具有任意溢出与延续效应的时空因果推断：伊拉克战争中的空袭与叛乱暴力
Spatiotemporal causal inference with arbitrary spillover and carryover effects: Airstrikes and insurgent violence in the Iraq War
AI总结：
本文提出通用时空因果推断框架及开源R包geocausal，支持任意溢出与延续效应，并应用于伊拉克战争重新检验空袭对叛乱暴力的因果影响。
摘要：
社会科学研究者如今经常利用高频、高粒度的“微观层面”数据来估计次国家层面干预措施的因果效应。迄今为止，大多数研究者将这些数据聚合为面板数据，通常与大规模行政单元相关联。这种方法存在两个局限。第一，数据的（过度）聚合掩盖了有价值的空间和时间信息，增加了错误推断的风险。第二，现有的面板方法要么完全忽略空间溢出和时间延续效应，要么施加过于严格的假设。我们引入了一个通用的方法学框架以及配套的开源R软件包geocausal，该框架能够在任意溢出和延续效应下进行时空因果推断。利用这一框架，我们展示了如何定义和估计感兴趣的因果量、探索异质性处理效应、进行因果中介分析以及执行数据可视化。我们将该方法应用于伊拉克战争（2003—2011年），重新审视了关于空袭对叛乱暴力影响的长期问题。
英文摘要：
Social scientists now routinely draw on high-frequency, high-granularity ''microlevel'' data to estimate the causal effects of subnational interventions. To date, most researchers aggregate these data into panels, often tied to large-scale administrative units. This approach has two limitations. First, data (over)aggregation obscures valuable spatial and temporal information, heightening the risk of mistaken inferences. Second, existing panel approaches either ignore spatial spillover and temporal carryover effects completely or impose overly restrictive assumptions. We introduce a general methodological framework and an accompanying open-source R package, geocausal, that enable spatiotemporal causal inference with arbitrary spillover and carryover effects. Using this framework, we demonstrate how to define and estimate causal quantities of interest, explore heterogeneous treatment effects, conduct causal mediation analysis, and perform data visualization. We apply our methodology to the Iraq War (2003-11), where we reexamine long-standing questions about the effects of airstrikes on insurgent violence.
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