Circular A-4 

September 17, 2003 

TO THE HEADS OF EXECUTIVE AGENCIES AND ESTABLISHMENTS 

Subject: Regulatory Analysis 

This Circular provides the Office of Management and Budget’s (OMB=s) guidance to 

Federal agencies on the development of regulatory analysis as required under Section 6(a)(3)(c) 

of Executive Order12866, ARegulatory Planning and Review,@ the Regulatory Right-to-Know 

Act, and a variety of related authorities. The Circular also provides guidance to agencies on the 

regulatory accounting statements that are required under the Regulatory Right-to-Know Act. 

This Circular refines OMB=s Abest practices@ document of 1996 

(http://www.whitehouse.gov/omb/inforeg/riaguide.html), which was issued as a guidance in 

2000 (http://www.whitehouse.gov/omb/memoranda/m00-08.pdf), and reaffirmed in 2001 

(http://www.whitehouse.gov/omb/memoranda/m01-23.html). It replaces both the 1996 Abest 

practices@ and the 2000 guidance. 

In developing this Circular, OMB first developed a draft that was subject to public 

comment, interagency review, and peer review. Peer reviewers included Cass Sunstein, 

University of Chicago; Lester Lave, Carnegie Mellon University; Milton C. Weinstein and 

James K. Hammitt of the Harvard School of Public Health; Kerry Smith, North Carolina State 

University; Jonathan Weiner, Duke University Law School; Douglas K. Owens, Stanford 

University; and W. Kip Viscusi, Harvard Law School. Although these individuals submitted 

comments, OMB is solely responsible for the final content of this Circular. 

A. Introduction

This Circular is designed to assist analysts in the regulatory agencies by defining good 

regulatory analysis B called either Aregulatory analysis@ or Aanalysis@ for brevity B and 

standardizing the way benefits and costs of Federal regulatory actions are measured and reported. 

Executive Order 12866 requires agencies to conduct a regulatory analysis for economically 

significant regulatory actions as defined by Section 3(f)(1). This requirement applies to 

rulemakings that rescind or modify existing rules as well as to rulemakings that establish new 

requirements. 

The Need for Analysis of Proposed Regulatory Actions1

Regulatory analysis is a tool regulatory agencies use to anticipate and evaluate the likely 

consequences of rules. It provides a formal way of organizing the evidence on the key effects B

 

1 We use the term “proposed” to refer to any regulatory actions under consideration regardless of the stage of the 

regulatory process. 

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good and bad B of the various alternatives that should be considered in developing regulations. 

The motivation is to (1) learn if the benefits of an action are likely to justify the costs or (2) 

discover which of various possible alternatives would be the most cost-effective. 

A good regulatory analysis is designed to inform the public and other parts of the 

Government (as well as the agency conducting the analysis) of the effects of alternative actions. 

Regulatory analysis sometimes will show that a proposed action is misguided, but it can also 

demonstrate that well-conceived actions are reasonable and justified. 

Benefit-cost analysis is a primary tool used for regulatory analysis.2

 Where all benefits

and costs can be quantified and expressed in monetary units, benefit-cost analysis provides 

decision makers with a clear indication of the most efficient alternative, that is, the alternative 

that generates the largest net benefits to society (ignoring distributional effects). This is useful 

information for decision makers and the public to receive, even when economic efficiency is not 

the only or the overriding public policy objective. 

It will not always be possible to express in monetary units all of the important benefits

and costs. When it is not, the most efficient alternative will not necessarily be the one with the 

largest quantified and monetized net-benefit estimate. In such cases, you should exercise 

professional judgment in determining how important the non-quantified benefits or costs may be 

in the context of the overall analysis. If the non-quantified benefits and costs are likely to be 

important, you should carry out a Athreshold@ analysis to evaluate their significance. Threshold 

or Abreak-even@ analysis answers the question, AHow small could the value of the non-quantified 

benefits be (or how large would the value of the non-quantified costs need to be) before the rule 

would yield zero net benefits?@ In addition to threshold analysis you should indicate, where 

possible, which non-quantified effects are most important and why. 

Key Elements of a Regulatory Analysis 

A good regulatory analysis should include the following three basic elements: (1) a 

statement of the need for the proposed action, (2) an examination of alternative approaches, and 

(3) an evaluation of the benefits and costs—quantitative and qualitative—of the proposed action 

and the main alternatives identified by the analysis. 

To evaluate properly the benefits and costs of regulations and their alternatives, you will 

need to do the following: 

• Explain how the actions required by the rule are linked to the expected benefits. For 

example, indicate how additional safety equipment will reduce safety risks. A similar 

analysis should be done for each of the alternatives. 

• Identify a baseline. Benefits and costs are defined in comparison with a clearly stated 

alternative. This normally will be a Ano action@ baseline: what the world will be like if

the proposed rule is not adopted. Comparisons to a Anext best@ alternative are also 

especially useful. 

 

2

 See Mishan EJ (1994), Cost-Benefit Analysis, fourth edition, Routledge, New York. 

2
• Identify the expected undesirable side-effects and ancillary benefits of the proposed 

regulatory action and the alternatives. These should be added to the direct benefits and 

costs as appropriate. 

With this information, you should be able to assess quantitatively the benefits and costs 

of the proposed rule and its alternatives. A complete regulatory analysis includes a discussion of 

non-quantified as well as quantified benefits and costs. A non-quantified outcome is a benefit or 

cost that has not been quantified or monetized in the analysis. When there are important nonmonetary values at stake, you should also identify them in your analysis so policymakers can 

compare them with the monetary benefits and costs. When your analysis is complete, you 

should present a summary of the benefit and cost estimates for each alternative, including the 

qualitative and non-monetized factors affected by the rule, so that readers can evaluate them. 

As you design, execute, and write your regulatory analysis, you should seek out the 

opinions of those who will be affected by the regulation as well as the views of those individuals 

and organizations who may not be affected but have special knowledge or insight into the 

regulatory issues. Consultation can be useful in ensuring that your analysis addresses all of the 

relevant issues and that you have access to all pertinent data. Early consultation can be 

especially helpful. You should not limit consultation to the final stages of your analytical efforts. 

You will find that you cannot conduct a good regulatory analysis according to a formula. 

Conducting high-quality analysis requires competent professional judgment. Different 

regulations may call for different emphases in the analysis, depending on the nature and 

complexity of the regulatory issues and the sensitivity of the benefit and cost estimates to the key

assumptions. 

A good analysis is transparent. It should be possible for a qualified third party reading 

the report to see clearly how you arrived at your estimates and conclusions. For transparency=s 

sake, you should state in your report what assumptions were used, such as the time horizon for 

the analysis and the discount rates applied to future benefits and costs. It is usually necessary to 

provide a sensitivity analysis to reveal whether, and to what extent, the results of the analysis are 

sensitive to plausible changes in the main assumptions and numeric inputs. 

A good analysis provides specific references to all sources of data, appendices with 

documentation of models (where necessary), and the results of formal sensitivity and other 

uncertainty analyses. Your analysis should also have an executive summary, including a 

standardized accounting statement. 

B. The Need for Federal Regulatory Action 

Before recommending Federal regulatory action, an agency must demonstrate that the 

proposed action is necessary. If the regulatory intervention results from a statutory or judicial 

directive, you should describe the specific authority for your action, the extent of discretion 

available to you, and the regulatory instruments you might use. Executive Order 12866 states 

that AFederal agencies should promulgate only such regulations as are required by law, are 

necessary to interpret the law, or are made necessary by compelling need, such as material 

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failures of private markets to protect or improve the health and safety of the public, the 

environment, or the well being of the American people ... .@ 

Executive Order 12866 also states that AEach agency shall identify the problem that it 

intends to address (including, where applicable, the failures of private markets or public 

institutions that warrant new agency action) as well as assess the significance of that problem.@ 

Thus, you should try to explain whether the action is intended to address a significant market 

failure or to meet some other compelling public need such as improving governmental processes 

or promoting intangible values such as distributional fairness or privacy. If the regulation is 

designed to correct a significant market failure, you should describe the failure both qualitatively 

and (where feasible) quantitatively. You should show that a government intervention is likely to 

do more good than harm. For other interventions, you should also provide a demonstration of 

compelling social purpose and the likelihood of effective action. Although intangible rationales 

do not need to be quantified, the analysis should present and evaluate the strengths and 

limitations of the relevant arguments for these intangible values. 

Market Failure or Other Social Purpose 

The major types of market failure include: externality, market power, and inadequate or 

asymmetric information. Correcting market failures is a reason for regulation, but it is not the 

only reason. Other possible justifications include improving the functioning of government, 

removing distributional unfairness, or promoting privacy and personal freedom. 

1. Externality, common property resource and public good 

An externality occurs when one party's actions impose uncompensated benefits or costs 

on another party. Environmental problems are a classic case of externality. For example, the 

smoke from a factory may adversely affect the health of local residents while soiling the property 

in nearby neighborhoods. If bargaining were costless and all property rights were well defined, 

people would eliminate externalities through bargaining without the need for government 

regulation.3

 From this perspective, externalities arise from high transactions costs and/or poorly 

defined property rights that prevent people from reaching efficient outcomes through market 

transactions.

Resources that may become congested or overused, such as fisheries or the broadcast 

spectrum, represent common property resources. APublic goods,@ such as defense or basic 

scientific research, are goods where provision of the good to some individuals cannot occur 

without providing the same level of benefits free of charge to other individuals. 

2. Market Power 

Firms exercise market power when they reduce output below what would be offered in a 

competitive industry in order to obtain higher prices. They may exercise market power 

collectively or unilaterally. Government action can be a source of market power, such as when 

regulatory actions exclude low-cost imports. Generally, regulations that increase market power 

 

3

 See Coase RH (1960), Journal of Law and Economics, 3, 1-44. 

4
for selected entities should be avoided. However, there are some circumstances in which 

government may choose to validate a monopoly. If a market can be served at lowest cost only 

when production is limited to a single producer B local gas and electricity distribution services, 

for example B a natural monopoly is said to exist. In such cases, the government may choose to 

approve the monopoly and to regulate its prices and/or production decisions. Nevertheless, you 

should keep in mind that technological advances often affect economies of scale. This can, in 

turn, transform what was once considered a natural monopoly into a market where competition 

can flourish. 

3. Inadequate or Asymmetric Information 

Market failures may also result from inadequate or asymmetric information. Because 

information, like other goods, is costly to produce and disseminate, your evaluation will need to 

do more than demonstrate the possible existence of incomplete or asymmetric information. Even 

though the market may supply less than the full amount of information, the amount it does 

supply may be reasonably adequate and therefore not require government regulation. Sellers 

have an incentive to provide information through advertising that can increase sales by 

highlighting distinctive characteristics of their products. Buyers may also obtain reasonably 

adequate information about product characteristics through other channels, such as a seller 

offering a warranty or a third party providing information. 

Even when adequate information is available, people can make mistakes by processing it 

poorly. Poor information-processing often occurs in cases of low probability, high-consequence 

events, but it is not limited to such situations. For instance, people sometimes rely on mental 

rules-of-thumb that produce errors. If they have a clear mental image of an incident which 

makes it cognitively Aavailable,@ they might overstate the probability that it will occur. 

Individuals sometimes process information in a biased manner, by being too optimistic or 

pessimistic, without taking sufficient account of the fact that the outcome is exceedingly unlikely 

to occur. When mistakes in information processing occur, markets may overreact. When it is 

time-consuming or costly for consumers to evaluate complex information about products or 

services (e.g., medical therapies), they may expect government to ensure that minimum quality 

standards are met. However, the mere possibility of poor information processing is not enough 

to justify regulation. If you think there is a problem of information processing that needs to be 

addressed, it should be carefully documented. 

4. Other Social Purposes 

There are justifications for regulations in addition to correcting market failures. A 

regulation may be appropriate when you have a clearly identified measure that can make 

government operate more efficiently. In addition, Congress establishes some regulatory 

programs to redistribute resources to select groups. Such regulations should be examined to 

ensure that they are both effective and cost-effective. Congress also authorizes some regulations 

to prohibit discrimination that conflicts with generally accepted norms within our society. 

Rulemaking may also be appropriate to protect privacy, permit more personal freedom or 

promote other democratic aspirations. 

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Showing That Regulation at the Federal Level Is the Best Way to Solve the Problem 

Even where a market failure clearly exists, you should consider other means of dealing 

with the failure before turning to Federal regulation. Alternatives to Federal regulation include 

antitrust enforcement, consumer-initiated litigation in the product liability system, or 

administrative compensation systems. 

In assessing whether Federal regulation is the best solution, you should also consider the 

possibility of regulation at the State or local level. In some cases, the nature of the market failure 

may itself suggest the most appropriate governmental level of regulation. For example, 

problems that spill across State lines (such as acid rain whose precursors are transported widely 

in the atmosphere) are probably best addressed by Federal regulation. More localized problems, 

including those that are common to many areas, may be more efficiently addressed locally. 

The advantages of leaving regulatory issues to State and local authorities can be 

substantial. If public values and preferences differ by region, those differences can be reflected 

in varying State and local regulatory policies. Moreover, States and localities can serve as a 

testing ground for experimentation with alternative regulatory policies. One State can learn from

another=s experience while local jurisdictions may compete with each other to establish the best 

regulatory policies. You should examine the proper extent of State and local discretion in your 

rulemaking context. 

A diversity of rules may generate gains for the public as governmental units compete 

with each other to serve the public, but duplicative regulations can also be costly. Where Federal 

regulation is clearly appropriate to address interstate commerce issues, you should try to examine 

whether it would be more efficient to retain or reduce State and local regulation. The local 

benefits of State regulation may not justify the national costs of a fragmented regulatory system. 

For example, the increased compliance costs for firms to meet different State and local 

regulations may exceed any advantages associated with the diversity of State and local 

regulation. Your analysis should consider the possibility of reducing as well as expanding State 

and local rulemaking. 

The role of Federal regulation in facilitating U.S. participation in global markets should 

also be considered. Harmonization of U.S. and international rules may require a strong Federal 

regulatory role. Concerns that new U.S. rules could act as non-tariff barriers to imported goods 

should be evaluated carefully. 

The Presumption Against Economic Regulation

Government actions can be unintentionally harmful, and even useful regulations can 

impede market efficiency. For this reason, there is a presumption against certain types of 

regulatory action. In light of both economic theory and actual experience, a particularly 

demanding burden of proof is required to demonstrate the need for any of the following types of 

regulations: 

• price controls in competitive markets;

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• production or sales quotas in competitive markets;

• mandatory uniform quality standards for goods or services if the potential problem can be 

adequately dealt with through voluntary standards or by disclosing information of the 

hazard to buyers or users; or 

• controls on entry into employment or production, except (a) where indispensable to 

protect health and safety (e.g., FAA tests for commercial pilots) or (b) to manage the use 

of common property resources (e.g., fisheries, airwaves, Federal lands, and offshore 

areas). 

C. Alternative Regulatory Approaches 

Once you have determined that Federal regulatory action is appropriate, you will need to 

consider alternative regulatory approaches. Ordinarily, you will be able to eliminate some

alternatives through a preliminary analysis, leaving a manageable number of alternatives to be 

evaluated according to the formal principles of the Executive Order. The number and choice of 

alternatives selected for detailed analysis is a matter of judgment. There must be some balance 

between thoroughness and the practical limits on your analytical capacity. With this qualification 

in mind, you should nevertheless explore modifications of some or all of a regulation=s attributes 

or provisions to identify appropriate alternatives. The following is a list of alternative regulatory 

actions that you should consider. 

Different Choices Defined by Statute 

When a statute establishes a specific regulatory requirement and the agency is 

considering a more stringent standard, you should examine the benefits and costs of reasonable 

alternatives that reflect the range of the agency=s statutory discretion, including the specific 

statutory requirement. 

Different Compliance Dates 

The timing of a regulation may also have an important effect on its net benefits. Benefits 

may vary significantly with different compliance dates where a delay in implementation may 

result in a substantial loss in future benefits (e.g., a delay in implementation could result in a 

significant reduction in spawning stock and jeopardize a fishery). Similarly, the cost of a 

regulation may vary substantially with different compliance dates for an industry that requires a 

year or more to plan its production runs. In this instance, a regulation that provides sufficient 

lead time is likely to achieve its goals at a much lower overall cost than a regulation that is 

effective immediately. 

Different Enforcement Methods 

Compliance alternatives for Federal, State, or local enforcement include on-site 

inspections, periodic reporting, and noncompliance penalties structured to provide the most 

appropriate incentives. When alternative monitoring and reporting methods vary in their benefits 

and costs, you should identify the most appropriate enforcement framework. For example, in 

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some circumstances random monitoring or parametric monitoring will be less expensive and 

nearly as effective as continuous monitoring. 

Different Degrees of Stringency 

In general, both the benefits and costs associated with a regulation will increase with the 

level of stringency (although marginal costs generally increase with stringency, whereas 

marginal benefits may decrease). You should study alternative levels of stringency to understand 

more fully the relationship between stringency and the size and distribution of benefits and costs 

among different groups. 

Different Requirements for Different Sized Firms 

You should consider setting different requirements for large and small firms, basing the 

requirements on estimated differences in the expected costs of compliance or in the expected 

benefits. The balance of benefits and costs can shift depending on the size of the firms being 

regulated. Small firms may find it more costly to comply with regulation, especially if there are 

large fixed costs required for regulatory compliance. On the other hand, it is not efficient to 

place a heavier burden on one segment of a regulated industry solely because it can better afford 

the higher cost. This has the potential to load costs on the most productive firms, costs that are 

disproportionate to the damages they create. You should also remember that a rule with a 

significant impact on a substantial number of small entities will trigger the requirements set forth 

in the Regulatory Flexibility Act. (5 U.S.C. 603(c), 604). 

Different Requirements for Different Geographic Regions 

Rarely do all regions of the country benefit uniformly from government regulation. It is 

also unlikely that costs will be uniformly distributed across the country. Where there are 

significant regional variations in benefits and/or costs, you should consider the possibility of 

setting different requirements for the different regions. 

Performance Standards Rather than Design Standards 

Performance standards express requirements in terms of outcomes rather than specifying 

the means to those ends. They are generally superior to engineering or design standards because 

performance standards give the regulated parties the flexibility to achieve regulatory objectives 

in the most cost-effective way. In general, you should take into account both the cost savings to 

the regulated parties of the greater flexibility and the costs of assuring compliance through 

monitoring or some other means. 

Market-Oriented Approaches Rather than Direct Controls 

Market-oriented approaches that use economic incentives should be explored. These 

alternatives include fees, penalties, subsidies, marketable permits or offsets, changes in liability 

or property rights (including policies that alter the incentives of insurers and insured parties), and 

required bonds, insurance or warranties. One example of a market-oriented approach is a 

8
program that allows for averaging, banking, and/or trading (ABT) of credits for achieving 

additional emission reductions beyond the required air emission standards. ABT programs can 

be extremely valuable in reducing costs or achieving earlier or greater benefits, particularly when 

the costs of achieving compliance vary across production lines, facilities, or firms. ABT can be 

allowed on a plant-wide, firm-wide, or region-wide basis rather than vent by vent, provided this 

does not produce unacceptable local air quality outcomes (such as Ahot spots@ from local 

pollution concentration).

Informational Measures Rather than Regulation 

If intervention is contemplated to address a market failure that arises from inadequate or 

asymmetric information, informational remedies will often be preferred. Measures to improve 

the availability of information include government establishment of a standardized testing and 

rating system (the use of which could be mandatory or voluntary), mandatory disclosure 

requirements (e.g., by advertising, labeling, or enclosures), and government provision of 

information (e.g., by government publications, telephone hotlines, or public interest broadcast 

announcements). A regulatory measure to improve the availability of information, particularly 

about the concealed characteristics of products, provides consumers a greater choice than a 

mandatory product standard or ban. 

Specific informational measures should be evaluated in terms of their benefits and costs. 

Some effects of informational measures are easily overlooked. The costs of a mandatory 

disclosure requirement for a consumer product will include not only the cost of gathering and 

communicating the required information, but also the loss of net benefits of any information 

displaced by the mandated information. The other costs also may include the effect of providing 

information that is ignored or misinterpreted, and inefficiencies arising from the incentive that 

mandatory disclosure may give to overinvest in a particular characteristic of a product or service. 

Where information on the benefits and costs of alternative informational measures is 

insufficient to provide a clear choice between them, you should consider the least intrusive 

informational alternative sufficient to accomplish the regulatory objective. To correct an 

informational market failure it may be sufficient for government to establish a standardized 

testing and rating system without mandating its use, because competing firms that score well 

according to the system should thereby have an incentive to publicize the fact. 

D. Analytical Approaches 

Both benefit-cost analysis (BCA) and cost-effectiveness analysis (CEA) provide a 

systematic framework for identifying and evaluating the likely outcomes of alternative 

regulatory choices. A major rulemaking should be supported by both types of analysis wherever 

possible. Specifically, you should prepare a CEA for all major rulemakings for which the 

primary benefits are improved public health and safety to the extent that a valid effectiveness 

measure can be developed to represent expected health and safety outcomes. You should also 

perform a BCA for major health and safety rulemakings to the extent that valid monetary values 

can be assigned to the primary expected health and safety outcomes. In undertaking these 

analyses, it is important to keep in mind the larger objective of analytical consistency in 

9
estimating benefits and costs across regulations and agencies, subject to statutory limitations. 

Failure to maintain such consistency may prevent achievement of the most risk reduction for a 

given level of resource expenditure. For all other major rulemakings, you should carry out a 

BCA. If some of the primary benefit categories cannot be expressed in monetary units, you 

should also conduct a CEA. In unusual cases where no quantified information on benefits, costs 

and effectiveness can be produced, the regulatory analysis should present a qualitative discussion 

of the issues and evidence. 

Benefit-Cost Analysis 

A distinctive feature of BCA is that both benefits and costs are expressed in monetary 

units, which allows you to evaluate different regulatory options with a variety of attributes using 

a common measure.4

 By measuring incremental benefits and costs of successively more 

stringent regulatory alternatives, you can identify the alternative that maximizes net benefits. 

The size of net benefits, the absolute difference between the projected benefits and costs, 

indicates whether one policy is more efficient than another. The ratio of benefits to costs is not a 

meaningful indicator of net benefits and should not be used for that purpose. It is well known 

that considering such ratios alone can yield misleading results. 

 

Even when a benefit or cost cannot be expressed in monetary units, you should still try to 

measure it in terms of its physical units. If it is not possible to measure the physical units, you 

should still describe the benefit or cost qualitatively. For more information on describing 

qualitative information, see the section “Developing Benefit and Cost Estimates.” 

When important benefits and costs cannot be expressed in monetary units, BCA is less 

useful, and it can even be misleading, because the calculation of net benefits in such cases does 

not provide a full evaluation of all relevant benefits and costs. 

You should exercise professional judgment in identifying the importance of nonquantified factors and assess as best you can how they might change the ranking of alternatives 

based on estimated net benefits. If the non-quantified benefits and costs are likely to be 

important, you should recommend which of the non-quantified factors are of sufficient 

importance to justify consideration in the regulatory decision. This discussion should also 

include a clear explanation that support designating these non-quantified factors as important. In 

this case, you should also consider conducting a threshold analysis to help decision makers and 

other users of the analysis to understand the potential significance of these factors to the overall 

analysis. 

Cost-Effectiveness Analysis5

4

 Mishan EJ (1994), Cost-Benefit Analysis, fourth edition, Routledge, New York. 5

 For a full discussion of CEA, see Gold, ML, Siegel, JE, Russell, LB, and Weinstein, MC (1996), Cost 

Effectiveness in Health and Medicine: The Report of the Panel on Cost-Effectiveness in Health and Medicine, 

Oxford University Press, New York. 

10
Cost-effectiveness analysis can provide a rigorous way to identify options that achieve 

the most effective use of the resources available without requiring monetization of all of relevant 

benefits or costs. Generally, cost-effectiveness analysis is designed to compare a set of 

regulatory actions with the same primary outcome (e.g., an increase in the acres of wetlands 

protected) or multiple outcomes that can be integrated into a single numerical index (e.g., units 

of health improvement). 

 

Cost-effectiveness results based on averages need to be treated with great care. They 

suffer from the same drawbacks as benefit-cost ratios. The alternative that exhibits the smallest 

cost-effectiveness ratio may not be the best option, just as the alternative with the highest 

benefit-cost ratio is not always the one that maximizes net benefits. Incremental costeffectiveness analysis (discussed below) can help to avoid mistakes that can occur when policy 

choices are based on average cost-effectiveness.

CEA can also be misleading when the Aeffectiveness@ measure does not appropriately 

weight the consequences of the alternatives. For example, when effectiveness is measured in 

tons of reduced pollutant emissions, cost-effectiveness estimates will be misleading unless the 

reduced emissions of diverse pollutants result in the same health and environmental benefits. 

When you have identified a range of alternatives (e.g., different levels of stringency), you 

should determine the cost-effectiveness of each option compared with the baseline as well as its 

incremental cost-effectiveness compared with successively more stringent requirements. Ideally, 

your CEA would present an array of cost-effectiveness estimates that would allow comparison 

across different alternatives. However, analyzing all possible combinations is not practical when 

there are many options (including possible interaction effects). In these cases, you should use 

your judgment to choose reasonable alternatives for careful consideration. 

When constructing and comparing incremental cost-effectiveness ratios, you should be 

careful to determine whether the various alternatives are mutually exclusive or whether they can 

be combined. If they can be combined, you should consider which might be favored under 

different regulatory budget constraints (implicit or explicit). You should also make sure that 

inferior alternatives identified by the principles of strong and weak dominance are eliminated 

from consideration.6

The value of CEA is enhanced when there is consistency in the analysis across a diverse 

set of possible regulatory actions. To achieve consistency, you need to carefully construct the 

two key components of any CEA: the cost and the Aeffectiveness@ or performance measures for 

the alternative policy options. 

With regard to measuring costs, you should be sure to include all the relevant costs to 

society B whether public or private. Rulemakings may also yield cost savings (e.g., energy 

savings associated with new technologies). The numerator in the cost-effectiveness ratio should 

reflect net costs, defined as the gross cost incurred to comply with the requirements (sometimes 

 

6

 Gold ML, Siegel JE, Russell LB, and Weinstein MC (1996), Cost Effectiveness in Health and Medicine: The

Report of the Panel on Cost-Effectiveness in Health and Medicine, Oxford University Press, New York, pp. 284-

285. 

11
called Atotal@ costs) minus any cost savings. You should be careful to avoid double-counting 

effects in both the numerator and the denominator of the cost-effectiveness ratios. For example, 

it would be incorrect to reduce gross costs by an estimated monetary value on life extension if 

life-years are already used as the effectiveness measure in the denominator. 

In constructing measures of Aeffectiveness@, final outcomes, such as lives saved or lifeyears saved, are preferred to measures of intermediate outputs, such as tons of pollution reduced, 

crashes avoided, or cases of disease avoided. Where the quality of the measured unit varies (e.g., 

acres of wetlands vary substantially in terms of their ecological benefits), it is important that the 

measure capture the variability in the value of the selected Aoutcome@ measure. You should 

provide an explanation of your choice of effectiveness measure. 

Where regulation may yield several different beneficial outcomes, a cost-effectiveness 

comparison becomes more difficult to interpret because there is more than one measure of 

effectiveness to incorporate in the analysis. To arrive at a single measure you will need to 

weight the value of disparate benefit categories, but this computation raises some of the same

difficulties you will encounter in BCA. If you can assign a reasonable monetary value to all of 

the regulation=s different benefits, then you should do so. But in this case, you will be doing 

BCA, not CEA. 

When you can estimate the monetary value of some but not all of the ancillary benefits of 

a regulation, but cannot assign a monetary value to the primary measure of effectiveness, you 

should subtract the monetary estimate of the ancillary benefits from the gross cost estimate to 

yield an estimated net cost. (This net cost estimate for the rule may turn out to be negative B that 

is, the monetized benefits exceed the cost of the rule.) If you are unable to estimate the value of 

some of the ancillary benefits, the cost-effectiveness ratio will be overstated, and this should be 

acknowledged in your analysis. CEA does not yield an unambiguous choice when there are 

benefits or costs that have not been incorporated in the net-cost estimates. You also may use 

CEA to compare regulatory alternatives in cases where the statute specifies the level of benefits 

to be achieved. 

The Effectiveness Metric for Public Health and Safety Rulemakings 

When CEA is applied to public health and safety rulemakings, one or more measures of 

effectiveness must be selected that permits comparison of regulatory alternatives. Agencies 

currently use a variety of effectiveness measures. 

There are relatively simple measures such as the number of lives saved, cases of cancer 

reduced, and cases of paraplegia prevented. Sometimes these measures account only for 

mortality information, such as the number of lives saved and the number of years of life saved. 

There are also more comprehensive, integrated measures of effectiveness such as the number of 

"equivalent lives" (ELs) saved and the number of "quality-adjusted life years" (QALYs) saved. 

The main advantage of the integrated measures of effectiveness is that they account for a 

rule's impact on morbidity (nonfatal illness, injury, impairment and quality of life) as well as 

premature death. The inclusion of morbidity effects is important because (a) some illnesses (e.g., 

12
asthma) cause more instances of pain and suffering than they do premature death, (b) some

population groups are known to experience elevated rates of morbidity (e.g, the elderly and the 

poor) and thus have a strong interest in morbidity measurement

7

, and (c) some regulatory 

alternatives may be more effective at preventing morbidity than premature death (e.g., some

advanced airbag designs may diminish the nonfatal injuries caused by airbag inflation without 

changing the frequency of fatal injury prevented by airbags). 

However, the main drawback of these integrated measures is that they must meet some 

restrictive assumptions to represent a valid measure of individual preferences.8

 For example, a 

QALY measure implicitly assumes that the fraction of remaining lifespan an individual would 

give up for an improvement in health-related quality of life does not depend on the remaining 

lifespan. Thus, if an individual is willing to give up 10 years of life among 50 remaining years 

for a given health improvement, he or she would also be willing to give up 1 year of life among 5 

remaining years. To the extent that individual preferences deviate from these assumptions, 

analytic results from CEA using QALYs could differ from analytic results based on willingnessto-pay-measures.9

 Though willingness to pay is generally the preferred economic method for 

evaluating preferences, the CEA method, as applied in medicine and health, does not evaluate 

health changes using individual willingness to pay. When performing CEA, you should consider 

using at least one integrated measure of effectiveness when a rule creates a significant impact on 

both mortality and morbidity. 

When CEA is performed in specific rulemaking contexts, you should be prepared to 

make appropriate adjustments to ensure fair treatment of all segments of the population. 

Fairness is important in the choice and execution of effectiveness measures. For example, if 

QALYs are used to evaluate a lifesaving rule aimed at a population that happens to experience a 

high rate of disability (i.e., where the rule is not designed to affect the disability), the number of

life years saved should not necessarily be diminished simply because the rule saves the lives of 

people with life-shortening disabilities. Both analytic simplicity and fairness suggest that the 

estimated number of life years saved for the disabled population should be based on average life 

expectancy information for the relevant age cohorts. More generally, when numeric adjustments 

are made for life expectancy or quality of life, analysts should prefer use of population averages 

rather than information derived from subgroups dominated by a particular demographic or 

income group. 

OMB does not require agencies to use any specific measure of effectiveness. In fact, 

OMB encourages agencies to report results with multiple measures of effectiveness that offer 

different insights and perspectives. The regulatory analysis should explain which measures were 

selected and why, and how they were implemented. 

The analytic discretion provided in choice of effectiveness measure will create some

inconsistency in how agencies evaluate the same injuries and diseases, and it will be difficult for 

 

7

 Russell LB and Sisk JE (2000), “Modeling Age Differences in Cost Effectiveness Analysis”, International Journal 

of Technology Assessment in Health Care, 16(4), 1158-1167. 8

 Pliskin JS, Shepard DS, and Weinstein MC (1980), "Utility Functions for Life Years and Health Status," 

Operations Research, 28(1), 206-224. 9

 Hammitt JK (2002), "QALYs Versus WTP," Risk Analysis, 22(5), pp. 985-1002.

13
OMB and the public to draw meaningful comparisons between rulemakings that employ 

different effectiveness measures. As a result, agencies should use their web site to provide OMB 

and the public with the underlying data, including mortality and morbidity data, the age 

distribution of the affected populations, and the severity and duration of disease conditions and 

trauma, so that OMB and the public can construct apples-to-apples comparisons between 

rulemakings that employ different measures. 

There are sensitive technical and ethical issues associated with choosing one or more of 

these integrated measures for use throughout the Federal government. The Institute of Medicine 

(IOM) may assemble a panel of specialists in cost-effectiveness analysis and bioethics to 

evaluate the advantages and disadvantages of these different measures and other measures that 

have been suggested in the academic literature. OMB believes that the IOM guidance will 

provide Federal agencies and OMB useful insight into how to improve the measurement of 

effectiveness of public health and safety regulations. 

Distributional Effects 

Those who bear the costs of a regulation and those who enjoy its benefits often are not 

the same people. The term Adistributional effect@ refers to the impact of a regulatory action 

across the population and economy, divided up in various ways (e.g., income groups, race, sex, 

industrial sector, geography). Benefits and costs of a regulation may also be distributed 

unevenly over time, perhaps spanning several generations. Distributional effects may arise 

through @transfer payments@ that stem from a regulatory action as well. For example, the 

revenue collected through a fee, surcharge in excess of the cost of services provided, or tax is a 

transfer payment. 

Your regulatory analysis should provide a separate description of distributional effects 

(i.e., how both benefits and costs are distributed among sub-populations of particular concern) so 

that decision makers can properly consider them along with the effects on economic efficiency. 

Executive Order 12866 authorizes this approach. Where distributive effects are thought to be 

important, the effects of various regulatory alternatives should be described quantitatively to the 

extent possible, including the magnitude, likelihood, and severity of impacts on particular 

groups. You should be alert for situations in which regulatory alternatives result in significant 

changes in treatment or outcomes for different groups. Effects on the distribution of income that 

are transmitted through changes in market prices can be important, albeit sometimes difficult to 

assess. Your analysis should also present information on the streams of benefits and costs over 

time in order to provide a basis for assessing intertemporal distributional consequences, 

particularly where intergenerational effects are concerned. 

E. Identifying and Measuring Benefits and Costs 

This Section provides guidelines for your preparation of the benefit and cost estimates 

required by Executive Order 12866 and the ARegulatory Right-to-Know Act.@ The discussions in 

previous sections will help you identify a workable number of alternatives for consideration in 

your analysis and an appropriate analytical approach to use. 

14
General Issues 

1. Scope of Analysis

Your analysis should focus on benefits and costs that accrue to citizens and residents of 

the United States. Where you choose to evaluate a regulation that is likely to have effects 

beyond the borders of the United States, these effects should be reported separately. The time 

frame for your analysis should cover a period long enough to encompass all the important 

benefits and costs likely to result from the rule. 

2. Developing a Baseline

You need to measure the benefits and costs of a rule against a baseline. This baseline 

should be the best assessment of the way the world would look absent the proposed action. The 

choice of an appropriate baseline may require consideration of a wide range of potential factors, 

including: 

• evolution of the market, 

• changes in external factors affecting expected benefits and costs, 

• changes in regulations promulgated by the agency or other government entities, and 

• the degree of compliance by regulated entities with other regulations. 

It may be reasonable to forecast that the world absent the regulation will resemble the 

present. If this is the case, however, your baseline should reflect the future effect of current 

government programs and policies. For review of an existing regulation, a baseline assuming 

Ano change@ in the regulatory program generally provides an appropriate basis for evaluating 

regulatory alternatives. When more than one baseline is reasonable and the choice of baseline 

will significantly affect estimated benefits and costs, you should consider measuring benefits and 

costs against alternative baselines. In doing so you can analyze the effects on benefits and costs 

of making different assumptions about other agencies= regulations, or the degree of compliance 

with your own existing rules. In all cases, you must evaluate benefits and costs against the same

baseline. You should also discuss the reasonableness of the baselines used in the sensitivity 

analyses. For each baseline you use, you should identify the key uncertainties in your forecast. 

EPA=s 1998 final PCB disposal rule provides a good example of using different baselines. 

EPA used several alternative baselines, each reflecting a different interpretation of existing 

regulatory requirements. In particular, one baseline reflected a literal interpretation of EPA=s 

1979 rule and another the actual implementation of that rule in the year immediately preceding 

the 1998 revision. The use of multiple baselines illustrated the substantial effect changes in 

EPA=s implementation policy could have on the cost of a regulatory program. In the years after 

EPA adopted the 1979 PCB disposal rule, changes in EPA policy -- especially allowing the 

disposal of automobile Ashredder fluff@ in municipal landfills -- reduced the cost of the program

by more than $500 million per year.

In some cases, substantial portions of a rule may simply restate statutory requirements 

that would be self-implementing, even in the absence of the regulatory action. In these cases, 

15
you should use a pre-statute baseline. If you are able to separate out those areas where the 

agency has discretion, you may also use a post-statute baseline to evaluate the discretionary 

elements of the action. 

3. Evaluation of Alternatives 

You should describe the alternatives available to you and the reasons for choosing one 

alternative over another. As noted previously, alternatives that rely on incentives and offer 

increased flexibility are often more cost-effective than more prescriptive approaches. For 

instance, user fees and information dissemination may be good alternatives to direct commandand-control regulation. Within a command-and-control regulatory program, performance-based 

standards generally offer advantages over standards specifying design, behavior, or manner of 

compliance. 

You should carefully consider all appropriate alternatives for the key attributes or 

provisions of the rule. The previous discussion outlines examples of appropriate alternatives. 

Where there is a Acontinuum@ of alternatives for a standard (such as the level of stringency), you 

generally should analyze at least three options: the preferred option; a more stringent option that 

achieves additional benefits (and presumably costs more) beyond those realized by the preferred 

option; and a less stringent option that costs less (and presumably generates fewer benefits) than 

the preferred option. 

You should choose reasonable alternatives deserving careful consideration. In some

cases, a regulatory program will focus on an option that is near or at the limit of technical 

feasibility. In this case, the analysis would not need to examine a more stringent option. For 

each of the options analyzed, you should compare the anticipated benefits to the corresponding 

costs. 

It is not adequate simply to report a comparison of the agency=s preferred option to the 

chosen baseline. Whenever you report the benefits and costs of alternative options, you should 

present both total and incremental benefits and costs. You should present incremental benefits 

and costs as differences from the corresponding estimates associated with the next less-stringent 

alternative.10 It is important to emphasize that incremental effects are simply differences 

between successively more stringent alternatives. Results involving a comparison to a Anext 

best@ alternative may be especially useful. 

In some cases, you may decide to analyze a wide array of options. In 1998, DOE 

analyzed a large number of options in setting new energy efficiency standards for refrigerators 

and freezers and produced a rich amount of information on their relative effects. This analysis -- 

examining more than 20 alternative performance standards for one class of refrigerators with 

top-mounted freezers -- enabled DOE to select an option that produced $200 more in estimated 

net benefits per refrigerator than the least attractive option. 

 

10 For the least stringent alternative, you should estimate the incremental benefits and costs relative to the baseline. 

Thus, for this alternative, the incremental effects would be the same as the corresponding totals. For each alternative 

that is more stringent than the least stringent alternative, you should estimate the incremental benefits and costs 

relative to the closest less-stringent alternative. 

16
You should analyze the benefits and costs of different regulatory provisions separately 

when a rule includes a number of distinct provisions. If the existence of one provision affects the 

benefits or costs arising from another provision, the analysis becomes more complicated, but the 

need to examine provisions separately remains. In this case, you should evaluate each specific 

provision by determining the net benefits of the proposed regulation with and without it. 

Analyzing all possible combinations of provisions is impractical if the number is large 

and interaction effects are widespread. You need to use judgment to select the most significant or 

relevant provisions for such analysis. You are expected to document all of the alternatives that

were considered in a list or table and which were selected for emphasis in the main analysis. 

You should also discuss the statutory requirements that affect the selection of regulatory 

approaches. If legal constraints prevent the selection of a regulatory action that best satisfies the 

philosophy and principles of Executive Order 12866, you should identify these constraints and 

estimate their opportunity cost. Such information may be useful to Congress under the 

Regulatory Right-to-Know Act. 

4. Transparency and Reproducibility of Results 

Because of its influential nature and its special role in the rulemaking process, it is 

appropriate to set minimum quality standards for regulatory analysis. You should provide 

documentation that the analysis is based on the best reasonably obtainable scientific, technical, 

and economic information available. To achieve this, you should rely on peer-reviewed 

literature, where available, and provide the source for all original information. 

A good analysis should be transparent and your results must be reproducible. You should 

clearly set out the basic assumptions, methods, and data underlying the analysis and discuss the 

uncertainties associated with the estimates. A qualified third party reading the analysis should be 

able to understand the basic elements of your analysis and the way in which you developed your 

estimates. 

To provide greater access to your analysis, you should generally post it, with all the 

supporting documents, on the internet so the public can review the findings. You should also 

disclose the use of outside consultants, their qualifications, and history of contracts and 

employment with the agency (e.g., in a preface to the RIA). Where other compelling interests 

(such as privacy, intellectual property, trade secrets, etc.) prevent the public release of data or 

key elements of the analysis, you should apply especially rigorous robustness checks to analytic 

results and document the analytical checks used. 

Finally, you should assure compliance with the Information Quality Guidelines for your 

agency and OMB=s AGuidelines for Ensuring and Maximizing the Quality, Objectivity, Utility, 

and Integrity of Information Disseminated by Federal Agencies@ (Adata quality guidelines@) 

http://www.whitehouse.gov/omb/fedreg/reproducible.html.

17
Developing Benefit and Cost Estimates 

1. Some General Considerations 

The analysis document should discuss the expected benefits and costs of the selected 

regulatory option and any reasonable alternatives. How is the proposed action expected to 

provide the anticipated benefits and costs? What are the monetized values of the potential real

incremental benefits and costs to society? To present your results, you should: 

• include separate schedules of the monetized benefits and costs that show the type and 

timing of benefits and costs, and express the estimates in this table in constant, 

undiscounted dollars (for more on discounting see “Discount Rates” below); 

• list the benefits and costs you can quantify, but cannot monetize, including their timing; 

• describe benefits and costs you cannot quantify; and 

• identify or cross-reference the data or studies on which you base the benefit and cost 

estimates. 

When benefit and cost estimates are uncertain (for more on this see “Treatment of 

Uncertainty” below), you should report benefit and cost estimates (including benefits of risk 

reductions) that reflect the full probability distribution of potential consequences. Where 

possible, present probability distributions of benefits and costs and include the upper and lower 

bound estimates as complements to central tendency and other estimates. 

If fundamental scientific disagreement or lack of knowledge prevents construction of a 

scientifically defensible probability distribution, you should describe benefits or costs under 

plausible scenarios and characterize the evidence and assumptions underlying each alternative 

scenario. 

2. The Key Concepts Needed to Estimate Benefits and Costs 

“Opportunity cost@ is the appropriate concept for valuing both benefits and costs. The 

principle of Awillingness-to-pay@ (WTP) captures the notion of opportunity cost by measuring 

what individuals are willing to forgo to enjoy a particular benefit. In general, economists tend to 

view WTP as the most appropriate measure of opportunity cost, but an individual=s Awillingnessto-accept@ (WTA) compensation for not receiving the improvement can also provide a valid 

measure of opportunity cost. 

WTP and WTA are comparable measures under special circumstances. WTP and WTA 

measures may be comparable in the following situations: if a regulation affects a price change 

rather than a quantity change; the change being evaluated is small; there are reasonably close 

substitutes available; and the income effect is small.11 However, empirical evidence from

experimental economics and psychology shows that even when income/wealth effects are 

“small”, the measured differences between WTP and WTA can be large.12 WTP is generally 

 

11 See Hanemann WM (1991), American Economic Review, 81(3), 635-647. 12 See Kahneman D, Knetsch JL, and Thaler RH (1991), "Anomalies: The Endowment Effect, Loss Aversion, and 

Status Quo Bias," Journal of Economic Perspectives 3(1), 192-206.

18
considered to be more readily measurable. Adoption of WTP as the measure of value implies 

that individual preferences of the affected population should be a guiding factor in the regulatory 

analysis. 

Market prices provide rich data for estimating benefits and costs based on willingness-topay if the goods and services affected by the regulation are traded in well-functioning 

competitive markets. The opportunity cost of an alternative includes the value of the benefits 

forgone as a result of choosing that alternative. The opportunity cost of banning a product -- a 

drug, food additive, or hazardous chemical -- is the forgone net benefit (i.e., lost consumer and 

producer surplus13 ) of that product, taking into account the mitigating effects of potential 

substitutes. 

The use of any resource has an opportunity cost regardless of whether the resource is 

already owned or has to be purchased. That opportunity cost is equal to the net benefit the 

resource would have provided in the absence of the requirement. For example, if regulation of 

an industrial plant affects the use of additional land or buildings within the existing plant 

boundary, the cost analysis should include the opportunity cost of using the additional land or 

facilities. 

To the extent possible, you should monetize any such forgone benefits and add them to 

the other costs of that alternative. You should also try to monetize any cost savings as a result of 

an alternative and either add it to the benefits or subtract it from the costs of that alternative. 

However, you should not assume that the Aavoided@ costs of not doing another regulatory 

alternative represent the benefits of a regulatory action where there is no direct, necessary 

relationship between the two. You should also be careful when the costs avoided are attributable 

to an existing regulation. Even when there is a direct relationship between the two regulatory 

actions, the use of avoided costs is problematic because the existing regulation may not 

maximize net benefits and thus may itself be questionable policy. (See the section, ADirect Use 

of Market Data,@ for more detail.) 

Estimating benefits and costs when market prices are hard to measure or markets do not 

exist is more difficult. In these cases, you need to develop appropriate proxies that simulate 

market exchange. Estimates of willingness-to-pay based on revealed preference methods can be 

quite useful. As one example, analysts sometimes use Ahedonic price equations@ based on 

multiple regression analysis of market behavior to simulate market prices for the commodity of

interest. The hedonic technique allows analysts to develop an estimate of the price for specific 

attributes associated with a product. For instance, a house is a product characterized by a variety 

of attributes including the number of rooms, total floor area, and type of heating and cooling. If 

there are enough data on transactions in the housing market, it is possible to develop an estimate 

of the implicit price for specific attributes, such as the implicit price of an additional bathroom or 

for central air conditioning. This technique can be extended, as well, to develop an estimate for 

 

13 Consumer surplus is the difference between what a consumer pays for a unit of a good and the maximum amount

the consumer would be willing to pay for that unit. It is measured by the area between the price and the demand

curve for that unit. Producer surplus is the difference between the amount a producer is paid for a unit of a good and 

the minimum amount the producer would accept to supply that unit. It is measured by the area between the price 

and the supply curve for that unit. 

19
the implicit price of public goods that are not directly traded in markets. An analyst can develop 

implicit price estimates for public goods like air quality and access to public parks by assessing 

the effects of these goods on the housing market. Going through the analytical process of 

deriving benefit estimates by simulating markets may also suggest alternative regulatory 

strategies that create such markets. 

You need to guard against double-counting, since some attributes are embedded in other 

broader measures. To illustrate, when a regulation improves the quality of the environment in a 

community, the value of real estate in the community generally rises to reflect the greater 

attractiveness of living in a better environment. Simply adding the increase in property values to 

the estimated value of improved public health would be double counting if the increase in 

property values reflects the improvement in public health. To avoid this problem you should 

separate the embedded effects on the value of property arising from improved public health. At 

the same time, an analysis that fails to incorporate the consequence of land use changes when 

accounting for costs will not capture the full effects of regulation. 

3. Revealed Preference Methods 

Revealed preference methods develop estimates of the value of goods and services -- or 

attributes of those goods and services -- based on actual market decisions by consumers, workers 

and other market participants. If the market participant is well informed and confronted with a 

real choice, it may be feasible to determine accurately and precisely the monetary value needed 

for a rulemaking. There is a large and well-developed literature on revealed preference in the 

peer-reviewed, applied economics literature. 

Although these methods are well grounded in economic theory, they are sometimes 

difficult to implement given the complexity of market transactions and the paucity of relevant 

data. When designing or evaluating a revealed preference study, the following principles should 

be considered: 

• the market should be competitive. If the market isn=t competitive (e.g., monopoly, 

oligopoly), then you should consider making adjustments such that the price reflects the 

true value to society (often called the Ashadow price@); 

• the market should not exhibit a significant information gap or asymmetric information 

problem. If the market suffers from information problems, then you should discuss the 

divergence of the price from the underlying shadow price and consider possible 

adjustments to reflect the underlying shadow price; 

• the market should not exhibit an externality. In this case, you should discuss the 

divergence of the price from the underlying shadow price and consider possible 

adjustments to reflect the underlying shadow price; 

• the specific market participants being studied should be representative of the target 

populations to be affected by the rulemaking under consideration; 

• a valid research design and framework for analysis should be adopted. Examples include 

using data and/or model specifications that include the markets for substitute and 

complementary goods and services and using reasonably unrestricted functional forms. 

When specifying substitute and complementary goods, the analysis should preferably be 

20
based on data about the range of alternatives perceived by market participants. If such 

data are not available, you should adopt plausible assumptions and describe the 

limitations of the analysis. 

• the statistical and econometric models employed should be appropriate for the application 

and the resulting estimates should be robust in response to plausible changes in model 

specification and estimation technique; and 

• the results should be consistent with economic theory. 

You should also determine whether there are multiple revealed-preference studies of the 

same good or service and whether anything can be learned by comparing the methods, data and 

findings from different studies. Professional judgment is required to determine whether a 

particular study is of sufficient quality to justify use in regulatory analysis. When studies are 

used in regulatory analysis despite their technical weaknesses (e.g., due to the absence of other 

evidence), the regulatory analysis should discuss any biases or uncertainties that are likely to 

arise due to those weaknesses. If a study has major weaknesses, the study should not be used in 

regulatory analysis. 

a. Direct Uses of Market Data 

Economists ordinarily consider market prices as the most accurate measure of the 

marginal value of goods and services to society. In some instances, however, market prices may 

not reflect the true value of goods and services due to market imperfections or government 

intervention. If a regulation involves changes to goods or services where the market price is not 

a good measure of the value to society, you should use an estimate that reflects the shadow price. 

Suppose a particular air pollutant damages crops. One of the benefits of controlling that 

pollutant is the value of the crop yield increase as a result of the controls. That value is typically 

measured by the price of the crop. However, if the price is held above the market price by a 

government program that affects supply, a value estimate based on this price may not reflect the 

true benefits of controlling the pollutant. In this case, you should calculate the value to society 

of the increase in crop yields by estimating the shadow price, which reflects the value to society 

of the marginal use of the crop. If the marginal use is for exports, you should use the world 

price. If the marginal use is to add to very large surplus stockpiles, you should use the value of 

the last units released from storage minus storage cost. If stockpiles are large and growing, the 

shadow price may be low or even negative. 

Other goods whose market prices may not reflect their true value include those whose 

production or consumption results in substantial (1) positive or negative external effects or (2) 

transfer payments. For example, the observed market price of gasoline may not reflect marginal 

social value due to the inclusion of taxes, other government interventions, and negative 

externalities (e.g., pollution). This shadow price may also be needed for goods whose market 

price is substantially affected by existing regulations that do not maximize net benefits. 

b. Indirect Uses of Market Data 

Many goods or attributes of goods that are affected by regulation--such as preserving 

environmental or cultural amenities--are not traded directly in markets. The value for these 

21
goods or attributes arise both from use and non-use. Estimation of these values is difficult 

because of the absence of an organized market. However, overlooking or ignoring these values 

in your regulatory analysis may significantly understate the benefits and/or costs of regulatory 

action. 

AUse values@ arise where an individual derives satisfaction from using the resource, either 

now or in the future. Use values are associated with activities such as swimming, hunting, and 

hiking where the individual makes use of the natural environment. 

“Non-use values@ arise where an individual places value on a resource, good or service 

even though the individual will not use the resource, now or in the future. Non-use value 

includes bequest and existence values. 

General altruism for the health and welfare of others is a closely related concept but may 

not be strictly considered a Anon-use@ value.14 A general concern for the welfare of others should 

supplement benefits and costs equally; hence, it is not necessary to measure the size of general 

altruism in regulatory analysis. If there is evidence of selective altruism, it needs to be

considered specifically in both benefits and costs. 

Some goods and services are indirectly traded in markets, which means that their value is 

reflected in the prices of related goods and services that are directly traded in markets. Their use 

values are typically estimated through revealed preference methods. Examples include estimates 

of the values of environmental amenities derived from travel-cost studies, and hedonic price 

models that measure differences or changes in the value of real estate. It is important that you 

utilize revealed preference models that adhere to economic criteria that are consistent with utility 

maximizing behavior. Also, you should take particular care in designing protocols for reliably 

estimating the values of these attributes. 

4. Stated Preference Methods 

Stated Preference Methods (SPM) have been developed and used in the peer-reviewed 

literature to estimate both Ause@ and Anon-use@ values of goods and services. They have also 

been widely used in regulatory analyses by Federal agencies, in part, because these methods can 

be creatively employed to address a wide variety of goods and services that are not easy to study 

through revealed preference methods. 

The distinguishing feature of these methods is that hypothetical questions about use or nonuse values are posed to survey respondents in order to obtain willingness-to-pay estimates 

relevant to benefit or cost estimation. Some examples of SPM include contingent valuation, 

conjoint analysis and risk-tradeoff analysis. The surveys used to obtain the health-utility values 

used in CEA are similar to stated-preference surveys but do not entail monetary measurement of 

value. Nevertheless, the principles governing quality stated-preference research, with some

obvious exceptions involving monetization, are also relevant in designing quality health-utility 

research. 

 

14 See McConnell KE (1997), Journal of Environmental Economics and Management, 32, 22-37.

22
When you are designing or evaluating a stated-preference study, the following principles 

should be considered: 

• the good or service being evaluated should be explained to the respondent in a clear, 

complete and objective fashion, and the survey instrument should be pre-tested; 

• willingness-to-pay questions should be designed to focus the respondent on the reality of 

budgetary limitations and alerted to the availability of substitute goods and alternative 

expenditure options; 

• the survey instrument should be designed to probe beyond general attitudes (e.g., a 

"warm glow" effect for a particular use or non-use value) and focus on the magnitude of 

the respondent's economic valuation; 

• the analytic results should be consistent with economic theory using both "internal" 

(within respondent) and "external" (between respondent) scope tests such as the 

willingness to pay is larger (smaller) when more (less) of a good is provided; 

• the subjects being interviewed should be selected/sampled in a statistically appropriate 

manner. The sample frame should adequately cover the target population. The sample 

should be drawn using probability methods in order to generalize the results to the target 

population; 

• response rates should be as high as reasonably possible. Best survey practices should be 

followed to achieve high response rates. Low response rates increase the potential for 

bias and raise concerns about the generalizability of the results. If response rates are not 

adequate, you should conduct an analysis of non-response bias or further study. Caution 

should be used in assessing the representativeness of the sample based solely on 

demographic profiles. Statistical adjustments to reduce non-response bias should be 

undertaken whenever feasible and appropriate; 

• the mode of administration of surveys (in-person, phone, mail, computer, internet or 

multiple modes ) should be appropriate in light of the nature of the questions being posed 

to respondents and the length and complexity of the instrument; 

• documentation should be provided about the target population, the sampling frame used 

and its coverage of the target population, the design of the sample including any 

stratification or clustering, the cumulative response rate (including response rate at each 

stage of selection if applicable); the item non-response rate for critical questions; the 

exact wording and sequence of questions and other information provided to respondents; 

and the training of interviewers and techniques they employed (as appropriate); 

• the statistical and econometric methods used to analyze the collected data should be 

transparent, well suited for the analysis, and applied with rigor and care. 

Professional judgment is necessary to apply these criteria to one or more studies, and thus 

there is no mechanical formula that can be used to determine whether a particular study is of 

sufficient quality to justify use in regulatory analysis. When studies are used despite having 

weaknesses on one or more of these criteria, those weaknesses should be acknowledged in the 

regulatory analysis, including any resulting biases or uncertainties that are likely to result. If a 

study has too many weaknesses with unknown consequences for the quality of the data, the study 

should not be used. 

23
The challenge in designing quality stated-preference studies is arguably greater for nonuse values and unfamiliar use values than for familiar goods or services that are traded (directly 

or indirectly) in market transactions. The good being valued may have little meaning to 

respondents, and respondents may be forming their valuations for the first time in response to the 

questions posed. Since these values are effectively constructed by the respondent during the 

elicitation, the instrument and mode of administration should be rigorously pre-tested to make 

sure that responses are not simply an artifact of specific features of instrument design and/or 

mode of administration. 

Since SPM generate data from respondents in a hypothetical setting, often on complex 

and unfamiliar goods, special care is demanded in the design and execution of surveys, analysis 

of the results, and characterization of the uncertainties. A stated-preference study may be the 

only way to obtain quantitative information about non-use values, though a number based on a 

poor quality study is not necessarily superior to no number at all. Non-use values that are not 

quantified should be presented as an “intangible” benefit or cost. 

If both revealed-preference and stated-preference studies that are directly applicable to 

regulatory analysis are available, you should consider both kinds of evidence and compare the 

findings. If the results diverge significantly, you should compare the overall size and quality of 

the two bodies of evidence. Other things equal, you should prefer revealed preference data over 

stated preference data because revealed preference data are based on actual decisions, where 

market participants enjoy or suffer the consequences of their decisions. This is not generally the 

case for respondents in stated preference surveys, where respondents may not have sufficient 

incentives to offer thoughtful responses that are more consistent with their preferences or may be 

inclined to bias their responses for one reason or another. 

5. Benefit-Transfer Methods 

It is often preferable to collect original data on revealed preference or stated preference to 

support regulatory analysis. Yet conducting an original study may not be feasible due to the time 

and expense involved. One alternative to conducting an original study is the use of "benefit 

transfer" methods. (The transfer may involve cost determination as well). The practice of 

Abenefit transfer@ began with transferring existing estimates obtained from indirect market and 

stated preference studies to new contexts (i.e., the context posed by the rulemaking). The 

principles that guide transferring estimates from indirect market and stated preference studies 

should apply to direct market studies as well. 

Although benefit-transfer can provide a quick, low-cost approach for obtaining desired 

monetary values, the methods are often associated with uncertainties and potential biases of 

unknown magnitude. It should therefore be treated as a last-resort option and not used without 

explicit justification. 

In conducting benefit transfer, the first step is to specify the value to be estimated for the 

rulemaking. You should identify the relevant measure of the policy change at this initial stage. 

For instance, you can derive the relevant willingness-to-pay measure by specifying an indirect 

utility function. This identification allows you to Azero in@ on key aspects of the benefit transfer. 

24
The next step is to identify appropriate studies to conduct benefit transfer. In selecting 

transfer studies for either point transfers or function transfers, you should base your choices on 

the following criteria: 

• The selected studies should be based on adequate data, sound and defensible empirical 

methods and techniques. 

• The selected studies should document parameter estimates of the valuation function. 

• The study context and policy context should have similar populations (e.g., demographic 

characteristics). The market size (e.g., target population) between the study site and the 

policy site should be similar. For example, a study valuing water quality improvement in 

Rhode Island should not be used to value policy that will affect water quality throughout 

the United States. 

• The good, and the magnitude of change in that good, should be similar in the study and 

policy contexts. 

• The relevant characteristics of the study and the policy contexts should be similar. For 

example, the effects examined in the original study should be Areversible@ or 

“irreversible” to a degree that is similar to the regulatory actions under consideration. 

• The distribution of property rights should be similar so that the analysis uses the same

welfare measure. If the property rights in the study context support the use of WTA 

measures while the rights in the rulemaking context support the use of WTP measures, 

benefit transfer is not appropriate. 

• The availability of substitutes across study and policy contexts should be similar. 

If you can choose between transferring a function or a point estimate, you should transfer 

the entire demand function (referred to as benefit function transfer) rather than adopting a single 

point estimate (referred to as benefit point transfer).15

Finally, you should not use benefit transfer in estimating benefits if: 

• resources are unique or have unique attributes. For example, if a policy change affects 

snowmobile use in Yellowstone National Park, then a study valuing snowmobile use in 

the state of Michigan should not be used to value changes in snowmobile use in the 

Yellowstone National Park. 

• If the study examines a resource that is unique or has unique attributes, you should not 

transfer benefit estimates or benefit functions to value a different resource and vice versa. 

For example, if a study values visibility improvements at the Grand Canyon, these results 

should not be used to value visibility improvements in urban areas. 

• There are significant problems with applying an Aex ante@ valuation estimate to an Aex 

post@ policy context. If a policy yields a significant change in the attributes of the good, 

you should not use the study estimates to value the change using a benefit transfer 

approach. 

• You also should not use a value developed from a study involving, small marginal 

 

15 See Loomis JB (1992), Water Resources Research, 28(3), 701-705 and Kirchoff, S, Colby, BG, and LaFrance, JT 

(1997), Journal of Environmental Economics and Management, 33, 75-93. 

25
changes in a policy context involving large changes in the quantity of the good. 

Clearly, all of these criteria are difficult to meet. However, you should attempt to satisfy 

as many as possible when choosing studies from the existing economic literature. Professional 

judgment is required in determining whether a particular transfer is too speculative to use in 

regulatory analysis. 

6. Ancillary Benefits and Countervailing Risks 

Your analysis should look beyond the direct benefits and direct costs of your rulemaking 

and consider any important ancillary benefits and countervailing risks. An ancillary benefit is a 

favorable impact of the rule that is typically unrelated or secondary to the statutory purpose of 

the rulemaking (e.g., reduced refinery emissions due to more stringent fuel economy standards 

for light trucks) while a countervailing risk is an adverse economic, health, safety, or 

environmental consequence that occurs due to a rule and is not already accounted for in the 

direct cost of the rule (e.g., adverse safety impacts from more stringent fuel-economy standards 

for light trucks). 

You should begin by considering and perhaps listing the possible ancillary benefits and 

countervailing risks. However, highly speculative or minor consequences may not be worth 

further formal analysis. Analytic priority should be given to those ancillary benefits and 

countervailing risks that are important enough to potentially change the rank ordering of the 

main alternatives in the analysis. In some cases the mere consideration of these secondary 

effects may help in the generation of a superior regulatory alternative with strong ancillary 

benefits and fewer countervailing risks. For instance, a recent study suggested that weight-based, 

fuel-economy standards could achieve energy savings with fewer safety risks and employment 

losses than would occur under the current regulatory structure. 

Like other benefits and costs, an effort should be made to quantify and monetize ancillary 

benefits and countervailing risks. If monetization is not feasible, quantification should be 

attempted through use of informative physical units. If both monetization and quantification are 

not feasible, then these issues should be presented as non-quantified benefits and costs. The 

same standards of information and analysis quality that apply to direct benefits and costs should 

be applied to ancillary benefits and countervailing risks. 

One way to combine ancillary benefits and countervailing risks is to evaluate these 

effects separately and then put both of these effects on the benefits side, not on the cost side. 

Although it is theoretically appropriate to include disbenefits on the cost side, legal and 

programmatic considerations generally support subtracting the disbenefits from direct benefits. 

7. Methods for Treating Non-Monetized Benefits and Costs 

Sound quantitative estimates of benefits and costs, where feasible, are preferable to 

qualitative descriptions of benefits and costs because they help decision makers understand the 

magnitudes of the effects of alternative actions. However, some important benefits and costs 

(e.g., privacy protection) may be inherently too difficult to quantify or monetize given current 

26
data and methods. You should carry out a careful evaluation of non-quantified benefits and 

costs. Some authorities16 refer to these non-monetized and non-quantified effects as 

“intangible”. 

a. Benefits and Costs that are Difficult to Monetize 

You should monetize quantitative estimates whenever possible. Use sound and 

defensible values or procedures to monetize benefits and costs, and ensure that key analytical 

assumptions are defensible. If monetization is impossible, explain why and present all available 

quantitative information. For example, if you can quantify but cannot monetize increases in 

water quality and fish populations resulting from water quality regulation, you can describe

benefits in terms of stream miles of improved water quality for boaters and increases in game

fish populations for anglers. You should describe the timing and likelihood of such effects and 

avoid double-counting of benefits when estimates of monetized and physical effects are mixed in 

the same analysis. 

b. Benefits and Costs that are Difficult to Quantify 

If you are not able to quantify the effects, you should present any relevant quantitative 

information along with a description of the unquantified effects, such as ecological gains, 

improvements in quality of life, and aesthetic beauty. You should provide a discussion of the 

strengths and limitations of the qualitative information. This should include information on the 

key reason(s) why they cannot be quantified. In one instance, you may know with certainty the 

magnitude of a risk to which a substantial, but unknown, number of individuals are exposed. In 

another instance, the existence of a risk may be based on highly speculative assumptions, and the 

magnitude of the risk may be unknown. 

For cases in which the unquantified benefits or costs affect a policy choice, you should 

provide a clear explanation of the rationale behind the choice. Such an explanation could include 

detailed information on the nature, timing, likelihood, location, and distribution of the 

unquantified benefits and costs. Also, please include a summary table that lists all the 

unquantified benefits and costs, and use your professional judgment to highlight (e.g., with 

categories or rank ordering) those that you believe are most important (e.g., by considering 

factors such as the degree of certainty, expected magnitude, and reversibility of effects). 

 

While the focus is often placed on difficult to quantify benefits of regulatory action, some

costs are difficult to quantify as well. Certain permitting requirements (e.g., EPA=s New Source 

Review program) restrict the decisions of production facilities to shift to new products and adopt 

innovative methods of production. While these programs may impose substantial costs on the 

economy, it is very difficult to quantify and monetize these effects. Similarly, regulations that 

establish emission standards for recreational vehicles, like motor bikes, may adversely affect the 

performance of the vehicles in terms of driveability and 0 to 60 miles per hour acceleration. 

Again, the cost associated with the loss of these attributes may be difficult to quantify and 

monetize. They need to be analyzed qualitatively. 

16 Mishan EJ (1994), Cost-Benefit Analysis, fourth edition, Routledge, New York. 

27
8. Monetizing Health and Safety Benefits and Costs 

We expect you to provide a benefit-cost analysis of major health and safety rulemakings 

in addition to a CEA. The BCA provides additional insight because (a) it provides some

indication of what the public is willing to pay for improvements in health and safety and (b) it 

offers additional information on preferences for health using a different research design than is 

used in CEA. Since the health-preference methods used to support CEA and BCA have some

different strengths and drawbacks, it is important that you provide decision makers with both 

perspectives. 

In monetizing health benefits, a WTP measure is the conceptually appropriate measure as 

compared to other alternatives (e.g., cost of illness or lifetime earnings), in part because it 

attempts to capture pain and suffering and other quality-of-life effects. Using the WTP measure 

for health and safety allows you to directly compare your results to the other benefits and costs in 

your analysis, which will typically be based on WTP. 

If well-conducted revealed-preference studies of relevant health and safety risks are 

available, you should consider using them in developing your monetary estimates. If appropriate 

revealed-preference data are not available, you should use valid and relevant data from statedpreference studies. You will need to use your professional judgment when you are faced with 

limited information on revealed preference studies and substantial information based on stated 

preference studies. 

A key advantage of stated-preference and health-utility methods compared to revealed 

preference methods is that they can be tailored to address the ranges of probabilities, types of 

health risks and specific populations affected by your rule. In many rulemakings there will be no 

relevant information from revealed-preference studies. In this situation you should consider 

commissioning a stated-preference study or using values from published stated-preference 

studies. For the reasons discussed previously, you should be cautious about using values from

stated-preference studies and describe in the analysis the drawbacks of this approach. 

a. Nonfatal Health and Safety Risks 

With regard to nonfatal health and safety risks, there is enormous diversity in the nature 

and severity of impaired health states. A traumatic injury that can be treated effectively in the 

emergency room without hospitalization or long-term care is different from a traumatic injury 

resulting in paraplegia. Severity differences are also important in evaluation of chronic diseases. 

A severe bout of bronchitis, though perhaps less frequent, is far more painful and debilitating 

than the more frequent bouts of mild bronchitis. The duration of an impaired health state, which 

can range from a day or two to several years or even a lifetime (e.g., birth defects inducing 

mental retardation), need to be considered carefully. Information on both the severity and 

duration of an impaired health state is necessary before the task of monetization can be 

performed. 

When monetizing nonfatal health effects, it is important to consider two components: (1) 

the private demand for prevention of the nonfatal health effect, to be represented by the 

28
preferences of the target population at risk, and (2) the net financial externalities associated with 

poor health such as net changes in public medical costs and any net changes in economic 

production that are not experienced by the target population. Revealed-preference or statedpreference studies are necessary to estimate the private demand; health economics data from

published sources can typically be used to estimate the financial externalities caused by changes 

in health status. If you use literature values to monetize nonfatal health and safety risks, it is 

important to make sure that the values you have selected are appropriate for the severity and 

duration of health effects to be addressed by your rule. 

If data are not available to support monetization, you might consider an alternative 

approach that makes use of health-utility studies. Although the economics literature on the 

monetary valuation of impaired health states is growing, there is a much larger clinical literature 

on how patients, providers and community residents value diverse health states. This literature 

typically measures health utilities based on the standard gamble, the time tradeoff or the rating 

scale methods. This health utility information may be combined with known monetary values 

for well-defined health states to estimate monetary values for a wide range of health states of 

different severity and duration. If you use this approach, you should be careful to acknowledge 

your assumptions and the limitations of your estimates. 

b. Fatality Risks 

Since agencies often design health and safety regulation to reduce risks to life, evaluation 

of these benefits can be the key part of the analysis. A good analysis must present these benefits 

clearly and show their importance. Agencies may choose to monetize these benefits. The 

willingness-to-pay approach is the best methodology to use if reductions in fatality risk are 

monetized. 

Some describe the monetized value of small changes in fatality risk as the "value of 

statistical life" (VSL) or, less precisely, the "value of a life." The latter phrase can be misleading 

because it suggests erroneously that the monetization exercise tries to place a Avalue@ on 

individual lives. You should make clear that these terms refer to the measurement of willingness 

to pay for reductions in only small risks of premature death. They have no application to an 

identifiable individual or to very large reductions in individual risks. They do not suggest that 

any individual=s life can be expressed in monetary terms. Their sole purpose is to help describe 

better the likely benefits of a regulatory action. 

Confusion about the term "statistical life" is also widespread. This term refers to the sum

of risk reductions expected in a population. For example, if the annual risk of death is reduced 

by one in a million for each of two million people, that is said to represent two "statistical lives"

extended per year (2 million people x 1/1,000,000 = 2). If the annual risk of death is reduced by 

one in 10 million for each of 20 million people, that also represents two statistical lives extended. 

The adoption of a value for the projected reduction in the risk of premature mortality is 

the subject of continuing discussion within the economic and public policy analysis community. 

A considerable body of academic literature is available on this subject. This literature involves 

either explicit or implicit valuation of fatality risks, and generally involves the use of estimates of 

29
VSL from studies on wage compensation for occupational hazards (which generally are in the 

range of 10-4 annually), on consumer product purchase and use decisions, or from an emerging 

literature using stated preference approaches. A substantial majority of the resulting estimates of

VSL vary from roughly $1 million to $10 million per statistical life.17

There is a continuing debate within the economic and public policy analysis community 

on the merits of using a single VSL for all situations versus adjusting the VSL estimates to 

reflect the specific rule context. A variety of factors have been identified, including whether the 

mortality risk involves sudden death, the fear of cancer, and the extent to which the risk is 

voluntarily incurred.18 The consensus of EPA=s recent Science Advisory Board (SAB) review of 

this issue was that the available literature does not support adjustments of VSL for most of these 

factors. The panel did conclude that it was appropriate to adjust VSL to reflect changes in 

income and any time lag in the occurrence of adverse health effects. 

The age of the affected population has also been identified as an important factor in the 

theoretical literature. However, the empirical evidence on age and VSL is mixed. In light of the 

continuing questions over the effect of age on VSL estimates, you should not use an ageadjustment factor in an analysis using VSL estimates.19

Another way that has been used to express reductions in fatality risks is to use the life 

expectancy method, the Avalue of statistical life-years (VSLY) extended.@ If a regulation protects 

individuals whose average remaining life expectancy is 40 years, a risk reduction of one fatality 

is expressed as A40 life-years extended.@ Those who favor this alternative approach emphasize 

that the value of a statistical life is not a single number relevant for all situations. In particular, 

when there are significant differences between the effect on life expectancy for the population 

affected by a particular health risk and the populations studied in the labor market studies, they 

prefer to adopt a VSLY approach to reflect those differences. You should consider providing 

estimates of both VSL and VSLY, while recognizing the developing state of knowledge in this 

area. 

Longevity may be only one of a number of relevant considerations pertaining to the rule. 

You should keep in mind that regulations with greater numbers of life-years extended are not 

necessarily better than regulations with fewer numbers of life-years extended. In any event, 

when you present estimates based on the VSLY method, you should adopt a larger VSLY 

estimate for senior citizens because senior citizens face larger overall health risks from all causes 

and they may have accumulated savings to spend on their health and safety.20 

 

The valuation of fatality risk reduction is an evolving area in both results and 

methodology. Hence, you should utilize valuation methods that you consider appropriate for the 

17 See Viscusi WK and Aldy JE, Journal of Risk and Uncertainty (forthcoming) and Mrozek JR and Taylor LO

(2002), Journal of Policy Analysis and Management, 21(2), 253-270. 18 Distinctions between “voluntary” and “involuntary” should be treated with care. Risks are best considered to fall 

within a continuum from “voluntary” to “involuntary” with very few risks at either end of this range. These terms 

are also related to differences in the cost of avoiding risks. 19 Graham JD (2003), Memorandum to the President’s Management Council, Benefit-Cost Methods and Lifesaving

Rules. This memorandum can be found at http://www.whitehouse.gov/omb/inforeg/pmc_benefit_cost_memo.pdf 20 Office of Information and Regulatory Affairs, OMB, Memorandum to the President’s Management Council, ibid.

30
regulatory circumstances. Since the literature-based VSL estimates may not be entirely 

appropriate for the risk being evaluated (e.g., the use of occupational risk premia to value 

reductions in risks from environmental hazards), you should explain your selection of estimates 

and any adjustments of the estimates to reflect the nature of the risk being evaluated. You should 

present estimates based on alternative approaches, and if you monetize mortality risk reduction, 

you should do so on a consistent basis to the extent feasible. You should clearly indicate the 

methodology used and document your choice of a particular methodology. You should explain 

any significant deviations from the prevailing state of knowledge. If you use different 

methodologies in different rules, you should clearly disclose the fact and explain your choices. 

c. Valuation of Reductions in Health and Safety Risks to Children 

The valuation of health outcomes for children and infants poses special challenges. It is 

rarely feasible to measure a child's willingness to pay for health improvement and an adult's 

concern for his or her own health is not necessarily relevant to valuation of child health. For 

example, the wage premiums demanded by workers to accept hazardous jobs are not readily 

transferred to rules that accomplish health gains for children. 

There are a few studies that examine parental willingness to pay to invest in health and 

safety for their children. Some of these studies suggest that parents may value children’s health 

more strongly than their own health. Although this parental perspective is a promising research 

strategy, it may need to be expanded to include a societal interest in child health and safety. 

Where the primary objective of a rule is to reduce the risk of injury, disease or mortality

among children, you should conduct a cost-effectiveness analysis of the rule. You may also 

develop a benefit-cost analysis to the extent that valid monetary values can be assigned to the 

primary expected health outcomes. For rules where health gains are expected among both 

children and adults and you decide to perform a benefit-cost analysis, the monetary values for 

children should be at least as large as the values for adults (for the same probabilities and 

outcomes) unless there is specific and compelling evidence to suggest otherwise.21 

Discount Rates 

Benefits and costs do not always take place in the same time period. When they do not, it 

is incorrect simply to add all of the expected net benefits or costs without taking account of when 

the actually occur. If benefits or costs are delayed or otherwise separated in time from each 

other, the difference in timing should be reflected in your analysis. 

 

As a first step, you should present the annual time stream of benefits and costs expected 

to result from the rule, clearly identifying when the benefits and costs are expected to occur. The 

beginning point for your stream of estimates should be the year in which the final rule will begin 

to have effects, even if that is expected to be some time in the future. The ending point should be 

far enough in the future to encompass all the significant benefits and costs likely to result from

the rule. 

21 For more information, see Dockins C., Jenkins RR, Owens N, Simon NB, and Wiggins LB (2002), Risk Analysis, 

22(2), 335-346.

31
In presenting the stream of benefits and costs, it is important to measure them in constant 

dollars to avoid the misleading effects of inflation in your estimates. If the benefits and costs are 

initially measured in prices reflecting expected future inflation, you can convert them to constant 

dollars by dividing through by an appropriate inflation index, one that corresponds to the 

inflation rate underlying the initial estimates of benefits or costs. 

1. The Rationale for Discounting 

Once these preliminaries are out of the way, you can begin to adjust your estimates for 

differences in timing. (This is a separate calculation from the adjustment needed to remove the 

effects of future inflation.) Benefits or costs that occur sooner are generally more valuable. The 

main rationales for the discounting of future impacts are: 

(a) Resources that are invested will normally earn a positive return, so current consumption 

is more expensive than future consumption, since you are giving up that expected return 

on investment when you consume today. 

(b) Postponed benefits also have a cost because people generally prefer present to future 

consumption. They are said to have positive time preference. 

(c) Also, if consumption continues to increase over time, as it has for most of U.S. history, 

an increment of consumption will be less valuable in the future than it would be today, 

because the principle of diminishing marginal utility implies that as total consumption 

increases, the value of a marginal unit of consumption tends to decline. 

There is wide agreement with point (a). Capital investment is productive, but that point 

is not sufficient by itself to explain positive interest rates and observed saving behavior. To 

understand these phenomena, points (b) and (c) are also necessary. If people are really 

indifferent between consumption now and later, then they should be willing to forgo current 

consumption in order to consume an equal or slightly greater amount in the future. That would 

cause saving rates and investment to rise until interest rates were driven to zero and capital was 

no longer productive. As long as we observe positive interest rates and saving rates below 100 

percent, people must be placing a higher value on current consumption than on future 

consumption. 

To reflect this preference, a discount factor should be used to adjust the estimated 

benefits and costs for differences in timing. The further in the future the benefits and costs are 

expected to occur, the more they should be discounted. The discount factor can be calculated 

given a discount rate. The formula is 1/ (1+ the discount rate)t

 where At@ measures the number of 

years in the future that the benefits or costs are expected to occur. Benefits or costs that have 

been adjusted in this way are called Adiscounted present values@ or simply Apresent values@. 

When, and only when, the estimated benefits and costs have been discounted, they can be added 

to determine the overall value of net benefits. 

32
2. Real Discount Rates of 3 Percent and 7 Percent 

 OMB=s basic guidance on the discount rate is provided in OMB Circular A-94 

(http://www.whitehouse.gov/omb/circulars/index.html). This Circular points out that the 

analytically preferred method of handling temporal differences between benefits and costs is to 

adjust all the benefits and costs to reflect their value in equivalent units of consumption and to 

discount them at the rate consumers and savers would normally use in discounting future 

consumption benefits. This is sometimes called the Ashadow price@ approach to discounting 

because doing such calculations requires you to value benefits and costs using shadow prices, 

especially for capital goods, to correct for market distortions. These shadow prices are not well 

established for the United States. Furthermore, the distribution of impacts from regulations on 

capital and consumption are not always well known. Consequently, any agency that wishes to 

tackle this challenging analytical task should check with OMB before proceeding. 

As a default position, OMB Circular A-94 states that a real discount rate of 7 percent 

should be used as a base-case for regulatory analysis. The 7 percent rate is an estimate of the 

average before-tax rate of return to private capital in the U.S. economy. It is a broad measure 

that reflects the returns to real estate and small business capital as well as corporate capital. It 

approximates the opportunity cost of capital, and it is the appropriate discount rate whenever the 

main effect of a regulation is to displace or alter the use of capital in the private sector. OMB 

revised Circular A-94 in 1992 after extensive internal review and public comment. In a recent 

analysis, OMB found that the average rate of return to capital remains near the 7 percent rate 

estimated in 1992. Circular A-94 also recommends using other discount rates to show the 

sensitivity of the estimates to the discount rate assumption. 

 Economic distortions, including taxes on capital, create a divergence between the rate of 

return that savers earn and the private rate of return to capital. This divergence persists despite 

the tendency for capital to flow to where it can earn the highest rate of return. Although market 

forces will push after-tax rates of return in different sectors of the economy toward equality, that 

process will not equate pre-tax rates of return when there are differences in the tax treatment of

investment. Corporate capital, in particular, pays an additional layer of taxation, the corporate 

income tax, which requires it to earn a higher pre-tax rate of return in order to provide investors 

with similar after-tax rates of return compared with non-corporate investments. The pre-tax rates 

of return better measure society=s gains from investment. Since the rates of return on capital are 

higher in some sectors of the economy than others, the government needs to be sensitive to 

possible impacts of regulatory policy on capital allocation. 

The effects of regulation do not always fall exclusively or primarily on the allocation of 

capital. When regulation primarily and directly affects private consumption (e.g., through higher 

consumer prices for goods and services), a lower discount rate is appropriate. The alternative 

most often used is sometimes called the Asocial rate of time preference.@ This simply means the 

rate at which Asociety@ discounts future consumption flows to their present value. If we take the 

rate that the average saver uses to discount future consumption as our measure of the social rate 

of time preference, then the real rate of return on long-term government debt may provide a fair 

approximation. Over the last thirty years, this rate has averaged around 3 percent in real terms on 

a pre-tax basis. For example, the yield on 10-year Treasury notes has averaged 8.1 percent since 

33
1973 while the average annual rate of change in the CPI over this period has been 5.0 percent, 

implying a real 10-year rate of 3.1 percent. 

For regulatory analysis, you should provide estimates of net benefits using both 3 percent 

and 7 percent. An example of this approach is EPA=s analysis of its 1998 rule setting both 

effluent limits for wastewater discharges and air toxic emission limits for pulp and paper mills. 

In this analysis, EPA developed its present-value estimates using real discount rates of 3 and 7 

percent applied to benefit and cost streams that extended forward for 30 years. You should 

present a similar analysis in your own work. 

In some instances, if there is reason to expect that the regulation will cause resources to 

be reallocated away from private investment in the corporate sector, then the opportunity cost 

may lie outside the range of 3 to 7 percent. For example, the average real rate of return on 

corporate capital in the United States was approximately 10 percent in the 1990s, returning to the 

same level observed in the 1950s and 1960s. If you are uncertain about the nature of the 

opportunity cost, then you should present benefit and cost estimates using a higher discount rate 

as a further sensitivity analysis as well as using the 3 and 7 percent rates. 

3. Time Preference for Health-Related Benefits and Costs 

When future benefits or costs are health-related, some have questioned whether 

discounting is appropriate, since the rationale for discounting money may not appear to apply to 

health. It is true that lives saved today cannot be invested in a bank to save more lives in the 

future. But the resources that would have been used to save those lives can be invested to earn a 

higher payoff in future lives saved. People have been observed to prefer health gains that occur 

immediately to identical health gains that occur in the future. Also, if future health gains are not 

discounted while future costs are, then the following perverse result occurs: an attractive 

investment today in future health improvement can always be made more attractive by delaying 

the investment. For such reasons, there is a professional consensus that future health effects, 

including both benefits and costs, should be discounted at the same rate. This consensus applies 

to both BCA and CEA. 

A common challenge in health-related analysis is to quantify the time lag between when a 

rule takes effect and when the resulting physical improvements in health status will be observed 

in the target population. In such situations, you must carefully consider the timing of health 

benefits before performing present-value calculations. It is not reasonable to assume that all of 

the benefits of reducing chronic diseases such as cancer and cardiovascular disease will occur 

immediately when the rule takes effect. For rules addressing traumatic injury, this lag period 

may be short. For chronic diseases it may take years or even decades for a rule to induce its full 

beneficial effects in the target population. 

When a delay period between exposure to a toxin and increased probability of disease is 

likely (a so-called latency period), a lag between exposure reduction and reduced probability of 

disease is also likely. This latter period has sometimes been referred to as a "cessation lag," and 

it may or may not be of the same duration as the latency period. As a general matter, cessation 

lags will only apply to populations with at least some high-level exposure (e.g., before the rule 

34
takes effect). For populations with no such prior exposure, such as those born after the rule takes 

effect, only the latency period will be relevant. 

Ideally, your exposure-risk model would allow calculation of reduced risk for each year 

following exposure cessation, accounting for total cumulative exposure and age at the time of 

exposure reduction. The present-value benefits estimate could then reflect an appropriate 

discount factor for each year's risk reduction. Recent analyses of the cancer benefits stemming 

from reduction in public exposure to radon in drinking water have adopted this approach. They 

were supported by formal risk-assessment models that allowed estimates of the timing of lung 

cancer incidence and mortality to vary in response to different radon exposure levels.22

In many cases, you will not have the benefit of such detailed risk assessment modeling. 

You will need to use your professional judgment as to the average cessation lag for the chronic 

diseases affected by your rule. In situations where information exists on latency but not on 

cessation lags, it may be reasonable to use latency as a proxy for the cessation lag, unless there is 

reason to believe that the two are different. When the average lag time between exposures and 

disease is unknown, a range of plausible alternative values for the time lag should be used in 

your analysis. 

4. Intergenerational Discounting 

Special ethical considerations arise when comparing benefits and costs across 

generations. Although most people demonstrate time preference in their own consumption 

behavior, it may not be appropriate for society to demonstrate a similar preference when 

deciding between the well-being of current and future generations. Future citizens who are 

affected by such choices cannot take part in making them, and today=s society must act with 

some consideration of their interest. 

One way to do this would be to follow the same discounting techniques described above 

and supplement the analysis with an explicit discussion of the intergenerational concerns (how 

future generations will be affected by the regulatory decision). Policymakers would be provided 

with this additional information without changing the general approach to discounting. 

Using the same discount rate across generations has the advantage of preventing timeinconsistency problems. For example, if one uses a lower discount rate for future generations, 

then the evaluation of a rule that has short-term costs and long-term benefits would become more

favorable merely by waiting a year to do the analysis. Further, using the same discount rate 

across generations is attractive from an ethical standpoint. If one expects future generations to 

be better off, then giving them the advantage of a lower discount rate would in effect transfer 

resources from poorer people today to richer people tomorrow. 

 

Some believe, however, that it is ethically impermissible to discount the utility of future 

generations. That is, government should treat all generations equally. Even under this approach, 

22 Committee on Risk Assessment of Exposure to Radon in Drinking Water, Board on Radiation Effects Research, 

Commission on Life Sciences (1996), Risk Assessment of Radon in Drinking Water, National Research Council, 

National Academy Press, Washington, DC. 

35
it would still be correct to discount future costs and consumption benefits generally (perhaps at a 

lower rate than for intragenerational analysis), due to the expectation that future generations will 

be wealthier and thus will value a marginal dollar of benefits or costs by less than those alive 

today. Therefore, it is appropriate to discount future benefits and costs relative to current 

benefits and costs, even if the welfare of future generations is not being discounted. Estimates of 

the appropriate discount rate appropriate in this case, from the 1990s, ranged from 1 to 3 percent 

per annum.

23

A second reason for discounting the benefits and costs accruing to future generations at a 

lower rate is increased uncertainty about the appropriate value of the discount rate, the longer the 

horizon for the analysis. Private market rates provide a reliable reference for determining how 

society values time within a generation, but for extremely long time periods no comparable 

private rates exist. As explained by Martin Weitzman24, in the limit for the deep future, the 

properly averaged certainty-equivalent discount factor (i.e., 1/[1+r]t) corresponds to the 

minimum discount rate having any substantial positive probability. From today=s perspective, 

the only relevant limiting scenario is the one with the lowest discount rate B all of the other states 

at the far-distant time are relatively much less important because their expected present value is 

so severely reduced by the power of compounding at a higher rate. 

If your rule will have important intergenerational benefits or costs you might consider a 

further sensitivity analysis using a lower but positive discount rate in addition to calculating net 

benefits using discount rates of 3 and 7 percent. 

5. Time Preference for Non-Monetized Benefits and Costs 

Differences in timing should be considered even for benefits and costs that are not 

expressed in monetary units, including health benefits. The timing differences can be handled 

through discounting. EPA estimated cost-effectiveness in its 1998 rule, AControl of Emissions 

from Nonroad Diesel Engines,@ by discounting both the monetary costs and the non-monetized 

emission reduction benefits over the expected useful life of the engines at the 7 percent real rate 

recommended in OMB Circular A-94. 

Alternatively, it may be possible in some cases to avoid discounting non-monetized 

benefits. If the expected flow of benefits begins as soon as the cost is incurred and is expected to 

be constant over time, then annualizing the cost stream is sufficient, and further discounting of 

benefits is unnecessary. Such an analysis might produce an estimate of the annualized cost per 

ton of reduced emissions of a pollutant. 

6. The Internal Rate of Return 

 

The internal rate of return is the discount rate that sets the net present value of the 

discounted benefits and costs equal to zero. The internal rate of return does not generally 

23 Portney PR and Weyant JP, eds. (1999), Discounting and Intergenerational Equity, Resources for the Future, 

Washington, DC. 24 Weitzman ML In Portney PR and Weyant JP, eds. (1999), Discounting and Intergenerational Equity, Resources

for the Future, Washington, DC. 

36
provide an acceptable decision criterion, and regulations with the highest internal rate of return 

are not necessarily the most beneficial. Nevertheless, it does provide useful information and for 

many it will offer a meaningful indication of regulation=s impact. You should consider including 

the internal rate of return implied by your regulatory analysis along with other information about 

discounted net present values. 

Other Key Considerations 

1. Other Benefit and Cost Considerations

You should include these effects in your analysis and provide estimates of their monetary 

values when they are significant: 

• Private-sector compliance costs and savings; 

• Government administrative costs and savings; 

• Gains or losses in consumers' or producers' surpluses; 

• Discomfort or inconvenience costs and benefits; and 

• Gains or losses of time in work, leisure and/or commuting/travel settings. 

Estimates of benefits and costs should be based on credible changes in technology over 

time. For example, retrospective studies may provide evidence that Alearning@ will likely reduce 

the cost of regulation in future years. The weight you give to a study of past rates of cost savings 

resulting from innovation (including Alearning curve@ effects) should depend on both its 

timeliness and direct relevance to the processes affected by the regulatory alternative under 

consideration. In addition, you should take into account cost-saving innovations that result from

a shift to regulatory performance standards and incentive-based policies. On the other hand, 

significant costs may result from a slowing in the rate of innovation or of adoption of new 

technology due to delays in the regulatory approval process or the setting of more stringent 

standards for new facilities than existing ones. In some cases agencies are limited under statute 

to consider only technologies that have been demonstrated to be feasible. In these situations, it 

may be useful to estimate costs and cost savings assuming a wider range of technical 

possibilities.

When characterizing technology changes over time, you should assess the likely 

technology changes that would have occurred in the absence of the regulatory action (technology 

baseline). Technologies change over time in both reasonably functioning markets and imperfect 

markets. If you assume that technology will remain unchanged in the absence of regulation 

when technology changes are likely, then your analysis will over-state both the benefits and costs 

attributable to the regulation. 

Occasionally, cost savings or other forms of benefits accrue to parties affected by a rule 

who also bear its costs. For example, a requirement that engine manufacturers reduce emissions 

from engines may lead to technologies that improve fuel economy. These fuel savings will 

normally accrue to the engine purchasers, who also bear the costs of the technologies. There is 

no apparent market failure with regard to the market value of fuel saved because one would 

expect that consumers would be willing to pay for increased fuel economy that exceeded the cost 

37
of providing it. When these cost savings are substantial, and particularly when you estimate 

them to be greater than the cost associated with achieving them, you should examine and discuss 

why market forces would not accomplish these gains in the absence of regulation. As a general 

matter, any direct costs that are averted as a result of a regulatory action should be monetized 

wherever possible and either added to the benefits or subtracted from the costs of that alternative. 

2. The Difference between Costs (or Benefits) and Transfer Payments 

Distinguishing between real costs and transfer payments is an important, but sometimes 

difficult, problem in cost estimation. Benefit and cost estimates should reflect real resource use. 

Transfer payments are monetary payments from one group to another that do not affect total 

resources available to society. A regulation that restricts the supply of a good, causing its price 

to rise, produces a transfer from buyers to sellers. The net reduction in the total surplus 

(consumer plus producer) is a real cost to society, but the transfer from buyers to sellers resulting 

from a higher price is not a real cost since the net reduction automatically accounts for the 

transfer from buyers to sellers. However, transfers from the United States to other nations 

should be included as costs, and transfers from other nations to the United States as benefits, as 

long as the analysis is conducted from the United States perspective. 

You should not include transfers in the estimates of the benefits and costs of a regulation. 

Instead, address them in a separate discussion of the regulation=s distributional effects. Examples 

of transfer payments include the following: 

• Scarcity rents and monopoly profits 

• Insurance payments 

• Indirect taxes and subsidies 

Treatment of Uncertainty 

 

The precise consequences (benefits and costs) of regulatory options are not always 

known for certain, but the probability of their occurrence can often be developed. The important 

uncertainties connected with your regulatory decisions need to be analyzed and presented as part 

of the overall regulatory analysis. You should begin your analysis of uncertainty at the earliest 

possible stage in developing your analysis. You should consider both the statistical variability of 

key elements underlying the estimates of benefits and costs (for example, the expected change in 

the distribution of automobile accidents that might result from a change in automobile safety 

standards) and the incomplete knowledge about the relevant relationships (for example, the 

uncertain knowledge of how some economic activities might affect future climate change).25 By 

assessing the sources of uncertainty and the way in which benefit and cost estimates may be 

affected under plausible assumptions, you can shape your analysis to inform decision makers and 

the public about the effects and the uncertainties of alternative regulatory actions. 

25 In some contexts, the word Avariability@ is used as a synonym for statistical variation that can be described by a 

theoretically valid distribution function, whereas Auncertainty@ refers to a more fundamental lack of knowledge. 

Throughout this discussion, we use the term “uncertainty” to refer to both concepts. 

38
The treatment of uncertainty must be guided by the same principles of full disclosure and 

transparency that apply to other elements of your regulatory analysis. Your analysis should be 

credible, objective, realistic, and scientifically balanced.26 Any data and models that you use to 

analyze uncertainty should be fully identified. You should also discuss the quality of the 

available data used. Inferences and assumptions used in your analysis should be identified, and 

your analytical choices should be explicitly evaluated and adequately justified. In your 

presentation, you should delineate the strengths of your analysis along with any uncertainties 

about its conclusions. Your presentation should also explain how your analytical choices have 

affected your results. 

In some cases, the level of scientific uncertainty may be so large that you can only 

present discrete alternative scenarios without assessing the relative likelihood of each scenario 

quantitatively. For instance, in assessing the potential outcomes of an environmental effect, 

there may be a limited number of scientific studies with strongly divergent results. In such cases, 

you might present results from a range of plausible scenarios, together with any available 

information that might help in qualitatively determining which scenario is most likely to occur. 

When uncertainty has significant effects on the final conclusion about net benefits, your 

agency should consider additional research prior to rulemaking. The costs of being wrong may 

outweigh the benefits of a faster decision. This is true especially for cases with irreversible or 

large upfront investments. If your agency decides to proceed with rulemaking, you should 

explain why the costs of developing additional information—including any harm from delay in 

public protection—exceed the value of that information. 

 

For example, when the uncertainty is due to a lack of data, you might consider deferring 

the decision, as an explicit regulatory alternative, pending further study to obtain sufficient 

data.27 Delaying a decision will also have costs, as will further efforts at data gathering and 

analysis. You will need to weigh the benefits of delay against these costs in making your 

decision. Formal tools for assessing the value of additional information are now well developed 

in the applied decision sciences and can be used to help resolve this type of complex regulatory 

question. 

AReal options@ methods have also formalized the valuation of the added flexibility 

inherent in delaying a decision. As long as taking time will lower uncertainty, either passively or 

actively through an investment in information gathering, and some costs are irreversible, such as 

the potential costs of a sunk investment, a benefit can be assigned to the option to delay a 

decision. That benefit should be considered a cost of taking immediate action versus the 

alternative of delaying that action pending more information. However, the burdens of delay—

including any harm to public health, safety, and the environment—need to be analyzed carefully. 

1. Quantitative Analysis of Uncertainty

26 When disseminating information, agencies should follow their own information quality guidelines, issued in

conformance with the OMB government-wide guidelines (67 FR 8452, February 22, 2002). 27 Clemen RT (1996), Making Hard Decisions: An Introduction to Decision Analysis, second edition, Duxbury 

Press, Pacific Grove. 

39
Examples of quantitative analysis, broadly defined, would include formal estimates of the 

probabilities of environmental damage to soil or water, the possible loss of habitat, or risks to 

endangered species as well as probabilities of harm to human health and safety. There are also 

uncertainties associated with estimates of economic benefits and costs, such as the cost savings 

associated with increased energy efficiency. Thus, your analysis should include two 

fundamental components: a quantitative analysis characterizing the probabilities of the relevant 

outcomes and an assignment of economic value to the projected outcomes. It is essential that

both parts be conceptually consistent. In particular, the quantitative analysis should be 

conducted in a way that permits it to be applied within a more general analytical framework, 

such as benefit-cost analysis. Similarly, the general framework needs to be flexible enough to 

incorporate the quantitative analysis without oversimplifying the results. For example, you 

should address explicitly the implications for benefits and costs of any probability distributions 

developed in your analysis. 

As with other elements of regulatory analysis, you will need to balance thoroughness 

with the practical limits on your analytical capabilities. Your analysis does not have to be 

exhaustive, nor is it necessary to evaluate each alternative at every step. Attention should be 

devoted to first resolving or studying the uncertainties that have the largest potential effect on 

decision making. Many times these will be the largest sources of uncertainties. In the absence 

of adequate data, you will need to make assumptions. These should be clearly identified and 

consistent with the relevant science. Your analysis should provide sufficient information for 

decision makers to grasp the degree of scientific uncertainty and the robustness of estimated 

probabilities, benefits, and costs to changes in key assumptions. 

For major rules involving annual economic effects of $1 billion or more, you should 

present a formal quantitative analysis of the relevant uncertainties about benefits and costs. In 

other words, you should try to provide some estimate of the probability distribution of regulatory 

benefits and costs. In summarizing the probability distributions, you should provide some

estimates of the central tendency (e.g., mean and median) along with any other information you 

think will be useful such as ranges, variances, specified low-end and high-end percentile 

estimates, and other characteristics of the distribution. 

Your estimates cannot be more precise than their most uncertain component. Thus, your 

analysis should report estimates in a way that reflects the degree of uncertainty and not create a 

false sense of precision. Worst-case or conservative analyses are not usually adequate because 

they do not convey the complete probability distribution of outcomes, and they do not permit 

calculation of an expected value of net benefits. In many health and safety rules, economists 

conducting benefit-cost analyses must rely on formal risk assessments that address a variety of 

risk management questions such as the baseline risk for the affected population, the safe level of 

exposure or, the amount of risk to be reduced by various interventions. Because the answers to 

some of these questions are directly used in benefits analyses, the risk assessment methodology 

must allow for the determination of expected benefits in order to be comparable to expected 

costs. This means that conservative assumptions and defaults (whether motivated by science 

policy or by precautionary instincts), will be incompatible with benefit analyses as they will 

result in benefit estimates that exceed the expected value. Whenever it is possible to characterize 

quantitatively the probability distributions, some estimates of expected value (e.g., mean and 

40
median) must be provided in addition to ranges, variances, specified low-end and high-end 

percentile estimates, and other characteristics of the distribution. 

 

Whenever possible, you should use appropriate statistical techniques to determine a 

probability distribution of the relevant outcomes. For rules that exceed the $1 billion annual 

threshold, a formal quantitative analysis of uncertainty is required. For rules with annual 

benefits and/or costs in the range from 100 million to $1 billion, you should seek to use more 

rigorous approaches with higher consequence rules. This is especially the case where net 

benefits are close to zero. More rigorous uncertainty analysis may not be necessary for rules in 

this category if simpler techniques are sufficient to show robustness. You may consider the 

following analytical approaches that entail increasing levels of complexity: 

• Disclose qualitatively the main uncertainties in each important input to the calculation of 

benefits and costs. These disclosures should address the uncertainties in the data as well 

as in the analytical results. However, major rules above the $1 billion annual threshold 

require a formal treatment. 

• Use a numerical sensitivity analysis to examine how the results of your analysis vary with 

plausible changes in assumptions, choices of input data, and alternative analytical 

approaches. Sensitivity analysis is especially valuable when the information is lacking to 

carry out a formal probabilistic simulation. Sensitivity analysis can be used to find 

Aswitch points@ -- critical parameter values at which estimated net benefits change sign or 

the low cost alternative switches. Sensitivity analysis usually proceeds by changing one 

variable or assumption at a time, but it can also be done by varying a combination of 

variables simultaneously to learn more about the robustness of your results to widespread 

changes. Again, however, major rules above the $1 billion annual threshold require a 

formal treatment. 

• Apply a formal probabilistic analysis of the relevant uncertainties B possibly using 

simulation models and/or expert judgment as revealed, for example, through Delphi 

methods.28 Such a formal analytical approach is appropriate for complex rules where 

there are large, multiple uncertainties whose analysis raises technical challenges, or 

where the effects cascade; it is required for rules that exceed the $1 billion annual 

threshold. For example, in the analysis of regulations addressing air pollution, there is 

uncertainty about the effects of the rule on future emissions, uncertainty about how the 

change in emissions will affect air quality, uncertainty about how changes in air quality 

will affect health, and finally uncertainty about the economic and social value of the 

change in health outcomes. In formal probabilistic assessments, expert solicitation is a 

useful way to fill key gaps in your ability to assess uncertainty.29 In general, experts can 

be used to quantify the probability distributions of key parameters and relationships. 

These solicitations, combined with other sources of data, can be combined in Monte 

Carlo simulations to derive a probability distribution of benefits and costs. You should 

28 The purpose of Delphi methods is to generate suitable information for decision making by eliciting expect 

judgment. The elicitation is conducted through a survey process which eliminates the interactions between experts. 

See Morgan MG and Henrion M (1990), Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Riskand

Policy Analysis, Cambridge University Press. 29 Cooke RM (1991), Experts in Uncertainty: Opinion and Subjective Probability in Science, Oxford University

Press. 

41
pay attention to correlated inputs. Often times, the standard defaults in Monte Carlo and 

other similar simulation packages assume independence across distributions. Failing to 

correctly account for correlated distributions of inputs can cause the resultant output 

uncertainty intervals to be too large, although in many cases the overall effect is 

ambiguous. You should make a special effort to portray the probabilistic results—in 

graphs and/or tables—clearly and meaningfully. 

New methods may become available in the future. This document is not intended to 

discourage or inhibit their use, but rather to encourage and stimulate their development. 

2. Economic Values of Uncertain Outcomes 

In developing benefit and cost estimates, you may find that there are probability 

distributions of values as well for each of the outcomes. Where this is the case, you will need to 

combine these probability distributions to provide estimated benefits and costs. 

Where there is a distribution of outcomes, you will often find it useful to emphasize 

summary statistics or figures that can be readily understood and compared to achieve the 

broadest public understanding of your findings. It is a common practice to compare the Abest 

estimates@ of both benefits and costs with those of competing alternatives. These Abest 

estimates@ are usually the average or the expected value of benefits and costs. Emphasis on these 

expected values is appropriate as long as society is Arisk neutral@ with respect to the regulatory 

alternatives. While this may not always be the case, you should in general assume Arisk 

neutrality@ in your analysis. If you adopt a different assumption on risk preference, you should 

explain your reasons for doing so. 

3. Alternative Assumptions 

If benefit or cost estimates depend heavily on certain assumptions, you should make 

those assumptions explicit and carry out sensitivity analyses using plausible alternative 

assumptions. If the value of net benefits changes from positive to negative (or vice versa) or if 

the relative ranking of regulatory options changes with alternative plausible assumptions, you 

should conduct further analysis to determine which of the alternative assumptions is more 

appropriate. Because different estimation methods may have hidden assumptions, you should 

analyze estimation methods carefully to make any hidden assumptions explicit. 

F. Specialized Analytical Requirements 

In preparing analytical support for your rulemaking, you should be aware that there are a 

number of analytic requirements imposed by law and Executive Order. In addition to the 

regulatory analysis requirements of Executive Order 12866, you should also consider whether 

your rule will need specialized analysis of any of the following issues. 

42
Impact on Small Businesses and Other Small Entities 

Under the Regulatory Flexibility Act (5 U.S.C. chapter 6), agencies must prepare a 

proposed and final "regulatory flexibility analysis" (RFA) if the rulemaking could "have a 

significant impact on a substantial number of small entities." You should consider posting your 

RFA on the internet so the public can review your findings. 

Your agency should have guidelines on how to prepare an RFA and you are encouraged 

to consult with the Chief Counsel for Advocacy of the Small Business Administration on 

expectations concerning what is an adequate RFA. Executive Order 13272 (67 FR 53461, 

August 16, 2002) requires you to notify the Chief Counsel for Advocacy of any draft rules that 

might have a significant economic impact on a substantial number of small entities. Executive 

Order 13272 also directs agencies to give every appropriate consideration to any comments 

provided by the Advocacy Office. Under SBREFA, EPA and OSHA are required to consult with 

small business prior to developing a proposed rule that would have a significant effect on small 

businesses. OMB encourages other agencies to do so as well.

Analysis of Unfunded Mandates 

Under the Unfunded Mandates Act (2 U.S.C. 1532), you must prepare a written statement 

about benefits and costs prior to issuing a proposed or final rule (for which your agency 

published a proposed rule) that may result in aggregate expenditure by State, local, and tribal 

governments, or by the private sector, of $100,000,000 or more in any one year (adjusted 

annually for inflation). Your analytical requirements under Executive Order 12866 are similar to 

the analytical requirements under this Act, and thus the same analysis may permit you to comply 

with both analytical requirements. 

Information Collection, Paperwork, and Recordkeeping Burdens 

Under the Paperwork Reduction Act (44 U.S.C. chapter 35), you will need to consider 

whether your rulemaking (or other actions) will create any additional information collection, 

paperwork or recordkeeping burdens. These burdens are permissible only if you can justify the 

practical utility of the information for the implementation of your rule. OMB approval will be

required of any new requirements for a collection of information imposed on 10 or more persons 

and a valid OMB control number must be obtained for any covered paperwork. Your agency's

CIO should be able to assist you in complying with the Paperwork Reduction Act. 

Information Quality Guidelines 

Under the Information Quality Law, agency guidelines, in conformance with the OMB 

government-wide guidelines (67 FR 8452, February 22, 2002), have established basic quality 

performance goals for all information disseminated by agencies, including information 

disseminated in support of proposed and final rules. The data and analysis that you use to 

support your rule must meet these agency and OMB quality standards. Your agency's CIO 

should be able to assist you in assessing information quality. The Statistical and Science Policy 

43
Branch of OMB's Office of Information and Regulatory Affairs can provide you assistance. This 

circular defines OMB=s minimum quality standards for regulatory analysis. 

Environmental Impact Statements 

The National Environmental Policy Act (42 U.S.C. 4321-4347) and related statutes and 

executive orders require agencies to consider the environmental impacts of agency decisions, 

including rulemakings. An environmental impact statement must be prepared for "major Federal 

actions significantly affecting the quality of the human environment." You must complete 

NEPA documentation before issuing a final rule. The White House Council on Environmental 

Quality has issued regulations (40 C.F.R. 1500-1508) and associated guidance for 

implementation of NEPA, available through CEQ's website (http://www.whitehouse/gov/ceq/). 

Impacts on Children 

Under Executive Order 13045, AProtection of Children from Environmental Health Risks 

and Safety Risks,@ each agency must, with respect to its rules, Ato the extent permitted by law 

and appropriate, and consistent with the agency=s mission,@ Aaddress disproportionate risks to 

children that result from environmental health risks or safety risks.@ For any substantive 

rulemaking action that Ais likely to result in@ an economically significant rule that concerns Aan 

environmental health risk or safety risk that an agency has reason to believe may 

disproportionately affect children,@ the agency must provide OMB/OIRA Aan evaluation of the 

environmental health or safety effects of the planned regulation on children,@ as well as Aan 

explanation of why the planned regulation is preferable to other potentially and reasonably 

feasible alternatives considered by the agency.@

Energy Impacts 

Under Executive Order 13211 (66 FR 28355, May 22, 2001), agencies are required to 

prepare and submit to OMB a Statement of Energy Effects for significant energy actions, to the 

extent permitted by law. This Statement is to include a detailed statement of Aany adverse effects 

on energy supply, distribution, or use (including a shortfall in supply, price increases, and 

increased use of foreign supplies)@ for the action and reasonable alternatives and their effects. 

You need to publish the Statement or a summary in the related NPRM and final rule. For further 

guidance, see OMB Memorandum 01-27 (“Guidance on Implementing Executive Order 13211”, 

July 13, 2001), available on OMB=s website. 

G. Accounting Statement 

You need to provide an accounting statement with tables reporting benefit and cost 

estimates for each major final rule for your agency. You should use the guidance outlined above 

to report these estimates. We have included a suggested format for your consideration. 

44
Categories of Benefits and Costs 

To the extent feasible, you should quantify all potential incremental benefits and costs. 

You should report benefit and cost estimates within the following three categories: monetized 

quantified, but not monetized; and qualitative, but not quantified or monetized. 

These categories are mutually exclusive and exhaustive. Throughout the process of 

listing preliminary estimates of benefits and costs, agencies should avoid double-counting. This 

problem may arise if more than one way exists to express the same change in social welfare. 

Quantifying and Monetizing Benefits and Costs 

You should develop quantitative estimates and convert them to dollar amounts if 

possible. In many cases, quantified estimates are readily convertible, with a little effort, into 

dollar equivalents. 

Qualitative Benefits and Costs 

You should categorize or rank the qualitative effects in terms of their importance (e.g., 

certainty, likely magnitude, and reversibility). You should distinguish the effects that are likely 

to be significant enough to warrant serious consideration by decision makers from those that are 

likely to be minor. 

Treatment of Benefits and Costs over Time 

You should present undiscounted streams of benefit and cost estimates (monetized and 

net) for each year of the analytic time horizon. You should present annualized benefits and costs 

using real discount rates of 3 and 7 percent. The stream of annualized estimates should begin in 

the year in which the final rule will begin to have effects, even if the rule does not take effect 

immediately. Please report all monetized effects in 2001 dollars. You should convert dollars 

expressed in different years to 2001 dollars using the GDP deflator. 

Treatment of Risk and Uncertainty

You should provide expected-value estimates as well as distributions about the estimates, 

where such information exists. When you provide only upper and lower bounds (in addition to 

best estimates), you should, if possible, use the 95 and 5 percent confidence bounds. Although 

we encourage you to develop estimates that capture the distribution of plausible outcomes for a 

particular alternative, detailed reporting of such distributions is not required, but should be 

available upon request. 

The principles of full disclosure and transparency apply to the treatment of uncertainty. 

Where there is significant uncertainty and the resulting inferences and/or assumptions have a 

critical effect on the benefit and cost estimates, you should describe the benefits and costs under 

plausible alternative assumptions. You may add footnotes to the table as needed to provide 

documentation and references, or to express important warnings. 

45
In a previous section, we identified some of the issues associated with developing 

estimates of the value of reductions in premature mortality risk. Based on this discussion, you 

should present alternative primary estimates where you use different estimates for valuing 

reductions in premature mortality risk. 

Precision of Estimates 

Reported estimates should reflect, to the extent feasible, the precision in the analysis. For 

example, an estimate of $220 million implies rounding to the nearest $10 million and thus a 

precision of +/-$5 million; similarly, an estimate of $222 million implies rounding to the nearest 

$1 million and thus, a precision of +/-$0.5 million. 

Separate Reporting of Transfers 

You should report transfers separately and avoid the misclassification of transfer 

payments as benefits or costs. Transfers occur when wealth or income is redistributed without 

any direct change in aggregate social welfare. To the extent that regulatory outputs reflect 

transfers rather than net welfare gains to society, you should identify them as transfers rather 

than benefits or costs. You should also distinguish transfers caused by Federal budget actions -- 

such as those stemming from a rule affecting Social Security payments -- from those that involve 

transfers between non-governmental parties -- such as monopoly rents a rule may confer on a 

private party. You should use as many categories as necessary to describe the major 

redistributive effects of a regulatory action. If transfers have significant efficiency effects in 

addition to distributional effects, you should report them. 

Effects on State, Local, and Tribal Governments, Small Business, Wages and Economic 

Growth 

 

You need to identity the portions of benefits, costs, and transfers received by State, local, 

and tribal governments. To the extent feasible, you also should identify the effects of the rule or 

program on small businesses, wages, and economic growth.30 Note that rules with annual costs 

that are less than one billion dollars are likely to have a minimal effect on economic growth. 

30 The Regulatory Flexibility Act (5 U.S.C. 603(c), 604). 

46
OMB #: Agency/Program Office: 

Rule Title: RIN#: Date: 

Category Primary Estimate Minimum Estimate Maximum Estima

BENEFITS 

monetized benefits

Annualized quantified, but unmonetized, benefits 

(unquantified) benefits

COSTS 

Annualized monetized costsAnnualized quantified, but unmonetized, costs Qualitative (unquantified) costs

TRANSFERS 

Annualized monetized transfers: “on budget” from whom to whom?Annualized monetized transfers: “off-budget” From whom to whom?

Category Effects 

Effects on State, local, and/or tribal governments Effects on small businesses Effects on wagesEffects on growth

47
H. Effective Date 

The effective date of this Circular is January 1, 2004 for regulatory analyses received by 

OMB in support of proposed rules, and January 1, 2005 for regulatory analyses received 

by OMB in support of final rules. In other words, this Circular applies to the regulatory 

analyses for draft proposed rules that are formally submitted to OIRA after December 31, 

2003, and for draft final rules that are formally submitted to OIRA after December 31, 

2004. (However, if the draft proposed rule is subject to the Circular, then the draft final 

rule will also be subject to the Circular, even if it is submitted prior to January 1, 2005.) 

To the extent practicable, agencies should comply earlier than these effective dates. 

Agencies may, on a case-by-case basis, seek a waiver from OMB if these effective dates 

are impractical. 

48