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Forecasting GDP at the regional level with many predictors

Listed author(s):
  • Lehmann, Robert
  • Wohlrabe, Klaus

In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a large data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden- Württemberg) and Eastern Germany. We overcome the problem of a ’data-poor environment’ at the sub-national level by complementing various regional indicators with more than 200 national and international indicators. We calculate single– indicator, multi–indicator, pooled and factor forecasts in a pseudo real–time setting. Our results show that we can significantly increase forecast accuracy compared to an autoregressive benchmark model, both for short and long term predictions. Furthermore, regional indicators play a crucial role for forecasting regional GDP.

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File URL: https://epub.ub.uni-muenchen.de/17104/1/Lehmann_Wohlrabe_2013.pdf
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Paper provided by University of Munich, Department of Economics in its series Discussion Papers in Economics with number 17104.

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Date of creation: 14 Sep 2013
Handle: RePEc:lmu:muenec:17104
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