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An Assessment of the Merits of Selective Nuclear Proliferation
Abstract
We assume that in a conflict between a nation with a nuclear capability and one without, the conflict may become nuclear, while, in a conflict between two nuclear powers, the conflict is unlikely to become nuclear by reason of fear of retaliation. Then, as the number of nations with nuclear weapons increases, the chance of bilateral conflict becoming nuclear initially increases and then decreases to zero when all nations are nuclearly armed. Empirical evidence suggests that nuclear deterrence does in fact work in the way the model assumes. We set forth an expected utility model for initiating conflict when nuclear weapons are held by both sides, by one side, and by neither side. While there are dangers in proliferation, these dangers may not be as great as dangers of asymmetry in nuclear power.
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Citations
Cited by
Nuclear Weapons and Coercive Diplomacy
Sechser, T. S., & Fuhrmann, M. (2016) · doi:10.1017/9781316227305 · Cited by 155
What Does It Take to Deter? Regional Power Nuclear Postures and International Conflict
Narang, V. (2013) · Journal of Conflict Resolution · doi:10.1177/0022002712448909 · Cited by 58
Metadata
- Authors
- de Mesquita, B. B., & Riker, W. H.
- Venue
- Journal of Conflict Resolution
- Publisher
- SAGE Publications
- Published
- 1982-06
- Volume
- 26
- Issue
- 2
- Pages
- 283-306
- ISSN
- 0022-0027 (ISSN-L)
- 1552-8766
- OpenAlex
- W2151969361
- Cited by
- 161
- References
- 0
- FWCI
- 18.71
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: An Assessment of the Merits of Selective Nuclear Proliferation. https://app.cochat.ai/papers/10.1177/0022002782026002005
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- de Mesquita, B. B., & Riker, W. H. (1982). An Assessment of the Merits of Selective Nuclear Proliferation. Journal of Conflict Resolution. https://doi.org/10.1177/0022002782026002005
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.