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Humans Against Virus or Humans Against Humans: A Game Theory Approach to the COVID-19 Pandemic

Author

Listed:
  • Santiago Forero-Alvarado
  • Nicolás Moreno-Arias
  • Juan J. Ospina-Tejeiro

Abstract

Externalities and private information are key characteristics of an epidemic like the Covid-19 pan-demic. We study the welfare costs stemming from the incomplete information environment that these characteristics foster. We develop a framework that embeds a game theory approach into a macro SIR model to analyze the role of information in determining the extent of the health-economy trade-o of a pandemic. We apply the model to the Covid-19 epidemic in the US and find that the costs of keeping health information private are between USD 5:9 trillion and USD 6:7 trillion. We then find an optimal policy of disclosure and divulgation that, combined with testing and containment measures, can improve welfare. Since it is private information about individuals' health what produces the greatest welfare losses, finding ways to make such information known as precisely as possible, would result in significantly fewer deaths and significantly higher economic activity. **** RESUMEN: Las presencia de externalidades y de información privada son características esenciales de una pandemia como la de la COVID-19. En este paper estudiamos los costos de bienestar de un ambiente de información incompleta fomentado por estas características. Desarrollamos una estructura analítica que introuduce un enfoque de teoría de juegos a un modelo Macro-SIR para analizar el rol de la información en la determinación del tamaño del trade-off entre economía y salud en una pandemia. Aplicamos el modelo a la pandemia de COVID-19 en EE.UU y encontramos que los costos de mantener privada la información de salud están entre USD 5,9 billones y USD 6,7 billones. Luego encontramos la política óptima de divulgación que, junto con Testeo y Confinamientos, pueden mejorar el bienestar. Debido a que la información privada sobre los estados de salud de los individuos genera las mayores pérdidas de bienestar en la pandemia, elaborar políticas que hagan pública esta información al máximo nivel de desagregación y precisión posible, resultaría en reducciones significativas de las muertes y un desempeño económico significativamente superior.

Suggested Citation

  • Santiago Forero-Alvarado & Nicolás Moreno-Arias & Juan J. Ospina-Tejeiro, 2021. "Humans Against Virus or Humans Against Humans: A Game Theory Approach to the COVID-19 Pandemic," Borradores de Economia 1160, Banco de la Republica de Colombia.
    • Handle: RePEc:bdr:borrec:1160
    DOI: https://doi.org/10.32468/be.1160
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    References listed on IDEAS

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    1. David Argente & Chang-Tai Hsieh & Munseob Lee, 2022. "The Cost of Privacy: Welfare Effects of the Disclosure of COVID-19 Cases," The Review of Economics and Statistics, MIT Press, vol. 104(1), pages 176-186, March.
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    12. Andrew Atkeson, 2020. "What Will be the Economic Impact of COVID-19 in the US? Rough Estimates of Disease Scenarios," Staff Report 595, Federal Reserve Bank of Minneapolis.
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    Cited by:

    1. Juan C. Méndez-Vizcaíno & Nicolás Moreno-Arias, 2021. "A Global Shock with Idiosyncratic Pains: State-Dependent Debt Limits for LATAM during the COVID-19 pandemic," Borradores de Economia 1175, Banco de la Republica de Colombia.

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    More about this item

    Keywords

    COVID-19; epidemic; game theory; information assymetries; macroeconomics; testing; containment policies; disclosure; divulgation; optimal policies; epidemia; teoría de juegos; asimetrías de información; macroeconomía; testeo; políticas de contención; cuarentenas; divulgación; políticas óptimas;
    All these keywords.

    JEL classification:

    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • E1 - Macroeconomics and Monetary Economics - - General Aggregative Models
    • H0 - Public Economics - - General
    • I1 - Health, Education, and Welfare - - Health

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