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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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    1. Marianne P. Bitler & Jonah B. Gelbach & Hilary W. Hoynes, 2006. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," American Economic Review, American Economic Association, vol. 96(4), pages 988-1012, September.
    2. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, January.
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    5. Sergio Firpo & Cristine Pinto, 2016. "Identification and Estimation of Distributional Impacts of Interventions Using Changes in Inequality Measures," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 457-486, April.
    6. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    7. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2003. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometrica, Econometric Society, vol. 71(4), pages 1161-1189, July.
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    12. Chernozhukov, Victor & Hansen, Christian, 2006. "Instrumental quantile regression inference for structural and treatment effect models," Journal of Econometrics, Elsevier, vol. 132(2), pages 491-525, June.
    13. Myoung‐jae Lee, 2009. "Non‐parametric tests for distributional treatment effect for randomly censored responses," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(1), pages 243-264, January.
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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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