Econometrica: Jan 1997, Volume 65, Issue 1

Bayesian Vector Autoregressions with Stochastic Volatility<59:BVAWSV>2.0.CO;2-#
p. 59-73

Harald Uhlig

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.

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