Gender Wage Gap: A Semi-parametric Approach with Sample Selection Correction

Matteo Picchio and Chiara Mussida

No 2010005, LIDAM Discussion Papers IRES from Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES)

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.

Keywords: gender wage gap; hazard function; sample selection; glass ceiling; sticky floor (search for similar items in EconPapers)
JEL-codes: C21 C41 J16 J31 J71 (search for similar items in EconPapers)
Pages: 31
Date: 2010-03-12
New Economics Papers: this item is included in nep-ecm and nep-lab
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Citations: View citations in EconPapers (11)

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Related works:
Journal Article: Gender wage gap: A semi-parametric approach with sample selection correction (2011)
Working Paper: Gender Wage Gap: A Semi-Parametric Approach with Sample Selection Correction (2010)
Working Paper: Gender Wage Gap: A Semi-Parametric Approach With Sample Selection Correction (2010)
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Persistent link: https://EconPapers.repec.org/RePEc:ctl:louvir:2010005

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