Team of former rivals: A multilateral theory of non-aggression pacts. (May 2016)

• Record Type: Journal Article
• Authors: Lupu, Yonatan; Poast, Paul
• Other Names: Dorussen Han guest-editor.; Gartzke Erik guest-editor.; Westerwinter Oliver guest-editor.
• Is Part Of: Journal of peace research. Volume 53:Number 3(2016:May)
• Page Start: 344
• Page End: 358
• Publication Date: 2016-05
• Subjects: alliances -- non-aggression pacts -- rivalries; Peace -- Periodicals; Conflict management -- Periodicals; International relations -- Periodicals; 327.17205
• DOI: 10.1177/0022343316630782
• Languages: English
• ISSNs: 0022-3433

Abstract

Why do states form non-aggression pacts? Non-aggression pacts are different from typical alliances because the latter tend to be focused on relationships between members of the alliance and other states, such as by deterring external threats or mediating the resolution of conflicts between an alliance member and a third-party challenger. We offer two contributions that build on existing work. First, we provide a theory that explains why leaders use non-aggression pacts as information mechanisms. Leaders of states that have recently emerged from a rivalry seek to overcome an important information asymmetry: they know the probability of future conflict among the former rivals has decreased, but other actors may fear a resumption of hostilities. Such leaders use non-aggression pacts to signal that the rivalry has truly ended and that future relations are likely to remain peaceful. Second, our analysis recognizes the often multilateral nature of the non-aggression pact formation process. We use the 'k'-adic statistical procedure to model non-aggression pact formation as a multilateral process. To operationalize recent rivalry cessation within a group, we use a network analytic density measure. Consistent with our theory, we find that groups of states with greater densities of recently ended rivalries are significantly more likely to form non-aggression pacts. These results hold across a series of model specifications.