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Computational economics

Author

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  • Paola Tubaro

    (University of Greenwich, CNRS - Centre National de la Recherche Scientifique, LRI - Laboratoire de Recherche en Informatique - UP11 - Université Paris-Sud - Paris 11 - CentraleSupélec - CNRS - Centre National de la Recherche Scientifique)

Abstract

Bringing together a collection of leading contributors to this new methodological thinking, the authors explain how it differs from the past and point towards further concerns and future issues. The recent research programs explored include behavioral and experimental economics, neuroeconomics, new welfare theory, happiness and subjective well-being research, geographical economics, complexity and computational economics, agent-based modeling, evolutionary thinking, macroeconomics and Keynesianism after the crisis, and new thinking about the status of the economics profession and the role of the media in economics.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Paola Tubaro, 2011. "Computational economics," Post-Print hal-01372973, HAL.
  • Handle: RePEc:hal:journl:hal-01372973
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    1. Whan-Seon Kim, 2009. "Effects of a Trust Mechanism on Complex Adaptive Supply Networks: An Agent-Based Social Simulation Study," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(3), pages 1-4.
    2. David Hales & Juliette Rouchier & Bruce Edmonds, 2003. "Model-to-Model Analysis," Post-Print halshs-00550488, HAL.
    3. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    4. Arthur, W Brian, 1993. "On Designing Economic Agents That Behave Like Human Agents," Journal of Evolutionary Economics, Springer, vol. 3(1), pages 1-22, February.
    5. Shyam Sunder, 2006. "Determinants of Economic Interaction: Behavior or Structure," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 1(1), pages 21-32, May.
    6. Matteo Richiardi & Roberto Leombruni & Nicole J. Saam & Michele Sonnessa, 2006. "A Common Protocol for Agent-Based Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 9(1), pages 1-15.
    7. Shyam Sunder, 2006. "Economic Theory: Structural Abstraction or Behavioral Reduction?," History of Political Economy, Duke University Press, vol. 38(5), pages 322-342, Supplemen.
    8. Paola Tubaro, 2009. "Is individual rationality essential to market price formation? The contribution of zero-intelligence agent trading models," Journal of Economic Methodology, Taylor & Francis Journals, vol. 16(1), pages 1-19.
    9. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    10. Ron Sun & Isaac Naveh, 2004. "Simulating Organizational Decision-Making Using a Cognitively Realistic Agent Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 7(3), pages 1-5.
    11. 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 353-359, May.
    12. John Kemp, 1999. "Spontaneous Change, Unpredictability and Consumption Externalities: a Dynamic Approach to Consumer Choice," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 2(3), pages 1-1.
    13. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers Archive 10368, Iowa State University, Department of Economics.
    14. Tesfatsion, Leigh S., 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Staff General Research Papers Archive 5075, Iowa State University, Department of Economics.
    15. Mark Pingle & Leigh Tesfatsion, 2004. "Evolution Of Worker-Employer Networks And Behaviors Under Alternative Non-Employment Benefits: An Agent-Based Computational Study," World Scientific Book Chapters, in: Roberto Leombruni & Matteo Richiardi (ed.), Industry And Labor Dynamics The Agent-Based Computational Economics Approach, chapter 8, pages 129-163, World Scientific Publishing Co. Pte. Ltd..
    16. José Manuel Galán & Luis R. Izquierdo & Segismundo S. Izquierdo & José Ignacio Santos & Ricardo del Olmo & Adolfo López-Paredes & Bruce Edmonds, 2009. "Errors and Artefacts in Agent-Based Modelling," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(1), pages 1-1.
    17. John B. Davis & D. Wade Hands (ed.), 2011. "The Elgar Companion to Recent Economic Methodology," Books, Edward Elgar Publishing, number 13684.
    18. Rosaria Conte & Mario Paolucci, 2001. "Intelligent Social Learning," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(1), pages 1-3.
    19. Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
    20. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    21. Juliette Rouchier, 2008. "Agent-Based simulation as a useful tool for the study of markets," Working Papers halshs-00334051, HAL.
    22. Leigh Tesfatsion & Kenneth L. Judd (ed.), 2006. "Handbook of Computational Economics," Handbook of Computational Economics, Elsevier, edition 1, volume 2, number 2.
    23. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011, Elsevier.
    24. David Hales & Juliette Rouchier & Bruce Edmonds, 2003. "Model-To-Model Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(4), pages 1-5.
    25. 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.
    26. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
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