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Evidence on Gender Wage Discrimination in Portugal: parametric and semi-parametric approaches

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Author Info
Aurora Galego () (Department of Economics, University of Évora)
João Pereira () (Department of Economics, University of Évora)

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Abstract

In this paper we use two alternative approaches to study the extent of gender wage discrimination in Portugal. Both methods involve the estimation of wage equations for males and females and the Blinder [1973] and Oaxaca [1973] decomposition. However, to take into account possible sample selection bias, we consider both parametric and semi-parametric methods. First, we consider a parametric approach that relies on distributional assumptions about the distribution of the error terms in the model (Vella (1992, 1998) and Wooldridge (1998)). Within this approach, if the distributional assumption is not satisfied, the parameters’ estimates may be inconsistent. Secondly, we apply Li and Wooldridge [2002] semi-parametric estimator, which does not assume any known distribution on the joint distribution of the errors of the wage equation and of the sample selection equation; the distribution has an unknown form and is estimated through non-parametric kernel techniques. We employ micro data for Portugal from the European Community Household Panel (ECHP). The results from both approaches provide evidence in favour of the existence of gender wage discrimination in Portugal. However, the extent of labour market discrimination decreases when sample selection bias corrections are taken into account.

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Publisher Info
Paper provided by University of Évora, Department of Economics (Portugal) in its series Economics Working Papers with number 13_2006.

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Length: 17 pages
Date of creation: 2006
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Handle: RePEc:evo:wpecon:13_2006

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Find related papers by JEL classification:
J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods

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This page was last updated on 2009-11-22.


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