Learning in a Misspecified Multivariate Self-referential Linear Stochastic Model

Eran Guse

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: This paper introduces a general method to study stability (under learning) of equilibria resulting from agents with misspecified perceptions of the law of motion of the economy. This is done by transforming the actual and perceived laws of motion into the form of seemingly unrelated regressions and then linearly projecting the actual law of motion into the same class as the perceived law of motion. I study the New Keynesian IS-LM model with inertia under all possible classes of restricted perceptions. It turns out that the results found in Bullard and Mitra (2002, 2003) are robust under misspeci.ed expectations.

Keywords: Adaptive Learning; Expectational Stability; Monetary Policy Rules; Restricted Perceptions Equilibria; Seemingly Unrelated Regression (search for similar items in EconPapers)
JEL-codes: E4 E5 (search for similar items in EconPapers)
Pages: 27
Date: 2005-10
New Economics Papers: this item is included in nep-mac
Note: Ma
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Citations: View citations in EconPapers (2)

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Related works:
Journal Article: Learning in a misspecified multivariate self-referential linear stochastic model (2008)
Working Paper: Learning in a Misspecified Multivariate Self-Referential Linear Stochastic Model (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:0548

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