Predicting Conflict in Space and Time

Nils B. Weidmann and Michael D. Ward
Additional contact information
Nils B. Weidmann: Woodrow Wilson School of Public and International Affairs, Princeton University, Princeton, NJ, USA, nils.weidmann@gmail.com
Michael D. Ward: Department of Political Science, Duke University, Durham, NC, USA

Journal of Conflict Resolution, 2010, vol. 54, issue 6, 883-901

Abstract: The prediction of conflict constitutes a challenge to social scientists. This article explores whether the incorporation of geography can help us make our forecasts of political violence more accurate. The authors describe a spatially and temporally autoregressive discrete regression model, following the framework of Geyer and Thompson. This model is applied to geo-located data on attributes and conflict events in Bosnia over the period from March 1992 to October 1995. Results show that there is a strong spatial as well as temporal dimension to the outbreak of violence in Bosnia. The authors then explore the use of this model for predicting future conflict. Using a simulation approach, the predictive accuracy of the spatial—temporal model is compared to a standard regression model that only includes time lags. The results show that even in a difficult out-of-sample prediction task, the incorporation of space improves our forecasts of future conflict.

Keywords: civil war; Bosnia; conflict prediction; spatial statistics (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:sae:jocore:v:54:y:2010:i:6:p:883-901

DOI: 10.1177/0022002710371669

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