Introducing nu-CLEAR
University of Rochester / Center for International Security and Cooperation
Abstract:
Latent nuclear capability is a concept of central importance to scholars of nuclear weapons. However, existing measures of nuclear latency are plagued by a number of issues due to the fact that nuclear latency is inherently unobservable. To overcome this, we adopt a statistical approach well-suited to the estimation of unobservable quantities and apply it to the study of nuclear latency. Specifically, we develop a model grounded in item-response theory that recovers an estimate of this unobserved capability. By estimating the model in a Bayesian framework, we are also able to assess the inherent uncertainty of our measures in a straightforward way. Throughout, we demonstrate a number of ways in which our scores improve upon the additive-indexing approach taken in existing measures of nuclear capability. In particular our estimates provide information about activities related to nuclear production in addition to information about state capability. For example, the estimates indicate, contrary to existing arguments, that the possession of enrichment sites is a relatively poor indicator of nuclear capability. We also demonstrate the utility of these scores for empirical scholars with applications. Finally, we provide user-friendly code for scholars to reestimate these scores as new data on state activity becomes available.
Discussants:
Roseanne McManus, Baruch College
Daniel Hill, University of Georgia
Matthew Fuhrmann, Texas A&M University
Andrew Coe, University of Southern California
OPSC Coordinator: Emily Ritter, University of California - Merced
Graduate Assistant:
Peter D. Carey II (University of California Merced)
