Give it Another Try: What are the Effects of a Job Creation Scheme Especially Designed for Hard-to-Place Workers?

Tobias Brändle () and Lukas Fervers ()
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Lukas Fervers: University of Cologne, German Institute for Adult Education (DIE) and Institute for Applied Economic Research (IAW)

Journal of Labor Research, 2021, vol. 42, issue 3, No 4, 382-417

Abstract: Abstract Previous evaluations of job creation schemes (JCS) reveal mostly negative employment effects, mainly due to inherent lock-in effects. In this paper, we assess the impact of an innovative JCS that employs a pre-selection mechanism to target programme participation on unemployed job seekers with very low integration chances, hereby reducing possible lock-in effects. Relying on high-quality administrative as well as survey data, we conduct regression-adjusted matching analyses to estimate the programme effect on integration into regular employment. Our results show that the programme did not succeed to foster labour market integration, but still entails remarkably negative employment effects in the first years after participation. We argue that this results from a principal-agent problem at the last step of the selection mechanism that may have led to cream-skimming rather than targeting on very hard to place workers. However, supplementary analyses reveal that negative effects can be avoided for subgroups with very poor employment chances in case of non-participation. These results are robust to the use of different matching estimators and definitions of non-participation. The inclusion of usually unobservable survey variables as well as placebo tests based on past employment outcomes refute concerns about endogenous selection. From a policy-perspective, these findings imply that targeting JCS on workers with very low integration chances is a key factor to avoid negative employment effects found in previous evaluations. At the methodological level, our analyses add to recent literature that assesses the credibility of non-experimental evaluations based on high-quality administrative data.

Date: 2021
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DOI: 10.1007/s12122-021-09322-x

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