Working Papers
Explaining Civil War Severity: A formal model and empirical analysis
With Christopher K. Butler and Scott Gates
Abstract: What explains variation in civil-war severity? We argue that governments and rebel groups make strategic decisions regarding how much effort to devote to fighting based on their relative and absolute capabilities and the number of groups fighting. We develop a formal model that examines how the number of rebel groups and the resources available to governments and rebels influence conflict severity. The effect of the three parameters is highly interactive. In general, fighting is more severe in conflicts with multiple rebels groups where both sides have more resources compared to other conflicts. The model generates specific predictions about the severity of civil war that we calculate empirically by inserting the number of rebel groups and each side's troop levels directly into the equilibrium equations. We compare these theoretical predictions to actual battle-related deaths in statistical tests and find that the equilibrium-derived variable is a robust predictor of civil war severity.
With Christopher K. Butler and Scott Gates
Abstract: What explains variation in civil-war severity? We argue that governments and rebel groups make strategic decisions regarding how much effort to devote to fighting based on their relative and absolute capabilities and the number of groups fighting. We develop a formal model that examines how the number of rebel groups and the resources available to governments and rebels influence conflict severity. The effect of the three parameters is highly interactive. In general, fighting is more severe in conflicts with multiple rebels groups where both sides have more resources compared to other conflicts. The model generates specific predictions about the severity of civil war that we calculate empirically by inserting the number of rebel groups and each side's troop levels directly into the equilibrium equations. We compare these theoretical predictions to actual battle-related deaths in statistical tests and find that the equilibrium-derived variable is a robust predictor of civil war severity.
An Integrated Picture of Conflict
With Eric Dunford, David Backer, Karsten Donnay, and Erin McGrath
Abstract: Growth in event datasets is fostering research about patterns, dynamics, causes, and consequences of conflict. Studies typically rely on a single dataset. Instead, we advocate integrating multiple datasets to improve measurement and analysis. In this article, we demonstrate the benefits of integrating multiple datasets to improve measurement and analysis. We generate an integrated dataset covering Africa from 1997-2016 of four leading datasets (ACLED, UCDP-GED, SCAD, and GTD) with overlapping coverage of diverse types of conflict events. Using the integrated dataset, we document events that should be included, yet are missing in individual datasets. We also show that results of studies about the relationship between climate and conflict are sensitive given the conceptualization of conflict reflected by particular datasets. These illustrations highlight the potential for integration to advance conflict research by yielding a more complete and accurate picture of activity, which has repercussions for both descriptive and theoretical findings. Integration is likely to be increasingly worthwhile as event datasets proliferate, expand in coverage, and exhibit wider applications.
With Eric Dunford, David Backer, Karsten Donnay, and Erin McGrath
Abstract: Growth in event datasets is fostering research about patterns, dynamics, causes, and consequences of conflict. Studies typically rely on a single dataset. Instead, we advocate integrating multiple datasets to improve measurement and analysis. In this article, we demonstrate the benefits of integrating multiple datasets to improve measurement and analysis. We generate an integrated dataset covering Africa from 1997-2016 of four leading datasets (ACLED, UCDP-GED, SCAD, and GTD) with overlapping coverage of diverse types of conflict events. Using the integrated dataset, we document events that should be included, yet are missing in individual datasets. We also show that results of studies about the relationship between climate and conflict are sensitive given the conceptualization of conflict reflected by particular datasets. These illustrations highlight the potential for integration to advance conflict research by yielding a more complete and accurate picture of activity, which has repercussions for both descriptive and theoretical findings. Integration is likely to be increasingly worthwhile as event datasets proliferate, expand in coverage, and exhibit wider applications.