During pandemics, what economic costs associated with regulation should society tolerate to reduce health risks? Economists usually argue that the answer should be guided by the decisions we observe in labor markets in which individuals accept additional morbidity and mortality risk in return for higher compensation. Coal miners and construction workers, for example, are paid more than others with similar skills because they face higher statistical risk of injury and death on the job. A recent estimate of the Value of a Statistical Life (VSL) is $9 million, which implies that policies that reduce mortality risk are acceptable if the cost per life saved is $9 million or less.
Regulatory economists routinely evaluate health and safety policies in this manner. Some interventions, such as rules mandating that lighters be childproof, only cost $100,000 per statistical life saved and are thus highly cost effective, while OSHA regulations regarding formaldehyde exposure in the workplace cost $78 billion per statistical life saved, more than 1,000 times greater than the VSL estimate.
So are lockdown regulations, such as mandating the closure of non‐essential businesses and issuing stay‐at‐home orders, cost‐effective means of reducing COVID-19 mortality risk, like the childproof lighter regulations, or absurd overkill, like the formaldehyde‐exposure rules? Recent papers use epidemiological models to estimate the number of lives that can be saved through various isolation measures that are less severe than those currently in place for much of the country (7‐day isolation for anyone showing coronavirus symptoms, a 14‐day voluntary quarantine for their entire household, and dramatically reduced social contact for those over 70 years of age). Greenstone and Nigam, for example, conclude that moderate social distancing can save 1.76 million lives through October 1. Using age‐varying estimates of a statistical life (VSL for those under age 9 is $14.7 million while VSL for those over age 79 is $1.5 million), they estimate the benefits of such policies at slightly less than $8 trillion. A constant $9 million VSL, rather than age‐varying estimates, implies benefits of $15.8 trillion.
In 2019 U.S. gross domestic product (GDP) was $21.4 trillion. The benefits from moderate social distancing are thus estimated to range from more than one‐third to more than two‐thirds of a year’s worth of national income.
The apparent implication of the analysis is that a policy‐induced reduction of national income on the order of the Great Depression (between 1929 and 1933, real U.S. GDP fell around 30%) would be efficient if the estimate of lives saved (1.76 million) were correct. And thus the non‐essential business closures mandated by states are cost‐effective because they are unlikely to result in a loss of income as severe as the Great Depression: 8.5 percent of annual GDP if kept in place for just three months.
While we welcome attempts to estimate the relationship between the costs of forced reduction in human interaction and the mortality benefits that result, we believe that policies that deliberately reduce economic output have large costs beyond the lost income. In traditional analyses of health and safety regulation, such as the previously mentioned lighter and formaldehyde rules, the estimates of costs include only compliance costs: the extra material and labor costs involved in complying with the rule. The cost estimates do not include any other reasons that would cause consumers to oppose the regulation, or any broader costs more generally (such as long run, unintended effects of new government policies).
In most traditional health and safety regulatory contexts that omission is probably not empirically important: the airbag container makes the steering wheel less attractive for some people, perhaps, but the effect is tiny. In other traditional regulatory contexts, the omission is more important but ignored: childproof caps on OTC and prescription medicines are annoying for many people and especially difficult for the elderly, but most compliance cost analyses ignore such effects.
In the forced reduction of social interaction during the current pandemic, we think that many costs, beyond just lost income, are important: the cost of missing your last chance to see Grandad before he dies alone, the costs to mental and physical health of isolation, the cost of lost time for single people to meet a partner in the window of life where fertility is possible, the cost of missing travel opportunities, or the cost of acquiring new skills or talents that require exiting the home. In economic terms, these might be dubbed the broader costs of restrictions on our non‐market liberties, or the decline in productivity of our leisure time. If they were monetized and added to any analysis assessing lockdowns, then the cost‐effectiveness of restrictions would be much reduced.
To reiterate, we agree that, during a pandemic, comparing some estimate of the value of lives saved against the full costs of shutdowns is a fruitful analysis. Of course, this only tells us which broad policy is preferable, not “optimal.” It may be that lockdowns are more cost‐effective than doing nothing, but that a range of safety protocols and isolation of vulnerable groups is even more cost‐effective in minimizing the combined economic and health costs of the virus, for example. But our key point is this: a large component of the cost estimate of lockdowns should consist of the monetary value of the loss of freedom to move and interact as we normally do, in addition to the actual lost income from reduced market activity. Thus, the appropriate (cost‐effective) policy‐induced reduction in economic activity would likely be significantly smaller than currently estimated as cost effective by many economists.