We use data on insurance deductible choices to estimate a structural model of risky choice that incorporates standard risk aversion (diminishing marginal utility for wealth) and probability distortions. We find that probability distortions - characterized by substantial overweighting of small...

We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between agents' choice sets and...

We propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between agents' choice sets and...

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...

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...

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...

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...

Karni and Vierø (2013) propose a model of belief revision under growing awareness- reverse Bayesianism- which posits that as a person becomes aware of new acts, conse- quences, or act-consequence links, she revises her beliefs over an expanded state space in a way that preserves the relative...

Karni and Viero (2013) propose a model of belief revision under growing awareness reverse Bayesianism which posits that as a person becomes aware of new acts, consequences, or act-consequence links, she revises her beliefs over an expanded state space in a way that preserves the relative...

This paper examines patent protection in an endogenous-growth model. Our aim is twofold. First, we show how the patent policies discussed by the recent patent-design literature can influence R&D in the endogenous-growth framework, where the role of patents has been largely ignored. Second, we...