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Markets as Artifacts: Aggregate Efficiency from Zero-Intelligence Traders

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  • Shyam Sunder
  • MODELS A

Abstract

The possibility of building a mathematical theory of a system or of simulating that system does not depend on having an adequate microtheory of the natural laws that govern the system components. Such a microtheory might indeed be simply irrelevant. Herbert A. Simon, The Sciences of the Artificial, p. 19. Three phenomena - the disparity between the assumed and observed attributes of economic man, the link between nature and artifacts, and the use of computers as a source of knowledge - fascinated Herbert A. Simon. He built a new paradigm for each field-bounded rationality to deal with the disparity, the science of the artificial as its link to nature, and artificial intelligence for creation of knowledge. In this paper we show that the sciences of the artificial and computer intelligence also hold the key to an understanding of the disparity between individual behavior and market outcomes. When seen as human artifacts, a science of markets need not be built from the science of individual behavior. We outline how, in the nineties, computer simulations enabled us to discover that allocative efficiency - a key characteristic market outcomes - is largely independent of variations in individual behavior under classical conditions. The Sciences of the Artificial suggests such independence and points to its benefits: This skyhook-skyscraper construction of science from the roof down to the yet unconstructed foundations was possible because the behavior of the system at each level depended on only a very approximate, simplified, abstracted characterization of the system at the level next beneath. This is lucky, else the safety of bridges and airplanes might depend on the correctness of the "Eightfold Way" of looking at elementary particles (Simon 1996, p. 16).

Suggested Citation

  • Shyam Sunder & MODELS A, 2002. "Markets as Artifacts: Aggregate Efficiency from Zero-Intelligence Traders," Yale School of Management Working Papers ysm284, Yale School of Management, revised 01 Sep 2004.
    • Handle: RePEc:ysm:somwrk:ysm284
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    References listed on IDEAS

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    Cited by:

    1. Miller, Ross M., 2008. "Don't let your robots grow up to be traders: Artificial intelligence, human intelligence, and asset-market bubbles," Journal of Economic Behavior & Organization, Elsevier, vol. 68(1), pages 153-166, October.
    2. Vernon L. Smith, 2003. "Constructivist and Ecological Rationality in Economics," American Economic Review, American Economic Association, vol. 93(3), pages 465-508, June.
    3. Chen, Shu-Heng, 2012. "Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 1-25.
    4. Gode, Dhananjay (Dan) K. & Sunder, Shyam, 2004. "Double auction dynamics: structural effects of non-binding price controls," Journal of Economic Dynamics and Control, Elsevier, vol. 28(9), pages 1707-1731, July.
    5. Mousavi, Shabnam & Sunder, Shyam, 2023. "Physics, Biology and Human Faculties: A Structural Stepwise Approach to Modeling Human Behavior," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 311-321.
    6. Basu Sudipta & Waymire Gregory B., 2019. "Historical Cost and Conservatism Are Joint Adaptations That Help Identify Opportunity Cost," Accounting, Economics, and Law: A Convivium, De Gruyter, vol. 9(1), pages 1-13, March.
    7. Marco LiCalzi & Paolo Pellizzari, 2006. "The Allocative Effectiveness of Market Protocols Under Intelligent Trading," Lecture Notes in Economics and Mathematical Systems, in: Charlotte Bruun (ed.), Advances in Artificial Economics, chapter 2, pages 17-29, Springer.
    8. Karim Jamal & Michael Maier & Shyam Sunder, 2019. "Aggregation of Diverse Information with Double Auction Trading among Minimally-Intelligent Algorithmic Agents," Cowles Foundation Discussion Papers 2182, Cowles Foundation for Research in Economics, Yale University.
    9. Anush Kapadia, 2017. "The structure of state borrowing: towards a political theory of control mechanisms," Cambridge Journal of Regions, Economy and Society, Cambridge Political Economy Society, vol. 10(1), pages 189-204.
    10. 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.

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