CROSS‐SECTIONAL DEPENDENCE AND SPILLOVERS IN SPACE AND TIME: WHERE SPATIAL ECONOMETRICS AND GLOBAL VAR MODELS MEET

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 str...

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Bibliographic Details
Published in:Journal of economic surveys 2021-02, Vol.35 (1), p.192-226
Main Authors: Elhorst, J. Paul, Gross, Marco, Tereanu, Eugen
Format: Article
Language:English
Subjects:
Econometrics
GVARs
Indirect effects
Matrices
Measurement
Spatial models
Spillover effect
Spillovers
Weak and strong cross‐sectional dependence
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Summary: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.
ISSN:0950-0804
1467-6419
DOI:10.1111/joes.12391