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Estimating Risk Preferences in the Field


  • Levon Barseghyan
  • Francesca Molinari
  • Ted O'Donoghue
  • Joshua C. Teitelbaum


We survey the literature on estimating risk preferences using field data. We concentrate our attention on studies in which risk preferences are the focal object and estimating their structure is the core enterprise. We review a number of models of risk preferences—including both expected utility (EU) theory and non-EU models—that have been estimated using field data, and we highlight issues related to identification and estimation of such models using field data. We then survey the literature, giving separate treatment to research that uses individual-level data (e.g., property-insurance data) and research that uses aggregate data (e.g., betting-market data). We conclude by discussing directions for future research.

Suggested Citation

  • Levon Barseghyan & Francesca Molinari & Ted O'Donoghue & Joshua C. Teitelbaum, 2018. "Estimating Risk Preferences in the Field," Journal of Economic Literature, American Economic Association, vol. 56(2), pages 501-564, June.
  • Handle: RePEc:aea:jeclit:v:56:y:2018:i:2:p:501-64
    Note: DOI: 10.1257/jel.20161148

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    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. James K. Hammitt, 2020. "Valuing mortality risk in the time of COVID-19," Journal of Risk and Uncertainty, Springer, vol. 61(2), pages 129-154, October.
    2. Johannes G. Jaspersen & Marc A. Ragin & Justin R. Sydnor, 2019. "Predicting Insurance Demand from Risk Attitudes," NBER Working Papers 26508, National Bureau of Economic Research, Inc.
    3. Kuroishi, Yusuke & Sawada, Yasuyuki, 2019. "Motivations behind prosocial behavior: Evidence from the Philippines," Journal of Asian Economics, Elsevier, vol. 64(C), pages 1-1.
    4. Jiong Gong & Ping Jiang & Xiaochuan Xing, 2018. "Compensation Convexity without Utility Restriction," Australian Economic Papers, Wiley Blackwell, vol. 57(3), pages 238-249, September.
    5. Levon Barseghyan & Francesca Molinari & Matthew Thirkettle, 2019. "Discrete choice under risk with limited consideration," CeMMAP working papers CWP08/19, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    6. Undral Byambadalai & Ching-to Albert Ma & Daniel Wiesen, 2019. "Changing Preferences: An Experiment and Estimation of Market-Incentive E§ects on Altruism," Boston University - Department of Economics - Working Papers Series WP2019-11, Boston University - Department of Economics.
    7. Moshe A. Milevsky, 2018. "Swimming with Wealthy Sharks: Longevity, Volatility and the Value of Risk Pooling," Papers 1811.11326,
    8. Xue, Xiaole & Wei, Pengyu & Weng, Chengguo, 2019. "Derivatives trading for insurers," Insurance: Mathematics and Economics, Elsevier, vol. 84(C), pages 40-53.

    More about this item

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D11 - Microeconomics - - Household Behavior - - - Consumer Economics: Theory
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • I13 - Health, Education, and Welfare - - Health - - - Health Insurance, Public and Private


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