Detailed RIF Decomposition with Selection - The Gender Pay Gap in Italy - Marina Töpfer (ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft, 2017)
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.
Keywords: J7; J13; J31; 330; Gender Pay Gap; Detailed Decomposition; Unconditional Quantile Regression; Sample Selection