Reducing the excess nutrient and sediment pollution that is damaging habitat and diminishing recreational experiences in coastal estuaries requires actions by people and communities that are within the boundaries of the watershed but may be far from the resource itself, thus complicating efforts to understand tradeoffs associated with pollution control measures. Such is the case with the Chesapeake Bay, one of the most iconic water resources in the United States. All seven states containing part of the Chesapeake Bay Watershed were required under the Clean Water Act to submit detailed plans to achieve nutrient and sediment pollution reductions. The implementation plans provide information on the location and type of management practices making it possible to project not only water quality improvements in the Chesapeake Bay but also improvements in freshwater lakes throughout the watershed, which provide important ancillary benefits to people bearing the cost of reducing pollution to the Bay but unlikely to benefit directly. This paper reports the results of a benefits study that links the forecasted water quality improvements to ecological endpoints and administers a stated preference survey to estimate use and nonuse value for aesthetic and ecological improvements in the Chesapeake Bay and watershed lakes. Our results show that ancillary benefits and nonuse values account for a substantial proportion of total willingness to pay and would have a significant impact on the net benefits of pollution reduction programs.

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.

Our research investigates the effects of residential energy efficiency audit programs on subsequent household electricity consumption. Here there is a one-time interaction between households, which participate voluntarily, and the surveyors. Our research objective is to determine whether and to what extent the surveys lead to behavioral changes. We then examine how persistent the intervention is over time and whether the effects decay or intensify. The main evaluation problem here is survey participants’ self-selection, which we address econometrically via several non-parametric estimators involving kernel-based propensity-score matching. In the first method we use difference-in-differences (DID) estimation. Our second estimator is quantile DID, which produces estimates on distributions. The comparison group consists of households who were not yet participating in the survey but participated later. Our evidence is that the customers who participated in the survey reduced their electricity consumption by about 7%, on average compared to customers who had not yet participated in the survey. Considering the total number of high-usage households participating in the survey in 2009, we estimate that electricity consumption was reduced by an aggregate of 2 million kWh per year, which is approximately equal to the monthly consumption of 3500 typical households in California with an estimated 1527 metric tons less of carbon dioxide emissions. Because the energy audit program is inexpensive ($10–$20 per household) a key issue is that while the program is cost-effective, is it regressive? We find that as the quantiles of the outcome distribution increase, high-use households save proportionally less electricity than do low-use customers. Overall, our results imply that program designers can better target low-use and low-income households, because they are more likely to benefit from the programs through energy savings.

This paper demonstrates a new connection between benefit-cost analysis (BCA) and the national income and product accounts. The article computes an augmented measure of output, which is defined as gross domestic product (GDP) less environmental pollution damage. Environmental policy BCA is incorporated directly into the adjusted measure of output in two ways. In a particular time period, damages from pollution emissions are deducted from market GDP in a standard with-and-without policy comparison. Second, secular changes in damages, output (GDP), and correspondingly, in the adjusted measure of output are employed to estimate augmented rates of growth. Comparison to a no-policy counterfactual then yields the effect of the policy on the augmented measure of environmentally adjusted value added (EVA) growth. The empirical results suggest that, in the 30 states that adopted flue-gas desulfurization (FGD) technology between 2005 and 2011, augmented output grew 0.12% more quickly than in a no-scrub counterfactual. Augmented output growth in four states was at least 0.20% more rapid because of the installation of scrubbers. The paper reports that benefits-per-capita from FGD were mildly progressive and that counties with relatively large African American populations incur large benefits from FGD installation.

Examination of estimates of the income elasticity of the value of a statistical life based on international stated preference studies yields an average between 0.94 and 1.05 overall and 0.65 and 0.80 after controlling for covariates. Quantile regression estimates indicate that the income elasticity is about 0.55 for more affluent countries and 1.0 for lower income nations, i.e., those countries that have estimates of the value of a statistical life below $2 million or per capita income levels below $3212. The estimates distinguish the values of the income elasticity across country either by income level or by the value of a statistical life. These elasticities are similar to those found in revealed preference labor market studies. The estimates are robust, controlling for possible sample selection bias and the influence of covariates, such as the type of risk.

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.

Agencies are frequently required to analyze the impact of their decisions, particularly in the context of regulatory policy. Advocates of analysis have championed the transparency benefit of these requirements. But there has been very little attention paid to the effectiveness of analysis in spurring useful participation in practice. This article examines how analysis can hinder and motivate public participation. Interviews were conducted with 48 analysts (including economists, risk assessors, and environmental impact assessors). In addition I conducted a case study on a unique method for using analysis in partnership with participation, the use of panels of small business owners to evaluate a regulatory proposal by the Occupational Safety and Health Administration (OSHA). I find that participation in agency decisions as a result of traditional analytical requirements has been very uneven. Examples of success exist but so do cases where participation may be deterred by the density and complexity of analysis as well as cases of massive letter-writing campaigns ignored by decision-makers. I recommend a move toward simpler and earlier analysis, and the use of panels (such as described in the case study) to better take advantage of the potential synergy between analysis and participation.

Retrospective, or ex post, analysis of U.S. federal regulation aims to rigorously document regulatory outcomes using cost, benefit, and distributional metrics. This paper presents nine new case studies involving a total of 34 comparisons of ex ante and ex post estimates from a diverse group of environmentally oriented rules. Despite the potential for selection bias and other limitations of the case study approach, the results suggest a slight tendency to overestimate both costs and benefits (or effectiveness) of regulation. This paper considers various analytic issues relevant to developing credible baselines for comparison, and offers policy lessons regarding the design of emissions trading programs along with approaches for incorporating uncertainty into both preregulatory studies and policy designs. Recommendations to facilitate and support future retrospective analyses are also presented.

Advances in theoretical and computable general equilibrium modeling brought their conceptual foundations more in line with standard microeconomic constructs. This reduced the theoretical gap between welfare measurements using a partial or a general equilibrium approach. However, the separation of the partial and general equilibrium literatures lingers in many applications that this manuscript seeks to bridge. The now shared conceptual foundations, the importance of functional specification, the role of common price movements and closure rules are discussed. The continuing stricture in U.S. Government guidelines against including secondary effects in welfare measures is questioned.

Although benefit-cost analysis (BCA) can be traced back to European thinkers, its first practical applications were in the United States. Recent years have witnessed a growing demand for economic appraisals of policies in different sectors in Europe, but the implementation rate is still low compared to that in the United States. This article introduces a symposium that includes four articles that present current examples of how BCA is being applied in different sectors and in different institutional settings in Europe. They deal with environmental valuation in the United Kingdom, economic analysis for investment in Sweden’s transport sector, economic versus financial returns in European Union investment project appraisal, and BCA in EU chemicals legislation. The goal is to stimulate continuing discussion on the implementation of BCA, not only in Europe but also worldwide.

The European Union’s regulation for chemical safety (REACH) addresses the registration, evaluation, assessment, and consequent authorization (or restriction) of chemicals which are potentially harmful for both public health and the environment. The current study aims at ascertaining the costs and benefits of the REACH framework for the Austrian economy under major uncertainties, and draws on a wide range of databases on public and workplace health, chemical accidents in households, and the potential environmental impacts of harmful chemicals.

The uncertainties in the REACH system assessments of the effects of chemicals on health lie not only in the insufficiency of scientific evidence but also in the economic evaluation of effects on health, especially in regard to the value of statistical life (VSL), and the economic value of diseases attributed to chemicals.

This benefit-cost analysis (BCA) of the REACH system in Austria therefore takes into account these manifold uncertainties by designing a conservative baseline scenario and by varying all determinants in comprehensive sensitivity analyses. Projected over a period of about 30 years, this paper provides evidence that the REACH system most probably leads to net benefits for the Austrian economy (benefit-cost ratio of about 10.6) even though many benefits are still highly uncertain or unknown.

Recent research examining voting behavior in contingent valuation referenda informs on how consequential survey respondents behave and its impact on willingness-to-pay (WTP) values. This research attempts to examine whether this behavior holds across population subgroups. We consider resident and nonresident users of artificial reefs and find improved construct validity for our resident models over nonresident models. Specifically, resident behavior is in line with a priori expectations with consequential residents more likely to vote in favor of a policy for additional reef funding – a result that is consistent with the “protest no” literature. Consequently, consequential resident voters exhibit a greater WTP than inconsequential voters. Nonresident behavior differs, however. For this subgroup, consequentiality does not influence voting behavior and WTP values do not differ by consequentiality. Overall, more work is required to appropriately identify WTP values for nonresident populations, particularly from a benefit-cost perspective, where appropriately identifying subgroup WTP values are a critical component of measuring the net present value of a given policy.

Recreational saltwater anglers from the mid-Atlantic through the Gulf of Mexico commonly target red drum. Due to concerns about overharvesting within South Carolina coupled with regional management actions, South Carolina explored the technical feasibility of stocking hatchery-produced juvenile red drum as a technique to augment the abundance of South Carolina stock. In order to assess a continued program, in 2005 a mail survey was used to collect data for estimating the economic benefits with the contingent valuation method. The theoretical validity of willingness to pay was assessed by comparison to the value of a change in red drum fishing trips that would result from the program. Benefits were compared to estimated, explicit stocking costs. We illustrate how a certainty recode approach can be used in sensitivity analysis. The net present values (NPVs) for the stocking program are positive suggesting that the program would have been economically efficient relative to no program.

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.

Food and Drug Administration (FDA) published a final regulation in 2004 that requires pharmaceutical manufacturers to place linear bar codes on certain human drug and biological products. The intent was that bar codes would be part of a system where healthcare professionals would use bar code scanning equipment and software to electronically verify against a patient’s medication regimen that the correct medication is being given to the patient before it is administered, which could ultimately reduce medication errors. In the 2004 prospective regulatory impact analysis, FDA anticipated that the rule would stimulate widespread adoption of bar code medication administration technology among hospitals and other facilities, thereby generating public health benefits in the form of averted medication errors. FDA estimated that annualized net benefits would be $5.3 billion. In this retrospective analysis, we reassess the costs and benefits of the bar code rule and our original model and assumptions. Employing the most recent data available on actual adoption rates of bar code medication administration technology since 2004 and other key determinants of the costs and benefits, we examine the impacts of the bar code rule since its implementation and identify approaches to improve the accuracy of future analyses. In this retrospective study, we use alternative models of health information technology diffusion to create counterfactual scenarios against which we compare the benefits and costs of the bar code rule. The magnitudes of the costs and benefits of the 2004 rule are sensitive to assumptions about the counterfactual technology adoption rate, with the upper-bound range of calculated annualized net benefits between $2.7 billion and $6.6 billion depending on the baseline scenario considered.

Disclaimer: The findings, interpretations, and conclusions expressed in this article are those of the authors in their private capacities, and they do not represent the views of the Food and Drug Administration.

Beginning as a planning tool within Sweden’s national road administration some 50 years ago, benefit-cost analysis (BCA) has come to be a pillar of the national transport policy because of subsequent strategic choices made by the national parliament. These choices made it necessary to widen the analysis of costs to include also externalities and a foregone conclusion was that efficient investment priorities should be made based on BCA. But no one asked whether the political decision makers or the BCA models were up to that task. This paper reviews the institutional framework and practice of BCA in Sweden for transport infrastructure investment, and considers design issues that have been and still are debated, such as whether the discount rate should include a risk term and how to account for the marginal cost of public funds. A main concern with BCA results is the underestimation of construction costs, making transport sector projects look better than they are. Several ex post analyses have established that a higher NPV ratio increases the probability of being included in the investment program proposal prepared by the agency. The requirement to let projects undergo BCA seems to make planners “trim” project proposals by trying to reduce investment costs without significantly reducing benefits. This relationship is weaker among profitable projects. Moreover, there is no correlation between rate of return and the probability of being included in the final program, which is established on political grounds.

The federal government and over thirty states nationwide offer a tax credit in lieu of certain expenditures incurred as part of historic rehabilitation projects. Several economic impact studies have shown the positive effect of the credit on job creation, property values, and environmental friendly behavior in Louisville, KY (Gilderbloom, Hanka & Ambrosius, 2009) and in the state of Maryland (Frizzell & Mitchell, 2002). Most of the studies of historic preservation credits are, however, nonempirical and evaluate only the economic impact of the credit. The societal benefit-cost analysis conducted in this manuscript is the first study of its kind of the Ohio Historic Preservation Tax Credit (OHPTC) program. In addition, this study provides an OHPTC fiscal impact analysis (benefit-cost analysis from the government perspective).

The data for the analysis come from the county auditors’ offices, and multiple proprietary sources, including administrative estimates provided by the agencies managing the OHPTC program, and online survey of the developers. The sensitivity analysis accounts for the differences in discount rates and other factors. The study finds that the overall societal benefits will outweigh overall societal costs by 2023. From the fiscal perspective, the program begins to pay for itself in 2025, but the overall program costs will remain higher than overall benefits during the considered study period (until 2030).

Practitioners of benefit-cost analysis face many difficulties. Despite the best training, guidance, and intentions, practitioners can stumble: actual benefit-cost analysis is hard and mistakes get made. Over the years, I have collected the mistakes I have seen in actual benefit-cost analyses. Many of the same mistakes occur over and over: the pitfalls of practical benefit-cost analysis. In this paper, I describe common pitfalls and suggest ways to avoid them.

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.