Template-type: ReDif-Paper 1.0
Author-Name: Cockx, Bart
Author-Name: Lechner, Michael
Author-Name: Bollens, Joost
Title: Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium
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.
Classification-JEL: j68
Series: ROA Research Memoranda
Creation-Date: 20200512
Number: 006
File-URL: https://cris.maastrichtuniversity.nl/ws/files/48078430/ROA_RM_2020_6.pdf
File-Format: application/pdf
File-Size: 1535287
Handle: Repec:unm:umaror:2020006
DOI: 10.26481/umaror.2020006