The value of a statistical life (VSL) establishes the money-risk tradeoff that U.S. government agencies have used for four decades to monetize the mortality reduction benefits of proposed regulations. This article advocates the adoption of the VSL more generally both for policy evaluation purposes and for setting the magnitude of regulatory sanctions involving fatalities. Agencies currently employ the inconsistent practice of using the VSL to set the stringency of regulations, while at the same time, reverting to very low monetary values of sanctions for violations that result in fatalities. Reform of penalty levels to reflect the VSL will require increasing the current statutory limits on regulatory penalties. Revamping the penalty structure also will incentivize private companies to incorporate the VSL in their corporate risk analyses. Government agencies, including those concerned with national defense, similarly could profit from greater expansion of the use of the VSL in policy decisions.

Most cost-benefit analyses assume that the estimates of costs and benefits are more or less accurate and unbiased. But what if, in reality, estimates are highly inaccurate and biased? Then the assumption that cost-benefit analysis is a rational way to improve resource allocation would be a fallacy. Based on the largest dataset of its kind, we test the assumption that cost and benefit estimates of public investments are accurate and unbiased. We find this is not the case with overwhelming statistical significance. We document the extent of cost overruns, benefit shortfalls, and forecasting bias in public investments. We further assess whether such inaccuracies seriously distort effective resource allocation, which is found to be the case. We explain our findings in behavioral terms and explore their policy implications. Finally, we conclude that cost-benefit analysis of public investments stands in need of reform and we outline four steps to such reform.

I calibrate an eco-epidemiological age-structured Susceptible-Infected-Recovered (SIR) model of the B.1.1.7 covid variant on the eve of the vaccination campaign in France, under a stop-and-go lockdown policy. Three-quarters of the welfare benefit of the vaccine can be achieved with a speed of 100,000 full vaccination per day. A 1-week delay in the vaccination campaign raises the death toll by approximately 2500, and it reduces wealth by 8 billion euros. Because of the large heterogeneity of the rates of hospitalization and mortality across age classes, it is critically important for the number of lives saved and for the economy to vaccinate older people first. Any departure from this policy has a welfare cost. Prioritizing the allocation of vaccines to the most vulnerable people save 70,000 seniors, but it also increases the death toll of younger people by 14,000. Vaccine nationalism is modeled by assuming two identical Frances, one with a vaccine production capacity and the other without it. If the production country vaccinates its entire population before exporting to the other, the global death toll would be increased by 20 %. I also measure the welfare impact of the strong French anti-vax movement, and of the prohibition of an immunity passport.

It has been demonstrated that irrationality reduces the efficiency of individuals’ allocations, as measured by their “true” or rational preferences. There is also evidence that poverty increases irrationality of different sorts. As a result, the net benefit to society of a cash transfer from taxpayers to welfare recipients may not be zero. The fact that the transfer will be allocated less efficiently by the recipients than by the taxpayers will reduce the value of the transfer, while if the transfer increases recipients’ rationality, it will increase the efficiency of the allocation of their pretransfer budgets, thus increasing the value of the transfer. The net effect on society will be positive or negative, depending in large part on the degree to which the transfer increases rationality. I model these effects in the context of present-biased preferences and explore the effect of irrationality, income, and the size of transfer on the value of transfers. I conclude that under a plausible range of conditions, transfers can generate a substantial positive net benefit. I also model the choices of a fully rational paternalist and find little support for paternalistic in-kind transfers.

Total cost estimates for crime in the USA are both out-of-date and incomplete. We estimated incidence and costs of personal crimes (both violent and non-violent) and property crimes in 2017. Incidence came from national arrest data, multi-state estimates of police-reported crimes per arrest, national victimization and road crash surveys, and police underreporting studies. We updated and expanded upon published unit costs. Estimated crime costs totaled $2.6 trillion ($620 billion in monetary costs plus quality of life losses valued at $1.95 trillion; 95 % uncertainty interval $2.2–$3.0 trillion). Violent crime accounted for 85 % of costs. Principal contributors to the 10.9 million quality-adjusted life years lost were sexual violence, physical assault/robbery, and child maltreatment. Monetary expenditures caused by criminal victimization represent 3 % of Gross Domestic Product – equivalent to the amount spent on national defense. These estimates exclude the additional costs of preventing and avoiding crime such as enhanced lighting and burglar alarms. They also exclude crimes against businesses and most white-collar and corporate offenses.

The “shutdown” economy of April 2020 is compared to a normally functioning economy both in terms of market and nonmarket activities. Three novel methods and data indicate that a full shutdown of “nonessential” activities puts market production about 25 % below normal in the short run. At an annual rate, a full shutdown costs $9 trillion, or about $18,000 per household per quarter. Employment already fell 24 million by early April 2020. These costs indicate, among other things, the value of innovation in both health and general business sectors that can accelerate the time when, and the degree to which, normal activity resumes.

There is a great deal of variability in estimates of the lifetime medical care cost externality of obesity, partly due to a lack of transparency in the methodology behind these cost models. Several important factors must be considered in producing the best possible estimate, including age-related weight gain, differential life expectancy, identifiability, and cost model selection. In particular, age-related weight gain represents an important new component to recent cost estimates. Without accounting for age-related weight gain, a study relies on the untenable assumption that people remain the same weight throughout their lives, leading to a fundamental misunderstanding of the evolution and development of the obesity crisis. This study seeks to inform future researchers on the best methods and data available both to estimate age-related weight gain and to accurately and consistently estimate obesity’s lifetime external medical care costs. This should help both to create a more standardized approach to cost estimation as well as encourage more transparency between all parties interested in the question of obesity’s lifetime cost and, ultimately, evaluating the benefits and costs of interventions targeting obesity at various points in the life course.

The idea of assessing the costs and benefits of public and private projects is not new to Europe, dating back to studies at the Ecole des Ponts et Chaussees (Paris) in the XIX century. Later on, in the last century, Benefit-Cost Analysis (BCA) in its current form has been more extensively used in the United States than in Europe. In the last two decades, however, there has been a rapid increase in its use in a number of European countries and at the European Union (EU) level. European governments often undertake tasks that would be done by private companies in the United States, such as the provision of transport, energy, water and waste management, health services, etc. In the United States the focus of BCA has often been regulatory impact analysis, rather than public project evaluation. One might, therefore, expect that Europeans might approach some things differently from their American counterparts and that new insights might result from these efforts. The articles in this symposium, taken from the recent European Society for Benefit-Cost Analysis (SBCA) conference in Toulouse, illustrate some of these differences and some converging themes.

A commonly assumed reason for the delegation of authority from a legislature (politicians) to bureaucracies is that the bureaucrats have an information advantage over the politicians, including knowledge of cost–benefit analysis (CBA). But it is reasonable to assume that the bureaucrats use their information advantage by taking all relevant aspects of policy into account? We model the use of CBA using a delegation model and then test the theoretical predictions with empirical data collected from five Swedish government agencies. The empirical results lend support both for the hypothesis that risk aversion concerning the environmental outcome, the bureaucrats’ environmental attitudes, and the cost of taking CBA information into account have a considerable impact on the probability of using information from a CBA. Hence risk averse and bureaucrats with strong environmental preferences are less likely and bureaucrats with low cost of doing a CBA more likely than other bureaucrats to use CBA information. Finally, a binding governmental budget constraint may positively influence a bureaucrat’s choice of using CBA information. A tentative conclusion is therefore that it may be possible to increase the use of CBA by making the budgetary consequences of policies much clearer and demanding due consideration of costs.

Benefit–cost analysis (BCA) is often viewed as measuring the efficiency of a policy independent of the distribution of its consequences. The role of distributional effects on policy choice is disputed; either: (a) the policy that maximizes net benefits should be selected and distributional concerns should be addressed through other measures, such as tax and transfer programs or (b) BCA should be supplemented with distributional analysis and decision-makers should weigh efficiency and distribution in policy choice. The separation of efficiency and distribution is misleading. The measure of efficiency depends on the numéraire chosen for the analysis, whether monetary values or some other good (unless individuals have the same rates of substitution between them). The choice of numéraire is not neutral; it can affect the ranking of policies by calculated net benefits. Alternative evaluation methods, such as BCA using a different numéraire, weighted BCA, or a social welfare function (SWF), may better integrate concerns about distribution and efficiency. The most appropriate numéraire, distributional weights, or SWFs cannot be measured or statistically estimated; it is a normative choice.

Biodiversity points are a quantitative measure for biodiversity. For over a decade, biodiversity points are being applied in the Netherlands for measuring the impact of roads, enclosure dams, and other water management projects on the non-use value of biodiversity. Biodiversity points are quite similar to the quality-adjusted life years used for cost-effectiveness analysis of healthcare treatments. Biodiversity points can be calculated by multiplying the size of the ecotope (e.g., number of hectare), the ecological quality of the ecotope (0–100 %), and the ecological scarcity of each type of ecotope. For many infrastructure projects, the impact on the non-use value of biodiversity can be a principal purpose or a major co-benefit or trade-off, for example, for a park, a fish sluice, a road, an ecoduct, an enclosure dam, or a marine protected area. Biodiversity points are a simple, transparent, and standardized way to aggregate and quantify the qualitative or ordinal assessments by ecological experts. For measuring the non-use value of biodiversity, they are also more informative than valuation by revealed or stated preferences methods. This paper provides the first overview of the application of this method in the Dutch practice of cost–benefit analysis. It also discusses its merits and limitations. The calculation and use of biodiversity points are illustrated by four case studies.

Despite repeated calls for retrospective regulatory review by every President since the 1970s, progress on implementing such reviews has been slow. We argue that part of the explanation for the slow progress to date stems from misalignment between the goals of regulatory review and the institutional framework used for the review. We define three distinct goals of regulatory review – the rule relevance goal, the rule improvement goal, and the regulatory learning goal. We then examine the text of the Presidential Executive Orders and major Congressional legislation addressing retrospective review, and document which goals were targeted and which institutions were used to conduct the reviews. We find that the U.S. federal government has almost always sought review of one rule at a time, conducted by the agency that issued or promulgated the rule and that these reviews tend to focus on rule relevance and costs. This institutional framework for retrospective review – one rule, assessed by the promulgating agency, focused on relevance and cost – is only well-suited to a narrow interpretation of the rule improvement goal. We then review alternative institutional structures that could better meet the rule improvement goal and the broader regulatory learning goal across multiple rules and agencies, and we offer recommendations for developing new guidance and institutions to promote multiagency regulatory learning.

Although a carbon value has often been integrated in the frameworks established to guide public decision-making, benefit-cost analysis (BCA) has played no more than a minor role in the design of climate policies. It is urgently necessary to promote BCA in this area, and there is currently a unique opportunity for doing so. Major countries are designing new packages in order to meet their commitments, as illustrated by the European Green Deal, recent decisions on the part of the Biden Administration, and the creation of a Chinese national carbon market. These constructive processes must be based on BCA. BCA is absolutely necessary in order to achieve net-zero emissions by 2050 at a reasonable cost. Indeed, abatement costs across and within sectors, and across and within countries, are extremely heterogeneous, and many of the policy instruments in use (subsidies, feed-in tariffs, technical standards, etc.) overlap inefficiently. The instrumental debate between carbon pricing and other instruments is sterile if it merely remains at the level of stating principles. BCA can help on this point too, by specifying comparisons between alternatives, identifying complementarities, and selecting the most relevant combinations of instruments. Its scope should therefore range from setting benchmarks for carbon pricing to assessing, e.g., green investments or measures to enhance carbon sinks. When applied to decarbonization policies, BCA requires firstly the selection of a carbon value, in order to monetize the climate benefits of investments and policies. However, the whole assessment framework must be updated, including the time horizon, the discount rate, the cobenefits of climate mitigation actions, and the pricing of climate risks. We show that such an updated framework leads to an upward revision in the assessment of the climate benefits of mitigation actions, and that combining the valuation of damages and cost-effectiveness approaches is necessary in order to meet the needs of policy assessment. Finally, there is a need to extend analysis beyond the efficiency criterion in order to deal with other dimensions of climate policies, particularly their distributive impacts. This requires specific analyses, which should be articulated with BCA and carried out at an early stage for a better implementation of climate policies than we have seen to date.

This paper sets out to explore to what extent integrating employment effects, equity, and risk aversion within cost–benefit analysis (CBA) affect the economic appraisal of a climate change adaptation project designed to protect against flood risk in a region of Bilbao (Basque Country, Spain). Four CBAs are conducted: (i) a standard CBA; (ii) a standard CBA considering equity; (iii) a standard CBA considering equity and employment; and (iv) a standard CBA considering equity, employment and risk aversion. All CBAs are conducted using a time frame of 2014–2080 and considering a 100-year return period under a middle of the road emission scenario (RCP4.5). A sensitivity analysis is also undertaken. Results suggest that the economic efficiency of the adaptation investment is contingent on what types of considerations are included within CBA. Integrating elements of employment, equity and risk aversion can strengthen or weaken the case for action (leading to higher or lower net-present values) and (depending on the discount rate chosen) may even be the deciding factor for determining whether a particular action should be carried out or not (whether the net-present value is positive or negative).

The problem of how to evaluate investments in airports has now been studied for over 50 years. This paper analyzes the use of different methods like cost–benefit analysis (CBA), economic impact analysis (EIA), and computable general equilibrium (CGE) models to address the question. It assesses the strength and weaknesses of each method, and it discusses which methods have been used in different countries. The paper argues that the CBA approach and the newer CGE modeling approach address the policy issue well and that both methods are appropriate, although improvements are possible, especially in the newer aspects of evaluation. Furthermore, more data intensive CGE models are able to analyze broader aspects of the evaluation question for which CBA has had difficulty. EIA does not address the problem satisfactorily, and it misleads air transport policy. But this evaluation contrasts sharply with practice. EIA has been extensively used to decide on airport investment. CGE approaches are very promising, though further work is needed for them to reach their full potential. This paper pays particular attention to the relationship between CBA and CGE in airport investment evaluation and also the possible role of wider economic benefits (WEBs) of aviation in evaluation.

Benefit-cost analyses of regulations address Kaldor-Hicks efficiency but rarely investigate the distribution of benefits and costs as experienced by low-income households. In order to fill this gap, this article assembles the available evidence to determine how regulations of the automobile industry may impact the well-being of low-income Americans. The scope of the investigation includes air pollution, safety and fuel-economy regulations. We find that performing benefit-cost analyses for low-income households is more challenging than commonly understood. Given the difficulties in completing distributional analysis with available information, the authors offer practical suggestions on how to change the federal data systems and the rulemaking process to ensure that information is collected about how future automobile regulations impact the well-being of the poor.

Mineral deposits of base metals, precious metals, and rare earth elements have been discovered on deep seabeds, and the commercial exploitation of these resources seems poised to begin after faltering for many years. The development of seabed resources could be socially beneficial if all goes well, but the industry faces daunting challenges and uncertainties. Emerging regulations and contracting mechanisms are the principal means for managing these uncertainties. This article recommends a complementary approach: the use of ex ante benefit–cost analysis of proposed seabed mining contracts that incorporates a fundamental uncertainty evaluation. We argue that such an ex ante evaluation will improve the state of information for the decision-making, reducing the risk of regulatory noncompliance or costly contract disputes after seabed mining begins.

This article describes a methodology for a risk-informed benefit–cost analysis that includes (i) risk analysis to quantify risk reduction benefits and (ii) uncertainty analyses to quantify probability distributions over costs and benefits. It also summarizes the lessons from 25 applications of this methodology to evaluate R&D projects of the Science and Technology Directorate of the Department of Homeland Security. The article then illustrates the methodology with a specific application to evaluate the benefits and costs of the Advanced Personal Protection System (APPS), a new garment system developed to protect wildland firefighters. The goals of the APPS project were to reduce risk and to improve comfort. The cost analysis revealed that the APPS garments are more expensive by about $279 per garment system. Total costs were roughly $7.3 million, including the upfront project cost and the increased 5 year cost of purchasing the APPS. Benefits from reduced injuries and fatalities resulted in 5 year benefits of about $19.3 million, with an NPV of $13.6 million in 2019 dollars. In the base case, the benefit–cost ratio was 2.87 and the return on investment was 187 % over 5 years. Taking the perspective of a decision-maker when the project was first funded in 2011, NPVs are $11,993,728, $10,025,519, and $7,967,479 in 2011 dollars for discount rates of 0, 3, and 7 % respectively. An uncertainty analysis of the NPV showed a large variability, ranging from the 5th percentile of $6.4 million to a median of $19.3 million to the 95th percentile of $43.7 million in 2019 dollars. This large range was primarily due to the uncertainty about the reduction of fatality and injury risks and the market penetration rates of the new garments.

Bystander programs contribute to crime prevention by motivating people to intervene in violent situations. Social media allow addressing very specific target groups, and provide valuable information for program evaluation. This paper provides a conceptual framework for conducting benefit–cost analysis of bystander programs and puts a particular focus on the use of social media for program dissemination and data collection. The benefit–cost model treats publicly funded programs as investment projects and calculates the benefit–cost ratio. Program benefit arises from the damages avoided by preventing violent crime. We provide systematic instructions for estimating this benefit. The explained estimation techniques draw on social media data, machine-learning technology, randomized controlled trials and discrete choice experiments. In addition, we introduce a complementary approach with benefits calculated from the public attention generated by the program. To estimate the value of public attention, the approach uses the bid landscaping method, which originates from display advertising. The presented approaches offer the tools to implement a benefit–costs analysis in practice. The growing importance of social media for the dissemination of policy programs requires new evaluation methods. By providing two such methods, this paper contributes to evidence-based decision-making in a growing policy area.