DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning

Anders Warne

doi:10.1002/for.70155

journal article Open Access Apr 09, 2026

DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning

Anders Warne

Journal of Forecasting · Wiley

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Abstract

ABSTRACT
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 and 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.

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Published: Apr 09, 2026
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Anders Warne

Forecasting and Policy Modelling Division of DG‐Economics European Central Bank Frankfurt am Main Germany

Cite This Article

Anders Warne (2026). DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning. Journal of Forecasting. https://doi.org/10.1002/for.70155

DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning

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