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NATIONAL CENTER FOR
ENVIRONMENTAL ECONOMICS
Regulatory Impact Analyses of Environmental Justice
Effects
H. Spencer Banzhaf
Working Paper Series
Working Paper # 10-08
August, 2010
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Regulatory Impact Analyses of Environmental Justice Effects
H. Spencer Banzhaf
NCEE Working Paper Series
Working Paper # 10-08
August, 2010
DISCLAIMER
The views expressed in this paper are those of the author(s) and do not necessarily represent
those of the U.S. Environmental Protection Agency. In addition, although the research described
in this paper may have been funded entirely or in part by the U.S. Environmental Protection
Agency, it has not been subjected to the Agency's required peer and policy review. No official
Agency endorsement should be inferred.
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REGULATORY IMPACT ANALYSES OF ENVIRONMENTAL JUSTICE EFFECTS
H. Spencer Banzhaf
Abstract
Finding an appropriate way to incorporate environmental justice considerations into policy-
making has been a procedural challenge since President Clinton issued Executive Order 12,898
over 15 years ago. Moreover, environmental justice continues to be overshadowed by efficiency
considerations as embodied in benefit-cost analysis. This article argues that the environmental
justice and benefit-cost policies and procedures in EPA's rule-making can both be improved by
bringing them closer together, ultimately improving environmental regulations as well. In
particular, environmental justice consideration should be incorporated into Regulatory Impact
Analyses (RIAs) by drawing on the much older tradition of incorporating distributional effects
into benefit-cost analysis.
By providing information on the distribution of benefits and costs of its regulatory
actions, EPA would further its environmental justice objectives by providing the information that
all groups—including the poor, minorities, and environmental justice communities—need to
understand the impacts of a regulatory action. By incorporating such information into its RIAs,
EPA would integrate environmental justice considerations into its development of regulations.
Finally, by actually allowing the new information to inform the design and selection of
regulations so as to better protect disadvantaged groups, adding distributional impacts to RIAs
would improve the distributive justice associated with EPA's actions as well as the procedural
justice.
Key words: environmental justice, benefit-cost analysis, disperse pollutants
Associate Professor, Dept. of Economics, Andrew Young School of Policy Studies, Georgia State University, PO
Box 3992, Atlanta, GA, 30302, 404-413-0252, hsbanzhaf@gsu.edu. For valuable comments, I thank participants in
the EPA-Abt Workshop on Analytical Methods for Assessing the Environmental Justice Implications of
Environmental Regulations. I especially thank Matthew Adler, Kelly Maguire, and Tauhidur Rahman. The views
in this paper are those of the author and do not reflect official U.S. EPA policy.
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Introduction
The environmental justice movement was launched in 1982, when residents of Warren County,
NC, protested the construction of a hazardous waste landfill in their predominantly African-
American Community.1 Minority communities' sense that such hazardous facilities are to be
found disproportionately in their communities was soon borne out by two landmark studies by
the US GAO (1983) and the United Church of Christ (1987). Since then, research has shown
consistently that poor and minority households tend to live in more polluted neighborhoods.
This correlation appears to be quite robust to the statistical methods employed and to the type of
pollution considered, including hazardous waste facilities, landfills, large air polluters, and the
concentration of air pollutants.2 In short, the correlation qualifies as a "stylized fact" as much as
1 For an introduction to the topic, including these historical origins, see generally ROBERT D.
Bullard, Dumping in Dixie: Race, Class, and Environmental Quality (2nd ed. 1994).
2 For the classic studies on the location of landfills and hazardous waste facilities, see generally
United States General Accounting Office {hereinafter, GAO), SITING OF HAZARDOUS WASTE LANDFILLS
AND THEIR CORRELATION WITH RACIAL AND ECONOMIC STATUS OF SURROUNDING COMMUNITIES
(1983); United Church of Christ, Toxic Wastes and Race in the United States (1987); United
Church of Christ, Toxic Wastes and Race at Twenty: 1987-2007 (2007). For more recent work,
see generally Brett M. Baden & Don L. Coursey, The Locality of Waste Sites within the City of Chicago:
A Demographic, Social, and Economic Analysis, 24 RESOURCE & ENERGY ECON. 53 (2002); Vicki Been,
Locally Undesirable Land Uses in Minority Neighborhoods: Disproportionate Siting or Market
Dynamics?, 103 YALE L. J. 1383 (1994); J. Tom Boer et al., Is there environmental racism? The
demographics of hazardous waste in Los Angeles County, 78 SOCIAL SCIENCE Q. 793 (1997); BENJAMIN
A. Goldman & Laura Fitton, Toxic Wastes and Race Revisited (1994). On the proximity of large
polluters, see generally H. Spencer Banzhaf, Joshua Sidon, & Randall P. Walsh, Segregation and Tiebout
Sorting: Investigating the Link (2008), unpublished manuscript; Evan Ringquist, Equity and Distribution
of Environmental Risk: The Case ofTRI Facilities, 78 SOCIAL SCIENCE Q. 811 (1997); James L. Sadd et
al., 'Every Breath You Take...:" The Demographics of Toxic Air Releases in Southern California, 13
ECONOMIC DEVELOPMENT Q. 107 (1999); Ann Wolverton, The Role of Demographic and Cost-Related
Factors in Determining where Plants Locate—A Tale of Two Texas Cities (2009), unpublished
manuscript. On the emissions of air pollutants, see generally Seema Arora & Timothy N. Cason, Do
Community Characteristics Influence Environmental Outcomes? Evidence from the Toxics Release
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anything in social science.
This finding of a disproportionate environmental burden borne by the poor and by people
of color motivated President Clinton to issue Executive Order (EO) 12,898.3 Still in force, the
order requires nondiscrimination in federal environmental programs and focuses federal
resources, such as the US Environmental Protection Agency's (EPA's) Brownfields Program, on
low-income and minority communities.4 EPA defines environmental justice as
Inventory, 65 SOUTHERN ECON. J. 691 (1999); Nancy Brooks & Rajiv Sethi, The Distribution of
Pollution: Community Characteristics and Exposure to Air Toxics, 32 J. ENVTL. ECON. & MGMT. 233
(1997); Warren Kriesel, Terence J. Centner, & Andrew G. Keller, Neighborhood Exposure to Toxic
Releases: Are there Racial Inequities?, 27 GROWTH & CHANGE 479 (1996); Ringquist, Equity and
Distribution, supra. On estimated air pollution concentrations, see generally Michael Ash & T. Robert
Fetter, Who Lives on the Wrong Side of the Environmental Tracks? Evidence from the EPA's Risk-
Screening Environmental Indicators Model, 85 SOCIAL SCIENCES Q. 85 441 (2004); Rachel Morello-
Frosch & Bill M. Jesdale, Separate and Unequal: Residential Segregation and Estimated Cancer Risks
Associated with Ambient Air Toxics in US Metropolitan Areas, 114 ENVIRONMENTAL HEALTH
PERSPECTIVES 386 (1996); Rachel Morello-Frosch, Manuel Pastor, & James Sadd, Environmental Justice
and Southern California's 'Riskscape': The Distribution of Air Toxics Exposures and Health Risks among
Diverse Communities 36 URBAN AFFAIRS REV. 551 (2001). For the classic book-length introduction to
the literature over-all, see generally Bullard, DUMPING IN DIXIE, supra note 1. For more recent reviews
and discussion of this literature, see generally H. Spencer Banzhaf, Environmental Justice: Opportunities
through Markets, 42 PERC POLICY SERIES; H. Spencer Banzhaf & Eleanor McCormick, Moving Beyond
Cleanup: Identifying the Crucibles of Environmental Gentrification, NATIONAL CENTER FOR
Environmental Economics Working Paper 07-02 (2006), available at
yosemite.epa.gov/EE/epa/eed.nsf/WPNumberNew/2007-02?OpenDocument; William Bowen, An
Analytical Review of Environmental Justice Research: What Do We really Know?, 29 ENVTL MGMT 3
(2002); Douglas S. Noonan, Evidence of Environmental Justice: A Critical Perspective on the Practice of
EJ Research and Lessons for Policy Design, 89 SOCIAL SCIENCE Q. 1154 (2008); Manuel Pastor,
Environmental Justice: Reflections from the United States, 1 Political Economy Research Institute
Conference Paper(2002), available at www.peri.umass.edu/fileadmin/pdf/conference_ papers/CDP 1 .pdf;
Evan J. Ringquist, Environmental Justice: Normative Concerns, Empirical Evidence, and Government
Action, in ENVIRONMENTAL POLICY: NEW DIRECTIONS FOR THE TWENTY-FIRST CENTURY 241 (Norman
J. Vig & Michael E. Kraft eds., 2003); Evan J. Ringquist, Assessing Evidence of Environmental
Inequities: A Meta-Analysis, 24 J. POL'Y ANAL. & MGMT 223 (2005).
3 Exec. Order No. 12,898, 59 Fed. Reg. 7629 (Feb. 11, 1994).
4 See United States Environmental Protection Agency {hereinafter EPA), Final
Guidance For Incorporating Environmental Justice Concerns in EPA's NEPA Compliance
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the fair treatment and meaningful involvement of all people regardless of race,
color, national origin, or income with respect to the development, implementation,
and enforcement of environmental laws, regulations, and policies. EPA has this
goal for all communities and persons across this Nation. It will be achieved when
everyone enjoys the same degree of protection from environmental and health
hazards and equal access to the decision-making process to have a healthy
environment in which to live, learn, and work.5
This interpretation predominantly situates environmental justice within the larger concept of
procedural justice, in which EPA's rule-making and enforcement processes must be fair and open
to the participation of all. But EPA's interpretation also hints at distributive justice, according to
which the distribution of environmental quality should be fair and equitable.6
But, politically, the environmental justice order has never lived in isolation. It is but one
in a series of executive orders that have shaped the promulgation of environmental regulations.
Perhaps the most important was President Reagan's EO 12,291, which required a regulatory
impact analysis (hereinafter, RIA), including an economic analysis of benefits and costs, for all
major federal rules.7 President Clinton's EO 12,866 revised this order in some respects,
emphasizing the non-quantitative effects of rules as well, but maintained the benefit-cost
ANALYSES (1998), available at http://www.epa.gov/regionl/ej/pdfs/ej_guidance_nepa_epa0498.pdf,
EPA, Addressing Environmental Justice in EPA Brownfields Communities (2009), available at
http://epa.gov/brownfields/policy/ej_brochure_2009.pdf.
5 EPA, Home page for the office of Environmental Justice (2010), available at www.epa.gov/
environmentaljustice/index.html.
6 But note EPA's aspiration that "everyone enjoys the same degree of protection" is subtly distinct
from "enjoys the same level of environmental quality." Government agencies are not in the business of
promising utopia. On the tentative steps taken here toward a concept of distributive justice, see generally
Matthew D. Adler, Risk Equity: A New Proposal, 32 HARV. ENVTL. L. REV. 1 (2008). For a more
general discussion of the relationship between environmental justice and these more fundamental notions
of justice, see generally, Sheila Foster, Justice from the Ground up: Distributive Inequities, Grassroots
Resistance, and the Transformative Politics of the Environmental Justice Movement, 86 CAL. L. REV. 775
(1998).
7 Exec. Order No. 12,291, 3 CFR 127 (1981).
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requirement for all "economically significant" rules, defined as those having costs greater than
$ 100m.8 These orders have implicitly made economic efficiency a criterion for evaluating
potential actions to protect the environment. Historically, such efficiency considerations have
carried much more weight than other considerations, including environmental justice.9
The environmental justice and benefit-cost executive orders, like the underlying policy
objectives of fairness and efficiency that motivate them, interact in important ways. For
example, RIAs are a crucial part of the opportunity for public participation, providing critical
information on the benefits and costs of proposed rules. Yet EPA's standard practice, like that of
other agencies, is to document only aggregate benefits and costs, to whosoever they may accrue.
This article argues that expanding RIAs to include information on the distribution of benefits and
costs of regulatory actions would provide environmental justice communities (and other
communities too) with crucial information they need to participate fully in the process.
Accordingly, providing such information would enhance procedural justice.
By the same token, documenting distributional effects in RIAs would provide the
information agencies need to choose rules that would foster environmental equity as well as
efficiency, enhancing distributive justice. Thus, the over-arching theme of this article is that, far
from necessarily being at loggerheads, the environmental justice and benefit-cost executive
orders can mutually interact to improve environmental policy-making.
8 Exec. Order No. 12,866 §l(a), §3(f), 58 Federal Register 51735 (Sept. 30, 1993).
9 For discussion of the role of this benefit-cost requirement in environmental regulations, see
generally Robert W. Hahn, Sheila M. Olmstead, and Robert N. Stavins, Environmental Regulation in the
1990s: A Retrospective Analysis, 27 HARV. ENVTL. L. REV. 377 (2003); WINSTON HARRINGTON, LISA
Heinzerling, & Richard D. Morgenstern, Reforming Regulatory Impact Analysis (2009);
Environmental Policy Under Reagan's Executive Order: The Role of Benefit-Cost
Analysis (V. Kerry Smith, ed. 1984); Cass R. Sunstein, THE COST-BENEFIT STATE: THE FUTURE OF
Regulatory Protection (2002).
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This article begins by exploring environmental justice objectives as they have been
incorporated into RIAs to date. It suggests that these objectives have been too limited. In
particular, it concludes that EPA's emphasis on providing negative assurance that its programs
do not exacerbate environmental justice concerns hampers its ability to consider environmental
justice factors in many regulatory settings. In addition, EPA's focus on environmental justice
considerations at discrete "sites" and the surrounding local "communities" limits the domain in
which environmental justice considerations come into play. The paper argues that a more
fruitful approach would simply be to think in terms of distributional impacts. In particular, RIAs
should compute the benefits and costs of an action on specific demographic groups, as well as
the aggregate benefits and costs.
I. Environmental Justice Objectives and Regulatory Actions
EPA has stated that it "will work to ensure that environmental justice is incorporated into the
Agency's regulatory process.10 Of course, conducting an RIA is an integral part of the
regulatory process, yet in comparison to the prodigious opportunities for incorporating
environmental justice into an RIA, EPA's vision appears to be quite limited. EPA's
Environmental Justice Strategy begins a statement of its objectives by stating: "No segment of
the population, regardless of race, color, nation origin or income, as a result of EPA's policies,
programs, and activities, suffers disproportionately from adverse human health or environmental
effects...,"u That is, EPA appears to be focused more on avoiding exacerbating environmental
10 EPA, Environmental Justice Strategy 17 (1995), available at http://www.epa.gov/
compliance/ej/resources/policy/ej_strategy_l 995 .pdf
11 Id. at 1 (emphasis added).
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justice concerns than on alleviating pre-existing concerns. In other words, first do no harm.12
Unfortunately, when it has incorporated even these limited environmental justice
objectives into its RIAs, EPA has tended to stop at perfunctory, pro forma assertions that it is not
creating or exacerbating an environmental injustice. For example, the RIA for arsenic in
drinking water consists of these meager 116 words:
Executive Order 12898 establishes a Federal policy for incorporating
environmental justice into Federal agency missions by directing agencies to
identify and address disproportionately high and adverse human health or
environmental effects of its programs, policies, and activities on minority and
low-income populations. The Executive Order requires the Agency to consider
environmental justice issues in the rulemaking and to consult with Environmental
Justice (EJ) stakeholders.
The Agency has considered environmental justice related issues concerning the
potential impacts of this regulation and has determined that there are no
substantial disproportionate effects. Because the arsenic rule applies to all
community water systems, the majority of the population, including minority and
low-income populations will benefit from the additional health protection.13
An only slightly expanded treatment is given in the RIA for disinfection byproducts.14 These
recent RIAs have not even documented this absence of harm, but instead have only given
negative assurance that no evidence of harm has come to EPA's attention. Thus, even if EPA
confines itself to the objective "do no harm," there is room for improved documentation, for
moving from beyond "negative assurance" to "positive assurance" that it is doing no harm.
12 It might be argued that this focus is found in EO 12,898 itself, which mandates that "each Federal
agency shall make achieving environmental justice part of its mission by identifying and addressing, as
appropriate, disproportionately high and adverse human health or environmental effects of its programs,
policies, and activities on minority populations and low-income populates..." (Supra note 3, at §1-101,
emphasis added). However, as discussed infra, in the context of the benefit-cost executive orders,
EO 12,898 can be read to as providing a basis for more positive steps.
13 EPA, Proposed Arsenic in Drinking Water Rule: Regulatory Impact Analysis §8.9
(2000), available at http://yosemite.epa.gov/ee/epa/ria.nsf/vwAN/A200012B,pdf/$file/A200012B.pdf
14 EPA, Economic Analysis for the Final Stage 2 Disinfectants and Disinfection
BYPRODUCTS Rule §8.10 (2005), available at www.epa.gov/safewater/disinfection/stage2/pdfs/
anaylsis_stage2_ecconomic_main.pdf.
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One reason for moving beyond simply asserting negative assurance toward actually
documenting the distributional effects of an action is that it would facilitate informed citizen
involvement and comment. Again, the importance of this involvement was emphasized in
EO 12,898 itself, which emphasizes that agency strategies for environmental justice should,
at a minimum, (1) promote enforcement of all health and environmental statutes
in areas with minority populations and low-income populations: (2) ensure greater
public participation; (3) improve research and data collection relating to the health
of and environment of minority populations and low-income populations; and (4)
identify differential patterns of consumption of natural resources among minority
populations and low-income populations.15
EPA likewise recognized the role of public participation when it noted that environmental justice
requires the "meaningful involvement of all people regardless of race, color, national origin, or
income with respect to the development... of environmental laws, regulations, and policies."16
Its Environmental Justice Strategy elaborates,
Those who live with environmental decisions—community residents, State,
Tribal, and local governments, environmental groups, businesses—must have
every opportunity for public participation in the making of those decisions. An
informed and involved community is a necessary and integral part of the process
to protect the environment.17
Of course, to be full partners in decision making, these groups must have access to relevant data
about the effects of these environmental actions, as EPA also recognizes: "EPA will work with
affected communities, State, Tribal, and local governments, and others to have the best possible
information available to identify and address disproportionately high and adverse human health
or environmental effects on minority populations and low-income populations."18
15 Exec. Order 12,898, supra note 3, at §1-103 (emphasis added).
16 EPA, Environmental Justice Home Page, supra note 5.
17 EPA, Environmental Justice Strategy, Supra note 10, at 1-2.
18 Id. at 11.
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Surely, the "best possible information" would include data on the distributional effects of
a policy. Again, EPA seemingly recognizes this when it writes: "EPA will collect, analyze, and
disseminate data that will compare environmental and human health risks to populations
identified by race, national origin, or income."19 But what could be more appropriate than to
incorporate this information directly into its RIAs, which provides the critical information for
both technical analysis of and public comment on proposed rules?
But there is also good reason to move beyond this defensive posture. "First do no harm"
has always been wise council, but Hippocrates would never have had much of a medical career if
his practice had ended there. Like the physician, EPA, like any federal regulatory agency, takes
actions to achieve national objectives. As implicitly embodied in benefit-cost analysis, one of
those objectives is to maximize an aggregation of individuals' welfare. But in addition to this
efficiency objective, a more equitable distribution of welfare is also a social objective in our
society. Accordingly, the analysis in an RIA should provide the information needed to design
regulations, not only with the objective of efficiency in mind, but with equity as well.
There is ample precedent for doing so. Of course, EO 12,898 does not explicitly require
distributional analysis in RIAs, but those actions it does specifically mention are characterized as
a minimum requirement of federal agencies.20 But because RIAs are a crucial source for public
comment, by stressing the public participation of all groups in the development of environmental
regulations, the order implicitly requires the documentation of such effects in RIAs.
As previously noted, RIAs are governed by benefit-cost orders as well.21 But this
19 Id. at 12.
20 See infra text accompanying note 15.
21 See infra text surrounding note 9.
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overlap poses no problem; indeed the environmental justice basis for documenting distributional
effects only reinforces pre-existing precedents for doing so within benefit-cost analysis on its
own terms. For decades, academic experts in benefit-cost analysis have called for this
approach22, and they continue to endorse it.23 Accordingly, other nations, like the United
Kingdom, have adopted this approach.24
Documenting distributional effects in benefit-cost analysis has precedent within the US
federal government as well. The US Water Resource Council has long allowed (though not
required) effects on the income distribution to be included in benefit-cost analyses of water
22 For a history of efforts to incorporate distributional effects in the academic literature, see
generally H. Spencer Banzhaf, Objective or Multi-objective? Two Historically Competing Visions for
Benefit-Cost Analysis, 85 LAND ECON. 1 (2009). For specific early instances of academic experts and
practitioners of benefit-cost analysis incorporating distributional effects, see, e.g., PARTHA DASGUPTA,
Stephen Marglin, & Amartya Sen, Guidelines for Project Evaluation (1972); A. Myrick
Freeman III, Income Distribution and Planning for Public Investment, 57 Am. ECON. REV. 494 (1967);
Freeman, Six Federal Reclamation Projects and the Distribution of Income, 3 WATER RESOURCES
RESEARCH 319 (1967); Arnold C. Harberger, On the Use of Distributional Weights in Social Cost-Benefit
Analysis, 86 J. POL. ECON S87 (1978); ROBERT H. HAVEMAN, WATER RESOURCES INVESTMENT AND
the Public Interest (1965); Arthur Maass et al., Design of Water-Resource Systems: New
Techniques for Relating Economic Objectives, Engineering Analysis, and Governmental
PLANNING (1962); Burton A. Weisbrod, Income Redistribution Effects and Cost-Benefit Analysis, in
Problems in Public Expenditure Analysis 177 (Samuel B. Chase, ed. 1968).
23 See, e.g., Kenneth J. Arrow et al., Is there a Role for Benefit-Cost Analysis in Environmental,
Health, and Safety Regulations?, 272 SCIENCE 221, 222 (1996); Adler, Risk Equity, supra note 6; John D.
Graham, Saving Lives through Administrative Law and Economics, 157 UNIV. PENN. L. REV. 101, §V.B
(2008); Harrington et al., Reforming Regulatory Impact Analysis, supra note 9; Olof
Johansson-Stenman, Distributional Weights in Cost-Benefit Analysis—Should We Forget about Them?,
81 LAND ECONOMICS 337 (2005); Olof Johansson-Stenman, On the Value of Life in Rich and Poor
Countries and Distributional Weights Beyond Utilitarianism, 17 ENVTL & RESOURCE ECON. 299 (2000).
24 See H.M. TREASURY, THE GREEN BOOK: APPRAISAL AND EVALUATION IN CENTRAL
GOVERNMENT 24-25, 91-96 (2003), available at http://www.hm-treasury.gov.Uk/d/green_book_
complete.pdf
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projects, and the Office of Management and Budget (hereinafter, OMB) approves this practice.25
For example, OMB has recommended that "when benefits and costs have significant
distributional effects, these effects should be analyzed and discussed, along with the analysis of
net present value." It elaborates:
Analysis should aim at identifying the relevant gainers and losers from policy
decisions. Effects on the preexisting assignment of property rights by the
program under analysis should be reported. Where a policy is intended to benefit
a specified subgroup of the population, such as the poor, the analysis should
consider how effective the policy is in reaching its targeted group.26
Last, but certainly not least, the last three Presidents of the United States have embraced this
perspective. In setting forth a "statement of regulatory philosophy and principles," President
Clinton's Executive Order 12,866 included "distributive impacts" and "equity" as part of benefits,
broadly construed.27 Meanwhile, President Obama has called for OMB to produce a set of
recommendations for a new Executive Order, with attention to "the role of distributional
considerations, fairness, and concern for the interests of future generations.28" All these
authorities—political, academic, and historical—have understood that documenting
distributional effects is essential for understanding the effect of regulatory actions on all policy
objectives, including distributional ones as well as efficiency. The relative newer objective of
25 United States Water Resource Council, Economic and Environmental Principles
and Guidelines for Water and Related Land Resources Implementation Studies (1983),
available at http://www.usace.army.mil/CECW/Documents/pgr/pg_1983.pdf; OMB, BUDGET CIRCULAR
A-94, REVISED (1992), available at http://www.whitehouse.gov/omb/circulars_a094/.
26 Id. at §10.
27 Exec. Order 12,866, §l(a), supra note 8. Amendments to EO 12,866 by Presidents Bush,
subsequently revoked by President Obama, left this language intact: see Exec. Order 13,258, 67 Fed.
Reg. 9385 (Feb. 26, 2002) and Exec. Order 13,422, 72 Fed. Reg. 2763 (Jan. 18, 2007); Exec. Order
13,497 74 Fed. Reg. 6113 (Jan. 30, 2009).
28 See Harrington et al., Reforming Regulatory Impact Analysis, supra note 9, at 12.
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environmental justice only reinforces the importance of documenting these effects, both for the
sake of public participation and, ultimately, for the design of regulations.
II. Diffusing the situation
EPA approach to environmental justice is limited in another respect as well. In particular, it has
tended to focus mainly on local environmental problems, discrete in space. For example, EPA's
Environmental Justice Strategy and its Toolkit for Assessing Potential Allegations of
Environmental Injustice speak in terms of "major facilities" and "sites," emphasizes the activities
of the Office of Solid Waste and Emergence Response (OSWER), brownfields remediation, and
the permitting of hazardous waste facilities under the Resource Conservation and Recovery Act
(RCRA) or the permitting of air emissions under the Clean Air Act.29
This focus is understandable, for since its origins in the 1982 protests in Warren County,
NC over hazardous waste siting and in the early research of Robert Bullard on solid waste siting
in Houston, the three pillars supporting "environmental justice"—activism, research, and
policy—have traditionally focused on discrete sources of pollution to be found at specific points
in space.30 This local perspective greatly simplifies questions about the extent of the market and
29 EPA, Environmental Justice Strategy, Supra note 10 at 11, 18-25; EPA, Toolkit for
Assessing Potential Allegations of Environmental Injustice (2004) passim, e.g. §4.1,
Appendices A-C, available at www.epa.gov/compliance/ej/resources/policy/ej-toolkit.pdf. There are
some exceptions: for example, in addition to brownfields cleanup and enforcement of pollution permits,
EPA's environmental justice demonstration projects include abatement of lead in paint and plumbing and
general education programs (see EPA, ENVIRONMENTAL JUSTICE STRATEGY, Supra note 10 at 18-25).
30 The first generation of research in the 1980s, following the Warren Co. episode, followed up with
examinations of communities near hazardous waste facilities: see GAO, SITING OF HAZARDOUS WASTE,
supra, note 2; UNITED CHURCH OF CHRIST, TOXIC WASTES AND RACE, supra, note 2. Soon after, the
second generation of studies in the 1990s looked largely at large polluters listed in the Toxics Release
Inventory: see, e.g., Arora & Cason, Do Community Characteristics Influence Environmental Outcomes,
supra, note 2; Brooks & Sethi, The Distribution of Pollution, supra, note 2; Sadd et al., "Every Breath
You Take...supra, note 2.
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the appropriate spatially scale of analysis, though it by no means eliminates them.31
But this local approach is also limiting, making it difficult to think about diffuse
pollutants, widely dispersed through the water or air. And many—perhaps most—pollutants fall
into this category. Even when released from point sources, many pollutants disperse through
water or air. Examples include municipal water supplies contaminated with disinfectants and/or
disinfection byproducts, which disperse throughout the service area, and the long-range transport
of air pollutants like fine particulates and ozone. Other pollutants are widely dispersed even at
the point of emissions. Examples include air pollution from mobile sources and pathogens like
Cryptosporidium and giardia from livestock operations. Arsenic in drinking water is a
particularly striking example, as it may enter water supplies through groundwater contaminated
by arsenic occurring naturally in soil and rock, as well as from industry and agriculture. Such
pollutants range from EPA's historical priorities (pathogens in drinking water, criteria air
pollutants) to more recent concerns (disinfection byproducts, air toxics).
And, in fact, the academic literature has long moved on from the bread-and-butter work
of comparing the demographics around RCRA facilities, TRI facilities, or similar discrete sites.
For example, Michael Ash and Robert Fetter have compared the distribution of modeled
concentrations of air toxics—that is an entire spatial surface of pollution—to the distribution of
demographic groups across space.32 Similarly, others have compared the spatial distribution of
31 See generally, Douglas L. Anderton et al., Environmental Equity: The Demographics of
Dumping, 31 DEMOGRAPHY 229 (1994); Brett M. Baden, Douglas S. Noonan, & Rama Mohana Turaga,
Scales of Justice: Is There a Geographic Bias in Environmental Equity Analysis?, 50 J. ENVTL
PLANNING & MGMT 163 (2007); Paul Mohai & Robin Saha, Reassessing Racial and Socioeconomic
Disparities in Environmental Justice Research, 43 DEMOGRAPHY 383 (2006).
32 Ash & Fetter, Who Lives on the Wrong Side of the Environmental Tracks?, supra, note 2.
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ozone, a criteria air pollutant, to the spatial distribution of demographic groups.33
Environmental justice considerations are still relevant to such diffuse pollutants because
there will still be spatial variation in the effects of the action—spatial variation which may be
correlated with demographics. Such correlations may arise for at least three reasons. First, the
action may affect pollution differently in different locations, and those effects may be spatially
correlated with demographic patterns. Second, even if the effects of an action on pollution levels
were uniform in space, other spatial differences may imply differences in the actual outcomes of
interest. For example, if the concentration-response function relating pollution levels to health
effects or other impacts is non-linear, then variation in background levels of pollution may result
in different effects of even a uniform change in pollution. (For instance, there may be no effect
of a decrease in pollution if it is already below a threshold.) Similarly, differences in background
weather or climate may interact with a given change in pollution to produce differential effects.
Or, differences in local residents' opportunities to avoid or mitigate pollution may imply different
effects from a given change in pollution. For example, access to mass transit, air conditioning,
or health care may differ across space. If these opportunities interact with pollution levels in
important ways, and if they are correlated in space with demographics, then again the impact of
an action may differ across groups.
Third and finally, even with identical changes in pollution and identical background
conditions, different groups may have differential responses to a given change in pollution
because of something about the group itself. Such group-level responses could arise from
genetic differences, differences in economic conditions, and/or differences in background health
33 Brooks Depro & Christopher Timmins, Residential Mobility and Ozone Exposure: Challenges
for Environmental Justice Policy (2009), unpublished manuscript; Florenz Plassmann & Neha Khanna,
Household Income and Pollution, 15 J. ENVT. & DEVELOPMENT 22 (2006).
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and nutrition. Sometimes there is evidence of such differential impacts on sensitive subgroups
like children or women of child-bearing age, but typically our understanding of concentration-
response relationships is insufficient to document differential effects.
The differential effects of concern in the context of environmental justice have always
been for particular groups of people: low-income and minority populations, including African-
Americans, Hispanics, Asian-American, and Native Americans.34 But traditionally,
environmental-justice analysts and researches have taken their logical unit of analysis to be the
"community," located in a fairly confined place. For example, one might define a community
which is proximate to a hazardous waste facility, or that is surrounded by a number of pollution
sources. One might then look for a suitable "reference community" for purposes of comparison.
One then looks at the demographic groups living in these communities.35
In the context of dispersed pollutants, it is better to reverse this logic. That is, the logical
unit of analysis should be the group itself. One would then analyze the effects of an action on
different groups, partly as a function of the communities in which they live. Put in these terms,
incorporating environmental justice considerations into RIAs boils down to assessing the
distributional impacts of an action. And such distributional considerations have a long history in
benefit-cost analysis.36 To be sure, environmental justice is a specific instance of such
distributional analyses, one focused on environmental applications and on the demographic
34 Naturally, the self-claimed goal (and title) of EO 12,898 itself is "To Address Environmental
Justice in Minority Populations and Low-Income Populations." For EPA's definition of "minority" in this
context, see EPA, TOOLKIT, supra, note 29, at 17, 44.
35 For this approach in the classic studies, see, e.g., BULLARD, DUMPING IN DIXIE, supra, note 1;
GAO, Siting of Hazardous Waste Landfills, supra, note 2; United Church of Christ, Toxic
WASTES AND Race, supra, note 2; Been, Locally Undesirable Land Uses, supra, note 2. For this
approach in EPA's guidance, see, e.g., EPA, TOOLKIT, supra, note 29, at §4.1.
36 Supra notes 22-26.
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groups that have been identified by previous environmental justice research, by the communities
themselves, and by agency guidance as being most at risk or facing the greatest cumulative
burden of exposure to pollution. But as it is a special case of this wider issue, environmental
justice analysts have the advantage of being able to tap into this larger literature.
One common argument against incorporating distributional effects into benefit-cost
analysis is that government projects and regulations should be based only on efficiency, while
distributional considerations should be dealt with in other policy settings, especially the tax code,
welfare programs, and so forth. This perspective is implicit in the Kaldor-Hicks potential
compensation tests commonly invoked in benefit-cost analysis, which requires only that losers
from an action can potentially be compensated for their losses out of the winners' gains, not that
they are actually made whole inside the policy.37 Similarly, it is implicit in Richard Musgrave's
three-branch theory of government (allocation, distribution, stabilization), as enshrined in his
classic textbook on public finance.38 It is also implicit in more modern work on optimal
taxation, in which distributional effects are considered around the optimum.39
To this argument there are two rejoinders. First, actual compensations for the
distributional effects of government projects and regulations are exceedingly rare, if not an
outright fiction. At any rate, the tax system is far from optimal, so any regulatory action that
effects a desirable transfer in more efficient ways than is being done through the tax code should
37 See J.R. Hicks, Foundations of Welfare Economics 49 ECON. J. 696 (1939); N. Kaldor, Welfare
Propositions of Economics and Interpersonal Comparisons of Utility 49 ECON. J. 549 (1939).
38 Richard A. Musgrave, The Theory of Public Finance (1959).
39 See, e.g., Aanund Hylland & Richard Zeckhauser, Distributional Objectives should Affect Taxes
but not Program Choice or Design 81 SCANDINAVIAN J. ECON. 264 (1979); Louis Kaplow, On the
(Ir)Relevance of Distribution and Labor Supply Distortion to Government Policy 18 J. ECON.
Perspectives 159.
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be given credit for this achievement.40 Second, as Stephen Marglin has argued, socially we care
not only about the size of the pie and its distribution, but also the method of slicing it. Many
would prefer to see a disadvantaged group aided through jobs or environmental protection than
through the dole, for example.41 Perhaps the simplest way of making the point is that if
redistribution is a national objective, then any regulatory action that promotes this objective,
ceteris paribus, is obviously preferable to one that doesn't.
Perhaps the best example of recent work incorporating distributional issues into benefit-
cost analyses of environmental regulations is work by Ronald Shadbegian, Wayne Gray, and
Cynthia Morgan on the distributional effects of the sulfur dioxide trading program enacted in the
1990 Clean Air Act Amendments.42 They compute estimated changes in particulate matter, and
the consequent changes in mortality, at the county level. Using a model of the US electricity
sector and its costs of abating pollution43, they compute control costs at the state level. Then,
assuming that costs are passed on to consumers and that all households consume the same
amount of electricity, they compute per-capita costs at the state level. Finally, they compute
estimated net benefits by different demographic groups, including African-Americans,
Hispanics, and the poor. More recently, Ellen Post et al. have undertaken a still more detailed
40 See Joel Slemrod & Shlomo Yitzhaki, Integrating Expenditure and Tax Decisions: The Marginal
Cost of Funds and the Marginal Benefit of Projects, 54 NATIONAL TAX J. 189 (2001).
41 Stephen A. Marglin, Objectives of Water-Resource Development: A General Statement, in
MAASSETAL., Design, supra note 22, at 17-18, 66-67.
42 Ronald J. Shadbegian, Wayne Gray, & Cynthia Morgan, Benefits and Costs from Sulfur Dioxide
Trading: A Distributional Analysis, in ACID IN THE ENVIRONMENT: LESSONS LEARNED AND FUTURE
PROSPECTS (Gerald R. Visgilio & Diana M. Whitelaw eds., 2006).
43 Viz., A. Denny Ellerman, et al., EMISSIONS TRADING UNDER THE US ACID RAIN PROGRAM:
Evaluation of Compliance Costs and Allowance of Market Performance (1997).
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distributional analysis of the highway diesel fuel rule, but do not consider benefits and costs.44
Many of EPA's RIAs are already detailed enough, and make use of scientific and
economic models sufficiently rich enough, that extending them to incorporate such distributional
issues would require only modest additional effort. EPA's RIA for its arsenic rule and its
disinfectants and disinfection byproducts rule are cases in point.45 For example, in the arsenic
RIA, EPA identified a distribution of costs across individual water treatment systems (from
under 100 people served to over 1 million). In some cases, individual systems were modeled, in
others, it categorized systems by statistical distributions. EPA considered the capital and
operating costs of achieving a proposed arsenic standard using various treatment technologies,
given background arsenic levels at each system. It then computed the least-cost method for
individual facilities to achieve a standard, given background arsenic levels. These costs reflect
the economies of scale enjoyed by larger facilities as well as the distribution of background
arsenic levels.46 Similarly, EPA determined benefits for its arsenic rule based on the population,
by age category, exposed to various levels of arsenic. This combination of exposures and
exposed populations implied the number of cases of bladder cancer that could be expected with
and without the regulation.47
44 Ellen Post et al., Methodology for Distributional Benefit Analysis of a National Air Quality Rule
(2009), unpublished paper, available at http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE-0520-
01.pdf/$file/EE-0520-01.pdf. For the original RIA of the diesel rule, see EPA, REGULATORY IMPACT
Analysis: Heavy Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur
CONTROL Requirements (2000), available at http://epa.gov/otaq/highway-diesel/regs/2007-heavy-duty-
highway.htm.
45 EPA, Arsenic in Drinking Water Rule, supra note 13; EPA, Economic Analysis, supra
note 14.
46 See EPA, ARSENIC IN DRINKING WATER RULE, supra note 13 at §6.
47 See Id. §5.
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With these data and with this conceptual architecture, EPA essentially has already
approached a distributional analysis in the style of Shadbegian et al. It simply did not follow
through to break them out and report them in the same way. In particular, once EPA had
determined benefits and costs by water treatment system, virtually all the steps needed to
compute costs and benefits by demographic group were completed. All that would remain to be
done would be to determine who lives in each of those systems, a small additional step in light of
the tremendous amount of work that was done in the analysis.48
III. Distribution of What?
A. General Considerations
How best to incorporate distributional effects into RIAs will depend on the distributional
objectives. More equity, ceteris paribus, may be desirable, but equity of what? Of exposure to a
particular contaminant (arsenic, say, in the case of the arsenic rule, or disinfection byproducts for
the Stage 2 rule?) Of environmental health generally? Or, most generally, over-all welfare? In
some respects, this is a false choice. We care about environmental health because it effects over-
all welfare.
Accordingly, the most fundamental distributional objective is equity in welfare. Because
it is the most fundamental, it is this objective that should guide our thinking about incorporating
environmental justice considerations into RIAs. This conclusion may seem counter-intuitive.
After all, doesn't the "environmental" in "environmental justice" imply a concern about equity in
environmental health per se? Actually, not necessarily. Instead, we can interpret it as implying a
48 EPA individually modeled only the water treatment facilities serving the largest populations.
Smaller facilities were characterized by a statistical distribution. This lowers the accuracy of both the
estimated aggregate benefits as well as potentially estimated distributional effects, but in principle does
not make it harder to extend the analysis to the latter, so long as the locations of the set of facilities in the
statistical analysis are known.
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concern about the environment insofar as it affects over-all welfare.
Indeed, focusing on more narrow types of equity could well result in counter-intuitive
and unintended, even perverse, decision rules for policy. Suppose for example that there is some
particular environmental contaminant which minorities are actually less exposed to than whites.
Suppose further than a particular regulatory action under consideration turns out to reduce the
environmental concentrations of this contaminant, with reductions especially large in the
minority communities.49 If the underlying objective motivating distributional analyses were
equity in a particular contaminant, the RIA would have to down-weight the net benefits of this
action on the grounds that it helped the minority group! This is hardly a move toward greater
justice if the minority group is otherwise disadvantaged. The problem of course lies in the
mischaracterization of the objective. If the objective were instead greater equity in over-all
welfare, the benefit-cost analysis of this regulation would over-weight the net benefits of the
action for its preferential treatment of the minority group.
To say that we are concerned with the distribution of over-all welfare is a start, but other
questions about what constitutes welfare soon follow. An early step of any RIA is to identify the
potential impacts of an action which need to be analyzed. Similarly, an early step of any benefit-
cost analysis is to identify those impacts to be monetized. Should all of those effects be of
interest for any distributional analysis? The relevant effects will differ on a case-by-case basis,
but four general issues warrant discussion, two on the cost side and two on the benefit side.
B. Cost-side Considerations
First, and most important, it is essential to emphasize that over-all welfare includes costs
49 Though this scenario is unlikely in most cases, it might well happen for some particular
contaminant. In any case, I propose it only as a thought experiment.
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as well as benefits. Thus, it is not sufficient to look at the distribution of environmental benefits.
It is the distribution of net benefits that is of ultimate interest. Wherever possible, RIAs should
document the distributional effects of net benefits, as in the work by Shadbegian et al. on the
clean air act amendments.50 As an alternative, it may be sufficient to separately document the
distribution of benefits and costs. As noted above, OMB specifically mentions costs as well as
benefits when discussing distributional effects.51 Moreover, EPA has recognized the importance
of costs within an expansive framework for understanding environmental justice. In particular,
EPA's Guidance for Incorporating Environmental Justice Concerns in EPA's NEPA Compliance
Analyses urges "consideration of the distribution of costs to pay for environmental projects," as
when there are user fees, for example. It also notes that populations intended to benefit from
regulations may rely on polluting industries for jobs and tax revenue, so that they may
experience economic costs indirectly.52
C. Indirect Costs
The importance of jobs and the local tax base to citizens' welfare leads directly to the
second issue, namely, indirect effects transmitted through markets (or, in the economist's jargon,
so-called "general equilibrium" effects). Wherever possible, such effects should be considered in
RIAs of dispersed pollutants. This recommendation does not follow simply from a commitment
to thoroughness. It follows from research showing the importance of general equilibrium effects
on the distribution of net benefits.53 For example, the indirect effects of a regulatory action on
50 Shadbegian et al., Benefits and Cost from Sulfur Dioxide Trading, supra note 42.
51 OMB, Budget Circular A-94, supra note 25, at §10.
52 EPA, GUIDANCE, supra note 4 at §2.3, Exhibit 3/
53 See generally DON FULLERTON, DISTRIBUTIONAL EFFECTS OF ENVIRONMENTAL AND ENERGY
Policy (2009).
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welfare through land markets may be particularly important. Because pollution is undesirable,
the demand for housing in a polluted neighborhood is lower than in a clean neighborhood,
lowering housing values. Poor people may live in these neighborhoods because they cannot
afford to purchase more expensive housing in cleaner locations.54 This is not to say that they do
not value a clean environment as much as richer households. But because of their limited
income, their willingness to pay for a clean environment is lower. The reverse of this logic is
that when neighborhoods improve, demand increases and housing values rise. But housing
prices may rise by more than existing residents' values for the environment, as richer gentrifying
households bid up housing values by their own higher willingness to pay for the improvement.
If the incumbent residents owned their home, they would of course reap the capital gains from
these appreciating housing values. But in the US, 83 percent of people living in poverty are
renters. These residents would have to pay higher rents, and the increase in these rents may
more than offset the direct benefit they receive from the environmental improvement.55
My colleagues and I have called this process "environmental gentrification."56 In
54 This raises the possibility that disadvantaged groups sometimes "come to the nuisance," as
opposed to polluting facilities coming to their neighborhoods. For evidence on both sides of this debate,
see Baden & Coursey, The Locality of Waste Sites, supra note 2; H. Spencer Banzhaf & Randall P.
Walsh, Do People Vote with their Feet? An Empirical Test ofTiebout's Mechanism, 98 Am. ECON. REV.
843 (2008); Been, Locally Undesirable Land Uses, supra, note 2; Vicki Been, Coming to the Nuisance or
Going to the Barrios? A Longitudinal Analysis of Environmental Justice Claims 34 ECOLOGY L. Q. 3
(1997); Depro & Timmins Residential Mobility and Ozone, supra note 33; Manuel Pastor, Jim Sadd, &
John Hipp, Which Came First? Toxic Facilities, Minority Move-in, and Environmental Justice, 23 J.
URBAN Affairs 1 (2001); Wolverton, The Role of Demographic and Cost-Related Factors, supra note 2.
Also, see generally Banzhaf & McCormick, Moving Beyond Cleanup, supra note 2.
55 See Id. For a more whimsical take, see Armen Alchian, The Beneficiaries of Cleaner Air, in Tl III
Collected Works of Armen A. Alchian, Vol. 2: Property Rights and Economic Behavior
(Daniel K. Benjamin, ed. 2006).
56 Holger Sieg et al., Estimating the General Equilibrium Benefits of Large Changes in Spatially
Delineated Public Goods, 45 INT'L ECON. REV. 1047, 1074 (2004).
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empirical work examining air quality improvements in Los Angeles, we show that incorporating
these general equilibrium effects significantly alter the distribution of net benefits of air quality
improvements, with renters in those communities which began as the most polluted, but which
saw the greatest improvement in air quality, being harmed the most. In extensions of this work
re-examining benefit-cost analyses of the Clean Air Act, we show that these effects have
tremendous importance for the relative winners and losers of actual environmental policies.57
Far from being only of academic interest, these gentrification effects have been identified by the
National Environmental Justice Advisory Commission (,hereinafter NEJAC) as an important
unintended consequence of some environmental policies such as brownfields redevelopment.58
Land markets are not the only avenue for important general equilibrium effects with
distributional implications. Compliance costs fall on firms and thence the owners of capital, who
are generally rich, but some of those costs may be passed on through higher prices. For example,
the clean-air act has substantially raised the price of energy-intensive goods.59 If energy-
intensive goods are consumed primarily by the poor, the distribution of costs could be regressive.
Moreover, if regulatory actions work through cap-and-trade-style permit markets, they produce
assets with marketable value. If those assets are given to firms (as when pollution permits are
grandfathered), they create new sources of wealth for the owners of capital (primarily the rich).
57 V. Kerry Smith et al., General Equilibrium Benefits for Environmental Improvements: Projected
Ozone Improvements under EPA's Prospective Analysis for the Los Angeles Air Basin 47 J. ENVTL.
ECON. & MGMT 559 (2004); see also Corbett A. Grainger, The Distributional Effect of Pollution
Regulations: Rental Housing and Air Quality Improvements (2009), unpublished manuscript available at
http://www.econ.ucsb.edu/~grainger/.
58 NEJAC, Unintended Impacts of Redevelopment and Revitalization Efforts in Five
Environmental Justice Communities, available at http://www.epa.gov/compliance/resources/
publications/ej/nej ac/redev-revital-recomm-9-27-06 .pdf
59 See Michael Hazilla & Raymond J. Kopp, Social Cost of Environmental Quality Regulations: A
General Equilibrium Analysis, 98 J. POL. ECON. 853 (1990).
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Consequently, regulatory actions with grandfathered permits, such as the US SO2 trading
program, appear to be quite regressive when the indirect effects of asset prices and output prices
are considered. The poor bear the burden of higher electricity prices, while the wealthy, through
their ownership of capital, receive the rents from the permit allocation.60
The importance of such general equilibrium effects for benefit-cost analysis has been
recognized by OMB. OMB notes:
Individuals or households are the ultimate recipients of income; business
enterprises are merely intermediaries. Analyses of distribution should identify
economic incidence, or how costs and benefits are ultimately borne by households
or individuals.
Determining economic incidence can be difficult because benefits and costs are
often redistributed in unintended and unexpected ways. For example, a subsidy
for the production of a commodity will usually raise the incomes of the
commodity's suppliers, but it can also benefit consumers of the commodity
through lower prices and reduce the incomes for suppliers of competing products.
A subsidy also raises the value of specialized resources used in the production of
the subsidized commodity. As the subsidy is incorporated in asset values, its
distributional effects can change.61
In any case, the key point is that once we accept the objective to be over-all welfare, then all
channels by which a regulatory action significantly affects welfare should be documented in an
60 See Ian W.H. Parry, Are Emissions Permits Regressive? 47 J. ENVTL. ECON. & MGMT 364
(2004); Lawrence H. Goulder & Ian W.H. Parry, Instrument Choice in Environmental Policy, 2 REV.
ENVTL. ECON. & POLICY 152 (2008).
61 OMB, Budget Circular A-94, supra note 25, at § 10b.
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RIA.
Whether the most important general equilibrium effects are to be found in land markets,
product markets, or labor markets, or whether they are important at all, will differ from case to
case. Land markets and gentrification may be particularly important for the traditional case of
locally undesirable land uses and large point sources of pollution. Because they are so obviously
observed by residents, these sources of pollution are easily reflected in land prices. But some
widely dispersed pollution, like the criteria air pollutants, are also fairly easy to observe and have
been shown to affect property values.62
I). Inter-group Heterogeneity in Values
To these two cost-side considerations about what constitutes over-all welfare we can add
two benefit-side considerations. The third issue to consider is group-level heterogeneity in
willingness to pay for health and environmental improvements. Providing a clean environment,
like any other good, comes at the cost of other private or public goods that could have been
provided with those resources. Understanding that trade-off is the underlying motive for
regulatory impact analyses. But different groups may be willing to make those trade-offs
differently, perhaps because of differences in their ability to pay, because of their differential
access to other substitutes, or because of differences in preferences.
Introducing heterogeneity in willing to pay into benefit-cost analysis seemingly poses a
dilemma. On the one hand, we should not impose costs on one group that it is not willing or able
to bear in order to achieve some benefit that another group desires. To the contrary, we do the
62 See Patrick Bayer, Nathaniel Keohane, & Christopher Timmins, Migration and Hedonic
Valuation: The Case of Air Quality 58 J. ENVTL ECON. & MGMT 1 (2009); Kenneth Y. Chay & Michael
Greenstone, Does Air Quality Matter? Evidence from the Housing Market, 113 J. POL. ECON. 376
(2005); Grainger, Distributional Effect, supra note 57; V. Kerry Smith & Ju-Chin Huang, Can Markets
Value Air Quality? A Meta Analysis of Hedonic Property Value Models, 103 J. POL. ECON. 209 (1995).
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greatest justice to groups when we honor their ability to set their own priorities.63 On the other
hand, allowing for heterogeneity in willingness to pay for benefits appears to discriminate again
groups with lower valuations, biasing benefit-cost analysis toward rules that favor other groups.
The backlash against the "senior discount" for age-adjusted willingness to pay to avoid mortality
risks is an example of that perception.64 Such a concern is entirely valid for the standard benefit-
cost regime without distributional weights. But it is not valid for generalized benefit-cost
analysis with such weights. Indeed, this distinction might be viewed as the best argument for
why distributional weights are necessary to give benefit-cost analysis more integrity.
Consider for example policies that will save lives. The average value of a statistical life
(VSL) is $6m, but the VSL of the rich is $8m and the VSL of the poor, because of their lower
income, is $4m. By virtue of the very fact of what it means to be poor, the poor cannot afford to
pay as much money to reduce risks to their health and safety without foregoing other basic
needs, while the rich can make such purchases while only foregoing luxuries. That is, these
differences can be driven by the differences in ability to pay, even if preferences or "tastes" are
the same.
63 See, e.g., Foster, Justice from the Ground Up, supra note 6, at 802-807, emphasizing as an
example the importance of "sovereignty" for native Americans.
64 On the controversy, see Katharine Q. Seelye & John Tierny, EPA Drops Age-Based Cost Studies,
NEW YORK Times (May 8, 2003), available at http://www.nytimes.com/2003/05/08/us/epa-drops-age-
based-cost-studies.html. On the economic and empirical basis for such discounts, see generally Joseph E.
Aldy & W. Kip Viscusi, Age Differences in the Value of Life: Revealed Preference Evidence, 1 REV.
ENVTL. ECON. & POLICY 241 (2007); Mary F. Evans & V. Kerry Smith, Do We Really Understand the
Age-VSL Relationship?, 28 RESOURCE & ENERGY ECON. 242 (2006); Alan Krupnick, Mortality Risk
Valuation and Age: Stated Preference Evidence, 1 REV. ENVTL. ECON. & POLICY 261 (2007); W. Kip
Viscusi & Joseph E. Aldy, Labor Market Estimates of the Senior Discount for the Value of Statistical
Life, 53 J. ENVTL. ECON. & MNGT 377 (2007). For a critique of this practice, see Lisa Heinzerling, The
Rights of Statistical People, 24 HARVARD ENVTL. L. REV. 189, 192-94 (2000). For a rejoinder, see
Graham, Saving Lives, supra note 23.
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Consider now two policies, Policy A and Policy B, that save lives. Details of the two
policies are illustrated respectively in Tables 1A and IB. The table shows that both policies
impose gross costs of $ 1700m on the rich but nothing on the poor. Policy A saves 100 statistical
lives of the rich and 200 statistical lives of the poor, for a total of 300 statistical lives. Policy B
saves 200 lives of the rich and 50 lives of the poor, for a total of only 250 lives. Both policies
cost the same, yet Policy A saves more lives. Using the average VSL of $6m implies aggregate
net benefits of $100m for Policy A, compared to an aggregate loss of $200m for Policy B.
Because it saves more lives at the same cost, Policy A must look better using this approach. If
we use heterogeneous values, however, Policy A would generate $-900m in net benefits for the
rich and only $800m in net benefits for the poor, for an aggregate loss of $100m. Policy B
would generate $-100m in net benefits for the rich and $200m in net benefits for the poor, for a
net gain of $100m in aggregate. Policy B has higher net benefits. Thus, using heterogeneous
values, the efficiency criterion would steer us to Policy B because it saves more rich lives. This
would seem to imply that socially, we would trade 100 lives of the poor for 50 lives of the rich.
Nothing could be less just or more reprehensible.
Yet in fact, the supposed choice of Policy B does not follow from using heterogeneous
VSLs per se, but only from doing so without distributional weights. Giving greater weight to the
net benefits of the poor would have steered us back to Policy A, which intuitively is the right
choice.65 Why use heterogeneous VSLs if we are going to un-do them with the distributional
weights? The reason can be made clear with the following example.
65 More precisely, a precise relationship between the social welfare of utilities of the rich and poor,
respectively, the value of money to the rich and poor, and the value of avoiding risks to the rich and poor
can be identified that would just offset one another so as to generate equal VSLs. However, this
relationship need not hold in practice. See Johansson-Stenman, On the Value of Life, supra note 23 at
304.
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Consider two different policies, Policy C and Policy D, illustrated respectively in
Tables 1C and ID. Both policies cost $700m, but the split is $350 for rich and poor alike for
Policy C, whereas with Policy D the split is $600m for the rich and $100m for the poor. Both
policies save 150 lives, but Policy C saves 100 of the 150 from the rich, while Policy D saves
100 of the 150 from the poor. Using homogenous VSLs of $6m, we see that the aggregate net
benefits of both policies are $200m. Using the efficiency criterion alone, the two policies appear
to be tied. Looking next at distributional considerations, we would say that Policy C is better,
because compared to Policy D it results in a costless transfer of $50m from the rich to the poor.
Policy C looks more favorable, so using these criteria we would choose it over Policy D. But
this is the wrong conclusion. When we consider the groups' true VSLs, we now see that both
groups are better off under Policy D than Policy C. Under Policy D, the poor get $100m in net
benefits versus only $50m under Policy C, while the rich get $200m versus $50m.
The problem with Policy C is that the additional 50 lives saved from the poor over
Policy D come at an incremental cost to the poor of $250m, while the group is only willing to
pay $200m for those statistical lives. These costs may be direct effects (higher cost for water or
energy) or indirect effects (higher rents or higher costs for consumer goods). In any case,
imposing homogeneity in values does violence to each group's preferences. It requires the poor
group to actually pay a cost they cannot afford: For them, more basic priorities (perhaps food
and shelter) take precedence over the reduction in pollution, whereas the rich can afford the cost.
Again, true environmental justice respects groups' own preferences rather than imposing them
from the outside.66
The reason for the seeming dilemma is that in evaluating the relative merits of Policies A
66 Foster, Justice from the Ground Up, supra note 6, at 802-807.
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and B, we jumped too quickly to the conclusion that using heterogeneous VSLs favors Policy B.
In fact, we only found that the efficiency criterion alone favored Policy B. What this actually
shows is not the importance of imposing homogeneity in willingness-to-pay values, but the
importance of considering the equity objective as well. Considering heterogeneous values, we
see that Policy A, relative to Policy B results in a transfer of $600m to the poor ($800m-$200m)
at a cost of $800m to the rich. Whether this distributional improvement is worth the loss in
aggregate benefits is not necessarily obvious to everybody. But those who would argue that
Policy A is preferable to B are essentially claiming that it is.
The only way to make the "right" choice in both comparisons (A over B and D over C) is
to consider both heterogeneity in willingness to pay and distributional objectives in the analysis.
This is a two step process. First, when comparing benefits for a group to costs for the same
group, that group's preferences should be respected. This is the only way to respect the group's
preferences and its consumer sovereignty. The result of this step is group-by-group net benefits.
Then, in the second step, group-level net benefits should be compared to one another and/or
aggregated using some kind of social weight. For example, using a social weight of 2:1 for the
poor group relative to the rich would exactly un-do the effect of the higher VSL for the rich. Net
benefits would now be $700m for Policy A and only $300m for Policy B. Thus, we would now
choose Policy A, which saves more lives, over Policy B. Policy D would continue to be chosen
over Policy C.
A logically equivalent way to arrive at the same point would be to use the same VSL for
all groups, but increase the weight on costs to the poor group. Although equivalent logically,
this framing of the analysis may be more palatable politically. It can also be easily explained by
the notion that costs to the poor are especially burdensome because of their more basic needs to
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be purchased. (In the language of economics, they have a higher marginal utility of income.)
E. Nonuse Values
The fourth and final issue to consider is the role of so-called nonuse or existence values
in distributional benefits. These are values that households have simply for things being a
certain way rather than for using them to produce some good or service.67 For example, EPA's
RIA for the regulation of cooling intake structures notes that households may hold significant
existence values for the marine life that would be spared by the new rules.68 (These values
would be in addition to use values related to subsistence or recreational fishing.) It is entirely
plausible that a stated preference study of such existence values would find that different
demographic groups hold different values for those benefits.
If so, should the distribution of nonuse values also be incorporated into an analysis of
distributional effects? One might argue in the affirmative, on the grounds that nonuse values are
a part of over-all welfare and benefits are benefits. On the other hand, if society's motivation in
considering distributional considerations is to some extent paternalistic, perhaps nonuse values
for particular groups should not be given extra weight. In any case, nonuse benefits are rarely
quantified in most RIAs anyway. Extending the analysis of more tangible benefits (or "use
values"), routinely quantified in benefit-cost analysis, to distributional considerations is a logical
first step, before nonuse benefits are similarly extended.
67 On the economic theory of nonuse values, see generally A. MYRICK FREEMAN III, THE
Measurement of Environmental and Resource Values, Ch. 5 (2nd ed. 2003). For a defense of the
role of nonuse values in federal environmental regulation, see David A. Dana, Existence Value and
Federal Preservation Legislation, 28 HARVARD ENVTL L. REV. 343 (2004). For critiques of their role,
see sources cited in Id. at note 6.
68 EPA, Economic and Benefit Analysis for the Final Section 316(b) Phase II Existing
FACILITIES Rule (2004), available at http://www.epa.gov/waterscience/316b/phase2/econbenefits/
final.htm.
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IV. Incorporating Distributional Effects.
Recognizing the importance of distributional effects is one thing; actually incorporating them
into environmental RIAs is another. How is this to be done in practice? One approach is to
incorporate the distributional objective into the efficiency objective by using distributional
weights on net benefits, and then aggregating them up to total net benefits. That is, net benefits
for poorer (or other disadvantaged) groups would receive a larger weight when aggregating up
across groups.69 For example, one common approach is to parameterize a utility function of the
M.
———
form v(y)=l ~ P" , where y is income, p is a parameters, and a is an arbitrary scaling. Then
the marginal utility of money is ayp. These marginal utilities of money would be the social
weights for a household with income >\70
Just as standard benefit-cost analyses using willingness-to-pay weights to combine
different benefit categories (morbidity, mortality, recreation, etc.) into a single aggregate benefit,
and uses dollars to combine benefits and costs into a single net benefit, so too would this
approach combine efficiency and distribution by using these social welfare weights. Thus, it has
the same advantage of reducing all the policy trade-offs to a single criterion. Accordingly, this
approach is advocated by those who have the most ambitious and lofty vision for benefit-cost
analysis and would have it be the all-purpose arbiter of policy choices.
On the other hand, this approach has two disadvantages. First, most utility functions
69 For early advocates of this approach, see, e.g., Freeman, Income Distribution, infra note 22;
Freeman, Six Federal Reclamation Projects, infra note 22; HAVEMAN, WATER RESOURCES INVESTMENT,
infra note 22; Weisbrod, Income Redistribution Effects, infra note 22. For more recent proposals, see,
e.g., Adler, Risk Equity, supra note 6; Johansson-Stenman, Distributional Weights, supra note 23;
Johansson-Stenman, On the Value of Life, supra note 23.
70 See e.g. Harberger, On the Use of Distributional Weights, supra note 22; Johansson-Stenman,
Distributional Weights, supra note 23; Johansson-Stenman, On the Value of Life, supra note 23.
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result in very severe penalties on benefits to richer households. For example, if, say, p = 2 in the
above utility function (a common rule of thumb), then a household with an income of $100,000
would be given a weight 1/100 of a household with an income of $10,000. That is, these weights
imply we would trade $100 to the first household for $1 to the second, even if the other $99 is
wasted.71 But however inefficient the tax system, surely there are more efficient ways to transfer
funds than that! Arnold Harberger has suggested that one alternative might be to cap the weights
based on the marginal cost of public funds.72 For example, based on recent evidence from
European countries, the social cost of $1 in tax revenue appears to be about $2.73 According to
this approach, the weight on net benefits for the poorest group could be no more than 2 times the
weight for the richest group, on the grounds that money can be transferred through the tax
system at that rate of efficiency.
The second disadvantage of using distributional weights is the flipside of its greatest
advantage: its attempt to reduce all objectives into a single scalar value is too ambitious by half.
In making this attempt, it arrogates too much power to the benefit-cost practitioner.74 An
alternative approach is simply to display the distributional effects alongside aggregate benefits.
For example, tables such as those accompanying the above examples could be displayed. Then,
based on this information the truly authorized decision-makers can make the judgment call about
the relative merits of an action. In other words, the decision-makers could use their own
judgments—effectively, their own distributional weights—to shape policy.
71 Harberger, On the Use of Distributional Weights, supra note 22, at SI 12.
72Id. at SI 15.
73 See Henrik Jacobsen Kleven & Claus Thustrup Kreiner, The Marginal Cost of Public Funds:
Hours Worked versus Labor Force Participation 90 J. PUBLIC ECON. 1955 (2006) 1955.
74 See generally Banzhaf, Objective orMultiobjective?, supra note 22.
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This second broad approach of simply documenting distributional effects can in turn
proceed along two paths. One path is to document the change in an index that reflects the degree
of equity.75 For example, for changes in income, one might show the change in the Gini
coefficient or an Atkinson index, two well-known summary measures of inequality.76 Recently,
this approach has been extended approach to indices of distribution in health.77 For example,
Jonathan Levy et al. compute both the total changes in lives and the change in an Atkinson index
of mortality rates resulting from a number of policies to control particulate emissions from
buses.78 They then display the combinations of the two objectives in a figure, with benefits on
one axis and the distributional index on the other and various policies plotted in the two
dimensions.79 After providing this information, this approach would stop here and allow policy
makers to make the trade-offs among these two objectives.
The second path to documenting distributional effects separately is simply to display the
effects on different groups, whether monetized as net benefits or not, in a table. This is the
approach taken by Shadbegian et al. in their work on the acid rain trading program80 and
illustrated with the simple example of Table 1 discussed previously. This approach is probably
most appropriate for incorporating environmental justice considerations into RIAs for dispersed
75 See, e.g., Adler, Risk Equity, supra note 6.
76 On both approaches, see Anthony B. Atkinson, On the Measurement of Inequality, 2 J. ECON.
THEORY 244 (1970).
77 See Jonathan I. Levy, Andrew W. Wilson, & Leonard M. Zwack, Quantifying the Efficiency and
Equity of Power Plant Control Strategies in the United States, 115 ENVTL HEALTH PERSPECTIVES 743
(2007); Jonathan I. Levy et al., Evaluating Efficiency-Equality Tradeoffs for Mobile Source Control
Strategies in an Urban Area, 29 RISK ANALYSIS 34 (2009).
78 Id.
19 Id. at 42.
80 Shadbegian et al., Benefits and Cost from Sulfur Dioxide Trading, supra note 42.
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pollutants, for two reasons.
First, even choosing a summary statistic to capture the distribution of an effect, such as
the Atkinson index, unnecessarily imposes a judgment about distributional tradeoffs. A policy
analyst would have to impose assumptions about the importance of inequity, and not just as
measured by the variance of the distribution but by higher moments as well.81 Little empirical
evidence being available to justify any assumptions, the analyst would imply a degree of false
precision.
Second, identifying distributional effects only in a single summary statistic runs counter
to the goal of providing information of interest to various demographic groups. In contrast,
documenting the net benefits across groups would provide the most information to the public as
well as to policy makers. In the short run, fully informing the public of distributional effects in
this way would facilitate public comments on specific regulations; in the long-run, it would
empower citizens to shape the legislative agenda. In this respect, providing information on
distributional effects it is consistent with one of the leading goals of EO 12,898 and EPA's
interpretation of it: public participation.82
V. Conclusions
Finding an appropriate way to incorporate environmental justice considerations into policy-
making has been a procedural challenge since President Clinton issued Executive Order 12,898
81 That is, unless one income distribution second-order stochastically dominates another, there may
not be a clear-cut ranking between the two. Different indices will variously weight different portions of
the income distribution, some emphasizing realizations near the median, others in the tails of the
distribution. Another way to state this is that different inequality indices are consistent with different
social welfare functions. See generally, AMARTYA SEN & JAMES FOSTER, ON ECONOMIC INEQUALITY
(2nd ed. 1997).
82 See supra text accompanying notes 15-19 and references therein.
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over 15 years ago. Moreover, environmental justice continues to be overshadowed by efficiency
considerations as embodied in benefit-cost analysis.
This article has argued that both types of analyses can be enhanced by bringing them
closer together. In particular, the most fruitful way to think about incorporating environmental
justice consideration into RIAs is to draw on the much older tradition of incorporating
distributional effects into benefit-cost analysis. Environmental justice considerations are a
specific form of such distributional effects, effects specifically working through environmental
channels and on the poor and/or minorities.
There are many ways to incorporate distributional analyses into RIAs and specifically
benefit-cost analyses, from using distributional weights to simply documenting them in a table as
a side display. Side displays may be the most feasible scientifically, the most pragmatic
politically, and the most informative for environmental justice communities and other
stakeholders.
By providing such distributional information, EPA would further its environmental
justice objectives, by providing the information that all groups, including the poor, minorities,
and environmental justice communities, need to understand the impacts of a regulatory action.
By incorporating such information into its RIAs, EPA would integrate environmental justice
considerations into its development of regulations. Finally, by actually allowing the new
information to inform the design and selection of regulations so as to better protect
disadvantaged groups, adding distributional impacts to RIAs would improve the distributive
justice associated with EPA's actions as well as the procedural justice.
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Table 1A. Benefit-Cost Analyses for Policy A
Benefits
Benefits
Net Benefits
Net Benefits
Lives
without
with
without
with
Group
Costs
Saved
Heterogeneity
Heterogeneity
Heterogeneity
Heterogeneity
Rich
$ 1700m
100
$600m
$800m
-$ 1100m
-$900m
Poor
0
200
$ 1200m
$800m
$1200m
$800m
Total $1700m 300 $1800m $1600m $100m -$100m
Table IB. Benefit-Cost Analyses for Policy B
Group
Costs
Lives
Saved
Benefits
without
Heterogeneity
Benefits
with
Heterogeneity
Net Benefits
without
Heterogeneity
Net Benefits
with
Heterogeneity
Rich
$ 1700m
200
$1200m
$ 1600m
-$500m
-$100m
Poor
0
50
$300m
$200m
$300m
$200m
Total
$ 1700m
250
$1500m
$ 1800m
-$200m
$100m
Benefits without heterogeneity in willingness to pay are based on a VSL of $6m; benefits with heterogeneity are
based on a VSL of $8m for the rich and $4m for the poor.
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Table 1C. Benefit-Cost Analyses for Policy C
Benefits Benefits Net Benefits Net Benefits
Group
Costs
Lives
Saved
without
Heterogeneity
with
Heterogeneity
without
Heterogeneity
with
Heterogeneity
Rich
$350m
50
$300m
$400m
-$50m
$50m
Poor
$350m
100
$600m
$400m
$250m
$50m
Total
$700m
150
$900m
$800m
$200m
$100m
Table ID. Benefit-Cost Analyses for Policy D
Group
Costs
Lives
Saved
Benefits
without
Heterogeneity
Benefits
with
Heterogeneity
Net Benefits
without
Heterogeneity
Net Benefits
with
Heterogeneity
Rich
$600m
100
$600m
$800m
$0
$200m
Poor
$100m
50
$300m
$200m
$200m
$100m
Total
$700m
150
$900m
$ 1000m
$200m
$300m
Benefits without heterogeneity in willingness to pay are based on a VSL of $6m; benefits with heterogeneity are
based on a VSL of $8m for the rich and $4m for the poor.
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