Large Bayesian VARs

Domenico Giannone, Lucrezia Reichlin and Marta Banbura

No 966, Working Paper Series from European Central Bank

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. JEL Classification: C11, C13, C33, C53

Keywords: Bayesian VAR; forecasting; large cross-sections; monetary VAR (search for similar items in EconPapers)
Date: 2008-11
Note: 93468
References: View complete reference list from CitEc
Citations: View citations in EconPapers (70)

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Related works:
Working Paper: Large Bayesian VARs (2008)
Working Paper: Large Bayesian VARs (2008)
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Persistent link: https://EconPapers.repec.org/RePEc:ecb:ecbwps:2008966

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