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Gender wage gap: A semi-parametric approach with sample selection correction

Author

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  • Picchio, Matteo
  • Mussida, Chiara
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.

Suggested Citation

  • Picchio, Matteo & Mussida, Chiara, 2011. "Gender wage gap: A semi-parametric approach with sample selection correction," Labour Economics, Elsevier, vol. 18(5), pages 564-578, October.
    • Handle: RePEc:eee:labeco:v:18:y:2011:i:5:p:564-578
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    More about this item

    Keywords

    Gender wage gap Hazard function Sample selection Wage distribution;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J71 - Labor and Demographic Economics - - Labor Discrimination - - - Hiring and Firing

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