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...

This paper is concerned with learning decision makers' preferences using data on observed choices from a finite set of risky alternatives. We propose a discrete choice model with unobserved heterogeneity in consideration sets and in standard risk aversion. We obtain sufficient conditions for the...

This paper is concerned with learning decision makers' (DMs) preferences using data on observed choices from a fi nite set of risky alternatives with monetary outcomes. We propose a discrete choice model with unobserved heterogeneity in consideration sets (the collection of alternatives...

Standard accident models are based on the expected utility framework and represent agents' beliefs about accident risk with a probability distribution. Consequently, they do not allow for Knightian uncertainty, or ambiguity, with respect to accident risk and cannot accommodate optimism...

Auto insurers often use credit-based insurance scores in their underwriting and rating processes. The practice is controversial — many consumer groups oppose it, and most states regulate it, in part out of concern that insurance scores proxy for policyholder income in predicting claim risk. We...