This paper studies how the internal organization of firms interacts with labor and product markets. I analyze millions of task assignments across hundreds of salons using data from a software company.

We develop a model in which a principal delegates sequential search over uncertain objects to an agent. We use the model to analyze how recruiters influence the search for talent. During search, the recruiter does not learn worker productivity but only forms a belief characterized by an expectation and a variance.

This paper investigates the relationship between individual workplace injury risk and labor supply. I utilize a novel panel data set of traffic officers. Unique aspects of overtime assignment, including randomization, leave of coworkers, and informal trading enable identification.

In this paper we demonstrate tips are sensitive to service quality even when future interaction is unlikely. Using a novel data set covering 150,000 hair salon appointments where customers can be observed over time, we are able to exploit variation in service quality and exogenous separation rates.