In response to tire failures and vehicle rollover accidents, most notably those experienced by Ford Explorers with Firestone Tires, the 106th Congress and President Clinton enacted the Transportation Recall Enhancement, Accountability, and Documentation (TREAD) Act of 2000. Section 13 of the TREAD Act requires vehicle manufacturers to install tire pressure monitoring systems (TPMS) that alert drivers when a tire is significantly under-inflated. This paper first discusses the political economy that ultimately led to the final TREAD Act TPMS regulation. Then, relying on the variation of model-year TPMS introduction, I investigate whether and to what extent TPMS reduces all vehicle fatalities and those associated with tire failure and improper inflation. I find that the introduction of TPMS is associated with just over 11 fewer tire failure-related deaths per year, resulting in a net benefit of −$752 million to −$1,876 million (in $2001) per year. I find no change in the number of tire inflation-related fatalities with the introduction of TPMS.

Jerry Ellig was a unique character and a great economist. He believed in one thing, using economic analysis to help solve problems. He became an expert at Regulatory Impact Analyses and how they helped governments to choose the best option to do just that, all the while recognizing the problems that government has with necessarily much less information than markets. He believed in holding governments to account for achieving results including periodic lookbacks to see what they were doing. What was great about Jerry is that he had fun doing all of this both on the job and at his beloved Tiki bars.

Cannabis is the most commonly used illicit drug worldwide. In countries with repressive drug policies, the costs of its prohibition plausibly outweigh the benefits. We conduct a cost–benefit analysis of cannabis legalization and regulation in the Czech Republic, taking into consideration alternative scenarios designed using parameters from the known effects of cannabis legalization in selected U.S. states, Canada, and Uruguay. Our analysis focuses on tax revenues, law enforcement costs, the cost of treatment and harm reduction, and the value of Quality Adjusted Life Years (QALYs). Under all the projected scenarios, the identified benefits of legalizing cannabis for personal use exceed the potential costs. The estimated net social benefit of legalization is in the range of 34.4 to 107.6 million EUR per year (or between 3.2 and 10.1 EUR per capita), depending on the size of the cannabis market and the development of cannabis prices after legalization.

We briefly describe the structure of a regulatory system that alleviates many of the problems that arise when elected officials delegate rulemaking authority to government agencies. These problems include principal-agent issues, monopoly provision, information asymmetry, and tragedy of the commons. This structure better aligns the incentives of regulators with those of legislators and with the well-being of the public. We intend the solutions and process structure presented here not to serve as a collection of proposed changes but as guideposts for those hoping to make any part of the regulatory system better attuned to the needs of the populace.

In 2020 the Federal Communications Commission (FCC) revisited a spectrum allocation decision it made in 1999. The Agency found that frequencies set aside for specific technologies used by vehicles – Intelligent Transportation Services (ITS) – had been left largely unused. It crafted new rules, shifting 45 MHz of the 75 MHz allocation to newly designated wireless services focusing on Wi-Fi applications, while leaving the remaining (40% of bandwidth) reserved for ITS. The FCC decision was premised on a cost–benefit analysis performed by the agency, supported by two similar studies submitted by outside interests. Yet, upon examination, the cost–benefit calculations prove stunningly uncompelling. In their economic logic, their understanding of existing market data and their use of FCC policy, fundamental errors render net benefit estimates irrelevant to decision-making. In particular, the value of marginal products (VMPs) as well as the opportunity costs of rival allocations are ignored. These failings are stunning, both on their own and given that the FCC, in its reallocation, critiqued its 1999 decision as socially unproductive – and yet deployed just the same basic methodological format, relying on FCC administrative determinations to select favored business models for supplying wireless services.

Conventional benefit–cost analysis is well-established and widely used to assess interventions designed to improve public health and welfare. While it has many advantages, it has well-known limitations. Chief among these is its inattention to the distributional equity of the impacts. To measure individual well-being, the conventional approach relies on individuals’ willingness to exchange their own income for the outcomes they experience. To measure societal welfare, it relies on simple aggregation of these values across individuals. This approach reflects a relatively narrow conception of welfare and ignores how impacts are distributed across advantaged and disadvantaged individuals. Social welfare analysis has been proposed as an alternative approach to address these limitations, but real-world applications are rare due largely to the complexity of the calculations. This article provides a pragmatic approach for conducting equity-sensitive benefit–cost analysis globally that addresses data limitations and other challenges, illustrated with example applications. It formally develops and implements equity weights that adjust for the decreasing marginal value of money and for additional moral considerations, prioritizing increases in welfare for those who are worse off.

This article is part of a larger series that is dedicated to the memory of Dr. Jerry Ellig, with whom I had the pleasure of working on multiple occasions. It explores the concept of regulatory subsidiarity, which involves pushing regulatory power down from centralized governments to state, local, tribal, and other governments. It explains how this approach both promotes policy tailoring and facilitates regulatory experimentation, allowing policy makers to test which interventions produce the best results. Finally, it considers how regulatory subsidiarity has proven itself outside of the U.S. and can succeed within the U.S. as well.

An invited contribution to an issue of the Journal of Benefit–Cost Analysis honoring the work of the late Dr. Jerry Ellig, this essay recognizes and draws upon the Regulatory Report Card methodology developed by Ellig and Dr. Patrick McLaughlin to evaluate the quality of regulatory impact analysis published by federal government agencies in conjunction with notice-and-comment rulemaking. The essay anticipates a forthcoming study of changes to tax regulatory practices as a result of a 2018 Memorandum of Agreement between the Treasury Department and the Office of Information and Regulatory Affairs – a study the authors discussed and hoped to conduct with Ellig before he passed away. The essay summarizes the Regulatory Report Card methodology, offers a brief typology of tax regulations, addresses why regulatory impact analysis and the Regulatory Report Card methodology are appropriate for the tax context, but also documents a few tax-specific adjustments to the Regulatory Report Card methodology.

Public sector allocative decisions should reflect, as far as possible, the preferences of those affected by the decisions. Conventional benefit–cost analysis (BCA) will simply aggregate individuals’ private willingness-to-pay (WTP) over all affected individuals to estimate the total benefits of a policy that delivers a public good. Given the nature of a public good, it is not unreasonable to consider that an individual may have altruistic preferences over the consumption of the public good by others. In this paper, we set out the theoretical underpinnings for a new citizen-based WTP, informed by political philosophy. Our model extends the standard social utility model (Bergstrom, 2006) of WTP for a public good when individuals are altruists by incorporating a Veil of Ignorance (VoI; Harsanyi, 1955). Our findings show that our WTP (Citizen) correctly includes altruistic as well as distributional preferences of individuals in society into WTP for use in a BCA. When WTP (Citizen) are aggregated for use in a BCA, equal weight is given to each individual’s preference and the BCA will correctly identify potentially Pareto-improving projects in a consistent manner.

This special issue of the Journal of Benefit–Cost Analysis is dedicated to the memory of Jerry Ellig, a brilliant economist whose untimely death in 2021 cut short a productive and influential career in government and academia. Jerry was adept at applying economic concepts and empirical analysis to improve public policy, and he enjoyed not only studying real policy problems, but finding practical solutions to them. He was also a generous mentor, supporting and collaborating with graduate students and colleagues to publish prolifically in peer-reviewed economics, public administration, and political science journals, as well as law reviews and more popular outlets. He was a great communicator, able to take his academic work and translate it for different audiences, including through testimony, seminars, op-eds, short presentations, and classroom teaching. In addition to these immense talents, Jerry was genuinely kind and unpretentious; he wore Wal-Mart suits and garish ties. And he was laugh-out-loud funny, a master at diffusing difficult situations with a witty, but never mean, quip.

For the past decade, U.S. communications policymakers have been debating the need for net-neutrality regulation of “dominant” communications carrier platforms. One of the reasons advanced for regulating these carriers derives from a fear that carriers could reduce competition in the production and distribution of video media through their ownership of media companies, but is there any evidence supporting the notion that vertically integrated communications companies have successfully used such a strategy? This paper provides evidence from the financial markets that carrier integration into video production has not redounded to the benefit of these companies’ stockholders. In fact, this integration appears to reduce the value that investors place on such carriers, a result that suggests that the difficulties in managing a large, vertically integrated media and communications company more than offset any benefits (if any) that may derive from anticompetitive behavior induced by vertical integration.

This paper explores the role of microeconomic analysis in policy formulation by assessing how the regulatory impact analyses (RIAs) that federal regulatory agencies prepare for important proposed rules may affect outcomes when regulations are challenged in court. Conventional wisdom among economists and senior regulatory officials in federal agencies suggests that high-quality economic analysis can help a regulation survive such challenges, particularly when the agency explains how the analysis affected decisions. However, highlighting the economic analysis may also increase the risk a regulation could be overturned by inviting court scrutiny of the RIA. Using a dataset of economically significant, prescriptive regulations proposed between 2008 and 2013, we put these conjectures to the test, studying the relationships between the quality of the RIA accompanying each rule, the agency’s explanation of how the analysis influenced its rulemaking decisions, and whether the rule was overturned when challenged in court. The regression results suggest that higher-quality RIAs are associated with a lower likelihood that the associated rules are later invalidated by courts, provided that the agency explained how it used the RIA in its decisions. Similarly, when the agency described how the RIA was used, a poor-quality analysis appears to increase the likelihood that the regulation is overturned, perhaps because it invites a greater level of court scrutiny. In contrast, when the agency does not describe how the RIA was utilized, there is no correlation between the quality of analysis and the likelihood that the regulation will be invalidated.

Over the last century, the United States has witnessed three approaches to achieving better regulatory outcomes: the removal of “economic” regulations in certain sectors; regulatory impact analysis (RIA) of new “social” regulations; and retrospective analysis of existing regulations. This article reviews the rationale for each approach, the results to date, and the remaining challenges. It finds that both institutional and technical factors influence the success of reform efforts.

This article uses the well-being valuation (WV) approach to estimate and monetize the well-being impacts of informal care provision on caregivers. Using nationally representative longitudinal data from the UK, the British Household Panel Survey, we address two challenging methodological issues related to the economic valuation of informal care: (i) the anticipatory nature of informal care; and (ii) the sensitivity of income estimates used in valuation. We address the anticipatory issue by focusing on well-being impacts associated with caring for a relative who had recently suffered a serious accident. We use the fixed effects filtered (FEF) estimator to estimate a “time-invariant income” coefficient free from individual fixed effects bias, which helps to partially improve the quality of the income estimate as an alternative to using instrumental variables. This estimate is used in the calculation of shadow prices of informal care. Our estimates suggest that, focusing on the first year of unanticipated care provision, those experiencing the well-being losses from providing unanticipated informal care would be willing to pay approximately £13,167 on average to avoid it.

Coal is declining in the U.S. as part of the clean energy transition, resulting in remarkable air pollution benefits for the American public and significant costs for the industry. Using the AP3 integrated assessment model, we estimate that fewer emissions of sulfur dioxide, nitrogen oxides, and primary fine particulate matter driven by coal’s decline led to $300 billion in benefits from 2014 to 2019. Conversely, we find that job losses driven by less coal plant and mining activity resulted in $7.84 billion in foregone wages over the same timeframe. While the benefits were greatly distributed (mostly throughout the East), costs were highly concentrated in coal communities. Transferring a small fraction of the benefits to workers could cover these costs while maintaining societal net benefits. Forecasting coal fleet damages from 2020 to 2035, we find that buying out or replacing these plants would result in $589 billion in air quality benefits, which considerably outweigh the costs. The return on investment increases when policy targets the most damaging capacity, and net benefits are maximized when removing just facilities where marginal benefits exceed marginal costs. Evaluating competitive reverse auction policy designs akin to Germany’s Coal Exit Act, we find that adjusting bids based on monetary damages rather than based only on carbon dioxide emissions – the German design – provides a welfare advantage. Our benefit–cost analyses clearly support policies that drive a swift and just transition away from coal, thereby clearing the air while supporting communities needing assistance.

This article discusses the difference between benefit–cost analysis (BCA) and social welfare analysis in the evaluation of pandemic preparedness policies. Two social welfare approaches are considered: utilitarianism and prioritarianism. BCA sums the individuals’ monetary equivalents of the pandemic impacts. Social welfare analysis aggregates individuals’ well-being impacts. The aggregation rule identifies the normative judgments about what is fair. This article shows that the two methods yield very different estimates of the value of avoiding a future pandemic similar to the COVID-19 one. Compared to BCA, considerations about the distribution of the costs of the hypothetical intervention play a major role in the estimate of both utilitarian and prioritarian pandemic burdens: The more progressive the distribution of the costs is, the larger the net benefits of preventing the pandemic. In contrast, the BCA pandemic burden is indifferent to the distribution of the intervention costs. In addition, BCA tends to underestimate the burden suffered by low-income countries compared to social welfare analysis.

There is a need to value health technologies in a way that accommodates their broader economic impacts and competing approaches for doing so have emerged. The Pareto principle (PP) requires policymakers to resolve intrapersonal trade-offs by deferring to the preferences of the individuals facing those trade-offs. Many broad value frameworks such as cost-utility analysis and its extensions, health-centric multicriteria decision analysis, and poverty-free life expectancy are not sufficiently deferential to these preferences, violating PP. I propose using the health-augmented lifecycle model (HALM) to value health technologies in a way that flexibly incorporates the interactions among health and economic factors – specifically mortality and morbidity risks, paid and unpaid work, consumption, leisure, and public and private transfer inflows and outflows--over the life course. It relies on individual preferences, satisfying PP. It is compatible with cost-benefit analysis, social welfare functions, and equivalent income approaches. I calibrate the HALM for the US setting and apply it to a pediatric vaccine.

Estimating value of statistical life (VSL) is an important input to many benefit-cost analysis (BCA) approaches, but for many low- and middle-income countries, there are limited or no data estimating VSL. Current guidance relies on extrapolation of results from high-income settings, which may be unreliable, leading to low confidence applying VSL. During 2019, we surveyed 1,820 low-income individuals (average consumption per capita USD329) across four diverse regions in Ghana and Kenya, to inform recommendations about effective spending in the development sector. We elicited VSL using a stated-preference approach, capturing the willingness-to-pay to reduce the risk of death for themselves and their children. Additionally, we conducted multiple “policy choice experiments” (PCEs) in which we asked respondents to choose, from the perspective of a decision-maker, between programs that save lives of different ages, and save lives and provide cash transfers. VSL estimates for this population fell in the range of USD66,795–USD90,453 (PPP-adjusted). We found similar results in the PCE but uncovered much stronger preferences for saving younger lives. Overall, our results suggest that VSL in low-income countries may be higher than estimates based on extrapolations from wealthy countries and that within these communities, policymakers should place more weight on saving the lives of young children. We also explore methodological learnings about how to apply and collect data for BCA in particularly low-income, low-education settings. We find that through careful training and gatekeeping, it is feasible to elicit complicated preferences in this population, and both approaches have their benefits and drawbacks.

In its 2023 revision of the social cost of carbon, the U.S. Environmental Protection Agency values people’s lives on the basis of their willingness to pay for them, without applying any distributional weights. It justifies this proposal on grounds of the Kaldor–Hicks criterion, which avoids interpersonal comparisons of wellbeing. But this criterion was discredited 70 years ago. Interpersonal comparisons of wellbeing cannot truly be avoided, and they should be used to determine distributional weights. One way of doing so is to identify as a numeraire a good that brings equal wellbeing to each person. A healthy life year is a reasonable, though only approximate, candidate for such a good. This article presents the point of view of a philosopher, regarding the practice of economists from outside the discipline.

Unweighted benefit–cost analysis (BCA) based on aggregate willingness to pay might be, at long last, falling into disrepute, as it is widely recognized that it exhibits a bias toward the wealthy, and as alternatives are appearing more and more practicable. However, the choice of alternatives is often framed in terms of choosing an alternative metric to willingness to pay in money, such as willingness to pay in healthy life years, or a measure of subjective well-being. It is argued in this paper that (i) a simple summation of individuals’ willingness to pay in any numeraire (e.g., money, healthy life years) is bound to generate non-transitivity issues in a similar way as money-based BCA, and (ii) a metric such as subjective well-being involves distributional value judgments that are too specific to reflect the relevant spectrum in the public debate. The “orthodox” weighted BCA method, which links BCA to an underlying social welfare function, offers more flexibility and guarantees transitive choices. Fortunately, in some relevant cases, these various methods may provide similar results, and the main options currently proposed all give greater weight to the worse off in the population than does unweighted BCA.