Risk Regulation: Technocratic and Demo-
cratic Tools for Regulatory Reform
Jeremy D. Fraiberg and Michael J.Trebilcock”
This article reviews the empirical evidence on the
results of regulation of health and safety risks. It notes
dramatic variances in the costs per life saved of various
health and safety regulations which implies serious
misallocations of social resources. The authors argue
that problems of over and under regulation are the re-
sult of political and regulatory processes insufficiently
disciplined by technocratic tools, especially scientific
risk assessment and cost-benefit analysis. On the other
hand, both scientific risk assessment and cost-benefit
analysis are themselves beset by numerous technical
and normative frailties, hence requiring in turn that
public participation in the regulatory process discipline
the use of these technocratic tools so that scientific and
technical analysts do not over-step the
legitimate
bounds of their disciplines and usurp value judgments
more properly made ultimately by citizens in a liberal
democracy. Hence, science must discipline politics and
politics must discipline science. The article develops a
set of institutional proposals for risk regulation de-
signed to assign appropriate roles to technocratic and
democratic tools in regulatory reform.
Cet article passe en revue les rdsultats de la r6-
glementation des risques pour la sant6 et la s6curit6. II
relive les 6carts importants dans les coflts des diverses
r~glementations visant a sauver des vies humaines,
mettant ainsi en lumi~re la mauvaise allocation de res-
sources sociales. Les auteurs sont d’avis que la
sur/sous-r~glementation est le fruit d’un processus po-
litique et r~glementaire insuffisamment disciplin6 par
des outils technocratiques tels l’6valuation du risque et
les analyses cofits-bdn6fices. Toutefois, les 6valuations
du risque et les analyses cofits-bn6fices sont 4 leur
tour soumises t des limites techniques et normatives,
n cessitant consquemment la participation publique
afin que l’analyse scientifique et technocmtique ne d6-
passe pas ses limites. Cette analyse ne doit pas usurper
le pouvoir d6cisionnel des citoyens dans une d6mocra-
tie librale. Ainsi, la science doit discipliner la politique
et vice-versa. L’article sugg~e un ensemble de m6ca-
nismes
capable
d’assigner un r6le appropri6 aux outils d6mocratiques
et technocratiques.
institutionnels de rdglementation
. Jeremy Fraiberg is a recent LL.B. graduate from the University of Toronto and will be clerking at
the Supreme Court of Canada in 1999. Michael Trebilcock is Professor of Law and Director of the
Law and Economics Programme of the University of Toronto. The authors would like to thank the
Centre for the Study of State and Market for its generous financial support. They also profited from
the comments of Anthony Ogus, Alan Brudner, Bruce Chapman, Kevin Davis, Robert Howse and
Ernest Weinrib. Martha Hundert provided valuable research assistance.
McGill Law Journal 1998
Revue de droit de McGill
To be cited as: (1998) 43 McGill L.i. 835
Mode de r6frence: (1998) 43 R.D. McGill 835
MCGILL LAW JOURNAL / REVUE DE DROIT DE MCGILL
[Vol. 43
I. Introduction
A. The Drive for Regulatory Reform
B. Market Failure and the Need for Regulation
C. Legal Failure and the Need for Regulation
D. Public Risk Perception and the Demand for Regulation
E. Government Responses
F Results of Regulation
I1. Strengths and Limitations of Science
A. Risk Assessment and Risk Management
B.
C. Sources of Uncertainty
Is Risk Assessment a Science?
Ill. Strengths and Limitations of Cost-Benefit Analysis
A. Valuation Problems – The Value of Life
B. Valuing Harms to the Environment
C. Risk Equity and Distributive Justice
D. Discount Rate
E, Cost-Effectiveness Comparisons between Regulations
F Cost-Benefit Analysis and Substitution Effects
G. Practical Difficulties
IV. Regulatory Reform
A. Mandatory Scientific Risk Assessments
B. Notice and Comment Period
C. Peer Review
D. Mandatory Cost-Benefit Analyses
E. Emergency Situations
F Decision Criteria and Judgmental Inputs
G. Risk Communication, Risk Perception, and Trust
H. The Role of the Courts
I. The Role of the Political Process
Conclusion
1998]
J.D. FRAIBERG AND M.J. TREBILCOCK- RISK REGULATION
I.
Introduction
We spend too much money for too little safety. This assertion lies at the heart of
the recent wave of political and academic criticism levied against risk regulation.’ In a
leading study, Tammy Tengs and John Graham surveyed 185 life-saving interventions
and their implementation in the United States. They found “the annual resources con-
sumed by those interventions total approximately $21.4 billion. For such a sum, we
avert approximately 56,700 premature deaths and save 592,000 years of life annually.
On average we spend about $376,000 per life or $36,100 per life year saved “‘2 In con-
sidering the opportunity costs of these investments, they conclude that if resources
were better allocated, the same $21.4 billion could save a total of 117,000 lives annu-
ally. ‘That represents an additional 60,200 lives saved, or about twice as many lives
saved relative to the status quo.'” As they comment, “it is hard to defend the regulation
of some toxins at a cost of billions of dollars per life saved while children go without
immunizations and women cannot afford good pre-natal care.”‘ To illustrate their
point, consider that approximately $17 million per life year saved is expended to pre-
vent deaths from benzene exposure, while 70 percent of women over fifty in the
United States do not receive mammograms which cost a mere $17,000 per life year
saved.! Cass Sunstein notes that in the U.S., “resources for risk reduction are badly
allocated … Some regulations cost $100,000 or less per life saved; a number cost less
than $1 million; many cost between $1 million and $5 million; and many range be-
tween $5 million and over $1 billion per life saved'”‘ W. Kip Viscusi and Richard
Zeckhauser warn that “[ulnless we reorient our risk-management policies, we will
continue to pay more than we should for health gains that are less than we could
achieve’ 7 Niels Lind, a Canadian risk expert from the University of Waterloo, echoes
‘ Environmental, health and safety regulations are all aimed at reducing hazardous risks of various
kinds. We will discuss examples of each type of regulation in this article, since our focus is on the ef-
ficient regulation of these risks generally.
2 T.O. Tengs & J.D. Graham, “The Opportunity Costs of Haphazard Social Investments in Life-
Saving” in R.W. Hahn, ed., Risks, Costs and Lives Saved: Getting Better Results from Regulation?
(New York: Oxford University Press, 1996) 167 at 172 [hereinafter Risks, Costs].
Ibid.
4 Ibid. at 180.
3Ibid. at 167. There are differences in the nature of certain risks which might explain some discrep-
ancies in allocations. That is, some risks are severely dreaded, and the public is willing to pay more to
avoid them. For example, we are willing to pay more to avoid dying in a plane crash than in an auto-
mobile accident. Moreover, how voluntary a risk is, as well as the degree to which citizens can insure
against it may also account for some of the discrepancy in resource allocation. We will address these
issues in greater detail in Parts I and IV, below.
6 C.R. Sunstein, “The Cost-Benefit State” in Chicago Working Paper in Law and Economics
(Working Paper No. 39 (2d Series)) (1996) at 9-10.
7 W.K. Viscusi & R. Zeckhauser, “Risk Within Reason” (1990) 248 Science 559, reprinted in W.
Viscusi, Fatal Tradeoffs: Public and Private Responsibilities for Risk (New York: Oxford University
Press, 1992) 149 at 149 [hereinafter cited to Fatal Tradeoffs]. See also A.I. Ogus, “Risk Management
838
MCGILL LAW JOURNAL / REVUE DE DROITDE MCGILL
[Vol. 43
this sentiment, claiming “[t]here is enormous room for improvement'” in Canadian
regulation.
This article seeks to explain why regulatory initiatives currently achieve sub-
optimal results. Although a number of factors contribute to the problem, the institu-
tional arrangements now in place are primarily responsible. The main deficiency is
that the regulatory process is undisciplined and inconsistent, often “overreacting to
small and speculative risks while leaving larger and more certain risks unattended” ‘
This article is guided by a single question: what would ideal risk regulating insti-
tutions look like in a free and democratic society? We argue that such institutions
would seek to maximize the following values: safety, efficiency, equity, and demo-
cratic process values, namely, transparency, legitimacy, and citizen participation. The
focus of this article is conceptual issues of institutional design. It does not pursue em-
pirical questions of the extent to which, or ways in which, Canadian risk regulating
agencies, either in general or in particular cases, in fact conform to or diverge from
our ideal model, which portends an important future research agenda.
A. The Drive for Regulatory Reform
Regulatory reform has become a major political issue in both Canada and the
United States. The total compliance costs of regulations in the U.S. for 1995 were es-
timated by one expert at $668 billion U.S. The average American household carries a
$7,000 yearly regulatory burden, as compared to only $6,000 for taxes.'” Environ-
mental, health and safety regulations comprise a significant portion of these costs.
While taxes are sometimes criticized for being too high, no one denies that some
taxes are necessary. Even the most ardent libertarian acknowledges the need for taxa-
tion in order to fund essential public goods, like national defence. Rather, the argu-
ment is that greater efficiencies than presently attained can be realized through low-
ering taxes. Similarly, when regulatory excesses are criticized, it should be recognized
that some regulations are necessary. From an economic point of view, regulation is
and ‘Rational’ Social Regulation” in R. Baldwin, ed., Law and Uncertainty: Risks and Legal Proc-
esses (New York: Kluwer Law International, 1997) 139.
8 N. Lind, “Policy Goals for Health and Safety” (1995) 6 Risk Analysis 639 at 643.
9 Center for Risk Analysis, “Reform of Risk Regulation: Achieving More Protection at Less Cost”,
Harvard School of Public Health, (Working Paper, March 1995) at 5.
See “Over-Regulating America” The Economist 340:7976 (27 July 1996) 19 at 19. The figures
used are those of Thomas Hopkins of the Rochester Institute of Technology. Using Hopkins’ 1992 es-
timate of $500 billion, Viscusi notes that “[t]his total can be divided up in various ways. More than
half the cost is attributable to paperwork requirements arising out of regulations, but there is also more
than $200 billion in direct costs of regulation, including costs to business. More than half of this
amount is due to environmental regulation, and much of the remainder is attributable to various forms
of risk regulation” (W.K. Viscusi, “Economic Foundations of the Current Regulatory Reform Efforts”
(1996) 10:3 J. of Econ. Perspectives 119 at 119) [hereinafter “Economic Foundation”]. For a study of
regulatory costs in Canada, see F. Mihlar, Regulatory Overkill: The Cost of Regulation in Canada
(Vancouver Fraser Institute, 1996).
1998]
J.D. FRAIBERG AND M.J TREBILCOCK- RISK REGULATION
839
justified when the marginal social benefits of each dollar spent regulating exceeds the
marginal social costs.
The drive behind regulatory reform is premised on the belief that by lessening the
regulatory burden on individuals and businesses, resources that would otherwise have
been allocated to comply with regulations would now be allocated more efficiently.
For example, when the government passes air pollution regulation requiring busi-
nesses to alter their manufacturing processes, the costs are often reflected in lower
profits for business and in higher prices for consumers. Unless there are some incon-
trovertible countervailing benefits-in this case a cleaner environment and resultant
health benefits-that exceed the costs imposed, the regulation does more harm than
good. Implicit in the critique of over-regulation is that the costs of regulation exceed
the benefits, or that if the benefits of certain regulations exceed their cost, even greater
benefits could be realized by substituting other forms of regulation.
B. Market Failure and the Need for Regulation
Reliance on markets and a system of private exchange to allocate risks is often
impracticable due to information failures of various kinds. Where product safety is
concerned, this may justify the provision of mandatory information so that consumers
can make more informed choices. But even assuming that perfect information were
made available to all consumers, the time, energy and skill required to process such
information entail additional costs. An attempt to absorb the instructions accompa-
nying a bottle of cold medicine illustrates how complex and intimidating such infor-
mation may be. Predicting consumer reactions to safety labels or instructions–espe-
cially the under- or over-reactions-will often be quite conjectural. Thus, information
failures are not always easily remedied merely through the provision of additional in-
formation. In some instances more stringent regulation, such as minimum product
standards or outright bans, may be required.” Apart from information failures, exter-
nalities (negative impacts on involuntary third parties) are another significant form of
market failure –
that may justify
regulation and to which informational policies will rarely be responsive.”
exemplified most clearly in the case of pollution –
C. Legal Failure and the Need for Regulation
Some would argue that a combination of the market, even given its imperfections,
and the tort system is preferable to more direct forms of regulation. For those risks
” For a more detailed discussion of these issues, see W.K. Viscusi & R. Zeckhauser, “Hazard
Communication: Warnings and Risk” (1996) 545 Annals of the American Academy of Political and
Social Science [hereinafter Annals] 106.
” For a discussion of market failure and the need for regulation, see R. Noll, “Reforming Risk
Regulation” (1996) 545 Annals 165 at 167, J. Krier, “Risk and the Legal System” (1996) 545 Annals
176, and D. Dewees, F Mathewson & M.J. Trebilcock, “The Rationale for Government Regulation of
Quality” in D. Dewees, ed., The Regulation of Quality (Toronto: Butterworths, 1983).
840
MCGILL LAW JOURNAL / REVUE DE DROITDE MCGILL
[Vol. 43
that do materialize in harms that were not voluntarily undertaken,” the tort system,
operating ex post, will compensate victims and create ex ante incentives for firms to
make cost-justified investments in safety precautions, thereby leading to a socially
optimal level of safety.”
This argument is problematic for several reasons. First, it assumes that there is no
legal failure of any kind. For the tort system to work optimally as an ex ante deterrent,
it is necessary that all meritorious claims are brought to trial and correctly decided (or
settled). Otherwise, tortfeasors can continue to create unreasonable risks without fear
of paying damages, and will therefore be less likely to invest in safety precautions.
However, given the enormous transaction costs, collective action and difficult causa-
tion problems many cases present, potentially successful claimants are deterred from
litigating, resulting in legal failure, which can be more properly defined as the failure
of the legal system to achieve welfare maximizing results.”
Even if we assume that there is no legal failure, there are still compelling reasons
to regulate. Consider the thalidomide tragedy. Marketed as a non-toxic drug which
“had no side effects and was completely safe for pregnant women,”” many unsus-
pecting women took the two pill-a-day suggested prescription in their first trimester to
alleviate some of the adverse effects of their pregnancy, such as morning sickness.
Tragically, the drug turned out to be teratogenic, leading to approximately 10,000 ba-
bies born worldwide'” with deformities and internal injuries of various kinds. Tort ac-
tions can only be brought after the risks have materialized into harms. It is small com-
fort to the victims and their parents to receive ex post compensation for the injuries
sustained. Full compensation for such injuries is inherently impossible. Clearly, vic-
tims and their parents would have preferred some form of direct ex ante regulation so
that the tragedy could have been averted.
D. Public Risk Perception and the Demand for Regulation
Regulation is often necessary to redress market and legal failures. When regula-
tion is tailored to address these shortcomings, it is typically cost-justified. Real-world
politics, however, is often a far cry from ideal theory. In piractice, regulations are often
sible, or externalities from other transactions.
” For instance, due to either information failures that make the voluntary assumption of risk impos-
‘4 See R. Posner, “A Theory of Negligence” (1971) 1 J. Legal Studies 29.
” For a more detailed discussion of the obstacles to litigation, see D. Dewees, D. Duff & M.J. Tre-
bilcock, Exploring the Domain of Accident Law: Taking the Facts Seriously (New York: Oxford Uni-
versity Press, 1996) [hereinafter Exploring the Domain]; D. Dewees & M.J. Trebilcock, “The Effi-
cacy of the Tort System and Its Alternatives: A Review of Empirical Evidence” (1992) 30 Osgoode
Hall L.J 57 [hereinafter”The Efficacy of the Tort System”].
‘6 The Sunday Times Insight Team, Suffer the Children: The Story of Thalidonide (London: Andre
Deutsch, 1979) at 2.
” See Report on CBC’s “National Magazine” (26 June 1996).
1998]
J.D. FRAIBERG AND M.J. TREBILCOCK – RISK REGULATION
implemented without careful analysis of the resulting costs and benefits, or with a
view to the market and legal failures that necessitate them.
Life threatening health and safety risks that potentially affect a significant seg-
ment of the population typically generate wide-spread public concern and, hence, po-
litical demands for government action. Witness the response to Rachel Carson’s influ-
ential book, Silent Spring,’8 which sparked a public outcry and increased regulation of
pesticides. Meryl Streep was instrumental in publicizing the successful campaign to
ban the sale of Alar, a pesticide frequently used on apple crops, in the late 1980s.’9
The Love Canal incident led to major U.S. environmental legislation.” The Three
Mile Island accident increased public demands for the regulation of nuclear power.
Ontario implemented stringent regulations after conducting a Royal Commission Re-
port examining asbestos-related health risks following the mesothelioma deaths of
workers and the public furor that ensued.2′ The recent mad cow crisis in England has
raised demands for increased regulation of beef.
The public’s perception of risk can directly influence the intensity of the demands
for regulation, but is often seriously flawed with systemic overestimation of the prob-
ability of some risks, such as dying in an airline crash, and the underestimation of
others.’ For example, Bruce Ames and Lori Gold point out that “pollution appears to
account for less than 1 percent of human cancer; – yet public concern and resource
allocation for chemical pollution are very high*”‘ They also note that “by weight,
there are more rodent carcinogens in a single cup of coffee than there are potentially
R. Carson, Silent Spring (Boston: Houghton Mifflin, 1962).
9See K. Harrison & G. Hoberg, Risk, Science, and Politics (Montreal: McGill-Queen’s University
Press, 1994) at 55.
‘0 See C.R. Sunstein, Free Markets and Social Justice (New York: Oxford University Press, 1997) at
309 [hereinafter Free Markets].
21 See Report of the Royal Commission on Matters of Health and Safety Arising from the Use of As-
bestos in Ontario, vols. 1-3 (Toronto: Ontario Ministry of the Attorney General, 1984) (Chair: J.
Stefan Dupr6). See also P. Brodeur, Outrageous Misconduct: The Asbestos Industry on Trial (New
York: Pantheon Books, 1985).
n Public perception of risk is not always irrational, and is at times superior to expert judgment. See
P Slovic, “Perceived Risk, Trust, and Democracy” (1993) 13 Risk Analysis 675 at 675 [hereinafter
“Perceived Risk”]. He states:
Early studies of risk perception demonstrated that the public’s concerns could not sim-
ply be blamed on ignorance or irrationality. Instead, research has showed that many of
the public’s reactions to risk could be attributed to a sensitivity to technical, social, and
psychological qualities of hazards that were not well-modeled in technical risk assess-
ments (e.g., qualities such as uncertainty in risk assessments, perceived inequity in the
distribution of risks and benefits, and aversion to being exposed to risks that were in-
voluntary, not under one’s control, or dreaded). The important role of social values in
risk perception and risk acceptance thus became apparent.
B.N. Ames & L. Swirsky Gold, “The Causes and Prevention of Cancer Gaining Perspectives on
the Management of Risk” in Risks, Costs, supra note 2,4 at 4.
MCGILL LAW JOURNAL / REVUE DE DROITDE MCGILL
[Vol. 43
carcinogenic pesticide residues in the average American diet in a year.” Alvin Wein-
berg notes that “[tihe connection between low-level insult [radiation] and bodily harm
is probably as difficult to prove as is the connection between witches and failed crops.
That our society nevertheless has allowed this issue to emerge as a serious social con-
cern … is hardly less fatuous than were the witch-hunts of the Middle Ages”
A host of factors contribute to perceived risk. Paul Slovic notes:
A major development in this area has been the discovery of a set of mental
strategies, or heuristics, that people employ in order to make sense out of an
uncertain world. Although these rules are valid in some circumstances, in oth-
ers they lead to large and persistent biases, with serious implications for risk as-
sessment. In particular, laboratory research on basic perceptions and cognitions
has shown that difficulties in understanding probabilistic processes, biased me-
dia coverage, misleading personal experiences, and the anxieties generated by
life’s gambles cause uncertainty to be denied, risks to be misjudged (sometimes
overestimated and sometimes underestimated), and judgments of fact to be
held with unwarranted confidence. 6
E. Government Responses
According to Roger Noll, the following problem presents itself: “How does one
deal with incoherence in demands for regulation by citizens?”” Governments, unfor-
tunately, have not responded well to this challenge. Instead of judiciously assessing
the magnitude of the risks that are subject to citizen demands and weighing the costs
and benefits of regulation, governments frequently respond with highly visible, direct
forms of regulation, such as ex ante or ex post bans on hazardous products, and ex
ante or ex post minimum standard setting.” Often this results in over-regulation of
some risks and the under-regulation of others.
Economic models of government may be able to account for this phenomenon.
Voters and politicians can be conceived of as demanders and suppliers of policies re-
spectively, with the behaviour of both being primarily motivated by self-interest, just
241bid at5.
Minimis Risk (New York: Plenum Press, 1987) 27 at 37-38.
A.M. Weinberg, “Science and Its Limits: The Regulator’s Dilemma” in C. Whipple, ed., De
26 p. Slovic, “Perception of Risk” (1987) 236 Science 280 at 281. See also R.E. Kasperson & J.X.
Kasperson, “The Social Amplification and Attenuation of Risk” (1996) 545 Annals 95. For a discus-
sion of the heuristics referred to, see A. Tversky & D. Kahneman, “Judgment Under Uncertainty:
Heuristics and Biases” in D. Kahneman, P. Slovic, & A. Tversky, eds., Judgment Under Uncertainty:
Heuristics and Biases (Cambridge: Cambridge University Press, 1982) c.1, reprinted from (1974) 185
Science 1124.
27 Supra note 12 at 173. See also R.G. Noll & J.E. Krier “Some Implications of Cognitive Psychol-
ogy for Risk Regulation” (1990) 19 J. Legal Studies 747.
See G. Hadfield, R. Howse & M.J. Trebilcock, “Rethinking Consumer Protection Policy” (Cen-
ter for the Study of State and Market Working Paper) (University of Toronto Roundtable on New Ap-
proaches to Consumer Law, 20 June 1996) at 6.
1998]
J.D. FRAIBERG AND M.J. TREBILCOCK- RISK REGULATION
843
as it is in private markets. Self-interest in the case of voters encompasses an infinitely
wide range of sources of utility. Self-interest in the case of politicians might also en-
tail a wide range of objectives, but an immediate objective that must be met in order to
meet more ultimate objectives would seem to be the attainment of electoral office. In
this sense, vote maximization might be viewed as the dominant factor governing poli-
ticians’ behaviour. Toward this end, direct forms of regulation are often in politicians’
best interests and will accordingly be pursued in many cases. Highly dogmatic forms
of regulation –
“hazardous products are banned” or “pollution must stop” —drasti-
cally reduce the information costs faced by voters in determining a government’s
policies on these matters and have high symbolic value in signaling strong ostensible
commitment by government to these goals. Direct regulation demonstrates to the
population that proactive steps are being taken whereas relying on market forces even
supplemented by mandated provision of information and tort liability may create the
impression that too little or nothing is being done. Even though in some instances the
more efficient response would be to rely on the market and tort system where the
costs of regulation would be higher than maintaining the status quo (although for the
reasons considered above this will not always be the case, given market and legal fail-
ures), the fact that these benefits may be unperceived by voters creates a strong incen-
tive to take more decisive action.’
Although regulators are not subject to the same direct political pressures as politi-
cians, and many regulations are implemented without any public scrutiny whatsoever,
agency problems exist which one would predict, if left unchecked, would lead to over-
regulation. Regulators regulate. The more of it they do, the more likely they are to re-
ceive prestige, power and recognition, at least within their own bureaucratic circles.
Thus, there is an incentive for regulators to regulate more aggressively than is perhaps
optimal, just as there is for politicians.
U.S. Supreme Court Justice Stephen Breyer, in his book, Breaking the Vicious
Circle, argues that inefficiencies in U.S. regulation are a product of institutional de-
sign. Three problems are particularly pressing, including what he calls “tunnel vision
of agencies” that single-mindedly pursue goals to the point of bringing about more
harm than good; “random agenda selection” where agencies respond to public opin-
ion in an undisciplined fashion; and “inconsistency” among different regulatory agen-
cies in the assessment of risks and implementation of regulations.”
The vicious circle Breyer describes, in which these three problems manifest
themselves, comes about through the dynamic interplay of another three factors: (1)
public risk perception, (2) Congressional action and reaction, and (3) uncertainties in
the technical regulatory process. The public pressures Congress on the basis of per-
ceived risk. Congress in turn pressures agencies to act. The regulatory process is initi-
ated, and there is invariably controversy and uncertainty in the risk assessments.
‘ See Dewees, Mathewson & Trebilcock, supra note 12.
See S. Breyer, Breaking the Vicious Circle: Toward Effective Risk Regulation (Cambridge: Har-
vard University Press, 1993).
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[Vol. 43
When the public learns of these uncertainties through a sensationalist media, it be-
comes more anxious and increases its pressure on Congress, leading to the vicious
circle. The results, according to Breyer, are random agenda selection, tunnel vision
and inconsistency?
F Results of Regulation
Not surprisingly, the regulatory efforts of governments have met with mixed re-
views. A recent study by Robert Hahn of the Brookings Institute concludes that “we
have reason to believe that most regulations implemented in the [U.S.] since 1990
would not pass a cost-benefit test”” The following table illustrates some of the dra-
matic discrepancies in resource allocation to various risk regulations:”
3, See ibid at 11-29.
32R.W. Hahn, “Regulatory Reform: What Do the Government’s Numbers Tell Us?” in Risks, Costs,
supra note 2, 208 at 225.
“3 Table modified from Sunstein, supra note 20 at 304, which in turn was taken from R. Lutter &
J.F Morrall, “Health-Health Analysis” (1994) 8 J. Risk and Uncertainty 59.
1998]
J.D. FRA/BERG AND M.J. TREBILCOCK – RISK REGULATION
Resource Allocation to Risk Regulations
Budgeted Regulations
Year
Agency
Cost Per Life Saved
(Millions of 1992
(U.s.) $)
Steering Column Protection
Unvented Space Heaters
Cabin Fire Protection
Passive Restraints/Belts
Fuel System Integrity
Trihalomethanes
Underground Construction
Alcohol & Drug Control
Servicing Wheel Rims
Seat Cushion Flammability
Floor Emergency Lighting
Children’s Sleepware Flammability
Side Doors
Hazard Communication
Asbestos
Grain Dust
Benzene
Ethylene Oxide
Acrylonitrile
Asbestos
Coke Ovens
Arsenic
DES (Cattlefeed)
Arsenic/Glass Manufacturing
BenzenelStorage
Radionuclides/DOE Facilities
Acrylonitrile
Benzene/Maleic Anhydride
Formaldehyde
1967
1980
1985
1984
1975
1979
1989
1985
1984
1984
1984
1974
1979
1983
1986
1987
1987
1984
1978
1989
1976
1978
1979
1986
1984
1984
1978
1984
1987
NHTSA
CPSC
FAA
NHTSA
NHTSA
EPA
OSHA-S
FRA
OSHA-S
FAA
FAA
CPSC
NHTSA
OSHA-S
OSHA-H
OSHA-S
OSHA-H
OSHA-H
OSHA-H
EPA
OSHA-H
OSHA-H
FDA
EPA
EPA
EPA
OSHA-H
EPA
OSHA-H
0.1
0.1
0.3
0.4
0.4
0.4
0.4
0.7
0.7
0.8
0.9
1.8
1.8
2.4
2.8
8.8
23.1
34.6
50.8
72.9
83.4
125.0
178.0
192.0
273.0
284.0
416.0
1,107.0
119,000.0
846
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Empirical studies of safety standards adopted by the U.S. Consumer Product
Safety Commission (CPSC) find trivial to non-existent safety benefits from regula-
tions pertaining to such matters as child-resistant caps, mattress flammability stan-
dards, bicycle safety regulations, carpet and rug flammability regulations and chil-
dren’s crib regulations. Similar studies find that even where product safety standards
do generate safety gains, often the safety benefits are outweighed by the costs, both
direct and indirect, generated by the standards. This appears to be so, for example,
with respect to urea formaldehyde foam standards, power lawnmower standards,
matchbook standards and architectural glazing standards.’ Other regulatory expendi-
tures have proved much more cost effective and beneficial –
for instance, steering
column protection, airplane cabin fire protection and passive restraints and seat belts
required in automobiles.
In light of these findings, what can be done to make risk regulation more effi-
cient? We argue that a more judicious use of science and cost-benefit analysis in the
regulatory process would lead to significant improvements. Currently, inconsistent
and irrational demands by citizens are met with undisciplined government responses,
contributing in part to the inefficient results observable today.
Science and cost-benefit analysis can help address these difficulties and discipline
politics. To achieve the primary goal of risk regulation – maximizing safety at least
cost –
two steps must be taken. The first is an assessment of the magnitude of the
risks confronted, while the second is a determination of the costs and benefits of pro-
posed regulatory responses. Consider the regulation of a supposedly carcinogenic
substance such as saccharin. Is saccharin carcinogenic? If so, how potent a carcinogen
is it? How many annual cases of cancer are expected per year given a certain level of
consumption? These questions, which are amenable to scientific inquiry, must be an-
swered if we are to regulate effectively. Once risks are assessed scientifically, cost-
benefit analyses should be conducted on proposed regulatory responses to determine
whether they are cost-justified.
The use of science and cost-benefit analysis, then, is warranted because these
technocratic tools will constrain the political process by targeting the most pressing
risks and tailoring measured responses to them. Decisions based on these techniques
are also of value because they can be more easily justified to the public, since they are
made by following a well-defined process that citizens can scrutinize.
However, both science and cost-benefit analysis are subject to serious limitations,
most notably significant uncertainties. It is extremely difficult to arrive at accurate as-
sessments of the magnitude of risks, such as the probability of a nuclear reactor core
meltdown. Perhaps even more complex is a determination of the costs and benefits of
proposed regulatory responses. For instance, in considering the costs and benefits of
m See “Efficacy of the Tort System”, Dewees & Trebilcock, supra note 15 at 101. See also Explor-
ing the Domain, supra note 15 at 223-30.
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J.D. FRAIBERG AND M.J. TREBILCOCK – RISK REGULATION
building a nuclear reactor and the appropriate safety features it should have, what is
the appropriate value to assign to a life that may be lost in the event of a nuclear acci-
dent?
In light of these pervasive uncertainties, experts are often required to make value
judgments. Sheila Jasanoff claims that “most risk analysts, regardless of their disci-
plines, would probably agree … that facts and values frequently merge when we deal
with issues of high uncertainty.'”” These value judgments are in essence a political
matter, and experts are no better than other members of the public in making them.
Thus, the role of experts, necessary to discipline the excesses of unconstrained poli-
tics, must be limited. Experts should not overstep their bounds-politics must also
discipline science. Without politics tempering science, there is a risk of excluding the
public from the decision-making process and relying on relatively unaccountable ex-
perts to make decisions that are not wholly technocratic in nature. As Jasanoff states,
“the cost of risk management by technical experts is that the public relinquishes con-
trol over important political and value choices.” ”
Part II analyzes the strengths and limitations of science, while Part III does the
same for cost-benefit analysis. Part IV contains proposals for regulatory reform-how
best to use science and cost-benefit analysis to maximize efficiency, while at the same
time providing mechanisms for the public to participate meaningfully in the regula-
tory process.
I1. Strengths and Limitations of Science
A. Risk Assessment and Risk Management
Consider first the use of science in the process of risk regulation. Following Wil-
liam Lowrance, a fundamental distinction must be made between “measuring risk, an
objective but probabilistic pursuit; and judging the acceptability of that risk (judging
safety), a matter of personal and social value judgment.” Former EPA Administrator
William D. Ruckelshaus defines the terms as follows:
Risk assessment is the use of a base of scientific research to define the prob-
ability of some harm coming to an individual or a population as a result of ex-
posure to a substance or situation. Risk management, in contrast, is the public
process of deciding what to do where risk has been determined to exist. It in-
cludes integrating risk assessment with considerations of engineering feasibility
“S. Jasanoff, “Bridging the Two Cultures of Risk Analysis” (1993) 13 Risk Analysis 123 at 123.
‘6 S. Jasanoff, Risk Management and Political Culture: A Comparative Study of Science in the
Policy Context (New York: Russell Sage Foundation, 1986) at 81.
” W.W. Lowrance, OfAcceptable Risk. Science and the Determination of Safety (Los Altos, Calif.:
William Kaufmann, 1976) at 8 [emphasis in original].
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and figuring out how to … reduce risk in the light of social, economic, and po-
litical factors.”
Lowrance elaborates that
[f]ailure to appreciate how safety determinations resolve into the two discrete
activities is at the root of many misunderstandings. In one of the most common
instances, it gives rise to the false expectation that scientists can measure
whether something is safe. They cannot, of course, because the methods of the
physical and biological sciences can assess only the probabilities and conse-
quences of events, not their value to people.”
The distinction between risk assessment and risk management is a common feature of
both the Canadian and U.S. regulatory regimes’ and is also now recognized in the
WTO Agreement on Technical Barriers to Trade and the Agreement on the Applica-
tion of Sanitary and Phytosanitary Measures negotiated during the Uruguay Round of
multilateral trade negotiations (and similar provisions in the North American Free
Trade Agreement (NAFTA)).”
A hypothetical example serves to illustrate Lowrance’s point. Suppose that a new
food additive is developed, and that the manufacturer seeks regulatory approval of the
additive before distributing it on the market. Scientists will conduct a variety of tests
and studies to determine the risks associated with the use of the product. Suppose
further that the scientists can conclude with near certainty that the additive, if con-
sumed in a certain amount over a certain period of time (for instance a typical daily
intake), will lead to a 1/1000 chance of developing cancer within five years. Have the
scientists concluded the product is safe or unsafe?
Clearly the scientists have not answered this question. They have merely provided
the decision-maker with a highly useful set of facts about the risks associated with the
product that the decision-maker can then use to make a judgment about the product’s
acceptability. Whether a 1/1000 risk of developing cancer in five years by consuming
the product is acceptable or not depends on a host of non-scientific factors. What are
the benefits of the product? Can we do without it? Are there alternatives available? If
so, how much more expensive are they? What risks do they entail? Should the product
be allowed on the market if information is provided to the consumers so that they can
voluntarily choose whether to assume the risks associated with it? Lowrance writes
that “[d]eciding whether people, with all their peculiarities of need, taste, tolerance,
3′ W.D. Ruckelshaus, “Risk in a Free Society” (1984) 4 Risk Analysis 157 at 157.
39Supra note 37 at 9 [emphasis in original].
40 See “Health Risk Determination: The Challenge of Health Protection” (Canada: Health Protection
Branch (1993)) [hereinafter “Health Risk Determination”]. See also R.A. Pollak, “Government Risk
Regulation” (1996) 545 Annals 25 at 26.
4′ Agreement Establishing the World Trade Organization, Annex IA (1994), online: WTO
Hormone case for an extensive discussion of this distinction, EC- Measures Concerning Meat and Meat
Podu(1997), WIDDoc. WT
(PaeRepoa), onin:
R
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J.D. FRAIBERG AND M.J. TREBILCOCK- RISK REGULATION
and adventurousness, might or should be willing to bear the estimated risks is a value
judgment that scientists are little better qualified to make than anyone else.”.
B. Is Risk Assessment a Science?
Accepting in principle the distinction between risk assessment and risk manage-
ment, we may ask, just how scientific is risk assessment? First, we should clarify what
is meant by “science”. Cumming writes that “[s]cience uses the ‘scientific method’ as
an investigative tool, whereby experimental observations are interpreted as supporting
or failing to support well defined hypothetical alternatives.” 3 In the context of risk as-
sessment, science seeks to answer questions such as “how hazardous is X?” If X is a
suspected carcinogen, presumably scientific studies can be conducted that can predict
the effects of exposure at different doses. If X is a complex engineering system, such
as a dam, presumably science can make predictions about the probabilities of an acci-
dent.
Science, however, is able to explain only relatively simple causal mechanisms
with a great deal of accuracy. The more complex the system and the more variables at
play, the more difficult it becomes to design effective experiments and reach definitive
conclusions. Much risk assessment is concerned with complex problems where ex-
periments are difficult to design and control. Consequently, the results of scientific
risk assessments are often uncertain. As John Graham and Lorenz Rhomberg observe,
“all studies provide some information, albeit imperfect, about the nature and magni-
tude of the true risk. Each study is a view through a blurry window at the truth.’
Alvin Weinberg has coined the term “trans-science” to describe questions which
can be asked within the framework of science but which are beyond the capacity of
science to answer:
Many of the issues which arise in the course of the interaction between science
or technology and society –
e.g., the deleterious side effects of technology, or
the attempts to deal with social problems through the procedures of science –
hang on the answers to questions which can be asked of science and yet which
cannot be answered by science. I propose the term trans-scientific for these
questions since, though they are, epistemologically speaking, questions of fact
and can be stated in the language of science, they are unanswerable by science;
they transcend science.”
In a later article, he writes “[o]ne can think of a somewhat fuzzy demarcation between
what I’ve called science and trans-science: the domain of science covers phenomena
that are deterministic, or the probability of whose occurrence can itself be stated pre-
“Supra note 37 at 9.
,R.R. Cumming, “Is Risk Assessment a Science?” (1981) 1 Risk Analysis I at 1.
,J. Graham & L. Rhomberg, “How Risks Are Identified and Assessed” (1996) 545 Annals 15 at 19.
“A. Weinberg, “Science and Trans-Science” (1979) 10 Minerva 209 at 209 [emphasis in original].
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cisely; trans-science, the domain of events whose probability of occurrence is itself
highly uncertain.”
C. Sources of Uncertainty
Uncertainty in risk assessment is inescapable. Ruckelshaus claims “[w]e should
remember that risk assessment data can be like the tortured spy. If you torture it long
enough, it will tell you anything you want to know.” The amount of uncertainty will
vary depending on the nature of the risk to be assessed. Some risks are relatively well
understood, such as the probability of being killed in a car accident or airline crash,
since much actuarial data has accumulated over the years. Even this data, however, is
unable to predict whether any particular driver or airline passenger will be killed, but
it is sufficiently accurate upon which to base well-informed policy choices. M.
Granger Morgan points out that it is considerably more difficult to assess risks where
good actuarial data are unavailable. “The development of risk assessment during the
past two decades has been in large part the story of finding ways to determine the ex-
tent of risks that have little precedent.”
Consider the risks associated with complex engineering systems, such as nuclear
reactors or hydro-electric dams. Brooks writes that
In an increasing number of cases, it is impossible to design an integral test of a
whole engineering system; one can only infer its performance theoretically by
compounding the results of experiments on separate components or by ex-
trapolating the findings of experiments in a different regime of parameters than
applicable in real life.’
Such is the case with nuclear reactors, where probabilistic risk assessments (“PRA”)
are used to measure risk. A PRA “seeks to identify all sequences of subsystem fail-
ures that may lead to a failure of the overall system” and “estimate the consequences
of each system failure so identified.”‘ A PRA is required for nuclear reactors because
of the practical impossibility of building full-scale prototypes and testing them for
their useful lives when immediate decisions need to be made about whether to pro-
ceed with the technology.
Probability risk assessments are fraught with uncertainties. In the case of nuclear
reactors, Weinberg notes that a PRA “requires two separate estimates: first, an esti-
mate of the probability of each accident sequence, and second an estimate of the con-
sequences –
caused by the uncontrolled
particularly the damage to human health –
‘ Supra note 25 at 29.
“7 Supra note 38 at 157-58.
33.
Technology & Human Values 39 at 43.
m Weinberg, supra note 25 at 29.
M. Granger Morgan, “Risk Analysis and Management” (1993) 269:1 Scientific American 32 at
“H. Brooks, “The Resolution of Technically Intensive Public Policy Disputes” (1984) 9:1 Science,
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effluents released in the accident “’51 With respect to the first estimate, Rasmussen, in
the famous WASH-1400 nuclear reactor study, noted that “his estimate of core-melt
probability might be in error by a factor of 10 –
that is, the probability may be as
high as 1 in 2000 reactor years or as low as 1 in 200,000 per [reactor year.]j
2
The estimates of the possible health effects from the uncontrolled effluents re-
leased in the event of an accident are equally difficult to ascertain. Particularly prob-
lematic is modelling the effects of low level exposure to possible toxins. Various tech-
niques are used by scientists to assess these types of risk, and regulation of possible
carcinogens and other toxic substances are based upon them.
To illustrate some of the pervasive uncertainties in the assessment of exposure to
hazardous substances, following Lave, we consider four common methods used by
scientists towards this end: (1) case clusters, (2) structural toxicology, (3) long-term
animal bioassays, and (4) epidemiology. Each of these techniques differs in cost,
quality of information, and length of study time. 3
Case clusters, or inferences from real world observation, are “the most rudimen-
tary form of risk assessment.’
‘ Health professionals notice “one or more cases of a
rare disease or an unusual concentration of a common one”5 and attempt to find the
cause. Lester Lave gives the example of Percival Pott, who inferred the cause of scro-
tal cancer among chimney sweeps,” and John Graham and Lorenz Rhomberg use the
example of the Turkish hematologist Muzaffer Aksoy, who having noticed that a large
number of shoe workers began to develop aplastic anemia and certain forms of leu-
kemia, traced the cause to the growing use in shoemaking of commercially prepared,
benzene-based adhesives. His findings were later confirmed by more detailed epide-
miological studies’ Case clusters, however, are of limited value.” They are a good
beginning point for further, more detailed research into potential health hazards, but
on their own they are neither accurate nor definitive, in large part because they do not
rigorously analyze causal relationships but instead rely on intuitive inferences from
correlations.
A recent example of the use of case clusters in risk assessment is the mad cow
crisis in Britain.? A higher than expected number of cases of Creutzfeldt-Jakob dis-
51 Ibid
5’2 Ibid. at 30.
” See L.B. Lave, “Methods of Risk Assessment” in L.B. Lave, ed., Quantitative Risk Assessment in
Regulation (Washington, D.C.: Brookings Institution, 1982) 23.
-‘Graham & Rhomberg, supra note 44 at 19.
5 Lave, supra note 53 at 28.
SSee ibid. at 29.
57See supra note 44 at 16-17.
5 Graham and Rhomberg note that “[c]linical intuition is fallible, however, and even if true, clini-
cally based insights are hard to prove ” (ibid. at 17).
5′ The following discussion is drawn from “Made in Britain” The Economist 338:7959 (30 March
1996) 17; “The BSE Scare: Mad Cows and Englishmen” The Economist 338:7959 (30 March 1996)
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ease (CJD) was observed in humans. CJD causes victims’ brains to rot, finally killing
them. Some scientists believe there may be a link between this recent outbreak and
bovine spongiform encephalopathy (BSE), a similar condition afflicting cattle. Eng-
land has a high number of cows infected with BSE that have been slaughtered and
sold in beef markets, and there is speculation that the recent rash of CJD has been
triggered by people eating tainted beef. Although there is more information than
merely the case clusters and the similar molecular structure of CJD and BSE upon
which scientists have based their tentative findings, there is nevertheless significant
uncertainty concerning the etiology of the disease, which has created considerable
political and economic perturbation in the United Kingdom and the European Union.
Structural toxicology attempts to draw comparisons in chemical structure be-
tween suspected toxins and known toxins. For instance, if substance A is known to be
carcinogenic, and substance B has an extremely similar molecular structure, an infer-
ence may be drawn that substance B is likewise carcinogenic. Such reasoning is
highly speculative, although it is a fairly cheap and quick way to obtain at least some
information about potential hazards.
Animal bioassays and epidemiological studies are the two best methods of the
four we are considering, yet both are subject to serious limitations. Bioassays are
controlled studies done on animals, typically mice and rats, where the potential risks
to humans are predicted based on the responses of test animals to the hazardous sub-
stance. These studies are done on animals for a number of reasons. First and most im-
portantly, conducting experiments of this nature on humans would be unethical. When
we say we do not want to treat people like guinea pigs, we say it with good reason –
test animals are given massive doses of potentially harmful substances and are subject
to rigid controls before dying or being killed and dissected. Doing the same to a hu-
man being, needless to say, would be unconscionable. Second, rodents have short
lifetimes and are relatively inexpensive to feed and house.’ As a result, studies can be
performed cheaply and quickly.
Underlying bioassays is the basic assumption that it is possible to extrapolate
from animals to humans. This premise is not without some empirical corroboration.
Virtually all human carcinogens are known to be animal carcinogens as well, although
the converse is not true – we cannot assume that all animal carcinogens are human
carcinogens.”
Selecting “the animal species that best predicts the response of man”62 is a source
of uncertainty. As Lowrance points out, “[m]an is unique. Therefore any extrapolative
step can only be a hesitant one. No animal is a best model for man; for any given ex-
25, “Coping with BSE” The Economist 346:8059 (14 March 1998) 15; “The Science of BSE: Bun-
gled” The Economist 346:8059 (14 March 1998) 21.
6 See Graham & Rhomberg, supra note 44 at 18.
6′ See Harrison & Hoberg, supra note 19 at 18.
62 G. Majone, “Science and Trans-Science in Standard Setting” (1984) 9:1 Science, Technology &
Human Values 15 at 17.
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periment, one can only use the species that appears to be most like man in the aspects
at question “‘3 Lowrance then proceeds to describe some of the anomalous results ob-
tained when conducting bioassays even on closely related species:
For example, the median lethal dose for the physiologically active compound
histamine is 400 milligrams of histamine per kilogram body weight for rats and
200 milligrams per kilogram for mice, but less than 1 milligram per kilogram
for rabbits and guinea pigs. The infamous thalidomide, so horribly teratogenic
to the human fetus, also causes birth defects in monkeys and rabbits –
but not
at all in rats.’
Majone notes that “[ulsing multiple species in toxicological experiments could im-
prove predictions somewhat, but heterogeneity in human populations is often social in
origin, and social conditions cannot be reproduced in the toxicologist’s laboratory.”
Additional difficulties beyond selecting the correct species are determining how
many tests will be run, what the mode of exposure to the impugned substance should
be in the test, how large the dose should be, and how dosages should be extrapolated
from animals to man.’ These decisions are often subject to economic and time con-
straints. Majone provides the following example:
[I]f we assume that a chemical agent will cause cancer in 1 out of 10,000 peo-
ple who are exposed to it, and that humans and test animals do not differ sig-
nificantly in sensitivity with respect to the given agent, we must test at least
10,000 animals (but preferably something like 30,000 animals) to detect one
case of cancer. In practice, no more than 50 or so animals are usually available
per dose level; hence high doses are used on small samples of animals.67
Extrapolating from high doses to low doses is the subject of intense scientific
controversy. “The theory is that a chemical that causes cancer at high doses will
probably do so at low doses as well, though with less frequency at lower doses” The
choice of an extrapolating function is based on fitting an appropriate model to the
data. There are three basic approaches that can be used: (1) a linear-dose response, (2)
a threshold (nonlinear) dose-response leading to a virtually safe standard set at the
threshold value, and (3) a non-linear curve at low doses that may indicate more or less
serious health effects than the linear model would predict.’9
Ames and Gold note that “[l]inear extrapolation from the maximum tolerated
dose in rodents to low-level exposure in humans has led to grossly exaggerated fore-
casts of mortality’ ‘, Hendee adds that “we do not know, and probably cannot know
‘ Supra note 37 at 64.
6 Ibid.
Supra note 62 at 17.
See Lowrance, supra note 37.
67Supra note 62 at 17.
SGraham & Rhomberg, supra note 44 at 18.
See Majone, supra note 62 at 16.
7′ Supra note 23 at 6.
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with certainty, whether low doses cause any damage at all. Numerous studies of hu-
mans exposed to low doses of radiation have failed to show any statistically signifi-
cant adverse health effects.”” Important regulatory decisions are nevertheless made on
this basis. In the famous saccharin studies of the 1970s, rats were given the saccharin
equivalent of 800 diet beverages a day, as a result of which they developed bladder
tumors.’ An extrapolation then had to be made to humans from rats, problematic
enough in itself, and complicated further by the need to extrapolate from high to low
doses.
Establishing a virtually safe dose, or no observable effects level (“NOEL”) is
likewise subject to great uncertainty. A safety factor of 100 is often used, “meaning
that test animals should show no adverse health effects from a given pollutant when
exposed to doses at least 100 times greater than the likely human dose:” This number
is somewhat arbitrary, although it is justified on the grounds that “humans may be ten
times more sensitive than the experimental animals used, and that, in addition, there
may be a tenfold variation in sensitivity among individuals.”‘ The Health Protection
Branch of Health Canada utilizes such safety factors,” as do provincial health and
safety regulatory agencies, as well as state and federal agencies in the U.S. and other
countries. Notwithstanding the somewhat arbitrary use of a safety factor of 100, there
is deviation even from that norm. Harrison and Hoberg discuss the varying safety
factors used by Health and Welfare Canada, Ontario, the Netherlands, New York
State, and Germany –
in assessing the risks of
dioxin. 6
100, 10, 4, 2, and 1 respectively –
Compounding the difficulties of bioassays is determining the best way to ex-
trapolate from animals to humans once the best species has been selected as well as
the best dose-response model. Lave points out that there are different ways of ex-
trapolating from rodents to humans: “dose per unit body weight, body area, or con-
centration in inhaled or ingested substances” As Lave says,
The methods used for extrapolating from mouse to man can have significantly
different results, as seen in the following example. Since a human weighs about
2,500 times as much as a mouse, a dose of I milligram per day to a mouse
would be equivalent to a dose of 2,500 milligrams per day to a human, if ex-
trapolation were done by weight. If extrapolation were done by surface area
(which is proportional to weight to the two-thirds power), the mouse dose
would be equivalent to a dose of 184 milligrams per day to a human. Thus if 1
7, W.R. Hendee, “Modeling Risk at Low Levels of Exposure” in Risks, Costs, supra note 2,46 at 46.
7 See Harrison & Hoberg, supra note 19 at 84-85. See chapter 5 for a discussion of the regulation
of saccharin in Canada and the U.S.
” Majone, supra note 62 at 17.
74 Ibid.
‘ See supra note 40 at 23-24.
76 See supra note 19 at 49.
“Supra note 53 at 42.
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J.D. FRAIBERG AND M.J. TREBILCOCK – RISK REGULATION
855
milligram per day were the highest safe dose in a mouse, the highest safe dose
in a human might vary from 184 to 2,500 milligrams per day.78
Epidemiological studies, unlike bioassays, focus on human populations, but de-
spite this improvement, they too are subject to serious limitations. “The inherent diffi-
culties with epidemiology include the inability to control for all relevant factors and
the need for inordinately large samples in order to deal with conditions of low inci-
dence. “‘ Epidemiological studies are also frequently of little value to regulators who
have to make immediate decisions about whether to regulate a potentially hazardous
substance. To conduct a thorough epidemiological study with suitable controls (as-
suming it is possible) may take years, or even a generation, while a regulator may be
forced to make a decision immediately, such as in the mad cow crisis. If regulators
wait until solid epidemiological evidence is available before making decisions, the
potential harms that were initially feared may have already materialized. The infor-
mation gleaned from such studies may prove helpful in preventing future harms, but is
of little help to those who have already been injured. Use of control groups who are
exposed to different levels of risk from other populations may also be ethically con-
troversial.
Thus, the risk assessment of hazardous substances is fraught with scientific un-
certainty and value judgments. Kristin Shrader-Frechette points out that
Assessors must make value judgments about which data to collect; how to sim-
plify myriad facts into a workable model; how to extrapolate because of un-
knowns; how to choose statistical tests to be used; how to select sample size;
detennine criteria for NOEL (no observed effects level); decide where the bur-
den of proof goes, which power function to use, what size of test to run, and
which exposure-response model to employ'”
Brooks notes that “[t]he more an issue is in the public eye, the more expert judg-
ments are likely to be influenced unconsciously by pre-existing policy preferences or
by supposedly unrelated factors such as media presentations, the opinion of col-
leagues or friends, or even the emotional overtones of certain words used in the de-
bate.”” Weinberg echoes this sentiment. Commenting on the intermingling of facts
and values in trans-science, he writes,
A scientist who believes that nuclear energy is evil because it inevitably leads
to proliferation of nuclear weapons (which is a common basis for opposition to
nuclear energy) is likely to judge the data on induction of leukemia from low-
level exposures at Nagasaki differently than a scientist whose whole career has
been devoted to making nuclear power work. Cognitive dissonance is all but
79 Ibid.
79 Ibid at36.
‘0 K.S. Shrader-Frechette, Risk and Rationality: Philosophical Foundations for Populist Reforms
(Berkeley: University of California Press, 1991) at 57.
“I Supra note 49 at 40.
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unavoidable when the data are ambiguous and the social and political stakes
are high. 2
In response to ubiquitous uncertainty, many risk estimates are “not guided by the
formal statistical properties of risk but rather by administrative procedures incorpo-
rating various types of ‘conservatism.”‘” Ruckelshaus writes: [H]istorically at EPA it
has been thought prudent to make what have been called conservative assumptions;
that is, our values lead us, in a situation of unavoidable uncertainty, to couch our con-
clusions in terms of a plausible upper bound.’
The decision to be conservative in risk assessment under conditions of uncertainty
is decidedly a risk management decision. As such, scientists are no better qualified
than other members of the public to make this decision. As Zeckhauser and Viscusi
caution, there are several problems with this approach. They give as examples the use
of results from the most sensitive animal species in bioassays from which regulators
draw conclusions about the magnitude of a risk, as well as the tendency to focus on
the upper end of the plausible risk assessments that are commissioned.” The “most
fundamental problem” with this approach is that “tilting risk assessments in a conser-
vative direction confuses the informational and decisional aspects of research about
risks. A conceptually sound form of conservatism would have the decision maker (not
the risk estimator) adjust the weights on the consequences. Adjusting the probabilities
amounts to lying to ourselves about what to expect “‘ They further note that excessive
conservatism, even at the risk management stage, can lead to inefficiencies.” The is-
sue of whether conservatism in risk estimates is in fact a wise policy decision is dis-
cussed in more detail in Part IV.
Thus far we have argued that science in the context of risk assessment is subject
to serious limitations. Nevertheless, it is indispensable for at least two reasons. The
first is that, despite the pervasive uncertainties, science is capable of identifying and
ranking many risks in a somewhat reliable way. For instance, scientists can say that
dioxin is more hazardous than saccharin. There is absolutely no doubt about this. We
agree with Harrison and Hoberg, who state, “[wje begin from the premise that some
substances do present greater risks than others and that the norms and methods of sci-
ence, while imperfect, constitute our best bet for distinguishing among them”
‘2 Supra note 25 at 33.
‘3 Fatal Tradeoffs, supra note 7 at 156.
Supra note 38 at 158.
Viscusi is critical of the use of upper bound estimates in assessing the risks of second hand to-
bacco smoke. See W.K. Viscusi, “Secondhand Smoke: Facts and Fantasy” (1995) 18 Regulation 42.
‘ Fatal Tradeoffs, supra note 7 at 157.
Hendee notes that “if the no-threshold model is overly conservative, and if risks are less-or non-
existent-at low levels of exposure, then the costs of radiation protection may be higher than neces-
sary, and the intrusiveness of regulations into the beneficial applications of radiation may be exces-
sive?’ He cites as an example the US Department of Energy’s $200 billion program of radiation
cleanup at DOE facilities, supra note 71 at 55.
‘ Supra note 19 at 8.
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Second, scientific analysis is valuable in a democracy because scientific proce-
dures are systematic and can be well documented. When decisions are made on a sci-
entific basis, they are available for public inspection and review. The public and
stakeholder groups can monitor the regulators by conducting experiments of their
own, or hiring scientists to do the analyses for them. In this way they can be reassured
that regulatory decisions are being made with the best possible information, and if
not, that something can be done to remedy the situation.
The limitations of science have already been pointed out. First, science is valuable
only at the stage of risk assessment. Science does not tell us whether something is
safe or not; it merely provides us with facts about the probability of harm under cer-
tain conditions. Judgments as to the acceptability of risk are beyond the scope of sci-
ence and belong more properly in the domain of risk management. Second, there are
questions as to how accurately science can perform its more limited role of risk as-
sessment. Uncertainty is inherent in risk assessments. This is a fact of life, and one we
may lament. But what are the alternatives to scientific risk assessment? There seem to
be no viable alternatives, so the challenge now becomes dealing effectively with un-
certainty. This issue is discussed further in Part IV.
Ill. Strengths and Limitations of Cost-Benefit Analysis
Once scientists have assessed the risks associated with a hazard, a decision must
be made about whether to regulate and if so by what means. Weiss and Strickland
write,
Not every 6nvironmental or health and safety problem is worth the social cost
of “solving” it. If we continue to ignore the costs imposed on industry, we are
likely to pay with low productivity and a stagnant economy. If we ignore the
environmental, safety, and health effects of some aspects of modem industry,
we will face a deteriorating and maybe dangerous environment and continuing
human costs of industrial disease and danger to consumers.8
Cost-benefit analysis is a formal, prescriptive technique that seeks to inform deci-
sions of this kind.*9 Arrow et. al point out:
Because society has limited resources to spend on regulation, benefit-cost
analysis can help illuminate the trade-offs involved in making different kinds of
social investments. In this regard, it seems almost irresponsible to not conduct
such analyses, because they can inform decisions about how scarce resources
can be put to the greatest social good.9
L.W. Weiss & A.D. Strickland, Regulation: A Case Approach (New York: McGraw-Hill, 1982) at
384.
nomics?” (Law and Economics Programme, University of Toronto Workshop –
1996-1997 (8)).
‘0 See generally A.I. Ogus, “Regulatory Appraisal: A Neglected Opportunity For Law and Eco-
“‘ K.J. Arrow et al., “Is There a Role for Benefit-Cost Analysis in Environmental, Health, and
Safety Regulation?” (1996) 272 Science 221 at 221 [hereinafter Science]. For a more detailed discus-
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As an indication of just how scarce resources are, Viscusi notes that “if the entire U.S.
gross domestic product were devoted to avoiding fatal accidents, we would have only
$55 million to spend per life at risk. ‘ The results of more judicious use of cost-
benefit analysis, it is argued, would be greater safety for the same cost, or the same
amount of safety for less cost.
We agree with Sunstein, who argues that in addition to the justification of cost-
benefit analysis “on economic grounds, as a way of promoting economic efficiency
and thus eliminating unnecessary and wasteful public and private expenditures,” there
“also are strong democratic justifications'”‘ for cost-benefit analysis. According to
Sunstein, it “can be understood as a way of diminishing interest-group pressures on
regulation and also as a method for ensuring that the consequences of regulation are
not shrouded in mystery, but are instead made available for public inspection and re-
view.” With respect to safeguarding the regulatory process from inappropriate inter-
est group pressure, Herman Leonard and Richard Zeckhauser note that although “any
technique employed in the political process may be distorted to suit parochial ends
and particular interest groups … [o]ur claim is that [cost-benefit analysis’] ultimate
grounding in analytic disciplines affords some protection”
Cost-benefit analysis in the context of risk management, however, as with its
technocratic analogue, science, in risk assessment, is subject to serious uncertainties.
The entire method is contingent on the ability to value accurately both costs and bene-
fits. As we shall see, there are enormous difficulties associated with monetizing the
costs and benefits of regulation.
A. Valuation Problems – The Value of Life
Suppose a company is emitting a pollutant as a byproduct of its manufacturing
process. Assume that this pollutant is known to increase the annual risk of a certain
kind of fatal cancer by 1/100,000. There are 200,000 people living in the vicinity of
the facility who are all equally exposed to this risk. We can predict that two statistical
lives will be lost each year if nothing is done to regulate the company’s manufacturing
process. Government is under pressure to regulate. A plan is proposed that will elimi-
nate this risk at an estimated annual cost of $30 million. This figure includes the costs
of complying with the regulations by changing the manufacturing process, the higher
prices consumers will have to pay for products that are now more expensive to pro-
sion, see K.J. Arrow et aL, Benefit-Cost Analysis in Environmental, Health, and Safety Regulation: A
Statement of Principles (Washington: American Enterprise Institute for Public Policy Research, 1996)
[hereinafter Benefit- Cost Analysis].
92 W.K. Viscusi, “The Dangers of Unbounded Commitments to Regulate Risk” in Risks, Costs, su-
pra note 2, 135 at 135.
“”The Cost-Benefit State”, supra note 6 at 4.
Ibtid
9′ H.B. Leonard & R.J. Zeckhauser, “Cost-Benefit Analysis Applied to Risks: Its Philosophy and
Legitimacy” in D. MacLean, ed., Values at Risk (Totowa, N.J.: Rowman & Allanheld, 1986) 31 at 31.
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duce, the lower profits the company will receive, which we will assume are reflected
in lower wages for employees, as well as the costs of the regulatory agency’s moni-
toring of the company. Assume further that these cost calculations are accurate, and
all possible costs have been properly accounted for.’
Should the proposed regulations be implemented? Do the benefits of saving two
statistical lives outweigh the $30 million in costs? In other words, are the two statisti-
cal lives worth at least $30 million in costs, giving a value of $15 million per statisti-
cal life?
Based on currently accepted figures, the answer would, in all probability, be no.
In Fatal Tradeoffs, Viscusi states: “Although the estimates of the risk-dollar trade-off
vary considerably depending on the population exposed to the risk, the nature of the
risk, and similar factors, most of the reasonable estimates of the value of life are clus-
tered in the $3 to $7 million range “‘ 7 Costs in this instance exceed the benefits.
There are two serious objections that can be raised at this point. The first is that it
is “morally and intellectually deficient’ ” to attempt to place a dollar value on human
life; life is a priceless commodity. In response to this objection, note that people rou-
tinely and voluntarily trade off safety for cost. Consider automobile purchase deci-
sions. Individuals frequently choose to buy smaller, more fuel efficient cars without
added safety features such as airbags, as opposed to larger cars equipped with such
risk reducing amenities, despite their knowledge that the car they choose to purchase
places them at greater risk of death in the event of an accident.’ This indicates that
citizens do not place an infinite value on their lives, as they are “willing to trade off
small risks of death for other valued objectives”‘
Furthermore, recall the discussion above about the scarcity of resources and how
cost-benefit analysis can inform decisions about how they can be put to the greatest
social good.”‘ Given the fact that individuals trade off safety for cost, coupled with the
fact that difficult decisions with respect to the allocation of scarce resources across a
range of potential regulatory initiatives must be made, it is not unreasonable to use
value of life figures when fashioning regulatory policy. Viscusi notes
[Tihe man in the street –
has an in-
stinctive aversion to placing a dollar value on a life. But economists do not cal-
culate such values because they are unfeeling technicians. They do so because
and the ordinary member of Congress –
9’ Lave notes that “[flor many projects, we cannot enumerate all the consequences of a decision,
which implies that all important consequences may not have been considered” See L.B. Lave, “Bene-
fit-Cost Analysis: Do the Benefits Exceed the Costs?” in Risks, Costs, supra note 2, 104 at 115.
97 Fatal Tradeoffs, supra note 7 at 73.
98 J.D. Graham & J.W. Vaupel, “Value of a Life: What Difference Does It Make?” (1981) 1 Risk
Analysis 89 at 89.
” See Fatal Tradeoffs, supra note 7 at 3-4.
“” Ibid. at 19.
“‘ See supra notes 89-92 and accompanying text.
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sensible regulation –
it. There is no escape from this aspect of regulatory policy.'”
the making of sound choices –
in many cases requires
The second objection accepts the principled argument underlying the use of a
value of life figure, but questions the specific values employed in the analysis. Not-
withstanding the need to make tough policy choices, who is to say that a life is worth
less that $15 million? If one were offered that amount in exchange for their life, it is
virtually certain everyone would refuse such a deal. How, then, can a figure such as $5
million dollars be used in making regulatory decisions?
The answer is that life is not actually being valued. Rather, what is being valued
are individuals “attitudes toward lotteries involving small risks of death”‘ 3 It also
bears pointing out that it is statistical lives, and not certain identified lives, that are
being valued.”‘
In the example considered above, we know that the costs of the proposed regula-
tions are $30 million. Each individual faces an increased annual risk of death of
1/100,000. Presumably, the affected individuals would rather not face the additional
annual risk of death.”5 The question, though, is how much, in dollar terms, do they
value the elimination of this risk? Faced with a lottery in which each faces a
1/100,000 risk of death, what trade-offs between safety and cost are those affected
willing to make?
The willingness to pay measure, which is the standard measure of benefits in
cost-benefit analysis’ would have us ask each citizen how much they would be will-
ing to pay to eliminate the risk. Suppose the average amount the 200,000 affected in-
dividuals would be willing to pay to eliminate the risk is $50. Altogether, $10 million
could be raised to eliminate the risk, thereby averting two statistical deaths. Pursuant
to this methodology, the implicit value of a statistical life is $5 million. “Another way
of conceptualizing this calculation is to view it as simply ascertaining the value we are
willing to pay per unit risk.”‘” The estimate of the value of a statistical life would then
equal the willingness to pay for additional safety, $50, divided by the risk increment
that is involved, 1/100,000, giving a value of $5 million.'”
’02Supra note 92 at 137.
“o Fatal Tradeoffs, supra note 7 at 17.
‘o, The fact that life is not actually being valued as such, but rather our attitudes toward lotteries in-
volving small risks of death, and that it is statistical lives, not certain identified lives, that are at issue
provides another ground for responding to the first objection, viz. that it is “morally and intellectually
deficient” to place a dollar value on human life.
‘0’ This is likely true, notwithstanding any countervailing benefits accruing from bearing the risk.
‘”6 See E.J. Mishan, Cost-Benefit Analysis (New York: Praeger, 1976) for a more detailed discussion.
7 Fatal Tradeoffs, supra note 7 at 20.
” See ibid This approach, which is premised upon an “implied assumption of linearity”, only
holds for risks of very low probabilities. See Mishan, Cost-Benefit Analysis, supra note 106 at 303, n.
11. See also infra note 114 and accompanying text.
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But where do we get the values people place on risk-dollar tradeoffs in their lives?
Maclean states: “The idea is that individual preferences for risk and safety trade-offs
are revealed in certain areas … to justify decisions in other areas … safety standards
can be set through centralized decisions that mimic the trade-offs that market data re-
veal.”‘ These areas include, most prominently, labour markets, where workers receive
wage premiums for assuming jobs with higher risks,”‘ automobile speed choices, seat
belt use, smoke detector purchase, property value decisions, and cigarette smoking
decisions.”‘ Other sources of data are contingent valuations. 2 or expressed preferences
which are obtained through surveys and psychometrics.’ 3
It is important to stress that the value of life figures are only meaningful when
dealing with small risks of fatality. As the probability of death increases, compensa-
tion demanded by those exposed to the risk rises exponentially. No rational person
will accept compensation for certain death, absent some bequeathment motive, as they
will not survive to enjoy the proceeds.”‘ Economists therefore tend to focus on the
amount of compensation people demand in exchange for exposure to relatively small
risks of fatality, (as well as the amount people are willing to pay to reduce risks of this
nature). These are the types of risks that are most frequently involved in risk regula-
” D. MacLean, “Risk and Consent: Philosophical Issues for Centralized Decisions” in Values at
Risk, supra note 95, 17 at 22-23.
” Economists use the willingness to accept measure, the economic measure for losses, in calculat-
ing the value of life from labour market data. If data from labour markets consistently show that
workers are willing to accept an increased risk of death of 1/10,000 for a wage premium of $500, then
the implicit value of a statistical life will be represented as $500 divided by 1/10,000 or $5 million.
Both the willingness to pay and willingness to accept measures are used in relation to lotteries in-
volving small risks of death, and as illustrated, both can be used to value life. Viscusi notes that “[flor
sufficiently small changes in risk, the willingness-to-pay and willingness-to-accept amounts should be
approximately equal, but in practice, they are not” (Fatal Tradeoffs, supra note 7 at 19). In actuality,
willingness to accept measures tend to be significantly greater than willingness to pay measures. This
creates a difficulty for practitioners of cost-benefit analysis, who must determine which measure
ought to be used in a particular analysis. See infra notes 130-34 and accompanying text for a more
detailed discussion.
. See Fatal Tradeoffs, supra note 7 at 8.
112 Paul Portney defines “contingent valuation” as follows: “[t]he contingent valuation method in-
volves the use of sample surveys (questionnaires) to elicit the willingness of respondents to pay for
(generally) hypothetical projects or programs” The debate “raises broad questions about what
economists have to say about the values that individuals place on public or private goods” (P.R. Port-
ney, “The Contingent Valuation Debate: Why Economists Should Care” (1994) 8 J. Econ. Perspec-
tives 3 at 3).
“,3 See B. Fischhoff et aL, Acceptable Risk (Cambridge: Cambridge University Press, 1981). Viscusi
notes that “[t]he advantage of using market-based estimates of money-risk trade-offs is that those ex-
posed to risk have a greater incentive to think carefully about the implications of the risks for their
lives than do respondents who are quickly briefed on potential risk trade-offs” (supra note 92 at 140).
He does, however, acknowledge the utility of surveys where good market data are unavailable.
“,4 See W.D. Schulze & A.V. Kneese, “Risk in Cost-Benefit Analysis” (1981) 1 Risk Analysis 81.
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tion and they are also risks where there is at least some market data available from
which to derive valuations.
Notwithstanding the availability of market data, however, the valuation of life is
highly uncertain. Lave notes that “clever people have found ingenious ways to value”
life and other goods, but he “would not want to bet the family jewels on the numbers
estimated'””‘ Sunstein comments that “smoke alarm purchases, safety cap expendi-
tures, and the use of suntan lotion cannot plausibly be said to reflect general judg-
ments about the value of life.””‘ He adds that “actual choices are highly geared to the
context in which they are made; it is not clear that one can infer from actual choices in
one context people’s valuations about other choices in a different context.””‘
One of the fundamental objections to the use of market data in determining the
value of life is that “the willingness of individuals to pay for reductions in risk de-
pends on their income levels, their expectations, and the hypothesized method of fi-
nancing.”‘ ‘ Using the methodology employed by labour economists to determine the
value of life, we might find that workers in high risk jobs tend to be poorer on average
that those in lower risk jobs, and thus might be more likely, due to economic pres-
sures, to assume higher risks for the prospect of increased pay than would wealthier
people who do not need the extra money. This would lead to the result that the
wealthy value their lives more than the poor. Besides the morally problematic claim
that might arise from these findings –
that wealthier persons’ lives are more valuable
than poorer persons’ lives –
there is another more practical quandary confronting de-
cision-makers: given a potentially disparate set of value of life figures, which ones
should be used in conducting the cost-benefit analysis? Coal miners will likely value
their lives less than university professors, meaning that they will accept risks for less
compensation. Using a lower end figure, such as the value coalminers attach to their
lives, might make a proposed regulation appear to be unjustified, while using a higher
end figure may have the opposite effect.
To remedy this situation, it has been suggested that an average figure, such as $5
million, be used in cost-benefit analysis. Even if economists were able to discount dif-
ferences in wealth and individually idiosyncratic tastes for risk (discounting the
pathologically risk averse as well as daredevils) and arrive at an agreed upon figure
for the value of life (which would be no small accomplishment), it is unlikely that this
figure will be suitable for use in every risk situation. As Nicholas Rescher points out,
“there is substantial variation in people’s valuation of the ‘social cost’ of different
“‘ Supra note 96 at 114.
“6Free Markets, supra note 20 at 141.
“7Ibi. at 310.
L.A. Cox & R Ricci, “Legal and Philosophical Aspects of Risk Analysis” in D.J. Paustenbach,
ed., The Risk Assessment of Environmental and Human Health Hazards: A Textbook of Case Studies
(New York: John Wiley & Sons, 1989) 1017 at 1039.
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modes of death:'”‘ Our attitudes towards death by murder, industrial accident and
sporting misadventure are all different.’ Consequently, we will be willing to pay
more or less to avoid certain kinds of fatal risks.
Research by Slovic, Fischhoff and Lichtenstein’ has shown that public risk per-
ception differs from expert risk perception in important respects. As we noted in Part
I, lay people sometimes lack certain information about hazards, and have “a well-
documented tendency to overestimate risks with low probabilities and risks that have
received substantial media attention,”” However, “their basic conceptualization of
risk is much richer than that of the experts and reflects legitimate concerns that are
typically omitted from expert risk assessments.'”
Experts often judge risk solely in terms of the expected number of fatalities or
injuries likely to arise in the event the risk materializes in harm. The public, though, is
sensitive to two additional factors. Factor one, or the “dread factor”, is defined by
“perceived lack of control, dread, catastrophic potential, fatal consequences, and the
inequitable distribution of risks and benefits.”‘2” Nuclear weapons and nuclear power
are examples. Factor two, “unknown risk”, comprises risks that are “judged to be un-
observable, unknown, new, and delayed in their manifestation of harm.”” HIV infec-
tion is an example of an unknown risk that is also dreaded.
The perceived acceptability of risk, not surprisingly, is also strongly correlated to
its voluntariness. Chauncey Starr, in his pioneering study on risk, notes that “[t]he in-
dications are that the public is willing to accept ‘voluntary’ risks roughly 1000 times
greater than ‘involuntary’ risks.”‘ Sound social policy requires experts to take the
voluntariness factor into account.’s
Given these differences in expert and public judgments, it is likely that the use of
a standardized value of life figure will tend to systematically underestimate the bene-
fits stemming from the regulation of dreaded and unknown risks. Making adjustments
“9 N. Rescher, Risk. A Philosophical Introduction to the Theory of Risk Evaluation and Manage-
inent (Washington: University Press of America, 1983) at 176.
,0 See ibiL at 171.
12 p. Slovic, B. Fischhoff & S. Lichtenstein, “Why Study Risk Perception?” (1982) 2 Risk Analysis
83.
‘2 Viscusi, supra note 92 at 152.’
‘ Slovic, ‘Perception of Risk”, supra note 26 at 285.
‘A Ibid. at 283.
125Ibid.
“6 C. Starr, “Social Benefit Versus Technological Risk” (1969) 165 Science 1232 at 1237.
.2 For an instructive discussion, see P. Slovic, N. Kraus & V.T. Covello, “What Should We Know
About Making Risk Comparisons?” (1990) 10 Risk Analysis 389 at 389. They are critical of com-
parisons of unrelated risks which “are frequently advanced as a means for setting priorities and de-
termining which risks are acceptable” They state that “risk acceptability depends on a wider range of
factors than the probabilities of expected fatality or morbidity estimates that are typically compared.
Comparisons that stress acceptability of risk are, therefore, vulnerable to criticism”
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in the value of life figure used depending on the nature of the risk confronted is a pos-
sibility, but is subject to considerable uncertainty.
The rationality of this move, despite its uncertainties, is easy to defend. The pub-
lic, assuming it is well-informed about the probabilities of death stemming from two
different kinds of risk, may rationally prefer to allocate more resources to risk A than
to risk B, even though the same allocation of resources to risk B would yield a greater
expected number of lives saved. This is because the public does not merely desire an
absolute reduction of fatalities. It also has an interest in reducing fatalities of a par-
ticular kind. As Amartya Sen has argued:
There are deep and fundamental and intuitively understood grounds for reject-
ing the view that confines itself merely to checking the parity of outcomes, the
view that matches death for death, happiness for happiness, fulfilment for ful-
filment, irrespective of how all this death, happiness, and fulfilment comes
about.’
B. Valuing Harms to the Environment
How much is peace and quiet worth? A view? The preservation of an endangered
species? If cost-benefit analysis is to be used, there needs to be some meaningful way
to determine these values. Economists have attempted to derive shadow prices for
these goods from market data and contingent valuation research, just as they have
done for the value of life. Steven Kelman claims that the methodological obstacles
confronting analysts in these endeavors are so great that it is virtually impossible to
arrive at meaningful figures. For instance, in discussing studies aimed at identifying
the value of clean air or peace and quiet by comparing property values, he notes the
difficulties in controlling for all dimensions of quality other that the presence or ab-
sence of the good in question. One might pay a higher price for a house not only be-
cause it is in a quieter area of town, but also because one’s friends and family live
nearby, or it is close to one’s work or children’s school. Moreover, Kelman claims that
the dollar values imputed to non-market goods which most people would wish to
avoid, such as a polluted environment, will be lower than they should be because peo-
ple with weak aversions or limited resources will take the bad bundle at lower prices
than average, thereby skewing the results.'”
In their article, Robin Gregory, Thomas Brown and Jack Knetsch make similar
arguments.'” They too are critical of current valuation techniques and strategies. One
of their more trenchant observations is that the willingness to pay measure, used to as-
sess the economic valuation of environmental benefits, may seriously understate them
and therefore adversely affect the implementation of environmental regulations. This
is due to the fact “that people commonly value losses much more than commensurate
Quoted in Free Markets, supra note 20 at 298.
See S. Kelman, “Cost-Benefit Analysis: An Ethical Critique” (1981) 5 Regulation 33 at 37.
“0 R. Gregory, T.C. Brown & J.L. Knetsch, “Valuing Risks to the Environment” (1996) 545 Annals
54.
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gains.””‘ However, the prevailing assumption among practitioners of cost-benefit
analysis is that the willingness to pay measure (the economic measure for gains) and
the willingness to accept measure (used for losses) ought to be equivalent. Therefore,
to the extent that cost-benefit analysis uses willingness to pay measures, there may be
“serious understatements””‘2 of benefits. To illustrate their point, they note that
“[r]esults of tests demonstrating large disparities in valuations of environmental losses
were first reported two decades ago, based on responses to hypothetical questions in-
dicating that duck hunters would demand four times as much money to give up habi-
tat than they were willing to pay to maintain the same resource”” In light of these
findings, practitioners of cost-benefit analysis must make a value judgment about
which measure to use. Cost-benefit analysis cannot resolve this question within its
own terms.”‘
The use of cost-benefit analysis when decisions are made to preserve wildlife and
endangered species is also the subject of serious criticism. Many of these decisions
are made for aesthetic reasons such as preserving our natural history. Trying to derive
shadow prices by looking at how much individuals are willing to pay to go to state
parks or trips such as safaris in which to see wildlife are at best poor approximations
of the benefits of such regulation and ignore “existence” values that many people at-
tach to these resources, even if they themselves are unlikely ever to avail themselves
of them (e.g., the preservation of endangered species or rare natural treasures in dis-
tant locations). In the United States, there was recently a debate over a federal pro-
posal that will cost more than $1 billion per year to preserve the spotted owls in their
forest homes. Lave notes that “[w]hether the United States should incur a cost of more
than $1 billion per year requires examining a large bundle of benefits, including ro-
mantic notions about preserving the primeval forest””‘ He also points out that in cases
such as these, “wisdom calls for stating the benefits and costs in multidimensional
terms, not in dollars”‘ 6 Kelman argues that it is as absurd to make such valuations on
a strictly cost-benefit basis as it is to value sex by reference to the current price for
prostitution services.’
C. Risk Equity and Distributive Justice
Another significant problem with cost-benefit analysis is its relative insensitivity
to the distributional consequences of regulatory options. Cost-benefit analysis seeks to
Analysis and Management 68 at 70.
.. J.L. Knetsch, “Assumptions, Behavioral Findings, and Policy Analysis” (1995) 14 J. Policy
,2 Ibid. at 74.
.Gregory, Brown & Knetsch, supra note 130 at 58.
” See Kelman, supra note 129 at 38.
… Supra note 96 at 118.
136 Ibid. at 117. See also Matthew Adler, “Incommensurability and Cost-Benefit Analysis” (1998)
146 Univ. Pa. L. Rev. 1371.
“‘ See supra note 129 at 39.
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identify the net benefits and net costs of proposed regulatory options summed over the
entire affected population. It is not primarily concerned with the distribution of these
costs and benefits. In principle, then, it is possible that a cost-benefit analysis may
lead to the adoption of a policy that imposes great costs on a few individuals or
groups if the benefits to the community as a whole outweigh these costs.
Consider the case in which a factory is emitting a pollutant as a by-product of its
manufacturing process. This pollutant, let us assume, causes minor irritation to most
nearby residents, but leads to more serious and debilitating consequences in asthmat-
ics and others with respiratory disorders, who comprise a small percentage of those
within the ambit of the risk. Suppose that the following three courses of action are
proposed: (1) do nothing, (2) alter the manufacturing process so that the pollution is
cut by 50%, or (3) ban the manufacturing process altogether. Suppose further that the
results of the cost-benefit analysis suggest that the most efficient course of action is
option 1, followed by option 2, and then 3. In turn, the asthmatics most prefer option
3, followed by 2, then 1.
Adherence to a strict cost-benefit calculus would lead to the adoption of option 1.
Leonard and Zeckhauser would likely defend such a move through the use of a con-
tractarian argument similar to the argument from the original position used by John
Rawls in A Theory of Justice.’ They write: “What mechanisms for making decisions
would individuals choose if they had to contract before they knew their identities in
society or the kinds of problems they would confront? Our answer is that, on an ex-
pected-value basis, cost-benefit analysis would serve them best and hence would be
chosen.”’39
It is ironic that Leonard and Zeckhauser would employ such an argument to jus-
tify the use of cost-benefit analysis without specifying the obvious limits to its appli-
cation that individuals in such a hypothetical situation would insist on. As Rawls
writes, “[flustice is the first virtue of social institutions”” –
not efficiency. The par-
ties in the original position, according to his argument, would only agree to principles
of justice that guaranteed their basic liberties. Furthermore, they would endorse insti-
tutions and policies that worked to the greatest advantage of the least advantaged
groups in society. The unconstrained use of cost-benefit analysis, though, as illus-
trated in the example above, raises the spectre of holding citizens’ basic liberties and
legitimate expectations hostage to the calculus of social interests, violating principles
of justice and equity. Thus, the failure of cost-benefit analysis to account for distribu-
tional consequences adequately is one of its most serious flaws.’
‘ J. Rawls, A Theory of Justice (Cambridge: Harvard University Press, 1971).
,39Supra note 95 at 33.
, Supra note 138 at 3.
See Royal Commission on Matters of Health and Safety Arising from the Use of Asbestos in
Ontario, Policy Options in the Regulation of Asbestos-Related Health Hazards (Study No. 3) by C.J
Tuohy & MJ. Trebilcock (Toronto: Ontario Ministry of the Attorney General, 1982).
1998]
J.D. FRAIBERG AND M.J. TREBILCOCK – RISK REGULATION
D. Discount Rate
Yet another difficulty encountered in the use of cost-benefit analysis is the deter-
mination of the correct rate through which future benefits and costs should be dis-
counted to present values. As Gregory et aL point out, $100 compounded annually at
6% would be worth $1842 at the end of fifty years, and conversely, $1842 fifty years
in the future would have a present value of $100.142 In many risk regulations, decisions
have to be made about whether to invest resources in precautionary measures to avoid
future harms. As Arrow et al. note, “[b]oth economic efficiency and inter-generational
equity require that benefits and costs experienced in future years be given less weight
in decision-making than those experienced today.” 3
Gregory et aL, citing a number of studies, find that individuals do not use a con-
stant and unvarying rate to discount all future outcomes, as it would seemingly be ra-
tional for them to do. The implications for risk valuations are that
[i]ncurring present costs to avert potentially catastrophic losses far in the future,
which would not appear to be worth undertaking using the constant discount
rates of standard analyses, may well be economically worthwhile when ac-
count is taken of the lower time preference rates for losses, for longer time ho-
rizons, and for more important outcomes.'”
Knetsch uses the examples of global climate change and reforestation to illustrate this
point. “Nearly any conventional invariant positive discount rate would preclude an
easy economic justification of precautionary efforts in many such cases””5 Even ac-
knowledging these points, how are we to decide on the correct rate? The choice is
subject to serious uncertainty, and the results of analyses will be subject in many in-
stances to legitimate doubts and challenges.”
E. Cost-Effectiveness Comparisons between Regulations
We have already noted the considerable difficulties associated with valuing goods
such as human lives and the environment. To avoid some of these problems, a more
limited use can be made of cost-benefit analysis: cost-effectiveness analysis of regu-
lation.’ On this approach, all that needs to be valued are the costs of alternative regu-
latory responses. Although making such a determination is itself problematic, it will
,42 See supra note 130 at 59.
’41 Science, supra note 91 at 222.
‘Supra note 130 at 60.
” Supra note 131 at 70.
‘”Arrow et aL suggest that “[t]he rate at which future benefits and costs should be discounted to
present values will generally not equal the rate of return on private investment. The discount rate
should instead be based on how individuals trade off current for future consumption” (Benefit-Cost
Analysis, supra note 91 at 13-14). This suggestion may reduce uncertainty in determining rates but by
no means eliminates it.
,4′ See Fischhoff et aL, supra note 113 at 104; and Rescher, supra note 119 at c. 14. See also Gra-
ham & Vaupel, supra note 98 at 93.
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typically be easier than valuing benefits of regulation since some of the more difficult
valuation problems will be bypassed.’ 8 J.L. Regens notes that
In practice, EPA has utilized cost-effectiveness analysis more frequently be-
cause the benefit-cost approach ‘is often difficult to do, since the Agency is fre-
quently concerned with protecting such things as human life and the stability of
ecosystems, social values for which there is no market price, or for which cur-
rent procedures for finding ‘shadow prices’ are bitterly controversial.”
Although cost-effectiveness analysis “does not address the question of whether
the outcome is worth having in the first place:’ it “can be used to allocate resources
among several programs in order to achieve the greatest result per unit cost; or it can
be used to project and compare the total costs (to industry, government and the con-
‘ For example, without attaching any values
sumer) of several alternative programs”‘
to lives saved, the 1979 EPA trihalomethane drinking water standard cost approxi-
mately $200,000 per life saved, whereas EPA’s 1990 hazardous waste listing for
wood-preserving chemicals was estimated at $6.3 trillion per life saved.'”‘ (It bears
pointing out that $6.3 trillion was not actually spent. The figure is the result of expen-
ditures made divided by the expected number of lives saved given the expenditure.)
Clearly, regardless of the value of the benefits of these regulations, this information is
helpful. In comparing the costs of the two regulations, we know, for instance, if the
opportunity presented itself, that as between the two, it would be more efficient to in-
vest in the cheaper regulation.
While cost-effectiveness analysis is a valuable tool in promoting a more efficient
allocation of resources, even this more limited use of cost-benefit analysis is subject to
limitations. For example, consider the two following regulatory proposals. In proposal
A, air bags will be made mandatory in all new cars sold. Assume that this regulation
will save each statistical life at a cost of $2 million. Proposal B is a ban on the emis-
sion of certain toxic pollutants into the atmosphere, pollutants which affect a large
number of people living in residential areas in the vicinity of the source. Suppose this
regulation would save each statistical life at a cost of $10 million and that the deaths
that would be averted are particularly dreaded.
On a straight-forward cost-effectiveness approach that seeks to maximize num-
bers of lives saved at least cost, it is clear that regulation A is preferable to regulation
B. But this conclusion neglects some important differences between the two risks. In
1- But not completely. A thorough analysis of the costs of regulation will consider substitution ef-
fects as well, which may entail valuing lives and harms to the environment. We will return to this is-
sue below.
‘ J.L. Regens, “Attitudes Toward Risk-Benefit Analysis for Managing Effects of Chemical Expo-
sure” in H.M. Seip & A.B. Heiberg, eds., Risk Management of Chemicals in the Environment (New
York: Plenum, 1989) 75 at 81 (quoting from U.S. Environmental Protection Agency, Risk Assessment
and Management: Framework for Decision Making (Washington: U.S. Environmental Protection
Agency, 1984) at 27).
150 “Health-Risk Determination”, supra note 40 at 33.
… See Arrow et aL, Science, supra note 91 at 221.
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869
the case of the air bags, it is still possible for consumers who value safety highly to
purchase cars with air bags without making them mandatory and thereby driving up
the costs for everyone else. The situation is far different in the pollution case. The risk
faced by the residents is an involuntary externality-risks are imposed upon them
without their consent.’ 2 In addition to the involuntariness of the risk, there may be im-
portant distributive concerns, as those most affected are nearby residents, who will
likely bear a disproportionate share of the risk. Finally, the deaths sought to be averted
under proposal B are dreaded. Thus, in light of these differences, and recalling our
discussion above of perceived risk factors and their effect on the acceptability of risk,
it may make more sense to implement proposal B instead of or before proposal A,
even though we will be spending more money to save each statistical life and will
therefore appear not to be acting as cost-effectively as possible.”
F Cost-Benefit Analysis and Substitution Effects
A well-conducted cost-benefit analysis should also take account of possible sub-
stitution effects of proposed regulations. Sunstein provides the following example: “A
regulatory ban may result in independent health risks coming from ancillary ‘re-
placement’ risks. If we ban substance A, the replacement substance B may be danger-
ous too. If a carcinogenic substance is regulated, perhaps people will use a product
that is not carcinogenic but that causes serious risks of heart disease. “‘
5
Government agencies frequently fail to take into account the replacement risks of
proposed regulations. Cost-benefit analysis can therefore be of considerable help by
pointing out, to the extent feasible, all possible costs and benefits, including the possi-
bility of regulations simultaneously increasing new risks while reducing old ones. Of
course, there are still the practical limitations referred to above: the difficulties of
identifying all possible costs and benefits, and even if identified, problems in valuing
them.
Sunstein notes that “there are many different mechanisms by which risk regula-
tion may increase aggregate risks’ 55 For the purposes of the discussion, this article
focuses on recent research, which has indicated that regulatory expenditures of a cer-
52 Assume these people did not know of the risk when they purchased their homes.
If a perfect cost-benefit analysis were conducted, the net benefits of B would exceed the net
benefits of A. However, the use of cost-effectiveness analysis precludes reaching this conclusion,
since cost-effectiveness analysis focuses exclusively on the relative costs of regulations, and not at all
on their relative benefits. Recall that the rationale underlying the use of this technique is that the
valuation of the benefits or regulations is generally more difficult than the valuation of costs. This is at
once cost effectiveness analysis’ greatest strength and weakness. Since the valuation of the benefits of
regulations is fraught with difficulties, cost-effectiveness analysis is helpful because it enables deci-
sion-makers to bypass these valuations. However, bypassing the valuation of the benefits or regula-
tions can lead to the implementation of suboptimal regulations, as illustrated in the example above.
‘u Free Markets, supra note 20 at 301.
‘5 Ibid. See also ibid. at 279-81 for a number of examples.
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tain magnitude, with their resultant effects on the economy, may actually lead to fa-
talities because of the “richer is safer” argument.” Sunstein summarizes the point
well: “Regulations cost money-sometimes a great deal of money-and private ex-
penditures on regulatory compliance may produce less employment and more pov-
erty. People who are unemployed or poor tend to be in worse health and live shorter
l i v e s – ,,
7
M
Ralph Keeney has attempted to quantify the health effects of regulatory expendi-
tures.’5’ He writes that “several studies suggest that for every $2 million to $15 million
spent on public programs one statistical life is lost””‘ He argues that “[t]he induced
fatalities caused by the expenditures to satisfy regulations provide an upper bound for
a reasonable value trade-off between statistical lives and statistical costs:”‘ Viscusi
echoes this sentiment when he says “[i]n effect, saving lives becomes a break even
proposition where every time we are willing to spend money to save a life, we lose a
life because we become poorer in doing so'””‘ Courts in the United States have been
receptive to this research. Easterbrook J. cited concerns about the income-mortality
link in his dissenting judgment in International Union v. Johnson Controls,’62 as did
Williams J. in UAW v. OSHA.'”
Accepting in principle the “richer is safer” argument, there is still considerable
uncertainty on how to measure the health effects of regulatory expenditures, as re-
flected in the large range of values in existing studies.'” The “richer is safer” substitu-
tion effect is yet another instance of both the strengths and limitations of cost-benefit
analysis.
G. Practical Difficulties
We note also two practical difficulties with the use of cost-benefit analysis. The
first is what Sunstein refers to as “excessive proceduralism'”” Conducting a thorough
cost-benefit analysis and accounting for all possible costs and benefits requires con-
siderable time and resources. In many cases, the costs of these studies may exceed the
‘” See A. Wildavsky, “Richer is Safer” (1980) 60 Public Interest 23.
‘ 7Supra note 20 at 302.
‘ See R.L. Keeney, “Mortality Risks Induced by Economic Expenditures” (1990) 10 Risk Analysis
147.
,”9 R.L. Keeney, “The Role of Values in Risk Management” (1996) 545 Annals 126 at 130; see also
Viscusi, “The Dangers of Unbounded Commitments”, supra note 92 at 161.
’60 Keeney, ibid at 131.
.6, Supra note 92 at 160.
,62 886 F.2d 871 (7th Cir. 1989), reversed by the U.S. Supreme Court (April 22, 1991).
’63 938 F.2d 1310 (D.C. Cir. 1991), remanded 37 E 3d 665 (D.C. Cir. 1994). See Free Markets,
supra note 20, for a brief discussion of these and other related cases.
‘ See Viscusi, supra note 92 at 162.
’65 “Te Cost-Benefit State”, supra note 6 at 27.
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J.D. FRAIBERG AND M.J. TREBILCOCK – RISK REGULATION
871
benefits, leading to the incongruous result that cost-benefit analysis may fail cost-
benefit analysis.'”
Failure, however, to conduct thorough analyses may result in other problems.
Although time and money may be saved in the short term, the results of many agency
analyses are of questionable quality. Lave dramatically presents these difficulties with
the following example:
[W]hat should EPA Administrator Carol Browner infer from a benefit-cost
analysis of a new automobile emissions standard? Suppose she was informed
that the analysis was done by a GS-9 with a B.A.–or even an M.B.A.-in six
weeks with no supplementary budget. The analyses produced by government
agencies often contain major flaws in theory, quantification, and analysis.’6″7
Thus, there are difficult trade-offs agencies must make between the costs and benefits
of cost-benefit analysis.
The second major difficulty is the use of value judgments by practitioners of cost-
benefit analysis. Given the significant uncertainties we have noted above, analysts are
forced to make value judgments in much the same way as scientists do in risk assess-
ment. And just as scientists are vulnerable to influence from public opinion, friends,
family, and their own personal points of view, so too are cost-benefit practitioners.
Lave comments that this “recognition leads to a shocking assertion. The same econo-
mist might do quite different benefit-cost analyses of the same issue, depending on
who the client is.”163
IV. Regulatory Reform
This article began by pointing out that the current way in which institutions de-
sign and implement environmental, health and safety regulation is sub-optimal. To
improve performance, we argue that it is necessary to make greater use of two tech-
science and cost-benefit analysis. Science and cost-benefit analysis
nocratic tools –
are systematic procedures which can discipline the politics of risk regulation. Both
can help to achieve the goal of allocating society’s scarce resources as efficiently as
possible, leading to greater safety at the same cost as currently expended, or alterna-
tively, the same amount of safety at less cost.
Science and cost-benefit analysis, however, are subject to serious limitations,
many of which we have noted. In light of these uncertainties, the need to make value
judgments is inescapable. These judgments are often a political matter, and experts
are no better qualified than other members of the public to make them. Daniel Fiorino
remarks that “[e]xperts must take part in these decisions, because they have the
knowledge and methods to estimate the likely range of consequences. However, par-
‘6 See ibid
167 Supra note 96 at 120.
‘ Ibid at 121.
872
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ticipation by the lay public is necessary to ‘represent societal values to the experts and
to clarify necessary choices that the political process must make.””‘ He goes on to ar-
gue that “a technological society can remain a democratic one only by remaining con-
scious of democratic values and by searching for institutional measures that will pro-
mote those values in social decision-making”‘
Public involvement in both risk assessment and risk management decisions is es-
sential. The challenge we address in this final section is straightforward: how can we
design credible risk regulating institutions that incorporate these technocratic tools
and make appropriate use of experts while still allowing room for the public to par-
ticipate in a meaningful way? This article adopts Fiorino’s view that “agencies will
need to take the design of participating institutions as seriously as they take the design
of their analytical documents.'”
A. Mandatory Scientific Risk Assessments
Scientific risk assessments should be mandatory for all regulatory initiatives. The
enabling legislation of all risk regulating institutions, both federal and provincial,
should be amended to include this requirement. Since these studies are costly, both in
terms of time and money, following Graham, whose recommendations have informed
our thinking throughout this section, it is appropriate that “agencies … tailor the com-
plexity of the analysis to the importance of the rule. “” Perhaps different categories of
regulation should be defined, with the most extensive studies reserved for “major”
regulatory initiatives. The term “major” will of course require elaboration, but similar
language has been used in presidential executive orders in the United States.”‘ Refer-
ring to the United States, Hahn notes that:
While the definition of a “major” or “significant” rule has changed somewhat
over time, it is generally a regulation that is expected to have one or more of the
following characteristics: an annual impact on the economy of $100 million or
more; a major increase in costs or prices for consumers or business; or signifi-
cant effects on competition, employment,
investment, productivity, or
innovation 7
‘6 D.J. Fiorino, “Environmental Risk and Democratic Process” (1989) 14 Col. J. of Env’l L. 501 at
509, quoting Brooks, supra note 49.
“o Ibid. at 523.
“‘ Ibid at 546. See also W.D. Ruckelshaus, “Science, Risk and Public Policy” (1983) 221 Science
1026 at 1028, where he writes “we should seek more imaginative ways to involve the various seg-
ments of the public.”
,’7 J.D. Graham, “Making Sense of Risk” in Risks, Costs, supra note 2, 183 at 199.
‘ Executive Order 12291, issued by President Reagan in 1981, as well as Executive Order 12866,
issued by President Clinton in 1993 require cost-benefit analysis for major regulations. For more de-
tailed discussion of Reagan’s pioneering order, see D. Whittington & W. Norton Grubb, “Economic
Analysis in Regulatory Decisions: The Implications of Executive Order 12291” (1984) 9:1 Science,
Technology & Human Values 63.
“4Supra note 32 at 244.
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For the purposes of the discussion, this article assumes that the regulatory initiatives
under review are “major” and therefore require the most extensive analysis. This is
done to illustrate, in a limiting case, how science can best be used in risk regulation.
Agencies ought to conduct or commission one or more assessments using a vari-
ety of plausible assumptions, in order to provide risk managers with a balanced view
of the uncertainties. William Leiss and Christina Chociolko, in Risk and Responsibil-
ity, wisely state that “there be a reasonable effort made … to produce a truly disinter-
ested risk assessment, that the nature of the uncertainties be described as fully as pos-
sible”‘ 5 Graham says that “[s]ingle-point estimates, such as plausible upper bounds or
worst-case scenarios, should generally be accompanied by lower-bound (optimistic)
and realistic (or likely) estimates of risk?”‘ He also urges the use of “distributional
methods of variability analysis,” since some citizens may be more sensitive to certain
kinds of risk than others. For instance, asthmatics incur a disproportionate share of the
adverse effects of air pollution. “Without that kind of information, risk managers are
in a poor position to incorporate equity and justice considerations into their deci-
sion.”” With the information provided, the agency should make a preliminary deter-
mination of which numbers it plans to use, publishing the results and the reasons for
its choice.
B. Notice and Comment Period
Following mandatory scientific risk assessment, there should be a mandatory no-
tice and comment period in which various stakeholders can challenge or confirm the
agency’s scientific findings if they choose by conducting or commissioning studies of
their own. Since uncertainties in the agency’s assessments will be clearly identified,
stakeholder groups can take issue directly with controversial assumptions. In doing
so, stakeholders’ studies should also clearly identify the assumptions they are making
and offer reasons for them. Including the public in this way, Jasanoff argues, is “an es-
sential counterweight to biases that scientists might bring to policymaking, individu-
ally or as a professional class?”7′
Of course, the financial hurdles associated with conducting these kinds of studies
may prove an insurmountable obstacle for some stakeholder groups, particularly citi-
zen groups, who, compared with industry, will typically comprise more diffuse inter-
ests and have fewer resources with which to undertake studies of their own. To redress
these possible financial and collective action problems, it may be appropriate to pro-
vide funding for certain recognized stakeholder groups to conduct studies of their own
,’ W. Leiss & C. Chociolko, Risk and Responsibility (Montreal: McGill-Queen’s University Press,
1994) at 261.
’16 Supra note 172 at 190.
‘” Ibid. at 191. See also ED. Hoerger, “Presentation of Risk Assessments” (1990) 10 Risk Analysis
359.
178 S. Jasanoff, “Peer Review in the Regulatory Process” (1985) 10 Science, Technology and Human
Values 20 at 23-24.
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in cases of major regulatory importance.'” This will no doubt result in increased gov-
ernment expenditures, but these may be justified as promoting democratic values, a
greater likelihood of arriving at a consensus, and increased trust in the regulatory pro-
cess. The effects of greater trust in the regulatory process are not to be underesti-
mated, as is argued later in this section.
Once all studies have been submitted, an opportunity for discussion and negotia-
tion among various constituencies and the government agency presents itself.’8 Per-
haps a consensus can be reached as to what numbers are most appropriate. Brooks
notes that even in the absence of consensus, “[i]f the parties to a controversy could
actually agree on the specifications for the research needed to resolve their technical
differences (or at least narrow them appreciably), it might spur a research program fo-
cused on critical issues and thus accelerate the resolution of controversies through re-
search.””‘
C. Peer Review
If there is still substantial disagreement at the end of the notice and comment pe-
riod between the agency’s risk assessment and those submitted by stakeholder groups,
how should the controversy be resolved? The agency which produced the assessment
that sparked the controversy may be subject to charges of bias if it is responsible for
resolving the dispute.
One possible solution is the use of independent scientific peer review committees,
in which the various studies (both the agency’s and the public’s) are submitted to a
blue ribbon panel of disinterested scientific experts.”2 The composition of these panels
will of course be of fundamental importance, and serious thought must be given to
how members are selected. Professional reputation and no direct interest in the out-
come of the dispute would clearly be pre-requisites. The scientific profession cur-
rently has well developed methods for making peer review selections, and should be
consulted by government-when creating panels for regulatory review.
The peer review committee would be charged with determining the most accurate
assessment of the risk and reporting back to the agency, operating as a science court.’
In making this determination, it is possible that the committee will support a particular
‘” Shrader-Frechette makes a similar suggestion, supra note 80 at c. 12.
,8 See ibid. For an overview of multistakeholder consultation in Canada, see G. Hoberg, “Environ-
mental Policy: Alternative Styles” in M.M. Atkinson, ed., Governing Canada: Institutions and Public
Policy (Toronto: Harcourt Brace Jovanovich, 1993) 307.
I Supra note 49 at 43.
,si See L. Salter, “Science and Peer Review: The Canadian Standard-Setting Experience” (1985)
10:4 Science, Technology & Human Values 37.
” Arthur Kantrowitz is a proponent of this view. He writes “if the making of mixed judgments is
meticulously separated into scientific and nonscientific parts, then a system can be devised by which
the experts can make objective judgments regarding the scientific parts of the question:’ See A. Kan-
trowitz, “Controlling Technology Democratically” (1975) 63 American Scientist 505 at 509.
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J.D. FRAIBERG AND M.J. TREBILCOCK- RISK REGULATION
875
group’s study, or that it will issue a new set of results based on the synthesis of the
best data and assumptions from each study under review. A range of values, including
the mean estimate, plausible upper and lower bounds and worst-case scenario, as well
as the distributional impacts, should be reported back to the agency. The agency
would then be bound by these figures, and risk management decisions would be based
upon them. Creating similar or overlapping peer review committees for families of
regulatory agencies, or at least generic classes of risks, would promote consistency of
treatment across agencies.
D. Mandatory Cost-Benefit Analyses
Just as scientific risk assessment should be mandatory for all major regulatory
initiatives, so too should cost-benefit analysis. The enabling legislation of risk regu-
lating agencies should be amended to include this requirement, and, acknowledging
that cost-benefit analysis may sometimes fail cost-benefit analysis, “the intensity of
the analysis ‘should be tailored’ to the importance and complexity of the specific
problem” ‘ An initial cost-benefit analysis should be conducted by the agency after it
has completed its preliminary risk assessment. Without data from this assessment, it
would be impossible to conduct such an analysis.
All possible costs and benefits, including substitution effects, should be valued for
a range of regulatory proposals. For example, consider a case of air pollution arising
from an industry’s manufacturing process. Many policy options could be imple-
mented, e.g., do nothing, tax the industry, modify the manufacturing process through
standards, or ban the process altogether. There are various costs and benefits associ-
ated with each proposal, all of which should be calculated.”
As we have recognized earlier, valuing costs and benefits is fraught with uncer-
tainty. Consequently, agencies should explicitly identify the values used and the rea-
sons for using them. Arrow et al. suggest that “a core set of economic assumptions
should be used in calculating benefits and costs. Key variables include the social dis-
count rate, the value of reducing risks of premature death and accidents, and the val-
ues associated with other improvements in health”‘” Two main arguments underlie
this suggestion. First, using such a core set of assumptions promotes consistency
among agencies, allows for the comparison of different agencies’ cost-effectiveness,
and makes the analyses easier to perform. Second, although there are obstacles to
valuation, some figures are clearly more plausible than others, and a degree of con-
sensus has emerged around certain bounded values given revealed preferences in the
market place and other data from research on expressed preferences.
‘8 Graham, supra note 172 at 184.
5 For a discussion of policy options in regulation, see Dewees, Mathewson & Trebilcock, supra
note 12 at c. 2.
‘ Science, supra note 91 at 222.
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Some goods, however, such as distributive justice, defy monetization. A responsi-
ble cost-benefit analysis should acknowledge the difficulties in valuation and indicate
that these goods, in so far as they are implicated in the analysis, are to be given a
qualitative as opposed to a quantitative description. If valuations of these goods is at-
tempted, then special care should be taken to note their highly speculative nature.”‘
After a preliminary analysis is completed, with all uncertainties and assumptions
clearly identified, it should be published and submitted for public scrutiny and criti-
cism. Although we have discussed the proposals for scientific risk assessment and
cost-benefit analysis sequentially, in practice the preliminary risk assessment and the
preliminary cost-benefit analysis based upon it should be published and released to
the public at the same time. The only reason the two proposals were discussed se-
quentially is that risk assessment is logically prior to a cost-benefit analysis.
The notice and comment period for the cost-benefit analysis should occur simul-
taneously with the notice and comment period for the risk assessment. Stakeholders,
in addition to commissioning scientific risk assessments, should also be free to con-
duct cost-benefit analyses and submit the results for consideration. Funding should be
provided for these studies as discussed above.
Assuming that no consensus emerges after a mediated discussion among the vari-
ous constituencies, the studies should be sent for peer review. The same principles of
selection should apply to the peer review committees responsible for the cost-benefit
analyses as for scientific analyses. The experts should have excellent professional cre-
dentials and no conflicts of interest. They would be charged with evaluating the qual-
ity and accuracy of competing studies, in the same way as the scientific peer review
committee would evaluate the competing risk assessments. The cost-benefit peer re-
view committee, however, will have to await the scientific review committee’s report
on its findings before issuing its final report, because the outcomes of the cost-benefit
analysis will be affected by modifications to the assessment of the magnitude of the
risk. Again, creating similar or overlapping cost-benefit peer review committees for
families of regulatory agencies, or at least generic classes of risks, would promote
consistency of treatment.
E. Emergency Situations
In certain emergency situations, it may be appropriate for the government to make
regulatory decisions without following the proposed procedures. Consider the recent
“mad cow” crisis in Britain. Little was known about the cause of the outbreak of CJD.
There was a presumed link with BSE, but no conclusive data to that effect. Even if
there were a correlation, no accurate dose-response relationship could be established,
and therefore the dangers of consuming beef could not be estimated with a high de-
gree of accuracy. A frightened public and alarmist media demanded that some action
be taken. What should the government do?
‘”See Arrow etal., Benefit-Cost Analysis, supra note 91 at 10.
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Under such circumstances, the government should be given the power to regulate
through a Quick Response Mechanism (“QRM”). This article does not outline the
procedures of such a mechanism in any detail. However, this power should be exer-
cised by government through formal cabinet directives to a regulatory agency tabled
in Parliament. Its exercise would be conditional upon meeting the requirements relat-
ing to risk assessment and cost-benefit analysis (as laid out above) in the future, say
within six months of the emergency enactments, and sustaining, modifying or with-
drawing the regulations accordingly. It is of interest to note that the new WTO Agree-
ment on the Application of Sanitary and Phytosanitary Measures” envisages a similar
procedure.
For example, a QRM could authorize regulators, on apprehension by government
of a serious product hazard, to temporarily ban goods from sale and if necessary to
seize them, and in appropriate cases to recall them from retailers, pending fuller
evaluation of the risks apprehended. This would require a subsequent systematic re-
view of the evidence and appropriate weighing of costs and benefits of continued in-
tervention, which would need to be performed and completed within a prescribed
limited time in order not to unfairly prejudice manufacturers, importers and retailers
of the product. Perhaps if the product in question were found to be safe at the conclu-
sion of this process, the government should compensate manufacturers or suppliers at
least for out-of-pocket losses incurred during the period of its removal from the mar-
ket. The risk of such compensation would provide an incentive for the government to
use the QRM judiciously.”
F Decision Criteria and Judgmental Inputs
Now that the agency has conducted its scientific risk assessments and cost-benefit
analyses, published its preliminary reports, subjected them to public scrutiny in a no-
tice and comment period, and submitted the competing studies for peer review, what
is it to do? The report of the scientific peer review committee on risk assessment has
provided the agency with a range of values reflecting the magnitude of the risk, while
the cost-benefit panel has provided the agency with the expected values-net benefits
or costs-associated with various policy options. )With respect to (1) the risk assess-
ment data, should the mean estimates of the risk always be utilized? Or, given the un-
certainties, ought more conservative figures be employed in some circumstances, and
if so, when? With respect to (2) the results of the cost-benefit analysis, should the
policy option with the greatest expected value, that is, the greatest net benefits, always
be implemented? Or are there occasions when agencies should implement regulations
even if they are not cost-justified, or when there are greater efficiencies to be realized
through the implementation of other regulations? This article considers each of these
two questions in turn.
“nSupra note 41.
z See Hadfield, Howse & Trebilcock, supra note 28 at 74.
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Rescher notes three cardinal rules in risk management decision-making. They are
(1) maximize expected values; (2) avoid catastrophes; and (3) dismiss extremely re-
mote possibilities.” What do these rules mean, and how do they inform the two ques-
tions we are seeking to answer?
Maximizing expected values is essentially a call on decision-makers to maximize
net benefits. This simple, intuitive idea lies at the heart of the calls for increased use of
cost-benefit analysis. There are, however, limits to this principle of practical reason.
One of them is the second cardinal rule: avoid catastrophes. There are circumstances
where the materialization of a risk may produce consequences that are so awful and
dreaded that we may rationally choose to avoid it, even if running the risk, despite its
catastrophic potential, yields greater benefits (according to the results of a cost-benefit
analysis) than avoiding it.
Suppose nuclear fusion becomes a viable energy source. Assume that in building
a fusion power plant, there is a slim chance, say 1%, of a catastrophic accident leading
to 20,000 deaths. Let us assume that the energy savings are so dramatic, however, that
the benefits of the technology significantly outweigh the costs. One may quite ration-
ally insist that such a plant not be built because of the slim chance of a catastrophic
accident. In principle, it is argueable that a suitably conducted cost-benefit analysis
should be able to capture this “dread factor”, but in recognizing the limitations of this
formal method, it is more accurate to say that given the potential for a catastrophe, the
risk faced is simply unacceptable.”‘ A judgment is made that the risk is too great to
bear. This is often referred to as the “precautionary principle” which holds that “if an
action or a policy potentially has catastrophic effects, then we should refrain from un-
dertaking it even if the probabilities are uncertain.”‘ ” The minimax rule in decision
theory is intimately related to the avoid catastrophes rule and the precautionary prin-
ciple. The minimax rule “tells us to identify the worst outcome of each available al-
ternative and then to adopt the alternative whose worst outcome is better than the
worst outcomes of all the other alternatives.””‘9 The question is, when should the
minimax rule be applied? The answer seems to be where there is either considerable
uncertainty as to the magnitude of the risk and the worst possible outcome is poten-
tially catastrophic, or alternatively in situations where even if the probabilities of a
risk are known with certainty, a non-trivial potential for a catastrophe is known to ex-
ist.
” See supra note 119 at 114.
191 As a means of capturing this dread factor, Shrader-Frechette notes that “[s]everal authors have
proposed that n lives lost simultaneously in a catastrophic accident should be assessed by a loss of n2
lives. They argue that the risk-conversion factor for catastrophic accidents should be exponential” (su-
pra note 80 at 94). We believe that an adoption of the avoid catastrophes rule is superior to this ad hoc
manipulation to the cost-benefit analysis.
“nSee D. Jamieson, “Scientific Uncertainty and the Political Process” (1996) 545 Annals 35 at 40.
I9 J. Rawls, Justice as Fairness: A Briefer Restatement (Cambridge: Harvard University, 1990) at
80 [unpublished].
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879
It bears pointing out that there is a difference between risk and uncertainty, and
the application of the minimax rule, as well as the avoid catastrophe rule and the pre-
cautionary principle, ought to be sensitive to this distinction.'” Under conditions of
risk, there are known probabilities of future contingencies, whereas under conditions
of uncertainty, these probabilities are not well defined. There is the greatest need to
apply the minimax rule under conditions of serious uncertainty, since the outcomes of
a cost-benefit analysis will be impossible to determine. One could argue that its appli-
cation under conditions of risk, even where benefits from the risks are expected to ex-
ceed the costs, is unnecessarily risk averse, irrational and inefficient. In response to
this claim, this article responds that the minimax rule should nevertheless still be ap-
plied where potentially catastrophic outcomes with a known probability exist, for the
reasons offered above, although perhaps more judiciously than under conditions of
uncertainty, where it should be applied more readily.
The use of the minimax decision rule, however, presupposes that judgments
should be made about the likelihood of a catastrophic event. Suppose the risk of a
catastrophic accident at the fusion plant,
instead of being 1%, were only
0.0000001%? The third rule, dismiss extremely remote possibilities, holds that in-
finitesimal risks can be ignored. For example, the U.S. FDA has used a de minimis
threshold of one in a million individual lifetime risk.’93 Any risk that has a one in a
million lifetime chance or less of occurring may be discounted.
Each rule, Rescher argues, is limited by the subsequent rule. That is, the rule
about maximizing expected values is limited by the avoidance of catastrophes, while
the avoidance of catastrophes is limited by the rule about discounting effectively zero
probabilities.
This article proposes the addition of a fourth rule to Rescher’s list of three: (4)
adopt equitable regulations. This rule recognizes another instance, besides avoiding
catastrophes, where the rule of maximizing expected values should yield to other con-
siderations. As argued above, regulations that would otherwise fail a cost-benefit
analysis should nevertheless still be adopted in circumstances where failing to do so
would lead to the inequitable treatment of certain groups. This is due to the fact that
our considered judgments about justice are often incapable of being adequately cap-
tured in a cost-benefit analysis.
The differential imposition of risks on citizens threatens to violate both their basic
liberties and their legitimate expectation that the government fashion policies and in-
stitutions that work to the greatest advantage of the least advantaged groups in society.
Consider the regulation of blood in Canada. In choosing to adopt suitable policies, the
preferences of hemophiliacs, a disadvantaged group, should be given additional
weight. A cost-benefit analysis may suggest that certain policies are warranted under
” See further on the distinction between risk and uncertainty, REH. Knight, Risk, Uncertainty and
Profit (Chicago: University of Chicago Press, 1985).
,9′ See J. Fiksel in De Minimis Risk, supra note 25, 3.
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circumstances where the vast majority of citizens face minimal risk of contracting
HIV or hepatitis, even though these policies subject relatively more frequent users of
the blood system such as hemophiliacs to risks that most would intuitively judge as
unacceptable.
Hemophiliacs could argue that their basic liberties are violated by these proposed
regulations since they have a right, as citizens, to the provision of certain primary
goods (such as a safe blood system) in a manner which does not expose them to grave
risks of morbidity and mortality. Alternatively, as an already disadvantaged group,
they could argue that they have a legitimate expectation based on justice that policies
operating to the greatest advantage of the least advantaged groups in society be
adopted.
A strict adherent of cost-benefit analysis may counter that a suitably conducted
analysis ought to capture our intuitions about the unacceptability of this risk. Since
hemophiliacs are subject to greater risks, they would be willing to pay much more to
avoid them than those without the condition. Whereas the risks of mortality and mor-
bidity for an average citizen may be one in a million, the risks faced by hemophiliacs
may be orders of higher magnitude. Thus, a cost-benefit analysis should reflect this
by, perhaps, using a higher value of life figure for hemophiliacs than for average citi-
zens. Consequently, the results of the cost-benefit analysis will become more congru-
ent with our intuitions.
This argument presupposes the ability to accurately measure citizens’ increased
willingness to pay to avoid risks of increasing probability. However, the most reliable
market data available to measure how much people are willing to pay to avoid risk, or
conversely, are willing to accept for the imposition of additional risk is based on re-
sponses to risks of low probability. This data, as noted above, is subject to significant
uncertainty. The uncertainty becomes even greater when looking to market data to
measure willingness to pay or willingness to accept responses to the types of higher
probability risks that are at issue in the example under consideration. Simply put,
there is little reliable data for measuring the benefits of avoiding risks above a certain
size. In the absence of such data, our collective intuitions and considered judgments
are preferable to a cost-benefit analysis. Doctoring the analysis to suit these intuitions,
which could be done, is superfluous. It is more straightforward merely to rely on in-
tuitions about justice directly.
Even if reliable market data were available to measure the benefits of high-risk
avoidance, the cost-benefit analysis would nevertheless be unable to measure the in-
stinctive aversion most people have to placing certain groups under high risks for the
benefit of other groups –
treating those at higher risk as means rather than ends in
themselves –
even when one is a member of the group that benefits. This aversion is
heightened when those at risk are among society’s already disadvantaged. Average
citizens, considering proposed blood policies under which their safety is not in jeop-
ardy, may still find the policies unacceptable since their preferences may also include
the altruistic desire to see that others such as hemophiliacs who have been tradition-
ally disadvantaged are not subject to dangerously high risks.
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J.D. FRAIBERG AND M.J. TREBILCOCK – RISK REGULATION
For the foregoing reasons, strict adherence to the results of cost-benefit analyses
is not warranted when there are significant distributional inequalities. In seeking to
adopt equitable regulations, decision-makers should be attentive to a number of fac-
tors. First, they should look to the results of the scientific risk assessment, which, as
noted above, ought to include the distributional consequences of the risk. Second, if
the risks are not distributed equally, regulators should turn their minds to the severity
of the risk at issue. Differences in the severity of the risk should inform judgments as
to whether deviating from the cost-benefit analysis is warranted. If the risks are life-
threatening as opposed to merely debilitating, there is greater reason to reject the
findings of the cost-benefit analysis. Third, the question of who bears the brunt of the
risk ought to be taken into account. Even if the severity of the risk at issue is not great,
if it is borne by traditionally disadvantaged groups there may still be good reason for
regulators to depart from maximizing expected values. This is because considerations
of justice discussed above may militate against the imposition of yet another burden
on groups that are already subject to disproportionate burdens. Fourth, decision-
makers should be sensitive to whether those who bear the brunt of the risk are also
those who derive the greatest benefits. For example, if an industry of national impor-
tance creates health risks that are concentrated in a small area, members of the af-
fected community may be willing to bear those risks if they result in increased eco-
nomic prosperity for those within their ambit. Under such circumstances, decision-
makers may see the differential benefits to those at higher risk as a mitigating factor,
and therefore choose to follow the cost-benefit analysis, notwithstanding the distribu-
tional inequality.
This last point raises the possibility that government compensate, either ex ante or
ex post, those groups who suffer a disproportionate share of the risk in question, rather
than foregoing the activity or proposed regulatory policies which yield net benefits to
others in society. While it is true that awarding compensation will alter the cost-
benefit ratios, such awards may nevertheless be worthwhile if they still allow for effi-
ciency gains in an ethically acceptable fashion. Agencies, however, should not be
given the power to award such compensation. Rather, at the end of the regulatory pro-
cess and discussions with the affected constituencies, through which a sense of the vi-
ability of such a compensation scheme can be gauged, a report to the relevant gov-
ernment should be made suggesting a plausible course of action. It would then be left
to elected representatives to make a final decision, informed by the agency’s findings.
We note that decision-makers can only be guided by the factors listed above if
they are presented with the requisite information. Given the above proposals to in-
clude distributional consequences in the scientific risk assessment and to fund various
stakeholder groups so that they may participate in the decision-making process, the
information necessary to make these kinds of decisions will hopefully become more
readily available.
Having now presented four decision rules, it is important to note that rules two
through four require judgmental inputs that are different in kind from the formal rules
associated with rule one. That is, when maximizing expected values, costs and bene-
fits are plugged into a calculus which yield a result in a relatively mechanistic way. Of
course, judgments are made in valuing the costs and benefits, but these judgments are
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of a different kind from the judgments in two through four. What is a catastrophe?
What is an extremely remote possibility? What are equitable regulations? Unlike cost-
benefit analysis in rule one, there is no formal method for making these judgments,
and agencies should be given some latitude in making decisions of this nature. Over
time, guidelines and precedents should develop to constrain decision-makers’ discre-
tion. Nevertheless, given the subjective nature of the judgments involved, the back-
grounds, qualifications and perspectives of members of regulatory agencies are an
important issue. While formal stakeholder or constituency representation may not be
desirable out of concern for political paralysis and unprincipled decision-making,
governments could commit themselves in the legislative mandates of regulatory agen-
cies to appointing members in their individual capacities to reflect a balanced range of
qualifications and perspectives, which should not be exclusively technocratic in nature
but include members with, for example, industry, consumer, environmental or other
perspectives (depending upon the risks being regulated). In a Canadian context, where
much risk regulation occurs within executive branches of government rather than by
quasi-independent regulatory agencies (as in the U.S.), the above proposals imply a
somewhat less anonymous, more structured, transparent and accessible regulatory
process than the traditional Canadian risk regulation process has entailed.
In light of the four decision rules presented, it is now possible to attempt to an-
swer the questions posed at the beginning of this section. With respect to what figures
should be taken from the risk assessments, the default assumption ought to be the
mean risk estimates provided by the peer review committee.” However, if it can be
shown that the upper bound estimates are potentially catastrophic, then it may make
sense for risk managers to use those figures in the cost-benefit analysis. Of course, a
judgment needs to be made about whether the risk is potentially catastrophic, and if
so, whether or not the risk is small enough to discount completely. Some criteria for
judging the catastrophic nature of the risk are the potential number of fatalities, the
voluntariness of the risk, the type of death, and whether the deaths will occur simulta-
neously or not. Viscusi and Zeckhauser, however, properly caution that conservative
figures are used far too often and lead to more costly regulations than might be neces-
sary, as risks are frequently overestimated, and hence so too are the benefits of risk
avoidance.'”
With respect to whether the policy option with the highest expected value should
always be implemented, there should be a default presumption in favour of maximiz-
ing expected benefits, save for two instances. The first is in a situation such as the hy-
pothetical example given above about the fusion plant. If there is a non-trivial risk of a
catastrophe, then the option that best avoids the catastrophic risk should be imple-
‘” Viscusi states “[f]rom a statistical decision theory standpoint, if we are concerned with maxi-
mizing the expected benefits of government efforts, we should rely upon the mean risk values in
making these assessments rather than some other value along the risk distribution” (“Economic Foun-
dations”, supra note 10 at 131).
“7 See “Risk Within Reason”, supra note 7.
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J.D. FRAIBERG AND M.J. TREBILCOCK – RISK REGULATION
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mented, even if that means rejecting the results of a cost-benefit analysis. The second
is when a regulatory decision, although cost-justified, has distributional consequences
which are inequitable, for example because the rights or legitimate expectations of al-
ready seriously disadvantaged citizens are violated. Again, it is important to stress that
making these decisions requires the exercise of judgment by agencies. Guidelines
should be developed to help ensure consistency in making them.
G. Risk Communication, Risk Perception, and Trust
One of the main benefits of the proposals we are considering is the development
of increased public trust. A trusting public is much more likely to tolerate the imposi-
tion of certain risks than a mistrustful one. A patient who trusts a doctor is more likely
to submit to a risky surgical procedure recommended by the physician. Similarly, the
public will be more willing to submit to certain regulatory policies, including the de-
cision to forego regulation in some instances where it is initially demanded, if there is
trust in both the decision-makers and the decision-making process.
Good risk communication, “defined as the flow of information and risk evaluation
back and forth between academic experts, regulatory practitioners, interest groups,
and the general public””‘ is essential for increasing public trust. Leiss poses the fol-
lowing challenge: “[H]ow can we improve the quality of the dialogue about risk …
that separates experts from the general public? Second, how can we apply this im-
proved dialogue to achieving a higher degree of social consensus on the inherently
controversial aspects of managing environmental and health risks?”‘”
The institutional reforms proposed herein will help to improve the dialogue be-
tween government experts and the public, and afford an opportunity for greater con-
sensus.’ By publishing the results of risk assessments and cost-benefit analyses and
allowing the public to participate meaningfully in the shaping of policy, and by being
attentive to balanced membership composition of regulatory agencies, a strong mes-
sage is sent that government is receptive to the concerns of its citizens.
For example, increased citizen participation in the regulatory process can help to
make use of the best aspects of both expert and public perceptions of risk. As dis-
cussed above, public perceptions of risk are often based on poor information. If care-
ful scientific risk assessments and cost-benefit analyses are performed and the results
are communicated to the public in an open setting, it is likely that on some occasions
citizens’ risk perceptions will become more congruent with the scientific state of
“‘ W. Leiss, “Three Phases in the Evolution of Risk Communication Practice” (1996) 545 Annals
85 at 86.
‘” Ibid See further on risk communication, see B. Fischhoff, “Risk Perception and Communication
Unplugged: Twenty Years of Process” (1995) 15 Risk Analysis 137. See also Slovic, “Perceived
Risk”, supra note 22.
” National Research Council, Committee on Risk Perception and Communication, Improving Risk
Communication (Washington, D.C.: National Academy Press, 1989).
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knowledge and thus citizens will be more accepting of expert judgments. This process
is likely to be facilitated by agencies relating the risks at issue to commonly assumed
risks so that the public has some readily understood comparators to relate to. On the
other hand, there may be times when regulatory decision-makers will change their
view to one more in line with public risk perceptions. Consider a situation in which
the public, although fully appraised of the probabilities of fatality, demands a regula-
tion that, according to standard value of life figures, would not be cost justified. After
consulting with the public and learning more about how dreaded the risks are per-
ceived to be, regulators may decide to modify their assessments accordingly.
H. The Role of the Courts
Despite the opportunities for participation and independent peer review, various
stakeholders are likely to be unaccepting of the decisions that regulators reach. There
will always be winners and losers. What options are available to the losers to appeal
decisions that they feel are unjustified? There are two main avenues: the courts and
the political process.
Canadian courts have traditionally been deferential to the decisions of regulatory
agencies, particularly with respect to expert judgments.”‘ This deference stands in
marked contrast to activist courts in the United States which have overruled risk
regulatory decisions on numerous occasions.’
Under our proposed regulatory changes, however, citizens would be able to
launch judicial review applications only on due process grounds. For instance, if there
is insufficient public consultation before a decision is made, a court could hold a
regulation invalid until such time as proper procedures are followed. The courts in
such a case would serve to enforce the proposed rules, which are aimed at a more
participatory and transparent process, a goal which Hoberg and Harrison, in their
comparative study of Canadian and U.S. regulatory styles, argue would be a welcome
development. 3 Jasanoff echoes this sentiment, as does Salter.’
Canada currently has less citizen participation and a more closed regulatory style
than the United States. 3 The offsetting benefit would appear to be the ability to enact
201 See Canadian Union of Public Employees, Local 963 v. New Brunsvick Liquor Corporation
[1979] 2 S.C.R. 227,97 D.L.R. (3d) 417 [hereinafter CUPE].
202 See, for example, T.O. McGarity, “Judicial Review of Scientific Rulemaking” (1984) 9:1 Sci-
ence, Technology & Human Values 97. See also R.A. Merrill, “The Legal System’s Response to Sci-
entific Uncertainty: The Role of Judicial Review” (1984) 4 Fundamental and Applied Toxicology
S418.
“‘ See supra note 19 at 168-84.
‘See supra note 36, and note 182 at 42-43.
2
203 See AJ. Green, “Institutional Structures and Policy Outcomes: The ‘Americanization’ of Envi-
ronmental Regulation in Canada” (Working Paper #26) (Centre for the Study of State & Market, No-
vember 1996). See also P. Nemetz, W.T. Stanbury & R Thompson, “Social Regulation in Canada: An
Overview and Comparison with the American Model” (1986) 14 Policy Studies J. 580.
1998]
J.D. FRAIBERG AND M.J. TREBILCOCK – RISK REGULATION
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regulations more expeditiously, but Harrison and Hoberg find that there is no evidence
to support this claim. In actuality, there are few practical advantages to the current
system. In urging a more participatory and transparent Canadian system, we are not
advocating the rampant litigiousness and judicial activism that marks the U.S. regu-
latory process. Judicial review should be restricted to policing procedural irregulari-
ties. Courts should not engage in substantive second-guessing, unless decisions are
for example, a patently unreasonable determination of an
patently unreasonable
effectively zero probability based on no credible evidence at all –
a highly unlikely
eventuality, given the peer review processes envisaged. One possible caveat to this
strong presumption of judicial deference relates to the fourth (distributive justice) de-
cision criterion which qualifies utilitarian judgments out of concern for individual or
minority rights. Here, more intensive judicial scrutiny of agency decisions may be
warranted, paralleling the judicial role played in protecting constitutional or civil
rights.
–
I. The Role of the Political Process
The second avenue for aggrieved citizens to pursue their complaints with regula-
tory policies is in the political arena. This article has argued that regulatory bodies
should make their decisions in accordance with the procedures outlined above. This
process, although better than that which currently exists in Canada, is still not perfect.
It is merely an attempt to yield welfare maximizing results. Sometimes it may fail or
be perceived as failing in this task.
In cases of such failure, at least from the standpoint of aggrieved citizens, lobby-
ing can be undertaken to prompt legislative or ministerial action to override regulatory
decisions. Political rallies can be organized, contributions withheld, politicians pun-
ished at the polls. When these pressures are brought to bear on politicians, they may
eventually yield to public demands and overturn the regulatory decision in question.
Doing so will not be costless, however. Politicians will be acting against the findings
of a detailed and well-documented regulatory procedure, and will have to justify their
actions, presumably by arguing that the valuations employed in the cost-benefit analy-
sis were flawed or that an error in judgment was made in applying one of the decision
rules discussed above.
Political override has occurred in the past. A notable example was the lifting of
the saccharin ban in the United States after an enormous public outcry and letter
writing campaign, orchestrated by concerned citizens and industry members, bom-
barded Congress until they finally relented.’ Another was Congress’ decision, by an
overwhelming majority, to repeal an ignition interlock standard which prevented an
automobile from being started unless seatbelts were attached, despite highly favorable
206 See CUPE, supra note 201.
’07 See Hanison & Hoberg, supra note 19 at c. 5.
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cost-benefit ratios associated with that standard.”‘ Such political action is not to be
lamented. If the public demands an overturning of a regulatory decision, so be it.
Democratic societies must, in the end, yield to the will of the citizenry, provided rights
are not violated. The public has the ultimate decision-making prerogative. It is crucial,
however, that political override be public, e.g. by a formal Cabinet or Presidential di-
rective to an agency, tabled in Parliament or Congress, and subject to open debate and
criticism (and perhaps in turn legislative override by a super-majority, e.g. a two-thirds
vote of the legislative body), so that the government is fully accountable, politically
and publicly, for exceptionalist decisions.
Designing an appropriate institutional division of labour between regulatory
agencies, courts, and the political process is an important challenge. Different analyti-
cal currencies or discourses will be relevant in different institutional fora. Just as dis-
tributional equities are not relevant, as a general matter, in private law tort or breach of
contract actions, but may be relevant in other fora, structuring the mandate of institu-
tions in the risk regulation field so as to clarify what kinds of analysis, arguments and
evidence are relevant in what fora should serve to maximize institutional comple-
mentaries and comparative advantages.
Conclusion
The democratic political process must be disciplined by the introduction of tech-
nocratic tools such as the use of science in risk assessment and cost-benefit analysis in
risk management. If not, misallocation of scarce resources will continue. The use of
these technocratic tools, however, must also be disciplined by the democratic process.
Key social decisions cannot be made solely by unaccountable experts. Not only would
the results be anti-democratic, they may be inefficient or inequitable as well. By im-
plementing the regulatory proposals outlined above, which address these two con-
cerns, it will be possible to move closer to achieving the goal of a safer, more effi-
cient, and more democratic society. International trade obligations under the
GAT1IWTO and NAFrA, as exemplified by the recent GATT/WTO Panel ruling
striking down EU Beef Hormone regulations inter alia for lack of scientific justifica-
tion,’ and the potential application of the proportionality test to such regulations, will
increasingly require domestic risk regulation regimes to move in the directions pro-
posed in this paper.
As noted at the outset, this article has been largely cast at a conceptual level. In a
Canadian context at least, much less is known empirically about the structure and pro-
cesses of risk regulating institutions, both federal and provincial, than is required to
See M.J. Trebilcock, “Requiem for Regulators: The Passing of a Counter-Culture?” (1991) 8
Yale J. on Reg. 497 at 500.
‘w The GATT/WTO Panel Decision in the Beef Hormone Case, supra note 41; see further M.L Tre-
bilcock & R. Howse, “Trade Liberalization and Regulatory Diversity: Reconciling Competitive Mar-
kets with Competitive Politics” (1998) 6 Eur. L L. & Econ. 5.
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inform concrete policy prescriptions. More detailed empirical research is required
with this institutional focus (perhaps by way of case-study) to establish the extent to
which, and ways in which, Canadian risk regulating institutions in practice conform
to, or diverge from, the ideal risk regulation regime that this article has attempted to
develop and defend.
