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Introducing ν-CLEAR: a latent variable approach to measuring nuclear proficiency

Author

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  • Bradley C. Smith

    (Department of Political Science, Vanderbilt University, USA)

  • William Spaniel

    (Department of Political Science, University of Pittsburgh, USA)

Abstract

The causes and consequences of nuclear proficiency are central to important questions in international relations. At present, researchers tend to use observable characteristics as a proxy. However, aggregation is a problem: existing measures implicitly assume that each indicator is equally informative and that measurement error is not a concern. We overcome these issues by applying a statistical measurement model to directly estimate nuclear proficiency from observed indicators. The resulting estimates form a new dataset on nuclear proficiency which we call ν -CLEAR. We demonstrate that these estimates are consistent with known patterns of nuclear proficiency while also uncovering more nuance than existing measures. Additionally, we demonstrate how scholars can use these estimates to account for measurement error by revisiting existing results with our measure.

Suggested Citation

  • Bradley C. Smith & William Spaniel, 2020. "Introducing ν-CLEAR: a latent variable approach to measuring nuclear proficiency," Conflict Management and Peace Science, Peace Science Society (International), vol. 37(2), pages 232-256, March.
    • Handle: RePEc:sae:compsc:v:37:y:2020:i:2:p:232-256
    DOI: 10.1177/0738894217741619
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    References listed on IDEAS

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    Cited by:

    1. William Spaniel, 2022. "Scientific intelligence, nuclear assistance, and bargaining," Conflict Management and Peace Science, Peace Science Society (International), vol. 39(4), pages 447-469, July.

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