The Potential of Recommender Systems for Directing Job Search: A Large-Scale Experiment

Luc Behaghel, Sofia Dromundo (), Marc Gurgand, Yagan Hazard () and Thomas Zuber ()
Additional contact information
Sofia Dromundo: OECD
Yagan Hazard: Paris School of Economics
Thomas Zuber: Banque de France

No 16781, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: We analyze the employment effects of directing job seekers' applications toward establishments likely to recruit. We run a two-sided randomization design involving about 800,000 job seekers and 40,000 establishments, based on an empirical model that recommends each job seeker to firms so as to maximize total potential employment. Our intervention induces a 1% increase in job finding rates for short term contracts. This impact comes from a targeting effect combining (i) a modest increase in job seekers' applications to the very firms that were recommended to them, and (ii) a high success rate conditional on applying to these firms. Indeed, the success rate of job seekers' applications varies considerably across firms: the efficiency of applications sent to recommended firms is 2.7 times higher than the efficiency of applications to the average firm. This suggests that there can be substantial gains from better targeting job search, leveraging firm-level heterogeneity.

Keywords: recommender systems; matching; RCT; active labor market policies (search for similar items in EconPapers)
JEL-codes: J64 (search for similar items in EconPapers)
Pages: 66 pages
Date: 2024-02
New Economics Papers: this item is included in nep-exp, nep-hrm and nep-lab
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Related works:
Working Paper: The Potential of Recommender Systems for Directing Job Search: a Large Scale Experiment (2024)
Working Paper: The Potential of Recommender Systems for Directing Job Search: a Large Scale Experiment (2024)
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