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Learning Rational Expectations under Computability Constraints


  • Spear, Stephen E


In this paper, the author considers how boundedly rational agents learn rational expectations when all equilibrium price functions or forecasts of future equilibrium prices are required to be computable. The paper examines two learning environments. In the first, agents have perfect information about the state of nature. In this case, the theory of machine inference can be applied to show that there is a broad class of computable economies whose rational expectations equilibria can be learned by inductive inference. In the second environment, agents do not have perfect information about the state of nature. In this case, a version of Godel's incompleteness theorem implies that rational expectations equilibria cannot be learned. Copyright 1989 by The Econometric Society.

Suggested Citation

  • Spear, Stephen E, 1989. "Learning Rational Expectations under Computability Constraints," Econometrica, Econometric Society, vol. 57(4), pages 889-910, July.
  • Handle: RePEc:ecm:emetrp:v:57:y:1989:i:4:p:889-910

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    References listed on IDEAS

    1. Nelson, Forrest D & Savin, N E, 1990. "The Danger of Extrapolating Asymptotic Local Power," Econometrica, Econometric Society, vol. 58(4), pages 977-981, July.
    2. Killingsworth, Mark R. & Heckman, James J., 1987. "Female labor supply: A survey," Handbook of Labor Economics,in: O. Ashenfelter & R. Layard (ed.), Handbook of Labor Economics, edition 1, volume 1, chapter 2, pages 103-204 Elsevier.
    3. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
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    Cited by:

    1. H. Reiju Mihara, 1997. "Arrow's Theorem and Turing computability," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 10(2), pages 257-276.
    2. Chen Xiaohong & White Halbert, 2002. "Asymptotic Properties of Some Projection-based Robbins-Monro Procedures in a Hilbert Space," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(1), pages 1-55, April.
    3. (Vela) Velupillai, K., 1997. "Expository notes on computability and complexity in (arithmetical) games," Journal of Economic Dynamics and Control, Elsevier, vol. 21(6), pages 955-979, June.
    4. DeCanio, Stephen J. & Watkins, William E., 1998. "Information processing and organizational structure," Journal of Economic Behavior & Organization, Elsevier, vol. 36(3), pages 275-294, August.
    5. STEPHEN J. DeCANIO, 1997. "Economic Modeling And The False Tradeoff Between Environmental Protection And Economic Growth," Contemporary Economic Policy, Western Economic Association International, vol. 15(4), pages 10-27, October.
    6. Anderlini, Luca, 1998. "Forecasting errors and bounded rationality: An example," Mathematical Social Sciences, Elsevier, vol. 36(2), pages 71-90, September.
    7. Blume, Lawrence & Easley, David & Kleinberg, Jon & Kleinberg, Robert & Tardos, √Čva, 2015. "Introduction to computer science and economic theory," Journal of Economic Theory, Elsevier, vol. 156(C), pages 1-13.
    8. Kelly, David L. & Shorish, Jamsheed, 2000. "Stability of Functional Rational Expectations Equilibria," Journal of Economic Theory, Elsevier, vol. 95(2), pages 215-250, December.
    9. Bruno Biais & Pierre Hillion & Chester Spatt, 1999. "Price Discovery and Learning during the Preopening Period in the Paris Bourse," Journal of Political Economy, University of Chicago Press, vol. 107(6), pages 1218-1248, December.
    10. Richter, Marcel K. & Wong, Kam-Chau, 1999. "Computable preference and utility," Journal of Mathematical Economics, Elsevier, vol. 32(3), pages 339-354, November.
    11. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2002. "On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 217-239, October.
    12. Brown, Paul M., 1995. "Learning from experience, reference points, and decision costs," Journal of Economic Behavior & Organization, Elsevier, vol. 27(3), pages 381-399, August.
    13. K. Vela Velupillai, 2008. "The Mathematization of Macroeconomics: A Recursive Revolution," Department of Economics Working Papers 0807, Department of Economics, University of Trento, Italia.
    14. Stephen J. Decanio, 1999. "Estimating The Non-Environmental Consequences Of Greenhouse Gas Reductions Is Harder Than You Think," Contemporary Economic Policy, Western Economic Association International, vol. 17(3), pages 279-295, July.
    15. Ke-Hung Lai & Shu-Heng Chen & Ya-Chi Huang, 2005. "Bounded Rationality and the Elasticity Puzzle: What Can We Learn from the Agent-Based Computational Consumption Capital Asset Pricing Model?," Computing in Economics and Finance 2005 207, Society for Computational Economics.
    16. Stephen Kinsella & David M. Ramsey, 2011. "A Model of Partnership Formation with Friction and Multiple Criteria," Working Papers 201119, Geary Institute, University College Dublin.
    17. H. Reiju Mihara, 1997. "Arrow's Theorem, countably many agents, and more visible invisible dictators," Public Economics 9705001, EconWPA, revised 01 Jun 2004.
    18. K. Vela Velupillai, 2010. "Reflections on Mathematical Economics in the Algorithmic Mode," ASSRU Discussion Papers 1016, ASSRU - Algorithmic Social Science Research Unit.
    19. Anderlini, Luca, 1999. "Communication, Computability, and Common Interest Games," Games and Economic Behavior, Elsevier, vol. 27(1), pages 1-37, April.
    20. Francesco Luna, "undated". "Computable Learning, Neural Networks and Institutions," Computing in Economics and Finance 1996 _037, Society for Computational Economics.
    21. Koye Somefun, 2001. "Posted Offer versus Bargaining: An Example of how Institutions can Facilitate Learning," Computing in Economics and Finance 2001 79, Society for Computational Economics.
    22. Mihara, H. Reiju, 1999. "Arrow's theorem, countably many agents, and more visible invisible dictators1," Journal of Mathematical Economics, Elsevier, vol. 32(3), pages 267-287, November.
    23. Stefano Ficco & Vladimir A. Karamychev, 2004. "Information Overload in Multi-Stage Selection Procedures," Tinbergen Institute Discussion Papers 04-077/1, Tinbergen Institute.

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