Value of life

The value of life is an economic value used to quantify the benefit of avoiding a fatality. It is also referred to as the cost of life, value of preventing a fatality, implied cost of averting a fatality, and value of a statistical life. In social and political sciences, it is the marginal cost of death prevention in a certain class of circumstances. In many studies the value also includes the quality of life, the expected life time remaining, as well as the earning potential of a given person especially for an after-the-fact payment in a wrongful death claim lawsuit.
As such, it is a statistical term, the value of reducing the average number of deaths by one. It is an important issue in a wide range of disciplines including economics, health care, adoption, political economy, insurance, worker safety, environmental impact assessment, globalization, and process safety.
The motivation for placing a monetary value on life is to enable policy and regulatory analysts to allocate the limited supply of resources, infrastructure, labor, and tax revenue. Estimates for the value of a life are used to compare the life-saving and risk-reduction benefits of new policies, regulations, and projects against a variety of other factors, often using a cost-benefit analysis.
Estimates for the statistical value of life are published and used in practice by various government agencies. In Western countries and other liberal democracies, estimates for the value of a statistical life typically range from –; for example, the United States FEMA estimated the value of a statistical life at in 2020.

Treatment in economics and methods of calculation

There is no standard concept for the value of a specific human life in economics. However, when looking at risk/reward trade-offs that people make with regard to their health, economists often consider the value of a statistical life. The VSL is very different from the value of an actual life. It is the value placed on changes in the likelihood of death, not the price someone would pay to avoid certain death. This is best explained by way of an example. From the EPA's website:

Suppose each person in a sample of 100,000 people were asked how much he or she would be willing to pay for a reduction in their individual risk of dying by 1 in 100,000, or 0.001%, over the next year. Since this reduction in risk would mean that we would expect one fewer death among the sample of 100,000 people over the next year on average, this is sometimes described as "one statistical life saved.” Now suppose that the average response to this hypothetical question was $100. Then the total dollar amount that the group would be willing to pay to save one statistical life in a year would be $100 per person × 100,000 people, or $10 million. This is what is meant by the "value of a statistical life”.

This again emphasizes that VSL is more of an estimate of willingness to pay for small reductions in mortality risks rather than how much a human life is worth. Using government spending to see how much is spent to save lives in order to estimate the average individual VSL is a popular method of calculation. The United States government does not have an official value of life threshold, but different values are used in different agencies. It might be that the government values lives quite highly or that calculation standard are not applied uniformly. Using the EPA as an example, the Agency uses estimates of how much people are willing to pay for small reductions in their risks of dying from adverse health conditions that may be caused by environmental pollution in their cost-benefit analyses.
Economists often estimate the VSL by looking at the risks that people are voluntarily willing to take and how much they must be paid for taking them. This method is known as revealed preference, where the actions of the individual reveal how much they value something. In this context, economists would look at how much individuals are willing to pay for something that reduces their chance of dying. Similarly, compensating differentials, which are the reduced or additional wage payments that are intended to compensate workers for conveniences or downsides of a job, can be used for VSL calculations. For example, a job that is more dangerous for a worker's health might require that the worker be compensated more. The compensating differentials method has several weaknesses. One issue is that the approach assumes that people have information, which is not always available. Another issue is that people may have higher or lower perceptions of risk they are facing that do not equate to actual statistical risk. In general, it is difficult for people to accurately understand and assess risk. It is also hard to control for other aspects of a job or different types of work when using this method. Overall, revealed preference may not represent population preferences as a whole because of the differences between individuals.
One method that can be used to calculate VSL is summing the total present discounted value of lifetime earnings. There are a couple of problems using this method. One potential source of variability is that different discount rates can be used in this calculation, resulting in dissimilar VSL estimates. Another potential issue when using wages to value life is that the calculation does not take into account the value of time that is not spent working, such as vacation or leisure. As a result, VSL estimates may be inaccurate because time spent on leisure could be valued at a higher rate than an individual's wage.
Another method used to estimate VSL is contingent valuation. Contingent valuation asks individuals to value an option either that they have not chosen or are unable to currently choose. Economists might estimate the VSL by simply asking people how much they would be willing to pay for a reduction in the likelihood of dying, perhaps by purchasing safety improvements. These types of studies are referred to as stated preference studies. However, contingent valuation has some flaws. The first problem is known as the isolation of issues, where participants may give different values when asked to value something alone versus when they are asked to value multiple things. The order of how these issues are presented to people matters as well. Another potential issue is the “embedding effect” identified by Diamond and Hausman 1994. All of these methods might result in a VSL that is overstated or understated.
When calculating value of statistical life, it is important to discount and adjust it for inflation and real income growth over the years. An example of a formula needed to adjust the VSL of a specific year is given by the following:
where
VSL_O = Original Base Year, VSL_T = Updated Base Year, P_T = Price Index in Year t, I_T = Real Incomes in Year t, ε = Income Elasticity of VSL.

Value of preventing a casualty

is a more general concept to value of preventing a fatality. It means the value of preventing a fatality or a serious injury. According to Economic and Social Council's provisional agenda for review and analysis of the economic costs of level crossing accidents, ''"the value of preventing a casualty should be established by either Willingness-To-Pay or Human Capital/Lost Output approaches. It is essential to consider not only fatal injuries, but also serious in this statistical life valuation exercise."''

Comparisons to other methods

The value of statistical life estimates are often used in the transport sector and in process safety. In health economics and in the pharmaceutical sector, however, the value of a quality-adjusted life-year is used more often than the VSL. Both of these measures are used in cost-benefit analyses as a method of assigning a monetary value of bettering or worsening one's life conditions. While QALY measures the quality of life ranging from 0–1, VSL monetizes the values using willingness-to-pay.
Researchers have first attempted to monetize QALY in the 1970s, with countless studies being done to standardize values between and within countries. However, as with the QALY, VSL estimates have also had a history of vastly differing ranges of estimates within countries, notwithstanding a standardization among countries. One of the biggest movements to do so was the EuroVaQ project which used a sample of 40,000 individuals to develop the WTP of several European countries.

Policy applications

Value of life estimates are frequently used to estimate the benefits added due to a new policy or act passed by the government. One example is the 6-year retroactive study on the benefits and costs of the 1970 Clean Air Act in the period from 1970 to 1990. This study was commissioned by the U.S. Environmental Protection Agency, Office of Air and Radiation and Office of Policy, Planning and Evaluation, but was carried out by an independent board of public health experts, economists, and scientists headed by Dr. Richard Schmalensee of MIT.
On conducting the benefit-cost analysis, the team measured each dollar value of an environmental benefit by estimating a how many dollars a person is willing to pay in order to decrease or eliminate a current threat to their health, otherwise known as their "willingness-to-pay". The WTP of the U.S. population was estimated and summed for separate categories including mortality, chronic bronchitis, hypertension, IQ changes, and strokes. Thus, the individual WTPs were added to get the value of a statistical life for each category considered in the valuation of the act's benefits. Each valuation in figure 1 was the product of several studies which compiled both solicited WTP information from individuals and WTP estimates from risk compensation demanded in the current labor market and was averaged to find a singular VSL. Such data from the labor market was taken from the Census of Fatal Occupational Injuries collected by the Bureau of Labor Statistics.
For example, the valuation estimates used for mortality were divided by the typical life expectancy of each survey sample in order to get a dollar estimate per life-year lost or saved which was discounted with a 5 percent discount rate.
Using these estimates, the paper concluded that the benefits, ranging from $5.6 to $49.4 trillion in 1990 dollars, of implementing the Clean Air Act from 1970 to 1990 outweighed the economic costs of $523 billion in 1990 dollars.