The Effects of Algorithmic Labor Market Recommendations: Evidence from a Field Experiment

37 Pages Posted: 29 Oct 2013 Last revised: 17 Oct 2015

See all articles by John J. Horton

John J. Horton

New York University (NYU) - Department of Information, Operations, and Management Sciences

Date Written: October 15, 2015

Abstract

Algorithmically recommending workers to employers for the purpose of recruiting can substantially increase hiring: in an experiment conducted in an online labor market, employers with technical job vacancies that received recruiting recommendations had a 20% higher fill rate compared to the control. There is no evidence that the treatment crowded-out hiring of non-recommended candidates. The experimentally induced recruits were highly positively selected and were statistically indistinguishable from the kinds of workers employers recruit “on their own.” Recommendations were most effective for job openings that were likely to receive a smaller applicant pool.

Keywords: employer search, labor market intermediation, field experiments

JEL Classification: C93, J41, D47, D21

Suggested Citation

Horton, John J., The Effects of Algorithmic Labor Market Recommendations: Evidence from a Field Experiment (October 15, 2015). Available at SSRN: https://ssrn.com/abstract=2346486 or http://dx.doi.org/10.2139/ssrn.2346486

John J. Horton (Contact Author)

New York University (NYU) - Department of Information, Operations, and Management Sciences ( email )

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