We use an extensive, matched employer-employee dataset to analyze the employersize wage relation and its contribution to wage inequality in Germany. Applying models with additive fixed effects for workers and establishments, we document that the large firm wage premium, which has risen over 25...

In this paper, we analyze the connection between value added, wages, and labor market ows at the establishment level. For this purpose, we first develop a simple model to illustrate the expected comovement of these variables. For the empirical analysis, we link the new German Administrative Wage...

This paper investigates determinants and wage effects of educational mismatch for both natives and immigrants in Germany. Using the GSOEP panel data from 1991 to 2013, I find that conditional on educational attainment immigrants face a higher incidence of overeducation compared to their native...

This paper describes the updated version of the Administrative Wage and Labor Market Flow Panel (AWFP, v1.1). The AWFP is a dataset on labor market flows and stocks for the universe of German establishments covering the years 1975-2014. It contains data on job flows, worker flows, and wages for...

This paper describes the new Administrative Wage and Labor Market Flow Panel (AWFP). The AWFP is a dataset on labor market flows and stocks for the universe of German estab-lishments. It contains data on job flows, worker flows, and about wages for each establishment. The AWFP contains this...

Using representative linked employer-employee data for Germany, this paper analyzes short- and long-run differences in labor market performance of workers joining start-ups instead of incumbent firms. Applying entropy balancing and following individuals over ten years, we find huge and...

This study investigates the interplay between personality traits, cognitive ability, marriage and the gender wage gap for West Germany by using data from the GSOEP. The findings indicate that personality traits in the form of the five factors of personality account for 11% of the total gender...