Arbeitspapier
Evaluating Ensemble Density Combination - Forecasting GDP and Inflation
Forecast combination has become popular in central banks as a means to improve forecasts and to alleviate the risk of selecting poor models. However, if a model suite is populated with many similar models, then the weight attached to other independent models may be lower than warranted by their performance. One way to mitigate this problem is to group similar models into distinct `ensembles'. Using the original suite of models in Norges Bank's system for averaging models (SAM), we evaluate whether forecast performance can be improved by combining ensemble densities, rather than combining individual model densities directly. We evaluate performance both in terms of point forecasts and density forecasts, and test whether the densities are well-calibrated. We find encouraging results for combining ensembles.
- ISBN
-
978-82-7553-524-3
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 2009/19
- Klassifikation
-
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
Monetary Policy
- Thema
-
forecasting
density combination
model combination
clustering
ensemble density
pits
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Gerdrup, Karsten R.
Jore, Anne Sofie
Smith, Christie
Thorsrud, Leif Anders
- Ereignis
-
Veröffentlichung
- (wer)
-
Norges Bank
- (wo)
-
Oslo
- (wann)
-
2009
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Gerdrup, Karsten R.
- Jore, Anne Sofie
- Smith, Christie
- Thorsrud, Leif Anders
- Norges Bank
Entstanden
- 2009
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