Gini Index

Understanding the Gini Index: A Concise Guide to Income Inequality

Key takeaways
* The Gini index measures income or wealth inequality on a scale from 0 (perfect equality) to 1 (perfect inequality); it is often expressed as 0–100.
* Wealth Gini values tend to be higher than income Gini values because wealth is more concentrated and harder to measure.
* Global inequality has risen over long historical periods; estimates put the world Gini near 0.67 in recent decades, with COVID-19 contributing to a notable single-year rise.
* The Gini index is a useful summary statistic but has important data and interpretive limitations.

What the Gini index is
The Gini index (or Gini coefficient) was introduced by Corrado Gini in 1912 to quantify how income (or wealth) is distributed across a population. A value of 0 means everyone has exactly the same income; a value of 1 (or 100 if scaled that way) means one person has all the income and everyone else has none.

How it is calculated (intuition)
The Gini index is most commonly visualized using the Lorenz curve, which plots cumulative population (x-axis) against cumulative income (y-axis). The 45-degree line represents perfect equality. The Gini coefficient equals the area between the line of perfect equality and the Lorenz curve divided by the total area under the line of perfect equality — equivalently, twice the area between the line and the curve. In simple terms, the farther the Lorenz curve bows away from the equality line, the higher the Gini.

Examples and interpretation
* 0 (or 0%): perfect equality.
* 0.5 (or 50%): a widely used reference point indicating substantial inequality — as of 2024, only a small number of countries have Gini values at or above this level.
* 1 (or 100%): perfect inequality.

Country snapshots
* South Africa: among the highest recorded income Gini values (about 63.0%), reflecting extreme income disparities stemming from historical and structural factors.
* Norway: an example of low inequality (about 22.7%).
* United States: a relatively high Gini for a developed economy (about 39.8%), driven by factors such as technological change, globalization, declining unionization, and wage pressures at the bottom.

Global trends
Historical and recent estimates indicate rising global inequality over the long term. Long-run series show increases during the 19th and 20th centuries; recent estimates place the global Gini in the mid-0.6 range. Major shocks and epidemics have tended to widen inequality: analyses suggest epidemics can raise the Gini over subsequent years, and the COVID-19 pandemic produced one of the largest single-year increases in recent history.

Why the distinction between income and wealth matters
Most published Gini figures refer to income because income data are more readily available. Wealth distribution is typically much more unequal, but wealth data are harder to collect and are often obscured by tax havens and reporting gaps. Thus, wealth Ginis are higher and less precisely measured than income Ginis.

Limitations and cautions
* Data quality: The Gini’s accuracy depends on reliable income and wealth data. Shadow economies and underreporting—especially in developing countries—can distort estimates.
* Single-number summary: Different underlying distributions can produce the same Gini value; the index hides details such as where inequality is concentrated (bottom, middle, top).
* Lack of demographic breakdown: The Gini does not show how inequality varies by age, gender, race, region, or household type.
* Comparability issues: Differences in survey methods, tax and transfer systems, and whether Gini is measured for pre- or post-tax/post-transfer income affect cross-country comparisons.
* Interpretation nuance: Two countries with identical Gini coefficients may have very different average living standards—low inequality in a poor country is not the same as low inequality in a rich country.

When to use the Gini index
Use the Gini index as a starting point for comparing levels of inequality across time or between regions. It is helpful for tracking broad trends and highlighting changes that merit deeper investigation. Complement the Gini with other measures (e.g., shares of income held by top deciles, Palma ratio, poverty rates) and with demographic breakdowns to get a fuller picture.

Conclusion
The Gini index is a compact and widely used measure of income or wealth inequality. It provides a quick summary of distributional patterns and is useful for monitoring trends and prompting policy discussion. However, it should be interpreted with caution and supplemented with richer data and additional metrics to understand the causes, consequences, and specific nature of inequality in any given context.