A Primer on Nonmarket Valuation

Nonmarket valuation, i.e., valuing environmental goods and services that are not traded in a market, has been increasingly used in a variety of policy and decision-making contexts. This is one (but not the only) way that researchers and practitioners have sought to define and measure the values that individuals assign to environmental goods and services. The idea of putting a dollar value on protecting the environment has been controversial, but often because the economic approach to valuation has not been well-understood. This chapter provides a nontechnical overview of and rationale for the economic approach to valuation, starting from a broad conceptualization of values versus valuation. It summarizes the economic concept of value and its key features. It then discusses the use of economic valuation in decision making, followed by an overview of the steps involved in the valuation process and important issues that arise in implementing that process. Finally, it identifies and briefly summarizes the principal non-market valuation methods used by economists. In doing so, it sets the stage for the more detailed chapters on theory and methods that follow.

This chapter provides an overview of the theoretical foundations of nonmarket valuation. The chapter first develops a model of individual choice where private goods are freely chosen but environmental goods are rationed from the individual’s perspective. The model is used to define compensating and equivalent welfare measures for changes in prices and environmental goods. These welfare measures form the basis of the environmental values researchers seek to measure through nonmarket valuation. The chapter discusses the travel cost model with and without weak complementarity, the household production model, the hedonic model, and the general concept of passive-use value. The individual choice model is extended to a dynamic framework and separately to choice under uncertainty. Finally the chapter develops welfare measures associated with averting expenditures and random utility models.

This chapter describes how to collect primary and secondary data for nonmarket valuation studies. The bulk of this chapter offers guidance on how to design and implement a high-quality nonmarket valuation survey. Understanding the full data collection process will also help in evaluating the quality of data that someone else collected (i.e., secondary data). As there are not standard operating procedures for collecting nonmarket valuation, this chapter highlights the issues that should be considered in each step of the data collection process from sampling to questionnaire design to administering the questionnaire. While high-quality data that reflect individual preferences will not ensure the reliability or validity of estimated nonmarket values, quality data are a prerequisite for reliable and valid nonmarket measures.

Contingent Valuation in Practice takes the reader through each of the basic steps in the design and administration of a contingent-valuation study. The text is written for the novice conducting their first study, decision makers who might want to better understand the method, and experienced researchers. Rich citations to the literature are provided to help a novice reader gain a deeper understanding of the supporting literature and to assist experienced researchers in developing the context for research to enhance contingent valuation in practice. The novice and users of value estimates can rely on the content of this chapter to understand best current practices and researchers can use the content to identify research that addresses uncertainties in the design and conduct of contingent valuation studies. Following the steps outlined in the chapter provides a basis to establish that an empirical study satisfies conditions of content validity.

There has been an explosion of interest during the past two decades in a class of nonmarket stated-preference valuation methods known as choice experiments. The overall objective of a choice experiment is to estimate economic values for characteristics (or attributes) of an environmental good that is the subject of policy analysis, where the environmental good or service comprises several characteristics. Including price as a characteristic permits a multidimensional, preference-based valuation surface to be estimated for use in benefit-cost analysis or any other application of nonmarket valuation. The chapter begins with an overview of the historical antecedents contributing to the development of contemporary choice experiments, and then each of the steps required for conducting a choice experiment are described. This is followed by detailed information covering essential topics such as choosing and implementing experimental designs, interpreting standard and more advanced random utility models, and estimating measures of willingness-to-pay. Issues in implementing and interpreting random utility models are illustrated using a choice experiment application to a contemporary environmental problem. Overall, this chapter provides readers with practical guidance on how to design and analyze a choice experiment that provides credible value estimates to support decision-making.

This chapter provides an introduction to Travel Cost Models used to estimate recreation demand and value recreational uses of the environment such as fishing, rock climbing, hunting, boating, etc. It includes a brief history, covers single-site and random-utility-based models, and discusses current issues and topics. The chapter is laid out in a step-by-step primer fashion. It is suitable for first-timers learning about travel cost modeling as well as seasoned analysts looking for a refresher on current approaches. The chapter includes an application of the random-utility-based model to beach use on the east coast of the USA along with measures of welfare loss for beach closures and changes in beach width.

This chapter covers the current theory and empirical methods in hedonic valuation of environmental and natural resources.  A framework is first presented that links hedonic price functions to theoretically correct welfare measures for changes in environmental amenities. The major empirical methods for estimating a hedonic price function are discussed beginning with data construction and basic estimation approaches, and progressing through to techniques for addressing endogenous regressors including spatial econometrics and quasi-experimental methods.  The use of the hedonic price function for obtaining measures of welfare change for changes in environmental amenities are also presented.  Sorting models and second-stage demand analysis in both a single-market and multiple-market context are described.  Applications and examples from housing and labor markets are used throughout to illustrate concepts covered.

Averting behavior refers to actions taken to defend against environmental or other hazards, whether by reducing exposure to hazards or by mitigating adverse effects of exposure. This chapter examines how information on averting behavior can be used to improve nonmarket valuation. The chapter describes the history, theoretical foundation, and empirical application of averting behavior methods. These methods support estimation of economic benefits of public policies, especially those that reduce morbidity or mortality, in a way that is consistent with utility maximization and is based on observable behavior. The chapter: (1) shows how ignoring averting behavior may cause an invalid measurement of physical and economic damages of pollution or other hazards, and how controlling for averting behavior may improve welfare measurement; (2) explains several ways of using information on averting behavior to estimate the benefits of environmental improvement; (3) provides a simple empirical illustration; and (4) argues that the validity of welfare measurement using averting behavior methods depends on how the challenges of joint production, unknown prices of averting actions, and identification of the effects of pollution and averting behavior are met.

This chapter covers two nonmarket valuation methods founded on the concept of substitution—the replacement cost method and equivalency analysis. Both methods are widely applied but frequently misunderstood. The replacement cost method is commonly used to value ecosystem services, and equivalency analysis is typically employed to determine required compensation for natural resource losses. The chapter describes and contrasts the methods, clarifies when (and when not) to apply them, illustrates the steps of a successful application, and provides examples of past applications. The reader will gain an appreciation of when the methods can provide a valid measure of economic value, and alternatively when the methods more usefully provide only a measure of cost. Following the guidance provided here can enhance the credibility of empirical applications of substitution methods.

This chapter discusses the role of behavioral experiments in evaluation of individual economic values. Principles of experimental design play a role in application and assessment of non-market valuation methods. Experiments can be employed to assess the formation of preferences and the role of personal characteristics, social factors, and economic constraints on economic values. Experiments can be used to test the efficacy of nonmarket valuation methods and to study the effect of the valuation task, information, and context on valuation responses. We discuss these issues in turn, incorporating pertinent literature, to provide a review and synthesis of experimental methods in valuation.

Benefit transfer is a nonmarket valuation tool that is widely-used in a variety of decision contexts. Its primary role is deriving reliable estimates of value from prior research when new, original research is not feasible given time and resource constraints. This chapter begins by setting the development of benefit transfer in its historical context, which formally began in earnest in the early 1990’s in response to an increased need for value measures in environmental and natural resource management and policy decisions. The two primary types of benefit transfer—value transfer and function transfer—are conceptually defined, including key steps when conducting them and examples of their empirical application. Sub-types of value transfers discussed include point estimate and measures of central tendency, and administratively-approved value transfers. Sub-types of function transfers discussed include benefit or demand function, and meta-regression analysis transfers. Reliability of benefit transfer is shown to be 45% transfer error for value transfers and 36% transfer error for function transfers. Criteria for minimizing transfer error rates in benefit transfers are provided to help guide practitioner decisions when using this tool.

A central goal of nonmarket valuation studies is to provide accurate value estimates.   We suggest a systematic, comprehensive approach to accuracy assessment using the twin concepts of reliability and validity.  Reliability has to do with variance; validity has to do with bias. If procedures applied in a valuation study are produce erratic results, accuracy suffers even if those procedures are unbiased.  And, even if the procedures in question are reliable, they will be less useful if the procedures applied produce large biases in the estimates.  We adapt the general concepts of reliability and validity to apply to nonmarket valuation studies.  As in many other disciplines, the concept to be measured, the “true values,” is unobservable.  Hence, criteria must be developed to serve as indicators of accuracy. Reliability is typically observed using the estimated standard error of the mean from repeated estimates of value.  Validity is assessed using the concepts of content validity, construct validity, and criterion validity; what we refer to as the “three Cs” of validity.  After fleshing out these concept, we illustrate how they can be applied using two case studies. Contingent valuation serves as an example of stated preference methods. The travel cost method provides a case study of revealed preference methods.