Estimation of conditional average treatment effects with high-dimensional data

Estimation of conditional average treatment effects with high-dimensional data

Given the unconfoundedness assumption, we propose new nonparametric estimators for the reduced dimensional conditional average treatment effect (CATE) function. In the first stage, the nuisance functions necessary for identifying CATE are estimated by machine learning methods, allowing the number of...

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書目詳細資料
Main Authors:	FAN, Qingliang, HSU, Yu-Chin, LIELI, Robert P., ZHANG, Yichong
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2020
主題:	Heterogenous treatment effects high-dimensional data uniform confidence band Econometrics
在線閱讀:	https://ink.library.smu.edu.sg/soe_research/2455 https://ink.library.smu.edu.sg/context/soe_research/article/3454/viewcontent/Unconditional_Quantile_Regression_High_D_sv.pdf
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機構:	Singapore Management University
語言:	English

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