Short-Term Forecasting of GDP and Inflation in Real-Time: Norges Bank's System for Averaging Models

Bericht

In this paper we describe Norges Bank's system for averaging models (SAM) which produces model-based density forecasts for Norwegian Mainland GDP and inflation. We combine the forecasts from three main types of models typically used at central banks: Vector autoregressive models, leading indicator models and factor models. By combining models we hedge against uncertain instabilities. We update SAM several times during the quarter to highlight the importance of new data releases, and we show how the performance of SAM improves steadily as new information arrives. The framework is robust with regard to alternative vintages of data to evaluate against. We show that our chosen weighting scheme is superior or on a par with some common alternative weighting schemes, and, finally, that a strategy of trying to pick the best model, ex ante, is inferior to model combination.

Object Details

• ISBN: 978-82-7553-617-2
• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Staff Memo ; No. 09/2011

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 ; Monetary Policy
• Subject: density combination ; forecast densities ; forecast evaluation ; monetary policy ; nowcasting ; real-time data

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Aastveit, Knut Are ; Gerdrup, Karsten R. ; Jore, Anne Sofie
• Event: Veröffentlichung
• (who): Norges Bank
• (where): Oslo
• (when): 2011

Further information

• Handle: http://hdl.handle.net/10419/210225
• Last update: 10.03.2025, 11:44 AM CET