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Convergence of Learning Algorithms without a Projection Facility

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Author Info
Honkapohja, Seppo
Evans, George W.

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Abstract

Drawing upon recent contributions in the statistical literature, we present new results on the convergence of recursive, stochastic algorithms which can be applied to eonomic models with learning and which generalize previous results. The formal results provide probability bounds for convergence which can be used to describe the local stability under learning of rational expectations equilibria in stochastic models. Economic examples include local stability in a multivariate linear model with multiple equilibria and global convergence in a model with a unique equilibrium.

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Publisher Info
Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number CESifo Working Paper No. 109.

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Date of creation: 1996
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Handle: RePEc:ces:ceswps:_109

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  1. Chryssi Giannitsarou, 2003. "Heterogeneous Learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 6(4), pages 885-906, October. [Downloadable!] (restricted)
  2. Chryssi Giannitsarou, 2004. "Supply-side reforms and learning dynamics," Money Macro and Finance (MMF) Research Group Conference 2003 36, Money Macro and Finance Research Group. [Downloadable!]
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  3. Seppo Honkapohja & Kaushik Mitra, . "Adaptive Learning in Stochastic Nonlinear Models When Shocks Follow a Markov Chain," Discussion Papers 03-22, University of Copenhagen. Department of Economics, revised Apr 2003. [Downloadable!]
  4. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2006. "Adaptive Learning in Practice," CEPR Discussion Papers 5627, C.E.P.R. Discussion Papers. [Downloadable!] (restricted)
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  5. Sinn, Hans-Werner, 1999. "Inflation and Welfare: Comment on Robert Lucas," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
    Other versions:
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This page was last updated on 2009-11-3.

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