Abdelrahman Amer

This paper studies the role of commuting costs in shaping labor market power and the allocation of workers to firms. I build, identify, and estimate a two-sided labor market matching model that features strategic interactions in wage setting, commuting costs, and residential choice. I use the model to study the direct and distributional consequences of a commuting cost shock due to a subway expansion in Vancouver. Empirically, workers who gained improved access to the subway network experienced an increase in earnings by 1.5-2% relative to workers with no change in access. Using the estimated model, I show that the expansion improved access to more productive firms for workers in affected areas, but increased competition for high-productivity jobs for workers elsewhere. Neighborhoods with improved access experienced an 8% drop in labor market concentration. These results show that improvements in access to firms for some neighborhoods can generate adverse spillover effects for others due to higher competition amongst workers. To underscore the role of differential job access in shaping labor market power, I show that 10-15% of the spatial variation in wage markdowns can be explained by the non-uniform access to firms within a commuting zone.

Performance evaluations in interviews are central to employment decisions. We combine two field experiments, administrative data and video analysis to study the sources of gender gaps in interview evaluations. Leveraging 60,000 mock interviews on a platform for software engineers, we find that code quality ratings are 12 percent of a standard deviation lower for women. This gap persists after controlling for an objective measure of code quality. Providing evaluators with automated performance measures does not reduce gender gaps. Comparing blind to non-blind evaluations without live interaction reveals no gender gap in either case. In contrast, gaps widen with longer personal interaction and are larger among evaluators from regions with stronger implicit gender bias. Video analysis shows that women apologize more; and interviewers are more condescending and harsher with them. Both correlate with lower ratings. Our findings highlight how interpersonal dynamics can introduce bias into evaluations that otherwise rely on objective metrics.