1. Region 1 2. Region 2 3. No Preference Between Regions Percent of Water 50% 50% With Good Quality: Good Good Water Water Quality Quality Source of Animal Industrial Pollution for Wastes Toxic February 2000 74 Lakes and Rivers Wastes  ( If sourceb1= 3 then the survey skips to opennew)  sourceb2 ( Only if sourceb1= 1)  What if the Region 2, the region with industrial toxic waste pollution, had a higher percentage of lakes and rivers with good water quality?

Now which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Percent of Water 50% 50% With Good Quality 65% New Source of Animal Industrial Pollution for Wastes Toxic Lakes and Rivers Wastes  ( If sourceb2= 3 then the survey skips to dbag)  sourceb3 ( Only if sourceb1= 2)  What if the Region 1, the region with animal waste pollution, had a higher percentage of lakes and rivers with good water quality?

Now which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Percent of Water 50% 50% With Good Quality 65% New Source of Animal Industrial Pollution for Wastes Toxic Lakes and Rivers Wastes  ( If sourceb3= 3 then the survey skips to dbsrct)  sourceb4 ( Only if sourceb2= 1)  What if the Region 2, the region with industrial toxic waste pollution, had a higher percentage of lakes and rivers with February 2000 75 good water quality?

Now which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Percent of Water 50% 50% With Good Quality 65% 80% New Source of Animal Industrial Pollution for Wastes Toxic Lakes and Rivers Wastes  ( If sourceb4= 3 then the survey skips to dbag)  sourceb5 ( Only if source2b= 2)  What if the Region 2, the region with industrial toxic waste pollution, had a higher percentage of lakes and rivers with good water quality?

Now which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Percent of Water 50% 50% With Good Quality 65% 60% New Source of Animal Industrial Pollution for Wastes Toxic Lakes and Rivers Wastes  ( If sourceb5= 3 then the survey skips to dbag)  sourceb6 ( Only if source3b= 1)  What if the Region 1, the region with animal waste pollution, had a higher percentage of lakes and rivers with good water quality?

Now which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions February 2000 76 Percent of Water 50% 50% With Good Quality 65% 60% New Source of Animal Industrial Pollution for Wastes Toxic Lakes and Rivers Wastes  ( If sourceb6= 3 then the survey skips to dbsrct)  sourceb7 ( Only if sourceb3= 2)  What if the Region 1, the region with animal waste pollution, had a higher percentage of lakes and rivers with good water quality?

Now which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Percent of Water 50% 50% With Good Quality 65% 80% New Source of Animal Industrial Pollution for Wastes Toxic Lakes and Rivers Wastes  ( If sourceb7= 3 then the survey skips to dbsrct)  sourceb8 ( Only if sourceb4= 1)  What if the Region 2, the region with industrial toxic waste pollution, had a higher percentage of lakes and rivers with good water quality?

Now which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Percent of Water 50% 50% With Good Quality 65% 80% 95% New Source of Animal Industrial Pollution for Wastes Toxic Lakes and Rivers Wastes  February 2000 77 ( If sourceb8= 3 then the survey skips to dbag)  dbsrct2  Your responses to the previous questions show that you place a higher value on reducing toxic chemical pollutants.

We would like to know why.

Do you believe that toxic chemical wastes pose a greater health risk than agricultural wastes?

1. Yes 2. No  ( Subjects who are asked the above question now skip to opennew)  dbag  Your responses to the previous questions show that you place a higher value on reducing animal waste pollutants.

We would like to know why.  dbag2  Your responses to the previous questions show that you place a higher value on reducing animal waste pollutants.

We would like to know why.

Do you believe that animal wastes pose a greater health risk than toxic chemical wastes?

1. Yes 2. No  Open1 ( 1/ 3 of subjects get a range of 50% to 65% Good Water Quality 1/ 3 of subjects get a range of 25% to 40% Good Water Quality 1/ 3 of subjects get a range of 75% to 90% Good Water Quality)  Yes / No Policy Questions Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

The policy would also improve water in a region downstream from February 2000 78 you by 15%, though you do not think you will visit that region.

This policy, through additional taxes, would increase your cost of living by $ 250 per year.

Would you be in favor of this policy?

1. Yes 2. No  Open2 ( Only if Open1= 1)  Let's consider this policy question again Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

The policy would also improve water in a region downstream from you by 15%, though you do not think you will visit that region.

This policy, through additional taxes, would increase your cost of living by $ 350 per year ( rather than $ 250 in the previous question).

Would you be in favor of this policy?

1. Yes 2. No  Open3 ( Only if Open1= 2)  Let's consider this policy question again Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

The policy would also improve water in a region downstream from you by 15%, though you do not think you will visit that region.

This policy, through additional taxes, would increase your cost of living by $ 150 per year ( rather than $ 250 in the previous question). February 2000 79 Would you be in favor of this policy?

1. Yes 2. No  Open4 ( Only if Open2= 1)  Let's consider this policy question again Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

The policy would also improve water in a region downstream from you by 15%, though you do not think you will visit that region.

This policy, through additional taxes, would increase your cost of living by $ 500 per year ( rather than $ 350 in the previous question).

Would you be in favor of this policy?

1. Yes 2. No  Open5 ( Only if Open2= 2)  Let's consider this policy question again Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

The policy would also improve water in a region downstream from you by 15%, though you do not think you will visit that region.

This policy, through additional taxes, would increase your cost of living by $ 300 per year ( rather than $ 350 in the previous question).

Would you be in favor of this policy?

1. Yes 2. No  Open6 ( Only if Open3= 1)  February 2000 80 Let's consider this policy question again Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

The policy would also improve water in a region downstream from you by 15%, though you do not think you will visit that region.

This policy, through additional taxes, would increase your cost of living by $ 200 per year ( rather than $ 150 in the previous question).

Would you be in favor of this policy?

1. Yes 2. No  Open7 ( Only if Open3= 2)  Let's consider this policy question again Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

The policy would also improve water in a region downstream from you by 15%, though you do not think you will visit that region.

This policy, through additional taxes, would increase your cost of living by $ 100 per year ( rather than $ 150 in the previous question).

Would you be in favor of this policy?

1. Yes 2. No  Open8 ( Only if Open4= 1)  Let's consider this policy question again Imagine again that you have recently moved to another region of the country, where water quality is 50% Good. February 2000 81 Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

The policy would also improve water in a region downstream from you by 15%, though you do not think you will visit that region.

This policy, through additional taxes, would increase your cost of living by $ 750 per year ( rather than $ 500 in the previous question).

Would you be in favor of this policy?

1. Yes 2. No  Open9 ( Only if Open7= 2)  Let's consider this policy question again Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

The policy would also improve water in a region downstream from you by 15%, though you do not think you will visit that region.

This policy, through additional taxes, would increase your cost of living by $ 50 per year ( rather than $ 100 in the previous question).

Would you be in favor of this policy?

1. Yes 2. No  demog0  That is all the questions we will ask you about water quality.

We would like to ask you some final questions about yourself.  demog1  Are you male or female?

1. Male 2. Female February 2000 82  demog2  Are you married?

1. Yes 2. No  demog3  Which racial or ethnic background best describes you?

1. White 2. African American 3. Hispanic 4. Asian or Pacific Islander 5. Other 6. I prefer not to answer this question  demog4  What is your age?

1. 18  25 years old 2. 26  35 years old 3. 36  45 years old 4. 46  55 years old 5. 56  65 years old 6. Over 65 years old  demog5  What is the highest level of education that you have completed?

1. 8th grade or less 2. 9th  12th grade 3. High school graduate 4. 13  15 years ( some post high school education)

5. College graduate February 2000 83 6. Some post college education  demog6a  We would like to ask you some questions about your employment status.

Are you currently employed?

1. Yes 2. No  demog6b ( Only if demog6a= 1)  Is that full or part time employment 1. Full time 2. Part time  demog6c  We would like to ask you some questions about your employment status.

Are you retired?

1. Yes 2. No  demog6d  Are you a full time student?

1. Yes 2. No  demog6e  Are you a full time homemaker?

1. Yes 2. No  demog7  What was your total family income last year?

1. $ 0  $ 5,000 2. $ 5,000  $ 10,000 3. $ 10,000  $ 15,000 4. $ 15,000  $ 20,000 5. $ 20,000  $ 30,000 6. $ 30,000  $ 50,000 7. $ 50,000  $ 100,000 8. More than $ 100,000 February 2000 84 9. I prefer not to answer this question  zipq  What is your five digit Zip Code?

Type your Zip Code then press the enter key  Envorg  Environmental Defense Fund Greenpeace National Audubon Society National Wildlife Federation Nature Conservancy Natural Resources Defense Council Sierra Club Are you a member of any of the above organizations?

1. Yes 2. No  Pret1  Where did you take the survey?

1. On my own computer at home 2. On my work computer at work 3. On a neighbor's or friend's computer 4. At a Kinko's near my home 5. None of these  Pret2  Did you have any problems using the diskette to run the survey program?

1. Yes 2. No  Pret3  February 2000 85 How did you feel about the length of the survey?

1. Shorter than I expected 2. About the right length 3. Longer than I expected 4. Too long  Pret4  Did you have any problem understanding any of the questions in the survey?

1. Many questions were unclear or confusing 2. A few questions were unclear or confusing 3. The questions were clear and understandable 4. Some questions seemed overly simple  endq  You have reached the end of the survey. Thank you for participating in our survey on water quality. Your answers and the answers of other survey takers will be used to help the government understand how you and others value water quality.

Please remember to place the survey disk in the return envelope and put it in the mail.

Press any key to end the survey.

Press any key and the survey will end  February 2000 86 Attachment 3: Pilot Study Report DRAFT 28 May, 1998 THE VALUE OF CLEAN LAKES, RIVERS, AND STREAMS:

THE ITERATIVE CHOICE APPROACH*

by JOEL HUBER Duke University WESLEY A. MAGAT Duke University and W. KIP VISCUSI Project Manager, Harvard University With the assistance of JASON BELL Computer programmer, Duke University BARUCH FISCHHOFF Psychologist, Carnegie Mellon University Preliminary Draft Report: DO NOT CITE February 2000 87 THE VALUE OF CLEAN LAKES, RIVERS, AND STREAMS:

THE ITERATIVE CHOICE APPROACH EXECUTIVE SUMMARY 1. The purpose of this study was to establish benefit values for water quality improvements for lakes, rivers, and streams. These values were intended to be relevant to EPA policy evaluations. Results reported here are for a pre test as a prelude to a larger national study.

2. Previous water quality benefits assessments have utilized the water quality ladder as the reference point. However,

the hierarchical ranking that all water that is drinkable is swimmable, and that all water that is swimmable is fishable,

is not valid. Moreover, it does not correspond to the water quality rating systems used in the National Water Quality Inventory, which is the framework used for this study.

3. The National Water Quality Inventory defines water quality in terms of the percent of water in a state that is good for fishing, swimming, or aquatic life.

4. The structure of the survey instrument that we developed involved the use of an interactive computer survey consequently requiring the use of in person interviews. Two approaches were evaluated in this study. Phase 1 used a random telephone approach to contact potential survey participants, who then took the survey at a central location.

Phase 2 utilized mall intercepts.

5. The pre test site for the Phase 1 central location interviews was Research Triangle Park, North Carolina. For the mall intercepts the sites were Cary, NC; Charlotte, NC; Denver, CO; and Colorado Springs, CO.

6. The survey established benefit values for improvements in water quality. These were calculated based on responses to paired comparisons involving water quality changes and cost of living levels for regions to which the respondent might move. Overall, respondents averaged approximately a $ 20 value per unit increase in the water quality level.

There is not a strong variation in this valuation by locale.

7. The water quality valuations also were linear with respect to the baseline water quality. Thus, they were not sensitive as to whether the initial water quality level was low, medium, or high.

8. As a cross check on the paired comparison approach, the survey also incorporated a referendum question near the end of the survey. The referendum responses yielded similar results. Analyses of the various quartiles of the paired comparison valuations indicate that the referendum values are strongly correlated with these amounts.

9. The survey also elicited the relative valuation of improvements in the water quality of lakes as opposed to rivers and streams. Lakes have the higher relative value among the respondents in terms of the mean effect.

10. Individuals may also value water quality attributes beyond simply the overall EPA water quality rating. The attributes for which the respondents were willing to pay an additional amount to reduce these attributes included February 2000 88 whether the water was smelly, cloudy, or polluted by toxic chemicals.

11. In addition to these use values, this survey also explored the non use value that respondents attach to improvements in water quality in regions where they do not live. These values were quite substantial on the order of half of the value of the use benefit amount.

12. The survey also explored the relative valuations of water quality for different dimensions. Swimming had the highest value, followed by valuation of the aquatic environment, with the lowest valuation being water quality for fishing. February 2000 89 This report summarizes the research findings to date on our EPA supported research project directed at establishing the economic value of improvements in the water quality of lakes, rivers, and streams. This is a preliminary report on our results from the pilot project phase and does not report national estimates valid for benefit assessment. While the sample size is reasonably extensive, it is not a national random sample. Without a national study, we do not recommend that these results be used to place dollar values on water quality benefits for policy purposes.

The sections in the report below outline the research task, the research approach, and the findings of our study. The general methodology used to obtain valuations is in the spirit of the literature on contingent valuation and environmental benefit surveys more generally. However, we believe that the approach we have devised is distinctive in that we construct individual preferences based on the individual attributes involved. Thus, our hope is that this research will be of methodological as well as substantive interest.

I. The Research Task The overall focus of this study was on developing values for improvements in water quality for lakes, rivers, and streams. Thus, water quality changes for estuaries, oceans, groundwater, and other excluded categories are not part of the focus of the study.

The policy oriented nature of our analysis dictated much of the overall structure of the research approach. The overall objective was to develop benefit values that could be used in conjunction with the water quality data used by the EPA to assess the benefits of changes in water quality. So that these results would be operational for the EPA it was important that the EPA data structure be used as the frame of reference.

Previous studies had used a water quality ladder as an index of different levels of water quality. Exhibit 1 presents a representative water quality ladder modeled after that used by Mitchell and Carson in their contingent valuation study of the quality of fresh water. Water quality rankings are on an ordinal scale from zero to ten. At the top of the scale is drinkable water that is safe to drink and for all other uses listed below. The components of the water quality hierarchy are: water that is swimmable, water that is fishable, water that is boatable, and water that is not safe for any February 2000 90 of these uses. This water quality hierarchy captured the previous EPA scientific understanding of different levels of water quality.

At this juncture it is also worth noting that this water quality ladder formulation also has attractive properties from a survey standpoint. By using a single ladder, gradations in water quality can be converted into a single dimension. The cognitive difficulties for respondents in terms of the thinking about water quality consequently will be less than if they have to consider a multi dimensional good in which each of the attributes may change independently of one another.

One drawback of using the water quality ladder are that the ordinal quality ranking may not have cardinal significance.

However, even it that problem is avoided the ladder becomes strictly inappropriate if the implied hierarchical ranking may not in fact hold.

The basic assumption of the water quality ladder is that all water that is drinkable is also swimmable, that all water that is swimmable is also fishable, and that all water that is fishable is also boatable. Exhibit 2 shows that this relationship does not hold based on actual data pertaining to the water quality ladder reference points using water quality information from the U. S. EPA's Water Quality Inventory. These results are for the nation as a whole, and the statistics vary by state. Consider first the values for lakes. Overall, 85 percent of the water is drinkable but only 79 percent is swimmable, violating the ladder hierarchy. Similarly, 82 percent of the water is fishable, which is below the amount of water that is drinkable. The hierarchy also fails to hold for rivers, for which 87 percent of the water is boatable and 95 percent of the water is fishable.

The failure for the water quality rankings to adhere to the water quality ladder structure is even more pronounced when considering individual state data. Of the 28 states with lake data for both fishing and swimming, 18 of the states ( or 64 percent) do not obey the hierarchy in the water quality ladder. Similarly, of the 29 states with river data for both fishing and swimming, 15 of them ( or 52 percent) do not obey the water quality ladder. Adherence to the water quality ladder is consequently the exception rather than the rule.

In recognition of these and other deficiencies of the single dimensional ranking of water quality, EPA has developed several dimensions of water quality to reflect these different characteristics. Our survey design uses the following three dimensions of water quality: February 2000 91 1. Aquatic life support The water body supports many plants, fish, and other aquatic life.

2. Fish consumption Fish caught in the water body are safe to eat.

3. Primary contact recreation swimming.

Prolonged contact with the water in the water body will not cause illness.

Within these three categories, each state's water has a particular score that reflects the percentage of water that meets the water quality standards with respect to that particular dimension. Thus, the quality of the water with respect to fish consumption, aquatic life support, and swimming receive independent rankings with respect to each of these dimensions as opposed to combining the rankings in terms of a composite index of overall water quality.

Exhibit 3 illustrates a page of water quality inventory data for one particular state. EPA has similar information for other states that can be used in projecting benefit levels associated with changes in the water quality index values with respect to each of the quality dimensions. It is noteworthy that because the rating of each dimension is presented with respect to the percent of water that meets certain quality levels, the quantitative scores do in fact have quantitative significance and are not simply qualitative rankings. The valuation task requires, however, that some kind of metric be constructed to both establish tradeoffs across the water quality dimensions as well as tradeoffs between improved water quality and money. Thus, the cognitive task that will be posed in our survey will be much more complex than would be encountered using a single water quality metric. The advantage of this more complex structure is that it is related both to our current understanding of the scientific structure of the problem and to EPA's valuation needs.

II. General Survey Approach As in contingent valuation studies, the survey approach that we use involves individual interviews regarding hypothetical choices involving economic and environmental commodities. However, the overall structure we utilize is more abstract than in traditional contingent valuation. Under the standard approach, the respondent considers a February 2000 92 detailed characterization of some environmental good for which the respondent is asked to pay some amount to improve its quality. Our approach instead is to determine individual preferences based on the valuation of underlying attributes.

To reduce the cognitive demands of the task, the survey structure establishes a valuation of each of the component attributes of water quality, determines these tradeoff values, and also assesses the overall conversion of the water quality component improvements into a dollar valuation of water quality more generally. Although this analysis begins with an assumption of linearity in terms of the valuation of any particular attribute, we test this assumption in a variety of ways. The key aspect of the survey structure is that respondents will consider moves to a hypothetical location for which different components of the choice will be varied. This method contrasts with the need for elaborate detail required in a conventional contingent valuation approach The key structure of this study is based on an interactive computer survey in which respondents considered a task in which they could move to one of two different locations. These locations differed in terms of water quality dimensions and cost of living. The computer then framed subsequent choices until the respondent reached the point of indifference. This approach established both their tradeoff rates across water quality dimensions as well as their tradeoff rate between improved water quality and money. The details of the survey will be considered much more extensively below. February 2000 93 A. Simplifying the Task Our survey design considered three dimensions of water quality described in the National Water Quality Inventory.

These dimensions are the ones most commonly reported in the water quality inventory state data. Because of the different aspects addressed by these attributes, subjects can understand that EPA can influence water quality in different ways by considering each of these dimensions in turn. The three dimensions of water quality included were aquatic life support, fish consumption, and primary contact recreation swimming, while the excluded water quality category was drinking water supply. We explicitly excluded drinking water from the study because even though it is a use that is often considered when people think of water being safe or unsafe, it is outside the scope of our survey design. From a policy standpoint, drinking water is distinct since it can be removed from a lake or river and treated before consumption. Unlike other uses, it is also a more easily replaceable use ( through bottled water) than the visit related uses.

For each of these water quality dimensions, EPA rates the water quality along five different qualitative scales in terms of the level of water quality. For convenience, and to assist respondent understanding, we combine the highest two quality rating categories as indicating that the water is " Good." Under the EPA criteria, water meeting this standard is safe to use for the specified use. The three lower water quality categories we label as " Not Good." Under the EPA rating system, the water body is unsafe in some way if it is in this category. In terms of the state data table presented in Exhibit 3, Good combines the first two columns, and Not Good combines the remaining three columns of data.

Our survey design uses the National Water Quality Inventory data only as it pertains to lakes and rivers. In the first parts of the survey, we combine these water quality ratings by presenting lakes and rivers as having the same level of water quality in the survey questions. Later, we include a separate set of questions within the structure of the survey instrument to differentiate an individual's preferences between lake and river water quality. February 2000 94 B. Survey Design Ideally a survey should elicit values of some standardized water quality improvement. This change in water quality should not be specific to the individual respondent in a way that cannot be generalized to obtain national water quality benefit values. In some respects, this approach is similar to placing all subjects within the context of John Rawls'

original position. Each subject will be moving to a hypothetical new region without the specific water quality and availability attributes of the person's current residence.

To avoid the difficulties arising from very local water characteristics, our survey asks subjects to imagine that they are moving to a different region. Moving to another region prevents undue focus on individual local water bodies and permits subjects to consider improvements for a large, well defined area rather than for their own specific neighborhood alone. Subjects may of course differ in terms of their valuation of water quality, and this valuation may also depend on their current availability of water. As a result, the survey instructs subjects that they will move to an area that has the same volume of lakes and rivers as where they live now. Thus, the valuations that are elicited should be reflective of any regional influences to the extent that they are consequential, but they will do so in a manner that is highly structured. Notice, it also should not elicit responses that relate to a personal circumstance for example whether they currently live right next to a lake or a river.

The survey also defines what is meant by a region, which is the area within two hours' drive of the subject's home.

To better envision what a region entails, and the extent of local lakes and rivers, each subject receives a map showing their state, the lakes and rivers in the state, with a circle defining the two hour region ( see Exhibits 5 and 6).

Exhibit 4 presents a representative cost of living water quality tradeoff question. Subjects considered two possible regions to which they could move, each of which is characterized by the increase in the annual cost of living and the percent of lake acres and river miles in that region with good water quality. Respondents then considered a series of such paired comparisons until they reach a point of indifference. This result of this exercise is that it establishes a value of water quality for each respondent in terms of the dollar increase in cost of living that they are willing to incur per one percent improvement in water quality. This value of increasing percent good by 1% will be the principal measure of water quality changes. The value can be derived using a straightforward calculation based on two February 2000 95 equilibrating regions, each of which has an associated cost of living and percent of lake acres and river miles with good water quality. In the example shown in Exhibit 4, let us suppose that subjects are indifferent between these two regions. This means they are indifferent to incurring an additional $ 150 for a 15 percent improvement in water quality.

Then each one percent improvement in water quality has a value of $ 10.

A noteworthy characteristic of the survey approach is that it involves a series of binary choices instead of an openended willingness to pay format. This iterative choice structure permits subjects to determine their value for water quality by choosing which of two options that they see as more reasonable. A more open ended format would ask subjects to put a value on a good that has just been defined for them recently and would be a more formidable task.

Each survey question includes two different regional choices as well as a no preference option. The choices define a level of tradeoff between money and water quality. The subject's response demonstrates an upper or lower bound for the subject's value of water quality at the level of tradeoff.

The questions then iterate based on the subject's initial response to either increase or decrease the level of tradeoff between money and water quality. This iteration continues until the subject's answers provide both and upper and lower bounds on their value of water quality or until their answer reaches an extreme high or low value. If an extreme is reached, this survey tests the subject's understanding with a dominated choice question where one alternative is better on both cost of living and water quality. Subjects who fail this dominated choice question will be the focus of a separate analysis below as part of the consistency checks to ensure the reliability of the study data.

The features of this choice approach continue throughout the survey. Subjects always make choices that are restricted to two different dimensions. While one could envision multiple dimensions, and it would be valuable to ask questions about multiple dimensions, such questions would exceed individuals' cognitive capabilities. The study considers changes in cost of living, water quality for lakes and rivers, water quality for each of the three different uses, variations in water quality depending on whether the water is cloudy, smelly, or the result of toxic pollutants, as well as the role of nonuse value. In each case, to prevent the task from exceeding their cognitive limitations, the survey approach asks for choices among alternatives that differ on two dimensions. A noteworthy feature of the survey is that subjects also do not consider new domains of choice without extensive preparation. The survey defines new concepts with which February 2000 96 the subjects may be unfamiliar. In addition, the survey includes training questions throughout the survey instrument to ensure that subjects understand the concepts being utilized in the survey.

The regional exhibits considered by the survey respondents consisted of maps for the two states in which the interviews were held, North Carolina and Colorado. Exhibit 5 is the map showing one of the North Carolina regions of interest and Exhibit 6 is the map for one of the Colorado regions. Whereas the rest of the survey was undertaken entirely using an interactive computer program approach, the maps were hardcopy exhibits that were handed to the subjects as part of the survey task. These maps were considerably larger than is shown in Exhibits 5 and 6 and the maps were also in color, with blue indicating pertinent water bodies.

The manner in which respondents proceeded through the iterative series of choices is reflected in the decision tree presented in Exhibit 7. This tree indicates how respondents move through a series of questions based on their earlier answers to the survey questions. As can be seen, respondents who value water quality by more ( or less) than is indicated by the initial valuation of subsequently pushed into situations in which there is a greater ( or lower) valuation of water implied by the choice question. Once the respondent hits the extreme at either the high or low end, there is a dominated choice question included in the survey to ascertain whether the subject has become lax in attending to the survey task. People who fail this test we label as " inconsistent" and do not include them in the statistical analysis.

C. Survey Contents The survey consisted of ten different sections. By subdividing the survey task into different substantive units,

respondents could be engaged in a particular valuation task and their responses could be elicited with respect to a specific tradeoff, avoiding the complicating influences of multiple dimensions that otherwise might be at stake.

1. Lake/ river usage. This section of the survey ascertains whether the respondent has used lakes, rivers,

and streams recently and also obtains information regarding the character of the use. For example, has the respondent engaged in fishing or swimming? If yes, how often? The primary purpose of these questions is to encourage the respondent to think about the value of these activities in such a way that will motivate the later choices.

2. Question format explanation. This section of the survey introduces the format of most survey questions that will follow. Thus, the intent of this section is to provide a general introduction to the character of the tradeoffs February 2000 97 that will be faced, but will not include specific questions to ascertain the cost of living water quality tradeoff values.

3. Cost of living versus water quality. This is the key section of the survey that is designed to ascertain the rate of tradeoff between increases in cost of living and water quality improvements. The structure of this section utilizes a sequence of paired comparisons until a point of indifference has been achieved.

4. Lake quality versus river quality. This section of the survey determines the individual's rate of tradeoff between lake and river water quality improvement. Using these results it will be possible to ascertain the relative benefit assessment for water quality improvements for these two different classes of water bodies. As in the case of the cost of living water quality tradeoffs, this section of the survey as well as subsequent sections will utilize a series of paired comparisons until a point of indifference has been achieved.

5. Water uses tradeoff. In this section, the respondent determines relative tradeoffs for swimming, aquatic environment, and fishing in three paired comparisons, i. e., swimming versus aquatic environment, swimming versus fishing, and fishing versus aquatic environment.

6. Source of pollution. Respondents may not care simply about the overall level of water quality as it has been affected by pollutants, but also about the nature of the pollution that causes the decrease in water quality. A pollution component of particular interest is industrial toxic wastes. Are people more fearful of the decreases in water quality caused by toxic waste as opposed to conventional pollutants? The section of the survey addresses this issue by assessing rates of tradeoff between pollution due to agricultural wastes and pollution due to industrial toxic wastes.

7. Nonuse values. A major and controversial benefit component in environmental policy areas is the nonuse value that should be placed on environmental improvements. If, for example, the respondent is never likely to visit a particular region in which a water quality improvement will occur, is there nevertheless an economic benefit to the individual from improving the water quality? To explore this issue this section examines the rate of tradeoff between water quality improvements in the person's own region versus water quality improvements in a region which the respondent will not visit. Moreover, this section also analyzes the potential for evaluation of water quality based on February 2000 98 the probability that the respondent will visit another region, which can be viewed as a form of economic option value.

8. Aesthetic properties, smelliness and cloudiness. Even if water quality meets a particular level based on the EPA criteria, individuals may also be sensitive to other attributes. The two attributes considered were the smelliness and cloudiness of water. In each case, the survey determines the rate of tradeoff between that attribute and water quality improvements more generally. These results also may be instructive with respect to identifying different demographic groups who place greater weight on these aspects of water quality that are not currently part of EPA's criteria. .

9. Cost of living versus water quality referendum. All previous tradeoffs considered thus far are based on a series of choices among paired alternatives. Here we adopt a referendum approach to assessing the value of water quality. In particular, individuals are asked to determine whether they support a policy referendum in which there will be some associated cost as well as an associated water quality improvement. Asking the water quality valuation question in this alternative way will provide a valuable consistency test on the results above for section three of this survey in which the cost of living versus water quality tradeoff has been elicited through paired comparisons.

10. Demographics. This section of the survey obtains detailed information regarding the demographic characteristics of the respondents. These characteristics are of interest for a variety of reasons. First, analyzing the demographic characteristics is useful in testing whether the respondent group is representative of the population in the same area. Second, analyzing the characteristics of the respondents also is helpful in analyzing how various responses to questions, such as the valuation of water quality, vary with demographic characteristics. Based on a regression analysis of these valuations in conjunction with information on demographic characteristics, one could project water quality valuation from a sampled population to a broader population. February 2000 99 D. Recruiting and Survey Format The survey consisted of two different phases. Phase one of the survey involved bringing respondents to a central location after making phone contact with them. This phase is useful in obtaining insight into the potential limitations of this method of recruiting subjects. Phase two involves the use of a series of mall intercepts. This is a lower cost method of recruiting subjects than paying respondents to come to a central location but one which, as it turned out,

also yielded a much more representative sample and more reliable responses.

Exhibits 8 and 10 compare the demographics of the those who participated in Phase 1 to those of the area. As is clear,

the process resulted in strong oversampling of highly educated people, older people, and non minorities. The discussion of the sampling process will clarify how these biases occurred.

The implementation of the Phase 1 portion of the survey took place from August 13, 1997 to August 29, 1997. The incentive of $ 15 was offered to respondents for taking the survey at a central location. Four callers from a North Carolina marketing research firm recruited respondents using a list of 1,000 phone numbers from a 10 mile radius around the interview location. They placed 2,211 calls to these numbers, and 144 people agreed to take part in the survey. Of this group, 106 showed up to the survey location and completed the survey The callers described a process by which about one third of the calls placed actually reached a person. The remainder either reached answering machines, disconnected numbers, or there was no answer to the call. Of the one third of the calls that were successful in reaching an individual, about one in five people answering the phone agreed to take the survey. Most people called accepted screening questions. Callers were of the opinion that since it was mentioned that the survey was for EPA, most people were agreeable to answer the questions.

The people who refused to take the survey gave a variety of reasons. The reasons most often mentioned were time conflicts, distance to the survey location, traffic in the central location area, or just a thank you saying that they were not interested. Time conflicts often included the fact that a school semester started around the pre test period for college age people and parents of children. Presumably the time conflicts associated with the new school schedule,

less free time, and for the college aged not knowing exactly what their schedule would be were reasons for many of the school related conflicts. Some of the time conflicts were reduced by the availability of evening and weekend times February 2000 100 to take the survey.

The central location used for the survey was at the marketing research firm, which is located in the Research Triangle Park area. This area is close to major arteries and centrally located with respect to Chapel Hill, Durham, Raleigh, and Cary, N. C. However, it is not in an urban location, and, as a result, is not as convenient to access as would be, for example, a shopping mall. Mentioning the Research Triangle Park location may have caused some people to decline because of the distance of the travel, but others felt that it added some legitimacy to the offer to participate in this study.

It should be noted that the Research Triangle Park area includes many high technology corporate operations as well as research offices of the U. S. EPA. This mix may have in part contributed to the above average education level of the respondents.

A possible problem in recruiting subjects is that people often refused to participate in the survey on the grounds that since they do not use recreational water they would not have any reason to take the survey. This difficulty may require a change in the call sheet and encouragement by callers for participation even if this is the case. If this difficulty were to occur for the main survey, not simply this pilot, the result would be that we would have a value for water quality that overstates the value for the nation overall to the extent that the non respondents have a lower valuation.

The screening for participating in this study required that the subject be over age 18 and have a high school diploma.

Very few people were disqualified by the screening questions. None of the callers recalled having disqualified anyone though data show that one person was disqualified for being under 18, and 7 more were disqualified for not having a high school diploma. There seem to be no major difficulties with respect to educational group in terms of the ability to take the survey, so that the high school diploma requirement may be removed in the main survey. A few respondents disqualified themselves as being EPA employees, and one disqualified himself because he was a state park ranger.

Callers were unsure whether such facts should disqualify people, and there is a need for guidance to be given to the callers when undertaking the main survey. Also, it was apparently inconsistent on the call sheet whether the qualifying age was 18 or 21. Other caller observations were that people in the sample seemed older than they had expected to reach, and this may reflect the types of people who were at home to answer phones during the calling hours of 6: 00 p. m. to 9: 00 p. m. February 2000 101 Once people agreed to be respondents, they scheduled a time to take the survey. The first week saw many no shows,

and the callers generally called back to reschedule. After the first week, the marketing firm sent confirmation letters with an enclosed map and this effort seemed to increase the response rate. Weekend times had a higher no show rate than week day times, which the marketing researchers did not find surprising.

There were a few cases of self referrals, meaning that the respondents had someone else take the survey instead of themselves. When this happened, it was either a spouse or in one case a daughter, but in all cases from the same household. This happened a total of eight times out of 100 and was not a significant problem.

Phase two of the study utilized a series of mall intercepts in Cary, NC ( 49 interviews), Charlotte, NC ( 53 interviews),

Denver, CO ( 100 interviews), and Colorado Springs, CO ( 101 interviews). These interviews took place from January 27, 1998 to February 6, 1998. The incentive provided to respondents was $ 10.

Obtaining a sample of respondents with mall intercepts posed much fewer difficulties than did the phone central location approach. Respondents could be recruited at the time when they would take the survey so there was not the problem of no shows, etc. In the discussion below we will compare detailed information concerning the demographic breakdown of the people at each of locations as well as for the central location, showing that the mall intercepts proved to be much more representative of the local population than did the phone central location approach. Since the central location in the Phase 1 study was closely related to a population area with an extremely high density of, for example,

Ph. D. scientists, the high education of the Phase 1 sample may be representative of the extremely localized survey area.

However, it is not representative of the entire county or region more generally. Other researchers who have undertaken phone central location surveys in North Carolina have had a similar experience in attracting respondents who have what appear to be above average education levels. The cost per completed interview was considerably less for mall intercepts. Section III describes the sample characteristics in detail.

E. Survey Changes Between Phases Shifting from Phase 1 to Phase 2 involved not only a shift in survey methodology but also a refinement in many of the survey questions. The most important change is that we attempted to alter the format of the first question in each set so that there would be closer to a 50 50 split in terms of the respondents taking either an increase or a decrease in, for February 2000 102 example, the value of water quality. At the Research Triangle Park location, for example, 81 percent of the respondents chose a higher water quality given the cost of living increase in that area. After the initial tradeoff question was revised for Phase 2 the percentage of respondents choosing the higher water quality level after the first question was 59 percent.

We adopted a similar approach throughout the survey, altering the initial set of choices used to derive the tradeoff in a manner so that roughly half the respondents will choose more of the good and half the respondents will choose less of it given the specified tradeoff level.

III. Sample Characteristics The demographic breakdowns for the full sample as well as for each component of the sample appear in Exhibit 8.

As was indicated above, the Research Triangle Park ( RTP) sample tends to be much more highly educated than were the samples at the various mall intercept locations. Overall, the mall intercepts in particular appear to be more successful in recruiting a more diverse population group.

Some of the demographic characteristics vary in the expected fashion. There is greater representation among black respondents for the North Carolina samples, and more representation of Hispanic respondents in Colorado. The environmental membership and water usage responses also indicate that this sample does not include an overwhelming concentration of individuals who are active environmentalists.

Exhibit 9 presents the consistent sample, which consists of the people who give a dominated response once they hit such a corner position. The characteristics of the consistent sample closely parallel those of the full sample in Exhibit 8.

We are presenting the consistent sample results here in detail, however, because they will be the focus of the subsequent analysis of the responses. The findings for the full sample are very similar.

Exhibit 10 presents the census demographics that will serve as the reference point for each of the areas. As can be seen, Cary and Raleigh have a much higher proportion of college educated adults than North Carolina overall, as does Chapel Hill ( not shown). In the analysis below, we will use a dummy code to take out any effect of a particular location that is not accounted for by the demographic variables. February 2000 103 IV. Cost of Living versus Water Quality Tradeoffs Summarizing, the key aspects of the methodology we are espousing, which will be described in detail below are:

1. Importance of getting respondents to think about the impact of the attributes on their lives 2. Iterative paired choices 3. Choices pit one attribute against another 4. Attributes are balanced in the sense that approximately half the respondents should choose either alternative in the first iteration 5. Include consistency tasks and delete those respondents who do not respond consistently The main focus of the survey was to obtain an estimate of an individual's tradeoff between money and improvements in water quality. Although later questions are directed at nuances in this valuation, such as differences in the valuation of water quality improvements that affect swimming as opposed to fishing, the first overall tradeoff of concern and the one that will drive any overall benefit assessment will be how respondents value water quality generally. The next sections detail how this valuation is achieved.

Exhibit 11 presents the text of a sample cost of living survey question. The survey defines what the term cost of living is and attempts to engage the respondent in thinking about the importance of cost of living within the context of their overall household expenditures. After establishing this framework, the survey then confronts the respondent with a regional choice in which there is clear dominance, as both regions are otherwise alike except for a difference in their cost of living. In the case that the respondent does choose the low cost of living area, the explanation included in Exhibit 11 is provided, and the dominated question is repeated. Otherwise, the respondent to the section defining water quality.

Exhibit 12 shifts the focus from defining what we mean by cost of living to defining water quality. This question indicates that water quality may differ across regions and that water quality may either be " Good" or " Not Good,"

where the survey defines what it means for water quality to be Good or Not Good. This section of the survey also clarifies that drinking water is specifically excluded and defines what is meant by the size of the region and the percent change in water quality. The respondent then considers a simple regional choice question where the regions differ only February 2000 104 in terms of water quality. Once again, the first choice is deliberately a dominated choice, and individuals failing to choose correctly will be given the explanation that corrects their error and then repeats the question. Exhibit 13 shows the question in which respondents now have to trade off both cost of living as well as water quality. Within the context of this sample question there is a clearcut dominant choice, as Region 2 is less expensive in terms of the increased cost of living and has a higher percentage of water that is of Good quality. Individuals failing to recognize the dominated choice and answer the question correctly will once again be taken through the loop that explains the error in their answers. These dominated questions serve both to give the respondents easy questions as they begin, and to give extra training to those who do not understand.

At the bottom of Exhibit 13 we present a tradeoff question that does not involve a dominant choice. Depending on the respondents answer to the question, the subsequent tradeoffs considered by the respondent will be either higher or lower than in the initial tradeoff situation.

Exhibit 14 presents the overall statistics summarizing the water quality cost of living tradeoffs. For all the samples as a group, respondents were willing to pay an additional $ 22.40 per one percent increase in the level of water quality.

These amounts ranged from a low value of $ 20.10 for Colorado Springs to a high of $ 28.50 for Charlotte. The median responses were much more tightly clustered and lower than the values of the means. With the exception of Cary and Charlotte, the median values are ranged from $ 11.30 to $ 13.60 for each one percentage point increase. The fact that the mean values are roughly twice as high as the medians suggests that the distribution of the valuation of water quality is skewed by some respondents having extremely high values for water quality. At this overall simple statistic level,

RTP does not appear to be an outlier even though the sample methodology used and the structure of the survey differed somewhat for that sample site.

The structure of the survey that was used to generate these valuation statistics is indicated in the decision tree sketched in Exhibit 15. That tree indicates the branching of the survey based on the individuals' responses to each of the cost

ofliving tradeoff questions. The three columns indicate the three potential answer choices. The top row indicates the implicit tradeoff value associated with the answer choice. The bottom row indicates the percentage of the sample choosing the answer choice. Bold values indicate endpoints of the decision tree. As is indicated, respondents who February 2000 105 persistently undervalue or overvalue water quality based on the choice offered continually confront more extreme choices until ultimately they face a dominated decision at the tip of the tree. Respondents who pick the dominated choice are those who are not included in our consistent sample since they do not appear to be attending to the survey task with the desired level of diligence. Imposing this consistency test on the survey results represents a more stringent rationality test than is typically found in environmental valuation surveys.

The regression results that analyzed the determinants of the valuations of cost of living and water quality appear in Exhibit 16. The dependent variable is the total dollars of cost of living increase that the respondent is willing to incur in return for an increase in the water quality level of one percentage point. The first set of regression results in Exhibit 16 includes RTP respondents in the sample, and the second set of results excludes this sample group. In each case,

separate dummy variables are included to reflect the particular survey location. The only such variable of consequence is that for RTP, which may reflect both the differences in the character of the sample as well as differences in the structure of the survey. Controlling for other factors, RTP respondents are willing to spend roughly $ 7 less per unit change in water quality than the other survey locations.

A noteworthy aspect of the results is that there is not strong variation in the responses based on region. However, the omitted category Colorado Springs, does not differ significantly in terms of the level of the response from any of the other cities. As indicated above, the only significant difference is that reflected by RTP. From the standpoint of subsequent survey design, this finding suggests that there may not be stark differences across regions in the valuation of water quality other than those that are reflected in the demographic variables included in the equation. If this lack of variation occurs more generally, then it implies that there need not be as many regional sites for the subsequent national survey as would be required if water quality valuations differed starkly from region to region.

Of the other variables in the equation, several are consequential, with the effects tending to be fairly consistent across the two different sets of results in Exhibit 16. For concreteness, let us focus on the findings in the sample excluding the RTP respondents. Overall, the non white, non black minorities tend to have slightly lower valuations than did the other groups. Age is consequential, as the valuation of water quality rises with age but then declines with the square of age. This non linearity implies that water quality valuation is strongly related to the respondent's age, which is an February 2000 106 effect that will carry over to many of the other findings below.

The variables intended to capture the environmental orientation of the respondent were not particularly influential.

An important variable that had a consistent impact on water valuation and was consistently significant was whether the respondent had visited a lake or river in the last twelve months. Respondents who met this test valued improvements in water quality at roughly $ 8 more per unit increase in the water quality level.

Analyzing the determinants of water quality valuation in terms of a value per unit of water quality may not be fully reflective of the character of individual preferences if these valuations differ depending on the level of water quality.

If, for example, water quality has a higher value when it is very bad then do improvements in water quality when the value of water quality is quite high, then we would want to recognize this non linearity when establishing benefit values. The survey can potentially incorporate such non linearities into the analysis, though doing so would ultimately complicate any benefit assessment figures. As a result, it is important to test whether there are any statistically significant non linearities in the value of water quality depending on the initial water quality level.

Exhibit 17 provides two panels of information pertaining to these non linearity tests. Panel A presents overall mean statistics based on three different initial water quality levels. Respondents who considered low water quality levels were confronted with choices in which the initial levels of Good water quality ranged from 25 to 40 percent. A second group of respondents considered middle water quality levels ranging from 50 to 65 percent , and a final group saw water quality levels from 75 to 90 percent. The mean valuation per unit of water quality ranges from $ 20 to $ 25 across these categories, but the there is no clearcut pattern. For example, water quality valuation is not a steadily increasing function of the level of the initial water quality.

To test for such a possibility more explicitly, Panel B of Exhibit 17 includes a regression analysis in which the lower bound of the water quality level considered by a respondent is presented as a variable with a value of 25, 50, or 75.

Once again, there is no evidence of any statistically significant non linearity in the water quality valuation. Whether the starting point, in terms of the water quality level is low, medium, or high does not seem to be consequential in terms of how it affects the overall valuation amount. This linearity is an advantage because it suggests that water February 2000 107 quality can be evaluated by only testing one initial level. We caution against generalizing about this promising finding until it is replicated in a larger study.

Testing for such a starting point bias is not the norm in contingent valuation studies, though it is a desirable practice.

If there had been significant variation, it would not necessarily be an indication of a flawed survey instrument, but it would indicate that attempts to use the results of the study for policy purposes would need to recognize the initial water quality level of the policy region in question before assigning benefit values.

V. Referendum Version of the Cost of Living Water Quality Tradeoff The last section of this survey, before eliciting the demographic information, included a referendum version of the cost of living water quality tradeoff. The referendum question was asked only following around five minutes of questions that elaborated on the value of components of water quality. The purpose of separating the referendum from the paired comparison regional choice was to decrease the chance that respondents would attempt to simply mimic their answers to their earlier questions when answering the referendum version.

Exhibit 18 presents the initial referendum policy choice. In the referendum question , the respondent first moves to another region and is informed of the region's level of water quality. The respondent must then face a choice of whether a government policy will increase the quality of water by a certain amount, where this policy improvement would be paid for by additional taxes. The respondent then indicates whether he or she is in favor of this water quality improvement policy. If the answer is " Yes ( No)" then the respondent considers subsequent pairwise comparisons that increase ( decrease) the relative dollar value of water quality improvement.

The results of the referendum approach in many respects are quite similar to those found with the pairwise regional choice questions. Exhibit 19 summarizes the mean and median responses for each of the sample groups. The mean referendum response has a low value of $ 13 per unit increase in water quality for the RTP site, but otherwise is closely clustered in the $ 20.50 per unit to $ 27 per unit range. For the median responses, the RTP group once again tends to be an outlier, though to less of an extent than for the mean responses. As in the earlier results, the distribution of the valuation of water quality is skewed, with some respondents having particularly high values for water quality, leading February 2000 108 the mean value to exceed the median in every case. In some instances, however, the mean and median valuations are relatively close so that there is less of a disparity in the mean and median responses for the referendum version of the question than there was for the regional choice pairwise comparison.

Exhibit 20 reports the regression analysis using as the dependent variable water quality valuation based on the referendum questions. Results appear for both the sample including all survey locations as well as for the sample excluding RTP. These results only pertain to the sample of consistent respondents so that the findings in Exhibit 20 closely parallel in terms of their substantive content the results in Exhibit 16. Once again, the non white, non black minority members of the sample tend to have a lower value for water quality. Although the age variable is not significant, the squared valued of age is, indicating that the value of water quality tends to diminish with age. Unlike the cost of living tradeoff questions, there is no significant effect of visiting a lake or river on the referendum response.

While the respondents' answers to the cost of living and referendum questions were not identical, they were nevertheless related. Exhibit 21 presents different quartiles for the cost of living water quality tradeoff valuation. For each tradeoff information is included with respect to the mean level of the valuation implied by the referendum question. As is indicated, this value is a steadily increasing function of the pairwise regional choice valuation response.

The referendum value for the lowest cost of living regional choice quartile was $ 12.89 per unit increase in water quality, and this amount increases to a high of $ 26.73 for the fourth quartile.

VI. Other Choice Dimensions The survey distinguished not only the valuation of overall water quality, but also sought to assess how these valuations depended on the particular water body whose quality was affected as well as the character of the change. The four different aspects of water and its quality that were analyzed were the following: lakes versus rivers, cloudy versus not cloudy, smelly versus not smelly, and toxic pollutants versus agricultural wastes. These dimensions of choice should be distinguished from water quality uses, e. g., swimming, which are separate dimensions of water quality that will be discussed below. February 2000 109 Exhibit 22 presents the survey text for the comparison between lakes and rivers. Subjects first considered general questions to engage them in thinking about the water quality for lakes and rivers. They then considered a sample question dealing with lake and river quality in which one region was dominant. After completing this dominance question, they then considered a series of actual choices between regions, where the regions differed in their relative quality of lakes and rivers. For example, for the case in Exhibit 22 Region 2 has a higher percentage of river miles with Good water quality, whereas Region 1 has a higher percentage of lake acres with Good water quality.

Exhibit 23 summarizes the aesthetic properties of the water that will be explored, notably whether the water is smelly or cloudy. The questions ask the respondent how important these dimension are and then poses the kind of tradeoff that will be explored in further detail throughout the analysis of aesthetic water quality attributes. In particular, how much of a tradeoff are people willing to make between the percent of Good water quality which is smelly and the percent of Good water quality without smell. Respondents similarly will consider tradeoffs involving whether the water is cloudy, where once again whether the water is cloudy or smelly does not affect the water quality rating, only the aesthetic characteristics of the water.

To assess whether the source of the pollution is consequential in affecting individuals' valuations, a series of questions explored whether respondents valued pollution stemming from agricultural waste differently from pollution from industrial toxic wastes. Exhibit 24 describes the different sources of pollution and presents the initial tradeoff question.

The overall EPA rating of water quality begins as the same irrespective of the source of the pollution. The task for the respondent is whether pollution arising from toxic chemicals that gives rise to the same percent of water with Good quality is as valuable as to clean up as pollution arising from agricultural wastes from farms. Once again, respondents faced a series of tradeoffs designed to ascertain their point of indifference between the two types of pollution.

The tradeoff results for the different aspects of water quality indicate that the various dimensions of choice regarding water quality improvements are often influential in determining the overall benefit value. Exhibit 25 presents the overall valuation of lake water quality relative to river water quality. Although the median respondent viewed water quality improvements in lakes and rivers as being equivalent, the mean valuation was that lake water quality was February 2000 110 roughly twice as valuable as improvements in river water quality. These mean responses range from a low value of 1.7 in Cary, NC to a high of 2.41 in Colorado Springs, CO.

The character of the water in terms of its aesthetic characteristics are also influential. For the full sample as is shown in Exhibit 26, respondents are indifferent to a 1.0 percent increase in the percentage of water with Good quality that is not smelly and a 3.6 percent improvement in water quality that is smelly. Similarly, respondents shown in Exhibit 27 believe that a 1.0 percent increase in the percentage of water with Good quality that is not cloudy is equivalent to a 2.79 percent improvement in water quality that is cloudy. The source of the pollution is particularly influential, as it is shown in Exhibit 28. At the initial water quality levels faced by respondents, individuals in the sample are willing to have a water quality level that is 17 percent lower if the pollution is caused by agricultural wastes rather than by industrial toxic wastes.

Although there is no strong theoretical basis for believing that any particular demographic factors should be influential in affecting these preferences for water quality dimensions, some systematic effects are observed. As is indicated in the regression results in Exhibit 29 for lake water quality versus river water quality, women and non white, non black minority respondents value lakes more highly, as do the very old respondents and the more affluent respondents. The analysis of smelly water quality in Exhibit 30 similarly indicates that the female and non white, non black minority respondents value smelly water quality more highly. It is noteworthy that members of environmental organizations are significantly less concerned about smelly water quality than good water quality overall. This result is consistent with their more fundamental concern with the overall quality of the environment rather than more superficial aesthetic properties. In the case of the cloudy water analysis in Exhibit 31, however, the environmental organization membership effect falls just short of statistical significance. The main influences are that the two categories of minority respondents value reductions in the cloudiness of water more highly than improvements in water quality overall, which may indicate a distrust of scientific assessments of the water quality levels, compared with that which they can see.

The analysis of the greater concern for producers of industrial toxic wastes is shown in Exhibit 32. Concern for industrial toxic wastes more likely to be held by black respondents and more likely to be held by those who have visited lakes or rivers in the last twelve months ( regression analyses for the sample excluding RTP). February 2000 111 VII. Non Use Benefit Values The benefits that individuals derive from improvements in water quality stem from the fact that water quality affects how they might use the water, for example, for recreational purposes such as fishing. There may also be a benefit that people derive from improvements in water quality even if they will not use the water. Non use benefit values have been among the most controversial topics in the literature on contingent valuation. One of the fundamental difficulties in ascertaining the non use benefit value is developing a survey structure that does in fact isolate true non use, as opposed to some probabilistic possibility of use or option value that the resource might have. Our survey approach in which individuals move from a region where water quality is improved or some other hypothetical regions where they do not live might experience a water quality improvement potentially overcomes many of the traditional shortcomings in the way in which this issue has been approached. Nevertheless, we regard this examination of non use benefits as very much exploratory in nature given the difficulty of capturing this benefit component.

Exhibit 33 presents a policy choice question in which individuals can improve water quality in their region or a region of the same size, but which they will never visit. The tradeoff question is consequently posed in terms of what water quality improvement in their current region is equivalent to a water quality improvement in this region they will not visit. Subsequent questions alter the choice by permitting the potential for probabilistic use. In the version of the survey question appearing in this exhibit, the respondent will be making one out of every ten trips that might be taken to a lake or river using this water in the other region. Exhibit 34 shows a question that half respondents saw that suggests the respondent will use this other region for one out of three visits.

Exhibit 35 summarizes the valuation results. In the situations in which there is either no chance of visiting the other region or a small probability, such as 10 percent, respondents need a 0.51 percent improvement in the water quality in their own region to be equivalent to a 1.0 percent improvement in the water quality in the other region. However,

if the probability rises to a 33 percent chance of using the other region, then improvements in the water quality in the other region rise to 59 percent as valuable as improvements in their home region. Indeed, even in the extreme case February 2000 112 in which there is no prospect of use of the water in the other region, subjects are willing to sacrifice substantial improvements in the water quality in their home region to make the environment better elsewhere.

Exhibit 36 presents regression results for non use benefits when there is no chance for visiting the other region. In all cases the demographic factors were not particularly influential, with the exception of household income. The more affluent respondents are more willing to support water quality in another region as compared to improvements in water quality for their home region.

VIII. Uses Dimensions of Water Quality The final aspect of the study is an exploration of the valuation of the different uses of the water quality swimming,

aquatic uses, and fishing. In this case the task was to establish relative values for each of these uses. For example, do respondents value improvements in the water quality index for fishing more highly than improvements in aquatic water quality measures?

Exhibit 37 summarizes the different uses of water and their characteristics. In it the survey text informs the respondent of what we mean by these different categories. For example, water that is good for fishing is rated Good " if fish caught in the lake or river are safe to eat," whereas a Good aquatic environment implies that " the lake or river supports many plants, fish, and other aquatic life." The survey then introduces how each of these components of water quality is rated,

which is in terms of its percent Good in the region. Since the respondents have already dealt with percent Good ratings in detail by the time they consider these tradeoffs, they should be better able to handle the additional dimensions of choice. The structure of the survey considers a sequence of pairwise comparisons in which respondents trade off swimming versus aquatic water quality improvements, swimming versus fishing water quality improvements, and aquatic versus fishing. Because of the nature in which the series of pairwise comparisons are chained, it is possible to determine whether respondents display the appropriate transitivity with respect to their water quality valuation responses. Overall, only 46 of the 348 respondents or 13.2 percent displayed inconsistent responses to the different sets of pairwise comparison valuations. If the subjects had been answering the survey randomly, one would have expected 52 percent of the respondents to be inconsistent for the three uses in some way. February 2000 113 To convey the implications of the relative valuations of water quality, a useful index is the percent of overall water quality improvement that should be allocated to each of the three dimensions. These statistics clearly indicate the relative quantitative importance of the water quality uses. As is shown in Exhibit 39, swimmable water quality accounts for 35 percent of the overall benefit value, aquatic water quality is the second most highly valued at 31.8 percent, and fishable water quality has the lowest valuation 28.4 percent of water quality.

In terms of the demographic factors affecting these valuations, Exhibit 13 reporting of the regression results indicates that swimmable water quality is less highly valued by environmental group members and by people who have visited lakes and rivers in the last twelve months. However, large households tend to value swimming more highly, as one would expect for families with children. The aquatic and the fishable water quality valuations were not strongly influenced by any of the demographic characteristics.

REFERENCES Mitchell, Robert Cameron, and Richard T. Carson, Using Surveys to Value Public Goods: The Contingent Valuation Method, Washington: Resources for the Future, 1989.

Mitchell, Robert Cameron, and Richard T. Carson ( 1993). " The Value of Clean Water: The Public's Willingness to Pay for Boatable, Fishable, and Swimmable Quality Water," Water Resources Research, 29( 7), 2445 2454.

Smith, V. Cary, and William H. Desvousges, Measuring Water Quality Benefits, Boston: Kluwer Academic Publishers, 1986. February 2000 114 Attachment 4: Pilot Study Report Exhibits February 2000 115 Exhibit 1: The Water Quality Ladder Best PossibleWater Quality 10 Drinkable Water is Suitable for Drinking 7 Swimmable Water is Suitable for Swimming 5 Fishable Water is Suitable for Fishing 2 Boatable Water is Suitable for Boating 0 Water is Not Suitable for Any Use Worst Possible Water Quality February 2000 116 Exhibit 2: Water Quality Ratings Pertinent to the Water Quality Ladder Water Quality Ladder Feature National Value for Lakes National Value for Rivers Drinkable 85% 69%

Swimmable 79% 73%

Fishable 82% 95%

Boatable 86% 87% February 2000 117 Exhibit 3: Water Quality Inventory State Page Individual Use Support in California Good Good Fair Poor Poor Designated Use Fully Threatened Partially Not Not Supporting Supporting Supporting Attainable Rivers and Streams ( Total Miles = 211,513) Miles Assessed 12,567 30 2 66 2 0 Aquatic Environment 4,253 63 6 27 4 0 Edible Fish 5,449 52 5 41 2 0 Swimming Lakes ( Total Acres = 1,672,684) February 2000 118 Acres Assessed 489,982 31 0 68 0 0 Aquatic Environment 239,194 38 0 62 0 0 Edible Fish 328,517 35 0 65 0 0 Swimming February 2000 119 Exhibit 4: Representative Cost of Living Water Quality Tradeoff Task The basic measure we use for the value of water quality is $ per 1% improvement in water quality. This is calculated by offering subjects two choices which differ in the level of water quality and cost of living.

1. Region 1 2. Region 2 3. No Preference Between Regions Increase in $ 100 $ 250 Annual Cost More More Of Living Expensive Expensive Percent of Lake 50% 65% Acres and River Miles With Good Water Quality February 2000 120 Exhibit 5: Map of North Carolina February 2000 121 Exhibit 6: Map of Colorado February 2000 122 February 2000 123 February 2000 124 Exhibit 7: Study Decision Tree 1. Region 1 2. Region 2 3. No Preference Between Regions Increase in $ 100 $ 250 Annual Cost More More Of Living Expensive Expensive Percent of Lake 50% 65%

Acres and River Miles With Good Water Quality If Region 1 If Region 2 $ 150 $ 250 $ 100 $ 250 50% 65% 50% 60%

If Region 1 If Region 2 If Region 1 If Region 2 $ 200 $ 250 $ 125 $ 250 $ 100 $ 250 $ 100 $ 250 50% 65% 50% 65% 50% 62% 50% 55%

If Region 1 If Region 2 $ 225 $ 250 $ 100 $ 250 50% 65% 50% 50%

If Region 1 $ 250 $ 250 50% 65% February 2000 125 Exhibit 9: Sample Characteristics, The Full Sample Colorado Springs Denver Cary Charlotte RTP N= 101 N= 100 N= 49 N= 53 N= 106 Mean ( Std Dev) Mean ( Std Dev) Mean ( Std Dev) Mean ( Std Dev) Mean ( Std Dev)

Race: White 68.3 61 65.3 79.2 73.6 Race: Black 8.9 22 18.4 13.2 11.3 Race: Nonwhite, Nonblack 22.8 17 16.3 7.5 15.1 High School Diploma 93.1 84 98 92.5 98.2 College Diploma 26.7 23 42.9 33.9 75.5 Employed 71.3 76 73.5 90.6 71.7 Employed Full time 57.4 62 61.2 79.2 54.7 Retired 11.9 14 6.1 5.7 16 Full time Student 6.9 2 12.2 3.8 9.4 Full time Homemaker 17.8 18 14.3 7.5 14.2 Live in Urban Area 74.3 57 48 64.2 36.8 Live in Suburban Area 16.8 39 34 22.6 58.5 Live in Rural Area 8.9 4 16 13.2 4.7 M e m b e r o f a n Environmental Organization 5 8 6.1 9.4 17.9 Live in State of Study Site 98 99 95.9 94.3 100 Gender, Female 39.6 49 71.4 52.8 52.8 Married 41.6 37 32 50.9 63.2 Age 34.15 13.46 36.91 14.18 30.91 10.79 37.78 14.36 43.06 13.59 Years of Education 13.94 2.26 13.5 2.1 14.8 1.9 14 2.2 16.24 2.1 Household Family Income 28,620 23,110 32,194 24,926 42,955 29,136 35,700 24,908 54,475 27,509 February 2000 126 Time to Complete Study, in Minutes 28.3 9.79 22.82 10.57 24.03 7.69 26.06 13.42 32.58 11.01 Number of Family Members in Household 2.51 1.47 2.66 1.48 2.38 1.32 2.58 1.28 2.54 1.24 February 2000 127 Exhibit 10: Sample Characteristics, The Consistent Sample Colorado Springs Denver Cary Charlotte RTP N= 74 N= 80 N= 44 N= 44 N= 106 Mean ( Std Dev) Mean ( Std Dev) Mean ( Std Dev) Mean ( Std Dev) Mean ( Std Dev)

Race: White 68.9 63.8 65.9 81.8 73.6 Race: Black 6.8 18.8 15.9 11.4 11.3 Race: Nonwhite, Nonblack 24.3 17.5 18.2 6.8 15.1 High School Diploma 93.2 88.7 97.7 97.7 98.2 College Diploma 23 27.6 40.9 38.6 75.5 Employed 68.9 73.8 72.7 93.2 71.7 Employed Full time 58.1 62.5 61.4 79.5 54.7 Retired 9.5 13.8 4.5 4.5 16 Full time Student 4.1 2.5 13.6 2.3 9.4 Full time Homemaker 18.9 20 13.6 6.8 14.2 Live in Urban Area 75.7 58.8 50 65.9 36.8 Live in Suburban Area 13.5 36.3 38.6 25 58.5 Live in Rural Area 10.8 5 11.4 9.1 4.7 M e m b e r o f a n Environmental Organization 4.1 10 6.8 11.4 17.9 Live in State of Study Site 98.6 100 97.7 95.5 100 Gender, Female 36.5 55 72.7 54.5 52.8 Married 44.6 36.3 27.3 52.3 63.2 Age 33.31 13.28 36.99 14.32 30.41 10.42 37.86 15.24 43.06 13.59 Years of Education 13.88 2.12 13.74 2.11 14.7 1.82 14.34 2.16 16.24 2.1 Household Family Income 28,204 21,104 34,810 25,791 40,385 28,380 38,110 25,136 54,475 27,509 February 2000 128 Time to Complete Study, in Minutes 28.2 10.12 23.25 10.1 23.97 7.59 25.17 13.83 32.58 11.01 Number of Family Members in Household 2.55 1.42 2.66 1.53 2.34 1.33 2.59 1.23 2.55 1.24 February 2000 129 Exhibit 11: Census Demographics USA Colorado North Carolina Colorado Springs Denver Cary Charlotte Raleigh Mean Mean Mean Mean Mean Mean Mean Mean Race, White 80.29 88.19 75.56 85.9 72.11 89.78 65.51 69.18 Race, Black 12.06 4.04 21.97 7.02 12.84 5.51 31.78 27.58 Race, Nonwhite, Nonblack 7.65 7.77 2.47 7.08 15.05 4.71 2.61 3.24 High School Diploma 75.2 84.4 70 87.8 79.2 94.9 81 86.6 College Diploma 20.3 27 17.4 27.5 29 48.8 28.4 40.6 Unemployment Rate 6.7 5 5.8 5.9 5.4 2.4 5 4.1 Gender, Female 51.3 50.5 51.5 51 51.3 50.6 52.5 51.5 Age ( Median) 31.1 33.9 31.2 32.1 30.3 Income ( Median) 30,056 30,140 26,647 28,928 25,106 46,259 31,873 32,451 Family Size 2.63 2.51 2.54 2.49 2.17 2.59 2.45 2.26 February 2000 130 Exhibit 12: Cost of Living Task Text =========================================================================== Cost of Living For purposes of this survey, the cost of living is defined as the amount of money that your family spends each year for things like food, clothing, and rent or mortgage.

When we say that a region has a higher cost of living, we mean that each year you would have to spend more for these items overall. =========================================================================== How concerned would you be if your family's cost of living suddenly went up $ 200 per year? ( This would mean that items like food, clothing, and rent or mortgage would cost a total of $ 200 more each year than they do now.) This might mean an increase of $ 2 per week for food ( or $ 104 per year) and $ 8 per month more for housing ( or another $ 96 per year).

1. Not at all concerned 2. A little concerned 3. Somewhat concerned 4. Very concerned =========================================================================== Try answering this sample question to make sure we explained Cost of Living clearly.

Imagine that you must move to another region of the country. You have narrowed your choices down to two. Both regions have a higher cost of living than where you live now, but are alike in all other ways.

Which region would you prefer? 1. Region 1 2. Region 2 3. No Preference Between Regions Increase $ 100 $ 250 In Annual More More Cost of Living Expensive Expensive =========================================================================== The question was not clear.

You chose to move to the region with a higher cost of living. You could have chosen a region with a lower cost of living that is alike in all other ways.

To change your answer, press any key and we will ask the question again.

Otherwise, please tell the interviewer you do not want to change your answer. =========================================================================== You indicated that you have no preference between two regions whose only difference is that it is more expensive to live in one of them.

Are you sure that you don't care whether you would move to a region where it is more expensive to live? After all, you could move to a region with a lower cost of living that is alike in all other ways.

1. Yes, I'm sure that I have no preference. 2. No, I'm not sure. Ask the cost of living question again. =========================================================================== February 2000 131 The Region you chose, Region 1, has a lower annual cost of living than Region 2. February 2000 132 Exhibit 13: Water Quality Task Text =========================================================================== Water Quality Some questions will ask you to choose between regions that differ in terms of the quality of the water in either lakes or rivers in the regions. The government rates water quality as either * Good or * Not Good. Water quality is Good if the water in a lake or river is safe for all uses. Water quality is Not Good if a lake or river is polluted or unsafe to use. =========================================================================== More specifically, Water quality is Good if the lake or river * Is a safe place to swim, * Has fish that are safe to eat, and * Supports many plants, fish, and other aquatic life.

Water quality is Not Good if the lake or river * Is an unsafe place to swim due to pollution, * Has fish that are unsafe to eat, and * Supports only a small number of plants, fish and other aquatic life. =========================================================================== This survey will not ask you about drinking water.

Drinking water is treated by water treatment plants to ensure safety.

Water treatment cannot be done for the dimensions described on the previous screen, since these dimensions involve visiting a lake or river instead of treating a limited amount of water taken from the lake or river. =========================================================================== We will talk about water quality for more than one lake or river.

The questions will include all the lakes or rivers in the region. This means all lakes and rivers within a 2 hour drive or so of your home, in other words, within 125 miles. =========================================================================== We define the quality of the water in the lakes and rivers of a region by the percent of the total acres of lakes or miles of rivers in the region which have good water quality.

For example, let's say a region has several rivers, running a total of 100 miles in the region.

If pollution causes 50 of those miles to have water quality that is not good, leaving 50 miles with good water quality, then we would call the water quality for rivers in that region 50% good. =========================================================================== Try this sample question about water quality. Imagine again that you must move to another region of the country. You have narrowed your choices down to two regions. They differ in only one way, the quality of the water in the regions. They even have the same number of acres of lakes and miles of rivers within 2 hours or so of where you would live. Which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions February 2000 133 Percent of Lake Acres and River Miles With Good Water 50% 65% Quality =========================================================================== The question was not clear.

You chose to move to the region with worse water quality.

You could have chosen a region with better water quality that is alike in all other ways.

To change your answer, press any key and we will ask the question again.

Otherwise, please tell the interviewer you do not want to change your answer. =========================================================================== The Region you chose, Region 2, has better water quality than Region 1.

Next will be a sample question that combines water quality and cost of living. =========================================================================== You indicated that you have no preference between two regions whose only difference is that one has better water quality than the other.

Are you sure that you don't care whether you would move to a region where a lower proportion of lakes and rivers are safe and clean when you could move to a region with more rivers that are safe and clean that is alike in all other ways?

1. Yes, I'm sure that I have no preference 2. No, I'm not sure, ask the water quality question again =========================================================================== February 2000 134 Exhibit 14: Water Quality  Cost of Living Sample Task =========================================================================== We would like to ask you one more sample question to make sure we explained both cost of living and water quality clearly.

Remember, the cost of living is the amount of money that your family spends each year for things like food, clothing, and rent or mortgage.

Also remember that water quality in a region is the percent of the total acres of lakes and miles of rivers in the region which are safe for swimming, fishing, and have a healthy environment. =========================================================================== Cost of Living and Water Quality Questions This sample question combines the two ideas explained earlier. Now how would you choose between regions that differ in both the quality of the water in the regions and their annual cost of living? Which region would you prefer? 1. Region 1 2. Region 2 3. No Preference Between Regions Increase in $ 250 $ 100 Annual Cost More More Of Living Expensive Expensive Percent of Lake Acres and 50% 65% River Miles With Good Water Quality =========================================================================== The question was not clear.

You chose to move to the region with worse water quality and a higher cost of living.

You could have chosen a region with better water quality and a lower cost of living that is alike in all other ways.

To change your answer, press any key and we will ask the question again.

Otherwise, please tell the interviewer you do not want to change your answer. =========================================================================== The Region you chose, Region 2, has better water quality and a lower annual cost of living than Region 1.

Now we would like to ask some more questions like these, but whose answers depend more on how you value water quality and cost of living differences. =========================================================================== You indicated that you have no preference between two regions whose only difference is that one has a lower cost of living and better water quality than the other.

Are you sure that you don't care whether you would move to a region where it is more expensive to live and where a lower proportion of lakes and rivers are safe and clean? After all, you could move to a region with a lower cost of living and where more lakes and rivers are clean that is alike in all other ways.

1. Yes, I'm sure that I have no preference. 2. No, I'm not sure, ask the question again. =========================================================================== February 2000 135 We would like to ask you some more questions like these. However, in these questions, one region will have higher water quality and the other will have a lower annual cost of living. Remember that these regions are the same in all other ways, including the number of lakes and rivers near your home. Which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Increase in $ 100 $ 250 Annual Cost More More Of Living Expensive Expensive Percent of Lake 50% 65% Acres and River Miles With Good Water Quality =========================================================================== February 2000 136 Exhibit 15: Overall Cost of Living  Water Quality Tradeoff Values Cost of Living vs. Water Quality Level. ( Units are $ per 1% Improvement in Water Quality)

N Mean StDev Median All 348 22.4 22.5 13.3 Cary 44 24.0 20.8 18.8 Charlotte 44 28.5 23.9 22.5 Colorado Spr. 74 20.1 20.0 11.3 Denver 80 22.4 22.1 13.6 RTP 106 20.7 24.2 13.3 RTP Excluded 242 23.1 21.7 13.6 February 2000 137 Exhibit 16: Regression Estimates for Cost of Living Value for Water Quality Dependent Variable: Cost of Living vs. Water Quality Level. ( Units are $ per 1% Improvement in Water Quality)

Higher value means willing to pay more for water quality improvement Parameter Standard Variable Estimate Error INTERCEP  2.42 6.76 * Gender: Female 4.33 2.43 * Race: Black  6.07 3.70 *** Race: Nonwhite, Nonblack  8.45 3.25 *** Age 0.46 0.12 *** Age Squared  Mean Age  0.02 0.006 Household Family Income x 10,000 0.54 0.51 Income Data Missing  3.23 5.72 Employment: Full Time 0.857 2.62 Member of an Environmental Organization  2.25 3.83 * Visited Lake or River in Last 12 Months 7.44 3.88 Number of Family Members in Household  0.37 0.92 Survey Location: Denver 0.58 3.60 Survey Location: Charlotte 5.17 4.21 Survey Location: Cary 3.28 4.28 * Survey Location: Research Triangle Park  6.88 3.62 Time in Minutes to Complete Conjoint Study 0.15 0.12 N 348 F Value 3.435 R square 0.1424 Dependent Variable: Cost of Living vs. Water Quality Level. ( Units are $ per 1% Improvement in Water Quality)

Higher value means willing to pay more for water quality improvement Parameter Standard Variable Estimate Error INTERCEP  8.16 7.51 Gender: Female 4.39 2.79 Race: Black  2.93 4.10 *** Race: Nonwhite, Nonblack  8.95 3.61 *** Age 0.38 0.13 ** Age Squared  Mean Age  0.01 0.01 ** Household Family Income x 10,000 1.3 0.59 Income Data Missing  3.64 6.48 Employment: Full Time 3.20 3.00 Member of an Environmental Organization  2.58 5.05 ** Visited Lake or River in Last 12 Months 7.86 3.93 Number of Family Members in Household 0.04 0.99 Survey Location: Denver 0.20 3.43 February 2000 138 Survey Location: Charlotte 4.37 4.02 Survey Location: Cary 2.55 4.12 * Time in Minutes to Complete Survey 0.25 0.14 N 242 F Value 3.692 R square 0.1968 February 2000 139 Exhibit 17: Cost of Living Valuation of Water Quality Linearity Tests A. Simple Statistics Cost of Living vs. Water Quality Level. N Mean StDev Median Low Water Quality Levels ( 25% 40%) 82 24.79 22.11 13.64 Middle Water Quality Levels ( 50% 65%, RTP) 106 20.70 24.24 13.33 Middle Water Quality Levels ( 50% 65%) 79 24.13 21.07 22.5 High Water Quality Levels ( 75% 90%) 81 20.36 21.77 10 This test indicates that willingness to pay is higher when water quality is low ( 25 40), and lower when water quality is high ( 75 90)

B. Regression Results Dependent Variable: Cost of Living vs. Water Quality Level. ( Units are $ per 1% Improvement in Water Quality)

Higher value means willing to pay more for water quality improvement Value for Variable Low, Middle, or High Water Quality reflects the lower bound of water quality in the tradeoff questions. Values are either 25%, 50% or 75%.

Parameter Standard Variable Estimate Error INTERCEP 1.87 7.52 Low, Middle, or High Water Quality  0.087 0.067 * Gender: Female 4.25 2.43 Race: Black  5.97 3.70 *** Race: Nonwhite, Nonblack  8.45 3.25 *** Age 0.45 0.12 *** Age Squared  Mean Age  0.02 0.006 Household Family Income x 10,000 0.56 0.51 Income Data Missing  2.89 5.72 Employment: Full Time 0.84 2.62 Member of an Environmental Organization  2.05 3.83 ** Visited Lake or River in Last 12 Months 7.62 3.88 Number of Family Members in Household  0.36 0.92 Survey Location: Denver 0.75 3.60 Survey Location: Charlotte 5.10 4.21 Survey Location: Cary 3.24 4.28 * Survey Location: Research Triangle Park  6.87 3.62 Time in Minutes to Complete Survey 0.14 0.12 February 2000 140 N 348 F Value 3.339 R square 0.1468 Dependent Variable: Cost of Living vs. Water Quality Level. Higher value means willing to pay more for water quality improvement ( Units are $ per 1% Improvement in Water Quality)

Value for Variable Low, Middle, or High Water Quality reflects the lower bound of water quality in the tradeoff questions. Values are either 25%, 50% or 75%. Parameter Standard Variable Estimate Error INTERCEP  3.61 8.13 Low, Medium, or High Water Quality  0.09 0.06 Gender: Female 4.23 2.79 Race: Black  2.82 4.09 *** Race: Nonwhite, Nonblack  9.16 3.60 *** Age 0.38 0.13 ** Age Squared  Mean Age  0.015 0.007 ** Household Family Income x 10,000 1.37 0.59 Income Data Missing  3.15 6.47 Employment: Full Time 3.18 2.99 Member of an Environmental Organization  2.18 5.05 ** Visited Lake or River in Last 12 Months 8.07 3.92 Number of Family Members in Household 0.06 0.99 Survey Location: Denver 0.36 3.42 Survey Location: Charlotte 4.26 4.01 Survey Location: Cary 2.51 4.11 * Time in Minutes to Complete Survey 0.24 0.14 N 242 F Value 3.609 R square 0.2042 February 2000 141 Exhibit 18: Sample Referendum Water Quality Task ====================================================================== Yes / No Policy Questions Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

This policy, through additional taxes, would increase your cost of living by $ 150 per year.

====================================================================== Imagine again that you have recently moved to another region of the country, where water quality is 50% Good.

Imagine that the government is considering a policy that would increase water quality in your region from 50% Good to 65% Good.

This policy, through additional taxes, would increase your cost of living by $ 150 per year.

Would you be in favor of this policy? 1. Yes 2. No ====================================================================== February 2000 142 Exhibit 19: Overall Referendum Water Quality Tradeoff Values Cost of Living vs. Water Quality Level, policy choice question ( Units are $ per 1% Improvement in Water Quality)

Sample N Mean StDev Median All 348 20.5 18.0 18.6 Cary 44 27.0 20.8 22.5 Charlotte 44 22.5 20.4 15.0 Colorado Spr. 74 22.0 19.8 18.3 Denver 80 24.2 20.9 22.5 RTP 106 13.0 5.7 12.0 RTP Excluded 242 23.7 20.4 22.5 February 2000 143 Exhibit 20: Regression Estimates for Referendum Water Quality Values Dependent Variable: Cost of Living vs. Water Quality Level, policy choice question ( Units are $ per 1% Improvement in Water Quality)

Higher value means willing to pay more for water quality improvement Parameter Standard Variable Estimate Error *** INTERCEP 20.02 5.43 Gender: Female 0.06 1.95 Race: Black  2.47 2.97 * Race: Nonwhite, Nonblack  4.65 2.61 Age 0.03 0.10 ** Age Squared  Mean Age  0.011 0.0049 Household Family Income x 10,000 0.17 0.41 Income Data Missing  1.32 4.59 Employment: Full Time 0.85 2.10 Member of an Environmental Organization 2.47 3.08 Visited Lake or River in Last 12 Months 0.09 3.12 ** Number of Family Members in Household  1.45 0.74 Survey Location: Denver 3.23 2.89 Survey Location: Charlotte 0.33 3.38 Survey Location: Cary 5.17 3.44 *** Survey Location: Research Triangle Park  11.13 2.91 *** Time in Minutes to Complete Study 0.25 0.10 N 348 F Value 3.238 R square 0.1353 Dependent Variable: Cost of Living vs. Water Quality Level, policy choice question ( Units are $ per 1% Improvement in Water Quality)

Higher value means willing to pay more for water quality improvement Parameter Standard Variable Estimate Error ** INTERCEP 15.80 7.54 Gender: Female 0.32 2.81 Race: Black  2.41 4.12 * Race: Nonwhite, Nonblack  6.15 3.62 Age 0.06 0.13 ** Age Squared  Mean Age  0.014 0.0070 Household Family Income x 10,000 0.19 0.60 Income Data Missing 0.41 6.51 Employment: Full Time 2.71 3.01 Member of an Environmental Organization 6.63 5.07 Visited Lake or River in Last 12 Months  1.09 3.94 Number of Family Members in Household  1.35 0.99 Survey Location: Denver 3.31 3.44 February 2000 144 Survey Location: Charlotte  0.42 4.04 Survey Location: Cary 5.20 4.14 *** Time in Minutes to Complete Study 0.37 0.14 N 242 F Value 1.439 R square 0.0872 February 2000 145 Exhibit 21: Comparison of Cost of Living Tradeoff and Referendum Values Cost of Living vs. Water Quality Level. ( Units are $ per 1% Improvement in Water Quality)

N Mean StDev Median All 348 22.4 22.5 13.3 Cary 44 24.0 20.8 18.8 Charlotte 44 28.5 23.9 22.5 Colorado Spr. 74 20.1 20.0 11.3 Denver 80 22.4 22.1 13.6 RTP 106 20.7 24.2 13.3 RTP Excluded 242 23.1 21.7 13.6 Cost of Living vs. Water Quality Level, policy choice question ( Units are $ per 1% Improvement in Water Quality)

N Mean StDev Median All 348 20.5 18.0 18.6 Cary 44 27.0 20.8 22.5 Charlotte 44 22.5 20.4 15.0 Colorado Spr. 74 22.0 19.8 18.3 Denver 80 24.2 20.9 22.5 RTP 106 13.0 5.7 12.0 RTP Excluded 242 23.7 20.4 22.5 The values for Cost of Living vs. Water Quality Level were sorted by ascending value, and split into four quartiles. Each of these quartiles were then compared to the corresponding Cost of Living vs. Water Quality Level, policy choice question for the observations within that quartile.

Cost of Living vs. Water Quality Level, policy choice question ( Units are $ per 1% Improvement in Water Quality) Policy Choice N Mean Std Dev Min Max Cost of Living vs. Water Quality Level, 1st Quartile 87 12.89 10.57 0.83 80 Cost of Living vs. Water Quality Level, 2nd Quartile 87 20.08 18.49 0.83 80 Cost of Living vs. Water Quality Level, 3rd Quartile 87 22.24 15.18 0.83 80 Cost of Living vs. Water Quality Level, 4th Quartile 87 26.73 22.78 0.83 80 February 2000 146 Exhibit 22: Sample Lakes and Rivers Task ============================================================================= Differences in Water Quality Between Lakes and Rivers Some questions in this survey have asked you to choose between regions based on water quality for both lakes and rivers.

Now, we would like to ask you some questions that ask you to choose between regions based upon water quality differences where lakes have a different level of water quality than rivers.

============================================================================= Which is more important to you?

1. Good water quality for lakes 2. Good water quality for rivers 3. Both are equally important to me ============================================================================= Try this sample question about lake and river water quality. Which of the two regions below would you choose if you had to move to one of them? Remember that both regions are alike in all other ways to where you live now, including the number of lake acres and river miles in your region. Which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Percent of river Miles With Good 50% 75% Water Quality Percent of lake Acres With Good 50% 75% Water Quality ============================================================================= The question was not clear.

You chose to move to the region with worse water quality for both lakes and rivers.

You could have chosen a region with better water quality for both lakes and rivers that is alike in all other ways.

To change your answer, press any key and we will ask the question again.

Otherwise, please tell the interviewer you do not want to change your answer. ============================================================================= The Region you chose, Region 2, has better water quality than Region 1 for both lakes and rivers.

Now we would like to ask some more questions like these, but whose answers depend more on how you value water quality differences between lakes and rivers. ============================================================================= You indicated that you have no preference between two regions whose only difference is that one has better water quality for both lakes and rivers than the other.

Are you sure that you don't care whether you would move to a region where a lower proportion of lakes and rivers are safe and clean. After all, you could move to a region with more lakes and February 2000 147 rivers that are safe and clean that is alike in all other ways.

1. Yes, I'm sure that I have no preference 2. No, I'm not sure, ask the question again ============================================================================= Now we would like to ask you some more questions like these. However, in the next questions, one region will have a higher level of water quality for rivers, and the other will have a higher level of water quality for lakes. Which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Percent of river 50% 75% Miles With Good Water Quality Percent of lake 75% 50% Acres With Good Water Quality ============================================================================= February 2000 148 Exhibit 23: Sample Aesthetic Properties Task ============================================================================= Aesthetic Properties Other aspects of water quality for lakes and rivers do not affect whether the water is safe to use, but may affect your enjoyment of activities at a lake or river.

Two such aspects are whether the water in the lake or river is:

* Smelly, meaning that the water in the lake or river has an unpleasant odor, even though it is otherwise good.

* Cloudy, meaning that the water in the lake or river is dark brown from sediment, green from algae, or is colored or murky for any other reason, even though it is otherwise good.

============================================================================= How important is it to you that water in lakes and rivers not be smelly?

1. Not at all important 2. Somewhat important 3. Quite important 4. Very important ============================================================================= Imagine that you have moved to a region where 50% of lakes acres and river miles have Good Quality and are not Smelly, and the other 50% do not have Good Quality and are Smelly. Suppose you had to decide between two government policies that improve the quality of the 50% of water that does not have Good Quality and is Smelly.

* Policy 1 increases the percent of water with Good Quality, but the water improved remains Smelly.

* Policy 2 increases the percent of water with Good Quality and removes any Smell, but does so on fewer lakes and rivers than Policy 1.

============================================================================= Imagine that you have moved to a region where 50% of lakes acres and river miles have Good Quality and are not Smelly, and the other 50% do not have Good Quality and are Smelly. Which policy would you prefer?

Aspect of 1. Policy 1 2. Policy 2 3. No Preference Water Improved Between Policies % Good Quality 25% 15% Improvement Improvement % Without Smell 0% 15% Improvement Improvement ============================================================================= Those are all the questions we will ask about smelly water.

Now the questions will ask you about how you feel about cloudy water and water quality for lakes and rivers.

============================================================================= How important is it to you that water in lakes and rivers February 2000 149 not be cloudy?

1. Not at all important 2. Somewhat important 3. Quite important 4. Very important ============================================================================= Imagine that you have moved to a region where 50% of lakes acres and river miles have Good Quality and are not Cloudy, and the other 50% do not have Good Quality and are Cloudy. Suppose you had to decide between two government policies that would improve the quality of the 50% of water that does not have Good Quality and is Cloudy.

* Policy 1 increases the percent of water with Good Quality, but the water improved remains Cloudy.

* Policy 2 increases the percent of water with Good Quality and removes any Cloudiness, but does so on fewer lakes and rivers than Policy 1.

============================================================================= Imagine that you have moved to a region where 50% of lakes acres and river miles have Good Quality and are not Cloudy, and the other 50% do not have Good Quality and are Cloudy. Which policy would you prefer?

Aspect of 1. Policy 1 2. Policy 2 3. No Preference Water Improved Between Policies % Good Quality 25% 15% Improvement Improvement % With Clear Water 0% 15% Improvement Improvement ============================================================================= February 2000 150 Exhibit 24: Sample Sources of Pollution Task ============================================================================= Sources of Pollution Pollution in lakes and rivers that hurts water quality can come from different sources. We will talk about two sources of pollution:

* Animal Wastes, where rain runoff from animal holding areas on farms can wash animal wastes into lakes and rivers.

* Industrial Toxic Wastes, where toxic chemicals from businesses pollute lakes and rivers.

============================================================================= We would like to ask you some questions about how you feel about sources of pollution and water quality. Keep in mind that these regions are the same in all other ways, including the number of acres of lakes and miles of rivers near your home. The regions are not different in the types of industries in the regions, just the ones polluting lakes and rivers. Which region would you prefer?

1. Region 1 2. Region 2 3. No Preference Between Regions Percent of Water 75% 75% With Good Quality:

Source of Animal Industrial Pollution for Wastes Toxic Lakes and Rivers Wastes ============================================================================= February 2000 151 Exhibit 25: Lake Quality Versus River Quality Summary Statistics Lake Water Quality vs. River Water Quality. ( Units are % Improvement in River Quality necessary to forego 1% Improvement in Lake Quality)

N Mean StDev Median All 346 2.10 2.77 1 Cary 44 1.70 2.44 1 Charlotte 44 1.96 2.77 1 Colorado Spr. 74 2.41 3.36 1 Denver 80 2.16 2.88 1 RTP 104 2.05 2.34 1 RTP Excluded 242 2.12 2.94 1 February 2000 152 Exhibit 26: Smelly Water Quality Summary Statistics Smelly Water vs. Overall Water Quality Level. ( Units are % Improvement in Water Quality for water that is Smelly necessary to forego 1% Improvement in Water Quality that is Not Smelly) N Mean StDev Median All 348 3.66 3.23 2.14 Cary 44 3.74 3.19 2.17 Charlotte 44 4.75 3.83 3.75 Colorado Spr. 74 3.60 3.42 1.85 Denver 80 4.51 3.76 3.13 RTP 106 2.58 1.85 1.92 RTP Excluded 242 4.14 3.58 2.17 February 2000 153 Exhibit 27: Cloudy Water Quality Summary Statistics Cloudy Water vs. Overall Water Quality Level. ( Units are % Improvement in Water Quality for water that is Cloudy necessary to forego 1% Improvement in Water Quality that is Not Cloudy)

N Mean StDev Median All 348 2.79 2.89 1.67 Cary 44 2.67 2.55 1.67 Charlotte 44 3.34 3.34 1.73 Colorado Spr. 74 3.06 2.98 1.67 Denver 80 3.97 3.56 2.05 RTP 106 1.82 1.58 1 RTP Excluded 242 3.34 3.20 1.79 February 2000 154 Exhibit 28: Toxic Water Quality Summary Statistics Source of Water Pollution. ( Units are % Difference in Water Quality at which Subjects are indifferent between Agricultural Waste or Industrial Toxic Waste as the source of pollution in their region. A Negative number indicates the subject is willing to incur a decrease in overall water quality to have pollution caused by Agricultural Waste instead of Industrial Toxic Waste. A Positive number indicates the subject is willing to incur a decrease in overall water quality to have pollution caused by Industrial Toxic Waste instead of Agricultural Waste.)