A1506
Title: A new decomposition method using expectiles
Authors: Pedro Raposo - Catolica Lisbon school of business and economics (Portugal) [presenting]
Pedro Portugal - Banco de Portugal (Portugal)
Paulo Rodrigues - Universidade Nova de Lisboa and Banco de Portugal (Portugal)
Abstract: A new expectile panel data method is developed for high-dimensional fixed effects estimation in line with prior research, which allows for a wide range of applications in fields such as labor economics, the economics of education, and inequality. It is also shown how the Gelbach decomposition can be validly implemented in the context of panel expectile regressions. Using a unique Portuguese-linked employer-employee dataset, the approach is used to explore the determinants of the gender wage gap over the period 1995-2021. It is found that (i) the gender wage gap is significantly larger in the upper tail; (ii) the difference is mainly explained both in the left and right tail, around 80\% by the individual unobserved heterogeneity and 20\% by the firm unobserved heterogeneity. Education does not play a significant role in explaining the wage difference between man and woman.
