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Improving Quantitative Studies of International Conflict: A Conjecture

Published online by Cambridge University Press:  01 March 2000

Nathaniel Beck ,
Gary King  and
Langche Zeng
Nathaniel Beck
Affiliation:
University of California, San Diego
Gary King
Affiliation:
Harvard University
Langche Zeng
Affiliation:
Harvard University and the George Washington University
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Abstract

We address a well-known but infrequently discussed problem in the quantitative study of international conflict: Despite immense data collections, prestigious journals, and sophisticated analyses, empirical findings in the literature on international conflict are often unsatisfying. Many statistical results change from article to article and specification to specification. Accurate forecasts are nonexistent. In this article we offer a conjecture about one source of this problem: The causes of conflict, theorized to be important but often found to be small or ephemeral, are indeed tiny for the vast majority of dyads, but they are large, stable, and replicable wherever the ex ante probability of conflict is large. This simple idea has an unexpectedly rich array of observable implications, all consistent with the literature. We directly test our conjecture by formulating a statistical model that includes its critical features. Our approach, a version of a “neural network” model, uncovers some interesting structural features of international conflict and, as one evaluative measure, forecasts substantially better than any previous effort. Moreover, this improvement comes at little cost, and it is easy to evaluate whether the model is a statistical improvement over the simpler models commonly used.

Type
Articles
Information
American Political Science Review , Volume 94 , Issue 1 , March 2000 , pp. 21 - 35
Copyright
Copyright © American Political Science Association 2000

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