An Empirical Test of Gain-Loss Separability in Prospect Theory
George Wu () and
Alex B. Markle ()
Additional contact information
George Wu: Center for Decision Research, Graduate School of Business, University of Chicago, Chicago, Illinois 60637
Alex B. Markle: Stern School of Business, New York University, New York, New York 10012
Management Science, 2008, vol. 54, issue 7, 1322-1335
Abstract:
We investigate a basic premise of prospect theory: that the valuation of gains and losses is separable. In prospect theory, gain-loss separability implies that a mixed gamble is valued by summing the valuations of the gain and loss portions of that gamble. Two experimental studies demonstrate a systematic violation of the double-matching axiom, an axiom that is necessary for gain-loss separability. We document a reversal between preferences for mixed gambles and the associated gain and loss gambles--mixed gamble A is preferred to mixed gamble B, but the gain and loss portions of B are preferred to the gain and loss portions of A. The observed choice patterns are consistent with a process in which individuals are less sensitive to probability differences when choosing among mixed gambles than when choosing among either gain or loss gambles.
Keywords: risky choice; prospect theory; mixed gambles; double matching; probability weighting function (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (30)
Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.1070.0846 (application/pdf)
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:inm:ormnsc:v:54:y:2008:i:7:p:1322-1335
Access Statistics for this article
More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().