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Inference Under Stability Of Risk Preferences, Levon Barseghyan, Francesca Molinari, Joshua C. Teitelbaum
Inference Under Stability Of Risk Preferences, Levon Barseghyan, Francesca Molinari, Joshua C. Teitelbaum
Georgetown Law Faculty Publications and Other Works
We leverage the assumption that preferences are stable across contexts to partially identify and conduct inference on the parameters of a structural model of risky choice. Working with data on households' deductible choices across three lines of insurance coverage and a model that nests expected utility theory plus a range of non-expected utility models, we perform a revealed preference analysis that yields household-specific bounds on the model parameters. We then impose stability and other structural assumptions to tighten the bounds, and we explore what we can learn about households' risk preferences from the intervals defined by the bounds. We further …
Are Risk Preferences Stable Across Contexts? Evidence From Insurance Data, Levon Barseghyan, Jeffrey Prince, Joshua C. Teitelbaum
Are Risk Preferences Stable Across Contexts? Evidence From Insurance Data, Levon Barseghyan, Jeffrey Prince, Joshua C. Teitelbaum
Georgetown Law Faculty Publications and Other Works
Using a unique data set, the authors test whether households' deductible choices in auto and home insurance reflect stable risk preferences. Their test relies on a structural model that assumes households are objective expected utility maximizers and claims are generated by household-coverage specific Poisson processes. They find that the hypothesis of stable risk preferences is rejected by the data. Their analysis suggests that many households exhibit greater risk aversion in their home deductible choices than their auto deductible choices. They find that their results are robust to several alternative modeling assumptions.