Forecasting GDP at the Regional Level with Many Predictors
Robert Lehmann and
Klaus Wohlrabe
No 3956, CESifo Working Paper Series from CESifo
Abstract:
In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a unique 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 including more than 300 international, national and regional indicators. We calculate single–indicator, multi–indicator and pooled forecasts. Our results show that we can significantly increase forecast accuracy compared to an autoregressive benchmark model, both for short- and long-term predictions. Furthermore, our best leading indicators describe the specific regional economic structure better than other indicators.
Keywords: leading indicators; regional forecasting; forecast evaluation; forecast combination; data rich environment (search for similar items in EconPapers)
JEL-codes: C32 C52 C53 E37 R11 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
https://www.cesifo.org/DocDL/cesifo1_wp3956.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 503 Service Unavailable
Related works:
Journal Article: Forecasting GDP at the Regional Level with Many Predictors (2015) 
Journal Article: Forecasting GDP at the Regional Level with Many Predictors (2015) 
Working Paper: Forecasting GDP at the regional level with many predictors (2013) 
Working Paper: Forecasting GDP at the regional level with many predictors (2013) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ces:ceswps:_3956
Access Statistics for this paper
More papers in CESifo Working Paper Series from CESifo Contact information at EDIRC.
Bibliographic data for series maintained by Klaus Wohlrabe ().