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Core Stability and Core Selection in a Decentralized Labor Matching Market

Author

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  • Heinrich H. Nax

    (Department of Humanities, Social and Political Sciences, ETH Zürich, Clausiusstr. 37, Zürich 8092, Switzerland)

  • Bary S. R. Pradelski

    (Department of Humanities, Social and Political Sciences, ETH Zürich, Clausiusstr. 37, Zürich 8092, Switzerland
    Oxford-Man Institute of Quantitative Finance, Walton Well Road, Oxford, OX2 6ED, UK)

Abstract

We propose a dynamic model of decentralized many-to-one matching in the context of a competitive labor market. Through wage offers and wage demands, firms compete over workers and workers compete over jobs. Firms make hire-and-fire decisions dependent on the wages of their own workers and on the alternative workers available on the job market. Workers bargain for better jobs; either individually or collectively as unions, adjusting wage demands upward/downward depending on whether they are currently employed/unemployed. We show that such a process is absorbed into the core with probability one in finite time. Moreover, within the core, allocations are selected that are characterized by surplus splitting according to a bargaining solution such that ( i ) firms and workforce share total revenue according to relative bargaining strengths, and ( i i ) workers receive equal workforce shares above their individual outside options. These results bridge empirical evidence and provide a rich set of testable predictions.

Suggested Citation

  • Heinrich H. Nax & Bary S. R. Pradelski, 2016. "Core Stability and Core Selection in a Decentralized Labor Matching Market," Games, MDPI, vol. 7(2), pages 1-16, March.
  • Handle: RePEc:gam:jgames:v:7:y:2016:i:2:p:10-:d:66888
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    References listed on IDEAS

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    3. Jacob D Leshno & Bary S R Pradelski, 2021. "The importance of memory for price discovery in decentralized markets," Post-Print hal-03100097, HAL.
    4. Bary S. R. Pradelski & Heinrich H. Nax, 2020. "Market sentiments and convergence dynamics in decentralized assignment economies," International Journal of Game Theory, Springer;Game Theory Society, vol. 49(1), pages 275-298, March.
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    7. Arnaud Zlatko Dragicevic, 2022. "Exchange Networks with Stochastic Matching," Games, MDPI, vol. 14(1), pages 1-18, December.
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    More about this item

    Keywords

    cooperative games; core; evolutionary games; matching; generalized Nash bargaining solution; C71; C73; C78; D83;
    All these keywords.

    JEL classification:

    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • 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

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