Spillovers in space and time: where spatial econometrics and Global VAR models meet
Marco Gross and
No 2134, Working Paper Series from European Central Bank
We bring together the spatial and global vector autoregressive (GVAR) classes of econometric models by providing a detailed methodological review of where they meet in terms of structure, interpretation, and estimation methods. We discuss the structure of cross-section connectivity (weight) matrices used by these models and its implications for estimation. Primarily motivated by the continuously expanding literature on spillovers, we define a broad and 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. JEL Classification: C33, C38, C51
Keywords: GVARs; spatial models; spillovers; weak and strong cross-sectional dependence (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-geo and nep-ure
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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:20182134
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