Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/96667
Authors: 
Lehmann, Robert
Wohlrabe, Klaus
Year of Publication: 
2013
Series/Report no.: 
Ifo Working Paper 171
Abstract: 
In this paper, we ask whether it is possible to forecast gross value-added (GVA) and its sectoral subcomponents at the regional level. With an autoregressive distributed lagmodel we forecast total and sectoral GVA for one German state (Saxony) with more than 300 indicators from different regional levels (international, national and regional) and additionally make usage of different forecast pooling strategies and factor models.Our results show that we are able to increase forecast accuracy of GVA for every sector and for all forecast horizons (one up to four quarters) compared to an autoregressive process. Finally, we show that sectoral forecasts contain more information in the short term (one quarter), whereas direct forecasts of total GVA are referable in the medium (two and three quarters) and long term (four quarters).
Subjects: 
Regional forecasting
gross value-added
forecast combination
disaggregated forecasts
factor models.
JEL: 
C32
C52
C53
E37
R11
Document Type: 
Working Paper

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