Forecasting European GNP Data through Common Factor Models and Other Procedures

Antonio Garcia-Ferrer and Pilar Poncela

Journal of Forecasting, 2002, vol. 21, issue 4, 225-44

Abstract: In this paper we present an extensive study of annual GNP data for five European countries. We look for intercountry dependence and analyse how the different economies interact, using several univariate ARIMA and unobserved components models and a multivariate model for the GNP incorporating all the common information among the variables. We use a dynamic factor model to take account of the common dynamic structure of the variables. This common dynamic structure can be non-stationary (i.e. common trends) or stationary (i.e. common cycles). Comparisons of the models are made in terms of the root mean square error (RMSE) for one-step-ahead forecasts. For this particular group of European countries, the factor model outperforms the remaining ones. Copyright © 2002 by John Wiley & Sons, Ltd.

Date: 2002
References: Add references at CitEc
Citations: View citations in EconPapers (9)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
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: https://EconPapers.repec.org/RePEc:jof:jforec:v:21:y:2002:i:4:p:225-44

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().