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Spillovers in space and time: where spatial econometrics and Global VAR models meet

J.Paul Elhorst, Marco Gross and Eugen Tereanu

No 2134, Working Paper Series from European Central Bank

Abstract: 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
Date: 2018-02
Note: 3098116
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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:20182134

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