Prediction, Proxies, and Power

Robert J. Carroll, Brenton Kenkel

Research output: Contribution to journalArticle

Abstract

Many enduring questions in international relations theory focus on power relations, so it is important that scholars have a good measure of relative power. The standard measure of relative military power, the capability ratio, is barely better than random guessing at predicting militarized dispute outcomes. We use machine learning to build a superior proxy, the Dispute Outcome Expectations (DOE) score, from the same underlying data. Our measure is an order of magnitude better than the capability ratio at predicting dispute outcomes. We replicate Reed et al. (2008) and find, contrary to the original conclusions, that the probability of conflict is always highest when the state with the least benefits has a preponderance of power. In replications of 18 other dyadic analyses that use power as a control, we find that replacing the standard measure with DOE scores usually improves both in-sample and out-of-sample goodness of fit.

Original languageEnglish (US)
Pages (from-to)577-593
Number of pages17
JournalAmerican Journal of Political Science
Volume63
Issue number3
DOIs
StatePublished - Jul 2019
Externally publishedYes

ASJC Scopus subject areas

  • Sociology and Political Science
  • Political Science and International Relations

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