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

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.