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Tests for distributional treatment effects under unconfoundedness

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  • Maier, Michael
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    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.

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    File URL: http://www.sciencedirect.com/science/article/B6V84-517J239-2/2/4402c1936dae5e83b7bc7ed551e240c9
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    Bibliographic Info

    Article provided by Elsevier in its journal Economics Letters.

    Volume (Year): 110 (2011)
    Issue (Month): 1 (January)
    Pages: 49-51

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    Handle: RePEc:eee:ecolet:v:110:y:2011:i:1:p:49-51

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    Web page: http://www.elsevier.com/locate/ecolet

    Related research

    Keywords: Distributional treatment effects Econometric evaluation Kolmogorov-Smirnov test Unconfoundedness;

    References

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    1. Guido M. Imbens & Jeffrey M. Wooldridge, 2008. "Recent Developments in the Econometrics of Program Evaluation," NBER Working Papers 14251, National Bureau of Economic Research, Inc.
    2. Marianne Bitler & Jonah Gelbach & Hilary Hoynes, 2003. "What Mean Impacts Miss: Distributional Effects of Welfare Reform Experiments," NBER Working Papers 10121, National Bureau of Economic Research, Inc.
    3. 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.
    4. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
    5. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
    6. Sergio Firpo, 2007. "Efficient Semiparametric Estimation of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 75(1), pages 259-276, 01.
    7. Firpo, Sergio, 2010. "Identification and Estimation of Distributional Impacts of Interventions Using Changes in Inequality Measures," IZA Discussion Papers 4841, Institute for the Study of Labor (IZA).
    8. Heckman, James J & Ichimura, Hidehiko & Todd, Petra, 1998. "Matching as an Econometric Evaluation Estimator," Review of Economic Studies, Wiley Blackwell, vol. 65(2), pages 261-94, April.
    9. Cowell, F.A., 2000. "Measurement of inequality," Handbook of Income Distribution, in: A.B. Atkinson & F. Bourguignon (ed.), Handbook of Income Distribution, edition 1, volume 1, chapter 2, pages 87-166 Elsevier.
    10. 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.
    11. Alberto Abadie & Joshua Angrist & Guido Imbens, 1999. "Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings," Working papers 99-16, Massachusetts Institute of Technology (MIT), Department of Economics.
    12. repec:cup:cbooks:9780521496032 is not listed on IDEAS
    13. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    14. Markus Frölich & Blaise Melly, 2007. "Unconditional quantile treatment effects under endogeneity," CeMMAP working papers CWP32/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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    Cited by:
    1. 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.

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