IDEAS home Printed from https://ideas.repec.org/p/sur/surrec/1512.html
   My bibliography  Save this paper

Learning from learners

Author

Listed:
  • Tom Holden

    (University of Surrey)

Abstract

Traditional macroeconomic learning algorithms are misspecified when all agents are learning simultaneously. In this paper, we produce a number of learning algorithms that do not share this failing, and show that this enables them to learn almost any solution, for any parameters, implying learning cannot be used for equilibrium selection. As a by-product, we are able to show that when all agents are learning by traditional methods, all deep structural parameters of standard new-Keynesian models are identified, overturning a key result of Cochrane (2009; 2011). This holds irrespective of whether the central bank is following the Taylor principle, irrespective of whether the implied path is or is not explosive, and irrespective of whether agents’ beliefs converge. If shocks are observed then this result is trivial, so following Cochrane (2009) our analysis is carried out in the more plausible case in which agents do not observe shocks.

Suggested Citation

  • Tom Holden, 2012. "Learning from learners," School of Economics Discussion Papers 1512, School of Economics, University of Surrey.
  • Handle: RePEc:sur:surrec:1512
    as

    Download full text from publisher

    File URL: https://repec.som.surrey.ac.uk/2012/DP15-12.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ellison, Martin & Pearlman, Joseph, 2011. "Saddlepath learning," Journal of Economic Theory, Elsevier, vol. 146(4), pages 1500-1519, July.
    2. Holden, Tom, 2008. "Rational macroeconomic learning in linear expectational models," MPRA Paper 10872, University Library of Munich, Germany.
    3. Lubik, Thomas A. & Schorfheide, Frank, 2003. "Computing sunspot equilibria in linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 28(2), pages 273-285, November.
    4. Pearlman, Joseph & Currie, David & Levine, Paul, 1986. "Rational expectations models with partial information," Economic Modelling, Elsevier, vol. 3(2), pages 90-105, April.
    5. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    6. Paul Levine & Joseph Pearlman & George Perendia & Bo Yang, 2012. "Endogenous Persistence in an estimated DSGE Model Under Imperfect Information," Economic Journal, Royal Economic Society, vol. 122(565), pages 1287-1312, December.
    7. Norbert Christopeit & Michael Massmann, 2010. "Consistent Estimation of Structural Parameters in Regression Models with Adaptive Learning," Tinbergen Institute Discussion Papers 10-077/4, Tinbergen Institute.
    8. Cochrane, John H., 2009. "Can learnability save new-Keynesian models?," Journal of Monetary Economics, Elsevier, vol. 56(8), pages 1109-1113, November.
    9. McCallum, Bennett T., 1983. "On non-uniqueness in rational expectations models : An attempt at perspective," Journal of Monetary Economics, Elsevier, vol. 11(2), pages 139-168.
    10. Gabrielsen, Arne, 1978. "Consistency and identifiability," Journal of Econometrics, Elsevier, vol. 8(2), pages 261-263, October.
    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. Holden, Tom, 2008. "Rational macroeconomic learning in linear expectational models," MPRA Paper 10872, University Library of Munich, Germany.
    2. Marco Airaudo & Salvatore Nisticò & Luis‐Felipe Zanna, 2015. "Learning, Monetary Policy, and Asset Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 47(7), pages 1273-1307, October.
    3. Cristiano Cantore & Vasco J. Gabriel & Paul Levine & Joseph Pearlman & Bo Yang, 2013. "The science and art of DSGE modelling: II – model comparisons, model validation, policy analysis and general discussion," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 19, pages 441-463, Edward Elgar Publishing.
    4. Farmer, Roger E.A. & Waggoner, Daniel F. & Zha, Tao, 2011. "Minimal state variable solutions to Markov-switching rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 35(12), pages 2150-2166.
    5. Ellison, Martin & Pearlman, Joseph, 2011. "Saddlepath learning," Journal of Economic Theory, Elsevier, vol. 146(4), pages 1500-1519, July.
    6. Paolo Surico, 2005. "Monetary Policy Shifts, Indeterminacy and Inflation Dynamics," Macroeconomics 0504014, University Library of Munich, Germany.
    7. Farmer, Roger E.A. & Khramov, Vadim & Nicolò, Giovanni, 2015. "Solving and estimating indeterminate DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 54(C), pages 17-36.
    8. Paul Levine & Joseph Pearlman & Bo Yang, 2012. "Imperfect Information, Optimal Monetary Policy and Informational Consistency," School of Economics Discussion Papers 1012, School of Economics, University of Surrey.
    9. Paul Levine & Joseph Pearlman & George Perendia & Bo Yang, 2012. "Endogenous Persistence in an estimated DSGE Model Under Imperfect Information," Economic Journal, Royal Economic Society, vol. 122(565), pages 1287-1312, December.
    10. Paolo Surico, 2008. "Monetary policy shifts and inflation dynamics," Bank of England working papers 338, Bank of England.
    11. Levine, P. & Pearlman, J. & Wright, S. & Yang, B., 2019. "Information, VARs and DSGE Models," Working Papers dp16/19, Department of Economics, City University London.
    12. Thomas A. Lubik & Frank Schorfheide, 2004. "Testing for Indeterminacy: An Application to U.S. Monetary Policy," American Economic Review, American Economic Association, vol. 94(1), pages 190-217, March.
    13. Elmar Mertens & Christian Matthes & Thomas Lubik, 2017. "Indeterminacy and Imperfect Information," 2017 Meeting Papers 337, Society for Economic Dynamics.
    14. Efrem Castelnuovo & Paolo Surico, 2005. "The Price Puzzle and Indeterminacy," Macroeconomics 0507021, University Library of Munich, Germany.
    15. Efrem Castelnuovo & Paolo Surico, 2005. "The Price Puzzle: Fact or Artefact?," Macroeconomics 0505015, University Library of Munich, Germany, revised 19 Jul 2005.
    16. Buiter, Willem H., 1984. "Policy Evaluation and Design for Continuous Time Linear Rational Expectations Models: Some Recent Developments," CEPR Discussion Papers 15, C.E.P.R. Discussion Papers.
    17. Tetlow, Robert J. & von zur Muehlen, Peter, 2009. "Robustifying learnability," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 296-316, February.
    18. Thomas Lubik & Frank Schorfheide, 2002. "Testing for Indeterminacy in Linear Rational Expectations Models," Computing in Economics and Finance 2002 214, Society for Computational Economics.
    19. Norman, Thomas W.L., 2020. "Market selection with an endogenous state," Journal of Mathematical Economics, Elsevier, vol. 91(C), pages 51-59.
    20. Frank Hespeler, 2008. "Solution Algorithm to a Class of Monetary Rational Equilibrium Macromodels with Optimal Monetary Policy Design," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 207-223, April.

    More about this item

    Keywords

    Identification; Learnability; Limited Information; Indeterminacy; Taylor Rules;
    All these keywords.

    JEL classification:

    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:sur:surrec:1512. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/desuruk.html .

    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: Ioannis Lazopoulos (email available below). General contact details of provider: https://edirc.repec.org/data/desuruk.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.