A visual, step-by-step introduction to the world's most widely used measure of income inequality.
Imagine you live in a country with just 5 people. If everyone earned exactly the same income, that would be perfect equality. If just one person earned everything and the other four earned nothing, that would be perfect inequality.
The Gini coefficient is a single number between 0 and 1 (or 0 and 100 when expressed as a percentage) that tells you where a population sits on this spectrum — whether income is distributed more equally or more unequally. It was invented by the Italian statistician Corrado Gini in 1912. The "population" can be a country (like Sweden), a region, a city, or any group of people.
Both countries have the same total income — €100,000 — but distribute it very differently:
Same total wealth, completely different distribution. The Gini captures this difference in one number. We'll keep following these two countries throughout this guide. But how is the Gini actually calculated? To understand that, we first need one simple concept: cumulative shares.
The trick behind the Gini is to transform raw incomes into two running totals that we can compare against each other. Here's how it works:
First, we rank all 5 people from the lowest income to the highest. Then, going person by person, we calculate two cumulative (running-total) shares: what percentage of the total population have we counted so far, and what percentage of the total income have they earned together?
| Person | Income | Cum. % Pop. | Cum. % Income |
|---|---|---|---|
| P1 | €20k | 20% | 20% |
| P2 | €20k | 40% | 40% |
| P3 | €20k | 60% | 60% |
| P4 | €20k | 80% | 80% |
| P5 | €20k | 100% | 100% |
The two cumulative columns grow at the same rate — perfectly equal.
| Person | Income | Cum. % Pop. | Cum. % Income |
|---|---|---|---|
| P1 | €5k | 20% | 5% |
| P2 | €5k | 40% | 10% |
| P3 | €5k | 60% | 15% |
| P4 | €5k | 80% | 20% |
| P5 👑 | €80k | 100% | 100% |
The bottom 80% earn only 20% of income — the income column lags far behind.
Now let's turn those tables into a picture. We put the cumulative share of the population on the x-axis and the cumulative share of income on the y-axis. Each row from the table becomes a point on the graph, and connecting them gives us a curve. This is the Lorenz Curve, named after the American economist Max Lorenz who introduced it in 1905.
For Equaland, the two shares always match (20% = 20%, 40% = 40%, etc.), so the curve is a straight diagonal line — the line of equality. For Unequaland, the income share lags behind the population share, so the curve sags below the diagonal. The more it sags, the more unequal the distribution.
Click the buttons below to see our two imaginary countries and then compare them to real-world distributions:
Notice how the curve sags further from the diagonal as inequality increases. The area of that gap between the diagonal and the curve is exactly what the Gini coefficient measures. But how do we turn a shape on a graph into a single number? That's what Part 4 explains.
Look at the diagram below. The space between the line of equality (the diagonal) and the Lorenz curve is coloured in red — we call it area A. Everything below the Lorenz curve is coloured in blue — area B. Together, A and B fill the entire triangle beneath the diagonal.
The Gini coefficient is simply the ratio of the gap (area A) to the whole triangle (A + B):
This is why the Gini always falls between 0 and 1:
The Lorenz curve is the diagonal.
Area A = 0, so there's no gap.
The Lorenz curve hugs the bottom-right corner.
Area A fills the whole triangle (= ½).
You'll see Gini on a 0–1 scale (as a coefficient, e.g. 0.29) or a 0–100 scale (as an index, e.g. 29). They mean the same thing — just multiply by 100. Eurostat and most policy reports use 0–100; many academic papers use 0–1.
Now that we understand what the Gini measures and how it's calculated, let's look at real data. This map shows Eurostat's Gini coefficients for equivalised disposable income across the EU in 2024. Hover over the dots to explore.
Sorted from most equal (lowest Gini) to least equal (highest Gini).
The Gini coefficient gives you a single, comparable number for any population — you can instantly see that Slovakia (21.7) distributes income more evenly than Bulgaria (38.4). Because it's standardised and tracked over time by institutions like Eurostat and the World Bank, it's a powerful tool for comparing inequality across countries, regions, or time periods.