Boosting and regional economic forecasting: the case of Germany

Robert Lehmann and Klaus Wohlrabe

Munich Reprints in Economics from University of Munich, Department of Economics

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.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Published in Letters in Spatial and Resource Science 2 10(2017): pp. 161-175

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Journal Article: Boosting and regional economic forecasting: the case of Germany (2017)
Working Paper: Boosting and Regional Economic Forecasting: The Case of Germany (2016)
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:lmu:muenar:49919

Access Statistics for this paper

More papers in Munich Reprints in Economics from University of Munich, Department of Economics Ludwigstr. 28, 80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Tamilla Benkelberg ().