V. Kerry Smith

Is There a Role for Benefit-Cost Analysis in Environmental, Health, and Safety Regulation?

Benefit-cost analysis can play an important role in legislative and regulatory policy debates on protecting and improving health, safety, and the natural environment. Although formal benefit-cost analysis should not be viewed as either necessary or sufficient for designing sensible public policy, it can provide an exceptionally useful framework for consistently organizing disparate information, and in this way, it can greatly improve the process and, hence, the outcome of policy analysis. If properly done, benefit-cost analysis can be of great help to agencies participating in the development of environmental, health, and safety regulations, and it can likewise be useful in evaluating agency decision-making and in shaping statutes.

Measuring water quality benefits

1 Measuring Water Quality Benefits: An Introduction.- 1.1 Background.- 1.2 Regulation: An Overview.- 1.3 Objectives.- 1.4 Preview.- 1.5 References.- 2 The Conceptual Basis of Benefits Estimation.- 2.1 Introduction.- 2.2 A Brief Review of the Conventional Theory of Benefits Measurement.- 2.3 The Treatment of Nonuse Values and Uncertainty in Benefit Analysis.- 2.4 Measuring the Benefits Associated with Changes in Environmental Amenities: An Overview.- 2.5 Benefit Measurement Approaches Considered in This Study.- 2.5.1 The Travel Cost Approach.- 2.5.2 The Contingent Valuation Approach.- 2.5.3 The Contingent Ranking Approach.- 2.6 Summary.- 2.7 References.- Appendix: Analytical Background for Valuation Under Uncertainty.- 3 Survey Design.- 3.1 Introduction.- 3.2 The Monongahela River Basin.- 3.2.1 Geography.- 3.2.2 Uses.- 3.2.3 Recreation.- 3.2.4 Basin Socioeconomic Profile.- 3.3 Sampling Plan.- 3.3.1 Target Population.- 3.3.2 Sample Selection and Survey Design.- 3.4 Survey Plan.- 3.4.1 Questionnaire Design and Limited Local Pretest.- 3.4.2 Retaining Field Supervisors and Hiring Interviewers.- 3.4.3 Counting and Listing of Sample Segments.- 3.4.4 Developing Field Manuals and Conducting Interviewer Training.- 3.4.5 Conducting Household Interviews.- 3.4.6 Initial Contacts and Obtaining Cooperation.- 3.4.7 Household Enumeration.- 3.4.8 Interviewing Procedures.- 3.4.9 Implications.- 3.5 References.- Appendix: Interviewer Debriefing.- 4 Contingent Valuation Design and Results: Option Price and Use Values.- 4.1 Introduction.- 4.2 Design Issues and Contingent Valuation.- 4.2.1 Eliminating Information and Hypothetical Biases.- 4.2.2 Considering the Role of Framing Biases.- 4.2.3 Addressing Procedural Issues.- 4.3 Questionnaire Design.- 4.3.1 Part A-Background.- 4.3.2 Part B-Benefits Measures.- 4.4 Profiles of Survey Respondents.- 4.5 Protest and Outlying Bids.- 4.5.1 Protest Bids.- 4.5.2 Identifying Outliers.- 4.6 Distribution of Option Price Responses.- 4.7 Mean Option Price Responses.- 4.8 Test Findings: Starting Point and Interviewer Biases.- 4.9 Use Value Results.- 4.10 Implications.- 4.11 References.- Appendix: Additional Empirical Results.- 5 Measuring Option Value.- 5.1 Introduction.- 5.2 Recent Estimates of Option Values.- 5.3 Measuring Option Value: Survey Design.- 5.4 Survey Results-Option Value.- 5.4.1 Option Value-Demand Uncertainty.- 5.4.2 Option Value-Supply Uncertainty.- 5.5 Summary.- 5.6 References.- 6 The Contingent Ranking Method and Benefit Estimation.- 6.1 Introduction.- 6.2 The Random Utility Model of Consumer Behavior with Discrete Choices.- 6.3 Estimation of Random Utility Models with Ordered Alternatives.- 6.4 Contingent Ranking and Valuing Public Goods.- 6.5 Applications of Contingent Ranking Method.- 6.6 Monongahela Contingent Ranking Experiment: Design and Estimates.- 6.7 Benefit Estimates with Contingent Ranking Models.- 6.8 Implications and Further Research.- 6.9 References.- 7 The Travel Cost Approach to Recreation Demand Modeling: An Introduction.- 7.1 Introduction.- 7.2 The Household Production Framework and Recreation Demand Models.- 7.3 The Opportunity Costs of Time.- 7.4 Measuring Site Usage.- 7.5 Heterogeneous Recreation Sites and Site Characteristics.- 7.6 Summary.- 7.7 References.- 8 Travel Cost Model: Data Sources and Variable Measures.- 8.1 Introduction.- 8.2 Sources of Data.- 8.2.1 The 1977 Federal Estate Survey.- 8.2.2 Recreation Resources Management System.- 8.2.3 National Water Data Exchange.- 8.2.4 Personal Correspondence.- 8.3 Survey Issues.- 8.3.1 Onsite Survey.- 8.3.2 Multiple Visits.- 8.4 Data Character.- 8.4.1 The Quantity Measure: Visits.- 8.4.2 Distance Cost Component of Travel Costs.- 8.4.3 Time Cost Component of Travel Costs.- 8.5 Site Profile.- 8.6 Congestion at U.S. Army Corps of Engineers Sites.- 8.7 Water Quality.- 8.8 Users.- 8.9 Profile of Activities at the Corps Sites.- 8.10 Summary.- 8.11 References.- 9 Generalized Travel Cost Model.- 9.1 Introduction.- 9.2 Implementing the Generalized Travel Cost Model.- 9.2.1 The Conceptual Links Between Visits and Characteristics.- 9.2.2 The Two-Step Estimation Procedure.- 9.2.3 Additional Econometric Considerations.- 9.3 Estimating the Generalized Travel Cost Model.- 9.4 Valuing Water Quality Changes.- 9.5 Summary.- 9.6 References.- 10 Comparing Direct and Indirect Benefit Estimation Approaches.- 10.1 Introduction.- 10.2 Past Comparisons of Benefit Estimation Approaches: A Review.- 10.3 A Comparison of the Generalized Travel Cost Model and Contingent Valuation.- 10.4 A Comparison of a Simple Travel Cost Model and Contingent Valuation.- 10.5 Comparisons of Benefit Estimation Approaches: Some Interpretations.- 10.6 References.- 11 Research Issues in Benefit Estimation.- 11.1 Introduction.- 11.2 Our Findings: A Perspective.- 11.3 Measuring Nonuse Values.- 11.4 Site Attributes and Recreation Demand.- 11.5 Contingent Valuation Versus Indirect Methods for Benefit Estimation.- 11.6 Benefits Transfer.- 11.7 Prognosis.- 11.8 References.- Appendix A: Survey Questionnaire as Administered During the Monongahela River Basin Survey.

Arbitrary values, good causes, and premature verdicts

Abstract This paper offers an alternative interpretation of the conclusions Kahneman and Knetsch propose based on two contingent valuation (CVM) surveys. The evaluation argues that while framing is important to CVM estimates, the design, implementation, and empirical findings reported from these surveys do not support their judgments. Moreover, with the exception of temporal embedding, conventional economic descriptions of individual behavior can explain the response patterns that they suggest are at variance with standard value theory.

Recreation Demand Models

Travel cost recreation demand models stem from a simple, but penetrating, insight. Consumption of an outdoor recreation sites services requires the user to incur the costs of a trip to that site. Travel costs serve as implicit prices. These costs reflect both peoples distances from recreation sites visited and their specific opportunity costs of time. Today, economic analyses of recreation choices are among the most advanced examples of microeconometric modeling of consumer behavior in economics.The primary focus of this chapter is on the methods used to describe individuals recreation choices. We are interested in the economic assumptions made in descriptions of behavior and measures of the economic value of amenities. Before developing this summary, in Section 2 we discuss how outdoor recreation fits within consumers overall expenditures. Section 3 describes how we might ideally like to estimate consumers preferences for recreation resources and the compromises implied by the models currently being used. Econometric details are deferred until Section 5, after a discussion of the features of recreation data in Section 4. In Section 6 we turn to conceptual issues in welfare measurement. We close in Section 7 with a discussion of a few research opportunities that seem especially important for the future.

Using Random Utility Models to Estimate the Recreational Value of Estuarine Resources

In this paper we describe a model using a household production framework to link measures of nonpoint source pollution to fishing quality and a random utility model to describe how that quality influences sport fishing parties decisions in North Carolina. The results provide clear support for using a model that evaluates the effects of pollution on the activities and decisions associated with the fishing activity once a trip is taken. Site selection decisions are then conditioned on the anticipated quality of fishing sites. The framework also has the advantage of linking the spatial, technical, and economic information required to evaluate the management plans required for estuaries under the National Estuarine Program.

Hedonic models and air pollution: Twenty-five years and counting

This paper reports a meta analysis of how effectively hedonic property models have detected the influence of air pollution on housing prices. Probit estimates are reported describing how data, model specification, and local property market conditions in cities represented in thirty-seven studies influence the ability of hedonic models to uncover negative, statistically significant relationships between housing prices and air pollution measures.

Do Contingent Valuation Estimates Pass a

This paper considers two tests proposed to judge the internal consistency of contingent valuation estimates. Both tests are quite sensitive to the maintained hypotheses required to derive fairly precise expectations for the properties of WTP functions. This result suggests a different approach may be needed in gauging the reliability of CV. This paper describes an alternative approach that relies on a weight of the evidence criterion and uses meta analysis to develop a systematic appraisal of what are the economic values of changes in amenity resources. The approach is illustrated for the case of estimating peoples willingness to pay for improving (or maintaining) visibility at the national parks.

Option Value: A Conceptual Overview

The importance of nonuser benefits to the process of efficiently allocating natural environments was first emphasized by Krutilla [15] a decade and a half ago. One of the components of these nonuser benefits is option value. Originally introduced by Weisbrod [23] as relevant for assets that might be difficult to reproduce, option value has been the subject of considerable debate. Perhaps the simplest approach to explaining the meaning of option value is to use an example. Consider an individual who is uncertain whether he (or she) will consume the services of a particular asset in the future. Furthermore, assume this individual is also uncertain whether the asset will be available in the future should he

Marine Debris, Beach Quality, and Non-Market Values

This paper reports the first attempt to measure the importance of controlling marine debris as an aesthetic characteristic of beaches and coastal area. The results are based on a contingent valuation survey designed to estimate the economic value people would place on controlling marine debris on recreational beaches in New Jersey and North Carolina. A Weibull survival model was estimated treating for and against votes as defining censoring points for an unknown willingness to pay distribution. The findings suggest: (1) people do distinguish situations with differing amounts of debris when they are described using color photographs; (2) the pilot survey implies measures of peoples willingness to pay (WTP) for debris control are consistent with a scope test in that larger WTP is associated with programs intended to address situations for more serious background levels of debris; and (3) local beach conditions seem to influence how people interpreted the plans describing beach conditions without the proposed control programs.

Measuring the Environmental Consequences of Trade Policy: A Nonmarket CGE Analysis

The newly approved GATT trade agreement is likely to focus greater attention on the conflicts between the proliferation of diverse national policies toward environmental quality and the need to maintain competitiveness in world markets. Virtually all policy evaluations of this conflict have been limited by a significant misspecification in existing models. None of the available computable general equilibrium (CGE) models for international trading patterns consistently reflect the effects of environmental resources on consumers preferences. The purpose of this paper is to report the first generation of a composite nonmarket and CGE model (NM/CGE) for the European Community, the United States, Japan, and a single region for the rest of the world. The model incorporates the morbidity and mortality effects of particulates, sulfur oxides, and nitrogen oxides. It uses existing nonmarket valuation estimates (Freeman) with a specification for consumer preferences that allows changes in atmospheric emissions to diffuse in different amounts to