Kurzbeschreibung

Dauth et al. (2022) show that the tendency of assortative matching increases in the size of local labor markets, which implies that larger labor markets are more efficient. However, the size of the local labor markets is limited by the distance individuals are willing to commute on a regular basis. According to Dauth/Haller (2020), the number of commuters declines convexly with distance and only a negligible share of the workforce commutes more than one hour. Working from home reduces the costs of distance between residence and workplace. A preliminary analysis reveals that this distance has indeed increased for job changers in 2021 as compared to before 2020. This implies that the geographic scope of local labor markets has increased.In this task, we study whether this increase leads to an improvement of the average match quality of workers and firms. We further study whether worker-firm matching improves uniformly across space and therefore provides opportunities for firms in remote locations or whether the improvement is limited to cities with initially larger local labor markets. In particular, we are interested in whether firms in remote locations benefit from the possibility to hire highly skilled workers that prefer to live in larger cities. Our analysis will base on the IEBgeo dataset of the Institute for Employment Research. This data stems from process data of the full universe of workers subject to social security in Germany and comprises information on wages, education, age, gender, and the precise location of the residence and workplace. We proxy the match quality by the correlation of worker and firm fixed effects obtained from so-called AKM-regressions (after Abowd/Kramarz/Margolis, 1999) and use a difference-in-differences approach to analyze whether match quality has improved differentially across regions and occupations in the wake of the pandemic.