Arbeitspapier
DSGE model forecasting: Rational expectations vs. adaptive learning
This paper compares within-sample and out-of-sample fit of a DSGE model with rational expectations to a model with adaptive learning. The Galí, Smets and Wouters model is the chosen laboratory using quarterly real-time euro area data vintages, covering 2001Q1-2019Q4. The adaptive learning model obtains better within-sample fit for all vintages used for estimation in the forecast exercise and for the full sample. However, the rational expectations model typically predicts real GDP growth better as well as jointly with inflation. For the marginal inflation forecasts, the same holds for the inner quarters of the forecast horizon, while the adaptive learning model predicts better for the outer quarters.
- ISBN
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978-92-899-5510-2
- Language
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Englisch
- Bibliographic citation
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Series: ECB Working Paper ; No. 2768
- Classification
-
Wirtschaft
Bayesian Analysis: 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
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
- Subject
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Bayesian inference
CRPS
euro area
forecast comparison/evaluation
log score
real-time data
- Event
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Geistige Schöpfung
- (who)
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Warne, Anders
- Event
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Veröffentlichung
- (who)
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European Central Bank (ECB)
- (where)
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Frankfurt a. M.
- (when)
-
2023
- DOI
-
doi:10.2866/05307
- Handle
- Last update
-
10.03.2025, 11:41 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Warne, Anders
- European Central Bank (ECB)
Time of origin
- 2023
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