@TechReport{iza:izadps:dp18367,
            	author={Ferreira, Francisco H. G. and Peragine, Vito and Brunori, Paolo and Salas-Rojo, Pedro and Moramarco, Domenico and Barajas, Luis and Barbieri, Teresa and Daza-Baez, Nancy and Datt, Gaurav and Sandi, Vito de and Farella, Fabio and Jr, Arturo Martinez and Nguyen, John and Park, Albert and Simeone, Enza and Sirugue, Louis and Torres-Lopez, Pedro and Zotti, Giorgia},
            	title={Global Estimates of Opportunity and Mobility: A Database},
            	year={2026},
	month={Feb},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={18367},
            	url={https://www.iza.org/publications/dp18367},
	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 high-income 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},
            }