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Distinguishing Probability Weighting from Risk Misperceptions in Field Data

Author

Listed:
  • Levon Barseghyan
  • Francesca Molinari
  • Ted O'Donoghue
  • Joshua C. Teitelbaum
Abstract
We outline a strategy for distinguishing rank-dependent probability weighting from systematic risk misperceptions in field data. Our strategy relies on singling out a field environment with two key properties: (i) the objects of choice are money lotteries with more than two outcomes; and (ii) the ranking of outcomes differs across lotteries. We first present an abstract model of risky choice that elucidates the identification problem and our strategy. The model has numerous applications, including insurance choices and gambling. We then consider the application of insurance deductible choices and illustrate our strategy using simulated data.

Suggested Citation

  • Levon Barseghyan & Francesca Molinari & Ted O'Donoghue & Joshua C. Teitelbaum, 2013. "Distinguishing Probability Weighting from Risk Misperceptions in Field Data," American Economic Review, American Economic Association, vol. 103(3), pages 580-585, May.
    • Handle: RePEc:aea:aecrev:v:103:y:2013:i:3:p:580-85
    Note: DOI: 10.1257/aer.103.3.580
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    References listed on IDEAS

    as
    1. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    2. Alma Cohen & Liran Einav, 2007. "Estimating Risk Preferences from Deductible Choice," American Economic Review, American Economic Association, vol. 97(3), pages 745-788, June.
    3. Helga Fehr-Duda & Thomas Epper, 2012. "Probability and Risk: Foundations and Economic Implications of Probability-Dependent Risk Preferences," Annual Review of Economics, Annual Reviews, vol. 4(1), pages 567-593, July.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Hayley Clatterbuck & Clinton Castro & Arvo Mu~noz Mor'an, 2024. "Risk Alignment in Agentic AI Systems," Papers 2410.01927, arXiv.org.
    2. Yokoo, Hide-Fumi & Arimura, Toshi H. & Chattopadhyay, Mriduchhanda & Katayama, Hajime, 2023. "Subjective risk belief function in the field: Evidence from cooking fuel choices and health in India," Journal of Development Economics, Elsevier, vol. 161(C).
    3. Nicholas Barberis, 2013. "The Psychology of Tail Events: Progress and Challenges," American Economic Review, American Economic Association, vol. 103(3), pages 611-616, May.

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    More about this item

    JEL classification:

    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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