Heterogeneous Employment Effects of Job Search Programs

Abstract

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Some Children Left Behind: Variation in the Effects of an Educational Intervention

“…The best method continues to be the elastic net (Appendix Table A15); the FH lower bound is nearly unchanged for the full-cost program and about four percent lower for the reduced-cost program (Appendix Table A16). The estimates in our IZA working paper (Buhl-Wiggers et al 2020), which used the LASSO-based method of Knaus, Lechner, and Strittmatter (2020), yield a lower bound of the impact SD of 1.02 for the full-cost program, and 0.65 for the reduced-cost version.…”

“…Though we have no real way to tell in which world we reside, it turns out to matter for the asymptotic theory. See, e.g., Chen et al (2017), Imai and Ratkovic (2013), Knaus, Lechner, andStrittmatter (2020), andTian et al (2014), for more detail on the LASSO and empirical applications in different substantive domains.…”

Some Children Left Behind: Variation in the Effects of an Educational Intervention

“…As they note, our ability to capture systematic heterogeneity depends crucially on the set of available candidate moderators. We conduct our search for meaningful moderators using both a traditional approach of looking for first-order interactions between the treatment indicators and various "usual suspects" and via the machine learning algorithm laid out in Knaus, Lechner, and Strittmatter (2020).…”

“…Relative to OLS, the regularization implicit in the LASSO pushes coefficients toward zero, which avoids over-fitting in contexts with many candidate moderators. 60 See, e.g., Chen et al (2017), Imai and Ratkovic (2013), Knaus, Lechner, andStrittmatter (2020), andTian et al (2014), for more detail on the LASSO and empirical applications in different substantive domains.…”

Active Labour Market Policies for the Long-Term Unemployed: New Evidence from Causal Machine Learning

“…This study is among the early papers in policy evaluation to systematically analyse treatment effect heterogeneity using causal machine learning (CML) methods. In a LASSObased approach to analyse heterogeneous treatment effects, Knaus, Lechner, and Strittmatter (2020) evaluate a job-search programme in Switzerland. Using administrative data from 2003, they find heterogeneity in the short run, but effects become more homogeneous in the long run.…”