National poverty line
  


Population below the poverty line
Population below the poverty line
Survey year Rural
%		 Urban
%		 National
%
Survey year Rural
%		 Urban
%		 National
%

International poverty line
   
Survey year Population below
$1 a day
%		 Poverty gap at
$1 a day
%		 Population below
$2 a day
%		 Poverty gap at
$2 a day
%
 
Afghanistan   .. .. ..   .. .. ..   .. .. .. ..
Albania 2002 29.6 19.8 25.4 .. .. .. 2002a <2 <0.5 11.8 2.0
Algeria 1988 16.6 7.3 12.2 1995 30.3 14.7 22.6 1995a <2 <0.5 15.1 3.8
Angola   .. .. ..   .. .. ..   .. .. .. ..
Argentina 1995 .. 28.4   1998  .. 29.9  .. 2003b 7.0 2.0 23.0 8.4
Armenia 1998–99 50.8 58.3 55.1 2001 48.7 51.9 50.9 2003a <2 <0.5 31.1 7.1
Australia   .. .. .. .. .. ..   .. .. .. ..
Austria   .. .. .. .. .. ..   .. .. .. ..
Azerbaijan 1995 .. .. 68.1 2001 42.0 55.0 49.0 2002a <2 <0.5 <2 <0.5
Bangladesh 1995–96 55.2 29.4 51.0 2000 53.0 36.6 49.8 2000a 36.0 8.1 82.8 36.3
Belarus 2000 .. .. 41.9    .. ..  ..  2002a <2 <0.5 <2 <0.5
Belgium   .. .. ..   .. .. ..   .. .. .. ..
Benin 1995 25.2 28.5 26.5 1999 33.0 23.3 29.0 2003a 30.9 8.2 73.7 31.7
Bolivia 1997 77.3 53.8 63.2 1999 81.7 50.6 62.7 2002b 23.2 13.6 42.2 23.2
Bosnia and Herzegovina 2001–02 19.9 13.8 19.5   .. .. ..   .. .. .. ..
Botswana   .. .. ..     ..  ..  .. 1993a 23.5 7.7 50.1 22.8
Brazil 1996 54.0 15.4 23.9 1998 51.4 14.7 22.0 2003b 7.5 3.4 21.2 8.5
Bulgaria 1997 .. .. 36.0 2001 .. .. 12.8 2003a <2 <0.5 6.1 1.5
Burkina Faso 1998 61.1 22.4 54.6 2003 52.4 19.2 46.4 2003a 27.2 7.3 71.8 30.4
Burundi 1990 36.0 43.0 36.4   .. .. .. 1998a 54.6 22.7 87.6 48.9
Cambodia 1997 40.1 21.1 36.1 1999 40.1 13.9 35.9 1997a 34.1 9.7 77.7 34.5
Cameroon 1996 59.6 41.4 53.3 2001 49.9 22.1 40.2 2001a 17.1 4.1 50.6 19.3
Canada   .. .. ..   .. .. ..   .. .. .. ..
Central African Republic   .. .. ..   .. .. .. 1993a 66.6 38.1 84.0 58.4
Chad 1995–96 67.0 63.0 64.0   .. .. ..   .. .. .. ..
Chile 1996 .. .. 19.9 1998 .. .. 17.0 2000b <2 <0.5 9.6 2.5
China 1996 7.9 <2 6.0 1998 4.6 <2 4.6 2001a 16.6 3.9 46.7 18.4
Hong Kong, China   .. .. ..   .. .. ..   .. .. .. ..
Colombia 1995 79.0 48.0 60.0 1999 79.0 55.0 64.0 2003b 7.0 3.1 17.8 7.7
Congo, Dem. Rep.   .. .. ..   .. .. ..   .. .. .. ..
Congo, Rep.   .. .. ..   .. .. ..   .. .. .. ..
Costa Rica 1992 25.5 19.2 22.0   .. .. .. 2001b 2.2 0.8 7.5 2.8
Côte d’Ivoire   .. .. ..    ..  ..  ..  2002a 14.8 4.1 48.8 18.4
Croatia   .. .. ..   .. .. .. 2001a <2 <0.5 <2 <0.5
Cuba   .. .. ..   .. .. ..   .. .. .. ..
Czech Republic   .. .. ..   .. .. .. 1996b <2 <0.5 <2 <0.5
Denmark   .. .. ..   .. .. ..   .. .. .. ..
Dominican Republic 1992 49.0 19.3 33.9 1998 42.1 20.5 28.6 2003b 2.5 0.8 11.0 3.6
Ecuador 1995 56.0 19.0 34.0 1998 69.0 30.0 46.0 1998b 15.8 6.3 37.2 15.8
Egypt, Arab Rep. 1995–96 23.3 22.5 22.9 1999–2000 .. .. 16.7 1999–2000a 3.1 <0.5 43.9 11.3
El Salvador 1992 55.7 43.1 48.3   .. .. .. 2002b 19.0 9.3 40.6 17.7
Eritrea 1993–94 .. .. 53.0   .. .. ..   .. .. .. ..
Estonia 1995 14.7 6.8 8.9   ..  ..  ..  2003a <2 <0.5 7.5 1.9
Ethiopia 1995–96 47.0 33.3 45.5 1999–2000 45.0 37.0 44.2 1999–2000a 23.0 4.8 77.8 29.6
Finland   .. .. ..   .. .. ..   .. .. .. ..
France   .. .. ..   .. .. ..   .. .. .. ..
Gabon   .. .. ..   .. .. ..   .. .. .. ..
Gambia, The 1992  .. ..  64.0 1998 61.0 48.0 57.6 1998a 59.3 28.8 82.9 51.1
Georgia 2002 55.4 48.5 52.1 2003 52.7 56.2 54.5 2003a 6.5 2.1 25.3 8.6
Germany   .. .. ..   .. .. ..   .. .. .. ..
Ghana 1992 .. .. 50.0 1998–99 49.9 18.6 39.5 1998–99a 44.8 17.3 78.5 40.8
Greece   .. .. ..   .. .. ..   .. .. .. ..
Guatemala 1989 71.9 33.7 57.9 2000 74.5 27.1 56.2 2002b 13.5 5.5 31.9 13.8
Guinea 1994 .. .. 40.0   .. .. ..   .. .. .. ..
Guinea-Bissau   .. .. ..   .. .. ..   .. .. .. ..
Haiti 1987 .. .. 65.0 1995 66.0 .. .. 2001b 53.9 26.6 78.0 47.4
Honduras 1997 58.0 35.0 47.0 1999 58.0 37.0 48.0 1999b 20.7 7.5 44.0 20.2
Hungary 1993 .. .. 14.5 1997 .. .. 17.3 2002a <2 <0.5 <2 <0.5
India 1993–94 37.3 32.4 36.0 1999–2000 30.2 24.7 28.6 1999–2000a 34.7 8.2 79.9 35.3
Indonesia 1996 .. .. 15.7 1999 34.4 16.1 27.1 2002a 7.5 0.9 52.4 15.7
Iran, Islamic Rep.   .. .. ..   .. .. .. 1998a <2 <0.5 7.3 1.5
Iraq   .. .. ..   .. .. ..   .. .. .. ..
Ireland   .. .. ..   .. .. ..   .. .. .. ..
Israel   .. .. ..   .. .. ..   .. .. .. ..
Italy   .. .. ..   .. .. ..   .. .. .. ..
Jamaica 1995 37.0 18.7 27.5 2000 25.1 12.8 18.7 2000a <2 <0.5 13.3 2.7
Japan   .. .. ..   .. .. ..   .. .. .. ..
Jordan 1991 .. .. 15.0 1997 .. .. 11.7 2002–03a <2 <0.5 7.0 1.5
Kazakhstan 1996 39.0 30.0 34.6   .. .. .. 2003a <2 <.5 16.0 3.8
Kenya 1994 47.0 29.0 40.0 1997 53.0 49.0 52.0 1997a 22.8 5.9 58.3 23.9
Korea, Dem. Rep.   .. .. ..   .. .. ..   .. .. .. ..
Korea, Rep.   .. .. ..   .. .. .. 1998b <2 <0.5 <2 <0.5
Kuwait   .. .. ..   .. .. ..   .. .. .. ..
Kyrgyz Republic 2000 56.4 43.9 52.0 2001 51.0 41.2 47.6 2003a <2 <0.5 21.4 4.4
Lao PDR 1993 48.7 33.1 45.0 1997–98 41.0 26.9 38.6 2002a 27.0 6.1 74.1 30.2
Latvia   .. .. ..   .. .. .. 2003a <2 <0.5 4.7 1.2
Lebanon   .. .. ..   .. .. ..   .. .. .. ..
Lesotho    .. ..  ..     ..  ..  .. 1995a 36.4 19.0 56.1 33.1
Liberia   .. .. ..   .. .. ..   .. .. .. ..
Libya   .. .. ..   .. .. ..   .. .. .. ..
Lithuania   .. .. ..   .. .. .. 2003a <2 <0.5 7.8 1.8
Macedonia, FYR   .. .. ..   .. .. .. 2003a <2 <0.5 <2 <0.5
Madagascar 1997 76.0 63.2 73.3 1999 76.7 52.1 71.3 2001a 61.0 27.9 85.1 51.8
Malawi 1990–91 .. .. 54.0 1997–98 66.5 54.9 65.3 1997–98a 41.7 14.8 76.1 38.3
Malaysia 1989 .. .. 15.5   .. .. .. 1997b <2 <0.5 9.3 2.0
Mali 1998 75.9 30.1 63.8   .. .. .. 1994a 72.3 37.4 90.6 60.5
Mauritania 1996 65.5 30.1 50.0 2000 61.2 25.4 46.3 2000a 25.9 7.6 63.1 26.8
Mauritius   .. .. ..   .. .. ..   .. .. .. ..
Mexico 1996 52.4 26.5 37.1 2002 34.8 11.4 20.3 2002a 4.5 1.2 20.4 6.5
Moldova 2001 64.1 58.0 62.4 2002 67.2 42.6 48.5 2001a 22.0 5.8 63.7 25.1
Mongolia 1995 33.1 38.5 36.3 1998 32.6 39.4 35.6 1998a 27.0 8.1 74.9 30.6
Morocco 1990–91 18.0 7.6 13.1 1998–99 27.2 12.0 19.0 1999a <2 <0.5 14.3 3.1
Mozambique 1996–97 71.3 62.0 69.4   .. .. .. 1996a 37.9 12.0 78.4 36.8
Myanmar   .. .. ..   .. .. ..   .. .. .. ..
Namibia   .. .. ..   .. .. .. 1993b 34.9 14.0 55.8 30.4
Nepal 1995–96 43.3 21.6 41.8 2003–04 34.6 9.6 30.9 2003–04a 24.1 5.4 68.5 26.8
Netherlands   .. .. ..   .. .. ..   .. .. .. ..
New Zealand   .. .. ..   .. .. ..   .. .. .. ..
Nicaragua 1993 76.1 31.9 50.3 1998 68.5 30.5 47.9 2001a 45.1 16.7 79.9 41.2
Niger 1989–93 66.0 52.0 63.0   .. .. .. 1995a 60.6 34.0 85.8 54.6
Nigeria 1985 49.5 31.7 43.0 1992–93 36.4 30.4 34.1 2003a 70.8 34.5 92.4 59.5
Norway   .. .. ..   .. .. ..   .. .. .. ..
Oman   .. .. ..   .. .. ..   .. .. .. ..
Pakistan 1993 33.4 17.2 28.6 1998–99 35.9 24.2 32.6 2002a 17.0 3.1 73.6 26.1
Panama 1997 64.9 15.3 37.3   .. .. .. 2002b 6.5 2.3 17.1 6.9
Papua New Guinea 1996 41.3 16.1 37.5   .. .. ..   .. .. .. ..
Paraguay 1991 28.5 19.7 21.8   .. .. .. 2002b 16.4 7.4 33.2 16.2
Peru 1994 67.0 46.1 53.5 1997 64.7 40.4 49.0 2002b 12.5 4.4 31.8 13.4
Philippines 1994 53.1 28.0 40.6 1997 50.7 21.5 36.8 2000a 15.5 3.0 47.5 17.8
Poland 1993 .. .. 23.8   .. .. .. 2002a <2 <0.5 <2 <0.5
Portugal   .. .. ..   .. .. .. 1994b <2 <0.5 <2 <0.5
Puerto Rico   .. .. ..   .. .. ..   .. .. .. ..
Romania 1994 27.9 20.4 21.5   .. .. .. 2003a <2 0.5 12.9 3.0
Russian Federation 1994 .. .. 30.9   .. .. .. 2002a <2 <0.5 12.1 3.1
Rwanda 1993 .. .. 51.2 1999–2000 65.7 14.3 60.3 1999–2000a 51.7 20.0 83.7 45.5
Saudi Arabia   .. .. ..   .. .. ..   .. .. .. ..
Senegal 1992 40.4 23.7 33.4   .. .. .. 1995a 22.3 5.7 63.0 25.2
Serbia and Montenegro   .. .. ..   .. .. ..    .. .. ..  .. 
Sierra Leone 1989 .. .. 82.8 2003–04 79.0 56.4 70.2 1989a 57.0 39.5 74.5 51.8
Singapore   .. .. ..   .. .. ..   .. .. .. ..
Slovak Republic   .. .. ..   ..  .. .. 1996b <2 <0.5 2.9 0.8
Slovenia   .. .. ..   .. .. .. 1998a <2 <0.5 <2 <0.5
Somalia   .. .. ..   .. .. ..   .. .. .. ..
South Africa   .. .. ..   .. .. .. 2000a 10.7 1.7 34.1 12.6
Spain   .. .. ..   .. .. ..   .. .. .. ..
Sri Lanka 1990–91 22.0 15.0 20.0 1995–96 27.0 15.0 25.0 2002a 5.6 0.8 41.6 11.9
Sudan   .. .. ..   .. .. ..   .. .. .. ..
Swaziland   .. .. ..   .. .. ..   .. .. .. ..
Sweden   .. .. ..   .. .. ..   .. .. .. ..
Switzerland   .. .. ..   .. .. ..   .. .. .. ..
Syrian Arab Republic   .. .. ..   .. .. ..   .. .. .. ..
Tajikistan   .. .. ..   .. .. .. 2003a 7.4 1.3 42.8 13.0
Tanzania 1991 40.8 31.2 38.6 2000–01 38.7 29.5 35.7 2000–01a 57.8 20.7 89.9 49.3
Thailand 1990 .. .. 18.0 1992 15.5 10.2 13.1 2002a <2 <0.5 25.2 6.2
Togo 1987–89 .. .. 32.3   .. .. ..   .. .. .. ..
Trinidad and Tobago 1992 20.0 24.0 21.0   ..  ..  ..  1992b 12.4 3.5 39.0 14.6
Tunisia 1990 13.1 3.5 7.4 1995 13.9 3.6 7.6 2000a <2 <0.5 6.6 1.3
Turkey 1994 .. .. 28.3 2002 34.5 22.0 27.0 2003a 3.4 0.8 18.7 5.7
Turkmenistan   .. .. ..   .. .. ..   ..  ..  ..  .. 
Uganda 1999–2000 37.4 9.6 33.8 2002–03 41.7 12.2 37.7   .. .. .. ..
Ukraine 2000 34.9   31.5 2003 28.4 ..  19.5 2003b <2 <0.5 4.9 0.9
United Arab Emirates   .. .. ..   .. .. ..   .. .. .. ..
United Kingdom   .. .. ..   .. .. ..   .. .. .. ..
United States   .. .. ..   .. .. ..   .. .. .. ..
Uruguay 1994 .. 20.2 .. 1998 .. 24.7 .. 2003b <2 <0.5 5.7 1.6
Uzbekistan 2000 30.5 22.5 27.5   .. .. ..   .. .. .. ..
Venezuela, RB 1989 .. .. 31.3   .. .. .. 2000b 8.3 2.8 27.6 10.2
Vietnam 1998 45.5 9.2 37.4 2002 35.6 6.6 28.9   .. .. .. ..
West Bank and Gaza   .. .. ..   .. .. ..   .. .. .. ..
Yemen, Rep. 1998 45.0 30.8 41.8   .. .. .. 1998a 15.7 4.5 45.2 15.0
Zambia 1996 82.8 46.0 69.2 1998 83.1 56.0 72.9 2002–03a 75.8 36.4 94.1 62.2
Zimbabwe 1990–91 35.8 3.4 25.8 1995–96 48.0 7.9 34.9 1995–96a 56.1 24.2 83.0 48.2
          
Footnotes
 
a. Expenditure base.
b. Income base.
2.7a
Regional poverty estimates
  Region

1981

1984

1987

1990

 1993

1996

1999

2002a
  People living on less than $1 a day (millions)                
East Asia & Pacific 796 562 426 472 415 287 282 214
 China 634 425 308 375 334 212 223 180
 Europe & Central Asia 3 2 2 2 17 20 30 10
 Latin America & Caribbean 36 46 45 49 52 52 54 47
 Middle East & North Africa 9 8 7 6 4 5 8 5
 South Asia 475 460 473 462 476 461 429 437
 Sub-Saharan Africa 164 198 219 227 242 271 294 303
 Total 1,482 1,277 1,171 1,218 1,208 1,097 1,096 1,015
 Excluding China 848 852 863 844 873 886 873 835
                  
  Share of people living on less than $1 a day (%)                
East Asia & Pacific 57.7 38.9 28.0 29.6 24.9 16.6 15.7 11.6
 China 63.8 41.0 28.5 33.0 28.4 17.4 17.8 14.0
 Europe & Central Asia 0.7 0.5 0.4 0.5 3.7 4.3 6.3 2.1
 Latin America & Caribbean 9.7 11.8 10.9 11.3 11.3 10.7 10.5 8.9
 Middle East & North Africa 5.1 3.8 3.2 2.3 1.6 2.0 2.6 1.6
 South Asia 51.5 46.8 45.0 41.3 40.1 36.6 32.2 31.2
 Sub-Saharan Africa 41.6 46.3 46.8 44.6 44.0 45.6 45.7 44.0
 Total 40.4 32.8 28.4 27.9 26.3 22.8 21.8 19.4
 Excluding China 31.7 29.8 28.4 26.1 25.6 24.6 23.1 21.1
                  
  People living on less than $2 a day (millions)                
East Asia & Pacific 1,170 1,109 1,028 1,116 1,079 922 900 748
 China 876 814 731 825 803 650 627 533
 Europe & Central Asia 20 18 15 23 81 98 113 76
 Latin America & Caribbean 99 119 115 125 136 117 127 123
 Middle East & North Africa 52 50 53 51 52 61 70 61
 South Asia 821 859 911 958 1,005 1,029 1,039 1,091
 Sub-Saharan Africa 288 326 355 382 410 447 489 516
 Total 2,450 2,480 2,478 2,654 2,764 2,674 2,739 2,614
 Excluding China 1,574 1,666 1,747 1,829 1,961 2,024 2,111 2,082
                  
  Share of people living on less than $2 a day (%)                
East Asia & Pacific 84.8 76.6 67.7 69.9 64.8 53.3 50.3 40.7
 China 88.1 78.5 67.4 72.6 68.1 53.4 50.1 41.6
 Europe & Central Asia 4.7 4.1 3.3 4.9 17.2 20.7 23.8 16.1
 Latin America & Caribbean 26.9 30.4 27.8 28.4 29.5 24.1 25.1 23.4
 Middle East & North Africa 28.9 25.2 24.2 21.4 20.2 22.3 24.3 19.8
 South Asia 89.1 87.2 86.7 85.5 84.5 81.7 78.1 77.8
 Sub-Saharan Africa 73.3 76.1 76.1 75.0 74.6 75.1 76.1 74.9
 Total 66.7 63.7 60.1 60.8 60.2 55.5 54.4 50.0
 Excluding China 58.8 58.4 57.5 56.6 57.4 56.3 55.8 52.7
                  
Note: Estimates are computed based on population data from World Development Indicators 2005.
a. Preliminary estimates not strictly comparable with earlier estimates. See About the data for more information.

 About the data
 
The World Bank produced its first global poverty estimates for developing countries for World Development Report 1990 using household survey data for 22 countries (Ravallion, Datt, and van de Walle 1991). Incorporating survey data collected during the last 15 years, the database has expanded considerably and now includes 440 surveys representing almost 100 developing countries. Some 1.1 million randomly sampled households were interviewed in these surveys, representing 93 percent of the population of developing countries. The surveys asked detailed questions on sources of income and how it was spent and on other household characteristics such as the number of people sharing that income. Most interviewas were conducted by staff of government statistics offices. Along with improvements in data coverage and quality, the underlying methodology has also improved, resulting in better and more comprehensive estimates.
 
Data availability
Since 1979 there has been considerable expansion in the number of countries that field such surveys, the frequency of the surveys, and the quality of their data. The number of data sets rose dramatically from a mere 13 between 1979 and 1981 to 100 between 1997 and 1999. The drop to 41 available surveys after 1999 reflects the lag between the time data are collected and the time they become available for analysis, not a reduction in data collection. Data coverage is improving in all regions, but Sub-Saharan Africa continues to lag, with only 28 of 48 countries having at least one data set available. A complete overview of data availability by year and country can be obtained at http://iresearch.worldbank.org/povcalnet/.
 
Data quality
The problems of estimating poverty and comparing poverty rates do not end with data availability. Several other issues, some related to data quality, also arise in measuring household living standards from survey data. One relates to the choice of income or consumption as a welfare indicator. Income is generally more difficult to measure accurately, and consumption comes closer to the notion of standard of living. And income can vary over time even if the standard of living does not. But consumption data are not always available. Another issue is that household surveys can differ widely, for example, in the number of consumer goods they identify. And even similar surveys may not be strictly comparable because of differences in timing or the quality and training of survey enumerators.
 
Comparisons of countries at different levels of development also pose a potential problem because of differences in the relative importance of consumption of nonmarket goods. The local market value of all consumption in kind (including own production, particularly important in underdeveloped rural economies) should be included in total consumption expenditure. Similarly, imputed profit from the production of nonmarket goods should be included in income. This is not always done, though such omissions were a far bigger problem in surveys before the 1980s. Most survey data now include valuations for consumption or income from own production. Nonetheless, valuation methods vary. For example, some surveys use the price in the nearest market, while others use the average farmgate selling price.
 
Whenever possible, the table uses consumption data for deciding who is poor and income surveys only when consumption data are unavailable. In recent editions there has been a change in how income surveys are used. In the past, average household income was adjusted to accord with consumption and income data from national accounts. But in testing this approach using data for some 20 countries for which income and consumption expenditure data were both available from the same surveys, income was found to yield a higher mean than consumption but also higher inequality. When poverty measures based on consumption and income were compared, these two effects roughly cancelled each other out: statistically, there was no significant difference. So recent editions use income data to estimate poverty directly, without adjusting average income measures.
 
International poverty lines
International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries. Is it reasonable to treat two people with the same standard of living—in terms of their command over commodities—differently because one happens to live in a better-off country?
 
Poverty measures based on an international poverty line attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for the World Bank’s World Development Report 1990: Poverty because it is typical of the poverty lines in low-income countries. PPP exchange rates, such as those from the Penn World Tables or the World Bank, are used because they take into account the local prices of goods and services not traded internationally. But PPP rates were designed for comparing aggregates from national accounts, not for making international poverty comparisons. As a result, there is no certainty that an international poverty line measures the same degree of need or deprivation across countries.
 
Early editions of World Development Indicators used PPPs from the Penn World Tables. Recent editions use 1993 consumption PPP estimates produced by the World Bank. Recalculated in 1993 PPP terms, the original international poverty line of $1 a day in 1985 PPP terms is now about $1.08 a day. Any revisions in the PPP of a country to incorporate better price indexes can produce dramatically different poverty lines in local currency.
 
Issues also arise when comparing poverty measures within countries. For example, the cost of living is typically higher in urban than in rural areas. One reason is that food staples tend to be more expensive in urban areas. So the urban monetary poverty line should be higher than the rural poverty line. But it is not always clear that the difference between urban and rural poverty lines found in practice reflects only differences in the cost of living. In some countries the urban poverty line in common use has a higher real value—meaning that it allows the purchase of more commodities for consumption—than does the rural poverty line. Sometimes the difference has been so large as to imply that the incidence of poverty is greater in urban than in rural areas, even though the reverse is found when adjustments are made only for differences in the cost of living. As with international comparisons, when the real value of the poverty line varies it is not clear how meaningful such urban-rural comparisons are.
 
By combining all this information, a team in the World Bank’s Development Research Group calculates the number of people living below various international poverty lines, as well as other poverty and inequality measures that are published in World Development Indicators. The database is updated annually as new survey data become available, and a major reassessment of progress against poverty is made about every three years.
 
Do it yourself: PovcalNet
Recently, this research team developed PovcalNet, an interactive Web-based computational tool that allows users to replicate the calculations by the World Bank’s researchers in estimating the extent of absolute poverty in the world. PovcalNet is self-contained and powered by reliable built-in software that performs the relevant calculations from a primary database. The underlying software can also be downloaded from the site and used with distributional data of various formats. The PovcalNet primary database consists of distributional data calculated directly from household survey data. Detailed information for each of these is also available from the site.
 
Estimation from distributional data requires an interpolation method. The method chosen was Lorenz curves with flexible functional forms, which have proved reliable in past work. The Lorenz curve can be graphed as the cumulative percentages of total consumption or income against the cumulative number of people, starting with the poorest individual. The empirical Lorenz curves estimated by PovcalNet are weighted by household size, so they are based on percentiles of population, not households.
 
PovcalNet also allows users to calculate poverty measures under different assumptions. For example, instead of $1 a day, users can specify a different poverty line, say $1.50 or $3. Users can also specify different PPP rates and aggregate the estimates using alternative country groupings (for example, UN country groupings or groupings based on average incomes) or a selected set of individual countries. PovcalNet is available online at http://iresearch.worldbank.org/povcalnet/.
 
Note on the 2002 estimates
The 2002 estimates are adapted from Global Economic Prospects 2006 (page 9, table 1.3). Note that a typesetting error occurred in the printed edition of Global Economic Prospects 2006; the 2002 poverty rate estimates reported in table 2.7a are the correct estimates.
 

 
 Definitions
 
• Survey year is the year in which the underlying data were collected. • Rural poverty rate is the percentage of the rural population living below the national rural poverty line. • Urban poverty rate is the percentage of the urban population living below the national urban poverty line. • National poverty rate is the percentage of the population living below the national poverty line. National estimates are based on population-weighted subgroup estimates from household surveys. • Population below $1 a day and population below $2 a day are the percentages of the population living on less than $1.08 a day and $2.15 a day at 1993 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions. • Poverty gap is the mean shortfall from the poverty line (counting the nonpoor as having zero shortfall), expressed as a percentage of the poverty line. This measure reflects the depth of poverty as well as its incidence.
   

 
 Data sources
The poverty measures are prepared by the World Bank’s Development Research Group. The national poverty lines are based on the World Bank’s country poverty assessments. The international poverty lines are based on nationally representative primary household surveys conducted by national statistical offices or by private agencies under the supervision of government or international agencies and obtained from government statistical offices and World Bank Group country departments. The World Bank Group has prepared an annual review of its poverty work since 1993. For details on data sources and methods used in deriving the World Bank’s latest estimates, see Chen and Ravallion (2004), “How Have the World’s Poorest Fared Since the Early 1980s?”