Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/169367
Authors: 
Töpfer, Marina
Year of Publication: 
2017
Series/Report no.: 
Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017
Abstract: 
In this paper, we estimate the gender pay gap along the wage distribution using a detailed decomposition approach based on unconditional quantile regressions. Non-randomness of the sample leads to biased and inconsistent estimates of the wage equation as well as of the components of the wage gap. Therefore, the method is extended to account for sample selection problems. The decomposition is conducted by using Italian microdata. Accounting for labor market selection may be particularly relevant for Italy given a comparably low female labor market participation rate. The results suggest not only differences in the income gap along the wage distribution (in particular glass ceiling), but also differences in the contribution of selection effects to the pay gap at different quantiles.
Subjects: 
Gender Pay Gap
Detailed Decomposition
Unconditional Quantile Regression
Sample Selection
JEL: 
J7
J13
J31
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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