The Value of Statistical Life: Tradeoffs between the Cure and the Problem Itself

Catherine Kaufman is a staff writer for Brief Policy Perspectives and a second-year MPA student.

Back in March, President Donald Trump tweeted, “WE  CANNOT LET THE CURE BE WORSE THAN THE PROBLEM ITSELF,” referring to shutdowns amid the coronavirus outbreaks across the country in a sentiment that has often been repeated. The economic costs of shutdowns are, of course, astronomical—but policymakers have to decide whether these costs are worth reducing the risk of death for millions of citizens. These calculations are based on science and projections that are constantly evolving, but the underlying question remains the same: how do policymakers make that tradeoff, and at what point will “the cure” no longer be deemed necessary?  

Policymakers always have to weigh risk with reward when making decisions, not just during a pandemic. And sometimes those decisions come down to tradeoffs between economic costs and the risk to human safety and even lives. They may need to decide, for example, to lower a speed limit to reduce pedestrian deaths (even though that could mean increased traffic and slower commutes) or to mandate that cars must be manufactured with a seat belt, which could save lives but add significant costs for manufacturers. 

During a pandemic, these decisions are brought into stark focus. Is reopening schools worth risking the lives of students, teachers, and the broader community in order to provide valuable education and extracurricular programs? Is allowing restaurants to seat customers indoors or allowing theaters to show movies worth risking the spread of a deadly disease in order to keep businesses afloat? These questions are often painted as black and white, yes or no, but there is often much more nuance to the decision. Policymakers must decide a point at which it is safe enough to reopen—i.e., when the number of people who may die (or fall seriously ill) is low enough to make reopening (in whatever form that may take) worth the cost.

This decision seems macabre, but it is a necessary one that is made every day. And a simple way to compare costs and benefits is to assign monetary value to each side—which, in this case, means assigning a value to human life in order to compare it to the value of social or economic benefit. One way agencies can make this calculation is by using the value of statistical life (VSL), which is assessed across agencies to make public safety regulations throughout the country.  

What Is VSL?

In 1968, economist Thomas Schelling coined the phrase “value of statistical life.” Before this groundbreaking insight, economists and policymakers assessed benefit-costs analyses involving lives saved through two methods: the human capital approach, which used an individual’s wages to calculate the value of their life (or the cost of their death), and the social value approach, which used the policymakers’ own social values to determine how much a life was worth. The first clearly raises ethical issues, and the second is cyclical and not the most helpful when making policy decisions. 

Schelling changed how this value was calculated by pointing out that policymakers could instead think about individuals’ willingness to trade money for incremental risk. For example, from a single person’s perspective, a policy that could save three lives per one million people only reduces their individual risk of death by .0003%. This rhetorical distinction is important, because it shifts the conversation from the value of life to the value of reducing risk.

In the 1980s, economist W. Kip Viscusi pointed out individuals already demonstrate their own VSL calculation when they take on hazardous jobs. The extra pay they take on to do these jobs, according to Viscusi, is the money-risk tradeoff that they are willing to take, thus signaling to policymakers how much a statistical life should be worth. Extrapolating based on the hazard pay that companies have to give employees to convince them to work risky jobs, Viscusi currently estimates the statistical value of life to be about $10 million, which is the value that federal agencies use when making policy tradeoff decisions. 

Of course, this calculation is not without its critics—analysts debate how valuable VSL really is and how it should be used by regulatory bodies, including whether VSL should be adjusted based on age or other factors. Most federal agencies do not adjust VSL for age, though the Department of Health and Human Services (HHS) is a notable exception. These uncertainties about how VSL should be calculated play heavily in various COVID-19 policy decisions. 

How COVID-19 Policies Take VSL into Account

On November 2, 2020, Viscusi published an article entitled “Pricing the Global Health Risks of the COVID-19 Pandemic,” in which he laid out the mortality costs of the disease. He estimates that, through July 2020, the total global morbidity cost is $3.5 trillion, with the U.S. accounting for 41% of these costs (but only 25% of cases). He raises the equity concerns of lowering the VSL based on shorter life expectancy or lower income, as well as the question of how health problems arising from COVID-19 that do not result in death should be valued. Economist James K. Hammit similarly discusses the various ways that VSL should be calculated in the context of COVID-19, pointing out that VSL may be too high during these times for reasons including the higher age of most individuals who die from COVID-19 and the overall decrease in individuals’ incomes. However, he also posits that the higher uncertainty and ambiguity surrounding COVID-19 could justify a higher VSL. 

Viscusi and Hammit, of course, are not the only economists or analysts making these calculations. Countless studies have been released describing the benefit-cost analyses of various COVID-19 policies, such as stay-at-home order and mask mandates, and many rely on VSL calculations such as those conceived by Viscusi and Hammit. These analyses and calculations can be extremely helpful especially to those in decision-making positions at state and local levels, where experience in risk-regulation runs thin. Because most decision-making during COVID-19 has been left to these levels of government, including school superintendents and county health boards, having a simple tool at their disposal when making these types of decisions can be invaluable, though oversimplification of this problem should be avoided. After all, there are plenty of uncertainties and risks of COVID-19 that go beyond what a VSL can capture.

COVID-19 has forced policymakers to make difficult tradeoffs between health and finances. Failing to reduce widespread health costs will have a financial cost, as will shutdown policies aimed at slowing the spread of the disease. The two are not mutually exclusive, as both will have impacts on the other. The balance between economic or financial costs and health costs, then, are difficult to determine, but, with so much at stake, both sides of the tradeoff must be calculated in order to make an informed, rational decision.

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