Skip to main content Accessibility help


  • Isabelle Salle (a1) and Pascal Seppecher (a2)

This paper applies a social learning model to the optimal consumption rule of Allen and Carroll [Macroeconomic Dynamics 5(2001), 255–271] and delivers convincing convergence dynamics toward the optimal rule. These findings constitute a significant improvement over previous results in the literature, in terms of both speed of convergence and parsimony of the learning model. The learning model exhibits several appealing features: it is frugal, is easy to apply to a various range of learning objectives, and requires few procedures and little information. Particular care is given to behavioral interpretation of the modeling 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 modeling social learning behavior. Our results suggest a method for modeling bounded rationality, which could be interestingly tested in a wide range of economic models with adaptive dynamics.

Corresponding author
Address correspondence to: Isabelle Salle, CeNDEF, Amsterdam School of Economics, University of Amsterdam, Roetersstraat 11, NL-1018 WB, Amsterdam, the Netherlands; e-mail:
Hide All
Allen, T.W. and Carroll, C. (2001) Individual learning about consumption. Macroeconomic Dynamics 5, 255271.
Arifovic, J. (2000) Evolutionary algorithms in macroeconomic models. Macroeconomic Dynamics 4, 373414.
Arifovic, Y. (1995) Genetic algorithms and inflationary economies. Journal of Monetary Economics 36 (1), 219243.
Arifovic, Y., Bullard, J., and Kostyshyna, O. (2013) Social learning and monetary policy rules. Economic Journal 123 (567), 3876.
Arthur, W.B. (1991) Designing economic agents that act like human agents: a behavioral approach to bounded rationality. American Economic Review 81 (2), 353359.
Bikhchandani, S., Hirshleifer, D., and Welch, I. (1998) Learning from the behavior of others: Conformity, fads, and informational cascades. Journal of Economic Perspectives 12 (3), 151170.
Binswanger, J. (2011) Dynamic decision making with feasibility goals: A procedural-rationality approach. Journal of Economic Behavior and Organization 78 (3), 219228.
Brown, A.L., Chua, Z.E., and Camerer, C.F. (2009) Learning and visceral temptation in dynamic saving experiments. Quarterly Journal of Economics 124 (1), 197223.
Bullard, J. and Duffy, J. (1998) A model of learning and emulation with artificial adaptive agents. Journal of Economic Dynamics and Control 22 (2), 179207.
Carroll, C. (1997) Buffer stock saving and the life cycle permanent income hypothesis. Quarterly Journal of Economics 112 (1), 156.
Carroll, C. (2001) A theory of the consumption function, with and without liquidity constraints. Journal of Economic Perspectives 15 (3), 2346.
Dawid, H. (1997) Learning of equilibria by a population with minimal information. Journal of Economic Behavior and Organization 32, 118.
Dawid, H. and Hornik, K. (1996) The dynamics of genetic algorithms in interactive environments. Journal of Network and Computer Applications 19, 519.
Deaton, A. (1991) Saving and liquidity constraints. Econometrica 59 (5), 12211248.
Ellison, G. and Fudenberg, D. (1993) Rules of thumb for social learning. Journal of Political Economy 101 (4), 612643.
Ellison, G. and Fudenberg, D. (1995) Word-of-mouth communication and social learning. Quarterly Journal of Economics 110 (1), 93125.
Eshelman, L. and Schaffer, J. (1993) Real-coded genetic algorithms and interval-schemata. In Foundations of Genetic Algorithms 2. San Mateo, CA: Morgan Kaufmann.
Franke, J. (1999) Memory enhanced evolutionary algorithms for changing optimization problems. In Proceedings of the 1999 Congress on Evolutionary Computation, vol. 3.
Friedman, M. (1953) Essays in Positive Economics. Chicago: University of Chicago Press.
Fudenberg, D. and Levine, D. (1998) Theory of Learning in Games. Cambridge, MA: MIT Press.
Gigerenzer, G. and Selten, R. (2001) Bounded Rationality: The Adaptive Toolbox. Cambridge, MA: MIT Press.
Goldberg, D. E. (1989) Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison–Wesley.
Herrera, F., Lozano, M., and Verdegay, J. (1998) Tackling real-coded genetic algorithms: Operators and tools for behavioural analysis. Artificial Intelligence Review 12, 265319.
Hoffrage, U. and Reimer, T. (2004) Models of bounded rationality: The approach of fast and frugal heuristics. International Review of Management Studies 15 (4), 437459.
Holland, J. (1975) Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence. Oxford, UK: University of Michigan Press.
Holland, J., Goldberg, D., and Booker, L. (1989) Classifier systems and genetic algorithms. Artificial Intelligence 40, 235289.
Holland, J. and Miller, J. (1991) Artificial adaptive agents in economic theory. AER Papers and Proceedings 91 (2), 365370.
Howitt, P. and Özak, O. (2013) Adaptive consumption behavior. Journal of Economic Dynamics and Control 39 (C), 3761.
Huguet, P., Dumas, F., Monteil, J.M., and Genestoux, N. (2001) Social comparison choices in the classroom: Further evidence for students' upward comparison tendency and its beneficial impact on performance. European Journal of Social Psychology 31, 557578.
Hutchinson, J.M. and Gigerenzer, G. (2005) Simple heuristics and rules of thumb: Where psychologists and behavioural biologists might meet. Behavioural Processes 69, 97124.
Janetos, A.C. (1980) Strategies of female mate choice: A theoretical analysis. Behavioral Ecological Sociobiology 7, 107112.
Judd, K. (2006) Computationally intensive analyses in economics. In Tesfatsion, L. and Judd, K. (eds.), Handbook of Computational Economics, vol. 2, Chap. 17, pp. 881884. Amsterdam: North-Holland.
Kahneman, D. and Tversky, A. (1996) On the reality of cognitive illusions. Psychological Review 103, 582591.
Lettau, M. and Uhlig, H. (1999) Rules of thumb versus dynamic programming. American Economic Review 89 (1), 148174.
Lux, T. and Schornstein, S. (2005) Genetic learning as an explanation of stylized facts of foreign exchange markets. Journal of Mathematical Economics 41 (1–2), 169196.
Palmer, N. (2012) Learning to Consume: Individual versus Social Learning. Mimeo, George Mason University.
Penrose, E.T. (1952) Biological analogies in the theory of the firm. American Economic Review 42 (5), 804809.
Rubinstein, A. (1998) Modeling Bounded Rationality. Cambridge, MA: MIT Press.
Salle, I., Zumpe, M., Yıldızoğlu, M., and Sénégas, M.-A. (2012) Modelling Social Learning in an Agent-Based New Keynesian Macroeconomic Model. Technical report 2012-20, Cahiers du GREThA, University of Bordeaux.
Salmon, M. (1995) Bounded rationality and learning: Procedural learning. In Kirman, A.P. and Salmon, M. (eds.), Learning and Rationality in Economics, Chap. 8, pp. 236275. Oxford, UK: Basil Blackwell.
Sargent, T. (1993) Bounded Rationality in Macroeconomics. Oxford, UK: Oxford University Press.
Simon, H. (1955) A behavioural model of rational choice. Quarterly Journal of Economics 69, 99118.
Simon, H. (1962) The architecture of complexity. Proceedings of the American Philosophical Society 106, 467481.
Simon, H. (1976) From substantial to procedural rationality. In Latsis, S.J. (ed.), Method and Appraisal in Economics, pp. 129148. Cambridge, UK: Cambridge University Press.
Simon, H. (1978) Rational Decision-Making in Business Organizations. Nobel Memorial Lecture.
Simon, H.A. (1996) The Sciences of the Artificial, 3rd ed. Cambridge, MA: MIT Press.
Suls, J. and Wheeler, L., eds (2000) Handbook of Social Comparison: Theory and Research. Dordrecht, the Netherlands: Kluwer Academic Publishers.
Tversky, A. and Shaar, E. (1982) Choice under conflict: The dynamics of the deferred decision. Psychological Science 3, 358361.
Vallée, T. and Yıldızoğlu, M. (2009) Convergence in the finite Cournot oligopoly with social and individual learning. Journal of Economic Behavior and Organization 72 (2), 670690.
Van den Berg, J. (1955) The Phenomenological Approach to Psychiatry: An Introduction to Recent Phenomenological Psychopathology. Springfield, IL: Thomas.
Von Hippel, E., Franke, N., and Prügl, R. W. (2009) Pyramiding: Efficient search for rare subjects. Research Policy 38 (9), 13971406.
Vriend, N. (2000) An illustration of the essential difference between individual and social learning, and its consequences for computational analyses. Journal of Economic Dynamics and Control 24, 119.
Waltman, L., van Eck, N. J., Dekker, R., and Kaymak, U. (2011) Economic modeling using evolutionary algorithms: The effect of a binary encoding of strategies. Journal of Evolutionary Economics 21, 737756.
Yang, S. (2008) Genetic algorithms with memory- and elitism-based immigrants in dynamic environments. Evolutionary Computation 16 (3), 385416.
Yıldızoğlu, M. (2001) Connecting adaptive behaviour and expectations in models of innovation: The potential role of artificial neural networks. European Journal of Economic and Social Systems 15 (3), 5165.
Yıldızoğlu, M., Sénégas, M.-A., Salle, I., and Zumpe, M. (2014) Learning the optimal buffer-stock consumption rule of Carroll. Macroeconomic Dynamics 18 (4), 727752.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Macroeconomic Dynamics
  • ISSN: 1365-1005
  • EISSN: 1469-8056
  • URL: /core/journals/macroeconomic-dynamics
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed