Publication

In this paper, the authors develop, test and defend their neural network model of interstate conflicts. Their goal is to add to non-linear and interactive models of militarized disputes by enhancing the predictive accuracy of statistical models. By incorporating variables such as economic interdependence, democracy, and international organizations, the authors conclude that their model can correctly predict 82 percent of militarized disputes and 72 percent of non-disputes from the Cold War era.