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Main Authors: Eickhoff, Katharina, McCormick, S. Thomas, Peis, Britta, Rieken, Niklas, Koch, Laura Vargas
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2304.14262
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author Eickhoff, Katharina
McCormick, S. Thomas
Peis, Britta
Rieken, Niklas
Koch, Laura Vargas
author_facet Eickhoff, Katharina
McCormick, S. Thomas
Peis, Britta
Rieken, Niklas
Koch, Laura Vargas
contents We consider a market where a set of objects is sold to a set of buyers, each equipped with a valuation function for the objects. The goal of the auctioneer is to determine reasonable prices together with a stable allocation. One definition of "reasonable" and "stable" is a Walrasian equilibrium, which is a tuple consisting of a price vector together with an allocation satisfying the following desirable properties: (i) the allocation is market-clearing in the sense that as much as possible is sold, and (ii) the allocation is stable in the sense that every buyer ends up with an optimal set with respect to the given prices. Moreover, "buyer-optimal" means that the prices are smallest possible among all Walrasian prices. In this paper, we present a combinatorial network flow algorithm to compute buyer-optimal Walrasian prices in a multi-unit matching market with additive valuation functions and buyer demands. The algorithm can be seen as a generalization of the classical housing market auction and mimics the very natural procedure of an ascending auction. We use our structural insights to prove monotonicity of the buyer-optimal Walrasian prices with respect to changes in supply or demand.
format Preprint
id arxiv_https___arxiv_org_abs_2304_14262
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A flow-based ascending auction to compute buyer-optimal Walrasian prices
Eickhoff, Katharina
McCormick, S. Thomas
Peis, Britta
Rieken, Niklas
Koch, Laura Vargas
Computer Science and Game Theory
We consider a market where a set of objects is sold to a set of buyers, each equipped with a valuation function for the objects. The goal of the auctioneer is to determine reasonable prices together with a stable allocation. One definition of "reasonable" and "stable" is a Walrasian equilibrium, which is a tuple consisting of a price vector together with an allocation satisfying the following desirable properties: (i) the allocation is market-clearing in the sense that as much as possible is sold, and (ii) the allocation is stable in the sense that every buyer ends up with an optimal set with respect to the given prices. Moreover, "buyer-optimal" means that the prices are smallest possible among all Walrasian prices. In this paper, we present a combinatorial network flow algorithm to compute buyer-optimal Walrasian prices in a multi-unit matching market with additive valuation functions and buyer demands. The algorithm can be seen as a generalization of the classical housing market auction and mimics the very natural procedure of an ascending auction. We use our structural insights to prove monotonicity of the buyer-optimal Walrasian prices with respect to changes in supply or demand.
title A flow-based ascending auction to compute buyer-optimal Walrasian prices
topic Computer Science and Game Theory
url https://arxiv.org/abs/2304.14262