The WALRAS Algorithm: A Convergent Distributed Implementation of General Equilibrium Outcomes
AbstractThe 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.
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Bibliographic InfoPaper provided by EconWPA in its series Computational Economics with number 9508001.
Length: 23 pages
Date of creation: 03 Aug 1995
Date of revision:
Note: Type of Document - postscript; pages: 23 ; figures: included. Submitted for publication
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tatonnement; distributed computation; progressive equilibration;
Other versions of this item:
- Cheng, John Q & Wellman, Michael P, 1998. "The WALRAS Algorithm: A Convergent Distributed Implementation of General Equilibrium Outcomes," Computational Economics, Society for Computational Economics, vol. 12(1), pages 1-24, August.
- C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
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