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...

We use (donut) regression discontinuity design and difference-in-differences estimators to estimate the impact of a one-shot hiring subsidy targeted at low-educated unemployed youths during the Great Recession recovery in Belgium. The subsidy increases job-finding in the private sector by 10...