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Valuing mortality risk in the time of COVID-19

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  • James K. Hammitt

    (Harvard University (Center for Risk Analysis & Center for Health Decision Science)
    University of Toulouse-Capitole)

Abstract

In evaluating the appropriate response to the COVID-19 pandemic, a key parameter is the rate of substitution between wealth and mortality risk, conventionally summarized as the value per statistical life (VSL). For the United States, VSL is estimated as approximately $10 million, which implies the value of preventing 100,000 COVID-19 deaths is $1 trillion. Is this value too large? There are reasons to think so. First, VSL is a marginal rate of substitution and the potential risk reductions are non-marginal. The standard VSL model implies the rate of substitution of wealth for risk reduction is smaller when the risk reduction is larger, but a closed-form solution calibrated to estimates of the income elasticity of VSL shows the rate of decline is modest until the value of a non-marginal risk reduction accounts for a substantial share of income; average individuals are predicted to be willing to spend more than half their income to reduce one-year mortality risk by 1 in 100. Second, mortality risk is concentrated among the elderly, for whom VSL may be smaller and who would benefit from a persistent risk reduction for a shorter period because of their shorter life expectancy. Third, the pandemic and responses to it have caused substantial losses in income that should decrease VSL. In contrast, VSL is plausibly larger for risks (like COVID-19) that are dreaded, uncertain, catastrophic, and ambiguous. These arguments are evaluated and key issues for improving estimates are highlighted.

Suggested Citation

  • James K. Hammitt, 2020. "Valuing mortality risk in the time of COVID-19," Journal of Risk and Uncertainty, Springer, vol. 61(2), pages 129-154, October.
  • Handle: RePEc:kap:jrisku:v:61:y:2020:i:2:d:10.1007_s11166-020-09338-1
    DOI: 10.1007/s11166-020-09338-1
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    3. Patrick Carlin & Brian E. Dixon & Kosali I. Simon & Ryan Sullivan & Coady Wing, 2022. "How Undervalued is the Covid-19 Vaccine? Evidence from Discrete Choice Experiments and VSL Benchmarks," NBER Working Papers 30118, National Bureau of Economic Research, Inc.
    4. W. Kip Viscusi, 2020. "Pricing the global health risks of the COVID-19 pandemic," Journal of Risk and Uncertainty, Springer, vol. 61(2), pages 101-128, October.
    5. Thomas J. Kniesner & W. Kip Viscusi, 2023. "Compensating Differentials for Occupational Health and Safety Risks: Implications of Recent Evidence," Research in Labor Economics, in: 50th Celebratory Volume, volume 50, pages 83-116, Emerald Group Publishing Limited.
    6. Hammitt, James K. & Tuncel, Tuba, 2023. "Monetary values of increasing life expectancy: sensitivity to shifts of the survival curve," TSE Working Papers 23-1416, Toulouse School of Economics (TSE).
    7. Nadia J. Sweis, 2022. "Revisiting the value of a statistical life: an international approach during COVID-19," Risk Management, Palgrave Macmillan, vol. 24(3), pages 259-272, September.
    8. Adler, Matthew, 2020. "What should we spend to save lives in a pandemic? A critique of the value of statistical life," LSE Research Online Documents on Economics 105283, London School of Economics and Political Science, LSE Library.
    9. Caulkins, Jonathan P. & Grass, Dieter & Feichtinger, Gustav & Hartl, Richard F. & Kort, Peter M. & Prskawetz, Alexia & Seidl, Andrea & Wrzaczek, Stefan, 2021. "The optimal lockdown intensity for COVID-19," Journal of Mathematical Economics, Elsevier, vol. 93(C).
    10. Brad R. Humphreys & Gary A. Wagner & John C. Whitehead & Pamela Wicker, "undated". "Willingness to pay for COVID-19 environmental health risk reductions in consumption: Evidence from U.S. professional sports," Working Papers 21-05, Department of Economics, Appalachian State University.
    11. Barro, Robert J., 2022. "Vaccination rates and COVID outcomes across U.S. states," Economics & Human Biology, Elsevier, vol. 47(C).
    12. W. Kip Viscusi, 2021. "Economic lessons for COVID‐19 pandemic policies," Southern Economic Journal, John Wiley & Sons, vol. 87(4), pages 1064-1089, April.
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    More about this item

    Keywords

    Value per statistical life; Pandemic; COVID-19; Age-dependence; Ambiguity aversion; Risk perception;
    All these keywords.

    JEL classification:

    • J17 - Labor and Demographic Economics - - Demographic Economics - - - Value of Life; Foregone Income
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • H42 - Public Economics - - Publicly Provided Goods - - - Publicly Provided Private Goods
    • I10 - Health, Education, and Welfare - - Health - - - General

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