The Global Vector Autoregressive (GVAR) approach has proven to be a very useful approach to analyse interactions in the global macroeconomy and other data networks where both the cross‐section and the time dimensions are large. This paper surveys the latest developments in the GVAR modelling, examining both the theoretical foundations of the approach and its numerous empirical applications. We provide a synthesis of existing literature and highlight areas for future research.
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Chudík et al. (2014) studied this question.
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