Forecasting European GNP data through common factor models and other procedures

• Published in: Journal of forecasting Vol. 21; no. 4; pp. 225 - 244
• Main Authors: García-Ferrer, Antonio, Poncela, Pilar
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.07.2002; Wiley Periodicals Inc
• Subjects: Business cycles; common factors; Data analysis; Datasets; Economic forecasting; Economic models; Economics; Europe; Forecasting; Forecasts; GNP; GNP data; Gross National Product; Mean square errors; multiple time series; Recessions; Studies; Time series; Trends; unobserved components models; Europe
• ISSN: 0277-6693; 1099-131X
• DOI: 10.1002/for.829

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 John Wiley & Sons, Ltd.