Wage Decompositions using Panel Data Sample Selection Correction

Abstract

This paper analyzes wage decomposition methodology in the context of panel data sample selection embedded in a correlated random effects setting. Identification issues unique to panel data are examined for their implications for wage decompositions. As an empirical example, we apply our methodology to the German Socio-Economic Panel (SOEP) data with which we investigate gender wage differentials in the German Labor Market. Our results highlight the sensitivity of inferences about potential discrimination to how elements of the panel data selection model are assigned to explained and unexplained components.