Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach
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- Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2022. "Heterogeneous Employment Effects of Job Search Programs: A Machine Learning Approach," Journal of Human Resources, University of Wisconsin Press, vol. 57(2), pages 597-636.
- Lechner, Michael & Strittmatter, Anthony & Knaus, Michael C., 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," CEPR Discussion Papers 12224, C.E.P.R. Discussion Papers.
- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," Economics Working Paper Series 1711, University of St. Gallen, School of Economics and Political Science.
- Michael Knaus & Michael Lechner & Anthony Strittmatter, 2017. "Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach," Papers 1709.10279, arXiv.org, revised May 2018.
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More about this item
Keywords
conditional average treatment effects; individualized treatment effects; machine learning; active labour market policy;All these keywords.
JEL classification:
- J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy
- H43 - Public Economics - - Publicly Provided Goods - - - Project Evaluation; Social Discount Rate
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
NEP fields
This paper has been announced in the following NEP Reports:- NEP-BIG-2017-09-03 (Big Data)
- NEP-EXP-2017-09-03 (Experimental Economics)
Statistics
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