Over the past half-century or more, economists have developed a robust literature on the theory and practice of benefit-cost analysis (BCA) as applied to diverse projects and policies. Recent years have seen a growing demand for practical applications of BCA to climate change policy questions. As economists seek to meet this demand, they face challenges that arise from the nature of climate change impacts, such as the long time frame and the potential for non-marginal changes, the importance of intangible effects, and the need to grapple with Knightian uncertainty. As a result of these and other characteristics of climate change, many of the fundamental tenets of BCA are coming under scrutiny and the limits of BCA’s methodological and practical boundaries are being tested. This special issue assembles a set of papers that review the growing body of literature on the economics of climate change. The papers describe the state of the literature valuing climate change impacts, both globally and at more disaggregated levels. The papers also discuss the challenges economists face in applying BCA to support climate change decision making and adaptation planning. This introduction provides background and context on the current use of BCA in climate change analysis, and sets each paper firmly in that context, identifying also areas for future research. While the challenges in conducting BCA and interpreting its results are significant, across the papers it becomes clear that economic analysis in general, and the tools and methods of BCA in particular, have a central role to play in supporting decision-making about how to respond to climate change.

EPA has conducted several ex post assessments of regulatory compliance costs, with the ultimate goal of identifying ways to improve ex ante cost estimation. The work to date has culminated in four case studies that examine five regulations using a common conceptual framework. The standardized framework provides a systematic way to investigate key drivers of compliance costs to see if judgments can be made about why and how ex ante and ex post estimates of costs differ. In addition to describing this conceptual framework, we describe the criteria used to select the rules to be analyzed, summarize the main hypotheses for why ex ante and ex post cost estimates may differ and discuss some of the challenges encountered in conducting these ex post analyses.

This paper discusses the challenges inherent in developing benefit-cost analysis (BCAs) of climate change. Challenges are explored from three perspectives: meeting the foundational premises for conducting BCA within the framework of welfare economics, methodological considerations that affect the application of the tools and techniques of BCA, and practical limitations that arise out of resource constraints and the nature of the question, project, or policy being evaluated. Although economic analysts frequently face – and overcome – conceptual and practical complications in developing BCAs, climate change presents difficulties beyond those posed by more conventional environmental problems. Five characteristics of the climate system and associated impacts on human and natural systems are identified that pose particular challenges to BCA of climate change, including ubiquity of impacts, intangibility, non-marginal changes, long timeframes, and uncertainty. These characteristics interact with traditional economic challenges, such as valuing non-market impact, addressing non-marginal changes, accounting for low-probability but high-impact events, and the eternal issue of appropriately discounting the future. A mapping between the characteristics of climate change and traditional economic challenges highlights the difficulties analysts are likely to encounter in conducting BCA. Despite these challenges, the paper argues that the fundamental ability of economic analysis to evaluate alternatives and tradeoffs is vital to decision making. Climate-related decisions span a wide range in terms of their scope, complexity, and depth, and for many applications of economic analyses the issues associated with climate change are tractable. In other cases it may require improved economic techniques or taking steps to ensure uncertainty is more fully addressed. Augmenting economic analysis with distribution analysis or an account of physical effects, and exploring how economic benefit and cost estimates can be incorporated into broader decision making frameworks have also been suggested. The paper concludes that there are opportunities for BCA to play a key role in informing climate change decision-making.

This paper compares EPA’s ex ante cost analysis of the Cluster Rule, EPA’s first integrated, multi-media regulation, and MACT II Rule to an ex post cost assessment. The goal of this assessment is to determine if actual costs diverged from ex ante costs and, if so, what factors caused this divergence. We find the EPA ex ante costs overestimated the ex post capital costs for the Cluster Rule by 30 to 100%. Contributing factors appear to be use of cleaner technology, flexible compliance options, site-specific rules, shutdowns and consolidations. Ex ante estimates for the MACT II Rule are found to be overestimated by 25% for capital costs and 200 or more percent for annual costs. The primary reason for the overestimate is the use of the bubble compliance strategy that required fewer paper mills to install pollution abatement equipment than anticipated by EPA.

Much is known about private financial returns to education in the form of higher earnings. Less is known about how much social value exceeds this private value. Associations between education and socially-desirable outcomes are strong, but disentangling the effect of education from other causal factors is challenging. The purpose of this paper is to estimate the social value of one form of higher education. We elicit willingness to pay for the Kentucky Community and Technical College System (KCTCS) directly and compare our estimate of total social value to our estimates of private value in the form of increased earnings. Our earnings estimates are based on two distinct data sets, one administrative and one from the U.S. Census. The difference between the total social value and the increase in earnings is our measure of the education externality and the private, non-market value combined. Our work differs from previous research by focusing on education at the community college level and by eliciting values directly through a stated-preferences survey in a way that yields a total value including any external benefits. Our preferred estimates indicate the social value of expanding the system exceeds private financial value by at least 25% with a best point estimate of nearly 90% and exceeds total private value by at least 15% with a best point estimate of nearly 60%.

This paper reviews applications of benefit-cost analysis (BCA) in climate policy assessment at the US national and global scales. Two different but related major application types are addressed. First there are global-scale analyses that focus on calculating optimal global carbon emissions trajectories and carbon prices that maximize global welfare. The second application is the use of the same tools to compute the social cost of carbon (SCC) for use in US regulatory processes. The SCC is defined as the climate damages attributable to an increase of one metric ton of carbon dioxide emissions above a baseline emissions trajectory that assumes no new climate policies. The paper describes the three main quantitative models that have been used in the optimal carbon policy and SCC calculations and then summarizes the range of results that have been produced using them. The results span an extremely broad range (up to an order of magnitude) across modeling platforms as well as across the plausible ranges of input assumptions to a single model. This broad range of results sets the stage for a discussion of the five key challenges that face BCA practitioners participating in the national and global climate change policy analysis arenas: (1) including the possibility of catastrophic outcomes; (2) factoring in equity and income distribution considerations; (3) addressing intertemporal discounting and intergenerational equity; (4) projecting baseline demographics, technological change, and policies inside and outside the energy sector; and (5) characterizing the full set of uncertainties to be dealt with and designing a decision-making process that updates and adapts new scientific and economic information into that process in a timely and productive manner. The paper closes by describing how the BCA models have been useful in climate policy discussions to date despite the uncertainties that pervade the results that have been produced.

Methyl bromide (MBr) has been widely used as a fumigant to control pests in the agricultural sector, but it is also an ozone depleting substance. After 2005, methyl bromide could only be produced when a critical use exemption was agreed to by the signatories to the Montreal Protocol. This paper examines how the EPA’s ex ante cost analyses for open field fresh strawberries in California for the 2006–2010 seasons compare to an ex post assessment of costs. A key input into the ex ante cost analysis is the assumed yield loss associated with methyl bromide alternatives. The EPA used conservative assumptions given the wide range of estimates in the literature at the time, but it appears that a number of viable MBr alternatives – either new fumigants or new ways of applying existing fumigants – may have become available more quickly and resulted in lower yield loss than initially anticipated. Likewise, it appears that farmers who substituted away from methyl bromide did so without imposing large negative impacts on production in prime California strawberry growing areas. Ex post evaluation also confirms the effect of California regulatory restrictions in limiting the use of various economically competitive alternatives. It is worth noting that unanticipated complications after switching away from methyl bromide, such as new diseases, slowed the transition to MBr alternatives.

Prevention of juvenile sex trading in the US has risen to prominence in public policy discourse. We develop a generalized benefit-cost model to shed light on this policy issue and illustrate the framework with a case study from Minnesota. The model treats government-funded intervention as an investment project and calculates its net present value. Benefits are derived from harms avoided by reducing the extent of sex trading. The impacts of youth involvement in the market for sexual services are highly complex, and clear data on them are lacking. To account for empirical ambiguity we develop the model around a representative individual, approximate the effect of intervention on the sex market, and conduct sensitivity analysis with key model parameters. The case study evaluates seventeen distinct harms caused by sex trading based on conservative best estimates from scholarly literature. We find a large positive Net Present Value, suggesting it is in the best interest of Minnesota taxpayers to support intervention.

This paper discusses the current literature on impacts and adaptation costs at the sectoral level. The focus is primarily the US, but includes examples on international applications that highlight key differences or other relevant demonstrations of method and data use. The paper provides an overall framework that addresses the components of economic impacts, including definitions of impacts, adaptation costs, and residual damages. The paper then focuses on understanding the current breadth and depth of the literature that exists to characterize what we know about economic sectors studied in the recent literature (agriculture, coastal resources, water resources, infrastructure, health, crime, energy, labor productivity, and ecosystems), how the methodologies differ, what the gaps and challenges are, and offers a sense of the impacts at the US national level. A new generation of impact studies, including the U.S. EPA’s ongoing Climate Impacts and Risk Analysis (CIRA) project; the new Intergovernmental Panel on Climate Change (IPCC) AR5 Working Group II report; the U.S. National Climate Assessment; and the Risky Business Project led by the Next Generation Foundation, provide the motivation for this review. These efforts, taken together, have advanced the state of US economic impact assessment work along two critical frontiers, both of which support benefit-cost analyses of climate change: assessment of the risk and economic consequences of extreme climatic events; and assessment of ecosystem effects. Yet, the latest work also highlights gaps in the lack of comprehensive sectoral coverage; more complete incorporation of adaptation opportunities in impact assessment; and critical cross- and multi-sectoral effects that remain poorly understood.

This paper compares EPA’s ex ante cost analysis of the 2001 maximum contaminant limit (MCL) for Arsenic in Drinking Water to an ex post assessment of the costs. Because comprehensive cost information for installed treatment technologies or other mitigation strategies pursued by water systems to meet the new standard is not available, this case study relies upon ex post cost data from EPA Demonstration Projects, capturing a total of 50 systems across the US. Information shared by several states and independent associations on the types (but not costs) of treatment technologies used by systems is also summarized. Comparisons of predicted costs to realized costs using our limited data yield mixed results. Plotting the capital cost data from the Demonstration Projects against the cost curves for the compliance technologies recommended for smaller systems, we find that the EPA methodology overestimated capital costs in most cases, especially as the size of the system increases (as measured by the design flow rate).

Behavioral economics posits a number of cognitive biases and limitations, which raises questions as to whether revealed willingness to pay equals true willingness to pay. If so, benefit-cost analysis, with a number of methodological advantages, would need to be replaced. Prior analyses of the issue by Sunstein, Sugden, and Bernheim and Rangel fail to offer guidance that would avoid substituting centralized judgments for decentralized information on benefits and costs. Alternatives including using post-implementation valuations, libertarian paternalism, and direct democracy on policy issues also have conceptual or practical limitations. A tentative suggestion is democratic delegation, somewhat appealing because it is already applied to cope with bounded rationality and non-efficiency values. Viewing benefit-cost analysis as a market analogue, and restricting the domain of behavioral economics to uninformed consumers, may be useful guides. The most important guidance may be to require very strong evidence of substantial choice failure before abandoning benefit-cost analysis.

As directed by the American Recovery and Reinvestment Act of 2009, the US Department of Transportation (DOT) created the Transportation Investment Generating Economic Recovery (TIGER) discretionary grant program for surface transportation infrastructure projects. Through 2013, there have been five rounds of the grant program. TIGER uses a multi-step competitive application process to award surface transportation funds. TIGER applications are initially screened by US DOT’s staff of technical experts. For projects forwarded by the review team, US DOT economic experts then review the applicant’s benefit-cost analysis (BCA) and attempt to determine the likelihood that the benefits exceeded costs (i.e. not the applicant’s self-determination). The final awardees are then selected by a Review Team of Modal Administrators and DOT Office of the Secretary level officials. The purpose of this paper is to discuss many of the common errors in preparing, and issues in reviewing the applicant’s BCA and in making a net benefit determination. A secondary purpose is to determine if the most deserving projects, based on an applicant’s BCA and the likelihood that benefits exceeded costs, are more likely to receive grant funding. We do so for the second through the fifth rounds of the program.

While the need to update EPA benefit-cost analysis to reflect the most recent science is broadly acknowledged, little work has been done examining how well ex ante BCAs estimate the actual benefits and costs of regulations. This paper adds to the existing literature on ex post cost analyses by examining EPA’s analysis of the 1998 Locomotive Emission Standards. Due to data limitations and minimal ability to construct a reasonable counterfactual for each component of the cost analysis, the assessment relies mainly on industry expert opinion, augmented with ex post information from publicly available data sources when possible. The paper finds that the total cost of bringing line-haul locomotives into compliance with the 1998 Locomotive Emission Standards rule remains uncertain. Even though the initial per-unit locomotive compliance costs were higher than predicted by EPA, total costs also depend on the number of locomotives affected by the regulation. Over 2000–2009, the number of newly built line-haul locomotives was higher but the number of remanufactured line-haul locomotives was lower than EPA’s estimate.

The development of national and sectoral climate change adaptation strategies is burgeoning in the US and elsewhere in response to damages from extreme events and projected future risks from climate change. Increasingly, decision makers are requesting information on the economic damages of climate change as well as costs, benefits, and tradeoffs of alternative actions to inform climate adaptation decisions. This paper provides a practical view of the applications of economic analysis to aid climate change adaptation decision making, with a focus on benefit-cost analysis (BCA). We review the recent developments and applications of BCA with implications for climate risk management and adaptation decision making, both in the US and other Organisation for Economic Co-operation and Development countries. We found that BCA is still in early stages of development for evaluating adaptation decisions, and to date is mostly being applied to investment project-based appraisals. Moreover, the best practices of economic analysis are not fully reflected in the BCAs of climate adaptation-relevant decisions. The diversity of adaptation measures and decision-making contexts suggest that evaluation of adaptation measures may require multiple analytical methods. The economic tools and information would need to be transparent, accessible, and match with the decision contexts to be effective in enhancing decision making. Based on the current evidence, a set of analytical considerations is proposed for improving economic analysis of climate adaptation that includes the need to better address uncertainty and to understand the cross-sector and general equilibrium effects of sectoral and national adaptation policy.

Many critics of economic analysis of climate change impacts and response options claim that information is needed on ecosystem characteristics as well as on economic values to fully inform decisions about how climate change affects human well-being. Information on the irreversibility of impacts also is important, critics argue, because it relates to how society evaluates implications for intergenerational equity. In addition, because climate change is subject to a large degree of Knightian uncertainty, it is useful to understand both the information available for assessing climate change risks, and how individuals themselves perceive and evaluate risks. The paper discusses rationales for using these types of information as important complements to benefit-cost analysis for evaluating climate change risks and responses. Ideally such information could be available in a “dashboard” for decision makers assessing social and economic impacts, although limits on currently available information are a significant barrier to using that approach.

It has occasionally been asserted that regulators typically overestimate the costs of the regulations they impose. A number of arguments have been proposed for why this might be the case. The most widely credited is that regulators fail sufficiently to appreciate the effects of innovation in reducing regulatory compliance costs. Most existing studies have found that regulators are more likely to over- than to underestimate costs. While it is difficult to develop summary statistics to aggregate the results of different studies of disparate industries, one such measure is the average of the ratio of ex ante estimates of compliance costs to ex post estimates of the same costs. This ratio is generally greater than one. In this paper I argue that neither the greater frequency of overestimates nor the fact that the average ratio of ex ante to ex post cost estimates is greater than one necessarily demonstrates that ex ante estimates are biased. There are several reasons to suppose that the distribution of compliance costs could be skewed, so that the median of the distribution would lie below the mean. It is not surprising, then, that most estimates would prove to be too high. Moreover, Jensen’s inequality implies that the expected ratio of ex ante to ex post compliance costs would be greater than one. I propose a regression-based test of the bias of ex ante compliance cost estimates, and cannot reject the hypothesis that estimates are unbiased. Failure to reject a hypothesis with limited and noisy data should not, of course, be interpreted as a strong argument to accept the hypothesis. Rather, this paper argues for the generation of more and better information. Despite the existence of a number of papers reporting ex ante and ex post compliance cost estimates, it is surprisingly difficult to get a large sample with which to make such comparisons.

The core analytical elements of Executive Order 12291 are widely seen as having been embraced by both Democratic and Republican administrations. Some critics argue, however, that this embrace is superficial and serves more as a cover for political decisions. To address this question, this paper examines the analytical priorities presented in the annual Report to Congress on the Benefits and Costs of Federal Regulations over the period from 1997 to 2012. While there is general agreement across administrations on such broad issues as the importance of benefit-cost analysis in providing a shared framework and discipline to the analytic process, we identify important differences in five areas: monetization of benefits, scope of costs considered, behavioral economics, intergenerational benefits, and the general equilibrium impacts of regulation. All are active and exciting issues in the current scholarly work on regulation. These cross-administration differences appear to reflect a relatively modest shifting across political parties on issues where reasonable people might disagree, rather than major ideological swings in approach.

Benefit-cost analysis (BCA) aims to help people make better decisions. But BCA does not always serve this role as well as intended. In particular, BCA’s aim of aggregating all attributes of concern to decision makers into a single, best-estimate metric can conflict with the differing world views and values that may be an inherent characteristic of many climate-related decisions. This paper argues that new approaches exist that can help reduce the tension between the benefits of providing useful, scientifically based information to decision makers and the costs of aggregating uncertainty and differing values into single best estimates. Enabled by new information technology, these approaches can summarize decision-relevant information in new ways. Viewed in this light, many limitations of BCA lie not in the approach itself, but with the way it is used. In particular, this paper will argue that the problem lies in a process that begins by first assigning agreed-upon values to all the relevant inputs and then using BCA to rank the desirability of alternative decision options. In contrast, BCA can be used as part of a process that begins by acknowledging a wide range of ethical and epistemological views, examines which combinations of views are most important in affecting the ranking among proposed decision options, and uses this information to identify and seek consensus on actions that are robust over a wide range of such views.