Economic Inequality

Tracking the incomes of the richest: data from the World Inequality Database Inequality of what? Why WID and survey-based data measure different things

Public attention to economic inequality has grown a lot over the last twenty years. Alongside, the available data has greatly improved too: estimates now cover many more countries and longer time periods, and new international databases have helped make the data more comparable and much more accessible. Where our view was once limited to individual countries, we can increasingly take a global perspective on inequality.

At the same time, the wide range of sources and metrics now available can be difficult to navigate. There are many different approaches to measuring inequality, each with its own strengths and weaknesses, and it can be hard to know how they relate — or where to start.

This page is designed to make the range of inequality data easier to understand. Here you’ll find all our data, charts, and writing on economic inequality, organized around three key international databases: the World Bank’s Poverty and Inequality Platform, the Luxembourg Income Study, and the World Inequality Database.

Taken together, this data shows that inequality in many countries is very high and, in many cases, has been rising . Globally, the gaps between the poorest and richest are extremely large and are compounded by overlapping inequalities in health, education, and many other dimensions.

But it also shows that inequality is not rising everywhere. Global income inequality — measured across the world’s population as a whole — has fallen in recent decades , driven in particular by rapid economic growth in parts of Asia. And within many individual countries, income inequality has fallen in recent decades or remained stable.

This variation across countries tells us something important that is often missed: high and rising inequality is not inevitable. Through their institutions and policy choices, individual countries can affect the level of inequality among their citizens. Inequality is not purely determined by global forces beyond our control; it is something that we can change.

The World Bank’s Poverty and Inequality Platform (PIP) publishes data for almost all countries in the world, based on a large collection of national survey data. To achieve such wide coverage, it pools data from two kinds of surveys. For high-income countries, the data measures people’s incomes after taxes and benefits. For most low- and middle-income countries, it instead measures their consumption. These two concepts are closely related but not the same. 1

The big strength of the World Bank dataset is the global perspective it provides. It gives us a picture of how much people have to live on all across the world, from the richest to the poorest, and everyone in between. 2

When thinking about inequality, what people often have in mind is the level of inequality within a given country. What the World Bank’s global data shows is that this inequality within individual countries is just one part of the story. In addition, there are also large inequalities between countries: the citizens of some countries are much better off than the citizens of others. Below, we take a look at both kinds of inequality.

Measures of inequality try to capture how evenly or unevenly economic resources are spread, or “distributed” across the population.

One commonly used measure is the Gini coefficient . Although popular, a downside of the measure is that it is not very easy to interpret. Often, it’s more intuitive to compare incomes at particular points in the distribution.

Aside: We explain how the Gini works in more detail in Measuring inequality: what is the Gini coefficient? That’s the approach taken in the chart below. For six different countries, it shows the ratio between the 90th percentile and the 10th percentile. These are the income levels that mark the thresholds for the richest and poorest tenth of the population, respectively. The 90th percentile is the income that just puts someone inside the top 10%. The 10th percentile is the income that just puts someone inside the bottom 10%.

The ratio of these two numbers — the “P90/P10 ratio” — gives us a measure of inequality that’s easy to interpret. It tells us how many times richer a person just inside the bottom 10% would have to be to just enter the top 10%. The bigger the ratio, the bigger the gap separating the richest and poorest tenth.

In the United States, there’s a 7-fold gap between the incomes marking the richest tenth and the poorest tenth. In Germany, the gap is much lower: 4.5-fold. In Brazil, inequality is much higher — more than twice as large as in Germany, with a 10-fold gap.

The data for Angola, Vietnam, and Madagascar refers to consumption rather than income. 3 Looking within these three countries, we again see inequality varies hugely. The relative gap between the top and bottom tenth in Angola is twice as big as it is in either Madagascar or Vietnam.

These large differences demonstrate a basic, but important insight. Inequality varies widely across countries, even among countries with similar levels of economic development, technology adoption, or exposure to global markets. These factors can all play a role, but they do not wholly determine inequality — far from it. 4

The variation we see suggests that inequality is not simply dictated by forces beyond a country’s control. Through the institutions they build and the policies they adopt, countries can take different paths that lead to higher or lower levels of inequality.

The ratios in the chart above show us the different levels of inequality that exist within these countries. But they miss out on something important: the huge income differences that exist between the countries. Being in the richest or poorest tenth within a country means something very different depending on whether you live in a rich or a poor country.