This project examines the expansion of war; specifically, the spread of ongoing interstate wars to include states (i.e., third parties) beyond the original participants. The project builds around a theory of war expansion that is developed using computer simulations and then tested empirically using statistical analysis of actual wars. The research begins by using agent-based modeling -- a method that consists of computer simulations performed in an artificial international system -- to examine how multiple interacting "agents" (i.e., states) behave under different war scenarios. The outcomes of these simulations reveal emergent behavioral patterns of war expansion in the virtual environment: the precise conditions under which third parties will and will not decide to join an ongoing war, and the effects that third party participation will have on the dynamics of the war itself. These emergent patterns, in turn, serve as theoretical predictions of the real-life behavioral patterns that should emerge in the world under parallel conditions. After developing theoretical predictions based on simulations of the agent-based model, these predictions are tested empirically through statistical analysis of a new data set of military interventions in interstate wars between 1816 and 1997.
The main contributions of the project are the theoretical and methodological advances that it affords. In addition to advancing understanding of why third parties join ongoing interstate wars, the theory of joining behavior that results can be generalized and applied to research questions throughout the social and behavioral sciences. This project also makes a methodological contribution by demonstrating that agent-based modeling combined with statistical analysis can provide better leverage on a research question than either method used in isolation. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.
