To enhance the measurement of economic and financial spillovers, we bring together the spatial and global vector autoregressive (GVAR) classes of econometric models by providing a detailed methodological review where they meet in terms of structure, interpretation, and estimation. We discuss the structure of connectivity (weight) matrices used by these models and its implications for estimation. To anchor our work within the dynamic literature on spillovers, we define a general yet measurable concept of spillovers. We formalize it analytically through the indirect effects used in the spatial literature and impulse responses used in the GVAR literature. Finally, we propose a practical step‐by‐step approach for applied researchers who need to account for the existence and strength of cross‐sectional dependence in the data. This approach aims to support the selection of the appropriate modeling and estimation method and of choices that represent empirical spillovers in a clear and interpretable form.

中文翻译：

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时空上的横断面依赖和溢出：空间经济和全局变量模型的相遇

为了增强对经济和金融溢出效应的度量，我们通过提供详细的方法论综述（在结构，解释和估计方面满足），将计量经济模型的空间和全局向量自回归（GVAR）类组合在一起。我们讨论了这些模型使用的连通性（权重）矩阵的结构及其对估计的影响。为了将我们的工作纳入关于溢出的动态文献中，我们定义了一个普遍但可衡量的溢出概念。我们通过空间文献中使用的间接效应和GVAR文献中使用的冲激响应来分析形式化。最后，我们为需要考虑数据中横断面依赖性的存在和强度的应用研究人员提出了一种实用的分步方法。