DATA-DRIVEN DRAFTING: APPLYING ECONOMETRICS TO EMPLOY QUARTERBACKS

摘要

We show that firms can employ data-driven methods to improve their hiring decisions. Specifically, we use data available to National Football League (NFL) teams prior to the NFL draft to estimate econometric models that predict the future performance of drafted quarterbacks. As our methods are replicable, stakeholders can use them to improve the draft's efficiency and help it accomplish its mission to promote competitive balance. Furthermore, data-driven methods such as ours can help firms avoid biases against employee characteristics that do not affect future job performance. (JEL L83)