Initial Expectations in New Keynesian Models with Learning

37 Pages Posted: 15 Jun 2008

See all articles by James Murray

James Murray

University of Wisconsin - La Crosse – Department of Economics

Date Written: June 13, 2008

Abstract

This paper examines how the estimation results for a standard New Keynesian model with constant gain least squares learning is sensitive to the stance taken on agents beliefs at the beginning of the sample. The New Keynesian model is estimated under rational expectations and under learning with three different frameworks for how expectations are set at the beginning of the sample. The results show that initial beliefs can have an impact on the predictions of an estimated model; in fact previous literature has exposed this sensitivity to explain the changing volatilities of output and inflation in the post-war United States. The results indicate statistical evidence for adaptive learning, however the rational expectations framework performs at least as well as the learning frameworks, if not better, in in-sample and out-of-sample forecast error criteria. Moreover, learning is not found to better explain time varying macroeconomic volatility any better than rational expectations. Finally, impulse response functions from the estimated models show that the dynamics following a structural shock can depend crucially on how expectations are initialized and what information agents are assumed to have.

Keywords: Learning, expectations, New Keynesian model, maximum likelihood

JEL Classification: C13, E31, E50

Suggested Citation

Murray, James, Initial Expectations in New Keynesian Models with Learning (June 13, 2008). CAEPR Working Paper No. 2008-017, Available at SSRN: https://ssrn.com/abstract=1145416 or http://dx.doi.org/10.2139/ssrn.1145416

James Murray (Contact Author)

University of Wisconsin - La Crosse – Department of Economics ( email )

1725 State Street
La Crosse, WI 54601
United States
608-785-5140 (Phone)

HOME PAGE: http://www.murraylax.org

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