Two-Stage Least Squares Random Forests with an Application to Angrist and Evans (1998)

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: IZA Discussion Papers ; No. 13613

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models: Single Variables: Instrumental Variables (IV) Estimation ; Large Data Sets: Modeling and Analysis ; Time Allocation and Labor Supply ; Fertility; Family Planning; Child Care; Children; Youth ; Semiparametric and Nonparametric Methods: General
• Subject: machine learning ; generalized random forests ; fertility ; instrumental variable estimation

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Biewen, Martin ; Kugler, Philipp
• Event: Veröffentlichung
• (who): Institute of Labor Economics (IZA)
• (where): Bonn
• (when): 2020

Further information

• Handle: http://hdl.handle.net/10419/224055
• Last update: 10.03.2025, 11:43 AM CET