Forecasting and Turning Point Predictions in a Bayesian Panel VAR Model
Fabio Canova () and
No 2961, CEPR Discussion Papers from C.E.P.R. Discussion Papers
We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model that accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for hierarchical and for Minnesota-type priors. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided.
Keywords: bayesian methods panel VAR markov chains monte carlo methods; forecasting; turning points (search for similar items in EconPapers)
JEL-codes: C11 C15 E32 E37 (search for similar items in EconPapers)
References: Add references at CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
CEPR Discussion Papers are free to download for our researchers, subscribers and members. If you fall into one of these categories but have trouble downloading our papers, please contact us at email@example.com
Journal Article: Forecasting and turning point predictions in a Bayesian panel VAR model (2004)
Working Paper: FORECASTING AND TURNING POINT PREDICTIONS IN A BAYESIAN PANEL VAR MODEL (2000)
Working Paper: Forecasting and turning point predictions in a Bayesian panel VAR model (1999)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:2961
Ordering information: This working paper can be ordered from
http://www.cepr.org/ ... ers/dp.php?dpno=2961
Access Statistics for this paper
More papers in CEPR Discussion Papers from C.E.P.R. Discussion Papers Centre for Economic Policy Research, 33 Great Sutton Street, London EC1V 0DX.
Bibliographic data for series maintained by ().