Large Bayesian VARs

Marta Banbura, Domenico Giannone and Lucrezia Reichlin

No 2008_033, Working Papers ECARES from ULB -- Universite Libre de Bruxelles

Abstract: This paper shows that Vector Autoregression with Bayesian shrinkage is an appropriate tool for large dynamic models. We build on the results by De Mol, Giannone, and Reichlin (2008) and show that, when the degree of shrinkage is set in relation to the cross-sectional dimension, the forecasting performance of small monetary VARs can be improved by adding additional macroeconomic variables and sectoral information. In addition, we show that large VARs with shrinkage produce credible impulse responses and are suitable for structural analysis.

Keywords: Bayesian VAR; Forecasting; Monetary VAR; large cross-sections (search for similar items in EconPapers)
JEL-codes: C11 C13 C33 C53 (search for similar items in EconPapers)
Pages: 37 p.
Date: 2008
New Economics Papers: this item is included in nep-cba, nep-ecm, nep-ets, nep-for and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (82)

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Related works:
Journal Article: Large Bayesian vector auto regressions (2010)
Working Paper: Large Bayesian VARs (2008)
Working Paper: Large Bayesian VARs (2008)
Working Paper: Bayesian VARs with Large Panels (2007)
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