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Race, Gender and Poverty: Evidence from Brazilian Data

Yeutseyeva, Sasha and Deguilhem, Thibaud (2022): Race, Gender and Poverty: Evidence from Brazilian Data.

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Abstract

Race and gender are commonly considerated as two of the most important structural factors associated with unequal socioeconomic systems. Previous research has found that these factors are significant for explaining the income inequality in Latin America and particularly in Brazil. This study aims to address whether both determinants predict an individual’s chances of being in poverty in Brazil, using national dataset and articulating different econometric strategies. Overall, being a woman had a small positive impact on an individual’s predicted chance of poverty and only in a probability linear specification. We think that this result does not align well with previous literature because of the selection bias affecting women labor market participation. However, evidence of strong and robust racial differenciation in Brazil was present. Discussing the representativeness of the sample, this study highlights the importance of data quality as well as the relevance of using various statistical methods.

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