In the first analysis purporting to causally link environmental pollution to personality, Schwaba and colleagues leveraged a natural experiment driven by the United States. They used the Clean Air Act to assess the impact of decreased atmospheric lead on the “big five” personality traits. Using data from an online personality test taken by more than 1.2 million U.S. residents, Schwaba et al. reported that people born after lead levels had peaked in their county of birth had more mature, psychologically healthy personalities in adulthood (higher agreeableness and conscientiousness, and lower neuroticism) than cohorts born earlier and exposed to higher levels of atmospheric lead. One concern with their findings is that personality differences among people born in different periods could come from factors unrelated to lead, for example, access to abortion and birth control, or demographic, cultural, or technological changes. Schwaba et al. recognized this possibility but did not fully explore it. When we account for cohort-wide changes by introducing birth year fixed effects into Schwaba et al.’s models, the estimated effects of the lead phaseout on personality largely disappear, becoming indistinguishable from zero while remaining precise. Meanwhile, the estimated birth year fixed effects are jointly significant, suggesting differences in personality traits across cohorts. These results indicate that any effects of the lead phaseout on more mature, psychologically healthy adult personalities are not consistently observable in the data used by Schwaba et al. More broadly, they caution against making causal inferences without controlling for time period effects.

We develop a model to perform a cost–benefit analysis of bus fare subsidies under financial constraints that preclude the purchase of additional buses. Our model considers users’ costs in the provision of bus services and the lack of road pricing to internalize urban transport externalities in a context where financial constraints severely limit the institutional ability to plan and design the bus system. Because of financial constraints, the bus system can hardly accommodate demand during peak times: buses travel overcrowded, passengers cannot board the first bus to arrive at the bus stop, and they cannot arrive at their destination at their desired time. Another salient aspect of our model is the inclusion of motorcycles as a second private transport mode. Motorcycles are typical in many urban agglomerations in the emerging world and engender many negative transport externalities. According to our results, fare subsidies provide social benefits in Metropolitan Asunción. During peak hours, a higher subsidy is justified as the reduction of the unpriced external costs of substitute modes compensates for the increased cost created by an additional bus passenger. In the off-peak, a higher subsidy is justified (i) as the higher frequencies induced by the new bus ridership reduce waiting times and (ii) because of the reduction of the unpriced external costs of substitute modes. Although our model does not explicitly include inequality aversion, we discuss the distributional aspects of subsidies in the context of middle-income countries.

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.

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.

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.