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Matching in Dynamic Imbalanced Markets

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  • Itai Ashlagi
  • Afshin Nikzad
  • Philipp Strack

Abstract

We study dynamic matching in exchange markets with easy- and hard-to-match agents. A greedy policy, which attempts to match agents upon arrival, ignores the positive externality that waiting agents generate by facilitating future matchings. We prove that this trade-off between a ``thicker'' market and faster matching vanishes in large markets; A greedy policy leads to shorter waiting times, and more agents matched than any other policy. We empirically confirm these findings in data from the National Kidney Registry. Greedy matching achieves as many transplants as commonly-used policies (1.6\% more than monthly-batching), and shorter patient waiting times.

Suggested Citation

  • Itai Ashlagi & Afshin Nikzad & Philipp Strack, 2018. "Matching in Dynamic Imbalanced Markets," Papers 1809.06824, arXiv.org, revised Jun 2019.
    • Handle: RePEc:arx:papers:1809.06824
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    References listed on IDEAS

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    1. Ross Anderson & Itai Ashlagi & David Gamarnik & Yash Kanoria, 2017. "Efficient Dynamic Barter Exchange," Operations Research, INFORMS, vol. 65(6), pages 1446-1459, December.
    2. Nikhil Agarwal & Itai Ashlagi & Eduardo Azevedo & Clayton R. Featherstone & Ömer Karaduman, 2019. "Market Failure in Kidney Exchange," American Economic Review, American Economic Association, vol. 109(11), pages 4026-4070, November.
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    Cited by:

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    2. Yu-Tse Lee & Jhan-Jia Lin & Jane Yung-Jen Hsu & Ja-Ling Wu, 2020. "A Time Bank System Design on the Basis of Hyperledger Fabric Blockchain," Future Internet, MDPI, vol. 12(5), pages 1-16, May.

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