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

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  • Dreger, Christian
  • Schumacher, Christian

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. -- Diese Arbeit diskutiert ein großes Faktorenmodell für die deutsche Wirtschaft. Der jüngeren Literatur folgend werden aus einem umfangreichen Datensatz von 121 Zeitrehen mit einer Hauptkomponentenanalyse gemeinsame Faktoren extrahiert, welche in ein dynamisches Modell zur Erklärung des deutschen Bruttoinlandsprodukts eingehen. Das Modell wird mit alternativen univariaten und multivariaten Modellen verglichen, die auf Regressionsansätzen und deutlich kleineren Datensätzen beruhen. Vergleiche von Pronosen außerhalb des Schätzzeitraums zeigen, dass die Prognosefehler des großen Faktenmodells kleiner als bei den alternativen Modellen sind. Jedoch sind diese emprischen Vorteile nicht statistisch signifikant, wie Tests auf paarweise Gleichheit der Prognosegüte zeigen. Demzufolge scheinen die Effizienzvorteile des auf einem großen Datensatz beruhenden Faktorenmodells lediglich gering zu sein.

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Bibliographic Info

Paper provided by Hamburg Institute of International Economics (HWWA) in its series HWWA Discussion Papers with number 199.

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Date of creation: 2002
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Handle: RePEc:zbw:hwwadp:26321

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Keywords: Factor models; Principal components; forecasting accuracy;

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