2020
DOI: 10.1111/jpet.12475
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A noncooperative model of contest network formation

Abstract: In this paper we study a situation in which agents embedded in a network simultaneously play interrelated bilateral contest games with their neighbors. Spillovers between contests induce complex local and global network effects. We first characterize the equilibrium of the game on a given network. Then we study a network formation model, introducing a novel but intuitive link formation protocol. As links represent negative relationships, link formation is unilateral while link destruction is bilateral. The uni… Show more

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Cited by 8 publications
(5 citation statements)
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“…The authors investigate optimal seeding rules (according to various criteria), which sort the players into two groups for elimination in the first stage, and find that seedings that delay encounter of strong players are optimal for various criteria. 7 Finally, our paper is also related to the literature of (static) contests with team players or alliances, such as Nitzan (1991), Skaperdas (1998), Esteban and Ray (2001), Münster (2007), 6 There is also an extensive literature on Tullock contests with asymmetric valuations or endogenous network structure (see, e.g., Feng & Lu, 2017;Huremovic, 2021;Nti, 1999;and references therein). Asymmetry in our setting however is different and is due to collusion, which leads to different payoff functions and strategy sets among the players.…”
Section: Literaturementioning
confidence: 99%
“…The authors investigate optimal seeding rules (according to various criteria), which sort the players into two groups for elimination in the first stage, and find that seedings that delay encounter of strong players are optimal for various criteria. 7 Finally, our paper is also related to the literature of (static) contests with team players or alliances, such as Nitzan (1991), Skaperdas (1998), Esteban and Ray (2001), Münster (2007), 6 There is also an extensive literature on Tullock contests with asymmetric valuations or endogenous network structure (see, e.g., Feng & Lu, 2017;Huremovic, 2021;Nti, 1999;and references therein). Asymmetry in our setting however is different and is due to collusion, which leads to different payoff functions and strategy sets among the players.…”
Section: Literaturementioning
confidence: 99%
“…only group 1 exist in the contest: if β ∈ (1, 2], according to Proposition 4, group 2 retires from the contest and the effort of group 1 is still decreasing in s. Therefore, we get the largest aggregate effort X(0) = v1v2(v1+ωv2) (v1+v2) 2 at s * = 0. If β > 2, after the weak group retires from the contest, the effort of group 1 is still increasing in s, by (26), and we can maximize aggregate effort X( v1…”
Section: Endogenous Group Informationmentioning
confidence: 99%
“…, after the weak group retires from the contest, by (26), we can get the highest aggregate effort X( v1 4 ) = v1 4 at s = v1 4 . It is easy to verify that X(s * 1 ) > X( v1 4 ) for any…”
Section: Endogenous Group Informationmentioning
confidence: 99%
See 1 more Smart Citation
“…The network characterizes players' social relations in society, so the network structure affects the level of effort of participants in different contests. 4 Franke and Özt ürk (2015) and Huremović (2021) consider conflict networks where multiple participants are involved in multiple bilateral conflicts. Xu, Zenou, and Zhou (2022) use variational inequality techniques to address equilibrium uniqueness and propagation of shocks in conflict networks.…”
Section: Introductionmentioning
confidence: 99%