NDLI: On Loss Aversion in Bimatrix Games

Content Provider	Springer Nature Link
Author	Driesen, Bram Perea, Andrés Peters, Hans
Copyright Year	2008
Abstract	In this article three different types of loss aversion equilibria in bimatrix games are studied. Loss aversion equilibria are Nash equilibria of games where players are loss averse and where the reference points—points below which they consider payoffs to be losses—are endogenous to the equilibrium calculation. The first type is the fixed point loss aversion equilibrium, introduced in Shalev (2000; Int. J. Game Theory 29(2):269) under the name of ‘myopic loss aversion equilibrium.’ There, the players’ reference points depend on the beliefs about their opponents’ strategies. The second type, the maximin loss aversion equilibrium, differs from the fixed point loss aversion equilibrium in that the reference points are only based on the carriers of the strategies, not on the exact probabilities. In the third type, the safety level loss aversion equilibrium, the reference points depend on the values of the own payoff matrices. Finally, a comparative statics analysis is carried out of all three equilibrium concepts in 2 × 2 bimatrix games. It is established when a player benefits from his opponent falsely believing that he is loss averse.
Starting Page	367
Ending Page	391
Page Count	25
File Format	PDF
ISSN	00405833
Journal	Theory and Decision
Volume Number	68
Issue Number	4
e-ISSN	15737187
Language	English
Publisher	Springer US
Publisher Date	2008-04-03
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	bimatrix games loss aversion reference-dependence Operations Research/Decision Theory Methodology of the Social Sciences Game Theory, Economics, Social and Behav. Sciences Game Theory/Mathematical Methods Economic Theory
Content Type	Text
Resource Type	Article
Subject	Arts and Humanities Economics, Econometrics and Finance Developmental and Educational Psychology Social Sciences Decision Sciences Applied Psychology Computer Science Applications

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