WPS7094


Policy Research Working Paper                 7094




 The Need for Multiple Types of Information
   to Inform Climate Change Assessment
                              Michael Toman




Development Research Group
Environment and Energy Team
November 2014
Policy Research Working Paper 7094


  Abstract
  Information on ecosystem characteristics as well as economic                       Information on the irreversibility of impacts also is relevant
  statistics is needed to more fully inform decision makers on                       for evaluating implications for intergenerational equity. In
  the impacts of climate change on human well-being. Cli-                            addition, climate change is subject to a large degree of
  mate change risks involve potentially large and irreversible                       Knightian uncertainty, making it useful to understand
  as well as highly uncertain impacts that need to be evaluated                      how individuals perceive and evaluate climate change risks.
  with information that complements cost-benefit analysis.




  This paper is a product of the Environment and Energy Team, Development Research Group. It is part of a larger effort by
  the World Bank to provide open access to its research and make a contribution to development policy discussions around
  the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be
  contacted at mtoman@worldbank.org.




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                                                        Produced by the Research Support Team
      The Need for Multiple Types of Information to
           Inform Climate Change Assessment
                                          Michael Toman 1




JEL: D61, D63, D81, Q54, Q56, Q57
Keywords: Climate change. Sustainable development. Benefit-cost analysis. Ecosystem
valuation. Uncertainty. Intergenerational equity. Safe minimum standard.


1
  Views expressed in the paper are the author’s alone. The author acknowledges with gratitude comments
from Fran Sussman, Ed Barbier, and an anonymous reviewer, as well as editorial assistance from Elaine
Wylie.
      The Need for Multiple Types of Information to
           Inform Climate Change Assessment
1.      Introduction
For the Second Assessment Report of the Intergovernmental Panel on Climate Change (IPCC),
David Pearce led a team that investigated the economic costs of climate change (Pearce et al.,
1996). Among the impacts assessed was the threat of increased mortality, e.g., from increased
occurrence of tropical diseases and more intense heat waves in locations where the poor did not
have much access to air conditioning. Carefully documenting every assumption and calculation,
Pearce and his co-authors determined a range of estimates for the economic cost of increased
mortality risk. The upper bound used estimates from work in OECD countries on the value of
statistical life, and the lower bound used that value scaled by relative incomes, assuming a unit
income elasticity for the statistical life valuation. The authors pointed out that there were good
reasons to think that the elasticity would be less than one, putting the value somewhere inside the
range. The authors were vilified by a number of critics who accused them, among other things,
of saying that the life of a poor person is worth only a fraction of a life in the OECD. 2
        This story illustrates both the importance of doing serious assessment of costs and
benefits of climate change, and the difficulty one faces in carrying out such assessment. The
criticism of the economic valuation work in the Second Assessment Report (which has had a
lingering effect on subsequent IPCC assessments) was not the result of ignorance. It reflects a
deep disagreement with the assumptions—and even the framing of issues—that go into the
economic calculus.
        A great deal of the cost-benefit analysis carried out for climate change makes use in one
way or another of Integrated Assessment Models (IAMs). A modeling approach is unavoidable
given that we have little observational information for constructing a climate change damage
function, especially one that would describe the future impacts of current emissions, and only
somewhat better information for constructing an emissions mitigation cost function given
uncertainties about future energy and other technologies. Like any model, IAMs are built on a set
of parametric and structural assumptions, in this case for representing both the future evolution
of the climate system and the future evolution of the economic system (and interactions between
them).
       The robustness of IAMs for assessing costs of climate change and benefits from response
options is a matter of ongoing debate. What can be said, however, is that IAMs provide the
capacity for a variety of important if-then policy impact experiments, and anything that can
improve the scope and accuracy of information in the IAMs is beneficial. Especially high



2
  This was reported at the time in, e.g., Masood (1995). Pearce and his colleagues stood by the scientific
integrity of what they had done, and Pearce in particular protested modification of the basic conclusions
in later summary documents. For further explanation of the approach taken, (see Fankhauser, Tol, &
Pearce, 1997, 1998).
                                                        2
priority are efforts that can reduce uncertainty about probabilities related to climate change, and
efforts that can increase the scope of what can be captured in the representation of economic
damages from climate change (Yohe 2009; Gerst, Howarth, and Borsuk 2010).
        Some critics of cost-benefit analysis applied to climate change have suggested that even
with such improvements, economic analysis of climate change’s costs and benefits is not useful
and should not be performed. I believe the opposite is the case. Measures of economic costs and
benefits inevitably, and appropriately, play a significant role in public policy evaluation and
resource allocation for climate change (Yohe 2009). Done well, economic analysis can provide
an organized and transparent approach to assessing climate change risks and response options. 3
This can be useful in the face of high uncertainties surrounding climate change and the
cacophony of different philosophical and political perspectives held about it.
        Nevertheless, there are limits to what economic analysis can accomplish in informing
climate change debates. Yohe (2009) expresses one important perspective on this issue by noting
the need for a “risk management approach” to complement conventional cost-benefit analysis,
with its focus on expected net benefits (or certainty-equivalent results from a small number of
scenarios). He cites government-approved language from the Fourth Assessment Report of the
Intergovernmental Panel on Climate Change: “Responding to climate change involves an
iterative risk management process that includes both adaptation and mitigation, and takes into
account climate change damages, co-benefits, sustainability, equity and attitudes to risk” (see
Intergovernmental Panel on Climate Change, 2007, p. 22). 4
        This quotation emphasizes a very inclusive approach toward measurement of benefits and
costs; the importance of distributional issues; and an approach to incorporating (quantifiable)
uncertainty that takes into account the overall nature of the risk distribution, not just central
tendencies. It also emphasizes the importance of learning about risks and costs and incorporating
new information when analyzing them. Given the nature of climate change, these are very


3
  OMB (2003) guidance for regulatory impact analysis states (page 2): “Regulatory analysis is a tool
regulatory agencies use to anticipate and evaluate the likely consequences of rules. It provides a formal
way of organizing the evidence on the key effects—good and bad—of the various alternatives that should
be considered in developing regulations. The motivation is to (1) learn if the benefits of an action are
likely to justify the costs or (2) discover which of various possible alternatives would be the most cost-
effective.”
4
  A referee has very helpfully pointed out that much of the debate over the lessons to be drawn from
IAMs has been focused on the strengths and weaknesses of the standard Hicks-Kaldor criterion in cost-
benefit analysis, that a project is good if benefits exceed costs in the aggregate and benefits to winners are
sufficient to compensate losers. As part of that, criticisms of conventional approaches to discounting as
marginalizing future generations recalls arguments from classical utilitarianism. However, the relative
lack of attention to distributional issues in many cost-benefit analyses overlooks the possibility that a
major change in distribution from climate change or from policy responses to it could leave a society
concerned with distributional equity worse off, even if the Hicks-Kaldor criterion was satisfied. No less
important, much less attention has been paid to the limitations in how climate change risks and damages
are typically described in IAMs.
                                                          3
important considerations for providing a clearer and comprehensive picture to decision makers of
what is at stake. At the same time, the importance of incorporating these considerations is
underscored in best-practice documents such as OMB (2003), and so they are consistent with
high-quality cost-benefit analysis (although in practice they may not get addressed as one would
like).
        In this paper I focus on the needs for other information to complement the application of
cost-benefit analysis to climate change. One concern involves reservations with respect to
addressing the risks of climate change and the impacts of response policies with a small number
of economic summary statistics, even when the statistics are transparently calculated and
presented according to best practice. 5 This concern arises especially in the context of addressing
the systemic effect of climate change on ecosystems, and it argues for including measures of
changes in ecosystem characteristics from climate change, not just measures of economic values
of service flows provided by ecosystems.
         Two additional concerns reflect the nature of climate change as involving potentially
quite large and irreversible impacts. This has implications for how society evaluates moral
aspects of climate change risks and responses, in particular the implications for intergenerational
equity. In addition, the nature of these impacts is subject to a large degree of Knightian
uncertainty (Knight, 1921), in contrast to uncertainty that can be more readily quantified
statistically (i.e., statistical risk). Both of these considerations have implications for how
individuals perceive and evaluate climate change risks, which indicates in turn the usefulness of
having more information about what goes into shaping those perceptions.
       The next three sections of the paper develop these strands of argument for evaluating
climate change risks and responses. Section 5 summarizes the implications for providing
information in addition to what cost-benefit analysis can contribute.


2.     Differences in Ecological Valuation Metrics
Guidance for best-practice cost-benefit analysis prescribes that when an important impact of a
prospective policy cannot be monetized, it should be otherwise quantified to the extent
practicable. Similarly, distributional considerations are to be quantified and described separately
from the analysis of overall costs and benefits. 6 Nevertheless, the usefulness of applying cost-




5
  From my own limited participation in and observation of policy debates, those that disagree with the
framing and content of calculus can include a number of officials in high places.
6
  See OMB (2003), pages 2, 14, and 18, and US EPA (2014), Sections 7.5 and 11.1, for examples of such
guidance in the context of regulatory policy analysis. The EPA guidance in fact describes how economic
and non-economic information can be brought together in an organized way to inform users of the
regulatory analysis.     Hanley and Barbier (2009) provide further insight into best practices for
environmental cost-benefit analysis.
                                                      4
benefit analysis to climate change (and other larger-scale ecosystem changes) has been contested
on two grounds related to metrics for assessing values associated with ecosystems. 7
        One set of criticisms, from behavioral economics, argues that actual behavior of
individuals departs from the predictions of a standard economic model of maximizing
individualistic well-being. In addition to issues related to how individuals perceive and respond
to uncertainty, the topic of Section 4 below, several other issues related to measurement of
benefits and costs have been pointed out by various authors. Perhaps the most familiar is that
individuals seem to discount the longer-term future less extensively than is implied by the
standard model of exponential discounting. This means that longer-term costs of climate change
and longer-term benefits of response options count more than in standard cost-benefit analysis. 8
The behavioral economics literature also indicates that people exhibit a regard for others that
motivates self-sacrifices beyond what a standard preference ordering with altruism would predict
(J. Gowdy & Manner, 2010; Gsottbauer & Bergh, 2011).
         Another argument is based on loss aversion: individuals value reductions in income from
a particular reference point more than equal increases. This would tend to increase the cost (in
utility terms) of bearing nearer-term costs for longer-term gains. The same can be said of the
effects of inertia and the use of heuristics in evaluating a change from the status quo (Hammitt,
2013). Preferences are not a once-for-all given, but evolve with experience (J. M. Gowdy, 2004).
Perceived fairness is itself an influence on well-being, according to the behavioral literature, so
evaluation of climate change risks and responses needs to account for people’s feelings about the
justness of an outcome and the fairness of the procedures leading to it (Faucheux & Froger,
1995).
        In principle at least, these concerns could be addressed by modifying how a cost-benefit
analysis is carried out. Another set of criticisms, from philosophy and systems ecology, argues
that the concepts of monetization and net benefit calculation themselves are inherently limited in
their capacity to provide information sufficient for evaluation of the impacts of climate change
on ecosystems, and the benefits from policy responses to those impacts. Norton (2005) argues
that environmental problems are inherently “messy,” or “wicked” (see also Batie, 2008), in the
sense of not fitting comfortably into any one set of assumptions and value judgments—be it the
assumptions and judgments used by economists to determine what is important to study, or



7
  The impacts of climate change include impacts on productivity of agricultural lands; changes in species
range for forests and incidence of pests; and coastal flooding, among others. These can be evaluated at a
variety of spatial scales. At a local scale, one can assess the impact on crop yields or vulnerability of
specific coastal wetlands. At a broader scale, one can assess e.g. the impacts on productivity of a
country’s entire agricultural landscape, and the consequences for its social structure as well as economy.
As discussed below, the ability to assess these larger-scale impacts is a key element in philosophical as
well as methodological criticisms of applying cost-benefit analysis to climate change.
8
  See e.g. Hammitt (2013). There is increasing conceptual work in support of the argument that the
socially optimal discount rate applied to climate change should decline over time, even without resorting
to intergenerational equity or behavioral arguments (see, e.g., Arrow et al., 2013).
                                                        5
principles of distributive justice or inherent rights. The difficulty is especially acute in addressing
a problem such as climate change, since the relevant impacts operate across many different
spatial scales and associated temporal scales over which change occurs. From this perspective,
Norton questions the conceptual and practical soundness of any “monistic” or “reductionistic”
approach that seeks to impose one analytical framework leading to a single metric of value. Both
ecosystems and people are more complicated than that.
        The concern about how climate change can affect ecosystems in complex and large-scale
ways is hardly restricted to environmental philosophy. The latest (fifth) climate change
assessment by the IPCC provides evidence for serious concern about the potential impacts of
unrestricted anthropogenic climate change. Even leaving aside the risks of very large-scale
catastrophic events, climate change poses threats ranging from impacts on unique ecosystems to
impacts on the overall economy that grow more severe, the greater the change in global average
temperature. Even before serious effects are widely felt, the IPCC concludes, they will be felt in
lower-income and more vulnerable economies. 9
        Norton and Noonan (2007) further articulate the view that ultimately, the whole concept
of ecosystem used to organize information about the natural world and human impacts on it is
not just a measurable scientific construct. Instead, it “…rests on metaphors…[that] connect our
values and emotions with our choice of models” for evaluation. 10 Norton and Noonan argue that
the types of human values associated with longer-term and larger-scale functioning of
ecosystems that are suggested by this metaphor are not capable of being adequately captured in
an economic analysis, even one that includes existence values. Toman (1994, p. 405) classified
this position as a kind of “ecological organicism …[it] is not entirely individualistic; it also
encompasses concerns for ecological systems and the human species as a whole.” 11
       Nelson (2013) goes even further in emphasizing the connection of values to emotions.
She argues that feelings about what is right or necessary (e.g., empathy or shame) are as
important or more important than moral principles, let alone preferences, in explaining what
people actually do. What drives choices then becomes a much more complicated set of
motivations than is envisaged in the standard revealed-preference individual economic model
underlying cost-benefit analysis—including issues related to altruism, community, loyalty, self-
image, and importantly, the conditioning of past experiences.
       What do these observations on the limits of standard economic metrics tell us about what
is important to measure for assessing climate change? Norton and Noonan (2007) argue that this
question cannot be answered until individuals with different values and perspectives begin to



9
    See IPCC (2014), page 9. I am grateful to a referee for pointing this out.
10
   To illustrate this point, the authors quote Aldo Leopold, the American preservationist and philosopher,
who said in his essay “Thinking Like a Mountain” that “…only the mountain has lived long enough to
listen objectively to the howl of the wolf” (Leopold, 1949, p. 129).
11
  For a somewhat contrary view of what can be incorporated in economic analysis of large-scale risks,
see Barbier (2011).
                                                            6
have a common understanding of the problem. However, this begs the question of how such a
shared understanding can be gained in practice (see Section 5 below). At the very least, it would
seem to be important to provide information on the vulnerability of different ecosystems and
their functions to climate change, and the perceptions that people hold about such vulnerabilities,
in addition to measures of the economic costs of climate change.


3.  Irreversibility, Intergenerational Equity, and Assessment of Climate
Change
Toman (1994) argues that the larger the scale and the more irreversible the impacts of ecosystem
changes, as would be the case with unconstrained growth in greenhouse gas emissions, the more
limited is the ability of economic cost-benefit analysis to adequately inform social choices. There
are two reasons for this. One is that larger and more irreversible changes can call into question
the common economic assumption of significant substitutability between “natural capital” and
other forms of societal wealth, which at least in principle would make possible continued
improvements in human well-being even with rising climate change damages. The limit on
substitutability can reflect both the difficulty for individuals to evaluate losses of unique
environmental and cultural assets, and the challenge of overcoming negative impacts on
economic activity from seriously compromised ecosystem processes that are fundamental for
economic function and life itself. When substitution is more limited, shadow prices are harder to
define meaningfully. This compounds the problem already noted regarding the adequacy of
economic valuation statistics to reflect concerns regarding large-scale threats to the environment
(Norton & Toman, 1997).
       The other reason is that larger and more irreversible ecosystem changes of the type
expected from global climate change are likely to have important implications for
intergenerational equity, about which standard cost-benefit analysis is silent. Purely economic
motivations tend to have a fairly short-term orientation, even if individuals’ preferences
incorporate a degree of altruism. Equity-based considerations regarding the risks of climate
change or the benefits of response options would be grounded in moral sentiments regarding the
importance of maintaining a wide range of opportunities for future generations in general.
       Even with such a motive, however, it may not even be possible to provide an
intergenerational bequest with comparable opportunities to the present, unless certain key
elements of natural capital are safeguarded from the adverse impacts of climate change. Howarth
(1997, 2007) provides a deeply probing analysis of how concepts of rights of/responsibilities to
future generations, and ethics of stewardship held by the current generation, can shape an
approach to “sustainability as opportunity.” His analysis leads to recommendations for
incorporating specific bequests of natural capital (those related to underlying life-supporting
ecosystem functions in particular) such that there is a meaningful possibility for future
generations to enjoy undiminished (or increased) opportunities. In practice, there continues to be
empirical debate among economists and ecologists about what parts of the natural endowment
should be regarded as “critical natural capital” (see Ekins, Simon, Deutsch, Folke, & De Groot,
2003 for one approach).

                                                    7
         In light of the challenges discussed above, some analysts have looked for evaluation
criteria beyond the expected net-benefit measure of standard economic cost-benefit analysis. A
number of approaches have been suggested that share a link to the idea of a “safe minimum
standard” (SMS) first advanced by Ciriacy-Wantrup (1952) and refined by Bishop (1978).
Woodward and Bishop (1997, p. 506) state that “According to the SMS, policymakers should
focus on avoiding critical levels of resources below which economically irreversible degradation
of the resource will take place.” Quoting Ciriacy-Wantrup (1952, pp. 261–262), they continue
with the observation that “the economic rationale for adopting a safe minimum standard defined
in physical terms is allowance for uncertainty” (emphasis added). They argue that an SMS
approach is entirely consistent with rational choice if there is significant and difficult-to-quantify
uncertainty.
         Norton and Toman (1997, p. 562), again quoting Ciriacy-Wantrup, state that “This
criterion places a larger burden of proof on those who would destroy important ecosystem
functions by asserting that the resource be saved ‘provided the social costs are bearable’… This
rule requires those who would undertake such a risk to a resource to show the costs of protecting
it are unacceptably high before undertaking the risk. It is a concrete expression of a moral
judgment that large-scale negative environmental effects may have unacceptable consequences
for the intergenerational distribution of opportunities and well-being.” Importantly, the SMS
concept explicitly does not require the establishment of fixed, immutable targets without
balancing costs and benefits. However, the burden of proof in evaluation of costs and benefits
shifts (to a degree dependent on the circumstances) toward protecting the resources in question.
        Norton and Toman (1997) and Toman (1999) build on these observations to
conceptualize a “two-tier” model for evaluating ecosystem values and risks. In this model,
society establishes higher-level rules for determining when environmental impact assessment and
economic cost-benefit analysis can be used to inform decisions, and when a broader and more
pluralistic approach to evaluation and policy dialogue is needed. They argue that to properly
assess risks and costs requires looking at the natural systems involved across multiple spatial and
temporal scales.
        What do these observations on the importance of irreversibility and intergenerational
equity tell us about what is important to measure for assessing climate change? If there were
broad agreement on the composition and scale of “critical natural capital” to be protected, such
agreement would tell us a lot about what physical indicators need to be measured to provide a
fuller picture of climate change risks and the impacts of potential responses. Unfortunately, such
agreement does not exist, though efforts such as that of Ekins et al. (2003) provide valuable
insights about what is important to consider. In particular, it is important to provide information
about the substitutability of other inputs for natural capital services, as a way of gauging the
irreversibility and significance of climate change impacts. As noted, this means consideration of
ecosystem functions and climate change impacts at various spatial as well as temporal scales.
Ultimately, information about the proximity of important ecosystem functions to highly adverse
“tipping points” would be especially useful. Moreover, in a safe-minimum-standard approach,
the cost of preventing further ecosystem degradation matters as well.


                                                      8
4.   Perceptions of Climate Change Uncertainty and Evaluation of Response
Options
Dealing with uncertainty is an important element of good practice in standard cost-benefit
analysis. Mathematically, when marginal cost is increasing (that is, total cost is convex), the
expected value of cost evaluated across different uncertain states of the world is larger than the
cost of the expected value of those states (i.e., the certainty-equivalent). If the cost in question is
the cost of climate change damages, then this simple argument implies that all else being equal,
cost-benefit analysis that fully accounts for climate change uncertainty will imply more
aggressive mitigation (and adaptation) activity than a deterministic analysis using expected
values of climate change impacts. Risk aversion with respect to uncertain future climate change
impacts strengthens this conclusion, as does the economics of irreversibility when less
aggressive mitigation causes potentially valuable options to be foreclosed. Another factor
arguing for more aggressive early mitigation is the possibility of a larger-scale future catastrophe
from climate change whose probability of occurrence rises as greenhouse gases accumulate. 12 On
the other hand, mitigation costs are uncertain as well, and early commitment to a mitigation
strategy involving irreversible investment also forecloses options (the possibility to use more
effective or cheaper mitigation technologies that emerge in the future from current R&D).
        Dealing with these complications is not easy, but it can be done and is being done in
some studies of long-term climate change impacts and the benefits of mitigation. A bigger
challenge for dealing with uncertainty in assessment of climate change impacts and response
options is identified in behavioral economics research on how individuals perceive and respond
to low-probability, high-impact events. Large-scale catastrophic events of interest would include
major sea level rise from melting and collapse of Antarctic or Greenland ice sheets, large-scale
ecosystem degradation (e.g., the drying out and burning of vast areas of the Amazon forest), or
release of methane current trapped in permafrost and under water that would create a runaway
positive feedback loop in terms of warming (see, e.g., Lenton & Ciscar, 2013). As pointed out,
for example by Pindyck (2013), the way in which these risks are addressed is a key element in
determining the logic and soundness of climate policy. However, many low-probability, high-
consequence impacts of climate change are shrouded in Knightian uncertainty.
        Among the key findings of behavioral research are that individuals tend to weight losses
more heavily than equivalent gains. They may also be concerned with ex post regret: how far
away an actual policy outcome may be from the ex-ante expectation. In addition, individuals
tend to anchor their judgments in the status quo, thus implying greater resistance to the relative
certainty of near-term mitigation costs over the uncertainty of long-term risk reduction than
might be predicted by a standard expected-gains model. Individuals may fix attention more on
the consequences of a dreaded event than on its perceived likelihood, so they may see actions
that only reduce (but do not eliminate) the probability of such an event as not that useful.
Individuals may give more weight to unfamiliar and potentially large-scale hazards than to more
familiar and serious hazards, thus implying less resistance to a strong mitigation response


12
     See, e.g., Kopits, Marten, and Wolverton (2013), and van der Ploeg and de Zeeuw (2014).
                                                         9
(though that resistance would also depend on how uncertainties associated with mitigation
activities were viewed). 13
        What do these observations on the uncertainty regarding how individuals respond to
uncertainty tell us about what is important to measure for assessing climate change? One
implication is that it may be quite difficult to describe a stable and generalizable measure of
willingness to pay for reducing the risks of climate change if individuals make choices in ways
that are quite distinct from the predictions of standard expected-utility theory. Individuals may
respond to new information about climate change by altering the ways they frame and anchor
concerns about it. Differences in perception of climate change uncertainty across individuals can
pose significant challenges to the standard construct of a representative economic agent. Studies
of preference elicitation by, e.g., Howarth and Wilson (2006) and Spash (2008), show that
provision of information and communication among respondents can significantly affect values
expressed. 14
        It is unclear how different perspectives on the deep uncertainties surrounding climate
change could be resolved any time soon. 15 However, the nature of challenges with respect to
understanding how individuals perceive and respond to climate change uncertainty also points
toward some ways to try to organize the information gathered and analysis performed. Starting
with the observation that individuals confront deep uncertainty with respect to climate change
and may exhibit elements of ex post regret, analytical approaches that seek to quantify and
minimize potential regret can be as (or even more) informative than an expected net benefits
analysis based on extremely speculative subjective probabilities (Kunreuther et al., 2013;
Lempert, Groves, Popper, & Bankes, 2006). The key is the space over which potential regret is
defined and assessed. In particular, it is important to consider regret over how a policy performed
relative to expectations in mitigating greenhouse gases or strengthening resilience to climate
change, regret over divergence between anticipated and actual cost of implementation, and regret
over side effects (more negative or less positive than anticipated).
       Since individuals facing deep uncertainties have limited capabilities to “price” different
aspects of climate change risks, there is also a case for using a multi-criteria approach. Kousky et



13
     For further discussion see e.g. Summers and Zeckhauser (2008), and Berger et al. (2011).
14
   Sagoff (2004) argues that democratic processes for obtaining expressions of beliefs and desires is the
appropriate way to deal with such social questions, and that technocratic cost-benefit analysis has little
place in this. An alternative view is to see society as delegating to elected and/or appointed leaders the
task of addressing climate change (and other wicked problems) in as rational a way as possible for society
as a whole, including the practice of a kind of benevolent paternalism with respect to individual
preferences that are subject to logical paradoxes (e.g., intransitivity, non-monotonicity) or misperception
of risks (Zeckhauser & Sunstein, 2009).
15
  Given that individuals may be little affected by whether the risk of a climate change catastrophe has a
probability of 1% or 0.1% (see, e.g., Summers & Zeckhauser, 2008), there is some reason to doubt how
much even significant scientific progress in narrowing climate change uncertainties might affect
individuals’ beliefs and preferences over what to do about the risk of climate change catastrophe.
                                                         10
al. (2009) illustrate this approach for assessing different policy responses to lessen the potential
for a global-scale climatic catastrophe. They evaluate radical energy sector decarbonization,
radical land use changes for adaptation, and injection of particulates into the atmosphere to
prevent warming (a form of so-called “radiation management”), using four criteria: technical
efficacy, cost, robustness, and flexibility. Bellamy et al. (2013) evaluate a number of general
responses to climate change (mitigation and adaptation) against several criteria including
economic efficacy in limiting climatic change, other environmental impacts, ethical issues,
technical feasibility, and political and social aspects. Better understanding which of these criteria
are more relevant than others for assessing public perceptions of climate change risks and
response options can provide information on what types of scientific and technological
information may be most useful.


5.     Concluding Remarks
Economic analysis remains a key part of the effort to assess climate change risks and response
options, even after one recognizes that conventional cost-benefit analysis has important
limitations in addressing these issues. Nevertheless, differences in ecological value metrics, the
importance of addressing intergenerational impacts and critical natural capital considerations in
the face of irreversibility, and the existence of deep uncertainty surrounding climate change point
to the value of having several types of information for assessing climate change.
        My focus in this paper has been on additional types of information that can help provide a
more complete information base for assessing climate change risks and response options. It is
important to note first that our current capacity for policy evaluation remains limited. We can
measure the atmospheric concentration of greenhouse gases in the atmosphere (though even that
measurement depends on a set of judgments about the CO2-equivalency of other greenhouse
gases). We can estimate the rate of greenhouse gas emissions coming from various sources. We
can also measure (with varying degrees of precision) other statistics relevant to the changing
climate, such as the areal extent of glaciers and forests, or changes in ocean temperature, salinity,
and acidity. While various sorts of physical measurements could be used as proxy indicators for
the state of natural capital relevant to the global climate system, translating such physical
indicators into measures that relate more clearly to potential future human well-being (e.g.,
changes in agricultural yields, frequency of extreme weather events, or survival probabilities for
iconic species) depends on a variety of assumptions about various factors subject to considerable
uncertainty. We do not escape the problem of uncertainty or the need for making difficult value-
related judgments by shifting from economic to physical indicators.
        One implication of the discussion in this paper is that improved information about the
scale and irreversibility of climate change impacts can be especially useful. Large and
irreversible impacts tend to be ones for which monetization of costs is most difficult, uncertainty




                                                     11
is the greatest, and the more precautionary approach of a safe minimum standard is most
relevant. 16
       Information is needed in particular about the speed of climate change, as well as the
magnitude. This information is useful for gauging risks faced by hard-to-value ecosystem
services, and ecosystems that may irreversibly convert to a fundamentally different state.
NOAA’s climate information web site is an example of a source that provides a variety of such
information. 17 Better understanding also is needed as well about the nature of ecosystem
vulnerabilities from climate change at a systemic scale, and the consequences of those
vulnerabilities for human well-being. This kind of information provides a capacity for making
more informed judgments about resource substitutability, vis-à-vis “critical natural capital.”
Similarly, information is needed about the flexibility and robustness of potential policy responses
as well as their expected benefits and costs. These are areas where research needs to advance
considerably to provide the information desired.
        To make well-informed judgments about climate change risks and policy responses also
requires better understanding how the public perceives climate change risks, and how those risks
compare with other policy-relevant risks. In general terms, the public’s attitude toward risk can
substantially influence the “social cost of carbon” (see, e.g., Anthoff, Tol, & Yohe, 2009).
However, as noted in Section 4, there are reasons that individuals may systematically overstate
or understate the significance of climate change risks because, e.g., probabilities are
misconstrued or impacts are outside the realm of experience. 18 Thus, information about how
society evaluates other risks (e.g., expenditures on reducing risks of other causes of ecological
degradation and losses from extreme events) can complement information on climate change
risks themselves and public attitudes toward them in establishing comparative risk valuations for
use in policy evaluation.
        One final point involves the level (if any) of aggregating to undertake in looking across
different types of information. For example, Bellamy et al. (2013) aggregate the evaluations of



16
   One approach to economic analysis in this context involves evaluating the potential cost of achieving
different degrees of slowdown in the accumulation of greenhouse gases in the atmosphere, and then
making informed judgments—based on a range of different types of information about comparative
risks—about what levels of climate change risks are acceptable compared with the costs, as best as they
can be understood. This approach reflects the idea of Ciriacy-Wantrup mentioned previously, that social
costs of protection should be “bearable.” It does not rely on the untenable assumption of lexicographic
societal interests, with reduction of climate change risks coming first and costs of risk reduction second.
Nor does it attempt to summarize the nature of climate change risks with a few numbers on the marginal
(discounted present-value) cost of greenhouse gas emission accumulation.
17
   http://www.climate.gov/#understandingClimate. The acceleration of climate change is often noted as an
indication of why there is need for greater concern. On the other hand, recent research has begun to shed
light on how a slowing down of certain processes may be a harbinger of an approaching tipping point
(Lenton, 2011; Scheffer et al., 2012).
18
     This is different than “dread” of an unfamiliar risk, which is a reflection of preferences.
                                                            12
their various policy options across their multiple criteria to come up with overall composite
scores. This kind of aggregation is very familiar in working with economic data, where relative
(actual, adjusted, or shadow) prices provide the necessary weights. It is also used in other
contexts.
        Bohringer and Jochem (2007) provide a wide-ranging critique of both economic and non-
economic indicators for sustainability that has relevance for this discussion as well. They argue
that the indicators they review do not adequately represent all the facets of sustainability, and
that there are no generally accepted ways to normalize or weight different metrics to form an
indicator. Aggregation inherently involves value judgments that can be easily lost once the
aggregated indicator is made the focus of attention, involving weights that are open to criticism
in terms of their implications for human values. 19 It seems to me better to retain the original
information collected so that the relevance and adequacy of specific metrics for assessing climate
change can be judged and debated.




19
     Ravallion (2010) makes this point in his critique of “mash-up” indicators of economic development.
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