SUPPORTING STATEMENT FOR INFORMATION COLLECTION REQUEST FOR

WILLINGNESS TO PAY SURVEY FOR §316(B) EXISTING FACILITIES COOLING WATER INTAKE 

STRUCTURES: INSTRUMENT, PRE-TEST, AND IMPLEMENTATION
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TABLE OF CONTENTS 

PART A OF THE SUPPORTING STATEMENT ......................................................................... 1

1. Identification of the Information Collection ....................................................................... 1 

1(a) Title of the Information Collection ..................................................................................... 1 

1(b) Short Characterization (Abstract) ....................................................................................... 1

2. Need For and Use of the Collection .................................................................................... 5 

2(a) Need/Authority for the Collection ...................................................................................... 5

2(b) Practical Utility/Users of the Data ...................................................................................... 5

3. Non-duplication, Consultations, and Other Collection Criteria.......................................... 5 

3(a) Non-duplication .................................................................................................................. 5 

3(b) Public Notice Required Prior to ICR Submission to OMB ................................................ 7 

3(c) Consultations..................................................................................................................... 12 

3(d) Effects of Less Frequent Collection .................................................................................. 13 

3(e) General Guidelines ............................................................................................................ 14 

3(f) Confidentiality .................................................................................................................. 14 

3(g) Sensitive Questions ........................................................................................................... 14

4. The Respondents and the Information Requested ............................................................ 14 

4(a) Respondents ...................................................................................................................... 14 

4(b) Information Requested ...................................................................................................... 16 

(I) Data items, including recordkeeping requirements .......................................................... 16 

(II) Respondent activities ........................................................................................................ 20

5. The Information Collected - Agency Activities, Collection Methodology, and 

Information Management .............................................................................................................. 21 

5(a) Agency Activities .............................................................................................................. 21 

5(b) Collection Methodology and Information Management ................................................... 22 

5(c) Small Entity Flexibility ..................................................................................................... 23 

5(d) Collection Schedule .......................................................................................................... 23 
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6. Estimating Respondent Burden and Cost of Collection ................................................... 24 

6(a) Estimating Respondent Burden......................................................................................... 24 

6(b) Estimating Respondent Costs ........................................................................................... 24

6(c) Estimating Agency Burden and Costs .............................................................................. 25 

6(d) Respondent Universe and Total Burden Costs ................................................................. 25 

6(e) Bottom Line Burden Hours and Costs .............................................................................. 26 

6(f) Reasons for Change in Burden ......................................................................................... 26 

6(g) Burden Statement .............................................................................................................. 26

PART B OF THE SUPPORTING STATEMENT ....................................................................... 28

1. Survey Objectives, Key Variables, and Other Preliminaries ............................................ 28 

1(a) Survey Objectives ............................................................................................................. 28 

1(b) Key Variables.................................................................................................................... 28 

1(c) Statistical Approach .......................................................................................................... 29 

1(d) Feasibility .......................................................................................................................... 29

2. Survey Design ................................................................................................................... 30 

2(a) Target Population and Coverage ....................................................................................... 30 

2(b) Sampling Design ............................................................................................................... 30 

(I) Sampling Frames .............................................................................................................. 30 

(II) Sample Sizes ..................................................................................................................... 31 

(III) Stratification Variables ..................................................................................................... 31 

(IV) Sampling Method .............................................................................................................. 32 

(V) Multi-Stage Sampling ....................................................................................................... 33 

2(c) Precision Requirements .................................................................................................... 33 

(I) Precision Targets ............................................................................................................... 33 

(II) Non-Sampling Errors ........................................................................................................ 33 

2(d) Questionnaire Design ........................................................................................................ 36

3. Pretests and Pilot Tests ..................................................................................................... 37

4. Collection Methods and Follow-up .................................................................................. 38 

4(a) Collection Methods ........................................................................................................... 38 
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4(b) Survey Response and Follow-up ...................................................................................... 38

5. Analyzing and Reporting Survey Results ......................................................................... 39 

5(a) Data Preparation ................................................................................................................ 39 

5(b) Analysis............................................................................................................................. 40

5(c) Reporting Results .............................................................................................................. 57 

REFERENCES ............................................................................................................................. 58

ATTACHMENTS 

Attachment 1: Full Text of State Preference Survey Component ................................................. 68 

Attachment 2: Federal Register Notice ......................................................................................... 93 

Attachment 3: Description of Statistical Survey Design ............................................................ 103 

Attachment 4: Description of Internet-based Sampling Alternative ........................................... 109 

Attachment 5: Telephone Screener Script .................................................................................. 113 

TABLES 

Table A1: Geographic Stratification Design ................................................................................. 15

Table A2: Schedule for Survey Implementation .......................................................................... 24

Table A3: Total Estimated Bottom Line Burden and Cost Summary .......................................... 26 

Table B1: Number of Households and Household Sample for Each EPA Study Region ............ 33 

Table B2: Illustration of an External Scope Test ......................................................................... 55 
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PART A OF THE SUPPORTING STATEMENT 

1. Identification of the Information Collection 

1(a) Title of the Information Collection 

Willingness to Pay Survey for Section 316(b) Existing Facilities Cooling Water Intake 

Structures: Instrument, Pre-test, and Implementation 

1(b) Short Characterization (Abstract) 

On February 16, 2004, the U.S. Environmental Protection Agency (EPA) took final 

action on the Phase II rule governing cooling water intake structures at existing facilities that are 

point sources; that, as their primary activity, both generate and transmit electric power or 

generate electric power for sale to another entity for transmission; that use or propose to use 

cooling water intake structures with a total design intake flow of 50 MGD or more to withdraw 

cooling water from waters of the United States; and that use at least 25 percent of the withdrawn 

water exclusively for cooling purposes. See 69 FR 41576 (July 9, 2004). Industry and 

environmental stakeholders challenged the Phase II regulations. On judicial review, the Second 

Circuit (Riverkeeper, Inc. v. EPA, 475 F.3d 83, (2d Cir., 2007)) remanded several provisions of 

the Phase II rule. Some key provisions remanded are as follows: EPA improperly used a costbenefit analysis as a criterion for determining Best Technology Available (BTA), and EPA 

inappropriately used ranges in setting performance expectations. In response, EPA suspended the 

Phase II regulation in July 2007 pending further rulemaking. The U.S. Supreme Court granted 

Entergy Corporation’s petition for writ of certiorari, solely on the question of whether EPA had 

the authority under §316(b) of the Clean Water Act to consider costs and benefits in decisionmaking. On April 1, 2009, the Court, in Entergy Corp. v. Riverkeeper Inc., decided that “EPA 

permissibly relied on cost-benefit analysis in setting the national performance standards ... as 

part of the Phase II regulations.” EPA is now taking a voluntary remand of the rule, thus ending 

Second Circuit review. 

On June 1, 2006, EPA promulgated the 316(b) Phase III Rule for existing manufacturers, 

small flow power plants (facilities that use cooling water intake structures with a total design 
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intake flow of less than 50 MGD to withdraw cooling water from waters of the United States; 

and that use at least 25 percent of the withdrawn water exclusively for cooling purposes), and 

new offshore oil and gas facilities. Offshore oil and gas firms and environmental groups 

petitioned for judicial review, which was to occur in the Fifth Circuit, but was stayed pending the 

Supreme Court decision on the Phase II case. EPA has petitioned the Court for a voluntary 

remand of the existing facilities portion of the Phase III rulemaking. In developing the Phase III 

regulation, EPA began, but did not complete, a similar stated preference survey effort. The 

current effort builds on that earlier work. 

EPA is now combining the two phases into one rulemaking covering all existing 

facilities. EPA will develop regulations to provide national performance standards for controlling 

impacts from existing cooling water intake structures (CWIS) under Section 316(b) of the Clean 

Water Act (CWA). 

Under Executive Order 12866, EPA is required to estimate the potential benefits and 

costs to society. To assess the public policy significance or importance of the ecological gains 

from the section 316(b) regulation for existing facilities, EPA requests approval from the Office 

of Management and Budget to conduct a stated preference survey and analysis. Data from the 

associated stated preference survey will be used to estimate the values (willingness to pay, or 

WTP) derived by households for changes related to the reduction of fish losses at CWIS, and to 

provide information to assist in the interpretation and validation of survey responses. As 

indicated in the prior literature (Cummings and Harrison 1995; Johnston et al. 2003, 2005), it is 

virtually impossible to justify, theoretically, the decomposition of empirical estimates of use and 

non-use values. The survey will provide the flexibility, however, to estimate nonuser values, 

using various nonuser definitions drawn from responses to survey questions 11 to 13. The 

structure of choice attribute questions will also allow the analysis to separate value components 

related to the most common sources of use values—effect on harvested recreational and 

commercial fish. The remaining welfare estimates are expected to be composed primarily of 

non-use components, although some use value components might also be included for some 

respondents. In summary, the survey will provide estimates of total use plus non-use values, will 

allow estimates of value associated with specific choice attributes (following standard methods 

for choice experiments), and will also allow the flexibility to provide some insight into the 

relative importance of use versus non-use values in the 316(b) context. 
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Within rulemaking, among the most crucial concerns is the avoidance of benefit (or cost) 

double counting. Here, for example, the WTP estimates will include use and non-use values 

among a representative population sample. These may overlap—to a potentially substantial 

extent—with use value estimates that might be provided through some other methods, including 

revealed preference methods that might be used to estimate use values of recreational anglers for 

fish kill reductions (i.e., through related improvements in fishing quality). While using the 

proposed stated preference value estimates for benefit estimation, particular care will be given to 

avoid any possible double counting of values that might be derived from alternative valuation 

methods. In doing so, the Office of Water will rely upon standard theoretical tools for nonmarket welfare analysis, as presented by authors including Freeman (2003) and Just et al. (2004). 

From a purely mechanistic perspective, survey results will be used to derive use and non-use 

values following standard practice for choice experiments (Adamowicz et al. 1998). 

The target population for this stated preference survey is all individuals from continental 

U.S. households who are 18 years of age or older. The population of households will be 

stratified by the geographic boundaries of 5 EPA study regions: California, Great Lakes, Inland, 

Northeast, and Southeast. The Northeast survey region includes the North Atlantic and Mid 

Atlantic 316(b) benefits regions and the Southeast survey region includes the South Atlantic and 

Gulf of Mexico 316(b) benefits regions. Respondents will be recruited using a random digit 

dialing (RDD) sample (overlapping dual frame; land and cell) and a brief telephone 

questionnaire. Participation in the survey is voluntary. If the person in the household agrees, the 

recruited respondent will be asked to complete the survey questionnaire by mail. EPA intends to 

administer the mail survey to 5,000 households in order to achieve 2,000 completed responses 

assuming a 40% completion rate for households agreeing to participate. EPA is also considering 

implementing the proposed survey as an internet-based, choice experiment questionnaire. This 

alternative approach is described in Attachment 4. 

For the selection of households, the population of households in the 48 states will be 

stratified by the 5 EPA regions. The sample is allocated to each region in proportion to the total 

number of households in that region with the restriction that we get at least 288 persons in each 

region. Non-response bias has the potential to occur due to households declining to participate in 

the mail survey when contacted by phone and households which fail to return a completed 

survey after agreeing to participate. To conduct a non-response study, EPA will use a brief 

telephone questionnaire to collect sample characteristics in the course of the telephone contact. 
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EPA will analyze the characteristics of the completed and non-completed cases from the random 

digit dialing sample to determine whether there is any evidence of significant non-response bias 

in the completed sample. This analysis will suggest whether any weighting or statistical 

adjustment needs to be used to minimize the non-response bias in the completed sample. 

As part of the testing of the survey instrument, EPA is in the process of requesting and 

obtaining approval from the Office of Management and Budget to conduct a series of eight focus 

groups with a total of 80 respondents (10 participants per focus group). Because focus groups in 

different study regions might provide distinct information relevant to survey design the Agency 

will conduct focus groups in multiple regions. These focus groups will be conducted following 

standard, accepted practices in the stated preference literature, as outlined by Mitchell and 

Carson (1989), Desvousges et al. (1984), Desvousges and Smith (1988) and Johnston et al. 

(1995). Some of the focus groups will incorporate individual cognitive interviews, as detailed 

by Kaplowicz et al. (2004). The focus groups and cognitive interviews will allow EPA to better 

understand the public's perceptions and attitudes concerning fishery resources, to frame and 

define survey questions, to pretest draft survey questions, to test for and reduce potential biases 

that may be associated with stated preference methodology, and to ensure that both researchers 

and respondents have similar interpretations of survey language and scenarios. In particular, 

cognitive interviews will allow in-depth exploration of the cognitive processes used by 

respondents to answer survey questions, without the potential for interpersonal dynamics to sway 

respondents’ comments (Kaplowicz et al. 2004). These eight focus groups will be conducted in 

addition to focus groups conducted previously by EPA under ICR #2155.01 to test the draft 

survey for the Phase III benefits analysis. Transcripts from the previously conducted focus 

groups can be found in the docket for EPA ICR #2155.02 (Besedin et al., 2005). Findings from 

these previous focus groups were incorporated into the development of the current survey. 

The total national burden estimate for all components of the survey is 1,527 hours. The 

burden estimate is based on 8,333 participants in telephone screening interviews and 2,000 

respondents to the 5,000 mailed questionnaires. EPA assumes an average burden estimate of 5 

minutes per telephone screening participant and 30 minutes per mail survey respondent including 

the time necessary to complete and mail back the questionnaire. Given an average wage rate of 

$20.42, the total respondent cost is $34,600. 
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2. Need For and Use of the Collection 

2(a) Need/Authority for the Collection 

The project is being undertaken pursuant to section 104 of the Clean Water Act dealing 

with research. Section 104 of the Clean Water Act authorizes and directs the EPA Administrator 

to conduct research into a number of subject areas related to water quality, water pollution, and 

water pollution prevention and abatement. This section also authorizes the EPA Administrator to 

conduct research into methods of analyzing the costs and benefits of programs carried out under 

the Clean Water Act. 

This project is exploring how public values for fishery resources (covering both use and 

non-use values) are affected by fish losses from impingement and entrainment at cooling water 

intake structures. Understanding total public values, including the more difficult to estimate 

non-use values, for fishery resources is necessary to determine the full range of benefits 

associated with reductions in impingement and entrainment losses, and whether the benefits of 

government action to reduce impingement and entrainment losses at existing facilities are 

commensurate with the costs of such actions. Because non-use values may be substantial, failure 

to recognize such values may lead to improper inferences regarding benefits and costs. The 

findings from this study will be used by EPA to improve estimates of the economic benefits of 

the section 316(b) regulation for existing facilities as required under Executive Order 12866. 

2(b) Practical Utility/Users of the Data 

 

EPA plans to use the results of the survey to improve estimates of the economic benefits 

of the section 316(b) regulation for existing facilities. Specifically, the Agency will use the 

survey results to estimate total values for preventing losses of fish through impingement and 

entrainment at CWIS, following standard practices outlined in the literature (Freeman 2003; 

Bennett and Blamey 2001; Louviere et al. 2000; U.S. EPA 2000). 

3. Non-duplication, Consultations, and Other Collection Criteria 

3(a) Non-duplication 
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EPA has not identified any previous studies that would allow direct estimation of the 

social benefits of nationwide reductions in fish losses for all species (including forage, 

recreational, and commercial species) affected by the proposed 316(b) regulation. Therefore, to 

the best of our knowledge this survey is unique and does not duplicate other efforts. 

There are many studies in the environmental economics literature that quantify benefits 

or willingness to pay (WTP) associated with various types of water quality and aquatic habitat 

changes. However, none of these studies allows the isolation of non-market WTP associated with 

quantified reductions in fish losses for forage fish. Most available studies estimate WTP for 

broader, and sometimes ambiguously defined, policies that simultaneously influence many 

different aspects of aquatic environmental quality and ecosystem services, but for which WTP 

associated with fish or aquatic life alone cannot be identified. Other studies provide benefit 

estimates associated with improvements in fish (or aquatic) habitat, but do not link this to welldefined and quantified changes in affected or supported organisms. Still other studies address 

willingness to pay for changes in charismatic or recreational species that have little relationship 

to the types of forage fish that are the vast majority of species affected by cooling water intake 

structures. 

For example, choice experiment studies such as Hanley et al. (2006a, b) and Morrison 

and Bennett (2004) estimate WTP for aquatic ecosystem changes that affect fish, but the effects 

on fish are quantified and valued solely in terms of the presence/absence of different types of fish 

species. This approach renders associated results unsuitable for 316(b) benefit estimation. Also, 

many of these studies were conducted outside the U.S. (e.g., the European Union or Australia), 

making their use for benefit transfer to a U.S. policy context much more challenging. 

Other studies have estimated the value of changes in catch rates or populations of select 

recreational and commercial species, charismatic species such as salmon, or changes in water 

quality that affect fish, but none have specifically valued changes in forage fish populations. For 

example, Olsen et al. (1991) conducted a survey of Pacific Northwest residents, including both 

anglers and non-anglers, to determine their WTP for doubling the size of the Columbia River 

Basin salmon and steelhead runs. EPA’s proposed survey approach differs from this study and 

others like it (such as Cameron and Huppert, 1989) in that it would include respondents from 

various geographic regions in the United States and would provide values for the full range of 

forage, recreational, and commercial species affected by 316(b) regulations, instead of valuing a 

few recreational species in one specific geographical area. 
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Among available studies, the most closely related is Johnston et al. (2009), which 

estimates total willingness to pay (WTP) for multi-attribute aquatic ecosystem changes related to 

improvements in small migratory (diadromous) fish in Rhode Island. Unlike other studies, the 

choice experiment data of Johnston et al. (2009) allow estimation of WTP associated with 

quantified changes in forage fish (e.g., WTP per fish or percentage change in fish), holding other 

ecological effects constant. That is, unlike results provided by other studies in the literature, 

WTP estimates of Johnston et al. (2009) are not confounded with values for other changes 

including water quality, habitat, overall ecological condition, etc. In addition, the choice 

experiment of Johnston et al. (2009) addresses species such as alewife and blueback herring that 

are neither subject to recreational or commercial harvest in Rhode Island, nor are charismatic 

species. Hence, the species affected are a close analog to the forage fish that are at primary issue 

in the 316(b) policy context. 

Although the methods and data of Johnston et al. (2009) allow quantification of 

combined use and non-use values associated with specific improvements in forage and/or 

recreational fish, and also provide limited ability to isolate non-use values from use values, the 

policy context and scale of the survey prevent its direct use for analysis of national benefits of 

the 316(b) regulation. Specifically, Johnston et al. (2009) estimate Rhode Island residents’ 

preferences for the restoration of migratory fish passage over dams in the Pawtuxet and WoodPawcatuck watersheds. Hence, the case study is for a watershed-level policy with statewide 

welfare implications. In contrast, 316(b) policies would have nationwide implications, both on 

ecosystems and on affected facilities. 

3(b) Public Notice Required Prior to ICR Submission to OMB 

In accordance with the Paperwork Reduction Act (44 U.S.C. 3501 et seq.), EPA 

published a notice in the Federal Register on July 21, 2010, announcing that the survey 

questionnaire and sampling methodology are available for comment. A copy of the first Federal 

Register notice is attached at the end of this document (EPA ICR #2402.01.02) (See Attachment 

2). 

As mentioned in the abstract (section1(b)) this current survey effort grew out of work 

conducted for the Phase III rulemaking. EPA received a number of comments on that proposed 

Phase III information collection, which are summarized in the following paragraphs. Also see 
8

docket # EPA-HQ-OW-2005-0006. EPA considered relevant comments on the draft Phase III 

survey when developing the survey questionnaire and sampling methodology for the current 

survey for existing facilities. 

Several commenters stated that the Phase III survey would provide inaccurate estimates 

of WTP to prevent fish losses. One commenter argued that the presentation materials prepared 

by EPA contain inaccurate statements and invalid comparisons that would lead respondents to 

believe that the benefits of increased regulation of cooling water intakes would be substantially 

greater than is actually the case. A different commenter argued the opposite: that the proposed 

contingent valuation survey is biased against protecting ecosystems, and will drastically 

undervalue non-use benefits. EPA agrees that certain details of the Phase III survey and 

presentation materials provided in the supporting documentation for the June 9, 2005 Federal 

Register notice required revision. Following the June 9, 2005 Federal Register notice, EPA 

conducted four focus groups and two cognitive interview sessions to improve the Agency’s 

understanding of the public's perceptions and attitudes concerning fishery resources, to pretest 

draft survey questions and presentation materials, to test for and reduce potential biases that may 

be associated with stated preference methodology, and to ensure that both researchers and 

respondents have similar interpretations of survey language and scenarios. As a result of this 

extensive pre-testing, a number of revisions were made to the Phase III survey that significantly 

improved its reliability and reduced its potential for bias. These comments were considered 

when developing the current existing facilities survey. 

One commenter argued that the Phase III survey did not sufficiently emphasize the 

uncertainty in the estimates of the fish losses that would be prevented by the proposed policies. 

EPA points out that debriefing sessions during focus groups and cognitive interviews showed 

that respondents clearly understood that the ecological changes described in the survey were 

uncertain. Furthermore, respondents were comfortable making decisions in the presence of this 

uncertainty. Additionally, EPA emphasizes the uncertainty of the expected environmental 

changes within the current existing facilities survey. For example, the following statement is 

included in the current survey with accompanying graphs: “Scientists know that about 1.1 

billion young fish are lost per year in Northeast coastal waters due to cooling water use. But, 

scientists do not know the total number of fish in Northeast coastal waters. Studies of specific 

fish can provide some information on how many fish are lost, compared to the total number of 

fish in the water. Sometimes the number of fish lost is relatively small compared to the total 
9

number of adult fish – an example is striped bass (see graph below). Sometimes the number of 

fish lost is relatively large compared to the total number of adult fish – an example is winter 

flounder (see graph below). For many types of fish, the number of young fish lost compared to 

the total number of adult fish lies somewhere in between these extremes. Even though scientists 

can predict approximately the number of fish that will be saved, the ultimate effects on fish 

populations (the number of fish in the water) is uncertain.” EPA also added debriefing questions 

to the survey instrument that are designed to identify individuals whose responses are based on 

incorrect interpretation of the environmental changes described in the survey, including the 

uncertainty of the expected changes. 

The same commenter on the Phase III survey also argued that the benefits of regulating 

cooling water intake structures for recreationally and commercially significant species are 

already reflected in the EPA’s RIA for the proposed rule for Phase III facilities. EPA disagrees 

with the commenter’s statement. As stated by Freeman, “Non-use values, like use values, have 

their basis in the theory of individual preferences and the measurement of welfare changes. 

According to theory, use and non-use values are additive” (Freeman, 2003). EPA notes that the 

non-use benefits of the proposed regulation are a completely separate category of value from the 

commercial and recreational welfare effects of the proposed rule. Furthermore, results from the 

previous focus groups and cognitive interviews indicated that some individuals hold substantial 

non-use values for protecting fish species with direct uses, in addition to any use values that they 

have for those species. 

As indicated on pages 2 and 3 above, the survey will be used to estimate total values 

(WTP) derived by households for changes related to the reduction of fish losses at CWIS. 

Therefore EPA will take particular care to avoid any possible double counting of benefits values 

that might be derived from alternative valuation methods. 

The commenter also argued that the survey is unnecessary because in independently 

conducted verbal protocol interviews with 15 individuals, respondents did not demonstrate 

meaningful values for marginal changes in forage fish populations. EPA notes that this finding 

contradicts the results of the EPA focus groups and cognitive interviews conducted under ICR 

#2155.01. These focus groups and interviews provided strong evidence that many individuals 

value forage fish and are willing to pay to prevent losses of all fish species including forage fish. 

Participants in the EPA focus groups and interviews cited a variety of motivations for preventing 

fish losses, including the satisfaction of knowing that the fish exist, the desire to bequeath 
10

healthy fish populations to future generations, and the desire to protect the functioning of aquatic 

ecosystems. Furthermore, EPA notes that the economic literature advises against the use of ad 

hoc, expert assumptions regarding the magnitude of non-use values—particularly assumptions 

that non-use values are trivial. Because values are inherently subjective, Bateman et al. (2002, p. 

75) emphasize that “it would be wrong for experts to assume that one resource is a perfectly 

good substitute for another” [and hence that non-use values are trivial or small]. As further 

noted by Bateman et al. (2002, p. 75), “there are, therefore, no easy rules for determining at the 

outset” whether non-use values are likely to be significant or non-significant. Based on this clear 

guidance, EPA believes that empirical analysis should be used to determine the magnitude of 

non-use values in the 316(b) regulation for existing facilities. 

The commenter argued that because the survey materials are based on unreliable 

population and fish losses data, the survey results will also be unreliable. In response, EPA first 

notes that the survey materials are based on the best biological and engineering data available. 

Second, even if this data is uncertain, the stated preference survey will still produce results that 

are meaningful in the context of the scenarios that are presented to respondents. Different 

versions of the 316(b) survey will show a range of different baseline and resource improvement 

levels, where these levels are chosen to almost certainly bound actual levels. Different 

respondents will be asked to make choices over all possible policy scenarios where impingement 

and entrainment reductions range from 0% (no policy) to 98%. Given that there will almost 

certainly be some biological uncertainty regarding the specifics of the actual baselines and 

improvements, the resulting valuation estimates will allow flexibility in estimating WTP for a 

wide range of different circumstances. 

Finally, the commenter expressed the opinion that the survey should be peer reviewed by 

an independent panel of experts. EPA conducted an external peer review of the previous version 

of the survey instrument focusing on (1) the appropriateness of the survey design for measuring 

fish resources affected by cooling water intake structures (CWIS), (2) sufficiency and 

appropriateness of information provided in the survey on the baseline ecological conditions, the 

expected changes, and the expected costs, and (3) whether the answers to this survey lend 

themselves to straightforward economic interpretation of WTP. Reviewers offered concrete 

suggestions for further improvements of the survey instrument. EPA has incorporated many of 

the reviewers’ comments in this new existing facilities survey (Versar, 2006). 
11

Another commenter argued that neither the Clean Water Act nor section 316(b) require or 

allow EPA to use monetized cost-benefit analysis to determine regulatory standards for cooling 

water intake structures. However, the Supreme Court ruled that EPA does have the authority to 

consider costs and benefits in §316(b) regulations. EPA is also conducting this survey because of 

Executive Order 12866, “Regulatory Planning and Review,” which requires Federal Agencies to 

conduct economic impact and cost-benefit analysis for all major rules. Furthermore, cost-benefit 

analysis requires a comprehensive, estimate of total social benefits, including both use and nonuse values. The current information collection would provide valuable information that includes 

both use and non-use benefits of the 316(b) regulation for existing facilities, thus enabling the 

Agency to perform cost-benefit analysis for the regulation and to satisfy the requirements of 

Executive Order 12866. 

In addition to the comments received in response to the June 9, 2005 Federal Register 

notice for the Phase III survey, a number of the comments received by EPA in response to the 

previous focus group information collection request (EPA ICR #2155.01) are relevant to the 

current ICR. Most of these comments addressed the more general topic of resource valuation 

and stated preference surveys. Many of the claims made in the submitted comments represent 

empirical questions that were appropriately addressed within the survey design process. Some 

commenters argued that non-use benefits in the Phase III policy context are likely to be trivial. 

EPA points out that (1) these claims are unsubstantiated by the empirical literature and (2) that 

the magnitude of non-use benefits in the 316(b) existing facilities context is an empirical issue 

that can only be addressed with appropriate research methods. Even if non-use values for fish are 

small on a per-capita basis, they may be large in the aggregate. 

Commenters also questioned the reliability of the empirical estimates of total benefits of 

the Phase III regulation and thus the practical value of the information provided by the focus 

groups and stated preference survey. EPA believes, however, following guidance in the 

literature, that stated preference methods are capable of measuring total values (including use 

and non-use) of fish affected by impingement and entrainment, if surveys and approaches are 

appropriately designed. The Office of Management and Budget’s “Circular A-4" states that “a 

stated preference study may be the only way to obtain quantitative information about non-use 

values,” and EPA’s own guidance explicitly permits the use of stated preference methods for use 

and non-use value estimation (US EPA 2000), following prior findings of the NOAA Blue 

Ribbon Panel on Contingent Valuation (Arrow et al. 1993). EPA recognizes the difficulties 
12

faced in the design of appropriate stated preference survey instruments (focus groups), but does 

not consider these difficulties to be insurmountable. As stated by Freeman (2003, p. 154), stated 

preference survey methods “are likely to offer the only feasible approaches to estimating non-use 

values.” Furthermore, although the peer reviewed literature is highly skeptical of stated 

preference surveys that attempt to decompose use and non-use values, there is general conceptual 

acceptance that the total values of non-users can be used to approximate non-use values for all 

individuals (Cummings and Harrison 1995, Johnston et al. 2003a)1

. 

Finally, one commenter noted that if EPA is to consider non-use value effects on the 

benefit side of the regulation, then the Agency should also consider non market and non-use 

value effects on the cost side of the regulation, such as values for effects on mining, the 

efficiency of energy production, and the use of depletable resources. While EPA acknowledges 

the theoretical validity of this point, EPA knows of no precedents to guide design of a survey on 

non-use costs, nor does EPA expect economic impacts as significant as closures that would 

warrant further consideration of non-use costs. 

For a more detailed discussion of the issues raised by commenters on the previous Phase 

III survey ICR, see EPA’s response to pubic comments on the Federal Register notice published 

on June 9, 2005 (70 FR 33746). For a discussion of issues raised by commenters on the previous 

Phase III focus group ICR, see EPA's response to public comments on the Federal Register 

notice published on November 23, 2004 (69 FR 68140). 

3(c) Consultations 

 The Principal Investigator for the stated-preference portion of this effort is Dr. Robert 

Johnston. Dr. Johnston is assisted by Dr. Elena Besedin, a Senior Economist at Abt Associates 

Inc. Dr. Erik Helm at the U.S. Environmental Protection Agency serves as the project manager 

and a contributor to this research. 

Robert J. Johnston is Director of the George Perkins Marsh Institute and Professor of 

Economics at Clark University. He is President-elect of the Northeastern Agricultural and 

Resource Economics Association (NAREA), on the Program Committee for the Charles Darwin 

Foundation, the Science Advisory Board for the Communication Partnership for Science and the 

Sea (COMPASS), and is the Vice President of the Marine Resource Economics Foundation. 

Professor Johnston has published extensively on the valuation of non-market commodities 

 

1

 Note that by definition, total values for non-users are non-use values. 
13

(goods, services, and resources), benefit cost analysis, and resource management. His recent 

research emphasizes coordination of ecological and economic models to estimate ecosystem 

service values, with particular emphasis on the role of aquatic ecological indicators. He has also 

worked extensively in methodologies for benefit transfer, including the use of meta-analysis. 

Professor Johnston’s empirical work on non-market valuation and benefit transfer has 

contributed to numerous benefit cost analyses conducted by federal, state and local government 

agencies in the US, Canada and elsewhere. 

Elena Y. Besedin, a senior economist at Abt Associates Inc., specializes in the economic 

analysis of environmental policy and regulatory programs, Her work to support EPA has 

concentrated on analyzing economic benefits from reducing risks to the environment and human 

health and assessing environmental impacts of regulatory programs for many EPA program 

offices. She has worked extensively on valuation of non-market benefits associated with 

environmental improvements of aquatic resources. Dr. Besedin’s empirical work on non-market 

valuation includes design and implementation of stated and revealed preference studies and 

benefit transfer methodologies. Her recent work has focused on developing integrated 

frameworks to value changes in ecosystem services stemming from environmental regulations. 

EPA has conducted an external peer review of the previous version of the survey 

instrument. The previous version of the survey instrument was reviewed by Dr. Richard C. 

Bishop, Dr. Kevin J. Boyle, Dr. Timothy C. Haab, Dr. James R. Kahn, and Dr. Alan J. Krupnick. 

The review focused on (1) the appropriateness of the survey design for measuring fish resources 

affected by cooling water intake structures (CWIS), (2) sufficiency and appropriateness of 

information provided in the survey on the baseline ecological conditions, the expected changes, 

and the expected costs, and (3)whether the answers to this survey lend themselves to 

straightforward economic interpretation of WTP. The reviewers acknowledged the extensive 

effort that was placed into survey design and noted that the 316(b) survey was a well-designed 

study. They also offered concrete suggestions for further improvements of the survey 

instrument. EPA has incorporated many of the reviewers comments in this new survey for 316(b) 

existing facilities (Versar 2006, Docket ID No. EPA-HQ-OW-2004-0002-2007). 

3(d) Effects of Less Frequent Collection 

The survey is a one-time activity. Therefore, this section does not apply. 
14

3(e) General Guidelines 

The survey will not violate any of the general guidelines described in 5 CFR 1320.5 or in 

EPA’s ICR handbook. 

3(f) Confidentiality 

All responses to the survey will be kept strictly anonymous. To ensure that the final 

survey sample includes a representative and diverse population of individuals, the survey 

questionnaire will elicit basic demographic information, such as age, household size, 

employment status, and income. However, the survey questionnaire will not ask respondents for 

personal identifying information, such as names, phone numbers, or addresses. Prior to taking 

the survey, respondents will be informed that their responses will be held strictly anonymous. 

The survey data will be made public only after it has been thoroughly vetted to ensure that all 

potentially identifying information has been removed. 

3(g) Sensitive Questions 

The survey questionnaire will not include any sensitive questions pertaining to private or 

personal information, such as sexual behavior or religious beliefs. 

4. The Respondents and the Information Requested 

4(a) Respondents 

The target population for the Stated Preference Survey is all individuals from continental 

U.S. households who are 18 years of age or older. Survey participants are recruited randomly 

through random digit dialing. EPA will identify a random stratified sample of 5,000 adults who 

express their willingness to participate in a mail survey when contacted by telephone through 

random digit dialing. All of these recruits will be sent a copy of the mail survey. Approximately 

2,000 of the adults of the 5,000 adults sent a survey are expected to return a completed survey. 

For the selection of households, the population of households in the 48 states will be 

stratified by 5 study regions. There are a total of seven study regions for purposes of evaluating 
15

the 316(b) existing facilities rule benefits. For the purposes of the stated preference survey 

implementation, EPA uses five geographic regions: California, Great Lakes, Inland, Northeast, 

and Southeast. The Northeast region includes the North Atlantic and Mid Atlantic regions and 

the Southeast region includes the South Atlantic and Gulf of Mexico regions. The survey sample 

is allocated to each region in proportion to the total number households in that region with the 

restriction that we get at least 288 persons in each region. This is the number required to 

estimate the main effects and interactions under an experimental design model. The minimum 

sample size required for model estimation (i.e., 288 persons per region) may increase if revisions 

to the survey result in additional effects and interactions. However, an increase in the minimum 

sample size for a given region would have a negligible effect on the total sample size because the 

total sample size is much larger then the minimum sample size required for model estimation for 

all but one region (Inland). Part B of this document provides detail on sampling methodology. 

Table A1 shows the stratification design for the geographic regions covered by the 

sample for this survey. More detail on planned sampling methods and the statistical design of 

the survey can be found in Part B of this supporting statement. 

Table A1: Geographic Stratification Design 

Region States Included 

Sample 

Sizea

Percentage 

of Sample 

Northeast CT, DC,DE, MA, MD, ME, NH, 

NJ, NY, RI, VT 

301 15% 

Southeast AL, AR, FL, GA, KY, LA, MS, NC, OK, SC, TN, TX, VA, WV 626 31% 

Great Lakes IA, IL, IN, MI, MN, MO, OH, 

PA, WI 

461 23% 

Inland Region CO, ID, KS, MT, NE, ND, SD, 

UT, WY 

288 14% 

Pacific Mountain AZ, CA, NM, NV, OR, WA 324 16% 

Total, All Regions U.S. (excluding AK and HI) 2,000 100% 

a

 Sample sizes presented in this table include only the 2,000 individuals returning completed mail surveys. 
16

4(b) Information Requested 

(I) Data items, including recordkeeping requirements 

Individuals who agree to participate in the survey will be mailed a copy of the survey. 

The full text of the draft mail survey is provided in Attachment 1. EPA may revise the survey 

based on the findings of a series of eight additional focus groups designed to pretest the survey. 

EPA is expecting approval to conduct these focus goups under a different ICR (OMB control # 

2090-0028). Additional information regarding the focus groups implementation is provided in 

Section 5(b). EPA has determined that all questions in the survey are necessary to achieve the 

goal of this information collection, i.e., to collect data that can be used to support an analysis of 

the total benefits of the 316(b) regulation. 

The following is an outline of the major sections of the survey. 

Relative Importance of Issues Associated with Industrial Cooling Water. The first survey 

question asks respondents to rate the general importance of (a) reducing government regulations 

on facilities, (b) preventing losses of fish used by humans, (c) preventing losses of fish not used 

by humans, (d) maintaining ecological health in rivers, lakes, and bays, and (e) allowing facilities 

to produce products and services at low cost. This question is designed to elicit the respondent’s 

general preferences for regulation, reductions in fish losses, and ecological health. It also places 

respondents in the mindset where they are cognizant of the range of issues associated with the 

use of cooling water by industrial facilities. 

Concern for Policy Issues. The second survey question asks respondents to rate the general 

importance of a range of public policy issues, including both environmental and nonenvironmental issues. This question is designed to highlight the many important policy issues 

and substitute concerns to which respondents might choose to direct funds, rather than spending 

these funds to prevent fish losses. Such questions are commonly used in introductory sections of 

stated preference surveys (e.g., Mitchell and Carson 1984), in order to place respondents in a 

mindset in which they are cognizant of substitute goods and policy issues to which they might 

direct their scarce household budgets. 

Relative Importance of Effects. Question 3 asks the respondent to rate the importance of each 

of the effects captured by the five scores: (a) fish saved, (b) commercial fish sustainability, (c) 

fish population, (d) condition of aquatic ecosystems, and (e) cost per year. This question is 

designed to promote understanding of the scores by placing respondents in a mindset where they 

consider the meaning of each score and consider their general preferences for effects prior to 
17

considering specific policy options. The question also promotes understanding by telling the 

respondent that they can return to previous pages for reminders of what the scores mean. 

Voting for Regulations to Prevent Fish Losses in the Respondent’s Region. Questions 4, 5, 

and 6 are “choice experiment” or “choice modeling” questions (Adamowicz et al. 1998; Bennett 

and Blamey 2001), and ask respondents to choose how they would vote, if presented with two 

hypothetical regulatory options (and a third “status quo” choice to reject both options) for waters 

within the respondents’ region (e.g., Northeast waters). Each of the multi-attribute options is 

characterized by (a) fish saved per year (out of total fish lost in regional cooling water intakes), 

(b) commercial fish sustainability (in 3-5 years), (c) fish population (all fish; in 3-5 years), (d) 

condition of aquatic ecosystems (in 3-5 years), and (e) an unavoidable cost of living increase for 

the respondent’s household. Following standard choice experiment methods, respondents choose 

the regulatory options that they prefer, based on their preferences. Respondents always have the 

option to vote for neither option—providing the status quo option is necessary for appropriate 

welfare estimation (Adamowicz et al. 1998). Advantages of choice experiments, and the many 

examples of the use of such approaches in the literature, are discussed in later sections of this 

ICR. Following standard approaches (Opaluch et al. 1993, 1999; Johnston et al. 2002a, 2003b), 

respondents are instructed to answer each of the three choice questions independently, and not to 

“add up or compare programs across different pages.” This is included to avoid biases 

associated with sequence aggregation effects (Mitchell and Carson 1989). EPA will also 

randomize the order in which the policy option attributes are presented across respondents. This 

would allow for a statistical test of potential ordering effects. 

Reasons for Voting “No Policy”. Question 7 is a follow-up to the prior voting questions, and 

asks respondents to identify the primary reason for voting no, if they always voted for “no 

policy” in questions 4-6. It is designed to identify respondents whose “no policy” responses are 

based on their budget constraint, respondents who do not consider fish losses important enough 

to vote for a policy, or respondents who ignored information presented in the survey and 

answered questions based on their general convictions and principles. In an electronic survey 

format, respondents who voted for a policy would not see this question, potentially reducing 

burden. 

Voting for Regulations to Prevent Fish Losses in the Entire United States. Question 8 is a 

choice experiment question and asks respondents to choose how they would vote, if presented 

with two hypothetical regulatory options (and a third choice to reject both options) for the entire 
18

United States. This question presents multi-attribute options using the same scores as questions 

4-6 for region-specific policy options. However, the scale of the policy is changed to the entire 

United States and assumes that all U.S. households would pay for the programs. This question is 

designed to capture potential differences in the value that respondents place on improvements 

within their region compared to improvements in U.S. waters outside of their region. It also 

captures potential differences in respondents’ preferences for regional and national policies. 

Respondent Certainty and Reasons for Voting. Questions 9 and 10 are follow-up questions to 

the prior voting. Question 9 assesses the certainty that respondents feel in their choice 

experiment responses, following methods of Champ et al. (2004; 2009), Akter (2009), 

Kobayashi et al. (2010), and others. It is designed to identify respondents whose responses are 

based on incorrect interpretation of the resource changes and the uncertainty of ecological 

outcomes from policy options. EPA will evaluate respondent understanding when completing 

stated preference surveys using methods and approaches discussed in Boyle (2003), Kaplowitz 

et al. (2004), Bateman et al. (2002), Powe (2007) and others. Question 10 asks respondents to 

rate the effect of factors on their choices, and why they voted for or against the regulatory 

programs. Responses to such questions have been used in the literature to successfully control 

for hypothetical bias. 

Recreational Experience. Questions 11, 12, and 13 ask respondents how often they participate 

in specific types of water-related recreational activities, and whether those activities would be 

affected by changes in fish abundance. Question 11 asks respondents about their participation at 

all locations while Question 12 asks respondents about their participation within their region. 

These questions can be used to identify non-users of the fishery resource—thereby allowing the 

estimation of non-user values for I&E reductions. Examples of this approach to estimation of 

non-user values are provided by Johnston et al. (2005), Whitehead et al. (1995), Croke et al. 

(1986), Olsen et al. (1991), Cronin (1982), Whitehead and Groothuis (1992), and Mitchell and 

Carson (1981). 

Demographics. Questions 14-22 ask respondents to provide basic demographic information, 

including age, gender, highest level of education, household size, household composition, 

location, employment status, and household income. This information will be used in the 

analysis of survey results, as well as in the nonresponse analysis. 

Comments. The survey offers respondents a chance to comment on the survey. 
19

The Agency will modify the survey instrument for each region relative to the current 

survey draft in Attachment 1 for the Northeast region as follows: 

 Cover – The text on the cover currently reads “A survey of Northeast Residents (CT, DE, 

MA, MD, ME, NH, NJ, NY, RI, VT)”. “Northeast Residents” and the list of included 

states will be changed to match the respondent’s region. 

 Cover – The photo on the cover is of a forage species (silversides) in found in the 

Northeast region. If that species isn't found in other regions, we will replace the cover 

photo with a similar substitute photo for a forage species relevant to that region. 

 Page 1 – The survey states that it “asks for your opinions regarding policies that would 

affect fish and habitat in the Northeast US.” “Northeast US” will be replaced with the 

respondent’s region. 

 Page 1 – Includes the statement that “Northeast fresh and salt waters support billions of 

fish.” “Northeast” will be replaced with the respondent’s region and “salt water” will be 

removed from the Inland and Great Lakes regions. 

 Page 2 - The survey states that “Cooling water use affects fresh and salt waters 

throughout the Northeast US, but almost all fish losses are in salt waters such as coastal 

bays.” For the California and Southeast regions, which include both salt water and 

freshwater facilities, reference to the Northeast region would be replaced with the name 

of the respondent’s region. For the Great Lakes and Inland survey regions, which only 

include freshwater facilities, reference to salt water will be removed. 

 Page 2 – A map of the Northeast region and facility locations is presented. A comparable 

map will be produced for each region, and map included in the survey will correspond to 

the respondent’s region. 

 Page 4 - This page provides an example for two Northeast coastal species and includes a 

figure comparing estimates of young fish lost to the total number of adult fish. The 

estimate of total losses and example species will be modified to describe species and 

losses occurring within the respondent’s region. 

 Page 5 - The total losses (1.1 billion) currently included within the survey corresponds to 

losses from facilities in Northeast coastal waters. This total would be replaced with the 

total losses for the respondent’s region. The pie charts will be updated based on the 

regional total while maintaining the 25% and 95% reductions used in the example. 
20

 Page 7 - The table text describing each score will be changed to include the current scores 

for the respondent’s region. 

 Page 8 - Text describing the commercial fish sustainability score and fish population 

score will be changed to describe the current score for the respondent’s region relative to 

its maximum. 

 Page 9 – The text states that the aquatic ecosystem score measures “how close affected 

Northeast waters are to the most natural, undisturbed condition that is possible.” 

“Northeast waters” will be replaced with a reference to waters within the respondent’s 

region. 

 Page 12 – The included figure illustrates the location of “Coastal Facilities Affected by 

the Proposed Policies”. For other regions which include both salt water and freshwater 

facilities, the figure will be replaced with a similar figure circling salt water facilities 

within the respondent’s region. For the Great Lakes and Inland regions (which do not 

include salt water facilities), only facilities within the region will be shown in the figure, 

making the circle unnecessary. 

 Pages 13-16 – Regional references within the table headings in Questions 4, 5, and 6 

(e.g., “Policy Effect NE Coastal”, “Option A NE Coastal”) will be modified to refer to 

the policy effects and options for the respondent’s region. The “Fish Saved per Year” 

score includes a note reminding the respondent of total fish lost within the region due to 

I&E (e.g., 1.5 billion); this number will be changed to reflect total losses within the 

respondent’s region. The values describing the current situation and Options A and B 

within experiment questions 4, 5, and 6 will also vary across regions. 

 Page 17 – Text describing “National versus Northeast policies” will be modified to refer 

to the respondent’s region. 

 Page 21 – Question 12 asks the respondent how times he participated each of six activity 

categories over the last year within the “Northeastern US only”. Text will be changed to 

reflect the respondent’s region including the list of states which the region includes. 

(II) Respondent activities 

EPA expects individuals to engage in the following activities during their participation in the 

contingent valuation survey: 
21

 Review the background information provided in the beginning of the survey document. 

 Complete the survey questionnaire and return it by mail. 

A typical subject participating in the mail survey is expected to take 25 minutes to 

complete the survey. These estimates are derived from previous focus groups and cognitive 

interviews for the Phase III survey in which respondents were asked to complete a survey of 

similar length and detail to the current survey. 

5. The Information Collected - Agency Activities, Collection Methodology, and 

Information Management 

5(a) Agency Activities 

The survey is being developed, conducted, and analyzed by Abt Associates Inc. and is 

funded by EPA contract No. EP-C-07-023 which provides funds for the purpose of analyzing the 

economic benefits of the proposed rule for existing facilities subject to the section 316(b) 

regulation. Agency activities associated with the survey consist of the following: 

 Develop the survey questionnaire and sampling design. 

 Printing of questionnaires. 

 Telephone screening of respondents. 

 Mailing of questionnaires. 

 Mailing of postcard reminders. 

 Follow-up with non-respondents to the mail survey/resending of questionnaire if needed. 

 Data Entry and cleaning of data file. 

 Analysis of survey results. 

Although not covered under this ICR, EPA will primarily use the survey results to 

estimate the social value of changes in impingement and entrainment losses of forage, 

recreational, and commercial species of fish, as part of the Agency’s analysis of the benefits of 

the 316(b) rule for existing facilities. If reliable environmental data are developed for population 

changes and other ecosystem impacts, social values for these benefit types may also be assessed 

for the rulemaking using survey results. 
22

5(b) Collection Methodology and Information Management 

To pretest the survey questionnaire, EPA will conduct a series of eight focus groups, 

including some using cognitive interview methodologies (conducted under a separate 

information collection request). EPA is planning to conduct these focus groups under a different 

ICR (OMB control # 2090-0028). Focus groups will provide valuable feedback that will allow 

EPA to iteratively edit and refine the questionnaire, and eliminate or improve imprecise, 

confusing, and redundant questions. Focus groups and cognitive interviews will be conducted 

following standard approaches in the literature, as outlined by Desvousges et al. (1984), 

Desvousges and Smith (1988), Johnston et al. (1995), Schkade and Payne (1994), Kaplowicz et 

al. (2004), and Opaluch et al. (1993). 

EPA plans to implement the proposed survey as a mail choice experiment questionnaire. 

First, EPA will use a telephone screener to solicit respondents to receive the mail questionnaire. 

A dual frame, random digit dial design will be used, including both landline and cell phone 

numbers. This ensures that even cell phone only households have an opportunity to participate 

in the survey. The telephone screener includes not only an invitation to participate in the mail 

survey, but also some attitudinal and behavioral questions that are also included in the mail 

survey, as well as demographic characteristics. EPA will use this information for the nonresponse analysis to compare respondents and non-respondents to the mail questionnaire. 

It is anticipated that approximately 60 percent of respondents to the telephone screener 

will agree to participate in the mail survey. EPA will then send the mail survey to those who 

agree to participate, along with a cover letter explaining the purpose of the survey. All of these 

respondents will receive a reminder postcard approximately one week after the initial 

questionnaire mailing. 

Approximately three weeks after the reminder postcard, all those who have not responded 

will receive a second copy of the questionnaire with a revised cover letter. The following week, 

another reminder postcard will be sent. Based on this approach to mail data collection, it is 

anticipated that approximately 40 percent of those who agree to participate in the mail survey 

will actually do so. Since the desired number of completed surveys is 2,000, it will be necessary 

to recruit 5,000 respondents by telephone who agree to participate. 

Data quality will be monitored by checking submitted surveys for completeness and 

consistency, and by asking respondents to assess their own responses to the survey. Question 9 
23

asks respondents to rate their understanding of the survey and their confidence in their responses. 

Questions 7 and 10 are designed to assess the presence or absence of potential response biases by 

asking respondents to indicate their reasoning and rate the influence of various factors on their 

responses to the choice experiment questions. Responses to the survey will be stored in an 

electronic database. This database will be used to generate a data set for a regression model of 

total values for reductions in fish impingement and entrainment by section 316(b) existing 

facilities. 

To protect the confidentiality of survey respondents, the survey data will be released only 

after it has been thoroughly vetted to ensure that all potentially identifying information has been 

removed. 

Alternatively, EPA is considering implementing the proposed survey as an internetbased, choice experiment questionnaire. This alternative method is described in Attachment 4. 

5(c) Small Entity Flexibility 

This survey will be administered to individuals, not businesses. Thus, no small entities 

will be affected by this information collection. 

5(d) Collection Schedule 

The schedule for implementation of the survey will be as follows: 
24

Table A2: Schedule for Survey Implementation 

Activity 

Duration of 

Each Activity 

Printing of questionnaires Weeks 1 to 2 

Telephone screening of respondents Weeks 3 to 8 

Mailing of questionnaires Weeks 3 to 8 

Postcard reminder (one week after initial questionnaire mailing) Weeks 4 to 9 

Follow-up with non-respondents to the mail survey/resending of 

questionnaire if needed (4 weeks after initial questionnaire mailing) 

Weeks 6 to 13 

Data entry Weeks 4 to 16 

Cleaning of data file Week 17 

Delivery of data Week 18 

6. Estimating Respondent Burden and Cost of Collection 

6(a) Estimating Respondent Burden 

Subjects who participate in the survey and follow-up interviews will expend time on 

several activities. Based on the administration of the mail survey to 5,000 households, the 

national burden estimate for all respondents is 1,527 hours assuming that 8,333 households will 

participate in telephone screening and 2,000 respondents complete and return the survey, 

EPA estimates that telephone screening interviews will take 5 minutes (0.08 hours) per 

interview for each of the 8,333 screened households. Based on pretests conducted in focus 

groups, EPA estimates that on average each respondent mailed the survey will spend 25 minutes 

reviewing the introductory materials and completing the survey questionnaire. Thus, the average 

burden per respondent is 25 minutes (0.42 hours) for these 2,000 respondents. 

These burden estimates reflect a one-time expenditure in a single year. 

6(b) Estimating Respondent Costs 

According to the Bureau of Labor Statistics, the average hourly wage for private sector 

workers in the United States is $20.42 (2009$) (U.S. Department of Labor 2009). Assuming an 

average per-respondent burden of 0.08 hours for each of the 8,333 screening participants and an 
25

average hourly wage of $20.42, the average cost per screening participant is $1.70. Therefore 

the total cost to participants in the telephone screening phase would be $14,180. Assuming an 

average per-respondent burden of 0.5 hours for individuals mailed the survey and an average 

hourly wage of $20.42, the average cost per respondent is $10.21. Of the 5,000 individuals 

receiving the mail survey, 2,000 are expected to return their completed survey. The total cost for 

all individuals that return surveys would be $20,420. 

EPA does not anticipate any capital or operation and maintenance costs for respondents. 

6(c) Estimating Agency Burden and Costs 

This project will be undertaken by Abt Associates Inc. with funding of $397,540 from 

EPA contract EP-C-07-023, which provides funds for the purpose of analyzing the economic 

benefits of the proposed rule for existing facilities subject to the section 316(b) regulation. Abt 

Associates Inc. staff is expected to spend 1,126 hours pre-testing the survey questionnaire and 

sampling methodology, conducting the survey, and tabulating and analyzing the survey results. 

The cost of this contractor time is $74,931. In addition to the effort expended by EPA’s 

contractors, EPA staff is expected to spend 320 hours managing and reviewing this project and 

contributing to the analysis at a cost of $30,971. Agency and contractor burden is 1,446 hours, 

with a total cost of $105,902 excluding the costs of survey printing and mailing. Telephone 

screening is expected to take 7,342 hours and cost $215,797 while mailing and printing of the 

survey is expected to take 141 hours and cost $106,812, including the cost of survey printing and 

mailing. Thus, the total Agency and contractor burden would be 8,929 hours and would cost 

$428,511 

6(d) Respondent Universe and Total Burden Costs 

EPA expects the total cost for survey respondents to be $34,600 (2009$), based on a total 

burden estimate of 1,694 hours and an hourly wage of $20.42. 
26

6(e) Bottom Line Burden Hours and Costs 

The following table presents EPA’s estimate of the total burden and costs of this 

information collection: 

Table A3: Total Estimated Bottom Line Burden and Cost Summary 

Affected Individuals Total Burden Total Cost (2009$) 

Participants in Telephone Screening 694 hours $14,180 

Mail Survey Respondents 1,000 hours $20,420 

Total for Survey Respondents 1,694 hours $34,600 

EPA Staff 320 hours $30,971 

Telephone Screening 7,342 hours $215,797 

Survey Printing and Mailing 141 hours $106,812 

EPA’s Contractors 1,126 hours $74,931 

Total Burden and Cost 10,624 hours $463,111 

6(f) Reasons for Change in Burden 

The survey is a one-time data collection activity. 

6(g) Burden Statement 

EPA estimates that the public reporting and record keeping burden associated with the 

mail survey will average 0.5 hours per respondent (i.e., a total of 1,000 hours of burden divided 

among 2,000 survey respondents). Households included in telephone screening are expected to 

average 0.08 hours per screening interview participant (i.e., a total of 694 hours of burden 

divided among 8,333 screening interview participants). This results in a total burden estimate of 

1,694 hours including both the telephone screening interviews and mail survey. Burden means 

the total time, effort, or financial resources expended by persons to generate, maintain, retain, or 

disclose or provide information to or for a Federal agency. This includes the time needed to 

review instructions; develop, acquire, install, and utilize technology and systems for the purposes 

of collecting, validating, and verifying information, processing and maintaining information, and 
27

disclosing and providing information; adjust the existing ways to comply with any previously 

applicable instructions and requirements; train personnel to be able to respond to a collection of 

information; search data sources; complete and review the collection of information; and 

transmit or otherwise disclose the information. An agency may not conduct or sponsor, and a 

person is not required to respond to, a collection of information unless it displays a currently 

valid OMB control number. The OMB control numbers for EPA's regulations are listed in 40 

CFR part 9 and 48 CFR chapter 15. 

To comment on the Agency's need for this information, the accuracy of the provided 

burden estimates, and any suggested methods for minimizing respondent burden, including the 

use of automated collection techniques, EPA has established a public docket for this ICR under 

Docket ID No. EPA-HQ-OW-2010-0595, which is available for online viewing at 

www.regulations.gov, or in person viewing at the Office of Water Docket in the EPA Docket 

Center (EPA/DC), EPA West, Room 3334, 1301 Constitution Ave., NW, Washington, DC. The 

EPA/DC Public Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through Friday, 

excluding legal holidays. The telephone number for the Reading Room is 202-566-1744, and the 

telephone number for the Office of Water Docket is 202-566-1752. 

Use www.regulations.gov to obtain a copy of the draft collection of information, submit 

or view public comments, access the index listing of the contents of the docket, and to access 

those documents in the public docket that are available electronically. Once in the system, select 

“search,” then key in the docket ID number identified in this document. 
28

PART B OF THE SUPPORTING STATEMENT 

1. Survey Objectives, Key Variables, and Other Preliminaries 

1(a) Survey Objectives 

The overall goal of this survey is to explore how public values (including non-use values) 

for fish and aquatic organisms are affected by impingement and entrainment at cooling water 

intake structures (CWIS) located at existing 316(b) facilities, as reflected in individuals’ 

willingness to pay for programs that would prevent such losses. EPA has designed the survey to 

provide data to support the following specific objectives: 

 To estimate the total values that individuals place on preventing losses of fish and other 

aquatic organisms caused by CWIS at existing 316(b) facilities. 

 To understand how much individuals value preventing fish losses, increasing fish 

populations, improvements in aquatic ecosystems, and increasing commercial and 

recreational catch rates. 

 To understand how such values depend on the current baseline level of fish populations 

and fish losses, the scope of the change in those measures, and the certainty level of the 

predictions. 

 To understand how such values vary with respect to individuals’ economic and 

demographic characteristics. 

Understanding total public values values for fish resources lost to impingement and 

entrainment–is necessary to determine the full range of benefits associated with reductions in 

impingement and entrainment losses at existing 316(b) facilities. Because non-use values may be 

substantial in some cases, failure to recognize such values may lead to improper inferences 

regarding policy benefits (Freeman 2003). 

1(b) Key Variables 

The key questions in the survey ask respondents whether or not they would vote for 

policies that would increase their cost of living, in exchange for specified changes in (a) 

impingement and entrainment losses of fish, (b) commercial fish sustainability, (c) long-term fish 
29

populations, and (d) condition of aquatic ecosystems. More specifically, the choice experiment 

framework allows respondents to view pairs of multi-attribute policies associated with the 

reduction of I&E losses. Respondents are asked to choose the program that they would prefer, or 

to choose to reject both policies. This follows well-established choice experiment methodology 

and format (Adamowicz et al. 1998; Louviere et al. 2000; Bennett and Blamey 2001; Bateman et 

al. 2002). Important variables in the analysis of the choice questions are how the respondent 

votes, the amount of the cost of living increase, the number of fish losses that are prevented, the 

sustainability of commercial fishing, the change in fish populations, and the condition of aquatic 

ecosystems. Other important variables include whether or not the respondent is a user of the 

affected aquatic resources, household income, and other respondent demographics. 

1(c) Statistical Approach 

EPA believes that a statistical survey approach is appropriate. A census approach is 

impractical because contacting all households in the U.S. would require an enormous expense. 

On the other hand, an anecdotal approach is not sufficiently rigorous to provide a useful estimate 

of the total value of fish loss reductions for the 316(b) case. Thus, a statistical survey is the most 

reasonable approach to satisfy EPA’s analytic needs for the 316(b) regulation benefit analysis. 

EPA has retained Abt Associates Inc. (55 Wheeler Street, Cambridge, MA 02138) as a 

contractor to assist in questionnaire design, sampling design, and analysis of the survey results. 

1(d) Feasibility 

The survey instrument will be repeatedly pre-tested during a series of eight focus groups 

(conducted under a different ICR with OMB control # 2090-0028), in addition to the twelve 

focus groups conducted for the Phase III survey (EPA-HQ-OW-2004-0020), and it will be 

subject to review by reviewers in academia and government, so EPA does not anticipate that 

respondents will have difficulty interpreting or responding to any of the survey questions. 

Additionally, since the survey will be administered as a mail survey, it will be easily accessible 

to respondents. Thus, EPA believes that respondents will not face any obstacles in completing 

the survey, and that the survey will produce useful results. EPA has dedicated sufficient funding 

(under EPA contracts No. EP-C-07-23) to design and implement the survey. Given the timetable 
30

outlined in Section A.5(d) of this document, the survey results will be available for timely use in 

the benefits analysis for the 316(b) existing facilities rule. 

2. Survey Design 

2(a) Target Population and Coverage 

The target population for this survey includes individuals from continental U.S. 

households who are 18 years of age or older. The sample will be chosen to reflect the 

demographic characteristics of the general U.S. population. 

2(b) Sampling Design 

(I) Sampling Frames 

The sampling frame for this survey is the panel of individuals recruited by random digit 

dialing (over-lapping dual frame; land and cell) to participate in a mail survey. The overall 

sampling frame from which these individuals would be selected is the set of all individuals in 

continental U.S. households who are 18 years of age or older and who have listed phone 

numbers. Individuals in the panel are recruited using a list-assisted random digit dialing 

telephone methodology, thus providing a probability-based starting sample of U.S. telephone 

households. 

The telephone screening will use an overlapping dual frame design of landline and cell 

phone numbers to increase the coverage of the sample. The inclusion of cell phone numbers will 

allow us to reach potential respondents who only have cell phones and would be missed if only a 

sample of landlines was selected. The dual frame design also avoids bias because the cell-phone 

only population skews heavily towards lower-income and younger individuals. The cell and 

landline samples will be weighted to correct for each individual’s probability of being included 

in the survey. People who live in a household with more than one person are less likely to be 

chosen for the survey, and people with more than one telephone line (e.g., both cell and landline) 

are more likely to be chosen for the survey. All landline respondents to the telephone screener 

will be asked the number of eligible respondents in their household and every respondent (cell 

and landline) will be asked whether they have a landline only, a cell phone only, or both. Next, 

the survey data will be weighted to match national data (U.S. Census and National Health 
31

Interview Survey) by a set of demographic variables (e.g., age and gender) as well as phone 

usage (cell-only users, landline-only users and people who use both cell phones and landline 

phones). For January through June 2009, the National Health Interview Survey indicated that 

15.5 percent of households are landline only, 22.7 percent are cell phone only, and 59.4 percent 

have both landline and cell phone service. Less than two percent of households have no 

telephone service. It is anticipated that estimates for landline and cell phone service from the 

January to June 2010 National Health Interview Survey will be available for weighting purposes 

by the time the survey would be implemented. 

For discussion of techniques that EPA will use to minimize non-response and other nonsampling errors in the survey sample, refer to Section 2(b)(II), below. 

(II) Sample Sizes 

The intended sample size for the survey is 2,000 households including only households 

providing completed mail surveys. This sample size was chosen to provide statistically robust 

regression results while minimizing the cost and burden of the survey. Given this sample size, 

the level of precision (see section 2(c)) achieved by the analysis will be more than adequate to 

meet the analytic needs of the benefits analysis for the 316(b) regulation. For further discussion 

of the level of precision required by this analysis, see Section 2(c)(I) below. 

(III) Stratification Variables 

The survey sample will be selected using a stratified selection process. For the selection 

of households, the population of households in the contiguous 48 states will be stratified by the 

geographic boundaries of 5 EPA study regions: California, Great Lakes, Inland, Northeast, and 

Southeast. As described previously, the Northeast region includes the North Atlantic and Mid 

Atlantic 316(b) benefits regions and the Southeast region includes the South Atlantic and Gulf of 

Mexico 316(b) benefits regions. The sample is allocated to each region in proportion to the total 

number of households in that region with at least 288 persons in each region. This is the number 

required to estimate the main effects and interactions under an experimental design model as 
32

described in Section 4(a) of Part A. To accommodate this requirement the sample sizes in other 

regions will be slightly reduced. 

(IV) Sampling Method 

Using the stratification design discussed above, respondents will be randomly selected. 

First, a larger sample of households will be selected through random digit dialing in each of the 5 

regions. The household to which the selected telephone number belongs will be called and the 

respondent will be asked whether he or she is willing to provide information required by the 

survey. If the person in the household agrees, then a questionnaire will be mailed to that 

household. If it is assumed that 40% of the households which agreed to provide information 

actually return a completed mail survey (completion rate) then 5,000 questionnaires will need to 

be mailed to households.2

If we assume that 60% of the households that are called say “yes” they are willing to 

receive a questionnaire (the screening response rate), then we need to screen 8,333 households. 

A dual frame random digit dialing design, including both landline and cell phone numbers, will 

be used for telephone screening. If we assume that 40% of the households called will participate 

in the telephone screener, then we will need to call 20,833 numbers. The actual number of 

telephone number selected through random digit dialing sampling will be larger than the number 

of households called. This is because we are expecting that 40% of the telephone numbers 

initially selected will be screened out as non-working or business numbers. Therefore the actual 

number of telephone numbers selected will be around 34,721. The quantity of telephone 

numbers that we need to select in each region can be obtained by allocating the total number in 

proportion to the total households in that region. 

For obtaining population-based estimates of various parameters, each responding 

household will be assigned a sampling weight. This weight combines a base sampling weight 

which is the inverse of the probability of selection of the household and then an adjustment for 

non-response. The weights will be used to produce estimates that are generalizable to the 

population from which the sample was selected (e.g., percent of population participating in 

water-based recreation such as fishing and shellfishing). Proportional allocation of the sample to 

regions ensures an equal probability sample. To estimate total WTP for the quantified 

 

2

 The assumed response rate is based on similar stated preference studies (e.g., Johnston et al. 2009). 
33

environmental benefits of the 316(b) existing facilities rulemaking data will be analyzed 

statistically using a standard random utility model framework. 

(V) Multi-Stage Sampling 

Multi-stage sampling will not be necessary for this survey. 

2(c) Precision Requirements 

(I) Precision Targets 

Table B1, below, shows the target samples sizes for both the U.S. (excluding AK and HI) 

and each of the 5 EPA study regions. A sample of 2,000 households (completed surveys) will 

provide estimates of population percentages with a margin of error no greater than +/- 2.2 

percentage points at the 95% confidence level. The margin of error for the estimates at the 

regional level will range from 3.7 to 9.3 percentage points at the 95% confidence level. 

Table B1: Number of Households and Household Sample for Each EPA Study Region 

Region Household Population Household Sample 

Northeast 18, 936,383 301 

Southeast 39, 382,881 626 

Great Lakes 29, 003,114 461 

Inland 6,304,690 288 

Pacific Mountain 20,370,838 324 

All Regions 113,997,907 2,000 

Source: The number of households in each region was obtained based on the estimated population size 

and average household size from the 2005-2007 American Community Survey (ACS). 

(II) Non-Sampling Errors 

One issue that may be encountered in stated preference surveys is the problem of protest 

responses. Protest responses are responses from individuals who reject the survey format or 
34

question design, even though they may value the resources being considered (Mitchell and 

Carson 1989). For example, some respondents may feel that any amount of impingement and 

entrainment is unacceptable, and choose not to respond to the survey. To deal with this issue, 

EPA has included several questions, including an open-ended comments section, to help identify 

protest responses. The use of such methods to identify protest responses is well-established in 

the literature (Bateman et al. 2002). Moreover, many researchers (e.g., Bateman et al. 2002) 

suggest that a choice experiment format, such as that proposed here, may ameliorate such 

responses. 

A different type of non-sampling error is non-response bias. Non-response rates in this 

survey are affected by non-response at each stage of sampling. There are two types of nonrespondents to this survey: respondents unwilling to complete a questionnaire when initially 

contacted by phone and respondents who agree but do not complete the questionnaire. EPA will 

conduct several additional activities to minimize the potential for non-response bias in the 

current survey: 

(1) The telephone interviews will be conducted by trained interviewers who are 

experienced in encouraging response. Calls will be placed on different days of the 

week and at different times to maximize response. 

(2) The mail survey will be designed to maximize response. A mail survey will be sent 

to all those who agree to participate. Then, one week later, a postcard reminder will 

be sent. Three weeks later, a second copy of the questionnaire with a revised cover 

letter will be sent to non-respondents. As final follow-up, another postcard reminder 

will be sent one week later. 

(3) Response rates will be tracked on a daily basis for both the telephone screener and 

mail survey. If any unexpected declines are encountered, corrective action can 

immediately be undertaken. 

(4) EPA will undertake non-response bias analysis as detailed in the following section. 

If necessary, EPA will use appropriate weighting or other statistical adjustment to correct the 

bias because of non-response. 

Non-response Interviews 

To determine whether there is any evidence of significant non-response bias in the 

completed sample, EPA will compare the characteristics of the completed and non-completed 
35

cases from the random digit dialing sample. There are two main stages of non-response: nonresponse to the telephone survey and non-response to the mail survey. 

To assess the potential for telephone non-response bias, EPA will collect sample 

characteristics in the course of the telephone survey as follows: (1) prior to household contact, 

(2) at respondent selection for the survey, and (3) after beginning the interview. EPA will then 

analyze the data available for respondents and non-respondents prior to household contact and at 

respondent selection. Because the telephone instrument is very short, we do not expect many 

people prematurely terminating the call after the selected household member has started the 

interview. 

The drawn sample of random digit dialing numbers from the landline frame that are 

released to telephone interviewers for contact attempts can be coded for certain contextual 

characteristics. The “hundreds bank” from which the RDD number is drawn (e.g., 301-608-

38xx) is classified geographically according to the unit from which the majority of listed 

numbers in that bank are located. This permits us to classify all of the numbers drawn by EPA 

region, State, and urbanicity (central city, metro remainder, and non-metropolitan area). It also 

permits us to classify those numbers by demographic characteristics, such as percentage of 

African-American and Hispanic, based on Census data linked to telephone exchanges. EPA will 

compare the characteristics of all dialed residential numbers in which an interview had not been 

completed with those that had been completed using these variables to determine whether nonresponse bias is present. 

Once contact is achieved with a household, one adult is selected in each household as the 

designated respondent. If there is more than one eligible respondent per household, then a 

random selection is done for the individual with the most recent/next birthday. EPA will identify 

the age and gender of this individual if callbacks are necessary. This information permits 

additional comparisons of any differences in the age and gender of respondents in the completed 

sample and those in the non-completed sample after household contact and respondent selection 

have been made. 

The telephone screener includes not only an invitation to participate in the mail survey, 

but also some attitudinal (relative importance of various government activities) differences and 

behavioral differences (recreational activities), as well as demographic characteristics (see 

Attachment 5 for detail). EPA will use the telephone screening data to compare mail survey 

respondents and non-respondents. The items of information collected during telephone screening 
36

will help determine the type of person that is likely to not respond to the survey and may help in 

forming weighting classes for adjusting weights of respondents to account for non-response and 

minimize the bias because of non-response. 

2(d) Questionnaire Design 

The information requested by the survey is discussed in Section 4(b)(I) of Part A of the 

supporting statement. The full text of the draft questionnaire is provided in Attachment 1. 

The following bullets discuss EPA’s reasons for including the questions in the survey: 

 Relative Importance of Issues Associated with Industrial Cooling Water. EPA 

included this section to prepare respondents to answer the stated preference questions by 

motivating respondents to consider the relative importance of key issues associated with 

the use of cooling water by industrial facilities. 

 Concern for Policy Issues. EPA included this section to prepare respondents to answer 

the stated preference questions by motivating respondents to think about the relative 

importance of different policy issues. 

 Relative Importance of Effects. This section was included to promote understanding of 

the metrics included in the stated preference questions by asking them to consider their 

relative importance prior to evaluating policy options and by encouraging respondents to 

re-read previous pages for reminders if necessary.

 Voting for Regulations to Prevent Fish Losses in the Respondent’s Region. The 

questions in this section are the key part of the survey. Respondents’ choices when 

presented with specific fish-related resource changes within their region and household 

cost increases are the main data that allow estimation of willingness-to-pay. The 

questions are presented in a choice experiment (A, B, or neither) format because this is an 

elicitation format that has been successfully used by a number of previous valuation 

studies (Adamowicz et al. 1998; Bateman et al. 2002; Bennett and Blamey 2001; 

Louviere et al. 2000; Johnston et al. 2002a, 2005; Opaluch et al. 1993). Furthermore, 

many focus group participants indicated that they have some previous experience making 

choices within a framework in which they are asked to vote for one of a series of options, 

and are comfortable with this format. 
37

 Reasons for Voting “No Policy”. These questions provide information that will be used 

by EPA to identify protest responses. 

 Voting for Regulations to Prevent Fish Losses in the Entire United States. This 

section is a key part of the survey. It uses a format consistent with the region-specific 

choice questions described above, however it asks respondents to value policies affecting 

the entire U.S. This question is designed to capture potential differences in the value that 

respondents place on improvements within their region compared to improvements in 

U.S. waters outside of their region. It also captures potential differences in respondents’ 

preferences for regional and national policies. 

 Respondent Certainty and Reasons for Voting. This section is designed to identify 

respondents who incorrectly interpreted the choice questions or the uncertainty of 

outcomes, Responses to these questions are important to successfully control for 

hypothetical bias. 

 Recreational Experience. These questions elicit recreational experience data to test if 

certain respondent characteristics influence responses to the referendum questions. These 

questions will also allow EPA to identify resource non-users, for purposes of estimating 

non-user WTP (to gauge the relative importance of non-use values to overall benefits). 

 Demographics. Responses to these questions will be used to estimate the influence of 

demographic variables on respondents’ voting choices, and ultimately, their WTP to 

prevent I&E losses of fish. This information will allow EPA to use regression results to 

estimate WTP for populations in different regions affected by the 316(b) rule for existing 

facilities. 

 Comments. This section is primarily intended to help identify protest responses, i.e. 

responses from individuals who rejected the format of the survey or the way the questions 

were phrased. 

3. Pretests and Pilot Tests 

EPA will conduct extensive pretests of the survey instrument during a set of 8 focus 

groups (EPA ICR # 2090-0028), in addition to the twelve focus groups conducted for the Phase 

III survey. These focus groups will include individual cognitive interviews with survey 

respondents (Kaplowicz et al. 2004), and think-aloud or verbal protocol analyses (Schkade and 
38

Payne 1994). Individuals in these focus groups will complete draft survey questionnaires and 

provide comments and feedback about the survey format and content, their interpretations of the 

questions, and other issues relevant to stated preference estimation. Based on their responses, 

EPA will make improvements to the survey questionnaire. Particular emphasis in these survey 

pretests will be on testing for the presence of potential biases associated with poorly-designed 

stated preference surveys, including hypothetical bias, strategic bias, symbolic (warm glow) bias, 

framing effects, embedding biases, methodological misspecification, and protest responses 

(Mitchell and Carson 1989). Focus groups and cognitive interviews may lead to changes that 

ameliorate and minimize these biases in the final survey instrument. Survey pretests may also 

demonstrate the ability of follow-up survey questions (i.e., after the primary choice questions) to 

clearly identify the respondents whose answers to the choice questions display the influence of 

bias, or do not understand the survey context or information. 

4. Collection Methods and Follow-up 

4(a) Collection Methods 

The survey will be administered as a mail survey. Respondents identified by random 

digit dialing who agree to participate will be mailed a copy of the survey questionnaire. 

Respondents will be asked to mail the completed survey back to EPA. 

4(b) Survey Response and Follow-up 

The target response rate for the mail survey is 40 percent. That is, 40 percent of 

households which agreed to participate in the mail survey are expected to return a completed 

survey. However, the actual response rate compared to the general population is lower, given 

that the telephone screening process is expected to have a response rate of 60 percent among 

contacted households. The resolution rate (determining the status of a telephone number), the 

screener response rate and the survey completion rate will contribute to the overall response rate 

in the survey. The actual number of telephone numbers selected for inclusion will be much 

larger to account for the exclusion of non-working and business numbers. The number of 
39

telephone numbers needed for selection in each region can be obtained by allocating the total 

number in proportion to the number of households in that region. 

To improve the response rate, all of these respondents will receive a reminder postcard 

approximately one week after the initial questionnaire mailing. Then, approximately three weeks 

after the reminder postcard, all those who have not responded will receive a second copy of the 

questionnaire with a revised cover letter. The following week, another reminder postcard will be 

sent. 

As noted in Section 2(b), the survey sample will be selected using a stratified selection 

process. For the selection of households, the population of households in the contiguous 48 

states will be stratified by the geographic boundaries of 5 EPA study regions. We will keep track 

of the response rates by region to ensure that the rates in each region are reasonable. We will 

also look at the frame characteristics of non-respondents to determine if there are any substantial 

biases in the estimates because of an imbalance in the distribution of certain important subgroups 

in the sample. 

5. Analyzing and Reporting Survey Results 

5(a) Data Preparation 

Since the survey will be administered as a mail survey, survey responses will manually 

entered into an electronic database after they are returned. After all responses have been entered, 

the database contents will be converted into a format suitable for use with a statistical analysis 

software package. The mail survey, database management, and data set conversion will be 

conducted by Abt Associates Inc. 

All survey responses will be vetted for completeness. Additionally, respondents’ answers 

to the choice experiment questions will be tested to ensure that they are internally consistent with 

respect to scope and other expectations of neoclassical preference theory, such as transitivity. 

Responses which satisfy transitivity exhibit relational relationships when separate choices among 

policy options are compared. For example, if values for policy A are greater than policy B, and 

values for policy B are greater than Policy C, then values for policy A should also be greater than 

values for Policy C. 
40

5(b) Analysis 

 Once the survey data has been converted into a data file, it will be analyzed using 

statistical analysis techniques. The following section discusses the model that will be used to 

analyze the stated preference data from the survey. 

Analysis of Stated Preference Data 

 The model for analysis of stated preference data is grounded in the standard random 

utility model of Hanemann (1984) and McConnell (1990). This model is applied extensively 

within stated preference research, and allows well-defined welfare measures (i.e., willingness to 

pay) to be derived from choice experiment models (Bennett and Blamey 2001; Louviere et al. 

2000). Within the standard random utility model applied to choice experiments, hypothetical 

policy alternatives are described in terms of attributes that focus groups (Johnston et al. 1995; 

Adamowicz et al. 1998; Opaluch et al. 1993) reveal as relevant to respondents’ utility, or wellbeing. One of these attributes would include a mandatory monetary cost to the respondent’s 

household. 

 Applying this standard model to choices among policies to reduce entrainment and 

impingement (I&E) losses, EPA defines a standard utility function Ui(

.

) that includes 

environmental attributes of an I&E reduction plan and the net cost of the plan to the respondent. 

Following standard random utility theory, utility is assumed known to the respondent, but 

stochastic from the perspective of the researcher, such that 

(1) Ui(

.

) = U(Xi, D, Y-Fi) = v(Xi, D, Y-Fi) + εi

where: 

Xi = a vector of variables describing attributes of I&E reduction plan i; 

D = a vector characterizing demographic and other attributes of the respondent. 

Y = disposable income of the respondent. 

Fi = mandatory additional cost faced by the household under plan i; 

v(.

) = a function representing the empirically estimable component of utility; 

εi = stochastic or unobservable component of utility, modeled as an econometric error. 
41

 Econometrically, a model of such a preference function is obtained by methods designed 

for limited dependent variables, because researchers only observe the respondent’s choice among 

alternative policy options, rather than observing values of Ui(.) directly (Maddala, 1983; 

Hanemann, 1984). Standard random utility models are based on the probability that a 

respondent’s utility from a policy Plan i, Ui(.), exceeds the utility from alternative Plans j, Uj(.), 

for all potential plans j≠i considered by the respondent. In this case, the respondent’s choice set 

of potential policies also includes maintaining the status quo. The random utility model presumes 

that the respondent assesses the utility that would result from each I&E reduction plan i 

(including the status quo), and chooses the plan that would offer the highest utility. 

When faced with k distinct plans defined by their attributes, the respondent will choose 

plan i if the anticipated utility from plan i exceeds that of all other k-1 plans. Drawing from (1), 

the respondent will choose plan i if 

(2) (v(Xi, D, Y-Fi) + εi) ≥ (v(Xk, D, Y-Fk) + εk)  k≠i. 

 If the εi are assumed independently and identically drawn from a type I extreme value 

(Gumbel) distribution, the model may be estimated as a conditional logit model, as detailed by 

Maddala (1983), Greene (2003) and others. This model is most commonly used when the 

respondent considers more than two options in each choice set (e.g., Plan A, Plan B, Neither 

Plan), and results in an econometric (empirical) estimate of the systematic component of utility 

v(.), based on observed choices among different policy plans. Based on this estimate, one may 

calculate welfare measures (willingness to pay) following the well-known methods of Hanemann 

(1984), as described by Freeman (2003) and others. Following standard choice experiment 

methods (Adamowicz et al. 1998; Bennett and Blamey 2001), each respondent will consider 

questions including three potential choice options (i.e., Plan A, Plan B, Neither Plan)—choosing 

the option that provides the highest utility as noted above. Following clear guidance from the 

literature, a “neither plan” or status quo option is always included in the visible choice set, to 

ensure that WTP measures are well-defined (Louviere et al. 2000). 

 EPA also anticipates that respondents will consider more than one choice question within 

the same survey, to increase information obtained from each respondent. This is standard 

practice within choice experiment and dichotomous choice contingent valuation surveys (Poe et 

al. 1997; Layton 2000). While respondents will be instructed to consider each choice question as 
42

independent of other choice questions, it is nonetheless standard practice within the literature to 

allow for the potential of correlation among questions answered within a single survey by a 

single respondent. That is, responses provided by individual respondents may be correlated even 

though responses across different respondents are considered independent and identically 

distributed (Poe et al. 1997; Layton 2000; Train 1998). 

 There are a variety of approaches to such potential correlation. Following standard 

practice, EPA anticipates the estimation of a variety of models to assess their performance. 

Models to be assessed include random effects and random parameters (mixed) discrete choice 

models, now common in the stated preference literature (Greene 2003; McFadden and Train 

2000; Poe et al. 1997; Layton 2000). Within such models, selected elements of the coefficient 

vector are assumed normally distributed across respondents, often with free correlation allowed 

among parameters (Greene 2002). If only the model intercept is assumed to include a random 

component, then a random effects model results. If both slope and intercept parameters may 

vary across respondents, then a random parameters model is estimated. EPA anticipates that 

such models will be estimated using standard maximum likelihood for mixed conditional logit 

techniques, as described by Train (1998), Greene (2002) and others. Mixed logit model 

performance of alternative specifications will be assessed by EPA using standard statistical 

measures of model fit and convergence, as detailed by Greene (2002), Greene (2003), and Train 

(1998). 

Advantages of Choice Experiments 

 Choice experiments following the random utility model outlined above are favored by 

many researchers over other variants of stated preference methodology (Adamowicz et al. 1998; 

Bennett and Blamey 2001), and may be viewed as a “natural generalization of a binary discrete 

choice CV [contingent valuation]” (Bateman et al. 2002, p. 271). Advantages of choice 

experiments include a capacity to address choices over a wide array of potential policies, 

grounded in well-developed random utility theory, and the similarity of the discrete choice 

context to familiar referendum or voting formats (Bennett and Blamey 2001). Compared to 

other types of stated preference valuation, choice experiments are better able to measure the 

marginal value of changes in the characteristics or attributes of environmental goods, and avoid 

response difficulties and biases (Bateman et al. 2002). For example, choice experiments may 

reduce the potential for ‘yea-saying’ and symbolic biases (Blamey et al. 1999; Mitchell and 
43

Carson 1989), as many pairs of multi-attribute policy choices (e.g., Plan A, Plan B, Neither) will 

offer no clearly superior choice for a respondent wishing to express solely symbolic 

environmental motivations. For similar reasons choice experiments may ameliorate protest 

responses (Bateman et al. 2002). An additional advantage of such methods is that they permit 

straightforward assessments of the impact of resource scope and scale on respondents’ choices. 

This will enable EPA to easily conduct scope tests and other assessments of the validity of 

survey responses (Bateman et al. 2002, p. 296-342). Finally, such methods are well-established 

in the stated preference literature (Bennett and Blamey 2001). Additional details of choice 

experiment methodology (also called choice modeling) are provided by Bennett and Blamey 

(2001), Adamowicz et al. (1998), Louviere et al. (2000) and many other sources in the literature. 

An additional advantage of choice experiments in the present application is that they are 

commonly applied to assess WTP for ecological resource improvements of a type quite similar to 

those at issue in the 316(b) policy case. Examples of the application of choice experiments to 

estimate WTP associated with changes in aquatic life and habitat include Hoehn et al. (2004), 

Johnston et al. (2002b), and Opaluch et al. (1999), among others. EPA has drawn upon these and 

other examples of successful choice experiment design to provide a basis for survey design in the 

present case. 

A final key advantage of choice experiments in the present application is the ability to 

estimate respondents WTP for a wide range of different potential outcomes of 316(b) policies, 

differentiated by their attributes. The proposed choice experiment survey versions will allow 

different respondents to choose among a wide variety of hypothetical policy options, some with 

larger and other with very small changes in the presented attributes (annual fish losses, long-term 

fish populations, recreational and commercial catch, ecosystem condition, and household cost). 

That is, because the survey is to be implemented as a choice experiment survey, levels of 

attributes in choice scenarios will vary across respondents (Louviere et al. 2000). The 

experimental design will also explicitly allow for variation in baseline population and harvest 

levels, following standard practice in the literature (Louviere et al. 2000; Bateman et al. 2002). 

Aside from providing the capacity to estimate WTP for a wide range of policy outcomes, 

it also frees EPA from having to predetermine a single policy outcome for which WTP will be 

estimated. Given the potential biological uncertainty involved in the 316(b) policy case, the 

ability to estimate values for a wide range of potential outcomes is critical. 
44

The ability to estimate WTP for a wide range of different policy outcomes is a 

fundamental property of the choice experiment method (Bateman et al. 2002; Louviere et al. 

2000; Adamowicz et al. 1998). EPA emphasizes that the survey version included in this ICR is 

for illustration only; it is but one of what will ultimately be a large number of survey versions 

covering a wide range of potential policy outcomes as described in Attachment 3. For the 

purpose of the stated preference survey implementation, EPA will use five geographic regions: 

California, Great Lakes, Inland, Northeast, and Southeast. The survey version included in this 

ICR is for the Northeast region. The experimental design (see below) will allow for survey 

versions showing a range of different baseline and resource improvement levels, where these 

levels are chosen to (almost certainly) bound the “actual” levels. Given that there will almost 

certainly be some biological uncertainty regarding the specifics of the “actual” baselines and 

improvements, the resulting valuation estimates will allow flexibility in estimating WTP for a 

wide range of different circumstances. Additional details on the statistical (experimental) design 

of the choice experiment is provided in later sections of this ICR. 

Comment on Survey Preparation and Pretesting 

 Following standard practice in the stated preference literature (Johnston et al. 1995; 

Desvousges and Smith 1988; Desvousges et al. 1984; Mitchell and Carson 1989), all survey 

elements and methods will be subjected to extensive development and pretesting in focus groups 

to ameliorate the potential for survey biases (cf. Mitchell and Carson 1989), and to ensure that 

respondents have a clear understanding of the policies and goods under consideration, such that 

informed choices may be made that reflect respondents’ underlying preferences. Following the 

guidance of Arrow et al. (1993), Johnston et al. (1995), and Mitchell and Carson (1989), focus 

groups will be used to ensure that respondents are aware of their budget constraints, the scope of 

the resource changes under consideration, and the availability of substitute environmental 

resources. 

As noted above, survey pretests will also include individual cognitive interviews with 

survey respondents (Kaplowicz et al. 2004), and think-aloud or verbal protocol analyses 

(Schkade and Payne 1994). Individuals in these pretests will complete draft survey 

questionnaires and provided comments and feedback about the survey format and content, their 

interpretations of the questions, and other issues relevant to stated preference estimation. Based 
45

on their responses, EPA will make improvements to the survey questionnaire. Of particular 

emphasis in these survey pretests is testing for the presence of potential biases including 

hypothetical bias, strategic bias, symbolic (warm glow) bias, framing effects, embedding biases, 

methodological misspecification, and protest responses (Mitchell and Carson 1989). Focus 

groups and cognitive interviews may lead to changes to ameliorate and minimize these biases in 

the final survey instrument and introductory materials if necessary. Results from focus groups 

and cognitive interviews used to test the final survey version will provide evidence as to whether 

respondents answer the stated preference survey in ways appropriate for stated preference WTP 

estimation, and that their responses do not reflect the biases noted above. Moreover, survey 

pretests can demonstrate the ability of follow-up survey questions (i.e., after the primary choice 

questions) to clearly identify the respondents whose answers to the choice questions display the 

influence of bias, or do not understand the survey context or information. 

The number of focus groups used in survey design (8, excluding the 12 focus groups 

conducted for the Phase III survey) exceeds the number of focus groups used in typical 

applications of stated preference valuation. Moreover, EPA will incorporate cognitive 

interviews as detailed by Kaplowicz et al. (2004). We note that the current survey instrument is 

built upon an earlier version that was peer reviewed in January 2006 and it incorporates 

recommendations received from that peer review panel. Given this extensive effort in survey 

design—applying the most state-of-the-art methods available in the literature—EPA believes that 

survey design far exceeds standards that are typical in the published literature. The details of 

focus groups to be used in the survey’s design are discussed by EPA in a prior ICR (#2155.01). 

Econometric Specification 

 Based on prior focus groups, expert review, and attributes of the policies under 

consideration, EPA anticipates that four attributes will be incorporated in the vector of variables 

describing attributes of an I&E reduction plan (vector Xi), in addition to the attribute 

characterizing unavoidable household cost Fi.

3

 These attributes will characterize the annual 

reduction in I&E losses (x1), anticipated long-term effects on fish populations (x2), anticipated 

long-term effects on recreational and commercial harvest (x3), and anticipated impacts on aquatic 

 

3

 EPA plans to complete focus group testing of the instrument before the second Federal Register notice of this 

information collection request. The inclusion of all four attributes is an important aspect of focus group testing. If 

focus groups find this number cognitively challenging, the number will be reduced, and if cognitive issues are 

minimal as identified by randomly selected focus group participants, all four will remain. 
46

ecosystem condition (x4). These variables will allow respondents’ choices to reveal the potential 

impact of both annual fish losses and long-term population effects on utility. Based on results of 

prior focus groups and expert opinion, these will be presented as averages across identified 

aggregate species groups. The survey will also allow for changes in baseline population levels, 

to assess whether WTP depends on the “starting point” of fish populations. 

 Although the literature offers no firm guidance regarding the choice of specific functional 

forms for v(.) within choice experiment estimation, in practice, linear forms are often used 

(Johnston et al. 2003b), with some researchers applying more flexible (e.g., quadratic) forms 

(Cummings et al. 1994). Standard linear forms are anticipated as the simplest form to be 

estimated by EPA, from which more flexible functional forms (able to capture interactions 

among model variables) will be derived and compared. Anticipated extensions to the simple 

linear model include more fully-flexible forms that allow for systematic variations in slope and 

intercept coefficients associated with demographic or other attributes of respondents. Such 

variations may be incorporated by appending the simple linear specification with quadratic 

interactions between variables in vector D and the variables Xi and Fi (cf. Johnston et al. 2003b). 

 One may also incorporate quadratic interactions between policy attributes Xi and Fi, (cf. 

Johnston et al. 2002b). Such quadratic extensions of the basic linear model allow for additional 

flexibility in modeling the relationship between policy attributes (including cost) and utility, as 

suggested by Hoehn (1991) and Cummings et al. (1994). EPA anticipates estimating both simple 

linear specifications, as well as more fully-flexible quadratic specifications following Hoehn 

(1991) and Cummings et al. (1994), to identify those models which provide the most satisfactory 

statistical fit to the data and correspondence to theory. EPA anticipates estimating all models 

within the mixed logit framework outlined above. Model fit will be assessed following standard 

practice in the literature (e.g., Greene 2003; Maddala 1983). Linear and quadratic functional 

forms discussed here, as they are common practice in the literature, are presented and discussed 

in many existing sources (e.g., Hoehn 1991, Cummings et al. 1994, Johnston et al. 1999, and 

Johnston et al. 2003b). 

 For example, for each choice occasion, the respondent may choose Option A, Option B, 

or Neither, where “neither” is characterized by 0 values for all attributes (except Baseline 

population levels). Assuming that the model is estimated using a standard approximation for the 

observable component of utility, an econometric specification of the desired model (within the 

overall multinomial logit model) might appear as: 
47

v() = 0 + 1(Fish Saved) + 2(Population Change) + 3(Change in Commercial 

Sustainability) + 4(Change in Condition of Aquatic Ecosystem) + 5(Cost) + 6(Fish 

Saved)(Baseline) + 7(Population Change)(Baseline) + 8(Change in Commercial 

Sustainability)(Baseline) + 9(Change in Aquatic Ecosystem)(Baseline) + 10(Cost)(Baseline) + 

11(Fish Saved)(Population Change) + 12(Fish Saved)(Change in Commercial Sustainability) + 

13(Fish Saved)(Change in Aquatic Ecosystem) + 14(Population Change)(Change in 

Commercial Sustainability) + 15(Population Change)(Change in Aquatic Ecosystem) + 

16(Change in Commercial Sustainability)(Change in Aquatic Ecosystem)

Main effects are in bold. Interactions are in italics. This sample specification—one of many to 

be estimated by EPA—allows one to estimate the relative “main effects” of policy attributes 

(annual reduction in I&E losses, long-term effects on fish populations, long-term effects on 

recreational and commercial harvest) on utility, effects on aquatic ecosystem condition, as well 

as interactions between these main effects. This specification also allows EPA to assess the 

impact of baseline fish populations on the marginal value of changes in other model attributes. 

In sum, specifications such as this allow WTP to be estimated for a wide-range of potential 

policy outcomes, and allow EPA to test for a wide-range of main effects and interactions within 

the utility function of respondents. Such flexible utility specifications for stated preference 

estimation are recommended by numerous sources in the literature, including Johnston et al. 

(2002b), Hoehn (1991), and Cummings et al. (1994), and follow standard practice in choice 

modeling outlined by Louviere et al. (2000) and others.

Experimental Design 

 Experimental design for the choice experiment surveys will follow established practices. 

Fractional factorial design will be used to construct choice questions with an orthogonal array of 

attribute levels, with questions randomly divided among distinct survey versions (Louviere et al. 

2000). Based on standard choice experiment experimental design procedures (Louviere et al. 

2000), the number of questions and survey versions will be determined by, among other factors: 

a) the number of attributes in the final experimental design and complexity of questions, b) the 

extent to which estimation of interactions and higher-level effects is desired, and c) pretests 

revealing the number of choice experiment questions that respondents are willing/able to answer 

in a single survey session, and the number of attributes that may be varied within each question 

while maintaining respondents’ ability to make appropriate neoclassical tradeoffs. 
48

Based on the models proposed above and recommendations in the literature, EPA 

anticipates an experimental design that allows for an ability to estimate main effects, quadratic 

effects, and two-way interactions between policy attributes (Louviere et al. 2000). Choice sets 

(Bennett and Blamey 2001), including variable level selection, will be designed by EPA based 

on the goal of illustrating realistic policy scenarios that “span the range over which we expect 

respondents to have preferences, and/or are practically achievable” (Bateman et al. 2002, p. 259), 

following guidance in the literature. This includes guidance with regard to the statistical 

implications of choice set design (Hanemann and Kanninen 1999) and the role of focus groups in 

developing appropriate choice sets (Bennett and Blamey 2001). 

Based on these guiding principles, the following experimental design framework is 

proposed by EPA. The experimental design will be conducted by Abt Associates Inc. The 

experimental design will allow for both main effects and selected interactions to be efficiently 

estimated, based on a choice experiment framework. For a more detailed discussion of the 

experimental design, refer to Attachment 3. 

Each treatment (survey question) includes two choice Options (A and B), characterized 

by four attributes and a cost variable that vary across the two choice options (Fish Saved, 

Commercial Fish Sustainability, Fish Population, Condition of Aquatic Ecosystems, and 

Household Cost). Hence, there are a total of ten attributes for each treatment. Based on focus 

groups and pretests, and guided by realistic ranges of attribute outcomes, EPA allows for three 

different potential levels for Fish Saved, Commercial Fish Sustainability, Fish Population, and 

Condition of Aquatic Ecosystems, and allows for six different levels of monthly Household Cost 

for both regional and national choice questions. Survey questions also include two treatments of 

location, or geographic scope; the first refers to policies only within the respondent’s region and 

the second refers to national policies. 

The number of combinations for each attribute may be summarized as follows: 

 LocationA, LocationB (2 levels) 

 Fish SavedA, Fish SavedB (3 levels) 

 Commercial Fish SustainabilityA, Commercial Fish SustainabilityB (3 levels) 

 Fish PopulationA, Fish PopulationB (3 levels) 

 Condition of Aquatic EcosystemsA, Condition of Aquatic EcosystemsB (3 levels) 

 CostA, CostB (6 levels) 

Beyond the levels specified above, each question will include a “no policy” option, characterized 

by baseline levels for each attribute including a household cost of $0. 
49

Following standard practice, EPA constrained the design somewhat in response to 

findings in prior focus groups conducted for the phase III survey and the prior literature. For 

example, prior focus groups showed that respondents react negatively and often protest when 

offered choices in which one option dominates the other in all attributes. Given that such 

choices provide negligible statistical information compared to choices involving nondominant/dominated pairs, they are typically avoided in choice experiment statistical designs. 

For example, Hensher and Barnard (1990) recommend eliminating profiles including dominating 

or dominated profiles, because such profiles generally provide no useful information. Following 

this guidance, EPA constrained the design to eliminate such dominant/dominating pairs. EPA 

also constrained the design to eliminate the possibility of pairs in which, when looking across 

two options, one of the options offers both a greater reduction in fish losses and a smaller 

increase in the population. The elimination of such nonsensical (or non-credible) pairs is 

common practice, and is done to avoid protest bids and confusion among respondents (Bateman 

et al. 2002). 

The resulting experimental design is characterized by 72 unique A vs. B option pairs, 

where attribute levels for option A and B differ across each of the pairs. Each pair represents a 

unique choice modeling question—with a unique set of attribute levels distinguishing options A 

and B. Following standard practice for mail surveys, these questions will be randomly assigned 

to survey respondents, with each respondent considering three questions. 

Information Provision 

 According to Arrow et al. (1993, p. 4605), “[i]f CV surveys are to elicit useful 

information about willingness to pay, respondents must understand exactly what it is they are 

being asked to value.” It is also well known that the provided information can influence WTP 

estimates derived from stated preference survey instruments and that respondents must be 

provided with sufficient information to make an informed assessment of policy impacts on utility 

(e.g., Bergstrom and Stoll 1989; Bergstrom et al. 1989; Hoehn and Randall 2002). As stated 

clearly by Bateman et al. (2002, p. 122), “[d]escribing the good and the policy context of interest 

may require a combination of textual information, photographs, drawings, maps, charts and 

graphs. ...[V]isual aids are helpful ways of conveying complex information...while 

simultaneously enhancing respondents’ attention and interest.” Given that many respondents 

may not be fully familiar with the details of programs to reduce I&E losses and potential impacts 
50

on aquatic life, the survey will include introductory figures to aid respondents’ comprehension of 

the goods and policies addressed by the survey instrument, and to encourage appropriate 

neoclassical tradeoffs in responding to choice experiment questions. 

Following this guidance of Bateman et al. (2002) and prior examples of Opaluch et al. 

(1993) and Johnston et al. (2002a), among others, EPA extensively pretested, during the Phase 

III focus groups, all graphics used in the draft mail survey, to ensure that these graphical 

elements were not prejudicial, and that they did not bias responses. Graphics judged to be 

prejudicial based on the next round of eight focus groups and/or cognitive interviews will be 

removed and replaced. EPA acknowledges that certain types of graphics can be prejudicial in 

certain contexts—and hence will pretest all graphical elements extensively. However, EPA also 

emphasizes that there is no precedent or support in the literature for the total elimination of 

graphics in survey instruments. To the contrary, the literature explicitly indicates that pictures 

and graphics may be necessary and useful components of survey instruments in many cases 

(Bateman et al. 2002). EPA highlights that numerous peer-reviewed surveys described in the 

literature include pictures and graphics both in survey instruments and in introductory materials 

such as slide shows. For example, see Horne et al. (2005), Ready et al. (1995), Powe and 

Bateman (2004) and Duke and Ilvento (2004), Opaluch et al. (1993), Johnston et al. (1999, 

2002a, 2002b), and Mazzotta et al. (2002). Bateman et al. (2002) also includes examples of 

various types of survey materials including pictures and graphical elements. 

Amelioration of Hypothetical Bias 

EPA considers the amelioration of hypothetical bias to be a paramount concern in survey 

design. However, the agency acknowledges—based on prior evidence from the literature—that 

hypothetical bias is not unavoidable. For example, not all research finds evidence of 

hypothetical bias in stated preference valuation (Champ and Bishop 2001; Smith and Mansfield 

1998; Vossler and Kerkvliet 2003; Johannesson 1997), and some shows that hypothetical bias 

may be ameliorated using cheap-talk, certainty adjustments, or other mechanisms (Champ et al. 

1997; Champ et al. 2004; Cummings and Taylor 1999; Loomis et al. 1996). 

To obtain reliable estimates of WTP, the Agency will test and design all survey elements 

to promote incentive compatible preference elicitation mechanisms. Incentive compatible stated 

preference surveys provide no incentive for non-truthful preference revelation (Carson and 

Groves 2007). The literature is clear regarding the importance of incentive compatibility in stated 
51

preference value elicitation and the role of both question format and scenario consequentiality in 

ensuring this property (Carson et al. 2000; Carson and Groves 2007; Collins and Vossler 2009; 

Herriges et al. 2010; Johnston 2006; Vossler and Evans 2009). It has been established that 

referendum-type stated preference choices are incentive compatible given that certain conditions 

are met, including the condition that responses are believed by respondents to be consequential, 

or potentially influencing public policy decisions (Carson and Groves 2007; Herriges et al. 

2010). 

The survey is explicitly designed to emphasize the importance of the budget constraint 

and program cost. For example, the survey reminds respondents of other policy issues (e.g., 

improving public safety, protecting air quality) for which the government could potentially ask 

households to pay costs. The survey itself includes explicit reminders of program cost and the 

budget constraint. 

The survey has also been explicitly designed to maximize the consequentiality of choice 

experiment questions, thereby maximizing incentive compatibility (i.e., reducing strategic and 

hypothetical biases), following clear guidance of Carson et al. (2000). Elements specifically 

designed to maximize consequentiality include a] explicitly mentioning that this survey is 

associated with assessment of proposed policies that are being considered, b] numerous details 

provided in the survey concerning specifics of the proposed policies, and c] emphasis that the 

type of policy enacted will depend in part on survey results and that their vote is important. 

Johnston and Joglekar (2005) show the capacity of such information to eliminate hypothetical 

bias in choice-based stated preference WTP estimation. 

Focus groups and cognitive interviews will provide information as to whether 

respondents viewed choices as consequential, that they considered their budget constraints when 

responding to all questions, and that they would answer the same way were similar questions 

asked in a binding referendum. In previous focus groups conducted for the Phase III survey, 

when asked if they thought about the program cost in the same way as “money coming out of 

their pocket,” the vast majority of focus group and interview respondents indicated that they 

treated program costs the same way that they would have if there were actual money 

consequences. For example, respondents made statements such as “If this is just an exercise to 

see how I would react, I'd still answer the same as if the government really used it to create 

policy,” and “I would be very certain that I would answer in a real referendum the way I did it 

here.” 
52

 EPA does not anticipate significant hypothetical bias in the proposed survey, however 

hypothetical bias will be evaluated based on findings from the focus groups and cognitive 

interviews and indications of consequentiality in the survey. Regarding the potential use of 

cheap talk mechanisms or other devices to further address the potential for hypothetical bias, the 

Agency emphasizes that the literature is mixed as to their performance. For example, the 

seminal work by Cummings and Taylor (1999) shows that cheap talk is able to reduce 

hypothetical biases. Similar results are shown by Aadland and Caplan (2003). However, other 

authors (e.g., Cummings et al. 1995; List 2001; Brown et al. 2003) find that a cheap talk script is 

only effective under certain circumstances, and for certain types of respondents. For example, 

Cummings et al. (1995) find that a relatively short cheap talk script actually worsens 

hypothetical bias, while a longer script appears to ameliorate bias. Brown et al. (2003) finds 

cheap talk only effective at higher bid amounts—a result mirrored by Murphy et al. (2004). Still 

other authors find no effect of cheap talk, including Poe et al. (2002). Given the clearly mixed 

experiences with such mechanisms, EPA is not convinced that cheap talk scripts are likely to 

provide a panacea for hypothetical bias in the present case—although they appear to reduce bias 

in a limited set of circumstances – and cheap talk is not included in the survey. 

Amelioration of Symbolic Biases and Warm-Glow Effects 

Following clear guidance of Arrow et al. (1993) and others, EPA has taken repeated steps 

to ensure that survey responses reflect the value of the affected fish resources only, and do not 

reflect symbolic or warm glow concerns (Mitchell and Carson 1989). Focus groups and 

cognitive interviews will be used to determine whether respondents are aware of the ecological 

role of fish and ground their preferences in the role that fish play in larger aquatic ecosystems 

(e.g., as food for other organisms, etc.), as indicated in previous focus groups for the Phase III 

survey. They will also be used to determine whether respondents answered questions based on 

the specific changes in resources described in the survey, and not based on symbolic concerns. 

Following explicit guidance of the NOAA Blue Ribbon Panel on Contingent Valuation (Arrow 

et al. 1993, p. 4609), EPA has explicitly designed all elements of the survey to “deflect the 

general ‘warm glow’ of giving or the dislike of ‘big business’ away from the specific program 

that is being valued.” This was done in a variety of ways, based on prior examples in the 

literature, such as asking respondents to reflect on importance of attributes before making 
53

selections, and using a payment vehicle that doesn’t raise trust issues (cost of living increase 

rather than an electric bill increase). 

 The survey includes clear language to instruct respondents only to consider the specific 

attributes in the survey, and not to base answers on broader environmental concerns including 

the statement that: 

 “Scientists expect that effects on the environment and economy not shown explicity will 

be small.“ 

Focus groups will be used to determine whether survey responses reflect symbolic or warm-glow 

concerns. This is also consistent with the statement from Arrow et al. (1993) that a referendumtype format may limit the warm-glow effect. For example, one participant in a previous focus 

group stated, “You know, if you were telling me you were saving spiders, who cares? You know 

what I mean? So, it is not just to do the right thing. I think that fish are important.” Another 

participant stated, “No, I don't have any specific fish in mind. I think every fish will be equally 

important for one thing or another, whether it's for food or I guess some fish are food for other 

fish. Or even just to enjoy, you know. They have a right to live like anything else, you know?” 

This evidence notwithstanding, EPA believes that it is important to include follow-up 

questions to ensure that responses do not reflect symbolic biases. Question 10 in the survey 

instrument—which addresses the rationale for choice responses given earlier in the draft 

survey—explicitly tests for the presence of symbolic or warm-glow biases. Follow-up questions 

such as these are common in stated preference survey instruments, to assess the underlying 

reasons for the observed valuation responses (e.g., Mitchell and Carson 1984).

Assessing Scope Sensitivity 

The NOAA Blue Ribbon Panel on Contingent Valuation (CV) (Arrow et al. 1993, p. 

4605) states clearly that “if CV surveys are to elicit useful information about willingness to pay, 

respondents must understand exactly what it is they are being asked to value (or vote upon)...” 

They further indicate that surveys providing “sketchy details” about the results of proposed 

policies call “into question the estimates derived there from,” and hence suggest a high degree of 

detail and richness in the descriptions of scenarios. Similar guidance is provided by other key 

sources in the CV literature (e.g., Mitchell and Carson 1989; Louviere et al. 2000). Among the 

reasons for this guidance is that such descriptions tend to encourage appropriate framing and 

sensitivity to scope. 
54

Following Arrow et al. (1993), Mitchell and Carson (1989), and others, while noting the 

clear limitations in scope tests discussed by Heberlein et al. (2005), EPA believes that it is 

important that survey responses in this case show sensitivity to scope. This is one of the primary 

reasons for the use of the choice experiment methodology, which is better able to capture WTP 

differentials related to changes in resource scope (Bateman et al. 2002). Unlike open-ended 

questions, in which scope insensitivity is a primary concern, EPA emphasizes that choice 

experiments generally have shown much less difficulty with respondents reacting appropriately 

to the scope and scale of resource changes. Moreover, as clearly noted by Bennett and Blamey 

(2001, p. 231), “internal scope tests are automatically available from the results of a [choice 

modeling] exercise.” That is, within choice experiments, sensitivity to scope is indicated by the 

statistical significance and sign of parameter estimates associated with program attributes 

(Bennett and Blamey 2001). Internal scope sensitivity will therefore be assessed through model 

results for the variables Fish Saved, Commercial Fish Sustainability, Fish Population, and 

Condition of Aquatic Ecosystems. Statistical significance of these variables—along with a 

positive sign—indicates that respondents, on average, are more likely to choose plans with larger 

quantities of these variables. 

In addition to internal scope tests implicit in all choice experiment statistical analysis, 

EPA will also conduct external scope tests (cf. Giraud et al. 1999). The primary difference 

between internal and external tests is that the former assess sensitivity to scope across choices of 

a single respondent, while the latter involves split-sample assessments across different 

respondents. Within a choice modeling context, external scope tests are generally considered 

“stronger,” although also more likely to be confounded by differences in the implied choice 

frame (Bennett and Blamey 2001). A variety of options for external scope tests exist, depending 

on the structure of the stated choice questions under consideration. 

In the present case, attribute-by-attribute external scope tests will be conducted over a 

split sub-sample of respondents considering a specific set of choices, with all held constant 

across the considered choices except the scope of the attribute for which the test is to be 

conducted. For example, to conduct an external scope test for reductions in annual fish losses, 

one would consider a set of choices that is identical over two respondent groups, except that one 

considers a choice with a greater reduction in fish losses. Assessing the choices over this split 

sample allows for an external test of scope. To illustrate this test, consider the following stylized 
55

choice between Option A and Option B. The generic labels “Level 0”, “Level 1”, and “Level 2” 

are used to denote attribute levels, where for all attributes Level 2 > Level 1 > Level 0. 

 

Table B2: Illustration of an External Scope Test 

Variable Option A Option B

Fish Saved per Year Sample 1: Fish Saved Level 1 

Sample 2: Fish Saved Level 2

Fish Saved Level 0 

Commercial Fish Sustainability Commercial Fish Sustainability 

Level 0 

Commercial Fish Sustainability 

Level 0 

Fish Populations Population Level 0 Population Level 0 

Condition of Aquatic Ecosystems Aquatic Ecosystem Condition 

Level 0 

Aquatic Ecosystem Condition 

Level 0 

Increase in Cost of Living for Your 

Household 

Cost Level 1 Cost Level 0 

In the above example, only Fish Saved and Cost vary across the choice options. Because 

both Fish Saved (at Level 1 and Level 2) and Cost are higher in Option A than in Option B, 

neither option is dominant. In the illustrated split-sample test, respondent sample 1 views the 

choice with Fish Saved at Level 1, while respondent sample 2 views an otherwise identical 

choice with Fish Saved at Level 2, where Level 2 > Level 1. If responses are externally sensitive 

to scope in Fish Saved, this will manifest in a greater proportion of sample 2 respondents 

choosing Option A than sample 1 respondents. This hypothesis may be easily assessed using a 

test of equal proportions across the two sub-samples, and provides a simple attribute-by-attribute 

test of external scope. Analogous tests may be conducted for all attributes within the choice 

experiment design, using parallel methods. EPA emphasizes that the formal applicability of the 

above-noted scope test is contingent upon the specific choice frame implied by levels of other 

attributes in the choice question. This is a characteristic of nearly all external scope tests applied 

in choice experiment frameworks (Bennett and Blamey 2001). 

Split-sample tests such as those proposed above often require the addition of question 

versions to the experimental design, to accommodate the specific structural needs of the 

attribute-by-attribute external scope test. Otherwise, confounding effects of other varying 

attributes (including demographic information) can render results of scope tests ambiguous. In 
56

the present case, the proposed tests would require the addition of up to six unique question 

versions to the experimental design, enabling scope tests for the three non-cost attributes within 

the 316(b) choice experiment scenarios. If scope tests in additional question frames are desired 

(e.g., the same scope test illustrated above, but given Level 1 for commercial fish sustainability, 

fish population, and aquatic ecosystem condition attributes), still additional question versions 

would be added. While small numbers of questions added to the experimental design should 

have minimal impacts on overall efficiency (e.g., orthogonality of the design), larger numbers 

may have a more significant impact. Hence, given constraints on the total number of survey 

respondents, there is a potential empirical tradeoff between the number of external scope tests 

that may be conducted and the efficiency of the experimental design and statistical analysis. 

Communicating Uncertainty to Respondents 

EPA believes that the role of risk and uncertainty is an important issue to be addressed in 

the development of benefits estimates, and points out that the literature provides numerous 

examples of cases in which appropriate survey design, including focus groups, was used to 

successfully address such concerns. For example, as stated by Desvousges et al. (1984), “using 

contingent valuation to estimate the benefits of hazardous waste management regulations 

requires detailed information on how and the extent to which respondents understand risk (or 

probability) and how government regulatory actions might change it... Using focus groups 

helped make this determination...” EPA also emphasizes that all regulatory analyses involve 

uncertainty of some type (Boardman et al. 2001). 

The ecological outcome of I&E reductions is subject to considerable uncertainty. EPA 

believes that it is important that survey respondents be aware of this uncertainty, and that their 

responses reflect the knowledge that the resource changes reflected in the survey are scientific 

estimates. However, EPA is also aware of the clear advice from the choice modeling literature 

(e.g., Bennett and Blamey 2001; Louviere et al. 2000) to avoid cognitive burden on respondents. 

Hence, the proposed survey materials clearly indicate the uncertainty involved with the described 

resource changes in choice modeling scenarios, yet do so in a way designed to minimize 

cognitive burden. 

For example, prior to answering choice experiment questions, respondents are told: 

“Scientists know that about 1.1 billion young fish are lost per year [name of region] 

coastal waters due to cooling water use. But, scientists do not know the total number of 

fish in [name of region] coastal waters.” 
57

“Even though scientists can predict approximately the number of fish that will be saved, 

the ultimate effects on fish populations (the number of fish in the water) is uncertain.” 

These statements clearly indicate the uncertainty involved with scientific estimates of the 

outcomes of I&E regulations. This is followed by a further reminder of uncertainty: 

“Policy costs and effects depend on many factors. Saving more fish does not necessarily 

mean that effects will improve.” 

Focus groups and cognitive interviews will be used to indicate whether repondents understood 

that the numbers provided in the survey were scientific estimates subject to uncertainty, and 

answered choice questions accordingly. Respondents in previous focus groups conducted for the 

Phase III survey were comfortable making decisions in the presence of this uncertainty. For 

example, one respondent stated, “...we know that fish populations are declining and so these are 

all estimates. And I accept them as estimates.” Other respondents made statements such as: “If 

they had stated figures as though these figures are it—that I would question,” and “I'll take that 

the estimate comes with some degree of scientific knowledge behind it. More than throwing a 

dart, but accept it for what it was.” 

EPA also tested alternative versions of the Phase III survey instrument in which choice 

experiment attributes were presented as 90% confidence ranges, rather than as point estimates. 

Focus group respondents were explicitly asked whether the ranges were helpful in understanding 

the uncertainty of estimates presented in the choice question or whether they were a source of 

confusion. Seven out of the eight respondents interviewed on that occasion indicated that the use 

of ranges was more confusing than the use of point estimates, Furthermore, respondents were 

comfortable making decisions in the presence of this uncertainty. 

5(c) Reporting Results 

The results of the survey will be made public as part of the benefits analysis for the 

316(b) regulation for existing facilities. Provided information will include summary statistics for 

the survey data, extensive documentation for the statistical analysis, and a detailed description of 

the final results. The survey data will be released only after it has been thoroughly vetted to 

ensure that all potentially identifying information has been removed. 
58

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Attachment 1: Full Text of State Preference Survey Component 
69

Fish and Aquatic Habitat 

A Survey of Northeast Residents 

(CT, DE, MA, MD, ME, NH, NJ, NY, RI, VT) 

DRAFT FOR PRETESTING ONLY 

Do not quote or cite 

Thank you for helping us to test and develop this important survey! 
70

HUMAN ACTIVITIES, AQUATIC HABITAT 

AND FISH 

This survey asks for your opinions regarding policies that would affect fish and habitat 

in the Northeast US. This section provides important background information. 

Northeast fresh and salt waters support billions of fish. These include fish that are used 

by humans, as well as forage fish that are not used by humans. Natural factors such 

as weather have always influenced fish habitat, but in recent years human activities 

have had an increasing effect. 

This survey concerns proposed policies that would reduce fish losses caused by 

cooling water use by industrial facilities, including factories and power plants. 

Activities that affect fish include fishing, 

pollution, commercial and residential 

development, and the extraction of cooling 

water at industrial facilities. 

Declines in fish can affect the condition of 

ecological systems, food webs, and related 

human uses such as fishing. 
71

HOW DOES COOLING WATER 

AFFECT FISH? 

The water that industrial facilities use to cool equipment is pumped from bays, rivers, 

and lakes. The largest amount is used by power plants that produce electricity. 

How Cooling Water Use Affects Fish 

Cooling water use affects fresh and salt waters 

throughout the Northeast US, but almost all fish 

losses are in salt waters such as coastal bays. 

The equipment that pumps the cooling 

water kills small fish and fish eggs. 

Large fish may be injured or killed 

against screens or filters. 

Pumping warm water back into the 

environment (called thermal discharge) 

also affects ecological systems. 
72

WHAT KINDS OF FISH ARE AFFECTED? 

Question 1. When thinking about how industrial facilities use cooling water, please 

rate the importance of the following to you. Check one box for each. 

Not 

Important

Somewhat 

Important

Very 

Important

1. Preventing the loss of fish that 

are caught by humans 1 2 3 4 5

2. Preventing the loss of fish that 

are not caught by humans 1 2 3 4 5

3. Maintaining the ecological health 

of rivers, lakes and bays 1 2 3 4 5

4. Allowing facilities to produce 

products and services at low cost 1 2 3 4 5

5. Reducing government 

regulations on facilities 1 2 3 4 5

Cooling water use is not the largest cause of fish loss in most areas (fishing causes 

greater losses), but has affected some fish stocks. 

About 1/3 of the fish lost are species caught by commercial and recreational 

fishermen. Examples include striped bass, flounder, and cod. 

The other 2/3 of the fish lost are species not caught by humans but are part of 

the food web. Examples include killifish, silverside, and stickleback. 
73

HOW MANY FISH ARE AFFECTED? 

A NORTHEAST COASTAL EXAMPLE 

SCIENTISTS KNOW THAT about 1.1 billion young fish are lost per year in Northeast 

coastal waters due to cooling water use. But, scientists do not know the total number 

of fish in Northeast coastal waters. 

Studies of specific fish can provide some information on how many fish are lost, 

compared to the total number of fish in the water. 

 Sometimes the number of young fish lost is relatively small compared to the 

total number of adult fish—an example is striped bass (see graph below). 

 Sometimes the number of young fish lost is relatively large compared to the total 

number of adult fish—an example is winter flounder (see graph below). 

 For many types of fish, the number of young fish lost compared to the total 

number of adult fish lies somewhere in between these extremes. 

 Even though scientists can predict approximately the number of fish that will be 

saved, the ultimate effects on fish populations (the number of fish in the water) 

is uncertain. 

Total Number of

Adult Striped

Bass

24 million

Total Number of

Adult Winter

Flounder

18 million

Young Fish Lost in

Cooling Water

Intakes

<0.2 million

Young Fish Lost in

Cooling Water

Intakes

7.5 million

0

5,000,000

10,000,000

15,000,000

20,000,000

25,000,000

Striped Bass Winter Flounder
74

NEW REGULATIONS ARE BEING 

PROPOSED TO PROTECT FISH 

 

Current Situation

1.1 Billion Fish Lost 

 

With Advanced Filters

0.8 Billion Fish Lost 

0.3 Billion Fish 

Saved per Year

 

With Closed Cycle Cooling

<0.1 Billion Fish Lost

>1.0 Billion Fish 

Saved per Year

Advanced filters and closed cycle cooling are already in use at many facilities and are 

proven technologies. There are options being considered by the government that 

would require these types of equipment at all facilities. 

While these policies would reduce fish losses, they would also increase the 

costs of producing many goods and services — these costs would be passed on 

to consumers like you. 

Under current regulations, about 1.1 billion 

fish are lost in coastal waters. 

The government is considering policies that 

would require additional measures to protect 

fish. 

One policy would require advanced filters

that block fish from entering cooling water 

facilities. Requiring advanced filters could 

reduce fish losses about 25%. 

Another possibility is closed cycle cooling

that substantially reduces the need for 

outside cooling water. Requiring closed 

cycle cooling could reduce fish losses by 

95%. However, costs are higher than for 

advanced filters. 
75

WOULD YOU VOTE FOR POLICIES TO 

HELP PROTECT FISH AND FISH HABITAT? 

The government needs to know whether households are willing to pay the costs 

required to reduce fish losses and related ecological effects. This survey will help the 

government decide which policies will be enacted, if any. 

Question 2. Indicate the importance of the following issues to you. Check one box for 

each. 

Not 

Important

Somewhat 

Important

Very 

Important

1. Improving public safety 1 2 3 4 5

2. Protecting air quality 1 2 3 4 5

3. Reducing taxes 1 2 3 4 5

4. Improving homeland security 1 2 3 4 5

5. Protecting aquatic life and habitat 1 2 3 4 5

6. Maintaining industry and jobs 1 2 3 4 5

7. Reduce cost of living to 

households 1 2 3 4 5

8. Protecting water quality 1 2 3 4 5
76

THIS SURVEY IS SIMILAR TO A 

PUBLIC VOTE 

This survey asks you to compare policies with different effects on cooling water use, 

fish, and costs to your household. You will be asked to vote for the options you prefer. 

Effects of each project will be described using the following scores: 

TWO SCORES SHOW EFFECTS ON FISH 

Effect of 

Policy What It Means

Fish Saved 

(per Year) 

The reduction in the number of fish lost: 0 to 100 score showing the 

reduction in young fish losses because of the new policy. A score of 100 

means that no fish are lost in cooling water intakes (all fish are saved). A 

score of 0 represents the status quo. 

Commercial Fish 

Sustainability 

(Fish Used by People) 

A score between 0 - 100 that shows effects on the sustainability of 

commercial fish. Higher scores mean that fishing is more sustainable 

compared to fish population (see details on following pages). The current 

score in the Northeast US is 65. 

Fish Population 

(All Fish) 

A score between 0 - 100 that shows the size of all fish populations 

compared to the natural abundance without human influence. Higher 

scores mean more fish (see details on following pages). The current score 

in Northeast coastal waters is 37. 

Condition of 

Aquatic 

Ecosystems 

The effect on coastal ecosystems and food webs: 0 to 100 score 

showing the ecological condition of affected areas, compared to the most 

natural waters in the Northeast. Higher scores mean that the area is more 

natural (see details on following pages). The current score in Northeast 

coastal waters is 48.

$ 

Cost per Year 

How much the project will cost your household, in unavoidable price 

increases for products you buy. 
77

1. Commercial Fish Sustainability Score 

A score between 0 - 100 that shows effects on the sustainability of commercial fish. 

Higher scores mean that the ecosystem can maintain current fishing levels without 

compromising the ability of future generations to fish commercially. 

A score of 100 means that scientists are fairly certain that all fish stocks are used 

sustainably (e.g., fishing is within biological limits). 

The lowest score anywhere in the US is approximately 25. A score this low means that 

ecosystems can not maintain fish populations for half of all species, and that scientists 

do not have reliable information on 4 out of every 10 species. 

The current score in Northeast US waters is 654 — commercial fish sustainability is at 

65% of maximum. 

2. Fish Population Score 

A score between 0 - 100 that shows the size of all fish populations compared to 

population sizes without human influence. Higher scores mean more fish. 

A score of 100 means that populations are at the largest natural size possible in the 

ecosystem. This is the number of fish that existed before humans started fishing. 

A score of 0 would mean that there are no fish at all. 

The current score in Northeast US waters is 37 — current fish populations are at 37% 

of the size they would be without human influence. 

 

4

 Technical Note: The scientific name for this score is the Fish Stock Sustainability Index (FSSI), calculated by the 

National Oceanic and Atmospheric Administration (NOAA). Three components combine to make the overall score: (1) the 

size of commercial fish populations compared to the most productive biological size; (2) how many fish are caught 

compared to sustainable levels; (3) whether scientists have good information regarding fish populations. 
78

THE AQUATIC ECOSYSTEMS SCORE 

The Aquatic Ecosystems Score is a 0 - 100 score showing the effects of 

policies on the overall ecological condition of affected areas. 

It measures how close affected Northeast waters are to the most natural, undisturbed 

condition that is possible. Higher scores mean the area is more natural. 

The following information is combined to make the final score: 

Measurements Combined 

to Form the Aquatic 

Ecosystems Score 

What Each Measure Means 

Water Quality Score 

The score indicates whether the water is suitable for 

recreation and aquatic life. It is based on measures such as 

dissolved oxygen, nitrogen and phosphorus pollution, water 

clarity, temperature and algae. 

Benthic Score (bay, river 

or lake bottom)

The health of species that live on the bottom (e.g., 

mussels, crayfish). Measures such things as the number of 

all species and presence of rare species. 

Sediment Quality Score

Based on the survival of bottom dwellers, level of sediment 

pollution and excessive organic material on the bottom. 

Sediment quality will not be affected by the proposed 

programs. 

Coastal Habitat Score 

Based on average historical changes of wetland areas 

compared to changes in recent years. Wetland areas will 

not be affected by the proposed programs. 

Fish Tissue 

Contamination 

Contaminants measured in fish tissue are indicators of 

contaminants present in surface waters. Fish tissue 

contamination will not be affected by the proposed 

programs.
79

 

HOW WOULD YOU RATE THE 

IMPORTANCE OF THESE EFFECTS? 

Question 3. When considering policies that affect how coastal facilities use cooling 

water, how important to you are effects on each of the following scores? Check one 

box for each. (For reminders of what the scores mean, please see page 8). 

Not 

Important

Somewhat 

Important

Very 

Important

1. Effect on fish losses prevented 1 2 3 4 5

2. Effect on commercial fish 

sustainability 1 2 3 4 5

3. Effect on the fish populations 

(for all fish) 1 2 3 4 5

4. Effect on the condition of

aquatic ecosystems 1 2 3 4 5

5. Effect on cost to my household 1 2 3 4 5

The next questions will ask you to choose between different policy options that would 

affect fish losses in cooling water systems. 

You will be given choices and asked to vote for the choice you prefer by checking the 

appropriate box. Questions will look similar to the sample on the next page. 
80

SAMPLE QUESTION 

Questions will look like the sample below.

Policy Effect Current 

Situation 

(No policy) 

Option A Option B 

Fish Saved per Year 

(Out of 1.1 billion fish lost 

in salt water intakes)

0% 

No change in status quo

25% 

0.3 billion fish saved 

50% 

0.6 billion fish saved

Commercial Fish 

Sustainability 

(in 3-5 Years) 

65% 

Out of 100% maximum 

67% 

Out of 100% maximum 

69% 

Out of 100% maximum 

Fish Population 

(all fish) 

(in 3-5 Years) 

37% 

Out of 100% maximum 

40% 

Out of 100% maximum 

40% 

Out of 100% maximum 

Condition of Aquatic 

Ecosystems 

(in 3-5 Years) 

48% 

Out of 100% maximum 

48% 

Out of 100% maximum 

50% 

Out of 100% maximum 

$ 

Increase in Cost of 

Living for Your 

Household 

$0 

No cost increase 

$24 

per year

($2 per month) 

 

$36 

per year

($3 per month)

HOW WOULD 

YOU VOTE? 

(CHOOSE ONE 

ONLY) 



I would vote for 

NO POLICY



I would vote for 

OPTION A



I would vote for 

OPTION B

If you prefer Option A, 

check this box 

If you do not want A 

or B, check this box 

If you prefer Option B, 

check this box 

X X X 
81

AS YOU VOTE PLEASE REMEMBER 

 The map below shows the coastal (salt water) facilities and areas that would

be affected by the proposed policies. 

 Depending on the policies chosen, costs to your household could range from 

$0 per month to a maximum of $6 per month. 

 Depending on the type of technology required and other factors, effects on 

fish and ecosystems may be different—even if the annual reduction in fish 

losses is similar. 

 Consider each pair of policy options separately—do not add them up or 

compare programs from different pages.

 Scientists expect that effects on the environment and economy not shown 

explicitly will be small. 

 Your votes are important. Answer all questions as if this were a real, 

binding vote. 

Coastal Facilities Affected by the Proposed Policies 

Salt Water 

Facilities 
82

Question 4. Assume that Options A and B would require different 

technology to prevent fish losses in coastal facilities that use cooling water, 

and that all types of fish would be affected. How would you vote? 

Policy Effect 

NE Coastal

Current 

Situation 

(No policy) 

Option A 

NE Coastal

Option B 

NE Coastal 

Fish Saved per Year 

(Out of 1.1 billion fish 

lost in salt water intakes)

0% 

No change in status quo

25% 

0.3 billion fish saved 

50% 

0.6 billion fish saved

Commercial Fish 

Sustainability 

(in 3-5 Years) 

65% 

Out of 100% maximum 

65% 

Out of 100% maximum 

65% 

Out of 100% maximum 

Fish Population 

(all fish) 

(in 3-5 Years) 

37% 

Out of 100% maximum 

40% 

Out of 100% maximum 

40% 

Out of 100% maximum 

Condition of Aquatic 

Ecosystems 

(in 3-5 Years) 

48% 

Out of 100% maximum 

48% 

Out of 100% maximum 

50% 

Out of 100% maximum 

$ 

Increase in Cost of 

Living for Your 

Household 

$0 

No cost increase 

$24 

per year

($2 per month) 

 

$36 

per year

($3 per month)

HOW WOULD 

YOU VOTE? 

(CHOOSE ONE 

ONLY) 



I would vote for 

NO POLICY



I would vote for 

OPTION A



I would vote for 

OPTION B
83

Now you will be asked to consider a new set of policy options for Northeast 

waters. As you vote, please remember— 

 Questions 5 and 6 present a new set of policy options. These options require 

different technology in different areas. 

 Each question is a separate vote. Questions 5 and 6 cannot be directly 

compared to each other, or to Question 4. 

 Do not add up effects or costs across different questions. 

 Policy costs and effects depend on many factors. Saving more fish does not

necessarily mean that all effects will improve. 
84

Question 5. Assume that Options A and B would require different 

technology to prevent fish losses in coastal facilities that use cooling water, 

and that all types of fish would be affected. How would you vote? 

Policy Effect 

NE Coastal

Current 

Situation 

(No policy) 

Option A 

NE Coastal

Option B 

NE Coastal 

Fish Saved per Year 

(Out of 1.1 billion fish 

lost in salt water intakes)

0% 

No change in status quo

25% 

0.3 billion fish saved 

75% 

0.8 billion fish saved

Commercial Fish 

Sustainability 

(in 3-5 Years) 

65% 

Out of 100% maximum 

67% 

Out of 100% maximum 

69% 

Out of 100% maximum 

Fish Population 

(all fish) 

(in 3-5 Years) 

37% 

Out of 100% maximum 

37% 

Out of 100% maximum 

42% 

Out of 100% maximum 

Condition of Aquatic 

Ecosystems 

(in 3-5 Years) 

48% 

Out of 100% maximum 

48% 

Out of 100% maximum 

52% 

Out of 100% maximum 

$ 

Increase in Cost of 

Living for Your 

Household 

$0 

No cost increase 

$36 

per year

($3 per month) 

 

$40 

per year

($5 per month)

HOW WOULD 

YOU VOTE? 

(CHOOSE ONE 

ONLY) 



I would vote for 

NO POLICY



I would vote for 

OPTION A



I would vote for 

OPTION B
85

Question 6. Assume that Options A and B would require different 

technology to prevent fish losses in coastal facilities that use cooling water, 

and that all types of fish would be affected. How would you vote? 

Policy Effect 

NE Coastal

Current 

Situation 

(No policy) 

Option A 

NE Coastal

Option B 

NE Coastal 

Fish Saved per Year 

(Out of 1.1 billion fish 

lost in salt water intakes)

0% 

No change in status quo

95% 

1.0 billion fish saved 

50% 

0.6 billion fish saved

Commercial Fish 

Sustainability 

(in 3-5 Years) 

65% 

Out of 100% maximum 

72% 

Out of 100% maximum 

72% 

Out of 100% maximum 

Fish Population 

(all fish) 

(in 3-5 Years) 

37% 

Out of 100% maximum 

45% 

Out of 100% maximum 

45% 

Out of 100% maximum 

Condition of Aquatic 

Ecosystems 

(in 3-5 Years) 

48% 

Out of 100% maximum 

52% 

Out of 100% maximum 

52% 

Out of 100% maximum 

$ 

Increase in Cost of 

Living for Your 

Household 

$0 

No cost increase 

$72 

per year

($6 per month) 

 

$24 

per year

($2 per month)

HOW WOULD 

YOU VOTE? 

(CHOOSE ONE 

ONLY) 



I would vote for 

NO POLICY



I would vote for 

OPTION A



I would vote for 

OPTION B
86

 

Question 7. If you always voted for NO POLICY in questions 4-6, what was the 

primary reason? Check one. (Skip this question if you voted for Option A or B in any 

question above.) 

____ The cost to my household was too high 

____ Preventing fish losses is not important to me 

____ I do not trust the government to fix the problem 

____ I would rather spend my money on other things 

____ I did not believe the choices were realistic 

____ Since the problem was created by private facilities, they should fix it 

without passing costs on to consumers 

NATIONAL VERSUS NORTHEAST POLICIES

Now assume that the same types of policies were proposed for the entire 

United States instead of only the Northeast, and that affected facilities 

include all those shown on the map, including those in fresh and salt 

waters. How would you vote? 
87

Question 8. Now assume that the same types of policies were proposed for 

the entire United States. Assume that all US households would pay for 

these programs. How would you vote?

Policy Effect 

ALL of US

Current 

Situation 

(No policy) 

Option A 

ALL of US

Option B 

ALL of US 

Fish Saved per Year 

(Out of 2.7 billion fish 

lost in salt water intakes)

0% 

No change in status quo

25% 

0.7 billion fish saved 

50% 

1.4 billion fish saved

Commercial Fish 

Sustainability 

(in 3-5 Years) 

61% 

Out of 100% maximum 

61% 

Out of 100% maximum 

61% 

Out of 100% maximum 

Fish Population 

(all fish) 

(in 3-5 Years) 

42% 

Out of 100% maximum 

42% 

Out of 100% maximum 

44% 

Out of 100% maximum 

Condition of Aquatic 

Ecosystems 

(in 3-5 Years) 

46% 

Out of 100% maximum 

46% 

Out of 100% maximum 

48% 

Out of 100% maximum 

$ 

Increase in Cost of 

Living for Your 

Household 

$0 

No cost increase 

$72 

per year

($6 per month) 

 

$120 

per year

($10 per month)

HOW WOULD 

YOU VOTE? 

(CHOOSE ONE 

ONLY) 



I would vote for 

NO POLICY



I would vote for 

OPTION A



I would vote for 

OPTION B
88

Question 9. Indicate how strongly you agree with the following statements about 

questions 4 - 8 and the information provided. Check one box for each. 

Strongly 

Disagree Disagree Neutral Agree Strongly Agree 

The survey provided enough 

information for me to make 

informed choices 1 2 3 4 5

I feel confident about my 

answers 1 2 3 4 5 

Information in the survey was 

easy to understand 1 2 3 4 5

Information in the survey was 

fair and balanced 1 2 3 4 5

Questions were easy to 

answer 1 2 3 4 5

I would vote the same way in 

an actual public vote 1 2 3 4 5

The effect of the proposed 

policies depends on many 

factors 

1 2 3 4 5

Future ecological conditions 

are never 100% guaranteed 1 2 3 4 5
89

Question 10. How much did the following factors affect your answers to questions 4 – 

8? Check one box for each. 

Effect on my answers to questions 4-8 

Very Small 

Effect

Moderate 

Effect

Very Large 

Effect

. 

Wanting to reduce taxes or costs 

to my household. 1 2 3 4 5

Wanting to prevent the loss of 

industrial jobs. 1 2 3 4 5

Wanting to preserve fish for 

commercial fishing. 1 2 3 4 5

Wanting to send a message that 

all environmental issues are 

important regardless of cost. 

1 2 3 4 5

Wanting to preserve fish for 

recreation (fishing, etc.). 1 2 3 4 5

Wanting to preserve fish to benefit 

aquatic ecosystems. 1 2 3 4 5

Wanting to know that fish exist in 

local lakes, rivers and bays. 1 2 3 4 5

Wanting to pay my fair share for 

government programs. 1 2 3 4 5

Wanting to increase the 

competitiveness of US business 1 2 3 4 5

Wanting to preserve fish as a 

source of food for people. 1 2 3 4 5

Wanting to preserve fish and 

ecosystems for future generations. 1 2 3 4 5
90

Question 11. How many days did you participate in the following during the last year? 

Please include activities in ALL LOCATIONS. Remember to count each day 

separately for trips longer than one day. Check one box for each. 

Number of days you did the activity during the past year 

0 1-5 6-10 11-15 16+ 

Boating / Canoeing / Kayaking 1 2 3 4 5

Swimming / Going to the Beach 1 2 3 4 5

Recreational Fishing (Fresh Water) 1 2 3 4 5

Recreational Fishing (Salt Water) 1 2 3 4 5

Shellfishing / Crabbing 1 2 3 4 5

Scuba Diving / Snorkeling 1 2 3 4 5

Question 12. How many days did you participate in each of the following activities 

during the last year, IN THE NORTHEASTERN US ONLY? Northeastern states 

include: CT, DE, MA, MD, ME, NH, NJ, NY, RI, VT. Remember to count each day 

separately for trips longer than one day.Check one box for each. 

Number of days you did the activity during the past year 

0 1-5 6-10 11-15 16+ 

Boating / Canoeing / Kayaking 1 2 3 4 5

Swimming / Going to the Beach 1 2 3 4 5

Recreational Fishing (Fresh Water) 1 2 3 4 5

Recreational Fishing (Salt Water) 1 2 3 4 5

Shellfishing / Crabbing 1 2 3 4 5
91

Scuba Diving / Snorkeling 1 2 3 4 5

Question 13. For each of the following activities, indicate whether the activity is better 

or worse if there are more fish in the water. Check one box for each statement. 

Activity is 

worse if there 

are more fish 

Activity is not 

better or 

worse if there 

are more fish 

Activity is 

better if there 

are more fish 

N/A 

I do not 

participate in 

this activity 

Boating / Canoeing / Kayaking 1 2 3 4

Swimming / Going to the Beach 1 2 3 4

Recreational Fishing (Fresh Water) 1 2 3 4

Recreational Fishing (Salt Water) 1 2 3 4

Shellfishing / Crabbing 1 2 3 4

Scuba Diving / Snorkeling 1 2 3 4
92

The following questions ensure that all groups are fairly represented. 

All answers are anonymous and confidential. 

14. What is your age? ___ years 

15. What is your gender?  Male  Female 

16. What is the highest level of education that you have completed? 

Less than high school One or more years of college 

High school or equivalent Bachelor’s Degree 

High school + technical school Graduate Degree 

16. How many people live in your household? _____________ 

17. How many of these people are 16 years of age or older? ____ 

18. How many of these people are 6 years of age or younger? ____ 

19. What is your zip code?_____________________________ 

20. What town and state do you live in? Town: _____________ State:____ 

21. Are you currently employed? ___ Yes _____ No 

22. What category comes closest to your total household income? 

 Less than $10,000  $60,000 to $79,999 

 $10,000 to $19,999  $80,000 to $99,999 

 $20,000 to $39,999  $100,000 to $249,999 

 $40,000 to $59,999  $250,000 or more 

23. If you have any comments on this survey, please write them below: 

Thank you for your participation in this important survey!
93 

Attachment 2: Federal Register Notice 

ENVIRONMENTAL PROTECTION AGENCY 

[EPA-HQ-OW-2010-0595; FRL_XXXX-X] 

Agency Information Collection Activities; Proposed Collection; Comment Request; 

Willingness to Pay Survey for §316(b) Existing Facilities Cooling Water Intake Structures 

(New), EPA ICR No. 2402.01, OMB Control No. 2040-NEW 

AGENCY: Environmental Protection Agency (EPA). 

ACTION: Notice. 

SUMMARY: In compliance with the Paperwork Reduction Act (PRA) (44 U.S.C. 3501 et seq.), 

this document announces that EPA is planning to submit a request for a new Information 

Collection Request (ICR) to the Office of Management and Budget (OMB). Before submitting 

the ICR to OMB for review and approval, EPA is soliciting comments on specific aspects of the 

proposed information collection as described below. 

DATES: Comments must be submitted on or before [insert date 60 days after publication in the 

Federal Register]. 

ADDRESSES: Submit your comments, identified by Docket ID No. EPA-HQ-OW-2010-0595

by one of the following methods: 

• www.regulations.gov: Follow the on-line instructions for submitting comments. 

• Email: OW-Docket@epa.gov, Attention Docket ID No. EPA-HQ-OW-2010-

0595 
94 

• Mail: Water Docket, Environmental Protection Agency, Mailcode: 28221T, 1200 

Pennsylvania Ave., NW., Washington, DC 20460, Attention Docket ID No. EPAHQ-OW-2010-0595. Please include a total of 3 copies. 

• Hand Delivery: Water Docket, EPA Docket Center, EPA West, Room 3334, 1301 

Constitution Ave., NW., Washington, DC, Attention Docket ID No. EPA-HQOW-2010-0595. Such deliveries are only accepted during the Docket’s normal 

hours of operation and special arrangements should be made. 

Instructions: Direct your comments to Docket ID No. EPA-HQ-OW-2010-0595. EPA's policy 

is that all comments received will be included in the public docket without change and may be 

made available online at www.regulations.gov, including any personal information provided, 

unless the comment includes information claimed to be Confidential Business Information (CBI) 

or other information whose disclosure is restricted by statute. Do not submit information that you 

consider to be CBI or otherwise protected through www.regulations.gov or e-mail. The 

www.regulations.gov website is an “anonymous access” system, which means EPA will not 

know your identity or contact information unless you provide it in the body of your comment. If 

you send an e-mail comment directly to EPA without going through www.regulations.gov your 

e-mail address will be automatically captured and included as part of the comment that is placed 

in the public docket and made available on the Internet. If you submit an electronic comment, 

EPA recommends that you include your name and other contact information in the body of your 

comment and with any disk or CD-ROM you submit. If EPA cannot read your comment due to 

technical difficulties and cannot contact you for clarification, EPA may not be able to consider 

your comment. Electronic files should avoid the use of special characters, any form of 

encryption, and be free of any defects or viruses. For additional information about EPA’s public 

docket visit the EPA Docket Center homepage at http://www.epa.gov/dockets. 
95 

FOR FURTHER INFORMATION CONTACT: Erik Helm, Office of Water, Office of 

Science and Technology, Engineering and Analysis Division, Economic and Environmental 

Assessment Branch, 4303T, Environmental Protection Agency, 1200 Pennsylvania Ave., NW, 

Washington, DC 20460; telephone number: 202-566-1049; fax number: 202-566-1053; email 

address: Helm.Erik@epa.gov. 

SUPPLEMENTARY INFORMATION: 

How Can I Access the Docket and/or Submit Comments? 

 EPA has established a public docket for this ICR under Docket ID No. EPA-HQ-OW2010-0595 which is available for online viewing at www.regulations.gov, or in person viewing at 

the Water Docket in the EPA Docket Center (EPA/DC), EPA West, Room 3334, 1301 

Constitution Ave., NW, Washington, DC. The EPA/DC Public Reading Room is open from 

8:30 a.m. to 4:30 p.m., Monday through Friday, excluding legal holidays. The telephone number 

for the Reading Room is 202-566-1744, and the telephone number for the Water Docket is 202-

566-1752. 

 Use www.regulations.gov to obtain a copy of the draft collection of information, submit 

or view public comments, access the index listing of the contents of the docket, and to access 

those documents in the public docket that are available electronically. Once in the system, select 

“search,” then key in the docket ID number identified in this document. 

What Information is EPA Particularly Interested in? 

Pursuant to section 3506(c)(2)(A) of the PRA, EPA specifically solicits comments and 

information to enable it to: 

 (i) evaluate whether the proposed collection of information is necessary for the proper 

performance of the functions of the Agency, including whether the information will have 

practical utility; 
96 

 (ii) evaluate the accuracy of the Agency's estimate of the burden of the proposed 

collection of information, including the validity of the methodology and assumptions used; 

(iii) enhance the quality, utility, and clarity of the information to be collected; and 

 (iv) minimize the burden of the collection of information on those who are to respond, 

including through the use of appropriate automated electronic, mechanical, or other 

technological collection techniques or other forms of information technology, e.g., permitting 

electronic submission of responses. In particular, EPA is requesting comments from very small 

businesses (those that employ less than 25) on examples of specific additional efforts that EPA 

could make to reduce the paperwork burden for very small businesses affected by this collection. 

What Should I Consider when I Prepare My Comments for EPA? 

You may find the following suggestions helpful for preparing your comments: 

 1. Explain your views as clearly as possible and provide specific examples. 

 2. Describe any assumptions that you used. 

 3. Provide copies of any technical information and/or data you used that support your 

views. 

 4. If you estimate potential burden or costs, explain how you arrived at the estimate that 

you provide. 

 5. Offer alternative ways to improve the collection activity. 

 6. Make sure to submit your comments by the deadline identified under DATES. 

 7. To ensure proper receipt by EPA, be sure to identify the docket ID number assigned to 

this action in the subject line on the first page of your response. You may also provide the name, 

date, and Federal Register citation. 

What Information Collection Activity or ICR Does this Apply to? 

Affected entities: Entities potentially affected by this action are individuals/households.
97 

Title: Willingness to Pay Survey for Section 316(b) Existing Facilities Cooling Water Intake 

Structures: Instrument, Pre-test, and Implementation (New)

ICR numbers: EPA ICR No. 2402.01, OMB Control No. 2040-NEW. 

ICR status: This ICR is for a new information collection activity. An Agency may not conduct 

or sponsor, and a person is not required to respond to, a collection of information, unless it 

displays a currently valid OMB control number. The OMB control numbers for EPA's 

regulations in title 40 of the CFR, after appearing in the Federal Register when approved, are 

listed in 40 CFR part 9, are displayed either by publication in the Federal Register or by other 

appropriate means, such as on the related collection instrument or form, if applicable. The 

display of OMB control numbers in certain EPA regulations is consolidated in 40 CFR part 9. 

Abstract: Section 316(b) of the Clean Water Act (CWA) requires EPA to ensure that the 

location, design, construction, and capacity of cooling water intake structures (CWIS) reflect the 

best technology available (BTA) to protect aquatic organisms from being killed or injured by 

impingement or entrainment. EPA divided this rulemaking into three phases. At question here 

are the Phases II and III. 

The Phase II rule, which covered existing electric generating plants that withdraw at least 

50 million gallons a day (MGD) of cooling water, was completed in July 2004. Industry and 

environmental stakeholders challenged the Phase II regulations. On judicial review, the Second 

Circuit remanded several key provisions. In July 2007, EPA suspended the Phase II Rule. 

Following additional review in 2009 by the U.S. Supreme Court in Entergy Corp. v. Riverkeeper 

Inc., which decided that “EPA permissibly relied on cost-benefit analysis in setting the national 

performance standards ... as part of the Phase II regulations.” EPA has voluntary remanded the 

rule. 
98 

In June of 2006, EPA promulgated the 316(b) Phase III Rule for existing manufacturers, 

small flow power plants (facilities that withdraw less than 50 MGD), and new offshore oil and 

gas facilities. Offshore oil and gas firms and environmental groups petitioned for judicial review, 

which was to occur in the Fifth Circuit, but was stayed pending the completion of the Phase II 

litigation. EPA has asked the Fifth Circuit to remand the existing facilities portion of the Phase 

III rule so that it can consider what might be appropriate requirements for all existing facilities. 

While the 5th Circuit has not yet issued a decision, EPA is anticipating combining Phases II and 

III into one rulemaking covering all existing facilities. 

Under Executive Order 12866, EPA is required to estimate the potential benefits and 

costs to society of proposed rule options. To assess the public policy significance or importance 

of the ecological gains from the section 316(b) regulation for existing facilities, EPA requests 

approval from the Office of Management and Budget to conduct a stated preference survey. 

Data from the associated stated preference survey will be used to estimate values (willingness to 

pay, or WTP) derived by households for changes related to the reduction of fish losses at CWIS, 

and to provide information to assist in the interpretation and validation of survey responses. 

EPA has designed the survey to provide data to support the following specific objectives: [a] the 

estimation of the total values (use plus non-use) that individuals place on preventing losses of 

fish and other aquatic organisms caused by 316(b) facilities; [b] to understand how much 

individuals value preventing fish losses, increasing fish populations, and increasing commercial 

and recreational catch rates; [c] to understand how such values depend on the current baseline 

level of fish populations and fish losses, the scope of the change in those measures, and the 

certainty level of the predictions; and [d] to understand how such values vary with respect to 

individuals’ economic and demographic characteristics. 
99 

The target population for this stated preference survey is all individuals from continental 

U.S. households who are 18 years of age or older. The population of households will be 

stratified by the geographic boundaries of 5 EPA study regions: California, Great Lakes, Inland, 

Northeast, and Southeast. Survey participants will be recruited randomly through random digit 

dialing. The intended sample size for the survey is 2,000 households including only households 

providing completed surveys. This sample size was chosen to provide statistically robust results 

while minimizing the cost and burden of the survey. In addition to the sample size, EPA will 

take steps to both test for and ameliorate survey non-response bias. EPA will follow standard 

practice in stated preference design, including the extensive use of focus groups and pretesting to 

develop survey questionnaires.

The key elicitation questions in each of the five regional surveys ask respondents whether 

or not they would vote for policies that would increase their cost of living, in exchange for 

specified multi-attribute changes in [a] impingement and entrainment losses of fish, [b] 

commercial fish sustainability, [c] long-term fish populations, and [d] condition of aquatic 

ecosystems. This “choice experiment” or “choice modeling” framework allows respondents to 

state their preferences by making a voting-type selection between two hypothetical multiattribute regulatory options (and a third “status quo” choice that rejects both options). These 

stated preferences with respect to levels of environmental goods and cost to households, when 

used in conjunction with other information collected in the survey on the respondent’s use of the 

affected aquatic resources, household income, and other demographics, can be analyzed 

statistically (using either a fixed or random effects mixed logit framework) to estimate total WTP 

for the quantified environmental benefits of the 316(b) existing facilities rulemaking. Data 

analysis and interpretation is grounded in a standard random utility model. 
100 

In addition, to the total values, the survey will allow the estimation of values associated 

with specific choice attributes (following standard methods for choice experiments), and will 

also allow the flexibility to provide some insight into the relative importance of use versus nonuse values in the 316(b) context. Analysis also allows estimation of the variation in WTP across 

different types of households, in different areas. As indicated in prior literature, it is virtually 

impossible to justify, theoretically, the decomposition of empirical total willingness-to-pay 

estimates into separate use and non-use components. The survey will, however, provide the 

flexibility to estimate nonuser values, using various nonuser definitions drawn from responses to 

survey questions. The structure of the choice attribute questions will also allow the analysis to 

separate value components related to the most common sources of use values—effect on 

harvested recreational and commercial fish. 

The various welfare values that can be derived from this stated preference survey 

(discussed above) along with those that are estimated apart from the survey effort will offer 

insight into the composition of the value people place on the 316(b) environmental impacts. But 

within rulemaking, among the most crucial concerns is the avoidance of benefit (or cost) double 

counting. Here, for example, WTP estimates derived from the survey may overlap—to a 

potentially substantial extent—with estimates that can be provided through some other methods. 

Therefore, particular care will be given to avoid any possible double counting of values that 

might be derived from alternative valuation methods. In doing so, the Office of Water will rely 

upon standard theoretical tools for non-market welfare analysis, as presented by authors 

including Freeman (2003) and Just et al. (2004). 

Burden Statement: The annual public reporting and recordkeeping burden for this collection of 

information is estimated to average 5 minutes per telephone screening participant and 30 minutes 

per mail survey respondent including the time necessary to complete and mail back the 
101 

questionnaire. Burden means the total time, effort, or financial resources expended by persons to 

generate, maintain, retain, or disclose or provide information to or for a Federal agency. This 

includes the time needed to review instructions; develop, acquire, install, and utilize technology 

and systems for the purposes of collecting, validating, and verifying information, processing and 

maintaining information, and disclosing and providing information; adjust the existing ways to 

comply with any previously applicable instructions and requirements which have subsequently 

changed; train personnel to be able to respond to a collection of information; search data sources; 

complete and review the collection of information; and transmit or otherwise disclose the 

information. 

The ICR provides a detailed explanation of the Agency’s estimate, which is only briefly 

summarized here: 

Estimated total number of potential respondents: 8,333 for telephone screening and 2,000 

for mailed questionnaires. 

 Frequency of response: one-time response. 

 Estimated total average number of responses for each respondent: one-time response. 

 Estimated total burden hours: 1,527 hours. 

Estimated total costs: $ 34,600. EPA estimates that there will be no capital and operating 

and maintenance cost burden to respondents. 

What is the Next Step in the Process for this ICR? 

 EPA will consider the comments received and amend the ICR as appropriate. The final 

ICR package will then be submitted to OMB for review and approval pursuant to 5 CFR 

1320.12. At that time, EPA will issue another Federal Register notice pursuant to 5 CFR 

1320.5(a)(1)(iv) to announce the submission of the ICR to OMB and the opportunity to submit 
102 

additional comments to OMB. If you have any questions about this ICR or the approval process, 

please contact the technical person listed under FOR FURTHER INFORMATION CONTACT. 

Dated: ________________ 

__________________________________ 

Ephraim S. King, Director 

Office of Science and Technology
103 

Attachment 3: Description of Statistical Survey Design 

Experimental design and sampling strategies depend on the details of the final survey 

instrument, which cannot be finalized prior to focus groups. The following represents an 

anticipated experimental design for survey implementation, along with the associated number of 

completed surveys that will be required. Part B of this supporting statement provides detail on 

the sampling design. The proposed design and sampling plan is based on standard design and 

sampling theory for choice experiments and population surveys, as outlined by Louviere et al. 

(2000), Kuhfeld (2009) and Dillman (2000). 

The purpose of the 316(b) survey is to calculate average per household parameters (e.g., 

willingness to pay and choice probabilities) within a given survey population. No sub-population 

estimates are required. The anticipated experimental design for the choice experiment includes 

two multi-attribute choice options or alternatives, A and B, together with a fixed status quo or 

“no policy” option. Options A and B are characterized by levels for the following six attributes: 

1. Location in A and B (x1A; x1B) – 2 possible levels 

2. Fish Saved in A and B (x2A; x2B) – 3 possible levels 

3. Commercial Fish Sustainability in A and B (x3A; x3B) – 3 possible levels 

4. Fish Population in A and B (x4A; x4B) – 3 possible levels 

5. Aquatic Ecosystem Condition in A and B (x5A; x5B) – 3 possible levels 

6. Cost in A and B (x6A; x6B) - 6 possible levels 

This implies an experimental design characterized by [2 34

 6] for each alternative, or [22 38 62] 

for alternatives A and B combined. 

To construct a preliminary main effects design that is sufficiently flexible to estimate 

alternative specific main effects and response patterns (i.e., a non-generic design), we begin with 

the smallest available 100% efficient linear main effects plan for a full 22

 38 62 design. This treats 

each attribute of each alternative as a separate design element. The result is a design with 72 

profiles, with attributes labeled following the above notation, and levels indicated by integers 

1...N, where N for each attribute is the number of levels identified above: 
104 

Table 1: Set of 72 Design Profiles

Obs x1A x2A x3A x4A x5A x6A x1B x2B x3B x4B x5B x6B 

1 1 1 1 1 1 1 1 1 1 1 1 1 

2 1 1 1 1 2 2 2 2 2 2 2 2 

3 1 1 1 3 1 6 2 2 3 3 1 3 

4 1 1 1 3 3 5 2 1 1 2 3 2 

5 1 1 2 2 1 3 1 1 3 2 2 3 

6 1 1 2 2 2 1 2 3 1 1 2 4 

7 1 1 2 2 3 4 1 2 2 2 1 1 

8 1 1 2 2 3 6 1 3 2 3 3 6 

9 1 1 3 1 1 2 1 3 2 3 2 5 

10 1 1 3 1 2 3 2 1 3 1 3 6 

11 1 1 3 3 2 4 1 2 1 3 3 4 

12 1 1 3 3 3 5 2 3 3 1 1 5 

13 1 2 1 1 2 4 2 3 3 2 1 6 

14 1 2 1 2 2 5 1 3 3 3 2 1 

15 1 2 1 2 3 2 1 3 1 1 3 3 

16 1 2 1 3 1 3 2 3 2 2 3 4 

17 1 2 2 1 1 5 2 1 2 3 1 4 

18 1 2 2 1 3 1 2 2 3 2 3 5 

19 1 2 2 3 1 2 1 2 1 1 1 6 

20 1 2 2 3 2 6 1 1 1 2 2 5 

21 1 2 3 1 3 4 1 1 1 3 2 3 

22 1 2 3 2 1 1 1 2 3 3 3 2 

23 1 2 3 2 2 6 1 1 2 1 1 2 

24 1 2 3 3 3 3 1 2 2 1 2 1 

25 1 3 1 1 3 6 2 2 3 1 2 4 

26 1 3 1 2 1 4 2 1 2 1 3 5 

27 1 3 1 2 2 3 1 2 1 3 1 5 

28 1 3 1 3 3 1 1 1 2 3 2 6 

29 1 3 2 1 2 5 2 2 2 1 3 3 

30 1 3 2 1 3 3 2 3 1 3 1 2 

31 1 3 2 3 1 4 2 3 3 1 2 2 

32 1 3 2 3 2 2 2 1 3 3 3 1 

33 1 3 3 1 1 6 1 3 1 2 3 1 

34 1 3 3 2 1 5 2 2 1 2 2 6 

35 1 3 3 2 3 2 1 1 3 2 1 4 

36 1 3 3 3 2 1 2 3 2 2 1 3 

37 2 1 1 1 1 1 2 1 1 1 1 1 

38 2 1 1 1 2 2 1 2 2 2 2 2 

39 2 1 1 3 1 6 1 2 3 3 1 3 

40 2 1 1 3 3 5 1 1 1 2 3 2 

41 2 1 2 2 1 3 2 1 3 2 2 3 

42 2 1 2 2 2 1 1 3 1 1 2 4 

43 2 1 2 2 3 4 2 2 2 2 1 1 

44 2 1 2 2 3 6 2 3 2 3 3 6 

45 2 1 3 1 1 2 2 3 2 3 2 5 

46 2 1 3 1 2 3 1 1 3 1 3 6 
105 

47 2 1 3 3 2 4 2 2 1 3 3 4 

48 2 1 3 3 3 5 1 3 3 1 1 5 

49 2 2 1 1 2 4 1 3 3 2 1 6 

50 2 2 1 2 2 5 2 3 3 3 2 1 

51 2 2 1 2 3 2 2 3 1 1 3 3 

52 2 2 1 3 1 3 1 3 2 2 3 4 

53 2 2 2 1 1 5 1 1 2 3 1 4 

54 2 2 2 1 3 1 1 2 3 2 3 5 

55 2 2 2 3 1 2 2 2 1 1 1 6 

56 2 2 2 3 2 6 2 1 1 2 2 5 

57 2 2 3 1 3 4 2 1 1 3 2 3 

58 2 2 3 2 1 1 2 2 3 3 3 2 

59 2 2 3 2 2 6 2 1 2 1 1 2 

60 2 2 3 3 3 3 2 2 2 1 2 1 

61 2 3 1 1 3 6 1 2 3 1 2 4 

62 2 3 1 2 1 4 1 1 2 1 3 5 

63 2 3 1 2 2 3 2 2 1 3 1 5 

64 2 3 1 3 3 1 2 1 2 3 2 6 

65 2 3 2 1 2 5 1 2 2 1 3 3 

66 2 3 2 1 3 3 1 3 1 3 1 2 

67 2 3 2 3 1 4 1 3 3 1 2 2 

68 2 3 2 3 2 2 1 1 3 3 3 1 

69 2 3 3 1 1 6 2 3 1 2 3 1 

70 2 3 3 2 1 5 1 2 1 2 2 6 

71 2 3 3 2 3 2 2 1 3 2 1 4 

72 2 3 3 3 2 1 1 3 2 2 1 3 

This candidate design will be subject to refinements based on results of focus groups and 

other design evaluations (e.g., to eliminate dominated profiles), as described by Louviere et al. 

(2000) and Kuhfeld (2009), but this will not significantly alter design dimensions. 

Following common examples in the environmental economics literature, we anticipate 

three choice questions per survey. This will allow the 72 profiles to be included (orthogonally 

blocked) in 24 unique survey booklets. Monte Carlo experiments indicate that approximately 6 

completed responses are required for each profile in order to achieve large sample statistical 

properties for choice experiments (Louviere et al. 2000, p. 104, citing Bunch and Batsell 1989). 

Following this guidance, the above design will require 24×6 = 144 completed surveys, or 6 

completed surveys for each unique survey booklet. This will provide a total of 432 profile 

responses. 
106 

Sample Sizes for Maximum Acceptable Sampling Error 

The goal of the choice experiment is to estimate regression coefficients from mixed or 

conditional logit models that may be used to estimate willingness to pay for multi-attribute 

policy alternatives, or the likelihood of choosing a given multi-attribute alternative, following 

standard random utility modeling procedures (Haab and McConnell 2002). Required sample 

sizes to estimate population parameters with given degrees of freedom are drawn from standard 

statistical theory, as described by Dillman (2000). 

The maximum acceptable sampling error for predicting response probabilities (the 

likelihood of choosing a given alternative) in the present case is ±10%, assuming a true response 

probability of 50% associated with a utility indifference point. Given the survey population size, 

this level of precision requires a minimum sample size of approximately 96 observations. The 

number of observations (completed surveys) required to obtain large sample properties for the 

choice experiment design provide more than sufficient observations to obtain this required 

precision for population parameters. The choice experiment design requires 432 completed 

profile responses from 144 surveys. Statistical theory shows that 400 assumed-independent 

profile responses will allow a 50% choice probability to be estimated within ±4.9 percent, at a 

95% confidence level. With only a single choice question per survey (144 responses), the same 

probability and confidence level can be obtained within approximately ±8.2 percent; this is also 

within acceptable limits. 

Experimental Design Allowing Two-Way Interactions with Location (x1A; x1B) 

In order to estimate a parallel design that allows for interactions with policy location, and 

insulates main effects from these interactions, we follow the suggested design strategies of 

Louviere et al. (2000). First, we estimate the smallest available 100% efficient linear main 

effects plan for non-location factors (X2 – X6) across both alternatives A and B, [38

 62]. This 

results in a main effects design with 36 profiles: 

Table 2: Set of 36 Design Profiles 

Obs x2A x3A x4A x5A x6A x2B x3B x4B x5B x6B 

1 1 1 1 1 1 1 1 1 1 1 

2 1 1 2 2 2 2 2 2 1 2 

3 1 1 2 3 4 3 2 1 1 6 

4 1 1 3 2 6 3 1 2 2 4 

5 1 2 1 1 4 2 1 3 2 5 
107 

6 1 2 2 2 3 1 3 1 3 5 

7 1 2 2 3 5 3 3 2 3 1 

8 1 2 3 3 2 1 1 3 1 3 

9 1 3 1 2 6 3 3 1 2 3 

10 1 3 1 3 3 2 2 3 3 4 

11 1 3 3 1 1 2 3 2 3 6 

12 1 3 3 1 5 1 2 3 2 2 

13 2 1 1 1 5 2 3 1 1 4 

14 2 1 2 2 5 2 1 3 3 3 

15 2 1 3 2 1 3 2 3 3 5 

16 2 1 3 3 3 1 3 1 2 2 

17 2 2 1 1 3 3 2 2 1 3 

18 2 2 2 3 1 1 1 2 2 4 

19 2 2 3 2 4 2 2 1 2 1 

20 2 2 3 3 6 2 3 3 1 6 

21 2 3 1 2 2 1 1 1 3 6 

22 2 3 1 3 4 3 1 2 3 2 

23 2 3 2 1 2 3 3 3 2 1 

24 2 3 2 1 6 1 2 2 1 5 

25 3 1 1 3 2 2 3 2 2 5 

26 3 1 1 3 6 1 2 3 3 1 

27 3 1 2 1 3 3 1 3 2 6 

28 3 1 3 1 4 1 3 2 3 3 

29 3 2 1 2 1 3 3 3 1 2 

30 3 2 1 2 5 1 2 2 2 6 

31 3 2 2 1 6 2 1 1 3 2 

32 3 2 3 1 2 3 2 1 3 4 

33 3 3 2 2 4 1 3 3 1 4 

34 3 3 2 3 1 2 2 1 2 3 

35 3 3 3 2 3 2 1 2 1 1 

36 3 3 3 3 5 3 1 1 1 5 

This design is then repeated for each of the four possible combinations of values for x1A

and x1B (i.e., 1,1; 2,2; 1,2; 2,1) creating a candidate design of 36×4 = 144 profiles. The resulting 

design fully insulates all main effects (eliminates aliasing) from interactions with location 

attributes x1A and x1B, and allows associated location interactions to be estimated independent of 

main effects. The number of required survey versions (48) and completed surveys (288) is 

doubled compared to the main effects plan outlined above. As above, the number of 

observations (completed surveys) required to obtain large sample properties for the choice 

experiment design provide sufficient observations to obtain required precision for population 

parameters.1 Also as above, this candidate design may be subject to refinements based on results 

 

1

 Alternatively, the smallest possible main effects plan for all attributes (72 profiles) may be folded over to make 

another 72 profiles, for a combined set of 144 profiles. This protects main effects from all unobserved 2-way 
108 

of focus groups and other design evaluations, as described by Louviere et al. (2000) and Kuhfeld 

(2009), but this is unlikely to alter design dimensions. 

 interactions, but does not guarantee that specific interactions may be estimated. The required sample size is the 

same as that which would guarantee that location interactions can be estimated. 
109 

Attachment 4: Description of Internet-based Sampling Alternative 

EPA is also considering the use of an internet-based (i.e., web-based) sampling approach 

as an alternative to the mail survey described in Part B of the supporting statement. The survey 

content, pre-testing, review process, and data analysis would be identical to the mail survey 

described in Parts A and B of the supporting statement. To support implementation of the webbased alternative, EPA would retain a vendor that maintains a preexisting representative national 

panel. . This attachment provides a brief summary of the web-based alternative, focusing on 

differences from the mail survey approach described in Part B of the supporting statement. 

Sampling Frame 

The sampling frame for the web-based survey is the panel of individuals previously 

recruited by a vendor to participate in online surveys. The overall sampling frame would be the 

set of all individuals in continental U.S. households who are 18 years of age or older and who 

have listed phone numbers. Individuals in the panel most likely be recruited using a list-assisted 

random digit dialing telephone methodology, thus providing a probability-based starting sample 

of U.S. telephone households. Panels of this type are usually routinely supplemented to account 

for panel attrition. The preexisting panel would have to closely tracks the U.S. population on 

age, race, Hispanic ethnicity, geographical region, employment status, and other demographic 

elements. If differences between the panel and the U.S. population do exist, sample weights 

using U.S. Census demographic benchmarks could be developed to reduce error due to noncoverage of non-telephone households and to reduce bias due to non-response and other nonsampling errors. 

Sample Size 

The intention is to obtain 2,000 completed web-based surveys from the preexisting panel. 

The same geographically stratified design will be implemented following the same the same 

regions and sample sizes as described in Part B of the supporting statement under the mail survey 

approach. Within each region, the sample will be stratified by demographic variables including 

age, education, Hispanic ethnicity, race, gender, and household income. The actual number of 

panel members contacted for this survey will be determined by the vendor’s knowledge of within 

panel response rates. Most likely, the stratification design used in the web-based survey will 
110 

systematically oversamples groups that tend to have lower response and consistency rates so that 

the demographic characteristics of respondents who provide valid completed surveys will mirror 

the Census demographic benchmarks more closely. This potential oversampling correction 

technique will reduce error due to non-coverage of non-telephone households in the original 

panel member recruitment process, and will also reduce bias due to non-response and other nonsampling errors. 

Survey Response 

The target response rate for the survey among panel members that are sampled is 80 

percent. However, the actual response rate compared to the general population is lower, given 

that the telephone recruitment process for a preexisting panel has an expected response rate in 

the 30 to 40 percent range. This will produce a lower cumulative response rate. Panel members 

who are selected for the survey will be contacted to inform them that the survey is available 

online and reminders will be sent to panel members who do not complete the survey within a 

short period of time. 

Although the cumulative response rate for this survey may be low compared to response 

rates typically achieved using other survey methods (e.g., phone and mail surveys), the webbased format facilitates geographic and demographic stratification, which will substantially 

improve the quality of the survey. 

Non-response and Other Non-Sampling Error Corrections 

Approaches to minimize non-response bias in internet surveys are established in the 

literature (Dillman 2000) and include initial RDD probability sampling, careful panel 

management, and effective survey sampling procedures. The representativeness of preexisting 

panel survey sample is generally comparable to those telephone surveys sponsored by various 

Federal agencies. Nonetheless, EPA would conduct several additional activities to minimize the 

potential for non-response bias if the survey were implemented through the use of a preexisting 

panel including: (1) use of a stratified survey sample to mitigate the effect of non-response bias, 

(2) use of non-response follow-up interviews to increase the overall response rate, and (3) 

statistical correction for unobserved heterogeneity that might be present in the data from 

respondents interviewed for this study 
111 

Non-response Interviews 

In order to minimize non-response bias from individuals who chose not to respond during 

some stage of panel recruitment, EPA will conduct non-response follow-up interviews within the 

initial sample for all stages of panel attrition. Respondents will include individuals who were 

contacted but did not join the preexisting panel, who agreed to join the panel but did not connect 

to the vendors web-site, who connected but did not complete the first survey, who completed the 

first survey but did not complete any following surveys, and who completed following surveys 

but did not complete the 316(b) survey. The end result of this effort will be a direct 

measurement of non-response bias and EPA will use the information to increase the effective 

cumulative response rate by using a weighted response rate formulation. 

Statistical Correction for Unobserved Heterogeneity 

EPA is also considering the use of a statistical technique to correct for unobserved 

heterogeneity, based on work by Heckman (Heckman, 1979). This correction would be 

conducted as a complement to a non-response study effort. The technique will provide the 

probabilities of participation for each subpopulation grouping (as defined by Census long form 

data, voting data, and other data sources) included in the initial sample frame. These 

probabilities of participation will demonstrate the extent of self-selection bias in the actual 

survey sample. The selection correction technique will take fully into account each stage of the 

panel recruitment and sampling process: that is, all stages in between construction of the sample 

frame for panel recruitment and interviewing of the panel respondents. 

The technique could be used to produce both adjusted and unadjusted estimates of WTP. 

Because the technique yields regression estimates that explain survey outcomes using 

subpopulation data related to neighborhood characteristics, it can be used to identify the sources 

of differences between the adjusted and unadjusted estimates. 

As described above, EPA will use statistical techniques to correct for unobserved 

heterogeneity in the survey sample and non-response follow-up interviews to increase the 

effective survey response rate. Combined, these techniques will reduce error due to noncoverage of non-telephone households in the original panel recruitment process, and also reduce 

bias due to non-response and other non-sampling errors. For an example of a similar research 
112 

effort that successfully used this web-based survey approach to evaluate WTP for changes in 

water quality, see Viscusi et al. (2004). 

Data Preparation 

Since the survey will be administered as an online survey, survey responses will be 

automatically entered into an electronic database at the time they are submitted. After all 

responses are submitted, the database contents will be converted into a format suitable for use in 

EPA’s statistical analysis. 
113 

Attachment 5: Telephone Screener Script 

Fish and Aquatic Habitat Telephone Screener 

Hello, this is _________________calling from the Abt Associates. We are conducting an 

important survey of U.S. residents for the Environmental Protection Agency, or EPA. This is not 

a sales call. 

SL1 [ASK IF SAMPLE=LANDLINE] 

Could you please tell me how many people, age 18 and older, live in this household? 

IF NEEDED: This study will help us to better understand the value of environmental protection 

and public programs. Any answers you give are kept strictly confidential. 

IF ASKED: THIS IS A SHORT SURVEY WHICH SHOULD TAKE NO MORE THAN FIVE 

MINUTES. 

0 None THANK AND SCREEN OUT 

1 One 

__ Number of persons 16+ SKIP TO SL1c 

98 Refused (VOL) THANK AND TERMINATE – Soft Refusal 

99 Refused (VOL) THANK AND TERMINATE – Hard Refusal 

SL1b [ASK IF SAMPLE=LANDLINE] 

May I speak with that person? 

1 Rspn on line SKIP TO SL2

2 Rspn called to phone SKIP TO SL1d

3 Rspn unavailable SCHEDULE CALLBACK 

8 Refused THANK AND TERMINATE – Soft Refusal

9 Refused THANK AND TERMINATE – Hard Refusal 

SL1c [ASK IF SAMPLE=LANDLINE] 

In order to select just one person to interview, may I please speak to the person 

in your household, age 18 or older, who (has had the most recent/will have the 

next) birthday? 

1 Rspn on line SKIP TO SL2

2 Rspn called to phone 

3 Rspn unavailable SCHEDULE CALLBACK

8 Refused THANK AND TERMINATE – Soft Refusal

9 Refused THANK AND TERMINATE – Hard Refusal 
114 

SL1d[ASK IF SAMPLE=LANDLINE] 

Hello, this is _________________calling from the Abt Associates. We are 

conducting an important survey of U.S. residents for the Environmental 

Protection Agency, or EPA. Could we begin now? 

IF ASKED: THIS IS A SHORT SURVEY WHICH SHOULD TAKE NO MORE 

THAN FIVE MINUTES. 

1 Yes 

2 No time SCHEDULE CALLBACK

8 Refused THANK AND TERMINATE – Soft Refusal

9 Refused THANK AND TERMINATE – Hard Refusal 

SL2 [ASK IF SAMPLE=LANDLINE] 

Do you have a cell phone in addition to the line on which we’re speaking right now? 

1 Yes, also have cell phone 

2 No, this is only phone SKIP TO SA2

8 (VOL) Don’t know THANK AND END, screen out 

9 Refused THANK AND END, soft refusal

SC1 [ASK IF SAMPLE = CELL] 

Are you in a safe place to talk right now? 

IF NEEDED: Are you Driving? [IF RESPONDENT ANSWERS YES, DRIVING, 

SCHEDULE CALLBACK AND TERMINATE - CODE AS 2] 

IF ASKED: THIS IS A SHORT SURVEY WHICH SHOULD TAKE NO MORE THAN FIVE 

MINUTES. 

1 Yes, safe place to talk 

2 No, call me later SCHEDULE CALLBACK

3 No, CB on land-line RECORD NUMBER, schedule call back

4 Cell phone for business only THANK & END - BUSINESS#

8 Refused THANK AND TERMINATE – Soft Refusal 

9 Refused THANK AND TERMINATE – Hard Refusal 

SC2 [ASK IF SAMPLE=CELL] 

Are you at least 18 years old? 

IF NEEDED: This study will help us to better understand the value of environmental 

protection and public programs. Any answers you give are kept strictly confidential. 

1 Yes 

2 Yes, no time SCHEDULE CALLBACK
115 

3 No SCREEN OUT

8 Refused THANK AND TERMINATE – Soft Refusal 

9 Refused THANK AND TERMINATE – Hard Refusal 

SC3 [ASK IF SAMPLE=CELL] 

Do any other people age 18 or older regularly ANSWER your cell phone, or just you? 

INTERVIEWER: This question refers to the physical phone and not to their calling plan 

1 Yes, others 

2 No, just respondent SKIP TO SC4

9 Don’t know/Refused SKIP TO SC4

SC3b [ASK IF SAMPLE=CELL] 

How many other people age 18 or older regularly answer your cell phone? 

[ENTER NUMBER 1-10] 

99 Don’t know/Refused

SC4 [ASK IF SAMPLE=CELL] 

Not counting any that are used strictly for business purposes, are there other cell phones 

that you use regularly, or is it just the one? 

1 Yes, use other cell phones 

2 No SKIP TO SC5

9 Don’t know/Refused SKIP TO SC5

SC4b [ASK IF SAMPLE=CELL] 

How many other cell phones do you use regularly, excluding those used only for 

business purposes? 

 

[ENTER NUMBER 1-10] 

99 Don’t know/Refused 

SC5 [ASK IF SAMPLE=CELL]

Not counting (this/these) cell phone(s), do you also have a regular land-line phone at 

home? 

1 Yes, has a regular phone at home SKIP TO SA1

2 No, cell is only phone SKIP TO SA2 

7 Don’t know (VOL) THANK AND TERMINATE – Screen out

8 Refused (VOL) THANK AND TERMINATE – Soft Refusal 

9 Refused (VOL) THANK AND TERMINATE – Hard Refusal 
116 

SA1 [ASK BOTH SAMPLES] 

Of all of the phone calls that you or your family receives, are...(Read List) 

1 all or almost all calls received on cell phones, 

2 some received on cell phones and some received on land lines, or 

3 very few or none on cell phones. 

8 (VOL) Don’t know 

9 (VOL) Refused 

SA2 Record gender from observation. (Ask only if Necessary) 

1 Male 

2 Female 

1. (MATCHES Q2 IN THE MAIL SURVEY) First, would you please tell me the importance of 

each of the following issues to you, on a scale of 1 to 5 where 1 is “not important” and 5 is “very 

important”: (DO NOT ROTATE SO THAT THE QUESTION MATCHES THE PAPER VERSION) 

a. Improving public safety 

b. Protecting air quality 

c. Reducing taxes 

d. Improving homeland security 

e. Protecting aquatic life and habitat 

f. Maintaining industry and jobs 

g. Reducing your cost of living 

h. Protecting water quality 

2. People have ideas about the extent to which the government should be involved in protecting 

the environment. On a scale of 1 to 5 where 1 is “not at all involved” and 5 is “highly involved”, 

how involved do you think the government should be in environmental protection? 

 1 2 3 4 5 (VOL) DK (VOL) Ref 

3. Could you please tell me if you participated in each of following activities during the last 

year? (DO NOT ROTATE) 

Yes 

No 

(VOL) Don’t Know 

(VOL) Refused 

a. Boating, canoeing, or kayaking 

b. Swimming/going to the beach 

c. Fresh Water Recreational fishing 

d. Salt Water Recreational fishing 

e. Shell fishing or crabbing 

f. Scuba diving or snorkeling 
117 

Now, I have just a few questions for classification purposes. 

D1. What is your age? 

 ________ Years DK Ref 

D2. What is the highest level of education that you have completed? Is it... (READ LIST) 

1 Less than high school 

2 High school or equivalent 

3 High school and technical school 

4 One or more years of college 

5 Bachelor’s degree 

6 Graduate degree 

D3. Including everyone living in your household, which of the following categories best 

describes your total household income before taxes? Is it ... (READ LIST)

1 $10,000 or Less, 

2 Between $10,001 and $20,000, 

3 Between $20,001 to $35,000, 

4 Between $35,001 to $50,000, 

5 Between $50,001 to $75,000, 

6 Between $75,001 to $100,000, or 

7 More than $100,000 

8 (VOL) Don’t know 

9 (VOL) Refused 

D4. Are you of Hispanic or Latino origin?

1 Yes 

2 No 

8 (VOL) don’t know 

9 (VOL) Refused 

D5. Which of the following racial categories describes you? You may select more than one. 

Would it be... (READ LIST – MULTIPLE RECORD) 

1 American Indian or Alaskan Native, 

2 Asian, 

3 Black or African American, 

4 Native Hawaiian or Other Pacific Islander, or 

5 White 

6 (VOL) Hispanic / Latino 

8 (VOL) Other 

9 (VOL) Refused 

D6. Do you... (READ LIST) 

1 Rent your home or apartment 

2 Own your own home 

3 Live with family or friends and pay part of the rent or mortgage 
118 

4 Live with family or friends and do not pay rent 

7 (VOL) Other, Specify 

8 (VOL) Other 

9 (VOL) Refused 

Recruitment:

In addition to this telephone survey, we are also conducting a mail survey to help U.S. 

policymakers to better understand your priorities for the environment and the use of public 

funds. This survey will be mailed to households along with a free reply envelope 

The survey takes most people about 25 minutes to complete. 

 I1. Would you be willing to participate in this mail survey? 

 

1 Yes 

2 No 

3 Don’t know 

4 Refused 

(IF NO, DK, OR REF ) Thank you very much for your participation today. 

I2. (IF I1 = 1) To what name and address should we mail the survey? (RECORD NAME, 

ADDRESS, CITY, STATE, AND ZIP CODE AND REPEAT BACK) 

I3. And is this the best number to reach you at if we should have a problem mailing your 

survey? 

 

1 Yes 

2 No 

 

I4. (IF I3 = 2) What is the best number to reach you? (RECORD NUMBER AND REPEAT 

BACK) 

Thank you. The survey will be sent to you in approximately one to two weeks. The packet will 

include information about the study, how to return your survey, and additional contact 

information in case you have questions. Thank you very much for your time, and have a great 

evening/day.