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Learning in a Misspecified Multivariate Self-Referential Linear Stochastic Model

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  • Eran Guse

    (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 misspecified expectations

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Bibliographic Info

Paper provided by Money Macro and Finance Research Group in its series Money Macro and Finance (MMF) Research Group Conference 2006 with number 71.

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Date of creation: 02 Feb 2007
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Handle: RePEc:mmf:mmfc06:71

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Web page: http://www.essex.ac.uk/afm/mmf/index.html

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Keywords: Adaptive Learning; Expectational Stability; Monetary Policy Rules; Restricted Perceptions Equilibria; Seemingly Unrelated Regression;

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Cited by:
  1. Eran A. Guse, 2008. "Heterogeneous Expectations, Adaptive Learning, and Evolutionary Dynamics," Working Papers 09-01, Department of Economics, West Virginia University.
  2. George W. Evans & Seppo Honkapohja, 2008. "Expectations, Learning, And Monetary Policy: An Overview Of Recent Research," Working Papers Central Bank of Chile, Central Bank of Chile 501, Central Bank of Chile.
  3. Jim Granato & Eran Guse & Sunny Wong, 2006. "Learning From the Expectations of Others," Computing in Economics and Finance 2006, Society for Computational Economics 449, Society for Computational Economics.

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