Bayesian Vector Autoregressions with Stochastic Volatility

H.F.H.V.S. Uhlig

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This paper proposes a Bayesian approach to a vector autoregression with stochastic volatility, where the multiplicative evolution of the precision matrix is driven by a multivariate beta variate.Exact updating formulas are given to the nonlinear filtering of the precision matrix.Estimation of the autoregressive parameters requires numerical methods: an importance-sampling based approach is explained here.
Original languageEnglish
Place of PublicationTilburg
Number of pages20
Publication statusPublished - 1996

Publication series

NameCentER Discussion Paper


  • Vector Autoregressions

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