Economic management in Australia has effectively been outsourced to health experts. Political and business leaders are deferring exclusively to public health advice about how to contain the COVID-19 virus with no serious public discussion of the economic costs.
On the 26th of March, the Associated Press reported that, "Gov. Andrew Cuomo of New York has said that if all of his sweeping, expensive measures to stem the coronavirus saved one life, it would be worth it." This surely must be hyperbole, but he has also said, "We’re not going to accept a premise that human life is disposable… And we’re not going to put a dollar figure on human life." At the same time, it seems that there is an increasing call in public discourse for a sensible weighing of the pros and cons of "lockdown" measures, which I suspect anyone reading this blog would agree is a necessary component of good decision making. If Cuomo's sentiment about the value of life is shared among decision makers and the public, how do we get our benefit-cost message across in an effective way, that can actually improve the quality of public decision making, at this particular moment, in this particular context?
The U.S. Environmental Protection Agency (EPA) has a long history of providing comprehensive guidance for conducting economic analyses, including benefit-cost analyses for environmental regulations. Much of that guidance is distilled in the EPA’s Guidelines for Preparing Economic Analyses, which was first released in 1983. The Guidelines are a mix of theory, empirical evidence, and practical recommendations and directives for ensuring the agency is providing the best available economic science for policy makers to consider when making decisions about regulatory actions.
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.
Currently, e-cigarette supporters and opponents are passionately debating what regulations to impose on the products, if any. These debates have been playing out in legislative chambers across the United States, ranging from city halls to Congress, and in federal agencies including the Food and Drug Administration (FDA). Proponents who argue for no or little regulation maintain that e-cigarettes save lives by helping people quit smoking. Opponents, meanwhile, argue that e-cigarettes themselves are addicting teenagers to nicotine.
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?
Outer space probes, radio telescopes, large particle accelerators, genomic platforms, and similar entities are fascinating focal points of intellectual curiosity and discovery. While we marvel at what we learn from them, we can be taken aback by their costs. The $150 billion cost for the International Space Station has been shared by taxpayers in the United States, Europe, Russia, Japan, and Canada. The Large Hadron Collider near Geneva, Switzerland that enabled the 2012 discovery of the elusive Higgs Boson is estimated to cost about 13.5 billion Euros over the 1993-2025 period for taxpayers in the participating countries. According to a recent article in The Economist, proposals are being made to build new infrastructures: A Future Circular Collider in Switzerland, an International Linear Collider in Japan, and a Circular Electron-Position Collider in China. Such are the topic of Massimo Florio’s book, Investing in Science: Social Cost-Benefit Analysis of Research Infrastructures. In it, he demonstrates that benefit-cost analysis (BCA) can be useful in answering the question: Are these costly research infrastructures worth it? He draws upon his substantial experience to adapt the traditional framework to the specific characteristics of research infrastructure (RI). He identifies elements common to RIs, describes how they can be measured and valued, and gives examples from work that he and others have done. This pioneering book fills a gap in that such large-scale investments in science only infrequently have been evaluated using BCA.
Sometimes conferences actually do stimulate research that otherwise might not be done. Six years ago, I was enjoying a breakfast conversation at the SBCA annual research conference with our immediate past president, Clark Nardinelli. At that time, he was overseeing the Regulatory Impact Analysis (RIA) of Federal Drug Administration (FDA) rules implementing the Food Safety Modernization Act, which included provisions to reduce the risks posed to people and pets from adulterated pet food. He complained that, unlike the case of human mortality risks, he had no sound basis for monetizing changes in mortality risks for dogs and other pets. As dogs do not freely make tradeoffs between risks and wages in labor markets, I suggested that finding a value of statistical dog life would likely require a contingent valuation study. Would his unit provide the approximately $50 thousand dollars needed to do the contingent valuation survey? Unfortunately, he had nothing but praise for the suggestion.
So, you've done this great research, had this novel idea, attended a phenomenal event, or read a paradigm-shifting book, and you want to enlighten everyone in the benefit-cost analysis community. Yes, we absolutely want your blog at the Society for Benefit-Cost Analysis.
This post describes a new article forthcoming in the Journal of Benefic Cost Analysis, “When Benefit-Cost Analysis Becomes Optional: Regulatory Analysis at the Consumer Product Safety Commission in the CPSIA Era.” The article describes a familiar scenario for practitioners of regulatory benefit cost analysis: a high impact event followed by swift and forceful congressional action. In the Consumer Product Safety Commission (CPSC) case, the high impact event was a series of product recalls involving toys contaminated with lead. Congress’s response was to pass the Consumer Product Safety Improvement Act (CPSIA) and require several rulemakings.
Applying benefit-cost analysis to homeland security regulations and related applications is difficult, in part due to issues in measuring security or risk avoided (Roberts, 2019; Farrow and Shapiro, 2009). The Office of University Programs within the Department of Homeland Security (DHS) asked our team of benefit-cost, decision, and risk analysts to evaluate changes in their security practices based on DHS funded research and development (R&D) projects over the last 15 years. Initial results have been published in von Winterfeldt, et al. (2019) with additional submissions planned for peer reviewed journals.
Policymakers are called to act in the present to protect the public against future risks while operating under the constraints of doing so in an economically efficient yet effective manner. Unfortunately, these risks tend to present the most difficulty for traditional analytical tools in support of policymaking. This post describes a recently published article, “Dynamic Benefit-Cost Analysis for Uncertain Futures,” co-authored with Susan E. Dudley, Brian F. Mannix, and Christopher Carrigan as part of the open access Symposium on Analysis for Uncertain Futures in the Journal of Benefit Cost Analysis. The article explores the challenges “uncertain futures” pose for analytical tools to satisfactorily support policymaking and proposes the use of “dynamic benefit-cost analysis” frameworks as a necessary approach to address these challenges.
Professor Martin Weitzman passed away unexpectedly at the end of August 2019. A substantial number of accounts of his many contributions to economics in general and environmental economics in particular are available, and collectively provide a good overview of his contributions and influence on the profession (see links at the end of this post). In this short note, I want to highlight some aspects of his works that are relevant for applied welfare economics in general and cost-benefit analysis in particular. I single out two stellar contributions that opened up new vistas for research and enriched the literature on welfare measurement.
The National Center for Children in Poverty reports that 21% of American children are living in poverty, including 46% of African American and 40% of Latino children. Compared to non-poor children, on average impoverished children are 15.6% less likely to graduate high school and 37% more likely to be unemployed as adults.
Research has documented that high-quality early childhood education boosts the skills of disadvantaged children in the short-term. However, a recent series of articles finds that comprehensive early childhood education programs have positive long-term impacts on earnings, criminal activity, and health. Such programs remediate socioeconomic inequality by improving the economic prospects of their participants. While the boost in cognitive skills eventually fades away, the boost in non-cognitive skills persists over the life cycle.
Over four decades ago I struggled through my first year of graduate school in economics, a struggle made palatable by the extraordinary professor who taught my first economics course. Deirdre McCloskey was (and is) smart, fun, and eccentric, and she enthusiastically led us through our first pass at economics. Part of that passage included learning to write, for McCloskey held – a notion considered eccentric – that economists should write well. Although good writing remains suspect among economists, Deirdre McCloskey taught me long ago that good writing makes for good economics.
In the following interview I asked Richard Zeckhauser to recount what it was like to be part of the “Whiz Kids,” the name given to a group of experts with which Robert McNamara (then Secretary of Defense and later President of the World Bank) surrounded himself in order to turn around the management of the United States Department of Defense in the 1960s. The group sought to shape government decision making by bringing in economic analysis, operations research, game theory, and computing, as well as by implementing new methods, such as Planning Programming Budgeting System (PPBS). Their efforts did a lot to extend and solidify the influence of the principles of benefit cost analysis in U.S. Federal government decisions.
The field of benefit-cost analysis is replete with guidance on theoretical and empirical valuation of impacts. Many fewer resources, however, are available for analysts to consult when determining the set of policy impacts to value in the first place. This post describes a new article published with co-authors Joseph Ripberger, Wesley Wehde, Hank Jenkins-Smith, Carol Silva, Kuhika Gupta, Benjamin Jones, and Robert Berrens, in the Spring 2019 Issue of the Journal of Benefit-Cost Analysis. The article, entitled, ‘Benefit-Cost Analysis, Policy Impacts, and Congressional Hearings,’ proposes a method for identifying policy impacts that contributes a degree of systematism, transparency, and replicability to the process.
Academic researchers and government institutions have both encouraged retrospective analysis of the costs and benefits of regulation to facilitate evidence-based review and possibly revision of the design and stringency of existing regulations (White House 2012; Morgenstern 2015). However, rigorous examples of these types of ex post analyses are relatively rare. This post describes a study comparing the retrospective costs (evaluated ex post) of a U.S. Environmental Protection Agency (EPA) regulation to the cost estimates reported during the regulatory process (calculated ex ante). These findings are reported in more detail in a recent article, “Retrospective Evaluation of the Costs of Complying with Light-Duty Vehicle Surface Coating Requirements,” published in the Spring Issue of the Journal of Benefit Cost Analysis, with co-authors Nathalie Simon and Ann E. Ferris.
Since Ronald Reagan’s 1981 Executive Order 12291 established benefit-cost analysis as standard practice for major rule changes, benefit-cost analysis has been commonly used to assess the efficiency of proposed federal regulations. Because of this and subsequent executive orders, all federal regulations that are projected to have a total economic impact of over $100 million are subject to a full benefit-cost analysis. Despite this prevalence at the federal level, benefit-cost analysis is much less common at the state level. In 2013, the Pew-MacArthur Results First Initiative released a study of the use of benefit-cost analysis in the states (study results were subsequently reported in the Journal of Benefit Cost Analysis in 2015). The study found that, over the four years from 2008 to 2011 states conducted only 36 full cost benefit analyses and 312 partial cost-benefit analyses. This averaged out to 9 full analyses and 78 partial analyses per year across all 50 states.