What Works for the Unemployed? Evidence from Quasi-Random Caseworker Assignments - Anders Humlum; Jakob R. Munch; Mette Rasmussen (Institute of Labor Economics (IZA), 2023)
This paper examines if active labor market programs help unemployed job seekers find jobs using a novel random caseworker instrumental variable (IV) design. Leveraging administrative data from Denmark, our identification strategy exploits that (i) job seekers are quasi-randomly assigned to caseworkers, and (ii) caseworkers differ in their tendencies to assign similar job seekers to different programs. Using our IV strategy, we find assignment to classroom training increases employment rates by 25% two years after initial job loss. This finding contrasts with the conclusion reached by ordinary least squares (OLS), which suffers from a negative bias due to selection on unobservables. The employment effects are driven by job seekers who complete the programs (post-program effects) rather than job seekers who exit unemployment upon assignment (threat effects), and the programs help job seekers change occupations. We show that job seekers exposed to offshoring – who tend to experience larger and more persistent employment losses – also have higher employment gains from classroom training. By estimating marginal treatment effects, we conclude that total employment may be increased by targeting training toward job seekers exposed to offshoring.
Keywords: J08; J64; I21; 330; unemployed workers; active labor market policy; classroom training; caseworker instrumental variable