Theory and Practice of GVAR Modeling
By A. Chudik, M. Pesaran. Social Science Research Network, 2016
148 citations recorded by the source corpus.
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.
Subfields: Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/41e21068115c50cb2537c5a89ecf58b341683475
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Georgios P. Georgiadis
- Kamiar Mohaddes
- Maizar Raissi
- Paul Cashin
- M. Pesaran
- C. Offermanns
- Michael Hachula
- P. Anaya
Citations in the corpus
- Panel Vector Autoregressive Models: A Survey (2013, unknown): “ISSN: 0731-9053/doi:10.1108/S0731-9053(2013)0000031006”
- Determinants of Global Spillovers from US Monetary Policy (2015, methodology): “By now, GVAR models have been applied to the analysis of numerous empirical questions (see Chudik and Pesaran, 2014, for a survey).”
- Fair Weather or Foul? The Macroeconomic Effects of El Niño* (2015, methodology): “…an early illustration of the solution of the GVAR model, using a VARX*(1, 1) model, see Pesaran (2004), and for an extensive survey of the latest developments in GVAR modeling, both the theoretical foundations of the approach and its numerous empirical applications, see Chudik and Pesaran (2014).”