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