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Social Learning about Consumption

  • Isabelle Salle

    (GREThA - Groupe de Recherche en Economie Théorique et Appliquée - CNRS - Université Montesquieu - Bordeaux 4, CeNDEF - Center for Nonlinear Dynamics in Economics and Finance - Universiteit van Amsterdam)

  • Pascal Seppecher

    ()

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS - UNS - Université Nice Sophia Antipolis)

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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Date of creation: 10 Sep 2013
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Handle: RePEc:hal:wpaper:hal-00989233
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  1. Ellison, Glenn & Fudenberg, Drew, 1993. "Rules of Thumb for Social Learning," Scholarly Articles 3196332, Harvard University Department of Economics.
  2. 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.
  3. 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.
  4. A. Banerjee & Drew Fudenberg, 2010. "Word-of-Mouth Communication and Social Learning," Levine's Working Paper Archive 425, David K. Levine.
  5. Isabelle Salle & Murat Yildizoglu & Martin Zumpe & Marc-Alexandre Sénégas, 2012. "Modelling social learning in an Agent-Based new keynesian macroeconomic model," Post-Print hal-00779045, HAL.
  6. Murat Yildizoglu & Marc-Alexandre Sénégas & Isabelle Salle & Martin Zumpe, 2011. "Learning the optimal buffer-stock consumption rule of Caroll," Post-Print hal-00646314, HAL.
  7. 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.
  8. Jasmina Arifovic & James B. Bullard & Olena Kostyshyna, 2007. "Social learning and monetary policy rules," Working Papers 2007-007, Federal Reserve Bank of St. Louis.
  9. Drew Fudenberg & David K. Levine, 1996. "The Theory of Learning in Games," Levine's Working Paper Archive 624, David K. Levine.
  10. von Hippel, Eric & Franke, Nikolaus & Prügl, Reinhard, 2009. "Pyramiding: Efficient search for rare subjects," Research Policy, Elsevier, vol. 38(9), pages 1397-1406, November.
  11. 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.
  12. Deaton, Angus, 1991. "Saving and Liquidity Constraints," Econometrica, Econometric Society, vol. 59(5), pages 1221-48, September.
  13. Arifovic, Jasmina, 2000. "Evolutionary Algorithms In Macroeconomic Models," Macroeconomic Dynamics, Cambridge University Press, vol. 4(03), pages 373-414, September.
  14. Harald Uhlig & Martin Lettau, 1999. "Rules of Thumb versus Dynamic Programming," American Economic Review, American Economic Association, vol. 89(1), pages 148-174, March.
  15. James B. Bullard & John Duffy, 1994. "A model of learning and emulation with artificial adaptive agents," Working Papers 1994-014, Federal Reserve Bank of St. Louis.
  16. Todd W Allen & Christopher D Carroll, 2001. "Individual Learning About Consumption," Economics Working Paper Archive 444, The Johns Hopkins University,Department of Economics.
  17. 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.
  18. 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.
  19. Vriend, Nicolaas J., 2000. "An illustration of the essential difference between individual and social learning, and its consequences for computational analyses," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 1-19, January.
  20. 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.
  21. Christopher D. Carroll, 1997. "Buffer-Stock Saving and the Life Cycle/Permanent Income Hypothesis," The Quarterly Journal of Economics, Oxford University Press, vol. 112(1), pages 1-55.
  22. 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.
  23. Arifovic, Jasmina, 1995. "Genetic algorithms and inflationary economies," Journal of Monetary Economics, Elsevier, vol. 36(1), pages 219-243, August.
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