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Average Treatment Effect Bounds with an Instrumental Variable: Theory and Practice

Author

Listed:
  • Carlos A. Flores

    (California Polytechnic State University)

  • Xuan Chen

    (Renmin University of China)

Abstract

No abstract is available for this item.

Suggested Citation

  • Carlos A. Flores & Xuan Chen, 2018. "Average Treatment Effect Bounds with an Instrumental Variable: Theory and Practice," Springer Books, Springer, number 978-981-13-2017-0, December.
    • Handle: RePEc:spr:sprbok:978-981-13-2017-0
    DOI: 10.1007/978-981-13-2017-0
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    Citations

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    Cited by:

    1. Lina Zhang & David T. Frazier & Don S. Poskitt & Xueyan Zhao, 2020. "Decomposing Identification Gains and Evaluating Instrument Identification Power for Partially Identified Average Treatment Effects," Monash Econometrics and Business Statistics Working Papers 34/20, Monash University, Department of Econometrics and Business Statistics.
    2. Donald S. Poskitt & Xueyan Zhao, 2023. "Bootstrap Hausdorff Confidence Regions for Average Treatment Effect Identified Sets," Monash Econometrics and Business Statistics Working Papers 9/23, Monash University, Department of Econometrics and Business Statistics.
    3. Heshani Madigasekara & D. S. Poskitt & Lina Zhang & Xueyan Zhao, 2024. "Partial Identification of Distributional Treatment Effects in Panel Data using Copula Equality Assumptions," Papers 2411.04450, arXiv.org.
    4. Hodjo, Manzamasso & Dalton, Timothy & Nakelse, Tebila & Acharya, Ram N & Blayney, Don, 2021. "From coupon to calories: Assessing input coupon impact on household food calories production," World Development Perspectives, Elsevier, vol. 22(C).
    5. Matthew A. Masten & Alexandre Poirier, 2021. "Salvaging Falsified Instrumental Variable Models," Econometrica, Econometric Society, vol. 89(3), pages 1449-1469, May.

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