3 papers
econ.GN2026
Targeting Support Using Job Seekers' Biases: A Randomized Experiment
Bruno Crépon, Aurélien Frot, Christophe Gaillac
Most digital job-search assistance encourages unemployed workers to broaden their search toward related occupations, targeting one important source of search inefficiency: insuffic…
econ.GN2026
Biases-Informed Job Search Guidance: Characterization, Implications, and Targeting Support
Bruno Crépon, Aurélien Frot, Christophe Gaillac
Job seekers' expectations about reemployment are increasingly used to study job search, but what their biases reveal about underlying beliefs and preferences is ambiguous. We combi…
econ.EM2026
A Job I Like or a Job I Can Get: Designing Job Recommender Systems Using Field Experiments
Guillaume Bied, Philippe Caillou, Bruno Crépon +3
Recommendation systems (RSs) are increasingly used to guide job seekers on online platforms, yet the algorithms currently deployed are typically optimized for predictive objectives…