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ID: 183696

Does Insurgent Selective Punishment Deter Collaboration? evidence from the Drone War in Pakistan / Bauer, Vincent ; Reese, Michael ; Ruby, Keven

Ruby, Keven	Journal Article
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Summary/Abstract

Scholars of civil wars have long argued that non-state actors can use selective punishment to reduce collaboration with state adversaries. However, there is little systematic evidence confirming this claim, nor investigation into the mechanisms at play. In this paper, we provide such evidence from the drone war in Pakistan. Militants in Pakistan’s tribal areas engaged in a brutal counterespionage campaign with the aim of reducing collaboration with the United States. Our analysis combines a novel dataset of collaborator killings with data on drone strike outcomes. We find that strikes killed half as many militant leaders and fighters following collaborator killings and that this suppressive effect likely works by deterring spying in the future. Beyond providing an empirical confirmation of the selective punishment hypothesis, our paper suggests an unacknowledged vulnerability of the drone program to reprisals against local allies and collaborators that limits its effectiveness as a long-term tool of counterterrorism

Key Words

Civil Wars ; Counterterrorism ; Asymmetric Conflict ; Foreign Policy

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ID: 154744

Solving the problem of unattributed political violence / Pape, Robert; Ruby, Keven; Bauer, Vincent

Pape, Robert	Journal Article
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Summary/Abstract

High rates of missing perpetrator information in political violence data pose a serious challenge for studies into militant group behavior and the microdynamics of conflict more generally. In this article we introduce multiple imputation (MI) as the best available method for minimizing the impact of missing perpetrator information on quantitative analyses of political violence, a method that can easily be incorporated into most quantitative research designs. MI will produce unbiased attributions when the reasons for missingness are known and can be controlled for using observed variables, rendering responsibility for unclaimed attacks, “missing at random” (MAR) – which we show is a reasonable assumption in the case of political violence based on current theory of militant group claiming. We lay out the logics and steps of MI, identify variables and data sources, and demonstrate that MI produced better results in the case of the Pakistani Taliban’s response to drone strikes.

Key Words

Terrorism ; Conflict ; Civil Wars ; Events Data ; Multiple Imputation

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