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Regressão Quantílica com Correção Para a Seletividade Amostral: Estimativa dos Retornos Educacionais e Diferenciais Raciais na Distribuição de Salários das Mulheres no Brasil

Listed author(s):
  • Danilo Coelho
  • Róbert Veszteg
  • Fabio Veras Soares

Este texto estima os retornos educacionais e diferenciais raciais na distribuição de salários das mulheres no Brasil, usando regressão quantílica com correção semiparamétrica para viés de seleção amostral. As estimativas mostram que os retornos educacionais são elevados e que não são constantes ao longo da distribuição salarial. Tanto os retornos educacionais quanto os diferenciais raciais são mais elevados nos pontos mais altos da distribuição de salário condicional, o que indica, no caso dos diferenciais raciais, que as mulheres negras enfrentam um teto de vidro nos níveis salariais mais altos. Para os diferenciais por anos de estudo, questões como a qualidade da educação podem ser um fator importante na explicação da desigualdade salarial entre as mulheres. O texto revela que o uso de uma especificação probit para a equação de participação, a fim de corrigir problemas de seleção, produz resultados muito semelhantes à correção semiparamétrica tanto para os retornos educacionais quanto para a discriminação racial. Palavras-chave: discriminação de gênero; discriminação racial; regressão quantílica; correção de seleção não paramétrica. We estimate the returns to education for women and the racial wage differential among women over the wage distribution in Brazil by using quantile regression with semiparametric correction for sample selection. Our estimates show that the returns to education are high and that they are not constant along the wage distribution. Both returns to education and the racial wage differentials are higher at higher points of (the conditional) wage distribution. Black women seem to be facing a glass-ceiling in the higher wage segment of the distribution. In addition, quality of education seems also to play some role in the inequality observed among higher paid women. The paper also reveals that using a probit specification to the participation equation in order to correct selection issues yields very similar results to the semiparametric correction for both returns to education and racial discrimination. Keywords: gender discrimination; racial discrimination; quantile regression; nonparametric selection correction.

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Paper provided by Instituto de Pesquisa Econômica Aplicada - IPEA in its series Discussion Papers with number 1483.

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Length: 25 pages
Date of creation: Apr 2010
Handle: RePEc:ipe:ipetds:1483
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