Principal Investigator(s): Beck, Nathaniel L., University of California-San Diego; King, Gary, Harvard University; Zeng, Langche, George Washington University and Harvard University
In this article, the authors 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. The authors 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 in prior research, 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. The authors provide a direct test of their conjecture by formulating a statistical model that includes its critical features. The approach, a version of a "neural network" model, uncovers some structural features of international conflict and also functions as an evaluative measure by forecasting. Moreover, it is easy to evaluate whether the neural network model is a statistical improvement over the simpler models commonly used.
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Beck, Nathaniel L., Gary King, and Langche Zeng. Improving Quantitative Studies of International Conflict: A Conjecture. ICPSR01218-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2000-05-02. doi:10.3886/ICPSR01218.v1
Persistent URL: http://doi.org/10.3886/ICPSR01218.v1
This survey was funded by:
- National Science Foundation
- United States Department of Health and Human Services. Centers for Disease Control and Prevention
- World Health Organization
- United States Department of Health and Human Services. National Institutes of Health. National Institute on Aging
Scope of Study
Geographic Coverage: Global
Data Collection Notes:
(1) The file submitted is beckkingzeng.zip, which unzips to data and program files that include a readme file. (2) These data are part of ICPSR's Publication-Related Archive and are distributed exactly as they arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigators if further information is desired.
Original ICPSR Release: 2000-05-02
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