Incorporating Framing into Prospect Theory Modeling: A Mixture-Model Approach

Mei Wang () and Paul S. Fischbeck ()

Journal of Risk and Uncertainty, 2004, vol. 29, issue 2, 197 pages

Abstract: This paper illustrates the use of a statistical technique, finite mixture models, to fit the parameters in cumulative prospect theory. For a given decision, some individuals may adopt a gain frame, while others may adopt a loss frame. By using finite mixture models, the best fitting parameters can be obtained for the two subgroups, even though the information about subjective frames was not available. Our application uses two health insurance survey datasets collected by Rand and Chinese State Natural Science Foundation, respectively. The results are compared with previous studies on framing effects and parameterizations of prospect theory.

Date: 2004
References: Add references at CitEc
Citations: View citations in EconPapers (10)

Downloads: (external link)
http://journals.kluweronline.com/issn/0895-5646/contents (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:jrisku:v:29:y:2004:i:2:p:181-197

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/11166/PS2

Access Statistics for this article

Journal of Risk and Uncertainty is currently edited by W. Kip Viscusi

More articles in Journal of Risk and Uncertainty from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().