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Permanent link (DOI): https://doi.org/10.7939/R33B5WF8K
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Stated Preference Methods for Environmental Valuation Open Access
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Boxall, Peter C.
Louviere, Jordan J.
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Contingent valuation (CV) has been employed by economists for approximately 30 years to value changes in natural resources and environments. Estimating the value of resource improvements or damages is analogous to the problem in marketing research of estimating the demand for new products or services. There are two basic approaches to this problem which have evolved during the past two decades, although there are minor variations within each (See, e.g. Urban and Hauser 1993). The first approach involves the development of a detailed concept description of the product for which the demand forecast is to be made. This description need not be limited to verbiage, but may require the development of renderings, models, mockups, prototypes, multimedia, etc. In any case, the essential elements are that the most accurate description possible of one (or at most a very few) potential products are used as the basis for determining the potential demand or share. In the second approach, the product of interest is viewed as one of many possible products which differ in the values or positions they occupy on key product characteristics or features. In this approach, carefully designed arrays of product characteristics are used to develop a number of product concept descriptions to which consumers react. This approach differs in terms of whether the product descriptions are shown \"one-at-a-time,\" which represents some variant of traditional conjoint analysis (Green, et al. 1971; Green and Srinavasan 1978, 1990; Louviere 1988, 1994); or presented as sets of competing options, which represents some variant of experimental choice analysis (Louviere and Woodworth 1983; Louviere, 1988a,b, 1994; Batsell and Louviere 1991; Carson, et al. 1994). The first approach shares many similarities with traditional applications of CV, in which as accurate as possible a description of a resource improvement or damage is created, and samples of individuals are asked to respond to that improvement using open- or closed-ended valuation questions. The problem with this approach is that it relies very heavily on the accuracy of a particular description, and any errors in the description discovered after the fact cannot be changed. Thus, in the case of product concepts, if consumers are told the selling price is $5.48, but the actual selling price upon and after introduction is $7.24, there is no way to \"adjust\" the forecast to take this into account. Similarly, in the case of a resource damage scenario, if later research indicates that instead of 250 dead ducks, the number was closer to 375, there is no way to take this into account. Similarly, this approach cannot actually value the various and separate components of the description; hence, the value of each duck cannot be determined. Likewise, in marketing research applications, the values of individual product features that comprise the product bundle cannot be ascertained. In contrast, the second approach relies less on the accuracy and completeness of any particular product bundle description, but rather more on the accuracy and completeness of the product characteristics and features used to describe all the bundles. In this approach, a stream pollution \"event\" is viewed as one of many possible such events, and the onus is on the researcher to determine as exhaustive a set of variables as possible to describe either stream pollution events in general, or events that fall within a particular mutually exclusive category that includes the event in question. Statistical design techniques are used to sample from the universe of all possible \"events\" that are spanned by the variables and the values that the variables can take on in the type(s) of problem of interest. Rather than being questioned about a single event in detail, therefore, consumers are questioned about a sample of events drawn from the universe of possible events of that type. We refer to this latter method as the stated preference (SP) approach. While CV methods have attracted environmental and natural resource economists' attention for nearly three decades, SP approaches to eliciting consumer preferences have not. SP methods have remained in the domain of human decision research, marketing and transportation research, even though support for their use in economic analysis was formalized some time ago (McFadden, 1986). In this paper, we outline the stated preference approach and describe how it can be used to value environmental amenities. We also discuss the advantages of SP techniques both in relation to CV methods and revealed preference (RP) techniques.
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