Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium
(2020) , 81 pages
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- Authors
- Abstract
- 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 substantial heterogeneity across programmes and unemployed. Simulations show that “black-box” rules that reassign unemployed to programmes that maximise estimated individual gains can considerably improve effectiveness: up to 20% more (less) time spent in (un)employment within a 30 months window. A shallow policy tree delivers a simple rule that realizes about 70% of this gain.
- Affiliations
Citations
Bart Cockx, Michael Lechner, & Joost Bollens. (2020). Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium (IRES Discussion Papers 2020016). https://hdl.handle.net/2078.5/97621