Global estimates of opportunity and mobility: a database

Francisco H. G. Ferreira, Vito Peragine, Paolo Brunori, Pedro Salas Rojo, Domenico Moramarco, Luis Barajas Prieto, Teresa Barbieri, Nancy Daza Baez, Gaurav Datt, Vito de Sandi, Fabio Farella, Arturo Martinez , John Nguyen, Albert Park, Enza Simeone, Louis Sirugue, Pedro Torres Lopez and Giorgia Zotti

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: This paper describes a new public-access online database containing internationally comparable estimates of inequality of opportunity for seventy-two countries, covering two-thirds of the world’s population. The estimates were computed directly from the unit-record microdata for 196 household surveys, using a suite of machine-learning tools selected to minimize the omitted variable and overfitting biases discussed in the literature. Overall, differences in opportunities account for substantial shares of total income inequality (with the mean of our preferred estimate being 40.9%), but there is substantial variation across countries, with estimates ranging from 18.9% in Denmark (2011) to 76.7% in South Africa (2017). The latest US estimate of 41.6% places it among the most opportunity unequal highincome countries. We also find strong support for the existence of a positive association between income inequality and relative inequality of opportunity, analogous to the “Great Gatsby Curve” for mobility and inequality. Similarly, there is evidence of an inverted-U “Opportunity Kuznets curve”. The database is available at www.geom.ecineq.org.

Keywords: inequality of opportunity; mobility; machine learning (search for similar items in EconPapers)
JEL-codes: D31 D63 I39 (search for similar items in EconPapers)
Pages: 52 pages
Date: 2026-01-11
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