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Equilibrium Models in EconomicsPurposes and Critical Limitations$
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Lawrence A. Boland

Print publication date: 2017

Print ISBN-13: 9780190274320

Published to Oxford Scholarship Online: May 2017

DOI: 10.1093/acprof:oso/9780190274320.001.0001

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Equilibrium models vs. complexity economics

Equilibrium models vs. complexity economics

Chapter:
(p.159) Chapter 12 Equilibrium models vs. complexity economics
Source:
Equilibrium Models in Economics
Author(s):

Lawrence A. Boland

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780190274320.003.0013

This chapter will critically examine the non-equilibrium-based complexity theory approach to model building. Complexity theory replaces equilibrium-based models with algorithm-based models. Attention will be paid to the work of W. Brian Arthur and the other researchers at the Santa Fe Institute, with a particular assessment of their approach to including knowledge and learning recognition in their alternative to equilibrium models. Topics discussed include complexity economics, technology, increasing returns, diversity, learning, path dependency and evolution. Particular attention is given to the Santa Fe Institutes use of inductive learning to characterize how a market participant acts in the face of incomplete and uncertain information.

Keywords:   complexity economics, Santa Fe Institute, non-equilibrium, inductive learning, path-dependency, diversity of decision makers

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