Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models?

Jahrbücherfür Nationalökonomie und Statistik (Journal of Economics and Statistics), Vol. 224, pp. 732-750, 2004

Posted: 16 Jun 2008

See all articles by Christian Schumacher

Christian Schumacher

Deutsche Bundesbank

Christian Dreger

European University Viadrina Frankfurt (Oder); IZA Institute of Labor Economics; Chinese Academy of Social Sciences (CASS)

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Abstract

This paper discusses a large-scale factor model for the German economy. Following the recent literature, a data set of 121 time series is used via principal component analysis to determine the factors, which enter a dynamic model for German GDP. The model is compared with alternative univariate and multivariate models. These models are based on regression techniques and considerably smaller data sets. Out-of-sample forecasts show that the prediction errors of the factor model are smaller than the errors of the rival models. However, these advantages are not statistically significant, as a test for equal forecast accuracy shows. Therefore, the effciency gains of using a large data set with this kind of factor models seem to be limited.

Keywords: Factor models, Principal components, forecasting accuracy

JEL Classification: E32, C51, C43

Suggested Citation

Schumacher, Christian and Dreger, Christian, Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models?. Jahrbücherfür Nationalökonomie und Statistik (Journal of Economics and Statistics), Vol. 224, pp. 732-750, 2004, Available at SSRN: https://ssrn.com/abstract=728304

Christian Schumacher (Contact Author)

Deutsche Bundesbank ( email )

Wilhelm-Epstein-Str. 14
Frankfurt/Main, 60431
Germany

Christian Dreger

European University Viadrina Frankfurt (Oder) ( email )

Frankfurt (Oder)
Germany

IZA Institute of Labor Economics

P.O. Box 7240
Bonn, D-53072
Germany

Chinese Academy of Social Sciences (CASS) ( email )

Beijing, 100732
China

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