On learnability of Eâ€“stable equilibria
While under recursive least squares learning the dynamics of the economy converges to rational expectations equilibria (REE) which are Eâ€“stable, some recent examples propose that Eâ€“stability is not a sufficient condition for learnability. In this paper, we provide some further evidence on the conditions under which Eâ€“stability of a particular equilibrium might fail to imply its stochastic gradient (SG) or generalized SG learnability. We also claim that the requirement on the speed of convergence of the learning process imposed by  also implies that Eâ€“stable equilibria are likely to be GSG learnable. We show this in a simple â€ New Keneysianâ€ model of optimal monetary policy design in which the stability of REE under SG learning. In this case, the paper gives the conditions which are necessary for reversal of learnability
|Date of creation:||04 Jul 2006|
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- George W. Evans & Seppo Honkapohja & Noah Williams, 2005.
"Generalized Stochastic Gradient Learning,"
NBER Technical Working Papers
0317, National Bureau of Economic Research, Inc.
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- George W. Evans & Seppo Honkapohja & Noah Williams, 2005. "Generalized Stochastic Gradient Learning," CESifo Working Paper Series 1576, CESifo Group Munich.
- George W. Evans & Seppo Honkapohja & Noah Williams, 2005. "Generalized Stochastic Gradient Learning," University of Oregon Economics Department Working Papers 2005-17, University of Oregon Economics Department, revised 18 May 2008.
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- Giuseppe Ferrero, 2004.
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19, Society for Computational Economics.
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- Barucci, Emilio & Landi, Leonardo, 1997. "Least mean squares learning in self-referential linear stochastic models," Economics Letters, Elsevier, vol. 57(3), pages 313-317, December.
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