The social cost of greenhouse gases is important in many regulatory impact analyses. However, calculations of the social cost of greenhouse gases are highly complex and periodically revisited. We offer seven recommendations to improve current estimates. These include recommendations to use both country-level and global measures of the social cost of greenhouse gases, to use country-specific values for monetizing climate damages, to represent uncertainties by reporting distributions instead of using only central values, and to conduct a temporal distributional analysis that shows the magnitudes of climate damages across generations. We also provide recommendations for the discount rates that should be used when estimating the social cost of greenhouse gases, and the appropriate discount rates for regulatory impact analyses that include the social cost of greenhouse gases.

As its practitioners know well, benefit-cost analysis (BCA) walks a fine line between the positive and normative, between the science of economics and the art of political economy. Missteps threaten to undermine its credibility as a value-free science, while overcaution risks irrelevance to the pressing questions of the day. As BCA adapts to give more weight to distributional concerns, while operating in a more highly charged political environment than ever before, these tensions will only grow. For perspective, I reexamine three prominent episodes in the history of economics where these issues were vigorously debated: (i) The founding of the NBER by Wesley Clair Mitchell, who insisted that the organization eschew all policy recommendations; (ii) the introduction of the modern definition of economics as the study of tradeoffs by Lionel Robbins, who insisted welfare effects could never be aggregated; and (iii) the origins of BCA as a measure of income, which to first-generation practitioners seemed to foreclose the possibility of measuring “intangible” benefits like recreation opportunities, mortality risks, and equity. These episodes, together with critiques of economics from philosophers of science, suggest we are best served by being as transparent as possible about the ways values influence BCA reasoning, without arrogating political decisions into it.

In addition to effects from greenhouse gases, climate change is affected by short-lived climate forcers (SLCF). These are often co-emitted with carbon dioxide, and some are regulated air pollutants. In the governance of these pollutants, established estimates of damage costs of pollution inform benefit–cost analyses. However, climate change impact of SLCFs is omitted from these estimates. The purpose of this study is to calculate economic damage costs of air pollutants’ effect on climate change and compare these with established damage costs. Focus is on European emissions governed in the EU National Emission Reduction Commitments Directive during 2020–2050. We use well-known SLCF emission metrics and multiply with literature values on social costs of methane to calculate climate damage costs of SLCFs. The results indicate that average absolute climate damage costs are highest for black carbon ($59,500/ton in 2050) and lowest for nonmethane volatile organic compounds ($661/ton). Our indicative values are likely underestimations. Indicative climate damage costs are usually lower than established damage costs, with notable exceptions. We propose that more detailed studies are necessary, and that inclusion of climate damage costs into economic valuation of SLCFs is important for future air pollution and climate benefit–cost analyses.

Motivated by traffic congestion and air pollution, Beijing is one of several major cities to restrict vehicle ownership by requiring residents to win a lottery for the right to obtain an additional car. We examine the welfare cost of preventing people from owning cars because of misallocation: under a lottery, some individuals with low willingness to pay (WTP) for cars can obtain cars, while other individuals with high WTP cannot. We estimate welfare costs using a new contingent valuation method survey of Beijing lottery participants which we designed and conducted explicitly for this purpose. We find that restricting vehicle ownership reduced private welfare by 26 billion yuan. Back-of-the-envelope calculations suggest that the benefits of lower congestion and pollution roughly equal the costs. Our WTP estimates indicate a net welfare gain of approximately 32 billion yuan if Beijing’s lottery were replaced with an auction, which is similar to previous estimates.

This article compares the U.S. Environmental Protection Agency’s (EPA) ex ante cost analysis of its 1995 Large Municipal Waste Combustor (MWC): New Source Performance Standards and Emissions Guidelines rule to an ex post assessment of its cost. Unlike many retrospective cost analyses, where ex post assessments are limited due to lack of data on compliance costs, this case study is unique because we located and used plant-level survey data from the U.S. Department of Energy and Governmental Advisory Associates in a comparison of ex ante and ex post costs of individual MWCs. We find the ex post capital expenditures for nitrogen oxide control systems are typically lower than the EPA ex ante estimates, while the ex post capital expenditures for mercury control systems tend to be higher than the EPA ex ante estimates. Finally, while we find a few outliers, the average ratio of ex post to ex ante capital expenditures for particulate matter and sulfur dioxide emissions control is near unity.

This study is an attempt to determine whether the need to get hydropower project appraisals perfectly right during the pre-construction phase, so as to prevent significant overruns along with benefit shortfalls, should supersede the need to deliver projects at the earliest possible time so as to meet the needs of the people. To achieve the study objective, we test whether the Hiding Hand principle is predominantly benevolent or malevolent. We argue that if the Hiding Hand is benevolent, then project stakeholders are better off focusing on the quick delivery of power projects; however, if it is malevolent, then more attention should be given to perfecting project appraisals. It transpires from the statistical analysis that the Benevolent Hiding Hand dominates the Malevolent Hiding Hand in the selected World Bank-financed hydropower projects (33% v. 21%), and that ultimately, 75% of the projects were even more successful than anticipated—while 25% of the projects failed. Our findings further show that while a total loss of 2.335 billion USD in the sampled dams was caused by the Malevolent Hiding Hand, 11.259 billion USD was gained as a result of the Benevolent Hiding Hand. The predominance of the Benevolent Hiding Hand justifies placing some weight on proceeding with hydropower projects that show significant promise even if all the implantation risks are not fully quantified at the appraisal stage, especially in developing countries.

We review the practice of safety benefits analysis for federal transportation regulations in the USA. Using a case-study approach, we explore the linkages between risk assessment and benefits analysis, adding to previous work exploring these linkages for environmental health regulations. Challenges for calculating the benefits of transportation safety regulations arise because safety outcomes, like many noncancer health effects, typically do not have formal risk relationships like dose–response functions established for them. Analysts often rely on engineering or other expert judgments or resort to qualitative discussions to connect a regulatory intervention to its intended outcome. Challenges also arise when regulatory outcomes are intangible or do not have established metrics. Safety outcomes are not always measurable in concrete terms like mortality risk and may include difficult-to-operationalize concepts like “safety culture.” If the outcome is not measurable, then quantifying or monetizing the expected effects of a regulation is not possible, and the ability to conduct robust qualitative discussions also may be limited. Economists evaluating benefits for safety regulations encounter limitations analogous to difficulties found in health regulations. To inform policymaking effectively, economists and safety experts could look to the relationship developed in environmental economics between economists and health scientists.

This paper presents new benefit–cost estimates for the Tulsa universal pre-K program. These calculations are based on estimated effects, from two recent papers, of Tulsa pre-K on high-school graduation rates and college attendance rates of students who were in kindergarten in the fall of 2006. In the current paper, educational effects from these prior papers are used to infer lifetime earnings effects. Our conservative estimates suggest that per pre-K participant, the present value of earnings effects in 2021 dollars is $25,533, compared with program costs of $9,628, for a benefit–cost ratio of 2.65. Compared to prior benefit–cost studies of Tulsa pre-K, this benefit–cost ratio is below what was predicted from Tulsa pre-K’s effects on kindergarten test scores, but above what was predicted from Tulsa pre-K’s effects on grade retention by ninth grade. This fading and recovery of predicted pre-K effects as children go through K-12 and then enter adulthood is consistent with prior research. It suggests that pre-K may have important effects on “soft skills,” such as persisting in school, and reminds us that short-term studies of pre-K provide useful information for public policy.

Intentional violence against healthcare workers inflicts a physical and mental toll, motivating legislative proposals to better regulate these occupational risks. This article uses this context to address two novel issues for benefit assessment raised by injuries from assailants: potential heterogeneity in valuation based on the context of the injury risk and possible reductions in self-reported valuations when the exposed population has been trained to feel responsible for the risk. This article presents experimental evidence on workers’ preferences over the form of intervention: protection (risk reduction) or insurance (cost-sharing). The experiment also elicits worker valuations of occupational health care risks, calculating the value of a statistical injury (VSI), based on local wage-risk tradeoffs, in the general range of $200,000. Workers accord a premium to risk reductions that might eliminate the risk of injuries. Both the physical harm and the process by which the injury occurs may affect benefit assessments for the regulation of workplace violence. Non-healthcare participants require a $40,000 premium per expected injury resulting from intentional harm. While health care workers do not generally require such a premium, health care workers in clinical positions require more compensation to face occupational risks. Insurance coverage for monetary losses is more highly valued than protective measures for accidental harms, though there is no significant comparable preference for insurance against intentional harms. The results have important practical implications for addressing the concerning phenomenon of violence against healthcare workers, suggesting that expanding insurance compensation would be desirable, as would assigning an intentionality premium to intentional injuries.

Estimates of the elasticity of the marginal utility of income are necessary for determining distributional weights to correct for diminishing marginal utility of income, which is particularly important in light of increasing concern about accounting for distributional impacts in regulatory review. The elasticity is also necessary for computing the social discount rate using the Ramsey formula. Despite many attempts to estimate the elasticity of the marginal utility of income, considerable uncertainty exists about the magnitude of this key parameter. In this paper, we use meta-analysis of estimates of the elasticity from the US and UK to shed light on the appropriate elasticity values to use for both distributional weighting and discounting. Relying on our findings, we tentatively conclude that it is reasonable to base the social discount rate and distributional weights on an elasticity of 1.6, with lower- and upper-bound sensitivity testing at 1.2 and 2.0. This estimate results in distributional weights which appear plausible, and which we believe can contribute to a consensus on how to conduct distributional weighting. Moreover, the resulting social discount rate is within the range typically recommended when the Ramsey formula is used.