Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/123828 
Year of Publication: 
2013
Series/Report no.: 
53rd Congress of the European Regional Science Association: "Regional Integration: Europe, the Mediterranean and the World Economy", 27-31 August 2013, Palermo, Italy
Publisher: 
European Regional Science Association (ERSA), Louvain-la-Neuve
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 ones. 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. Keywords: regional forecasting, forecast combination, factor models, model confidence set, data?rich environment JEL Code: C32, C52, C53, E37, R11
Subjects: 
LEADING INDICATORS
REGIONAL FORECASTING
FORECAST EVALUATION
FORECAST COMBINATION
DATA RICH ENVIRONMENT
JEL: 
C32
C52
C53
E37
R11
Document Type: 
Conference Paper

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