fiD-Ai74 785 NATIONAL ECONOMIC DEVELOPMENT PROCEDURES MANUAL - 1/f RECREATION VOLUME i REC (U) ARMY ENGINEER INST FOR

VATER RESOURCES FORT BELVOIR VA MI K VINCENT ET AL

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* National Economic

Development Procedures

Manual - Recreation * DTIC

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Recreation Use and

Benefit Estimation Techniques

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March 1986 IWR Report 86-R-4

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UNCIASS TFTED

SECURITY CLASSIFICATION OF THIS PAGE (when Date Entered) REPORT DOCUMENTATION PAGE READ INSTRUCTIONS

BEFORE COMPLETING FORM

I. REPORT NUMBER 2. GOVT ACCESSION NO. 3. RECIPIENT'S CATALOG NUMBER

IWR Report 86-R-4

4. TITLE (and Subtitle) S. TYPE OF REPORT & PERIOD COVERED

National Economic Development Procedures Manual -

Recreation - Volume I - Recreation Use and Benefit

Estimation Techniques 6. PERFORMING ORG. REPORT NUMBER

86-R-4 7. AUTHOR(a) 8. CONTRACT OR GRANT NUMBER(s)

Mary K. Vincent

David A. Moser, Ph.D.

William J. Hansen

9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK

Water Resources Support Center AREA & WORK UNIT NUMBERS

Institute for Water Resources

Casey Building, Ft. Belvoir, VA 22060-5586

I. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE

Water Resources Support Center March 1986

Institute for Water Resources 13. NUMBEROFPAGES

Casey Building, Ft. Belvoir, VA 22060-5586 112

14. MONITORING AGENCY NAME & AODRESS(If different from Controlling Office) 15. SECURITY CLASS. (of this report)

Unclassified 1aS. OECLASSIFICATION/DOWNGRAOING

SCHEDULE

16. DISTRIBUTION STATEMENT (of this Report)

Approved for public release; unlimited

17. DISTRIBUTION STATEMENT (of the abstract etered in Block 20, If different from Report)

IS. SUPPLEMENTARY NOTES

19. KEY WORDS (Continue on reverae side If necessary nd Identify by block number)

Recreation Benefits, Recreation Use Estimation, Travel Cost Method, Use

Estimation Models, Regional Models, Similar Project Approach, Capacity

Approach, Unit Day Value Method, Contingent Value Method

20. A USTR ACT (Cforrtfue m ,erers isi t nif-cweo ry and Identlfy by block numbelr,

The primary purpose of this report is to prov ide an expanded description of

thc recreation evaluation procedures recommeded in thne Water Resources

Council's "Economic and Environmental Principles a:d Guidelines for Water

and Related Land Resources Implementation Studies.' The report summarizes

the conceptual basis of procedures; for recreation v:iliation associated with

water and related land resource planning, describe , t, e mechanics of

acceptable valuation methods, and offers criteria ',)r determining the

applicability of various methods to particular palni in>; situations.

DO I F 1473 EDITION OF I NOV 85 IS OBSOLETE UNCLASSIFIED
NATIONAL ECONOMIC DEVELOPMENT PROCEDURES MANUAL - RECREATION

Volme I

Recreation Use and Benefit Estimation Technigues

by

Mary K. Vincent

David A. Moser. Ph.D.

William J1. Hansen

IAccetlon ForI

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BY .... ............ -

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U.S. Army Corps of Engineers

Water Resources Support Center

Institute for Water Resources

Fort Belvoir, Virginia 22060-5586

March 1986 IWR Report 86-R-4

- - .r 'p.
Table of Contents

Page

Chapter I: Introduction I

Scope and Organization of the Manual 1

Chapter II: Basic Concepts 3

Overview of Recreation Benefits Analysis

within NED 3

Economic Principles of Valuing Recreation 4

Chapter III: Basic Considerations to Understanding a

Benefits Evaluation 9

Description of Techniques for Estimating

Recreation Use 10

Use Estimating Models 10

Similar Project Method 13

Capacity Method 13

Techniques for Estimating the Value of

Recreation Use 14

Travel Cost Method 16

Contingent Value Method 18

Unit Day Value Method 19

Bibliography and Literature Cited 23

Appendix A: Glossary A-I

Appendix B: Sources for Data and Information B-I

Appendix C: Use Estimation Modeling C-i

Appendix D: Similar Project Approach for Use Estimation D-I

Appendix E: Capacity Approach for Use Estimation E-1

Appendix F: Valuating Use with Travel Cost Method F-i

Appendix G: Example of the Application of the Travel

Cost Method G-1

Appendix H: Valuating Use with Unit Day Method H-1
CHAPTER I: INTRODUCTION

Preauthorization planning for water resources development projects

involves an assessment of the anticipated impacts of project alternatives and

an information account display of beneficial and adverse effects on National

Economic Development, Regional Development, Environmental Quality, and Other

Social Effects. National Economic Development (NED) is significant not only

as an account but also as a planning objective. Under Principles and

Guidelines (P&G), one of the alternative plans to address the needs and

opportunities in water and land related planning must be the NED plan. The

NED plan reasonably maximizes the net difference between NED benefits and NED

costs. NED benefits arise when a Federal investment in water resources

increases the nation's 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

cost are measured as the dollar value of the resources in their next best

alternative use.

The purpose of this manual is to provide an expanded description of the

recreation evaluation procedures recommended in P&G and to thereby supplement

the Planning Guidance Notebook.r The manual summarizes the conceptual basis of

procedures for recreation valuat ion associated with water and related land

resource planning, describes the m~ehanics of acceptable valuation methods,

and offers criteria for determining the applicability of various methods to

particular planning situations. The manual is intended for use in Level C

planning and evaluation.

The major requirements of NED benefit evaluation for recreational

components of alternative plans may be summarized as follows. For each

alternative plan, the planning study must estimate NED benefits by:

a. Estimating the value of projected recreational use that would occur

with the plan and also that would be diminished by the plan;

b. Taking into explicit account the competition from other recreational

opportunities within the area of influence of the proposed plan;

c. Estimating future recreational use and value, on the basis of

3oCio-economic variables, over the entire life of the project under both with

and without project conditions;

d. Calculating benefits as the difference between the with-plan and

without-plan value of recreational opportunities within the market area of the

project.

Scope and Organization of the Manual

The manual presentation assumes that a planning study's need for an NED

recreation benefits evaluation has been established. It also assumes some

V 1
understanding of the major causes or explanations of patterns in recreational

": . behavior and some ability to forecast the effects of economic and social

changes as they may impact on planning alternatives.

This manual does not present the historical development of the various

concepts regarding recreation demand and economics, nor is it concerned with

any issues surrounding the theories, application, or improvement of existing

techniques. This manual conforms to the view that existing techniques are

sufficiently well developed to be used in recreation benefit analysis.

There are three major parts to the manual. Chapter II, Basic Concepts,

presents the basic material necessary for understanding the rationale of

recreation benefits evaluation and the process for conducting such an

evaluation within the planning framework. Chapter III discusses different

recreation use estimation and valuation techniques as well as considerations

for selecting the appropriate technique. Finally, the manual is completed

with several appendices that supplement the information in the main text.

Included are a series of appendices that provide general guidance for

ir.plementing all of the use estimation and valuation techniques described in

Chapter III, except for the Contingent Value Method. Detailed guidance for

this technique is provided separately in the Contingent Value Methodology

Guide, (Moser and Dunning, 1985).

.'2

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CHAPTER II-. BASIC CONCEPTS

This chapter outlines the basics of economic valuation concepts and

describes the application of economic theory to the evaluation of outdoor

recreation. In addition, this chapter provides a description of how a

recreation benefit analysis is developed within a planning framework.

Overview of Recreation Benefit Analysis Within NED

Concept of net benefits. A Federal water resources project may both

create and displace recreational opportunities. For example, reservoirrelated recreation may be provided while stream and associated terrestrial

recreation may be lost. The value of the lost recreational opportunities

could be considered as part of the opportunity costs of the project and could

be included in NED costs. The approach suggested in P&G is to determine the

net recreational gains with the project and to add the value of these gains to

NED benefits.

Met NED recreation benefits are defined as the difference between the

value of the recreational opportunities gained and the value of the

recreational opportunities displaced, and may therefore be positive or

negative:

Net Recreation

Benefits = Value of Benefits - : Value of Benefits:

(+ or-) Gained I Lost

Willingness to pay as a measure of benefits. NED benefits arising from

recreation opportunities created or displaced by a project are measured in

terms of aggregate willingness to pay. Total willingness of users to pay is

the sum of two components: the actual entrance fees and user charges for the

right to use the site plus any excess amount which they would be willing to

pay but do not have to pay. This excess amount is the consumers' surplus.

Thus for the recreational opportunity created by the project:

Value Entrance Fees Consumer

of and £

!Benefits: !Total Willingness to Pay! z 1 User Charges + Surplus

Gained _ _ _ _ _ __ _ I _

A similar relationship can be used to represent the value of the benefits lost

with the project from the displaced recreational opportunities. Note that the

gross benefit is the willingness to pay to gain admittance to the recreational

site. It does not include payments made for other goods and services (e.g., food, lodging, transportation or equipment) associated with the recreational

activity. These payments are costs that must be incurred for

3
these goods and services to be used as inputs to the recreational experience,

not an additional amount users would be able to pay for admittance to the

recreational site.

Economic Principles of Valuing Recreation

The basic principle of 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 resources 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

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. Some of the determinants of demand for a particular good include

the price of the good as well as income, tastes and preferences, the prices of

other goods, and the size of the population of potential purchasers.

The demand for marketed goods is usually represented by a demand curve. A

demand curve shows the relationship between the amount of a good people are

willing and able to purchase and the price of the good. The typical demand

curve obeys the Law of Demand that reductions in the price will result in

increases in quantity demanded. The Law of Demand, however, only holds if all

the other determinants of demand, such as income and the prices of other

goods, remain constant. Changes in these determinants shift the demand curve.

For instance, increases in real income or population is predicted to shift the

demand curve, for most goods, to the right. The introduction of substitutes

or a reduction in the price of substitutes is predicted to shift the demand

curve to the left.

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

to consumers. From economic theory, the area under a market demand curve is

considered to measure the total value of the good to consumers. If consumers

must pay to obtain the good, the difference between the value to consumers of

the quantity they consume and the money they must pay to obtain the good is

called consumers' surplus. In Figure II-1 below, if the price of the good is

$5 per unit, consumers are willing to purchase 50 units of the good. 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 ust pay is $5

per unit X 50 units = $250. The difference, the consumers' surplus, is $5 per

unit X 50 units/2 = $125. This amount measures the maximum amount consumers

of the good are willing to pay rather than go without the good.

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$ 10

/

U

N

I CONSUMER'S

T SURPLUS

R 5

I

C

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50 100

Q U A N T I T Y UNITS/TIME

Figure II-1: Demand Curve and Consumers' Surplus Example

Conceptually, a recreational facility has a demand curve analagous to

that of a marketed good. Therefore, the area under the demand curve for a

boat launching ramp or a beach measures the value of the gross NED benefits,

to the users, of providing these facilities. If markets existed for beaches

and for boat ramps, we could estimate the market demand for the facilities as

a function of the price, the socio-economic characteristics of the user

population and other determinants of demand. Then, based on projections of

the future values of these determinants, such as real income, population, and

distribution, we could predict the present and future demand and value of the

recreational site. The analyst attempting to forecast the value of a

recreational facility by forecasting demand is faced with several difficult

problems. First, many recreational facilities are provided to users without

charging a price or admission fee. Therefore, we may only know one point on

the demand curve for the site: the quantity demanded at zero price. We would

not have any other information about other price-quantity demanded points on

the demand curve to determine the value of the site for recreation. Second,

analysts are often faced with the problem of forecasting the demand and value

of a recreational site that does not exist but is being planned. In this

case, we have no direct information at all about the demand for and value of

the recreational opportunity.

Several techniques have been developed to estimate recreational demand

and value and have been applied to a variety of recreational goods. Three of

these techniques are described in P&G: unit day method, travel cost method,

and contingent value method. The acceptability of these methods under P&G

guidance is shown in Figure 11-2. An examination of Figure 11-2 indicates

that the unit day method is acceptable under very limited situations.

Assuming a regional model is not available, the unit day method is acceptable

if expected annual visitation is less than 750,000 visitor days and if either,

(a) recreation costs do not exceed 25 percent of expected total project costs,

5
or (b) specific annual Federal recreation costs do not exceed $1,000,000 per

year.

The P&G does allow for the use of other methods that meet the following

criteria of acceptability and that conform to the selection process described

in Figure 11-2:

1. Valuation is based on an empirical estimate of demand applied to the

particular project.

2. Estimates of demand reflect user population distribution and

socioeconomic characteristics, characteristics of recreation

resources made available, and characteristics of alternative existing

recreation opportunities.

3. Valuation accounts for value of losses or gains to existing sites in

area of influence (without-project condition).

4. Willingness to pay over time is based on projected changes in

underlying determinants of demand.

The three techniques described in P&G can be basically divided into two

types: those that approach the measurement of value by considering price and

use separately; and those that are demand based considering price and quantity

simultaneously.

The unit day method does not attempt to account for the impact of price

on visitation to a recreational site. Instead, an assigned user day value is

applied to the total number of estimated visitors. The visitation estimate

should include the effects of variables that shift the quantity demanded such

as population, distance and income. Regardless of the sophistication of the

visitation estimation approach, however, the unit day method can only at best

provide a rough approximation of the total value of the recreational

opportunity to the potential users.

Both the travel cost and contingent value methods determine the value of

a recreational site by attempting to approximate the price-quantity demanded

relationship. This means they can simultaneously estimate use as well as the

willingness to pay for that use. A separate use estimation technique (and

study) such as needed by the unit day method is not required.

The travel cost method uses indirect means to determine the price

component. Visitation to a site generally varies inversely with travel

distance and time to the site, directly with the population of potential

users, and may also be dependent on other variables. Thus, participation

rates by different user populations at different distances from a site can be

* *6 6

IN, K, .:. , . .. ., - , ,. ., .- -..,. - . - . . .. . .; .-:.. . . - , . .. . . ,..
Is an applicable regional I Use regional

!model available? ---- ES->:model (TCM or CVM)

NO

V

Do uses affected involve

specialized recreation activities? 7I

I I

I I

YES NO

V V

i Develop a regional model or 1 Do estimated annual!

conduct a site specific study !<-YES- ! visits affected

(TCM or CVM) 1 exceed 750,000?

YES NO

V

Do specific annual Federal' 1 Do expected recreation __ recreation costs exceed '<--YES--: costs exceed 25 percent:

$1,000,000 (FT 1982)? of expected total

project costs?

* I

NO NO I

------- >: Use unit day values- -

Figure 11-2: Criteria for Selecting Procedures for Evaluating Recreation

Benefits

Source: P&G Figure 2.8.2

7
estimated from intercept surveys at similar sites within the region. In the

travel cost method, it is assumed that distance or travel time acts as a

barrier to the use of the site and that the cost of travel is a measure of

that barrier for different user groups. Individuals will only visit a site if

the value of the recreational activity at a site is equal or exceeds the cost

of traveling to the site. These travel costs are used to impute the maximum

admission fee that individuals are willing to pay for the use of the site.

The application of the method results in predicting that those individuals

living closest to a recreational site are willing to pay the largest entrance

fee since they have the lowest travel costs.

The contingent value method is a direct approach to determining the

demand and value of a recreational site. Instead of imputing willingness to

pay as a travel cost differential, contingent value directly asks potential

users of a site the most they would pay to enjoy the recreational site as well

as their visitation to the site. The payment is contingent on the provision

of the recreational opportunity and the existence of the hypothetical market

for the site. This information is then used to simulate a willinbness to

pay-quantity demanded relationship for the potential user population.

Although contingent value can use some of the same techniques as the travel

cost method, particularly in predicting visitation, it has several other

advantages. For the travel cost method to be usable, there must be sufficient

variation between the travel costs of the closest and the farthest potential

users. In addition, multiple destination trips present significant

difficulties. These problems are typically not associated with the contingent

value method. In addition, contingent value can be used to determine the

value of a recreational site to current non-users. Economic theory suggests

that individuals may be willing to pay some amount to have a recreational

opportunity provided so it will be available for their future enjoyment, even

if they don't intend to use it immediately. Other individuals may be willing

to pay to have a recreational opportunity provided even if they will never

visit it. Contingent value can be used to estimate these option and existence

values.

In general, the demand based methods are more acceptable from both

economic theory and P&G policy perspectives. This should not suggest that

each of these methods is without problems. As noted above, the travel cost

method is not applicable to every problem. The contingent value method also

has several potentially serious problems. Because it is a stated preference

approach, there is the potential for the stated willingness to pay responses

to be biased. There is also concern whether individuals even know their true

willingness to pay. These problems suggest that a degree of caution and

skepticism on the part of the analyst is appropriate in using either of these

recommended methods. A final test of the results from any method must always

be the analyst's informed judgement about the reasonableness of the results.

-8
CHAPTER III: BASIC CONSIDERATIONS TO

UNDERSTANDING A BENEFITS EVALUATION

Coiponent3 of the Procedure for Benefit Estimation and

Tools Available for Each Component

The benefit estimation process consists of two basic components:

o estimating recreation use

o estimating the value of the recreation use

There are several techniques available for both use estimation and use

valuation:

Techniques for estimating recreation use

o Use Estimating Models

- regional models

- site specific models

o The Similar Project Method

o The Capacity Method

Techniques for estimating the value of recreation use:

o Travel Cost Method

o Contingent Value Method

o Unit Day Value

Although the P&G makes a distinction between use estimation and

valuation, it should be noted that the travel cost MUst, and the contingent

value can, include both components. That is, in the case of the travel cost

method, the use estimation model or similar project data (described below)

used to estimate recreation use is also used directly in the valuation

process. The valuation process is an analytical one, not requiring a second

technique per se. This is an obvious advantage of the travel cost approach.

Similarly the contingent value method can also be used to simultaneoulsy

elicit information on use and value not requiring a separate use estimation

technique or study effort. The unit day method, on the other hand, provides

only an estimate of value and must be used in conjunction with some other use

estimation technique.

In selecting both a use and a valuation technique, consideration must be

given to certain characteristics of the proposed project as well as to data

and other resources available to the planning study. This chapter provides a

basic description of each of the use estimation and valuation techniques as

9
well as guidelines for selecting techniques appropriate for use on a given

project.

Description of Technlques for Estimting Recreation Use

There are three techniques that are considered by the Council's

procedures to be acceptable for predicting the recreational use associated

with plan alternatives:

o use estimating models, of which there are two types: regional and site

specific

o the similar project method

, o the capacity method

Use Estimating Models

The use estimating models are the most technically sound and hence

acceptable methods for use prediction. This technique has the capability for

explicitly accounting for variation in recreation demand. It yields use

estimates that are a product of multivariate analysis of such use-explaining

variables as demographic and socioeconomic characteristics of market areas,

availability of substitute recreation opportunities, travel distance, and

quality factors. The equation for estimating use may be developed from data

from a single (site specific) or group (regional model) of projects.

Within the general category of use estimation models is a sub-category

that are often called gravity models. These are use estimation models that NJ

include the distance between user populations and recreation supply area(s) as

a major explanatory variable. These models are also referred to as travel

cost models and, when certain underlying assumptions are met, can be used for

both use estimation and valuation.

Regional Models. The Water Resources Council's Principles and Guidelines

(P&G) (2.8.9(l)) define Regional Use Estimating Models as statistical models

that relate use to the relevant determinants based on data from existing

recreation sites in the study area. One of the primary advantages of regional

models is that by using cross sectional data from a number of different sites,

the effect on actual behavior of different project features (e.g. lake pool

size or water quality), can be explicitly tested.

- The Principles and Guidelines recognize that the application of Regional

Use Estimating Models can significantly reduce the time and effort required to

conduct an evaluation of benefits for a proposed project. The WRC Principles

and Guidelines not only encourage the use of regional models but also state

* that if an applicable use estimating model has already been developed for the

region in which a proposed project is to be located, it should be used.

As indicated in P&G, the WRC intended to develop, publish, and

periodically update a list of available regional models that may be used to

evaluate proposed projects. However, because of organizational changes, the

WRC has not been able to undertake the task. Nevertheless, the WRC has issued

guidelines for regional models, which, by providing a set of criteria and

10

a4"Z_, % 
characteristics that are desirable in such models, has served to accomplish

the preparatory work for undertaking the task. The WRC guidelines appeared in

the WRC Reference Handbook for fiscal year 1982; for convenience, they are

provided in paragraphs a-d, below.

a. Introduction or Purpose

The purpose of these guidelines for recreation models is to encourage

development of meaningful regional use and benefit estimating models

consistent with the intent of the Procedures for Evaluation of National

Economic Development Benefits and Costs (18 CFR 713, Part K). These

guidelines should foster interagency cooperation in model development by

providing a common set of criteria and characteristics of desirable

regional models.

b. Nature of the Criteria

The criteria are based on the planning and evaluation information that

models should provide rather than their detailed structural

characteristics. This emphasis on model performance will permit

innovation and flexibility in model design, choice of variables, data

collection strategies, and development of recreation use estimates. Good

estimating models, in general, are based on statistically sound

methodologies, incorporate relevant variables, are replicable, and have

predictive power. Specifically, regional recreation models should yield 0an empirical estimate of demand applied to the particular project or site

based on: (1) socioeconomic characteristics of market area populations,

(2) qualitative characteristics and uniqueness of the recreation

opportunities, and (3) costs and characteristics of substitute

opportunities. Models should permit generation of recreation use

projections over time that vary with underlying determinants of demand,

and allow for evaluation of gains and losses in the study area. The

model should reflect the effects of site congestion on the users'

willingness to pay for the recreation opportunity and then be able to

evaluate the possible long term effects of congestion on site

characteristics.

c. Concept of the Region

The region must be determined by a combination of factors based on

relevant activities (functional), types of recreation resources,

geographical boundaries (spatial), geographic distribution of prospective

recreation users, etc. A helpful step is to take into account existing

or future sites that may be significant substitutes for the proposed

site(s). Thus, the concept of the region, as defined in the NED

procedures, is not to use pre-established areas, but to define regions

iteratively during the study as planners develop parameters for a cross

section of sites and determine which are relevant to water related

activities of the proposed sites. Planners should choose a sample

containing a representative number of sites so that the variables will

have predictive power.

d. Application of the Model

The model should be able to be applied to sites rather than to market

areas because water resource planning is designed to produce changes at

1(V
specific locations rather than to abstract area-wide markets of

recreation goods and services. The estimates of value to be obtained

from the model should be consistent with and of a level of precision

similar to the estimates of value derived for other goods and services

produced by a plan.

The procedures should be readily applicable to evaluating proposed

changes on the availability of the specific recreation opportunities

affected by the plans. For example, can the model estimate the benefit of

an additional opportunity of a recreation activity at a particular

location? Have questions concerning the relevant resources and sites

been included in the household or similar surveys?

When meaningful to the resource situation being evaluated, the

consideration of substitution should account for choices among (a)

recreational and non-recreational activities, (b) alternative

recreational activities, and (c) alternative sites for identical

activities.

By following these guidelines, the regional recreation models developed

by planners and researchers should be realistic in terms of their

applicability to the water based recreation setting being evaluated.

The key statement in the guidelines is that the region is to be

determined on a functional basis, not a spatial one. Functional definition of

a region Must take into account interaction or the substitutional effects

among specific sites.

Site-specific Models. The primary differences between regional and

site-specific models is that data from only one project are used for the

latter. This makes it more difficult to account for the impact on actual

behavior of changes in site specific qualitative variables. These can only be

explicitly accounted for by conducting longitudinal studies encompassing

periods during which such qualitative changes occur at the single site.

Contingent value studies could, however, be used to determine individuals

perceived reaction to qualitative changes for inclusion in such models.

The Corps of Engineers has pioneered in the development of both regional

and site specific use estimating procedures for application to both reservoir

and non-reservoir planning situations. For example, a regional use estimating

model (Brown and Hansen, Vol. V, 1974) based on the statistical analysis of

seven reservoirs in the Sacramento District estimates annual day use

visitation as a function of the projected population for the year of estimate,

the road mile distances between the proposed project and users points of

origin, the water surface area, and the availability of recreation

alternatives in relation to the proposed reservoir. The use estimation

equation developed for this model is a good example because it takes into

account those variables that are considered to be critical to recreation use

regardless of location. General guidance on the development and application

of use estimation models based on this work is provided in Appendix C.

12

. 4

,
-I--

Similar Project Method

The similar project method involves comparing certain characteristics of

the proposed project with those of a bank of existing water resources projects

for which use statistics and other information have been compiled (site

specific studies). The objective is to match the proposed project as closely

as possible to one of the projects in the bank. The method assumes that if

the proposed project displays characteristics that are similar to an existing

project, than recreation use at the proposed project may be expected to be

similar to that at the existing project. The characteristics that are

compared include: project type, size, and quality; market area demographic

characteristics; user chiaracteristics; existence and relative location of

competing recreation opportunities; and other demand variables.

Because of the large number of variables which normally are involved, it

is rarely possible to obtain exact matches which would allow the direct

estimation of use. For this reason, the most efficient and technically sound

similar project techniques are those which provide for the development of per

capita use curves (i.e., gravity models comparing per capita rates of use

against travel distance) from which use estimates are then indirectly derived.

In procedural terms such techniques initially involve the identification of a

basic per capita use curve which belongs to that project in the data bank

which most closely resembles the proposed project, including resemblance of

user characteristics. The shape and location of the per capita use curve is

then manually adjusted in order to account for the significant differences

which may exist between the respective projects and to explicitly account for

demand variables which are unique to the planning alternative. Manual

adjustment is admittedly subjective, but the degree of accuracy can be

improved by generalizing on experience with the technique.

One important disadvantage of the similar project method is that it does

not explicitly consider substitutes, site attributes, and socioeconomic

characteristics. One advantage of the method is that when it employs per

capita use curves based on travel distance, the resulting incremental use

estimates can be used directly as input for applying the travel cost method

for use valuation. General guidance on the implementation of the similar

project approach is provided in Appendix D.

Capacity Method

The capacity method involves the estimation of annual reoreation use

based on instantaneous resource or facility capacities and expected daily,

weekly and seasonal use patterns. Since the estimates are based on

instantaneous capacities which normally remain constant, annual use estimates

will not vary over time unless changes are anticipated in seasonal use

patterns. Likewise seasonal use patterns, which are climate and culture

dependent, will probably account for the greatest variation in use estimates

between projects.

* - Because the capacity method does not involve the estimation of sitespecific demand, its use is valid only when it has been otherwise determined

that sufficient need exists in the market area of the proposed project to

13
accommodate the project's calculated capacity. Determination of the market

area need is done as Step 4 (Determine the Without-Project Condition) of the + :-

planning framework.

The capacity method has its greatest potential for use in urban settings

when it is immediately obvious that sufficient need exists for the

opportunities that the proposed project could provide. Use of the method

should be limited to small projects possessing a facility orientation (as

opposed to a resource attraction) and having restricted market areas. General

guidance on the application of the capacity method is provided in Appendix E.

Summary of Considerations on Use Estimation Techniques

The Water Resources Council encourages use of regional models where

available. Even if a regional model is available there may be circumstances,

however, in which it would be better to develop a site- specific model: for

example, in situations in which the proposed project is unique or else will

provide or displace an activity or resources to which the regional model is

not amenable. Table III-I summarizes the major points to consider in

selecting a use estimation technique. One of the chief points to note is that

use of the capacity method for estimating use precludes application of the

travel cost method for valuation.

Because of the limitations of the capacity method, the similar project

approach and the use estimating models are the most desirable techniques for

use estimation. The similar project approach is much simpler to use than the

models but it requires substantial judgement by the planner to account for

differences in factors (e.g., water surface acreage) between the existing

project from which it was developed and the proposed project at which it is to

be applied. A use estimation model requires more work by way of the

measurement of variables and testing for statistical significance, but it

enables and eases the explicit consideration of such factors as site

characteristics, available substitutes, and the socio-economic characteristics

of potential users.

Techniques for EstimutIng the Value of Recreation Use

The methods which are recognized in the Council's procedures as being

acceptable for valuating recreation use are the travel cost method, the

contingent value method, and the unit day method. Other methods may be used

if they satisfy the following acceptability criteria, which were established

by the Council:

o Evaluation is based on an empirical estimate of demand applied to the

particular project.

o Estimates of demand reflect the socioeconomic characteristics of

market area populations, qualitative characteristics of the recreation

resources under study, and characteristics of alternative existing

recreation opportunities.

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14

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o Evaluation accounts for the value of losses or gains to existing sites

in the study area affected by the project (without project condition).

o Willingness to pay projections over time are based on projected

changes in underlying determinants of demand.

If other valuation procedures are used, evidence of their conformance to the

criteria must be given.

This section provides information on the three WRC recognized valuation

methods so as to help in selecting one suitable for a particular project. For

each method this material includes: a brief description, the basic principles

and assumptions, and remarks on appropriate use.

Travel Cost Method

Brief Description. The travel cost method uses the variable costs of

travel as a proxy for price in determining net willingness to pay for

increments or decrements of supply above fees and user charges. The variable

costs of travel include travel distance and the value of travel time. Because

travel distance and travel time provide the basis for evaluation, the method

builds directly off gravity type use estimation models. These models describe

in a mathematical form (curve or equation) the relationship between the

location of a population mass and the frequency of visits to a given

recreation area. The travel cost method is based on empirical data of

recreation visitors making use of the opportunity to participate in activities

at existing areas and so derives use estimates based on the actual market

behavior of individuals. The demand curve it generates for a resource area,

* however, is indirectly imputed because the method uses expenditure behavior as

a proxy for price.

Briefly, the process for applying a use estimation model to derive a

demand curve for the resource being evaluated can be described as follows.

First, the model is applied to all areas of origin of potential users using

actual mileage data and other variable measurements included in the model. The

predicted use from all origins is summed to obtain an estimate of total use at

zero price. It is then assumed that participants will react to an increase in

fees just as they do to an increase in travel cost. Therefore, the travel

distance for each origin is incremented by a fixed amount with the associated

travel cost used as the proxy for price, and the model used to estimate use at

this new hypothetical fee level. The procedure is repeated, and successive

estimates of use at each level of fees obtained. These estimates are then

used to construct a site demand curve. Consumer's net willingness to pay for

the opportunity to participate in recreation at the site or resource is

estimated by the area under this demand curve. An estimate of gross

willingness to pay may then be obtained by adding site entry or use fees, if

any, to net willingness to pay.

Basic Principles and Assumptions. The travel cost model is developed by

using actual observations on use and user characteristics from various origins

to a site. The wide range of costs facing individuals at different distances

from a site provides considerable information about the influence of costs on

4.m

16
., -

participation. This information can be used to generate a demand curve i.e.,

estimates of participation at various entry fees). A direct measure of site

demand would require data relating site use to various levels of user fees.

Since actual fees show little variation, and are not charged for many sites,

only indirect estimation of the demand curve is possible. An experiment with

changing site fees is an obvious way to find the demand curve at an existing

site. It might provide a useful check on other methods, however, the

practicality of such an undertaking is subject to question.

A number of assumptions are either implicitly or explicitly made in the

use of the travel cost approach. Three major assumptions are listed below.

These must be satisfied in order for the method to provide useful estimates of

use and benefits.

1. Entry Fees: It is assumed that an individual would react to an

increase in entry fees in the same manner as to an increase in travel

costs. That is, recreationists treat travel expenditures as

equivalent to admission costs.*

2. Specification: The assumption is made that all relevant and

statistically significant variables which affect trip-making behavior

are included in the use estimation procedures. Under this

assumption, unbiased estimates of the slope of the site demand curve

may be found.

3. Capacity Constraints: It is assumed that observed data points used to

estimate the original use estimation model are true demand points.

That is, there is no unobserved demand that is unsatisfied due to

capacity restrictions at the sites where the data are collected, or

if people are turned away, it is done so randomly with respect to the

distance they traveled to use the site.

Appropriate Use. In general, the travel cost method is the appropriate

use valuation technique to apply when the following circumstances exist:

1. There is sufficient variation in travel costs among users to allow

estimation of demand.

2. The proposed changes being evaluated are significant enough to alter

travel cost to some individuals or to alter the number of trips that

will be made at the existing travel cost.

3. The travel expenses have been made mainly for the purpose of

recreation at the resource which is to be evaluated.

* The travel cost method has broad application, but it is clearly most suited for rural sites where users may come from a wide range of distances and

0 Recent work by Bowes and Loomis (1980) indicates this assumption may not be

as critical as once thought.

17
when most visits result from trips made for the sole purpose of using the

site. It is less useful for urban parks where there may be too little

variation in travel costs.%J

The circumstances under which the travel cost method is not suited should

also be mentioned:

1. It is not appropriate for evaluating the benefits of a site which has

insufficient capacity to meet demand unless it can be shown that

individuals are turned away randomly with respect to distance

traveled.

2. It is difficult to apply the method when the purpose of the trip is

not primarily for the sole purpose of visiting that site.

3. It cannot be applied to recreation activities involving limited

travel. There Must be sufficient variation in travel distance to

trace out a demand curve.

General guidance on applying the valuation portion of the travel cost

method is provided in Appendix F. A detailed example of a travel cost

application, including development and use of a site-specific use estimation

Vmodel is provided in Appendix G.

Contingent Valuation Method

Brief Description. The contingent valuation method 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 or a telephone or personal interview) questions that indicate

their willingness to pay entry fees for recreation opportunities.

Contingent valuation methods consist 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 hypothetical market, in detail; (2) the analyst

communicates that hypothetical market to the respondent and permits the

respondent to "use" the hypothetical market to make "trades" and 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 the goods,

contingent upon the existence of the hypothetical market, and treats them,

along with the data contained in the market description (step 1) as basic data

for estimation of the aggregate value of the goods, services, and amenities.

Basic Principles and Assumptions. The contingent value method

specifically differs from the travel cost method in that, rather than being

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

contingent behavior. The contingent value method is predicated on the

assumptions that: (1) consumers can assign an accurate valu e to recreation

18

IAIN ,
experience, (2) that this valuation can be directly elicited from them in

response to questionnaires.

Appropriate Use. Successful application of the contingent value method

demands a high degree of skill and precision in the development, pretesting,

and conduct of survey instruments to minimize the opportunity for biased

responses and to maximize the consistency and repeatability of results. Some

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

consumer surplus and therefore is not dependent on historical use statistics

or other types of historical data; (2) it is particularly useful for

evaluating small changes in quality and differences in management strategies;

(3) it is capable of quantifying the effects of projects on the value of

competing recreation areas; (4) it can be used to evaluate sites that may be

one of several destinations visited on a single trip; (5) it can be used to

evaluate the effect of congestion; and (6) it can be used for sites or

activities with insufficient variation in travel distance for using the travel

cost method. For a more complete description of the use of the contingent

value method to evaluate recreational components of Corps projects, see the

Contingent Value Methodology Guide (Moser and Dunning, 1985).

Unit Day Value Method

Brief Description. The unit day value method applies a simulated market

*value to projected use. The simulated value is judgmentally derived from a

range of values agreed to by Federal water resource agencies (PG). It is

intended to represent the users average willingness to pay for a day of

recreation activity at the site. When a properly formulated unit day value is

applied to estimated use, an approximation of the area under the site demand

curve is obtained, which is used in estimating recreation benefits.

A national schedule is available (in the Planning Guidance Notebook)

showing a range of values for each of two types of recreational opportunities:

general and specialized. General opportunities are those that appeal to the

majority of recreationists and that usually require the development of access

or facilities, e.g., picnicking and boating. Specialized opportunities, in

general, are limited, and are associated with low intensity of use and high

user skills. A survey of market (private) prices or a point rating system can

be used to select a specific value from the published schedule of value

ranges.

Basic Principles and Assumptions. The method inherently relies on

professional judgement to arrive at a project specific unit day value.

Consistent application of the procedure for each alternative being evaluated

will produce meaningful estimates of value. When using the unit day value

method, departure from the published range of values is not permissible.

Appropriate Use. When preliminary evaluations indicate a value outside

of the published range of value, either a travel cost or a contingent value

study is generally indicated.

General guidance on the implementation of the unit day approach is

provided in Appendix H.

19

1 le
Summary of Consideration on Use Valuation Techniques

The Water Resources Council procedures include a decision flowchart of

criteria to consider in selecting a valuation technique. The flowchart was

given earlier in this manual as Figure 11-2. An adapted version of this

flowchart is provided as Figure III-I. It may be necessary to employ two

different valuation techniques on the same study. This is because an

appropriate technique Must be selected for each of two categories of use:

a. expected use of facilities to be provided by the project (including

transfer of use from other sites).

b. existing site use to be displaced or eliminated by the project.

In addition, different techniques could be needed within each category of

use if both generalized and specialized recreation activities are affected.

Use of the unit day value technique is not warranted if an applicable

regional model is available. If a regional model is not available, use of the

unit day value method is appropriate only when the estimated number of annual

visits affected is less than 750,000. Even under this condition, the unit day

value method should not be applied if expected recreation costs not only

exceed 25 percent of the expected project costs, but also if the annual

Federal recreation costs exceed $1,000,000 (FY 1982).

20

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26

.1 el
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27

V . "...
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Moncur, J.E.T. 1975. Estimating the value of alternative outdoor recreation

facilities within a small area. J. Leisure Research 7(Autumn) 301-311.

Moser, D.A. and C.M. Dunning. 1985. A guide for using the contingent value

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Engineer Institute for Water Resources, Fort Belvoir, Virginia.

lorton, G.A. 1970. Public outdoor recreation and resource allocation: a

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32b-8 37.

28

9%
Shafer, E.L. and J. Mietz. 1969. Aesthetics and emotional experiences rattbigger with northeast bikers. Environ. and Behavior 1(2): 187-139.

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29

" .""' ,". ', " "','" -' " ",""/ "". ,'."% , : " .. w % " ' .. " , ". - , . . .-, -.-- -, . '-V. .. ,
Van Doren, C.S. 1967. An interaction travel model for projecting attendances

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.)f oater oriented recre', ;)n quality. Utah Water Res. Lab. Logan, Utah.

Wol(a, K.K. -nd G.H. 7oW-3. 1974. Estimating reservoir recreational visits

,# Indi-3na. Te!cnnLcl ,-port No. 48. Purdue University Water Resources

R,6-?arch Cente r. Weit i.i!'3yette, l iana.

30

_ .
APPNDIX A: GLOSSARY

[-' -. ° 
APPENDIX A: GLOSSARY

Accessibility: the relative difficulty or ease of access; its distance from

the visitor's point of origin; its nearness to other developed or undeveloped

sites or areas; and its natural, physical characteristics.

Benefit: gross value, positive or negative, of recreation use of the resource

for the with-project condition less the gross loss in recreation caused by the

project or plan.

Carrying Capacity: tnt number of users (for example, per acre) per day that

can be accommodated without deterioration of the resource or the recreation

activity. These are a function of user-site interactions varying according to

personal taste, the nature of the recreational activity, quality of facility

design, the natural features of the site and the levels of investment in

cultural treatments, supervision, and education.

Consumer Surplus: a concept of the net benefit to consumers, or the

willingness of consumers to pay in excess of their actual payment. It is

represented as the area under the demand curve above the price line. Consumer

Surplus is also known as unpaid for value.

Demand: a schedule of quantities of goods or services that an individual or

group of individuals will purchase at various prices. Refers to the quantity

or number of units of a good or service demanded at specific levels of price.

General Recreation: refers to a category of recreation activities. General

recreation involves primarily those activities attractive to the majority of

outdoor recreationists and which generally require the development of

convenient access and adequate facilities. This category includes, but is not

limited to, swimming, picnicking, hiking, sightseeing, nature studies, tent

and trailer camping, water skiing, scuba diving, motor boating, sailing, and

canoeing in placid waters. It also includes most warm water fishing, small

game hunting, and marine pier nd party boat fishing.

Market Area: the area within which some percent (e.g. 80 percent) of the

potential day use visitation and some percentage (e.g. 50 percent) of the

potential overnight and weekend use visitation would originate plus an

additional area containing the alternative recreation opportunities for ma'ket

area populations. In heavily populated areas, the market area may constitute

an hour's drive or approximately 50 miles. Good roads and lack of alternative

recreational opportunities may indicate that the market areas should be

extended based upon local conditions and habits of users at other recreational

development in the area. On the other hand, topographical features or

barriers may determine that the market area be retracted.

National Economic Development: A national objective of water resour 'es

planning. Contributions to national economic development (NED) are increases

in the national output of goods and services, expressed in monetary units.

P . Contributions to NED are the direct net benefits that accrue in the planning

area and the rest of the nation. Contributions to NED include increases in

A-1
'ne ne' va''ue tose goods and servi:es that are mar~eted, and also of znose

that nay :,-> -KoeI

Net Recreat.on Benefits: difference between the value of tne gains and the

vale )f t oss net oenefits may be positive or negative.

Outdoor Rec eimaa Activities: include water-dependent activities such as

swimming, b.aY-a' ,, '-sning, and fishing and water-enhanced activities

such as campIng. niK1ng, picnicking, hunting, birdwatching, wildlife

photog-,ipr!, 'v n :eing, and other activities. (FR 44(242): 72985, 14 Dec.

Potential i.. >.- ".':ted visitation at prevailing prices unconstrained by

supply.

Recreation ;.: a '-actof land and water area of substantial size which may

contain one j," ,-,era -e eational activities on a project. Usually reached

% by 3 ' ngie ,:e- ->aL for control purposes.

Recreation Da_: s-nvdari unit of use consisting of a visit by one individua"

to a ecrea.ior eveopmert or area for recreation purposes during any

reasonable pori:,,n or al of a 24-hour period.

*1 <zRecreational Development: ?ny type of facility or improvements which are

planned, designed. developed and managed for recreational purposes.

Recreational Experience: a human experience that finds its source in

voluntary engagements that. are motivated by inherent self-actualization

satisfactions ierived therefrom and that occur during non-obligated time.

Recreation Facilities: investments in equipment or modification of resources

in order to provide for certain kinds of recreational use.

Recreation Resources: in-lude those lands and waters and the living resources

supported by the that n ar- or can reasonably be expected to become available

or developed for purlic u3e in the absence of the project being considered.

Recreation Supply: a meiEure of the capability of existing resources or

facilitie3 to satisfy re,:reation demands without consideration of the p'Ip: ei

project or programs.

3pecialized Recreation: refers to a category of recreation activities.

Specialized r-!,reation i-;volves those outdoor activities for whiclh

opportunities, in genera., are limited, intensity of use ts low, and users'

skill, knowledge, and 2nv)reciation are great, and which often involve a Large

personal expense Da tre iser. This category includes, but is not limited to,

cold water fishing, 4,: biro and waterfowl hunting, wilderness pack %rips,

whi.te water coca i rig jrn oing, and Long-range cruises in areas of

outstanding 3-ern e:ivi -,nrnent.

J:3e: recreat ,-,ti atte mi r,ce. Actual participation in or ccnsunrpt -,

7! .)

recre~atv-al "e O'-::. oi). to be confused with demand, use is the

rea Lz ol .. .' ,.-', I :;:>,,,ply consilerations.

% AV
Willingness to Pay: a concept of the willingness of users to pay for each

increment of output provided. For recreation output, willingness to pay is

the concept of payment by participants specifically for the use of a site or

an area. Recreational willingness to pay includes entry and use fees actually

paid and also an estimate of the Maximum amount in excess of these charges

that users could be induced to pay. It is not appropriate to include payment

for equipment, food, travel, or lodging that may be made in conjunction with

the recreation experience since these payments represent the opportunity costs

of the items purchased. Net willingness to pay is represented as the area

under the demand curve between the old and new supply and is conceptually the

increase in consumers' surplus.

A-3
I

V -- 5M T. T W V

.- S

.4

'+,"APPNDIX B: SOURCES FOiR DATA AND INFORMATION

.............................................-.. ..

. . . .. . . . . . ! . . . . . . . . . . .
APPENDIX B: SOURCES FOR DATA AID INFOR1ATION

Sorces of Data

i' 1 Sources of data and other support for use estimation and evaluation

purposes are many and varied. The following table outlines the sources of

some significant data and other support material for the various methods

according to a functional breakdown.

Function Data Services

1. Needs determination

a. Local per capita partici- State Comprehensive Outdoor Recreapation rates tion Plans (SCORPS)

Market area survey

b. Regional and national partic- SCORPS

ipation rates and outdoor National ?ark Service (NPS) - National

Recreation Survey data*

recreational trends US Fish and Wildlife Service (FWS) -

National Survey of Fishing and

and Hunting data

National Marine Fisheries Service

(NMFS) - NMFS National Salt Water

Angling Survey data

C. Market area population pro- OBERS or supportable alternative

jections Level A and B planning reports

d. Recreation supply, demand and SCORPS

needs Level A and B planning reports

Local outdoor recreation plans

2. Determination of least cost

alternatives

a. Unused capacity Physical inventory of existing

recreation areas and facilities

in influence area

Local outdoor recreation plans

SCORPS

Project development and operation

plans

Project master plans

Former Heritage Conservation and Recreation Service re:pons1ltly for

National Recreation Surveys has oeen assigned to NPS.

B-i
b Cost data SCORPS

Local outdoor recreation plans

Federal agency cost criteria .-

3. Use estimation

a. Without-project use estima- SCORPS

tion Population trends (OBERS or

alternative)

Outdoor recreation trends - NPS,

FWS, NMFS

Survey and appraisal of resources

and sites in influence area

b. Availability of regional Literature search

estimators Requests for proposals and requests

") , for quotations

c. Similar project method

(1) Visitation data Historical use statistics

(2) Origin of visitors Visitor surveys

Registration (e.g. campground receipt)

forms

(3) Project characteristics Physical inventory and description

through on-site survey

(4) Market area characteristics Market area analysis

Census data, OBERS

(5) Availability of substi- Inventory and appraisal of existing

tutes recreation areas and facilities in

influence areas

S CORPS

(6) Distance from point of Map measure

origin of visitors to

recreation areas

d. Capacity method

(1) Needs determination See main heading above

- (2) Resource requirements Agency planning and design criteria

(e.g., land/',ater Visitor surveys

ratios)

(3) Site development Agency planning and design criteristandards Visitor surveys

- -. -

B-2

"A " ""
(4) Facility standards Agency planning and design criteria

Visitor surveys

4. Evaluation

a. Travel cost method

(1) Stage 1 site demand curve Per capita use curves (see regional

estimator and similar project

method above)

(2) Value of time Minimum wage or supportable

alternative

(3) Variable costs of travel Department of Transportation data

(4) Entrance fees and user Market area survey and agency

charges operating policies and fee

schedules

b. Contingent valuation method Literature search

and VEM development Requests for proposals and requests

for quotations

c. Unit day comparable market

price method

(1) Existing price schedules Survey of influence area

(2) Project impact on existing Survey of existing supply in influence

supply area

d. Unit day general national

estimate method

(1) Categorization of recrea- Historical use statistics

tion activity Project development and master plans

(2) Recreation experience Project development and master plans

(3) Availability of opportunity Physical survey of influence area,

SCORPS and local recreation plans

Level A and B planning reports

(4) Carrying capacity Agency recreation plans

(5) Accessibility Agency recreation plans

(6) Environmental quality Agency recreation plans and resource

inventory

B-3

:, ." 3,,]' w ' ..''£',S L - L .:., '. -...-. , .. L-"-"""-""""".r'- -" , t. , . '-'-"
4 Data Bases

There are a number of data bases that contain project-specific

information on actual recreation use and/or facilities. Among the more

prominent of these are:

1. Recreation Information System (RIM).

U.S. Forest Service, Washington, DC

Content: Information, over time, on the facilities, description,

and use of all recreation areas in the Forest Service.

Output: The principal reports are annual reports on recreation use

by location and type, directory of recreation facilities, and

annual plans for construction and maintenance.

2. Recreation Survey Processing System.

Tennessee Valley Authority

Content: Information on activities and facilities use at selected

TVA Public Use Areas for use in recreation planning and budgeting.

Data collected includes number of visits, hours of use by activity,

and type of facilities used. There are about 3,000 observations

per year.

Output: Recreation visitation at selected TVA public use areas.

3. Annual Recreation Development and Use Survey.

Tennessee Valley Authority

Content: Information on the specific type and value of facilities

provided at individual recreation sites throughout the TVA

reservoir system.

Output: Survey of total recreation facilities and visits to

reservoirs, value of recreation facilities, and estimates of

man-hours of recreation employment.

4. Recreation Resource Management System.

U.S. Army Corps of Engineers, Office, Chief of Engineers

Content: Corps-wide recreation data on projects having an annual

visitation of at least 5000 recreation days of use. The system

contains variables such as monthly visitation, percent use by

activity, number of concessions, and length of trails for over 450

projects.

Output: Project data by year, trends are not reported or analyzed.

S urces of Information

The literature provides an extensive body of existing written information

on recreation econonucs. Examples of journals that are excellent sources for

literature on this subject: (1) Journal of Land Economics; (2) Journal of

Environmental Economics and Management; (3) American Journal of Agricultural

Economics; (4) Journal of Leisure Research; and (5) Leisure Sciences. These

B-4
journals should be consulted in order to keep up with concepts, developments,

and technique applications.

Knowledgeable persons are another excellent source of information and an

invaluable aid in supplementing and elucidating the literature. Many of these

people are in universities, but resource agencies are also good locations.

Finally, a source of information that would be useful for anyone

preparing to undertake a survey, is a book by Don Dillman. The full citation

for this reference is:

Dillman, Don A. 1978. Mail and telephone surveys: the total design

method. Wiley Interscience. New York.

This book is a catalog of response surveys and an aid in what to include as

well as avoid in developing and conducting a survey.

There are also two other books that should be mentioned as being useful

to questionnaire preparation:

Stouffer, S.A. et. al. 1950. Measurement and prediction. Princeton

University Press. Princeton, N.J.

Shaw, M.E. and J.M. Wright, 1967. Scales for measurement of attitudes.

McGraw-Hill, N.Y.

8-5
4

-,.

-. /APPUNDII C: USE ESTIMATIOU NODEL INC

p

",t

,.1 J

1
APPENDIX C: USE ESTIMATION MODELING

Formmlating a Regional Nodel

Basically, the development of a regional model involves the determination

of what factors influence recreation use and how they are related. Data are

needed on each of the factors to be considered and on the observations of use

associated with some range of variations in each factor. This is necessary in

order to determine if differences in the magnitude or quantity of the

variables have any effect on use rates and what this impact might be. For

example, the effect of distance on use can be seen only by observing the

visitation from population centers of varying distances form the recreation

resource. If all users were an equal distance from the resource it would be

impossible to estimate what visitation might be expected at any other

distance.

Estimates of use at a proposed new recreation area can be derived from

empirical estimates of the relationship between observed use at existing areas

and the influencing factors. This relationship, which is to be empirically

calibrated, can be put in terms of an expression or model such as the

following:

Vij = f(D ij Pi' Elt A., Sij)

Here the independent variable V.. may be visitation from a population source i

to a recreation site destination3J., where the total visits to the sites are

broken down by the origins (usually place of residence) of the visitors to

each. The V.. can then be related to such variables as the size of the

population in origin area i (Pi), socioeconomic characteristics of origin i

(E.), size, attractiveness or other characteristics of the resource I (A.),

ans a measure of the substitute recreation opportunities to site j availible

to potential users in origin i (S ). Parameters can be estimated for such an

expression using visitation data h4om existing recreation areas usually by

using fairly straightforward statistical techniques but with appropriate care

being given to complying with the as3umptions of the methods. The expression

can then be used to estimate visitation to other areas. Estimates of how the

attendance at these sites or another site may be expected to change over time.

given changes in population characteristics and in supply configurations in

the region, can also be made.

Any number of factors might be considered if there is some plausible

basis for inclusion. This last qualification forestalls inclusion of spurioi.Z

correlations that have no causal connections to the relations at hand but thal.

by chance or by some unrelated reasons just happen to be correlated. Their

inclusion would obscure the effects of the more relevant variables and cou'J

lead estimates far astray. Table C-i provides a list of some factors known to

influence recreational use.

The procedures required to develop a regional use estimation model are

exemplified in work conducted by Brown and Hansen (Vols. III and V, 1974) ,o

develop models for the Sacramento Region and the Southwestern Region. As

C-1

, * " ., *, .. , . . -,F -, ,r ". •
Table C- 1

Factors Related to Recreation Use

(From Clawson and Knetsch, 1969)

1. Factors relating to the potential recreation users, as individuals:

a. their total number in the surrounding tributary area.

b. their geographic distribution within this tributary area - how many

are relatively near, how many are relatively far, etc.

c. their socioeconomic characteristics, such as age, sex, occupation,

family size and composition, educational status and race.

d. their average incomes, and the distribution of income among

individuals.

e. their average leisure and the time distribution of that leisure.

f. their specific education, their past experiences, and present

knowledge relating to outdoor recreation.

g. their tastes for outdoor recreation.

2. Factors relating to the recreation area itself:

a. its innate attractiveness, as judged by the average user.

b. the intensity and character of its management as a recreation area.

c. the availability of alternative recreation sites and the degree to

which they are substitutes for the area under study.

d. the capacity of the area to accommodate recreationists.

e. climatic and weather characteristics of the area, the latter during

the period under study.

3. Relationship between potential users and the recreation area

a. the time required to travel from home to the area, and return.

b. the comfort or discomfort of the travel.

c. the monetary costs involved in a recreation visit to the area.

d. the extent to which demand has been stimulated by advertising.

C-2
accomplished in that study, the major components of regional model development

are: visitor surveys, factors relating to use, and development of the use

estimator equation.

Visitor Surveys

Model development is based on recreation use data. Brown et al. (1974)

is an example of a source on usage. It provides data for 52 reservoir

projects in seven Corps districts during a four-year period, 1966 through

1969. The method of collection serves as a guide to collecting data if a

previously compiled database is not to be used. The visitor surveys were

conducted on a sample basis in which recreational users were interviewed at

the site and questioned on activity participation, trip origins, and the

number of persons in the party. The data were collected from both day users

and overnight visitors. A detailed discussion and evaluation of tne survey

procedures are provided in Crane et al. (1974).*

The origins of the visitors were classified into area groupings based

primarily on county or county census division. Although this scheme is

somewhat arbitrary, the origin designations matter little, and using census

boundaries offers greater convenience for compiling data on population

characteristics. Some earlier analyses have used concentric rings around

sites as the units of observation. The county units, however, introduce more

variation in the data, allowing more meaningful, locationally specific

variables to be measured.

As distance from the reservoir increased, the size of the areal unit of

resident populations was also allowed to increase; that is, for areas close to

each site a single county or part of a county was used as an observation, but,

for areas further removed, the counties were grouped together. The number of

areal units taken as being the points of origin or observations for each lake

varied.

Factors Related to Use

The main intent of the analysis is to quantify the relationship between

the number of visitors going to each of the surveyed lakes from each of the

origin areas and those factors responsible for the observed differences. A

number of independent variables are used in an attempt to explain the

variation in the observed visit numbers from each origin to each lake. For

example, for their Sacramento Region model, Brown and Hansen (Vol. V, 1974)

used four variables which, although they did not offer a complete explanation

of visitor behavior, yielded a reasonable formulation with considerable

predictive ability for the type of recreationist involved. The four variables

were:

D Road mileage. The first and most important variable was the road

mileage form the areal unit of origin to the lake. For purposes of

measurement, the origin was taken to be the population centroid of

the area.

*Improvements to these procedures have been developed through research

conducted within the Corps Natural Resources Research Program 1y the USAE

Waterways Experiment Station.

C-3

§Z T6zr"
P = Population of the areal unit. Simple population totals were used

with the expectation that more use would originate from areas

having a greater population, all else being equal.

A = Size of average recreation pool . A size indicator was deemed

necessary to account for the increased capacity of the different

lakes. This measure of attractiveness of a recreational site is

crude, but for this type of area it sufficed. Several alternative

I 'size or capacity variables were included, but water surface area at

average recreation pool provided to be as good as others in this

case. For other areas and for different comparisons, some further

definition of attraction might be more useful. It should be notea,

that with increasingly refined inventory or site information, it

would be expected that increasingly fine distinctions could be made

in user response.

5 Index of substitute recreation opportunities. This index was included to account for the substitute recreational opportunities

of a similar nature available to residents of different origin

areas. It would be expected that if readily available substitute

areas were accessible, than fewer visitors would be expected to

make the trip to a lake in question. This index took into account

other lakes and reservoirs, the value being larger as the number,

size, and proximity of the lakes available to a population

increased.

Use Estimator Equation

With these four variables, an equation was derived by multiple regressionW

methods on the basis of the observed visit patterns. After several

alternatives were tried, the equation finally used for the Sacramento Region

was as follows:

V. = -4577 - 2.52(Pi/D ij) + 0.0013(A.Pi/D ij) + 27(Pi/D ijSij)

which, after rearranging terms, can be written as:

Vij = -4577 + (Pi/Dij) (-2.52 + O.0013A. + 27/Sij)

Where V is the annual number of recreation visits form area of origin i to

lake 1, is the population of areal unit i, D.. is the road mile distance

between tAe area of origin i and the lake , A.1is the average recreational

pool size of lake 1, and S . is the index of sdbstitute lakes available to area i for lake . 13

For the Sacramento Region, statistical results of the analysis indicate

that all coefficients are significant at the one percent level, and the

equation explained approximately 92 percent of the variation in visitation

among the observations. In other words, all but eight percent of the

variation in the indivilual visitation totals among the 168 observations are

explained ny this equation.

C-4

14~**u -
Test of Predictive Capability

The prediction capability for the individual observations (i.e., the V..)

is the primary test of how well it can be expected to predict for a new lake.

Although the main point is to determine more general effects that would have

the most validity for prediction purposes, it is also instructive to compare

the total number of visitors to the individual lakes in the original sample

with the predicted totals, which are simply the V.j sumuned over all areas or

origin for each single lake.

Actual and Predicted Day Use Visitation to Seven California Lakes

Visitation Estimated Predicted

Lake From Survey Visitation

Isabella 845 839

Pine Flat 493 612

Success 481 430

Kaweah 289 236

New Hogan 243 272

Black Butte 161 16L4

Engelbright 109 57

As indicated above, the regional model provides a fairly accurate

prediction of the annual day use visitation for each of the seven lake

projects in this sample. It seems reasonable therefore that the equation

could be used with considerable confidence to predict visitation at a new or

proposed lake in the region.

Data requirements

Development of regional use estimation models requires that data from

existing areas be systematically collected. The major requirement is that the

data on the use and the users of a range of types and locations of facilitiesspan the types and locations of those proposed areas for which estimates are

to be made. A series of surveys at existing sites can provide such basic dat-,

which would normally include total use, timing and patterns of use, the

characteristics of the users, and their areas of origin.

Methods of data collection that have proven fairly satisfactory involve a

very short handout questionnaire or interviews of a small sample of randomly

selected users of the different recreation areas. It is important that fairly

reliable total visit statistics be obtained for each existing area

investigated. This can usually be done satisfactorily with judicious use Of

traffic counters at most water-based recreation areas. If totals are

collected throughout the season, samples for questionnaires or interviews need

be drawn only on a few days, on both weekends and weekdays, as patterns are

likely to vary greatly between them.

C-5
a

The questions 3sied may be similarly limited. The major concerns are the

origin and purpose of tne trip and limited information about the party. A

representative range of areas, facilities, and locational proximities should .-

be covered in such surveys. Fully adequate methods are available that are

relatively inexpensive, entail a minimum of difficulty at the site and to the

user, and yield meaningful results (Mischon and Wyatt, 1978). Many such

surveys are currently being conducted at Corps lake projects as part of their

visitation reporting requirements (Engineer Regulation 1130-2-430).

ApplyiNg an Existing Regional Model

If an existing model is to be applied, the steps for its implementation

are fairly straigntforw3rd:

1. Determine the market area for the proposed project. This is the

area from which project users may be exoected to originate. If the

market area is divided according to census boundaries (e.g.

counties), it will be easier to compile demographic data for use in

subsequent steps.

2. Collect data for each of the variables in the regional model use

equation for each origin area and for each year for which a use

estimate is to be calculated.

3. Calculate use from each origin area for each year.

4. Aggregate use from each area to get the estimated annual use.

Application of the previously described Brown and Hansen (1974, Vol. V)

regional model to a given year of estimate, involves the following steps which

are briefly described here, Although the general procedures would be similar

for other applications, specifics (e.g., definition of area of origin and

variables included) would differ with each application.

Step 1. Delimit the areaj of origin for the proposed project

As an areal unit, thp county is an efficient and convenient basis for

data processing. However, because of shape irregularities, it may be ,x.re

useful to cluster counties in sets for defining the areas of origin. 1) t-i

concept, counties are divided in County Census Divisions (CCD) and ther

clustered to form more meaningful observation units.

To delimit the sets about a proposed project, first locate the project on

a map containing CCD boundaries (available from the U.S. Bureau of Census) arid

sketch on the approximate 50, 150, and 250 road mile boundaries. Next, adjust

the zonal boundaries to coincide with county or CCD boundaries. If a zonal

boundary intersects a county such that a significant portion of its population

lies in more than one zore, the zonal boundary should be adjusted to follow

the approprizjte CCD bounAliries. However, if 3 majority of the population life

within )ne zone, the zorn;i boundary shouli coincide with the county bounda-y

so that the entire .,ourt- lies within the appropriate zone.

C-6
The three zones are next divided into the appropriate number of county

sets. The first zone should contain approximately four county sets anc .e

remaining two zones approximately ten each. The sets are formed by grouping

contiguous counties or subcounties which have similar characteristics, while

keeping in mind the approximate number of sets desired within each zone. The

delineation of county sets is somewhat arbitrary and different planners would

probably not construct the sets exactly the same. However, if the general

guidelines are followed, the final use estimates should be very similar even

with different set descriptions.

Step 2. Compute the measures of the variables included in the model for each

area of origin for the year of estimates

The measures of the factors affecting use are first derived for the

individual counties and subcounties within the general market area in the

following manner:

Population: for counties - the projected county population for the

year of the estimate; for subcounties - the proportion

of the county population residing in the subcounty

during the most recent census times the projected

county population for the year of the estimate.

Distance: the road mileage between the largest city in the county

or subcounty and the nearest access at the project.

Project Size: average recreational pool size in acres.

Alternative Index: the alternative index is computed for each area of

origin and is estimated by the following:

(1 + k)2 for all

k= Idij

In ak > in a1

dik dij

where the subscripts i, J, and k are for the areas ot

origin, the proposed project and the substitute

facilities; a is measured by the water surface acres

at gross pool; and d is again the road mileage from

the largest city in area i to the nearest access at

lakes I or k.

The county set measures are then derived from the county data in the followin ,

manner:

C-7
Population: simple sum of the projected populations of all counties

and subcounties within the set.

Distance: population weighted average of the distance of the

counties and subcounties within the set.

Project Size: average recreational pool size.

Alternative Index: mean of the alternative indices of all counties and

subcounties within the set.

For project planning purposes one annual estimate of recreation use is

usually made for each decade throughout the life of the project. County set

populations are projected for the year of each of these estimates, the

measures of the other factors can either remain constant or be adjusted to

account for anticipated changes in the highway network or in the availability

of substitute opportunities.

Step 3. Substitute the appropriate measures into the estimator equation

For each annual estimate the measures of the factors affecting use

associated with each area of origin are substituted into the estimator

equation and the results summed over all areas of origin.

Step 4. Adjust the result to account for camping use and for any unique

characteristics of the project or its market area not accounted for by the estimation

Some adjustments may need to be made to the use estimates derived form

the estimator. One would be to account for measures of variables for the

proposed project that may be outside the range of those from which the model

was developed. For example, assume the proposed average recreation pool size

of a project being evaluated was larger than any of the pool sizes of the

projects from which the regional model was developed. To assist in adjusting

the initial use projections, the estimates are recomputed with all measures

the same except that the average recreation pool is assumed to be the size of

the largest lake used in building the model. The expected day use for the

proposed project should then be between the estimates calculated for the size

of the proposed project and the size of the largest project in the model.

Using these two estimates as guides, a final estimate is made of the day use

expected at the proposed lake.

Another adjustment that may be needed is to account for use not

considered by the model. The Sacramento regional model was for day use only

and an adjustment to account for camping is required. To illustrate this,

assume for example that camping use is estimated to be equal to 10 percent of

total use, as derived from comparison of survey data from existing lakes. The

day use estimate would then be divided by .90 to obtain the final, total use

estimate for the year of estimate.

C-8

[ - AI.- . . ,TS
APPENDIX D: S ILAR PROJECT APPROACH FOR USE ESTIMATION

.1

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APPENDIX D: SIMILAR PROJECT APPROACH FOR USE ESTIMATION

Similar Project Approach

This approach is based on the concept that recreation Jemand for a

proposed project can be estimated from observations of visitation patterns at

one or more existing projects that have similar resources, operation, and

anticipated recreation-use characteristics. One variation of the methodology

uses a per capita use curve or function from one or more existing projects

with similar resource, operation, and user characteristics as those for the

proposed project for which estimates are to be made. One inventory of such

curves and associated data for 52 lake projects is contained in Brown, et al.

(1974). That report also gives a detailed discussion of how to utilize the

similar project approach for estimating use at proposed lake projects. The

procedures described in that study are also applicable to non-lake projects as

long as appropriate per capita curves from similar, existing non-lake projects

are first developed.

An overview of the methodology adapted from Brown, et al. (1974) is

provided below. As described, the methodology assumes per capita use curves

are either available only for day use recreation or can be constructed;

guidance is provided to adjust for camping use. If per capita use curves are

subsequently developed for camping use, estimates of such use could be derived

directly form the curves using the same general procedures.

The similar project prediction method is' comprised of the following

eleven steps.

Step 1: Evaluate Characteristics of Proposed Project

The characteristics to be considered in evaluating a proposed project art

summarized in Table D-1. If needed, a complete description is given in Brown,

et al. (1974). Information is gathered on these characteristics and, where

necessary, evaluations made (e.g. quality of access routes) so that

comparisons can be made with like data from the inventory of similar projtec%.

Step 2. Select similar project(s)

An existing similar project or projects should be selected by comparison

*' of the project characteristics. When possible, consideration should be given

to selecting a similar reservoir near the site of the proposed reservoir.

After selection of the similar project(s), evaluation of the day-use market

area conditions may provide further information which will modify this

selection (Step 5). The planner should be alert to unusual socioeconomic

characteristics on a broad scale, (e.g., a large area oredominantly composed

of retirement communities). Another important consideration is alternative

water-oriented recreation opportunities. Information about alternative

opportunities such as the latest attendance estimates, attendance trends,

kinds of recreation facilities, expected development level, and degree of

saturation should be obtained for proper evaluation.

D- 1
Table !D-1

Sugary of Characteristics to Consider in

Evaluating a Proposed Project and in

Selecting a Similar Project

Characteristic Considerations

Reservoir Area Reservoir Size: Surface area of average

recreational pool

Miles of recreation shore

Reservoir Basin Topography: Land area and

gradient

Accessibility Existing Roads

Planned Improvements to Existing Roads

Planned Addition of New Roads

Number of Major Access Routes

Quality of Access Route

Number of Access Points

Length of Shoreline Accessible by Auto

Reservoir Fluctuations Seasonal and Annual Drawdown (extent, frequency,

duration)

Bank Slope

Alternative Recreation Water-oriented Outdoor Recreation. Available to

Opportunities Market Area Population

Number of Opportunities

User Capacity

Quality of Recreation Experience

Relative Price of the Recreation Experience

Recreation Facilities Investment, Campsites, Boat-launching ramps, etc.

Activity Limitation County and State laws or regulations

Water Temperature

Water Quality

Forest Fire Hazard

Size of Project

Weather Conditions (e.g., length of season)

Activity Potential Reservoir Area Quality

Utility of Water for Specific Activities

Fishing Potential

D-2
The initial selection of a similar project from which to obtain per

capita use rates should be based on approximate reservoir size in terms of the

surface area of the average recreation pool. In general, the reservoir most

similar in physical characteristics and water-oriented competition should

serve as the similar reservoir. If the planner has difficulty in obtaining a

similar project based on comparison of average recreation pools, the next

smaller and next larger projects should be examined. In the absence of a

single most similar project, it may be desirable to use the characteristics

and data from two or more similar projects.

Step 3. Evaluate similar project(s) day use market area

The day use market area is considered to be the area from which some

specified percentage of the annual day use visitation is drawn. The extent of

this area is dependent upon what percentage of annual day use is used and the

arrangement of major and secondary access routes with respect to the

project(s). Road mile distance zones are determined and a per capita

visitation rate by distance zone is calculated. The day use market area

corresponds to the zone at which the desired percent level is reached or

exceeded.

Step 4. Select (or construct) a per capita use curve for similar projects(s.,

Per capita use curves for 52 reservoirs in seven districts are contained

in Brown, et al. (1974). Guidance on the selection of a curve from among the

52 is also included in that report.

If the similar project(s), is not among the 52 for which per capita use

curves have been developed, then a curve will need to be constructed. The

process for curve construction is as follows:

a. The day use market area is divided into distance zones (e.g., the

first 50 miles from the project might be divided into zones of O0

miles width, while the remainder of distance out to the outer

boundary of the market area might be divided into zones of 25 miles

width). The zone widths are measured in road miles determined by

measuring the road mile distance along major and secondary access

routes from the visitor's origin to the reservoir.

b. An estimate of the population within each zone is made.

c. An estimate of the aggregate annual recreation day use of the

project by each zone is made.

d. A zonal per capita use rate is calculated for each zone by dividing

the annual use by the population. This yields an estimate of the

number of visits to the project for each person in a particular

zone in one year.

e. A per capita use curve is obtained by plotting the zonai per capit.

use rates against zonal distance from the project.

D-3
Step dissimilarities 5. Modify the between similar the project(s) per capita use curve to reflect the similar project(s) and the proposed project

The recreation use data from the similar project(s) is used to adjust the

similar project per capita rates to more nearly fit the prospective project.

The difference among the per capita rates of day use for various projects may

be associated with differences in either project or population variables.

Under ideal condit.ons, when the proposed and similar project are alike, no

adjustment would be required. However, it is more likely that dissimilarities

will exist, and if they do, they will have an effect upon the magnitude and

the slope of the per capita curve. The variables given in Table D-1 should be

examined carefully for differences between the similar project and the project

under study. Adjustment in per capita rates should be based upon differences

in these variables. However, it should be noted that extremes in any of the

variables (e.g., polluted water unfit for contact) may affect recreation use

out of proportion of their normal influence.

Step 6. Determine project market area population for initial year of

operation

The day-use market area for a proposed reservoir project under study is

established using the existing market area of the similar project with

appropriate adjustment by the planner based on experience and personal

knowledge of the area. The market area of the proposed project need not have

a minimum 50 mile radius; the area can and often will be smaller or

considerably larger depending on the location of the major using population.

If, when establishing the counties to include in the market area, there is

some doubt as to where the boundary should be drawn, the general criteria for

selection is inclusion of those counties which have approximately one-half of

their population and/or land area within the tentative day-use market area

boundary.

Step 7. Derive the per capita use rate for counties in the proposed project's

market area

For each county from Step 6:

a. measure the mile distance form the proposed project to the center

of the most populated city within the county. (The most populated

city serves as a proxy for the centroid of county population).

b. using the modified per capita use curve obtained in Step 5, read

off the rate associated with the mile distance measured for the

county. This is the per capita use rate for that county.

Step 8. Calculate the aiinual day use from each county

-1 This is done by mul-,iplying the county population (Step 6) by the derived

use rate (Step 7).

D- 4

A ll--
County

Annual I County x County per capita I

Day Use Population use rate

Step 9. Calculate annual day use for the project

This is done by summing annual day use calculated for each county in

Step 8.

Step 10. Calculate total initial annual use for the proposed project

If recreation at the proposed project is to consist only of day use

activities, then the annual day use estimate calculated in Step 9 is taken as

the total initial annual use estimate.

If recreation at the proposed project is to include camping, then the

estimate derived in Step 9, is only a portion of the total use,

Total Use : Percent Use + Percent Use:

(100%) Day Activities Camping

and the portions of the total use that are expected to be given to camping and

day, use must be determined before an estimate of total initial use can be

made.

a. Determine the percent of use given to camping at the similar

project and use this as the percent of use given to camping at the

proposed project.

b. Figure the estimated total initial use at the proposed project as:*

Total Initial 1 Total Day + 1.00 - % camping 1

Use : Use (Step 9) : 100

A similar adjustment would be made to the initial day use estimate if the

market area boundary was defined to include the origins of less than 100

percent of the potential day users. This adjustment would be made before the

adjustment for camping use.

D-5
APPENIDX E: CAPACITY APPROACH FOR USE ESTIMATION

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APPENDIX E: CAPACITY APPROACH FOR USE ESTIMATION

Capacity Method

In order to apply the Capacity Method, it is first necessary to

demonstrate that there is an unquestionable need for recreation in the market

area. In some cases this may be obvious before conducting a needs

assessment. In other cases, a need for recreation may not be clearly

recognized until completion of Step 4 ("Determine the Without Project

Condition") of the planning framework.

There are essentially two steps in the capacity method:

Step 1. Calculate the project recreation design load.

With the capacity method the design day load is defined as the number of

visitors that could be supported by specified resources or facilities on the

design day. It is a function of the instantaneous capacity of a unit of the

facility or resource, its daily turnover rate (i.e. how often it would be used

by different visitors or groups of visitors) and the number of units being

considered. Information on capacities and turnover rates are available from

site development and facility standards which are part of agency planning and

design criteria and from previous recreation surveys from similar projects

that account for daily use patterns.

Design Instantaneous Daily Number

Day Capacity x Turnover x Units

Load per Unit Rate

Step 2. Convert design day load to estimated annual use.

The design day is usually considered an average weekend day during the

peak season of use for the particular facility or resource being considered.

The design day load can, therefore, be converted to an annual use estimate by

accounting for the number of weekend (usually including holiday) days during

the peak season, the proportion of peak season use expected on weekend days,

and the proportion of annual use expected during the peak season. Information

on peak season use patterns can be obtained from previous visitor surveys from

similar projects or from agency planning and design standards.

Design Average Number Proportion Peak Proportion Annual

Use Day x Weekend Days + Season Use + Use Expected

Load in Peak Season Expected on During Peak Season

Weekend

E-1
APPENDIX F: VALUATING USE WITH TRAVEL COST METHOD

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APPENDIX F: VALUATING USE WITH TRAVEL COST METHOD

Travel Cost

The basic premise of the travel cost method is that per capita use of a

recreation site will decrease as the out-of-pocket and time costs of traveling

from place of origin to the site increase, other things being equal.

Application of the travel cost method to estimate value requires that an

estimate of use has been made, with a gravity or similar type model that

includes distance or travel cost as an explanatory variable. With this

information, the method enables an estimation of: (a) expected use, (b) a

demand function for recreation at the site, and (c) the NED recreation

benefits of the site. The travel cost method essentially consists of three

steps:

1. estimating use

2. deriving a demand curve

3. computing benefits

Estimating Use

As noted in Chapter III, there are two methods that are appropriate for

providing a gravity type use estimator for employment in the travel cost

method: either a Use Estimating Model or the Similar Project Approach. Since

O the travel cost method builds directly on gravity type use estimation models,

they are the preferred means for estimating use. Appendicies C and D provide

details on procedures for implementing both of these use estimation

techniques, this appendix presents a brief statement on their make-up.

A use estimation model applies a use estimating equation that is derived

from observations of use patterns at existing projects and that serves to

relate use at a proposed site to distance traveled, socioeconomic factors, the

characteristics of the site, and alternative recreation opportunities. Use

estimating equations have a firm empirical base because they are based on

actual use patterns observed at existing recreational facilities. Because

they explicitly incorporate the important factors that influence use, they are

statistically more accurate than other use estimating techniques. Since a use

equation is based on data collected at existing sites, it is assumed that tkie

proposed project will offer similar recreation opportunities and will be

operated under similar management practices as those at the existing sites.

Major differences will be accounted for by the quality variables in the use

equation, but the planner may have to make some adjustments to allow for

characteristics that are unique to the project under study. Such adjustments

must, of course, be justified.

The objective of the similar project approach is to obtain as close a

match as possible with respect to location, type, size and quality of project

and user characteristics between a proposed project and an existing project

for which a gravity type use estimator has been derived. The level of

professional judgement required for this use estimation method can be

substantial because it is necessary for the selection of a similar project as

well as for the modification of existing use estimators to reflect

dissimilarities between the "similar" and the proposed projects.

F-i
py , yy

Deriving a Demand Curve

The travel cost method assumes that increasing the distance from areas of

origin to the site is equivalent to increasing the cost or price of recreation

at the site. The procedure consists of calculating total use at different

incremental distances (prices). The process is based entirely on the use

estimator. The result is a demand curve for the site being evaluated that

relates "prices" to total visits. Distances are converted to dollar values

using per mile conversion factors reflecting both time and out-of-pocket .-travel costs. The area under the demand curve plus any user charges or 9, entrance fees measures the recreation benefits attributable to the site. The

general procedures for applying the travel cost method are provided in the following paragraphs. More detailed guidance, including illustrative

examples, is provided in Appendix G.

The estimate of recreation use for a project derived from application of a

per capita use curve or regional estimator yields an initial point on a

resource's demand curve. This point is the quantity of use that would be

demanded considering all costs that would be incurred by the users to

participate including user charges or entrance fees (if any). This point is

defined as the zero price point for the purpose of deriving the users'

consumer surplus or the amount they would be willing to pay but do not have to

pay to utilize the resource. (As discussed in Chapter II, entrance fees and

user charges are a part of project benefits although they are not a part of

the user's consumers surplus.)

To find sufficient points to determine the entire demand curve, it is

'A-. necessary to make incremental changes in the price of recreation and to

measure the quantity of use that would be demanded given these changes.

Unfortunately, it would be impractical to actually make incremental increases

in fees at the projects and to then observe the changes in use that occur.

However, the results can be approximated with the use of a gravity type use

estimator and a proxy for price.

With the travel cost method, the use estimator includes measures of the

distance between the project and areas of origin as one of the independent

variables influencing use. After the initial (zero price) use estimate is

made, increments are adced to the distance measurement between the project end

each area of origin. The increments are equivalent to moving the project

further and further from the users, requiring them to pay more and more in

travel time and travel costs to reach the project.

As distance is increased, use decreases, and for each increment in

distance a new use estimate is computed with the use estimator. The new use

estimates are the various quantities of recreation that would be demanded at

increasing prices. To determine the price at which these quantities are

demanded, it is only necessary to convert the incremental increases in

distance to the costs (both travel and time), that would be incurred by the

recreationists if they were required to travel the additional mileage.

F-2
Proxy for Price

Variable or out-of-pocket costs per mile to operate an automobile are used

for the travel cost portions of the proxy for price. Out-of-pocket costs are

used since these are the costs potential users would be most cognizant of when

making a decision whether or not to visit a particular resource area. Such

fixed costs as depreciation, insurance and registration should not be included

since they would generally not affect the potential users decision as to

whether or not to travel the additional mileage for recreation purposes.

The conversion of mileage to price is readily accomplished by the use of

published results from studies conducted periodically by the U.S. Department

of Transportation, concerning the average cost of operating an automobile.

Current data on average operating costs are available from the U.S. Department

of Transportation.

Some adjustments may be required, however, before these costs can be used

as the proxy for price. First is an adjustment for round trip mileage. If

the distance measure used in the per capita use curve or regional estimator is

the one-way mileage between the project and the areas of origin, then the

costs should be doubled to account for the recreation user incurring the

variable costs while traveling to and from the project. In addition, since

more than one user may arrive in each vehicle, a second adjustment may be

needed to distribute the travel costs of the trip between the number of users

within each vehicle. This can be readily accomplished by the use of the

average number of users per vehicle determined from the data from the survey

of existing sites that was used to develop the per capita use curve or

regional estimator.

An Adjustment for the Disutility of Time. The use of just the variable

travel costs in the development of the demand schedules ignores the disutility

of time which is an important consideration to the recreationist in overcoming

distance. When time is ignored the demand schedules are constructed under the

hypothesis that increasing distance decreases use only because there is then a

higher money cost. However, the additional time required to travel the

increased distance would seem to be an equal or greater deterrent to the

recreationist than the out-of-pocket money costs. The exclusion of the time

factor introduces a consistent bias in the derived demand schedule, shifting

it to the left of the true demand schedule and resulting in an underestimation

of the recreation benefits.

Unfortunately, there is normally a high correlation between travel cost

and travel time. People from more distant areas of origin generally must

spend more time as well as more money getting to a site than people who live

closer. It is, therefore, often not possible to estimate the separate effects

of the two variables in use estimation models. Ignoring the effect of time

during benefit evaluation, however, will result in a consistent bias, an

underestimation of the benefits.

One procedure which is often used to accommodate consideration for tne

disutility of time is to assume a known tradeoff between time and money. No

universally accepted formulation of this tradeoff has yet been established and

F-3
0

empirically tested. A linear tradeoff is most widely used and is recommended

until further research validates a more precise formulation.

A linear tradeoff between time and money assumes a constant opportunity

cost of travel time and implies a constant willingness to pay to avoid the

time required to travel to distant recreational sites. In a review of

empirical studies of the opportunity cost of travel time, Cesario (1976)*

found that the estimated value of nonwork travel time is between 1/4 to 1/2 of

the wage rate. Cesario and others have used 1/3 the average wage rate for the

opportunity cost per hour of travel time for adults and 1/12 the average wage

rate for the opportunity cost of travel time for children under the age of 12.

These values are suggested for use by P&G but other estimates of the value of

time can be used if supported by empirical evidence.

P&G also recommends that onsite time costs as well as travel time costs

should be included in the derivation of the total willingness to pay for

access to the site. As noted by Knetsch and Cesario (1976) and reiterated by

Mendelsohn and Brown (1983), the value of onsite time should not be included

unless it is reasonable to assume that the marginal utility of onsite

" activities is zero. These onsite costs are not related to the individual's

marginal cost of obtaining the site and, therefore, should not be included as

part of travel cost.

Computing Benefits

The final computational step in the travel ccst approach is to measure the

area under the demand curve. This area is equal to the amount users would be

willing to pay but do not nave to pay for the opportunity to participate in

recreation at the resource being evaluated. Computationally, this area is

approximated by multiplying the average use estimates associated with each

increment in price times the proxy (travel and time cost) for the price

increment and summing over all such increments, Any user charges or entrance

fees that nave been incur-ed by the user should be added to this value to

determine the gross value of the resource associated with the specified

management option.

As previously noted the travel cost approach can be used for evaluating

either the with or without project conditions as long as a gravity type use

estimator is available for estimating use under the specified condition. When

evaluating the without project condition the estimate is of the value of the

recreation that would be lost at a site if a water resource development

project is undertaken. If evaluating a with project alternative, the estimate

is of the value of the new recreation opportunities that would be created. If

a gravity use estimator is not available for evaluating either the without or

one of the with project conditions, then one of the techniques in other

portions of this manual should be utilized.

The procedure described above is applicable for any type of activity or

groups of activities for which use can be described by a gravity type

estimating model. The level of disaggregation of the estimator, for example

References are given in the bibliography and literature cited section

following the main text.

F-4

.. -tM ll l lll M~ll ~ll , lal'I~ k,,ll J: = + : -" .. .} 2 .. ''o" . , * ,. + , "-
i . . ' : - = . % -= V -- - OW - = . - ; . 'r 'T -. ;-, - U.

day use versus overnight use or sightseeing versus other day use activities,

is dependent upon the specificity of the survey data and the model

- formulation.

Documentation

In order to provide adequate information for updating or verifying the

computational process, it is important that adequate documentation be retained

of the data and model used. As a minimum such documentation should include:

(1) The per capita use curve or regional estimator utilized to estimate

use.

(2) Whether one-way or round trip mileage is used in the use estimator.

(3) Delineation of the areas of origin used in the analysis.

(4) Population projections, time periods and sources for such

projections used to estimate use.

(5) Variable travel costs and time period and source for such costs

used to estimate benefits.

(6) Proxy used for evaluating time.

,X.F

U-

/

F-5
APPENDIX G: EXAMPLE OF THE APPLICATION OF THE TRAVEL COST METHOD

- A 

.4.

hr .

,!4,

I 1 4 - - -
APPENDIX G: EIAUPLE OF THE APPLICATION OF THE

TRAVEL COST METHOD*

The purpose of this appendix is to illustrate by hypothetical example the

mechanics of the travel cost approach. It is not intended to be a detailed

primer on recreation use estimation or benefit valuation. If at times the

example seems overly simplistic, it is intentional. The objective is to

illustrate use of the travel cost approach without clouding the presentation

with other judgements and considerations (e.g., resource and social carrying

capacity, accounting for substitute sites) that must be made no matter what

benefit valuation approach is used. One advantage of the travel cost approach

is that many of these considerations can be incorporated into the valuation

process as familiarity is gained through application. Although the example is

presented in a simplified and hypothetical nature, much of the data originated

from a feasibility study prepared by the Buffalo District and an ongoing

Campground Receipt Study (Curtis et al. 1982) * being conducted by the U.S.

Army Engineer Waterways Experiment Station.

There are certain minimum types of information that are necessary to

perform the calculations that the travel cost approach requires. These types

of information and their most likely sources are presented in Table G-1. Tie

example illustrates how this information is used.

Travel Cost Example: Day Use

For this example assume we are trying to estimate the potential

recreation benefits for one alternative being considered during a feasibility

study. The alternative is a multipurpose reservoir (MR) that would provide

opportunities for both camping and day use activities.

As previously described in this report, the travel cost approach uses

observations of visitor responses to varying travel distances to estimate what

additional amounts (above the travel cost actually incurred) they would be

willing to pay to use an existing or proposed recreation resource. Therefore,

the first step is to determine whether or not an appropriate use estimation

model (or the data to develop such a model) is available from similar

projects. (For a more detailed discussion of the characteristics to consider

when selecting similar projects, see Brown et al. 1974, pp. 7-10.)

Although no model was available for the MR, an existing project, Good

Time Lake (GTL), is located in the same geographic region. GTL has similar

resource attributes (e.g., size) as would the MR, but does not have fee

camping areas. A local university conducted visitation and area of origin

surveys the previous year at GTL. These data combined with population

*Prepared by William Hansen and Dennis Propst, Environmental Laboratory, U.S.

Army Engineer Waterways Experiment Station, Vicksburg, Mississippi. Dr.

* •. Propst was assigned to WES at the time under terms of an Intergovernmental

Personnel Act Appointment with Shepards College, West Virginia.

**References are given in the bibliography and literature cited section

following the main text.

G-1
Table G-1 :

InfomritIo Needed in Travel Cost Approach

Information Needed Sources

(1) Population by distance zone 1980 U.S. Census data (available

from county planning offices,

regional planning agencies,

extension service of state land

grant universities, libraries,

4 etc.)

(2) Road mile distances State highway maps

(3) Project visitation (a) Day use - project surveys used

to update load factors; surveys

conducted by universities, state

agencies, etc.

Usually measured in units of

recreation days use. For day use

only, recreation days use = number

of visits. Thus, recreation days

use/capita visits/capita.

(b) Camping -project surveys used

to update load factors; surveys

conducted by universities, stage

agencies, etc.; campground fee H . receipts (see discussion in text).

Usually measured in units of

" recreation days use. For camping,

recreation days use =Visits X

length of stay. Thus, visits

recreation days use divided by

length of stay.

N (4) Variable motor vehicle costs U.S. Department of Transportation

(see Table G-5).

(5) Average weekly earnings 1980 U.S. Census data; State

Employment Offices; State,

regional, or local planning

offices.

IG-2
information and road mileages can be used to develop the necessary

use/distance relationships for using the travel cost approach to estimate day

use benefits at the MR; additional data sources will be needed to derive the

benefit estimates for camping.

Day Use Estimation for the Similar Project

To derive distance/use relationships for day use at GTL, we must first

determine the market area and then divide this area into zones of varying

distances. The market area will vary from project to project. One valid way

of determining the total market area is to look at the visitation patterns,

identified by visitor surveys. For example, data form the GTL visitation

surveys indicated that 100 percent of the 633,130 total day use visitors were

presently driving up to 125 miles to participate. The total market area was,

therefore, defined as all counties within 125 road miles of GTL. This market

area was divided into five 25-mile distance zones with use estimates by zone

derived from the visitor survey (Table G-2).

Table G-2:

Good Time Lake Distance Zones and Annual Use Estimates

Percent Distribution

Distance Zones (miles) Annual Day Use Visitors of Day Users

0-25 353,345 55.8

26-50 190,420 30.1

51-75 33,685 5.3

76-100 28,185 4.5

101-125 27,495 4.3

TOTAL 633,130 100.0

There is nothing sacred about the 125 mile cut-off or the 25 mile

increments. Under appropriate circumstances increments of 10 city blocks, 10

miles, or 25 miles may be appropriate. Rarely are the increments in excess of

50 miles, but this does not rule out the possibility of having 100 mile

increments, say, for very remote projects. Nor do the distance zones have to

be the same size throughout the market area (see Brown et al. (1974) for an

example). You could begin with relatively narrow zones near the project (10

miles each, say) and establish wider zones farther away (50 miles, say).

Next we must determine the population of each of the distance zones. The

most efficient manner for doing this is to obtain population figures for each

county in the market area and sum these figures according to the distance

zones in which they are located. The criterion for determining into which

distance zone the county falls is the road mileage along the most likely

traveled route between each county's population center (usually the largest

town or city) and the nearest recreation access area on the project. For

example, a county whose population center was located 53 miles from the

nearest recreation area on GTL would be included in the 51-75 mile zone for

data compilation purposes.

G-3

L M~~ &X&* 41 s IO'*'-6 
You do not have to compile population data on a county basis. Larger .IN

counties or counties with large populations in more than one zone, can be

subdivided by County Census Division (Brown and Hansen, Vol. III, 1974) or zip

code areas (U.S. Army Engineer District, Sacramento, 1976) for more

appropriate zonal allocations.

For GTL, the market area contains the following county distribution by

origin zone:

Distance Zones Number of Counties Population by Zone

0-25 2 79,741

26-50 8 801,178

51-75 10 2,472,318

76-100 18 4,307,937

101-125 25 4,361,719

The final step in deriving the use/distance relationship is to determine

the per capita use rate by zone. This is accomplished by dividing the zonal

populations into the estimates of use originating from each zone. For GTL

these are:

Annual Visitation Population Per Capita

,Zone by Zone by Zone Use by Zone

0-25 353,345 79,741 4.4311

26-50 190,J420 807,778 0.2377 W

51-75 33,685 2,472,318 0.0136

76-100 28,185 4,307,937 0.0065

101-125 27,495 4,361,719 0.0063

Day Use Estimation for the Alternative

To estimate day use for the MR it is necessary to determine the total

market boundary, divide that boundary into areal zones of origin, estimate the

populations of the zonal areas of origin, multiply the population of each zone or origin by the appropriate per capita use rate, and sum over all zones.

Normally, the appropriate per capita use rate is found by first statistically

estimating the use/distance relationship and then using that statistical

relationship (plotted curve or equation) to estimate per capita use for

varying distances at the project being evaluated.* However, when the market

area for the alternative is divided into the same distance increments as for

the existing similar project, the zonal rates from the similar project can be

used directly. Although this latter technique simplifies the procedures, it

is not as valid as the more rigorous statistical analysis.

OTne technique for statistically estimating the use/distance relationship is

illustrated in a later section of this appendix by way of example for

estimating camping use.

G-4
Since the MR would be very similar to GTL in terms of types of day use

facilities and geographic location, the same market area criteria (125 miles

and 25-mile zonal boundaries) are used. The estimation of visitation for the

MR using existing GTL per capita rates is summarized in Table G-3.

Table G-3:

Derivation of Expected Visitation to the MR

(1) (2) (3) (4) (5)

Base Year Visits

No. of Projected Visits Per for the MR

Zone Counties Population Capita for GTL (3) x (4)

0-25 3 679,444 4.4311 3,010,684

26-50 7 491,958 0.2377 116,938

51-75 13 3,394,276 0.0136 46,162

76-100 15 4,425,762 0.0065 28,767

101-125 22 2,675,484 0.0063 16,856

TOTAL 3,219,407

i Day Use Benefit Estimation

The use estimate calculated above represents the initial point on the

resource demand curve (sometimes referred to as the second stage demand

curve): the amount of visitation that would be expected given the travel costs

confronting visitors due to their existing geographical distribution about the

MR. At zero additional distance from the site, we can expect 3,219,407 total

visits for the purpose of using day use facilities (Figure G-1). As part of

the process to derive benefits we must calculate the remaining points on the

demand curve. Basically, this is done by estimating the amount of visitation

that could be expected if visitors from each zone were confronted with the

increased travel costs associated with the more distant zones.

To derive a second point on the demand curve we hypothetically increase

the distance between visitors' origins and the MR by a constant amount and

observe the effect that this increase in distance has on visitation. For the

MR, we will use distance increments of 25 miles. This increase in 25-mile

increments will continue until participation at the MR is zero. A distance

shift of 25 miles is equivalent to the MR being moved 25 miles from the

potential participants. The people living in Zone 1 would now be expected to

visit at the same rate as the people living in Zone 2 (before adding the 25

mile increment). Thus the use rate for the population of Zone 1 would drop

from 4.4311 to 0.2377 and expected visits would drop form 3,010,684 to 161,504

(679,444 x 0.2377). We do this for the remaining distance zones and sum the

total visitation for each distance zone to compute the expected total

visitation given a distance increment of 25 miles. This gives us an expected

total visitation of 219,138 visits. Thus, the second point on our resource

demand curve is 25 miles on the Y-axis and 219,138 visits on the X-axis.

G-5
41:1

0n

a-l

oW

LMV-L

-gP3 ap 0"w~ 
The calculations for the second point on the demand curve are:

Zone Trips Per Estimated

Zone Population x Capita - Visits

1 679,444 .2377 161,504

2 491,958 .0136 6,691

3 3,394,276 .0065 22,061

4 4,425,762 .0063 27,882

5 2,675,484 .0000 0

TOTAL 219,138

The same procedure is repeated with added distances of 50, 75, 100 and

125 miles. At a distance shift of 125 additional miles, no day use

participation occurs. People are no longer willing to travel that distance to

use the site. Thus, the final point on the demand curve is: 125 additional

miles distance and 0 visits. The results of these calculations are summarized

in Table G-4. The first and last coluim of Table G-4 are the points used to

plot the second stage demand curve (Figure G-1). The area under the curve in

Figure G-1 is the visitors' consumer surplus or the additional amount they

would be willing to pay but do not have to pay to use the resource. The eproject benefit is the area under this curve plus any entrance or user fees

that would be collected (which, in this example, are zero for the day use

visitors).

In order to estimate the dollar benefits under this curve, we must first

convert the mileage increments into dollars. Incurred travel costs are made

up of two components: out-of-pocket or variable motor vehicle costs and the

value of travel time. The average vehicle cost per mile to the MR is 14.1

cents for 1981. The der4 lation of this amount is shown on Table G-5. Since

there are 3.5 people per vehicle sharing these costs (based on survey results

form GTL), the cost per mile per person is 4.1 cents.

Table G-4:

Second Stage Day Use Demand Schedule for the MR

Added Visits by Origin Total

Miles 1 2 3 4 5 Visits

0 3,010,684 116,938 46,162 28,767 16,856 3,219,407

25 161,504 6,691 22,061 27,882 0 219,138

50 9,240 3,198 21,384 0 0 33,822

75 4,416 3,099 0 0 0 7.515

100 4,280 0 0 0 0 4,280

125 0 0 0 0 0 0

G-7

.'-", ~~~~~~~ " .. ""'," ' "' ,"" ": " ~~ " " , "" ~ " 1 ',,w V w , , "
Table G-5:

Motor Vehicle Cost Computation:

Cents/Mile (1981 Variable Cost)*

Standard Compact Subcompact Average

Maintenance Accessories,

Parts and Tires 7.10 6.19 5.29 6.19

Gasoline and Oil 7.10 6.32 5.29 6.24

Taxes on Gas, Oil, Tires 2.06 1.67 1.41 1.71

TOTAL 14.1

01979 costs updated to 1981 values based on changes in the Consumer price

Index for Transportation, private.

Source: U.S. Department of Transportation, Federal Highway Administration

1979. The Cost of Owning and Operating Automobiles and Vans, 1979.

Office of Highway Planning, Highway Statistics Division.

The value of travel time per person is based on the average weekly

earnings of the state in which the MR will be located. For 1981, this figure

was $286.00 per week and was derived from the average weekly earnings for

occupations covered by the relevant State's unemployment compensation law.

For this particular state the $286.00 figure represented approximately 95

percent of the payroll workers. Assuming an average work week of 40 hours,

the average wage rate is $7.15 per hour.

The adult value of travel time per hour is one-third of $7.15 ($2.38)

while the value for children is one-twelfth of $7.15 (U.S. Water Resources

Council, 1979). As indicated earlier, the vehicle load factor for day use

activities at GTL was 3.5. Survey results indicated that, on the average,

there were 2 adults per vehicle and 1.5 children. Thus, 57 percent of the

total day use attendance (2 divided by 3.5) is by adults, 43 percent (1.5

divided by 3.5) is by children. The weighted average value of travel time per

person per hour is calculated to be $1.61:

.57 ($2.38) + .43 ($0.60) = $1.61

The average vehicle speed is 45 miles per hour. Thus, the time cost to

travel a 25-mile increment is approximately $0.90 (25 miles divided by 45

miles/hour) x ($1.61/hour) and $1.80 for the round trip. The vehicle cost per

person for the 25-mile increment is $2.05 (50-mile round trip x $0.041/mile).

The total cost for a 25-mile increment is $3.85 ($2.05 + $1.80). The total

costs for the additions of 25, 50, 75, 100, and 125 miles are:

G-8
Increments Round-trip Time Cost of Vehicles Cost/ Total

(miles) Mileage Travel Cs) Person ($) Cost ($)

25 50 - 1.80 $ 2.05 $ 3.85

50 100 3.60 4.10 7.70

75 150 5.40 6.15 11.55

100 200 7.20 8.20 15.40

125 250 9.00 10.25 19.25

Plotting total cost per visit on the Y-axis and total visits on the

X-axis provides the second stage demand curve converted into dollars. The

line connecting the points is the demand curve. To estimate benefits you need

to determine the area under this curve. You can do this by breaking the area

under the curve into trapezoids, determining the area of each, and summing

their areas (see Figure G-2). This amount ($7,217,358) is the total day use

benefits for the " To calculate the average benefit per visit, divide total

benefits by the t fnber of visits estimated at zero additional miles

(3,219,407) :

$7,217,358 divided by 3,219,407 % $2.24 (average benefits per visit)

Travel Cost Example: Camping

Since GTL has no fee areas, we Must select another similar project to

develop a camping use estimate. The name of the second similar project Is Q

Lake. Although located over 500 miles from the alternative, Q Lake is

extremely similar in term of the number and type of camping facilities and

expected visitation patterns.

Camping Use Estimation

We will obtain expected use rates for the alternative directly from a

camping use equation (estimator) developed for Q Lake. As was true of day

use, we need 3 pieces of information to develop the camping use estimate:

county population figures, amount of campground use by county of origin, and

road mile distances. County population figures were obtained from the "1980

Census of Population and Housing" for the states and counties surrounding 0

Lake. Campground use data came from 533 fee receipts (see Figure G-3)

collected during 1981 at Q Lake's only fee area. Road mile distances were

obtained from state highway maps. All 3 data sets were entered and stored in

a computer at WES. The data were tabulated using a program developed by

Curtis et al. (1982) specifically for the campground fee receipts. Since this

program allows visitation figures to be compiled according to campers' zip

codes, it is easy to determine the source and amount of recreation area or

project visitation.

Again, the first step in developing use rates is to define the market

area for Q Lake. Remember that this market area now applies to camping only.

As before, there are no set guidelines. You Must use some judgment based on

the characteristics of the area and visitation patterns. Data from the

campground fee receipts indicate that 93.6 percent of the campers originate

G-9
CV)

oc

t- 0iL 404

G-1 _
- L a --

LA-J

(3 oC.) ~z 

-C cc -,FC

= C) = c i

UJ C.)Z i

41C La I 4- cr.I LU )- . GJ3 0

cc cc 00 00 0 5 I~l ci ac

U 0

J.AJ - .. C

U 'Si

cz 401li

CL~ -i

-= u

o0 -0. 00000 a a

C=..

W C.) 00 00

'a t L

2c=Eg- Luuuuuu ___-w

mO crm loca

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CG-11
from within 150 miles of Q Lake. Thus, the total market area was defined as

all counties within 150 road miles of Q Lake. The origins of the relatively "'.

few remaining campers that drove further than 150 miles were scattered over a

variety of large distances from the lake.

For the camping e3timate, it is advisable to select a market area that

accounts for most of the visitation - 90 percent, say. This is because

benefits accruing to those visitors originating outside the market area - 150

miles in this example - are difficult to determine. To do so, one would have

to measure road mile distances from numerous counties located large distances

from the lake. This would be a very time-consuming task. More importantly,

it is highly unlik-ly that campers from such great distances would be using

Corps reservoirs as primary destination sites. For Q Lake, 98.5 percent of

the campers from within 150 miles were primary destination users. The travel

cost approach is not usually used to estimate benefits by individuals using a

project as a stopover on a longer trip. However, at the end of this example,

we illustrate one method of adjusting benefits calculated by the travel cost

approach. This adjustment method accounts for non-primary destination camping

both within and outside of the 150-mile designated market ares as well as

primary destination users from beyond 150-miles.

The 150-mile market area was divided into fifteen 10-mile distance zones.

Use estimates by zone (see Table G-6) were derived from the campground fee

receipts. There were two major reasons for using the 10-mile zones:

a. Nearly half of the use originated from within 50 miles of Q Lake.

Thus, finer gradations than 50 miles were deemed necessary,

b. Since there are 15 zones, there are 15 possible observations on whih

to base the regression analysis. For models with only one

independent variable (the type we will be using in this example), 15

observations should be sufficient to produce a valid per capita use

equat i on.

Population and use rates by zone were derived in a manner similar to that

used in the day use example. These data are presented in Table G-6.

In this example, we will test 5 functional forms of the use estimation

curve:

(a) V/C = f (D) (d) V = f (P/D3 )

(b) V = f (P/D (e) (V/C) VP= f (D/7)

(C) V f (P/D)

where, V/C = visits per capita

V T visits

D : di.st.;ince

P pop, ' ition

G-12
Table G-6:

Q Lake Market Area Information

Distance Zones Number of Zone Number of Visits

(miles) Counties Population** Camping Visits# Per Capita

0-100 0 -

11-20* 0 - - -

21-30 3 59,829 498 .0083

31-40 a 0 - -

41-50 2 112.410 371 .0033

51-60 2 27,800 52 .0019

61-70 2 27,276 41 .0015

71-80 2 33,696 30 .0009

81-90 4 213,914 108 .0005

91-100 1 65,639 17 .0003

101-110 3 101,009 59 .0006

111-120 2 187,824 4 .0000

121-130 2 420,901 283 .0007

131-140 3 58,049 84 .0014

141-150 3 488,770 83 .0002

No counties had a population center within these distance zones; hence no

data are recorded. This means that subsequent regression analyses are

based on 12 observations, not 15.

03 There are some counties in a particular zone from which no visitation was

recorded. The population of these counties must also be included in the

total zone population.

Primary destination campers only.

G-13

r~ N V.
* These five functions describe possible relationships among visitation,

distance, and population. Our goal is to find the relationship that best

predicts visitation. An example of form (a) would be V/C = 0.211 - 0.0015 (D) Y

0.211

Visits slope = -00.0015

per

Capita

Distance

where 0.211 is the Y-intercept and -0.0015 is the slope of the line that best

describes the relationship between visitation and distance. The negative sign

attached to the slope indicates that as distance from the project increases,

visitation decreases.

Thus, visitation from city X located 100 miles from the project described by

the above relationship would be determined as follows:

visits per capita = 0.211 - 0.0015 (100) - 0.211 - 0.15

- 0.061 visits per capita from city X

If we knew that the population of city X were 100,000, we would expect 6100

(100,000 x 0.061) visits from that city during a given year.

Deriving the use equation should not be something taken lightly. The use

equation is a necessary first step in determining project benefits, the goal

of the travel cost method. Therefore, failure to give full attention to

collecting the best available data at the initial stage will increase the

chances of your benefit estimates being erroneous.

In using form (a) to derive per capita use curves, Pankey and Johnston

(1969) noted the problem of heteroscedasticity (a biased estimator) in the

regression estimate. To avoid this problem, researchers (Brown and Hansen,

Vol. III, 1974; Bowes and Loomis, 1980) recommend the use of forms (b), (c),

(d), or (e). We refer interested readers to these two sources for a more

detailed discussion of this issue.

Table G-6 contains all the data necessary to compute the five use

equations. For example, to compute form (a), we use visits per capita as rThe

dependent variable and distance as the independent variable. As values for

G-14
distance, we used the midpoints of each zone. For example, the value of

distance for the 41-50 mile zone is 45 miles.

Table G-7 displays the results of the regression analysis for each of the

5 functional forms. You may derive these equations by using either a computer

or a calculator. We prefer the computer since it is faster and the chances of

errors in entering the raw data can be minimized. In addition, the computer

provides the opportunity for storing the raw data. Thus, at a later date you

may modify the data easily without running the risk of more errors in making

the changes by hand. If you decide to derive a use model with more than one

independent variable, computer analysis is mandatory.

As indicated in Table G-7, form (c), V=f (P/D2), gives us the largest R

0.86. This means that 86 percent of the oserved variation in visitation to Q

Lake can be explained by the variable, P/DP. Since this model gives us the

best prediction of visitation and is conceptually plausible, we will use it in

*subsequent analyses.

Table G-7:

Per Capita Use Equations for Q Lake*

Functional

Form Equation R2

a V/C = .00556364 - .00004413 (D) .52

(.0015) (.0082)

b V = 0.36417114 + .07826997 (P/D) .53

(.8834) (.0505)

c V = 5.44525384 + 5.46150513 (P/D2 ) .86

(.8279) (.0001)

d V = 68.64748813 + 125.11378765 (P/D3 ) .73

(.0355) (.0004)

e V/Cvr/ = .68498591 - .00000709 (DV7) .13

(.0231) (.2403)

* Numbers in parentheses are significance levels of t values. All models are

based on 12 observations.

You do not have to collapse data by county into distance zones in order

to derive the use model. You could enter the values for visitation, distance,

and population by county and then derive your regression estimates. In doing

so, you may find better predictive models than those generated by lumping the

data into zones. We tried both types of data for Q Lake, but discovered that

the data summed by zone gave us our "best" model.

Now that we have a use equation, the next step, estimating use for the

MR, is straightforward:

a. determine the market area boundary

- b. divide the market area into distance zones

G-15
c. estimate the population of these zones

d. determine the value of P/D2 for each zone

e. insert this value into the equation to derive an estimate of visits

from each zone

f. sum over all zones.

Remember, these steps are appropriate for this example; depending on what

functional form gives you your best model, its requirements would be

substituted in steps (d) and (e).

Table G-8 displays these calculations for the MR. We expect 43,541

primary destination camping visits from within the market area to the MR.

Table G-8:

Derivation of Expected Primary Destination Campground Use to

the MR from the Market Area as Based on the Prediction

Model Selected for the MR

Zone Population P/D2 Visits

0-10 98,760 3950.40 21,581

11-20 301,427 1339.68 7,322

21-30 411,201 657.92 3,599

31-40 No counties in this zone ---

41-50 238,264 1117.66 648

51-60 1,037,434 342.95 1,878

61-70 988,884 234.06 1,284

71-80 2,318,666 412,21 2,257

81-90 1,580,371 218.74 1,200

91-100 1,894,683 209.94 1,147

101-110 1,036,602 94.02 519

111-120 1,242,765 93.97 519

121-130 1,656,636 106.02 584

131-140 1,407,334 77.22 427

141-150 2,195,954 104.44 576

Total 43,541*

' Expected visitation by campers from within 150 road miles, who are using the

project as a primary destination.

Camping Benefit Estimation

Using the same reasoning as before for the day use example, the first

point on the second stage demand curve is 0 additional miles from the site and

43,541 total visits. To determine the second point, we hypothetically

Increase the distance between campers' origins and the MR by 10 miles and

G-16
observe the effect that this increase has on visitation. The origin for a

given zone or its distance from the MR, is reckoned as the midpoint of that

zone. For example, the first zone's origin or current distance from the MR is

5 miles; adding 10 miles to that origin's current distance of 5 miles gives it

a new hypothetical distance of 15 miles. Next calculate P/D2 by dividing

origin one's (the first zone) current population, 98,760, by the hypothetical

distance squared (152 = 225). Thus, 98,760 divided by 225 = 438.93.

Inserting this value into our equation yields a new estimate of visitation,

5.445 + 5.46(438.93) = 2,402. Continue adding increments of 10 miles and

estimating number of visits for each origin. Perform these steps until the

sum of the original distance of the first zone or zone nearest to the project

(in this case 5 miles) plus the added mileage exceeds the market area (150

miles in this example). Repeat this process for all origins (15 here) and sum

visits across origins for each distance increment. Continue this process

until participation at the MR is zero. This procedure produces a resource or

second stage demand schedule showing the number of visits to MR at increasing

distances:

Added Total

Miles Visits

0 43,541

10 15,041

20 9,577

30 6,767

40 5,042

50 3,859

60 2,771

70 1,970

80 1,144

90 742

100 400

110 286

120 248

130 119

140 31

150 0

These points are used to plot the second stage demand curve (Figure G-4).

Total project benefits are the area under this curve plus the entrance or user

fees collected at Q Lake.

To estimate benefits under the curve, we must convert the added mileage

into dollars (added travel costs). As was true for the day use example,

incurred travel costs included variable motor vehicles costs and the value of

travel time. The average cost per mile to the MR is 14.1 cents (See Table

G-4). Campground receipt information indicates an average of 3.2 people per vehicle. Thus, the cost per mile per person is 4.4 cents.

To compute the value of travel time per person, we will use nearly the

same figures as we did for day use. The only deviation is that for camping we

will use 1.2 children per vehicle. Thus, 62.5 percent (2 divided by 3.2) of

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G- 18
the campers are adults and 37.5 percent (1.2 divided by 3.2) are children.

The value of travel per person per hour is:

.625 ($2.38) + .375 ($0.60) = $1.71,

The average vehicle speed is 45 miles per hour. Therefore, the time cost

to travel a 10-mile increment is $0.76 ((20 miles round trip divided by 45

miles/hour) x $1.71/hour). The vehicle cost per person for the 10-mile

increment is $0.88 (20 miles round trip x $0.044/mile). The total cost for a

10-mile increment is $1.64 ($0.76 + $0.88). The total costs for all the

mileage increments are:

Increments Round-trip Time Cost of Vehicles cost/ Total

(miles) mileage Travel (5) Person () Cost (M)

10 20 0.76 0.88 1.64

20 40 1.53 1.76 3.29

30 60 2.29 2.64 4.93

40 80 3.06 3.52 6.58

50 100 3.82 4.40 8.22

60 120 4.59 5.28 9.87

70 140 5.35 6.16 11.51

80 160 6.12 7.04 13.16

90 180 6.88 7.92 14.80

100 200 7.64 8.80 16.44

110 220 8.41 9.68 18.09

120 240 9.17 10.56 19.73

130 260 9.94 11.44 21.38

140 280 10.70 12.32 23.02

150 300 11.47 13.20 24.67

We now plot total cost per visit on the Y-axis and total visits on the

X-axis to obtain the second stage demand curve converted into dollars. To

compute the consumer surplus (total benefits minus fees), we break the area

under the curve into trapezoids, determine the area of each, and sum all

areas. Carrying out this procedure (the area of each trapezoid is shown in

Figure G-5), we derive an estimate of $114,419.

To determine total benefits, we must add expected user fees to the

consumer surplus of $114,419. Expected visitation to the MR's fee area from

our use estimator is 43,541 visits (Table G-8). This estimate is the expected

visitation by campers from within 150 road miles using the project as a

primary destination. To estimate total benefits, we must also include

expected user fees paid by those campers within 150 road miles using the

project as a stopover on a longer trip and all campers from beyond 150 miles.

To make this inclusion, we first convert visits into recreation days of use:

43,541 x 1.4 days (average length of stay) z 60,957 recreation days

S Next we expand 60,957 recreation days by the proportion of non-primary

destination campers within the market area and by the proportion of all

campers coming from outside the market area:

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a. 60,957 divided by 0.985 (proportion of primary destination campers

within 150 miles) = 61,885 recreation days of use within the market

area

b. 61,885 divided by 0.936 (proportion of all campers within 150

miles) equals 66,116 total recreation days of use from within and

outside the market area.

Dividing 66,116 recreation days by 3.2 average persons per party gives us

20,661, the expected number of nights paid for camping. 4.9 percent of the

total number of fee receipts collected at Q Lake in 1981 were issued to

campers with Golden Age Passports. Thus, we estimate that 1,012 nights of

camping (20,661 x .049) at the MR will be by Golden Age Passport holders,

while 19,649 (20,661 minus 1,012) will cost the normal fee. If we assume an

overnight fee of $4 at the MR, then (19,649 x $4) + (1,012 x $2) = $80,620.

Adding consumer surplus to total revenues yields a total benefit estimate

for camping of $195,039 ($114,419 + $80,620).

Adding total day use benefits (Figure G-2) to total camping benefits

yields a total recreational benefit estimate of $7,412,397 ($195,039 +

$7,217,358).

Figure G-6 summarizes the steps in the travel cost method. Readers

should use Figure G-6 as a quick overview of the travel cost procedure,

referring to appropriate sections of the text for more detailed discussions

and examples pertaining to each step.

We used both day use and camping data to illustrate the mechanics of the

travel cost approach to benefit estimation. The procedures for estimating day

use visitation were somewhat different from those used to estimate campground

visitation. Under the circumstances we described, both procedures were valid.

In order to increase the reader's understandinf6 of the travel cost

approach, we used real data but simplified the procedures. We wish to point

out, however, that other factors besides population and distance can be

incorporated into use estimation models and thus be given appropriate

consideration in benefit calculations. Some of these other factors include

site quality, substitutes, socioeconomic characteristics, and management

considerations (e.g., carrying capacity). Cited references provide

illustrations of more complex applications of the travel cost methodology.

G-21

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Figure G-6:

Travel Cost Method: Outline

A. Use Estimation

1. Find use estimation model from similar project(s). (If not

available, find data from similar project(s) to develop such a

model).

2. Determine similar project's market area and decide on appropriate

distance zones.

3. Determine population of each distance zone (or county set, county,

census tract).

4. Determine amount of visitation from each zone (or county set,

county, census tract).

5. Determine use for the alternative in either the following manners:

a. Determine market area and appropriate distance zones.

b. Estimate population by distance zone.

c. Determine amount of visitation from each zone.

-OR--

a. Derive regression model showing relationship between the

dependent variable (number of visits, visits per capita, etc.)

and one or more independent variables (distance, substitutes,

etc.)

b. Substitute into regression equation estimated values of the

independent variable for the alternative.

c. Determine amount of visitation for each zone.

6. Sum over all zones (this figure is total visitation at zero

additional cost, the first point of the second stage demand curve).

B. Benefit Estimation

1. Plot added distance on Y-axis and total visitation at various

distance on X-axis (first point is zero additional distance and

total visitation from A.6. above.

2. Derive subsequent points by increasing distance and observing

effect on visitation.

3. Continue deriving points until added distance results in zero

visitation (last point on curve).

4. Estimate dollar benefits.

G-22
*Fiure G-6 (continued):

Travel Cost Method: Outline

a. Convert added distance, Y-axis, into dollars (variable motor

vehicle costs plus value of travel time). The area under this

curve represents the additional willingness of visitors to pay

for the experience.

b. Total benefits equals the area under the second stage demand

curve (consumer surplus) plus any entrance/user fees.

c. Total benetA'ts divided by total number of visits at zero

additional miles (first point) - average benefits per visit.

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APPENDIX H: VALUATING USE WITH UNIT DAY METHOD

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APPENDIX H: VALUATING USE WITH UNIT DAY METHOD

Unit Day Value

Unit day values represent an attempt to approximate the average

willingness to pay of recreationists for a day of recreation activity. When

using this method to estimate recreation benefits, departure from an approved

range of values is not permissible. If preliminary evaluations indicate a

value outside of the range, either a travel cost or a contingent value study

is generally indicated. Due to the nature of the unit day value method, the

burden is on the planner to Justify its use and to explain the selection of

any particular value whether it is for a general or specialized recreation

activity.

Information Needed

Prior to implementation of the technique, the planner will need to

conduct the following tasks:

o Identify and analyze the recreation market.

o Determine the recreation need for both existing and future conditions

by type of recreation activity.

o Calculate resource capability.

o Investigate recreation opportunities foregone.

o Characterize both the with and without resource conditions in terms of

annualized recreation days by activity.

Description of Procedure

The mechanics of the technique are fairly simple and can be reduced to

the framework diagrammatically displayed below:

H-1
Annual Value 1 Estimated Average 1 x 1 Value of a Day

Recreation Use I Annual Use 1 of Recreation

Obtained Via Obtained Via

Use Estimating Equation Comparable

(Use Estimating Model) Market Prices

OR * OR

Per Capita Use Curve Point System

(Similar Project Approach) _

OR

Use Capacity

(Capacity Method)

The steps in the procedure are stated as follows, further details on the

selection of value for a day of recreation (Step 2) are given in the sections

immediately after the list.

Step 1. For each recreation activity or category of activity, under both

with and without conditions, obtain the value of a day of

recr eation.

Step 2. In the context of with project conditions, and for each

recreation activity or category of activity, multiply the value

of a day of recreation by the estimated average annual use.

Step 3. Sum the values obtained in Step 2 to derive total activity

benefit.

Step 4. Divide by the total estimated average annual recreation activity

days to compute an average unit value per recreation day.

Step 5. Multiply the value obtained in Step 4 by the estimated annual

use over the project life.

Step 6. Repeat Steps 2-5 for without project conditions for those

activities expected to be diminished by the project.

Step 7. Compute net benefit as the difference between values obtained in

Steps 6 and 7.

Clearly, the Most significant step in the application of the unit day value

method is Step 1, in which the value of a day of recreation is assigned. As

just indicated in the diagrammatic framework for the method, the value of a

day of recreation can be obtained in either of two ways: via use of comparable

market prices or via the point system. The process for assignment of values

through both of these ways is described in the following sections.

H-2

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Use of Comparable Market Prices to Obtain Value. In this alternative,

the planner selects a value from within the ranges of unit day values for both

generalized and special recreation activities. These ranges are updated and

published each year by the Water Resources Council. Local market price

information provides guidance in the selection of a value from within the

range. In general, three conditions must be met:

1. The amount of recreation opportunities provided at the site must not

significantly change the total amount of similar recreation available

in the affected area; 20 percent of the total is the maximum change

permitted.

2. Recreation opportunities to be created or destroyed by a proposed

project must be similar in all important respects (e.g., distance

from user populations, facilities, quality) to the recreation

opportunities for which market data are obtained.

3. Market prices must reflect only use of the site and associated

facilities (i.e., they must be equivalent to entrance or use fees).

Guidance is obtained from local prices by a sample of market values drawn from

at least ten private sector establishments with comparable facilities in the

affected recreation area. Prices or entry fees at public sites may not be

S included. The price data should be annualized to remove seasonal variability

if needed. The average of the prices is then used as the activity day value

if it falls within the appropriate range of published values. If the average

does not fall within the range, it may be used only if fully documented and

justified.

Each of the activity day values is then weighted by the predicted annual

use for each activity. The sum of total activity values divided by the sum of

annual activity use days yields a weighted value for the average recreation

day. This value should be comparable to that obtained by the alternative

approach, the point system. A final check of the reasonableness of the

selected unit value is whether or not it represents the amount prospective

recreationists should be willing to pay to enjoy the recreational

opportunities to be afforded by the project.

Use of the Point System to Obtain Value. In this alternative, the

planner uses tables that categorize certain attributes of recreation

activities. Based on these categories, points are assigned. Then, using

another table, the point score is translated into a dollar value per

recreation day. In the Principles and Guidelines, the WRC provides guideline

tables for use in the point system. They are merely suggested tables, others

may be used. The table that converts points to dollars is set up using the

same range of values as are updated and published each year by the Water

Resources Council. Two tables are available for assigning points and are

differentiated as follows:

H-3

9.9
a. For general recreation such as picnicking, camping, hiking, riding,

cycling, fishing, and hunting.

b. For specialized recreation such as big game hunting, wilderness

pack trips, white water canoeing, and other relatively unique

experiences.

To use the tables, the planner judges each activity against each of the

specified attributes assigning an appropriate point value. For each activity

the points are summed across attributes, and the total is used to derive an

activity unit day value from the conversion table. As with the market price

approach, each of the activity day values is weighted by that activity's

predicted annual use. The sum of total weighted activity values divided by

the sum of total annual activity days yields a weighted value for use with

estimates of recreation days.

By setting up and categorizing attributes, the point system provides a means of explicitly taking into account some of the factors that influence

recreation demand and narrows the vagaries of professional judgement as

N required for the comparable market price method. The validity of the system

rests on the subjective judgements of the person who developed the tables as well as the analysts who use them.

4.

H--4

S (,M[ N ! NT PRVNTING O- FICE 1916 163 74
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