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Tests for distributional treatment effects under unconfoundedness

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  • Maier, Michael

Abstract

This note describes tests for distributional treatment effects under the unconfoundedness assumption. Tests for distributional equality and stochastic dominance as well as a bootstrap procedure for computing critical values are presented, and the asymptotic properties of the procedure are derived.

Suggested Citation

  • Maier, Michael, 2011. "Tests for distributional treatment effects under unconfoundedness," Economics Letters, Elsevier, vol. 110(1), pages 49-51, January.
    • Handle: RePEc:eee:ecolet:v:110:y:2011:i:1:p:49-51
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    Cited by:

    1. Masahiro Kato & Akari Ohda & Masaaki Imaizumi, 2023. "Asymptotically Unbiased Synthetic Control Methods by Distribution Matching," Papers 2307.11127, arXiv.org, revised May 2024.
    2. Donald, Stephen G. & Hsu, Yu-Chin, 2014. "Estimation and inference for distribution functions and quantile functions in treatment effect models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 383-397.
    3. Victor Chernozhukov & Iván Fernández‐Val & Blaise Melly, 2013. "Inference on Counterfactual Distributions," Econometrica, Econometric Society, vol. 81(6), pages 2205-2268, November.
    4. Steven F. Lehrer & R. Vincent Pohl & Kyungchul Song, 2022. "Multiple Testing and the Distributional Effects of Accountability Incentives in Education," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 40(4), pages 1552-1568, October.
    5. Steven F. Lehrer & R. Vincent Pohl & Kyungchul Song, 2016. "Targeting Policies: Multiple Testing and Distributional Treatment Effects," NBER Working Papers 22950, National Bureau of Economic Research, Inc.

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