Peter Haan
- 14 April 2026
- WORKING PAPER SERIES - No. 3219Details
- Abstract
- We propose a new approach to estimate selection-corrected quantiles of the gender wage gap. Our method employs instrumental variables that explain variation in the latent variable but, conditional on the latent process, do not directly a_ect selection. We provide semiparametric identi_cation of the quantile parameters without imposing parametric restrictions on the selection probability, derive the asymptotic distribution of the proposed estimator based on constrained selection probability weighting, and demonstrate how the approach applies to the Roy model of labor supply. Using German administrative data, we analyze the distribution of the gender gap in full-time earnings. We _nd pronounced positive selection among women at the lower end, especially those with less education, which widens the gender gap in this segment, and strong positive selection among highly educated men at the top, which narrows the gender wage gap at upper quantiles.
- JEL Code
- C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
J16 : Labor and Demographic Economics→Demographic Economics→Economics of Gender, Non-labor Discrimination
J21 : Labor and Demographic Economics→Demand and Supply of Labor→Labor Force and Employment, Size, and Structure
J31 : Labor and Demographic Economics→Wages, Compensation, and Labor Costs→Wage Level and Structure, Wage Differentials