Issues pertaining to the value of life and risks to life are among the most sensitive
and controversial in economics. Much of the controversy stems froma misunderstanding
of what is meant by this terminology. There are two principal value-of-life concepts—
the amount that is optimal fromthe standpointof insurance, and the value needed for
deterrence. These concepts address quite different questions that are pertinent to
promoting different economic objectives.
The insurance value received the greatest attention in the literature until the past
several decades. The basic principle for optimalinsurance purchases is that it is desirable
to continue to transfer incometo the post-accidentstate until the marginal utility of
incomein that state equals the marginal utility of incomewhenhealthy. In the case of
property damage, it is desirable to have the same level ofutility and marginal utility of
incomeafter the accident as before. In contrast, fatalities and serious injuries affect one’s
utility function, decreasing both the level of utility and the marginal utility for any given
level ofincome, making a lower incomelevel after a fatality desirable froman insurance
standpoint. Thus, the value oflife and limb fromthe standpoint of insurance may be
relatively modest.
The second approach to valuing life isthe optimaldeterrence amount. What
value for a fatality sets the appropriate incentives for those avoiding the accident? In the
case of financial losses, the optimal insurance amount, the optimal deterrence amount,
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and the ‘make whole’ amount are identical; however, for severe health outcomes such as
fatalities, the optimal deterrence amount will exceed the optimal level of compensation.
The economic measure for the optimal deterrence amount is the risk-money
tradeoff for very small risks of death. Since the concern is with small probabilities, not
the certaintyof death, these values are referredtoas the valueofstatistical life (VSL).
Economic estimates of the VSL amounts haveincluded evidence frommarket decisions
that revealthe implicit values reflected inbehavior as well as the use of survey
approaches to elicit these money-risk tradeoffsdirectly. Government regulators in turn
have used these VSL estimates to value the benefits associated with risk reduction
policies. Because of the central role of VSL estimates in the economics literature, those
analyses will be the focus here rather than incomereplacement for accident victims.
Valuing Risks to Life
Although economics has devoted substantial attention to issues generally termed
the ‘value of life’, this designation is in many respects a misnomer. What is at issue is
usually not the value oflifeitselfbut rather the value ofsmall risks to life. As Schelling
(1968) observed, the key question is how muchare people willing to pay to prevent a
small risk of death?For small changes in risk, this amount will beapproximately the
sameas the amount of money that they should be compensated to incur such a small risk.
This risk-money tradeoff provides an appropriate measure of deterrence in that it
indicates the individual’sprivate valuation of small changes in the risk. It thus serves as
a measure of the deterrence amount for the value to the individual atrisk of preventing
accidents and as a reference point for the amount the government should spend to prevent
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small statistical risks. Because the concern is with statistical lives, not identified lives,
analyses of government regulations now use these VSL levels to monetize risk reduction
benefits.
Suppose that the amount people are willing to pay to eliminate a risk of death of
1/10,000 is $700. This amount can be converted intoa value of statistical life estimate in
one of two ways. First, consider a group often thousand individuals facing that risk
level. If each of themwerewilling to contribute $700 to eliminate the risk, then one
could raise a total amount to prevent the statistical death equal to ten thousand people
multiplied by$700 per person, or $7 million. An alternative approach to conceptualizing
the risk is to think of the amount that is being paid per unit risk. If we divide the
willingness to pay amount of $700 by the risk probability of one in ten thousand, then
one obtainsthe value perunit risk. The value perstatistical life is $7 million using this
approach as well.
Posing hypothetical interview questions to ascertain the willingness to pay
amount has been a frequent survey technique inthe literature on the value of life. Such
studies are often classified as contingent valuation surveysor stated preference surveys,
in that they seek information regarding respondents’ decisions given hypothetical
scenarios (see Jones-Lee 1989 and Viscusi 1992). Survey evidence is most useful in
addressing issues that cannot be assessed using market data. How, for example, do
people value death fromcancer compared withacute accidental fatalities? Would people
be interested in purchasing pain and suffering compensation, and does such an interest
vary with the nature of the accident? Potentially,survey methods can yield insights into
these issues.