Analysts debate how agencies should measure the benefits of reducing mortality.
Regulatory agencies often must make life-or-death decisions. In the process, those decisions can also have other consequences. To help make sound decisions about the inevitable tradeoffs in regulations that save lives, regulators often rely on benefit-cost analysis. But how much value should be placed on the statistically estimated human lives that will be saved by a regulation? For decades, the answer to that question has been to apply a monetized estimate known as the “value of a statistical life”—or VSL, for short.
Earlier this year, The Regulatory Review published an opinion piece by James Broughel of the Mercatus Center at George Mason University, entitled “Rethinking the Value of a Statistical Life.” After Broughel’s essay appeared in The Review, we received a response from W. Kip Viscusi of Vanderbilt University, the author of Pricing Lives: Guideposts for a Safer Society and numerous other publications on benefit-cost analysis. In accordance with The Review’s standard editorial practice when publishing a response to one of our author’s works, we allowed Broughel to respond. Then, to give our readers further value, we allowed Viscusi and Broughel to engage in a short exchange with each other, giving Broughel the customary last word—at least in this series.
Rethinking the Value of a Statistical Life
February 10, 2020 | James Broughel, Mercatus Center
The value of a statistical life, a popular way to quantify the benefits of mortality risk reduction in cost-benefit analysis, has fundamental and often overlooked flaws that make many of its uses questionable.
Failing to Think Properly About the Value of a Statistical Life
March 16, 2020 | W. Kip Viscusi, Vanderbilt University
James Broughel’s essay, “Rethinking the Value of a Statistical Life,” does not rethink the valuation of mortality risks in any meaningful way. Use of the value of a statistical life to monetize the benefits of mortality risk reductions has been the mainstream economic technique for valuing mortality risks for several decades.
The Myopic Short-Termism of the Value of a Statistical Life
March 17, 2020 | James Broughel, Mercatus Center
The preferences of future generations matter as much as our own. When resources are exhausted in wasteful ways, it may well be in line with present preferences. But in exchange for this ephemeral gain, there is an unseen future cost to consider as well.
The Long-Term Value of the Value of a Statistical Life
March 17, 2020 | W. Kip Viscusi, Vanderbilt University
If basing the valuation of mortality risks on the value of a statistical life leads to benefit estimates that are too high, then all market decisions that are used to estimate the value of a statistical life are also flawed. In effect, we are supposedly living in a world of rampant market failure in which people place too great a value on safety. Should we also override all private decisions that have led to the risk-money tradeoff rates used in estimating the value of a statistical life?
Putting the Horse Before the Cart in Cost-Benefit Analysis
March 17, 2020 | James Broughel, Mercatus Center
The value of a statistical life is based on an assumption that marginal willingness-to-pay values observed in the marketplace are efficient. That assumption is untenable; although consumers and workers may optimize their own utility across their lifetimes, they are not optimizing utility across generations.
Efficient Risk Regulations Do Not Increase Risks
March 17, 2020 | W. Kip Viscusi, Vanderbilt University
Policies that pass a benefit-cost test based on the value of a statistical life on balance will both enhance safety and promote economic efficiency.
The Value of a Statistical Life is Not Efficient
March 17, 2020 | James Broughel, Mercatus Center
The value of a statistical life treats compounding investment returns as equivalent to fleeting consumption. As such, reliance on it will often lead to excessive risk reduction in the present.
