DATA‐DRIVEN DRAFTING: APPLYING ECONOMETRICS TO EMPLOY QUARTERBACKS

Jeremy Rosen and Alexandre Olbrecht

Contemporary Economic Policy, 2020, vol. 38, issue 2, 313-326

Abstract: 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)

Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://doi.org/10.1111/coep.12454

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:coecpo:v:38:y:2020:i:2:p:313-326

Ordering information: This journal article can be ordered from
https://ordering.onl ... 5-7287&ref=1465-7287

Access Statistics for this article

Contemporary Economic Policy is currently edited by Brad R. Humphreys

More articles in Contemporary Economic Policy from Western Economic Association International Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().