VALUING NONMARKET ENVIRONMENTAL GOODS AND SERVICES

Transcription

1 VALUING NONMARKET ENVIRONMENTAL GOODS AND SERVICES Many if not most environmental goods have no market in the usual sense. For example, one does not buy a day s worth of enjoyment of the scenic beauty along the north shore of Lake Superior. One could buy a trip, a guide, access to a site, and gasoline or supplies along the way, but the aesthetic enjoyment itself is free. The same is true of a beach or fishing opportunities on Lake Michigan. Although there are consumers of these aspects of the Great Lakes environment, there is no supplier in the usual sense, and there is no price that can be observed in the usual way. Markets for resources such as clean air, clean water, or abundant wildlife are also difficult to imagine. The fact that many environmental goods and services are not traded in markets makes alternative approaches to measuring their value necessary. Some approaches, such as the travel-cost method and hedonic valuation, deduce nonmarket value indirectly from the value of associated market goods and services. Contingent valuation involves asking people directly how much a specific environmental good is worth to them. Responses to carefully crafted questions of this kind can be helpful in assessing benefits not easily associated with market goods and services. Existing estimates from similar interventions can also be transferred to new applications through benefits transfer and meta-analysis methods. All of these methods are described briefly below. Travel-Cost Method 7 Application The travel-cost method is generally used to estimate economic values associated with the use of recreation sites. This technique assumes that visitors to a particular site incur economic costs, in the form of outlays of time and travel expenses, to visit the site. In effect, these economic expenditures, or travel costs, reflect the price for the goods and services provided by the site. As noted in Chapter 5, price and what a consumer is willing to pay, or the value of the site to the consumer, are two different things. However, by observing the number of recreation trips individuals make at different levels of travel cost, economists are able to estimate the demand for recreational trips, and how environmental interventions may alter a consumer s willingness to pay for them, i.e., the value. The travel-cost method has a number of applications it can be used, for example, to measure the effects that changes in access costs to a recreational area, elimination of a 7 Frank Lupi, Assistant Professor, Department of Agricultural Economics and Department of Fisheries and Wildlife, Michigan State University 70

2 To use the site, or changes in environmental quality have on a consumer s willingness to pay. A policy intervention could result in any of these changes. To use the travel-cost method to value an intervention, recreation behavior must be linked to the effects the intervention has on recreation sites. For example, if the intervention changes environmental quality, then the relationship between the environmental quality at recreation sites and the number of trips to these sites must be established. Changes in environmental quality at a site can be valued only if they result in changes in trips to a site (i.e., the change in quality changes the demand for the site). The recreational use value of the change in environmental quality is the change in net benefits (i.e., consumer surplus) that accompanies the change in the trip demand. There are two main types of travel-cost models: single-site and multiple-site models. The two approaches differ in how explicitly they account for the ability of individuals to take trips to alternative recreation sites. These alternative recreation sites are often referred to as substitutes. travel-cost method to value an intervention, recreation behavior must be linked to the effects the intervention has on recreation sites. To see the importance of alternative recreation sites, suppose quality changes at site A. If similar recreation opportunities are widely available at alternative sites, then trips to site A will be more responsive to changes in the quality at site A than if site A was quite unique. The availability and comparability of substitutes determines the relative scarcity of any given recreation site. With many high-quality alternatives, decrements in quality at any one site will result in larger reductions in trips to that site, and improvements in quality will result in larger increases in trips. Consequently the availability of alternative recreation sites plays a dual role: mitigating some of the losses from decreases in site quality, and enhancing the gains from improvements in site quality. Thus, as with market goods, omitting the prices and qualities of relevant substitutes will bias the resource valuations. The single-site travel-cost model simply measures trips to a single site. Single-site travel-cost models underlie the bulk of the travel-cost methods in the literature until the early 1990s. More recent literature, however, relies almost exclusively on multiplesite models. Several variants of the multiple-site travel-cost model have appeared in the literature. The basic goal behind these variants is to estimate a system of trip demand equations for several sites rather than for a single site. The majority of multiple-site models use a 71

3 method referred to as the random utility model (RUM). The RUM is a theoretical and statistical model used widely by economists to model the choice of a single alternative from a larger set of alternatives. In travel-cost applications, the RUM is used to estimate the choice of which recreation site to visit. When coupled with a method for predicting quantity of trips, the RUM provides a tractable way to model the number of trips to each site when a large number of potentially relevant substitutes is available. Data Needs Typically data are collected through surveys of individual travelers. The survey data usually include the characteristics of individuals, the number and locations of their trips, and information for deriving travel costs. On-site surveys can provide heavy sampling of users, but these surveys oversample frequent users and need to be augmented with general population data to learn what proportion of the population uses the resource. Although they are often more costly than on-site surveys, general population surveys also provide data that help the economist estimate decisions about whether to visit the site. Finally, if the travel-cost method is to be used for valuing environmental quality, data are needed to establish the linkage between the behavior of visitors and the level of environmental quality. Single-site surveys require all the basic data needed to use the travel-cost method: the characteristics of individuals, the number of visits they made to the site, and information for deriving their travel costs. In most cases, some proxy variables for the prices and qualities of substitute sites are needed. If the method is to be used to value changes in environmental quality, then site-quality data are needed that vary over time or across individuals. Data needs are greatest in the multiple-site models. In addition to the characteristics of individuals, data are needed to delineate the set of sites that is to be included in the model. Behavioral data are needed for the total recreation trips for all sites that will be included in the model and for the specific locations for some of these trips. In addition, the travel costs and quality characteristics are needed for each of the substitute sites. Strengths of the Travel-Cost Method The travel-cost method is relatively uncontroversial because it mimics empirical techniques used elsewhere in economics. Some economists tend to prefer techniques of this sort because they are based on actual behavior rather than verbal responses to hypothetical scenarios. In the travel-cost method, individuals must spend money and time, and their economic values are deduced from their behavior. The resulting 72

4 demand concept is fairly intuitive: The travel-cost method explains how trips are related to personal characteristics, travel costs, and site-quality variables. In addition to valuation, the estimated demand model can be used to predict changes in behavior (i.e., trips) in response to changes in model variables that may be useful for other policy purposes. In some circumstances, a travel-cost model can be applied without enormous expense. Single-site models can often be easy to implement. They are most useful when potential policies will affect only a single site that has few substitutes. Data can be collected on-site and combined with other data sources to estimate the demand function and correct for the on-site sampling. General population surveys can be more targeted because behavioral data need to be collected for only one site. Multiple-site models deal explicitly with potentially important site substitution (i.e., switching from one site to another when site quality changes). These models can generally be used to value the addition of new sites as well as the elimination of some sites. Because these models are well suited to examining changes in the quality characteristics of the substitutes, they can be used for environmental valuation and for the valuation of policies that affect numerous sites. When only a small number of substitutes is available, some versions of the RUM are easy to estimate. Most economists consider multiple-site models to be the state-of-the-art. Limitations of the Travel-Cost Method The greatest disadvantage of the travel-cost method is that it cannot be employed unless some observable behavior can be used to reveal values. Thus the method is inappropriate for measuring nonuse values. In the case of nonuse values, there is no observable interaction between the individual and the resource in question. Again, if the travel-cost method is to be used to value changes in environmental quality, then travel to the site(s) in question must be linked to alternative levels of environmental quality. It is important to recognize that any relationship between the site characteristic and recreational use must be established statistically. As a result, a host of data issues are involved in identifying this linkage. Some of these data issues are listed below: The data must exist to describe (i.e., quantify) the aspect of environmental quality to be valued; The data must be available for all sites to be modeled; The data should exhibit sufficient variation across sites; 73

5 The data cannot be highly correlated with other variables that influence site choice; and The range of variation in the data should be sufficient to cover the range of policies to be examined. Most of these concerns apply to any statistical modeling effort. However, they are particularly important in the travel-cost method because the linkage between site-quality characteristics and recreation trips is used to infer the value of changes in environmental quality. Ultimately, any travel-cost method valuation of environmental quality is only as good as the statistical link between site-quality characteristics and the number of trips to the site. In contrast to most market goods, the market outlays and time costs that comprise travel costs vary across individuals and are not observed directly in a market transaction. Instead, these time and money costs are inferred by the economist. Therefore, the values derived from travel-cost models are sensitive to the specification of travel costs. In addition, the data about individuals and their trips that are needed to implement the travel-cost method must be gathered through surveys. Although collecting data through surveys is not a disadvantage per se, it is important to bear in mind that any survey data can suffer from poor design and implementation. The following issues must be considered when using travel-cost modeling: Accurate information on costs (both travel and time costs are not observed directly in a market transaction, and these costs are often critical in recreational consumption); Characterization of the quality dimensions of the site and statistical linkage of demand to site quality; Consideration of substitute sites and their characteristics; and Gathering of accurate and representative survey data on how much individuals use sites (i.e., which sites are used and how many visits are made). Several disadvantages have led to a decrease in the popularity of single-site travel-cost models. First, if numerous substitutes are available, then the prices and qualities of these sites should enter the demand function. Second, single-site models give little information regarding the value of additional sites. Third, single-site models cannot be used to evaluate policies that affect multiple recreation sites. Thus, if the scope of the intervention is larger than a single site, this method is not appropriate. Finally, and most important, single-site models are difficult to use for measuring the value of changes in environmental quality because such valuation requires knowledge 74

6 Although of how the recreation trips (i.e., demand) will change when quality changes. Gathering such knowledge usually requires variation in the measure of environmental quality to identify statistically how different levels of environmental quality affect trip demand. With a single site, most users will face the same level of environmental quality. Sometimes the requisite variation exists if the study extends over longer time periods during which quality is changing (e.g., trip behavior has been measured before and after the intervention). In other cases, the variation might be available if individuals have different perceptions of quality or different skill levels (e.g., fishing success). In some cases, hypothetical surveys can be developed to generate data on visitation levels under various environmental quality conditions. collecting data through surveys is not a disadvantage per se, it is important to bear in mind that any survey Multiple-site models are more demanding of data than are singlesite models. The researcher needs to identify the set of sites that data can suffer will enter the model, and this decision usually involves a fair from poor amount of the researcher s judgment. The models become increasingly difficult to estimate as the number of sites grows. The RUM design and by itself deals only with site choice; it does not address the quantity of trips to these sites. If trips are anticipated to change in implementation. response to policies, then a method of modeling the trip quantity dimension must be adopted. In addition, the typical RUMs assume choices are independent over time. Modeling interrelatedness among the choices made by each individual is challenging in the multiple-site models. Because environmental quality can vary across sites, multiple-site models provide a means of valuing changes in environmental quality. However, the valuation results cannot be divorced from the empirical adequacy of the site-quality data. As with any statistical analysis, the estimate of the effects of environmental quality may be affected by data difficulties. A key difficulty is a potential lack of variation in the quality variable across sites. Moreover, because recreation site choices are based on perceived quality, there is no guarantee that site choices are related to the scientific measures of site quality. Finally, as with any statistical analysis, the estimated results are most reliable when they are applied within the range of variation in the data used to estimate the model. 75