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Wealth & Income Inequality

How the Gini Coefficient Measures Inequality

The single number economists most often use to summarize how unequal an economy's income or wealth distribution is.

The Gini coefficient is a single number, ranging from 0 to 1, that summarizes how evenly income or wealth is distributed across a population. A value of 0 represents perfect equality - everyone has exactly the same amount - while a value of 1 represents perfect inequality, where a single person or household holds everything and everyone else has nothing. Real economies always fall somewhere in between.

How the number is actually built

The Gini coefficient is derived from a Lorenz curve, a graph plotting the cumulative share of total income or wealth held by the bottom X% of the population. A perfectly equal distribution produces a straight diagonal line on that graph. The more the actual curve bows away from that diagonal line, the more unequal the distribution, and the higher the resulting Gini coefficient.

Comparing two countries with the number

A country with a Gini coefficient of 0.25 has a considerably more even income distribution than a country with a Gini coefficient of 0.55 - the second country's income is concentrated much more heavily among a smaller share of the population. This single number lets economists compare inequality across very different countries and time periods using one consistent scale.

What the Gini coefficient doesn’t capture

A single summary number necessarily loses detail: two countries can have an identical Gini coefficient while having very different underlying distributions - one might have widespread modest inequality, while another has a small ultra-wealthy group alongside broad equality everywhere else. The Gini coefficient also says nothing about the absolute standard of living - a very equal but very poor country and a less equal but wealthier country can produce surprisingly similar scores.

Treating the Gini coefficient as the full picture

Comparing two countries by Gini coefficient alone, without also considering absolute income levels, poverty rates, and the shape of the underlying distribution, can lead to a misleadingly simple conclusion. The Gini coefficient is a useful single summary statistic, not a complete substitute for a fuller analysis.

Key takeaways
  • The Gini coefficient ranges from 0 (perfect equality) to 1 (perfect inequality).
  • It's derived from a Lorenz curve comparing actual distribution to a perfectly equal line.
  • It allows consistent comparison of inequality across different countries and time periods.
  • It's a useful summary number, but doesn't capture the full shape of a distribution or absolute living standards.
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