Two-stage least squares random forests with an application to Angrist and Evans (1998)
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DOI: 10.1016/j.econlet.2021.109893
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- Biewen, Martin & Kugler, Philipp, 2020. "Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)," IZA Discussion Papers 13613, Institute of Labor Economics (IZA).
References listed on IDEAS
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"Two-stage least squares random forests with an application to Angrist and Evans (1998),"
Economics Letters, Elsevier, vol. 204(C).
- Biewen, Martin & Kugler, Philipp, 2020. "Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)," IZA Discussion Papers 13613, Institute of Labor Economics (IZA).
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- Koryu Sato & Haruko Noguchi & Kosuke Inoue, 2023. "Heterogeneous Treatment Effect of Retirement on Cognitive Function," Working Papers 2306, Waseda University, Faculty of Political Science and Economics.
- Biewen, Martin & Kugler, Philipp, 2021.
"Two-stage least squares random forests with an application to Angrist and Evans (1998),"
Economics Letters, Elsevier, vol. 204(C).
- Biewen, Martin & Kugler, Philipp, 2020. "Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)," IZA Discussion Papers 13613, Institute of Labor Economics (IZA).
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More about this item
Keywords
Machine learning; Generalized random forests; Fertility; Instrumental variable estimation;All these keywords.
JEL classification:
- C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
- C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
- J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
- J13 - Labor and Demographic Economics - - Demographic Economics - - - Fertility; Family Planning; Child Care; Children; Youth
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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