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An Empirical Model Of Learning Under Ambiguity: The Case Of Clinical Trials

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  • Jose M. Fernandez

Abstract

This article presents a two‐dimensional structural model of learning under ambiguity in the context of clinical trials. Clinical trials offer an ideal environment to study learning under ambiguity. The randomization process found in these studies leaves patients uncertain to their actual group assignment. Therefore, patients cannot immediately attribute changes in health to the experimental drug. The article proposes the use of “learning instrumental variables” to simultaneously update patients’ beliefs of the treatment effect and group assignment. Patient learning is found to be faster when observable side effects are incorporated to account for the uncertainty in group assignment.

Suggested Citation

  • Jose M. Fernandez, 2013. "An Empirical Model Of Learning Under Ambiguity: The Case Of Clinical Trials," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 54(2), pages 549-573, May.
    • Handle: RePEc:wly:iecrev:v:54:y:2013:i:2:p:549-573
    DOI: iere.12006
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    Cited by:

    1. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Learning Models: An Assessment of Progress, Challenges and New Developments," Economics Papers 2013-W07, Economics Group, Nuffield College, University of Oxford.
    2. Barton H. Hamilton & Andrés Hincapié & Robert A. Miller & Nicholas W. Papageorge, 2021. "Innovation And Diffusion Of Medical Treatment," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(3), pages 953-1009, August.
    3. Mark Egan & Tomas Philipson, 2016. "Health Care Adherence and Personalized Medicine," Working Papers 2016-H01, Becker Friedman Institute for Research In Economics.
    4. Andrew T. Ching & Tülin Erdem & Michael P. Keane, 2013. "Invited Paper ---Learning Models: An Assessment of Progress, Challenges, and New Developments," Marketing Science, INFORMS, vol. 32(6), pages 913-938, November.
    5. Jürgen Maurer & Katherine M. Harris, 2016. "Learning to Trust Flu Shots: Quasi‐Experimental Evidence from the 2009 Swine Flu Pandemic," Health Economics, John Wiley & Sons, Ltd., vol. 25(9), pages 1148-1162, September.
    6. Maurer, J. & Harris, K.M., 2015. "Learning to trust flu shots: quasi-experimental evidence on the role of learning in influenza vaccination decisions from the 2009 influenza A/H1N1 (swine flu) pandemic," Health, Econometrics and Data Group (HEDG) Working Papers 15/19, HEDG, c/o Department of Economics, University of York.

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    More about this item

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • I1 - Health, Education, and Welfare - - Health

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