Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/82464 
Erscheinungsjahr: 
2004
Schriftenreihe/Nr.: 
Sveriges Riksbank Working Paper Series No. 171
Verlag: 
Sveriges Riksbank, Stockholm
Zusammenfassung: 
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.
Schlagwörter: 
Causality
Fractional Bayes
graphical models
lag length selection
vector autoregression
JEL: 
C11
C22
C52
Dokumentart: 
Working Paper
Erscheint in der Sammlung:

Datei(en):
Datei
Größe
298.07 kB





Publikationen in EconStor sind urheberrechtlich geschützt.