Values, Numbers, and Decisions: The Use of Constructed

Preference Approaches in Environmental Valuation

Robin Gregory, Decision Research, Vancouver, B.C.

Researchers interested in how people assign values in the context of
environmental choices often end up shaking their heads in frustration at
the messiness of the venture. Although the prescribed steps may be
clearly set out ahead of time, in my experience one is never quite sure
what one will find in the course of actually completing an evaluation
study. The potential problems are numerous: identifying the relevant
stakeholder groups without omitting any significant parties; defining a
manageable set of issues and understanding enough of their context and
science to ask meaningful questions of participants; establishing the
key dimensions of the problem, and knowing explicitly what to include
and what not; deciding whether to work with small groups or large, a
random survey or clustered sample; determining how tradeoffs should be
made, whether in monetary or other units; establishing a relevant time
frame; and speaking effectively to multiple audiences, including
interested public and expert and government listeners or readers. Often,
a project turns out to be either enjoyable or a pain depending on such
unpredictable factors as which personalities in a stakeholder or client
group emerge as dominant, or the degree to which local politicians
believe they are free to interfere with the agreed-to process.

A constructed preference approach to evaluation acknowledges many of
these sources of frustration. It is based on the insights of
multiattribute utility analysis and, in essence, makes the point that
the process of assigning values to the multiple dimensions of many
environmental problems is a novel and difficult task that requires help.
Because these values are not known a priori, participants in a survey or
group are thought to work with available cues and signals to construct a
value. These cues and signals include factual information about the
item, the values placed on similar goods, the scale or metric being used
for the valuation, and the social and historical context within which
the valuation takes place.

A careful construction process should increase the validity of a
response; in particular, consideration of the mulitple dimensions of a
proposed action should improve the fit between the good being valued (by
an individual) and the good thought to be under consideration (by
policymakers). Careful construction should also decrease the influence
of the embedding effect, although the success of the construction
process will vary across survey or group participants. The perceived
precision of a constructed response also will vary across participants;
some will think that they can express their value(s) closely, whereas
others (more critical of the construction process, or simply less sure
of what they believe) will interpret their own response as only a vague
estimate or subject to substantial error.

This variation in the precision of responses matters to analysts,
because some circumstances call for ballpark estimates of value (either
quantitative or qualitative) that can support a defensible decision
process whereas others require quite precise numbers to support a more
exact evaluation. In the former, ballpark category I=d place suggested
actions that have significant nonmonetary impacts (e.g., cultural and
affective dimensions) as well as those that are either clear winners
(i.e., high benefits to costs ratio) or clear losers. In the latter
category, I=d place actions that compete closely with other alternatives
or ones that have strong support but imply irreversible consequences
(e.g., significant increases in the probability of extinction of a
species). In general, I believe it is helpful to determine ahead of time
(a) why a valuation number is needed for the decision at hand; (b) if it
is, how precise the numerical expression of a value estimate needs to
be, and (c) to elicit assessments of the perceived Avalue range@ from
expert and public participants in the process.

Consider a hydroelectric water-licensing project on the Alouette River
in southern British Columbia, where in 1996 I co-led an expert-public
stakeholder Management Committee (with Tim McDaniels). Higher water
flows and a more natural hydrologic regime meant better fish habitat and
improved recreational opportunities, but also lower electric power
production and altered flood risks. Our task was to facilitate a
multi-stakeholder committee of about 20 representatives, to consider the
pros and cons of alternative water flows across a broad range of impact
categories, and to make recommendations to the local utility. For some
of the actions under consideration, there was no reason to conduct
detailed quantitative analyses across impact categories because they
were either clear winners (e.g., occasional Aflushing flows@ to aid
salmon habitat) or clear losers (e.g., removing the dam, which would
imperil neighboring residents). Stated differently, the values of
stakeholders led to a clear decision even though the associated numbers
were vague. For other actions, the group quickly focused on
consideration of a range of options (e.g., desired water flows of 70 -
100 cfs) but required detailed quantitative analyses to aid in
distinguishing the distribution of anticipated benefits, costs, and
uncertainties. For these cases, impacts were considered across the five
value categories using simplified objectives by alternative matrices,
which simultaneously organized the available information on the pros and
cons of competing alternatives and served as a reference for coming up
with suggestions for mitigation and compensation. Although it would have
been possible to calculate the relative utility of these alternatives,
the decision process adopted by the management Committee instead led to
decisions being made on the basis of explicit trade-offs across key
objectives: questions, for example, of the type AIs it worthwhile to
decrease electricity production by X mw/year in order to increase salmon
production by Y fish/year.@ Quantitative (including monetary) values
were used to help in making these comparisons but only to the extent
necessary; power production effects were closely modelled but, for other
value dimensions, broad distributions were often sufficient because at
either end of the anticipated impact range the same decision was clearly
preferred. Thus, time and money was spent in structuring the decision
and in identifying the various impact categories rather than in coming
up with better numbers to feed into the analysis.

A similar approach is now being used to assist the National Estuary
Program in Tillamook Bay, Oregon to develop a community-supported
estuary protection plan. In this project (co-led with Trina Wellman),
the main focus is again to find a way for local residents to consider
the multiple components of value that will be affected if any of a set
of alternative actions is undertaken. Getting true citizen participation
in this type of process is difficult: involvement at a general level is
easy, but cooperation becomes more problematic once difficult trade-off
questions start to be asked. Estimates of residents= willingness-to-pay,
such as would be obtained from a contingent valuation survey, will be an
output of some portions of the study. But in addition, we will provide
detailed information on the relative level of community support for
these actions based on equally important considerations such as the
labor (e.g., time and training for local farmers) required for their
implementation, their equity implications, and their level of community
acceptance.

There is both a theoretical and a practical argument here for explicit
attention to preference construction. The theoretical argument is that
dollar-scaled attributes involved in the decision (as measured by
willingess-to-pay) form only one of several, simultaneously valued
components of well-being. Asking community residents to collapse these
other values into dollar terms is too heroic a task; as Paul Slovic and
colleagues noted in the context of selecting a nuclear repository site,
we would be Aasking them to tell more than they can know@ (Slovic et.
al, 1991). The practical argument is that, in the context of this
social/ecological/economic decision, no survey asking for wtp responses
alone would make sense to local citizens or be permitted by community
leaders. Thus, a multi-attribute approach is required to integrate the
environmental valuation process with community-based participation.

Would better numerical information on benefits or costs help these
evaluation exercises? Perhaps, but I expect only a little. The real
stumbling block is much more in the framing of the decision process and
in finding ways to encourage broad-based and informed debate among local
citizens about the multidimensional impacts of the actions under
consideration.

Despite this overall endorsement of the approach, many questions still
remain concerning the application of constructed preference approaches.
One of the more interesting issues has to do with selection of either a
choice or pricing mode for value construction. If the evaluation
question considers different levels of an action (e.g., different levels
of stream clean-up), then typically an individual will invoke a set of
similar alternatives whose major differences will be at the margin,
expressed in terms of peripheral or secondary alternatives. If an action
is instead considered in contrast to other, unlike items (e.g., spending
money on stream clean-up versus keeping the money for personal use),
then the evaluation task is more likely to focus on prominent or central
attributes of the choice. For many environmental assets, this latter
framing or mode of construction \-- emphasizing choice rather than a
direct evaluation of worth \-- may result in the assignment of a
significantly higher value because it emphasizes the more attractive
attributes of the environmental alternative (e.g., its ethical
foundations or the provision of benefits for future generations). People
may want the things they personally can buy but think that they ought to
prefer the public good, so the weight of the arguments favoring the
environmental option will increase when a choice is required. Although
laboratory results on this topic are quite compelling, I haven=t yet
seen any tests of this hypothesis from community participants involved
in real environmental decisions.

Another issue has to do with the time frame for the analysis, since
people are being asked now to make choices about the future (in
Tillamook, for example, our valuation efforts follow closely a separate
community survey to Avision@ alternative futures for the region). This
requires guesses about the future consequences of present actions, but
it also requires (as noted by March, 1978) making guesses about future
preferences for these consequences. If this element of additional
uncertainty is brought explicitly into the preference construction
process, experience suggests that individuals are more likely to adopt a
precautionary (risk-averse) attitude. In part, this is due to the
heightened salience of responsibility costs: people feel worse about a
negative outcome they have had a part in choosing than if it simply
occurs. In addition, the act of making uncertainty about future
preferences explicit appears to have the result of making the future
more real, which could lower an individual=s discount rate and could
change what a person wants to know and value regarding the range of
possible future consequences. I know of very little research about how
explicit preference construction affects inter-temporal choices, but I
think that the topic is important.

In conclusion, I am struck by the complexity of many of the
environmental decisions we typically ask individuals to make and the
lack of training or insight they are given in how to make these
decisions responsibly. The fact that we can obtain a number and attach
it to a valuation priority \-- \$30 for an individual=s extra day of
freshwater fishing, or \$30 million for a community=s efforts to clean
up a polluted estuary \-- means little if the stated context for the
decision is either poorly understood or inappropriate. In most cases, I
believe that the complexity of the environmental valuation tasks
requires a deliberate, thoughtful process of value construction across
multiple dimensions and across multiple metrics in order to help
individuals arrive at an informed decision.

This comment, however, raises a final issue, which is how little I
believe we know about what constitutes a sufficiently Awell-formed@
value. I might lead a group of stakeholders through a preference
construction exercise, asking them to delineate and measure value
attributes and even to assign these components priorities (i.e.,
weights) in the context of the decision at hand, in hopes that their
environmental choice will benefit from a Awell-formed@ expression of
value. But who is to say that this value is well-formed? What criteria
exist for measuring the progress that has been made on defining the
participants= values? Payne, Bettman, and Schkade (in press) have made a
start in asking questions such as this, following the analogy of
developing a Abuilding code@ for the construction of values. But it is
only a start. Currently, I=m wondering whether the universe of
environmental values might not be divided into two parts. The first is
composed of all those things that we assign values to on the basis of
readily at-hand cues and social discourse. The second is composed of
those things that are fundamental to who we are and to our sense of
well-being. It may that that the first set of values can be constructed
more or less well but they always will be susceptible to alternative
framings; given the informational equivalent of a minor earthquake,
these constructed values will either shake a whole lot or fall over. The
second set of values may in fact be very solid and may survive the
cognitive earthquake with no problem. If this is true, perhaps we want
to focus more of our evaluation efforts on understanding and correctly
eliciting this second, Abedrock@ category of values, so that they can be
more fully represented in policy decisions.

*References*

March, J. (1978). Bounded Rationality, Ambiguity, and the Engineering of
Choice. *Bell Journal of Economics*, 587-608.

Payne, J., Bettman, J. & Schkade, D. (In press). Measuring Preferences
in a Constructive World: Towards a Building Code. *Journal of Risk and
Uncertainty*.

Slovic, P. et. al. (1991). Perceived Risk , Stigma, and Potential
Economic Impacts of a High-Level Nuclear Waste Repository in Nevada.
*Risk Analysis*, 683-696.

file: nashvill.doc