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Agents come to bits: Towards a constructive comprehensive taxonomy of economic entities

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  • Tesfatsion, Leigh

Abstract

This essay is an invited comment on Philip Mirowski's essay titled "Markets Come to Bits: Evolution, Computation, and Markomata in Economic Science," also to appear in JEBO. In his usual brilliant and provocative style, Mirowski argues for a constructive approach to economic modeling centered on the computational representation of markets as integrated sets of algorithms that evolve over time. This essay counters that a broader constructive approach to economic modeling can and should be taken. The recent advent of powerful computer technologies supporting Agent-Based Modeling (ABM) renders feasible the computational study of economies modeled as evolving systems of interacting agents. In ABM, an "agent" refers broadly to bundled data and behavioral methods representing an entity constituting part of a computationally constructed world. Examples of possible agent referents include individuals, social groupings, institutions (e.g., markets), biological entities such as crops, and physical entities such as transportation networks and weather. Consequently, ABM provides tremendous opportunities for economists and other social scientists to tailor the breadth and depth of the entities represented in their models to the application at hand. A simple ABM of a two-sector decentralized market economy is used for concrete illustration. Annotated pointers to related work can be accessed here: http://www2.econ.iastate.edu/tesfatsi/ace.htm
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  • Tesfatsion, Leigh, 2007. "Agents come to bits: Towards a constructive comprehensive taxonomy of economic entities," Journal of Economic Behavior & Organization, Elsevier, vol. 63(2), pages 333-346, June.
    • Handle: RePEc:eee:jeborg:v:63:y:2007:i:2:p:333-346
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    1. Tesfatsion, Leigh, 2006. "Agent-Based Computational Economics: A Constructive Approach to Economic Theory," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 16, pages 831-880, Elsevier.
    2. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    3. Albin, Peter & Foley, Duncan K., 1992. "Decentralized, dispersed exchange without an auctioneer : A simulation study," Journal of Economic Behavior & Organization, Elsevier, vol. 18(1), pages 27-51, June.
    4. Leigh Tesfatsion, 2005. "Agent-Based Computational Laboratories for the Experimental Study of Complex Economic Systems," Computing in Economics and Finance 2005 72, Society for Computational Economics.
    5. Axelrod, Robert & Tesfatsion, Leigh, 2006. "A Guide for Newcomers to Agent-Based Modeling in the Social Sciences," Staff General Research Papers Archive 12515, Iowa State University, Department of Economics.
    6. 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, December.
    7. Epstein, Joshua M., 2006. "Remarks on the Foundations of Agent-Based Generative Social Science," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 34, pages 1585-1604, Elsevier.
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    5. Li, Boyao, 2017. "The impact of the Basel III liquidity coverage ratio on macroeconomic stability: An agent-based approach," Economics Discussion Papers 2017-2, Kiel Institute for the World Economy (IfW Kiel).
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    7. Kumar, Satish & Chavan, Meena & Pandey, Nitesh, 2023. "Journal of International Management: A 25-year review using bibliometric analysis," Journal of International Management, Elsevier, vol. 29(1).
    8. Dan Farhat, 2011. "Bookworms versus Party Animals: An Artificial Labor Market with Human and Social Capital Accumulation," Working Papers 1103, University of Otago, Department of Economics, revised May 2011.

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    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • D - Microeconomics
    • E - Macroeconomics and Monetary Economics

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