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Gender Wage Gap : A Semi-Parametric Approach With Sample Selection Correction

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  • Picchio, M.

    (Tilburg University, School of Economics and Management)

  • Mussida, C.

Abstract

Sizeable gender differences in employment rates are observed in many countries. Sample selection into the workforce might therefore be a relevant issue when estimating gender wage gaps. This paper proposes a new semi-parametric estimator of densities in the presence of covariates which incorporates sample selection. We describe a simulation algorithm to implement counterfactual comparisons of densities. The proposed methodology is used to investigate the gender wage gap in Italy. It is found that when sample selection is taken into account gender wage gap widens, especially at the bottom of the wage distribution. Explanations are offered for this empirical finding.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Picchio, M. & Mussida, C., 2010. "Gender Wage Gap : A Semi-Parametric Approach With Sample Selection Correction," Other publications TiSEM b7a548d2-9ba3-43b6-8e87-a, Tilburg University, School of Economics and Management.
    • Handle: RePEc:tiu:tiutis:b7a548d2-9ba3-43b6-8e87-afcd6c6ac536
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    as
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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • 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

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