What is the Value Added by using Causal Machine Learning Methods in a Welfare Experiment Evaluation?
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- Strittmatter, Anthony, 2019. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," GLO Discussion Paper Series 336, Global Labor Organization (GLO).
- Anthony Strittmatter, 2018. "What Is the Value Added by Using Causal Machine Learning Methods in a Welfare Experiment Evaluation?," Papers 1812.06533, arXiv.org, revised Mar 2019.
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Cited by:
- Lechner, Michael, 2018.
"Modified Causal Forests for Estimating Heterogeneous Causal Effects,"
IZA Discussion Papers
12040, Institute of Labor Economics (IZA).
- Lechner, Michael, 2019. "Modified Causal Forests for Estimating Heterogeneous Causal Effects," CEPR Discussion Papers 13430, C.E.P.R. Discussion Papers.
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- Knaus, Michael C. & Lechner, Michael & Strittmatter, Anthony, 2018.
"Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence,"
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12039, Institute of Labor Economics (IZA).
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- Knaus, Michael C. & Lechner, Michael & anthony.strittmatter@unisg.ch, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," Economics Working Paper Series 1817, University of St. Gallen, School of Economics and Political Science.
- Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2018. "Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence," Papers 1810.13237, arXiv.org, revised Dec 2018.
More about this item
Keywords
Labour supply; individualized treatment effects; conditional average treatment effects; random forest;JEL classification:
- H75 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Government: Health, Education, and Welfare
- I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
- J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
- J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
- 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-2019-11-04 (Big Data)
- NEP-CMP-2019-11-04 (Computational Economics)
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