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Varieties of risk preference elicitation

Author

Listed:
  • Friedman, Daniel
  • Habib, Sameh
  • James, Duncan
  • Williams, Brett
Abstract
We explore risk preference elicitation when subjects choose directly from an exogenously specified set of lotteries. Our choice tasks differ incrementally, e.g., from choosing between two lotteries to selecting a portfolio from a continuous set of bundled Arrow securities, and from text to spatial presentation. Each subject completes multiple instances of five different tasks, and responses for each task are summarized in parametric (CRRA) and non-parametric (normalized risk premium) measures of risk preference. Variation in task attributes explains much of the observed wide variation in elicited preferences and in correlations across task pairs.

Suggested Citation

  • Friedman, Daniel & Habib, Sameh & James, Duncan & Williams, Brett, 2022. "Varieties of risk preference elicitation," Games and Economic Behavior, Elsevier, vol. 133(C), pages 58-76.
    • Handle: RePEc:eee:gamebe:v:133:y:2022:i:c:p:58-76
    DOI: 10.1016/j.geb.2022.02.002
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Segovia, Michelle & Palma, Marco & Lusk, Jayson L. & Drichoutis, Andreas, 2022. "Visual formats in risk preference elicitation: What catches the eye?," MPRA Paper 115572, University Library of Munich, Germany.
    2. Mikhail Freer & Daniel Friedman & Simon Weidenholzer, 2023. "Motives for Delegating Financial Decisions," Papers 2309.03419, arXiv.org, revised Apr 2024.
    3. Beşliu, Corina, 2022. "Complexity in insurance selection: Cross-classified multilevel analysis of experimental data," Journal of Behavioral and Experimental Finance, Elsevier, vol. 35(C).
    4. Liu Shi & Jianying Qiu & Jiangyan Li & Frank Bohn, 2024. "Consciously stochastic in preference reversals," Journal of Risk and Uncertainty, Springer, vol. 68(3), pages 255-297, June.
    5. Fidanoski, Filip & Johnson, Timothy, 2023. "A z-Tree implementation of the Dynamic Experiments for Estimating Preferences [DEEP] method," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    6. Gary Charness & Nir Chemaya & Dario Trujano-Ochoa, 2023. "Learning your own risk preferences," Journal of Risk and Uncertainty, Springer, vol. 67(1), pages 1-19, August.
    7. Jacob K Goeree & Bernardo Garcia-Pola, 2023. "A Non-Parametric Test of Risk Aversion," Papers 2308.02083, arXiv.org.
    8. Brice Corgnet & Roberto Hernán González, 2023. "On The Appeal Of Complexity," Working Papers 2312, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    9. Collins, Sean M. & James, Duncan, 2024. "Hidden in plain sight: Payoffs, probability, space, and time in isomorphic tasks," Games and Economic Behavior, Elsevier, vol. 145(C), pages 117-136.
    10. Michele Garagnani, 2023. "The predictive power of risk elicitation tasks," Journal of Risk and Uncertainty, Springer, vol. 67(2), pages 165-192, October.

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    More about this item

    Keywords

    Risk aversion; Experiment; Elicitation; Multiple price list;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D89 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Other

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