Equilibrium analysis in majority-based coalitional bargaining games
Guangjing Yang and
Hao Sun
Journal of Mathematical Economics, 2024, vol. 114, issue C
Abstract:
This paper introduces majority rule into coalitional bargaining games, adapting traditional models that rely on unanimous consent to more accurately mirror decision-making processes in real-world scenarios. We introduce a majority-based coalitional bargaining game (MBCBG), wherein coalitions pass proposals via majority votes. Our analysis of the stationary subgame perfect equilibrium (SSPE) not only establishes the necessary and sufficient conditions for SSPE strategy profiles but also confirms the existence of no-delay SSPEs in MBCBGs. We further delve into symmetric MBCBGs, delineating conditions that ensure equitable outcomes for homogeneous players. Furthermore, we provide a necessary and sufficient condition for the formation of the grand coalition under SSPEs. Additionally, we briefly explore how asymmetries in coalition values, proposal probabilities, and voting weights may influence both the dynamics of coalition formation and the expected equilibrium payoffs.
Keywords: Game theory; Coalitional bargaining; Majority rule; Stationary subgame perfect equilibrium (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304406824001034
Full text for ScienceDirect subscribers only
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:eee:mateco:v:114:y:2024:i:c:s0304406824001034
DOI: 10.1016/j.jmateco.2024.103043
Access Statistics for this article
Journal of Mathematical Economics is currently edited by Atsushi (A.) Kajii
More articles in Journal of Mathematical Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().