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BAYESIAN ESTIMATION OF A SMALL-SCALE NEW KEYNESIAN MODEL WITH HETEROGENEOUS EXPECTATIONS

Published online by Cambridge University Press:  25 August 2020

Christopher J. Elias
Christopher J. Elias*
Affiliation:
Eastern Michigan University
*
Address correspondence to: Christopher J. Elias, Department of Economics, Eastern Michigan University, 703 Pray-Harrold, Ypsilanti, MI 48197, USA. e-mail: celias@emich.edu. Phone: 734-487-2209.
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Abstract

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This paper uses Bayesian methods to estimate a small-scale New Keynesian model with heterogeneous expectations (HE). Agents form expectations via Euler equation adaptive learning (AL) and differ by the model they use to forecast. Type A agents use a correctly specified model, while type B and type C agents use misspecified models. Quarterly US data from the pre-Great Moderation and Great Moderation periods are used to jointly estimate the degree of agent heterogeneity, the AL parameters, and the deep model parameters. Results show that the data exhibit significant expectational heterogeneity, and that the HE model fits the data better than a model with homogeneous agent AL.

Keywords

Heterogenous ExpectationsAdaptive LearningBayesian EconometricsNew Keynesian Model

Information

Type
Articles
Information
Macroeconomic Dynamics , Volume 26 , Issue 4 , June 2022, pp. 920 - 944
Copyright
© 2020 Cambridge University Press

Footnotes

I am grateful to James Saunoris, Steven Hayworth, Amanda Stype, seminar participants at Eastern Michigan University, journal editor William Barnett, co-editor George Evans, and two anonymous referees for many useful comments and suggestions that improved the paper significantly. All errors are my own.

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