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Published: February 26, 2008

 
 

The Myth of Cost-Benefit Analysis

The U.S. government’s method for evaluating risk isn’t as objective as it’s made out to be.

Illustration by Lars Leetaru

In 2005, the U.S. Environmental Protection Agency announced a new regulation that specified how it would limit mercury emissions from coal-burning power plants. In response to a swell of criticism that the new controls were too lenient, officials declared that the controls could not be any more aggressive because, by the agency’s estimates, the cost to the coal industry — US$750 million a year — far exceeded the public health benefit, which they valued at $50 million per year.

But a Harvard Center for Risk Analysis cost-benefit study on the regulation, paid for that same year by the EPA and coauthored and peer-reviewed by three EPA scientists, had reached a dramatically different conclusion. Its study showed that same $750 million that the coal industry would give up would allow the public to reap a benefit of nearly $5 billion per year, 100 times the EPA’s public estimate, by decreasing the neurological and cardiac damage attributed to mercury poisoning.

What was the source of the discrepancy? The EPA’s cost-benefit analysis had focused on the effects of reducing mercury levels in freshwater fish only, while ignoring the idea that ocean fish might also be affected by coal plant emissions.  But the Harvard report had asserted, with at least enough credibility to merit investigation, that coal emissions could affect mercury levels in tuna and other fish. And, to be sure, most of the fish Americans eat — including tuna, which is responsible for much of the mercury exposure in the U.S. — comes from oceans. The EPA also greatly reduced the cost of cardiac damage in its cost-benefit analysis, declaring that although mercury could indeed damage the heart, the harm might be offset by the cardiac benefits of eating fish.

This example, along with scores like it over the past decades, provides ample evidence that using cost-benefit analysis to determine the value of new regulations isn’t working, and that it’s time to find a better approach. Businesspeople should be particularly eager for such a change, because although many regard cost-benefit analysis almost as a game that can be finessed, “customizing” the numbers can have dangerous consequences. Aside from its obvious implications for exposing businesses and the public to undue risk, it can effectively quash new ventures, or arbitrarily favor some technologies over others.

Cost-benefit analysis has long been extolled as the best method for stripping regulatory decisions of bias and anchoring them with objective, real-world economic consequences. To that end, President Bill Clinton signed a law in 1993 requiring that every regulatory proposal — even those mandated by Congress — undergo at least one cost-benefit analysis before being submitted for approval. This policy assumes that cost-benefit analysis is unbiased, but that is not the case in practice. The flaws of cost-benefit analysis, which has gained momentum over the past 40 years, have become more apparent. Sometimes it gives government agencies or corporations a disproportionate influence over what goes into the analysis and therefore what comes out of it. Other times, it skews the results in unexpected ways simply because of hidden biases or unintentional misapplication of the data. Even when conducted with the best of intentions, the method is still problematic, because it substitutes calculation for informed and considered judgment. Although we need not abandon such analysis altogether, we must recognize how and why it is subject to misuse and abuse.

The main problem with cost-benefit analysis is that it requires translation of all value of a given proposal into economic terms. To proponents, this is its chief asset. Because the cost-benefit approach uses economic value as a universal metric, they say, it is a neutral tool; monetizing risk and benefit is the least biased way to judge the impact of regulatory decisions.

 
 
 
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