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Convergence of Learning Algorithms without a Projection Facility

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  • Seppo Honkapohja
  • George W. Evans

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.

Suggested Citation

  • Seppo Honkapohja & George W. Evans, 1996. "Convergence of Learning Algorithms without a Projection Facility," CESifo Working Paper Series 109, CESifo.
    • Handle: RePEc:ces:ceswps:_109
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    Cited by:

    1. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    2. Mele, Antonio & Molnár, Krisztina & Santoro, Sergio, 2020. "On the perils of stabilizing prices when agents are learning," Journal of Monetary Economics, Elsevier, vol. 115(C), pages 339-353.
    3. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2007. "Adaptive learning in practice," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2659-2697, August.
    4. Giannitsarou, Chryssi, 2006. "Supply-side reforms and learning dynamics," Journal of Monetary Economics, Elsevier, vol. 53(2), pages 291-309, March.
    5. Hans-Werner Sinn, 1999. "Inflation and Welfare: Comment on Robert Lucas," NBER Working Papers 6979, National Bureau of Economic Research, Inc.
    6. Davide Delle Monache & Ivan Petrella, 2014. "Adaptive Models and Heavy Tails," Working Papers 720, Queen Mary University of London, School of Economics and Finance.
    7. Chryssi Giannitsarou, 2003. "Heterogeneous Learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 6(4), pages 885-906, October.

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