The proposed revisions to Circular A-4 recently put forward by the Office of Information and Regulatory Affairs include guidance on applying what are referred to as "distributional weights." Costs and benefits to households and individuals with lower income are multiplied by a number greater than one, while those to households and individuals with higher income are multiplied by a number less than one. In the public comments on the proposed revisions, a number of criticisms of distributional weighting have been put forth, including:

• Distributional weighting conflates information about welfare with information about equity, undermining transparency.
• Distributional weighting introduces subjective value judgments into BCA;
• Distributional weighting puts a finger on the scale.

In our paper (Acland and Greenberg, 2023), we explicitly recommend that distributional weighting of the sort presented in the proposed revisions be adopted by federal agencies. As such, we feel that some clarification of our position is in order, in the hope that these criticisms may be better understood and laid to rest.

We begin by emphasizing that two justifications for distributional weighting have been historically put forth, only one of which is addressed in the proposed revisions. This justification is that a dollar means more to a poor person than to a wealthy person due to the diminishing marginal utility of income.  Consequently, any given impact on the welfare (or utility, or wellbeing) of the poor is represented by a smaller number of dollars in BCA than the same impact on the welfare of the wealthy: if a poor person and a wealthy person experience the same increase or decrease in their welfare as a result of a policy, the dollar value of that welfare impact that is recorded in BCA will be smaller for the poor person than for the wealthy person, and will thus count for less in the net benefit calculated in the BCA. If this is ignored in BCA, then a bias results, because the welfare or utility of the poor is undercounted in dollar terms and that of the wealthy is overcounted. Applying weights based on the marginal utility of income at different income levels has been proposed as a way to correct this bias, so that a given dollar amount in BCA would represent the same welfare impact on the poor as on the wealthy. We call this "utility weighting."

Regulations to improve air quality, save energy, or reduce climate risks account for the largest share of benefits and costs of the US regulatory program.  We address the economic methods for evaluating this class of regulations in “Benefit-Cost Analysis of Air Pollution, Energy, and Climate Regulations.  This work was recently published as open access in the Cambridge Core Element Series in public economics. The methods considered are relevant for OMB’s ongoing revision of BCA guidance (Circulars A-4 and A-94), and EPA’s proposed changes for measuring the economic benefits of reducing greenhouse gas emissions.  

The work compares and contrasts Regulatory Impact Assessment (RIA) in the U.S. and Europe, and addresses five methodology issues: the estimation of costs, the estimation of benefits, discounting methods, distributional analysis, and the evaluation of less and more fundamental uncertainty. The intended audience is regulators and other constituencies interested in the nexus between scholarship and practice, analysts in government agencies and research organizations, and academic scholars and their graduate students.

The following are some of the key takeaways. 

Economists have for decades recommended that carbon dioxide and other greenhouse gases be taxed to provide incentives for their reduction. The United States does not have a federal carbon tax; however, many state and federal programs to reduce carbon emissions effectively price carbon—for example, through cap-and-trade systems or regulations. There are also programs that subsidize reductions in carbon emissions. At the 2022 meetings of the American Economic Association, the Society for Benefit-Cost Analysis brought together five well-known economists—Joe Aldy, Dallas Burtraw, Carolyn Fischer, Meredith Fowlie, and Rob Williams—to discuss how the United States does, in fact, price carbon already and how it could do so more effectively. Maureen Cropper chaired the panel.

Meredith Fowlie discussed problems that a carbon tax would present if levied on the US energy sector. As Fowlie pointed out, setting a carbon tax equal to the social cost of carbon assumes that the prices of carbon-intensive goods reflect suppliers’ marginal private costs. In many US states, however, regulated retail electricity and natural gas prices exceed marginal supply costs—in the case of electricity, sometimes by a factor of two to three. Electricity prices have risen to cover the costs of upgrading generation, transmission, and distribution systems and making the grid more resilient to extreme weather events. Adding a carbon tax to these prices would slow the pace of electrification for the clean energy transition and would burden low-income households. Fowlie discussed these issues and suggested that retail rate reform is needed.

Joe Aldy presented an overview of clean energy subsidies that the federal government has provided to reduce carbon emissions. These include investment and production tax credits for renewable energy sources, loan guarantees for renewable power, and state block grants to promote energy efficiency. Aldy discussed the limitations of these subsidies relative to a carbon tax. Whereas a carbon tax would provide a price signal throughout the economy that would tend to equalize marginal abatement costs, clean energy subsidies do not. And because of their limited lifetime, clean energy subsidies do not usually provide dynamic incentives for emissions reductions. Aldy discussed how specific clean energy subsidies could be redesigned to better mimic a carbon tax. He also suggested using formal program evaluation to improve the design of subsidies to reduce carbon emissions.
Dallas Burtraw reviewed the barriers to implementing carbon pricing and noted nonetheless that it is important that we price carbon. Pricing carbon encourages cost-effective reductions in greenhouse gases (GHGs), rewards technological innovation to reduce carbon emissions, and helps coordinate activities to decarbonize the economy. To move in the direction of pricing carbon, Burtraw argued for formulating an industrial policy that mimics a carbon tax but is politically acceptable. One way to do this is to couple regulatory standards with sector-specific subsidies. Tradable emissions performance standards, such as California’s Low Carbon Fuel Standard, are an example. Burtraw discussed the extent to which tradable performance standards embody the attributes of a carbon tax.

On June 30, 2022, the Supreme Court of the United States decided West Virginia v. Environmental Protection Agency. The case was about whether EPA in the Clean Power Plan could set the carbon emissions standard for existing power plants at a level that would require the power plants to reduce coal use and shift to or subsidize natural gas or renewable-energy electricity generation (referred to as “generation shifting”). But the focus was not on whether such a level would be benefit-cost justified—but rather on whether the agency was allowed to set a standard requires generation shifting for compliance under this provision of the Clean Air Act. Writing for the majority, Chief Justice Roberts applied the “major questions” doctrine and concluded that EPA could not do this despite reasonable textual support for it; on issues like this one, which have “vast economic and political significance,” Congress must clearly authorize an agency to act in this way.

It is tempting to conclude that this decision about statutory interpretation has no relevance for benefit-cost analysis (BCA). But unfortunately, the decision contains language that suggests the Court misunderstands and disregards the value of using BCA in federal regulatory policy.

The trouble starts when the Court appears to ignore how BCA can help agencies set stringency levels for various standards. The Clean Power Plan, for example, was supported by a BCA that concluded that the rule’s benefits to society would dwarf its costs, with $22.6 billion worth of net health and safety benefits each year in likely scenarios (EPA 2015). But the majority opinion refers to this analysis to highlight only the expected costs of EPA’s approach—without mentioning the expected benefits at all (p. 10). And more concerning, when the EPA argued that its discretion to set an emissions standard is bounded by the fact that it must consider costs, the Court suggested that this admission is itself somehow evidence that EPA’s authority was too vast (p. 25). In fact, the Court seemed to not understand how BCA could reasonably inform and constrain the agency’s choice of the stringency level—or, as the Court called it, the “emissions cap” (p. 29). The Court appeared to think EPA was unconstrained in setting the cap, calling it a cap set to “wherever the Agency sees fit” as opposed to a cap “based on some scientific, objective criterion” (p. 29-30).

The primary way the Society pursues its mission to improve the theory and practice of benefit-cost analysis is by bringing people together, particularly during its annual meetings held each March. It is therefore very rewarding to note the recent increases in conference attendance and the associated increases in Society membership.

The first Society conference took place in 2008 and drew 79 people (Table 1). Attendance has grown steadily since then. In particular, the move to an online format in 2021 and 2022 resulted in very large increases in attendance, with attendance topping 600 people.

Table 1: SBCA Annual Conference Registrations

China is investing trillions of dollars in hundreds of projects, mainly infrastructures under its Belt and Road Initiative. This Initiative termed the BRI seeks to increase trade and contribute to global economic growth through increased connectivity, ports' development, building transport networks, pipelines, and other major infrastructures stretching from the northwestern part of China through Central Asia and Middle East through Africa and onwards to Europe.

We discuss some implications of this BRI in the context of new developments and key challenges it faces, not widely covered in the literature. Specifically, we identified three major areas which require immediate attention if any success of the BRI is to materialize. Such new areas may constitute the new research agenda for Cost-Benefit Analysis. One concern is the issue of NIMBYs (Not In My Backyard) which essentially deals with siting decisions. The second concern has to do with applying Cost-Benefit Analysis to BRI countries and that is whether the framework of conventional Cost-Benefit Analysis remain the same as with applications in developed countries. And, thirdly, the arrival of competing initiatives from the United States and European Union on the BRI. We discuss some conflict resolution instruments to siting issues and the role of auctions. Highlights from the new Health and Digital Silk roads are also presented.

Here are the key takeaways from our presentation at the 2022 Society for Benefit-Cost Analysis Annual Conference:

Hedonic property value regression is a leading technique for estimating how much consumers are willing to pay for nonmarket amenities. The prevailing style of estimation has evolved in recent years to incorporate insights from the “credibility revolution” in applied economics, with high expectations for data quality and econometric transparency. At the same time, recent research has improved our understanding of how parameters identified by quasi-experimental designs relate to welfare measures. This post describes an article summarizing modern best practices for developing credible hedonic research designs and valid welfare interpretations of the estimates. I wrote the article together with Kelly Bishop, Spencer Banzhaf, Kevin Boyle, Kathrine von Gravenitz, Jaren Pope, Kerry Smith, and Christopher Timmins. It was published in the Summer 2020 issue of the Review of Environmental Economics and Policy as part of a symposium on best practices for using revealed preference methods for nonmarket valuation of environmental quality. A 20-minute video summary is posted here.

There have been thousands of hedonic property value studies since the model was formalized in the 1970s and the pace has accelerated due to advances in data, econometrics, and computing power. The model’s enduring popularity is easy to understand. It starts with an intuitive premise that is economically plausible and empirically tractable. The model envisions buyers choosing properties based on housing attributes (e.g., indoor space, bedrooms, bathrooms) and on location-specific amenities (e.g., air quality, park proximity, education, flood risk). In the absence of market frictions, spatial variation in amenities can be expected to be capitalized into housing prices. When buyers face the resulting menu of price-attribute-amenity pairings, their purchase decisions can reveal their marginal willingness to pay (MWTP) for each of the amenities. In principle, estimating MWTP is straightforward. In practice, several key modeling decisions must be made. These include defining the market, choosing appropriate measures of prices and amenities, selecting an econometric specification, and developing a research design that isolates exogenous variation in the amenity of interest.

Defining the Market. Best practices in hedonic estimation start with defining the relevant housing market in a way that satisfies the “law of one price function”. This means that identical houses will sell for the same price throughout that market. The precise spatial and temporal boundaries that satisfy this condition may vary across space and over time as information, institutions, and moving costs change. One common practice is to define the market as a single metro area over a few years. An alternative is to pool data over larger areas and longer periods, and to model the hedonic price function as evolving over space and time.

Modernizing Regulatory Review, a Presidential memorandum published January 20, 2021, serves as a preface to the regulatory policies of the Biden Administration. As such, the memorandum complements three executive orders (E.O 13993: Revocation of Certain Executive Orders Concerning Federal Regulation; E.O. 13990: Protecting Public Health and the Environment and Restoring Science to Tackle the Climate Crisis; and E.O. 13979: Ensuring Democratic Accountability in Agency Rulemaking) that collectively rescind the previous administration’s regulatory policy. The regulatory policy foreshadowed in the memorandum and other documents, however, goes beyond rescinding the Trump administration’s program or restoring previous regulatory regimes.

Modernizing Regulatory Review calls for “improving and modernizing” regulatory review. Regulatory review includes, among other things, the benefit-cost and other analyses that Executive Order 12866 (Regulatory Planning and Review) requires for all significant executive branch regulations; agencies include these analyses in the Regulatory Impact Analyses or Economic Analyses reviewed by the Office of Information and Regulatory Affairs. Regulatory review as now practiced has been in place for 28 years, although there have been occasional hiccups, such as in the last administration when -- most notably -- E.O. 13771 made regulatory costs primary and created new regulatory categories in parallel to existing measures.

The memorandum calls for reform because it finds current regulatory review deeply flawed: “When carried out properly, [regulatory review] can help to advance regulatory policies that improve the lives of the American people.” Regulatory review could of course be done better; benefit-cost analyses do not always follow best practices (Farrow and Viscusi 2011), and the assessment of distributional effects is often spotty.

What is important cannot be measured?
According to a famous expression¹, the most important things cannot be measured. This seemed also to be true for biodiversity in cost-benefit analysis, in particular for the impact on non-economic benefits of biodiversity. However, this is not true anymore, as for over a decade in the Netherlands a methodology known as biodiversity points is being applied for this purpose (see Bos and Ruijs, 2021). Biodiversity points are quite similar to the quality-adjusted life years (QALY) used for cost-effectiveness analysis of health care treatments. Biodiversity points provide a quality-adjusted measure of the changes in the quantity of biodiversity. It is not based on the preferences and information of consumers or citizens, but is based in a standardized way on the expert-opinion of ecologists. The unit of measurement is not dollars or euros but is the number of biodiversity points.

For many cost-benefit analyses (CBA), properly assessing the welfare effects of a policy measure on biodiversity is important. This does not only apply to CBA on conservation or stimulation of biodiversity, but also to CBA on other policy areas such as mobility, agriculture and water safety, as the policy measures in these policy areas often have impacts on biodiversity. For example, a new road connecting two cities through a forest is good for mobility but has also impact on the value of biodiversity. The value of the forest for various economic uses may increase due to the reduction in travel time for visitors but the non-use value, e.g. the existence value and the value for future generations of the forest and the biodiversity of its species, may be affected severely by fragmenting the forest and by increasing traffic, pollution and visitors.

The revelations of the Facebook Files have again focused public attention on the spread of misinformation, hate speech and incitement to violence on Facebook. Youths across the globe use Facebook's Instagram and similar platforms to share violent videos. The question inevitably arises if authorities could use these platforms for violence prevention.

Bystander programs represent an established prevention measure. They motivate people to intervene in violent situations and teach the skills for safe and effective intervention. Studies suggest that bystander programs could reduce violent victimization and perpetration. However, face-to-face programs are cost-intensive and difficult to scale. Online programs face the challenge of reaching enough relevant participants. Social media can help on both counts. They allow reaching large audiences at relatively low cost and precisely addressing individuals at risk, i.e. micro-targeting.

This blog series is a partnership of the Society for Benefit-Cost Analysis On Balance blog and Dr. Zoë Plakias’ Spring 2021 Benefit-Cost Analysis (AEDECON 5330) class at The Ohio State University. Students interviewed experts in benefit-cost analysis to learn about what they do and why they do it. All interviews have been edited for brevity and clarity with the help of Dr. Plakias and are shared with the approval of the interviewer and interviewee.

• Expert: Dr. Charles Griffiths
• Interviewer: Katrina Hadley

Dr. Charles Griffiths is a Senior Economist at the U.S. Environmental Protection Agency. He has also taught courses on benefit-cost analysis at Johns Hopkins University and the University of Maryland and served as a Senior Economist for Environment, Energy and Natural Resources on the Council of Economic Advisers during the George W. Bush administration.

The views expressed in this interview are those of the interviewee and do not represent the position of the U.S. Environmental Protection Agency (EPA).

Monetizing the impact of regulation in order to weigh its benefits against its costs is comme il faut in the US, see, e.g., a recent blog post by Dan Ackland in On Balance. In Sweden, this is not the case. Three laws govern the requirements for background analyses ahead of regulation in Sweden: National Budget Law, Authority Regulation, and Ordnance on impact assessment in regulation. These stipulate that consideration must be taken of costs to the state budget, and to firms, but not to individual citizens or the society as a whole. As a consequence, if a benefit-cost analysis (BCA) is conducted ahead of environmental, energy, and climate policymaking (a big if), it is often of a very poor quality (Swedish Environmental Protection Agency, 2020; Hammes, Nerhagen, & Fors, 2021).

Since the 1970s, Swedish politicians and government agencies love to view the country as a forerunner in environmental policy. Politicians regularly set goals, such as reducing the greenhouse gas emissions from transport by 70 percent by 2030 compared to 2010 levels, meeting water-quality requirements even in waters that naturally don’t meet them, and being carbon neutral by 2045 that are very expensive to reach. At the same time, strong industrial interests influence policies, e.g., a vehicle industry that at times wields an undue influence over policy proposals (SOU 2016:33; Hammes, 2014). This has, among other things, led to a car fleet with the highest CO2 emissions in Europe, when domestic industry has been accommodated in the definition of an “environmentally friendly car”. Policy is made by consensus, and the politicians’ self-image is one of being able to weigh different interests against one other in the process – a process, that nevertheless does not contain a formal BCA.

Benefit-cost analysis, as usually practiced, sums the monetary values of effects on individuals. It can be justified by the potential compensation test: if the total monetary gain to the “winners” (those who gain from a policy) exceeds the total monetary loss to the “losers” (those who are harmed), the “winners” could (in principle) pay compensation to the “losers” so that everyone would judge herself better off with the combined policy and compensation than without. The idea is that by summing the net benefits across individuals, BCA measures “efficiency” or the size of the social pie, and that questions about distribution can be evaluated separately. Logically, policies that expand the social pie permit everyone to have a bigger slice; a smaller pie guarantees that at least some people get a smaller slice. 

The separation of efficiency and distribution is illusory: the size of the social pie can depend on the “numéraire” or measuring rod. Ideally, one might wish to measure each person’s slice by how much it contributes to her wellbeing. But without an objective method for comparing increments to wellbeing between people, one must choose a standard for comparison; the numéraire provides that standard.

Over the course of the past few years, there has been greater attention and scrutiny as to the high cost of America’s “Endless Wars” and over the past few months, alarms have sounded at the estimated price tag of $2.313 trillion in treasure and approximate 243,000 in direct lives lost from the War in Afghanistan (2021, Brown University, Watson Institute Costs of War Project) as well as calls for resignations at the collapse of Kabul. Similarly, the question of what were the benefits, if any at all, and the associated and more philosophical question of “Was it Worth it?” are even more difficult to explain and justify. The answer to these questions will be for each individual and generation to ponder, but it is expected that government leaders and policymakers should fully consider and take into account the benefits and costs prior to the declaration of war – not years and certainly not decades after the fact.

SBCA blogs from June 8 and February 25 this year already suggests ideas for revisions to the 2003 OMB Circular A-4 following President Biden’s January 20, 2021 memo on “Modernizing Regulatory Review”. This blog considers and suggests how to revise Circular A-4 specific to foreign policy decisions and the issue of “standing” in Benefit-Cost Analysis (BCA) by 1) addressing impacts on how Americans residing abroad, varying from a few million to several million (Department of State and GAO, 2015) as a demographic not to be ignored, but also 2) examining the BCA impacts to include global impacts and not only to extend to impacts on the global networks and transboundary linkages that affect U.S. residents. The former, in my view, was an obvious, critical population brought to light in the chaotic airlifts of American citizens as well as allies in Afghanistan and the pressures placed on the Department of State Bureaus of Consular Affairs (CA) and Population, Refugees and Migration (PRM), in particular. The proposed revisions would have implications from public policy and foreign policy perspectives in specific ways on interpretation, as explained below.

This blog series is a partnership of the Society for Benefit-Cost Analysis On Balance blog and Dr. Zoë Plakias’ Spring 2021 Benefit-Cost Analysis (AEDECON 5330) class at The Ohio State University. Students interviewed experts in benefit-cost analysis to learn about what they do and why they do it. All interviews have been edited for brevity and clarity with the help of Dr. Plakias and are shared with the approval of the interviewer and interviewee.

• Expert: Dr. James Hammitt
• Interviewer: Loryssa Lake

Dr. James Hammitt is a Professor of Economics and Decision Sciences at Harvard University. He is also the director for the Harvard Center for Risk Analysis and has affiliations with the Harvard University Center for the Environment, Harvard School of Public Health, Harvard Center for Risk Analysis, Harvard Environmental Economics Program, the Harvard China Project, and a joint appointment at the Toulouse School of Economics. 

Q: I know you started in applied mathematics. Is that something that you knew you wanted to get into or did you find out about environmental economics as you were studying?

This blog series is a partnership of the Society for Benefit-Cost Analysis On Balance blog and Dr. Zoë Plakias’ Spring 2021 Benefit-Cost Analysis (AEDECON 5330) class at The Ohio State University. Students interviewed experts in benefit-cost analysis to learn about what they do and why they do it. All interviews have been edited for brevity and clarity with the help of Dr. Plakias and are shared with the approval of the interviewer and interviewee.

• Expert: Dr. Sandra Hoffmann
• Interviewer: Melissa Ferruso

Dr. Sandra Hoffmann is a Senior Economist with the Food Economics Division of the USDA Economic Research Service (ERS). She received her undergraduate education at Iowa State University and went on to earn a J.D. from the University of Michigan Law School. She holds a Ph.D. from the Department of Agricultural and Resource Economics, University of California, Berkeley and an M.A. in Agricultural Economics from the University of Wisconsin-Madison.  She worked on pesticide regulation as an attorney.  She also served on faculty at the University of Wisconsin-Madison and was a research fellow at Resources for the Future before joining USDA Economic Research Service. Most of her work with the USDA concentrates on food safety and on valuation of the health benefits related to public policies. I had the wonderful opportunity to meet with Dr. Hoffmann to discuss her work with the USDA, as well as the career and education paths that brought her to where she is today.

Q: What was your undergraduate degree in, and how did you end up going from there, to studying law, to studying agricultural economics?

This blog series is a partnership of the Society for Benefit-Cost Analysis On Balance blog and Dr. Zoë Plakias’ Spring 2021 Benefit-Cost Analysis (AEDECON 5330) class at The Ohio State University. Students interviewed experts in benefit-cost analysis to learn about what they do and why they do it. All interviews have been edited for brevity and clarity with the help of Dr. Plakias and are shared with the approval of the interviewer and interviewee.

• Expert: Lisa A. Robinson
• Interviewer: Katherine Bowman

Lisa A. Robinson is Deputy Director of the Center for Health Decision Science and Senior Senior Research Scientist at the Center for Health Decision Science and Center for Risk Analysis at the Harvard T.H. Chan School of Public Health. She served as the President of the Society for Benefit-Cost Analysis in 2014.

Q: How did you get interested in benefit-cost analysis?