Unlike what is commonly thought, this paper demonstrates that audience costs exist because individuals have substantive preferences over policy.
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.
A counterintuitive finding in IR is that important changes in policy are initiated by unlikely leaders. This project emphasizes that public preferences are central to explain this dynamic.
This projects examines the impact of established survey instruments on the cognitive burden of participants and proposes a new instrument design to improve survey response quality.
This project finds that individuals have an intuitive sense of the power to hurt and explores three plausible mechanisms that could account for this dynamic.
This paper introduces a new way to estimate individual preferences to investigate how participants respond to partisan cues regarding tariffs.
This project draws on psychometrics and machine learning techniques to propose a non-parametric Bayesian method to optimize complex multidimensional experimental estimation.