Prepared for:

U.S. Fish and Wildlife Service

U.S. Department of Interior

U.S. Department of Justice

Prepared by:

Stratus Consulting Inc.

P.O. Box 4059

Boulder, CO 80306-4059

(303) 381-8000

Contacts:

Richard C. Bishop

William S. Breffle

Jeffrey K. Lazo

Robert D. Rowe

Sonya M. Wytinck

October 25, 2000

RESTORATION SCALING BASED ON TOTAL

VALUE EQUIVALENCY: GREEN BAY

NATURAL RESOURCE

DAMAGE ASSESSMENT

Final Report
Contents

Acronyms ................................................................................................................................. v

Figures ............................................................................................................................... vii

Tables ................................................................................................................................ ix

Chapter 1 Introduction

1.1 Purpose of the Study ............................................................................................ 1-1

1.2 Background.......................................................................................................... 1-2

1.3 Objectives ............................................................................................................ 1-3

1.4 Approach.............................................................................................................. 1-7

1.5 Summary of Results........................................................................................... 1-11

Chapter 2 Survey Design

2.1 Survey Design Overview ..................................................................................... 2-1

2.1.1 Background.............................................................................................. 2-1

2.1.2 Selection of the stated preference choice-question survey approach....... 2-4

2.1.3 Choice-question method as an established method ................................. 2-5

2.1.4 Key design considerations ....................................................................... 2-6

2.2 Detailed Design.................................................................................................. 2-14

2.2.1 Introductory materials............................................................................ 2-14

2.2.2 Natural resource topics .......................................................................... 2-16

2.2.3 Choice questions.................................................................................... 2-19

2.2.4 Follow-up questions and demographics................................................. 2-24

Chapter 3 Survey Implementation

3.1 Sample Selection.................................................................................................. 3-1

3.2 Implementation .................................................................................................... 3-3

3.3 Evaluation of Potential Sample and Nonresponse Biases.................................... 3-6

3.3.1 Introduction.............................................................................................. 3-6

3.3.2 Comparison of phone survey and mail survey respondents..................... 3-7

3.3.3 Comparison of Census information and mail survey respondents........... 3-9

3.4 Summary ............................................................................................................ 3-14

Chapter 4 Survey Results

4.1 Introduction.......................................................................................................... 4-1

4.2 Topic Awareness.................................................................................................. 4-1

4.3 Outdoor Recreational Activity in and around the Waters of Green Bay Area .... 4-2
Stratus Consulting (Final, 10/25/00)

Page iv

4.4 Importance and Action Scores............................................................................. 4-6

4.4.1 Benefits importance scores...................................................................... 4-6

4.4.2 Action scores............................................................................................ 4-9

4.5 Evaluation Scores............................................................................................... 4-10

4.6 Comments.......................................................................................................... 4-12

4.7 Choice Pair Evaluation Using Simple Comparisons ......................................... 4-14

Chapter 5 A Model of Preferences for Resource Alternatives

5.1 Introduction.......................................................................................................... 5-1

5.2 Factors Affecting Utility from Green Bay Resources.......................................... 5-1

5.3 Other Model Features .......................................................................................... 5-3

5.3.1 Positioning effects.................................................................................... 5-3

5.3.2 Varying difficulty of choice..................................................................... 5-3

5.4 The Utility Function............................................................................................. 5-5

5.5 Willingness to Pay per Household....................................................................... 5-7

5.6 Model Estimation................................................................................................. 5-8

5.7 The Estimated Model........................................................................................... 5-8

5.7.1 Signs and significance of the parameter estimates .................................. 5-8

5.7.2 Measures of model fit ............................................................................ 5-12

Chapter 6 Restoration Scaling and Valuation Results

6.1 Introduction.......................................................................................................... 6-1

6.2 Restoration Scaling .............................................................................................. 6-1

6.3 WTP Measures of Values .................................................................................... 6-5

6.3.1 Population-weighted annual measures of WTP per household ............... 6-5

6.3.2 Aggregate present values of PCB-caused losses ..................................... 6-8

6.3.3 Comparison to recreational fishing damage determination ................... 6-10

6.4 Conclusions........................................................................................................ 6-13

References ............................................................................................................................. R-1

Appendices

A Survey Materials

B Modeling Consumer Preferences for Green Bay Resource Characteristics Using

Stated Preference Data

C Survey with Means and Frequencies

D Existing Literature
Acronyms

CERCLA Comprehensive Environmental Reponses, Compensation, and Liability Act

CVM contingent valuation method

EPA U.S. Environmental Protection Agency

FCAs fish consumption advisories

FRGS Fox River Global Meeting Goal Statement

iRCDP Initial Restoration and Compensation Determination Plan

NRDA natural resource damage assessment

PCBs polychlorinated biphenyls

RAP Remedial Action Plan

RCDP Restoration and Compensation Determination Plan

RI/FS Remedial Investigation and Feasibility Study

RV revealed preference

SP stated preference

TVE total value equivalency

WTP willingness to pay
Figures

1.1 Wisconsin and Michigan waters of Green Bay................................................................ 1-4

1.2 Sample choice question.................................................................................................... 1-9

1.3 PCB-caused service flow losses under alternative time paths for a return

to baseline ...................................................................................................................... 1-11

2.1 Typical choice question ................................................................................................... 2-3

2.2 Target population counties............................................................................................. 2-11

6.1 Population-weighted willingness to pay estimates for resource programs...................... 6-7
Tables

1.1 Importance of natural resource action benefits.............................................................. 1-12

1.2 Preferred actions for natural resource programs............................................................ 1-12

1.3 Illustration of restoration scaling ................................................................................... 1-14

2.1 Green Bay total value equivalency survey focus groups and pretests............................ 2-13

2.2 Outline of Green Bay total value equivalency survey.................................................... 2-15

2.3 Format of the natural resource topic sections ................................................................ 2-16

2.4 Green Bay equivalency value survey — attribute levels................................................ 2-21

2.5 Correlation between choice set attribute levels.............................................................. 2-25

3.1 Green Bay total value equivalency survey sample plan................................................... 3-2

3.2 Households with listed telephone numbers...................................................................... 3-3

3.3 Mail survey response rates............................................................................................... 3-5

3.4 Comparison of importance ratings from phone and mail surveys ................................... 3-8

3.5 Ownership of residence.................................................................................................... 3-9

3.6 Gender of respondents ................................................................................................... 3-10

3.7 Household and family size............................................................................................. 3-11

3.8 Racial or ethnic background .......................................................................................... 3-11

3.9 Highest level of schooling attained................................................................................ 3-11

3.10 Employment status......................................................................................................... 3-12

3.11 Household income ......................................................................................................... 3-13

4.1 Awareness of natural resource topics before receiving the survey .................................. 4-2

4.2 Correlations between topic awareness and other variables.............................................. 4-3

4.3 Average participation level in outdoor activities on the waters and shorelines

of the Bay of Green Bay by distance of residence to Green Bay ..................................... 4-4

4.4 Participation level by awareness of issue......................................................................... 4-5

4.5 Importance of all natural resource action benefits........................................................... 4-7

4.6 Mean importance of all natural resource action benefits by awareness of issues............ 4-8

4.7 Preferred level of action for natural resource programs................................................... 4-9

4.8 Importance of program attributes in making choices between alternatives................... 4-10

4.9 Confidence in choices between alternatives .................................................................. 4-11

4.10 Extent to which public officials should consider your responses

to choice questions......................................................................................................... 4-12

4.11 General comments made at end of survey, coded into categories ................................. 4-13

4.12 Pairs with PCB removal versus other single resource programs ................................... 4-14

4.13 Simple comparison of choice pairs: Resource comparisons.......................................... 4-16

4.14 Simple comparison of choice pairs: Referendum comparisons..................................... 4-18
Stratus Consulting (Final, 10/25/00)

Page x

5.1 Model variables................................................................................................................ 5-6

5.2 Parameter estimates ......................................................................................................... 5-9

6.1 Illustration of restoration scaling ..................................................................................... 6-4

6.2 Mean population-weighted household willingness to pay for resource programs........... 6-6

6.3 Household WTP estimates by respondent type................................................................ 6-9

6.4 Present value of total WTP for ongoing PCB-caused losses: Residents

of 10 Wisconsin counties............................................................................................... 6-10

6.5 Comparison of total future damages in the recreational fishing and total

value equivalency assessments ...................................................................................... 6-12

6.6 Omissions, biases, and uncertainties resulting in conservative estimates...................... 6-14
1. Introduction

1.1 Purpose of the Study

This study was prepared as part of the Lower Fox River/Green Bay natural resource damage

assessment (NRDA) by the U.S. Fish and Wildlife Service (the Service), the National Oceanic

and Atmospheric Administration, the Oneida Tribe of Indians of Wisconsin, the Menominee

Tribe of Indians of Wisconsin, the Michigan Attorney-General, and the Little Traverse Bay

Board of Odawa Indians (collectively referred to as the Co-trustees) in accordance with the

regulations at 43 CFR §§ 11.81-11.84, the Assessment Plan: Lower Fox River/Green Bay NRDA

at 61 FR 43,558 (August 2, 1996), and the Lower Fox River/Green Bay NRDA: Initial

Restoration and Compensation Determination Plan (iRCDP) at 63 FR 50,254 (September 21,

1998).

Releases of polychlorinated biphenyls (PCBs) into the Lower Fox River and Green Bay have

resulted in, and continue to result in, injuries to natural resources and related ecologic and human

use service flow losses at these sites. The objective of this total value equivalency (TVE) study is

to support the restoration planning portion of the Co-trustees’ damage determination by

(1) obtaining public preferences for the types and mix of restoration alternatives, and (2)

providing value-based methods to scale resource restoration projects to provide services of

equivalent societal value to the total value of all PCB-caused service flow losses from 2000 until

service flows are returned to baseline (PCB-caused service flow losses are also referred to as

PCB-caused losses, or as losses).

This study considers PCB-caused losses based on remedial scenarios proposed in the draft

remedial investigation/feasibility study (ThermoRetec Consulting, 2000a,b). The results herein

may be revised and the revisions incorporated into the Co-trustees restoration determination after

the U.S. Environmental Protection Agency (EPA) issues a Record of Decision.

The remainder of this introduction provides background on the case, explains how this study

supports the Co-trustees damage determination, and provides a summary of key results. This

study uses a survey to obtain preferences and to scale restoration. Chapters 2 and 3 provide a

summary of the survey instrument design and implementation. Chapter 4 provides a summary of

survey results, focusing on the public’s preferences across different types of restoration

alternatives. Chapter 5 provides the economic model used, and Chapter 6 reports the results for

the scaling of alternative restoration actions to provide services equivalent in value to the

ongoing PCB-caused losses. Chapter 6 also addresses the comparability and overlap between this

study and the Co-trustees’ recreational fishing damage determination (Breffle et al., 1999), and

provides additional study conclusions. The appendices provide copies of survey materials,
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-2

supporting economic model details, and a summary of related literature concerning area

residents’ preferences and values regarding natural resource injuries and restoration programs.

While not the focus of this study, the study survey design also provides information that can be

used to compute willingness-to-pay (WTP) monetary measures for interim losses from 2000 until

a return to baseline, which can be used as a measure of compensable values. The methods to

compute these values are presented in Chapter 5 and the results are presented in Chapter 6.

1.2 Background

PCBs are hazardous substances that were released into the Lower Fox River of Wisconsin,

primarily by paper company facilities as part of the manufacturing, deinking, and repulping of

carbonless copy paper that contained PCBs (Sullivan et al., 1983; WDNR, 1998; Stratus

Consulting, 1999c), primarily between the late 1950s and mid-1970s.1

 Through time, PCBs have

been and continue to be redistributed into the sediments and natural resources of the Lower Fox

River and Green Bay (Stratus Consulting, 1999c).

Fish and wildlife throughout the Lower Fox River and the waters of Green Bay are exposed to

PCBs, primarily through the food chain process (Stratus Consulting, 1999c). As a result of

elevated PCB concentrations in fish, in 1976 the Wisconsin Department of Health and Human

Services issued fish consumption advisories (FCAs) for sport-caught fish in the Wisconsin

waters of Green Bay (including the Lower Fox River), and in 1977 Michigan issued FCAs for

the Michigan waters of Green Bay (Stratus Consulting, 1999b). These FCAs continue today and

are expected to continue for decades into the future, depending on the level of remediation and

restoration at the site (Thermoretec Consulting, 2000a,b). Past and future recreational fishing

active use losses from PCB-caused FCAs in these waters were addressed by the Co-trustees in

Breffle et al. (1999). Similar to FCAs, waterfowl consumption advisories have been issued since

1987 in the Lower Fox River area because of elevated concentrations of PCBs (WDNR, 1987).

PCBs have caused injuries to fish and wildlife in the area, causing ecologic and human use

service flow losses. Walleye have higher rates of tumors and pre-tumors than do walleye from

comparable reference areas, and the difference has been attributed to PCBs (Stratus Consulting,

1999b; Barron et al., 2000). PCB injuries to bald eagles, double-crested cormorants, and

common and forster’s terns (both identified as endangered species by the State of Wisconsin) in

the area include decreased egg hatching success. Forster’s terns are also injured as a result of

 

1. PCBs are a hazardous substance under 40 CFR § 301.4 pursuant to Section 102(a) of the Comprehensive

Environmental Response, Compensation, and Liability Act (CERCLA) and Section 311 of the Federal Water

Pollution Control Act.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-3

increased deformity rates (Stratus Consulting, 1999a). In addition, PCB concentrations pose risks

of adverse effects on piscivorous mammals in the area, such as mink (ThermoRetec Consulting,

2000c).

The assessment area includes the waters of Green Bay2 and the surrounding land and wildlife

resources directly or indirectly impacted by the PCB contamination in the waters of Green Bay,

plus a part of northeast Lake Michigan (Figure 1.1).

1.3 Objectives

The purpose of the Co-trustee’s damage determination is to “establish the amount of money to be

sought in compensation for injuries to natural resources resulting from a release of a hazardous

substance” [43 CFR §11.80(b)]. The measure of damages is defined as restoration costs plus, at

the discretion of the Co-trustees, compensable values for interim losses [43 CFR §11.80(b)]. In

addition, damages include the Co-trustees’ reasonable assessment costs [42 USC §

9607(a)(4)(C)]. The term interim losses refers to losses from the time of release to when

resources and services are returned to baseline and encompasses past losses up to the present,

and ongoing losses during and after remediation and restoration actions until services flows are

returned to baseline [43 CFR §11.80(b)]. The primary focus of this study is to support restoration

planning.

Restoration refers to actions undertaken to return an injured resource to its baseline condition as

measured by the services provided by that resource [43 CFR § 11.14(ll)]. Baseline refers to the

conditions that would have existed in the assessment area had the release of hazardous

substances not occurred [43 CFR § 11.14(e)] and services are defined as the “physical and

biological functions performed by the resource, including the human use of those functions”

[43 CFR § 11.14 (nn)]. Restoration can be accomplished by restoring or rehabilitating resources

or by replacing or acquiring the equivalent of the injured natural resources, as measured by the

services those resources provide [43 CFR § 11.82(a)]. In restoration planning, Trustees evaluate

restoration alternatives and select and determine the scale of the preferred alternative based on

the magnitude of service flow losses the releases cause over time.3

 The costs to perform the

preferred alternative become the restoration cost component of the damage determination.

 

2. The waters of Green Bay are defined to include the Bay of Green Bay, all bays within Green Bay

(e.g., Little and Big Bay de Noc, Sturgeon Bay), and all rivers feeding into Green Bay up to the first dam or

obstruction, including the Lower Fox River starting at Little Lake Buttes des Morts to the Bay of Green Bay.

3. An alternative can consist of single actions or combinations of actions [43 CFR § 11.82(b)(1)].
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-4

#S

#S

ú

ú

ú

M i c h i g a n

L a k e

#

Green Bay

Marinette

Sturgeon

Bay

G r e e n

B a y

Lake 

Winnebago

Duck Cr.

Low er Fox R.

Walton R .

Cedar R

Oconto R.

Pensaukee R.

Little Suamico R.

Big Suamico R.

Peshtigo R

Wisconsin Big Bay

# de Noc

Little Bay

de Noc

Michigan Menominee R.

5 0 5 10 15 20 Miles

N Waters of Green Bay Michigan waters

Wisconsin waters

ú First dam

Figure 1.1. Wisconsin and Michigan waters of Green Bay.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-5

This TVE study supports restoration planning in two ways. First, the study explicitly obtains

public input regarding the preferences and values for alternative types of restoration projects,

which aids the Co-trustees in evaluating the benefits of alternatives [43 CFR § 11.82(d)(2)], and

ensures that the public has input on the selection of alternatives [43 CFR § 11.90].

Second, the study provides value-based methods to determine the appropriate scale of potential

restoration actions. In some cases, restoration can be obtained by actions that restore,

rehabilitate, or acquire the same amount of the same services at the same or very similar

locations as those that were lost. For example, if an oil spill causes a boat launch to be closed,

opening access to a comparable new boat launch nearby may provide the same services of the

same scale as the losses, and thus the replacement services are equivalent (in type, level, and

value) to the service flow losses. The amounts of services to be restored depend on the injuries

through time, which may vary with the contamination and with the remediation efforts through

time. For example, if contamination reduces mink populations, restoration might include habitat

enhancements to support the population, combined with periodic mink stocking at varying levels

to return the stocks to baseline levels through time. Scaling restoration programs that provide the

same or very similar services is sometimes referred to as service-to-service scaling, where the

amount of restored services are scaled to be equal to the amount of lost services now and through

time.

For a large share of the PCB-caused service flow losses in the assessment area, particularly

within Green Bay, where most of the PCBs have come to be located, providing restoration with

the same or very similar services may not be technically feasible (i.e., the Co-trustees may be

unable to find or develop resources that are sufficiently extensive to be developed in sufficient

quantities), may be undesirable (e.g., increasing the population of fish or birds that may continue

to experience injuries from PCB exposure), or may be too expensive. For this and other reasons,

it may be preferable to select restoration actions that provide resources and services of a similar

but different type or quality than those injured. Because such restoration may not provide the

same services, it may not be possible to apply service-to-service scaling. In these cases, valuebased scaling methods provide a basis for selecting and scaling restoration activities.

Value-to-value scaling is used in this study to scale restoration projects that provide services

similar to, but not the same as, those lost.4

 Scaling is computed such that the societal value of the

services gained through restoration equals the societal value of PCB-caused losses. Value is

measured by the utility (benefits or satisfaction) that people derive from all active and passive

uses of the resources. Dollar measures of value are not required for value-to-value scaling.

 

4. See also 15 CFR § 990.53(d) for additional discussion of value-based scaling concepts and methods.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-6

In this study we focus on restoring all human use losses, including active use losses related to

well-identified active, and often on-site, resource uses such as recreational fishing, and passive

use losses arising from services individuals receive from resources apart from their own readily

identified and measured active uses. 5

Certain active use losses may be cost-effectively and readily individually measured and valued,

as the Co-trustees have done for recreational fishing active use losses (see Breffle et al., 1999).

However, focusing solely on these losses omits consideration of other potentially significant

losses, thus understating the services to be restored. This TVE study is a total value assessment

because it addresses most or all PCB-caused service flow losses, including but not limited to

recreational fishing and other recreational losses such as waterfowl hunting and wildlife viewing;

casual or indirect losses such as reduced enjoyment while driving or walking by or working near

a site, and when hearing about, reading about, or seeing photographs of a site; and option and

bequest losses tied to preserving resource services for future use for oneself or for others.

Value-to-cost scaling can be used to select the type and scale of restoration projects such that

their cost equals the value of the lost services. This is the same as computing compensable values

[CFR 43 § 11.83-11.84] and applying the recovered damages to selected restoration projects

[43 CFR § 11.93 (b)]. This study supports the selection of the mix and scale of restoration

projects once damages are recovered by identifying project preferences and the relative value of

alternative mixes of projects. While not the primary focus of this study, the study can provide a

measures of compensable values for interim losses from 2000 until services are returned to

baseline using a WTP measure [43 CFR §11.83(c)(2)].6,7

 

5. Some authors use different terms to refer to these concepts, or define the terms slightly differently. These

differences generally have little substantive impact when the focus is on restoring all human use losses. These

terms are consistent with the DOI regulations, where passive use losses include nonuse losses such as bequest

and existence losses.

6. Compensable values include “the value of lost public use of the services provided by the injured resources,

plus lost nonuse values such as existence and bequest values” [43 CFR § 11.83(c)(1)].

7. The values provided in this study could also be used to support value-to-value scaling of the compensable

values for the total interim recreational fishing losses (Breffle et al., 1999) to the value of the restoration

programs addressed here.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-7

1.4 Approach

Survey of preferences and values

To obtain public preferences and values, a survey was conducted with residents of 10 Wisconsin

counties surrounding the Wisconsin waters of Green Bay. The survey focuses on four groups of

natural resource restoration programs for the Green Bay area. Over 600 restoration projects for

the assessment area were compiled and analyzed, with a large majority of the proposed projects

falling into one of these groups (see Chapter 2). The levels of restoration considered for each of

the four program groups were selected reflecting relevant technical options and responses from

respondents in survey focus groups and pretests.

1. Restore wetlands near the waters of Green Bay. Wetlands restoration will provide

increased spawning and nursery habitat and increased food for a wide variety of fish,

birds, and other wildlife. This provides wildlife services similar to, but not the same as,

those injured by PCBs. Preferences and values for restoration of wetlands can also be

applied as an indicator of the preferences and values for preventing further wetland loss

and for other habitat enhancement projects. Restoration levels range from taking no

action up to a 20% increase in wetlands within five miles of Green Bay within Wisconsin

(although selected wetlands for restoration could also be located in Michigan).

2. Remove PCBs in the sediments of the assessment area. Removal of PCBs will reduce the

number of years until FCAs and the injuries to wildlife are eliminated. The levels of

removal considered result in the number of years until PCBs are at safe levels (i.e., a

return to baseline conditions) ranging from 100 years (no additional removal) to 20 years

with intensive remediation.

3. Enhance outdoor recreation in 10 counties surrounding Green Bay. Enhanced recreation

includes increasing facilities at existing parks such as adding picnic grounds, boat ramps,

and biking and hiking trails, and developing new parks. These facilities provide

recreation services, although not the same services as those affected by the PCB-caused

losses. The levels of recreation enhancements considered range from no improvements up

to a 10% increase in facilities at existing parks and a 10% increase in new park acreage.

4. Reduce runoff that contributes to pollution of the waters of Green Bay. Controlling runoff

improves water quality by lessening algae growth and improving water clarity, especially

in the lower bay. This improves aquatic vegetation and habitat for fish and some birds

and improves recreation. Runoff control in this case provides similar, but not the same,

services as those injured by PCBs. The runoff control levels considered range from no

change in the amount of runoff up to a 50% reduction, reflected by changes in water

quality measures.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-8

This TVE study is designed to support restoration planning by providing a large-scale

perspective of public preferences across alternative types of restoration programs, and providing

a method to scale programs that provide equivalent value to the service flow losses. The study is

not intended to provide a selection of individual projects such as specific wetland acres or

specific recreational facilities. That task is left to Co-trustees and regional planners who have a

detailed knowledge of needs, technical effectiveness, and cost-effectiveness.

The survey describes each of the four natural resource restoration programs and asks a variety of

questions to elicit preferences about the programs and the program levels. Next, the survey

includes six stated preference choice questions, where respondents state their preferences by

choosing which of two alternatives (A or B) they prefer, where each alternative has a specified

level for each of the four restoration programs.

Figure 1.2 provides an illustration of the choice questions presented to respondents. In this

question respondents are making a choice between enhanced outdoor recreational facilities at

existing parks and increased levels of runoff control. By varying the program mixes and levels

across questions and examining the choices made, mathematical methods (knows as random

utility models) are used to determine how much of one kind of restoration has equivalent value to

different amounts of other kinds of restoration.

The alternatives, and the choice between alternatives, are designed to reflect realistic and

meaningful options for natural resource management in the study area. To present realistic

choices, each of the alternatives includes a dollar cost to the household associated with the

alternative. The dollar values presented differ across choice pair, and across survey versions,

which allows for calculation of the public’s WTP for the value of PCB-caused losses, or

compensable values (see Chapter 5), and for the natural resource enhancements considered.

The TVE survey was implemented through a mail survey of a stratified random sample of

households in 10 counties near Green Bay. Of the 650 eligible respondent households,

470 responded, resulting in a 72% response rate. An evaluation of the sampling plan and

responses indicates that any potential sampling and response biases are likely to be small and

thus have a minimal impact on the results (see Chapter 3 for further discussion of potential

sampling and response biases).
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-9

Figure 1.2. Sample choice question.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-10

Remediation scenarios

This TVE study determines what level of enhancements in the selected natural resource

programs has a value that is equivalent to the value of PCB-caused losses over various time

periods for alternative remediation scenarios. Figure 1.3 illustrates how ongoing PCB-caused

losses depend on the rate of remediation f services. In the figure, Area A represents past losses

experienced before remediation begins at the site (assumed to be 2000); these losses are not

addressed in this TVE study. Area B reflects an assumption of a 10 year period (2000-2009) for

remediation actions during which time limited, if any, recovery may occur. Areas C-F are

ongoing losses after remediation (if any), depending on the level of remediation. We consider

several scenarios:

1. Intensive remediation. This scenario assumes that losses continue largely unabated during

the remediation period (Area B), then linearly decline to baseline over another 10 years

(Area C) for a total of 20 years of ongoing losses. This scenario reflects the Fox River

Global Meeting Goal Statement (FRGS-97) by the Fox River Global Meeting

Participants (1997), and is similar to the more intensive remedial actions being

considered in the Remediation Investigation and Feasibility Study (RI/FS, ThermoRetec

Consulting, 2000a,b).

2. Intermediate remediation. This scenario assumes that losses continue largely unabated

during a 10 year remediation period (Area B), then linearly decline to baseline over

another 30 years (Areas C + D) for a total of 40 years on ongoing losses (10 + 30). This

scenario is similar to the intermediate remediation scenarios in the RI/FS.

3. Little or no additional remediation. These scenarios consider limited remediation over

10 years (Area B), resulting in declining losses over either (a) an additional 60 years

(Areas C + D + E) for a 70 year total (10 + 60), or (b) an additional 90 years

(Areas C + D + E + F) for a 100 year total (10 + 90).

The TVE study design allows the calculation of the scale of restoration to provide services of

equal value to the value of PCB-caused losses through time, or to a portion of the losses through

time, such as between a 20 year intensive remediation and a 40 year intermediate remediation

(Area D in Figure 1.3).
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-11

1.5 Summary of Results

Awareness and preferences

Respondents were asked how aware they were of each of the four natural resource topics

presented (wetlands, PCBs, outdoor recreation, and runoff control) before receiving the survey.

Respondents reported being moderately to highly aware of the topics, with over 80% reporting

they were somewhat to very aware of each topic. The literature identifies that higher awareness

can be expected to enhance the reliability of responses and to reduce the burden of

communication in survey design. High levels of awareness of a topic most likely reflect personal

interest in the topics and increased preference for, and values for, natural resource restoration.

Various questions address respondent concerns and preferences for the four programs and the

service flow benefits they provide. There is a strong and statistically significant preference for

PCB removal over other natural resource enhancement programs, even though efforts were taken

to ensure that PCB removal was treated in the survey on an equal basis with the other natural

resource restoration programs (see Chapter 2). Relative to PCB removal, runoff control and

wetland enhancements have modest interest and values. Limited interest is expressed in

enhancing 120 regional parks, and almost no interest is expressed in adding new regional parks.

Table 1.1 summarizes the importance ratings for the benefits from each program. Table 1.2

summarizes preferences in terms of doing and spending less, the same, or more, compared to

current levels, for each program in the future.

Baseline Services

level of

services

Reduced

levels of

services =

losses

Time

1980 2000 2010 2020 2040 2070 2100

A BC D E F

Figure 1.3. PCB-caused service flow losses under alternative time paths for a return

to baseline.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-12

Table 1.1. Importance of natural resource action benefits

(1 = not at all important to 5 = very important).

Benefitsa

Mean importance ranking

(SE of mean)

Remove PCBs to reduce risks to birds, fish, and other wildlife 4.3

(0.05)

Remove PCBs so that it is safe to eat fish, and waterfowl 4.3

(0.05)

Reduce runoff to improve water clarity 4.0

(0.05)

Increase wetland acreage to support birds, fish, and other wildlife 3.9

(0.05)

Reduce runoff to reduce algae blooms 3.8

(0.05)

Add facilities at existing parks 3.6

(0.05)

Add new parks 3.3

(0.06)

a. Listed in order of mean importance score, not in the order they appear in the survey.

Table 1.2. Preferred actions for natural resource programs.

Natural resource

programsa Do less and spend lessb Do and spend the same

Do more and spend

more

PCB investigations and

removal NAc 17% 83%

Runoff reduction 2% 34% 65%

Wetlands maintenance

and/or restoration 3% 42% 56%

New facilities at existing

parks and/or opening new

parks 2% 51% 47%

a. Listed in order of mean importance score, not in the order they appear in the survey.

b. Percentages are adjusted to remove missing responses, which amount to less than 2.4% for all questions

and may not sum to 100% due to rounding.

c. Not applicable: “Do less and spend less” was not offered as an option for PCBs.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-13

The reported preferences vary by household characteristics. For example, households report

higher importance for the benefits of a program, and interest in doing more and spending more, if

they have anglers active in fishing the waters of Green Bay, if they live very near Green Bay, and

if they were previously very aware of the natural resource topic.

Scaling restoration

The results of the choice questions, which trade off enhancements in natural resource programs,

demonstrate that respondents predominately answer in a manner consistent with our

expectations: more enhancements are preferred to fewer enhancements, and lower costs are

preferred to higher costs. These results support the reliability of the results.

The resource trade-off questions are used to scale combinations of resource restoration programs

that would provide services that the public considers to be equivalent in value (measured in

utility) to eliminating the continuing PCB-caused losses. While the final mix and scale of

restoration programs will be determined later, the model presented here provides a basis upon

which to scale alternative restoration programs. The costs for the selected restoration programs

are addressed in the Co-trustees’ Restoration Compensation Determination Plan (RCDP).

Table 1.3 provides examples of the scale of sample mixes of restoration projects that provide

services with value equal to the ongoing PCB-caused losses for selected scenarios. Each line

represents one possible mix of restoration projects. The listed examples are but a few of the

infinite number of possible combinations that the Co-trustee Council and potentially responsible

parties could develop to provide services of equal value to the PCB-caused losses. The first three

lines provide example combinations for the scale of restoration providing services of value equal

to the PCB-caused losses from 2000 until a return to baseline if an intensive level of remediation

returns services to baseline by 2020:

} A combination of 3,100 acres of wetlands restoration, plus a 10% enhancement in

existing park facilities, plus a 50% runoff control program

} A combination of 5,500 acres of wetlands restoration, plus an 8% increase in existing

park facilities, plus a 45% runoff control program

} 11,000 acres of wetlands restoration, plus a 45% runoff control program.

The second block provides examples for the 40 year intermediate level of remediation. The third

and fourth blocks provide examples of the scale of restoration that provides services of value

equal to a portion of the PCB-caused losses corresponding to the differences between a 20 and

40 year remediation and between a 20 and 70 year remediation.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-14

Table 1.3. Illustration of restoration scaling.

Example mixes of restoration programs

Scenario Wetland restoration acresa Existing park enhancement Runoff controlb

PCB remediation scenariosc

Intensive: (0 to 20 years)

Intermediate: (0 to 40 years)d

Partial restoration

Intensive vs. 40 year

Intermediate (20 to 40 years)

Intensive vs. 70 year

Intermediate (20 to 70 years)

3,100

5,500

11,000

24,100

16,000

2,900

5,000

2,400

5,700

13,000

10%

8%

0%

10%

20%

2%

3%

0%

0%

10%

14”/50%

12”/45%

12”/45%

16”/55%

16”/55%

4”/25%

2”/13%

7”/33%

14”/50%

10”/40%

a. Rounded to nearest 100 acres.

b. Additional inches of water clarity/percentage decrease in number of excess algae days.

c. Restoration is for PCB-caused losses during the period indicated.

d. Requires extrapolating beyond the range of actions considered for some or all programs.

These illustrations do not include additional acres of new parks as a restoration approach because

acres of new parks in the 10 county area was found to have a near-zero value. A few key findings

emerge as applicable to the ultimate selection and scaling of restoration alternatives within the

identified three project types (wetlands, outdoor recreational facilities, and runoff control):

} Wetland (and likely other wildlife habitat) restoration programs and runoff control

programs are preferred to, and more highly valued than, programs to enhance outdoor

recreation in the assessment area. While specific outdoor recreation enhancements would

benefit some residents, the majority of residents indicated limited interest in additional

facilities and parks.

} Continued increases in the levels of wetland restoration programs increase benefits, but at

a declining rate. That is to say, there are diminishing marginal utility gains as more

wetlands are restored. As a result, increased restoration well beyond the levels addressed

in the study will most likely result in limited additional benefits to the public.
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-15

} The value of PCB-caused losses is so substantially larger than the value of service flow

benefits from the restoration programs that it is difficult to generate benefits equivalent in

value to the PCB-caused losses with just improvements in one program. For instance, a

widespread improvement in regional parks provides services that are equal in value to

value of the first few years of PCB-caused losses, a 20% increase in wetland acres

provides services with value equal to about the first seven years of PCB-caused losses,

and a 50% additional runoff control provides services with value equal to about the first

15 years of PCB-caused losses. Therefore, to provide sufficient restoration with value

equal to the value of ongoing PCB-caused losses until a return to baseline will likely

require a combination of several programs.

} The restoration combinations presented in Table 1.3 consider up to a 40 year time

horizon for eliminating PCB injuries because even the maximum combination of the

wetlands, outdoor recreation, and runoff control programs considered do not provide

enough service flow benefits to be equivalent to eliminating PCB losses more than

40 years more quickly. To provide services flow benefits for PCB-caused losses beyond

40 years would required additional natural resource programs, or variations on the

programs addressed herein.

Double counting and comparison to other studies

The WTP value measures for interim losses estimated in this TVE study can be used to eliminate

double counting in the final damage determination and to compare the results here with other

existing literature.

This TVE study differs from, but necessarily partially overlaps, the Co-trustees’ recreational

damage determination (Breffle et al., 1999) because both include a portion of the recreational

fishing losses due to PCB-caused fish consumption advisories. The WTP results of the TVE and

recreational fishing studies can be compared for those households with Green Bay anglers in the

10 nearby Wisconsin counties. For this comparison population, the WTP values in this TVE

study are comparable to or slightly larger than the WTP values in the recreational fishing study.

This is as expected because this study values a larger set of losses than does the recreational

fishing study, although for households with Green Bay anglers, fishing losses may well be the

dominant component of PCB-caused losses. The comparability of the results supports the

estimated magnitude of damages in each study, and allows double counting between the studies

to be readily addressed (see Section 6.3.3).

The results of this study are also consistent with other existing literature specifically addressing

social preferences and values for PCBs and other natural resource management programs in

northeastern Wisconsin (see Appendix D). Existing literature consistently identifies that regional

residents are aware of and concerned about water pollution issues, and place a high priority and
Stratus Consulting Introduction (Final, 10/25/00)

Page 1-16

value on cleaning up contaminated water resources. While the existing literature does not address

the same scenarios as in this TVE study, allowing for differences in the scenarios, the

preferences and WTP values calculated in this TVE study are of a consistent magnitude with

those found in the literature.
2. Survey Design

Section 2.1 provides an overview of the survey instrument, key survey design considerations

influencing why we selected the stated preference choice-question approach, and how we

designed the survey. Section 2.2 provided a detailed discussion of the individual elements of the

survey.

2.1 Survey Design Overview

2.1.1 Background

To support the restoration planning objectives of this study, the survey needed to address the

range of the most relevant restoration alternatives. Therefore, we first developed a database of

potential restoration projects, drawing on work completed by many groups in the Green Bay area

(Hagler Bailly Services, 1998). The database merged the specific project recommendations made

in the 1988 Lower Green Bay Remedial Action Plan for the Lower Fox River and Lower Green

Bay Area of Concern (WDNR, 1988), projects from the 1994 Green Bay Habitat Restoration

Workshop Summary (WDNR, 1994), and projects that in various documents were developed,

gathered by, and presented to the WDNR Habitat Restoration Workgroup (the Boronow Group),

which worked during 1997 and 1998. The Potential Restoration Projects Database contains over

600 individual projects or ideas.

Most of the identified restoration projects could be placed into one of four broad natural resource

topic areas. Working with scientists, for each topic area we next developed technical information

about current conditions, and about the types of benefits that could be obtained from restoration

projects. The levels of restoration to be considered in the survey for each topic area were selected

reflecting technical options and responses from respondents in survey focus groups and pretests

(see Section 2.2.2). The four natural resource restoration topics, along with their related service

flows and range of restoration levels are as follows:

1. Restoration of wetlands near the waters of Green Bay. Wetlands restoration will provide

increased spawning and nursery habitat and increased food for a wide variety of fish,

birds, and other wildlife. This provides wildlife services similar to, but not the same as,

those injured by PCBs. Preferences and values for restoration of wetlands can also be

applied as an indicator of the preferences and values for preventing further wetland loss

and for other nonwetland habitat enhancement projects. Restoration levels range from

taking no action up to a 20% increase in wetlands within five miles of Green Bay in

Wisconsin (although selected wetlands could also be located in Michigan).
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-2

2. Removal of PCBs in the sediments of the assessment area. Removal of PCBs will reduce

the number of years until FCAs and the injuries to wildlife are eliminated. The levels of

removal considered result in the number of years until PCBs are at safe levels (i.e., a

return to baseline conditions), ranging from 100 years (no additional removal) to

20 years.

3. Enhance outdoor recreation in 10 counties surrounding Green Bay. Enhanced recreation

includes increasing facilities at existing parks such as adding picnic grounds, boat ramps,

and biking and hiking trails, and developing new parks. These facilities provide

recreation services, although not the same services as those affected by the PCB-caused

losses. The levels of recreation enhancements considered range from no improvements up

to a 10% increase in facilities at existing parks and a 10% increase in new park acreage.

4. Reduce runoff that contributes to pollution of the waters of Green Bay. Controlling runoff

improves water quality by lessening algae growth and improving water clarity, especially

in the lower bay. This improves aquatic vegetation and habitat for fish and some birds

and improves recreation. Runoff control in this case provides similar, but not the same,

services as those injured by PCBs. The runoff control levels considered range from no

change in runoff up to a 50% reduction, reflected by changes in water quality measures.

After describing the topics and restoration program levels, the survey included six stated

preference choice questions, where respondents stated their preferences across restoration types

and levels. Figures 1.2 and 2.1 provide illustrations of two examples of choice questions.

} In Figure 1.2, respondents were asked to make a choice between two restoration

alternatives: enhanced outdoor recreational facilities at existing parks in Alternative A or

increased levels of runoff control in Alternative B. In both alternatives, household costs

increase by $25 per year for 10 years.

} In Figure 2.1, respondents were asked to make a choice between a restoration alternative

or remaining with the status quo: PCB removal resulting in a reduction to 40 years until

PCBs are safe, at a per household cost increase of $200, in Alternative A, or no additional

resource enhancements and no additional household costs in Alternative B.

The restoration levels for the four programs and the associated household costs are varied across

the alternatives in each question and across the questions. By examining the choices made,

mathematical methods (knows as random utility models) are used to determine how much of one

kind of restoration has equivalent value to different amounts of other kinds of restoration, and to

compute the WTP value of ongoing PCB-caused losses and of the restoration alternatives.
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-3

Figure 2.1. Typical choice question.

 14 If you had to choose, would you prefer Alternative A or Alternative B? Check one

box at the bottom.

Alternative A 

ï

Alternative B

ï

Wetlands

 Acres . . . . . . . . . . . . . . . . . . . . . . 

 

58,000 acres 

(current)

58,000 acres

(current)

PCBs

 Years until safe for nearly all fish

 and wildlife . . . . . . . . . . . . . . . . .

40 years until safe

(60% faster)

100+ years until safe

(current)

Outdoor Recreation 

 Facilities at existing parks. . . . . . 

 Acres in new parks . . . . . . . . . . . . 

0% more

0 acres 

(current)

0% more

0 acres

(current)

Runoff

 Average water clarity in the 

 southern Bay . . . . . . . . . . . . . . . .

 Excess algae days in lower Bay . .

20 inches

(current)

80 days or less

(current)

20 inches

(current)

80 days or less

(current)

Added cost to your household 

 Each year for 10 years . . . . . . . . . $200 more $0 more

Check (U) the box for the

alternative you prefer Û ñ ñ
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-4

2.1.2 Selection of the stated preference choice-question survey approach

Generally, two broad classes of approaches are often used to evaluate preferences and values for

natural resource changes: stated preference (SP) approaches and revealed preference (RP)

approaches.1

 SP approaches use survey questions to have respondents explicitly or implicitly

state their preferences and value. In a very simple SP approach, respondents could be asked,

“When fishing in this area do you prefer fishing for perch, or fishing for catfish?” or “Would you

pay $5 to launch your boat in these waters?” In contrast, an RP approach examines behavioral

choices that have been made, and which are observed in markets or reported by respondents in

surveys, to infer preferences and values. In our simple example, RP data might find that most

anglers in the area fish for perch and few fish for catfish, and thus we reveal that for the current

conditions there is a preference for perch fishing; and RP data might find that most boat anglers

will pay $5 to launch their boat at the site rather than fish elsewhere, or would fish elsewhere.

We selected the SP approach because it would cost-effectively provide the most comprehensive,

valid, and accurate information to support the restoration planning objectives of the study.2

 A

stated preference survey can be more comprehensive because it can measure preferences and

values (in utility or dollars) for more PCB-caused service flow losses, and for most or all of the

service flow gains from a restoration alternative. Another strength of the SP approach is that the

researcher can measure public preferences and values directly relevant to all levels of all four

restoration alternatives being considered for the site of interest, including restoration providing

service levels that do not currently exist, thus obtaining valid and accurate information

(Morikawa et al., 1990; Louviere, 1996).

We judged that using RP approaches would not sufficiently serve the study objectives. RP

approaches could be cost-effectively applied, or applied at all, for only a limited number of PCBcaused losses, such as for recreational fishing (such as in Chen and Cosslett, 1998; Herriges

et al., 1999; and Breffle and Morey, 2000), and for only a limited number of the service flow

benefits for a few of the restoration alternatives of interest (such as for selected recreational

activities). RP approaches would not be cost-effective for many types of active uses related to

enjoying a site and generally could not be used to reveal values for some service flows, including

passive uses and cultural uses.

 

1. See, for example, Kopp and Smith (1993), Freeman (1993), Adamowicz et al. (1994), Breffle et al. (1999),

and the U.S. DOI NRDA regulations at 43 CFR § 11.83(c). Some authors use different terms to refer to these

methods.

2. Comprehensive refers to covering all or a large set of the service flow losses and gains, for all or a large set

of the restoration options of interest. Valid refers to measuring the specific variable of interest, without bias,

rather than measuring a close but different variable or measuring the variable with bias. Accuracy refers to

measuring the variable with reasonable precision.
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-5

Even for the service flows that RP approaches could cost-effectively measure, RP approaches

would not be able to reliably and accurately measure values for many of the restoration

alternatives of interest because some alternatives enhance natural resources in ways that do not

currently exist in the assessment area. Therefore, relevant behavioral data for the assessment area

to measure preferences and values does not exist. In some cases, RP information can be used

from other comparable sites, or the same site in prior years, to learn about preferences and values

for some of the service flows of interest, but generally the ability to comprehensively, reliably,

and accurately measure current preferences and values relevant to the unique assessment area is

limited.

Using RP data as the primary approach would have the undesirable effect of understating PCBcaused losses and limiting the evaluation to the types and levels of restoration alternatives to

those that may not be of the most interest and value. Thus, for a comprehensive assessment,

SP studies would be required. Conducting additional RP studies, beyond the recreational fishing

damage determination and in addition to the required SP study, would not be cost-effective

because of the limited coverage of restoration alternatives and service flows that RP studies

could provide.

2.1.3 Choice-question method as an established method

We selected a choice-question method because the method is established in the literature, and

can be designed to cost-effectively and directly assess the study objectives for the specific types

and levels of PCB-caused losses and restoration alternatives of relevance.

Choice questions evolved from conjoint analysis, which has been extensively used in marketing

and transportation research.3

 Choice questions have come into widespread use in environmental

economics. For example, Magat et al. (1988) and Viscusi et al. (1991) applied SP data to

estimate the value of reducing health risks; Adamowicz et al. (1994, 1997) and Morey et al.

(1999a) applied it to estimate recreational site choice models for fishing, moose hunting, and

mountain biking, respectively; Breffle et al. (1999) used it to value changes in recreational

fishing; Adamowicz et al. (1998) used it to estimate the value of enhancing the population of a

threatened species; Layton and Brown (1998) used it to estimate the value of mitigating forest

loss resulting from global climate change; Morey et al. (1999b) applied SP data to estimate WTP

for monument preservation in Washington, DC; Swait et al. (1998) compared prevention versus

compensation programs for oil spills; and Mathews et al. (1997) and Ruby et al. (1998) asked

anglers to choose between two saltwater fishing sites as a function of their characteristics.

Breffle et al. and Mathews et al. were NRDA applications.

 

3. For survey articles and reviews related to use in marketing, see Louviere (1988, 1992, 1994), Green and

Srinivasan (1990) Batsell and Louviere (1991); and for use in transportation planning, see Hensher (1994).
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-6

A number of additional applications to environmental topics have used a rating variation of

choice questions, in which survey respondents rate the degree to which they prefer one

alternative over the other. For example, Opaluch et al. (1993) and Kline and Wichelns (1996)

develop a utility index of the characteristics associated with potential noxious facility sites and

farm land preservation. Johnson and Desvousges (1997) estimate preferences and WTP for

various electricity generation scenarios and related environmental and social impacts.4

We chose to use choice questions rather than the rating variation of choice questions and to limit

the choice to two alternatives. Choice questions mimic the real choices individuals continuously

make, whereas individuals rank and rate much less often.5

 And choice questions among two

options are easier, thus reducing the burden on our respondents while still providing information

sufficient for the study objectives.

The use of the choice-question method in this natural resource damage assessment is consistent

with U.S. DOI NRDA regulations [43 CFR § 11.83(c)(3)]. The choice-question methods used

here combine elements of random utility models used in recreation assessment and stated

preference methods, which are identified as acceptable methods in the U.S. DOI regulations

[43 CFR § 11.83(c)(3)]. Choice-question methods are explicitly identified (under the name

“conjoint methods”) in the NOAA NRDA regulations for use in value-to-value scaling of

restoration alternatives (15 CFR Part 990, preamble Appendix B, part G), which is supported in

Mathews et al. (1995, 1997).

2.1.4 Key design considerations

Once we had chosen a survey based choice-question approach, our attention turned to strategies

to design and implement a state-of-the-art application. To provide valid and accurate preferences

and values, our SP survey incorporates general survey design considerations as described in

several standard works, including Dillman (1978, 2000), Shuman and Presser (1996), and

Tourangeau et al. (2000). In addition, we addressed survey design considerations that are specific

to all SP surveys (Mitchell and Carson, 1989; Kopp et al., 1997) and to choice-question

application of SP surveys. In this section we discuss selected key survey design considerations.

 

4. Other examples include Rae (1983), Lareau and Rae (1998), Krupnick and Cropper (1992), Gan and Luzar

(1993), and Mackenzie (1993). Adamowicz et al. (1997) provide an overview of environmental valuation

choice and ranking studies up to 1996. Dozens of new environmental economic applications are now occurring

each year.

5. See, for example, Louviere and Woodward (1983), Louviere (1988), and Elrod et al. (1992).
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-7

Accurate, neutral, and accessible information

An important consideration to our design was to present accurate information in a neutral and

accessible manner. Throughout the survey design we consulted with scientists and public

officials to assure and document that all of the information presented in the survey provided

accurate and balanced perspectives of the natural resource topics of interest.

Beyond accuracy in the scientific information, several actions were taken to assure the survey

made a neutral presentation. These included not identifying the sponsor, but rather noting the

usefulness of the results to government, industry, and citizen groups; assuring there was a

consistent and equal presentation of each of the four natural resource topics addressed; and

repeatedly recognizing that respondents may not place importance on the identified resource

enhancements (e.g., “how important, if at all, . . .” and rather than assuming restoration would be

preferred, including options such as “do less and spend less” and “do and spend the same”).

In pretests, when respondents were asked for whom and why they thought the survey was being

conducted, the most frequent answer was they did not know, second was that it involved the

State of Wisconsin in its efforts to help evaluate what to do in the Green Bay area, and some

respondents indicated that they thought the paper companies were sponsoring the research.

While our focus was on restoration preferences and scaling for PCB-caused losses, focus group

and pretest respondents indicated they thought that the survey had to do with all four resource

topics and was not motivated by, or oriented to, consideration of PCBs or any of the other topics.

When asked if they felt that the survey contained any bias for or against any particular issue,

focus group and pretest respondents overwhelmingly indicated that they did not feel the survey

was biased.

An important design consideration is to present the required information in a manner that is

accessible to, and not a burden to, respondents; otherwise respondents may not complete any or

all of the survey, and may be confused by information and provide unreliable and/or inaccurate

information. In this survey, wherever possible, we present information at a basic level, and to

facilitate reading the survey we carefully structured the information in consistent formats for

each resource topic and in the choice questions. While considerable information is presented,

simple questions and maps, graphs, and tables are interspersed among the text to break up the

information, to be visually interesting, and to help the respondent think about the information as

he or she progresses through the survey. The simple questions also provide useful attitudinal and

demographic information. Again, focus groups and pretests were used to work on survey

language and respondent ability to understand the survey and provide valid and accurate

answers.
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-8

Context

A standard tenet of SP design is that if the SP context of the presentation and questions simulates

real choices, and if the responses could have a real impact on the respondents, there is incentive

for the respondents to provide answers that are a valid and accurate reflection of their

preferences. In this survey, we present a realistic context that government, industry, and citizen

group planners are examining options for natural resources in northeast Wisconsin. These issues

have long and frequently received a high level of attention in the news in the assessment area. In

fact, a large portion of respondents in the focus groups, pretests, and final instrument expressed

awareness of, and concern about, the various natural resource topics being addressed. A large

share of the residents in the area enjoy the natural resources of interest in one way or another,

and thus changes in the resources would affect them. Often there are public meetings on these

natural resource topics, and it is reasonable for citizens to accept that decision makers seek

public input through a survey of this type, and that results will influence the selection of the

types and levels of actions to be taken.

In most SP studies, the context of who will pay, and how, is a key design feature. While our

study focused on restoration priorities and scaling of restoration, which did not require that we

specify the costs, participants in focus groups quickly identified that consideration of who will

pay and how was important to set a realistic context for the choices they were presented with:

“Who is going to pay,” or “I know we will have to pay some for these natural resource

improvements, but industry, users, and farmers should pay their share” typify the types of

comments received. These types of concerns also identify that respondents took the survey

seriously.

Reflecting the concern about who pays and how, we included dollar costs to the household

associated with each alternative. Dollar costs would be paid through a combination of federal,

state, and local taxes, as most often occurs for these types of major natural resource programs.

Dollar costs would be paid over a 10 year period, matching the implementation period identified

for the projects. With these aspects added to the context, most respondents in focus groups and

the pretest identified the choice questions as reasonable and meaningful. While the inclusion of

dollar costs adds realism to the context of the presentation, by varying the costs across choice

pairs and across survey versions, it also allows for calculation of the public’s WTP for the value

of PCB-caused losses (see Chapter 5), and for the natural resource enhancements considered.

Information presentation

Another consideration in any SP survey is that respondents have the information necessary for

them to make informed choices (Fischoff and Furby, 1988). Choices that are poorly informed

may result in inaccurate and potentially biased reflections of preferences. We addressed this

consideration in two ways: by carefully selecting the information to be presented (and making
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-9

sure it is accurate), and by limiting the population surveyed to those households near the site (see

the section below on the choice of population to be surveyed).

One of the most important peculiarities of SP surveys, compared to surveys used for other

purposes, is the amount of information that must be conveyed to, and understood by,

respondents. Ideally, to make the best choices, people should be fully informed, but a goal of full

information is impractical, would create an unnecessary respondent burden, and may even

worsen the response rates and the quality of response. As identified by Fischoff and Furby

(1988):

Simply telling people everything provides no guarantee that they have understood

everything. Such a strategy might even impede understanding if attention to

critical features of the contingent market is diverted by a deluge of details about

features that could have gone without saying because they have little practical

effect on decisions.

What we strive for in designing SP surveys (and often in life) is information that is fundamental

to the choice process; that is accurate, neutral, and realistic; and that is simple and

straightforward to understand. In this specific SP instrument, we specifically identify the natural

resource topics of interest and identify characteristics of current conditions, and changes in

current conditions if natural resource programs are undertaken. Thus, we have specified the

goods to be compared in the choice questions and, as discussed above, the context under which

changes would occur.

A related informational consideration is the number of restoration alternatives, and their

characteristics, to present. Clearly, as the number of details about restoration alternatives

increase, it becomes more challenging for the respondent to understand, track, and trade off

many characteristics, which increases the chance of confusion or focusing on only one or a few

of the attributes (reducing accuracy), or dropping out (resulting in low response rates).

We chose to present four types of restoration program characteristics by seven index variables,

as illustrated in Figures 1.2 and 2.1. Generally, a small number of characteristics is included so

as not to overwhelm the respondent.6

 The respondent must understand each of the characteristics

(in our case, programs and their benefits) and keep track of changes in each of the characteristics

in both alternatives of a choice question.

 

6. For example, Opaluch et al. (1993) characterize noxious facilities in terms of seven characteristics;

Adamowicz et al. (1997) use six characteristics to describe recreational hunting sites; Johnson and Desvousges

(1997) use nine characteristics to describe social and environmental impacts of electricity-generation

scenarios; and Mathews et al. (1997) use seven characteristics to describe fishing sites.
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-10

Our design asks respondents meaningful questions that support restoration planning by providing

a large-scale perspective of public preferences across alternative types of restoration programs,

and by providing information to scale programs that provide equivalent value to the PCB-caused

losses. The study is not intended to provide a selection of individual projects such as which

specific wetland acres to restore or specific recreational facilities to build. That task is left to Cotrustees and regional planners who have a detailed knowledge of needs, technical effectiveness,

and cost-effectiveness.

The choice of the population to be surveyed

We limited the study to a “target population” of residents from a 10-county area near Green Bay

and the Lower Fox River (Figure 2.2) and sampled from this population. Each county is located

nearly entirely within 60 miles of Green Bay. Because of their proximity to the bay, individuals

from these counties could be expected to be more active users of, and more familiar with, the

natural resources in the Green Bay area than individuals from outside of the target population.

For example, approximately 90% of all recreational fishing days in the waters of Green Bay

(including the Lower Fox River and other tributaries up to the first obstruction) by Wisconsin

residents are by anglers who reside in the 10 counties (Breffle et al., 1999). Respondent

familiarity with the resources increases saliency and thus response rates and reduces the amount

of information that must be presented in the survey. In addition, Shuman and Presser (1996) have

argued that the more crystallized respondent attitudes and values are (which familiarity should

support), the less important small context changes are likely to be in survey design.

Of course, people farther from Green Bay may have suffered damages from PCBs. Restricting

our study to the 10 counties represented a compromise. Some losses would probably remain

uncounted for the sake of greater accuracy of the losses that would be addressed (see Section 6.4

for additional discussion).

Choice of survey mode

The survey was designed to be conducted by mail, with a telephone survey of nonrespondents

(see Chapter 3). On a general level there are three major modes for administering surveys:

personal interview, telephone interview, and mail (Dillman, 2000; Tourangeau et al., 2000).

Telephone interviews were rejected as the main survey mode because we concluded that we

needed to present too much information to effectively convey over the phone without also

mailing information to respondents, and thus increasing costs with limited demonstrated gain in

the response rates and quality over a mail survey. Personal interviews with visual aids can be

effective in communicating information for these types of surveys (Carson et al., 1992), but are

very labor intensive to obtain the desired response rates and generally cost hundreds of dollars

per completed interview. Both telephone and personal interview surveys can be beneficial when

there is a need for interaction between an interviewer and respondent, such as to explain complex
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-11

#

#

#

#

# #

#

#

#

Michigan

Chilton

Oconto

Sturgeon Bay

Kewaunee

OUTAGAMIE

WINNEBAGO

CALUMET

MANITOWOC

BROWN

KEWAUNEE

DOOR

SHAWANO

OCONTO

MARINETTE

Lake

Michigan

Manitowoc

Appleton

Oshkosh

Shawano#

Lake Winnebago

B a y

G r e e n

Marinette

Green Bay

Lowe r Fox R.

Wisconsin

MI

WI

10 0 10 20 Miles

10 0 10 20 Kilometers

Adjacent counties

Second tier counties

City population

# 0 - 12,000 # 12,000 - 30,000

# 30,000 - 55,000

# 55,000 - 65,000

# 65,000 - 97,000

4

Michigan Wisconsin

Area of Detail

Figure 2.2. Target population counties.
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-12

information, or when the series of questions to be asked varies depending on the answers

received as the survey progresses. However, the interpersonal communication in telephone and

personal interviews is more likely to result in potential social desirability biases, wherein the

respondents are more likely to provide what they consider to be socially desirable responses

(Dillman and Tarnai, 1991; Whittaker et al., 1998; Ethier et al., 2000).

By limiting the sample to people in the 10-county area, and by careful design and pretesting, we

reduced the burden of information communication substantially. Our statistical design for the

key questions did not require the questions to be asked to vary depending on the responses to

prior questions. Based on experience, and on repeated pretesting, we concluded that the required

information could be successfully presented in a mail survey approach with high quality

responses and high response rates, so long as respondents were provided a modest completion

incentive of $15. As such, the mail survey approach was the most cost-effective approach to

obtain high quality data.

Focus groups, pretesting, and peer review

An important aspect of survey design is to use focus groups and pretests to ensure that all

material in the survey was clear and readable by members of the general public, that the

information was presented so the context was meaningful and realistic to ensure neutrality of the

survey, and that respondents are providing the information that researchers seek (e.g., the survey

obtains valid information for the study objectives). The TVE survey instrument was developed

and pretested through a series of eight focus groups and three rounds of in-person pretest

interviews conducted in northeast Wisconsin with 182 subjects. The focus groups generally

included 8 to 12 people in semi-structured discussions. In the pretests, the respondents completed

draft survey instruments, and a research team member debriefed the respondent on the survey

instrument and their answers. Table 2.1 indicates the date, site, activity, number of participants,

and focus of the various survey development and pretesting steps.

To further assure that the survey reflected professional standards, the survey instrument was peer

reviewed at various stages by Vic Adamowicz, Professor, Department of Rural Economics,

University of Alberta; Don A. Dillman, Professor of Sociology and Rural Sociology and Deputy

Director for Research of the Social and Economic Sciences Research Center at Washington State

University in Pullman; and Roger Tourangeau, Senior Research Scientist at the Survey Research

Center at the University of Michigan and Research Professor at the Joint Program in Survey

Methodology at the University of Maryland.
Stratus Consulting Survey 

Page 2-13

Table 2.1. Green Bay total value equivalency survey focus groups and pretests.Date Site Activity

Number of

participants

Type of

respondents Focus 

4/29/98 and4/20/98

Green Bay,Wisconsin

Four focus groups 34 General public Assess familiarity with and

terminology used to describenatural resource issues in NEWisconsin

J

9/22/98 and9/23/98

Green Bay,Wisconsin

Four focus groups 42 General public Explore strategies for using stated

preference questions and to betterunderstand the amount and typeof information that was neededand could be provided

J

6/9/99 and6/10/99

Green Bay,Wisconsin

Self-administeredw/debriefing

56 General public Explore stated preference

strategies and ways of describingthe resource management options

RS

8/4/99 Green Bay,

Wisconsin

Self-administeredw/debriefing

36 General public Pretest final survey instrument R

8/5/99 Oshkosh,

Wisconsin

Self-administeredw/debriefing

14 General public Pretest final survey instrument R
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-14

2.2 Detailed Design

In this section we discuss the details of the four major sections of the survey:

1. introductory materials

2. introduction of the four natural resource management topics and programs

3. choice questions

4. follow-up questions including sociodemographic questions.

Table 2.2 outlines the final survey instrument and the general purposes of the questions. A copy

of one version of the survey instrument is provided in Appendix A (the versions vary only by the

levels of programs and costs in the choice questions, which is discussed below).

2.2.1 Introductory materials

Along with the survey instrument, respondents received a personalized cover letter. The

sponsor(s) of the survey and the intended use of the results for restoration planning and damage

assessment were not identified. The cover letter stated that the survey would help

“representatives from government, industry, and citizen groups” determine “what should the

priorities be for natural resource programs in Northeast Wisconsin?” This approach was adopted

as part of our strategy to make the survey neutral with respect to the natural resource alternatives.

The introductory material identified the study area as northeast Wisconsin. This was

reemphasized on the cover page with the title, “What Are Your Opinions About the Future of

Natural Resources in Northeast Wisconsin,” and a color map of the study area on the front page.

When respondents opened the survey booklet, they found an introductory sentence stating that

“Decision makers are examining options for natural resources in northeast Wisconsin.” The

inside front cover provided the definition of the “Bay of Green Bay” as “the waters of the Bay of

Green Bay and all tributaries up to the first dam or obstruction” to focus respondents on

resources issues related to the Bay.

Question 1 asked respondents how often they personally participate in activities related to the use

of the resources on the waters and shorelines of the Bay of Green Bay. This question served as a

simple beginning question, reinforced the location of interest, and elicited information on the

respondents’ natural resource uses to begin the cognitive process of thinking about how the

resources relate to the respondent through their activities.
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-15

Table 2.2. Outline of Green Bay total value equivalency survey.

Section Item or question Purpose

Cover letter Provide information on the purpose and importance of the study.

Cover page —

map

Show the location of Green Bay, major cities and towns, tributaries,

and first dam or obstruction. Identify the study area and indicate the

general purpose of the survey to seek their opinions about the future of

natural resources in the area.

Inside cover Define the term “Bay of Green Bay.”

Introductory

materials

Question 1 Elicit information on participation in outdoor activities. Have

individuals consider their uses of the natural resources around the Bay.

Introduce the four natural resource topics addressed in the remainder of

the survey.

Questions 2-3 Provide information on wetlands and the benefits from increased

wetlands. Elicit the importance on increased wetlands benefits.

Introduce levels of program options in terms of restoring wetlands.

Questions 4-6 Provide information on PCBs and the benefits from PCB removal.

Elicit the importance of PCB removal benefits. Introduce levels of

removal, safe levels, and years of injury.

Questions 7-9 Provide information on state and county parks and their facilities.

Identify levels of enhancements and elicit importance of improved

facilities and new park benefits. Introduce concepts and levels of

programs for enhancing and enlarging state and county parks.

Introduction

to natural

resource

programs

Questions 10-12 Provide information on runoff (nonpoint source pollution) and the

benefits from increased runoff control. Elicit importance of the benefits

of runoff control. Introduce levels of programs to reduce runoff and its

impacts in terms of water quality variables.

What alternatives

do you prefer

Introduce the choice questions. Introduce and define the payment

vehicle. Reiterate key information about each of the four resource

topics.

Choice

questions

Questions 13-18 Implement the choice questions.

Questions 19-22 Obtain information to assist in analyzing individuals’ responses to the

choice questions.

Questions 23-35 Obtain sociodemographic information.

Follow-up and

sociodemographics

Question 36 Elicit additional open-ended comments on the survey.
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-16

2.2.2 Natural resource topics

The next section of the survey introduced each of the four natural resource topics in four separate

two-page sections. Each natural resource topic was given consistent treatment so that none of the

four topics stood out as being presented as more or less important than the others. The four

sections followed a similar presentation, as outlined in Table 2.3 and discussed below.

Table 2.3. Format of the natural resource topic sections.

Natural

resource

topic

Define

topic and

related

benefits

Describe historical trends and

current status of resources for

the topic, and elicit

respondents’ opinions on

importance of enhancement

benefits

Introduce possible

levels of

enhancement and

respondents’

attitudes on action

Provide supporting

table or diagram

on the natural

resource topic and

service flows

Wetlands Introduction Question 2 Question 3 Map of WI wetlands

within 5 miles of the

Bay of Green Bay

PCBs Introduction Questions 4 & 5 Question 6 Table of GB/LFR

FCAs

Outdoor

recreation

Introduction Questions 7 & 8 Question 9 Map of state and

county recreation

areas

Runoff Introduction Questions 10 & 11 Question 12 Figure of water

pollution from

runoff

For each natural resource topic, the presentation began with information defining the resources in

the topic area and other information found to be useful to respondents, such as historical trends

and current status. The next questions identified the benefits associated with resource

enhancements (or correspondingly the impacts of current conditions) and asked how important it

was to the respondent, if at all, to undertake resource programs that would obtain these benefits.

These questions again have respondents consider how the benefits relate, if at all, to their own

interests. Each presentation was accompanied by diagrams or tables, which provided supporting

information, and helped to sustain respondent interest and attention.

The last section for each topic gave more information about potential enhancement programs and

program levels, identified a 10 year implementation period (which matches the subsequent

10 year payment period), and provided other program information. The questions then asked

respondents if they felt that less, the same, or more should be done and spent on the resource

enhancement programs. These questions continue the process of considering program benefits,

especially relative to the added costs to undertake the programs.
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-17

In addition to providing useful information on their own, the responses to the importance and

action questions in these sections also provide consistency checks against the results of the

choice questions. We expected when we designed these questions that the relative importance of

benefits from the natural resource programs, and desire to do or spend less, the same, or more on

these types of programs, would be highly correlated with the results to the choice questions for

all respondents as a whole and generally for each individual respondent.

Wetlands

The resource description focused on wetlands within 5 miles of the Bay of Green Bay and

historical trends in wetland losses and related policies (Harris et al., 1977; Bosley, 1978; WDNR,

1988; Shideler, 1992). A distance of five miles was used to include the primary feeding range of

bald eagles and other species living near the bay, and as an approximation of the distance up the

tributaries where Green Bay fish spawn most often, thus making a strong connection to the

injured natural resources and services. These wetlands were identified using GIS techniques

(ESRI, 1998; WDNR, 1999a). It was stated that regulations now in place will effectively prevent

further reductions in wetland acres (NRCS, 1990; USGS, 1996; WDNR, 1999c) to focus on the

benefits of wetland restoration.

Question 2 identified wetland services such as habitats for fish, birds, and mammals and

described the expected changes in wetland-dependent species if the quantity of wetlands

increased (WDNR, 1979; Christie and Meyers, 1987; Brazner, 1997; Stratus Consulting, 1999a).

Respondents were asked to indicate how important they felt it was to increase wetland acreage to

support birds, fish, and other wildlife (e.g., to obtain program benefits).

Question 3 asked respondents whether they would prefer that less or the same be done and spent

to maintain wetlands, or more be done and spent to restore wetlands. The “do more” option

introduces information on options to restore wetlands and indicates that up to 11,600 acres could

be restored. Based on a review of proposed restoration options, it seemed unlikely that

significantly more than a 20% to 30% increase in wetland acreage would be likely. In addition,

in focus groups and survey pretests, there was significantly diminishing interest in more than a

20% increase in wetlands.

PCBs

The industrial sources of PCBs in the Lower Fox River were identified (U.S. EPA, 1997) and it

was pointed out that PCBs were banned from industrial use in the mid-1970s, which makes it

clear that the issue is not one of stopping continued industrial releases (U.S. EPA, 1998). To

identify how PCBs affect the environment and people, the survey identifies that PCBs have

accumulated in the sediments of the Lower Fox River and the Bay of Green Bay and that birds,

fish, and wildlife ingest PCBs through the food chain (WDNR, 1999b). Injuries were then
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-18

described in terms of (1) FCAs, including an FCA summary table (U.S. EPA, 1996, 1999;

WDNR, 1999b), and (2) harm to wildlife in and around Green Bay. The indicated magnitudes of

risks to birds, fish, and other wildlife were based on several sources (Christie and Meyers, 1987;

Matteson, 1988; Mossman, 1988; Matteson and Erdman, 1992; U.S. EPA, 1998; Stratus

Consulting, 1999a, 1999b; ThermoRetec Consulting, 1999).

Questions 4 and 5 discussed the impact of PCBs on wildlife and potential human health impacts

and asked respondents to tell us how important they felt PCB removal was, if at all, to them so

that it is safe to eat fish and waterfowl, and to reduce harm to birds, fish, and other wildlife.

Question 6 then asked them whether they would prefer that no further efforts go into PCB

investigations and removal, or that more should be done to remove PCBs. To provide a single

index of PCB injuries (or benefits from removal), the concept of years until PCBs are at safe

levels was identified and defined: “By safe levels we mean there are no consumption advisories

for, and no harm to, nearly all fish and wildlife.” The question introduction and responses

identified how long it will be until safe levels under alternative options, ranging from 100 years

under the do-no-more options to between 20 and 70 years with some PCB removal (Stratus

Consulting, 1999a). Also introduced are the 10 year removal implementation period and that

damages would decline through time thereafter. “ No “do less” option was offered since doing

less removal (other than completing the demonstration projects) is not feasible.

Outdoor recreation

The quantity and distribution of state parks and natural areas and county parks (there are no

national parks) in the 10 county region were described in the introduction and on the

accompanying map in this section of the survey (ESRI, 1998; WDNR/GEO, 1998). Recreational

sites throughout the 10 counties are widely accessible to residents, and many of these sites

provide services similar to the types of recreational services affected by PCB contamination. We

included all 10 counties to increase the likelihood that a respondent (from any of the 10 counties)

would expect to experience benefits from the proposed enhancements (e.g., focus groups

suggested that if only parks within two miles of the bay were included, many respondents from

greater distances would have a lower likelihood of using the enhancements, and would most

likely report lower importance and values for such a recreation program). We excluded city

parks as many of these provide services (e.g., ball parks, playgrounds) dissimilar to the affected

recreational services. Facilities offered at outdoor recreation sites were described (WLRB, 1997)

as was the potential need for more facilities to meet future needs.

Questions 7 and 8 introduced the possibility of adding facilities at existing parks and opening

new parks throughout the 10 county area, with the 10% enhancement level illustrated.

Respondents were asked how important it was to them to improve existing parks and to add new

parks. In Question 9, the 10 year implementation period was defined, and respondents were

asked if they prefer less or the same be done and spent to maintain existing facilities, or more be
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-19

done to add facilities and new parks. Note that only a 10% enhancement was considered because,

in focus groups and pretests, most respondents expressed significantly diminishing and even zero

interest in more than a 10% increase in recreational facilities.

Runoff

Sources of runoff to the Green Bay watershed, and the impacts of runoff on bay resources, were

explained next (WDNR, 1988, 1993a, 1993b, 1996a, 1996b, 1997a, 1997b, 1997c; Harris, 1993).

In response to what we heard in focus groups and pretest interviews, we identified how runoff

can be reduced; pointed out that invasion of zebra mussels was leading to some improvements in

water clarity, but that the future effects of the zebra mussel invasion were uncertain (Harris,

1993); and identified that runoff is not a source of PCBs and does not affect drinking water

quality (Bierman et al., 1992). To improve respondents’ understanding of runoff, an illustration

provided a stylized river cross-section showing sources, transport, and impacts.

Question 10 discussed how, how much, and where nutrients in runoff lead to excess algae in

Green Bay (Harris and Christie, 1987; Harris, 1993; Sachs, 1999), and asked respondents how

important it is to them to reduce the number of days with excess algae in Green Bay. Question 11

discussed the impacts of sediments and algae on water quality, and the resulting impacts on

aquatic habitat, fish, and birds (Sager et al., 1996). Because not all these effects could be

quantified, water clarity was used as an index for these effects when asking how important it

would be to reduce runoff to improve water clarity (and used in subsequent survey questions).

Question 12 stated that runoff control options would take 10 years to reach their goals and asked

individuals if they prefer less, the same, or more be done and spent to control runoff. The “do the

same” option reminded respondents that current water clarity averages about 20 inches in the

summer and that there are currently about 80 days a year of excess algae in the southern Bay of

Green Bay. The “do more” option specifies that potential control programs could lead to up to a

50% reduction in runoff, resulting in water clarity of 34 inches and 40 days a year of excess

algae. The days of excess algae and inches of water clarity were estimated based on regression

models of phosphorus and water quality in lower Green Bay using data provided by Dr. Paul

Sager, University of Wisconsin-Green Bay, and summarized in Harris (1993).

2.2.3 Choice questions

Introduction

The choice questions were preceded by an introductory page “What Alternatives Do You

Prefer?” which set the context for the choices to be made. The context included making choices

among alternatives that enhance natural resources and that will cost more for the respondents’

households beyond what they are now paying. To provide a credible scenario and to reduce
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-20

scenario rejection since respondents often indicated that the responsible parties (industry,

farmers) and specific/interest user groups should pay for these improvements, the survey

indicated that “some costs will be paid by industry, farmers, and conservation organizations. But

taxpayers may have to pay something as well.” Household payments would be made through

increases in local, state, and federal taxes. Consistent with the 10 year time period for each of the

natural resource options to be implemented, a 10 year payment period was specified. Based on

the focus groups and pretest interviews, we judged that this represented an acceptable and

realistic payment vehicle and time frame to respondents.

To ensure that key features of the trade-off scenarios were clear, the choice section introduction

reiterated key items of the natural resource programs, and the choice questions further identified

how the proposed program levels compared to existing conditions. The first choice question also

provided extended information, including describing the baseline conditions and identifying the

specific differences between the two alternatives to aid in successfully working through the first

question.

Choice question design

Each choice question includes a pair of alternatives, or a choice pair. Each alternative contains a

specific combination of the levels of the four natural resource programs and costs to the

respondent’s household. The levels considered for each natural resource program, and household

costs, are summarized in Table 2.4. The levels considered ranged from the current conditions to

varying levels of improvement to current conditions (discussed above for each program). This

reflects the objective of determining the level of restoration program enhancements that will

provide services of equivalent value to the value of an enhanced PCB removal program. Further,

we found in pretesting, as well as in the final results, that very few respondents preferred to do

less and spend less on any one of the natural resource programs (typically less than 3%). If fact,

except for increased recreational facilities and parks, the majority of respondents supported

doing more and spending more on each of the programs (between 55% and 81%). However, for

some or all programs, some respondents may prefer the status quo level of effort, spending, and

benefits as compared to program improvements that cost them money. This potential is

accommodated in the design of the questions (see “referendum pairs” below). The annual

household costs ranged from $0 to $200. This range reflected focus group and pretest results and

a desire to have a range that covered a substantial share of the likely range of values that

households may have so as to reduce potential truncation bias that could bias downward the

valuation results (Rowe et al., 1996).
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-21

Table 2.4. Green Bay equivalency value survey — attribute levels.

Attribute Level 1 Level 2 Level 3 Level 4 Level 5

Wetlands

Acres in Wisc. around Green Bay

(currently 58,000)

58,000

acres

(current)

60,900

acres

(5% more)

63,800

acres

(10% more)

69,600

acres

(20% more)

n.a.

PCBs

Years until safe

(currently more than 100 years)

100 or more

years

(current)

70 years

(30%

faster)

40 years

(60%

faster)

20 years

(80%

faster)

n.a.

Outdoor recreation

Facilities at existing parks 0% more

(current)

10% more n.a. n.a. n.a.

Outdoor recreation

Acres in new parks

(currently about 86,000 acres in

state and county parks)

0

(current)

4,300

(5% more)

8,600

(10% more)

n.a. n.a.

Runoff

Average water clarity in southern

Bay (currently 20 inches)

Excess algae (currently up to 80

summer days in the southern 

Bay)

20 inches

(current)

80 days or

less

(current)

24 inches

(20%

deeper)

60 days or

less

(25%

fewer)

34 inches

(70%

deeper)

40 days or

less

(50%

fewer)

n.a.

n.a.

n.a.

n.a.

Added cost to your household

Each year for 10 years $0 $25 $50 $100 $200

The alternatives were designed and combined into choice pairs to obtain sufficient independent

variation in the attributes to statistically identify the separate influence of each attribute on the

choice of Alternative A or Alternative B. The survey was designed to include six choice pairs to

limit potential respondent fatigue associated with answering repetitive questions. Ten sets of

choice pairs (i.e., 10 survey versions) were designed to obtain sufficient variation in choice pairs

for statistical analysis. Thus, a total of 60 alternatives were designed (10 sets with 6 pairs each).

Given the number of characteristics and the levels they can take, there were over 1,400 possible

alternatives and an extremely large number of possible pairs of alternatives. Several software

packages are available to select choice pairs to meet statistical design objectives, and in many
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-22

packages constraints may be imposed to eliminate certain types of inappropriate pairs. We used

SAS Proc Factex and Proc Optex to help design the pairs. However, one quickly finds that, even

with multiple constraints imposed on the selected pairs, the software package results are not

entirely satisfactory. Therefore, we further designed the selected choice pairs to reflect additional

considerations related to the complexity of the pairs and to ensure realism and consistency in the

pairs presented to any one respondent, as discussed below. The final survey pairs are

summarized in Appendix A, Table A.1.

Using randomly generated pairs results in many, or even most, pairs involving varying levels of

many attributes in each alternative. Thus, respondents are presented with the task of

comprehending and selecting between mixes of multiple programs changes in each alternative in

most or all of the questions. This may be a complex task for some respondents, especially if there

are limited practice questions, and may result in respondents choosing to focus only on a subset

of attributes as the basis for decision making, thus increasing the variance in the estimation of

preferences. One way to try to partially address this would be to provide simplified practice

questions to make respondents accustomed to the format. However, a lot of space and respondent

time would go into practice questions that would not generate useful data.

Instead of practice questions, we selected a design to graduate respondents from simple to more

complex choice pairs as they progressed through the survey instrument, thus reducing the

cognitive burden at the outset. This would have the additional benefit of allowing us to do

selected statistical comparisons of the responses across different types of choice pairs and, early

in the question sequence, to address potential preferences for the status quo (see Section 4.7 and

Chapter 5). Three types of choice questions were used:

} Simple resource-to-resource pairs. The first paired comparison question in each version

of the survey (see Figure 1.2 and Question 13 in all of the survey versions) presented a

choice between an improvement in one attribute in Alternative A and an improvement in

a second attribute in Alternative B.7

 Other program levels (attributes) were held at current

levels in both alternatives, and the same dollar cost was presented in both alternatives

(see Question 13 in the sample survey in Appendix A). The programs and levels of

changes were varied across the survey versions, and across Alternatives A and B, to

cover all the resources, with slightly more cases with PCBs as one of the alternatives.

This design provided several benefits. First, respondents began the paired comparisons

with a relatively simple question that was expected to be more easily answered, leading

them to continue the survey. Second, the results provided simple tradeoff results between

program levels that did not require a complex statistical model to begin to evaluate the

results.

 

7. A few simple resource-to-resource questions were added or randomly occur in subsequent questions.
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-23

} Referendum pairs. The second question in each survey version (Question 14) presented

a choice between an improvement in one attribute and the associated increased costs

versus no change in the attributes from current levels and costs (e.g., the status quo, see

Figure 2.1 from survey version 1 where Alternative A reduces the years until PCBs are at

safe levels from 100 years to 40 years at a cost of $200, and no other changes occurring,

compared to Alternative B of the status quo and no increase in household costs). For the

referendum questions, the attribute levels and dollar costs were varied across the survey

versions, and across Alternatives A and B, to cover a broad range of the resources, with

slightly more cases with PCB as one of the alternatives. These questions provided a

relatively simple trade-off early in the question sequence to aid respondents’ progress

through the choice questions, and provided an early question in which respondents may

demonstrate a preference for the status quo as opposed to program enhancements at

added costs to their household. This type of question is similar to a traditional contingent

valuation referendum question and provided evidence on the relative merits of resourceto-resource trade-offs versus resource-to-money trade-off questions.

} Complex choice pairs. The third type of questions are ones in which either or both

Alternative A and Alternative B may have changes in more than one resource program

and costs as compared to current conditions, generally resulting in complex comparisons

that we expect may result in increased noise in the estimation of preferences.

The pairs in Questions 15 through 18 were allowed to be of any of the above question types, and

generally are complex choice pairs. The starting point for selecting these pairs was obtained by

applying the pair-design software programs to generate more pairs than needed. To retain

realism, dominant choice pairs were eliminated. These were cases where one alternative was

clearly an improvement over the second alternative. For example, Alternative A would have the

same or increased levels of each natural resource program at the same or reduced cost compared

to Alternative B. Respondents reported such questions as unrealistic choices (e.g., “How can you

get more environmental benefits at the same or lower costs?”). Furthermore, such choices

provide little statistical benefit.

Next, the selection and assignment of pairs to survey versions was considered. Sequencing

conflicts within a survey version were evaluated and limited. For example, assume Question 14

proposed a small change in wetlands (e.g., 5,800 acres) at a high cost (e.g., $100 per year per

household). If a subsequent question traded off a much larger change in wetlands (or the same

small change in wetlands plus enhancements in other resource programs) at a much lower cost

(e.g., $25 per year per household), participants in focus groups and pretests questioned the

realism of the question set and its policy relevance. Sequencing was also evaluated in terms of

avoiding a string of questions in any survey version focusing on one of the four resource

programs, to avoid emphasizing any one topic in any survey version. The assignment of pairs to
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-24

survey versions also considered the ability to compare results across survey versions, as well as

within survey versions.

These steps increased the realism of the choices for respondents. There are some nonzero

correlations between the various attribute levels across the alternatives (see Table 2.5), but this is

not uncommon and the correlations here are sufficiently orthogonal to support the accurate

estimation of parameters.

2.2.4 Follow-up questions and demographics

The remaining survey questions help us analyze responses to the choice questions and other

survey questions. Question 19 asked how important each attribute in the choice questions

(i.e., acres of wetland, years until safe levels of PCBs) was in the choices made by the

respondent. We expect a strong correlation between the choice question results and the ratings in

this question, reflecting that respondent answers to the choice questions are consistent with their

intended rating of importance of the various factors to be considered, and we further expect both

of these results to be correlated with the importance assigned to the benefits of the natural

resource programs, and desired actions for less, the same, or more of these programs as reported

in Questions 2 through 12.

Question 20 asked how confident respondents were in their answers to the choice questions, and

Question 21 asked whether their responses to the choice questions should be considered by

decision makers. Recognizing that the choice questions may be difficult for some respondents,

these questions are intended to give an indication of the quality that respondents assign to their

responses. Question 22 asked about pre-survey awareness of natural resource issues. We

expected that awareness of the issues would be related to increased interest in and value for these

programs, and that increased awareness would result in improved response quality (Cameron and

Englin, 1997).

Because we expected that whether or not individuals from a household fish in Green Bay may be

a significant explanatory variable, and to address potential double counting between the

recreational damage determination (Breffle et al., 1999), Question 23 asked whether the

respondent or anyone else in the household had fished in Green Bay or its tributaries up to the

first dam in the last 12 months. This question is more specific than Question 1, which asks about

the typical activity levels. We treat this question as an improved measure of interest in Green

Bay fishing compared to Question 1, rather than as a specific estimate of such activity because

the survey does not focus on fishing and asks for a full year recall (see Breffle et al., for
Stratus Consulting Survey 

Page 2-25

Table 2.5. Correlation between choice set attribute levels.

Wetlands

A

PCBs

A

Recreation

A

New

parks A

Runoff

A

Cost

A

Wetlands

B

PCBs

B

Recreation

B

N

par

Wetlands A 1.000PCBs A -0.104 1.000Recreation A 0.205 0.078 1.000New Parks A 0.386 0.121 0.080 1.000Runoff A 0.313 -0.167 0.097 0.186 1.000Cost A 0.337 -0.298 0.101 0.330 0.206 1.000Wetlands B 0.163 -0.071 0.008 0.140 0.115 0.094 1.000PCBs B -0.474 0.107 -0.361 -0.142 -0.123 -0.042 0.076 1.000Recreation B 0.304 -0.149 -0.045 0.116 0.178 0.102 0.122 -0.114 1.000New Parks B 0.294 -0.319 -0.053 0.170 0.191 0.077 0.126 -0.122 0.141 1.0Runoff B 0.194 -0.141 0.026 0.150 0.013 0.144 0.162 0.003 0.156 0.Cost B 0.388 0.053 0.263 0.262 0.194 0.030 0.171 -0.412 0.191 0.3
Stratus Consulting Survey Design (Final, 10/25/00)

Page 2-26

estimates of Green Bay fishing activities and for discussions of recall bias in reported fishing

activity levels).

Questions 24 through 35 asked background sociodemographic questions. Question 36 allowed

respondents to provide additional comments about the survey and topics addressed.
3. Survey Implementation

3.1 Sample Selection

Our goal was to obtain 400 to 450 completed surveys, which would provide sufficient sample

size to evaluate preferences with statistical confidence based on experience with similar studies

(Breffle et al., 1999). With 6 choice questions per respondent, such a sample size would provide

a minimum of 2,400 choice question responses (6 × 400). Based on experience with rates of

ineligible addresses from mailing lists (10% to 20%) and expected response rates from eligible

households (60% to 75%), a total starting sample of 750 was selected.

A stratified random sample was drawn from the 10-county area based on two sampling strata, as

identified in Figure 2.1 and Table 3.1. The two strata radiate out from the Bay of Green Bay,

reflecting the focus on the natural resource programs presented:

1. The “adjacent” stratum of five counties with shoreline on the Bay of Green Bay, the

population of which is predominately located within about 20 miles of the bay.

2. The “second tier” stratum of five counties that border the “adjacent” counties.1

 These

counties are located 10 to 60 miles from the bay, with the largest cities in these counties

generally 30 or more miles from the bay.

The sample was weighted to emphasize households in the first stratum, since these households

were likely to be the most familiar with the resources in question, and have the highest PCBcaused service flow losses and the highest potential benefits from natural resource restoration

projects. However, we judged that people in the second tier counties were close enough to the

assessment area to be familiar with the resources in question and potentially to have PCB-caused

service flow losses. Furthermore, including the second tier would allow us to investigate how the

scaling of restoration and WTP vary with distance within 60 miles of the site. The strata were

weighted to achieve a minimum of 300 responses from the adjacent stratum and a minimum of

125 responses from the second tier stratum. Within each stratum, the sample was divided among

counties based on the estimated 1998 population in the county, assuming the number of

individuals per household was consistent across counties.

 

1. Three potential second tier counties (Forest, Menominee, and Langlade) were excluded because all or nearly

all of Forest and Langlade are more than 60 miles from the site, and Menominee has a small population.
Stratus Consulting Survey Impleme

Page 3-2

Table 3.1. Green Bay total value equivalency survey sample plan.County City

County

touches

bay

Approx. county

distance to bay

Approx. largest

city distance

to bay

1998a

population % of total Sampleb

Adjacentstrata

Strata

weight 1.600

Brown Green Bay Yes <20 <10 218,149 26.87% 320Door Sturgeon Bay Yes <20 <10 26,537 3.27% 40Kewaunee Kewaunee Yes <25 <20 19,904 2.45% 30Marinette Marinette Yes <60 <10 42,523 5.24% 65Oconto Oconto Yes <60 <10 33,089 4.07% 50Adjacent strata subtotal 340,202 41.90% 505 Second tierstrata

Strata

weight 0.570

Calumet Chilton No 25-40 35 38,760 4.77% 20Manitowoc Manitowoc No 15-50 35 84,434 10.40% 45Outagamie Appleton No 10-40 30 155,953 19.21% 80Shawano Shawano No 10-60 30 38,730 4.77% 20Winnebago Oshkosh No 30-60 45 153,937 18.96% 80Second tier subtotal 471,814 58.10% 245 Totals 812,016 100% 750 a. Wisconsin Official Population Estimates, County Estimates (1998).b. Sample by county = 750 × % of total × strata weight, rounded to nearest 5. Ten survey versions randomized across each coun
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-3

Households within a county were randomly selected by Genesys Sampling Systems from

households with listed telephone numbers and available addresses. In northeast Wisconsin this

provided coverage of more than 77% of all households in the target population, as measured by

the ratio of households with listed telephone numbers to total households (Table 3.2). The

percentage of listed households varies by county, but is consistent across the aggregate of all

counties in the two sampling strata (76.9% and 78.4%).

Table 3.2. Households with listed telephone numbers.a

Strata/county Households Number listed Listed %

Adjacent strata

- Brown

- Door

- Kewaunee

- Marinette

- Oconto

Subtotal

88,228

17,593

7,453

26,455

17,896

157,625

71,350

14,050

6,074

19,125

10,555

121,244

81%

80%

81%

73%

59%

76.9%

Second tier strata

- Calumet

- Manitowoc

- Outagamie

- Shawano

- Winnebago

Subtotal

14,140

31,570

68,238

16,227

58,971

189,146

6,745

25,179

57,155

12,077

47,081

148,237

48%

80%

84%

74%

80%

78.4%

Total

- Unweighted

- Weightedb

77.8%

77.3%

a. Source — Genesys Sampling Systems.

b. Weighted by sample size for each strata; see Table 3.1.

Because the survey was designed to obtain head of household attitudes and values, the design

allowed for either a male or a female head of household to complete the survey.

3.2 Implementation

The survey was implemented by the Hagler Bailly Survey Center in Madison, Wisconsin. As

noted above, ten versions of the mail survey were prepared. Sampled households were randomly

assigned a version number before implementation. Standard procedures for repeat-contact mail
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-4

surveys (Dillman, 2000) were followed, except that we added an attempt to contact

nonrespondents by telephone.

1. Initial mail survey package. This package consisted of a cover letter from the Hagler

Bailly Survey Research Center explaining the study, a 21-page mail survey booklet, and a

postage-paid return envelope. The cover letter stated that a $15 check would be sent to

respondents if they completed the survey by September 30. The surveys were mailed on

September 10.

2. Thank you/reminder postcard. All sampled individuals were mailed a postcard 5 days

after the initial mailing (September 15). The postcard thanked those who had responded

to the survey and reminded those who had not yet responded to please do so.

3. Combination telephone and mail follow-up. Between October 5 and October 12, 1999,

we tried follow-up telephone calls with all sample households that had remained

potentially eligible and that had not returned the survey up to that point. Those we

reached were told that the study deadline had been extended. They were asked whether

they had received the survey and whether they had returned it. Those who had not

returned the survey were asked to please complete it by October 18 and return it. If they

needed another copy of the survey, it was mailed the day after the telephone call.

Respondents reached by telephone who recalled receiving the mail survey, and who

indicated they would not be returning it, were asked to complete a short telephone survey.

Households that were not reached by phone by October 13 were sent another mail survey.

The cutoff date for accepting completed mail surveys was November 5, 1999.

Table 3.3 shows the response rates for the mail survey, by county, stratum, and in total. Overall,

we received completed mail surveys from 72% of the eligible (adjusted) sample. The eligible

sample did not include those who were known to be deceased, those for whom the mailings were

undeliverable, those who had disconnected telephone numbers, those where the telephone was no

longer a residential phone, and one individual identified as a U.S. Fish and Wildlife Service

employee.2 Four surveys were returned less than half completed and were treated as

nonresponses.

 

2. Of the starting sample, 87% remained in the eligible sample (13% were removed from the sample based on

the above criteria). While this varied somewhat by county, the eligible sample proportion of the starting

sample was quite consistent across the aggregate of all counties in each of the two sampling strata (86.5% and

87.1%). The completion rate varied by county, but was consistent across the aggregate of all counties in each

sampling strata (72.3% and 71.3%).
Stratus Consulting Survey Impleme

Page 3-5

Table 3.3. Mail survey response rates.

Total Brown Calumet Door Kewaunee Manitowoc Marinette Oconto Outagami

Starting sample size 750 320 20 40 30 45 65 50 80 Undeliverable 53 15 1 9 3 1 8 5 2 Deceased 4 2 0 0 0 0 1 1 0 Out of sample 43 19 1 2 2 5 3 0 5 

Service employee 1 0 0 0 1 0 0 0 0 Disconnected phone number 39 19 1 1 1 4 3 0 5 Non-household 3 0 0 1 0 1 0 0 0 

Adjusted sample size 650 284 18 29 25 39 53 44 73 Refused 51 22 1 1 3 4 7 1 6 

Mail refusals 5 0 0 0 1 1 0 0 2 Phone refusals 39 19 1 1 2 2 4 1 4 Elderly/unable tocomprehend 7 3 00 0 1 3 0 0 

Partially completed survey (lessthan half completed) 4 1 00 0 0 2 0 0 Number of completed surveys 470 214 13 20 17 25 33 32 52 Response rate to mail surveya 72% 75% 72% 69% 68% 64% 62% 73% 71% a. Computed as the number of completed surveys/adjusted sample size.
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-6

We tried to call 327 members of the sample, reached 217 and 136 said that they intended to

return the survey. Of these 136, 83 (61%) did return the survey by the cutoff date. The remaining

81 respondents reached by telephone either refused to complete the mail survey or were

incapable of returning the survey (e.g., language barrier or age), including 13 who completed the

brief telephone survey (these 81 nonrespondents remained in the sample for response rate

calculations).

We could not reach 110 members of the sample. Of these, 42 were deleted from the sample

because of bad or disconnected telephone numbers (the sample was of households with listed

phone numbers). Of the remaining 68 subjects, 60 were sent a second mail survey and cover

letter extending the response deadline (a few respondents were deleted from this mailing

reflecting households where an individual was reached but where there was a potential language

barrier). All 68 respondents with potentially valid phone numbers, but where contact could not

be made, were left in the sample for the response rate calculations.

Of the 60 people who were sent a second survey after we could not reach them by telephone,

24 (40%) returned it before the cutoff date. The lower response rate for these households most

likely reflected a combination of factors: more resistant sample members, additional bad

addresses in the sample, and seasonal residences where respondents may not have received any

of the mail or phone contacts. The 1990 Census (Census of Population and Housing, STF1A) for

Door and Marinette counties (two counties with lower response rates) indicated that about onethird of the housing units were for “seasonal, recreational or occasional use,” compared to an

average of about 7% for the other eight counties.

The response rate to individual survey questions was high. For all questions other than the

11 parts of Question 1 and Question 35, item nonresponse was less than 2.5%. Item nonresponse

for Question 35, the income question, was 4.7%. The rate of “don’t know” responses was also

very low, less than 3.0% for every question in the survey.

3.3 Evaluation of Potential Sample and Nonresponse Biases

3.3.1 Introduction

To summarize the results at the outset, while we find some differences in the characteristics of

the survey respondents compared to the target population, statistical analyses in Chapters 4 and 5

indicate that these differences are not likely to result in any significant biases to the results.

Sampling bias refers to possible differences between the sample selected and the target

population. The target population was all households in the 10 counties neighboring the Bay of

Green Bay and the Lower Fox River, with responses sought from a head of the selected
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-7

household. Given the sample was selected from households with listed telephone numbers, the

most likely source of sampling bias, if any, would be differences between those households with

and without telephone numbers. Given that about 77% of the households in both sampling strata

of the target population have listed phone numbers (Table 3.2), households without listed

telephones would need to be dramatically different from those with listed phones for there to be a

substantial sampling bias in the results of this study.

Research by Piekarski (1989) indicates that households with unlisted telephone numbers are

more likely to be multifamily housing units and renter occupied than are listed households

(which are more likely to own their residences). Younger persons (both female and male) and

single, divorced, and separated householders (with and without children) are more likely to be

unlisted than are other types of households. Finally, retired householders are more likely to be

listed than employed householders. We examine the impact of these potential differences later in

this section.

Nonresponse biases potentially result from the differences between the respondents and the

nonrespondents in the sample. In some valuation assessments, analysts are concerned that

individuals who are less interested in (and have lower awareness of) the topics addressed in the

survey are less likely to respond. Such individuals would be likely to have lower benefits from

natural resource improvements. This difference could lead to an upward bias in the estimated

WTP values. However, for restoration scaling this potential bias would be minimal if

nonrespondents have proportionately lower values for both PCB injuries and for the benefits

from other restoration projects. In any case, the mail survey had a high response rate of 72%,

which can be expected to significantly limit the magnitude of any potential nonresponse bias on

the overall assessment.

3.3.2 Comparison of phone survey and mail survey respondents

In the phone survey, we completed comparison questions with 13 individuals who said they

would not return the mail survey. While the telephone follow-up sample size of 13 for this

comparison is very small, the results are suggestive. The telephone survey covered demographic

characteristics, participation rates in fishing and other outdoor activities, and streamlined

versions of the importance ratings for increased wetlands, PCB removal, and increasing facilities

at existing parks in questions that closely parallel the mail survey questions 2, 4, 5, and 7. (To

streamline the telephone survey, a runoff question was omitted.) The 13 nonrespondents were

much less likely to report that they or household members are Green Bay anglers than the mail

survey respondents (1 of 13 versus 30% in the mail survey). As described in Chapter 5, Green

Bay anglers have PCB values approximately 20% larger than for those who were not Green Bay

anglers, and similar relative values for the other natural resource programs. Thus,

nonrespondents may require slightly less restoration to provide services of equal value to PCB
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-8

injuries than do respondents, but we would not expect the effects to be large. In addition, we

found the following:

} The 13 nonrespondents reported lower participation rates than did mail survey

respondents for each of the outdoor recreational activities asked.

} The importance ratings for each of the natural resource benefits are not statistically

different between the 13 nonrespondents and mail survey respondents (Table 3.4). As in

the mail survey, the rating for outdoor recreation facilities is much lower than for the

other programs, and the ratio of importance for PCBs and wetlands to outdoor recreation

is larger for the 13 nonrespondents than in the mail survey. The relative significance of

wetlands to PCBs is slightly higher in the phone follow-up than in the mail survey, but

the sample size is insufficient to place much emphasis on this.

} The 13 nonrespondents are slightly, but not statistically significantly, older (58.6 years

versus 50.8 years), have smaller household sizes (1.7 versus 2.7), and are more likely to

be female (46% versus 29%). The sample size in the telephone survey is insufficient to

conclude that these are meaningful differences, and thus any differences are expected to

have at most a negligible impact on the assessment.

Table 3.4. Comparison of importance ratings from phone and mail surveys.

Telephone survey Mail survey

Net of don’t knows Net of missing/don’t knows

Importance to . . . Mean SE Mean SE

Z value

for

difference

Increase wetland to support increased

populations of wildlife 4.16 0.37 3.9 0.05 0.70

Remove PCBs so it is safe to eat fish and

waterfowl 4.08 0.38 4.3 0.05 0.58

Remove PCBs to reduce risks to wildlife 4.16 0.37 4.3 0.05 0.38

Add new facilities at existing state and

county parks 3.00 0.51 3.6 0.05 1.18

In summary, the results for the 13 nonrespondents who completed the phone comparison

questions suggest that while modest differences in restoration scaling might occur because of

differences between respondents and nonrespondents, the evidence from within the study does

not support concluding that any resulting biases would be substantial.
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-9

3.3.3 Comparison of Census information and mail survey respondents

Another way to consider sampling and nonresponse bias is to look outside the study by

comparing the characteristics of the sample and the target population based on Census data, and

then consider how these differences may affect the assessment based on the analyses in

Chapters 4 and 5. However, the mail survey sample is of heads of households, and for most

socioeconomic characteristics the most similar readily available Census data are for all adults

age 18 and older. This provides a somewhat misleading comparison because many younger

adults are less likely to be heads of households.

The analyses in Chapters 4 and 5 show that higher levels of participation in outdoor recreation

(especially whether respondents are Green Bay anglers) and higher levels of awareness of the

four resource issues are key variables in explaining how much restoration is of equal value to the

value of PCB-caused losses, and the magnitude of WTP values, per household. Therefore, we

consider here how demographic characteristics of the survey respondents might be different from

the population and how the differences might, if at all, affect the assessment.

Table 3.5 shows that more survey respondents own their residences than do members of the 1990

adult population (84% versus 71%). In part, this most likely reflects that some young adults in

the Census data are not heads of households and are less likely to own their residence than are

heads of households. This is also consistent with the Piekarski (1989) evidence that samples

based on listed telephones may over-represent households that own their residences. Simple

Pearson correlations suggest that residence ownership is positively and significantly correlated

with awareness for three of the four natural resource topics (with outdoor recreation being the

exception) and with increased levels of recreation, but not with increased participation in Green

Bay fishing. However, the strength of the relationships between residence ownership and these

variables, or on choices made in Questions 13 through 18, is either small or insignificant.

Table 3.5. Ownership of residence (Question 24).

Tenure

Number of

observations Percent of respondents

Percent of occupied housing units

in 10 county areaa

Own 395 84.0% 71.2%

Rent 73 15.5% 28.8%

Missing 2 0.4% NA

a. Source: U.S. Census Bureau (1990).

About 71% of the mail survey respondents were males, which exceeds the population proportion

among adults (Table 3.6). The fact that listed telephones are more likely to be in the male head of

household name than the female head of household name explains this result. Further, any adult

head of household could complete the survey to reflect the household attitudes and values, so it
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-10

Table 3.6. Gender of respondents (Question 26).

Number of

observations Percent of respondents

Percent of population in

10 county areaa

Male 335 71.3% 49.2%

Female 135 28.7% 50.8%

Missing 0 0.0% NA

a. Source: U.S. Census Bureau (1990).

is valid for female heads of household to have their male counterparts complete the survey.

While we do not consider the sample gender ratio to be a source of bias, we note that males

reported higher rates of outdoor participation (including Green Bay fishing) and were more

aware of all four resource issues than females. This also may be part of the reason why the male

head of household chose to complete the survey.

The average age of survey respondents is about 51 years (ranging from 21 to 96 with a standard

error of 0.73). The Census population average is 44.3 years old for adults over 18 years of age.

That retired individuals are more likely to have listed telephones may be part of the reason.

However, the Census population average includes young adults who are living with others

(e.g., parents, older relatives), and who are not a head of the household. Thus, heads of

households are expected to be older than the average adult age 18 and older. Further, male heads

of household, who more frequently completed the survey, on average are older than female heads

of household. Finally, while recreational participation (other than fishing) increased with age, the

rate of participation in Green Bay fishing decreased. Overall, we do not anticipate that difference

between the age distribution of our respondents and the age distribution of all adults in the

population had a biasing effect on the analysis in the next chapters.

Table 3.7 shows that the sample mean family size of 2.7 individuals is comparable to the

population mean family size (also 2.7 people per household). Table 3.8 shows that the racial and

ethnic compositions of the sample and the population also are very comparable. For these two

characteristics, the Census variable is directly comparable to its counterpart sample variable, and

the results are very similar.

Table 3.9 shows that the sample tends to have a higher level of educational attainment than the

population of all adults. Here again, the Census statistics may not be strictly comparable to our

population of heads of households. Many adults 18 and older in the Census figures are younger

adults who may not have completed their schooling. There may also be some effect due to

households with unlisted telephone numbers being more likely to be renters rather than

homeowners. Presumably homeowners tend to have higher levels of educational attainment and

income.
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-11

Table 3.7. Household and family size (Questions 28, 29, 30, 31).

Net of missing

Question

Number of

observations Mean SE Missing

How many people are there in your household,

including yourself? 468 2.7 0.06 0.4%

How many children do you have, whether

living with you or not? 467 2.3 0.08 0.6%

How many grandchildren do you have, whether

living with you or not? 464 2.0 0.18 1.3%

How many listed telephone numbers does your

household have? 465 1.1 0.02 1.1%

Census estimate of average household size

for 10 counties a NA 2.7 NA NA

a. Source: U.S. Census Bureau (1990).

Table 3.8. Racial or ethnic background (Question 34).

Racial or ethnic background Percent of respondents

Percent of population in

10 county areaa

White or Caucasian 97.9% 97.3%

Black or African American 0.2% 0.3%

Hispanic or Mexican American 0.2% 0.7%

Asian or Pacific Islander 0.4% 1.0%

Native American Indian 0.9% 1.2%

Other 0.0% 0.2%

Missing 0.4% NA

a. Source: U.S. Census Bureau (1990).

Table 3.9. Highest level of schooling attained (Question 32).

Level of schooling

Percent of

respondents

Percent of population

age 18 and older in

10 county areaa

Did not complete high school 5.1% 21.0%

High school diploma or equivalent 38.1% 40.0%

Some college, two year college degree (AS) or technical school 31.7% 17.3%

Four year college graduate (BA, BS) 12.3% 10.6%

Some graduate work but did not receive a graduate degree 4.3% NA

Graduate degree (MA, MS, MBA, PhD, JD, MD, etc.) 7.7% 3.7%

Missing 0.9%

a. Source: U.S. Census Bureau (1990).
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-12

Table 3.10 shows that the sample has fewer employed individuals and more retired individuals

than the population. Education levels and employment status were found to have little influence

on the key assessment variables.

Table 3.10. Employment status (Question 33).

Employment category Percent of respondents Percent of 10 county populationa

Employed full time 64.7%

Employed part time 5.5%

77.4%

(employed full or part time)

Retired 25.7%

Homemaker 2.1%

Student 0.6%

19.8%

(not in labor force)

Unemployed 1.1% 2.8%

Missing 0.2% NA

a. Percent of labor force aged population (i.e., 16 years and older) for 1997.

Source: Wisconsin Department of Workforce Development (2000).

Table 3.11 summarizes the 1998 household income levels reported by the mail survey

respondents. The median household income is in the $40,000 to $49,999 bracket. We compute

the population median income as approximately $43,000 based on Census data.3 These figures

are for the same variable and the results are very comparable and do not suggest any source for

substantive sampling and nonresponse bias.

 

3. Specifically, we computed the median household income for each county based on 1995 Census data

(U.S. Census Bureau, 1998), escalated by the CPI from 1995 to 1998 dollars (1.0696), and weighed the county

estimates by county population to compute a 10 county median.
Stratus Consulting Survey Implementation (Final, 10/25/00)

Page 3-13

Table 3.11. Household income.

Mail survey income categories % of survey respondents (omitting missing)a

Less than $10,000 4.5%

$10,000 to $19,999 11.8%

$20,000 to $29,999 12.9%

$30,000 to $39,999 15.6%

$40,000 to $49,999 14.5%

$50,000 to $59,999 10.7%

$60,000 to $79,999 16.5%

$80,000 to $99,999 6.3%

$100,000 to $149,999 3.8%

$150,000 or more 3.3%

10 county sample median

10 county Census medianb

$40,000 to $49,999

about $43,000

a. 4.7% missing. Percents may not total 100% due to rounding.

b. Based on 1995 median household income by county (U.S. Census Bureau, 1998), inflated to

1998 with the CPI, and weighted by county population.

3.4 Summary

The above evaluation indicates that any sampling and nonresponse biases will have limited

impact on the assessment. First, the differences between the measurable sample and population

characteristics are generally small, and these differences are not associated with strong

influences on the assessment. Second, the high sample coverage rates and response rates reduce

the potential for these biases and reduce the influence of these biases, if any, on the overall

assessment. Finally, the influence of any potential sampling and nonresponse bias is further

minimized in the scaling of restoration because the potential biases typically would be in the

same direction for all of the resource programs. Thus some of the potential bias may largely

cancel out when computing the scale of restoration of equivalent value to PCB losses.
4. Survey Results

4.1 Introduction

This chapter provides results on respondent activities, attitudes, awareness, and evaluations of

the four natural resource topics and programs. Responses to choice Questions 13 through 18 are

addressed in Section 4.6 and in Chapter 5. Responses to sociodemographic questions were

summarized in Section 3.3 (see also Appendix C).

A respondent’s awareness of the four natural resource topics before receiving the survey (from

Question 22) is found to be an important indicator of responses to opinion and attitude questions

(reported in this chapter), and to preferences and values for natural resource restoration options

(as reported in the next chapter). We begin by reporting on respondent awareness of the four

topics, and note throughout the presentation how the results are related to respondent awareness.

Then, we report the results on respondent activity levels in potentially related recreation, and

respondents’ ratings of the importance of natural resource topics. We conclude by simple

evaluations of the choice pair results that do not require models such as used in Chapter 5.

4.2 Topic Awareness

Question 22 asked respondents, “Prior to receiving this survey, how aware were you of each of

the four natural resource topics we addressed?” Each topic was rated from 1 = “I was not aware

of this topic” to 5 = “I was very aware of this topic.” Respondents with more awareness, or

familiarity, generally have more crystallized attitudes and values regarding the natural resource,

and thus responses may have greater validity and accuracy. Increased awareness probably

reflects respondents’ interests, and in general increased awareness may be associated with

increased preferences for natural resource enhancements.

Results for the awareness question are presented in Table 4.1. These results indicate that

respondents have a moderate to high level of awareness of the topics, especially of PCBs:

approximately 70% of respondents report awareness scores of 4 or 5 for PCBs, and over 90%

reporting scores of 3 or greater. For the other three topics, about 45% to 50% report scores of

4 or 5, and over 80% report scores of 3 or greater. Topic awareness is correlated with

participation in recreational activities, especially fishing in the waters of Green Bay, and with

several sociodemographic variables (Table 4.2). Awareness is also highly correlated with several

policy variables and with responses to questions in which respondents evaluate their own

responses to the program choice questions (discussed below).
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-2

Table 4.1. Awareness of natural resource topics before receiving the surveya (Question 22:

1 = was not aware of this topic to 5 = very aware of this topic).

Net of missing

Natural

resource

topic

Not at all

aware

1 2

Somewhat

aware

3 4

Very

aware

5 Missing

Number of

observations

Mean

awareness

rating SE

Wetlands 8.7% 9.8% 36.6% 24.7% 20.0% 0.2% 469 3.4 0.05

PCBs 4.3% 2.6% 21.7% 29.2% 40.6% 1.7% 462 4.0 0.05

Outdoor

recreation 6.4% 12.6% 35.1% 25.3% 19.4% 1.3% 464 3.4 0.05

Runoff 7.9% 10.9% 30.0% 27.5% 22.6% 1.3% 464 3.5 0.06

a. Totals may not sum to 100% because of rounding.

4.3 Outdoor Recreational Activity in and around the Waters of

Green Bay Area

Question 1 examines the level of outdoor recreation participation for many activities on the

waters and shoreline of the Bay of Green Bay. It reiterates the geographic focus of the survey,

motivates respondents to think about if and how the natural resource enhancements might affect

them, and provides potentially useful explanatory variables for evaluation of subsequent

responses, such as the types and levels of recreational activity. Question 1 is not intended to

provide precise estimates, but indicators of relative activity levels across respondents.

The most popular outdoor activities are ones that do not require a lot of equipment or time, such

as enjoying outdoor scenery, viewing wildlife, camping or picnicking, and hiking, walking, or

jogging. More than 50% of respondents report participating in those activities at least once a

year. Other activities have smaller groups of avid participants, but more than 50% of respondents

never participate or participate less than once a year. Fishing, biking, swimming, and boating

attract about 40% of the respondents at least once a year. The least popular activities are

waterskiing or jetskiing, and canoeing or kayaking; only about 12% indicated they do these

activities at least once a year. Hunting is also a less common activity, with only 26%

participating at least once a year.

Proximity to the Bay of Green Bay influences participation. As would be expected, respondents

who live closer to the bay participate more frequently in many of the activities on the bay

(Table 4.3). The only activities that did not show a significant difference in participation by those

who live near Green Bay (about 50% live within 8.8 miles) and those who live farther away

(more than 8.8 miles, but still within the 10 neighboring counties) were camping or picnicking,

fishing, hunting, and canoeing or kayaking.
Stratus Consulting Survey 

Page 4-3

Table 4.2. Correlations between topic awareness (Question 22) and other variables.

Natural resource topic awarenessa Correlation

variables Wetlands PCBs Outdoor recreation Recreationvariables

Question 1 noneb

Question 23 fish Green Bay

Question 1 fishing, boating,skiing, canoeing, swimming,hunting, hiking/walking,hunting, wildlife viewing,enjoying sceneryQuestion 23 fish Green Bay

Question 1 enjoying scenery,boating, skiing, swimming, wildlifeviewing, hiking/walking, canoeing,hunting, bikingQuestion 23 fish Green Bay

QuesQues

Policyvariables

Question 2 wetland acresQuestion 6 PCB spending

Question 2 wetland acresQuestion 4 PCBs FCAs

Question 2 wetland acresQuestion 6 PCB spendingQuestion 7 enhance facilitiesQuestion 8 add facilities

QuesQuesQues

Evaluationvariables

Question 19 wetlands,algae, costsQuestion 20 confidenceQuestion 21 use of resultsQuestion 22 awareness —all issuesMade a comment

Question 19 wetlands, PCBsQuestion 20 confidenceQuestion 21 use of resultsQuestion 22 awareness — allissuesMade a comment

Question 19 wetlands, enhancefacilities, new parks, excess algaeQuestion 20 confidenceQuestion 21 use of resultsQuestion 22 awareness — all

issuesMade a comment

QuesPCBsclaritQuesQuesQuesall issMade 

Sociodemographicvariables

Question 24 own residenceQuestion 26 maleQuestion 34 ethnicbackground

Question 24 own residenceQuestion 26 maleQuestion 28 # in household

Question 26 male

QuesQuesQues

a. Bold = correlation at 99% confidence or higher, italics = correlation at 95% to 99% confidence, regular = correlation at 90% t

b. Correlated with “enjoying outdoor scenery” at 10.4% level.
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-4

Table 4.3. Average participation levela in outdoor activities on the waters and shorelines of

the Bay of Green Bay by distance of residence to Green Bay (Question 1).

Location of

residence

Enjoying outdoorsceneryWildlife viewingHiking, walking, orjoggingCamping orpicnickingFishingBikingSwimmingBoating(nonfishing)HuntingCanoeing orkayakingWaterskiing orjetskiing

Mean 3.04d 2.49d 2.41d 1.92 1.81 1.83d 1.79d 1.70d 1.50 1.22 1.21d

SE 0.065 0.072 0.077 0.063 0.065 0.074 0.067 0.058 0.062 0.038 0.038

Near Green

Bayb

Nobs 232 229 229 222 229 225 223 222 221 217 218

Mean 2.73d 2.22d 2.23d 1.87 1.76 1.55d 1.54d 1.45d 1.51 1.17 1.13d

SE 0.077 0.076 0.082 0.066 0.073 0.063 0.058 0.051 0.066 0.036 0.033

Farther from

Green Bayc

Nobs 212 213 209 209 217 207 210 209 210 206 205

Mean 2.89 2.36 2.32 1.90 1.78 1.69 1.67 1.58 1.50 1.20 1.17

SE 0.051 0.053 0.056 0.046 0.048 0.049 0.045 0.039 0.045 0.026 0.025

All

respondents

Nobs 444 442 438 431 446 432 433 431 431 423 423

Nobs = Number of observations.

a. Where 1 = less than once a year or never, 2 = 1 to 5 times a year, 3 = 6 to 10 times a year, and 4 = more than

10 times a year.

b. Respondents are near Green Bay if their residence is less than 8.8 miles from Green Bay (about half the

respondents).

c. Respondents are farther from Green Bay if their residence is 8.8 miles or more from Green Bay (about half

the respondents).

d. Indicates activity level of those who live near Green Bay is significantly different from those who live farther

from Green Bay at the 95% level.

Those who were very aware of the natural resource topics addressed in the survey tended to be

more avid participants in recreational activities in the Green Bay area than those who were only

somewhat or not at all aware. Table 4.4 shows the mean activity levels for respondents who

indicated that they were more aware of all the natural resource programs presented (i.e., a rating

of 4 or 5 in Question 22 for all four issues) and for those respondents who indicated they were

less aware of the natural resource programs presented (i.e., a rating of 1, 2, or 3 in Question 22

for all four issues). The only activity that did not have a statistically significant difference in

participation levels between more aware and less aware respondents was waterskiing or

jetskiing. For all other activities named in Question 1, the respondents who were more aware of
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-5

Table 4.4. Participation level by awareness of issue (Question 1 by Question 22).

Activity

Awareness

level

Number of

observations

Mean frequency of

activityc SE

less awarea 86 1.52d Fishing 0.093

more aware

b 112 1.93d 0.101

less awarea 83 1.45d Boating (nonfishing) 0.084

more aware

b 106 1.76d 0.086

less awarea Waterskiing or jetskiing 83 1.12 0.049

more aware

b 100 1.21 0.052

less awarea 82 1.09d Canoeing or kayaking 0.036

more aware

b 104 1.38d 0.070

less awarea 83 1.49d Swimming 0.079

more aware

b 107 1.80d 0.105

less awarea 84 1.31d Hunting 0.079

more aware

b 104 1.66d 0.101

less awarea 84 1.96d Wildlife viewing 0.104

more aware

b 111 2.77d 0.108

less awarea 85 2.49d Enjoying outdoor scenery 0.111

more aware

b 110 3.21d 0.096

less awarea 81 1.73d Camping or picnicking 0.102

more aware

b 107 1.99d 0.092

less awarea 82 1.54d Biking 0.095

more aware

b 108 1.86d 0.104

less awarea 85 2.11d Hiking, walking, or jogging 0.125

more aware

b 109 2.53d 0.115

a. In Question 22 for each of the four natural resource topics, respondent indicated a 1, 2, 3 for how aware they

were of the topic before receiving the survey (1 = not at all aware, 3 = somewhat aware, 5 = very aware).

b. In Question 22 for each of the four natural resource topics, respondent indicated a 4 or 5 for how aware they

were of the topic before receiving the survey (1 = not at all aware, 3 = somewhat aware, 5 = very aware).

c. 1 = less than once a year or never, 2 = 1 to 5 times a year, 3 = 6 to 10 times a year, 4 = more than 10 times

a year.

d. Indicates activity level of those who are more aware is significantly different from those who are less aware

at the 95% level.

the natural resource programs in the region were also more avid participants. This result is

intuitive: people who use the resource are more aware of topics related to the resource.

Question 23 asks how many days the respondent fished in the last 12 months. The intent of this

question was to obtain an indication of interest in Green Bay fishing for respondent households

rather than a precise estimate of participation in the sample counties, which is available

elsewhere (Breffle et al., 1999). The Green Bay fishing participation rate reported in Question 23

is about 30.4%, and just over double the participation rates determined in Breffle et al. (1999).

Two reasons explain this result. First, the sample is weighted to more heavily sample
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-6

respondents in counties adjacent to Green Bay, who would fish these waters more often

(Stratum 1, see Section 3.1). Reweighting the results to the population in the 10 study counties

results in an estimate of about 26.5%. Second, because this question asks for one year recall, we

can expect some telescoping in the response, e.g., respondents who fished in the prior year, but

not the last 12 months, may report the event in the past 12 months because of telescoping and/or

to indicate they generally fish the site (Westat, 1989; Tourangeau et al., 2000).

Question 23 also asked for the number of days fished in the waters of Green Bay by those who

had fished on Green Bay. These anglers reported fishing Green Bay an average of 10.5 days

(SE = 1.14) in the prior 12 months. This level is similar to that found in Breffle et al. (1999),

where anglers who fished Green Bay reported fishing 9.95 days (SE = 0.55) per year. In both

instances the anglers were asked to recall their fishing activities over a 12 month period, which

may be subject to recall bias. A discussion of potential biases and adjustments for bias can be

found in Breffle et al. (1999, pp. 3-29 to 3-32). With adjustments for recall bias, it was estimated

that anglers in the 1999 study had spent an average of 6.19 days of open water plus ice fishing

the Bay of Green Bay in that 12 month period.

4.4 Importance and Action Scores

Questions 2 through 12 are part of the presentation of the four natural resource topics considered

in this survey. Each presentation has a description of the current state of the resource followed by

one or two importance questions and then one action question. The importance questions ask

how important the benefits from potential programs are to the respondent. The action questions

ask whether the respondent feels that less, the same, or more should be done and spent on each of

these topics.

4.4.1 Benefits importance scores

Respondents were asked to rate the importance of the environmental and human use service flow

benefits for each of the four general programs (Question 2 for wetlands, Questions 4, 5 for PCBs,

Questions 7, 8 for outdoor recreation, Questions 10, 11 for runoff). Table 4.5 shows the ratings

of the importance questions. From the responses we see that residents of this area are concerned

about natural resource issues in and around Green Bay. Of the four programs considered,

removing PCBs is rated most important (with statistical significance), reducing runoff and

increasing wetlands are next (their ratings are not significantly different from each other at the

95% level), and improving outdoor recreation is rated least important (with statistical

significance).
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-7

Table 4.5. Importance of all natural resource action benefits (Questions 2, 4, 5, 7, 8,

10, 11: 1 = not at all important to 5 = very important).

Net of missing/don’t know

Benefitsa

Number of

observations

Mean

importance

rating SE

Don’t

know Missing

Remove PCBs so that it is safe to eat fish and

waterfowl (Question 4) 458 4.3 0.05 1.7% 0.9%

Remove PCBs to reduce risks to birds, fish

and other wildlife (Question 5) 462 4.3 0.05 1.3% 0.4%

Reduce runoff to improve water clarity

(Question 11) 461 4.0 0.05 1.9% 0.0%

Increase wetland acreage to support birds, fish

and other wildlife (Question 2) 460 3.9 0.05 1.7% 0.4%

Reduce runoff to reduce algae blooms

(Question 10) 457 3.8 0.05 2.8% 0.0%

Add facilities at existing parks (Question 7) 467 3.6 0.05 0.6% 0.0%

Add new parks (Question 8) 466 3.3 0.06 0.9% 0.0%

a. Listed in order of mean importance, not in the order they appeared in the survey.

Respondents’ levels of awareness of the different resource topics before receiving the survey

often affects their benefits importance scores. Those who are more aware had higher benefits

importance scores for each of the natural resource topics than those who are less aware

(Table 4.6). Benefits from removing PCBs are rated on average as 4.3 on the 5 point scale by all

those who are more aware of any individual topic, and 4.1 to 4.2 by those who were less aware

of individual topics. Outdoor recreation parks and facilities receive the highest scores from those

who are more aware of outdoor recreation in the area, but they still have the lowest action score

even by this group.

While scores change with awareness, the rankings of the different benefits from natural resource

actions remain nearly the same. Removing PCBs always rank first, and enhancing outdoor

recreation (adding facilities or new parks) always rank last. The only difference is that the

rankings of wetlands programs and runoff programs sometimes switch, although the difference

in scores generally are not large.

Thus, while awareness is correlated with benefit importance scores (higher awareness scores

generally resulting in somewhat higher benefit importance scores), awareness has a relatively

limited impact on the average rankings across the four programs (e.g., PCBs always ranked first

and outdoor recreation always ranked last).
Stratus Consulting Survey 

Page 4-8

Table 4.6. Mean (SE) importance of all natural resource action benefits by awareness of issues (Questions 1 = not at all important to 5 = very important).

Natural resourceaction benefitsa

More

aware

alla

Less

aware

alla

More

aware

wetlandsb

Less

aware

wetlandsb

More

aware

PCBsb

Less

aware

PCBsb

More

aware

recreationb

Less

aware

recreatio

Number of observations 117 92 210 258 327 140 209 259 Remove PCBs so that it is safeto eat fish and waterfowl(Question 4)

4.4

(0.10)

4.0

(0.13)

4.3

(0.07)

4.2

(0.07)

4.3

(0.06)

4.1

(0.10)

4.3

(0.07)

4.2

(0.07)

Remove PCBs to reduce risksto birds, fish, and otherwildlife (Question 5)

4.4

(0.10)

4.0

(0.13)

4.3

(0.07)

4.2

(0.07)

4.3

(0.06)

4.2

(0.09)

4.3

(0.07)

4.2

(0.07)

Reduce runoff to improvewater clarity (Question 11)

4.1

(0.10)

3.8

(0.11)

4.1

(0.07)

3.9

(0.06)

4.0

(0.06)

3.9

(0.09)

4.0

(0.07)

3.9

(0.06)

Increase wetland acreage tosupport birds, fish, and otherwildlife (Question 2)

4.3

(0.11)

3.5

(0.13)

4.3

(0.08)

3.6

(0.07)

4.1

(0.06)

3.7

(0.10)

4.1

(0.08)

3.8

(0.08)

Reduce runoff to reduce algaeblooms(Question 10)

4.0

(0.10)

3.6

(0.12)

3.9

(0.08)

3.7

(0.07)

3.8

(0.06)

3.7

(0.09)

3.9

(0.07)

3.7

(0.07)

Add facilities at existing parks(Question 7)

3.7

(0.12)

3.5

(0.12)

3.6

(0.08)

3.6

(0.07)

3.6

(0.06)

3.7

(0.09)

3.8

(0.08)

3.4

(0.07)

Add new parks(Question 8)

3.5

(0.12)

3.2

(0.14)

3.3

(0.09)

3.3

(0.07)

3.3

(0.07)

3.3

(0.11)

3.6

(0.09)

3.1

(0.07)

a. If respondents chose 4 or 5 for awareness of all four topics in Question 22, they fall in the “more aware all” category. If responall four topics in Question 22, they fall in the “less aware all” category.b. If respondents chose 4 or 5 for awareness of the topic in Question 22, they fall in the “more aware topic” category, otherwise taware topic” category.
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-9

4.4.2 Action scores

Action scores refers to the questions about whether respondents prefer doing and spending less,

the same, or more than currently occurs for each resource topic (Question 3, Question 6,

Question 9, Question 12). Table 4.7 shows the level of action respondents would like to see

implemented to improve these resources. The greatest support is for actions to remove PCBs,

there is moderate support for wetlands and runoff programs, and the lowest support is for actions

to improve outdoor recreation. Respondents who are more aware tend to want more done and

spent than respondents who are less aware of the resource topic, except for PCBs, where even

respondents who indicated they were less aware also feel it is important to do more and spend

more.

Table 4.7. Preferred level of action for natural resource programs (Questions 3, 6, 9, 12).

Natural resource programa

Do less and

spend less

Do the

same

Do more and

spend more Missingd

All NAc 16.4% 81.3% 2.3%

More aware of PCBsb NA 16.2% 81.7% 2.1%

PCB investigations and

removal (Question 6)

Less aware of PCBsb NA 16.9% 80.3% 2.8%

All 1.5% 33.4% 63.6% 1.5%

More aware of runoffb 0.9% 23.8% 74.5% 0.8%

Runoff reduction

(Question 12)

Less aware of runoffb 2.1% 43.0% 52.8% 2.1%

All 2.6% 40.9% 54.7% 1.9%

More aware of wetlandsb 1.9% 26.7% 70.0% 1.4%

Wetlands maintenance and/or

restoration (Question 3)

Less aware of wetlandsb 3.1% 52.3% 42.3% 2.3%

All 1.9% 50.9% 46.8% 0.4%

More aware of recreationb 1.9% 40.0% 58.1% 0.0%

New facilities at existing parks

and/or opening new parks

(Question 9) Less aware of recreationb 1.9% 59.6% 37.7% 0.8%

a. Listed in order of preference for more action, not in the order they appeared in the survey.

b. If respondents chose 4 or 5 for awareness of the topic in Question 22, they fall in the “more aware of topic”

category, otherwise they are in the “less aware of topic” category.

c. Not applicable: “Do less and spend less” was not offered an option for PCBs, as discussed in Section 2.2.2.

d. Percentage may not total to 100% because of rounding.

These measures are correlated with the benefits importance scores. For instance, in Table 4.5 we

see that removing PCBs receives the highest importance rating of all the issues, and in Table 4.7

we see that most respondents would like to see more done and more spent to remove the PCBs.
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-10

4.5 Evaluation Scores

This section provides results for Questions 19 through 21, to which respondents provide followup evaluation of their own responses to the choice questions, Question 13 through Question 18.

Question 19 is again asking about the importance of various natural resource program benefits,

but the context is slightly different. Here the question relates to the tradeoffs that respondents

made in the set of choice questions. In these tradeoffs the respondent is constrained by the cost of

the sets of programs. The cost is an important factor for respondents (rated second to PCB

removal) and as such has an effect on the ratings of all the programs. Comparing results reported

in Table 4.5 to those in Table 4.8, we see that adding a monetary dimension reduces the average

rating of each of the issues, but does not change their relative ranking.

Table 4.8. Importance of program attributes in making choices between alternatives

(Question 19: 1 = not at all important to 5 = very important).

Net of missing

Program attributea

Number of

observations

Mean importance

rating SE Missing

Years until safe levels of PCBs 468 3.9 0.05 0.4%

Annual cost to your household 466 3.8 0.05 0.9%

Inches of water clarity 465 3.5 0.05 1.1%

Days of excess algae each summer 467 3.3 0.05 0.6%

Acres of wetlands 468 3.3 0.05 0.4%

Facilities at existing parks 464 3.1 0.05 1.3%

Acres of new parks 466 2.9 0.06 0.9%

a. Listed in order of mean importance, not in the order they appeared in the survey.

For example, PCB removal remains the most important action, but while the benefits of PCB

removal are rated an average of 4.3 on a scale of 5 (1 = not at all important, 5 = very important)

with no consideration of cost, they are rated an average of 3.9 on the same scale when a

monetary constraint is introduced. Cost is the next most important consideration. Recreation

remains the lowest ranked resource topic. In the benefits importance questions, adding facilities

was rated 3.6 and new parks 3.3, but with the addition of a monetary constraint in Question 19,

they are rated 3.1 and 2.9 on a scale of 1 to 5.

In their responses to Question 19, the more aware and less aware groups have the same relative

rankings for the benefits of natural resource programs that we saw in the benefits importance

scores (Table 4.6). When the benefits of the resource programs are ranked along with cost in
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-11

Question 19, cost is ranked the most important factor for those who are less aware of all of the

topics and the second most important factor (after PCBs) for those who are more aware of all the

topics, suggesting that values will be lower for those who are less aware than for those who are

more aware.

Questions 20 and 21 provide two perspectives on respondents’ evaluations of their responses to

the choice questions, and these are summarized in Tables 4.9 and 4.10. Question 20 asks

respondents to consider their confidence in their choices between the alternatives in Questions 13

through 18. Question 21 takes a pragmatic perspective and tells the respondent to consider that

“Questions 13 to 18 were asked to provide citizen input for decisions makers to consider along

with scientists and planners,” and then asks, “With this in mind how much should public officials

consider your responses to Questions 13 through 18?”

Table 4.9. Confidence in choices between alternatives (Question 20: 1 = not at all

confident to 5 = very confident).

Net of missing

Categorya

Not at all

confident

1 2

Somewhat

confident

3 4

Very

confident

5 Missing Nobs

Mean

confidence

rating SE

All 1.3% 4.9% 40.0% 37.9% 15.5% 0.4% 468 3.6 0.04

More aware 0.9% 3.4% 23.9% 46.2% 24.8% 0.9% 116 3.9 0.08

Less aware 2.2% 12.9% 49.5% 29.0% 6.5% 0% 93 3.2 0.09

Nobs = Number of observations.

a. If respondents chose 4 or 5 for awareness of all four topics in Question 22, they fall in the “more aware”

category. If respondents chose 1, 2 or 3 for all four topics in Question 22, they fall in the “less aware”

category.

Respondents were generally confident about the choices in the paired comparison questions:

93% indicated they were somewhat to very confident in the choices they made. And 95% felt

that their responses should be somewhat or completely considered (along with other information

from scientists and planners) in decisions made by public officials concerning these natural

resource issues. Respondents who were more aware of the natural resource issues before

receiving the survey tended to be more confident in their answers and more certain that their

responses to the choice questions should be considered by public officials. Most all of those who

are least confident in their responses (value = 1 or 2 in both Question 20 and Question 21) are

individuals with lower awareness for several or all of the response topics and who report lower

preference for, and values for, the restoration programs.
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-12

Table 4.10. Extent to which public officials should consider your responses to choice

questions (Question 21: 1 = should not consider my responses at all to 5 = should

completely consider my responses).

Net of missing

Categorya

Should not

consider my

responses

at all

1 2

Should

somewhat

consider my

responses

3 4

Should

completely

consider my

responses

5 Missing Nobs

Mean

confidence

rating SE

All 0.6% 3.4% 27.2% 39.4% 28.9% 0.4% 468 3.9 0.04

More aware 0.0% 0.9% 11.1% 42.7% 44.4% 0.0% 116 4.3 0.07

Less aware 1.1% 12.9% 40.9% 29.0% 16.1% 0% 93 3.5 0.10

Nobs = Number of observations.

a. If respondent chose 4 or 5 for awareness of all four topics in Question 22, they fall in the “more aware”

category. If respondent chose 1, 2 or 3 for all four topics in Question 22, they fall in the “less aware”

category.

4.6 Comments

In response to Question 36, 125 (27%) of the respondents provided written comments on the

survey. Table 4.11 provides a summary of their 181 comments. A total of 37 respondents (7.9%

of all respondents) made one or more comments that might indicate scenario rejection.1

When considering the impact of potential scenario rejection on the scaling of restoration to be of

equivalent value to PCB-caused service flow losses, what would matter is if there were a

disproportionate level of rejection tied to PCBs versus the other topics. This is in fact the case. A

total of 29 respondents made comments suggesting potential rejection of paying for PCB

removal, 4 respondents made comments suggesting potential rejection of paying for runoff

programs, 3 respondents made comments suggesting potential rejection of paying for outdoor

recreation programs, and 6 respondents made comments suggesting potential rejection of

implementing it through the government bureaucracy. Thus, this suggests that a bias, if any,

would be toward understating the required level of restoration to be of equivalent value to PCBcaused service flow losses.

 

1. Scenario rejection occurs when an individual’s preference statement does not reflect his value for a

commodity but rather is in response to some component of the choice pair scenario, such as the payment

vehicle or the timing of commodity provision.
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-13

Table 4.11. General comments made at end of survey, coded into categories.

Comment

numbera Comment category

Number

making

commentb

Percent of

those with

comments

Percent

of all

respondents

11 Industry should pay / is liable for PCBs 21 16.8% 4.5%

12 Farmers should pay for runoff 4 3.2% 0.9%

13 User should pay 3 2.4% 0.6%

14 Use other funding source / taxes already too high 5 4.0% 1.1%

15 Bureaucracy / government wastes money 6 4.8% 1.3%

16 Amount must be reasonable / don’t raise it too much 4 3.2% 0.9%

23 PCB removal is very important 11 8.8% 2.3%

24 Concerns about PCB removal — process, efficiency,

effectiveness

11 8.8% 2.3%

25 Quit fishing because of PCBs / want safer fish 7 5.6% 1.5%

30 Parks — general 1 0.8% 0.2%

31 Need more info about parks 1 0.8% 0.2%

33 Improve current parks / stop decline / current

conditions poor

6 4.8% 1.3%

34 Don’t expand / add facilities / add more parks 2 1.6% 0.4%

35 I don’t use parks 1 0.8% 0.2%

36 I do use, or have used parks 2 1.6% 0.4%

40 Wetlands — general 2 1.6% 0.4%

41 Need more info about wetlands 2 1.6% 0.4%

42 Wetlands are important for future generations 1 0.8% 0.2%

43 Wetlands are a very important resource 8 6.4% 1.7%

44 Don’t spend more on wetlands 1 0.8% 0.2%

50 Runoff — general 1 0.8% 0.2%

51 Need more info about runoff 1 0.8% 0.2%

53 Runoff is an important issue 1 0.8% 0.2%

60 Survey issues — general 3 2.4% 0.6%

61 Support for survey (compliment, thanks) 19 15.2% 4.0%

62 Survey biased 6 4.8% 1.3%

63 Didn’t like tradeoffs (wanted a spend no more option,

didn’t want to trade recreation for environment)

3 2.4% 0.6%

70 Other — general 11 8.8% 2.3%

71 Mention other environmental issues 22 17.6% 4.7%

72 Enforce current regulations 6 4.8% 1.3%

73 Environment is important / general support for

environment

9 7.2% 1.9%

a. Comment number as coded.

b. Sum is greater than 125 because some respondents brought up several topics in their comments.
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-14

4.7 Choice Pair Evaluation Using Simple Comparisons

In Chapter 5 we apply a sophisticated statistical model to evaluate the responses to the choice

questions accounting for characteristics of the respondents. However, simple evaluations of a

subset of the choice pairs provide straightforward insight into respondent preferences and into

whether respondents are responsive to the natural resource changes being presented. These

simple comparisons are based on the percentage of respondents to a choice pair that selects one

or the other of the two alternatives in the choice pair. They do not consider respondent

characteristics and are based on small sample sizes.

Table 4.12 summarizes the eight simple resource-to-resource pairs (i.e., costs are held constant

across the two alternatives) involving PCB removal, measured as years until safe levels of PCBs

are reached, versus other enhancements in one of the other three resource programs. The table

lists the version and question number (e.g., the pair of alternatives) and sample size, the change

in years until PCBs are safe and the changes in the other resource topics that are compared in the

two alternatives, the dollar amount that was held constant in both alternatives, and the percent

choosing the alternative with fewer years until PCBs are at safe levels.

Table 4.12. Pairs with PCB removal versus other single resource programs.

V#/Q#a

Number of

observations

Years until

PCB levels are

safe Versus

Fixed $

value

Percent

choosing

reduced

PCBs

9/13 48 100 to 70 years Runoff: 0% to 25% control $25 57%

9/17 49 100 to 70 years Wetlands: 0% to 10% increase in acres $25 76%b

10/13 40 100 to 40 years Runoff: 0% to 50% control $50 58%

8/13 44 100 to 40 years Wetlands: 0% to 20% increase in acres $50 69%b

6/13 32 100 to 20 years Wetlands: 0% to 20% increase in acres $50 82%b

3/16 42 70 to 40 years Parks: 0% to 5% increase in new acres

and 0% to 10% enhancements at

existing parks

$100 69%b

10/17 48 70 to 20 years Recreation: 0% to 10% enhancements

at existing parks

$50 92%b

5/15 50 40 to 20 years Recreation: 0% to 10% enhancements

at existing parks

$50 60%

a. V# =Version number, Q# = question.

b. Statistically significant at 10% or higher levels.

The results in Table 4.12 highlight a consistent preference for PCB removal when directly

compared to enhancements in other programs. In each such direct comparison, PCB removal is

preferred. Even with the small sample sizes in the individual choice questions, the preference is

statistically significant at a 10% level for most of the comparisons (falling just short of statistical
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-15

significance in the other cases, which involve either smaller PCB changes and/or runoff control).

For other simple resource-to-resource comparisons, we find certain runoff control programs are

preferred to outdoor recreational enhancements and to certain wetland programs, and statistically

significantly so in three of four such comparisons. These simple comparisons identify that PCB

removal and runoff control are, respectively, the first and second most preferred restoration

actions. These results are consistent with the attitude scores provided earlier in this chapter and

with the model presented in Chapter 5 that incorporate all of the choice pairs and important

respondent attributes (and thus has more statistical power).

Comparing results for choice pairs from different survey versions can be used as “betweensample” tests of if and how respondents respond to changes in the level of resource changes and

costs presented. One would expect that a program providing more benefits (e.g., more acres of

wetlands or less years of PCB contamination) would be valued the same as or more than a

program providing a lesser level of benefits. Such “scope tests” have sometimes been suggested

as a validity test for contingent valuation studies (Carson, 1997). The choices respondents make

indicate that respondents are responding to different levels of natural resource attributes

presented to them — the support for programs varies with the level of change in the program

results.

Table 4.13 compares the results of resource-to-resource choice pairs that provide scope test type

comparisons. Using the first row as an example, pair 5/15 (Version 5, Question 15, which has

50 observations) asks for a choice between a 10% increase in existing recreational facilities

(resource change 1) and reducing the years until PCBs are at safe levels from 40 years to

20 years. In this choice, the dollar cost presented to respondents for both alternatives is the same

at $50. Pair 10/17 calls for a choice between the same change in existing recreational facilities

(10% increase) and reducing the years until PCBs are at safe levels from 70 years to 20 years (in

this question, the cost of both programs was $50). In both choice pairs (5/15 and 10/17), one

resource change was a 10% increase in existing recreational facilities. In the second choice pair

listed, this change in recreation was compared to a larger change in PCBs than in the first choice

pair (70 to 20 years versus 40 to 20 years). One would expect that the preference for the

recreational enhancement in the second pair (10/17) would be less than in the first pair because

the PCB change is even larger, and this is what is found. In this case, the preference for the

recreational enhancement program drops from 40% to 8%, which is a statistically significant

change. The dollar levels are not expected to influence the choices because, except in the seventh
Stratus Consulting Survey 

Page 4-16

Table 4.13. Simple comparison of choice pairs: Resource comparisons.Comparison V#/Q#

Number of

observations Resource change 1 Resource change 2 $

1 5/15

10/17

5048

Rec: 0% to 10% ↑Rec: 0% to 10% ↑

PCBs: 40 to 20 yrsPCBs: 70 to 20 yrs

5050

2 8/13

6/13

4444

Wetland: 0% to 20% ↑Wetland: 0% to 20% ↑

PCBs: 100 to 40 yrs.PCBs: 100 to 20 yrs

5050

3 10/17

5/18

4849

PCBs: 70 to 20 yearsPCBs: 70 to 20 years

Rec: 0% to 10% ↑Rec: 0% to 10% ↑ and

Wetlands: 0% to 10% ↑

5050

4 10/13

1/16

4838

PCBs: 100 to 40 yrsPCBs: 100 to 40 yrs

Rec: 0% to 10% ↑Rec: 0% to 10% ↑ and

Runoff control: 0% to 50% ↑

5050

5 5/15

8/15

5045

PCBs: 40 to 20 yrsPCBs: 40 to 20 yrs

Rec: 0% to 10% ↑Rec: 0% to 10% ↑ and

Wetlands: 0% to 5% ↑

5050

6 9/16 49 PCBs: 40 to 20 yrs Rec: 0% to 10% ↑ and

Runoff control: 0% to 25% ↑

50 

7 2/13

4/15

4847

Wetlands: 0% to 5% ↑

Wetlands: 0% to 5% ↑

Parks: 0% to 5% ↑

Parks: 0% to 10% plus otherimprovements and cost decreases

25

NA

8 5/15

2/17

5048

Rec: 0% to 10% ↑Rec: 0% to 10% ↑

PCBs: 40 to 20 yearsPCBs: 40 to 20 years andWetlands: 10% to 20% ↑

50

100

Notes: V# = version number, Q# = question number. $ = fixed dollar amount in both alternatives of a pair. Pairs are ordered in eaprobability of choosing resource change 1 would be expected to decrease with the second pair compared to the first pair. ↑ = enh

a. Statically significant difference a 10% one-tailed test level.
Stratus Consulting Survey Results (Final, 10/25/00)

Page 4-17

comparison in this table, they are the same for both alternatives in a choice pair, but are

presented for perspective on the questions.2

The remainder of Table 4.13 lists seven additional comparisons (note that 5/15 is compared to

both 8/15 and 9/16). The table is presented so that the expected probability of selecting the

enhancements listed as “resource change 1” as compared to “resource change 2” decreases with

the second pair because the improvements in resource change 2 are larger in the second pair than

in the first pair.3 Limited pairs can be compared in this manner because in many pairs not listed

here some resources or costs increase while other decrease, or the pairs compare increases in one

or many programs with increases in one or many programs. The pairs listed provide comparisons

where the expected change in preferences is clear so long as one assumes zero or increasing

utility with increasing program levels and with decreasing costs.

In all cases in Table 4.13, the results are as expected, and in many cases the differences are

statistically significant. This is important because the sample sizes are small for such betweensample comparisons that do not control for other variables (resident location, awareness, angler).

Given these considerations, the results provide strong evidence for between-sample scope

responsiveness for the accuracy of the resource-to-resource comparison question responses.

Table 4.14 makes similar comparisons using the referendum style questions (Question 14 in all

10 survey versions). Again, in each comparison the data are presented so that the probability of

selecting resource change 1 is expected to be less for the second choice pair than for the first

choice pair. The results here also support that respondents are responding to scope, but in two

comparisons the results do not support expectations. Both cases involve responses to Version 2,

Question 14. The reasons why the results to Version 2, Question 14 provide contradictory results

are unclear, and may be the small sample size and varying sample characteristics. For example,

respondents to Version 2 rated the importance of costs, in Question 19, higher than did

respondents in any other survey version, which is consistent with the results reported in

Table 4.14. Given the sample sizes, respondent characteristics, and other potential influences, are

not controlled in these simple comparisons, it is not surprising or unreasonable that one of the

pairs, and 2 of 14 comparisons in Tables 4.13 and 4.14, would result in unexpected results from

simple comparisons.

 

2. The dollar values are also the same for both choice pairs in most of the comparisons in Table 4.13. In many

utility function specification (e.g., utility linear in program levels and income, utility linear in program levels

and program levels all consistently interacting with income), the dollar level would not affect the choice

between alternatives. Other utility specifications may exist where the dollar value could affect the choice

between alternatives, but the results in Tables 4.12 and 4.13, and in Chapter 5, do not suggest cause for

concern that the dollar levels are substantially, if at all, influencing the preference and scope test conclusions

reported here.

3. The pairs are presented in this manner to facilitate comparisons. Resource change 1 and resource change 2

may be either Alternative A or Alternative B in the actual question.
Stratus Consulting Survey 

Page 4-18

Table 4.14. Simple comparison of choice pairs: Referendum comparisons.

Comparison V#/Q#

Number of

observations Resource change 1

Resource change 2

(or $ cost change) $

% 

c

1 4/14

1/14

4738

PCBs: 100 to 20 yrsPCBs: 100 to 40 yrs

$0 to $200$0 to $200

NANA

2 5/14

1/14

5138

PCBs: 100 to 40 yrsPCBs: 100 to 40 yrs

$0 to $50

$0 to $200

NANA

3 2/14

1/14

4838

PCBs: 100 to 20 yrsPCBs: 100 to 40 yrs

$0 to $50

$0 to $200

NANA

4 2/14

4/14

4847

PCBs: 100 to 20 yrsPCBs: 100 to 20 yrs

$0 to $50

$0 to $200

NANA

5 2/14

5/14

4851

PCBs: 100 to 20 yrsPCBs: 100 to 40 yrs

$0 to $50$0 to $50

NANA

6 9/14

8/14

4945

Parks: 0% to 10% ↑Parks: 0% to 5% ↑

$0 to $50

$0 to $100

NANA

Notes: V# = version number, Q# = question number. $ = fixed dollar amount in both alternatives of a pair. Pairs are ordered in probability of choosing resource change 1 would be expected to decrease with the second pair compared to the first pair. ↑ = en

a = Statically significant difference a 10% one-tailed test level.
5. A Model of Preferences for

Resource Alternatives

5.1 Introduction

In this chapter we present the choice-question model used to estimate preferences for resource

enhancement projects in and around the Bay of Green Bay. This model can be used to examine

how individuals trade off different levels of the four programs, such as wetlands acres and years

until PCBs are at safe levels. It can also show how individuals value changes in program levels

in monetary terms, such as the WTP for program enhancements.

The choice-question model seeks to explain statistically each respondent’s six choices from the

choice pairs as a function of a number of program and individual characteristics. The model

parameters represent a quantitative measure of the relative importance of the program

characteristics in determining the benefits individuals receive from their availability. For

example, the parameter on a variable for the number of years until no PCB-caused losses remain

indicates the decrease in benefits if the number of years increases by that much.

We assume in the model that survey respondents chose the alternative (Alternative A or

Alternative B) in each pair that would provide them with the largest net benefit. The technical

logic of pairwise choice-question models is presented in Appendix B.

Sections 5.2 and 5.3 present variables affecting utility and discuss model features. Section 5.4

constructs the utility function for the natural resource program benefits and discusses the

parameters. Section 5.5 discusses the computation of WTP for environmental changes;

Section 5.6 describes the estimation method; and Section 5.7 presents the estimated parameters

and assesses model performance.

5.2 Factors Affecting Utility from Green Bay Resources

Our choice questions are “binary” choices (i.e., they are choices between two alternatives).

Economists assume respondents choose one of the alternatives over the other because the

respondents believe that they would receive more satisfaction, or “utility,” from the chosen

alternative than from the rejected one. To analyze the survey responses, it is necessary to assume

that the “utility function” takes on a specific mathematical form. Utility is assumed to be a

function of the characteristics of the alternatives. Here we followed the common practice of
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-2

assuming that utility is a linear function of the utility parameters as shown in Equation B-1 of

Appendix B.

In our choice pairs, the levels of the characteristics take on a limited number of discrete values

(see Table 2.4). For example, the number of years until no PCB-caused losses remain takes on a

value of 100, 70, 40, or 20; wetlands variables also take on four values. Rather than assume that

these variables are continuous variables, and then impose a functional form on the data, we have

chosen to treat each of the resource levels as separate “dummy variables,” which take on a value

of one if a particular resource level occurs in the choice alternative, and zero otherwise. This

method allows the greatest degree of flexibility in the model because the utility from each level

of a characteristic is estimated independently from other levels. Therefore, the model is not linear

in the characteristics; that is, marginal utilities (benefits) for increasing amounts of a type of

resource action are not constant. There are 11 different dummy variables for the five resource

groups (not counting the base case in each group that does not have a dummy variable, for

identification of the model). The cost of the alternative is also a determinant of utility.1

The model also incorporates preference heterogeneity; that is, marginal utilities for changes in

characteristics are allowed to vary over different types of people. Preferences typically vary

across individuals, although assuming preferences are the same across individuals is a common

assumption in models of this kind. The classic way of including heterogeneity is to let effects on

utility from changes in site characteristics vary as a function of individual socioeconomic and

demographic characteristics. This traditional method, which we use in this study, has been

employed for many years, and a summary discussion can be found in Pollack and Wales (1992).

To reduce greatly the number of parameters introduced into the model by incorporating

preference heterogeneity, a restriction was imposed to add structure within each resource group.

As noted above, for example, the model contains three dummy variables for four PCB

characteristics.2 It is assumed that the set of PCB parameters, or parameters for any of the other

resource groups, varies across different types of respondents proportionately. For example, the

PCB parameters for anglers (based on Question 23) are all higher than for non-anglers by the

same percentage.

 

1. Because our model is linear in income, it does not have income effects, and the income variable does not

affect estimation. When computing the utility difference between the alternatives, income drops out when

utility from one alternative is subtracted from utility in the other alternative, because income is the same in

both.

2. The fourth level serves as the current level and thus does not require a dummy variable. Its utility is simply

the level of utility when the other three dummy variables are set at zero.
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-3

Recreational anglers and those living close to Green Bay are allowed to have different

preferences for reductions in PCB years. Further, those who have a high self-reported level of

awareness for a given resource group are allowed to have different preferences for that particular

resource group than those less aware.3 Prior respondent experience with environmental

commodities tends to increase values, which should be addressed in the econometric model, and

awareness is an effective means to proxy that experience (see Cameron and Englin, 1997). The

awareness variable is an index or conglomeration reflecting past experience and behavior as well

as exogenous characteristics of the individual, as discussed in Chapter 4. Including awareness

also captures respondent confidence in their reported results (Section 4.5).

In preliminary analyses, other individual-specific variables including gender and involvement in

other types of recreation, were found not to be statistically significant. Any variables found not

to be significant were omitted from the final specification of the model to: 1) increase the

accuracy (efficiency) of the estimates by reducing unnecessary noise, and 2) make the estimated

model parameters more straightforward to interpret by removing needless complications.

5.3 Other Model Features

5.3.1 Positioning effects

Positioning effects occur when respondents have a tendency to choose one of the alternatives

(usually the first one, Alternative A in this case) more frequently than the other after controlling

for all other relevant variables (here, the six attributes). Positioning may occur because the

survey process may be difficult or tiring for some individuals, or their preferences for the

resource program may not be well defined. In such cases, respondents may tend to select the first

alternative repeatedly to reduce their cognitive burden. In the final sample of 470 respondents,

32 chose Alternative A in all six choices and 8 chose Alternative B in all choices. To evaluate

the impact of positioning effects on our results, if any, a dummy variable equal to one was

included for A alternatives.

5.3.2 Varying difficulty of choice

Using randomly generated levels of changes in natural resource programs will result in many, or

even most, pairs involving varying levels for multiple programs in each choice pair. Thus,

respondents would be presented with the challenging task of comprehending multiple changes

 

3. Awareness interactions were included for all resource groups except new parks, because that resource action

was not found to yield significantly positive benefits in preliminary specifications.
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-4

each time they compare a pair of alternatives. The choice task may be daunting for some

respondents and, if so, they may tend to focus only on a subset of the characteristics as the basis

for decision-making, thus increasing the variance in the parameter estimates.

The choice pairs throughout the 10 different versions of the survey were designed to be of

distinctly different types, some which may be more difficult for respondents to rank than others.

These are described in detail in Section 2.2.3:

} Simple resource-to-resource pairs: These choice questions present a simple one resource

versus one resource tradeoff: for example, an improvement in wetlands in one alternative

versus an improvement in recreational facilities in the second alternative, with the levels

of other programs and taxes paid the same in both alternatives.

} Referendum pairs: These choice questions mimic standard referendum questions

developed in the contingent valuation literature: for example, an improvement in

wetlands with an increase in taxes in one alternative versus the status quo in the other

alternative.

} Complex pairs: These choice questions present complex mixes of multiple changes in

natural resource levels and taxes paid in either or both alternatives of a choice pair.

The ability of respondents to reveal preferences may vary across these different types of

questions, which exhibits itself in varying degrees of randomness in decision-making. The

magnitude of this randomness can be examined using scale parameters, that differ by type of

choice question, that make all of the model parameters larger or smaller relative to the variance

of the random component of preferences. Therefore, we model not only heterogeneity of

preferences across individuals but also heterogeneity in the variance of the stochastic component

across pair types for a given individual. Two dummy variables were added to scale the

parameters to account for the fact that results may be statistically “noisier” across the three

different types of questions.4

 

4. Estimating separate scale factors for different choice questions in the estimation of environmental

preferences has been done to test for learning and fatigue effects (see, for example, Breffle et al., 1999 and

Adamowicz et al., 1998). With learning, randomness may decrease; and with fatigue, randomness may

increase. Swait and Adamowicz (2000) allowed for the level of unexplained noise in choices to vary over

choices and individuals using stated preference choices, and combining stated preference and revealed

preference data. Scale parameters were allowed to vary with complexity, where complexity was represented by

an endogenously-determined overall measure of uncertainty called entropy (which increases in the number of

alternatives and correlations between attributes), rather than using prespecified complexity categories as we

have done. Mazzotta and Opaluch (1995) present results supporting the hypothesis that increasing complexity

in the choice task increases the associated noise in the choice.
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-5

5.4 The Utility Function

The following equation presents the utility function for individual i; all of the variables in this

function are defined in Table 5.1:

(1 ) ,

(1 )

[(1 ) ]

(1 )( )

( )

2

1

2

1

3

1

3

1

A A i

r

roa roa ro ror

q

pea pea pe pe pn pn

f p p

m

pa pa n n f

weta wet wet

l

weta

i y i i

D D D

D D D

D D D D

D D

U y COST

i r

i q q

i i i m m

i l l

β β β ε

β β β

β β β β

β β

β

+ + + +

+ + +

+ + + +

+ +

= −

∑

∑

∑

∑

=

=

=

=

(5-1)

where ) (1 ) ~ (0, 2

2

s s r r

i s D s D

N

+ +

σ ε ε , and σ ε is not identified and so is set to 1/ 2 .

Parameter β y indicates the increase in utility if the cost decreases by $1 and is typically referred

to as the marginal utility of money. It is assumed to be a constant. This parameter is expected to

have a positive sign, which also implies that the individual prefers to pay a lower cost.

Downward sloping demand (i.e., demand is a decreasing function of price) is a standard tenet of

consumer economic theory and is very often observed in practice.

The other site-characteristic parameters, , , , , wetl pm pe pmq β β β β and r β ro represent the change in

utility from a change in each of the respective resource characteristics. The expected signs of the

elements of β ro are positive for all levels and increasing for better runoff quality; individuals are

expected to prefer better water clarity and fewer excess algae days. The expected signs of the

elements of β p are expected to be negative for all levels and getting larger in absolute values as

the number of years increases; individuals prefer PCB-caused losses to last a shorter period.

Finally, we expect wetlands and parks to provide increasing benefits as more of the resources are

provided.

Individual characteristic dummies are defined such that the base parameter (where the dummy

equals zero) is for the type of individual with the largest expected parameter. For example,

anglers may have larger marginal utilities (in absolute value) than non-anglers, and anglers are

given a value of zero for the dummy. The parameters on the dummy variables are then used to

scale (down) the base parameters multiplicatively (see Equation 5-1) for the types of individuals
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-6

Table 5.1. Model variables.

Variable Definition

Green Bay characteristics

COST Cost per year for 10 years

D ,l ∈[1,3] wetl

= 1 if acres of preserved wetlands increased to amount in level l

 = 0 otherwise

baseline level: 58,000 acres; increased levels: 60,900 acres, 63,800 acres, 69,600 acres

D , m∈[1,3] pm

= 1 if years until safe from PCBs is decreased to time in level m

 = 0 otherwise

baseline level: 100 years; decreased levels: 70 years, 40 years, 20 years

Dpe = 1 if facilities at existing parks are increased by 10%

 = 0 otherwise

D ,q∈[1,2] pnq

= 1 if acres of new parks increased by the amount in level q

 = 0 otherwise

increased levels: 5%, 10%

D ,r ∈[1,2] r ro = 1 if runoff improves water quality level to level r

 = 0 otherwise

baseline level: 20” of water clarity and 80 excess algae days or less; improved levels: 24”

(20% improvement) and 60 days or fewer (25% reduction), 34” (70% improvement) and

40 days or fewer (50% reduction)a

Individual characteristicsb

i y Income of respondent i

D D

D D

weta pa

pea roa

i i

i i

, ,

,

= 0 if respondent i is highly aware of issues related to wetlands, PCBs, existing parks, and

runoff, respectively (Question 22 = 4 or 5)

 = 1 otherwise

ni D = 0 if respondent i lives near Green Bay (within two miles based on zip code)

 = 1 otherwise

i Df = 0 if respondent i is a Green Bay recreational angler (Question 23)

 = 1 otherwise

Pair- and alternative-specific variables

DA = 1 if alternative is A alternative

 = 0 otherwise

Ds = 1 if pair compares two alternatives in which only one resource characteristic varies in

each alternative (single v. single)

 = 0 otherwise

Dr = 1 if pair contains resource improvement(s) with positive cost compared to baseline

conditions with no cost (referendum)

 = 0 otherwise

a. Note that changes in water clarity and excess algae days are perfectly correlated in the choice pairs.

b. Note that the dummy variable definitions for individual characteristics are opposite the usual convention:

those with a characteristic get a value of zero instead of one. The base case with all dummies equal to zero is

the type expected to have the highest value for PCBs and other resources (i.e., angler, lives near, higher

awareness). Given the form of the utility function, estimation was easier by scaling down the marginal

utilities of other, lower-value types of individuals with dummies set to one.
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-7

with dummies equal to one (e.g., non-anglers). It is easier for the estimation program to scale

down larger parameters than to scale up smaller parameters (the latter of which may effectively

equal zero). To clarify, suppose that some type of individual has a marginal utility that is

effectively zero. For example, those less aware of wetland resources may have no value for more

wetlands, and an associated zero marginal utility. It would be impossible for the estimation

program to scale up the zero parameter for the less aware group to anything positive for another

type of individual (e.g., more aware). Conversely, it is easy for the program to scale down a

positive marginal utility, even to zero.

The awareness parameters, , , , β weta β pa β pea and β roa , are expected to be negative, because those

with a higher awareness are expected to have a higher value for resource quality than those with

a lower awareness. Likewise, those living near Green Bay, and those who fish Green Bay

recreationally, are expected to value PCB cleanup more than those who live far and those who do

not fish; β n and β f are expected to be negative for those who do not fish and live at a distance.

5.5 Willingness to Pay per Household

For a model with no income effects and only one alternative in each state, such as this model, the

computation of WTP for a resource program (such as to avoid years of PCB-caused losses) per

household, measured as the compensating variation (CVi), is straightforward. It can be computed

as the difference between utility in the two states divided by the marginal utility of money.

Because utility is linear in the vector of marginal utilities βi, the formula for CVi is:

[ ( )] , 1 1 0

i i i

y

i CV x − x ′ = β β

(5-2)

where x is the vector of the resource characteristics and βi varies across individuals as a function

of individual characteristics.

Because all of the resource (and respondent) characteristics are incorporated as dummy variables

with values of zero or one, the formula for CVi for a given resource characteristic is simply the

marginal utility for that characteristic as represented by a model parameter(s) divided by the

marginal utility of money. Also note that the stochastic component cancels out of Equation 5-2,

so E(CVi) = CVi æ i. Estimated values are reported in Chapter 6.
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-8

5.6 Model Estimation

In the empirical model, parameters are estimated using a mathematical search algorithm that

makes the individuals’ observed choices most likely. In other words, the estimated parameters

maximize the likelihood of collectively observing the chosen alternatives from the choice pairs.

The parameter estimates are called maximum likelihood estimates because they are estimates of

the population parameters that maximize the likelihood of drawing the sample of the observed

choices.

The Gauss application module “Maxlik” was used to maximize the likelihood function

(Equation B-4 in Appendix B). Convergence was achieved for a variety of starting values, and

always at the same point. The model was estimated using a personal computer with a 400 MHz

Pentium II chip and 128 MB of RAM and took approximately 12 minutes to converge.

The likelihood function that is maximized is derived and presented in detail in Appendix B. In

short, it is a joint probability over all of the individuals in the data set. For a single individual it is

computed as the product of the probabilities of the chosen Green Bay alternatives over the six

choice-occasion pairs. Maximizing the likelihood function is equivalent to maximizing the joint

probability of observing the collective angler choices. Parameters estimated by maximum

likelihood have desirable statistical properties. For example, the estimates get closer to their

actual values as the sample size grows larger. Under some additional assumptions, these are also

the most precise estimates.

5.7 The Estimated Model

This section presents an overview of the estimation of the model described above. The estimated

parameters of the utility function in Equation 5-1 are discussed qualitatively here, and the

specific parameter estimates are reported in Table 5.2. In the next chapter, these parameters are

used to compute the rates at which individuals trade off PCB-caused losses with other site

characteristics, and to value in WTP the changes in site characteristics. Major conclusions that

can be drawn from this section are that model parameters are estimated with accuracy, and that

the model accurately predicts the choices.

5.7.1 Signs and significance of the parameter estimates

An important result from this estimation is that all of the estimated parameters with expected

signs do in fact have the expected signs, and within resource groups, parameters have reasonable

relative magnitudes. As expected, the cost of an alternative has a highly significant negative

effect on utility.
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-9

Table 5.2. Parameter estimates.

Parameter Estimatea

 (asymptotic t statistic)

β y (marginal utility of money) 0.0060 (13.286)

wetl β (wetlands)

l = 60,900 acres

l = 63,800 acres

l = 69,600 acres

0.1873 (2.264)

0.3420 (3.780)

0.4187 (5.000)

m β p (PCBs)

m = 20 years

m = 40 years

m = 70 years

1.2172 (7.253)

0.8477 (6.735)

0.3273 (3.871)

β pe (existing parks) 0.1077 (1.918)

q β pn (new parks)

q = 5%

q = 10%

0.0236 (0.438)

-0.1030 (-1.856)

r β ro (runoff/water quality)

r = 24” clarity and < 60 excess algae days

r = 34” clarity and < 80 excess algae days

0.1838 (2.856)

0.4817 (7.465)

β weta (wetlands awareness)b

β pa (PCBs awareness)b

β pea (existing parks awareness)b

β roa (runoff/water quality awareness)b

-1.0879 (-5.527)

-0.3387 (-3.729)

-1.0780 (-2.234)

-0.4599 (-3.202)

β n (PCBs for group not living near)

β f (PCBs for non-angler group)

-0.1618 (-1.708)

-0.1958 (-2.498)

β A (position dummy) 0.1244 (4.456)

s s (scale for resource-to-resource pairs)

r s (scale for referendum pairs)

0.5897 (2.363)

-0.4422 (-3.932)

a. Parameters can be interpreted as the change in utility for the specified change in the characteristics, as

compared to current levels.

b. Awareness = 1 if less aware of this specific resource topic.
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-10

The signs on the wetlands improvements parameters are significant at a 5% level, and positive

and increasing at a decreasing rate with greater numbers of acres restored, suggesting

diminishing marginal utility. The second 5,800 additional acres is only valued about one-fifth as

much as the first 5,800 acres. Utility from improvements in runoff is also increasing and

significant at a 5% level; inches of water clarity also exhibit diminishing marginal utility. The

first 4 additional inches of water clarity are valued about 54% more per inch compared to

subsequent inches.

Increasing facilities at existing parks is significant at a 10% (and almost 5%) level using a twotailed test. A 5% increase in new parks has a positive parameter, and a 10% increase has a

negative parameter, indicating that respondents do not value more parks. Individuals may think

land designation for a significant increase in parks is a waste of government funds, or that better

uses of land exist.

Parameters on the PCB variables are highly significant, show sensitivity to scope (i.e., a greater

number of years until PCB-caused losses no longer remain reduces utility more), and indicate

that individuals discount the future. For example, a change in the number of years until PCBs are

at safe levels from 100 years to 70 years increases utility 41% less per year of change than a

change from 40 to 20 years.

Awareness was found to be a highly significant variable. Those who are less aware of

recreational parks and wetlands essentially derive no utility from changes in the levels of these

resources. Those less aware of PCBs have benefits that would be about 34% less for their

removal, and those less aware of runoff and water quality issues get about one-half the utility.

Anglers and those living in close proximity also would get more utility from the reduction in the

years until PCBs are at safe levels: the parameter for non-anglers is approximately 20% lower,

and the parameter for those living beyond two miles is approximately 16% lower.5

 Distance and

angler status were found not to be significant for other resource groups. This result makes sense

because the other programs have a wider geographic impact than just the waters of Green Bay.

The parameter for positioning is significant and positive, meaning that A is selected more

frequently than B, controlling for other variables. This parameter is retained in the model to

eliminate positioning bias in the assessment; the utility from a program alternative (and

subsequently tradeoffs and WTP) is then computed using the estimated parameters but excluding

the positioning parameter, because the positioning parameter is used to calibrate for survey

 

5. Two miles from the Bay of Green Bay, where the large majority of recreational fishing occurs in the “waters

of Green Bay” (Breffle et al., 1999), was chosen to define the distance variable in the econometric analysis

because that is the farthest distance for which we found a statistically significant difference between the two

distance groups.
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-11

design effects but is not a demand parameter. The significance of the positioning parameter is

caused largely by a small number of respondents (28) who chose Alternative A in all six pairs,

which may happen for some respondents because of the complexity of the choices. Furthermore,

some choices of A are expected for these individuals, and their choices are generally consistent

with other survey responses. For example, in the group who chose Alternative A in every case,

PCBs and cost were generally ranked as most important, and alternatives with better PCB and

cost characteristics were generally chosen. Theory cannot predict what effect the omission of the

positioning parameter would have on the estimated relative importance of PCBs and other

parameters; it was included as a precautionary measure, and its inclusion is econometrically

preferred.

The simple resource-to-resource comparisons have the smallest variance in the random

component. 6 The variance for simple resource-to-resource pairs is about 0.4 times the variance

of the complex pairs (60% smaller). It is not surprising that these pairs have less noise than the

complex pairs because the comparison of alternatives is more straightforward. The referendumstyle questions have the greatest variance, suggesting that individuals can make tradeoffs

between different resource improvements more easily than they can trade off site characteristics

for money; the variance for referendum pairs is about 3.21 times the variance for complex pairs

(221% larger), and about 8.11 times the variance for simple resource-to-resource pairs (or the

variance for simple resource-to-resource pairs is about 12% as large as the variance for

referendum pairs). The greater noise with referendum pairs may also suggest some degree of

scenario rejection when the respondent is essentially asked for a WTP in money. This

referendum result is supported by the data in Tables 4.13 and 4.14 which also suggest that

sensitivity to scope is manifested less in the referendum pairs.

By allowing only the variances to differ across question types (and not the means of the

parameters), we are imposing parameter proportionality across question types, where the

relative magnitude of different demand parameters remains the same. With parameter

proportionality, expected choices across the types of choice questions will be the same; only the

level of randomness varies.7

 Louviere (1996) notes that parameter proportionality is often not

 

6. It is important here not to confuse estimated variances of the random components (which are maximum

likelihood parameter estimates that are not expected to change in any particular direction as sample size grows)

with the estimated variances for those parameter estimates (which do shrink with sample size). The statistical

significance of the estimated variance parameters is notable, given the smaller sample sizes for the referendum

and single versus single type choice pairs (about one-quarter the sample size each as compared to the number

of observations with complex pairs).

7. The reader should be clear that smaller estimated scales for certain types of choice questions mean that

responses to those types receive less weight in estimation of the model parameters (i.e., less weight in the

likelihood function discussed in Appendix B) than other types with higher scales. The demand parameter

estimates would be different if the scale were the same for every pair.
Stratus Consulting Resource Alternatives Preferences (Final, 10/25/00)

Page 5-12

rejected across different types of data sets in numerous studies. However, even in cases where

parameter proportionality is statistically rejected, Louviere suggests that modeling only error

variability will account for most of the heterogeneity. Estimating separate models by choice type

to test for parameter proportionality was not possible. Sample sizes were not large enough and

the variation in attribute levels too limited for some choice types and variables. Several

parameters were not identified in the models separated by choice type.

5.7.2 Measures of model fit

Statistical procedures were implemented to show how well the model explains the data. First, an

intuitively appealing test of fit is to examine the proportion of choices from choice pairs that are

accurately predicted by the model. To determine which alternative the model predicts would be

chosen from a pair, the estimated parameter values are put into Equation 5-1, along with the

resource characteristics and costs from the two alternatives. Whichever alternative gives the

highest value for estimated expected utility is the alternative the model predicts will be chosen.

The model correctly predicts about 66% of the 2,784 choices in the data.

A pseudo-R2

 for the choice pairs is approximately 0.12. It is akin to a measure of fit for a simple

linear regression model where the value ranges from zero to one and indicates the percentage of

variation in the data that is explained by the model. A value of 0.12 is typical for cross-sectional

data.
6. Restoration Scaling and Valuation Results

6.1 Introduction

Section 6.2 addresses the scale of restoration of equal value to the ongoing PCB-caused losses in

terms of the three types of programs evaluated: wetlands enhancements, recreational

enhancement, and runoff control. The selection and cost of preferred restoration is addressed in

the RCDP. WTP measures for ongoing PCB-caused losses from 2000 until a return to baseline,

as well as WTP measures for the restoration alternatives, are presented in Section 6.3. The WTP

results provide additional perspective on the values used to scale restoration, as the underlying

utility measures and WTP measures are linearly related. The WTP results for PCB-caused losses

are also compared with those in the recreational fishing damage determination (Breffle et al.,

1999) to avoid double counting [43 CFR § 11.84 (c)]. Section 6.4 provides conclusions,

including a summary of study design features that indicates the estimates are likely to understate

the required amounts of restoration and understate the WTP value measures (or ongoing PCBcaused losses).

For this assessment we assume that the regional population remains constant over the scenario

time period. This assumption has limited impact on the scaling of restoration so long as the

relative preferences between PCB removal and other restoration programs considered remain

relatively stable in the future. However, this assumption will likely understate the WTP value

measures if there will be population growth in the future because this growth is not factored into

the computations.

6.2 Restoration Scaling

We use the model results in Chapter 5 to scale the wetlands, runoff, and recreation enhancement

restoration programs to provide services of equal value to the PCB-caused service flow losses,

and to compute WTP values. Because there are many possible combinations of the mix and

levels of restoration programs, we illustrate the scale of restoration for a sample of program

combinations for selected scenarios.

The scale of restoration for PCB-caused losses is computed such that the marginal disutility from

continued PCB-caused losses is just offset by the marginal utility gained from enhancements in

other natural resource restoration programs. For example, if the estimated marginal disutility for

10 more (or utility from 10 fewer) years of PCB-caused losses is estimated to be 4, and the

marginal utility for a 25% increase in runoff control in Green Bay is estimated to be 4, then a

25% increase in runoff control would provide restoration of equal value to 10 more years of
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-2

PCB-caused losses. As a further example, if preserving an additional 5,000 acres of wetlands

(above the current amounts) generates a marginal utility of 4 and an additional 10,000 acres has a

marginal utility of 6, and the marginal utility for a 20-year reduction in PCB-caused losses is 5,

we use linear interpolation. We infer that a 7,500-acre increase in wetlands would provide

restoration of equivalent value to 20 more years of PCB-caused losses.

To scale restoration (and subsequently to compute WTP value measures), we first need to weight

the sample results to reflect the differences between the sample and the population in the

10 sample counties. The sample was made comparable to the population using weights for

distance (counties closer to Green Bay were sampled more heavily than counties farther away,

and some living near Green Bay have higher PCB-caused losses) and recreational angler status

(the sample has a disproportionately high number of anglers, who value PCB removal more).1

Weighting did not have a large impact on results. For example, average WTP values for PCB

removal (and therefore for PCB-caused losses) per household fell by about 9% when the weights

were used. For restoration scaling the effect was even smaller. Those who value a reduction in

the number of years until PCBs are at safe levels less also tend to have lower values for other

resource programs, so the effects of sample adjustments on the computation of the scale of

restoration are largely offsetting.

Individuals differ in terms of how they trade off different resource programs for reductions in

PCB-caused losses. We determine the level of restoration that is necessary for the population as a

whole. For each scenario, for each individual in the weighted sample we use the model

parameters to compute the utils associated with the PCB-caused losses and to compute the utils

associated with the varying levels of the restoration programs. The individual utils are added up

across all individuals in the weighted sample and the appropriate scale of restoration is

determined so it yields the same total utils as the PCB-caused losses.

We consider the scale of restoration, and the WTP measures of ongoing PCB-caused losses, for a

range of remediation scenarios (see Section 1.4). Estimates of the scale of restoration of

equivalent value to PCB losses, and WTP measures for PCB-caused losses, between now (2000)

and 20 years from now are computed by annualizing the utility and WTP for changes in losses

 

1. The proportion of angler households in the population was determined using data from the recreational

damage determination (Breffle et al., 1999). Green Bay angler households were identified in the current study

using Question 23 about fishing Green Bay in the last 12 months. However, this question may simply reflect

interest in fishing, and weighting on the basis of this response compared to population data about anglers who

actually did fish the waters of Green Bay may result in an overcorrection. Because households with interest in

Green Bay angling have higher WTP and value the reduction of PCB years more relative to other resource

actions, this overcorrection will lead to an understatement of the scale of restoration and of WTP values for the

public as a whole.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-3

between remediation lasting 20 years and remediation lasting 40 years, and using a discount rate

of 3% to compute the present value of losses from period 2000 to 2020 based on Figure 1.3. A

3% discount rate is selected to be consistent with regulatory guidance (Section 6.3.2) and

consistent with all other present value calculations in the Co-trustee damage determination.

Potential natural recovery during the assumed 10 year period of remediation is not considered.

After remediation is selected, the damage estimates can be revised to account for natural

recovery. However, unless the rate of natural recovery is rapid, such revisions would be minimal.

Table 6.1 provides examples of the scale of sample mixes of restoration projects that provide

services with value equal to the ongoing PCB-caused losses over specified time periods. For

instance, the first three lines provides three examples of restoration providing services of value

equal to the PCB-caused losses from 2000 until a return to baseline if an intensive level of

remediation returns services to baseline in 2020. The second block provides examples for the

40 year intermediate level of remediation and the third block provides examples of the scale of

restoration that provides services of value equal to a portion of the PCB-caused losses

corresponding to differences between a 20 year and 40 year remediation, and between a 20 year

and 70 year remediation. The examples include a combination of wetland acreage, park

enhancements, and runoff control to provide sufficient restoration. Additional acreage of new

parks was not found to be valued, so this program is not included in constructing restoration

combinations.

For some scenarios, single resource programs using wetlands only or runoff control only, or

combinations of these two actions, provide a sufficient scale of restoration. However, even a

substantial recreation program of enhancements at 120 regional parks, for example, provides

restoration benefits equivalent to only a few years of PCB-caused losses. In some cases, more of

a program is required than considered in the survey. In these cases we extrapolate at the same

marginal utility as for the last program units added, which likely understates the scale of

restoration due to diminishing marginal utility of increasing program units (wetland acres, %

control of runoff, % improvement in existing parks).

For two reasons, it may be economically more efficient to pursue combinations of programs

rather than a single-resource program to provide properly scaled restoration. First, diminishing

marginal utility at increasingly high levels for wetlands and runoff control means that the

benefits do not increase at the same rate as the size of these programs are increased. Second, very

high quantities of a given program may result in increasing marginal costs, to the point where

some large programs may be technically infeasible.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-4

Table 6.1. Illustration of restoration scaling.

Example mixes of restoration programs

Scenario Wetland restoration acresa Existing park enhancement Runoff controlb

PCB remediation scenariosc

Intensive: (0 to 20 years)

Intermediate: (0 to 40 years)d

Partial restoration

Intensive vs. 40 year

Intermediate (20 to 40 years)

Intensive vs. 70 year

Intermediate (20 to 70 years)

3,100

5,500

11,000

24,100

16,000

2,900

5,000

2,400

5,700

13,000

10%

8%

0%

10%

20%

2%

3%

0%

0%

10%

14”/50%

12”/45%

12”/45%

16”/55%

16”/55%

4”/25%

2”/13%

7”/33%

14”/50%

10”/40%

a. Rounded to nearest 100 acres.

b. Additional inches of water clarity/percentage decrease in number of excess algae days.

c. Restoration is for PCB-caused losses during the period indicated.

d. Requires extrapolating beyond the range of actions considered for some or all programs.

The scenarios in Table 6.1 do not include ongoing damages from 2000 that continue beyond

2040. This is because the levels considered for increased wetlands acres plus runoff control plus

recreational enhancements do not provide benefits sufficient for ongoing PCB-caused losses

starting in 2000 and continuing beyond 2040 without extrapolating well beyond the levels

considered, and because the diminishing marginal utility reflected in the results suggests that the

incremental value may be close to zero for additional enhancements well beyond the range

considered. Therefore, for remediation that takes longer than 40 years, additional restoration

actions beyond (or variations to) the three programs considered here may also be required.

Table 6.1 also provides scales of restoration for a portion of ongoing losses. These measures may

be combined with other damage measures as an alternative approach to assess damages for all

losses through time, such as using a combination of recreational fishing damages, total

compensable damages, or habitat restoration programs for past damages and interim damages up

to 2020, and then using Table 6.1 to scale restoration for ongoing losses after 2020.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-5

6.3 WTP Measures of Values

6.3.1 Population-weighted annual measures of WTP per household

By asking respondents to consider tradeoffs between resource programs and monetary costs their

household pays, we are also able to derive WTP for the programs, which for PCBs is a measure

of total compensable values for ongoing PCB-caused losses. To obtain population based WTP

measures, as for restoration scaling, the sample WTP values are weighted to reflect the

population in the 10 county assessment area. To obtain present value measures, the stream of

10 year payments is discounted to 2000.

Table 6.2 presents the annual WTP estimates over 10 years based on CVi from Equation 5-2. The

values reported in Table 6.2 are population means, obtained by weighting the sample results to

the population as described in Section 6.2. The 95% confidence intervals are approximated using

the Krinsky-Robb procedure using 500 draws.

Figure 6.1 graphically presents the mean WTP results for each level of the four programs.

Table 6.2 and Figure 6.12

 demonstrate that PCB removal is generally much more highly valued

than any other resource program, reflecting the results in the previous section that large

quantities of multiple programs would be necessary to compensate for some injury scenarios.

Diminishing marginal utility for a single program is reflected in the values for wetlands and

runoff control (i.e., total values for these resource programs increase at a decreasing rate as more

of the action is undertaken). The values for PCB removal increase as the years decrease until safe

levels are reached. This reflects that near-term losses (e.g., between 0 and 20 years from now)

are valued more highly by respondents than losses in the more distant future (e.g., between 100

and 70 years). Note that the mean WTP values for all resource changes and scenarios is less than

1% of the typical household’s budget.

The mean WTP values per household for PCB-caused losses in the intensive remediation

scenario (constant losses between 2000 and 2009, then linearly declining losses to zero at the end

of 2019) averages to about $36 per year (the present value of 10 payments of $83.42 = $733,

divided by 20 years of losses). The present value of annual losses ranges from about $52 per year

in the first 10 years prior to remediation reducing losses, then declining to zero at the end of the

20th year. These values are of a similar size as those reported in the literature for other

significant natural resource programs in the assessment area and Great Lakes area (Appendix D).

 

2. Figure 6.1 omits values for outdoor recreation enhancements through additional acres of park, which are not

statistically different from zero for all respondents or for the more aware respondents.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-6

Table 6.2. Mean population-weighted household willingness to pay for resource

programs (dollars per year for 10 years, in 1999 dollars).

Resource program Mean E(CV)

a

PCB remediation scenarios

Intensive: (0 to 20 years)

Intermediate: (0 to 40 years)

No additional remediation: (0 to 100 years)

Other PCB scenariosb

20 to 100 years

40 to 100 years

70 to 100

0 to 70 years

20 to 70 years

40 to 70 years

20 to 40 years

$83.42 [$47.04, $116.99]

$118.92 [$67.06, $166.77]

$200.37 [$146.10, $251.59]

$116.95 [$91.09, $139.97]

$81.45 [$61.52, $102.27]

$31.44 [$17.17, $47.26]

$168.93 [$114.61, $217.11]

$85.50 [$64.95, $106.63]

$50.00 [$33.76, $68.21]

$35.50 [$20.02, $49.78]

Other resource programs

Wetlands

58,000 6 60,900 acres

58,000 6 63,800 acres

58,000 6 69,600 acres

Existing parks (10% increase)

New parks

5% increase

10% increase

Runoff control

Clarity: 20” 6 24”; reduction in algae days: 25%

Clarity: 20” 6 34”; reduction in algae days: 50%

$13.48 [$2.60, $24.76]

$24.61 [$10.76, $38.30]

$30.12 [$18.58, $42.89]

$7.73 [-$0.15, $15.83]

$0c

$0c

$23.50 [$7.54, $42.24]

$61.60 [$46.92, $78.65]

a. Simulated 95% confidence interval in brackets.

b. WTP is for avoidance of PCB-caused losses during the period indicated.

c. Not significantly different from $0 for all respondents or even for the more aware respondents

(Table 6.3).
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-7

$200.37

$81.44

$0.00

$31.44

$116.95

$0.00

$30.00

$60.00

$90.00

$120.00

$150.00

$180.00

$210.00

100 80 60 40 20 0

PCBs (years until safe levels)

WTP

$0.00 $23.50

$61.60

$0.00

$30.00

$60.00

$90.00

$120.00

$150.00

$180.00

20 24 28 32

Runoff (inches of water clarity)

 24" (34") water clarity =

25% (50% ) reduction in algae days

WTP

$0.00

$13.48 $24.61

$30.21

$0.00

$30.00

$60.00

$90.00

$120.00

$150.00

$180.00

58000 60900 63800 66700 69600

Wetlands (acres)

WTP

$0.00 $7.73

$0.00

$30.00

$60.00

$90.00

$120.00

$150.00

$180.00

0% 5% 10%

Existing Parks (% increase)

WTP

Figure 6.1. Population-weighted willingness to pay estimates for resource programs (household

WTP per year for 10 years, $1999).
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-8

Heterogeneity of preferences was incorporated into the model to allow different types of

respondents to report different household WTP values. As illustrated in Table 6.3, values vary in

plausible ways; e.g., households closer to the site and with recreational anglers have higher PCB

values. For each natural resource program and scenario, the values are reported by households

that are more aware of the natural resource topic (topic awareness = 4 or 5) and by households

that are less aware of the natural resource topic (topic awareness = 1, 2, or 3). Note that the WTP

values decrease with awareness for each of the topics except the addition of new parks, for which

the values are not statistically different from zero for either the more aware or less aware group.

For PCB removal, the values are lower for the less aware group, compared to the more aware

group (by 34% to 53% depending on household location and angler status), but are still

statistically significantly larger than zero. Similarly, the runoff control values decrease by nearly

half for the less aware group as compared to the more aware group. The wetlands and existing

parks values decrease to $0 for the less aware group.

6.3.2 Aggregate present values of PCB-caused losses

In this section, the present values of interim WTP for PCB-caused losses between 2000 and a

return to baseline are presented for alternative scenarios based on the population-weighted

estimates of WTP. The aggregate values represent losses to the 346,700 households in the

10 county area; we assume the population remains constant into the future. The aggregate values

are computed using a 3% discount rate (with no discounting in the first year of payment and then

discounting the subsequent nine years of payment). A 3% discount rate is consistent with the

average real three-month Treasury bill rates over the last 15 years (Bureau of Economic

Analysis, 1998; Federal Reserve, 1998) and is consistent with the U.S. DOI implementation

guidelines (U.S. DOI, 1995) for NRDAs under 43 CFR § 11.84 (e)(2). Using a 3% discount rate,

the present value multiplier for 10 years of payments is 8.786. Using a 2% discount rate on the

10 years of payments would result in a 4.3% increase in the aggregate present value, and using a

6% discount rate would result in an 11.2% decrease in the aggregate present value. The total

values for key remediation scenarios, and differences between remediation scenarios, are

reported in Table 6.4 and range from $254 million for ongoing losses with a 20 year return to

baseline, to $610 million for ongoing losses if there is little or no PCB removal.

Aggregate WTP values for interim PCB-caused losses from 2000 until a return to baseline may

be larger than, similar to, or smaller than the costs of the appropriately scaled restoration

programs to provide services of equal value to PCB-caused losses. Differences can be attributed

to the degree of cost and technical feasibility of restoration programs, and the degree to which

resource enhancement programs provide multiple benefits, including both active and passive use

benefits, such that the values of these programs exceed the costs of these programs.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-9

Table 6.3. Household WTP estimates by respondent type (dollars per year for 10 years, in

1999 dollars).

Mean WTP

Resource change More awarea Less aware

PCB remediation scenariosb

Intensive: (0-20 years)

all respondents

angler, near (within two miles)

angler, not near

non-angler, near (within two miles)

non-angler, non near

Intermediate: (0-40 years)

all respondents

angler, near (within two miles)

angler, not near

non-angler, near (within two miles)

non-angler, non near

No additional remediation: (0-100 years)

all respondents

angler, near (within two miles)

angler, not near

non-angler, near (within two miles)

non-angler, non near

$118.96

$145.32

$121.80

$116.86

$93.34

$169.58

$207.16

$173.63

$166.59

$133.06

$285.72

$349.03

$292.52

$280.68

$224.19

$65.90

$96.09

$72.57

$67.64

$44.12

$93.94

$136.98

$103.45

$96.42

$62.89

$158.28

$230.80

$174.31

$162.46

$105.97

Other resource programs

Wetlands

58,000 6 60,900 acres

58,000 6 63,800 acres

58,000 6 69,600 acres

Existing parks (10% increase)

New parks

5% increase

10% increase

Runoff control

Clarity: 20” 6 24”; reduction in algae days: 25%

Clarity: 20” 6 34”; reduction in algae days: 50%

$31.34

$57.24

$70.07

$18.02

$0c

$0c

$30.75

$80.61

$0c

$0c

$0c

$0c

$0c

$0c

$16.61

$43.54

a. If respondents chose 4 or 5 for awareness of the relevant topic in Question 22, they fall in the “more aware”

category, otherwise they are in the “less aware” category.

b. WTP is for avoidance of PCB-caused losses during the period indicated.

c. Estimated values were not statistically different from zero. To estimate population-weighted means, individual

values were set to $0.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-10

Table 6.4. Present value of total WTP for ongoing PCB-caused losses: Residents of

10 Wisconsin counties (millions of 1999 dollars).

Scenario Mean (rangea)

PCB remediation scenarios

Intensive (20 years)

Intermediate (40 years)

Intermediate (70 years)

Limited or none (100 years)

$254 ($143-$356)

$362 ($204-$508)

$515 ($349-$661)

$610 ($445-$766)

Changes in remediation scenarios

20 rather than 40 years

20 rather than 70 years

20 rather than 100 years

40 rather than 70 years

40 rather than 100 years

70 rather than 100 years

$108 ($ 61-$75)

$260 ($198-$325)

$356 ($276-$426)

$152 ($103-$208)

$248 ($187-$312)

 $96 ($52-$144)

a. 95% confidence interval.

6.3.3 Comparison to recreational fishing damage determination

Introduction

The PCB-caused losses considered in this TVE assessment differ from, and only partially

overlap, the PCB-caused losses considered in the Co-trustee’s recreational fishing damage

determination (Breffle et al., 1999).

} Time periods. The recreational fishing assessment considers losses from 1980 until a

return to baseline. This TVE assessment considers losses from 2000 until a return to

baseline, or a subset of the time period in the recreational fishing assessment.

} Affected populations. The recreational fishing assessment considers losses to Wisconsin

resident and non-resident anglers who purchased licenses in an 8 county area of

Wisconsin surrounding the Bay of Green Bay to fish the Wisconsin waters of Green Bay,

plus losses experienced by anglers who fished the Michigan waters of Green Bay. This

TVE assessment considers losses to all residents of a 10 county area of Wisconsin. This

population includes the anglers from these counties, but does not include other anglers

from outside of these counties (e.g., from anglers from other Wisconsin counties, or from

out-of-state).

} Losses considered. The recreational fishing assessment considers only active use losses

resulting from fish consumption advisories. This TVE assessment considers these losses

and all other PCB-caused losses.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-11

The results of this TVE assessment and the recreational fishing assessment can be compared for

a comparison population of households with Green Bay anglers in the 10 Wisconsin counties

near the Bay of Green Bay. For this comparison population, and for ongoing damages from 2000

until a return to baseline, the WTP measures of compensable values in this TVE assessment are

slightly larger than the WTP measure of compensable values in the recreational fishing

assessment. This is as expected as this assessment values a larger set of losses than in the

recreational fishing assessment, although for households with Green Bay anglers, the active use

fishing losses may well be the dominant component of PCB-caused losses. While the two

assessments take different approaches to measure compensable values, the comparability of the

results for a comparison population supports the estimated magnitude of damages in each

assessment, and allows double counting between the assessments to be readily addressed.

Comparison

The recreational fishing assessment computed annual WTP per angler for losses in 2000. The

present value of all losses was then computed reflecting an assumed 10-year remediation period

with minimal recovery, followed by a recovery period of varying lengths (10, 20, and 90 years

for a total time period for return to baseline of 20, 40, and 100 years), and discounted to a present

value using a 3% discount rate (which is used in all subsequent comparisons). In contrast, the

estimation of WTP damages in this TVE assessment is based on the respondent WTP per year

for 10 years to obtain changes in future PCB-caused losses, including recreational fishing and

other losses. For comparison purposes, for each remediation scenario we assume that the time

stream of losses corresponding to the TVE values is the same as in the recreational fishing study.

We also use a 3% discount rate for all present value calculations.

We make the following adjustments to the total values from each assessment to make them

comparable for households in the 10 counties who have Green Bay anglers. For the TVE

assessment, we multiply the total values reported in Table 6.4 by 11.46% (the percent of

households with Green Bay anglers)3

 and by 1.1703 (the ratio of WTP per household for

households with Green Bay anglers to the WTP per household for all households in the sample).

These numbers are reported in the first data column of Table 6.5. For the recreation assessment

we take the total damages for Wisconsin waters of Green Bay, which were computed for anglers

who purchase licenses in 8 neighboring counties. These values are reduced reflecting that only

76% of the anglers resided in these counties (Breffle et al., 1999; Table 3.18), and escalated by

 

3. In 1998 there were about 48,600 Green Bay anglers who purchased their Wisconsin fishing license in

8 nearby counties (Breffle et al., 1999; page 8-6). Approximately 76% of these anglers resided in these

8 counties. Allowing for 5% of households to have more than one Green Bay angler results in

35,117 households with Green Bay anglers, or 11.12%). We assume the same percent for Shawano and

Calumet counties, which are also included in the TVE assessment, resulting in 38,553 households and

40,480 Green Bay anglers.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-12

Table 6.5. Comparison of total future damages in the recreational fishing and total value

equivalency assessments.

Total values for comparison population of households

in 10 county region with Green Bay anglers

(millions, 1999$)

Scenario

Total value

equivalency study

Recreational

fishing study

Ratio of total

values to

recreational

fishing values

Intensive restoration

(0-20 years) $33.1 $30.7 1.08

Intermediate restoration

(0-40 years) $47.1 $43.1 1.09

No restoration

(100+ years) $79.4 $61.9 1.28

Intensive — intermediate

restoration (20-40 years) $14.1 $12.6 1.12

1.02 for inflation and by 1.096 to reflect the number of households in the 10 counties in the TVE

assessment as compared to households in the 8 counties in the recreational fishing assessment

(see Table 3.2). These values are reported in the second data column of Table 6.5.

The ratios of the TVE total values to the recreational fishing compensable values (for the

comparison population) are reported in the last column of Table 6.4 and range from 1.07 to 1.28,

with the variation in the ratio most likely reflecting differences in the assumptions and actual

values for discount rates and other computation variables, and normal imprecision in the

underlying estimates.

A similar comparison can be made based on individual angler household damages. For

simplicity, consider the WTP for reducing the period of recovery from 40 years to 20 years (from

intermediate to intensive remediation), a value directly reported in this TVE study (reducing

required assumptions for comparison) and estimated to be $364 ($41.4 per year for Green Bay

angling households) for 10 years discounted at 3%, where the first payment is not discounted.

The recreation study reports average angler values of approximately $51 per angler per year for

current damages for open water fishing ($1998 from Table 1.1 in Breffle et al., 1999). Adding

ice fishing (+18%), updating to 1999 dollars (+2%), and allowing for multiple Green Bay anglers

per Green Bay household results in values of $65 per year per household with Green Bay

anglers. Computing these damages for the period 20 to 40 years hence, with damages declining

from baseline levels to zero over this period (2020 to 2040), and discounting to a present value at

3% discount rate, results in a present value of $335 per household with Green Bay anglers, or

about 9% less than the comparable $364 from this assessment.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-13

Double counting

If both the Co-trustees’ recreational fishing damage assessment and this TVE assessment are to

be used to assess damages, double counting should be eliminated. The overlap between the

studies is for future losses from 2000 until injuries and losses are eliminated, limited to

Wisconsin households in the 10 neighboring counties with Green Bay anglers. There is no

double counting for past damages, for Wisconsin resident anglers from outside of the

10 counties, for nonresident anglers, or for any damages associated with fishing in Michigan

waters of Green Bay.

Double counting can be addressed in several ways. First, in this TVE assessment we compute the

WTP values for ongoing PCB-caused losses to households with Green Bay anglers (anglers who

fish the waters of Green Bay) in the 10-county area to be about 13% of the total value of losses

to all households in the study. Thus, one could add the recreational fishing study damages (in

total) to 87% of the values from this study and remove double counting. Alternatively, one could

add the total damages from this study to the non-overlapping portions of the recreational fishing

assessment (past damages, damages in Michigan waters of Green Bay), and to 17% of the future

losses in Wisconsin waters of Green Bay (from non-residents and from residents from outside of

the 10 county area).4

6.4 Conclusions

This TVE assessment identifies that the scale of restoration of equivalent value to, and the WTP

values for, PCB-caused losses in the Lower Fox River and Green Bay area are substantial. It is

possible for combinations of natural resource restoration programs, including wetlands

restoration, improvements to outdoor recreational facilities, and runoff control, to provide

sufficient benefits with value equal to PCB-caused losses during a limited time frame (less than

40 years) if the programs are sufficiently comprehensive and extensive.

The overall assessment results are consistent with the literature identified in Appendix D, and the

estimated values for anglers in the population are consistent with the more specific recreational

fishing damages assessment — the damages are larger here because this assessment considers all

injuries rather than just reduced enjoyment of fishing because of fish consumption advisories

considered in the recreational fishing assessment (Breffle et al., 1999).

 

4. 48,600 individuals purchasing licenses in the 8 counties minus 40,480 Green Bay anglers from the

10 counties accounting for in the TVE study leaves 8,180, or 17%.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-14

The key biases and omissions in the assessment are summarized below and in Table 6.6. Overall,

the estimated scale of restoration and WTP values are expected to be conservative (i.e., the level

or restoration, and the WTP estimates, are understated).

Table 6.6. Omissions, biases, and uncertainties resulting in conservative estimates.

Method or assumption

Effect on scale

of restoration

Effect on WTP values for

PCB losses

Past damages were omitted - -

Only about 15% of the Wisconsin households were

considered (10 counties) unknown, small -

Michigan household losses are not considered unknown, small -

Tribal resource losses are not considered - -

Unknown period for return to baseline unknown unknown

Sampling and non-response bias unknown, small +, small

Population growth not incorporated no effect -

Increasing environmental preferences not

considered unknown -

A “-” (“+”) indicates that the effect of the omission, bias, or uncertainty on the scale of restoration or WTP

value measures is to understate (overstate) the true level or value.

1. Omission of past damages. Past damages are omitted and potentially substantial. In the

recreational fishing report past damages accounted for between 44% and 60% of total

damages, depending on the remediation scenario. The significance of the omission in this

study is unknown but could be expected to be important compared to ongoing losses.

2. Omission of Wisconsin residents outside of the neighboring 10 counties and of Michigan

residents. This TVE assessment focused on residents in 10 Wisconsin counties. Distance

was found to have little effect on values except for the existence of higher values for

PCB-caused losses for a minority of respondents living very close to Green Bay.

The effect of omitting more distant residents on the scale of restoration is unknown;

however, the effect may be small because study results do not show distance as having a

great effect on tradeoffs. The effect on WTP values for PCB losses is to have a clear

downward bias that results in understated aggregate values. For example, because there

are over five times as many Wisconsin households outside of the 10 county region, even

if the average value for PCB losses by residents from outside the 10 county region were

10% of the values for households within the 10 county region, the omitted values would

be as much as 50% of the measured aggregate values.
Stratus Consulting Restoration Scaling and Valuation Results (Final, 10/25/00)

Page 6-15

3. Omitted losses to Michigan households. Also omitted are preferences and values for

Michigan residents in the region. In 1990 there were about 24,000 households in two

Michigan counties adjacent to the upper portion of the waters of Green Bay (Delta and

Menominee), and another 44,000 in the next four adjacent counties (Alger, Dickinson,

Marquette, and Schoolcraft). All totaled this amounts to slightly less than 20% as many

households as in the 10 Wisconsin counties considered. Because of their proximity to the

injured natural resources, one might also expect these households to experience losses,

although potentially less than for Wisconsin households because the degree of some (but

not all) injuries is less in the upper bay. As above, the scale of restoration (largely located

in Wisconsin) may not be substantially altered, but the WTP value measures of PCBcaused losses are understated.

4. Omitted losses associated with Tribal resources. Estimates of PCB losses focused on the

Lower Fox River and Green Bay and did not include detail on injuries to Tribal lands and

waters, and to the associated Tribal, cultural, and other losses. Neither the scale of

restoration nor the WTP value measures account for Tribal resources, and thus are

understated.

5. Unknown period for a return to baseline. The time period for remediation, and the

resulting time period until a return to baseline, is uncertain until the Record of Decision is

completed. Therefore, the assessment scales restoration, and computes WTP value

measures of ongoing losses, for a range of scenarios.

6. Sampling and nonresponse biases. As identified in Sections 3.3 and 3.4, any such biases

are expected to be small due to the comparability of the sample and the population, and

the high response rates. Any such bias would likely similarly influence the value of all

natural resource enhancement programs and thus largely cancel out for the restoration

scaling resulting in minimal impact. The impact of sampling and nonresponse biases on

the WTP values would likely be to increase the computed values, although the analysis

suggests any such biases would be small, if they existed at all.

7. Constant population. The population is expected grow over time. This is not expected to

have any effect on the scale of restoration so long as relative preferences and values

remain constant for PCB removal and for other restoration programs, but aggregate WTP

will be understated by the amount the population grows.

8. Constant preferences. Preferences for environmental commodities may change over time.

How PCB losses vis-à-vis benefits from other resource enhancement programs will

change is not clear, so the effect on the scale of restoration is unknown. However,

increased environmental preferences would have a tendency to increase WTP, and

therefore WTP value measures for PCB-caused losses.
References

Adamowicz, W., J. Louviere, and M. Williams. 1994. Combining revealed and stated preference

methods for valuing environmental amenities. Journal of Environmental Economics and

Management 26:271-292.

Adamowicz, W., P. Boxall, M. Williams, and J. Louviere. 1998. Stated Preference Approaches

for Measuring Passive Use Values: Choice Experiments and Contingent Valuation. American

Journal of Agricultural Economics 80:64-75.

Adamowicz, W.L., J. Swait, P. Boxall, J. Louviere, and M. Williams. 1997. Perceptions versus

objective measures of environmental quality in combined revealed and stated preference models

of environmental valuation. Journal of Environmental Economics and Management 32:65-84.

Baba, R.K., P.K. Johnsen, G.J. Knapp, and L.J. Smith. 1991. Public Perceptions and Attitudes

Toward Water Quality Rehabilitation of the Lower Green Bay Watershed: A Report to the Green

Bay Remedial Action Plan Implementation Committee and Community. Center for Public

Affairs, University of Wisconsin — Green Bay, Working Paper Number 90.12 (July).

Barron, M.G., M.J. Anderson, D. Cacela, J. Lipton, S.J. Teh, D.E. Hinton, J.T. Zelikoff,

A.L. Dikkeboom, D.E. Tillitt, M. Holey, and N. Denslow. 2000. PCBs, liver lesions, and

biomarker responses in adult walleye (Stizostedium vitreum vitreum) collected from Green Bay,

Wisconsin. Journal of Great Lakes Research 26(3):250-271.

Batsell, R.R. and J.J. Louviere. 1991. Experimental analysis of choice. Marketing Letters

2:199-214.

Bierman, V.J., J.V. DePinto, T.C. Young, P.W. Rodgers, S.C. Martin, R. Raghunathan, and

S.C. Hinz, 1992. Development and Validation of an Integrated Exposure Model for Toxic

Chemicals in Green Bay, Lake Michigan. Prepared for U.S. EPA Large Rivers and Lakes

Research Branch, Draft Final Report. September 1.

Bosley, T.R. 1978. Loss of Wetlands on the West Shore of Green Bay. Wisconsin Academy of

Sciences, Arts and Letters, Vol. 66:238-239.

Brazner, J.C. 1997. Regional, habitat, and human development influences on coastal wetland

beach assemblages of Green Bay, Lake Michigan. Journal of Great Lakes Research 23:36-51.
Stratus Consulting References (Final, 10/25/00)

Page R-2

Breffle, W.S. and E.R. Morey. 2000. Investigating preference heterogeneity in a repeated

discrete-choice recreation demand model of Atlantic salmon fishing. Marine Resource

Economics 15:1-20.

Breffle, W.S., E.R. Morey, R.D. Rowe, D.M. Waldman, and S.M. Wytinck. 1999. Recreational

Fishing Damages from Fish Consumption Advisories in the Waters of Green Bay. Prepared for

the U.S. Fish and Wildlife Service by Stratus Consulting Inc., Boulder, CO. November 1.

Bureau of Economic Analysis. 1998. http://www.bea.doc.gov/bea/dn1.htm (see Summary,

1929-97, from the Survey of Current Business), released August 1998.

Cameron, T.A. and J. Englin. 1997. Respondent experience and contingent valuation of

environmental goods. Journal of Environmental Economics and Management 33(3):296-313.

Campbell, S. 1999. Most residents back Superfund cleanup: survey on Fox River finds health

concerns. Press-Gazette. October 21.

Carson, R.T. 1997. Contingent Valuation Surveys and Tests of Insensitivity to Scope.

In Determining the Value of Non-Market Goods: Economic, Psychological, and Policy Relevant

Aspects of Contingent Valuation Methods. R. Kopp, W. Pommerehne, and N. Schwarz (eds.).

Kluwer, Boston. pp. 127-164.

Carson, R.T., R.C. Mitchell, W.M. Hanemann, R.J. Kopp, S. Presser, and P.A. Ruud. 1992.

A Contingent Valuation Study of Lost Passive Use Values Resulting from the Exxon Valdez Oil

Spill. Report to the Attorney General of the State of Alaska. Natural Resource Damage

Assessment, Inc.

Chen, H.Z. and S.R. Cosslett. 1998. Environmental quality preference and benefit estimation in

multinomial probit models: A simulation approach. American Journal of Agricultural Economics

80:512-520.

Christie, J. and L. Meyers. 1987. Biota and Habitat Management Technical Advisory Committee

Report for the Lower Green Bay Remedial Action Plan, Wisconsin Department of Natural

Resources PUBL-WR-165 87, Final Draft, July.

Dillman, D.A. 1978. Mail and Telephone Surveys — The Total Design Method. John Wiley &

Sons, Inc., New York.

Dillman, D.A. 2000. Mail and Internet Surveys: The Tailored Design Method. 2nd Edition. John

Wiley and Sons, Inc. New York.
Stratus Consulting References (Final, 10/25/00)

Page R-3

Dillman, D.A. and J. Tarnai. 1991. Mode Effects of Cognitively Designed Recall Questions:

A Comparison of Answers to Telephone and Mail Surveys. In Measurement errors in surveys.

P.P. Bierner, R.M. Groves, L.E. Lyberg, N.A. Mathiowetz, and S. Sudman. John Wiley & Sons,

NY.

Elrod, T., J.J. Louviere, and K.S. Davey. 1992. An empirical comparison of ratings-based and

choice-based conjoint models. Journal of Marketing Research 30:368-377.

ESRI. 1998. Arc/Info v. 7.2.1, the Arc/Info GRID module and ArcView v. 3.1, Environmental

Systems Research Institute, Inc., Redlands, CA.

Ethier, R.G., G.L. Poe, and J. Clark. 2000. A comparison of hypothetical phone and mail

contingent valuation responses for green-pricing electricity programs. Land Economics 76(1):54.

Federal Reserve. 1998. The Federal Reserve. Website:

http//www.bog.frb.fed.us/releases/H15/data.thm (see Treasury Bills 3-month constant

maturities). Updated April 1999.

Fischoff, B. and L. Furby. 1988. Measuring values: A conceptual framework for interpreting

transactions with special references to contingent valuation of visibility. Journal of Risk and

Uncertainty 1(June):147-184.

Fox River Global Meeting Participants. 1997. Fox River Global Meeting Goal Statement.

Meeting at U.S. EPA Region 5 Offices, Chicago, IL. October 27.

Freeman, A.M. 1993. Valuing Natural Assets: The Economics of Natural Resource Damage

Assessment. Resources for the Future, Washington, DC.

Gan, C. and E.J. Luzar. 1993. A conjoint analysis of waterfowl hunting in Louisiana. Journal of

Agricultural and Applied Economics 25(2):36-45.

Green, P.E. and V. Srinivasan. 1990. Conjoint analysis in marketing: New developments with

implications for research and practice. Journal of Marketing October: 3-19.

Hagler Bailly Services. 1998. Confidential Memorandum from M. Anderson, D. Mills,

K. LeJeune, to David Allen re Results of Preliminary Restoration Project Scoring. June 3.

Harris, H.J. 1993. The State of the Bay, A Watershed Perspective, University of WisconsinGreen Bay, Institute for Land and Water Studies.

Harris, H.J., T.R. Bosley, and F.D. Roznik. 1977. Green Bay’s Coastal Wetlands, A Picture of

Dynamic Change. In proceedings of Waukesha Conference on Wetlands, Madison, WI, June 2-5.
Stratus Consulting References (Final, 10/25/00)

Page R-4

Harris, V.A. and J. Christie. 1987. Nutrient and Eutrophication Management Technical Advisory

Committee Report, Lower Green Bay Remedial Action Plan, Wisconsin Department of Natural

Resources. Publ.-WR-167 87. July.

Hensher, D.A. 1994. Stated preference analysis of travel choices: The state of practice.

Transportation 21:107-133.

Herriges, J.A., C.L. Kling, and D.J. Phaneuf. 1999. Corner Solution Models of Recreation

Demand: A Comparison of Competing Frameworks. In Valuing Recreation and the

Environment, J.A. Herriges and C.L. Kling (eds.). Elgar, Northampton, MA. pp. 163-197.

Johnsen, P.K., G.J. Knapp, and L.J. Smith. 1992. Public perceptions and attitudes toward

environmental rehabilitation of the Lower Green Bay watershed. Coastal Management 20:9-23.

Johnson, F.R. and W.H. Desvousges. 1997. Estimating stated preferences with rated-pair data:

Environmental, health, and employment effects of energy programs. Journal of Environmental

Economics and Management 34:79-99.

Katz, E.F. and S. Schuler. 1995. Baseline Survey: Eight Great Lakes States’ Public Knowledge

and Opinions about Great Lakes Issues, Final Report. Prepared for the U.S. Environmental

Protection Agency, Great Lakes National Program Office.

Kline, J. and D. Wichelns. 1996. Measuring public preferences for the environmental amenities

provided by farmland. European Review of Agricultural Economics 23:421-436.

Kopp, R.J. and V.K. Smith. 1993. Valuing Natural Assets: The Economics of Natural Resource

Damage Assessment. Resources for the Future, Washington, DC.

Kopp, R.J., W.W. Pommerehne, and N. Schwarz. 1997. Determining the Value of Non-Marketed

Goods: Economic, Psychologic, and Policy Relevant Aspects of Contingent Valuation Methods.

In Studies in Risk and Uncertainty. W.K. Viscusi (ed.). Kluwer Academic Publishers, Boston.

Krupnick A. and M.L. Cropper. 1992. Effects of information on health risk valuations. Journal

of Risk and Uncertainty 5:29-48.

Lareau, T.J. and D.A. Rae. 1998. Valuing WTP for diesel odor reductions: An application of

contingent ranking technique. Southern Economics Journal 55(3):728-742.

Layton, D.F. and G. Brown. 1998. Application of Stated Preference Methods to a Public Good:

Issues for Discussion. Prepared for the NOAA Workshop on the Application of Stated

Preference Methods to Resource Compensation, Washington, DC. June 1-2.
Stratus Consulting References (Final, 10/25/00)

Page R-5

Lichtkoppler, F.R. and T.W. Blaine. 1999. Environmental awareness and attitudes of Ashtabula

County voters concerning the Ashtabula River Area of Concern: 1996-1997. Journal of Great

Lakes Research 25(3):500-514.

Louviere, J.J. 1988. Conjoint analysis modeling of stated preferences. Journal of Transport

Economics and Policy 10:93-119.

Louviere, J.J. 1992. Experimental choice analysis: Introduction and overview. Journal of

Business Research 24:89-95.

Louviere, J.J. 1994. Conjoint Analysis. In Advances in Marketing Research. R. Bagozzi (ed.).

Blackwell Publishers, Cambridge, MA.

Louviere, J.J. 1996. Combining Revealed and Stated Preference Data: The Rescaling Revolution.

Presented at the Association of Environmental and Resource Economists, Lake Tahoe.

Louviere, J.J. and G. Woodward. 1983. Design and analysis of simulated consumer choice or

allocation experiments: An approach based on aggregated data. Journal of Marketing Research

20:350-367.

Mackenzie, J. 1993. A comparison of contingent preference models. American Journal of

Agricultural Economics 75:593-603.

Magat, W.A., W.K. Viscusi, and J. Huber. 1988. Paired comparison and contingent valuation

approaches to morbidity risk valuation. Journal of Environmental Economics and Management

15:395-411.

Manski, C.F. 1999. Analysis of choice expectations in incomplete scenarios. Journal of Risk and

Uncertainty 19:49-65.

Mathews, K.E., W.H. Desvousges, F.R. Johnson, and M.C. Ruby. 1997. Using Economic

Models to Inform Restoration Decisions: The Lavaca Bay, Texas Experience. TER Technical

Report prepared for presentation at the Conference on Restoration of Lost Human Uses of the

Environment, Washington, DC. May 7-8.

Mathews, K.E., F.R. Johnson, R.W. Dunford, and W.H. Desvousges. 1995. The Potential Role of

Conjoint Analysis in Natural Resource Damage Assessments. TER General Working Paper

No. G-9503.

Matteson, S.W. 1988. Wisconsin Common Tern Recovery Plan. Wisconsin Endangered

Resources Report No. 41, Wisconsin Department of Natural Resources.
Stratus Consulting References (Final, 10/25/00)

Page R-6

Matteson, S.W. and T.C. Erdman. 1992. Lower Green Bay Colonial Waterbird Management

Plan (Draft). Prepared by the Bureau of Endangered Resources at the Wisconsin DNR and the

Museum of Natural History at the University of Wisconsin-Green Bay.

Mazzotta, M. and J. Opaluch. 1995. Decision making when choices are complex: A test of

Heiner’s hypothesis. Land Economics 71(4):500-515.

Mitchell, R.C. and R.T. Carson. 1989. Using Surveys to Value Public Goods: The Contingent

Valuation Method. Resources for the Future, Washington, DC.

Morey, E.R., T. Buchanan, and D.M. Waldman. 1999a. Happy (hypothetical) Trails to You: The

Impact of Trail Characteristics and Access Fees on a Mountain Biker’s Trail Selection and

Consumer’s Surplus. Working paper, University of Colorado, Boulder.

Morey, E.R., K.G. Rossmann, L. Chestnut, and S. Ragland. 1999b. Estimating E[WTP] for

Reducing Acid Deposition Injuries to Cultural Resources: Using Choice Experiments in a Group

Setting to Estimate Passive-Use Values. In Valuing Cultural Heritage: Applying Environmental

Valuation Techniques to Historic Buildings, Monuments and Artifacts, S. Narvud and R.C.

Ready (eds.). Edward Elgar Publishing.

Morikawa T., M. Ben-Akiva, and D. McFadden. 1990. Incorporating Psychometric Data in

Econometric Travel Demand Models. Prepared for the Banff Invitational Symposium on

Consumer Decision Making and Choice Behavior.

Mossman, M.J. 1988. Wisconsin’s Forster’s Tern Recovery Plan. Wisconsin Endangered

Resources Report No. 42, Wisconsin Department of Natural Resources.

NRCS. 1990. “Swampbuster” provision of the Food Security Act, administered by NRCS.

404 Permitting.

Opaluch, J.J., S.K. Swallow, T. Weaver, C.W. Wessells, and D. Wichelns. 1993. Evaluating

impacts from noxious facilities: Including public preferences in current siting mechanisms.

Journal of Environmental Economics and Management 24:41-59.

Piekarski, L. 1989. Choosing between Directory Listed and Random Digit Sampling in Light of

New Demographic Findings. Paper presented at the annual American Association of Public

Opinion Research Conference. May 19.

Pollack, R.A. and T.J. Wales. 1992. Demand System Specification and Estimation. Oxford

University Press, New York.
Stratus Consulting References (Final, 10/25/00)

Page R-7

Rae, D.A. 1983. The Value to Visitors of Improving Visibility as Mesa Verde and Great Smokey

National Parks. In Managing Air Quality and Scenic Resources at National Parks and

Wilderness Areas, R.D. Rowe and L.G. Chestnut (eds.). Boulder, CO: Westview Press.

Rowe, R.D., W.D. Schulze, and W.S. Breffle. 1996. A test for payment card biases. Journal of

Environmental Economics and Management 31:178-85.

Ruby, M.C., F.R. Johnson, and K.E. Mathews. 1998. Just Say ‘No:’ Assessing Opt-Out Options

in a Discrete-Choice Stated-Preferences Survey of Anglers. TER Working Paper T-9801.

Sachs, D. 1999. Unpublished Summary of Water Quality Data from Lower Green Bay, 1993-

1998 presented at Fox-Wolf Basin Surface Water & Shoreland Habitat Monitoring & Research

Workshop, April 20, Lawrence University, Appelton, WI.

Sager, P., B. Harris, and P. Robinson. 1996. Remedial Measures to Restore Submergent Aquatic

Vegetation in Lower Green Bay. Final Report to WDNR. July 31.

Shideler, G.L. 1992. Critical Coastal Wetland Problem Areas along the Michigan-Wisconsin

Shoreline of Lake Michigan, and their Prioritization for Further Study. Open-File Report 92-22.

U.S. Dept. of the Interior, Geological Survey.

Schuman, H. and S. Presser. 1996. Questions and Answers in Attitude Surveys: Experiments on

Question Format, Wording and Content. Second printing. Academic Press, NY.

St. Norbert College Survey Center. 1999. 1999 Fox River Public Opinion Survey. Prepared by

St. Norbert College.

Stoll, J. 1997. Benefits of Contaminated Sediment Remediation. Selected slides from the

presentation to the Great Lakes Protection Fund Project Advisory Board. May 15.

Stoll, J. 2000a. Economic Analysis of Sediment Remediation on the Fox River. Chapter 1, Part II

in Framework Report: Costs and Benefits of Cleaning Up Contaminated Sediments in Great

Lakes Areas of Concern. P. Keillor et al. (eds.). University of Wisconsin Sea Grant Institute.

Stoll, J. 2000b. Results of a Contingent Valuation Survey of the Benefits of Remediation in the

Green Bay Area of Concern. Chapter 20 in Framework Report: Costs and Benefits of Cleaning

up Contaminated Sediments in Great Lakes Areas of Concern. P. Keillor et al. (eds.). University

of Wisconsin Sea Grant Institute.

Stratus Consulting. 1999a. Injuries to Avian Resources, Lower Fox River/Green Bay Natural

Resources Damage Assessment. Prepared for the U.S. Fish and Wildlife Service by Stratus

Consulting Inc., Boulder, CO.
Stratus Consulting References (Final, 10/25/00)

Page R-8

Stratus Consulting. 1999b. Injuries to Fishery Resources, Lower Fox River/Green Bay Natural

Resource Damage Assessment. Prepared for U.S. Fish and Wildlife Service, U.S. Department of

Interior, U.S. Department of Justice, by Stratus Consulting Inc., Boulder, CO. November 8.

Stratus Consulting. 1999c. PCB Pathway Determination for the Lower Fox River/Green Bay

Natural Resource Damage Assessment. Prepared for U.S. Fish and Wildlife Service,

U.S. Department of the Interior, and U.S. Department of Justice by Stratus Consulting Inc.,

Boulder, CO. August 30.

Sullivan, J., J. Delfino, C. Buelow, and T. Sheffy. 1983. Polychlorinated biphenyls in the fish

and sediment of the Lower Fox River, Wisconsin. Bulletin of Environmental Contamination and

Toxicology 30:58-64.

Swait, J. and W. Adamowicz. 2000. Choice Environment, Market Complexity and Consumer

Behavior: A Theoretical and Empirical Approach for Incorporating Decision Complexity into

Models of Consumer Choice. Working paper, University of Florida.

Swait, J., W. Adamowicz, and J. Louviere. 1998. Attribute-Based Stated Choice Methods for

Resource Compensation: An Application to Oil Spill Damage Assessment. Prepared for

presentation at the Natural Resources Trustee Workshop on Applications of Stated Preference

Methods to Resource Compensation, Washington, DC. June 1-2.

ThermoRetec Consulting. 1999. Draft Remedial Investigation: Lower Fox River, WI. Project

No. 3-3584-540. Prepared for Wisconsin Department of Natural Resources. February.

ThermoRetec Consulting. 2000a. Pre-Draft Feasibility Study: Lower Fox River and Green Bay,

Wisconsin Remedial Investigation and Feasibility Study. Prepared for Wisconsin Department of

Natural Resources. September 14.

ThermoRetec Consulting. 2000b. Draft Remedial Investigation: Lower Fox River and Green

Bay, Wisconsin. Prepared for Wisconsin Department of Natural Resources. May.

ThermoRetec Consulting. 2000c. Pre-Draft Baseline Human Health and Ecological Risk

Assessment, Lower Fox River, Wisconsin Remedial Investigation and Feasibility Study.

Prepared for Wisconsin Department of Natural Resources. July 31.

Tourangeau, R., L.J. Ripps, and K. Rasinski. 2000. The Psychology of Survey Responses.

Cambridge University Press, UK.

U.S. Census Bureau. 1990. 1990 Census, State and County Quick Facts.

http://www.census.gov/datamap/www/55.html.
Stratus Consulting References (Final, 10/25/00)

Page R-9

U.S. Census Bureau. 1998. www.census.gov/statab/USA98/55. [Accessed 10/9/00].

U.S. DOI. 1995. The Appropriate Discount Rate of Social Policy Analysis: Discussion and

Estimation. Issue paper 11/22/95. United States Department of Interior

U.S. EPA. 1996. Public Health Implications of PCB Exposures. The Agency for Toxic

Substances and Disease Registry U.S. Department of Health and Human Services, Atlanta,

Georgia, U.S. EPA Washington, D.C. December 1996 —

http://www.epa.gov/reg5oopa/foxriver/lower_fox_river_PCB_Exposures.htm [Accessed

November 5, 1999].

U.S. EPA. 1997. U.S. EPA’s Superfund Role Lower Fox River Cleanup Winnebago, Outagamie,

and Brown Counties, Wisconsin. U.S. EPA Factsheet, July 1997. —

http://www.epa.gov/region5/pdf/lowerfox.pdf. [Accessed 10/9/00].

U.S. EPA. 1998. PCBs: Lower Fox River Impacts. U.S. EPA Factsheet, April 1998. —

http://www.epa.gov/region5/pdf/lf-pcbs.pdf [Accessed November 5, 1999].

U.S. EPA. 1999. Fox River Current, May/June 1999 —

http://www.epa.gov/region5/foxriver/current/june99/index.html. [Accessed 10/9/00].

USGS. 1996. Emergency Wetlands Resources Act (1986). Pages 411-416 National Water

Summary — Wetland Resources, USGS Water Supply Paper W2425.

Viscusi, W.K., W.A. Magat, and J. Huber. 1991. Pricing environmental health risks: Survey

assessments of risk-risk and risk-dollar trade-offs for chronic bronchitis. Journal of

Environmental Economics and Management 21:32-51.

WDNR. 1979. Green Bay West Shores Master Plan Concept Element, Wisconsin Department of

Natural Resources. April.

WDNR. 1987. Wisconsin Waterfowl Consumption Advisory. Wisconsin Department of Natural

Resources.

WDNR. 1988. Lower Green Bay Remedial Action Plan, Wisconsin Department of Natural

Resources.

WDNR. 1993a. Lower Green Bay Remedial Action Plan 1993 Update. Wisconsin Department of

Natural Resources.

WDNR. 1993b. Nonpoint Source Control Plan for the Arrowhead River, Rat River and Daggets

Creek Priority Watershed Project, WDNR Publication WT-331-93.
Stratus Consulting References (Final, 10/25/00)

Page R-10

WDNR. 1994. 1994 Green Bay Habitat Restoration Workshop Summary.

WDNR. 1996a. Nonpoint Source Control Plan for the Branch River Priority Watershed Project:

Project Summary, WDNR Publication WT-450-96.

WDNR. 1996b. Nonpoint Source Control Plan for the Red River/Sturgeon Bay Watershed

Project, WDNR Publication WT-466-96.

WDNR. 1997a. Nonpoint Source Control Plan for the Pensaukee Priority Watershed Project:

Project Summary, WDNR Publication WT-485.

WDNR. 1997b. Nonpoint Source Control Plan for the Duck, Apple and Ashwaubenon Priority

Watershed Project: Project Summary, WDNR Publication WT-494-97.

WDNR. 1997c. Nonpoint Source Control Plan for the Duck, Apple and Ashwaubenon Priority

Watershed Project, WDNR Publication WT-493-97.

WDNR. 1998. Important Health Information for People Eating Fish from Wisconsin Waters.

Wisconsin Division of Health and Wisconsin Department of Natural Resources

PUB No FH824-98.

WDNR. 1999a. DOT Wetland Banking System, Wisconsin wetland acreage facts, Unpublished

handout from Lois Stoerzer, Coordinator, Wisconsin Wetland Inventory, Wisconsin Department

of Natural Resources, Madison.

WDNR. 1999b. Important Health Information for People Eating Fish from Wisconsin Waters.

Wisconsin Division of Health and Wisconsin Department of Natural Resources

PUB No FH824-99.

WDNR. 1999c. Wisconsin Wetlands: 1:24,000 scale wetlands from Wisconsin Department of

Natural Resources. Received 3/18/99.

WDNR/GEO. 1998. GEODISC 2.1, Wisconsin Department of Natural Resources, Geographic

Services Section May 1998.

Westat. 1989. Investigation of Possible Recall/Reference Period Bias in National Surveys of

Fishing, Hunting and Wildlife-Associated Recreation. Westat, Inc. Prepared for the

U.S. Department of Interior, Fish and Wildlife Service, Washington, DC, under Contract

No. 14-16-009-87-008. Rockville, MD. December.
Stratus Consulting References (Final, 10/25/00)

Page R-11

Whittaker, D., J.J. Vaske, and D.S. DeRuiter. 1998. Mail versus telephone surveys: Potential

biases in expenditure and willingness to pay data. Journal of Park and Recreation

Administration 16(3):15-30.

Wisconsin Department of Workforce Development. 2000.

www.dwd.state.wi.us/dwelmi/cp_pdf/cd_mainx.htm [Accessed September 8, 2000.].

Wisconsin Official Population Estimates, County Estimates. 1998.

http://www.doa.state.wi.us/boi.htm [Accessed July 1, 1999].

WLRB. 1997. State of Wisconsin 1997-1998 Blue Book. Joint Committee on Legislative

Organization, Wisconsin Legislature, Wisconsin Legislative Reference Bureau.
Appendix A — Survey Materials
Stratus Consulting Appendix A (Final, 10/25/00)

Page A-2

A.1 Introduction

This appendix includes survey materials, including:

} Initial letter with first mailing

} Mail survey instrument. Note: Only Version 1 is included. All other versions are the same

except that the choice pairs vary across versions.

} Table of choice pairs by survey version

} Follow-up postcard

} Follow-up phone survey script

} Follow-up letters for those reached by phone

} Follow-up letters for those not reached by phone

} Thank you letter

The letters included here do not show the letterhead. For the final hard copy report the letters

with letterhead will be copied and included.

The mail survey included here does not have all the pictures. For the final hard copy report the

mail survey with the pictures will be copied and included.
Initial letter with first mailing

CASEID

<Address>

Dear <Address>:

What should the priorities be for natural resource programs in Northeast Wisconsin?

Representatives from government, industry, and citizen groups are addressing this question right

now in order to develop regional action plans. Informed decisions can only be made if these

decision makers know how citizens like you think about natural resource issues in your area.

The questionnaire included with this letter asks for your household’s opinions on natural resource

issues in Northeast Wisconsin. It should be answered by either the male or female head of

household. Your opinion matters! Your household is part of a small sample of households in

Northeast Wisconsin that were scientifically selected to provide citizen opinions. Because the

sample size is small, it is important that we hear from you. The survey does not require any special

knowledge--we just ask that you consider each question and respond with your own opinion.

We realize this questionnaire takes time to answer and that your time is valuable. If you return the

survey by September 30 and complete all the questions, we will send you a $15 “Thank You”

check. A postage-paid envelope has been provided. As a further thank you for returning a

completed survey, we will also send you a summary of the results later this year.

All of your answers are confidential; your name will never be revealed to anyone. A code number

has been put on the questionnaire so we can send you the $15 check for completing and returning it.

If you have any questions, please call me toll-free at 1-800-935-4277. Thank you for your help, and

please remember to complete all questions.

Sincerely,

Pam Rathbun, Manager

Survey Research Center
WHAT ARE YOUR OPINIONS ABOUT THE

FUTURE OF NATURAL RESOURCES IN

NORTHEAST WISCONSIN?
V1

Important Definition

In this survey “the Bay of Green Bay” means the waters of the

Bay of Green Bay and all tributaries up to the first dam or obstruction.
1

Introduction

Decision makers are examining options for natural resources in northeast Wisconsin. Your

responses to this survey will help in making decisions about which options are best.

How often do you personally participate in each of the following activities in Wisconsin

on the waters and shorelines of the Bay of Green Bay? Circle the letter of your answer for each

activity.

Less than

once a year

or never

1 to 5

times a

year

6 to 10

times a

year

More than

10 times a

year

Fishing . . . . . . . . . . . . . . . . A B C D

Boating (non-fishing) . . . . . A B C D

Waterskiing or jetskiing . . . A B C D

Canoeing or kayaking . . . . . A B C D

Swimming . . . . . . . . . . . . . . A B C D

Hunting . . . . . . . . . . . . . . . . A B C D

Wildlife viewing . . . . . . . . . A B C D

Enjoying outdoor scenery . . A B C D

Camping or picnicking . . . . A B C D

Biking . . . . . . . . . . . . . . . . . A B C D

Hiking, walking, or jogging A B C D

This survey addresses four natural resource topics. The information provided reflects the

most recent scientific reports about these topics.

< Wetlands

< PCBs

< Outdoor recreation

< Runoff

V1
 2

Wetlands

Within 5 miles of the Bay of Green Bay there are about 58,000 acres of wetlands in Wisconsin

(see map on the facing page), and another 86,000 acres in Michigan. These nearby wetlands

are very important to the fish and wildlife of the Bay of Green Bay.

< Farming, cutting forests, and developing residential and urban areas have reduced

wetlands in this area by more than half in the past 100 years.

< Current regulations are designed to prevent further loss of wetlands in this area.

< Programs have been proposed to restore wetlands in this area. Any wetlands

restoration would take about 10 years.

Wetlands around the Bay of Green Bay provide spawning and nursery habitats for a

majority of the fish species in the Bay, including yellow perch, bluegill, largemouth bass,

northern pike, and over 35 other species. These wetlands also provide necessary habitat and

food for many bird species in the Bay area, including terns, many species of ducks and geese,

shorebirds, bald eagles, several species of hawks, coots, and others. Other wildlife such as

deer, muskrat, and mink also use wetlands for habitat.

Increases in wetlands would support nearly proportional increases in the populations of those

bird and fish species that depend on wetlands. For example, increasing wetland acres by 10%

would increase the numbers of those birds and fish that rely on wetlands by about 10%.

How important to you, if at all, is it to increase wetland acreage near to the Bay of Green Bay

to support birds, fish, and other wildlife? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Don’t

know

12 3 4 5 8

V1
 3

Wisconsin Wetlands Within 5 Miles of the Bay of Green Bay

Which of the following options do you prefer for Wisconsin wetlands near to the Bay of

Green Bay? Circle the number of your answer.

 1 Do less and spend less to maintain wetlands, resulting in a loss of wetlands.

 2 Do and spend about the same to maintain the current wetland acreage (about 58,000 acres).

 3 Do more and spend more to restore wetlands. Options to restore wetlands range from

restoring 2,900 acres (5% more than now) to restoring 11,600 acres (20% more than now).

V1
 4

 5

 6

PCBs

PCBs are substances that were used by industry until the mid-1970s, when they were banned.

< PCBs released into the Lower Fox River have accumulated in the sediments at the

bottom of the Lower Fox River and Green Bay.

< PCBs get into fish, birds, and other wildlife through the food chain.

Because of PCBs, consumption advisories have been issued for all sport-caught fish in

Green Bay (including all tributaries up to the first dam) and for some waterfowl in the area.

The fish consumption advisories tell how often a meal of fish may be safely eaten (see table on

the facing page). Eating more fish than is recommended may increase a woman’s risk of

bearing children with learning disabilities and slow development, and for everyone may

increase the risk of cancer.

Programs have been proposed to remove PCBs in this area. How important to you, if at all, is

it to remove PCBs so that it will be safe to eat fish and waterfowl? Circle the number of your

answer.

Not at all

important

Somewhat

important

Very

important

Don’t

know

12 3 4 5 8

PCBs cause harm to wildlife in and near the Bay of Green Bay.

Birds Forester’s terns and common terns in the area reproduce at rates that are about half of

the rate elsewhere in Wisconsin. Both are listed as Wisconsin endangered species.

Bald eagles in the area also reproduce at about half the normal rate for Wisconsin. PCBs

contribute to this problem. Bald eagles are no longer listed as endangered.

A small percentage of cormorants experience deformities such as crossed bills.

Fish About 25% of walleye have abnormalities that can become cancerous liver tumors.

Other Wildlife Some sensitive fish-eating wildlife, like mink, may be harmed.

Even though PCBs harm wildlife, it is unclear whether the total numbers of terns, eagles,

cormorants, walleye, mink and other species in the area are less than if there were no PCBs.

This is because wildlife migrates into and out of the area, because there is limited habitat in

the area for some species, and because other factors influence wildlife populations.

How important to you, if at all, is it to remove PCBs in the Bay of Green Bay area to reduce

harm to birds, fish, and other wildlife? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Don’t

know

12 3 4 5 8

V1

PCB removal would take about 10 years. Any PCB removal would use the best

available technology to minimize stirring up PCBs, and the PCBs that are removed would be

disposed of in a manner that would prevent future risks to humans and wildlife.

Not all PCBs can be removed. The PCBs that are not removed may continue to harm some

fish and wildlife. For example, with extensive PCB removal, fish consumption advisories for

yellow perch and some impacts to wildlife would be eliminated shortly after PCB removal, but

it would be 20 years total (10 years for removal plus 10 more years for nature to recover)
Wisconsin Department of Natural Resources

 Fish Consumption Advisories for PCBs

before PCBs are at safe levels. By safe levels we mean there are no consumption advisories

for, and no harm to, nearly all fish and wildlife.

Which of the following options do you prefer for PCBs in the Green Bay area of Wisconsin?

Circle the number of your answer.

 1 No further PCB investigations or removal. With no further removal it will be 100 years or

more until PCBs are at safe levels.

 2 Do more and spend more to remove PCBs. Depending on how many PCBs are removed, the

time until PCBs are at safe levels would range from 20 years up to 70 years.

V1
 7

 8

Outdoor Recreation

In 10 Wisconsin counties around the Bay of Green Bay, there are over 120 state parks,

natural areas, and county parks covering more than 86,000 acres (see map on the facing

page).

< These parks include a variety of facilities such as picnic grounds, beaches, scenic sites,

piers, boat ramps, biking and hiking trails, and interpretive centers.

< To meet the current and future needs of area residents, programs have been proposed

to add facilities at existing parks and to open new parks.

Adding facilities at existing parks can improve recreational opportunities in these

parks. For example, 10% more facilities would mean that most parks would see

improvements. Some parks would add hiking or biking trails, some parks would add picnic

areas, some parks would add a boat ramp, some parks would add adjacent land, and so forth.

How important to you, if at all, is adding facilities at existing parks throughout the area to

enhance recreational opportunities? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Dont

know

12 3 4 5 8

New parks can be opened throughout the area to increase recreational opportunities.

How important to you, if at all, is opening new parks to enhance outdoor recreational

opportunities? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Dont

know

12 3 4 5 8

V1
 9

State and County Recreation Areas

Any new facilities at existing parks, and any new parks, would be located throughout

the area to best meet the needs of residents and would take up to 10 years to accomplish.

Which of the following options do you prefer for state and county parks in northeast

Wisconsin? Circle the number of your answer.

 1 Do less and spend less to maintain existing outdoor recreation parks.

 2 Do and spend about the same to maintain existing park conditions and facilities.

 3 Do more and spend more to add facilities at existing parks and/or to open new parks.

V1
 10

 11

Runoff

Runoff from farms, highways, construction sites, and residential and urban neighborhoods

carries plant nutrients and sediments into the Bay of Green Bay and its tributaries, causing

algae growth, muddy water, and changes in aquatic habitat (see figure on the facing page).

< Runoff pollution can be reduced by decreasing erosion; controlling farm, urban, and

residential wastes; fencing livestock away from streams; and other measures.

< Zebra mussels (small shellfish) have invaded Green Bay. They filter the water, making

it clearer. However, scientists say we cannot count on zebra mussels to improve water

clarity in the future.

< Runoff is not a significant source of the PCBs in the Lower Fox River and Green Bay

and does not affect the quality of your drinking water.

When too many plant nutrients are present, excess algae coats the surface of the water

with decaying plants and causes a foul odor. The frequency of excess algae varies by location

in the Bay of Green Bay from seldom in the central and northern Bay to up to 80 days a

summer in the southern Bay. Most excess algae occurs from mid-June to mid-September.

How important to you, if at all, is it to control runoff to reduce the number of days with excess

algae in Green Bay? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Dont

know

12 3 4 5 8

Because of sediments and algae, you can only see down into the water about 20 inches

on average in southern Green

 Bay, with clearer water to the north. This not only makes the water look less appealing but

also reduces the light that reaches underwater plants and thus reduces aquatic habitat.

Populations of desirable fish and birds are smaller and carp populations are larger than they

would be otherwise, but scientists cannot yet put numbers on the vegetation and wildlife

effects.

How important to you, if at all, is it to control runoff to improve water clarity? Circle the

number of your answer.

Not at all

important

Somewhat

important

Very

important

Dont

know

12 3 4 5 8

V1
 12

Water Pollution from Runoff

Any actions to reduce runoff would take up to 10 years to reach their goals. Which of

the following options do you prefer for controlling runoff around the Bay of Green Bay?

Circle the number of your answer.

 1 Do less and spend less, resulting in reduced water clarity, increased days of excess algae,

and less aquatic habitat in Green Bay and its tributaries.

 2 Do and spend about the same. In the southern parts of Green Bay, average summer water

clarity would remain about 20 inches, excess algae would occur up to 80 days a summer,

and aquatic habitat would remain the same.

 3 Do more and spend more to control runoff. Options range up to a 50% reduction in runoff.

In the southern parts of Green Bay, this would result in about 34 inches of water clarity,

excess algae up to 40 days per year, and increased aquatic habitat.

V1
What Alternatives Do You Prefer?

In each of the next questions there are two alternatives, labeled A and B (see Question 13).

< Each alternative describes a possible combination of options for natural resources in

and around the Bay of Green Bay and the additional costs to your household beyond

what you are now paying.

< Depending on the options, some costs will be paid by industry, farmers, and

conservation organizations. But taxpayers may have to pay something as well. Assume

your household pays its share of any added costs through a combination of federal,

state, and local taxes each year for the next 10 years.

< Since we do not yet know how much each alternative will actually cost you or others,

we are asking about a range of costs.

< For each question, even if you do not view either Alternative A or B as ideal, still tell us

which of the two alternatives you would prefer.

< To help you get started, for Question 13 we have provided information on the righthand side indicating the differences, if any, between Alternatives A and B.

REMEMBER

1. The goal of wetlands restoration is to provide additional habitat for fish and wildlife.

2. For PCBs, the "years until safe" is the number of years until there are no consumption

advisories for, and no harm to, nearly all fish and wildlife. Many advisories and effects

will end sooner, but a few advisories and effects may last longer.

3. New recreation facilities at existing parks could include rest rooms, trails, boat ramps,

and picnicking and camping facilities. Any new facilities at existing parks and any new

parks would be located to best meet the needs of area residents.

4. Pollution from runoff creates excess algae, reduces water clarity, and causes the loss of

aquatic habitat, all of which occur most often in the southern Bay.

V1
 13 If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Alternative A

ï

Alternative B

ï

Wetlands

 Acres in Wisc. around Green

Bay.

 (Currently 58,000)

58,000 acres

(current)

69,600 acres

(20% more)

11,600

more acres in

wetlands

PCBs

 Years until safe for nearly all

 fish and wildlife . . . . . . . . . . . .

 (Currently 100 years or more)

100+ years until safe

(current)

100+ years until safe

(current) No difference

Outdoor Recreation

 Facilities at existing parks . . . . . .

Acres in new parks. . . . . . . . . . . . . .

 (Currently 86,000 acres in state

 and county parks)

10% more

0 acres

(current)

0% more

0 acres

(current)

10% more

facilities at

existing parks

No difference

Runoff

 Average water clarity in southern

 Bay (Currently 20 inches) . . . . . .

 Excess algae (Currently up to 80

 summer days in the southern Bay)

20 inches

(current)

80 days or less

(current)

20 inches

(current)

80 days or less

(current)

No difference

No difference

Added cost to your household

 Each year for 10 years. . . . . . . . . $25 more $25 more No difference

Check (U) the box for

 the alternative you prefer Û ñ

I Prefer

Alternative A

ñ

I Prefer

Alternative B

V1
 14 If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Alternative A

ï

Alternative B

ï

Wetlands

 Acres . . . . . . . . . . . . . . . . . . . . .

 

58,000 acres

(current)

58,000 acres

(current)

PCBs

 Years until safe for nearly all

fish and wildlife . . . . . . . . . . . . . . .

.

40 years until safe

(60% faster)

100+ years until safe

(current)

Outdoor Recreation

 Facilities at existing parks. . . . .

 Acres in new parks . . . . . . . . . . .

0% more

0 acres

(current)

0% more

0 acres

(current)

Runoff

 Average water clarity in the

 southern Bay . . . . . . . . . . . . . . .

 Excess algae days in lower Bay .

.

20 inches

(current)

80 days or less

(current)

20 inches

(current)

80 days or less

(current)

Added cost to your household

 Each year for 10 years . . . . . . . . $200 more $0 more

Check (U) the box for the

alternative you prefer Û ñ ñ

V1
 15 If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Alternative A

ï

Alternative B

ï

Wetlands

 Acres . . . . . . . . . . . . . . . . . . . . .

 

60,900 acres

(5% more)

63,800 acres

(10% more)

PCBs

 Years until safe for nearly all

fish

 and wildlife . . . . . . . . . . . . . . . .

100+ years until safe

(current)

20 years until safe

(80% faster)

Outdoor Recreation

 Facilities at existing parks . . . . .

 Acres in new parks . . . . . .. . . .

0% more

0 acres

(current)

10% more

8,600 acres

(10% more)

Runoff

 Average water clarity in the

 southern Bay . . . . . . . . . . . . . . .

 Excess algae days in lower Bay.

.

20 inches

(current)

80 days or less

(current)

24 inches

(20% deeper)

60 days or less

(25% fewer)

Added cost to your household

 Each year for 10 years . . . . . . . . $50 more $200 more

Check (U) the box for the

alternative you prefer Û ñ ñ

V1
 16 If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Alternative A

ï

Alternative B

ï

Wetlands

 Acres . . . . . . . . . . . . . . . . . . . . .

 

58,000 acres

(current)

58,000 acres

(current)

PCBs

 Years until safe for nearly all

fish

 and wildlife . . . . . . . . . . . . . . . .

100+ years until safe

(current)

40 years until safe

(60% faster)

Outdoor Recreation

 Facilities at existing parks . . . . .

 Acres in new parks . . . . . . . . .

10% more

0 acres

(current)

0% more

0 acres

(current)

Runoff

 Average water clarity in the

 southern Bay . . . . . . . . . . . . . . .

 Excess algae days in lower Bay .

34 inches

(70% deeper)

40 days or less

(50% fewer)

20 inches

(current)

80 days or less

(current)

Added cost to your household

 Each year for 10 years . . . . . . . . $50 more $50 more

Check (U) the box for the

alternative you prefer Û ñ ñ

V1
 17 If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Alternative A

ï

Alternative B

ï

Wetlands

 Acres . . . . . . . . . . . . . . . . .

 

69,600 acres

(20% more)

69,600 acres

(20% more)

PCBs

 Years until safe for nearly all

fish

 and wildlife . . . . . . . . . . . . . . . .

40 years until safe

(60% faster)

100+ years until safe

(current)

Outdoor Recreation

 Facilities at existing parks . . . .

 Acres in new parks . . . .. . . . . .

0% more

4,300 acres

(5% more)

10% more

4,300 acres

(5% more)

Runoff

 Average water clarity in the

 southern Bay . . . . . . . . . . . . . . .

 Excess algae days in lower Bay

.

34 inches

(70% deeper)

40 days or less

(50% fewer)

24 inches

(20% deeper)

60 days or less

(25% fewer)

Added cost to your household

 Each year for 10 years . . .. . . . . $100 more $50 more

Check (U) the box for the

alternative you prefer Û ñ ñ

V1
 18 If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Alternative A

ï

Alternative B

ï

Wetlands

 Acres . . . . . . . . . . . . . . . . . . . . .

 

63,800 acres

(10% more)

60,900 acres

(5% more)

PCBs

 Years until safe for nearly all

fish and wildlife . . . . . . . . . . . . . . .

.

20 years until safe

(80% faster)

70 years until safe

(30% faster)

Outdoor Recreation

 Facilities at existing parks . . . . .

 Acres in new parks . . . . . . . . .

0% more

4,300 acres

(5% more)

0% more

8,600 acres

(10% more)

Runoff

 Average water clarity in the

 southern Bay . . . . . . . . . . . . . .

 Excess algae days in lower Bay.

.

20 inches

(current)

80 days or less

(current)

34 inches

(70% deeper)

40 days or less

(50% fewer)

Added cost to your household

 Each year for 10 years . . . . . . . . $50 more $25 more

Check (U) the box for the

alternative you prefer Û ñ ñ

V1
 19

 20

 21

When you were making your choices between alternatives A and B in Questions 13

through 18, how important were each of the following? Circle the number of your

answer for each item.

Not at all

important

Average

importance

Very

important

Acres of wetland . . . . . . . . . . . . . . . 1 2 3 4 5

Years until safe levels of PCBs . . . . 1 2 3 4 5

Facilities at existing parks . . . . . . . . . 1 2 3 4 5

Acres of new parks . . . . . . . . . . . . . . 1 2 3 4 5

Inches of water clarity . . . . . . . . . . . 1 2 3 4 5

Days of excess algae each summer. . . 1 2 3 4 5

Annual cost to your household . . . . . 1 2 3 4 5

Overall, how confident do you feel about your choices between the alternatives in

Questions 13 through 18? Circle the number of your answer.

Not at all

confident

Somewhat

confident

Very

confident

12345

Questions 13 through 18 were asked to provide citizen input for decision makers to

consider along with other information from scientists and planners. With this in mind,

how much should public officials consider your responses to Questions 13 through 18?

Circle the number of your answer.

Should not

consider my

responses at all

Should somewhat

consider my

responses

Should completely

consider my

responses

12 34 5

V1
 22

 23

Prior to receiving this survey, how aware were you of each of the four natural resource

topics we addressed? Circle the number of your answer for each topic.

I was not

aware of this

topic

I was somewhat

aware of this

topic

I was very

aware of this

topic

Wetlands . . . . . . . . . . . . . . 1 2 3 4 5

PCBs . . . . . . . . . . . . . . . . 1 2 3 4 5

Outdoor recreation . . . . . . 1 2 3 4 5

Runoff . . . . . . . . . . . . . . . 1 2 3 4 5

About You and Your Household

This information is used to help group your responses with responses of other households.

Your individual responses and your name will not be released.

In the last 12 months, have you fished in Green Bay or its tributaries up to the first

dam (see map on the cover)? Circle the number of your answer.

1 No (If no) in the last 12 months, have other household members fished in

Green Bay or its tributaries up to the first dam? Circle the number of

your answer.

1 No

2 Yes

3 Dont know/Uncertain

2 Yes (If yes) in the last 12 months, on about how many days have you fished

in Green Bay or its tributaries up to the first dam?

 Days

V1
 24

 25

 26

 27

 28

 29

 30

 31

Do you own or rent your residence? Circle the number of your answer.

1 Own

2 Rent

Do you have a vacation home or cabin in northeast Wisconsin? Circle the number of

your answer.

1 Yes (If yes) about how many miles is it from your vacation home or cabin to

the Bay of Green Bay?

 _______ Miles to Green Bay

2 No

Your gender: 1 Female

2 Male

Your age: Years old

How many people are there in your household, including yourself?

 number

How many children do you have, whether living with you or not?

 number

How many grandchildren do you have, whether living with you or not?

 number

How many listed telephone numbers does your household have?

 listed telephone numbers

V1
 33

 34

 35

 32 What is the highest level of schooling you have completed? Circle the number of your

answer.

1 Did not complete high school

2 High school diploma or equivalent

3 Some college, two year college degree (AS) or technical school

4 Four year college graduate (BA, BS)

5 Some graduate work but did not receive a graduate degree

6 Graduate degree (MA, MS, MBA, PhD, JD, MD, etc.)

What is you present employment status? Circle the number of your answer.

1 Employed full time 4 Homemaker

2 Employed part time 5 Student

3 Retired 6 Unemployed

Which of the following categories best describes your racial or ethnic background?

Circle the number of your answer.

1 White or Caucasian 4 Asian or Pacific Islander

2 Black or African American 5 Native American Indian

3 Hispanic or Mexican American 6 Other: 

What was your household income (before taxes) in 1998? Circle the number of your

answer.

1 less than $10,000 6 $50,000 to $59,999

2 $10,000 to $19,999 7 $60,000 to $79,999

3 $20,000 to $29,999 8 $80,000 to $99,999

4 $30,000 to $39,999 9 $100,000 to $149,999

5 $40,000 to $49,999 10 $150,000 or more

V1
 36 Is there anything we have overlooked? Please use this space for any additional

comments you would like to make.

Your Participation Is Greatly Appreciated!

Please return the survey in the enclosed envelope to:

Hagler Bailly Services

University Research Park

455 Science Drive

Madison, Wisconsin 53711

V1
Table of choice pairs by survey version

Table A-1

Version 1 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 69600 58000 58000

Change in Wetlands current 20 % more current current

PCBs - Years Until Safe 100+ 100+ 40 100+

Percent Increase in Facilities at Existing Parks 10 0 0 0

Acres in New Parks 0 0 0 0

Change in Acres in Parks current current current current

Inches of Average Water Clarity 20 20 20 20

Change in Water Clarity current current current current

Excess Algae Days in Lower bay 80 80 80 80

Change in Excess Algae Days current current current current

Added Cost to Household for 10 Years 25 25 200 0

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 60900 63800 58000 58000

Change in Wetlands 5% more 10% more current current

PCBs - Years Until Safe 100+ 20 100+ 40

Percent Increase in Facilities at Existing Parks 0 10 10 0

Acres in New Parks 0 8600 0 0

Change in Acres in Parks current 10% more current current

Inches of Average Water Clarity 20 24 34 20

Change in Water Clarity current 20% deeper 70% deeper current

Excess Algae Days in Lower bay 80 60 40 80

Change in Excess Algae Days current 25% fewer 50% fewer current

Added Cost to Household for 10 Years 50 200 50 50

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 69600 69600 63800 60900

Change in Wetlands 20 % more 20 % more 10% more 5% more

PCBs - Years Until Safe 40 100+ 20 70

Percent Increase in Facilities at Existing Parks 0 10 0 0

Acres in New Parks 4300 4300 4300 8600

Change in Acres in Parks 5% more 5% more 5% more 10% more

Inches of Average Water Clarity 34 24 20 34

Change in Water Clarity 70% deeper 20% deeper current 70% deeper

Excess Algae Days in Lower bay 40 60 80 40

Change in Excess Algae Days 50% fewer 25% fewer current 50% fewer

Added Cost to Household for 10 Years 100 50 50 25
Table A-2

Version 2 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 60900 58000 58000

Change in Wetlands current 5% more current current

PCBs - Years Until Safe 100+ 100+ 100+ 20

Percent Increase in Facilities at Existing Parks 0 0 0 0

Acres in New Parks 4300 0 0 0

Change in Acres in Parks 5% more current current current

Inches of Average Water Clarity 20 20 20 20

Change in Water Clarity current current current current

Excess Algae Days in Lower bay 80 80 80 80

Change in Excess Algae Days current current current current

Added Cost to Household for 10 Years 25 25 0 50

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 63800 63800 63800

Change in Wetlands current 10% more 10% more 10% more

PCBs - Years Until Safe 70 70 100+ 70

Percent Increase in Facilities at Existing Parks 10 0 10 0

Acres in New Parks 4300 8600 8600 4300

Change in Acres in Parks 5% more 10% more 10% more 5% more

Inches of Average Water Clarity 24 20 20 24

Change in Water Clarity 20% deeper current current 20% deeper

Excess Algae Days in Lower bay 60 80 80 60

Change in Excess Algae Days 25% fewer current current 25% fewer

Added Cost to Household for 10 Years 25 200 200 50

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 69600 63800 63800 60900

Change in Wetlands 20 % more 10% more 10% more 5% more

PCBs - Years Until Safe 20 40 40 20

Percent Increase in Facilities at Existing Parks 0 10 10 10

Acres in New Parks 4300 4300 0 0

Change in Acres in Parks 5% more 5% more current current

Inches of Average Water Clarity 34 34 34 34

Change in Water Clarity 70% deeper 70% deeper 70% deeper 70% deeper

Excess Algae Days in Lower bay 40 40 40 40

Change in Excess Algae Days 50% fewer 50% fewer 50% fewer 50% fewer

Added Cost to Household for 10 Years 100 100 100 200
Table A-3

Version 3 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 58000 58000 69600

Change in Wetlands current current current 20 % more

PCBs - Years Until Safe 100+ 100+ 100+ 100+

Percent Increase in Facilities at Existing Parks 0 10 0 0

Acres in New Parks 8600 0 0 0

Change in Acres in Parks 10% more current current current

Inches of Average Water Clarity 20 20 20 20

Change in Water Clarity current current current current

Excess Algae Days in Lower bay 80 80 80 80

Change in Excess Algae Days current current current current

Added Cost to Household for 10 Years 25 25 0 50

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 69600 69600 63800 63800

Change in Wetlands 20 % more 20 % more 10% more 10% more

PCBs - Years Until Safe 100+ 20 70 40

Percent Increase in Facilities at Existing Parks 10 0 10 10

Acres in New Parks 8600 8600 4300 0

Change in Acres in Parks 10% more 10% more 5% more current

Inches of Average Water Clarity 24 34 20 20

Change in Water Clarity 20% deeper 70% deeper current current

Excess Algae Days in Lower bay 60 40 80 80

Change in Excess Algae Days 25% fewer 50% fewer current current

Added Cost to Household for 10 Years 50 200 100 100

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 60900 60900 58000 69600

Change in Wetlands 5% more 5% more current 20 % more

PCBs - Years Until Safe 20 40 40 70

Percent Increase in Facilities at Existing Parks 0 0 0 10

Acres in New Parks 0 8600 8600 0

Change in Acres in Parks current 10% more 10% more current

Inches of Average Water Clarity 34 24 24 34

Change in Water Clarity 70% deeper 20% deeper 20% deeper 70% deeper

Excess Algae Days in Lower bay 40 60 60 40

Change in Excess Algae Days 50% fewer 25% fewer 25% fewer 50% fewer

Added Cost to Household for 10 Years 25 100 200 100
Table A-4

Version 4 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 58000 58000 58000

Change in Wetlands current current current current

PCBs - Years Until Safe 100+ 100+ 20 100+

Percent Increase in Facilities at Existing Parks 10 0 0 0

Acres in New Parks 0 0 0 0

Change in Acres in Parks current current current current

Inches of Average Water Clarity 20 34 20 20

Change in Water Clarity current 70% deeper current current

Excess Algae Days in Lower bay 80 40 80 80

Change in Excess Algae Days current 50% fewer current current

Added Cost to Household for 10 Years 25 25 200 0

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 60900 63800 69600

Change in Wetlands current 5% more 10% more 20 % more

PCBs - Years Until Safe 70 100+ 20 70

Percent Increase in Facilities at Existing Parks 10 0 0 0

Acres in New Parks 8600 4300 4300 8600

Change in Acres in Parks 10% more 5% more 5% more 10% more

Inches of Average Water Clarity 34 24 34 24

Change in Water Clarity 70% deeper 20% deeper 70% deeper 20% deeper

Excess Algae Days in Lower bay 40 60 40 60

Change in Excess Algae Days 50% fewer 25% fewer 50% fewer 25% fewer

Added Cost to Household for 10 Years 50 200 200 25

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 69600 60900 60900 69600

Change in Wetlands 20 % more 5% more 5% more 20 % more

PCBs - Years Until Safe 70 40 70 70

Percent Increase in Facilities at Existing Parks 0 10 10 10

Acres in New Parks 8600 8600 0 0

Change in Acres in Parks 10% more 10% more current current

Inches of Average Water Clarity 20 20 34 24

Change in Water Clarity current current 70% deeper 20% deeper

Excess Algae Days in Lower bay 80 80 40 60

Change in Excess Algae Days current current 50% fewer 25% fewer

Added Cost to Household for 10 Years 200 50 50 50
Table A-5

Version 5 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 58000 58000 58000

Change in Wetlands current current current current

PCBs - Years Until Safe 100+ 100+ 40 100+

Percent Increase in Facilities at Existing Parks 0 0 0 0

Acres in New Parks 8600 0 0 0

Change in Acres in Parks 10% more current current current

Inches of Average Water Clarity 20 24 20 20

Change in Water Clarity current 20% deeper current current

Excess Algae Days in Lower bay 80 60 80 80

Change in Excess Algae Days current 25% fewer current current

Added Cost to Household for 10 Years 25 25 50 0

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 58000 60900 58000

Change in Wetlands current current 5% more current

PCBs - Years Until Safe 40 20 70 40

Percent Increase in Facilities at Existing Parks 10 0 0 0

Acres in New Parks 0 0 8600 0

Change in Acres in Parks current current 10% more current

Inches of Average Water Clarity 20 20 24 24

Change in Water Clarity current current 20% deeper 20% deeper

Excess Algae Days in Lower bay 80 80 60 60

Change in Excess Algae Days current current 25% fewer 25% fewer

Added Cost to Household for 10 Years 50 50 100 25

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 63800 60900 63800 58000

Change in Wetlands 10% more 5% more 10% more current

PCBs - Years Until Safe 70 70 70 20

Percent Increase in Facilities at Existing Parks 0 10 10 0

Acres in New Parks 0 4300 0 0

Change in Acres in Parks current 5% more current current

Inches of Average Water Clarity 34 20 20 20

Change in Water Clarity 70% deeper current current current

Excess Algae Days in Lower bay 40 80 80 80

Change in Excess Algae Days 50% fewer current current current

Added Cost to Household for 10 Years 50 25 50 50
Table A-6

Version 6 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 69600 58000 63800

Change in Wetlands current 20 % more current 10% more

PCBs - Years Until Safe 20 100+ 100+ 100+

Percent Increase in Facilities at Existing Parks 0 0 0 0

Acres in New Parks 0 0 0 0

Change in Acres in Parks current current current current

Inches of Average Water Clarity 20 20 20 20

Change in Water Clarity current current current current

Excess Algae Days in Lower bay 80 80 80 80

Change in Excess Algae Days current current current current

Added Cost to Household for 10 Years 50 50 0 25

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 69600 69600 69600 60900

Change in Wetlands 20 % more 20 % more 20 % more 5% more

PCBs - Years Until Safe 20 40 40 70

Percent Increase in Facilities at Existing Parks 10 0 10 10

Acres in New Parks 0 4300 0 8600

Change in Acres in Parks current 5% more current 10% more

Inches of Average Water Clarity 20 34 24 24

Change in Water Clarity current 70% deeper 20% deeper 20% deeper

Excess Algae Days in Lower bay 80 40 60 60

Change in Excess Algae Days current 50% fewer 25% fewer 25% fewer

Added Cost to Household for 10 Years 100 100 50 100

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 60900 63800 69600 58000

Change in Wetlands 5% more 10% more 20 % more current

PCBs - Years Until Safe 70 100+ 100+ 20

Percent Increase in Facilities at Existing Parks 10 0 10 0

Acres in New Parks 4300 0 8600 0

Change in Acres in Parks 5% more current 10% more current

Inches of Average Water Clarity 24 34 34 20

Change in Water Clarity 20% deeper 70% deeper 70% deeper current

Excess Algae Days in Lower bay 60 40 40 80

Change in Excess Algae Days 25% fewer 50% fewer 50% fewer current

Added Cost to Household for 10 Years 200 50 200 200
Table A-7

Version 7 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 69600 58000 58000

Change in Wetlands current 20 % more current current

PCBs - Years Until Safe 100+ 100+ 100+ 100+

Percent Increase in Facilities at Existing Parks 0 0 0 10

Acres in New Parks 0 0 0 0

Change in Acres in Parks current current current current

Inches of Average Water Clarity 34 20 20 20

Change in Water Clarity 70% deeper current current current

Excess Algae Days in Lower bay 40 80 80 80

Change in Excess Algae Days 50% fewer current current current

Added Cost to Household for 10 Years 50 50 0 50

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 60900 69600 58000 58000

Change in Wetlands 5% more 20 % more current current

PCBs - Years Until Safe 40 20 70 40

Percent Increase in Facilities at Existing Parks 10 0 10 0

Acres in New Parks 4300 8600 4300 0

Change in Acres in Parks 5% more 10% more 5% more current

Inches of Average Water Clarity 20 20 20 20

Change in Water Clarity current current current current

Excess Algae Days in Lower bay 80 80 80 80

Change in Excess Algae Days current current current current

Added Cost to Household for 10 Years 50 100 25 25

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 63800 63800 69600 63800

Change in Wetlands 10% more 10% more 20 % more 10% more

PCBs - Years Until Safe 40 20 100+ 20

Percent Increase in Facilities at Existing Parks 0 10 10 10

Acres in New Parks 0 4300 8600 0

Change in Acres in Parks current 5% more 10% more current

Inches of Average Water Clarity 24 24 20 24

Change in Water Clarity 20% deeper 20% deeper current 20% deeper

Excess Algae Days in Lower bay 60 60 80 60

Change in Excess Algae Days 25% fewer 25% fewer current 25% fewer

Added Cost to Household for 10 Years 25 50 50 100
Table A-8

Version 8 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 69600 58000 58000

Change in Wetlands current 20 % more current current

PCBs - Years Until Safe 40 100+ 100+ 100+

Percent Increase in Facilities at Existing Parks 0 0 0 0

Acres in New Parks 0 0 0 4300

Change in Acres in Parks current current current 5% more

Inches of Average Water Clarity 20 20 20 20

Change in Water Clarity current current current current

Excess Algae Days in Lower bay 80 80 80 80

Change in Excess Algae Days current current current current

Added Cost to Household for 10 Years 50 50 0 100

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 60900 58000 69600 60900

Change in Wetlands 5% more current 20 % more 5% more

PCBs - Years Until Safe 40 20 100+ 70

Percent Increase in Facilities at Existing Parks 10 0 0 0

Acres in New Parks 0 0 4300 0

Change in Acres in Parks current current 5% more current

Inches of Average Water Clarity 20 20 20 24

Change in Water Clarity current current current 20% deeper

Excess Algae Days in Lower bay 80 80 80 60

Change in Excess Algae Days current current current 25% fewer

Added Cost to Household for 10 Years 50 50 100 200

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 60900 69600 63800 58000

Change in Wetlands 5% more 20 % more 10% more current

PCBs - Years Until Safe 40 40 20 100+

Percent Increase in Facilities at Existing Parks 0 10 10 10

Acres in New Parks 8600 4300 8600 8600

Change in Acres in Parks 10% more 5% more 10% more 10% more

Inches of Average Water Clarity 20 34 34 20

Change in Water Clarity current 70% deeper 70% deeper current

Excess Algae Days in Lower bay 80 40 40 80

Change in Excess Algae Days current 50% fewer 50% fewer current

Added Cost to Household for 10 Years 25 200 100 50
Table A-9

Version 9 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 58000 58000 58000

Change in Wetlands current current current current

PCBs - Years Until Safe 100+ 70 100+ 100+

Percent Increase in Facilities at Existing Parks 0 0 0 0

Acres in New Parks 0 0 0 8600

Change in Acres in Parks current current current 10% more

Inches of Average Water Clarity 24 20 20 20

Change in Water Clarity 20% deeper current current current

Excess Algae Days in Lower bay 60 80 80 80

Change in Excess Algae Days 25% fewer current current current

Added Cost to Household for 10 Years 25 25 0 50

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 58000 58000 58000

Change in Wetlands current current current current

PCBs - Years Until Safe 20 70 40 20

Percent Increase in Facilities at Existing Parks 0 0 10 0

Acres in New Parks 0 8600 0 0

Change in Acres in Parks current 10% more current current

Inches of Average Water Clarity 20 20 24 20

Change in Water Clarity current current 20% deeper current

Excess Algae Days in Lower bay 80 80 60 80

Change in Excess Algae Days current current 25% fewer current

Added Cost to Household for 10 Years 50 100 50 50

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 63800 60900 63800

Change in Wetlands current 10% more 5% more 10% more

PCBs - Years Until Safe 70 current 40 70

Percent Increase in Facilities at Existing Parks 0 0 0 0

Acres in New Parks 0 0 8600 8600

Change in Acres in Parks current current 10% more 10% more

Inches of Average Water Clarity 20 20 34 20

Change in Water Clarity current current 70% deeper current

Excess Algae Days in Lower bay 80 80 40 80

Change in Excess Algae Days current current 50% fewer current

Added Cost to Household for 10 Years 25 25 100 25
Table A-10

Version 10 Choice Sets

Question 13 Question 14

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 58000 58000 58000

Change in Wetlands current current current current

PCBs - Years Until Safe 40 100+ 100+ 100+

Percent Increase in Facilities at Existing Parks 0 0 0 0

Acres in New Parks 0 0 0 0

Change in Acres in Parks current current current current

Inches of Average Water Clarity 20 34 20 24

Change in Water Clarity current 70% deeper current 20% deeper

Excess Algae Days in Lower bay 80 40 80 60

Change in Excess Algae Days current 50% fewer current 25% fewer

Added Cost to Household for 10 Years 50 50 0 25

Question 15 Question 16

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 63800 63800 58000

Change in Wetlands current 10% more 10% more current

PCBs - Years Until Safe 40 100+ 40 40

Percent Increase in Facilities at Existing Parks 0 10 0 0

Acres in New Parks 0 8600 4300 8600

Change in Acres in Parks current 10% more 5% more 10% more

Inches of Average Water Clarity 24 34 24 24

Change in Water Clarity 20% deeper 70% deeper 20% deeper 20% deeper

Excess Algae Days in Lower bay 60 40 60 60

Change in Excess Algae Days 25% fewer 50% fewer 25% fewer 25% fewer

Added Cost to Household for 10 Years 100 100 50 100

Question 17 Question 18

Alternative A Alternative B Alternative A Alternative B

Wetlands - Acres 58000 58000 69600 60900

Change in Wetlands current current 20 % more 5% more

PCBs - Years Until Safe 20 70 70 20

Percent Increase in Facilities at Existing Parks 0 10 0 0

Acres in New Parks 0 0 8600 0

Change in Acres in Parks current current 10% more current

Inches of Average Water Clarity 20 20 34 20

Change in Water Clarity current current 70% deeper current

Excess Algae Days in Lower bay 80 80 40 80

Change in Excess Algae Days current current 50% fewer current

Added Cost to Household for 10 Years 50 50 25 100
Follow-up postcard

Hello,

A few days ago you should have received a questionnaire asking for your opinions about natural resources in Northeast

Wisconsin. If you have already completed and returned the questionnaire, accept our sincere thanks. You will soon

receive your $15 “Thank You” check. If you have not completed and returned the questionnaire, we ask that you do so

today.

It is very important that we hear from you. Your response will help shape decisions being made on natural resource

priorities. We cannot survey all households in Northeast Wisconsin, so your responses will represent other households

like yours that were not selected for the study. If you need another copy of the questionnaire, please call us at 1-800-

935-4277 and we will mail another one. As a thank you for returning the questionnaire with all questions completed,

we will send you a $15 “Thank You” check and a summary of the study results. Please return the survey by September

30. 

Thank you for your help with this important study.

Pam Rathbun, Manager

Survey Research Center
Follow-up phone survey script

Hello, my name is ________________ and I am calling from the Hagler Bailly Survey Research

Center in Madison, Wisconsin. I am trying to reach [respondent name].

[IF RESPONDENT IS NOT AVAILABLE:]

Is there another adult head of household that I could speak to?

[If concerned about purpose of the call] This is not a marketing or sales call. We are collecting

citizen input for government, industry, and citizen groups to consider when developing action plans

for natural resources in Northeast Wisconsin. I want to assure you that your answers will be kept

confidential and your name will not be revealed to anyone.

[If asking about the study sponsor] In order not to bias the responses to the survey, the sponsor is

confidential until the results are released to government, industry and the general public later this

fall. You will be mailed a summary of the results at that time.

[Response to: “The response date passed”.] Because receiving responses from every household in

our sample is important, we have extended the response date to October 16 (NOTE: this will

change if calling goes into next week). If we mail the survey again tomorrow, can you complete it

and return it in a week?

[Response to: “Why are you paying $15?”]

The survey is very important and we find we can get more citizen input for less money this way.

More people return the survey faster, so we don’t have to contact as many households, and contact

you as often, to get an accurate sample of the public’s input.

[If correct respondent is on the phone]

QA Recently, we mailed you a questionnaire asking your opinions about the future of natural

resources in Northeast Wisconsin and offered to pay $15 for an adult head of your household

to complete the survey. The survey had a map of northeast Wisconsin on the cover and some

color graphics inside. Do you remember receiving that questionnaire?

1 YES

2 NO [SKIP TO QA2]
QA1 As of today, we have not received your completed questionnaire. Your household is part of

a small group of people we are asking for opinions, so your response is very important. We

are extending the deadline for completing the survey, and receiving $15 as a thank you for

your time and effort. If we send you another survey, could you find the time to complete

the survey and return it to us within a week of receiving it?

1 YES – SEND NEW SURVEY [SKIP TO VERIFY]

2 YES – DO NOT NEED ANOTHER SURVEY [THANK AND TERMINATE]

3 SURVEY HAS ALREADY BEEN RETURNED [THANK AND TERMINATE]

4 NO [SKIP TO QB]

QA2 We are collecting citizen input for government, industry, and citizen groups to consider

when developing actions plans for natural resources in Northeast Wisconsin. Your

household is part of a small group of people we are asking for opinions, so your response is

very important. If we send you another survey, could you return the survey to us within a

week after you receive it? We will send you $15 as a thank you for your time and effort.

1 YES – SEND NEW SURVEY [SKIP TO VERIFY]

2 YES – DO NOT NEED ANOTHER SURVEY [THANK AND TERMINATE]

3 SURVEY HAS ALREADY BEEN RETURNED [THANK AND TERMINATE]

4 NO [SKIP TO QA2A]

QA2A Since we only sampled a small number of households, it is very important that we hear from

your household. Your opinions will represent those of other households similar to you. Is

there another adult head of household that would be interested in completing the survey for

$15?

1 YES, GETTING THEM TO THE PHONE [REPEAT QA2]

2 YES, BUT NOT AVAILABLE AT THIS TIME [SET CALLBACK]

3 NO [SKIP TO QB]

QB It is very important for our preliminary analysis that we understand how those who haven’t

returned the survey compare to those who did. This way we will not misinterpret the results.

Could I take about 5 minutes to ask you a few questions? I’d like to remind you that all of

your answers are confidential and your name will not be revealed to anyone.

1 YES [SKIP TO Q1]

2 NO [ASK FOR A MORE CONVENIENT TIME, OTHERWISE, THANK AND

TERMINATE]

VERIFY (If new survey needs to be sent) I would like to verify some information that I have.
I have your name as...

NAME____________________________________________________

STREET ADDRESS_________________________________________

CITY__________________________STATE _______ ZIP__________

PHONE___________________________________________________

Q1 In the last 12 months, have you fished in Green Bay or in rivers or streams near where they

enter Green Bay?

1 YES [SKIP TO Q1A]

2 NO [SKIP TO Q1B]

8 DON’T KNOW [SKIP TO Q1B]

9 REFUSED [SKIP TO Q1B]

Q1A In the last 12 months, how often did you fish in the Bay of Green Bay or rivers or streams

that enter into the Bay of Green Bay? Would it be...

1 LESS THAN 5 DAYS,

2 5 TO 10 DAYS, OR

3 MORE THAN 10 DAYS?

8 DON’T KNOW

9 REFUSED

Q1B In the last 12 months, have OTHER household members fished Green Bay or rivers or

streams near where they enter Green Bay?

1 YES

2 NO

8 DON’T KNOW

9 REFUSED
Q2 How often do you participate in each of the following 3 activities in the waters or on the

shorelines of the Bay of Green Bay and the rivers or streams near to where they feed into

Green Bay. For each activity, tell me if you participate in the activity just around the Bay of

Green Bay once a year or less often, about 1 to 5 times a year, or more than 5 times a year.

Q2a Wildlife viewing or enjoying the scenery

Q2b Camping or picnicking

Q2c Biking, hiking, walking, or jogging

1 ONCE A YEAR OR LESS

2 1 TO 5 TIMES A YEAR

3 MORE THAN 5 TIMES A YEAR

8 DON’T KNOW

9 REFUSED

Q3 Next, I am going to read you a list of 4 actions that may be taken to enhance natural

resources in Northeast Wisconsin. After I read the list, we will go back through them one by

one and I will want you to rate the importance to you of the action on a 1 to 5 scale, where 1

equals not at all important, 3 is somewhat important, and 5 is very important.

1. increase wetland and other habitat around the Bay of Green Bay to support increased

populations of birds, fish and other wildlife.

2. remove PCBs in the Lower Fox River and the Bay of Green Bay so that consumption

advisories on fish and waterfowl can be removed.

3. remove PCBs in the Lower Fox River and the Bay of Green Bay to reduce risks to birds,

fish and other wildlife.

4. add new facilities at existing state and county parks throughout a 10 county Northeast

Wisconsin area (new facilities may include boat launches, picnic areas, hiking and

biking trails, and the like.)
Q3a OK, let’s take them one at a time. On a 1 to 5 scale, where 1 is not at all important, 3 is

somewhat important, and 5 is very important, how important is it to you to...

Increase wetland and other habitats around the Bay of Green Bay to support increased

populations of birds, fishing and other wildlife?

1 NOT AT ALL IMPORTANT

2

3 SOMEWHAT IMPORTANT

4

5 VERY IMPORTANT

8 DON’T KNOW

9 REFUSED

Q3b How important is it to you to remove PCBs in the Lower Fox River and the Bay of Green

Bay so that consumption advisories on fish and waterfowl can be removed?

1 NOT AT ALL IMPORTANT

2

3 SOMEWHAT IMPORTANT

4

5 VERY IMPORTANT

8 DON’T KNOW

9 REFUSED

Q3c How important is it to you to remove PCBs in the Lower Fox River and the Bay of Green

Bay to reduce risks to birds, fish and other wildlife?

1 NOT AT ALL IMPORTANT

2

3 SOMEWHAT IMPORTANT

4

5 VERY IMPORTANT

8 DON’T KNOW

9 REFUSED
Q3d How important is it to add new facilities at existing state and county parks throughout a 10

county Northeast Wisconsin area? (new facilities may include boat launches, picnic areas,

hiking and biking trails, and the like.)

1 NOT AT ALL IMPORTANT

2

3 SOMEWHAT IMPORTANT

4

5 VERY IMPORTANT

8 DON’T KNOW

9 REFUSED

(For recreation, if asked: the 10 county area is around the Bay of Green Bay from Winnebago,

Calumet and Manitowoc counties on the south to Marinette and Door counties on the north. Your

county is in this area).

I have just 3 more quick questions about you and your household to help us group your responses

with others.

Q5 What is your age?

____ YEARS OLD

999 REFUSED

Q6 How many people are there in your household, including yourself?

____ PEOPLE

99 REFUSED
Q7 What was your total household income before taxes in 1998? I’ll read off the categories, so

just stop me when I reach the category that includes your household’s total 1998 income.

1 LESS THAN $20,000

2 $20,000 TO $40,000

3 $40,000 TO $60,000

4 $60,000 TO $80,000

5 $80,000 TO $150,000

6 MORE THAN $150,000

8 DON’T KNOW

9 REFUSED

That’s all the questions I have for you. Do you have any comments that you would like to add?

Thank you for your time. We really appreciate your participation in this brief survey.

Thanks again, and have a good evening.

[TERMINATE INTERVIEW]

GENDER

Respondent gender:

1 MALE

2 FEMALE

8 DON’T KNOW

LANG Language or other barrier:

1 YES, POSSIBLE LANGUAGE BARRIER

2 YES, DEFINITE LANGUAGE BARRIER

3 NO LANGUAGE, BUT OTHER TYPE OF BARRIER [SPECIFY]

4 NO BARRIERS
Follow-up letters for those reached by phone

«CASEID»

Dear «FIRSTNAM» «LASTNAM»:

Enclosed is another copy of the questionnaire we discussed on the phone this week. Thank you for

your willingness to complete and return this questionnaire.

Since we were only able to survey a small number of households in Northeast Wisconsin, your

response is very important. Informed decisions about natural resource issues can only be made if

decision-makers know how citizens like you think about natural resource issues in your area. We

want to remind you that the questionnaire does not require any special knowledge--we just ask that

you consider each question and respond with your own opinion.

You will be sent a summary of the results of this study later this year. In addition, if you

postmark the questionnaire by October 18 and complete all the questions, we will send you a

$15 “Thank You” check.

All of your answers are confidential; your name will never be revealed to anyone. A code number

has been put on the questionnaire so we can send you the $15 check for completing and returning it.

If you have any questions, please call me toll-free at 1-800-935-4277.

Thank you for your help, and please remember to complete all questions.

Sincerely,

Pam Rathbun

Hagler Bailly Survey Manager
Follow-up letters for those not reached by phone

«ID»

Dear «FIRST_NAME» «LAST_NAME»,

A couple weeks ago, we sent you a questionnaire asking for your household’s opinions on natural

resource issues in Northeast Wisconsin. We are pleased that many households have returned their

questionnaire, but we still would like to hear from you. If you recently mailed our questionnaire

back to us, please accept our thanks and disregard this letter.

Since we were only able to survey a small number of households in Northeast Wisconsin, your

response is very important. Regardless of whether you are a full-time resident of Northeast

Wisconsin or a seasonal resident, your opinion counts. Informed decisions about natural resource

issues can only be made if decision-makers know how citizens like you think about natural resource

issues in your area. We want to remind you that the questionnaire does not require any special

knowledge--we just ask that you consider each question and respond with your own opinion.

In the event that your questionnaire has been misplaced, a replacement questionnaire and a postage

paid, self-addressed envelope are enclosed for your convenience. This questionnaire should be

answered by either the male or female head of your household.

You will be sent a summary of the results of this study later this year. Because receiving responses

from every household in our sample is important, we have extended the response date to October

25--if you postmark the questionnaire by Monday, October 25 and complete all the questions,

we will send you a $15 “Thank You” check.

If there is anything we can do to help you complete this questionnaire, please feel free to call me

toll-free at 1-800-935-4277.

Your cooperation in this study is greatly appreciated!

Sincerely,

Pam Rathbun

Hagler Bailly Survey Manager
Thank you letter

Dear Northeast Wisconsin Resident:

Thank you for responding to the survey about “Your Opinions about the Future of Natural

Resources in Northeast Wisconsin”. Enclosed is a $15 check to thank you for your assistance with

this important study. Around the end of this year, you will also be receiving a summary of the study

results.

Please call me at 608-232-2800 if you have any other questions.

Pam Rathbun, Manager

Survey Research Center
Appendix B — Modeling Consumer

Preferences for Green Bay Resource

Characteristics Using Stated

Preference Data
Stratus Consulting Appendix B (Final, 10/25/00)

Page B-2

B.1 Introduction

The purpose of this model is to estimate the parameters in a conditional indirect utility function

for natural resource program characteristics using stated preference (SP) data, which consist of

the answers to choice questions. Each sampled individual indicated his or her choice between a

pair of Green Bay alternatives (Green Bay under different conditions). For each sampled

individual, this comparison is repeated J times, where the characteristics of the Green Bay

alternatives in the pairs are varied over the J pairs.

Section B.2 develops the choice probabilities for the two Green Bay alternatives using the SP

data that indicate which Green Bay alternative is chosen. Section B.3 presents the likelihood

function for the model.

B.2 Choice Probabilities for SP Green Bay Pairs

Let utility for the Green Bay alternatives be given by:

+ , = 1,..., ; = 1,..., ; ∈[1,2] , ′ = ij

k

ij

k

i ij

k

ij U x i m j J k ij ij ij β ε (B-1)

where ij k Uij is the utility of the k-th alternative of pair j to individual i. That is, i indexes the m

respondents, j indexes the J pairs, and kij indicates which of the two alternatives within each pair

is chosen. The L H 1 vector ij k

ij x contains the characteristics of the alternatives, and hence the

elements of the unknown L H 1 vector β i can be interpreted as marginal utilities.1

 The first

element of ij k

ij x is the difference between income for individual i and the cost of alternative kij,

and the model is restricted to one with a constant marginal utility of money, which is the first

element of β i . This specification implies no income effects; that is, the probability of choosing

any alternative is independent of income. The term ij k

i ij x

′ β is the nonstochastic part of utility,

while ij k

ij ε represents a stochastic component. It is assumed the ij kij ε are independent (across i) and

identically distributed mean zero normal random variables, uncorrelated with ij k

ij x , with constant

unknown variance 2 σ ε . For SP data, it is assumed that the individual does not know his stochastic

component before actually deciding on the particular alternative. That is, ij k

ij ε is assumed to be

the sum of factors unknown to both the individual and the investigator, although its distribution

 

1. The parameter vector β is subscripted by i to indicate the marginal utilities may vary over individuals as a

function of individual characteristics.
Stratus Consulting Appendix B (Final, 10/25/00)

Page B-3

is assumed to be known.2,3 That an individual does not know his preferences completely results

from the fact that preferences have a component that varies randomly over time. When the

individual answers stated-choice questions he does not know exactly what his preferences would

be if he were presented with these alternatives as an actual choice at some point in the future. We

assume the survey questions are answered probabilistically and reflect what he is likely to do if

he were repeatedly presented with the actual choice.

Let ∈[1,2] Kij be the Bernoulli random variable that is the choice for individual i on occasion j.

The individual is assumed to choose alternative kij with the probability4:

( ) ( ) , ij ij 3 ij k

ij

k

ij

k P Kij kij Pij P U U − = = = > (B-2)

where kij is the observed value of Kij. That is, we may think of the individual’s choice as a

drawing from a Bernoulli distribution with the probability given by Equation B-2.

From Equations B-1 and B-2 and assumptions regarding the stochastic component, the

probability of choosing alternative kij is:

 

2. For revealed preference data, the usual discrete-choice model specification is that the disturbances are

known to the individual, and the behavioral assumption is utility maximization. The assumption is also

sometimes made for SP data, although the rationale is less clear. However, even under the assumption that

each unique pair of disturbances for each choice occasion is known to the individual a priori (and that the

individual would evaluate utility for the two scenarios under the assumption of utility maximization), the

identical likelihood function would be produced.

3. Manski (1999) assumes that stated choices made when it may be impractical for scenarios to contain all

information relevant to making some actual choice in the future (which is represented by the stochastic

component in equation B-1) do represent respondents’ “intentions.” According to Manski (p. 62), under this

assumption the individual “applies his or her subjective distribution of [the stochastic term] to form a

subjective choice probability,” and subsequently chooses between alternatives. This theory is adopted in our

specification. He provides a formal, theoretical proof that under standard economic and econometric

assumptions, the researcher can obtain consistent estimates of choice probabilities (that is, as the sample gets

large, the estimated sample probability approaches the true population probability; see p. 59). Choice questions

can be used not only to predict choice behavior for the scenarios presented, but also can be used to extrapolate

to other feasible scenarios using familiar statistical methods, including the binary probit model (Section 3 in

Manski).

4. In this notation, if the individual chooses alternative =1[or 2] Kij , then the alternative that was not chosen

is 3− = 2[or 1] Kij .
Stratus Consulting Appendix B (Final, 10/25/00)

Page B-4

[ ( )/ 2 ] ,

P[ ( )]

P(

3

3 3

3 3

β σ ε

ε ε β

β ε β ε

ij ij

ij ij ij ij

ij ij ij ij ij

k

ij

k

i ij

k

ij

k

i ij

k

ij

-k

ij

k

ij

k

i ij

k

ij

k

i ij

k

ij

x x

x x

P x x

− ′ = Φ −

− ′ = − < −

+ ′ + > ′ =

−

−

− −

(B-3)

where σ ε 2 is the standard deviation of ij ij k

ij

k

ij ε − ε 3− and Φ(⋅) is the univariate standard normal

cumulative distribution function. This probability will enter into the likelihood function in

Section B.3. The parameter vector β i is identified only up to the scale factor σ ε 2 , and σ ε is not

identified, since only the sign and not the scale of the dependent variable (the utility difference)

is observed.5 Nevertheless, we have chosen to list the parameters of the likelihood function

( , ) β σ ε separately. Notice also the J observations for each respondent have simply been stacked

to produce a data set with Jm observations.

B.3 The Likelihood Function

The maximum likelihood parameter estimates are consistent. They are also asymptotically

efficient under the additional assumption that the ij k

ij ε are uncorrelated across j. The likelihood

function is a function of the probabilities of the preferred alternatives from the Green Bay pairs

(Section B.2). The likelihood function is:

( , 1,..., ; 1,..., | , ; , ) P( ) . 1 1

1 2

∏ ∏= =

= = = =

J

j

ij ij

m

i

ij ij ij i L k i m j J x x K k β σ ε (B-4)

 

5. However, the scale factor can be allowed to vary across individuals or choice occasions as long as one scale

is fixed for identification. Individuals or choice questions with smaller scales will receive less weight in the

likelihood function in Section B-3, and will therefore have less influence on the estimation of parameters.
Appendix C — Survey with Means

and Frequencies
WHAT ARE YOUR OPINIONS ABOUT THE

FUTURE OF NATURAL RESOURCES IN

NORTHEAST WISCONSIN?

Important Definition

In this survey $the Bay of Green Bay# means the waters of the

Bay of Green Bay and all tributaries up to the first dam or obstruction.
1

Introduction

Decision makers are examining options for natural resources in northeast Wisconsin. Your

responses to this survey will help in making decisions about which options are best.

How often do you personally participate in each of the following activities in Wisconsin

on the waters and shorelines of the Bay of Green Bay? Circle the letter of your answer for each

activity.

N Less than

once a year

or never

1 to 5 times

a year

6 to 10

times a year

More than

10 times a

year

Missing

Fishing . . . . . . . . . . . . . . . 446 238 119 36 53 24

Boating (non-fishing) . . . . 431 250 132 29 20 39

Waterskiing or jetskiing . . 423 372 36 9 6 47

Canoeing or kayaking . . . . 423 363 42 13 5 47

Swimming . . . . . . . . . . . . . 433 249 113 36 35 37

Hunting . . . . . . . . . . . . . . . 432 312 59 22 39 39

Wildlife viewing . . . . . . . . 442 117 150 73 102 28

Enjoying outdoor scenery . 444 53 121 91 179 26

Camping or picnicking . . . 431 178 161 51 41 39

Biking . . . . . . . . . . . . . . . . 420 264 87 31 38 38

Hiking, walking, or jogging 438 145 116 66 111 32

This survey addresses four natural resource topics. The information provided reflects the

most recent scientific reports about these topics.

< Wetlands

< PCBs

< Outdoor recreation

< Runoff
 2

Wetlands

Within 5 miles of the Bay of Green Bay there are about 58,000 acres of wetlands in Wisconsin

(see map on the facing page), and another 86,000 acres in Michigan. These nearby wetlands

are very important to the fish and wildlife of the Bay of Green Bay.

< Farming, cutting forests, and developing residential and urban areas have reduced

wetlands in this area by more than half in the past 100 years.

< Current regulations are designed to prevent further loss of wetlands in this area.

< Programs have been proposed to restore wetlands in this area. Any wetlands

restoration would take about 10 years.

Wetlands around the Bay of Green Bay provide spawning and nursery habitats for a

majority of the fish species in the Bay, including yellow perch, bluegill, largemouth bass,

northern pike, and over 35 other species. These wetlands also provide necessary habitat and

food for many bird species in the Bay area, including terns, many species of ducks and geese,

shorebirds, bald eagles, several species of hawks, coots, and others. Other wildlife such as

deer, muskrat, and mink also use wetlands for habitat.

Increases in wetlands would support nearly proportional increases in the populations of those

bird and fish species that depend on wetlands. For example, increasing wetland acres by 10%

would increase the numbers of those birds and fish that rely on wetlands by about 10%.

How important to you, if at all, is it to increase wetland acreage near to the Bay of Green Bay

to support birds, fish, and other wildlife? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Don t

know

N

Missing

N Mean Std. Dev.

25 26 101 110 198 8 2 460 3.93 1.67
 3

Wisconsin Wetlands Within 5 Miles of the Bay of Green Bay

Which of the following options do you prefer for Wisconsin wetlands near to the Bay

of Green Bay? Circle the number of your answer.

Category Freq.

1 Do less and spend less to maintain wetlands, resulting in a loss of wetlands. 12

2 Do and spend about the same to maintain the current wetland acreage (about 58,000 acres). 192

3 Do more and spend more to restore wetlands. Options to restore wetlands range from restoring 2,900

acres (5% more than now) to restoring 11,600 acres (20% more than now).

257

Missing 9

Total 470
 4

5

PCBs

PCBs are substances that were used by industry until the mid-1970s, when they were banned.

< PCBs released into the Lower Fox River have accumulated in the sediments at the

bottom of the Lower Fox River and Green Bay.

< PCBs get into fish, birds, and other wildlife through the food chain.

Because of PCBs, consumption advisories have been issued for all sport-caught fish in

Green Bay (including all tributaries up to the first dam) and for some waterfowl in the area.

The fish consumption advisories tell how often a meal of fish may be safely eaten (see table on

the facing page). Eating more fish than is recommended may increase a woman s risk of

bearing children with learning disabilities and slow development, and for everyone may

increase the risk of cancer.

Programs have been proposed to remove PCBs in this area. How important to you, if at all, is

it to remove PCBs so that it will be safe to eat fish and waterfowl? Circle the number of your

answer.

Not at all

important

Somewhat

important

Very

important

Don t

know

N

Missing

N Mean Std. Dev.

17 16 66 88 271 8 4 458 4.27 1.07

PCBs cause harm to wildlife in and near the Bay of Green Bay.

Birds Forster s terns and common terns in the area reproduce at rates that are about half of

the rate elsewhere in Wisconsin. Both are listed as Wisconsin endangered species.

Bald eagles in the area also reproduce at about half the normal rate for Wisconsin. PCBs

contribute to this problem. Bald eagles are no longer listed as endangered.

A small percentage of cormorants experience deformities such as crossed bills.

Fish About 25% of walleye have abnormalities that can become cancerous liver tumors.

Other Wildlife Some sensitive fish-eating wildlife, like mink, may be harmed.

Even though PCBs harm wildlife, it is unclear whether the total numbers of terns, eagles,

cormorants, walleye, mink and other species in the area are less than if there were no PCBs.

This is because wildlife migrates into and out of the area, because there is limited habitat in

the area for some species, and because other factors influence wildlife populations.

How important to you, if at all, is it to remove PCBs in the Bay of Green Bay area to reduce

harm to birds, fish, and other wildlife? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Don t

know

N

Missing

N Mean Std. Dev.

13 17 69 93 270 6 2 462 4.28 1.03
 6

Wisconsin Department of Natural Resources

 Fish Consumption Advisories for PCBs

Wisconsin waters of Green Bay, including all tributaries up to the first dam

(PCB advisories in the Lower Fox River are the same or more restrictive)

Species

Eat no more than

One meal/week

or 52 meals/year

Eat no more than

One meal/month

 or 12 meals/year

Eat no more than

One meal every

two months or

six meals/year

Do not eat

Northern Pike Less than 22" Larger than 22"

Walleye Less than 17" 17-26" Larger than 26"

Yellow Perch All sizes

Carp, White Bass,

Sturgeon

All sizes

Smallmouth Bass, White

Sucker, Rainbow Trout

All sizes

Channel Catfish, White

Perch, Whitefish

All sizes

Chinook Salmon Less than 30" Larger than 30"

Brown Trout Less than 17" 17-28" Larger than 28"

PCB removal would take about 10 years. Any PCB removal would use the best

available technology to minimize stirring up PCBs, and the PCBs that are removed would be

disposed of in a manner that would prevent future risks to humans and wildlife.

Not all PCBs can be removed. The PCBs that are not removed may continue to harm some

fish and wildlife. For example, with extensive PCB removal, fish consumption advisories for

yellow perch and some impacts to wildlife would be eliminated shortly after PCB removal, but

it would be 20 years total (10 years for removal plus 10 more years for nature to recover)

before PCBs are at safe levels. By safe levels we mean there are no consumption advisories

for, and no harm to, nearly all fish and wildlife.

Which of the following options do you prefer for PCBs in the Green Bay area of Wisconsin?

Circle the number of your answer.

Category Freq.

1 No further PCB investigations or removal. With no further removal it will be 100 years or more until

PCBs are at safe levels.

77

2 Do more and spend more to remove PCBs. Depending on how many PCBs are removed, the time

until PCBs are at safe levels would range from 20 years up to 70 years.

382

Missing 11

Total 470
 7

 8

Outdoor Recreation

In 10 Wisconsin counties around the Bay of Green Bay, there are over 120 state parks,

natural areas, and county parks covering more than 86,000 acres (see map on the facing

page).

< These parks include a variety of facilities such as picnic grounds, beaches, scenic sites,

piers, boat ramps, biking and hiking trails, and interpretive centers.

< To meet the current and future needs of area residents, programs have been proposed

to add facilities at existing parks and to open new parks.

Adding facilities at existing parks can improve recreational opportunities in these

parks. For example, 10% more facilities would mean that most parks would see

improvements. Some parks would add hiking or biking trails, some parks would add picnic

areas, some parks would add a boat ramp, some parks would add adjacent land, and so forth.

How important to you, if at all, is adding facilities at existing parks throughout the area to

enhance recreational opportunities? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Don t

know

N

Missing

N Mean Std. Dev.

22 43 168 103 131 3 0 467 3.60 1.13

New parks can be opened throughout the area to increase recreational opportunities. 

How important to you, if at all, is opening new parks to enhance outdoor recreational

opportunities? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Don t

know

N

Missing

N Mean Std. Dev.

41 76 156 90 103 4 0 466 3.30 1.23
 9

State and County Recreation Areas

Any new facilities at existing parks, and any new parks, would be located throughout

the area to best meet the needs of residents and would take up to 10 years to accomplish. 

Which of the following options do you prefer for state and county parks in northeast

Wisconsin? Circle the number of your answer.

Category Freq.

1 Do less and spend less to maintain existing outdoor recreation parks. 9

2 Do and spend about the same to maintain existing park conditions and facilities. 239

3 Do more and spend more to add facilities at existing parks and/or to open new parks. 220

Missing 2

Total 470
 10

 11

Runoff

Runoff from farms, highways, construction sites, and residential and urban neighborhoods

carries plant nutrients and sediments into the Bay of Green Bay and its tributaries, causing

algae growth, muddy water, and changes in aquatic habitat (see figure on the facing page).

< Runoff pollution can be reduced by decreasing erosion; controlling farm, urban, and

residential wastes; fencing livestock away from streams; and other measures.

< Zebra mussels (small shellfish) have invaded Green Bay. They filter the water, making

it clearer. However, scientists say we cannot count on zebra mussels to improve water

clarity in the future.

< Runoff is not a significant source of the PCBs in the Lower Fox River and Green Bay

and does not affect the quality of your drinking water.

When too many plant nutrients are present, excess algae coats the surface of the water

with decaying plants and causes a foul odor. The frequency of excess algae varies by location

in the Bay of Green Bay from seldom in the central and northern Bay to up to 80 days a

summer in the southern Bay. Most excess algae occurs from mid-June to mid-September.

How important to you, if at all, is it to control runoff to reduce the number of days with excess

algae in Green Bay? Circle the number of your answer.

Not at all

important

Somewhat

important

Very

important

Don t

know

N

Missing

N Mean Std. Dev.

13 35 134 129 146 13 0 457 3.79 1.07

Because of sediments and algae, you can only see down into the water about 20 inches

on average in southern Green Bay, with clearer water to the north. This not only makes the

water look less appealing but also reduces the light that reaches underwater plants and thus

reduces aquatic habitat. Populations of desirable fish and birds are smaller and carp

populations are larger than they would be otherwise, but scientists cannot yet put numbers on

the vegetation and wildlife effects.

How important to you, if at all, is it to control runoff to improve water clarity? Circle the

number of your answer.

Not at all

important

Somewhat

important

Very

important

Don t

know

N

Missing

N Mean Std. Dev.

7 29 116 134 175 9 0 461 3.96 1.01
12

Water Pollution from Runoff

Any actions to reduce runoff would take up to 10 years to reach their goals. Which of

the following options do you prefer for controlling runoff around the Bay of Green Bay?

Circle the number of your answer.

Category Freq.

1 1 Do less and spend less, resulting in reduced water clarity, increased days of excess algae, and less

aquatic habitat in Green Bay and its tributaries.

7

2 Do and spend about the same. In the southern parts of Green Bay, average summer water clarity

would remain about 20 inches, excess algae would occur up to 80 days a summer, and aquatic habitat

would remain the same.

157

3 Do more and spend more to control runoff. Options range up to a 50% reduction in runoff. In the

southern parts of Green Bay, this would result in about 34 inches of water clarity, excess algae up to 40

days per year, and increased aquatic habitat. 

299

Missing 7

Total 470
What Alternatives Do You Prefer?

In each of the next questions there are two alternatives, labeled A and B (see Question 13).

< Each alternative describes a possible combination of options for natural resources in

and around the Bay of Green Bay and the additional costs to your household beyond

what you are now paying.

< Depending on the options, some costs will be paid by industry, farmers, and

conservation organizations. But taxpayers may have to pay something as well. Assume

your household pays its share of any added costs through a combination of federal,

state, and local taxes each year for the next 10 years.

< Since we do not yet know how much each alternative will actually cost you or others,

we are asking about a range of costs.

< For each question, even if you do not view either Alternative A or B as ideal, still tell us

which of the two alternatives you would prefer.

< To help you get started, for Question 13 we have provided information on the righthand side indicating the differences, if any, between Alternatives A and B.

REMEMBER

1. The goal of wetlands restoration is to provide additional habitat for fish and wildlife.

2. For PCBs, the $years until safe# is the number of years until there are no consumption

advisories for, and no harm to, nearly all fish and wildlife. Many advisories and effects

will end sooner, but a few advisories and effects may last longer.

3. New recreation facilities at existing parks could include rest rooms, trails, boat ramps,

and picnicking and camping facilities. Any new facilities at existing parks and any new

parks would be located to best meet the needs of area residents.

4. Pollution from runoff creates excess algae, reduces water clarity, and causes the loss of

aquatic habitat, all of which occur most often in the southern Bay.
 13 If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Alternative A

ï

Alternative B

ï

Wetlands

 Acres in Wisc. around Green Bay.

 (Currently 58,000)

PCBs

 Years until safe for nearly all

 fish and wildlife . . . . . . . . . . . . .

 (Currently 100 years or more)

Outdoor Recreation

 Facilities at existing parks . . . . . . .

 

Acres in new parks. . . . . . . . . . . . . . .

 (Currently 86,000 acres in state

 and county parks)

Runoff

 Average water clarity in southern

 Bay (Currently 20 inches) . . . . . . .

 Excess algae (Currently up to 80

 summer days in the southern Bay)

Added cost to your household

 Each year for 10 years. . . . . . . . . .

Check (U) the box for

 the alternative you prefer Û ñ

I Prefer

Alternative A

ñ

I Prefer

Alternative B

Q13 Version

1 2 3 4 5 6 7 8 9 10 Total

Alternative A 21 27 18 16 20 36 38 30 21 28 255

Alternative B 17 21 23 32 30 8 14 14 28 20 207

Neither A nor B 0 0 0 0 2 0 0 0 0 0 2

Don’t Know 0 0 0 0 0 1 0 0 0 0 1

Missing 0 0 1 0 1 0 1 1 0 1 5

Total 38 48 42 48 53 45 53 45 49 49 470
 14

 15

 16

 17

 18

If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Q14 Version

1 2 3 4 5 6 7 8 9 10 Total

Alternative A 15 27 17 27 34 25 33 35 28 21 262

Alternative B 23 21 25 20 17 20 19 10 21 28 204

Neither A nor B 0 0 0 0 1 0 0 0 0 0 1

Missing 0 0 0 1 1 0 1 0 0 0 3

Total 38 48 42 48 53 45 53 45 49 49 470

If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Q15 Version

1 2 3 4 5 6 7 8 9 10 Total

Alternative A 20 45 25 43 20 26 34 22 41 25 301

Alternative B 18 3 17 4 30 18 18 23 8 23 162

Neither A nor B 0 0 0 0 2 0 0 0 0 0 2

Don’t Know 0 0 0 0 0 1 0 0 0 0 1

Missing 0 0 0 1 1 0 1 0 0 1 4

Total 38 48 42 48 53 45 53 45 49 49 470

If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Q16 Version

1 2 3 4 5 6 7 8 9 10 Total

Alternative A 18 4 13 26 13 40 14 30 29 38 225

Alternative B 20 44 29 22 37 4 39 15 20 11 241

Neither A nor B 0 0 0 0 2 0 0 0 0 0 2

Don’t Know 0 0 0 0 0 1 0 0 0 0 1

Missing 0 0 0 0 1 0 0 0 0 0 1

Total 38 48 42 48 53 45 53 45 49 49 470

If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Q17 Version

1 2 3 4 5 6 7 8 9 10 Total

Alternative A 27 33 36 10 23 16 26 32 37 44 284

Alternative B 11 15 6 38 27 28 27 13 12 4 181

Neither A nor B 0 0 0 0 2 0 0 0 0 0 2

Don’t Know 0 0 0 0 0 1 0 0 0 0 1

Missing 0 0 0 0 1 0 0 0 0 1 2

Total 38 48 42 48 53 45 53 45 49 49 470

If you had to choose, would you prefer Alternative A or Alternative B? Check one box

at the bottom.

Q18 Version

1 2 3 4 5 6 7 8 9 10 Total

Alternative A 19 41 12 30 16 22 18 33 30 30 251

Alternative B 18 6 30 18 33 22 35 12 19 18 211

Neither A nor B 0 0 0 0 2 0 0 0 0 0 2

Don’t Know 0 0 0 0 0 1 0 0 0 0 1

Missing 11002000015

Total 38 48 42 48 53 45 53 45 49 49 470
 19

 20

 21

 22

When you were making your choices between alternatives A and B in Questions 13

through 18, how important were each of the following? Circle the number of your

answer for each item.

Not at all

important

Average

importance

Very

important

N

Missing

N Mean Std.

Dev.

Acres of wetland 36 58 189 91 94 2 468 3.32 1.15

Years until safe levels of 

PCBs

17 37 123 110 181 2 468 3.86 1.13

Facilities at existing parks 43 78 173 113 57 6 464 3.14 1.12

Acres of new parks 68 107 154 87 50 4 466 2.88 1.19

Inches of water clarity 22 53 164 138 88 5 465 3.47 1.07

Days of excess algae each

summer.

32 66 170 113 86 3 467 3.33 1.13

Annual cost to your

household

15 49 135 99 168 4 466 3.76 1.14

Overall, how confident do you feel about your choices between the alternatives in

Questions 13 through 18? Circle the number of your answer.

Not at all

confident

Somewhat

confident

Very

confident

N

Missing

Don t

know

N Mean Std. Dev.

6 23 188 178 73 2 0 468 3.62 0.85

Questions 13 through 18 were asked to provide citizen input for decision makers to

consider along with other information from scientists and planners. With this in mind,

how much should public officials consider your responses to Questions 13 through 18?

Circle the number of your answer.

Should not

consider my

responses at all

Should somewhat

consider my

responses

Should completely

consider my

responses

Don t

know

N

Missing

N Mean Std.

Dev.

3 16 128 185 136 0 2 468 3.93 0.87

Prior to receiving this survey, how aware were you of each of the four natural resource

topics we addressed? Circle the number of your answer for each topic.

I was not

aware of

this topic

I was

somewhat

aware of

this topic

I was

very 

aware of

this topic

Don t

know

N

Missing

N Mean Std.

Dev.

Wetlands . . . . . . . . 41 46 172 116 94 0 1 469 3.38 1.17

PCBs . . . . . . . . . . . 20 12 102 137 191 0 8 462 4.01 1.06

Outdoor recreation . 30 59 165 119 91 0 6 464 3.39 1.13

Runoff . . . . . . . . . . 37 51 141 129 106 0 6 464 3.47 1.19
 23

About You and Your Household

This information is used to help group your responses with responses of other households. 

Your individual responses and your name will not be released.

In the last 12 months, have you fished in Green Bay or its tributaries up to the first

dam (see map on the cover)? Circle the number of your answer.

1 No 326.

1 No 281

2 Yes 22

3 Don t know/Uncertain 16

Missing 7

(If no) in the last 12 months, have other

household members fished in Green Bay

 or its tributaries up to the first dam?

Circle the number of your answer.

Total 326

2 Yes 143

(If yes) in the last 12 months, on about how many

days have you fished in Green Bay or its

tributaries up to the first dam? Days

N

Mean

Std. Dev

Median

143

10.50

13.67

7

Missing 1

Total 470

Frequencies for Question 23 Part 2 $ about how many days have you fished in Green Bay or

its tributaries up to the first dam?#

Days Frequency Cumulative Frequency Cumulative Percent

1 10 10 6.99

2 18 28 19.58

3 18 46 32.17

4 10 56 39.16

5 13 69 48.25

6 11 80 55.94

7 6 86 60.14

8 5 91 63.64

10 14 105 73.43

12 5 110 76.92

15 6 116 81.12

16 1 117 81.82

20 12 129 90.21

23 1 130 90.91

24 1 131 91.61

25 1 132 92.31

30 4 136 95.10

40 2 138 96.50

50 2 140 97.90

60 1 141 98.60

70 1 142 99.30

100 1 143 100.00
 24

 25

Do you own or rent your residence? Circle the number of your answer.

Own 395

Rent 73

Missing 2

Total 470

Do you have a vacation home or cabin in northeast Wisconsin? Circle the number of

your answer.

1 Yes 85

(If yes) about how many miles is it from your vacation

home or cabin to the Bay of Green Bay?

_______ Miles to Green Bay

N

Mean

Std. Dev.

Median

84

63.91

35.43

65

2 No 377

Missing 8

Total 470

Frequencies for Question 25 - Part 2 $(If yes) about how many miles is it from your vacation home or

cabin to the Bay of Green Bay? #

Miles Frequency Cumulative Frequency Cumulative Percent

1 5 5 5.88

6 1 6 7.06

8 1 7 8.24

10 3 10 11.76

15 2 12 14.12

29 1 13 15.29

30 2 15 17.65

35 1 16 18.82

36 1 17 20.00

40 7 24 28.24

45 4 28 32.94

50 6 34 40.00

60 6 40 47.06

64 1 41 48.24

65 5 46 54.12

69 1 47 55.29

70 5 52 61.18

75 4 56 65.88

80 7 63 74.12

90 2 65 76.47

100 12 77 90.59

110 2 79 92.94

125 2 81 95.29

130 1 82 96.47

135 1 83 97.65

140 1 84 98.82

150 1 85 100.00
 26

 27

Your gender:

Female 135

Male 335

Missing 0

Total 470

Your age: Years old

Mean 50.92

Std. Dev. 15.85

N 470

Missing 0

Frequencies or responses to Age Question

Age (Years) Frequency Cumulative Frequency Cumulative Percent

21 2 2 0.43

22 6 8 1.70

23 4 12 2.55

24 2 14 2.98

25 3 17 3.62

27 4 21 4.47

28 6 27 5.74

29 6 33 7.02

30 2 35 7.45

31 6 41 8.72

32 2 43 9.15

33 11 54 11.49

34 14 68 14.47

35 8 76 16.17

36 16 92 19.57

37 11 103 21.91

38 18 121 25.74

39 6 127 27.02

40 17 144 30.64

41 9 153 32.55

42 11 164 34.89

43 9 173 36.81

44 18 191 40.64

45 12 203 43.19

46 8 211 44.89

47 8 219 46.60

48 9 228 48.51

49 11 239 50.85

50 12 251 53.40

51 9 260 55.32
Age (Years) Frequency Cumulative Frequency Cumulative Percent

52 11 271 57.66

53 10 281 59.79

54 8 289 61.49

55 11 300 63.83

56 8 308 65.53

57 8 316 67.23

58 7 323 68.72

59 9 332 70.64

60 9 341 72.55

61 8 349 74.26

62 11 360 76.60

63 9 369 78.51

64 5 374 79.57

65 6 380 80.85

66 6 386 82.13

67 3 389 82.77

68 7 396 84.26

69 7 403 85.74

70 7 410 87.23

71 4 414 88.09

72 5 419 89.15

73 3 422 89.79

74 4 426 90.64

75 3 429 91.28

76 1 430 91.49

77 7 437 92.98

78 4 441 93.83

79 2 443 94.26

80 5 448 95.32

81 3 451 95.96

82 5 456 97.02

83 3 459 97.66

84 1 460 97.87

85 1 461 98.09

86 3 464 98.72

87 2 466 99.15

89 1 467 99.36

91 1 468 99.57

96 1 469 99.79

99 1 470 100.00
 28

 29

 30

 31

How many people are there in your household, including yourself?

N 468

Mean 2.68

Std. Dev. 1.34

Missing 2

How many children do you have, whether living with you or not?

N 467

Mean 2.28

Std. Dev. 1.78

Missing 3

How many grandchildren do you have, whether living with you or not? 

N 464

Mean 1.99

Std. Dev. 3.82

Missing 6

How many listed telephone numbers does your household have?

N 465

Mean 1.13

Std. Dev. 0.44

Missing 5

Frequencies for Question 28 - Number of People in Household

Number Frequency Cumulative Frequency Cumulative Percent

0 2 2 0.43

1 79 81 17.31

2 186 267 57.05

3 67 334 71.37

4 85 419 89.53

5 34 453 96.79

6 13 466 99.57

7 2 468 100.00

Frequencies for Question 29 - Number of Children

Number Frequency Cumulative Frequency Cumulative Percent

0 79 79 16.92

1 71 150 32.12

2 140 290 62.10

3 87 377 80.73

4 49 426 91.22

5 19 445 95.29

6 10 455 97.43

7 5 460 98.50

8 3 463 99.14

9 2 465 99.57

10 1 466 99.79

13 1 467 100.00
 32

Frequencies for Question 30 - Number of Grandchildren

Number Frequency Cumulative Frequency Cumulative Percent

0 286 286 61.64

1 36 322 69.40

2 28 350 75.43

3 20 370 79.74

4 15 385 82.97

5 18 403 86.85

6 11 414 89.22

7 9 423 91.16

8 7 430 92.67

9 6 436 93.97

10 5 441 95.04

11 5 446 96.12

12 4 450 96.98

13 1 451 97.20

14 4 455 98.06

15 3 458 98.71

16 2 460 99.14

17 2 462 99.57

18 1 463 99.78

33 1 464 100.00

Frequencies for Question 31 - Number of Listed Telephones in Household

Number Frequency Cumulative Frequency Cumulative Percent

0 4 4 0.86

1 407 411 88.39

2 44 455 97.85

3 8 463 99.57

4 2 465 100.00

What is the highest level of schooling you have completed? Circle the number of your

answer.

Frequency

Did not complete high school 24

High school diploma or equivalent 179

Some college, two year college degree (AS) or technical school 149

Four year college graduate (BA, BS) 58

Some graduate work but did not receive a graduate degree 20

Graduate degree (MA, MS, MBA, PhD, JD, MD, etc.) 36

Missing 4

Total 470
 33

 34

 35

 36

What is you present employment status? Circle the number of your answer.

Frequency

Employed full time 460

Employed part time 1

Retired 1

Homemaker 2

Student 4

Unemployed 0

Missing 2

Total 470

Which of the following categories best describes your racial or ethnic background?

Circle the number of your answer.

Frequency

White or Caucasian 460

Black or African American 1

Hispanic or Mexican American 1

Asian or Pacific Islander 2

Native American Indian 4

Other: 0

Missing 2

Total 470

What was your household income (before taxes) in 1998? Circle the number of your

answer.

Frequency

less than $10,000 20

$10,000 to $19,999 53

$20,000 to $29,999 58

$30,000 to $39,999 70

$40,000 to $49,999 65

$50,000 to $59,999 48

$60,000 to $79,999 74

$80,000 to $99,999 28

$100,000 to $149,999 17

$150,000 or more 15

Missing 22

Total 470

Is there anything we have overlooked? Please use this space for any additional

comments you would like to make.

Frequency

No comment 344

Made a comment 126

Total 470
County of respondent

County Frequency

Brown 214

Calumet 13

Door 20

Kewaunee 17

Manitowoc 25

Marinette 33

Oconto 32

Outagamie 52

Shawano 13

Winnebago 51

Total 470

MAIL_RET - Dates of survey return

Date Code Frequency Cumulative Frequency Cumulative Percent

1-Nov-99 2 2 0.43

1-Oct-99 7 9 1.91

3-Nov-99 2 11 2.34

3-Oct-99 1 12 2.55

4-Oct-99 4 16 3.4

5-Oct-99 2 18 3.83

7-Oct-99 1 19 4.04

8-Oct-99 7 26 5.53

13-Oct-99 13 39 8.3

14-Oct-99 20 59 12.55

14-Sep-99 65 124 26.38

15-Sep-99 30 154 32.77

16-Sep-99 53 207 44.04

17-Oct-99 16 223 47.45

17-Sep-99 30 253 53.83

18-Oct-99 16 269 57.23

19-Oct-99 11 280 59.57

20-Oct-99 9 289 61.49

20-Sep-99 73 362 77.02

21-Oct-99 2 364 77.45

21-Sep-99 24 388 82.55

22-Oct-99 1 389 82.77

22-Sep-99 23 412 87.66

23-Sep-99 6 418 88.94

24-Sep-99 16 434 92.34

25-Oct-99 2 436 92.77

26-Oct-99 1 437 92.98

27-Oct-99 1 438 93.19

27-Sep-99 18 456 97.02

28-Oct-99 2 458 97.45

28-Sep-99 2 460 97.87

29-Oct-99 1 461 98.09

29-Sep-99 5 466 99.15

30-Sep-99 4 470 100
Your Participation Is Greatly Appreciated!

Please return the survey in the enclosed envelope to:

Hagler Bailly Services

University Research Park

455 Science Drive

Madison, Wisconsin 53711
Appendix D — Existing Literature
Stratus Consulting Appendix D (Final, 10/25/00)

Page D-2

Several studies have been conducted in the Great Lakes basin, and for Green Bay in particular,

addressing the importance and value of environmental resources to the general public. While

none of this literature is exactly applicable to the objective of selecting and scaling restoration

options and/or valuing all of the specific injuries in this case, the literature shows considerable

consistency in that residents are aware of, concerned about, and place a high priority and value

on cleaning up contaminated water resources.

Breffle et al. (1999). In a related study to this one, Breffle et al. (1999) estimate damages to

current Green Bay recreational anglers from the presence of fish consumption advisories by

combining stated preference (SP) choice-pair data on different Green Bay alternatives with SP

and revealed preference frequency data on current use and use under various conditions. Using

variation on a probit model, it is estimated that anglers would be willing to pay $9.75 more per

Green Bay fishing day if FCAs were removed, and $4.17 per existing fishing day to all sites for

the option of choosing a Green Bay without FCAs. The study also estimates values for improved

catch rates, and how anglers would trade off catch rates for FCAs. Aggregate recreational fishing

damages for all Wisconsin and Michigan waters of Green Bay from 1980 until FCAs are

removed range from $106 million with intensive remediation (FCAs totally removed by 2020) to

$148 million with no remediation (all FCAs in place for over 100 years).1

 These damages do not

include damages to non-anglers who would fish in the absence of injuries, or to other individuals

who do or do not participate in other types of recreation.

Stoll (2000a and 2000b). Stoll (2000a,b) reports results from a 1997 repeat mail survey of the

general population conducted to estimate benefits of contaminated sediment remediation in the

Fox-Wolf River basin, which contains the Fox River and the entire Green Bay watershed and

Area of Concern (21 square miles of lower Green Bay). As reported in an earlier presentation of

survey results, the survey was administered to a stratified random sample of 1,500 individuals,

55% in contiguous counties and the rest in other Wisconsin counties (Stoll, 1997). The

proportion of respondents reporting that they are “somewhat” or “very” worried about human

health concerns from fish consumption is 60%.

Using a double-bounded referendum contingent valuation method (CVM), Stoll estimates total

active and passive use benefits from the improvement of water quality within the Area of

Concern in congruence with programs envisioned in the 1988 Lower Green Bay Remedial

Action Plan (RAP). The basic goals of the Green Bay RAP, based on its Key Action Items,

include (Baba et al., 1991; Stoll, 2000b):

 

1. Breffle et al. (1999) summarize other relevant fishing studies, which generally provide comparable findings

that FCAs are significantly adverse to recreational fishing.
Stratus Consulting Appendix D (Final, 10/25/00)

Page D-3

} impose greater pollution controls on industry

} provide more public education about water quality issues

} do more to protect wetlands and marshes

} conduct more basic research on water quality

} make sure that harbor dredging does not make the water quality worse

} encourage farmers to use better soil conservation practices

} require much more treatment of municipal wastes

} remove toxins from bottom sediments

} restore swimming and an edible fishery

} provide suitable habitat for enhancing and sustaining a diversity of wildlife

} establish a self-sustaining, balance, and diversified, edible fish community

} improve the water quality and trophic state of the area to relieve ecological stresses

} achieve and maintain water quality that protects the ecosystem from toxic substances

} ensure sustainability of a restored and healthy environment through pollution prevention.

The results show that 70% of households would be willing to pay $10 every year for the removal

of contaminated sediments, and 21% would pay at least $1,500 each year (Stoll, 1997). The

adjusted mean value of remediation benefits for 100% actualization of RAP projects is $222 per

household per year every year (in 1997 dollars), using a logistic function with a truncation at

$300 (Stoll, 2000b). Most values fall generally in the range of $100 to $300. This survey

addresses environmental problems much broader than the PCB contamination addressed in this

study (e.g., the study also addresses dissolved oxygen and temperature), and the study area is

much bigger than the Green Bay NRDA assessment area. It is not possible to scale Stoll’s values

to values that would be just for PCB restoration with the current information, although a

significant portion of the value would be expected to be attributable to PCBs, based on the

expressed concerns about FCAs in his work (and in the preference for PCB removal in this TVE

study).

Another approach to making remediation decisions by considering costs relative to benefits was

also presented by Stoll (2000a). Based upon an estimate of $700 million for remediation

activities, if remediation costs were borne entirely by Fox River Basin counties, the estimated per

household cost would be $167 per year for 30 years. This amount is commensurate with (or less

than, considering the finite time frame for incurring costs) remediation benefits estimates

typically ranging from $100 to $300 annually indefinitely into the future, with a mean of $222,

as reported in Stoll (2000b).

Johnsen et al. (1992). An earlier study also examined public perceptions and attitudes toward

environmental rehabilitation of the lower Green Bay watershed and the same Green Bay RAP.

Johnsen et al. (1992) is the published article based on the initial report, Baba et al. (1991). The

two documents contain different information. Johnsen et al. (1992) report wide public support

for items in the RAP. In 1990, over 700 members of Brown County households (which contains
Stratus Consulting Appendix D (Final, 10/25/00)

Page D-4

the lower Fox River and its mouth), plus a small sample of recreationists to augment the original

sample, were interviewed by telephone and asked 71 questions about recreational use,

perceptions about water quality and water quality requirements for recreation, and willingness to

pay to implement the RAP. Two-thirds of the sample had used the Area of Concern for

recreational purposes in the previous year. On a 1-to-10 scale (from worst possible water quality

to best), the mean perception of water quality in the lower bay near the mouth of the Fox River

was 3.95, and the perceptions of water quality were far below what was considered appropriate

for recreation (e.g., 8.05 was the rating associated with “game fish could live in it”). Each of the

RAP goals was supported by at least 72% of respondents, and considered important by at least

75% of respondents.

The study also reports a lower-bound mean willingness to pay for implementation of the RAP of

$34.08 per household per year every year (in 1990 dollars), although respondents felt that

industries polluting the water, as well as recreationists, should help pay to improve water quality

(Johnsen et al., 1992). WTP did not differ significantly between recreational users and nonusers.

WTP estimates for lower resource quality than the RAP projects would yield (e.g., swimmable

water with edible fish) were somewhat lower, ranging from $20.32 to $21.80 (Baba et al., 1991).

The primary motivations to pay for resource improvements were for recreational opportunities

and a cleaner environment.

Several study design features may be causing WTP values to be considerably lower in this study

than the values reported by Stoll (1997 and 2000b). First, this study used a telephone survey

format and presented very limited information on the injuries and benefits from remediation;

Stoll’s mail survey presented more comprehensive and detailed information, making it easier to

assess the benefits of the RAP program. Second, this study was conducted seven years earlier

than the Stoll study; only 21.8% of respondents had heard of the RAP prior to the survey.

Finally, the range of presented values in the iterative referendum format may have been

improperly truncated in this study (see Rowe et al., 1996): the highest value was $200, whereas

values in the Stoll survey went up to $3,000. Stoll (2000b) reports the mean value for the RAP is

higher than the highest value presented in this study ($222). Note that neither of these studies

estimate how individuals would be willing to tradeoff different resource improvements.

St. Norbert College Survey Center (1999). An October 1999 news article (Campbell, 1999),

based on a 1999 Fox River public opinion survey (St. Norbert College Survey Center, 1999),

sums up the current attitudes about health concerns in the Fox River of nearby Brown County

residents. The majority of individuals are displeased with the water quality in the Fox River;

38% rate the water quality as “poor,” and 34% rate it as “not too good.” Almost two-thirds report

that they are “somewhat” or “very” concerned with the health effects of the Fox River, and that

the paper mills should pay for the cleanup of the Fox River rather than the government. This

survey was conducted only with individuals living in Brown County. Other studies confirm that
Stratus Consulting Appendix D (Final, 10/25/00)

Page D-5

individuals living farther away are also concerned about water quality in the Fox River basin and

Green Bay (Breffle et al., 1999; Stoll, 2000b).

Other Studies. Other studies focus on Great Lakes areas outside of the NRDA assessment area.

Katz and Schuler (1995) survey public knowledge and opinions about Great Lakes issues in

general. Generally, respondents report that water quality is only fair overall. They also report

wanting more to be done to reduce pollution harmful to people (93%) and to reduce pollution

harmful to fish and wildlife (91%). There is significant concern even by respondents who live at

distances over 100 miles from the site, and by individuals living outside of the Great Lakes

basin.

Finally, a study was done to learn about environmental awareness and attitudes about Lake Erie

and the Ashtabula River by surveying random samples of Ashtabula County voters in Ohio

(Lichtkoppler and Blaine, 1999). Part of the contamination in Lake Erie is due to PCBs from the

Ashtabula River. The survey and WTP question in particular note that three other rivers

(Cuyahoga, Black, and Maumee) are sources of contamination to Lake Erie. While findings from

this study are not directly applicable to the Green Bay assessment, the two sites are roughly

comparable, and similar attitudes might be expected of Green Bay area residents as reported in

the Lichtkoppler and Blaine (1999) study.

In general, respondents attach high levels of importance to improving water quality, and they are

moderately aware of pollution problems. Out of 15 environmental issues related to Lake Erie and

the Ashtabula River, the three most important were improving water quality in the lake, reducing

contaminants in the river, and improving water quality in the river and harbor area. On a 1-to-6

scale (from not important to very important), each of these on average rated higher than 5.5. A

higher awareness of contamination issues was significantly correlated with higher importance

ratings as well, and higher WTP.

An iterative referendum CVM question for the dredging and disposal of contaminated sediment

in the Ashtabula River and Harbor was asked to assess monetary value. In the WTP question, it

is stated that the dredging will address the following five issues caused by contamination in the

lower Ashtabula River and Harbor areas:

} restrictions on consuming fish from the Ashtabula River and Harbor

} degraded fish and wildlife populations and habitat

} restrictions on dredging that jeopardize commercial and recreational boating

} fish with tumors and other deformities

} diminished quality of bottom habitat in the river.
Stratus Consulting Appendix D (Final, 10/25/00)

Page D-6

The lower bound mean estimate of WTP is $32.50 per household per year for 30 years (in 1996

dollars),2 and value was significantly correlated with resource awareness and recreational use

(and other individual characteristics), suggesting that those individual characteristics may be

important determinants of preferences in the current study. Note the WTP question describes the

benefits of dredging associated with the river only; it does not discuss any water quality

improvements to Lake Erie. Also, the range of values presented in the referenda may again be

truncated: the highest listed value is $200, although the respondent could report “more than

$200” and write in a value.

 

2. For comparison with results of other studies, the present value of 30 years of payments of $32.50/year, at a

3% discount rate, is approximately $650.