The value of small changes in mortality risks, conventionally expressed as the value per statistical life (VSL), is an important parameter in benefit-cost analysis. These risk reductions often dominate the benefit estimates for environmental, health and safety policies and regulations. As a result, their value has been extensively studied, raising questions about how to best synthesize the resulting research and to adjust it for different contexts. The VSL terminology has led to substantial confusion about what is being measured, however. The VSL reflects individuals’ willingness to pay for small reductions in their own mortality risks within a defined time period. It is not the value of preventing certain death.
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Uncertainty is prevalent in policymaking, and is thus an important dimension of policy evaluation and BCA. This chapter introduces the methods and practices to take uncertainty into account in BCA. The pedagogical approach consists in building on the contrast between two related concepts, such as risk versus uncertainty, static versus sequential analysis or ex ante versus ex post BCA.
Arnold C. Harberger
This chapter presents a simple exposition of general equilibrium applied welfare economics. It focuses first on the efficiency costs of a set of tax distortions on different goods, and then explores the efficiency effects of adding a new tax to a set of already existing ones. It near considers non-tax distortions such as pollution and traffic congestion, followed by a discussion of distributional weights and basic needs externalities. Finally, it deals briefly with several strategic issues involved in implementing a national system for the benefit-cost analysis of public investments and other expenditures.
Government projects may cause workers in the private sector to lose their jobs by replacing the functions they perform or, alternatively, to be hired away from the private sector in order to work on the project. Similarly, new regulation may decrease employment in some sectors of the economy and increase employment in others. This chapter attempts to clarify these situations through a simple illustration: a city that is building a subway that will replace an existing privately owned bus system. It first examines what happens when private sector workers (for example, the bus drivers) lose their jobs as a result of a government project. In doing this, it assumes that new jobs are available to these workers, although sometimes not immediately. The chapter then examines hiring persons to work on the project (such as construction workers needed to build the subway) from a labor market in which there is considerable unemployment.
This chapter is devoted to models for transport, trade and land use decisions. They complement traditional benefit-cost analyses (BCA) insofar as they allow describing the distribution of effects and coping with market imperfections such as externalities and market powers. They can be classified according to several types: dynamic or static, taking into account or not the land market, and also ranked according to their degree of complexity. Their use for BCA is presented, along with some recommendations on how they can help to assess projects and schemes.
Simulation is an increasingly accessible method to investigate uncertainty in an analysis. This chapter supports that conclusion, explains the concept behind simulation and presents class exercises using both standard Excel as well as more advanced spreadsheet simulation tools.
Per-Olov Johansson and Bengt Kriström
The typical approach in benefit-cost analysis is partial equilibrium. Thus, a policy’s impacts on other markets are ignored. We discuss partial equilibrium evaluation versus general equilibrium ones. It is shown that the rules coincide when markets are perfect and the considered policy is (infinitesimally) small. If changes in some parameters are discrete, the approaches produce different outcomes, in general. In particular, market-based (Marshallian) demand curves no longer reflects the willingness-to-pay for, say, a change in a price. Therefore, income-compensated (Hicksian) tools must be employed. Greater technical detail is expected here that may be more familiar to graduate students in economics.
For the past five decades, the literature on economic evaluations of health programs or policies has consisted largely of cost-effectiveness analysis (CEA) rather than benefit-cost analysis (BCA). One factor contributing to this orientation was the view that we could not obtain valid estimates of consumers’ monetary valuations (that is, willingness-to-pay figures) for the benefits provided by these programs or policies. As interest in CEA methods in health expanded, and the limits of simple effectiveness measures in CEA became clearer, further refinements in effectiveness measurement have: (1) brought us closer and closer to actually conducting BCAs for heath programs and (2) generated important new insights into defining and valuing program benefits in willingness-to-pay (WTP) terms. This chapter traces these developments in the convergence of the CEA and BCA literatures in health. A simple example is presented to highlight the major challenges to obtaining valid WTP valuations for benefits of health programs, and to compare major strategies used for generating monetary WTP benefit valuation figures.
Addiction harms individuals and the rest of society. It poses a challenge to conventional CBA because it involves sovereign consumers apparently making mistakes. Although the neoclassical approach to addiction, the rational addiction model, does not adequately explain harmful addiction, it introduces the useful notion that the utility of current consumption can depend on the stock of prior consumption. Behavioral economics offers a number of explanations for addiction: non-exponential time discounting, presentism, cue-dependent consumption choices and costly self-control in the face of temptation. The latter provides some normative leverage: addictive consumption involves a loss of individual welfare when the individual would be willing to pay to avoid facing the tempting choice. Practical CBA can assess the welfare loss from addictive consumption if a marginal valuation schedule for non-addicted consumption can be distinguished from the market demand schedule. Unfortunately, it is currently unclear how to identify the non-addicted demand schedule from revealed preference data. Further, the task is complicated because consumption of most goods commonly classified as addictive involve both addictive and non-addictive consumption.