Boosting and Regional Economic Forecasting: The Case of Germany

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CESifo Working Paper ; No. 6157

Classification and Topics

• Classification: Wirtschaft ; Forecasting Models; Simulation Methods ; General Aggregative Models: Forecasting and Simulation: Models and Applications ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications ; Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
• Subject: boosting ; regional economic forecasting ; gross domestic product

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Lehmann, Robert ; Wohlrabe, Klaus
• Event: Veröffentlichung
• (who): Center for Economic Studies and ifo Institute (CESifo)
• (where): Munich
• (when): 2016

Further information

• Handle: http://hdl.handle.net/10419/149244
• Last update: 10.03.2025, 11:42 AM CET