We propose a network-based theory of alliance formation. Our theory implies that, in addition to key state and dyad attributes already established in the literature, the evolution of the alliance network from any given point in time is largely determined by its structure. Specifically, we argue that closed triangles in the alliance network-where i is allied with j is allied with k is allied with i - produce synergy effects in which state-level utility is greater than the sum of its dyadic parts. This idea can be generalized to n-state closure, and, when considered along with factors that make dyadic alliance formation more attractive, such as military prowess and political compatibility, suggests that the network will evolve toward a state of several densely connected clusters of states with star-like groupings of states as an intermediary stage. To evaluate our theory, we use the temporal exponential random graph model and find that the roles of our network effects are robustly supported by the data, whereas the effects of non-network parameters vary substantially between periods of recent history. Our results indicate that network structure plays a greater role in the formation of alliance ties than has been previously understood in the literature.
All Science Journal Classification (ASJC) codes
- Political Science and International Relations