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LEARNABILITY OF E–STABLE EQUILIBRIA

Published online by Cambridge University Press:  03 April 2013

Atanas Christev
Affiliation:
Heriot-Watt University and IZA
Sergey Slobodyan
Affiliation:
CERGE-EI
Corresponding
E-mail address:

Abstract

If private sector agents update their beliefs with a learning algorithm other than recursive least squares, expectational stability or learnability of rational expectations equilibria (REE) is not guaranteed. Monetary policy under commitment, with a determinate and E-stable REE, may not imply robust learning stability of such equilibria if the RLS speed of convergence is slow. In this paper, we propose a refinement of E-stability conditions that allows us to select equilibria more robust to specification of the learning algorithm within the RLS/SG/GSG class. E-stable equilibria characterized by faster speed of convergence under RLS learning are learnable with SG or generalized SG algorithms as well.

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Copyright © Cambridge University Press 2013 

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LEARNABILITY OF E–STABLE EQUILIBRIA
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