ORCID: https://orcid.org/0000-0002-3599-8988; Ragin, Marc A.
ORCID: https://orcid.org/0000-0003-2370-410X und Sydnor, Justin R.
ORCID: https://orcid.org/0000-0003-0532-1949
(2022):
Predicting insurance demand from risk attitudes.
In: Journal of Risk and Insurance, Vol. 89, No. 1: pp. 63-96
Abstract
Can measured risk attitudes and associated structural models predict insurance demand? In an experiment (n = 1730), 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 12 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. This is because established structural models predict opposite reactions to probability changes and more sensitivity to prices than people display. Approaches that temper the price responsiveness of structural models show more promise for predicting insurance choices across different conditions.
| Item Type: | Journal article |
|---|---|
| Faculties: | Munich School of Management > Institute for Risk Management and Insurance Munich School of Management > Professorship for Behavioral Risk Management and Insurance |
| Subjects: | 300 Social sciences > 330 Economics |
| ISSN: | 0022-4367 |
| Language: | English |
| Item ID: | 95015 |
| Date Deposited: | 10. Mar 2023 06:39 |
| Last Modified: | 03. Aug 2023 05:58 |
