期刊
CONFLICT MANAGEMENT AND PEACE SCIENCE
卷 34, 期 5, 页码 461-484出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/0738894215600385
关键词
Forecasting models; mass killing; political violence; pro-government militias
Forecasting models of state-led mass killing are limited in their use of structural indicators, despite a large body of research that emphasizes the importance of agency and security repertoires in conditioning political violence. I seek to overcome these limitations by developing a theoretical and statistical framework that highlights the advantages of using pro-government militias (PGMs) as a predictive indicator in forecasting models of state-led mass killing. I argue that PGMs can lower the potential costs associated with mass killing for a regime faced with an internal threat, and might hence tip the balance in its favor. In estimating a series of statistical models and their receiver-operator characteristic curves to evaluate this hypothesis globally for the years 1981-2007, focusing on 270 internal threat episodes, I find robust support for my expectations: including PGM indicators in state-led mass killing models significantly improves their predictive strength. Moreover, these results hold even when coefficient estimates produced by in-sample data are used to predict state-led mass killing in cross-validation and out-of-sample data for the years 2008-2013. This study hence provides an introductory demonstration of the potential advantages of including security repertoires, in addition to structural factors, in forecasting models.
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