Arbeitspapier
Doubly robust uniform confidence band for the conditional average treatment effect function
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.
- Sprache
-
Englisch
- Erschienen in
-
Series: cemmap working paper ; No. CWP03/16
Klassifikation
Wirtschaft
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Semiparametric and Nonparametric Methods: General
Single Equation Models; Single Variables: Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
Thema
average treatment effect conditional on covariates
uniform confidence band
double robustness
Gaussian approximation
uniform confidence band
double robustness
Gaussian approximation
Ereignis
Geistige Schöpfung
(wer)
Lee, Sokbae
Okui, Ryo
Wang, Yoon-Jae
Okui, Ryo
Wang, Yoon-Jae
Ereignis
Veröffentlichung
(wer)
Centre for Microdata Methods and Practice (cemmap)
(wo)
London
(wann)
2016
- DOI
-
doi:10.1920/wp.cem.2016.0316
- Handle
- Letzte Aktualisierung
-
20.09.2024, 08:24 MESZ
Objekttyp
- Arbeitspapier
Beteiligte
- Lee, Sokbae
- Okui, Ryo
- Wang, Yoon-Jae
- Centre for Microdata Methods and Practice (cemmap)
Entstanden
- 2016
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