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
19 pages, October 1, 2004
Full text files
WP_171.pdf PostScript file
Questions (including download problems) about the papers in this series should be directed to Lena Löfgren ()
Report other problems with accessing this service to Sune Karlsson ().
This page generated on 2024-02-05 17:13:28.