%0 Report
        %A Picchio, Matteo
%A Mussida, Chiara
        %T Gender Wage Gap: A Semi-Parametric Approach with Sample Selection Correction
        %D 2010
        %8 2010 Feb
        %I Institute of Labor Economics (IZA)
        %C Bonn
        %7 IZA Discussion Paper
        %N 4783
        %U https://www.iza.org/publications/dp4783
        %X 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.
        %K glass ceiling
%K sample selection
%K hazard function
%K gender wage gap
%K sticky floor