\ " The information in this document has been funded wholly or in part by the United States Environmental Protection Agency under Contract No. 68 01 5838. It has been subject to the Agency's peer and administrative review, and it has been approved for publication as an EPA document. Mention of trade names or commercial products does not constitute endorsement or recommendation for use."

i March 1983 A Comparison of Alternative Approaches for Estimating Recreation and Related Benefits of Water Quality Improvements Prepared for U. S. Environmental Protection Agency Economic Analysis Division Washington, DC 20460 Dr. Ann Fishe~ Project Officer Prepared by Dr. William H. Desvousges Research Triangle Institute Research Triangle Park, NC 27709 Dr. V. Kerry Smith University of North Carolina Chapel Hill, NC 27514 and Matthew P. McGivney Research Triangle Institute Research Triangle Park, NC 27709 EPA Contract No. 68 01 5838 This research project was initiated and supported under work agkeement 68 01 5838 by the Benefits Staff in the Office of Policy Analysis at the U. S. Environmental Protection Agency ( EPA).

Throughout this research effort, the authors of this report were fortunate enough to take advantage of research activities already in progress. One author had partially completed an analysis of the problems of defining and measuring option value, for example, and another had partially completed research to design a generalized travel cost site demand model. In addition the authors also benefited from free access to any array of related working papers   many of which have subsequently been published   that improved the final research design beyond that possible otherwise. Finally, access to an independently developed estimator for ranked data improved the authors' ability to make certain types of comparisons for the contingent ranking component of the survey. Although none of these complementary activities was contemplated when the project was initially proposed, each has played a substantial role in the final results, We would not expect these same circumstances to be easily replicated in future projects of comparable scale and duration.

This final report has been substantially improved through the constructive comments of many reviewers. In particular we would like to thank Ann Fisher, the EPA project officer, for her careful commentary and continuous support. In addition, as part of the EPA's review, six other individuals furnished detailed comments:

Richard Bishop, University of Wisconsin Rick Freeman, Bowdoin College Bill Lott, University of Connecticut Robert Mitchell and Richard Carson, Resources for the Future ( RFF) Bill Schuize, University of Wyoming.

In addition, useful comments were also received from the following individuals:

Tayler Bingham, Research Triangle Institute ( RTI) Peter Caulkins, U. S. EPA Warren Fisher, U. S. Fish and Wildlife Service David Gallagher, University of New South Wales Debbie Gibbs, Bureau of Reclamation Jerry Hausman, Massachusetts Institute of Technology Reed Johnson, U. S. Naval Academy and U. S. EPA John Loomis, U. S. Forest Service Glenn Morris, RTI Doug Rae, Charles River Associates Liz Wilman, RFF.

The authors also have benefited from the comments of participants at presentations given at RFF; Vanderbilt University; the University of Missouri Rolla; Dillon, Colorado ( Visual Values Workshop); Research Triangle Park ( Triangle Econometrics Seminar); and Washington, DC. ( EPA). We pre most grateful for all these efforts. Finally, we are most appreciative of the efforts of our editor, Hall Ashmore, and of Jan Shirley, Supervisor of RTI's Word Processing Center.

111 . , _ . . ... ._     . ... C O N T E N T S Page Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 Introduction, Objectives, and Summary . . . . . . . . . . . . 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . 1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . 1.3 SummaryofResults. . . . . . . . . . . . . . . . . . . 1.3.1 Overview. . . . . . . . . . . . . . . . . . . . . 1 .3.2 Contingent Valuation Approach . . . . . . . . . . 1 .3.3 Travel Cost Approach. . . . . . . . . . . . . . . 1 .3.4 Approach Comparison. . . . . . . . . . . . . . . 1 .3.5 Considerations for Future Research . . . . . . . . l. 4Guide to the Report... . . . . . . . . . . . . . . . .

2 A Brief Review of the Conceptual Basis for the Benefit Estimation Approaches . . . . . . . . . . . . . . . . . . . . 2.11ntroduction . . . . . . . . . . . . . . . . . . . . . . 2.2 A Brief Review of the Conventional Theory of Benefits Measurement . . . . . . . . . . . . . . . . . . 2.3 A Framework for Comparing Alternative Benefit Measurement Approaches. . . . . . . . . . . . . . . . . 2.4 The Nature of the Benefits Measured in the Alternative Approaches . . . . . . . . . . . . . . . . . 2.4.1 Travel Cost Approach. . . . . . . . . . . . . . . 2.4.2 Contingent Valuation Approach . . . . . . . . . . 2.4.3 Contingent Ranking Approach. . . . . . . . . . . 2.5 Summary . . . . .

3 Survey Design . . . . . 3.1 Introduction . . . 3.2 General Description 3.2.1 Geography . 3.2.2 Uses . . . . 3.2.3 Recreation . . . . . . . . . . . . . . . . . . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . of the Monongahela River Basin . . . . . . . . . . . . . . . 3.2.4 Socioeconomic Profile 3.3 Sampling Plan . . . . . . 3.3.1 Target Population . 3.3.2 Sample Selection and 3.3.3 Sampling Weights . . 3.4 Survey Plan . . . . . . . 3.4.1 Questionnaire Desicjn . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Survey Design. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . and Limited Local Pretest . . 3.4.2 Retaining Field Su~ ervisors and Hiring Interviewers . . . . . . . . . . . . . . . . . . .

v ix xi 1 1 1 1 1  4 1 5 1 5 1 5 1 7 1 8 1 11 1 15 2 1 2 1 2  2 2  9 2 12 2 12 2 13 2 14 2 14 3 1 3 1 3 1 3 1 3 3 3  3 3  4 3  5 3  5 3  6 3  6 3 6 3 7 3  9 F.

CONTENTS ( continued)

3.4.3 Counting and Listing of Sample Segments . 3.4.4 Developing Field Manuals and Conducting Interviewer Training . . . . . . . . . . . 3.4.5 Training Session . . . . . . . . . . . . . 3.4.6 Conducting Household Interviews . . . . . 3.4.7 Initial Contacts and Obtaining Cooperation 3.4.8 Household Enumeration . . . . . . . . . . 3.4.9 Interviewing Procedures . . . . . . . . . 3.4.10 Interviewer Debriefing . . . . . . . . . . 3.4.11 Data Receipt, Editing, and Keypunching . . . . .

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4 Contingent Valuation Design and Results: Option Price and User Values . . . . . . . . . . . . . . . . . . . . 4.11ntroduction . . . . . . . . . . . . . . . . . . . 4.2 A Review of Design Issues in Contingent Valuation Survey s . . . . . . . . . . . . . . . . . . . . . . 4.2.1 Hypothetical Bias . . . . . . . . . . . . . 4.2.2 Strategic Bias.... . . . . . . . . . . . 4.2.3 Payment Vehicle Bias. . . . . . . . . . . . 4.2.4 Starting Point Bias . . . . . . . . . . . . 4.2.5 Information Bias . . . . . . . . . . . . . . 4.2.6 Interviewer Bias . . . . . . . . . . . . . . 4.2.7 Summary and Implications for Contingent Valuation Research Design . . . . . . . . . 4.3 Questionnaire Design . . . . . . . . . . . . . . . 4.3.1 Questionnaire Design: Part A . . . . . . . 4.3.2 Benefits Measures: Part B. . . . . . . . . 4.4 Profiles of Survey Respondents . . . . . . . . . . 4.50ption Price Results . . . . . . . . . . . . . . . 4.6 User Value Results . . . . . . . . . . . . . . . . 4.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . .

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5 Contingent Valuation Design and Results: Option and Existence Values . . . . . . . . . . . . . . . . . . . . . . 5.1 Introduction 5 . 2 C o n t i n g e n t Cla; m& " Marke~ s and. the. M. odel. ing of. . " . . .

Uncertainty . . . . . . . . . . . . . . . . . . . . . . . 5.3 Option Value: The " Timeless" Analyses . . . . . . . . . 5.4 The Time Sequenced Analyses . . . . . . . . . . . . . . 5.5 Recent Estimates of Nonuser Values . . . . . . . . . . . 5.6 Measuring Option Value: Survey Design . . . . . . . . 5.7 Survey Results Option Value . . . . . . . . . . . . . . 5.7.1 Option Value Demand Uncertainty . . . . . . . . 5.7.2 Option Value Supply Uncertainty . . . . . . . . 5.8 Existence Value Estimates . . . . . . . . . . . . . . . . 5.9 Summary . . . . . . . . . . . . . . . . . . . . . . . .

vi Page 3 9 3 1o 3 11 3 11 3 13 3 14 3 14 3 16 3 18 4 1 4 1 4 2 4  2 4  4 4  6 4 6 4 7 4 7 4  9 4  9 4  9 4 11 4 20 4 27 4 36 4 38 5 1 5 1 5  3 5 7 5 14 5 16 5 21 5 25 5 25 5 29 5 31 5 33 . . . ... . . . . . CONTENTS ( continued)

Page 6 Contingent Ranking Design and Results: Option Prices. . . . 6.11ntroduction . . . . . . . . . . . . . . . . . . . . . . . 6.2 Consumer Behavior and the Contingent Ranking Framework . . . . . . . . . . . . . . . . . . . . . . . 6.3 Estimation of Random Utility Models with Ordered Alternatives . . . . . . . . . . . . . . . . . . . . . . 6.4 Past Applications of Contingent Ranking . . . . . . . . . 6.5 Monongahela Contingent Ranking Experiment: Design and Estimates . . . . . . . . . . . . . . . . . . 6.6 Benefit Estimates with Contingent Ranking Models . . . . 6.7 Implications and Further Research . . . . . . . . . . . .

7 A Generalized Travel Cost Model for Measuring the Recreation Benefits of Water Quality Improvements . . . . . . 7.1 Introduction 7.2 Travel Cost Model JI III j::::::::::;::: 7.3 The Travel Cost Model for Heterogeneous Recreation Sites . . . . . . . . . . . . . . . . . . . . 7.4 Sources of Data..... . . . . . . . . . . . . . . . . 7.5 Empirical Results for Site Specific Travel Cost Models . . 7.5.1 The Treatment of Onsite Time . . . . . . . . . . 7.5.2 The Opportunity Cost of Travel Time . . . . . . . 7.5.3 Results for the Basic Model . . . . . . . . . 7.5.4 Results for the Tailored Modeis" . . . . . . . . . 7.5.5 Evaluation of Measures of the Opportunity Cost of Travel Time..... . . . . . . . . . . . . . 7.6 Further Evaluation of the Travel Cost Models . . . . . . 7.7 Analyzing the Role of Water Quality for Recreation Demand . . . . . . . . . . . . . . . . . . . . . . . . . 7.8 A Measure of the Benefits of a Water Quality Change . . . . . . . . . . . . . . . . . . . . . . . . . 7.9 Summary . . . . . . . . . . . . . . . . . . . . . . . .

8 A Comparison of the Alternative Approaches for Estimating Recreation and Related Benefits . . . . . . . . , . . . . . . 8.1 Introduction 8.2 The Conceptual ; ram. ewo; k. for. a. Cornpar; s& . o; " . " . .

Recreation Benefit Estimation Approaches . . . . . . . . 8.2.1 Background . . . . . . . . . . . . . . . . . . . 8.2.2 Research Design and Comparative Analysis . . . . 8.2.3 Past Comparisons of Benefit Estimation Methods . . . . . . . . . . . . . . . . . . . . . 8.3 A Comparative Evaluation of the Contingent Valuation, Travel Cost, and Contingent Ranking Benefit Estimation Methods . . . . . . . . . . . . . . . . . . . 8.41mplications . . . . . . . . . . . . . . . . . . . . . . 6 1 6 1 6 2 6 7 6 9 6 16 6 25 6 28 7 1 7 1 7  2 7 1o 7 22 7 30 7 31 7 32 7 32 7 36 7 38 7 43 7 51 7 57 7 64 8 1 8 1 8 2 8 2 8 3 8 9 8 12 8 20 vii , CONTENTS ( continued)

9 References . . . . . . . . . . . . . . . . . . . . . . . . . .

Appendixes A Sample Design . . . . . . . . . . . . . . . . . . . . B Survey Forms and Procedures . . . . . . . . . . . . Part l Household Control Form. . . . . . . . . . . Part 2 Counting and Listing Examples . . . . . . . Part 3 Debriefing Agenda . . . . . . . . . . . . . Part 4 Quality Control Procedures . . . . . . . . . c Survey Analysis: Supporting Tables . . . . . . . . . D Survey Questionnaires . . . . . . . . . . . . . . . . Part l Survey Questionnaire . . . . . . . . . . . Part 2 Suggestions for Improving the Questionnaire Future Use . . . . . . . . . . . . . . . . . . . . E Technical Water Quality Measures: An Economist's Perspective . . . . . . . . . . . . . . . . . . . . . F Travel Cost: Supporting Tables . . . . . . . . . . . G Alternative Regression Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . for . . . .

. . . . . . . . . . . . . Paqe 9 1 A 1 B 1 B 1 B  4 B 7 B 9 c  1 D 1 D 2 D 28 E 1 F 1 G 1 . . . Vlll FIGURES Number 1 1 1 2 2 1 2 2 2 3 2 4 2 5 3 1 3 2 3 3 3  4 4 1 4 2 4 3 4 4 4 5 4  6 4 7 4  8 5 1 5  2 5 3 5  4 5 5 6 1 7 1 Effects and responses to water quality regulatory actions . . A spectrum of water quality benefits . . . . . . . . . . . . .

The demand function and the consumer surplus welfare measure . . . . . . . . . . . . . . . . . . . . . . . . . . . A comparison of alternative welfare measures . . . . . . . . . Surplus measures for a change in quantity . . . . . . . . . . Smith  Krutilla framework for classifying the measurement bases and approaches of economic benefits resulting from improved water quality. . . . . . . . . . . . . . . . . . . . Travel cost demand function with water quality improvement . . . . . . . . . . . . . . . . . . . . . . . . .

Map of Monongahela River and other area recreation sites . . . . . . . . . . . . . . . . . . . . . . . Geographic location of survey area . . . . . . . . . . . . . . Field interviewer training session agenda . . . . . . . . . . Summary of completed interviews . . . , . . . . . . . . . . .

Activity card . . . . . . . . . . . . . . . . . . . . . . . . Site activity matrix . . . . . . . . . . . . . . . . . . . . . Map of Monongahela River and other area recreation sites. . . Recreation sites . . . . . . . . . . . . . . . . . . . . . . . Water quality ladder . . . . . . . . . . . . . . . . . . . . . Value card . . . . . . . . . . . . . . . . . . . . . . . . . . Payment card Rankordercardjjj; l:: j:::::::::::::::

Optimal allocation of choice with contingent claims . . . . . Optimal allocation of choices of contingent claims without uniqueness . . . . . . . . . . . . . . . . . . . . . . Option value in Cicchetti Freeman analysis . . . . . . . . . . Option value in Cicchetti Freeman with " no demand" . . . . . Option value with contingent claims in Graham's analysis . . .

Rank order card . . . . . . . . . . . . . . . . . . . . . . .

Measurement of consumer surplus increment due to water quality improvement . . . . . . . . . . . . . . . . . .

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ix Page 1 2 1 3 2  3 2  5 2  6 2 1o 2 12 3  2 3  5 3 12 3 13 4 1o 4 1o 4 12 4 12 4 13 4 14 4 17 4 20 5  6 5  7 5 12 5 12 5 13 6 18 7 59 ., I ABLtb Number 1 1 1 2 2 1 3 1 3 2 4 1 4  2 4 3 4 4 4 5 4 6 4 7 4  8 4  9 4 1o 4 11 4 12 4 13 4 14 5 1 5  2 5 3 5  4 5 5 A Comparison of Mean Benefit Estimates . . . . . . . . . . . Regression Comparisons of Contingent Valuation and Travel Cost Benefit Estimates . . . . . . . . . . . . . . . .

Alternative Welfare Measures and Types of Consumer Surplus Measures for Contingent Valuation Studies . . . . . .

Questionnaire Development Activity . . . . . . . . . . . . . . Final Distribution of Sample Housing Units . . . . . . . . . .

Summary of Biases in Contingent Valuation Experiments . . . . Summary of Option Price Question Formats by Interview Type . . . . . . . . . . . . . . . . . . . . . . . Characteristics of Key Respondent Groups . . . . . . . . . . Reasons for Zero Bids by Elicitation Method . . . . . . . . . Degree of Importance of Water Quality by Key Respondent Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . Respondent Attitudes About Self by Key Respondent Groups . Logit Estimation of Zero Bids . . . . . . . . . . . . . . . . Profile of Outliers . . . . . . . . . . . . . . . . . . . . . Estimated Option Price for Changes in Water Quality: Effects of Instrument and Type of Respondent Protest Bids and Outliers Excluded. . . . . . . . . . . . . . . . . . Student t Test Results for Option Price Protest Bids and Outliers Excluded.. . . . . . . . . . . . . . . . . . . Regression Results for Option Price Estimates Protest Bids and Outliers Excluded . . . . . . . . . . . . . . . . . Student t Test Results for Option Price Protest Bids and Outliers Excluded.. . . . . . . . . . . . . . . . . . . Estimated User Values Protest Bids and Outliers Excluded . . Regression Results for User Value Estimates of Water Quality Changes  Protest Bids and Outliers Excluded . . . . .

Summary of Mitchell Carson Estimated Mean Annual Willingness to Pay by Version and Water Quality . . . . . . . Summary of Willingness to Pay Questions by Type oflnterview . . . . . . . . . . . . . . . . . . . . . . . . . Summary of User, Supply Uncertainty, and Existence Value Questions . . . . . . . . . . . . . . . . . . . . . . . Estimated Option Values for Water Quality Change: Effects of Instrument and Type of Respondent Protest Bids and Outliers Excluded.. . . . . . . . . . . . . . . . . . . Student t Test Results for Question Format. . . . .  . . . . Paqe 1 9 1 1o 2 7 3  8 3 15 4 8 4 18 4 21 4 23 4 24 4 25 4 26 4 30 4 32 4 33 4 34 4 36 4 37 4 38 5 19 5 24 5 24 S 26 5 27 xi TABLES ( continued)

Number Page 5 6 5 7 5 8 5  9 6 1 6  2 6  3 6  4 6 5 7 1 7  2 7  3 7  4 7  5 7  6 7 7 7 8 7  9 7 1o 7 11 7 12 7 13 7 14 7 15 7 16 7 17 7 18 7 19 Regression Results for Option Value Estimates Protest Bids and Outliers Excluded.. . . . . . . . . . . . . . . . . . . . Effects of Supply Uncertainty on Option Price . . . . . . . . Student t Tests for the Effects of Supply Uncertainty for Users... . . . . . . . . . . . . . . . . . Estimated Existence Values . . . . . . . . . . . . . . . . . .

Summary of Rae/ CRA Contingent Ranking Studies . . . . . , Combinations of Water Quality and Payments for Monongahela Contingent Ranking Survey . . . . . . . . . . . . . . . . . Selected Results for the Random Utility Model With Ranked Logit Estimator . . . . . . . . . . . . . . . . . . . . Comparison of Ordered Logit and Keener Waldman Ordered Normal ML Estimator . . . . . . . . . . . . . . . . . Benefit Estimates from Contingent Ranking Models . . . . . .

Hedonic Wage Models . . . . . . . . . . . . . . . . . . . . . Summary of Predicted Hourly Wage Rates . . . . . . . . . . . The Characteristics of the Sites and the Survey Respondents Selected from the Federal Estate Survey . . . . . Regression Results of General Model, by Site . . . . . . . . . Summary of Cicchetti, Seneca, and Davidson [ 1969] Participation Models . . . . . . . . . . . . . . . . . . . . . Comparison of Basic Model with Tailored Model : Coefficient for( TC+ MC) . . . . . . . . . . . . . . . . . . . F Test for Restriction of General Model . . . . . . . . . . . F Test for Restriction of Tailored Models . . . . . . . . . . Effects of Truncation on the Travel Cost Models' Estimates . . Two Stage Least Squares Estimates for Selected Travel Cost Site Demand Models... . . . . . . . . . . . . . . . . Comparison of Ordinary Least Squares and Two Stage Least Squares Estimates of Travel Cost ( TC. + MC. ) Parameters . . . . . . . . . . . . . . . . . Hausman ~ est f~ r Differences Between Two Stage Least Squares and Ordinary Least Squares Estimates . . . . . Description of U. S. Army Corps of Engineers Data on Site Characteristics . . . . . . . . . . . . . . . . . . . . . Generalized Least Squares Estimates of Determinants of Site Demand Parameters . . . . . . . . . . . . . . . . . . . Recreation Sites on the Monongahela River . . . . . . . . . . Dissolved Oxygen Levels for Recreation Activities . . . . . . Mean and Range of Benefit Estimates for Water Quality Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . Consumer Surplus Loss Due to the Loss of Use of the Monongahela River by Survey Users' Income . . . . . . . . . Consumer Surplus Loss Due to Loss of Use of the Monongahela River by Survey Users' Travel Cost . . . . . . . 5 28 5 30 5 31 5 32 6 11 6 18 6 21 6 24 6 27 7 26 7 27 7 28 7 33 7 36 7 37 7 39 7 42 7 45 7 48 7 49 7 50 7 53 7 56 7 57 7 60 7 61 7 62 7 62 xii TABLES ( continued)

Number 7 20 7 21 8 1 8 2 8 3 8  4 8  5 Consumer Surplus Increments Due to Water Quality lmprovement Boatable to Fishable by Survey Users' Income . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Consumer Surplus Increment Due to Water Quality lmprovement Boatable to Swimmable by Survey Users' Income . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Predicted Demand Parameters for Monongahela Sites. . . . . . Bishop Heberlein Comparative Results for Benefit Approaches . . . . . . . . . . . . . . . . . . . . . . . . . A Comparison of Benefit Estimates for Water Quality Improvements . . . . . . . . . . . . . . . . . . . . . . . . . A Comparison of Contingent Valuation and Generalized Travel Cost Benefit Estimates . . . . , . . . . . . . . . . . A Comparison of Contingent Valuation and Contingent Ranking Benefit Estimates . . . . . . . . . . . . . . . . . . Page 7 63 7 63 8  8 8 10 8 13 8 16 8 19 . . . X111 ."     7 CHAPTER 1 INTRODUCTION, OBJECTIVES, AND SUMMARY 1.1 INTRODUCTION This Research Triangle Institute ( RTI ) report to the U. S. Environmental protection Agency ( EpA) compares alternative approaches for estimating the recreation and related benefits of water quality improvements. The results provide information on the performance of various ways to estimate the benefits of environmental quality improvements, so EPA can use such methods in preparing the regulatory impact analyses required by Executive Order 12291 and in evaluating other regulatory proposals. This report is also relevant to the proposed revision of the Federal water quality standards regulations, which recommends that States consider incremental benefits and costs in setting their water quality standards. Site specific water quality standards are likely to play an important role in future water policy issues because they bring together the crucial elements of appropriate stream uses and advanced treatment requirements for municipalities and industries. Benefit cost assessments can yield valuable information for these decisions.

Evaluations of benefits and costs depend on a determination of the links between regulatory policy, technical effects, and behavioral responses. Figure 1 1 illustrates one set of linkages  in this case for the proposed water quality standards regulations. This report addresses the last component of Figure 1 1, which involves estimating monetized benefits for regulatory policy. One of the difficulties in such a task arises from the absence of organized markets for many of the services derived from water resources.

The benefits of water resource regulations are usually measured with one of three types of approaches: ( 1) market based approaches, which use indirect I in kages between the environmental goods and some commodities exchanged in markets; ( 2) contingent valuation approaches, which establish an institutional framework for a hypothetical market; and ( 3) public referenda. This report considers the first two approaches; the last is omitted since it is beyond EPA's mandate.

Some opponents argue that benefit cost analysis is invalid because it cannot measure all of the benefits of environmental regulations. Nevertheless, this report describes the measurement of several benefits from water quality improvements, including some regarded as unmeasurable in earlier environmental benefits research efforts. Specifically, as highlighted in Figure 1 2, this study considers both the recreation benefits that accrue to users of a recreation site and the intrinsic benefits* that accrue to both users and nonusers.

* This classification modifies the one in Mitchell and Carson [ 1981] .

1 1 rl Changs Oasignatad Lb( s)

II Watar @ diW Regulatory Action( s)

v i Modify Critaria to Provida for Osaignatad Usa( s)

f t I rl Chan~ in Effluants I I I Cfsangas in Vktar Ouality I ' O" A" iOn( s~ * Taohnioal Effects of Watar Ouality L + Effaots on Economic Agarsts  w=(')< nEiiicl Bahaviod Effacts of Watar Ouallw Figure 1 1. Effects and responses to water quality regulatory actions.

User benefits arise from recreation uses of the river and are measured by users' willingness to pay for the water quality levels necessary to permit these recreation uses. That is, the valuation depends on the use of the river. In this case, clean water in a river is worth something because recreationists are going to fish, boat, swim in, or picnic along the river.

Intrinsic benefits consist of two value types: option value and existence value. Relevant to both current users and potential future users, option value is the amount an individual would be willing to pay for improved water quality ( over his expected user values) to have the right to use the river in the future when there is uncertainty either in the river's availability at a particular quality level or in his use of it ( with the river meeting specified water quality conditions). For example, if an individual might use the river, but is not sure he will, he may pay some amount each year for the right ( or option) to use it ( with the river meeting specified water quality conditions). Under some conditions, this payment, the option price, will exceed his expected consumer surplus  the value he would derive from anticipated use. This excess the amount that the option price exceeds the expected consumer surplus is defined as the option value.

1 2 potential Water Quality Benefits Current User Benefits Intrinsic Benefits Direct use Indirect use Potential use No Use + Recreational l   fishing, swimming, boating, rafting, etc. In Stream Commercial   fishing, navigation { Municipal   drinking water, waste disposal Withdrawal Agricultural   irrigation Industrial/ Commercial   cooling, process treatment, waste disposal, steam generation { Recreational*   hiking, picnicking, birdwatching, photography, etc. Near Stream Relaxation*   viewing Aesthetic"   enhancement of adjoining site amenities + Near term potential use Option*

Long term potential use  i Stewardship   maintaining a good environment for everyone to enjoy ( including future Existence* family use   bequest)

Vicarious consumption   enjoyment from the knowledge that others are using the resource.

l   Considerad in this project.

Figure 1 2. A spectrum of water quality benefits.

Existence value, on the other hand, is an individual's willingness to pay for the knowledge that a resource exists. That is, an individual either a user or a nonuser might be willing to pay something to maintain a high level of water quality at a recreation site in a particular area, even though he will not use it, so that his children may have future use of the site or simply to know that the ecosystem at the site will be maintained.

This study's comparison of alternative benefits measurement approaches estimates user values by the travel cost approach ( indirect method), by four different ways of eliciting option price in a contingent valuation experimental design ( direct method), and by a contingent ranking of water quality outcomes and option price amounts. The central comparison evaluates whether there are differences between approaches because " true" values for each of these types of benefits are unknowns. In addition, since the other methods are not suitable for measuring them, option and existence values are compared only in terms of alternative ways for posing the hypothetical questions.

A distinguishing feature of this project is its use of a case study of the Pennsylvania portion of the Monongahela River as the point of reference for 1 3 both the comparison of approaches and the estimation of option and existence values. The Monongahela is representative of a number of rivers in the country, has multiple uses, and has recently been the focus of effluent guidelines for the iron and steel industry. The survey design for the Monongahela, calling for a household survey, is a middle ground between the macro approach for estimating benefits of water po{ lution controls ( see Mitchell and Carson [ 1981 ] ) and the user orientation of many micro contingent valuation efforts ( see Schulze, d'Arge, and Brookshire [ 1981]). The design uses a representative sample of households for the region and, similar to Mitchell Carson, includes both user and intrinsic benefits. It also is a specific application, considering individuals' willingness to pay for a specific river basin's water quality.

1.2 OBJECTIVES The potential implications of this study for water policy dictated clearly defined objectives and a project design to achieve them. The overall objective of this project was to conduct a study comparing alternative approaches for estimating the recreation and related benefits of different water quality levels. In particular, the study sought to measure user, option, and existence values for the Pennsylvania segment of the Monongahela River and to estimate the recreation and related benefits that would be derived from providing different use classifications ( fishable, swimmable, beatable) for this river segment.

In addition to meeting its own specific objectives, an environmental benefits research project ideally would fit the needs of those involved in the evaluation of public policy questions and the needs of the research community in general. Since the most important direct use of natural environments is for water based recreation ( see Freeman [ 1979a] ), this project's general research area considers one of the primary components of environmental benefits research. In addition to its water quality orientation, the project is also relevant to two areas Freeman identified for future research:

I think that a major research effort should be made to select an appropriate area and water bodies for a study, to develop a properly specified model, and to gather the necessary data. Until such an effort is made, t h e p r a c t i c a l i t y o f t h e Clawson Knetsch [ 1 9 6 6 ] [ travel cost] technique for estimating recreation benefits will remain an open question. [ p. 256]

There should be carefully conducted experiments with the survey techniques for estimating willingness to pay for reduction in pol Iu  tion. These experiments should be coordinated with studies based on other analytical techniques in an effort to provide a cross check or validation of benefit estimates obtained by different approaches. [ p. 265]

.

1  4 1 . 3 S U M M A R Y O F R E S U L T S This section summarizes at e presented for individual preaches.

1 .3.1 Overview the major findings of the research. The findings approaches and for the comparison between ap

The results of this project strongly support the feasibility of measuring the recreation and related benefits of water quality improvements. Moreover, the benefits measurement approaches  several contingent valuation formats and the travel cost method  show consistent results for comparable changes in water quality. Indeed, the range of variation is generally less than that expected in models used to transiate the effects of effluents in a water body into the corresponding water quality parameters. In addition, the results also clearly show that the intrinsic benefits of water quality improvements especially option values  can be measured and that they are a sizable portion  greater than half  of the total recreation and related benefits total .

1 .3.2 Contingent Valuation Ap preach Based on the results of the Monongahela River case study, the general prognosis is good for the continued use of the contingent valuation approach to estimate the benefits of water quality improvements. Statistical analysis using regression methods to evaluate the determinants of the variation in the option price bids gave little indication that individual interviewers influenced the results. The consistently plausible signs and magnitudes of key economic variables suggest that the respondents perceived the survey structure as realistic and did not experience problems with the hypothetical nature of some of the questions. These findings were realized despite the fact that the sample included households whose socioeconomic profile was comparable to demographic groups that were found to be more difficult respondents in past contingent valuation surveys. On average, the respondents were older, less educated, and poorer than those in the most successful contingent valuation studies.

The contingent valuation estimates of the option price for water quality improvements, which include user and option values , are consistently plausible across the various analytical approaches, with estimates for the combined water quality levels ranging from roughly $ 50 to $ 120 per year per household sampled in the Monongahela River basin. Nonetheless, the empirical results do indicate that the methods used to elicit the willingness to pay amount have a statistically significant effect on the estimates of willingness to pay. For example, both the direct question with a payment card and the bidding game with a $ 125 starting point produced higher willingness to pay estimates than either the direct question without an aid or the bidding game with a $ 25 starting point. Thus, there is some evidence of starting point bias in the bidding game, but the statistical analyses are not conclusive. The results comparing the two bidding game methods as a set ( i. e. , those with $ 25 and $ 125 starting points) with the non bidding games ( direct question and payment card combined) indicated no differences between these two sets of approaches.

1 5 The findings provide clear support for a positive, statistically significant, and sizable option value for water quality improvements along the Monongahela River. The estimated option values for loss of the use of the area in its current condition ( i . e. , boatable) range from approximately $ 15 to $ 60 per year per household, and the option values for improving water quality to a swimmable level range from approximately $ 20 to $ 45 per year per household. Thus, option value is a substantial fraction of the user's option price, and the value of this change in water quality generally exceeds user values.

The survey also provided estimates of existence values. Unfortunately, respondents did not necessarily understand the distinction sought. Many bid the same amounts as they had earlier on the option price for a comparable change in water quality. It is not clear whether these responses were deliberate or a reflection of misunderstanding of the questions. Thus, while the findings suggest that these values are positive and statistically significant, prudence requires they be interpreted cautiously.

Of course, it should also be acknowledged that the available estimates of intrinsic values are quite limited. Most can be criticized for problems in the research design, including possible flaws in the survey. The design of the Monongahela River study relies on the use of a schematic classification of the sources of an individual's valuation of the river ( i. e. , a card showing different types of values) in eliciting a division of user and other benefits. Because this is the first application of this device, it was not possible to evaluate its effectiveness.

In addition to the more widely used bidding game and direct question formats for contingent valuation experiments, t h e Monongahela R i v e r b a s i n survey also applied the contingent ranking format. This format requires only that individuals rank combinations of water quality levels and option prices and uses a statistical procedure ( ranked order logit)* to estimate willingness to pay. While other contingent valuation formats require that individuals directly provide willingness to pay, contingent ranking asks them to rank hypothetical outcomes. In effect, it asks a simpler task of the respondent only to rank outcomes  but requires more sophisticated and less direct techniques to estimate the value of the outcomes.

Since use of the contingent ranking format to estimate the benefits of environmental quality improvements is quite new, the behavioral model underlying its estimation procedures is also early in its development. Although this project provides a description of these underpinnings, its evaluation of the theoretical properties and practical issues is incomplete. Overall, the findings of this study suggest that, even though the behavioral models used to derive benefits estimates with the contingent ranking format were somewhat arbitrary, the results from the ranking format closely parallel other contingent valuation estimates.

* ln more technical terms, the procedure uses a specification for the indirect utility function together with a maximum Ii kelihood estimator.

1 6 The mean estimates derived from the contingent ranking format roughly $ 6 0 annuallY Per household for imProvin9 water quality in the Monongahela to fishable and approxlamteiy $ 50 more annUallY for improving it to swimmable appear l a r g e r t h a n those derived with other contingent valuation formats. However, these differences are not statistically significant. In addition, the benefit estimates from all continent vaiuation formats are comparable across individuals, with the primary differences between contingent ranking and other methods stemmin9 from the questioning format used in the other methods.

1 .3.3 Travel Cost Ap preach This study also developed and used a generalized travel cost model to predict the recreation benefits of water quality improvements at recreation sites.

The travel cost model assumes that site features or attributes affect both an individual's ability to participate in recreation activities at any particular site and the quality of his recreation experiences at the site. In considering the demand for a recreation site as a derived demand, the common sense rationale of the model suggests that a recreation site's features or attributes will influence the demand for its services. Since the level of water quality i s a site attribute, a basis is established for relating water changes to shifts in demand for a recreation site's services.

The generalized model was estimated from data on 43 water based recreation sites in the Federal Estate Survey component of the 1977 National Outdoor Recreation Survey. This survey provided information on recreation use patterns at each site during a single season. Based on sample sizes for each site that ranged from approximately 30 to several hundred respondents, t h e survey described individuals' recreation behavior, socioeconomic characteristics travel time necessary to reach the site of other factors. , residential location, and a variety Several advantages of this travel cost model include:

. Deriving individual estimates for the time associated with traveling to the site as well as the roundtrip distance for each t r i p .

. Using the opportunity cost of time to evaluate travel time and estimating opportunity cost for each individual based on his characteristics, inclu ding age, education, race, occupation.

. Considering for each site the potential effects of differences in onsite time per visit.

The generalized model was used to estimate the benefits Monongahela R i v e r , as identified in the survey of the basin. model predicted a value of $ 83 per year per user household sex, and individuals'

for users of the The travel cost if a decrease in 1 7 .     . .. water quality is avoided and a value of $ 15 per year for each user household [ if water quality is improved to a swimmable level.

i$

Several features of the generalized travel cost model are of particular importance: it provides a framework for estimating the value of water quality improvements for a substantial range of sites, and its site specific orientation is especially relevant for water quality standards applications. Finally, it includes the effect of key site features like access and facilities and can use data frequently available in the public domain.

1 .3.4 Approach Comparison One of the primary objectives of this research has been to compare available approaches for measuring the benefits of water quality improvement. Such a comparison  reflecting the assumptions inherent in each approach will show the plausibility of the required assumptions as descriptions of real world behavior and constraints. However, since the " true" value of water quality improvement benefits is unknown, a comparison cannot be interpreted as a validation of any one approach. On the other hand, an evaluation of the c o m  parability of estimates across approaches that considers the reasons for their consistencies and differences provides a basis for an improved use of benefit methodologies. Consistency also would give increased flexibility in matching a method to available data for each particular application.

Based on the research for the Monongahela River basin case study, the comparison between the travel cost and contingent valuation approaches is the most interesting. Estimates of benefits from water quality improvement are compared for the 69 users identified in the survey of households in the basin /

area. Previous comparisons of approaches relied on the use of mean estimates c from each method. When these means are compared, it is assumed that all individuals can be treated as drawing from populations with the same mean benefits. Differences in individuals or error in the pairing of means can lead to a confounding of the benefit comparisons. In contrast, this study compared each household's user value, derived from the contingent valuation survey, with the corresponding estimate for that household from the travel cost model. Thus, this study gives a " more controlled comparison than was possible in earlier studies. ~ Table 1 1 shows the mean benefit estimates of user values for the travel cost and contingent valuation approaches. On theoretical grounds, the contin [ gent valuation estimates of compensating surplus should be less than the travel 1 cost estimates based on ordinary consumer surplus, but the differences should be slight due to the small income effects found in the research. However, \

this is not the case for three out of four contingent valuation estimates for improvements in water quality. Only the estimates derived with the $ 25 bidding game format are less than the travel cost estimates, although the travel cost estimates are within the range of contingent valuation estimates. For the loss of the area, the means comparison conforms to theoretical expectations, with the travel cost estimates larger than the contingent valuation estimates. Most of the differences between approaches exceed the size expected from theory. At best, simple comparisons of mean estimates augmented by a priori information  are rough judgments of plausibility. On the basis of this comPar

11 1 8 Table 1 1. A Comparison of Mean Benefit Estimates ( 1981 Dollars) a Water quality changeb Boatable Boatable Approach Loss of area to fishable to swimmable Contingent valuation Direct question 19.71 ( 17) 21.18 ( 17) 31.18 ( 17)

payment card 19.71 ( 17) 30.88 ( 17) 51.18 ( 17)

iterative bidding ($ 25) 6.59 ( 19) 4.21 ( 19) 10.53 ( 19)

iterative bidding ($ 125) 36.25 ( 16) 20.31 ( 16) 48.75 ( 16)

Generalized travel cost 82.65 ( 94) 7.01 ( 94) 14.71 ( 94)

a The travel cost estimates were converted from 1977 to 1981 dollars using the consumer price index for December 1981, the last month of the survey.

bThe numbers in parentheses after the means are the number of observations on which each of these estimates was based. The number for the travel cost estimates exceeds the sum of the sample size for the contingent valuation results because some users visited more than one Monongahela River site.

ison, however, the Monongahela River basin precise.

A more discriminating comparison of the estimates are plausible, but not travel cost and contingent valuation approaches, one that judges how the two approaches compare across individuals is also possible with the Monongahela River basin benefit estimates. In this comparison, presented in Table 1 2, the contingent valuation measure of user value was regressed on the travel cost estimate ( see Chapter 8 for details). The ~ priori expectations of comparability in methods can be structured as two statistical tests. These models also take account of the effect of question formats used in the contingent valuation survey.

The results from the regression tests generally reinforce the earlier conclusions based on comparing the means estimated from each method. Several additional conclusions are possible from these comparisons:

. The contingent valuation estimates of water quality improvements overstate willingness to pay in contrast to the theoretical expectation s but the results do not permit a judgment of statistically significant differences between the two sets of estimates Some caution is required, however, because the properties of the statistical tests are approximate.

. The travel cost model overstates  by an amount greater than theory would predict willingness to pay for the loss of the area, and the estimates are not comparable to the~ ntingent valuation estimates. ,

1 9 r Table 1 2. Regression Comparisons of Contin~ ent Valuation and Travel Cost Benefit Estimates Water quality change Independent Boatable to Boatable variables Loss of area game fishing to swimming Intercept Travel cost benefit estimate Qualitative variables Payment card Direct question Iterative bid ($ 25)

R 2 F 2 1 . 8 6 ( 1.37)

0.33 ( 1.17) b (  4 . 3 6 )

 32.64 (  2 , 5 5 )

 14.60 ( 1 .27)

 31.82 (  2 . 5 5 )

0.10 2.42 ( 0.05) C 33.99 ( 1.90)

5 1 . 7 6 ( 2.64)

12.96 ( 0.75)

 11.24 (  0 . 6 0 )

0.12 3.00 ( 0.02) C 59.57 ( 2.02)

 2.71 ( 1.14) b ( 1 .79)

77.01 ( 2.36)

21.00 ( 0.73)

 21.82 (  0 . 6 9 )

0.11 2.62 ( 0.04) C a The numbers below the estimated coefficients are t ratios for the null hypothesis of no association. b These statistics are the t ratios for the hypothesis equivalent to unity for the slope coefficientl% r Ordinary Consumer Surplus ( OCS) after adjustment is made for the fact that Compensating Surplus ( CS) is measured in 1981 dollars and OCS in 1977 dollars.

c The number in parentheses below the reported F statistic is the level of significance for rejection of the null hypothesis of no association between the dependent and independent variables.

. The comparative performance of the contingent valuation approach in relationship to the travel cost method is sensitive to differences in question format with the clearest distinctions found between the payment card and the bidding game with the $ 125 starting point.

. The explanatory power of the models used in the comparison are not high, but the null hypothesis of no association between methods is clearly rejected at high levels of significance ( based on the F tests reported at the bottom of the table).

1 10 1 .3.5 Considerations for Future Research T h e findings of this project also suggest that there are a number of areas for future benefits research, including both general and specific issues especially those concerned with particular benefits measurement approaches.

Genera] ! SSUeS Option and existence values remain the most difficult general issues to address adequately. The research design for this project relied on the individual to divide the hypothetical option price payment into its user and option value components and then to add existence values to these option price bids as an incremental premium. Other studies ( Brookshire, Cummings, et al. [ 1982] and Randall, Hoehn, and Tolley [ 1981 ] ) have elicited preservation values  including both option and existence values as additions to user values. Mitchell and Carson [ 1981 ] found user values by subtracting nonuser's option price payments from user option price payments. Regardless of the procedures, however, all these studies have found option and existence values to be substantial greater than half of the total benefits of environmental improvements. The choice among elicitation procedures, remains an open question.

One question that arises from the results of this and other recent studies of intrinsic benefits is, " Why worry about measuring option value when it is possible to elicit option price bids that include it?" Empirical estimates are of interest because of the controversy over the sign and magnitude of option value that has arisen in the theoretical literature. I n addition, many practical applications of benefit methods do not measure intrinsic benefits, suggesting a need for empirical estimates to gauge the extent of the omitted portion of benefits from particular environmental policies. The early theoretical work seemed to imply ( without explicitly stating this conclusion) that option values would be small in comparison to user values. Recent theoretical work by Freeman [ 1982] makes a case for positive option values and confirms this presumption by suggesting that option values should be small under almost all conditions. Only by attempting to distinguish between option and other intrinsic values will it be possible to bring some empirical evidence to bear on this question.

Proportional relationships between user and intrinsic values from earlier studies have often been used in attempts to infer the size of the omitted benefits when the intrinsic values are not directly estimated. The limited resources available for many public policy evaluations is the primary reason for the widespread use of the proportional approach. Since it is unlikely that these constraints on evaluations will ease in the future, more empirical research on the use and size of these proportions might be productive. For instance, determining how ( and if) the proportions differ for certain classes of assets  ranging from unique natural environments to waterbodies with numerous substitutes would provide useful guidance for applying these proportions. Moreover, attempting to distinguish between option and existence values for different classes of environmental assets may indicate the feasibility and need for such distinctions ( see Fisher and Raucher [ 1982] for a review).

1 11 . The research in this project has skirted another important issue benefits aggregation. The travel cost model used in this project predicts recreation site benefits for " the representative" user. By assuming that all sites are possible substitutes ( because one site's attributes can be " repackaged" to be equivalent to any other site), it implicitly maintains a simplistic view of the relationship between recreation sites within a region. Individuals always select the site providing the desired mix of attributes at the lowest implicit price. Clearly, not all sites adhere to these relationships. For example, a historical monument at the site may make it unique. What is needed is a more general characterization that would accommodate sites not conforming to the aggregation rule used to relate effective site services to site attributes. Such a framework would explain the relationship between an individual's patterns of site usage for facilities permitting very different types of recreation activities ( e. g., water based recreation versus skiing). Nevertheless, consistent regional and national benefit estimates will require a careful description of the interrelationships between the individual's demands for different types of recreation sites.

Another unresolved issue involves regional aggregation of local benefits estimated with the contingent valuation approach. Conventional practice in statistical surveys is to use statistical weights, which reflect the probability of selecting a particular sampling unit, to estimate aggregate benefits for t h e representative population ( see Mitchell and Carson [ 1981 ]). H o w e v e r , t h i s approach raises fundamental problems with the conventional practice in economic modeling that assumes common ( and constant) parameters across individuals for correctly specified behavioral models. The definition of a representative sample is often based on a description of statistical models, leading to observed data that are at variance with conventional economic modeling. More research following the work of Porter [ 1973] is needed to consider t h e relevance of this issue for the extrapolation of contingent valuation estimates.

Another general research issue involves comparing alternative benefit estimation approaches. This project's comparison, which examines benefits predicted with the generalized travel cost model and contingent valuation will  ingness to pay estimates for the same individuals, permitted a fairly direct comparison of estimates with theoretical bounds. However, this study used estimates from only 69 users of the Monongahela River. A comparison having a larger number of users and based on a water based recreation site with a greater diversity of users would provide a more revealing comparison. Indeed, following Bishop and Heberlein, attempts to compare simulated market results with the results of this project also may shed light on the relationships among the estimation approaches. Before these comparisons are made, however, more systematic attention should be given to the theoretical underpinnings of t h e approaches, following the work of Schulze et al. [ 1981], Smith and Krutilla [ 1982], and Bockstael and McConnell [ 1982].

Future research should also reconsider the economic principles underlying comparisons of economic welfare particularly the measurement basis ( ordinary consumer surplus and the more precise Hicksian based measures). The comparisons made in this project have involved expenditures of such a small percentage of individuals' budgets that the differences between the measures is 1 12 insignificant. Since some, and perhaps many, environmental issues may involve large price and quantity changes with more significant income effects, the emPirical application of various measures becomes significant. Bockstael a n d McConnell [ 19801 have raised some empirically b a s e d i s s u e s , b u t a m o r e extensive effort such as Willig's [ 19761, comparing recent approaches proposed by Hausman [ 1981], McKenzie and Pearce [ 1982] , and Takayama [ 1982], may yield guidance for applications with these large changes.

A final general issue on the research agenda that, unfortunately, was beyond the scope of this project and too many other benefits analyses is the distribution aspect of benefit policies. By neglecting distribution concerns, economists are unable to appreciate many policy objections expressed in the political arena. For example, attention to the distributional effects of alternative water pollution policies would be a valuable complement to the efficiencyoriented questions that constitute the primary focus of benefits analysis. Further rationale for such efforts stems from Executive Order 12291, which recognizes the importance of distribution effects by requiring them in regulatory impacts analyses.

The future research agenda for the individual benefits estimation approaches contains items ranging in subject from experimental design and sampling to the behavioral models that underlie several approaches. Some of the agenda items are already being studied in various quarters, while others will involve substantial funding  e. g. , basic data collection for any progress to be made.

Specific Research Issues The travel cost model developed in the project raises as many research questions as it answers. The main answer is that the model can be used to estimate the benefits of water quality improvements in a way ~ sistent with economic theory. * However, many problems were encountered on the way to answering this fundamental question. For example, in the survey data used to estimate the travel cost model, as in many surveys involving noneconomic data, the data were heaped at specific points, possibly presenting problems for ordinary least squares regression analysis. Specifically, all visitors who made only one visit to a site were heaped at the zero point for the logarithmic transformation of the dependent variable , while the visitors who made the maximum were heaped at the other end point. The maximum is the value ( 8) assigned to the open interval for five or more visits. The remaining visitors were arrayed at specific intervals in between. The need, obviously, is for a statistical estimator that can handle this problem. I n terms of the absolute magnitude of the estimated values, which is important for estimating benefits, the differences may be small, but this is a fundamental question requiring statistical analysis rather than judgment. Equally important, the fact that all respondents have used the site at least once implies that this study fails to consider the demands of individuals whose maximum willingness to pay falls below their travel cost. This truncation can, as suggested in the report, lead to biased estimates of * This is one of the items on Freeman's [ 1979a] research agenda cited earlier.

1 13 !

site demands. It is important to evaluate the implications of amending the statistical models to directly account for these effects for the benefit estimates derived for water quality improvements.

Many of the items on the travel cost research agenda stem from limited data. This project used the 1977 Outdoor Recreation Survey's Federal Estate component, which surveyed visitors at various recreation sites on Federal lands. Although in many ways these data are far better than those in earlier survey efforts, they omit many items important for the travel cost model. For example, there were no questions on substitute sites that respondents had considered or even visited at other times before visiting a particular site. While the generalized model assumes that site attributes are capable of reflecting substitution potential, the model would be considerably improved if it had a better measure of substitutes.

The travel cost model also assumed that the sole purpose of an individual's trip was to visit a particular site. However, Haspel and Johnson [ 1982] point out the potential for overstating benefits when there are multiple purposes for a trip, suggesting the need for more research using itinerary information to assess the importance of multipurpose trips. Also needed for the travel cost model are more data on the types of time allocations the individual considered in making the trip. For example, was work time forgone or compulsory vacation time? Each may have a different opportunity cost. With answers to these questions, it will be possible to improve the calculation of an individual's time costs for recreation.

Including site attributes in the travel cost model created several datarelated questions. Specifically, because water quality data from the standard storage system ( STORET) were inadequate for many recreation sites, observations were missing on key parameters , and the monitoring station information was frequently unreliable. Clearly, more comprehensive data are needed, especially for water quality parameters relevant to recreation activities. Data on other site attributes such as access or size were available for the U . S. Army Corps of Engineers' sites through the Corps' Resource Management System. However, to apply the model to other recreation sites e. g. , sites managed by the U. S. Forest Service would require similar information on important site attributes. Present! y, such data are not readily available.

The future research agenda for the contingent valuation approach is aimed at a more systematic treatment of issues involving the design of the hypothetical market. The research questions are in the general area that economists have termed " framing the question" ( see Brookshire, Cummings, et al. [ 1982] ) an area generally called " context" in the psychological literature The definition of the commodity to be valued, the question format used to elicit the value, the ordering of various valuation and nonvaluation questions the means of payment in the market, and the information provided in the survey questionnaire are all important elements in this framing process. More attention to these issues is likely to substantially improve the understanding of the approach and provide results that are easier to interpret.

1 14 This project addressed several general contingent valuation issues by comparing several question formats  bidding games with two starting points,

direct question, and the unachored payment card  both to each other and to results from the contingent ranking format. Different payment cards, such as the anchored card USed bY Mitchell and Carson [ 1981 1, were not compared. In addition, the contingent ranking format was always used in conjunction with another question format, which limits the independence of the conclusions. Both of these are good candidates for future research.

This survey was conducted in a specific river basin, making the orientation more micro in scope than Mitchell and Carson's [ 1981]. A more systematic comparison of their results for overall national water quality and the results of this study for the Monongahela River basin may be useful. Moreover, the general framin9 questions are especially relevant to the macro approach, where it is more difficult to define the hypothetical commodity. if policy decisions require basin specific results , either specific surveys ( or the ability to transfer results between basins) or the ability to infer estimates for specific river basins from the macro approach will be required.

Recently, Brookshire, Cummings, et al. [ 1982] introduced the ideas of environmental accounts and budget constraints as part of the framing issue. The accounts question aims at determining whether people give an overall environmental quality bid in a survey or a bid for the specific hypothetical commodity. The budget constraint requires that individuals provide rough budget shares for their monthly incomes and then reallocate these categories to provide the budget amount for the hypothetical commodity. The preliminary results in Brookshire, Cummings, et al. [ 1982] suggest this is a useful avenue for learning more about framing influences.

Finally, improving efficiency in defining hypothetical markets is a neglected area in the contingent valuation literature. One promising approach is the use of focus groups ( from market research literature) to obtain impressions about terminology, visual aids, and other framing issues. Applying these marketing research ideas to contingent valuation may indicate their overall merits.

Research agendas must continually evolve, producing new avenues from deadends that once offered promise. The present agenda tries to map some of these new avenues. The passage of time and the fruits of future research will mark its ultimate usefulness.

1.4 GUIDE TO THE REPORT This chapter has introduced the report by highlighting the project object i v e s a n d s u m m a r i z i n g t h e f i n d i n g s o f t h e r e s e a r c h . Chapter 2 provides a brief review of some of the theoretical issues of comparing alternative benefit estimation approaches. After describing the Monongahela River basin, Chapter 3 summarizes the sampling and survey plans for the contingent valuation and contingent ranking approaches used in the case study. Chapter 4 builds on the contingent valuation foundation laid in Chapter 3 by presenting the research design for the contingent valuation survey, by profiling key groups of respondents , and by summarizing the empirical option price results, includ

1 15 ing the effects of question format, starting point, and interviewer bias. Chapter 5 synthesizes the theoretical underpinnings of option value, giving particular attention to the role of supply uncertainty, and presents empirical results for both option and existence values. Chapter 6 reviews the theory underlying the contingent ranking approach, provides a critical summary of its previous applications, considers appropriate measures of benefits, and summarizes the empirical findings from its application to the Monongahela River basin. Chapter 7 presents the development of a generalized travel cost model and describes its application to predict the recreation benefits of water quality improvements in the Monongahela River. The development of the model treats the empirical significance of model specification, site time costs, simultaneity in visit/ site time decisions, and statistical biases in its predicted values. Chapter 8 compares the alternative approaches for estimating recreation and related benefits, in light not only of previous comparison attempts but also of g priori expectations. In addition, Chapter 8 also describes paired comparisons of the contingent valuation and travel cost approaches and of the contin  gent valuation and contingent ranking approaches using multivariate regression techniques.

1 16 CHAPTER 2 A BRIEF REVIEW OF THE CONCEPTUAL BASIS FOR THE BENEFIT ESTIMATION APPROACHES 2.1 INTRODUCTION An ideal comparison of benefit estimation approaches would begin with a detailed theoretical appraisal of each approach, showing how each is derived from a common conceptual framework. However, this kind of appraisal is beyond the scope of this project. Instead, this chapter highlights the assumptions information, and types of benefits measured by each of three approaches and compares these features on general, rather than on common, theoretical grounds.

The definition of economic benefits based on theoretical welfare economics has closely followed the model of consumer behavior, which suggests that individuals can acquire utility only through consuming goods or services. This framework leads to definitions of economic benefits best suited for describing user benefits associated with improvements in environmental quality. However, since the work of Krutilla [ 1967], nonuser, or intrinsic, benefits have been increasingly recognized as playing an important role in the aggregate values for certain environmental resources.

Intrinsic benefits are generally viewed as arising from two sources. The first source suggests that an individual can realize utility without direct consumption of a good or service. Rather, other motives can be satisfied with allocation patterns for certain resources, and these motives " stewardship" and " vicarious consumption" in Freeman's [ 1981 ] terms can lead to utility, therefore providing nonuser benefits. An alternate view can be derived by redefining the act of consumption to admit what might be considered indirect use of the services of an environmental amenity.

The second source of intrinsic benefits is derived by relaxing one of the assumptions underlying conventional consumer behavior models. The simplest treatment of the conditions for efficient resource allocation assumes that all goods and services whether they provide positive increments to utility or decrease it are available with certainty. Of course, this is not the case in the real world. Indeed, in some circumstances e. g. , the degree of reversibility in water quality conditions  uncertainty may well be the most important element of the public policy problem. I n these cases, therefore, consumer behavior models must be amended to reflect how households react to uncertainty and whether they would be willing to pay for action that would reduce i t . e 2 1 A second relevant feature of the definitions of economic benefits presumably arises from the early focus on goods or services exchanged in private markets. These definitions developed measures of benefits for price changes. Since environmental policy has dealt mostly with quantity ( or quality) changes in services provided outside of private markets, these measures must be adapted to meet policy needs.

The purpose of this chapter is to briefly review the theoretical concepts generally used in measuring economic benefits, Specifically, Section 2.2 deals with the theoretical basis of benefit measurement based on the concept of an individual's willingness to pay and describes alternative ways to measure changes in consumer welfare. Section 2.3 outlines the framework for comparing different benefit estimation approaches  an adaptation of the Smith  Krutilla [ 1982] framework for classifying the different approaches and summarizing their conceptual bases. Section 2.4 describes the welfare measurement bases underlying the two benefit estimation approaches compared in this study  travel cost and contingent valuation ( including the contingent ranking format). Finally, Section 2.5 prvides a brief summary.

2.2 A BRIEF REVIEW OF THE CONVENTIONAL THEORY OF BENEFITS MEASUREMENT The primary emphasis for this study of recreation and related benefits of water quality improvements focuses on the measurement of benefits that accrue to individual households. Fortunately, the theory of consumer behavior provides a framework for measuring these benefits. This section briefly reviews this framework to set the stage for the comparison of approaches that follows.

The first guidepost for the definition and measurement of economic benefits that the theory of consumer behavior provides is the individual demand function, shown in Figure 2 1. This function describes for any good, X, the maximum amount an individual would be willing to pay for each quantity of X. The downward slope of the curve indicates that individuals are willing to buy more of X at lower prices than they are at higher prices. The simple twodimensional diagram in Figure 2 1 assumes all other factors that might influence demand  income, the prices of related goods, etc.  do not change. Thus, according to the demand function, if the market leads to a price of P o, the individual will purchase Q. of X and make a total expenditure equal to POAQOO. Since the demand curve measures the individual's maximum willingness to pay for each level of consumption, the total willingness to pay for Q. can be derived total expenditures ~ the triangle PoPiA. This difference between the amount they are willing to pay and what individuals actually pay with a constant price per unit is defined as the consumer surplus the conventional dollar measure of the satisfaction individuals derive from consuming a good or service, exclusive of what they pay for it.

As a dol~ r measure of individual welfare, however, consumer surplus is not ideal. The most direct way of understanding its limitations is to consider 2  2 Price ($/ unit) t Quantity/ time Figure 2 1. The demand function and the consumer surplus welfare measure,

the measurements underlying a conventional demand function. An individual's demand function describes the maximum an individual with a given nominal income would be willing to pay for each level of consumption of a particular good . Specifically, if the price paid changes, it will affect not only what the individual can purchase of this good, but also the purchases of all other commodities through its effect on the remaining disposable income. Thus, movement along a conventional demand function affects the level of satisfaction an individual will be able to achieve with a given income. For example, suppose the price of hypothetical good X declines to P 1 . The individual can purchase the same quantity of X at its new price as indicated in Figure 2 1 by the area OPIBQO and have income remaining, as given by PIPOAB, to purchase more X or more of other goods and services. The movement to a consumption level of OQ1 describes the increased selection of X under the new price. This change leads to a higher utility level because more goods and services can be consumed with the same income. For consumer surplus to provide an " ideal" dollar measure of individual well being, however, the conversion between dollars and individual utility levels must be constant for every point on the demand curve. According to this example, then , each point on a conventional demand function in principle corresponds to a different level of utility. Thus, no single conversion factor links consumer surplus and utility.

In his seminal work on consumer demand theory, Hicks [ 1943] noted that an ideal measure would require that utility be held constant at all points along the demand curve. As a practical matter, however, the difference between the area under such an ideal, Hicksian based demand curve and that under a conventional demand curve depends on the size of the income effects accompanying the price changes associated with movements along the ordinary demand curve. As suggested earlier, price reductions lead to more disposable income. To judge the association between the two measures of welfare change, all = pects of the choice process that affect the size of the change in disposable income must be considered. For example, if the price change for X is small and the share of the budget spent on the good X is also small, the 2  3 r., .~!

change in disposable income is likely to be small. Thus, little difference will exist between the ordinary measure of consumer surplus and the measure derived from Hicks' idealized demand curve. However, the same outcome arises either if income has littIe effect on the demand for X or if an individual's preferences are such that the demand responsiveness to income is equal for all goods ( i. e., unitary income elasticities of demand).

Of course, each of the conditions described above is a special case. When ordinary demand functions are used to measure the benefits of an action in practical applications, the factors influencing the demand function's relationship to an ideal dollar measure of welfare change must be identified. ., Fortu  nately, Will ig [ 1976] and Randall and Stoll [ 1980] have derived such guidelines for cases involving price and quantity changes, respectively. To understand these guidelines, the possible theoretical measures of individual welfare change must first be defined in more precise terms.

Hicks' [ 1943] theoretical analysis of measures of welfare change provides the basis for developing a set of rigorous measures and, with them, the error bounds for ordinary consumer surplus. The four Hicksian welfare measures for a price decrease are summarized below:

. Compensating variation ( CV) is the amount of compensation that must be taken from an individual to leave him at the same level of satisfaction as before the change.

l Equivalent variation ( EV) is the amount of compensation that must be given to an individual, in the absence of the change, to enable him to realize the same level of satisfaction he would have with the price change.

. Compensating Q surplus ( CS) is the amount of compensation that must be taken from an individual, leaving him just as well off as before the change if he were constrain cd to buy at the new price the quantity of the commodity he would buy in the absence of compensation.

l Equivalent surplus ( ES) is the amount of compensation that must be given to an individual , in the absence of the change, to make him as well off as he would be with the change if he were constrained to buy at the old price the quantity of the commodity he would actually buy with the new price in the absence of compensation

As a simplified comparison, Figure 2 2 highlights the essential differences between the Hicksian variation measures and the ordinary consumer surplus measures when the price of a good decreases. The two Hicksian demand c u r v e s hold ing utility constant ( at levels U. and U 1 with U 1 > Uo) are shown a s H( uo) and H( U 1), the prechange and postchange Ieveis of utilitY/ respect i v e l y . The ordinary demand curve also known as the Marshal lian demand curve  is shown as D, where income, and not utility, is held constant. Ths 2  4 Qumltity H( U1) NOTE: D  ordinary dommd curve H( IJO), H( U1)  Hidcsian dmand ww. s Figure 2 2. A comparison of alternative welfare measures.

compensating variation measure, labeled as area a, uses the original level of utility as its reference point and indicates the amount of compensation that must be taken from an individual to leave him at the original level of utility when the price changes from P. to PI. The equivalent variation measure is represented by area a+ b+ c. It measures the change in income equivalent to the change in prices and thereby permits an individual to realize the new level of utility with old price P o . The change in ordinary consumer surplus is the area under the ordinary demand curve, D, between P. and PI. In Figure 2 2 it is shown as areas a+ b.

The concepts of compensating surplus and equivalent surplus were originally defined as measures of the welfare change resulting from a price change, given that the quantity of the good whose price has changed is not allowed to adjust. However, it is also possible to interpret these concepts as measures of the welfare change associated with a quantity change ( see Randall and Stoll [ 1980] ). Just, Hueth, and Schmitz [ 1982] have recently offered a diagrammatic illustration of compensating and equivalent surplus in a format similar to that used above to describe compensating and equivalent variation. However, in the present example, the price is assumed constant at some arbitrarily low value ( effectively zero for Figure 2 3), and D is interpreted as an ordinary demand curve ( i. e., as if the quantities consumed could be realized only at the corresponding prices and not the constant price). In Figure 2 3 a change in the quantity of the good available from Q. to Q 1 leads to a compensating surplus of c+ f and an equivalent surplus of a+ e+ c+ d+ f+ g. The ordinary consumer surplus is c+ d+ f+ g, which is d+ g more than the compensating surplus measure and a+ e less than the equivalent surplus.

2  5 Priti PO b c P,

f \ H( lfo)

`% al * Quantity . Sowco: Just, Hucth, and % hmitz [ 1982].

Nota: Ordinary consumer turplus  c + d + f + g Compmmting wrplus = c + f Equivalent surplus = a + e + d + c + f + g Figure 2 3, Surplus measures for a change in quantity.

Table 2 1 relates the welfare measures under different conditions of willingness to pay/ accept, showing quite clearly that no one unique measure exists. Rather, the appropriate measure is determined by the particular situation Table 2 1 reinforces this point by presenting the types of welfare measure in relation to different situations. For a price decrease, for example, the following relationship holds between the alternative welfare measures:

ES> EV> CV> CS.

For a quantity increase, the equivalent surplus measure will be greater than the compensating surplus measure. The primary reason for the differences between welfare measures is that the equivalent surplus and equivalent variation are not bounded by' an individual's income constraint, while the compensating variation and compensating surplus measures are. It should also be noted that the measures are symmetrical and that, for a price increase or quantity decrease the relationship between the measures is exactly the reverse.

It is important to recognize that the compensating and equivalent measures of welfare changes differ because they imply a different assignment of property rights to the individual and therefore are based on different corresponding f rame~ of reference. For example, with a price decrease, the compensating variation measure takes the initial price set as an individual's frame of reference and asks, in effect, " What is the maximum amount he would be willing to pay to have access to the lower prices?" By contrast, equivalent variation takes the new, lower price set as an individual's frame of reference and 2  6 Table 2 1. Alternative Welfare Measures and Types of Consumer Surplus Measures for Contingent Valuation Studies Price Price Quantity Quantity decrease increase increase decrease WT P C v ; Cs EV; ES Cs ES WTA EV; ES Cv; Cs ES Cs NOTE:

Cs is the amount of compensation that must be taken from an individual, leaving him just as well off as before the change if he were constrained to buy at the new price the quantity of the commodity he would buy in the absence of compensation.

Cv is the amount of compensation that must be taken from an individual to leave him at the same level of satisfaction as before the change.

ES is the amount of compensation that must be given to an individual, in the absence of the change, to make him as well off as he would be with the change if he were constrained to buy at the old price the quantity of the commodity he would buy in the absence of compensation.

EV is the amount of compensation that must be given to an individual, in the absence of the change, to enable him to realize the same level of satisfaction he would have with the price change.

WTA is the amount of money that would have to be paid to an individual to forego the change and leave him as well off as if the change occurred.

WTP is the amount of money an individual will pay to obtain the change and still be as well off as before.

describes the minimum amount an individual would be willing to accept to relinquish his right to the lower price. These measures bound the range of dollar values for the welfare changes because they describe the results obtained from the perspectives of the initial utility level and the final utility level. Consequently Willig [ 1976] uses this feature to establish conditions under which conventional consumer surplus would approximate " ideal" measures for the welfare change associated with a price change. Moreover, Randall and Stoll [ 1980] follow essentially the same logic to gauge the relationship between ordinary consumer surplus measures for a quantity change and the corresponding compensating and equivalent surplus measures.

Equations ( 2.1 ) and ( 2.2) provide the basis for the Willig bounds for the difference between the ordinary consumer surplus measure and the equivalent 2 7 variation and compensating variation measures of a change in welfare due to a price change: *

C v  OCS ~ IOCSI N IOCSI  2 M `

OCS  EV ~ ! OCSI N , IOCSI  2 M ( 2 . 1 )

( 2 . 2 )

where O c s = ordinary consumer surplus measure of welfare change N = income elasticity of demand = 4/ y Q M = initial level of income.

These relationships can be evaluated at different values for ticity of demand over the region for the price change a n d the income elasthereby ~ rovide bounds for the magnitude of ~ he discrepanc y between ` ordinary consumer surplus and the equivalent and compensating variation welfare measures. Equations ( 2.1) and ( 2.2) assume that the income elasticity of demand ( N) is approximately constant over the region for the price change ( see Willig [ 1976], pp. 592 593, for a discussion). If this assumption is relaxed, the bounds can be stated as inequalities for the percentage difference between ordinary consumer surplus and the corresponding measures of welfare, as in Equations ( 2.3) and ( 2.4):

IOCSI ` s ~ cv  OCS ~ Iocst ` L ,

2M  IOCSI  2 M ( 2 . 3 )

( 2 . 4 )

where ` s = the smallest value of the income elasticity of demand over the region for the price change * lt is important to note that the direction of the price change affects the sign of ordinary consumer surplus, compensating variation, and equivalent variation and, thus, the interpretation of Equations ( 2.1) through ( 2.4). This formulation " adopts Willig's convention that ordinary consumer surplus is posi  tive for a price increase and negative for a price decrease so that it corresponds to the interpretation of compensating variation or equivalent variation. ~

See Willig [ 1976], p. 589. ` L = the largest value of the income elasticity of demand over the region for the price change.

The Willig approximation is reasonable if the value of $%&. S ~.~~ If t h i s .

value is greater than 0.05, Willig has provided a table of error bounds based on the relationships used to derive these approximate bounds. *

2.3 A FRAMEWORK FOR COMpARING ALTERNATIVE BENEFIT MEASUREMENT APPROACHES Comparing alternative approaches for estimating the recreation and related benefits of water quality improvements at first seems formidable because of the wide range of consumer behavior outcomes described by each. However, despite this diversity, all approaches adhere to a consistent general model of consumer behavior: individuals allocate their monetary and time resources to maximize their utility subject to budget and time constraints. As noted at the outset, a complete comparison of the methods could derive each method from this common conceptual basis. However, this section simply provides a taxonomic framework that eases the comparison of approaches by drawing clear distinctions between the assumptions underlying each.

Figure 2 4 presents the Smith Krutilla [ 1982] framework for classifying the alternative approaches for measuring the recreation and related benefits of water quality improvements. This framework considers I inkages between changes in water quality and observable actions of economic agents that affect the information available for measuring water quality benefits. In particular, Smith and Krutilla suggest that all approaches for measuring the benefits of a change in an environmental resource can be classified as involving either physical or behavioral assumptions.

The category associated with physical assumptions in this framework maintains that the association between the environmental service of interest ( i. e. , water quality) and the observable activities ( or changes in goods or services) is a purely physical relationship. The responses are determined by either engineering or technological relationships. Thus, the evaluation of water quality changes in such a framework must begin by identifying the activities affected by water quality. Analysis must then focus on measuring the technical relationships, sometimes referred to as damage functions, assumed to exist between water quality and each activity. Because water quality improvements can be associated with the support of gamefish, swimming, and the use of water for human consumption, the physical approach seeks to specify the technical linkages between water quality levels and permitted amounts of recreation fishing, swimming, and water consumption. Another example of the * Two excellent discussions of the practical implications of the Willig bounds for benefit measurement are available in Freeman [ 1979a], pp. 47 50, and in Just, Hueth, and Schmitz [ 1982], pp. 97 103.

2  9 No Role for Behavioral Responses of Economic Agents Behavioral Responses of Economic Agents Are Essential Types of Linkega Between Water Ouality Change and Observed Effects Typas of Assumptions Measurement Raqui Approachaa I Responses are Physical determined by I I Linkages I engineering or I Damage Function " technological" I Behavioral Linkages Indirect Links Restrictions on the nature of individual preferences OR obaawad technical associations in the dolivary of goods or services Hedonic Proparty Value Travel Cost"

Figure 2 4. Smith Krutilla framework for classifying the measurement bases and approaches of economic benefits resulting from improved water quality.

physical approach to evaluating the effects ( and, ultimately, the benefits) of a water quality change can be found in the dose response models used to evaluate the health risks associated with certain forms of water pollution ( see Page, Harris, a n d Bruser [ 1981] for a review of these models). Although these models ignore economic behavior and postulate that the relationships involved can be treated independently of the motivations of economic agents, they may well provide reasonable approximations of the actual effects on water quality for certain classes of impacts. However, these models are unlikely to be adequate when economic agents can adjust their behavior in response to the water quality changes and, as a result , are not considered in this study.

The behavioral category of valuation methodologies in the Smith Krutilla framework relies on the observed responses of economic agents and on a model describing their motivations to estimate the values ( or economic benefits) associated with a change in a nonmarketed good or service. Within this class, direct or indirect links identify three classes of assumptions that can be used to develop measures of individual willingness to pay. T h e f i r s t t y p e o f assumption used  within the indirect behavioral framework requires restrictions on the nature of the individual's utility function and is usually associated with Maler's [ 1974] weak complementarily. This type of assumption maintains that an individual's utility function is such that there is a specific a s s o c i a t i o n between the nonmarketed good ( or service) and some marketed commodity such 2 lC that the mar9inal utilitY of an increment to the consumption of the nonmarketed good is zero when the individual is not consuming some positive amount of the associated, marketed commodity. This assumption maintains that a type of lljOintrleSS1l exists in the formation of the individual's utility, which, in turn, constrains the feas~ ble resPonses to Price changes for the marketed good ( or changes In the . av. allability of the nonmarketed good). Thus, the selection of the two 9oods IS loint~ and market transactions for one good can be used to determine demand for the other. Of course, this approach depends upon the plausibility of the restriction on an individual's utility function. Researchers have used this restriction to justify both hedonic property value and travel cost studies.

Smith and Krutilla [ 1982] argue that the weak complementarily behavioral restriction is .~ necessary for these approaches and that the observed technical associations between marketed and nonmarketed goods are responsible for the abi Iity to use these methods to measure benefits of changes in a nonmarketed good. In the case of the technical assumptions, the availability of the nonmarketed service is tied to some marketed good by the nature of its natural delivery system, making the linkage an observable phenomenon rather than a feature of an individual's preferences. For example, water based outdoor recreation is undertaken using the services of recreation sites on rivers or lakes. Each recreationist is interested in the water qualities only at the sites considered for his recreation use. By selecting a site for these activities, an individual is also selecting a water quality, because the two are " technically linked" or jointly supplied. Thus, where there is a range of choice ( i. e., several different combinations of recreation sites and water quality), how an individual values the nonmarketed good or service can be seen through his observable actions, including such decisions as the selection of a residential location or visits to specific recreation facilities ( see Rosen [ 1974] and Freeman [ 1979c] ). This study specifically considers the travel cost method, which uses this technical association as its basis for measuring water quality benefits.

The last case of behavioral approaches to benefit estimation involves direct linkages between water quality and an individual's actions. The assumptions made to ensure these linkages are labeled institutional, a designation somewhat more difficult to understand than previous descriptions because it encompasses the contingent valuation and contingent ranking methods for measuring an individual's valuation of environmental amenities. Specifically, the institutional assumptions arise because the analyst assumes that individual responses to hypothetical decisions ( or transactions) are completely comparable to individual responses revealed in actual transactions. The term institutional is used for this class because the organized markets in which goods and services are exchanged are institutions that provide the information on individuals' marginal valuations of the commodity involved. With the survey approach, the interviewer poses the survey questions to construct an equivalent institutional mechanism in the form of a hypothetical market. Both the contingent valuation and the contingent ranking methods will be considered under this approach.

2 11 2.4 THE NATURE OF THE BENEFITS MEASURED IN THE ALTERNATIVE APPROACHES This section highlights the nature of the benefits measured in the travel cost and contingent valuation approaches.

2.4.1 Travel Cost Appreach The travel cost approach measures the change in ordinary consumer surplus for a water quality improvement, represented for an individual incurring travel costs per trip of OPI by area ABCD in Figure 2 5. To empirically develop the ordinary consumer surplus estimate, the travel cost approach assumes both that travel to a recreation site reveals a respondent's reservation price for that site's services and that water quality is jointly supplied along with the other site attributes. If other variables are held constant, and if sites are placed on a common measurement scale, * area ABCD can be measured by observing individuals' site selections across sites with varying levels of water quality, thus revealing the effect of water quality on site demand. Therefore, while both Freeman [ 1979b] and Feenberg and Mills [ 1980] maintain that conventional travel cost models cannot measure benefits associated with water quality change, ? the generalized travel cost model developed for this Travel costs ($/ ox)

I PI o B c Qx/ t ( visits/ year)

Figure 2 5. Travel cost demand function with water quality improvement.

x~ he rat~ onale in Section 7.3.

~ Their models quality change. for this measurement approach is presented in more detail do not gauge the demand change that accompanies a water 2 12 study ( see Cha Pter 7) uses the resPonses of individuals at different locations to both travel cost and water quality levels to infer benefits of water quality changes. The information provided by these responses allows the change from D( WQI) to D( WQ2) in Figure 2 5 to be distinguished ( where WQI a n d W Q 2 represent different levels of water quality, with WQ2 > WQI).

2.4.2 Contingent Valuation Ap preach The contingent valuation approach directly measures an individual's willingness to pay for water quality in an institutional arrangement that approximates the market for water quality. Unlike the travel cost approach, contingent valuation does not require observations of individuals' decisions on use of recreation sites with given " implicit" service prices, but it does assume an individual's response in the hypothetical market is the same as it would be in a real market. That is, respondents are assumed not to behave strategically, not to give unrealistic responses, and not to be influenced by the survey questionnaire or the interviewer who administers the survey questionnaire. Furthermore, the contingent valuation approach imposes an institution that leads to a hypothetical change in an individual's budget constraint by requiring that the individual " pay" for the specified water quality improvement. Thus, the new budget constraint for the utility maximization process includes both the prices and quantities of market goods and the hypothetical price and defined quantity of water quality.

The institutional design underlying contingent valuation surveys requires that ownership of the property rights for water quality at the recreation site be determined in the specification of the question, thus affecting the appropriate measure of consumer welfare. Specifically, consumer ownership of property rights would indicate a willingness to accept measure as the appropriate valuation concept, and industry ownership would dictate a willingnessto pay measure. Although currently boatable throughout, the Monongahela River the site used for this study ( see Chapter 3) supports swimming and fishing only upriver from Pittsburgh, and property rights are in a state of flux with considerable confusion over ownership ( see Feenburg and Mills [ 1980]). Thus, a reasonable allocation for this study's survey of Pittsburgh residents is that consumers own the rights to beatable water ( which suggests an equivalent surplus measure), while no one yet owns the rights to fishable, swimmable water along the entire river ( which indicates a compensating surplus measure).

While using a willingness to accept measure for maintaining a boatable water quality level and a willingness to pay measure for the value of moving to fishable and swimmable levels is consistent with current Monongahela property rights, willingness to accept measures have proven difficult in hypothetical market experiments, thus creating serious problems in the development of a workable survey methodology. For example, respondents have either refused to answer, given infinite bids, or refused to accept any compensation f o r r e d u c t i o n s i n e n v i r o n m e n t a l q u a l i t y [ Schulze, d'Arge, and Brookshire [ 1981 ] and Bishop and Heberlein, 1979]. To cope with this problem, this study employs a willingness to pay ( equivalent surplus) measure for the decrease from boatable water quality and a compensating surplus measure for improvements from the same level.

2 13 2.4.3 Continent Ranking Approach Like the other contingent valuation formats , contingent ranking relies on ~ individuals' responses in a hypothetical market situation. However, instead of requiring an individual to respond with the maximum willingness to pay for a water qtiality improvement, contingent outcomes  consisting of a hypothetical water quality from most preferred to underlying contingent ranking is that to the hypothetical market when both maximization framework underlying the ranking requires tha~ individuals rank p a y m e n t a n d a c o r r e s p o n d i n g l e v e l o f ` least preferred. T h e i m p l i c i t a r g u m e n t an individual is better able to respond outcomes are specified. In the utility " contingent ranking approach, an indi  vidual ranks the alternatives based on their implications for his ability to maximize utility with a given income, the prices of other goods, and the proposed combination of payment and water quality. Analytically, this choice can be described by comparisons of the indirect utility functions arising from each of these sets of decisions. An appropriate compensating surplus measure can then be derived from estimates of the indirect utility function.

2.5 Summary Partly because they are all based utility maximization, the travel cost, r a n k i n g ap~ roaches can each develoD on the common standard of constrained contingent valuation, and contingent measurements of changes in consumer welfare. The travel cost approach measures the change in ordinary consumer surplus, the contingent valuation approach measures equivalent and compensating surpluses, and the contingent ranking format yields a compensating surplus welfare measure. * The relationship between each of these methods' measures of the welfare changes associated with water quality changes is considered in the comparison analysis reported in Chapter 8.

* lt should be noted that, for the contingent valuation approaches, questions have b& en formulated to include both user and nonuser values. Strictly ~ speaking, both approaches n) easure the option price, but the contingent valua  ~ tion approach permits the user value component to be identified. ! $

2 14 CHAPTER 3 SURVEY DESIGN 3.1 INTRODUCTION Estimating the recreation and related benefits of water quality improvement with the contingent valuation approach requires an integrated survey design. This chapter describes the survey design for the case study of the Monongahela River. Specifically, Section 3.2 describes the general backg r o u n d o f t h e Monongahe! a R i v e r b a s i n a r e a , Section 3.3 highlights the sampling plan for the project, and Section 3.4, a discussion of the survey plan, concludes the chapter with detailed information on the survey field procedure.

3.2 GENERAL DESCRIPTION OF THE MONONGAHELA RIVER BASIN This section describes the Monongahela River basin, providing a general description of river geography, river uses, river related recreation activities, and a socioeconomic profile.

3.2.1 Geography Formed by the confluence of the West Fork and Tygart Rivers near Fairmont, West Virginia, the Monongahela River drains an area of 7,386 square miles in southwest Pennsylvania, northern West Virginia, and northwest Maryland. ( See Figure 3 1 for a map of the area. ) It flows northerly 128 miles to Pittsburgh, where it forms the Ohio River headwaters with the Allegheny River, and has two major tributaries, the Youghiogheny and Cheat Rivers. All 128 miles of the Monongahela are navigable year round by motorized commercial traffic.

Characterized by steep banks and rugged terrain, the Monongahela River basin lies in five Pennsylvania Counties ( Allegheny, Greene, Fayette, Westmoreland and Washington) and two West Virginia counties ( Monongalia and Marion ) in the Appalachian Plateau and the Allegheny Mountains. The Monongahela basin currently supports four major reservoirs:

. Deep Creek Reservoir A privately owned Maryland facility operated on a Youghiogheny River tributary to generate 51 megawatts of electric power.

. Lake Lynn Reservoir A privately owned West Virginia facility operated on the Cheat River to produce 19 megawatts of electric power.

3 1 t 3>' ______ i      .,//' W81un ~

I it%%!! P7 1:  1

\/'

Figure 3 1. Map of Monongahela River and other area recreation sites.

. Tygart River Reservoir A facility operated by the U. S. Army Corps of Engineers to provide flood control, recreation, and low flow augmentation. This reservoir provides most of the Monongahela's augmented flow, a minimum of 340 cfs in the upper river.

. Youghiogheny River Reservoir A facility operated by the U. S. Army Corps of Engineers to provide a minimum flow of 200 cfs for the Monongahela River.

Comprising nearly 30 percent of the river basin's seven county area, the following urban areas and boroughs ( listed below with 1970 census population) line the Monongahela's banks:

Pittsburgh McKeesport Clairten Duquesne Monessen Monongahela Morgantown Fairmont 520,117 37,977 15,051 11,410 17,216 7,113 29,431 26,093 Donora Charleroi Brownsville Braddock Glassport Munhall Port Vue West Miff in 8,825 6,723 4,856 8,795 7,450 16,574 5,862 28,070 3 2 3.2.2 Uses As part of the Mississippi River Waterway System, the Monongahela has a 9 foot deep navigation channel from Pittsburgh to Fairmont to support both commercial and recreation river traffic. This navigation channel ranges in width from a minimum of 25~ feet to nearly full river width at the river's mouth and is currently maintained by a series of nine lock and dam structu res. The heaviest barge traffic occurs at Structures 2 and 3. Use of the locks and dams for generating hydroelectric power is currently under consideration and would provide an estimated total capacity of 96.2 megawatts. To support river traffic, the Monongahela's banks have a boat dock concentration approaching one dock per mile. However, these docks  which numbered 147 in 1979 are mostly single purpose, single user facilities.

Industrial activity along the Monongahela is dominated by the primary metals industry, which accounts for over 31 percent of the area's total manufacturing employment, including 29 percent of all Pennsylvania's steel industry employment. Also important with respect to industrial activity along the Monongahela are significant amounts of natural resources, including oil and gas, limestone, sandstone, sand and gravel, and coal. are estimated at approximately 23 billion tons, and the region alone accounted for 24 percent of total 1977 Pennsylvania and West Virginia. Underground mining in 78 percent of this total, with strip mining operations remainder.

3.2.3 Recreation Area coal reserves Monongahela R i v e r coal production in the area produced accounting for the Because it essentially is a series of large pools ranging from 400 to 1,741 surface acres created by its nine lock and dam structures, the Monongahela offers substantial opportunities for recreation. I n fact, although the lower 20 river miles, subjected to heavy industrial and urban development, offer limited recreation opportunities, the remaining 108 miles have seen dramatic increases in recreation usage over the last 10 years, partially because of improved water quality. As a result of this increased recreation usage, numerous public and private facilities have been developed along the Monongahela, ranging from single lane boat launching ramps to boat club docks, commercial marinas, and community parks.

The primary recreation activities along the river are power boating and fishing. Because power boating is more popular, many recreation facilities have been constructed primarily to serve it. Partially as a result, the Monongahela River comprises a substantial portion of the water acreage available in the region for unlimited horsepower boating.

Although it is second to power boating in popularity, fishing occurs over a greater number of water acres in the area when small lakes and streams are considered. I n fact, fishing accounts for approximately 12 percent of all current uses of the Monongahela. Fishing in the river is encouraged by special programs in both Pennsylvania and West Virginia to stock warmwater fish, and fish sampling has revealed the presence of up to 47 separate species,

3  3 plus 3 hybrids. Of special interest, the U. S. Environmental Protection Agency ( EPA) and the Pennsylvania Fish Commission, which have monitored fish population trends in the Monongahela since 1967, have reported a dramatic increase over an Ii year period in species' diversity and biomass, particularly in the upper reach.

In addition to power boating and fishing, the Monongahela also offers other recreation opportunities at several major facilities, including two constructed by the U . S. Army Corps of Engineers at the Maxwell and Opekiska pools; the Tenmile Creek Recreational Area ( adjacent to the Maxwell Pool), which showed increased visitor days from 1972 to 1975; and the Prikett Bay Recreational Area ( at Opekiska Pool), which has also experienced increased visitation from 1972 to 1975. Recreation activities offered by these sites include picnicking, camping, boating, and swimming. Despite its length and general popularity for recreation, t h e Monongahela nowhere offers either campgrounds or State parks for potential recreational ists, who are forced to the substitute sites offered by the Youghiogheny River Reservoir and the Allegheny River. Both of these substitutes offer better water quality than the Monongahela and, perhaps, more scenic settings for recreation.

3.2.4 Socioeconomic Profile In 1977, population for the seven county area of the Monongahela River basin totaled 2,417,885, which results in an average population density of 518 persons per square mile. Although density is greatest along the river, there is a recent trend to move into other areas. However, population changes in the basin vary according to State: several Pennsylvania counties have experienced a noticeable population decrease in the period from 1960 to 1977, but Monongalia County in West Virginia experienced a dramatic population increase during the same period. in general, the basin has a greater percentage of urban population than either the Pennsylvania or West Virginia State averages.

Per capita income within the basin is Iuwer than either the Pennsylvania or West Virginia State averages, and the basin in fact contains a higher percentage of persons living below the poverty level than does either State generally. Not surprisingly, then, much of the basin's housing stock is generally Considered substandard, and, in 1970, 70 percent of it was more than 25 years old.

The average education level, which has steadily increased since 1950, is higher in the basin than it is in either Pennsylvania or West Virginia or in the United States generally. However, the difference between the basin and the nation has almost disappeared, eroded by a steadily rising U. S. education level. Another steadily eroding difference between the basin and the nation as a whole is in the percentage of the workforce made up of craftsmen and laborers. Specifically, due primarily to the area's heavy concentration of primary metals and extraction industry, the basin still has a higher concentration of blue collar workers than does the difference has greatly diminished during the last 20 nation generally, but this years. .

3  4   . ,.. . ..   .       . .    . . ._ ,. . . . . .  ,,. 3.3 SAMPLING PLAN The following subsections describe the sampling plan implemented to accomplish the objectives of this study. A single stage, area household sampling design was used to contact approximately 384 sample households in a four county area of southwest Pennsylvania. Appendix A contains additional detaiis of the survey design, sample selection, and weight calculation.

3.3.1 Target Population Five counties comprised the sample area for this study ( outlined in Figure 3 2): Allegeny, Fayette, Greene, Washington, and Westmoreland. These counties were selected because they contain the reach of the Monongahela River within Pennsylvania. The random nature of the sample resulted in no sample segments being chosen in Greene County. The target population consisted of all households in this five county area. Group quarters were not included, and only adult ( persons 18 years and older) household members were eligible for interview. One adult was selected for the interview from each household.

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@ Ptacw of 100,000 or moro inhtiitants l   PIs~ of 50,0@ to 100,000 inhabitants a Central citia of SMSAS with fowor than 50,000 inhabitwrta O pl~ o. g of ~,~ to 50,000 in~ bitin~ o~~. ~~ s Figure 3 2. Geographic location of survey area.

3  5 3.3.2 Sample Selection and Survey Design The design was a single stage, stratified cluster sample. The sampling units ( S US) were noncompact clusters of approximately seven households each. The clusters were developed by partitioning all the block groups ( BGs) and enumeration districts ( EDs) within the five county area into noncompact clusters. The clusters were nonoverlapping and, when aggregated, completely accounted for all of the households in the five county area.

The sampling units were stratified into three disjoint groups: ( 1) Pittsburgh ( 2) not in a place, and ( 3) a place other than Pittsburgh. Fifty one clusters with an average of 7.78 sample housing units ( SHUS) each were selected, yielding 397 SHUS. A roster of all adults was compiled for each SHU. One adult was randomly selected from each SHU for interview.

3.3.3 Sampling Weights The probability structure used to select the SHUS and the adults within each SHU allows calculation of the selection probability for each individual interviewed. The sampling weights, reciprocals of the probability of selec  tion, were then calculated. selected SHUS ( 80.59 percent for the nonresponse.

3.4 SURVEY PLAN T h i s Droiect recauired a Because interviews were response), the sampling detailed survey plan to not obtained from all weights were adjusted enable the successful completion of a full ranae of survey tasks. The following subsections discuss the ` procedures and me~ hods developed to carry out these tasks. The major field tasks were as follows:

. To design and perform a limited local pretest of the survey questionnaire.

l To retain field interviewers.

l To count and list households within the randomly selected area segments. ( Two field supervisors and two interviewers performed this task. )

l To develop a field procedures manual and interviewer training materials.

l To conduct a field interviewer training session.

l To administer the benefits instrument at randomly selected  households within the area segments. ( One questionnaire was to be administered by an in person interview at each sample household. The desired number of interviews to be conducted was 305. )

3  6 l . To develop and implement onsite and off site quality control procedures on the work performed by the field staff.

. To conduct an interviewer debriefing.

. To develop and implement data receipt, data editing, and keypunch procedures for all resultant data.

3.4.1 Questionnaire Design and Limited Local Pretest The design of the benefits questionnaire involved the combined talents of RTI staff knowledgeable in benefits analysis and questionnaire design, the EPA project officer, and selected consultants. Efforts to design the questionnai re centered on satisfying the two primary objectives:

. To collect the data required for analysis . To collect the data in such a way that reliability and validity are enhanced.

In meeting these objectives, the number and types of questions included in the instrument and the format that those questions took were determined by several interrelated factors: Those factors included:

. The precise analytic goals of the survey.

. The adequacy of the project budget to support the data collection required.

. The facility of the interviewers in administering the instrument.

l The tolerance of potential respondents of the time and effort required to answer the questions.

l The ability of respondents to provide the data requested.

Table 3 1 outlines questionnaire development activity. After the data collection was completed and the interviewers debriefed, it was clear that the careful attention given to questionnaire design had reaped substantial rewards. The nuances of the questions and intricate skip patterns made necessary by anticipated responses necessitated a considerable investment of time early in the questionnaire development.

Another factor that had a considerable effect on the overall quality of the instrument was the variety of skills brought to bear on the wording of questions. The economic concepts, of course, resided with the economists. However, the wording of questions was critiqued by survey specialists for sensibility and administrative ease and further reviewed by staff experienced in questionnaire formatting and overall survey methodology. The net effect of these efforts was a questionnaire that was more comprehensible than the economists could have ever produced themselves and more sophisticated than the survey specialists alone would have designed.

3  7 9 Table 3 1. Questionnaire Development Activity Activity Date ( 1982)

Review existing survey work: Resources for the August 5 Future, Inc. ( RFF) ( Mitchell); Colorado State; Wyoming Develop first draft for presentation at workshop August 10 Revise draft for review by EPA project officer, August 17 consultant, and survey specialist Incorporate revisions from review August 20 Review by survey staff August 22 Send revisions to EPA project officer for review by August 24 EPA survey liaison officer Perform limited pretest in Raleigh area August 26 Revise Submit Revise Submit instrument based on pretest August 28 draft instrument to EPA for review September 2 instrument based on additional pretest September 6 Office of Management and Budget October 9 ( OMB) package Incorporate OMB suggestions October 27 OMB approval November 5 After the instrument was developed, it was administered on a limited pretest basis in the Research Triangle Park, North Carolina, area. Further limited pretesting of the instrument was completed in Pittsburgh after the Office of Management and Budget ( OMB) package was submitted for EPA review.

The Research Triangle Park pretest was conducted on people from the Pittsburgh area to detect major faux ~ in the instrument that Triangle area residents could not perceive. Am result of this pretest, several recreation sites were added to the site list, the groups of activities were rearranged, and a better map was developed. Most of the benefits from the pretest came from find? ng' flaws in the logic of the questionnaire. The pretest was especially helpful in determining what subsequent questions were appropriate for zero bidders and for bidders who gave a zero to only certain parts of tho questionnaire.

3  8 t A limited budget prevented extensive pretesting in the target area. I n future surveys this activity should be budgeted. Because of the logical consistency desired across all items in the questionnaire, a pretest in the survey area would reveal potential logical inconsistencies only sample area residerltS could expose via their responses. Researching the river and the sample area was a viable substitute; but a pretest in Pittsburgh would have been a valuable complement.

3.4.2 Retaining Field Supervisors and Hirinq Interviewers The project used two field supervisors experienced in hiring and training interviewers and in managing survey fieldwork to supervise and carry out the count and list task and to recruit the field interviewers who performed the household interviewing task. Because much of the cost of a data collection effort is due to count and list activities and to interviewer recruiting, using off site fieid supervisors made the project's field operations more economical. The survey task leader closely monitored the field supervisors in the countand list and recruiting activities, which were carried out during the week of October 19, 1981.

Project staff and the field supervisors worked together to select the interviewers from among experienced applicants who had previously performed well on similar surveys. Top prospects in the Pittsburgh area were screened by telephone to verify general qualifications, availability, and interest. During the count and list activity, the field supervisors interviewed some of the best qualified applicants in person. Personal and work references were checked before final selections were made. Relevant selection criteria included interest in the objectives of the study, availability of dependable transportation perceived ability to relate well to the sample population of interest, input from personal and work references, and interviewing skills ( e. g. , ability to read questions clearly, to follow instructions, to use nondirectional probes, to record responses accurately and legibly, etc.).

The selected interviewers were nine professionals who had extensive experience in household surveys, focus groups, census work~ and a variety of other interviewing activities. These interviewers performed admirably throughout the data collection process, overcoming inclement weather, a few irate refusals, and an approaching holiday season. This was done with a refreshing enthusiasm and reinforced the confidence of the project team members. The interviewers were aware of all the things that can possibly bias a respondent and were careful to follow the procedures outlined in the manual and covered in the training session. In summary, the importance of using experienced, professional interviewers cannot be overstated.

3.4.3 Counting and Listing of Sample Segments Two field supervisors and two experienced interviewers conducted z!! counting and listing of sample segments. This task involved:

. Locating the segment . Identifying segment boundaries 3 9 . Counting the housing units l Listing all eligible housing units.

The count and list task was completed in 1 week and the materials returned for an in house check and preparation of interviewer assignments. Appendix B shows samples of the results from the count and list activities. Details of how these materials were used by the interviewers are provided in the Field Interviewer's Manual, available from Research Triangle Institute.

3.4.4 Developing Field Manuals and Conducting Interviewer Training Because the interviewers were supervised from the Research Triangle Park during the household interviewing phase, a high degree of administrative organization of field personnel was required for the project. Interviewers were carefully informed of reporting and communications channels, procedures, schedule requirements, documentation of nonresponse, reassignments, quality control techniques, and other operating procedures required to complete the project in a timely, cost effective manner. The Field Interviewer's Manual provided the details of the organization of the field procedures and covered the following topics:

. Purposes and sponsorship of the project . Role of the interviewer . Data collection schedule . Field sampling and locating procedures . Contacting and obtaining cooperation from sample members l Reporting results of attempts to secure interviews . Documentation of nonresponse l Validations, field edits, and other quality control procedures . Disposition of completed cases . Completion of administrative forms ( e. g. , field status reports, reassignment forms, and production and expense reports)

. Communications with central office staff.

In addition to the Field Interviewer's Manual, a series of administrative forms was  developed including a household control form ( see Appendix B), which served the following functions:

. Provide assignment information for the interviewer ( i. e. , sample household address).

3 1o . Provide the interviewer with an introductory statement explaining the survey.

. Provide appropriate household enumeration questions and queries to obtain demographic data on persons in the sample household.

. Provide the interviewer with instructions for selecting a household member to be interviewed.

. Require the interviewer to document all attempted and successful contacts with the sample member.

. Provide an appropriate set of result codes for describing interim and final results for each case.

. Require the interviewer to record certain information required for validation of completed interviews and noninterviews.

The training materials developed for the project included background on benefits analysis and administrative procedures. The Interviewer's Manual and a C O P Y of the questionnaire were sent to the interviewers prior to their classroom training. A specified amount of time was authorized for advance study, and interviewers were expected to read the manual and specifications prior to the training session.

3.4.5 Training Session The extensive experience of the interviewers enabled the project team to focus on the unique aspects of the project and to highlight the technical details of the interviewing procedures. The agenda, shown in Figure 3 3, shows the variety of topics covered in the 2 day session on November 11 and 12, 1981.

I n addition to covering the project objectives, the training session provided an opportunity for personal interaction with the interviewers. The session focused on benefits, EPA water policy, the water pollution basics, and mock interviews with all versions of the questionnaire. The mock interviews included zero bidders, recalcitrant and reluctant bidders, use of the payment card, and procedural problems that might be encountered. The interviewers were reminded not to provide supplemental information but to reread an item as many times as necessary. Each interviewer received a healthy dose of information on benefits methodology and the important policy implications of the project. The participation by the project officer in the training also conveyed the feeling that the interviewers were important to the successful completion of the survey.

3.4.6 Conducting Household Interviews Face to face interviews were conducted between November 13 and December 20, 1981. Conducting the interviews involved a series of interrelated operations, which included taking steps to obtain the desired number 3 11     Field Intewiewer Training Sassion Agenda Study for Estimating Recreation and Related Benefits of Water Quality November 11, 1981 9: 00 a. m. 9: 10 a. m. 9: 15a, m.

9: 45 a. m. 10: 15 a. m. 11: 00 a. m. 11: 15 a. m. 12: OOa. m.  l: OOp. m. l: OOp. m.

1: 30 p. m.

2: 30 p. m.

2: 45 p. m. 3: 00 p. m. 5: 00 p. m.

November 12, 1981 9: 00 a. m.

9: 30 a. m. 10: OOa. m. 10: 30 a. m. 12: OOa. m.  l: 00 p. m. l: OOp. m.

2: 00 p. m. Introduction of RTI staff and field interviewers Review of training agenda Project administrative procedures Break/ picture taking and IDs Explanation of the Benefits Study Overview of field interviewer responsibilities Locating sample housing units Lunch Completing household control form and selecting sample individuals Questionnaire administration Demonstration interview Break Mock interview Version A Adjourn Questions and answers/ discussion of yesterday's session Water pollution: Dimensions of a problem The Benefits Study Mock Interview Version C Lunch Questions and answers Distribution of assignments Adjourn Kirk Pate Kirk Pate Kirk Pate Bill Desvousges Kirk Pate Kirk Pate Kirk Pate Kirk Pate Kirk Pate/ Bill Desvousges Group Kirk Pate/ Bill Desvouages Bill Desvousges Dr. Ann Fisher Group Figure 3 3. Field interviewer training session agenda.

of interviews, instituting interviewer assignment and re~ ortin~ PrOCe dU r eS I making initial household contacts and obtaining cooperation ~ enumerating household members, and administering the instrument.

Initial assignments of cases to interviewers were made on the basis of each interviewer's location and characteristics. Generally, assignments were made on the basis of the interviewer's geographic proximity to the sample segments. That was, of course, a cost effective practice and usually resulted in interviewers sharing some c h a r a c t e r i s t i c s w i t h t h e people to be interviewed

Efforts were made to equalize interviewer workloads; however, individual assignments were made after careful consideration of factors related to the difficulty of the areas assigned to each. Based on an assumed equal distribution of cases per interviewer, the average number of cases initially assigned per interviewer for the 6 week data collection period was 40. Under Number of Cases Assigned, Figure 3 4 shows the final case load for each interviewer after adjustments in the field.

3 12 f. ,

t I Rrl Project 2222 2 F IELO DATA Collection WEEKLY STATUS REPORT ESTINATING BENEFITS OF WATER QUALITK lie, k { 1 6 Dates C o v e r e d : .~ f @_/ A to L/ 4.1 L Oate Report P r e p a r e d : LLl al & .

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Number En. meratxon No I n t e r v i e w of cases A c t i o n Cases i n F i n a l Stat~ s Code+ Fin. 1 S t a t u s Cod.<+ _

FI N., mr Ass, Sned Taken _ P:~ gress 02 04 05 06 07 _ o 8 20 22 23 26 _~._ 26       .