Economic valuation depends heavily on information that is fundamentally noneconomic. Evidence of WTP and WTA varies along two dimensions of quality: consistency with the conceptual framework of welfare-change measurement and reliability of the data themselves. For example, data generated by market transactions are convincing in at least one respect—paying money is the sincerest expression of WTP and accepting money and relinquishing an amenity constitute the sincerest expression of WTA. But the data might, for a variety of reasons, fail to measure the correct value concept.
Price typically indicates marginal value literally, the value of the next unit more or less than the status quo quantity—a small change ; but a proposal might involve nonmarginal big changes. In addition, market distortions of various kinds might distort prices, markets might be incomplete or otherwise imperfect, and the environmental service involved might be nonmarketed.
Data generated by contingent valuation or contingent policy referendums often can because a researcher controls the valuation context be addressed to the right value measure, but still this might raise doubts as to whether contingent payments and votes are reliable predictors of behavior. Valuation researchers are often faced with one or another form of this dilemma: "harder" data might depart from the ideal, and conceptually valid measures might be "softer". In some cases where hard data depart from the ideal value concepts, economists have developed ingenious methods of inferring the ideal values; however, there is always a risk that they will be forced to substitute assumptions for evidence and structure for information.
The resulting value estimates will be to some degree artifacts of the methods used and the research decisions made. It is hard to imagine a market for biodiversity as a whole, but its various components are routinely marketed. Consider a biodiverse forest. Timber, fuel wood, and some nonwood products can be produced and sold. The forest can provide catchment for water that is valued by downstream farmers and urban residents.
The forest ecosystem can harbor genetic resources with commercial potential, for example, rare species that might be of pharmacological interest or wild species that are precursors of modern, commercially important plant varieties. Recreationists and nature-lovers can devote resources money and time to visiting the forest. People can buy homes near the forest to have access to its amenities. The productivity and value of these various activities depend on how the forest is managed, so proposals that affect forest planning and management will generate costs and benefits that are reflected, to various degrees, directly or indirectly in markets.
The Pacific Northwest case study in this chapter provides a detailed example. For commodities that can be sold in quantities that are small relative to the total market, the economic value that can be assigned to a decision to sell or preserve is simply the product of the market price of the commodity and the quantity.
For example, if 20 acres of old-growth timber is reserved from the market to protect a pair of spotted owls, one estimate of the cost of this decision is the product of the volume of the timber and the market price per unit volume. That holds as long as the quantity is so small that its removal from the market does not affect the market price of timber generally. The quantity of timber removed from the market was clearly large enough to affect the market price for timber in much of the country. For such a decision, an estimate of the economic cost must consider not only the change in the quantity of timber marketed from that area, but also the change in the market price per unit volume of the remaining marketable timber from before the decision to after the decision.
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Such an estimate must also consider what economists refer to as "substitution effects". The changes in quantities and prices that result from a decision of this magnitude affect the market price of timber in other areas. Timber producers in forests other than those immediately affected by the decision for example, the southern United States respond to the change in timber price by changing the quantities of timber that they put on the market, thus causing further changes in the price of timber. Additional complications include the effects of the changes in timber price on the marketing of such substitute products as steel and plastics and the modifying effects of time as these various factors work through the marketplace.
In sum, calculating the effects of decisions that affect market prices is not easy, but it is conceptually feasible. The goal of valuation—measuring net present value—introduces two complications. First, "net value" requires that any costs associated with using the resources, such as, timber-harvesting costs, be subtracted from gross value.
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Second, "present value" requires prediction of future demands for environmental services. In the cases of timber, water supply, and genetic materials, the forest augments the supply of things that are valued as factors in production. So the demand for forest products is a derived demand, which complicates predictions of demand: the analyst needs to be concerned with demands for the final products houses, irrigated crops, and pharmaceutical products and with the supply of other things that might serve as substitute factors in their production.
The idea of substitutes suggests another approach to valuation: when it is hard to observe market demands for forest products directly, the analyst might look to market evidence concerning substitutes. For example, the avoidance cost method might value improved water quality by observing the household water-filtration costs avoided, and the replacement-cost method might value increased water catchment by calculating the cost of additional reservoir capacity that would serve the same purpose.
In both cases, the methods provide an upper-bound value for the particular services they address: the services cannot be valued at more than the cost of avoiding the need for replacing the service with a perfect substitute, but they could be valued at less than that, in the event that effective demand would not clear the market for these services at these prices.
The Quabbin Reservoir and Lake Washington case studies in chapter 6 illustrate this.
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Recreationists spending their money and time to visit the forest leave a trail of indirect evidence about their WTP for the services and amenities that it provides, and travel-cost methods attempt to tease out this WTP. The weak-complementarity assumption, of course, limits the travel-cost method to estimating the use values associated with site amenities. The simplest travel-cost models posit simply that the number of visits, at a given level of site quality, is a function of travel costs and socioeconomic variables, where travel cost is a proxy for the ''price'' of visits and includes costs of distance traveled and time spent in traveling.
Substitute sites and activities typically are included in arbitrary fashion or assumed to be of little import formally, this is accomplished via assumptions of separability in the utility function. A large literature attests to the difficulty that researchers have experienced in estimating the cost of travel time Bockstael , but this is symptomatic of a general difficulty: it is inherently difficult for researchers to observe the cost of a visit, that is, the value opportunities foregone to make the visit Randall If one assumes a relationship between the quality of on-site amenities and the costs of goods and services used in traveling to the site, the value of an increment or decrement in site quality is measured as the integral between demands for visits at the with-proposal and without-proposal levels of site quality.
The random-utility model RUM has become the travel-cost model of choice Bockstael because its systematic treatment of substitute sites allows it to characterize site quality more completely. RUM models are therefore more useful than basic travel-cost models for valuing changes in levels of environmental amenities. Their disadvantage arises from their substantial information needs, which in practice often lead to the use of very large data sets and simplifying analytical assumptions that impose rigidities; thus, estimates based on travel-cost models are to some degree influenced by researchers' analytical choices.
When travel-cost models are used to predict number of visits, validation is relatively simple, and several well-known models have performed well for example, Bockstael and others However, direct validation of the value estimates obtained with travel-cost models is impossible; the best one can do is test for convergence of the results of travel-cost methods and the results of alternative approaches, such as contingent valuation, and such tests have provided some empirical evidence of convergent validity. Hedonic price analysis separates the factors that contribute to prices to identify the contribution of those based on environmental amenities.
Imagine a good with several important or desirable features, such as a house or automobile. It is a reasonable hypothesis that the price of a particular house or car reflects its particular characteristics. If a statistical analysis succeeds in explaining the price of a house as a function of its characteristics and one of those characteristics is the level of environmental amenities, then the marginal small impact of a change in an amenity level a trait that makes it attractive on the house price should provide evidence of this amenity value. This is the intuition behind hedonic price analysis.
Perspectives on Biodiversity: Valuing Its Role in an Everchanging World.
A hedonic price function, relating house prices to characteristics, is estimated. Typically, three kinds of characteristics are used: on-site characteristics, such as the number of bedrooms; neighborhood characteristics, such as school quality; and environmental amenities, such as access to a biodiverse forest.
The first derivative of the hedonic price function with respect to the environmental characteristic of interest is its hedonic price or marginal implicit price , a measure of the marginal value of the amenity. The literature suggests that hedonic price analysis has succeeded, in a fairly wide range of circumstances, in generating plausible estimates of marginal hedonic prices for various housing characteristics, including environmental amenities.
To value nonmarginal changes in amenity levels, however, it is necessary to estimate hedonic demands, that is, demands for amenities. The literature reports many attempts to find conceptually valid methods of identifying hedonic demands, but no method has proved generally acceptable.
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Hedonic price analysis is often effective for valuing marginal changes in the levels of environmental amenities that can be accessed via, say, choice of home site but cannot generally be used for valuing nonmarginal environmental changes. The assumptions underlying the method limit its application to a subset of use values; for example, a housing-price hedonic analysis will measure use values associated with home site amenities, but not values that can be accessed regardless of exactly where one lives.
If we design and ask the questions with enough care, perhaps people can provide reliable evidence of amenity values by telling us their WTP or WTA directly or by telling us what they would do for example, buy or not buy or vote yes or no if given well-specified choice situations that we construct to generate data that we can analyze to infer their WTP or WTA. That is the intuition behind contingent valuation and contingent-choice experiments.
The great advantage is that the researcher controls the context of choice, which makes it possible to estimate total economic value, passive-use value, and various use values that can elude the methods that use market-generated evidence, directly or indirectly. A further advantage is that information can be obtained to value amenity levels beyond the existing range; if it can be described by the researcher and comprehended by the respondent, it can be valued. The potential disadvantages lie in the self-reported nature of the data: some people might seek to answer strategically, some might answer carelessly, and some might struggle mightily but hopelessly in the end to provide valid responses to questions that cannot be answered meaningfully.
Economists, who are weaned on the admonition to "watch what people do, not what they say", approach these methods with a well-developed skepticism; yet the results, although mixed, have been encouraging enough to stimulate a proliferation of applications. The techniques require primary data collection in a survey or experimental context.
With rapid advances in information and communication technologies and increasing synergism among research programs in, for example, economics, social psychology, and marketing, it is reasonable to expect vigorous innovation in research design and data collection methods. In this report, we use the standard categories of contingent valuation in which responses to one or a few choice questions provide the basic data for valuation and contingent-choice experiments in which value is inferred from responses to a sometimes long sequence of pairwise choices.
The basic project underlying the methods is to learn about value from people's self-reports; and as development and testing of these methods proceed, we can expect new approaches to emerge and existing categorizations to become obsolete. The essential elements of a contingent-valuation CV exercise are a description of the default and alternative situations respectively, what you get if the proposal fails and if it passes , the institutional environment, the valuation question, and the policy-decision rule: How does the answer to the valuation question affect whether the proposal passes or fails?
See the Grand Canyon flush case study below. The valuation question can be continuous or open-ended ; for example, What would you be willing to pay? Or it can be in the form of a dichotomous choice; for example, Given the stated cost to you and the policy-decision rule, would you vote yes or no?
Alternatives in common use are, Would you buy it or not? The different forms of the valuation question require different analyses to estimate WTP or WTA; for example, the results of the dichotomous form are usually analyzed with some kind of RUM Hanemann With different policy-decision rules, they imply different kinds of incentives for truthful responses Hoehn and Randall There is already an extensive literature of CV applications, and attempts to validate CV include tests for internal consistency and tests of convergence with value estimates obtained with different methods.enter
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Encouraging results have been obtained for example, Carson and others ; Smith and Osborne , but critics have raised enough doubts for example, Hausman for CV to remain controversial. A report by a prestigious panel Arrow and others failed to settle the issues when it endorsed CV in principle, even for measuring passive-use values in environmental-damage litigation, but announced a long and demanding list of standards that a valid CV should satisfy.
CV that would meet the panel's standards would be prohibitively expensive in most applications, and, as methodological innovation and the accumulation of evidence proceed, the process of rethinking the panel's recommendations is beginning. One of the panel's recommendations deserves highlighting here.