Essays on Employer Learning in the Labor Market

Abstract

The efficient allocation of labor relies on the identification of talent. This dissertation consists of three essays that study information frictions about talent and quantify their impacts on individual career outcomes and aggregate productivity. The first chapter investigates how employer learning affects individual career mobility and overall productivity in the labor market for computer scientists. The large volume of computer science conference proceedings provide public information on the research ability of authors. I find evidence of public learning by showing that workers with a new paper have higher inter-firm mobility rates than do coworkers without a paper. I test for asymmetric employer learning by exploiting the delayed disclosure of patent applications that accompany some high-quality research papers. Removing the delayed disclosure is estimated to accelerate the positive assortative matching between firms and workers and increase innovation outputs. Are firms equally likely to identify high-ability workers? The second chapter, co-authored with Sabrina Di Addario, provides an answer in Italy’s labor market for potential inventors. We find a substantial gap between lower-wage and higher-wage firms in the discovery of new inventors who apply for a patent for the first time. We also study how wages are set given imperfect information about talent. Lower-wage firms set a higher wage return to the first patent application of an inventor. We interpret the findings through a model where heterogeneous firms invest in talent discovery and use wage incentives to elicit effort from workers. The third chapter examines if the learning about an individual’s ability is contaminated by stereotype and in-group bias. I study how women and men are portrayed differently on an anonymous online forum for economists. Discussions about women are more likely to highlight their personal characteristics rather than professional accomplishments. Posts that mention a female economist also have also a higher chance to deviate from professional topics than posts that mention a male. The findings are interpreted via an identity model where male posters are incentivized to boost their own professional identities relative to the out-group in the profession.