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Stochastic Learning in Co-ordination Games: a Simulation Approach

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  • Enrico Zaninotto

    ()
    (DISA, Faculty of Economics, Trento University)

  • Alessandro Rossi
  • Loris Gaio

Abstract

In the presence of externalities, consumption behaviour depends on the solution of a co-ordination problem. In our paper we suggest a learning approach to the study of co-ordination in consumption contexts where agents adjust their choices on the basis of the reinforcement (payoff) they receive during the game. The results of simulations allowed us to distinguish the roles of different aspects of learning in enabling co-ordination within a population of agents. Our main results highlight: 1. the role played by the speed of learning in determining failures of the co-ordination process; 2. the effect of forgetting past experiences on the speed of the co-ordination process; 3. the role of experimentation in bringing the process of co-ordination into an efficient equilibrium.

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Bibliographic Info

Paper provided by Department of Computer and Management Sciences, University of Trento, Italy in its series ROCK Working Papers with number 001.

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Length: 27 pages
Date of creation: Jan 1999
Date of revision: 21 May 1999
Handle: RePEc:trt:rockwp:001

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  1. Alessandro Beber, 2001. "Determinants of the implied volatility function on the Italian Stock Market," LEM Papers Series 2001/05, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
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  4. Alessandro Beber, 1999. "Introduzione all'analisi tecnica," Alea Tech Reports 002, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
  5. Narduzzo, Alessandro & Warglien, Massimo, 1996. "Learning from the Experience of Others: An Experiment on Information Contagion," Industrial and Corporate Change, Oxford University Press, vol. 5(1), pages 113-26.
  6. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
  7. Marco Bee, 2001. "Mixture models for VaR and stress testing," Alea Tech Reports 012, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
  8. Alessandro Beber, 1999. "Il dibattito su dignità ed efficacia dell'analisi tecnica nell'economia finanziaria," Alea Tech Reports 003, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
  9. Engle, Robert F. & Manganelli, Simone, 2001. "Value at risk models in finance," Working Paper Series 0075, European Central Bank.
  10. Kaniovski Yuri M. & Young H. Peyton, 1995. "Learning Dynamics in Games with Stochastic Perturbations," Games and Economic Behavior, Elsevier, vol. 11(2), pages 330-363, November.
  11. M.J.B. Hall, 1996. "The amendment to the capital accord to incorporate market risk," Banca Nazionale del Lavoro Quarterly Review, Banca Nazionale del Lavoro, vol. 49(197), pages 271-277.
  12. Ellison, Glenn, 1993. "Learning, Local Interaction, and Coordination," Econometrica, Econometric Society, vol. 61(5), pages 1047-71, September.
  13. Kandori, M. & Mailath, G.J., 1991. "Learning, Mutation, And Long Run Equilibria In Games," Papers 71, Princeton, Woodrow Wilson School - John M. Olin Program.
  14. Flavio Bazzana, 2001. "I modelli interni per la valutazione del rischio di mercato secondo l'approccio del Value at Risk," Alea Tech Reports 011, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
  15. Luca Erzegovesi, 1999. "Capire la volatilità con il modello binomiale," Alea Tech Reports 004, Department of Computer and Management Sciences, University of Trento, Italy, revised 14 Jun 2008.
  16. M.J.B. Hall, 1996. "The amendment to the capital accord to incorporate market risk," BNL Quarterly Review, Banca Nazionale del Lavoro, vol. 49(197), pages 271-277.
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