IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-09-00718.html
   My bibliography  Save this article

Stability under learning: the neo-classical growth problem

Author

Listed:
  • Orlando Gomes

    (ISCAL - IPL; Economics Research Center [UNIDE/ISCTE - ERC])

Abstract

A local stability condition for the standard neo-classical Ramsey growth model is derived. The proposed setting is deterministic, defined in discrete time and expectations are formed through adaptive learning. The stability condition imposes an upper bound on the long-term value of the gain sequence.

Suggested Citation

  • Orlando Gomes, 2009. "Stability under learning: the neo-classical growth problem," Economics Bulletin, AccessEcon, vol. 29(4), pages 3186-3193.
  • Handle: RePEc:ebl:ecbull:eb-09-00718
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2009/Volume29/EB-09-V29-I4-P308.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cellarier, Laurent, 2006. "Constant gain learning and business cycles," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 51-85, March.
    2. Bullard James, 1994. "Learning Equilibria," Journal of Economic Theory, Elsevier, vol. 64(2), pages 468-485, December.
    3. Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2016. "Stock Market Volatility and Learning," Journal of Finance, American Finance Association, vol. 71(1), pages 33-82, February.
    4. Stefano Eusepi & Bruce Preston, 2011. "Expectations, Learning, and Business Cycle Fluctuations," American Economic Review, American Economic Association, vol. 101(6), pages 2844-2872, October.
    5. Gomes, Orlando, 2009. "Stability under learning: The endogenous growth problem," Economic Modelling, Elsevier, vol. 26(5), pages 807-816, September.
    6. Schonhofer, Martin, 1999. "Chaotic Learning Equilibria," Journal of Economic Theory, Elsevier, vol. 89(1), pages 1-20, November.
    7. Sobel, Joel, 2000. "Economists' Models of Learning," Journal of Economic Theory, Elsevier, vol. 94(2), pages 241-261, October.
    8. KevinX.D. Huang & Zheng Liu & Tao Zha, 2009. "Learning, Adaptive Expectations and Technology Shocks," Economic Journal, Royal Economic Society, vol. 119(536), pages 377-405, March.
    9. Carceles-Poveda, Eva & Giannitsarou, Chryssi, 2007. "Adaptive learning in practice," Journal of Economic Dynamics and Control, Elsevier, vol. 31(8), pages 2659-2697, August.
    10. Sorger, Gerhard, 1998. "Imperfect foresight and chaos: an example of a self-fulfilling mistake," Journal of Economic Behavior & Organization, Elsevier, vol. 33(3-4), pages 363-383, January.
    11. Klaus Adam & Albert Marcet & Juan Pablo Nicolini, 2006. "Learning and Stock Market Volatility," Computing in Economics and Finance 2006 15, Society for Computational Economics.
    12. Martin Schonhofer, "undated". "Chaotic Learning Equilibria," Computing in Economics and Finance 1997 121, Society for Computational Economics.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gomes, Orlando, 2009. "Stability under learning: The endogenous growth problem," Economic Modelling, Elsevier, vol. 26(5), pages 807-816, September.
    2. Orlando Gomes, 2010. "Ordinary Least Squares Learning And Nonlinearities In Macroeconomics," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 52-84, February.
    3. repec:ebl:ecbull:v:3:y:2008:i:57:p:1-15 is not listed on IDEAS
    4. Hommes, Cars H. & Rosser,, J. Barkley, 2001. "Consistent Expectations Equilibria And Complex Dynamics In Renewable Resource Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 180-203, April.
    5. Gomes, Orlando, 2009. "Adaptive learning and complex dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 1206-1213.
    6. Caines, Colin, 2020. "Can learning explain boom-bust cycles in asset prices? An application to the US housing boom," Journal of Macroeconomics, Elsevier, vol. 66(C).
    7. Orlando Gomes, 2009. "The timing of information updates: a stability result," Economics Bulletin, AccessEcon, vol. 29(4), pages 2860-2869.
    8. Troy Tassier, 2013. "Handbook of Research on Complexity, by J. Barkley Rosser, Jr. and Edward Elgar," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 39(1), pages 132-133.
    9. Antonio Doria, Francisco, 2011. "J.B. Rosser Jr. , Handbook of Research on Complexity, Edward Elgar, Cheltenham, UK--Northampton, MA, USA (2009) 436 + viii pp., index, ISBN 978 1 84542 089 5 (cased)," Journal of Economic Behavior & Organization, Elsevier, vol. 78(1-2), pages 196-204, April.
    10. Kuang, Pei, 2014. "A model of housing and credit cycles with imperfect market knowledge," European Economic Review, Elsevier, vol. 70(C), pages 419-437.
    11. Gaunersdorfer, A. & Hommes, C.H. & Wagener, F.O.O., 2000. "Bifurcation Routes to Volatility Clustering," CeNDEF Working Papers 00-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    12. Nakov, Anton & Nuño, Galo, 2015. "Learning from experience in the stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 52(C), pages 224-239.
    13. Berardi, Michele & Galimberti, Jaqueson K., 2017. "On the initialization of adaptive learning in macroeconomic models," Journal of Economic Dynamics and Control, Elsevier, vol. 78(C), pages 26-53.
    14. Eva Carceles-Poveda & Chryssi Giannitsarou, 2008. "Asset Pricing with Adaptive Learning," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(3), pages 629-651, July.
    15. Pei Kuang, 2013. "Imperfect Knowledge About Asset Prices and Credit Cycles," Discussion Papers 13-02r, Department of Economics, University of Birmingham.
    16. Berardi, Michele & Galimberti, Jaqueson K., 2017. "Empirical calibration of adaptive learning," Journal of Economic Behavior & Organization, Elsevier, vol. 144(C), pages 219-237.
    17. KevinX.D. Huang & Zheng Liu & Tao Zha, 2009. "Learning, Adaptive Expectations and Technology Shocks," Economic Journal, Royal Economic Society, vol. 119(536), pages 377-405, March.
    18. Kuang, Pei & Mitra, Kaushik, 2016. "Long-run growth uncertainty," Journal of Monetary Economics, Elsevier, vol. 79(C), pages 67-80.
    19. 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 University of Manchester.
    20. Volker Böhm & Carl Chiarella, 2005. "Mean Variance Preferences, Expectations Formation, And The Dynamics Of Random Asset Prices," Mathematical Finance, Wiley Blackwell, vol. 15(1), pages 61-97, January.
    21. Francesco Caprioli & Pietro Rizza & Pietro Tommasino, 2011. "Optimal Fiscal Policy when Agents Fear Government Default," Revue économique, Presses de Sciences-Po, vol. 62(6), pages 1031-1043.

    More about this item

    Keywords

    Neo-classical growth; Adaptive learning; Stability;
    All these keywords.

    JEL classification:

    • O4 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ebl:ecbull:eb-09-00718. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: John P. Conley (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.