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Evolution of subjective hurricane risk perceptions: A Bayesian approach

David Kelly (), David Letson, Forrest Nelson, David S. Nolan and Daniel Solis ()

Journal of Economic Behavior & Organization, 2012, vol. 81, issue 2, 644-663

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.

Keywords: Risk perceptions; Correlated information; Bayesian learning; Event markets; Prediction markets; Favorite-longshot bias; Hurricanes (search for similar items in EconPapers)
Date: 2012
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Working Paper: Evolution of Subjective Hurricane Risk Perceptions: A Bayesian Approach (2009) Downloads
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Handle: RePEc:eee:jeborg:v:81:y:2012:i:2:p:644-663