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Stochastic Gradient Learning in the Cobweb Model

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  • Evans, G.W.
  • Honkapohja, S.

Abstract

We consider the effects of replacing least squares learning by stochastic gradient learning in the multivariate "Cobweb" model. Are the stability conditions altered? For this model, we show global convergence of stochastic gradient learning to the unique rational expectations equilibrium provided the E-stability condition is satisfied.

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Bibliographic Info

Paper provided by Department of Economics in its series University of Helsinki, Department of Economics with number 438.

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Length: 7 pages
Date of creation: 1998
Date of revision:
Handle: RePEc:fth:helsec:438

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Postal: University of Helsinki; Department of Economics, P.O.Box 54 (Unioninkatu 37) FIN-00014 Helsingin Yliopisto
Phone: +358 9 191 8897
Fax: +358 9 191 8877
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Web page: http://www.helsinki.fi/politiikkajatalous/
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Keywords: ECONOMETRICS ; ECONOMIC MODELS ; BOUNDED RATIONALITY;

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References

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  1. Kuan, Chung-Ming & White, Halbert, 1994. "Adaptive Learning with Nonlinear Dynamics Driven by Dependent Processes," Econometrica, Econometric Society, vol. 62(5), pages 1087-1114, September.
  2. Evans, George W & Honkapohja, Seppo, 1998. "Economic Dynamics with Learning: New Stability Results," Review of Economic Studies, Wiley Blackwell, vol. 65(1), pages 23-44, January.
  3. Marcet, Albert & Sargent, Thomas J., 1989. "Convergence of least squares learning mechanisms in self-referential linear stochastic models," Journal of Economic Theory, Elsevier, vol. 48(2), pages 337-368, August.
  4. 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.
  5. Bray, Margaret M & Savin, Nathan E, 1986. "Rational Expectations Equilibria, Learning, and Model Specification," Econometrica, Econometric Society, vol. 54(5), pages 1129-60, September.
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Cited by:
  1. Ronald B. Davies & Paul Shea, 2003. "Adaptive Learning with a Unit Root: An Application to the Current Account," University of Oregon Economics Department Working Papers 2006-15, University of Oregon Economics Department, revised 10 Jun 2003.
  2. Gauthier, S., 1999. "Determinacy and Stability under Learning of Rational Expectations Equilibria," DELTA Working Papers 1999-22, DELTA (Ecole normale supérieure).
  3. Domenico Colucci & V. Valori, 2001. "Error learning behaviour and stability revisited," CeNDEF Workshop Papers, January 2001 1A.1, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
  4. Honkapohja, Seppo & Mitra, Kaushik, 2002. "Learning stability in economics with heterogeneous agents," Working Paper Series 0120, European Central Bank.
  5. Atanas Christev, 2006. "Learning Hyperinflations," Computing in Economics and Finance 2006 475, Society for Computational Economics.
  6. Michele Berardi & Jaqueson K. Galimberti, 2012. "A note on exact correspondences between adaptive learning algorithms and the Kalman filter," Centre for Growth and Business Cycle Research Discussion Paper Series 170, Economics, The Univeristy of Manchester.
  7. Berardi, Michele & Galimberti, Jaqueson K., 2014. "A note on the representative adaptive learning algorithm," Economics Letters, Elsevier, vol. 124(1), pages 104-107.
  8. 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.
  9. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the plausibility of adaptive learning in macroeconomics: A puzzling conflict in the choice of the representative algorithm," Centre for Growth and Business Cycle Research Discussion Paper Series 177, Economics, The Univeristy of Manchester.
  10. Michele Berardi & Jaqueson K. Galimberti, 2012. "On the initialization of adaptive learning algorithms: A review of methods and a new smoothing-based routine," Centre for Growth and Business Cycle Research Discussion Paper Series 175, Economics, The Univeristy of Manchester.

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