Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/130093
Authors: 
Lee, Sokbae
Okui, Ryo
Wang, Yoon-Jae
Year of Publication: 
2016
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP03/16
Abstract: 
In this paper, we propose a doubly robust method to present the heterogeneity of the average treatment effect with respect to observed covariates of interest. We consider a situation where a large number of covariates are needed for identifying the average treatment effect but the covariates of interest for analyzing heterogeneity are of much lower dimension. Our proposed estimator is doubly robust and avoids the curse of dimensionality. We propose a uniform confidence band that is easy to compute, and we illustrate its usefulness via Monte Carlo experiments and an application to the effects of smoking on birth weights.
Subjects: 
average treatment effect conditional on covariates
uniform confidence band
double robustness
Gaussian approximation
JEL: 
C14
C21
Document Type: 
Working Paper

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