Naz, Antonia Corinthia C and Mario Tuscan N. Naz. 2006. Modeling ...

ECOSWAM board in August 2004 and created the ECOSWAM Technical Working
Group with technical assistance from this EEPSEA project. The municipal council also
adopted Resolution 282, series 2003 adopting an LGU-wide ECOSWAM program. A
local resident donated one hectare of land for Tuba’s waste disposal site. The Tuba
municipal government plans to purchase from the said donor, an adjoining one hectare
of land as an additional disposal area.
3.2 Stated Preference Approach or Choice Modeling
The researchers used the stated preference (SP) approach. The SP analysis has its
roots in conjoint analysis where individual judgments of multi-attribute stimuli are
represented (Adamowicz, et. al.,1999, Batsell and Louviere, 1991). The particular type
of conjoint analysis used here is the experimental analysis of choice. This particular
approach parallels the Random Utility Model (RUM) structure (see McFadden, 1974;
Ben-Akiva and Lerman, 1985) that is common in referendum contingent valuation (CV)
models (Mitchell and Carson, 1989) and in discrete-choice travel-cost models
(Bockstael et al., 1991).
Each alternative (i) in the choice set has an associated utility level represented
by (Adamowicz, et. al., 1999:465)
Ui = Vi+ εi (1)
This utility is composed of an objective component (Vi) and an error component
(εi ). The study assumes that the utility for an option (i) depends on a vector of its
observable attributes, (Z) and a vector of the socio-economic characteristics and
environmental knowledge, attitudes, practices and perceptions of the respondents, (S).
Ui = Vi (Zi, Si) + εi (Zi, Si) (2)
This function is also known as a conditional indirect utility function since it is
conditional on the choice of the option (i). Selection of one option (package of
attributes) over another implies that the utility (Ui) of that option is greater than the
utility of another option say j (Uj). Since overall utility is random, one can only analyze
the probability of choice of one option over another, or
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Pr {i chosen} = Pr { Vi+ εi > Vj + ε j ∀j ∈ C} (3)
Where C is the choice set
Specific choices of error distributions lead to methods for the estimation of the
parameters of this utility function and to quantitative representations of trade-offs
between attributes. An assumption of Type I extreme value distributed errors produces
the conditional logit specification of the probability choice, or the probability of an
individual choosing an alternative i can be written as the following closed-form
multinomial logit model (MNL):
Pr {i} = e Vi
∑ e Vj
j∈C
(4)