Learning-Based Inflation Expectations in an Unobserved Components Model
28 Pages Posted: 6 Apr 2021
Date Written: April 2, 2021
We examine the role of adaptive learning-based inflation expectations in determining the output gap within the context of an Unobserved Components model. The forward-looking New Keynesian Phillips curve serves as the backbone for modeling inflation dynamics. We find that learning based inflation forecasts largely shadow survey expectations in the pre-Volcker era and they do not exhibit persistent overshooting during the initial stages of the financial crisis. Likewise, our implied output gap also deviates the most from a gap estimated using survey expectations in the post 1984 sample. The interesting learning dynamics around business cycle turning points during this period indicate that the last three recessions were at least partially driven by large drops in the trend component of output.
Keywords: Adaptive Learning, Output Gap, Inflation, Unobserved Components Model
JEL Classification: E31, E32, E50, C32
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