How to put a value on human life? A policymaker’s dilemma in time of coronavirus
The coronavirus is presenting policymakers with a tradeoff between economic and public health interests: allow people to work, spend and consume; or help people to avoid the coronavirus. Deciding requires placing a value on human life, no matter how repugnant that might seem to those who see every life as priceless. How is such a calculation performed?
There is a well-developed method for valuing human lives. Though the name suggests otherwise, the technique does not involve asking people how much they are willing to pay to avoid certain death, as the most likely response, infinity, would not assist policymakers in navigating difficult tradeoffs.
Instead, it is based on seeing how much people are willing to pay to avoid small increases in their likelihood of death, a number which we know is finite because people behave accordingly every day.
For example, crossing the road might increase your likelihood of a traffic death by 0.001 percent; or eating a steak might increase your likelihood of death by choking by 0.003 percent. The fact that we take actions we know increase our likelihood of death implies that we make choices based on criteria that extend beyond minimizing the likelihood of death. Therefore, it makes sense for policymakers to analogously consider outcomes beyond the number of lives saved.
There are two main techniques. The first is the direct survey, or contingent valuation, method, whereby people are asked to estimate the value that they attach to hypothetical changes in the likelihood of death. For example: “How much would you be willing to pay to have a bus driver who is 0.01 percent less likely to cause a fatal traffic accident?”
Some scientists are uncomfortable with the survey technique, because they think that humans are either poor at hypothetical calculations – it is hard to imagine what 0.01 percent is – or because their responses suffer from tacit bias caused by irrelevant factors such as the tone of voice used by the surveyor, or the weather outside when the survey is conducted.
This is why some scientists prefer the revealed preference method. It involves observing actual choices and determining the implied value of changes in the likelihood of death. For example, more dangerous jobs, such as high-rise window cleaner or bodyguard, command higher wages as compensation for the higher risk employees face. Given knowledge of the increased risk of death, the difference in wage can be used to infer the willingness to pay to avoid an increase in the likelihood of death.
The revealed preference technique also has drawbacks, most notably that it assumes people have common and accurate perceptions regarding the increased likelihood of death associated with certain activities. In practice, we know that people have widely varying beliefs that are often highly inaccurate. In the case of the coronavirus, for example, in the initial stages, egged-on by hysterical media outlets, people were considerably overestimating the likelihood of dying as a result of COVID-19. By supplying accurate information explicitly, the direct survey method can help overcome this drawback.
Once we know how much the average person is willing to pay to avoid a one percent increase in the likelihood of death, we can multiply this number by 100 to estimate how much one life is “worth.” Typical valuations are of the order of $5-to-$10 million per life. Refinements of the technique also yield useful sub-estimates, such as the value of a life when the person is old and therefore only has a few years of life left; or the value of a life when the person has a medical condition that diminishes the quality of life.
Once policymakers are equipped with these numbers, they can start to make explicit tradeoffs. For example, they might estimate that relaxing social distancing will cause 1,000 more deaths, valued at $10 billion, assuming each life is worth $10 million; while also causing a boost to national income equal to $3 billion. In this case, the net effect ($3 billion minus $10 billion) is negative, so the government might choose to maintain social distancing.
While these sorts of calculations might seem callous, the reality is that we have little by way of alternative. Whether it is choosing when to try to rescue hostages, how much funding to allocate to the health sector, or how much to fine people who fail to wear a seatbelt, it is the job of policymakers to explicitly tradeoff the quality versus the quantity of life, and to steer clear of fairytale lands where trite maxims such as “life is precious; no money can compensate society for a death” reign supreme. Or perhaps we should seek guidance in the words of American writer Mark Twain: “The fear of death follows from the fear of life. A man who lives fully is prepared to die at any time.”
Omar Al-Ubaydli (@omareconomics) is a researcher at Derasat, Bahrain