Economics
Income Inequality Measurement and the Gini Coefficient
Quick fact
The Gini coefficient is zero if everyone has exactly the same income and 1 if one person has everything. Most countries fall between 0.25 and 0.65, with Denmark around 0.28 and South Africa around 0.63.
Why this is interesting
When you hear 'the top 1% own more than the bottom 90%,' how do economists capture that whole picture in a single number? The Gini coefficient turns the messy reality of income inequality into a neat 0-to-1 scale.
Read the full explanation
Understanding Income Inequality Measurement and the Gini Coefficient
Imagine lining up all households from poorest to richest (horizontal axis) and then plotting the cumulative percentage of total income they hold (vertical axis). This line is called the Lorenz curve. If income were perfectly equal, the poorest 20% would hold 20% of income, the poorest 50% would hold 50%, and so on—that would be a straight diagonal line from (0,0) to (1,1). In reality, the poorest people hold a smaller share, so the Lorenz curve bows downward. The Gini coefficient measures how far the actual Lorenz curve is from that perfect-equality diagonal. Specifically, it's the area between the diagonal and the Lorenz curve, divided by the total area under the diagonal. This gives a number between 0 (perfect equality) and 1 (perfect inequality). The larger the area, the more unequal the distribution.
A deeper explanation
The Gini coefficient is not just a random statistic—it's a geometric measure of dispersion. Its power lies in its ability to summarize a whole distribution in a single comparable figure. It also has an intuitive connection to pairwise income comparisons: the Gini is essentially half of the relative mean absolute difference between all pairs of incomes in the population. This means a Gini of 0.3 tells you that, on average, two randomly chosen individuals differ by about 60% of the mean income. Because it is a relative measure, it is scale-invariant: doubling everyone's income does not change the Gini. That makes it perfect for comparing countries with different currencies or for tracking inequality over time even as economies grow. However, it has limitations: it is insensitive to where in the distribution the inequality occurs (a transfer from the middle to the very rich produces a similar change as a transfer from the poor to the middle), and it can be sensitive to how data are collected (surveys versus tax records, household versus individual income). Recognizing these caveats is essential for interpreting Gini values correctly.