Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones?

Arbeitspapier

In this paper, we ask whether it is possible to forecast gross value-added (GVA) and its sectoral subcomponents at the regional level. With an autoregressive distributed lagmodel we forecast total and sectoral GVA for one German state (Saxony) with more than 300 indicators from different regional levels (international, national and regional) and additionally make usage of different forecast pooling strategies and factor models.Our results show that we are able to increase forecast accuracy of GVA for every sector and for all forecast horizons (one up to four quarters) compared to an autoregressive process. Finally, we show that sectoral forecasts contain more information in the short term (one quarter), whereas direct forecasts of total GVA are referable in the medium (two and three quarters) and long term (four quarters).

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: ifo Working Paper ; No. 171

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 ; gross value-added ; forecast combination ; disaggregated forecasts ; factor models.

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Lehmann, Robert ; Wohlrabe, Klaus
• Event: Veröffentlichung
• (who): ifo Institute - Leibniz Institute for Economic Research at the University of Munich
• (where): Munich
• (when): 2013

Further information

• Handle: http://hdl.handle.net/10419/96667
• Last update: 10.03.2025, 11:44 AM CET