In Short:

We find that the data can be explained by expected utility theory with low levels of risk aversion and heterogeneous non-singleton choice sets, and that more than three in four households require limited choice sets to explain their deductible choices.

Abstract

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 choice sets and preferences. We first characterize the sharp identification region of the model’s parameters by a finite set of conditional moment inequalities. We then apply our theoretical findings to learn about households’ risk preferences and choice sets from data on their deductible choices in auto collision insurance. We find that the data can be explained by expected utility theory with low levels of risk aversion and heterogeneous non-singleton choice sets, and that more than three in four households require limited choice sets to explain their deductible choices. We also provide simulation evidence on the computational tractability of our method in applications with larger feasible sets or higher-dimensional unobserved heterogeneity.

About the author

Levon Barseghyan

professor, school of government and policy

Levon Barseghyan’s work, both theoretical and empirical, is aimed at uncovering mechanisms that shape economic behavior and how such behavior is affected by market structure, economic policies and political institutions.

Francesca Molinari

professor, school of government and policy

Francesca Molinari is a leading authority in econometric theory and applied econometrics.