Common Drifting Volatility in Large Bayesian VARs

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Show simple item record CARRIERO, Andrea CLARK, Todd E. MARCELLINO, Massimiliano 2012-03-13T14:46:33Z 2012-03-13T14:46:33Z 2012
dc.identifier.issn 1725-6704
dc.description.abstract The estimation of large Vector Autoregressions with stochastic volatility using standard methods is computationally very demanding. In this paper we propose to model conditional volatilities as driven by a single common unobserved factor. This is justified by the observation that the pattern of estimated volatilities in empirical analyses is often very similar across variables. Using a combination of a standard natural conjugate prior for the VAR coefficients, and an independent prior on a common stochastic volatility factor, we derive the posterior densities for the parameters of the resulting BVAR with common stochastic volatility (BVAR-CSV). Under the chosen prior the conditional posterior of the VAR coefficients features a Kroneker structure that allows for fast estimation, even in a large system. Using US and UK data, we show that, compared to a model with constant volatilities, our proposed common volatility model significantly improves model fit and forecast accuracy. The gains are comparable to or as great as the gains achieved with a conventional stochastic volatility specification that allows independent volatility processes for each variable. But our common volatility specification greatly speeds computations. en
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries EUI ECO en
dc.relation.ispartofseries 2012/08 en
dc.rights info:eu-repo/semantics/openAccess
dc.subject Bayesian VARs en
dc.subject stochastic volatility en
dc.subject forecasting en
dc.subject prior specification en
dc.subject C11 en
dc.subject C13 en
dc.subject C33 en
dc.subject C53 en
dc.title Common Drifting Volatility in Large Bayesian VARs en
dc.type Working Paper en
dc.neeo.contributor CARRIERO|Andrea|aut|
dc.neeo.contributor CLARK|Todd E.|aut|
dc.neeo.contributor MARCELLINO|Massimiliano|aut|EUI70008
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