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Working Papers
The dynamics of racial inequality in human capital formation in Brazil
Joint with Naercio Menezes-Filho, Ana M. B. Menezes, Helen Gonçalvez, and Fernando C. Wehrmeister
Using data that follows the same cohort from birth up to age 18, we document racial patters of human capital formation in Brazil across the life-cycle. We analyze racial differences in birth weight, years of schooling and socioemotional skills.
Descriptive representation in politics: a measurement proposal and application for Brazil
Joint with Sergio Firpo, Michael França, Leila Pereira, and Rafael Tavares
This paper develops a new measure of descriptive representation in politics. It takes as inputs the minority share in the electorate and among representatives. Contrary to other disproportionality measures, our index attains the upper bound in more usual situations. Our empirical exercises uses Brazilian electoral data to measure racial imbalances in Brazilian states' legislative bodies and in the National Congress.
Work in Progress
Wage Volatility in Brazil
Joint with Sergio Firpo and Pedro Souza
Using short panel data from Brazil, we investigate patterns of wage volatility between 2012 and 2021.
Poverty Dynamics in Brazil
Joint with Solange Gonçalves, Pedro Souza, Rafael Osório
Using short panel data from Brazil, we investigate patterns of poverty dynamics between 2012 and 2021.
Racial Gaps in Earnings: The Role of Private Education, Technical Schooling and Advanced Graduate Levels
Joint with Michael França
Using data from Brazil, we investigate importance of different levels of education in explaining racial gaps in earnings. Years of schooling, together with a host of other controls, explain a great share of racial earnings inequality in Brazil. However, including other forms of education apart from formal schooling are also important. We show that advanced graduate programs, especially specialization courses, are relevant. Moreover, attending private high-schools also explain part of racial differences in earnings. These effects are most important at the top of the earnings distribution.
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