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.
This project introduces a new survey instrument to investigate the relation between the power to hurt (i.e. enemy casualties) and to be hurt (i.e. friendly casualties) and their combined impact on the willingness to support the use of military force.
This project draws on psychometrics and machine learning techniques to propose a non-parametric Bayesian method to optimize complex multidimensional experimental estimation.
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 researches how democratic backsliding impact the ability of credibility of leaders abroad by distinguishing between the effects of domestic polarization and of weakening democratic institutions.
Building upon recent innovations in Computational Science, this projects proposes a new framework for inference in international relations where strategic considerations are rampant.
This paper introduces a novel network measure to assess how variations in state strength and relational power affect the rate of international conflict and finds that greater differences in the military capabilities and relational power of states is associated with higher rates of conflict.
This project draws on psychometrics and machine learning techniques to propose a non-parametric Bayesian method to optimize complex multidimensional experimental estimation.
Using a survey experiment concurrently fielded in Korea, Japan, and the U.S., this project investigates what states are looking for in an ally.
This projects introduces a new method to estimate the temporal preferences of individuals regarding collective outcomes.