Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/104405
Authors: 
Lehmann, Robert
Wohlrabe, Klaus
Year of Publication: 
2013
Series/Report no.: 
Munich Discussion Paper 2013-13
Abstract: 
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.
Subjects: 
regional forecasting
forecast combination
factor models
model confidence set
data–rich environment
JEL: 
C32
C52
C53
E37
R11
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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