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Matching in the Large: An Experimental Study

Author

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  • Yan Chen

    (School of Information, University of Michigan, 105 South State Street, Ann Arbor, MI 48109-2112)

  • Ming Jiang

    (Antai College of Economics and Management, Shanghai Jiao Tong University. 1954 Huashan Road, Shanghai 200434, China)

  • Onur Kesten

    (Tepper School of Business, Carnegie Mellon University, PA 15213)

  • Stéphane Robin

    (Univ Lyon, CNRS, GATE L-SE UMR 5824, F-69131 Ecully, France)

  • Min Zhu

    (School of Business, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China)

Abstract

Market size has been predicted to play an influential role in a broad class of economic environments. We study the performance of the Boston and the Deferred Acceptance (DA) mechanism in a laboratory where we increase the market size. Our results show that increasing the market size from 4 to 40 students per match increases participant truth-telling under the DA but decreases it under the Boston mechanism, leading to a decrease in efficiency for both mechanisms but no change in the large stability advantage of the DA over the Boston mechanism. We then further increase the market size to 4,000 by introducing robots. When humans play truthful robots (without strategic uncertainty), we find that scale has no effect on best response behavior. However, when humans play empirical robots (with strategic uncertainty), scale increases best responses under both mechanisms, which is likely due to the increase in the precision of subjects’ beliefs about others’ strategies.

Suggested Citation

  • Yan Chen & Ming Jiang & Onur Kesten & Stéphane Robin & Min Zhu, 2017. "Matching in the Large: An Experimental Study," Working Papers 1702, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
  • Handle: RePEc:gat:wpaper:1702
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    2. He, Simin & Wu, Jiabin & Zhang, Hanzhe, 2021. "Experimental and Noncooperative Analyses of Decentralized Matching with Transfers," Working Papers 2021-2, Michigan State University, Department of Economics.
    3. Hakimov, Rustamdjan & Kübler, Dorothea, 2019. "Experiments On Matching Markets: A Survey," Rationality and Competition Discussion Paper Series 153, CRC TRR 190 Rationality and Competition.
    4. Yan Chen & Peter Cramton & John A. List & Axel Ockenfels, 2021. "Market Design, Human Behavior, and Management," Management Science, INFORMS, vol. 67(9), pages 5317-5348, September.
    5. Adam Kapor & Mohit Karnani & Christopher Neilson, 2019. "Negative Externalities of Off Platform Options and the Efficiency of Centralized Assignment Mechanisms," Working Papers 635, Princeton University, Department of Economics, Industrial Relations Section..
    6. Christoph March, 2019. "The Behavioral Economics of Artificial Intelligence: Lessons from Experiments with Computer Players," CESifo Working Paper Series 7926, CESifo.
    7. Hoyer, B. & Stroh-Maraun, N., 2020. "Matching strategies of heterogeneous agents under incomplete information in a university clearinghouse," Games and Economic Behavior, Elsevier, vol. 121(C), pages 453-481.
    8. Chen, Yan & He, YingHua, 2021. "Information acquisition and provision in school choice: An experimental study," Journal of Economic Theory, Elsevier, vol. 197(C).
    9. Hakimov, Rustamdjan & Kübler, Dorothea, 2021. "Experiments on centralized school choice and college admissions: a survey," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 24(2), pages 434-488.
    10. Eric Budish & Judd B. Kessler, 2022. "Can Market Participants Report Their Preferences Accurately (Enough)?," Management Science, INFORMS, vol. 68(2), pages 1107-1130, February.
    11. Daniel Stephenson, 2022. "Assignment feedback in school choice mechanisms," Experimental Economics, Springer;Economic Science Association, vol. 25(5), pages 1467-1491, November.
    12. Chen, Yan & Kesten, Onur, 2019. "Chinese college admissions and school choice reforms: An experimental study," Games and Economic Behavior, Elsevier, vol. 115(C), pages 83-100.
    13. March, Christoph, 2021. "Strategic interactions between humans and artificial intelligence: Lessons from experiments with computer players," Journal of Economic Psychology, Elsevier, vol. 87(C).
    14. Umut Dur & Robert G. Hammond & Thayer Morrill, 2019. "The Secure Boston Mechanism: theory and experiments," Experimental Economics, Springer;Economic Science Association, vol. 22(4), pages 918-953, December.
    15. Wu, Binzhen & Zhong, Xiaohan, 2020. "Matching inequality and strategic behavior under the Boston mechanism: Evidence from China's college admissions," Games and Economic Behavior, Elsevier, vol. 123(C), pages 1-21.
    16. Cho, Wonki Jo & Hafalir, Isa E. & Lim, Wooyoung, 2022. "Tie-breaking and efficiency in the laboratory school choice," Journal of Economic Theory, Elsevier, vol. 205(C).

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    More about this item

    Keywords

    matching; school choice; experiment; scale;
    All these keywords.

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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