This paper is based on public comments I submitted in 2023 to the Office of Management and Budget (OMB) on the draft revisions to its Circular A-4 guidance on “Regulatory Analysis.” It includes my comments as submitted and a “prologue” and “epilogue” written after OMB published the 2023 version of Circular A-4. The major issues discussed in my and the other public comments on the 2023 revisions have been long been, and will remain, central to the practice of regulatory BCA. My public comments compare the 2023 revisions to the principles and practice of standard efficiency-based benefit–cost analysis (BCA). Standard BCA is a tool to evaluate whether regulations fix market failures and improve economic efficiency. The 2023 revisions to Circular A-4 depart from standard BCA in important ways.

This article presents my 2023 peer review panel comments on the 2023 Office of Management and Budget (OMB) Circular A-4 and offers recommendations for future revisions of this circular. The Prologue section introduces my official peer review comments and indicates how the structure of my comments was tailored to the guidelines established by the OMB. The main section consists of my 2023 peer review comments as they were submitted to OMB. I recommended changes in the draft Circular A-4 to increase the discount rate from the 1.7% rate that OMB proposed, to report domestic benefits whenever global benefits are reported, to adopt a behavioral transfer test for the use of behavioral economics findings, to update the procedures for estimating the value of a statistical life, and to abandon the proposed distributional weights. The most problematic component of the new Circular A-4 is the OMB distributional weights, which will shift the role of benefit–cost analyses away from the current role of providing an efficiency-oriented test. The Epilogue to my comments summarizes how the final version of Circular A-4 differs from the draft version and how future administrations might revise Circular A-4 after President Trump rescinded it.

The current method used by the US Government to calculate benefits and costs does not accurately measure the monetary value of some regulations. The problem is that the method fails to recognize the possibility that individual valuations, reflecting judgments in a relatively isolated, uncoordinated situation, might be significantly different from individual valuations in a situation of coordination. For example, people might be willing to pay $X for a good, supposing that other people have that good, but might be willing to pay $Y to abolish that good, supposing that no one will have that good. Or people might be willing to pay $X to protect members of an endangered species in their individual capacity, but far more than $X for the same purpose, assuming that many others are paying as well; one reason may be that an individual expenditure seems futile. We sketch, identify, and explain this unmeasured value, which we define as coordination value, meant as an umbrella concept to cover several categories of cases in which individual valuation measured in the uncoordinated state might be inadequate. Changing the methodology of benefit–cost analysis to consider coordination value would present serious empirical challenges, but would eliminate the estimation error.

Conventional benefit–cost analysis plays an important role in informing policy decisions, encouraging systematic investigation of the positive and negative impacts of alternative policies. It is based on strong normative assumptions, however. To measure individual wellbeing, the conventional approach relies on individuals’ willingness to exchange their income for the outcomes they experience. To measure societal welfare, it relies on simple aggregation of these values across individuals. In this “Ethics and Benefit–Cost Analysis” special issue, we explore alternative conceptions of individual and societal welfare, their application, and the implications, from both practical and ethical perspectives.

Cannabis is the most commonly used illicit drug worldwide. In countries with repressive drug policies, the costs of its prohibition plausibly outweigh the benefits. We conduct a cost–benefit analysis of cannabis legalization and regulation in the Czech Republic, taking into consideration alternative scenarios designed using parameters from the known effects of cannabis legalization in selected U.S. states, Canada, and Uruguay. Our analysis focuses on tax revenues, law enforcement costs, the cost of treatment and harm reduction, and the value of Quality Adjusted Life Years (QALYs). Under all the projected scenarios, the identified benefits of legalizing cannabis for personal use exceed the potential costs. The estimated net social benefit of legalization is in the range of 34.4 to 107.6 million EUR per year (or between 3.2 and 10.1 EUR per capita), depending on the size of the cannabis market and the development of cannabis prices after legalization.

This paper studies the vulnerability of the pivotal mechanism with respect to manipulation by groups. In a lab experiment, groups decide on the implementation of various alternatives, some of which imply opposite interests for the two subgroups. We investigate the occurrence of tacit and explicit collusion by allowing for communication within subgroups in one treatment and prohibiting it in another. Even though all agents’ preferences are common knowledge and there exists a simple symmetric collusive strategy for one subgroup, we find little evidence for tacit collusion. Only when explicit communication is allowed, collusion is established. A behavioral model using quantal response equilibrium in which subjects have beliefs over the correlation of errors of same-type subjects helps explain the main features of our data.

We conduct laboratory experiments for the multi-unit Vickrey auction with and without advice to subjects on strategy-proofness. The rate of truth-telling among the subjects without advice stays at 20%, whereas the rate increases to 47% among those who have received advice. By conducting similar experiments for the pay-your-bid auction, which is not strategy-proof, we confirm that the increase in truth-telling is due significantly to the net advice effect (i.e., the effect beyond the so-called experimenter demand effect). Moreover, we find that providing advice improves efficiency in the Vickrey auction, particularly in the early periods, when the subjects are less experienced. In general, subjects tend to overbid in Vickrey auction experiments. Our results indicate the possibility that providing simple advice decreases such overbidding by promoting a better understanding of the strategy-proofness of the Vickrey auction. Strategy-proof mechanisms are sometimes criticized because players often fail to recognize the benefit of telling the truth. However, our observations show that introducing advice on the property of strategy-proofness helps them behave “correctly.”

This paper introduces a new matching mechanism that is a hybrid of the two most common mechanisms in school choice, the Boston Mechanism (BM) and the Deferred Acceptance algorithm (DA). BM is the most commonly used mechanism in the field, but it is neither strategyproof nor fair. DA is the mechanism that is typically favored by economists, but it is not Pareto efficient. The new mechanism, the Secure Boston Mechanism (sBM), is an intuitive modification of BM that secures any school a student was initially guaranteed but otherwise prioritizes a student at a school based upon how she ranks it. Relative to BM, theoretical results suggest that sBM is an improvement in terms of strategyproofness and fairness. We present experimental evidence using a novel experimental design that confirms that sBM significantly increases truth-telling and fairness. Relative to DA, theoretical results suggest that sBM can be a Pareto improvement in equilibrium but the efficiency comparison of sBM and DA is theoretically ambiguous. We present simulation evidence that suggests that sBM often does Pareto dominate DA when DA is inefficient, while sBM and DA very often overlap when DA is efficient. Overall, our results strongly support the use of sBM over BM and suggest that sBM should be considered as a viable alternative to DA.

Healthcare technologies are often appraised under considerable ambiguity over the size of incremental benefits and costs, and thus how decision-makers combine unclear information to make recommendations is of considerable public interest. This paper provides a conceptual foundation for such decision-making under ambiguity, formalizing and differentiating the decision problems of a representative policy-maker reviewing the results from an economic evaluation. A primary result is that presenting information to regulators in an incremental cost-effectiveness ratio or cost-effectiveness analysis (CEA) format instead of a net monetary benefit or cost–benefit analysis (CBA) framework may induce errors in decision-making when there exists ambiguity in incremental benefits and decision-makers use well-known decision rules to combine information. Ambiguity in incremental costs or the value of the cost-effectiveness threshold does not distort decision-making under these rules. In reasonable contexts, I show that the CEA framing may result in the approval of fewer technologies relative to CBA framing. I interpret these results as predictions on how the presentation of information from economic evaluations to regulators may frame and distort recommendations. All the results extend to non-healthcare contexts.

A BioBlitz is a rapid and intensive survey of a specific geographic area that brings together experts and often lay participants to assess biodiversity, typically of macrobiota that are easily observed and identifiable on-site. This concept has become popular across taxonomic fields, attracting interest globally to increase knowledge of local biodiversity. Inspired by the success of the approach, we undertook a ‘ParasiteBlitz’ at an unexplored locality (Stono Preserve, Charleston, South Carolina, USA) to determine its feasibility for parasites, whose assessment of diversity is largely neglected worldwide. We assembled a team of parasitologists with complementary expertise. Over 12 days (3 days in each habitat) in April 2023, we intensively screened fishes and aquatic invertebrates for parasites, and sampled sediment and water for environmental DNA (eDNA) metabarcoding from four aquatic habitats: wetland, freshwater pond, brackish impoundment, and tidal creek. We incorporated assistance from non-parasitologists and students. Details on methodologies and results are provided in individual papers in this Special Collection. Traditional methods revealed the presence of ca. 100 species of seven major metazoan parasite taxa, and the eDNA survey yielded over 1,000 amplicon sequence variants identified as parasites, most with sequences unmatched in GenBank, and resulting in only a few species identified as named species in the one-year post-Blitz timeframe we imposed upon ourselves for identification. Limitations and challenges of the ParasiteBlitz are discussed, and our results support that this approach can be effective for rapid discovery of the dimensions of parasite assemblages in an understudied environment and contribute to parasitology knowledge.

This paper builds on Hsieh and Klenow’s (2009) model to offer a refined analysis of how input misallocations impact aggregate total factor productivity (TFP). We enhance the original model by relaxing the assumption of uniform input prices and adopting an econometric approach to estimate parameters using firm-level data. Estimation of model parameters and allocation efficiency is based on the system of input demand and the production function. We use an indirect inference approach to estimate the system to avoid maximum likelihood estimation, which often faces convergence issues, when there are numerous constraints. We demonstrate our model using the US firm-level manufacturing panel data from 1975 to 2010. Our final sample contains 55,518 observations. We divide the manufacturing industry into seven major categories. Our findings indicate that between 1975 and 2010, the average productivity growth rate was 2.8% but could have reached 3.2% without misallocation, highlighting the substantial gains possible through better resource allocation.

Public sector allocative decisions should reflect, as far as possible, the preferences of those affected by the decisions. Conventional benefit–cost analysis (BCA) will simply aggregate individuals’ private willingness-to-pay (WTP) over all affected individuals to estimate the total benefits of a policy that delivers a public good. Given the nature of a public good, it is not unreasonable to consider that an individual may have altruistic preferences over the consumption of the public good by others. In this paper, we set out the theoretical underpinnings for a new citizen-based WTP, informed by political philosophy. Our model extends the standard social utility model (Bergstrom, 2006) of WTP for a public good when individuals are altruists by incorporating a Veil of Ignorance (VoI; Harsanyi, 1955). Our findings show that our WTP (Citizen) correctly includes altruistic as well as distributional preferences of individuals in society into WTP for use in a BCA. When WTP (Citizen) are aggregated for use in a BCA, equal weight is given to each individual’s preference and the BCA will correctly identify potentially Pareto-improving projects in a consistent manner.

Over the last century, the United States has witnessed three approaches to achieving better regulatory outcomes: the removal of “economic” regulations in certain sectors; regulatory impact analysis (RIA) of new “social” regulations; and retrospective analysis of existing regulations. This article reviews the rationale for each approach, the results to date, and the remaining challenges. It finds that both institutional and technical factors influence the success of reform efforts.

The so-called Flyvbjerg database is the largest source of data on the performance of major investment projects. It has generated influential analyses of the magnitude of and reasons for cost overruns and demand shortfalls in major projects. Those analyses have demonstrated, among other things, the systematic presence of large forecast errors in both construction costs and in user demand in the first year of operation. They have also linked those results to the social welfare consequences of the underlying projects, suggesting that the large and systematic forecast errors are indicative of welfare destruction. Given how influential those analyses have been, this paper examines the link between the database, empirical analyses thereof, and social benefit–cost analysis (BCA). To that end, both the measurement of variables in the database and the estimation of forecast errors are contrasted against BCA. The conditions for the estimated forecast errors to approximate those obtained from a BCA are spelled out, and the scope for drawing welfare conclusions based on those estimates is discussed. Furthermore, numerical simulations are presented to explore whether the estimated forecast errors do indeed imply likely welfare destruction. The simulations suggest that as large as the forecast errors are, welfare destruction is no foregone conclusion.

In 2023, the U.S. Office of Management and Budget (OMB) issued guidance documents that specified new procedures for assessing prospective government regulations (Circular A-4) and economic policies more generally (Circular A-94). These revisions to long-standing guidance were not minor updates but shifted policy analyses from an efficiency-oriented perspective to a redistributive approach. OMB broadened the guidelines for reporting distributional consequences of policies and also specified how policy impacts on different income groups should be weighted. The weights assume that the social welfare function is governed by the sum of identical individual utility functions, each of which exhibits a substantial rate of diminishing marginal utility of income. The resulting weights provide a premium for households below the median-income level and a considerable penalty for those at higher-income levels. Application of the weights to property losses creates potentially substantial inefficiencies. If based on current empirical evidence on the income elasticity of the value of a statistical life rather than assuming that there is a complete offset of the weights, application of the weights to mortality risk valuation would generate inequities in protection.

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.

Compromised kidney function is associated with an array of environmental contaminants and pathogens that may be considered for regulation. However, there are few valuation estimates for kidney effects for use in benefit–cost analyses, particularly willingness-to-pay estimates. This paper is one of several surveys valuing morbidity developed by the OECD Surveys to elicit Willingness-to-pay to Avoid Chemicals-related negative Health Effects project, which aims to improve the basis for benefit–cost analyses. We report the results of a stated preference survey valuing reduced the risk of symptomatic chronic kidney disease, filling an important gap in the valuation literature and addressing a need for applied benefits analysis of chemical regulation. The survey was administered to representative samples in each of 10 countries: Canada, Chile, China, Denmark, Germany, Italy, Norway, Türkiye, the United Kingdom, and the United States. The mean (median) WTP for an average reduction of 3.5 in 1,000 of the risk of serious kidney disease over 5 years is $2,609 ($764), corresponding to a mean (median) value per statistical case (VSC) of chronic kidney disease of $805,000 ($224,000). The mean VSC varies between $700,000 for Canada and $1,200,000 for Türkiye.

Both Republican and Democratic administrations make regulatory and funding decisions with close reference to benefit–cost analysis (BCA). With respect to regulation, there has been a great deal of academic discussion of BCA and its limits, but almost no attention has been paid to the role of BCA in government funding. That is a serious gap, not least in connection with climate-related risks, such as wildfire, drought, extreme heat, and flooding. Office of Management and Budget (OMB) Circular A-94 sets out guidelines for the BCA required when people are applying to many federal discretionary grant programs. Through Circular A-94, OMB has long required applicants to demonstrate that the benefits of their projects would exceed the costs. But under Circular A-94 as it stood for many years, efficiency-based BCA could produce results that fail to maximize welfare and that are also highly inequitable. The 2023 revision of Circular A-94 focuses more directly on welfare and equity, which are now – not uncontroversially – being brought directly into policy. At the same time, the new Circular A-94 raises fresh questions about how best to promote welfare, and to consider equity, in practice. This article explains the economic foundations for promoting welfare through distributional weighting – and how the old BCA guidance fell short. It then offers recommendations on how to operationalize distributional weighting on the ground specifically for government spending programs – and for BCA more broadly.

Unweighted benefit–cost analysis (BCA) based on aggregate willingness to pay might be, at long last, falling into disrepute, as it is widely recognized that it exhibits a bias toward the wealthy, and as alternatives are appearing more and more practicable. However, the choice of alternatives is often framed in terms of choosing an alternative metric to willingness to pay in money, such as willingness to pay in healthy life years, or a measure of subjective well-being. It is argued in this paper that (i) a simple summation of individuals’ willingness to pay in any numeraire (e.g., money, healthy life years) is bound to generate non-transitivity issues in a similar way as money-based BCA, and (ii) a metric such as subjective well-being involves distributional value judgments that are too specific to reflect the relevant spectrum in the public debate. The “orthodox” weighted BCA method, which links BCA to an underlying social welfare function, offers more flexibility and guarantees transitive choices. Fortunately, in some relevant cases, these various methods may provide similar results, and the main options currently proposed all give greater weight to the worse off in the population than does unweighted BCA.