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The Dimension of Superpower Rivalry

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  • John T. Williams
  • Michael D. McGinnis

    (Indiana University)

Abstract

The security policies of the United States and the Soviet Union can be interpreted as manifestations of a single “rivalry system.†If each state's security policies are driven by the same underlying factors, then any effort to separate the contributions of internal and external determinants of the arms race is essentially misleading. We use dynamic factor analysis to evaluate whether an unobservable dimension of rivalry explains the dynamics exhibited by the military expenditures and diplomatic hostility of these two states. A one-factor model explains much of the variance of these data series, although some evidence indicates the possible existence of a second factor. More generally, the results of this analysis question the validity of many structural equation models of dyadic interaction.

Suggested Citation

  • John T. Williams & Michael D. McGinnis, 1992. "The Dimension of Superpower Rivalry," Journal of Conflict Resolution, Peace Science Society (International), vol. 36(1), pages 86-118, March.
    • Handle: RePEc:sae:jocore:v:36:y:1992:i:1:p:86-118
    DOI: 10.1177/0022002792036001004
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    References listed on IDEAS

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    1. Ordeshook,Peter C., 1986. "Game Theory and Political Theory," Cambridge Books, Cambridge University Press, number 9780521315937.
    2. Ostrom, Charles W., 1978. "A Reactive Linkage Model of the U.S. Defense Expenditure Policymaking Process," American Political Science Review, Cambridge University Press, vol. 72(3), pages 941-957, September.
    3. Thomas J. Sargent & Christopher A. Sims, 1977. "Business cycle modeling without pretending to have too much a priori economic theory," Working Papers 55, Federal Reserve Bank of Minneapolis.
    4. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    5. T. Anderson, 1963. "The use of factor analysis in the statistical analysis of multiple time series," Psychometrika, Springer;The Psychometric Society, vol. 28(1), pages 1-25, March.
    6. McGinnis, Michael D. & Williams, John T., 1989. "Change and Stability in Superpower Rivalry," American Political Science Review, Cambridge University Press, vol. 83(4), pages 1101-1123, December.
    7. Watson, Mark W. & Engle, Robert F., 1983. "Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models," Journal of Econometrics, Elsevier, vol. 23(3), pages 385-400, December.
    8. Walter Isard & Charles H. Anderton, 1985. "Arms Race Models: A Survey and Synthesis," Conflict Management and Peace Science, Peace Science Society (International), vol. 8(2), pages 27-98, February.
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