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Fairness in the use of limited resources during a pandemic

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  • Josef Schosser

Abstract

Capacity limitations are indispensable measures of social distancing in fighting COVID-19 and other pandemics. The paper at hand analyzes these restrictions from the viewpoint of fairness, understood as the possibility of equal access to the scarce resource. To this end, it employs the so-called El Farol Bar problem in conjunction with an adaptive learning approach. Particular emphasis is given to the distribution of information. Our results show that information is, indeed, central to the situation. Policy recommendations are derived.

Suggested Citation

  • Josef Schosser, 2022. "Fairness in the use of limited resources during a pandemic," PLOS ONE, Public Library of Science, vol. 17(6), pages 1-8, June.
  • Handle: RePEc:plo:pone00:0270022
    DOI: 10.1371/journal.pone.0270022
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    References listed on IDEAS

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    1. Anirban Chakraborti & Damien Challet & Arnab Chatterjee & Matteo Marsili & Yi-Cheng Zhang & Bikas K. Chakrabarti, 2013. "Statistical Mechanics of Competitive Resource Allocation using Agent-based Models," Papers 1305.2121, arXiv.org, revised Sep 2014.
    2. Duncan Whitehead, 2008. "The El Farol Bar Problem Revisited: Reinforcement Learning in a Potential Game," Edinburgh School of Economics Discussion Paper Series 186, Edinburgh School of Economics, University of Edinburgh.
    3. Thomson, William, 2003. "Axiomatic and game-theoretic analysis of bankruptcy and taxation problems: a survey," Mathematical Social Sciences, Elsevier, vol. 45(3), pages 249-297, July.
    4. D. Challet & A. Chessa & M. Marsili & Y-C. Zhang, 2001. "From Minority Games to real markets," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 168-176.
    5. Ritmeester, Tim & Meyer-Ortmanns, Hildegard, 2021. "Minority games played by arbitrageurs on the energy market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
    6. Challet, D. & Zhang, Y.-C., 1997. "Emergence of cooperation and organization in an evolutionary game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 407-418.
    7. Shu-Heng Chen & Umberto Gostoli, 2017. "Coordination in the El Farol Bar problem: The role of social preferences and social networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(1), pages 59-93, April.
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    Cited by:

    1. Estevez-Rams, E. & Moya, D. Estévez & Kantz, H., 2026. "Pattern production and community emergence in the minority game," Chaos, Solitons & Fractals, Elsevier, vol. 202(P2).

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