©EPA
United States Office of Children's Health Protection EPA 100-R-03-003
Environmental Protection Office of Policy, Economics, and Innovation October 2003
Agency National Center for Environmental Economics
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Children's
Health
Valuation
Handbook
Office of Children's
Health Protection
NCEE0
NATIONAL CENTER FOR
ENVIRONMENTAL ECONOMICS
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POL
F.CONOM
INNOVAT
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ON
NOTICE
The statements in this document have been developed by the EPA solely for use as a reference for economic analysts in the Agency,
and those consultants, contractors, or other persons who perform work under Agency contract or sponsorship. In addition, publica-
tion of this handbook makes information on the principles, concepts, and methods used by the Agency available to all interested
members of the public. This document is not intended, nor can it be relied upon, to create any rights enforceable by any party in lit-
igation with the United States. The Agency may decide to follow the recommendations provided in this document, or to act at vari-
ance with its recommendations based on its analysis of the specific facts present. This handbook may be revised without public
notice to reflect changes in the Agency's approach to preparing economic analyses, or to clarify and update text.
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Children's Health Valuation Handbook October 2003
Table of Contents
1. Introduction 1-1
1.1 Purpose 1-1
1.2 The Need to Value Children's Health Benefits 1-3
1.2.1 Benefit-Cost Analysis 1-3
1.2.2 Distributional Analysis/Equity Assessment 1-5
1.2.3 Valuing Children's Health Effects 1-6
1.3 Organization of the Handbook 1-8
2. Fundamental Differences Between Adult and Child Health Benefits Valuation .. 2-1
2.1 Risk Differences 2-1
2.1.1 Exposure Differences 2-1
2.1.2 Dose-Response Differences 2-3
2.2 Valuation Differences 2-5
2.2.1 Perspective and Childhood Health Values 2-6
2.2.1.1 The Societal Perspective 2-7
2.2.1.2 The Perspective of Adults-as-Children 2-8
2.2.1.3 The Parental Perspective 2-8
2.2.1.4 Practical Conclusions 2-10
2.2.2 Other Important Factors 2-11
2.2.2.1 Preferences for Risk 2-12
2.2.2.2 Time/Age 2-13
2.2.2.3 Costs Associated with Illness 2-16
2.3 Summary and Implications for Benefit Transfer 2-16
3. Benefit Transfer 3-1
3.1 Benefit Transfer Technique and Children's Health Valuation 3-1
3.1.1 Step 1: Describe the Policy Case 3-4
3.1.1.1 Health Effect Measurement 3-4
3.1.1.2 Health Effect Characteristics 3-5
3.1.1.3 Impacts on Well-Being 3-5
3.1.1.4 Population Characteristics 3-6
3.1.2 Step 2: Assess the Suitability of Existing Studies 3-6
3.1.2.1 Study Quality 3-6
3.1.2.2 Study Similarity 3-8
3.1.3 Step 3: Transfer the Estimates 3-9
3.1.3.1 Point Estimate Approach 3-9
3.1.3.2 Benefit Function Transfer 3-10
3.1.3.2 Lifetime Wealth Adjustment 3-10
3.1.4 Step 4: Evaluate Qualitatively and Characterize Uncertainty 3-11
3.1.5 Summary 3-12
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Children's Health Valuation Handbook October 2003
3.2 Applications of Benefit Transfer to Mortality Risks 3-12
3.2.1 Age 3-13
3.2.2 Risk Aversion 3-14
3.2.3 Voluntariness of Risk 3-14
4. Valuation Methods 4-1
4.1 Standard Economic Valuation Techniques 4-1
4.1.1 Hedonic Method 4-2
4.1.2 Averting Behavior Approach 4-3
4.1.2.1 Household Production Model 4-3
4.1.2.2 Intrahouseho Id Allocation Mo dels 4-5
4.1.2.3 Safety Product Market Models 4-5
4.1.3 Stated Preference Methods 4-6
4.2 An Alternative Approach to WTP: Cost of Illness (COI) 4-8
5. Other Important Types of Analyses 5-1
5.1 Cost-Effectiveness Analysis 5-1
5.2 Breakeven Analysis 5-3
5.3 Bounding Analysis 5-4
5.4 Risk-Risk and Health-Health Analyses 5-4
5.5 Summary 5-5
6. Risk Assessment and Economic Analysis 6-1
6.1 Communication Between Risk Assessors and Economists 6-1
6.1.1 Economists' Contributions to a Risk Assessment 6-2
6.1.2 Risk Assessors' Contributions to an Economic Analysis 6-3
6.1.3 Interaction Between Risk Assessors and Economists 6-3
6.2 Key Components of the Risk Assessment Data 6-4
References Ref-1
Appendix A: Annotated Bibliography A-l
Appendix B: Summary of External Reviewer Comments B-l
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Children's Health Valuation Handbook October 2003
Acknowledgments
Many individuals assisted with the preparation of the Children's Health Valuation Handbook.
The Handbook's principal authors and project managers were Edward Chu of the U.S.
Environmental Protection Agency's (EPA) Office of Children's Health Protection and Chris
Dockins, Robin Jenkins, Nicole Owens, Nathalie Simon, and Lanelle Wiggins of EPA's National
Center for Environmental Economics. The Handbook would not be possible without the support
and leadership of E. Ramona Trovato, former Director of the Office of Children's Health
Protection, and Al McGartland, Director of the National Center for Environmental Economics.
Representatives from various EPA offices provided invaluable assistance developing the
Handbook and providing internal peer review. The program offices were represented by the
following individuals:
• Office of Air and Radiation: Allen Basala and Jim DeMocker;
• Office of Prevention, Pesticides, and Toxic Substances: Nick Bouwes, Gary Cole, and John
Faulkner;
• Office of Solid Waste and Emergency Response: Paul Balserak and Jean Schumann; and
• Office of Water: John Bennett, Christopher Miller, and William Wheeler.
In addition to EPA staff, a number of other individuals developed key background materials used
in the preparation of the Handbook. They included Mark Agee, Pennsylvania State University;
Thomas Crocker, University of Wyoming; Robert Fabian, University of Illinois - Chicago; Harriet
Greenwood, Industrial Economics; James Harbaugh, University of Oregon; Maria Markowski,
Industrial Economics; James Neumann, Industrial Economics; Jason F. Shogren, University of
Wyoming; Kimberly M. Thompson, Harvard School of Public Health; and George Tolley,
University of Chicago. Full citations for these background materials are in Appendix A.
The Handbook also benefitted greatly from the deliberations of the Economics and Assessment
Workgroup of the Children's Health Protection Advisory Committee and from the encouragement
of its members. Members and their affiliations at the time of these discussions include: Jane Hall
(Chair), University of California - Fullerton; Trudy Cameron, University of California - Los
Angeles; Joy Carlson, Children's Environmental Health Network; Mark Dickie, University of
Southern Mississippi; Fernando Guerra, San Antonio Metropolitan Health District; Michael
Hanemann, University of California - Berkeley; Tim Hunt, American Petroleum Institute; Bruce
W. Karrh, Chemical Manufacturers Association; Lilian Kawasaki, Department of Environmental
Affairs - City of Los Angeles; V. Kerry Smith, North Carolina State University; and Rabbi Daniel
Swartz, National Religious Partnership for the Environment. The Workgroup was assisted by
Edward Chu, EPA Office of Children's Health Protection.
The following individuals served as external peer reviewers of the Handbook: Lauraine G.
Chestnut, Stratus Consulting; Jason F. Shogren, University of Wyoming; James K. Hammitt,
Harvard School of Public Health; and A. Myrick Freeman, III, Bowdoin College.
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IV
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Children's Health Valuation Handbook October 2003
1. Introduction
In the last few years, the plight of our nation's children has been a growing concern both within
the U.S. Environmental Protection Agency (EPA) and across other Federal agencies. In the fall
of 1995, the Administrator directed EPA to consider environmental health risks of infants and
children in all risk assessments, risk characterizations, and public health standards set by EPA for
the United States. A year later, in October 1996, the Administrator announced EPA's National
Agenda to Protect Children's Health from Environmental Threats. The Agenda focuses on
several areas: standards protecting children; research strategy; community right-to-know; and
educational efforts for parents, teachers, healthcare providers, and environmental professionals.
The Agenda was followed by the 1997 Executive Order (E.O.) 13045, "Protection of Children
from Environmental Health Risks and Safety Risks." E.O. 13045 states that "each Federal
agency: (a) shall make it a high priority to identify and assess environmental health and safety
risks that may disproportionately affect children; and (b) shall ensure that its policies, programs,
activities, and standards address disproportionate risks to children that result from environmental
health risks or safety risks." It requires, for each covered regulatory action,1 "(a) an evaluation of
the environmental health or safety effects of the planned regulation on children; and (b) an
explanation of why the planned regulation is preferable to other potentially effective and
reasonably feasible alternatives considered by the agency."
While the Agency's Guidelines for Preparing Economic Analyses (U.S. EPA, 2000a) provides
general guidance on how best to perform benefit-cost assessments of policies and programs, this
Handbook discusses issues concerning the valuation of health benefits accruing to children that
are not directly covered in the Guidelines. Information provided in this Handbook, when used in
conjunction with that provided in the Guidelines, should allow analysts to more fully characterize
the benefits of Agency policies and programs.
1.1 Purpose
This Handbook is a reference tool for analysts conducting economic analyses of EPA policies
when those policies are expected to affect risks to children's health. For the purposes of this
document, a child is considered to be a person under the age of 18.2 Thus, the focus of this
E.O. 13045 defines a "covered regulatory action" as one that "may (a) be 'economically significant'
under E.O. 12866 (a rule-making that has an annual effect on the economy of $100 million or more or would
adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the
environment, public health or safety, or State, local, or Tribal governments or communities); and (b) concern an
environmental health risk or safety risk that an agency has reason to believe may disproportionately affect
children."
In various instances, the legal and appropriate definition of "child" may vary. In some cases, adults
with limited cognitive capabilities may be considered children. For help in determining if a policy is expected to
affect children and whether a separate analysis of impacts on children is needed, see EPA Rule Writer's Guide to
Executive Order 13045 (U.S. EPA, 1998).
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Handbook is on valuing the reduction of environmental risks to children living today3 (or for the
purposes of multi-year analyses, in the very near future) and not on future generations. To that
end, the Handbook does not consider issues relevant to inter-generational analyses. Instead, it
focuses on the challenging task of identifying special concerns that arise when considering risks to
the unique subpopulation of those under 18 years of age.
The specific purpose of this document is to inform analysts attempting to estimate the value of
changes in risks to children's health caused by environmental improvements or degradations. This
Handbook:
• Describes three alternative perspectives to a child-determined value of reducing child
health risks (Section 2.2.1);
• Provides information on the valuation of children's health effects by discussing if, when,
and how values for children may differ from values for adults for the same effects (Section
2.2);
• Gives guidance on qualitatively describing the likely over- or under-valuation of reduced
child risk resulting from the transfer of risk values estimated for adults to children (Section
2.2.2);
• Suggests a practical method for adjusting adult health values to better approximate child
health values (Section 3.1.3.1);
• Provides a description of the best way to value risk experienced by children, recognizing
that direct estimates of these values are not yet available (Section 4.1.2.2);
• Discusses how economic methods used to estimate values for adult health effects can be
applied to value children's health effects (Chapter 4);
• Provides instructions on when and how to transfer value estimates derived for adults to
scenarios involving children, as a second best alternative to actual child values (Chapter
3);
• Describes additional analyses that should accompany value estimates as part of a
sensitivity analysis. When other information is lacking, these analyses can substitute for
value estimates as a third best alternative to actual child values (Chapter 5);
• Describes a team approach to risk assessment in which risk assessors and economists
collaborate to arrive at meaningful risk estimates for children (Chapter 6); and
Even when environmental risks to children result in outcomes that manifest themselves in adulthood,
the techniques and recommendations contained in this Handbook are relevant.
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• Provides an annotated bibliography that identifies and describes the limited economics
literature that estimates children's health effect values (Appendix A).
Further, this Handbook presents and discusses issues that may not be satisfactorily addressed by
the current state of knowledge. Discussion of these issues should improve economic analyses of
children's health effects by alerting analysts to unresolved areas and by identifying areas for future
research. In this way, the Handbook will serve as a description of EPA's needs for valuing
children's health effects and will encourage research among EPA and non-EPA economists as
well as other experts.
It is important for readers to note that while this document sometimes makes specific suggestions,
it is generally meant to be informative rather than prescriptive. This is largely because the current
state of economic science has not reached conclusions on many issues related to children. With
few exceptions, in fact, economics literature has not historically considered children in the context
of health valuation. As more information becomes available, this Handbook will be updated to
reflect relevant additions to the literature.
1.2 The Need to Value Children's Health Benefits
A major emphasis of the Children's Health Valuation Handbook is ensuring that the economic
impacts of a regulation or other policy on children are fully considered in the supporting economic
analyses. This includes incorporating children's health considerations in an assessment of
efficiency, as well as in any distributional analysis that seeks to examine the implications
specifically for children. In both cases, the welfare measures for the populations of concern
should be as comprehensive and complete as possible.
1.2.1 Benefit-Cost Analysis
One useful tool for characterizing the efficiency of policies, programs, and activities, regardless of
whether they affect children, is benefit-cost analysis. Benefit-cost analysis allows decision-makers
to directly compare costs and benefits using the same measure (dollars). For policies that have a
substantial impact on children's health, any complete benefit-cost analysis must consider the
resulting changes in children's welfare. Ignoring these effects may alter the conclusions of the
analysis. In an effort to help analysts more fully characterize benefits and, therefore, produce
more complete benefit-cost analyses, this Handbook discusses issues concerning the valuation of
health benefits accruing to children.
To estimate the value of the health benefits to children from a given environmental improvement
and incorporate this value into the benefit-cost analysis of a proposed rule, analysts typically
complete the following general procedures:4
Chapter 7 of EPA's Guidelines for Preparing Economic Analyses (2000a) defines and describes a
general process for benefits analysis, including concerns associated with quantifying significant physical effects.
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• Hazard identification: Identifying the adverse health effects in children that can be
caused by exposure to the contaminant being considered.
• Dose-response evaluation: Describing how the likelihood and severity of adverse health
effects in children are related to the amount and conditions of their exposure to the
contaminant.
• Exposure assessment: Measuring or estimating the magnitude, frequency, duration, and
distribution of children's exposure to the contaminant.
• Risk characterization: Integrating exposure and toxicity information to produce an
estimate of the health risk, often presented as a probability that an adverse health effect
will occur. Risk characterization includes descriptions of the statistical and biological
uncertainties associated with the estimate.
• Quantification of welfare effects: Specifying the ways in which changes in children's
health affect welfare. These may include impacts on school attendance, parents'
attendance at work, medical expenditures, pain and suffering endured, etc.
• Valuation of the welfare effects: Monetizing the expected changes in welfare using
appropriate economic techniques. If monetization is impractical, alternatives including
simple health effect inventories are considered.
Generally, the first four steps of the process (hazard identification through risk characterization)
fall under the realm of risk assessment.5 In the final two steps, quantification and valuation of the
welfare effects, economists use estimates provided by risk assessors and produce monetary values
of the expected changes in welfare.6 These two steps are the main focus of this Handbook.
It is important to note that an explicit or separate analysis of children's welfare may not be
necessary in a benefit-cost analysis if such effects are already embedded in existing welfare
measures. This is most likely to be the case if the household, rather than the individual, is the unit
of analysis. For example, when valuation estimates are based upon household preferences for risk
reductions, and those households include children, it is reasonable to expect that the value of
reduced health risks to children are embedded in the estimates. Because it is not generally
possible to estimate the portion of the household's willingness to pay that is specific to children,
the precise magnitude of the children's health benefits will be unknown. Nonetheless, benefits to
children are included in such measures and therefore are already incorporated into the benefit-cost
EPA's Risk & Decision Making (1992) and Guidance for Risk Characterization (1995) both provide a
description of the components of risk assessment.
For general information on valuing welfare effects, see Chapter 7, Section 7.5 "Methods for Benefits
Valuation" in Guidelines for Preparing Economic Analyses (U.S. EPA, 2000a).
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analysis. In these cases, a separate, additive estimate of children's health benefits would lead to
double-counting.7
In practice, many valuation estimates are expected to measure welfare changes for an individual
only. Such cases include, but are not limited to, value-of-statistical-life measures from wage-risk
studies, most cost-of-illness estimates, and some contingent valuation estimates. Because children
are not explicitly considered in these value estimates, it should not be assumed that benefit-cost
analyses utilizing these values fully account for children's welfare. If children comprise a
significant proportion of the affected population, a separate, explicit benefit estimate may be
required. These estimates will then need to be added to other estimates of welfare changes in the
benefit-cost analysis to examine the efficiency of a proposed policy action.
1.2.2 Distributional Analysis/Equity Assessment
Policymakers may also find it useful to have information on a policy's specific impact on
children's health, regardless of whether the impact heavily influences the overall benefit-cost
analysis. Analysts may wish to conduct an equity assessment with children as the target sub-
population. An equity assessment is a distributional analysis that examines the net costs, net
benefits, or other economic impacts of a policy that accrue to a specific subpopulation.8 E.O.
13045 states that regulations with annual national economic impacts beyond $100 million should
be accompanied by evaluations of the regulation's effects on children. Such evaluations can occur
via equity assessments.
Even for policies with smaller national economic impacts, analysts might wish to conduct child-
focused equity assessments. Two separate, but potentially related, reasons to do so would be if
the policy was expected to have a large or disproportionate impact on children's health or on
children's economic well-being. E.O. 13045 directs policy makers to identify, assess, and address
health risks that disproportionately affect children. Children may be disproportionately affected
by a health risk for a number of reasons including that they make up a substantial component of
the affected population. A different reason might be that they experience exposures to and effects
from pollution that are greater than those of the population as a whole.
A policy might also have a disproportionate impact on the economic well-being of children. A
higher proportion of children live in poverty, thus children are more likely than adults to be
economically disadvantaged (Dalaker and Naif eh, 1997). As a result, the ability of households
with children to undertake averting behaviors might be compromised.
7 More information on methods that may have embedded values for children's health can be found in
Section 5.1.2.
See Chapter 9, Section 9.3 "Equity Assessment" and Chapter 10, Section 10.3.2 "Results from
Economic Impacts Analysis and Equity Assessment" in Guidelines for Preparing Economic Analyses (U. S. EPA,
2000a) for further discussion of the meaning and content of an equity assessment.
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In addition, a third reason to conduct an equity assessment for children for any policy expected to
affect them is that adults do not necessarily act in the best interest of children, regardless of
intention. As a result, children's interests may be less well represented in benefit-cost analyses.
1.2.3 Valuing Children's Health Effects
As a final note, analysts may often lack information on risk and/or valuation, making it difficult to
present first-best valuation estimates specific to children in any analysis.9 In these cases, analysts
should choose one of two alternatives as appropriate. As a second-best option, they might wish
to transfer benefit values estimated for adults to children. Transferred adult values should be
accompanied by a qualitative description of expected differences between children and adults.
Together, Chapters 2 and 3 give guidance for this type of analysis. Box 1.1 shows several
examples where EPA and other agencies have relied on adult values for morbidity and mortality
risk reductions to children. These examples highlight the need for research and analysis targeted
at finding values for children's health effects. As a third-best option, analysts facing an absence of
appropriate values for transfer might choose to analyze impacts via cost effectiveness, breakeven,
or bounding analyses. Chapter 5 gives guidance for these kinds of analyses.
Chapter 4 discusses the options when appropriate child-specific valuation information is not available.
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Box 1.1 Examples Where Children's Health Values Are Needed
There are several examples where regulatory impact analyses have differentiated risks to children from risks to
adults, when appropriate, by identifying exposure and response differences, either qualitatively or quantitatively.
However, in valuing the health effects, most economic analyses rely on adult values for children's health effects,
due to lack of current valuations of children's health effects.
The following are three examples from three different federal agencies:
EPA conducted an economic analysis for the final Heavy-Duty Engine/Diesel Fuel Rule. The economic
analysis specifically discusses impacts on children's health, including acute bronchitis (children, 8-12), lower
respiratory symptoms (children, 7-14), and upper respiratory symptoms (asthmatic children, 9-11). However,
in valuing avoided health effects, no distinction is made between children's health and adult health effects.
Willingness-to-pay (WTP) values for avoiding these symptoms based on studies of adults were used, because
WTP values for avoiding these symptoms in children were not available. (U.S. EPA, 2000f)
The Food and Drug Administration (FDA) conducted an economic analysis in developing final regulations
for the safe and sanitary processing of fruit and vegetable juices. FDA issued these regulations to address
food hazards, including some directly affecting children. These included long-term toxic effects of non-
microbial hazards since children consume larger quantities of juice relative to body weight, well-documented
developmental effects in children due to lead, and illnesses due to E. coli and other bacteria that affect
children more adversely. While effects on children due to different types of contamination are discussed, the
valuation using cost of illness, does not distinguish between adult and children health end points. (U.S. Food
and Drug Administration, 2001)
The National Highway Traffic Safety Administration conducted an economic analysis in support of a final
rule to upgrade the Agency's standard to improve occupant protection provided by air bags. The analysis
quantified risks posed to infants, children, and adults. Alternative regulatory strategies are evaluated using a
cost-effectiveness approach and alternatives are compared by net cost (or savings) per fatality saved. The total
adult, child, and infant fatalities are combined in this calculation, effectively evaluating fatalities across all
age groups equally. (U.S. National Highway Traffic Safety Administration, 2000)
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1.3 Organization of the Handbook
The remainder of this Handbook begins in Chapter 2 by briefly outlining the distinction between
risk differences and valuation differences in adult and child health effects. The rest of Chapter 2
discusses the perspectives that can be taken in estimating values for health risk reductions in
children and then describes the economic reasons for the valuation differences in child and adult
health benefits. In many instances, conducting original valuation research is impractical, requiring
analysts to turn to benefits transfer. This is the subject of Chapter 3 - when and how to transfer
value estimates derived for adults to scenarios involving children. Chapter 4 reviews issues
associated with applying standard and alternative valuation techniques to children's health effects.
Chapter 5 follows with a description of important types of analyses that may complement, or
when valuation data are scarce, substitute for, benefits valuation. Chapter 6 describes a team
approach to risk assessment in which economists and risk assessors collaborate early in the
benefits valuation process with useful results.
Although the focus of this Handbook is on benefits valuation for use in benefit-cost analysis, it
also discusses measures used in other types of analysis. For the reader's reference, Box 1.2
briefly defines these types of analyses and associated measures and references sections where
more information can be found in the Handbook.
The Handbook includes two appendices. Appendix A is an annotated bibliography of the current
literature providing estimates of child health effect values plus references for relevant papers that
have been presented at conferences and workshops. Appendix B summarizes EPA's response to
comments received during an external review of the draft Handbook.
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Box 1.2 Types of Analyses and Measures Discussed in This Handbook
Type of Analyses and Measures Used
...
Information
Benefits Analysis
Used to estimate the beneficial consequences of policy for use in a benefit-cost test of Chapter 3
efficiency. Measures used in benefits analysis, in order of desirability, include:
• Primary WTP estimates: WTP estimates drawn from the context in which they _, .
- , - Chapter 4
are used.
• Transferred WTP estimates: WTP estimates from other contexts applied to the _,
— T - : — u - r77~ f * t, • Chapter 3
policy case using benefit transfer techniques.
• Cost-of-illness estimates: Direct and indirect cost of medical treatment and lost _ . „
- Pase 4- /
productivity; usually lower than WTP for the same health endpoint.
Cost-Effectiveness
Used to rank policy alternatives according to most "bang for the buck. " Measures used Chapter 5
in cost-effectiveness analysis include:
• Physical measures of health such as lives saved or cases avoided. Page 5-1
• Utility measures of health such as quality-adjusted-life-years (QALYs) and _
disability-adjusted-life-years (DALYs).
Health-Health Analysis
Compares regulatory costs to estimated threshold at which regulatory costs result in a Page 5-4
statistical life lost.
Breakeven Analysis
Used when valuation or risk data are unavailable; identifies what the value would need to Page 5-3
be for an option to be efficient and/or more cost-effective than other alternatives.
Bounding Analysis
Used when valuation data are unavailable; may place upper and lower bounds on the Page 5-4
value of reduced health effects by referencing known values for other effects.
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2. Fundamental Differences Between Adult and Child
Health Benefits Valuation
When estimating children's health benefits for any analysis, two sets of potential differences
between children and adults may exist:
• Risk differences: Children and adults differ in exposure to pollutants and in the nature
and magnitude of health effects arising from exposure.
• Valuation differences: Individuals may systematically place a different economic value
on reducing health risks to children than on reducing health risks to adults.
When these differences exist, estimates of the value of children's health benefits are likely to differ
from those for adults. These risk and valuation differences will vary in importance depending
upon the particular health benefits associated with a proposed policy. No hard and fast rules
currently exist for determining when a separate valuation of childhood risks should be conducted.
However, analysts should consider estimating and presenting the dollar value of changes in health
risks specifically to children when the differences in risk and/or valuation between children and
adults are potentially important. The greater these differences, the more valuable will be estimates
of health benefits specific to children. The implications of both types of differences are discussed
in the sections that follow.
2.1 Risk Differences
10
Risks from environmental contamination may not affect children and adults in the same manner
due to differences in exposure and the response to that exposure. Generally, accounting for the
risk differences between children and adults should be a component of risk assessments. While
risk assessment is not the focus of this Handbook, many important decisions that may ultimately
affect the final value assigned to children's health effects are made during the risk assessment
process. Economists should be aware of the implications of these decisions for value estimation.
In Chapter 6, the importance of good risk assessment data for an economic analysis is discussed,
and suggestions for stimulating productive communication among health professionals, risk
assessors, and economists are provided. A team approach to assessing risks to children is
recommended when differences in risk are suspected.
2.1.1 Exposure Differences
Children's exposures often vary from those of adults. Due to their higher metabolic activity,
children have higher daily requirements for food, water, and oxygen per unit of body weight than
do adults (International Life Sciences Institute, 1992; Bearer, 1995). To the extent that these
This section is based in part on information presented in Thompson, 1999.
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media provide the routes of exposure to the substance, children can experience a larger effective
dose than adults. Box 2.1 provides an example of how exposure differences were considered in
the arsenic in drinking water rule.
Box 2.1 Arsenic in Drinking Water: An Example of Exposure Differences
The Office of Ground Water and Drinking Water conducted an economic analysis in December 2000 for the
arsenic in drinking water rule. The analysis specifically considered impacts on children. Due to their higher
fluid and food intake in relation to their body weight, children's dose (milligrams per kilogram of body weight
per day- mg/kg/day) of arsenic will be, on average, greater than that of adults. For example, an intake of 1.2
liters per day in a 70 kg adult yields an overall water intake of 0.017 liters per kg of body weight. An infant
who consumes 1 liter per day and weighs 10 kg is consuming 0.1 liter per kg of body weight, which is more
than 5 times the water intake per kg of an adult. Any contaminant that is present in the water will be delivered
at a correspondingly higher level on a daily basis.
Source: U.S. EPA, 2000d.
Children's activity patterns may also differ significantly from those of adults. Consequently, some
exposure scenarios or conditions that apply to one group might not apply to the other. For
instance, occupational exposure scenarios for adults would probably not apply to children.
Conversely, exposure due to extended periods of time spent crawling on the ground, excessive
hand-to-mouth behavior, or high rates of soil ingestion would probably not apply to adults.
Lack of child-specific risk information may lead to uncertain risk measurements. Children are less
often exposed to levels of substances that cause observably harmful effects. For instance, children
do not endure hazardous occupational exposures, as do some adults, nor do they participate in
clinical trials of exposure to environmental contaminants. Even when the affected population
consists of adults, EPA analysts, who typically are studying scenarios involving low levels of
exposure, must extrapolate from limited data on health effects observed at high levels of
exposure. The problem is compounded when estimating effects on children, since now
information about health effects observed in adults experiencing high levels of exposure must be
extrapolated to children experiencing low levels of exposure. The limited existing data that
demonstrate differential effects on children as compared with adults largely come from infrequent
cases where children experienced accidental, high exposures that resulted in significant numbers
of cases of relatively rare, detectable diseases (Rogan, 1995).
While in some cases extrapolation from data based on limited evidence from a cohort of
occupationally exposed adults may be required to estimate the effects on children, in others, the
best available evidence may be from animal studies. Under this scenario, risk assessors are forced
to extrapolate toxicological data across species as well as across groups.
One notable exception is research on the effects of exposure to ambient air pollution. A large
number of epidemic logical studies exist that focus on the relationship between health risks among
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children (e.g., asthma and low birth rate) and ambient levels of criteria air pollutants (Fauroux et
al., 2000; McConnell et al, 2002; Maisonet et al., 2001). Age specific studies on health risk
should be used when available.
2.1.2 Dose-Response Differences
A child's response to exposure to a given level of toxic substances can differ from that of an adult
in outcome (a qualitative difference) and in severity (a quantitative difference). For instance,
examples exist of cases where exposures of children resulted in health effects that did not occur in
exposed adults (e.g., vaginal and cervical cancer from fetal exposure to diethylstilbestrol) and vice
versa (e.g., sterility following adult exposure to mumps) (Wilson et al., 1991). Examples also
exist of cases where adults are more sensitive to exposure (i.e., endure a more severe outcome)
than children for the same effect (e.g., liver toxicity from exposure to acetaminophen) and vice
versa (e.g., neurological damage from exposure to lead or hexachlorophene) (Kauffman, 1992;
Davis and Grant, 1992; Kacew, 1992). Box 2.2 provides examples of differences in both
outcome and severity.
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Box 2.2
Examples of Dose-Response Differences
Health Effects Due to Lead: An Example of Response Outcome Differences
EPA's Office of Air and Radiation developed a retrospective analysis estimating the benefits and costs of the
Clean Air Act itself covering the period beginning with passage of the Clean Air Act Amendments of 1970 until
1990 when Congress enacted the most recent comprehensive amendments to the Act. Appendix G, "Lead
Benefits Analysis," of The Benefits and Costs of the Clean Air Act, 1970 to 1990 identifies quantified and
unquantified health effects of lead and differentiates children from adult males and females as follows:
Population
Group
Quantified Health Effect
Unquantified Health Effect
Adult
Male
For men in specified age ranges:
Hypertension
Non-fatal coronary heart disease
Non-fatal strokes
Mortality
For men in other age ranges:
Other cardiovascular diseases
Neurobehavioral function
Adult
Female
For women in specified age ranges:
Non-fatal coronary heart disease
Non-fatal stroke
Mortality
Health effects For women in other age
ranges:
Other cardiovascular diseases
Reproductive effects
Neurobehavioral function
Children
IQ loss effect on lifetime earnings
IQ loss effect on special educational needs
Neonatal mortality due to low birth weight
caused by maternal exposure to lead
Fetal effects from maternal exposure
(including diminished IQ)
Other neurobehavioral and physiological
effects
Delinquent and anti-social behavior
Source: U.S. EPA, 1997.
Ground Water Rule: An Example of Severity of Response Differences
EPA's Office of Ground Water and Drinking Water conducted a regulatory impact analysis for a proposed
ground water rule (GWR) in April 2000. The primary goal of the proposed GWR was to improve public health
by identifying public ground water systems that are, or are likely to become, fecally contaminated, and to insure
adequate measures are taken to remove or inactivate pathogens in drinking water provided to the public by these
systems. Rotavirus represents a large group of viruses suspected to cause outbreaks of gastroenteritis in public
water system drinking water supplies. These viruses include Norwalk, Norwalk-like small round structured
viruses, caliciviruses, adenovirus, astrovirus, and other enteric viruses. The populations that are particularly
sensitive to this class of viruses include infants and young children. For example, there are response differences
between children less than two years old and the rest of the population. The probability of illness given a
rotavirus infection is 0.88 for children less two years old and 0.10 for all others. The regulatory impact analysis
indicates that the viral and bacterial illnesses of concern to the GWR disproportionately affect children;
therefore, the benefits of the proposed rule accrue disproportionately to children.
Source: U.S. EPA, 2000e.
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Also, the degree of vulnerability to exposure to a particular substance may vary by stage of
development. Recent research on teen cigarette smoking, for example, suggests that smoking
earlier in life may lead to permanent DNA damage (Wiencke et al, 1999). This same damage
does not occur in those who start smoking later in life.
Analysts should also be aware of relevant advances in medical technology. Economists valuing
childhood cancer cases, for example, may need to factor in higher survival probabilities due to
recent advances in the successful treatment and management of many types of childhood cancers
(Carroquino et al., 1998).
Finally, analysts should remember that in many cases children represent a group that is relatively
understudied lexicologically. Historically, pediatric populations have not been the subject of
sufficient pharmaceutical trials (U.S. Department of Health and Human Services, 1997) or of
epidemiological studies due to the relative rarity of disease (Grufferman, 1998). Because
sufficient information is often lacking, analysts should not automatically assume that children are
unequivocally more (or less) sensitive and vulnerable to adverse health effects from exposure to
toxic substances than adults (i.e., that children always have higher (or lower) risk). Instead, the
evidence that is available for children suggests that relative risk must be assessed on a substance-
by-substance basis.
2.2 Valuation Differences
The theoretically preferred method for estimating the value of health risk reductions is to measure
the affected population's ex ante WTP to avoid the health risk.11 However, sometimes the only
practical estimation alternative is to measure the costs of illness (COI). The primary purpose of
this section is to discuss differences between the WTP for child health and the WTP for adult
health. In addition, we discuss differences that should be expected in values intended to represent
the costs of illness. For an explanation of how to estimate values under the two methods, please
see Chapter 4.
While the economics literature contains many estimates of WTP for adult health risk reductions, it
contains very few for children. As a result, distinctions between WTP values applied to risk
reductions experienced by children and those applied to risk reductions experienced by adults are
difficult to make, even though they are likely to exist for a number of reasons. Currently, the only
practical alternative for estimating WTP for child health is to transfer values estimated for adults
to children.12 If the value of reducing risks to children's health does indeed differ from that of
Ex ante WTP is generally preferred for a regulatory context in which the relevant question is how to
reduce the chances of an adverse event occurring (and not how to compensate individuals who have already
experienced an event). For an explanation of the conceptual underpinnings of WTP in benefits analysis, see
Chapter 7, Section 7.2 "A Conceptual Framework for Benefits Analysis" in Guidelines for Preparing Economic
Analyses (U.S. EPA, 2000a).
See Chapter 3 for a detailed discussion of the benefit transfer of adult values to children.
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adults', this practice may bias the conclusions of an economic analysis and result in inefficient
policy choices.
A few studies have gathered evidence supporting the notion that the value of reducing health risks
to children differs from that of adults. They are based on surveys that collect information on the
public's preferences for saving lives or improving the health of individuals who belong to one age
group versus another. Generally, these studies find that preferences for reducing morbidity and
mortality risks vary with the age of the affected population. Where children are explicitly
included, children's health benefits are ranked more highly than adults' health benefits, with
certain stages in adult life receiving a higher value than others (Jones-Lee, Hammerton, and
Philips, 1985; Williams, 1988; Lewis and Charney, 1989; Busschbach, Messing, and De Charro,
1993; Cropper, Aydede, and Portney, 1994). Other research has generated estimates of WTP for
child and adult health that are directly comparable, since they are derived using comparable data
and methods. The findings vary. One study estimates the value of a statistical child's life as lower
than the value of a statistical adult's (Jenkins, Owens, and Wiggins, 2001). A different study
estimates the WTP for child health as higher than the WTP for adult health (Liu et al, 2000).
The sections that follow provide a more detailed discussion of the economic reasons for the
differences in child and adult health benefit values. The fundamental issue of whose perspective
should determine the WTP for child health is tackled first. Three possibilities are discussed and
assessed in terms of their validity, use, and practicality. This is followed by a discussion of eight
potential differences between values associated with children's health risks and values estimated
for adults. Of the eight differences, only the one stemming from expected lifetime wealth suggests
a practical method for adjusting an adult value to bring it closer to a child value. The method is
outlined and the reader is referred to sample applications presented in a later chapter.
2.2.1 Perspective and Childhood Health Values
Childhood health valuation presents the economist with a unique question, "Whose preferences
should determine the value?" Welfare economics rests on the assumption that decisions are made
by rational individuals. Rationality, while not meant to imply sensibility, does imply that the
decision process is coherent and logically consistent. Individuals are assumed to be capable of
ranking alternate consumption bundles and determining the final choice, as constrained by a
budget. The suggestion is that individuals are best suited to judge for themselves the value of
goods or services (Randall, 1987). Thus, when economists have estimated values of risk
reduction, they have preferred to derive these estimates from the willingness of individuals to pay
for risk reductions that affect themselves. For the purposes of policy assessment, these individual
risk-dollar trade-offs are then aggregated over the population at risk to calculate measures such as
the value of a statistical life (VSL) for fatal risks or the value of a statistical injury (VSI) for non-
fatal health risks. Although in some cases altruism may serve to increase the value of reducing an
individual's risk, adult health risks are typically valued using data on trade-offs made between
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"own-risk" and "own-income."13 Estimates of these values have typically been derived from data
on observed behavior in the labor market or from surveys directed at valuing self-experienced
risks.
Unfortunately for the analyst valuing childhood risks, children cannot reasonably be assumed to
exhibit rationality. Due to their immature cognitive ability, children do not have well-defined
preferences over the full range of health and safety alternatives. In addition, they do not have
control of the financial resources required to make trade-offs between money and health. In
short, the basic tenets of welfare economics cannot reasonably be assumed to represent children.
Dockins et al. (2002) thoroughly explores the different viewpoints from which child health values
could be estimated. They suggest that researchers focus their inquiry on what individuals who
have the long-run best interests of the child at heart would pay. They discuss three possible
alternative perspectives - that of society, by which is meant an aggregation of parent and non-
parent adults; that of adults placing themselves in the position of children, for example by thinking
back to their own childhoods; and finally, that of parents assessing risks faced by their own
children.14
2.2.1.1 The Societal Perspective
Dockins et al. (2002) explain that one approach to valuing risk reductions to children in a public
policy context is to rely on values that reflect both parents' preferences for risk reductions to their
own children as well as adult altruistic concerns for children in general. Limited empirical
evidence suggests that values associated with altruism may be substantial, particularly for children
(Viscusi, Magat, and Forrest, 1988). While altruism does not necessarily increase the value of
risk reductions, it has the potential to do so. If altruism is paternalistic - an individual is
concerned with the level of safety experienced by his neighbor but does not respect his neighbor's
preferences for risk - it will result in higher values (Jones-Lee, 1992). For children's health
valuation, if an adult were concerned about children's health risks and did not respect the parents'
risk preferences toward their own children, then it may be appropriate to include these additional
values in an assessment of social valuation.
While it is interesting to consider societal preferences for children's health, the practical
implications are quite limited. As mentioned, when assessing adult WTP for reductions in adult
risks, economists measure personal WTP for one's own health. Estimates of societal WTP for
adult risk reductions are generally unavailable because of the difficulty in assessing the degree and
Altruism does not necessarily increase the value of risk reductions. Only if altruism is paternalistic -
an individual is concerned with the level of safety experienced by his neighbor but does not respect his neighbor's
preferences for risk - will it result in higher values (Jones-Lee, 1992).
They also briefly consider the possibility of relying on children themselves and for similar reasons as
those above, determine that this is ill advised.
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type of altruism in WTP estimates for the health of others (or for the health of other people's
children).15 Lacking these measures, analysts must turn to more practical considerations.
2.2.1.2 The Perspective of Adults-as-Children
Another perspective from which to assess values of childhood risk is termed by Dockins et al. as
the "adults-as-children" perspective (2002). It requires adults to place themselves in the position
of children, for example by asking adults about preferences they currently exhibit as they think
back to their own childhood and the risks they faced. This approach allows the analyst to avoid
relying on irrational (child) decision-makers and bestows the further advantage that the values are
reported by individuals considering their own selves.
There are several concerns about this perspective. First, one method for measuring it might
literally involve asking adults to think back to their childhoods and assess values of risk
reductions. Such a question would be extremely difficult for a researcher to develop and for a
respondent to answer. Respondents simply might not be able to entirely accept whatever
hypothetical scenario is postulated and as a result could respond based on an ex post position.
This would cause the responses to diverge from the researcher's objective of estimates of ex ante
WTP for reductions in risk. Finally, by asking adults to think back in time, the method neglects to
account for the expected growth in income to be earned by today's children over the course of
their lives relative to today's adults. Concern about wealth growth is covered in more detail in
Chapter 3 where we present a practical method to account for it.
A second concern is that there is a gap in the economics literature regarding this perspective.
Models to represent it have only recently been developed and, to our knowledge, no applications
of the method currently exist with one exception. Researchers have represented the perspective
via the human capital approach. Here is where the perspective holds promise. One approach for
estimating values representative of the adult-as-child perspective is to construct value estimates
that provide some sort of bound on what a child might express as WTP if that child was an adult
looking back. For example, if an early intervention increases a child's expected lifetime earnings,
one might reasonably assume that this hypothetical child would be willing to pay up to the present
value of those larger returns to secure them.16
2.2.1.3 The Parental Perspective
Children rely upon parents and other caregivers to monitor and make decisions concerning health
and safety for them. Thus, a logical valuation-by-proxy approach for children's health risk is the
elicitation of values from parents or other primary caregivers. The sparse existing research that
For further discussion of the problems involved in identifying the extent and type of altruism in WTP
for children's health, see Dockins et al. (2002).
For a discussion and apj
Chapter 4, Section 4.2 and Box 4.1.
For a discussion and application of estimating the value of a child's reduced human capital, see
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has estimated the WTP for children's health has relied upon the preferences of parents and
guardians, or in one case, of adults in the same household as children. For example, Carlin and
Sandy (1991) examine car safety seat purchases and use behavior of mothers to estimate the value
of a statistical child's life (VSCL). Agee and Crocker (1996a) rely on parents' decisions to treat
their children's elevated blood-lead level to infer WTP for reduced burdens. Viscusi, Magat, and
Huber (1987) present evidence on the value of reducing health risks to children from misuse of
household chemicals based on the preferences or decisions of adults living in the same household
as children. Indeed, a complete review of this literature reveals that economists have emphasized
the importance of households as the relevant decision-making unit regarding children's health and
have modeled children's health values accordingly. See Chapter 4 for a discussion and assessment
of the relevant household models.
An advantage of the parental perspective is its reliance on adults who seem likely to have the
child's best interests at heart. A disadvantage is that it introduces a third party into the valuation
exercise; that is, it does not gather values from economic agents who are considering their own
selves. This introduces a number of special concerns.
• Parental motivations: It is possible that parents might not always be motivated to make
decisions in a child's best interests (Agee and Crocker, 1999). If this is the case, then
parental values for child risk reductions may be incomplete or biased, a concern suggested
by some of the empirical work on child health valuation. Two potential motivations are
concern about self in old age and safety-focused paternalistic altruism.
• concern about self in old age - Parents concerned mainly about their own security
during old age may generate value estimates that reflect only the "use value" of
services provided by grown children and exclude the other positive effects of
reducing risks to children, such as higher future utility experienced by the child
himself. In this extreme example, a parental intermediary might underestimate the
full value to the child of reducing his risks.
• safety-focused paternalistic altruism - Parental values for reducing a child's risk
might reflect paternalistic altruism. In this case, parental values of a child's risk
reduction may be inflated as compared with the value that the child himself would
have as a competent adult looking back at his childhood.
• Information deficiencies: Parents might not possess complete information regarding
children's health and safety risks. For instance, uninformed parents might not be aware of
the impact some of their own actions have on the welfare of their child and may engage in
actions that contribute to illness or injury in their own children. Dickie and Nestor (1998)
note some of these actions, including parental smoking, failure of parents to manage
childhood asthma, and resistance to the use of child safety seats. Of course, a similar
concern can be expressed regarding adult ignorance of consequences to his own health
caused by similar actions, such as smoking. That parents are intermediaries representing
children's interests, however, suggests a greater likelihood of ignorance because the child,
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and not the parent, actually experiences the consequences.
• Extreme cases: Certain information deficiencies and motivations not aligned with the
children's best interests are likely to affect parental decision-making in only a few extreme
cases, for example, when parents suffer from severe mental illness. In general, from a
valuation standpoint, these cases pose little concern since economic values used in benefit-
cost analyses are estimated by averaging over a large number of individuals. However, if
these characteristics describe large segments of the parent population, the resulting values
may not be appropriate for policy analysis.
• Parents' budget constraint: Parents must operate within their budget constraint while
making decisions regarding their children's health. Two aspects of the parents' budget
constraint warrant consideration.
• It is important to recognize that parents may react to a policy intended to reduce
children's health risk by redistributing household resources among different
activities. Parents may change the amount of resources being devoted to the
human capital or consumption of other family members.17
• As already mentioned, the expected lifetime wealth of children is higher than that
of adults. Generally, parents cannot borrow against children's future incomes and
so might be constrained to value their own children's health less than would their
hypothetical grown-up child.
2.2.1.4 Practical Conclusions
Although there are concerns regarding use of the parental perspective, it seems well-suited to the
task of estimating child health values. The perspective is from individuals likely to have children's
best interests at heart, it is modeled within the context of the household where most decision-
making regarding health actually occurs, and is estimated using numerous practical methods,
including examining safety product spending or modeling parental decisions regarding treatments
or preventions.
The primary advantage of the parental perspective over the adult-as-child perspective is that there
is a literature, albeit a sparse one, that has focused on the parental perspective. This literature on
WTP for child health has offered theoretical models to represent the parental perspective while
only preliminary modeling efforts have been directed at the adult-as-child perspective. The
literature has also led to the development of more than one practical estimation method for
representing a parent's perspective. These advantages might diminish with further research into
the adult-as-child perspective. The primary advantage of the adult-as-child perspective over the
17 For a full discussion, please see the discussion in Chapter 4 regarding household production models
and intrahousehold allocation models, Sections 4.1.2.1 and 4.1.2.2, respectively.
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parental perspective is that it does not present the variety of issues that arise from obtaining
values from a third party.18
In conclusion, both the parental and adult-as-child perspectives are useful for representing
children's health values. Each offers distinct advantages and disadvantages. Analysts are likely to
encounter values representative of the parental perspective when gathering estimates of WTP for
child health currently available in the economics literature. Values representative of the adult-as-
child perspective are more closely linked to the COI method. These values can be estimated via
the human capital approach by measuring lost lifetime income due to childhood illnesses. This
approach has been taken by government agencies measuring the impact of lead poisoning on
children's future earnings potential.19
Recommendation (perspective): Based on the discussion above, analysts can rely on either the
parental or the adult-as-child perspectives for representing children's health values. Concerns
regarding reliance on third party proxy values aside, the parental perspective provides value
estimates from individuals likely to have the child's best interest at heart, incorporates the
household context into the estimation approaches, and can be implemented using a variety of
valuation techniques. The adult-as-child perspective, on the other hand, although perhaps more
difficult to implement, does not suffer from the problems associated with using proxy values.
Regardless of which perspective is ultimately chosen, the analyst should take care to make the
perspective explicit.
2.2.2 Other Important Factors
In practice, because of the paucity of estimates of WTP for children's health, analysts will often
transfer estimates of WTP for adult health to childhood cases. Because of practical difficulties in
obtaining even adult WTP values for many health endpoints, analysts will also occasionally need
to transfer estimates of COI for adult health to children. Table 2-1 lists factors that suggest that
transferring adult values to children introduces a bias. When possible, the expected direction of
the bias is discussed. For some factors there is an expected direction for this bias and other
factors have an unknown bias. Therefore it is not possible to conclusively know the direction of
bias introduced by all the factors together. As noted in the table, some of the factors are relevant
to both transferred WTP and transferred COI estimates, while others to only one of these
valuation methodologies.
Interestingly, for the transferred adult WTP values, the biases introduced by the factors in Table
2-1 do not depend on the perspective the value is intended to represent. Whether the analyst is
interested in representing the parental or the adult-as-child perspective, the direction of the impact
of each factor is expected to be the same. This is explained in the discussions of the bias
associated with each factor that follow the table.
For further discussion of these perspectives, please see Dockins et al., 2002.
19 Please see Chapter 4 for a discussion and applications of the human capital approach.
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Table 2-1. Transferring from Adult to Child: Factors That May Cause Differences in
Values Estimated for Children Compared to Values Estimated for Adults
Factor That May Cause
Difference
Preferences for Risk
• Risk aversion
• Involuntariness of risk
• Ambiguous risk
Time/Age
• Duration of illness/
life expectancy
• Expected lifetime
wealth
• Discount rate
Costs Associated with Illness
• Medical treatment
• Value of time
(including caregivers'
time)
Potential Difference
Relative to Transferred
Adult Values
• Higher child values
• Higher child values
• Higher child values
• Higher child values
• Higher child values
• Unknown
• Unknown
• Higher child values
Type of Value to be
Transferred from Adult to
Child
WTP
WTP
WTP
WTP and COI
WTP and COI
WTP
COI
WTP and COI
2.2.2.1
Preferences for Risk
Individual preferences about risk suggest three reasons to expect transferred WTP values for adult
health to be different from WTP values estimated directly for children.
• Risk aversion: Parents might be more conservative in their decisions to expose children
to risk or, stated differently, might be more risk averse with respect to their children's
well-being than they are regarding their own. In addition, adults thinking back to risks
experienced during childhood might exhibit greater aversion to risks experienced by their
child selves than to those experienced by their adult selves. Evidence of this can be found
in common everyday actions as well as in U.S. law. For instance, parents may take greater
care in washing their children's fruits and vegetables free of potentially harmful pesticides
than they do their own. Another example can be found in statewide bicycle helmet laws
that apply only to children (of various age ranges). In addition, the Food Quality
Protection Act of 1996 requires an additional tenfold margin of safety for children to
ensure that they face no harm from aggregate exposure to pesticide and chemical residues.
While the risks faced by adults and children may differ considerably in these examples, the
level of protection mandated for children suggests that society is more risk averse in the
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case of children. Greater risk aversion suggests that reducing risks to children is likely to
be valued more highly than reducing similar risks to adults.
• Involuntariness of risk: A different aspect of risk is the degree to which the voluntary
nature of risks influences WTP. Research suggests that individuals generally prefer to
avoid risks to themselves that are less voluntary (Fischhoff et al, 1978; Slovic, 1987). It
is unclear, however, whether parents' attitudes about the voluntariness of risks to
themselves are the same as their attitudes toward risks to their children. There has been
no empirical research on this subject, likewise for adults thinking back to risks experienced
during childhood. One might argue, however, that the issue of voluntariness is always
important in the case of risks to children because in some sense all risks to children are
involuntary in that children rely on the risk-related decisions of caregivers.
• Ambiguous risk: Finally, the uncertainty surrounding the risk estimate itself may have an
effect on the value individuals place on the risk. Economists distinguish risk from the
uncertainty about that risk, terming the latter "ambiguity." Individuals appear to exhibit
ambiguity aversion, preferring certain risks to those that are less certain (Viscusi, Magat,
and Huber, 1991). These preferences have strictly been found to hold for different
degrees of uncertainty in otherwise identical risks. It is reasonable, however, to expect
many situations in which adults and children face risks of similar magnitude, but for which
the children's estimates are much less certain. This follows from the fact that, for ethical
reasons, children are excluded from the pool of subjects available for clinical trials of
harmful exposures and do not face occupational exposures like adults. To the extent that
parents must balance relatively well-defined risks to themselves against relatively
ambiguous risks to their children, ambiguity aversion would lead them to prefer reducing
the latter, all else equal. For the same reason, adults thinking back to childhood
experiences might exhibit more conservative preferences regarding risks experienced
during childhood compared to risks experienced during adulthood. Thus, the value of risk
reductions to children may include a component of ambiguity aversion.
2.2.2.2 Time/Aae
Three factors related to time or age suggest that transferred WTP or COI values for adult health
should be different than values estimated for child health. The first, and perhaps most obvious, is
that children have a greater number of life years remaining (all else equal) as compared with
adults. Second, children have a greater expected lifetime wealth as compared with adults. The
third factor concerns the potential for the application of different discount rates used to calculate
the present value of latent health effects. While all three of these factors may cause differences in
health risk valuation, it should be noted that a practical method for adjusting adult values to better
approximate child values has been developed for one of them- expected lifetime wealth. In fact,
of all the factors listed in Table 2-1, expected lifetime wealth is the only factor at this time for
which a quantitative adjustment is offered.
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• Duration of iDness/life expectancy: All else equal, children have more years of life
remaining than adults. This implies that in terms of years, a larger number will be lost
when a child dies than when an adult dies, all else equal. A child may also experience a
longer period of morbidity than an adult for some chronic, non-fatal health endpoints, such
as asthma or a longer period of disability for a permanent injury. This suggests that,
whether estimating WTP or COI, avoiding a child's illness, injury, or death is likely to be
valued more highly than avoiding the same in an adult.20
• Expected lifetime wealth: The expected lifetime wealth of an average citizen increases
as the years pass.21 Thus, the wealth expected to accumulate over the life span of
someone who is currently young is greater than that expected to accumulate over the life
span of someone who is currently old. Estimates of the elasticity of WTP with respect to
income for reduced mortality or morbidity risk are available in the economics literature
and range from 0.3 to 1.0 (Blomquist, 1979; Jones-Lee, Hammerton, and Philips, 1985;
Evans and Viscusi, 1990; Liu, Hammitt, and Liu, 1997).22 Assuming that the average
elasticity is positive but less than 1.0, as wealth increases, VSL should also increase, albeit
by a smaller proportion. Everything else held constant, this suggests that the WTP for a
reduced risk expressed by a current adult will be lower than the WTP for the same risk
expressed by a future adult.23
A parent reporting WTP to avoid health risks faced by their child is considering the
welfare of a person who is currently young and whose wealth will grow. Parents may,
consciously or unconsciously, attempt to account for these future expected increases in
their children's wealth when determining their WTP for child risk reductions. Analysts
attempting to represent the parental perspective will therefore want to adjust transferred
adult values to reflect the expected growth in lifetime wealth of children.
The adult-as-child perspective can be measured via two different approaches. One
involves an adult thinking back in time which would not lead to WTP estimates that take
into account future wealth growth. Thus, analysts interested in representing this
The greater life expectancy for children may also increase the value of other investments besides risk
reduction. Because WTP for health reflects the household's trade-off between spending on risk reduction and
spending on other goods and services, when the value of spending on other investments in children rises along
with the value of health spending, WTP for health might not necessarily increase.
While real GDP per capita has fluctuated over the years, and annual growth rates have occasionally
been negative, it has trended upwards for at least the last 70 years.
It is assumed that income is a proxy for lifetime wealth.
23 Examples of variables held constant are tastes, all other prices, and skill at avoiding risks. Also held
constant is the timing of risk. For example, if the risk considered by a current adult is an immediate risk, then so
is the risk to be considered by a future adult.
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perspective would not necessarily adjust for this factor.24 However, another approach to
the adult-as-child perspective is to estimate a lower bound of what a child might express
as WTP if that child was an adult. Such an estimate can be obtained via the human capital
method. Under this approach, the adult-as-child perspective would indeed account for the
greater expected lifetime wealth of children.
Unlike all the other factors expected to cause a difference in child and adult health values
(see Table 2-1), the growth in expected lifetime wealth suggests a practical method for
adjusting a transferred estimate of WTP for adult health to bring it closer to a WTP for
child health. This method is presented in Chapter 3.
• Discounting a latent health effect: In cases where the latency period is short enough so
that both adults and children experience the health effect, differences may arise in the
discount rate itself. It is possible that parents discount their WTP for their own latent
health effect using a different discount rate than one that they would apply to their WTP
for a child's latent health effect or that adults thinking back to their childhood or
hypothetical grown-up children might apply a different discount rate. Still, there is little
empirical evidence that this is the case and research in this area has only recently begun
(Agee and Crocker, 1996b; Tolley and Fabian, 1999).25
• Discounting benefits to future generations: Finally, while it may be tempting to think
of children as a "future generation" and therefore expand the time issue to incorporate
intergenerational discounting, analysts should remember that, for the purposes of this
Handbook, children have been defined as individuals under the age of 18. As such, their
welfare and preferences are considered in the decisions made for them by their parents. In
addition, the values analysts are interested in are of risk reductions to children in the
current time period, not some distant future. Intergenerational discounting, therefore,
should not be applied to children.26 In the context of a multi-year economic analysis,
however, care should be taken to appropriately project population growth by age group to
properly capture and assess a rule's effect on the exposed child population.
24 However, an analyst on theoretical grounds might justifiably desire a wealth adjustment to any WTP
estimate representing the adult-as-child perspective. Adjusting for future wealth seems to move closer to what a
current child himself would be willing to pay as a competent adult looking back at his childhood.
25 Please see EPA's Guidelines for Preparing Economic Analyses (2000a) fora discussion of discounting
over latency periods.
For more information on the appropriate use of intragenerational and intergenerational discounting,
see Chapter 6, Section 6.3, "Approaches to Social Discounting" in Guidelines for Preparing Economic Analyses
(U.S. EPA, 2000a).
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2.2.2.3 Costs Associated with Illness
The final two factors consist of the costs that are borne due to an illness and are relevant to
transferred COI estimates; although the latter of the two, the value of time, is also relevant to
transferred WTP estimates. Important disparities may exist in the measurable costs of a child's
illness or death as compared with an adult's. These differences are due primarily to differences in
the costs of medical treatment and the opportunity cost of time.
• Medical treatment: Medical treatment costs are likely to differ between adults and
children; however, the direction of the difference is unclear. For some illnesses, children
may be more resilient and may require less recuperation time than adults. On the other
hand, the same illness may require a different course of treatment and, therefore, a
different cost of treatment in children than in adults. Child asthmatics, for instance, are
more likely to use nebulizers to deliver medication to their bronchial passageways than
adult asthmatics who are more likely to use inhalers.27
• Value of time: The value of time lost due to a child's illness will be different than that
associated with the same illness for an adult because of the number of individuals directly
affected by the illness. When an adult is ill, the cost of the time spent recuperating is
generally measured by an estimate of productivity loss. This is often calculated using lost
wages (real or inferred) or other measures of restricted-activity-days or bed-disability-days
(these methods do not work for valuing a child's lost time, see Section 4.2). When a child
falls ill, however, both the child and the caregiver are affected. The productivity loss of
both affected individuals should be included in the valuation estimate of a child's illness.
This double productivity loss is also likely to affect individual's WTP for child health. To
the extent that a caregiver is more likely to be involved when a child is recuperating, the
total value of lost time is likely to be higher for a child's illness than for an adult's.
2.3 Summary and Implications for Benefit Transfer
This chapter has identified two fundamental sources of differences between adult and child health
benefit values - differences in risk and differences in economic valuation. Not only can the
youthfulness of the exposed population affect the level of susceptibility and the response to that
exposure, it also affects the value individuals place on reducing risks to that population.
There are three possible perspectives from which to measure WTP for child health - that of
society, the adult-as-child, and parents. Only the latter two are both practical and legitimate.
Each of the two offers a distinct set of advantages and disadvantages and analysts can legitimately
rely on either for representing children's health values.
7 A more detailed description of the cost-of-illness method for valuing health benefits is provided in
Section 4.2.
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As summarized in Table 2-1, there are eight sources of bias when transferring to child cases
estimates of WTP or COI for adult health effects to child cases. Only one of the eight sources of
bias, expected lifetime wealth, actually suggests a practical method (presented in Chapter 3) for
adjusting adult health values to more closely approximate child values. The other sources of bias
sometimes suggest a likely direction of difference between child and adult values. Until better
estimates become available, benefit-cost analyses of regulations affecting children can incorporate
this information in two ways. First, transferred adult benefit values can be quantitatively adjusted
to reflect that children have higher expected lifetime wealth. Second, analysts can write careful
qualitative descriptions of the likely over- or under-valuation of reduced child risk resulting from
the transfer of risk values estimated for adults to children.
The results discussed above suggest it may be likely that VSCL is higher than that for adults.
This difference will be compounded in an economic analysis if children are more susceptible to the
risk being studied. The difference will be smaller in cases where the children are less susceptible
to the risk being studied. In short, analysts could introduce error into child health values if they
simply transfer unadjusted values from adults if risk and/or valuation differences exist.
Recommendation (differences between child and adult values): Given the likely differences
between adult and child values and the paucity of available age-specific value estimates for
health outcomes, analysts would do well to qualitatively describe the likely over- or under-
valuation of reduced child risk resulting from the transfer of risk values estimated for adults to
children. Analysts may wish to undertake the quantitative adjustment suggested by the
discussion of expected lifetime wealth. Directions for this adjustment are given in Chapter 3.
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3. Benefit Transfer28
The benefit transfer approach to valuation relies upon existing data, rather than on primary data
collection efforts, to estimate willingness to pay for risk reductions and other benefits of EPA
rules and policies. EPA typically relies upon benefit transfer because conducting original research
is often prohibitively time-consuming and expensive. For more specific information on how to
conduct appropriate benefit transfer and deal with difficult analytic issues embedded in
transferring benefits, analysts are encouraged to refer to the Guidelines for Preparing Economic
Analyses (U.S. EPA, 2000a).29
This section of the Handbook describes analytical considerations when conducting a benefit
transfer for children's health effects. Because the empirical literature on child-specific valuation is
relatively thin, the recommendations in this section generally assume analysts will be transferring
from studies that have estimated adult willingness to pay to reduce their own risk. This section,
however, does contain some notes on benefit transfer based on child-specific estimates. As
primary research on valuing children's health effects expands, analysts will become increasingly
able to draw upon such studies in their analysis, and the Handbook will be updated accordingly.30
3.1 Benefit Transfer Technique and Children's Health Valuation
As suggested in Chapter 2, there are many aspects of children's health values that differ from
those of adults. Transferring adult risk reduction value estimates to children generally will not be
a straightforward process. Critical considerations of children's health issues must enter into the
benefit transfer steps illustrated in Table 3-1.31
This chapter is in part based on information presented in Markowski, 1999.
Specifically, please see Chapter 7, Section 7.5.4, "Benefit Transfer" in Guidelines for Preparing
Economic Analyses (U.S. EPA, 2000a).
30 Dockins et al. (2002), Neumann and Greenwood (1999), and Dickie and Nestor (1998) describe
existing studies that provide estimates of child-oriented values related to mortality, childhood cancers, chronic
effects, acute effects, prenatal exposure effects, and reproductive effects. These papers identify relatively few
(approximately 20) existing studies of child-oriented values. See Appendix A for a summary of these studies.
As mentioned, more information on the benefit transfer approach in general can be found in Chapter 7,
Section 7.5.4 in EPA's Guidelines for Preparing Economic Analyses (U.S. EPA, 2000a). In addition, general
information on transferring benefit estimates is contained in EPA's Handbook for Non-Cancer Health Effects
Valuation (U.S. EPA, 2000b); a special issue of Water Resources Research dedicated to the topic (1992, volume
28, number 3); Desvousges, Johnson, and Banzhaf (1998); and the proceedings of the 1992 AERE workshop (U.S.
EPA, 1993). While not particular to children, Desvousges, Johnson, and Banzhaf (1998) presents a well-
developed case study that analyzes electricity generation and Kask and Shogren (1993) develop the approach for
surface water contamination.
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Analysts should note that the final step in Table 3-1 is somewhat different from that in the
Guidelines for Preparing Economic Analyses (U.S. EPA, 2000a). In addition to characterizing
the uncertainty in the resulting estimate, analysts are directed to qualitatively evaluate the
differences between the study and policy cases that result from systematic, unquantifiable
differences between valuing risk reductions for children and doing so for adults. Particular
attention should be given to factors outlined in Table 2-1 and discussed in Chapter 2.
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October 2003
Table 3-1. Steps in the Benefit Transfer Process
Benefit Transfer Step
Step 1:
Selected Factors to Consider
Describe the Policy Case
• Health effect measurement
• Health effect characteristics
• Impacts on well-being
• Population characteristics
Step 2:
Definition of the physical effect.
Definition of the welfare effect measurement (e.g., restricted activity
days).
Probability of occurrence.
Frequency, duration, and severity.
Defensive behaviors.
Single vs. multiple symptoms.
Latency or lagged effects.
Exclusion of lost school time.
Caregiver disutility due to child pain and suffering.
Caregiver foregone earnings.
Child caregiver foregone future earnings.
Socioeconomic variables, including age, income, baseline health
level, and education level.
Assess the Suitability of Existing Studies
• Study quality
• Study similarity
Step 3:
Use of best research practices.
Peer review and acceptance in the scientific community.
Consistency with other studies.
Consistency with theoretical expectations.
Differences in policy and study case populations.
Differences in health effect characteristics and severity levels.
Transfer the Estimates
• Point estimate approach
• Benefit function transfer
• Other techniques
• Lifetime wealth adjustment
Step 4:
Point estimates for scoping or screening.
Equivalence of parameter estimates for adults and children in benefit
function transfer.
Ability of the approach to capture household level decisions and
capture factors noted above.
Suggests a practical method for adjusting an adult value to bring
closer to a value for a child.
Evaluate Qualitatively and Characterize Uncertainty
it
Qualitatively discuss differences between study and policy cases for
which quantitative adjustments are not feasible.
Characterize and quantify overall uncertainty, noting major sources
from the policy case, the study case, and the benefit transfer process.
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Each of the steps in the benefit transfer process is discussed in detail below, focusing on the
transfer of adult values to children.
3.1.1 Step 1: Describe the Policy Case
The first step in conducting a benefit transfer is to describe carefully the policy case. This
includes a description of:
• How the health effects of the policy are defined and measured, including an assessment of
the magnitude of the risk change;
• The characteristics of the health effect likely to influence the valuation measure used;
• How a change in the health effect will affect well-being; and
• The population experiencing the change in the health effect.
Several considerations specifically related to children arise in each step of describing the policy
case.
3.1.1.1 Health Effect Measurement
It is important to detail how health effects are defined and measured, and to consider how this
might differ between adult and child populations. Two key questions to address are:
• How are the physical and welfare effects defined? The physical effect described in the
risk assessment must have an impact on welfare for it to have economic value. Analysts
should carefully define this physical effect in order to ensure that it is economically
meaningful. Adults and children may experience the same physical effect from
environmental contamination, but suffer different welfare impacts. For example, elevated
blood lead levels in children (a physical effect) lead to cognitive impairments, while
elevated levels in adults appear to be associated with hypertension, kidney problems, and
other health problems. It is important to carefully define the welfare impact that will serve
as a basis of comparison with adult effects from possible policy studies.
• How is the welfare effect measured? Welfare effects - the result of the physical effect -
may reflect a health effect alone, such as an asthma attack, or a behavioral response as
well, such as a day of work loss. Measures described by a behavioral response assume
some action on the part of those affected by the policy. The behavior assumed should be
made clear so that the analyst can later assess how it compares to what was captured in
candidate policy studies, and whether the action is reasonable for child populations as
well.
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3.1.1.2 Health Effect Characteristics
The valuation measure under the policy scenario maybe affected by health effect characteristics,
including:
• Probability, or risk, with which the health effect is likely to occur. Under reasonable
theoretical conditions willingness to pay for small reductions in health risks is linear in the
magnitude of the risk (Shepard and Zeckhauser, 1982; Cropper and Sussman, 1990). The
upshot of this finding is that for small health risks and risk changes, analysts can apply a
per unit value for reduced risk. However, large risk changes may not be consistent with
the linearity assumption and may require adjustments to be made if they are markedly
different in size from those in candidate policy studies.
• Baseline level and policy-induced change in the frequency, severity, and duration of
the health effects. All of these dimensions should be detailed because children may
experience a given health effect more or less often than adults and at a higher or lower
level of severity. Each health effect must be considered individually. Improvements in
environmental conditions may have differential effects on baseline values for children and
adults.
• Availability of defensive behaviors to easily avoid or relieve the health effect. Adults
and children may not face the same set of available opportunities to avoid or mitigate
health effects. The analyst will need to catalog the behaviors available to children in the
policy situation so that they can be compared later to any adult behaviors present in
candidate study cases.
• Nature of the health effect as occurring in isolation or with other symptoms.
Depending on the specific health effect, adults and children may tend to have particular
symptoms grouped with other symptoms. These groupings may be different for adults and
children. Because the value of eliminating a symptom in isolation may be valued more or
less highly than a symptom occurring in conjunction with others, analysts will need to
carefully define any relevant groupings for later comparison with candidate studies.
• Existence of a latency period associated with the health effect. Reduced risks of
delayed effects are generally valued less than reduced risk of an immediate effect. Where
there is a distinction between latency periods in adults and children, analysts should gather
this information. Currently there are relatively few empirical estimates of any kind that
include the latency associated with health effects, but any differences between adult and
child latency can be expected to have a significant impact on value.
3.1.1.3 Impacts on Weil-Being
Individual health effects often have identifiable sets of impacts on well-being. A given illness, for
example, may lead to pain and suffering, increased medical expenses, and work loss. Analysts will
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need to categorize these health-related impacts on children's well-being for later comparison with
the effects in original studies. While welfare effects on children have not been systematically
explored, there are some outcomes that may be common to many childhood illnesses. In addition
to direct consequences such as a child's pain and suffering, childhood illnesses may lead to lost
earnings of caregivers who are responsible for taking the child for medical care. Additional
welfare impacts may include caregiver disutility from witnessing a child's pain and suffering,
reduced human capital for the child due to lost school time, and increased averting expenditures.
In the case of a minor illness, the effects of lost school time on human capital may be negligible or
reversible; however, for chronic illnesses these effects could be significant.
3.1.1.4 Population Characteristics
A complete description of the policy case includes a discussion of the demographic characteristics
likely to affect the valuation measure such as income, age, education, health status, and other
socioeconomic variables. In the case of children's health, this description will generally need to
include the characteristics of the adult caregivers and of the children affected by the policy. Data
such as caregiver's income, education level, ethnicity, and immigrant status are necessary because
these adult characteristics may affect the degree and type of mitigation, the caregivers' knowledge
concerning the health effect, and the accuracy of the caregivers' perceptions of the risks to the
child. Characteristics of the affected children, including education level and age, can also be
expected to influence the valuation measure and should be included in the policy case description.
All of this information will also be necessary in assessing the suitability of existing studies for
transfer to the policy case.
3.1.2 Step 2: Assess the Suitability of Existing Studies
Two major issues involved in reviewing existing studies for relevance to the policy case concern
the quality of the existing studies and their similarity to the new policy situation. Study quality
refers to the soundness of the research methodology employed and the reliability and precision of
the estimates obtained. Study similarity refers to the match between the study case (the situation
examined in the original study) and the policy case (the situation relevant to the new policy).32
Because child- and adult-oriented value determinants differ, any particular study that is suitable
for an adult policy case may not be for a children's policy case.
3.1.2.1 Study Quality
A useful general reference for study quality can be found in the discussion of analytic methods in
Chapter 7 of the Guidelines for Preparing Economic Analyses (U.S. EPA, 2000a). The
discussion of each benefit estimation method concludes with a section titled "Considerations in
A summary of the criteria for evaluating the quality and similarity of existing studies in general can be
found in Desvousges, Johnson, and Banzhaf (1998).
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Evaluating and Understanding" studies using the method. For the case of children's health,
questions to consider when evaluating the quality of a study for use in a benefit transfer include:
• Does the study employ the "best research practices" for estimating health values?
Indicators of study quality generally depend on the method used. When the study case
does estimate the value of children's effects, analysts can use the information Chapter 4
provides on existing estimation methods and their applicability to children's health33.
Currently, the "best research practices" for estimating health values for children are largely
undefined, although these practices are relatively well-defined for studies targeting adult
effects. Section 7.5 of the Guidelines for Preparing Economic Analysis summarizes many
best practice considerations for a number of stated and revealed preference methods.
Particularly useful may be subsections titled "Considerations in Evaluating and
Understanding..." under each type of benefit valuation method described.
• Has the study been published in a peer-reviewed journal, and is it currently being
cited by the professional community? Publication in a peer-reviewed journal is an
excellent first check on study quality. However, even peer-reviewed, published studies
may become dated and analysts will need to assess the study's current standing in the
economic literature. The relative novelty of valuation studies focused on children's health
suggests that analysts may find useful studies in the "gray literature" and so may need to
seek the opinion of external experts on the quality of such studies.34
• Are the study results consistent with results from other studies? If the study's focus
is on children's health risks then there may be few similar studies for comparison, but it is
useful to consider how the study compares with adult-oriented studies and/or studies that
deal with comparable but not equivalent endpoints, particularly those employing the same
analytical approach. In making the comparison, analysts will need to pay particular
attention to the extent to which the candidate study addressed many of the same factors as
other studies. For example, did a wage-risk or consumer product study consider all health
endpoints associated with job accidents or mitigated by use of the product, respectively?
• Do the study results conform with theoretical expectations? In all cases, analysts
should take care to ensure that studies used in benefit transfer conform to the theoretical
expectations of the authors and to well-developed theoretical expectations in the
economics literature. Often studies that are focusing primarily on theoretical or
methodological issues will include a comment by the authors on the appropriateness of the
study for policy analysis.
EPA's Guidelines for Preparing Economic Analyses (2000a) provides information on assessing the
quality of studies for benefit transfer.
"Gray literature" may inc
unpublished manuscripts and reports.
"Gray literature" may include working papers, papers presented at conferences, dissertations, theses,
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3.1.2.2 Study Similarity
For any type of health-related benefit transfer, similarity can be assessed by comparing the study
case with the policy case regarding the way in which the health effects are measured, the impacts
on well-being, and the affected population. Elements to consider when assessing the
comparability of the study case to the policy case include:
• How similar are the study and policy case populations? Similarity should be assessed
for both adults and children from both the policy and study cases. The caregivers' age,
income, location, number of children, and the relative prices they face for goods and
services may influence decisions caregivers make about children's health. Key elements
for the children that may influence the decisions of their caregivers include the child's age
and health status.
• Is the physical effect in the policy case equivalent to that being valued in the study
case? As noted earlier, there may fundamental health effect differences (physical
responses) that may exist between adults and children. For example, because elevated
lead blood levels affect adults and children differently, an adult WTP estimate for reduced
blood lead burden would not be a useful study case for estimating the same value in
children.
• How does the welfare measure in the case study compare to that in the policy case?
Comparability of welfare measures between a study case and a policy case may not be as
straight-forward as it appears initially. A "work loss day," for example, may still be
appropriate to the value of a children's health effect because caregivers may have to miss
work to care for a sick child. But the degree to which parents miss as much work when
their child is sick as they do when they are sick themselves may differ according to the
health effect in question. A "work loss day" may also fail to reflect effects that children
experience (e.g., missed school).
• Are the policy and study cases broadly similar in their baseline risk levels and the
change in risks? While WTP for risk reductions is expected to vary according to the
baseline level of risk, the effect will not be large for most of the risks subject of EPA
policies. WTP is generally expected to be proportional to the risk change. This means
that analysts will usually only need to confirm that the policy cases and study cases are
roughly similar in baseline and marginal risk. If the baseline risk levels of the policy and
case studies differ greatly, analysts would need to use a benefit transfer function to infer
how WTP would also differ.
• Are the policy and study cases similar in the severity of the effects? Even if the basic
physical effect is the same in policy and study cases, the same health effect in adults and
children may differ in frequency, duration, or other measures of severity. As a result, the
analyst must be sure to investigate the potential differences in physical effects from
contaminant exposure between children and adults for each policy case. Because children
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have longer expected lives than adults they may experience a chronic health effect for a
longer duration than an adult. This is a particularly important consideration when an
illness leads to significant and long-term indirect effects (e.g., educational attainment
impacts).
• Are the policy and study cases similar in the averting behaviors available to those
affected? In children's health valuation, it is important to consider how risk enters into
the caregiver's decision process, and how that decision process compares with the model
described and estimated in the existing studies. For example, analysts must consider
whether the study case accounts for caregiver actions to reduce risk (i.e., an averting
behavior) and to lessen the effect on the child (i.e., a mitigating behavior), and then
determine the extent to which the same or similar measures can be expected in the policy
case. Averting behavior may be more difficult to fully describe with children's versus
adults' health values. The caregiver may try to control the child's behavior in an effort to
avoid or relieve a given health effect, and the child may or may not respond to this
intervention. In addition, caregiver behavior or intervention may not accurately reflect
child health values if the caregiver is unaware of the risks to the child's health or does not
perceive the health risks accurately.
3.1.3 Step 3: Transfer the Estimates
In any benefit transfer, transferring estimates involves adjusting and applying (and, in some cases,
combining) estimates from the appropriate study case(s) to the policy case, aggregating benefits
to the relevant population, and considering the uncertainties and limitations of the procedure.
There are three general transfer approaches: (1) the point estimate approach, (2) the benefit
function transfer approach, and (3) meta-analytic techniques. Meta-analytic techniques are
appropriate when multiple studies are available. As child-oriented studies are relatively scarce,
and it is often the case that multiple studies dealing with the same health endpoints in adults are
not available (asthma may be an exception), meta-analytic techniques are not discussed here at
this time.35 The remainder of this section discusses the applicability of the point estimate and
benefit function transfer approaches in the context of a transfer from an adult to a child.
3.1.3.1 Point Estimate Approach
The point estimate approach is most appropriate for scoping and screening analyses. It is rare
that a policy case and study case will be identical when considering children's health values.
Analysts may adjust point estimates based on judged differences between the study and the policy
cases (e.g., growth in income over time or duration of illness). When transferring adult health
Interested analysts should see Desvousges, Johnson, and Banzhaf (1998) for an excellent discussion of
meta-analysis. Desvousges, Johnson, and Banzhaf also describes benefit transfer using Bayesian techniques.
Another emerging benefit transfer alternative is "preference calibration," which uses available benefit measures to
estimate a preference function and transfers estimates from that function. While this technique is relatively new, it
has some advantages over other approaches (Smith, Van Houtven, and Pattanayak, 1999).
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values for children, these adjustments should also account for known differences in the
determinants of values that may exist for adults and children (see Table 2.1 for a summary of
suspected differences). The rationale for these adjustments should be stated explicitly and clearly
in the analysis.
3.1.3.2 Benefit Function Transfer
Benefit function transfer is a richer, but more complex approach for transferring value estimates
from adults to children. If a study case provides a willingness-to-pay function and relevant data
from the policy case are available, valuation estimates can be updated by substituting applicable
values of key variables, such as baseline risk and population characteristics (e.g., mean or median
income, racial or age distribution) from the policy case into the benefit function.
The relevant factor to consider in transferring adult values to the case of children's health is
whether the characteristics of the policy case (i.e., characteristics specific to children) are
significantly different from the characteristics of the adult study sample. The validity of
transferring a benefit function relies, in part, on the equality of the coefficients of the study case
with those of the policy case (if such a function were to exist to describe the policy case) (Loomis,
1992).36 In this case, the existing parameter estimates of the adult-oriented valuation model
would only be peripherally useful for valuing children's health effects. Crucial valuation elements,
such as intertemporal effects, duration, and altruism, may play a significant role in children's
health values that may not be represented in existing models of adult valuation. As a result, the
child-specific factors omitted from the adult-oriented model have the effect of biasing the
estimated coefficients for purposes of benefit transfer (see Table 2.1).
3.1.3.3 Lifetime Wealth Adjustment
To the extent possible, analysts should consider adjusting adult WTP estimates to account for a
child's greater expected lifetime wealth as part of the benefit transfer exercise. Chapter 2
describes the underlying theoretical basis for this adjustment, noting that it is independent of the
choice of perspective for the analysis.
The growth in expected lifetime wealth suggests a practical method for adjusting an adult value to
bring it closer to a value for a child. This adjustment would only be appropriate when transferring
existing adult value estimates to children, and should not be used for study cases of parental
values for children. The latter might already include consideration of higher expected lifetime
wealth for children.
In some cases, benefit function transfer has been shown to be unreliable (Kirchhoff, Colby, and
LaFrance, 1997; Downing and Ozuna, 1996).
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The following equation relates a present adult's WTP for risk reduction to a future adult's WTP.
WTP(/) = [(l+g)e ]*WTP(p)
where WTP(.) is adult WTP for a risk reduction to self;
fandp designate the future and present generations, respectively;
g is the total growth in future generation's income relative to present generation; 37 and
e is the income elasticity of WTP for risk reductions.38
Applying this equation to adult values would produce estimates that are more appropriate for
transfer from adults to children in the context of an economics analysis involving health risks to
children.
Box 3.1. Examples of Adjustments to WTP to Account for Growth in Expected Lifetime Wealth
Three examples of the expected lifetime wealth adjustments are presented below. In each, we assume that
WTP(p) = $l and g = 0.56;
Depending on the value assumed for the income elasticity of WTP for risk reductions, WTP(/) varies from
$1.17 (withe = 0.3) to $1.56 (withe = 1.0). Thus, the range of elasticities currently reported by the economics
literature leads to increases in future WTP ranging between 17 and 56 percent.
Hypothetical Future WTP for Risk Reduction
e WTP(/)
0.3 $1.17
0.7 $1.39
1.0 $1.56
3.1.4 Step 4: Evaluate Qualitatively and Characterize Uncertainty
The latter sections of Chapter 2 suggest several factors to consider in adult-to-child benefit
transfers. For each relevant factor, the analyst should discuss whether it is expected to have a
positive or a negative effect on the child values estimated. For example, it is likely that children
diagnosed with asthma will experience the condition for a greater number of years than will be
7 Note that this is the relative difference wealth and not an annual rate of growth. If Yp is the adult's
income and Yc is the child's income, then g=(Yj-Yj)/Yp. The Bureau of Labor Statistics produces projections for
changes in national income over time. These estimates are the best available data for estimating expected
generational differences in lifetime wealth.
This assumes that income elasticity for future generations is the same as the present one. It is not clear
in which direction this assumption may bias results, but it is consistent with the general presumption that the next
generation exhibits preferences that are similar to the current one.
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similarly afflicted adults, assuming the children do not "outgrow" the condition. All else equal,
this suggests that reductions in child risks of asthma will command a greater value than similar
reductions for adults. Regardless of whether point estimates or benefit functions are transferred,
it is unlikely that the analyst will be able to quantitatively account for the differences in willingness
to pay related to this time dimension.
Analysts will also need to characterize overall uncertainty in the resulting transferred estimates,
noting major sources from the policy case, the study case, and the benefit transfer process itself.
In many cases, risk assessments for children's health effects may be more uncertain than those for
adults due to lack of child-specific data.39
3.1.5 Summary
The current practice of using benefit transfer to estimate rough approximations of the monetary
benefits of avoiding adverse health effects appears to be the best strategy that is currently
attainable for children's health values. However, benefit transfers should always be conducted
and interpreted with careful consideration of potential sources of inaccuracy or imprecision. At
the same time, inaccuracy and imprecision must also be weighed against the uncertainty that might
arise in conducting incomplete primary research. In some cases it may be important for some
policy analyses to more accurately estimate children's health values. In cases where the rough
approximations of children's health values indicate that this category of benefits may be a crucial
component in the policy analysis, additional primary research to estimate child-related values may
be prudent.
Recommendation (benefit transfer): With few child health valuation studies available, analysts
may need to rely on transferring adult benefits to children until more information becomes
available. Table 3-1 summarizes the steps an analyst will follow when conducting a benefit
transfer exercise. Because of the factors discussed within Chapter 2, the study case and policy
case will likely have many differences. Therefore, the qualitative discussion of these differences
(Step 4), becomes very important in situations where adult benefits are transferred to children.
In general it is appropriate to account for differences in lifetime earnings when transferring
WTP estimates from adult-based studies to the case of children.
3.2 Applications of Benefit Transfer to Mortality Risks
The value of mortality risk reductions among the general population is generally estimated using
the value of a statistical life (VSL). This measure is an aggregation of the willingness to pay for
See Chapter 5, Section 5.5.1 "Guiding Principles for Uncertainty Analysis" in Guidelines for
Preparing Economic Analyses (U.S. EPA, 2000a) for a general discussion of how to account for uncertainty in
economic analyses.
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small reductions in the chance of dying over the population at risk.40 It can also be viewed as a
simple normalization of WTP for small risk changes. For example, if a person is willing to pay
$600 for a 1/10,000 reduction in the risk of death, then their VSL is $600 divided by 1/10,000 -
or $6 million. However one views their construction, VSL measures are not values for saving a
specific individual's life.
Currently, a relatively large number of such estimates exist, although most are based on adult
populations. The Guidelines for Preparing Economic Analyses (2000a) conclude that there is
not sufficient support in the economics literature for making adjustments to the existing estimates
to account for the impact of age (including children), health status, and many other
socioeconomic characteristics. Therefore, the Guidelines recommend that a central VSL estimate
serve as a default value for all economic analyses dealing with reductions in mortality risks. The
VSL figure was derived for EPA's recent Report to Congress, The Benefits and Costs of the
Clean Air Act, 1970 to 1990 (1997), and is based on a selection of 26 studies estimating the VSL.
These estimates, derived from wage-risk and contingent valuation studies of adult subjects, range
from $0.6 million to $13.5 million with a mean of $5.8 million (in 1997 dollars) per statistical life.
The Guidelines recognize that there are limitations associated with this single point estimate,
recommending that analysts present the limitations associated with use of the central VSL
estimate and that analysts consider sensitivity analyses to address uncertain benefit transfer
factors. Factors for which sensitivity analysis may be appropriate include the age of the affected
population, their baseline health status, their level of risk aversion, and the voluntariness of risk.41
Some of these factors are more relevant than others when transferring adult-based WTP estimates
to children's risk.
3.2.1 Age
All else equal, children can be expected to have a greater number of years ahead of them. This
suggests that reductions in mortality risks to children would be valued more highly than those for
adults.
One measure of the benefits of reduced mortality risk that attempts to account for age is the value
of a statistical life-year. The Benefits and Costs of the Clean Air Act, 1970 to 1990 (U.S. EPA,
1997) developed estimates of the value of a statistical life-year. Here EPA followed the approach
suggested by Moore and Viscusi (1988) in which the value of a statistical life is the number of
expected life years remaining multiplied by the value of one life year. Given that those
represented in the 26 values used to estimate VSL have approximately 35 life years remaining,
two estimates of the value of a statistical life-year were calculated — approximately $166,000
(1997 dollars) (remaining life years not discounted) and approximately $270,000 (1997 dollars)
An extensive discussion of this topic can be found in Chapter 7, Section 7.6.1 "Human Health:
Mortality Risks" in Guidelines for Preparing Economic Analyses (U.S. EPA, 2000a).
Each of these factors has been discussed in Chapter 2.
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(remaining life years discounted at an annual rate of 3 percent). However, the relationship
between the value of risk reductions and expected remaining life years is more complex than the
simple discounted linear relationship assumed by Moore and Viscusi (1988). Current research
does not provide a reliable method for estimating a value of a statistical life-year.
3.2.2 Risk Aversion
The general population is thought to be more risk averse than the average worker considered in
wage-risk studies because workers selected the riskier jobs voluntarily. Parents maybe even
more risk averse when it comes to the safety of children. If this is the case, then labor market-
based VSL estimates will be even less representative of the preferences of parents and more likely
to be underestimates of their willingness to pay to reduce mortality risks to children.
3.2.3 Voluntariness of Risk
It is often thought that job-related risks are undertaken more voluntarily than are environmental
risks, and research suggests that people tend to prefer reducing in voluntary risks over voluntary
ones (Slovic, 1987; Fischhoff et al, 1978; Revesz, 1999).42 At first glance, this issue does not
seem to be particular to children; however, there is no reason to suspect that parental preferences
for reducing in voluntary mortality risks to themselves are the same as their preferences for
reducing such risks to their children. In fact, it may be that parents are willing to pay more to
reduce involuntary mortality risks to their children. If this is the case, it suggests that existing
VSL estimates understate true parental willingness to pay to reduce mortality risks to children.
Recommendation (premature mortality valuation): Because of the paucity of studies, the
current literature on the value of reductions in fatal risks to children does not provide distinct,
defensible VSL estimates for children for use in policy analyses. As such, until more child-
specific research becomes available, the practical alternative appears to be the use of the adult
VSL as a "default" value. However, as stated in the Guidelines, "it is important to recognize
the limitations of a single VSL point estimate and to consider whether any of the factors
discussed" have a significant impact on the benefit estimates. In most cases, it is likely that
there will be several differences, in addition to age, between the base and policy cases. As such,
analysts may wish to "explore where sensitivity analysis can satisfactorily address some " of the
other concerns that arise from the use of a VSL point estimate. As high-quality estimates of the
value of fatal risk reductions to children become available, analysts should begin to incorporate
these estimates into their analyses.
It should be noted that all of these studies are based on adults' preferences for reducing risks.
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4. Valuation Methods
This chapter discusses issues surrounding the methods for estimating child health benefit values.
It discusses the theoretical underpinnings of several valuation techniques. In addition to a
discussion of standard economic valuation techniques that yield willingness-to-pay values, this
chapter presents a discussion of the cost-of-illness approach including human capital approaches.
This chapter identifies particular issues or problems that might arise when estimating children's
health benefits with each of these techniques. This discussion is of particular interest to
researchers who are estimating original health effect values.
4.1 Standard Economic Valuation Techniques
Changes in welfare are the basis for measuring the benefits of a policy. Economists generally
measure changes in welfare by estimating willingness to pay (WTP). In the case of an
environmental policy, WTP is the maximum amount of money an individual would voluntarily
exchange to obtain an improvement (or avoid a decrement) in the environmental effects of
concern.43 The benefits of a policy are the total of each affected individual's WTP for the policy.
When one method alone does not fully capture WTP for improvements in children's health,
analysts may choose to combine valuation techniques to yield more complete benefit estimates.
Prior to selecting a valuation approach, analysts should recognize the advantages and limitations
of each of the available methods.44 This section discusses standard economic valuation techniques
and issues surrounding their application to valuing child health benefits. The three methods
presented here that yield willingness-to-pay values are hedonic models, averting behavior models
(via safety product market models, household production models, and intrahousehold allocation
models), and stated preference methods, including contingent valuation (CV). Researchers have
begun to assess how these methods may be applied to children's health valuation. Recent efforts
include Dockins et al. (2002), Agee and Crocker (1999), and Tolley and Fabian (1999).
Some of the methods listed above yield a value for reduced risk to individual members of a
household while others produce values for reduced risk to the household as a whole. For
instance, some, although not all, averting behavior models can produce value estimates to
individual members of the household. Specifically, safety product models in which specific
See Chapter 7, Section 7.2.1 "Welfare Measures: WTP and WTA Compensation" in Guidelines for
Preparing Economic Analyses (U.S. EPA, 2000a) for a thorough description ofthe meaning of WTP and the
related concept of willingness to accept (WTA).
Explanations of these methods appear in Chapter 7, Section 7.5 "Methods for Benefits Valuation" in
Guidelines for Preparing Economic Analyses (U.S. EPA, 2000a) and can be found in Chapter 3 of EPA's
Handbook for Non-Cancer Health Effects Valuation (U.S. EPA, 2000b). The general merits of these and other
methods are discussed extensively in many texts such as Freeman (1993) and Braden and Kolstad (1991). None of
these sources detail the unique or important considerations associated with estimating values for children's health
effects, however.
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products are purchased for identifiable members of the household can lead to value estimates for
reduced risk to that person (Jenkins, Owens, and Wiggins, 2001). However, household
production models and hedonic models tend to produce willingness-to-pay estimates for reduced
risk to the household. Since estimates are based on household expenditure decisions, it is often
difficult to tease out values for specific family members. Fortunately, these values at least
include the value of improved protection of children. In the future, as these models are applied to
a wider variety of products, separate values for improved children's health may indeed be
possible. In addition, while value estimates derived from stated preference methods can reflect
reduced risk to individuals depending on how the questions are structured, stated preference
methods can also produce estimates of the value of reduced risk to entire households without
separately identifying the portion of value assigned to different household members. The value
obtained will ultimately be determined by the manner in which the questions are framed and the
position of the respondent within the family.
The perspective achieved also differs across methods. As mentioned above, hedonic property
models and averting behavior models generally produce estimates of the value of reduced risk to
entire households. As the decision-makers within a household with children present are parents,
these models yield values from the parental perspective. To the extent that safety products can be
identified that protect a specific individual rather than an entire household, safety product studies
may yield individual estimates of value of statistical life (VSL) from a parental perspective
(Jenkins, Owen, and Wiggins, 2001; Carlin and Sandy, 1991). Stated preference techniques could
be used, however, to elicit values for risk reductions from adults thinking back to their own
childhood.
4.1.1 Hedonic Method
Hedonic wage and property value methods give estimates of consumer willingness to pay to avoid
(or willingness to accept compensation for) a health risk at the margin. These methods are
applied to heterogeneous goods and services, which are differentiated from each other by the
quantity and quality of various attributes, including environmental quality or exposure to
pollutants.
In general, using differences in property values or wages to determine the value of health benefits
from reductions in environmental hazards rests on a variety of strong assumptions. Thus,
empirical implementation of hedonic methods is not always straightforward. The case of
children's health poses additional challenges. First, because young children do not generally work
for wages in our society, hedonic wage models cannot estimate the value of risk reductions to
children. Hedonic property models can potentially yield values of risk reduction that reflect the
value to the household of protecting its children as well as its adult members, although existing
analyses have focused on individual mortality risk valuation (Portney, 1981). In that sense,
hedonic property models include, and do not neglect, the value of health benefits to children.
However, in order to separate out the benefits to children, the value of the environmental hazard's
contribution to child health at a site must be distinguished from the value of its contribution to the
health, amenities, and productivity of the child's caregiver(s). With current methods, making this
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separation will be difficult, if not impossible. At the very least, it requires empirical
implementation of a model of internal household decision-making. Such a model is discussed
further in Section 4.1.3. Hedonic property value models could control for the presence, number,
and age distributions of the household's children as additional "attributes" of the choice scenario,
as a start.45
Hedonic property models focus on the behavior of the individual household and are limited to
private features of protecting children from environmental hazards. The benefits measured accrue
to the household. To the extent that there is a substantial public good component to
improvements in children's health, hedonic property measures will be incomplete.
4.1.2 Averting Behavior Approach
Averting behavior models make use of existing data on risk reducing behaviors and/or actions
taken to mitigate the effects of exposure to a particular risk. For instance, purchase decisions of
products that increase safety can be used as an input in the willingness-to-pay calculation for
reduced risk of death or injury. Examples of mitigating actions include the purchase of additional
health care to alleviate the symptoms associated with a health outcome. Since children are not
considered mature enough to make rational decisions regarding their own health and safety,
analysts must rely on risk reducing behaviors in which parents and caretakers engage on behalf of
their children. Ultimately, the perspective achieved using the averting behavior approach is that of
the parent. Three modeling approaches have been developed that incorporate these decisions -
the household production model, the intrahousehold allocation models, and the safety product
market models.
4.1.2.1 Household Production Model
The household production model assumes that parents have the ability to protect their children
from known hazards. Generally, the model consists of a production function in which parents
combine private commodities either to reduce their child's risk of harm (which may include
fatality) or to enhance their child's general health or safety. Linkages between groups of private
commodities and a non-marketed good provide a means of inferring the value of the good
(Bockstael and Kling, 1988). For example, the value of risk reduction might be inferred from the
demand for a child-protection commodity. Empirically tractable expressions for the demand for
environmental quality have been developed.46
Some researchers have used other models in settings involving housing or product choices, and some
of these models may perform better under some circumstances. Cropper et al. (1993), for example, shows that
random utility models allow more flexibility in including individual characteristics of purchasers relative to
hedonic models. Nonetheless, hedonic models are the most widely used approach in these settings.
46 See, for example, Pollak and Wachter (1975), Bockstael and McConnell (1983; 1993), Maler (1985),
Gerking and Stanley (1986), and Agee and Crocker (1999).
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Typically, values derived from the household production model involve expressions for the
demand for an input that can either be classified as a substitute or a complement to the
environmental service or state in question. These inputs either maybe directly observed (e.g.,
medical care to alleviate sickness) or inferred from other observable behaviors (e.g., the demand
for child health). In both cases, these inputs contain enough information to infer value, but must
be subject to certain restrictions to justify the value on theoretical grounds.
Thus far, two methods have been applied to market data in the literature, both of which are
similar in the initial modeling stage. The first method involves the case of perfect substitutes (also
called pure averting goods), in which two items can replace each other in a health production
technology. For example, a child health ailment, such as a cough, can be alleviated by the
purchase of a medication. Smith (1991) shows that for the case of perfect substitutes, parental
valuation of increased child health (i.e., reducing a child's coughing) can be inferred by estimating
an expression for the demand for the cough suppressant (including the opportunity cost of
parental time to administer it, valued at the parent's wage or opportunity cost of time).
The second method involves inputs that are essential to the production of child health. Bockstael
and McConnell (1983) show that, with or without other inputs, the area under the demand curve
for an essential input will provide an accurate and theoretically sound value for the environmental
commodity. However, if an essential input cannot be identified, but clearly important health
production inputs are observable, then the area under the demand curve for the observable input
represents a lower bound to the parent's true willingness to pay for the child's health state.
Unfortunately, most health technologies are not so simple and cases with perfect substitutes and
essential inputs are the exception rather than the rule. As discussed in Chapter 3, economics
generally sheds light on the ability and willingness of households to substitute one product for
another. However, there are limits to this knowledge and these limits might be pronounced for
behaviors or products connected to children. Researchers may under-specify the full set of
potential behaviors available to parents in the face of changes in environmental quality.
Caregivers must control child activities along an extensive margin (i.e., which behaviors to allow)
and an intensive margin (i.e., what frequency or duration of each behavior to allow). Because it is
relatively more difficult for caregivers to control their children's behavior at the intensive margin
than it is to control the behavior for themselves, they may opt not to allow the behavior at all. If
researchers fail to recognize the potential for changes along the extensive margin, their results
may be biased. These kinds of complexities often make empirical work very difficult.
Currently, there are very few empirical studies that use a household production technique to
assess monetary equivalents of parental benefits of reduced pollution-related health effects in
children.47 Data limitations have probably hampered their development. Researchers need
7 Agee and Crocker (1996a) use expenditures on lead chelation therapy to reveal the values parents place
on reductions in perceived risks to their children's health from exposure to lead sources. Inferences are based on a
household production model in which parents invest in medical treatments and other exposure reducing activities
to reduce their perceived risk of their child developing lead-induced neurological deficits. Similarly, Joyce,
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detailed household level data on parental expenditures, time allocations, commodity prices, and
wage rates, along with environmental quality measures experienced by these same households.
Without these data, few empirical advances can be made in applying the approach more generally.
Finally, analysts should note that, like hedonic models, the household production model is limited
to estimating the value the household places on improvements in their own children's health.
Altruistic values held by others outside of the household will not be captured in these models.
4.1.2.2 Intrahousehold Allocation Models
Intrahousehold allocation models explore relationships among household members and how these
relationships affect the allocation of resources among family members. In models with children
present, parents make decisions that affect each family member. Two forms of the intrahousehold
allocation model exist with the difference being that one assumes parental consensus and the other
does not (Behrman, Pollack, and Taubman, 1995).
In the parental consensus models, parents are assumed to act as if they are maximizing a single
utility function, subject to appropriate constraints (similar to a household production model). The
parents' utility function, however, does not explicitly reflect the preferences of the children but
rather the parents' utility depends on outcomes (or utilities) experienced by their children.
Although children are generally incorporated in these models as passive participants, on occasion
they have been modeled as active, independent decision-makers. In these cases, however, parents
are able to exert their influence on their children's behavior by conditioning certain parental
decisions (e.g., bequests) on their children's actions.
Non-consensus parental preference models, in which the two adult household members are
allowed to disagree, view household behavior as the outcome of either anon-cooperative or a
cooperative game. This model holds considerable promise in understanding the interactions
between parents and children as well as between individual children when there is dissent. To
date, however, non-consensus models have generally been applied to capture the interactions
between husbands and wives and have not been extended to include children.48'49
4.1.2.3 Safety Product Market Models
Safety product market models (also known as consumer market studies) are a third application of
Grossman, and Goldman (1989) develop a health production function in which mothers' decisions regarding
neonatal and prenatal care are modeled.
A theoretical structure does exist for intrahousehold allocation models to determine whether a household
operates with one, two, or more than two decision-making units. If this structure is applied to a household with children
and observable behaviors suggest the presence of more than two decision-making units, then one can conclude that at least
one of the children plays an active role in household decisions (Browning and Chiappori, 1998).
See Mount et al. (2000) for an application of the intrahousehold allocation model.
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averting behavior models that allow estimation of willingness-to-pay values for reduced mortality
risk and reduced morbidity risk. These models combine existing data on consumer purchases of
safety products with assumptions regarding use and maintenance of the products in order to infer
values for health risk reductions. As discussed in the Guidelines for Preparing Economic
Analyses (U.S. EPA, 2000a), the purchase decision (and therefore risk reducing activity) often
occurs as a discrete rather than a continuous action and may lead to underestimation of the value
of the risk reduction to the consumer. Furthermore, to the extent that unobserved costs (e.g.,
equipment maintenance time or time spent using equipment) are not adequately captured, risk
reduction values may be underestimated.
These models can be useful for valuing risk reductions to children only insofar as products can be
identified that reduce these risks. Examples of applications of this approach include Carlin and
Sandy (1991) and Jenkins, Owens, and Wiggins (2001),which examined child safety seats and
bicycle safety helmets respectively.
4.1.3 Stated Preference Methods
Stated preference methods generally rely on surveys to estimate the benefits of a broad range of
environmental improvements. Contingent valuation (CV), the most widely used of these
methods, generally either asks respondents if they would pay (accept) a specified amount for a
described hypothetical commodity or asks for their highest willingness to pay for it (lowest
willingness to accept).50 A few applications of this method to valuing child health risks exist in
the literature.51
In general, a major advantage of stated preference methods is their flexibility. Questions can be
framed to capture aspects of individuals' preferences, including uncertainty about the state of the
world. Furthermore, a good can be alternatively described so as to elicit the importance of
different motives for desiring such a good or service, both at the present time and in the future.
For surveys to provide useful value estimates, the market must be specified and described in
enough detail to allow respondents to understand all of its important dimensions. In the context
of children's health, design of a survey instrument may be difficult. In the event that parental
preferences are sought, it is important to keep in mind that caregivers have often had little direct
experience with environmental hazards to children (e.g., ambient lead prior to the 1980s). They
may even be ignorant of the existence of a hazard and, if not, are uncertain as to how they feel
about the severity and the time pattern of its consequences. Further, CV surveys of children's
health changes might be at particular risk for problems with embedding. That is, respondents
For a good overview of the CV method, see Mitchell and Carson (1989) or Kopp, Pommerehne, and
Schwarz (1997).
See Appendix A for an annotated bibliography of studies that estimate of the value of child health
benefits.
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might interpret the hypothetical commodity more broadly than the researcher intended. Failure to
account for this may lead to biased value estimates (Tolley and Fabian, 1999).
The value of a child's health to society might differ from the value to his or her own parents for a
variety of reasons, including any possible public good aspects. Stated preference methods are
unique in their potential to contribute to our understanding of the value of children's health by
providing an avenue for assessing the values people attach to these possible public good reasons
for protecting children from environmental hazards. However, as noted by Tolley and Fabian
(1999), estimating a value for this component will require careful construction of information
given to respondents.52
The gradual transformation of a child into an adult means that there is an uncertain period,
probably during the teenage years, when researchers may need to consider the child's own
preferences for risk reduction in addition to those of their caregivers.53 Many factors will
influence how quickly a child matures into a rational decision-making consumer, including
physical maturation rate and cultural expectations. Furthermore, maturation may be uneven in
that a child may demonstrate adult behavior and rational thinking for some issues earlier than for
others. Thus, the degree of consumer sovereignty exercised by children might be different for
different risks. When consumer sovereignty exercised by children is high, analysts may, at a
minimum, need to account for how the child's own actions relating to health and health risks
compares to those assumed in caregivers' responses. Also, the dynamics of household allocation
may change as children take greater control of resources and make more independent decisions.
The final alternative is to turn to adult respondents and ask that they value risk changes in their
own childhoods (the adult-as-child perspective described in Chapter 2). This task, however, may
prove to be too cognitively challenging to yield reliable estimates given the length of time
separating the adults from their childhood experiences and the fact that the risk in question has
already occurred.
Examples of stated preference approaches applied to children's health valuation include Liu et al.
(2000) and Viscusi, Magat, and Huber (1987). Both examples employ the parental perspective.
Several practical problems, not unique to children's health, also arise in applying stated preference
methods. For more information, please see U.S. EPA (2000a); Cummings, Brookshire, and Schulze (1986); and
Hanemann (1994).
Davis and Meltzer (2002) review evidence from the health economics literature suggesting that although
parents assessment of their children's quality of life is closer to the child's own than are assessments by health
professionals, there are often significant discrepancies between the caretakers' and child's own rankings. The data
indicate that household composition may affect how parental assessment of their child's health-related quality of
life.
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4.2 An Alternative Approach to WTP: Cost of Illness (COI)
When willingness-to-pay values are not available for a specific health endpoint, analysts will
generally be forced to rely on cost-of-illness estimates to value health benefits. The cost-of-illness
(COI) method estimates the value of a health benefit as the direct savings in the medical costs and
time costs of an illness that result from a reduced occurrence of an illness. Medical costs include
such items as expenditures on diagnosis, treatment, rehabilitation, and accommodation.
Generally, analysts would follow similar steps to estimate the medical cost savings associated with
children's health benefits as they would to estimate adults' health benefits by this method.54 Care
should be taken to use the most up to date estimates of medical costs as possible since rapidly
changing medical technologies could render estimates obsolete in a relatively short period of time.
Analysts should also be aware that differences in medical treatment occur by age in some cases
and COI estimates should reflect these differences when possible.
Under the COI method, it has been noted that the value of reduced illness commonly includes
estimates of the value of time lost to illness. When a child is ill, time is lost by both the caregiver
and the child. For the caregiver, the cost of time of obtaining medical treatments for the child
should be valued either as lost work time (using the caregiver's wage rate) or as lost household
production time (using the caregiver's imputed wage rate). Imputed wage rates are difficult to
estimate and, to the extent that they are disproportionately affected by childhood illnesses, they
introduce additional error into estimates of COI for children.
The child's time lost to sickness also has value, although no direct measure exists for this loss. If
a health effect is serious enough to reduce a child's human capital (e.g., through missed
schooling) or life expectancy, then there are additional costs of time lost due to illness. Under the
COI technique, these would include the (discounted) future losses in labor market earnings,
although these losses are likely to be very small for most minor and acute illnesses. Determining
future earnings requires difficult predictions of the child's educational choices and career path
over the life cycle. In practice, a simplified relationship such as that of IQ and average earnings
may serve as a proxy. Regardless of how values are estimated, these costs of time lost due to
illness introduce additional difficulties in estimating COI values for children's health effects.55 An
application of the cost-of-illness methodology to children appears in Box 4.1.
Note that medical treatment costs associated with a particular illness may vary across age groups. See
the discussion in Section 2.2.2 for more details.
Estimation of parents' foregone earnings due to their child's ill health appears somewhat more
straightforward than that of a child's foregone future earnings. However, because COI estimates focus on output or
production lost, whether market or non-market related, the measure does not capture all the costs a parent or
caregiver incurs with the child's medical and remedial treatments. Utility maximizing behavior implies that
parents will allocate time toward work, childcare, and other household-related activities, including leisure. At the
margin, the value of leisure time equals the value of working time (assuming at the margin, that the time spent at
work itself has no effect on utility). Thus, additional time allocated to care of a sick child, whether it comes from
leisure time or from work time, is generally valued by the wage rate of the individual.
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Box 4.1. The Case of Lead-Based Paint Hazards: An Application of COI Methodology to
Children
Exposure to lead during childhood can result in impaired cognitive functioning and loss of IQ. Recently, U.S.
EPA set standards for lead-based paint hazards to reduce childhood exposure to lead from deteriorating paint
and contaminated soil and dust. Several standards were considered and the benefits of each were presented in
the supporting economic analysis. A brief summary of the analysis appears below.
Because little information is available on society's willingness to pay to avoid cognitive impairment or IQ loss,
analysts focused on three economic consequences of increased blood lead levels that could be valued using COI
techniques. These included decreased expected lifetime earnings, increased educational resources expended,
and costs of increased medical intervention associated with several critical blood lead levels requiring follow-up
monitoring and/or specific medical intervention.
Decreased Expected Lifetime Earnings
To calculate the loss of expected lifetime earnings associated with loss of IQ, analysts first calculated the
average expected earnings stream for an average newborn in 1997. Earnings data by age and education level
were taken from the 1992 Current Population Survey and were adjusted for survival probability and expected
increases in productivity and were then discounted to express the figure in present value terms. The present
value of expected lifetime earnings for the entire population was found to be $366,021.
Effects of a single IQ point loss on expected lifetime earnings were then calculated using a study by Salkever
(1995). Both direct and indirect effects are considered, including the direct effects of IQ on employment and
earnings for employed persons holding years of schooling constant and the indirect effect of IQ on employment
through schooling. The participation-weighted average effect across men and women was calculated as a 2.379
percent reduction in earnings per IQ point loss or $8,708.
The final calculation, however, must also take into account the reduced number of years of education pursued
and the associated expenditures with a loss of IQ. Salkever estimated a 0.1007 reduction in years of education
per IQ point which translates to a reduction in educational expenditures of $554 (1995). After adjusting this
amount for the opportunity cost of lost income while in school, the total decrease in expected lifetime earnings
associated with a single IQ point loss is $8,346.
Increased Educational Resources Expended
Analysts considered two categories of increased educational resource expenditure depending on the level of
impairment suffered by affected children: special education for children with IQs less than 70 and
compensatory education for children with blood lead levels greater than 20 |ig/dL. The total cost of special
education was calculated by multiplying the reduction in the probability a child will have an IQ less than 70 by
the number of children born in a specified year and then by the cost of the special education. Special education
costs were assumed to occur each year between the ages of 7 and 18 and were calculated assuming the child
remained in a regular classroom. Reduced compensatory education benefits were calculated by assuming that
20 percent of the children with blood lead levels greater than 20 |ig/dL received compensatory education for
three years after which no further intervention was necessary. Costs were based on the same costs for special
education.
Costs of Increased Medical Intervention
For this analysis, the costs of increased medical interventions were taken from a CDC report, Preventing Lead
Poisoning in Young Children, which recommends protocols for blood lead screening and medical treatment for
various blood lead levels (1991). Treatment costs were based on medical interventions recommended by the
American Academy of Pediatrics.
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Analysts should be aware that COI estimates do not necessarily capture a value for the pain and
suffering associated with an illness and as a result do not reflect and individual's WTP to reduce
risk. It is important to remember that COI estimates measure ex post costs associated with being
ill rather than a willingness to pay to avoid an illness. In addition, most individuals purchase
health insurance that drives a wedge between the WTP of households and costs charged by health
care providers. Besides not reflecting WTP in its entirety, COI estimates may not even accurately
reflect the costs of treating an illness when estimates are derived from hospital charges. For
instance, hospital administration costs are often rather arbitrarily allocated across different medical
procedures.
There is controversy in the economics literature about whether COI estimates reflect lower
bounds to WTP (Berger et al, 1987; Harrington and Portney, 1987). COI estimates do not
reflect the cost of many effects of disease. They neglect pain and suffering, defensive
expenditures, lost leisure time, and any potential altruistic benefits.56 Available comparisons of
COI and WTP estimates suggest that the difference can be large (Rowe et al., 1995). However,
this difference varies greatly across health effects and individuals. There is no a priori reason to
suspect that the discrepancy is large or small for child health effects.
The COI method has great empirical feasibility. However, it is important to remember that it rests
upon calculations of the medical and time cost savings that would accrue from reduced treatment
of childhood illnesses. It is not a measure of willingness to pay. Nor can COI estimates be
systematically rescaled (e.g., with a multiplier) to approximate willingness to pay values. There
are additional weaknesses to the COI technique when valuing children's health effects, due to the
need to value household production time and a child's expected future earnings. Despite these
and other shortcomings, the COI approach remains widely accepted by many professionals as a
practical method for estimating a lower bound for the value of changes in both child and adult
health status, particularly when alternative methods are not available.
Recommendation (valuation techniques): All of the valuation techniques discussed above are
potentially viable for estimating the value of reduced risk to children. Each is associated with its
own advantages and limitations with respect to children's health valuation. As such, each
technique should be assessed for the particular health effect being valued. In general, hedonic,
averting behavior, and stated preference methods are preferred over COI because they estimate
the WTP for (or willingness to accept (WTA)) reduced risk, and WTP (WTA) gives the
theoretically correct measure of the value of welfare change. At present, however, analysts may
need to rely upon the results of COI studies until empirical estimates from other methods become
available.
For the case of children, defensive expenditures would include parent spending on measures directed at
preventing a child from exposure to a pollutant.
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5. Other Important Types of Analyses
Alternative types of analyses exist that can support benefits valuation. These include cost-
effectiveness analysis, breakeven analysis, bounding analysis, and risk-risk or health-health
analyses. When robust value estimates and/or risk estimates are lacking, which in the short-term
may be the case for children's health valuation, these types of analyses may provide decision-
makers with some useful information. Additionally, given the various sources of divergence
between child and adult values discussed in Chapter 2, analysts should expect that transferring
adult values to children will often result in child benefit estimates that contain substantial error.
Thus, analysts assessing children's health benefits may wish to perform one or more of these
alternative techniques as a sensitivity or supplemental analysis in an effort to provide decision-
makers with as complete a picture as possible of the impacts of a proposed policy or regulation.
However, analysts should remember that because these alternatives do not estimate the net
benefits of a policy or regulation, they fall short of benefit-cost analysis in their ability to identify
an economically efficient policy. This and other short-comings should be discussed when
presenting results from these analyses to decision-makers.
5.1 Cost-Effectiveness Analysis
Cost-effectiveness analysis ranks alternatives by the cost per unit of benefits, where the cost is the
social cost of the policy as would be calculated for a benefit-cost analysis.57 Benefits are generally
expressed in terms of the number of adverse health outcomes avoided, for example, the number of
statistical cases of illness averted or lives saved. However, cost-effectiveness analysis can use any
number of adverse outcomes including, for example, pounds of a pollutant avoided. In terms of
health, the most cost-effective policy alternative is the one with lowest cost per statistical life
saved or the lowest cost per statistical case of illness averted. It should be noted that the most
cost-effective alternative may not be efficient in an economic sense. Therefore, it does not
necessarily point to a social welfare maximizing alternative.
Cost-effectiveness analysis gives more meaningful information when there is only a single health
effect with a missing value. When more than one health effect cannot be valued directly, the
manner in which the effects are weighted is arbitrary. This means that it is not possible to compare
a policy that reduces relatively more expected cancers, but fewer expected cases of kidney failure,
with one that has the opposite relative effects. As alternative tools are developed, a procedure for
assigning non-arbitrary weights to physical outcomes might become generally accepted.
Currently, there is no such procedure.
Even when there is only a single health effect with a missing value, the information provided by
7 A brief explanation of cost-effectiveness analysis is in Chapter 10, Section 10.3.3 "Results from Cost-
Effectiveness Analysis" in Guidelines for Preparing Economic Analyses (U.. S EPA, 2000a). Boardman et al.
(1996) presents an introduction to cost-effectiveness analysis that includes many examples from the medical and
public health literature.
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cost-effectiveness analysis is not easy to interpret if there are important non-monetized non-health
effects. For example, some policies give important non-monetized ecological benefits. In these
cases, dollar estimates of the costs-per-statistical-life-saved neglect the ecological benefits.
Cost-Utility Analysis and Health-related Quality of Life Measures
The fields of public health economics and policy make extensive use of various types of cost-
effectiveness analysis. A form in which the outcome is a utility-weight rather than a health effect
enjoys widespread acceptance. For this reason, these types of cost-effectiveness analyses are
sometimes referred to as cost-utility analysis. These weights are expressed in a variety of
measures that fall under the general heading ofhealth-related-quality-of life, and include quality-
adjusted-life-years (QALYs) and disability-adjusted-life-years (DALYs). QALYs, DALYs, and
other measures may differ greatly from one another in their underlying assumptions and
implications for policy, but they each purport to estimate some measure of utility loss from illness
or death. Because utility is generally focused strictly on health, it is defined more narrowly in this
context than in traditional benefit-cost analysis. Researchers have produced a substantial
theoretical and empirical literature on QALY rankings and their use in these types of cost-
effectiveness analyses. Health-related-quality-of-life measures are currently used by the World
Health Organization, the World Bank, and some federal agencies.
Like more general cost-effectiveness analysis, cost-utility analysis cannot evaluate the efficiency of
policy alternatives in the same manner as benefit-cost analysis. Instead, cost-utility analysis ranks
alternatives according to which gives the greatest "bang for the buck" In the case of an analysis
using QALYs, the preferred alternative would be that with the lowest dollar per QALY ratio.
This alternative is not necessarily the one that provides the greatest net benefit as defined in a
benefit-cost analysis.
Cost-effectiveness analyses using QALYs, DALYs or other utility measures face many of the
same challenges detailed throughout this handbook related to benefit-cost analysis. For example,
because QALY weights are elicited from surveys researchers must confront the issue of who
should assess children's quality of life under health impairments in much the same way as
contingent valuation surveys. A useful, recent reference looking at this and other issues in the use
of QALYs for children's health is Davis and Meltzer (2002). The most widely cited general
reference for these types of cost-effectiveness analyses is Cost-Effectiveness in Health and
Medicine (Gold et al., 1996). This book describes the roles and limitations of cost-effectiveness
analysis, provides background on its theoretical basis, and offers recommendations on various
practical considerations.
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5.2 Breakeven Analysis
Breakeven analysis is another alternative that can be used when either risk data or valuation data
are lacking.58 Analysts who have per unit estimates of economic value but lack risk estimates,
cannot quantify net benefits. They may, however, estimate the number of cases (each valued at
the per unit value estimate) at which overall net benefits become positive, or where the policy
action will break even.59 For example, consider a proposed policy that is expected to reduce the
number of cases of Respiratory Syncytial Virus (RSV) with an associated cost estimate of $1
million. Further, suppose that the analyst estimates that willingness to pay to avoid a case of a
RSV is $200 but that because of limitations in risk data, it is not possible to generate an estimate
of the number of cases of RSV reduced by the policy. In this case, the proposed policy would
need to reduce the number of cases by 5,000 in order to "breakeven." This estimate can then be
assessed for plausibility either quantitatively or qualitatively. Policy makers will need to
determine if the breakeven value is acceptable or reasonable.
The same sort of analysis may be performed when analysts lack valuation estimates, producing a
breakeven value that should again be assessed for credibility and plausibility. Continuing with the
example above, suppose the analyst estimates that the proposed policy would reduce the number
of cases of RSV by 5,000 but does not have an estimate of willingness to pay to avoid a case of
RSV. In this case, the policy can be considered to "breakeven" if willingness to pay is at least
$200.
One way to assess the credibility of economic breakeven values is to compare them to risk values
for effects that are more or less severe than the health endpoint being evaluated. For the
breakeven value to be plausible, it should fall between the estimates for these more and less severe
effects. For the example above, if the estimate of willingness to pay to avoid a case of a more
serious health effect was only $100, the above "breakeven" point may not be considered plausible.
Breakeven analysis is most effective when there is only one missing value in the analysis. For
example, if an analyst is missing risk estimates for two different health effects (but has valuation
estimates for both), then they will need to consider a "breakeven frontier" that allows the number
of both health effects to vary. It is possible to construct such a frontier, but it is difficult to
determine which points on the frontier are relevant for policy analysis.
Boardman et al. (1996) describes determining breakeven points under the general subject of sensitivity
analysis and includes empirical examples.
OMB (1996) refers to such values as "switch points" in its discussion of sensitivity analysis.
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5.3 Bounding Analysis
Bounding analysis can help when analysts lack value estimates for a particular endpoint. As
suggested above, reducing the risk of health effects that are more severe and of longer duration
should be valued more highly than those that are less severe and of shorter duration, all else equal.
If robust valuation estimates are available for effects that are unambiguously "worse" and others
that are unambiguously "not as bad," then one can use these estimates as the upper and lower
bounds on the value of the effect of concern. Presenting alternative benefit estimates based on
each of these bounds can provide valuable information to policy makers. If the sign of the net
benefit estimate is positive across this range then analysts can have some confidence that the
program is welfare enhancing. It is worth pointing out that for children's health effects,
determining appropriate bounding values may be difficult, especially if only adult risk reduction
valuations are available. Analysts should carefully describe judgments or assumptions made in
selecting appropriate bounding values.
5.4 Risk-Risk and Health-Health Analyses
Risk-risk and health-health analyses do not require benefits or costs to be monetized. A risk-risk
analysis enumerates the risks that are reduced and those that are inadvertently increased by a
government policy. For example, a policy that requires installation of scrubbers at coal-fired
electric generating plants, will reduce health risks from air pollution but will also present risks to
the construction crews installing the scrubbers. In risk-risk analysis, both the desirable and
undesirable risk changes are denominated in physical, and not dollar, terms, although each could
be denominated in different physical units. This type of analysis is most useful when policy
options are very restricted as it usually cannot provide a clear ranking of policies.
The implementation of health-health analysis, in practice, has been restricted to cases of mortality
risk reduction.60 In this application, health-health analysis evaluates policies by comparing the
number of deaths prevented by a government policy with the number of deaths induced by
transferring income from individuals to the government in order to finance the policy. Generally,
government programs, even those that directly serve public health, have to be financed. Money
for those programs has to come from individuals; thus, paying for programs reduces individuals'
ability to purchase risk reduction privately.
In principle, health-health analysis could include the detrimental effects of loss of income on
morbidity, however, this would require aggregating health effects using quality adjusted life
years61 or some alternative, common metric. In current applications focused on mortality risks,
Kuchler and Golan (1999) and Perkins (1998) provide reviews of existing health-health studies.
While QALYs have been widely used in evaluating the cost-effectiveness of medical interventions and
in some other policy contexts, methods involving their use have not yet been fully amalgamated into the welfare
economic literature on risk valuation.
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health-health analysis fails to consider non-fatal health effects and other welfare effects of
policies.62 If these other effects are expected to be significant, then this type of analysis can be
misleading. For example, consider an expensive regulation that results in no reduction in
fatalities, but a large reduction in childhood developmental impairment. In this case, the number of
deaths prevented is zero, while the number induced due to diverting money from the private
sector and hence reducing spending on safety goods is likely to be positive. Health-health analysis
seems most usefhl as a screening tool for policies with insubstantial non-fatal health and welfare
effects.
5.5 Summary
The techniques discussed, especially cost-effectiveness, breakeven, and health-health analyses, are
most useful when there is only a single non-monetized benefit category. (For health-health
analysis, the category must be mortality risk.) Most EPA policies generate multiple benefits, many
of which are difficult to monetize. In such cases, analysts can determine if a single non-monetized
benefit stands out as potentially the most significant—statistical lives or life years saved are likely
candidates. Applying the above techniques to what analysts judge to be the most significant
benefit category can provide useful information. However, care should be taken to remind policy
makers relying on these alternative analyses that there are other, neglected, non-monetized benefit
categories. Despite expectations that these others are less significant, analysts should remember
that they are potentially important to decision-makers. In addition, analysts should remember that
because these alternative types of analyses do not estimate the net benefits of a policy, they fall
short of benefit-cost analysis in their ability to identify an economically efficient policy.
Recommendation (alternative analyses): Despite the fact that the techniques outlined above do
not provide information on net benefits, analysts assessing children's health benefits may wish to
perform one or more of the alternative techniques as a sensitivity or supplemental analysis in an
effort to provide decision-makers with a complete as picture as possible of the impacts of a
proposed policy or regulation. This sort of analysis will be especially important when age-
specific valuation estimates for the health effects of concern are not available. Regardless of the
technique used, care should be taken to discuss the short-comings of the analysis.
Lutter, Morrall, and Viscusi (1999), for example, state the major assumption embodied in their
empirical model is that "the purpose of health expenditures is to reduce mortality, not to reduce morbidity or
provide peace of mind."
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6. Risk Assessment and Economic Analysis63
As noted in Chapter 1, estimation of the health benefits to children will generally involve six steps:
hazard identification, dose-response evaluation, exposure assessment, risk characterization,
welfare effect quantification, and valuation of the welfare effect. This Handbook focuses on
issues directly relating to the valuation of changes in risks to children's health and, as such, is on
the final two steps of this process. Previous chapters provide in depth discussion on issues
relating to these two steps; however, in order to quantify the health benefits of environmental
policies, economists generally require estimates of the type and number of cases of illness
reduced. The development of such estimates involves the first four of the steps noted above and
generally falls to risk assessors. Historically, economists and risk assessors have had little
meaningful interaction regarding these six steps. However, in order for useful information on
quantifiable and monetizable physical effects be developed, it is essential that risk assessors and
economists work together as a team to complete all of the procedures presented. This type of
collaboration should yield health outcomes that are specified in a way that is useful for subsequent
economic valuation.
6.1 Communication Between Risk Assessors and Economists
Risk analysts and economists must communicate clearly if the risk assessment process is to
produce useful estimates of physical benefits.64 In the case of child-specific risks and benefits,
clear communication may be even more important. Risk analysts and economists have generally
had more experience working together assessing the effects of policies that alter risks to adults
than those specific for children. New risk assessment and economic models are being developed
for children and changes in both fields may occur rapidly. Unless clear and continuing
communication exists among all analysts involved in assessing policies addressing children's
health, developments might not be as productive as they would otherwise be.
The uncertainties surrounding estimates of risk and economic value may be greater for children's
health effects. Assumptions used in assessing adult health risks may not be applicable for
children's health effects (e.g., small children spend a lot of time on the ground or floor and put
everything in their mouth - they therefore have a much higher exposure to lead and other
pollutants found in dust and dirt). To perform a sound analysis of benefits, economists will need
to know if new assumptions change the basic nature of the risk characterization. Economists and
risk assessors both bear responsibility for sharing information about assumptions made. The
interfaces between risk assessment and benefit analysis are dependent on the scope and methods
63
64
This chapter is based in part on information presented in Thompson (1999).
Chapter 7, Section 7.3 "The Benefits Analysis Process" in Guidelines for Preparing Economic
Analyses (U.S. EPA, 2000a) emphasizes that communication must begin early in the process of benefits analysis
and should continue throughout the development of the analysis. A more formal discussion of the importance of
communication between risk assessors and economists can also be found in Shogren and Crocker (1999).
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of the underlying research. Risk assessments based on animal toxicological studies may require
dialogue between risk assessors and economists at more steps in the analytical process than
econometric studies where the health risks are endogenized. For example, an econometric study
may examine what effect a change in drinking water quality has on a certain health outcome. By
construction, the econometric study incorporates decisions consumers make about bottled water
usage into the model, so human behavior is determined within the model. In contrast, using an
animal toxicological study requires the analyst to construct a chain of events. For example,
suppose a pollutant found to cause a health effect in animals is expected to cause the same effect
in humans. The dose-response function estimated for animals for this particular pollutant is
extrapolated to humans with appropriate adjustments. However, in order to estimate the human
health outcome associated with a change in the pollutant level, the analyst must determine what
changes in human behavior may occur (e.g., the pollutant creates a bad taste in drinking water
causing more people to drink bottled water thereby avoiding exposure to the pollutant in
question). Human behavior must be modeled and built into the chain of events.65
Risk assessors should interact with risk managers and economic analysts to discuss what risks will
be assessed (i.e., what information decision-makers care about). Early discussions that jointly
identify the key subpopulations (e.g., adults exposed to a pollutant that exhibits reproductive
toxicity, pregnant women/fetuses, infants, adolescents, etc.) and potential health effects will focus
the risk assessment and help economists plan for valuation. Economists should emphasize to risk
assessors those endpoints that have economic value so that they can be included in the risk
assessment. Early discussions among analysts can identify and circumvent many problems, and
early discussions may also allow enough lead time for economists to collect additional necessary
valuation data.
6.1.1 Economists' Contributions to a Risk Assessment
Economists and risk assessors may possess different types of information about the behavior of
children. Economists can assist risk assessors by providing insights, information, and analysis
concerning behavioral changes in the face of environmental risks that may affect the results of
exposure assessment. For instance, the activity patterns of children and their caregivers may
change due to perceived environmental risks. With increased environmental awareness and
information regarding drinking water, soil, and air quality conditions, perceptions of
environmental risks may change. The result may be increases in some averting or mitigating
behaviors associated with elevated environmental risks. Examples of such behaviors include
increased use of bottled and/or boiled water, increased time spent indoors, and reduced direct
exposure to the sun. Consequently, the expected incidence of adverse health effects may diminish
due to increased averting or mitigating behavior. In such cases, the benefits of reduced health
risks to children should also include the gains from opportunities to reduce averting and
Understanding averting behaviors is important when estimating the benefits of reducing pollution, not
only because such behaviors reduce the population's exposure but also because the need for the averting behaviors
is reduced. When calculating benefits, the value of the reduction in averting behavior is added to the value of
reduced illness.
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mitigating behavior. An effective dialogue between the risk assessors and economists is often the
only way to determine if averting or mitigating behavior should be addressed and, if so, whether
those factors are provided for in the risk assessment.
Economists can also provide insight on which kinds of risk information are most useful for
benefits estimation, most notably in the hazard identification and risk characterization steps of the
risk assessment process. In the hazard identification step, economists should make clear the need
for information on particular health endpoints expected to have economic value. For example,
forced expiratory volume is commonly used as a measure of lung function, but there is little
evidence that small changes are correlated with a willingness to pay for relief. Because relatively
small reductions in forced expiratory volume are not generally perceived as adverse, it is a poor
candidate for economic valuation. While it may be infeasible to monetize these types of effects,
quantifying them can give decision-makers useful information. In the risk characterization step,
economists should discuss with risk assessors the need for information on probabilities and the
distribution of risk in order to develop central and bounding estimates of benefits. Economists
should also discuss with risk assessors how information on point estimates and reference doses
alone may limit an economic analysis of benefits.
6.1.2 Risk Assessors' Contributions to an Economic Analysis
Economists have a great deal to learn from risk assessors. Understanding the activity patterns of
children at risk and their parents is often central to credible valuations of children's health.
Activity patterns of children often vary on a daily, weekly, and seasonal basis. These patterns may
be affected by a number of factors, including variations in the temperature, wind, and
precipitation, regardless of whether information on pollution levels and risks is available.
Assumptions about baseline conditions and their natural variability are addressed either explicitly
or implicitly in any risk assessment. A full understanding of the context for the risk assessment
helps in the design of the benefits analysis.
6.1.3 Interaction Between Risk Assessors and Economists
The impacts of environmental policies and regulations should be assessed using an "interactive
team" approach in which risk assessors and economists work collaboratively rather than
sequentially. Box 6.1 provides a list of questions designed to facilitate dialogue between risk
assessors and economists. This list is not intended to be exhaustive, but rather to suggest a
starting point for communication between risk assessors, economists, and other participants in the
policy process. By discussing these questions specifically and through regular communication,
risk and economic analysts will maximize the usefulness of risk assessment data. Answers to the
questions in Box 6.1 will not always be available. Additionally, other specialists such as public
health professionals, physicians, or industrial engineers are likely to provide more detailed answers
to the questions and their opinions should be sought when appropriate.
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Box 6.1 Discussion Questions to Facilitate Interaction Between Risk Assessors and Economists
1. What are the health outcomes (that will be) characterized?
2. How do the risk estimates support valuation?
3. How many children are expected to experience the outcome(s) without additional action?
4. How many children are expected to experience the outcome(s) with each additional action under
consideration?
5. What risk factors put children particularly at risk?
6. What ages of individuals are exposed?
7. What is known about the susceptibility or sensitivity of the exposed children to the disease?
8. What, if any, trade-offs might be induced by the actions under evaluation?
9. What is the latency period between exposure and disease?
10. Is the disease detectable in children? treatable? reversible?
11. Does the disease alter the child's quality of life because it changes his or her normal growth or
development?
12. What is the magnitude of the uncertainty around the quantitative estimates?
13. What assumptions drive this uncertainty?
Recommendation (interaction between economists and risk assessors): Economists and risk
assessors would do well to coordinate their efforts in an "interactive team " approach rather
than working sequentially. Working together will help ensure that information needs for benefits
estimation are met. Assumptions made collaboratively by both types of analysts should be made
as transparent as possible.66
6.2 Key Components of the Risk Assessment Data
Economists require various types of data to fully assess benefits. Some of these data are provided
as a matter of course throughout the risk assessment process, but others may require further work
on the part of both the economist and the risk assessment analyst, perhaps with the help of
additional professionals. A description of these data is provided below.
• A description of the type of risk estimate. Economists generally need an estimate of the
number of expected adverse health effects avoided as a result of the policy action. Risk
characterizations produce estimates of the health risk associated with a particular
EPA's Guidelines for Preparing Economic Analyses (U.S. EPA, 2000a), Chapter 7, Section 7.3.1 "A
General 'Effect-by-Effect' Approach" outlines steps for risk assessors and economists to ensure that health
outcomes are specified so that they are useful for subsequent economic valuation.
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contaminant. But, the kinds of population risks most useful to economists are not always
available. Some risk characterizations, such as those for cancer, are conducive to
economic valuation because they can be converted into cases of illness. Others are less so,
such as those that focus only on determining whether an individual is exposed above an
acceptable threshold. Furthermore, valuing programs that emphasize individual risk
estimates, rather than population risk, will typically require additional assumptions or data
about the number of exposed individuals in the population in order to estimate social
benefits.
• A description of the changes and timing of changes in ambient concentrations. Risk
assessors might use monitored ambient pollutant concentrations and assume immediate
decreases in those concentrations when estimating changes in relative risk, whereas
economists might be working with modeled pollutant concentrations and/or permit limits
and lagged compliance schedules when estimating economic impacts.
• A description of the exposed population. The economist also ideally needs a
description of the demographic characteristics of the affected population or sub-
population. This description should obviously include the age distribution of the exposed
population.
• A description of the adverse health effect. This description should include a discussion
of severity, duration, latency period (if any), and the percentage of cases that are typically
fatal. Much of this information likely will come from medical professionals.
• A description of uncertainties in the risk assessment. Also of use to the economist is
information about the models used by the risk assessor as well as any assumptions made in
extrapolating from available data. When available, probability distributions that
characterize the uncertainty or variability associated with risk estimates can be extremely
valuable in assessing the uncertainty of the benefit analysis as a whole. This is especially
important for children because the lack of child-specific information may result in
relatively less certain risk estimates. At a minimum, risk analysts should qualitatively
discuss the important sources of uncertainty and, when possible, should quantitatively
demonstrate the impacts of different assumptions on the risk assessment results.67
More information on these issues as they apply to benefit transfer can be found in Chapter 5.
7 A checklist of common assumptions focusing on children and used by risk assessors can be found in
Thompson (1999). When listing assumptions, risk assessors should be as specific as possible so that economists
and others can be fully informed of value judgments and limitations inherent in the analysis (Henry et al., 1992).
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Appendix A
Annotated Bibliography
Twenty published studies were located that provide estimates of child-oriented values related to
mortality, childhood cancers, chronic effects, acute effects, prenatal exposure effects, and
reproductive effects.68 Following are citations and annotations for them, followed by a list of
citations of unpublished, on-going research in the area of children's health valuation.
Published Papers
Agee, M.D. and T.D. Crocker. 1996a. "Parental Altruism and Child Lead Exposure:
Inferences from the Demand for Chelation Therapy." The Journal of Human Resources.
31:677-691.
The authors use a household production model of the demand for chelation therapy to estimate
parental willingness to pay (WTP) for reduced body-lead burdens for (their own) children. The
data were obtained from a sample of 256 households with children attending the first and second
grades between 1975 and 1978 in two Boston area communities. This sample was drawn from a
larger sample interviewed initially during this time period. Body lead burden was determined for
each child using shed teeth. Other relevant information was obtained from a physical examination
of the child and a comprehensive medical and social history completed by the parent. Information
on whether or not chelation therapy was pursued was collected in a follow-up survey conducted
in 1985 together with wage information for the parents.
Parental willingness to pay for reduced child body lead burdens was calculated for parents who
did not choose therapy as well as for those who did choose therapy. As a result, WTP ranged
from $11.18 to $104.39. In addition, they find that aggregate WTP for a one percent reduction in
child lead burden is no less than twice the value of ex post family and social, medical, and
educational outlays saved by avoiding the "ill-omened" state.
Analysts should exercise caution in employing these values in a cost-benefit analysis of reduced
body lead burdens among children. The sample is not necessarily representative of households
across the country because every family possessed medical insurance. Also, the use of the wage
rate of employed mothers as the parental opportunity costs of time is open to criticism.
This appendix is based in part on information presented in Neumann and Greenwood (1999).
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Boyle, M.H., G.W. Torrance, J.C. Sinclair, and S.P. Horwood. 1983. "Economic
Evaluation of Neonatal Intensive Care of Very-Low-Birth-Weight Infants." The New
England Journal of Medicine. 308(22):1330-37.
The authors calculate the direct and indirect lifetime costs of low birth weight. The most relevant
data concerned infants weighing 500 g to 1,499 g at birth and was collected from one county in
Ontario, Canada, from 1973 to 1977. In addition, the authors consulted with physicians to
predict future medical costs and reduced productivity and then developed a health-state index to
create an estimate of lost quality-adjusted life-years.
Estimated costs per live birth through hospital discharge, to age 15, and to death are $14,200,
$20,700, and $100,100, respectively, for 1,000 g to 1,499 g infants.69 For 500 g to 999 g infants,
these costs were $ 13,600, $19,900, and $43,600. Costs per life-year gained and per quality-
adjusted life-year gained are also presented.
Analysts should exercise caution in applying these estimates in a benefit-cost analysis. At present,
the science linking environmental exposure to low birth weight is limited. No estimates are
presented for normal birth weight infants, eliminating the analysts ability to estimate the
incremental cost per birth weight category. Additionally, it is likely that treatment course, length,
and cost have changed, perhaps substantially, since the 1970s.
Carlin, P.S. and R. Sandy. 1991. "Estimating the Implicit Value of a Young Child's Life."
Southern Economic Journal. 58:186-202.
Carlin and Sandy collected data on car seat usage from ten cities in Indiana. At a site for each
city, surveyors, with the help of state troopers, stopped every passing car that carried a child who
appeared to be aged four or under. Data were collected about whether the child was properly
restrained, and drivers were asked to complete a follow-up questionnaire and return it by mail.
Carlin and Sandy combined the following data: drivers' reported wage rates; an estimated $80
price of a car seats in Indiana; an estimated amount of time spent harnessing and unharnessing the
child; and data from the States of Washington and Tennessee on the reduction in the probability
of death faced by a child wearing a car seat. They estimated, in 1985 dollars, a value of statistical
life for a child of $418,597, which they amended to $526,827 by appending the costs of raising a
child.
Analysts should exercise caution in applying these figures to a benefit-cost analysis for several
reasons, one of which is that the data are regional. Secondly, estimates of the value of statistical
life calculated by examining consumer expenditures on averting behaviors are lower bound
estimates. Finally, the values estimated by Carlin and Sandy are for very young children - aged
four or under - and are not intended to represent older children.
Estimates are in 1978 Canadian dollars.
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Dickie, M. and D.V. Nestor. 1999. "Valuation of Environmental Health Effects in
Children: A Survey." Preliminary Draft.
With the aid of a simple formula, Dickie and Nestor use the Joyce, Grossman, and Goldman
(1989) WTP estimates for improved neonatal survival from a 10 percent reduction in sulfur
dioxide, along with estimates of the risk of infant death, to calculate WTP by mothers to avoid
statistical infant deaths. (See the Joyce, Grossman, and Goldman, 1989 annotated bibliographic
entry.) With information on the average number of births, they also calculate the WTP per birth.
Table A-l. Implied Values of Statistical Lives for Infants ($1977)
Race of mother
White
Black
Based on prenatal care
Per mother
$ 27,650
$ 50,955
Per birth
$ 16,265
$22,155
Based on neonatal intensive care
Per mother
$480,915
$ 1,273,360
Per birth
$ 282,890
$ 553,635
The same cautions given for the WTP estimates calculated by the Joyce, Grossman, and Goldman
(1989) apply to the values of statistical life (VSLs) provided by Dickie and Nestor; that is, the
data on which they are based are county-level and not individual-level and thus reflect substantial
aggregation error.
Hoffman, C., D. Rice, and H.Y. Sung. 1996. "Persons with Chronic Conditions: Their
Prevalence and Costs." Journal of the American Medical Association. 276(18): 1473-1479.
Hoffman, Rice, and Sung use the results of two national surveys to estimate the total direct and
indirect costs associated with all chronic conditions. The 1987 National Medical Expenditure
Survey was used to estimate the direct costs associated with chronic conditions, and the 1990
National Health Interview Survey, along with the 1990 Vital Statistics of the United States, was
used to estimate indirect costs, including mortality costs measured by lost expected earnings.
Results for both types of costs are presented by age group, but these age groupings differ by
group due to differences in the underlying data. For persons aged 0-17, direct costs of chronic
conditions in 1987 averaged $22.9 billion (1987 dollars), or $1,843 per chronically ill person in
that age group. Indirect costs were estimated for persons under 25 years, and totaled $13.2
billion (1990 dollars) for 1990. Over $10 billion of this total is due to mortality associated with
chronic conditions. The study also indicates that over one-fourth of children with a chronic
condition have multiple chronic conditions; children with multiple conditions experience more
missed school days, more time spent in bed, and higher costs.
While the study provides insight into the large financial impact of chronic conditions in these age
groups and indicates the importance of considering co-morbidities, it does not provide estimates
that are readily employed in benefit-cost analyses. The estimated costs of mortality are
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particularly ill-suited for use in Agency benefit-cost analysis because the authors focus on ex post
productivity losses rather than ex ante estimates of willingness to pay to reduce risk.
Jenkins, R.R., N. Owens, and L.B. Wiggins. 2001. "Valuing Reduced Risks to Children:
The Case of Bicycle Safety Helmets." Contemporary Economic Policy. 19(4):397-408.
Jenkins, Owens, and Wiggins use the market for bicycle safety helmets to estimate a VSL for two
child age groups and one adult age group. The following table, taken from their article,
summarizes VSLs by age range and assumption.
Table A-2. VSL by Age Range and Assumptions (Million $1997)
Age
5-9
10- 14
20-59
Helmet worn 100%of
the time
$1.5
$1.1
$2.0
Helmet worn less than
100% of the time
$2.7
$2.6
$4.0
Helmet worn less than
100 % of the time and
equal weight on death
and injury
$1.3
$1.3
$2.0
These estimates are the first directly comparable VSLs calculated for child and adult age
categories and one of very few calculated for school age children. Analysts are not advised to
directly use estimates such as these until many more child VSL studies have been completed using
different data sources and methodologies.
Joyce, T.J., M. Grossman, and F. Goldman. 1989. "An Assessment of the Benefits of Air
Pollution Control: The Case of Infant Health." Journal of Urban Economics. 25:32-51.
Joyce, Grossman, and Goldman develop a health production function to estimate the social
willingness to pay for improved neonatal survival associated with a 10 percent reduction in annual
average sulfur dioxide concentrations. They use aggregate data on counties to derive two sets of
estimates — one based on the cost of prenatal care and another based on the cost of neonatal
intensive care. Separate estimates are developed for white and black populations, and the results
are generated per mother (a WTP for benefits to all expected children). The authors assert that
the methodology measures social WTP rather than private because most of the costs measured are
covered by insurance.
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Table A-3 WTP for Improved Neonatal Survival from a 10 Percent Reduction in Sulfur
Dioxide ($1977)
Prenatal Care
Neonatal Care
Black mothers
$4
$110
White mothers
$1
$16
These values, as they stand, are of limited use to analysts in need of estimates of the value of
reduced morbidity or mortality. However, Dickie and Nestor (1999) convert the values in the
table above to VSLs. (See the Dickie and Nestor (1999), annotated bibliographic entry.) The
underlying data for the estimates are county level; thus, analysts should exercise caution in
adopting them or their derivatives. Finally, the assertion by the authors that the estimates
represent social WTP is questionable because the choice that they model regarding quantity of
prenatal and neonatal care was made by parents, not society.
Lewit, E.M., L. Schuurmann Baker, H. Corman, and P.H. Shlono. 1995. "The Direct Cost
of Low Birth Weight." The Future of Children. 5(l):35-56.
Lewit et al. present estimates of the direct incremental costs of low birth weight. The study relies
on analyses derived from two nationally representative population surveys, the 1988 Child Health
Supplement of the National Health Interview Survey (CHS-NHIS) and the 1991 National
Household Education Survey's (NHES) Pre-Primary and Primary Surveys.
Table A-4. Mean Incremental Cost per Low Birth Weight Child ($1988) by Age Group
Age group
Infancy
1 to 2 years
3 to 5 years
3 to 5 years
6 to 1 0 years
6 to 1 5 years
11 to 15 years
Cost type
Health care
All
Health care
Child care
Health care
Special education
Grade repetition
Mean incremental cost per low birth weight
child (1988 dollars)
$15,000
not available
$290
$180
$470
$150
$45
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Lewit et al. do not develop comprehensive estimates for costs associated with children aged 1-2,
11-15, and 16 and older. The authors point out that they fail to include very costly special
services utilized by severely disabled low birth weight children and other early intervention
services utilized by very young children. All of these factors imply that the values in the table
above are underestimates. On the other hand, the authors point out that rapidly changing
technology is leading to increased survival and lower costs in treating low birth weight babies
(i.e., widespread adoption of the use of exogenous surfactant).
Liu, J.-T., J.K. Hammitt, J.-D. Wang, and J.-L. Liu. 2000. "Mother's Willingness to Pay
for Her Own and Her Child's Health: A Contingent Valuation Study in Taiwan." Health
Economics. 9:319-326.
Liu et al. used the results of a survey of 700 Taiwanese mothers to estimate a WTP to avoid a
minor illness themselves and a WTP to have their children avoid a similar illness. Respondents
were asked, using binary-choice questions, how much they would be willing to pay for a
preventative medicine that would cause them to avoid a cold with the same symptoms and
severity of their most recent cold. They were asked a similar question with respect to one of their
children. The authors estimate that the median mother is willing to pay $37 (U.S. $1995) to avoid
her own cold, yet she is willing to pay $57 for her child to avoid a cold. When these values are
adjusted for the fact that the average mother's cold is longer and more severe than the average
child's, the child's value is about twice that of the mother's.
These values themselves may be of little direct use to U.S. policy analysis as they are more
applicable to developing countries.
Marion, R.J., T. Creer, and R. Reynolds. 1985. "Direct and Indirect Costs Associated with
the Management of Childhood Asthma." Annals of Allergy. 54:31-34.
In this paper, the authors attempt to estimate the direct and indirect costs associated with the
management of chronic, intractable childhood asthma. The results are based on reports kept over
a year period by 25 families in Denver, CO. None of the families included in the study were
enrolled in health maintenance organizations, and all reported at least 4 months of asthma-related
expenditures over the year-long period. For the purposes of this study, direct costs were defined
as those expenditures associated with the direct medical management of the child's asthma such as
medications, laboratory tests, physician care, and hospitalizations. Indirect costs, on the other
hand, included "peripheral" expenditures such as time lost from work, babysitter use,
transportation costs, and other miscellaneous expenses such as purchases of air cleaners,
humidifiers, or non-allergic bedding. A table from the paper summarizing their findings is
reproduced below.
Analysts seeking to apply these numbers to a benefit-cost analysis should exercise caution. These
figures are based on a small number of families in a specific locale. Furthermore, in the evaluation
of air pollution regulations, these values may not be appropriate since they focus on asthma
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management rather than the alleviation of acute asthma symptoms. The scientific evidence is
inconclusive regarding the role of air pollution as an inducer of asthma.
Table A-5. Direct and Indirect Asthma Expenditures for AD Families and Costs by
Percentage of Total Income (In Dollars Unless Otherwise Indicated)
N^>c
— z5
Income
Direct costs
Physician
Pharmacy
Hospital
Indirect costs
Miles
Income loss
Miscellaneous
Total costs
Average
24,744.40
940.72
358.80
233.90
204.86
146.48
418 miles
50.00
33.10
1,087.19
Range
Low
5,500.00
52.25
0.00
0.00
0.00
0.00
0.0 miles
0.00
0.00
88.86
High
85,000.00
3,935.55
1,902.00
1,534.00
1,872.31
383.25
1,392 miles
280.00
300.00
3,965.25
Percent of total income
Direct costs
Indirect costs
Total costs
5.50%
0.87%
6.40%
0.10%
0.0%
0.35%
32.8%
6.3%
33.0%
McCormick, M.C., J.C. Bernbaum, J.M. Eisenberg, S.L. Kustra, and E. Finnegan. 1991.
"Costs Incurred by Parents of Very Low Birth Weight Infants After the Initial Neonatal
Hospitalization." Pediatrics. 88(3):533-541.
McCormick et al. compare the medical costs for 32 very low birth weight infants with the costs
for 34 normal weight infants. The study looks at medical costs for the first year of life, recorded
by parents in a diary and collected quarterly via telephone questionnaire. McCormick et al.
estimate that direct medical charges for very low birth weight infants are $8,960 ($1,984 higher
than full term infants) during the first year of life. Hospitalization and increased visits to doctors
account for most of the disparity in medical costs across the two populations.
Analysts should be wary of using these estimates for use in policy analyses. They are derived
from a very small, unrepresentative sample.
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Neumann, P. and M. Johannesson. 1994. "Willingness to Pay for In Vitro Fertilization: A
Pilot Test Using Contingent Valuation." Medical Care. 32(7):686-699.
To estimate the value of reducing human exposure to environmental contaminants that cause
infertility or reduced fecundity, analysts could turn to estimates of the WTP for infertility
treatments. Neumann and Johanneson estimate the WTP for in vitro fertilization procedures by
analyzing the results of a small, unrepresentative sample consisting mainly of students, physicians,
and nurses in and near Boston, Massachusetts. Respondents were interviewed as part of a
contingent valuation survey pilot study. Their survey was designed to elicit estimates for
willingness to pay for three situations: ex post (the couple knows they are infertile); ex ante (the
couple does not know they are infertile); and a comprehensive program providing treatment for all
couples in the State, to be financed by higher taxes. They find, in 1992 dollars, that the value of a
statistical birth ex post is $177,730 per birth; the value of a statistical birth ex ante is $1.8 million
per birth; and the value of public provision of in vitro fertilization is $32 per person per year.
Analysts should exercise extreme caution in adopting these estimates for use in policy analysis.
They are derived from a very small, unrepresentative sample.
Prinzinger, J.M. 1993. "A Valuation of a Generic Child: The Investment Approach."
Journal of Forensic Economics. 6(2): 121-134.
Prinzinger develops a "human capital" estimate of the value of a child's life. He presents children
as an "investment" undertaken by parents only if expected benefits exceed expected costs. While
he finds it impractical to estimate the benefits of an investment in children, Prinzinger instead
estimates the costs. The objective of the paper is to develop estimates appropriate for wrongful
death cases. As a result, the estimates are more appropriate for ex post application, that is for
estimating the value of lives of identifiable children who have actually died. Thus, the estimates
are not appropriate for estimating the value of a statistical life.
Combining the work of other forensic economists, Prizinger develops estimates for the direct
costs of raising a child (e.g., food, clothing, education, etc.) and the indirect or opportunity costs
(e.g., time spent caring for children or cleaning up after them). For the direct costs, Prinzinger
relies on a previous study that uses the Consumer Expenditure Survey to estimate parents'
expenditures on a child. Indirect costs are based on a previous study that analyzed the
information contained in parents' time diaries. Prinzinger assigns a monetary value to that time
based on the average hourly wages of maids, housemen, and janitors. He develops an illustrative
example of total costs using the Consumer Price Index and a financial rate of interest to derive a
present value of the expenditures. In the illustrative calculation, he uses long-term U.S. Treasury
bond rates for specific years, looking retrospectively over the 18-year life of a deceased child. In
1991 dollars, Prinzinger estimates the total investment in a first child expected to go to college as
$219,829 to $277,181. Each additional child is estimated to cost $196,207 to $218,850. The
dollar values vary directly with the educational level of the parents.
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To repeat, Prinzinger's estimates are appropriate for valuing the lost life of an identifiable child
and not for valuing a statistical child life. Thus, estimates are of very limited use to analysts
conducting benefit-cost analyses of EPA regulations.
Schwartz, R. 1989. "What Price Prematurity?" Family Planning Perspectives. 21(4):70-
94.
The author calculates the direct costs for inpatient hospital case for neonates by birth weight. The
data were obtained from a sample of 28 U.S. hospitals providing tertiary neonatal care.70 These
hospitals, representing 16 percent of total urban tertiary hospitals and 54 percent of low birth
weight infants, provided data on infants that received care and were discharged to home during a
12-month period, including all or part of 1985. In order to standardize charges, all charges were
converted to costs. The costs presented in the paper do not include medical education and capital
expense.
The results presented indicate that hospital costs for low birth weight infants (less than 2,500 g)
average $9,072, while those for normal birth weight infants average $678.71 The author also
presents the cost-savings per infant associated with a one category upward shift in birth weight.
Calculated savings range from $1,890 (for a shift from 2,000 g - 2,499 g to 2,500 g or more) to
$18,826 (for a shift from 500 g - 749 g to 740 g - 999 g).
Analysts should exercise caution in applying these estimates in a benefit-cost analysis. At present,
the science linking environmental exposure to low birth weight is limited. The estimates
presented are direct medical costs and additionally do not include costs associated with low birth
weight incurred after release, which may be substantial. Also, it is likely that treatment course,
length, and cost have changed since 1985.
U.S. Environmental Protection Agency. 1985. Costs and Benefits of Reducing Lead in
Gasoline: Final Regulatory Impact Analysis. Washington, D.C.
EPA benefit-cost analysis of removing lead additives from gasoline evaluates the benefits of
reduced blood levels in children. The study estimates direct medical costs and increased costs of
special education for children with blood lead levels over 25 ug/dL. Medical costs were based
upon previously published literature and include screening, follow-up tests, physician visits,
hospitalization, and chelation. The average cost per child with blood levels exceeding 25 ug/dL is
approximately $900 in 1983 dollars, with a range of $100 to $8,400. Special education costs are
estimated assuming that 25 percent of children with blood lead levels over 25 ug/dL require part-
time help but remain in the classroom. Each child was also assumed to need such care for 3 years
7 "Hospitals were considered to provide tertiary care if they had a neonatal intensive care unit, retained
all neonates who required treatment (with the exception of surgical cases) and had at least one full-time
neonatologist on staff"
71A11 estimates are $1985.
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at a total cost of about $2,600 per child (1983 dollars). Special education costs ranged from zero
to $12,870. Total medical and special education costs average $3,500 per affected child.
This study did not include opportunity costs for parents' time or for lost lifetime earnings for the
child resulting from elevated blood lead levels and associated IQ loss. The values reported in this
study probably understate the direct and indirect costs of blood lead burdens in children. The
estimates are almost certainly an underestimate of willingness to pay to reduce these blood lead
levels.
U.S. Environmental Protection Agency. 1997. The Benefits and Costs of the Clean Air Act,
1970 to 1990. Washington, D.C.
This study estimates the value of reduced lead exposure in children that resulted from ambient
lead reductions under the Clean Air Act over a 20 year period from 1970 to 1990. The cost of
elevated blood lead levels in children are based on two components: (1) the loss of future earnings
potential due to IQ associated with elevated blood lead levels, and (2) and special education costs
incurred due to these IQ losses. The study also used a value-of-statistical-life approach to
estimate the benefits of reduced mortality due to neonatal exposure to lead.
The study first employed a meta-analysis of existing studies to estimate average IQ loss from unit
increases in blood lead levels. The effect of this IQ loss on earnings was then estimated, including
adjustments for savings in direct and indirect schooling costs due to reduced educational
attainment. The present value of reduced earnings was approximately $3,000 per IQ point in
1990 dollars. The blood lead-IQ relationship was also used to estimate the number of children
with an IQ less than 70 due to lead exposure. These children are presumed to require special
education from grades 1 through 12 at a cost of approximately $42,000 per child (1990 dollars).
These estimates probably understate the direct and indirect costs of high blood lead levels. The
study did not include medical care costs, including the opportunity costs of parents' time, and
special education costs assume that mentally handicapped children are kept in a regular classroom.
Willingness to pay to reduce high blood lead levels almost certainly exceeds the values reported in
this study.
U.S. Environmental Protection Agency. 1999. Cost of Illness Handbook. Draft Report
prepared for the Office of Pollution Prevention and Toxics by Abt Associates, Inc.
Washington, D.C.
EPA's ongoing cost-of-illness research analyzes the costs of treating asymptomatic children under
6 years old identified through screening programs as having high blood lead levels.
Asymptomatic children do not present overt symptoms but may still suffer health impacts from
lead exposure. Costs are estimated by risk classes defined by the CDC. Each risk class, based on
information on blood lead concentration, is assigned a treatment profile and costs are estimated
for the components of the different profiles. These costs are based on earlier EPA cost estimates.
The study develops average costs per child screened in each risk class and adjusts the values by:
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(1) the probability that a child is screened, and (2) the survival rates for the children. At a
discount rate of 3 percent, the present value of treatment costs range from $104 (in 1996 dollars)
for those in the lowest risk class, to $5,185 for those in the highest.
The values in this study capture only the costs of chelation therapy and other medical
interventions and do not include indirect costs associated with the opportunity costs of time. As
is the case for many estimates based on a cost-of-illness approach, the values here probably
understate willingness to pay to reduce blood lead levels.
Viscusi, W.K., W. Magat, and J. Huber. 1997. "An Investigation of the Rationality of
Consumer Valuations of Multiple Health Risks." Rand Journal of Economics. 18:465-479.
This article reports the results of a survey of consumers to test risk trade-off hypothesis.
Additionally, the article reports willingness to pay to reduce the risks of child poisoning. The
sample was drawn from consumers at a Greensboro, North Carolina, shopping mall. All
respondents were asked to consider a single product (toilet bowl cleaner or insecticide) and were
given the number of injuries associated with use of 10,000 bottles. Consumers with children were
asked to consider child poisoning and eye burns (toilet bowl cleaner) and inhalation and child
poisoning (insecticide). Consumers were then asked to indicate their maximum willingness to pay
for a specified reduction in risk of one injury.
Estimates of the value of avoiding a statistical injury ranged from $1,010 for child poisoning from
the toilet bowl cleaner to $2,860 for child poisoning from the insecticide.72 The results from this
study may not be directly applicable to benefit-cost analyses of environmental regulations. First,
the sample is not likely to be representative of households across the country. Second, the
number or severity of child poisonings is probably not impacted by the majority of environmental
rules and policies.
Waitzman, N., P. Romano, and R. Scheffler. 1994. "Estimates of the Economic Costs of
Birth Defects." Injury. 33:188-205.
This article examines the cost of birth defects in the United States. Most children with birth
defects do not die in infancy, and they usually require special medical treatment, special education,
and other services throughout their lives. This study uses a cost-of-illness methodology to
estimate the cost of 18 clinically significant birth defects in the United States, including Spina
bifida, Truncus arteriosus, single ventricle, cleft lip, and Down Syndrome. The authors estimate
the incremental (above the costs of those incurred by the "average" infant, child, or adult) indirect
mortality and morbidity costs and direct costs of medical, developmental, and special education
services over the entire life span of those born with each defect in California in 1988. The total
cost by birth defect are presented in below.
72Estimates are $1987.
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Table A-6. Total Costs of Birth Defects in California ($ OOOs 1988)
Condition
Spina bifida
Truncus arteriosus
Traposition/DORV
Tetralogy of Fallot
Single ventricle
Cleft lip/palate
TE fistula
Atresia, small intestine
Colorectal/anal artesia
Renal agenesis
Urinary obstruction
Upper limb reduction
Lower limb reduction
Diaphragmatic hernia
Gastroschisis
Omphalocele
Down syndrome
Cerebral palsy
Cost per case by discount rate
2%
538
908
569
466
747
246
295
123
278
667
220
238
495
610
195
415
1,020
1,067
5%
258
437
237
227
304
92
128
64
111
230
79
91
182
227
94
159
410
445
10%
121
242
102
125
121
29
61
40
45
59
24
30
54
77
54
58
153
167
Analysts should exercise caution in applying these estimates in a benefit-cost analysis. As
mentioned, the above estimates include the costs of premature mortality (calculated as lost
earnings). The authors also discuss other potential biases of their estimates including that profiles
or care and treatment were calculated using 1988 cross-sectional data. Prevalence, incidence,
survival, and cost data are primarily based upon records from California.
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Weiss, K.B., P.J. Gergen, and T.A. Hodgson. 1992. "An Economic Evaluation of Asthma
in the United States." The New England Journal of Medicine. 326(13):862-866.
Weiss et al. estimates the national direct and indirect costs associated with asthma for 1985, using
data from the National Center for Health Statistics. The direct costs included expenditures on
inpatient hospitalization, hospital outpatient services, emergency room services, medications, and
physician services (both in-patient care and office visits). Indirect costs included value of time
lost from school and work including both values for both outside employment and housekeeping.
It should be noted, however, that no values were included for a child's time when the patient was
below the age of 18. These indirect costs were only computed for adults and adult caregivers.
Results are reported separately for children (individuals aged 17 and under) and adults
(individuals aged 18 and up). Of most interest to analysts are those national cost figures reported
as reproduced below. Analysts should exercise caution in applying these figures to a benefit-cost
analysis of the reduction of air pollution because the figures do not give an indication of the per
case cost and the role of ambient pollution in inducing new asthma cases is still in question.
Table A-7. Costs of Asthma in 1985 Among Selected Age Groups
Category
Direct Costs
Hospital Care
Inpatient
Emergency room
Outpatient
Physicians' Services
Inpatient
Outpatient
Medications
All direct costs
Indirect Costs
School Days lost
Loss of work
Outside employment
Housekeeping
Mortality
All indirect costs
Age 17 or under
250.3
90.4
37.1
20.2
67.14
-
465.1
726.1*
-
-
99.0"
825.1
Age 18 or over
808.4
109.9
92.1
61.2
126.2
-
1197.8
726.1*
284.7
406.0
676.2"
2093.0
* Includes value of caretaker time only.
** Valued using loss of future income (i.e.,human capital approach).
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Conference Presentations/Working Papers
73
Agee, M., and T. Crocker. 2001. "Some Economics of Child Health and Environmental Tobacco
Smoke." Paper presented at the Association of Environmental and Resource Economists 2001
Summer Workshop, "Assessing and Managing Environmental and Public Health Risks." Bar
Harbor, Maine, June 13-15, 2001.
Agee, M.D. and T.D. Crocker.* 1999. "On Techniques to Value the Impact of Environmental
Hazards on Children's Health." Issue paper prepared for the U.S. Environmental Protection
Agency, National Center for Environmental Economics.
Brajer, V., J.V. Hall, and F. Lurmann. 2002. "Economic Valuation of Ozone-Related School
Absences in the South Coast Air Basin of California." Paper presented at the Western Economic
Association International Annual Conference. Seattle, Washington, June 29 - July 3, 2002.
Davis, M.M. and D.O. Meltzer.* 2002. "Methodological Issues in the Application of Quality
Adjusted Life Years to Interventions Regarding Children." Paper presented at the Allied Social
Science Associations meetings, Atlanta, Georgia, January 4-6, 2002.
Dickie, M. and S. Gerking. 2001. "Parents' Valuation of Latent Health Risks to Their Children."
Paper presented at the EPA Workshop, "Economic Valuation of Mortality Risk Reduction:
Assessing the State of the Art for Policy Applications." Silver Spring, Maryland, November 7,
2001. (http://yosemite.epa.gov/ee/epa/eerm.nsf/vwRepNurnLookup/EE-04647OpenDocument)
Dickie, M. and V. Ulery. 2001. "Valuing Health in the Household: Are Kids Worth More than
Adults?" Paper presented at the Association of Environmental and Resource Economists 2001
Summer Workshop, "Assessing and Managing Environmental and Public Health Risks." Bar
Harbor, Maine, June 13-15, 2001.
Harbaugh, W. 1999.* "Valuing Children's Health and Life: What Does Economic Theory Say
about Including Parental and Societal Willingness to Pay?" Paper Commissioned for U.S. EPA
Environmental Policy and Economics Workshop, "Valuing Health for Environmental Policy with
Special Emphasis on Children's Health Issues." March 24-25, 1999, Silver Spring, MD.
Jenkins, R.R., N. Owens, and L.B. Wiggins. 2002. "Age and the Valuation of Risk Reduction: An
Examination of Spending on Bicycle Safety Helmets." Paper presented at the Allied Social
Science Associations meetings. Atlanta, Georgia, January 4-6, 2002.
Maguire, K.B., N. Owens, and N. Simon. 2002. "What do Organic Baby Food Purchases Tell Us
7 Papers with a * next to the author name(s) were commissioned by EPA's National Center for
Environmental Economics. Please see the NCEE Working Paper Series webpage
(http://yosemite.epa.gov/EE\Epa\eed.nsf/pages/wpseries#WorkingPapers) to obtain a copy.
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About Parental Values for Reductions in Risk to Children's Health?" Paper presented at the
Allied Social Science Associations meetings. Atlanta, Georgia, January 4-6, 2002.
Mansfield, C., F.R Johnson, and G. Van Houtven. 2002. "Behavioral Reactions to Ozone Alerts:
Estimating the lost outdoor playtime of asthmatic children." Paper presented at the Western
Economic Association International Annual Conference. Seattle, Washington, June 29 - July 3,
2002.
Markowski, M.* 1999. "Benefits Transfer of Children's Health Values." Issue paper prepared for
the U.S. Environmental Protection Agency, National Center for Environmental Economics.
Mount, T., W. Weng, W. Schulze, and L. Chestnut. 2001. "Automobile Safety and the Value of
Statistical Life for Children, Adults, and the Elderly: Results from New Data On Automobile
Usage," Paper presented at the Association of Environmental and Resource Economists 2001
Summer Workshop, "Assessing and Managing Environmental and Public Health Risks." Bar
Harbor, Maine, June 13-15, 2001.
Neumann, J. and H. Greenwood.* 1999. "Existing Literature and Recommended Strategies for
Valuation of Children's Health Effects." Issue paper prepared for the U.S. Environmental
Protection Agency, National Center for Environmental Economics.
Shogren, J.* 1999. "Valuing Indirect Effects from Environmental Hazards on a Child's Life
Chances." Issue paper prepared for the U.S. Environmental Protection Agency, National Center
for Environmental Economics.
Thompson, K.* 1999. "Data Requirements for Valuation of Children's Health Effects and
Alternatives to Valuation." Issue paper prepared for the U.S. Environmental Protection Agency,
National Center for Environmental Economics.
Tolley, G. and R.Fabian.* 1999. "Contingent Valuation and Valuing Children's Health." Paper
prepared for U.S. EPA Environmental Policy and Economics Workshop Valuing Health for
Environmental Policy with Special Emphasis on Children's Health Issues. March 24-25, 1999,
Silver Spring, MD.
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Appendix B
Summary of External Reviewer Comments
In an effort to ensure the Handbook presents quality, sound, and consistent, as well as practical,
information on valuing improvements in children's health, a previous version of this Handbook
was reviewed by Lauraine Chestnut (Stratus Consulting), A. Myrick Freeman (Bowdoin College),
James Hammitt (Harvard University), and Jason Shogren (University of Wyoming). Their
comments proved very useful and have lead to revisions that provide a clearer, more accurate and
improved document. Below is a summary of their major comments along with more minor
comments that readers may find interesting. Following each comment is discussion of where,
how, or whether the document was revised.
In general, all of the reviewers felt that the document was well-written, technically accurate, and
useful to program analysts within the Agency. One reviewer felt that there "is little practical
guidance to give policy analysts at this point." Another reviewer noted, "Overall, I think this is an
excellent report...[I]t appears to be technically accurate, reflects current economic research, and
identifies relevant questions that have yet to be addressed. In addition, it is clearly written and
provides technically sound but practical guidance for policy analysts."
The document should include a section that reviews welfare economics and discusses the
perspective that should be adopted when valuing children's health. When valuing children's
health, three potentially relevant perspectives exist: child, parental, and child-as-adult. Each
reviewer made several comments related to the issue of perspective, including pros and cons of
each perspective, suggestions for considering household decision making, and the impact of
altruism.
Response: The comments on perspective prompted inclusion of Section 2.2.1,
Perspective and Childhood Health Values, where each perspective is described and its
relevance for valuing children's health effects is discussed. Ideas developed in this section
help shape additional sections of the Handbook. Specific examples include:
• The discussion in Chapter 2 of the factors that may cause differences in
values estimated for children compared to values estimated for adults
includes the influence that perspective may have on these factors; and
• The discussion in Chapter 4 where the perspective assumed by each
valuation technique is highlighted.
The idea that there is a public good component to children's health and that improving
children's health leads to a more productive society needs additional explanation and
justification. The presumption that social values for children's health should be added to the
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values for use in a benefit-cost analysis is not necessarily correct and may, in fact, result in double
counting benefits.
Response: The authors of the Handbook did not intend to suggest that social values for
children's health should somehow be added to the values traditionally used in a benefit-
cost analysis in the reviewed version of the Handbook. The current version provides a
more extensive and clearer description of the altruism concept. In responding to the
comments, the authors found it difficult to distinguish a "public good component to
children's health" that would somehow be different from a pub lie good aspect of adult
health, although some researchers have argued that such differences exist generally
(Folbre, 1994). This version of the Handbook does not include the phrase "a public good
component," but rather relies on the various forms of altruism to discuss the concept of
one person's utility being a function of another person's utility.
Appropriate application of the lifetime wealth adjustment requires consideration of when
the risk reduction takes place and who is expected to pay for the risk reduction.
Response: The revised version of the Handbook clarifies the lifetime wealth adjustment
that is only appropriate for benefit transfer of values for risk reductions experienced by
adults to policy scenarios involving children's risks. The adjustment would not be
appropriate when drawing on parental values for these risks. Please see the discussion in
Chapter3.
The Handbook would benefit from a more rigorous discussion concerning adjusting values
for cross-sectional differences in income.
Response: Agency policy currently does not support this type of adjustment. In this
respect, EPA concurs with recommendations on the subject from the Environmental
Economics Advisory Committee of the Science Advisory Board. Please see the
SAB/EEAC report, "An SAB Report on EPA's White Paper Valuing the Benefits of Fatal
Cancer Risk Reductions" (http://www.epa.gov/sab/fiscalOO.htm).
The document does not provide information on the treatment of health outcomes that are
not manifest until adulthood but result from childhood exposures.
Response: The techniques and recommendations contained in this Handbook are relevant
to the situation described by the reviewer, and this is now noted explicitly in Footnote 3.
The document reasonably argues that children's health values might be different from
those for adults; however, the document could provide more information on why these
values may, in fact, be the same. For example, adult willingness to pay (WTP) for reduced
morbidity and mortality risks does not vary by age as much as would be predicted if willingness to
pay were proportional to remaining life years.
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Response: The authors have sought to provide balance in presenting the factors that may
cause differences in the values for children compared to the values for adults. The limited
information that does exist suggests that there is a difference. Please see the discussion in
Section 2.2, Valuation Differences.
It would help to make the writing more sensitive to the fact that health values are often
treated as fixed values per case. Value of statistical life (VSL) is really an estimate of the
marginal rate of substitution between income and mortality risk, which is expected to vary with
the baseline risk. In benefits transfer, using a function allows the possibility of variation in unit
values with the quantity obtained and/or with the baseline.
Response: The current version of the Handbook includes this point in Section 3.2.1
where "Study Similarity" is discussed. For most of the risks subject to Agency policy, this
is not an issue.
Cost-of-illness (COI) estimates are not an "alternative measure of value" although they do
provide valuable information. The real issue with these estimates is that they do not measure
what is needed for use in benefit-cost analyses not that they do not measure well what they were
designed to measure.
Response: The current version of the Handbook presents willingness-to-pay measures as
the most theoretically desirable estimates for use in benefit-cost analysis. Cost-of-illness
estimates are presented as alternative measures to WTP which, since they do not represent
willingness to pay, are not as theoretically desirable for benefits analysis purposes. The
Handbook no longer refers to COI estimates as an "alternative measure of value." Please
see Section 4.2, An Alternative Approach to WTP: Cost of Illness.
The document would benefit from a short section on quality adjusted life years.
Response: EPA's National Center for Environmental Economics and Office of Children's
Health Protection have commissioned a white paper on the topic of quality adjusted life
years and are considering their usefulness in benefits analysis of children's health risk
reductions.
The document should provide information on how to value the effects of parental or of
other family members' illness or death on children. If caregivers are fully informed, then such
indirect effects are included in adult measures of willingness to pay for own risk reductions;
however, if caregivers are not fully informed, such indirect effects may be underestimated.
Response: While indirect effects are important, the focus of the Handbook is on the direct
health effects experienced by children. Intrahousehold allocation and household
production models may provide a way for analysts to address indirect effects.
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