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Markovian assignment rules

Author

Listed:
  • Francis Bloch

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • David Cantala

Abstract

We analyze dynamic assignment problems where agents successively receive different objects (positions, offices, etc.). A finite set of n vertically differentiated indivisible objects are assigned to n agents who live n periods. At each period, a new agent enters society, and the oldest agent retires, leaving his object to be reassigned. We define independent assignment rules (where the assignment of an object to an agent is independent of the way other objects are allocated to other agents), efficient assignment rules (where there does not exist another assignment rule with larger expected surplus), and fair assignment rules (where agents experiencing the same circumstances have identical histories in the long run). When agents are homogenous, we characterize efficient, independent and fair rules as generalizations of the seniority rule. When agents draw their types at random, we prove that independence and efficiency are incompatible, and that efficient and fair rules only exist when there are two types of agents. We characterize two simple rules (type-rank and type-seniority) which satisfy both efficiency and fairness criteria in dichotomous settings.

Suggested Citation

  • Francis Bloch & David Cantala, 2013. "Markovian assignment rules," Post-Print hal-01013737, HAL.
  • Handle: RePEc:hal:journl:hal-01013737
    DOI: 10.1007/s00355-011-0566-x
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    Citations

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    Cited by:

    1. John Kennes & Daniel Monte & Norovsambuu Tumennasan, 2015. "Dynamic Matching Markets and the Deferred Acceptance Mechanism," Economics Working Papers 2015-23, Department of Economics and Business Economics, Aarhus University.
    2. 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.
    3. Schummer, James, 2021. "Influencing waiting lists," Journal of Economic Theory, Elsevier, vol. 195(C).
    4. Morimitsu Kurino, 2020. "Credibility, efficiency, and stability: a theory of dynamic matching markets," The Japanese Economic Review, Springer, vol. 71(1), pages 135-165, January.
    5. Xinsheng Xiong & Yong Zhao & Yang Chen, 2017. "A computational approach to the multi-period many-to-one matching with ties," Journal of Combinatorial Optimization, Springer, vol. 33(1), pages 183-201, January.
    6. Francis Bloch & David Cantala, 2017. "Dynamic Assignment of Objects to Queuing Agents," American Economic Journal: Microeconomics, American Economic Association, vol. 9(1), pages 88-122, February.
    7. Matsui, Akihiko & Murakami, Megumi, 2022. "Deferred acceptance algorithm with retrade," Mathematical Social Sciences, Elsevier, vol. 120(C), pages 50-65.
    8. Lawrence M. Ausubel & Thayer Morrill, 2014. "Sequential Kidney Exchange," American Economic Journal: Microeconomics, American Economic Association, vol. 6(3), pages 265-285, August.
    9. Samuel Dooley & John P. Dickerson, 2020. "The Affiliate Matching Problem: On Labor Markets where Firms are Also Interested in the Placement of Previous Workers," Papers 2009.11867, arXiv.org.
    10. Anno, Hidekazu & Kurino, Morimitsu, 2016. "On the operation of multiple matching markets," Games and Economic Behavior, Elsevier, vol. 100(C), pages 166-185.
    11. 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.
    12. ANDERSSON, Tommy & EHLERS, Lars & MARTINELLO, Alessandro, 2018. "Dynamic refugee matching," Cahiers de recherche 2018-16, Universite de Montreal, Departement de sciences economiques.
    13. Pereyra, Juan Sebastián, 2013. "A dynamic school choice model," Games and Economic Behavior, Elsevier, vol. 80(C), pages 100-114.
    14. Morimitsu Kurino, 2014. "House Allocation with Overlapping Generations," American Economic Journal: Microeconomics, American Economic Association, vol. 6(1), pages 258-289, February.
    15. Monte, Daniel & Tumennasan, Norovsambuu, 2015. "Centralized allocation in multiple markets," Journal of Mathematical Economics, Elsevier, vol. 61(C), pages 74-85.
    16. Morimitsu Kurino & Yoshinori Kurokawa, 2024. "Job rotation or specialization? A dynamic matching model analysis," Review of Economic Design, Springer;Society for Economic Design, vol. 28(2), pages 243-273, June.
    17. Kawasaki, Ryo, 2015. "Roth–Postlewaite stability and von Neumann–Morgenstern stability," Journal of Mathematical Economics, Elsevier, vol. 58(C), pages 1-6.

    More about this item

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D73 - Microeconomics - - Analysis of Collective Decision-Making - - - Bureaucracy; Administrative Processes in Public Organizations; Corruption
    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions

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