In evaluating the appropriate response to the covid-19 pandemic, a key parameter is the rate of substitution between mortality risk and wealth or income, 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 the implied value of non-marginal risk reductions decreases slowly until the value accounts for a substantial share of income, after which it decreases sharply; average individuals are predicted to be willing to spend more than half their income to reduce one-year mortality risk by only 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.
value per statistical life; pandemic; age-dependence; ambiguity aversion; risk perception;
TSE Working Paper, n. 20-1115, June 2020