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Reassessing the Role of Theory and Machine Learning in Forecasting Civil Conflict

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  • Andreas Beger
  • Richard K. Morgan
  • Michael D. Ward

Abstract

We examine the research protocols in Blair and Sambanis’ recent article on forecasting civil wars, where they argue that their theory-based model can predict civil war onsets better than several atheoretical alternatives or a model with country-structural factors. We find that there are several important mistakes and that their key finding is entirely conditional on the use of parametrically smoothed ROC curves when calculating accuracy, rather than the standard empirical ROC curves that dominate the literature. Fixing these mistakes results in a reversal of their claim that theory-based models of escalation are better at predicting onsets of civil war than other kinds of models. Their model is outperformed by several of the ad hoc, putatively non-theoretical models they devise and examine. More importantly, we argue that rather than trying to contrast the roles of theory and “atheoretical†machine learning in predictive modeling, it would be more productive to focus on ways in which predictive modeling and machine learning could be used to strengthen extant predictive work. Instead, we argue that predictive modeling and machine learning are effective tools for theory testing.

Suggested Citation

  • Andreas Beger & Richard K. Morgan & Michael D. Ward, 2021. "Reassessing the Role of Theory and Machine Learning in Forecasting Civil Conflict," Journal of Conflict Resolution, Peace Science Society (International), vol. 65(7-8), pages 1405-1426, August.
  • Handle: RePEc:sae:jocore:v:65:y:2021:i:7-8:p:1405-1426
    DOI: 10.1177/0022002720982358
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    References listed on IDEAS

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    1. Fariss, Christopher J. & Jones, Zachary M., 2018. "Enhancing Validity in Observational Settings When Replication is Not Possible," Political Science Research and Methods, Cambridge University Press, vol. 6(2), pages 365-380, April.
    2. Bruce Bueno de Mesquita & Alastair Smith & Randolph M. Siverson & James D. Morrow, 2005. "The Logic of Political Survival," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262524406, April.
    3. Chiba, Daina & Metternich, Nils W. & Ward, Michael D., 2015. "Every Story Has a Beginning, Middle, and an End (But Not Always in That Order): Predicting Duration Dynamics in a Unified Framework," Political Science Research and Methods, Cambridge University Press, vol. 3(3), pages 515-541, September.
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    Cited by:

    1. Robert A. Blair & Nicholas Sambanis, 2021. "Is Theory Useful for Conflict Prediction? A Response to Beger, Morgan, and Ward," Journal of Conflict Resolution, Peace Science Society (International), vol. 65(7-8), pages 1427-1453, August.

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