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On Matching and Thickness in Heterogeneous Dynamic Markets

Published: 21 July 2016 Publication History

Abstract

We study dynamic matching in an infinite-horizon stochastic networked market, in which some agents are a priori more difficult to match than others. Agents have compatibility-based preferences and can match either bilaterally, or indirectly through chains. We study the effect matching technologies and matching policies have on efficiency in markets with different compositions of hard and easy-to-match agents. First, we analyze myopic matching policies and identify a strong connection between market thickness and the efficiency driven by the matching technology. We show that when "hard-to-match" agents join the market more frequently than "easy-to-match" ones, moving from bilateral matchings to chains significantly increases efficiency. Otherwise, the difference between matching bilaterally or through a chain is negligible. Second, we show that the lack of thickness cannot be compensated by non-myopic matching policies implying that the only way to thicken the market fruitfully is by attracting more agents.

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cover image ACM Conferences
EC '16: Proceedings of the 2016 ACM Conference on Economics and Computation
July 2016
874 pages
ISBN:9781450339360
DOI:10.1145/2940716
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 July 2016

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EC '16
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EC '16: ACM Conference on Economics and Computation
July 24 - 28, 2016
Maastricht, The Netherlands

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EC '16 Paper Acceptance Rate 80 of 242 submissions, 33%;
Overall Acceptance Rate 664 of 2,389 submissions, 28%

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The 25th ACM Conference on Economics and Computation
July 7 - 11, 2025
Stanford , CA , USA

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  • (2022)Matching in Dynamic Imbalanced MarketsThe Review of Economic Studies10.1093/restud/rdac04490:3(1084-1124)Online publication date: 2-Aug-2022
  • (2019)Edge Weighted Online Windowed MatchingProceedings of the 2019 ACM Conference on Economics and Computation10.1145/3328526.3329573(729-742)Online publication date: 17-Jun-2019
  • (2019)Stable SecretariesAlgorithmica10.1007/s00453-019-00569-681:8(3136-3161)Online publication date: 31-Jul-2019
  • (undefined)Matching in Dynamic Imbalanced MarketsSSRN Electronic Journal10.2139/ssrn.3251632

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