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Global Income Inequality: Rich Nations Overestimate How Poor the World Is

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Global Income Inequality: Rich Nations Overestimate How Poor the World Is

2026-07-27 07:37 UTCBy AlphaScala Research DeskSource reporting: ourworldindata.orgEditorial standards

Global Income Inequality: Rich Nations Overestimate How Poor the World Is

Global median income is $290 a month, half the world lives on less. Data shows rich nations vastly overestimate how poor the rest of the world is.

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The gap between the world's richest and poorest people is far wider than most people in wealthy countries realize, according to data from the World Bank's Poverty and Inequality Platform.

The global median income in 2026 is $290 per month, or a little under $10 a day. Half the world's population lives on less than that amount. That income level is far below what even the poorest tenth of people in high-income countries earn.

A study by political economist Gautam Nair showed that Americans overestimate the global median income by a factor of ten. The World Bank data helps correct that misperception.

The data covers 172 countries. It shows that incomes at the top of the global distribution have risen much more in absolute terms than incomes at the bottom. From 1990 to 2026, the income threshold for the richest 10% rose by about $18 per person per day. The threshold for the poorest 10% rose by only about $1.80.

In percentage terms, the picture is different. The incomes of the poorest 10% and the global median have more than doubled since 1990. That growth lifted hundreds of millions of people out of extreme poverty. The rise for the richest 10% was about half in proportional terms.

How inequality varies within countries

Inequality within individual countries also varies widely, and the data shows that high inequality is not inevitable.

In the United States, there is a 7-fold gap between the income that marks the richest tenth and the poorest tenth. In Germany, the gap is 4.5-fold. In Brazil, it is 10-fold.

These differences exist even among countries with similar levels of economic development or exposure to global markets. Economist Tony Atkinson argued that comparing these different paths across countries can help identify causes. The fact that the UK saw a steep rise in inequality in the late 1980s while the US saw a more gradual increase over the same period, despite both facing similar global pressures, points to the role of national institutions and policy choices.

The limits of survey data

Household surveys are the most common source of inequality data, but they have a known blind spot at the very top of the income distribution. The extremely rich are few in number, less likely to participate in surveys, and their income from investments and business ownership tends to be undercounted. This is sometimes called the "missing rich" problem.

To address this, researchers use tax records and national accounts data. The World Inequality Database (WID) combines these sources to estimate how a country's total national income is distributed. The WID data shows that in Brazil, the richest 1% received over a quarter of all income before taxes and benefits in 2022. In the Netherlands, that figure was around 7%.

Even within the richest 1%, income is highly concentrated. In the US, the richest 0.1% received about 10% of national income in 2024, almost as much as the rest of the richest 1% combined.

The WID approach has trade-offs. It uses a broader concept of income that includes undistributed corporate profits and imputed rent for homeowners. These are not income in the usual sense that people can spend. The data also requires many assumptions, especially for countries where the underlying data is missing. The WID team describes its estimates for those countries as "imperfect and provisional."

Which data source to use

The different databases each have strengths. The World Bank data gives the widest global coverage, using a mix of income and consumption data. The Luxembourg Income Study (LIS) prioritizes comparability across countries by harmonizing survey definitions, but covers only 52 countries. The WID dataset provides the best view of top incomes but uses a more technical income concept.

All three sources agree on one central point: global inequality is extremely large, and the gap between the richest and poorest is compounded by overlapping inequalities in health, education, and opportunity.