Josef Korbel School of International Studies, International Studies
State failure, Quantitative models, Clustering analysis, Civil conflict
Quantitative methods have been used to: (1) better predict civil conflict onset; and (2) understand causal mechanisms to inform policy intervention and theory. However, an exploration of individual conflict onset cases illustrates great variation in the characteristics describing the outbreak of civil war, suggesting that there is not one single set of factors that lead to intrastate war. In this article, we use descriptive statistics to explore persistent clusters in the drivers of civil war onset, finding evidence that some arrangements of structural drivers cluster robustly across multiple model specifications (such as young, poorly developed states with anocratic regimes). Additionally, we find that approximately one-fifth of onset cases cannot be neatly clustered across models, suggesting that these cases are difficult to predict and multiple methods for understanding civil conflict onset (and state failure more generally) may be necessary.
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This work is licensed under a Creative Commons Attribution 4.0 International License.
This article was originally published as:
Moyer, J., Matthews, A., Rafa, M., & Xiong, Y. (2022). Identifying Patterns in the Structural Drivers of Intrastate Conflict. British Journal of Political Science, 1-8. doi:10.1017/S0007123422000229
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Moyer, Jonathan D.; Matthews, Austin S.; Rafa, Mickey; and Xiong, Yutang, "Identifying Patterns in the Structural Drivers of Intrastate Conflict" (2022). International Studies: Faculty Scholarship. 27.