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Theory and practice of GVAR modeling

  • Chudik, Alexander

    (Federal Reserve Bank of Dallas)

  • Pesaran, M. Hashem

    ()

    (University of Southern California and Trinity College)

The Global Vector Autoregressive (GVAR) approach has proven to be a very useful approach to analyze 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 modeling, 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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Paper provided by Federal Reserve Bank of Dallas in its series Globalization and Monetary Policy Institute Working Paper with number 180.

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Length: 55 pages
Date of creation: 01 May 2014
Date of revision:
Handle: RePEc:fip:feddgw:180
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