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Conflict Prevention by Bayesian Persuasion

Authors: Raphaela Hennigs;

Conflict Prevention by Bayesian Persuasion

Abstract

AbstractDrawing upon the Bayesian persuasion literature, I show that a mediator can provide conflicting parties strategically with information to decrease the ex‐ante war probability. In a conflict between two parties with private information about military strength, the mediator generates information about each conflicting party's strength and commits to sharing the obtained information with the respective opponent. The conflicting parties can be convinced not to fight each other. The conflicting parties benefit from mediation, as the ex‐ante war probability is reduced. The benefit is taken up by weak conflicting parties. This benefit is larger when war is costlier and when the war probability absent mediation is higher.

Keywords

ddc:330

  • BIP!
    Impact byBIP!
    citations
    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).
    6
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
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!
6
Top 10%
Average
Average
hybrid