Others titles
- Historic Values of The GINI Index
- GINI Coefficients Database
- Global Gini Index Data
Keywords
- GINI
- GINI Coefficients
- GINI Index
- High Income Economies
- World Bank Data
- GINI Ratio
GINI Index Data
GINI Index Data consists of information based on primary household survey data obtained from government statistical agencies and World Bank country departments. In economics, the GINI index (sometimes expressed as a GINI ratio, GINI coefficient or a normalized GINI index) is a measure of statistical dispersion intended to represent the income or wealth distribution of a nation’s residents, and is the most commonly used measure of inequality.
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Description
GINI index measures the extent to which the distribution of income (or, in some cases, consumption expenditure) among individuals or households within an economy deviates from a perfectly equal distribution. A Lorenz curve plots the cumulative percentages of total income received against the cumulative number of recipients, starting with the poorest individual or household. The GINI index measures the area between the Lorenz curve and a hypothetical line of absolute equality, expressed as a percentage of the maximum area under the line. Thus a GINI index of 0 represents perfect equality, while an index of 100 implies perfect inequality.
The World Bank’s internationally comparable poverty monitoring database now draws on income or detailed consumption data from more than one thousand household surveys across 138 countries in six regions and 21 other high income countries (industrialized economies). While income distribution data are published for all countries with data available, poverty data are published for low- and middle-income countries and countries eligible to receive loans from the World Bank (such as Chile) and recently graduated countries (such as Estonia) only.
GINI coefficients are not unique. It is possible for two different Lorenz curves to give rise to the same GINI coefficient. Furthermore it is possible for the GINI coefficient of a developing country to rise (due to increasing inequality of income) while the number of people in absolute poverty decreases. This is because the GINI coefficient measures relative, not absolute, wealth. Another limitation of the GINI coefficient is that it is not additive across groups, i.e. the total GINI of a society is not equal to the sum of the GINI’s for its sub-groups. Thus, country-level GINI coefficients cannot be aggregated into regional or global GINI’s, although a GINI coefficient can be computed for the aggregate. Because the underlying household surveys differ in methods and types of welfare measures collected, data are not strictly comparable across countries or even across years within a country.
Two sources of non-comparability should be noted for distributions of income in particular. First, the surveys can differ in many respects, including whether they use income or consumption expenditure as the living standard indicator. The distribution of income is typically more unequal than the distribution of consumption. In addition, the definitions of income used differ more often among surveys. Consumption is usually a much better welfare indicator, particularly in developing countries. Second, households differ in size (number of members) and in the extent of income sharing among members. And individuals differ in age and consumption needs. Differences among countries in these respects may bias comparisons of distribution. World Bank staff have made an effort to ensure that the data are as comparable as possible. Wherever possible, consumption has been used rather than income. Income distribution and GINI indexes for high-income economies are calculated directly from the Luxembourg Income Study database, using an estimation method consistent with that applied for developing countries.
About this Dataset
Data Info
Date Created | 2017-07-20 |
---|---|
Last Modified | 2022-06-30 |
Version | 2022-06-30 |
Update Frequency |
Annual |
Temporal Coverage |
1981-2021 |
Spatial Coverage |
World |
Source | John Snow Labs; World Bank, Development Research Group; |
Source License URL | |
Source License Requirements |
N/A |
Source Citation |
N/A |
Keywords | GINI, GINI Coefficients, GINI Index, High Income Economies, World Bank Data, GINI Ratio |
Other Titles | Historic Values of The GINI Index, GINI Coefficients Database, Global Gini Index Data |
Data Fields
Name | Description | Type | Constraints |
---|---|---|---|
Country_Name | Name of the country | string | required : 1 |
Country_Code | ISO 3166-1 alpha-2 country code | string | required : 1 |
Region_Name | Name of the region within the country | string | - |
Income_Group | Country's income group | string | - |
Special_Notes | Special notes, if any. | string | - |
Year_1981 | GINI Index value for the country in 1981 | number | level : Ratio |
Year_1982 | GINI Index value for the country in 1982 | number | level : Ratio |
Year_1983 | GINI Index value for the country in 1983 | number | level : Ratio |
Year_1984 | GINI Index value for the country in 1984 | number | level : Ratio |
Year_1985 | GINI Index value for the country in 1985 | number | level : Ratio |
Year_1986 | GINI Index value for the country in 1986 | number | level : Ratio |
Year_1987 | GINI Index value for the country in 1987 | number | level : Ratio |
Year_1988 | GINI Index value for the country in 1988 | number | level : Ratio |
Year_1989 | GINI Index value for the country in 1989 | number | level : Ratio |
Year_1990 | GINI Index value for the country in 1990 | number | level : Ratio |
Year_1991 | GINI Index value for the country in 1991 | number | level : Ratio |
Year_1992 | GINI Index value for the country in 1992 | number | level : Ratio |
Year_1993 | GINI Index value for the country in 1993 | number | level : Ratio |
Year_1994 | GINI Index value for the country in 1994 | number | level : Ratio |
Year_1995 | GINI Index value for the country in 1995 | number | level : Ratio |
Year_1996 | GINI Index value for the country in 1996 | number | level : Ratio |
Year_1997 | GINI Index value for the country in 1997 | number | level : Ratio |
Year_1998 | GINI Index value for the country in 1998 | number | level : Ratio |
Year_1999 | GINI Index value for the country in 1999 | number | level : Ratio |
Year_2000 | GINI Index value for the country in 2000 | number | level : Ratio |
Year_2001 | GINI Index value for the country in 2001 | number | level : Ratio |
Year_2002 | GINI Index value for the country in 2002 | number | level : Ratio |
Year_2003 | GINI Index value for the country in 2003 | number | level : Ratio |
Year_2004 | GINI Index value for the country in 2004 | number | level : Ratio |
Year_2005 | GINI Index value for the country in 2005 | number | level : Ratio |
Year_2006 | GINI Index value for the country in 2006 | number | level : Ratio |
Year_2007 | GINI Index value for the country in 2007 | number | level : Ratio |
Year_2008 | GINI Index value for the country in 2008 | number | level : Ratio |
Year_2009 | GINI Index value for the country in 2009 | number | level : Ratio |
Year_2010 | GINI Index value for the country in 2010 | number | level : Ratio |
Year_2011 | GINI Index value for the country in 2011 | number | level : Ratio |
Year_2012 | GINI Index value for the country in 2012 | number | level : Ratio |
Year_2013 | GINI Index value for the country in 2013 | number | level : Ratio |
Year_2014 | GINI Index value for the country in 2014 | number | level : Ratio |
Year_2015 | GINI Index value for the country in 2015 | number | level : Ratio |
Year_2016 | GINI Index value for the country in 2016 | number | level : Ratio |
Year_2017 | GINI Index value for the country in 2017 | number | level : Ratio |
Year_2018 | GINI Index value for the country in 2018 | number | level : Ratio |
Year_2019 | GINI Index value for the country in 2019 | number | level : Ratio |
Year_2020 | GINI Index value for the country in 2020 | number | level : Ratio |
Year_2021 | GINI Index value for the country in 2021 | number | level : Ratio |
Data Preview
Country Name | Country Code | Region Name | Income Group | Special Notes | Year 1981 | Year 1982 | Year 1983 | Year 1984 | Year 1985 | Year 1986 | Year 1987 | Year 1988 | Year 1989 | Year 1990 | Year 1991 | Year 1992 | Year 1993 | Year 1994 | Year 1995 | Year 1996 | Year 1997 | Year 1998 | Year 1999 | Year 2000 | Year 2001 | Year 2002 | Year 2003 | Year 2004 | Year 2005 | Year 2006 | Year 2007 | Year 2008 | Year 2009 | Year 2010 | Year 2011 | Year 2012 | Year 2013 | Year 2014 | Year 2015 | Year 2016 | Year 2017 | Year 2018 | Year 2019 | Year 2020 | Year 2021 |
Aruba | ABW | Latin America & Caribbean | High income | ||||||||||||||||||||||||||||||||||||||||||
Africa Eastern and Southern | AFE | 26 countries, stretching from the Red Sea in the North to the Cape of Good Hope in the South (https://www.worldbank.org/en/region/afr/eastern-and-southern-africa) | |||||||||||||||||||||||||||||||||||||||||||
Afghanistan | AFG | South Asia | Low income | The reporting period for national accounts data is designated as either calendar year basis (CY) or fiscal year basis (FY). For this country, it is fiscal year-based (fiscal year-end: March 20). Also, an estimate (PA.NUS.ATLS) of the exchange rate covers the same period and thus differs from the official exchange rate (CY). In addition, the World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. In this country, multiple or dual exchange rate activity exists and must be accounted for appropriately in underlying statistics. An alternative estimate (âalternative conversion factorâ - PA.NUS.ATLS) is thus calculated as a weighted average of the different exchange rates in use in the country. Doing so better reflects economic reality and leads to more accurate cross-country comparisons and country classifications by income level. For this country, this applies to the period 1960-2006. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors. | |||||||||||||||||||||||||||||||||||||||||
Africa Western and Central | AFW | 22 countries, stretching from the westernmost point of Africa, across the equator, and partly along the Atlantic Ocean till the Republic of Congo in the South (https://www.worldbank.org/en/region/afr/western-and-central-africa) | |||||||||||||||||||||||||||||||||||||||||||
Angola | AGO | Sub-Saharan Africa | Lower middle income | The World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. In this country, multiple or dual exchange rate activity exists and must be accounted for appropriately in underlying statistics. An alternative estimate (âalternative conversion factorâ - PA.NUS.ATLS) is thus calculated as a weighted average of the different exchange rates in use in the country. Doing so better reflects economic reality and leads to more accurate cross-country comparisons and country classifications by income level. For this country, this applies to the period 1994-2021. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors. | 52.0 | 42.7 | 51.3 | ||||||||||||||||||||||||||||||||||||||
Albania | ALB | Europe & Central Asia | Upper middle income | 27.0 | 31.7 | 30.6 | 30.0 | 29.0 | 34.6 | 32.8 | 33.7 | 33.1 | 30.1 | 30.8 | |||||||||||||||||||||||||||||||
Andorra | AND | Europe & Central Asia | High income | ||||||||||||||||||||||||||||||||||||||||||
Arab World | ARB | Arab World aggregate. Arab World is composed of members of the League of Arab States. | |||||||||||||||||||||||||||||||||||||||||||
United Arab Emirates | ARE | Middle East & North Africa | High income | 32.5 | 26.0 | ||||||||||||||||||||||||||||||||||||||||
Argentina | ARG | Latin America & Caribbean | Upper middle income | The World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. In this country, multiple or dual exchange rate activity exists and must be accounted for appropriately in underlying statistics. An alternative estimate (âalternative conversion factorâ - PA.NUS.ATLS) is thus calculated as a weighted average of the different exchange rates in use in the country. Doing so better reflects economic reality and leads to more accurate cross-country comparisons and country classifications by income level. For this country, this applies to the period 1971-2018. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors. | 42.8 | 45.3 | 46.8 | 45.5 | 44.9 | 45.9 | 48.9 | 49.5 | 49.1 | 50.7 | 49.8 | 51.1 | 53.3 | 53.8 | 50.9 | 48.4 | 47.7 | 46.3 | 46.2 | 44.9 | 43.7 | 43.6 | 42.6 | 41.3 | 40.9 | 41.6 | 42.0 | 41.1 | 41.3 | 42.9 | 42.3 |