How the Gini Coefficient Measures Income Inequality

One Number to Capture an Economy's Fairness—and Its Limits

In 1912, Italian statistician Corrado Gini published a paper titled "Variability and Mutability" in which he proposed a simple mathematical measure for statistical dispersion. Applied to income distributions, his coefficient—now universally called the Gini coefficient—compresses the entire income distribution of a country or region into a single number between 0 and 1. A Gini of 0 means perfect equality: every person has identical income. A Gini of 1 means perfect inequality: one person receives all income and everyone else receives nothing. No real economy sits at either extreme. The United States posted a Gini coefficient of approximately 0.49 for income before taxes and transfers in 2023. Norway posted approximately 0.26. South Africa—one of the world's most unequal countries—has recorded Ginis consistently above 0.62. The measurement is precise. What it tells you about fairness, welfare, and policy is considerably less simple.

The Lorenz Curve: The Geometry Behind the Number

The Gini coefficient is a summary of the Lorenz curve, a graphical representation of income distribution introduced by American economist Max Lorenz in 1905. Constructing a Lorenz curve requires four steps:

1. Rank all households or individuals from lowest to highest income
2. Calculate the cumulative share of the population (x-axis: 0% to 100%)
3. Calculate the cumulative share of total income received by that share of the population (y-axis: 0% to 100%)
4. Plot the resulting curve against the 45-degree "line of perfect equality"

The line of perfect equality is a straight diagonal: the bottom 20% of the population receives exactly 20% of income, the bottom 50% receives exactly 50%, and so on. Any real income distribution falls below this line—the bottom 20% of earners always receive less than 20% of total income. The further the Lorenz curve bows below the line of perfect equality, the more unequal the distribution.

The Gini coefficient is the ratio of the area between the line of perfect equality and the Lorenz curve (area A) to the total area under the line of perfect equality (areas A + B). Gini = A / (A + B). A higher coefficient means a larger gap between actual distribution and perfect equality—more inequality.

Why the US Number Has Multiple Values

The U.S. Gini coefficient appears differently depending on what is measured. The U.S. Census Bureau's Current Population Survey measures market income (before taxes and transfers) and disposable income (after taxes and government transfers) separately—and produces substantially different Gini estimates for each.

• Market income Gini: Approximately 0.49–0.51. This measures what people earn before government intervention—wages, salaries, capital gains, business income. It captures the distribution of economic rewards in the private sector.
• Disposable income Gini: Approximately 0.39. After accounting for taxes paid and government transfers received (Social Security, Medicare, Medicaid, SNAP, tax credits), inequality is significantly reduced. The U.S. tax and transfer system reduces the Gini by about 0.10–0.12 points.
• OECD adjusted Gini: The OECD typically reports the U.S. Gini as approximately 0.39–0.41, using post-tax-and-transfer income, making international comparisons more meaningful.

The choice of which measure to report is not purely technical—it carries political implications. Critics of U.S. inequality tend to emphasize market income Ginis; defenders of U.S. redistribution tend to emphasize disposable income Ginis. Both are measuring real things; they are measuring different things.

Income vs. Wealth: A Much Larger Gap

Income—annual earnings from labor and capital—is distinct from wealth—accumulated assets minus liabilities. Wealth is dramatically more concentrated than income in most countries, and wealth Gini coefficients are correspondingly much higher.

Sweden's wealth Gini is higher than its income Gini by more than Sweden's income Gini in absolute terms—a counterintuitive finding that reflects how pension assets are counted (or excluded) and how capital is distributed in wealthy societies regardless of income distribution. The wealth Gini for the United States, at approximately 0.85, means the wealth distribution is far closer to perfect inequality than any income measure suggests. The top 1% of U.S. households hold approximately 31% of total household wealth; the bottom 50% hold approximately 3%.

What the Gini Cannot Tell You

The Gini coefficient has several well-documented limitations that make it insufficient as a standalone measure of inequality or welfare.

• Same Gini, different distributions: Multiple different income distributions can produce an identical Gini coefficient. A society where the poor are clustered at the bottom and a large middle class exists can have the same Gini as one with no middle class and a small wealthy elite—but very different welfare implications.
• No absolute income information: A Gini of 0.40 in a country with per capita income of $60,000 implies very different material conditions than a Gini of 0.40 in a country with per capita income of $5,000. The coefficient captures distribution, not level.
• Sensitivity varies across the distribution: The Gini is most sensitive to changes in the middle of the income distribution and less sensitive to extreme changes at the very top or very bottom. It can miss increases in very high-end inequality that other measures (top income shares, Palma ratio) capture better.
• No interpersonal welfare comparison: A high Gini country might have very high social mobility—children can move across the distribution across generations. A low Gini country might have low mobility. The Gini measures a snapshot; mobility measures across-time dynamics that the snapshot cannot capture.

Supplementary Measures Economists Use

Because of these limitations, economists rarely rely on the Gini alone when analyzing inequality. Common supplementary measures include:

• Top income shares: The share of total income received by the top 1%, 10%, or 0.1% of earners. In the U.S., the top 1% received approximately 19% of pre-tax income in 2022 (World Inequality Database).
• Palma ratio: The ratio of the top 10%'s income share to the bottom 40%'s share. Less sensitive to middle-distribution noise; better captures elite-to-poor comparisons.
• 90/10 ratio: The income of a household at the 90th percentile divided by income at the 10th percentile. Intuitive and easy to interpret for policy purposes.

The Gini coefficient is a useful starting point. It summarizes a distribution in one number, enables quick international comparisons, and has a century of methodological consistency. What it measures precisely, it measures well. What it cannot measure—absolute living standards, intergenerational mobility, distributional shape—requires additional tools. Numbers this neat always require more questions.