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Research ArticleArticle

Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach

Michael C. Knaus, Michael Lechner and Anthony Strittmatter
Published online before print March 26, 2020, 0718-9615R1; DOI: https://doi.org/10.3368/jhr.57.2.0718-9615R1
Michael C. Knaus
†Michael C. Knaus assistant professor of econometrics at the University St. Gallen and is also affiliated with IZA, Bonn. Email:
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Michael Lechner
‡Michael Lechner is full professor of econometrics at the University St. Gallen and is also affiliated with CEPR, London, CESIfo, Munich, IAB, Nuremberg, and IZA, Bonn. Email:
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Anthony Strittmatter
*Anthony Strittmatter is assistant professor of econometrics at the University St. Gallen. Email:
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Abstract

We systematically investigate the effect heterogeneity of job search programmes for unemployed workers. To investigate possibly heterogeneous employment effects, we combine non-experimental causal empirical models with Lasso-type estimators. The empirical analyses are based on rich administrative data from Swiss social security records. We find considerable heterogeneities during the first six months after the start of training. Consistent with previous results in the literature, unemployed persons with fewer employment opportunities profit more from participating in these programmes. Finally, we show the potential of easy-to-implement programme participation rules for improving average employment effects of these active labour market programmes.

Keywords
  • Causal machine learning
  • individualized treatment effects
  • conditional average treatment effects
  • active labour market policy
JEL Classification
  • J68
  • H43
  • C21

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Journal of Human Resources: 60 (3)
Journal of Human Resources
Vol. 60, Issue 3
1 May 2025
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Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach
Michael C. Knaus, Michael Lechner, Anthony Strittmatter
Journal of Human Resources Mar 2020, 0718-9615R1; DOI: 10.3368/jhr.57.2.0718-9615R1

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Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach
Michael C. Knaus, Michael Lechner, Anthony Strittmatter
Journal of Human Resources Mar 2020, 0718-9615R1; DOI: 10.3368/jhr.57.2.0718-9615R1
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Keywords

  • Causal machine learning
  • individualized treatment effects
  • conditional average treatment effects
  • active labour market policy
  • J68
  • H43
  • C21
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