Working Paper: NBER ID: w21797
Authors: Keith Marzilli Ericson; Philipp Kircher; Johannes Spinnewijn; Amanda Starc
Abstract: 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.
Keywords: Insurance; Risk Preferences; Revealed Preference; Health Insurance
JEL Codes: D81; I13
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| high risk aversion (D81) | willingness to buy insurance (G52) |
| high risk (D81) | willingness to buy insurance (G52) |
| high risk aversion and high risk (D81) | variation in marginal willingness to buy insurance (G52) |
| variation in insurance plans offered (G52) | separate identification of high risk aversion and high risk (D81) |
| revealed preference approach (D11) | full identification in a model with binary risks (C25) |
| revealed preference approach (D11) | full identification in a model with continuous risks (G22) |
| variation in choices (D91) | rationalization by differences in risks (D81) |
| preference heterogeneity (D11) | understanding insurance choices (G52) |
| rejection of homogeneity in risks (D81) | importance of preference heterogeneity (D11) |