Working Paper: CEPR ID: DP10981
Authors: Philipp Kircher; Keith Marzilli Ericson; 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: heterogeneity; identification; insurance
JEL Codes: D81; D83; G22
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Risk Aversion (D81) | Marginal Willingness to Buy Insurance (G52) |
| Risk Type (D81) | Marginal Willingness to Buy Insurance (G52) |
| Risk Aversion + Risk Type (D81) | Insurance Demand (G52) |
| Revealed Preference Approach (D11) | Separation of Risk Preferences and Risk Types (D81) |
| Plan Variation (C29) | Identification of Type Distributions (C46) |
| Insurance Choices (G52) | Informative Bounds on Risk Preferences and Risk Types (D81) |