Gini Coefficient
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The Gini coefficient is a statistical measure that shows how income or wealth is distributed among people in a given area. Its value ranges from 0 to 1 (sometimes expressed as 0 to 100). A value of 0 means everyone has equal income, while a value of 1 means all income goes to a single person. Therefore, as the coefficient rises, inequality increases.
The measure is named after Italian statistician Corrado Gini, who introduced this method in the early 20th century. Today it is used to compare different countries and to track changes over time within a single country. Organizations such as the World Bank and national statistical agencies employ it.
How it is calculated
The calculation is based on the Lorenz curve, a graph showing what percentage of total income is held by what percentage of the population, starting from the poorest. If perfect equality existed, the curve would be a straight diagonal line at 45 degrees. The Gini coefficient is the ratio of the area between the equality line and the Lorenz curve to the total area under the equality line. It can also be calculated as the average difference between every pair of individuals.
Uses and interpretation
Most Western and Northern European countries have low Gini coefficients, while countries outside this region show higher values, particularly some in Latin America and Southern Africa. It is important to note that a coefficient calculated using income before tax and transfers (market income) differs from one calculated using income after tax and social support (disposable income). Comparing the two types shows the effect of tax and welfare policies.
Limitations
The Gini coefficient is a single number, which means it does not show where inequality comes from. Two countries with the same Gini coefficient can have different actual distributions—for example, one with a large middle class and one split into two groups. It also does not indicate poverty levels, nor does it show inequality between genders, regions, or age groups. The data used—typically household surveys—may have errors, especially when the income of the highest-earning groups is not fully reported.