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LEARNABILITY OF E–STABLE EQUILIBRIA

  • Atanas Christev (a1) and Sergey Slobodyan (a2)

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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Corresponding author

Address correspondence to: Atanas Christev, Department of Economics, Mary Burton Building, Room 1.4, Heriot-Watt University, Riccarton, Edinburgh EH14 4AS, UK; e-mail: A.Christev@hw.ac.uk.

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