A Primer on Nonmarket Valuation

Consider the choices faced by those responsible for managing releases of water at the Glen Canyon Dam on the Colorado River. The size and timing of the releases determine the value of the hydroelectric power generated. But the pattern of the releases influences the nature and value of the recreational activities on Lake Powell above the dam and on the rivers in Glen Canyon and Grand Canyon below the dam. The release patterns also affect, in complex ways, the availability of suitable habitat for and the probabilities of the survival of several endangered species. Thus, managers face choices that involve tradeoffs.¹ More hydroelectric power means reduced quality and quantity of recreation opportunities and, perhaps, reductions in the survival of some endangered species. It is necessary to reconcile the sometimes conflicting desires and interests of those affected by management decisions and to make wise choices concerning these trade-offs. To do so, resource managers require information on the value of hydroelectric power and the values that people place on various attributes and types of recreation on and along the Colorado River and on changes in the survival probabilities for endangered species.²

Serious practice of nonmarket valuation requires a working knowledge of the economic theory because it forms the basis for the explicit goals in any nonmarket valuation exercise. This chapter provides readers with the requisite theory to meaningfully apply the nonmarket valuation techniques.

The unique nature of environmental and natural resource amenities makes valuation a challenge in many respects. Prices reflect aggregate societal values for market goods but nonmarket goods lack an analogous indicator of value. Estimation of nonmarket values requires that the researcher either ask the public about their values for the good of interest or use existing data to infer the values. Either approach is sensitive to the quality of the data used for the estimation, which is why this chapter focuses on how to collect data for estimating nonmarket values. Understanding where such data come from and the procedures used to collect the data will make the descriptions of the nonmarket valuation techniques in Chapters 4–11 more meaningful.

Stated preference approaches to nonmarket valuation rely on answers to carefully worded survey questions. Those answers—in the form of monetary amounts, choices, ratings, or other indications of preference—are scaled following an appropriate model of preference to yield a measure of value. Two common, and one not so common, stated preference methods are discussed in the next three chapters.

Contingent valuation is a survey-based methodology for eliciting values people place on goods, services, and amenities. The first contingent valuation study was conducted by Davis (1963) to estimate the value of big game hunting in Maine. A decade later, Hammack and Brown (1974) applied contingent valuation to valuing waterfowl hunting. Simultaneously, an application to valuing visibility in the Four Corners region of the Southwest represented a turning point after which contingent valuation gained recognition as a methodology for estimating Hicksian surplus for public goods (Randall, Ives, and Eastman 1974). Contingent valuation filled a substantial void by providing a way to estimate values when markets do not exist and revealed preference methods are not applicable.

Stated preference methods of environmental valuation have been used by economists for decades where behavioral data have limitations. The contingent valuation method (Chapter 5) is the oldest stated preference approach, and hundreds of contingent valuation studies have been conducted. More recently, and especially over the last decade, a new class of stated preference methods has been developed, which we generically refer to as attribute-based methods (ABMs). As with contingent valuation, numerous ABM variants exist, employing, for example, different constructs for eliciting preferences. In this chapter, we describe the various ABMs currently used, explain how to construct an attribute-based experiment, and recommend methods for environmental valuation.

Assume for the moment that you are the supervisor of the Roosevelt National Forest (it’s located near our town of Fort Collins, Colorado). You have been asked by the Chief of the Forest Service how you would spend a specified increase in your budget. You could spend the increase on such projects as improved campgrounds, better roads for reaching the backcountry, reduction in forest fuels to lower the risk of wildfire, and watershed management to lower erosion and thereby improve fish habitat. You know your chances of getting an increase depend on how well you support your proposal. You can design options that use up the budget increase, but you don’t have good information about the benefits of, or even the public preferences for, the options. You know what the vocal interest groups want, but you would like your proposal to have some quantitative justification that reflects the values of the wider citizenry who care about the National Forest. You examined the economic analyses that had been done about forest resources in the area and found no studies for most of the major resources you manage. You don’t have time for separate valuation studies of each of the options. However, you could commission a single study directly comparing the values people place on the options-a multiple good valuation study. Furthermore, because the options cost the same amount, a preference ordering of the options is all you need to choose the best one. That option might then become the focus of an economic valuation study, which would allow a benefit-cost comparison.¹

Revealed preference methods draw statistical inferences on values from actual choices people make within markets. Estimation of the values people place on environmental amenities and disamenities proceeds by specifying a theoretical framework and conducting data analyses from purchase decisions (prices paid and quantities purchased) according to this conceptual framework. Four commonly used revealed preference methods are discussed in the next three chapters (Chapter 9, travel cost; Chapter 10, hedonics; Chapter 11, defensive behavior and damage costs).

The travel cost model is used to value recreational uses of the environment. For example, it may be used to value the recreation loss associated with a beach closure due to an oil spill or to value the recreation gain associated with improved water quality on a river. The model is commonly applied in benefit-cost analyses and in natural resource damage assessments where recreation values play a role. Since the model is based on observed behavior, it is used to estimate use values only.

Heterogeneous or differentiated goods are products whose characteristics vary in such a way that there are distinct product varieties even though the commodity is sold in one market (e.g., cars, computers, houses). The variation in product variety gives rise to variations in product prices within each market. The hedonic method for non-market valuation relies on market transactions for these differentiated goods to determine the value of key underlying characteristics. For instance, by observing the price differential between two product varieties that vary only by one characteristic (e.g., two identical cars, but with one having more horsepower than the other), we indirectly observe the monetary trade-offs individuals are willing to make with respect to the changes in this characteristic. As such, the hedonic method is an “indirect” valuation method in which we do not observe the value consumers have for the characteristic directly, but infer it from observable market transactions.

If a tree falls in the forest and no one is around to hear it, does it make a sound? Likewise, if a nonmarket valuation study is done and it is not used to affect or inform policy or management, does it serve a purpose? Previous chapters in this book have gone into detail about how to implement specific nonmarket valuation techniques. After reading all those chapters, one might reasonably ask: Who cares? Do these methods make a difference in the real world of policy and management decisions related to resource allocation? answer is ... well, sometimes.

While our editors were too polite to call it that, I was assigned to write the Old Professor’s chapter. It’s up to me to wrap up this volume by taking stock and looking into the future. Actually, being 30 years past the Ph.D., I rather like this role. Taking the long view suits me fine.