noviembre 10, 2020

What’s new about Income Inequality in Latin America?

Inequality in Latin America Revisited: Insights from Distributional National Accounts

In this issue brief, Mauricio De Rosa, Ignacio Flores, and Marc Morgan describe their preliminary findings from the new Latin American income inequality series presented in the November 2020 update on They find that income inequality in Latin America is very high and is underestimated in official measures based solely on survey data. The authors complement survey data with tax data and national accounts to provide a more accurate picture of the true inequality level in Latin America.  Finally, they stress the importance of significantly increasing the quality of the data on income and wealth in the region and welcome comments and feedback from the research community on this on-going project.

Key Results

  • In Latin America, the top 10% captures 54% of the national income, making it one of the most unequal regions in the world.
  • Chile, Mexico, and Brazil are the 3 most unequal countries in the region, with the top 10% share capturing respectively 60%, 58%, 57% of the average national income (2019).
  • Data shows a decline in inequality since 2000 in Ecuador, Argentina, and Uruguay, with the top 10% share capturing respectively 38%, 40%, and 42% of the national income (2019).
  • Significant data inconsistencies are found in many countries, which need to be clarified and studied along with local data producers (especially on national accounts). Data quality is highly heterogeneous in the region.

>> Click here to access the regional data

Figure – Income Inequality in Latin America 

This figure shows the evolution of the pretax top 10% income shares for several countries in Latin America, since 2000.

Income Inequality in Latin America




  • Mauricio De Rosa (PSE; EHESS):
  • Ignacio Flores (WIL; INSEAD):
  • Marc Morgan (PSE; WIL)

Media inquiries

  • Olivia Ronsain:; +33 7 63 91 81 68



The author gratefully acknowledges funding from the European Research Council (ERC Grant 856455) from the French National Research Agency (EUR Grant ANR-17-EURE-0001), as well as from the United Nations Development Program (Project 00093806).