Gini Coefficient
Also known as: Gini index, Gini ratio, Gini concentration ratio, G
The Gini coefficient is the most widely used single-number summary of inequality in a distribution such as income or wealth. Introduced by the Italian statistician Corrado Gini in 1912, it equals twice the area between the Lorenz curve and the line of perfect equality, ranging from 0 when everyone has the same amount to a maximum approaching 1 when one unit holds everything.
Key highlights
- Single, scale- and population-size-invariant number enabling broad comparison across countries and over time.
- Intuitive geometric and pairwise-difference interpretations.
- Bounded on [0,1) with a clear meaning at both ends.
- Decomposable by income source via the covariance form, and widely tabulated for almost every country.
Intuition
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How it works
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When to use it
Use the Gini coefficient for a compact, scale-invariant summary of inequality in any nonnegative distribution — income, wealth, land, firm size — when a single comparable number is wanted and the Lorenz dominance is not strictly required. It is the lingua franca of inequality comparison across countries and time. It is less suitable when you need sensitivity to a particular part of the distribution (the Gini is most sensitive to the middle and can be insensitive to extreme tails), when distributions' Lorenz curves cross (the single number can mislead), or when an explicit social-welfare interpretation with a tunable inequality-aversion parameter is desired (use the Atkinson index). It should not be applied to distributions with negative values without adjustment.
Strengths & limitations
- Single, scale- and population-size-invariant number enabling broad comparison across countries and over time.
- Intuitive geometric and pairwise-difference interpretations.
- Bounded on [0,1) with a clear meaning at both ends.
- Decomposable by income source via the covariance form, and widely tabulated for almost every country.
- Most sensitive to changes around the middle of the distribution and relatively insensitive to the extreme tails.
- Two very different distributions can share the same Gini; it is uninformative when Lorenz curves cross.
- Not cleanly decomposable into between- and within-group components (unlike entropy measures) because of an overlap term.
- Carries no explicit social-welfare or inequality-aversion parameter, unlike the Atkinson index.
Common pitfalls
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Applications
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Frequently asked
What does a Gini of 0.4 mean?
It is a scale-free index of how unequal a distribution is, with 0 meaning everyone has the same amount and values near 1 meaning near-total concentration. A Gini of 0.4 indicates moderate-to-high inequality; for context, disposable-income Ginis cluster around 0.25–0.35 in the most egalitarian welfare states and reach 0.5 or higher in the most unequal countries. The number is comparable only when the same income concept and unit are used.
Why can two countries with the same Gini have different inequality?
The Gini summarizes the entire Lorenz curve in a single number, so distributions whose Lorenz curves cross can yield the same value while differing in where the inequality lies — one concentrated at the top, another at the bottom. When Lorenz curves cross there is no unambiguous inequality ranking, and a single index like the Gini may obscure the difference. Reporting tail-sensitive measures (Atkinson, Palma) alongside it helps.
Is the Gini decomposable across subgroups?
Not cleanly. Unlike the generalized entropy (Theil) family, the Gini does not split exactly into between-group and within-group parts: a decomposition leaves a residual 'overlap' or interaction term that arises when subgroup distributions overlap. For exact additive subgroup decomposition, entropy-based measures are preferred; the Gini does, however, decompose neatly by income source.
Sources
- 1.Ceriani, L., & Verme, P. (2012). The origins of the Gini index: extracts from Variabilità e Mutabilità (1912) by Corrado Gini. The Journal of Economic Inequality, 10(3), 421–443.
- 2.Lorenz, M. O. (1905). Methods of measuring the concentration of wealth. Publications of the American Statistical Association, 9(70), 209–219.
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Cite this page
ScholarGate. (2026, June 22). Gini Coefficient. ScholarGate. https://scholargate.app/sociology/gini-coefficient