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Identification of Treatment Effects under Conditional Partial Independence

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  • Matthew A. Masten
  • Alexandre Poirier

Abstract

Conditional independence of treatment assignment from potential outcomes is a commonly used but nonrefutable assumption. We derive identified sets for various treatment effect parameters under nonparametric deviations from this conditional independence assumption. These deviations are defined via a conditional treatment assignment probability, which makes it straightforward to interpret. Our results can be used to assess the robustness of empirical conclusions obtained under the baseline conditional independence assumption.

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  • Matthew A. Masten & Alexandre Poirier, 2017. "Identification of Treatment Effects under Conditional Partial Independence," Papers 1707.09563, arXiv.org.
    • Handle: RePEc:arx:papers:1707.09563
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    1. Ivan A. Canay & Azeem M. Shaikh, 2016. "Practical and theoretical advances in inference for partially identified models," CeMMAP working papers CWP05/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Charles F. Manski, 1989. "Anatomy of the Selection Problem," Journal of Human Resources, University of Wisconsin Press, vol. 24(3), pages 343-360.
    3. Joseph G. Altonji & Todd E. Elder & Christopher R. Taber, 2005. "Selection on Observed and Unobserved Variables: Assessing the Effectiveness of Catholic Schools," Journal of Political Economy, University of Chicago Press, vol. 113(1), pages 151-184, February.
    4. Andrea Ichino & Fabrizia Mealli & Tommaso Nannicini, 2008. "From temporary help jobs to permanent employment: what can we learn from matching estimators and their sensitivity?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(3), pages 305-327.
    5. Jörg Stoye, 2010. "Partial identification of spread parameters," Quantitative Economics, Econometric Society, vol. 1(2), pages 323-357, November.
    6. Matthew Masten & Alexandre Poirier, 2016. "Partial independence in nonseparable models," CeMMAP working papers CWP26/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    7. Molinari, Francesca & Peski, Marcin, 2006. "Generalization Of A Result On “Regressions, Short And Long”," Econometric Theory, Cambridge University Press, vol. 22(1), pages 159-163, February.
    8. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    9. Rosenbaum, Paul R. & Silber, Jeffrey H., 2009. "Amplification of Sensitivity Analysis in Matched Observational Studies," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1398-1405.
    10. V. Joseph Hotz & Charles H. Mullin & Seth G. Sanders, 1997. "Bounding Causal Effects Using Data from a Contaminated Natural Experiment: Analysing the Effects of Teenage Childbearing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 575-603.
    11. Philip J. Cross & Charles F. Manski, 2002. "Regressions, Short and Long," Econometrica, Econometric Society, vol. 70(1), pages 357-368, January.
    12. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881.
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    Cited by:

    1. Nathan Canen & Kyungchul Song, 2021. "Counterfactual analysis under partial identification using locally robust refinement," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(4), pages 416-436, June.
    2. Matthew A. Masten & Alexandre Poirier, 2022. "The Effect of Omitted Variables on the Sign of Regression Coefficients," Papers 2208.00552, arXiv.org, revised Feb 2023.
    3. Matthew A. Masten & Alexandre Poirier & Linqi Zhang, 2024. "Assessing Sensitivity to Unconfoundedness: Estimation and Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(1), pages 1-13, January.
    4. Tenglong Li & Kenneth A. Frank, 2020. "The probability of a robust inference for internal validity and its applications in regression models," Papers 2005.12784, arXiv.org.
    5. Paul Diegert & Matthew A. Masten & Alexandre Poirier, 2022. "Assessing Omitted Variable Bias when the Controls are Endogenous," Papers 2206.02303, arXiv.org, revised Jul 2023.
    6. Tenglong Li & Kenneth A. Frank & Mingming Chen, 2024. "A Conceptual Framework for Quantifying the Robustness of a Regression-Based Causal Inference in Observational Study," Mathematics, MDPI, vol. 12(3), pages 1-14, January.
    7. Arkadiusz Szydłowski, 2019. "Endogenous censoring in the mixed proportional hazard model with an application to optimal unemployment insurance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 34(7), pages 1086-1101, November.
    8. Sungwon Lee, 2021. "Partial Identification and Inference for Conditional Distributions of Treatment Effects," Papers 2108.00723, arXiv.org, revised Nov 2023.
    9. Christophe Bruneel-Zupanc, 2023. "Don't (fully) exclude me, it's not necessary! Identification with semi-IVs," Papers 2303.12667, arXiv.org, revised Jul 2023.
    10. Roy Allen & John Rehbeck, 2020. "Counterfactual and Welfare Analysis with an Approximate Model," Papers 2009.03379, arXiv.org.
    11. Sakaue, Katsuki & Wokadala, James, 2022. "Effects of including refugees in local government schools on pupils’ learning achievement: Evidence from West Nile, Uganda," International Journal of Educational Development, Elsevier, vol. 90(C).
    12. Yiwei Sun, 2023. "Extrapolating Away from the Cutoff in Regression Discontinuity Designs," Papers 2311.18136, arXiv.org.
    13. Tenglong Li & Kenneth A. Frank, 2019. "On the probability of a causal inference is robust for internal validity," Papers 1906.08726, arXiv.org.
    14. Sungwon Lee, 2024. "Partial identification and inference for conditional distributions of treatment effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 107-127, January.

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