Arbeitspapier
Bayesian Forecast Combination for VAR Models
We consider forecast combination and, indirectly, model selection for VAR models when there is uncertainty about which variables to include in the model in addition to the forecast variables. The key di erence from traditional Bayesian variable selection is that we also allow for uncertainty regarding which endogenous variables to include in the model. That is, all models include the forecast variables, but may otherwise have di ering sets of endogenous variables. This is a difficult problem to tackle with a traditional Bayesian approach. Our solution is to focus on the forecasting performance for the variables of interest and we construct model weights from the predictive likelihood of the forecast variables. The procedure is evaluated in a small simulation study and found to perform competitively in applications to real world data.
- Sprache
-
Englisch
- Erschienen in
-
Series: Working Paper ; No. 13/2007
- Klassifikation
-
Wirtschaft
Bayesian Analysis: General
Statistical Simulation Methods: General
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
- Thema
-
Bayesian model averaging
Predictive likelihood
GDP forecasts
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Andersson, Michael K
Karlsson, Sune
- Ereignis
-
Veröffentlichung
- (wer)
-
Örebro University School of Business
- (wo)
-
Örebro
- (wann)
-
2007
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:46 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Andersson, Michael K
- Karlsson, Sune
- Örebro University School of Business
Entstanden
- 2007
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