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Inference under covariate-adaptive randomization with imperfect compliance

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  • Bugni, Federico A.
  • Gao, Mengsi

Abstract

This paper studies inference in a randomized controlled trial (RCT) with covariate-adaptive randomization (CAR) and imperfect compliance of a binary treatment. In this context, we study inference on the local average treatment effect (LATE), i.e., the average treatment effect conditional on individuals that always comply with the assigned treatment. As in Bugni et al. (2018, 2019), CAR refers to randomization schemes that first stratify according to baseline covariates and then assign treatment status so as to achieve “balance” within each stratum. In contrast to these papers, however, we allow participants of the RCT to endogenously decide to comply or not with the assigned treatment status.

Suggested Citation

  • Bugni, Federico A. & Gao, Mengsi, 2023. "Inference under covariate-adaptive randomization with imperfect compliance," Journal of Econometrics, Elsevier, vol. 237(1).
    • Handle: RePEc:eee:econom:v:237:y:2023:i:1:s0304407623002130
    DOI: 10.1016/j.jeconom.2023.105497
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    References listed on IDEAS

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    1. Pascaline Dupas & Dean Karlan & Jonathan Robinson & Diego Ubfal, 2018. "Banking the Unbanked? Evidence from Three Countries," American Economic Journal: Applied Economics, American Economic Association, vol. 10(2), pages 257-297, April.
    2. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2018. "Inference Under Covariate-Adaptive Randomization," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(524), pages 1784-1796, October.
    3. Yuehao Bai, 2022. "Optimality of Matched-Pair Designs in Randomized Controlled Trials," American Economic Review, American Economic Association, vol. 112(12), pages 3911-3940, December.
    4. Federico A. Bugni & Ivan A. Canay & Azeem M. Shaikh, 2019. "Inference under covariate‐adaptive randomization with multiple treatments," Quantitative Economics, Econometric Society, vol. 10(4), pages 1747-1785, November.
    5. Duflo, Esther & Glennerster, Rachel & Kremer, Michael, 2008. "Using Randomization in Development Economics Research: A Toolkit," Handbook of Development Economics, in: T. Paul Schultz & John A. Strauss (ed.), Handbook of Development Economics, edition 1, volume 4, chapter 61, pages 3895-3962, Elsevier.
    6. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    7. Max Tabord-Meehan, 2023. "Stratification Trees for Adaptive Randomisation in Randomised Controlled Trials," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 90(5), pages 2646-2673.
    8. Vincent Somville & Lore Vandewalle, 2018. "Saving by Default: Evidence from a Field Experiment in Rural India," American Economic Journal: Applied Economics, American Economic Association, vol. 10(3), pages 39-66, July.
    9. Orazio Attanasio & Adriana Kugler & Costas Meghir, 2011. "Subsidizing Vocational Training for Disadvantaged Youth in Colombia: Evidence from a Randomized Trial," American Economic Journal: Applied Economics, American Economic Association, vol. 3(3), pages 188-220, July.
    10. Miriam Bruhn & David McKenzie, 2009. "In Pursuit of Balance: Randomization in Practice in Development Field Experiments," American Economic Journal: Applied Economics, American Economic Association, vol. 1(4), pages 200-232, October.
    11. Yuehao Bai, 2022. "Optimality of Matched-Pair Designs in Randomized Controlled Trials," Papers 2206.07845, arXiv.org.
    12. Ansel Jason & Hong Han & Jessie Li and, 2018. "OLS and 2SLS in Randomized and Conditionally Randomized Experiments," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 238(3-4), pages 243-293, July.
    13. Joshua Angrist & Victor Lavy, 2009. "The Effects of High Stakes High School Achievement Awards: Evidence from a Randomized Trial," American Economic Review, American Economic Association, vol. 99(4), pages 1384-1414, September.
    14. Craig McIntosh & Tito Alegría & Gerardo Ordóñez & René Zenteno, 2018. "The Neighborhood Impacts of Local Infrastructure Investment: Evidence from Urban Mexico," American Economic Journal: Applied Economics, American Economic Association, vol. 10(3), pages 263-286, July.
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    More about this item

    Keywords

    Covariate-adaptive randomization; Stratified block randomization; Treatment assignment; Randomized controlled trial; Strata fixed effects; Saturated regression; Imperfect compliance;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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