The Potential of Recommender Systems for Directing Job Search: a Large Scale Experiment - Paris-Jourdan Sciences Économiques
Pré-Publication, Document De Travail (Working Paper) Année : 2024

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

Sofia Dromundo
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Thomas Zuber
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Résumé

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.
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Dates et versions

halshs-04716995 , version 1 (01-10-2024)

Identifiants

  • HAL Id : halshs-04716995 , version 1

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Luc Behaghel, Marc Gurgand, Sofia Dromundo, Yagan Hazard, Thomas Zuber. The Potential of Recommender Systems for Directing Job Search: a Large Scale Experiment. 2024. ⟨halshs-04716995⟩
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