SOME ISSUES CONCERNING SPECIFICATION AND INTERPRETATION OF OUTDOOR RECREATION DEMAND MODELS



The other quantity proxy, the number of days
per visit, as advocated by Edwards, et al, [4], assumes
the only variation among recreationists is in the
length of stay and not the number of trips. Again,
this may be realistic in selected instances, although
realistic examples are more difficult to conceive.

In a majority of cases neither choice is correct,
since recreationists react to costs by adjusting both
number of visits and length of stay per visit. It is
suggested that total quantity of recreation demanded
per time period (yearly, or seasonally), Ds, be
recognized in recreation demand studies. Total
quantity demand can be defined as:

(1) Ds≡V∙Dv

where V refers to the number of visits per time
period, and Dv the number of days per visit.3

This identity alone does not explain; it merely
describes. It does point out that the recreationist’s
decision to take a certain quantity of recreation at a
given site actually involves two decisions, one of how
often to visit and the other of how long to tarry on a
particular visit. A general analysis of recreation
should explain both.

A GENERAL MODEL

A suggested demand model that incorporates
both quantity variables is presented in general as:

(2) Dv = Dv (Et, Es, I, Ee) and

(3) V = V(Et, Ee, I, Ee)

where Et is a recreationist’s travel cost, Es is on-site
costs of a recreationist, I is annual income, Ee
represents other socio-economic variables, the
components of which should correspond to the focal
point of any particular study, and Dv, V, and Ds are
as previously defined.

Under the Clawsonian influence, equation (3)
was utilized — with two differences: (1) variables
were measured in terms of averages over distance
zones, and (2) all travel and on-site costs were
summed to represent one price variable, of which
travel costs make up the largest part. Other studies
have focused only on equation (2), utilizing daily
on-site costs was the site-price proxy. Clearly, there
can be no complete discussion of these apparent
differences of opinion except through analysis of
both equations.

The fact that two decisions are involved in the
recreationist’s planning might seem to indicate a
simultaneous system of equations involving equations
(2) and (3). Pursuing this, however, reveals that it is
scarcely possible to conceive of an independent
variable belonging to either equation (2) or (3) that
does not also fit in the other. In this sense then,
estimation of the two relationships separately will
provide information concerning tradeoff between
number of visits and the length of each visit.

For example, predicting the impact of an
increase in travel cost on the mix of visits and days
per visit can be accomplished by collating the
corresponding travel cost coefficients in the two
equations. It is hypothesized, for example, based on
empirical evidence [4, 5], that travel costs are
negatively correlated to number of visits and
positively related to length of stay.

PRICE PROXIES

The price proxies are meant to reflect variation
in the visitor’s opportunity cost, or supply price, of
recreation at a given site. They sometimes seem better
indexes of other things, including even quantities
taken of ancillary inputs.

On-Site Costs

The daily on-site expenditures of a recreationist
reflect both prices and quantities taken of the things
he buys. A change in daily expenditures due to a
change in those prices moves him along his demand
curve for on-site recreation. In this case the change in
daily on-site expenditures would represent the effect
of a true price change. On the other hand, the change
in daily expenditures may be due to a change in
quantities taken at given prices of goods consumed on
site. In this case, the change in daily expenditures is
not an index of daily on-site price; on the contrary, it
can be more reasonably assumed a demand shifter
reflecting changes in site quality, or tastes.4

The observations are specifically directed to
previous treatments of daily on-site costs as the price
of a day’s recreational benefits, which in common
practice means the price of a visitor day. Edwards’, et
al., study exemplifies one such treatment. The
function sought would relate number of days at the
site to daily on-site costs (among other relevant

3It is, perhaps, worth noting that, while time may be generally the most easily measured evidence of recreation
consumption, where appropriate Ds, for example could be total ducks bagged, V the number of visits per season to a given
hunting preserve, and Dy the number of ducks bagged per visit. In any case, Ds is a measure of use-intensity of recognized interest
for planning and management of public facilities.

4Examples of site quality changes include those due to such things as insect pests (causing changes in purchases of
repellants), and weather (causing changes in a gamut of things ranging from fish bait to strong drink).

166



More intriguing information

1. MATHEMATICS AS AN EXACT AND PRECISE LANGUAGE OF NATURE
2. The name is absent
3. Effects of red light and loud noise on the rate at which monkeys sample the sensory environment
4. Staying on the Dole
5. Family, social security and social insurance: General remarks and the present discussion in Germany as a case study
6. Food Prices and Overweight Patterns in Italy
7. Who is missing from higher education?
8. The name is absent
9. The name is absent
10. Modelling Transport in an Interregional General Equilibrium Model with Externalities
11. The name is absent
12. The name is absent
13. An Attempt to 2
14. The Cost of Food Safety Technologies in the Meat and Poultry Industries.
15. Knowledge and Learning in Complex Urban Renewal Projects; Towards a Process Design
16. MANAGEMENT PRACTICES ON VIRGINIA DAIRY FARMS
17. The name is absent
18. The name is absent
19. The name is absent
20. Endogenous Heterogeneity in Strategic Models: Symmetry-breaking via Strategic Substitutes and Nonconcavities