Models Versus Rankings: Forecasting Political Violence

Artur N. Usanov, T. Sweijs
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引用次数: 3

Abstract

We compare the predictive performance in forecasting the onset of large scale political violence worldwide of five statistical models and three commonly used fragility/instability indices using PITF and UCDP data for the period 2000-2015. We find that the models typically outperform the rankings and that a ‘consensus’ model performs better than the individual models. We highlight problems with measurement of the dependent conflict variable, reflect on problems associated with forecasting political violence, and we outline ways forward for future research.
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模型与排名:预测政治暴力
我们使用2000-2015年期间PITF和UCDP数据,比较了五种统计模型和三种常用的脆弱性/不稳定性指数在预测全球大规模政治暴力发生方面的预测性能。我们发现,这些模型的表现通常优于排名,而“共识”模型的表现优于单个模型。我们强调了依赖冲突变量的测量问题,反映了与预测政治暴力相关的问题,并概述了未来研究的前进方向。
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