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What economic agents do: How cognition and interaction lead to emergence and complexity

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  • Robert Axtell

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Abstract

Kohn (The Cato Journal, 24(3):303–339, 2004) has argued that the neoclassical conception of economics—what he terms the “value paradigm”—has experienced diminishing marginal returns for some time. He suggests a new perspective is emerging—one that gives more import to economic processes and less to end states, one that bases behavior less on axioms and more on laboratory experiments. He calls this the “exchange paradigm”. He further asserts that it is the mathematization of economics that is partially at fault for leading the profession down a methodological path that has become something of a dead end. Here I suggest that the nascent research program Kohn has rightly spotted is better understood as distinct from its precursors because it is intrinsically dynamic, permits agent actions out of equilibrium, and treats such actions as occurring within networks. Analyzing economic processes having these characteristics is mathematically very difficult and I concur with Kohn’s appeal to computational approaches. However, I claim it is so-called multi-agent systems and agent-based models that are the way forward within the “exchange paradigm,” and not the cellular automata (Wolfram, A new kind of science, 2002) that Kohn seems to promote. Agent systems are generalizations of cellular automata and support the natural abstraction of individual economic agents as software agents. Copyright Springer Science+Business Media, LLC 2007

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Bibliographic Info

Article provided by Springer in its journal The Review of Austrian Economics.

Volume (Year): 20 (2007)
Issue (Month): 2 (September)
Pages: 105-122

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Handle: RePEc:kap:revaec:v:20:y:2007:i:2:p:105-122

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Web page: http://www.springerlink.com/link.asp?id=100335

Related research

Keywords: Agent-based modeling; Heterogeneous agents; Self-organizing systems; Emergence; Complexity; B4; D5; D8;

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References

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  15. Meir Kohn, 2004. "Value and Exchange," Cato Journal, Cato Journal, Cato Institute, vol. 24(3), pages 303-339, Fall.
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Citations

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Cited by:
  1. Chad Seagren, 2011. "Examining social processes with agent-based models," The Review of Austrian Economics, Springer, vol. 24(1), pages 1-17, March.
  2. Lengnick, Matthias, 2013. "Agent-based macroeconomics: A baseline model," Journal of Economic Behavior & Organization, Elsevier, vol. 86(C), pages 102-120.
  3. Lengnick, Matthias & Krug, Sebastian & Wohltmann, Hans-Werner, 2012. "Money creation and financial instability: An agent-based credit network approach," Economics Working Papers 2012-15, Christian-Albrechts-University of Kiel, Department of Economics.
  4. Hopfensitz, Astrid & Wranik, Tanja, 2008. "Psychological and environmental determinants of myopic loss aversion," MPRA Paper 9305, University Library of Munich, Germany.
  5. Andrei, Amanda L. & Comer, Kevin & Koehler, Matthew, 2014. "An agent-based model of network effects on tax compliance and evasion," Journal of Economic Psychology, Elsevier, vol. 40(C), pages 119-133.

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