Two-stage least squares random forests with an application to Angrist and Evans (1998)

Martin Biewen, Philipp Kugler

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.

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Year of publication:	August 2020
Authors:	Biewen, Martin ; Kugler, Philipp
Publisher:	Bonn, Germany : IZA - Institute of Labor Economics
Subject:	machine learning \| generalized random forests \| fertility \| instrumental variable estimation \| Künstliche Intelligenz \| Artificial intelligence \| Fertilität \| Fertility \| Schätztheorie \| Estimation theory \| Forstwirtschaft \| Forestry \| Forstpolitik \| Forest policy \| IV-Schätzung \| Instrumental variables \| Kleinste-Quadrate-Methode \| Least squares method

Extent:	1 Online-Ressource (circa 24 Seiten) Illustrationen
Series:	Discussion paper series / IZA. - Bonn : IZA, ISSN 2365-9793, ZDB-ID 2120053-1. - Vol. no. 13613
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Graue Literatur ; Non-commercial literature ; Arbeitspapier ; Working Paper
Language:	English
Other identifiers:	hdl:10419/224055 [Handle]
Classification:	c26 ; c55 ; J22 - Time Allocation and Labor Supply ; J13 - Fertility; Family Planning; Child Care; Children; Youth ; C14 - Semiparametric and Nonparametric Methods
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012269068