Besoin d'une information ?

Logo laboratoire
Les thèses, post-docs & HDR

"How can AI improve search and matching? Evidence from 59 million personalized job recommendations"

Séminaire Roland RATHELOT

Prochain séminaire du GAINS

Le prochain séminaire du GAINS a lieu 26 septembre 2023 de 10h30 à 12h00.


Roland Rathelot (CREST-ENSAE, IP Paris) présentera un papier intitulé "How can AI improve search and matching? Evidence from 59 million personalized job recommendations" co-écrit avec Thomas Le Barbanchon (Bocconi University) et Lena Hensvik (Uppsala University).


Abstract :  

We explore how Artificial Intelligence can be leveraged to help frictional markets to clear. We design a collaborative-filtering machine-learning job recommender system that uses job seekers' click history to generate relevant personalised job recommendations. We deploy it at scale on the largest online job board in Sweden, and design a clustered two-sided randomised experiment to evaluate its impact on job search and labor-market outcomes. Combining platform data with unemployment and employment registers, we find that treated job seekers are more likely to click and apply to recommended jobs, and have 0.6% higher employment within the 6 months following first exposure to recommendations. At the job-worker pair level, we document that recommending a vacancy to a job seeker increases the probability to work at this workplace by 5%. Leveraging the two-sided vacancy-worker randomisation or the market-level randomisation, we find limited congestion effects. We find that employment effects are larger for workers that are less-educated, unemployed, and have initially a large geographic scope of search, for jobs that are attached to several jobs, and are relatively older. Results also suggest that recommendations expanding the occupational scope yield higher effects.





Partagez : FacebookTwitterLinkedInMailImprimez