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.

Substance use disorder (SUD) is a public health crisis in the United States associated with significant economic costs including healthcare, criminal justice, productivity, and mortality and morbidity costs. In this paper, we present a tool for a customizable economic analysis that can be utilized by different recovery program owners and operators within the SUD continuum of care that considers these program’s operating and capital costs, location, size, and success rate. The goal of this tool is to provide owners and operators with an accessible tool that can estimate their individual program’s economic costs, benefits, and return on investment. In applications of the tool, we find that there are significant benefits associated with SUD recovery-oriented services, even with more conservative modeling of recovery benefits. Specifically, we find that a representative recovery housing program in Florida yields a net benefit of $143 million over 20 years with an associated return on investment of $22.19 per dollar invested. Further, we find that the net benefits of different recovery-oriented modalities including a recovery house, a recovery campus, and a residential inpatient program are positive, with returns on investment varying from nearly $22 per dollar invested to $1 per dollar.

In clinical trials involving experimental subjects who are also patients, what is supposed to become of the imperative to focus on the patient’s best interest? A second set of policy questions concerns patients who want to die. Are there limits to the imperative to let patients choose for themselves? Is commodification a threat to autonomy? When, if ever, do costs and benefits become decisively important? Can we know what to count as a cost-effective preparation for the next pandemic? When we put procedures in place to protect against abuse, is there any way to prevent such measures from becoming bureaucratic obstacles to accomplishing anything at all?

Public health emergencies sometimes require the restriction of civil liberties through social distancing: lockdowns, quarantines, the closure of public spaces and institutions, and so on. Social distancing measures can decrease mortality and morbidity, but they also cause social and economic harm. Policymakers have to make trade-offs between “lives and livelihoods,” while introducing only minimally necessary restrictions on civil liberties. Traditionally, cost-benefit analysis has played a central role in formulating these trade-offs. Recently, however, some philosophers have argued that the trade-offs should instead be made on the basis of contractualist moral theory. In this essay, I argue against the use of contractualism for this purpose.

There is a need to value health technologies in a way that accommodates their broader economic impacts and competing approaches for doing so have emerged. The Pareto principle (PP) requires policymakers to resolve intrapersonal trade-offs by deferring to the preferences of the individuals facing those trade-offs. Many broad value frameworks such as cost-utility analysis and its extensions, health-centric multicriteria decision analysis, and poverty-free life expectancy are not sufficiently deferential to these preferences, violating PP. I propose using the health-augmented lifecycle model (HALM) to value health technologies in a way that flexibly incorporates the interactions among health and economic factors – specifically mortality and morbidity risks, paid and unpaid work, consumption, leisure, and public and private transfer inflows and outflows--over the life course. It relies on individual preferences, satisfying PP. It is compatible with cost-benefit analysis, social welfare functions, and equivalent income approaches. I calibrate the HALM for the US setting and apply it to a pediatric vaccine.

Animal welfare is often ignored in decision-making, despite widespread agreement about its importance. This is partly because of a lack of quantitative methods to assess the impacts of policies on humans and nonhumans alike on a common scale. At the same time, recent work in economics, philosophy, and animal welfare science has made progress on the fundamental theoretical challenge of estimating the well-being potential of different species on a single scale. By combining these estimates of each species’ well-being potential with assessments of how various policies impact the quality of life for these species, along with the number of animals affected, we can arrive at a framework for estimating the impact of policies on animal health and well-being. This framework allows for a quantifiable comparison between policies affecting humans and animals. For instance, it enables us to compare human QALYs to animal QALYs tailored to specific species. Hence, the intrinsic value of animal welfare impacts of policies can be monetized on the same scale as market and non-market impact for humans, facilitating benefit–cost analysis. Many challenges remain though, including issues of population ethics, political feasibility, and new complexities in addressing equity and uncertainty.

As the world has become more digitally dependent, questions of data governance, such as ethics, institutional arrangements, and statistical protection measures, have increased in significance. Understanding the economic contribution of investments in data sharing and data governance is highly problematic: outputs and outcomes are often widely dispersed and hard to measure, and the value of those investments is very context-dependent. The “Five Safes” is a popular data governance framework. It is used to design and critique data management strategies across the world and has also been used as a performance framework to measure the effectiveness of data access operations. We report on a novel application of the Five Safes framework to structure the economic evaluation of data governance. The Five Safes was designed to allow structured investigation into data governance. Combining this with more traditional logic models can provide an evaluation methodology that is practical, reproducible, and comparable. We illustrate this by considering the application of the combined logic model-Five Safes framework to data governance for agronomy investments in Ethiopia. We demonstrate how the Five Safes was used to generate the necessary context for a more traditional quantitative study, and consider lessons learned for the wider evaluation of data and data governance investments.

Each year, 295,000 women die during and just after pregnancy, and 2.4 million babies die in the first month of their lives. In 2019, 2,160,000 neonatal deaths and 275,000 maternal deaths occurred in low-income and lower-middle-income countries alone, translating to a welfare loss equivalent to $426 billion and $36 billion for neonatal and maternal deaths, respectively. The total loss was $462 billion or almost 6 % of these countries’ combined GDP. In the sustainable development goals pledge, the world promised to reduce maternal deaths to 0.07 % and neonatal mortality to below 1.2 %, saving about 200,000 women and 1.2 million children from dying annually. However, on the current trajectory, maternal mortality is expected to decline to only 0.16 % and neonatal deaths to only 1.5 % by 2030. This article analyses the most cost-effective way to reduce maternal and neonatal deaths – Increase coverage of basic emergency obstetric and newborn care from 68 to 90 % combined with increased family planning services in 55 low-income and lower-middle-income countries which account for around 90 % of the burden of maternal and neonatal mortality globally. The proposed package will require $3.2 billion per year more investment and will deliver benefits worth $278 billion per year in avoided deaths and higher economic growth. It will also yield a demographic dividend benefit equivalent to $25 billion annually. For every $1 invested, the social and economic benefits are estimated to be $87. The benefit-cost ratio is 87.

Behavioural economists often claim that their policy recommendations are justified by cost–benefit analysis (CBA), but without adequate explanation of the methodology they have in mind. I sketch the outlines of a CBA methodology that is compatible with the findings of behavioural economics and is in accord with my account in Sugden (2018) of a well-functioning market as a network of opportunities for mutually beneficial transactions. The key idea is that the CBA of a project is concerned only with effects that are not transmitted through voluntary interactions. I illustrate this proposal by considering the appraisal of fuel economy mandates.

The traditional concerns about farm animal welfare have centred around the impact of intensive environments and management practices on the animal. This emphasis on the physical environment is changing, however, with greater consideration being given to animal factors and in particular to the selective breeding of farm animals. In this paper we use examples from our own research on dairy cattle and sheep breeding that have made positive and practical contributions towards reducing welfare problems by creating more balanced breeding programmes. In both examples, inclusion of health and fitness traits into breeding indexes can be shown to be more profitable than selecting on production traits alone. In addition, we propose that in principle animal breeding combined with economics research can make a more general contribution towards resolving animal welfare issues, by providing a framework for the quantitative evaluation of the costs and benefits of an animal production system. The advantage of the approaches currently used in multi-trait selection is that they transform all traits (production-based or welfare-based) to a common currency allowing direct comparisons of costs and benefits. Currently the weights applied to traits reflect their economic value to the producer. This approach is likely to underestimate non-economic welfare aspects such as the pain or discomfort associated with lameness, and new approaches are needed to more fully account for these non-economic welfare costs. We therefore propose that consideration is given to the use of approaches such as contingent valuation, which has been widely used in economics to derive values for non-economic activities. The question of who would pay for the addition of these welfare costs to a breeding index remains open, but it would seem most reasonable to treat these as a public good and pay for them as such through appropriate mechanisms.

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.

Viruses and related graft-transmissible pathogens cause diseases that cost the grape industry billions of dollars annually if left uncontrolled. The National Clean Plant Network (NCPN), a USDA Farm Bill program, is an organization of clean plant centers that produce and maintain virus-tested foundation vine stocks and distribute propagation material derived thereof to nurseries and growers to minimize the introduction of viruses and virus-like diseases into the vineyard. Foundation Plant Services (FPS) is the major NCPN-grapes center. We examined the economic impacts of public investments in FPS from 2006 to 2019. By focusing on grapevine leafroll disease, our analyses revealed a benefit-cost ratio ranging from 22:1 to 96:1, with a 5% and a 20% disease infection rates in commercial vineyards, respectively. A welfare analysis was consistent with grape growers and nurseries capturing most (64–98%) of the benefits from adopting clean planting material compared with winemakers and other actors in the downstream wine supply chain system. This study provided new insights into the returns to public investments in a clean plant center and documented strong financial incentives for higher adoption of clean vines derived from virus-tested stocks, while justifying continued support of NCPN centers from public and private sectors.