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Journal of Economic Behavior & Organization
Article . 2025 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
https://doi.org/10.2139/ssrn.4...
Article . 2024 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2023
License: CC BY SA
Data sources: Datacite
DBLP
Article . 2023
Data sources: DBLP
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Ultimatum Game: Regret or Fairness?

Authors: L.H. Aleksanyan; A.E. Allahverdyan; V.G. Bardakhchyan;

Ultimatum Game: Regret or Fairness?

Abstract

In the ultimatum game, the challenge is to explain why responders reject non-zero offers thereby defying classical rationality. Fairness and related notions have been the main explanations so far. We explain this rejection behavior via the following principle: if the responder regrets less about losing the offer than the proposer regrets not offering the best option, the offer is rejected. This principle qualifies as a rational punishing behavior and it replaces the experimentally falsified classical rationality (the subgame perfect Nash equilibrium) that leads to accepting any non-zero offer. The principle is implemented via the transitive regret theory for probabilistic lotteries. The expected utility implementation is a limiting case of this. We show that several experimental results normally prescribed to fairness and intent-recognition can be given an alternative explanation via rational punishment; e.g. the comparison between "fair" and "superfair", the behavior under raising the stakes etc. Hence we also propose experiments that can distinguish these two scenarios (fairness versus regret-based punishment). They assume different utilities for the proposer and responder. We focus on the mini-ultimatum version of the game and also show how it can emerge from a more general setup of the game.

13 pages, 2 figures

Keywords

FOS: Economics and business, FOS: Computer and information sciences, Physics - Physics and Society, Computer Science - Computer Science and Game Theory, Economics - Theoretical Economics, Theoretical Economics (econ.TH), FOS: Physical sciences, Physics and Society (physics.soc-ph), Computer Science and Game Theory (cs.GT)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green