The Consumer Product Safety Commission’s regulation of disposable lighters was targeted at preventing injuries due to use of lighters by children not over 4 years of age. Based on a difference-in-differences analysis of national data for 1990–2019, this article estimates that the regulation reduced all injuries to the target population by 71%, burn injuries by 74%, and injuries severe enough to warrant admission to the hospital by 85% overall and by 84% for burn injuries. Unlike the counterproductive performance of safety cap regulations, this safety device enhanced safety levels in the target population group. The safety improvements from lighter safety devices outweigh any lulling effect of viewing products as being “childproof.” The regulation had a broader safety impact beyond the target population group, as it also reduced all types of injuries by at least 50% for children in the 5–17 age groups. Total annual risk reduction benefits were $940–$1465 million. A benefit-cost analysis based on a retrospective assessment of the regulation finds a more favorable impact than was anticipated.

Economic incentives are in widespread use to stimulate the development of the electric vehicle industry. However, the distributional effects of such incentives have been subject to little empirical inquiry. This study examines how California’s electric vehicle rebate program impacts different income groups financially. Two effects are considered: the income distribution of rebate beneficiaries and the income distribution of the rebate payers. The results reveal that the overall net financial impacts of the electric vehicle rebate program are regressive: the benefit distribution is highly regressive while the cost distribution is slightly progressive. Recent efforts to improve the fairness of the rebate program do not alter our findings. Policy implications are discussed.

There can be a serious tension between the commitment to cost-benefit analysis and a realistic appreciation of the limits of official knowledge. Without significant efforts to reduce those limits, that analysis might be inadequately informed. Whenever regulators face significant informational deficits, or what is sometimes called “the knowledge problem,” it is important to explore tools that take advantage of what the private sector knows; market-friendly tools, such as economic incentives, have important advantages on that count. An advanced regulatory system should also try to reduce the knowledge problem through three routes: (i) creative use of notice-and-comment rulemaking; (ii) retrospective analysis of regulations and their costs and benefits; and (iii) advance testing, as a way of informing ex ante analysis. For the future, the most promising approach is (iii).

How do economists use graphs, and do they use them well? Using Amazon’s Mechanical Turk, I provide evidence to these questions by exploring more than 2600 graphs published in the first issue of the American Economic Review from 1911 to 2017. I find that economists use a lot of line charts – more than 80% of the total sample are line charts. I also find that the share of graphs that use data (as opposed to diagrams) fell over the first half of the century and then increased from about the early 1980s to today, correlated with perceived graph quality.

The relationship between costs and health benefits of branded pharmaceuticals remains controversial. This paper examines the incremental costs incurred for incremental health benefits gained from the largest available sample of cost-effectiveness studies of branded drugs in the USA, the 1994–2015 Tufts Registry of Cost-Effectiveness Analyses. Earlier studies used small, specialized samples of drugs. We use linear regression analysis to estimate the association in those studies between additional quality-adjusted life years (QALYs) and incremental pharmaceutical costs. The preferred sample uses 476 studies involving branded pharmaceuticals with both higher costs and increased effectiveness compared to the previous standard of care. Regressions of costs on QALYs imply that an additional QALY is associated, on average, with a $28,561 increase in cost (95 % CI, $18,853–$38,270). This regression explains 20 % of the variation in sample costs. In this analytical sample, a share of the variation in the cost of pharmaceuticals is, therefore, not random but rather associated with variation in QALYs; prices are to some extent “value-based.” Our results are robust to varying sample inclusion criteria and to the funding source. In subgroup analyses, the highest cost per QALY was $44,367 (95 % CI, $35,373–$53,361). Costs of pharmaceuticals in this data set are, on average, lower than common estimates of the monetary value of a QALY to American consumers. As in other studies, we find that sellers of patent-protected beneficial new technology appear to capture only a fraction of the benefits provided.

This article examines the economic foundations of three criteria used for evaluating the costs and benefits of social programs. Some criteria do not consider the scale of programs or address the costs associated with programs that expand or contract the total government budget. A recent addition to the list of evaluation criteria – the marginal value of public funds – does not adopt a social optimality perspective. It evaluates the optimality of expenditures assuming a predetermined aggregate budget without considering the social costs of raising that budget.

Three common misconceptions persist about federal regulations. The first misconception is that most new regulations concern the environment, but in fact, only a small minority of regulatory flows are environmental. The second misconception is that regulators offer reasonable justifications and quantitative evidence for the majority of regulations. However, quantitative estimates rarely appear in published rules, negating the impression given by executive orders and Office of Management and Budget guidance, which require cost-benefit analysis (CBA) and clearly articulate sound economic principles for conducting CBA. Environmental rules have relatively higher-quality CBAs, at least by the standards of other federal rules. The third misconception, which is particularly relevant to the historic regulations promulgated during the COVID-19 pandemic, is that regulatory costs are primarily clerical, rather than opportunity or resource costs.

The value of statistical life (VSL) is arguably the most important number in benefit–cost analyses of environmental, health, and transportation policies. However, agencies have used a wide range of VSL values. One reason may be the embarrassment of riches when it comes to VSL studies. While meta-analysis is a standard way to synthesize information across studies, we now have multiple competing meta-analyses and reviews. Thus, to analysts, picking one such meta-analysis may feel as hard as picking a single “best study.” This article responds by taking the meta-analysis another step, estimating a meta-analysis (or mixture distribution) of seven meta-analyses. The baseline model yields a central VSL of $8.0 m, with a 90 % confidence interval of $2.4–$14.0 m. The provided code allows users to easily change subjective weights on the studies, add new studies, or change adjustments for income, inflation, and latency.

Partial equilibrium models have been used extensively by policy makers to prospectively determine the consequences of government programs that affect consumer incomes or the prices consumers pay. However, these models have not previously been used to analyze government programs that inform consumers. In this paper, we develop a model that policy makers can use to quantitatively predict how consumers will respond to risk communications that contain new health information. The model combines Bayesian learning with the utility-maximization of consumer choice. We discuss how this model can be used to evaluate information policies; we then test the model by simulating the impacts of the North Dakota Folic Acid Educational Campaign as a validation exercise.

Economists have for decades recommended that carbon dioxide and other greenhouse gases be taxed – or otherwise priced – to provide incentives for their reduction. The USA 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 USA does, in fact, price carbon and how it could price carbon. Maureen Cropper chaired the panel. This paper summarizes their remarks.

This article evaluates the long-term impacts of the Chicago Child-Parent Centers (CPC), a comprehensive early childhood program launched in the 1960s, on physical and mental health outcomes. This study follows a cohort of 1539 participants born in 1979–1980 and surveyed most recently at age 35–37 by employing a matched study design that included all 989 children who entered CPCs at ages 3 and 4 (1983-1985) and 550 comparison children of the same age from randomly selected schools participating in the usual district early childhood programs in kindergarten. Using propensity score weighting that addresses potential issues with differential attrition and non-random treatment assignment, results reveal that CPC preschool participation is associated with significantly lower rates of adverse health outcomes such as smoking and diabetes. Further, evaluating the economic impacts of the preschool component of the program, the study finds a benefit-cost ratio in the range of 1.35–3.66 (net benefit: $3896) indicating that the health benefits of the program by themselves offset the costs of the program even without considering additional benefits arising from increased educational attainment and reduced involvement in crime reported in earlier cost-benefit analyses. The findings are robust to corrections for multiple hypothesis testing, sensitivity analysis using a range of discount rates, and Monte Carlo analysis to account for uncertainty in outcomes.

Economic and health benefits assessments of air quality changes often quantify and report changes in deaths at a given point in time. The typical approach uses a method that attributes air pollution-related health impacts to a single year air quality change (or “pulse”). The perspective on benefits from these static pulse analyses can be enhanced by conducting a dynamic population assessment using life tables. Such analyses can provide a richer characterization of health risks across a population over a multiyear time horizon. In this article, we use the life table approach to quantify cumulative counts of reductions in PM-attributable deaths and life-years gained due to overlapping impacts of PM2.5 changes over a multiyear period, using case studies of air quality improvements in the USA and Chile. Our comparison of health risk and economic valuation for the two approaches shows life table analysis can be a valuable adjunct analysis to the pulse approach though both come with their own set of uncertainties and limitations. If applied jointly, they provide a broader characterization of how air quality actions can change populations in terms of life-years lost, life expectancy, and age structure. The value of these metrics is illustrated using case studies with dramatically different air quality reduction trajectories.

Disruptions in routine immunization caused by COVID-19 put African countries with large vaccine-preventable disease burdens at high risk of outbreaks. Abbas et al. (2020) showed that mortality reduction from resuming immunization outweighs excess mortality from COVID-19 caused by exposure during immunization activities. We leverage these estimates to calculate benefit-cost ratios (BCRs) of disrupted immunization and apply cost of illness (COI) and value of statistical life-year (VSLY) approaches to estimate the cost of excess child deaths from eight vaccine-preventable diseases. BCRs were computed for each country, vaccine, and Expanded Program on Immunization visit. Secondary estimates that include the cost of providing immunization are presented in scenario analysis. Suspended immunization may cost $4949 million due to excess mortality using the COI approach, or $34,344 million using the VSLY approach. Likewise, excess COVID-19 deaths caused by exposure from immunization activities would cost $53 and $275 million using the COI and VSLY approaches, respectively. BCRs of continuing routine immunization are 94:1 using COI and 125:1 using VSLY, indicating that the economic costs of suspending immunization exceed that of COVID-19 deaths risked by routine immunization. When including the costs of providing routine immunization during the COVID-19 pandemic, the BCRs are 38:1 and 97:1 using the COI and VSLY approaches, respectively.

This article describes the process from first proposals in the early 1990s to project completion many years later for seven large Swedish road and railway projects. The purpose is to find reasons for the massive cost overruns as well as explanations for why projects are brought to completion despite much higher costs than when the decision to build was made. Cost overruns are set in an institutional context to highlight the interplay among national, regional, and local policymakers. National investment programs are seen as promises by other parts of society, irrespective of whether project costs increase during the process toward procurement and implementation. Another aspect is that the infrastructure manager’s administrative framework currently makes it impossible to compare costs in contracts with final cost, meaning that there is no institutionalized learning process in place. Design preparations and the estimation of costs for new projects must therefore be done without an understanding of what has been working well in the implementation of previous projects. While Benefit-Cost Analysis (BCA) played no role in the planning of the seven projects, the article sends a stark warning that early cost estimates provide poor input for assessing project rate of return.

This article conducts a benefit-cost analysis of a child allowance. Through a systematic literature review of the highest quality evidence on the causal effects of cash and near-cash transfers, this article produces core estimates on the benefits and costs per child and per adult of increasing household income by $1000, which can be used for any cash or near-cash program that increases household income. We then apply these estimates to three child allowance proposals, with the main proposal converting the $2000 Child Tax Credit in the federal income tax code into a fully refundable and more generous child allowance of $3600 per child ages 0–5 and $3000 per child ages 6–17, as enacted for 1 year in the American Rescue Plan. Aggregate costs and benefits are estimated via micro-simulation. Our estimates indicate that making the $2000 Child Tax Credit fully refundable and increasing benefits to $3000/$3600 would cost $97 billion per year and generate social benefits of $929 billion per year. Sensitivity analyses indicate that the results are robust to alternative assumptions and that each of the three child allowance proposals produces a very strong to an extraordinarily strong return for the U.S. population.

Due to COVID-19, many households faced hardships in the spring of 2020 – unemployment, an uncertain economic future, forced separation, and more. At the same time, the number of people who participated in outdoor recreation in many areas increased, as it was one of the few activities still permitted. How these experiences affect the public’s willingness to pay (WTP) for environmental public goods is unknown. During the early months of the pandemic, we conducted a stated preference survey to value statewide water quality improvements in Delaware. While a majority of participants report experiencing hardship of some sort (economic, emotional, etc.), mean household WTP declined by only 7 % by May 2020.

The paper investigates the validity of individual perceptions of heart disease risks, and examines how information and risk perceptions affect marginal willingness to pay (MWTP) to reduce risk, using data from a stated preference survey. Results indicate that risk perceptions held before receiving risk information are plausibly related to objective risk factors and reflect individual-specific information not found in aggregate measures of objective risk. After receiving information, individuals’ updates of prior risk assessments are broadly consistent with Bayesian learning. Perceived heart disease risks thus satisfy construct validity and provide a valid basis for inferring MWTP to reduce risk. Consistent estimators of the relationship of MWTP to endogenously perceived risk are developed. Estimating MWTP based on objective rather than subjective risks causes misleading inferences about benefits of risk reduction. An empirical case study shows that estimated benefits may be as much as 60–98 % higher when estimated using individuals’ heterogeneous perceptions of risk than when using aggregate estimates of objective risk. The main contributions include assessing the validity of risk perceptions and their updating, consistently estimating the relationship between MWTP and endogenously perceived risk, and demonstrating the importance of employing risk perception information for accurate benefit measurement.

Many economic analyses, including those that address the COVID-19 pandemic, focus on the value of averting deaths and do not include the value of averting nonfatal illnesses. Yet, incorporating the value of averting nonfatal cases may change conclusions about the desirability of the policy. While per case values may be small, the number of nonfatal cases is often large, far outstripping the number of fatal cases. The value of averting nonfatal cases is also increasingly important in evaluating COVID-19 policy options as vaccine- and infection-related immunity and treatments reduce the case-fatality rate. Unfortunately, little valuation research is available that explicitly addresses COVID-19 morbidity. We describe and implement an approach for approximating the value of averting nonfatal illnesses or injuries and apply it to COVID-19 in the USA. We estimate gains from averting COVID-19 morbidity of about 0.01 quality-adjusted life year (QALY) per mild case averted, 0.02 QALY per severe case, and 3.15 QALYs per critical case. These gains translate into monetary values of about $5300 per mild case, $11,000 per severe case, and $1.8 million per critical case. While these estimates are imprecise, they suggest the magnitude of the effects.

Under the current practice of benefit-cost analysis, the direct economic benefits produced by a newly built transit facility are assessed based on how it affects travel time and various costs that are associated with transport needs and travel behavior. However, the time-saving-based benefit calculation approach has been questioned and criticized. Given the strong correlation between accessibility and land value, we propose the access-based land value benefit assessment as an alternative, and apply this assessment method to analyzing the Second Avenue Subway project in Manhattan, New York. The primary principle of the access-based method is that the economic value of a transport project’s intangible gains is largely capitalized by nearby properties’ value appreciation, which is directly caused by improved transport accessibility. We find that: (i) the actual travel time saving is lower than originally forecast; (ii) a strong positive correlation between residential property value and job accessibility by transit is observed; (iii) the appreciation in sold property value and rented property value both far exceed total project cost; and (iv) such results support the decision to approve and construct the Second Avenue Subway.