Improving Quantitative Studies of International Conflict: A Conjecture

American Political Science Review, Vol. 94, No. 1, pp. 21-36, March 2000

15 Pages Posted: 17 Jan 2008

See all articles by Nathaniel Beck

Nathaniel Beck

New York University (NYU) - Wilf Family Department of Politics

Gary King

Harvard University

Langche Zeng

University of California, San Diego

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 nonexistant. 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 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.

Suggested Citation

Beck, Nathaniel and King, Gary and Zeng, Langche, Improving Quantitative Studies of International Conflict: A Conjecture. Available at SSRN: https://ssrn.com/abstract=1083736

Nathaniel Beck (Contact Author)

New York University (NYU) - Wilf Family Department of Politics ( email )

715 Broadway
New York, NY 10003
United States

Gary King

Harvard University ( email )

1737 Cambridge St.
Institute for Quantitative Social Science
Cambridge, MA 02138
United States
617-500-7570 (Phone)

HOME PAGE: http://gking.harvard.edu

Langche Zeng

University of California, San Diego ( email )

9500 Gilman Drive
Code 0521
La Jolla, CA 92093-0521
United States

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