Gini Index

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What is the 'Gini Index'

The Gini index is a measurement of the income distribution of a country's residents. This number, which ranges between 0 and 1 and is based on residents' net income, helps define the gap between the rich and the poor, with 0 representing perfect equality and 1 representing perfect inequality. It is typically expressed as a percentage, referred to as the Gini coefficient.


The Gini coefficient is an important figure for the analysis of relative poverty within a country or region, but it should not be mistaken for a measurement of wealth. A wealthy country and a poor country can have the same Gini coefficient, as long as they have similar income distributions.

Graphical Representation

The Gini coefficient is often represented graphically as the area between the Lorenz curve and a line of equality. The Lorenz curve is also a graphical representation of income distribution, plotting cumulative income shares relative to cumulative population shares. For example, the chart would could show that the poorest 80% of the population takes in 50% of total income. The Lorenz curve and Gini coefficient can also be altered to reflect wealth rather than income, though wealth is often more difficult to measure than income.

Gini Coefficients Around the World

The world Gini index is estimated around 0.52 as of 2016, marking a slight decline from a peak near 0.545 in the early 2000s. The index is well above the levels displayed in the 1970s, when Gini was estimated below 0.47. Economic expansion in Latin America, Eastern Europe and the ex-Soviet countries drove much of this recent improvement. Gini coefficients and per-capita gross domestic product (GDP) exhibit negative correlation. Less developed countries tend to lack a large middle class, with limited industrialization hampering the ability of many to earn a regular wage. South Africa is a notably high Gini nation, with a 0.625 coefficient estimated in 2013. European nations such as Denmark, Slovenia, Sweden and Ukraine have the most even income distributions, with coefficients below 0.25.


Though useful for the purpose of inequality analysis, the Gini coefficient has some shortcomings that require attention. The metric's accuracy is dependent on reliable GDP and income data. Shadow economies and informal economic activity are present in every country, and these transactions tend to represent a larger portion of true economic production in developing countries. As a result, these are not reflected in official GDP figures, which leads to inaccurate data. Inaccurate GDP data threatens the reliability of the Gini index. Further, very different income distributions can result in identical Gini coefficients, because the index measures aggregate distribution. Gini lacks the granularity to explain variations among subgroups within the distribution. Demographics can also lead to natural income inequalities, with large retired populations pushing the Gini higher.

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