .. 3 293 .. 2,177 2,156 275 .. .. .. .. 17 11 ..

Ratio of Bank bank noncapital to asset performing loans to total ratio gross loans

Domestic credit provided by banking sector

Interest rate spread

Risk premium on lending Prime lending rate minus treasury bill rate percentage points 2009

%

%

% of GDP

Lending rate minus deposit rate percentage points

2009

2009

2009

2009

15.3 9.7 13.1 3.3 18.7 15.5 16.5 2.3 5.3 2.3 .. 5.9 5.1 .. .. 8.1 2.0 0.4 .. .. .. 5.3 .. .. .. 13.2 5.6 .. 4.2 40.2 4.8 3.5 5.4 1.0 .. 3.0 .. .. .. .. .. 4.2 m .. 4.8 5.1 4.2 5.3 .. 9.3 3.0 .. 10.5 .. 3.4 3.6

52.7 33.8 .. 0.6 26.6 44.8 10.7 91.2 53.8 94.5 .. 183.5 228.4 39.6 20.0 9.1 143.8 191.0 45.1 27.5 18.1 136.9 -18.4 30.2 26.5 75.2 63.0 .. 11.2 88.5 114.5 228.9 230.5 27.9 .. 20.5 123.0 .. 19.3 18.5 .. 169.0 w 35.1 89.4 110.3 63.3 88.4 134.2 47.1 67.1 40.9 65.6 78.5 201.8 152.0

5.3 6.7 9.8 .. .. 0.0 14.8 5.1 4.3 4.5 .. 3.2 .. 5.1 .. 6.0 .. 2.7 3.7 17.1 7.1 4.9 10.3 .. 8.5 .. .. .. 11.2 7.1 .. .. .. 10.9 .. 3.5 3.1 .. 7.3 15.0 457.5 6.2 m 11.5 6.3 7.3 5.5 6.8 7.1 5.7 7.7 4.3 5.9 8.5 .. ..

7.6 15.7 13.0 11.9 9.3 21.0 18.9 10.5 9.6 8.3 .. 6.7 6.8 .. .. 16.9 5.0 5.5 .. .. .. 9.8 .. .. .. .. 13.3 .. 13.4 13.1 16.0 5.4 11.0 8.9 .. 9.4 .. .. .. .. .. 9.4 m .. 10.1 10.0 9.7 .. .. 13.3 9.6 .. 6.4 .. 6.8 6.5

6.4 .. 8.9 .. .. 1.4 9.0 5.0 .. 4.8 .. 3.9 .. 2.7 .. 3.4 .. 2.8 .. .. 7.9 4.7 .. .. 9.2 .. .. .. 13.9 .. .. 0.1 3.1 3.4 .. .. 2.0 .. 4.5 6.7 330.2


5.5

states and markets

Financial access, stability, and efficiency About the data Access to finance can expand opportunities for all with

all nonfinancial and financial assets. Data are from

consumer loans, business loans, trade loans, student

higher levels of access and use of banking services

internally consistent financial statements.

loans, emergency loans, agricultural loans, and the

associated with lower financing obstacles for people

The ratio of bank nonperforming loans to total gross

like. • Commercial banks branches are retail locations

and businesses. A stable financial system that pro-

loans, a measure of bank health and efficiency, helps

offering a wide array of face-to-face and automated

motes efficient savings and investment is also crucial

identify problems with asset quality in the loan portfo-

financial services. • Automated teller machines are

for a thriving democracy and market economy.

lio. A high ratio may signal deterioration of the credit

computerized telecommunications devices that pro-

There are several aspects of access to financial ser-

portfolio. International guidelines recommend that

vide clients of a financial institution with access to

vices: availability, cost, and quality of services. The

loans be classified as nonperforming when payments

financial transactions in a public place. • Point-of-sale

development and growth of credit markets depend on

of principal and interest are 90 days or more past

terminals are the equipment used to manage the sell-

access to timely, reliable, and accurate data on bor-

due or when future payments are not expected to be

ing process by a salesperson-accessible interface in

rowers’ credit experiences. Access to credit can be

received in full. Domestic credit provided by the bank-

the location where a transaction takes place. • Bank

improved by making it easy to create and enforce col-

ing sector as a share of GDP is a measure of bank-

capital to asset ratio is the ratio of bank capital and

lateral agreements and increasing information about

ing sector depth and financial sector development in

reserves to total assets. Capital and reserves include

potential borrowers’ creditworthiness. Lenders look at

terms of size. In a few countries governments may hold

funds contributed by owners, retained earnings, gen-

a borrower’s credit history and collateral. Where credit

international reserves as deposits in the banking sys-

eral and special reserves, provisions, and valuation

registries and effective collateral laws are absent—

tem rather than in the central bank. Since the claims

adjustments. • Ratio of bank nonperforming loans to

as in many developing countries—banks make fewer

on the central government are a net item (claims on

total gross loans is the value of nonperforming loans

loans. Indicators that cover getting credit include the

the central government minus central government

divided by the total value of the loan portfolio (including

strength of legal rights index and the depth of credit

deposits), this net figure may be negative, resulting

nonperforming loans before the deduction of loan loss

information index.

in a negative figure of domestic credit provided by the

provisions). The amount recorded as nonperforming

banking sector.

should be the gross value of the loan as recorded

The “unbanked” have to resort to informal services to manage their money—saving under the

The interest rate spread—the margin between

on the balance sheet, not just the amount overdue.

mattress, borrowing from family and friends, or

the cost of mobilizing liabilities and the earnings on

• Domestic credit provided by banking sector is all

money lenders—that are usually less reliable and

assets—is a measure of financial sector efficiency in

credit to various sectors on a gross basis, except to

more costly than formal banking institutions. The

intermediation. A narrow interest rate spread means

the central government, which is net. The banking

table presents data on financial access cover-

low transaction costs, which reduces the cost of funds

sector includes monetary authorities, deposit money

ing deposits and loans, and outreach indicators

for investment, crucial to economic growth.

banks, and other banking institutions for which data

The risk premium on lending is the spread between

are available. • Interest rate spread is the interest rate

the lending rate to the private sector and the “risk-

charged by banks on loans to prime customers minus

Data on financial access cover 142 coun-

free” government rate. Spreads are expressed as

the interest rate paid by commercial or similar banks

tries and present indicators on savings, credit,

annual averages. A small spread indicates that the

for demand, time, or savings deposits. • Risk premium

and payment services in banks and regulated

market considers its best corporate customers to be

on lending is the interest rate charged by banks on

nonbank financial institutions. Data were col-

low risk. A negative rate indicates that the market

loans to prime private sector customers minus the

lected for commercial banks and regulated

considers its best corporate clients to be lower risk

“risk-free” treasury bill interest rate at which short-

nonbank financial institutions such as cooperatives,

than the government.

term government securities are issued or traded in

such as the number of branches, automatic teller machines, and point-of-sale terminals.

credit unions, specialized state financial institutions, and microfinance institutions.

Definitions

the market.

The size and mobility of international capital flows

• Strength of legal rights index measures the degree

make it increasingly important to monitor the strength

to which collateral and bankruptcy laws protect the

of financial systems. Robust financial systems can

rights of borrowers and lenders and thus facilitate

increase economic activity and welfare, but instability

lending. Higher values indicate that the laws are bet-

in the financial system can disrupt financial activity and

ter designed to expand access to credit. • Depth of

impose widespread costs on the economy. The ratio

credit information index measures rules affecting

Data sources

of bank capital to assets, a measure of bank solvency

the scope, accessibility, and quality of information

Data on getting credit are from the World Bank’s

and resiliency, shows the extent to which banks can

available through public or private credit registries.

Doing Business project (www.doingbusiness.org).

deal with unexpected losses. Capital includes tier 1

Higher values indicate the availability of more credit

Data on financial access and outreach are from

capital (paid-up shares and common stock), a com-

information. • Deposit accounts are accounts at com-

the Consultative Group to Assist the Poor and the

mon feature in all countries’ banking systems, and

mercial banks that allow money to be deposited and

World Bank Group’s Financial Access 2010. Data

total regulatory capital, which includes several types of

withdrawn by the account holder. The major types of

on bank capital and nonperforming loans are from

subordinated debt instruments that need not be repaid

deposits are checking accounts, savings accounts,

the IMF’s Global Financial Stability Report. Data

if the funds are required to maintain minimum capital

and time deposits. • Loan accounts at commer-

on credit and interest rates are from the IMF’s

levels (tier 2 and tier 3 capital). Total assets include

cial banks include loans from banks to individuals,

International Financial Statistics.

businesses, and others, including home mortgages,

2011 World Development Indicators

285


5.6

Tax policies Tax revenue collected by central government

% of GDP

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

286

Taxes payable by businesses

Number of payments

Time to prepare, file, and pay taxes hours

Profit tax % of commercial profits

Labor tax and contributions % of commercial profits

Other taxes % of commercial profits

Total tax rate % of commercial profits

June 2010

June 2010

June 2010

June 2010

June 2010

2000

2009

June 2010

.. 16.1 .. .. 9.8a .. 23.0a 19.9a .. 7.6 16.6 27.4a 15.5a 13.2a .. .. 14.0 17.9 10.5a 13.6 8.2a 11.2 15.3a .. .. 16.7a 6.8 9.1a 11.0a 3.5 5.9 .. .. 22.4 .. 15.4 30.8 a .. .. 13.4 10.7a .. 15.8 a 8.1 24.7a 23.2a .. .. 7.7 11.9a 17.2 23.3a 10.1 11.1 .. .. ..

7.3 .. 34.3a .. .. 16.4 22.1a 18.7a 16.7 8.6 19.4 24.0a 16.1a 17.0a 19.6a .. 15.6 20.9 12.9a .. 9.6a .. 11.8a .. .. 15.3a 10.3 13.0a 11.9a .. .. 13.9a 16.4 a 19.1 .. 13.5 34.5a 14.9a .. 15.7 12.5a .. 17.6a .. 21.3a 19.6a .. .. 23.2 12.0a 12.5 19.1a 10.4 .. .. .. 14.4 a

8 44 34 31 9 50 11 22 18 21 82 11 55 42 51 19 10 17 46 32 39 44 8 54 54 9 7 3 20 32 61 42 64 17 .. 12 9 9 8 29 53 18 7 19 8 7 26 50 18 16 33 10 24 56 46 42 47

2011 World Development Indicators

275 360 451 282 453 581 109 170 306 302 798 156 270 1,080 422 152 2,600 616 270 211 173 654 131 504 732 316 398 80 208 336 606 272 270 196 .. 557 135 324 654 433 320 216 81 198 243 132 488 376 387 215 224 224 344 416 208 160 224

0.0 8.5 6.6 24.6 2.8 16.6 25.9 15.7 13.8 25.7 22.0 4.8 14.8 0.0 5.3 15.9 21.4 4.6 16.1 19.4 18.9 29.9 9.8 176.8 31.3 18.0 6.0 18.7 17.7 58.9 0.0 18.9 8.8 11.4 .. 7.4 21.9 20.5 18.4 13.2 17.0 8.8 8.0 26.8 15.9 8.2 18.4 41.4 13.3 23.0 18.1 13.9 25.9 19.4 14.9 23.3 26.7

0.0 27.3 29.7 9.0 29.4 23.0 20.7 34.6 24.8 0.0 39.3 50.4 27.3 15.5 12.6 0.0 40.9 20.4 22.6 7.8 0.1 18.3 12.6 8.1 28.4 3.8 49.6 5.3 33.9 7.9 32.9 29.5 20.1 19.4 .. 38.4 3.6 18.3 13.7 25.8 17.2 0.0 39.2 0.0 27.7 51.7 22.7 12.9 0.0 22.0 14.1 31.7 14.3 24.5 24.8 12.4 10.7

36.4 4.9 35.7 19.5 76.0 1.1 1.3 5.1 2.2 9.2 19.2 1.8 23.9 64.6 5.0 3.6 6.6 3.9 6.2 126.2 3.5 0.9 6.9 18.9 5.7 3.2 7.9 0.1 27.1 272.8 32.6 6.6 15.5 1.6 .. 3.0 3.7 1.8 3.2 3.6 0.8 75.8 2.4 4.3 1.0 5.9 2.3 238.0 2.0 3.3 0.5 1.6 0.7 10.8 6.1 4.3 10.9

36.4 40.6 72.0 53.2 108.2 40.7 47.9 55.5 40.9 35.0 80.4 57.0 66.0 80.0 23.0 19.5 69.0 29.0 44.9 153.4 22.5 49.1 29.2 203.8 65.4 25.0 63.5 24.1 78.7 339.7 65.5 55.0 44.4 32.5 .. 48.8 29.2 40.7 35.3 42.6 35.0 84.5 49.6 31.1 44.6 65.8 43.5 292.3 15.3 48.2 32.7 47.2 40.9 54.6 45.9 40.1 48.3


Tax revenue collected by central government

% of GDP

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

5.6

states and markets

Tax policies Taxes payable by businesses

Number of payments

Time to prepare, file, and pay taxes hours

Profit tax % of commercial profits

Labor tax and contributions % of commercial profits

Other taxes % of commercial profits

Total tax rate % of commercial profits

2000

2009

June 2010

June 2010

June 2010

June 2010

June 2010

June 2010

21.9a

23.5a

9.0 11.6 6.3 .. 26.0a 28.7a 23.2a .. .. 19.0 10.2 16.8 .. 15.4 .. 1.3 11.7 .. 14.2 11.9a 37.4 .. .. 14.6a .. 11.3a .. 13.7 13.2a .. .. 11.7 14.7 14.5 19.9a .. 3.0 27.5 8.7 22.3a 29.2a 13.8 .. .. 27.4 a 7.2 10.1 10.2 19.0 10.9 12.2 13.7 16.0a 20.6a .. ..

9.8 11.4 9.3 .. 20.8a 23.0a 23.0a 21.9a 9.2a 16.2 8.1 19.6 .. 15.5 21.1 0.9 15.4 12.5 12.6 17.3a 60.0 0.3 .. 13.8a 19.7 13.0a .. 15.7 14.7a .. 19.2a .. 17.8 18.0 23.8a .. .. 27.3 12.2 22.7a 30.8a 17.8 11.5a 0.3 25.4 a .. 9.3 .. .. 13.0 13.4 12.8 16.4 a 19.7a .. 19.8

14 56 51 20 13 9 33 15 72 14 26 9 41 .. 14 33 15 48 34 7 19 21 32 .. 11 40 23 19 12 59 38 7 6 48 43 28 37 .. 37 34 9 8 64 41 35 4 14 47 62 33 35 9 47 29 8 16 3

277 258 266 344 312 76 235 285 414 355 101 271 393 .. 250 163 118 202 362 293 180 324 158 .. 175 119 201 157 145 270 696 161 404 228 192 358 230 .. 375 338 134 192 222 270 938 87 62 560 482 194 311 380 195 325 298 218 36

16.7 24.0 26.6 17.8 14.9 11.9 23.8 22.8 28.6 27.9 15.2 16.3 33.1 .. 15.3 10.2 4.7 8.9 25.2 6.5 6.1 16.4 0.0 .. 0.0 6.3 15.8 23.3 16.7 12.9 44.2 11.8 23.1 0.0 9.5 18.1 27.7 .. 4.0 16.2 20.9 30.4 24.8 20.1 21.8 24.4 9.7 14.3 17.0 22.0 9.6 26.0 21.3 17.7 14.9 26.3 0.0

34.4 18.2 10.6 25.9 13.5 11.6 5.3 43.4 13.0 14.7 12.4 11.5 6.8 .. 12.9 5.6 10.7 21.5 5.6 27.2 24.1 0.0 5.4 .. 35.1 0.6 20.3 1.1 15.6 32.6 17.6 5.0 26.1 30.2 12.4 22.2 4.5 .. 1.0 11.3 17.9 3.0 19.2 19.6 9.7 15.9 11.8 15.0 22.6 11.7 18.6 11.0 10.3 22.1 26.8 14.4 11.3

2.2 21.1 0.1 0.4 0.0 3.0 2.6 2.4 8.5 6.0 3.6 1.9 9.9 .. 1.6 0.6 0.0 26.7 2.9 4.8 0.0 3.2 38.3 .. 3.6 3.8 1.6 0.7 1.4 6.7 6.6 7.3 1.3 0.7 1.0 1.4 2.1 .. 4.6 10.7 1.7 0.9 19.2 6.8 0.7 1.3 0.1 2.3 10.5 8.6 6.7 3.2 14.2 2.5 1.6 27.0 0.0

53.3 63.3 37.3 44.1 28.4 26.5 31.7 68.6 50.1 48.6 31.2 29.6 49.7 .. 29.8 16.5 15.5 57.2 33.7 38.5 30.2 19.6 43.7 .. 38.7 10.6 37.7 25.1 33.7 52.2 68.4 24.1 50.5 30.9 23.0 41.7 34.3 .. 9.6 38.2 40.5 34.3 63.2 46.5 32.2 41.6 21.6 31.6 50.1 42.3 35.0 40.2 45.8 42.3 43.3 67.7 11.3

2011 World Development Indicators

287


5.6

Tax policies Tax revenue collected by central government

% of GDP

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

2000

2009

11.7a 13.6a .. .. 16.1 .. 10.2 15.4 .. 20.6 .. 24.0a 16.2a 14.5 6.4 24.9 23.6a 11.1 .. 7.7 .. .. .. .. 22.1 21.3 .. .. 10.4 14.1 1.7 28.4a 12.5a 14.7 .. 13.3 .. .. 9.4 18.6 .. 15.5 w 10.4 10.9 8.2 .. 10.9 7.7 .. 13.0 12.0 9.3 .. 16.4 19.1

17.9a 12.9a .. .. .. 21.0 10.8 13.8 12.4 a 18.3 .. 25.4 a 8.5a 13.3 .. .. 21.5a 10.9 .. .. .. 15.1a .. 17.0a 31.6 21.9 18.9a .. 12.0 16.4 .. 26.0a 8.2a 18.8 .. .. .. .. .. 17.1 .. 14.2 w 11.6 14.1 11.3 15.8 14.0 11.1 15.0 .. 17.5 9.7 17.9 14.2 17.1

Taxes payable by businesses

Number of payments

Time to prepare, file, and pay taxes hours

Profit tax % of commercial profits

Labor tax and contributions % of commercial profits

Other taxes % of commercial profits

Total tax rate % of commercial profits

June 2010

June 2010

June 2010

June 2010

June 2010

June 2010

222 320 148 79 666 279 357 84 257 260 .. 200 197 256 180 104 122 63 336 224 172 264 276 270 210 144 223 .. 161 657 12 110 187 336 205 864 941 154 248 132 242 282 u 271 337 326 351 319 233 340 408 263 283 311 179 190

10.4 9.0 21.2 2.1 14.8 11.6 0.0 7.4 7.0 14.8 .. 24.4 20.9 27.4 13.8 28.1 16.4 8.9 23.2 17.7 19.9 28.9 0.0 8.8 21.6 15.0 17.0 .. 23.3 10.4 0.0 23.1 27.6 23.6 1.6 10.0 12.5 16.2 35.1 1.7 24.0 17.9 u 24.8 17.1 16.3 18.0 19.2 18.4 10.0 21.4 16.6 17.8 23.3 14.3 13.9

32.3 31.8 5.7 12.4 24.1 20.2 11.3 14.9 39.6 18.2 .. 2.5 35.0 16.9 19.2 4.0 36.6 17.5 19.3 28.5 18.0 5.7 0.0 28.3 5.8 25.2 23.1 .. 11.3 43.3 14.1 10.8 10.0 15.6 27.1 18.0 20.3 0.0 11.3 10.4 6.2 16.3 u 12.6 15.8 14.3 17.5 14.9 10.3 22.7 15.3 18.9 7.8 13.2 20.1 29.2

2.2 5.7 4.4 0.0 7.0 2.2 224.3 3.1 2.1 2.4 .. 3.7 0.7 20.3 3.1 4.7 1.6 3.6 0.5 39.9 7.3 2.8 0.2 13.7 5.8 22.5 4.4 .. 1.1 1.8 0.0 3.3 9.2 2.9 66.9 24.6 0.3 0.6 1.4 4.0 10.1 13.7 u 39.2 8.6 9.6 7.5 17.0 7.8 9.6 11.2 6.1 14.2 31.7 4.2 2.4

44.9 46.5 31.3 14.5 46.0 34.0 235.6 25.4 48.7 35.4 .. 30.5 56.5 64.7 36.1 36.8 54.6 30.1 42.9 86.0 45.2 37.4 0.2 50.8 33.1 62.8 44.5 .. 35.7 55.5 14.1 37.3 46.8 42.0 95.6 52.6 33.1 16.8 47.8 16.1 40.3 47.8 u 76.5 41.5 40.2 43.0 51.1 36.5 42.2 47.9 41.6 39.9 68.2 38.6 45.5

113 11 26 14 59 66 29 5 31 22 .. 9 8 62 42 33 2 19 20 54 48 23 6 53 40 8 15 .. 32 135 14 8 11 53 44 70 32 27 44 37 49 30 u 38 34 36 32 35 27 47 34 25 31 37 15 15

Note: Regional aggregates for Taxes payable by businesses are for developing countries only. a. Data were reported on a cash basis and have been adjusted to the accrual framework of the International Monetary Fund’s Government Finance Statistics Manual 2001.

288

2011 World Development Indicators


About the data

5.6

states and markets

Tax policies Definitions

Taxes are the main source of revenue for most

To make the data comparable across countries,

• Tax revenue collected by central government

governments. The sources of tax revenue and their

several assumptions are made about businesses.

is compulsory transfers to the central government

relative contributions are determined by government

The main assumptions are that they are limited liabil-

for public purposes. Certain compulsory transfers

policy choices about where and how to impose taxes

ity companies, they operate in the country’s most

such as fines, penalties, and most social security

and by changes in the structure of the economy. Tax

populous city, they are domestically owned, they per-

contributions are excluded. Refunds and corrections

policy may reflect concerns about distributional

form general industrial or commercial activities, and

of erroneously collected tax revenue are treated as

effects, economic efficiency (including corrections

they have certain levels of start-up capital, employ-

negative revenue. The analytic framework of the

for externalities), and the practical problems of

ees, and turnover. For details about the assump-

International Monetary Fund’s (IMF) Government

administering a tax system. There is no ideal level

tions, see the World Bank’s Doing Business 2011.

Finance Statistics Manual 2001 (GFSM 2001) is

of taxation. But taxes influence incentives and thus

The Doing Business methodology on business

based on accrual accounting and balance sheets.

the behavior of economic actors and the economy’s

taxes is consistent with the Total Tax Contribution

For countries still reporting government finance data

competitiveness.

framework developed by PricewaterhouseCoopers,

on a cash basis, the IMF adjusts reported data to the

The level of taxation is typically measured by tax

which measures the taxes that are borne by compa-

GFSM 2001 accrual framework. These countries are

revenue as a share of gross domestic product (GDP).

nies and affect their income statements. However,

footnoted in the table. • Number of tax payments

Comparing levels of taxation across countries pro-

PricewaterhouseCoopers bases its calculation on

by businesses is the total number of taxes paid by

vides a quick overview of the fiscal obligations and

data from the largest companies in the economy,

businesses during one year. When electronic filing is

incentives facing the private sector. The table shows

while Doing Business focuses on a standardized

available, the tax is counted as paid once a year even

only central government data, which may significantly

medium-sized company.

if payments are more frequent. • Time to prepare,

understate the total tax burden, particularly in coun-

file, and pay taxes is the time, in hours per year, it

tries where provincial and municipal governments are

takes to prepare, file, and pay (or withhold) three

large or have considerable tax authority.

major types of taxes: the corporate income tax, the

Low ratios of tax revenue to GDP may reflect weak

value-added or sales tax, and labor taxes, includ-

administration and large-scale tax avoidance or eva-

ing payroll taxes and social security contributions.

sion. Low ratios may also reflect a sizable parallel

• Profit tax is the amount of taxes on profits paid

economy with unrecorded and undisclosed incomes.

by the business. • Labor tax and contributions is

Tax revenue ratios tend to rise with income, with

the amount of taxes and mandatory contributions on

higher income countries relying on taxes to finance

labor paid by the business. • Other taxes includes

a much broader range of social services and social

the amounts paid for property taxes, turnover taxes,

security than lower income countries are able to.

and other small taxes such as municipal fees and

The total tax rate payable by businesses provides

vehicle and fuel taxes. • Total tax rate measures

a comprehensive measure of the cost of all the taxes

the amount of taxes and mandatory contributions

a business bears. It differs from the statutory tax

payable by the business in the second year of opera-

rate, which is the factor applied to the tax base. In

tion, expressed as a share of commercial profits.

computing business tax rates, actual tax payable is

Doing Business 2011 reports the total tax rate for

divided by commercial profit. The indicators cover-

fiscal 2009. Taxes withheld (such as sales or value

ing taxes payable by businesses measure all taxes

added tax or personal income tax) but not paid by

and contributions that are government mandated

the company are excluded. For further details on the

(at any level—federal, state, or local), apply to stan-

method used for assessing the total tax payable, see

dardized businesses, and have an impact in their

the World Bank’s Doing Business 2011.

income statements. The taxes covered go beyond the definition of a tax for government national accounts (compulsory, unrequited payments to general government) and also measure any imposts that affect business accounts. The main differences are in labor contributions and value-added taxes. The indicators account for government-mandated contributions paid

Data sources

by the employer to a requited private pension fund

Data on central government tax revenue are from

or workers insurance fund but exclude value-added

print and electronic editions of the IMF’s Govern-

taxes because they do not affect the accounting prof-

ment Finance Statistics Yearbook. Data on taxes

its of the business—that is, they are not reflected in

payable by businesses are from Doing Business

the income statement.

2011 (www.doingbusiness.org).

2011 World Development Indicators

289


5.7

Military expenditures and arms transfers Military expenditures

% of central government expenditure

% of GDP

Afghanistan Albania Algeria Angola Argentina Armenia Australia Austria Azerbaijan Bangladesh Belarus Belgium Benin Bolivia Bosnia and Herzegovina Botswana Brazil Bulgaria Burkina Faso Burundi Cambodia Cameroon Canada Central African Republic Chad Chile China Hong Kong SAR, China Colombia Congo, Dem. Rep. Congo, Rep. Costa Rica Côte d’Ivoire Croatia Cuba Czech Republic Denmark Dominican Republic Ecuador Egypt, Arab Rep. El Salvador Eritrea Estonia Ethiopia Finland France Gabon Gambia, The Georgia Germany Ghana Greece Guatemala Guinea Guinea-Bissau Haiti Honduras

290

Armed forces personnel

thousands

2000

2009

2000

2009

2000

2009

.. 1.2 3.4 6.4 1.1 3.6 1.9 1.0 2.3 1.4 1.3 1.4 0.6 1.9 3.6 3.3 1.8 2.7 1.2 6.0 2.2 1.3 1.1 1.0 1.9 3.7 1.8a .. 2.8 1.0 1.4 .. .. 3.1 .. 2.0 1.5 0.7 1.7 3.2 0.9 36.4 1.4 7.6 1.3 2.5 1.8 0.8 0.6 1.5 1.0 4.3 0.8 1.5 4.4 .. 0.5

1.8 2.1 3.8 4.2 0.8 4.0 1.9 0.9 3.5 1.1 1.8 1.1 1.0 1.6 1.5 3.1 1.6 2.3 1.3 3.8 1.2 1.5 1.4 1.8 6.4 3.1 2.0a .. 4.1 1.1 1.2 .. 1.6 1.8 3.2 1.5 1.4 0.6 3.3 2.1 0.6 .. 2.3 1.3 1.5 2.4 1.1 0.7 5.6 1.4 0.4 4.0 0.4 .. .. .. 0.8

.. 5.4 .. .. 5.5 .. 7.8 2.5 .. 14.9 5.3 3.2 4.7 7.6 .. .. 8.1 8.6 9.8 30.3 16.8 12.4 6.0 .. .. 17.7 19.8a .. 15.6 11.4 5.9 .. .. 7.8 .. 6.1 4.3 .. .. 12.3 4.3 .. 4.7 29.7 3.7 5.7 .. .. 5.3 4.7 3.3 9.8 7.5 11.8 .. .. ..

4.6 .. 15.0 .. .. 17.1 7.3 2.3 22.9 10.0 5.5 2.5 6.8 7.9 3.8 .. 6.4 7.2 10.4 .. 13.9 .. 7.5 .. .. 13.6 16.1a .. 20.9 .. .. .. 8.8 5.0 .. 4.1 3.3 3.8 .. 7.1 3.0 .. 6.2 .. 3.8 5.1 .. .. 18.1 4.3 2.4 7.9 3.5 .. .. .. 3.2

400 68 305 118 102 42 52 41 87 137 91 39 7 70 76 10 673 114 11 46 360 22 69 5 35 117 3,910 .. 247 93 15 15 15 101 85 63 22 40 58 679 29 200 8 353 35 389 7 1 33 221 8 163 53 19 9 5 14

256 15 334 117 104 56 57 26 82 221 183 39 7 83 11 11 713 65 11 51 191 23 66 3 35 104 2,945 .. 442 159 12 10 19 22 76 27 19 40 59 866 33 202 5 138 25 342 7 1 32 251 16 143 34 19 6 0 20

2011 World Development Indicators

Arms transfers

% of labor force 2000

5.4 5.2 2.7 1.9 0.6 2.9 0.5 1.0 2.5 0.2 1.9 0.9 0.3 2.0 4.1 1.3 0.8 3.2 0.2 1.4 6.1 0.4 0.4 0.3 1.1 1.9 0.5 .. 1.6 0.5 1.2 1.0 0.2 5.1 1.8 1.2 0.8 1.1 1.2 3.1 1.3 14.5 1.2 1.2 1.3 1.5 1.2 0.1 1.4 0.5 0.1 3.3 1.3 0.5 1.7 0.1 0.6

Trend indicator values 1990 $ millions Exports Imports

2009

2000

2009

2.7 1.0 2.3 1.4 0.5 3.4 0.5 0.6 2.0 0.3 3.7 0.8 0.2 1.8 0.5 1.1 0.7 1.8 0.2 1.1 2.4 0.3 0.3 0.2 0.8 1.4 0.4 .. 2.3 0.6 0.8 0.5 0.2 1.1 1.5 0.5 0.6 0.9 1.0 3.2 1.3 9.4 0.8 0.3 0.9 1.2 0.9 0.1 1.4 0.6 0.1 2.8 0.6 0.4 1.0 0.0 0.7

.. .. .. 2 2 .. 43 21 .. .. 295 24 .. .. 4 .. 26 2 .. .. 1 .. 110 .. .. 1 272 .. .. .. .. .. .. 2 .. 78 20 .. .. .. .. 0 .. .. 9 1,055 .. .. 54 1,603 .. 2 .. .. .. .. ..

.. .. .. .. .. .. 51 33 .. .. 292 217 .. .. .. .. 49 7 .. .. .. .. 177 .. .. 133 870 .. .. .. .. 0 .. .. .. 19 12 .. .. .. .. .. .. .. 40 1,851 .. .. .. 2,473 .. .. .. .. .. .. ..

2000

2009

33 .. 418 200 209 2 364 25 3 205 41 39 6 19 25 52 124 7 .. 1 .. 1 550 .. 15 179 2,015 .. 62 74 0 .. 33 70 .. 16 64 13 12 788 16 17 27 124 516 106 .. .. 6 135 1 710 1 19 .. .. ..

344 25 942 11 11 1 757 330 49 12 .. 84 2 5 .. 10 210 153 1 .. 4 1 80 .. 23 231 595 .. 250 .. 0 .. .. 3 .. 5 47 6 46 217 4 4 56 .. 70 149 21 .. 81 137 13 1,269 0 0 .. 1 0


Military expenditures

% of central government expenditure

% of GDP 2000

Hungary India Indonesia Iran, Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea, Dem. Rep. Korea, Rep. Kosovo Kuwait Kyrgyz Republic Lao PDR Latvia Lebanon Lesotho Liberia Libya Lithuania Macedonia, FYR Madagascar Malawi Malaysia Mali Mauritania Mauritius Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Papua New Guinea Paraguay Peru Philippines Poland Portugal Puerto Rico Qatar

1.7 3.1 1.0 3.8 .. 0.7 7.8 2.0 0.5 1.0 6.2 0.8 1.3 .. 2.6 .. 7.1 2.9 0.8 0.9 5.4 4.1 .. 3.2 1.7 1.9 1.2 0.7 1.6 2.4 3.5 0.2 0.6 0.4 2.2 2.3 1.3 2.3 2.4 1.0 1.6 1.2 0.8 1.1 0.8 1.7 10.6 4.0 1.0 0.9 1.1 2.0 1.1 1.8 1.9 .. 4.7

Armed forces personnel

2009

2000

1.3 2.7 0.9 2.7 6.3 0.6 6.9 1.7 0.6 1.0 5.5 1.2 1.9 .. 2.9 .. 3.2 3.6 0.4 2.6 4.1 2.8 0.8 1.2 1.7 2.1 1.1 1.2 2.0 2.0 3.8 0.2 0.5 0.5 1.4 3.3 0.9 .. 3.3 1.6 1.5 1.1 0.7 .. 0.9 1.5 8.7 3.0 .. 0.5 0.9 1.2 0.8 2.0 2.0 .. 2.2

4.1 19.5 5.8 22.5 .. 2.6 17.6 5.2 .. .. 23.1 5.7 7.8 .. 15.6 .. 24.9 18.0 .. 3.2 17.7 7.8 .. .. 6.5 .. 11.5 .. 9.9 20.7 .. .. 3.7 1.4 9.5 12.0 .. .. 8.3 .. 4.0 3.5 4.7 .. .. 5.3 40.4 23.4 4.6 2.9 6.4 10.9 6.2 5.4 5.1 .. ..

2009

2.9 16.6 5.6 12.2 .. 1.5 17.0 3.9 1.6 .. 19.3 6.9 8.7 .. 13.2 .. 7.5 21.4 3.6 7.5 14.0 3.1 .. .. 4.4 5.8 9.3 .. 8.9 13.4 .. .. .. 1.2 5.8 12.0 .. .. 10.7 .. 3.4 3.1 3.2 .. 10.8 4.1 .. 18.0 .. .. 5.2 6.7 4.6 5.7 4.6 .. 13.7

thousands 2000

2009

58 2,372 492 753 479 12 181 503 3 249 149 99 27 1,244 688 .. 20 14 129 9 77 2 15 77 17 24 29 6 116 15 21 2 208 13 16 241 6 429 9 90 57 9 16 11 107 27 48 900 12 4 35 193 149 239 91 .. 12

42 2,626 582 563 659 10 185 327 3 260 111 81 29 1,379 660 .. 23 20 129 6 79 2 2 76 25 8 22 5 134 12 21 2 332 8 17 246 11 513 15 158 43 10 12 11 162 26 47 921 12 3 25 192 166 121 91 .. 12

Arms transfers

% of labor force 2000

1.4 0.6 0.5 3.4 8.0 0.7 7.2 2.2 0.3 0.4 10.4 1.3 0.2 11.2 3.0 .. 1.8 0.7 5.2 0.8 6.5 0.2 1.3 4.2 1.0 2.8 0.4 0.1 1.2 0.5 2.0 0.3 0.5 0.7 1.4 2.4 0.1 1.7 1.5 0.9 0.7 0.5 0.9 0.3 0.3 1.1 5.4 2.2 0.9 0.2 1.5 1.7 0.5 1.4 1.7 .. 3.6

5.7

states and markets

Military expenditures and arms transfers

2009

1.0 0.6 0.5 1.9 8.6 0.5 6.0 1.3 0.2 0.4 5.7 0.9 0.2 11.2 2.7 .. 1.5 0.8 4.2 0.5 5.4 0.2 0.1 3.2 1.6 0.9 0.2 0.1 1.1 0.3 1.5 0.4 0.7 0.5 1.2 2.1 0.1 1.9 1.9 1.2 0.5 0.4 0.5 0.2 0.3 1.0 4.3 1.6 0.8 0.1 0.8 1.4 0.4 0.7 1.6 .. 1.2

Trend indicator values 1990 $ millions Exports Imports 2000

34 16 16 0 .. .. 354 189 .. .. .. 19 .. 13 8 .. 99 .. .. .. 45 .. .. 11 3 .. .. 1 8 .. .. .. .. 6 .. .. .. .. .. .. 280 1 .. .. .. 3 .. 3 .. .. .. 10 .. 45 .. .. 9

2009

6 22 .. 5 .. 4 760 588 .. .. 44 .. .. .. 163 .. .. 16 .. .. .. .. .. 12 .. .. .. .. .. .. .. .. .. 11 .. .. .. .. .. .. 608 .. .. .. .. 17 .. .. .. .. .. .. 4 93 40 .. ..

2000

2009

14 911 171 415 .. 0 357 37 5 431 130 147 9 18 1,262 .. 238 .. 7 3 4 6 8 145 5 11 .. .. 30 7 31 .. 227 .. .. 123 0 3 18 11 141 45 .. .. 38 263 120 158 0 .. 6 24 9 159 2 .. 11

2 2,116 452 91 365 1 158 112 2 391 195 49 35 5 1,172 .. 17 .. 7 0 47 .. .. 11 26 .. .. .. 1,494 7 .. .. 57 .. 12 49 .. 3 10 .. 243 48 .. 0 73 576 93 1,146 .. .. .. 33 4 94 431 .. 285

2011 World Development Indicators

291


5.7

Military expenditures and arms transfers Military expenditures

% of GDP

Romania Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Singapore Slovak Republic Slovenia Somalia South Africa Spain Sri Lanka Sudan Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Timor-Leste Togo Trinidad and Tobago Tunisia Turkey Turkmenistan Uganda Ukraine United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela, RB Vietnam West Bank and Gaza Yemen, Rep. Zambia Zimbabwe World Low income Middle income Lower middle income Upper middle income Low & middle income East Asia & Pacific Europe & Central Asia Latin America & Carib. Middle East & N. Africa South Asia Sub-Saharan Africa High income Euro area

Armed forces personnel

% of central government expenditure

thousands

2000

2009

2000

2009

2000

2.5 3.7 3.5 10.6 1.3 5.5 3.7 4.7 1.7 1.1 .. 1.6 1.2 5.0 4.7 1.6 2.0 1.1 5.3 1.2 1.3 1.4 .. .. .. 1.7 3.7 2.9 2.5 3.6 9.4 2.4 3.0 1.3 1.2 1.5 .. .. 5.0 1.8 5.2 2.3 w 2.2 2.1 2.2 2.0 2.1 1.7 3.4 1.4 3.5 3.1 2.0 2.3 1.8

1.4 4.3 1.4 11.0 1.6 2.2 2.3 4.3 1.5 1.8 .. 1.4 1.3 3.5 .. 2.1 1.3 0.8 4.2 .. 1.0 1.8 11.8 2.0 .. 1.4 2.8 .. 2.2 2.9 5.6 2.7 4.7 1.6 .. 1.3 2.2 .. 4.4 1.7 2.8 2.6 w 1.5 2.2 2.1 2.2 2.1 1.9 3.3 1.5 3.5 2.6 1.7 2.8 1.7

8.9 19.3 .. .. 10.4 .. 12.8 28.7 .. 2.9 .. 5.6 3.9 21.9 53.0 7.3 .. 4.2 .. 13.4 .. .. .. .. .. 6.2 .. .. 16.0 13.5 .. 6.6 15.6 5.0 .. 7.1 .. .. 23.9 10.3 .. 10.2 w .. 15.0 18.0 .. 15.0 18.7 .. 7.2 12.7 19.9 .. 10.1 4.8

4.4 14.0 .. .. .. 5.9 11.2 27.9 4.0 4.1 .. 4.4 4.1 18.5 .. .. .. 4.7 .. .. .. 9.1 .. 13.0 .. 4.6 10.1 .. 15.9 7.0 .. 5.8 17.8 5.3 .. .. .. .. .. 5.7 .. 10.0 w .. 12.2 14.3 9.8 12.2 14.6 12.0 .. 12.3 16.5 .. 9.9 4.2

283 1,427 76 217 15 136 4 169 41 14 50 72 242 204 120 3 88 28 425 7 35 417 .. 8 8 47 828 15 51 420 66 213 1,455 25 79 79 524 .. 136 23 62 29,353 s 4,040 18,924 12,446 6,478 22,965 7,794 3,871 2,084 3,379 4,114 1,724 6,388 1,869

2009

152 1,495 35 249 19 29 11 148 17 12 2 77 222 223 127 .. 22 26 403 16 28 420 1 9 4 48 613 22 47 215 51 178 1,564 25 87 115 495 56 138 17 51 27,924 s 3,845 18,350 12,108 6,242 22,195 6,978 3,227 2,439 3,591 4,404 1,554 5,729 1,569

Arms transfers

% of labor force 2000

2009

2.4 2.0 2.0 3.4 0.4 .. 0.2 8.2 1.6 1.4 1.7 0.5 1.3 2.6 1.1 0.8 2.0 0.7 8.6 0.4 0.2 1.2 .. 0.4 1.3 1.5 3.6 0.8 0.5 1.8 3.5 0.7 1.0 1.6 0.9 0.8 1.4 .. 3.2 0.6 1.2 1.1 w 1.3 1.0 0.8 1.6 1.0 0.8 2.1 0.9 3.8 0.8 0.7 1.2 1.3

1.6 2.0 0.7 2.9 0.3 .. 0.5 5.5 0.6 1.2 0.1 0.4 1.0 2.7 0.9 .. 0.4 0.6 5.8 0.6 0.1 1.1 0.3 0.3 0.6 1.2 2.4 0.9 0.3 0.9 1.8 0.6 1.0 1.5 0.7 0.9 1.1 5.9 2.2 0.3 1.0 0.9 w 1.0 0.8 0.7 1.4 0.8 0.6 1.7 0.9 3.1 0.7 0.5 1.0 1.0

Trend indicator values 1990 $ millions Exports Imports 2000

2009

3 3 3,985 4,469 .. .. .. .. .. .. .. .. .. .. 10 124 92 8 .. .. .. .. 18 154 46 925 .. .. .. .. .. .. 306 353 176 270 .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. .. 15 36 .. .. .. .. 288 214 3 .. 1,484 1,024 7,220 6,795 1 .. .. 90 .. 17 .. .. .. .. .. .. .. .. 3 .. .. s .. s .. .. .. .. 983 1,251 .. .. .. .. 389 870 4,667 4,830 .. .. .. .. 19 22 .. .. 13,136 16,637 3,319 6,779

2000

2009

23 56 .. 1 14 6 80 626 .. 3 .. .. 13 .. 622 1,729 2 1 1 6 1 .. 16 139 332 430 274 64 107 39 1 .. 210 46 14 31 19 175 .. 7 .. 0 90 34 .. .. .. .. 10 6 11 8 1,170 675 .. 47 6 1 .. .. 243 604 829 288 301 831 4 37 6 .. 108 172 5 44 .. 14 158 45 27 3 2 .. 18,088 s 22,223 s 572 329 8,353 10,467 5,109 5,682 3,244 4,785 8,925 10,889 2,339 2,644 .. 1,162 970 1,058 2,056 2,065 1,548 3,606 647 354 9,163 11,334 2,075 3,322

Note: For some countries data are partial or uncertain or based on rough estimates. See SIPRI (2010). a. Estimates differ from statistics of the government of China, which has published the following estimates: military expenditure as 1.2 percent of GDP in 2000 and 1.4 percent in 2008 and 7.6 percent of national government expenditure in 2000 and 6.7 percent in 2008 (see National Bureau of Statistics of China, www.stats.gov.cn).

292

2011 World Development Indicators


About the data

5.7

states and markets

Military expenditures and arms transfers Definitions

Although national defense is an important function of

always strictly comparable across countries. How-

• Military expenditures are SIPRI data derived from

government and security from external threats that

ever, SIPRI puts a high priority on ensuring that the data

the NATO definition, which includes all current and

contributes to economic development, high levels of

series for each country is comparable over time. More

capital expenditures on the armed forces, including

military expenditures for defense or civil conflicts bur-

information on SIPRI’s military expenditure project can

peacekeeping forces; defense ministries and other gov-

den the economy and may impede growth. Data on

be found at www.sipri.org/contents/milap/.

ernment agencies engaged in defense projects; para-

military expenditures as a share of gross domestic

Data on armed forces refer to military personnel on

military forces, if judged to be trained and equipped

product (GDP) are a rough indicator of the portion of

active duty, including paramilitary forces. Because

for military operations; and military space activities.

national resources used for military activities and of

data exclude personnel not on active duty, they

Such expenditures include military and civil person-

the burden on the national economy. As an “input”

underestimate the share of the labor force working

nel, including retirement pensions and social services

measure military expenditures are not directly related

for the defense establishment. Governments rarely

for military personnel; operation and maintenance;

to the “output” of military activities, capabilities, or

report the size of their armed forces, so such data

procurement; military research and development;

security. Comparisons of military spending between

typically come from intelligence sources.

and military aid (in the military expenditures of the

countries should take into account the many fac-

SIPRI’s Arms Transfers Programme collects data

donor country). Excluded are civil defense and current

tors that influence perceptions of vulnerability and

on arms transfers from open sources. Since publicly

expenditures for previous military activities, such as

risk, including historical and cultural traditions, the

available information is inadequate for tracking all

for veterans benefits, demobilization, and weapons

length of borders that need defending, the quality of

weapons and other military equipment, SIPRI covers

conversion and destruction. This definition cannot be

relations with neighbors, and the role of the armed

only what it terms major conventional weapons. Data

applied for all countries, however, since that would

forces in the body politic.

cover the supply of weapons through sales, aid, gifts,

require more detailed information than is available

Data on military spending reported by governments

and manufacturing licenses; therefore the term arms

about military budgets and off-budget military expen-

are not compiled using standard definitions. They

transfers rather than arms trade is used. SIPRI data

ditures (for example, whether military budgets cover

are often incomplete and unreliable. Even in coun-

also cover weapons supplied to or from rebel forces

civil defense, reserves and auxiliary forces, police and

tries where the parliament vigilantly reviews bud-

in an armed conflict as well as arms deliveries for

paramilitary forces, and military pensions). • Armed

gets and spending, military expenditures and arms

which neither the supplier nor the recipient can be

forces personnel are active duty military personnel,

transfers rarely receive close scrutiny or full, public

identified with acceptable certainty; these data are

including paramilitary forces if the training, organiza-

disclosure (see Ball 1984 and Happe and Wakeman-

available in SIPRI’s database.

tion, equipment, and control suggest they may be used

Linn 1994). Therefore, the Stockholm International

SIPRI’s estimates of arms transfers are designed

to support or replace regular military forces. Reserve

Peace Research Institute (SIPRI) has adopted a defi-

as a trend-measuring device in which similar weap-

forces, which are not fully staffed or operational in

nition of military expenditure derived from the North

ons have similar values, reflecting both the quantity

peace time, are not included. The data also exclude

Atlantic Treaty Organization (NATO) definition (see

and quality of weapons transferred. SIPRI cautions

civilians in the defense establishment and so are not

Definitions). The data on military expenditures as a

that the estimated values do not reflect financial

consistent with the data on military expenditures on

share of GDP and as a share of central government

value (payments for weapons transferred) because

personnel. • Arms transfers cover the supply of military

expenditure are estimated by SIPRI. Central govern-

reliable data on the value of the transfer are not avail-

weapons through sales, aid, gifts, and manufacturing

ment expenditures are from the International Mon-

able, and even when values are known, the transfer

licenses. Weapons must be transferred voluntarily by

etary Fund (IMF). Therefore the data in the table may

usually includes more than the actual conventional

the supplier, have a military purpose, and be destined

differ from comparable data published by national

weapons, such as spares, support systems, and

for the armed forces, paramilitary forces, or intelligence

governments.

training, and details of the financial arrangements

agencies of another country. The trends shown in the

(such as credit and loan conditions and discounts)

table are based on actual deliveries only. Data cover

are usually not known.

major conventional weapons such as aircraft, armored

SIPRI’s primary source of military expenditure data is official data provided by national governments. These data are derived from national budget docu-

Given these measurement issues, SIPRI’s method

vehicles, artillery, radar systems and other sensors,

ments, defense white papers, and other public docu-

of estimating the transfer of military resources

missiles, and ships designed for military use, as well as

ments from official government agencies, including

includes an evaluation of the technical parameters

some major components such as turrets for armored

governments’ responses to questionnaires sent by

of the weapons. Weapons for which a price is not

vehicles and engines. Excluded are transfers of other

SIPRI, the United Nations, or the Organization for

known are compared with the same weapons for

military equipment such as most small arms and light

Security and Co-operation in Europe. Secondary

which actual acquisition prices are available (core

weapons, trucks, small artillery, ammunition, support

sources include international statistics, such as

weapons) or for the closest match. These weapons

equipment, technology transfers, and other services.

those of NATO and the IMF’s Government Finance

are assigned a value in an index that reflects their

Statistics Yearbook. Other secondary sources include

military resource value in relation to the core weap-

country reports of the Economist Intelligence Unit,

ons. These matches are based on such characteris-

Data on military expenditures are from SIPRI’s Year-

country reports by IMF staff, and specialist journals

tics as size, performance, and type of electronics,

book 2010: Armaments, Disarmament, and Interna-

and newspapers.

and adjustments are made for secondhand weap-

tional Security. Data on armed forces personnel are

In the many cases where SIPRI cannot make inde-

ons. More information on SIPRI’s Arms Transfers

from the International Institute for Strategic Stud-

pendent estimates, it uses the national data pro-

Programme is available at www.sipri.org/research/

ies’ The Military Balance 2011. Data on arms trans-

vided. Because of the differences in definitions and

armaments/transfers.

fers are from SIPRI’s Arms Transfers Programme

the difficulty in verifying the accuracy and complete-

Data sources

(www.sipri.org/research/armaments/transfers).

ness of data, data on military expenditures are not

2011 World Development Indicators

293


5.8

Fragile situations International Development Association Resource Allocation Index

Peacebuilding and peacekeeping

Operation namea

1–6 (low to high)

December 2010

2009

Afghanistan Angola Bosnia and Herzegovina Burundi Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d’Ivoire Eritrea Georgia Guinea Guinea-Bissau Haiti Iraq Kiribati Kosovo Liberia Myanmar Nepal São Tomé and Príncipe Sierra Leone Solomon Islands Somalia Sudan Tajikistan Timor-Leste Togo West Bank and Gaza Western Saharaj Yemen, Rep. Zimbabwe Fragile situations Low income

2.8 2.8 3.7 3.1 2.6 2.5 2.5 2.7 2.8 2.8 2.2 4.4 2.8 2.6 2.9 .. 3.1 3.4 2.8 .. 3.3 2.9 3.2 2.8 .. 2.5 3.2 2.9 2.8 .. .. 3.2 1.9    

UNAMA     BINUB MINURCATe MINURCAT   MONUC   UNOCI         MINUSTAH UNAMI   UNMIK UNMIL   UNMIN     RAMSI   UNMISg   UNMIT     MINURSO        

Battlerelated deaths

Troops, police, and military observers number December 2010

16 .. .. 4 3 .. .. 19,105 .. 9,071 .. .. .. .. 11,984 235 .. 16 9,392 .. 72 .. .. 580 .. 10,416 .. 1,517 .. .. 242 .. ..    

number

Intentional homicides per 100,000 people Law enforcement Public and criminal health justice sources sources

Military expenditures

% of GDP

2000–08b

2004

2004–08c

2009

26,589 3,534 0 4,937 350 4,328 0 75,118 116 1,265 57 648 1,174 0 244 124,002 0 0 2,487 2,833 11,520 0 212 0 3,983 12,363 0 0 0 0 .. 0 0 275,761 s 146,844

3.4 38.6 1.9 37.4 29.8 19.2 11.9 35.0 19.9 50.8 16.1 3.7 16.9 17.6 21.8 7.3 6.6 .. 17.4 15.6 13.6 5.3 37.2 1.5 3.2 27.2 1.9h 12.5 14.3 .. .. 2.5 34.3 21.1 w 17.6

.. 5.0 1.9 .. .. .. .. .. .. 0.4 .. 7.6 0.4 .. .. .. .. .. .. .. 2.2 .. 2.6 .. .. .. 2.3 .. .. 3.9 .. 4.0 8.7 .. ..

1.8 4.2 1.5 3.8 1.8 6.4 .. 1.1 1.2 1.6 .. 5.6 .. .. 0.0 6.3 .. .. 0.8 .. 1.6 .. 2.3 .. .. .. .. 11.8 2.0 .. .. 4.4 2.8 3.2 w 1.4

Business environment

Survey year

2008 2006 2009 2006   2009   2010 2009 2009 2009 2008 2006 2006       2009 2009   2009   2009       2008 2009 2009 2006 2010      

Losses due to theft, robbery, vandalism, and arson

Firms formally registered when operations started

% of sales

% of firms

1.5 0.4 0.2 1.1 .. 2.5 .. 1.8 3.3 3.4 0.0 0.7 2.0 1.1 .. .. .. 0.3 2.8 .. 0.9 .. 0.8 .. .. .. 0.3 1.5 2.4 1.2 .. 0.6 ..    

88.0 .. 98.6 .. .. 77.1 .. 61.9 84.3 56.4 100.0 99.6 .. .. .. .. .. 89.2 73.8 .. 94.0 .. 89.2 .. .. .. 92.7 91.8 75.8 .. .. 81.7 ..    

Note: The countries with fragile situations in the table are primarily International Development Association–eligible countries and nonmember or inactive countries and territories with a 3.2 or lower harmonized average of the World Bank's Country Policy and Institutional Assessment rating and the corresponding rating by a regional development bank, or that have had a UN or regional peacebuilding and political mission (for example, by the African Union, European Union, or Organization of American States) or peacekeeping mission (for example, by the African Union, European Union, North Atlantic Treaty Organization, or Organization of American States) during the last three years. This definition is pursuant to an agreement between the World Bank and other multilateral development banks at the start of the International Development Association 15 round in 2007. The list of countries and territories with fragile situations is an interim one, and the World Bank will continue to improve and refine its understanding of fragility. a. UNAMA is United Nations Assistance Mission in Afghanistan, BINUB is Bureau Intégré des Nations Unies au Burundi (United Nations Integrated Office in Burundi), MINURCAT is United Nations Mission in the Central African Republic and Chad, MONUC is United Nations Organization Mission in DR Congo, UNOCI is United Nations Operation in Côte d'Ivoire, MINUSTAH is United Nations Stabilization Mission in Haiti, UNAMI is United Nations Assistance Mission for Iraq, UNMIK is Interim Administration Mission in Kosovo, UNMIL is United Nations Mission in Liberia, UNMIN is United Nations Mission in Nepal, RAMSI is Regional Assistance Mission to Solomon Islands, UNMIS is United Nations Missions in Sudan, UNMIT is United Nations Integrated Mission in Timor-Leste, and MINURSO is United Nations Mission for the Referendum in Western Sahara. b. Total over the period. c. Data are for the most recent year available. d. Average over the period. e. Includes peacekeepers in Chad. The mission ended in 2010. f. The Internal Displacement Monitoring Centre's (IDMC) high estimate; the low estimate is 50,000. g. Does not include 22,444 troops, police, and military observers from the African Union–UN Hybrid Operation in Darfur. h. Data are for 2005. i. Includes Palestinian refugees under the mandate of the United Nations Relief and Works Agency for Palestine Refugees in the Near East, who are not included in data from the UN High Commissioner for Refugees. j. The designation Western Sahara is used instead of Former Spanish Sahara (the designation used on the maps on the front and back cover flaps) because it is the designation used by the UN operation established there by Security Council resolution 690/1991. Neither designation expresses any World Bank view on the status of the territory so-identified. k. IDMC's high estimate; the low estimate is 570,000.

294

2011 World Development Indicators


Children in employment

Refugees

Internally displaced persons

Access to an improved water source

Access to improved sanitation facilities

Maternal mortality ratio

Under-five Depth of mortality hunger rate

per 100,000 live births

Survey year

Afghanistan Angola Bosnia and Herzegovina Burundi Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d’Ivoire Eritrea Georgia Guinea Guinea-Bissau Haiti Iraq Kiribati Kosovo Liberia Myanmar Nepal São Tomé and Príncipe Sierra Leone Solomon Islands Somalia Sudan Tajikistan Timor-Leste Togo West Bank and Gaza Western Saharaj Yemen, Rep. Zimbabwe Fragile situations Low income

% of children ages 7–14

  .. 2001 30.1 2006 10.6 2005 11.7 2000 67.0 2004 60.4   .. 2000 39.8 2005 30.1 2006 45.7   .. 2006 31.8 1994 48.3 2006 50.5 2005 33.4 2006 14.7   ..   .. 2007 37.4   .. 1999 47.2   .. 2007 14.9   .. 2006 43.5 2000 19.1 2005 8.9   .. 2006 38.7   ..   .. 2006 18.3 1999 14.3    

By country of origin

By country of asylum

number

2009

2009

2009

2,887,123 141,021 70,018 94,239 159,554 55,014 268 455,852 20,544 23,153 209,168 15,020 10,920 1,109 24,116 1,785,212 33 .. 71,599 406,669 5,108 33 15,417 66 678,309 368,195 562 7 18,378 95,201 .. 1,934 22,449 7,636,291 s 5,427,548

37 14,734 7,132 24,967 27,047 338,495 .. 185,809 111,411 24,604 4,751 870 15,325 7,898 3 35,218 .. .. 6,952 .. 108,461 .. 9,051 .. 1,815 186,292 2,679 1 8,531 1,885,188i .. 170,854 3,995 3,182,120 s 1,893,823

% of % of population population

297,000 20,000 114,000 100,000 162,000 168,000 .. 1,900,000 7,800 621,000 10,000 230,000 .. .. .. 2,764,000 .. 19,700 .. 470,000 70,000 f .. .. .. 1,500,000 4,900,000 .. 400 1,500 .. 160,000 175,000 1,000,000k 14,047,900 s ..

2008

48 50 99 72 67 50 95 46 71 80 61 98 71 61 63 79 61 .. 68 71 88 89 49 69 30 57 70 69 60 91 .. 62 82 64 w 64

2008

National estimates

Modeled estimates

per 1,000

2004–09c

2008

2009

37 57 95 46 34 9 36 23 30 23 14 95 19 21 17 73 31 .. 17 81 31 26 13 29 23 34 94 50 12 89 .. 52 44 43 w 35

.. .. 3 615 543 1,099 .. 549 781 543 .. 14 980 405 630 84 .. .. 994 316 281 148 857 .. 1,044 1,107 38 .. .. .. .. .. 555 .. ..

1,400 610 9 970 850 1,200 340 670 580 470 280 48 680 1,000 300 75 .. .. 990 240 380 .. 970 100 1,200 750 64 370 350 .. .. 210 790 640 w 580

states and markets

5.8

Fragile situations

Primary gross enrollment ratio

kilocalories per person % of relevant age group per day

199 161 14 166 171 209 104 199 128 119 55 29 142 193 87 44 46 .. 112 71 48 78 192 36 180 108 61 56 98 30 .. 66 90 132 w 118

2005–07d

.. 320 140 380 300 310 300 410 230 230 350 150 260 250 430 .. 180 .. 340 230 220 160 340 180 .. 240 240 260 280 190 .. 270 300 290 w 285

2009

104 128 109 147 89 90 119 90 120 74 48 108 90 120 .. 103 116 .. 91 116 .. 131 158 107 33 74 102 113 115 79 .. 85 .. 94 w 104

About the data The table focuses on countries with fragile situations

According to the Geneva Declaration on Armed Vio-

have to build their own institutions tailored to their

and highlights the links among weak institutions,

lence and Development, more than 740,000 people

own needs. Peacekeeping operations in post-conflict

poor development outcomes, fragility, and risk of

die each year because of the violence associated with

situations have been effective in reducing the risks

conflict. These countries and territories often have

armed conflict and large- and small-scale criminality.

of reversion to conflict.

weak institutions that are ill-equipped to handle eco-

Recovery and rebuilding can take years, and the chal-

The countries with fragile situations in the table

nomic shocks, natural disasters, and illegal trade

lenges are numerous: infrastructure to be rebuilt,

are primarily International Development Association–

or to resist conflict, which increasingly spills across

persistently high crime, widespread health problems,

eligible countries and nonmember or inactive coun-

borders. Organized violence, including violent crime,

education systems in disrepair, and landmines to be

tries or territories of the World Bank with a 3.2 or

interrupts economic and social development through

cleared. Most countries emerging from conflict lack

lower harmonized average of the World Bank’s Country

lost human and social capital, disrupted services,

the capacity to rebuild the economy. Thus, capacity

Policy and Institutional Assessment rating and the cor-

displaced populations and reduced confidence for

building is one of the first tasks for restoring growth

responding rating by a regional development bank or

future investment. As a result, countries with fragile

and is linked to building peace and creating the con-

that have had a UN or regional peacebuilding mission

situations achieve lower development outcomes and

ditions that lead to sustained poverty reduction. The

(for example, by the African Union, European Union,

make slower progress toward the Millennium Develop-

World Bank and other international development agen-

or Organization of American States) or peacekeeping

ment Goals.

cies can help, but countries with fragile situations

mission (for example, by the African Union, European

2011 World Development Indicators

295


5.8

Fragile situations

About the data (continued) Union, North Atlantic Treaty Organization (NATO), or

fewer types of contracts and investments, constrain-

• Troops, police, and military observers in peace-

Organization of American States) during the last three

ing growth. The table presents data on the loss of

building and peacekeeping refer to people active in

years. Peacebuilding and peacekeeping involve many

sales due to theft, robbery, vandalism, and arson and

peacebuilding and peacekeeping as part of an official

elements—military, police, and civilian—working

on the percentage of firms operating informally. For

operation. Peacekeepers deploy to war-torn regions

together to lay the foundations for sustainable peace.

further information on enterprise surveys, see About

where no one else is willing or able to go to prevent

The list of countries and territories with fragile situa-

the data for table 5.2.

conflict from returning or escalating. • Battle-related

As the table shows, the human toll of armed vio-

deaths are deaths of members of warring parties in

lence across various contexts is severe. Additionally,

battle-related conflicts. Typically, battle-related

An armed conflict is a contested incompatibility

in countries with fragile situations weak institutional

deaths occur in warfare involving the armed forces

that concerns a government or territory where the

capacity often results in poor performance and fail-

of the warring parties (battlefield fighting, guerrilla

use of armed force between two parties (one of them

ure to meet expectations of effective service deliv-

activities, and all kinds of bombardments of military

the government) results in at least 25 battle-related

ery. Failure to deliver water, health, and education

units, cities, and villages). The targets are usually

deaths in a calendar year. There were 35 active

services can weaken struggling governments. The

the military and its installations or state institutions

armed conflicts in 26 locations in 2009. Separate

table includes several indicators related to living con-

and state representatives, but there is often sub-

measures are presented for intentional homicides—

ditions in fragile situations: children in employment,

stantial collateral damage of civilians killed in cross-

unlawful deaths purposefully inflicted on a person

refugees, internally displaced persons, access to

fire, indiscriminate bombings, and other military

by another person—which exclude deaths arising

water and sanitation, maternal and under-five mortal-

activities. All deaths—civilian as well as military—

from armed conflict. One measure draws from inter-

ity, depth of hunger, and primary school enrollment.

incurred in such situations are counted as bat-

national public health data sources, while the other

For more detailed information on these indicators,

tlerelated deaths. • Intentional homicides are esti-

draws from estimates by the United Nations Office on

see About the data for table 2.6 (children in employ-

mates of unlawful homicides purposely inflicted as

Drugs and Crime, which obtains data from national

ment), table 6.18 (refugees), table 2.18 (access to

a result of domestic disputes, interpersonal violence,

and international law enforcement and criminal jus-

improved water and sanitation), table 2.19 (maternal

violent conflicts over land resources, intergang vio-

tice sources. Data from these two sources measure

mortality), table 2.22 (under-five mortality), and table

lence over turf or control, and predatory violence and

different phenomena and are therefore unlikely to

2.12 (primary school enrollment).

killing by armed groups. Intentional homicide does

tions is an interim one, and the World Bank will continue to improve and refine its understanding of fragility.

provide identical numbers. Data on military expenditures reported by governments are not compiled using standard definitions

not include all intentional killing; the difference is Definitions

usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas

and are often incomplete and unreliable. Even in

• International Development Association Resource

killing in armed conflict is usually committed by fairly

countries where the parliament vigilantly reviews

Allocation Index is from the Country Policy and Insti-

cohesive groups of up to several hundred members

budgets and spending, military expenditures and

tutional Assessment rating, which is the average

and is thus usually excluded. Data are from interna-

arms transfers rarely receive close scrutiny or full

score of four clusters of indicators designed to mea-

tional public health organizations such as the World

public disclosure. Data are from the Stockholm

sure macroeconomic, governance, social, and struc-

Health Organization (WHO) and the Pan American

International Peace Research Institute (SIPRI), which

tural dimensions of development: economic manage-

Health Organization and from the United Nations

uses NATO’s pre-2004 definition of military expen-

ment, structural policies, policies for social inclusion

Survey of Crime Trends and Operations of Criminal

diture (see Definitions). Therefore, the data in the

and equity, and public sector management and insti-

Justice Systems (CTS), which draws from national

table may differ from comparable data published by

tutions (see table 5.9). Countries are rated on a

and international law enforcement and criminal jus-

national governments. For a more detailed discus-

scale of 1 (low) to 6 (high). • Peacebuilding and

tice sources. • Military expenditures are SIPRI data

sion of military expenditures, see About the data for

peacekeeping refer to operations that engage in

derived from NATO's pre-2004 definition, which

table 5.7.

peacebuilding (reducing the risk of lapsing or relaps-

includes all current and capital expenditures on the

Along with public sector efforts, private sector

ing into conflict by strengthening national capacities

armed forces, including peacekeeping forces;

development and investment, especially in competi-

for conflict management and laying the foundation

defense ministries and other government agencies

tive markets, has tremendous potential to contribute

for sustainable peace and development) or peace-

engaged in defense projects; paramilitary forces, if

to growth and poverty reduction. The World Bank’s

keeping (providing essential security to preserve the

judged to be trained and equipped for military opera-

Enterprise Surveys review the business environment,

peace where fighting has been halted and to assist

tions; and military space activities. Such expendi-

assessing constraints to private sector growth and

in implementing agreements achieved by the peace-

tures include military and civil personnel, including

enterprise performance. In some countries doing

makers). UN peacekeeping operations are authorized

retirement pensions and social services for military

business requires informal payments to “get things

by the UN Secretary-General and planned, managed,

personnel; operation and maintenance; procure-

done” in customs, taxes, licenses, regulations, ser-

directed, and supported by the United Nations

ment; military research and development; and mili-

vices, and the like. Crime, theft, and disorder also

Department of Peacekeeping Operations and the

tary aid (in the military expenditures of the donor

impose costs on businesses and society. And in

Department of Field Support. The UN Charter gives

country). Excluded are civil defense and current

many developing countries informal businesses oper-

the Security Council primary responsibility for main-

expenditures for previous military activities, such as

ate without licenses. These firms have less access

taining international peace and security, including

for veterans benefits, demobilization, and weapons

to financial and public services and can engage in

the establishment of a UN peacekeeping operation.

conversion and destruction. This definition cannot

296

2011 World Development Indicators


5.8

states and markets

Fragile situations be applied to all countries, however, since the neces-

disposal facilities that can effectively prevent

on intentional homicides are from the UN Office

sary detailed information is missing in some cases

human, animal, and insect contact with excreta.

on Drugs and Crime’s International Homicide Sta-

for military budgets and off-budget military expendi-

Improved facilities range from protected pit latrines

tistics database. Data on military expenditures are

tures (for example, whether military budgets cover

to flush toilets. • Maternal mortality ratio is the

from SIPRI’s Yearbook 2010: Armaments, Disar-

civil defense, reserves and auxiliary forces, police

number of women who die from pregnancy-related

mament, and International Security and database

and paramilitary forces, and military pensions).

causes during pregnancy and childbirth per 100,000

(www.sipri.org/databases/milex). Data on the

• Survey year is the year in which the underlying

live births. National estimates are based on national

business environment are from the World Bank’s

data were collected. • Losses due to theft, robbery,

surveys, vital registration records, and surveillance

Enterprise Surveys (www.enterprisesurveys.

vandalism, and arson are the estimated losses from

data or are derived from community and hospital

org). Data on children in employment are esti-

those causes that occurred on business establish-

records. Modeled estimates are based on an exer-

mates produced by the Understanding Children’s

ment premises calculated as a percentage of annual

cise by the WHO, United Nations Children’s Fund

Work project based on household survey data

sales. • Firms formally registered when operations

(UNICEF), United Nations Population Fund (UNFPA),

sets made available by the International Labour

started are the percentage of firms formally regis-

and the World Bank. See About the data for table

Organization’s International Programme on the

tered when they started operations in the country.

2.19 for further details. • Under-five mortality rate

Elimination of Child Labour under its Statistical

• Children in employment are children involved in

is the probability per 1,000 that a newborn baby will

Monitoring Programme on Child Labour, UNICEF

any economic activity for at least one hour in the

die before reaching age 5, if subject to current age-

under its Multiple Indicator Cluster Survey pro-

reference week of the survey. • Refugees are people

specific mortality rates. • Depth of hunger, or the

gram, the World Bank under its Living Standards

who are recognized as refugees under the 1951 Con-

intensity of food deprivation, indicates how much

Measurement Study program, and national sta-

vention Relating to the Status of Refugees or its

people who are food-deprived fall short of minimum

tistical offices (see table 2.6). Data on refugees

1967 Protocol, the 1969 Organization of African

food needs in terms of dietary energy. It is measured

are from the UNHCR’s Statistical Yearbook 2009,

Unity Convention Governing the Specific Aspects of

by comparing the average amount of dietary energy

complemented by statistics on Palestinian refu-

Refugee Problems in Africa, people recognized as

that undernourished people get from the foods they

gees under the mandate of the United Nations

refugees in accordance with the UN Refugee Agency

eat with the minimum amount of dietary energy they

Relief and Works Agency for Palestine Refugees

(UNHCR) statute, people granted refugee-like human-

need to maintain body weight and undertake light

in the Near East as published on its website (www.

itarian status, and people provided temporary protec-

activity. Depth of hunger is low when it is less than

unrwa.org). Data on internally displaced persons

tion. Asylum seekers—people who have applied for

200 kilocalories per person per day and high when

are from the Internal Displacement Monitoring

asylum or refugee status and who have not yet

it is above 300. • Primary gross enrollment ratio is

Centre. Data on access to water and sanitation

received a decision, or who are registered as asylum

the ratio of total enrollment, regardless of age, to the

are from the WHO and UNICEF’s Progress on Sani-

seekers—are excluded. Palestinian refugees are

population of the age group that officially corre-

tation and Drinking Water (2010). National esti-

people (and their descendants) whose residence was

sponds to the primary level of education. Primary

mates of maternal mortality are from UNICEF’s The

Palestine between June 1946 and May 1948 and

education provides children with basic reading, writ-

State of the World’s Children 2009 and Childinfo

who lost their homes and means of livelihood as a

ing, and mathematics skills along with an elementary

and Demographic and Health Surveys by Macro

result of the 1948 Arab-Israeli conflict. • Country of

understanding of such subjects as history, geogra-

International. Modeled estimates for maternal

origin refers to the nationality or country of citizen-

phy, natural science, social science, art, and music.

mortality are from WHO, UNICEF, UNFPA, and

ship of a claimant. • Country of asylum is the country

the World Bank’s Trends in Maternal Mortality in

where an asylum claim was filed and granted. • Inter-

1990–2008 (2010). Data on under-five mortal-

nally displaced persons are people or groups of people who have been forced or obliged to flee or to

Data sources

ity estimates by the Inter-agency Group for Child Mortality Estimation (which comprises UNICEF,

leave their homes or places of habitual residence, in

Data on the International Development Asso-

WHO, the World Bank, United Nations Population

particular as a result of armed conflict, or to avoid

ciation Resource Allocation Index are from

Division, and other universities and research insti-

the effects of armed conflict, situations of general-

the World Bank Group’s International Develop-

tutes) and are based mainly on household surveys,

ized violence, violations of human rights, or natural

ment Association database (www.worldbank.

censuses, and vital registration data, supple-

or human-made disasters and who have not crossed

org/ida). Data on peacebuilding and peace-

mented by the World Bank’s Human Development

an international border. • Access to an improved

keeping operations are from the UN Depart-

Network estimates based on vital registration and

water source refers to people with reasonable

ment of Peacekeeping Operations. Data on

sample registration data (see table 2.22). Data on

access to water from an improved source, such as

battle-related deaths are primarily from the

depth of hunger are from the Food and Agriculture

piped water into a dwelling, public tap, tubewell, pro-

Peace Research Institute Oslo/Uppsala Conflict

Organization’sFood Security Statistics (www.fao.

tected dug well, and rainwater collection. Reasonable

Data Program (UCDP) Armed Conflict Dataset (v.4-

org/economic/ess/food-security-statistics/en/).

access is the availability of at least 20 liters a person

2010) 1946-2009 (www.pcr.uu.se/research/ucdp/

Data on primary gross enrollment are from the

a day from a source within 1 kilometer of the dwell-

datasets), supplemented with data from the UCDP

United Nations Educational, Scientific, and Cul-

ing. • Access to improved sanitation facilities refers

Battle-Related Deaths Dataset (v.5-2010). Data

tural Organization’s Institute for Statistics.

to people with at least adequate access to excreta

2011 World Development Indicators

297


5.9

Public policies and institutions International Development Association Resource Allocation Index 1–6 (low to high)

Afghanistan Angola Armenia Azerbaijan Bangladesh Benin Bhutan Bolivia Bosnia and Herzegovina Burkina Faso Burundi Cambodia Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d’Ivoire Djibouti Dominica Eritrea Ethiopia Gambia, The Georgia Ghana Grenada Guinea Guinea-Bissau Guyana Haiti Honduras India Kenya Kiribati Kosovo Kyrgyz Republic

Economic management

Structural policies

1–6 (low to high)

1–6 (low to high)

Macroeconomic management

Fiscal policy

Debt policy

Average

2009

2009

2009

2009

2009

2.8 2.8 4.2 3.8 3.5 3.5 3.9 3.8 3.7 3.8 3.1 3.3 3.2 4.2 2.6 2.5 2.5 2.7 2.8 2.8 3.2 3.8 2.2 3.4 3.3 4.4 3.8 3.7 2.8 2.6 3.4 2.9 3.5 3.8 3.7 3.1 3.4 3.7

3.5 3.0 5.0 4.0 4.0 4.0 4.5 4.0 4.0 4.5 3.5 4.5 4.0 4.5 3.5 2.5 3.0 3.5 3.5 3.5 3.5 4.0 2.0 3.5 4.0 4.5 3.5 3.5 2.5 2.5 3.5 4.0 3.0 4.5 4.5 2.5 3.5 4.5

3.0 3.0 5.0 4.5 4.0 3.5 4.5 4.0 3.5 4.5 3.5 3.5 4.0 4.5 3.0 2.5 2.0 3.5 3.0 2.5 3.0 4.5 2.0 4.0 3.5 4.5 3.5 2.5 2.5 2.5 3.0 3.5 3.5 3.5 4.0 3.0 3.0 4.0

3.5 3.0 5.0 5.0 4.0 3.5 4.5 4.5 4.0 4.0 3.0 3.5 3.0 4.5 2.5 2.5 2.0 2.5 2.5 2.5 2.5 3.0 1.5 3.5 3.0 5.0 4.0 3.0 2.0 1.5 4.0 2.5 4.0 4.0 4.0 5.0 3.5 4.0

3.3 3.0 5.0 4.5 4.0 3.7 4.5 4.2 3.8 4.3 3.3 3.8 3.7 4.5 3.0 2.5 2.3 3.2 3.0 2.8 3.0 3.8 1.8 3.7 3.5 4.7 3.7 3.0 2.3 2.2 3.5 3.3 3.5 4.0 4.2 3.5 3.3 4.2

Trade

Financial sector

Business regulatory environment

Average

2009

2009

2009

2009

3.0 4.0 4.5 4.0 3.5 4.0 3.0 5.0 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 4.0 1.5 3.0 3.5 6.0 4.0 4.5 4.0 4.0 4.0 4.0 4.5 3.5 4.0 3.0 5.0 5.0

2.5 2.5 4.0 3.5 3.5 3.5 3.0 4.0 4.0 3.0 2.5 2.5 3.0 4.0 2.5 3.0 2.5 2.0 3.0 3.0 3.5 3.5 1.0 3.0 3.0 3.5 4.0 4.0 3.0 3.0 3.5 3.0 3.0 4.0 4.0 3.0 3.5 3.0

2.5 2.0 4.0 4.0 3.5 3.5 3.5 2.5 4.0 3.5 2.5 3.5 3.0 3.5 2.0 2.5 2.5 2.0 2.5 3.0 3.5 4.5 2.0 3.5 3.5 5.5 4.0 4.0 3.0 2.5 3.0 2.5 3.5 3.5 4.0 3.0 3.5 3.5

2.7 2.8 4.2 3.8 3.5 3.7 3.2 3.8 4.0 3.5 3.0 3.3 3.2 3.8 2.7 2.8 2.7 2.5 3.0 3.3 3.7 4.0 1.5 3.2 3.3 5.0 4.0 4.2 3.3 3.2 3.5 3.2 3.7 3.7 4.0 3.0 4.0 3.8

About the data The International Development Association (IDA) is the

assessments have been carried out annually since

terms. The IRAI is a key element in the country per-

part of the World Bank Group that helps the poorest

the mid-1970s by World Bank staff. Over time the cri-

formance rating.

countries reduce poverty by providing concessional loans

teria have been revised from a largely macroeconomic

The CPIA exercise is intended to capture the quality

and grants for programs aimed at boosting economic

focus to include governance aspects and a broader

of a country’s policies and institutional arrangements,

growth and improving living conditions. IDA funding helps

coverage of social and structural dimensions. Country

focusing on key elements that are within the country’s

these countries deal with the complex challenges they

performance is assessed against a set of 16 criteria

control, rather than on outcomes (such as economic

face in meeting the Millennium Development Goals.

grouped into four clusters: economic management,

growth rates) that are influenced by events beyond

The World Bank’s IDA Resource Allocation Index

structural policies, policies for social inclusion and

the country’s control. More specifically, the CPIA

(IRAI), presented in the table, is based on the results

equity, and public sector management and institu-

measures the extent to which a country’s policy and

of the annual Country Policy and Institutional Assess-

tions. IDA resources are allocated to a country on per

institutional framework supports sustainable growth

ment (CPIA) exercise, which covers the IDA-eligible

capita terms based on its IDA country performance

and poverty reduction and, consequently, the effective

countries. The table does not include Myanmar and

rating and, to a limited extent, based on its per capita

use of development assistance.

Somalia because they were not rated in the 2009

gross national income. This ensures that good per-

All criteria within each cluster receive equal weight,

exercise even though they are IDA eligible. Country

formers receive a higher IDA allocation in per capita

and each cluster has a 25 percent weight in the overall

298

2011 World Development Indicators


International Development Association Resource Allocation Index 1–6 (low to high)

Lao PDR Lesotho Liberia Madagascar Malawi Maldives Mali Mauritania Moldova Mongolia Mozambique Nepal Nicaragua Niger Nigeria Pakistan Papua New Guinea Rwanda Samoa São Tomé and Príncipe Senegal Sierra Leone Solomon Islands Sri Lanka St. Lucia St. Vincent & Grenadines Sudan Tajikistan Tanzania Timor-Leste Togo Tonga Uganda Uzbekistan Vanuatu Vietnam Yemen, Rep. Zambia Zimbabwe

Economic management

Structural policies

1–6 (low to high)

1–6 (low to high)

Macroeconomic management

Fiscal policy

Debt policy

Average

2009

2009

2009

2009

2009

3.2 3.5 2.8 3.5 3.4 3.4 3.7 3.2 3.7 3.4 3.7 3.3 3.7 3.3 3.5 3.2 3.3 3.8 4.1 2.9 3.7 3.2 2.8 3.5 3.8 3.8 2.5 3.2 3.8 2.9 2.8 3.5 3.9 3.3 3.4 3.8 3.2 3.4 1.9

4.0 4.0 3.5 4.0 3.0 2.5 4.5 3.5 3.5 3.5 4.5 3.5 4.0 4.0 4.0 3.0 4.0 4.0 4.0 3.0 4.0 4.0 3.5 3.0 4.0 4.0 3.5 3.5 4.5 3.0 3.0 3.0 4.5 4.0 4.0 4.5 3.5 4.0 2.0

4.0 4.0 3.5 3.0 3.5 2.0 4.0 2.5 3.5 3.0 4.5 3.5 4.0 3.5 4.5 3.0 3.5 4.0 4.0 3.0 4.0 3.5 2.5 3.0 3.5 3.5 3.0 3.5 4.5 3.5 3.0 3.0 4.5 4.0 3.5 4.5 2.5 3.0 2.0

3.0 4.0 2.5 4.0 3.0 3.0 4.5 3.5 4.0 3.0 4.5 3.0 4.5 4.0 4.5 3.5 4.5 3.5 5.0 2.5 4.0 3.5 3.0 3.5 3.5 3.5 1.5 3.5 4.0 3.5 2.5 3.0 4.5 4.0 4.5 4.0 3.5 3.5 1.0

3.7 4.0 3.2 3.7 3.2 2.5 4.3 3.2 3.7 3.2 4.5 3.3 4.2 3.8 4.3 3.2 4.0 3.8 4.3 2.8 4.0 3.7 3.0 3.2 3.7 3.7 2.7 3.5 4.3 3.3 2.8 3.0 4.5 4.0 4.0 4.3 3.2 3.5 1.7

states and markets

5.9

Public policies and institutions

Trade

Financial sector

Business regulatory environment

Average

2009

2009

2009

2009

3.5 3.5 3.0 4.0 4.0 4.0 4.0 4.0 4.5 4.5 4.5 3.5 4.5 4.0 3.5 3.5 4.5 4.0 5.0 4.0 4.0 3.5 3.0 3.5 4.0 4.0 2.5 4.0 4.0 4.5 4.0 5.0 4.0 2.5 3.5 3.5 4.5 4.0 3.0

2.0 3.5 2.5 3.0 3.0 3.0 3.0 2.5 3.5 2.0 3.5 3.0 3.0 3.0 3.5 3.5 3.0 3.5 4.0 2.5 3.5 3.0 3.0 3.5 3.5 3.5 2.5 2.5 4.0 2.5 2.5 3.5 3.5 3.0 3.0 3.0 2.0 3.5 1.5

3.0 3.0 3.0 3.5 3.5 4.0 3.5 3.5 3.5 3.5 3.0 3.0 3.5 3.0 3.5 4.0 3.0 4.0 3.5 2.5 4.0 3.0 2.5 4.0 4.5 4.5 3.0 3.0 3.5 1.5 3.0 3.0 4.0 3.0 3.5 3.5 3.5 3.0 2.0

2.8 3.3 2.8 3.5 3.5 3.7 3.5 3.3 3.8 3.3 3.7 3.2 3.7 3.3 3.5 3.7 3.5 3.8 4.2 3.0 3.8 3.2 2.8 3.7 4.0 4.0 2.7 3.2 3.8 2.8 3.2 3.8 3.8 2.8 3.3 3.3 3.3 3.5 2.2

score, which is obtained by averaging the average

criteria are designed in a developmentally neutral man-

two key phases. In the benchmarking phase a small

scores of the four clusters. For each of the 16 criteria

ner. Accordingly, higher scores can be attained by a

representative sample of countries drawn from all

countries are rated on a scale of 1 (low) to 6 (high).

country that, given its stage of development, has a

regions is rated. Country teams prepare proposals

The scores depend on the level of performance in

policy and institutional framework that more strongly

that are reviewed first at the regional level and then

a given year assessed against the criteria, rather

fosters growth and poverty reduction.

in a Bankwide review process. A similar process is

than on changes in performance compared with the

The country teams that prepare the ratings are very

followed to assess the performance of the remaining

previous year. All 16 CPIA criteria contain a detailed

familiar with the country, and their assessments are

countries, using the benchmark countries’ scores as

description of each rating level. In assessing country

based on country diagnostic studies prepared by the

guideposts. The final ratings are determined following

performance, World Bank staff evaluate the country’s

World Bank or other development organizations and

a Bankwide review. The overall numerical IRAI score

performance on each of the criteria and assign a rat-

on their own professional judgment. An early con-

and the separate criteria scores were first publicly

ing. The ratings reflect a variety of indicators, observa-

sultation is conducted with country authorities to

disclosed in June 2006.

tions, and judgments based on country knowledge and

make sure that the assessments are informed by

on relevant publicly available indicators. In interpreting

up-to-date information. To ensure that scores are

the assessment scores, it should be noted that the

consistent across countries, the process involves

See IDA’s website at www.worldbank.org/ida for more information.

2011 World Development Indicators

299


5.9 Afghanistan Angola Armenia Azerbaijan Bangladesh Benin Bhutan Bolivia Bosnia and Herzegovina Burkina Faso Burundi Cambodia Cameroon Cape Verde Central African Republic Chad Comoros Congo, Dem. Rep. Congo, Rep. Côte d'Ivoire Djibouti Dominica Eritrea Ethiopia Gambia, The Georgia Ghana Grenada Guinea Guinea-Bissau Guyana Haiti Honduras India Kenya Kiribati Kosovo Kyrgyz Republic

Public policies and institutions Policies for social inclusion and equity

Public sector management and institutions

1–6 (low to high)

1–6 (low to high)

Policies and institutions for Social protection environmental and labor sustainability Average

Quality of budgetary and Property financial rights and rule-based management governance

Transparency, accountability, and corruption Quality Efficiency in the public of public of revenue sector Average mobilization administration

Gender equality

Equity of public resource use

Building human resources

2009

2009

2009

2009

2009

2009

2009

2009

2009

2009

2009

2009

2.0 3.5 4.5 4.0 4.0 3.5 4.0 4.0 4.5 3.5 4.0 4.0 3.0 4.5 2.5 2.5 3.0 2.5 3.0 2.5 3.0 3.5 3.5 3.0 3.5 4.5 4.0 4.5 3.5 2.5 4.0 3.0 4.0 3.5 3.0 2.5 3.5 4.5

3.0 2.5 4.5 4.0 3.5 3.0 4.0 4.0 3.5 4.0 3.5 3.0 3.0 4.5 2.5 2.5 2.5 3.0 2.5 2.0 3.0 3.5 2.5 4.5 3.5 4.5 4.0 3.5 3.0 3.0 3.5 3.0 4.0 4.0 3.5 3.5 3.5 3.5

3.0 2.5 4.0 4.0 4.0 3.5 4.0 4.0 3.5 3.5 3.0 3.5 3.5 4.5 2.5 2.5 3.0 3.0 3.0 2.5 3.5 4.0 3.5 4.0 3.5 4.5 4.5 4.0 3.0 2.0 4.0 2.5 3.5 4.0 4.0 2.5 2.5 3.5

2.5 3.0 4.5 4.0 3.5 3.0 3.5 3.5 3.5 3.5 3.0 3.0 3.0 4.5 2.0 2.5 2.5 3.0 2.5 2.5 3.0 3.5 2.5 3.5 2.5 4.5 3.5 3.5 3.0 2.5 3.0 2.5 3.5 3.5 3.5 3.0 3.5 3.5

2.5 3.0 3.0 3.0 3.0 3.5 4.5 3.5 3.5 3.5 3.0 3.0 3.0 3.5 3.0 2.0 2