Capturing the spatio-temporal diffusion effects of armed conflict: A nonparametric smoothing approach
提出一种非参数平滑回归方法，同时捕捉武装冲突在空间和时间上的扩散效应，并用非洲数据揭示冲突从人口密集区向低人口区扩散的规律。
Abstract Facilitated by advancements in conflict event databases, studies have moved towards predicting armed conflict and understanding its determinants subnationally. However, existing statistical models neither analyse nor capture the diffusion of armed conflict, and hence do not adequately account for its dependence across both time and space. To address this, we introduce a regression approach that simultaneously captures both spatial and temporal dimension of the diffusion of armed conflict through nonparametric smoothing, while all its effects and parameters remain fully interpretable. Using fine-grained conflict data on Africa, we observe that diffusion exhibits long-lasting and far-reaching dependencies that decay exponentially in both space and time, thus highlighting the importance of controlling for these effects. We illustrate the flexibility of our method for studying conflict diffusion by investigating the role of population in the transmission of conflict. We find that conflict typically breaks out in densely populated areas, and from there diffuses, specifically to lower population areas.