Gender wage gap: A semi-parametric approach with sample selection correction
Picchio,M. Mussida,C.
Picchio,M.
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. We propose a 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. We find that, when sample selection is taken into account, the gender wage gap widens, especially at the bottom of the wage distribution.
Description
Appeared earlier as CentER Discussion Paper 2010-016
Date
2011
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
Organizational Units
Journal Issue
Keywords
SDG 1 - No Poverty, SDG 5 - Gender Equality, SDG 8 - Decent Work and Economic Growth, SDG 10 - Reduced Inequalities
Citation
Picchio, M & Mussida, C 2011, 'Gender wage gap : A semi-parametric approach with sample selection correction', Labour Economics, vol. 18, no. 5, pp. 564-578. https://doi.org/10.1016/j.labeco.2011.05.003