Max-Min Group Contests with Incomplete Information à la Global Games
Davide Bosco,
Mario Gilli and
Andrea Sorrentino
No 545, Working Papers from University of Milano-Bicocca, Department of Economics
Abstract:
The main novelty of this paper is the introduction of incomplete information à la global games into max-min group contests with binary actions. Depending on whether the complete information assumption is relaxed on the value of the prize or on the cost of providing effort, we obtain different results in terms of equilibrium selection: in the first case, there exist both an equilibrium in monotone switching strategies and an equilibrium in which no player in either group exerts effort, whereas in the second one there exists a unique equilibrium in monotone switching strategies. Then, we discuss the presence of the group-size paradox for both classes of games. The results are thus extended to the case of M groups, and the properties of Bayes-Nash equilibria for these classes of games are investigated. Finally, we show a vanishing-noise limit and a cost-case noise-independent selection result.
Keywords: Group contests; incomplete information; global games. (search for similar items in EconPapers)
JEL-codes: C72 D71 D74 (search for similar items in EconPapers)
Pages: 85
Date: 2024-10, Revised 2026-09
New Economics Papers: this item is included in nep-gth and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://repec.dems.unimib.it/repec/pdf/mibwpaper545.pdf (application/pdf)
Related works:
Working Paper: Max-Max Group Contests with Incomplete Information à la Global Games (2026) 
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:mib:wpaper:545
Access Statistics for this paper
More papers in Working Papers from University of Milano-Bicocca, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Matteo Pelagatti ().