Boosting and regional economic forecasting: the case of Germany

Robert Lehmann and Klaus Wohlrabe

Letters in Spatial and Resource Sciences, 2017, vol. 10, issue 2, No 3, 175 pages

Abstract: Abstract This paper applies component-wise boosting to the topic of regional economic forecasting. Component-wise boosting is a pre-selection algorithm of indicators for forecasting. By using unique quarterly real gross domestic product data for two German states (the Free State of Saxony and Baden-Wuerttemberg) and Eastern Germany for the period from 1997 to 2013, in combination with a large data set of monthly indicators, we show that boosting is generally doing a very good job in regional economic forecasting. We additionally take a closer look into the algorithm and ask which indicators get selected. All in all, boosting outperforms our benchmark model for all the three regions considered. We also find that indicators that mirror the region-specific economy get frequently selected by the algorithm.

Keywords: Boosting; Regional economic forecasting; Gross domestic product (search for similar items in EconPapers)
JEL-codes: C53 E17 E37 R11 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Boosting and regional economic forecasting: the case of Germany (2017)
Working Paper: Boosting and Regional Economic Forecasting: The Case of Germany (2016)
Working Paper: The role of component-wise boosting for regional economic forecasting (2015)
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DOI: 10.1007/s12076-016-0179-1

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