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Bayesian Vector Autoregressions with Stochastic Volatility

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  • Uhlig, H.F.H.V.S.

    (Tilburg University, Center For Economic Research)

Abstract

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.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Uhlig, H.F.H.V.S., 1996. "Bayesian Vector Autoregressions with Stochastic Volatility," Discussion Paper 1996-09, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:4fd55395-6830-46a2-9d18-efb61c0ed3f3
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    References listed on IDEAS

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    1. Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
    2. Jacquier, Eric & Polson, Nicholas G & Rossi, Peter E, 2002. "Bayesian Analysis of Stochastic Volatility Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 69-87, January.
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    Keywords

    Vector Autoregressions;

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