This paper investigates the role of cost-benefit analysis (CBA) in the context of the European Union (EU) Cohesion Policy. After presenting the EU policy framework and the CBA guidelines adopted by the European Commission, we perform an empirical analysis drawing from a dataset of around 1000 major project applications, submitted during the period 2007–2013 by 22 European countries, and representing almost €180 billion of investment. A distinctive feature of the current CBA approach adopted by the European Commission is that applications for funding must provide a forecast of both the project’s financial rate of return (FRR) and economic rate of return (ERR). While the former represents the financial profitability of the project from a private investors’ perspective, the latter reveals its socio-economic benefits for the whole society. The difference between ERR and FRR mainly depends on the use of shadow prices, the inclusion of externalities and other nonmarket effects in the estimation of ERR, whilst the FRR is based on market prices. We find that, on average, the FRR is slightly negative ($-2.9$%) and the ERR is positive (16.2%). ERR and FRR are positively correlated on average with differences across sectors. We discuss these findings and suggest further research needs.

This paper presents an evaluation of the use of environmental valuation – techniques to assign monetary values to environmental impacts of policies and projects, especially nonmarket impacts – in U.K. policy. In doing so, we seek to contribute to the debate, more generally, of the use and influence of benefit-cost analysis (BCA) in national policy processes such as Impact Assessment. Specifically, our contribution in this paper is two-fold. First, we identify a number of trends that have characterized U.K. policy use of environmental valuation over the past two or so decades. While this has notably involved development of “sharable values” allowing more widespread uptake, it also seems that different branches of government have developed different traditions of use adding nuance to what, on the face of it, is otherwise a shared endeavor. Second, we evaluate the extent to which the use of environmental valuation can be said to have influenced policy decisions and the degree to which this is embedded by evolving policy processes. As such, we discuss two areas of environmental policy – water quality improvements and natural capital – which have entailed either substantial use of environmental valuation either in determining specific policy and investment project options or where this has helped shape the broader policy agenda. Our evaluation is not exhaustive; nor do our findings suggest that environmental valuation and BCA are necessarily the dominant driver of decisions, as we discuss. However, in recognizing this, we argue it is also important to consider a number of established or evolving cultural and legal institutional processes which broadly appear to support our assessment of such cases.

This paper looks at how to measure the tradeoffs in monetary terms that the public is prepared to make with respect to adoption of different community policing options. The approach advanced is a discrete choice experiment in which survey respondents face different policing options which can be described by a set of attributes ranging from costs to outcomes. The main contribution of this paper is to show how to go beyond the usual characterization of the monetized benefits of reducing the level of a specific type of crime to asking the question of whether those benefits differ depending on how that outcome is achieved.

Selection of the best estimates of economic parameters frequently relies on the “best estimates” or a meta-analysis of the “best set” of parameter estimates from the literature. Using an all-set dataset consisting of all reported estimates of the value of a statistical life (VSL) as well as a best-set sample of the best estimates from these studies, this article estimates statistically significant publication selection biases in each case. Biases are much greater for the best-set sample, as one might expect, given the subjective nature of the best-set selection process. For the all-set sample, the mean bias-corrected estimate of the VSL for the preferred specification is $8.1 million for the whole sample and $11.4 million based on the CFOI data, while for the best-set results, the whole sample value is $3.5 million, and the CFOI data estimate is $4.4 million. Previous estimates of huge publication selection biases in the VSL estimates are attributable to these studies’ reliance on best-set samples.

Under the 1990 Clean Air Act Amendments, the U.S. Environmental Protection Agency (EPA) was required to establish standards limiting air toxics emissions from industrial plants. This paper examines the effects of five of the largest-cost rules issued by EPA in the initial round of air toxics rulemaking over the 1995 to 2000 period. Our estimates suggest that plants in the printing and publishing and pulp and paper industries realized important reductions in their air toxics emissions in the period between publication of the final rule and the effective date for compliance with the rule – although the reduction in air toxics emissions by pulp and paper mills fell short of EPA’s ex ante projections. However, our estimates also suggest that plants in three other industries – petroleum refining, pharmaceuticals, and wood furniture – achieved little or no additional reduction in air toxics emissions over the compliance period in response to EPA’s rules. Finally, the paper explores steps that EPA should take in setting up future retrospective analyses.

The value of small changes in mortality risks, generally expressed as the value per statistical life, is an important parameter in benefit-cost analysis. However, little is known about the values held by populations in low- and middle-income countries. This article introduces a symposium that includes three additional articles which explore related theory and research.

Regulatory impact analyses (RIAs) weigh the benefits of regulations against the burdens they impose and are invaluable tools for informing decision makers. We offer 10 tips for nonspecialist policymakers and interested stakeholders who will be reading RIAs as consumers.

1. 1. Core problem: Determine whether the RIA identifies the core problem (compelling public need) the regulation is intended to address.

2. 2. Alternatives: Look for an objective, policy-neutral evaluation of the relative merits of reasonable alternatives.

3. 3. Baseline: Check whether the RIA presents a reasonable “counterfactual” against which benefits and costs are measured.

4. 4. Increments: Evaluate whether totals and averages obscure relevant distinctions and trade-offs.

5. 5. Uncertainty: Recognize that all estimates involve uncertainty, and ask what effect key assumptions, data, and models have on those estimates.

6. 6. Transparency: Look for transparency and objectivity of analytical inputs.

7. 7. Benefits: Examine how projected benefits relate to stated objectives.

8. 8. Costs: Understand what costs are included.

9. 9. Distribution: Consider how benefits and costs are distributed.

10. 10. Symmetrical treatment: Ensure that benefits and costs are presented symmetrically.

As higher education costs rise, many communities have begun to adopt their own financial aid strategy: place-based scholarships for students graduating from the local school district. In this paper, we examine the benefits and costs of the Kalamazoo Promise, one of the more universal and more generous place-based scholarships. Building upon estimates of the program’s heterogeneous effects on degree attainment, scholarship cost data, and projections of future earnings by education, we examine the Promise’s benefit-cost ratios for students differentiated by income, race, and gender. Although the average rate of return of the program is 11%, rates of return vary greatly by group. The Promise has high returns for both low-income and non-low-income groups, for non-Whites, and for women, while benefit assumptions matter more for Whites and men. Our results show that universal scholarships can reach many students and have a high rate of return, particularly for places with a high percentage of African American students. They also highlight the importance of disaggregating benefits and costs by subgroup when performing benefit-cost analysis when the treatment is heterogeneous.

This paper discusses the ways in which behavioral economics challenges the premises of conventional welfare economics. It proposes revised premises that survive those challenges and sets forth a welfare framework derived from that foundation. It argues that the proposed framework is practical, in the sense that it lends itself to applications, as well as unifying, in the sense that it subsumes other approaches and illuminates the relationships between them.

The prospect of improving “noncognitive” skills through intervention increases the need to understand how to represent them in evaluations. Economic assessment of such efforts rarely incorporates these factors, especially when a benefit-cost approach is employed. Programs targeting such skills are more likely to be assessed through approaches that do not monetize noncognitive ability (e.g., using cost-effectiveness analysis). This could lead to ineffective policy formulations in situations where policy is swayed toward programs that can show monetized effects. Benefit-cost analyses (BCAs) that are employed for programs that target noncognitive competencies currently may underestimate the true economic impact if such skills are left out of the equation. The limitations in valuing these skills impede thorough economic assessment for important and effective programs that target noncognitive competencies. This is especially the case for programs for younger children where readily monetized outcomes are few. The targeted outcomes in programs for children are often noncognitive skills, skills that are perceived as vital to healthy human development and valued by parents, teachers, and educators.

In this paper, we review the state of valuation of key noncognitive skills that are often targeted in social policy intervention directed toward children in youth. We examine the state of valuation of noncognitive skills through a summary of the frameworks in research for characterizing noncognitive ability and by considering the measurement approaches for noncognitive skills in terms of origin (interpersonal versus intrapersonal) and measurement type (observed versus assessed). We review examples of recent BCAs that have employed shadow prices for certain noncognitive skills. Finally, we consider what research is necessary to facilitate valuation in BCA in the future. Shadow price methodology should be carried out in a rigorous manner that recognizes uncertainty in cost projections. Improved methodologies in this area will increase the potential for more comprehensive BCA in evaluations of programs for children and youth.

The analysis of regulations affecting addictive or habitual goods has drawn considerable controversy. Some studies have suggested that such regulations have only small welfare benefits, as consumers value these goods despite health benefits from quitting, while other studies suggest that information or behavioral problems make existing consumption decisions a poor guide to welfare evaluation. We examine potential utility offsets to health benefits of regulations affecting addictive or habitual goods theoretically and empirically. Our analysis focuses on individuals who consume these goods only, ignoring other social costs and benefits. Theoretically, we show the importance of several factors including: money saved in addition to health improvements; differentiating steady-state utility losses from short-term withdrawal costs; lack of utility loss for people dissuaded from starting to consume the good; and accounting for utility consequences of explicit or implicit cost increases. Our empirical analysis considers regulations that affect smoking. To measure the welfare cost of smoking cessation, we divide the population into those with more and less rational smoking behavior and use the valuation of smoking from more rational smokers to impute values of losses for less rational smokers. Our results show that the utility cost of smoking cessation is small relative to the health gains in people for whom withdrawal costs are the main utility loss of quitting, and even among people who have some ongoing loss, the utility offsets represent 20%–25% of the health gains. While marginal smokers induced to quit by regulations can be expected to have low or no steady-state loss, even this higher estimate is far below prevailing estimates of the utility cost of smoking used by the Food and Drug Administration and other analysts.

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.