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Dynamic Allocation of Objects to Queuing Agents: The Discrete Model

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Abstract

This paper analyzes the optimal allocation of objects which arrive sequentially to agents organized in a waiting list. Applications include the assignment of social housing, deceased donor organs and daycare slots. A mechanism is a probability distribution over all priority orders which are consistent with the waiting list. We consider three efficiency criteria: first order stochastic dominance in the vector of agents' values, the probability of misallocation and the expected waste. We show that the strict seniority order dominates uniform random order according to the two first criteria, and the uniform random order dominates strict priority according to the third criterion. If agents values are perfectly correlated, strict priority dominates all other probabilistic mechanisms for all agents values

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  • Francis Bloch & David Cantala, 2014. "Dynamic Allocation of Objects to Queuing Agents: The Discrete Model," Documents de travail du Centre d'Economie de la Sorbonne 14066, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
  • Handle: RePEc:mse:cesdoc:14066
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    1. Alvin E. Roth & Tayfun Sönmez & M. Utku Ünver, 2004. "Kidney Exchange," The Quarterly Journal of Economics, Oxford University Press, vol. 119(2), pages 457-488.
    2. Francis Bloch & David Cantala, 2013. "Markovian assignment rules," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 40(1), pages 1-25, January.
    3. Xuanming Su & Stefanos A. Zenios, 2005. "Patient Choice in Kidney Allocation: A Sequential Stochastic Assignment Model," Operations Research, INFORMS, vol. 53(3), pages 443-455, June.
    4. Francis Bloch & Nicolas Houy, 2012. "Optimal assignment of durable objects to successive agents," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 51(1), pages 13-33, September.
    5. M. Utku Ünver, 2010. "Dynamic Kidney Exchange," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(1), pages 372-414.
    6. John Kennes Jr. & Daniel Monte Jr. & Norovsambuu Tumennasan Jr., 2014. "The Day Care Assignment: A Dynamic Matching Problem," American Economic Journal: Microeconomics, American Economic Association, vol. 6(4), pages 362-406, November.
    7. Francis Bloch & David Cantala, 2014. "Dynamic Allocation of Objects to Queuing Agents: The Discrete Model," Documents de travail du Centre d'Economie de la Sorbonne 14066, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    8. , & , & ,, 2011. "Revenue maximization in the dynamic knapsack problem," Theoretical Economics, Econometric Society, vol. 6(2), May.
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    Cited by:

    1. Itai Ashlagi & Maximilien Burq & Patrick Jaillet & Vahideh Manshadi, 2019. "On Matching and Thickness in Heterogeneous Dynamic Markets," Operations Research, INFORMS, vol. 67(4), pages 927-949, July.
    2. Francis Bloch & David Cantala, 2014. "Dynamic Allocation of Objects to Queuing Agents: The Discrete Model," Post-Print halshs-01109667, HAL.

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    More about this item

    Keywords

    Dynamic matching; queuing; queuing disciplines; social housing; organ transplant;
    All these keywords.

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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