Gini Coefficient Calculator
Paste any set of income, wealth, or value figures (separated by commas or spaces) and this calculator returns the Gini coefficient on a 0-to-1 scale, constructs the Lorenz curve, breaks down shares by quintile, and flags how your result compares to real-world inequality benchmarks. Results update as you type.
Formula
Worked example
Five households with incomes 10,000, 20,000, 30,000, 50,000, 90,000. Total = 200,000. Sorted cumulative shares: (20%, 5%), (40%, 15%), (60%, 30%), (80%, 55%), (100%, 100%). Area B under the Lorenz curve via trapezoids = 0.335. Gini = 1 - 2 x 0.335 = 0.330.
What is the Gini coefficient?
The Gini coefficient (also called the Gini index or Gini ratio) is a statistical measure of distribution developed by the Italian statistician Corrado Gini in 1912. It measures how evenly a resource - most commonly income or wealth - is spread across a population. A Gini of 0 represents perfect equality, where every person holds an identical share. A Gini of 1 represents maximum concentration, where one person holds everything. In practice, national income Gini values range from about 0.24 (highly equal Scandinavian economies) to about 0.63 (South Africa, one of the most unequal countries measured). The index is dimensionless, so it can compare distributions of any size or unit.
How the Gini coefficient is calculated
The standard method uses the Lorenz curve - a graph that plots the cumulative share of population (ordered from lowest to highest income) on the x-axis against the cumulative share of income on the y-axis. Perfect equality is the diagonal line from (0,0) to (1,1). Any real distribution bows below that line, creating an area A between the line and the curve. The area under the Lorenz curve is B. The Gini coefficient is A / (A + B), which simplifies to G = 1 - 2B. This calculator estimates B by dividing the sorted data into trapezoidal slices - a standard numerical approach that produces the exact result for any finite dataset.
Quintile analysis and the top-10% share
A single Gini number condenses the full distribution into one figure, which makes it easy to compare but hides structural detail. Quintile analysis divides the sorted population into five equal groups (each 20%) and reports each group's share of total income. The bottom quintile's share reveals how the poorest fifth fare; the top quintile's share shows concentration at the top. The top-10% share is an even finer lens on concentration, because many studies find that the 90th-to-100th percentile drives the bulk of inequality growth in recent decades. The bottom-50% share rounds out the picture: in the United States it hovers around 11-12%, while in Scandinavian countries it can reach 20-22%.
Limitations and context
The Gini coefficient has well-known limitations. Two distributions can share the same Gini yet look very different - one might have inequality concentrated at the top, another at the bottom. It is sensitive to how income is defined: market income (before taxes and transfers) Ginis are typically 0.05-0.10 higher than disposable income Ginis in developed countries, because redistribution compresses the distribution. Household size adjustments, regional price differences, and whether capital gains are included all affect the result. For richer comparisons, economists pair the Gini with Palma ratios (top-10% share divided by bottom-40% share), Atkinson indices, or Theil indices. Despite these caveats, the Gini remains the most widely reported and internationally comparable single measure of inequality.
Gini coefficient benchmarks by country (income, recent estimates)
| Country / Region | Approx. Gini | Inequality level |
|---|---|---|
| Slovakia, Slovenia | 0.24-0.25 | Very Low |
| Denmark, Norway | 0.26-0.28 | Very Low |
| Sweden, Finland | 0.27-0.29 | Low |
| Germany, Austria | 0.30-0.32 | Low |
| France, Canada | 0.31-0.33 | Low |
| Australia, United Kingdom | 0.34-0.36 | Moderate |
| United States | 0.39-0.41 | Moderate-High |
| China | 0.38-0.42 | Moderate-High |
| Mexico | 0.43-0.46 | High |
| Brazil | 0.49-0.52 | High |
| Colombia | 0.51-0.54 | Very High |
| South Africa | 0.60-0.65 | Very High |
Approximate Gini coefficients based on national statistical agencies and World Bank data. Values vary by year and methodology.
Frequently asked questions
What is a good Gini coefficient?
There is no single "good" value, but most economists consider a Gini below 0.30 to represent low inequality. Nordic countries achieve values in the 0.26-0.30 range. OECD countries average around 0.32-0.34. Values above 0.40 are widely seen as high inequality, and above 0.50 as extreme. The context matters: a Gini of 0.38 for wealth is considered modest inequality, whereas the same value for income would be toward the high end for a developed economy.
What is the Lorenz curve?
The Lorenz curve is a graph that shows the cumulative share of income (or wealth) held by the cumulative share of the population, ordered from poorest to richest. The 45-degree diagonal represents perfect equality. The further the Lorenz curve bows below that line, the greater the inequality. The Gini coefficient is exactly twice the area between the diagonal and the Lorenz curve.
How many data points do I need?
You need at least two values to compute a Gini, but the result is most meaningful with 10 or more observations. With very small samples - say, five to ten households - the Gini can be unstable, jumping significantly when a single value changes. For national-level estimates, statistical agencies typically use microdata from hundreds of thousands of households. For small-group analysis (a classroom, a company pay scale, a set of five countries), interpret the result with appropriate caution.
What is the difference between the Gini coefficient and the Gini index?
They are the same measure with different scaling. The Gini coefficient is expressed as a decimal between 0 and 1. The Gini index is the same number multiplied by 100, expressed as a percentage between 0 and 100. The World Bank reports the Gini index; academic papers more often use the coefficient form. This calculator shows both.
Can I use this for wealth inequality rather than income?
Yes. The Gini coefficient measures any distribution, including net wealth, land holdings, market shares, test scores, or biodiversity counts. Wealth Ginis are typically much higher than income Ginis because wealth accumulates over generations and is more concentrated. The United States wealth Gini is around 0.85-0.87, compared to an income Gini of about 0.39.
Why does the Gini not capture all aspects of inequality?
The Gini collapses the entire distribution into one number. Two distributions with the same Gini can differ substantially: one might have a concentrated top, another a compressed bottom. It is also insensitive to transfers within an income band that do not cross the mean. Economists therefore pair it with complementary measures such as the Palma ratio (top-10% share divided by bottom-40% share), which better captures recent trends in top-end concentration, or the Atkinson index, which can weight inequality at different points in the distribution.