The WALRAS Algorithm: A Convergent Distributed Implementation of General Equilibrium Outcomes

John Q. Cheng and Michael Wellman
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John Q. Cheng: University of Michigan

Computational Economics from University Library of Munich, Germany

Abstract: The WALRAS algorithm calculates competitive equilibria via a distributed tatonnement-like process, in which agents submit single-good demand functions to market-clearing auctions. The algorithm is asynchronous and decentralized with respect to both agents and markets, making it suitable for distributed implementation. We present a formal description of this algorithm, and prove that it converges under the standard assumption of gross substitutability. We relate our results to the literature on general equilibrium stability and some more recent work on decentralized algorithms. We present some experimental results as well, particularly for cases where the assumptions required to guarantee convergence do not hold. Finally, we consider some extensions and generalizations to the WALRAS algorithm.

Keywords: tatonnement; distributed computation; progressive equilibration (search for similar items in EconPapers)
JEL-codes: C8 (search for similar items in EconPapers)
Pages: 23 pages
Date: 1995-08-03
Note: Type of Document - postscript; pages: 23 ; figures: included. Submitted for publication
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Related works:
Journal Article: The WALRAS Algorithm: A Convergent Distributed Implementation of General Equilibrium Outcomes (1998)
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpco:9508001

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