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Partial identification of the distribution of treatment effects and its confidence sets

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  • Fan, Yanqin
  • Park, Sang Soo

Abstract

In this paper, we study partial identification of the distribution of treatment effects of a binary treatment for ideal randomized experiments, ideal randomized experiments with a known value of a dependence measure, and for data satisfying the selection-on-observables assumption respectively. For ideal randomized experiments, (i) we propose nonparametric estimators of the sharp bounds on the distribution of treatment effects and construct asymptotically valid confidence sets for the distribution of treatment effects; (ii) we propose bias-corrected estimators of the sharp bounds on the distribution of treatment effects; and (iii) we investigate finite sample performances of the proposed confidence sets and the bias-corrected estimators via simulation.

Suggested Citation

  • Fan, Yanqin & Park, Sang Soo, 2009. "Partial identification of the distribution of treatment effects and its confidence sets," MPRA Paper 37148, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:37148
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Matthew Gentry & Tong Li, 2014. "Identification in Auctions With Selective Entry," Econometrica, Econometric Society, vol. 82(1), pages 315-344, January.
    2. Callaway, Brantly, 2021. "Bounds on distributional treatment effect parameters using panel data with an application on job displacement," Journal of Econometrics, Elsevier, vol. 222(2), pages 861-881.
    3. Matthew A. Masten & Alexandre Poirier, 2020. "Inference on breakdown frontiers," Quantitative Economics, Econometric Society, vol. 11(1), pages 41-111, January.
    4. Pablo Lavado & Gonzalo Rivera, 2016. "Identifying Treatment Effects with Data Combination and Unobserved Heterogeneity," Working Papers 2016-79, Peruvian Economic Association.
    5. Fan, Yanqin & Park, Sang Soo, 2012. "Confidence intervals for the quantile of treatment effects in randomized experiments," Journal of Econometrics, Elsevier, vol. 167(2), pages 330-344.
    6. Pablo Lavado, "undated". "Identifying Treatment Effects and Counterfactual Distributions using Data Combination with Unobserved Heterogeneity," Working Papers 13-25, Departamento de Economía, Universidad del Pacífico.
    7. Brantly Callaway, 2017. "Job Displacement during the Great Recession: Tight Bounds on Distributional Treatment Effect Parameters using Panel Data," DETU Working Papers 1703, Department of Economics, Temple University.
    8. Fan, Yanqin & Yu, Zhengfei, 2012. "Partial identification of distributional and quantile treatment effects in difference-in-differences models," Economics Letters, Elsevier, vol. 115(3), pages 511-515.
    9. Pablo Lavado & Gonzalo Rivera, 2015. "Identifying treatment effects and counterfactual distributions using data combination with unobserved heterogeneity," Working Papers 15-14, Centro de Investigación, Universidad del Pacífico.
    10. Fan, Yanqin & Guerre, Emmanuel & Zhu, Dongming, 2017. "Partial identification of functionals of the joint distribution of “potential outcomes”," Journal of Econometrics, Elsevier, vol. 197(1), pages 42-59.
    11. Chiburis, Richard C., 2010. "Semiparametric bounds on treatment effects," Journal of Econometrics, Elsevier, vol. 159(2), pages 267-275, December.
    12. Sergio Firpo & Antonio F. Galvao & Thomas Parker, 2019. "Uniform inference for value functions," Papers 1911.10215, arXiv.org, revised Apr 2021.
    13. Fan, Yanqin & Park, Sang Soo, 2014. "Nonparametric inference for counterfactual means: Bias-correction, confidence sets, and weak IV," Journal of Econometrics, Elsevier, vol. 178(P1), pages 45-56.
    14. Fan, Yanqin & Park, Sang Soo, 2010. "Confidence sets for some partially identified parameters," MPRA Paper 37149, University Library of Munich, Germany.
    15. Fan Yanqin & Sherman Robert & Shum Matthew, 2016. "Estimation and Inference in an Ecological Inference Model," Journal of Econometric Methods, De Gruyter, vol. 5(1), pages 17-48, January.

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    More about this item

    Keywords

    Confidence sets; partial identification; distribution; treatment effects;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C19 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Other
    • C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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