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Gini Coefficient by Country Map

Attribution 4.0 International (CC BY 4.0)The World Bank
Global developmentearthcountryginigini-coefficient

What is The Gini Coefficient?

The Gini coefficient is a measure used in economics to express the level of inequality in a distribution, such as income or wealth distribution within a population. It is a number between 0 and 1, where 0 corresponds to perfect equality (everyone has the same income) and 1 corresponds to perfect inequality (one person has all the income, and everyone else has none). The coefficient is calculated based on the Lorenz curve, which graphs the proportion of the total income of a population that is cumulatively earned by the bottom x% of the population. The Gini coefficient is essentially the ratio of the area that lies between the line of equality and the Lorenz curve over the total area under the line of equality. A higher Gini coefficient means greater inequality. For instance, a Gini coefficient of 0.3 implies a fairly equitable distribution of income, while a coefficient of 0.7 indicates high inequality. When expressed as a percentage, the Gini Coefficient is expressed from 0 - 100, so 0.3 is equivalent to 30% and so forth.



Gini Coefficient Analysis - 2022

  • Countries with High Inequality: Countries like South Africa, Namibia, and Suriname have some of the highest Gini coefficients reported, with South Africa at 63, Namibia at 59.1, and Suriname at 57.9. These values indicate a high level of income inequality.
  • Countries with Low Inequality: On the other end of the spectrum, nations like Slovenia (24), Slovakia (23.2), and Belarus (24.4) show some of the lowest levels of income inequality according to their Gini coefficients.
  • Middle Range: Many countries fall somewhere in between, such as the United States (39.8), China (37.1), and India (34.2), indicating moderate levels of income inequality.
  • Recent Data: The data for some countries is very recent, with Bangladesh, Bhutan, and Ecuador having Gini coefficients reported for the year 2022.
  • Older Data: Conversely, there are countries for which the most recent data is quite old. For example, Belize's last Gini index data is from 1999, and Azerbaijan's from 2005, which may not accurately reflect current conditions.
  • Geographical Trends: There's a noticeable trend where Latin American and African countries often have higher Gini coefficients, typically associated with greater inequality, whereas European countries often have lower Gini coefficients, suggesting more equitable income distribution.
  • Variations Over Time: The most recent year of data collection varies significantly by country, which suggests that the data may not be fully comparable across all countries at the same point in time.

It's important to note that while the Gini coefficient provides insight into income inequality, it does not give reasons for the inequality or information about absolute income or poverty levels. Moreover, differences in data collection methods and the years of data reported can affect the comparability of the Gini coefficient across countries.