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LEARNING TO FORECAST AND CYCLICAL BEHAVIOR OF OUTPUT AND INFLATION

Published online by Cambridge University Press:  01 February 2005

KLAUS ADAM
KLAUS ADAM
Affiliation:
CEPR Goethe University of Frankfurt, European Central Bank and Center for Financial Studies
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Abstract

This paper considers a sticky price model with a cash-in-advance constraint where agents forecast inflation rates with the help of econometric models. Agents use least-squares learning to estimate two competing models of which one is consistent with rational expectations once learning is complete. When past performance governs the choice of forecast model, agents may prefer to use the inconsistent forecast model, which generates an equilibrium where forecasts are only constrained rational. Output and inflation then display persistence, inflation responds sluggishly to nominal disturbances, and the dynamic correlations of output and inflation match U.S. data surprisingly well. The rational expectations equilibrium instead has great difficulty in matching any of these features.

Keywords

LearningBusiness CyclesConstrained Rational ExpectationsInefficient ForecastsOutputInflation Persistence
Type
ARTICLES
Information
Macroeconomic Dynamics , Volume 9 , Issue 1 , February 2005 , pp. 1 - 27
Copyright
© 2005 Cambridge University Press

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