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Doubly robust uniform confidence band for the conditional average treatment effect function

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  • Sokbae (Simon) Lee
  • Ryo Okui
  • Yoon-Jae Whang

Abstract

In this paper, we propose a doubly robust method to present the heterogeneity of the average treatment e ffect with respect to observed covariates of interest. We consider a situation where a large number of covariates are needed for identifying the average treatment eff ect 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 eff ects of smoking on birth weights.

Suggested Citation

  • Sokbae (Simon) Lee & Ryo Okui & Yoon-Jae Whang, 2016. "Doubly robust uniform confidence band for the conditional average treatment effect function," CeMMAP working papers 03/16, Institute for Fiscal Studies.
    • Handle: RePEc:azt:cemmap:03/16
    DOI: 10.1920/wp.cem.2016.0316
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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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