Large Bayesian VARs

44 Pages Posted: 21 Nov 2008

See all articles by Marta Banbura

Marta Banbura

European Central Bank

Domenico Giannone

International Monetary Fund (IMF); Centre for Economic Policy Research (CEPR)

Lucrezia Reichlin

London Business School; Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES); Centre for Economic Policy Research (CEPR); European Central Bank (ECB)

Date Written: November 14, 2008

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

JEL Classification: C11, C13, C33, C53

Suggested Citation

Banbura, Marta and Giannone, Domenico and Reichlin, Lucrezia, Large Bayesian VARs (November 14, 2008). ECB Working Paper No. 966, Available at SSRN: https://ssrn.com/abstract=1292332 or http://dx.doi.org/10.2139/ssrn.1292332

Marta Banbura (Contact Author)

European Central Bank ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany

Domenico Giannone

International Monetary Fund (IMF) ( email )

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Washington, DC 20431
United States

Centre for Economic Policy Research (CEPR)

London
United Kingdom

Lucrezia Reichlin

London Business School ( email )

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United Kingdom

Université Libre de Bruxelles (ULB) - European Center for Advanced Research in Economics and Statistics (ECARES) ( email )

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Centre for Economic Policy Research (CEPR)

London
United Kingdom

European Central Bank (ECB) ( email )

Sonnemannstrasse 22
Frankfurt am Main, 60314
Germany

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