Measuring and Understanding Income Inequality

Core Idea

Income inequality is measured by Gini coefficients, Lorenz curves, and percentile shares. High inequality imposes economic costs through reduced social cohesion, political instability, and potentially reduced growth. Developing countries show substantial variation—Latin America exhibits high inequality despite moderate income levels while East Asia shows lower inequality, demonstrating that development paths and policy choices shape distributional outcomes.

Explainer

From your understanding of GDP and national income, you know that aggregate measures like GDP per capita tell you how much income a country produces on average — but averages can be deeply misleading. A country where ten people each earn $10,000 and a country where one person earns $91,000 and nine earn $1,000 have the same GDP per capita, but they are fundamentally different economies with different social dynamics, political pressures, and development prospects. Income inequality measurement provides the tools to look inside the average and understand how income is actually distributed.

The most intuitive tool is the Lorenz curve. To build one, rank every person in the population from poorest to richest along the horizontal axis (as cumulative percentages), and plot the cumulative share of total income they hold on the vertical axis. If income were perfectly equal, the Lorenz curve would be a 45-degree line — the bottom 20% would hold 20% of income, the bottom 50% would hold 50%, and so on. In practice, the curve bows below this line: the bottom 20% might hold only 5% of income while the top 20% holds 50%. The further the curve bows from the 45-degree line, the more unequal the distribution.

The Gini coefficient converts the Lorenz curve into a single number between 0 (perfect equality) and 1 (one person holds all income). It equals the area between the Lorenz curve and the 45-degree line, divided by the total area under the 45-degree line. A Gini of 0.25 (typical of Scandinavian countries) means relatively compressed incomes; a Gini of 0.60 (typical of South Africa or parts of Latin America) indicates extreme concentration. Percentile ratios offer a complementary view: the 90/10 ratio compares income at the 90th percentile to income at the 10th, capturing the gap between rich and poor without being sensitive to extreme outliers. The Palma ratio (share of the top 10% divided by share of the bottom 40%) has gained popularity because the middle 50% of the distribution tends to be stable across countries — most of the action is in the tails.

Why does inequality matter for development, beyond fairness? High inequality can suppress growth through several channels. It reduces social cohesion and trust, making collective action and public investment harder. It creates political instability — extreme inequality breeds resentment, corruption, and rent-seeking that divert resources from productive use. It can reduce human capital accumulation if poor households cannot invest in education and health. And it weakens domestic demand — when most income flows to a small elite, consumer markets remain thin, limiting opportunities for firms that serve mass markets. The wide variation in inequality across developing countries — Latin America persistently high, East Asia relatively low — shows that inequality is not an inevitable consequence of being poor. It reflects historical legacies (colonial land distribution, racial exclusion), policy choices (progressive taxation, public education, land reform), and the structure of growth itself (whether growth creates broad-based employment or concentrates gains in resource extraction and finance).