Published at AJPS (2024). Computational model in which orders and war emerge from the interactions of agents, and structure their subsequent behavior.
Using a computational model, this project argues that intergroup conflict makes the creation of coercive centralized hierarchy more likely by increasing within-group cooperation and that institutions which were built up during conflict can be ex-post efficient even in times of peace and therefore can outlast the conflicts which provided their initial impetus.
Great powers engaged in hegemonic competition face a trilemma as they can only achieve 2 out of the 3 desirable policy objectives that are: maximizing their influence, promoting their values, ensuring peace.
This project leverages a partial observability model of conflict initiation to estimate systemic uncertainty, where values of the unobserved variables are inferred from the relationship of observed variables to outcomes.
This paper proposes to quantify common usages of "international order" in order to catalyze a more robust scientific research program on this important concept.
Uses computational modeling and network analysis to introduce a theory of hierarchy misalignment, where discrepancies between states' material and relational power drive conflict in multiple domains.
This project investigates how states renegotiate international bargains after unexpected events undermine the initial deal and finds that internal reforms are most likely when powerful and weak states alike desire change. If there is an imbalance, however, and only one group is mobilized for change, then the creation of a new institution becomes more likely as it bypasses the veto of the other group.