A uniform value of a statistical life (VSL) is part of established practice within the federal government. Some people have applauded a uniform VSL on the ground that it respects the equality of persons; takes harm to poor people as seriously as it does harm to wealthy people; avoids expressive harms; and builds appropriate wealth redistribution into regulatory policy. Other people have strenuously objected to a uniform VSL, emphasizing that to reduce mortality risks, poor people are willing to pay less than rich people are, and urging that poor people should not have to pay more than they are willing to pay. Whether a uniform VSL is in the interest of poor people depends on whether we are dealing with subsidies or regulations. In the case of subsidies, a uniform VSL is highly likely to benefit poor people. If we are dealing with regulations, we cannot know whether a uniform VSL helps or harms poor people without knowing the incidence of costs (and benefits).

The impact and economic merits of President Biden’s Executive Order 13985 on equity depend on how the executive order is implemented. While policy discussion to date has focused on equitable outcomes, we propose framing risk equity policies in terms of equitable risk tradeoff rates based on six policy guidelines. The starting point for ex ante evaluation of equity for mortality risk policies should be the symmetric application of the value of a statistical life (VSL) to all groups. Because of the substantial heterogeneity in VSLs by income and demographic characteristics, symmetric tradeoff rates generate subsidies and deficits relative to private values of risk. Efforts to provide for distributional preferences should be grounded in an understanding of the differentials already provided through application of a uniform VSL. Targeting government programs to specific groups ex ante should be coupled with estimates of the efficiency loss based on symmetric tradeoff rates and the implicit tradeoff rate ratio relative to the average VSL needed to support the redistributive policy. Here, we propose equity guidance that could be incorporated in a revised version of Office of Management and Budget Circular A-4. We contrast the ex ante equity guidance approach with the ex post risk equity evaluation procedure that is incorporated in the Biden Administration’s recently proposed Justice40 plan, where 40% of the benefits of existing programs must be targeted to certain minority groups without ex post examination of their cost effectiveness either feasible or currently planned.

The Biden administration has made equity a priority when issuing regulations, encouraging agencies to ensure that their regulations appropriately benefit and do not inappropriately burden disadvantaged groups. But scholarly examinations of agencies’ practices to date on understanding the distributional consequences of their regulations and on promoting equity have revealed significant gaps. In particular, agencies pay very little attention to the incidence of the costs of their regulations. The U.S. Environmental Protection Agency, for example, rarely considers the incidence of regulatory costs among disadvantaged groups, despite being an agency that conducts relatively complete benefit–cost analyses and explicitly analyzes environmental justice implications of its regulations. But this cost-blindness is a mistake; it presents a missed opportunity to use the current equity-focused momentum to make real improvements for disadvantaged groups that could have long-lasting effects. This essay calls for agencies to give more attention to the incidence of regulatory costs in order to identify needs and opportunities for grants and investments to disadvantaged groups. This approach could provide much-needed direction for a program like the Biden administration’s Justice40 initiative.

The generalized risk-adjusted cost-effectiveness (GRACE) analysis method modifies standard cost-effectiveness analysis (CEA), the primary method currently used worldwide to value health improvements arising from healthcare interventions. Generalizing standard CEA, GRACE allows for decreasing or even increasing returns to health. Previous presentations of GRACE have relied extensively on Taylor Series expansion methods to specify key model parameters, including those that properly adjust for illness severity and preexisting disability, consequences of uncertain treatment outcomes, and the marginal rate of substitution between life expectancy and health-related quality of life. Standard CEA cannot account for these sources of value or cost in its valuation of medical treatments. However, calculations of GRACE measures based on Taylor Series are approximations, which may be poorly behaved in some contexts. This paper provides a new approach for implementing GRACE, using exact utility functions instead of Taylor Series approximations. While any proper utility function will suffice, we illustrate with three well-known functions: constant relative risk aversion (CRRA) utility; hyperbolic absolute risk aversion (HARA) utility, of which CRRA is a special case; and expo-power (EP) utility, of which constant absolute risk aversion (CARA) is a special case. The analysis then extends from two-period to multiperiod models. We discuss methods to estimate parameters of HARA and EP functions using two different types of data, one from discrete choice experiments and the other from “happiness economics” methods. We conclude with some reflections on how this analysis might affect benefit-cost analysis studies of healthcare interventions.

There are increasing calls for concrete suggestions on how to account for distributional impacts in policy analysis. Within the context of benefit-cost analysis, per se, one possibility is to apply “distributional weights,” to inflate costs and benefits experienced by poor or disadvantaged groups. We distinguish between “utility-weights,” intended to correct for the bias in willingness to pay caused by diminishing marginal utility of income, and “equity-weights,” intended to account for the possibility that decision makers might have disproportional concern about the welfare of the poor or other disadvantaged groups. We argue that utility-weights are appropriate and necessary to maintain the legitimacy of BCA as a measure of aggregate welfare, but that equity-weights are inappropriate because they involve moral judgments that should remain in the domain of democratically accountable decision makers, and because they conflate information about both the welfare and equity impacts of policies, making it impossible for decision-makers to apply their own moral values to the assessment of tradeoffs between welfare and equity. We offer concrete suggestions regarding the application of utility-weights and the calculation of a set of metrics to provide intuitively comprehensible and useful information about, and allow decision makers to quantitatively assess the tradeoffs between, welfare and equity caused by specific policies.

Regulatory impact analyses of proposed environmental, occupational, and consumer product safety regulations often rely on a metric known as the Value per Statistical Case of Cancer (VSCC), that is, the public’s willingness to pay (WTP) for reductions in the risk of developing cancer. In this paper, we ask whether the VSCC depends on cancer survival prospects. We develop a simple theoretical model that shows that under standard assumptions the VSCC is decreasing in the chance of surviving cancer. We empirically test this prediction by means of a stated preference survey, where we ask subjects aged 45–60 from the general population in the Czech Republic to report information about their WTP for reductions in the risk of getting cancer. One half of the sample was told that, if they got cancer, the 5-year survival rate was 60 % (corresponding to the average survival chances across all types of cancer), while the other half was told that it was 75 %. Consistent with the theoretical model, we find that the VSCC is larger in the former group. The ratio between the VSCC of the two groups is approximately equal to the ratio between the conditional cancer mortality risks implied by the survey’s survival rates, suggesting that the VSCC is proportional to conditional cancer mortality. Our findings have important policy implications in the context of regulations that focus on pollutants linked to cancers with different chances of survival.

We make four main contributions in this paper related to the theory and practice of benefit–cost analysis (BCA). First, we show that most BCAs of policy interventions do not consider the welfare consequences in secondary markets, where goods or services can be complements or substitutes to those in the directly regulated markets. Second, we provide a general theoretical analysis for examining the sign of welfare effects in secondary markets, showing how the results depend on the welfare measure of interest and on whether the goods are complements or substitutes. We conclude that the welfare effects in secondary markets will typically be negative in cases most relevant for policy analysis. Third, we develop a straightforward tool that BCA analysts can use to evaluate the potential magnitude of secondary-market effects in particular applications. The tool itself highlights how secondary markets are likely to be relatively small in most circumstances. Finally, we illustrate use of the tool in different applications that provide further evidence that secondary-market effects are likely to be small.

The goal of natural resource damage assessment (NRDA) is to compensate the public for losses to natural resources from past or ongoing hazardous releases, including losses that may persist into the future. Compensation is delivered in the form of restoration projects. Resolving NRDA liability requires balancing losses and restoration benefits over multiple decades and converting them into a present value for calculating appropriate damages. For the past two decades, NRDA practitioners have used a real discount rate of 3 % to convert losses and benefits to a present value equivalent. That rate was based, in part, on real historical yields on risk-free debt (e.g., the real rate of return on 3-month Treasury bills). Declining interest rates on risk-free debt in recent years has led to suggestions to reexamine the historical consensus discount rate. This paper reviews two alternative conceptual paradigms for selecting a discount rate in NRDA cases: the social rate of time preference and discount rates for tort cases. We summarize historical data for empirically implementing the two paradigms and discuss the ramifications of the different options. Based on our review, we suggest maintaining the 3 % consensus as a practical solution to a range of empirical candidates within the two conceptual paradigms.

Border management is a government activity affecting immigration and the economy. Benefit–cost and equivalent decision analyses are used to evaluate U.S. border management for 2017. Controversial issues arise. Among these are the issue of standing and the values of asylum, a criminal career, child custodial care, foreign deaths, fiscal and labor market effects, and distributional weighting. Sixteen unique shadow prices (imputed marginal value) are computed. Those shadow pries are combined with proportions and levels of border management outcomes. The aggregate result is not only a large expected present value net benefit per year from managed outcomes of $46.6 billion but also a large residual unmanaged annual cost of $23.7 billion. Significant uncertainty exists, but estimated net benefits remain positive.