Joshua C. Teitelbaum

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We use data on households’ deductible choices in auto and home insurance to estimate a structural model of risky choice that incorporates "standard" risk aversion (concave utility over final wealth), loss aversion, and nonlinear probability weighting. Our estimates indicate that nonlinear probability weighting plays the most important role in explaining the(More)
There is a large literature that attempts to estimate risk preferences from field data (e.g., Jullien and Salanié 2000 (horse race bets); Cohen and Einav 2007 (auto insurance); Snowberg and Wolfers 2010 (horse race bets); Sydnor 2010 (home insurance); Barseghyan et al. forthcoming (auto and home insurance)). Many of the studies in this literature consider(More)
We use data on households’ deductible choices in auto and home insurance to estimate a structural model of risky choice that incorporates "standard" risk aversion (concave utility over final wealth), loss aversion, and nonlinear probability weighting. Our estimates indicate that nonlinear probability weighting plays the most important role in explaining the(More)
We survey the literature on estimating risk preferences using field data—i.e., data on individuals’real-world economic behavior. We mostly limit our attention to studies in which risk preferences are the focal object and estimating their structure is the core enterprise. We motivate shining a spotlight on this literature with an example that highlights why(More)
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