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DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning

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  • Anders Warne

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.

Suggested Citation

  • Anders Warne, 2026. "DSGE Model Forecasting: Rational Expectations Versus Adaptive Learning," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(5), pages 2565-2586, August.
    • Handle: RePEc:wly:jforec:v:45:y:2026:i:5:p:2565-2586
    DOI: 10.1002/for.70155
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