September 17, 2003
TO THE HEADS OF EXECUTIVE AGENCIES AND ESTABLISHMENTS
Subject: Regulatory Analysis
B. The Need for Federal Regulatory Action
C. Alternative Regulatory Approaches
D. Analytical Approaches
E. Identifying and Measuring Benefits and Costs
F. Specialized Analytical Requirements
G. Accounting Statement
H. Effective Date
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, "Regulatory 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
This Circular refines OMB's "best practices" document of 1996 (/omb/inforeg/riaguide.html),
which was issued as a guidance in 2000 (/omb/memoranda/m00-08.pdf),
and reaffirmed in 2001 (/omb/memoranda/m01-23.html).
It replaces both the 1996 "best 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.
This Circular is designed to assist analysts in the regulatory agencies
by defining good regulatory analysis B called either "regulatory analysis"
or "analysis" 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
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 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
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 "threshold" analysis to evaluate
their significance. Threshold or "break-even" analysis answers the question,
"How 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
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:
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 "no action" baseline:
what the world will be like if the proposed rule is not adopted. Comparisons
to a "next best" alternative are also especially useful.
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 non-monetary
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
"Federal 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 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 "Each 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. "Public 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 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 "available," 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.
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
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
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
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;
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 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 Requirements for Different Sized
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.
Different Requirements for Different Geographic
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
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 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 "hot 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
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 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.
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
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 non-quantified 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 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 cost-effectiveness
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 "effectiveness" 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 "effectiveness" or performance measures for the alternative policy
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 called
"total" 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 "effectiveness", final outcomes, such as lives
saved or life-years 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 "outcome"
measure. You should provide an explanation of your choice of effectiveness
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"
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., 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 measurement7,
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 willingness-to-pay-measures. 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
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 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.
Those who bear the costs of a regulation and those who enjoy its benefits
often are not the same people. The term "distributional 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 "Regulatory 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.
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
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 "no 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 "shredder 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, 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 command-and-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 "continuum" 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 "next 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.
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
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
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
Finally, you should assure compliance with the Information Quality Guidelines
for your agency and OMB's "Guidelines for Ensuring and Maximizing the Quality,
Objectivity, Utility, and Integrity of Information Disseminated by Federal
Agencies" ("data quality guidelines") /omb/fedreg/reproducible.html.
Developing Benefit and Cost Estimates
1. Some General
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:
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);
the benefits and costs you can quantify, but cannot monetize, including
benefits and costs you cannot quantify; and
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.
The Key Concepts Needed to Estimate Benefits and Costs
“Opportunity cost" is the appropriate concept for valuing both benefits
and costs. The principle of "willingness-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 "willingness-to-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 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-to-pay 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
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 "avoided" 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, "Direct 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 "hedonic 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 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.
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 "shadow 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 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.
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.
- 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 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.
"Use 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 "non-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.
Stated Preference Methods
Stated Preference Methods (SPM) have been developed and used in the peer-reviewed
literature to estimate both "use" and "non-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
The distinguishing feature of these methods is that hypothetical questions
about use or non-use 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.
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
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;
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;
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
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.
The challenge in designing quality stated-preference studies is arguably
greater for non-use 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.
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 "benefit 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 "zero in" on key aspects of
the benefit transfer.
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
- 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 "reversible"
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
Finally, you should not use benefit transfer in estimating benefits if:
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.
are significant problems with applying an "ex ante" valuation
estimate to an "ex 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
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.
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
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.
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 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”.
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.
- 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.
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 stated-preference 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
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.
- 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 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 stated-preference 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.
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
"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 "value" 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
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 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
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 age-adjustment
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 "value 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 "40 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
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 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.
- 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
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
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.
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.
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:
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
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 "t" 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 "discounted
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.
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
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 "shadow
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 "social rate of time preference." This simply
means the rate at which "society" 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 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.
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 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.
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
time-inconsistency 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, 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.
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, "Control 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.
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 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.
Benefit and Cost Considerations
include these effects in your analysis and provide estimates of their
monetary values when they are significant:
compliance costs and savings;
administrative costs and savings;
or losses in consumers' or producers' surpluses;
or inconvenience costs and benefits; and
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
"learning" 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 "learning 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 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:
rents and monopoly profits
taxes and subsidies
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
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. 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.
"Real 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.
Quantitative Analysis of Uncertainty
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 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:
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
- 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 "switch 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.
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 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
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 "best estimates" of both benefits
and costs with those of competing alternatives. These "best 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 "risk neutral"
with respect to the regulatory alternatives. While this may not always be
the case, you should in general assume "risk neutrality" in your analysis.
If you adopt a different assumption on risk preference, you should explain
your reasons for doing so.
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.
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.
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.
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
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 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.
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
Under Executive Order 13045, "Protection of Children from Environmental
Health Risks and Safety Risks," each agency must, with respect to its rules,
"to the extent permitted by law and appropriate, and consistent with the
agency's mission," "address disproportionate risks to children that result
from environmental health risks or safety risks." For any substantive rulemaking
action that "is likely to result in" an economically significant rule that
concerns "an environmental health risk or safety risk that an agency has
reason to believe may disproportionately affect children," the agency must
provide OMB/OIRA "an evaluation of the environmental health or safety effects
of the planned regulation on children," as well as "an explanation of why
the planned regulation is preferable to other potentially and reasonably
feasible alternatives considered by the agency."
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 "any 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.
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.
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.
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.
Benefits and Costs
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.
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
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 5 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.
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
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.
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.
on State, Local, and Tribal Governments, Small Business, Wages and Economic
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. Note that rules with annual costs that are less
than one billion dollars are likely to have a minimal effect on economic
Click here to access the form
H. Effective Date
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.
We use the term “proposed” to refer to any regulatory actions
under consideration regardless of the stage of the regulatory process.
See Mishan EJ (1994), Cost-Benefit Analysis, fourth edition,
Routledge, New York.
See Coase RH (1960), Journal of Law and Economics, 3, 1-44.
Mishan EJ (1994), Cost-Benefit Analysis, fourth edition, Routledge,
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.
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.
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.
Pliskin JS, Shepard DS, and Weinstein MC (1980), "Utility
Functions for Life Years and Health Status," Operations Research,
Hammitt JK (2002), "QALYs Versus WTP," Risk
Analysis, 22(5), pp. 985-1002.
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.
See Hanemann WM (1991), American Economic Review,
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.
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.
See McConnell KE (1997), Journal of Environmental Economics and Management,
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.
Mishan EJ (1994), Cost-Benefit Analysis, fourth edition, Routledge,
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.
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.
Graham JD (2003), Memorandum to the President’s Management Council,
Benefit-Cost Methods and Lifesaving Rules. This memorandum can be found
Office of Information and Regulatory Affairs, OMB, Memorandum to the President’s
Management Council, ibid.
For more information, see Dockins C., Jenkins RR, Owens N, Simon NB, and
Wiggins LB (2002), Risk Analysis, 22(2), 335-346.
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.
Portney PR and Weyant JP, eds. (1999), Discounting
and Intergenerational Equity, Resources for the Future, Washington,
Weitzman ML In Portney PR and Weyant JP, eds. (1999), Discounting
and Intergenerational Equity, Resources for the Future, Washington,
In some contexts, the word “variability” is used as a synonym
for statistical variation that can be described by a theoretically valid
distribution function, whereas “uncertainty” refers to a more
fundamental lack of knowledge. Throughout this discussion, we use the
term “uncertainty” to refer to both concepts.
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).
Clemen RT (1996), Making Hard Decisions: An Introduction to Decision
Analysis, second edition, Duxbury Press, Pacific Grove.
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.
Cooke RM (1991), Experts in Uncertainty: Opinion and Subjective Probability
in Science, Oxford University Press.
The Regulatory Flexibility Act (5 U.S.C. 603(c), 604).
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