Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/35971
Authors: 
Picchio, Matteo
Mussida, Chiara
Year of Publication: 
2010
Series/Report no.: 
IZA Discussion Papers 4783
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.
Subjects: 
Gender wage gap
hazard function
sample selection
glass ceiling
sticky floor
JEL: 
C21
C41
J16
J31
J71
Document Type: 
Working Paper

Files in This Item:
File
Size
584.36 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.