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

John Horton

Journal of Labor Economics


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.

Field Experiments, Firm Behavior: Theory, Market Design, Macroeconomic Issues of Monetary Unions, Macroeconomic Aspects of International Trade and Finance: Forecasting and Simulation: Models and Applications, Labor Contracts

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