• Graduate program
  • Research
  • News
  • Events
    • Summer School
      • Climate Change
      • Gender in Society
      • Inequalities in Health and Healthcare
      • Business Data Science Summer School Program
      • Receive updates
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • Conference: Consumer Search and Markets
    • Annual Tinbergen Institute Conference
  • Summer School
    • Climate Change
    • Gender in Society
    • Inequalities in Health and Healthcare
    • Business Data Science Summer School Program
    • Receive updates
  • Alumni
  • Magazine
Home | Events Archive | Do Algorithmic Job Recommendations improve Search and Matching? Evidence from a Large-Scale randomised Field Experiment in Sweden
Seminar

Do Algorithmic Job Recommendations improve Search and Matching? Evidence from a Large-Scale randomised Field Experiment in Sweden


  • Series
  • Speaker(s)
    Thomas Le Barbanchon (Bocconi University, Italy)
  • Field
    Empirical Microeconomics
  • Location
    Online
  • Date and time

    June 01, 2021
    16:00 - 17:00

Please send an email to Nadine Ketel or Paul Muller if you are interested to participate in this seminar (series).

Abstract: We design a job recommender system that recommends job ads to Swedish job seekers. The job recommender system is hosted on the largest online job board in Sweden, and it is based on a collaborative filtering ML algorithm. We then evaluate how job seekers respond to job recommendations (clicks, applications, job finding, earnings), and the implications for vacancies and recruiters. Joint with Hensvik, Le Barbanchon, and Rathelot.