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Original Articles

The evolution of the returns to education and wage differentials in Brazil: a quantile approach

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Pages 1453-1460 | Published online: 30 Oct 2009
 

Abstract

This paper uses quantile regression techniques to analyze the returns to education across the conditional distribution of wages from individuals separated both by gender and skin color, while accounting for the endogeneity of the education decisions. Using data from the Brazilian households survey (PNAD) for the years of 1988 and 1996, the results indicate that the returns to education are significantly heterogeneous across the distribution of earnings, as well as the wage gap between the groups, according to gender and skin color. Moreover, there has been a significant improvement in the wage differentials between the groups across the years.

Acknowledgements

The authors would like to thank an anonymous referee for valuable comments. The usual disclaimer applies. Professor Biderman gratefully acknowledges the financial support of FAPESP, grant 2004/03327-1.

Notes

1See Arias et al. (Citation2001) for more details.

2One of the central issues concerning the Brazilian labour market is the fact that a great part of the working force, due to high cost associated to working in the formal sector choose to work in the informal sector. This control assumes a value of 1 if the individual works in the formal sector and 0 otherwise.

3See Arias et al . (Citation2001) for details about the properties of this estimator. The covariance matrix was obtained via bootstrapping with 400 replications.

4Values are expressed in Reais from July of 2003.

5See, for instance, Buchinsky (Citation1994), Machado and Mata (Citation2001) and Hartog et al. (Citation2001).

6Following Buchinsky (Citation1995), this test is performed after an interquantile regression, which re-estimates the model taking the difference between the coefficients across the wage distribution β kθ1  − β kθ2  = 0, where θ1 and θ2 are two distinct quantiles and β k refers to the coefficient on regressor k.

7See Ferreira et al . (Citation2006) for a more detailed discussion on this issue.

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