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1997 Progress Report: Innovation in the Valuation of Ecosystems A Forest Application
EPA Grant Number: R824699Title: Innovation in the Valuation of Ecosystems A Forest Application
Investigators: Russell, Clifford , Dale, Virginia
Institution: Vanderbilt University , Oak Ridge National Laboratory
EPA Project Officer: Clark, Matthew
Project Period: October 1, 1995 through September 1, 1997
Project Period Covered by this Report: October 1, 1996 through September 1, 1997
Project Amount: $139,327
RFA: Valuation and Environmental Policy (1995)
Research Category: Economics and Decision Sciences
Description:
Objective:The goal of this project is to investigate the claim made in Gregory, et. al. 1993 (Journal of Risk and Uncertainty, Vol. 7), that multi-attribute utility (MAU) questioning techniques hold promise for direct valuation of environmental goods and services because they: (a) reduce the cognitive demands on lay respondents by simplifying the questions asked; and (b) are congruent with the multi-dimensional character of many problem settings, ecosystem valuation in particular. Specifically, using a forest valuation case study, we are examining whether and how MAU: (1) can be implemented in a manner consistent with the case; and (2) affects how lay respondents consider six-dimensional descriptions of forests.
>Progress Summary Our approach involved the creation of an MAU valuation survey instrument that is based on a six-dimensional description of a southern appalachian forest. The dimensions are intended to be ecologically meaningful and yet relevant to respondents' judgments about the value of forests to them. (We do not prejudge the identities of the sources of these values or the suitability of any particular forest relative to any particular one of these sources.)
The six dimensions or attributes that we are using are listed in Figure 1, which is the first response work sheet from the survey. The questions on this sheet ask respondents to identify their most- and least-preferred levels of the attributes. They do this as they view visual representations and read descriptive material concerning the attributes.
The other steps in the survey are sufficiently straightforward to be within the capability of even respondents with severely limited education. These steps are: (1) to list the attributes in order of declining importance (triggered by a question asking which attribute the respondent would change first, from least to most preferred level, if they had the power); (2) to supply "swing" weights that quantify the relative importance list; and (3) to answer willingness to pay (WTP) questions concerning the most important attribute. (These questions ask about WTP to ensure that the attribute will be found at its most, rather than its least, preferred level in a forest that the respondent could easily visit.) Linearity and independence assumptions make these answers sufficient to determine what we might call the "sub-WTP" functions for each attribute and respondent. (There is some residual uncertainty regarding parts of the functions for attributes for which a respondent has picked an interior most-preferred level in the first step.)
The last questions of the survey, and the key to the test of whether MAU makes a difference, concern three "blended" forests ? forests that are described using the same six attributes in three different combinations, with the combinations presented all at once. Respondents are asked to state their preferences for forest 1 versus forest 2, for forest 2 versus forest 3, and for 1 versus 3 (the last question providing them with enough scope to display intransitivity). Respondents are also asked to supply WTP judgments for the difference between their preferred and not preferred choice in each of the first two pairings. Based on their answers to the MAU questions, we can calculate WTP numbers for each respondent and blended forest. These can then be compared with the stated preferences and WTP numbers from the last part of the survey.
Progress Summary:Our findings should be considered very preliminary. The first data come from a "deliberative polling" exercise held in Nashville this past fall, from which we obtained about 75 completed surveys. Another, larger, event will be held in early March. This mode of administration has been necessary because we believe the instrument is far too long for a successful mail survey, and our budget will not support one-on-one interviewing.
We find that MAU does work in the sense already noted; i.e., that the tricky business of asking questions concerning a multi-dimensional ecosystem can be simplified enough that poorly educated respondents can answer. But this achievement comes at a price. Despite our many simplifications, the survey is long.
On the crucial matter of the blended forests, our first examination of the data reveals that people who have worked through all of the material do not have much trouble when asked to consider changing combinations of all six attributes. Thus, we have seen no intransitivity implied by the preference statements, suggesting no serious confusion. Further, by and large, the stated preference orderings are the same as the orderings implied by the answers to the MAU questions. And the stated WTPs are at least in the same realm as the values implied by the sub-WTP functions derived from the MAU responses.
While we do not want to base conclusions on these early numbers, they suggest that a large investment of time and effort in familiarizing respondents with aspects of a complex problem may be as important as the details of the questioning technique employed to seek their preferences and even their WTPs.
Future Activities:Our next steps will involve additional data gathering, computation of all relevant quantities for all respondents, and development of appropriate formal tests for the variety of comparisons possible within the data. Journal Articles:
No journal articles submitted with this report: View all 5 publications for this project
Supplemental Keywords:Economic, Social, & Behavioral Science Research Program, Scientific Discipline, RFA, Social Science, decision-making, Economics & Decision Making, Ecology and Ecosystems, public issues, stakeholder, ecosystem valuation, policy analysis, psychological attitudes, public resources, decision analysis, economic objectives, incentives, environmental policy, willingness to pay, multi-attribute utility, valuing environmental quality, community involvement, Appalachians, deliberative policy, forests, multi-objective decision making, public values, social psychology, valuation, environmental assets, interviews, environmental values
Progress and Final Reports:
Original Abstract
Final Report