Recently, economists and other policy analysts have called for the use of benefit-cost analysis to assess existing and proposed public policies to address the novel coronavirus pandemic, the incidence of COVID-19, and the deaths that may follow. These calls for a benefit-cost perspective have unfortunately generated both confusion and controversy; and – most important – are unlikely to be persuasive to key decision makers. But ignoring economics when considering alternative policy responses to the pandemic would be a mistake.
Fortunately, a different type of economic analysis is available, which is much more likely to be acceptable to policy makers, and would enable government authorities to identify policy instruments that minimize costs to achieve given objectives. I’m referring to cost-effectiveness analysis, which differs in important ways from the benefit-cost analysis now being recommended by my fellow economists, as well as others.
First, I should note that in principle, sensible arguments can and have been made in favor of the use of benefit-cost analysis. I endorse the use of such analysis to assess the wisdom (efficiency) of a wide range of government policies (through what is known as Regulatory Impact Analysis in the U.S. government), and I have been teaching these methods, under the rubric of “net present value analysis,” in my environmental economics course at Harvard for some 30 years. This type of analysis facilitates the identification of efficient policies that generate the greatest net benefits, that is, benefits minus costs.
So, to be perfectly clear, I enthusiastically endorse the work being carried out by economists and others to execute such benefit-cost analyses of COVID-19 policies. My concern, however, is that in the current context, policy makers are likely to be highly resistant to embracing this type of analysis for assessing existing and potential pandemic responses. Rather than throwing out the (economic analysis) baby with the (benefit-cost) bath water, I am suggesting that other forms of economic analysis — namely cost-effectiveness analysis — can be useful, and the results of such analysis should be seriously considered by policy makers.
The problem is that executing benefit-cost analysis requires evaluating not only the costs, but also the benefits of policies in economic terms. In the COVID-19 context, that is difficult enough on the cost side because of the great uncertainties involved, but at least those costs – largely the loss of GDP due to slowdown in economic activity – are fundamentally financial.
The benefit side – primarily the reduced risk of mortality – requires estimates of the value of a statistical life (VSL), which typically draw upon empirical evidence from markets in which people receive higher wages for taking on more risky jobs (in sectors such as mining, forestry, and commercial fishing). The concept and use of VSL – estimated by the U.S. Environmental Protection Agency to be about $10 million per life saved – is well accepted by economists, but is highly controversial among nearly everyone else.
For these reasons, politicians are reluctant, to say the least, to adopt the benefit-cost paradigm to help them formulate better policies to address the current pandemic. But much of the confusion and nearly all of the controversy could be avoided by employing cost-effectiveness analysis, in which economics is brought to bear only on the cost-side of an issue.
I need not tell readers of this blog that this is an approach that is frequently employed in the environmental realm to examine alternative policies that would bring about a given degree of environmental benefits, that is, a given reduction in environmental damages. For example, in the case of carbon dioxide (CO2) emissions, a variety of analyses have found that cost-effective approaches would cost just 25% of what the costs would be with some other approaches.
In the current, COVID-19 context, take some policy objective as given (presumably not a reckless one such as reopening “large sections of the country” by Easter Sunday with “packed churches,” as President Trump had recently promised). Rather, a policy objective to be used in such analysis might be a specified maximum mortality number, a specified mortality risk reduction, or – more simply – a specified case transmission rate. Then, the economic costs of achieving that objective by using various alternative policy instruments can be estimated and compared. At a minimum, these policy instruments would include – among others – the current approach of social distancing of nearly the entire population to suppress the curve of new incidence; and a targeted approach to reduce transmission – more testing, more contact tracing, and more and better facilities for those who need to be separated from others or treated.
For example, one recent study estimated that the current practice of widespread social distancing may be expected to save some 1.2 million lives at an economic cost of $6.8 trillion. Without resorting to trying to value human lives, the question is “simply” how much would it cost with an alternative, more targeted policy to save a similar number of lives?
By the way, the uncertainty that plagues various aspects of these and other policy approaches can be taken into account in the cost-effectiveness calculations. Likewise, constraints – whether physical (such as limited availability of ventilators or cotton swabs), economic, institutional, or political – can all be included in the analysis. In my work as an environmental economist (focused on climate change policies), we do this regularly. My professional cousins – health economists, principally in schools of public health – are equally or more familiar with these approaches, and are well equipped to make the cost comparisons.
In this way, without the confusion and controversy that arises with trying to quantify the economic benefits of mortality risk reduction, economic analysis can still play an exceptionally important role by identifying policies through cost-effectiveness analysis that can help achieve sensible objectives with as little sacrifice as possible of the many other things we value.
