Gender Wage Gap: A Semi-Parametric Approach with Sample Selection Correction
Matteo Picchio and
Chiara Mussida
No 4783, IZA Discussion Papers from Institute of Labor Economics (IZA)
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: glass ceiling; sample selection; hazard function; gender wage gap; sticky floor (search for similar items in EconPapers)
JEL-codes: C21 C41 J16 J31 J71 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2010-02
New Economics Papers: this item is included in nep-ecm and nep-lab
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Citations: View citations in EconPapers (9)
Published - published in: Labour Economics, 2011, 18 (5), 564-578
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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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