Finding good predictors for inflation: a Bayesian model averaging approach

Sune Karlsson () and Tor Jacobson ()

Journal of Forecasting, 2004, vol. 23, issue 7, pages 479-496

Abstract: We consider a Bayesian model averaging approach for the purpose of forecasting Swedish consumer price index inflation using a large set of potential indicators, comprising some 80 quarterly time series covering a wide spectrum of Swedish economic activity. The paper demonstrates how to efficiently and systematically evaluate (almost) all possible models that these indicators in combination can give rise to. The results, in terms of out-of-sample performance, suggest that Bayesian model averaging is a useful alternative to other forecasting procedures, in particular recognizing the flexibility by which new information can be incorporated. Copyright © 2004 John Wiley & Sons, Ltd.

Date: 2004
View citations in EconPapers

Downloads: (external link)
http://hdl.handle.net/10.1002/for.924 Link to full text; subscription required (text/html)

Related works:
Working Paper: Finding Good Predictors for Inflation: A Bayesian Model Averaging Approach (2002)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:jof:jforec:v:23:y:2004:i:7:p:479-496

Access Statistics for this article

Journal of Forecasting is edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Series data maintained by Christopher F. Baum ().