For over 50 years, economists have developed and refined methods to value environmental and other nonmarket goods to provide benefit estimates that are commensurate with goods that are exchanged in markets. Without these estimates, benefit cost analysis of environmental regulations risk erroneous conclusions regarding the net benefits of a regulation. The methods can be broadly categorized into revealed preference (that infer values from behavioral clues) and stated preference (which directly elicit values through surveys). Despite their longer history and the many documented shortcomings, revealed preference methods have not been subject to the intense validity and reliability challenges as their stated preference counterparts. And, unlike stated preference methods (see Johnston et al.2017), there has not previously been an effort for scholars of the approaches to develop a set of “best practice” guidelines for the implementation and reporting of these analyses.

This post is a summary of a paper I’ve written called “What’s in, what’s out? Towards a rigorous definition of the boundaries of benefit-cost analysis,” forthcoming in Economics and Philosophy. Students are typically told that benefit-cost analysis is an application of the potential Pareto criterion, which defines net benefit as the difference between the willingness to pay of winners for their gains from a policy and the willingness to accept of losers for their losses. If the difference is positive, the policy is a potential Pareto improvement, and we say that it generates positive net benefits. Economic philosophers have presented many objections to this definition, but none of these objections refutes the basic logic.

Since electronic cigarettes were introduced, in 2007, they have presented controversial public health tradeoffs. E-cigarettes provide users with the addictive chemical nicotine but without exposing them to the harmful combustion-generated toxicants in cigarette smoke. On the one hand, because smoking combustible cigarettes is estimated to lead to almost 500,000 deaths each year, e-cigarettes have great potential as a harm reduction strategy. In particular, evidence from randomized clinical trials shows that vaping e-cigarettes helps adult smokers quit. On the other hand, the growing popularity of vaping among teens raises concerns about nicotine addiction, the possibility that vaping is a gateway to smoking, and unknown future health consequences. More teens now vape e-cigarettes than smoke cigarettes. In the National Youth Tobacco Survey, the fraction of high school students reporting vaping within the past 30 days increased from 11.7 percent in 2017 to 27.5 percent in 2019, before dropping to 19.6 percent in 2020.  Some public policies – increasing the legal purchase to 21 and banning e-cigarette flavors popular with teens – try to target teen vaping. Other policies, most notably e-cigarette excise taxes, discourage both adult and teen vaping.

Novel threats call us to action. Witness the response to the 9/11 attack and more recently to the coronavirus. Such risks may be particularly compelling if citizens do not understand how to deal with the harm or because of ambiguity around the probability that the threat will be realized. 

What a year it has been. Between the unfolding of a global pandemic and nationwide protests around the topic of police brutality, 2020 has already been a jam-packed year for public policy, and we haven’t even made it into election season.

Being in the SBCA is great because it connects me with so many very smart people who care about public policy and benefit-cost analysis. This value was illustrated by the rapid rate at which the SBCA network began to exchange ideas and estimates about the benefits and costs of interventions to address the COVID-19 situation. As these ideas start to work their way into the more general media, I wanted to share a few observations with readers of On Balance about the challenges facing our community in conducting and interpreting these benefit-cost analyses.

How much impact is your economic appraisal leaving out?” This is the perennial question that CBA practitioners face when putting forward their results of, normally, a poorly performing project. In investment appraisal, my area of work, the question is often decisive. I presume the same applies to CBA practice in policy appraisal.

AS A YOUNG CLINICIAN, I was interested in making a difference; it did not matter how much of a difference, as long as I could claim some patient benefit. And I really didn’t care what benefit: better survival, less local recurrence, shorter hospital stays, fewer narcotics—the specifics did not matter. With retrospective observational studies, it was easy to claim a benefit when I was demonstrating a potential or probable association. I intervened, and the patient improved! If I could prove that claim and make it look scientific with a randomized controlled trial, was I then done?