Inferring Risk Perceptions and Preferences using Choice from Insurance Menus: Theory and Evidence
Demand for insurance can be driven by high risk aversion or high risk. We show how to separately identify risk preferences and risk types using only choices from menus of insurance plans. Our revealed preference approach does not rely on rational expectations, nor does it require access to claims data. We show what can be learned non-parametrically from variation in insurance plans, offered separately to random cross-sections or offered as part of the same menu to one cross-section. We prove that our approach allows for full identification in the textbook model with binary risks and extend our results to continuous risks. We illustrate our approach using the Massachusetts Health Insurance Exchange, where choices provide informative bounds on the type distributions, especially for risks, but do not allow us to reject homogeneity in preferences.
We would like to thank Richard Blundell, Ian Crawford, Mark Dean, Geert Dhaene, Liran Einav, Phil Haile, Arthur Lewbell, Bernard Salanie and Frans Spinnewyn for helpful comments and discussions. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
I do not have relevant financial relationships. I do receive research funding from European Research Council Starting Grant #284119, and from the UK Economic Research Council Grants ES/L009633/1 and ES/L012499/1. None of these are related to the submitted research.
Keith Marzilli Ericson & Philipp Kircher & Johannes Spinnewijn & Amanda Starc, 2021. "Inferring Risk Perceptions and Preferences Using Choice from Insurance Menus: Theory and Evidence," The Economic Journal, vol 131(634), pages 713-744.