Abstract
Nonproliferation scholarship has been stymied by poor data. The recently developed Strategic Export Violation (SEV) dataset provides sufficient observations of illicit transfers of dual-use goods. Using the SEV data, a Count Exponential Random Graph Model (Count ERGM) identifies which covariates impact a state’s likelihood to appear within the observed dual-use proliferation network. The model results indicate that increased globalized economic integration increases a state’s likelihood of appearing in the observed proliferation network. This paper serves as the first use of a Count ERGM model for nonproliferation studies, demonstrating the potential benefits of the SEV data and the adoption of more network analytical tools in the supply-side nonproliferation literature. Broader implications include potential utility in other areas with “hidden populations” such as human trafficking.
