Titelaufnahme

Titel
Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium / Bart Cockx (Ghent University and IZA), Michael Lechner (SEW, University of St. Gallen and IZA), Joost Bollens (VDAB) ; IZA Institute of Labor Economics
VerfasserCockx, Bart ; Lechner, Michael ; Bollens, Joost
KörperschaftForschungsinstitut zur Zukunft der Arbeit
ErschienenBonn, Germany : IZA Institute of Labor Economics, December 2019
Ausgabe
Elektronische Ressource
Umfang1 Online-Ressource (68 Seiten) : Diagramme
SerieDiscussion paper ; no. 12875
URNurn:nbn:de:hbz:5:2-209656 
Zugänglichkeit
 Das Dokument ist öffentlich zugänglich im Rahmen des deutschen Urheberrechts.
Volltexte
Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium [1.63 mb]
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Zusammenfassung

We investigate heterogenous employment effects of Flemish training programmes. Based on administrative individual data, we analyse programme effects at various aggregation levels using Modified Causal Forests (MCF), a causal machine learning estimator for multiple programmes. While all programmes have positive effects after the lock-in period, we find substantial heterogeneity across programmes and types of unemployed. Simulations show that assigning unemployed to programmes that maximise individual gains as identified in our estimation can considerably improve effectiveness. Simplified rules, such as one giving priority to unemployed with low employability, mostly recent migrants, lead to about half of the gains obtained by more sophisticated rules.