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Review. There are two primary components for assessing visual quality and environmental justice. The first comprises techniques for designing and communicating the visual effects, described above. The second component involves determining how different population groups may perceive the effects differently and how effects are distributed among population groups. That is the topic of the remaining sections in this chapter. SELECTING AN APPROPRIATE METHOD OF ANALYSIS Proper design and communication of visual effects is an important part of environmental justice assessment, and the methods described above can be used for that purpose. However, that alone is not enough. The overriding objective of an environmental justice analysis is to ensure that protected populations are not subjected to a disproportionate share of the negative impacts of a project--or that negative impacts are counterbalanced by equivalently disproportionate benefits. In the case of visual quality impacts, this analysis is problematic due to the fact that it is difficult to quantify negative impacts on a population. The problem is made even more difficult when you consider that different subpopulations (e.g., ethnic groups or age cohorts) may vary in how they value the numerous aspects of visual quality. One approach to this problem is to survey the affected populations to determine how attractive or aversive the visual quality impacts of the project are perceived to be. Nelessen (1994) describes a well-developed methodology for rating visual quality aspects of public projects. This method is variously known as Visual Preference SurveyTM (VPS), Image Preference Survey, and Community Preference Survey. In a VPS, respondents are asked to rate each of a set of photographs on a 21-point hedonic scale ranging from -10 (most aversive) to +10 (most appealing). The results can be used to estimate how a population values various aspects of visual quality or how effective particular mitigation measures would be. Another approach is to estimate the economic "value" of visual quality effects for each protected population impacted by the project and for the total affected population. In this context, the estimation of economic value is not meant to imply that monetary compensation might be made for negative visual quality impacts; the estimations are for comparative purposes only. For example, if it could be determined that individuals in the protected population place half again as much economic value on visual quality as the population as a whole (i.e., 150 percent), that estimate could be factored in to the analysis of distributive effects. The question of how to assign economic value to things such as visual quality has received considerable attention from economists. Visual quality is one example of what are called "nonmarket goods"--that is, goods (things of value) that are not traded in open market systems. Economists use two broad classes of methods to establish the value of nonmarket goods: revealed preference and stated preference methods. Revealed preference (RP) methods rely on the analysis of quantifiable behaviors that, while not involving direct monetary payment for goods, can be used to infer willingness to pay for the goods in question. The travel cost method uses the amount of time someone is willing to spend traveling to see a visually appealing feature as a measure of its value. Similarly, the amount of time a person is willing to spend traveling to avoid a visually unappealing feature is a measure of 263
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its aversiveness. The hedonic pricing method is based on analysis of the effect of a nonmarket good on the actual value of market goods. For example, if you compared the values of homes that were close to a visually aversive feature with those of similar homes that were not close to the feature, you could derive an estimate of how much the visual feature would reduce the market value of the particular home. Stated preference (SP) methods rely on surveys to estimate how much value individuals ascribe to a non-market good. Two variants of SP have been widely used contingent valuation and contingent choice. The contingent valuation (CV) method makes use of survey questions that directly address the respondent's willingness to pay for a non-market good--for example, "How much would you be willing to pay in extra taxes to beautify the roadway?" Alternative survey formats for CV are closed-ended questions (e.g., "Would you be willing to pay $50/year in extra taxes to beautify the roadway?") and multiple-choice questions (e.g., "I would be willing to pay $10 / $25 / $50 / $75 / $100 per year in extra taxes to beautify the roadway"). Contingent valuation is the most commonly used method for establishing a value for nonmarket goods. In recent years, however, CV has been criticized for several reasons, including the fact that it generally overestimates the true value of goods (Diamond and Hausman 1994; Hanemann 1994). The contingent choice (CC) method--also known as the "method of choice experiments"--is similar to CV in that it asks people to make choices based on a hypothetical scenario. It differs from CV in that it does not directly ask people to state values in dollars. Instead, values are inferred from the hypothetical choices or tradeoffs that people make. The CC method asks respondents to state preferences between a scenario with one group of attributes or characteristics and other scenarios with different sets of attributes. Usually, each item on the survey is binary; in other words, there is a discrete choice between two scenarios. If one of the attributes in each scenario is a dollar amount, CC can be used to estimate dollar values. However, the method may also be used to simply rank options, without focusing on dollar values. Because it focuses on tradeoffs among scenarios with different characteristics, CC is especially suited to situations where a proposed project might result in multiple types of impacts or a proposed policy may have tradeoffs that need to be evaluated. For example, a highway project might result in improved access to work places and shopping venues but at the same time reduce the visual quality of the corridor. Economists have used RP and SP methods extensively to estimate the dollar value of nonmarket goods such as visual quality. In the present context, however, the intent is to characterize the standards and values of impacted populations, not to estimate the dollar value ascribed to visual quality. A dollar value estimate is only of interest to the extent that it can reveal the underlying standards and values of a population. RP and SP methods can be used to analyze the standards and values of a population as long as the results are cast in relative terms. For example, if an analysis reveals that a given population 264