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.