Estimating large-scale factor models for economic activity in Germany: Do they outperform simpler models?

Christian Dreger and Christian Schumacher

No 199, HWWA Discussion Papers from Hamburg Institute of International Economics (HWWA)

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 (search for similar items in EconPapers)
JEL-codes: C43 C51 E32 (search for similar items in EconPapers)
Date: 2002
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Citations: View citations in EconPapers (20)

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Related works:
Working Paper: Estimating Large-Scale Factor Models for Economic Activity in Germany: Do They Outperform Simpler Models? (2002)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:hwwadp:26321

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