@TechReport{iza:izadps:dp13613,
            	author={Biewen, Martin and Kugler, Philipp},
            	title={Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)},
            	year={2020},
	month={Aug},
            	institution={Institute of Labor Economics (IZA)},
            	address={Bonn},
            	type={IZA Discussion Paper},
            	number={13613},
            	url={https://www.iza.org/publications/dp13613},
	abstract={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.},
	keywords={fertility;generalized random forests;machine learning;instrumental variable estimation},
            }