The regulatory-reform debate in the 104th Congress has highlighted the role of benefit-cost analysis and cost-effectiveness analysis in regulatory decision-making. Each of the last five presidents has issued an executive order requiring estimation and consideration of the benefits and costs of major regulatory actions, but the questions of how and to what extent regulatory decisions are determined by economic considerations remains controversial.

Risk-assessment results can be used as the basis for estimating costs and benefits for the purpose of economic analysis, and the results of both risk assessment and economic analysis can contribute to or possibly even determine a regulatory decision. Both risk assessments and regulatory analyses can help improve risk management decisions. However, risk assessment and economic analysis can involve large investments of resources and multiple assumptions, and they produce uncertain results. Their results contribute only part of the information that must be considered in making decisions about the best ways to protect human health and the environment.

In view of the important and complementary roles of risk assessment and economic analysis, the Commission decided to consider the strengths and limitations of economic analysis, although it was not explicitly mandated to do so. The Commission relied on an invited issue paper by Alan Krupnick, Michael Toman, and Ray Kopp of Resources for the Future (see appendix A.5 for abstract) and on invited testimony and comments received from Lester Lave, of Carnegie Mellon University, Richard Morgenstern, of Resources for the Future (on leave from EPA), Nicholas Ashford, of MIT, Douglas MacLean, of the University of Maryland, and John Graham, of the Harvard School of Public Health.

This section briefly addresses the role of benefit-cost analysis (BCA) and cost-effectiveness analysis (CEA) (hereafter referred to as "economic analysis") in regulatory decision-making. Some health and environmental statutes requirethe consideration of costs and benefits in risk-related decision-making; others explicitly exclude their consideration, while still others are silent. Like risk- assessment results, the results of economic analyses have often been communicated solely in numeric terms and accompanied by little information on assumptions, nonquantified benefits and costs, and the analyst's confidence in the results. The 1996 Economic Report of the President recognizes the important role of cost and benefit considerations in risk-management decision-making, while highlighting the need to take uncertainty into account and to include factors that cannot be monetized or quantified.

FINDING 4.1.1: The role of economic analysis in regulatory decision-making is controversial. There is a concern that economic analysis places too much emphasis on assigning dollar values to aspects of health and the environment, which are difficult, if not impossible, to quantify and there is also a concern that regulatory decisions about health and environmental protection might be made strictly on the basis of whether their quantifiable benefits outweigh their monetized, quantifiable costs.

RECOMMENDATION: The tools of economic analysis should be recognized as legitimate and useful ways to obtain information for the risk-management framework and for regulatory decisions that will affect health, safety, and the environment, but not as the sole or overriding determinant of those regulatory decisions. Information about costs and benefits that cannot be assigned monetary values should be addressed and considered explicitly. Assumptions should be specified.

RATIONALE

Economic analysis plays an important role in our risk-management framework (see section 2). Like risk assessment, the tools of economic analysis have strengths and limitations. And like social and political considerations and information on risks to health and the environment, economic analysis can provide important input to risk-management and regulatory policy decisions. Considering costs and benefits in regulatory decision-making can help to clarify the tradeoffs and implications associated with alternative regulatory policies and help regulatory agencies to set priorities. Economic analysis can contribute to making better use of society's limited resources.

The goals and objectives of the tools of economic analysis differ. In cost-effectiveness analysis, which is a particular form of benefit-cost analysis, one of several options that achieves a specified regulatory goal with the smallest loss in overall social well-being is selected (while acknowledging that costs and benefits might be inequitably distributed; see section 4.1.2). CEA begins with an assumed goal and then explores the methods that could achieve that goal to identify the least-costly one. For example, if the health-based goal is to lower the current ambient-ozone standard to 0.1 ppm, CEA could be used to help to choose among options all of which are expected to attain the 0.1-ppm standard but use different approaches which give rise to different costs.

CEA also can be applied to assess the relative cost of different means of achieving intermediate regulatory goals. Suppose, for example, that several alternatives can be pursued to reduce automobile exhaust emissions as part of a larger ozone-control strategy. CEA can be used to rank the cost per unit of emissions reduction of those alternatives. Policy-makers could then compare the vehicle policies with other options to determine the least-cost way to achieve the larger goal of ozone reduction.

BCA has a different role: it can be used to assess the benefits and costs of alternative health-based standards with different levels of health protection. Consider the following hypothetical example:

In this example, BCA could assist EPA in selecting the standard that it should adopt by translating health effects into dollar-equivalent units with such methods as "willingness-to-pay". The willingness-to-pay concept reflects the economic principle that environmental quality and risk reductions ultimately are things people value, just as they value conventional consumer goods, and that it is possible, in principle, to infer how much people will give up to gain environmental improvements. In this hypothetical example, if economic analysis indicated that the public were willing to pay up to $5 million per averted health effect, the "efficient" standard would be between 5 and 20 ppm. This approach might be rejected if willingness-to-pay is unknown, BCA is considered inapplicable, or benefits are nonquantifiable. CEA, in contrast, could compare the costs of implementing different methods of control with the number of deaths or health effects that would be prevented by those controls. The policy-maker would have to decide which cost is acceptable and select a standard that is consistent with that cost and in keeping with other desired goals of the decision-making process.

The advantage of BCA, in principle, is that, guided by what members of society are thought to be willing to pay to reduce risk, it can be used to help make choices among policies and actions with quite different benefits and costs. It is no small challenge to compare, for example, costs and benefits of reducing lead derived from paint contamination in houses with those ambient of ozone reduction. Thus, BCA applied in a strict quantitative sense can be used only to the extent that costs and benefits can be monetized. In some cases, benefits and costs might be nonquantifiable because of the absence of reliable data, not because they are intrinsically nonquantifiable. In such cases, it is better to rely on qualitative analysis than to produce an indefensible quantitative analysis. When there are believed to be substantial benefits (or costs) that cannot be monetized, a BCA should be supplemented by discussion of the nonquantifiable elements, as emphasized in the 1996 Economic Report of the President. Effective methods of including nonquantifiable benefits in economic analysis are needed and should be pursued. At a minimum, good practice would include listing what the analyst believes are potentially important nonquantifiable benefits (and costs).

An example of a method for evaluating both quantifiable and nonquantifiable benefits is a study of environmental damages caused by the generation of electricity (Rowe et al. 1995). Benefits were divided into four categories: benefits quantifiable; damages probably de minimis, so quantification not justified; quantification possible but more resources required for analysis; and quantification not possible. The first category included the health benefits of reducing air pollution because the epidemiologic, cancer-risk, and valuation literature regarding air pollution is relatively rich. The benefits of reducing acid deposition on crops, vegetation, and forests were placed in the second category. The third category included impacts of surface-water chemical discharges on fisheries; monetization of the effects was thought to be possible for some chemicals, but many assumptions would be needed and the effects were unlikely to be large. The effect of greenhouse gases on climate was a prominent example in the fourth category; instead of monetization, a sensitivity analysis was provided, which indicated that every dollar of damage per ton of CO₂ emitted was equivalent to 0.1 cent per kilowatt-hour when electricity is generated by coal. Other category-four examples are the effects of air pollution on wildlife and the effects of acid deposition on cultural and historic materials.

A BCA of a proposed policy should also be supplemented with information on its distributional consequences. In an assessment of aggregate benefits and costs there is no accounting for who bears the risks and who bears the costs of the policy so, for example, it does not explicitly weigh consequences by income category or ethnic group.⁽¹⁾

A benefit of CEA, in contrast, is that it does not require monetized benefits (although they can be monetized when appropriate).⁽²⁾ CEA requires only that the "effectiveness" of a policy be defined by some physical measure (such as tons by which pollutants are reduced, or number of cancer deaths avoided). The cost of different policies per unit of effect can be compared. CEA cannot inform the debate over the goals of a policy, but it can provide information about the cost per death or effect averted; it is up to the policy-maker to decide how to use that information to make a decision. There is, however, a problem with CEA that its proponents sometimes overlook. If a proposed program has more than one favorable effect--for example, it saves lives, reduces illness, and provides ecological or aesthetic benefits--it is difficult, if not impossible, to compare it to other proposed programs on the basis of cost per one of the beneficial effects. If the other favorable effects can be monetized and subtracted from the costs, then a net cost-per-life-saved calculation could be made. By the same token, an estimate of the net costs of ecological or aesthetic benefits can be made by deducting estimates of reduced morbidity and mortality risk.

Despite its limitations, BCA can provide useful information to help to evaluate the favorable and unfavorable effects of proposed regulatory policies and should continue to be used as appropriate to inform, but not as the sole criterion for, decision-making. As the recent report Benefit-Cost Analysis in Environmental, Health, and Safety Regulation put it, "benefit-cost analysis is neither necessary nor sufficient for designing sensible public policy. If properly done, it can be very helpful to agencies in the decision-making process" (Arrow et al. 1996). But because estimates of costs and benefits are uncertain, BCA cannot be used to "prove" that the benefits of a policy outweigh its costs, nor should it be used as the only basis of a decision. However, providing information about the costs and benefits associated with a regulatory decision serves the public interest and, in fact, is mandated in the unfunded mandates reform act and executive order 12866. Moreover, BCA can be an important element of a more-inclusive set of decisional criteria for assessing the potential value of regulation. In particular, to ascertain that the benefits of regulations justify their costs, as stipulated in Executive Order 12866, it is important not only to identify and measure the costs and benefits that can be quantified but also identify those which are less quantifiable. A clear rationale should be provided for a regulatory decision based on both quantifiable and nonquantifiable elements. All economic analyses should include explicit information about the assumptions and uncertainties that underlie estimates of costs and benefits.

FINDING 4.1.2: Economic analyses have been criticized because they are often blind to issues of environmental equity and fail to make explicit who bears the costs of a regulatory decision and who reaps the benefits.

RECOMMENDATION: Economic analyses should present information, where practicable, that can be used to provide a firmer basis for evaluating any inequitable distributions of costs and benefits.

RATIONALE

CBAs generally do not address the equity implications of the policies that they seek to evaluate. For example, if implementing a policy that affects health, safety, or the environment decreases the welfare of poor people and increases the welfare of rich people, but the rich people's gain outweighs the poor people's loss, CBA would show the policy to lead to an improvement in aggregate social welfare while acknowledging the disproportionate or inequitable distributions of costs and benefits. For example, cutbacks in spending for abatement or control of lead-based paint might put poor people at greater risk for lead toxicity but result in lower taxes for rich people.

CBAs need not incorporate equity considerations quantitatively, however. Deciding how different groups should be weighted for equity in economic analysis would be highly value-laden. No objectively correct weightings can be substantiated. However, if groups or individuals within a societal group potentially affected by a policy are likely to feel the impact differently, they can be identified, and that information can be communicated to risk managers or regulatory decision-makers and considered as policies are formulated.

Human-health risk assessments often consider especially susceptible population groups (see sections 3.1 and 3.2). For example, a risk assessment might give children or pregnant women special consideration because they can suffer the adverse effects of toxicant exposure to a greater degree than the general population. Quantifying that special susceptibility and deciding how it should be reflected in standard-setting is usually highly subjective. But regulators have to recognize and identify the extent of protection for relevant subpopulations.

By analogy, identifying particular population segments that will no longer be able to afford particular fruits or vegetables because of a policy that reduces permissible pesticide residues, for example, while identifying other population segments whose health risks from pesticides are reduced because of that policy but that can afford to continue to buy those fruits and vegetables should be relatively straightforward. Evaluating such differences quantitatively would be problematic, but revealing them qualitatively would provide important information that could be considered in the regulatory decision.

1 Equity considerations can be considered in BCA, but doing so requires agreement on how to weight different social groups. No objectively correct weights can be substantiated (see issue 4.4).

² If benefits are not monetized, they cannot be aggregated, which is an advantage of using a money metric.