Two-Stage Least Squares Random Forests with a Replication of Angrist and Evans (1998)

Philipp Kugler and Martin Biewen

VfS Annual Conference 2020 (Virtual Conference): Gender Economics from Verein für Socialpolitik / German Economic Association

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: machine learning; generalized random forests; fertility; instrumental variable estimation (search for similar items in EconPapers)
JEL-codes: C14 C26 C55 J13 J22 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:vfsc20:224538

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