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National Economic

Development Procedures

Manual - Recreation

DTIC

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AUG 15 199ti

Volume IV B

Evaluating Changes in the Quality

of the Recreation Experience

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DW&&"u~m Uniuried

July 1991 IWR Report 91-R-7

• " ' , I I i I it I i II I I I I I I II I
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11. TITLE (Include Security Classification)

National Economic Development Procedures Manual - Recreation, Volume IV: Evaluating

Changes in the Quality of the Recreation Experience

12. PERSONAL AUTHOR(S)

William J. Hansen and Daniel D. Badger

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17 COSATI CODES 18. SUBJECT TERMS (Continue on reverse if necessary and identify by block number)

FIELD GROUP SUB-GROUP Recreation, Economics, Benefits, National Economic Developmen

Planning, Travel Cost Method, Contingent Valuation Method,

Environmental Benefits, 19. ABSTRACT (Continue on reverse if necessary and identify by block number)

This is the fourth in a series of manuals designed to provide recreation evaluation procedure

to further implement the "Principles and Guidelines" of the U.S. Water Resources Council.

The emphasis of the first three volumes of this series was, primarily, on the evaluation of

providing new or additional facility developments. This manual emphasizes the evaluation

of qualitative differences in the recreation experience. The primary purpose of this manual

is to describe procedures and methodologies for valuating changes in recreation use values

that result from management decisions impacting on recreation facilities and services and

on the related natural resource base.

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22a NAME OF RESPONSIBLE INDIVIDUAL 22b TELEPHONE (Include Area Code) 22c OFFICE SYMBOL

WILLIAM J. HANSEN (703) 355-3089 CEWR

DO FORM 1473, 84 MAP 83 APR edition may be used until exhausted SECURITY CLASSIFICATION OF THIS PAGE

All other editions are obsolete UNCLASSI FTED
NATIONAL ECONOMIC DEVELOPMENT PROCEDURES MANUAL

- RECREATION

VOLUME IV

EVALUATING CHANGES IN THE QUALITY

OF THE RECREATION EXPERIENCE

BY

WILLIAM J. HANSEN

DANIEL D. BADGER

U.S. ARMY CORPS OF ENGINEERS

WATER RESOURCES SUPPORT CENTER

INSTITUTE FOR WATER RESOURCES

FORT BELVOIR, VIRGINIA 22060-5586

JULY, 1991 IWR REPORT 91-R-7
ii
PREFACE

The work reported herein was conducted as part of the National Economic

Development (NED) Procedures Manual Work Unit within the U.S. Army Corps of

Engineers (COE) Planning Methodologies Research Program. Mr. William Hansen

of the COE Water Resources Support Center (WRSC), Institute for Water

Resources (IWR), manages this Work Unit under the general supervision of Mr.

Michael Krouse, Chief of the Research Division; Mr. Kyle Schilling, Director

of IWR; and Mr. Kenneth Murdock, Director of WRSC. Mr. Robert Daniel (CECWPD) is the Technical Monitor for Headquarters, COE.

Dr. Daniel D. Badger, Emeritus Professor, Department of Agricultural

Economics, Oklahoma State University, co-authored this report while serving

under terms of an Intergovernmental Personnel Act Agreement between IWR and

the Oklahoma Water Resources Board.

S/

Acoession For

INTIS GRA&I

DTIC TAB El

Unannounced El

Just ification.c

-DUtr: but Ion/

' 'blit'Y Codes

J'5lard/or

D i t S;,,, ctal

iii
iv
TABLE OF CONTENTS

PREFACE................................ . .......... . . .... . .. . . . ...

CHAPTER I: INTRODUCTION...................... . .. .... . .. .. .. ....

PURPOSE........................... . ...... . . .. .. .. .....

BACKGROUND.......................... .. ....... . . . .. .. .. .....

SCOPE...................................

INTENDED AUDIENCE............................5

ORGANIZATION OF MANUAL.........................6

CHAPTER 11: CONCEPTUAL BACKGROUND......................7

DEMAND CURVE..............................8

GENERAL APPLICATION...........................15

TRAVEL COST METHOD.......................16

CONTINGENT VALUE METHOD ..................... 18

CHAPTER III: EXAMPLE APPLICATIONS.....................21

TRAVEL COST METHOD...........................21

EFFECTS OF TIMBER HARVESTING ON FISHERY ............. 21

EFFECTS OF CHANGES IN INSTREAM FLOW ON FISHERY..........24

CONTINGENT VALUE METHOD ........................ 27

VALUATING QUALITATIVE DIFFERENCES IN ELK HUNTING IN MONTANA . 27

VALUING WETLAND RECREATION BENEFITS. .............. 31

INTERDISCIPLINARY MODELS.......................35

SUMMARY................................37

REFERENCES CITED..............................39
Table of Contents (concluded)

LIST OF TABLES

Table Page

Number Number

1. Definition of Variables Used in Data Analysis .... ............. ... 34

LIST OF FIGURES

Figure Page

Number Number

1. Interrelationships of Reallocation of Water and Resulting

Biological and Economic Effects ......... .................... 3

2. Demand Curve and Consumers' Surplus Example ....... .............. 9

3. Shift in Demand Curve Due to Improvement in Quality ... .......... . 12

4. Shift in Demand Curve Due to Decrease in Quality ... ........... . 14

vi
CHAPTER I

INTRODUCTION

PURPOSE

This is the fourth in a series of manuals designed to provide recreation

evaluation procedures to further implement the "Principles and Guidelines"

(P&G) of the U.S. Water Resources Council (1983). The emphasis of the first

three manuals in this series (Vincent, et al., 1986; Moser and Dunning, 1986;

and Hansen et al., 1990) was, primarily, on the evaluation of providing new or

additional recreation facility developments. This manual (Volume IV)

emphasizes the evaluation of qualitative differences in the recreation

experience. The first three volumes focused more on quantity issues (valuing

changes in supply), while this volume focuses more on how changes in the

quality of resource attributes affect the demand for, and the value of, the

recreation experience (valuing shifts in demand).'

The primary purpose of this manual is to dcccribe procedures and

methodologies for valuating changes in recreation use values that result from

management decisions impacting on recreation facilities and services and the

related natural resource base.

BACKGROUND

As described in the P&G, National Economic Development (NED) benefits

arise when a Federal investment in water resources increases the Nation's

lVolume I (section on region models) and Volume II (Contingent Value

Models) did discuss evaluating qualitative factors, but with lesser emphasis

than this manual will provide.

1
output of goods and services or reduces the cost of producing these goods and

services. These benefits are measured as the dollar value of the increased

output or the dollar value of the reduction in costs. The adverse economic

effects are the NED costs which arise because resources are diverted for the

project that would have value in alternative uses. These costs are measured

as the dollar value of the resources in their next best alternative use.

Although the P&G was primarily developed for planning new projects, NED

benefits and costs are also relevant in the valuation of management decisions

at existing projects. Activities, such as controlling water releases at dams,

managing fish and wildlife habitat programs, providing ranger patrols, and

mowing of road shoulders, impact the facilities, services, and/or natural

resource base that contribute to the recreation experience. Improved

valuation of the impacts of such actions could provide for a more efficient

and effective allocation of limited resources. For recreation, this valuation

is hindered, not only by an absence of market prices, but sometimes also by an

imprecise linkage between the management action and its impact on the

recreation experience.

For example, an illustration of the generalized linkages between a

potential reallocation of water and resulting impacts on water quality, fish

habitat and recreationists is presented in Figure 1. A change in the

allocation of water (or storage space) between project outputs (uses) could

affect the reservoir operating criteria, leading to a change in the flow

regime. Changes in water release schedules could result in changes in water

quality and in the aquatic habitat. Over a period of time, biological changes

in the fishery resource (e.g., in the size or number of fish) may occur. For

many recreation users, the fishery resource is an important attribute that

2
affects their recreation experience. The impacts on the fishery resource

would, therefore, ultimately be reflected in a change in recreation user

behavior and in economic value.

I Water Reallocation I

Changes in Designated Use(s)

Modify Criteria to Provide

for Designated Use(s)

Changes in Flow Regime

Changes in Water Quality

lChanges in Ecological Conditions

Effects on Recreation Attributes

Behavioral Responses of

Recreationists

Changes in NED Benefits

Figure 2. Interrelationships of Reallocation of Water and

Resulting Biological and Economic Effects

3
The economic evaluation of such actions as depicted in Figure I requires

not only being able to identify the general cause and effect relationships,

but also the marginal changes in user behavior and value that ultimately

occur. For example, assume a management action is going to improve (or

degrade) water quality or aquatic habitat in an a:ea, resulting in an increase

(decrease) in the fishery resource. Some previous studies have valuated such

actions based on an "average value per fish." That is, the total recreational

value for those fishing under existing conditions is first estimated and that

value is divided by the number of fish currently caught. The resulting

average value per fish is multiplied by the changes in fishery resource or

catch, to determine the benefits (positive or negative) of the management

action. Such a procedure violates two basic concepts: (1) it assumes the

total value of the recreation experience is entirely dependent on the fish

caught; and (2) it ignores the principle of diminishing marginal returns.

Although fish catch ma) be important, many fishermen participate in

other activities (e.g., camping or picnicking) during their fishing trips and

other factors (e.g., relaxation, being with friends, and enjoying the natural

environment) also may contribute to their overall experience. The total

economic value of that experience is a function of all factors, not just the

number of fish caught. In addition, the concept of diminishing marginal

returns infers that the value per unit of a good to the consumer or user

declines as more and more units are consumed or used (or, in this example,

fish caught). Average values based on the total fish catch under existing

conditions will almost always overestimate the marginal value of changes in

fish catch that might result from management actions.

4
SCOPE

Step by step proedures for valuation techniques, such as the Travel

Cost Method (TCM) and the Contingent Value Method (CVM), are documented in the

first three volumes of this series. This manual, therefore, does not present

the basic methodologies that have been developed for measuring recreation

benefits. This manual illustrates how these methodologies can be used to

value changes in the quality of the recreation experience.

This manual is limited in scope to addressing use-related values. Much

of the recent research literature on recreation, particularly CVM studies, is

addressing the measurement of such non-use values as option and existence

values. There is still concern and controveksy, however, on when these values

are particularly relevant and of the ability of existing techniques to

separate ideological content from the value measures. This manual is,

therefore, limited to the measurement of use-related values.

Finally, this manual is limited to the measurement of NED benefits and

does not address the issue of economic impacts. The economic impact of

recreation and related tourism expenditures is often of importance to local

sponsors and their constituents. Such impacts are not, however, considered in

the estimation of NED benefits and costs, and are, therefore, beyond the scope

of this manual.

INTENDED AUDIENCE

This manual has been written primarily for use by Corps of Engineers

economists, biologists, outdoor recreation and environmental specialists, and

other planners. Distribution to non-Federal sponsors and to others involved

in providing and/or evaluating outdoor recreation opportunities is encouraged.

5
ORGANIZATION OF MANUAL

Chapter II presents the conceptual background for the manual. It

provides a general discussion of NED benefits. It explores demand curve

analysis and the causes of shifts, either positive or negative, in the demand

curve for selected recreation and environmental attributes or activities.

Finally, the chapter addresses alternative techniques for measuring impacts of

demand curve shifts, such as regional travel cost and contingent value models.

Chapter III provides further amplification of the CVM and TCM

approaches. It gives examples of studies that may be useful as guides in

valuating management actions that impact on the quality of the recreation

experience.

6
CHAPTER II

CONCEPTUAL BACKGROUND

As cited in the Principles and Guidelines (U.S. Water Resources Council,

1983):

Benefits arising from recreation opportunities created by a

project are measured in terms of willingness to pay. Benefits

for projects (or project features) that increase supply are

measured as the willingness to pay for each increment of supply.

Benefits for projects (or project features) that alter willingness

to pay (e.g., through quality changes) are measured as the

difference between the without- and with-project willingness to

pay.

and,

Many proposed projects subject to NED benefit-cost analysis

involve both recreation gains and recreation losses. For example,

stream and land-based recreation may be lost because of the

project, or recreation may be transferred to the proposed site

from a more distant site. Net recreation benefits are the value

of the gains minus the value of the losses; benefits may be

positive or negative.

The basic principle for evaluating NED benefits is to use the concepts

developed from the economics of private goods as an analogy for valuing the

outputs of Federal water resource projects. Basic principles of economics

predict that private markets accurately determine the value of goods to

society. The economic model of markets is based on the behavior of producers

and consumers in the voluntary exchange of private goods and services.

Consumers influence the market through the purchase and consumption of goods

and services that provide them with utility or satisfaction. It is assumed

that consumers make purchases in markets based on their individual valuations

of the goods and services. The external representation of this value is

7
called demand, which describes the relationship between the quantity of a good

or service that individuals wish to buy and the factors that influence their

decisions.

DEMAND CURVE

The demand for a good or service can be represented by a demand curve.

A demand curve shows the relationship between the amount of a good or service

people are willing and able to purchase and the price of that good or service.

The typical demand curve obeys the Law of Demand, which postulates that

reductions (increases) in the price of the good or service will result in

increases (decreases) in the quantity purchased or consumed. As such, the

demand curve slopes downward, to the right. For example, the demand curve in

Figure 2 indicates that at a price of $10, none (0) of this particular good

(in this case recreation days) would be purchased or consumed by users. The

price would simply be too high for consumers to purchase any of the product.

If the price is lowered to $5; however, 50 units would then be purchased or

consumed. In Corps recreation studies, the quantity of the good is typically

measured in recreation days of use.

The Law of Demand only holds, however, if all the other determinants of

demand, such as income, the quality of the good and the prices of other goods,

remain constant. Changes in these other determinants will shift the demand

curve, outward or inward, depending on whether or not the resultant change

increases or decreases demand, respectively. For example, increases in real

income or population shift the demand curve for most goods or services

outward, to the right. For the same price, more units of the good or service

would be purchased or consumed. The introduction of substitutes or a

8
reduction in the price of substitute goods or services will shift the demand

curve inward, to the left. For the same price, fewer units of the good or

service would now be purchased or consumed.

$/Recreation Day

10- E

Consumers'

)5- Surplus

KA Expenditures DDm n uv

Demand Curve

0 50 100

Recreation Days/Unit of Time

Figure 2. Demand Curve and Consumers, Surplus Example

The demand curve also can be used to describe the total value of the

good or service to consumers. As described more fully below and under certain

assumptions, the area under a market demand curve is a good approximation of

the total value of the good or service. If consumers (recreationists) must

9
pay to obtain the good or service, the difference between the value to

consumers of the quantity they consume, and the money they must pay to obtain

the good or service, is called consumers' surplus.

Again referring to Figure 2, if the price of the good or service is $5

per unit, consumers are willing to purchase 50 units in a given time period.

The total value to the consumers of these 50 units is the area under the

demand curve between a quantity of 0 and 50 units. The amount they must pay,

or their expenditures, (area ABCD) is $5 per unit X 50 units - $250. The

difference between what they are willing to pay and what they actually have to

pay is the consumers surplus' (area BEC). In this example2 , the consumers'

surplus is ($5 per unit X 50 units)/2 - $125. The total amount of $375 ($250

+ $125) is the maximum amount consumers are willing to pay rather than go

without 50 units of this particular good or service.

The marginal value for the 50th unit, in this example, is $5. If the

price is higher than $5 per unit, fewer units would be purchased; if the price

is lower than $5, more units would be purchased. The average total

willingness to pay for 50 units, however, is $7.50 per unit ($375 + 50 units),

and the average consumers' surplus is $2.50 per unit ($125 + 50). The

consumers' surplus for the 50th or marginal unit is zero. The $5 price (cost)

is exactly equal to the value of the final unit consumed or taken.

When the quality of an environmental amenity, of the resource base, or

of the facilities or services provided is improved, it will serve as an

attractant to the recreation population. In essence, such an improvement will

shift the demand curve to the right, as shown in Figure 3 with the shift of D,

21n this simplified example where the demand curve is a straight line,

the consumers' surplus can be estimated using the formula for the area of a

right triangle, 1/2 (base x height).

10
to D2 . Improvements in the quality of the good or service will cause

consumers to desire more of that good or service at the same price. This

holds for a recreation day at a particular site or facility the same way it

holds for cars or microwave ovens. If restrooms are improved, attractive

landscaping is added, a gravel access road is paved, additional boat ramps are

added, increased water discharges clear up an algae problem, or fishing

habitat is improved, both current and potential recreationists soon find out

about these improvements. Some current recreationists will use that

particular site or facility more often, and others who had not previously used

the site or facility will begin using it.

Again referring to Figure 3, and assuming the cost per recreation day

stays the same as in the previous example ($5), the recreationists will now

take or consume (demand) 75 recreation days in a given time period rather than

the 50 units previously taken. The amount paid, or the expenditure, is now

$375. It includes the expenditure of $250 for the first 50 recreation days

(area ABCD) plus 25 X $5 or $125 (area DCFG) for the additional 25 recreation

days that would now be taken.

The area under the demand curve designated as consumers' surplus (area

BHF) also has increased. It is now ($7.50 [12.50 - 5.00] per recreation day X

75 recreation days)/2 - $281.25; an increase of $156.25. Again, the total

consumers' surplus of $281.25 represents the additional amount recreationists

would be willing to pay rather than forego the opportunity to use the

particular recreation area ksite or facility) 75 recreation days per unit of

time. Of the $156.25 increase in consumers' surplus in this example, ($2.50

per recreation day X 25 recreation days)/2 or $31.25 (area CKF) results from

the consumers' surplus associated with the 25 additional recreation days

I

11
taken. The remaining $125 (area CEHK) results from an increase in the

consumers' surplus associated with the first 50 recreation days of use

previously taken.

$/Recreation Day

12 -.50 HConsum ers'

10- Surplus

7.50-

0-A D. G

0 50 75 100

Recreation DayslUnit of Time

Figure 3. Shift in Demand Curve Due to Improvement in Quality

Benefit/cost analysis can be used to determine whether or not the

improvement in quality is economically justified. In the above example, the

change in consumers' surplus of $156.25 is the appropriate benefit measure to

12
include in such an analysis. 3 This should be compared to the cost of the

improvement, as well as any additional capital or operation and maintenance

costs that would be required to support the increase in use. If benefits and

costs continue over time, they would need to be projected and appropriately

discounted.*

There may be occasions when the quality of the recreation experience

declines. This could result from such factors as vandalism, inadvertent

pollution, deterioration in facilities because of a decrease in operation and

maintenance funds, an operational change in use of the water, or a drought

affecting water levels.

Figure 4 illustrates the effect of such a degradation in quality. In

Figure 4, the demand curve shifts to the left (from D, to D2 ), signifying that

recreationists will consume fewer recreation days of that resource (site or

facility) at the same cost as considered previously. At a price (cost) of $5

per recreation day, only 25 recreation days will now be taken, compared to 50

days prior to the loss in quality of the recreation experience. The aggregate

cost (expenditure) to the recreationists will be 25 X $5 or $125 (area ABFG),

which is a decrease from the $250 of area ABCD. Similarly, the consumers'

surplus will be reduced to $31.25, area BhF or ($2.50 [$7.50 - $5.00] X 25)/2,

which is less than the $125 of area BEC.

3This assumes that none of the $5.00 in expenditures is for entrance or

user fees.

'A detailed discussion of discounting procedures is beyond the scope of

this manual. The interested reader is referred to Chapter XI of the NED

Procedures Manual - Urban Flood Damage (Davis, et al., 1988).

13
$/Recreation Day

10 - E Cnsumers' Surplus

7.50 -

5-B F C

0 A G ID DD,_.-

0 25 50 75 100

Recreation Days/Unit of Time

Figure 4. Shift in Demand Curve Due to Decrease in Quality

The previous discussion has illustrated, conceptually, how demand curves

can be used to measure the NED benefits (changes in consumers' surplus)

associated with qualitative changes in the recreation experience. Both the

Travel Cost and the Contingent Value Methods can be used to empirically

incorporate demand shifters into use and value estimation models. The general

procedures for incorporating such measures are briefly described below;

several actual applications from the literature are summarized in Chapter III.

14
GENERAL APPLICATION

In its most simplified form, the price-quantity (demand) relationship

can be expressed as:

Q - f(P) (1)

Equation 1 states that the quantity demanded (Q) is a function of the

price or cost (P). Such a relationship was graphically illustrated in Figure

2 and can be used to measure changes in consumers' surplus resulting from

changes in the quantity of a good or service provided. However, to measure

changes in consumers' surplus resulting from qualitative changes in the good

or service, such as illustrated in Figure 3, a more comprehensive formulation

of the demand relationship is needed. Such a formulation can be expressed as:

Q - f(P, D., An, S.) (2)

Equation 2 states that the quantity demanded (Q) is not only a function

of price (P), but also a function of: a vector of m socio-demographic

variables (D), such as population, income, and education; a vector of n site

attributes (A), which could include natural resource related variables, such

as water quality, fish catch, and wiidlife observed, and/or facilities or

services provided, such as boat ramps, campgrounds, and ranger patrols; and a

vector of o measures of the price and quality of substitute opportunities (S).

The non-price variables (i.e., the D's, A's, and S's in equation 2) are demand

"shifters," since they shift the price/quantity relationship to the right or

left, depending on whether or not they have a positive or negative impact,

respectively, on the demand for a particular good or service.

~ •15
Conceptually, the amount and type of variables, or demand shifters, that

can be included in a demand function are unlimited. Data limitations and

resource constraints will, however, pragmatically limit the types and numbers

of variables that can be included. Both the Travel Cost and the Contingent

Value Methods can be used to estimate, or "quantify," the general relationship

described in equation 2.

TRAVEL COST METHOD

The Travel Cost Method (TCM) is fully described in Volume I of the NED

Procedures Manual - Recreation (Vincent, et al., 1986). It uses the variable

travel cost individuals incur to xisit a site as a proxy for price to

determine net willingness to pay. Observations of use at existing sites are

used to derive the price/quantity relationship. As such, there must be

sufficient variation in the prices (travel distances) faced by different

individuals to statistically estimate the relationship. Similarly, if

shifters are to be introduced into the demand relationship to account for

differences in the quality of the recreation experience, there must be

sufficient variation in the qualitative measure faced by different individuals

to statistically estimate the effect on the price/quantity relationship. For

the TCM, this will typically require the availability or development of either

a cross-sectional or longitudinal data base.

Cross-sectional data. Most travel cost studies that have included

measures of the quality of the recreation experience have used cross-sectional

data sources, that is, visitation data collected from several different

recreation sites or areas over a similar time period. The sites or areas must

exhibit significant differences in the measures of quality being valuated.

16
For example, as described in Appendix C of Volume I (Vincent, et al., 1986), a

TCM was previously developed for lake recreation in the Corps Sacramento

District. For this model, the size of the lake in surface acres during the

normal recreation season was included as a measure of lake attractiveness.

Visitation data were available for seven different Corps lakes with varying

pool sizes. Multiple linear regression then was used statistically to

separate the effect of pool size on visits (and value) from the effects of

other variables. In the Sacramento model these other variables were

popuLation, price (measured in terms of travel distance) and a measure of the

availability of substitute opportunities.

Longitudinal data. In some canes, TCM studies can take advantage of

longitudinal or time series data. In such applications, visitation data are

collected at the same recreation site or area over a period of time, during

which a change (improvement or degradation) of a particular factor affecting

the quality of the recreation experience is made. By comparing behavioral

patterns before and after the change, the effect of the qualitative factor on

both recreation use and value can be statistically measured.

Whether using cross-sectional or longitudinal data, the TCM is based on

observations of actual behavior. Although this is considered as an advantage

by some over the "contingent" questioning of the CVM, it does have some

limitations. An important limitation is that the types of variables and

ranges of values that can be tested statistically are limited to conditions

that presently exist or have previously occurred, and for which origindestination visitation data are available. For example, the normal recreation

pools for the seven lakes in the Sacramento model ranged in size from 570 to

6,520 acres. This model could be used to evaluate other lakes in the area

17
with pool sizes within this range with a high level of confidence. However,

as with any such model, if it is applied to lakes outside this range, for

example to valuate a lake with a pool size of 12,000 acres, there is less

confidence in the results. Another limitation is that the TCM generally

cannot be used to evaluate conditions, facilities or services not previously

existing or provided. Documentation of visitor behavior under such conditions

would simply not be available for model estimation.

CONTINGENT VALUE METHOD

The Contingent Value Method (CVM) estimates changes in NED benefits

based on the willingness to pay and the level of participation by individual

recreationists. This price/quantity consumed relationship is determined by

directly asking individual recreationists (either through a mail

questionnaire, telephone or personal interview) questions that Indicate their

willingness to pay for specific recreation opportunities.

As with the TCM, the CVM can be used in both cross-sectional and

longitudinal studies. A CVM survey can be designed to elicit behavioral

and/or valuation responses under varying qualitative conditions at many

different sites or at the same site before and after a qualitative change. In

addition, through the use of hypothetical scenarios, the CVM can elicit

possible behavioral reactions and valuation information on potential changes

in resource conditions, facilities or services not previously existing or

provided.

The CVM consists of designing and using hypothetical markets to identify

the value of recreational amenities, just as actual markets would if they

existed. Three basic steps are involved: (1) the analyst establishes a

18
. detailed hypothetical market; (2) the analyst communicates that hypothetical

market to the respondent and permits the respondent to "use" the hypothetical

market to establish prices or values which reflect the respondent's individual

valuation of the goods, services and amenities "bought" or "sold"; and, (3)

the analyst treats the values reported by the respondent as individual values

for goods, contingent upon the existence of the hypothetical market, and

treats them, along with the Jata contained in the market description (step 1),

as basic data for estimation of the aggregate value of the goods, services,

and amenities.

The CVM specifically differs from the TCM in that, rather than being

based on actual demonstrated behavior of users, it is based on their

hypothetical, contingent behavior. The CVM is predicated on the assumptions

that: (1) consumers can assign an accurate value to recreation experiences,

and (2) this valuation can be directly e .ctr-,J trom them in response to a

hypothetical scenario in a queistionnaire. Successful application of the CVM

requires a high degree ot skill ,A p'-enision in the development, pretesting,

and administration of survey instruments to minimize the opportunity for

biased or invalid response and to maximize the consistency and repeatability

of results.

Some of the advantages of the CVM method are: (1) it obtains direct

estimates of consumers' surplus and therefore is not dependent on historical

use statistics or other types of historical data; (2) it is particularly

useful for valuating small changes in quality and differences in management

strategies; (3) it can be used to evaluate sites that may be one of several

destinations visited on a single trip; and, (4) it can be used for sites or

0

19
activities with insufficient variation in travel distance for using the travel

cost method.

Specifically, CVM techniques can be used to obtain economic information

from respondents (recreationists) on the actual dollar values they are willing

to pay for improvement (or to prevent degradation) in the quality of the

recreation experience. One of the keys, however, to a successful CVM

application is being able to describe the impacts of management actions on the

recreation experience in terms that can be perceived and understood by

respondents.

Some management actions may be directly quantifiable and easily

described to potentially impacted users. Examples include changes in the

number or types of facilities such as campsites, boat ramps or beach areas.

For other management actions, however, the impact may not be as explicit. For

example, describing water quality improvements by percentage increases in

dissolved oxygen or improved fisheries by an increase in stream flows in cubic

feet per second would probably not be very meaningful to most recreationists.

What is probably perceived by most recreationists is, for example, the

additional opportunities (activities) provided by an improvement in water

quality or an increase in the size or number of fish caught because of the

improvements in the fishery. In the next chapter, specific examples are

provided as to how such qualitative variables are defined and measured.

20
CHAPTER III

EXAMPLE APPLICATIONS

This chapter presents some studies which incorporate measures of quality

into the value estimation models. They provide examples of how the

recreationist's willingness to pay for improvements in the quality of the

resource or environmental attribute can be measured. Selected studies using

both the TCM and CVM approaches are discussed. The primary emphasis of this

chapter is to highlight the approach used, rather than to emphasize the

results or findings of the studies presented.

TRAVEL COST METHOD

EFFECTS OF TIMBER HARVESTING ON FISHERY

Loomis (1989) used a bioeconomic approach to analyze the change in value

of recreational and commercial fisheries due to sedimentation from timber

harvesting and road building in two national forests. The case study sites

were the Siuslaw National Forest near Corvallis, Oregon, and the PorcupineHyalite Wilderness Study Area in Montana. Hydrologic models were linked with

fisheries models to predict the change in catchable fish populations due to

watershed disturbances from road building and timber harvesting. A travel

cost model was then used to estimate the change in NED benefits that would

result from alternative management actions that would impact the fi h

populations.

For the travel cost model, Loomis pooled cross-sectional data from

several sites to estimate a recreation demand equation explicitly

21
incorporating fish catch as a shifter (quality) variable. The data were

collected from a survey of licensed fishermen and included information needed,

not only to estimate the number of trips by area of origin typically included

in a travel cost model, but also the total number of fish caught by the

anglers. These latter data could be used to statistically estimate the effect

of "fish catch" on the visitation rate for various sites from the crosssectional data pool. The general form of the model used was:

Ln(Tij/POPi) - B0 - B1 (LnDISTij) + B 2(LnFISHj) - B3(LnSUBSik) + B4(LnINCi) (3)

where: Ti - trips from origin i to site J; i-l ... n; j-1 .. m;

POP i - population of origin i;

DISTij - round-trip travel cost from origin i to site J;

FISHj - total fish catch at site j by all anglers;

SUBSIj - substitute index reflecting the relative price, quality

and quantity of potential substitute sites for

individuals in I for site j;

INC - average income of anglers from origin i;

B's - coefficients to be estimated; and

Ln - natural logarithm

The model was estimated using the double logarithmic form so as to

impose the theoretically desirable condition of diminishing marginal impacts

of fish catch on the visitation rate and, therefore, on the value per fish.

The derived equation predicted a less than one to one proportional

relqtior-hip between the number of fish caught and the number of trips taken.

For example, for the Siuslaw case study, Loomis reported that, generally, a 10

22
percent increase in the number of catchable salmon resulted in an estimated 4-

5 percent increase in the number of trips taken.

Recreational sport fishing benefits were first derived for existing

conditions from the travel cost model for each site using the appropriate

average fish catch data from the angler survey. To derive the sport fishing

benefits under alternative management strategies (in this case levels of

timber harvesting ranging from the natural condition of no logging to

clearcutting), the effects of such strategies on the fish catch needed to be

estimated. Loomis worked with National Forest Service planning teams to

estimate the effects of alternative timber harvesting levels on sediment

levels, stream temperatures, and other fishery habitat conditions, and the

resultant impacts on catchable fish populations.

The estimated proportionate changes in catchable populations then were

used to estimate new average fish catch measures for each of the management

alternatives. By substituting the appropriate new fish catch measures for

those occurring under existing conditions, estimates of the recreational sport

fishing benefits associated with each alternative could be derived from the

travel cost model.

The NED sport fishing benefits associated with each of the alternatives

could then be estimated and comparisons made between alternatives. Those

alternatives that improved the fishery habitat conditions, and thus the

estimated average fish catch, shifted the resource demand curve to the right

resulting in an increase in sport fishing benefits. Those alternatives that

further degraded the habitat, resulting in a lower estimated fish catch

shifted the resource demand curve to the left and resulted in lower NED sport

fishing benefits. As noted by Loomis, net gains or losses in NED timber

23
harvesting benefits also must be considered to fully evaluate the alternative

management strategies.

In the Siuslaw National Forest, clearcutting on 87,000 acres would

result in an estimated loss of around 84,000 salmon and 24,000 steelhead trout

over the 30-year study period. Compared to natural (existing) conditions, an

estimated eccnomic loss of $2 million would accrue to recreational and

commercial anglers from the clearcutting alternative. For the PorcupineHyalite Wilderness Study Area in Montana, the results indicated a $3.5 million

loss in the value of trout fishing over a 50-year period from timber

harvesting in the Gallatin and Yellowstone River Drainages.

Several improvements in this bioeconomic methodology are possible. The

accuracy of the bioeconomic analysis can be improved if the fisheries models

are more precise. Fisheries biologists currently are revising the fishhabitat models that Loomis relied upon for his study. Such revisions will

lead to more accurate estimates of the losses to fisheries associated with

increases in sedimentation.

EFFECTS OF CHANGES IN INSTREAM FLOW ON FISHERY

Maintaining adequate river flows for recreational fisheries is a major

challenge for Federal and state water managers, in view of competing demands

for water. Loomis and Cooper (1990) analyzed the economic benefits of changes

in instream flow to fisheries on the North Fork of the Feather River in

California. The recreationists' benefits were measured using a TCM demand

equation. The level of fish catch was included as a quality variable, which

was in turn a function of the stream flow. In other words, instream flow is

an input to producing fishing quality.

24
River flow influences both the amount of water (such as wetted perimeter

and depth of pools) and quality of habitat (such as water temperature). If

fishing quality is measured as the total fish catch over a time period, it may

be a function of both stream flow and the number of fishing trips to a site.

A two equation system was estimated: (1) a trip demand and, (2) a quasi-supply

or production function for fish catch. For the recreational site, the

following generalized simultaneous system was specified:

TRIPSit/POPit - f(TRVCOSTit, INCit FISHCATCHt, SUBS1 ) + uit, (4)

FISHCATCHt - f(FLOWt, TRIPSit/POPit) + vit (5)

where:

TRVCOSTIt - transportation and time cost of traveling from origin

i to the specified site in year t; i-1 .... n; t-1 ..... T;

INCit - average household income in origin i in year t;

FISHCATCHt - river quality variable at time t;

SUBS1 - price of substitute fishing site available to origin i;

uit and v,, - randora disturbance terms; and,

FLOWt - cubic feet per second (cfs) of flow in yeart .

Data for the study were collected using a short on-site survey of

fishermen along six sections of the North Fork of the Feather River during

1981-1985. Information collected included the anglers' county of origin and

creel data, including the number of fish kept.

Creel and origin-of-angler data, were available for each of the six

river sections for each of the five years of study. The more typical cross25
sectional analysis of multi-site differences could have been conducted with

these area-of-origin data. However, flow data were only available for one

river section, and the objective of the study was to determine the benefits of

instream flow. Empirical estimates were presented, therefore, only for the

river section (section 3, Rock Creek Dam to the Rock Creek power house) for

which both stream flow and survey data were available. The five years of

time-series data for river section 3 made it possible to estimate a singlesite demand equation, incorporating river flow as a site quality variable.

For this study Loomis and Cooper used a nonlinear functional form to

estimate the generalized demand and fishing quality equations (4) and (5)

above. The areas of origin (i) were the 57 California counties from which

visitation originated during the study period. The time periods (t) were the

years 1981-1985. The travel cost was measured as a function of round trip

distance to river section 3 from each area of origin, variable vehicle

expenses such as fuel and repair costs per mile, the average number of

passengers per automobile, and the opportunity cost of travel time in terms of

a fraction of the wage rate. The income measure was the average household

income in county i, in time t. Total fish kept in year t was the measure of

fishing quality. Loomis and Cooper chose to model fishing quality as total

number of fish kept, rather than catch per angler day. They believe, and

other fishing research has shown (Sorg et al. 1985:5), that number of fish

kept may be a better approximation of how anglers form their perception of a

river's fishing quality.

The initial consumers' surplus (net economic benefits to anglers in

river section 3) in 1981 was $108,465 for 4,721 angler trips, or a consumers'

surplus per trip of $23.00. The average observed rate of flow was 101 cfs in

26
1981. Increasing the flow by 20 cfs increased the annual consumers' surplus

by $1,458 to $109,923, or a marginal change tor each 1 cfs of $72.90.

Increasing the flow by 100 cfs increased the annual consumer surplus' by

$5,672 to $114,137, or a marginal change for each 1 cfs of $56.72. Finally,

increasing the flow by 200 cfs increased the annual consumer surplus' by

$9,140 to $117,605, or a marginal change for each I cfs of $45.70. Anglers

were willing to pay more for the initial increases in flow, but less for each

increment as flow increases. The study also indicated a statistically

significant relationship between flow and catch.

As noted by Loomis and Cooper (1990):

To the extent that anglers represent most of the river's users and

fishing quality is their dominant concern regarding stream-flow,

fish stocking might be a viable mitigation option to offset below

natural flows. Our simple bioeconomic model provides the

information on the productivity of instream flow in producing fish

and how anglers value additional fish caught.

This is not to say that instream flow is the only variable affecting fish

populations or fishing quality, or that fish catch is the only variable

affecting the quality of the recreational experience. The study does

illustrate, however, how the interrelationships between management actions

(flows), environmental effects (fish populations), and user behavior

(recreational values) can be considered in a simplified valuation framework.

CONTINGENT VALUE METHOD

VALUATING QUALITATIVE DIFFERENCES IN ELK HUNTING IN MONTANA

Park, et al., (1991) report on evaluating the benefits for elk hunting

in Montana under three different conditions: (1) an elk hunting trip under

27
existing conditions; (2) an elk hunting trip where the chance of getting a

trophy elk would be twice as good as under existing conditions; and, (3) an

elk hunting trip where the hunter would see half as many other hunters as

under existing conditions.

As noted by the authors, elk hunting in Montana is considered both a

prized big game hunting experience and an increasingly scarce one. The state

is known for providing a "wilderness" type experience, where hunts can take

place in remote settings with few encounters with other hunters. Loss of

habitat, through timber harvesting and other such activities, results in fewer

opportunities to harvest a trophy elk (defined as one having antlers with six

or more points), and to participate in a wilderness hunting experience.

Information on the value to hunters of improving their opportunity to bag a

trophy elk or to participate in a wilderness hunting experience could assist

in valuating alternative timber harvesting and habitat management programs.

Data were collected from a sample of all resident and non-resident

hunters with the appropriate Montana big game hunting license and elk tags for

the fall 1986 season. Survey administration was based on the Total Design

Method developed by Dillman (1978). This included an initial questionnaire in

booklet form mailed to the sampled hunters. This was followed first by a

postcard reminder, and then a replacement survey to remaining non-respondents.

The response rate was 73% after adjusting for non-deliverable questionnaires.

For the contingent value portion of the questionnaire, each respondent

was asked a series of three questions concerning willingness to pay for

different hunting experiences. The dollar amount was phrased as an increase

in "$X" in trip costs. The dichotomous choice or referendum format was used.

With this format, respondents were asked whether or not (yes or no) they would

28
still make a trip under the described conditions (scenario) if they had to pay

$X more in trip costs than their current actual costs. The $X amount was

varied among respondents.

The first contingent value question concerned their most recent trip.

It provided an estimate of the benefit (additional willingness to pay) for

hunting trips taken under existing conditions. The second scenario described

an improvement in the chance of bagging a trophy elk. Respondents were asked

whether they would still have made their last trip if everything else had been

the same, except that their chance of getting a 6-point or better bull elk

would be double AND their trip costs would be $X more than their current

actual costs. The final scenario concerned encounters with other hunters.

Respondents were again asked whether or not they would still have made their

last trip if every-' . else had been the same, except that they would see

half as many hu,,r -s as they actually did AND their trip costs would be $X

more than r',eir current actual costs. As with the first scenario, the $X

amounts were also varied among respondents for the second and third questions.

In their analysis, the authors include a discussion of the comparison of

functional forms (linear versus logarithmic) and of a normalization procedure

which are beyond the scope of this manual. For illustrative purposes, only

their findings from the analysis of the logarithmic functional form are

29
presented here. The specification for the logarithmir logit 5 model used in

their analysis was:

YPAY - ao + fi~ln(BID) + f2ln(INC) + P31n(ELK) (6)

where:

YPAY - hunter's yes/no response (YES - 1; NO - 0) to the

willingness to pay question;

BID - increase in trip costs the hunter is asked to pay

for the alternative hunting condition;

INC - income of the elk hunter

ELK - number of elk seen on the most recent hunting trip.

Maximum-likelihood estimates of the above model were derived for each of

the three levels of hunting experience. The estimates were of the amount they

woiil be willing to pay above their actual costs. The mean willingness to pay

results were $126 for current conditions, $179 for doubling the chance of

getting a trophy elk, and $141 for reduced crowding conditions (fewer contacts

with other hunters). With the logarithmic model, the authors reported the

mean willingness to pay for getting a trophy elk, based on 95 percent

confidence intervals, was significantly higher than both the mean willingness

to pay for existing and reduced crowding conditions. Although the mean

willingness to pay for reduced crowding was higher than that for existing

5Logit is a special form of regression analysis that can be used when the

dependent variable is measured in discrete (for example, yes - 1; no - 0),

rather than continuous, terms. In this application the logit model estimates

the probability of receiving a yes answer to various hypothesized increases in

trip costs (willingness to pay). The area under the resulting logit curve is

a cumulative probability function and is used to estimate the maximum

likelihood willingness to pay. For those readers familiar with flood damage

analysis, the logit curve is similar to the flood damage/frequency curve; and

the maximum likelihood estimate is similar to expected annual flood damage.

30
conditions, the difference was not significant, again based on a 95 percent

confidence interval.

The results of the elk hunting analysis relate a change in user values

to a change in the recreation experience (in this case a change in crowding or

harvest). To valuate a specific management action (e.g., a change in timber

harvest practices) requires an estimate of how the management action would

impact environmental factors (e.g., available habitat, hunting area, or size

of elk herds), and ultimately those quality factors of the recreation

experience included in the analysis.

VALUING WETLAND RECREATION BENEFITS

The continued loss of wetland areas to agriculture, development, and

other activities is an issue of increasing concern. In a study for the Corps

New Orleans District, Stoll, et al., (1989) state that considerable research

has been devoted to identifying and quantifying major wetland functions, such

as support of commercial fish and shellfish stocks, waste assimilation, and

flood control. The support of outdoor recreation, however, is a wetland

function that has received limited economic research attention.

The authors note, that to be useful for applied benefit-cost analysis,

economic values must be linked to specific variables over which natural

resource management agencies have control. They state the fundamental

question of interest as: "How does a project induced change in wetland

characteristics impact the net benefits derived from wetland-based

recreation?"

The study was conducted in a large wetland area along the coast of

Louisiana during the 1985-1987 period. Wetlands in this area are heavily used

31
for varied recreational activities including: waterfowl hunting, saltwater

fishing, freshwater fishing, recreational shrimping, and recreational

crabbing. According to the authors, biological studies have shown that

wetlands acreage is directly related to waterfowl, fish, and shellfish

populations. Any loss of wetlands in the area is expected to directly impact

bag or catch and, therefore, the recreation experience. The economic benefits

of wetlands preservation are partially represented by the recreationist's

willingness to pay for higher levels of bag or catch than would otherwise

occur.

Data for the study were collected from a two-stage sampling process. To

estimate annual use of the marsh, an intensive on-site interview was conducted

at 80 access points. As part of this initial survey, respondents were asked

if they were willing to be surveyed by mail at a later date. Approximately

95% of those interviewed agreed to participate in the later survey.

The subsequent mail survcy included the contingent valuation scenarios

and questions. Respondents were asked to value alternative wetlands

protection programs using a series of referendum style questions (ye.- or no to

a specific dollar amount). As described by Stoll, et al., (1989):

Respondents were asked to assume that without the program,

continued wetlands loss would eventually reduce their average

bag/catch per day to zero. Thus, the "without" program scenario

was a zero level of average bag or catch per day. The "with"

program scenario was a positive level of bag/catch per day. In

particular, respondents were asked to value three "with" program

scenarios.

The three scenarios used weie preserving bag or catch at currcnt levels, at a

decrease to 50% of current Levels, and at a decrease to 25% of current levels.

The mail survey instrument was administered using Dillman's (1978) Total

Design Method previously described. A total of 3,842 quosLionnaires were

32
S mailed. After adjusting for questionnaires returned because of bad addresses

(163) and for blank questionnaires (29), the response rate was 55.2% (2,030).

A valuation model was estimated from the survey data and included the

variables defined in Table 1. The general form of the model was similar to

the previous elk hunting example (equation 6) except that many more

explanatory variables were included. Once again, the model estimates the

probability of a "YES" response to the CVM willingness to pay question. As

described by the authors, mean willingness to pay for wetlands-based

recreation was estimated by integrating6 the resulting equation from zero to

the maximum posted-price in the CVM survey. The integration results indicate

an annual willingness to pay of $330 per recreationist to prevent wetlands

loss. The authors interpret this value as the current annual value per user

of wetlands-based recreation in the study area.

O The researchers further indicate that with their estimated willingness

to pay function (the valuation model), total value curves can be derived for

recreational wetland use on an annual basis under varying bag/catch per day

conditions. That is, changes in willingness to pay can be estimated based on

changes in one or more of the bag or catch interaction variables defined in

Table 1. They illustrate this procedure with a hypothetical example.

Critical to such valuations is being able to predict the impact of physical

alterations on the biological populations, and ultimately the change in the

recreationist's bag or catch rate.

6A mathematical procedure for deriving the mean willingness to pay

O directly from the regional value estimating model.

33
S

Table 1. Definition of Variables Used in Valuation Model

Variable Definition

OFFER - natural logarithm (log) of posted-price

TDAYS - natural log of annual waterfowl hunting, freshwater

fishing, saltwater fishing, recreational shrimping, and

recreational crabbing days

WHDUM - indicator variable for waterfowl hunting participant

(1 - YES; 0 - NO)

WHINT - waterfowl bag interaction variable (product of natural log

of waterfowl bag per day and WHDUM)

FFDUM - indicator variable for freshwater fishing participant

(I - YES; 0 - NO)

FFINT - freshwater fish catch interaction variable (product of natural

log of average freshwater fish catch per day and FFDUM)

SFDUM - indicator variable for saltwater fishing participant

(1 - YES; 0 - NO)

SFINT - saltwater fish catch interaction variable (product of natural

log of average saltwater fish catch per day and SFDUM)

RSDUM - indicator variable for recreational shrimping

(1 - YES; 0 - NO)

RSINT - recreational shrimp catch interaction variable (product of

natural log of average recreational shrimp catch per day and

RSDUM)

RCDUM - indicator variable for recreational crabbing

(I - YES; 0 - NO)

RCINT - recreational crab catch interaction variable (product of natural

log of average recreational crab catch per day and RCDUM)

INCOME - natural log of annual income

EQUINDEX - aesthetics/environmental quality index

TYPE - indicator variable for primary reason for hunting or fishing in

wetland (1 - catch or bag fish and wildlife; 0 - other)

PERSPEND - natural log of percentage of annual income spent on recreation

CLUBMEM - indicator variable for membership in an outdoor club

(1 - YES; 0 = NO)

CONGEST - natural log of nonrecreational boats seen per mile per day

ACCESS - natural log of time spent waiting at boat launch and traveling

to site

PERYEAR - natural log of percentage of lifetime spent recreating in the

wetland study area

Source: Stoll, et al. (1989)

3

34
INTERDISCIPLINARY MODELS

The previous examples describe recent applications of the Travel Cost

and Contingent Valuation Methods in estimating the value of qualitative

changes in the recreation experience. They indicate how environmental impacts

and impacts on recreation facilities or services can be quantified for at

least one impacted population, recreation users. These studies have

implicitly, if not explicitly, noted that valuating management actions

requires an interdisciplinary effort to understand complex interrelationships

between physical conditions, biological communities, and human perceptions and

behaviors. Most valuation studies concentrate on modelling this latter human

behavioral component. Few have attempted to operationalize the entire

cause/effect relationship, for example, linking interrelated hydraulic,

biologic, and behavioral models.

* An exception is an on-going effort to develop an interdisciplinary

planning model for water and fishery management in New Mexico. RIOFISH is a

comprehensive simulation model incorporating and interfacing hydrologic,

ecologic and economic modules (Cole, et al., 1990A, and Green-Hammond, et al.,

1990). It was developed for 16 large reservoir fisheries of the Rio Grande

and the Canadian, Pecos and San Juan Rivers. The effort is summarized by

Cole, et al. (1990B) as:

the development of an interdisciplinary model that analyzes

the effects of resource management decisions on New Mexico fishery

production, yield, sportfishing effort, and economic benefit to

anglers. The model recreates river flows and materials

transported through reservoirs and their tailwaters from 1974

through 1987. Solar radiation, water temperature, phosphorus,

nitrogen, suspended solids, and water exchange rates determine

primary production. Organic loads from watershed sources, added

to primary production, form a trophic base for sportfish forage.

Fish production is partitioned into biomass and growth of each age

class in sporLfish and forage fish groups by differential

35
responses to food type, light, water-level fluctuation and

predation. Fish biomass, with angler population distribution and

site condition, contributes to determining angler effort and

economic benefits. Model users can vary and analyze water level

and quality, stocking, fishing regulations, site access, site

facilities, and site entry fees.

As stated by the authors, the principal objectives for developing

RIOFISH were: 1) simulate fisheries of major reservoirs and, to a lesser

extent, connecting rivers in the main river basins of New Mexico; 2) estimate

past fish yields, angler effort, and angler benefits; 3) simulate fish

population structure, growth, and survivorship in river and reservoir

habitats; 4) enable users to model economic impacts of changes in habitat

conditions, stocking rates, harvest regulations, angler access, angler

populations, and facilities as affected by potential management decisions;

and, 5) make the group of models user friendly and operable on microcomputers.

Development of a simulation model like RIOFISH is a comprehensive

interdisciplinary effort, requiring a large commitment of time and resources.

The development of RIOFISH was initiated in 1980, and is presently considered

at an ". . , advanced intermediate stage, ready to be structurally completed

as a comprehensive statewide planning tool (Cole et al., 1990A)." Obviously,

this level of effort is not possible for most Corps planning studies or

operations decisions. It is, however, demonstrative of the type of

interactive, multi-disciplinary analytical model that can be developed.

Possibly even more importantly, it is illustrative of the types of physical,

biological, and behavioral interactions that need to be considered in

valuating alternative water resource management plans.

36

0
SUMMARY

As demonstrated by the examples described earlier, techniques are

available to estimate the value of qualitative changes in recreational

opportunities and experiences. Incorporating these measures into the

valuation of alternative management actions, however, often still requires

qualitative predictions of the actions' impacts on physical and biological

conditions, and ultimately on recreation amenities that impact user behavior.

The importance of clearly defining without- and with-project conditions and

the potential interactions between physical, biological, and human activity

can not be overstated. Management actions and resulting environmental impacts

will often impact on recreational behavior in a manner that can be quantified.

However, the precision of such estimates requires an interdisciplinary effort,

providing outputs of engineering and biological studies in a usable format for

. input to the economic evaluations.

37
38
REFERENCES CITED

Cole, Richard. A., Timothy. J. Ward, Frank. A. Ward, R. A. Deitner, Susan

Bolton, John Fiore, and Katherine Green-Hammond, 1990A. RIOFISH. A

Fishery Management Planning Model for New Mexico Reservoirs. WRRI

Technical Report No. 253. New Mexico Water Resources Research

Institute, Las Cruces, New Mexico.

Cole, Richard A., Frank A. Ward, Timothy J. Ward, and Robert M. Wilson, 1990B.

"Development of an Interdisciplinary Planning Model for Water and

Fishery Management." Water Resources Bulletin. Vol. 26, No. 4, pp.

597-609.

Davis, Stuart A., Nahor B. Johnson, William J. Hansen, James Warren, Frank

R. Reynolds, Jr., Carl 0. Foley, and Robert L. Fulton, 1986. "National

Economic Development Procedures Manual - Urban Flood Damage." IWR

Report 90-R-11, U.S. Army Corps of Engineers, Water Resources Support

Center, Institute for Water Resources, Fort Belvoir, Virginia.

Dillman, Don A., 1978. Mail and Telephone Surveys, The Total Design Method.

John Wiley & Sons; New York.

Green-Hammond, Katherine, Richard A. Cole, Frank A. Ward, Timothy J. Ward,

Susan Bolton, Robert A. Deitner, and John Fiore, 1990. WRRI Technical

Report No. 252. User's Guide for RIOFISH. A Fishery Management Planning

Model for New Mexico Reservoirs. New Mexico Water Resources Research

Institute, Las Cruces, New Mexico.

Hansen, William J., Allan S. Mills, John R. Stoll, Roger L. Freeman, and

Carol D. Hankamer, 1990. "National Economic Development Procedures

Manual - Recreation, Volume III, A Case Study Application of the

Contingent Value Method for Estimating Urban Recreation Use and

Benefits." IWR Report 90-R-11, U.S. Army Corps of Engineers, Water

Resources Support Center, Institute for Water Resources, Fort Belvoir,

Virginia.

Loomis, John B., 1989. "A Bioeconomic Approach to Estimating the Economic

Effects of Watershed Disturbance on Recreational and Commercial

Fisheries". Journal of Soil and Water Conservation. Vol. 44, No. 1,

pp. 83-87.

Loomis, John B. and Joseph Cooper, 1990. "Economic Benefits of Instream Flow

to Fisheries: A Case Study of California's Feather River". Rivers.

Vol. 1, No. 1, pp. 23-30.

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