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Regions at Risk: Predicting Conflict Zones in African Insurgencies

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  • Schutte, Sebastian

Abstract

A method for predicting conflict zones in civil wars based on point process models is presented in this paper. Instead of testing the validity of specific theoretical conjectures about the determinants of violence in a causal framework, this paper builds on classic literature and a wide body of recent studies to predict conflict zones based on a series of geographic conditions. Using an innovative cross-validation design, the study shows that the quantitative research program on the micro-foundations of violence in civil conflict has crafted generalizable insights permitting out-of-sample predictions of conflict zones. The study region is delimited to ten countries in Sub-Saharan Africa that experienced full-blown insurgencies in the post-Cold War era.

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  • Schutte, Sebastian, 2017. "Regions at Risk: Predicting Conflict Zones in African Insurgencies," Political Science Research and Methods, Cambridge University Press, vol. 5(3), pages 447-465, July.
    • Handle: RePEc:cup:pscirm:v:5:y:2017:i:03:p:447-465_00
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    Cited by:

    1. Tobias Heinrich & Yoshiharu Kobayashi, 2022. "Evaluating explanations for poverty selectivity in foreign aid," Kyklos, Wiley Blackwell, vol. 75(1), pages 30-47, February.
    2. Sebastian Schutte & Claire Kelling, 2022. "A Monte Carlo analysis of false inference in spatial conflict event studies," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-22, April.
    3. Racek, Daniel & Thurner, Paul & Kauermann, Goeran, 2024. "Integrating Spatio-temporal Diffusion into Statistical Forecasting Models of Armed Conflict via Non-parametric Smoothing," OSF Preprints q59dr, Center for Open Science.
    4. Arzu Kibris, 2021. "The geo-temporal evolution of violence in civil conflicts: A micro analysis of conflict diffusion on a new event data set," Journal of Peace Research, Peace Research Institute Oslo, vol. 58(5), pages 885-899, September.

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