%0 Report
        %A Biewen, Martin
%A Kugler, Philipp
        %T Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)
        %D 2020
        %8 2020 Aug
        %I Institute of Labor Economics (IZA)
        %C Bonn
        %7 IZA Discussion Paper
        %N 13613
        %U https://www.iza.org/publications/dp13613
        %X 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.
        %K fertility
%K generalized random forests
%K machine learning
%K instrumental variable estimation