TY  - RPRT
        AU  - Biewen, Martin
AU  - Kugler, Philipp
        TI  - Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)
        PY  - 2020/Aug/
        PB  - Institute of Labor Economics (IZA)
        CY  - Bonn
        T2  - IZA Discussion Paper
        IS  - 13613
        UR  - https://www.iza.org/publications/dp13613
        AB  - We develop the case of two-stage least squares estimation (2SLS) in the general framework of Athey et al. (Generalized Random Forests, Annals of Statistics, Vol. 47, 2019) and provide a software implementation for R and C++. We use the method to revisit the classic application of instrumental variables in Angrist and Evans (Children and Their Parents' Labor Supply: Evidence from Exogenous Variation in Family Size, American Economic Review, Vol. 88, 1998). The two-stage least squares random forest allows one to investigate local heterogenous effects that cannot be investigated using ordinary 2SLS.
        KW  - fertility
KW  - generalized random forests
KW  - machine learning
KW  - instrumental variable estimation
        ER  -