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.

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.

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.

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).

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.