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

Author

Listed:
  • Sokbae (Simon) Lee

    (Institute for Fiscal Studies and Columbia University)

  • Ryo Okui

    (Institute for Fiscal Studies and Kyoto University)

  • Yoon-Jae Whang

    (Institute for Fiscal Studies and SNU)

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 confi dence 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 CWP03/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    • Handle: RePEc:ifs:cemmap:03/16
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Average treatment effect conditional on covariates; uniform confidence band; double robustness; Gaussian approximation.;
    All these keywords.

    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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