Statistical Analysis of International Interdependencies
The origin of the statistical analysis of international relations can be traced back to 1920s with the work of Quincy Wright, who founded the University of Chicago’s Committee on International Relations. He led an interdisciplinary study of war that provided a first compendium of what was then known about the causes of war. Wright's studies and those that came after them were based on the assumption that systematic data were required to advance our knowledge about the causes of violent conflicts, and that an analysis of the dynamics of strategic decision making were essential; in short, systematic data coupled with a theoretical framework that focused on the decision-making calculus. However, debates soon raged over whether this scientific approach was better than the classical approach, which was based on philosophy, history, and law, and did not conform to strict standards of verification and proof. Since then, the literature has evolved into studies with a strong theoretical motivation, often expressed via game theoretical analytics, examined empirically with statistical frameworks that are specifically sculpted to probe those strategic dependencies. As such, existing models have resolved the levels of analysis problem that appeared daunting to earlier generations by actually focusing on the modeling of aspects of world politics that enjoin many different levels simultaneously.