The social welfare function (SWF) framework converts the possible outcomes of governmental policy choice into vectors (lists) of interpersonally comparable well-being numbers, measuring the lifetime well-being of each individual in the population of interest. The SWF proper is a rule for ranking these vectors. The utilitarian SWF adds up well-being numbers. A prioritarian SWF adds up well-being numbers plugged into a strictly increasing and strictly concave transformation function. Governmental policies are conceptualized as probability distributions over well-being vectors. A recent literature applies the SWF framework to health policy. This article first provides a brief overview of the SWF framework and then reviews some of the key concepts and findings that have emerged from this literature. One such concept is the “social value of risk reduction” (SVRR): the marginal social value (as calculated by the SWF) per unit of reduction in fatality risk for a given individual. The SVRR is the analogue, within the SWF framework, to the value-of-statistical-life (VSL) concept within benefit–cost analysis. This article explicates the SVRR concept and reports on recent theoretical findings and simulations that illustrate the properties of utilitarian and prioritarian SVRRs and their differences from VSL.

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.

This is an appreciation of the life and work of Michael Jones-Lee. It describes his pioneering role in establishing and developing the theory and practice of the elicitation of monetary values for changes in risks to life, health and safety, using stated preference methods.

The value of statistical life (VSL) is arguably the most important number in benefit–cost analyses of environmental, health, and transportation policies. However, agencies have used a wide range of VSL values. One reason may be the embarrassment of riches when it comes to VSL studies. While meta-analysis is a standard way to synthesize information across studies, we now have multiple competing meta-analyses and reviews. Thus, to analysts, picking one such meta-analysis may feel as hard as picking a single “best study.” This article responds by taking the meta-analysis another step, estimating a meta-analysis (or mixture distribution) of seven meta-analyses. The baseline model yields a central VSL of $8.0 m, with a 90 % confidence interval of $2.4–$14.0 m. The provided code allows users to easily change subjective weights on the studies, add new studies, or change adjustments for income, inflation, and latency.

This study is the eighth in a series of stated-preference studies designed to enhance the basis for international benefits transfer of value of statistical life (VSL) estimates. The series has fielded essentially similar stated-preference surveys in Canada, China, France, Italy, Japan, Mongolia, the United Kingdom, and the United States. This Chinese study estimates the willingness to pay for contemporaneous and future mortality risk reductions of residents of Shanghai, Jiujiang, and Nanning, China using a stated-preference payment-card survey. The pooled VSL for a contemporaneous reduction in annual mortality risk reduction of 5 in 10,000 is about 1.47 million 2009 yuan ($614,805 U.S. $2016), with income elasticities of 0.2 to 0.25. This VSL estimate is at the lower end of estimates from the eight countries, between those from Mongolia and Japan, and in the mid-range of estimates of willingness to pay (WTP) for mortality risk reductions as a percentage of household income. We find lower discount rates in the Mongolia, Japan, and China studies than in those fielded in North America or Europe. The study also explores the relative performance of dichotomous choice and stated-preference card elicitation methods in a middle income country setting and develops a computerized “payment card” that allows testing for anchoring. Implicit transfer elasticities across countries, calculated using the VSLs we estimate and each country’s income, relative to those of the United States, yields estimates of 0.88–0.95 for the lower income countries. These compare with the default assumption of 1.0 or assumed elasticities of 1.2 for developing countries.

Willingness-to-pay (WTP) values and willingness-to-accept (WTA) values have received considerable attention, but the role of reference-dependence effects is more diverse. Policies involving cost and risk may have reference point effects with respect to both cost and risk, leading to four potential valuation measures. Experimental evidence for water quality policies suggests that the cost reference effects are particularly influential in that context. There is, however, no evidence of significant reference effects for labor market estimates of the value of a statistical life. Sound application of benefit values other than WTP measures requires pertinent empirical evidence and an assessment of the underlying rationality of the determinants of the reference-dependence effects.

The benefits associated with mortality risk reductions are a critical input for the benefit-cost analysis of economically significant federal regulations that affect health and safety. The dominant method of estimating the benefits of reducing mortality risks relies on labor markets to estimate the tradeoffs between workers’ wages and occupational risk. The past literature considers all labor market risks to be equivalent, failing to recognize the inherent heterogeneity in occupational hazards. In this research, heterogeneity in the value of reducing risks is explored within the labor market context. Unique location-specific risk data are developed for over 300 U.S. cities to separately identify the wage premiums for facing two disparate occupational risks: violent assault and motor vehicle accident risks. We find that ignoring the underlying heterogeneity in risks can lead to substantial over/under-statements of the benefits of reducing any one particular risk by up to 350%. As such, caution is urged for benefits transfer exercises that apply estimates of the marginal willingness to pay for reducing labor market accident risks to policies affecting very different risks, such as public safety or environmental risks.

Objectives: In the Netherlands, allocation decisions have not yet been explicitly based on the Value of Statistical Life. However, when policy makers decide whether or not to implement life saving interventions this trade-off is made implicitly. This study aimed to gain insights into this trade-off, hereafter referred to as Implicit Value of Statistical Life (IVSL), by means of a retrospective investment analysis of life saving interventions implemented in the Netherlands.

Methods: A literature search was conducted to find life saving intervention cases meeting the requirements for IVSL calculation. A final sample of ten cases was included in the study concerning interventions implemented in different societal sectors. For each case, an IVSL estimate was calculated according to a uniform method.

Results: IVSL estimates derived from the intervention cases differed considerably and ranged from €1 to almost €11 million. Differences were most extreme when comparing IVSL estimates concerning interventions implemented in different societal sectors. However, IVSL estimates also varied greatly between interventions in the same sector and even within the same interventions when critical assumptions were altered.

Conclusion: Our findings suggest that there are great imbalances between societal investments for preventing a statistical death. This highlights the need for further deliberation about how to improve transparency of policy decisions. An approach ex ante determining the Value of Statistical Life by means of empirical methods and based on societal preferences might circumvent the problems associated with the IVSL and needs further exploration.