Demographic change implies an increasing demand for elderly care and a lower labor force potential at the same time. Training unemployed workers in care occupations might mitigate this problem. This study analyzes the effectiveness of subsidized training in elderly care professions for the...

We analyse the impact of retraining for the unemployed on future labour market success, and estimate effects separately for different target occupations. We use German registry data and apply statistical matching methods. The results show that on average, after a period with strong lock-in...

Matching-type estimators using the propensity score are the major workhorse in active labour market policy evaluation. This work investigates if machine learning algorithms for estimating the propensity score lead to more credible estimation of average treatment effects on the treated using a...

In this paper, we compare two popular statistical learning techniques, logistic regression and random forest, with respect to their ability to classify jobseekers by their likelihood to become long-term unemployed. We study the performance of the two methods before the COVID-19 pandemic as well...