Scandinavian Working Papers in Economics

Working Paper Series,
Sveriges Riksbank (Central Bank of Sweden)

No 171: A Bayesian Approach to Modelling Graphical Vector Autoregressions

Jukka Corander and Mattias Villani ()
Additional contact information
Jukka Corander: Department of Mathematics and statistics, Postal: P.O. Box 68, FIN-00014, University of Helsinki, Finland
Mattias Villani: Research Department, Central Bank of Sweden, Postal: Sveriges Riksbank, SE-103 37 Stockholm, Sweden

Abstract: We introduce a Bayesian approach to model assessment in the class of graphical vector autoregressive (VAR) processes. Due to the very large number of model structures that may be considered, simulation based inference, such as Markov chain Monte Carlo, is not feasible. Therefore, we derive an approximate joint posterior distribution of the number of lags in the autoregression and the causality structure represented by graphs using a fractional Bayes approach. Some properties of the approximation are derived and our approach is illustrated on a four-dimensional macroeconomic system and five-dimensional air pollution data.

Keywords: Causality; Fractional Bayes; graphical models; lag length selection; vector autoregression

JEL-codes: C11; C22; C52

19 pages, October 1, 2004

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Published as
Jukka Corander and Mattias Villani, (2005), 'A Bayesian Approach to Modelling Graphical Vector Autoregressions', Journal of Time Series Analysis, vol 27, no 1, pages 141-156

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