Investing in global health and development requires making difficult choices about what policies to pursue and what level of resources to devote to different initiatives. Methods of economic evaluation are well established and widely used to quantify and compare the impacts of alternative investments. However, if not well conducted and clearly reported, these evaluations can lead to erroneous conclusions. Differences in analytic methods and assumptions can obscure important differences in impacts. To increase the comparability of these evaluations, improve their quality, and expand their use, this special issue includes a series of papers developed to support reference case guidance for benefit-cost analysis. In this introductory article, we discuss the background and context for this work, summarize the process we are following, describe the overall framework, and introduce the articles that follow.

The estimates used to value mortality risk reductions are a major determinant of the benefits of many public health and environmental policies. These estimates (typically expressed as the value per statistical life, VSL) describe the willingness of those affected by a policy to exchange their own income for the risk reductions they experience. While these values are relatively well studied in high-income countries, less is known about the values held by lower-income populations. We identify 26 studies conducted in the 172 countries considered low- or middle-income in any of the past 20 years; several have significant limitations. Thus there are few or no direct estimates of VSL for most such countries. Instead, analysts typically extrapolate values from wealthier countries, adjusting only for income differences. This extrapolation requires selecting a base value and an income elasticity that summarizes the rate at which VSL changes with income. Because any such approach depends on assumptions of uncertain validity, we recommend that analysts conduct a standardized sensitivity analysis to assess the extent to which their conclusions change depending on these estimates. In the longer term, more research on the value of mortality risk reductions in low- and middle-income countries is essential.

Valuing changes in time use is often a critical element of economic analyses of development projects. In this paper we review the literature on the monetary value of time in low- and middle-income countries and find support for a commonly used benchmark of 50% of after-tax wages for time changes in activities in the informal sector, such as collecting water or traveling to health clinics. We offer recommendations to analysts who are conducting benefit-cost analyses in these settings about what methods they can use to estimate the value of time. These include a benefits transfer approach and also a relatively simple stated preference approach that might be deployed in a specific context if the project recommendation is sensitive to the assumption of the value of time or if the distribution of the benefits of time savings is especially important.

The primary focus of this paper is to offer guidance on the analysis of time streams of effects that a project may have so that they can be discounted appropriately. This requires a framework that identifies the common parameters that need to be assessed, whether conducting cost-effectiveness or benefit-cost analysis. The quantification and conversion of the time streams of different effects into their equivalent health, health care cost or consumption effects avoids embedding multiple arguments in discounting policies. This helps to identify where parameters are likely to differ in particular contexts, what type of evidence would be relevant, what is currently known and how this evidence might be strengthened. The current evidence available to support the assessment of the key parameters is discussed and possible estimates and default assumptions are suggested. Reporting the results in an extensive way is recommended. This makes the assessments required explicit so the impact of alternative assumptions can be explored and analysis updated as better estimates evolve. Some projects will have effects across different countries where some or all of these parameters will differ. Therefore, the net present value of a project will be the sum of the country specific net present values rather than the sum of effects across countries discounted at some common rate.

There is strong interest in both developing and developed countries toward expanding health insurance coverage. How should the benefits, and costs, of expanded coverage be measured? While the value of reducing the financial risks that result from insurance coverage have long been recognized, there has been less attention in how best to measure such benefits. In this paper, we first provide a framework for assessing the financial value from health insurance. We focus on three distinct potential benefits: Pooling the risk of unexpected medical expenditures between healthy and sick households, redistributing resources from high- to low-income recipients and smoothing consumption over time. We then use this theoretical framework and an illustrative example to provide practical guidelines for benefit-cost analysis in capturing the full benefits (and costs) of expanding health insurance coverage. We conclude by considering other potential financial effects of broad insurance coverage, such as the ability to consolidate purchases and thus lower input prices.

Achieving ambitious targets to address the global tuberculosis (TB) epidemic requires consideration of the impact of competing interventions for improved identification of patients with TB. Cost-effectiveness analysis (CEA) and benefit-cost analysis (BCA) are two approaches to economic evaluation that assess the costs and effects of competing alternatives. However, the differing theoretical basis and methodological approach to CEA and BCA is likely to result in alternative analytical outputs and potentially different policy interpretations. A BCA was conducted by converting an existing CEA on various combinations of TB control interventions in South Africa using a benefits transfer approach to estimate the value of statistical life (VSL) and value of statistical life year (VSLY). All combinations of interventions reduced untreated active disease compared to current TB control, reducing deaths by between 5,000 and 75,000 and resulting in net benefits of Int$3.2–Int$137 billion (ZAR18.1 billion to ZAR764 billion) over a 20-year period. This analysis contributes to development and application of BCA methods for health interventions and demonstrates that further investment in TB control in South Africa is expected to yield significant benefits. Further work is required to guide the appropriate analytical approach, interpretation and policy recommendations in the South African policy perspective and context.

We conduct a benefit-cost analysis of a package of early childhood interventions that can improve nutrition outcomes in Haiti. Using the Lives Saved Tool, we expect that this package can prevent approximately 55,000 cases of child stunting, 7,600 low-weight births and 28,000 cases of maternal anemia annually, if coverage reaches 90% of the target population. In addition, we expect these nutrition improvements will avoid 1,830 under-five deaths, 80 maternal deaths and 900,000 episodes of child illness every year. Those who avoid stunting will experience lifetime productivity benefits equivalent to five times gross national income per capita in present value terms, at a 5% discount rate. While previous benefit-cost analyses of this specific package have only estimated the lifetime productivity benefits of avoided stunting, this paper also accounts for reductions in fatal and non-fatal health risks. In the base case scenario, the annualized net benefits of the intervention equal Haitian gourdes 13.4 billion (USD 211 million) and the benefit-cost ratio (BCR) is 5.2. Despite these substantial benefits, the package may not be the most efficient use of a marginal dollar, with alternative interventions to improve human capital yielding BCRs approximately three to four times higher than the base estimate.

Air pollution is a persistent and well-established public health problem in India: emissions from coal-fired power plants have been associated with over 80,000 premature deaths in 2015. Premature deaths could rise by four to five times this number by 2050 without additional pollution controls. We site a model 500 MW coal-fired electricity generating unit at eight locations in India and examine the benefits and costs of retrofitting the plant with a flue-gas desulfurization unit to reduce sulfur dioxide emissions. We quantify the mortality benefits associated with the reduction in sulfates (fine particles) and value these benefits using estimates of the value per statistical life transferred to India from high income countries. The net benefits of scrubbing vary widely by location, reflecting differences in the size of the exposed population. They are highest at locations in the densely populated north of India, which are also among the poorest states in the country.

Benefit-cost analyses of education policies in low- and middle-income countries have historically used the effect of education on future wages to estimate benefits. Strong evidence also points to female education reducing both the under-five mortality rates of their children and adult mortality rates. A more complete analysis would thus add the value of mortality risk reduction to wage increases. This paper estimates how net benefits and benefit-cost ratios respond to the values used to estimate education’s mortality-reducing impact including variation in these estimates. We utilize a ‘standardized sensitivity analysis’ to generate a range of valuations of education’s impact on mortality risks. We include alternative ways of adjusting these values for income and age differences. Our analysis is for one additional year of schooling in lower-middle-income countries, incremental to the current mean. Our analysis shows a range of benefit-cost ratios ranging from 3.2 to 6.7, and net benefits ranging from $2,800 to $7,300 per student. Benefits from mortality risk reductions account for 40% to 70% of the overall benefits depending on the scenario. Thus, accounting for changes in mortality risks in addition to wage increases noticeably enhances the value of already attractive education investments.