Predicting conflict in space and time

Published

Journal Article

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. © The Author(s) 2010.

Full Text

Duke Authors

Cited Authors

  • Weidmann, NB; Ward, MD

Published Date

  • January 1, 2010

Published In

Volume / Issue

  • 54 / 6

Start / End Page

  • 883 - 901

Electronic International Standard Serial Number (EISSN)

  • 1552-8766

International Standard Serial Number (ISSN)

  • 0022-0027

Digital Object Identifier (DOI)

  • 10.1177/0022002710371669

Citation Source

  • Scopus