Gender Wage Gaps Reconsidered: A Structural Approach Using Matched Employer–Employee Data. Collegio Carlo Alberto, Working Papers

In this paper I propose and estimate an equilibrium search model using matched employer-employee data to study the extent to which wage di¤erentials between men and women can be explained by dif-ferences in productivity, disparities in friction patterns, segregation or wage discrimination. The availability of matched employer-employee data is essential to empirically disentangle di¤erences in workers pro-ductivity across groups from di¤erences in wage policies toward those groups. The model features rent splitting, on-the-job search and two-sided heterogeneity in productivity. It is estimated using German microdata. I \u85nd that female workers are less productive and more mobile than males. Female workers have on average slightly lower bar-gaining power than their male counterparts. The total gender wage gap is 42 percent. It turns out that most of the gap, 65 percent, is accounted for by di¤erences in productivity, 17 percent of this gap is driven by segregation while di¤erences in destruction rates explain 9 percent of the total wage-gap. Netting out di¤erences in o¤er-arrival rates would increase the gap by 13 percent. Due to di¤erences in wage setting, female workers receive wages 9 percent lower than male ones