Skip to navigationSkip to content
UNEQUAL MEASURES

The main metric economists use to measure inequality is deeply flawed

A photograph of a fancy swimming pool with illustrations of the Lorenz curve superimposed over it.
Reuters/Gaston De Cardenas; Illustration Amanda Shendruk
A great equalizer?
  • Amanda Shendruk
By Amanda Shendruk

Visual journalist

Published Last updated on

In 2015, Greece, Thailand, Israel, and the UK were equally unequal. That is, all four countries had the same Gini coefficient, a common measure of income inequality.

The number suggests that the spread of incomes in the four nations was the same. However, a closer look at the poorest and wealthiest people in those societies shows a very different picture of inequality. The ratio between income held by the richest 10% and the poorest 10% ranged significantly from 13.8 in Greece to 4.2 in the UK.

This divergence has provoked some economists to argue the Gini should be put back in its bottle, while others defend its continued use. Most concede, though, that as a way to understand inequality, the century-old indicator is insufficient on its own.

What is the Gini Coefficient?

The Gini coefficient is the most well-known measure of income inequality. A Gini coefficient of zero means there is an equal distribution of income, whereas a number closer to one indicates greater inequality. The lower the Gini coefficient, the more equal the society is said to be.

The Gini Coefficient and the Lorenz Curve

The Gini coefficient builds on work by Max Lorenz, an early twentieth-century American economist, who established a way of charting the distribution of income in a population called the Lorenz curve.

The Gini coefficient’s appeal comes from its simple-to-understand range of 0 to 1, and its aim to encapsulate a complex distribution in a single figure. That makes it easy to use it as a basis of comparison across countries with vastly different population sizes.

“People love a single number. It’s neat in that it’s a measure of the whole of the income distribution,” says Dominic Webber, head of household income analysis at the UK’s Office for National Statistics (ONS). “There’s more going on than that number can convey, but nonetheless it’s really strong and powerful” to have a single number, he says.

Perhaps most important to its success is its widespread and continued use. Calculations of the Gini are regularly published and updated by international organizations and countries, including the OECD, the World Bank, and the International Monetary Fund.

“A lot of countries use it, so you can quite quickly and easily get an internationally comparable measure,” explains Webber

What’s wrong with the Gini Coefficient?

The World Inequality Database, one of the world’s leading sources of income inequality data with a network of researchers around the world, stays away from the Gini coefficient. The organization sees problems with any indictor that tries to summarize inequality into a single figure, according to Thomas Blanchet, an economist there.

On the Gini specifically, he and the ONS’ Webber note a few main issues:

  1. It is more sensitive to changes in the middle class, than for the extremes of the rich or poor.
  2. The single figure provides very little detail into a country’s inequality
  3. It has little meaning on its own, without some other context.
  4. It provides the same value for different manifestations of inequality.
  5. It is hard to explain.

“The downside of the Gini coefficient compared to some other measures, is that the number on its own doesn’t necessarily mean a huge amount…It’s only when you compare over time or with other countries that you get a sense of what it means,” says Webber. “You may observe a change in the Gini coefficient but that doesn’t tell you much more than inequality has increased or decreased…Have the rich got richer? Have the poorest got poorer?”

Other ways to measure income inequality

One of the biggest problems with the Gini coefficient is simply that too many groups rely on the statistic alone. Other yardsticks may be more revealing.

Commonly used indicators include:

Income of the top 1%: The share of the total amount of income held by the top 1% of earners.

P90/P10: The ratio of the income of person at the top tenth percentile of the income distribution to the income of the person at the bottom tenth percentile. For the US this number is around six, meaning the lowest income of the highest-earning 10% of households is more than six times that of the highest income of the lowest-earning 10% of households.

S80/S20 ratio: The ratio of the cumulative income of the highest earning 20% of people to the cumulative income of the lowest earning 20%.

The Palma Ratio: The ratio of the richest 10% of the population’s share of the gross national income (GNI) divided by the share of the poorest 40%. As you might expect, middle-class incomes typically account for about half of a country’s GNI, with the other half split between the lowest-earning 40% and highest-earning 10%. A Palma Ratio of 1, for example, means the cumulative income of the top 10% and bottom 40% are the same.

The World Inequality Database prefers to compare the share of total income held by various groups; like the top 1%, top 10%, middle 40%, and the bottom 50%. “The idea is that, if you know the share of those three or four groups, you basically have a pretty comprehensive picture of what’s happening to inequality and then you don’t really need to make a single indicator of it,” explains Blanchet.

The ONS includes multiple measures beyond the Gini coefficient in its releases about income inequality. It’s “important to have a broader range of measures” Webber told Quartz, “to really give a fuller picture of what’s going on.”

📬 Need to Know: COP26

Your guide to the world's biggest climate summit.

By providing your email, you agree to the Quartz Privacy Policy.