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 the second part of the 1990's Switzerland conducted an ambitious active labour market policy (ALMP) encompassing a wide variety of programmes. We evaluate the effects of these programmes on the individual employment probability of potential participants. Our econometric analysis uses...

Based on administrative data of unemployed in Belgium, we estimate the labour market effects of three training programmes at various aggregation levels using Modified Causal Forests, a causal machine learning estimator. While all programmes have positive effects after the lock-in period, we find...