Global Economic Inequality

OWID presents work from many different people and organizations. When citing this entry, please also cite the original data source. This entry can be cited as:

Max Roser (2016) – ‘Global Economic Inequality’. Published online at Retrieved from: [Online Resource]

This data entry is concerned with the inequality of global interpersonal income.

# Empirical View

# Global divergence followed by convergence – Economic history in one chart

This chart shows the distribution of the annual income between all world citizen. To make incomes comparable across countries and across time the annual incomes are measured in International Dollars – this is a currency that would would buy a comparable amount of goods and services a U.S. dollar would buy in the United States in 1990.

The distribution of incomes is shown at 3 points in time:

  • In 1820 only few countries achieved economic growth. The chart shows that the majority of the world lived in poverty with an income similar to the poorest countries in Africa today (around 500 International Dollars). The data entry on global poverty shows that in 1820 between 85% and 95% of the world lived in absolute poverty.
  • In the year 1950, 150 years later, the world has changed – it became very unequal. The world income distribution has become bimodal. It has the shape of a camel. One hump at around 500 International Dollars and a second hump at around 5,000 International Dollars – the world was divided into a poor developing world and a 10-times richer developed world.
  • Over the following 3 decades the world income distribution has again changed dramatically. The poorer countries, especially in South-East Asia, have caught up. The two-humped camel shaped has changed into a one-humped dromedar shape. World income inequality has declined. And not only is the world more equal again, the distribution has also shifted to the right – the world is much richer.
# World income distribution, 1820, 1970 and 20001

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# Global income inequality increased for 2 centuries and is now falling

The visualization below shows the distribution of incomes between 1988 and 2011. The data was compiled by the economists Branko Milanovic and Christoph Lakner.2
To see the change over time select the years just above the distribution.
The previous visualization that showed the the change from the year 1820 to the year 2000 is based on estimates of inflation-adjusted average incomes per country (GDP per capita) and a measure of income inequality within a country only. It gives us a rough idea of how the distribution of incomes changed, but it is not very detailed and not very precise. In contrast to this the work by Branko Milanovic and Christoph Lakner is based on much more detailed household survey data. This data is measuring household income at each decile of the income distribution and the two authors used this information to arrive at the global income distribution. The downside of this approach is that we can only go as far back in time as household surveys were conducted.
The visualization shows the end of the long era in human history in which global inequality was increasing. Starting with the industrialization in North-Western Europe incomes in this part of the world started to increase while material prosperity in the rest of the world remained low. While some countries followed the European industrialization – first Northern America, Oceania, and parts of South America and later Japan and East Asia – other countries in Asia and Africa remained poor. As a consequence of this global inequality increased over a long period of time. Only in the period shown in the visualization below did this change: With rapid growth in much of Asia in particular did the global distribution of incomes become less unequal. The incomes of the poorer half of the world population rose faster than the incomes of the richer half of the world population.

Global Income Distribution 1988 to 20113

If you want to use this visualisation for a presentation or for teaching purposes etc. you can download a zip folder with an image file for every year and an animated .gif here.

# The latest data on global inequality and a look into the future

The visualisation below show how the global income distribution has changed over the decade up to 2013. Tomáš Hellebrandt and Paolo Mauro – the authors of paper4 from which this data is taken – are confirming the finding that global inequality has declined: the Gini coefficient of global inequality has declined from 68.7 to 64.9.

The visualisations above show the income distribution on a logarithmic x-axis. This chart in contrast plots incomes on a linear x-axis and thereby emphasizes how very high global inequality still is: The bulk of the world population lives on very low incomes and the income distribution stretches out very far to the higher incomes at the right-hand side of the chart; and incomes over 14,000 international-$ are cut off as they would make this chart with a linear x-axis unreadable.

A second striking and very positive global development shown in this chart is the rise of the global median income. In 2003 half of the world population lived on less than 1,090 international-$ per year and the other half lived on more than 1,090 international-$. This level of global median income has has almost doubled over the last decade and was 2,010 international-$ in 2013.

Finally the authors also dare to make a projection of what global inequality will look like in 2035. Assuming the growth rates shown in the insert in the top-right corner the authors project global inequality to decline further and to reach a Gini of 61.3. At the same time the incomes of the world’s poorer half will continue to increase strongly so that global median income will again double and reach 4,000 international-$ in 2035.

# The global income distribution in 2003, 2013, and the projection for 20355


If you are looking for a visualisation of only the observed global income distribution in 2003 and 2013 you find it here.

# How global inequality has changed from 2003 to 2013

The following visualisation offers an alternative view on the data by Hellebrandt and Mauro6 shown in the chart before.

You see the yearly disposable income for all world citizens in both 2003 and 2013. On the x-axis you see the position of an individual in the global distribution of incomes and on the logarithmic y-axis you see the annual disposable income at that position.

The increase in prosperity – and decrease of poverty – is substantial. The income cut-off of the poorest 10% has increased from 260 international-$ to 480 international-% and the median income has almost doubled from 1,100 international-$ to 2,010. Global mean income in 2013 is 5,375 international-$.7

# The global income distribution in 2003 and 20138


# Global income inequality is still very high and will stay very high for a long time

The visualisation below presents the same data in the same way except that the y-axis is now not logarithmic but linear. In this perspective the still very high level of global inequality is shown even more clearly.

The previous and the following visualisation show how very high global income inequality still is: The cut-off to the richest 10% of the world in 2013 was 14,500 int-$; the cut-off for the poorest 10% was 480 int-$. The ratio is 30.2.

While global inequality is still very high we are now living in a period of falling inequality: In 2003 this ratio was 37.6. The Gini coefficient has also fallen from 68.7 to 64.9.

Taking the historical experience as a guide for what is possible in the future we have to conclude that global inequality will remain high for a long time. To see this we can ask how long it will take for those with incomes at the poorest 10% cutoff to achieve the current incomes of the richest 10% cutoff which is 14,500 international-$. This income level is roughly the level of GDP per capita above which the poverty headcount gets close to 0% for most countries (see here).

How long does it take for incomes to grow from 480$ to 14,500$?

2% growth 172.1 years
4% growth 86.9 years
6% growth 58.5 years
8% growth 44.3 years
10% growth 35.8 years

Even under a very optimistic scenario it will take several decades for the poor to reach the income level of the global top 10%.

2% is roughly the growth rate that the richest countries of today experienced over the last decades (see here). We have seen that poorer countries can achieve faster growth, but we have not seen growth rates of more than 6% over a time frame as long as necessary to reach the level of the global 10% in such a short time. If the past is a good guide for the future the world will very likely be highly unequal for a long time.

# The global income distribution in 2003 and 20139


# Inequality within countries and inequality between countries

Global inequality is driven by changes both of the inequality within countries and the inequality between countries. This visualisation shows how both of these changes determined the changing global inequality.

– Inequality within countries followed a U-shape pattern over the course of the 20th century.

– Inequality between countries increased over the course of 2 centuries and reached its peak level in the 1980s according to the data from Bourguignon and Morrison shown here. Since then inequality between countries has declined.

As is shown in the visualisation just below the inequality of incomes between different countries is much higher than the inequality within one country. The consequence of this is that the trend of global inequality is very much driven by what is happening to the inequality between countries.

# Global inequality between world citizens and its components 1820-199210

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# Within-country income percentiles vs world income percentiles by country – Milanovic (2010)11


# Maps – Current World Income Distribution

# World map of GDP per square km – Gallup and Sachs (1999)12
World-Map-of-GDP-per-square-km– Gallup-and-Sachs-(1999)

# World GDP density map, 1990 and 2025 – SEDAC (NASA)13

World GDP Density Map 1990 and 2025 – SEDAC (NASA)0

# Economic Convergence between Countries

# Strong convergence in Europe, 1950-2006 – World Development Report (2009)14

Strong Convergence in Europe between 1950 and 2006 – World Development Report (2009)

# Annual real GDP growth in poorer and richer countries, 1961-2013 – Max Roser15

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# GDP accumulated change, 1990-2006 – Wikipedia (originally from the IMF)16
GDP accumulated change (1990-2006) – Wikipedia (from IMF originally)

# Past Level of GDP and Subsequent Growth

# Growth vs initial income (population-weighted) – Sala-i-Martin (2006)17
Growth Versus Initial Income (Population-Weighted) – Sala-i-Martin (2006)

# Growth of Given Size by Time – Speed of Catching up

# Years for income per capita to grow from $2,000 to $4,000 (1990$ US) – Aghion & Durlauf [Eds.] (2006)18
Years for income per capita to grow from 2,000 to 4,000 (1990$ US) – Aghion & Durlauf [Eds.] (2006)

# Number of years for GDP per person to double, 1700-2040 – The Economist19
Number of years for GDP per person to double (1700-2040) – The Economist

# The changing geography of the global economy

# Shares of world GDP (% of world total), 1700-2030 – Max Roser20

# The world’s shifting economic center of gravity, 1 CE – 2025 CE – Oxford Martin School (2013)21
The world's shifting economic centre of gravity (1 CE - 2025 CE) – Oxford Martin School (2013)

# Present World and Future

Wikipedia’s list of estimates of real gross domestic product growth rate for the latest available year is here.

# Data Quality & Definition

# Growth convergence vs absolute income convergence, 1990-2003 – Todaro & Smith (2011)22
Growth Convergence versus Absolute Income Convergence (1990 to 2003) – Todaro & Smith (2011)
The already mentioned study by Sudhir Anand and Paul Segal is a very good review of this topic.23

# Total and between inequality: comparisons of different studies – Liberati (2013)24

Total-and-Between-Inequality-–-Comparisons-of-different-Studies-– Liberati-(2013)0

# Data Sources

# Clio-Infra Database
  • Data: Various economic and social indicators, including income inequality
  • Geographical coverage: Global
  • Time span: Depends on indicator being used
  • Available at: Online here