Ecological Economics 34 2000 63 – 76
M ETH OD S
Valuing watershed quality improvements using conjoint analysis
Stephen F arber
a,
, Brian G riner
b
a
Graduate S chool of Public and International A ffairs, Uni6ersity of Pittsburgh, Pittsburgh, PA
15260
, US A
b
A ngus R eid Group,
1700
Broadway, N ew Y ork, N Y
10019
, US A R eceived 25 October 1999; received in revised form 31 January 2000; accepted 1 F ebruary 2000
Abstract
This paper reports on a study of valuation of multiple stream quality improvements in an acid-mine degraded watershed in Western Pennsylvania. A technique extensively used in marketing research, conjoint CJ analysis, is
used in conjunction with a random utility model R U M to establish shadow valuations for various combinations of stream quality improvements in two streams. The technique shows promise in the valuation of ecosystems, which
provide a complex variety of services. Several variations on respondent choice, binary choice BC and intensity of preference IP were used, where the latter allowed for an expression of degree of preference between status quo and
alternative conditions. The sample constituted a panel data set from which user and non-user valuations were distinguished. In addition, sample respondents were identified by the distances of their residences to the stream sites,
permitting the analysis of effects of distance on quality improvement valuations. These valuations suggested that persons living within roughly 50 miles of the evaluated stream segments place some positive value on stream
improvements. © 2000 Elsevier Science B.V. All rights reserved.
Keywords
:
Conjoint; Valuation; Watersheds www.elsevier.comlocateecolecon
1. Introduction
The purpose of this study is to employ a utility- theoretic based conjoint analysis CJ for valuing
watershed quality improvements. While there are many examples of the use of CJ in marketing
M cF adden, 1986; Louviere, 1988; Wittink and Cattin, 1989; G reen and Srinivasan, 1990, it has
had limited use in economics. This is in spite of the fact that CJ estimating models are compatible
with R andom U tility M odel R U M formulations of choice M cF adden, 1981. In the environmental
area, CJ has been used to value water quality Whitmore
and Cavadias,
1974; Smith
and D esvousges, 1986, visibility improvements in na-
tional parks R ae, 1983, diesel odor reductions
Corresponding author. F ax: + 1-412-6482605. E -mail addresses
:
eofarbbirch.gspia.pitt.edu S. F arber, grinermindspring.com B. G riner
0921-800900 - see front matter © 2000 Elsevier Science B.V. All rights reserved. PII: S 0 9 2 1 - 8 0 0 9 0 0 0 0 1 5 3 - 1
Lareau and R ae, 1989, preferences for siting municipal landfills Opaluch et al., 1993, prefer-
ences for various energy programs Johnson and D esvousges, 1997, preferences for
waterfowl hunting M acK enzie, 1993, wild salmon manage-
ment options R oe et al., 1996, preferences for recreational activities G an, 1992; Adamowicz et
al., 1994, and values for protecting threatened woodland caribou populations Adamowicz et al.,
1998.
The purpose of CJ is to analyze choice in a multi-attribute context. Individuals are presented
choice alternatives with varying values of at- tributes, and are asked to choose the best or
rankrate the
alternatives. This
hypothetical choice setting appears to mimic real choice set-
tings in requiring the individual to simultaneously consider many dimensions of alternatives. The
potential of CJ procedures for contingent valua- tions of ecosystems is direct. F irst, allowing one
of the attributes to be a ‘price’ can be used to reveal implied valuations of individual attributes.
Second, the multidimensional nature of the alter- natives allows a more realistic representation of
complex ecosystems where a variety of dimensions may be important to individuals. Third, the
choice is referendum-like and thereby emulates public decision situations.
CJ is defined as ‘‘any decompositional method that estimates the structure of consumer’s prefer-
ences…given his or her overall evaluations of a set of alternatives that are prespecified in terms of
levels of different attributes. Price typically is included as an attribute’’ G reen and Srinivasan,
1990. As a general illustration of the CJ proce- dures, suppose we are interested in valuing a
wetlands system and its component services. Sup- pose wetlands services include storm protection
S , recreational fishing F, and water treatment W . Let the utility level of the individual depend
upon the level of these services as well as some price placed on the bundle of service, P. Then
U = f S , F, W , P . In particular, suppose that U = aS + bF + cW + dP, a general linear utility
function. CJ provides estimates of the ‘part- worths,’ a, b, c and d. In general, knowing these
part-worths permits the valuation of any wetlands system since cd, for example, measures the mar-
ginal value placed upon water quality treatment. The CJ procedure establishes several levels of
the attributes. F or example, S may be measured by the probability of a storm impacting the indi-
vidual, and may have several values, say, 0.10, 0.20 and 0.30. R ecreational fishing service, F, may
be measured by average fish catch per day, say, 0, 3, 6 and 10. Water treatment services may be
simply measured by whether toxics are in the water, Yes or N o. Several prices may be used, say,
10, 50, and 100 per household per year. CJ then presents the respondent with combinations
of the four attributes, and asks the respondent to select the best, to rank them or to provide a rating
of them. In this example, there would be 3 × 4 × 2 × 3 = 72 possible combinations of attribute lev-
els. In order to simplify the choice, only a subset of these combinations would be used. Various
software programs e.g. SPSS Conjoint Ortho- plan facilitate the selection of a reasonable num-
ber of choice combinations. They typically select combinations that permit the estimation of only
main effects. This is termed orthogonal design, and would not allow determining the interaction
effects of, say, levels of W on P.
This paper reports on a study of watershed quality improvement for two streams in Western
Pennsylvania, both degraded from acid mine drainage. CJ allows joint valuation of these poten-
tially substitute goods. The study design includes distance from the two sites as a value-determining
variable and allows determination of the spatial extent of the market for users and non-users.
Several choice models were used to determine the sensitivity of valuation results to model specifica-
tion. Section 2 outlines the experimental design, including the CJ design as well as survey ques-
tions and procedures. Section 3 derives the R U M - based estimation models, and Section 4 derives
specific estimating equations. Section 5 presents the results of model estimation, including distinc-
tions between user and non-user valuations. Sec- tion 6 is the conclusion.
2. Experimental design
