Heterogeneous Employment Effects of Job Search Programs: A Machine Learning Approach

A-Tier
Journal: Journal of Human Resources
Year: 2022
Volume: 57
Issue: 2

Score contribution per author:

1.341 = (α=2.01 / 3 authors) × 2.0x A-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

We systematically investigate the effect heterogeneity of job search programs for unemployed workers. To investigate possibly heterogeneous employment effects, we combine nonexperimental causal empirical models with Lassotype estimators. The empirical analyses are based on rich administrative data from Swiss social security records. We find considerable heterogeneities during the first six months after the start of training. Consistent with previous results in the literature, unemployed persons with fewer employment opportunities profit more from participating in these programs. Finally, we show the potential of easy-to-implement program participation rules for improving average employment effects of these active labor market programs.

Technical Details

RePEc Handle
repec:uwp:jhriss:v:57:y:2022:i:2:p:597-636
Journal Field
Labor
Author Count
3
Added to Database
2026-01-25