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Learning Competitive Equilibrium

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Abstract

The epsilon-intelligent competitive equilibrium algorithm is a decentralized alternative to Walras' tatonnement procedure for markets to arrive at competitive equilibrium. We build on the Gode-Spear-Sunder zero-intelligent algorithm in which random generation of bids and offers from agents' welfare-enhancing opportunity sets generates Pareto optimal allocations in a pure exchange economy. We permit agents to know if they are subsidizing others at such allocations, and to veto such allocations, restricting the subsequent iterations of the algorithm only to those trades that are both Pareto-improving and provide strictly greater wealth, and ultimately utility, for such agents. In this simple institution actions of minimally intelligent agents based on local information can lead the market to approximate competitive equilibrium in a larger set of economies than the tatonnement process would allow. This helps address one of the major shortcomings of the Arrow-Debreu-McKenzie model with respect to the instability of tatonnement in an open set of economies. It also addresses the behavioral critique of mathematically derived equilibria for the inability of cognitively-limited humans to maximize. The proof of convergence of the algorithm presented here also provides a way of showing the existence of competitive equilibrium for monotonic, convex exchange economies with heterogeneous agents and many goods without application of a fixed-point theorem.

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Paper provided by Carnegie Mellon University, Tepper School of Business in its series GSIA Working Papers with number 2003-E18.

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Date of creation: Dec 1899
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Handle: RePEc:cmu:gsiawp:-2052381325

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Postal: Tepper School of Business, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213-3890
Web page: http://www.tepper.cmu.edu/

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  1. Anderson, Christopher M. & Plott, Charles R. & Shimomura, K.-I.Ken-Ichi & Granat, Sander, 2004. "Global instability in experimental general equilibrium: the Scarf example," Journal of Economic Theory, Elsevier, vol. 115(2), pages 209-249, April.
  2. Hirota, Masayoshi, 1981. "On the Stability of Competitive Equilibrium and the Patterns of Initial Holdings: An Example," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 22(2), pages 461-67, June.
  3. Feldman, Allan M, 1973. "Bilateral Trading, Processes, Pairwise Optimality, and Pareto Optimality," Review of Economic Studies, Wiley Blackwell, vol. 40(4), pages 463-73, October.
  4. Noussair, C.N. & Plott, C. & Riezman, R., 1995. "An experimental investigation of the patterns of international trade," Open Access publications from Tilburg University urn:nbn:nl:ui:12-387775, Tilburg University.
  5. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70, pages 322.
  6. Sean Crockett, 2008. "Learning competitive equilibrium in laboratory exchange economies," Economic Theory, Springer, vol. 34(1), pages 157-180, January.
  7. Smale, S., 1974. "Global analysis and economics III : Pareto Optima and price equilibria," Journal of Mathematical Economics, Elsevier, vol. 1(2), pages 107-117, August.
  8. Kirman, Alan, 1989. "The Intrinsic Limits of Modern Economic Theory: The Emperor Has No Clothes," Economic Journal, Royal Economic Society, vol. 99(395), pages 126-39, Supplemen.
  9. Arlington W. Williams & John O. Ledyard & Steven Gjerstad & Vernon L. Smith, 2000. "Concurrent trading in two experimental markets with demand interdependence," Economic Theory, Springer, vol. 16(3), pages 511-528.
  10. Hurwicz, Leonid & Radner, Roy & Reiter, Stanley, 1975. "A Stochastic Decentralized Resource Allocation Process: Part II," Econometrica, Econometric Society, vol. 43(3), pages 363-93, May.
  11. Simon, Herbert A, 1978. "Rationality as Process and as Product of Thought," American Economic Review, American Economic Association, vol. 68(2), pages 1-16, May.
  12. 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 119-37, February.
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Cited by:
  1. Jean-Marc Bonnisseau & Orntangar Nguenamadji, 2009. "Discrete Walrasian exchange process," Documents de travail du Centre d'Economie de la Sorbonne 09085, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  2. Marco LiCalzi & Lucia Milone & Paolo Pellizzari, 2008. "Allocative efficiency and traders' protection under zero intelligence behavior," Working Papers 168, Department of Applied Mathematics, Università Ca' Foscari Venezia, revised Nov 2009.
  3. 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.
  4. Paola Tubaro, 2009. "Agent-based Computational Economics: a Methodological Appraisal," EconomiX Working Papers 2009-42, University of Paris West - Nanterre la Défense, EconomiX.
  5. Jacob K. Goeree & Luke Lindsay, 2012. "Stabilizing the economy: Market design and general equilibrium," ECON - Working Papers 092, Department of Economics - University of Zurich.

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