This paper is mainly concerned with weighted-average measures of the social discount rate, where the components of the average are the marginal productivity of investment (measured by its gross-of-tax rate of return), and the marginal rate of time preference (measured by the net-of-tax yield of capital). We believe that these components should best be measured using data (the national accounts) that span the whole economy and reflect the product actually produced and the rewards actually perceived. We use a methodology based on just four familiar parameters to generate productivity estimates applicable to a wide range of countries. In the process, we make an adjustment for infrastructure investment, also excluding income from land, monopoly markups, supra-marginal returns due to increases in total factor productivity (TFP), and returns to capital in financial intermediation. The end products are estimates of social discount rates averaging around 8% for the advanced countries, and 10% for healthy developing countries and Asian Tigers.

Benefit-cost analysis (BCA), a discipline best known for guiding policy choices, can also guide personal decisions. In either application, traditional BCA tallies benefits and costs using market values or willingness to pay. When future outcomes are uncertain, as they are across a wide array of situations, BCA must call as well on the methods of decision analysis. Thus, von Neumann–Morgenstern utilities, subjective probabilities, and sequential decision strategies are brought into play.

Traditional decision analysis distinguishes between risk and uncertainty. With risk, the probabilities of possible outcomes are known; with uncertainty, those outcomes are known, but not their probabilities. We introduce the concept of ignorance: a third, less tractable category. With ignorance, even the possible outcomes of decisions cannot be identified. Ignorance takes particular importance when high payoffs are associated with these unidentified outcomes, as is often the case. We identify such outcomes as consequential amazing developments (CADs). In the policy realm, the 2008 financial meltdown or the Arab Spring would represent a CAD. For an individual, a CAD might be that one’s secure tenured position had been inexplicably terminated, or that one’s trusted business partner had long been shuttling corporate secrets to a competitor. We distinguish between unrecognized and recognized ignorance. In the latter category, we identify specific cognitive biases that impair decision making.

Consequential ignorance cannot be studied in a controlled laboratory setting, since its payoffs are high, its time delays often long, and merely introducing the subject would tend to give away the game. Thus we develop a descriptive understanding of ignorance drawing on great works of literature, from antiquity to the present day, positing that skilled writers understand how humans make decisions and respond to unanticipated outcomes. Shakespearean examples would be Hamlet’s ignorance of his father’s killer, and Macbeth’s lack of awareness of the tragic ramifications following his actions to seize the Scottish crown.

Following this descriptive analysis, we turn to prescription. We draw on decision analysis to develop a formula for calculating consequential ignorance; it incorporates the expected magnitudes and assessed base rates for CADs. Finally, we propose a decision-analytic framework for measured decision making, given ignorance. Our recommended approach explicitly recognizes decision-making costs, and thus proposes when to use quick and intuitive as opposed to more deliberative approaches to decision, or the labels Kahneman has popularized as System 1 and System 2.

Studying ignorance through literature has important implications for BCA. Given the potential for ignorance, there are two key goals for prudent decision making. First, steps should be taken to recognize when ignorance might be present. Second, efforts should be made not to respond in a suboptimal fashion when ignorance is anticipated or when a CAD springs upon us. Great literature can provide the equivalent of widespread life experience, and can help a decision maker reach both goals. At its heart, this essay represents a benefit-cost approach to dealing with ignorance. Numerous connections to BCA are made throughout.

In this study, we conduct a cost-effectiveness analysis of nine air quality regulations recently issued by the U.S. Environmental Protection Agency (EPA). Taking emission reductions in the Regulatory Impact Analyses (RIAs) for these regulations as given, we independently assess uncertainty about the compliance costs of the regulations and the lives the regulations are estimated to save. The latter evaluation is based on a formal uncertainty analysis that integrates expert judgments about the effects of fine particle exposures on mortality risks. These expert judgments were given in an EPA-sponsored elicitation study conducted in 2006. The integrated judgments are used to generate probability distributions for several types of cost-effectiveness ratios, including the gross and net cost per life saved, net cost per life year saved, and net cost per quality-adjusted life year (QALY) gained. The results show that the cost-effectiveness ratios exhibit considerable uncertainty individually and also vary widely across regulations. Within a simulated 90% confidence interval for the gross cost per life saved, for example, there is both the possibility that benefits from lifesavings alone are sufficient to cover the rules’ costs and the possibility that no lives will be saved and cost-effectiveness ratios will be infinite. The wide ranges for the confidence intervals suggest the need for better information about the effects of fine particle exposures on mortality risks.

We explore the economic welfare effects of direct and indirect government-induced changes in employment under varying market conditions. We begin with a discussion of those policy-induced employment changes that seamlessly reshuffle workers among jobs in an efficient (i.e., full-employment, full-information) economy; generally such changes create few, if any, net changes in economic welfare not captured in changes in wage bills. We then turn to the effects of policy-induced employment changes in economies with two market distortions: (1) inflexible wages set by law or custom that result in involuntary unemployment during periods of deficient aggregate demand, and (2) illiquidity resulting from imperfect capital markets that prevent people from borrowing against future earnings. Induced employment changes in these circumstances impose real net social costs or generate real net social benefits beyond changes in the wage bill. We also assess the likely magnitude of the social opportunity cost of labor in the case of involuntary unemployment and imperfect liquidity, and address how the welfare effects of such employment changes should be valued. Based on currently available empirical research, we develop estimates of the opportunity costs of hiring or releasing an employee during periods of high unemployment with and without other market distortions. In contrast to conventional benefit-cost analysis practice, which treats releasing workers as having a negative opportunity cost, we estimate an opportunity cost for firing that is positive and equal to about 73% of pre-firing compensation, primarily because of the “scarring effect” of unemployment. Also in contrast to conventional practice, we estimate an opportunity cost for hiring an unemployed worker that is less than the worker’s opportunity cost of time.

Regulatory policies designed to improve societal welfare by “nudging” consumers to make better choices are increasingly popular. The application of benefit-cost analysis (BCA) to this sort of regulation confronts difficult theoretical and applied issues. In this analysis we contribute a worked example of behavioral BCA of U.S. anti-smoking policies. Our conceptual framework extends the standard market-based approach to BCA to allow for individual failures to make lifetime-utility-maximizing choices of cigarette consumption. We discuss how our market-based approach compares to the health benefits approach and the “consumer surplus offset” controversy in recent BCAs of several health-related regulations. We use a dynamic population model to make counterfactual simulations of smoking prevalence rates and cigarette demand over time. In our retrospective BCA the simulation results imply that the overall impact of anti-smoking policies from 1964 to 2010 is to reduce the total cigarette consumption by 28%. At a discount rate of 3% the 1964–present value of the consumer benefits from anti-smoking policies through 2010 is estimated to be $573 billion ($2010). Although we are unable to develop a hard estimate of the policies’ costs, we discuss evidence that suggests the consumer benefits substantially outweigh the costs. We then turn to a prospective BCA of future anti-smoking Food and Drug Administration (FDA) regulations. At a discount rate of 3%, the 2010–present value of the consumer benefits 30 years into the future from a simulated FDA tobacco regulation is estimated to be $100 billion. However, the nature of potential FDA tobacco regulations suggests that they might impose additional costs on consumers that make it less clear that the net benefits of the regulations will be positive.

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.

Differences between estimated willingness to accept compensation (WTA) and willingness to pay (WTP) that are larger than can be explained by standard economic theory raise questions about which measures should be used for benefit–cost analysis (BCA). These differences do not create a new problem but accentuate an existing one: the fact that the Kaldor–Hicks compensation test is ambiguous when its two components conflict. This conflict is more likely when the difference between WTA and WTP measures of a change is large. In many cases, the same individuals receive benefits and incur costs from a policy change and their preferences for the policy cannot depend on whether they ask whether their WTP for the benefit exceeds the cost they will incur or their WTA to forgo the benefit exceeds the cost they will save. In cases where benefits and costs are incurred by different people, it seems more useful to evaluate the fundamental question – whether the benefits to some justify the harms to others – than to obscure this question through a technical debate about valuation measures.

The results of the vast array of willingness to accept compensation/ willingness to pay (WTA/WTP) disparity studies provide strong evidence that people value many losses and reductions of losses, more, and often much more, than otherwise commensurate gains or foregoing of gains. These findings also make it clear that people commonly value many changes not as final states as standard theory assumes, but as positive or negative changes relative to a neutral reference state. Consequently, not only are losses to be most accurately assessed with the WTA measure, but most positive changes that reduce losses are as well. Current practice, which rarely takes such reference dependence into account, is therefore likely to substantially understate the value and importance of projects, policies, and programs that reduce losses. Failing to take the possibilities of valuation disparities into account also appears to undermine other kinds of analyses as well, including, for example, the estimation of elasticities and setting effective levels of Pigouvian taxes.