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i THESIS

 

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This is to certify that the
thesis entitled

ESTIMATING ECONOMIC VALUES FOR GREAT LAKES
COASTAL WETLANDS PROTECTION PROGRAMS

presented by

Oscar G. Arreola

has been accepted towards fulfillment
of the requirements for the

 

MS. degree in Resource Development

A1, /

 

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M mi] q] ZOO 31—

Date

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PLACE IN RETURN BOX to remove this checkout from your record.
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6/07 p:/CIRC/DateDue.indd-p.1

 

ESTIMATING ECONOMIC VALUES FOR
GREAT LAKES COASTAL WETLANDS PROTECTION PROGRAMS
By

Oscar G. Arreola

A THESIS

Submitted to
Michigan State University
In partial fulfillment of the requirements
For the degree of

MASTER OF SCIENCE

Department of Resource Development

2007

ABSTRACT

ESTIMATING ECONOMIC VALUES FOR GREAT LAKES COASTAL
WETLANDS PROTECTION PROGRAMS

By:

Oscar G. Arreola
Concerns about the loss of wetlands due to human activities have led to state and federal
efforts to protect wetlands on both public and private property. In designing wetland
protection programs, decisionmakers have to balance alternative program objectives,
competing priorities, and limited resources. This thesis presents the results of a study on
economic values related to programs for Great Lakes coastal wetlands conservation and
restoration. A mail survey was administered to a random sample of Michigan residents
and had a 40% response rate. The survey used the Attribute Based Referendum method,
and asked respondents about coastal wetland conservation / restoration programs with
attributes that varied across the sample. Program attributes included program focus or
priorities, the percentage of mix between conservation and restoration involved, and
alternative property acquisition mechanisms. Model estimates revealed that respondents
significantly preferred coastal wetland programs focusing on providing: i) water quality
and flood control, ii) biodiversity, and iii) waterfowl habitat, more than other possible
priorities (e. g. fish habitat, Open space). Respondents also preferred programs that
directed more effort at wetland preservation than wetland restoration. The data analysis
revealed a lower bound willingness to pay (WTP) for the coastal wetland programs of
$163/hhd which is roughly equivalent to a value of $20,500/acre of coastal wetland.
These results indicate that some individuals positively value wetland protection programs

and that they are willing to pay for such programs.

To my beloved family and to my wife Delanie Kellon.

iii

ACKNOWLEDGEMENTS

The work that is reflected in this thesis is the result of a team effort, and for that
reason, I would like to express my appreciation to my advisory committee members: Dr.
Michael Kaplowitz, Dr. Frank Lupi and Dr. Scott Witter.

This research project and my master’s program were possible thanks to the
financial support of Michigan Sea Grant, MSU Land Policy Institute, Michigan
Agriculture Experiment Station and USDA project W-1133. Also, I would like to
acknowledge MSU V.P. Poston and MSU-WATER for their contribution. I am also

grateful to the Ford Foundation and Lake Michigan Federation for their fellowships.

iv

TABLE OF CONTENTS

 

 

 

 

 

 

TABLE OF CONTENTS V
LIST OF TABLES VII
LIST OF FIGURES VIII
CHAPTER I: INTRODUCTION 1
CHAPTER 2: WETLANDS AND ECONOMIC VALUATION 7
WETLANDS AROUND THE WORLD ........................................................................... 7
DEFINITIONS OF WETLANDS .................................................................................... 7

WHY ARE WETLANDS IMPORTANT? ........................................................................ 9
WETLAND FUNCTIONS ............................................................................................ 9
WETLAND LOSS .................................................................................................... 10

THE LEGAL FRAMEWORK OF WETLAND CONSERVATION IN THE US. ................... 11

THE “NO NET Loss” POLICY ................................................................................ 13
GREAT LAKES COASTAL WETLANDS .................................................................... l3
REGULATION FOR WETLAND PROTECTION IN MICHIGAN ...................................... 14

THE ECONOMIC VALUE OF WETLANDS ................................................................. 16

Use Benefits .............................................................................................. I 7

Existence benefits ..................................................................................... 18

ECONOMIC VALUATION OF ENVIRONMENTAL BENEFITS ....................................... 18
VALUATION METHODS .......................................................................................... 20
Contingent valuation ................................................................................ 2]

WHY VALUATION? ................................................................................................ 23
PREVIOUS WETLAND’S VALUATION RESEARCH .................................................... 24
CHAPTER 3: SURVEY METHODS 28
INTRODUCTION ..................................................................................................... 28
SURVEY QUESTIONNAIRE DESIGN ......................................................................... 28

A) What do Respondents Know ................................................................ 29

B) What Program (Stated Choice) ........................................................... 2 9

C) Valuation Question (Contingent Valuation) ........................................ 30

D) Background ......................................................................................... 30

SURVEY QUESTIONNAIRE PRE-TESTING ................................................................ 31
Intercept Interviews .................................................................................. 3]

Debriefing Interview Sessions .................................................................. 32

SURVEY IMPLEMENTATION ................................................................................... 34
Sample ...................................................................................................... 34

Tailored Design Method ........................................................................... 35

Pre-notice Letter ...................................................................................... 36

First Survey Questionnaire ...................................................................... 36

Postcard ................................................................................................... 3 7

Second Survey Questionnaire ................................................................... 3 7

Third Survey Questionnaire ..................................................................... 3 7

DATA ENTRY AND RESPONSE RATE ...................................................................... 38

DEMOGRAPHIC CHARACTERISTICS OF THE SAMPLE ............................................... 4I

 

 

 

Behavioral Aspects of Respondents .......................................................... 42
CHAPTER 4: MODELS FOR ESTIMATION OF VALUES AND RESULTS ........ 44
EXPERIMENTAL DESIGN ........................................................................................ 44
Program Characteristics .......................................................................... 46

Combination of Program ’s Attributes Levels and Price Levels: Main
Effect Factorial Design ............................................................................ 48
ESTIMATION OF VALUES ....................................................................................... 49
PARAMETRIC MODEL - ATTRIBUTE BASED REFERENDA ........................................ 49
The Model ’s Theoretical foundation ........................................................ 50
The Random Utility Model with a Linear Utility Function: ..................... 52
RESULTS OF THE PARAMETRIC MODEL ................................................................. 55
SPECIFICATIONS OF THE MODEL ............................................................................ 57
GENERAL RESULTS FOR MODELS I TO 3 ............................................................... 59
Model 1 (x,- ) ............................................................................................ 60
Model 2 (x, + 21-) .................................................................................... 62
Model 3 ( Z j ) ........................................................................................... 63
NON-PARAMETRIC MODEL: APPLYING THE TURNBU LL ESTIMATOR ..................... 64
COMPARING THE ESTIMATION METHODS .............................................................. 66
EXPLAINING THE NO RESPONSE ............................................................................ 68
Accepting the proponed scenario when voting N0: ................................. 69
A N0 vote with comments related to “weak protest ” ............................... 70
Weak protest ............................................................................................. 71
Protest (Rejected the scenario) ................................................................ 72
Strong Protest .......................................................................................... 73
- CHAPTER 5: IMPLICATIONS AND RECOMMENDATIONS 75
IMPLICATIONS FOR MICHIGAN WETLAND’S POLICY .............................................. 75
RECOMMENDATIONS FOR FUTURE RESEARCH: METHODOLOGICAL ISSUES ............ 76
CONCLUSIONS - 78
APPENDIX 80
REFERENCES - - 102

 

vi

Table 1.

LIST OF TABLES

A typology of benefits associated with the improvement of freshwater quality for
purposes of economic valuation (adapted from Mitchell and Carson 1989) ..... 17

Table 2. Previous Research in Economic Valuation of Wetlands (adapted from LOSL
Report prepared by Werick, Lupi and Leger 2006. Valuating Wetland Benefits
Compared with Economic Benefits and Losses). .............................................. 26

Table 3. Survey Discussion Guide ................................................................................... 32

Table 4. Stratified Random Sample, Representing the Seven Most Populous Counties in
Michigan ...................... 35

Table 5. Response Rate Codes for the Sample ................................................................. 39

Table 6. Response Rate by Mailing Contacts ................................................................... 40

Table 7. Comparison Between Survey Respondents and Census Results for Michigan... 4]

Table 8. Priority: The Program’s Primary Focus. ............................................................ 46

Table 9. Possible Levels of Combined Effort Devoted to Preservation and Restoration..47

Table 10. Tool: Land Acquisition Method. ...................................................................... 47

Table 11. Cost To Implement the Program ...................................................................... 48

Table 12. Scale to vote for the program. .......................................................................... 49

Table I3. Variables Utilized in the Probit Model ............................................................. 55

Table 14. Definition of Dependent Variables ................................................................... 56

Table 15. Descriptive Statistics of Selected Variables ..................................................... 59

Table 16. Parametric Results Models 1 to 3. ................................................................... 60

Table 17. Tumbull Estimation Results ............................................................................. 65

Table 18. Type of No Vote .............................................................................................. 73

Vii

LIST OF FIGURES

Figure 1. Actual page from the survey showing the program scenario given to

respondents. ...................................................................................................... 45
Figure 2. Distribution of No Vote across Prices ............................................................... 64
Figure 3. Comparison of Models. .................................................................................... 67

viii

CHAPTER 1: INTRODUCTION

The coastal wetlands of the Great Lakes are unique and important ecosystems whose
functions provide diverse benefits to society and the surrounding environment. Wetlands
provide benefits such as: habitat for a significant number of wildlife species; water
quality improvements; flood and erosion control; aesthetic benefits; the reduction of
contaminant concentrations; carbon dioxide sinks; and even climate stabilization at a
global scale (Canadian Wildlife Service 2002, National Research Council 2001, Mitsch
and Gosselink 2000, Lewis 1995, Keating 1995, Mitsch 1994, Harrington 1993, Brown
1990, Maltby 1986). Since 1900, more than half of the wetlands of the world have
disappeared (Barbier 1993). In the United States, 117 million acres of the nation’s
original 221 million acres of wetlands have been lost (A National Program for Wetlands
Restoration and Creation, cited by Keating 1995). The greatest percentage of wetland
depletion in the United States has occurred in those states located along the eastern
seaboard, in the South, California, and areas adjacent to the Great Lakes (Keating 1995).
In the Great Lakes region, 70% of the area’s original wetlands have been lost, resulting in
a regional wetland loss that is significantly larger than the loss in the United States as a

whole (Brown 1990).

Concerns about the loss of wetlands due to human activities have led to state and federal
efforts, such as the “no net Ioss” goal, to protect wetlands on both public and private
property (National Research Council 2001). Several attempts have been made to establish
fimds for Great Lakes ecological restoration including the restoration of coastal wetlands,

and new legislative proposals such as the Great Lakes Collaboration Implementation Act,

the Great Lakes Environmental Protection and Restoration Programs Reauthorization Act
and the Great Lakes Environmental Restoration Act are aimed to protect and restore

coastal wetlands.

In the design of wetland conservation or restoration programs, decisionmakers have to
balance alternative program objectives, competing priorities, and limited resources. For
example, they may allocate resources to either protect existing wetlands or restore
wetlands that had been impaired by human activity. In light of the necessity of such
trade-offs, information on the public’s preferences for different coastal wetland program
characteristics would be helpful for developing wetland conservation policy.
Furthermore, an understanding of the characteristics of programs supported by Michigan
citizens, and an estimation of the public’s willingness to pay for these programs and
program characteristics would aid the design of wetland policy more likely to be

supported by the public.

Most wetland legislation contains references to the societal values that motivate wetland
protection since wetland functions support associated societal benefits (Lewis 1995). The
benefits that society derives directly or indirectly from ecosystem functions may be
considered ecosystem services (Costanza et al. 1998). However, private owners of
wetlands may not realize the full extent of the services that wetlands provide to society,
because private owners cannot easily profit directly from such large-scale and diffuse
services (Heimlich I998). The private economic benefits obtained by converting

wetlands to other land uses can be realized directly by the owner of the land and such

economic benefits have often been perceived as greater than preserving intact wetlands.
This condition can be interpreted as a private incentive to convert wetlands to other
competing land uses, which in the long run can result in large losses in social benefits

because of the loss of important wetland functions that provide services (Cwikiel 2003).

It is pertinent to point out that, although the value of a wetland is directly related to its
functions, economic value is an estimate of the worth of those functions to humans
(Canadian Wildlife Service 2002). Society does not necessarily assign value to all
wetland fimctions, since values are associated only to those functions that are interpreted
by individuals as services (Lewis 1995). Important wetland functions also provide
indirect services crucial for sustaining life in the Great Lakes’ region which may not be

clearly valuated or explicitly included as priorities in conservation programs.

A difficulty of estimating values for ecosystem services associated with wetland
functions is an absence of a market for them, despite the fact that society may consider
them important (Krutilla 1967; Costanza, Farber and Maxwell 1989; Wilson and
Carpenter 1999; Woodward and Wui 2001). Those ecosystem services without an explicit
market may be categorized as non-market goods and some uncertainty surrounds their

valuation and Significance (Turner, Pearce and Bateman 1994).

There is an important gap in the literature concerning Great Lakes coastal wetland
(GLCW) valuation. The available valuation literature for GLCW is limited to a handful

of studies including those by Amacher et al. (1989) and Whitehead et al. (2006). A recent

effort by the International Lake Ontario-St. Lawrence River Study resulted in a report
prepared by Werick, Lupi and Leger (2006). This report attempts to develop a crude
indication of economic values of benefits associated with Great Lakes wetland services

by compiling and comparing existing studies.

This thesis presents research results on public preferences for programs conserving and
restoring Great Lakes Coastal Wetlands. The purpose of this research is not to determine
whether Michigan residents demand protection of the state’s wetlands, rather it is to
understand what tradeoffs and preferences the public is willing to make for additional
programs targeting coastal wetlands restoration and preservation. It is expected that the
cost and characteristics of proposed wetland protection programs will influence the
respondents’ support of alternative programs. Simultaneously, the research examines
how demographic characteristics of survey respondents are associated with their

willingness to support coastal wetland protection programs.

This thesis presents the results of a state-wide contingent valuation survey that used an
attribute-based referendum (Holmes and Bole 2005) for a program to protect and restore
Great Lakes coastal wetlands in Michigan. The attribute-based referendum (ABR)
approach is a variant of the contingent valuation and stated choice methods in which
individuals are presented with a referendum valuation question for a program whose

attributes (characteristics, including price) are experimentally varied across the sample.

A main effects factorial design (Louviere et al. 2000) was utilized for the experimental

design of the attribute-based referendum.

The attributes used in the survey’s design are characteristics of proposed Great Lakes
coastal wetland conservation-restoration programs. These attributes are explained to
respondents in the survey booklet and are subsequently used in the valuation question.
The attributes included: (i) ecosystem services that serve as the primary focus of the
program (biodiversity, waterfowl habitat, fish habitat, non-game species, water quality
and flood control, and open space near cities), (ii) a mix of program effort devoted to
preservation of high quality wetlands and effort allocated to restoration of impaired
wetlands, (iii) the method used to acquire land from voluntary private land-owners, and
(iv) program cost in the form of a one-time statewide tax payment (seven levels ranging
from $40 to $1,320). The referendum question presented respondents with one program
with a set of attributes together with a specific price for the program’s implementation.
Respondents were asked to vote Yes / No to pay a one-time tax for the proposed

program’s implementation.

The coastal wetland questionnaire was designed using an iterative process of focus
groups and individual interviews (Kaplowitz, Lupi and Hoehn 2004) to produce a survey
booklet with wetland information, policy context, and valuation questions that were
understood and seen as plausible by respondents. The mail survey was implemented in
2004 and distributed to a random sample of 1,505 licensed drivers and state identification

card holders in Michigan. Using a Dillman “tailored design method” (Dillman 2000),

potential respondents received up to five contacts including as many as two replacement
survey booklets. The response rate1 for this statewide survey was slightly more than 40%

(AAPOR 2006).

The survey data were analyzed using both non-parametric (Tumbull) and parametric
(probit) methods. The Tumbull estimator was used to estimate a lower bound willingness
to pay, while the parametric method (standard discrete choice econometric model) was
used to infer the effect that each attribute had on the probability of voting for the
program. The results and models developed in this thesis should aid decisionmakers in
evaluating public preferences and support for policies and programs for protecting and

restoring GLCW.

 

l The response rate presented here is Response Rate (RR2),‘ which includes partial interviews (AAPOR
2006).

CHAPTER 2: WETLANDS AND ECONOMIC VALUATION

Wetlands around the World

Wetlands are among the most ecologically diverse and productive ecosystems in the
world (Maltby 1986). The global extent of wetlands is estimated to be six percent of the
world’s land surface. Despite this, wetlands have become a focus of conservation efforts
due to the alarming rates at which they are disappearing (Mitsch and Gosselink 2000).
The importance of wetlands is so significant that it is the only ecosystem type that has
prompted its own international convention, the Ramsar Convention of 1971, under which
signatory countries agreed to include wetland conservation in their national planning and
promote the wise use of these ecosystems (Mitsch and Gosselink 2000, Maltby et al.

1986).

Definitions of Wetlands
The definition of wetlands varies across the literature and is problematic. Most
definitions revolve around the presence and interaction of the biotic and abiotic
components of a wetland. Mitsch and Gosselink (2000) suggest three main components
of the definition of a wetland:
1. Hydrology: the area is defined by the presence of surface or ground (root zone)
water.
2. Physicochemical environment: the soils in the area often have unique
characteristics related to wet conditions.
3. Biota: wetlands support vegetation, animals and microbes that are adapted to wet

conditions.

The quality and interaction of these three components serve as the basis for these
productive ecosystems to generate associated benefits to the surrounding environment

and pe0ple.

A precise definition can help delimit these ecosystems for scientific understanding and
for their proper management. The Committee on Characterization of Wetlands for the U.
S. National Academy of Sciences (National Research Council 1995) gives another
definition for US. wetlands. While recognized as the most comprehensive definition of
wetlands (Mitsch and Gosselink 2000), NRC (1995) definition fails to stress the
importance of key factors necessary for wetlands when it describes hydric soils and
hydrophytic vegetation as “common diagnostic features”.
“A wetland is an ecosystem that depends on constant or recurrent, shallow
inundation or saturation at or near the surface ofthe substrate. The minimum
essential characteristics of a wetland are recurrent, sustained inundation or
saturation at or near the sutface and the presence of physical, chemical, and
biological features reflective of recurrent, sustained inundation or saturation.
Common diagnostic features of wetlands are hydric soils and hydrophytic
vegetation. These features will be present except where specific physicochemical,
biotic, or anthropogenic factors have removed them or prevented their
development. "
Definitions of wetlands vary across disciplines and purposes, and they are usually too
broad to be specifically applied in regulatory practices without being accompanied by
context-specific interpretation (Lewis 1995). For this thesis, wetlands are defined based
on US. Army Corps of Engineers regulation and Michigan’s legislation:

“ Wetland means [and characterized by the presence of water at aflequency and
duration sufficient to support, and that under normal circumstances does support,

wetland vegetation or aquatic life, and is commonly referred to as a bog, swamp,
..2
or marsh...

Why Are Wetlands Important?

Wetland ecosystems play an important role in sustaining life systems. They are known as
“the kidneys of the landscape” because of the ecological functions they perform and as
“biological supermarkets” because of the extensive food webs and rich biodiversity they
support (Barbier, Acreman and Knowler 1997, Mitsch and Gosselink 2000). Wetlands
are commonly compared to trepical rain forests and coral reefs because of the diversity of
species that rely on wetlands for habitat (Dennison and Schmid 1997). Wetlands are also
important components of watersheds because they are critical in the transition from
terrestrial to aquatic environments (Amacher et. al 1989, Lewis 1995, Dennison and

Schmid I997).

Wetland Functions

Wetland fimetions can be defined broadly as all processes and manifestations of
processes that occur in wetlands (Lewis 1995). Through these functions, wetlands are
capable of providing a wide range of benefits that can be interpreted as services, such as:
habitat for a significant number of wildlife species; water quality improvements; flood
and erosion control; aesthetic functions; reduction of contaminant concentrations; carbon
dioxide sinks; and even as climate stabilizers at a global scale (Canadian Wildlife Service
2002, National Research Council 2001, Mitsch and Gosselink 2000, Lewis 1995, Keating

I995, Mitsch I994, Harrington 1993, Brown 1990, Maltby 1986). Specifically with

 

2 www.lcgislature.mi.gov §324.3030l

respect to wildlife habitat and biodiversity conservation, wetland ecosystems represent
unique habitats for migratory and endemic species. Over one third of all bird species in
North America rely on wetlands, which are also the preferred habitat for animals such as
muskrat, beaver, otter, mink, and raccoon (Heimlich 1998). Wetlands can also provide
goods and service for direct use by people such as recreation and water transport; and
wetlands can be used for fishing, agriculture, wildlife products, wood products, and water

supply (Barbier 1994).

Although wetlands provide people, directly and indirectly, with an enormous range of
goods and services that have effects beyond the wetland boundary, peOple did not fully
realize their value to human society until recently (Barbier 1994). Historically, wetlands
have been converted to other land uses and are increasingly disappearing as a result of

development decisions (Barbier 1993, Matlby 1986, Canadian Wildlife Service 2002).

Wetland Loss

When wetlands are lost or damaged, the many fimctions they provide to the surrounding
environment are lost or compromised as well (Mitsch and Gosselink 2000). A
considerable percentage of wetland ecosystems have been lost or impaired by draining,
filling, dredging, excavating, building, polluting and other development activities (Brown
1990). Since 1900, more than half of the wetlands of the world have disappeared
(Barbier 1993). In the United States alone, 117 million acres of the nation’s original
inventory of 221 million acres of wetlands have been lost (Keating 1995). There has

been a loss of about 53% of the country’s original wetlands, of which 87% has been lost

10

to agricultural development, 8% to urban development, and 5% to other conversions
(Dahl 2000, Maltby 1986). The greatest percentage of wetland loss in the United States
has occurred in those states located along the eastern seaboard, in the South, adjacent to
the Great Lakes, and in California (Keating 1995). In the Great Lakes region, only 30%
of the original wetland area remains intact, representing a regional wetland loss that is
significantly larger than the loss throughout the United States as a whole. In Michigan,
the remaining area covered by wetlands is also 30% of the original wetland area (Brown

1990).

In the past, the functions of wetlands were neither understood nor appreciated by the
nation’s citizens, and wetlands were drained and filled in the name of development
decisions (Hey and Philippi 1999). In the early 19703, interest in wetlands increased as
scientists began to identify and quantify the significance of these ecosystems for the
services they provide (Mitsch and Gosselink 2000). As awareness about wetland services
grew, federal wetland programs evolved from offering incentives for wetland conversion,
to regulatory programs for conservation and incentives that promote restoration and
protection (Heimlich 1998). To prevent the loss of more wetland acreage, state, federal
and local regulatory programs currently operate in combination to place conditions on

wetland permits in an effort to avoid, reduce, and mitigate wetland loss.

The Legal Framework of Wetland Conservation in the U.S.

Most of the legislation dealing with wetlands contains references to the societal values

that motivate wetland protection given that some wetland functions are associated with

ll

societal benefits and values (Lewis 1995). Wetland laws attempt to determine where an
individual’s property rights end and where the public’s interest in resource protection
begins (Cwikiel 2003). Consequently, wetlands are the only ecosystem type to be
comprehensively regulated across all public and private land within the United States

(Lewis 1995).

Since 1899, several federal laws, directives and regulations have been implemented in the
United States to protect wetlands. However, not until the 1970s did the federal
government begins a more committed approach to carry out wetland protection through
executive orders and legislation (Lewis 1995). The primary federal laws that regulate
activities that impact wetlands are Section 401, Section 402 and most importantly,
Section 404 of the Clean Water Act (33 U.S.C. 1344). Section 10 of the Rivers and
Harbors Act (33 U.S.C. 403) also plays an important role in wetland regulation (Cwikiel
2003, Mitsch and Gosselink 2000, Dennison and Schmid 1997, Brinson and Rheinhardt
l 996). The objective of the Clean Water Act (CWA) is to “restore and maintain the
chemical, physical, and biological integrity of the Nation’s waters” (NRC 2001). The
CWA confers the U.S. Army Corps of Engineers or state with an Environmental
Protection Agency (EPA)-approved program with the authority to implement and issue
Section 404 permits (NRC 2001 ). It was not expected that the Section 404 would, by
itself, completely prevent the loss of wetlands, however it was meant to guarantee the

minimization of losses wherever possible (Hey and Philippi 1999).

12

The “No Net Loss” Policy
The U.S. EPA initiated a national wetlands policy development initiative in 1987 by
requesting that the Conservation Foundation convene a National Wetlands Forum to
investigate the use and management of wetlands across the nation. The members of this
Forum formulated the following goal in 1998:
“To achieve no overall loss of the nation’s remaining wetlands base and to create
and restore wetlands, where feasible, to increase the quantity and quality of the
nation’s wetland resource base” (Kean, National Wetlands Policy Forum and
Conservation Foundation 1998).
The EPA, which is jointly responsible together with the Army Corps of Engineers for
regulating the mitigation of damages to wetlands, requested that the National Research
Council evaluate the mitigation practices that were being used to restore and maintain the
quality of the Nation’s waters as regulated under Section 404 of the CWA. Recognizing
the importance of wetlands’ functions and values under the “no net loss” policy
established by the Bush administration in 1989 (National Research Council 2001), the
Committee on Mitigating Wetlands reported that the CWA cannot be achieved if
wetlands are lost. This is supported by the fact that one of the most important wetland
contributions is the protection of water resource quality, which is directly linked to the

quality of the environment surrounding the wetlands (Dennison and Schmid 1997).

Great Lakes Coastal Wetlands
There are approximately five million acres of inland and coastal wetlands in Michigan

(with a greater concentration in the Upper Peninsula), an area that corresponds to 30

I3

percent of the State’s territory (Gaddie and Regens 2000). GLCW represent unique and
biologically important ecosystems in the Great Lakes region (Canadian Wildlife Service
2002), they occur along the Great Lakes shoreline and in portions of tributary rivers and
streams that are directly affected by Great Lakes water regimes (Albert 2003). Despite
their ecological value, Great Lakes coastal resources are under increasing pressures from
urban sprawl, coastal development, beach grooming, invasive species, hydrologic

changes, and environmental degradation.

Evidence of the importance of coastal wetlands becomes more apparent when their
functions are identified and quantified in the context of the surrounding environment they
benefit. For example, of the approximately 200 fish species supported by the Great
Lakes, 90% live in coastal wetlands during some part of their lives, and large numbers of
geese, ducks and swans utilize the coastal marshes as a stationary feeding point during
their annual migrations (Albert 2003). A sharp decline in fish and waterfowl populations
was the first evidence of severe coastal wetland degradation, which eventually had a
negative effect on the economy and recreation activities of local communities. The
negative impact that chemical and physical degradation of the lakes’ waters had on
humans was an important factor that activated the clean-up of the Great Lakes, including

their wetlands (Albert 2003).

Regulation for Wetland Protection in Michigan

In Michigan, the Michigan Department of Environmental Quality (MDEQ) and the U.S.

Army Corps of Engineers share the responsibility of administering and enforcing the

I4

federal wetlands regulatory program. The State’s core legislation regulating this matter is
Michigan’s Wetland Regulatory Program, part 303, Wetland Protection of the Natural
Resources and Environmental Protection (Act 451 of 1994). The State of Michigan
through the MDEQ is one of the two states that have assumed the administration of
Section 404 of the Clean Water Act (Cwikiel 2003). MDEQ uses the definition of
wetlands as specified by Michigan’s legislature in the Natural Resources and
Environmental Protection Act, which applies to public and private lands regardless of

zoning or ownership:

“Wetland means land characterized by the presence ofwater at a frequency and
duration sufficient to support, and that under normal circumstances does support,
wetland vegetation or aquatic life, and is commonly re erred to as a bog, swamp,

9’3
or marsh...

Landowners and developers who wish to carry out activities on wetlands and
consequently impair, damage or fill-in a wetland, are required to apply for permits with
respect to federal, state and local laws and regulations. The CWA expects that the Corps
of Engineers, in cooperation with Michigan’s Wetland Protection Act, will consider the
public interest consequences when considering whether or not to issue a permit. The
determination of the impact on public interests is considered in the context of those
wetland fimctions that can be negatively affected by the proposed activity (Cwikiel

2003).

 

3 wwwlegislaturemi.gov §324.3030l

l5

If a permit is issued, project approval is conditional upon compensatory actions intended
to avoid the loss of wetland area and functions. That is, if wetlands are impaired or
destroyed, wetland mitigation is required by law. Mitigation refers to actions taken by the
landowner or developer to recreate, restore, or protect wetlands of an equivalent type and
fiJnction to those being impaired or destroyed (Dennison and Schmid 1997, Brinson and

Rheinhardt I996).

The Economic Value of Wetlands

For the services they provide to society, wetlands are resources that should be properly
valued; however, private owners of wetlands cannot realize the full extent of the services
wetlands provide to society at large, because private owners cannot profit directly from
such large-scale services (Heimlich 1998). The private economic benefits obtained by
converting wetlands to other land uses can be acquired directly by the owner of the land.
This condition can be interpreted as a private incentive to convert wetlands to other
competing land uses, which in the long run can result in larger economic losses to society

from the loss of wetland services (Cwikiel 2003).

It must be pointed out that although the value of a wetland is directly related to its
functions, value is an economic estimate of the worth of those functions to humans
(Canadian Wildlife Service 2002). Society does not necessarily assign value to all
wetland functions, since values are associated only to those functions that are interpreted
as services (Lewis 1995). Important functions that provide indirect services are also

crucial for sustaining life in the Great Lakes’ region and still are not clearly valuated or

16

explicitly included as priorities in conservation programs. Carson and Mitchell (1983)
developed a typology of benefits (Table 1) associated with freshwater ecosystems, which

is intended to include all of the possible benefits of freshwater quality improvements.

Table 1. A typology of benefits associated with the improvement of freshwater
quality for purposes of economic valuation (adapted from Mitchell and
Carson 1989)

 

 

Benefit Benefit Benefit
Class Category Subcategory
Use ln-stream Recreational (water sports, fishing,

boating, swimming)
Commercial (fishing, navigation)
Withdrawal Municipal (drinking water, waste
disposal)
Agriculture (irrigation)
Industrial/commercial (electricity)
Aesthetic Enhanced near-water recreation
(hiking, picnic, photography)
Enhanced routine Viewing (commuting,
office/home views)
Ecosystem (functions) Enhanced recreation support
(waterfowl hunting)
Enhanced general ecosystem support
(food chain, habitat, flood control)

 

Existence Vicarious Consumption Significant other (relatives, close
(or non-use) friends)
Diffuse others (the nation / world
pubhc)
Stewardship Inherent (preserving remote wetlands)

Bequest (family, future generations)

 

Use Benefits
Use benefits can be separated into direct and indirect uses. Direct benefits consist of
those derived from people’s direct interaction with the ecosystem and include
consumptive uses of the resource. Indirect benefits are those provided by the wetlands’
natural functions and fall under the “aesthetic” and “ecosystem” type of benefits. These

benefits include the non-consumptive use of resources (Mitchell and Carson 1989,

I7

Barbier 1993). The benefits that society derives directly or indirectly from ecosystem

fiInctions can be considered ecosystem services (Costanza et al. 1998).

Benefit measurement techniques that include the role played by the ecosystem can be
utilized to derive the value of direct and indirect uses. For direct uses associated with
commercial activities, the value can be assessed observing changes in the market prices
of those activities (Mitchell and Carson 1989). For indirect uses, the values might accrue
for ecosystem services that indirectly provide consumption goods or have an effect on

consumption goods, for example: aesthetic benefits or flood control (Sterner 2003).

Existence benefits
The value of this type of benefit can be derived from the value that the individuals attach
to the mere knowledge that a unique natural ecosystem exists, even if the individual does
not contemplate ever being able to use of the resources in that ecosystem (Portney 1994,
Wilson and Carpenter I999). The values derived fi'om this type of benefit are also called
“existence values” or “passive values” (Mitchell and Carson 1989; Portney 1994).
Economic Valuation of Environmental Benefits
While economic valuation of environmental benefits was explicitly prohibited when
environmental regulations where initially set (Cropper and Oates 1992), as regulation
evolved, economic valuation became more important. Currently, wetland regulations
such as the U.S. Clean Water Act require economic valuation of environmental benefits
(Carpenter and Turner 2000). Thus, valuing a wetland now essentially requires valuing

the ecosystem services.

l8

While several dimensions of use values and existence values are plausibly
distinguishable, and all enter into a consumer’s utility function, they are likely to be very
difficult to separate and measure individually (Mitchell and Carson 1989). In an
economic sense, a wetland is not a generic economic commodity. Rather, a wetland is a

multi-attribute bundle of benefits (Hoehn, Lupi and Kaplowitz 2003).

A difficulty of estimating values for many ecosystem services associated with wetland
functions is that there is no market for them, despite the fact that society considers them
important (Krutilla 1967, Costanza, Farber and Maxwell 1989, Wilson and Carpenter
1999, Woodward and Wui 2001). These goods are categorized as non-market goods and
some uncertainty surrounds their true value and significance (Turner, Pearce and

Bateman 1994).

The complication of not knowing the true value of wetland services is worsened when
individuals and decisionmakers have to make choices and trade-offs concerning
ecosystem services and development decisions. This trade-off situation implies and
requires valuation, because in a cost-benefit structure, any choice between competing
alternatives implies that the one chosen was more highly valued. In that sense, it is
important to realize what is being traded (Turner, Pearce and Bateman 1994, Costanza
2000, Perrnan et al. 2003). An accurate valuation of environmental goods and services is
becoming increasingly important as the ecosystems that provide them become more

scarce (Farber and Costanza 1987).

I9

Valuation methods

The economic value of a good or service is generally established in terms of what society
is willing to pay for that commodity and deducting the production costs. In the case of
natural resources that simply exist as “given” by nature. Where the public perceives that
there is no cost in producing the environmental goods it is our willingness to pay for the
good / service that establishes its value (Barbier, Acreman and Knowler 1997).
Researchers use two basic approaches for benefit valuation: A) revealed preference
methods and B) stated preferences methods (Freeman 2003). Among these two

approaches, several methods are available to estimate environmental values.

Revealed preference methods are essentially those that reflect the actual behavior of the
respondent when facing decisions about utility maximization subject to constraints. For
example, if an individual is offered a fixed quantity of a good at a given price on a yes-no
basis (as in referendum), the observation of the choice made by the individual reveals
only whether the value of the offered good to the individual was greater than or less than
the offering price (Freeman 2003). Examples of these methods are travel cost and

hedonic pricing.

Stated preference methods differ from in that they draw the value from people’s
responses to hypothetical questions rather than from observations of the real world
choices. In the simplest approach, stated preferences questions can present a hypothetical

market and directly ask (carefully worded survey questions) people what value they place

20

on environmental amenities. If the market scenario is plausible and the responses truthfirl,
the data elicited in the form of monetary amounts, choices, ratings, rankings, or other
indication of preference are scaled following appropriate models of preference to yield a
measure of value (Freeman 2003, Pennan et al. 2003, Champ, Boyle and Brown 2003).
While a variety of methods utilize this type of questioning, the most prevalent approach

is contingent valuation (Freeman 2003).

Contingent valuation
Since the publication in 1979 of “Principles and Standards for Water and Related Land
Resources Planning”, contingent valuation (CV), along with the travel method and the
unit day value method have been accepted as useful for determining project benefits
(Mitchell and Carson, 1989). CV has also been recognized as an approved method for
measuring benefits and damages under the Comprehensive Environmental Response,
Compensation, and Liability Act of 1980 (Superfund), according to the final rule
promulgated by the Department of the Interior in 1986 (Portney 1994). The literature in
CV is extensive (e.g., Cummigns et al. 1986, Mitchell and Carson I989, Bromley 1995,
Bateman and Willis 1999, Stavins 2000, Freeman 2003, Champ, Boyle and Brown 2003,
Haab and McConell 2003). For this thesis only the most relevant aspects of CV are

discussed.

CV was used in the reported research to elicit people’s preferences for a wetland

conservation or restoration program. Respondents were asked how they would vote for a

wetland protection program at a given price. The approach aimed at eliciting the

21

citizen’s willingness to pay (WTP) in dollar amounts for a GLCW conservation /

restoration program.

The goal in designing a CV survey is to formulate the question and scenario around a
specific “commodity” that captures what one seeks to value, yet is plausible and
meaningfirl (Hanemann, 1994). This research works when it presents a scenario that
seems real to respondents so that respondents answer truthfully while aware of their

individual budget constraints and preferences (Mitchell and Carson 1989).

The basic procedure is to ask CV survey questions that lead directly to WTP, or provide
information that may be used to estimate preferences (Haab and McConnell 2002). Some
common elicitation methods include:

0 Open Ended CV: A question in which respondents are asked to state an estimate
of their WTP for the good provided.

0 Bidding Game: Respondents are asked iteratively whether they would be willing
to pay a certain amount. The amounts are changed (lowered or raised) depending
on whether the respondent was or not willing to pay the first amount offered. The
number of iterations varies depending on the variant of the method utilized.

0 Payment Cards: A CV question format in which individuals are asked to choose
a willingness to pay point estimate (or a range of estimates) from a list of values
predetermined by the researchers, and shown to the respondent on a card.

0 Dichotomous or Discrete Choice: A CV question format in which respondents

are asked to respond yes or no to a predetermined amount.

22

The Dichotomous Choice approach has become quite widely adopted and a preferred
method of elicitation for CV practitioners (Haab and McConnell 2002). More details on

how the method was applied in this thesis are presented in Chapters 3 and 4.

Why valuation?

Valuation methods are important tools to assess and quantify values associated with
environmental amenities that have important roles sustaining life and providing quality of
life. A monetary expression of these benefits is one approach for judging the relative
importance of the environment when facing trade-offs. However, the cost of regulation
also plays a role in benefit and cost analysis. For example, Cropper and Oates (1992)
used EPA data to list the major pieces of environmental regulation and estimated the
costs of full compliance with all Federal regulations. For full implementation of the Clean
Water Act (CWA) throughout the entire nation, a total of $38,823 million4 would be
required annually. These costs ought to be compared with the attainable values in health,
recreation, water quality, and other ecosystem services in order to recognize the full

impact of the trade off.

On the other hand, the implementation of environmental protection policies is costly. For
instance, Jaffe et al. (1995), who also used EPA data, stated that the annual cost to the
United States for complying with environmental regulation equals 2.1 percent of the

gross domestic product, which in 1995 was approximately $125 billion. For the

 

“ In 1986 Dollars

23

implementation of Section 404 of the CWA in 1984, the Michigan Government estimated
that it would need to spend $462,0415 annually and hire five additional staff members

(Gaddie and Regens 2000).

Therefore, in the face of constant concerns about the cost of environmental regulation,
the need for assessing the values of multiple environmental services becomes extremely
important in evaluating alternatives. Although there is little evidence to support the
hypothesis that environmental regulations have had a serious, adverse effect on the
productivity of the country (Jaffe et al. 1995), in protecting or restoring wetlands, the
extent to which public and private resources should be used is still subject to debate.
Existing wetland laws do not find wetland preservation and restoration. The mere
existence of a market failure does not automatically warrant the implementation of a
given policy because the costs of market failures must be weighed against the potential

for “policy failures” (Sterner 2003).

Previous Wetland’s Valuation Research

Research efforts to estimate the value of wetlands have been increasingly more frequent.
An interesting example is the work of Farber and Costanza (1987) who used two methods
to estimate values for an entire wetland system by aggregating value measures of
different wetland services. Their WTP estimations for commercial fishing and trapping,
recreation and storm protection was about $590 per acre. Using an energy analysis

evaluation, their research estimated values in a range of $6,400 to $10,600 per acre. The

 

5 In I990 Dollars

24

authors considered the WTP estimation as undervaluing the wetland since several
wetland services seemed to be excluded from the analysis. On the other hand, they
believed that the energy analysis method overestimated the value of wetlands because it

includes wetland goods and services that may not be economically valuable.

There is a lack of GLCW valuation studies especially those studies associated with
restoration and preservation programs for GLCW. The literature available on valuation of
GLCW is limited to a handful of studies carried out mostly by Amacher et al. (1989) and
more recently by Whitehead et al. (2006) who estimated the economic values of Saginaw
Bay coastal marshes with multiple methods. Using two samples (Sportsmen and general
public), the Whitehead et al.’s Saginaw Bay study used CV to estimate willingness to pay
for a hypothetical “Saginaw Bay Coastal Marsh Protection Program”, which involved the
purchase of coastal marshes. This study found that an annual value of $1 13,000 for
protecting 1,125 acres of coastal marshes, for recreation and other not specified values
These authors are cautious in stating that this value may be too low considering that it
only addresses part of the overall importance of the subject wetlands and does not include

ecological services that might have additional values.

Werick, Lupi and Leger (2006) recently prepared a report for the lntemational Lake
Ontario-St. Lawrence River Study (LOSL). In this report, the authors attempt to deVCIOp
an indication of the economic value of benefits associated to wetland services by
compiling and comparing studies to evidence that wetland’s benefits have economic

value. Table 2, shows the main research results compiled by the authors of that report.

25

Table 2. Previous Research in Economic Valuation of Wetlands (adapted from

LOSL Report prepared by Werick, Lupi and Leger 2006. Valuating Wetland

Benefits Compared with Economic Benefits and Losses).

 

 

 

 

 

 

Reported Values
Study Services Per Acres/ Yr.
(Converted to 2006 $US)

Woodward and Wiu, 2001. Flood $595

Quality $632

Quantity $192

Recreational fishing $541

Commercial fishing $1,179

Bird Hunting $106

Bird Watching $1,836

Amenity $5

Habitat $464

Storm $359
Kazmierczak Habitat and species $287

protection
Costanza et al Habitat/refirgia $235

Recreation $263

Total ecosystem services $10,482
Breunig Total ecosystem services $17,307
Olewiler Total ecosystem services $4,217

(LOW)

Total ecosystem servrces $17,712

(High)

The authors of the LOSL Report offered the caveat that making generalizations about

wetland values is difficult since different types of wetland provide very different services.

Similarly, where a wetland is located in relation to people will affect its value. Moreover,

the demographic characteristics and behavior of the people surveyed will affect the

values they assign to wetlands. Consequently, and in contrast to some types of non-

26

market values, the wetland values per acre reported in the literature vary widely (Werick,

Lupi and Leger 2006).

27

CHAPTER 3: SURVEY METHODS

Introduction

This chapter presents the methods used for constructing and implementing a CV study
with state of the art survey design techniques. Fundamental elements of the survey
questionnaire design are presented, followed by discussion of survey pre-testin g,
implementation procedures, data entry management and response rate estimation.
Finally, demographic information of the respondents is compared to Michigan’s general

population

Survey Questionnaire Design

The order in which the information in the survey is presented and how the questions are
arranged in the survey used in this thesis, reflect the suggestions of the NOAA Panel
review on how to increase the effectiveness and reliability of CV instruments (Mitchell
and Carson 1989; Portney 1994; Hanemann 1994; Diamond and Hausman 1994).
According to Carson, Flores and Meade (2001), the general guidelines for a CV survey
design include the following steps: i) an introductory section to set the general context
for the decision to be made; ii) a detailed description of the good to be offered to the
respondent; iii) the institutional setting regarding how the good will be provided; iv) the
payment vehicle; v) the method to elicit the respondents’ preferences with respect to the
good; vi) debriefing questions about why respondents answered certain questions the way
that they did; and vii) information about the respondents’ characteristics including

attitudes, demographic information and debriefing questions.

28

The self-administered questionnaire was designed in accordance with state of the art
methods and was implemented following the Tailored Design Method (Dillman 2000).
The questionnaire booklet was made to be as “user-friendly” as possible in order to make
it easier for respondents to understand, follow and respond (see Appendix for the
complete questionnaire). The final survey instrument consisted of 52 items, grouped
under 24 headings, and separated into four sections that elicited the answers to the
following questions: A) what do respondents know about wetlands and what do they do
in wetlands; B) what kind of conservation program would they prefer; C) what is their
willingness to pay for that program; and lastly, D) what are some characteristics and

behaviors of the respondents.

A) What do Respondents Know
The first section of the survey gathered information on respondents’ knowledge of and
experience with Great Lakes coastal wetlands (GLCW). This section of the survey also
included information for respondents on the types of program characteristics associated
with wetland protection and restoration. The questionnaire offered scientific definitions
and explanations of GLCW and functions and services. Color pictures were used to

illustrate the concepts.

B) What Program (Stated Choice)
The second section consisted of a “stated choice” question, which was used to collect
information on the public’s preferences for conservation programs utilizing an attribute

based method. For more information on this part of the research, see Gibson (2005).

29

C) Valuation Question (Contingent Valuation)
The third section of the questionnaire is the focus of this thesis: a CV question using an
attribute based referendum format. This section is intended to gather information to
detect what value respondents place on particular wetland program attributes. This
question took one of the programs presented as an alternative program in the stated
choice question and added a monetary value to it. The CV question then asked
respondents if they would vote to approve the specified program, if they had to pay for it.
The cost was presented as a one-time payment which would be added to citizens’ taxes.
The CV question was followed by a question that prompts respondents for input as to
their reasoning behind their answer. The follow up question was used to gain insight into
the respondents’ decision making process and to test their understanding and acceptance

of the contingent valuation scenario (Hanemann 2005).

D) Background
The last section asked for background information on the respondents (e. g. attitudes,
behaviors, demographic characteristics). This information is valuable for evaluating how
representative of the general population the respondents are, as well as for obtain data

about respondents that might help explain the results.

30

Survey Questionnaire Pre-Testing

Presser (2004) recommends that high quality survey instruments need to be pre-tested as
part of the design and development process6. Pro-testing helps to ensure that the
questionnaire language is understandable and that the questions asked are realistic and
meaningfiil. Also, through pre-testing, the researcher can find out what the instrument’s
questions mean to people (Hanemann 1994). For the GLCW survey, pre-testing was

conducted in two stages: intercept interviews and debriefing interviews.

Intercept Interviews
The debriefing interviews were carried out by interviewing randomly selected
participants in public venues. To do this, two different “food courts” at shopping malls
were used as the pre-testing locations. Twenty of these pre-testing sessions were
conducted. Researchers approached individuals and asked them if they would be
interested in filling out and commenting on a “public policy survey”. Potential
participants were told they would receive an honorarium often dollars as an incentive for
participating, which was paid at the beginning of the session. Participants were asked to
fill out a draft of the survey questionnaire. Subsequently, an interview session was
conducted covering a series of questions pertaining to the questionnaire, its design, and

participants’ opinion of it (see Table 3).

The questions asked by researchers during this stage of pre-testin g were designed to

determine whether or not respondents understood the information and questions in the

 

6 See Kaplowitz, Lupi and Hoehn in Presser 2004, 503 -524 for further detail regarding Multiple Methods
for Developing and Evaluating a Stated-Choice Questionnaire to Value Wetlands.

31

questionnaire, and to find out if the correct amount and type of information was provided
to respondents. The pre-testing survey was also intended to evaluate whether or not the

contingent valuation question was designed properly.

Table 3. Survey Discussion Guide

 

1. Overall impression of the questionnaire
3) What did you think of the questionnaire?
b) Was there any information in the questionnaire that seemed odd or awkward to you?
c) Did the information that was provided help you to answer the questions?
Describe how.
(I) Were there questions where you would have liked more information? What
information?
e) Were there any areas where too much information was provided?
2. Wetland program
a) Now, I want to talk about the question near the end that asked how you would vote
on the wetland program. Tell me about what went through you mind as you made
your decision.
b) In your own words, describe to me what the program would provide.
c) How would coastal wetlands change if the program were implemented?
(1) How would the services provided by coastal wetlands change with the program?
e) Talk me through the table describing the program. What does each of these mean to
you?
f) How would the program affect you?
g) Was the program realistic to you?

3. Other

 

Debriefing Interview Sessions
In addition to intercept pre-testing, three debriefing interview sessions were conducted at
Michigan State University’s campus. Potential participants in mid-Michigan were

contacted by telephone through a system of random dialing telephone numbers from local

32

phone directory (Hoehn, Lupi and Kaplowitz 2003). After a brief screening interview,
participants were invited to campus for scheduled individual interviews and offered $20
to attend. The three sessions took place on November 20, December 4 and December 10,

2003. All together 23 debriefing interviews were conducted.

One week prior to each interview session, interviewers made telephone contact with
randomly Selected residents in mid-Michigan. Interviewers initially asked each potential
interviewee their age, education level, and gender. Any calls for which the demographic
characteristic had been filled was terminated at this point in order to avoid over sampling
any particular group of individuals. For each debriefing session, only one person from
the 18-25 year old age group was recruited, and no one with an education level of a
master’s degree or beyond was recruited for any of the sessions. Individuals who
possessed a master’s degree or beyond were not sampled because they were not a group
of concern for respondent comprehension. The researchers also sought to achieve an even
distribution of males and females in order to correspond to the almost equal ratio of

males to females in the state’s population.

On the evening of the debriefing interviews, invitee were told when they arrived that they
were to complete a self administered survey questionnaire on public policy, and then
individually discuss their answers with an interviewer. On average, the interviewees took
about ten minutes to complete the questionnaire. Following the completion of the
questionnaire, a 20-minute interview regarding their reaction to the survey instrument

was conducted. Based on the results of these pre-testing interviews, modifications to the

33

survey questionnaire were made in order to make it clearer, and to improve its overall

design.

Survey Implementation

Sample
The sample for the mail survey consisted of 1,505 individuals, who were randomly drawn
from a list of names and addresses obtained from the Michigan Office of the Secretary of
State. The sample list was made up of Michigan residents 21 years old or older who
possess a valid driver’s license or state identification card. The sample was stratified on
the basis of strata that corresponded to the seven most pOpulous counties in Michigan
(Table 4). These strata ensured that specific counties with large percentages of
Michigan’s population were accurately represented, so as not to over or under-sample
them. The number of individuals selected for each county directly corresponds to the
percentage of the state’s population that each county comprises. The eighth strata
contained individuals from the remaining counties in Michigan and represented 43.21%
of the sample. Because the sample strata proportions correspond to the actual proportions
of the State’s population, no weights are required in the analysis of the stratified sample

data (i.e. the weights to adjust for the stratified sampling all equal one).

Table 4. Stratified Random Sample, Representing the Seven Most Populous

Counties in Michigan

 

 

 

 

County County % ofState ’s Stratified Sample 0/0 of overall

Number Population Drawn Sample
Genesee 25 4.3 1 65 4.32
Ingham 33 2.91 44 2.92
Kent 41 5.61 85 5.65
Macomb 50 8.15 122 8.11
Oakland 63 12.17 183 12.16
Washtenaw 81 3.43 52 3 .46
Wayne 82 20.20 304 20.20
All other counties 43.21 650 43.19
Total 100 1505 100
Tailored Design Method

The mail survey was implemented using a Tailored Design Method (TDM) to achieve the

best response rate possible (Dillman 2000). The TDM includes the following

components: a user-friendly questionnaire; business reply enveIOpes that respondents

utilize to return the questionnaires; up to five contacts with each individual; personalized

correspondence; and a token incentive that was sent along with the survey.

In following the Dillman (2000) TDM, the researchers personalized the contacts by:

using envelopes and correspondence that were addressed directly to respondents, and

hand signing the letters; printing the large format questionnaires in color on glossy paper;

printing the letters on high quality watermarked paper; using only first class mail for

every contact; and in the first contact including three postage stamps as a token incentive

to complete and return the questionnaire.

Advocates of the TDM contend that multiple contacts have been shown to be more
effective than any other technique for increasing response to surveys by mail (Dillman
2000). Therefore, the researchers’ mail survey consisted of the five contacts
recommended by this method: i) a pre-notice letter; ii) a questionnaire; iii) a reminder
postcard; iv) a replacement questionnaire; v) and a final contact with an additional

replacement questionnaire.

Pre-notice Letter
The pre-notice letter was sent in order to let the respondent know that they would soon be
receiving a questionnaire from Michigan State University. The personally addressed,

hand-signed, pre—notiee letters were mailed first-class on July 6, 2004.

First Survey Questionnaire
The second contact was a survey questionnaire packet, which consisted of a hand-signed
cover letter, a questionnaire, a business reply envelope for respondents to return the
questionnaire, and an incentive of three first class stamps. This second contact was
mailed first class one week after the pre-notice letter, on July 12, 2004. The
recommendation of the TDM is to send this mailing a few days after the first contact

(Dillman 2000), however for the purpose of this research, the sending time was expanded

36

to seven days in order to give time for the undeliverable mail to be returned and addresses

corrected when possible respondent’s new contact information was returned.

Postcard
The third contact with respondents was a hand signed reminder postcard, which was
mailed first-class to respondents on July 20, 2004. Following Dillman (2000)
recommendation this contact was mailed a few days to a week after the questionnaire.
The postcard asked to please fill out and return the questionnaire, and thanked them if

they had already done so.

Second Survey Questionnaire
The fourth contact was mailed August 9, 2004. It consisted of a questionnaire, a business
reply envelope, and a cover letter that was changed to reflect the fact that this was a
“replacement survey questionnaire” in case they had misplaced their first copy. No
incentive was included in this wave. In accordance with TDM, this wave was mailed two

to four weeks after the third contact (Dillman 2000).

Third Survey Questionnaire
The fifth and final mailing was sent on September 7, 2004 and included a questionnaire,
business reply envelope, and a cover letter indicating that this was the final contact. This

wave was mailed within two to four weeks after the fourth contact (Dillman 2000).

37

 

Data Entry and Response Rate

Each of the five mailings was carefully documented, paying special attention to mailing
dates, returned mail received dates and post-mark dates. For the determination of
response rates (RR), information on returned mail and responses was recorded and coded
based on the American Association for Public Opinion Research (AAPOR) standards

(AAPOR 2004).

For the aggregate RR of this survey, the AAPOR — RR2 was used because partially
responded questionnaires were also counted as valid responses7. A final disposition code
was recorded for each individual in the survey sample. All categories, with the exception
of 2.31, 2.32 and 3.19, were aggregated (see Table 5). The response coding indicating
that an individual was deceased (2.31) was not considered as valid possible response.

The minimum response rate is determined by the following formula:

R2: (1+P)
(l+P_)+(R+NC+0)+(UH+U0)

 

Where response rate (AAPOR-RR2) is estimated using the number of complete
interviews (I) and partial questionnaires (P), divided by the number of total

questionnaires (complete plus partial), plus the number of non—interviews which include

 

7 Partial responded questionnaires are those that had at least 50 percent of all applicable questions
answered.

38

refusal to participate

(R), plus others8 (0), plus all cases of unknown eligibility to

participate (UH, UO).

Table 5. Response Rate Codes for the Sample

 

 

 

Response Coding # of Sample

I Complete interview (coded 1.1) 467
P Partial Interview (coded 1.2) 0
Refusal and break-off (coded 2.1) 21

NC Non-contact (coded 2.2) 0
O Other (coded and using only 2.32, 2.33) l
UH Unknown if Household / occupied HU (coded 3. I 9) 669
UO Unknown, other (coded 3.2) 6
Invalid (coded 3.3, 3.4 or 4.] including 2.3 l-the deceased) 341

Total 1505

 

Of the 1,505 persons in the initial sample, 341 had invalid addresses. That meant that the

researchers received

at least one notification that the address was incorrect (e.g.

undeliverable as addressed, moved-left no address). Removing these invalid addresses

yielded a sample with 1,191 valid addresses. In total, 467 questionnaires were returned

completed, yielding an overall response rate for the survey of 40. 1%. Of the 467

questionnaires completed, one was lost in the process of data entering; hence results are

based on 466 completed questionnaires. Table 6 details the estimated overall response

rate, as well as the response rates for each individual mailing contact.

 

8 Not counting deceased.

Table 6. Response Rate by Mailing Contacts

 

 

 

 

. Returned
. _ Units Response
MaIlIng Contact . Complete Bad Address or
Marled Rate (%)
Questionnaires Undeliverable
l Pre-notice letter 1,505 N/A N/A N/A
2 First questionnaire 1,505 355 310 30.4
3 Post Card 1,195 N/A N/A N/A
4 Second questionnaire 882 88 3 11.0
5 Third questionnaire 740 24 l 3.4
Overall 467 314 40.1

 

40

Demographic Characteristics of the Sample
This section presents the mean demographic characteristics of respondents and compares
them to those of Michigan’s general population. The information contained in Table 7

was generated with data from the returned questionnaires and from the U.S. Census

Bureau (2000).

Table 7. Comparison Between Survey Respondents and Census Results for

 

 

 

 

 

 

Michigan
Survey State of
Sample Michigan
Average Household Size 2.77 2.569
Average Age 50.62 46.410
Household Median Income $62,499 $46,986ll
Education
High School Graduate or Higher 63.5% 61.6%”
Bachelor’s Degree or Higher 27.9% 21.8%
Ethnicity
White 87.3% 82.1%13
African American 2.8% 13.1%
American Indian/Alaska Native 1.5% 0.5%
Hispanic, Latino or Spanish 1.3% 2.7%
Female 51.9% 51.8%'4

 

 

9 U.S. Census Bureau, Census 2000. Table DP-I Profile ofGeneral Demographic Characteristics: 2000.

Geographic area: Michigan.

'0 Computed from: U.S. Census Bureau, Population Estimates Branch, "Estimated Population ofStates by
Age Group and Sex, 2000—2003" as released by Census Bureau on March 10, 2004; for population over 20

years.

” U.S. Department of Commerce, Economics and Statistics Administration. U.S. Census Bureau. Money

Income in the United States: 2000, page 12; for population 25 years and over.

'2 U.S. Bureau of the Census, Census 2000. Table DP-2 Profile of Selected Social Characteristics: 2000.

Geographic area: Michigan; for population 25 years and over.

'3 U.S. Bureau Ofthe Census. Census 2000. Table PL4. Hispanic or Latino and Not Hispanic or Latino by
Race for the population 18 years and over [73] - Universe: Total population 18 years and over. Data Set:
Census 2000 Redistricting Data (Public Law 94-171) Summary File. http://faetfinder.census.gov/.

41

Table 7 shows that the demographic characteristics of the survey sample are reasonably
similar to those of Michigan’s general population. Some differences seem apparent with
respect to African American and Hispanic, Latino or Spanish ethnicities; average
household size; average age; and household median income, which represented the
highest discrepancy between survey respondents ($62,499) and the State’s median
($46,986). This apparent income difference does not appear to influence the estimation of

results and will be discussed later in the next chapter.

Additionally, with respect to educational attainment, a slightly higher percentage of
individuals responding to the survey had a high school degree or higher, compared to
Michigan’s population (63.5% and 61.6% respectively), and a larger percentage of
respondents held a Bachelor’s Degree or higher (27.9%) than the state’s average (21.8%).
Most of the respondents identified themselves as ‘white’, followed by smaller
percentages of respondents identified as ‘African Americans’, ‘American Indian or
Alaska native’ and ‘Hispanic, Latino or Spanish origin’. Other minority groups were,

‘Hawaiian or other Pacific Islander’ (0.2%), and ‘Asian’ (0.6%).

Behavioral Aspects of Respondents
The survey also asked some additional questions about respondent behavioral aspects
related to wetlands. For example: 69% of respondents answered that they “have visited”
a wetland, 26% of our respondents declared that they participated in environmental

conservation groups. Fifty-three percent declared that they practice fishing ancL’or

 

'4 U.S. Bureau Of the Census. Census 2000. Table DP-l. Profile of General Demographic Characteristics:
2000. Data Set: Census 2000 Summary File 4 (SF 4). Summary File. Geographic Area: Michigan. For
population 18 years and over. http://factfinder.census.gov/

42

hunting, and 66% practice camping or biking. The behavioral aspects captured by the
survey were expected to be usefirl for explaining the respondents’ willingness to pay for
the proposed program. While some of those variables turned out to be unimportant as
criterion for explaining why respondents voted yes or no to the contingent valuation
scenario, others turned out to significantly influence respondents’ votes as shown in the

next chapter.

43

CHAPTER 4: MODELS FOR ESTIMATION OF VALUES AND RESULTS

Experimental Design

The third section of the questionnaire consisted of a CV question that uses the attribute
based referendum format (Holmes and Boyle 2005) to elicit respondent’s preference for
program characteristics. Information gathered from this section of the questionnaire was
used to estimate the value respondents placed on a proposed wetland program. The
program to preserve or restore 12,000 acres of wetlands in Michigan was described in
detail, including a one in a lifetime tax payment per household, the cost for implementing
this program (Figure 1). The valuation question asked respondents if they would vote to

approve the specified program if they had to pay for it.

The program’s general characteristics are made up of three attributes and a “price”. These
attributes consisted of: A) the different ecological services that the program would focus
on as a program “priority”; B) the “mix” of effort divided between preservation and
restoration of coastal wetlands; C) the “tool” or mechanism used for land acquisition. The
final characteristic is the price respondents were asked to pay for the implementation of
the program. The attributes and the price are varied across the sample using an
experimental design, the result of the combination of these characteristics were 49
versions of the questionnaire, the procedure to combine these characteristics is described

further in the document.

44

 

 

PROPOSED COASTAL WETLAND PROGRAM AND COST

 

 

 

 

 

 

 

 

 

 

 

 

 

PROGRAM A
1
Primary Focus Non-Game Species 1‘:
Preservation effort 10% Preservation 5
Restoration effort 900/0 Restoration , I, Program

if" Attributes

Get Program Sites Purchase Property E

.Total “ms { 12,000 acres ::

111 program '/

One-time only payment { $ 40, one time
HOW WOULD YOU VOTE?

9. Think of yourself in the voting booth. There are many things that the State
can spend money on. Program A is one specific program. Suppose Program
A is on the ballot. If it passes, Program A will be implemented and you pay
the one-time, payment. If it does not pass, the program is not implemented
and you do not pay for it.

With the information you have now, how would you cast your vote on
Program A with a one-time cost to you of $40? (Mark one response)

 

I I

Definitely vote Probably Could vote I Probably vote iDefinitely votd
FOR it vote FOR it either way ‘ AGAINST it AGAINST it

 

 

 

 

 

 

 

For Program A 1:1 [3 E1 l [:1 1:1

I would...

 

 

Figure 1. Actual page from the survey showing the program scenario given to

respondents.

45

 

Program Characteristics

A) The “priority” included 1 of 6 possible ecosystem services that serve as the primary
focus of the preservation or restoration program. Table 8 lists this attribute’s levels. It
was explained in the questionnaire that wetland protection programs must prioritize their
efforts to accomplish their goals with limited funds by placing the highest priority on a

particular feature.

Table 8. Priority: The Program’s Primary Focus.

 

Levels

 

Non-Game Species

Open Space Near Cities

Water Quality & Flood Control
Fish Habitat

Waterfowl Habitat

Biodiversity

 

B) The program’s “mix” is how the program’s efforts are devoted to preservation of high
quality wetlands versus restoration of impaired wetlands. This attribute had seven
possible levels from 10% preservation, with the remainder allocated to restoration to 90%
preservation and 10% restoration. This attribute is indicative of how the program’s
resources would be split between the two activities. The proposed program could take 1

of the seven levels listed in Table 9.

46

Table 9. Possible Levels of Combined Effort Devoted to Preservation and

Restoration.

 

Mix Levels

 

10 % Preservation 90% Restoration
25 % Preservation 75% Restoration
40 % Preservation 60% Restoration
50 % Preservation 50% Restoration
60 % Preservation 40% Restoration
75 % Preservation 25% Restoration

90 % Preservation 10% Restoration

 

C) There were 3 levels for the “tool” attribute. Each level is a method itself to acquire
land from voluntary private land-owners. The proposed program showed respondents

only 1 method for acquiring the acreage for coastal wetland preservation or restoration.

Table 10. Tool: Land Acquisition Method.

 

Tool:

 

Purchase Property
Permanent Easements

Ten Year Contracts

 

D) The final characteristic is the program cost; the possible price (seven levels ranging
from $40 to $1,320) that an alternative program can take are listed in Table 11. In the

questionnaire, this cost was presented to respondents as a one-time statewide tax

payment.

47

Table 11. Cost To Implement the Program

 

Price $

40
120
280
370
525
870
1320

 

 

Combination of Program ’s Attributes Levels and Price Levels: Main Effect

Factorial Design
Main factorial design was used to combine the attribute levels and price levels into
alternative scenarios to create sufficient variation among the program scenarios. One
approach would be to use a full factorial design in which every level of every attribute is
combined with every level of all other attributes (Louviere, Hensher and Swait. 2000).
The experimental design of this research was made taking into consideration both the
Contingent Valuation and the Stated Choice questions. According to the main factorial
design method, to determine the number of combinations that would be necessary for a
full factorial design in which the number of levels of each attribute are squared (to
account for them being included in both programs A and B) and then multiplied by the
other squared attribute level counts. The full factorial design for this study would result in
62x72 x32, or 15,876 combinations. Such a design results in far too many options for a
sample (Louviere, et al., 2000). Because this number of combinations is far too large to
manage, a main effects design was utilized. A main effects design ensured that the
attributes, and their levels, are independent of each other. A main effects plan generates

variables that are linearly independent, within and across alternatives. Using this design,

48

only the first order interactions among variables can be identified. The main effects

design resulted in 49 pairs of alternative programs (49 questionnaire versions).

Estimation of Values

The CV question offered household respondents a scale to cast their vote for the attribute-
based referendum, meaning that if they would vote to approve the program they would
also be paying the proposed “price”.

To reduce hypothetical bias and maintain a high level of certainty in the use of the
responses, only “definitely yes” responses were considered as “YES” for the estimation
of values, the rest of responses in the scale, including “probably vote for it”, (Table 12)

were considered as NO.

Table 12. Scale to vote for the program.

 

Definitely vote Probably Could vote Probably vote Definitely vote
FOR it vote FOR it either way AGAINST it AGAINST it

For Program A [:1 C] 1:] 1:1 1:1
I would. . .

 

 

 

 

 

 

 

 

 

Two methods were used to relate the votes to estimation of values: parametric model
(probit) and the Tumbull Estimator as a non parametric model (Haab and McConnell

1997).

Parametric Model - Attribute Based Referenda

From the vote response, a utility function is inferred in order to calculate a monetary

measure, such as WTP. The purpose is to link the change in utility of Michigan’s Citizens

49

to a value measure, which might occur if a wetland’s conservation and restoration

program is implemented.

The Model ’s Theoretical foundation
In order to convert data from dichotomous choice responses into a monetary measure, a
utility theoretic model of choice is necessary (Freeman, M. 1993). A key element is the
individual optimization that relates the individual choice to the change in the quantity or
quality of the environmental resource. For well described theory in deriving net income
changes in individual preferences, see Freeman (1993) and Haab and McConell (2003).
For this thesis, a succinct revision of the Random Utility Model (RUM) routine is
described. RUM provides the theoretical framework for the valuation procedure that
relates the change in the indirect utility function of the respondent. Also, RUM helps to
understand how respondents will mimic actual behavior by making a choice in response
to the prOposed program, the price, and their individual constraints (Hanemann 1994;
Champ, Boyle and Brown 2003, Haab and McConell 2003). An important assumption
for RUM is that environmental services or environmental attributes relating to
environmental services can be treated as arguments in well-behaved utility functions
(Perman et al. 2003; Haab and McConnell 2003), so the indirect utility function of

respondent j can be written as

uij : ui(yj9xiazjagij)

wherei = l is the environmental condition acquired when the coastal wetland protection

program is implemented, and i = 0 for the status quo. The determinants of utility are yJ ,

50

-th
the ] respondent’s discretionary income, xi an argument about the attributes of the

wetland conservation / restoration program, Z]. a multi dimensional vector of household

characteristics (demographics and behavioral aspects), and 'j , a component of
preferences known to the individual respondent but not observed in this research. Based

~th
on this model, respondent J votes yes to a required payment (cost of the program) of

tj if the utility with the GLCW program exceeds the utility of the status quo,

"100' —tj,x,,zj,8,j) >u0(yl.,x0,zj,eoj),

Because it is not possible to know the random component of the preferences, only
probability statements can be made with indirect utility function ( V,- ). The probability of

a yes response depends upon respondent thinking that he or she is better off with the

oth
proposed program and paying for it, so that V] > V0 . For respondent j the probability
of yes is,
Pr(y€S,-) = PYIVIOQ- "1,.xpzj.8.,-)> Vo(y.,-.XO.Z_,-,80,- )1.

At this point, this probability statement provides the basis for non—parametric analysis;

however it’s too general for parametric analysis.

PTO/6.9!.) =Pr[v,(yj —t,'9x|azj)+81j > V0(yj9xoazj)+€0j]

The random difference between the status quo and the CV scenario are still unidentifiable

for the researcher. Haab and McConnel’s procedure suggests rewriting the random term

51

8.58. e F(a)

from 1 ll of to a single random term. Let E be the probability that the

random variable 5 is less than a . Therefore, the probability of yes can be expressed as

follow:

PrO’eSI) =1— Fe[’(VI(«Vj —tj,x,,zj) " v0(yj,x0,zj))],

The Random Utility Model with a Linear Utility Function:
This thesis applies the RUM with a deterministic part of the preferences that is linear in

function,
V300) = 61x; + aij +IBj(y_,-).
. . h . . .
where y J 15 the j ’ respondent’s discretionary Income, x,- an argument about the

attributes of the wetland conservation / restoration program, Z j a multi dimensional

. . E -- .
vector of household characteristlcs, ’1 IS a component of preferences known to the

individual respondent but not observed in this research; and 5,- , a]. and ,5,- are multi

m
dimensional vectors of parameters so that 59C,- = Z k=1 5,1, x”, ,

m m
“72.7 — 1.2100an and 1373’; ‘" Zk=lfljkyjk -

A Contingent Valuation question induces the respondent to make a choice between the
current state and a proposed condition at a required payment If . In this case our research

is proposing the scenario of improved conditions for wetlands due to the implementation

52

of conservation and restoration programs. The deterministic indirect utility under the

proposed scenario would be:
vlj —v0j :(61 —50)xi +(a1 _a0)Zj £400- _tj)_160yj ,
where if is the price offered to the j ”1 respondent (citizen). It is assumed that the

marginal utility of income is constant between the two Contingent Valuation states,

therefore, ,5] = ,60 and the utility difference becomes:

vU—voj.=(5c,+orzj+fltj,

In m
where 61:01 ‘64,, so that 0a]- = Zkzlaij-k ; and 5:6, —d) sot that 59 :Zzlélrxjk.

Once the deterministic part of the preferences is specified, the probability that the citizen

responds ‘yes’ can be expressed as:
Pr(yesj) = Pr(c$c,. +6th —,Btj +8]. > 0)_
The next step, in order to estimate the parameters of the utility difference, is to determine

the nature of the random term. According to Haab and McConnell (2003) the assumption

that a, are independently and identically distributed with mean zero describes most

distributions used. The probability of yes response can be estimated as:

Pr(63c, +02]. —,Btj +8]. >0) =Pr(—(c$c, +02]. —,Btj)<ej)
Pr(($c, +02]. —,Btj +8]. > O)=1—Pr(—(c3x,. +02]. —,Btj) >81.)

Pr(&x, +02]. —,Btj +8}. >0): Pr(ej < 6x, +02]. —,6t/.)

53

The last equation utilizes the symmetry of the distribution. For symmetric distributions

F (x) = l - F (—x) . Assuming thate, ~ N (0,0'2) , the conversion to a standard normal

( N (0,1)) variable is necessary to carry out the analysis with computer software. Let

6:8/0'. Then I9~ N(0,l)and,

Pr(ej <69 +02]. —,&,) =Pr(6<éc—’i- +9—21- wgti);
‘ ' 0' 0' 0"

however in a probit model, it is assumed that 8]. is normally distributed and that there is

no cost associated with maintaining the status quo therefore it bid (price) is zero.

Pr(ej<c$ci+oe,—,Bti)=d)(§i+fl—£tj),
-' ' 0' 0' 0'

Where (DH) is the cumulative standard normal distribution which iS the probability that a
unit normal variant is less than or equal to x . Probability now is in term of parameters
divided by an unknown variance in a probit model. Since the model is using a
dichotomous dependent variable taking a value of zero or one, the variance for this is
unidentified and so is simply normalized to l. The probit model developed statistical

relationship between wetlands program characteristics, pCOple’s choices, and costs.

54

Results of the Parametric Model

The variables included in the probit regression are all listed in Table 13. The selection of

variables used in the model was made on the basis of their relevance in explaining the

probability of vote. From the survey data, 52 variables were initially generated, all of

which were tested in the process of explaining the vote. Of the 52 variables, only 31 were

selected as relevant.

Table 13. Variables Utilized in the Probit Model

 

Dependent variable t j

x.

l

21

 

Definitely Vote for
the Program (YES*)

Price (cost for
the program)

Preservation continuous
Non game species"
Open space near cities“

Water quality and flood
control*

Fish habitat“
Waterfowl habitat*

Biodiversity“
Purchase property*
Pemianent easement“
Ten year contracts*

Urban_resl *
Suburban_resl *
Rura1_resl *
Env_Group_Member_1 *
F isher_Hunter_l *
Camp_Hike_l *
Imp_wet_there_l *

lmp_wet_future_l *
Age_resp
Female_1 *

White__l *
Democrats_1 *
Republican_l *
Complete_College_1 *
Work_fulltime_l *
Retired_l *
Income_Above50K *
Income_continuous
Visited_Wetl_1 *

 

*Equals 1 if true, 0 otherwise.

Table 14 Shows the description of each of these selected variables. Sets of dummy

variables were created for each block of attributes. For the program’s “Priority”, five

dummy variables were created, leaving ‘Biodiversity” as the excluded group. Same thing

55

for the “Tool” attribute, were ‘Pemianent easement’ was used as the excluded group

 

 

 

 

 

(baseline).
Table 14. Definition of Dependent Variables
Variable Variable Definition
Q9 Y“ Dependent dummy variable indicating only “Definitely
- " Yes” responses to the CV question.
Price . . . . .
.1 _ A continuous variable indicating the cost of the
Price of the program .
t j ‘ " conservation program to the respondent
Non Game Species Independent dummy vanable,1ndicating whether Non
Game Species IS the program 3 top priority.
Water Quality and Flood Independent dummy variable indicating whether Water
Control Quality and Flood Control is the program’s top priority.
“Priority” Fish Habitat Independent dummy variable indicating whether Fish
Habitat Is the program 3 top priority.
x i Waterjowl Habitat Independent dummy variable Indicating whether
Waterfowl Habitat is the program stop priority.
. . _ . Independent dummy variable indicating whether
Biodiversrtv . . . . , . .
' Biodiversity is the program S top priority.
Open Space Near Cities Independent dummy variable indicating whether Open
Space near Cities 18 the program 5 top priority.
Independent dummy variable indicating whether or not
Purchase Property Purchase Property was the approach used to acquire
wetland acreage.
“T001” Independent dummy variable indicating whether or not
x Permanent Easements Permanent Easements was the approach used to acquire
i wetland acreage.
Independent dummy variable indicating whether or not
Ten Year Contracts Ten Year Contracts was the approach used to acquire
wetland acreage.
“Mix” A ' ‘ bl ' h , f
Percent Preservation continuous varra e representing t e percentage 0
x1. program effort devoted to preservation.
Urban res l * A dummy variable indicating if respondent lives in a
'— Urban area
Suburban res I * A dummy variable indicating if respondent lives in a
_ Sub-urban area
HOUSChPI‘I R __ l ) '1 * A dummy variable indicating if respondent lives in a
Characteristics 1”" J“ Rural area
Z . Env Group Member 1* A dummy variable Indicating If respondent contributes
j _ — — or Is a member of an envrronmental group

F isher_Hzmter_ I *

C amp_Hike_l *

A dummy variable indicating if respondent go fishing
and/or hunting

A dummy variable indicating if respondent go camping
and/or hiking

56

Table 14. (con’t)

 

Household
Characteristics

Z .

Specifications of the Model

I

Imp_wet_there_l *
lmp_wet_/uture_l *
A ge_resp

Female__l *

White_l *
Democrats_l *
Republican_l *
Complete__Co/lege_l *
Work _/irlltime_l *
Retired_l *
Income_A bove50K *
Income_continuous

Vis i ted_ W etl__ I *

A dummy variable indicating if respondent considers as
extremely important wetland’s existence

A dummy variable indicating if respondent considers as
extremely important wetland’s future existence

A continuous variable indicating age of respondents

A dummy variable indicating if respondent is a female

A dummy variable indicating if respondent considers
herself as White (as ethnicity group)

A dummy variable indicating if respondent think of
herself as a member of the Democratic party

A dummy Variable indicating if respondent think of
herself as a member of the Republican party

A dummy variable indicating if respondent has
completed college at least.

A dummy variable indicating if respondent works full
time

A dummy variable indicating if respondent is retired

A dummy variable indicating if respondent’s income is
superior to fifty thousand dollars a year

A continuous variable for income

A dummy variable indicating if respondent has ever
Visited a wetland.

In order to maintain consistency in comparing results across different specifications of

the model, the data sets were filtered to include complete cases only. Complete cases

were those observations where respondents had not skipped any questions that were

determinant for the model. A total of 378 (81.1%) observations were selected.

The model was specified in six ways with the purpose of exploring the partial effect of

the variables in the estimation of willingness to pay for the program at two levels of

“Yes” response, i) Definitely yes, and ii) Definitely yes + Probably yes. However, only

the three models referring to Definitely Yes vote are reported in this thesis. These three

models utilize a set of variables arranged in the following manner: i) using price and the

57

program attributes; ii) using the price combined with the program attributes and
respondents’ characteristics; and iii) using only the price and respondents’

characteristics.

To determine the relevance of the independent variables, numerous specifications of the
model were estimated combining these variables in diverse arrangements, while
observing their estimated coefficient’s statistical significance. Variables that were not
different from zero or not different from the excluded group (for the case of dummy
variables) were drOpped from the model. To select the best models, we assessed the
performance of the probit models by observing the significant variables in each
specification and comparing their Pseudo R2. The same number of observations (3 78)
was kept across the specifications for comparison purposes. Goodness of fit was also

compared by calculating the correct prediction percentage of each model.

For all the specifications tested, ‘Biodiversity’ and ‘Permanent Easements’ were chosen
as baselines for the set of dummy variables representing the program’s ‘priority’ and
‘tool’ respectively. These baselines were chosen because they are the attributes that
matter the most in the models, according to their significance in relation to the other
variables in its respective sets (in all the possible iterations). After completing the
procedure of choosing the best six models, only 16 variables were left to help explain the

respondents’ votes.

58

Table 15. Descriptive Statistics of Selected Variables

 

 

 

Variable Mean Std. Dev. Min Max
N = 378
Q9 _yes 0.16 0.37 0 I
Q9_probyes 0.30 0.46 0 I
Yes_all 0.46 0.50 0 I
Price 489.39 423.58 40 1320
preserv_A_Cont 49.56 25 .62 10 90
nongame_SpA 0.27 0.45 0 I
openSpace_A 0.15 0.36 0 I
watQ_FIoodC_A 0.1 7 0.37 0 I
fishHab_A 0.14 0.35 0 1
waterfoleab_A 0.1 3 0.33 0 I
biodiverst_A 0. I 4 0.35 0 l
purch_PropertyA 0.31 0.46 0 l
perm_EasmtA 0.42 0.49 0 1
tenY_ContractA 0.28 0.45 0 1
visited_wetl_1 0.71 0.45 0 1
suburban_resl 0.51 0.50 0 I
env_group_member__l 0.28 0.45 0 I
fisher_hunter_l 0.57 0.50 O I
Age_resp 49.48 13.61 22 71

 

General Results for Models 1 to 3

When regressing Definitely Yes with the program attributes and demographic
characteristics, we found that the three models are statistically significant (Prob > chi2 =
0.00). The coefficients in the three models demonstrate that ‘price’ has a negative effect
on the probability of vote, reflecting theoretical expectations that at a higher price, the
probability of observing ‘Yes’ votes would decrease. The variable “price” is different
from zero at a 99% confidence level for the three selected models. For model 1 and 2, the
coefficient for preservation is also different than zero at 0 or level 0.01, and has a positive
Sign indicating that preservation increases the probability of vote. The estimated

coefficients for these models are presented in Table 16.

59

Table 16. Parametric Results Models.

 

Explaining Definitely Yes Vote

 

 

 

Model 1(x,) Model 2( x, + 2}) Model 3 ( Zj)
Coef. P>z Coef. P>z Coef. P>z

Price 0001 0.005 -0.001 0.001 -0.001 0.000
preserv_A_Cont 0.008 0.010 0.007 0.044

Nongame_SpA . -0.686 0.006 -0.575 0.028

openSpace_A -0.812 0.007 -0.743 0.017

watQ_FloodC_A -0.339 0.200 -0.303 0.273

fishHab_A -0.731 0.014 -0.771 0.013

waterfowlI-Iab_A 0392 0. l. 63 -0.2 36 0.438

Purch_PropertyA -0. l 38 0.476 -0.1 18 0.562

tenY_ContractA -0.143 0.4 76 -0.063 0.772

Urban resident -0.440 0.121 -0.392 0.145
Rural resident -0.442 0.023 —0.481 0.011
Visited wetland 0.449 0.042 0.467 0.026
.Env. Group Member 0.649 0.001 0.677 0.000
Constant -0.582 0.036 -0.855 0.014 -1.013 0.000
Prob(Yes=1) 0.14 0.12 0.13
Number of Obs. (n) 378 378 378

LR chi2 28.09 53.72 38.27

Prob > chi2 0.001 0.000 0.000

Pseudo R2 0.084 0.161 0.115

Log likelihood 153.011 140.195 147.918

 

 

 

Model 1 (x,)

This model only includes the program’s characteristics as explanatory variables (price
and attributes). The regression coefficient of price is negative and highly significant (01
level 0.01); preservation coefficient is positive and significant at or level 0.01. Implyin g
that in the population price has a negative effect on the probability of vote, while

preservation increases the probability.

60

Every coefficient for program’s attributes provides evidence that with the exception of
‘Water Quality and Flood Control’ and ‘Waterfowl Habitat’, the other groups are
statistically different then the excluded group “Biodiversity’ at 01 level 0.01. This results
are evidence that ‘Biodiversity’, ‘Water quality and flood control’ and ‘Waterfowl
habitat’ have a larger effect on the probability of vote, from where we can deduce the

preference of these priorities over other alternatives for the priority of the program.

The variables for the “tool” to acquire land from volunteers have coefficients that are not
statistically significant; therefore we can’t conclude that in the population the three

different tools are not equal from each other in determining vote.

The expected willingness to pay for this model was calculated by dividing the sum of the
attribute’s coefficients times their means plus the constant’s coefficient, by the negative

of the price coefficient (Haab and McConnell 2003).

x1+6x,+azj

“(13)

 

E€(WTPj |/I,5,,6,x,,z) 2

Results from this model render negative estimations of mean WTP for a program that
would have multiple foci and a mean share of preservation — restoration. However, other
interpretations of the coefficients are important for understanding how the attributes can
affect the estimation of WTP. For example, for this model, if the program provides 100%

preservation and Biodiversity as a priority, the expected WTP is $379.5.

61

Mode12(x, +21.)

This is the more complete model since it includes the price, program attributes and
respondents’ characteristics as explanatory variables. In this model we obtained the
highest pseudo R2 (0.161) of the three models presented. As in Model 1 the coefficients
for program’s attributes provide evidence that only ‘Water Quality and Flood Control’
and ‘Waterfowl Habitat’ are statistically different then the excluded group “Biodiversity’
at 01 level 0.01. This is again an indication of the preference of ‘Biodiversity’, ‘Water
quality and flood control’ and ‘Waterfowl habitat’ over these other alternatives for the
priority of the program.

In this regression, variables representing respondents that have visited wetlands and
respondents belonging to environmental groups have coefficients that are positive and
significant at or level 0.05. The average willingness to pay of the people who have
visited a wetland and belong to environmental groups is higher than that for those whom

these variables do not hold true.

For example, if the program provides 100% preservation, a wetland visitor that belongs
to an environmental group will be willing to pay as much as $210.2 for the program, all
else equal. On top of that, if the program provides Biodiversity as the priority, the same
group of people will have an expected WTP of $ 1,061.5. On the other hand, for the
average respondent (not member of an environmental group), for a program that provides
100% of preservation and ‘biodiversity’ as priority, the expected WTP is approximately

$47.

62

Model3 (2})

In this model, only individual’s characteristics were used in trying to explain the vote.
Surprisingly, most of the characteristics such as political affiliation, ethnicity, level of
income, age, level of education, gender, and individuals that hunt, fish, or camp and hike,
did not matter for the model. Variables related to site of residence indicated urban
residents are not significantly different than Suburban residents. However, rural residents
are different than these two last groups and its coefficient has a larger negative effect on
the expected probability of vote.

From the previous two models, we can expect a higher WTP from the people who belong
to environmental groups and have visited wetlands, and as expected this is the case for
this model. If we choose an even more specific group by only considering suburban
residents that belong to environmental groups and have visited wetlands, they have an

expected WTP of $156.4 on average.

Three criteria for a valid welfare measure should be satisfied: i) that WTP has a non-
negative lower bound and upper bound no greater than income, ii) that the calculation is
made without arbitrary truncation, and iii) that there is consistency between randomness
for estimation and randomness for calculation. The Tumbull Estimator satisfies these
criteria (Haab and McConnell 1997) and we used it to estimate WTP; and, the parametric

model was used to explain the effect of variables on the vote.

63

Non-Parametric Model: Applying the Turnbull Estimator

This method was used to calculate measures of central tendency and dispersion of WTP
that rely on the notion that when respondents answer Yes to a contingent valuation
question, their willingness to pay is not less than the offered bid price (Haab and
McConnell 2003). The estimation of lower bound WTP takes in consideration the
number of people who responded No to the referendum question. Figure 4 shows the
proportion of people voting NO at the different cost levels (n = 458). In this figure No
equals one, otherwise it equals zero. As cost goes up, the proportion of people that
responded (voted) NO also goes up. The remaining area between the top of the bar and

one, will be proportion of people willing to Pay for the program.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

1
0.75~ - 1
8 y _
“2‘ 0.5 #4 ' <—
'8
o\°
0.25“
O r I i I I I i i I i f I 1
$40 $120 $280 $370 $525 $870 $1 , 320
Prices

Figure 2. Distribution of No Vote across Prices.

64

Table 122 shows the calculations to estimate the lower bound WTP, which was estimated
in $163.0 per household in MI, with a 95% confidence interval between $116.8 and
$209.2

Table 17. Turnbull Estimation Results

 

 

 

Turnbull gestricted)

Bid Number Number Number F. *

Price of Yes of No's offered J f - E w (WT P )
0) (Y1) as.) a.) (NI/Tr) 1

$40 20 54 74 0.730 $0.00
$120 I l 48 59 0.814 ' 0.084 $3.35
$280 12 58 70 0.829 0.015 $1.80
8370 l l 55 66 0.833 0.005 $1.33
$525 10 58 68 0.853 0.020 $7.25
$870 7 46 53 0.868 0.015 $7.87
$1,320 4 64 68 0.941 0.073 $63.73
1 0.059 $77.65
$162.99

Taking the Turnbull lower bound mean WTP of $163, an aggregated WTP for the state of
Michigan can be inferred. Accounting for 3.7 million households across the State, the
aggregated demand for the program equals $241 million. Since the proposed program
offered the protection of 12,000 acres, the aggregated demand suggests a value of

$20,000 per acre.

An important limitation of the Tumbull estimator is that it is difficult to use demographic
characteristics to explain the vote. There are ways to do it by breaking the sample in
groups according to sub-sample characteristics, however the smaller the sample, the less
likely it is that the resulting distribution function will be monotonic, which is the case for

this research.

65

Comparing the Estimation Methods

The distribution of the functional forms (probit and logarithmic) can have substantial —
and undesirable- effect on the estimates of the WTP, since the parametric (probit)
functional form assumes that WTP distribution ranges from minus to plus infinite,
allowing for negative values of WTP. Due to the large number of No votes (83% of
respondents), the probit model places a large mass of the distribution in the negative side,
giving us a negative estimation of the expected mean WTP despite having no negative
costs offered for the program. AS shown in Figure 4, a logarithmic functional form of the
cost truncates the distribution at zero but has the problem of having very large estimates
of mean WTP and fat tails (Haab and McConnell 2003). The Tumbull estimation data
shows the observed distribution. It is evident that both, the probit regression and the
logarithmic form, have a reliable fit of the observed data within the range of prices we

used.

66

 

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Figure 3. Comparison of Models.

67

Explaining the NO response

After the referendum section, a follow up question asked respondents to explain the
reasons they vote they way they did. The analysis of the follow-up question revealed that
some respondents placed a zero value on the program for reasons that differ from the
program characteristics itself. These responses can be interpreted as “protest” votes and
can constitute a substantial portion of the zero bids that affects negatively the estimation
of WTP in CV studies (Mitchell and Carson 1993); it is necessary to distinguish them
from those voters that valued the program but preferred to forgo it rather than to have to
pay for it. As a measure to explore a possible bias in the estimation of WTP due to protest
votes all comments from the follow up question were categorized and coded to be
included in the regression as explanatory variables. By qualitatively coding these
comments and creating a variable for the protest voters, it was possible to analyze if the
“protest” group had any effect on the probability of vote.

As shown previously in Table 12, respondents had the option to cast their vote in a scaled
manner. Responses ranging from “Could vote either way” to “Definitely vote AGAINST
it” were classified as NO responses, making an 84% of the entire sample.

Three hundred and nine people, 66.3% of the sample, responded to the follow up
question; however only one hundred and seventy six (37.8%) of those were from
responses categorized as 'NO’S.

All comments from N0 respondents were coded according to qualitative criteria to
evaluate their acceptance or rejection to the valuation scenario and placed on a scale. The

scale included:

68

Accepting the proponed scenario when voting N0:
Respondents in this category understand and value the program; they may be willing to

pay but can’t afford it. Some examples of these responses are:

J I am on social security limited income. $528 is very expensive for me.

/ I would like the vote to pass. The only problem is I don't have an extra $1320.00,
seems like a lot of money to pay even though it is for a good cause. If I were rich
it would be another story. The reason I will owe on taxes is that I have to choose
between paying federal tax or having health insurance. Tough decision!

/ I might vote for it but right now is a poor time for me to fill this out . However I
don't want to avoid mailing it. I've had surgery and having problems with my
health these days. I do know preserving Michigan Great Lakes wetlands is
important for now and future. Clean water, flood control, the wonderful wildlife,
great outdoors, etc. Are precious and so important to maintain.

/ At this time I am on a fixed income and could not afford the $280 all at once.

/ Limited income in the future could affect the way I vote.

1 Personal financial status of a crisis is made clear to all. Better to vote for same,
regardless.

/ I would like more area helped than just 12,000. I would like to see the bad
coastal waste land helped along with the good coastal waste land equal. 1 would
like to learn and hear how the work would be done, on each. What goes into the
process.

/ I am not sure I want to be responsible for $1300 out of pocket expense for this
project. I think the Govt. Should take more responsibility or find matching funding
from Corporation / business or Federal Grants before they burden taxpayers.

/ Taxed to death.

J I am retired on a limited income. Also depends on what the market does to
increase my income.

\/ I am not quite sure either way and can not afford to pay $870 Since I have a lot
of medical bills to pay off.

/ Honestly, I cannot afford it with tax levies for the schools, insurance rates
skyrocketing and 4 children to support, I need every penny.

/ Money! Who has $120 for anything but food?

1 I'm not sure that money from taxpayers will solve or even help this problem. I
feel that the land left alone with out our help has a better chance of developing
its own ecosystem after all its been here since the time began. These areas
should be off-limits to expansion, no building at all.

/ While I like the program, the price tag is too much. I would agree to pay half of
the proposed tax and would like the other half to be absorbed by other funding
sources like federal aid or grants (private). Also, I wouldn't trust that the new tax
would go toward the wetlands (and not the general fund).

69

A N 0 vote with comments related to “weak protest”
Respondent understood the program and provided a reason to vote NO, however in the

comment some elements of protest are included. Here are some examples:

J I am in favor of wetland preservation and restoration and would not object to the "one
time" fee if there was assurance that: 1. There would not be a second "one time" fee
brought up at a future date. 2. The first "one time" fee would be wisely spent and not
get wasted on political projects.

J 1. State should pay for it. Taxes are too high now. 2. Can't afford any more taxes -
Individual ones. 3. Even though coastal wetlands should be protected. 4. We also
need to protect farm lands- being sold from farmers for spacious buildings. Pretty
soon we'll be short of food supplies because of lack of good farmlands and woodlands.

J As much as a person may feel strongly about this issue, the bottom line always is who
is going to pay for it. I would hope that I would be able to do my part.

J Cost. Generally, I am not very confident in the government handling these types of
programs.

J We are already overtaxed and there is enough waste and unnecessary programs and
inefficiency in Govt. That I feel we could raise this $ elsewhere vs. increased taxes.

J $870 is a high one time cost for middle low income families, I would rather see funds
diverted from current recreational programs temporarily, or use funds from the lottery
and have all work supervised by MSU Env. Scientists. Additionally Govt. often converts
one time payments into recurring expenses!

J Not enough information given. What checks and balances are in place to insure the
money goes to what it was intended for? What areas do they want to purchase? How
much money? Must get the most out of each dollar! What happens to the areas that
need restoration?

J I do believe that taxpayers are already paying too much money in taxes as it is.
Maybe the government Should utilize the tax money better and for things that really
require attention and are important.

J Nice plan, but I'm sincerely, honestly going to prophecy, "It's too late!" This is a joke to
me. I can't afford the bills I have now with various "1 owes" at this present time. I say,
"No", unless you give the bill to those who have $300,000+ homes living on, around or
near wetlands, including golf courses. To secure land requires occupation, occupation
pollutes land. Fact of life. Sincerely, thoughtful.

J I pay enough tax as is. Find a way to fund to program out of existing taxes.

J Taxes in the state are out of control!!! MI has the worst roads in the country!!! Ml has
some of the highest property taxes in the country!!! MI has one of the worst deficits in
the country!!! School systems are under funded!!! How can Ml ask for even one cent
more for taxes when our current tax dollars are mismanaged. I am very sorry but I can
not back any taxes imposed on M! residents!!!

70

Weak protest
Respondents while voting no, provided comments focusing on what they believe were

shortcomings of the survey or the proposed program’s implementation.

J There are no real specifics about the program. How and what are you going to do to
achieve your goals and purpose? Who owns the property currently, farmers or
politicians? How much will be collected and who will manage these funds? All too
Often we collect taxes or fund programs with only small portion going to the intended
purpose.

J My understanding of the problem is not great. I would need to really dive into the
wetland situation to present a definitive answer.

J It's hard to know for sure how I would respond at the time I really had to make this
decision. A lot of factors could come into play at that time.

J I would have to know more about A and B, both before I would cast my vote and feel
that the state should not be selling any state game lands or wetland at all. Around
where I live there are some spots where you have to know someone to get on the state
land cause there is houses all around it and no way into the land but as for the state
park I think it is great how they have them set up.

J I am 80 years old and some of the questions I am not well informed on.

J Not familiar enough with the exact needs for wetlands and how well the money will be
spent

J I really don't know a lot about wetlands
J I would need to do more research before deciding if I am for or against program.

J 1) I would need to research more on how bad the wetland threat is to MI. 2) I believe
in restoring nature... Not always giving in to urban expansion. 3) Nature is beautiful
and I enjoy the peacefulness it give when walking or bike riding.

J Everyone will benefit wetlands would be preserved and restored.

J I really have no opinion on this matter.

J We should not have to pay extra for not developing land. Most government programs
are poorly run.

J I want to know how this would affect the majority and if this is necessary.

J I think is a poorly worded question, if it is to cost me a one time payment of $120, how
is that going to be paid. I am all for protecting wetland, I see development ruining
wetland every day however a one time of $120 without clarification isn't going to get
anyone to vote for it.

71

Protest (Rejected the scenario)
The respondents in this group provided comments indicating that decided no to vote for
reasons not related to the program scenario. They differ from the next category in that

their vote for the referendum was “Probably vote against” the program. Examples are:

J The potential mismanagement of the money that should be used for the wetlands.

J Tired of paying for everything when you see so much waste in Govt.

J | feel that the State Government does not use funds correctly. Hunting and fishing
funds for example. Too much politics! The monies are never used the way they are
supposed to!

J I believe there are other ways of coming up with the funding.

J I want to see wetlands protected but don't think many people would be willing to
support the program if they personally had to pay $280. A better approach would be
education about the problem and working with environmental agencies. In my
circumstances, $280 would be a large contribution and I don't have much confidence
that the money would be used wisely.

J I think there are other ways of rising money for these types of things.

J 1. Most one time assessments are usually brought back time and time again for
renewal. 2. No guarantee that this money will not go into the general fund. 3. Would
this program grow the state Govt. and how much would be lost in administrative cost?
4. What happens if we approve this program and other surrounding states and
provinces don't? 5. I am extremely concerned as to how this would effect private
property rights and land use.

J Distrustful of state to manage a large influx of funds. See tobacco settlement, e.g.

J You want wetland "YOU” pay for it. Take budget from other useless programs and use
it to buy land. Hunting and fishing licenses come to mind. Don't ask the owners of the
wetlands to pay taxes on the land they can't use. Stop putting money into state golf
courses and put it into wetlands. If the state is not willing to transfer funds then forget
it!!! Don't ask me to pay more taxes.

J State has more money than I do. There are other monies out there!

J I would vote no on this issue because I would rather have the state set aside money
for these priorities if they are that important.

J I choose to live in a rural area with wetlands. I will not pay for someone who chooses
to live in a urban area who wants some wetlands. The state like its tax payers needs to
make choices. It should sell some of it state game areas and buy wetlands with the
money.

72

Strong Protest

In this case, respondent decided not to vote for the program for reasons differing from the

program scenario or survey procedure. This type of respondent is different from the past

category because in this case they voted “Definitely not vote” for the program. Examples:

J
J

\

This is just life I could vote other way!

(Summarized) Please understand, it is not because it will cost me more taxes. It is
because I am convinced those responsible for collecting, use tax dollars for their own
personal, professional needs, an none or very little would actually go to wetlands. The
problem is us, humans overrunning this planet, overpopulating it. No preservation
problem is going to help. We need to address the real problem Greedy PeOpIe.

The way the state has carelessly spent resources on welfare and other entitlement
programs is not responsible in my opinion. I think private companies could be hired
and are no as apt to foolishly waste finances. Funds now used in the State of
Michigan for programs (entitlement, etc.) could be channeled for environmental use.

Because it is my business.

Would the money be spent wisely?

1. My believe in ths. Ability to spend money correctly. 2. My distrust of agendas of
"environmental" groups.

I believe that we have more pressing social issues that should be addressed, before
we concern ourselves with issues of this nature.

The final distribution of frequencies for comments categorized on the previous scale is

shown in the next table:

Table 18. Type of No Vote

 

 

 

Category of NO Descri tion Observations
Vote p in Sample
No_l Qgepting the proponed scenario when voting 120
A NO vote with comments related to “weak
No 2 ,, 16
— protest
No_3 Weak protest 19
No_4 Protest 12
No_S Strong Protest (Reject the scenario) 9
Total 176

 

73

We found that most respondents provided comments indicating their acceptance of the
scenario when voting. Further testing of the influence of protest vote in the estimation of
WTP was carried on by systematically excluding the protest voter from the model. There
was no significant effect on the WTP estimations when drOpping the weak protest and

protest groups (40 observations).

74

- CHAPTER 5: IMPLICATIONS AND RECOMMENDATIONS

This research was aimed to assist in the development of a tool for decisionmakers
interested in deveIOping a coastal wetland preservation and restoration program. The
results demonstrate that the public cares for program characteristics. The data
demonstrate that “price” of the programs matters to some respondents. The estimated
aggregated demand of $20,000 per acre is a conservative estimation of the public
willingness to pay for the implementation of these types of program. Programs aiming to
restore or preserve coastal wetlands need to account for the alternative characteristics of
the program particularly when funding support will be asked to the public, their decision

must be taken into account.

Implications for Michigan Wetland’s Policy

Due to the necessity of making trade-offs, policymakers would be better equipped to
design programs likely to be widely supported by citizens if they had knowledge about:
the public’s understanding of coastal wetlands; their choices for protection programs’
characteristics; and their willingness to pay for these programs. Lupi et al. (2002)
demonstrate that ordinary citizens as quite capable of providing information concerning
trade Offs between alternative mixes of wetland attributes. Decisionmaking concerning
the Great Lakes coastal ecosystems can benefit from incorporating public choices for
coastal wetlands and wetland services. This thesis provides a positive step towards a
better understanding of what the public values about wetland protection programs

designed for Great Lakes coastal wetlands.

75

Recommendations for Future Research: Methodological Issues
There are approximately five million acres of wetlands in Michigan, which make up
approximately 30% of the state. Wetlands are extremely scattered in Michigan and one of
the most controversial problems in the regulation of wetlands has been the process of
identifying and classifying wetlands according to characteristics attributed to wetlands
(Gaddie and Reggens 2000). Perhaps for fiiture research, a physical description and
location of the area to be preserved can help respondents to picture the need to protect

critical or endangered coastal areas.

Physical descriptions of changes in resource conditions are frequently unavailable. In
this case, Contingent Valuation questions often are framed to value the policy change.
With unclear or nonexistent information on the resource change (e. g. what are the
positive additional wetland benefits provided by additional 12,000 acres under
protection), survey respondents are left to their own assumptions regarding what the
policy change will accomplish (Barbier, Acreman and Knowler 1997). This can be a
source of bias since different respondents will use different assumptions (i.e. they are
valuing different resource changes), future research should consider testing this type of

bias and explore potential effects, if any, on the estimated WTP.

Survey respondents without a clear understanding of wetland services and State policies,
were left to make two assumptions: 1) How the policy change affects resource conditions,
and 2) how the change in the resource affects the service they receive (Champ 2003,

l 17). The use of follow up questions or Spike Models are suggested to separate sub-

76

samples of respondents that have no economic value for the good in question or have a
different perception of the good Offered (Haab and McConnell 1997, Kristrbm 1997). In
that sense, further modifications in the survey design needs to be carried out for the Open
ended, follow up question in order to allow the researchers to better understand what the
respondents were thinking about when casting their vote. For this research, an Open
ended question was included to elicit each respondent’s explanation of their vote.
Although some respondents provided a comment, the number Of comments collected was
not enough to separate respondents sub samples that allowed for a deeper understanding

of respondent’s vote.

Property rights matter in the case of environmental goods, and in the best case respondent
should understand what they are currently paying for a given level of supply. It is hard to
provide a clear scenario indicating whether the levels of wetland protection are
improvements over the status quo, or potential declines in the absence of sufficient
payments (Mitchell and Carson I993, 50). Perhaps Michigan residents perceive high
levels of services provided by wetlands and do not foresee any threats to coastal wetlands
in their locality for which reason they do not feel that it is important to pay. It is possible
that the effect of degradation of GLCW has different degrees of intensity across the State

and subdivisions can be useful in explaining localized public preferences.

77

CONCLUSIONS

This thesis results demonstrate that the citizens of Michigan have a varied understanding
of Great Lakes coastal wetlands. The results also reveal that the public has definite
preferences about the relative preference for programs to protect Great Lakes coastal
wetlands. Because public support of coastal wetland programs can make them more
successful, it is important to address the public’s understanding and preferences in the

design and implementation of wetland protection programs.

The willingness to pay values per household translates into a present value of about
$20,500/acre of coastal wetland protected or restored. While these are economically
significant values, caution is warranted since less than l7% of the respondents indicated
they would “definitely vote for” the program. This means a referendum would not be
likely to pass under majority rule. In addition, the large share of potential zero values for
WTP suggest that future efforts with this data adOpt spike models with discrete

probability mass at zero.

The results from the parametric model reveals what attributes are preferred and the
demographic variables that are significant in determining the probability of vote for the
program. Programs with more effort to preserving wetlands were significantly more
likely tO be voted for than programs with more effort on restoring wetland (p<0.05). The
cost for the program had a significant (p<0.01) negative effect on votes; while for the
program priority, Biodiversity (p<0.01), Water quality/flood control (p<0.01) and

Waterfowl habitat (p<0.05) had significant positive effects on votes.

78

Using the parametric estimations, the data demonstrated that a positive WTP could still
be expected if the proposed program provides Biodiversity and the maximum
preservation. However, it is evident that conservation cannot serve only one purpose and
the program will have trade offs in terms Of different priorities and

conservation/restoration ratios.

With respect to the tool to acquire land, the results show that none of the three
alternatives are different from each other in explaining the vote because they were not
significantly (p<0.05) different from each other. This can be an indication of either the
indifference of our sample with respect to the tool to acquire land, or a low level Of
knowledge about how these tools are different from one another. The data provides
evidence that any policy Option that is characterized by changing the tool to acquire land
from volunteers will not change the consumer’s choice for the alternative programs.

A few demographics had positive effects on the vote, for instance, environmental group
members (p<0.01) and those who’d visited wetlands (p<0.05). Rural residents had a

negative effect (p<0.05) compared to urban and sub-urban residents.

79

APPENDIX

Pre-notice Letter — used in the first mail contact
First Cover Letter — used in the second mail contact with the first copy of survey

booklet

. Reminder Post Card — used in the third mail contact

Second Cover Letter — used in the fourth mail contact with the second COpy of
survey booklet

Final Cover Letter -— used in the fifth mail contact with the third and final COpy of
survey booklet

Survey Booklet

80

Date

Name Surname
Address
City, State, Zip

Dear Name Surname:

You have been selected to participate in a study of Michigan’s Great Lakes Coastal
Wetlands. The study is part of research at Michigan State University. The project will
provide needed information to local, regional, and state agencies about residents’
opinions and concerns about Michigan’s wetlands along the Great Lakes.

All that we ask is that you complete a brief survey booklet that you will receive in the

 

:' ° ' ‘ ° ° ' mail in about a week. We are writing to you now since many people like to receive
: advance notice of the survey booklet.
O
: Thank you very much.
.
Sincerely yours,
COLLEGE OF

AGRICULTURE
AND NATURAL

RESOURCES

Dr. Michael D. Kaplowitz
DOV-lemon! Pnncrpal Investigator

Michigan State University
323 Natural Resources
East Lansing, Michigan

48824-1222

517/353-1919
Fax: 517/353-8994
kaplowitflmsuedu

MSU is an allumatr’vuctrm.
emu oppodmrfy nstrlufion.

81

 

COLLEGE OF
AGRICULTURE
AND NATURAL

RESOURCES

Resource
Development

Michigan State Uriversity
323 Natural Resources
East Lansing, Michigan

48824-1222

517/353-1919
Fax: 517/35343994
kaplowit@msu.edu

MSU Is an affirmalrve-actim.
ml opportunity mutation.

 

Name Surname

Address
City, State Zip

Dear Name Surname:

You have been selected to participate in a study about Michigan’s Great Lakes Coastal
Wetlands. You may recall receiving a letter about this study about a week ago. The
study is part of an effort by Michigan State University to learn about citizens’ opinions
and concerns regarding the wetlands of Michigan’s Great Lakes.

Your input is important because managing Michigan’s wetlands, including decisions
about restoration or preservation, involves trade-offs that affect you. Results of the
questionnaire will provide needed guidance to local, regional, and state agencies about
residents’ opinions and concerns about Michigan’s wetlands along the Great Lakes.

You have been selected as part Of a scientific sample of Michigan residents. That is why
the survey asks a few questions about you and your household--so we can make sure
that we get a scientific cross-section of Michigan residents. Your participation is vital to
make sure that the information collected represents everyone.

We realize that it takes time out of your day to fill out this survey and have enclosed
three first class stamps as a way of saying thank you for your help.

By completing and returning this survey, you indicate your voluntary consent to
participate in this study and have your answers included in the project data set. The
answers are anonymous, and we will keep your individual views entirely confidential.
Rest assured, your privacy will be protected to the maximum extent allowable by law.

If you have any questions or comments about this study feel free to call me by phone at:
(517) 353-1919, fax at: (517) 353-8994, or e-mail at: kaplowit@msu.edu. If you have
questions concerning your rights as a survey participant, please contact Dr. Peter
Vasilenko, Chair of the MSU Committee on Research Involving Human Subjects, by
phone at (517) 355-2180, fax at: (517) 432-4503, or e-mail at: ucrihs@msu.edu.
Thanks for participating in this study.

Sincerely,

Dr. Michael Kaplowitz
Principal Investigator

82

 

 

MICHIGAN STATE

UNIVERSITY

COASTAL WETLANDS STUDY
c/O Dr. Michael D. Kaplowitz
Michigan State University

323 Natural Resources Building
East-Lansing, MI 48824-1222

Name Surname
Address
City, State Zip

 

 

 

Dear Sir or Madam:

We recently sent you a booklet and request to participate in a study of
Michigan’s Great Lakes Coastal Wetlands. If you returned the booklet,
thank you very much. If you have not yet completed the booklet, please
take some time to do so now. Your input is important to make sure that
policy decisions reflect the views of Michigan citizens. Thank you very
much.

Sincerely,

Dr. Michael D. Kaplowitz

Principal Investigator MICHIGAN STATE
Michigan State University U R Y
(517)343-1919

 

83

 

 

  

COLLEGE OF
AGRICULTURE
AND NATURAL

RESOURCES

Fleeouroe
Development

Michigan State University
323 Natural Resources
East Lansing, Michigan

48824-1222
517/353-1919

Fax: 517/353-8994
kaplowit@msu.edu

MSU is an Jimmie-action.
equal opportmity 'nstr'lutr’m.

MICHIGAN STATE

UNIVERSITY

 

Name Surname
Address
City, State Zip

Dear Name Surname:

About two weeks ago, we sent you a short survey about Michigan’s Great Lakes Coastal
Wetlands. While we’ve heard from some people, to the best Of our knowledge, we have
not yet heard from you. We are enclosing another copy of the survey booklet for you
convenience.

Please mail the completed booklet back to us in the enclosed pre-paid envelope.

lo_ur_ input is important because managing Michigan’s wetlands, including decisions
about restoration or preservation, involves trade-offs that affect you. Results of the
questionnaire will provide needed guidance to local, regional, and state agencies about
residents’ Opinions and concerns about Michigan’s wetlands along the Great Lakes.

You have been selected as part of a scientific sample of Michigan residents. That is why
the survey asks a few questions about you and your household--so we can make sure
that we get a scientific cross-section of Michigan residents. Your participation is vital to
make sure that the information collected represents everyone.

By completing and returning this survey, you indicate your voluntary consent to
participate in this study and have your answers included in the project data set. The
answers are anonymous, and we will keep your individual views entirely confidential.
Rest assured, your privacy will be protected to the maximum extent allowable by law.

If you have any questions or comments about this study feel free to call me by phone at:
(517) 353-1919, fax at: (517) 353-8994, or e-mail at: kaplowit@msu.edu. If you have
questions concerning your rights as a survey participant, please contact Dr. Peter
Vasilenko, Chair of the MSU Committee on Research Involving Human Subjects, by
phone at (517) 355-2180, fax at: (517)432-4503, or e-mail at: ucrihs@msu.edu.
Thanks for participating in this study.

Sincerely,

Dr. Michael Kaplowitz
Principal Investigator

84

 

COLLEGE OF
AGRICULTURE
AND NATURAL

RESOURCES

Resource

Development

Michigan State University
323 Natural Resources
East Lansing, Michigan
48824-1222

517/353-1919
Fax: 517/353-8994
kaplowit@msu.edu

MSU is an altInnatu/e-actrm.
equal opporhnity Iosfitulim.

 

Name Surname
Address

City, State Zip

Dear Name Surname:

During the last two months we have sent you several mailings about Michigan’s
Great Lakes coastal wetlands. Our study is drawing to a close, but we are making
one final attempt to obtain your input.

Your completed survey will provide needed guidance to local, regional, and state
agencies concerning wetlands along Michigan’s Great Lakes. You have been
selected as part of a scientific sample of Michigan residents, and YOUR
PARTICIPATION IS ESSENTIAL to make sure that the information collected represents
everyone.

Please mail the completed booklet back to us in the enclosed pre-paid envelope.

By completing and returning this survey, you indicate your voluntary consent to
participate in this study and have your answers included in the project data set. The
answers are anonymous, and we will keep your individual views entirely
confidential. Rest assured, your privacy will be protected to the maximum extent
allowable by law.

If you have any questions or comments about this study feel free to contact me by
phone at: (517) 353-1919, fax at: (517) 353-8994, or e-mail at: kaplowit@msu.edu.
If you have questions concerning your rights as a survey participant, please contact
Dr. Peter Vasilenko, Chair of the MSU Committee on Research Involving Human
Subjects, by phone at (517) 355-2180, fax at: (517) 432-4503, or e-mail at:
ucrihs@msu.edu.

Thanks for participating in this study.

Sincerely,

Dr. Michael Kaplowitz
Principal Investigator

85

  

 

1:.

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Michigan Great Lakes Wetlands:
Citizens ’ Survey Questionnaire

 

This is an opportunity to provide your opinion and feedback on natural resource
policy and management in Michigan. Your input will help decision makers make
more informed choices on how to restore and preserve Michigan’s coastal wetlands.

This booklet begins by explaining about Great Lakes coastal wetlands and what they
do. It then focuses on how programs can preserve high quality coastal wetlands and
restore poorly functioning coastal wetlands. You are then asked about a proposed
wetland protection program.

Your answers will help ensure that state level decisions reflect the views of the
citizens of Michigan. Thank you for your participation. This booklet’s several
sections of brief questions should take about 15 minutes to complete.

Please return your completed questionnaire in fire enclosed envelope to:

GL Wetland Study, Dept. of Resource Development, 323 Natural Resources
Building, Michigan State University, East Lansing, MI 48824-1222

86

THE GREAT LAKES AND THE GREAT LAKES
WATERSHED:
TYPICAL MICHIGAN COASTAL WETLANDS

 

 

 

 

 

87

GREAT LAKES COASTAL WETLANDS

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Michigan has many important resources, including Great Lakes coastal wetlands.
Coastal wetlands support the health and diversity of the Great Lakes ecosystem.

    

Coastal wetlands provide ecological functions and critical habitat for a wide
range of plants, fish, and animals. They also provide storm water retention,
erosion prevention, water filtration, and other services.

In Michigan, Great Lakes coastal wetlands range from shoreline wetlands and
marshes along the northern coastline, to extensive wetlands along Saginaw Bay, to
the delta marshes Of the St. Clair River.

. {QEAVHPQKESEIEWTL _"_..._ '1- ’"

Healthy Great Lakes coastal wetlands also support a range of recreational
activities including fishing, hunting, bird watching, and hiking.

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1*‘1MW1',> .' "'

 

 

1. Have you ever visited a Great Lakes coastal wetland? (Circle one response)
a. Yes
b. No (Skip to Question 3)
c. I don’t know

2. If you have visited a Great Lakes coastal wetland during the last year,
what did you do there? (Circle all that apply)

I have not been to a Great Lakes coastal wetland during the last year

Fish or hunt '

Watch for birds or other wildlife

Enjoy the outdoors

Other (If selected, fill in blank)

9999'.»

 

3. How important do you think Great Lakes coastal wetlands are for the
following activities? (Mark one response for each activity)

 

 

 

 

 

 

 

 

 

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b. Fishing? [:1 III III E] I [:1
c. Bird watching? Cl . Cl CI 1 E] El
d.,Hiking? 1:] j [:1 ISLE! El

 

 

 

 

 

 

88

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Water Quality & Flood Control
Wetlands absorb nutrients and chemicals as well as filter sediments. I
They control flood damage by intercepting and storing storm water.

.._._.._._..._....__..._.. _.____._.____- _. _ ____ _.\\

\ |

 

 

 

 

 

Open Space near Shore
Wetlands provide areas of open, undeveloped natural areas. They
may provide opportunities for public enjoyment and education.

Waterfowl Habitat
Wetlands provide food and breeding habitat that benefits waterfowl.
Wetlands support waterfowl such as ducks and geese.

 

Fish Habitat
Coastal wetlands provide shallow water areas with vegetative cover
that serve as spawning grounds, nursery areas, and adult fish habitat.

Non Game Species
Wetlands provide habitat for animals not fished or hunted. Such
species include shorebirds, amphibians, and wading birds.

( .
Biodiversity i}
Wetlands’ complex ecosystems support diverse and unique plants .'

 

 

4. In your opinion, how important are Great Lakes coastal wetlands for
providing and maintaining the following services?
(Mark one response for each function)

 

 

 

 

 

 

 

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e. Non-game species? El Cl Cl Cl C]
r. Biodiversity? _ I: [I [:1 El [3

 

 

 

 

 

 

 

 

 

89

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COASTAL WETLANDS STATUS

 
 

 

 

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Wetlands historically stretched from the western edge of Lake Erie across Ohio

into Indiana, and covered the southern edge of Ontario. However, more than

two-thirds of the Great Lakes coastal wetlands have been lost.

Three ways wetlands are typically damaged and destroyed:

5. In your opinion, how serious a threat to Great Lakes coastal wetlands are

Loss of Wetland Acres

Acres of coastal wetlands are destroyed for land development purposes
including agriculture, harbor facilities, shoreline development, resource
extraction (such as peat mining). and urban expansion.

Interference with Water Flows

Coastal wetlands are impaired and lost when activities disturb water
flows essential to support healthy wetland plants and animals. Adequate
water flows are essential for coastal wetlands.

Loss of Plant Diversity

Loss of wetland vegetation increases the danger of wetland loss.
Wetlands dominated by a single type of plant, including invasive
species, typically lead to decreased animal diversity because food and
habitat are unavailable.

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the following activities? (Mark one response for each activity)

 

 

 

 

 

 

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b. New harbor facilities? l3 C] E] Cl D
‘c. Shoreline development? [:1 Cl C] [:1 C]
id. Urban expansion? [:1 Cl C] C] D

 

 

 

 

 

 

 

 

90

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HOW TO PRESERVE AND RESTORE WETLANDS

 

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State and federal laws try to prevent loss of wetland acreage by placing ;
conditions on wetland permits to avoid, minimize, and mitigate wetland loss. i;
However, existing laws do not always protect wetland quality.

 

Wetland protection programs can preserve high quality wetlands already in E

the Great Lakes ecosystem. Wetland protection programs can also restore i
damaged or impaired wetlands to improve Great Lakes ecosystem health. i;
_ {ti

o Preservation of High Quality Wetlands g2?
Wetland programs can protect wetlands that are high quality, ii;
ecologically rich, and hydrologically sound. Wetland preservation is it}
accomplished by agreements with landowners that legally and physically {3%
protect wetlands and their surrounding uplands from adverse changes. iii

E‘i

0 Restoration of Wetlands and Wetland Functions ii;
Wetland programs can improve wetland ecosystems and wetland iii;

functions by restoring wetlands that have been degraded. The restored i3;
wetlands would then be preserved. Coastal wetlands that are impaired
may be restored by improving water flows, planting native species, and
removing invasive species.

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6. How familiar are you with the following approaches used in wetland
protection programs? (Mark one response for each activity)

 

 

 

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b. Restoration of wetlands? Cl C] E] E] El

 

 

 

 

 

 

 

 

 

91

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GETTING WETLANDS TO PRESERVE AND RESTORE

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C-‘W‘

 

When a wetland program is voluntary, the wetland program needs to
negotiate details of wetland access, restoration efforts, and protection plans

with interested property owners who receive compensation.

Written agreements restrict and prevent incompatible land uses and
activities around wetlands being preserved and restored. Here are three ways

for voluntary programs to get wetlands for preservation and restoration:

Purchase Property from Willing Sellers

Wetland programs may buy Great Lakes coastal properties that contain
wetlands and that may be well suited for restoration or preservation.
Purchases are made from property owners who are willing to sell.

Voluntary Permanent Easements

Programs may pay coastal propefly owners to place permanent restrictions,
called easements, on their wetland property. Permanent wetland easements
are voluntary and cost less than the purchase price of the land. Property
owners retain their land but are required to permanently protect the wetlands
and allow any negotiated restoration efforts to occur.

Short-term Contracts (10 Years)
Programs may contract with owners to pay them to protect wetlands on their
property. Contracts cost less than easements and land purchases. When the

contract ends. owners have no obligation to continue protecting the wetlands.

 

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7. How familiar are you with the idea of programs or agencies protecting
natural resources in the following ways? (Mark one response for each)
.3: is s: =: .- 3
. . . . . 5:: E =4 > = g r; r: o .
Familiarity With protecting natural .> E E g *5 g *5 a 8 :2 '
resources through L“ 3 “" Z L“ 2 L“
a. Purchasing property from volunteers? El Cl Cl C]
b. Voluntary permanent easements? Cl E] El Cl
c. l Short-term contracts (IO-years)? Cl J
l ..

 

 

 

 

 

 

92

ALTERNATIVE COASTAL WETLAND PROGRAMS

We need your in put on alternatives for protecting Michigan’s coastal wetlands. Please
review the elements of two alternative programs before answering Question 8.

--__._-...~._.~-.-.——--——..-..— -».—.__.——- _—_-_\

WW
"5 \

 

MICHIGAN ’S COASTAL W'ETLANDS
' These programs target the preservation and restoration of Michigan's coastal
wetland resources. Today, Michigan’s coastal wetlands account for 4% of
Michigan’s wetlands and cover 105,855 acres statewide. The area covered by
Great Lakes coastal wetlands has decreased by 70% in the last 150 years.

    
 
    
  

  

 

 

    
   
  
   
   
   
 
  
 
 
  
 
  
 
 

PROGRAM PRIORITIES

Wetland protection programs must prioritize their efforts to accomplish their
goals with limited funds. Michigan coastal wetland programs can select lands by
placing their highest priority on protecting any of the following features:

 

0 Non Game Species 0 Fish Habitat
0 Open Space near Cities 0 Waterfowl Habitat
Control

No wetland provides only one service. Even when one of the above is the
priority ofa program, some of the other features will also be provided. By
placing highest priority on a particular feature, the program ensures that feature

l
l
I
i
i
0 Water Quality & Flood 0 Biodiversity i
l
l
l
l
will be enhanced. i

 

Coastal wetland programs protect wetlands in two ways. These programs divide
their effort and resources between two types of activities:

 

0 Restoration of coastal wetlands in poor condition

l
l
[l
o Preservation of high quality coastal wetlands ii
ll
Wetlands restored by the program are then preserved by the program. i;

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93

WHICH PROGRAM WOULD YOU PREFER?

The two programs described below take different approaches to coastal wetland
protection. Please compare the two programs before answering Question 8.

 

 

 

 

Restoration of coastal
wetlands in poor condition

 

H How the program gets
coastal wetland sites from
volunteers

 

Pays for purchase, permanent
‘ easement, or ten-year contract

 

coastal wetlands {

90% Restoration

PROGRAM A PROGRAM B
Of the many features coastal
wetlands provide, which is the
program’s highest priority?
. . . Open Space Near
Primary Focus { Non-Game Specres Cities

How the program effort and
resources are divided

Preservanon 0f high quality 10% Preservation 25% Preservation

75 °/o Restoration

 

 

Purchase Property

 

 

Permanent Easements

 

8. If the state had to choose one of these two programs for protecting coastal

wetlands, which of these programs would you prefer?

(Circle one response)

a. Program A
b. Program B

94

 

YOUR VOTE ON A STATE-WIDE PROGRAM

New, we'd like your input on one of the wetland programs. We want your input in the
form of a vote. Please review the following information before recording your vote in
Question 9.

 
    
   
 
  
 
 
   
  
   
   
  
 
 

PROGRAM FUNDING 1*

The proposed program will be funded by a one-time only, tax payment.

The cost to your household will be $40 added to your 2005 state income tax. l
i
l

Programs cost money so voters have to decide which programs they want to
support. Some people will vote for the proposed wetland program because they
think that the program benefits are worth the costs. Others will vote against the
proposed wetland program because they think the program is not worth the costs.

We want your view.

 

 

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PROGRAM IMPLEMENTATION
The proposed program would provide funds for the preservation and restoration
of Michigan’s coastal wetlands.

o The program would do only those things described on the next page.

0 The program would begin only if voters approve it.

 

 

 

 

 

l MICHIGAN’S CURRENT W'ETLAND LAWS
3 State and federal laws try to prevent loss of wetland acreage by placing

j conditions on wetland permits to avoid, minimize, and mitigate wetland loss.
1 However, existing wetland laws do not always protect wetland quality.

l

3

For example, protecting wetland acreage does not always protect the things that
wetlands do. Also, existing wetland laws do not fund preservation and
restoration of wetlands.

 

 

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”"3 *EWWW. -.. _-_. . __ .__

 

 

 

95

PROPOSED COASTAL WETLAND PROGRAM AND COST

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

PROGRAM A
Primary Focus Non-Game Species
Preservation effort “ 10% Preservation
Restoration effort 90% Restoration
Get Program Sites Purchase Property
i
$3135: { 12,000 acres 1
One-time only payment { S 40, one time A
HOW WOULD YOU VOTE? —

9. Think of yourself in the voting booth. There are many things that the State
can spend money on. Program A is one specific program. Suppose Program
A is on the ballot. If it passes, Program A will be implemented and you pay
the one-time, payment. If it does not pass, the program is not implemented
and you do not pay for it.

With the information you have now, how would you cast your vote on
Program A with a one-time cost to you of $40? (Mark one response)

 

l

Definitely vote Probably Could vote Probably vote Definitely vote;
FOR it vote FOR. it either way AGAINST it AGAINST it |

 

av,

i F or Program A Cl C] 3 Cl [:1 C] i

LI would... _ L y

 

 

 

 

 

96

HELP US UNDERSTAND YOUR VOTE

It is very important for us to understand some of the reasons you voted the way
you did in Question 9. Please take a moment and share with us some of your
reasons. Use as much space as needed.

10. Some of the reasons I voted the way I did in Question 9 are

 

 

 

 

 

 

 

 

 

 

 

 

 

97

INFORMATION ABOUT YOU

 

 

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:W‘i‘v'fiim "H

.i T his section asks a few questions about your background so that we can compare ii
our results with the makeup of the state population. Your responses are completely ii

confidential and will not be linked to your identity in any way.

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11. Which best describes the area where you live? (Circle one answer)

a. An urban area
b. A suburban area
c. A rural area

12. How strongly do you agree with each of the following statements?

(Mark one response for each function)

 

 

 

 

 

 

 

 

 

 

 

 

. e E ~83 Es 3s
How strongly do you agree With the "Q 92' as) E; g 8 a, 43) 8b 3.? Eh
following statements? g 3:0 S 33° .5 811.2 E .2 g .2
m 53 Z < a g o m D
a. I contribute to/am a member of E] [I [I Cl
an envrronmental group.
b. I go fishing and/or hunting. E] E] El El El
0. I go camping and/or hiking. Cl E] El Cl El
d. I vote in all state and local elections. Cl C] E Cl [3
e. I wnte letters tonewspapers/ageneies Cl E] El El CI
to express my Views.
f, I follow community issues Cl El Cl Cl C]
(e.g., watch public meetings).
g. I manage my time well. Cl E] El Cl Cl
h. I am often late for appointments. Cl Cl : Cl Cl C]
i. I never seem to have enough time. Cl Cl Cl Cl C]
j. I have a hectic schedule. I] El CI Cl Cl

 

 

 

 

 

 

 

 

98

 

13.

14.

15.

16.

17.

18.

How important is it to know that wetlands are there? (Circle one response)

a. Extremely Important
b. Somewhat Important
c. Not Very Important
d. Not at All Important
e. Do Not Know

How important it is to know that wetlands will be there for future
generations? (Circle one response)

a. Extremely Important
b. Somewhat Important
c. Not Very Important
(1. Not at All Important
e. Do Not Know

What is your age? (Circle one response)

a. l8 to 25 years d. 46 to 55 years
b. 26 to 35 years c. 56 to 65 years
c. 36 to 45 years f. More the 65 years

What is your gender? (Circle one response)

a. Female b. Male

“(hat is your ethnicity and race? (Circle one response)

Hispanic, Latino, or Spanish origin
White

African American or Black
Hawaiian or other Pacific Islander
Asian

American Indian or Alaska Native
Other:

mess-99‘s

 

Generally speaking, do you think of yourself as a... (Circle one response)

a. Democrat 0. Independent
b. Republican d. Other:

 

 

99

19.

20.

21.

22.

23.

24.

What is the highest level of schooling that you have completed?

(Circle one response)

a. Some high school d Associate degree, 2 year college
b. High school degree e. College degree, 4 year college
e. Some college f. Advanced degree (MBA, MD, etc.)

We are interested in learning about the different ways people may earn
their living. Last week, were you? (Circle one response)

a. Working full-time d. A homemaker
b. Working part-ti me e. Retired
c. Going to school f. Other:

 

What was your gross household income in 2003? (Circle one response)

0 to $14,999

$15,000 - $24,999
$25,000 - $34,999
$35,000 - $49,999

$50,000 - $74,999
$75.000 - $99,999
$100,000 - $149,999
$150,000 or more

996*.»
Worm

Which category best describes your primary income source? (Circle one

response)
a. Construction e. Farming
b. Forestry f. Govern rnent
0. Education g. Tran sportati on
d. Real estate Ii. None of these

What is your household size?

a. Number of adults (18 years old and up):
b. Number of children (under 18 years old):

 

 

Which of the following best describes you? (Circle one response)

a. The person to whom the letter is addressed

b. A spouse or relative of the person to whom the letter is addressed
c. A close fn' end of the person to whom the letter is addressed

(1. Someone else (fill in please)

 

Thank You! This completes our questions for you.

100

You may use the back cover to share your ideas or opinions with us.

 

 

Please place the survey in the envelope provided and return it to:

CL Wetland Study, Dept. of Resource Development, 323 Natural Resources
Building, Michigan State University, East Lansing, MI 48824-1222

 

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101

 

REFERENCES

Albert, D. A. and Michigan Natural Features Inventory. (2003,). Between land and lake:
Michigan's Great Lakes coastal wetlands. Lansing, MI, Michigan Natural
Features Inventory.

Amacher, G. S., University of Michigan. School of Natural Resources, et al. (1989).
Application of wetland valuation techniques: examples from Great lakes coastal
wetlands. East Lansing, MI, Institute of Water Research, Michigan State
University.

Barbier, E., M. Acreman, et al. (1997). Economic valuation of wetlands: a guide for
policy makers and planners. Gland, Switzerland, Ramsar Convention Bureau.

Barbier, E. B. (1993). "Sustainable use of wetlands valuing tropical wetland benefits:
Economic methodologies and applications." The Geographical Journal 159(1):
22-32.

Barbier, E. B. (1994). "Valuing environmental functions: tropical wetlands." Land
economics 70(2): 155-173.

Bateman, l. and K. G. Willis (1999). Valuing environmental preferences: theory and
practice of the contingent valuation method in the ULEU, and developing
countries. Oxford [England]; New York, Oxford University Press.

Berrens, R. P., D. Brookshire, et al. (1998). "Exploring nonmarket values for the social
impacts of environmental policy change." 20(2): 1 17.

Brinson, M. M. and R. Rheinhardt (1996). "The Role of Reference Wetlands in
Functional Assessment and Mitigation." Ecological Applications 6(1): 69-76.

Bromley, D. W. (1995). Handbook of environmental economics. Cambridge, Mass,
USA, Blackwell.

Brown, 8., Great Lakes Wetlands Policy Consortium, et al. (1990). Preserving Great
Lakes wetlands: an environmental agenda: the final report of the Great Lakes
Wetlands Policy Consortium. Conway, Mich., Tip of the Mitt Watershed Council.

Cameron, T. A. and M. D. James (1987). "Efficient Estimation Methods for "Closed-
Ended" Contingent Valuation Surveys." The Review of Economic Statistics
69(2): 269-276.

Canadian Wildlife Service. (2002). Where land meets water: understanding wetlands of
the great lakes. Ottowa Queen's Printer.

102

Carpenter, S. R. and M. Turner (2000). "Opening the Black Boxes: Ecosystem Science
and Economic Valuation." Ecosystems 3(1): 1 - 3.

Carson, R. T., N. E. Flores, et al. (2001). "Contingent Valuation: Controversies and
Evidence." Environmental and Resource Economics 19(2): 173.

Carson, R. T., W. M. Hanemann, et al. (1998). "Referendum Design and Contingent
Valuation: The NOAA Panel's No-Vote Recommendation." Review of Economics
and Statistics 80(3): 484-487.

Champ, P. A., K J. Boyle, et al., Eds. (2003). A Primer on Nonmarket Valuation. The
Economics of Non-Market Goods and Resources. Boston, Kluwer Academic
Publishers.

Champ, P. A., N. E. Flores, et al. (2002). "Contingent valuation and incentives." Land
Economics 78(4): 591—604.

Costanza, R. (2000). "Social Goals and the Valuation of Ecosystem Services."
Ecosystems 3(1): 4 - 10.

Costanza, R., R. D'Arge, et al. (1998). "The value of the world's ecosystem services and
natural capital." 25(1): 3.

Costanza, R., S. C. Farber, et al. (1989). "Valuation and management of wetland
ecosystems." 1(4): 335.

Cropper, M. L. and W. B. Oates (1992). "Environmental Economics: A Survey. " Journal
of Economic Literature 30(2): 675-740.

Cummings, R. G., D. S. Brookshire, et al. (1986). Valuing environmental goods: an
assessment of the contingent valuation method. Totowa, NJ ., Rowman &
Allanheld.

Cwikiel, W. and Tip of the Mitt Watershed Council. (2003). Michigan wetlands -- yours
to protect: a citizen's guide to wetland protection. Petoskey, MI, Tip of the Mitt
Watershed Council.

Dahl, T. E., C. E. Johnson, et al. (1991). Wetlands, status and trends in the conterrninous
United States. mid-1970's to mid-1980's: first update of the national wetlands
status report. Washington, DC, U.S. Dept. of the Interior For sale by the U.S.
G.P.O., Supt. of Docs.

Dahl, T. E. and U.S. Fish and Wildlife Service. (2000). Status and trends of wetlands in

the conterminous United States 1986 to 1997. Washington, DC, U.S. Dept. of
the Interior, U.S. Fish and Wildlife Service.

103

Davis, T., D. Blasco, et al. (1997). The Ramsar Convention manual: a guide to the
Convention on Wetlands (Ramsar, Iran. 1971). Gland, Switzerland, Ramsar
Convention Bureau.

 

Dennison, M. S. and J. A. Schmid (1997). Wetland mitigation: mitigation banking and
other strategies for deveIOpment and compliance. Rockville, Md., Government
Institutes.

Diamond, P. A. and J. A. Hausman (1994). "Contingent Valuation: ls Some Number
better than No Number?" The Journal of Economic Perspectives 8(4): 45-64.

Dixon, J. A., Asian Development Bank., et al. (1994). Economic analysis of
environmental impacts. London, Earthscan Publications.

Farber, S. and R. Costanza (1987). "The economic value of wetlands systems." Journal of
Environmental Management 24(0301-4797): 41-51 p.

Farber, S., R. Costanza, et al. (2006). "Linking Ecology and Economics for Ecosystem
Management." BioScience 56(2): 121-133(13).

Freeman, A. M. (2003). The measurement of environmental and resource values: theory
and methods. Washington, DC, Resources for the Future.

Gaddie, R. K. and J. L. Regens (2000). Regulating wetlands protection: environmental
federalism and the States. Albany, State University of New York Press.

 

Gibson, M. (2005). Stated Preference of Michigan Residents for Great Lakes Coastal
Wetland Program Characteristics. Agricultural Economics. East Lansing,
Michigan State University. Master's Thesis.

Haab, T. C. and K. E. McConnell (1997). "Referendum Models and Negative
Willingness to Pay: Alternative Solutions." 32(2): 251.

Haab, T. C. and K E. McConnell (2002). Valuing environmental and natural resources:
the econometrics of non-market valuation. Cheltenham, UK; Northampton, MA,
Edward Elgar.

Hanemann, W. M. (1994). "Valuing the Environment Through Contingent Valuation."
The Journal of Economic Perspectives 8(4): 19—43.

Harrington, S. and Michigan. Dept. of Natural Resources. (1993). Wetland mtection in
Michigan: a handbook for prosecutors and law enforcement staff. [lansing,

Mich], Michigan Dept. of Natural Resources.

Heimlich, R. (1998). "Agriculture and Wetlands: Is "No Net Loss" Achievable?"
Agriculture Outlook: 20-23.

104

Hey, D. L. and N. S. Philippi (1999). A case for wetland restoration. New York, Wiley.

Hoehn, J. P., F. Lupi, et al. (2003). "Untying a Lancastrian bundle: valuing ecosystems
and ecosystem services for wetland mitigation." Journal Of Environmental
Management 68(3): 263-272.

Holmes, T. P. and K. J. Boyle (2005). "Dynamic learning and context-dependence in
sequential, attribute-based, stated-preference valuation questions." Land
Economics 81(1): 114-126.

Jaffe, A. B., S. R. Peterson, et al. (1995). "Environmental Regulation and the
Competitiveness of U.S. Manufacturing: What Does the Evidence Tell Us?"
Journal of Economic Literature 33(1): 132-163.

Kaplowitz, M. D. and J. P. Hoehn (2001). "Do focus groups and individual interviews
reveal the same information for natural resource valuation?" 36(2): 237.

Kean, T. H., National Wetlands Policy Forum (U.S.), et al. (1988). Protecting America's
wetlands: an action agenda: the final report of the National Wetlands Policy
Forum. Washington, DC, Conservation Foundation.

Keating, D. M. (1995). The valuation of wetlands: an Appraisal Institute handbook.
Chicago, Ill., Appraisal Institute.

Kristrom, B. (1997). "Spike Models in Contingent Valuation." American Journal of
Agricultural Economics 79(3): 1013-1023.

Krutilla, J. V. (1967). "Conservation Reconsidered." The American Economic Review
57(4): 777-786.

Lewis, W. M. and National Research Council (U.S.). Committee on Characterization of
Wetlands. (1995). Wetlands: characteristics and boundaries. Washington, DC,
National Academy Press.

Louviere, J. J ., D. A. Hensher, et al. (2000). Stated choice methods: analysis and
applications. Cambridge, UK; New York, Cambridge University Press.

Lupi, F., M. D. Kaplowitz, et al. (2002). "The Economics of Wetland Ecosystem
Restoration and Mitigation: The Economic Equivalency of Drained and Restored
Wetlands in Michigan." American Journal of Agricultural Economics 84(5):
1355-1361.

Maltby, B, International Institute for Environment and Development, et al. (1986).

Waterlogged wealth: why waste the world's wet places? London; Washington,
DC, International Institute for Environment and Development.

105

 

Mitchell, R. C. and R. T. Carson (1989). Using surveys to value public goods: the
contingent valuation method. Washington, DC, Resources for the Future.

Mitsch, W. J. (1994). Global wetlands: old world and new. Amsterdam; New York,
Elsevier.

Mitsch, W. J. and J. G. Gosselink (2000). Wetlands. New York, John Wiley & Sons Inc.

Mitsch, W. J., R. H. Mitsch, et a1. (1994). Wetlands of the Old and New Worlds: ecology
and management. Global wetlands: old world and new. W. J. Mitsch. Amsterdam;
New York, Elsevier: 3-56.

National Research Council (U.S.). Committee on Mitigating Wetland Losses. (2001).
Compensating for wetland losses under the Clean Water Act. Washington, DC,
National Academy Press.

Nyquist, H. (1992). "Optimal Designs of Discrete Response Experiments in Contingent
Valuation Studies." The Review of Economics and Statistics 74(3): 559-563.

Perman, R., Y. Ma, et al. (2003). Natural resource and environmental economics.
London; New York, Pearson Addison Wesley.

Portney, P. R. (1994). "The Contingent Valuation Debate: Why Economists Should
Care." The Journal of Economic Perspectives 8(4): 3-17.

Presser, 8., Ed. (2004). Methods for testing and evaluating survey guestionnaires. Wiley
series in survey methodology. Hoboken, NJ ., Wiley-Interscience.

Randall, A. (1997). "The NOAA Panel Report: A New Beginning or the End of an Era?"
American Journal of Agricultural Economics 79( 5, Proceedings Issue): 1489-
1494.

Stavins, R. N., Ed. (2000). Economics of the environment: selected readings. New York,
W. W. Norton & Company Inc.

Sterner, T. (2003). Policy instruments for environmental and natural resource
management. Washington, DC; Stockholm, Sweden, Resources for the Future:

World Bank; Swedish lntemational Development Cooperation Agency.

The American Association for Public Opinion Research (2006). Standard Definitions: Final
Dispositions of Case Codes and Outcome Rates for Surveys. Lenexa, Kansas, AAPOR.

Tietenberg, T. H. (2000). Environmental and natural resource economics. Reading, MA,
Addison-Wesley.

106

 

Tiner, R. W. (1999). Wetland indicators: 3 guide to wetland identification, delineation,
classification. and mapping. Boca Raton, Fla., Lewis Publishers.

Tumbull, B. W. (1976). "The Empirical Distribution Function with Arbitrarily Grouped,
Censored and Truncated Data." Journal of the Royal Statistical Society. Series B
(Methodological) 38(3): 290-295.

Turner, R. K., D. W. Pearce, et al. (1994). Environmental economics: an elementary
introduction. New York, Harvester Wheatsheaf.

Vileisis, A. (1997). Discovering the unknown landscape: a histogg of America's wetlands.
Washington, DC, Island Press.

Whitehead, J. C., P. A. Groothuis, et al. (2006). Economic Values of Saginaw Bay
Coastal Marshes, Department of Economics, Appalachian State University.

Wilson, M. A. and S. R. Carpenter (1999). "Economic Valuation of Freshwater
Ecosystem Services in the United States: 1971-1997." Ecological Applications
9(3): 772-783.

Woodward, R. T. and Y.-S. Wui (2001). "The economic value of wetland services: a
meta-analysis." 37(2): 257.

World Wildlife Fund (U.S.) (1992). Statewide wetlands strategies: a guide to protecting
and managing the resource. Washington, DC, Island Press.

107

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