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Evolution of subjective hurricane risk perceptions: A Bayesian approach

Author

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  • Kelly, David L.
  • Letson, David
  • Nelson, Forrest
  • Nolan, David S.
  • Solís, Daniel

Abstract

How do decision makers weight private and official information sources which are correlated and differ in accuracy and bias? This paper studies how traders update subjective risk perceptions after receiving expert opinions, using a unique data set from a prediction market, the Hurricane Futures Market (HFM). We derive a theoretical Bayesian framework which predicts how traders update the probability of a hurricane making landfall in a certain range of coastline, after receiving correlated track forecast information from official and unofficial sources. Our results suggest that traders behave in a way not inconsistent with Bayesian updating but this behavior is based on the perceived quality of the information received. Official information sources are discounted when a perception of bias and credible alternatives exist.

Suggested Citation

  • Kelly, David L. & Letson, David & Nelson, Forrest & Nolan, David S. & Solís, Daniel, 2012. "Evolution of subjective hurricane risk perceptions: A Bayesian approach," Journal of Economic Behavior & Organization, Elsevier, vol. 81(2), pages 644-663.
    • Handle: RePEc:eee:jeborg:v:81:y:2012:i:2:p:644-663
    DOI: 10.1016/j.jebo.2011.10.004
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    2. Conte, Marc N. & Kelly, David L., 2018. "An imperfect storm: Fat-tailed tropical cyclone damages, insurance, and climate policy," Journal of Environmental Economics and Management, Elsevier, vol. 92(C), pages 677-706.
    3. Craig W. Trumbo & Lori Peek & Michelle A. Meyer & Holly L. Marlatt & Eve Gruntfest & Brian D. McNoldy & Wayne H. Schubert, 2016. "A Cognitive‐Affective Scale for Hurricane Risk Perception," Risk Analysis, John Wiley & Sons, vol. 36(12), pages 2233-2246, December.
    4. Kajii, Atsushi & Watanabe, Takahiro, 2017. "Favorite–longshot bias in pari-mutuel betting: An evolutionary explanation," Journal of Economic Behavior & Organization, Elsevier, vol. 140(C), pages 56-69.
    5. Xu, Haifeng & Ding, Yi & Zhang, Cheng & Tan, Bernard C.Y., 2023. "Too official to be effective: An empirical examination of unofficial information channel and continued use of retracted articles," Research Policy, Elsevier, vol. 52(7).
    6. Karsten Hueffer & Miguel A. Fonseca & Anthony Leiserowitz & Karen M. Taylor, 2013. "The wisdom of crowds: Predicting a weather and climate-related event," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 8(2), pages 91-105, March.

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    More about this item

    Keywords

    Risk perceptions; Correlated information; Bayesian learning; Event markets; Prediction markets; Favorite-longshot bias; Hurricanes;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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