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Empirical Support for Systemic and Dyadic Explanations of International Conflict

Published online by Cambridge University Press:  13 June 2011

David Lalman
Affiliation:
Stanford University
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Abstract

Systemic theorists emphasize the interplay of the distribution of power, the number of poles, and their tightness in predicting the occurrence of major-power war. The authors link individual-level incentives to these systemic constraints as factors that might affect the likelihood of war. They believe that their model specification is more comprehensive than any prior effort to evaluate the impact of structural attributes on the risk of major-power war. Empirical results from the individual-level prespective are encouraging when one examines European crises from 1816 to 1965, but there is no evidence that decision makers were significantly constrained by variations in the structural attributes. Neither the distribution of power nor the number or tightness of poles appears to influence the risk of war.

Type
Research Article
Copyright
Copyright © Trustees of Princeton University 1988

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References

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17 Bueno de Mesquita (fn. 16).

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19 Model 3 can not be calculated with MPWAR as the dependent variable. With only 6 years in which major power wars began (out of the 140 years for which we have complete data), the independent variables outnumber the observations. Models 1 and 2 have been estimated.

20 Siverson and Sullivan (fn. i).

21 Lalman, David, “Conflict Resolution and Peace,” American Journal of Political Science 32 (August 1988CrossRefGoogle Scholar), forthcoming.

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25 Bueno de Mesquita (fn. 23).

26 Bueno de Mesquita and Lalman (fn. 23).

27 Altfeld and Bueno de Mesquita (fn. 18). For a full description of the estimation of the probability of success, see Bueno de Mesquita and Lalman (fn. 23). aS Results from these linear transformations are reported in Bueno de Mesquita and Lal-man (fn. 23). Lalman (fn. 21) reports results from various curvilinear functions and finds that these functions do not perform in significantly different ways from linear models. These studies yield strong empirical support for our contention that such functions reliably estimate the probability of war and other forms of violence.

28 To check for possible problems with multicolinearity, we correlated P(War) with the other independent variables: Tightness, Balance, and Polarity. The respective correlations are.199,.114, and —.344.

29 Comparable analyses cannot be conducted using the data set organized by years because P(War) is a dyadic, not a systemic, attribute; it is therefore undefined for the system as a whole.