Forecasting GDP at the regional level with many predictors

Arbeitspapier

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 indicators. 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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Munich Discussion Paper ; No. 2013-13

Classification and Topics

• Classification: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Model Evaluation, Validation, and Selection ; Forecasting Models; Simulation Methods ; Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications ; Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
• Subject: regional forecasting ; forecast combination ; factor models ; model confidence set ; data–rich environment

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Lehmann, Robert ; Wohlrabe, Klaus
• Event: Veröffentlichung
• (who): Ludwig-Maximilians-Universität München, Volkswirtschaftliche Fakultät
• (where): München
• (when): 2013

Further information

• DOI: doi:10.5282/ubm/epub.17104
• Handle: http://hdl.handle.net/10419/104405
• URN: urn:nbn:de:bvb:19-epub-17104-8
• Last update: 10.03.2025, 11:42 AM CET