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Probabilistic assignment: an extension approach

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  • Wonki Jo Cho

    (Korea University)

Abstract

We study the problem of allocating objects using lotteries when agents only submit preferences over objects. A standard approach is to “extend” agents’ preferences over objects to preferences over lotteries, using (first-order) stochastic dominance, or the sd-extension. Following (Cho, Games Econ Behav 95:168–177, 2016a), we complement this approach with two alternative extensions, the dl- and ul- extensions, that give rise to lexicographic preferences (dl stands for “downward lexicographic” and ul for “upward lexicographic”) and apply all three of them in tandem to probabilistic assignment. Each property of rules now has three versions that vary with the extension chosen. We introduce a family of rules that generalizes the probabilistic serial rule. Then we study their behavior, as well as that of the random priority rule, in terms of efficiency, no-envy, and strategy-proofness.

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  • Wonki Jo Cho, 2018. "Probabilistic assignment: an extension approach," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 51(1), pages 137-162, June.
    • Handle: RePEc:spr:sochwe:v:51:y:2018:i:1:d:10.1007_s00355-018-1110-z
    DOI: 10.1007/s00355-018-1110-z
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    Cited by:

    1. Alva, Samson & Manjunath, Vikram, 2020. "The impossibility of strategy-proof, Pareto efficient, and individually rational rules for fractional matching," Games and Economic Behavior, Elsevier, vol. 119(C), pages 15-29.
    2. Liu, Peng & Zeng, Huaxia, 2019. "Random assignments on preference domains with a tier structure," Journal of Mathematical Economics, Elsevier, vol. 84(C), pages 176-194.
    3. Sulagna Dasgupta & Debasis Mishra, 2022. "Ordinal Bayesian incentive compatibility in random assignment model," Review of Economic Design, Springer;Society for Economic Design, vol. 26(4), pages 651-664, December.
    4. Honda, Edward, 2021. "A modified deferred acceptance algorithm for conditionally lexicographic-substitutable preferences," Journal of Mathematical Economics, Elsevier, vol. 94(C).
    5. Tom Demeulemeester & Juan S. Pereyra, 2022. "Rawlsian Assignments," Papers 2207.02930, arXiv.org, revised Sep 2023.
    6. Mennle, Timo & Seuken, Sven, 2021. "Partial strategyproofness: Relaxing strategyproofness for the random assignment problem," Journal of Economic Theory, Elsevier, vol. 191(C).
    7. William Thomson, 2018. "On the terminology of economic design: a critical assessment and some proposals," Review of Economic Design, Springer;Society for Economic Design, vol. 22(1), pages 67-99, June.
    8. Andrew McLennan & Shino Takayama & Yuki Tamura, 2024. "An Efficient, Computationally Tractable School Choice Mechanism," Discussion Papers Series 668, School of Economics, University of Queensland, Australia.
    9. Yoshio Sano & Ping Zhan, 2021. "Extended Random Assignment Mechanisms on a Family of Good Sets," SN Operations Research Forum, Springer, vol. 2(4), pages 1-30, December.

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