Working Paper: NBER ID: w26508
Authors: Johannes G. Jaspersen; Marc A. Ragin; Justin R. Sydnor
Abstract: Can measured risk attitudes and associated structural models predict insurance demand? In an experiment (n = 1,730), we elicit measures of utility curvature, probability weighting, loss aversion, and preference for certainty and use them to parameterize seventeen common structural models (e.g., expected utility, cumulative prospect theory). Subjects also make twelve insurance choices over different loss probabilities and prices. The insurance choices show coherence and some correlation with various risk-attitude measures. Yet all the structural models predict insurance poorly, often less accurately than random predictions. Simpler prediction heuristics show more promise for predicting insurance choices across different conditions.
Keywords: insurance demand; risk attitudes; structural models; cumulative prospect theory; expected utility
JEL Codes: D01; D81; G22
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| utility curvature (D11) | insurance demand (G52) |
| loss aversion (G41) | insurance demand (G52) |
| probability weighting (C46) | insurance demand (G52) |
| probability weighting interacts with loss probability (D81) | insurance demand (G52) |
| risk attitudes (D81) | insurance demand (G52) |
| structural models (E10) | insurance choices (G52) |