The Gini index measures economic inequality in a country. Specifically, it is the extent to which the distribution of income (or, in some cases, consumption expenditure) deviates from a perfectly equal distribution among individuals or households within an economy. A Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.
The Gini index dataset was released by the World Bank. This data is reported at a national level with global coverage. Data is updated annually and is available for the years 1967-2018, though most countries only have data for a subset of these years.
The Gini Index was calculated from the World Bank’s internationally comparable poverty monitoring database, which draws on income or detailed consumption data from more than 1,000 household surveys across 138 countries in 6 regions and 21 other high-income countries (industrialized economies). To calculate the Gini index, 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 (45-degree) line of absolute equality, expressed as a percentage of the maximum area under the line. For full documentation, please see the source methodology.
2012, 2013, 2014, 2015, 2016 Gini Index: The Gini Index measures inequality in a country, defined as the extent to which the distribution of income among individuals or households within an economy deviates from a perfectly equal distribution. A Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality. Data shown represents the Gini Index for the indicated years.
Additional data for every year between 1990 and 2016 is available from the data provider. Please see Learn More button to find this data on the source website. This data has been mapped on Resource Watch by joining it with Natural Earth boundaries.
Excerpts of this description page were taken from the source metadata. Resource Watch shows only a subset of the dataset. For access to the full dataset and additional information, click on the “Learn more” button.
Gini index (World Bank estimate)
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; that is, the total Gini of a society is not equal to the sum of the Gini for its subgroups. Thus country-level Gini coefficients cannot be aggregated into regional or global Ginis, 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 is not strictly comparable across countries or even across years within a country. Two sources of noncomparability 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 is 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.