Dataset

Global and regional Gini coefficients of income inequality

Publishing date
09 February 2024
Authors
Zsolt Darvas
Man in the street being given money (black and white picture)

Latest update: 9 February 2024

This dataset includes updated global and regional Gini coefficient of income inequality estimates from the paper:

Darvas, Zsolt (2019), ‘’, World Development 121, 16-32.

An earlier version of this work has been published as:

Indicators of income distribution, such as quantile income shares and the Gini coefficient, are available for individual countries, but from official statistical sources they are not available for the world as a whole or for various country groups.

This dataset includes annual data from 1988-2021 (or 1980-2021 for EU15 countries) on global and regional Gini coefficient estimates, using various methodologies, for the following country groups:

  • 145 countries
  • 37 Advanced countries
  • 108 Emerging and developing countries
  • 13 Non-EU advanced countries
  • 17 Emerging and developing Asian countries and ASEAN-5
  • 32 Sub-Saharan African countries
  • 12 Commonwealth of Independent States countries
  • 28 European Union countries (current members plus the UK)
  • 27 European Union countries (current members)
  • 15 European Union countries (members before 2004)
  • 13 European Union countries (members joined in 2004-13)
  • 20 Euro area countries (current members)
  • 19 Euro area countries (first 19 members)
  • 24 Latin American and the Caribbean countries
  • 12 Middle East and North African countries

The dataset also includes the deconstruction of the change in global and regional Gini coefficients of net income inequality into three main components: (1) within-country inequality, (2) differences in mean incomes (between-country inequality), and (3) relative population size.

This page provides a number of Bruegel datasets for public use. Users can freely use our data in its unchanged form or after any transformation for any purpose and can freely distribute it, provided that proper attribution is made to the source, but not in any way that suggests that Bruegel endorses the user or their use of the data.

About the authors

  • Zsolt Darvas

    Zsolt Darvas is a Senior Fellow at Bruegel and part-time Senior Research Fellow at the Corvinus University of Budapest. He joined Bruegel in 2008 as a Visiting Fellow, and became a Research Fellow in 2009 and a Senior Fellow in 2013.

    From 2005 to 2008, he was the Research Advisor of the Argenta Financial Research Group in Budapest. Before that, he worked at the research unit of the Central Bank of Hungary (1994-2005) where he served as Deputy Head.

    Zsolt holds a Ph.D. in Economics from Corvinus University of Budapest where he teaches courses in Econometrics but also at other institutions since 1994. His research interests include macroeconomics, international economics, central banking and time series analysis.

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