Valuing mortality risk in the time of COVID-19
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Valuing mortality risk in the time of COVID-19 James K. Hammitt 1,2 Accepted: 13 October 2020 / Published online: 11 November 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
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. Keywords Value per statistical life . Pandemic . COVID-19 . Age-dependence . Ambiguity
aversion . Risk perception JEL Classification J17 . Q51 . D61 . D91 . H42 . I10
* James K. Hammitt [email protected]
1
Harvard University (Center for Risk Analysis & Center for Health Decision Science), Cambridge, MA, USA
2
Toulouse School of Economics, University of Toulouse-Capitole, Toulouse, France
130
Journal of Risk and Uncertainty (2020) 61:129–154
1 Introduction As societies try to judge what restrictions on normal activities should be taken to reduce the spread of pandemic SARS-CoV-2, a key parameter is the appropriate tradeoff between wealth or income and mortality risk. The usual approach to quantifying this tradeoff is the value per statistical life (VSL). In the United States, a value of about $10 million is currently used when evaluating government regulations that affect environmental, health, and safety risks (Robinson et al. 2019). Using this value suggests it would be worthwhile for the U.S. population to sacrifice $1 trillion, nearly 5% of U.S. GDP, to reduce the number of U.S. deaths from the pandemic by 100,000. With projections of U.S. deaths from COVID-19 in the absence of any control that have ranged as high as 2.2 million (Ferguson et al. 2020), it is possible that many hundreds of thousands of deaths could be preven
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