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Social Learning about Consumption

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Author Info

  • Isabelle Salle

    (Center for Nonlinear Dynamics in Economics and Finance (CeNDEF)
    Groupe De Recherche en Economie Théorique et Appliquée (GREThA))

  • Pascal Seppecher

    (GREDEG CNRS)

Abstract

This paper applies a social learning model to the optimal consumption rule of Allen & Carroll (2001), and delivers convincing convergence dynamics towards the optimal rule. These findings constitute a significant improvement regarding previous results in the literature, both in terms of speed of convergence and parsimony of the learning model. The learning model exhibits several appealing features: it is frugal, easy to apply to a range of learning objectives, requires few procedures and little information. Particular care is given to behavioural interpretation of the modelling assumptions in light of evidence from the fields of psychology and social science. Our results highlight the need to depart from the genetic metaphor, and account for intentional decision-making, based on agents’ relative performances. By contrast, we show that convergence is strongly hindered by exact imitation processes, or random exploration mechanisms, which are usually assumed when modelling social learning behaviour. Our results suggest a method for modelling bounded rationality, which could be tested most interestingly within the framework of a wide range of economic models with adaptive dynamics.

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File URL: http://www.gredeg.cnrs.fr/working-papers/GREDEG-WP-2013-18.pdf
File Function: Revised version, 2013
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Bibliographic Info

Paper provided by Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), University of Nice Sophia Antipolis in its series GREDEG Working Papers with number 2013-18.

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Length: 37 pages
Date of creation: May 2013
Date of revision: Sep 2013
Handle: RePEc:gre:wpaper:2013-18

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Keywords: learning; bounded rationality; evolutionary algorithms; consumption rule;

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References

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  1. A. Banerjee & Drew Fudenberg, 2010. "Word-of-Mouth Communication and Social Learning," Levine's Working Paper Archive 425, David K. Levine.
  2. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, December.
  3. Murat YILDIZOGLU (GREQAM, CNRS, UMR 6579) & Marc-Alexandre SENEGAS (GREThA, CNRS, UMR 5113) & Isabelle SALLE (GREThA, CNRS, UMR 5113) & Martin ZUMPE (GREThA, CNRS, UMR 5113), 2011. "Learning the optimal buffer-stock consumption rule of Carroll," Cahiers du GREThA 2011-11, Groupe de Recherche en Economie Théorique et Appliquée.
  4. Arifovic, Jasmina, 2000. "Evolutionary Algorithms In Macroeconomic Models," Macroeconomic Dynamics, Cambridge University Press, vol. 4(03), pages 373-414, September.
  5. James Bullard & John Duffy, 1994. "A model of learning and emulation with artificial adaptive agents," Working Papers 1994-014, Federal Reserve Bank of St. Louis.
  6. Allen, Todd W. & Carroll, Christopher D., 2001. "Individual Learning About Consumption," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 255-271, April.
  7. Ulrich Hoffrage & Torsten Reimer, 2004. "Models of Bounded Rationality: The Approach of Fast and Frugal Heuristics," management revue. Socio-economic Studies, Rainer Hampp Verlag, vol. 15(4), pages 437-459.
  8. Ludo Waltman & Nees Eck & Rommert Dekker & Uzay Kaymak, 2011. "Economic modeling using evolutionary algorithms: the effect of a binary encoding of strategies," Journal of Evolutionary Economics, Springer, vol. 21(5), pages 737-756, December.
  9. Allison, G. & Fudenberg, D., 1992. "Rules of Thumb for Social Learning," Working papers 92-12, Massachusetts Institute of Technology (MIT), Department of Economics.
  10. Jasmina Arifovic & James B. Bullard & Olena Kostyshyna, 2007. "Social learning and monetary policy rules," Working Papers 2007-007, Federal Reserve Bank of St. Louis.
  11. Christopher D. Carroll, 1996. "Buffer-Stock Saving and the Life Cycle/Permanent Income Hypothesis," NBER Working Papers 5788, National Bureau of Economic Research, Inc.
  12. Deaton, Angus, 1991. "Saving and Liquidity Constraints," Econometrica, Econometric Society, vol. 59(5), pages 1221-48, September.
  13. Christopher D. Carroll, 2001. "A Theory of the Consumption Function, With and Without Liquidity Constraints (Expanded Version)," NBER Working Papers 8387, National Bureau of Economic Research, Inc.
  14. Binswanger, Johannes, 2011. "Dynamic decision making with feasibility goals: A procedural-rationality approach," Journal of Economic Behavior & Organization, Elsevier, vol. 78(3), pages 219-228, May.
  15. Isabelle SALLE (GREThA, CNRS, UMR 5113) & Martin ZUMPE (GREThA, CNRS, UMR 5113) & Murat YILDIZOGLU (GREThA, CNRS, UMR 5113) & Marc-Alexandre SENEGAS (GREThA, CNRS, UMR 5113), 2012. "Modelling Social Learning in an Agent-Based New Keynesian Macroeconomic Model," Cahiers du GREThA 2012-20, Groupe de Recherche en Economie Théorique et Appliquée.
  16. Judd, Kenneth L., 2006. "Computationally Intensive Analyses in Economics," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 17, pages 881-893 Elsevier.
  17. Dawid, Herbert, 1997. "Learning of equilibria by a population with minimal information," Journal of Economic Behavior & Organization, Elsevier, vol. 32(1), pages 1-18, January.
  18. Harald Uhlig & Martin Lettau, 1999. "Rules of Thumb versus Dynamic Programming," American Economic Review, American Economic Association, vol. 89(1), pages 148-174, March.
  19. Arthur, W Brian, 1991. "Designing Economic Agents that Act Like Human Agents: A Behavioral Approach to Bounded Rationality," American Economic Review, American Economic Association, vol. 81(2), pages 353-59, May.
  20. Sushil Bikhchandani & David Hirshleifer & Ivo Welch, 1998. "Learning from the Behavior of Others: Conformity, Fads, and Informational Cascades," Journal of Economic Perspectives, American Economic Association, vol. 12(3), pages 151-170, Summer.
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